macroeconomic impacts of the low carbon transition … · 2017-02-09 · 2: putting the scenario in...

ANNEX 1 – MAIN RESULTS

MACROECONOMIC IMPACTS OF THE LOW CARBON TRANSITION IN BELGIUM

SECTORIAL RESULTS: IMPACT ANALYSIS

CLIMACT sa www.climact.com | [email protected] | T: +32 10 750 740

Analyzing the macroeconomic impacts of the transition to a low carbon society in Belgium

A project by Climact, Thierry Bréchet, Federal Planning Bureau and Oxford Economics

Annex 1 – Main results

October 2016

SECTORIAL RESULTS: IMPACT ANALYSIS3

Background

• The study analyses the macroeconomic impacts of the transition to a low carbon society by 2050 in Belgium

• The methodology is voluntarily broad and builds on three complementary models: HERMES, GEIM & OPEERA with multipliers

• Thematic workshops with stakeholders and experts have been organised • Several documents are available:

• Main findings• Report (methodology and results)• Annexes (1. Main results, 2. HERMES results, 3. GEIM Results, 4. OPEERA-IO results,

5. Literature Review)• The study was commissioned by the Federal Public Service Health, Food Chain Safety and

Environment and realised between January 2015 and September 2016• The study was conducted by CLIMACT, the Federal Plan Bureau, Oxford Economics and

Prof. Thierry Brechet


• This document presents the analysis of the main results from the models• The document divided into 6 chapters:

1. Overall results2. Results for the construction sectors3. Results for the transport sector4. Results for the power sector5. Results for the manufacturing sector6. Results for the agricultural sector

4

Background


1. Overall results

2. Results for the construction sector

3. Results for the transport sector

4. Results for the energy sector

5. Results for the manufacturing sector

6. Results for the agriculture sector

5

Table of content

SECTORIAL RESULTS: IMPACT ANALYSIS6(1) From the study Scenarios for a low carbon Belgium by 2050 available on www.climat.be/2050

Scenario definitionKey elements defining the CORE LOW CARBON SCENARIO

Complementary analyses have been performed and are presented where appropriate

Hermes GEIM OPEERA-IO

CO2 emissions evolution & low carbon measures

• -46% in BE (2030 vs 1990)(in line with -80% in 2050)

• -80% in EU (2050 vs 1990) • -46% in BE (2030 vs 1990)• -80% in BE (2050 vs 1990)

• Measures and actions defined in the CORE scenario from the study “Scenarios for a low carbon Belgium by 2050”

Carbon price& fiscal policy

• Carbon price in all sectors (gradually to 40€ in 2030) • ETS (+5€ in 2030, from 35€ to 40€)

• Rises to 150€ in 2050

• N/A

• Recycling of carbonrevenues through reduction in personal and employer’s social security contributions

• Recycling of carbonrevenues through reduction of government deficit

• N/A

International context

• Global action: low carbon transition policies in EU and the rest of the world

• N/A

1

2

3

SECTORIAL RESULTS: IMPACT ANALYSISSource: Climact, Federal Plan Bureau, Prof. T. Bréchet

1. Overall impacts - GrowthIt is possible to stimulate growth through investments in the low carbon economy

GDP and CO2 : putting the scenario in a historical perspective(million € 2005 / million tons CO2 in that year)

Key messages:

� Reaching GHG emission objectives can be done with limited (potentially positive) impact on growth

� Main growth enablers 1. Energy savings2. Demand push3. Recycling4. EU and global action

7

1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 20300

20

40

60

80

100

120

140

160

50,000

100,000

150,000

0

250,000

350,000

450,000

200,000

300,000

400,000

+2%GDP

-46%CO2

Oil crisis 1Oil crisis 2

Post oil crisis period

Kyoto 97

Financial crisis

Nuclear phase out

GDP (million € 2005)

GHG(million tons CO2)

CO2 - Historical dataGDP - Historical data

GDP - Hermes CORE Low Carbon CO2 - Hermes CORE Low carbon

CO2 - Hermes ReferenceGDP - Hermes Reference


0

10

20

30

40

50

60

70

80

90

100

1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030

Source: Climact, Federal Plan Bureau, Prof. T. Bréchet

8

1. Overall impacts - GrowthContinuation of decoupling trend between growth and energy/GHG

Energy and CO2 intensity of the GDP, historical and scenarios(Hermes, % evolution in base 100, M€ of energy / M€ of GDP & tons CO2 / M€ of GDP)

CO2 intensity - Hermes CORE LOW CARBON

CO2 intensity - Historical data

CO2 intensity - Hermes REFERENCE

Energy intensity - Historical data

Energy intensity - Hermes CORE LOW CARBON

Energy intensity - Hermes REFERENCE

Further improvement of 9% vs Reference

Further improvement of 15% vs Reference

Key message:

The low carbon scenario is a continuation of the current trend of decoupling between GDP and Energy / CO2 observed since 1970


1. Overall impacts - GrowthThe impact is positive for households, firms and public finance

Key messages:

• The low carbon investments and the carbon tax increase the energy and the overall production prices

• Energy savings and the recycling of the carbon tax more than compensate these increase for most agents

Impacts % changes Drivers

Households: Net disposable income

+0.27%

• Energy savings• Recycled carbon revenue invested inreduction of personal social security contributions

Firms:Gross operating surplus

+1.22(here as “change in percentage point”)

• Higher internal activity• Energy savings• Recycled carbon revenue invested inreduction of employer social security contributions

Public finance: Government balance

+0.4%• Social contribution (more jobs)• Direct and indirect taxes

Impacts on households, firms and public finance in 2030(Hermes, % change in 2030 wrt Reference scenario)

9Source: Climact, Federal Plan Bureau, Prof. T. Bréchet


10

1. Overall impacts - Jobs~80,000 additional jobs are created in 2030

Jobs creation by sectors in 2030, CORE LOW CARBON scenario(Hermes, thousands of jobs in that year wrt Reference scenario)

42 46 40

1724 27

7

117

6

2030

81

-3

1

2025

81

5

-2

1

2020

68

3

-1

0

Key messages:

• The main driver for job creation is the demand push: mostly in market services, construction and manufacturing industries

• Market services benefit from all low carbon measures and actionsand is job intensive

• There is a loss of 3.000 jobs in the energy sector (which includes both power and refining in Hermes)

Manufacturing industryConstruction

EnergyAgriculture

Other market servicesTransports et communications


1. Overall impacts - JobsDifferent drivers for growth and job creation

Main growth and job creation drivers in 2030(% of GDP change explained by the parameter, HERMES)

11

Key messages:

