technology transfer and investment risk in international …€¦ · annex v. applicability of...

Technology Transfer and Investment Risk in International Emissions Trading (TETRIS): Deliverable 3

Joint Implementation and Emissions Trading in Eastern Europe

Prepared by Jake Schmidt Jin Lee Andrzej Blachowicz Erin Silsbe

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ACKNOWLEDGMENTS Jake Schmidt (Manager International Program, Senior Policy Analyst), Jin Lee (Policy Associate), Andrzej Blachowicz (Brussels Representative), and Erin Silsbe (Policy Analyst) at the Center for Clean Air Policy (CCAP) prepared this paper for the Technology Transfer and Investment Risk in International Emissions Trading (TETRIS) project. This paper and the resulting analysis benefited greatly from the assistance of: the International Institute for Applied Systems Analysis (IIASA) which provided the detailed information on the results of the GAINS model; and EcoSolutions Consulting which provided the detailed “case study” of the application of the GAINS results to the JI situation in Poland. In addition, the paper benefited from the input of other team members in the TETRIS project, in particular the team from Ecoplan provided helpful comments.

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TABLE OF CONTENTS

I. INTRODUCTION ...........................................................................................................................................1 I.A TETRIS PROJECT AND PURPOSE OF ANALYSIS ..............................................................................................1

II. GHG EMISSIONS IN NEW MEMBER STATES AND ALLOCATION UNDER THE EU ETS ..........2 II.A GHG EMISSIONS ............................................................................................................................................3 II.B NATIONAL ALLOCATIONS...............................................................................................................................7 II.C SUMMARY ......................................................................................................................................................8

III. JOINT IMPLEMENTATION POTENTIAL IN EASTERN EUROPE.....................................................9 III.A ASSESSMENT METHODOLOGY: GAINS OVERVIEW........................................................................................9 III.B COUNTRY GROUPINGS..................................................................................................................................10 III.C GAINS RESULTS..........................................................................................................................................11 III.D JI POTENTIAL “REALITY CHECK”: POLAND CASE STUDY.............................................................................14

III.D.1 N2O Abatement Potential.....................................................................................................................15 III.D.2 CH4 Abatement Potential.....................................................................................................................16

III.E JI POTENTIAL IN EASTERN EUROPE ..............................................................................................................19 IV. EMISSIONS TRADING WITH CONVENTIONAL POLLUTANTS IN EU MEMBER STATES......27

IV.A NOX TRADING SCHEME IN THE NETHERLANDS.............................................................................................28 IV.B SO2 EMISSIONS TRADING PROGRAMME IN SLOVAKIA..................................................................................29 IV.C OTHER PROGRAMS .......................................................................................................................................30

IV.C.1 Swedish NOx Charge............................................................................................................................30 IV.C.2 SO2 and NOx Emissions Trading in Poland .........................................................................................30

IV.D SUMMARY ....................................................................................................................................................31 V. CONCLUSIONS............................................................................................................................................32

ANNEX I: MARGINAL COST CURVE DATA FOR CO2 EMISSIONS FOR RUSSIA AND UKRAINE (GAINS) .........................................................................................................................................................36

ANNEX II: MARGINAL COST CURVE DATA FOR N2O EMISSIONS FOR 8 COUNTRIES (GAINS) .....37

ANNEX III: MARGINAL COST CURVE DATA FOR CH4 EMISSIONS FOR 8 COUNTRIES (GAINS)....44

ANNEX IV: MARGINAL COST CURVE DATA FOR F-GAS EMISSIONS FOR 8 COUNTRIES (GAINS)........................................................................................................................................................................57

ANNEX V. APPLICABILITY OF POLAND GAINS RESULTS FOR JI ASSESSMENT ...............................69

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I. Introduction

I.A TETRIS Project and Purpose of Analysis TETRIS (Technology Transfer and Investment Risk in International Emissions Trading) is a multi-year, multi-agency project that aims to explore the economic and industrial impacts, as well as the prospects for achieving technology transfer, associated with the implementation of the Kyoto flexible mechanisms. It will also examine the extent to which greenhouse gas (GHG) emissions trading schemes outside the European Union (EU) are compatible with each other and the proposed European Union emissions trading scheme (EU ETS). This paper (or work package 5) will contribute to this effort by analyzing Joint Implementation (JI) and emissions trading systems in Eastern Europe.1 The main objectives include: • to gather data on emissions and allowance allocation in Eastern European countries • to assess the remaining scope and possibilities for JI in Acceding countries and the associated

technology transfer • to examine interactions with planned and existing trading schemes for other pollutants (SO2,

NOx) To achieve these objectives, the paper is further divided into three sections. Section two provides some background/context to the discussion of the EU ETS and the flexibility mechanisms of the Kyoto Protocol, namely JI. It further presents data on actual and projected GHG emissions and the likely allocation of EU allowances of new member states for the second trading period of the EU ETS. This information is to be used to model the market for trading and technology transfer under other work packages for the TETRIS project. Section three explores JI potential in the Eastern European region. Finally, section four presents the existing and planned trading schemes for other pollutants (SO2, NOx) in Europe and discusses some similarities and differences between these approaches and the EU ETS.

1 Eastern Europe consists of Belarus, Bulgaria, Czech Republic, Hungary, Moldova, Poland, Romania, Russia, Slovakia, and Ukraine. Among them, Czech Republic, Hungary, Poland, and Slovakia are currently Member states of the European Union (EU-25), having accessed in May 2004. Bulgaria and Romania finished accession negotiations and are waiting for the official decision on their date of joining (either January 2007 or January 2008) to be taken in October 2006. Former Soviet Union states, such as Belarus, Moldova, Ukraine, and Russia, make up the other non-EU countries in the Eastern Europe.


II. GHG Emissions in New Member States and allocation under the EU ETS

The 15 countries that were member states of the European Union (EU 15) before the fifth enlargement in May 2004 have agreed to a binding agreement to collectively reduce their GHG emissions by 8% below 1990 levels during the first commitment period of the Kyoto Protocol. The ten new member states (EU 10), with the exception of Cyprus and Malta, all have individual targets under the Kyoto Protocol. The EU ETS, designed to help the member states and the European Union meet their targets agreed to under the Kyoto Protocol, commenced operation on January 2005 and it is in its first phase (2005-2007). The EU ETS covers CO2 emissions from the power sector (all fossil fuel generators over 20 MW), oil refining, cement production, iron and steel manufacture, glass and ceramics, and paper and pulp production. In Phase I, over 11,000 participating installations bought and sold CO2 emission allowances, accounting for over 40% of EU emissions.2 All 25 member states (EU 25) are required to develop a National Allocation Plan (NAP) for each trading period that sets an overall target for the relevant period. The NAPs also set the total number of allowances for participating sectors and determines the fair and equitable distribution of these allowances amongst their installations. These allowances can then be bought and sold by the companies through national registries. For the first trading period, or Phase I, the approximate breakdown of allowances included: power and heat sector 55%, minerals (cement, glass, and ceramics) 12%, metals (steel production facilities) 12%, and oil and gas 10% (Capoor and Ambrosi, 2006). Member states are currently drafting NAPs for Phase II of the EU ETS and are to provide these to the European Commission by (EC) by 30 June 2006. Upon receipt of a complete plan, the Commission has 3 months for its assessment. While these installations are required to achieve the majority of their reductions within the EU, the so-called “Linking Directive”3 allows Member States to carry out emission reduction projects outside the EU through the JI or CDM. The Emission Reduction Units (ERUs) from JI or Certified Emission Reductions (CERs) from the CDM can be converted to European Union Allowances (EUAs) to be used for compliance under the EU ETS. This Linking Directive thus allows for participating companies to take advantage of lower-cost emissions reduction opportunities and helps create more efficient pricing of carbon across the expanding market. In spite of the positive aspects, the Linking Directive has also created concerns for member states when accounting emissions reductions accrued from JI project activities to meet their national targets established under the EU ETS. JI projects allow Annex I Parties to implement projects that reduce emissions in other Annex I countries, in return for emission reduction units (ERUs). The risk of double counting occurs if a project receives ERUs as well as EUAs under the EU ETS. For instance, if the expected ERUs from JI project have not been taken into account in the allocation of EUAs, some installations may receive “extra or free” allowances. Furthermore, indirect double-counting may occur if a JI project delivers electricity to the grid that potentially 2 The first trading period under the EU ETS runs from 2005-2007 and the second period runs from 2008-2012, in line with the first commitment period of the Kyoto Protocol. Draft NAPS for the second period have to be released by the 30 June 2006. 3 Available at: http://ec.europa.eu/environment/climat/emission/linking_en.htm


replaces electricity generated by an installation covered in the EU ETS. To prevent such cases, the Linking Directive specifies that EU member states should take the anticipated JI-based emissions reductions into account when developing their NAPs. If the EUAs have already been issued, the installation with JI projects should cancel their EUAs equivalent to the generated ERUs. Another option to avoid the complex accounting issue is for the non-Annex I member states to focus host JI projects in sectors and gasses not covered by the EU ETS. This issue is extremely relevant for the Eastern European countries that are EU Member States as it will surely limit the development of JI projects. In order to understand the potential for JI in these countries, it is important to first understand their current and projected emissions levels and their NAPs. The following sections outline the GHG emissions trends of Eastern European countries in the EU and the NAP allocations for these countries.

II.A GHG Emissions In 2003, total greenhouse gas (GHG) emissions (all six Kyoto gases) in the ten new member states were on average significantly below their base year emissions4, with the exception of Cyprus and Malta (see Table 1). As a result, these countries’ emissions levels are well below their Kyoto target (with the exception of Slovenia). This net surplus emissions level—the amount of emissions below their Kyoto targets—in the new member states is large enough to outweigh the emission increase expected within the EU-15. Table 1. New EU member states’ greenhouse gas emission trends and targets

Base Year Emissions (Mt CO2e)

GHG Emissions 2003

(Mt CO2e)

Change in 2003 Relative to Base

Year Kyoto Target

Cyprus 6 9.2 52.8% no target Czech Republic 192.1 145.4 -24.3% -8.0% Estonia 43.5 21.4 -50.8% -8.0% Hungary 122.2 83.2 -31.9% -6.0% Latvia 25.4 10.5 -58.5% -8.0% Lithuania 50.9 17.2 -66.2% -8.0% Malta 2.2 2.9 29.1% no target Poland 565.3 384 -32.1% -6.0% Slovakia 72 51.7 -28.2% -8.0% Slovenia 20.2 19.8 -1.9% -8.0% EU-10 1099.8 745.5 -32.2% -6.7% New Member States with Kyoto Targets* 1091.6 733.4 -32.2% -6.7%

EU-25 5352.2 4925.1 -8.0% -7.7% * Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Slovak Republic and Slovenia Sources: EEA, 2005 4 The base year is 1990, except for three countries which have a different base year: Poland (1988), Bulgaria (1989) and Hungary (average 1985-87).


As seen in Table 2 below, between the Kyoto base year and 2003, the total CO2 emissions in these ten new EU member states have declined significantly by 23 to 31 percent.5 This is the opposite of the trend in the EU 15 member states, where CO2 emissions have risen. Altogether, CO2 emissions in 2003 from all 25 EU member states are similar to their 1990 levels. Table 2. New EU member states’ CO2 Emission Trends based on data from European Environment Agency (EEA) and Director General – Energy and Transport (DG TREN)

Emissions by EEA (Mt CO2e) Emissions by DG TREN (Mt CO2e)

Base year 2003 Change 1990 2000 Change

EEA Projections for Emissions in

2010

Cyprus 4.6 9.2 100.0% 4.5 7.2 +60.0 -

Czech Republic 164.0 145.4 -11.3% 158.8 119.0 -25.1 124.8

Estonia 38.1 21.4 -43.8% 36.6 13.7 -62.6 -

Hungary 80.6 83.2 3.2% 68.5 53.7 -21.6 -

Latvia 18.7 10.5 -43.9% 16.9 6.6 -60.9 10.4

Lithuania 39.5 17.2 -56.5% 32.2 10.3 -68.0 21.7

Malta 1.8 2.9 61.1% 2.5 2.7 +8.0 -

Poland 476.6 384.0 -19.4% 340.1 290.2 -14.7 413.0

Slovakia 59.4 51.7 -13.0% 51.4 36.0 -30.0 50.4

Slovenia 16.0 19.8 23.8% 10.9 14.1 +29.4 -

EU-10 899.3 745.3 -17.1% 722.4 553.5 -23.4 % n/a

EU-15 3228.9 4179.8 29.4% 3082.1 3117.5 +1.1% n/a

EU-25 4128.2 4925.1 19.3% 3804.5 3671.0 -3.5 % n/a

Bulgaria* 85.5 73.6 41.4

Romania* 168.0 168.6 85.2

* Bulgaria and Romania are likely to join the EU in 2007

Source: EEA, 2005; DG TREN, 2003

For many of these countries they are also expected to be below their base year levels in 2010, which means that they could potentially have excess Assigned Amount Units (AAUs) for sale on the international market. Table 4 below highlights the total emissions projections for these new member states based upon two scenarios: (1) with existing policies and measures (PAMs) and (2) with additional policies and measures.6 In most cases the new member states are projected to

5 It is almost impossible to have data for GHG total and separately for CO2 from one and same source, so we present emissions of carbon dioxide coming from two sources: European Energy Agency (EEA) and European Commission Director General – Energy and Transport (DG TREN). 6 Key additional policies and measures reported by Member States are measures promoting electricity generation from renewable energy sources, cogeneration policies and energy efficiency policies, see EEA, 2005 for more details.


stay at or below their Kyoto targets under existing PAMs. The exception is Slovenia who is projected to decrease its gap with additional policies and measures but is still above its Kyoto target. Their total surplus is estimated to decline from over 30% in 2003 to between 5 and 9% in 2010.


Table 4. Emissions levels and of new EU Member States with Kyoto Protocol targets, compared with emission projections based on existing and additional domestic policies and measures

Kyoto Target With Existing Policies and Measures With Additional Policies and Measures

Projections for 2010 Gap between projections and target Projections for 2010 Gap between

projections and target Member States

Base Year GHG

Emissions* (Mt CO2)

Commitment (% reduction)

Emissions Target

(Mt CO2) Mt CO2 %

reduction Mt CO2 %

reduction Mt CO2 % reduction Mt CO2

% reduction

Czech Republic 192.1 -8.0 % 176.8 143.6 -25.3 % -33.2 -17.3 % 141.2 -26.5 % -35.6 -18.5 %

Estonia 43.5 -8.0 % 40.0 18.9 -56.6 % -21.1 -48.6 % 17.4 -60.0 % -22.6 -52.0%

Hungary 101.7 -6.0 % 95.6 95.6 -6.0 % +0.0 +0.0 % 95.6 -6.0 % 0.0 +0.0 %

Latvia 25.3 -8.0 % 23.3 13.7 -46.1 % -9.7 -38.1 % 13.0 -48.6 % -10.3 -40.6 %

Lithuania 51.0 -8.0 % 46.9 25.2 -50.6 % -21.7 -42.6 % no data no data no data no data

Poland 498.5 -6.0 % 468.6 438.4 -12.1 % -30.2 -6.1 % no data no data no data no data

Slovakia 72.1 -8.0 % 66.3 57.9 -19.7 % -8.4 -11.7 % 56.8 -21.3 % -9.6 -13.3 %

Slovenia 20.2 -8.0 % 18.6 21.2 +4.9 % +2.6 +12.9 % 20.3 +0.3 % 1.7 +8.3 %

EU8 1004.4 -6.8% 936.1 814.3 -18.9% -121.7 -12.1% 807.8 -19.6% -128.3 -12.8%

EU23 5149.8 -7.8% 4749.8 4894.6 -5.0% 144.8 2.8% 4669.8 -9.3% -80.1 -1.6%

* Base year used for the projection

Source: EEA, 2005.


II.B National Allocations For Phase I of the EU ETS, EC adopted NAPs based upon the member states original proposals or through bilateral exchanges to amend the proposed NAP.7 In late December 2005, the EC issued “further guidance” on the Phase II NAPs, which outlined the potential Phase II NAP level if the ETS sector was to contribute a proportionate share to achieving the Kyoto targets in these member states (EC, 2005). Under this guidance, the EC suggests that “some Member States have to lower the first period caps to respect the Kyoto target. Other Member States need to maintain their first phase caps to align the plan with the potential to reduce emissions” (EC, 2005). In late April and May of 2006, several member states reported lower than anticipated CO2 emissions in 2005, and concerns about “over-allocation” caused the price of EUA to drop from €30 to €9 then back up to €15 over the following two month period. This has created pressure on the European Commission to prevent a similar situation occurring in the Phase II of the EU ETS and has produced speculations that the Phase II cap will be tightened even further. NAPs for Phase II are to be presented to the European Commission on June 30, 2006, and only a few Eastern European countries have released their drafts as of June 9, 2006. Possible allocations of EUAs for the Phase II of the EU ETS (Point Carbon, 2006) are shown in Table 3, along with the few recently announced country proposals (in bold). For the Eastern European countries, the estimate holds the Phase II NAPs to similar levels as in Phase I since these member states were on target to comply with their Kyoto targets in 2003. For the other EU countries, the estimate includes a decrease below Phase I levels.

Table 3. Allocations of EUAs for New EU Member States under the EU ETS

Possible Allocations for Phase II [2008-2012] (Mt CO2e/year)

Phase I [2005-2007] (Mt CO2e/year) Point Carbon (2006)

Estimate Based Upon EC (2005)

Proposed Phase II NAPs

Cyprus 5.7 5.7

Czech Republic 97.6 97.6

Estonia 19.0 19 24.48*

Hungary 31.3 31.3

Latvia 4.6 4.6

Lithuania 12.3 12.3 16.5**

Malta 2.9 2.9 2.2***

Poland 239.1 239.1 257.4**

Slovakia 30.5 30.5 38.2***

Slovenia 8.8 8.4

EU-10 451.8 451.4

7 For a link to all Phase I NAPs, see: http://ec.europa.eu/environment/climat/first_phase_ep.htm


EU-15 1738.6 1612

EU-25 2190.9 2063.4

Bulgaria 56.2****

Romania * Point Carbon’s Carbon Market Daily June 6, 2006

** Point Carbon’s Carbon Market Europe May 26, 2006 *** Point Carbon’s Carbon Market Europe June 2, 2006 **** This number comes from the draft Bulgarian NAP as of March 2006 – this includes a significant reserve for new fossil fuel-fired capacities.

II.C Summary With a few exceptions, the total GHG emissions in the ten new EU member states are significantly below their base year emissions, and therefore well below their Kyoto targets. This net surplus in emissions level is in fact projected to be large enough to outweigh the emission increase within the EU-15. This fact will inevitably play a major role in EU member states discussions on the limits established in the EU ETS and in a post-2012 international regime. As has become apparent in the recent months, the allocation of EUAs has a significant impact on the carbon market. When several Member States began reporting less than expected level of CO2 emissions and subsequently an excess of allowances from the Phase I, the price of the EUA dropped dramatically from €30 to €9 then back up to €15 over the two month period. As in any other market, carbon price is a function of supply and demand, and while some observers suggest that the phase one NAPs were overly generous on purpose to encourage participation, actual emissions still vary depending on many other factors such as weather, fuel prices, economic growth, etc. Therefore, how the Phase II NAPs are decided, especially for the Eastern European Countries, will have a significant impact on these countries position in the EU ETS and JI since their excess AAUs will be a function of these decisions.


III. Joint Implementation Potential in Eastern Europe Joint Implementation (JI) was agreed under Article 6 of the Kyoto Protocol where:

“For the purpose of meeting its commitments …, any Party included in Annex I may transfer to, or acquire from, any other such Party emission reduction units resulting from projects aimed at reducing anthropogenic emissions by sources or enhancing anthropogenic removals by sinks of greenhouse gases in any sector of the economy”, provided that certain (participation) requirements are fulfilled.”

For this project, we sought to develop an assessment of the JI mitigation options available in the Eastern European countries in 2010—focused on Poland, Czech Republic, Slovakia, Hungary, Bulgaria, Romania, Russia and Ukraine. A number of studies have considered emissions reduction or JI potential in Eastern European countries (see for example, Bollen JC, 1995; Jílková et al., 1998; Golub et al., 1999; Kägi et al., 2003; Molnár, et al., 1996). These studies utilize various approaches to assess emission reduction potential and cost making developing a consistent cross country comparison difficult. In addition, a number of the results in these studies may be dated as they were conducted several years ago and the specific JI rules have only recently been agreed. In attempt to overcome these limitations, we developed a new assessment of JI potential in Eastern European countries. The assessment is based on the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS) model (Klaassen et al., 2004). The results from the GAINS modeling exercise are then discussed with reflections given the existing constraints (e.g., additionality demonstration requirement) and market realities (e.g., size of emissions reductions from the project type). For this “ground truthing” discussion, we consider Poland as a case study. Poland, the largest GHG emitter among new member states and currently under the European Union Emissions Trading Scheme (EU ETS), provides an interesting case in which its promising JI opportunities may face potential institutional barriers. For instance, one may be discouraged to develop a JI project due to a complex process of converting emissions reduction units (ERUs) accrued from a JI project into European Union Allowances (EUAs) from the EU ETS. Similar circumstances would be found outside of Poland in other EU member states and accession countries that would be covered by the EU ETS. Therefore, an in-depth assessment of JI potential in terms of GHG mitigation potential and existing institutional or market constraints and barriers using Poland as a case study would provide insights that can be reflected to the rest of the Eastern European within the EU countries. Using this “ground truthing” and other realities of JI, we then develop and estimate of JI potential in the Eastern European countries.

