from cost of control to cost of inaction: overview of the ... · from cost of control to cost of...

From cost of control to cost of inaction:

Overview of the CIRCLE project OECD Nuclear Energy Agency (OECD NEA) International Workshop

Paris, 20 January 2016

Olivier Durand-Lasserve

(OECD/ENV - IEA/STO)

Work coordinated by Rob Dellink, Jean Chateau and Elisa Lanzi

(OECD/ENV)

OUTLINES

Economic consequences of Climate Change 2

Introduction to CIRCLE 1

Elements on water scarcity for power generation 4

Discussion 5

Economic cost of air pollution 3

-Regional & sectoral GHG mitigation costs: impact on GDP, sectoral value

added, real income

-Assessment with Computable General Equilibrium model (CGE) allows to

account wide rage of reallocation mechanisms, input substitution, sectoral

reallocation, change in international trade…

3

Environmental outlook to 2050

0

50

100

150

200

250

300

350

400

450

2010 2015 2020 2025 2030 2035 2040 2045 2050

Index 2010=100

Baseline

450 ppm core scenario

GDP -5.5%

GHG emissions -69.5%

GDP

GHG emissions

• CIRCLE project : Costs of Inaction and Resource scarcity: Consequences for

Long-term Economic growth

• Aims to include the feedback of environnemental damages on economic

growth

– Regional and sectorial costs of inaction assess with CGE, based on

collaboration with several expert groups

– Use GDP as key indicator of economic growth

– Qualitative assessment to complete the picture

– Wide collection of damages are considered: climate change, land and water

scarcity, air pollution

4

CIRCLE project

5

CIRCLE project themes and tracks

Climate change

Modelling track Air pollution

Land-water-energy nexus

Water

Scoping track Biodiversity and ecosystems

Resource scarcity

OUTLINES




Discussion 5

Economic cost of Air pollution 3

• Aim: assess the economic consequences of

climate change

• Until 2060, multi-sector, multi-region

General Equilibrium production function

approach: climate change affects drivers of

growth

• After 2060, stylised Integrated Assessment

Model approach

• Collaboration with several expert groups, incl.

FEEM, CERE, NIES

7

Introduction

Selected impacts of climate change

8

• Agriculture: yield changes for 8 crop sectors, and fisheries

• Coastal zones: capital and land losses due to sea level rise

• Health: diseases and labour productivity losses from heat stress

• Energy demand

• Tourism demand

• Capital damages from hurricanes

Included in the modelling

• Fatalities from heatwaves

• Urban damages from river floods

• Ecosystems: biodiversity (crude approximation)

Stand-alone analysis

• Large-scale disruptive events, …

Still not quantified

9

Global importance of different impacts

Source: ENV-Linkages calculations

Global GDP loss:

0.3-1.0% 1.0-3.3%

Agriculture

Coastal Zones

Energy Demand

Extreme Precipitation

Events

Health

Tourism Demand

Global damages 2060

Agriculture

Coastal Zones

Energy Demand

Extreme Precipitation

Events

Health

Tourism Demand

Global damages 2035

10

Regional cost of selected climate

impacts


Uncertainty ranges in 2060 due to uncertainty in ECS

-7%

-6%

-5%

-4%

-3%

-2%

-1%

0%

2010 2020 2030 2040 2050 2060

- South & South East Asia

OECD Pacific

Rest of Europe & Asia

OECD Europe

Latin America

OECD America

World

- Sub Saharan Africa

Middle East & North Africa

Main messages (I)

1. Almost all regions significant negative market and

non-market impacts, plus downside risks

– Global GDP cost 1.0-3.3% by 2060, 2-10% by 2100

– Largest losses in Africa and Asia

– Largest losses from health and agricultural impacts

– Largest losses to capital and labour

– Costs increase more than proportionately with temperature

2. Losses spread across economies

– All sectors and regions are indirectly affected

3. Consequences are unavoidable and enduring

– Emissions commit the world to long-lasting impacts

11

Main messages (II)

4. Ambitious adaptation and mitigation can reduce

future impacts and limit risks

– Ambitious policies can reduce macroeconomic costs by

2100 from 2-10% to 1-3%

– Adaptation is important to ensure consequences of climate

change remain limited

– Ambitious global mitigation can help avoid half of the

economic consequences and limit downside risks

– Distribution of policy costs and benefits across regions and

sectors will not be proportional (but both imply a shift

towards more services)

12

OUTLINES




Discussion 5

Economic cost of Air pollution 3

14

Local air pollution in CIRCLE:

methodology

1. Projections Of Air Pollutant Emissions

2. Concentrations Of Air Pollutants

3. Impacts on Human Health

(Hospital admissions, sick days, premature deaths…)

4. VALUATION

5. Macroeconomic Impacts Of Air Pollution

(In ENV-Linkages)