1. Energy savings are reinvested in the low carbon products and services

2. Demand is pushed through additional (low carbon) investments

3. Accompanying recycling policy support economic growth

4. EU and global action support low carbon exports

Inter-sectoral effects will drive a decarbonized economic growth

Source: Climact, Federal Plan Bureau, Prof. T. Bréchet

70%

5%

10%

15%

Energy savingsDemand pushRecycling of carbon revenuesGlobal action

15%

50%

25%

10%

Growth drivers Jobs drivers


1. Overall impacts - Jobslow carbon measures and actions contribute to emissions reduction and job creation

Proportion of emission reduction and job creation by type of abatement levers(Hermes, in 2030 wrt Reference scenario)

Key messages:

• Transport and building measures contribute for more than 60% of CO2emissions reduction

• Building and industry measures contribute for more than 75% of jobs creation

Abatementlevers

% of total CO2

emissions reduction% of total jobs

creation

Transport 31% 10%

Building 30% 51%

Industry 26% 27%

Power 13% 12%

12


1. Overall impacts – competitivenessEnergy prices are impacted by the carbon price Key messages:

• Price levels increase more for carbon intensive fuels and for households

• Average energy price increases less for the industry as the ETS sectors already face a carbon price in the baseline (35€ in 2030)

• In 2030, the impact of the carbon tax and increased balancing costs on electricity prices are partly compensated by the decrease in production costs compared to 2020

Impact of CORE low carbon scenario on energy prices in BE(Hermes, % change in that year CORE Low Carbon vs Reference scenario)

13

Vector Use 2020 2025 2030

Solid fuels(a) Households & services 12.4 25.2 39.0

(b) industry 5.2 10.2 15.7

Liquid fuels

(a) gasoline 2.6 5.3 8.0

(b) Diesel oil 3.3 6.7 10.1

(c) Fuel for heating 6.2 12.5 18.3

(d) Heavy fuel 1.2 2.3 3.4

Natural gas

(a) Industry 0.9 1.8 2.7

(b) Services 4.7 8.6 12.2

(c) Households 5.3 11.0 16.7

Electricity(a) High tension 8.9 1.8 2.7

(b) Low tension 8.4 4.7 1.8

Average energy price 5.4 6.2 7.2

Of which households 5.4 7.2 8.3

Carbon value (€05/ton)

Non-ETS +16,65 +26,3 +40

ETS +1.65 +3.3 +5


1. Overall impacts – competitivenessOil prices are lower in all low carbon scenarios, due to lower demand

Key messages: • A Global action scenario

leads to a slightly lower energy demand than in the REFERENCE

• Low carbon measures and actions at the EU level impacts the energy demand at global level: other regions free ride on EU’s efforts

• Low carbon measures and actions global level further decrease demand and price

Impact on world oil prices (GEIM scenarios, $2014 per barrel)

14Source: Climact, Oxford Economics, Prof. T. Bréchet

SECTORIAL RESULTS: IMPACT ANALYSISSource: Climact, Oxford Economics, Prof. T. Bréchet

1. Overall impacts – competitivenessEU-only and global action scenarios lead to different energy prices evolution for Europe

Key messages:

• EU-only: US and China benefit from global fuel price decrease due to falling demand

• Global action: China (and the US to some extent), are impacted by the higher carbon intensity of their energy sources

Impact on energy prices(GEIM scenarios, % evolution in 2050 wrt REF scenario, real prices)

15

Energy prices EU-only Global action- EU28 8.0 -1.5- US -8.5 9.6- China -1.7 23.0


1. Overall impacts – competitivenessThe impact of the low carbon scenarios is limited at EU level

Key messages:

• The impact of the low carbon scenario is limited and positive for the EU added value of the overall industrial production

• In the global action scenario, the EU performs better than the rest of the world

Impact on overall industry GVA in EU28(GEIM scenarios, in 2010€ billions)

16

0

20

40

60

80

100

120

140

2030

+2,5%

+2,7%

20502015

Global action

ReferenceEU-only


1. Overall impacts – competitivenessThe impact of the global action scenario on GVA is larger than the impact of EU-only for most sectors

Key messages:

• The Global action scenario offsets some of the negative impacts of EU-only for more energy intensive sectors

• Impact on chemical sector is negative (-3,5%) but sector performs better in EU than in rest of world (-4%) – See Annex 3 for more details

Impact on industrial sectors GVA in EU28(GEIM scenarios, in 2010€ billions)

17

GLOBAL ACTIONEU-ONLYReference

0 200 400 600 800

Wood & Wood productsRefining

Basic metals

Rubber & Plastics

Electrical EngineeringMechanical engineering

Food, beverages & tobaccoChemicals

Construction

Printing

Metal products

Precision equipment

Paper

0 200 400 600 800

2030 2050


1. Overall impacts – competitivenessThe energy savings have a major positive impact on the energy balance deficit

Key messages: • The external energy bill is cut

by half in 2030 (= more than €12 billions) representing a large decrease of imports

• Overall, exports are boosted by the international coordinated policy (+2.7%)

• Increase of imports (+2.8%) is driven by intermediary and equipment goods (growing domestic activity)

• The effect on the global external trade balance is neutral

Belgian energy external balance, historical and scenarios(Hermes, in % of the GDP in that year)

18


1. Overall impacts – competitiveness External trade balance

Impact Comments

Exports +2.75% • Stronger foreign activity (coordinated policy in the EU)

• Belgian competitiveness improvements in a low carbon economy

Imports +2.79% • Lower fossil fuel imports• Offset by the increase in equipment and

intermediary goods

Current external trade balance

-0.10(here as “change in percentage point of

GDP”)

• Savings in energy imports offset by increase in imports in equipment goods

• Terms of trade are not impacted by the scenario

Exports and imports in 2030, CORE LOW CARBON scenario(Hermes, % change wrt Reference scenario)

19

Key messages:

• No significant impact is expected on the current external balance of Belgium

• Belgium is saving on energy imports but needs to increase the imports of equipment goods to respond to the growing demand of the economy


20

1. Overall impacts – Summary Details on impact of key scenario drivers

1.01.5

3.0

0.5

2.52.0

-0.50.0

Firms’ gross operating

surplus

Exports Households income

GDP Jobs

Impact of scenarios on main macroeconomic indicators(Hermes, difference wrt the Reference, in 2030)

Key messages:

A global coordinated policy with adequate mitigations and fiscal measures can yield positive impacts in the economy

Scenarios:

(% wrt Ref) (% wrt Ref) (% wrt Ref) (% wrt Ref) (diff pt. wrt Ref)

