table of contentec.europa.eu/environment/waste/studies/packaging/public...packaging waste in the...

"Evaluation of costs and benefits for the achievement of reuse and recycling targets for the different packagingmaterials in the frame of the packaging and packaging waste directive 94/62/EC" – proposed draft final report,

RDC-Environment & Pira International, May 2001

1

Table of content

EXECUTIVE SUMMARY............................................................................................................................7

1 CONSTRAINTS ...................................................................................................................................8

2 INTRODUCTION AND OBJECTIVES ..........................................................................................12

2.1 OBJECTIVES AND SCOPE OF THE STUDY ............................................................................................12

2.2 CONTRACTOR'S TASKS......................................................................................................................13

2.3 GENERAL METHODOLOGICAL APPROACH – LIFE CYCLE COST BENEFIT ANALYSIS ...........................16

3 DETAILED METHODOLOGY .......................................................................................................22

3.1 REVIEW OF THE CURRENT SITUATION (STEP 1) .................................................................................22

3.2 SELECTING AND DEFINING THE CASE STUDIES (STEP 2) ....................................................................24

3.3 FULL COST BENEFIT ANALYSIS OF CASE STUDIES (STEP 3)................................................................29

3.4 APPLICATION OF THE CBA RESULTS TO DETERMINE OPTIMAL RECYCLING TARGETS (STEP 4).........46

3.5 RECOMMENDATIONS AND CONCLUSIONS (STEP 5) ...........................................................................55

4 RESULTS............................................................................................................................................56

4.1 EVALUATION OF THE CURRENT SITUATION.......................................................................................56

4.2 RESULTS OF CASE STUDY CBAS ......................................................................................................60

4.3 SUGGESTED RECYCLING TARGETS ....................................................................................................90

4.4 REUSE...............................................................................................................................................99

5 CONCLUSIONS AND RECOMMENDATIONS .........................................................................112

6 GLOSSARY ......................................................................................................................................118

7 BIBLIOGRAPHY.............................................................................................................................119

ANNEXES...................................................................................................................................................123

ANNEX 1: PROCESS TREES AND SYSTEM DESCRIPTIONS...........................................................................123

ANNEX 2: INCINERATION AND LANDFILL MODELS ...................................................................................123

ANNEX 3: INTERNAL COST DATA .............................................................................................................123

ANNEX 4: ECONOMIC VALUATIONS APPLIED – SOURCES AND DERIVATION.............................................123

ANNEX 5: EMPLOYMENT DATA –JOBS FOR WASTE MANAGEMENT ACTIVITIES ........................................123

ANNEX 6: PACKAGING MIX BY MEMBER STATE ......................................................................................123

ANNEX 7: ENVIRONMENTAL DATA SOURCES ...........................................................................................123

ANNEX 8: CURRENT PERFORMANCE OF MEMBER STATES .......................................................................123

ANNEX 9: CRITICAL FACTORS LIMITING RECYCLING AND REUSE.............................................................123



2

ANNEX 10 : PRESENTATION OF CBA RESULTS FOR RECYCLING CASE STUDIES .......................................123

ANNEX 11 : CALCULATION OF RECYCLING RATES PER MEMBER STATES ................................................123

ANNEX 12 : PRESENTATION OF CBA RESULTS FOR REUSE CASE STUDIES ...............................................123

Table of figuresFigure 1 : Stepwise approach of the methodology............................................................ 22

Figure 2 : generic process tree for the recycling case study (household packaging) ........ 27

Figure 3 : Generic process tree for the recycling case study (industrial packaging) ........ 28

Figure 4 : Full CBA of case studies – sub-steps ............................................................... 31

Figure 5 : Impact assessment in LCA ............................................................................... 41

Figure 6 : Application of CBA results to determine possible recycling targets................ 48



3

Table of tablesTable 1 : Recycling case studies selected for full CBA .................................................... 25

Table 2 : Reuse case studies selected for full CBA........................................................... 25

Table 3 : Scenarios relating to household packaging waste.............................................. 32

Table 4 : scenarios relating to industrial & commercial packaging waste........................ 32

Table 5 : Achievable recycling rates for household packaging waste (%) ....................... 34

Table 6 : Determination of the potential recycling rate according to the application....... 36

Table 7 : achievable recycling rates for industrial packaging waste................................. 37

Table 8 : economic valuations........................................................................................... 42

Table 9 :Population density distribution by Member State (estimation for 2000)........... 51

Table 10 :Percentage split of municipal solid waste management (estimation for 2000). 52

Table 11 : Population mix as a function of density and national MSW treatment

(estimation for 2000)................................................................................................. 53

Table 12 : Performance of the Member States in 1997..................................................... 57

Table 13 : Summary of the recycling difficulties.............................................................. 58

Table 14 : Scenarios considered for PET beverage bottles............................................... 60

Table 15 : Calculation of GWP externality for 1 tonne PET bottles to landfill, low

population density ..................................................................................................... 63

Table 16 : Total externalities for PET bottles, Scenario 3 ................................................ 64

Table 17 : Internal costs, external costs and total social costs (low pop. density)............ 66

Table 18 : Internal costs, external costs and total social costs (high pop. density)........... 67

Table 19 : Transport distances .......................................................................................... 76

Table 20 : Optimum systems for steel packaging ............................................................. 84

Table 21 : Optimum systems for aluminium cans............................................................. 85

Table 22 : Optimum systems for other rigid and semi-rigid aluminium packaging ......... 86

Table 23 : Optimum systems for paper & board packaging ............................................. 86

Table 24 : Optimum systems for LBC packaging............................................................. 87

Table 25 : Optimum systems for mix plastic packaging................................................... 88

Table 26 : Optimum collection systems per case study, based on CBA........................... 90

Table 27 : Optimal collection systems for metal packaging ............................................ 91

Table 28 : Optimal recycling ranges per case study.......................................................... 91



4

Table 29 : Calculation of minimum and maximum recycling rate for the EU.................. 93

Table 30 : Summary of the ranges of optimal recycling rates per Member States ........... 95

Table 31 : Recycling rate per material .............................................................................. 96

Table 32 : Recycling targets per Member State in 2006 ................................................... 97

Table 33 : Sensitivity of the material recycling rates to the packaging mix ..................... 98

Table 34 : Internal, external and total cost of beverage packaging systems ................... 107



5

Table of GraphsGraph 1 : Total social costs (low population density)....................................................... 66

Graph 2 : Total social costs (high population density)...................................................... 67

Graph 3 : Sensitivity of the results to the external economic valuations applied - Low


Graph 4 : Sensitivity of the results to the external economic valuations applied - High


Graph 5 : Sensitivity of the results to the internal economic costs considered - Low


Graph 6 : Sensitivity of the results to the internal economic costs considered - High


Graph 7 : Addition of employment as an impact category - low pop. density.................. 72

Graph 8 : Addition of employment as an impact category - high pop. density ................ 72

Graph 9 : Sensitivity of the results to energy recovery assumptions ................................ 73

Graph 10 : Sensitivity of the results to energy recovery assumptions .............................. 74

Graph 11 : Sensitivity of results to offset electricity assumption - Low pop. density ...... 75

Graph 12 : Sensitivity of results to offset electricity assumption - High pop. density...... 75

Graph 13 : Sensitivity of results to transport distances - Low population density............ 77

Graph 14 : Sensitivity of results to transport distances - High population density........... 77

Graph 15 : Sensitivity of results to consumer transport step - High pop. density............. 78

Graph 16 : Sensitivity of results to consumer transport step - High pop. density............. 78

Graph 17 : Sensitivity of results to overseas transport step - Low population density ..... 80

Graph 18 : Sensitivity of results to overseas transport step - High population density .... 81

Graph 19 : Sensitivity of results to virgin production credit - Low pop. density.............. 81

Graph 20 : Sensitivity of results to virgin production credit - High pop. density............. 82

Graph 21 : Internal costs for glass................................................................................... 100

Graph 22 : External costs for glass.................................................................................. 101

Graph 23 : Total social costs for glass ........................................................................... 102

Graph 24 : Internal costs for PET.................................................................................... 104

Graph 25 : External costs for PET .................................................................................. 105

Graph 26 : Total social costs for PET ............................................................................ 106



6

Graph 27 : Internal costs for refillable and non refillable glass (33cl) and PET (1.5l)

beverage packaging ................................................................................................. 108

Graph 28 : External costs for refillable and non refillable glass (33cl) and PET (1.5l)

beverage packaging ................................................................................................. 109

Graph 29 : Total social costs for refillable and non refillable glass (33cl) and PET

(1.5l) beverage packaging ....................................................................................... 110



7

EXECUTIVE SUMMARY

Will be written when the main report is definitive.



8

1 CONSTRAINTS

This study aims to evaluate the costs and benefits of increased recycling targets for

packaging waste in the frame of the Packaging and Packaging Waste Directive

(94/62/EC). It also investigates the costs and benefits of reusable primary packaging.

In order to achieve this, the study applies the technique of life cycle cost benefit

analysis (CBA). This is a combined life cycle assessment and economic valuation

analysis.

To perform a full cost benefit analysis for all packaging recovery and recycling

options in all EU Member States would be an immense task, and its added value

might be limited. Due to budget and time restrictions, the consultants have therefore

limited the extent of the study so as to produce a representative but accessible

analysis. Choices have had to be made which lead to simplifications that do not

always represent the full details of real conditions.

It is recognised that there need to be reservations with regards to the validity of the

details of the study results. However, it is believed that the study gives a good overall

picture of the costs and benefits linked to the investigated targets and that the main

driving forces for the results have been covered.

Nonetheless, in order to prevent misunderstandings in the interpretation and

application of the study results, it is important to consider a number of constraints

imposed by the methodology, the extent of the analysis and the data applied. These

are discussed below.

1) Life cycle cost benefit analysis

Life cycle cost benefit analysis (CBA) is a new and developing technique. There is

no standardised methodology. This study aims to apply the best available knowledge

in the field, but debate continues amongst practitioners on key aspects of the

approach, including:



9

♦ The economic valuations applied to environmental impacts

♦ The limitations of life cycle assessment methodologies on which CBA is

based

The limitations of CBA are discussed in detail in Section 2.3 of this report.

2) Scope of the study

As required by the terms of reference, this study considers the costs and benefits of

various treatment options once packaging has become waste. The system boundaries

have been drafted to reflect this.

For the investigation of recycling of packaging waste, the system boundaries begin at

the point at which packaging is discarded by the final user. For the investigation of

reusable packaging, the system boundaries include the entire life cycle of the

packaging (including extraction, conversion, filling, and distribution).

The study does not consider upstream issues of material selection. It is recognised

that higher recycling targets (and therefore end of life management costs) for one

material compared to another may induce a switch from one material to another. This

could lead to changes in the competitivity of different materials and changes in the

overall environmental performance of packaging systems. This is not addressed in

the study.

3) Limitations of data collection

Data collection and the development and testing of hypotheses was limited due to

time and budget constraints:

♦ Data have been collected from a limited number of sources (often only one

or two sources)

♦ Assumptions and hypothesis have been necessary

♦ Data from literature has not always been cross-checked with other sources



10

4) Differences between Member States

The analysis considers the following differences between Member States

♦ The packaging mix available for recycling

♦ The fraction of a Member State’s population living in densely populated

areas

♦ The residual MSW treatment system applied to packaging waste that is not

recycled (i.e. landfill or incineration with energy recovery).

The internal costs of operating processes vary across EU. This will influence the costs

and benefits of recycling in different Member States. This is addressed where

possible by considering data ranges for internal costs.

The case studies do not explicitly take into account the following differences between

MS :

• Motivation of the population to participate in recycling schemes

This significantly influences the range of recycling rates that can be achieved

in Member States. The range of recycling rates modeled in the analysis

considers the collection and recycling rates that could be achieved if a scheme

is implemented where a motivated population exists. This implies an

appropriate level of communication of the scheme. However, communication

does not guarantee motivation of the population. In some Member States the

achievable collection and recycling rates may be lower than the range

modeled, in other Member States it may be higher. Cultural differences may

play an important role. This is not considered in the analysis.

• Existence of recycling infrastructures

The capital costs of infrastructure are allocated per ton of material handle, but

the analysis does not consider the existence or absence of an existing recycling

infrastructure in each MS. A “steady state” analysis is considered. The results

do not take into account the difficulty of establishing additional infrastructure.

It is assumed that there is available capacity throughout the EU or such

capacity may be established if there is enough supply of material and

sufficient demand for recyclate.



11

• Typical family structure

Although the packaging mix in each Member State has been considered, the

typical family structure has not been considered. This may influence the

composition of packaging waste in the household MSW stream, which will

ultimately influence collection and sorting of packaging waste arising from

households.

• Specific geographical problems

The study does not consider specific geographical problems imposed by

adverse weather conditions or isolated communities such as island or

mountain based communities.



12

2 INTRODUCTION AND OBJECTIVES

The Directive on packaging and packaging waste (94/62/EC) established the

following targets1 for the recovery and recycling of packaging waste for the period

1996 – 2001:

• A recovery target of between 50% and 65% by weight of packaging waste andwithin this,

• A recycling target of between 25% and 45% by weight of packaging waste with aminimum of 15% by weight for each packaging material.

The Directive requires the EC to review these targets before the end of the first five-

year period. As part of this review, the European Commission has commissioned a

number of studies, including this study.

The main purpose of this study is to perform an evaluation of the costs and benefits of

higher recycling targets and reuse targets. This section describes the study’s

objectives, scope and the concept of cost benefit analysis.

2.1 Objectives and scope of the study

As stated in the call for tender, “The objective of the study is to perform a

cost/benefit analysis of packaging recycling and reuse systems, including:

1. an evaluation of the situation concerning the fulfillment of specific targets as

required by the packaging and packaging waste Directive 94/62/EC by the end of

the first five-year phase (30/06/2001), i.e. 15% for each packaging material

(glass, plastic, paper/board, metals, composites, wood, others),

2. a prospective study concerning the fulfillment of higher recycling targets for

packaging materials by the end of the second five-year phase (30/06/2006) taking

into account limiting factors such as technical feasibility, economic implications

and environmental benefits,

3. an investigation concerning the possible establishment of reuse targets for the

relevant packaging materials by the end of the second five-year phase

1 Member States are permitted to implement higher targets where it can bedemonstrated that these can be achieved without disrupting the functioning of theinternal market.



13

(30/06/2006) taking into account technical feasibility, costs and environmental

benefits, and the development of a methodology for the calculation and

monitoring of these targets.”

A possible approach was to start from different recycling rates, to determine the way

to achieve them and to determine their costs and benefits. The approach used in this

study is different: we first considered the different possible systems, we determined

their optimum organization, calculated their costs and benefits and then considered

the recycling rates achievable by the “cheapest” system.

The study aims to cover:

♦ All fifteen Member States

♦ Each individual packaging material (glass, plastic, paper/board, metals,

composites, wood, others)

♦ All packaging applications (primary, secondary, tertiary)

♦ Alternative packaging collection and reprocessing options

However, in order to achieve the analysis within the budget and time constraints, it

has been necessary to make assumptions and hypotheses which limit the scope of the

analysis (see chapter 1 of this report).

2.2 Contractor's tasks

As stated in the call for tender, the contractor's tasks are the following ones :

"Task 1: Data compilation

The contractor shall perform a review of the relevant studies in the field of packaging

waste management systems including cost-benefit analyses.

The contractor shall also use the data provided by Member States according to the

provisions of the packaging and packaging waste Directive 94/62/EC and the

Commission Decision 97/138/EC establishing the database formats. This data covers

the calendar year 1997 and includes figures on the quantity of packaging material

placed on the market, re-used, recycled, recovered and disposed of.

The study shall consider both packaging waste treated within the territories of the

Member States as well as exported quantities. Information shall be given on the



14

countries of destination of exports, the used treatment methods and the monitoring

systems applied in these countries.

Data concerning the different packaging materials shall take into account their

source (municipal, industrial,...) and their utilisation nature (primary, secondary and

tertiary packaging).

Task 2: Analysis of collection, recycling and reuse systems

The different existing collection and sorting systems shall be described in terms of

costs and effectiveness (collection of packaging with the general municipal waste and

further sorting; selective collection through kerbside or drop-off systems; other

options).

The different existing treatment routes for recycling shall be described in as much

detail as possible in terms of capacities, costs and environmental impacts.

Special emphasis shall be put on the description of the different recycling processes

for plastics2, which shall be defined as clearly as possible. In that context, the

analysis will consider as far as possible the different plastics packaging materials

split up as relevant in PE (polyethylene), LDPE (low density polyethylene), HDPE

(high density polyethylene), LLDPE (linear low density polyethylene), PET

(polyethylene terephtalate), PP (polypropylene), PS (polystyrene), PVC

(polyvinylchloride),...

Existing deposit systems for returnable and reuse packaging materials shall be

investigated.

2 "mechanical recycling" where plastics are reprocessed with unchanged chemicalstructure;•"chemical recycling" (also known as feedstock recycling) where the polymericchemical structure is broken down to monomer or to a more basic chemical structure,including inter alia de-polymerisation processes such as methanolysis, glycolysis.aminolysis and acidolysis, thermal cracking processes (as Veba, BASF and BPprocesses), pyrolysis, gasification (Texaco process) and blast furnace process (use ofplastics as reductor agent);"pseudo recycling processes" consisting in an energy recovery from plasticspackaging, waste after "mechanical recycling" and/or "chemical recycling"



15

Task 3: Costs and benefits of packaging waste management according to current

and possible future targets

The contractor shall establish an appropriate general method of calculating costs

and benefits of packaging waste management. This method shall then be applied to

the situation in the fifteen Member States according to the scenarios described in

tasks 3.1, 3.2 and 3.3. Particular emphasis shall be put on plastics and composites

packaging.

§ The financial balance shall identify all relevant costs related to the collection and

treatment of packaging waste according to the various options, identify possible

revenues from the sale of secondary materials and calculate the reduced costs of

municipal waste management as a result of the separate collection.

§ The environmental evaluation shall identify the amounts of the primary raw

materials that can be saved through the re-use and recycling of packaging

according to the various possible targets. The associated change of environmental

impacts (in particular: climate change, acidification, tropospheric ozone,

eutrophication, toxic substances dispersion and disposal of final solid waste) shall

be quantified as far as possible in monetary terms of avoided externalities. In the

absence of monetary figures, quantitative values of avoided pollution shall be

given.

§ Employment and social effects shall be described and quantified as far as

possible.

The contractor shall also perform a sensitivity analysis on factors that might

substantially influence the results of the cost-benefit analysis.

Task 3.1: fulfillment of specific recycling targets as required by the Packaging

Directive by June 2001, i.e. 15% for each packaging material,

The contractor shall make an evaluation of the situation in the different Member

States:

• confirming that the targets foreseen will be met

• and describing possible positive or negative variations.

Task 3.2: fulfillment of higher recycling targets by June 2096.

The contractor shall, in agreement with the Commission, identify a set of meaningful

targets to be achieved by June 2006 for the various materials with a view to



16

maximising environmental benefits. A minimum of eight relevant case studies shall

describe possible combinations of these targets and investigate different optional

routes to achieve these targets. Again, particular emphasis should be put on the

recycling of plastics and composite packaging.

The contractor shall determine limiting factors for the achievement of these higher

targets, such as technical, ecological, economic and practical ones in terms of

collection. The contractor shall discuss possible solutions to be applied to these

limiting factors. Possible Community and national measures that are likely to

improve the efficiency of the systems shall be identified. Measures might include in

particular legislative and voluntary initiatives, financial assistance, innovation

incentives, etc.

Task 3.3: establishment of reuse targets

The report shall include information on existing deposit systems on packaging. It

shall describe and evaluate these systems according to the following factors:

materials covered, return rates/number of observed rotations, reuse/recycling levels

achieved, costs, system management and other issues that are of interest with respect

to the current situation and future development of these systems.The contractor shall make an evaluation of the technical feasibility, the costs and the

environmental benefits in order to set reuse targets by June 2006 for the relevant

packaging materials. A methodology for the calculation and monitoring of these

targets shall be proposed."

2.3 General methodological approach – Life cycle cost benefitanalysis

The general approach applied is based on the principle of life cycle cost benefit

analysis (CBA). This section of the report briefly describes the concept of CBA. A

detailed description of the methodology applied in this study is provided in Section 3

of this report.

What is CBA?

CBA is an economic evaluation tool used to compare the costs against the benefits of

different activities. Within the context of policy development, CBA attempts to

quantify the total costs and total benefits of a given policy option in order to

determine whether the policy is worth pursuing.



17

The policy is considered from the social welfare perspective. An action is considered

worthwhile if the total benefits to society outweigh the total costs to society.

These costs and benefits must be considered across the whole life cycle of the system

affected by the policy decision. Therefore, life cycle cost benefit analysis combines

aspects of financial cost benefit analysis with the economic valuation of the

environmental impacts which are determined by life cycle assessment techniques.

Why use CBA?

Environmental policies are pursued in order to provide environmental protection and

environmental improvement. These are the benefits of environmental policies. Such

benefits may be measured in terms of environmental protection provided or

environmental improvements made. For example, policies to reduce the effects of

global warming may be quantified in terms of avoided greenhouse gas (measured in

kilograms of CO2 equivalents). These benefits are known as externalities, as they are

external to the traditional economic model.

However, in addition to these environmental benefits, an environmental policy

decision will also incur implementation costs. Different policy options will incur

different cost implications. The internal costs of implementation are known as

internalities, as they are internal to the traditional economic model.

Politicians and decision-makers seek to pursue policies that provide good value for

money by achieving environmental objectives / benefits without incurring

disproportionate internal costs. A quantitative comparison of the costs and benefits of

environmental policies can only be achieved if the internalities and externalities are

measured in a common unit. CBA seeks to do this by valuing in monetary terms the

externalities, and comparing these against the internal costs of implementation. In

this way, we gain insight into the trade-offs (within and between economic costs and

environmental benefits) that are inevitably made when selecting and implementing

policies.

Limitations to CBA



18

CBA is a new and developing technique. As with all tools and techniques, there are

limitations to the methodology. The limitations of CBA should be recognised before

the methodology is applied:

• Ethical issues

Many critics of CBA question the underlying ethics of monetary valuation of

environmental impacts. They believe that the environment is something sacred upon

which it is not acceptable to place a monetary value. It needs to be underlined,

though, that every political decision on environmental measures implicitly gives a

value to the environment. The question is whether this is done on the basis of

transparent information or not.

• Methodological limitations of LCA

The environmental analysis that is performed prior to the economic valuation of the

environmental impacts is based on life cycle assessment (LCA) methodologies. LCA

has been subject to international standardisation efforts, but some methodological

limitations persist:

Ø The nature of choices and assumptions made in LCA (e.g. system boundary

setting, selection of data sources and impact categories) may be subjective

Ø Models used for inventory analysis or to assess environmental impacts are

limited by their assumptions , and may not be available for all potential

impacts

Ø Results for LCA studies focusing on global or regional issues may not be

appropriate for specific local applications

Ø The accuracy of LCA studies may be limited by accessibility or availability of

relevant data, or by data quality and data gaps

Ø A lack of spatial and temporal considerations in inventory data that are

subsequently used for impact assessment may introduce uncertainty to the

results



19

• Achieving economic valuation of environmental impacts

Not every externality can be valued in monetary terms at present:

Ø Several external effects are difficult to measure

Ø Some environmental impacts are too site specific to be reliably transferred

from specific studies to a general CBA methodology

Ø Studies to determine economic valuations have only been conducted in a

limited number of areas. Willingness-to-pay for prevention of damages to the

environment may vary between geographical populations, but it is necessary

to rely on the concept of benefit transfer in order to develop a general CBA

methodology.

• Methodological difficulties arising from attempts to perform monetisation

Where monetisation can be performed, the reliability of the values derived may be

questioned. A variety of techniques can be applied to derive economic valuations. In

many cases, application of different techniques results in conflicting valuations being

achieved, suggesting inherent bias in valuation methodologies. The alternative

techniques that can be applied are described in detail in Annex 4: Economic

valuations applied – sources and derivation.

§ Increasing difficulties of isolating external costs

Increasingly, national environmental policies have attempted to internalise some

aspects of external costs. For example, emission permits and landfill taxes effectively

internalise some elements of pollution. The charges for these permits and taxes have

rarely been based on a detailed evaluation of the external costs of the avoided

environmental impact. These charges should not be included when performing CBA,

but it is not easy to accurately determine the level of internalisation. This may lead to

some double counting in the methodology.

• Quantifying indirect and secondary effects

The difficulties of quantifying indirect costs and secondary effects means that many

studies focus only on the direct costs. This limited approach could have a significant

influence on the true “social cost”. In some cases, wider effects can only be taken



20

into account by inclusion of broad assumptions, which may be limiting. Indirect and

secondary effects have not been considered in this study.

How to use CBA

This type of approach enables decision-makers and stakeholders to better understand

the trade-offs within and between economic costs and environmental benefits that are

inevitably made when selecting policies. Thus, CBA makes decision-making more

transparent. It is an aid to the decision-making process, not a substitute for it.

The decision-maker must still judge how to weigh up environmental effects,

economic costs and the distributional impacts of the different policy options in order

to select the preferred option

It is important to recognize CBA as a useful tool rather than a decision rule. By

asking the right questions it opens up the discussion and identifies key issues.

Relationship of CBA to other economic evaluation tools

CBA considers the micro-economic effects of the policy in detail. This is known as a

“bottom-up” approach. However, in considering these micro-economic effects,

broader consequences of the policy decision should not be overlooked. In some

cases, it may be appropriate to support CBA with some form of “top-down” macro-

economic analyses.

Such macro-economic analysis techniques may consider the impacts of policy on

economic indicators such as GDP, inflation rate, and the trade balance. This type of

analysis is most appropriate for policy instruments with potentially significant macro-

economic effects.

Examples of macro-economic tools include:

§ General and partial equilibrium models

§ Input-Output models

§ Application of multipliers.



21

However, macro-economic analyses in isolation may not be appropriate for assessing

the potential benefits of specific environmental policy measures. Statistics such as

GDP are measures of the volume and structure of market transactions rather than

measures of welfare or the efficiency of resource use. Macro-economic analyses

sacrifice technical detail for greater spatial scope



22

3 DETAILED METHODOLOGY

This section describes the methodological approach applied in order to fulfil the study

objectives. The approach has been broken down into a series of steps, as described in

Figure 1. Where appropriate, the application of the methodology has been

demonstrated through reference to the calculations performed for a specific case study

(PET bottles).

Figure 1 : Stepwise approach of the methodology

Each of the Steps is described in greater detail in the following sections.

3.1 Review of the current situation (step 1)

In this step, the current packaging waste recovery and recycling situation in Europe is

reviewed. The aim is:

• To determine the performance of Member States against the current targets for

packaging waste recovery and recycling

STEP 1:Review ofcurrentsituation

STEP 2:Selecting andDefining CaseStudies

STEP 3:Full CBA ofSelectedCase Studies

STEP 4:Application ofresults to determinepossible recyclingtargets

STEP 5:Recommendationsand Conclusions



23

• To determine the critical factors that limit the levels of recycling or reuse that

can be achieved

3.1.1 Current performance of Member States

Data and forecasts have been collected for the years 1997, 1998 and 1999.

The collected data is classified by the following parameters:

♦ Classification of the data per year

♦ Classification according to waste production (packaging brought on the

market), and recycled amount, for individual Member States

♦ Data were collected for the material classes as detailed as possible

(as much sub-divisions according to material applications as

possible)

♦ glass,

♦ plastics,

♦ paper & cardboard,

♦ metals,

♦ composites,

♦ wood,

♦ other packaging materials

3.1.2 Critical factors limiting recycling and reuse

The critical factors limiting the levels of recycling or reuse that can be achieved for a

material and/or by packaging application are classified according to their specific

nature:

♦ Technical

♦ Economic

♦ Marketing

The critical factors for each material have been identified through a combination of

literature search and discussion with stakeholders.



24

3.2 Selecting and defining the case studies (step 2)

Due to the constraints of time and budget, the full cost benefit analysis can only be

applied to a limited number of case studies. The aim of Step 2 of the methodology is

to select appropriate case studies for full cost benefit analysis and to define the

specific process tree for each case study.

3.2.1 Select packaging applications for full cost benefit analysis

The selection of packaging applications for full CBA is ultimately subjective, but in

determining the case studies the following criteria have been considered:

♦ Packaging applications are not considered for full CBA where there is a

general consensus that the recycling rate should be high

♦ Packaging applications which contribute to the production of the highest

quantity (by weight) of packaging waste in the EU are favoured

♦ Special attention is given to plastics and composites3

♦ Some reuse systems must be included

♦ Efforts are made to ensure that a sufficient diversity of packaging materials

and applications are considered

♦ Efforts are made to ensure that there is a sufficient quality of data to complete

each CBA

Based on the consideration of these criteria, the following case studies have been

selected.

3 As required by the EC in the call for tender



25

Table 1 : Recycling case studies selected for full CBA

N° Material Case study Industrial/household

1 Plastics LDPE films Industrial

2 Paper/cardboard Corrugated board Industrial

3 Plastics PET bottles Household

4 Plastics Mixed plastics Household

5 Steel All applications Household

6 Aluminium All rigid and semi-rigid applications Household

7 Aluminium All flexible applications Household

8 Paper/cardboard All applications Household

9 Composites Liquid beverage cartons (LBC) Household

10 Glass Beverage bottles Household

Note: the two aluminium systems can be done as a single scenario for total aluminium

Table 2 : Reuse case studies selected for full CBA

N° Material Case study Industrial/household

1 Glass Single trip beverage bottles and

reusable beverage bottles

Household

2 PET Single trip beverage bottles and

reusable beverage bottles

Household

The recycling case studies selected represent a significant fraction of the total

packaging waste stream. The following important packaging waste flows have been

excluded from the full CBA case studies, as there is a general consensus that high

reuse and recycling rates should be achieved for these applications:

♦ Industrial steel applications, such as drums and pails (due to the high

economic value of the material high rates of reuse, reconditioning and

recycling are already achieved for these applications)

♦ Wood packaging applications, such as pallets - high levels of reuse,

reconditioning and recycling of wood pallets and other wood packaging

applications are already achieved

♦ Rigid industrial packaging applications, such as crates, drums and pails



26

3.2.2 For each packaging material / application selected for full CBA, define the

process tree

The process tree defines the individual unit processes and the system boundaries

considered in the analysis. A unit process is the smallest portion of a system for

which data are collected when performing an LCA study. The system boundary is the

interface between a system and the environment or other systems. Data is only

collected for those unit processes inside the system boundary.

The full process trees for each case study are presented and described in Annex 1:

Process trees and system descriptions of this report. The incineration and landfill

models considered are described in Annex 2: Incineration and landfill models.

3.2.2.1 Recycling case studies

Figure 2 and Figure 3 show the generic process trees for the recycling case studies.

The system boundaries begin at the point at which the packaging material is discarded

by the final holder. The system boundaries end at the point of final disposal (i.e.

landfill or incineration) or at the point at which the material directly replaces a virgin

product/material. The point at which the material directly replaces a virgin

product/material may be immediately after sorting or may be after some reprocessing

of the sorted packaging waste. Credit for offset virgin production is included in the

system boundaries.

Within the system boundaries, the operation of each unit process is considered. This

includes all waste management, reprocessing, transport, and energy production unit

process. The system boundaries include the capital necessary to provide these unit

processes.

"Evaluation of costs and benefits for the achievement of reuse and recycling targets for the different packaging materials in the frame of the packaging and packaging wastedirective 94/62/EC" – proposed draft final report, RDC-Environment & Pira International, May 2001

27

Figure 2 : generic process tree for the recycling case study (household packaging)

PACKAGING

WASTE ARISING

LANDFILL

MSW INCINERATION

ENERGY

CREDIT

RECYCLING

COLLECTION FOR

INCINERATION

COLLECTION FOR

LANDFILL

TRANSPORT TO

RECYCLERSSORTING +

BALING

SEPARATE

KERBSIDE

COLLECTION

ROUND

COLLECTION

FROM BRING

BANK

TRANSPORT TO

BRING BANK

MATERIAL

CREDIT

ENERGY

CREDIT


28

Figure 3 : Generic process tree for the recycling case study (industrial packaging)

PACKAGING

WASTE ARISINGMSW

INCINERATION

COLLECTION

FOR

INCINERATION

ENERGY

CREDIT

LANDFILLENERGY

CREDIT

COLLECTION

FOR

LANDFILL

RECYCLINGSORTING

COLLECTION

FOR

RECYCLING

MATERIAL

CREDIT



29

3.2.2.2 Reuse case studies

The system boundaries begin at the extraction of raw materials for the production of

packaging. The system boundaries end at the point of final disposal (i.e. landfill or

incineration) or at the point at which the material directly replaces a virgin

product/material. Within the system boundaries, the operation of each unit process is

considered. This includes all production, waste management, reprocessing, transport,

and energy production unit process, including those associated with the collection,

sorting, and washing of packaging for reuse. The system boundaries include the

capital necessary to provide these unit processes.

3.3 Full cost benefit analysis of case studies (step 3)

This section of the methodology describes how CBA techniques are applied to the

selected case studies. Life cycle cost benefit analysis (CBA) is an economic

evaluation tool used to compare the costs against the benefits of different activities.

CBA attempts to quantify the total social costs and total social benefits of an activity.

The total social costs of an activity are the sum of the internal costs and external costs.

Internal costs are those costs internalised to the economy. External costs are the costs

that arise when the social or economic activities of one group of people have an

impact on another, and when the first group fails to fully account for their impact.

For example, external costs arise if an economic activity causes environmental

damage and the polluter does not pay for clean up or fails to compensate those who

suffer from this damage.

The classic example of an external effect is that of an upstream factory polluting a

river in a way that has a negative impact on catches in a downstream fishery. In

deciding upon how much it will produce and consequently how much it will emit to

the river, the upstream factory will not take this effect into account.

To determine the internal and external costs and benefits, CBA combines aspects of

financial cost benefit analysis with the economic valuation of environmental impacts

as determined by life cycle assessment techniques.



30

Life cycle assessment is a technique for assessing the potential environmental impacts

of a product or process by compiling an inventory of relevant inputs and outputs of

the system and subsequently evaluating the potential environment impacts associated

with those inputs and outputs.

Economic valuation is a technique for determining the monetary value of a specific

environmental impact. This facilitates the direct summation of different

environmental impacts for comparison against the internal costs and benefits. It also

allows to take into account some types of local environmental impacts that are usually

not considered in LCA due to the lack of valuation methodology, in particular for

transport (traffic congestion, traffic accidents, traffic noise) and disaminity (odours,

vibrations, harmful animals, fear, dust…).

The full CBA of the case studies is completed in a series of sub-steps as illustrated in

Figure 4.



31

Figure 4 : Full CBA of case studies – sub-steps

DETERMINE SCENARIOS

MODELINTERNAL

COSTS

MODELEXTERNAL

COSTS

MODEL + VALUEGROSS

EMPLOYMENT

COMPILETOTALSOCIALCOSTS

UNCERTAINTY/SENSITIVITY ANALYSIS

INTERPRETATION

Each sub-step is described in detail below.

3.3.1 Determine scenarios

The specific scenarios to be considered in each case study must be determined. This

sub-step describes how the scenarios are derived.


For each household packaging waste case study, scenarios are determined according

to three key parameters:

♦ Population density (i.e. high or low population density)

♦ National municipal solid waste (MSW) management option available as an

alternative to recycling (i.e. landfill or incineration)

♦ Where recycling is considered, the type of selective collection scheme (i.e. bring

scheme or separate collection)



32

Thus, for the household packaging waste case studies the following combinations of

scenarios are possible:

Table 3 : Scenarios relating to household packaging waste

Population density Waste management of MSW Collection scheme Recycling rate

High Landfill None 0%

High Landfill Bring W to X%

High Landfill Separate kerbside collection Y to Z%

High Incineration None 0%

High Incineration Bring W to X%

High Incineration Separate kerbside collection Y to Z%

Low Landfill None 0%

Low Landfill Bring A to B%

Low Landfill Separate kerbside collection C to D%

Low Incineration None 0%

Low Incineration Bring A to B%

Low Incineration Separate kerbside collection C to D%

For each case study, the specific recycling rates considered are those that are

achievable in a steady state situation applying the selective collection system with an

efficient management, i.e. considering:

♦ efficient organization of the scheme, e.g. :

§ frequency (e.g. once every 2 weeks for kerbside collection of light packaging)

or

§ density (e.g. one glass bottle bank for 1000 or less inhabitants)

♦ efficient communication of the scheme to potential participants

♦ a scheme in existence for at least 3 years (steady state achieved).

For each commercial & industrial packaging waste case study, the scenarios are

determined only according to the solid waste management option available as an

alternative to recycling (i.e. landfill or incineration). Thus, for industrial &

commercial packaging waste case studies the following combinations of scenarios are

possible:

Table 4 : scenarios relating to industrial & commercial packaging waste

Waste management of MSW Collection scheme Recycling rate



33

Landfill None 0%

Landfill Source separated selective collection U to V%

Incineration None 0%

Incineration Source separated selective collection U to V%

Again, for each case study, the specific recycling rates considered are those that are

achievable applying the selective collection system with an efficient management, i.e.

considering:

♦ efficient collection frequency (no full containers)

♦ efficient communication of the scheme to workers.

The recycling rates considered for the household packaging case studies are

summarised in Table 5.



34

Table 5 : Achievable recycling rates for household packaging waste (%)

High density Low density

% Kerb. Bring Kerb. Bring

Plastics PET bottles 59-69 22-32 70-80 35-45

LPDE films 20-25 20-25 20-25 20-25

HDPE bottles 48-58 17-27 57-67 28-38

Mixed plastics - mech. recycling 5-10 5-10

Mixed plastics – blast furnace 60-80 60-80

Steel* 40-60 15-21 40-60 15-21

Aluminium* Cans 45-55 31-41 45-55 31-41

Other rigid and semi-rigidpackaging

6-16 3-8 7-17 3-10

Flexible packaging 0 0 0 0

Wood 0 0 0 0

Cardboard 55-65 19-29 61-71 25-35

composites LBC 55-65 24-34 55-65 24-34

Mainly based on plastic 20-25 20-25 20-25 20-25

Mainly based on cardboard 20-25 20-25 20-25 20-25

Mainly based on Al 20-25 20-25 20-25 20-25

Glass 42-91 73-83

Other 0 0 0 0

* A possible reason for the relatively low values of the achievable rates for the metals

(specially beverage cans) is the fact that a large part is consumed in the industry and

may not enter the selective collection schemes for household packaging waste.

Collections schemes of household packaging in industry have not been investigated.

The sources of those achievable recycling rates are given below. Only the sources

that refer to efficient selective collection systems (see above) were considered.



35

Data Sources Comments

Plastics Interview of Eco-Emballages

Extrapolation of data publishedin the Annual Report of theCompliance Schemes

Potential for post-user plasticwaste recycling, Sofres-TNO,commissioned by APME, March1998

Range of ± 5% was applied inorder to take into account thedifferences between MS.

Steel Interview of APEAL


Range was discussed withAPEAL.

Aluminium Interview of EAA


Interview of Eco-Emballages

Range of ± 5% was applied inorder to take into account thedifferences between MS

Cardboard Interview of Eco-Emballagesand CEPI



LBC Interview of ACE


"What happens to used beveragecartons ?", brochure made byTetra Pak, January 2000


Glass Glass recycling in EuropeanCountries – 1999, data providedby FEVE, November 2000

Eco-Emballages, interview ofstakeholders

In case of low pop. density a rangeof ± 5% was applied in order totake into account the differencesbetween MS.

Compositesother than LBC

Assumption

Wood and othermaterials

Assumption Insufficient amount to be collectedselectively

Example: Scenarios determined for the PET bottles case study



36

See Table 14, p. 60

Industrial packaging waste is subdivided into 3 categories (Table 6):

- waste that can’t be recycled for technical reasons (contamination, has contained

hazardous waste ,…)

- waste that can’t be recycled for economical reasons, i.e. when the industry does

not produce a sufficient amount packaging waste (assumption : 5% of the non

contaminated amount)

- waste that should be recycled

Table 6 illustrates the analysis of industrial plastic packaging, which was performed

in collaboration with EuPC.

Table 6 : Determination of the potential recycling rate according to theapplication

% % % achievablerecyclingrate

weightedtarget

20% hazardous 0% 0%

15% notrecyclable

0% 0%

30% small (<60l)

80% nonhazardous

85% recyclable 95% 19,4%

70% large (>60l) 100% reuse 10% 7%

Drums

(100%HDPE)

Total 26,4%

30% hazardous 0% 0%

50% not recyclable 0% 0%70% nonhazardous 50% food recyclable 95% 33,3%

Jerricans+/-100%HDPE

Total 33,3%

IBC 100% reuse 95% 95%

44% shrink 85% 37.4%

56% stretch 50% 28%

Films *

Total 65.4%

EPS notrecyclable

0%



37

Sacks 30% 30%

HDPE,LDPE, PP

Pallets pallets 96% reuse 40% 40%

Crates crates 90-95% reuse 25% 25%

* Stretch and shrink films can not be recycled together. They can be easily

identified and separated by hand by professionals.

The achievable recycling rates considered for the industrial & commercial packaging

waste case studies, taking into account the recycling limits, are summarised in Table

7:

Table 7 : achievable recycling rates for industrial packaging waste

Best estimate Range

Plastics LDPE films 65.4% 55-75%

Others 31.3% 21-41%

Total 46.3% 36-56%

Wood 60% 50-70%

Steel 85% 80-90%

Corrugated board 72% 64-80%

Glass 66% 50-83%

Others 0% 0%

The sources for those data are the following ones.



38

Data Source Comments

Plastics Interview of EuPC

Potential for post-user plasticwaste recycling, Sofres-TNO,commissioned by APME,March 1998

The recycling rates determined incollaboration with EuPC wereapplied to the available amount inWestern Europe.

Wood 40% are assumed to be used byhousehold – 60% recycling forrepair of pallets and making ofparticle board

Steel Interview of APEAL

Corrugated board Interview of CEPI

Glass Interview of FEVE In case of high amount, assumedto be mainly household packaging

Others Assumption Insufficient amount to be collectedselectively

3.3.1.2 Reuse case study

For the reuse case study, the following systems are considered:

♦ Single-trip packaging system for glass and PET

♦ Reusable packaging system for glass and PET

For the reusable system, a baseline scenario is modelled as a function of 2 main

influencing factors:

♦ Reuse rate of reusable primary pack = x times

♦ Distance travelled for the collection of reusable packaging = y km

The influence of reuse rate and distance are then investigated. Results are presented

as a function of those factors. But no optimum target can be derived from the

calculations because no market data was sought on the actual:

♦ transport distances

♦ number of uses of the refillable packaging

3.3.2 Model the internal costs

The internal costs considered in this study are defined as “the operational costs

incurred by industry”.



39


A “steady state” model is assumed (i.e. the costs of operating an existing successful

system are considered). The analysis includes the capital costs required to develop

the infrastructure necessary to achieve the defined recycling rate. These capital costs

are considered only as a function of throughput of waste (i.e. they are allocated per

tonne of waste managed). No consideration of the time at which these capital costs

would be incurred by each Member State has been made. E.g. for an incineration

plant, the cost per ton includes :

• the investment cost per ton : investment value / tons handled over the

lifetime

• the financing cost per ton : present value of the interests paid in the future

to finance the investment / tons handled over the lifetime

The total internal cost of each scenario is the sum of all costs minus the sum of all

revenues. This is similar to the concept of “financing need” as considered in the TN

Sofres report “Cost efficiency of Packaging Recovery Systems – The case of France,

Germany, The Netherlands and the UK”. Where the financing need is positive,

recycling is not a self-supporting activity – intervention in the market is required to

stimulate recycling. Where the financing need is negative, recycling is a potentially

profitable activity, and under the right circumstances may occur without intervention

in the market.

Internal costs have been determined for each specific detailed system. However, even

where equivalent waste management practices are compared, internal costs can vary

considerably between Member States, depending on a range of factors such as cost of

living and geographical considerations (mountainous regions, islands, etc). Therefore

the sensitivity analysis considers the influence of a variation of +/- 20% of the total

internal costs on the determination of the optimum system. The size of the range is

based on interviews with compliance schemes and industrials.

The internal costs applied in this study are summarised in Annex 3: Internal cost

data.



40

Example: Internal cost calculation for PET Bottles scenarios

See chapter 4.2.1.2


For the reuse case studies, the internal costs of reuse systems include the costs of raw

material production and conversion, filling, distribution, collection, washing, and

waste management of non-returned bottles (or single-trip bottles). The influence of

reuse rate and distance on internal costs is investigated. The internal costs applied in

this study are summarised in Annex 3: Internal cost data.

3.3.3 Model the external costs

In this study, the environmental impacts of each scenario are modelled using an LCA

approach.

First, the environmental inputs and outputs are modelled in line with the requirements

of ISO 140404 and ISO140415, using the Pira International LCA model PEMS 4.7

(inventory analysis).

Each environmental input or output is then classified according to the environmental

impacts to which it may contribute, and characterised according to its potential to

contribute to that impact. (For the LCA part the ISO methodology is applied, i.e. no

weighting. In a consecutive stage, the CBA methodology is applied, including

monetisation6 of environmental problems. This process is demonstrated in Figure 5.

4 ISO14040 Environmental management - Life cycle assessment - Principles andframework5 ISO14041 Environmental management - Life cycle assessment - Goal and scopedefinition and inventory analysis6 also called "economic valuation"



41

Figure 5 : Impact assessment in LCA

CO2 Global warming (in Kg of CO2equivalent)

CFC's

HCFC's

Ozone layer depletion (in Kg ofCFC11 equivalent)

"Environmental score"CH4 Photochemical oxidant formation

(in Kg of C2H4 equivalent)

HC

NOxAcidification (in Kg of SO2equivalent)

SO2

EconomicValuation

Inventory Classification/Characterisation

LCA part CBA part

Finally, an economic valuation is applied to each environmental impact category.

This allows the environmental impacts to be converted into a common monetary unit,

which can then be summed to provide an estimate of the total external costs of the

scenario. The sources of environmental data applied in this study are listed in Annex

7: Environmental data sources.

The methodology applied in this study considers the following impact categories (as

listed in Table 8).

The following environmental impact categories and economic valuations are applied:



42

Table 8 : economic valuations

Unit Valuation

GWP (kg CO2 eq.) /kg CO2 0,01344

Ozone depletion (kg CFC 11 eq.) /kg CFC11 0,68

Acidification /kg H+ 8,70

Toxicity Carcinogens (Cd equiv.) /kg Cadmium (carcinogenic effects only) 22

Toxicity Gaseous non carcinogens(SO2 equiv.)

/kg SO2 from electricity production 1

Toxicity Metals non carcinogens(Pb equiv.)

/kg Pb 62

Toxicity Particulates & aerosols(PM10 equiv.)

/kg PM10 from electricity production 24

Smog (ethylene equiv.) /kg VOC 0,73

Black smoke (kg dust eq.) /kg smoke 0,66

Fertilisation /kg expressed as NO2 mass equivalents -0,7

Traffic accidents (risk equiv.) /1000 km travelled on an average road 17

Traffic Congestion (car km equiv.) per 1000 car km equivalents 86

Traffic Noise (car km equiv.) per 1000 car km equivalents 3

Water Quality Eutrophication (Pequiv.)

/kg P 4,7

Disaminity (kg LF waste equiv.) /kg waste in landfill 0,037

The economic valuations applied in this study are principally based on damage cost

estimates, derived from hedonic pricing methods or willingness-to-pay studies. A

detailed summary of the sources and derivation of these economic valuations is

provided in Annex 4: Economic valuations applied – sources and derivation.


Example: Calculation of externalities for PET bottles scenarios

See chapter 4.2.1.3


The externalities are determined for the base case, and investigated as a function of

the reuse rate and collection distance.



43

3.3.4 Model gross employment created by each system

The EU has a special obligation to consider employment aspects in the development

of policies under the Treaty of Amsterdam.

However, in neo-classical economics, no social cost is associated with

unemployment. It is assumed that the economy is effectively fully employed. The

labour market is fully flexible and unemployed labour will find employment

elsewhere in the economy. Any unemployment is the result of transitional periods.

The terms of labour employment contracts and the terms of unemployment benefits

will reflect the presence of such periods. There will be no cost to society from the

existence of a pool of transitionally unemployed workers. Therefore, CBA of

environmental policies often deliberately excludes the direct and indirect employment

effects.

However, market conditions are not perfect. Some Member States experience

unemployment that is not due to a short-term transition in supply and demand of

labour and skills, but due to a medium or long-term lack of employment

opportunities. This unemployment has costs that should be considered. These costs

include the economic burden of unemployment benefit, and the social welfare (health

and well being) of the unemployed individuals and their family. Therefore a

consideration of the costs and benefits of employment generated by some policies

may be important.

However, quantifying the net employment created by recycling is not an easy task.