III.A Assessment Methodology: GAINS Overview Using GAINS model version 1.0, all the possible GHG emissions reduction options were considered to assess the emissions reduction potential in thee Eastern European countries. The GAINS model can assess any exogenously supplied projection of future economic activities, the resulting emissions of greenhouse gases and conventional air pollutants, the technical potential for emission controls, and the costs of such measures, as well as the interactions between the


emission controls of various pollutants (Klaassen et al., 2004). It assesses the options for reducing all six GHGs from all possible source categories, including agriculture. It quantifies for 43 countries/regions in Europe country-specific potentials of the various options in the different sectors of the economy, and estimates the societal resource costs of these measures. Mitigation potentials are estimated in relation to an exogenous baseline projection that is considered to reflect current planning. In considering the JI potentials in the GAINS model the following factors are important to note: • the potentials are relative to the baseline scenario that was used for the Clean Air for Europe

(CAFE) programme of the EU8; • we placed a €150 / tCO2e threshold on the reduction options and €65 / tCO2e for F-gas

reductions; • the marginal abatement costs are calculated with a discount rate (depreciation rate) of 4

percent per anum; • prices are in year 2000 values; • investment costs are annualized over the technical life of the investment; • cogeneration is not included; and • Russia covers only the European part (being part of the Eastern European region).9

III.B Country Groupings In our analysis, eight Eastern European countries were assessed as three “regions”, as follows, since these different groupings have implications for the emissions reduction opportunities available under JI.

New EU Member States: Poland, Czech Republic, Slovakia, and Hungary These countries have joined the European Union in 2005, and are now EU member states which are bound and limited by acquis communaitaire. These countries participate in the European Union Emissions Trading Scheme (EU ETS), which currently covers CO2 emissions from the power sector and major industrial sectors. These new Member States developed a NAP to set internal targets for the relevant sectors and comply with the current Phase I of the EU ETS. Participation in the EU ETS affects the JI potential of the country because a significant number of potential JI projects directly or indirectly impact installations subject to the EU ETS. If emission reductions from JI projects overlap with emissions covered by EU ETS, those reductions need to be subtracted from the NAPs, as discussed above.10 In case of a wind JI project, for instance, a new windmill constructed by a power company would replace some generating capacity of a more carbon-intensive power plant (e.g. pulverized coal-fired) covered by EU ETS, also owned by the same company. With no double-counting restrictions, this company would benefit from selling ERUs from this JI

8 The CAFE programme was launched by the Commission in 2001, with the aim of reviewing current air quality policies and assessing progress towards the long-term objectives of the 6th Environmental Action Programme. 9 European Russia is the mass of Russian land west of the Ural Mountains, which is a small portion of the Russian land but the majority of the population. 10 Directive 2003/87/EC amended by 2004/101/EC


project and excess EU allowances from a reduced emission at its coal-fired unit. More indirectly, new renewable capacities built by independent producers as JI projects and connected to the grid could reduce the level of electricity generation from fossil fuel-fired plants already covered by the EU ETS. In both cases, double counting presents a methodological challenge to JI project developers and requires careful planning.

The easiest way to avoid those complications is to disregard JI generally, and indeed that seems to be the approach taken by almost all new member states. However, given that the EU ETS currently regulates only CO2

11, there is still a role for JI in reducing CH4 and N2O emissions in these countries. For CO2 emissions from non-EU ETS sectors, a smaller number of JI opportunities are likely to be available. As a result, we looked only at opportunities for emissions reductions in non-CO2 gases, since CO2 is included in the EU ETS.

Accession Countries (or Candidate Countries): Bulgaria and Romania Bulgaria and Romania finished accession negotiations and are waiting for the official decision on their date of joining (either January 2007 or January 2008) to be taken in October 2006. Before the accession negations were complete, these two countries have had more flexibility in developing JI projects then other EU member states. However, their potential EU membership has already started to limit the development of JI projects. For similarly reasons to the new Member States, we only assessed non-CO2 gas emissions reductions opportunities for JI.

Russia and Ukraine. These are the biggest JI markets in Europe. There are no limits on JI availability as a result of EU membership so we considered emissions reduction opportunities in all six Kyoto gases.

III.C GAINS Results Marginal abatement cost (MAC) curve for all emissions reductions potentials for these Eastern European countries combined has been derived from the individual abatement potentials in GAINS. Figure 1 depicts the projected MAC curve in 2010 at less than €50/ton CO2e for all gases in the countries evaluated.

11 The Directive allows for opt-in of more gases and sectors. However, given the greater consequences of methodological uncertainties regarding other gases (their higher Global Warming Potential), member States would have to provide evidence of their ability to monitor these emissions with unprecedented levels of accuracy. Realistically the earliest possible extension of the scheme to other gases is from 2013 onwards.


Figure 1. GHG MAC curve in 2010 for Eastern European Countries Figure 2 depicts the projected CO2 emissions MAC curve in 2010 for Russia and Ukraine for the emissions reductions less than €50/ton CO2e.

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Figure 3 depicts the projected N2O emissions MAC curve in 2010 for all countries for the emissions reductions less than €50/ton CO2e.

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Figure 3. N2O MAC curve in 2010 for Eastern European Countries

Figure 4 depicts the projected CH4 emissions MAC curve in 2010 for all countries for the emissions reductions less than €50/ton CO2e.12

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Figure 4. CH4 MAC curve in 2010 for Eastern European Countries Figure 5 depicts the projected F-Gas emissions MAC curve in 2010 for all countries for the emissions reductions less than €50/ton CO2e.

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Figure 5. F-Gas MAC curve in 2010 for Eastern European Countries

The technology name, emissions reduction, cumulative emissions reduction, and marginal cost for each country are presented in Annexes I – IV.

III.D JI Potential “Reality Check”: Poland Case Study Without considering the technology application from the point of view of a JI developer, it is difficult to confirm that a technology assessed in economic models (e.g., GAINS) is feasible and plausible as a JI project. Key factors that may limit this applicability include: the project size (e.g., over 20,000 tCO2e annual reduction), the emission reduction integrity, the determination of the baseline, monitoring procedures, project leakage, other additional GHG emissions, possible increases in other negative environmental impacts, and data uncertainty. There are also other constraints which may limit the suitability of some technologies considered feasible in the GAINS model, such as the simultaneous mitigation of other non-GHG air pollutants. For a project developer, simultaneous reduction of some air pollutants which are under mandatory abatement may become an obstacle to proving the additionality of a JI project. These projects may then cease to be regarded as a JI project and are likely to be abandoned because they would not be economically feasible without the carbon incentive. For instance, if climate change

12 Annual CH4 emissions in 2000 from these countries is 575 MtCO2e (CAIT, 2006).


measures that aim at reduction of N2O will simultaneously reduce NOx, the project may not be recognized as additional, and as there are no regulatory requirements forcing an installation owner to spend money on N2O abatement, no proceeds from such abatement would mean that the project would not be implemented. An additional factor that distinguishes economic model results (e.g., GAINS) from practical JI project implementation is the timing of the emissions reductions and ability of JI project developers to generate enough emissions reductions over the JI crediting period (i.e., 2008-2012) to make the project profitable enough to proceed with the additional revenues generated from the sale of the emissions reductions. Since the GAINS model calculates emissions reductions and costs based upon the technical life of a project, there is likely be to be some disconnect between the GAINS results and the emissions reduction costs over the JI crediting period. For example, a JI project developer in the energy sector will consider whether the additional economic returns over the JI crediting period make the project viable, while the GAINS model shows the additional costs over the technical life of the measure which may be longer than the JI crediting period. This means that a JI project must generate enough additional investment over the JI crediting period to make the project viable over the life of the project. The majority of F-gases emission in Poland comes from dispersed sources and as such, it does not lend itself easily to abatement which would qualify for financing under Joint Implementation mechanism. Moreover, contribution of F-gases to the total national GHG emissions in Poland is low. Abatement of F-gases would involve, for example, destruction of HFCs from domestic appliances, such as fridges (at the end of their lifetime), or air conditioning. Such projects would be extremely difficult to monitor and the uncertainties in the estimates of F-gas emissions (and hence control costs) are large due to uncertainties in emission factors, the future penetration of technologies and abatement measures as well as lack of data on activities in a number of countries. In addition, to date there are no known JI projects implementing abatement of these gases. For these reasons, the emissions reduction opportunities in F-gases was left out of this consideration. The analysis, therefore, considered only N2O and CH4 abatement potentials defined by GAINS model and its applicability under JI using Poland as a case study. Below we discuss the results of this comparison. More detailed discussion is in Appendix V.

III.D.1 N2O Abatement Potential

Of all the N2O abatement technical measures considered by the GAINS model, only N2O abatement technologies from nitric acid production can be considered as a potential JI project in Poland.13 The choice of a specific technology, and of methodology, would depend on the technical parameters of the plant and are outside the scope of this report. The projected abatement potential for N2O from nitric acid production until 2010 was estimated in GAINs at the level of 6120 tN2O, or 1.8 million tCO2e. This appears too conservative an estimate, as even one of the potential JI projects in Poland, if implemented, would bring twice as much reduction in the Kyoto period (2008-2012). Although, all N2O reduction projects from nitric acid plants under JI may not be possible since abatement would cease to be additional and instead would 13 In some countries, this could be also N2O abatement from adipic acid production.


become business as usual after the installation of a number of these projects in Poland. Therefore, we could assume that at least 2 (maybe 3) such projects could be implemented without raising the issue of additionality in Poland. The costs for this emissions reduction options through installation of a catalyst were estimated using GAINS model as €130 /t N2O. N2O reduction projects can have very positive financial aspects as a JI project. Typically such a project may only cost €2 million to implement but could easily generate cash proceeds from the sale of ERUs of well over €10 million. However, there are a lot of technical, financial and political issues which mean that the project can go wrong. Tables 5 presents a comparison of GAINS emission reductions and an assessment of the “on-the-ground” JI potential in Poland. Table 5. Emission reduction potentials by GAINS model and from JI reality check; Poland; emissions of N2O; selected technologies

Emission reduction measure

Sum of Emissions Saved By

GAINS (tCO2e)

GAINS Marginal

Cost (€/t N2O)

JI reality check Estimated abatement potential for JI***

(tCO2e / y)

industry-process emissions- nitric acid plants 1,811,520 130 2,945,762 – 3,576,997

Industry: other combustion 509,120 1000 Not applicable for technological reasons before replacement of pulverized coal boilers with FBC technology

power plants: combustion 3,774,000 1000 Not applicable for technological reasons before replacement of pulverized coal boilers with FBC technology

power plants combustion new 728,160 1000

Not applicable for technological reasons before replacement of pulverized coal boilers with FBC technology

III.D.2 CH4 Abatement Potential

For CH4 abatement, reduction of methane from coal mining and reduction of methane from landfills involve technologies recognized by approved CDM methodologies. These abatement technologies, together with reduction of methane from oil and gas production are likely viable technologies for JI. In 2003, landfill sites emitted approximately 8.25 million tCO2e in Poland.14 In Poland there are 700 officially operating landfills, with more planned. For many towns, the landfills are already beyond their official capacities. Almost all municipal waste goes to landfills without separation. The greatest obstacle in implementing landfill gas extraction and utilization projects is connected with relatively small size of the landfills, especially older ones, and the non-compact deposition of waste. Typically a landfill suitable for implementing a methane capture project should receive between 40,000 and 50,000 tonnes of waste annually, with a suitable level of organic matter.

14 Poland NIR 2003, p 22. 1 m3 of CH4 equals 721 grammes of CH4.


The additionality of methane capture from landfills is an important issue in Poland. The Polish Ministry of the Environment has approved the Landfill Directive (EULFD) in 2001. Poland received a transitional period for implementing Article 14b (concerning existing landfill sites) until 2012 in order to take a definite decision on whether operations may continue on the basis on Directive 1999/31/EC. After year 2012 every operating landfill shall comply with the requirements of the Directive and if not, the landfill shall be closed down according to closure and after-care procedures. It is predicted that by 2012 it will be necessary to close down 361 waste storage facilities and to modernize further 663 ones. The tariffs for waste collection and processing are far below the average EU-levels and do not cover the costs for waste management according to EU standards. Therefore, private financial resources will play a dominant role in the implementation of landfill gas collection and utilization. The GAINS model cost estimates are for the British installation. Since none of the currently planned JI projects in Poland involving methane capture include installation of energy generation equipment, it is difficult to quote precise cost estimates from the local market. In 2003, Polish mines emitted approximately 11.8 million of CO2e. Assuming that potentially 70% of these emissions can technically be captured, this could generate 8.29 million ERUs. This estimate is, as usual, not applicable to JI potential because of additionality concerns. If all Polish coal mines wanted to implement JI projects, additionality could be a concern as the number of mines utilizing the approach grew. It is possible to argue that without a JI incentive it would be easy to continue venting. In Poland, methane can be recovered mainly from the mines located in Upper Silesia, from the mines owned by Katowicki Holding Węglowy (KHW).15 According to the GAINS estimate, the cost of abatement would range between – €107/tCH4 to €112/t CH4. These estimates can be confirmed on real project ideas. For example, a planned installation of a 5 MW CHP unit, combined with construction of 1.8 km of local pipeline, and modernization of the existing methane capture station in one of the KHW mines would cost € 4.23 million.16 The project would generate 129,595 tCO2e annually or 647,975 tCO2e in 2008-2012. Given this example, it appears that the GAINS results are within the range of likely costs; however, the cost would greatly depend on local factors. Tables 6 presents a comparison of GAINS emission reductions and an assessment of the “on-the-ground” JI potential in Poland.

Table 6. Emission reduction potentials by GAINS model and from JI reality check; Poland; emissions of CH4; selected technologies



GAINS (tCO2e)

GAINS Marginal Cost

(€/t N2O)


(tCO2e / y)

mining of brown coal (upgraded recovery & utilization of gas from current level to 70%)

222,600 -46,7 Not considered JI potential at present

15 Jastrzębska Spółka Węglowa owns 2 mines which could potentially implement JI projects, while methane emissions from Bogdanka Coal Mine near Lublin are to low to justify the expense of a CMM project. Existing projects include: a CHP generation unit at coal mine Krupiński, installed capacity: 2.7 MWe, 3.1 MWh, and a cooling unit at coal mine Pniówek: installed capacity of 5.7 MW. 16 PIN: Methane reduction through heat and power generation in Coal mine Staszic (draft)


Table 6. Emission reduction potentials by GAINS model and from JI reality check; Poland; emissions of CH4; selected technologies



GAINS (tCO2e)

GAINS Marginal Cost

(€/t N2O)


(tCO2e / y)

mining of hard coal (upgraded recovery & utilization of gas from current level to 70%)

3,595,410 -46,8 Abatement potential JI (estimated 70% of all CBM) 8,290,800****

Landfill paper waste (all options to reduce methane emissions from paper waste)

83,370 40,7

Not applicable (landfill waste methane recovery involve methane capture and flaring, no distinction of the organic matter content is made)

Pigs (liquid manure management) Farm scale

150,780 57,9 Too small abatement potential for JI acc to GAINS

crude oil produced (flaring instead of venting)

1680 73,9 Not applicable (too small acc to GAINS)

Production of natural gas (flaring instead of venting)

693,6 73,9 Not applicable (to small acc. to GAINS)

oil input to refineries (flaring instead of venting)


Dairy cattle (liquid manure management) Farm scale


landfill organic paper waste (all options to reduce methane emissions from organic waste)

247,590 122,5 (landfill waste methane recovery involve methane capture and flaring, no distinction of the organic matter content is made

other cattle (liquid manure management) Farm-scale

1050 131,9 Too small as JI potential acc to GAINS estimates)

wastewater treatment (gas recovery and utilization)

76,608 189,8 Too small as JI potential acc to GAINS estimates

petroleum refinery- combustion (replacement of grey cast iron networks)

233,310 1858,2 Too small and too costly, if considered in comparison with JI revenues

petroleum refinery- losses during transmission (replacement of grey cast iron networks)


combustion in a residential/commercial sector (replacement of grey cast iron networks)


industry- combustion in broilers (replacement of grey cast iron networks)


industry- other combustion (replacement of grey cast iron networks)


power and district heating plants (replacement of grey cast iron networks)


power and district heating plants- new (replacement of grey cast iron networks)


* Sector and technology abbreviations as in the GAINS model (see Annexes I-IV) ** obtained from the reduction of N2O at the prices from 7 to 11 EURO per 1 ERU *** (from all nitric acid production, not discounted for additionality reasons) **** based on 2003 NIR Report


III.E JI Potential in Eastern Europe As can be seen from the comparison of the GAINS results and Poland “case study”on JI feasibility, some emissions reduction opportunities assessed in GAINS may be too small or disperse, questionably additional, or uncertain to be likely candidates as JI projects. Further, some of the higher cost emissions reduction opportunities estimated in GAINS will naturally not be viable as JI projects given the purchase price of JI credits. Given these factors, the emissions reduction estimates from GAINS were modified to develop a more conservative estimate of JI potential in Eastern Europe, with the following assumptions. • All CO2 emissions reductions from Russia and Ukraine were considered potentially JI

eligible. • Only reduction of N2O from nitric acid and adipic acid production was included for all

countries. For these reductions, we assumed that all potentials would be available as JI projects.

• For CH4, only reductions from coal mining, landfill gas recovery, capture of methane from oil and gas production, flaring instead of venting of gas in refineries, and biogas from manure management was included for all countries.

• For F-Gas emissions reductions, no options were included since only incineration of HFC-23 has been developed as a CDM project and GAINS has no emissions reductions from this approach in the Eastern European countries.

• For all feasible options, the full technical potential of GAINS was included. • Only emissions reductions at less than €30 per ton CO2e are shown since the recent price of

JI is around €10 per ton CO2e (Point Carbon, 2006) and the price of the EUAs peaked at €30 per ton CO2e.

In total, we estimate that there is a JI potential in these Eastern European countries of 123.6 million tCO2e available at less than €17 per ton CO2e. Emissions reductions from these project types increase to 323.8 million tCO2e at less than €17 per ton CO2e. Figure 6 depicts the projected JI MAC curve in 2010 at less than €30/ton CO2e for all gases in the countries evaluated.


Figure 6. JI MAC curve in 2010 for all Eastern European Countries Figure 7 depicts the projected JI MAC curve in 2010 at less than €30/ton CO2e for all gases in Bulgaria.

Figure 7. JI MAC curve in 2010 for Bulgaria

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Figure 8. JI MAC curve in 2010 for the Czech Republic

Figure 9 depicts the projected JI MAC curve in 2010 at less than €30/ton CO2e for all gases in the Czech Republic.

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Figure 9. JI MAC curve in 2010 for Hungary

Figure 10 depicts the projected JI MAC curve in 2010 at less than €30/ton CO2e for all gases in Poland.

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Figure 10. JI MAC curve in 2010 for Poland Figure 11 depicts the projected JI MAC curve in 2010 at less than €30/ton CO2e for all gases in Romania.

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Figure 12 depicts the projected JI MAC curve in 2010 at less than €30/ton CO2e for all gases in Russia.

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Figure 12. JI MAC curve in 2010 for Russia

Figure 13 depicts the projected JI MAC curve in 2010 at less than €30/ton CO2e for all gases in Slovakia.

Figure 13. JI MAC curve in 2010 for Slovakia

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Figure 14. JI MAC curve in 2010 for Ukraine

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IV. Emissions trading with conventional pollutants in EU Member States Under Council Directive 1999/30/EC of 22 April 199917 and Directive 2001/81/EC18 establish National Emission Ceilings for certain pollutants (NECs) in 2010. All EU Member States are required to limit their emissions of sulphur dioxide (SO2), nitrogen dioxide and oxides of nitrogen (NOx), particulate matter (PM), and lead in ambient air. How the Member States choose to comply with this Directive is at their discretion. While emissions trading has had much success in the United States for conventional air pollutants (Burtraw and Palmer, 2003; Ellerman, 2003; Schmidt et al., 2004), emissions trading for conventional pollutants has been slow to gain acceptance in Europe. Traditional “command and control” regulations through EC Directives have been the favored policy mechanism to date; however, a few countries have attempted to implement other tools such as taxes, charges, and emissions trading. Analysts suggest a variety of challenges—such as designing a cap and trade system that meets EU directives, local opposition, market volatility, and market size—that have kept trading schemes of conventional pollutants from being more widely implemented within Europe (see for example, Martínez, 2005). There are a number of emission control technologies in the sectors covered by the EU ETS that reduce both air pollutants and greenhouse gases (e.g., selective catalytic reduction on gas boilers reduces NOx, N2O, CO and CH4). However, there are several examples of technologies which increase emissions of other pollutants (e.g., desulphurisation techniques involving CaCO3 increase CO2 emissions). Further some emissions control strategies (e.g., energy efficiency or fuel switching) result in avoided emissions of both air pollution and greenhouse gas emissions. Some investment decisions made for only controlling conventional pollutants, therefore, can lead to increased fuel use and thus CO2 emissions, and vice versa. Further, the economic optimal options for reducing SO2 and NOx on their own may not be the optimal choice when considering CO2 controls as well (see for example, Echeverri, 2003). Therefore, the timing, stringency, and regulatory structure of future air quality controls, and how these match those of the greenhouse gas emissions controls, could become a factor in firm’s investment decisions, the cost of meeting various regulations, and the policies implemented in Europe. While this has been a significant and growing debate within the U.S. (see for example, CCAP, 2000; NRDC, 2001), the discussions within Europe on these factors are in their infancy. This section briefly describes the few nascent systems in Europe to control air pollution through market-based systems and some preliminary insights on the relationships with the EU ETS. Further analysis will be needed on this issue as many of the air pollution systems are in their infancy and full analysis of the implications of the EU ETS on these systems, and vice versa, will focused research on that specific aspect.