GLOBAL ACTION

RECYCLING

CO2 PRICE

BOTTOM-UP MEASURES

EU-ONLY

= REFERENCE scenario + low carbon technical assumptions in BE

= EU POLICY scenario + similar policies and measures in the rest of the world

= BOTTOM-UP MEASURES scenario + gradual carbon price of 40€ in 2030 in BE

= CO2 PRICE scenario + recycling of revenues in BE (lower labor cost)= RECYCLING scenario + similar policies and measures in the whole EU


1. Overall results


� Main conclusions for the sector

� Key assumptions

� Results from macroeconomic models

� Results from OPEERA-IO model





22

Table of content


1.1 Main conclusions for the construction sectorThe construction sector has a very large potential for job creation

Impact of building, power and transport levers on jobs in construction sector(OPEERA-IO, in jobs in 2030 wrt Reference scenario, both direct and indirect jobs)

23

Key messages from macroeconomic models: • The construction sector gains about 27 000 jobs in 2030 driven by demand push through low carbon investments• The sector also benefits from carbon revenues recycling

Key insights from the workshops

• Challenge of social dumping / posting of jobs

• Risk of capacity constraints• Important role of public

procurement to stimulate domestic investments


1. Overall results



� Key assumptions







24

Table of content


10,250

Retrofit

Heating system2,451605

7,194

CORE

New build

+25%

REFERENCE

2,343

7,608

2,849

12,800

Source: Scenarios for a Low Carbon. Belgium by 2050, CLIMACT-VITO

25

1.2 Key assumptions for the construction sectorIllustration of assumptions on residential and commercial buildings levers

2030 investments for residential buildings (in million EUR)

4,995

CORE

+47%

7,348

REFERENCE

2030 investments for commercial buildings (in million EUR)

Expenditures drivers: • Increased renovation rate (+1%=>=2%)• Increased level of renovation• Large increase in the proportion of heat pumps at the

expense of oil and gas heating systems

Expenditures drivers: • Investment costs are not split in commercial buildings• Main drivers are also increased renovation rate and

electrification of heating systems• + electrification of cooling systems


536

536533525

2,342

31,668

Technology

24,454

20,710

3,208

Behaviour

23,116

19,854

2,729

Core

20,149

3,009

Reference

21,553

15,245

5355,773

34,546

-95%

+10%

23,683

+32%

1.2 Key assumptions for the construction sector Assumption on expenditures level evolution


CORE vs REF scenario

Overall buildings system costs

+10%

Investments in the buildings value chain

+32%

Fuel costs

-48%

2030 system costs for all buildings levers(in million EUR)

26

Operations & Maintenance

Fuel

Investment


1. Overall results



� Key assumptions







27

Table of content


1.3 Construction sector impacts from macroeconomiceconomic modelsImpact on production prices

Impact of scenarios on production prices in construction(Hermes, % changes wrt Reference scenario, in 2030) Production prices

+4%in 2030 in the CORE LOW

CARBON scenario

1. The strong demand push leads to a pressure on production capacities

2. Recycling offsets the CO2tax burden

3. Import prices increase in the CORE LOW CARBON scenario

2.0

0.0

5.0

1.0

4.0

3.0

4.0

Production prices

3.02.9

CO2 PRICE + RECYCLINGCORE LOW CARBON

BOTTOM UP MEASURES


1.3 Construction sector impacts from macroeconomic modelsImpact on sectoral jobs creation

Employment

+26,500 jobs(+9.4%) in 2030 in the CORE

LOW CARBON scenario

1. Mitigation measures create a demand push for the sector

2. Recycling has a positive but slight effect

3. The international environment also has a positive impact

Impact of scenarios on jobs in the construction sector(Hermes, % change wrt Reference scenario, in 2030)

8.0

6.0

10.0

4.0

2.0

0.0Employment

9.49.28.8

CORE LOW CARBONCO2 PRICE + RECYCLINGBOTTOM UP MEASURES


1.3 Construction sector impacts from macroeconomic modelsImpact on sectoral value added

Value added

+3.1%in 2030 in the CORE LOW

CARBON scenario

Recycling and the international

environment both have a significantly positive

impact

Impact of scenarios on value-added for the construction sector(Hermes, % changes in volume wrt Reference scenario, in 2030)

0.5

1.5

2.5

3.0

2.0

1.0

0.0

3.5 3.1

1.3

1.9

Value added

BOTTOM UP MEASURES

CORE LOW CARBONCO2 PRICE + RECYCLING


1. Overall results



� Key assumptions







31

Table of content


� The results focus on jobs evolution which is a relevant indicator to reflect the impact of the transition on the sector

� The results focus on buildings levers impacts (most relevant for the construction sector) as follow : 1. Jobs difference by EXPENDITURES categories 2. Jobs difference by LEVERS3. Jobs difference by SECTORS4. Variances analysis

� The results also give some power levers impacts relevant for the construction sector

32

1.4 Construction sector impacts from OPEERA-IO modelStructure of the results presented in next slides


1.4 Construction sector impacts from OPEERA-IO modelImpact on employment from low carbon scenario in Belgium

-55-18-1,810 -3,992

31,737

27,690

2025

-6,506-93

32,586

25,987

2030

28,289

26,461

2020

Jobs difference in CORE vs REF scenario - impact of buildings EXPENDITURES categories (jobs in that year, direct & indirect)

• This is in the same order of magnitude as what the macroeconomic models indicate

• Shift from fuel expenditures to investments leads to jobs creation

• Impact of operation and maintenance expenditures is negligible

Investment


Fuel


1.4 Construction sector impacts from OPEERA-IO modelImpact on employment from low carbon scenario

Jobs difference in CORE vs REF scenario – impacts of buildings LEVERS(in jobs in that year, including investments, operations and fuel expenditures, both direct and indirect)

2,282

-3,096

2,678

2025

11,964

13,891

2,802

27,689

3,907

-5,121

2030

13,665

25,988

-1,360

1,818

8,020

26,460

14,075

2,581

12,031

2020

• Buildings retrofit is the largest potential driver in terms of job creation

• (The “commercial buildings” lever also includes a large amount of retrofits)

Domestic - RetrofitDomestic - New Build

Commercial buildings

Domestic - Heating systemsDomestic - Fuel spendings


1.4 Construction sector impacts from OPEERA-IO modelImpact on employment from low carbon scenarios

Jobs difference in CORE vs REF scenario – impact of buildings developments on SECTORS(in jobs in that year, including investments, operations and fuel , both direct and indirect)

• The overall building value chain benefits from new investments

• Construction sector gains the largest share of the new created jobs

2.521 2.810 2.885

-3.223 -5.392-465-215-305-170

6.5426.1435.402

5.6525.5695.224

4.0613.9413.536

13.35313.21811.588

-467

2025

27.688 25.988

2020

26.769

-1.117

-646

2030

Energy - Solid & liquid fuels

Market services - technical servicesMarket services - non techical servicesIndustry - intermediary goodsIndustry - equipment goodsEnergy - Biomass fuel