Recycling will undoubtedly generate new employment in collection, sorting and

reprocessing activities. Other jobs may be lost (in virgin material extraction and

processing and MSW management) although obviously less due to the scale of the

activities and the high automation value of the virgin material production systems. It

needs to be underlined that a full evaluation of the employment effect of a policy

measure can only be made after consideration of macroeconomic effects (e.g.

crowding out effects). This is beyond the scope of this study. Even where this

information could be derived, difficulties exist in determining an acceptable economic



44

valuation for each job created, especially considering the variable quality of

employment in this sector7.

In this study, an attempt has been made to determine the employment created. Only

the gross jobs of each scenario are quantified. The gross jobs are those involved in

the collection and subsequent waste management processes (i.e. landfill & incinerator

operation, sorting and reprocessing). The base data used to determine the gross jobs

per scenario is presented in Annex 5: Employment data –jobs for waste

management activities. This data has been sourced from Beture, interviews of

compliance schemes and visits of recycling plants.

No economic valuation has been applied to the gross jobs in the base case. But the

effect of economic valuation of net job creation on the cost-benefit balances has been

tested in the sensitivity analysis. The information is considered cautiously in the

interpretation of the results.


Example: Calculation of gross employment for PET bottles scenarios

See chapter 4.2.1.4

7 for more detailed information see: “Employment effects of waste managementpolicies”, RPA for the European Commission, forthcoming in 2001



45


Only the gross jobs created by collection are considered.

3.3.5 Compile total social costs of each scenario


For each scenario, the total social cost is determined. The total social cost considered

is the sum of the internal costs to industry and the total externality.

Example: Total social costs by scenario for PET bottles

See chapter 4.2.1.5


The total social cost is determined as a function of reuse rate and distance for

collection.

3.3.6 Uncertainty / Sensitivity analysis of the CBA results

For each of the scenarios modelled, the main parameters that may affect the results

are investigated. Two types of parameters are considered:

♦ Uncertainties arising from methodological choices, including but not limited to:

♦ Energy model assumed

♦ Offset energy production from incineration (average or marginal)

♦ Valuations applied to externalities (a list of alternative economic valuations

that may be applied is given in Annex 4: Economic valuations applied –

sources and derivation)

♦ Uncertainties arising from scenario choices, including but not limited to:

♦ Distances for kerbside collection rounds and bring schemes

♦ Transport distances for delivery of sorted material to reprocessors

♦ Offset virgin production and save ratio

♦ Type of energy recovery from incineration and landfill (CH&P instead of

power)

♦ Alternative recovery options



46

♦ Data used and data gaps

Example: Uncertainty and sensitivity analysis for PET bottle case study

See chapters 4.2.1.7 and 4.2.1.8

3.3.7 Interpretation


For each case study, the results are presented as ranges for the following:

♦ total external costs

♦ total internal costs

♦ total social costs (sum of external and internal costs)

The key parameters influencing the results are presented, and the limitations this may

place on conclusions that can be drawn are discussed.

Example: Interpretation of results for PET bottles case study

See chapter 4.2.1.6 and 4.2.1.9


For the reuse case studies, the results are considered in light of the influence of reuse

rate and distance for collection.

3.4 Application of the CBA results to determine optimal recycling targets(step 4)

The aim of this step is to show how the results of the CBA case studies may be

applied to determine possible recycling targets.

A combination of factors will determine the ability of a Member State to meet a

specific recycling target. The following factors are considered in this analysis to

determine recycling targets:

♦ the packaging mix of the Member State

♦ the proportion of population living in high and low population density areas in

the Member State



47

♦ the proportion of landfill and incineration with energy recovery available in

the Member State

♦ the proportion of companies producing small and large quantities of packaging

waste (for commercial and industrial packaging applications only)

These factors are quantified for each Member State, so as to allow targets to be

determined at a number of levels:

♦ aggregated global targets

♦ Member State specific targets

♦ material specific targets

The process of applying the CBA results to determine the recycling targets is

illustrated by the sub-steps shown in Figure 6:



48

Figure 6 : Application of CBA results to determine possible recycling targets

3.4.1 Determine optimal recycling rate by application

For each household packaging application, the optimal recycling rate is determined

for each of the following combinations of parameters:

2.4.3: Determine optimal recycling rateby application for:• high population density, landfill

MSW• high population density, incineration

MSW

low population density, landfill

2.4.5: Determine optimalrecycling target perapplication for each MS

2.4.4: DetermineMS characteristics

2.4.7: Determine optimalrecycling target per MS

2.4.6: Determine totalpackaging mix byapplication for each MS

2.4.8: Determine globaloptimum recycling rate forthe European Union

2.4.9: Sensitivity Analysis

2.4.1: Determine collection system withthe lowest social cost by application for:• high population density, landfill

MSW• high population density, incineration

MSW

low population density, landfill

2.4.2: Determineachievable recycling ratewith the collection systemhaving the lowest socialcost



49

♦ High population density, with landfill as the alternative waste management

option

♦ High population density, with incineration as the alternative waste

management option

♦ Low population density, with landfill as the alternative waste management

option

♦ Low population density, with incineration as the alternative waste

management option

For each combination of parameters, the “optimal” recycling rate is considered to be

the recycling rate achievable by the scenario modelled with the lowest total social

cost.

Example: Determination of optimal recycling rate for PET bottles in function of the

MS characteristics

See chapters 4.2.1.5 & 4.2.1.6

For each (group of) industrial packaging application(s), the industrial companies are

classified according to the amount of packaging waste they produce. The internal and

external costs and benefits are calculated for 3 systems :

• selective collection and recycling

• no selective collection and incineration

• no selective collection and landfill

The internal costs of the selective collection are considered as a function of the

amount of packaging waste of the concerned material (cost of selective collection

decreases when the amount of waste increases). The amount of packaging waste for

which the total social cost of the selective collection system is equal to the total social

cost of the (cheapest among the 2) non-selective collection system(s) is the break-

even amount.



50

• Selective collection within companies which produce a “small” (i.e. smaller than

the break-even) amount of packaging waste is considered not beneficial8 and

therefore the optimum recycling rate is 0%.

• Selective collection within companies which produce a “high” (i.e. more than the

break-even) amount of packaging waste is considered beneficial and therefore

should be applied. The optimum recycling rate is considered to be the recycling

rate achievable with the selective collection.

The “optimum” recycling rate for the industrial packaging application is then equal to

:

Percentage of the packaging waste arising in companies which produce a “high”

amount of packaging waste multiplied by the recycling rate achievable in companies

who do make selective collection.

The 3 key stages of the work are :

• the determination of the break-even amount of packaging waste

• the determination of the fraction of the industrial packaging waste arising from

the companies producing larger amount than the break-even amount and

• the determination of the recycling rate achieved when there is a selective

collection

The optimum recycling rate is calculated according to 2 approaches :

Ø cost-benefit analysis : the break-even amount is the one for which the additional

cost due to the selective collection equals the (environmental and job creation)

benefits. An assumption needs further to be made on the fraction of the packaging

waste arising from large packaging waste production sites

Ø market approach : for Member States where the incineration/landfill tax is about

the same level as the (external) benefits of the selective collection, the external

benefits are considered as fully internalised. Therefore, assuming the market is

8 i.e. the total social cost of selective collection + recycling is higher than the total

social cost of non selective waste collection + incineration or landfill. ie theadditional internal cost for selective collection exceeds the additional externalbenefits from recycling



51

efficient, the current recycling rate is the optimum one. This second approach is

used to check and calibrate the first model.

3.4.2 Determine Member State Characteristics

For each Member State the following characteristics are determined:

♦ Population mix by density and alternative waste management option

This data is applied in the calculation of the optimal recycling target for household

packaging applications.

The population of each Member State is classified into 4 categories:

♦ High population density (> 200 inhabitants/km2) served by landfill

♦ High population density (> 200 inhabitants/km2) served by incineration

♦ Low population density (< 200 inhabitants/km2) served by landfill

♦ Low population density (< 200 inhabitants/km2) served by incineration

To achieve this, the % of the population living in high and low population density

areas is determined for each Member State, based on data available at I-Mage

(Belgian consulting company working for the EC) and checked by local consulting

companies9. The proportion of the population living in high and low population

density areas is shown in Table 9.

Table 9 :Population density distribution by Member State (estimation for 2000)

Population density AUT B DK FIN F D GK IRL I L NL P SP SE UK

Low density % pop 47% 14% 66% 58% 34% 26% 41% 50% 28% 34% 13% 40% 55% 73% 16%

High density % pop 53% 86% 34% 42% 66% 74% 59% 50% 72% 66% 87% 60% 45% 27% 84%

The percentage of municipal solid waste sent to landfill or incineration with energy

recovery in each Member State was determined by local consulting companies. The

distribution is determined based on data and forecasts for 2000. Otherwise data

9 A network of consulting company specialised in environmental matters support thedata search and checked the local data



52

related to previous years (1998-1999) are used. The proportion of landfill to

incineration is summarized in Table 10.

Table 10 :Percentage split of municipal solid waste management (estimation for2000)

Member State Waste fraction incinerated Waste fraction landfilled

Austria 30% 70%

Belgium 50% 50%

Denmark 100% 0%

Finland 5% 95%

France 47% 53%

Germany 40% 60%

Greece 0% 100%

Ireland 3% 97%

Italy 8% 92%

Luxembourg 70% 30%

The Netherlands 50% 50%

Portugal 9% 91%

Spain 7% 93%

Sweden 65% 35%

United Kingdom 7% 93%

Sources :

• Eco-Emballages 1999• Interviews of stakeholders 2000• Network of consultants.

Subsequently, the population is classified according to both the population mix and

the national MSW treat option. The results of this are presented in Table 11.



53

Table 11 : Population mix as a function of density and national MSWtreatment (estimation for 2000)

PopDensity

MSWsystem

AUT B DK FIN F D GR IRL I L NL P SP SE UK

Landfill 47% 7% 0% 58% 22% 16% 41% 49% 26% 10% 6% 36% 51% 26% 15%Low

Incin. 0% 7% 66% 0% 8% 10% 0% 2% 2% 24% 6% 4% 4% 47% 1%

Landfill 37% 43% 0% 40% 32% 44% 59% 48% 66% 20% 44% 55% 42% 9% 78%High

Incin. 16% 43% 34% 2% 39% 30% 0% 1% 6% 46% 44% 5% 3% 18% 6%

It should be noted that this allocation assumes that the proportion of landfill to

incineration is the same in high and low population density areas. In reality, there

may be localised variations that have been addressed in this study as far as data were

available (e.g. for Austria, France, Finland).

The situation in 2006 is considered in the sensitivity analysis.

3.4.3 Determine total packaging mix by application for each Member State

It is assumed that the optimal recycling rate in a Member State is a function of the

packaging mix in that Member State, as some packaging materials/applications will

be easier to recycle than others. Therefore the packaging mix in each Member State

must be determined in order to calculate the Member State’s optimal recycling target.

In this analysis, the packaging mix for 2000 is considered as the baseline. No forecast

for the year 2005 is considered, though the effect of changes in the packaging mix on

the optimal recycling rates are investigated in the sensitivity analysis.

In this analysis, data on the Member State packaging mix has been derived from a

number of sources:

♦ Data provided by the national compliance schemes

♦ Member State’s official declarations

♦ Additional input from local consultants where possible

The detailed packaging mix of each Member State as determined for this analysis is

given in Annex 6: Packaging mix by Member State.



54

3.4.4 Determine optimal recycling target per application for each Member State

The optimal recycling rate per application for each Member State is calculated by

combining the optimum recycling rate per application with the Member State

characteristics.

Example: PET bottles optimal recycling rate

EU PET packaging amount 1 501 kt

landfill Inc. landfill Inc.27% 12% 41% 20%

70% 35% 59% 59% 887 59%80% 80% 69% 69% 1 101 73%

amount to berecycled

Target range

Min targets

Max target

Achievable recycling rates

Percentage of population living in areas where population density is L/H and waste are I/L

Low High

In the above table the minimum target (i.e. minimum achievable recycling rate when

the collection systems with the lowest total social cost are applied) is 59%, i.e. 887

kt/1501 kt or 59% = (27%*70%) + (12%*35%) + (41%*59%) + (20%*59%).

3.4.5 Determine the optimal recycling rate for each Member State

By combining the optimal recycling rate for each packaging material/application by

Member State with the packaging mix by Member State, the overall recycling target

for that Member State is determined. The overall recycling targeted is a weighted

average of the individual packaging material/application targets.

3.4.6 Determine global packaging recycling for the whole EU

The optimal recycling rate of all packaging waste for the whole EU is the weighted

average of the optimal recycling rates of the individual Member States. The

weighting factor is the annual amount of packaging waste.

3.4.7 Sensitivity analysis

The sensitivity of the recycling targets to changes in the packaging mix is

investigated. Forecast for packaging mix in 2006 was investigated. Optimum



55

recycling ranges per application were applied to this new packaging mix, in order to

determine the influence of the packaging mix on the global results.

3.5 Recommendations and Conclusions (step 5)

Based on the results of the analysis, the consultants make conclusions and

recommendations on:

♦ The existing recycling and recovery rates achieved by the Member States

♦ The possible options for implementing higher recycling targets

♦ The possible range of the recycling targets

♦ The key factors that influence the costs and benefits of reuse



56

4 RESULTS

4.1 Evaluation of the current situation

4.1.1 Current performance of Member States

As explained in the description of the methodology (see chapter 3.1.1) the current

performances of the Member States were investigated.

The methodology and the problems encountered are described in Annex 8: Current

performance of Member States.

Data of 1999 are presented in Table 12. Data for 1997 and 1998 are presented in

annex 8 bis.

The main conclusions are:

v Most data were found for 1997 and 1998

v Exact data on the amount of waste, packaging waste and recycling are hard to get;

v Data on the amount of waste, packaging waste and recycling are not comparable;

v More reliable data are/will be available for 1998 and especially 1999 thanks to the

larger experience and the improvement of the calculation methods.



57

Table 12 : Performance of the Member States in 1997

Total HH + industrialMaterial Glass Plastic Paper and

boardMetals Al Steel composite

sWood Other Total

Application

1997Waste

AUT 260 180 666 85 28 50 1269BE 310 208 530 121 17 142 29 1356DK 202 183 463 58 61 4 971FI 52 90 244 31 417FR 3296 1571 3611 622 290 1679 11069DE 3750 1502 5448 1121 87 1034 1892 17 13731GK 1456IE 452IT 2248 1777 3246 487 1802 9560LU 17 7 11 3 1 1 80NL 469 611 1449 216 0 2745PO 1050SP 1398 1215 2255 340 671 5879SE 177 150 527 70 924UK 1787 1356 3035 809 112 697 749 18 7755EURecycled

AUT 199 36 500 29 8 7 779BE 217 53 411 85 5 75 846DK 124 11 219 2 357FI 24 9 136 2 171FR 1388 102 2276 331 300 4397DE 2797 675 3193 915 1040 8621GK 180

IE 80IT 750 164 1170 25 700 2809LU

NL 354 76 941 145 1516PO 32SP 522 65 1242 76 60 1966SE 134 21 348 32 535UK 441 100 1609 211 27 184 2361EULegend:

data EC -MS reports 1997data report PWC review data MS 1997data valorlux : chiffres cléfs only HHdata PWC The facts a European cost/benefit analysis 1998



58

4.1.2 Critical factors limiting recycling and reuse

The critical factors identified in this section are taken into account in the calculations

and the hypothesis taken for packaging applications when no CBA is performed.

Recycling difficulties can be classified according to technical, economic and

marketing constraints. Marketing constraints can be avoided by specific marketing

actions: they mainly depend on the willingness of the industries.

On the other hand technical and economical constraints are more difficult – or

impossible up to now - to overcome. Technical constraints require R&D investments

or increase of collecting, sorting and/or treatment capacities. Economic constraints are

very difficult to control: e.g.: market prices, internal market barriers.

In Annex 9: Critical factors limiting recycling and reuse, the different material are

investigated.

Table 13 shows the identified recycling constraints per material. They are classified in

factors which are reasonable reasons to limit recycling and factors which may be valid

points but are not really a reason to limit recycling.

Table 13 : Summary of the recycling difficulties

Recycling difficulties Glass Plastics Paper/board Metals CompositesCapacity X (X)Output market / market price X Xcontamination X X X (X)imbalance supply-demand X XInsufficient amount of waste X (X) XRecycling lifetime XNature of waste (too thin,…) X X XRecycling costs X

Factors which are not really a reason to limit recycling Noise XHuman wound XInsufficient maintenance XDisposers participation X X X X XColour, odour XResistance to the use of recyclate X

The critical factors identified in this section are taken into account in the calculations

and the hypothesis taken for packaging applications when no CBA is performed.

For reuse processes, as for recycling, it is possible to distinguish between technical

and economical constraints. The third kind of constraints concern consumer

convenience.



59

These constraints are discussed in Annex 9: Critical factors limiting recycling and

reuse.



60

4.2 Results of Case study CBAs

In this section, the full set of calculations and results for PET beverage bottles are

explained, including a detailed presentation of the sensitivity analysis. For other

cases studies, only the main results and conclusions and the implications of the

sensitivity analysis are presented.

4.2.1 PET bottles from household sources

4.2.1.1 Scenarios considered

Table 14 summarises the parameters considered for the baseline scenarios modelled.

Table 14 : Scenarios considered for PET beverage bottles

Population density

Selective collection scheme

Recycling rate achieved

MSW Waste management option

Scenario 1 Low None 0% LandfillScenario 2 Low None 0% IncinerationScenario 3 Low Separate kerbside collection 70-80% LandfillScenario 4 Low Separate kerbside collection 70-80% IncinerationScenario 5 Low Bring scheme 35-45% LandfillScenario 6 Low Bring scheme 35-45% IncinerationScenario 7 High None 0% LandfillScenario 8 High None 0% IncinerationScenario 9 High Separate kerbside collection 59-69% LandfillScenario 10 High Separate kerbside collection 59-69% IncinerationScenario 11 High Bring scheme 22-32% LandfillScenario 12 High Bring scheme 22-32% Incineration

4.2.1.2 Calculation of internal costs

The internal costs of each possible waste management option are calculated. To

achieve this, a number of allocations are applied:

♦ Allocation of MSW collection costs proportionally to the compressed density in

the collection truck

♦ Allocation of sorting costs proportionally to the density

♦ Allocation of fixed incineration costs proportionally to calorific value, necessary

combustion air (mainly), ash content, steel content, Al content, depending on the

part of the facilities

Allocation of variable incineration costs proportionally to variable parameters

(a.o. necessary combustion air, ash content, steel content, Al content)

For further details about incineration costs, see Annex 2: Incineration and

landfill models.



61

♦ Allocation of landfill costs proportionally to the crushed waste density in landfill

Costs for Landfilling 1 tonne PET bottles

Collection costs (Euro pertonne of PET bottles)

Landfill costs (Euro pertonne of PET bottles)

Total internal costsper tonne PET bottles

High populationdensity

294 140 434

Low populationdensity

228 140 368

Costs for Incineration of 1 tonne PET bottles

Collection costs(Euro per tonneof PET bottles)

Incineration –fixed costs (Europer tonne of PETbottles)

Incineration –variable costs(Euro per tonneof PET bottles)

Total internalcosts per tonnePET bottles


294 161 -63 392


228 161 -63 326

Costs for Recycling 1 tonne of PET bottles via separate kerbside collection

Collection

costs (Euro

per tonne of

PET bottles

recycled)

Sorting costs

(Euro per

tonne of

PET bottles

recycled)

Transport from

sorting plant to

reprocessor

(Euro per tonne

of PET bottles

recycled)

Reprocessing

cost (Euro per

tonne of

output)

Revenue

received for

reprocessed

material

Total internal

cost per tonne

PET bottles

recycled

High

population

density

255 474 46 332 -540 566

Low

population

density

306 474 46 332 -540 618

Costs for Recycling 1 tonne PET bottles via bring bank collection

Transport costs

from bring

bank to sorting

plant (Euro per

tonne of PET

bottles

recycled)

Sorting costs

(Euro per

tonne of

PET bottles

recycled)

Transport from

sorting plant to

reprocessor

(Euro per tonne

of PET bottles

recycled)

Reprocessing

cost (Euro per

tonne of

output)

Revenue

received for

reprocessed

material

Total internal

cost per tonne

PET bottles

recycled



62

High

population

density

196 474 46 332 -540 508

Low

population

density

242 474 46 332 -540 553

The costs per tonne for each waste treatment option are combined to give the cost per

tonne for each scenario modelled. For example, Scenario 3 considers low population

density, in which 70-80% of the PET bottles are recycled via separate kerbside

collection, with the remaining 20-30% going to landfill. Thus, the cost per tonne for

Scenario 3 can be calculated:

Scenario 3 cost per tonne = (0.7 * 618) + (0.3 * 368) to (0.8 * 618) + (0.2 * 368)

= 542 – 567 Euro per tonne

4.2.1.3 Calculation of externalities

The environmental models for each option were constructed using Pira International’s

LCI/LCIA software PEMS. The life cycle inventory is then compiled.

The environmental impacts associated with the inventory data set are then calculated.

To achieve this, the inventory data are characterised according to the potential impact

categories that they contribute to, and then multiplied by classification values.

Finally, the impact assessment data is multiplied by the economic valuations (as listed

in Annex 4: Economic valuations applied – sources and derivation) to achieve the

external cost of each impact category.

For example, if we consider only the global warming impact category, the following

results are achieved for PET bottles scenario 3:



63

Table 15 : Calculation of GWP externality for 1 tonne PET bottles to landfill,low population density

Classification factor

Economic valuation (Euro per kg CO2 Equiv)

carbon tetrachloride 0,0 to 0,0 -225 0,0 to 0,0CFC (unspecified) 0,0 to 0,0 1320 0,0 to 0,0CFC-11 0,0 to 0,0 1320 0,0 to 0,0CO2 (non renewable) -1479,4 to -1693,9 1 -1479,4 to -1693,9CO2 (renewable) 0,0 to 0,0 1 0,0 to 0,0CO2 (unspecified) 34,5 to 38,5 1 34,5 to 38,5dichloromethane 0,0 to 0,0 9 0,0 to 0,0haloginated HC (unspecified) 0,0 to 0,0 4 0,0 to 0,0halon -1301 0,0 to 0,0 -49750 -0,5 to -0,5halons (unspecified) 0,0 to 0,0 -49750 0,0 to 0,0HCFC (unspecified) 0,0 to 0,0 1350 0,0 to 0,0HCFC-22 0,0 to 0,0 1350 0,0 to 0,0hexafluoroethane 0,0 to 0,0 9200 0,0 to 0,0HFC (unspecified) 0,0 to 0,0 1000 0,0 to 0,0methane 0,2 to 0,2 21 4,5 to 5,0N2O 0,0 to 0,0 310 4,0 to 4,5tetrafluoromethane 0,0 to 0,0 6500 0,0 to 0,1tetrafluroethylene 0,0 to 0,0 1300 0,0 to 0,0trichloroethane 0,0 to 0,0 -1525 0,0 to 0,0trichloromethane 0,0 to 0,0 4 0,0 to 0,0

-1436,8 -1646,4 0,01344 -19,3112 to -22,127

Results of characterisation (CO2 Equiv.) Externality (Euros)

Emissions (kg of emission per tonne PET

landfilled)Inventory data

For each scenario, the external cost of all impact categories is summed to determine

the total external cost. The total external cost for PET bottles scenario 3 are presented

in Table 16



64

Table 16 : Total externalities for PET bottles, Scenario 3

ExternalitiesGWP (kg CO2 eq.) -19,3 to -22,1

Ozone depletion (kg CFC 11 eq.) 0,0 to 0,0Acidification (Acid equiv.) -6,9 to -7,9

Toxicity Carcinogens (Cd equiv) 0,0 to 0,0Toxicity Gaseous (SO2 equiv.) -24,8 to -28,4

Toxicity Metals non carcinogens (Pb equiv.) -5,4 to -6,2Toxicity Particulates & aerosols (PM10 equiv) -164,9 to -189,8

Toxicity Smog (ethylene equiv.) -35,7 to -40,9Black smoke (kg dust eq.) -16,5 to -18,9

Fertilisation 9,2 to 10,5Traffic accidents (risk equiv.) 0,9 to 1,0

Traffic Congestion (car km equiv.) 5,0 to 5,7Traffic Noise (car km equiv.) 2,8 to 3,1

Water Quality Eutrophication (P equiv.) -0,8 to -0,9Disaminity (kg LF waste equiv.) 11,1 to 7,4

TOTAL EXTERNALITIES -245,5 to -287,4

Euro per tonne

4.2.1.4 Calculation of Employment

The gross employment is determined for each waste management option. This is

presented in the tables below.

Gross Employment, landfilling of PET bottles (jobs per 1000 tonne per annum)

Collection Landfill management / operation TotalHigh population density 1.2 0.1 1.3Low population density 1.15 0.1 1.25

Gross Employment , incineration of PET bottles (jobs per 1000 tonne per annum)

Collection Incinerator management / operation TotalHigh population density 1.2 0.27 1.47Low population density 1.15 0.27 1.42

Gross Employment , kerbside collection and sorting of PET bottles

Jobs per 1000 tonne perannum

Collection Sorting Transport from sorting toreprocessing

Total

High population density 14.7 0.71 0.19 15.6Low population density 17.7 0.71 0.19 18.6

Gross Employment , bring scheme collection and sorting of PET bottles

Jobs per 1000 tonneper annum

Transport, bring bankto sorting

Sorting Transport fromsorting to

reprocessing

Total



65


3.2 0.71 0.19 4.1


3.8 0.71 0.19 4.7

The total gross jobs for each scenario modelled can then be calculated. For example,

Scenario 3 considers low population density, in which 70-80% of the PET bottles are

recycled via separate kerbside collection, with the remaining 20-30% going to

landfill. Thus, the gross employment per tonne for Scenario 3 can be calculated :

Scenario 3 jobs per 1000 tonne = (0.7 * 18.6) + (0.3 * 1.25) to (0.8 * 18.6) + (0.2 *

1.25)

= 13.4 – 15.13 jobs per 1000 tonne per annum (or 14.27

jobs per 1000 tonne per annum if the median is

considered).

The external economic value for these jobs is then calculated by applying the

economic valuation for employment (2945 Euro per job per annum, as described in

Annex 4: Economic valuations applied – sources and derivation). Thus, for

Scenario 3 the external economic value is 14.27/1000*2495 = 42.01 Euro per tonne of

waste PET bottles.



66

4.2.1.5 Compile total social costs - Results of the cost benefit analysis

Table 17 : Internal costs, external costs and total social costs (low pop. density)

Graph 1 : Total social costs (low population density)

PET bottles - Low Population DensityTotal Social Cost

0

50

100

150

200

250

300

350

400

450

Landfill Separatekerbside

collection / landfill

Bring scheme /landfill

Incineration Separatekerbside

collection /incineration

Bring scheme /incineration

Scenario

To

tal S

oci

al C

ost

/ Eu

ro p

er t

on

ne

Collection method N/A N/ARecycling rate 0,0 0,0Residual waste management option Landfill IncinerationExeternalities

GWP (kg CO2 eq.) 0,4 19,2 -19,3 to -22,1 -13,7 to -18,4 -9,5 to -12,3 2,8 toOzone depletion (kg CFC 11 eq.) 0,0 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to

Acidification (Acid equiv.) 0,0 -1,2 -6,9 to -7,9 -7,3 to -8,1 -3,4 to -4,4 -4,2 toToxicity Carcinogens (Cd equiv) 0,0 -0,1 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 toToxicity Gaseous (SO2 equiv.) 0,1 -4,1 -24,8 to -28,4 -26,1 to -29,3 -12,0 to -15,4 -14,7 to -1

Toxicity Metals non carcinogens (Pb equiv.) 0,1 -0,5 -5,4 to -6,2 -5,6 to -6,3 -2,6 to -3,4 -3,0 toToxicity Particulates & aerosols (PM10 equiv) 9,6 -44,6 -164,9 to -189,8 -181,2 to -200,7 -83,4 to -110,0 -118,6 to -13

Toxicity Smog (ethylene equiv.) 0,3 -0,8 -35,7 to -40,9 -36,1 to -41,1 -17,7 to -22,9 -18,4 to -2Black smoke (kg dust eq.) 0,2 -3,9 -16,5 to -18,9 -17,8 to -19,7 -8,1 to -10,5 -10,8 to -1

Fertilisation -0,1 0,4 9,2 to 10,5 9,4 to 10,6 4,5 to 5,9 4,9 toTraffic accidents (risk equiv.) 0,1 0,1 0,9 to 1,0 0,9 to 1,0 2,4 to 3,0 2,4 to

Traffic Congestion (car km equiv.) 0,1 0,1 5,0 to 5,7 5,0 to 5,7 2,6 to 3,3 2,6 toTraffic Noise (car km equiv.) 0,4 0,4 2,8 to 3,1 2,8 to 3,1 1,3 to 1,5 1,3 to

Water Quality Eutrophication (P equiv.) 0,0 -0,1 -0,8 to -0,9 -0,8 to -0,9 -0,4 to -0,5 -0,4 toDisaminity (kg LF waste equiv.) 37,0 12,0 11,1 to 7,4 3,6 to 2,4 24,1 to 20,4 7,8 to

TOTAL EXTERNALITIES 48,2 -22,9 -245,5 to -287,4 -266,8 to -301,6 -102,3 to -145,3 -148,5 to -18INTERNAL COSTS 368,0 326,0 542,3 to 567,2 529,7 to 558,8 432,8 to 451,3 405,5 to 42TOTAL SOCIAL COSTS 416,2 303,1 296,8 to 279,8 262,9 to 257,2 330,5 to 306,0 256,9 to 24

Bring scheme35-45%Landfill

Separate kerbside

collection70-80%

Incineration

Bring scheme35-45%

Incineration

Separate Kerbside collection

70-80%Landfill



67

Table 18 : Internal costs, external costs and total social costs (high pop. density)


GWP (kg CO2 eq.) 0,3 19,1 -15,9 to -18,7 -8,2 to -12,8 -6,2 to -9,1 8,5 to 3,7Ozone depletion (kg CFC 11 eq.) 0,0 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0

Acidification (Acid equiv.) 0,0 -1,2 -5,5 to -6,4 -6,0 to -6,8 -2,2 to -3,1 -3,1 to -4,0Toxicity Carcinogens (Cd equiv) 0,0 -0,1 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0Toxicity Gaseous (SO2 equiv.) 0,1 -4,1 -19,8 to -23,2 -21,5 to -24,5 -7,7 to -11,2 -11,0 to -14,1

Toxicity Metals non carcinogens (Pb equiv.) 0,1 -0,5 -4,3 to -5,1 -4,5 to -5,2 -1,6 to -2,4 -2,1 to -2,8Toxicity Particulates & aerosols (PM10 equiv) 8,3 -45,9 -136,3 to -160,8 -158,5 to -177,6 -52,6 to -80,2 -94,8 to -117,1

Toxicity Smog (ethylene equiv.) 0,2 -0,9 -28,7 to -33,6 -29,1 to -33,9 -11,2 to -16,4 -12,1 to -17,2Black smoke (kg dust eq.) 0,2 -3,9 -13,2 to -15,5 -14,9 to -16,8 -5,1 to -7,5 -8,3 to -10,3

Fertilisation -0,1 0,5 7,4 to 8,7 7,7 to 8,9 2,9 to 4,3 3,3 to 4,6Traffic accidents (risk equiv.) 0,2 0,2 1,0 to 1,1 1,0 to 1,1 0,8 to 1,1 0,8 to 1,1

Traffic Congestion (car km equiv.) 8,2 8,2 44,4 to 50,5 44,4 to 50,5 25,4 to 33,3 25,5 to 33,3Traffic Noise (car km equiv.) 0,2 0,2 1,1 to 1,3 1,1 to 1,3 0,4 to 0,6 0,4 to 0,6

Water Quality Eutrophication (P equiv.) 0,0 -0,1 -0,6 to -0,7 -0,7 to -0,7 -0,2 to -0,4 -0,3 to -0,4Disaminity (kg LF waste equiv.) 37,0 12,0 15,2 to 11,5 4,9 to 3,7 28,9 to 25,2 9,4 to 8,2

TOTAL EXTERNALITIES 54,6 -16,5 -155,3 to -190,9 -184,4 to -212,9 -28,4 to -66,1 -83,8 to -114,4INTERNAL COSTS 434,0 392,0 511,9 to 525,1 494,7 to 512,1 450,3 to 457,7 417,5 to 429,1TOTAL SOCIAL COSTS 488,6 375,5 356,6 to 334,2 310,2 to 299,2 421,9 to 391,6 333,7 to 314,7


Separate kerbside collection Bring scheme Bring scheme

59-69% 59-69% 22-32% 22-32%Landfill Incineration Landfill Incineration

Graph 2 : Total social costs (high population density)

PET bottles - High Population DensityTotal Social Cost

0

100

200

300

400

500

600

Landfill Separate kerbsidecollection / landfill


Incineration Separate kerbsidecollection /incineration


Scenario

To

tal S

oci

al C

ost

/ E

uro

pet

to

nn

e

4.2.1.6 Initial conclusions

For low population density, where landfill is the MSW treatment option the main

conclusions are:

♦ Landfilling is the preferred option from an internal cost perspective

♦ When total social costs are considered separate kerbside collection achieving a

recycling rate of 70-80% is the optimal solution of the options considered. This is

due to the environmental credit achieved by avoided production of virgin bottle



68

grade PET. The main benefit is associated with avoided emissions of particulates

and aerosols.

For low population density, where incineration is the MSW treatment option the main

conclusions are:

♦ Incineration is the preferred option from an internal cost perspective

♦ When total social costs are considered a bring scheme achieving a recycling rate

of 35-45% is the optimal solution of the options considered. This is due to the

environmental credit achieved by avoided production of virgin bottle grade PET.

The main benefit is associated with avoided emissions of particulates and

aerosols.

For high population density, where landfill is the MSW treatment option the main

conclusions are:

♦ Landfilling is the preferred option from an internal cost perspective

♦ When total social costs are considered separate kerbside collection achieving a




and aerosols.

For high population density, where incineration is the MSW treatment option the

main conclusions are:

♦ Incineration is the preferred option from an internal cost perspective

♦ When total social costs are considered a separate kerbside collection achieving a




and aerosols.

4.2.1.7 Sensitivity analysis: Methodological choices

Choice of external valuation values



69

Graph 3 and Graph 4 show the sensitivity of the analysis to the economic valuations

applied to the defined environmental impacts. The graph has been produced by

considering the same environmental impact results, but applying different impact

assessment valuations (see Annex 4: Economic valuations applied – sources and

derivation for a list of maximum and minimum valuations applied). The results of

the analysis and conclusions that can be drawn are extremely dependent on the

economic valuations applied. Applying the full range of available economic

valuations makes it impossible to make a clear and reliable distinction between any of

the waste management scenarios investigated.

Graph 3 : Sensitivity of the results to the external economic valuations applied -Low population density

PET bottles - Low Population DensitySensitivity analysis on variations in economic valuations

applied

-3500.0-3000.0-2500.0-2000.0-1500.0-1000.0

-500.0

0.0500.0

1000.0

Landfill Incineration Separatekerbside

collection /landfill

Separatekerbside




Scenario

To

tal S

oci

al C

ost

/ E

uro

per

to

nn

e



70

Graph 4 : Sensitivity of the results to the external economic valuations applied- High population density

PET bottles - High Population DensitySensitivity analysis on variations in economic valuations

applied

-3000.0

-2500.0

-2000.0

-1500.0

-1000.0

-500.0

0.0

500.0

1000.0



Separatekerbside




Scenario

To

tal S

oci

al C

ost

/ E

uro

per

to

nn

e

Internal costs

The internal costs applied in this study have been sourced mostly from the UK,

France and Belgium. Even where equivalent waste management practices are

compared internal costs can vary considerably between Member States, depending on

a range of factors such as cost of living and geographical considerations (mountainous

regions, islands, etc). In this part of the sensitivity analysis, the effect on the results

of considering a +/-20% variation in internal costs is investigated. The results are

presented in Graph 5 and Graph 6.



71

Graph 5 : Sensitivity of the results to the internal economic costs considered -Low population density

PET bottles - Low Population DensitySensitivity analysis on variations in Internal Costs

0.0

100.0

200.0

300.0

400.0

500.0

600.0



Separatekerbside




Scenario

To

tal s

oci

al c

ost

s / E

uro

per

to

nn

e

Graph 6 : Sensitivity of the results to the internal economic costs considered -High population density

PET bottles - High Population DensitySensitivity analysis on variations in Internal Costs

0.0

100.0

200.0

300.0

400.0

500.0

600.0

700.0



Separatekerbside




Scenario

To

tal s

oci

al c

ost

/ E

uro

per

to

nn

e

The graphs show that the conclusions that can be drawn from the analysis are highly

dependent upon the internal cost assumptions made.

Inclusion of employment as an impact category

In Graph 7 and Graph 8, employment has been added as an external impact category.

The graphs show that for low population density where incineration is the alternative



72

MSW option the scenario incorporating separate kerbside collection now becomes the

optimal system for the scenario considered.

Graph 7 : Addition of employment as an impact category - low pop. density


0,0

50,0

100,0

150,0

200,0

250,0

300,0

350,0

400,0

450,0

Landfill Incineration Separate kerbsidecollection / landfill

Separate kerbsidecollection /incineration



Scenario

To

tal S

oci

al C

ost

Graph 8 : Addition of employment as an impact category - high pop. density


0.0

100.0

200.0

300.0

400.0

500.0

600.0

Landfill Incineration Separate kerbsidecollection / landfill

Separate kerbsidecollection / incineration

Bring scheme / landfill Bring scheme /incineration

Scenario

To

tal S

oci

al C

ost

4.2.1.8 Sensitivity analysis: scenario and modelling choices

Incineration model

The baseline analysis for scenarios where incineration is the MSW option considers

that a proportion of the energy is recovered and converted to electricity. In this part

of the sensitivity analysis, the effect of considering combined heat and power is

investigated. The effect on the results for high and low population density is

presented in Graph 9 and Graph 10.



73

Graph 9 : Sensitivity of the results to energy recovery assumptions

low population density

P E T b o t t l e s - L o w P o p u l a t i o n D e n s i t yS e n s i t i v i t y a n a l y s i s o n i n c i n e r a t i o n w i t h C H P

0,0

50,0

100,0

150,0

200,0

250,0

300,0

350,0

Incinerat ion Sepa ra te ke rbs i decollection / incineration

B r i n g s c h e m e /incineration

S c e n a r i o

To

tal S

oci

al C

ost

/ E

uro

per

to

nn

e



74

Graph 10 : Sensitivity of the results to energy recovery assumptions

high population density

PET bottles - High Population DensitySensitivity analysis on incineration with CHP

0,0

50,0

100,0

150,0

200,0

250,0

300,0

350,0

400,0

Incineration Separate kerbside collection /incineration

Bring scheme / incineration

Scenario

To

tal S

oci

al C

ost

/ E

uro

per

to

nn

e

Although considering an efficient CHP scenario reduces the Total Social Cost of

incineration, the relative standing of the options is not affected. The results are not

sensitive to this assumption.

The baseline incineration model considers that the offset electricity from the

incineration process is undelivered average European electricity. Graph 11 and Graph

12 investigate the effect of considering a specific offset electricity production method

: coal.



75

Graph 11 : Sensitivity of results to offset electricity assumption - Low pop.density

PET bottles - Low Population Density

Sensitivity analysis on offset electricity production

180.0

190.0

200.0

210.0

220.0

230.0

240.0

250.0



Scenario

Tota

l Soc

ial C

ost /

Eur

o pe

r ton

ne

Graph 12 : Sensitivity of results to offset electricity assumption - High pop.density

PET bottles - High Population DensitySensitivity analysis on incineration with CHP

240.0

250.0

260.0

270.0

280.0

290.0

300.0

310.0



Scenario

Tota

l Soc

ial C

ost /

Eur

o pe

r to

nne

The analysis shows that the total social cost for incineration options is significantly

reduced. For low population density, the 100% incineration scenario is now

preferable to the scenario incorporating kerbside collection, but the overall conclusion

that the bring scheme achieving a recycling rate of 35-45% is the optimal scenario

remains valid. For high population density, the bring scheme achieving a recycling

rate of 35-45% is now slightly preferable than the kerbside collection. However 100%

incineration scenario remains the worst solution.



76

Transport distances

For the baseline models, the median distance was selected from a range for each

transport step. In the baseline analysis, transportation steps are relatively

uninfluential in determining the relative standing of the systems. However, in this

part of the sensitivity analysis the influence of the assumed transport distances is

investigated by compiling best case transport scenarios for landfilling and

incineration, and worst cast transport scenarios for kerbside collection and bring

schemes. The data applied are summarised in Table 19:

Table 19 : Transport distances

Transportation journey Baseline distance (kmper tonne)

Sensitivity (km pertonne)

Landfill and incineration

MSW collection, low population density 22.1 12

MSW collection, high population density 9.7 4

Separate kerbside collection

Kerbside collection round, low pop density 151.1 228

Kerbside collection round, high pop density 64.4 108

Transport from sorting plant to reprocessor 23.05 27

Bring scheme

Collection from bring bank, low pop density 83.05 124

Collection from bring bank, high pop density 27.6 37

Transport from sorting plant to reprocessor 23.05 27

The reason we made this type of analysis is that the objective is to try to find out if the

conclusions are robust. The results suggest that the scenarios incorporating recycling

are preferable. But what happens if the MSW options are better and the recycling

options worse? To find out, we reduce MSW collection round and increase separate

kerbside round, etc. This gives us best case MSW and worst case recycling for the

sensitivity analysis. If we considered the other end of the scale, (i.e. increase MSW

round, reduce recycling transport) all we would do is increase the difference between

the options.

The results are presented in Graph 13 and Graph 14.



77

Graph 13 : Sensitivity of results to transport distances - Low population density


0.0

50.0

100.0

150.0

200.0

250.0

300.0

350.0

400.0

450.0



Separatekerbside




Scenario

To

tal S

oci

al C

ost

Graph 14 : Sensitivity of results to transport distances - High populationdensity

PET bottles - High Population Density

Total Social Cost

0.0

100.0

200.0

300.0

400.0

500.0

600.0



Separatekerbside




Scenario

To

tal S

oci

al C

ost

These graphs demonstrate that the results and conclusions drawn are not sensitive to

the transport assumptions made for MSW collection, kerbside collection round,

collection from bring banks and transport from sorting to reprocessing. It is sensitive

for high population density in case of incineration considered as MSW alternative

treatment. Bring scheme is then “better” than kerbside collection system, from a total

social cost point of view. However, this does not provide any indication of the



78

sensitivity of the results to assumptions made for transport by the public to deliver

bottles to the bring bank. This is not easily tested, as no range of data for this

transport step was available, just a single value. In order to gauge whether this may

be an important parameter the assumed transport distance has been doubled – the

results of this sensitivity analysis are presented below.

Graph 15 : Sensitivity of results to consumer transport step - High pop. density


0.0

50.0

100.0

150.0

200.0

250.0

300.0

350.0

400.0

450.0


collection /

landfill

Separatekerbside

collection /

incineration



Scenario

Tota

l Soc

ial C

ost

Graph 16 : Sensitivity of results to consumer transport step - High pop. density


0.0

100.0

200.0

300.0

400.0

500.0

600.0



Separatekerbside




Scenario

Tota

l Soc

ial C

ost

From these graphs it can be seen that doubling distance reduces the favourability of

the bring scheme scenario in comparison with the separate kerbside system. The

relative standing of the bring scheme scenarios is not altered in comparison to 100%

landfill or 100% incineration.



79



80

Reprocessing overseas

The baseline scenario assumes that recycling will occur within the EU (within the

country of origin of the packaging waste, or in a neighbouring Member State).

However, it is common for secondary materials to be reprocessed overseas. The

influence of this assumption is investigated in Graph 17 and Graph 18, which add an

additional ship transport step to the journey from the sorting plant to reprocessing.

Although the total social cost of scenarios incorporating recycling is increased, the

relative standing of the scenarios is unaffected.

Graph 17 : Sensitivity of results to overseas transport step - Low populationdensity


0.0

50.0

100.0

150.0

200.0

250.0

300.0

350.0

400.0

450.0



Separatekerbside




Scenario

To

tal S

oci

al C

ost



81

Graph 18 : Sensitivity of results to overseas transport step - High populationdensity


0.0

100.0

200.0

300.0

400.0

500.0

600.0

Landfill Incineration Separate

kerbsidecollection /

landfill

Separate

kerbsidecollection /

incineration

Bring scheme /

landfill

Bring scheme /

incineration

Scenario

To

tal S

oci

al C

ost

Offset virgin production

The baseline scenarios for PET recycling assume that the recyclate offsets virgin

bottle grade PET production, with a save ratio of 1:1. The offset virgin production

accounts for the credit which dominates the externalities for the recycling systems.

The effect of this assumption on the validity of the results and conclusions is

investigated in Graph 19 and Graph 20, where it is assumed that the save ratio is

reduced to 0.8:1, and a lower grade of virgin PET is offset.

Graph 19 : Sensitivity of results to virgin production credit - Low pop. density


0,0

50,0

100,0

150,0

200,0

250,0

300,0

350,0

400,0

450,0


kerbsidecollection / landfill

Separate

kerbsidecollection /incineration

Bring scheme /

landfill

Bring scheme /

incineration

Scenario

To

tal S

oci

al C

ost



82

Graph 20 : Sensitivity of results to virgin production credit - High pop. density


0.0

100.0

200.0

300.0

400.0

500.0

600.0


kerbside


Separate

kerbside


Bring scheme /

landfill

Bring scheme /

incineration

Scenario

To

tal S

oci

al C

ost

Where landfill is the alternative MSW option, there is no change in the relative

standing of the scenarios. However, where incineration is the alternative MSW

option, changing the assumptions for the offset virgin production credit could

influence the results and conclusions – in this analysis (high population density) it

becomes very difficult to distinguish between 100% incineration and the scenarios

that incorporate recycling.

Alternative reprocessing options

The baseline scenarios consider that the PET bottle waste is reprocessed into PET

granulate for use in further PET bottle manufacture. Other options are available for

reprocessing of PET. In order to investigate the sensitivity of the results to this

parameter, Eco-Emballages provided life cycle data for the three layers and

Supercycle reprocessing processes.

In order to protect the confidentiality of the data, specific results are not presented in

this report, but the analysis revealed that the environmental externalities for the

alternative reprocessing options are of a similar scale due to the similar energy

requirements of the processes. In some specific cases where incineration is the MSW



83

option the choice of reprocessing option could make it difficult to distinguish between

a 100% incineration scenario and a scenario incorporating recycling.

Using data provided by Eco-Emballages, a sensitivity analysis using LCI data for the

TBI process was also applied. Due to time and resource constraints, the sensitivity

analysis considered only the implications of the alternative reprocessing route for

Global warming potential and for internal costs. The analysis suggested that although

TBI reprocessing may have higher internal costs the process could potentially

compete with material recycling from a total social cost perspective.

4.2.1.9 Summary of sensitivity analysis

Parameter investigated Influence on CBA results Influence on conclusionsdrawn

Methodological issues

Economic values applied Significant Critical – applying a maximum andminimum range of economic valuationsmakes it impossible to distinguishbetween scenarios

Internal costs Significant Critical – applying a +/-20% range ofinternal costs makes it impossible todistinguish between scenarios

Inclusion of employment as anexternality

Significant for kerbside collectionscenarios

Critical – valuing employment as anexternal impact category would changethe relative position of some scenarios.Where incineration with energyrecovery is the alternative MSW option,the scenarios incorporating separatekerbside collection would now beconsidered the optimal system, therebyincreasing optimal recycling rates forthis situation.

Scenario choices

Incineration model - CHP Total social cost of incinerationscenarios reduced

No effect on relative standing of thescenarios

Incineration model – offset electricity Total social cost of incinerationscenarios reduced.

For low population density, 100%incineration is now more favourablethan a system incorporating kerbsidecollection, but a system incorporating abring scheme remains the optimal of thescenarios considered

Significant for high population density,where incineration is the alternativeMSW option, the bring scheme systemwould now be considered the optimalsystem, thereby decreasing optimalrecycling rates for this situation.

Transport distances – MSW collectionround distance, separate kerbside round,

collection from bring banks, transportfrom bring bank to reprocessor

Effect on the relative standing ofscenarios

No effect on the choice of optimumscenarios

Significant for high population density,where incineration is the alternativeMSW option, the bring scheme systemwould now be considered the optimal



84

system, thereby decreasing optimalrecycling rates for this situation.

Transport distances – consumertransport to bring bank

Increases total social cost of bringschemes

Where incineration is the alternativeMSW option, choice of optimumscenario could change from systemincorporating bring scheme to systemincorporating separate kerbsidecollection. This would increase theoptimum recycling rate

Overseas reprocessing Total social cost of scenariosincorporating recycling is increased, butno change in relative standing of thescenarios

No effect on the choice of optimumscenarios

Offset virgin production Total social costs of scenariosincorporating recycling is increased.