17 For a copy of the Directive, see: http://eur-lex.europa.eu/smartapi/cgi/sga_doc?smartapi!celexplus!prod!DocNumber&lg=en&type_doc=Directive&an_doc=1999&nu_doc=30 18 For a copy of the Directive, see: http://europa.eu.int/eur-lex/pri/en/oj/dat/2001/l_309/l_30920011127en00220030.pdf


IV.A NOx Trading Scheme in the Netherlands In June 2005 the Netherlands launched its domestic trading programme for nitrogen oxides (NOx) emissions. The program is aimed at lowering compliance costs of meeting the NEC Directive, which requires the Netherlands to reduce NOx emissions from 490 kt in 1995 to 260 kt in 2010. Based upon negotiations with the major industry sectors, an agreement was reached that the industry sector would meet a target of 55 kt in 2010 as part of meeting the limits in the NEC directive. This target would be allied with the introduction of NOx emissions trading to limit annual industry costs. The program applies to facilities with total thermal capacity greater than 20 MW19, similar to the EU ETS, and to industrial facilities (e.g., cement) which release NOx as a part of their production process. A total of 249 installations are participating in establishing targets based upon their predicted production levels (Cozijnsen, 2006). Under the Phase I NAP of the Dutch participation in the EU ETS the number of participating installations is smaller—200 companies—since some installations with only process emissions (e.g., saltpetre and phosphate production) are not included (Cozijnsen, 2006). For the draft phase II NAP, the total installations participating increases to 330 installations. are participating The program allocates emissions credits to industrial facilities on the basis of performance standard rates (PSRs). The total cap for the trading programme was established at 55 kt of NOx in 2010—a 40% decline from the 2000 industrial level. A single PSR for combustion facilities above 20 MW is established to decline each year to a level of 40 grams per GJ in 2010. For industrial emissions, the program establishes 16 different PSRs. The allocation to each installation is determined ex-post by multiplying the PSR for a particular year by the total fuel input or product output for the same year. A company that exceeds its PSR can bank a portion of its allowances annually for use in future years and companies that emit more than allowed can borrow a portion from the next year’s allowances. In 2005, participating installations emitted a total of 47 kt of NOx, which was 10 kt less than the emissions allowed under the PSRs (NEA, 2006). Only 8 kt of this over compliance is allowed to be banked towards 2006 targets, with the excess two left permanently unsed. This surplus was expected as the PSR for NOx in the early years was developed to be less stringent and to become tighter over time (Cozijnsen, 2006). The cost of NOx abatement for the installations was estimated to vary significantly—from as low as €0.40 per kg up to costs in the range of €5 - €10 per kg (Stork Comprimo Protech, 1998; Stork Comprimo Protech, 1999). Emissions trading was estimated to reduce this cost for industry to €100 - €200 million per year. Since results of the program are only available for 7 months—June 2005 through December 2005—and the project was designed to be less stringent in the early years, the emissions trading component of the program has been limited. In 2005, there were 205 transactions for 17 kton NOx (NEA, 2006). In 2005, prices began at €1 per kg, but lowered to €0.5 per kg by the end of 2005—the average was around €0.82 per kg (Cozijnsen, 2006). The low price was to be expected as there was an overallocation, as discussed above.

19 There is an opt-out provision, however, for companies up to 30 MWth.


There are a number of similarities between the Dutch NOx system and the EU ETS. First, approximately 90% or more of Dutch NOx emissions and a similar percentage of the CO2 emissions are directly related to combustion of fossil energy (Dekkers and Allessie, 2005). As a result, companies investment decisions to reduce one type of emissions can impact on the other type of emission. Little evidence is available on how the combined NOx and CO2 program is driving firm’s investment decisions, but according to one analyst the second phase of the EU ETS will likely drive industrial reductions due to the much higher price of the EU ETS compared with the Dutch NOx program (Cozijnsen, 2006). Secondly, the legal establishments and institutional requirements for a CO2 trading program are often similar to those for a conventional emissions source. Both require similar monitoring, permitting, verification and inspection processes. In the case of the Dutch program, emissions permits for the covered installations cover both NOx and CO2 and are managed by a single entity—the Netherlands’ Emission Authority. Lastly, both systems ultimately lead to an absolute cap level. In the case of the Dutch program this level is determined based upon the level of production, whereas in the EU ETS it is based upon a predetermined level. Besides the difference in emissions that are trading, there are two major differences between the Dutch program and the EU ETS. The major difference is in the manner of allocation. The Dutch program does not allocate allowances ex-ante to installations as in the case of the EU ETS. Instead, allowances are automatically determined by multiplying PSR by the total fuel input or product output of the facility for a particular year. Second, the Dutch program does not allow trading outside of the Dutch boundary, whereas the EU ETS allows international trading. Table 5 presents a summary of the major similarities and differences between the Dutch program and the EU ETS.

Table 5. Similarities and differences between the EU Emissions Trading scheme for CO2 and the Dutch NOx trading programme

Similarities Differences • Around 90% of emissions of both: NOx and CO2 comes from combustion of fossil fuel and strong emissions reductions are needed

• Allocation philosophy: ex-ante for CO2, ex-post for NOx

• Both schemes are based on similar legal provisions

• Geographical scope: CO2 – EU-wide, NOx-only domestic

• Both schemes use one monitoring, permitting, verification and enforcement infrastructure

• Tradability: CO2 – anybody can hold an allowance, NOx – legally recognized are only transfers between participating installations

• Both schemes impose an absolute cap

IV.B SO2 Emissions Trading Programme in Slovakia In 1998, the government of Slovakia passed a law giving the Ministry of Environment the authority to establish a cap and trade program for large and medium source for a variety of pollutants. Each of its 79 administrative districts is given an emissions quota for the specific pollutant and each district sets quotas for individual emissions sources. At this stage, Slovakia has established limits for large sources—more than 50 MW thermal input—for SO2 and these sources are allowed to trade emissions permits. This effectively places a cap on 80% of SO2


emissions in Slovakia. The law requires Slovakia to reduce its SO2 emissions to 110 thousand tons by 2010—a 45% reduction. The emissions quotas are established to gradually decline until 2010.

IV.C Other Programs Two other efforts to introduce market-based mechanisms for conventional pollutants are worth briefly mentioning—the Swedish NOx charge and the discussions in Poland around a SO2 and NOx trading program.

IV.C.1 Swedish NOx Charge

The Swedish NOx charge system has been in operation since 1992 and applies to NOx emissions from energy production plants. Although it is not an emissions trading scheme, it has some components similar to output-based trading programs. Participants are charged over €4 per 1 kg of NOx emission. The revenue generated—minus administrative costs—is returned to the participants in proportion to their final production of energy where boilers with high emissions relative to their energy output are net payers. From 1997 onwards, all boilers producing at least 25 GWh per year were covered by the charge—about 250 plants (370 boilers). Largely as a result of this program, aggregate and intensity-based NOx emissions from the covered facilities has declined by around 40% between 1990 and 2004 (Figure 15).

Figure 15. NOx Emissions from Facilities Covered by the Swedish NOx Charge (Swedish EPA, 2006)

IV.C.2 SO2 and NOx Emissions Trading in Poland

Since 2003 there have been discussions in Poland on the introduction of an SO2 and NOx emissions trading system to provide an efficient means to meet the emissions limit agreed in the


Accession Treaty and the LCPD. However no strategic decision has been made on implementing such a system and the scheme on paper has been outlined in a variety of forms.

IV.D Summary While the United States has utilized emissions trading to control air pollution from conventional pollutants for a number of years, European countries have been slow to embrace trading as a policy tool. Europe on the other hand, has gone forward with an emissions trading program for CO2. Simultaneously, Europe has proceeded with further reductions of air pollution (e.g., SO2 and NOx) to meet address local and regional impacts. Addressing these emissions has largely been undertaken in Europe through command-and-control type regulations, with a few exceptions (i.e., the Netherlands, Sweden, and Slovakia). Developing a robust assessment of the interactions between conventional pollutant control and CO2 control in Europe is complicated by several factors, including data availability on plant-by-plant conventional and CO2 emissions, the early stage of the European programs, and data on conventional pollutant trading prices and volumes. Further analysis would be needed to consider the extent which there is interactions between the conventional pollutant trading programs and the CO2 trading system. Some aspects which have risen in the policy debate in the U.S. may become more prevalent as both the efforts to control conventional pollutants and CO2 progress in Europe, including:

• How do firms respond to command-and-control programs for one type of emissions source and cap-and-trade programs for another?

• Are investment decisions being made to address one type of emissions source having impacts on firm’s ability to comply with controls for another source? Is this positive or negative?

• Are allowance prices for CO2 driving those of conventional pollutants or vice versa? • If installation coverage is different between the two systems, has this brought about any

issues such as investment decisions, administrative complexity, compliance, etc? These questions and more are likely to arise as Europe embarks on further efforts to reduce conventional pollutants and CO2. The answers to these questions could play an important role in the policy developments of efforts to control both sets of emissions types.


V. Conclusions This report reviewed the current and projected emissions levels in Eastern European countries that are EU Members and assessed the JI opportunities available for Eastern European Countries as a part of the TETRIS project of the European Commission. The JI assessment utilized the mitigation potential and cost curves developed by IIASA for the GAINS model. These results were then modified to reflect some of the JI realities to develop a more conservative estimate of JI potential. Actual assessments on the ground as is the case with ongoing JI project development will likely provide a more realistic credibility check; however, this first order estimate provides some useful insights on the magnitude and potential for JI in these countries. Based upon this analysis, the following key observations are relevant. • For most of the Eastern European countries, the JI mitigation options are likely to mostly

occur in the non-CO2 gases since participation in the EU ETS makes developing JI projects that reduce CO2 emissions less straightforward out of “double-counting” concerns. For Russia and the Ukraine, this is not the case so JI projects in these countries are likely to include CO2 gas measures as well.

• At less than €10 per tCO2e—close to the current JI price—a total emissions reduction of 108 million tCO2e is available as JI projects in these countries.

• Approximately 6%—6.5 million tCO2e—of the total reductions are available at a net savings through coal bed methane recovery measures. An additional 32.8 million tCO2e of emissions reductions are available from coal bed methane recovery at less than €0.4 per per tCO2e.

• A total of 7.7 million tCO2e is available at adipic and nitric acid plants at a cost of less than €0.4 per tCO2e.

• Farm scale methane capture offers total reductions of 5.5 million tCO2e at a cost of around €10 per tCO2e.

• Above €10 per tCO2e, the achievable emissions reductions are modest—15.4 million tCO2e— up to a price of €17 per tCO2e. Most of these reductions are available in Russia and Ukraine through fuel switching and energy saving measures in industry.

• In comparison, the JI pipeline as of March 2006 (UNEP Risø Centre, 2006) had projects totaling 11.7 million tCO2e per year in the Eastern European countries in this study. In reality, the actual JI projects are likely to be less than the technical potential assessed in GAINS and modified in this report since practical aspects will likely limit the amount.


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and-Trade Program for Power Plants in the United States. Resources for the Future Discussion Paper. Available at: www.rff.org/Documents/RFF-DP-03-15.pdf

Capoor, K., and Ambrosi, P. 2006. State and Trends of the Carbon Market 2006, Washington

DC, World Bank and IETA, May 2006, p13. Center for Clean Air Policy. 2000. New Source Review Sector-Based Approach. Comments

submitted to USEPA. April. Cozijnsen, Jos. 2006. Personal communication. Available at: [email protected] Dekkers, C. and Allessie, M. 2005. The Infrastructure for Permitting, Inspection and

Enforcement of NOx and CO2 Emissions Trading in the Netherlands. Contribution to the 7th INECE conference. 10 – 15 April. Marrakech, Morocco.

Directorate General – Transport and Energy, DG TREN. 2003. European energy and transport –

Trends to 2030. January. Echeverri, D. 2003. The Cost of Regulatory Uncertainty in Air Emissions For a Coal-fired Power

Plant. Carnegie Mellon Electricity Industry Center. CEIC-03-03. Ellerman, D. 2003. Are Cap-and-Trade Programs more Environmentally Effective than

Conventional Regulation? Massachusetts Institute of Technology Center for Energy and Environmental Policy Research. Available at: http://web.mit.edu/ceepr/www/2003-015.pdf.

European Environment Agency, EEA. 2005. Greenhouse gas emission trends and projections

2005. EEA Report No 8/2005 European Commission. 2005. “Further guidance on allocation plans for the 2008 to 2012 trading

period of the EU Emission Trading Scheme.” Communications from the Commission. Brussels, December 12, 2005. Available at: http://ec.europa.eu/environment/climat/pdf/nap_II_guidance_en.pdf.

Golub, A, Avertchenkov, A., Berdin, V., Kokorin, A., Martynova, M., and Strukova, E. 1999.

Study on Russian National Strategy of Greenhouse Gas Emissions Reduction. World Bank National Strategy Studies Program. Available at: http://siteresources.worldbank.org/INTCC/1081874-1115369143359/20480345/NationalStrategyStudyRussia.pdf


Jílková, J., Haker, K., Luchinger, A., Malý, M., Splítek, V. Mauch, S., Nondek, L., Maroušek, J.,

Szomolanyiová, J., and Tichý, M. 1998. A National Strategy for Joint Implementation in the Czech Republic. World Bank National Strategy Studies Program. Available at: http://siteresources.worldbank.org/INTCC/1081874-1115369143359/20480335/NationalStrategyStudyCzech+Republic.pdf

Klaassen, G., M. Amann, C. Berglund, J. Cofala, L. Höglund-Isaksson, C. Heyes, R. Mechler, A.

Tohka, W. Schöpp, and W. Winiwarter. 2004. The Extension of the RAINS Model to Greenhouse Gases. IIASA Interim Report IR-04-015. Available at: www.iiasa.ac.at/rains/reports/ir-04-015.pdf

Martínez, K.K. 2005. Will the Combustion Plant Directive Ignite Trading? Environmental

Finance. April. Molnár, S., Harnos, Z, Takács, T., Somogyi, Z, Faragó, T., Pálvölgyi, T., Tajthy, T, Staub, K.,

and Bacskó, M. 1996. Mitigation Analysis for Hungary Hungary: Interim Report. US Country Study Program. Available at: http://yosemite.epa.gov/oar/globalwarming.nsf/UniqueKeyLookup/SHSU5BUNTM/$File/hungary_cs.pdf

Natural Resources Defense Council, NRDC. 2001. Regulating Four Power-Plant Pollutants More

Cost-Effective Than Three: Energy Department Study Finds That Ignoring Global Warming Pollution Won't Pay. Accessed online 8 August 2006. Available at: www.nrdc.org/globalWarming/fourp/f4pv3p.asp.

Netherlands Emissions Authority, NEA. 2006. Emissions Authority Information: 2005 report.

(Dutch only). May. Point Carbon. 2006. CDM & JI Monitor. 13 June. Schmidt, J. Davis, S., Lee, J., and Kittell, M. 2004. Comparison of the EU and US Approaches

Towards Acidification, Eutrophication, and Ozone Formation. Available at: www.ccap.org/pdf/EU%20AQ%20Case%20Study%201.pdf

Stork Comprimo Protech. 1998. Potential for Reduction of NOx Emissions at the Industry:

Refineries and the Power Industry, and the Costs involved. 26 October. (Available in Dutch only).

Stork Comprimo Protech. 1999. Sensitivity Analysis of the Cost of NOx Reductions in the

Industry, Refineries and the Power Industry. 28 May. (Available in Dutch only). Swedish EPA. 2006. The Swedish Charge on Nitrogen Oxides: Cost-Effective Emission

Reduction. March. Available at: www.naturvardsverket.se/bokhandeln/pdf/620-8245-0.pdf


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World Resources Institute. 2006. Climate Analysis Indicators Tool (CAIT): Version 3.0.


Annex I: Marginal cost curve data for CO2 emissions for Russia and Ukraine (GAINS) Table 9. Marginal cost curve data for CO2 emissions for Russia (GAINS)

Sector Measure

Marginal cost

(EUR/tCO2)

Potential reduction (Mt CO2)

Industry FSAVING_cheap 2.95 6.07 Industry FSAVING_med 11.96 8.61 PowerPlants Replace BC with GAS 16.85 3.76 PowerPlants Replace BC with WIND 35.4 89.55 PowerPlants Replace HC with WIND 38.1 84.5 PowerPlants Replace BC with HYD 38.7 10.55 Industry FSAVING_exp 42.7 3.26

PowerPlants Replace BC with Biomass (Existing plant) 49.43 1.4654

PowerPlants Replace HC with Biomass (Existing plant) 54.02 0.8776

DOM Electricity savings medium cost 65.1 2.13 DOM Replace MD with biomass 97.13 5.936 PowerPlants Replace GAS with Biomass 128.97 10.04

Table 10. Marginal cost curve data for CO2 emissions for Ukraine (GAINS)

Sector Measure

Marginal cost

(EUR/tCO2)

Potential reduction (Mt CO2)

Industry FSAVING_cheap 7.6 17.11 PowerPlants Replace BC with GAS 8.85 0.532 Industry FSAVING_med 16.55 2.39 PowerPlants Replace BC with WIND 34.56 0.2 PowerPlants Replace HC with WIND 37.16 0.2 PowerPlants Replace BC with HYD 38.7 2.2 Industry FSAVING_exp 42.79 1.71

PowerPlants Replace HC with Biomass (Existing plant) 49.43 6.6

PowerPlants Replace BC with Biomass (Existing plant) 54.02 0.85

PowerPlants Replace BC with Biomass ('NEW' plant) 58.35 0.85 DOM Electricity savings medium cost 61.99 0.88 PowerPlants Replace HC with Biomass ('NEW' plant) 63.78 6.6

DOM Replace MD with GAS & Improve insulation 90.57 0.81

PowerPlants Replace GAS with Biomass 142.59 2.43


Annex II: Marginal cost curve data for N2O emissions for 8 countries (GAINS) Table 11. Marginal cost curve data for N2O emissions for Bulgaria (GAINS)

Measure

Sum Of Emissions saved (kt)

Cumulative Emission Reduction

(kt)

Marginal Cost

(EURO/t N2O)

Sum Of Total costs

(E*G) 1,000s EURO

sewage treatment- optimization 0.16 0.16 0.00 0.00industry-process emissions- nitric acid plants 2.92 3.08 130.00 379.98fuel production and conversion: combustion 0.03 3.11 1000.00 25.60industry: combuston in broilers 0.01 3.12 1000.00 9.60industry: other combustion 0.08 3.19 1000.00 76.67power plants: combustion 1.61 4.80 1000.00 1608.96power plants combustion new 0.87 5.67 1000.00 869.38agricultural land- reduced fertilizer 1.32 6.99 1500.00 1975.11grassland- reduced fertilizer 0.01 7.00 1500.00 19.29agricultural land- timing of fertilizer 2.41 9.42 5363.64 12947.93grassland- timing of fertilizer 0.02 9.44 5363.64 126.48agricultural land- nitrification inhibitors 5.05 14.49 13000.00 65617.45grassland- nitrification inhibitors 0.05 14.54 13000.00 640.98agricultural land- precision farming 7.24 21.78 27242.42 197291.26grassland- precision farming 0.07 21.85 27242.42 1927.22use of n2o 0.60 22.45 200000.00 120829.35

Table 12. Marginal cost curve data for N2O emissions for Czech Republic (GAINS)

Measure


Cumulative Emission

Reduction (kt)

Marginal Cost (EURO/t

N2O)

Sum Of Total costs (E*G)

1,000s EURO

sewage treatment- optimization 0.21 0.21 0.00 0.00industry-process emissions- nitric acid plants 1.63 1.83 130.00 211.63

power plants combustion new 0.39 2.22 1000.00 387.26

industry: other combustion 0.79 3.01 1000.00 788.83

power plants: combustion 3.72 6.73 1000.00 3719.04

grassland- reduced fertilizer 0.05 6.78 1500.00 74.38

agricultural land- reduced fertilizer 1.00 7.78 1500.00 1502.36

grassland- timing of fertilizer 0.09 7.87 5363.64 487.60

agricultural land- timing of fertilizer 1.84 9.71 5363.64 9848.82


Measure


Cumulative Emission

Reduction (kt)


N2O)


1,000s EURO

grassland- nitrification inhibitors 0.19 9.90 13000.00 2471.07agricultural land- nitrification inhibitors 3.84 13.74 13000.00 49911.80

grassland- precision farming 0.27 14.01 27242.42 7429.74

agricultural land- precision farming 5.51 19.52 27242.42 150069.27

use of n2o 0.78 20.30 200000.00 156131.36


Table 13. Marginal cost curve data for N2O emissions for Hungary (GAINS)

Measure



(kt) Marginal Cost (EURO/t N2O)


1,000s EURO

sewage treatment- optimization 0.20 0.20 0.00 0.00industry-process emissions- nitric acid plants 1.45 1.65 130.00 188.51



use of n2o 0.76 8.61 200000.00 151507.51








agricultural land- nitrification inhibitors 4.24 17.56 13000.00 55162.49

grassland- nitrification inhibitors 0.08 17.64 13000.00 1017.18 Table 14. Marginal cost curve data for N2O emissions for Poland (GAINS)

Measure





1,000s EURO sewage treatment- optimization 0.77 0.77 0 - industry-process emissions- nitric acid plants 6.12 6.89 130

795.5

industry: other combustion 1.72 8.61 1000

1,715.9

power plants: combustion 12.75 21.36 1000

12,747.7 power plants combustion new 2.46 23.81 1000


2,456.8

agricultural land- reduced fertilizer 2.72 26.53 1500

4,079.3

grassland- reduced fertilizer 0.47 27.00 1500

708.4

agricultural land- timing of fertilizer 4.99 31.99 5363.636

26,742.4

grassland- timing of fertilizer 0.87 32.86 5363.636

4,643.9 agricultural land- nitrification inhibitors 10.42 43.28 13000

135,524.8

grassland- nitrification inhibitors 1.81 45.09 13000

23,534.2

agricultural land- precision farming 14.96 60.05 27242.42

407,480.9

grassland- precision farming 2.60 62.65 27242.42

70,759.9

use of n2o 2.93 65.58 200000

586,803.6 Table 15. Marginal cost curve data for N2O emissions for Romania (GAINS)

Measure



(kt)

Marginal Cost

(EURO/t N2O)