Energy - electricity & gas fuelsConstruction


1.4 Construction sector impacts from OPEERA-IO modelVariance analysis: imported content in the buildings value chain

-646-597 -671-456 -467-5,812

10,979

4,4683,100

-473

-28%

6,542

+53%

5,652

4,894

18,778

-5%

2,293

25,988

CORE

4,061

2,885

-5,392

13,353

+10%

39,849

9,838

4,071

8,018

5,984

-5,110

18,101

Jobs difference in CORE vs REF scenario – impacts of increase or decrease of BELGIAN content(in jobs in 2030, including investments, operations and fuel, both direct and indirect impacts)

• Changes in imported content could impact the construction sector:

• +10% of BELGIAN content = potential gain of 13,800 jobs

• -5% of BELGIAN content = potential loss of 7,000 jobs

= % change in Belgian content of goods and services in the non-energy value chain

Remark : the impact highlighted here is underestimated as potential international development (exports opportunities) is not taken into account

Energy - Biomass fuelEnergy - Solid & liquid fuels

ConstructionEnergy - electricity & gas fuels

Market services - non techical services

Industry - equipment goods

Market services - technical services

Industry - intermediary goods


1.4 Construction sector impacts from OPEERA-IO modelVariance analysis of impact of different low carbon scenarios

-651-651-660-646-409-504-467 -409

7,970

15,872

11,139

-6,664

82,321

38,320

16,744

+217%

TECH BEHAV -95%

+19%

13,353

-6,664

13,0494,715

8,459

30,821

13,93225,988

5,9675,6524,061

2,885

-5,3926,542

22,857

CORE

5,4863,766

-12%

5,5682,7123,216

-4,304

Jobs difference in scenario vs REF – impacts of CORE, Behaviour and Technological scenarios(in jobs in that year, including investments, operations and fuel, both direct and indirect)

• Technological and behavioural scenarios do NOTlead to a significant difference in terms of job creation for the building value chain

• More ambitious scenario (-95%) demand larger energy savings and investments that represent a larger demand push for the economy

Energy - electricity & gas fuelsConstruction


Industry - equipment goodsEnergy - Biomass fuel

Industry - intermediary goodsMarket services - non techical servicesMarket services - technical services


Remark: The impacts of buildings levers and power levers should be analysed separately as they do not take into account economic feedback loops. Only Hermes simulations take those into account.


Jobs created by CORE vs REF scenario – impact of power capacity developments in main economic sectors(in jobs in that year, including investments, operations and fuel spending, both direct and indirect)

The demand push for new infrastructures in the energy sector gives the opportunity to create new jobs in the construction sector in 2030

+500 jobs

586

20302020

3.050

4.429

2.804

2025

241343

Energy - electricity & gas fuelsEnergy - Solid & liquid fuelsEnergy - Biomass fuel

Construction

Market services - non techical servicesMarket services - technical services

Industry - intermediary goodsIndustry - equipment goods



Jobs difference in CORE vs REF scenario – impact of transport developments on SECTORS(in jobs in that year, including investments, operations and fuel , both direct and indirect)

The model also expects a positive but limited demand push in new infrastructures in the transport sector that also represent an opportunity to create new jobs in the construction sector in 2030

All vehicles

-3.426

-5.327

-886-607

-904-551

-2.431

6 456262

46167

-18

425

2025

-4.011

122-5

2020

-2.775

-35675 -331

2030

-6.497

Market services - technical servicesMarket services - non techical servicesIndustry - intermediary goodsIndustry - equipment goodsEnergy - Biomass fuelEnergy - Solid & liquid fuelsEnergy - electricity & gas fuelsConstruction


1. Overall results




� Key assumptions






41

Table of content


Key messages from macroeconomiceconomic models:� The transport services sector gains 3 000 additional jobs in 2030� A decrease in number of individual cars leads to a net decrease in numbers of jobs (-6 500 jobs) in the overall

transport vehicles value chain (especially technical services with - 5 000 jobs)� Investments in domestic capabilities for electric cars assembly and maintenance partially compensate such

decrease

42

2.1 Main conclusions for the transport sectorDifferent impacts for transport services and transport vehicles supply chain

Impact of low carbon transports vehicles development on jobs (OPEERA-IO, in jobs in 2030 wrt Reference scenario, both direct and indirect jobs)


• Key impact of investments in low carbon and smart transport infrastructures

• Development of collective vehicle value chains

• Links with co-benefits


1. Overall results




� Key assumptions






43

Table of content


2.2 Key assumptions for the transport sector Technical assumptions extracted from “Low Carbon Belgium” project results


44

REF 2050

REF 2030

CORE 2030

6,245

-85%

3,983

2010

4,2593,451

CORE 2050

-45%

5,356

Decrease of the overall number of cars because of

• Lower travel demand • Higher occupation of

vehicles (25 to 35%)• Higher and longer use

of vehicles and infrastructure

Almost complete shift to electric mobility is expected in 2050

ICE, incl. biofuels, CNG & hybridElectricPlug-in Hybrid ElectricFuel Cell (Hydrogen)

Total cars by technology(‘000s units)


2.2 Key assumptions for the transport sector Technical assumptions extracted from “Low Carbon Belgium” project results


45

-95%

4,686-36%3,400-59%

3,983

-45%

TECHBEHAVCOREReference

5,356

3,400• The number of ICE cars

decreases in all low carbon scenarios because of lower demand for transport

• But number of cars by technology is significantly different in the scenariosFuel Cell (Hydrogen)

ICE, incl. biofuels, CNG & hybridPlug-in Hybrid Electric

Electric

Total cars by technology in 2030(‘000s units)


1,465

8,703

7,354

1,826

Reference

21,673

17,694

7,868

4,10817,208

8,697

-95%

9,697

21,716

+9%-10%

0%-18%

17,883

-10%

-17%

Technology

10,576

8,832

2,308

BehaviourCORE

8,697

-10%

-21%

7,532

1,487

7,024

2.2 Key assumptions for the transport sector Assumptions on expenditures level evolution


Operations & MaintenanceInvestment

Fuel

• In the CORE and Behaviour scenarios, investment and fuel expenditures decrease by ~10% and ~55/60% with transport levers

• In the Technological and even more in the -95% scenarios, investments expenditures increase (higher cost of low carbon vehicles) and fuel expenditures decrease less

2030 total system costs for transport levers(in million EUR)

46


1. Overall results




� Key assumptions






47

Table of content


2.3 Transport sector impacts from macroeconomiceconomic modelsImpact on sectoral jobs creation and value added in transport services

Impact on employment and value added, CORE LOW CARBON scenario(Hermes, thousands of jobs / M€ constant price in that year wrt Reference scenario)

Impact on land transport services(e.g. NMBS/SNCB, logistic services, taxi services, etc.)