Where landfill is the MSW option, thereis no change in the relative standing ofthe scenarios.

In high population density, whereincineration is the MSW option, itbecomes impossible to choose betweenthe scenarios

Where landfill is MSW option, no effecton choice of optimum scenario

Where incineration is MSW option, noobvious optimum scenario and thereforeno obvious optimum recycling rate, incase of high population density.

Alternative reprocessing options General scale of externalities remainsthe same.

Could affect the choice of optimumscenario under certain circumstances

4.2.2 Steel packaging from household sources

18 scenarios were modelled taking into account the following parameters :

- low and high population density

- landfill, incineration with energy recovery but without slags recovery and

incineration with energy and slags recovery as alternative MSW treatment

options

- no selective collection, kerbside collection and bring scheme as potential

collection systems.

Results are compared from total social cost perspective, and the optimum system for

the scenarios considered is determined according to the methodology described in

chapter 3.4.1. (see Table 20)

Table 20 : Optimum systems for steel packaging

Low population density High population density

Landfill Bring scheme (Although thedifference between allscenarios is very small)

No selective collection andbring scheme (because thedifference between thesystems is negligible)

Incineration without slags Bring scheme No selective collection and



85

recovery bring scheme (because thedifference between thesystems is negligible)

Incineration with slagsrecovery

No selective collection No selective collection

Detailed results of the CBA and the sensitivity analysis are presented in Annex 10 :

Presentation of CBA results for recycling case studies.

4.2.3 Aluminium packaging from household sources

4.2.3.1 Cans





options


collection systems.


the scenarios considered is determined. Results are given in Table 21.

Table 21 : Optimum systems for aluminium cans


Landfill Separate kerbside collectionscheme

Separate kerbside collectionscheme

Incineration without slagsrecovery




No selective collection Bring scheme

Detailed results of the CBA and the sensitivity analysis are given in Annex 10 :


4.2.3.2 Other rigid and semi-rigid application




86




options


collection systems.



Table 22 : Optimum systems for other rigid and semi-rigid aluminiumpackaging


Landfill separate kerbside collection separate kerbside collectionand bring scheme

Incineration without slagsrecovery

separate kerbside collectionand bring scheme


separate kerbside collectionand bring scheme



4.2.4 Paper and board packaging from household sources



- landfill and incineration with energy recovery as alternative MSW treatment

options


collection systems.



Table 23 : Optimum systems for paper & board packaging



87


Landfill kerbside collection scheme kerbside collection scheme


kerbside collection scheme kerbside collection scheme



4.2.5 LBC from household sources




options

- landfill and incineration with energy recovery as recycling rejects treatment

options


collection systems.



Table 24 : Optimum systems for LBC packaging

MSW treatment Rejects treatment Low pop. density High pop. density

Landfill Landfill No selective collection No selective collection

Landfill Incineration No selective collection No selective collection

Incineration withslags recovery

Incineration No selective collection No selective collection



4.2.6 Mix plastic packaging from household sources





88


options

- no selective collection, kerbside collection with mechanical recycling or with

treatment in blast furnace as potential collection & recycling options.



Table 25 : Optimum systems for mix plastic packaging

MSW treatment Low pop. density High pop. density

Landfill No selective collection No selective collection

Incineration with slags recovery No selective collection No selective collection



4.2.7 Industrial case studies

For the 2 industrial case studies, i.e. LDPE plastic films and cardboard, we calculated

the minimum packaging waste production under which the selective collection is not

beneficial.

The external benefits (EB) of collecting and recycling industrial packaging waste has

been calculated as 11.7 EURO/t (corrugated board) and 208 EURO/t (PE film).

Collecting and transporting corrugated board and PE films as mixed waste is often

cheaper than collecting and transporting source sorted packaging. There is thus an

additional collection cost (ACC) to collect selectively.

The annual production of industrial packaging waste for which the ACC = EB is

Ø 5.5 t/year for cardboard

Ø 0.01 t/year for LDPE plastic films

Above this waste production the environmental benefits outweigh the additional

internal cost for the selective collection.

This means that, from a cost-benefit viewpoint, the companies who produce more

waste than 0.01 t of plastic film or 5.5 t of corrugated board per year should have a

selective collection scheme to recycle it. As the "break-even" amount is very low for

PE films, it can be concluded that selective collection of industrial packaging should



89

be systematic throughout the EU. As there are limits to the modelling, it has been

assumed for this study that 95% of the industrial sites (percentage in packaging

weight) should make the selective collection of packaging.

This means that the recycling rates that should achieved for the industrial packaging is

equal to "95% of the collection rate achievable when a selective collection scheme is

set up" multiplied by the fraction of the waste that may be recycled for safety (in

contact with hazardous products) or technical reasons (too high material degradation).

In other words, the recycling rates that minimise (read "optimise") the social cost of

the industrial packaging waste management are the ones given in Table 7 on page 37

multiplied by 95%.



90

4.3 Suggested recycling targets

4.3.1 Determination of optimum systems and recycling ranges

For each combination of parameters (i.e. population density, alternative MSW

treatment options), the “optimal” collection system is considered to be the collection

system corresponding to the scenario modelled with the lowest total social cost. The

scenarios and their results are discussed in chapter 4.2 and summarised in Table 26

Table 26 : Optimum collection systems per case study, based on CBA


Landfill Incineration Landfill Incineration

PET bottles Kerbside Bring Kerbside Kerbside

Steel packaging Bring No SC No or bring No SC

Al cans Kerbside No SC Kerbside Bring

Rigid & semi-rigid Alpackaging excluding cans

Kerbside Kerbside orbring

Kerbside orbring

Kerbside orbring

Paper and board packaging Kerbside Kerbside Kerbside Kerbside

LBC No SC No SC No SC No SC

Mix plastic packaging No SC No SC No SC No SC

However the choice of optimum collection system has also to consider

communication aspects. It mainly means to take into account the understanding and

behaviour of the consumer. E.g. the consumer will not be able to make the difference

between aluminium and steel cans. Therefore it assumed that both packaging material

should be collected with the same collection systems.

Insofar as the optimal collection systems, based on CBA calculation, are not the same

for all metals packaging, weighted Total Social Costs are compared in order to

determine the common optimal system. The weighting parameters are the amount of

packaging put on the market. The common optimal collection systems are given in

Table 27.



91

Table 27 : Optimal collection systems for metal packaging



Steel packaging Bring and kerbside No SC Kerbside No SC

Al cans Bring and kerbside No SC Kerbside No SC

Rigid & semi-rigid Alpackaging excluding cans

Bring and kerbside No SC Kerbside No SC

On the other hand the models do not consider scale effects. Therefore PET bottles,

LBC and metals packaging could be collected with different collection systems

provided that the collected amount is sufficient to justify a frequency of at least once a

month.

The “optimal” recycling rate is considered to be the recycling rate achievable by the

“optimal” collection system. Therefore Table 28 gives the range of “optimal”

recycling rates for each case study.

Table 28 : Optimal recycling ranges per case study

Low population density High populationdensity


PET bottles 70-80% 35-45% 59-69% 59-69%

Steel packaging 15-60% 80% 40-60% 80%

Al cans 31-55% 76% 45-55% 76%

Rigid & semi-rigid Al packagingexcluding cans

3-17% 50% 3-8% 50%

Paper and board packaging 61-71% 61-71% 55-65% 55-65%

LBC 0% 0% 0% 0%

Mix plastic packaging 0% 0% 0% 0%

4.3.2 Determination of optimal recycling rate for each Member State

This chapter concerns the determination of ranges of global optimal recycling rate for

each Member States. The global recycling rate takes into account all the packaging

whatever their origin (i.e. household and industrial sources).



92

For each application, optimal recycling rates were determined for each of the 4

categories (population density / MSW treatment) (see Table 28). The optimum target

for an application in a specific Member State is the weighted average of the 4 targets

related to the 4 categories. The weighting factors are the ones given in Table 11.

In order to obtain ranges of recycling targets, the minimum and maximum optimal

recycling rates are successively applied to the packaging mix of each Member State.

Table 29 illustrates the calculation of the range of global optimal recycling rate for the

European Union. The packaging mix considered is the sum of the packaging amount

arising in all the Member States.



93

Table 29 : Calculation of minimum and maximum recycling rate for the EU

Minimum recycling ratesEU 2000 Amount of Amount of waste

Material Application waste to be recycledIndustrial waste 1000 t/year 1000 t/year

Plastics Total 4.018 1.348LDPE films 1.651 869Other 2.367 479

Wood 7.812 3.711Steel 1.818 1.382Cardboard 18.823 11.444glass 1.789 850Other 289 0

Total 34.549 18.735

Global Target Industrial waste 54%

landfill Inc. landfill Inc.Household waste 27% 12% 41% 20%

Plastics 5.871 1.374PET bottles 1.502 70% 35% 59% 59% 887LPDE films 1.205 0% 0% 0% 0% 0HDPE bottles 1.015 57% 28% 48% 48% 487other 2.150 0% 0% 0% 0% 0

Steel 2.214 15% 80% 40% 80% 1.022aluminium total 391,6 96Wood 128 0% 0% 0% 0% 0Cardboard total 5.947 61% 61% 55% 55% 3.411composites liquid beverage c a 710 0% 0% 0% 0% 0

mainly based on p 109 0% 0% 0% 0% 0mainly based on c 165 0% 0% 0% 0% 0mainly based on A 86 0% 0% 0% 0% 0

Glass 13.445 73% 73% 42% 42% 7.288Other 65 0% 0% 0% 0% 0

Total 29.132 13.191

Global Target Household waste 45%

Total 63.681 31.926

Global target (Industrial + Household waste) 50%


Low High

0% 50%0% 0%

0% 80%0% 64%

0% 21%0% 50%

0% 55%

Optimised recycling/reuse targetLow packaging amount High packaging amount

5% 95%



94

Maximum recycling ratesEU 2000 Amount of Amount of waste


Plastics Total 4.018 2.111LDPE films 1.651 1.182Other 2.367 929

Wood 7.812 5.195Steel 1.818 1.555Cardboard 18.823 14.306glass 1.789 1.411Other 289 0

Total 34.549 24.577



Plastics 5.871 1.626PET bottles 1.502 80% 45% 69% 69% 1.037LPDE films 1.205 0% 0% 0% 0% 0HDPE bottles 1.015 67% 38% 58% 58% 589other 2.150 0% 0% 0% 0% 0

Steel 2.214 60% 80% 60% 80% 1.472aluminium total 391,6 122Wood 128 0% 0% 0% 0% 0Cardboard total 5.947 71% 71% 65% 65% 4.006composites liquid beverage c 710 0% 0% 0% 0% 0

mainly based o n 109 0% 0% 0% 0% 0mainly based o n 165 0% 0% 0% 0% 0mainly based o n 86 0% 0% 0% 0% 0

Glass 13.445 83% 83% 91% 91% 11.811Other 65 0% 0% 0% 0% 0

Total 29.132 19.036


Total 63.681 43.613



5% 95%

0% 75%0% 41%0% 70%0% 90%0% 80%0% 83%0% 0%


Low High

Detailed tables per Member State are given in Annex 11 : Calculation of recycling

rates per Member States.

The minimum and maximum recycling targets are summarised per Member States in

Table 30. They are detailed per industrial and household packaging sources.



95

Table 30 : Summary of the ranges of optimal recycling rates per MemberStates

Global Target Industrialwaste

Global Target Householdwaste

Global target (Industrial +Household waste)

Min Max Min Max Min Max

Austria 56% 74% 42% 60% 49% 67%

Belgium 54% 70% 42% 65% 48% 67%

Denmark 54% 70% 53% 66% 53% 68%

Finland 57% 73% 35% 48% 48% 63%

France 53% 72% 45% 68% 50% 70%

Germany 56% 72% 45% 71% 51% 72%

Greece 53% 70% 39% 52% 46% 61%

Ireland 50% 67% 27% 38% 40% 54%

Italy 54% 71% 44% 65% 49% 68%

Luxembourg 54% 70% 46% 66% 50% 68%

The Netherlands 55% 71% 44% 64% 51% 68%

Portugal 57% 75% 46% 64% 47% 65%

Spain 50% 66% 47% 65% 49% 65%

Sweden 59% 76% 44% 54% 52% 66%

United Kingdom 56% 72% 39% 64% 49% 69%

EU 54% 71% 45% 65% 50% 68%

Depending on MS and assumptions, the optimum recycling rate varies from 40% to

72%.

There is no uniform optimum recycling rate valid throughout EU. The optimum can

vary from MS to MS by as much as 31% (in absolute terms, i.e. from the minimum of

the minimum targets to the maximum of the maximum targets).

4.3.3 Determination of optimal recycling rate for each packaging material (at the

EU level)

The optimum recycling target for a material (e.g. plastics) in a specific Member State

is the weighted average of the optimum targets of the different applications (e.g. for

plastics: PET bottles, HDPE containers, LDPE industrial films, LDPE household

films and others) in this Member State.



96

In order to complete the previous data Table 31 summarised the range of recycling

rate per material for the European Union.

Table 31 : Recycling rate per material

Minimum recycling rate Maximum recycling rate

Plastic 28% 38%

Steel 60% 75%

Aluminium 25% 31%

Wood 47% 65%

Paper & board 60% 74%

Glass 53% 87%

Composites 0% 0%

4.3.4 Sensitivity analysis

Global recycling targets were calculated with the packaging mix forecast for 2000.

Insofar new targets will be applied in 2006, the influence of the packaging mix and

the evolution of the population density and the alternative MSW treatment on the

results are analysed.

The main constraint is the data availability. Forecasts for 2006 are not always

available and have to be used with caution.

The packaging mix modelled for 2006 is given in Annex 6: Packaging mix by

Member State.

Table 32 gives the global recycling rates that should be achieved considering the

packaging mix modelled for 2006.



97

Table 32 : Recycling targets per Member State in 2006

Min Max

Industrial Household Total Industrial Household Total

Austria 56% 41% 49% 74% 59% 66%

Belgium 54% 41% 47% 70% 62% 66%

Denmark 54% 49% 52% 70% 62% 67%

Finland 54% 39% 47% 72% 50% 62%

France 53% 46% 50% 72% 69% 70%

Germany 55% 42% 50% 72% 64% 68%

Greece 52% 38% 45% 70% 51% 60%

Ireland 49% 43% 47% 66% 60% 64%

Italy 54% 45% 50% 71% 66% 68%

Luxembourg 54% 47% 51% 70% 67% 68%

Netherlands 54% 42% 49% 71% 60% 66%

Portugal 52% 48% 49% 70% 67% 67%

Spain 51% 48% 49% 66% 66% 66%

Sweden 57% 42% 50% 74% 53% 65%

United Kingdom 55% 38% 48% 72% 61% 67%

EU10 54% 45% 50% 71% 64% 68%

Depending on MS and assumptions, the optimum recycling rate varies from 45 to

70%.




In general, the evolution of the packaging mix between 2001 and 2006 has only little

influence on the global recycling targets (mainly because the relative evolution is

rather limited).

10 Packaging mix modelled for the EU is the sum of packaging mix of all the Memberstates



98

However the influence of the packaging mix evolution on the "optimum" recycling

rates for household packaging is larger for Austria, Finland, Germany, Ireland and

The Netherlands.

Regarding the specific targets for Portugal, the influence of the packaging mix

evolution is also substantial but it is counterbalanced by the evolution of the

population density and alternative MSW treatment options so that the "optimum"

recycling rates show only a slight evolution.

The sensitivity of the material targets to the packaging mix was also examined (Table

33).

Table 33 : Sensitivity of the material recycling rates to the packaging mix

2000 2006

Min Max Min Max

Plastic 28% 38% 26% 36%

Steel 60% 75% 63% 76%

Aluminium 25% 31% 26% 31%

Wood 47% 65% 47% 66%

Paper & board 60% 74% 60% 74%

Glass 53% 87% 53% 87%

Composites 0% 0% 0% 0%

Considering the uncertainty on the assumptions, the evolution of the packaging mix

does not strongly influences the material recycling rates.



99

4.4 Reuse

The complete results concerning reuse are presented in Annex 12 : Presentation of

CBA results for reuse case studies.

4.4.1 Glass

The results concerning the internal, external and total social costs for glass are

summarised in Graph 21, Graph 22 and Graph 23 (next pages).

From an internal cost perspective, the glass returnable system is cheaper than the one-

way system as long as the distance from filler to distribution centre is smaller than :

• 125 km in the case 20 uses - 91% recycling rate




From an external cost perspective, the glass returnable system is better for the

environment than the one-way system as long as the distance from filler to

distribution centre is smaller than :





The total social cost for the glass returnable system is a better option than the one-way

system as long as the distance from filler to distribution centre is smaller than :






100

Graph 21 : Internal costs for glass

Internal costs - returnables versus single trip

0

100

200

300

400

500

600

700

800

50 100 150 200Distance to market (km)

Inte

rnal

co

st (

Eu

ro p

er 1

000l

pro

du

ct

pu

rch

ased

by

con

sum

er)

returnables (5 reuses)

returnables (20 reuses

single trip (42%recycling)

"single trip (91%recycling)


101

Graph 22 : External costs for glass

External costs - returnables versus single trip (assuming 100% return rate)

0

100

200

300

400

500

600

700

0 1000 2000 3000 4000 5000 6000

Distance to market (km)

Ext

ern

al c

ost

(E

uro

per

100

0l p

rod

uct

p

urc

has

ed b

y co

nsu

mer

) returnables (5 reuses)





102

Graph 23 : Total social costs for glass

Total social costs - returnables versus single trip (assuming 100% return rate)

700

800

900

1000

1100

1200

1300

1400

1500

150 200 250 300 350


To

tal s

oci

al c

ost

(E

uro

per

100

0l

pro

du

ct p

urc

hse

d b

y co

nsu

mer

)







103

From these results it can be drawn that :

♦ The reuse system is cheaper for relatively short transportation distances11 (under

100 to 150 km)

♦ The reuse system is always better from an environmental point of view

♦ From an total social cost perspective, the reuse system is preferable for short and

medium transportation distances12 (under 175 to 280 km).

4.4.2 PET

The results concerning the internal, external and total social costs for PET are

summarised in Graph 24, Graph 25 and Graph 26 (next pages).

From an internal cost perspective, the PET returnable system is always more

expensive than the single trip system. The difference is significant in the in the case

of 5 uses and less substantial for 20 uses.

From an external cost perspective, the PET returnable system is better for the

environment than the one-way system as long as the distance from filler to

distribution centre is smaller than :

• 50-130 km in the case 80% recycling rate

• 220-300 km in the case 20% recycling rate

From an total social cost perspective, the internal costs outweigh the external costs so

that logically, the conclusions are the same as for the internal costs : the PET single

trip system is always a better option than the returnable system. The difference is

significant in the in the case of 5 uses and less substantial for 20 uses.

11 from filler to distribution centre12 from filler to distribution centre


104

Graph 24 : Internal costs for PET

Internal costs - returnables versus single trip (assuming 100% return rate)

0

100

200

300

0 50 100 150 200


Inte

rnal

cos

t (Eu

ro p

er 1

000l

pro

duct

pu

rcha

sed

by c

onsu

mer

) returnables (5reuses)

returnables (20reuses




105

Graph 25 : External costs for PET

External costs - returnables versus single trip (assuming 100% return rate)

0

5

10

15

20

25

30

0 50 100 150 200 250 300


Ext

ern

al c

ost

(E

uro

per

100

0l p

rod

uct

p

urc

has

ed b

y co

nsu

mer






106

Graph 26 : Total social costs for PET

Total social costs - returnables versus single trip (assuming 100% return rate)

0

100

200

300

400

0 50 100 150 200


To

tal s

oci

al c

ost

(E

uro

per

100

0l p

rod

uct

p

urc

hse

d b

y co

nsu

mer





c



107

4.4.3 Glass and PET

The results concerning the internal, external and total social costs for both glass and

PET are summarised in Table 34and in Graph 27, Graph 28 and Graph 29 (next

pages). It is very important to note that as small content were considered for glass

packaging (330 ml) and large content (1.5 litre) for PET bottles, the comparison

between materials is biased.

Table 34 : Internal, external and total cost of beverage packaging systems

Distance from filler to

distribution centre

System

type

System Internal

Cost

External

Cost

Total Social

Cost

Glass 5U 249.15 90.30 339.45

PET 5U 234.80 9.95 244.76

Glass 20U 204.84 30.46 235.30refillable

PET 20U 106.05 7.42 113.47

Glass 42% 448.83 265.19 714.02

Glass 91% 410.81 224.71 635.52

PET 20% 79.63 15.72 95.35

0 km

single trip

PET 80% 88.46 10.90 99.36

Glass 5U 6225.15 269.68 6494.83

PET 5U 1175.34 109.38 1284.72

Glass 20U 6180.84 209.85 6390.69refillable

PET 20U 1046.58 106.84 1153.43

Glass 42% 3436.83 345.11 3781.94

Glass 91% 3398.81 304.64 3703.45

PET 20% 598.31 68.15 666.46

1800 km

single trip

PET 80% 607.14 63.32 670.46

A first conclusion from those results is that the internal costs outweigh the

environmental costs (external costs represent 10% or less of the total cost with the

exception of glass single trip – 60%).



108

Graph 27 : Internal costs for refillable and non refillable glass (33cl) and PET(1.5l) beverage packaging

Internal cost of beverage packaging systems

0

1 000

2 000

3 000

4 000

5 000

6 000

7 000

0 km 1800 km

Distance from fi l ler to distribution centre

cost

(E

UR

O/1

000

litre

s

Glass 5 uses

Glass 20 uses

PET 5 uses

PET 20 uses

Glass 42%

Glass 91%

PET 20%

PET 80%



109

Graph 28 : External costs for refillable and non refillable glass (33cl) and PET(1.5l) beverage packaging

External cost of beverage packaging systems

0

50

100

150

200

250

300

350

400

0 km 1800 km

Distance from filler to distribution centre

cost

(E

UR

O/1

000

litre

s

Glass 5 uses

Glass 20 uses

PET 5 uses

PET 20 uses

Glass 42%

Glass 91%

PET 20%

PET 80%



110

Graph 29 : Total social costs for refillable and non refillable glass (33cl) andPET (1.5l) beverage packaging

Total Social cost of beverage packaging systems

0

1 000

2 000

3 000

4 000

5 000

6 000

7 000

0 km 1800 km

Distance from fi l ler to distribution centre

cost

(E

UR

O/1

000

litre

s

Glass 5 uses

Glass 20 uses

PET 5 uses

PET 20 uses

Glass 42%

Glass 91%

PET 20%

PET 80%

From an internal cost perspective, the PET single trip system is clearly the cheapest

system. For short distances, the PET refillable system is also +/- competitive if the



111

number of uses is sufficient (20% more expensive for 20 uses, i.e. 0.02 EURO/litre)

but the difference is much more significant for the other refillable systems :

• glass 20 uses : 0.12 EURO/litre

• PET-5 uses : 0.15 EURO/litre;

• glass 5 uses : 0.16 EURO/litre;

For long distances, no system can compete with the PET single trip system

(difference of minimum 0.5 EURO/ litre for 1800 km13).

From an external cost perspective (environment) :

• for short distances, the PET returnable system is the best system, although the

PET single trip system’s score is quite similar. The glass returnable system

creates impacts that are 3 to 4 times higher (20 uses) or about 10 times higher

(5 uses). The impacts of the single trip glass are tremendous, even for high

recycling rates (about 25 times the impacts of PET systems).

• for long distances, the PET single trip system becomes the best system,

although the PET returnable system’s score remains quite similar. The glass

returnable and single trip systems create much more impacts.

The total social cost figures are similar to the internal cost figures.

• for short distances, the PET single trip and returnable 20 uses are the best

options. The returnable systems PET-5 uses and glass-20 uses are about 2 to

2.5 times higher and the glass-5 uses about 3 to 3.5 times. The single trip

glass is 6 to 7 times higher.

• For long distances, no system can compete with the PET single trip system

(difference of minimum 0.5 EURO/ litre for 1800 km14).

13 reminder : distance are given for the one-way trip14 reminder : distance are given for the one-way trip



112

5 CONCLUSIONS AND RECOMMENDATIONS

Reservations using those results

When using the results to inform the revision of the recycling targets in the context of

the Directive, the EC should take into account that :

ü CBA is not yet a mature instrument, specially concerning the economic valuation

of the environmental impacts which must therefore be considered carefully.

ü Materials that, according to this study, should attain a high recycling rate could be

financially penalised compared to other materials. Changes to packaging material

market shares that may be induced unintentionally by material specific targets

could have an adverse environmental impact if the entire packaging production

chain is considered. Material specific targets, if any, should thus take into account

the full production chain of the packaging, in order to avoid the risk to favour less

environmentally friendly materials.

ü Some results achieved and conclusions drawn (PET, paper&board15) are based

upon recent and current market prices for the recycled materials. These materials

can be subject to significant price fluctuations, which would change the results of

the cost benefit analysis.

ü The results achieved should not be interpreted and applied too simplistically.

Whilst every effort has been made to take into account variable factors that affect

the costs and benefits of recycling, it should be recognised that other local factors

not considered may also affect the results (e.g. availability of local output market

for the recycled materials). Nationally or locally, higher or lower recycling rates

than the ones suggested by the results may be acceptable.

For other reservations about the results please refer to chapter 1 Constraints on page 8

and chapter 2.3 General methodological approach – Life cycle cost benefit

analysis"Limitations to CBA".

Conclusion 1 Achieved recycling rates are satisfactory

Most Member States already achieved the recycling rates set in the Packaging

Directive in 1998. It seems that all member States will reach and often significantly



113

exceed the 25-45% overall recycling target by 2001, with the authorised exception of

the 3 Member States that had to fulfill less stringent requirements (i.e. Greece, Ireland

and Portugal). The 15% minimum target for each material will be reached in all

concerned Member States, with the exception of plastics for which the target will not

be reached in several Member States.

Conclusion 2 Generally speaking selective collection is better for the society

Generally speaking the selective collection of both household and industrial

packaging is better for the society than its treatment together with unsorted waste.

But there are some remarkable exceptions (see further conclusions).

Conclusion 3 Household packaging: separate kerbside collection is often

preferable

For household packaging very often the separate kerbside collection is preferable (and

might thus be considered as the "optimum system" among the modelled systems) due

to the higher collection rate. Notable exceptions are :

• Glass should be collected from bottle banks (minimum density : 1 bottle bank

per 1000 inhabitants)

• The metals

Ø should not be collected selectively in areas where the MSW is incinerated

with metals recovery and

Ø may also be collected selectively by a bring system in areas with a low

population density

• There is no evidence to support a mandatory target for the selective collection

of LBC, composites and mixed plastics

• Plastic bottles should be collected selectively by a bring system in areas where

both conditions are fulfilled at the same time :

Ø a low population density and

Ø the MSW is incinerated with efficient energy recovery

15 The other ones are based on average value over the last 3 years and are thus morestable



114

This is summarised in the following table (Table 26 on page 90 and Table 27 on page

91)



PET bottles Kerbside Bring Kerbside Kerbside

Steel packaging Bring +kerbside

No SC Kerbside No SC

Al cans Bring +kerbside


Rigid & semi-rigid Alpackaging excludingcans

Bring +kerbside


Paper and boardpackaging

Kerbside Kerbside Kerbside Kerbside

LBC No SC No SC No SC No SC

Mix plastic packaging No SC No SC No SC No SCNo SC = no selective collection

The following recycling rates are the ones achievable with the those systems (Table

28 on page 91).

Low population density High populationdensity


PET bottles 70-80% 35-45% 59-69% 59-69%

Steel packaging 15-60% 80% 40-60% 80%

Al cans 31-55% 76% 45-55% 76%

Rigid & semi-rigid Al packagingexcluding cans

3-17% 50% 3-8% 50%

Paper and board packaging 61-71% 61-71% 55-65% 55-65%

LBC 0% 0% 0% 0%

Mix plastic packaging 0% 0% 0% 0%

The results were calculated for mechanical recycling. Based on the sensitivity

analysis, there are some indications that some alternative routes could be considered

as about equivalent to the mechanical recycling : Supercycle, TBI. However these

routes have not been investigated deeply so that these conclusions have to be

considered very cautiously.



115

Conclusion 4 Industrial packaging : separate collection is preferable

For industrial packaging the separate collection for recycling is preferable. Notable

exceptions are :

• packaging that contained hazardous waste should be collected separately

because hazardous waste but should not be recycled

• Companies which produce a very small amount of cardboard waste (< 5.5 t

per year) may put the cardboard waste together with the unsorted waste due to

the relatively high additional internal cost.

Conclusion 5 Revised recycling targets

The recycling rates achievable with the "optimum systems" are summarised in the

following tables. They are given :

• per Member State and for the EU as a whole



116

Global Target Industrialwaste

Global Target Householdwaste

Global target (Industrial +Household waste)

Min Max Min Max Min Max

Austria 56% 74% 42% 60% 49% 67%

Belgium 54% 70% 42% 65% 48% 67%

Denmark 54% 70% 53% 66% 53% 68%

Finland 57% 73% 35% 48% 48% 63%

France 53% 72% 45% 68% 50% 70%

Germany 56% 72% 45% 71% 51% 72%

Greece 53% 70% 39% 52% 46% 61%

Ireland 50% 67% 27% 38% 40% 54%

Italy 54% 71% 44% 65% 49% 68%

Luxembourg 54% 70% 46% 66% 50% 68%

The Netherlands 55% 71% 44% 64% 51% 68%

Portugal 57% 75% 46% 64% 47% 65%

Spain 50% 66% 47% 65% 49% 65%

Sweden 59% 76% 44% 54% 52% 66%

United Kingdom 56% 72% 39% 64% 49% 69%

EU 54% 71% 45% 65% 50% 68%

Depending on MS and assumptions, the optimum recycling rate varies from 40% to

72%.




• per packaging material and for all materials together

Minimum recycling rate Maximum recycling rate

Plastic 28% 38%

Steel 60% 75%

Aluminium 25% 31%

Wood 47% 65%

Paper & board 60% 74%

Glass 53% 87%

Composites 0% 0%



117

Conclusion 6 Reuse should not be encouraged for beverage packaging

The PET single trip and PET returnable-20 uses are the best options for the beverage

packaging (only glass and PET systems were considered). The glass systems have

each a serious inconvenience :

• the impacts of the glass production (even at high recycling rates) for single trip

glass;

• the impacts of the additional transport for returnable glass.

However, as a small content were considered for glass packaging (330 ml) and a large

content (1.5 litre) for PET bottles, the comparison between materials is biased.

Thus, based on the results and with the reservations already expressed :

• non refillable glass is clearly the less favourable option for beverage

packaging 16;

• refillable systems for beverage packaging are not preferable to the PET single

trip system.

Those conclusions do not take into account some possible technical constraints. In

some cases those technical constraints could make it undesirable to favour the

systems that appear as the preferable ones considering only the environmental and

economic aspects. Exemples : single trip glass may be acceptable for whiskey for

conservation quality and it might be difficult to use PET bottles up to 20 times.

16 the relative difference is so huge for both the internal and external costs that theconclusion remains valid even if the content of the glass and PET bottles are different



118

6 GLOSSARY

CBA : Cost – Benefit Analysis

EBS :

EC : European Commission

ER : Energy Recovery

Grey bag Municipal solid waste

LBC : Liquid beverage cartons

MPM : Multiple Pathway Method

MS : Member State

MSW : Municipal Solid Waste

PMC : Plastic bottles, Metals and LBC ("Cartons")

WF : Weight Factor

PWP : packaging waste producers



119

7 BIBLIOGRAPHY

[1] “Interim report according to Art. 6.3 (a) of Directive 94/62/EC on packaging

and packaging waste”; Report from the Commission to the Council and the

European Parliament; COM (99) 596 final, 19.11.99

[2] Review of 1997 data on packaging and packaging waste recycling and

recovery; PWC, commissioned by ERRA; oct-99

[3] The facts: A European cost/benefit perspective; PWC, commissioned by

ERRA; nov-98

[4] Official reported data (1997 & 1998) from the Member States to the European

Commission

[5] Packaging Recovery Organisations (Compliance Scheme) : annual reports and

information on internet sites(DSD, ARA, Sociedade Ponto Verde, Valorlux,

Fost Plus, Val-I-Pak)

[6] Material federations (national and European): APEAL, APME

[7] Market data from Pira Int.

v European Markets for flexible Packaging

v European Market for corrugated board packaging

v Packaging in Germany

v European market for non-alcoholic beverage packaging

v Estimated and forecast of total packaging consumption 2000-2005

v European market for rigid plastics packaging

[8] Annual report; packaging committee; Ministry Housing, planning and

environment NL, 1999

[9] Interview of Mrs Noguer, Eco-Emballages; 20.03.2000

[10] Response to the proposed changes to the directive and progress with

implementation in Germany; Dr. Thomas Rummler; 7th Annual European

Packaging Law Conference; 22-23/03/2000; Swissôtel, Brussels

[11] The Producer Responsibility Regulations (Packaging waste) Regulations

1997: A forward look for planning purposes, UK Department of the

Environment, Transport and the Regions

[12] Glass making and recycling, Warmer Bulletin, May 1996, N°49, p. 12-13



120

[13] Glass re-use and recycling, World Resource Foundation, Information sheet,

May 1996, N°49

[14] Potential for post-user plastic waste recycling, Sofres-TNO, commissioned by

APME, March 1998

[15] Plastic, Paper, glass recycling, Bureau of International recycling

[16] Interview of Mr. Sneyers and Mr. Huysman (VAL-I-PAC), VAL-I-PAC, 02

April 2000

[17] Paper making and recycling, World Resource Foundation, Information sheet,

Nov. 1994

[18] Interview of CEPI, CEPI, 26 April 2000

[19] Compound packaging (1999), Pack News, vol. 17, no. 115, Feb. 1999, pp 22,

24

[20] Beverage cartons – composites, http://www.ace.be/fr_about_ace.htm,

http://www.drinks cartons.com/

[21] Case study (1998), Storage Handl. Distrib., vol. 42, no. 6, June 1998, pp 24,

26, 28, 30

[22] Interview of ASSURE, ASSURE, 22-06-00

[23] Interview of FOST Plus, FOST Plus, 28-06-00

[24] Plastics: an analysis of plastics consumption and recovery in Western Europe,

APME, Spring 2000

[25] European Packaging: Trends and Strategic Forecasts to 2005, Michael

Howkins and Sara Hulse, Pira International, 2000

[26] European Markets for Flexible Packaging, 2nd Edition, Paul Gaster, Pira

International, 1999

[27] European Market for Rigid Plastics Packaging, Paul Gaster, Pira International

1998

[28] Metals Packaging in Europe, Nnamdi Anyadike, Pira International, 1999

[29] European Market for Corrugated Packaging, Brian Navin, Pira International,

1998

[30] E-mail Maaike Jole, Petcore, August 2000

[31] Fax from Michael Sturges, Pira Int., March 2000



121

[32] Ecoembes (SP), Ecovidrio (SP), Plastval (PO), Sociedade Ponto Verde (PO),

Fost Plus (B), Eco-Emballages (F), ADEME (F), Valorlux (Lu), SVM-Pact

(Nl), ARA (AUT), PYR (SF), DSD (D)

[33] The National Waste Plan Until 2005, Ministry of Environment (1998), Finland

[34] DEPA – Miljostyrelsen, Denmark

[35] National Waste database report 1998, Environmental Protection Agency,

Ireland

[36] Increasing recovery and recycling of packaging waste in the UK - The

Challenge Ahead: A forward Look for Planning Purposes, DETR, UK

[37] Secondo rapporto sui rifiuti urbani e sugli imballagi e rifiuti di imballagio,

Agenzia Nazonale per la protezione dell'ambiante, February 1999

[38] Italy - Summary of management and prevention plan of Conai, European

packaging and waste law, N° 79, July 2000, pp. 32-34

[39] Municipal Solid Waste Incineration in Europe, Juniper, 1995

[40] Gestion des déchets d’emballages en Europe, Eco-emballages, 1999

[41] Interviews of stakeholders in 2000

[42] Network of consultants

[43] Valuation of waste-related externalities, Pieter van Beukering, April 2000

[44] Glass Gazette N° 25, FEVE, October 1999

[45] Glass recycling in European Countries – 1999, data provided by FEVE,

November 2000

[46] Determination and characterisation of optimised collection systems, Beture

Environnement, 2000

[47] Meeting with FOST Plus, November 10 & 13, 2000

[48] Meeting with Eco-Emballages (00-06-09) and e-mail from Ms Noguer (00-10-

17)

[49] Corinair, Inventaire des émissions de SO2, Nox, et COV dans la Communauté

Européenne, 1995

[50] Interview Mr Meneguzzi, ANDRIN, November 2000

[51] Interview Mr Dhaene, Valomac, November 2000

[52] Ökobilanzdaten für Weissblech und ECCS, Informationszentrum Weissblech,

Oktober 1995

[53] Visit and interview of several sorting plants, RDC-Environment, 2000



122

[54] Environmental Profile Report for the European Aluminium Industry EAA

April 2000

[55] Recycling and recovery of plastics from packagings in household waste –

LCA-type Analysis of different strategies, Fraunhofer-Institut, Freising,

December 1997

[56] Interview of Ace and Tetra Pak, 2000

[57] Interview of Dr. Ing. Janz, Stahlwerke Bremen, November 2000

[58] Recycling & Recovery (1) A1 2.2.2.3 (citation from Pira)

[59] Life cycle inventories for packagings, vol. 1 & 2, Buwal, 1998

[60] Reference Document on Best Available Techniques in the Glass

Manufacturing Industry, July 2000

[61] Interview of Colruyt

[62] Richtlijn Verpakking – Glas, HigH5, 2000

[63] DSD technical information

[64] Interview of Mr. Servol, TBI, November 2000

[65] Analyse de cycle de vie du recyclage chimique du PET en polyolspolyesters

selon le procédé TBI, BIO-Intellingence Service, December 1999

(Confidential)

[66] Interview of Pro-Europe Members, October 2000 – January 2001

[67] Interview of CEPI, 26/04/2000

[68] Interviews of ACE, August – December 2000

[69] Specific processing costs of waste materials in a municipal solid waste

combustion facility, TNO, TNO-MEP-R 96/248, 07/11/1996

[70] Interview consultant of constructors of incineration plant

[71] Tenders for incineration plants in Belgium



123

ANNEXES

Annex 1: Process trees and system descriptions

Annex 2: Incineration and landfill models

Annex 3: Internal cost data

Annex 4: Economic valuations applied – sources and derivation

Annex 5: Employment data –jobs for waste management activities

Annex 6: Packaging mix by Member State

Annex 7: Environmental data sources

Annex 8: Current performance of Member States

Annex 9: Critical factors limiting recycling and reuse

Annex 10 : Presentation of CBA results for recycling case studies

Annex 11 : Calculation of recycling rates per Member States

Annex 12 : Presentation of CBA results for reuse case studies

"Evaluation of costs and benefits for the achievement of reuse and recycling targets for the different packaging materials in the frameof the packaging and packaging waste directive 94/62/EC" –draft final report, RDC-Environment & Pira International

May 01

1

Annex 1: Process trees and system descriptions


May 01

2

1 GENERAL SYSTEM PARAMETERS

1.1 Optimised recycling chains

In this paragraph, optimised recycling chains are described for the different scenarios for which a

CBA is performed. Final system flow diagrams are given in chapter 2 of this annex.

1.2 Industrial packaging approach

For the 2 industrial case studies, i.e. LDPE plastic films and cardboard, we calculated the minimum

packaging waste production under which the selective collection is not beneficial.

The external benefits (EB) of collecting and recycling industrial packaging waste has been

calculated as 11.7 EURO/t (corrugated board) and 208 EURO/t (PE film).

Collecting and transporting corrugated board and PE films as mixed waste is often cheaper than

collecting and transporting source sorted packaging. There is thus an additional collection cost

(ACC) to collect selectively.

The annual production of industrial packaging waste for which the ACC = EB is

Ø 5.5 t/year for cardboard

Ø 0.01 t/year for LDPE plastic films.

Above this waste production the environmental benefits outweigh the additional internal cost for the

selective collection.

This means that, from a cost-benefit viewpoint, the companies who produce more waste than

0.01 t of plastic film or 5.5 t of corrugated board per year should have a selective collection

scheme to recycle it. As the "break-even" amount is very low for PE films, it can be concluded that

selective collection of industrial packaging should be systematic throughout the EU. As there are

limits to the modelling, it has been assumed for this study that 95% of the industrial sites

(percentage in packaging weight) should make the selective collection of packaging.

1.3 Kerbside collection

For PMC, it is assumed that the material is placed by the householder in a PMC selective collection

bag.


May 01

3

The selective collection bag may contain "light packaging" : plastic bottles, metals and LBC. It is

collected twice a month in high and low population density areas.

Collection vehicle is a truck with a volume of 16m_. The collected material is transported directly

to the sorting facility. Distance to sorting plant is about :

Truck Vehicle type High population density Low population density

Paper & board 17-25t truck 8 – 71,1 km/t 86,1 – 176,1 km/t

light packaging 17-25t truck 21,1 – 107,7 km/t 74,4 – 227,8 km/t

Employment and internal costs were determined based on Beture Environnement and FOST Plus

data. Air emissions from trucks are based on Corinair. Transport distances were provided by Eco-

emballages.

The paper and board selective collection happens once a month in high and low population density

areas. Packaging and magazines are collected together without any condition on the conditioning

(packaging).

Collection vehicle is a truck with a volume of 16m_.

Sources:[46], [48], [49], [66]

Note : The cost for selective collection is assumed to be independent from the amount of material to

be collected separately because the collection frequency is adapted to the amount of waste.

However, this is not true anymore for very low amounts (and frequencies) because there is a

minimum frequency under which the system is not efficient anymore.

1.4 Bring scheme

Consumers bring their sorted1 packaging waste and other waste to the bring scheme. Assumptions

on the distance which has to be attributed to “packaging collection” has be given by Eco-

Emballages..

In the bring scheme, packaging are collected in container of about 30m_. These containers are

transported to the sorting plant or the recycling facility about once a week for light packaging and

for paper & board packaging in high and low population density areas. The collected material is

taken directly to the sorting facility. Distance to sorting plant is about :

1 packaging waste are sorted in 2 fractions: light packaging on the first hand and paper & board +magazines on the other hand.


May 01

4

Truck High population density Low population density

Paper & board 3,8 – 10,5 km/t 11,1 – 20,2 km/t

Light packaging 18 – 37,2 km/t 42,2 – 123,9 km/t

Sources:[46], [48], [66]

1.5 Sorting

Only limited data for the environmental impacts at a sorting plant was sourced. Data for energy

consumption at the sorting plant (electricity to power conveyors and space heating) has been

collected. For residual material arising at the sorting plant, the following assumption has been

made:

• Waste arising at sorting plant from materials collected by separate kerbside collection – 20%

• Waste arising at sorting plant from materials collected by bring bank – 10%

The sorted material is baled. Energy consumption for baling has been included in the model.

Bag opening

The selective collection bags are torn open by a mechanical ripping unit. The contents are then

transported by conveyor belt to a drum sieve which separates out large-volume items and foils and

films.

Foil and film and bags residues separation (not systematically)

The foils, films and bags pieces are then passed on to a so-called air separator, which automatically

separates them from any impurities (items wrongly disposed of in the selective collection bag),

before being pressed into bales.

Tinplate extraction

The recyclable materials, now minus the impurities, foils and films (if any), are then transported by

conveyor belt to the magnet separator. A magnet extracts iron-containing metal packaging such as

tinplate cans, crown caps and jar lids from the recycling stream.

Aluminium separation

Downstream of the magnet, an eddy current separator separates out the aluminium and composites

containing aluminium.

Separation of beverage cartons (not taken into account in this study)

More and more sorting plants are using machines for the automatic identification and segregation of

beverage cartons. These are passed in front of a near-infrared light, recognised by a computer and


May 01

5

blown aside with compressed air. If this type of unit is positioned upstream of the eddy current

separator, it can also separate out composites containing aluminium at the same time.

Plastics sorting

To sort the materials completely, plastic bottles have to be sorted by hand according to their

characteristics:

- clear PET bottles,

- light blue PET bottles

- coloured PET bottles,

- HDPE bottles.

Note : There also exist different physical and opto-electronic based sorting machine for plastics

such as the sink-float process or hydrocyclone process.

Sources :[47], [53], [63], [66]

Sorted / baled materials are transported to the reprocessor for recycling. The specific transport

distances considered are summarised in the table below.

Transport from sorting plant to recycling facility

Stream Average loadmin max t

PET bottles 19,2 26,9 13HDPE bottles 17,7 52,0 13Glass bottles 2,0 9,6 20Al 15,0 91,7 6Steel 0,4 24,0 14-22Paper and cardboard 2,0 6,3 24Liquid beverage cartons 14,6 60,0 24

Transport distance (range in km/t)

Sources :[47], [48], [66]

1.6 Case study : Commercial and Industrial LDPE palletisation film

In case of non selective collection, packaging waste are landfilled or incinerated. Both options are

investigated.

This analysis is concerned with post-use commercial and industrial film, defined as “films for

palletisation”. This source of materials is fairly clean, at approximately 95-98% plastic. The results

of this case study only apply where there is a high degree of source separation (homogeneity of

material) and the material is clean. For example, where the source is clean shrink and stretch wrap


May 01

6

used to transport bottles from production to filling – this film is homogenous, and has come from a

food environment and should therefore be clean. Backdoor waste from supermarkets is also a major

source of film for recycling, though cross-contamination of materials / plastics may occur at

supermarkets due to the diversity of packs being handled.

Other materials that may be collected will be less clean, for example agricultural films which may

be only 60% plastic, the remainder being contamination (stones, soil, etc). This contamination must

be removed by washing otherwise damage to the blades during recycling can occur. The results of

this case study do not apply to such materials.

For material recycling, it is assumed that the source separated material is collected and transported

directly to the reprocessor.

Material losses through washing and sorting at the reprocessing are 27%. During reprocessing, the

recyclate must be mixed with a degree of virgin material. In this analysis, it is assumed that the

film produced is made up of 86% recycled LDPE and 14% virgin LLDPE material.

The recycled film is assumed to offset production of virgin LDPE film for white and other light

coloured sacks, with a save ratio of 80%.

1.7 Case study : Commercial and industrial corrugated board

In case of non selective collection, packaging waste are landfilled or incinerated. Both options are

investigated.

For material recycling, it is assumed that the collected corrugated board will be recycled into new

corrugated board materials. In order to credit the system for increased recycling, the burdens for the

production of testliner (a component of corrugated board which has a 100% recycled content) have

been compared to the burdens for the production of kraftliner (a component of corrugated board

with a recycled content of less than 20%). The difference between the high recycled content

testliner and low recycled content kraftliner is the assumed environmental credit.

The displacement ratio is assumed to be 80%. The actual displacement ratio could be within the

range 60 and 100% depending on the end use application and the quality of waste input (this is


May 01

7

investigated in the sensitivity analysis). The quality of the collected material and its usability in the

selected application is likely to reduce as the overall recycling rate increases.

It is important to note that the recycling loop for paper and board is extremely complex. Fibres

degrade, and cannot be used for the same application indefinitely. Each application requires

specific properties, and therefore specific mixes of fibres from different sources. Increasing the

recycled content of corrugated board may reduce the properties of the board.

Therefore, the situation modelled in this analysis is a theoretical situation, which illustrates the

range of costs and benefits that may be incurred where corrugated cases are recycled.

1.8 Case study : PET bottles

PET bottles can be

- collected with MSW and then landfilled or incinerated with energy recovery, according to

the scenario

- selectively collected with aluminium, steel and LBC by kerbside collection

- selectively collected with aluminium, steel and LBC within a bring scheme

In case of selective collection, plastic bottles are transported to the sorting plant where they are

manually sorted according to their characteristics (colour and polymer), crushed and baled.

Bales are transported to the recycling facility.

In the mechanical recycling facility, PET bottles are unbaled and PVC is separated. Then PET is

ground, washed and dried. Mechanical recycling into granulate for use in bottle production has been

considered in this study. The recycled material produced has been credited against the production

of virgin PET. The displacement save ratio assumed is 100%. For PET bottles, other reprocessing

routes are also available (for example fibre production or TBI process). These routes have not been

considered in detail in this analysis.

Interpretation and application of the results should take into account the following limitations:

§ The sorted/baled material sent to the reprocessor must meet required bale specifications in order

to be recycled by this technology. Therefore, results only apply to clear PET bottles and baled

materials that meet the required specifications.


May 01

8

§ Internal and external costs for other reprocessing routes will be different from those considered

in the analysis

The sensitivity analysis considers feedstock process as recycling alternative.

Sources :[55], [57], [63], [64], [65]

1.9 Case study : Mixed plastics from household sources

Four waste management options are considered for mixed plastics from household sources:

• Landfill

• Incineration with energy recovery

• Mechanical recycling (press forming) via separate kerbside collection

• Recovery in a blast furnace via separate kerbside collection.