Sum Of Total costs

(E*G) 1,000s EURO

sewage treatment- optimization 0.45 0.45 0.00 0.00

adipic acid production 1.52 1.97 44.00 66.84industry-process emissions- nitric acid plants 2.87 4.84 130.00 373.46fuel production and conversion: combustion 0.08 4.92 1000.00 80.64

industry: combuston in broilers 0.00 4.93 1000.00 4.61









Measure



(kt)

Marginal Cost

(EURO/t N2O)

Sum Of Total costs

(E*G) 1,000s EURO

agricultural land- nitrification inhibitors 10.45 28.21 13000.00 135796.15

grassland- nitrification inhibitors 2.47 30.68 13000.00 32121.21



use of n2o 1.71 50.92 200000.00 341053.03 Table 16. Marginal cost curve data for N2O emissions for Russia (GAINS)

Measure





1,000s EURO sewage treatment- optimization 2.31 2.31 0.00 0.00industry-process emissions- nitric acid plants 2.17 4.48 130.00 282.17fuel production and conversion: combustion 0.29 4.77 1000.00 293.12industry: other combustion 0.78 5.55 1000.00 779.37power plants: combustion 2.52 8.07 1000.00 2515.20power plants: combustion new 1.46 9.53 1000.00 1457.95agricultural land- reduced fertilizer 7.77 17.29 1500.00 11647.62grassland- reduced fertilizer 1.76 19.05 1500.00 2639.57agricultural land- timing of fertilizer 14.24 33.29 5363.64 76356.62grassland- timing of fertilizer 3.23 36.51 5363.64 17303.85agricultural land- nitrification inhibitors 29.77 66.28 13000.00 386959.76grassland- nitrification inhibitors 6.75 73.02 13000.00 87692.40


grassland- precision farming 9.68 125.41 27242.42 263663.72discontinue cultivation 8.72 134.13 42000.00 366299.98use of n2o 8.78 142.91 200000.00 1755014.71


Table 17. Marginal cost curve data for N2O emissions for Slovakia (GAINS)

Measure



(kt)

Marginal Cost

(EURO/t N2O)


1,000s EURO

sewage treatment- optimization 0.11 0.11 0.00 0.00industry-process emissions- nitric acid plants 0.63 0.74 130.00 81.81fuel production and conversion: combustion 0.05 0.78 1000.00 45.44industry: combuston in broilers 0.01 0.79 1000.00 6.40industry: other combustion 0.19 0.98 1000.00 189.57power plants: combustion 0.57 1.54 1000.00 566.30power plants combustion new 0.57 2.11 1000.00 569.76agricultural land- reduced fertilizer 0.28 2.40 1500.00 423.77grassland- reduced fertilizer 0.02 2.42 1500.00 34.11agricultural land- timing of fertilizer 0.52 2.94 5363.64 2778.06grassland- timing of fertilizer 0.04 2.98 5363.64 223.62agricultural land- nitrification inhibitors 1.08 4.06 13000.00 14078.65grassland- nitrification inhibitors 0.09 4.15 13000.00 1133.28agricultural land- precision farming 1.55 5.70 27242.42 42330.11grassland- precision farming 0.13 5.83 27242.42 3407.42use of n2o 0.41 6.24 200000.00 82060.24

Table 18. Marginal cost curve data for N2O emissions for Ukraine (GAINS)

Measure


Cumulative Emission

Reduction (kt)

Marginal Cost

(EURO/t N2O)

Sum Of Total costs

(E*G) 1,000s EURO

sewage treatment- optimization 0.99 0.99 0.00 0.00 adipic acid production 4.22 5.21 44.00 185.59 industry-process emissions- nitric acid plants 1.30 6.51 130.00 168.95 fuel production and conversion: combustion 0.13 6.64 1000.00 128.00 industry: other combustion 2.28 8.92 1000.00 2280.35 industry: other combustion 4.32 13.24 1000.00 4323.84 power plants combustion new 2.18 15.42 1000.00 2183.04 agricultural land- reduced fertilizer 6.81 22.23 1500.00 10210.34 grassland- reduced fertilizer 0.35 22.58 1500.00 520.61 agricultural land- timing of fertilizer 12.48 35.06 5363.64 66934.43 grassland- timing of fertilizer 0.64 35.69 5363.64 3412.91 agricultural land- nitrification inhibitors 26.09 61.79 13000.00 339210.05 grassland- nitrification inhibitors 1.33 63.12 13000.00 17295.92


Measure


Cumulative Emission

Reduction (kt)

Marginal Cost

(EURO/t N2O)

Sum Of Total costs

(E*G) 1,000s EURO

agricultural land- precision farming 37.44 100.56 27242.42 1019899.08 grassland- precision farming 1.91 102.46 27242.42 52003.44 discontinue cultivation 4.01 106.47 42000.00 168300.00 use of n2o 3.77 110.24 200000.00 753436.60


Annex III: Marginal cost curve data for CH4 emissions for 8 countries (GAINS) Table 19. Marginal cost curve data for CH4 emissions for Bulgaria (GAINS)

Measure



(kt)

Marginal Cost

(EURO/t CH4)

replacement of roughage for concentrate 0.19 0.19 -6844.72replacement of roughage for concentrate 0.63 0.82 -6844.72increased feed intake 0.20 1.02 -5290.92increased feed intake 0.67 1.70 -5290.92upgraded recovery & utilization of gas from current level to 70% 8.76 10.45 -48.83upgraded recovery & utilization of gas from current level to 70% 0.07 10.53 -48.83reduction at compressor stations 0.00 10.53 -36.68autonomous increases in agricultural productivity 0.00 10.53 0.00autonomous increases in agricultural productivity 0.00 10.53 0.00autonomous increases in agricultural productivity 0.00 10.53 0.00autonomous increases in agricultural productivity 0.00 10.53 0.00alternative rice strains 0.81 11.34 47.00farm-scale 6.68 18.02 56.61all options to reduce methane emissions from paper waste 26.20 44.22 57.47flaring instead of venting of gas-oil/gas production 0.00 44.22 72.86flaring instead of venting of gas-oil/gas production 0.17 44.39 72.86flaring instead of venting of gas-refineries 0.01 44.40 72.86farm-scale 0.33 44.73 97.60all options to reduce methane emissions from organic waste 60.22 104.95 119.06farm-scale 0.22 105.16 128.96doubling of leak control frequency of network 0.29 105.45 168.60doubling of leak control frequency of network 0.06 105.51 168.60doubling of leak control frequency of network 0.08 105.59 168.60doubling of leak control frequency of network 0.25 105.84 168.60doubling of leak control frequency of network 0.88 106.72 168.60doubling of leak control frequency of network 0.00 106.72 168.60doubling of leak control frequency of network 0.15 106.87 168.60doubling of leak control frequency of network 1.84 108.71 168.60doubling of leak control frequency of network 108.71 168.60gas recovery and utilization 9.20 117.92 189.54ban on agricultural waste burning 0.00 117.92 500.00propionate precursors 0.00 117.92 527.00propionate precursors 0.00 117.92 527.00propionate precursors 0.00 117.92 1100.00propionate precursors 0.00 117.92 1100.00replacement of grey cast iron networks 2.12 120.04 1858.25replacement of grey cast iron networks 0.44 120.48 1858.25replacement of grey cast iron networks 0.56 121.04 1858.25


Measure



(kt)

Marginal Cost

(EURO/t CH4)

replacement of grey cast iron networks 1.85 122.89 1858.25replacement of grey cast iron networks 6.41 129.30 1858.25replacement of grey cast iron networks 0.00 129.30 1858.25replacement of grey cast iron networks 1.12 130.42 1858.25replacement of grey cast iron networks 13.43 143.84 1858.25replacement of grey cast iron networks 143.84 1858.25change to more nsc in diet 0.55 144.40 3228.99change to more nsc in diet 0.17 144.56 3228.99replacement of roughage for concentrate 0.18 144.74 4559.71replacement of roughage for concentrate 0.05 144.80 4559.71change to more nsc in diet 0.08 144.88 4657.96change to more nsc in diet 0.28 145.16 4657.96increased feed intake 0.18 145.35 7792.53increased feed intake 0.05 145.40 7792.53housing adaptation 0.66 146.06 38150.00housing adaptation 0.00 146.06 38150.00integrated sewage system 19.03 165.09 1000000.00

Table 20. Marginal cost curve data for CH4 emissions for Czech Republic (GAINS)

Measure



(kt)

Marginal Cost

(EURO/t CH4)

replacement of roughage for concentrate 0.30 0.30 -12643.92replacement of roughage for concentrate 0.20 0.51 -12643.92increased feed intake 0.00 0.51 -11319.75increased feed intake 0.00 0.51 -11319.75upgraded recovery & utilization of gas from current level to 70% 0.32 0.82 -49.58upgraded recovery & utilization of gas from current level to 70% 110.36 111.18 -49.58reduction at compressor stations 0.00 111.18 -34.27autonomous increases in agricultural productivity 0.00 111.18 0.00autonomous increases in agricultural productivity 0.00 111.18 0.00autonomous increases in agricultural productivity 0.00 111.18 0.00autonomous increases in agricultural productivity 0.00 111.18 0.00all options to reduce methane emissions from paper waste 1.12 112.29 45.82alternative rice strains 0.00 112.29 47.00farm-scale 10.53 122.83 57.93flaring instead of venting of gas-oil/gas production 0.02 122.85 76.52flaring instead of venting of gas-oil/gas production 0.95 123.80 76.52flaring instead of venting of gas-refineries 0.01 123.81 76.52farm-scale 0.91 124.71 99.87all options to reduce methane emissions from organic waste 2.00 126.71 129.68farm-scale 0.56 127.28 131.95


Measure



(kt)

Marginal Cost

(EURO/t CH4)

gas recovery and utilization 12.59 139.87 186.37doubling of leak control frequency of network 0.20 140.07 318.72doubling of leak control frequency of network 0.37 140.44 318.72doubling of leak control frequency of network 2.28 142.72 318.72doubling of leak control frequency of network 1.01 143.73 318.72doubling of leak control frequency of network 3.75 147.48 318.72doubling of leak control frequency of network 0.00 147.48 318.72doubling of leak control frequency of network 0.46 147.94 318.72doubling of leak control frequency of network 2.09 150.02 318.72doubling of leak control frequency of network 150.02 318.72ban on agricultural waste burning 0.00 150.02 500.00propionate precursors 0.00 150.02 527.00propionate precursors 0.00 150.02 527.00propionate precursors 0.00 150.02 1100.00propionate precursors 0.00 150.02 1100.00replacement of grey cast iron networks 1.46 151.49 1850.35replacement of grey cast iron networks 2.68 154.17 1850.35replacement of grey cast iron networks 16.67 170.84 1850.35replacement of grey cast iron networks 7.35 178.19 1850.35replacement of grey cast iron networks 27.39 205.58 1850.35replacement of grey cast iron networks 0.00 205.58 1850.35replacement of grey cast iron networks 3.32 208.90 1850.35replacement of grey cast iron networks 15.25 224.15 1850.35replacement of grey cast iron networks 224.15 1850.35replacement of roughage for concentrate 0.00 224.15 2511.16replacement of roughage for concentrate 0.00 224.15 2511.16change to more nsc in diet 0.18 224.33 2873.87change to more nsc in diet 0.27 224.59 2873.87change to more nsc in diet 0.84 225.43 4606.07change to more nsc in diet 1.96 227.40 4606.07increased feed intake 0.00 227.40 5481.35increased feed intake 0.00 227.40 5481.35housing adaptation 1.04 228.44 38150.00housing adaptation 0.00 228.44 38150.00integrated sewage system 0.00 228.44 1000000.00

Table 21. Marginal cost curve data for CH4 emissions for Hungary (GAINS)

Measure



(kt)

Marginal Cost

(EURO/t CH4)

replacement of roughage for concentrate 0.01 0.01 -19640.28replacement of roughage for concentrate 0.31 0.32 -19640.28increased feed intake 0.01 0.33 -18593.13


Measure



(kt)

Marginal Cost

(EURO/t CH4)

increased feed intake 0.33 0.66 -18593.13reduction at compressor stations 0.00 0.66 -34.09autonomous increases in agricultural productivity 0.00 0.66 0.00autonomous increases in agricultural productivity 0.00 0.66 0.00autonomous increases in agricultural productivity 0.00 0.66 0.00autonomous increases in agricultural productivity 0.00 0.66 0.00upgraded recovery & utilization of gas from current level to 70% 26.13 26.79 10.97upgraded recovery & utilization of gas from current level to 70% 0.00 26.79 10.97alternative rice strains 0.88 27.68 47.00all options to reduce methane emissions from paper waste 1.24 28.91 57.20flaring instead of venting of gas-oil/gas production 0.09 29.01 76.80flaring instead of venting of gas-oil/gas production 23.53 52.53 76.80flaring instead of venting of gas-refineries 0.01 52.55 76.80farm-scale 11.37 63.92 82.90farm-scale 0.02 63.94 142.92all options to reduce methane emissions from organic waste 3.12 67.06 144.06farm-scale 0.00 67.06 188.84gas recovery and utilization 9.22 76.28 219.27doubling of leak control frequency of network 0.18 76.46 390.59doubling of leak control frequency of network 0.42 76.88 390.59doubling of leak control frequency of network 3.30 80.18 390.59doubling of leak control frequency of network 0.16 80.34 390.59doubling of leak control frequency of network 1.61 81.95 390.59doubling of leak control frequency of network 0.00 81.95 390.59doubling of leak control frequency of network 0.07 82.02 390.59doubling of leak control frequency of network 4.05 86.07 390.59doubling of leak control frequency of network 86.07 390.59ban on agricultural waste burning 0.00 86.07 500.00propionate precursors 0.00 86.07 527.00propionate precursors 0.00 86.07 527.00propionate precursors 0.00 86.07 1100.00propionate precursors 0.00 86.07 1100.00replacement of grey cast iron networks 1.33 87.40 1909.60replacement of grey cast iron networks 3.07 90.48 1909.60replacement of grey cast iron networks 24.05 114.52 1909.60replacement of grey cast iron networks 1.20 115.72 1909.60replacement of grey cast iron networks 11.74 127.46 1909.60replacement of grey cast iron networks 0.00 127.46 1909.60replacement of grey cast iron networks 0.49 127.95 1909.60replacement of grey cast iron networks 29.55 157.50 1909.60replacement of grey cast iron networks 157.50 1909.60replacement of roughage for concentrate 0.23 157.73 2347.54replacement of roughage for concentrate 0.00 157.73 2347.54


Measure



(kt)

Marginal Cost

(EURO/t CH4)

change to more nsc in diet 0.27 158.01 2445.46change to more nsc in diet 0.01 158.01 2445.46change to more nsc in diet 0.00 158.01 4601.93change to more nsc in diet 0.35 158.36 4601.93increased feed intake 0.23 158.60 5296.75increased feed intake 0.00 158.60 5296.75housing adaptation 1.13 159.72 38150.00housing adaptation 0.00 159.72 38150.00integrated sewage system 0.00 159.72 1000000.00

Table 22. Marginal cost curve data for CH4 emissions for Poland (GAINS)

Measure



(kt)


CH4) replacement of roughage for concentrate 0.05 0.05 -10463.08replacement of roughage for concentrate 4.64 4.68 -10463.08increased feed intake 0.05 4.73 -9052.55increased feed intake 4.93 9.67 -9052.55upgraded recovery & utilization of gas from current level to 70% 10.60 20.27 -46.77upgraded recovery & utilization of gas from current level to 70% 171.21 191.48 -46.77reduction at compressor stations 0.00 191.48 -35.99autonomous increases in agricultural productivity 0.00 191.48 0.00autonomous increases in agricultural productivity 0.00 191.48 0.00autonomous increases in agricultural productivity 0.00 191.48 0.00autonomous increases in agricultural productivity 0.00 191.48 0.00all options to reduce methane emissions from paper waste 3.97 195.45 40.69alternative rice strains 0.00 195.45 47.00farm-scale 7.18 202.63 57.92flaring instead of venting of gas-oil/gas production 0.08 202.72 73.90flaring instead of venting of gas-oil/gas production 33.03 235.75 73.90flaring instead of venting of gas-refineries 0.04 235.78 73.90farm-scale 0.08 235.86 99.86all options to reduce methane emissions from organic waste 11.79 247.65 122.59farm-scale 0.06 247.70 131.94


Measure



(kt)


CH4) gas recovery and utilization 36.48 284.18 189.88doubling of leak control frequency of network 1.52 285.71 213.55doubling of leak control frequency of network 0.83 286.54 213.55doubling of leak control frequency of network 4.35 290.89 213.55doubling of leak control frequency of network 0.91 291.80 213.55doubling of leak control frequency of network 5.03 296.83 213.55doubling of leak control frequency of network 0.00 296.83 213.55doubling of leak control frequency of network 0.35 297.18 213.55doubling of leak control frequency of network 6.41 303.59 213.55doubling of leak control frequency of network 303.59 213.55ban on agricultural waste burning 0.00 303.59 500.00propionate precursors 0.00 303.59 527.00propionate precursors 0.00 303.59 527.00propionate precursors 0.00 303.59 1100.00propionate precursors 0.00 303.59 1100.00replacement of grey cast iron networks 11.11 314.70 1858.25replacement of grey cast iron networks 6.09 320.79 1858.25replacement of grey cast iron networks 31.78 352.57 1858.25replacement of grey cast iron networks 6.62 359.20 1858.25replacement of grey cast iron networks 36.70 395.89 1858.25replacement of grey cast iron networks 0.00 395.89 1858.25replacement of grey cast iron networks 2.55 398.44 1858.25replacement of grey cast iron networks 46.77 445.21 1858.25replacement of grey cast iron networks 445.21 1858.25change to more nsc in diet 4.04 449.25 3007.42change to more nsc in diet 0.04 449.29 3007.42replacement of roughage for concentrate 1.40 450.69 3721.12replacement of roughage for concentrate 0.01 450.70 3721.12change to more nsc in diet 0.02 450.72 4636.72change to more nsc in diet 2.12 452.84 4636.72increased feed intake 1.40 454.24 6846.43increased feed intake 0.01 454.25 6846.43housing adaptation 0.71 454.96 38150.00housing adaptation 0.00 454.96 38150.00integrated sewage system 0.00 454.96 1000000.00

Table 23. Marginal cost curve data for CH4 emissions for Romania (GAINS)

Measure


Cumulative Emission

Reduction (kt)

Marginal Cost

(EURO/t CH4)

replacement of roughage for concentrate 0.55 0.55 -4785.26replacement of roughage for concentrate 1.85 2.40 -4785.26increased feed intake 0.59 2.99 -3149.91


Measure


Cumulative Emission

Reduction (kt)

Marginal Cost

(EURO/t CH4)

increased feed intake 1.97 4.96 -3149.91upgraded recovery & utilization of gas from current level to 70% 5.14 10.11 -48.83upgraded recovery & utilization of gas from current level to 70% 0.77 10.88 -48.83reduction at compressor stations 0.00 10.88 -36.68autonomous increases in agricultural productivity 0.00 10.88 0.00autonomous increases in agricultural productivity 0.00 10.88 0.00autonomous increases in agricultural productivity 0.00 10.88 0.00autonomous increases in agricultural productivity 0.00 10.88 0.00alternative rice strains 2.95 13.83 47.00farm-scale 22.47 36.30 56.61all options to reduce methane emissions from paper waste 32.63 68.92 57.47flaring instead of venting of gas-oil/gas production 0.00 68.92 72.86flaring instead of venting of gas-oil/gas production 140.42 209.34 72.86flaring instead of venting of gas-refineries 0.02 209.36 72.86farm-scale 0.94 210.31 97.60all options to reduce methane emissions from organic waste 177.50 387.80 119.06farm-scale 2.34 390.15 128.96doubling of leak control frequency of network 1.76 391.90 168.60doubling of leak control frequency of network 0.45 392.35 168.60doubling of leak control frequency of network 2.98 395.33 168.60doubling of leak control frequency of network 0.34 395.67 168.60doubling of leak control frequency of network 4.15 399.82 168.60doubling of leak control frequency of network 0.00 399.82 168.60doubling of leak control frequency of network 0.23 400.05 168.60doubling of leak control frequency of network 7.40 407.45 168.60doubling of leak control frequency of network 407.45 168.60gas recovery and utilization 20.41 427.86 189.54ban on agricultural waste burning 0.00 427.86 500.00propionate precursors 0.00 427.86 527.00propionate precursors 0.00 427.86 527.00propionate precursors 0.00 427.86 1100.00propionate precursors 0.00 427.86 1100.00replacement of grey cast iron networks 12.81 440.67 1858.25replacement of grey cast iron networks 3.26 443.93 1858.25replacement of grey cast iron networks 21.78 465.71 1858.25


Measure


Cumulative Emission

Reduction (kt)

Marginal Cost

(EURO/t CH4)

replacement of grey cast iron networks 2.47 468.18 1858.25replacement of grey cast iron networks 30.30 498.48 1858.25replacement of grey cast iron networks 0.00 498.48 1858.25replacement of grey cast iron networks 1.65 500.14 1858.25replacement of grey cast iron networks 53.98 554.12 1858.25replacement of grey cast iron networks 554.12 1858.25change to more nsc in diet 1.61 555.73 3355.10change to more nsc in diet 0.48 556.21 3355.10change to more nsc in diet 0.91 557.12 4675.40change to more nsc in diet 3.04 560.16 4675.40replacement of roughage for concentrate 2.00 562.17 5248.42replacement of roughage for concentrate 0.60 562.77 5248.42increased feed intake 2.00 564.77 8569.54increased feed intake 0.60 565.37 8569.54housing adaptation 2.23 567.60 38150.00housing adaptation 0.00 567.60 38150.00integrated sewage system 42.19 609.79 1000000.00

Table 24. Marginal cost curve data for CH4 emissions for Russia (GAINS)