Market Impacts • health expenditures

• labour productivity

Non-Market Impacts • value of lives lost, using VSL

• costs of pain and suffering

5. Welfare Impacts Of Air Pollution

(Separately)

OUTLINES




Discussion 5


Power generation

• Hydroelectric & thermoelectric (TE) plants

• Mostly water withdrawal (not consumption)

• Limited power trade & need for stable supply

Water for Energy

Energy Land

Energy

Water

Agriculture

Economic activities

Resource

Power

generation,

fossil fuels

extraction

Biofuels

Land

use

discharges,

pollution,…

Water

Fossil fuels

• Cons. & withdrawal for extraction &

processing

• Fossil resources available become

more water intensive (e.g. shale oil & gas)

• International trade (->virtual water trade)

Biofuels

• Water consumption, dep. types of crops

• Role of energy & env. policies

• International trade (->virtual water trade)

Power supply &

transportation

Power demand

Climate change

Water policies

Megatrends

Environmental policies

Socioeconomic drivers

Population & GDP

IT technologies

(+) quantity &

quality of supply

T° increase

Change in rainfall

Seasonal variations

Extreme events

Uncertainty

(-) quantity

TE plant cooling

system standards

(-) TE dependence on

water

(+) cooling

(-/+) pumping in

agric)

(-/+) annual load

(-/+) peak load

(-) hydro, (-) TE (-/+)

capacities

(-) hydro, (-) TE capacities

(+/-) seasonal H &

(+ ?) grid security

Energy conservation

Renewable (wind, sol...)

Efficiency standards

Local air protection

(+) hydro, (-) TE

dependence

(-) dependence on TE

(+) PG in less populated

areas

Climate change

Country level: ways to generate electricity

with less water, example in the US

0

0.5

1

1.5

2

2.5

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

(TK

Wh

)

Fossil fuel based electrcity generation in the US

Coal Gas Nuclear Oilsource: IEA extended energy balances 2014

0

50

100

150

200

250

300

350

400

450

500

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Bga

l/d

Water withdrawal by use in the US

Thermoelectric power Other usessource: USGS Water Use Data for the Nation

Reduced water withdrawal from thermoelectric generation:

-Cooling technologies: phase out of once-through systems

-Plant efficiency

But stress at the sub-national level

-South West US (DOE, 2012)

-No disruption but power provided to final consumers at a higher cost

Competition with other activities: urban demand, shale oil and gas,…

Cost for the power sector?

• PG technologies and water intakes

• Interconnections

• Response to water scarcity

• Uncertainty

>Need for detailed power generation model

Cost for the whole economy?

• Production function approach?

• Cost of disruption (with VOLL)?

• Cost for reducing the risk of disruption?

• Opportunity cost of reduced future access?

>How to get these notions in ENV-Linkages?

Assessment at the global level? Water demand for energy (Davies et al; 2013, Kyle et al., 2012 ) but no macroeconomic cost

How to assess macroeconomic costs of

water scarcity through power generation?

OUTLINES




Discussion 5


THANK YOU!

For more information:

www.oecd.org/environment/CIRCLE.htm

www.oecd.org/environment/modelling

[email protected]

APPENDIX

22

• Collaboration with existing impact studies

– Methodology largely based on the FEEM ICES model

– Data for a subset of damages from sectoral EU projects, obtained

with help of FEEM

– Additional data from range of collaborators, incl. NIES, VU

University Amsterdam, IIASA, IPTS-JRC

– Data consistency on damages is ensured by choosing damages

corresponding to an appropriate temperature pathway (no simple

damage functions relating everything to global T)

• Damages calculated in ENV-Linkages model to 2060

– Autonomous adaptation takes place via sectoral adjustments and

international trade

• Stylised calculations with AD-DICE to 2100

– Baseline and damages to 2060 harmonised with ENV-Linkages

Methodology for climate damages

23

-5.0%

-4.0%

-3.0%

-2.0%

-1.0%

0.0%

1.0%

2.0%

Can

ada

Ch

ile

Me

xico

USA

EU la

rge

4

Oth

er O

ECD

EU

Oth

er O

ECD

Au

s. &

New

Z.

Jap

an

Ko

rea

Ch

ina

No

n-O

ECD

EU

Ru

ssia

Cas

pia

n r

egi

on

Oth

er E

uro

pe

Bra

zil

Oth

er L

at.A

m.

Mid

dle

Eas

t

No

rth

Afr

ica

ASE

AN

9

Ind

on

esi

a

Ind

ia

Oth

er A

sia

Sou

th A

fric

a

Oth

er A

fric

a

OECD America OECD Europe OECD Pacific Rest of Europe and Asia LatinAmerica

MiddleEast &NorthAfrica

South- and South-EastAsia

Sub-Saharan

Africa24

Regional results and uncertainty from

climate sensitivity – year 2060


-14.0%

-12.0%

-10.0%

-8.0%

-6.0%

-4.0%

-2.0%

0.0%

2.0%

4.0%

Can

ada

Ch

ile

Me

xico

USA

EU la

rge

4

Oth

er O

ECD

EU

Oth

er O

ECD

Au

s. &

New

Z.