In case of selective collection, mix plastic packaging waste are transported to the sorting plant

where they are sorted, crushed and baled.

Bales are transported to the mechanical recycling facility or to the agglomeration plant (in case of

use in cement kilns or in blast furnace), according to the scenario.

In the mechanical recycling facility, mix plastic packaging are unbaled. After a dry process, plastic

is extruded in order to be used as palisade. The recovered material from mechanical recycling is

used for plastic palisade, and is assumed to offset production of wood. A displacement save ratio of

100% is assumed, although in reality this is highly variable (it is therefore investigated in the

sensitivity analysis). The recycling consists of a number of steps. Firstly, there is a dry treatment

stage. The output of this process is ground plastics. Losses at this stage are 20%. The ground

plastics are then press extruded into a product (in this case, palisade).

In the agglomeration plant the plastics mixture is processed in order to meet defined quality

criteria as regards bulk density, grain size, chlorine and dust content and residual moisture.

In technical terms, agglomeration consists of a sequence of shredding and separating processes,

followed by compacting of the plastic material. During the pelletisation process the shredded waste

plastic is compacted by means of pressure. The material is forced through the drilled holes of a

pelletiser and cut off with cutters : the process delivers agglomerate.

The so-called agglomerate is then transported or not to blast furnace or cement kiln where it is used

as a partial substitute for heavy oil (reduction process in blast furnace) or as secondary fuel (cement

kiln).


May 01

9

For recovery via the blast furnace, the system is credited against fuel oil (low sulphur). It is

assumed that 1 tonne of agglomerate entering the blast furnace offset 964kg of fuel oil. The blast

furnace recovery route consists of a number of steps. Firstly, agglomerate is produced. Losses at

this stage are 24%. The agglomerate is then injected into the blast furnace, where it is assumed to

offset fuel oil.

Interpretation of the results of the cost benefit analysis should consider the following:

§ Other recovery routes are also available (for example, recovery in a cement kiln). These options

have not been considered in this analysis. The internal and external costs for these options will

be different.

Sources :[55], [57], [63]

Note : the bring system has not been analysed because there is no data available for such a system.

1.10 Case study : household steel applications

Five waste management options are considered for steel packaging arising from households

• Landfill


• Incineration with energy recovery and extraction of steel from slags

• Material recycling via separate kerbside collection, selectively collected with aluminium,

plastic bottles and LBC

• Material recycling via bring scheme, selectively collected with aluminium, plastic bottles and

LBC.

In case of selective collection, steel packaging are transported to the sorting plant where they are

automatically sorted with magnetic separator and baled.

Bales are transported to the recycling facilities (blast furnace) where they are melt (after shredding

or not).

Two production routes are assumed for production of packing steel. These are the oxygen furnace

using principally iron ore as the raw material and the electric arc furnace using scrap steel.

Increased recycling increases electric arc steel production whilst reducing blast furnace production,

thereby yielding an environmental credit.


May 01

10

For incineration with extraction of slags it is assumed that 80% of the steel entering the incinerator

is recovered and sent for recycling.

A save ratio of 100% is considered for the recycled steel.

1.11 Case study : Aluminium beverage packaging

Household aluminium packaging waste can be

- collected with MSW and then landfilled or incinerated with aluminium recovery, according

to the scenario

- selectively collected with steel, plastic bottles and LBC by kerbside collection

- selectively collected with steel, plastic bottles and LBC within a bring scheme

Five waste management options are considered for aluminium beverage packaging arising from

households

• Landfill


• Incineration with energy recovery and extraction of aluminium from slags

• Material recycling via separate kerbside collection, selectively collected with steel, plastic

bottles and LBC

• Material recycling via bring scheme, selectively collected with steel, plastic bottles and LBC.

For incineration with extraction of aluminium from slags, it is assumed that 76% of the

aluminium beverage packaging entering the incinerator is recovered and sent for recycling.

In case of selective collection, aluminium packaging are transported to the sorting plant where they

are automatically sorted with Eddy current separator and baled.

Baled aluminium beverage cans from the sorting plant go through a scrap preparation stage. Losses

at the scrap preparation stage are 19%. The material is then melted and alloyed. The recycled

aluminium ingots are assumed to offset production of virgin aluminium ingots. A save ratio of

100% is assumed.


May 01

11

1.12 Case study : Other rigid and semi-rigid aluminium packaging

Five waste management options are considered for other rigid and semi-rigid aluminium packaging

arising from households:

• Landfill


• Incineration with energy recovery and extraction of aluminium from slags

• Material recycling via separate kerbside collection, selectively collected with steel, plastic

bottles and LBC

• Material recycling via bring scheme, selectively collected with steel, plastic bottles and LBC.

For incineration with extraction of aluminium from slags, it is assumed that 50% of the rigid and

semi-rigid aluminium packaging except beverage cans entering the incinerator is recovered and sent

for recycling.

Baled aluminium from the sorting plant go through a scrap preparation stage. Losses at the scrap

preparation stage are 19%. The material is then melted and alloyed. The recycled aluminium

ingots are assumed to offset production of virgin aluminium ingots. A save ratio of 100% is

assumed.

1.13 Case study : household paper & board

Household Paper & Board packaging waste can be

- collected with MSW and then landfilled or incinerated with energy recovery, according to

the scenario

- selectively collected with magazines by kerbside collection

- selectively collected with magazines within a bring scheme

Paper & board selectively collected are first purified and manually sorted into various qualities.

They are then baled and transported to the pulp and paper plant.

At the pulp & paper plant, paper and board waste are pulped (after shredding or not). After

screening or centrifugal cleaning the pulp is purified and is ridded of all undesirable elements.

Fibbers are dried on a conveyer belt (Filtration - water is extracted and fibres remain).

Fibres are recovered and the rejects are incinerated or landfilled.


May 01

12

For material recycling, limited life cycle inventory data or internal cost data for recycling processes

specific to household paper and cardboard packaging was available to the consultants.

Therefore the following limitations to the model should be recognised:

• It is assumed that the recovered fibre is reprocessed into testliner, and that the testliner

offsets the production of kraftliner (a save ratio of 80% has been assumed). This is a considerable

limitation of the model. The assumption has been made to facilitate a comparison of the burdens

associated with the production of a high recycled content substrate with the production of a low

recycled content substrate. In reality, recovered fibre from household paper and board packaging

will be mixed with virgin fibre and recovered fibre from other sources. The final application of the

substrate determines the properties required and therefore dictates the necessary pulp furnish. This

therefore also dictates the achievable recycling rate in the paper and board sector as a whole.

Increasing the recycling rate of paper and board packaging from household sources may not

increase the recycling rate of fibre overall. Increased recycling of paper and board packaging from

household sources may reduce recycling from other sectors such as newsprint. This has not been

addressed in this study, and should be recognised as a further limitation of the model.

Therefore, the situation modelled in this analysis is a theoretical situation, which illustrates the

range of costs and benefits that may be incurred where paper and cardboard packaging from

household sources are recycled.

Sources:[66], [67]

1.14 Case study : liquid beverage cartons

Six waste management options are considered for liquid beverage cartons:

• Landfill


• Material recycling of the fibre via separate kerbside collection (rejected aluminium and PE to

landfill)

• Material recycling of the fibre via separate kerbside collection (rejected aluminium and PE to

incineration)

• Material recycling of fibre via bring scheme (rejected aluminium and PE to landfill)


May 01

13

• Material recycling of fibre via bring scheme (rejected aluminium and PE to incineration)

It is assumed that LBC is selectively collected with aluminium, plastic bottles and steel packaging.

In case of selective collection, LBC are transported to the sorting plant where they are automatically

sorted with Eddy current separator, crushed and baled. Other sorting techniques are described in

paragraph “Sorting ”, but are not included in the CBA.

Bales are transported to the recycling facilities (pulp & paper plant) where they are pulped (after

shredding or not). After screening or centrifugal cleaning pulp is purified and is ridded of all

undesirable elements. Fibbers are dried on a conveyer belt (Filtration - water is extracted and fibres

remain).

As with the household paper and cardboard packaging model, it is assumed that the recovered fibre

is reprocessed into testliner, and that the testliner offsets the production of kraftliner (with a save

ratio of 80% assumed). The same limitations therefore apply as in the household paper and card

model.

The Al/PE fraction can be energetically valorised in cement kilns/incinerators or used in pyrolysis.

Both landfill and incineration routes are analysed in this study.

Source :[66], [68]

1.15 Case study Glass bottles

Three waste management options are considered for household glass beverage packaging:

• Landfill


• Material recycling via a bring scheme

The LCI data available to the consultants is lacking in transparency. The data aggregates the

reprocessing steps and environmental credit, but no description of the assumptions made and

conditions under which the data is applicable are provided. No indication of the type of cullet being

recycled is given.

Therefore, the results of this case study should be considered only as indicative to the possible costs

and benefits that may be incurred when glass bottles from household sources are recycled.

"Evaluation of costs and benefits for the achievement of reuse and recycling targets for the different packaging materials in theframe of the packaging and packaging waste directive 94/62/EC" –draft final report, RDC-Environment & Pira International

May 01

2 CASE STUDY PROCESS TREES

See annex 1 bis

MIXEDPLASTICS

SYSTEM BOUNDARY

COLLECTIONFOR

LANDFILL LANDFILL

MIXED PLASTICS FROM HOUSEHOLD

AGGLOMERATEPRODUCTION

BLASTFURNACE

Creditagainstfuel oil

COLLECTIONFOR

INCINERATION

MSW INCINERATION

ElectricityProduction

(av Europeanundelivered)

TRANSPORT TOREPROCESSOR

PRESSMOULDING

KERBSIDECOLLECTION

FOR RECOVERY

PLASTICPALISADE(CREDITAGAINSTWOOD)

SORTING +BALING

SORTING +BALING

MIXED PAPERPACKAGING

LANDFILL

SYSTEM BOUNDARY

MSW INCINERATION



PAPER AND BOARD ARISINGFROM HOUSEHOLDS

TRANSPORT TOBRING BANK

TESTLINERPRODUCTION

(Screening,Pulping,

Papermaking)

SORTINGTRANSPORT

TORECYCLERS

COLLECTIONFOR

LANDFILL

COLLECTIONFOR

INCINERATION

KERBSIDECOLLECTION

FORIRECYCLING

COLLECTIONFROM BRING

BANK

EnergyElectricity

(av Europeanundelivered from

landfill gas collection)

TESTLINER(CREDITAGAINST

KRAFTLINER)

STEELPACKAGING

SYSTEM BOUNDARY

LANDFILL

MSW INCINERATION

STEEL PRODUCTION(ELECTRIC ARC OROXYGEN FURNACE

CREDITAGAINST VIRGIN

PRODUCTION

STEEL PACKAGING FROM HOUSEHOLD

METALS RECOVERYFROM INCINERATION


COLLECTIONFOR

INCINERATION

COLLECTIONFOR

LANDFILL


(STEEL MILL)

SORTING +BALING

KERBSIDECOLLECTION

FORRECYCLING


BANK

TRANSPORTTO BRING

BANK

WASTEBEVERAGE

CARTONS

SYSTEM BOUNDARY

COLLECTIONFOR

INCINERATIONMSW

INCINERATION



COMPOSITE BEVERAGE CARTONSFROM HOUSEHOLD

CONSUMERTRANSPORT

TO BRINGBANK

KERBSIDECOLLECTION

FORRECYCLING


BANK

REPULPINGPROCESS

REJECTS (PE +AL) TO MSW

INCINERATION

COLLECTIONFOR

LANDFILLLANDFILL

EnergyElectricity

(av Europeanundelivered from landfill

gas collection)

SORTING +BALING

REJECTS (PE +AL) TO

LANDFILL

TESTLINERPRODUCTION

TESTLINER(CREDITAGAINSTKRAFTLINER)

RIGID + SEMI-RIGID

ALUMINIUMPACKAGING

SYSTEM BOUNDARY

COLLECTIONFOR

LANDFILL

COLLECTIONFOR

INCINERATION

KERBSIDECOLLECTION

FORRECYCLING


SORTING +BALING

RECYCLING +PRODUCTION

(SCRAPPREPARATIONSMELTING AND

ALLOYING)

TRANSPORTTO BRING

BANK


BANK

RIGID AND SEMI-RIGID ALUMINIUMPACKAGING FROM HOUSEHOLD

LANDFILL

MSW INCINERATION

MATERIALSRECOVERY FROM

INCINERATION

CREDITAGAINSTVIRGIN

PRODUCTION

LDPE FILMS

SYSTEM BOUNDARY

COLLECTIONFOR

LANDFILL LANDFILL

COLLECTIONFOR

INCINERATION

MSW INCINERATION



COLLECTIONAND BALING

FORRECYCLING


FILMRECYCLING

Credit to LDPEFILM

LDPE FILMS ARISING FROMINDUSTRIAL SOURCES

CORRUGATEDBOARD

COLLECTIONFOR

LANDFILL LANDFILL

SYSTEM BOUNDARY

COLLECTIONFOR

INCINERATIONMSW

INCINERATION

COLLECTIONFOR

RECYCLING

TESTLINERPRODUCTION

(Screening,Pulping,

Papermaking)

TESTLINER (CREDITAGAINST KRAFTLINER)

CORRUGATED BOARD ARISINGFROM INDUSTRIAL SOURCES



EnergyElectricity

(av European undeliveredfrom landfill gas collection)

SYSTEM BOUNDARY

PET BOTTLES FROM HOUSEHOLD

WASTE PETBOTTLES

COLLECTIONFOR

INCINERATION

COLLECTIONFOR

LANDFILL LANDFILL

MSW INCINERATION



KERBSIDECOLLECTION

FORRECYCLING

TRANSPORT TOREPROCESSORSORTING +

BALING

PETRECYCLING

PETGRANULATE

TRANSPORT TOBRING BANK


BANK

GLASS

SYSTEM BOUNDARY

COLLECTIONFOR

LANDFILL LANDFILL

COLLECTIONFOR

INCINERATION

MSW INCINERATION

CREDITAGAINST

LOW


GLASSRECYCLING

TRANSPORTTO BRING

BANK


BANK

GLASS BOTTLES FROM HOUSEHOLD

SORTING

GLASS

BOTTLE

PRODUCTION

TRANSPORT

TO FILLERFILLING

TRANSPORT/

DISTRIBUTIONUSE

TRANSPORT

TO BRING

BANK

COLLECTION

FOR LANDFILL

COLLECTION

FROM

INCINERATION

COLLECTION

FROM BRING

BANK

SORTING

TRANSPORT

TO

RECYCLERS

RECYCLINGMATERIAL

CREDIT

LANDFILL

MSW

INCINERATION

WASHING

TRANSPORT

TO WASHING SORTINGTRANSPORT

TO SORTING

PROCESS TREE: GLASS BOTTLES RETURNABLE

REUSABLE

PLASTIC

CRATE

REUSE OF

PLASTIC

CRATES

RECYCLING

OF PLASTIC

CRATES

RETURN +

DEPOSIT

GLASS

BOTTLE

PRODUCTION

TRANSPORT

TO FILLERFILLING

TRANSPORT/

DISTRIBUTIONUSE

TRANSPORT

TO BRING

BANK

COLLECTION

FOR LANDFILL

COLLECTION

FROM

INCINERATION

COLLECTION

FROM BRING

BANK

SORTING

TRANSPORT

TO

RECYCLERS

RECYCLINGMATERIAL

CREDIT

LANDFILL

MSW

INCINERATION

PROCESS TREE: GLASS BOTTLES SINGLE TRIP

RECYCLING

OF

SECONDARY

PACKAGING

SECONDARY

PACKAGING –

CORRUGATED

BOARD

MATERIAL

CREDITS

PET BOTTLE

PRODUCTIONTRANSPORT

TO FILLERFILLING

TRANSPORT/

DISTRIBUTIONUSE

COLLECTION

FOR LANDFILL

COLLECTION

FROM

INCINERATION

SEPARATE

KERSIDE

COLLECTION

SORTING

TRANSPORT

TO

RECYCLERS

RECYCLINGMATERIAL

CREDIT

LANDFILL

MSW

INCINERATION

PROCESS TREE: PET BOTTLES SINGLE TRIP

RECYCLING

OF

SECONDARY

PACKAGING

SECONDARY

PACKAGING –

CARTONBOARD,

FILM

MATERIAL

CREDITS

PET BOTTLE

PRODUCTIONTRANSPORT

TO FILLERFILLING

TRANSPORT/

DISTRIBUTIONUSE

COLLECTION

FOR LANDFILL

COLLECTION

FROM

INCINERATION

SORTING

TRANSPORT

TO

RECYCLERS

RECYCLINGMATERIAL

CREDIT

LANDFILL

MSW

INCINERATION

WASHING

TRANSPORT

TO WASHING SORTINGTRANSPORT

TO SORTING

PROCESS TREE: PET BOTTLES RETURNABLE

PLASTIC

CRATES

REUSE OF

PLASTIC

CRATES

RECYCLING

OF PLASTIC

CRATES

SEPARATE

KERBSIDE

COLLECTION

RETURN +

DEPOSIT


May 01

Annex 2: Incineration and landfill models


May 01

1 NON SELECTIVELY COLLECTED MSW2 COLLECTION SYSTEM

The grey bag is collected

• twice a week in high population density areas and

• once a week in low population density areas.

Collection vehicle is a truck with a volume of 16m_.

Employment and internal costs were determined by Beture Environnement [46].

2 INCINERATION MODEL

Pira Int. developed the incineration model shown in Figure 1.

Figure 1 : Incineration model

Activated carbonOn Site

vehical

Waste to Incineration

hydrogen chloride as HCl

HCl Acid

Sodium Hydroxide

electricity to grid

fly ash

ammonia

bottom ash

Sludge/cake

Incineration (Paper &

Board)General

Waste water treatment

Energy Conversion

Use of Heat

HEAT, natural

gas

HEAT, Heating oil

Gas, natural, delivered,

Europe

Oil, heating,

low sulphur, Europe

Incinerator Capital


May 01

2.1 Internal costs data

Allocation rules for the incineration cost

The allocation principle is to find a causal link between the waste composition and the incineration

cost.

The possible bases for the allocation are :

* The waste volume (or mass when only mass data are available and it is difficult to determine

the density) : to be used for the processes concerned when the waste is transported and stored

* The stoechiometric oxygen demand for full combustion (or fume volume or waste calorific

value) : to be used for the processes concerned when the waste produces heat and flue gas

* The waste inert content : to be used for the processes concerning the waste combustion

residues

* The pollutant concentration : to be used for the flue gas cleaning

Next tables give the allocation rules and the data and assumptions.

Annexes 1-2-3.doc

Page 18 of 30

Allocation baseA. Fixed cost

Construction

Reception, offices, waste pit mass

Furnace

grid mass

chamber stoichiometric oxygen demand for full combustion

Boiler, gas cleaning, chimney stoichiometric oxygen demand for full combustion

energy recovery (turbine, alternator) caloric value

Bottom ash extractor and treatment inert content

Magnetic separation Ferrous metal content

Eddy current separation Non ferrous metal content

Maintenance and replacement of pieces proportional to construction cost

Personnel proportional to construction cost

B. Variable costElectricity consumption stoichiometric oxygen demand for full combustion

Disposal of

Fly ash ash content

Boiler ash ash content

Bottom ash inert content

Gas cleaning residues

for acidic stage chlorine content

for basic stage sulphur content

activated carbon stoichiometric oxygen demand for full combustion

Consumption of additives

Activated carbon stoichiometric oxygen demand for full combustion

CaO for acidic stage chlorine content

CaO for basic stage sulphur content

Ammonia De-Nox stoichiometric oxygen demand for full combustion

C. Variable revenuesElectricity production calorific valueFerrous metals Ferrous metal contentNon Ferrous metals (Al) Non ferrous metal content

Cost Item

should be volume but very complicated to apply

Annexes 1-2-3.doc

Page 19 of 30

Incineration model - main data and assumptions

capacity 200.000 t/y Eurostaff 65 pers * 1.650.000 F 107.250.000 FB/y 2.658.658

Depreciation period 20 yearsinterest rate 6,0%

Fixed costReception, offices, waste pit 360.000.000 FB 8.924.167Furnace - grid 240.000.000 FB 5.949.445Furnace - chamber 360.000.000 FB 8.924.167Boiler, gas cleaning, chimney 1.480.000.000 FB 36.688.242energy recovery (turbine, alternator) 1.360.000.000 FB 33.713.519Bottom ash extractor and treatment 120.000.000 FB 2.974.722Magnetic separation 3.000.000 FB 74.368Eddy current separation 6.000.000 FB 148.736

Total 3.929.000.000 FB 97.397.366Variable cost

cost of treatment of dangerous waste (fly ash, gas cleaning residues) + landfilling class 1 6.000 FB/t 149amount of CaCl2.H2O + Ca(OH)2 generated 2,49 t residue / t Cl (CaCl2 + Ca(OH)2))stoechiometric coefficient (dictated by HCl) 1,65amount of CaSO4.1/2H2O generated for stoechiometry = 1 4,53 t CaSO4 / t Samount of Ca(OH)2 residue generated 1,50 t CaSO4 / t Samount of CaSO4 + Ca(OH)2 in landfill 6,03 t CaSO4 / t Ssale value of Fe recovered from bottom ash -587 FB/t Fe -15sale value of Al recovered from bottom ash -18.825 FB/t Al -467Ca(OH)2 cost 4.500 FB/t Ca(OH)2 112Ca(OH)2 use for acidic stage 1,72 t Ca(OH)2 / t ClCa(OH)2 use for basic stage 3,82 t Ca(OH)2 / t Scost of activated carbon 45.000 FB/ t act. carbon 1.116use of activated carbon 113 t act. Carbon /ycost of landfilling class 2 2.000 FB/t 50ammonia cost 3.654 FB/t 91ammonia use 114 t/yfly ash and boiler ash production 2,5% t/t MSWefficiency of electricity production (overall) 24,0%Internal electricity consumption -2,5% of low calorific valueefficiency of electricity production (net) 21,5%waste - low caloric value (positive) 10,2 GJ/tconversion factor 3,6 GJ/MWhelectricity sale price -1.500 FB/MWh -37production total 136.588 MWh/yInternal electricity consumption -14.228 MWh/ynet production 122.360 MWh/y

Specific flue gas volume (11% O2 dry) 6.000 Nm3/t (11% O2 dry)Inert content in MSW (including Fe and Al) 21% t inert/t MSW

bottom ash humidity 20% t water / t dry bottom ashFerrous metal content in MSW 2% t Fe / t MSWAl content in MSW 0,5% t Al / t MSWchlorine content 0,48% t Cl / t MSWsulphur content 0,075% t S / t MSWFe extraction rate from bottom ash 80% t Fe extracted / t Fe in MSW

Al extraction rate from bottom ash (only cans) 76%Electricity consumption for Fe extraction 0,007 MWh/t Fe extractedElectricity consumption for Al extraction 0,114 MWh/t Al extracted

t Al extracted / t Al in MSW(only cans)

Annexes 1-2-3.doc

Page 20 of 30

Therefore the costs are apportioned as follows :

Fixed cost Variablecost

Total cost Fixed cost Variablecost

Total cost

FB / t FB / t FB / t EURO / t EURO / t EURO / t

PVC 4.709 10.608 15.317 117 263 380

water 589 229 818 15 6 20

paper & board 4.230 718 4.948 105 18 123

glass 963 2.000 2.963 24 50 73

composites(LBC)

5.651 -31 5.619 140 -1 139

flexible Al 4.634 3.863 8.497 115 96 211

PE 10.918 -3.029 7.889 271 -75 196

PET 6.495 -2.532 3.963 161 -63 98

Fe 1.087 -69 1.017 27 -2 25

Rigid Al 1.950 -13.698 -11.747 48 -340 -291

PP 10.918 -3.449 7.469 271 -86 185

MSW 3.231 -138 3.094 80 -3 77

Sources :[69], [70], [71]

2.2 Environmental data

The incinerator modelled in this study assumes full compliance with current European

requirements for MSW incineration. In its original form the data assumed a set MSW mix.

The information summarised below has been use to allocate emissions between different

components of the waste stream:

• The allocation of CO2 emissions have been made on the basis of the carbon content of

the waste component

• The allocation of energy credits on the basis of the net energy yield of the waste

component

• The allocation of the bottom ash on the basis of the ash content of the waste component

• The allocation of the process related burdens, (e.g. NOx, SO2 & particulates) on the

basis of exhaust gas quantity

Annexes 1-2-3.doc

Page 21 of 30

• The allocation of waste independent burdens here assumed to include pre-treatment, on

site transport and burdens associated with the capital are allocated on a weight basis.

Main Assumptions

% Water2 %

Carbon1&2

% ash

Content3

Energy dry

weight)2

Exhaust Gas

(dry weight)4

Energy used

by water1

% % % MJ/kg kg/kg MJ/kg

Paper & board 24% 44% 8% 11 8 -480

Mixed Film 28% 85% 12% 22 24 -560

PE/PP Film 28% 86% 12% 31 24 -560

Rigid Plastic Mixed 10.50% 80% 7% 22 24 -210

PET 10.50% 58% 7% 22 14 -210

PE/PP 10.50% 86% 7% 31 24 -210

Ferrous metals 4.50% 0% 100% 0 -90

Aluminum (rigid) 12% 0% 100% -1 -240

Aluminum (foil) 12% 0% 189% 25 6 -240

Glass 2.50% 0% 100% -1 -50

Composite

beverage

24% 49% 17% 15 11 -482

1 Calculated2 sourced from Life Cycle Inventory Development for Waste Management Operations: Incineration, R&D Project Record P1/392/6,for the UK Environment Agency3 sourced from Integrated Waste Management, A Life Cycle Inventory, PR White, M Franke and P Hindle, 19954 from information supplied by RDC

3 LANDFILL MODEL

3.1 Internal costs

The landfill is operated in line with the landfill directive of April 26, 1999 (EC/1999/31).

The main environmental impact is the disamenity. The disamenity caused by waste is

assumed to be proportional to the waste volume.

The landfill costs (50 EURO/t of MSW) are also allocated proportionally to the waste

volume. The waste density is assumed to be the same as the bales density after sorting as

both are crushed.

Annexes 1-2-3.doc

Page 22 of 30

The costs are :

Density Cost Costkg/m3 EURO/t EURO/m3

MSW 700 50 35steel 800 43.75 35aluminium 200 175 35PET bottles 250 140 35LBC 500 70 35paper & board 500 70 35

3.2 Environmental data

The data used in this study is based on data generated in a study for the UK environment

agency. The landfill considered is fully lined with active gas management, energy

generation and an on site biological effluent treatment plant.

The model assumes that roughly one third of the landfill gas generated over the life time of

the site is flared, with one third being burnt for energy generation and one third lost to

atmosphere. The losses to atmosphere mainly occur during loading and after the active gas

management of the site has ceased. Leachate in this study has been assumed to be related to

moisture content, Alternative allocations have not been considered due to the low

significance of the leachate emissions for packaging related systems.

Dry quantity % Water Land Fill Gas Leachate Residual waste

% kg Kg kg

Paper & Board 1000 24% 913 316 87

Plastic Film 1000 28% 0 389 1000

Rigid Plastic 1000 10.50% 0 117 1000

Ferrous metals 1000 4.50% 0 47 1000

Non Ferrous Metals 1000 12% 0 136 1000

Glass 1000 2.50% 0 26 1000

Annexes 1-2-3.doc

Page 23 of 30

Annex 3: Internal cost data

Annexes 1-2-3.doc

Page 24 of 30

Costs for Landfilling 1 tonne PET bottles

Euro per tonne of packaging Collection costs Landfill costs Total internal costs

High population density 294 140 434

Low population density 234 140 374

Costs for Landfilling 1 tonne steel packaging


High population density 88.2 43.8 132

Low population density 68.4 43.8 112.2

Costs for Landfilling 1 tonne rigid and semi - rigid aluminium packaging




Costs for Landfilling 1 tonne paper & board packaging


High population density 78.8 70 148.8

Low population density 61.1 70 131.1

Costs for Landfilling 1 tonne Liquid Beverage Cartons




Costs for Landfilling 1 tonne mix plastics packaging




Annexes 1-2-3.doc

Page 25 of 30

Costs for Incineration of 1 tonne PET bottles

Euro per tonne ofpackaging

Collection costs Incineration –fixed costs

Incineration –variable costs

Total internalcosts

High pop. density 294 161 -63 392

Low pop. density 228 161 -63 326

Costs for Incineration of 1 tonne steel packaging




Total internalcosts

High pop. density- no slag recovery

88.2 73* 161.2

High pop. density- slag recovery

88.2 27 -2 113.2

Low pop. density- slag recovery

68.4 73* 141.4

Low pop. density- slag recovery

68.4 27 -2 93.4

Costs for Incineration of 1 tonne rigid and semi-rigid aluminium packaging




Total internalcosts

High pop. densitywith no slagrecovery

490 73* 563

High pop. densitywith slagrecovery (cans)

490 48 -340 198

High pop. densitywith slagrecovery(rigid/semi rigid)

490 48 -206 332

Low pop. densitywith no slagrecovery

380 73* 453

Low pop. densitywith slagrecovery (cans)

380 48 -340 88

Low pop. densitywith slagrecovery(rigid/semi rigid)

380 48 -206 222

Annexes 1-2-3.doc

Page 26 of 30

Costs for Incineration of 1 tonne Paper & Board packaging




Total internalcosts

High pop. density 78.8 105 18 201.8

Low pop. density 61.1 105 18 184.1

Costs for Incineration of 1 tonne Liquid Beverage Cartons




Total internalcosts



Costs for Incineration of 1 tonne mix plastics packaging




Total internalcosts



Annexes 1-2-3.doc

Page 27 of 30

Costs for Recycling 1 tonne of PET bottles via separate kerbside collection

Collection costs (Europer tonne of PET bottlesrecycled)

Sorting costs (Europer tonne of PETbottles recycled)

Transport from sorting plantto reprocessor (Euro pertonne of PET bottlesrecycled)

Reprocessing cost (Europer tonne of output)

Revenue received forreprocessed material

Total internal cost per tonnePET bottles recycled

High pop. density 255 474 46 332 -540* 566Low pop. density 306 474 46 332 -540 618*corresponding to a 540-332-46 = 162 EURO/t at the outlet of the sorting plant. This value is representative for the 2001 market situation. It issupposed to be more representative of the situation in 2006 than the average value over the last years (1998-2000) because the market has not beenstable and prices did not reflect the real cost in an efficient market.

Costs for Recycling 1 tonne PET bottles via bring bank collection

Transport costs from bringbank to sorting plant (Europer tonne of PET bottlesrecycled)

Sorting costs (Europer tonne of PETbottles recycled)

Transport from sortingplant to reprocessor (Europer tonne of PET bottlesrecycled)

Reprocessing cost (Europer tonne of output)

Revenue received forreprocessed material

Total internal cost per tonnePET bottles recycled

High pop. density 196 474 46 332 -540 508Low pop. density 242 474 46 332 -540 553

Costs for Recycling 1 tonne of steel packaging via separate kerbside collection

Euro per tonne of steel recycled Collection costs Sorting costs Transport from sorting plant to reprocessor Revenue received for material ready for use in steelproduction

Total internalcost

High population density 83.5 75.4 22.9 -34 147.8Low population density 100.5 75.4 22.9 -34 164.8

Costs for Recycling 1 tonne steel packaging via bring bank collection

Euro per tonne of steel recycled Transport costs from bringbank to sorting plant

Sorting costs Transport from sorting plant toreprocessor

Revenue received for material ready for use in steelproduction

Total internalcost


Annexes 1-2-3.doc

Page 28 of 30

Costs for Recycling 1 tonne of rigid and semi-rigid aluminium packaging via separate kerbside collection

Euro per tonne of aluminium sorted Collection costs Sorting costs Transport from sorting plant to reprocessor Revenue received for material ready for use inAl production

Total internal cost


Costs for Recycling 1 tonne rigid and semi-rigid aluminium packaging via bring bank collection

Euro per tonne ofaluminium sorted

Transport costs from bringbank to sorting plant

Sorting costs Transport from sorting plant to reprocessor Revenue received for material ready for use inAl production

Total internal cost

High population density 137.4 571.9 53.4 -316 446.7

Low population density 169.1 571.9 53.4 -316 478.4

Costs for Recycling 1 tonne of Paper & Board packaging via separate kerbside collection

Euro per tonne of paper & board Collection costs Sorting costs Transport from sorting plant to reprocessor Revenue received for baled paper Total internal cost

High population density 41.2 35 22.9 -21.6 77.5Low population density 49.6 35 22.9 -21.6 85.9

Costs for Recycling 1 tonne Paper & Board packaging via bring bank collection

Euro per tonne of paper &board

Transport costs from bring bank tosorting plant

Sorting costs Transport from sorting plant toreprocessor

Revenue received for baled paper Total internal cost

High population density 34 35 22.9 -21.6 70.3Low population density 41 35 22.9 -21.6 77.3

Annexes 1-2-3.doc

Page 29 of 30

Costs for Recycling 1 tonne of Liquid Beverage Cartons via separate kerbside collection (incineration of rejects)

Euro per tonne ofLBC sorted

Collection costs Sorting costs Transport fromsorting plant toreprocessor

Revenues frombales

Reprocessingcosts

Revenues frompaper product

Costs - revenues ofincineration of rejects (euro/trejects)

Total internal cost

High pop. density 146.2 302.3 22.9 -20 433 -455 57 486.4Low populationdensity

175.9 302.3 22.9 -20 433 -455 57 516.1

Costs for Recycling 1 tonne Liquid Beverage Cartons via bring bank collection (incineration of rejects)


Transport costs frombring bank to sortingplant

Sortingcosts

Transport from sortingplant to reprocessor

Revenues frombales

Reprocessingcosts

Revenues frompaper product

Costs - revenues ofincineration of rejects(euro/t rejects)

Total internalcost

High pop. density 112.6 302.3 22.9 -20 433 -455 57 452.8Low pop. density 138.6 302.3 22.9 -20 433 -455 57 478.8

Costs for Recycling 1 tonne of Liquid Beverage Cartons via separate kerbside collection (landfilling of rejects)


Collectioncosts

Sortingcosts


Revenues fromrecycling

Reprocessingcosts

Revenues from paperproduct

Costs - revenues oflandfilling of rejects(euro/t rejects)

Total internalcost


146.2 302.3 22.9 -20 433 -455 38.2 467.6


175.9 302.3 22.9 -20 433 -455 38.2 497.3

Costs for Recycling 1 tonne Liquid Beverage Cartons via bring bank collection (landfilling of rejects)


Transport costs frombring bank to sortingplant

Sortingcosts


Revenues fromrecycling

Reprocessingcosts

Revenues from paperproduct

Costs - revenues oflandfilling of rejects(euro/t rejects)

Total internalcost

High pop. density 112.6 302.3 22.9 -20 433 -455 38.2 434Low pop. density 138.6 302.3 22.9 -20 433 -455 38.2 460

Annexes 1-2-3.doc

Page 30 of 30

Costs for Recycling 1 tonne of mix plastics packaging via separate kerbside collection (mechanical recycling)

Euro per tonne of mix plastics sorted Collection, sorting, transport 1 Processing & transport 2 Overhead Revenue Total internal cost

High population density 1227 354 73 0 1654

Low population density 1227 354 73 0 1654

Costs for Recycling 1 tonne mix plastics packaging via separate kerbside collection (feedstock recycling)

Euro per tonne of mix plastics sorted Collection, sorting, transport 1 Processing & transport 2 Overhead Revenue Total internal cost

High population density 1227 354 73 0 1654

Low population density 1227 354 73 0 1654

Annexes 4-5-6.doc

Page 1 of 1

Annex 4: Economic valuations applied – sources

and derivation

Annexes 4-5-6.doc

Page 2 of 2

1 INTRODUCTION

The cost benefit analysis methodology used in the study is based on a life cycle assessment

to determine the environmental impacts of the selected systems, and economic valuation to

convert these environmental impacts into monetary values. The underlying characterisation

tables used are included in Table 1 (annex 4bis). Table 2 (annex 4bis) contains data on a

range of valuation and moneterisation methods, including the values applied in this study.

The environmental costs and benefits are summed to determine the total externality.

In parallel to this, the internal costs of the system are determined. The internal costs of the

system are the total costs minus the total revenues.

The externalities and internal costs of the system are summed to determine the total social

cost of the system.

The detail of determining environmental costs is discussed in the sections below.

The economic valuations applied in this study have been sourced by Pieter van Beukering

of IVM (Institute for Environmental Studies, University of Amsterdam) unless otherwise

indicated. The economic valuations have been sourced from a variety of reports and

documents. As far as possible, damage cost values are applied. However, where necessary

prevention costs have been used.

2 ENVIRONMENTAL IMPACTS

LCA is used to determine the environmental impacts of the system. The quantitative life

cycle inventory is generated. Characterisation and classification is then applied to the

inventory data. Characterisation assigns each environmental input and output (the

inventory data) to the environmental impacts to which it may potentially contribute.

Classification then applies a weighting factor according to the potential level of impact

relative to a specific reference emission. For example, the reference emission for global

warming is CO2. The weighting applied to CO2 is therefore 1. All other emissions which

Annexes 4-5-6.doc

Page 3 of 3

contribute to CO2 are weighted relative to their CO2 equivalence. For example, the effect

of global warming caused by a 1kg emission of methane is 21 times greater than the effect

caused by 1kg of CO2. Therefore methane is given a classification of 21.

The impact assessment data is then converted to monetary values through the application of

economic valuations to each individual impact category. The impact categories considered

and the impact assessment methodology applied have been developed with a consideration

of the needs of the economic valuations then applied. In some cases, this influences the

type of inventory data that is required in order to make a complete external economic

analysis.

The sections below and accompanying tables detail the classification values and economic

valuations applied.

2.1 Global warming

Global warming is characterised in CO2 equivalents. The classification values applied -

Time Horizon 100 years - are taken from figures given in Climate Change 1995

(Contribution of WG1 to IPPC second assessment report). The two principal contributors to

this category are carbon dioxide and methane with a GWP of 1 and 21 respectively.

The valuation stage is based on the most recent estimates from the FUND II model (Tol

and Downing 2000, FUND2 model, forthcoming).

Tol and Downing report the following marginal damages expressed per tonne of carbon (tC

not tCO2):

Pure time preference rate = 0% $75



Applying a 5% pure time preference rate, a value for GWP of US$46 tC, or US$12.5tCO2

(converted to 13.44 Euro per tonne CO2) is considered for this study.

Annexes 4-5-6.doc

Page 4 of 4

As global warming is not site specific, the emissions from different processes can be

directly summed. Overlap with other environmental effects can be ignored. One issue of

potential importance is that of the time horizon over which the emissions occur (i.e. in

incineration immediately and in landfill over many years). This issue has not been

addressed directly in the method applied, however previous studies suggest that application

of a time dependant analysis is of low significance. Where global warming is critical in the

results and time issues might be significant then the issue will be addressed in sensitivity

analysis.

New classification figures are due to be released shortly from the IPPC’s Third assessment

report but these were not available in time to be included in this study.

2.2 Ozone depletion

This category is typically unimportant for packaging waste systems, it is quantified in CFC

11 equivalents : The classification values applied are based on those in Climate Change

1995 and are listed in Annex 4 bis. The economic valuation applied to the impact

assessment data is 680 Euro per tonne of CFC 11 equivalents. This is based on an estimated

cost, associated with increased radiation, of 177 billion dollars and cumulative emissions of

an estimated 200 billion kg and should be considered as very approximate. This value has

been derived by Pira International specifically for inclusion in this study.

2.3 Human toxicity (Carcinogens)

Toxicity (carcinogens) refers to carcinogenic airborne emissions. Toxicity (carcinogens) is

quantified in Cd equivalents. The classification values applied to carcinogenic emissions

are listed in Annex 4 bis. The economic valuation applied to the impact assessment data is

22 140 Euro per tonne of Cd equivalents. This value is the average of the range of damage

costs reported by Dorland et al, 2000. The range reported is 5774 – 38498 Euro per tonne.

The range applies to damages to human health by emissions of cadmium arising from

production processes and electricity production.

Annexes 4-5-6.doc

Page 5 of 5

2.4 Human toxicity (Smog)

Toxicity (smog) relates to the production of ozone in the troposphere and is characterised in

Ethylene equivalents based on the values developed by Harwell Laboratories (Derwent &

Jenkin, 1990). NOx which also contributes to the formation of low level ozone is given a

value equivalent to 1.19kg ethylene/kg. The classification values applied to emissions that

contribute to Toxicity (smog) are listed in Annex 4 bis.

The economic valuation applied to the impact assessment data is 734 Euro per tonne of

Ethylene equivalents. The valuation is for VOC indirect impacts through ozone formation,

as reported in Dorland et al, (2000). The value refers to damages to human health by

emissions of production processes and electricity generation.

2.5 Human Toxicity (particulates)

Toxicity (particulates) refers to airborne emissions typically generated and measured

directly, such as PM10 or indirectly through the production of aerosols (Sulphate &

Nitrate). Toxicity (particulates) is measured in PM10 equivalents. The classification values

applied to emissions that contribute to Toxicity (particulates) are listed in Annex 4 bis. The

economic valuation applied to the impact assessment data is 23686 Euro per tonne of PM10

equivalents, as reported in Dorland et al, (2000). This value is for emissions of PM10

(directly emitted). The value refers to damages to human health by emissions arising from

production processes and electricity generation.

2.6 Human toxicity (Other air)

Toxicity (Other air) refers to airborne emissions which have toxic effects, other than

carcinogenic effects or effects caused by smog or particulates. Toxicity (other air) is

quantified in SO2 equivalents. The classification values applied to emissions that

contribute to this category are based on their relative human toxicity value and are listed in

Annex 4 bis.

Annexes 4-5-6.doc

Page 6 of 6

The economic valuation applied to the impact assessment data is 1002 Euro per tonne of

SO2 equivalents. This value is non-specific and based on general non-transport related

emissions. Should this category prove important then a sensitivity analysis will be

conducted to consider the significantly higher burden associated with SO2 emitted from

vehicles (over 2000 Euro/tonne).

2.7 Acidification

Acidification is quantified in Acid equivalents (H+). The classification values applied to

emissions that contribute to acidification are listed in Annex 4 bis. The economic valuation

applied to the impact assessment data is 8.7 Euro per kg of Acid equivalents equivalent to

0.27 Euro/kg of SO2. This value excludes the costs due to damage to buildings but includes

damage to crops, forestry and lakes (see Table 1).

Table 1

Crop Damage

Dorland et al. (2000)

Forests

(EC 1995)

Lakes

(EC 1995)

Total

0.215 0.036 0.015 0.27/kg SO2

= 8.7/kg H+ equiv.

2.8 Damage to structures

Damage to structures refers to soiling of buildings caused by black smoke. The definition

of black smoke is based on chemical properties of particles rather than on particle size, so

the size composition of black smoke can vary considerably. However, roughly speaking

black smoke consists of particles with a diameter of less than 15µm.

Damage to structures is measured in dust equivalents: The classification values applied to

emissions that contribute to Damage to structures are listed in Annex 4 bis. The economic

valuation applied to the impact assessment data is 662 Euro per tonne of dust equivalents.

Annexes 4-5-6.doc

Page 7 of 7

This value is sourced from Dorland et al 2000 who determine a damage cost of 662 Euro

per tonne of particulate emitted in the form of black smoke. This value is calculated by

Pieter van Beukering, estimated based on the total UK emissions of black smoke and an

assessment of the size of the UK market for cleaning buildings that is completely

attributable to soiling from particle pollution (as reported in Newby et al 1991).

In the methodology applied in this analysis, no distinction is made between emissions

arising from processes and emissions arising from transport.

2.9 Fertilisation

Deposited nitrogen has a beneficial effect on crop yields because it acts as a fertiliser. The

level of this externality is determined by the value of the yield increase due to the deposited

nitrogen. Pieter van Beukering provides a value of –697 Euro per tonne of NOx (expressed

as NO2 mass equivalents). It is uncertain whether these fertilisation effects are sustainable

in the long term.

The classification values applied to emissions that contribute to Fertilisation are listed in

Annex 4 bis.

2.10 Traffic accidents

The economic valuation applied to traffic accidents in this study has been calculated by

Pira International specifically for this project.

Traffic accidents is quantified in Car km equivalents. The classification values applied to

different road types are listed in Annex 4 bis and based on UK transport statistics. Little

evidence was found in these statistics of a difference between HGV/Commercial vehicles

and passenger cars in terms of the accidents or deaths/km driven (see Table 2).

Annexes 4-5-6.doc

Page 8 of 8

Table 2

Rate of Serious & Fatal Accidents/ 100 million vehicle km

Car 12

Light Van 10

Goods Vehicle 12

Road type however is significant - motorways being considerably safer. The higher value

for rural roads seems counter intuitive - however Rural roads are defined here as roads with

a speed restriction above 40 mph (~64 km/h). The overall accident rate goes counter to this

with urban roads having a rate more than twice as high. (See Table 3)

Table 3

Fatalities1999

SeriousAccidents

Total roadtraffic billionvehicle km

Deaths/billionvehicle km

SeriousAccidents /billionvehicle km

Characterisation(fatalityequivalent)

Characterisation- Seriousaccidentequivalent.

Motorway 176 1218 83.6 2.1 14.6 0.31 0.19

Urban 1338 23011 200.2 6.7 114.9 1.00 1.47

Rural 1621 12176 183.3 8.8 66.4 1.32 0.85

All 3135 36405 467.1 6.7 77.9 1.00 1.00

The methodology assumes that the average European situation follows the UK situation

and uses the characterisation values above to combine the different road types.

The serious accident figures are being excluded; firstly because the low valuation of injury

versus fatality means that it becomes insignificant and secondly because there is a risk of

double counting as the statistics for serious accidents include accidents, which led to

fatalities.

The economic valuation applied to the impact assessment data is 16.9 Euro per 1000 km

travelled on an average road.

2.11 Traffic congestion

The external costs of congestion result from various effects. The most important costs are

the time costs of delay. Indirect effects include increased emissions levels and danger in

Annexes 4-5-6.doc

Page 9 of 9

traffic. Traffic congestion is quantified in Car km equivalents with a HGV or van

equivalent to 2 cars. The differentiation between road types is based on UK data. The

classification values applied are listed in Annex 4 bis. The economic valuation applied to

the impact assessment data is 85.5 Euro per 1000 car km equivalents.

Brossier (1996) estimates the marginal congestion costs of trucks averaged over a year on

“National roads” at 17.1 Euro per 100 HGV km. No description of the term “national

roads” is provided, but assuming that this refers to a typical UK A road (rather than an

urban road) this gives an economic value of 8.55 Euro per 100 car km equivalents.

2.12 Traffic Noise

Noise is any unwanted sound. The main source of noise in recycling systems is transport

and disposal sites. The noise externality of landfill sites is included in the disamenity value

of landfilling (Section 2.14), so the focus of this impact category is transport related noise.

In many EU countries, transport is the most pervasive source of noise in the environment

(Houghton 1994).

It is difficult to relate noise or noise nuisance to a parameter that is quantifiable in a life

cycle study. The impact pathway is complex with many influencing factors. However, as

waste disposal and recycling activities involve a considerable amount of transport. The

disamenity of noise from transport cannot be neglected. Therefore, an attempt to quantify

this important impact has been made for the purposes of this study.

Two types of noise exist:

♦ Acute noise – arising from the operation of heavy machinery, and therefore mainly

related to occupational health

♦ Nuisance noise – less sudden noise, such as that experienced by people living near a

main road or rail track. The effects can include impairment of communication, loss of

concentration and loss of sleep.

Annexes 4-5-6.doc

Page 10 of 10

The actual damage of noise has three forms:

♦ Property value reductions

♦ Productivity loss resulting due to medical complaints of workers

♦ Damage to ecosystems (frightened wildlife)

An overview of available hedonic and contingent valuations is presented in Table 4.

Table 4 : Summary of studies on the WTP to halve the noise exposure level

Study Hedonic valuation (in Euro) Contingent valuation (in Euro)

Pommerehne (1988) 51 46

Iten and Maggi (1988) 43 -

Willeke et al (1990) - 81

Soguel (1994) 37 35-42Source: Soguel 1994

Even though two different techniques are applied, the estimates are within the same range.

Assuming a linear relationship between WTP and noise exposure, the average WTP for a

reduction of noise exposure is 3.8 Euro per dB(A).

Kageson (1993) determines the noise costs for road transport at 2-3 Euro per 1000 km and

passenger km, and rail transport at 0.5 – 0.7 Euro per 1000 km.

For this study, “Traffic noise” is quantified in Car km equivalents, using the economic

value of 3 Euro per 1000 car km equivalents. The classification values applied to different

transportation modes are listed in Annex 4 bis.