Measure


Cumulative Emission

Reduction (kt)

Marginal Cost

(EURO/t CH4)

replacement of roughage for concentrate 10.03 10.03 -3205.47 replacement of roughage for concentrate 9.26 19.29 -3205.47 increased feed intake 10.68 29.98 -1507.57 increased feed intake 9.86 39.83 -1507.57 autonomous increases in agricultural productivity 0.00 39.83 0.00 autonomous increases in agricultural productivity 0.00 39.83 0.00 autonomous increases in agricultural productivity 0.00 39.83 0.00 autonomous increases in agricultural productivity 0.00 39.83 0.00 reduction at compressor stations 8969.47 9009.30 42.52 alternative rice strains 0.00 9009.30 47.00 upgraded recovery & utilization of gas from current level to 70% 0.00 9009.30 55.17 upgraded recovery & utilization of gas from current level to 70% 1534.49 10543.79 55.17 flaring instead of venting of gas-oil/gas production 10.57 10554.36 72.86


Measure


Cumulative Emission

Reduction (kt)

Marginal Cost

(EURO/t CH4)

flaring instead of venting of gas-oil/gas production 427.77 10982.13 72.86 flaring instead of venting of gas-refineries 0.21 10982.35 72.86 all options to reduce methane emissions from paper waste 255.46 11237.81 95.82 farm-scale 66.75 11304.56 99.31 all options to reduce methane emissions from organic waste 885.46 12190.02 142.37 farm-scale 17.29 12207.31 171.20 farm-scale 17.67 12224.98 226.21 gas recovery and utilization 118.56 12343.53 246.42 doubling of leak control frequency of network 23.16 12366.69 272.60 doubling of leak control frequency of network 5.90 12372.59 272.60 doubling of leak control frequency of network 16.82 12389.41 272.60 doubling of leak control frequency of network 0.00 12389.41 272.60 doubling of leak control frequency of network 51.51 12440.93 272.60 doubling of leak control frequency of network 0.00 12440.93 272.60 doubling of leak control frequency of network 56.21 12497.14 272.60 doubling of leak control frequency of network 105.14 12602.28 272.60 doubling of leak control frequency of network 12602.28 272.60 ban on agricultural waste burning 0.02 12602.30 500.00 propionate precursors 0.00 12602.30 527.00 propionate precursors 0.00 12602.30 527.00 propionate precursors 0.00 12602.30 1100.00 propionate precursors 0.00 12602.30 1100.00 replacement of grey cast iron networks 169.00 12771.30 1960.95 replacement of grey cast iron networks 43.06 12814.36 1960.95 replacement of grey cast iron networks 122.79 12937.15 1960.95 replacement of grey cast iron networks 0.00 12937.15 1960.95 replacement of grey cast iron networks 375.95 13313.10 1960.95 replacement of grey cast iron networks 0.00 13313.10 1960.95 replacement of grey cast iron networks 410.25 13723.35 1960.95 replacement of grey cast iron networks 767.34 14490.68 1960.95 replacement of grey cast iron networks 14490.68 1960.95 change to more nsc in diet 8.06 14498.75 3451.83 change to more nsc in diet 8.74 14507.49 3451.83


Measure


Cumulative Emission

Reduction (kt)

Marginal Cost

(EURO/t CH4)

change to more nsc in diet 7.24 14514.72 4668.39 change to more nsc in diet 6.68 14521.40 4668.39 replacement of roughage for concentrate 4.40 14525.80 4971.66 replacement of roughage for concentrate 4.76 14530.56 4971.66 increased feed intake 4.40 14534.96 8257.30 increased feed intake 4.76 14539.72 8257.30 housing adaptation 6.61 14546.34 38150.00 housing adaptation 0.00 14546.34 38150.00 integrated sewage system 245.13 14791.47 1000000.00

Table 25. Marginal cost curve data for CH4 emissions for Slovakia (GAINS)

Measure

Sum Of Emissions saved

(kt)


(kt)


CH4) replacement of roughage for concentrate 0.10 0.10 -11720.59replacement of roughage for concentrate 0.09 0.19 -11720.59increased feed intake 0.10 0.29 -10359.86increased feed intake 0.10 0.39 -10359.86all options to reduce methane emissions from paper waste 0.68 1.07 -121.42reduction at compressor stations 0.00 1.07 -35.57autonomous increases in agricultural productivity 0.00 1.07 0.00autonomous increases in agricultural productivity 0.00 1.07 0.00autonomous increases in agricultural productivity 0.00 1.07 0.00autonomous increases in agricultural productivity 0.00 1.07 0.00upgraded recovery & utilization of gas from current level to 70% 2.92 3.99 2.51upgraded recovery & utilization of gas from current level to 70% 0.00 3.99 2.51alternative rice strains 0.00 3.99 47.00flaring instead of venting of gas-oil/gas production 0.01 3.99 74.55flaring instead of venting of gas-oil/gas production 0.71 4.71 74.55flaring instead of venting of gas-refineries 0.01 4.72 74.55farm-scale 2.88 7.60 78.44farm-scale 0.32 7.92 135.23


Measure


(kt)


(kt)


CH4) all options to reduce methane emissions from organic waste 1.04 8.95 135.54farm-scale 0.44 9.39 178.67gas recovery and utilization 14.25 23.65 216.34doubling of leak control frequency of network 0.06 23.71 289.51doubling of leak control frequency of network 0.10 23.80 289.51doubling of leak control frequency of network 1.16 24.97 289.51doubling of leak control frequency of network 0.08 25.05 289.51doubling of leak control frequency of network 2.25 27.30 289.51doubling of leak control frequency of network 0.00 27.30 289.51doubling of leak control frequency of network 0.38 27.69 289.51doubling of leak control frequency of network 2.52 30.20 289.51doubling of leak control frequency of network 30.20 289.51ban on agricultural waste burning 0.00 30.20 500.00propionate precursors 0.00 30.20 527.00propionate precursors 0.00 30.20 527.00propionate precursors 0.00 30.20 1100.00propionate precursors 0.00 30.20 1100.00replacement of grey cast iron networks 0.45 30.65 1905.65replacement of grey cast iron networks 0.71 31.36 1905.65replacement of grey cast iron networks 8.47 39.83 1905.65replacement of grey cast iron networks 0.60 40.43 1905.65replacement of grey cast iron networks 16.44 56.87 1905.65replacement of grey cast iron networks 0.00 56.87 1905.65replacement of grey cast iron networks 2.81 59.68 1905.65replacement of grey cast iron networks 18.36 78.04 1905.65replacement of grey cast iron networks 78.04 1905.65replacement of roughage for concentrate 0.10 78.14 2628.21replacement of roughage for concentrate 0.11 78.25 2628.21change to more nsc in diet 0.08 78.33 2930.41change to more nsc in diet 0.09 78.42 2930.41change to more nsc in diet 0.17 78.59 4609.04change to more nsc in diet 0.16 78.74 4609.04increased feed intake 0.10 78.84 5613.41increased feed intake 0.11 78.96 5613.41housing adaptation 0.29 79.24 38150.00


Measure


(kt)


(kt)


CH4) housing adaptation 0.00 79.24 38150.00integrated sewage system 0.00 79.24 1000000.00

Table 26. Marginal cost curve data for CH4 emissions for Ukraine (GAINS)

Measure



(kt)

Marginal Cost

(EURO/t CH4)

replacement of roughage for concentrate 6.55 6.55 -2209.64replacement of roughage for concentrate 6.04 12.59 -2209.64increased feed intake 6.97 19.56 -472.31increased feed intake 6.43 25.99 -472.31autonomous increases in agricultural productivity 0.00 25.99 0.00autonomous increases in agricultural productivity 0.00 25.99 0.00autonomous increases in agricultural productivity 0.00 25.99 0.00autonomous increases in agricultural productivity 0.00 25.99 0.00reduction at compressor stations 218.01 244.00 13.36alternative rice strains 0.00 244.00 47.00upgraded recovery & utilization of gas from current level to 70% 0.00 244.00 59.17upgraded recovery & utilization of gas from current level to 70% 596.56 840.56 59.17flaring instead of venting of gas-oil/gas production 0.44 841.00 72.86flaring instead of venting of gas-oil/gas production 157.12 998.12 72.86flaring instead of venting of gas-refineries 0.07 998.19 72.86all options to reduce methane emissions from paper waste 126.11 1124.31 96.53farm-scale 50.30 1174.60 100.95all options to reduce methane emissions from organic waste 368.50 1543.10 143.27farm-scale 11.28 1554.38 174.03farm-scale 14.54 1568.92 229.95gas recovery and utilization 49.34 1618.26 248.60doubling of leak control frequency of network 1.87 1620.13 276.60doubling of leak control frequency of network 1.53 1621.66 276.60doubling of leak control frequency of network 14.65 1636.31 276.60doubling of leak control frequency of network 0.00 1636.31 276.60doubling of leak control frequency of network 21.13 1657.44 276.60doubling of leak control frequency of network 0.00 1657.44 276.60doubling of leak control frequency of network 20.54 1677.98 276.60doubling of leak control frequency of network 24.36 1702.34 276.60doubling of leak control frequency of network 1702.34 276.60ban on agricultural waste burning 0.01 1702.35 500.00propionate precursors 0.00 1702.35 527.00


Measure



(kt)

Marginal Cost

(EURO/t CH4)

propionate precursors 0.00 1702.35 527.00propionate precursors 0.00 1702.35 1100.00propionate precursors 0.00 1702.35 1100.00replacement of grey cast iron networks 13.63 1715.98 1964.90replacement of grey cast iron networks 11.18 1727.16 1964.90replacement of grey cast iron networks 106.90 1834.06 1964.90replacement of grey cast iron networks 0.00 1834.06 1964.90replacement of grey cast iron networks 154.21 1988.27 1964.90replacement of grey cast iron networks 0.00 1988.27 1964.90replacement of grey cast iron networks 149.93 2138.20 1964.90replacement of grey cast iron networks 177.78 2315.98 1964.90replacement of grey cast iron networks 2315.98 1964.90change to more nsc in diet 5.26 2321.24 3512.81change to more nsc in diet 5.70 2326.94 3512.81change to more nsc in diet 5.64 2332.58 4698.60change to more nsc in diet 5.21 2337.79 4698.60replacement of roughage for concentrate 3.43 2341.22 6164.18replacement of roughage for concentrate 3.72 2344.93 6164.18increased feed intake 3.43 2348.36 9602.71increased feed intake 3.72 2352.08 9602.71housing adaptation 4.98 2357.06 38150.00housing adaptation 0.00 2357.06 38150.00integrated sewage system 102.01 2459.08 1000000.00


Annex IV: Marginal cost curve data for F-Gas emissions for 8 countries (GAINS) Table 27. Marginal cost curve data for F-Gas emissions for Bulgaria (GAINS)

Measure

Sum Of Emissions saved (t)


(t)

Marginal Cost

(EURO/t CO2eq)

alternative protection gas: SF6 replaced by SO2 0.00 0.00 0.10ban of use- SF6 0.00 0.00 0.10ban of use- windows 0.00 0.00 0.10incineration: post combustion of HFC-23 emitted from production of HCFC-22 0.00 0.00 0.30alternative blowing agents (many different kinds) one component foam 8840.00 8840.00 0.50alternative propellant (aerosols) 1144.00 9984.00 1.00SWPB retrofitting 0.00 9984.00 1.40

alternative refridgerant: use of open CO2 refridgerant system (transport refridgeration bank) 21711.64 31695.64 2.00

alternative refridgerant: use of open CO2 refridgerant system (transport refridgeration scrap) 0.00 31695.64 2.00SWBP to PFPB conversion 0.00 31695.64 3.30good practice: leakage control and end-of-life recollection and recycling 894.51 32590.14 3.60alternative blowing agents (many different kinds) other foams 734.07 33324.21 4.90VSS retrofitting 0.00 33324.21 7.10good practice: end-of-life recollection (domestic hermetic refridgerators) 15600.00 48924.21 14.60good practice: leakage control, improved components (industrial refridgeration) 18682.14 67606.35 15.10good practice: end-of-life recollection (industrial refridgeration) 322.94 67929.29 15.10good practice: leakage control, improved components (transport refridgeration) 26772.60 94701.89 17.82good practice: end-of-life recollection (transport refridgeration) 296.71 94998.60 17.82good practice: leakage control, improved components (commercial refridgeraton) 5754.85 100753.45 18.10good practice: end-of-life recollection (commercial refridgeration) 20284.04 121037.49 18.10good practice: leakage control, improved components (mobile air conditioning) 7866.69 128904.18 22.70good practice: end-of-life recollection (mobile air conditioning) 0.00 128904.18 22.70


Measure



(t)

Marginal Cost

(EURO/t CO2eq)

alternative solvent 0.00 128904.18 26.00alternative refridgerant: HFC134a replaced by pressurized CO2 (mobile air conditioning (bank)) 2557.26 131461.44 30.60alternative refridgerant: HFC134a replaced by pressurized CO2 (mobile air conditoning (scrap)) 0.00 131461.44 30.60process modification including alternative refridgerants (commercial refridgeration bank) 15538.10 146999.54 31.70process modification including alternative refridgerants (commercial refridgeration scrap) 0.00 146999.54 31.70process modification including alternative refridgerants (industrial refridgeration bank) 11956.57 158956.11 32.10process modification including alternative refridgerants (industrial refridgeration scrap) 0.00 158956.11 32.10good practice: leakage control, improved components(stationary air conditioning bank) 1817.61 160773.72 43.10good practice: end-of-life recollection (stationary air conditioning scrap) 72.51 160846.24 43.10VSS to PFPB conversion 0.00 160846.24 55.70process modification including alternative refridgerants (stationary air conditioning bank) 1615.65 162461.89 64.20process modification including alternative refridgerants (stationary air conditioning scrap) 0.00 162461.89 64.20

Table 28. Marginal cost curve data for F-Gas emissions for Czech Republic (GAINS)

Measure



(t)

Marginal Cost

(EURO/t CO2eq)

alternative protection gas: SF6 replaced by SO2 2.39 2.39 0.10ban of use- SF6 0.00 2.39 0.10ban of use- windows 0.00 2.39 0.10incineration: post combustion of HFC-23 emitted from production of HCFC-22 0.00 2.39 0.30alternative blowing agents (many different kinds) one component foam 35360.00 35362.39 0.50alternative propellant (aerosols) 4784.00 40146.39 1.00SWPB retrofitting 0.00 40146.39 1.40alternative refridgerant: use of open CO2 refridgerant system (transport refridgeration bank) 29521.01 69667.40 2.00alternative refridgerant: use of open CO2 refridgerant system (transport refridgeration swap) 0.00 69667.40 2.00SWBP to PFPB conversion 0.00 69667.40 3.30good practice: leakage control and end-of-life recollection and recycling 20076.00 89743.40 3.60


Measure



(t)

Marginal Cost

(EURO/t CO2eq)

alternative blowing agents (many different kinds) other foams 3082.09 92825.48 4.90VSS retrofitting 0.00 92825.48 7.10good practice: end-of-life recollection (domestic hermetic refridgerators) 0.00 92825.48 14.60good practice: leakage control, improved components 25401.84 118227.33 15.10good practice: end-of-life recollection 0.00 118227.33 15.10good practice: leakage control, improved components (transport refridgeration) 36402.32 154629.65 17.82good practice: end-of-life recollection (transport refridgeration) 0.00 154629.65 17.82good practice: leakage control, improved components 25217.28 179846.93 18.10good practice: end-of-life recollection 0.00 179846.93 18.10good practice: leakage control, improved components 71595.80 251442.73 22.70good practice: end-of-life recollection 0.00 251442.73 22.70alternative solvent 115830.00 367272.73 26.00alternative refridgerant: HFC134a replaced by pressurized CO2 (bank) 23273.98 390546.71 30.60alternative refridgerant: HFC134a replaced by pressurized CO2 (scrap) 0.00 390546.71 30.60process modification including alternative refridgerants (commercial refridgeration bank) 68086.66 458633.38 31.70process modification including alternative refridgerants (commercial refridgeration scrap) 0.00 458633.38 31.70process modification including alternative refridgerants (industrial refridgeration bank) 16257.18 474890.55 32.10process modification including alternative refridgerants (industrial refridgeration scrap) 0.00 474890.55 32.10good practice: leakage control, improved components ( stationary air bank) 7631.47 482522.02 43.10good practice: end-of-life recollection (stationary air scrap) 0.00 482522.02 43.10VSS to PFPB conversion 0.00 482522.02 55.70process modification including alternative refridgerants (stationary air bank) 6783.53 489305.55 64.20process modification including alternative refridgerants (stationary air scrap) 0.00 489305.55 64.20


Table 29. Marginal cost curve data for F-Gas emissions for Hungary (GAINS)

Measure



(t)


CO2eq) alternative protection gas: SF6 replaced by SO2 0.00 0.00 0.10ban of use- SF6 0.00 0.00 0.10ban of use- windows 0.00 0.00 0.10incineration: post combustion of HFC-23 emitted from production of HCFC-22 0.00 0.00 0.30alternative blowing agents (many different kinds) one component foam 32045.00 32045.00 0.50alternative propellant (aerosols) 4368.00 36413.00 1.00SWPB retrofitting 0.00 36413.00 1.40alternative refridgerant: use of open CO2 refridgerant system (transport refridgeration bank) 29097.60 65510.60 2.00alternative refridgerant: use of open CO2 refridgerant system ( transport refridgeration scrap) 0.00 65510.60 2.00SWBP to PFPB conversion 0.00 65510.60 3.30good practice: leakage control and end-of-life recollection and recycling 20076.00 85586.60 3.60alternative blowing agents (many different kinds) other foams 2800.53 88387.12 4.90VSS retrofitting 0.00 88387.12 7.10good practice: end-of-life recollection (domestic hermetic refridgerators) 0.00 88387.12 14.60good practice: leakage control, improved components 24896.72 113283.84 15.10good practice: end-of-life recollection 0.00 113283.84 15.10good practice: leakage control, improved components 35880.22 149164.06 17.82good practice: end-of-life recollection 0.00 149164.06 17.82good practice: leakage control, improved components 22913.58 172077.64 18.10good practice: end-of-life recollection 0.00 172077.64 18.10good practice: leakage control, improved components 15455.64 187533.29 22.70good practice: end-of-life recollection 0.00 187533.29 22.70alternative solvent 0.00 187533.29 26.00alternative refridgerant: HFC134a replaced by pressurized CO2 5024.24 192557.52 30.60alternative refridgerant: HFC134a replaced by pressurized CO2 0.00 192557.52 30.60process modification including alternative refridgerants (commercial refridgeration bank) 61866.68 254424.20 31.70process modification including alternative refridgerants (commercial refridgeration scrap) 0.00 254424.20 31.70process modification including alternative refridgerants (industrial refridgeration bank) 15933.90 270358.10 32.10process modification including alternative refridgerants (industrial refridgeration scrap) 0.00 270358.10 32.10good practice: leakage control, improved components (stationary air bank) 6934.30 277292.40 43.10


Measure



(t)


CO2eq) good practice: end-of-life recollection (stationary air scrap 0.00 277292.40 43.10VSS to PFPB conversion 122126.55 399418.95 55.70process modification including alternative refridgerants (stationary air bank) 6163.83 405582.78 64.20process modification including alternative refridgerants (stationary air scrap) 0.00 405582.78 64.20

Table 30. Marginal cost curve data for F-Gas emissions for Poland (GAINS)

Measure



(t)

Marginal Cost

(EURO/t CO2eq)

alternative protection gas: SF6 replaced by SO2 23.90 23.90 0.10ban of use- SF6 0.00 23.90 0.10ban of use- windows 0.00 23.90 0.10incineration: post combustion of HFC-23 emitted from production of HCFC-22 0.00 23.90 0.30alternative blowing agents (many different kinds) one component foam 111605.00 111628.90 0.50alternative propellant (aerosols) 15288.00 126916.90 1.00SWPB retrofitting 0.00 126916.90 1.40alternative refridgerant: use of open CO2 refridgerant system (transport refridgeration bank) 0.00 126916.90 2.00alternative refridgerant: use of open CO2 refridgerant system (transport refridgeration scrap) 0.00 126916.90 2.00SWBP to PFPB conversion 0.00 126916.90 3.30good practice: leakage control and end-of-life recollection and recycling 20076.00 146992.90 3.60alternative blowing agents (many different kinds) other foams 9784.25 156777.15 4.90VSS retrofitting 0.00 156777.15 7.10good practice: end-of-life recollection (domestic hermetic refridgerators) 0.00 156777.15 14.60good practice: leakage control, improved components (industrial refridgeration) 95723.10 252500.25 15.10good practice: end-of-life recollection (industrial refridgeration) 0.00 252500.25 15.10good practice: leakage control, improved components (transport refridgeration) 0.00 252500.25 17.82good practice: end-of-life recollection (transport refridgeration) 0.00 252500.25 17.82good practice: leakage control, improved components (commercial refridgeraton) 121269.55 373769.80 18.10


Measure



(t)

Marginal Cost

(EURO/t CO2eq)

good practice: end-of-life recollection (commercial refridgeration) 0.00 373769.80 18.10good practice: leakage control, improved components (mobile air conditioning) 196532.43 570302.23 22.70good practice: end-of-life recollection (mobile air conditioning) 0.00 570302.23 22.70alternative solvent 0.00 570302.23 26.00alternative refridgerant: HFC134a replaced by pressurized CO2 (mobile air conditioning (bank)) 63887.71 634189.93 30.60alternative refridgerant: HFC134a replaced by pressurized CO2 (mobile air conditoning (scrap)) 0.00 634189.93 30.60process modification including alternative refridgerants (commercial refridgeration bank) 327427.79 961617.72 31.70process modification including alternative refridgerants (commercial refridgeration scrap) 0.00 961617.72 31.70process modification including alternative refridgerants (industrial refridgeration bank) 61262.78 1022880.50 32.10process modification including alternative refridgerants (industrial refridgeration scrap) 0.00 1022880.50 32.10good practice: leakage control, improved components(stationary air conditioning bank) 26386.32 1049266.82 43.10good practice: end-of-life recollection (stationary air conditioning scrap) 0.00 1049266.82 43.10VSS to PFPB conversion 86911.83 1136178.65 55.70process modification including alternative refridgerants (stationary air conditioning bank) 23454.51 1159633.15 64.20process modification including alternative refridgerants (stationary air conditioning scrap) 0.00 1159633.15 64.20