Employment

+3,000 jobsin 2030

Value added

+1,325 M€2005

in 2030

2025 2030

1.9

3.0

2020

1.1

985

662

2020 2030

1,325

2025

Rail and road transport services

Jobs Value Added


2.3 Transport sector impacts from macroeconomic models Impact on sectoral production prices evolution in transport services

Impact of scenarios on production prices in 2030(Hermes, % changes wrt Reference scenario, in 2030)

• Efficiency gains related to Mitigation measures enable land transport services to decrease sectoral cost price

• Production prices are decreasing less in both Recycling and CORE LOW CARBON scenarios due to higher energy price and higher pressure on capacities

0.0

-1.0

-2.0

-3.0

-1.5

-2.5

-0.5

-3.5Rail and road transport services

-2.1

-3.1

-1.0

CO2 PRICE + RECYCLINGBOTTOM UP MEASURES

CORE LOW CARBON


2.3 Transport sector impacts from macroeconomic modelsImpact on sectoral jobs creation in transport services

• Employment in transport services is positively impacted by all 3 dimensions

• Mitigation measures have the largest impact because of their boosting effect to the overall economy that benefit transport services

Impact of scenarios on employment in 2030(Hermes, % change wrt Reference scenario, in 2030)

2.5

1.5

3.0

2.0

0.5

1.0

3.5

0.0Rail and road transport services

3.22.9

1.9

CORE LOW CARBON

BOTTOM UP MEASURESCO2 PRICE + RECYCLING


2.3 Transport sector impacts from macroeconomic models Impact on sectoral value added in transport services

• Efficiency gains related to mitigation measures is an important driver for increased value added in land transport services

• The effect of Tax + Recycling and CORE LOW CARBON scenarios are limited or neutral for value added

Impact of scenarios on value-added in 2030(Hermes, % changes in volume wrt Reference scenario, in 2030)

0.0

20.0

10.0

5.0

15.0

Rail and road transport services

19.719.717.9

CO2 PRICE + RECYCLINGBOTTOM UP MEASURES

CORE LOW CARBON


1. Overall results




� Key assumptions






52

Table of content


� The results focus is on jobs evolution which is a relevant indicator to reflect the impact of the transition on the sector (results also available on added value evolution in Appendix)

� The results focus on transport levers impacts as follow : 1. Jobs difference by EXPENDITURES categories 2. Jobs difference by LEVERS3. Jobs difference by SECTORS4. Variances analysis

53

2.4 Transport sector impacts from OPEERA-IO modelStructure of the results presented in next slides


2.4 Transport sector impacts from OPEERA-IO modelImpact on employment from low carbon scenario in Belgium

Jobs difference in CORE vs REF scenario - impact of transport EXPENDITURES categories (jobs in that year, direct & indirect)

• In the CORE scenario, the decrease in demand for transport (and the related decrease of ICE vehicles) has a negative impact on the overall transport value chain

• The negative impact is worsening in the long term as the decrease is getting more important

-761

-2.145-2.785

-1.842

-3.423

-2.024

-2.776

9

2020

-6.497

-4.010

-289

2025

-23

2030

Investment

FuelOperations & Maintenance

All vehicles


2.4 Transport sector impacts from OPEERA-IO modelImpact on employment from low carbon scenarios

Jobs difference in CORE vs REF scenario – impact of transport developments on SECTORS(in jobs in that year, including investments, operations and fuel , both direct and indirect)• The decrease of new

vehicle particularly impacts technical services (retail, distribution and maintenance)

• Manufacturing is not very impacted because of the high imported content of vehicles (positive impact of increasing collective vehicles)

• Shift to electric has a positive impact for electricity production and negative impacrt for other fossil fuels

All vehicles

-3.426

-5.327

-886-607

-904-551

-2.431

6 46262

456 167

-18

425

2025

-4.011

122-5

2020

-2.775

-35675 -331

2030

-6.497

Market services - technical servicesMarket services - non techical servicesIndustry - intermediary goodsIndustry - equipment goodsEnergy - Biomass fuelEnergy - Solid & liquid fuelsEnergy - electricity & gas fuelsConstruction


2.4 Transport sector impacts from OPEERA-IO modelVariance analysis: impact of different low carbon scenarios

-886 00

0

-18

323 326

279

75 75167

466425

376

94790

46

TECH

-5,327

BEHAV

-1,036

-95%

5,341

-1,113

-6,772

511

-1,036

6,642

-765

-7,636-7,543

511

903

CORE

-6,497

-6,772

-1,113-904

Jobs difference in scenario vs REF – impacts of CORE, Behaviour and Technological scenarios(in jobs in 2030, including investments, operations and fuel, both direct and indirect) • CORE, Behavioural and -

95% lead to a decrease of demand of mobility, meaning a decrease of number of cars and loss of jobs, especially in technical market services

• In the Technological scenario, the lower decrease of vehicles units and the higher cost of low carbon vehicles represent a boost to the economy

+6,600 jobsMarket services - non techical servicesIndustry - intermediary goods

Energy - Biomass fuelIndustry - equipment goods

Energy - Solid & liquid fuelsEnergy - electricity & gas fuelsConstruction


All vehicles


*Low carbon = Electric, Plug-in electric and fuel cell vehicles

57

2.4 Transport sector impacts from OPEERA-IO modelImpact on employment from low carbon scenario in Belgium

324 11,233

10,574 11,544

640

8,791

8,8265,144

604

2030

23,417

2025

20,004

2020

14,259

Jobs difference in CORE vs REF scenario - impact of transport EXPENDITURES categories (jobs in that year, direct & indirect)

• Focusing on low carbon vehicles only, the CORE scenario has a positive impact on job creation

+23,000 jobs

• Collective vehicles have a positive but relatively limited impact on jobs creation (not including services related to collective transport that are job intensive)

2030

484

2025

285

2020

254Investment


Fuel

Individual low carbon* vehicles

Collective low carbon* vehicles


2.4 Transport sector impacts from OPEERA-IO modelVariance analysis of imported content in transport value chain

Jobs created by CORE vs REF scenario – impacts of changes in Belgian content(in jobs in 2030, including investments, operations and fuel, both direct and indirect)

+32% more jobs in

electric, hybrid and fuel cells individual

vehicles

23.417

2030 CORE

30.958

+32%

+10%

Indiv vehicles

+163% more jobs in

electric, hybrid and fuel cells collective

vehicles

484,0

2030 CORE

+163%

+10%

1.272,0

Collective vehicles

The development of a more Belgian value chain (+10% of Belgian content) could create:

18/02/2016


1. Overall results





� Key assumptions


� Results from OPEERA-IO



60

Table of content


4.3 Energy sectorThe energy sector needs to adapt to the changes in energy demand and supply

Impacts of changes in Belgian content on jobs in power sector(OPEERA-IO, in jobs in 2030 wrt Reference scenario, both direct and indirect jobs)

Key messages from macroeconomiceconomic models: • The energy sector is expected to loose some existing jobs driven by the fall in energy demand• Investments in domestic capabilities for electrification (renewables, grid, services, etc.) create new jobs

(+ 4 500 jobs in 2030)


• Impact of other configurations of the production on the energy sector (decentralization, intermittency, grids, storage)

• Impact of decreasing renewables costs

• Specificities of the high efficiency of the Belgian refinery sector within the EU

• Importance of the quality of the new jobs


1. Overall results





� Key assumptions





62

Table of content


0

20

40

60

80

100

120

140

160

2010 2015 2020 2025 2030 2035 2040 2045 2050

TWh

Electricity production by sourceImports of decarbonizedelectricityCoal+Gas+Oil power stations

Nuclear power

Carbon Capture Storage (CCS)

Industry CHP

Residential CHP

Geothermal electricity

Biomass power stations

Hydroelectric power stations

Solar PV

Onshore wind

Offshore wind

Total consumption

Renewable energy sources

Intermittent sources

Reference scenario


63

3.2 Key assumptions for the energy sector Electricity production mix in the CORE scenario in Belgium, TWh per year

▪ Gas : used as an intermediary source of electricity, but replaced over time and used as back-up

▪ Intermittent RES : solar PV and wind make up ~50% of the production mix in 2050

▪ Non-intermittent RES : Biomass and geothermal are key to complement the mix, and support grid stability with back-up

0

20

40

60

80

100

120

140

160

2010 2015 2020 2025 2030 2035 2040 2045 2050

TWh

Electricity production by sourceImports of decarbonizedelectricityCoal+Gas+Oil power stations

Nuclear power

Carbon Capture Storage (CCS)

Geothermal electricity

Industry CHP

Residential CHP


Hydroelectric power stations

Solar PV

Onshore wind

Offshore wind

Total consumption

Renewable energy sources

Intermittent sources

Reference scenario

Nuclear

Gas

Offshore wind

SECTORIAL RESULTS: IMPACT ANALYSIS64SOURCE: CREG (2010), ECF Roadmap 2050 phase II (McKinsey/KEMA/ICL), Climact

1 Solar PV: ~10% (2010) to ~15% (2050); Onshore wind : 25% (2010) to 30% (2050)

3.2 Key assumptions for the energy sector Electricity capacity in Belgium in 2050 in the CORE scenario GW

16

5

7

28

2

2010

Intermittent

2050

18

40

-26%

Non-intermittentBack-up gas plants

+119%

� Non-intermittent production is completed by a large amount of back-up capacity

� Altogether firm capacity still decreases compared to 2010, but with better interconnections and DSM

� Total capacity increases as capacity factors of solar and wind1 are low

� If all 28 GW produce at max potential :‒ Minimal Belgian demand of ~10 GW‒ Interconnection potential of 15 to 30

GW to the rest of Europe‒ Additional increase in DSM and storage

SECTORIAL RESULTS: IMPACT ANALYSIS65Source: Scenarios for a Low Carbon. Belgium by 2050, CLIMACT-VITO

3.2 Key assumptions for the energy sector System costs assumptions

456 492

321

544641

786248

248

264

Biomass and gas power stations

2.334

1.670

REF

4

Hydro and geothermal

Wind power (on and offshore)

Core

Solar PV

+40%

Grid and balancing implications

Average yearly investment costs(undiscounted 2010-2050, in M€)

854

937

-14%

O&M

Investment

Fuel

Core

2,334

2,617

REF

6,815

1,670

4,291

+40%

5,888

Average yearly system costs (incl. primary energy costs) (undiscounted 2010-2050, in M€)


13

17

12 13

1225 25

25

33

4136

419

70

1513 1510

11

17

35

8

13

131

6 2

Technology

93

-31%

105

6

2

BehaviourCore

2

Reference

135126-6%

02

6

2

-34%

89

-95%

-22%

66Source: Scenarios for a Low Carbon. Belgium by 2050, CLIMACT-VITO

3.2 Key assumptions for the energy sector Electricity production in Belgiumin the various technical scenario, TWh

63

42 4052

9 7

9

13

1212

11

22

2524

25

43

10

11

23

-15%

99

Technology

5

5 1

Behaviour

5

-8% 1080%

-95%

96

4 1

-12%

4

Core

925 1

Reference

108

5

1

4 1

44

Gas

Carbon Capture and Storage (CCS)


Industrial and residential CHP

Wind on/offshore

Solar PV

Imports of decarbonized electricity1

Geothermal and hydro electricity

2030 2050


1. Overall results





� Key assumptions





67

Table of content


3.3 Energy sector impacts from macroeconomic modelsImpact on sectoral production prices

Impact of scenarios on production prices in the energy sector (power and refineries)(Hermes, % changes wrt Reference scenario, in 2030)

Production prices =-3,3%

in the energy sector in 2030 in the CORE LOW CARBON scenario

• The lower demand reduces pressure on production capacities utilisation in the mitigation scenario (~-12% in 2030)

• Recycling partially offsets the CO2 tax burden on cost price of the sector

• EU Policy and CORE LOW CARBON scenarios see pressure on both capacity and cost prices that increase the overall production prices

0.0

-1.0

-2.0

-3.0

-4.0

-5.0

-6.0

Production prices

-3.3-3.7

-4.6

-5.7

CO2 PRICE + RECYCLING

CORE LOW CARBON

BOTTOM UP MEASURES

EU-ONLY


3.3 Energy sector impacts from macroeconomic modelsImpact on sectoral employment

Employment =-2.900 jobs

in the energy sector in 2030 in the CORE LOW CARBON scenario

• Mitigation measures create a large reduction in energy demand which leads to decrease of employment in the energy sector

• The CO2 tax has a negative impact that is partially compensated by the recycling policy

• EU POLICY and CORE LOW CARBON scenarios have a limited but positive impact

Impact of scenarios on jobs in the energy sector (power and refineries)(Hermes, % change wrt Reference scenario, in 2030)