2.13 Water Quality – Eutrophication

Several difficulties exist in transferring the external effects of surface water pollution for

externalities occurring in recycling processes. Firstly, most values are presented in an

aggregated manner, whereas waste related and recycling processes are valued on a marginal

basis. Secondly, transferability is hampered by demographic differences. Most water

Annexes 4-5-6.doc

Page 11 of 11

pollution studies have been conducted in Scandinavian countries. Thirdly, the type of

water pollution may differ from the type of water contamination. Forth, there remains a

lack of reliable dose-response function information.

In this study, Water Quality – Eutrophication is quantified in P equivalents. The

classification values applied to water borne emissions that contribute to Eutrophication are

listed in Annex 4 bis. The economic valuation applied to the impact assessment data is

4700 Euro per tonne P equivalents. This is derived from Gren et al (1996), and is based on

the costs of increased abatement capacity at sewage or industrial plants necessary to reduce

these emissions.

2.14 Disamenity

Disamenity effects of waste management processes are likely to make up a significant share

of the externalities caused. In particular, landfill sites and incineration facilities generate

substantial social costs to their neighbouring population. The disamenity may take a

number of forms:

♦ Increased traffic noise (see Section 2.12 for details of valuation applied)

♦ Increased traffic congestion (see Section 2.11 for details of valuation applied)

♦ Odour and visual pollution

♦ (Perceived) increased health risk

A common approach to determine disamenity effects is to use variations in house prices

(hedonic price method). In this study, the externality of increased traffic noise and

congestion are valued separately. Changes in house price are assumed to relate to odour

and visual disamenity only, as these aspects are not valued elsewhere in the methodology.

It should be highlighted that this approach may lead to potential double counting of some of

the externalities.

Several hedonic price method studies on the value of disamenity effects of landfill have

been performed. Landfilling and incineration produce different effects, and therefore

should be assigned different externalities. Households are reluctant to live near an

Annexes 4-5-6.doc

Page 12 of 12

incinerator due to the perceived health effects of emissions. Disamenity of landfill is

caused by the perception of groundwater pollution, and the visual pollution and odour

nuisance. However, as no valuation data have been found to distinguish between their

waste management practices the overall disamenity value for landfilling and incineration

has been assumed to be equal.

All studies identify a significant house price reduction due to the existence of waste sites

nearby. House prices increase approximately 3-4% per kilometre distance from a landfill

site, within a radius of approximately 5.5 km.

Similarly, Contingent valuation studies demonstrate that WTP1 declines with distance to

the facility. An important determinant of WTP is income and perception of the risk of

leachate pollution of water supplies. Households with a high income whose water supplies

were at risk are willing to pay substantially more than low-income households dependent

on piped city-water. However, the CVM2 findings are generally consistent with the

findings of the HPM3.

Based on the literature, the following linear regression equation is determined (Brisson and

Pearce 1995): ∆ HP = 12.8 – 2.34 * D

(∆ HP = the percentage change in house price, D = distance in km from facility)

This suggests a maximum house price depreciation of 12.8% at the site of the facility, with

no price differential beyond 5.5 km.

Based on the disamenity function, the annual value of reduction in the real estate prices can

be calculated. Graph 1 shows how this varies substantially considering five categories of

household density and five levels of average house price. The overall values are converted

to annual values by taking 8% of the total reduction.

1 Willingness To Pay2 Contingent Valuation Method

Annexes 4-5-6.doc

Page 13 of 13

Graph 1

To link variations in the life cycle and economic valuation, external costs are then

calculated on a per unit basis. This step in the analysis is uncommon – in reality the

disamenity is not determined by the quantity of waste processed by the facility, but by the

simple existence of the facility. However, to facilitate a link disamenity value is assumed

to be proportional to the total amount of waste processed. Values reported in the literature

vary from 1.2 Euro per tonne for a study relating to landfilling in Minnesota (IIED 1996) to

10.6 Euro per tonne for a study in Milan, Italy (Ascari and Cernischi 1996). These

differences may arise due to the processing capacities of the facilities.

Table 5 determines the annual disamenity value of 1 tonne of landfilled and incinerated

solid waste. However, due to the potential influence of the simplifying assumptions, such

as the uniform disamentiy value for landfill and incinerator, and the neglect of income

elasticity, these values should be treated with caution. Ideally, the values should be

determined on a marginal basis and considering local circumstances such as average house

price, population density and processing capacity.

3 Hedonic Price Method

Annexes 4-5-6.doc

Page 14 of 14

Table 5 : Calculation of disamenity valuation per tonne of solid waste

Annual processingcapacity (ton / annum)

Total disamenity(million Euro)***

Disamenity per unit ofwaste (Euro per tonne)

Landfill* 200000 7.4 37

Incinerator** 730000 7.4 10* Total capacity estimated at 4 million tonnes over 20 year life time** Total capacity estimated at 10 million tonnes over a 14 year life time*** Based on an average house price of Euro 100000 and a density of 250 houses per km2

2.15 Heavy metals (airborne)

An accurate valuation is not available for this category. However a crude approximation

has been generated by Pira International specifically for this study, by dividing the

estimated total damage cost by the total emissions. Dubourg (1996) estimates that airborne

Pb was responsible for 62 deaths in England & Wales in 1987. Taking this figure and

multiplying by 3.1 million Euro (the value for a statistical life assumed for this calculation)

gives us a total cost of 192.2 million Euro. Another publication (The Environment in

Europe and North America, Annotated Statistics 1992, Economic Commission for Europe,

United Nations Publication) gives the total emissions of lead in the UK as 3100 tonnes in

1988. This gives us an economic value of 62 Euro/kg of Pb emitted.

2.16 Employment

Standard economic theory says that it is not possible to create a job without displacing

other employment. The argument is that for every job that is created, some other job is lost

– the reason being that economics assumes full employment in the economy. Any one not

in employment is in a transitional stage between one job and another, rather than being

“involuntarily unemployed”, and has therefore internalised the costs of unemployment in

their decision-making. If you now create a job for this person in recycling, it means that

this person is now not available for the job he/she would have taken if this job hadn’t been

created. There is therefore no social value in creating employment.

Annexes 4-5-6.doc

Page 15 of 15

However, the fact is that a proportion of the unemployed in Europe are not unemployed

voluntarily (i.e. they are not in a transitional stage, and have not internalised the costs of

unemployment in a decision). In such a case, the unemployment represents a social cost. If

such involuntary unemployment represents a significant and long-term proportion of the

total unemployment, then it may be argued that employment creation policies will have a

positive social impact and employment should have an economic valuation.

Table 6 presents unemployment rates in the EU for May 2000. For some Member States

high unemployment rates are experienced. This may include long-term involuntary

unemployment, and therefore an economic valuation of employment could be appropriate.

Thus, for this study, an economic valuation for employment is included in the sensitivity

analysis. The economic valuation applied is 2945 Euro per job per annum. This value

has been derived by RDC-Environment specifically for this study, and is based on the

economic support to job creation in Belgium. It is the value of the reduction of social

security taxes for newly employed workers in Belgium (law of 1999-03-26).

Table 6 :Unemployment rates in Europe (as at May 2000)

Country %

Austria 3.2

Belgium 8.4

Denmark 4.7

Finland 9.5

France 9.8

Germany 8.4

Greece No data

Ireland 4.7

Italy 10.7*

Luxembourg 2.2

Netherlands 3.0*

Portugal 4.5

Spain 14.3

Sweden 6.1

UK 5.7*** as at April 2000

** as at March 2000

Annexes 4-5-6.doc

Page 16 of 16

3 ALTERNATIVE ECONOMIC VALUATIONS

Economic valuation and cost benefit analysis are developing disciplines. Different

practitioners apply different economic valuations. Some alternative economic valuations

are list in annex 4 bis.

4 REFERENCES

Ascari, S and S Cernischi (1996) Integration of pollutant dispersion modelling and hedonoc

pricing techniques for the evaluation of external costs of waste disposal sites. In: A

Baranzini and F Carlevaro (eds) Econometrics of Environment and Transdisciplinarity

(Volume I). Preceeding of the LIst International Conference of the Applied Econometrics

Association (AEA), Lisbon, April 1-12 1996, 156-173

Brisson IE and D Pearce (1995) Benefits transfer for Disamenity from Waste Disposal. .

CSERGE Working Paper WM95-06. London, Centre for Social and Economic Research of

the Global Environment (CSERGE), University College London

Brossier, C (1996) Mise a jour de l’etude de l’implication des couts d’infrastrucre de

transports, Report for the Ministry of Transport, Paris

Derwent & Jenkin, 1990

Dorland C, AQA Omtzight and AA Olsthoorn (2000), Marginal Costs – The Netherlands,

In: R Friedrich and P Bickel (eds), External Environmental Costs of Transport, University

of Stuttgart

Gren, I-M, T Soderqvist, F Wulff, S Langrass and C Folke (1996) Reduced nutrient loads

to the Baltic Sea: Ecological consequences, costs and benefits. Beijer Discussion Paper

Annexes 4-5-6.doc

Page 17 of 17

Series No 83, Beijer International Institute of Ecological Ecomonics, The Royal Swedish

Academy of Science, Stockholm

Houghton, Sir John (1994) Eighteenth Report Transport and the Environment, Royal

Commission on Environmental Pollution. HMSO, London

IIED (1996), Towards a Sustainable Paper Cycle, International Institute for Environment

and Development / World Business Council for Sustainable Development, London

Intergovernmental Panel on Climate Change (1995) Climate Change 1995 The science of

Climate Change, Contribution of Woking Group 1 to the Second Assessment Report of the

Intergovernmental Panel on Climate Change, Cambridge University Press

Kageson (1993) Getting the Prices Right: a European Scheme for Making Transport Pay

its True Costs. European Federation of Transport and the Environment, T&E 93/6,

Stockholm

Newby P T, T A Mandfield and RS Hamilton (1991) Sources and economic implications of

building soiling in urban areas, The Science of the Total Environment, 100, 347

Newbery, DM (1995) Royal Commission Report on Transport and the Environment:

Economic Effects of Recommendations, The Economic Journal. Sept, Oxford, UK

Soguel N, (1994) Measuring benefits from traffic noise reduction using a contingent

market. CSERGE Working Paper WM94-03. London, Centre for Social and Economic

Research of the Global Environment (CSERGE), University College London

R Tol and T Downing, (2000) The Marginal Cost of Climate Changing Gases, Paper 00-08,

Institute for Environmental Studies, Free University of Amsterdam.

Annex 4 bis Appendix 1 - Characterisation Tables

Burden Name: Multiplier: Notes:

GWP (kg CO2 eq.)carbon tetrachloride -225CFC (unspecified) 1320 assumed as CFC-11CFC-11 1320CO2 (non renewable) 1CO2 (renewable) 1CO2 (unspecified) 1dichloromethane 9haloginated HC (unspecified) 4halon -1301 -49750halons (unspecified) -49750 assumed as halon-1301HCFC (unspecified) 1350 assumed as HFC-22HCFC-22 1350hexafluoroethane 9200HFC (unspecified) 1000methane 21N2O 310tetrafluoromethane 6500tetrafluroethylene 1300trichloroethane -1525trichloromethane 4

Ozone depletion (kg CFC 11 eq.)carbon tetrachloride 1.08CFC (unspecified) 1 assumed as for CFC 11CFC-11 1halon -1301 16halons (unspecified) 0.14 assumed as for Halon-2311HCFC (unspecified) 0.055 assumed as for HCFC 22HCFC-22 0.055trichloroethane 0.12

Acidification (Acid equiv.)acid as H+ (waterborne) 1HCl 0.02743484HF 0.050005NH3 0.02941176NOx 0.01086957SO2 0.03125

Toxicity Carcinogens (Cd equiv)acetaldehyde 0.0000016 acetaldehyde aromatics (unspecified) 0.000019 assumed as benzeneAs 0.18 Arsenic As (soil) 0.098 Arsenic (ind.) As (waterborne) 0.49 Arsenic benzene 0.000019 benzene benzene (waterborne) 0.000031 benzene benzo(a)pyrene 0.029 benzo(a)pyrene benzo(a)pyrene (waterborne) 22butadiene 0.00012 1,3-butadiene carbon tetrachloride 0.0062 carbontetrachloride Cd 1 Cadmium Cd (soil) 0.029 Cadmium (ind.) Cd (waterborne) 0.53 Cadmium Cr (IV) 13 assumed as Cr (6+)Cr (unspecified) 13Cr (unspecified) (soil) 2 Chromium (ind.) Cr (unspecified) (waterborne) 2.5 as Cr IVCr-VI (waterborne) 0.029 Chromium (VI) dichloroethane 0.00022 1-2 dichloroethanedichloromethane 0.0000032 dichloromethane dioxins and furanes (unspecified) 1300 assumed as 2,3,7,8-TCDD Dioxinethylene oxide 0.0014 ethylene oxide formaldehyde 0.0000073 formaldehyde formaldehyde (waterborne) 0.000037 formaldehyde haloginated HC (unspecified) 0.0000032 assumed as dichloromethaneheavy metals (air) 0.039 assumed as metalsinsecticide (unspecified) 0.0026 as lindanelindane 0.0026 gamma-HCH (Lindane) metals (unspecified) 0.039 metals Ni 0.17 Nickel Ni (soil) 0.029 Nickel (ind.) Ni (waterborne) 0.23 Nickel PAH (unspecified) 0.43 as Benzo(a) anthracenePAH (waterborne) 4.9 as Benzo(a) anthraceneparticulate (diesel) 0.000072 particles diesel soot pesticides (unspecified) (waterborne) 0.031 gamma-HCH (Lindane) styrene 0.00000018 styrene tetrachloride-dibenzo-dioxin 1300 2,3,7,8-TCDD Dioxin tetrachloroethene 0.0000036 perchloroethylenetrichloromethane 0.00019 chloroform vinyl chloride 0.0000015 vinyl chloride

Toxicity Metals non carcinogens (Pb equiv.) Relative toxicities taken from Ecoindicator 95

Page 1 of 4


Burden Name: Multiplier: Notes:B (waterborne) 0.03Ba (waterborne) 0.14Cu (waterborne) 0.005heavy metals (air) 1heavy metals (waterborne) 1 assumed as PbHg 1Hg (waterborne) 10metals (unspecified) 1 assumed as Pbmetals (unspecified) (waterborne) 1 assumed as PbMn 1Mn (waterborne) 0.02Mo (waterborne) 0.14Pb 1Pb (waterborne) 1

Toxicity Gaseous non carcinogens (SO2 equiv.)CO 0.67 Value based on EI99 (Respirotary effects - Egalitarian)H2S 43.59NH3 1.12SO2 1.00

Toxicity Particulates & aerosols (PM10 equiv)NOx 0.2particulate (diesel) 15.7PM10 1SO2 0.24TSP 0.7 Assumed as PM10 *.7

Toxicity Smog (ethylene equiv.)acetaldehyde 1.4acetic acid 1.1 assumed as for Non Methane hydrocarbons (average)acetone 0.47acrolein 1.1 assumed as for Non Methane hydrocarbons (average)alcohols (unspecified) 0.52aldehydes (unspecified) 1.2alkanes (unspecified) 1.1alkenes (unspecified) 2.4aromatics (unspecified) 2benzene 0.5benzo(a)pyrene 1.1 assumed as for Non Methane hydrocarbons (average)butadiene 1.1 assumed as for Non Methane hydrocarbons (average)butane (i) 0.84butane (n) 1.1butane (unspecified) 0.84 assumed as for i-butanebutene 2.6carbon tetrachloride 0.056 assumed as for halogenated hydrocarbons (average)CFC (unspecified) 0.056 assumed as for halogenated hydrocarbons (average)CFC-11 0.056 assumed as for halogenated hydrocarbons (average)cyclic alkanes (unspecified) 1.1 assumed as for Non Methane hydrocarbons (average)dichloromethane 0.027dioxins and furanes (unspecified) 0.056 assumed as for halogenated hydrocarbons (average)esters (unspecified) 0.59ethane 0.22ethanol 0.71ethene 2.7ethers (unspecified) 1.1 assumed as for Non Methane hydrocarbons (average)ethylbenzene 1.6ethylene dichloride 1.1 assumed as for Non Methane hydrocarbons (average)ethylene oxide 1.1 assumed as for Non Methane hydrocarbons (average)ethyne 0.45formaldehyde 1.1haloginated HC (unspecified) 0.056halon -1301 0.056 assumed as for halogenated hydrocarbons (average)halons (unspecified) 0.056 assumed as for halogenated hydrocarbons (average)HC (unspecified) 1HC excl CH4 (unspecified) 1.1HCFC (unspecified) 0.056 assumed as for halogenated hydrocarbons (average)HCFC-22 0.056 assumed as for halogenated hydrocarbons (average)heptane 1.4hexafluoroethane 0.056 assumed as for halogenated hydrocarbons (average)hexane 1.1 assumed as for n-hexaneHFC (unspecified) 0.056 assumed as for halogenated hydrocarbons (average)ketone 0.86mercaptans/smell gas (unspecified) 1.1 assumed as for Non Methane hydrocarbons (average)methane 0.019methanol 0.33methyl tert-butyl ether 1.1 assumed as for Non Methane hydrocarbons (average)naphthalene 1.1 assumed as for Non Methane hydrocarbons (average)non methane VOC (unspecified) 1.1 assumed as for Non Methane hydrocarbons (average)NOx 1.2organic acids (unspecified) 1.1 assumed as for Non Methane hydrocarbons (average)PAH (unspecified) 1.1 assumed as for Non Methane hydrocarbons (average)pentane 0.93phenol 1.1 assumed as for Non Methane hydrocarbons (average)phenols (unspecified) 1.1 assumed as for Non Methane hydrocarbons (average)phthalates (unspecified) 1.1 assumed as for Non Methane hydrocarbons (average)

Page 2 of 4


Burden Name: Multiplier: Notes:propane 1.1propene 2.7propionaldehyde 1.6propionic acid 1.1 assumed as for Non Methane hydrocarbons (average)styrene 1.1 assumed as for Non Methane hydrocarbons (average)tetrachloride-dibenzo-dioxin 0.056 assumed as for halogenated hydrocarbons (average)tetrafluoromethane 0.056 assumed as for halogenated hydrocarbons (average)tetrafluroethylene 0.056 assumed as for halogenated hydrocarbons (average)toluene 1.5trichloroethane 0.056 assumed as for halogenated hydrocarbons (average)trichloromethane 0.056 assumed as for halogenated hydrocarbons (average)VOC 1xylene (unspecified) 2.3 assumed as average xylenexylene(m-) 2.6xylene(o-) 1.8xylene(p-) 2.4

Damage to Structures (kg dust eq.)NOx 0.37particulate (diesel) 1PM10 1SO2 1.06 702 ecu/662 ecuTSP 1 assumed as particulates

FertilisationNOx 1

Traffic accidentsCar (motorway) 0.31Car (rural) 1.32Car (unspecified) 1Car (urban) 1HGV (motorway) 0.31HGV (rural) 1.32HGV (unspecified) 1HGV (urban) 1Road transport (rural) 0.31Road transport (unspecified) 1Road transport (urban) 1

Traffic Congestion (car km equiv.)Car (motorway) 0.08Car (rural) 0.03Car (unspecified) 1Car (urban) 4.9HGV (motorway) 0.15HGV (rural) 0.06HGV (unspecified) 2HGV (urban) 9.8Road transport (rural) 0.06 Car km congestion equiv.Road transport (unspecified) 2 Car km congestion equiv.Road transport (urban) 9.8 Car km congestion equiv.

Traffic Noise (car km equiv.)Car (motorway) 1Car (rural) 1Car (unspecified) 1Car (urban) 1HGV (motorway) 6HGV (rural) 6HGV (unspecified) 6HGV (urban) 6Road transport (rural) 6 Car km noise equiv.Road transport (unspecified) 6 Car km noise equiv.Road transport (urban) 6 Car km noise equiv.

Water Quality Eutrophication (P equiv.)COD 0.0072N (waterborne) 0.14NH3 0.029 Assuming 25% ends up in surface waternitrates (waterborne) 0.033 Average value for NO3- to waternitrites (waterborne) 0.033 Average value for NO3- to waternitrogenous compounds (unspecified) (waterborne)0.033 Average value for NO3- to waterNOx 0.011 Assuming 25% ends up in surface waterP (waterborne) 1phosphates (waterborne) 0.33

Disaminity (kg LF waste equiv.)Waste into Incinerator 0.274 200000/730000 ton/yearWaste into Landfill 1

Ecotoxicity (cu equiv.)As 0.41 Arsenic As (soil) 0.42 Arsenic (ind.) As (waterborne) 0.0078 Arsenic benzene 0.0000019 benzene benzene (waterborne) 0.000033 benzene

Page 3 of 4


Burden Name: Multiplier: Notes:Cd 6.6 Cadmium Cd (soil) 6.8 Cadmium (ind.) Cd (waterborne) 0.33 Cadmium Cr (IV) 2.8 as CrCr (unspecified) 2.8 Chromium Cr (unspecified) (soil) 2.9 Chromium (ind.) Cr (unspecified) (waterborne) 0.047 Chromium Cu 1 Copper Cu (soil) 1 Copper (ind.) Cu (waterborne) 0.1 Copper Hg 0.57 Mercury Hg (soil) 1.2 Mercury (ind.) Hg (waterborne) 0.13 Mercury insecticide (unspecified) 0.08 Malathion lindane 0.0015 gamma-HCH (Lindane) metals (unspecified) 0.18 metals Ni 4.9 Nickel Ni (soil) 5 Nickel (ind.) Ni (waterborne) 0.098 Nickel PAH (unspecified) 0.00000053 PAH's PAH (waterborne) 0.0000014 PAH's Pb 1.7 Lead Pb (soil) 0.0088 Lead (ind.) Pb (waterborne) 0.0051 Lead pesticides (unspecified) (waterborne) 0.0071 gamma-HCH (Lindane) tetrachloride-dibenzo-dioxin 90 2,3,7,8-TCDD Dioxin toluene 0.00000016 toluene toluene (waterborne) 0.00012 toluene Zn 2 Zinc Zn (soil) 2 Zinc (ind.) Zn (waterborne) 0.011 Zinc

Page 4 of 4

Annex 4 bis Appendix 2 - Moneterisation/Valuation

Prevention cost from Delft university

(Vogtlander et al 1999)

Prevention cost from Delft university

(Vogtlander et al 1999)

Ec--Indicator 95

marginal cost (1) average cost (1)

Global Warming Potential /kg CO2 equ. 0.114 0.08 0.01344

CO2 0.0632 0.0014 0.0018 0.01375 0.003 0.193

CH4 1.548

Acidification 204.8 22.857 1.86 3.27 8.73

SOx 6.4 2.5435 1.03 1.4 0.47 0.06 0.10

NOx 2.0348 0.911 1.16 2.3 16

Photochemical pollution due to VOCs 50 3.5 2.0348 3.55 0.734

O3 0.44 0.58 2.5 2.5

Ozone depletion (CFC11) 4.459 0.68

Toxicity : other emissions to air (SO2 equ.) 1.002

CO NA NA 0.0763 NA NA 0.01002

Eutrophication kg Phosphate equi. 3.05 0.0009 NA 2.357 NA 1.5369

COD in water 0.7122 NA NA

Eutrophication kg P equi. 9.327217125 0.002752294 NA NA 4.7

Winter Smog

Particulates (<10 µm) 12.3 5 0.5087 0.39 0.51 1.43 17 29 23.686

SO2

TSP

NOx

Heavy metals (Pb) NA 1571 62

Zn 680 0.3

Toxicity : carcinogenic substances NA NA

PAH 12.3 3837 6022.08

Dioxines NA 2000000 19720319

Arsenic 33 1571.4 44 6.642

Cadnium 9100 12000 78571 81 22.14

Chromium 330 440 314.2 820 128

Nickel 330 1688 17 7.08

Damages to structures (S02) 0.662

Disamenity Landfill 0.037

Disamenity Incinerator 0.01

Traffic accident /1000 km 16.9

Traffic congestion/1000km 86

Traffic noise/1000km 3

Fertilisation (N02 equ.) 0 -0.697

Ecotoxicity

Resource depletion (MJ) 0

Resources - fossil (MJ) 0

Land Use (m2.a) 0

Environmental damage cost (Krewitt et al. 1997 and Eyres

et al 1997) (max)

Eco-INDICATOR 95 (max)Impact / Flux damage cost GUA méthodology (CBA) (1)

Eco-INDICATOR 95 (min) Environmental damage cost (Krewitt et al. 1997 and Eyres

et al 1997) (min)

Pira International economic valuation

Page 1 of 2

Annex 4 bis Appendix 2 - Moneterisation/Valuation

Global Warming Potential /kg CO2 equ.

CO2

CH4

Acidification

SOx

NOx

Photochemical pollution due to VOCs

O3

Ozone depletion (CFC11)

Toxicity : other emissions to air (SO2 equ.)

CO

Eutrophication kg Phosphate equi.

COD in water

Eutrophication kg P equi.

Winter Smog

Particulates (<10 µm)

SO2

TSP

NOx

Heavy metals (Pb)

Zn

Toxicity : carcinogenic substances

PAH

Dioxines

Arsenic

Cadnium

Chromium

Nickel

Damages to structures (S02)

Disamenity Landfill

Disamenity Incinerator

Traffic accident /1000 km

Traffic congestion/1000km

Traffic noise/1000km

Fertilisation (N02 equ.)

Ecotoxicity

Resource depletion (MJ)

Resources - fossil (MJ)

Land Use (m2.a)

Impact / Flux

0.0014 0.193

0.0041 0.0133

0.0852 0.2933

0.06 0.10 1.860 205

0.01 0.04 0.734 50

20.32 56.67 1 4.459

1.002 1.002

0.010 0.0763

0.0009 3.05

0.712 0.7122

0.00275 9.327217125

7.26 18.27 0.390 29

1.06 2.60

2.13 5.35

0.08 2.31

2.18 247.65 62.00 1571

46.48 281.78 0.3 680

0.00 4.42 12.3 6022

0.00 4654000.00 2000000 19720319

66.67 639.60 6.64 1571

686.67 3510.00 22.14 78571

11933.39 45500.00 128 820

452.67 611.00 7.08 1688

0 0.662

0 0.037

0 0.01

0 16.9

0 86

0 3

-0.697 0

2.18 247.65 0.00 0

0.87 48.92 0 0

0.00 0.14 0 0.000

0.06 0.11 0 0.000

Eco-INDICATOR 99 (min) Not moneterisation!

Eco-INDICATOR 99 (max) Not

moneterisation!

MAX excluding EI 99MIN excluding EI 99

Page 2 of 2

Annex 4 bis Valuation table

Unit Valuation Min MaxGWP (kg CO2 eq.) /kg CO2 0.01344 0.0014 0.19Ozone depletion (kg CFC 11 eq.) /kg CFC11 0.68 0.68 0.68Acidification /kg H+ 8.70 1.9 200Toxicity Carcinogens (Cd equiv) /kg Cadmium (carcinogenic effects only) from electricity production22 22 12000Toxicity Gaseous non carcinogens (SO2 equiv.) /kg SO2 from electricity production 1 0 1Toxicity Metals non carcinogens (Pb equiv.) /kg Pb 62 0 62Toxicity Particulates & aerosols (PM10 equiv) /kg PM10 from electricity production 24 0.39 29Smog (ethylene equiv.) /kg VOC indirect impacts through ozone formation from electricity production0.73 0.73 50Black smoke (kg dust eq.) [damage to structure] /kg smoke 0.66 0 0.66Fertilisation /kg expressed as NO2 mass equivalents -0.7 -0.7 0Traffic accidents (risk equiv.) euro/1000 km travelled on an average road 17 0 17Traffic Congestion (car km equiv.) Euro per 1000 car km equivalents 86 0 86Traffic Noise (car km equiv.) Euro per 1000 car km equivalents 3 0 3Water Quality Eutrophication (P equiv.) /kg P 4.7 0.0028 9.3Disaminity (kg LF waste equiv.) /kg landfill 0.037 0 0.037

Annexes 4-5-6.doc

Page 18 of 18

Annex 5: Employment data –jobs for waste

management activities

Annexes 4-5-6.doc

Page 19 of 19

1 PACKAGING FROM HOUSEHOLD SOURCES

Gross Employment, Landfilling 1 tonne PET bottles

Jobs per 1000 tonne per annum Collection Landfill management / operation Total

High population density 1.2 0.1 1.3


Gross Employment for Landfilling 1 tonne steel packaging




Gross Employment for Landfilling 1 tonne rigid and semi - rigid aluminium packaging




Gross Employment for Landfilling 1 tonne paper & board packaging




Gross Employment for Landfilling 1 tonne Liquid Beverage Cartons




Gross Employment for Landfilling 1 tonne mix plastics packaging




Gross Employment for Landfilling 1 tonne glass




Annexes 4-5-6.doc

Page 20 of 20

Gross Employment for Incineration of 1 tonne PET bottles

Jobs per 1000 tonne per annum Collection Incinerator management / operation Total

High pop. density 1.2 0.27 1.47

Low pop. density 1.15 0.27 1.42

Gross Employment for Incineration of 1 tonne steel packaging




Gross Employment for Incineration of 1 tonne rigid and semi-rigid aluminium packaging




Gross Employment for Incineration of 1 tonne Paper & Board packaging




Gross Employment for Incineration of 1 tonne Liquid Beverage Cartons




Gross Employment for Incineration of 1 tonne mix plastics packaging




Gross Employment for Incineration of 1 tonne glass




Annexes 4-5-6.doc

Gross Employment , kerbside collection and sorting of PET bottles

Jobs per 1000 tonne per annum Collection Sorting Transport from sorting to reprocessing Total

High pop. density 14.7 0.71 0.19 15.6Low pop. density 17.7 0.71 0.19 18.6

Gross Employment , bring scheme collection and sorting of PET bottles

Jobs per 1000 tonne per annum Transport, bring bank to sorting Sorting Transport from sorting to reprocessing Total

High pop. density 3.2 0.71 0.19 4.1

Low pop. density 3.8 0.71 0.19 4.7

Gross Employment , kerbside collection and sorting of steel packaging

Jobs per 1000 tonne per annum Collection Sorting Transport from sorting plant to reprocessor Total

High population density 4.8 0.53 0.1 5.43

Low population density 5.8 0.53 0.1 6.43

Gross Employment , bring scheme collection and sorting of steel packaging


Transport from bring bank to sortingplant

Sorting Transport from sorting plant toreprocessor

Total

High population density 1 0.53 0.1 1.63


Gross Employment , kerbside collection and sorting of rigid and semi-rigid aluminium packaging




Gross Employment , bring scheme collection and sorting of rigid and semi-rigid aluminium

packaging




Total



Gross Employment , kerbside collection and sorting of Paper & Board packaging


High population density 2.6 n.a. 0.03 2.63

Low population density 3.1 n.a. 0.03 3.13

Annexes 4-5-6.doc

Gross Employment , bring scheme collection and sorting of Paper & Board packaging




Total

High population density 0.3 n.a. 0.03 0.33

Low population density 0.4 n.a. 0.03 0.43

Gross Employment , kerbside collection and sorting of Liquid Beverage Cartons (incineration of

rejects)


Collection

Sorting

Transport from sorting plant toreprocessor

incineration of rejects (jobs/1000trejects per annum)

Total


8.4 0.7 0.14 0.07 9.31

Low population density 10.1 0.7 0.14 0.07 11.01

Gross Employment , bring scheme collection and sorting of Liquid Beverage Cartons (incineration

of rejects)

Jobs per 1000 tonneper annum

Transport from bring bank tosorting plant

Sorting


incineration of rejects(jobs/1000t rejectsper annum)

Total

High pop. density 1.8 0.7 0.14 0.07 2.71

Low pop. density 2.2 0.7 0.14 0.07 3.11

Gross Employment , kerbside collection and sorting of Liquid Beverage Cartons (landfilling of

rejects)

Jobs per 1000 tonne of LBCper annum

Collection

Sorting


landfilling of rejects (jobs/1000trejects per annum)

Total

High population density 8.4 0.7 0.14 0.03 9.27

Low population density 10.1 0.7 0.14 0.03 10.97

Gross Employment , bring scheme collection and sorting of Liquid Beverage Cartons (landfilling of

rejects)

Jobs per 1000 tonne ofLBC per annum

Transport from bring bank tosorting plant

Sorting


landfilling of rejects(jobs/1000t rejectsper annum)

Total

High pop. density 1.8 0.7 0.14 0.03 2.67

Low pop. density 2.2 0.7 0.14 0.03 3.07

Gross Employment , bring scheme collection and sorting of Glass (landfilling of rejects)

Jobs per 1000 tonne per annum Transport from bring bank to sorting plant Transport from sorting plant to reprocessor Total



Annexes 4-5-6.doc

2 COMMERCIAL AND INDUSTRIAL CASE STUDIES

Gross Employment, Landfilling 1 tonne C&I films

Collection Landfill management / operation Total

Jobs per 1000 tonne per annum 1.2 0.1 1.3

Gross Employment for Incineration of 1 tonne C&I films

Collection Incinerator management / operation Total


Gross Employment for Recycling of 1 tonne C&I films

Collection Total

Jobs per 1000 tonne per annum 1.2 1.2

Gross Employment, Landfilling 1 tonne C&I corrugated board

Collection Landfill management / operation Total


Gross Employment for Incineration of 1 tonne C&I corrugated board

Collection Incinerator management / operation Total


Gross Employment for Recycling of 1 tonne C&I corrugated board

Collection Total

Jobs per 1000 tonne per annum 1.2 1.2

Annexes 4-5-6.doc

Annex 6: Packaging mix by Member State

Annexes 4-5-6.doc

1 INTRODUCTION

It is assumed that the optimal recycling rate in a Member State is a function of the packaging mix in

that Member State, as some packaging materials/applications will be easier to recycle than others.

Therefore the packaging mix in each Member State must be determined in order to calculate the

Member State’s optimal recycling target.

2 DATA SOURCES AND EXTRAPOLATION RULES

The main data sources are:

§ Member State’s official declarations for 1997 and 1998

§ Data provided by the national compliance schemes (1998-1999-2000)

§ Reports and interview from/of European Material Federations (APME, FEVE)

§ Additional input from local consultants where possible

Where data are missing, extrapolation rules are derived from the report “The Facts: A European

cost/benefit perspective” commissioned by ERRA in 1998, e.g. for the split between industrial &

commercial packaging and household packaging. The following assumptions are made

§ the ratios between industrial and household packaging applications remain unchanged up to

2000

§ the ratios between material applications are the best forecast where no other data is available

§ for industrial packaging, distribution between packaging material applications is assumed to be

the same in the south countries (Italy, Greece, Portugal and Spain)

§ data for 1998 or 1999 provide a reasonable forecast for 2000

Annexes 4-5-6.doc

Member State Source Comment

Austria "Bundesabfallwirtschaftsplan" 1998

Member State declaration, 1998

Data reviewed by the ComplianceScheme

Belgium Fost Plus, 2000

Val-I-Pac, 1999

Data provided and reviewed byCompliance Scheme

Extrapolation from Annual report andinterview

Denmark DEPA = Miljostyrelsen, 1998 Data provided by COWI

Finland PYR, 2000 Data reviewed by the ComplianceScheme

Shops packaging waste are consideredas industrial packaging waste

Extrapolation based on ERRA andAPME reports when no data available.

France Eco-Emballages, 1998 Data reviewed by Eco-emballages

Germany GVM Gesallschaft fürVerpackungsmarktforschung mbH,1998


Greece Forecast for 2000 Data provided by Ecopolis

Ireland National Waste database report 1998,Environmental Protection Agency


Italy CONAI, 2000 Data reviewed by the ComplianceScheme

Luxembourg Valorlux Data reviewed by the ComplianceScheme

The Netherlands Data reviewed by the ComplianceScheme

Portugal Sociedade Ponto Verde, 1999

PLASTVAL, 1999

Data collected by IDOM

Spain ECOEMBALAJES ESPAÑA, S.A

ECOVIDRIO


Data collected by IDOM andinterview of Ecoembes.

Sweden Member State declaration, 1998

Interview of RVF SvenskaRenhållningsverksföreningen, TheSwedish Association of WasteManagement

UK Increasing recovery and recycling ofpackaging waste in the UK TheChallenge Ahead: A forward Look forPlanning Purposes, DETR (versionunder production)

Plastic packaging amount are splitbetween application according toAPME ratios

Data reviewed by the Compliance

Annexes 4-5-6.doc

Annex 6 bis

Year 2000 unit: kt

Material Application

AUT BE DK FI FR DE GK IE IT LU NL PO SP SE UKLDPE films 55 42 51 22 260 384 28 13 261 2 92 24 125 19 273Other 20 49 58 26 470 486 102 39 330 3 163 0 286 21 314total 75 91 109 48 730 870 129 52 591 5 256 24 411 40 587

Wood all appl. 60 168 84 0 1,690 1,969 38 0 2,295 9 379 7 443 0 670Steel all appl. 4 56 11 18 280 654 108 10 223 3 118 20 43 53 217Cardboard all appl. 384 371 314 192 3,100 4,350 403 242 2,875 19 1,128 75 1,627 370 3,373glass all appl. 47 4 0 6 960 88 118 52 60 0 23 22 0 60 350Other all appl. 0 14 0 0 0 0 22 31 0 1 0 4 177 0 40

570 704 518 264 6,760 7,930 818 387 6,043 36 1,905 152 2,702 523 5,237PET bottles 20 44 5 6 250 100 34 11 426 2 67 106 159 19 252LPDE films 24 43 20 17 140 175 25 11 248 2 59 98 130 25 190HDPE bottles 24 18 17 15 100 152 21 9 215 1 51 75 112 22 183other 44 57 21 0 412 201 152 86 420 2 58 10 200 27 459Total 112 162 63 37 902 628 232 117 1,309 7 235 289 601 94 1,084

Steel all appl. 69 80 37 12 350 358 87 21 247 2 92 81 235 9 533Aluminium all appl. 9 14 7 2 36 62 14 8 57 1 10 15 41 8 108Metals Al + steel 81 93.5 44 14 386 421 101 29 304 3 109 96 276 17 641Wood all appl. 9 10 109 0Cardboard all appl. 98 153 121 18 872 978 302 50 1,300 11 447 198 828 150 420

liquid beverage cartons 23 20 0 29 120 209 25 8 10 1 47 12 117 40 51mainly based on plastic 4 3 1 4 18 32 4 1 2 0 7 2 18 6 7mainly based on cardboard 5 5 1 6 28 48 6 2 2 0 11 3 27 9 11mainly based on Al. 3 2 1 0 15 26 3 1 1 1 6 2 15 5 6Total 35 30 3 40 181 315 38 12 15 2 70 18 176 61 75

Glass all appl. 183 330 176 50 2,550 3,512 145 59 2,189 17 436 314 1,523 111 1,848Other all appl. 14 32 19

506 768 416 160 4,901 5,867 818 300 5,227 40 1,291 915 3,423 433 4,068

Material AUT BE DK FI FR DE GK IE IT LU NL PO SP SE UKGlass 230 334 176 56 3,510 3,600 263 111 2,249 17 459 336 1,523 171 2,198Plastic 191 256 173 89 1,650 1,530 365 170 1,902 12 498 315 1,029 140 1,678Paper and board 510 548 436 246 4,120 5,585 735 302 4,187 32 1,633 287 2,598 570 3,855Metals 85 152 56 32 681 1,100 212 40 528 7 226 118 334 75 864Wood 60 168 93 0 1,700 1,969 38 0 2,404 9 379 7 443 0 670Other 0 14 0 0 0 14 22 63 0 1 0 4 196 0 40Total 1,076 1,472 934 423 11,661 13,798 1,635 686 11,270 77 3,195 1,067 6,125 956 9,305

Total Household

composites

Plastics

PlasticsTotal Industrial

Annex 7: Environmental data sources

Environmental data for background systemsLCI data for the environmental analysis has been derived from the following sources:

Data Source CommentsTransportstepsVehicleemissions

“Life Cycle InventoryDevelopment for WasteManagement Operations: WasteTransport and Other VehicleUse”, UK Environment Agency2000

Data collected and reported byLatham S & Mudge G (TransportResearch Laboratory), 1997 asresearch contractors to the UKEnvironment Agency

Electricity andother energies

Calculated from “Life cycleinventories of energy systems”,ETH, Zurich, 1994

Raw materials Various sources including:“Life cycle inventories of energysystems”, ETH, Zurich, 1994

Environmental data related to PET bottles from household sourcesLCI data for the environmental analysis has been derived from the following sources:

Original Data Source CommentsWastemanagementLandfilling ofrigid plastics

Derived from “Life CycleInventory Development forWaste Management Operations:Landfill”, UK EnvironmentAgency 2000

Data collected and reported by RGGregory, AJ Revans & GAttenborough (WS AtkinsConsultants Ltd), 1997 as researchcontractors to the UKEnvironment Agency

Rigid plasticsincineration

RDC and Pira International 2000 Data reworked by P Dobson, PiraInternational, and Bernard deCaevel, RDC from varioussources:“Life Cycle InventoryDevelopment for WasteManagement Operations:Incineration”, UK EnvironmentAgency 2000“Integrated Solid WasteManagement: A Life cycleinventory”, PR White, M Frankeand P Hindle, 1995"Specific processing costs of wastematerials in a MSWcombustionfacility", ir. L.P.M Rijpkema andDr.ir.J.A. Zeevalkink,TNO 1996

MaterialrecyclingSorting Derived from “Life Cycle

Inventory Development forWaste Management Operations:Waste Collection andSeparation”, UK EnvironmentAgency 2000

Data collected and reported by VipPatel (Aspinwall and Co.), 1997 asresearch contractors to the UKEnvironment Agency

Baling Derived from “Life CycleAssessment of PackagingSystems for Beer and SoftDrinks, Disposable PETBottles”, Danish EnvironmentalProtection Agency, 1998

Recycling –Regranulation

“Life Cycle Assessment ofPackaging Systems for Beer andSoft Drinks, Disposable PETBottles”, Danish EnvironmentalProtection Agency, 1998

PET (bottlegrade andamorphous)

"Ecoprofiles of the Europeanplastics industry Report 8:Polyethylene terephthalate",APME, 1995

Environmental data related to Paper & board packaging from householdsources

LCI data for the environmental analysis has been derived from the following sources:Data Source Comments

WastemanagementLandfilling ofpaper



Paperincineration

RDC and Pira International 2000 Data reworked by P Dobson, PiraInternational, and Bernard deCaevel, RDC from varioussources:“Life Cycle InventoryDevelopment for WasteManagement Operations:Incineration”, UK EnvironmentAgency 2000“Integrated Solid WasteManagement: A Life cycleinventory”, PR White, M Frankeand P Hindle, 1995



Data collected and reported by VipPatel (Aspinwall and Co.), 1997 asresearch contractors to theEnvironment Agency

Testlinerproduction

Derived from “EuropeanDatabase for Corrugated BoardLife Cycle Studies”, FEFCO,Groupemont Ondule and KraftInstitute, 1997

Kraftlinerproduction


Environmental data related to corrugated board packaging from industrialsources

LCI data for the environmental analysis has been derived from the following sources:Data Source Comments

WastemanagementLandfilling ofpaper



Paperincineration


MaterialrecyclingTestlinerproduction


Kraftlinerproduction


Environmental data related LDPE films from Commercial and IndustrialSources

LCI data for the environmental analysis has been derived from the following sources:Original Data Source Comments

WastemanagementLandfilling offlexible plastics



LDPE films toincineration


MaterialrecyclingRecyclingprocesses

Derived from: "Recycling andRecovery of Plastics fromPackagings in Domestic Waste",Michael Heyde and MarkusKremer, LCA Documents, Vol 5,1999

Study carried out between 1994and 1995

LLDPE "Ecoprofiles of the Europeanplastics industry Report 8:Polyethylene terephthalate",APME, 1995

LDPE "Ecoprofiles of the Europeanplastics industry Report 8:Polyethylene terephthalate",APME, 1995

Environmental data related Mixed plastics from household sourcesLCI data for the environmental analysis has been derived from the following sources:

Original Data Source CommentsWastemanagementLandfilling ofmixed plastics



Mixed plasticsto incineration


MaterialrecyclingSorting andrecyclingprocesses



Pallisade(assumed to bewoodconstructionmaterial)

“Life cycle inventories of energysystems”, ETH, Zurich, 1994

OtherreprocessingAgglomerationand Blastfurnace



Heating oil “Life cycle inventories of energysystems”, ETH, Zurich, 1994

Environmental data related to Glass beverage bottles from household sourcesLCI data for the environmental analysis has been derived from the following sources:

Original Data Source CommentsWastemanagementLandfilling ofglass



Glass toincineration


MaterialrecyclingRecyclingprocesses andcredit

Derived from “Life CycleInventory Development forWaste Management Operations:Recycling”, UK EnvironmentAgency 2000

Sorting Derived from “Life CycleInventory Development forWaste Management Operations:Waste Collection andSeparation”, UK EnvironmentAgency 2000

Data collected and reported by VipPatel (Aspinwall and Co.), 1997 asresearch contractors to the UKEnvironment AgencyDatacollected and reported by VipPatel (Aspinwall and Co.), 1997 asresearch contractors to theEnvironment Agency

Environmental data related to aluminium beverage, rigid and semi-rigid fromhousehold sources

LCI data for the environmental analysis has been derived from the following sources:Original Data Source Comments

WastemanagementLandfilling ofaluminium



Aluminium toincineration


MaterialrecyclingRecyclingprocesses andvirginproduction

Derived from “EnvironmentalProfile Report for the EuropeanAluminium Industry”, EuropeanAluminium Association, April2000

Sorting andbaling

Derived from “Life CycleInventory Development forWaste Management Operations:Waste Collection andSeparation”, UK EnvironmentAgency 2000


Environmental data related to steel from household sourcesLCI data for the environmental analysis has been derived from the following sources:

Original Data Source CommentsWastemanagementLandfilling ofsteel



Steel toincineration


MaterialrecyclingRecyclingprocesses andvirginproduction

Derived from «Ökobilanzdatenfür Weissblech und ECCS » ;InformationszentrumWeissblech ; October 1995

Sorting andbaling



Environmental data related to LBC from household sourcesLCI data for the environmental analysis has been derived from the following sources:

Original Data Source CommentsWastemanagementLandfilling ofLBC


Data collected and reported by RGGregory, AJ Revans & GAttenborough (WS AtkinsConsultants Ltd), 1997 as researchcontractors to the UKEnvironment AgencyThe data for paper, aluminium andplastic film has been combined torepresent LBC

LBC toincineration

RDC and Pira International 2000 Data reworked by P Dobson, PiraInternational, and Bernard deCaevel, RDC from varioussources:“Life Cycle InventoryDevelopment for WasteManagement Operations:Incineration”, UK EnvironmentAgency 2000“Integrated Solid WasteManagement: A Life cycleinventory”, PR White, M Frankeand P Hindle, 1995The data for paper, aluminium foiland plastic film has beencombined to represent LBC

MaterialrecyclingFibre recyclingprocesses andcredit


Based on comparison of kraftlinerproduction and testliner production

Incineration ofrejects

RDC and Pira International 2000 Data reworked by P Dobson, PiraInternational, and Bernard deCaevel, RDC from varioussources:“Life Cycle InventoryDevelopment for WasteManagement Operations:Incineration”, UK EnvironmentAgency 2000“Integrated Solid WasteManagement: A Life cycleinventory”, PR White, M Frankeand P Hindle, 1995The data for aluminium foil and

plastic film has been combined torepresent LBC

Landfilling ofrejects


The data for aluminium and plasticfilm has been combined torepresent LBC

Sorting andbaling



Environmental Data for Refillable and single tripPET bottles


Original Data Source CommentsMaterialproductionPET Bottlegrade


HDPE "Ecoprofiles of the Europeanplastics industry Report 3:Polyethylene andpolypropolene" , APME, 1993

BottleproductionPreform andbottleproduction

Derived from "Life cycleassessment of PackagingSystems for Beer and SoftDrinks, Refillable PET Bottles",Environment Project No404,Danish EnvironmentalProtection Agency, 1998

CrateproductionCrateproduction andgrinding

"Life cycle assessment ofPackaging Systems for Beer andSoft Drinks, Refillable PETBottles", Environment ProjectNo404, Danish EnvironmentalProtection Agency, 1998

ReuseWashing &filling

"Life cycle assessment ofPackaging Systems for Beer andSoft Drinks, Refillable PETBottles", Environment ProjectNo404, Danish EnvironmentalProtection Agency, 1998

WastemanagementLandfilling ofrigid plastics



Rigid plastics RDC and Pira International 2000 Data reworked by P Dobson, Pira

Caevel, RDC from varioussources:“Life Cycle InventoryDevelopment for WasteManagement Operations:Incineration”, UK EnvironmentAgency 2000“Integrated Solid WasteManagement: A Life cycleinventory”, PR White, M Frankeand P Hindle, 1995




Baling Derived from “Life CycleAssessment of PackagingSystems for Beer and SoftDrinks, Disposable PETBottles”, Danish EnvironmentalProtection Agency, 1998

Recycling –Regranulation

“Life Cycle Assessment ofPackaging Systems for Beer andSoft Drinks, Disposable PETBottles”, Danish EnvironmentalProtection Agency, 1998

PET (bottlegrade andamorphous)


Environmental Data for Refillable and single tripGlass bottles


Original Data Source CommentsMaterialproductionHDPE "Ecoprofiles of the European

plastics industry Report 3:Polyethylene andpolypropolene" , APME, 1993

BottleproductionGlass bottleproduction

Derived from "Vergleichendeokologische bewertung vonanstrichstoffen im baubereich",BUWAL, 1999

Data for 1993-1995

CrateproductionCrateproduction andgrinding

"Life cycle assessment ofPackaging Systems for Beer andSoft Drinks, Refillable GlassBottles", Environment ProjectNo400, Danish EnvironmentalProtection Agency, 1998

ReuseWashing &filling

"Life cycle assessment ofPackaging Systems for Beer andSoft Drinks, Refillable GlassBottles", Environment ProjectNo400, Danish EnvironmentalProtection Agency, 1998

WastemanagementLandfilling ofglass



Glass toincineration

RDC and Pira International 2000 Data reworked by P Dobson, PiraInternational, and Bernard deCaevel, RDC from varioussources:“Life Cycle InventoryDevelopment for WasteManagement Operations:Incineration”, UK Environment

“Integrated Solid WasteManagement: A Life cycleinventory”, PR White, M Frankeand P Hindle, 1995

MaterialrecyclingRecyclingprocesses andcredit

Derived from “Life CycleInventory Development forWaste Management Operations:Recycling”, UK EnvironmentAgency 2000

Sorting Derived from “Life CycleInventory Development forWaste Management Operations:Waste Collection andSeparation”, UK EnvironmentAgency 2000


Annexes 8 - 9.doc

Annex 8 : Current performance of Member States

Annexes 8 - 9.doc

1 METHODOLOGY FOR THE DATA COLLECTION:

♦ Classification of the data per year

♦ Classification of the data (total (MSW + non-MSW)) into production (packaging brought on the

market) and recycling summary tables for individual Member States and for the whole of

Europe

♦ Data were collected for the material classes as detailed as possible (as much sub-divisions

according to material applications as possible)

♦ glass,

♦ plastics,

♦ paper & cardboard,

♦ metals,

♦ composites1 ,

♦ wood,

♦ other packaging materials

This gives the tables shown in Annex 8 bis (for 1997, 1998 and 1999).