Table 31. Marginal cost curve data for F-Gas emissions for Romania (GAINS)

Measure



(t)

Marginal Cost

(EURO/t CO2eq)

alternative protection gas: SF6 replaced by SO2 0.00 0.00 0.10 ban of use- SF6 0.00 0.00 0.10 ban of use- windows 0.00 0.00 0.10 incineration: post combustion of HFC-23 emitted from production of HCFC-22 0.00 0.00 0.30 alternative blowing agents (many different kinds) one component foam 24310.00 24310.00 0.50 alternative propellant (aerosols) 3328.00 27638.00 1.00 SWPB retrofitting 0.00 27638.00 1.40


Measure



(t)

Marginal Cost

(EURO/t CO2eq)

alternative refridgerant: use of open CO2 refridgerant system (transport refridgeration bank) 64149.99 91787.99 2.00 alternative refridgerant: use of open CO2 refridgerant system (transport refridgeration scrap) 0.00 91787.99 2.00 SWBP to PFPB conversion 0.00 91787.99 3.30 good practice: leakage control and end-of-life recollection and recycling 20076.00 111863.99 3.60 alternative blowing agents (many different kinds) other foams 0.00 111863.99 4.90 VSS retrofitting 0.00 111863.99 7.10 good practice: end-of-life recollection (domestic hermetic refridgerators) 39520.00 151383.99 14.60 good practice: leakage control, improved components (industrial refridgeration) 55198.93 206582.92 15.10 good practice: end-of-life recollection (industrial refridgeration) 954.16 207537.08 15.10 good practice: leakage control, improved components (transport refridgeration) 79103.29 286640.37 17.82 good practice: end-of-life recollection (transport refridgeration) 857.63 287498.00 17.82 good practice: leakage control, improved components (commercial refridgeraton) 4883.97 292381.97 18.10 good practice: end-of-life recollection (commercial refridgeration) 0.00 292381.97 18.10 good practice: leakage control, improved components (mobile air conditioning) 23094.65 315476.62 22.70 good practice: end-of-life recollection (mobile air conditioning) 0.00 315476.62 22.70 alternative solvent 0.00 315476.62 26.00 alternative refridgerant: HFC134a replaced by pressurized CO2 (mobile air conditioning (bank)) 7507.48 322984.10 30.60 alternative refridgerant: HFC134a replaced by pressurized CO2 (mobile air conditoning (scrap)) 0.00 322984.10 30.60 process modification including alternative refridgerants (commercial refridgeration bank) 13186.73 336170.83 31.70 process modification including alternative refridgerants (commercial refridgeration scrap) 0.00 336170.83 31.70 process modification including alternative refridgerants (industrial refridgeration bank) 35327.31 371498.15 32.10 process modification including alternative refridgerants (industrial refridgeration scrap) 0.00 371498.15 32.10


Measure



(t)

Marginal Cost

(EURO/t CO2eq)

good practice: leakage control, improved components(stationary air conditioning bank) 1102.27 372600.42 43.10 good practice: end-of-life recollection (stationary air conditioning scrap) 0.00 372600.42 43.10 VSS to PFPB conversion 0.00 372600.42 55.70 process modification including alternative refridgerants (stationary air conditioning bank) 979.79 373580.21 64.20 process modification including alternative refridgerants (stationary air conditioning scrap) 0.00 373580.21 64.20

Table 32. Marginal cost curve data for F-Gas emissions for Russia (GAINS)

Measure


Cumulative Emission

Reduction (t)

Marginal Cost

(EURO/t CO2eq)

alternative protection gas: SF6 replaced by SO2 836508.37 836508.37 0.10 ban of use- SF6 0.00 836508.37 0.10 ban of use- windows 0.00 836508.37 0.10 incineration: post combustion of HFC-23 emitted from production of HCFC-22 0.00 836508.37 0.30 alternative blowing agents (many different kinds) one component foam 0.00 836508.37 0.50 alternative propellant (aerosols) 47840.48 884348.84 1.00 SWPB retrofitting 0.00 884348.84 1.40 alternative refridgerant: use of open CO2 refridgerant system (transport refridgeration bank) 158.96 884507.80 2.00 alternative refridgerant: use of open CO2 refridgerant system (transport refridgeration scrap) 0.00 884507.80 2.00 SWBP to PFPB conversion 0.00 884507.80 3.30 good practice: leakage control and end-of-life recollection and recycling 1236228.00 2120735.80 3.60 alternative blowing agents (many different kinds) other foams 0.00 2120735.80 4.90 VSS retrofitting 0.00 2120735.80 7.10 good practice: end-of-life recollection (domestic hermetic refridgerators) 277682.78 2398418.58 14.60 good practice: leakage control, improved components (industrial refridgeration) 117283.06 2515701.64 15.10 good practice: end-of-life recollection (industrial refridgeration) 0.00 2515701.64 15.10 good practice: leakage control, improved components (transport refridgeration) 1950.18 2517651.82 17.82


Measure


Cumulative Emission

Reduction (t)

Marginal Cost

(EURO/t CO2eq)

good practice: end-of-life recollection (transport refridgeration) 15301.58 2532953.40 17.82 good practice: leakage control, improved components (commercial refridgeraton) 208901.66 2741855.06 18.10 good practice: end-of-life recollection (commercial refridgeration) 0.00 2741855.06 18.10 good practice: leakage control, improved components (mobile air conditioning) 27424.14 2769279.20 22.70 good practice: end-of-life recollection (mobile air conditioning) 0.00 2769279.20 22.70 alternative solvent 1188011.88 3957291.08 26.00 alternative refridgerant: HFC134a replaced by pressurized CO2 (mobile air conditioning (bank)) 8914.89 3966205.97 30.60 alternative refridgerant: HFC134a replaced by pressurized CO2 (mobile air conditoning (scrap)) 0.00 3966205.97 30.60 process modification including alternative refridgerants (commercial refridgeration bank) 24131.47 3990337.44 31.70 process modification including alternative refridgerants (commercial refridgeration scrap) 0.00 3990337.44 31.70 process modification including alternative refridgerants (industrial refridgeration bank) 4716.20 3995053.64 32.10 process modification including alternative refridgerants (industrial refridgeration scrap) 0.00 3995053.64 32.10 good practice: leakage control, improved components(stationary air conditioning bank) 31459.52 4026513.17 43.10 good practice: end-of-life recollection (stationary air conditioning scrap) 0.00 4026513.17 43.10 VSS to PFPB conversion 6016885.24 10043398.41 55.70 process modification including alternative refridgerants (stationary air conditioning bank) 1757.02 10045155.43 64.20 process modification including alternative refridgerants (stationary air conditioning scrap) 0.00 10045155.43 64.20

Table 33. Marginal cost curve data for F-Gas emissions for Slovakia (GAINS)

Measure



(t)

Marginal Cost

(EURO/t CO2eq)

alternative protection gas: SF6 replaced by 0.00 0.00 0.10


Measure



(t)

Marginal Cost

(EURO/t CO2eq)

SO2 ban of use- SF6 0.00 0.00 0.10 ban of use- windows 0.00 0.00 0.10 incineration: post combustion of HFC-23 emitted from production of HCFC-22 0.00 0.00 0.30 alternative blowing agents (many different kinds) one component foam 12665.20 12665.20 0.50 alternative propellant (aerosols) 1768.00 14433.20 1.00 SWPB retrofitting 0.00 14433.20 1.40 alternative refridgerant: use of open CO2 refridgerant system (transport refridgeration bank) 14813.53 29246.73 2.00 alternative refridgerant: use of open CO2 refridgerant system (transport refridgeration scrap) 0.00 29246.73 2.00 SWBP to PFPB conversion 0.00 29246.73 3.30 good practice: leakage control and end-of-life recollection and recycling 20076.00 49322.73 3.60 alternative blowing agents (many different kinds) other foams 1111.16 50433.89 4.90 VSS retrofitting 0.00 50433.89 7.10 good practice: end-of-life recollection (domestic hermetic refridgerators) 0.00 50433.89 14.60 good practice: leakage control, improved components (industrial refridgeration) 13457.89 63891.78 15.10 good practice: end-of-life recollection (industrial refridgeration) 0.00 63891.78 15.10 good practice: leakage control, improved components (transport refridgeration) 18266.54 82158.33 17.82 good practice: end-of-life recollection (transport refridgeration) 0.00 82158.33 17.82 good practice: leakage control, improved components (commercial refridgeraton) 9091.39 91249.71 18.10 good practice: end-of-life recollection (commercial refridgeration) 0.00 91249.71 18.10 good practice: leakage control, improved components (mobile air conditioning) 8773.02 100022.73 22.70 good practice: end-of-life recollection (mobile air conditioning) 0.00 100022.73 22.70 alternative solvent 0.00 100022.73 26.00 alternative refridgerant: HFC134a replaced by pressurized CO2 (mobile air conditioning (bank)) 2851.89 102874.62 30.60 alternative refridgerant: HFC134a replaced by pressurized CO2 (mobile air conditoning (scrap)) 0.00 102874.62 30.60


Measure



(t)

Marginal Cost

(EURO/t CO2eq)

process modification including alternative refridgerants (commercial refridgeration bank) 24546.74 127421.36 31.70 process modification including alternative refridgerants (commercial refridgeration scrap) 0.00 127421.36 31.70 process modification including alternative refridgerants (industrial refridgeration bank) 8613.05 136034.41 32.10 process modification including alternative refridgerants (industrial refridgeration scrap) 0.00 136034.41 32.10 good practice: leakage control, improved components(stationary air conditioning bank) 2751.31 138785.73 43.10 good practice: end-of-life recollection (stationary air conditioning scrap) 0.00 138785.73 43.10 VSS to PFPB conversion 0.00 138785.73 55.70 process modification including alternative refridgerants (stationary air conditioning bank) 2445.61 141231.34 64.20 process modification including alternative refridgerants (stationary air conditioning scrap) 0.00 141231.34 64.20

Table 34. Marginal cost curve data for F-Gas emissions for Ukraine (GAINS)

Measure Sum Of Emissions

saved (t)


(t)

Marginal Cost

(EURO/t CO2eq)

alternative protection gas: SF6 replaced by SO2 239000.00 239000.00 0.10ban of use- SF6 0.00 239000.00 0.10ban of use- windows 0.00 239000.00 0.10incineration: post combustion of HFC-23 emitted from production of HCFC-22 0.00 239000.00 0.30alternative blowing agents (many different kinds) one component foam 0.00 239000.00 0.50alternative propellant (aerosols) 8528.00 247528.00 1.00SWPB retrofitting 0.00 247528.00 1.40alternative refridgerant: use of open CO2 refridgerant system (transport refridgeration bank) 0.00 247528.00 2.00alternative refridgerant: use of open CO2 refridgerant system (transport refridgeration scrap) 0.00 247528.00 2.00SWBP to PFPB conversion 0.00 247528.00 3.30good practice: leakage control and end-of-life recollection and recycling 252000.00 499528.00 3.60alternative blowing agents (many different kinds) other foams 0.00 499528.00 4.90VSS retrofitting 0.00 499528.00 7.10


Measure Sum Of Emissions

saved (t)


(t)

Marginal Cost

(EURO/t CO2eq)

good practice: end-of-life recollection (domestic hermetic refridgerators) 0.00 499528.00 14.60good practice: leakage control, improved components (industrial refridgeration) 21823.06 521351.06 15.10good practice: end-of-life recollection (industrial refridgeration) 0.00 521351.06 15.10good practice: leakage control, improved components (transport refridgeration) 648.43 521999.50 17.82good practice: end-of-life recollection (transport refridgeration) 2732.72 524732.22 17.82good practice: leakage control, improved components (commercial refridgeraton) 39702.21 564434.43 18.10good practice: end-of-life recollection (commercial refridgeration) 0.00 564434.43 18.10good practice: leakage control, improved components (mobile air conditioning) 10978.57 575413.00 22.70good practice: end-of-life recollection (mobile air conditioning) 0.00 575413.00 22.70alternative solvent 0.00 575413.00 26.00alternative refridgerant: HFC134a replaced by pressurized CO2 (mobile air conditioning (bank)) 3568.85 578981.85 30.60alternative refridgerant: HFC134a replaced by pressurized CO2 (mobile air conditoning (scrap)) 0.00 578981.85 30.60process modification including alternative refridgerants (commercial refridgeration bank) 0.00 578981.85 31.70process modification including alternative refridgerants (commercial refridgeration scrap) 0.00 578981.85 31.70process modification including alternative refridgerants (industrial refridgeration bank) 0.00 578981.85 32.10process modification including alternative refridgerants (industrial refridgeration scrap) 0.00 578981.85 32.10good practice: leakage control, improved components(stationary air conditioning bank) 5853.73 584835.58 43.10good practice: end-of-life recollection (stationary air conditioning scrap) 0.00 584835.58 43.10VSS to PFPB conversion 410228.00 995063.58 55.70process modification including alternative refridgerants (stationary air conditioning bank) 0.00 995063.58 64.20process modification including alternative refridgerants (stationary air conditioning scrap) 0.00 995063.58 64.20


Annex V. Applicability of Poland GAINS Results for JI Assessment The potential for the application of cost-effective measures in GHG abatement in relation to non-CO2 greenhouse gases through the implementation of JI mechanism in Poland. 1. The usefulness of a GAINS Version 1.0 model for assessment of JI potential in EU member countries The aim of this report is to assess the potential for Joint Implementation projects involving transfer of new technologies to those industrial sectors in Poland, which remain outside the scope of the EU ETS and will not be affected by the associated Linking Directive in 2008-2012. This means such non-CO2 greenhouse gases as nitrous oxide, methane, and the three F-gases. The potential for JI mechanism in CO2 abatement will not be considered, since CO2 emissions from combustion and some other industrial processes20 come under the European Emissions Trading Scheme (EU ETS), now in its pilot phase (2005 – 2007). In the next trading phase, parallel to the first Kyoto commitment period, emissions abated under Joint Implementation projects influencing emissions from the grid, directly or indirectly, would have to be deducted from the sectoral emissions cap allocated to energy sector (indirect influence) or from an allocation granted to an individual combustion installation (direct influence) by a member country hosting that JI project. This rule will apply to the new member countries which have a surplus under Kyoto commitments and, since ERU prices are much lower than those of the EU allowances (EUAs), any potential abatement projects influencing emissions from combustion installation in these countries will be financed from the proceeds from the sale of EUAs rather than JI mechanisms. Renewable energy sector is a loser in this context. Usually renewable energy project developers and managers of big combustion installations are not the same people, especially when wind farm projects and small biomass, or small hydro installations are concerned. Yet ERUs granted under JI mechanism to RES projects would have to be allocated from a set-aside, deducted from sectoral allocation to the combustion installation. Only those JI projects which would be approved by the host governments by end of 2006 would qualify for allocation from such a JI reserve in the National Allocation Plan. Unless the EU Commission changes its mind (which is highly unlikely), or EU member countries veto double counting, this will seriously undermine development of small RES projects. With the EU ETS covering the majority of industrial CO2 emissions, and double counting guidelines limiting the number of renewable energy projects, CO2 emissions abatement potential in the new EU member countries becomes insignificant as JI potential. Initial identification and cost estimates for the technologies that offer the combination of the greatest tonnage reductions and the lowest costs to be used to develop future supply curves for each of non-CO2 greenhouse gases was partly based on GAINS model, developed by researchers working in the Transboundary Air Pollution program of the International Institute for Applied Systems Analysis (IIASA). However, in order to be applicable to the JI project potential, the results of this assessment have to be considered further in the light of the formal requirements associated with Joint Implementation mechanism. 20 Production of iron ore and steel, cement, lime, glass, ceramics and pulp and paper


GAINS Version 1:0 offers methodology to assess, for any exogenously supplied projection of future economic activities, the resulting emissions of greenhouse gases and conventional air pollutants, the technical potential for emission controls and the costs of such measures, as well as the interactions between the emission controls of various pollutants.21 It assesses the options for reducing all six greenhouse gases from all possible source categories, including agriculture. It quantifies for 43 countries/regions in Europe country-specific application potentials of the various options in the different sectors of the economy, and estimates the societal resource costs of these measures. Mitigation potentials are estimated in relation to an exogenous baseline projection that is considered to reflect current planning. The purpose of GAINS model is also to indicate a number of synergistic options which enable simultaneous abatement of GHG and other traditional air pollutants. The cost-efficiency is derived from simultaneous improvements for both traditional air pollutants and climate change agents. It is important to indicate that GAINS model calculates potential for emission controls relative to the baseline scenario that was used for the CAFE programme of the EU, although the authors do not say so in the IIASA reports quoted here.22 In order to assess the effectiveness of current air quality policies, CAFE constructed a baseline scenario (also called the "current legislation" scenario - CLE) showing the expected emission levels up to 2020. The main tool used for the scenario construction and analysis was the RAINS computer model for integrated assessment. In addition, other computer models were employed to provide information on trends in the energy, transport and agriculture sectors. GAINS model has been created on the basis of the RAINS model. The baseline energy scenario provides a consistent EU-wide view of energy developments, including certain measures needed for implementation of the Kyoto Protocol. It results in a reduction in CO2 emissions of 7.4 per cent by 2010 and 3.6 per cent by 2020, as compared to the base year 1990. The usefulness and applicability to the Kyoto mechanisms of technologies recommended under the GAINS model should be considered in the light of the Joint Implementation criteria: Joint Implementation projects, in order to be recognised as such, can apply only approved methodologies23, and this is true also in the case of non-CO2 greenhouse gases destruction. Without considering such aspects as: the emission reduction integrity, the determination of baseline, monitoring procedure, project leakage, other additional GHG emissions, possible increases in other negative environmental impacts, and data uncertainty, in other words, without looking at a technology application from the point of view of a JI developer, it is difficult to confirm that a technology commendable in the light of the criteria proposed by GAINS model could be applicable in the context of the JI mechanism. 21 The GAINS Model for Greenhouse Gases: Version 1:0, Nitrous Oxide (N2O), IIASA Interim Report IR-05-55, p.6 22 The Clean Air For Europe (CAFE) programme was launched by the Commission in 2001, with the aim of reviewing current air quality policies and assessing progress towards the long-term objectives of the 6th Environmental Action Programme. 23 Methodologies approved by CDM Executive Board apply also to JI projects


There are also other constraints which question suitability of some technologies advocated by GAINS model, such as environmental effectiveness measured by simultaneous mitigation of other non-GHG air pollutants. For a project developer, simultaneous reduction of some air pollutants which are under mandatory abatement may become an obstacle to proving an additionality of a JI project, which may then cease to be regarded as a JI project, and as it would then bring no revenue, therefore it would be abandoned. For instance, if climate change measures that aim at reduction of N2O will simultaneously reduce NOx, the project may not be recognised as additional, and as there are no regulatory requirements forcing an installation owner to spend money on N2O abatement, no proceeds from such abatement would mean that the project would not be implemented. GAINS model departs from JI criteria in yet another way. For a JI project, another measure of cost efficiency is a ratio between the cost of project implementation (and then later operational costs during the project’s lifetime) and the proceeds from the sale of ERUs generated by the project. Size of the emission reductions from one project is important in this context. Cost-efficiency of JI projects is considered without discounting costs of additional abatement of non-GHG air pollutants, as the additional abatement of those pollutants does not increase financial benefits to the project developer (they come only from the sale of ERU’s). According to additional criteria proposed for evaluation of JI projects, these projects should merely not lead to increases in other local/regional environmental quality indicators at the expense of achieving reductions in GHG emissions, and if proposed JI projects might lead to increases in other negative environmental impacts (eg. air pollution, waste water discharges, or waste disposal), appropriate mitigation measures should be incorporated into the project. However, the broad principles of the cost evaluation in the GAINS model may be considered indicative also for JI project potential, albeit with the reservations mentioned above. As stipulated by the IIASA authors, the GAINS model attempts to quantify the values to society of the resources diverted to reduce emissions in Europe, approximated by estimating costs at the production level rather than at the level of consumer prices. A central assumption in the GAINS cost calculation is the existence of a free market for abatement equipment throughout Europe which means that it is accessible to all countries at the same conditions. The calculation takes into account several country-specific parameters that characterise the situation in a given country. Some of these parameters are considered common to all countries. These include technology-specific data, such as removal efficiencies, unit investment costs, fixed operating and maintenance costs. Parameters used for calculating variable cost components such as the extra demand for labour, energy, and materials are also considered common to all countries. The expenditures for emission controls are differentiated into: • investments, • fixed operating costs, • variable operating costs, and • transaction costs.