Jap

an

Ko

rea

Ch

ina

No

n-O

ECD

EU

Ru

ssia

Cas

pia

n r

egi

on

Oth

er E

uro

pe

Bra

zil

Oth

er L

at.A

m.

Mid

dle

Eas

t

No

rth

Afr

ica

ASE

AN

9

Ind

on

esi

a

Ind

ia

Oth

er A

sia

Sou

th A

fric

a

Oth

er A

fric

a




Sub-Saharan

Africa

-14.0%

-12.0%

-10.0%

-8.0%

-6.0%

-4.0%

-2.0%

0.0%

2.0%

4.0%

Can

ada

Ch

ile

Me

xico

USA

EU la

rge

4

Oth

er O

ECD

EU

Oth

er O

ECD

Au

s. &

New

Z.

Jap

an

Ko

rea

Ch

ina

No

n-O

ECD

EU

Ru

ssia

Cas

pia

n r

egi

on

Oth

er E

uro

pe

Bra

zil

Oth

er L

at.A

m.

Mid

dle

Eas

t

No

rth

Afr

ica

ASE

AN

9

Ind

on

esi

a

Ind

ia

Oth

er A

sia

Sou

th A

fric

a

Oth

er A

fric

a




Sub-Saharan

Africa

OECD America OECD Europe OECD Pacific Rest of Europe and Asia Latin

America

Middle East &

N. Africa South and South-

East Asia

Sub-Saharan

Africa

25

Long-term damages

Source: AD-DICE calculations

-14%

-12%

-10%

-8%

-6%

-4%

-2%

0%

2010 2015 2020 2025 2030 2035 2040 2045 2050 2055 2060 2065 2070 2075 2080 2085 2090 2095 2100

Likely uncertainty range - central projection until 2100


Central projection until 2100


Weitzman damage function-14%

-12%

-10%

-8%

-6%

-4%

-2%

0%

2010 2015 2020 2025 2030 2035 2040 2045 2050 2055 2060 2065 2070 2075 2080 2085 2090 2095 2100




Central projection until 2060 (Committed by 2060)

Weitzman damage function-14%

-12%

-10%

-8%

-6%

-4%

-2%

0%

2010 2015 2020 2025 2030 2035 2040 2045 2050 2055 2060 2065 2070 2075 2080 2085 2090 2095 2100




Central projection until 2060 (Committed by 2060)

Weitzman damage function

26

Damages with policy controls

Source: Preliminary AD-DICE calculations

-10%

-9%

-8%

-7%

-6%

-5%

-4%

-3%

-2%

-1%

0%

2010 2015 2020 2025 2030 2035 2040 2045 2050 2055 2060 2065 2070 2075 2080 2085 2090 2095 2100

Likely uncertainty range - no policies

Likely uncertainty range - optimal policies

Central projection - no policies

Central projection - optimal policies-10%

-9%

-8%

-7%

-6%

-5%

-4%

-3%

-2%

-1%

0%

2010 2015 2020 2025 2030 2035 2040 2045 2050 2055 2060 2065 2070 2075 2080 2085 2090 2095 2100

Likely uncertainty range - no policies

Likely uncertainty range - optimal policies

Central projection - no policies

Central projection - optimal policies

27

Sectoral damages and mitigation costs


0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Damages Mitigation - global tax

Other services

Transport & Construction

Other industries

Energy-int. industries

Energy production

Agriculture

28

No-damage baseline GDP projection


29

Global damages under optimal

mitigation – alternative discounting rules

Source: AD-DICE calculations

-4.5%

-4.0%

-3.5%

-3.0%

-2.5%

-2.0%

-1.5%

-1.0%

-0.5%

0.0%

2010 2015 2020 2025 2030 2035 2040 2045 2050 2055 2060 2065 2070 2075 2080 2085 2090 2095 2100

Likely uncertainty range - Nordhaus discounting (DICE2013)

Likely uncertainty range - UK Treasury discounting

Likely uncertainty range - Stern discounting

Central projection - Nordhaus discounting (DICE2013)

Central projection - UK Treasury discounting

Central projection - Stern discounting

Europe France (IEA, 2012); Central Europe (Rübbelke and Vögele,

2011)

Australia: increased water withdrawal for power generation in water

stressed areas (Smart and Aspinall, 2009)

China: Power generation in regions with water scarcity, adoption of dry

cooling + (shale resources in water scarce areas) (IEA, 2012)

India: seasonal variations drought and heat waves create high demand

and low supply (IEA, 2012; Bhattacharya and Mitra, 2013)

Sub Saharan Africa: uncertainty on water flows increases the cost of

developing that hydro capacities (Cervigni et al 2015)

Howe local circumstances matter:

Hotspots and bottlenecks

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