1.1 Data of 1997

1.1.1 Introduction

For 1997 a lot of data has been published (by Compliance Scheme) besides the official reporting

from the Member States to the European Commission.

The data reported to the European Commission concern total data per material (quantities brought

on the market, reuse, recycling and recovery data), but not detailed data per material application and

no distinction between household and industrial packaging.

However, Member States are asked to report their data in the official data format, established by the

European Commission. This data format encourages the Member States to fill in data within

divisions of the main material groups (i.e. for PET, PP, PVC,... within the plastics group),

nevertheless on a voluntary basis. The total amounts per material group are obligatory to report.

1 composite means packaging made of different materials and which can not be separated by hand. [Commission

Annexes 8 - 9.doc

This means generally that Member States have only reported the obligatory data, meaning data for

glass, plastics, paper & cardboard and metals. Also obligatory is to report total data for quantities

on the market, total recycling and total recovery (the division in organic recycling, incineration, etc.

is voluntary and thus generally not reported).

Member States are asked to report within 18 months of the end of the relevant year (this means July

1999 was the end date for reporting the data of 1997, and the results of 1998 can be expected in July

2000).

1.1.2 Results

11 countries officially reported to the European Commission (Austria, Belgium, Denmark, Finland,

France, Germany, Italy, Spain, Sweden, the Netherlands and the United Kingdom).

No global data were reported from Luxembourg, Portugal, Greece, Ireland.

Comparable data for these countries were found in other sources, especially in references [2]and

[3]. Those two reports already analysed the 1997 data on packaging and packaging waste and

provided ERRA with summary tables with specific data of household, industrial and total data for

the Member States.

The conclusions of these studies [2], [3] by Price Waterhouse Coopers were:

v Exact data on the amount of waste, packaging waste and recycling is hard to get and

ambitious;

v Data on the amount of waste, packaging waste and recycling is not comparable; due to the

fact that :

v the definitions of packaging and other terms used are interpreted differently and the methods

of data collection and analysis differ

v e.g. for some countries the only information available concerns packaging processed by the

packaging organisations, those amounts have not been corrected to a national level, because of

insufficient information, so it is clear that total amounts of packaging for these countries are

higher (the same is true for recycling amounts)

v e.g. MSW sometimes includes packaging from small businesses, sometimes not

v a potential cause of inaccuracy of data is the inclusion of quantities exported for recycling in

the final recycling results (some countries reported these quantities separately, other not)

v methodologies for recycling and recovery assessment are not reported

Annexes 8 - 9.doc

v it is plausible that national factors influence the amount of packaging placed on the market

and the extent to which it is recycled (factors like Gross Domestic Product, geographical

position, reuse promotion, type of valorisation scheme have to be analysed in more detail to be

able to draw some conclusions)

Other specific data (for 1997) were found in various reports of packaging recovery organisations

and available study reports (see Bibliography).

1.2 Data of 1998 and following years

For some countries global data can be found in (annual) reports from packaging recovery

organisations (Duales System Deutschland for Germany, Altstoff Recycling Austria for Austria,

Sociedade Ponto Verde for Portugal, Valorlux for Luxembourg, …). Also material recycling

organisations publish data on collected and recycled amounts (e.g. Svensk Glasåtervinning for

Sweden, PYR for Finland,…).

Important to notice is that the results reported by the packaging recovery organisations do not

include full country coverage and are sometimes specific for MSW.

Generally, more specific information and data were found through the national (and European)

material federations.

The official data (of 1998) from the Member States available at the European Commission are also

included.

1.3 Summary of the results of the data compilation

v Most data were found for 1997 and 1998

v Exact data on the amount of waste, packaging waste and recycling are hard to get;

v Data on the amount of waste, packaging waste and recycling are not comparable;

v More reliable data are/will be available for 1998 and especially 1999 thanks to the

experiment and the improvement of the calculation methods.

1.4 Sources :

[1], [2], [3], [4], [5], [6], [7], [8], [9], [10]

Evaluation of costs and benefits for the achievement of reuse and recycling targets for the different packaging materials in the frame of the packaging and packaging waste directive 94/62/EC

Total HH + industrial

Material Glass Plastic Paper and board Metals Al Steel composites Wood Other TotalApplication

1997WasteAUT 260 180 666 85 28 50 1269BE 310 208 529.6 120.5 17.2 142 28.8 1356.1DK 202.306 183.43 463.021 58.035 60.782 3.639 971.213FI 52 90 243.5 31 416.5FR 3296 1571 3611 622 290 1679 11069DE 3750.3 1502.1 5447.8 1121.4 87.2 1034.2 1892.2 16.9 13730.7GK 1456IE 452IT 2248 1777 3246 487 1802 9560LU 17.3 7 11.3 2.8 0.68 0.92 80NL 469 611 1449 216 0 2745PO 1050SP 1398.1 1215 2255 340 670.7 5878.8SE 177.4 150 526.5 70 923.9UK 1787.265 1356.019 3034.893 809.093 112.258 696.835 749.476 17.769 7754.515EURecycledAUT 199 36 500 29 8 7 779BE 217.3 52.7 410.6 84.7 5.2 75 845.5DK 124.122 11.249 219 2.17 356.541FI 24.4 9.2 135.6 1.5 170.7FR 1388 102 2276 331 300 4397DE 2797.3 675.3 3193.1 914.9 1040 8620.6GK 180IE 80IT 750 164 1170 25 700 2809LUNL 354 76 941 145 1516PO 32SP 521.5 64.95 1242.4 76.4 60.4 1965.6SE 134.2 21 348 31.8 535UK 441 100 1609 211 27 184 2361EULegend:data EC -MS reports 1997data report PWC review data MS 1997data valorlux : chiffres cléfs only HHdata PWC The facts a European cost/benefit analysis 1998

RDC-Environment and Pira Int.Page 1 of 1 (1997)

Draft report




1998WasteAUT 230 190 510 85 40 60 1115BEDK 176 172 435 55 838FI 55 90 246 33 424FR 3513 1628 4123 681 1696 11641DE 6215.416GKIEIT 2200 1800 4023 511 57 454 2050 10584LU 21 9 28 5 12 77NL 459 491 1633 227 379 3189POSPSE 171 140 570 75 955UK 1889 1316 3015 808 123 7169EURecycledAUT 193.944 40.898 286.55 28.246 7.794 723BEDK 268FI 34.6 9.2 140.4 5 189FR 1576 131 2515 308 305 4835DE 2704.859 600.015 1415.502 418.216 43.343 374.873 344.962 5483.554GKIEIT 810 192 1489 34 7 27 400 2925LU 32NL 385 49 775 176 86 1471POSPSE 143.1 583UK 434.306 115.169 1894.086 161.738 14.517 147.221 170 2775.299EULegend:data EC -MS reports 1998data DSD : annual report 1998, only HH?data ARA: annual report 1998data DSD: press information mass flow verification 1999, only HH?data Swedish Glass recycling Facts 1998data PYR: Finnisch statistics for 1998data Ministery VROM: jaarverslag 1998data Conai: source : European Packaging and waste Law, N°79, July 2000, p.33, 34

RDC-Environment and Pira Int.Page 1 of 1 (1998)

Draft report




1999WasteAUTBEDKFIFRDE 6382

GKIEIT 2249 1850 4105 526 59 467 2404 11134

LUNLPO 261.027 108.9 207.776 44.204 5.574 38.63 2.677 3.536

SPSEUKEURecycledAUT 48.597BEDKFIFRDE 2710 610 1480 359 37 322 391 5909GKIEIT 890 243 1600 57 13 44 910 3700LUNLPOSPSEUKEULegend:data ÖKK Austria: verwertung kunststoff verpackungen 1999data DSD: press information mass flow verification 1999, only HH?data Sociedade Ponto verde : resultados Globais 1999data Conai: source : European Packaging and waste Law, N°79, July 2000, p.33, 34

RDC-Environment and Pira Int.

Page 1 of 1 (1999)

Draft report

Annexes 8 - 9.doc

Annex 9 : Critical factors limiting recycling and reuse

Annexes 8 - 9.doc

1 RECYCLING DIFFICULTIES

The critical factors identified in this section are taken into account in the calculations and the

hypothesis taken for packaging applications when no CBA is performed.

Recycling difficulties can be classified according to technical, economic and marketing constraints.

Marketing constraints can be avoided by specific marketing actions: they mainly depend on the

willingness of the industries.

On the other hand technical and economical constraints are more difficult – or impossible up to now

- to overcome. Technical constraints require R&D investments or increase of collecting, sorting

and/or treatment capacities. Economic constraints are very difficult to control: e.g.: market prices,

internal market barriers.

This paragraph provides a brief description of recycling difficulties and a summary of them. Reuse

recycling difficulties are also described.

1.1 Glass[11], [12], [13]

Especially for glass packaging the consultant identifies factors which are reasonable reasons to limit

recycling from factors which may be valid points but are not really a reason to limit recycling.

“Reasonable” factors are mainly technical and economic limits:

(1) Contamination : the stream quality must be free of contamination (e. g. no china cups),

otherwise the whole load may be rejected by the glass recycler.

(2) Imbalance in colour: the national glass production has to be in agreement with the national

glass consumption. This constraint could be avoided through the development of alternative

end-uses for recycled green glass.

(3) Market price: the low price value of glass hampers international trading and long transport

distance.

Factors which may be valid points recycling limitations but are not really a reason to limit recycling

mainly concern:

• Noise when disposal : it can lead to problems with the disturbance of neighbouring

residential areas

• Human wound : glass is dangerous once broken

Annexes 8 - 9.doc

• Consumers participation : put green glass in clear glass reduces the value of the load or may

cause it to be rejected. In countries where households are charged and recyclables taken away

free of charge, less care is taken to include only recyclable material in recycling collection

containers. Therefore automated processing of waste glass to remove colour and foreign objects

contamination has been more rapidly developed. On the other hand permitted contaminant

levels are set lower than in countries without direct waste disposal charges. This represent one

possibility to avoid this recycling limit.

The consultant concludes that recycling limits exists but could be avoided thanks to communication,

improved maintenance and custom changes.

1.2 Plastics[14], [15], [16]

Plastic applications constitute a very important issue as stakeholders point of view on their

recyclability diverge. The following critical factors were identified:

Technical limits

(a) Contamination

According to the nature of the impurities (surface or embedded contamination, e.g.) washing

can be considered to avoid this difficulty.

Bags containing raw materials may present sufficiently low contamination to be recycled

without difficulties. Contamination of pallet covers (plastic films) depends on the content and

the stock conditions. Recycling is therefore possible according to the contamination level.

(b) Insufficient amount (profitability aspect): throughput of recycling plants must be sufficient

in order to be profitable. The throughout will be dependent on a number of factors, including

available supply and market demand.

(c) Too thin plastic films : the thicker the film, the easier to recycle. This difficulty is linked to

contamination. It is only feasible to remove contamination if the thickness is sufficient.

(d) Nature of the plastics : due to the different molecular construction, practical recycling

depends on the ability to separate them from each other. Moreover, the output market is

different for each plastic type. Generally recycling is only possible if packaging is previously

sorted by material.

(e) (Main) Technical performance and processing difficulties : specific comments on these

subjects, if any, where integrated in the CBA.

Market acceptance

Annexes 8 - 9.doc

(f) Image : Can also be positive. Can be reversed if there are investments to convince the

consumers. Investments can only start if there are enough.

(g) Risk : failures in material performance are more frequent. A severe quality control could

partly overcome this problem, but would increase the cost of recycling.

(h) Minor characteristics (odour, touch and look) : current treatment techniques do not

overcome these problems. If guarantees are offered to consumers concerning the main technical

performance and if the image is improved, this might be overcome. This kind of difficulty could

also be reduced by marketing actions if marketers are convinced they have to help the market to

accept different colours.

(i) Legislative barriers : [[14], p.31]

EU food contact legislation (Pira to provide full reference) prevent the use of recycled plastics

for applications in direct contact with food. This limits the market potential of plastics recyclate

to non-food grade applications However there exist recycling techniques which allow PET

recycling into PET food grade.

(j) Polymer prices – polymer prices are very volatile and it is important it is recognised that the

virgin price can – and does - fall below the total costs associated with the recovery and

recycling of used plastic materials. The demise of many recycling companies is evidence of

this.

The cause of polymer price volatility is:

♦ Inequality in capacity and demand, which is difficult to rectify due to the fact that each new

production unit must be so large

♦ Stock building during a low price situation and stock use during high price situations

exacerbates the situation

♦ Price of virgin is also linked to oil price

However, the cost of collecting and recycling used film remains constant.

Economical reasons

(k) Recycling costs: high collection costs in Europe hinder general introduction of plastics

recycling. Development of sorting machines should reduce collecting and sorting costs and

increase the plastic streams quality.

1.3 Paper and board[17], [18]

Paper and board are widely recycled and not only as packaging waste. The critical factors are the

same for packaging and non packaging applications. They are described hereafter.

Annexes 8 - 9.doc

(1) Recycling close loop lifetime: paper cannot be continuously recycled (max ~4 times)

because the fibres will gradually degrade during the repeated pulping process

(2) Technical properties of the fibre – fibres from different sources (both virgin and recycled)

provide different technical properties. The demands of the end use product and the properties of

the fibres must be compatible. In effect, the end-use application determines the recycled content

that can be incorporated.

(3) Waste packaging composition (intrinsic contamination): paper to be recycled must be

pulpable ⇒ not laminated with plastics, no synthetic glues (⇒ sticky residues), no ink

(formulated to resist dispersion in water) ⇒ design new product for easier recycling

(4) Food contact legislation – food contact laws limit the use of recycled fibre for applications

in direct contact with food.

(5) Contamination : contamination such as fat or organic coming from the packaged product

should be avoided.

(6) Price volatilty and the balance of supply and demand :

Fibre is a global commodity, and the economic feasibility of particular paper and board

recycling activities may be dependent on the price of virgin fibre. Fibre prices are volatile:

♦ Inequality in capacity and demand, which is difficult to rectify due to the fact that each new

production unit is expensive and introduces significant new capacity

♦ Stock building during a low price situation and stock use during high price situations

exacerbates the situation

When the price of virgin fibre is low, then it can be cheaper than the cost of producing

recycled fibre.

1.4 Metals (steel and aluminium)

Identified limits to recycling are technical limits :

(1) Insufficient amount : there is very little aluminium in household waste stream (less than 1%).

Selective collection have to be adapted to local conditions

(2) Contamination : aluminium foils can be contaminated with food.

For both aluminium and steel recycling there is no output markets limits : fluctuating end-use

markets do not limit recycling as for paper. Whatever the price variation, it remains higher than for

other materials.

Annexes 8 - 9.doc

The consultant concludes that there is no technical, economical or marketing limits to recycling for

steel and aluminium packaging which can’t be avoided, except for contaminated aluminium foils.

1.5 Composites2

Packaging made of different material can be found at three different levels:

- compound packaging, where materials are put together with or without mechanical connections

or glue

- complex packaging, where materials are put together with glue or in a more durable manner

- composite packaging, where materials merge together in order to constitute a new material

Compound packaging are favourable to material recycling, while material recycling of complex

packaging can depend on technical and economic constraints. Energy recovery could be encouraged

due to the high calorific value of this latest packaging. [19]

Composite packaging contributes to a small extent to the packaging consumption (and waste).

For composite packaging waste other than liquid beverage cartons, the main difficulty is therefore

the low amount of waste. There are two main recycling route :

- they could be recycled with the main material stream, taking into account the same recycling

difficulties as for the main material recycling scheme

- Energy recovery or chemical recycling are recommended by the author (Sarens).[19].

Different publications [20] of the Alliance for Beverage Cartons and the Environment (ACE)

mentioned the composition of composites and suggest waste management options. No recycling

difficulties such as material separation are mentioned.

The composite beverage carton is made out of 89% paper and 11% PE or can consist of 70% paper,

25% PE and 5% Al.. Composite beverage carton is potentially suitable for different waste

management options:

- recycling: repulping enables the high quality fibre to be recycled, plastic and aluminium are

recovered separately

- energy recovery: high calorific value due to the content of paperboard and PE

- composting/biomethanisation: due to the high organic content of the paper

The consultant concludes that there is no technical constraints to recycle liquid beverage cartons.

Other recycling limits are the same as for the paper and board packaging waste recycling.

2 “Composite” means packaging made of different materials, and which cannot be separated by hand, none exceeding agiven percent by weight, which shall be established in accordance with the procedure laid down in Article 21 of

Annexes 8 - 9.doc

2 SUMMARY OF RECYCLING DIFFICULTIES

The above mentioned critical factors are considered in the definition of the range of recycling rates

considered in the cost benefit analysis. Table 1 shows the identified recycling constraints per

material. They are classified in factors which are reasonable reasons to limit recycling and factors

which may be valid points but are not really a reason to limit recycling.

Table 1 : Summary of the recycling difficulties

Recycling difficulties Glass Plastics Paper/board Metals CompositesCapacity X (X)Output market / market price X Xcontamination X X X (X)imbalance supply-demand X XInsufficient amount of waste X (X) XRecycling lifetime XNature of waste (too thin,…) X X XRecycling costs X

Factors which are not really a reason to limit recycling Noise XHuman wound XInsufficient maintenance XDisposers participation X X X X XColour, odour XResistance to the use of recyclate X

The critical factors identified in this section are taken into account in the calculations and the

hypothesis taken for packaging applications when no CBA is performed.

3 REUSE DIFFICULTIES[21], [22]

Reuse was one of the issue of this study. It is not a priority of the revision but it has to be taken into

account. Therefore a good understanding of its critical factors is essential to tackle the question. As

for recycling it is possible to distinguish between technical and economical constraints. The third

kind of constraints concern consumer convenience.

Economical constraints mainly concern the initial capital investment of re-usable packaging much

higher than for the disposable packaging3 and the on-cost burden of reverse logistics (e.g. transport

3 this is exacerbated if the reusable packaging line replaces a single trip line which has not yet reached the end of its

Annexes 8 - 9.doc

costs) of returning the empty packaging to its point of origin. The latest constraint can be reduced

by the development of European standard such as Europallets. Reuse can in this case happen in the

same geographical area as the use.

Maintenance (washing,…) and repairs can also can be costly and time consuming.

Consumer convenience can influence the reuse rate :

- by the choice between 1-way and reuse and

- by the level of return (the end-user may not return the packaging after use)

While the second point does not seem to be a limit to reuse rate, the first one has to be managed by

the way of communication and design.

Finally, technical limits mainly relate to the quality of reuse packaging and the necessity of an

effective control.

4 SECONDARY EFFECTS OF HIGHER RECYCLING TARGETS

Industry globally accepts efforts as long as they are the same for all competitors in all countries.

But they are opposed to :

ü very expensive systems (control becomes difficult and free riders get a sensible economic

advantage above honest competitors)

ü market decrease for packed products and/or for packaging materials

So the Industry's basic arguments/reasons are :

Reuse targets

ü "Reusable packaging is often less convenient for the consumer : heavier, no volume

reduction for storage at home (it may not be crushed), immobilised assets (deposit)… è the

market (of packed products) decreases.

ü Reuse system might be more expensive (mainly due to management cost of deposit and

returned packaging) è the market (of packed products) decreases."

Recycling targets

ü "Recycled materials compete with virgin materials è market prices and volume of virgin

materials decrease.

ü High cost encourages fraud infringers get a competitive advantage market share

decreases for honest industry"

So, the only basic concern of the industry is, by definition in an open market economy, to

maintain/increase the sales and benefits. So Industry's basic arguments/reasons to resist high targets

Annexes 8 - 9.doc

As industry seeks to reduce their waste management cost, they are inclined to favour energy

recovery (whose cost is supported by the public authorities). This means industry won't try to do

better than the mandatory targets. If industry had to finance all waste management operations (i.e.

also incineration and landfilling), recycling would appear relatively more attractive at their eyes.

This would motivate industry to do more than mandatory, give more confidence in the recycling

chain and so favour investments.

Annex 10: Presentation of the CBA results

1 Steel from household sources

1.1 Scenarios considered

Table 1 summarises the parameters considered for the baseline scenarios modelled.

Table 1 : Scenarios considered for steelPopulationdensity

Selective collection scheme Recyclingrate achieved

MSW waste managementoption

Scenario 1 Low None 0% Landfill

Scenario 2 Low None 0% IncinerationScenario 3 Low None 80% Incineration with slag

recoveryScenario 4 Low Separate kerbside collection 40-60% LandfillScenario 5 Low Separate kerbside collection 40-60% IncinerationScenario 6 Low Separate kerbside collection 88-92% Incineration with slag

recoveryScenario 7 Low Bring scheme 15-21% LandfillScenario 8 Low Bring scheme 15-21% IncinerationScenario 9 Low Bring scheme 83-84% Incineration with slag

recoveryScenario 10 High None 0% LandfillScenario 11 High None 0% IncinerationScenario 12 High None 80% Incineration with slag

recoveryScenario 13 High Separate kerbside collection 40-60% LandfillScenario 14 High Separate kerbside collection 40-60% IncinerationScenario 15 High Separate kerbside collection 88-92% Incineration with slag

recoveryScenario 16 High Bring scheme 15-21% LandfillScenario 17 High Bring scheme 15-21% IncinerationScenario 18 High Bring scheme 83-84% Incineration with slag

recovery

1.2 Results of the cost benefit analysis of steel

Table 2 :Steel – low population density: Internal costs, external costs and total social costs

Collection method N/A N/A N/ARecycling rate 0% 0% 80%

Residual waste management option Landfill Incineration

Incineration with recovery of steel from

slagsExternalities

GWP (kg CO2 eq.) 0,4 0,6 -14,0 -5,3 to -7,0 -5,1 to -6,8 -14,9 to -15,2 -0,8 to -2,5 -0,6 to -2,3 -14,2 to -14,5Ozone depletion (kg CFC 11 eq.) 0,0 0,0 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0

Acidification (Acid equiv.) 0,0 0,1 -0,2 0,0 to -0,1 0,0 to 0,0 -0,2 to -0,2 0,0 to 0,0 0,1 to 0,0 -0,2 to -0,2Toxicity Carcinogens (Cd equiv) 0,0 0,0 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0Toxicity Gaseous (SO2 equiv.) 0,1 0,2 -6,5 -2,6 to -3,4 -2,5 to -3,3 -7,0 to -7,1 -0,4 to -1,1 -0,3 to -1,0 -6,5 to -6,6

Toxicity Metals non carcinogens (Pb equiv.) 0,1 0,0 0,5 0,2 to 0,3 0,2 to 0,3 0,5 to 0,5 0,1 to 0,2 0,1 to 0,2 0,5 to 0,5Toxicity Particulates & aerosols (PM10 equiv) 9,2 8,8 13,0 14,8 to 16,4 14,5 to 16,2 17,2 to 18,5 9,3 to 9,3 8,9 to 8,9 12,7 to 12,4

Toxicity Smog (ethylene equiv.) 0,3 0,2 -0,4 0,2 to 0,1 0,2 to 0,1 -0,2 to -0,2 0,2 to 0,2 0,2 to 0,2 -0,3 to -0,3Black smoke (kg dust eq.) 0,2 0,3 -0,7 -0,1 to -0,3 -0,1 to -0,2 -0,8 to -0,8 0,1 to 0,0 0,2 to 0,1 -0,7 to -0,7

Fertilisation -0,1 -0,1 0,5 0,1 to 0,1 0,1 to 0,1 0,5 to 0,5 -0,1 to 0,0 -0,1 to 0,0 0,5 to 0,5Traffic accidents (risk equiv.) 0,1 0,1 0,6 0,4 to 0,5 0,4 to 0,5 0,8 to 0,8 0,6 to 1,2 0,6 to 1,2 1,0 to 1,6

Traffic Congestion (car km equiv.) 0,1 0,1 11,1 1,3 to 1,7 1,4 to 1,7 8,7 to 8,0 0,4 to 0,8 0,4 to 0,8 10,6 to 9,9Traffic Noise (car km equiv.) 0,4 0,4 1,1 1,5 to 1,8 1,5 to 1,8 2,0 to 2,2 0,6 to 0,8 0,6 to 0,8 1,3 to 1,4

Water Quality Eutrophication (P equiv.) 0,0 0,0 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0Disaminity (kg LF waste equiv.) 37,0 10,1 10,1 24,8 to 21,1 6,8 to 5,8 6,8 to 5,8 34,4 to 30,7 9,4 to 8,4 9,4 to 8,4

TOTAL EXTERNALITIES 47,8 21,0 15,1 35,3 to 31,5 17,3 to 16,2 13,4 to 12,9 44,4 to 39,6 19,4 to 17,3 14,0 to 12,5INTERNAL COSTS 112,2 141,4 93,4 133,2 to 143,8 150,8 to 155,4 122,0 to 136,2 116,9 to 118,8 141,7 to 141,8 100,9 to 103,9TOTAL SOCIAL COSTS 160,0 162,4 108,5 168,5 to 175,2 168,0 to 171,6 135,3 to 149,1 161,3 to 158,4 161,2 to 159,1 114,9 to 116,4

Bring scheme15-21%

Landfill

Separate kerbside

collection40-60

Incineration

Separate kerbside

collection88-92%


slags

Bring scheme15-21

Incineration


40-60%

Landfill

Bring scheme83-84%


slags

Table 3 : Steel – high population density: Internal costs, external costs and total social costs

Collection method N/A N/A N/ARecycling rate 0% 0% 80%



slagsExeternalities

GWP (kg CO2 eq.) 0,3 0,5 -14,8 -3,4 to -4,8 -3,2 to -4,7 -14,6 to -14,6 -0,7 to -1,6 -0,4 to -1,3 -14,9 to -15,1Ozone depletion (kg CFC 11 eq.) 0,0 0,0 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0

Acidification (Acid equiv.) 0,0 0,1 -0,2 0,0 to -0,1 0,0 to 0,0 -0,2 to -0,2 0,0 to 0,0 0,0 to 0,0 -0,2 to -0,2Toxicity Carcinogens (Cd equiv) 0,0 0,0 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0Toxicity Gaseous (SO2 equiv.) 0,1 0,2 -6,7 -1,6 to -2,2 -1,5 to -2,2 -6,6 to -6,6 -0,3 to -0,7 -0,2 to -0,6 -6,7 to -6,8

Toxicity Metals non carcinogens (Pb equiv.) 0,1 0,0 0,5 0,2 to 0,2 0,1 to 0,2 0,5 to 0,5 0,1 to 0,1 0,1 to 0,1 0,5 to 0,5Toxicity Particulates & aerosols (PM10 equiv) 8,0 7,5 -7,3 8,8 to 9,1 8,5 to 8,8 -2,6 to -0,8 7,4 to 6,9 7,0 to 6,5 -7,0 to -6,8

Toxicity Smog (ethylene equiv.) 0,2 0,2 -0,7 0,0 to 0,0 0,0 to -0,1 -0,7 to -0,6 0,1 to 0,1 0,1 to 0,1 -0,7 to -0,7Black smoke (kg dust eq.) 0,2 0,2 -0,9 -0,1 to -0,2 0,0 to -0,1 -0,9 to -0,9 0,1 to 0,0 0,2 to 0,1 -0,9 to -0,9

Fertilisation -0,1 -0,1 0,7 0,1 to 0,1 0,1 to 0,1 0,7 to 0,6 0,0 to 0,0 0,0 to 0,0 0,7 to 0,7Traffic accidents (risk equiv.) 0,2 0,2 0,3 0,4 to 0,5 0,4 to 0,5 0,5 to 0,6 0,3 to 0,4 0,3 to 0,4 0,4 to 0,5


Water Quality Eutrophication (P equiv.) 0,0 0,0 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0Disaminity (kg LF waste equiv.) 37,0 10,1 10,1 27,8 to 24,1 7,6 to 6,6 7,6 to 6,6 35,2 to 33,3 9,6 to 9,1 9,6 to 9,1

TOTAL EXTERNALITIES 54,2 27,3 -8,1 52,9 to 52,4 32,7 to 34,9 6,2 to 11,9 54,4 to 54,7 28,9 to 30,5 -4,7 to -1,4INTERNAL COSTS 132,0 161,2 113,2 138,3 to 141,5 155,8 to 153,2 127,0 to 134,0 131,5 to 131,3 156,3 to 154,4 115,5 to 116,5TOTAL SOCIAL COSTS 186,2 188,5 105,1 191,2 to 193,9 188,6 to 188,1 133,2 to 145,9 185,9 to 186,0 185,2 to 184,8 110,8 to 115,1

Bring scheme83-84%


slags

Bring scheme15-21%

Incineration


40-60%

Landfill

Bring scheme15-21%

Landfill

Separate kerbside

collection40-60%

Incineration

Separate kerbside

collection88-92%


slags

Graph 1 : Steel – low population density: Total social costs

Steel - Low PopulationTotal Social Cost

020406080

100120140160180200

L a n d f i l l Incineration Incineration

w i th s tee l

r e c o v e r y

Separate

kerbs ide

collection /

L a n d f i l l

Separate

kerbs ide

collection /

Incineration

Separate

kerbs ide

collection /

Incineration

w i th s tee l

r e c o v e r y

Br ing scheme

/ Landfill

Br ing scheme

/ Incineration

Br ing scheme

/ Incineration

w i th s tee l

r e c o v e r y

Scenario

To

tal S

oci

al C

ost

Graph 2 : Steel – high population density: Total social costs

Steel - High Population DensityTotal Social Cost

0

50

100

150

200

250


collection /Landfill

Bringscheme /Landfill


collection /Incineration

Bringscheme /

Incineration

Incinerationwith steelrecovery

Separatekerbside

collection /Incinerationwith steelrecovery

Bringscheme /


Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

1.3 Main findings:

For low population density:♦ From total social cost perspective, where landfilling is the MSW option, a bring scheme achieving a

recycling rate of 7-17% is the optimum system from the scenarios considered. (Although the differencebetween all scenarios is very small).

♦ From total social cost perspective, where incineration with energy recovery but no slag recovery is theMSW option, a bring scheme achieving a recycling rate of 7-17% is the optimum system from thescenarios considered.

♦ From total social cost perspective, where incineration with energy recovery and slag recovery is the MSWoption, 100% incineration with recycling of steel recovered from slags is the optimum system for thescenarios considered.

For high population density:♦ From total social cost perspective, where landfilling is the MSW option, 100% landfilling is the optimum

system (although the difference between the systems is very small)♦ From total social cost perspective, where incineration with energy recovery but no slag recovery is the

MSW option, there is no distinction between 100% incineration and a bring scheme achieving a recyclingrate of 5-10% as the optimum system from the scenarios considered.

♦ From total social cost perspective, where incineration with energy recovery and slag recovery is the MSWoption, 100% incineration with recycling of steel recovered from slags is the optimum system for thescenarios considered.

1.4 Sensitivity analysis

1.4.1 Methodological choices1.4.1.1 Choice of external valuationsGraph 3 & Graph 4 show the sensitivity of the analysis to the economic valuations applied to the definedenvironmental impacts. The graph has been produced by considering the same environmental impact results,but applying different impact assessment valuations (see Annex 4 for a list of maximum and minimumvaluations applied).

Graph 3 & Graph 4 show that the results achieved and conclusions drawn are highly dependent upon theeconomic valuations applied to the environmental impacts. Applying the full range of available economicvaluations makes it impossible to distinguish an optimum system from the scenarios studied.

Graph 3 : Steel – low population density: Sensitivity of the results to the external economic valuations applied

Steel - Low PopulationSensitivity analysis on variations in economic valuations applied

-150.0-100.0-50.0

0.050.0

100.0

150.0200.0250.0

Landfill Incineration Incinerationwith steelrecovery

Separatekerbside


Separatekerbside


Separatekerbside



Bringscheme /

Incineration

Bringscheme /


Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

Graph 4 : Steel – high population density: Sensitivity of the results to the external economic valuationsapplied

Steel - High Population DensitySensitivity analysis on variations in economic valuations applied

-150

-100

-50

0

50

100

150

200

250



Bring scheme /Landfill



Bring scheme /Incineration


Separatekerbside


Bring scheme /Incinerationwith steelrecovery

Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

1.4.1.2 Internal costsThe internal costs applied in this study have been sourced mostly from the UK, France and Belgium. Evenwhere equivalent waste management practices are compared internal costs can vary considerably betweenMember States, depending on a range of factors such as cost of living and geographical considerations(mountainous regions, island populations, etc.). In this part of the sensitivity analysis, the effect on the resultsof considering a +/-20% variation in internal costs is investigated. The results are presented in Graph 5 &Graph 6.

The graphs show that the results achieved and conclusions drawn are highly dependent upon the internal costsapplied. Applying a range of +/-20% to the internal costs makes it impossible to distinguish an optimumsystem from the scenarios studied.

Graph 5 : Steel – low population density: Sensitivity of the results to the internal economic costs considered

Steel - Low PopulationSensitivity analysis on variations in Internal Costs

0

50

100

150

200

250



Bring scheme/ Landfill



Bring scheme/ Incineration


Separatekerbside


Bring scheme/ Incineration

with steelrecovery

Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

Graph 6 : Steel – high population density: Sensitivity of the results to the internal economic costs considered

Steel - High Population DensitySensitivity analysis on variations in Internal Costs

0

50

100

150

200

250








Separatekerbside


Bring scheme /Incinerationwith steelrecovery

Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

1.4.1.3 Inclusion of employment as an impact category

Graph 7 & Graph 8 show the sensitivity of the analysis to the inclusion of employment as an impact category.The graphs have been produced by including employment along with the other environmental impacts used inthe baseline analysis.

Graph 7 : Steel – low pop. density: Sensitivity of the results to the addition of employment as an impactcategory

Steel - Low PopulationTotal Social Cost

0.020.040.060.080.0

100.0120.0140.0160.0180.0

Landfill Incineration Incinerationwith steelrecovery

Separatekerbside


Separatekerbside


Separatekerbside



Bringscheme /

Incineration

Bringscheme /


Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

Graph 8 : Steel – high pop. density: Sensitivity of the results to the addition of employment as an impactcategory

Steel - High Population DensityTotal Social Cost

020406080

100120140160180200






Bringscheme /

Incineration


Separatekerbside


Bringscheme /


Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

The following implications of including employment should be considered:For low population density:♦ From total social cost perspective, where landfill is the MSW option it is no longer possible to distinguish

between the scenarios♦ From total social cost perspective, where incineration with energy recovery but no slag recovery is the

MSW option it is no longer possible to distinguish between the scenarios♦ From total social cost perspective, where incineration with energy recovery and slag recovery is the MSW

option, it is not possible to distinguish between 100% incineration with recycling of steel recovered fromslags or a bring scheme achieving 7-17% recycling as the optimum system for the scenarios considered.

For high population density:♦ From total social cost perspective, where landfilling is the MSW option, it is no longer possible to

distinguish between the scenarios♦ From total social cost perspective, where incineration with energy recovery but no slag recovery is the

MSW option it is no longer possible to distinguish between the scenarios♦ From total social cost perspective, where incineration with energy recovery and slag recovery is the MSW

option, it is not possible to distinguish between 100% incineration with recycling of steel recovered fromslags or a bring scheme achieving 5-10% recycling as the optimum system for the scenarios considered.

1.4.2 Scenario and modelling choices

Findings from the sensitivity analysis of scenario and modelling choices are summarised in Table 4.

Table 4 : Summary of sensitivity analysis of scenario and modelling choices for steelParameter investigated Influence on CBA results Influence on conclusions drawnIncineration model

Combined heat and powerNo significant effect on scale ofCBA results

No effect on choice of optimumscenario

Incineration modelOffset electricity

No significant effect on scale ofCBA results

No effect on choice of optimumscenario

Transport distancesMSW collection round

Kerbside collection roundCollection from bring bank


Transport assumptions made canhave significant influence on therelative standing of results.

Considering best and worst casesfor each scenario makes itimpossible to determine anoptimum system for each set ofconditions

Transport distanceConsumer transport to bring

bank

Consumer transport assumptionscritical to relative standing of thebring scheme scenario

Alternative assumptions wouldaffect the choice of optimumscenario

2 Aluminium cans


The table below summarises the parameters considered for the baseline scenarios modelled.

Table 5 : Scenarios considered for aluminium cansPopulationdensity

Selective collection scheme Recycling rateachieved

MSW waste management option

Scenario 1 Low None 0% LandfillScenario 2 Low None 0% IncinerationScenario 3 Low None 76% Incineration with slag recoveryScenario 4 Low Separate kerbside collection 45-55% LandfillScenario 5 Low Separate kerbside collection 45-55% IncinerationScenario 6 Low Separate kerbside collection 87-89% Incineration with slag recoveryScenario 7 Low Bring scheme 31-41% LandfillScenario 8 Low Bring scheme 31-41% IncinerationScenario 9 Low Bring scheme 83-86% Incineration with slag recoveryScenario 10 High None 0% LandfillScenario 11 High None 0% IncinerationScenario 12 High None 76% Incineration with slag recoveryScenario 13 High Separate kerbside collection 45-55% LandfillScenario 14 High Separate kerbside collection 45-55% IncinerationScenario 15 High Separate kerbside collection 87-89% Incineration with slag recoveryScenario 16 High Bring scheme 31-41% LandfillScenario 17 High Bring scheme 31-41% IncinerationScenario 18 High Bring scheme 83-86% Incineration with slag recovery

2.2 Results of the cost benefit analysis for aluminium cans

This section presents and discusses the results of the cost benefit analysis for aluminium cans.

Table 6 : Aluminium cans - low population density: Internal costs, external costs and total social costs

Collection method N/A N/A N/A Separate Kerbsidecollection

Separate kerbsidecollection


Bring scheme Bring scheme Bring scheme

Recycling rate 0,0 0,0 80% 45-55% 45-55% 87-89% 31-41% 31-41% 83-86%Residual waste management option Landfill Inciner

ationIncinerati

on withnodule

recovery

Landfill Incineration Incineration withnodule recovery


ExeternalitiesGWP (kg CO2 eq.) 0,4 1,0 -95,5 -55,9 to -68,4 -55,5 to -68,1 -108,6 to -111,5 -38,4 to -50,9 -37,9 to -50,5 -104,5 to -107,5

Ozone depletion (kg CFC 11 eq.) 0,0 0,0 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0Acidification (Acid equiv.) 0,0 0,1 -13,1 -7,7 to -9,4 -7,7 to -9,4 -14,9 to -15,4 -5,3 to -7,0 -5,2 to -7,0 -14,3 to -14,8

Toxicity Carcinogens (Cd equiv) 0,0 0,0 -19,3 -11,4 to -13,9 -11,4 to -13,9 -22,0 to -22,6 -7,9 to -10,4 -7,9 to -10,4 -21,2 to -21,8

Toxicity Gaseous (SO2 equiv.) 0,1 0,3 -79,6 -47,0 to -57,5 -46,9 to -57,4 -90,8 to -93,3 -32,0 to -42,3 -31,9 to -42,2 -87,0 to -89,4Toxicity Metals non carcinogens (Pb equiv.) 0,1 0,1 -337,7 -199.9 to -244,4 -199,9 to -244,4 -385,7 to -396,4 -137,6 to -182,1 -137,7 to -182,1 -370,7 to -381,4

Toxicity Particulates & aerosols (PM10 equiv) 9,7 10,5 -550,4 -306.7 to -377,0 -306,2 to -376,6 -614,7 to -629,0 -213,4 to -285,3 -212,8 to -284,8 -599,8 to -615,8Toxicity Smog (ethylene equiv.) 0,3 0,3 -18,0 -10,2 to -12,5 -10,2 to -12,5 -20,2 to -20,7 -6,9 to -9,2 -6,9 to -9,2 -19,5 to -20,0

Black smoke (kg dust eq.) 0,2 0,4 -43,0 -25,3 to -31,0 -25,2 to -30,9 -49,1 to -50,5 -17,3 to -23,0 -17,2 to -22,9 -47,2 to -48,5



Water Quality Eutrophication (P equiv.) 0,0 0,0 -1,0 -0,6 to -0,7 -0,6 to -0,7 -1,1 to -1,1 -0,4 to -0,5 -0,4 to -0,5 -1,1 to -1,1

Disaminity (kg LF waste equiv.) 37,0 10,1 10,1 20,4 to 16,7 5,6 to 4,6 5,6 to 4,6 25,5 to 21,8 7,0 to 6,0 7,0 to 6,0TOTAL EXTERNALITIES 48,3 23,4 -1124,4 -628,5 to -778,9 -642,3 to -790,2 -1273,5 to -1306,6 -421,2 to -572,7 -438,4 to -587,4 -1230,3 to -1264,5INTERNAL COSTS 555,0 453,0 88,0 541,0 to 537,9 484,9 to 492,0 336,5 to 327,7 531,3 to 523,6 460,9 to 463,4 209,0 to 248,1TOTAL SOCIAL COSTS 603,3 476,4 -1036,4 -87,5 to -241,0 -157,3 to -298,2 -937,0 to -978,9 110,1 to -49,1 22,5 to -124,0 -1021,3 to -1016,5

Table 7 : Aluminium cans – high population density: Internal costs, external costs and total social costs

Collection method N/A N/A N/A Separate Kerbsidecollection



Bring scheme Bring scheme Bring scheme

Recycling rate 0,0 0,0 80% 45-55% 45-55% 87-89% 31-41% 31-41% 83-86%Residual waste management option Landfill Inciner

ationIncinerati

on withnodule

recovery



Externalities

GWP (kg CO2 eq.) 0,3 0,9 -95,9 -56,4 to -69,0 -56,1 to -68,8 -109,3 to -112,3 -38,8 to -51,4 -38,4 to -51,1 -105,2 to -108,2


Toxicity Carcinogens (Cd equiv) 0,0 0,0 -19,3 -11,4 to -14,0 -11,4 to -13,9 -22,0 to -22,6 -7,9 to -10,4 -7,9 to -10,4 -21,2 to -21,8Toxicity Gaseous (SO2 equiv.) 0,1 0,3 -79,7 -47,1 to -57,6 -47,0 to -57,5 -91,0 to -93,5 -32,3 to -42,7 -32,1 to -42,6 -87,3 to -89,8

Toxicity Metals non carcinogens (Pb equiv.) 0,1 0,1 -337,7 -199,9 to -244,4 -199,9 to -244,4 -385,7 to -396,4 -137,7 to -182,1 -137,7 to -182,1 -370,8 to -381,4

Toxicity Particulates & aerosols (PM10 equiv) 8,4 9,2 -563,9 -312,8 to -384,2 -312,3 to -383,8 -627,5 to -641,7 -218,1 to -291,1 -217,5 to -290,6 -612,9 to -628,7Toxicity Smog (ethylene equiv.) 0,2 0,2 -18,2 -10,5 to -12,9 -10,5 to -12,9 -20,6 to -21,1 -7,2 to -9,5 -7,2 to -9,5 -19,9 to -20,4

Black smoke (kg dust eq.) 0,2 0,4 -43,1 -25,5 to -31,2 -25,4 to -31,1 -49,3 to -50,7 -17,5 to -23,2 -17,3 to -23,1 -47,4 to -48,7Fertilisation -0,1 -0,1 10,7 6,2 to 7,6 6,2 to 7,6 12,1 to 12,4 4,2 to 5,6 4,2 to 5,6 11,7 to 12,0

Traffic accidents (risk equiv.) 0,2 0,2 0,6 1,0 to 1,2 1,0 to 1,2 1,2 to 1,4 1,1 to 1,5 1,1 to 1,5 1,5 to 1,7


Water Quality Eutrophication (P equiv.) 0,0 0,0 -1,0 -0,6 to -0,7 -0,6 to -0,7 -1,1 to -1,1 -0,4 to -0,5 -0,4 to -0,5 -1,1 to -1,1Disaminity (kg LF waste equiv.) 37,0 10,1 10,1 20,4 to 16,7 5,6 to 4,6 5,6 to 4,6 25,5 to 21,8 7,0 to 6,0 7,0 to 6,0

TOTAL EXTERNALITIES 54,7 29,7 -1130,7 -601,9 to -747,8 -615,6 to -759,0 -1253,9 to -1281,2 -398,4 to -544,6 -415,6 to -559,3 -1216,3 to -1244,0INTERNAL COSTS 665,0 563,0 198,0 585,2 to 567,4 529,1 to 521,5 377,1 to 357,3 597,3 to 575,5 526,9 to 515,3 275,1 to 300,0TOTAL SOCIAL COSTS 719,7 592,7 -932,7 -16,7 to -180,4 -86,6 to -237,5 -876,8 to -923,9 198,9 to 30,9 111,3 to -44,0 -941,2 to -944,0

Graph 9 : Aluminium cans – low population density: Total social cost

Aluminium cans - Low Population DensityTotal Social Cost

-1200-1000

-800-600-400-200

0200400600800







Incinerationwith recovery

Separatekerbside


with recovery


with recovery

Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

Graph 10 : Aluminium cans – high population density: Total social cost

Aluminium cans - High Population DensityTotal Social Cost

-1200-1000-800-600-400-200

0200400600800

1000







Incinerationwith recovery

Separatekerbside


with recovery


with recovery

Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

2.3 Main findings:

For low population density:♦ From total social cost perspective, where landfilling is the MSW option, a separate kerbside

collection scheme achieving a recycling rate of 45-55% is the optimum system from the scenariosconsidered.

♦ From total social cost perspective, where incineration with energy recovery but no slag recovery isthe MSW option a separate kerbside collection scheme achieving a recycling rate of 45-55% is theoptimum system from the scenarios considered.

♦ From total social cost perspective, where incineration with energy recovery and slag recovery isthe MSW option, 100% incineration with recycling of aluminium recovered from slags is theoptimum system for the scenarios considered.

For high population density:♦ From total social cost perspective, where landfilling is the MSW option, a separate kerbside

collection scheme achieving a recycling rate of 45-55% is the optimum system from the scenariosconsidered.

♦ From total social cost perspective, where incineration with energy recovery but no slag recovery isthe MSW option a separate kerbside collection scheme achieving a recycling rate of 45-55% is theoptimum system from the scenarios considered.

♦ From total social cost perspective, where incineration with energy recovery and slag recovery isthe MSW option, a bring scheme achieving a recycling rate of 31-41% is the optimum system forthe scenarios considered.


2.4.1 Methodological choices2.4.1.1 Choice of external valuationsThe graph below shows the sensitivity of the analysis to the economic valuations applied to the definedenvironmental impacts. The graph has been produced by considering the same environmental impactresults, but applying different impact assessment valuations (see Annex 4 for a list of maximum andminimum valuations applied).

For low population density, the graphs show when the full range of economic valuations is appliedwhere landfill is the MSW option it is no longer possible to distinguish between separate kerbsidecollection achieving 45-55% recycling and a bring scheme achieving 31-41% as the optimal systemfrom those considered.