GAINS calculates annual costs per unit of activity level. Subsequently, these costs are expressed per metric ton of pollutant abated.24 For a JI project developer, the cost estimate of technology used in GHG abatement is offset against project implementation costs. In practice only in the case of N2O reduction from chemical processes, and in some F-gases reduction projects, can the JI proceeds exceed the cost of technology used in abatement. In other cases, JI proceeds help to finance project implementation but are not sufficient to cover full costs. Taking a decision on whether to implement a JI project which brings, after all, a voluntary emission reduction25, a project proponent would only take into consideration whether the project would be beneficial in terms of increasing a return on investment, or even bringing profit. Project developer will consider cost effectiveness of the project for project financing rather than its value for the society or environment. This said, if a project is too profitable and could be considered as commercially justified for the profits that would come with its implementation, especially, if several project developers would become interested in implementing it for purely financial reasons, the project would cease to be considered as additional, and would become business-as-usual. As such, it would no longer qualify as a JI project. In this sense, the applicability of results obtained through the use of GAINS model for determination of potential for JI projects with the optimal cost-efficiency is arguable. The GAINS model has been used by IIASA authors to assess abatement potential of all greenhouse gases. However, as mentioned earlier, this report will consider only abatement potential of N2O and CH4 defined by GAINS model, and the usefulness of the GAINS model findings for the assessment of JI potential in new EU member countries, taking Poland as an example. F-gases emissions abatement potential discussed by GAINS model will be left out of our consideration. The majority of F-gases emission in Poland comes from dispersed sources and as such, it does not lend itself easily to abatement which would qualify for financing under Joint Implementation mechanism. Moreover, contribution of F-gases to the total national GHG emissions in Poland is low. Contribution of SF6 is really insignificant. In 2003 (the latest available national GHG inventory), SF6 emissions amounted to approximately 0.01% of the total GHG emissions. Leakage from gas insulation systems used in aerial substations of high voltage transmission lines is the main source of SF6 emissions, while really small amounts are emitted during the production of soundproof windows. The emission of PFCs is also small. In 2003 it amounted to 0.07 % of the total GHG emission, or 0.26 mtCO2e. Aluminium production is its main source. The total emission of HFCs in 2003 was 1.66 mtCO2e, or 0.46 % of the total GHG

24 Country-specific parameters characterise the type of capacity operated in a given country and its operation regime. They include the average size of installations in a given sector, operating hours, annual fuel consumption and mileage for vehicles. In addition, the prices for labour, electricity, fuel and other materials as well as cost of waste disposal also belong to this category. Transaction costs are country-specific since they describe costs of diverse activities such as training or even information distribution required for implementation of an abatement option. All costs in GAINS are expressed in constant € (in prices of the year 2000. )Idem, p.12-13 25 Not to be confused with Voluntary Offsets, or emission reductions for carbon branding purposes, which use VERs (Voluntary Emission Reductions). Such projects, usually much smaller than JI projects, are also subject to verification procedures but are not one of the Kyoto mechanisms.


emissions. Of all the F-gases, this is the only emission growing significantly, compared to base year (1995 for the F-gases), due to the increased popularity of air conditioning and refrigeration use. Abatement of F-gases would involve, for example, destruction of HFCs from domestic appliances, such as fridges (at the end of their lifetime), or air conditioning. Needless to say, such projects would be extremely difficult to monitor. Moreover, according to IIASA authors, uncertainties in the estimates of F-gasses emissions (and hence control costs) are large due to uncertainties in emission factors, the future penetration of technologies and abatement measures as well as lack of data on activities in a number of countries.26 Projects such as, for example, a CDM project of HFC 23 reduction by thermal oxidation at a refrigerant manufacturing facility planned at Rajasthan, India, are yet rare.27 To date there are no known JI projects implementing abatement of these gases. These circumstances result in leaving F-gases outside our consideration as JI project potential in the period 2008-2012. Taking into consideration all of the above mentioned arguments, this report will consider only N2O and CH4 abatement technologies potential defined by GAINS model and its applicability under Joint Implementation mechanism. JI and CDM projects have been implemented in connection with abatement of these two greenhouse gasses, more such projects are planned, and appropriate methodologies, as well as general cost estimates for these projects exist. The aim of the report is to briefly present all the abatement measures proposed by the GAINS model for the two greenhouse gases, then to discuss only those which may be recognised as legitimate abatement measures under Joint Implementation mechanisms, and to compare their cost effectiveness on the example of JI projects feasible in Poland with the costs estimates offered by the GAINS model. 2. N2O reduction technologies and JI potential: For N2O reduction, the sectors mentioned by IIASA authors offering abatement potential include: chemical industry agriculture, animal manure, other soil emissions, municipal wastewater treatment, combustion in industry and power plants, transport, N2O use.28 In Poland, the main N2O emission sources and their share in the national GHG emission in 2003 were as follows: agricultural soils – 44.2%, manure management – 22.4%, industrial processes – 18.4 %, fuel combustion – 9.7 %, and wastewater treatment – 3.3%29 Some N2O sources, though significant (soil emissions) do not lend themselves to abatement control, while others (N2O use, sewage) are also insignificant or relatively less significant as emission sources. In Europe, emissions from soils are generally considered the most important source of N2O, followed by industrial process emissions. The fraction of nitrogen released in the form of N2O from the soil depends on a large number of variables. These include soil properties30, the chemical form and pathway of nitrogen input into soil, and the further fate of compounds (i.e., leaching). The uncertainty of estimating baseline and project line in the case of 26 The GAINS Model for Greenhouse Gases: Version 1:0, HFC, PFC and SF6, IIASA Interim Report IR-05-56, p.3 27 Methodology AM0001/Version 3: Sectoral Scope 11: “Fugitive emissions from production and consumption of halocarbons and sulphur hexafluoride”. 28 See 8 categories of emission sources for N2O used for GAINS model, The GAINS Model for Greenhouse Gases: Version 1:0, Nitrous Oxide (N2O), IIASA Interim Report IR-05-55, p.16 29 Poland National Inventory Report to the UNFCCC 2003 30 Temperature, humidity, density, pore size, sand content, clay content, carbon content, nitrogen content, etc.


abatement of N2O emissions from the soil is obvious. Thus not only projects suitable in the context of the Kyoto mechanisms, but any abatement projects involving reductions of soil emissions would be difficult to implement and monitor. For that reason also GAINS model does not provide an estimate of N2O abatement costs from that source, albeit it is significant. N2O reduction potential in the GAINS model: In the GAINS model, options that specifically address N2O emissions were identified in five sectors: • selective catalytic reduction in industrial plants, • process modification in fluidized bed combustion, • optimization of sewage treatment, • replacing use of N2O as anaesthetics, and • optimised application of fertilizer (in agriculture) . An analysis given below undertakes to consider these N2O abatement opportunities as possible Joint Implementation projects: Reduction of N2O from agricultural processes and JI potential: As at present no approved CDM methodologies exist for abatement of N2O from agricultural processes, abatement potential in Poland of N2O emissions from agriculture cannot be considered in the context of its applicability in determination of potential for JI projects. Moreover, the implementation of the Nitrates Directive introduces a regulatory instrument which goes against the additionality concept. The Nitrates Directive (91/676/EC) was adopted in 1991 as an environmental measure designed to reduce water pollution by nitrate from agricultural sources and to prevent such pollution occurring in the future. Polish Law on Environment protection and a law of 26 July 2000 on fertilizers and land fertilisation implement the Directive as part of the acquis communaire. As any regulatory measures imposing emission reductions preclude additionality, such projects would not be recognised as JI projects. Reduction of N2O from municipal wastewater treatment and JI potential: Similar conclusion can be drawn in relation to abatement of N2O emissions from municipal wastewater treatment through optimisation of sewage treatment. The technology of such abatement has not been approved as a CDM/JI methodology and it will be difficult to generate a significant volume of such N2O reduction at a level of a sewage treatment plant to consider such an abatement project as a JI project. Moreover, according to GAINS model, N2O abatement from sewage treatment could be achieved at no extra cost, so even, if there was a sufficient abatement potential to consider such a project, it would not be considered additional (the proceeds from the sale of ERU’s would not be necessary to project finance). The level of N2O emissions from wastewater treatment in Poland amounts to 3.3% of the total N2O emissions. In 2003, it was equal to 2560 tonnes of N2O, or 757 760 tCO2e nationwide, and it remained stable compared to the previous reporting year. The dispersed character of N2O emissions from wastewater treatment does not allow to consider these emissions as a target for a potential JI project. According to GAINS model, the abatement potential from this source in Poland by 2010 equals 770 tN2O (77 kt), or 227.920 tCO2e. Normally, JI projects start from projected annual emission reduction on the level of about 20.000 tCO2e annually, and here we are speaking about the national level reductions, so the size of potential projects would be too insignificant, even, if


additionality were not a problem. Therefore abatement potential from wastewater treatment in the case of JI potential is nonexistent. Replacing use of N2O as anaesthetics and JI potential: Abatement from other sources emitting N2O, considered by GAINS model, has to be rejected on the basis of excessive costs and uncertainty, as well as unrecognised interaction with other air pollutants.31 In the case of replacing use of N2O as anaesthetics with Xenon is so high that it could never be considered as a JI project, and any abatement measures, acc. to the GAINS model, could only be considered on medical grounds rather than environment protection. The amount of N2O released from these sources in Poland is not reported. N2O abatement from transport and JI potential: N2O abatement from transport would be difficult to implement as a JI project, albeit for different reasons than those in the case of replacing N2O as anaesthetics: although reduction measures are known and results can be quantified, costs of monitoring would be prohibitive, with uncertainty of measurement depending on the level of the use of cars. Reported N2O emissions from transport in Poland amounted to 2030 tonnes in 2003, or to approximately 600 880 tonnes of CO2e annually on the national level. N2O abatement and JI project opportunities: Of the N2O abatement measures proposed by the GAINS model, this leaves for our consideration as a potential for Joint Implementation projects only two measures: selective catalytic reduction in industrial plants and process modification in fluidized bed combustion. The abatement potential of both have been discussed below in the context of their applicability to the N2O reduction JI projects in Poland. N2O abatement potential from nitric acid production in Poland: The main (and the only significant) abatement potential for N2O emissions can be identified in chemical industry. In Poland, N2O emissions come from the production of nitric acid, as adipic acid is not manufactured by Polish plants. The projected abatement potential for N2O from nitric acid production until 2010 was estimated at the level of 6120 tN2O, or 1.811.520 tCO2e. This is a too conservative estimate, as even one of the potential JI projects, if implemented, would bring twice as much reduction in the Kyoto period (2008-2012). Although, as explained later on, 100 % N2O reduction under JI is not possible from all nitric acid plants, as abatement would cease to be additional and instead would become business as usual, we can assume that at least 2 (maybe 3) such projects could be implemented without raising the issue of additionality in Poland. For N2O abatement from nitric acid production through the installation of a catalyst, the costs were estimated using GAINS model as € 130 /t N2O, at emission factor of 1.14 ktN2O/Mt at removal efficiency of 80 %. This does not give the true picture of the value of N2O abatement project for the installation owner, if a JI mechanism is considered, as in reality implementation of a JI project abating N2O from nitric acid production would be more profitable. 31 See, IIASA (N2O), p.4


N2O reduction projects can be a very good deal as JI projects. Typically such a project may only cost € 2 million to implement but could easily generate cash proceeds from the sale of ERUs of well over € 10 million. However, there are a lot of technical, financial and political issues which mean that the project can go wrong. Currently in most countries N2O emissions from industrial processes are unregulated - France is the only EU country at present mandating N2O emission standards - and therefore the N2O reduction project is not business as usual, so in theory it can become a JI project. Therefore from a regulatory point of view, N2O abatement projects in other EU countries (but not in France) are additional. However, there is a range of (relatively new) technologies available, and some of these bring such economic benefits (eg. lower energy use, lower ammonium consumption) that the N2O project would make economic sense without any JI money. This eliminates additionality and wipes out any possible JI proceeds. Also these N2O abatement technologies which simultaneously reduce non-GHG gases under mandatory abatement, such as NOx, may be arguably considered as not additional. Appropriate CDM methodologies which could be considered, depending on technological conditions in each of the plants include the following methodologies: NM0111; NM0143; NM0164. Of these, only NM0111 has been so far approved by the CDM Methodology Panel, while the remaining ones are still under consideration. The secondary technologies: NM0143 and NM0164 do not require additional energy consumption for the destruction facility to operate effectively. This is because the catalysts are fitted in the reactor where temperatures are well above the minimum required for the decomposition of N2O. In the case of the tertiary technology NM0111, it is required that the gas be heated from the normal stack temperature of approx. 200 ºC to over 400 ºC (in some cases: to 300 ºC). This means additional combustion of hydrocarbon fuels and additional emission of CO2, which has to be deducted from the emission reductions achieved through destruction of N2O. However, when considering technology viability in the JI project, it is important to remember that there may be technological reasons for preferring one N2O reduction technology over another, and the assessment of abatement potential through JI projects, based purely on the costs estimate of technology application may be purely conjectural. N2O emissions in Poland in 2003 (latest publicly available National Communication to UNFCCC) amounted to 77,210 tonnes, of which 14,200 tonnes of N2O were emitted from industrial processes (chemical industry). This was equal to emissions of 4,2 tCO2e from chemical production. Not all of this volume can be abated. However, there are four major fertilizer and chemical manufacturers with significant volume of N2O emissions which are considering N2O abatement as a JI potential: Kędzierzyn Nitric Acid Plant (ZAK), Tarnów Nitric Acid Plant (ZAT), Anwil in Włocławek and Puławy Nitric Acid Plant (ZAP). The number of ERUs from N2O abatement from nitric acid production in Poland is given in a table below: Plant tN2O/y tCO2e/y Abatement potential/y

(70 – 85 %) ERUs 2008 – 2012 (70 – 85 % of emission reduction)*

Anwil 2558 757 168 530 000 – 643 600 2 650 000 – 3 218 000


ZAK 3659 1 083 064 758 144 – 920 604 3 790 720 – 4 603 000 ZAT 2000 592 000 414 400 – 503 200 2 072 000 – 2 516 000 ZAP 6000 1 776 000 1 243 200 - 1 509 600 6 216 000 - 7 548 000 Total 14 217 4 208 232 2 945 762.4 - 3 576 997.2 14 728 812 – 17 884 986 * estimate The implementation costs of N2O abatement from nitric acid production through installation of a N2O catalyst N2O are comparable, and amount to the cost of monitoring equipment (c. € 100 000) plus cost of commissioning and installing the catalyst, estimated at € 1 to 3 million). Depending on the actual price of the ERUs obtained from the JI transaction, these costs are amply offset by revenues from the sale of carbon credits. It is enough to say that one tonne of N2O reduced would bring between € 2072 to € 3256 in revenue, at the prices of € 7 to € 11 per 1 ERU. This said, one needs to stress again that in the case when all the N2O emitters implemented abatement projects, these would become business-as-usual, and only two or three first N2O reduction projects could be recognised as JI projects. FBC related N2O abatement and JI potential: In Poland, fuel combustion (including transport) in 2003 resulted in 7490 tonnes of annual N2O emission or 2 217 040 tCO2e nationwide.32 Of these emissions, only approximately 2580 tN2O, or 763 680 tCO2e was emitted by the energy industry.33 Therefore the IIASA predictions of N2O abatement potential from combustion activities seem inflated. From power industry alone, the abatement potential is envisaged at 12.750 tN2O until 2010. It appears as well that there are technological constraints which cannot be overcome before that deadline: GAINS model proposes a method of N2O abatement from energy industry through new technologies associated with Fluidized bed combustion (FBC), which are recognised by IIASA authors as a convenient option to reduce NOx and particulate matter (PM) emissions. Without the introduction of these specific abatement measures, introduction of fluidized bed combustion would lead to an associated increase in N2O emissions: the specific combustion conditions of FBC (long residence time, lower combustion temperature) favour N2O formation. The most promising options to prevent such increase are the use of an afterburner to augment the temperature in the flue gas to destroy N2O, and a reversed air staging to optimize oxygen availability. Figures for costs, removal efficiencies and emission factors are similar. Both options have only been demonstrated at small scale and pilot plants. They are not yet used in practice, and will not be used, according to the authors of GAINS model, before 2010. However, IIASA authors predict a strong increase of the application of FBC for Europe, among others in connection with the implementation of the LPC Directive. At present no CDM/JI methodology justifies implementation of FBC modification as a N2O reduction JI project. Moreover, since retrofitting of existing installations is not possible, introduction is hampered by the natural turnover rate of the fluidized bed boilers (assuming that they have a typical technical life time of 30 years). Therefore, at maximum feasible reduction, even the GAINS model estimates that in 2020 no more than 40 percent and in 2030 no more than 80 percent of all installations in Europe may have modified combustion equipment installed. At first sight such project would be profitable as a JI project, due to cost of modification in FBC 32 Poland NIR 2003, p.25 33 Poland NIR 2003, p.25


estimated at present by IIASA authors at € 1000/t N2O, at removal efficiency of 80 % and controlled emission factor of 0.016 kt of N2O/PJ. A reduction of one tonne of N2O, considering its GWP potential of 296, would bring around € 2072 at current fixed prices, slightly more at currently offered mixed prices (i.e. prices linked to floor or to ceiling, plus a fraction indexed to the EU ETS prices). However, considering natural turnover and replacement rate of installed capacity in Poland, FBC will not make headway in this country before end of the first Kyoto commitment period which is the lifetime of JI projects. Since retrofitting of existing installations is not possible, introduction is hampered by the natural turnover rate of the boilers, assuming that they have a typical technical lifetime of 30 years. In the next three to five years, 300 to 400 MW of installed capacity will have to be retrofitted due to the end of their lifetime, but save for Bełchatów II, no new power plants/installations are planned in 2008 – 2012. FBC has not been popular in Poland, with the majority of power plants using pulverised fuel fired boilers installed in the 70’s. Lignite fired plants (BOT) use also such boilers, and the new Bełchatów II plant will have installed one of this type, using lignite. Power plants will nevertheless have to comply with the LPC Directive, and from 2012 at the latest they will have to install NOx catalysts or use other methods of NOx reduction. However, within the next 10 to 15 years Polish power plants will continue to use mainly pulverised fuel boilers, and only from 2020 onwards a reasonable demand for fluidized bed boilers (and associated N2O reduction technologies) can be expected to emerge, especially, if N2O abatement will become obligatory under the law. Given these constraints, N2O abatement from modified Fluidized Bed Combustion cannot be considered as a technology suitable in the context of Joint Implementation potential. 3. CH4 reduction technologies and JI potential Methane emissions arise from natural (e.g., wetlands) and anthropogenic sources (e.g., agriculture, landfills, and natural gas emissions). Of the estimated global emissions of 600 Mt in 2000, slightly over half originate from anthropogenic sources.34 According to IIASA authors, full application of the presently available emission control measures could achieve an additional decline in European CH4 emissions by 24,000 kt per year. About 70 % of this potential could be attained at a cost of less than two billion €/year or 50 €/t CO2–equivalent, while the further 7,000 kt CH4/year would require costs of 12 billion €/year.35 At such costs, considering that at present one ERU, equivalent to 1 tonne of CO2 brings between € 7 to € 11, this abatement potential could not be realised through the Joint Implementation mechanism. In Europe, the highest CH4 emissions originate from the production and distribution of natural gas. All over Europe production and distribution of gas contribute approximately one third to total emissions and come as the second largest source of methane emissions. The second largest source of CH4 emissions relates to agricultural activities. In the EU-25, agriculture is estimated 34 The GAINS Model for Greenhouse Gases: Version 1:0, Methane (CH4), IIASA Interim Report IR-05-54, p. 14 35 IIASA (CH4), p.2


to contribute 43 percent to total CH4 emissions. In the EU-25, the largest contribution of methane to GHG emissions comes from enteric fermentation, then waste disposal, coal mining and natural gas distribution.36 In Poland, structure of methane emissions is slightly different from this picture. While all of the methane emissions in 2003 amounted to 1,8 million tonnes (of CH4) or 37,7 million tonnes of CO2e, methane emissions in Poland come mainly from the following sources: fugitive emissions from fuels (44.3%), waste (27.5 %) and agriculture (24.6%).37 Fugitive emissions from fuels: Methane emissions registered by NIR under fugitive emissions from fuels category include emissions of methane from coal mining, emissions stemming from losses of natural gas during its transport and final use, and those occurring during oil transportation, refining and storage. Approximately 44% of CH4 emissions in the fugitive emissions from fuels category originate in Poland from coal mining related activities. The formation of coal produces CH4 that is released to the atmosphere when coal is mined, where CH4 releases are higher for underground mining. In addition, there are emissions from post-mining activities such as coal processing, transportation and utilization.38 Only 29 % of methane emissions in Poland come from losses of natural gas during transportation and use which in Poland has a lower share in total emissions than in Europe as a whole. Consequently, abatement potential in this area in Poland is lower. Due to the structure of primary fuel in Poland (mainly hard coal), and the importance of mining, abatement potential of methane from coal mining related activities continues to be important, despite constant decrease in methane emissions from that source, related to the decrease in coal mining and closing of mines in Poland. Methane emissions from waste: Methane from municipal solid waste is generated when biodegradable matter is anaerobically digested at a landfill. Biodegradable waste consists of paper and organic waste, where the latter includes food, garden and other organic matter. Methane is also generated from liquid waste during wastewater treatment. Under anaerobic conditions the handling of wastewater streams with high organic content can cause large amounts of CH4 emissions. Anaerobic digestion occurs primarily when large amounts of wastewater are collected and handled in an anaerobic environment. Approximately 70% of methane emissions from waste in Poland are emitted by landfill sites which offer considerable abatement potential.39 Methane emissions from agriculture: Approximately 90 % of methane emissions from agriculture in Poland comes from enteric fermentation.40 Methane emissions from enteric fermentation appear during the digestive process of herbivores and from manure management under anaerobic conditions. Methane emissions also

36 IIASA (CH4), p. 14, p. 78 37 Poland NIR 2003, p. 22 38 Poland NIR 2003, p. 23 39 Poland NIR 2003, p 22nn 40 Poland NIR 2003, p. 22


originate from (open) burning of agricultural waste, and from biomass burning for energy purposes. As with N2O abatement, reduction of methane from agriculture does not lend itself easily to abatement measures which could be properly assessed and monitored. A wide range of recognised measures that could reduce CH4 emissions from enteric fermentation is aggregated under GAINS Version 1.0 into five groups of measures: autonomous increases in agricultural productivity, increased feed intake, changes to more non-SC in diet, replacement of roughage for concentrate, and use of propionate precursors. None of these measures offers itself as a viable JI project due to either uncertainty of monitoring methodology or to high costs, etc. The majority of arguments viable in the context of N2O abatement in agriculture holds true also in the case of methane emissions. A potential for reduction of methane emissions under Joint Implementation mechanism in Poland exists, and it could be realised in the following sectors: Landfill gas recovery Coal bed methane recovery In addition, following the estimates produced by IIASA authors under the GAINS model, the report considers a JI potential of: Methane capture from oil & gas production and oil refining and methane loss reduction from gas transmission and distribution Manure management – liquid waste (biogas use) Methane emissions from landfills and JI potential: Methane emissions from landfills can be controlled by capping the landfill, recovering the gas, and flaring or utilizing it as an energy source. Capping of landfills is assumed to be a prerequisite for landfill gas recovery. In Poland, 70 % of methane emissions from waste category under the IPPC classification can be associated with landfill related methane emissions.41 In 2003, landfill sites emitted approximately 393,000 tCH4 or 8,25 mtCO2e.42 In Poland there are 700 officially operating landfills, with more planned. For many towns, the landfills are already beyond their official capacities. Almost all municipal waste goes to landfills without separation. The greatest obstacle in implementing landfill gas extraction and utilization projects is connected with relatively small size of the landfills, especially older ones, and the non-compact deposition of waste. Typically a landfill suitable for implementing a methane capture project should receive between 40,000 and 50,000 tonnes of waste annually, with a suitable level of organic matter. Additionality of methane capture from landfills is an important issue and has been discussed below: Additionality of landfill methane recovery projects in Poland: 41 Poland NIR 2003, p.22 42 Poland NIR 2003, p 22. 1 m3 of CH4 equals 721 grammes of CH4.