0.0

-2.0

-4.0

-6.0

-8.0

Employment

-7.3-7.6-7.5 -7.3

EU-ONLYCO2 PRICE + RECYCLINGBOTTOM UP MEASURES

CORE LOW CARBON


3.3 Energy sector impacts from macroeconomic modelsImpact on sectoral value added

Value added =-9.6%

in the energy sector in 2030 in the CORE LOW

CARBON scenario

• As for employment, the CO2 tax has a negative impact on the sector partially compensated by the recycling policy

• EU POLICY and CORE LOW CARBON scenarios have a limited but positive impact

Impact of scenarios on value-added in the energy sector (power and refineries)(Hermes, % changes in volume wrt Reference scenario, in 2030)

0.0

-2.0

-4.0

-6.0

-8.0

-10.0

Value added

-9.6-10.0-9.4 -9.7

BOTTOM UP MEASURESCO2 PRICE + RECYCLINGEU-ONLYCORE LOW CARBON


1. Overall results





� Key assumptions





71

Table of content


� The results focus on jobs evolution which is a relevant indicator to reflect the impact of the transition on the sector (results also available on output and added value evolution in Appendix)

� The results focus on power capacity development levers impacts as follow : 1. Jobs difference by EXPENDITURES categories 2. Jobs difference by LEVERS3. Jobs difference by SECTORS4. Variances analysis

72

3.4 Energy sector impacts from OPEERA-IO modelStructure of the results presented in next slides


3.4 Energy sector impacts from OPEERA-IO modelImpact on employment from low carbon scenario in Belgium

560

2.059

3.568

765

1.079

2.149

2030

4.428

-219

2025

2.804

-20

2020

2.912203

Jobs difference in CORE vs REF scenario - impact of transport EXPENDITURES categories(jobs in that year, direct & indirect)

Investment


Fuel • New biomass fuel needs more than compensate the loss in gas fuel consumption

• Investments in and maintenance of new capacity for renewable energy sources create more than 1800 and 600 jobs in 2030


3.4 Energy sector impacts from OPEERA-IO modelImpact on employment from low carbon scenario

Jobs difference in CORE vs REF scenario – impact of transport developments by LEVERS(in jobs in that year, including investments, operations and fuel spending, both direct and indirect)

-1.473 -1.409

1.7481.536

1.702

-1.078

552486425

770671

546487

688

1.771

711725

2030

4.429

204

6

145

2025

2.803

1906

116

2020

2.913

3701303

117

Geothermal electricityGas power stations

Onshore windSolar PVSolar thermal

InterconnectionsBiomass power stations

Offshore windHydroelectricity

• Compared to the REF scenario the CORE installs more RES based electricity production, and reduces gas-based production

• Some technologies like solar PV and onshore wind are already assumed to be well developed in the REF scenario in 2030, and therefore their additional impact on jobs is limited


3.4 Energy sector impacts from OPEERA-IO modelImpact on employment from low carbon scenarios

Jobs difference in CORE vs REF scenario – impact of transport developments on SECTORS(in jobs in that year, including investments, operations and fuel spending, both direct and indirect)

In 2030, the power developments lead to • +500 more jobs in the

construction sector • +700 jobs in

manufacturing value chain

• +1400 jobs in services value chain-1.059

1.544 1.8822.800

-653

499497

490

842

563

458

586

343241

-119

3516

2030

4.429

181

17

2025

2.804

284 82

13

2020

3.050

308 127


Industry - intermediary goods

Energy - Biomass fuel

Market services - non techical services

Industry - equipment goods

ConstructionEnergy - electricity & gas fuels



3.4 Energy sector impacts from OPEERA-IO modelVariance analysis of impact of different low carbon scenarios

842 858

593 463

439

-702

502499

13779

182181624289

566563

11 401

594586

-48%

-95%

+9%

2,477

1,680

282

12

BEHAV

-1,122

2,297

1,798

288

-1,200

TECH

4,824

2,807

17

CORE

4,429

2,800

17

-1,059

-44%

Jobs difference in scenario vs REF – impacts of CORE, Behaviour and Technological scenarios(in jobs in that year, including investments, operations and fuel, both direct and indirect)

Market services - technical servicesMarket services - non techical services

Energy - Solid & liquid fuelsEnergy - Biomass fuel

Construction

Industry - intermediary goodsIndustry - equipment goods

Energy - electricity & gas fuels

• Technological scenarios lead to same amount of job creation than CORE scenario

• The Behavioral and -95% scenarios leads to a lower but still positive net jobs evolution for the power capacity value chain


3.4 Energy sector impacts from OPEERA-IO modelImpact of increase or decrease in imported content in the power capacity value chain

Jobs difference in CORE vs REF scenario – impacts of increase or decrease of imported content(in jobs in that year, including investments, operations and fuel, both direct and indirect)

Remark : the impact highlighted here is underestimated as potential international development (exports opportunities) is not taken into account

More than

1,5xmore jobs in

solar PV value chain

+56%

+10%

1.204,0

2030 CORE

770,0

Solar PV

Nearly

3xmore jobs in

onshore wind value chain

204,0

+190%

592,0

+10%2030 CORE

Onshore Wind

The development of a more domestic value chain (+10% of Belgian content) could create:


1. Overall results






� Key assumptions

� Results from macroeconomiceconomic models


79

Table of content


4.1 Main conclusions for manufacturing industriesEnergy savings have a positive impact on industry production prices

Impact on jobs and value added(Hermes, thousands of jobs / M€ constant price in that year wrt Reference scenario)

80

Key messages from macroeconomic models: • The manufacturing sector as a whole gains about 11 000 jobs by 2030 • This gain is driven by lower production prices and higher overall economic activity • The limited carbon price increase in the industry does not impact overall firms competitiveness


• Specific risk of carbon leakage for ETS sectors needs attention

• Firms and sectors challenges and opportunities are specific

• Value chain and industrial clusters effects have to be taken into account


1. Overall results






� Key assumptions



81

Table of content

SECTORIAL RESULTS: IMPACT ANALYSISSource: Scenarios for a Low Carbon. Belgium by 2050, CLIMACT-VITO

82

3.2 Key assumptions for manufacturing industriesTechnical assumptions extracted from “Low Carbon Belgium” project results

-9

136

9

4

12

3

4

3

1

21

11

3

2050

13

0

-76%

2010

2

45

-3

Delta vs 2010

-33%-21%-23%-76%

-65%-97%

+250%

-54%

GHG emissions in the Belgium manufacturing industries, CORE scenarioMtCO2e per year

• Assumptions on energy efficiency levels by sectors have been included in the models in line with GHG emissions target

• But models do not include formal sector specific CO2emissions reduction targets