Where incineration with energy recovery but no recovery of slags is the MSW option it is no longerpossible to distinguish between separate kerbside collection achieving 45-55% recycling and a bringscheme achieving 31-41% as the optimal system from those considered. that for low populationdensity.

Where incineration with slag recovery is the MSW option, it is not possible to distinguish between theoptions considered.

For high population density, when the full range of economic valuations is applied where landfill isthe MSW option it is no longer possible to distinguish between separate kerbside collection achieving45-55% recycling and a bring scheme achieving 31-41% as the optimal system from those considered.

Where incineration with energy recovery but no recovery of slags is the MSW option it is no longerpossible to distinguish between separate kerbside collection achieving 45-55% recycling and a bringscheme achieving 31-41% as the optimal system from those considered.

Where incineration with slag recovery is the MSW option, it is not possible to distinguish between theoptions considered.

Graph 11 : Aluminium cans – low population density: Sensitivity of results to the external economicvaluations applied

Aluminium cans - Low Population DensitySensitivity analysis on variations in economic valuations applied

-18000

-16000

-14000

-12000

-10000

-8000

-6000

-4000

-2000

0

2000



Bringscheme /

landfill



Bringscheme /

incineration

Incinerationwith

recovery

Separatekerbside


withrecovery

Bringscheme /

incinerationwith

recovery

Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

Graph 12 : Aluminium cans – high population density: Sensitivity of results to the external economicvaluations applied

Aluminium cans - High Population DensitySensitivity analysis on variations in economic valuations applied

-18000

-16000

-14000

-12000

-10000

-8000

-6000

-4000

-2000

0

2000



Bringscheme /

landfill



Bringscheme /

incineration

Incinerationwith

recovery

Separatekerbside


withrecovery

Bringscheme /

incinerationwith

recovery

Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

2.4.1.2 Internal costsThe internal costs applied in this study have been sourced mostly from the UK, France and Belgium.Even where equivalent waste management practices are compared internal costs can vary considerablybetween Member States, depending on a range of factors such as cost of living and geographicalconsiderations (mountainous regions, island populations, etc.). In this part of the sensitivity analysis,the effect on the results of considering a +/-20% variation in internal costs is investigated. The resultsare presented in the graph below.

For low population density where landfill is the MSW option, it is no longer possible to distinguishbetween separate kerbside collection achieving 45-55% recycling and a bring scheme achieving 31-41% as the optimal system from those considered.

Where incineration with energy recovery but no slag recovery is the MSW option, the results are notsensitive to variations in the internal costs.

Where incineration with energy recovery and slag recovery is the MSW option it is not possible todistinguish between the options considered when variations in internal costs are taken into account.

For high population density, where landfill is the MSW option, it is no longer possible to distinguishbetween separate kerbside collection achieving 45-55% recycling and a bring scheme achieving 31-41% as the optimal system from those considered.

Where incineration with energy recovery but no slag recovery is the MSW option, the results are notsensitive to variations in the internal costs.

Where incineration with energy recovery and slag recovery is the MSW option it is not possible todistinguish between the options considered when variations in internal costs are taken into account.

Graph 13 : Aluminium cans – low population density: Sensitivity of the results to the internaleconomic costs considered

Aluminium cans - Low Population DensitySensitivity analysis on variations in Internal Costs

-1200.0-1000.0-800.0-600.0-400.0-200.0

0.0200.0400.0600.0800.0

1000.0

Landfill Incineration Incinerationwith

recovery

Separatekerbside


Separatekerbside


Separatekerbside


withrecovery

Bringscheme /

landfill

Bringscheme /

incineration

Bringscheme /

incinerationwith

recoveryScenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

Graph 14 : Aluminium cans – high population density: Sensitivity of the results to the internaleconomic costs considered

Aluminium cans - High Population DensitySensitivity analysis on variations in Internal Costs

-1500.0

-1000.0

-500.0

0.0

500.0

1000.0


recovery

Separatekerbside


Separatekerbside


Separatekerbside


withrecovery

Bringscheme /

landfill

Bringscheme /

incineration

Bringscheme /

incinerationwith

recovery

Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)


The graph below shows the sensitivity of the analysis to the inclusion of employment as an impactcategory. The graph has been produced by including employment along with the other environmentalimpacts used in the baseline analysis.

The graphs show that the results achieved and conclusions drawn are not sensitive to the inclusion ofthis parameter as an external impact category.

Graph 15 : Aluminium cans – low population density: Sensitivity of the results to the addition ofemployment as an impact category

Aluminium cans - low population densityTotal Social Cost when including employment as an impact category

-1200

-1000

-800

-600

-400

-200

0

200

400

600

800


recovery

Separatekerbside


Separatekerbside


Separatekerbside


withrecovery

Bringscheme /

landfill

Bringscheme /

incineration

Bringscheme /

incinerationwith

recoveryScenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

Graph 16 : Aluminium cans – high population density: Sensitivity of the results to the addition ofemployment as an impact category

Aluminium cans - high population densityTotal Social Cost when including employment as an impact category

-1200-1000-800-600-400-200

0200400600800


recovery

Separatekerbside


Separatekerbside


Separatekerbside


withrecovery

Bringscheme /

landfill

Bringscheme /

incineration

Bringscheme /

incinerationwith

recovery

Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)


Findings from the sensitivity analysis of scenario and modelling choices are summarised in the tablebelow.

Table 8 : Summary of sensitivity analysis of scenario and modelling choices for aluminium cansParameter investigated Influence on CBA results Influence on conclusions drawnIncineration model

Combined heat and powerNo significant effect on scale ofCBA results

No influence on choice ofoptimal scenario


No significant effect on scale ofCBA results





No influence on the relativestanding of options



bankNo influence on the relativestanding of options


3 Aluminium (other rigid and semi-rigid aluminium packaging,excluding beverage cans)



Table 9 : Scenarios considered for aluminium (other rigid than beverage cans)Populationdensity


MSW waste managementoption

Scenario 1 Low None 0% LandfillScenario 2 Low None 0% IncinerationScenario 3 Low None 0% Incineration with slag

recoveryScenario 4 Low Separate kerbside collection 7-17% LandfillScenario 5 Low Separate kerbside collection 7-17% IncinerationScenario 6 Low Separate kerbside collection 7-17% Incineration with slag

recoveryScenario 7 Low Bring scheme 3-10% LandfillScenario 8 Low Bring scheme 3-10% IncinerationScenario 9 Low Bring scheme 3-10% Incineration with slag

recoveryScenario 10 High None 0% LandfillScenario 11 High None 0% IncinerationScenario 12 High None 0% Incineration with slag

recoveryScenario 13 High Separate kerbside collection 6-16% LandfillScenario 14 High Separate kerbside collection 6-16% IncinerationScenario 15 High Separate kerbside collection 6-16% Incineration with slag

recoveryScenario 16 High Bring scheme 3-8% LandfillScenario 17 High Bring scheme 3-8% IncinerationScenario 18 High Bring scheme 3-8% Incineration with slag

recovery

3.2 Results of the cost benefit analysis for aluminium

Table 10 : Aluminium – low population density: Internal costs, external costs and total social costs

Collection method N/A N/A N/ARecycling rate 0,0 0,0 0,0


Incineration with slag recovery




Toxicity Metals non carcinogens (Pb equiv.) 0,1 0,1 -279,9 -31,0 to -75,5 -31,0 to -75,5 -291,4 to -307,9 -13,2 to -44,3 -13,3 to -44,4 -284,8 to -296,3Toxicity Particulates & aerosols (PM10 equiv) 9,7 10,5 -454,4 -39,6 to -109,9 -38,7 to -109,1 -471,2 to -495,1 -11,9 to -62,3 -11,1 to -61,5 -462,1 to -480,0

Toxicity Smog (ethylene equiv.) 0,3 0,3 -14,9 -1,4 to -3,7 -1,3 to -3,7 -15,4 to -16,3 -0,4 to -2,1 -0,4 to -2,0 -15,1 to -15,7Black smoke (kg dust eq.) 0,2 0,4 -35,6 -3,8 to -9,4 -3,6 to -9,3 -37,1 to -39,2 -1,5 to -5,5 -1,3 to -5,3 -36,2 to -37,7



Water Quality Eutrophication (P equiv.) 0,0 0,0 -0,8 -0,1 to -0,2 -0,1 to -0,2 -0,8 to -0,9 0,0 to -0,1 0,0 to -0,1 -0,8 to -0,8Disaminity (kg LF waste equiv.) 37,0 10,1 10,1 34,4 to 30,7 9,4 to 8,4 9,4 to 8,4 35,9 to 33,3 9,8 to 9,1 9,8 to 9,1

TOTAL EXTERNALITIES 48,3 23,4 -928,0 -57,0 to -207,4 -80,2 to -228,1 -965,0 to -1017,8 2,9 to -103,1 -21,3 to -125,6 -944,2 to -981,9INTERNAL COSTS 555,0 453,0 222,0 552,8 to 549,7 458,0 to 465,1 243,1 to 273,3 552,7 to 547,3 453,8 to 455,5 229,7 to 247,6TOTAL SOCIAL COSTS 603,3 476,4 -706,0 495,9 to 342,3 377,8 to 237,0 -721,8 to -744,4 555,6 to 444,2 432,4 to 329,9 -714,5 to -734,2

Separate Kerbside

7-17%

Landfill

Bring scheme3-10%

Landfill

Separate kerbside

7-17%

Separate kerbside

7-17%Incineration with nodule

recovery

Bring scheme3-10%

Incineration

Incineration with nodule

recovery

Bring scheme3-10%

Incineration

Table 11 : Aluminium – high population density: Internal costs, external costs and total social costs

Collection method N/A N/A N/ARecycling rate 0,0 0,0 0,0






Toxicity Metals non carcinogens (Pb equiv.) 0,1 0,1 -279,9 -26,6 to -71,0 -26,6 to -71,1 -289,8 to -306,2 -13,3 to -35,5 -13,3 to -35,5 -284,9 to -293,1Toxicity Particulates & aerosols (PM10 equiv) 8,4 9,2 -465,8 -34,4 to -105,8 -33,6 to -105,1 -480,2 to -504,2 -13,5 to -50,1 -12,7 to -49,3 -473,5 to -486,3

Toxicity Smog (ethylene equiv.) 0,2 0,2 -15,1 -1,2 to -3,6 -1,2 to -3,6 -15,6 to -16,4 -0,5 to -1,7 -0,5 to -1,7 -15,3 to -15,7Black smoke (kg dust eq.) 0,2 0,4 -35,7 -3,2 to -8,9 -3,1 to -8,8 -36,9 to -39,1 -1,5 to -4,4 -1,3 to -4,2 -36,3 to -37,4



Water Quality Eutrophication (P equiv.) 0,0 0,0 -0,8 -0,1 to -0,2 -0,1 to -0,2 -0,8 to -0,9 0,0 to -0,1 0,0 to -0,1 -0,8 to -0,8Disaminity (kg LF waste equiv.) 37,0 10,1 10,1 34,8 to 31,1 9,5 to 8,5 9,5 to 8,5 35,9 to 34,0 9,8 to 9,3 9,8 to 9,3

TOTAL EXTERNALITIES 54,7 29,7 -932,2 -32,8 to -178,7 -56,3 to -199,7 -960,5 to -1007,7 10,9 to -62,2 -13,4 to -85,2 -946,4 to -970,2INTERNAL COSTS 665,0 563,0 332,0 654,4 to 636,6 558,5 to 550,9 341,3 to 356,9 658,5 to 647,5 559,5 to 553,7 335,4 to 341,2TOTAL SOCIAL COSTS 719,7 592,7 -600,2 621,5 to 457,9 502,2 to 351,2 -619,2 to -650,8 669,3 to 585,3 546,1 to 468,5 -611,0 to -629,0


Bring scheme3-8%

Incineration


Bring scheme3-8%

Incineration


6-16%

Landfill

Bring scheme3-8%

Landfill

Separate kerbside

collection6-16%

Separate kerbside

collection6-16%

Graph 17 : Aluminium – low population density: Total social costs

Aluminium (rigid) - Low Population DensityTotal Social Cost

-1000.0

-800.0

-600.0

-400.0

-200.0

0.0

200.0

400.0

600.0

800.0


recovery

Separatekerbside


Separatekerbside


Separatekerbside


withrecovery

Bringscheme /

landfill

Bringscheme /

incineration

Bringscheme /

incinerationwith

recoveryScenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

Graph 18 : Aluminium – high population density: Total social costs

Aluminium (rigid) - High Population DensityTotal Social Cost

-800.0

-600.0

-400.0

-200.0

0.0

200.0

400.0

600.0

800.0


recovery

Separatekerbside


Separatekerbside


Separatekerbside


withrecovery

Bringscheme /

landfill

Bringscheme /

incineration

Bringscheme /

incinerationwith

recoveryScenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

3.3 Main findings:

For low population density:Where landfill is the MSW option, for a total social cost perspective it is not possible to distinguishbetween separate kerbside collection achieving a recycling rate of 7-17% and a bring scheme achieving3-10% as the optimum system from the scenarios modelled.

Where incineration with energy recovery but no slag recovery is the MSW option, for a total social costperspective it is not possible to distinguish between separate kerbside collection achieving a recyclingrate of 7-17% and a bring scheme achieving 3-10% as the optimum system from the scenariosmodelled.

Where incineration with energy recovery and slag recovery is the MSW option, for a total social costperspective it is not possible to distinguish between separate kerbside collection achieving a recyclingrate of 7-17% and a bring scheme achieving 3-10% as the optimum system from the scenariosmodelled.

For high population density

Where landfill is the MSW option, for a total social cost perspective it is not possible to distinguishbetween separate kerbside collection achieving a recycling rate of 6-16% and a bring scheme achieving3-8% as the optimum system from the scenarios modelled.

Where incineration with energy recovery but no slag recovery is the MSW option, for a total social costperspective it is not possible to distinguish between separate kerbside collection achieving a recyclingrate of 6-16% and a bring scheme achieving 3-8% as the optimum system from the scenarios modelled.

Where incineration with energy recovery and slag recovery is the MSW option, for a total social costperspective it is not possible to distinguish between separate kerbside collection achieving a recyclingrate of 6-16% and a bring scheme achieving 3-8% as the optimum system from the scenarios modelled.



Graph 19 : Aluminium – low population density: Sensitivity of the results to the external economicvaluations applied

Aluminium (rigid) - Low Population DensitySensitivity analysis on variations in economic valuations applied

-14000.0

-12000.0

-10000.0

-8000.0

-6000.0

-4000.0

-2000.0

0.0

2000.0


recovery

Separatekerbside


Separatekerbside


Separatekerbside


withrecovery

Bringscheme /

landfill

Bringscheme /

incineration

Bringscheme /

incinerationwith

recoveryScenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

Graph 20 : Aluminium – high population density: Sensitivity of the results to the external economicvaluations applied

Aluminium (rigid) - High Population DensitySensitivity analysis on variations in economic valuations applied

-14000.0

-12000.0

-10000.0

-8000.0

-6000.0

-4000.0

-2000.0

0.0

2000.0


recovery

Separatekerbside


Separatekerbside


Separatekerbside


withrecovery

Bringscheme /

landfill

Bringscheme /

incineration

Bringscheme /

incinerationwith

recoveryScenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

For low population densityWhere landfill is the MSW option, there is no influence on the results achieved or conclusions drawn.Where incineration with energy recovery but no slag recovery or incineration with energy and slagrecovery is the MSW option, it is no longer possible to distinguish between the systems modelled.

For high population density:Where landfill or incineration with energy recovery and no slag recovery is the MSW option, there isno influence on the results achieved or conclusions drawn.Where incineration with energy and slag recovery is the MSW option, it is no longer possible todistinguish between the systems modelled.


When potential variations in internal costs are taken into account it is no longer possible to distinguishbetween the alternative systems modelled.

Graph 21 : Aluminium – low population density: Sensitivity of the results to the internal economiccosts considered

Aluminium (rigid) - Low Population DensitySensitivity analysis on variations in Internal Costs

-1000.0-800.0-600.0-400.0-200.0

0.0200.0400.0600.0800.0


recovery

Separatekerbside


Separatekerbside


Separatekerbside


withrecovery

Bringscheme /

landfill

Bringscheme /

incineration

Bringscheme /

incinerationwith

recoveryScenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

Graph 22 : Aluminium – high population density: Sensitivity of the results to the internal economiccosts considered

Aluminium (rigid) - High Population DensitySensitivity analysis on variations in Internal Costs

-800.0

-600.0

-400.0

-200.0

0.0

200.0

400.0

600.0

800.0

1000.0


recovery

Separatekerbside


Separatekerbside


Separatekerbside


withrecovery

Bringscheme /

landfill

Bringscheme /

incineration

Bringscheme /

incinerationwith

recoveryScenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)



The results show that the results achieved and conclusions drawn are not sensitive to the inclusion ofthis parameter as an external impact.

Graph 23 : Aluminium – low population density: Sensitivity of the results to the addition of employmentas an impact category

Aluminium (rigid) - low population densityTotal Social Cost when including employment as an impact category

-1000.0-800.0-600.0-400.0-200.0

0.0200.0400.0600.0800.0


recovery

Separatekerbside


Separatekerbside


Separatekerbside


withrecovery

Bringscheme /

landfill

Bringscheme /

incineration

Bringscheme /

incinerationwith

recovery

Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

Graph 24 : Aluminium – high population density: Sensitivity of the results to the addition ofemployment as an impact category

Aluminium (other rigid than aluminium cans)Total Social Cost when including employment as an impact category

-800

-600

-400

-200

0

200

400

600

800

Landfill Incineration Incinerationwith recovery

Separatekerbside


Separatekerbside


Separatekerbside


with recovery

Bring scheme/ landfill

Bring scheme/ incineration

Bring scheme/ incinerationwith recovery

Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)



Table 12 : Summary of sensitivity analysis of scenario and modelling choices for aluminiumParameter investigated Influence on CBA results Influence on conclusions drawnIncineration model

Combined heat and power No influence on the relativestanding of options


Incineration modelOffset electricity No influence on the relative

standing of optionsNo influence on choice ofoptimal scenario




No influence on the relativestanding of options



bankNo influence on the relativestanding of options


4 Paper from household sources



Table 13 : Scenarios considered for paperPopulationdensity


MSW wastemanagement option

Scenario 1 Low None 0% LandfillScenario 2 Low None 0% IncinerationScenario 3 Low Separate kerbside collection 61-71% LandfillScenario 4 Low Separate kerbside collection 61-71% IncinerationScenario 5 Low Bring scheme 25-35% LandfillScenario 6 Low Bring scheme 25-35% IncinerationScenario 7 High None 0% LandfillScenario 8 High None 0% IncinerationScenario 9 High Separate kerbside collection 55-65% LandfillScenario 10 High Separate kerbside collection 55-65% IncinerationScenario 11 High Bring scheme 19-29% LandfillScenario 12 High Bring scheme 19-29% Incineration

4.2 Results of the cost benefit analysis for paper

Table 14 : Paper – low population density: Internal costs, external costs and total social costs


GWP (kg CO2 eq.) 32,5 17,0 26,5 to 25,5 20,5 to 21,0 29,9 to 28,9 18,3 to 18,8Ozone depletion (kg CFC 11 eq.) 0,0 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0

Acidification (Acid equiv.) -0,1 -0,4 -0,3 to -0,4 -0,4 to -0,4 -0,2 to -0,2 -0,4 to -0,4Toxicity Carcinogens (Cd equiv) 0,0 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0Toxicity Gaseous (SO2 equiv.) -0,6 -1,5 -0,9 to -1,0 -1,3 to -1,3 -0,5 to -0,5 -1,2 to -1,0

Toxicity Metals non carcinogens (Pb equiv.) 0,0 -0,2 -0,1 to -0,1 -0,2 to -0,2 0,0 to 0,0 -0,1 to -0,1Toxicity Particulates & aerosols (PM10 equiv) 6,3 -11,9 2,4 to 1,8 -4,7 to -3,5 -2,3 to -5,7 -15,9 to -17,5

Toxicity Smog (ethylene equiv.) 1,8 0,0 0,6 to 0,4 -0,1 to -0,1 1,3 to 1,1 -0,1 to -0,1Black smoke (kg dust eq.) -0,3 -1,4 -1,4 to -1,6 -1,8 to -1,9 -0,7 to -0,9 -1,6 to -1,6

Fertilisation -0,2 -0,1 0,0 to 0,0 0,1 to 0,1 -0,1 to 0,0 0,0 to 0,1Traffic accidents (risk equiv.) 0,1 0,1 0,7 to 0,8 0,7 to 0,8 1,6 to 2,2 1,6 to 2,2


Water Quality Eutrophication (P equiv.) 0,0 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0Disaminity (kg LF waste equiv.) 37,0 11,2 14,6 to 11,0 4,6 to 3,5 27,8 to 24,2 8,5 to 7,4

TOTAL EXTERNALITIES 77,1 13,5 51,3 to 47,1 26,5 to 28,7 60,4 to 53,8 12,7 to 12,4INTERNAL COSTS 131,1 184,1 103,5 to 99,0 124,2 to 114,4 117,7 to 112,3 157,4 to 146,7TOTAL SOCIAL COSTS 208,2 197,6 154,9 to 146,1 150,7 to 143,0 178,1 to 166,0 170,1 to 159,1


Separate kerbside

collection61-71%

Incineration

Bring scheme25-35%

Incineration


61-71%Landfill

Table 15 : Paper – high population density: Internal costs, external costs and total social costs


GWP (kg CO2 eq.) 32,4 16,9 26,4 to 25,3 19,4 to 19,9 30,8 to 30,0 18,3 to 19,0Ozone depletion (kg CFC 11 eq.) 0,0 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0

Acidification (Acid equiv.) -0,1 -0,4 -0,4 to -0,4 -0,5 to -0,5 -0,2 to -0,3 -0,5 to -0,5Toxicity Carcinogens (Cd equiv) 0,0 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0Toxicity Gaseous (SO2 equiv.) -0,6 -1,5 -1,1 to -1,1 -1,5 to -1,4 -0,7 to -0,7 -1,4 to -1,4

Toxicity Metals non carcinogens (Pb equiv.) 0,0 -0,2 -0,1 to -0,2 -0,2 to -0,2 -0,1 to -0,1 -0,2 to -0,2Toxicity Particulates & aerosols (PM10 equiv) 5,0 -13,2 -7,8 to -10,2 -16,0 to -16,5 -2,7 to -6,8 -17,5 to -19,7

Toxicity Smog (ethylene equiv.) 1,8 0,0 0,4 to 0,1 -0,4 to -0,5 1,3 to 1,0 -0,2 to -0,3Black smoke (kg dust eq.) -0,3 -1,4 -1,4 to -1,6 -1,9 to -2,0 -0,7 to -1,0 -1,6 to -1,8

Fertilisation -0,2 0,0 0,1 to 0,2 0,2 to 0,3 -0,1 to 0,0 0,1 to 0,1Traffic accidents (risk equiv.) 0,2 0,2 0,6 to 0,7 0,6 to 0,7 0,7 to 0,9 0,7 to 0,9


Water Quality Eutrophication (P equiv.) 0,0 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0 0,0 to 0,0Disaminity (kg LF waste equiv.) 37,0 11,2 16,8 to 13,2 5,2 to 4,1 30,0 to 26,4 9,2 to 8,1

TOTAL EXTERNALITIES 83,5 19,8 66,8 to 63,7 38,1 to 41,5 80,7 to 79,3 29,2 to 34,1INTERNAL COSTS 148,8 201,8 109,6 to 102,5 133,4 to 121,0 133,9 to 126,0 176,8 to 163,7TOTAL SOCIAL COSTS 232,3 221,6 176,4 to 166,2 171,6 to 162,5 214,6 to 205,3 206,0 to 197,8


Separate kerbside

collection55-65%

Incineration

Bring scheme19-29%

Incineration


55-65%Landfill

Graph 25 : Paper – low population density: Total social cost

Paper - Low Population DensityTotal Social Cost

0.0

50.0

100.0

150.0

200.0

250.0



Separatekerbside




Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

Graph 26 : Paper – high population density: Total social costs

Paper - High Population DensityTotal Social Cost

0.0

50.0

100.0

150.0

200.0

250.0



Separatekerbside




Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

4.3 Main findings:

For low population density, a kerbside collection scheme achieving a recycling rate of 61-71% is theoptimum system for the scenarios considered. This is not dependent on the available alternative wastemanagement option.

For high population density, a kerbside collection scheme achieving a recycling rate of 55-65% is theoptimum system for the scenarios considered. This is not dependent on the available alternative wastemanagement option.


4.4.1 Methodological choices4.4.1.1 Choice of external valuationsThe graph below shows the sensitivity of the analysis to the economic valuations applied to the definedenvironmental impacts. The graph has been produced by considering the same environmental impact

results, but applying different impact assessment valuations (see Annex 4 for a list of maximum andminimum valuations applied).

The graphs show that results are extremely sensitive to the external economic valuations applied. If thefull range of available external economic valuations is applied then it is not possible to make a cleardistinction as to which is the optimal waste management system for the scenarios considered.

Graph 27 : Paper – low population density: Sensitivity of the results to the external economicvaluations applied

Paper - Low Population DensitySensitivity analysis on variations in economic valuations applied

0.0

100.0

200.0

300.0

400.0

500.0

600.0

700.0

800.0

900.0



Separatekerbside




Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

Graph 28 : Paper – high population density: Sensitivity of the results to the external valuationsapplied

Paper - High Population DensitySensitivity analysis on variations in economic valuations applied

0.0100.0200.0300.0400.0500.0600.0700.0800.0900.0



Separatekerbside




Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)


The following points should be noted:♦ For low population density where landfill is the MSW option, it is no longer possible to distinguish

between separate kerbside collection achieving a recycling rate of 61-71% and a bring schemeachieving a recycling rate of 25-35%.

♦ For low population density where incineration is the MSW option it is no longer possible todistinguish between 100% incineration, separate kerbside collection achieving a recycling rate of61-71% and a bring scheme achieving a recycling rate of 25-35%.

♦ For high population density where landfill is the MSW option, it is no longer possible todistinguish between separate kerbside collection achieving a recycling rate of 61-71% and a bringscheme achieving a recycling rate of 25-35%.

♦ For high population density where incineration is the MSW option it is no longer possible todistinguish between 100% incineration, separate kerbside collection achieving a recycling rate of61-71% and a bring scheme achieving a recycling rate of 25-35%.

Graph 29 : Paper – low population density: Sensitivity of the results to the internal economic costsconsidered

Paper - Low Population DensitySensitivity analysis on variations in Internal Costs

0.0

50.0

100.0

150.0

200.0

250.0



Separatekerbside




Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

Graph 30 : Paper – high population density: Sensitivity of results to the internal economic costsconsidered

Paper - High Population DensitySensitivity analysis on variations in Internal Costs

0.0

50.0

100.0

150.0

200.0

250.0

300.0



Separatekerbside




Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)


The graph below shows the sensitivity of the analysis to the inclusion of employment as an impactcategory. The graph has been produced by including employment along with the other environmentalimpacts used in the baseline analysis. The main conclusions drawn are not sensitive to the inclusion ofthis additional parameter.

Graph 31 : Paper – low population density: Sensitivity of the results to the addition of employment asan impact category

Paper from household sourcesTotal Social Cost when including employment as an impact category

0

50

100

150

200

250



Separatekerbside




Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

Graph 32 : Paper – high population density: Sensitivity of the results to the addition of employment asan impact category

Paper from household sourcesTotal Social Cost when including employment as an impact category

0

50

100

150

200

250



Separatekerbside




Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)



Table 16 : Summary of sensitivity analysis of scenario and modelling choices for paperParameter investigated Influence on CBA results Influence on conclusions drawnIncineration model

Combined heat and powerTotal social cost of incinerationoptions is reducedNo influence on the relativestanding of alternative systems

No influence on the choice ofoptimum system


Total social cost of incinerationoptions is reducedNo influence on the relativestanding of alternative systems





Similar total social costsobserved for separate kerbsidecollection and bring schemescenarios.No distinction between kerbsidecollection and bring schemescenarios is possible

Could influence choice ofoptimum scenario – broaderoptimum recycling range wouldbe achieved


bank

Total social costs of recyclingoptions increased, but noinfluence on the relativestanding of alternative systems


5 Liquid beverage cartons from household sources



Table 17 : Scenarios considered for aseptic composite beverage cartonsPopulationdensity


MSW wastemanagementoption

Scenario 1 Low None 0% LandfillScenario 2 Low None 0% IncinerationScenario 3 Low Separate kerbside collection (fibres

recycled, foil/plastic residual to landfill)55-65% Landfill

Scenario 4 Low Separate kerbside collection (fibresrecycled, foil/plastic residual toincineration)

55-65% Landfill

Scenario 5 Low Separate kerbside collection (fibresrecycled, foil/plastic residual toincineration)

55-65% Incineration

Scenario 6 Low Bring scheme (fibre recycled, foil/plasticresidual to landfill)

24-34% Landfill

Scenario 7 Low Bring scheme (fibre recycled, foil/plasticresidual to incineration)

24-34% Landfill

Scenario 8 Low Bring scheme (fibre recycled, foil/plasticresidual to incineration)

24-34% Incineration

Scenario 9 High None 0% LandfillScenario 10 High None 0% IncinerationScenario 11 High Separate kerbside collection (fibres

recycled, foil/plastic residual to landfill)55-65% Landfill

Scenario 12 High Separate kerbside collection (fibresrecycled, foil/plastic residual toincineration)

55-65% Landfill

Scenario 13 High Separate kerbside collection (fibresrecycled, foil/plastic residual toincineration)

55-65% Incineration

Scenario 14 High Bring scheme (fibre recycled, foil/plasticresidual to landfill)

24-34% Landfill

Scenario 15 High Bring scheme (fibre recycled, foil/plasticresidual to incineration)

24-34% Landfill

Scenario 16 High Bring scheme (fibre recycled, foil/plasticresidual to incineration)

24-34% Incineration

5.2 Results of the cost benefit analysis for liquid beverage cartons

Table 18 : LBC – low population density: Internal costs, external costs and total social costs

Collection method N/A N/ARecycling rate 0.0 0.0Residual waste management option Landfill IncinerationExeternalities

GWP (kg CO2 eq.) 24.2 21.0 21.0 to 20.4 25.5 to 25.8 24.1 to 24.7 22.8 to 22.2 24.8 to 25.0 22.4 to 22.9Ozone depletion (kg CFC 11 eq.) 0.0 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0

Acidification (Acid equiv.) -0.1 -0.6 -0.2 to -0.2 -0.3 to -0.3 -0.5 to -0.5 -0.1 to -0.1 -0.2 to -0.2 -0.5 to -0.5Toxicity Carcinogens (Cd equiv) 0.0 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0Toxicity Gaseous (SO2 equiv.) -0.4 -2.0 -0.4 to -0.5 -0.9 to -1.0 -1.6 to -1.6 -0.2 to -0.1 -0.4 to -0.4 -1.6 to -1.4

Toxicity Metals non carcinogens (Pb equiv.) 0.0 -0.2 0.0 to -0.1 -0.1 to -0.1 -0.2 to -0.2 0.0 to 0.0 0.0 to 0.0 -0.2 to -0.2Toxicity Particulates & aerosols (PM10 equiv) 7.1 -17.1 23.6 to 26.6 17.5 to 19.4 6.6 to 10.9 10.3 to 11.7 7.7 to 7.9 -10.7 to -8.0

Toxicity Smog (ethylene equiv.) 1.4 0.0 1.0 to 0.9 1.0 to 0.9 0.3 to 0.4 1.3 to 1.2 1.2 to 1.2 0.2 to 0.2Black smoke (kg dust eq.) -0.1 -1.8 -0.7 to -0.8 -1.2 to -1.4 -1.9 to -1.9 -0.4 to -0.4 -0.6 to -0.7 -1.8 to -1.8

Fertilisation -0.2 -0.1 -0.2 to -0.2 -0.2 to -0.2 -0.2 to -0.2 -0.2 to -0.2 -0.2 to -0.2 -0.1 to -0.1Traffic accidents (risk equiv.) 0.1 0.1 0.9 to 1.0 0.9 to 1.0 0.9 to 1.0 1.7 to 2.4 1.7 to 2.4 1.7 to 2.4

Traffic Congestion (car km equiv.) 0.1 0.1 10.0 to 11.8 10.0 to 11.8 10.0 to 11.8 4.5 to 6.3 4.5 to 6.3 4.5 to 6.3Traffic Noise (car km equiv.) 0.4 0.4 2.4 to 2.8 2.4 to 2.8 2.4 to 2.8 1.0 to 1.3 1.0 to 1.3 1.0 to 1.3

Water Quality Eutrophication (P equiv.) 0.0 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0Disaminity (kg LF waste equiv.) 37.0 11.7 22.0 to 19.3 18.6 to 15.3 7.2 to 6.4 30.5 to 27.8 29.0 to 25.6 9.7 to 8.9

Employment -3.7 -4.0 -19.4 -22.2 -19.4 -22.2 -19.5 -22.3 -4.9 -5.5 -4.9 -5.5 -5.2 -5.7TOTALEXTERNALITIES

69.6 11.6 79.3 to 81.1 73.2 to 73.8 47.1 to 53.5 71.3 to 72.0 68.6 to 68.2 24.6 to 30.0INTERNAL COSTS 168.0 237.0 349.1 to 382.0 359.5 to 394.3 390.5 to 418.4 238.1 to 267.3 242.6 to 273.7 295.0 to 319.2TOTAL SOCIALCOSTS

237.6 248.6 428.4 to 463.1 432.6 to 468.1 437.6 to 472.0 309.4 to 339.3 311.2 to 341.9 319.6 to 349.2

Separatekerbside

collection(fibres recycled,

foil/plasticresidual to

incineration)55-65%Landfill

Bring scheme(fibre recycled,





landfill)24-34%Landfill

Separatekerbside

collection(fibres

recycled,foil/plasticresidual to

incineration)

SeparateKerbsidecollection

(fibresrecycled,



55-65%Incineration



incineration)24-34%

Incineration

Graph 33 : LBC – low population density: Total social cost

Liquid Beverage Cartons - Low Population DensityTotal Social Cost

0.050.0

100.0150.0

200.0250.0300.0350.0400.0450.0500.0

Landfill Incineration Separatekerbsidecollection

(fibresrecycled,foil/plasticresidual tolandfill) /landfill

Separatekerbsidecollection

(fibresrecycled,foil/plasticresidual to

incineration)/ incineration




Bringscheme(fibres

recycled,foil/plasticresidual tolandfill) /landfill

Bringscheme(fibres


incineration)/ landfill

Bringscheme(fibres



Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

Liquid Beverage Cartons - Low Population DensityTotal Social Cost

0.050.0

100.0150.0200.0250.0300.0350.0400.0450.0500.0









Bringscheme(fibres


Bringscheme(fibres



Bringscheme(fibres



Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

Table 19 : LBC – high population density: Internal costs, external costs and total social costs


GWP (kg CO2 eq.) 24.1 20.9 20.3 to 19.6 24.9 to 25.0 23.4 to 23.9 22.4 to 21.7 24.4 to 24.5 22.0 to 22.4Ozone depletion (kg CFC 11 eq.) 0.0 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0

Acidification (Acid equiv.) -0.1 -0.6 -0.2 to -0.2 -0.3 to -0.4 -0.6 to -0.6 -0.1 to -0.2 -0.2 to -0.2 -0.6 to -0.5Toxicity Carcinogens (Cd equiv) 0.0 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0

Toxicity Gaseous (SO2 equiv.) -0.4 -2.0 -0.6 to -0.6 -1.1 to -1.2 -1.8 to -1.7 -0.4 to -0.3 -0.6 to -0.7 -1.8 to -1.7Toxicity Metals non carcinogens (Pb equiv.) 0.0 -0.2 -0.1 to -0.1 -0.1 to -0.2 -0.2 to -0.2 0.0 to 0.0 0.0 to -0.1 -0.2 to -0.2

Toxicity Particulates & aerosols (PM10 equiv) 5.8 -18.7 16.4 to 18.4 10.4 to 11.2 -0.6 to 2.7 6.4 to 6.7 3.8 to 2.9 -14.8 to -13.2Toxicity Smog (ethylene equiv.) 1.4 0.0 0.7 to 0.5 0.6 to 0.5 0.0 to 0.0 1.1 to 0.9 1.0 to 0.9 0.0 to 0.0

Black smoke (kg dust eq.) -0.2 -1.8 -0.9 to -1.0 -1.3 to -1.5 -2.1 to -2.1 -0.5 to -0.6 -0.7 to -0.9 -1.9 to -2.0Fertilisation -0.2 -0.1 -0.1 to 0.0 -0.1 to 0.0 0.0 to 0.0 -0.1 to -0.1 -0.1 to -0.1 0.0 to 0.0

Traffic accidents (risk equiv.) 0.2 0.2 1.1 to 1.3 1.1 to 1.3 1.1 to 1.3 0.9 to 1.2 0.9 to 1.2 0.9 to 1.2Traffic Congestion (car km equiv.) 8.2 7.6 50.4 to 58.1 50.4 to 58.1 50.1 to 57.9 29.7 to 38.6 29.7 to 38.6 29.2 to 38.2

Traffic Noise (car km equiv.) 0.2 0.2 1.2 to 1.4 1.2 to 1.4 1.2 to 1.4 0.5 to 0.7 0.5 to 0.7 0.5 to 0.6Water Quality Eutrophication (P equiv.) 0.0 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0 0.0 to 0.0

Disaminity (kg LF waste equiv.) 37.0 11.7 22.0 to 19.3 18.6 to 15.3 7.2 to 6.4 30.5 to 27.8 29.0 to 25.6 9.7 to 8.9TOTAL EXTERNALITIES 75.9 17.1 110.5 to 116.7 104.3 to 109.5 77.8 to 88.9 90.4 to 96.4 87.7 to 92.6 43.0 to 53.7INTERNAL COSTS 196.0 265.0 345.4 to 372.5 355.7 to 384.8 386.8 to 408.9 253.1 to 276.9 257.6 to 283.3 310.1 to 337.9TOTAL SOCIAL COSTS 271.9 282.1 455.8 to 489.3 460.0 to 494.2 464.6 to 497.8 343.5 to 373.3 345.3 to 375.9 353.0 to 391.6

Separate kerbside

collection (fibres recycled,

foil/plastic residual to


Bring scheme (fibre recycled,






Separate kerbside



incineration)

Separate Kerbside




55-65%Incineration



incineration)24-34%

Incineration

Graph 34 : LBC – high population density: Total social cost

Liquid Beverage Cartons - High Population DensityTotal Social Cost

0.0

100.0

200.0

300.0

400.0

500.0

600.0





incineration) /incineration




Bring scheme(fibres


Bring scheme(fibres


incineration) /landfill

Bring scheme(fibres



Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

Liquid Beverage Cartons - High Population DensityTotal Social Cost

0.0

100.0

200.0

300.0

400.0

500.0

600.0









Bring scheme(fibres


Bring scheme(fibres


incineration) /landfill

Bring scheme(fibres



Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

5.3 Main findings:

From an internal cost perspective, where landfill is the MSW option 100% landfilling is the preferredwaste management system from the scenarios considered for both high and low population density.Where incineration is the MSW option, 100% incineration is the preferred waste management systemfrom the scenarios considered for both high and low population density.


5.4.1 Methodological choices

5.4.1.1 Choice of external valuationsThe graph below shows the sensitivity of the analysis to the economic valuations applied to the definedenvironmental impacts. The graph has been produced by considering the same environmental impactresults, but applying different impact assessment valuations (see Annex 4 for a list of maximum andminimum valuations applied).

The graphs show that the results achieved and conclusions drawn are sensitive to the economic valuesapplied to environmental impact categories. Applying the full range of available economic valuationsmakes it impossible to distinguish an optimal system from the scenarios considered.

Graph 35 : LBC – low population density: Sensitivity of the results to the external economicvaluations applied

Liquid Beverage Cartons - Low Population DensitySensitivity analysis on variations in economic valuations applied

0.0

100.0

200.0

300.0

400.0

500.0

600.0

700.0

800.0

900.0









Bringscheme(fibres


Bringscheme(fibres



Bringscheme(fibres



Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

Graph 36 : LBC – high population density: Sensitivity of the results to the external economicvaluations applied

Liquid Beverage Cartons - High Population DensitySensitivity analysis on variations in economic valuations applied

0.0100.0200.0300.0400.0500.0600.0700.0800.0900.0









Bringscheme(fibres


Bringscheme(fibres



Bringscheme(fibres



Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)


The graphs show that the results achieved and conclusions drawn are sensitive to potential variations ininternal costs. If a +/-20% variation in internal costs is considered, where landfill is the MSW option itis no longer possible to distinguish between 100% landfill and a bring scheme achieving a recyclingrate of 24-34% for either high or low population density. Where incineration is the MSW option it isno longer possible to distinguish between 100% incineration and a bring scheme achieving a recyclingrate of 24-34% for either high or low population density.

This sensitivity would affect the choice of optimum system from the scenarios considered, andtherefore affect the choice of optimum recycling rate selected from the cost benefit analysis.

Graph 37 : LBC – low population density: Sensitivity of the results to the internal economic costsconsidered

Liquid Beverage Cartons - Low Population DensitySensitivity analysis on variations in Internal Costs

0.0

100.0

200.0

300.0

400.0

500.0

600.0









Bringscheme(fibres


Bringscheme(fibres



Bringscheme(fibres



Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

Graph 38 : LBC – high population density: Sensitivity of the results to the internal economic costsconsidered

Liquid Beverage Cartons - High Population DensitySensitivity analysis on variations in Internal Costs

0.0

100.0

200.0

300.0

400.0

500.0

600.0

700.0









Bringscheme(fibres


Bringscheme(fibres



Bringscheme(fibres



Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

5.4.1.3 Inclusion of employment as an impact categoryThe graph below shows the sensitivity of the analysis to the inclusion of employment as an impactcategory. The graph has been produced by including employment along with the other environmentalimpacts used in the baseline analysis.

The graphs show that the results achieved and conclusions drawn are not sensitive to inclusion of thisimpact category.

Graph 39 : LBC – low population density: Sensitivity of the results to the addition of employment as animpact category

Liquid beverage cartons - low population densityTotal Social Cost when including employment as an impact category

050

100150200250300350400450500









Bringscheme(fibres


Bringscheme(fibres



Bringscheme(fibres



Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

Graph 40 : LBC – low population density: Sensitivity of the results to the addition of employment as animpact category

Liquid beverage cartons - high population densityTotal Social Cost when including employment as an impact category

0

100

200

300

400

500

600



Separatekerbside

collection(fibres






Bringscheme(fibres


Bringscheme(fibres



Bringscheme(fibres



Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

5.4.2 Scenario and modelling choicesFindings from the sensitivity analysis of scenario and modelling choices are summarised in the tablebelow.

Table 20 : Summary of sensitivity analysis of scenario and modelling choices for liquid beveragecartonsParameter investigated Influence on CBA results Influence on conclusions drawnIncineration model

Combined heat and powerNo influence on the relativestanding of scenarios modelled

No influence on choice ofoptimum waste managementsystem from the scenariosconsideredNo influence on choice ofoptimum recycling rate


No influence on the relativestanding of scenarios modelled








bank



6 Glass from household sources



Table 21 : Scenarios considered for glassPopulationdensity

Selective collection scheme Recycling rateachieved

MSW wastemanagement option

Scenario 1 Low None 0% LandfillScenario 2 Low None 0% IncinerationScenario 3 Low Bring scheme 73-83% LandfillScenario 4 Low Bring scheme 73-83% IncinerationScenario 5 High None 0% LandfillScenario 6 High None 0% IncinerationScenario 7 High Bring scheme 42-91% LandfillScenario 8 High Bring scheme 42-91% Incineration

6.2 Results of the cost benefit analysis for glass

Table 22 : Glass – low population density: Internal costs, external costs and total social costs


GWP (kg CO2 eq.) 0.4 0.9 -19.5 to -22.2 -19.3 to -22.1Ozone depletion (kg CFC 11 eq.) 0.0 0.0 0.0 to 0.0 0.0 to 0.0

Acidification (Acid equiv.) 0.0 0.1 -2.9 to -3.3 -2.9 to -3.3Toxicity Carcinogens (Cd equiv) 0.0 0.0 0.0 to 0.0 0.0 to 0.0

Toxicity Gaseous (SO2 equiv.) 0.1 0.3 -16.3 to -18.5 -16.2 to -18.5Toxicity Metals non carcinogens (Pb equiv.) 0.1 0.1 -0.3 to -0.3 -0.3 to -0.3

Toxicity Particulates & aerosols (PM10 equiv) 9.1 10.1 -60.5 to -70.0 -60.2 to -69.8Toxicity Smog (ethylene equiv.) 0.3 0.3 -3.3 to -3.8 -3.3 to -3.8

Black smoke (kg dust eq.) 0.2 0.4 -7.5 to -8.6 -7.5 to -8.6Fertilisation -0.1 -0.1 2.3 to 2.6 2.3 to 2.6

Traffic accidents (risk equiv.) 0.1 0.1 4.6 to 5.2 4.6 to 5.2Traffic Congestion (car km equiv.) 0.1 0.1 6.5 to 7.4 6.5 to 7.4

Traffic Noise (car km equiv.) 0.4 0.4 1.3 to 1.4 1.3 to 1.4Water Quality Eutrophication (P equiv.) 0.0 0.0 -0.2 to -0.2 -0.2 to -0.2

Disaminity (kg LF waste equiv.) 37.0 10.1 10.0 to 6.3 2.7 to 1.7TOTAL EXTERNALITIES 47.7 22.8 -85.7 to -104.0 -92.4 to -108.2INTERNAL COSTS 152.2 153.1 86.7 to 77.7 87.0 to 77.9TOTAL SOCIAL COSTS 199.9 175.9 1.0 to -26.2 -5.5 to -30.3

Bring Bring

Landfill Incineration73-83% 73-83%

Graph 41 : Glass – low population density: Total social costs

Glass - Low Population DensityTotal Social Cost

-50.0

0.0

50.0

100.0

150.0

200.0

250.0

Landfill Incineration Bring scheme / landfill Bring scheme /incineration

Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

Table 23 : Glass – high population density: Internal costs, external costs and total social costs



Acidification (Acid equiv.) 0.0 0.1 -1.7 to -3.6 -1.6 to -3.6Toxicity Carcinogens (Cd equiv) 0.0 0.0 0.0 to 0.0 0.0 to 0.0

Toxicity Gaseous (SO2 equiv.) 0.1 0.3 -9.6 to -20.9 -9.5 to -20.9Toxicity Metals non carcinogens (Pb equiv.) 0.1 0.1 -0.2 to -0.4 -0.2 to -0.4

Toxicity Particulates & aerosols (PM10 equiv) 7.9 8.8 -33.3 to -81.4 -32.8 to -81.3Toxicity Smog (ethylene equiv.) 0.2 0.2 -2.0 to -4.5 -2.0 to -4.5

Black smoke (kg dust eq.) 0.2 0.3 -4.4 to -9.6 -4.3 to -9.6Fertilisation -0.1 -0.1 1.4 to 3.0 1.3 to 3.0


Traffic Noise (car km equiv.) 0.2 0.2 0.6 to 1.0 0.6 to 1.0Water Quality Eutrophication (P equiv.) 0.0 0.0 -0.1 to -0.3 -0.1 to -0.3

Disaminity (kg LF waste equiv.) 37.0 10.1 21.5 to 3.3 5.9 to 0.9TOTAL EXTERNALITIES 54.1 29.1 -4.4 to -72.6 -18.9 to -74.9INTERNAL COSTS 172.5 173.3 123.8 to 66.9 124.2 to 67.0TOTAL SOCIAL COSTS 226.6 202.4 119.4 to -5.7 105.4 to -7.9

Bring Bring


Graph 42 : Glass – high population density: Total social costs

Glass - High Population DensityTotal Social Cost

-50.0

0.0

50.0

100.0

150.0

200.0

250.0


Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

6.3 Main findings:

For low population density, a bring scheme achieving a recycling rate of 73-83% is the optimumsystem for the scenarios modelled. For high population density, a bring scheme achieving a recyclingrate of 42-91% is the optimum system for the scenarios modelled.


6.4.1 Methodological choices6.4.1.1 Choice of external valuationsThe graph below shows the sensitivity of the analysis to the economic valuations applied to the definedenvironmental impacts. The graph has been produced by considering the same environmental impactresults, but applying different impact assessment valuations (see Annex 4 for a list of maximum andminimum valuations applied). The graphs below show that the general conclusions are not changed byapplying different economic valuations.