The Polish Ministry of the Environment has approved the Landfill Directive (EULFD) in 2001. Poland got transitional period for implementing Article 14b (concerning existing landfill sites) until 2012 in order to take a definite decision on whether operations may continue on the basis on Directive 1999/31/EC. After year 2012 every operating landfill shall comply with the requirements of the Directive and if not, the landfill shall be closed down according to closure and after-care procedures. It is predicted that by 2012 it will be necessary to close down 361 waste storage facilities and to modernize further 663 ones. Poland undertook a national environmental planning, but, as is the case with implementation, a source of problems with obtaining the financial investment needed is obvious. The development of the environmental programme requires very substantial investments, and given the financial resources Poland has available, these will by far not be enough. It must be recognized, that the tariffs for waste collection and processing are far below the average EU-levels and do not cover the costs for waste management according to EU standards. The transition period for the implementation of the environmental acquis given to Poland is just a small proportion of what was originally asked for. This in turn puts more pressure on the Polish Government in revising its schedule for transposition and implementation, further strengthening its administrative capacity and ultimately having to amend its initial financial assessments. Nevertheless, much technical and financial assistance will still be needed. EU support will meet only a small proportion of the total needs and will primarily focus on the construction of new landfills. Finances for the closure and/or rehabilitation of existing landfills and/or landfills that are scheduled to be closed down, are not available in Poland. It can therefore be concluded, that private financial resources will play a dominant role in the implementation of landfill gas collection and utilisation. It is evident, that carbon financing will therefore be an essential factor for achieving emission reduction. The recovered gas can be flared or utilized as an energy source. Costs of installing a typical boiler for gas utilization in Poland would be comparable to that in other EU countries. However, costs of energy are lower, and therefore cost effectiveness for such an installation would be lower, although detailed calculations are needed to come up with numbers. To date, the objective of the planned landfill gas recovery projects applying for co-financing under Joint Implementation mechanism in Poland is to collect and destroy landfill gas extracted at these sites.43 So far, two such landfill recovery JI projects have received LoAs in Poland, with one more granted a LoE and a PDD currently being developed. These projects have not yet been implemented. Moreover, neither in Konin landfill, nor in smaller bundled landfill gas recovery projects in Mazury and Silesia energy generation was planned and methane will initially be destroyed by flaring. This is justified on the basis of comparatively large costs of installing electricity generation equipment, where the size of landfill sites and amount of methane generated would not justify at present high costs of investment in power generation and grid connection. Landfill gas projects are a novelty in Poland, there is no local technology available and few experts in the field apply knowledge in actual projects. Landfill gas extraction and flaring can be implemented as a JI project using a CDM approved methodology ACM0001, called „Consolidated baseline methodology for landfill gas project 43 See, PDD of the Portfolio of Landfill Projects in Poland, prepared by EcoSecurities in February 2006


activities”. ACM0001 was developed as a way to unify approved baseline methodologies applicable to different situations where landfill gas destruction projects are proposed. One of these situations is where the captured gas is flared or used to produce energy, and emission reductions are claimed for avoiding or displacing energy generation from other sources, for example, if energy generation turbines were installed on a landfill site, and energy produced displaced energy from conventional sources used before project’s implementation by project developer. For projects proposed so far in Poland, this methodology was indicated in connection with the proposed method of methane disposal. However, with no electricity generation, a viable CDM methodology would be rather AM0011 „ Landfill gas recovery with electricity generation and no capture or destruction of methane in the baseline scenario”.44 The methodology is viable where the existing situation is no landfill gas recovery and where the project only includes emission reductions through capture and combustion of LFG. Since none of the currently planned JI projects involving methane capture would include installation of energy generation equipment, it is difficult to quote precise cost estimates from the local market. Following IIASA cost estimates under GAINS model, given for the British installation, a boiler with a capacity to burn 3.01 million m3 CH4/year or 2,139 t CH4/year would be enough for the typical landfill generating 1,440 t CH4/year. The lifetime of the equipment is assumed to be 20 years. Investments amount to 90,800 € or 3 €/t CH4 when annualized. Operating and maintenance cost are estimated at 10,400 €/year or 5 €/t CH4. Eighty percent of the recovered gas can be utilized as energy. A lower and more variable quality of the recovered gas reduces its value in comparison with pure natural gas. Therefore the value of recovered CH4 is assumed to correspond to 50 percent of the natural gas price.45 Coal mine methane recovery and JI potential: Methane emissions from coal mines can be reduced by upgrading the gas recovery of existing mines or by installing more efficient CH4 recovery in new mines. The recovered gas can then be utilized for energy purposes. There are three types of coal mine gas: Coal bed methane (CBM) – a coal mine gas from unmined coal seams/ CBM typically consists of over 90 % methane and can be harvested independently from coal mining in some locations. The gas composition is normally stable, and the gas can be fed directly into the natural gas network. CBM is sometimes referred to as Virgin Coal Bed methane, or VCBM, as it is derived from virgin seams. Coal mine methane (CMM) – coal mine released as a result of mining activities. It is a methane/air mixture released during coal mining and must be ventilated for safety reasons. CMM typically has an oxygen content of 5 – 12 % by volume. The methane content ranges from 25% to 60%. However, methane/air proportion can change rapidly, complicating its use in gas engines. Abandoned mine methane (AMM) – coal mine gas from abandoned mines. Main technology options for use of extracted CMM/CBM include: Flaring,

44 This methodology was proposed, eg. for CDM project: Ladfill gas Capture and Flaring at Chisinau Landfill, Moldova, 2004 (still at PDD stage) 45 IIASA (CH4), p.43


Gas supply, Power generation, Industrial feedstock (chemical industry). These options have the following gains: Flaring – GWP gain only. Flaring is used if gas quality is too low for power production or gas supply, or if supply exceeds demand and storage capacity/ Gas supply – GWP gain plus displacement of GHG emission due to alternative energy use. Power generation – GWP gain plus displacement due to alternative energy use. Industrial feedstock (chemical industry) – production of methanol, urea, synthesis gas, fluoride. It is assumed that it is technically possible to extend the recovery and utilization rate to on average 70 percent of total emissions from coal mines46 In 2003, Polish mines emitted approximately 564,000 tCH4, or 11,8 million of CO2e. So, potentially, 70 % of these emissions could generate 8,29 million ERUs, or between 58 to 91 million €/year ( or 290 to 456 million in the first Kyoto period), if abated through JI projects. This estimate is, as usual, not applicable to JI potential because of additionality concerns. If all Polish coal mines wanted to implement JI projects, additionality would disappear. The concept of additionality is so complicated, that it would be difficult to predict, when could it become questioned, and this consideration is largely outside the scope of this report. However, it has to be kept in mind constantly, when JI project potential is considered, and 100 % of abatement potential for any of the greenhouse gases could never be considered as equal to JI potential. Geological conditions are also crucial for determining abatement potential of coalbed methane. Having said that, CMM or CBM projects should be able to demonstrate additionality under most of the circumstances, especially where options are combined to achieve maximum destruction while optimising energy utilisation. JI project can make a big difference for the likelihood of the gas drainage and utilization scheme continuing to operate. Without a JI incentive it would be easy to continue venting as previously whenever anytthing goes wrong with the utilization of equipment or the gas supply. JI mechanism would make it possible to install flares in addition to gas engines to combust any excess methne that would otherwise be vented. It may also make additional funds available to invest in increased efficiency of gas drainage, improving safety. In Poland, methane can be recovered mainly from the mines located in Upper Silesia, from the mines owned by Katowicki Holding Węglowy (KHW).47 Several coal mines contemplate projects involving installation of CHP generation equipment using methane generated from coal mining. The costs of such project implementation would vary, depending on whether a modernisation of existing methane capture stations is necessary, whether additional pipelines have to be installed, or not, and depending on the cost of installation of a CHP generation unit. According to the GAINS estimate, the cost of abatement would range between – €107/tCH4 to €112/t CH4. Within that price range and GWP of methane equal 21, 1 tonne of CH4 reduced

46 IIASA (CH4), p.49 47 Jastrzębska Spółka Węglowa owns 2 mines which could potentially implement JI projects, while methane emissions from Bogdanka Coal Mine near Lublin are to low to justify the expense of a CMM project. Existing projects include: a CHP generation unit at coal mine Krupiński, installed capacity: 2.7 MWe, 3.1 MWh, and a cooling unit at coal mine Pniówek: installed capacity of 5.7 MW.


from coal mining would bring €147 to € 231 (assumed price of € 7 to € 11 per 1 ERU)48, so any of the projects involving upgraded recovery and utilization of coalbed methane from current level to 70% would be viable as a JI project. These estimates can be confirmed on real project ideas. For example, a planned installation of a 5 MW CHP unit, combined with construction of 1.8 km of local pipeline, and modernisation of the existing methane capture station in one of the KHW mines would cost € 4.23 million (PLN 16.1 million).49 The project would generate 129 595 tonnes of CO2e annually or 647 975 tCO2e in 2008-2012, bringing estimated revenue from a JI transaction in the range of € 4,5 million to € 7,1 million. So, according to a preliminary estimate of its cost-effectiveness, it should be possible to finance the project fully from JI proceeds. Existing CDM methodologies: Five methodologies have so far been submitted, all related to CDM projects in China. All of them are still under consideration, as the Methodology Panel is continuing to debate the merits of CMM and CBM. All the methodologies determine baseline and project emissions in roughly the same manner but differ in applicability and additionality arguments. 50 The Methodology Panel has proposed a consolidated methodology for CMM and CBM projects, entitled „ Consolidated baseline methodology for coal bed methane and coal mine methane capture and use for power (electrical or motive) and heat and/or destruction by flaring” which combines elements from all 5 previously submitted methodologies.51 Methane capture from oil & gas production and oil refining and methane loss reduction from gas transmission and distribution and JI potential in Poland: Emissions of CH4 occur during oil and gas production and the associated refining of oil. As Poland has relatively low own gas and oil production, main losses occur during transportation, refining and storage. GAINS considers flaring as the only option for reducing emissions from oil and gas production and refinery processes as flaring is a more emission effective measure than gas recovery and utilization. The removal efficiency of a flaring facility is 97 percent compared with 80 percent for a gas recovery and utilization installation and flaring is assumed to be applicable to 100 percent of the production and processing of oil and gas.52 Flaring is currently used as a safety option by refineries in Poland. With the cost range for flaring instead of venting of gas in refineries estimated by GAINS at € 73 to € 103/ tCH4, these projects would be viable as JI projects, assuming either bundling, or emissions from one source at the minimum level of 20,000 tCO2e annually (or 100,000 tCo2e in the first Kyoto period). However, according to GAINS model, the potential for such abatement until 2010 in Poland is too small. For projects involving flaring instead of venting in oil and gas production estimated by GAINS model at the same cost, also JI projects reducing emissions from these sources are viable, but with the same reservation regarding size of the project. Significant CH4 emissions occur from gas leakages during pipeline transmission and consumer distribution networks in Eastern Europe (with lower losses in Western Europe)

48 IIASA (CH4), p.50 49 PIN: Methane reduction through heat and power generation in Coal mine Staszic (draft) 50 These methodologies are: Nanshan NM0066, Pnsan NM0075, Fuxin NM0093, Panyi NM0094, Jincheng NM0102 51 For details, see http://cdm.unfccc.int/Panels/meth. 52 IIASA (CH4), p.50


(For Western Europe) Fugitive emissions from old consumer distribution networks can be reduced by replacing the grey cast iron networks, which were built when town gas was used instead of CH4, by polyethylene (PE) or polyvinylchloride (PVC) networks. This measure typically removes 97 percent of fugitive emissions (AEAT, 1998, p.132). Investments have a lifetime of 20 years.53 A second option is to increase the frequency of inspections and maintenance to improve leakage detection and repair but this solution cannot be considered as a JI project. The abatement potential in Poland for abatement projects of methane loss during production and transmission of gas and oil amounts to 230.000 t CH4, or approximately 4.8 million tCO2e. However, the majority of fugitive emissions occur from transport, and as such they are difficult to monitor, secondly, flaring as a safety measure makes difficult establishing a baseline for a potential project. Another difficulty for estimating JI potential for reduction of methane emissions from production and distribution of gas and oil in Poland in relation to the data offered by GAINS model stems from the fact that for Eastern Europe, IPCC emission factors and emission estimates are related to the amount of gas produced. In Poland, main emissions arise from leakages of gas transmission pipelines and distribution networks. Finally, estimated by GAINS costs of CH4 reduction at the level of € 1,756 to € 1,970 for methane reduction by replacing old cast iron networks, and € 338 to €1,394 for doubling leak control of the network, even discounting current gas prices, make the projects unviable as JI at current prices per ERU in the range of € 7 - € 11, and the expected revenue from reduction of 1t CH4 presently equal to € 147 to € 231. Manure management and JI potential in Poland: Methane emissions from manure can be reduced through anaerobic digestion of the manure in a closed vessel. The process generates CH4 that can then be utilized as an energy source, where 95 percent of the generated CH4 is captured. However, the process itself produces more CH4, and consequently, a lower removal efficiency of 80 percent of the original CH4 potential is assumed.54 In Poland, capacities of animal farming are much lower than in some countries in western Europe, nevertheless, such projects have been considered.55 Current farm-scale anaerobic digestion (biogas) plants have a minimum size of 100 dairy cows, 200 beef cattle or 1000 pigs. Centralized anaerobic digestion (AD) plants serving many farms are only feasible in areas with very intensive animal farming since long distance transport is costly and increases emissions of both CH4 and carbon oxides. Emissions per animal vary with temperature and manure management method (liquid or solid). The control cost per unit of reduced emissions will vary with these parameters. Anaerobic digestion is only considered to be feasible for liquid manure management, since emissions from solid manure management are much too low to justify the use of AD. There are no running Polish examples at present, so cost estimates are difficult to obtain. According to data quoted by IIASA authors, costs for installing AD are based on Italian cost data

53 IIASA (CH4), p.51 54 IIASA(CH4), p. 38 55 Small scale projects are planned by, eg. Poldanor. Typically, it would be a small biogas installation of 500 kW to 2-3 MW of installed capacity. Such projects are, obviously, too small to generate JI financing.


for the installation of a farm-scale AD plant (AEAT, 1998, p.37). The plant is designed to handle 22,000 t manure/year generating 180 MWh electricity and 440 MWh heat per year. Investments are estimated at 72,600 € or 5,344 €/year when annualized over a 20 years lifetime of the equipment. Operating and maintenance costs are estimated at 4,539 €/year, whereof 39 percent are labour costs. The utilized energy (i.e. electricity and heating) is regarded as a cost-saving.56 However, notwithstanding applicability of methodology to JI projects, the costs of removing 1t of CO2e are in several cases too high. In options quoted by GAINS model, the cost of removing one tonne for CH4 from manure emission reduction ranges between € 20 and € 294/ tCH4. With GWP of methane equal 21, this would bring revenues from ERUs generated from the project respectively between € 127 (assuming price of € 7 per 1 ERU) and an extra cost of € 147/tCH4 for the most expensive version.57 Only with a price of € 14/ERU would such a project break even in the most expensive version. This estimate has to be further considered in the light of production costs and available project finance. But in general, only bundled projects (i.e. several facilities generating energy from animal manure bundled together as one JI project), due to the size of biogas installations in Poland, could be considered as potentially good JI projects. According to GAINS model, the overall potential would be too small for JI projects but this assumption would have to be checked, as it seems that it may be not accurate. Notwithstanding, costs of manure abatement technologies as calculated by GAINS are too high at present to justify their implementation through a JI project. They would become cost effective when ERU achieves the price of € 14. Summary: To sum up, of all the technical measures of N2O abatement considered by the GAINS model, only N2O abatement technologies from nitric acid production can be considered as an option under JI mechanism in Poland.58 The choice of a specific technology, and of methodology, would depend on the technical parameters of the plant and are outside the scope of this report. Costs of N2O abatement from nitric acid production through an installation of a catalyst are broadly comparable, and would include: cost of a catalyst installation, costs of monitoring equipment, and would remain within €1,1 to 3,1 million, plus costs of catalyst operation and maintenance. When calculated per one tonne of Nitric acid reduced, as proposed by GAINS model, these costs could differ, depending on the size of reduction, which in turn depends on the size of nitric acid production. Calculation of profits from a JI project involving N2O reduction from nitric acid production would be much easier and would involve calculation of the number of ERUs, multiplied by the given average price of ERU. In practice, this would also differ between plants, depending on the negotiated price and structure of payment. For CH4 abatement, reduction of methane from coal mining and reduction of methane from landfills involve technologies recognised by approved CDM methodologies. These abatement technologies, together with reduction of methane from oil and gas production are viable as technologies of emission abatement under Joint Implementation mechanism. In the case of the projects involving upgraded recovery and utilization of coalbed methane from current level to 70%, according to the GAINS estimate, the cost of abatement would range

56 IIASA (CH4), p. 39 57 IIASA (CH4), p.39 58 In some countries, this could be also N2O abatement from adipic acid production.


between €107/tCH4 to €112/t CH4. Within that price range and GWP of methane equal 21, 1 tonne of CH4 reduced from coal mining would bring €147 to € 231 (assumed price of € 7 to € 11 per 1 ERU), so any of the projects involving such abatement would be viable as a JI project. While methane abatement from landfills through flaring appears profitable in Poland, since revenues from the sale of ERU’s would pay for a JI project implementation, a further consideration of costs involved in energy generation in each particular case of biogas energy use would be necessary in order to determine final cost effectiveness of the project, which also depends on the savings stemming from replacing natural gas and/or grid energy with gas and energy produced as a result of the project. It seems that at present such projects would not be profitable enough in Poland, since all the planned JI projects involving methane recovery from landfills prose flaring as the method of abatement, rather than energy production. With the cost range for flaring instead of venting of gas in refineries estimated by GAINS at € 73 to € 103/ tCH4, projects abating methane emission from oil production would be viable as JI projects, assuming either bundling, or emissions from one source at the minimum level of 20,000 tCO2e annually (or 100,000 tCO2e in the first Kyoto commitment period). For projects involving flaring instead of venting in oil and gas production estimated by GAINS model at the same cost, also JI projects reducing emissions from gas production are viable, but with the same reservation regarding size of the project. It seems that, if GAINS estimates are correct, there is no potential in Poland for such projects to be implemented as JI projects. Other technologies would be impractical as JI projects. For costs of CH4 reduction from methane reduction by replacing old cast iron networks, estimated by GAINS at the level of € 1,756 to € 1,970 and costs for doubling leak control of the network, estimated by GAINS at € 338 to €1,394, even when discounting current gas prices, the projects are unviable as JI projects at current prices per ERU in the range of € 7 - € 11, and the expected revenue from reduction of 1t CH4 presently equal to € 147 to € 231. Also costs of manure abatement technologies as calculated by GAINS are too high at present to justify their implementation through JI projects, and they would become cost effective when ERU achieves the price of € 14. A comparison of GAINS model and JI project evaluation: GAINS Model JI project evaluation Assessment of GHG emission levels

Assesses emissions of greenhouse gases and conventional air pollutants in 47 countries at national level

Assesses emission reductions through comparison of a project line with baseline emissions

Potential for emission reduction Calculates potential for emission controls acc to CAFE RAINS model predictions

Calculates potential for JI projects. This cannot be 100 % as it would become business-as-usual and will cease to be additional

Cost-effectiveness Calculates costs of abatement measures: attempts to quantify the values to society of the resources diverted to reduce emissions in Europe, approximated by estimating costs at the production level

Measure of cost effectiveness is a ratio between the cost of project implementation (and then later operational costs during the project’s lifetime) and the proceeds from the sale of ERUs generated by the project.


(societal resource costs) cost estimate of technology used in GHG abatement is offset against project implementation costs

Synergy in abatement of GHG and other air pollutants

Indicates a number of synergistic options which enable simultaneous abatement of GHG and other traditional air pollutants. (The cost-effectiveness)

Simultaneous reduction of some air pollutants which are under mandatory abatement may become an obstacle to proving an additionality of a JI project. projects should merely not lead to increases in other local/regional environmental quality indicators at the expense of achieving reductions in GHG emissions

Reduction potential versus technology application

Assesses the options for reducing all six greenhouse gases from all possible source categories, including agriculture

Only approved methodologies Only non-CO2 gases in EU-25 (linking Directive)

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