Lime and glass

Biomass allocated to industry

Other

CementSteel

Pulp & Paper

ChemicalsOil & Gas

Food, drinks and tobacco


1. Overall results






� Key assumptions



83

Table of content


4.3 Manufacturing industries impacts from macroeconomic modelsImpact on sectoral jobs creation and value added

Impact on employment and value added, CORE LOW CARBON scenario(Hermes, thousands of jobs / M€ constant price in that year wrt Reference scenario) Employment in

manufacturing industries

+10,700 jobsin 2030

Value added

+1,500 M€2005

in 20301,8 2,1 2,71,4 1,2

2,84,3

7,65,9

2025

7,5

0,4

2020

10,7

2030

605

585

852927

449239160

1.508

-25

20302025

985

1.357

2020

57

Consumption goodsIntermediary goods Equipment goods

Jobs Value Added


4.3 Manufacturing industries impacts from macroeconomic modelsImpact on sectoral production prices

Impact of scenarios on production prices in 2030(Hermes, % changes wrt Reference scenario, in 2030)

• Mitigation measures reduce production prices due to strong energy savings

• Smaller decrease of production prices in the recycling scenario

• The benefits of energy savings almost vanish in the EU POLICY & CORE LOW CARBON scenarios because of an increase in import prices-4.0

-1.0

0.0

-3.0

-2.0

1.0

-3.0

-1.8

Consumption goods

-1.0

Equipment goods

-1.0

-1.7

-0.8-0.4

-3.4

0.6 0.7

Intermediary goods

-0.9

-0.3

EU-ONLYCO2 PRICE + RECYCLING

CORE LOW CARBON

BOTTOM UP MEASURES


0,240,17 0,300,08

2,592,542,792,75

0,0

0,5

1,0

1,5

2,0

2,5

3,0

Belgian importsBelgian exports

86

4.3 Manufacturing industries impacts from macroeconomic modelsImpact on Belgian external trade

Impact of scenarios on external trade in 2030(Hermes, % changes in volume wrt Reference scenario, in 2030)

• Increase of exports in all scenarios

• Imports also increase because of high domestic demand and high imported content of our exports

• The EU POLICY & CORE LOW CARBON scenarios boost exports (and imports) because international trade of Belgium is very sensitive to EU and RoW growth

CO2 PRICE + RECYCLING

CORE LOW CARBON

BOTTOM UP MEASURES

EU-ONLY


4.3 Manufacturing industries impacts from macroeconomic modelsImpact on manufacturing external trade

Impact of scenarios on external trade(Hermes, M€ current in that year, CORE LOW CARBON and Reference scenario)

Equipment goodsIntermediate goods

• External trade of equipment goods is worsening because of high imported content of the sector

• External trade of intermediate goods is boosted by exports opportunities growth

• Consumption goods contribution to external trade is marginal

203020252020

0,0

-20.000,0-10.000,0

-30.000,0

20.000,030.000,0

10.000,0

60.000,050.000,040.000,0

70.000,0

203020252020 2020 20302025

CORE LOW CARBONReference

Consumption goods


4.3 Manufacturing industries impacts from macroeconomic modelsImpact on sectoral employment

• Jobs creation is positive in all sectors and in all scenarios

• Tax + recycling always fosters jobs creation

• EU POLICY and CORE LOW CARBON scenarios are:

• Very positive for intermediary

• Less positive for equipment

• Neutral for consumption

Impact of scenarios on employment(Hermes, % change wrt Reference scenario, in 2030)

0.0

3.0

5.0

4.0

1.0

2.0 1.51.8

Consumption goods

1.1

2.9

1.8

Intermediary goods

4.4

Equipment goods

0.5

1.5

3.2

4.3

0.6

1.8


CORE LOW CARBONEU-ONLY


4.3 Manufacturing industries impacts from macroeconomic modelsImpact on sectoral value added

• Value added mostly positively impacted by mitigations measures

• The impact of Tax + recycling scenario is relatively neutral

• Equipment goods experience a slight negative impact in the EU POLICY & CORE LOW CARBON scenario: strong increase in imports, and capacity constraints

Impact of scenarios on value-added(Hermes, % changes in volume wrt Reference scenario, in 2030)

4.0

3.0

5.0

-1.0

0.0

2.0

1.0

3.7

-0.2

4.03.73.6 3.53.9

Intermediary goods

4.2

Consumption goods

3.9

-0.4

1.4

Equipment goods

1.4

EU-ONLY


CORE LOW CARBON


1. Overall results







� Key assumptions

91

Table of content


Key insights from the workshops on impacts of 2 main emissions reduction levers:1) Technical options� Growing efforts for GHG emissions reduction in the sector : higher potential than identified in technical study� Initiatives should be pursued to favour innovation� Objectives of different agricultural models should be reconciled

2) Behavioural options� The necessity of a protein transition towards a more sustainable agricultural and food system should be analysed

in more details� The impact of such transition on production level in BE will depend on the competitiveness of the sector� The current trend for lower demand for animal proteins participates to the decrease of GHG emissions and has

positive co-benefits on public health (see next section)

Sectorial opportunities� Measures to limit food waste and support circular economy initiatives in the sector could have an important

economic development potential� Importance of developing initiatives with the entire food supply chain (from producers to customers) when

tackling the sustainability challenges

92

5.1 Main conclusion for the agricultural sectorThe agriculture sector must be analysed carefully


1. Overall results







� Key assumptions

93

Table of content


Source: Agriculture sector document from “Scenario for a low Carbon Belgium in 2050”

3.2 Key assumptions for a low carbon agricultureMain sources of direct GHG emissions from agriculture

� 40% are N2O emissions from soil management (application of manure and mineral nitrogen fertilizer)

� 36% are CH4 emissions from enteric fermentation (mainly coming from cattle and sheep)

� 24% are CH4 and N2O from manure management (emitted during storage and treatment of manure)

Non combustion GHG emissions of agriculture in Belgium(%, 2010)


� Decrease CH4 emissions from enteric fermentation� reduction of the amount of livestock� productivity increase (decrease of CH4 per unit of product) � improvement of rumen efficiency and feed conversion efficiency

� Decrease CH4 and N2O emissions from manure management � reduction of the amount of livestock� amount and characteristics of manure� animal waste management

� Decrease direct N2O emissions of agricultural soils � controls of nitrification and denitrification� soil and crop management

Source: Agriculture sector document from “Scenario for a low Carbon Belgium in 2050”

95

3.2 Key assumptions for a low carbon agricultureMain levers for reduction of direct GHG emissions from agriculture


CLIMACT sa www.climact.com | [email protected] | T: +32 10 750 740

Francis Bossier – [email protected]ïc Berger – [email protected] Bréchet - [email protected] Vermeulen – [email protected] Pestiaux – [email protected] Lemercier [email protected]

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macroeconomic impacts of the low carbon transition … · 2017-02-09 · 2: putting the scenario in...

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