Graph 43 : Glass – low population density: Sensitivity of the results to the external economicvaluations applied

Glass - Low Population DensitySensitivity analysis on variations in economic valuations applied

-800.0-700.0

-600.0-500.0-400.0

-300.0-200.0

-100.00.0

100.0200.0300.0


Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

Graph 44 : Glass – high population density: Sensitivity of the results to the external economicvaluations applied

Glass - High Population DensitySensitivity analysis on variations in economic valuations applied

-800.0

-600.0

-400.0

-200.0

0.0

200.0

400.0


Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e

6.4.1.2 Internal costsThe internal costs applied in this study have been sourced mostly from the UK, France and Belgium.Even where equivalent waste management practices are compared internal costs can vary considerablybetween Member States, depending on a range of factors such as cost of living and geographicalconsiderations (mountainous regions, island populations, etc.). In this part of the sensitivity analysis,the effect on the results of considering a +/-20% variation in internal costs is investigated. The resultsare presented in the graph below, which shows that the general conclusions drawn are not sensitive tothis parameter.

Graph 45 : Glass – low population density: Sensitivity of the results to the internal economic costsconsidered

Glass - Low Population DensitySensitivity analysis on variations in Internal Costs

-100.0

-50.0

0.0

50.0

100.0

150.0

200.0

250.0


Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

Graph 46 : Glass – high population density: Sensitivity of the results to the internal economic costsconsidered

Glass - High Population DensitySensitivity analysis on variations in Internal Costs

-50,0

0,0

50,0

100,0

150,0

200,0

250,0

300,0


Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)


The graph below shows the sensitivity of the analysis to the inclusion of employment as an impactcategory. The graph has been produced by including employment along with the other environmentalimpacts used in the baseline analysis. The general conclusions drawn are not affected by the inclusionof this impact category.

Graph 47 : Glass – low population density: Sensitivity of the results to the addition of employment asan impact category

Glass - Low Population DensityTotal Social Cost

-50.0

0.0

50.0

100.0

150.0

200.0

250.0


Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

Graph 48 : Glass – high population density: Sensitivity of the results to the addition of employment asan impact category

Glass - High Population DensityTotal Social Cost

-50.0

0.0

50.0

100.0

150.0

200.0

250.0


Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)



Table 24 : Summary of sensitivity analysis of scenario and modelling choices for glassParameter investigated Influence on CBA results Influence on conclusions drawnIncineration model

Combined heat and powerNo influence No influence


No influence No influence






bank


Alternative LCI data Not considered Not consideredAlternative reprocessingoptions

Not considered Not considered

The results are generally robust to the parameters investigated in the sensitivity analysis. However, itshould be noted that alternative LCI data has not been investigated. Also, no consideration ofalternative reprocessing options has been made. Alternative reprocessing options may be crucial forcountries to achieve higher recycling rates where an imbalance in supply and demand exists.

7 PE Film from commercial and industrial sources



Table 25 : Scenarios considered for PE filmSelective collection scheme Recycling rate achieved MSW waste management

optionScenario 1 None 0% LandfillScenario 2 None 0% IncinerationScenario 3 Separate collection 70-90% LandfillScenario 4 Separate collection 70-90% Incineration

7.2 Results of the cost benefit analysis for PE film

Table 26 : PE film: Internal costs, external costs and total social costs



Acidification (Acid equiv.) 0.1 -1.3 -3.0 to -3.8 -3.4 to -4.0Toxicity Carcinogens (Cd equiv) 0.0 -0.1 0.0 to 0.0 0.0 to 0.0

Toxicity Gaseous (SO2 equiv.) 0.2 -4.6 -7.8 to -10.0 -9.2 to -10.5Toxicity Metals non carcinogens (Pb equiv.) 0.1 -0.5 4.8 to 6.1 4.6 to 6.1

Toxicity Particulates & aerosols (PM10 equiv) 9.6 -50.0 -111.5 to -146.1 -129.4 to -152.0Toxicity Smog (ethylene equiv.) 0.2 -0.4 -15.3 to -19.8 -15.5 to -19.9

Black smoke (kg dust eq.) 0.2 -4.3 -8.5 to -11.0 -9.9 to -11.4Fertilisation -0.1 0.0 5.0 to 6.5 5.1 to 6.5


Traffic Noise (car km equiv.) 0.2 0.2 0.3 to 0.3 0.3 to 0.3Water Quality Eutrophication (P equiv.) 0.0 -0.1 -0.4 to -0.5 -0.4 to -0.5

Disaminity (kg LF waste equiv.) 37.0 13.3 11.1 to 3.7 4.0 to 1.3TOTAL EXTERNALITIES 56.1 0.4 -128.7 to -181.5 -145.4 to -187.1INTERNAL COSTS 255.2 217.2 42.0 to -18.9 30.6 to -22.7TOTAL SOCIAL COSTS 311.3 217.6 -86.7 to -200.4 -114.8 to -209.8

Recycling Recycling


Graph 49 : PE film: Total social costs

PE Film from commercial and industrial sourcesTotal Social Cost

-300.0

-200.0

-100.0

0.0

100.0

200.0

300.0

400.0

Landfill Incineration Recycling / landfill Recycling / incineration

Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

7.3 Main findings:

Where landfill is the MSW option, recycling of source separated material (achieving a recycling rate of70-90%) is the optimum waste management system for the scenarios considered.Where incineration is the MSW option, recycling of source separated material (achieving a recyclingrate of 70-90%) is the optimum waste management system for the scenarios considered.


7.4.1 Methodological choices7.4.1.1 Choice of external valuationsThe graph below shows the sensitivity of the analysis to the economic valuations applied to the definedenvironmental impacts. The graph has been produced by considering the same impact results, butapplying different impact assessment valuations (see Annex 4 for a list of maximum and minimumvaluations applied).

The graphs show that the results achieved and conclusions drawn are not sensitive to the economicvaluations applied to environmental impacts.

Graph 50 : PE film: Sensitivity of the results to the external economic valuations applied

PE Film from commercial and industrial sourcesSensitivity analysis on variations in economic valuations applied

-2500.0

-2000.0

-1500.0

-1000.0

-500.0

0.0

500.0

1000.0


Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

7.4.1.2 Internal costsInternal costs can vary considerably between Member States, depending on a range of factors such ascost of living and geographical considerations (mountainous regions, island populations, etc.). Toaccount for this variation, the dependency of the internal costs on the results have been investigated.The effect on the results of considering a +/-20% variation in internal costs is presented in the graphbelow. The graph shows that the results are not sensitive to this parameter.

Graph 51 : PE film: Sensitivity of the results to the internal economic costs considered

PE Film from commercial and industrial sourcesSensitivity analysis on variations in Internal Costs

-300.0

-200.0

-100.0

0.0

100.0

200.0

300.0

400.0


Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)


The graph below shows the sensitivity of the analysis to the inclusion of employment as an impactcategory. The graph has been produced by including employment along with the other environmentalimpacts used in the baseline analysis. The graph shows that the results achieved and conclusionsdrawn are not sensitive to inclusion of this external impact category.

Graph 52 : PE film: Sensitivity of the results to the inclusion of employment as an impact category

PE film Total Social Cost when including employment as an impact category

-300

-200

-100

0

100

200

300

400


Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)

7.4.2 Sensitivity analysis: Scenario and modelling choices


Table 27 : Summary of sensitivity analysis of scenario and modelling choices for PE filmParameter investigated Influence on CBA results Influence on conclusions drawnIncineration model

Combined heat and powerIncineration costs reducedNo effect on the relativestanding of scenarios

No effect on the choice ofoptimal scenario


Incineration costs reducedNo effect on the relativestanding of scenarios


Transport distancesCollection for landfill and

incinerationCollection for recycling

No effect on the relativestanding of scenarios


Offset virgin production – saveratio considered



8 Corrugated board from industrial sources



Table 28 : Scenarios considered for corrugated boardSelective collection scheme Recycling rate achieved MSW waste management

optionScenario 1 None 0% LandfillScenario 2 None 0% IncinerationScenario 3 Separate collection 70-90% LandfillScenario 4 Separate collection 70-90% Incineration

8.2 Results of the cost benefit analysis for corrugated board

This section presents and discusses the results of the cost benefit analysis for corrugated board.

Table 29 : Corrugated board: Internal costs, external costs and total social costs


GWP (kg CO2 eq.) 32.3 16.9 24.1 to 21.8 19.5 to 20.2Ozone depletion (kg CFC 11 eq.) 0.0 0.0 0.0 to 0.0 0.0 to 0.0

Acidification (Acid equiv.) -0.2 -0.4 -0.4 to -0.5 -0.5 to -0.6Toxicity Carcinogens (Cd equiv) 0.0 0.0 0.0 to 0.0 0.0 to 0.0

Toxicity Gaseous (SO2 equiv.) -0.7 -1.6 -1.3 to -1.5 -1.6 to -1.6Toxicity Metals non carcinogens (Pb equiv.) 0.0 -0.2 -0.2 to -0.2 -0.2 to -0.2

Toxicity Particulates & aerosols (PM10 equiv) 2.6 -14.1 -26.1 to -34.3 -31.1 to -36.0Toxicity Smog (ethylene equiv.) 1.8 -0.1 -0.2 to -0.8 -0.8 to -1.0

Black smoke (kg dust eq.) -0.3 -1.4 -1.9 to -2.4 -2.2 to -2.5Fertilisation -0.2 0.0 0.4 to 0.5 0.4 to 0.5


Traffic Noise (car km equiv.) 0.1 0.1 0.1 to 0.0 0.1 to 0.1Water Quality Eutrophication (P equiv.) 0.0 0.0 0.0 to 0.0 0.0 to 0.0

Disaminity (kg LF waste equiv.) 37.0 11.2 11.3 to 4.0 3.6 to 1.4TOTAL EXTERNALITIES 73.9 11.8 14.0 to -3.1 -4.7 to -9.4INTERNAL COSTS 148.8 154.8 84.5 to 66.2 86.3 to 66.8TOTAL SOCIAL COSTS 222.7 166.6 98.5 to 63.0 81.7 to 57.4

Recycling Recycling


Graph 53 : Corrugated board: Total social costs

Corrugated Board from industrial sourcesTotal Social Cost

0.0

50.0

100.0

150.0

200.0

250.0

Landfill Incineration Recycling / landfill Recycling /incineration

Scenario

To

tal S

oci

al C

ost

(E

uro

p

er t

on

ne)

8.3 Main findings:

Where landfill is the MSW option, recycling of source separated material (achieving a recycling rate of70-90%) is the optimum waste management system for the scenarios considered.Where incineration is the MSW option, recycling of source separated material (achieving a recyclingrate of 70-90%) is the optimum waste management system for the scenarios considered.



The graph shows that the results achieved and conclusions that can be drawn are highly sensitive to theeconomic valuations applied.

Graph 54 : Corrugated board: Sensitivity of the results to the external economic valuations applied

Corrugated Board from industrial sourcesSensitivity analysis on variations in economic valuations applied

0.0

100.0

200.0

300.0

400.0

500.0

600.0

700.0

800.0

900.0


Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)


The graph shows that the results achieved and conclusions that can be drawn are not sensitive to thisparameter.

Graph 55 : Corrugated board: Sensitivity of the results to the internal economic costs considered.

Corrugated Board from industrial sourcesSensitivity analysis on variations in Internal Costs

0.0

50.0

100.0

150.0

200.0

250.0

300.0


Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)



The graph shows that the results achieved and conclusions that can be drawn are not sensitive to thisparameter.

Graph 56 : Corrugated board: Sensitivity of the results to the addition of employment as an impactcategory

Corrugated boardTotal Social Cost when including employment as an impact category

0

50

100

150

200

250


Scenario

To

tal S

oci

al C

ost

(E

uro

per

to

nn

e)



Table 30 : Summary of sensitivity analysis of scenario and modelling choices for corrugated boardParameter investigated Influence on CBA results Influence on conclusions drawnIncineration model

Combined heat and powerTotal social cost of incinerationreducedNo effect on the relativestanding of scenarios

No effect on choice of optimumsystem


Total social cost of incinerationreducedNo effect on the relativestanding of scenarios


Transport distancesCollection for landfill or

incinerationCollection for recycling



Reprocessing overseasAddition of a distance of

1000 km by ocean ship



Annex 11: Presentation of the Global recycling targets per MemberState

This section presents the results of the targets calculation per Member State.

The 16 first pages concern the calculation of the minimum recycling targets, i.e. applying the lowest

recycling rate of the ranges to the packaging mix described in annex 6. The 16 last pages concern

the calculation of the maximum recycling targets per Member State, i.e. applying the highest

recycling rate of the ranges to the packaging mix described in annex 6.

The calculation methodology is described in the main report in chapter 3.4.

Minimum recycling ratesAUSTRIA 2000 Amount of Amount of waste


Plastics Total 75 33LDPE films 55 29Other 20 4

Wood 60 29Steel 4 3Cardboard 384 233glass 47 22Other 0 0

Total 570 320



Plastics 112 25PET bottles 20 70% 35% 59% 59% 13LPDE films 24 0% 0% 0% 0% 0HDPE bottles 24 57% 28% 48% 48% 13other 44 0% 0% 0% 0% 0

Steel 69 15% 80% 40% 80% 24aluminium total 9 2Wood 0 0% 0% 0% 0% 0Cardboard total 98 61% 61% 55% 55% 57composites liquid beverage cartons 23 0% 0% 0% 0% 0

mainly based on plastic 4 0% 0% 0% 0% 0mainly based on cardboard 5 0% 0% 0% 0% 0mainly based on Aluminium 3 0% 0% 0% 0% 0

Glass 183 73% 73% 42% 42% 104Other 0 0% 0% 0% 0% 0

Total 506 211


Total 1,076 532


data in blue are input data specific to each MSdata in red are the results of this studydata in green is calculated based on blue and red data

21%

50%

0% 55%0%

80%

0%0%

0%0%0%

0%

50%

64%


5% 95%


Low High

Minimum recycling ratesBelgium 2000 Amount of Amount of waste




Total 704 382






Glass 330 73% 73% 42% 42% 153Other 0 0% 0% 0% 0% 0

Total 768 322


Total 1,472 704



Low High

Optimised recycling/reuse targetLow packaging amount


0% 50%0% 0%

High packaging amount5% 95%

0% 55%0% 21%

0% 64%

0% 50%0% 80%

Minimum recycling ratesDENMARK 2000 Amount of Amount of waste




Total 518 278



Plastics 63 38PET bottles 5 70% 35% 59% 59% 2LPDE films 20 0% 0% 0% 0% 0HDPE food bottles 17 57% 28% 48% 48% 6other 21 0% 0% 0% 0% 0



Glass 176 73% 73% 42% 42% 110Other 0 0% 0% 0% 0% 0

Total 416 221


Total 934 499



0% 64%0% 50%0% 0%

0% 21%0% 55%


5% 95%


Low High

0% 50%0% 80%

Minimum recycling ratesFINLAND 2000 Amount of Amount of waste


Plastics Total 48 17LDPE films 22 12other 26 5


Total 264 150






Glass 50 73% 73% 42% 42% 30Other 0 0% 0% 0% 0% 0

Total 162 56


Total 425 206



Low High



0% 50%0% 0%


0% 55%0% 21%

0% 64%

0% 50%0% 80%

Minimum recycling ratesFRANCE 2000 Amount of Amount of waste



Wood 1,690 803Steel 280 213Cardboard 3,100 1,885glass 960 456Other 0 0

Total 6,760 3,588






Glass 2,550 73% 73% 42% 42% 1,308Other 0 0% 0% 0% 0% 0

Total 4,901 2,195


Total 11,661 5,783




Low High


5% 95%

0% 55%

0% 64%0% 50%0% 0%

50%0% 80%

0% 21%0%

Minimum recycling ratesGERMANY 2000 Amount of Amount of waste



Wood 1,969 935Steel 654 497Cardboard 4,350 2,645glass 88 42Other 0 0

Total 7,930 4,419






Glass 3,512 73% 73% 42% 42% 1,758Other 14 0% 0% 0% 0% 0

Total 5,867 2,638


Total 13,798 7,058




Low High


5% 95%

0% 55%

0% 64%0% 50%0% 0%

50%0% 80%

0% 21%0%

Minimum recycling ratesGREECE 2000 Amount of Amount of waste


Plastics Total 129.4 35LDPE films 27.8 15Other 101.6 21

Wood 38.3 18Steel 107.8 82Cardboard 402.7 245glass 118.1 56Other 21.6 0

Total 818 436






Glass 145 73% 73% 42% 42% 79Other 0 0% 0% 0% 0% 0

Total 818 316


Total 1,635 752




Low High


5% 95%

0% 55%

0% 64%0% 50%0% 0%

50%0% 80%

0% 21%0%

Minimum recycling ratesIRELAND 2000 Amount of Amount of waste




Total 387 194






Glass 59 73% 73% 42% 42% 34Other 32 0% 0% 0% 0% 0

Total 300 82


Total 687 276



0% 64%0% 50%0% 0%

0% 21%0% 55%


5% 95%


Low High

0% 50%0% 80%

Minimum recycling ratesITALY 2000 Amount of Amount of waste



Wood 2,295 1,090Steel 223 170Cardboard 2,875 1,748glass 60 28Other 0 0

Total 6,043 3,240



Plastics 1,309 368PET bottles 426 70% 35% 59% 59% 261LPDE films 248 0% 0% 0% 0% 0HDPE bottles 215 57% 28% 48% 48% 107other 420 0% 0% 0% 0% 0

Steel 247 15% 80% 40% 80% 91aluminium total 57 10Wood 109 0% 0% 0% 0% 0Cardboard total 1,300 61% 61% 55% 55% 737composites liquid beverage cartons 10 0% 0% 0% 0% 0


Glass 2,189 73% 73% 42% 42% 1,110Other 0 0% 0% 0% 0% 0

Total 5,227 2,316


Total 11,270 5,556



0% 50%0% 80%


Low High


5% 95%

0% 21%0% 55%

0% 64%0% 50%0% 0%

max

Minimum recycling ratesLUXEMBOURG 2000 Amount of Amount of waste




Total 36 20




Steel 2 15% 80% 40% 80% 1aluminium total 0.5 0Wood 0 0% 0% 0% 0% 0Cardboard total 11 61% 61% 55% 55% 7composites liquid beverage cartons 1 0% 0% 0% 0% 0


Glass 17 73% 73% 42% 42% 9Other 0 0% 0% 0% 0% 0

Total 40 19


Total 77 38



0% 50%0% 80%


Low High


5% 95%

0% 21%0% 55%

0% 64%0% 50%0% 0%

Minimum recycling ratesNL 2000 Amount of Amount of waste



Wood 379 180Steel 118 90Cardboard 1,128 686glass 23 11Other 0 0

Total 1,905 1,049






Glass 436 73% 73% 42% 42% 200Other 0 0% 0% 0% 0% 0

Total 1,291 569


Total 3,196 1,618



0% 64%

0% 50%0% 80%

0%


0% 55%0% 21%

Low High



0% 50%0%

Minimum recycling ratesPORTUGAL 2000 Amount of Amount of waste




Total 152 87






Glass 314 73% 73% 42% 42% 171Other 0 0% 0% 0% 0% 0

Total 915 418


Total 1,067 505



0% 50%0% 80%


Low High


5% 95%

0% 21%0% 55%

0% 64%0% 50%0% 0%

Minimum recycling ratesSPAIN 2000 Amount of Amount of waste




Total 2,702 1,356






Glass 1,523 73% 73% 42% 42% 899Other 19 0% 0% 0% 0% 0

Total 3,423 1,621


Total 6,125 2,977



0% 64%

0% 50%0% 80%

0%


0% 55%0% 21%

Low High



0% 50%0%

Minimum recycling ratesSWEDEN 2000 Amount of Amount of waste




Total 523 308






Glass 111 73% 73% 42% 42% 72Other 0 0% 0% 0% 0% 0

Total 433 190


Total 956 498



0% 50%0% 80%


Low High


5% 95%

0% 21%0% 55%

0% 64%0% 50%0% 0%

Minimum recycling ratesUK 2000 Amount of Amount of waste



Wood 670 318Steel 217 165Cardboard 3,373 2,051glass 350 166Other 40 0

Total 5,237 2,907






Glass 1,848 73% 73% 42% 42% 868Other 0 0% 0% 0% 0% 0

Total 4,068 1,606


Total 9,305 4,513



Low High

0%0%

areas where population density is L/H and waste are I/LPercentage of population living in

0%

0% 50%


5% 95%

0% 50%

55%0% 21%

0% 64%0% 80%

Minimum recycling ratesEU 2000 Amount of Amount of waste

Material Application waste to be recycled

Industrial waste 1000 t/year 1000 t/yearPlastics Total 4,018 1,348

LDPE films 1,651 869Other 2,367 479

Wood 7,812 3,711Steel 1,818 1,382Cardboard 18,823 11,444glass 1,789 850Other 289 0

Total 34,549 18,735



Plastics 5,871 1,374PET bottles 1,502 70% 35% 59% 59% 887LPDE films 1,205 0% 0% 0% 0% 0HDPE bottles 1,015 57% 28% 48% 48% 487other 2,150 0% 0% 0% 0% 0

Steel 2,214 15% 80% 40% 80% 1,022aluminium total 391.6 96

cans 140 31% 76% 45% 76% 72other rigid and semi-rigid 131 0% 50% 6% 50% 24flexible 121 0% 0% 0% 0% 0

Wood 128 0% 0% 0% 0% 0Cardboard total 5,947 61% 61% 55% 55% 3,411composites liquid beverage cartons 710 0% 0% 0% 0% 0


Glass 13,445 73% 73% 42% 42% 7,288Other 65 0% 0% 0% 0% 0

Total 29,132 13,191


Total 63,681 31,926



0% 55%


5% 95%

0% 50%0%

21%0%0% 50%0% 80%

64%

Low High

0%0%


Maximum recycling ratesAUSTRIA 2000 Amount of Amount of waste




Total 570 420






Glass 183 83% 83% 91% 91% 160Other 0 0% 0% 0% 0% 0

Total 506 302


Total 1,076 722




Low High


5% 95%

0%0%

0%0%0%

0%

70%

80%

41%

83%

0% 75%0%

90%

Maximum recycling ratesBelgium 2000 Amount of Amount of waste




Total 704 494






Glass 330 83% 83% 91% 91% 297Other 0 0% 0% 0% 0% 0

Total 768 497


Total 1,472 991



0% 80%

0% 70%0% 90%

0%


0% 75%0% 41%

Low High



0% 83%0%

Maximum recycling ratesDENMARK 2000 Amount of Amount of waste




Total 518 363



Plastics 63 40PET bottles 5 80% 45% 69% 69% 3LPDE films 20 0% 0% 0% 0% 0HDPE food bottles 17 67% 38% 58% 58% 8other 21 0% 0% 0% 0% 0



Glass 176 83% 83% 91% 91% 151Other 0 0% 0% 0% 0% 0

Total 416 276


Total 934 639



0% 70%0% 90%


Low High


5% 95%

0% 41%0% 75%

0% 80%0% 83%0% 0%

Maximum recycling ratesFINLAND 2000 Amount of Amount of waste


Plastics Total 48 26LDPE films 22 16other 26 10


Total 264 192






Glass 50 83% 83% 91% 91% 43Other 0 0% 0% 0% 0% 0

Total 162 78


Total 425 270



0% 80%

0% 70%0% 90%

0%


0% 75%0% 41%

Low High



0% 83%0%

Maximum recycling ratesFRANCE 2000 Amount of Amount of waste




Total 6,760 4,847






Glass 2,550 83% 83% 91% 91% 2,259Other 0 0% 0% 0% 0% 0

Total 4,901 3,326


Total 11,661 8,173



70%0% 90%

0% 41%0%

0% 80%0% 83%0% 0%

0% 75%


5% 95%


Low High

Maximum recycling ratesGERMANY 2000 Amount of Amount of waste




Total 7,930 5,709






Glass 3,512 83% 83% 91% 91% 3,123Other 14 0% 0% 0% 0% 0

Total 5,867 4,186


Total 13,798 9,895



70%0% 90%

0% 41%0%

0% 80%0% 83%0% 0%

0% 75%


5% 95%


Low High

Maximum recycling ratesGREECE 2000 Amount of Amount of waste


Plastics Total 129.4 60LDPE films 27.8 20Other 101.6 40

Wood 38.3 25Steel 107.8 92Cardboard 402.7 306glass 118.1 93Other 21.6 0

Total 818 576






Glass 145 83% 83% 91% 91% 127Other 0 0% 0% 0% 0% 0

Total 818 428


Total 1,635 1,004



70%0% 90%

0% 41%0%

0% 80%0% 83%0% 0%

0% 75%


5% 95%


Low High

Maximum recycling ratesIRELAND 2000 Amount of Amount of waste




Total 387 258






Glass 59 83% 83% 91% 91% 51Other 32 0% 0% 0% 0% 0

Total 300 114


Total 687 372



0% 70%0% 90%


Low High


5% 95%

0% 41%0% 75%

0% 80%0% 83%0% 0%

Maximum recycling ratesITALY 2000 Amount of Amount of waste




Total 6,043 4,265




Steel 247 60% 80% 60% 80% 152aluminium total 57 15Wood 109 0% 0% 0% 0% 0Cardboard total 1,300 71% 71% 65% 65% 867composites liquid beverage cartons 10 0% 0% 0% 0% 0


Glass 2,189 83% 83% 91% 91% 1,943Other 0 0% 0% 0% 0% 0

Total 5,227 3,409


Total 11,270 7,674



0% 70%0% 90%


Low High


5% 95%

0% 41%0% 75%

0% 80%0% 83%0% 0%

max

Maximum recycling ratesLUXEMBOURG 2000 Amount of Amount of waste




Total 36 26






Glass 17 83% 83% 91% 91% 15Other 0 0% 0% 0% 0% 0

Total 40 26


Total 77 52



0% 70%0% 90%


Low High


5% 95%

0% 41%0% 75%

0% 80%0% 83%0% 0%

Maximum recycling ratesNL 2000 Amount of Amount of waste




Total 1,905 1,360






Glass 436 83% 83% 91% 91% 392Other 0 0% 0% 0% 0% 0

Total 1,291 829


Total 3,196 2,188



0% 80%

0% 70%0% 90%

0%


0% 75%0% 41%

Low High



0% 83%0%

Maximum recycling ratesPORTUGAL 2000 Amount of Amount of waste




Total 152 113






Glass 314 83% 83% 91% 91% 276Other 0 0% 0% 0% 0% 0

Total 915 584


Total 1,067 697



0% 70%0% 90%


Low High


5% 95%

0% 41%0% 75%

0% 80%0% 83%0% 0%

Maximum recycling ratesSPAIN 2000 Amount of Amount of waste




Total 2,702 1,770






Glass 1,523 83% 83% 91% 91% 1,319Other 19 0% 0% 0% 0% 0

Total 3,423 2,229


Total 6,125 3,999



0% 80%

0% 70%0% 90%

0%


0% 75%0% 41%

Low High



0% 83%0%

Maximum recycling ratesSWEDEN 2000 Amount of Amount of waste




Total 523 395






Glass 111 83% 83% 91% 91% 95Other 0 0% 0% 0% 0% 0

Total 433 234


Total 956 629



0% 70%0% 90%


Low High


5% 95%

0% 41%0% 75%

0% 80%0% 83%0% 0%

Maximum recycling ratesUK 2000 Amount of Amount of waste




Total 5,237 3,789






Glass 1,848 83% 83% 91% 91% 1,658Other 0 0% 0% 0% 0% 0

Total 4,068 2,594


Total 9,305 6,384



Low High

0%0%


0%

0% 70%


5% 95%

0% 83%

75%0% 41%

0% 80%0% 90%

Maximum recycling ratesEU 2000 Amount of Amount of waste

Material Application waste to be recycled

Industrial waste 1000 t/year 1000 t/yearPlastics Total 4,018 2,111

LDPE films 1,651 1,182Other 2,367 929

Wood 7,812 5,195Steel 1,818 1,555Cardboard 18,823 14,306glass 1,789 1,411Other 289 0

Total 34,549 24,577



Plastics 5,871 1,626PET bottles 1,502 80% 45% 69% 69% 1,037LPDE films 1,205 0% 0% 0% 0% 0HDPE bottles 1,015 67% 38% 58% 58% 589other 2,150 0% 0% 0% 0% 0

Steel 2,214 60% 80% 60% 80% 1,472aluminium total 391.6 122Wood 128 0% 0% 0% 0% 0Cardboard total 5,947 71% 71% 65% 65% 4,006composites liquid beverage cartons 710 0% 0% 0% 0% 0


Glass 13,445 83% 83% 91% 91% 11,811Other 65 0% 0% 0% 0% 0

Total 29,132 19,036


Total 63,681 43,613



0% 75%


5% 95%

0% 83%0%

41%0%0% 70%0% 90%

80%

Low High

0%0%


$QQH[��3UHVHQWDWLRQ�RI�WKH�&%$�UHVXOWV��UHXVH�

5HILOODEOH�DQG�VLQJOH�WULS�3(7�EHYHUDJH�ERWWOHV�IURP�KRXVHKROGVRXUFHV

6FHQDULRV�FRQVLGHUHGIn order to investigate the potential costs and benefits of refillable PET beverage bottles, the purchase of 1000 litresof product by the consumer is compared for single trip and refillable bottles. The analysis relates to 1.5 litrebottles. The weight of a refillable bottle is assumed to be 0.084 kg1. The weight of a single trip bottle is assumedto be 0.039 kg2.

It is assumed that costs and burdens of transport will increase linearly as distance between filler and end marketincreases. In order to compare the costs and benefits of single trip and refillables over a range of distances, eightwide-ranging scenarios have been modelled. These are listed in the table below:

6FHQDULRV�FRQVLGHUHG�IRU�VLQJOH�WULS�DQG�UHILOODEOH�3(7�EHYHUDJH�ERWWOHV

Scenario Distance to market* Number of uses Recycling rateReuse Scenario 1 0km 5 (i.e. every 6th bottle is new)Reuse Scenario 2 1800km 5 (i.e. every 6th bottle is new)Reuse Scenario 3 0km 20 (i.e. every 21st bottle is new)Reuse Scenario 4 1800km 20 (i.e. every 21st bottle is new)Single trip scenario 1 0km 20%Single trip scenario 2 1800km 20%Single trip scenario 3 0 km 80%Single trip scenario 4 1800 km 80%*Distance to market = distance from filler to distribution centre*Transport from distribution centre to supermarket / retail outlet is assumed to be a 100 km round trip for allscenarios

The following assumptions have been made in order to simplify the analysis:♦ The common elements between the reusable and single trip bottles have been ignored. These include caps,

labels, and tertiary packaging♦ Returnable bottles are assumed to be packed in reusable crates (99,4% reuse)♦ Single trip bottles are packed in cartonboard trays with plastic film overwrap (100% to recycling)♦ The return rate for the refillable PET bottles is 100%. All losses occur during the washing and refilling

process.♦ For single trip PET bottles, the portion that is not recycled is split evenly between landfill and incineration

1 ³/LIH� &\FOH� $VVHVVPHQW� RI� 3DFNDJLQJ� 6\VWHPV� IRU� %HHU� DQG� 6RIW� 'ULQNV�� 'LVSRVDEOH� 3(7� %RWWOHV´� DanishEnvironmental Protection Agency, 19982 ³/LIH� &\FOH� $VVHVVPHQW� RI� 3DFNDJLQJ� 6\VWHPV� IRU� %HHU� DQG� 6RIW� 'ULQNV�� 'LVSRVDEOH� 3(7� %RWWOHV´� DanishEnvironmental Protection Agency, 1998

&DOFXODWLRQ�RI�LQWHUQDO�FRVWVThe internal costs used for the analysis are listed in the table below.

,QWHUQDO�FRVWV��3(7�VLQJOH�WULS

,QWHUQDO�FRVWV��3(7�UHILOODEOHV

6\VWHP

WUDQVSRUW�GLVWDQFH�IURP�ILOOHU�WR�GLVWULEXWRU��NP�

5HF\FOLQJ�UDWH��%ULQJ�VFKHPH��

QXPEHU�RI�QHZ�ERWWOHV�SHU��O�

3ULPDU\�SURGXFWLRQ�FRVWV��(XUR�SHU��O�SURGXFW�SXUFKDVHG�E\�FRQVXPHU�

&RVW�RI�GLVWULEXWLRQ�DQG�KDQGOLQJ��SHU��OLWUHV�SURGXFW�SXUFKDVHG�E\�FRQVXPHU�

)LOOHUV�FRVWV��OLWUHV�RI�SURGXFW�SXUFKDVHG�E\�FRQVXPHU�


FRVW�RI�ZDVWH�PDQDJHPHQW��SHU�WRQQH�RI�3(7�

&RVW�RI�ZDVWH�PDQDJHPHQW��SHU��O�SURGXFW�SUXFKDVHG�E\�FRQVXPHU�

7RWDO�FRVW�SHU��OLWUHV�RI�SURGXFW�SXUFKDVHG�E\�FRQVXPHU

System 1 0km 0.20 666.67 68.09 0.00 0.00 0.00 443.60 11.53 79.63System 2 1800km 0.20 666.67 68.09 518.69 0.00 1800.00 443.60 11.53 598.31System 3 0km 0.80 666.67 68.09 0.00 0.00 0.00 783.20 20.36 88.46System 4 1800km 0.80 666.67 68.09 518.69 0.00 1800.00 783.20 20.36 607.14

number of uses return rate

transport to market (all round distance from filling to market and back again) (km)

Frequency of bottle replacement

Number of new bottles per 1000l product purchased by consumer

new PET bottles required for 1000l product purchased by consumer (kg)

Cost of primary production per 1000l

GLVWULEXWLRQ�DQG�KDQGOLQJ�LQFOXGLQJ�UHWXUQ�WULS��SHU��OLWUHV�SURGXFW�SXUFKDVHG�filler

Cost of collection/sorting (per 1000litres of product purchased by consumer)

Waste management of non-reused bottles

System 1 5.00 100% 0.00 5.00 133.33 11.20 12.60 0.00 60.84 3.84System 2 5.00 100% 3600.00 5.00 133.33 11.20 12.60 940.53 60.84 3.84System 3 20.00 100% 0.00 20.00 33.33 2.80 50.39 0.00 60.84 0.96System 4 20.00 100% 3600.00 20.00 33.33 2.80 50.39 940.53 60.84 0.96

&DOFXODWLRQ�RI�H[WHUQDOLWLHV

The external costs of each scenario are presented in the table below:

([WHUQDO�FRVWV��3(7�UHILOODEOHV

ObservationsThe transportation distance plays a much more important role than the number of uses :

• DELTA = 2.53 ¼�EHWZHHQ��DQG��XVHV• DELTA = 99.43 ¼�IRU��NP��L�H��¼�IRU��NP�

The external costs are small compared to the internal costs (5-10%)

([WHUQDO�FRVW��3(7�VLQJOH�WULS

HeadingNameRefillables System 1

Refillables System 2



GWP (kg CO2 eq.) 0.32 3.32 0.16 3.16Ozone depletion (kg CFC 11 eq.) 0.00 0.00 0.00 0.00Acidification (Acid equiv.) 0.06 0.24 0.02 0.20Toxicity Carcinogens (Cd equiv) 0.00 0.01 0.00 0.01Toxicity Gaseous (SO2 equiv.) 0.20 0.76 0.06 0.62Toxicity Metals non carcinogens (Pb equiv.) 0.03 0.12 0.01 0.10Toxicity Particulates & aerosols (PM10 equiv) 5.85 50.31 4.03 48.49Toxicity Smog (ethylene equiv.) 0.26 1.89 0.10 1.74Black smoke (kg dust eq.) 0.16 0.84 0.06 0.74Fertilisation -0.09 -0.90 -0.04 -0.85Traffic accidents (risk equiv.) 0.13 2.02 0.12 2.01Traffic Congestion (car km equiv.) 2.80 47.41 2.71 47.32Traffic Noise (car km equiv.) 0.23 3.28 0.19 3.25Water Quality Eutrophication (P equiv.) 0.01 0.07 0.00 0.07Disaminity (kg LF waste equiv.) 0.00 0.00 0.00 0.00

Total external cost 9.95 109.38 7.42 106.84Internal costs 234.80 1175.34 106.05 1046.58

Total social cost 244.76 1284.72 113.47 1153.43

+HDGLQJ1DPH 6LQJOH�WULS�V\VWHP�� 6LQJOH�WULS�V\VWHP�� 6LQJOH�WULS��V\VWHP�� 6LQJOH�WULS�V\VWHP��


7RWDO�H[WHUQDO�FRVW ��

5HVXOWV�RI�WKH�FRVW�EHQHILW�DQDO\VLVThe results of analysis are presented in the three graphs below. The graphs present the internal costs and externalcosts and total social costs (i.e. the sum of the internal and external costs) for each scenario as a function ofdistance to market.

,QWHUQDO�FRVWV�±�3(7�UHILOOV�DQG�VLQJOH�WULS

,QWHUQDO�FRVWV��UHWXUQDEOHV�YHUVXV�VLQJOH�WULS��DVVXPLQJ��UHWXUQ�UDWH�

0

100

200

300

0 50 100 150 200

'LVWDQFH�WR�PDUNHW��NP�

,QWHUQDO�FRVW��(XUR�SHU��O�SURGXFW�

SXUFKDVHG�E\�FRQVXPHU�

returnables (5reuses)




([WHUQDO�FRVWV�±3(7�UHILOOV�DQG�VLQJOH�WULS

([WHUQDO�FRVWV��UHWXUQDEOHV�YHUVXV�VLQJOH�WULS��DVVXPLQJ��UHWXUQ�UDWH�

0

5

10

15

20

25

30

0 50 100 150 200 250 300


([WHUQDO�FRVW��(XUR�SHU��O�SURGXFW�

SXUFKDVHG�E\�FRQVXPHU�





7RWDO�VRFLDO�FRVWV�±�3(7�UHILOOV�DQG�VLQJOH�WULS

7RWDO�VRFLDO�FRVWV��UHWXUQDEOHV�YHUVXV�VLQJOH�WULS��DVVXPLQJ��UHWXUQ�UDWH�

0

100

200

300

400

0 50 100 150 200


7RWDO�VRFLDO�FRVW��(XUR�SHU��O�SURGXFW�

SXUFKVHG�E\�FRQVXPHU�





c

,QLWLDO�FRQFOXVLRQV�From an internal cost perspective:♦ Single trip PET bottles are always preferable to refillables

From an external cost perspective:♦ Refillables are preferable to single trip bottles up until approximately 30km♦ Above approximately 150km, single trip bottles are preferable♦ Between 30 and 1500km, the preferred option is dependent on the number of reuses achieved by the refillables

and the recycling rate achieved for the single trip bottles

From a total social cost perspective:♦ Single trip bottles are always preferable to refillables whatever distance is considered.♦ Internal costs outweight the external costs. The eco-efficiency of switching from single trip without recycling

to single trip with recycling is in any case considerably higher than switching from single trip to refillable (thisswitch might even be negative,as soon as the distance exceeds 100-200 km).

6XPPDU\�RI�VHQVLWLYLW\�DQDO\VLV�UHVXOWVThe results achieved and conclusions drawn are sensitive to the economic valuations applied and the internal costsapplied.

5HILOODEOH�DQG�VLQJOH�WULS�*ODVV�EHYHUDJH�ERWWOHV�IURP�KRXVHKROGVRXUFHIn this section, the results for glass refillable and single trip beverage bottles are explained. For other cases studies,the main results, conclusions and the implications of the sensitivity analysis are presented only.

6FHQDULRV�FRQVLGHUHGIn order to investigate the potential costs and benefits of refillable glass beverage bottles, the purchase of 1000 l ofproduct by the consumer is compared for single trip and refillable bottles. The analysis relates to 330 ml bottles.The weight of a refillable bottle is assumed to be 0.33kg, with the weight of a single trip bottle assumed to be 0.22kg.

It is assumed that costs and burdens of transport will increase in a linear manor as distance between filler and endmarket increases. In order to compare the costs and benefits of single trip and refillables over a range of distances,eight wide-ranging scenarios have been modelled. These are listed in the table below:

Scenarios considered for single trip and refillable glass beverage bottles

Scenario Distance to market* Number of reuses Recycling rateReuse Scenario 1 0km 5 (i.e. every 6th bottle is

new)Reuse Scenario 2 1800km 5 (i.e. every 6th bottle is

new)Reuse Scenario 3 0km 20 (i.e. every 21st bottle is

new)Reuse Scenario 4 1800km 20 (i.e. every 21st bottle is

new)Recycling scenario 1 0km 42%Recycling scenario 2 1800km 42%Recycling scenario 3 0km 91%Recycling scenario 4 1800km 91%*Distance to market = distance from filler to distribution centre*Transport from distribution centre to supermarket/retail outlet is assumed to be a 100 km round trip for allscenarios

The following assumptions have been made in order to simplify the analysis:♦ Common elements between the reusable and single trip bottles have been ignored. These include – the caps,

labels, and transport packaging.♦ the Returnable bottles are assumed to be packed in reusable plastic crates (99.4% reuse)♦ the single trip bottles are packed in Cartonboard trays with plastic film over wrap 100% of which goes to

material recycling♦ The return rate for the refillable glass bottle is assumed to be100%. All losses occur during the washing and

refilling process.♦ For single trip glass bottles, the portion that is not recycled is split evenly between landfill and incineration

&DOFXODWLRQ�RI�LQWHUQDO�FRVWVThe internal costs used for the analysis are listed in the table below.

,QWHUQDO�FRVWV��*ODVV�VLQJOH�WULS

,QWHUQDO�FRVWV��*ODVV�UHILOODEOHV

6\VWHP


5HF\FOLQJ�UDWH��%ULQJ�VFKHPH�� 1XPEHU�RI�

:HLJKW�RI�QHZ�JODVV�ERWWOHV�UHTXLUHG�IRU��O�SURGXFW�SXUFKDVHG�E\�FRQVXPHU��NJ�

&RVW�RI�JODVV�SURGXFWLRQ��OLWUHV�SXUFKDVHG�SURGXFW�

&RVW�RI�WUDQVSRUW�IURP�JODVV�IDFWRU\�WR�ILOOHUV��OLWUHV�RI�SURGXFW�SXUFKDVHG�E\�FRQVXPHU�

)LOOHUV�FRVWV��OLWUHV�RI�SURGXFW�SXUFKDVHG�E\�FRQVXPHU�


&RVW�RI�WUDQVSRUW�IURP�ILOOHUV�WR�GLVWULEXWLRQ��SHU��OLWUHV�SURGXFW�SXUFKDVHG�E\�FRQVXPHU�

FRVW�RI�ZDVWH�PDQDJHPHQW��SHU�WRQQH�RI�JODVV�

&RVW�RI�ZDVWH�PDQDJHPHQW��SHU��O�SURGXFW�SUXFKDVHG�E\�FRQVXPHU�

7RWDO�FRVW�SHU��OLWUHV�RI�SURGXFW�SXUFKDVHG�E\�FRQVXPHU

System 1 0km 0.42 3030.30 666.67 132.53 10.20 223.43 0.00 0.00 124.01 82.67 448.83System 2 1800km 0.42 3030.30 666.67 132.53 10.20 223.43 1800.00 2988.00 124.01 82.67 3436.83System 3 0km 0.91 3030.30 666.67 132.53 10.20 223.43 0.00 0.00 66.98 44.65 410.81System 4 1800km 0.91 3030.30 666.67 132.53 10.20 223.43 1800.00 2988.00 66.98 44.65 3398.81

number of reuses return rate

transport to market (all round distance from filling to market and back again) (km)

Frequency of bottle replacement

Number of new bottles per 1000l product purchased by consumer

new glass bottles required for 1000l product purchased by consumer (kg)

Cost of glass production (1000litres purchased product)

transport from glass factory to fillers (1000litres of product purchased by consumer)

Fillers costs (1000litres of product purchased by consumer)

transport from fillers to distribution (per 1000litres product purchased by

Cost of deposit infrastructure (per 1000litres of product purchased by consumer)

transport from deposit to sorting plant (per 1000litres product purchased by

sorting before washing (costs per 1000l product purchased by consumer)

transport from sorting to fillers (euro per 1000litres product purchased by

washing (Eurp per 1000l product purchased by consumer)

Waste management of non-reused bottles

Total costs Euro per 1000litres product purchased by consumer)

System 1 5.00 100% 0.00 5.00 606.06 200.00 39.76 3.06 71.58 0.00 27.62 4.01 11.70 0.00 75.15 16.26 ��

System 2 5.00 100% 3600.00 5.00 606.06 200.00 39.76 3.06 71.58 2988.00 27.62 4.01 11.70 2988.00 75.15 16.26 ��

System 3 20.00 100% 0.00 20.00 151.52 50.00 9.94 0.77 71.58 0.00 27.62 4.01 11.70 0.00 75.15 4.06 ��

System 4 20.00 100% 3600.00 20.00 151.52 50.00 9.94 0.77 71.58 2988.00 27.62 4.01 11.70 2988.00 75.15 4.06 ��

System 5 5.00 50% 0.00 2.50 1212.12 400.00 79.52 6.12 71.58 0.00 55.25 2.01 5.85 0.00 37.58 32.52 ��

System 6 5.00 50% 3600.00 2.50 1212.12 400.00 79.52 6.12 71.58 2988.00 55.25 2.01 5.85 1494.00 37.58 32.52 ��

System 7 20.00 50% 0.00 10.00 303.03 100.00 19.88 1.53 71.58 0.00 55.25 2.01 5.85 0.00 37.58 8.13 ��

System 8 20.00 50% 3600.00 10.00 303.03 100.00 19.88 1.53 71.58 2988.00 55.25 2.01 5.85 1494.00 37.58 8.13 ��

&DOFXODWLRQ�RI�H[WHUQDOLWLHVThe environmental models for each option were constructed using Pira International’s LCI/LCIA software PEMS.The life cycle inventory is then compiled. The environmental impacts associated with the inventory data set arethen calculated. To achieve this, the inventory data are characterised according to the potential impact categoriesthat they contribute to, and then multiplied by classification values. Finally, the impact assessment data ismultiplied by the economic valuations (as listed in annex 4) to achieve the external cost of each impact category

The external costs of each scenario are presented in the table below:

External costs: Glass refillables

External cost: Glass single trip

HeadingName 5HXVH�6\VWHP�� 5HXVH�6\VWHP�� 5HXVH�6\VWHP�� 5HXVH�6\VWHP��



+HDGLQJ1DPH 6LQJOH�WULS�V\VWHP�� 6LQJOH�WULS�V\VWHP�� 6LQJOH�WULS��V\VWHP�� 6LQJOH�WULS�V\VWHP��



5HVXOWV�RI�WKH�FRVW�EHQHILW�DQDO\VLVThe results of analysis are presented in the three graphs below. The graphs present the internal costs and externalcosts and total social costs (i.e. the sum of the internal and external costs) for each scenario as a function ofdistance to market.

,QWHUQDO�FRVWV�±�JODVV�UHILOOV�DQG�VLQJOH�WULS

Internal costs - returnables versus single trip (assuming 100% return rate)

300.00

400.00

500.00

600.00

700.00

800.00

50 100 150 200






([WHUQDO�FRVWV�±�JODVV�UHILOOV�DQG�VLQJOH�WULS

([WHUQDO�FRVWV��UHWXUQDEOHV�YHUVXV�VLQJOH�WULS��DVVXPLQJ��UHWXUQ�UDWH�

0.000

100.000

200.000

300.000

400.000

500.000

600.000

700.000

1000 2000 3000 4000 5000 6000






7RWDO�VRFLDO�FRVWV�±�JODVV�UHILOOV�DQG�VLQJOH�WULS

7RWDO�VRFLDO�FRVWV��UHWXUQDEOHV�YHUVXV�VLQJOH�WULS��DVVXPLQJ�

��UHWXUQ�UDWH�

700

800

900

1000

1100

1200

1300

1400

1500

150 200 250 300 350


7RWDO�VRFLDO�FRVW��(XUR�SHU��O�

SURGXFW�SXUFKVHG�E\�FRQVXPHU� returnables (5 reuses)




,QLWLDO�FRQFOXVLRQV�From an internal cost perspective:♦ Refillables are preferable to single trip bottles up until approximately 100km♦ Above approximately 150km, single trip bottles are preferable♦ Between 100 and 150km, the preferred option is dependent on the number of reuses achieved by the refillables


From an external cost perspective:♦ Refillables are preferable to single trip bottles up until approximately 2400km♦ Above 4200km, single trip bottles are preferable♦ Between 2400 and 42000km, the preferred option is dependent on the number of reuses achieved by the

refillables and the recycling rate achieved for the single trip bottles

From a total social cost perspective:♦ Refillables are preferable to single trip bottles up until approximately 175km♦ Above approximately 280km, single trip bottles are preferable♦ Between 175 and 280km, the preferred option is dependent on the number of reuses achieved by the refillables


6XPPDU\�RI�VHQVLWLYLW\�DQDO\VLV�UHVXOWVThe results achieved and conclusions drawn are sensitive to the economic valuations applied and to the internalcosts applied.

The distances over which the refillable bottles are a preferred option are sensitive to the return rate assumed. At areturn rate of less than 50% the refillables are no longer preferable from a total social cost perspective for anydistance.