Sector-wide Estimation of Economic Impacts of Climate Change Considering Variations in Exposure and Vulnerability

Represented by SSP Scenarios

Twelfth Annual Meeting of the IAMC 2019, Tsukuba, Japan

Jun’ya Takakura1, Shinichiro Fujimori2, Naota Hanasaki1Tomoko Hasegawa3, Yasushi Honda4, Toshichika Iizumi5, Chan Park6

Kiyoshi Takahashi1, Qian Zhou7 and Yasuaki Hijioka1

1 National Institute for Environmental Studies, Tsukuba, Japan2 Kyoto University, Kyoto, Japan3 Ritsumeikan University, Kusatsu, Japan4 University of Tsukuba, Tsukuba, Japan5 National Agriculture and Food Research Organization, Tsukuba, Japan6 University of Seoul, Seoul, Korea7 North China Electric Power University, Beijing, China

1

Introduction

• Risk of climate change depends on exposure and vulnerability as well as hazards.• Socioeconomic scenarios are needed for impact modeling to represent exposure and

vulnerability.• SSP have been widely used in studies in climate-change impacts. However, sector-wide

comparison and aggregation were difficult due to methodological inconsistency amongstudies.

IPCC AR5 WG2 SPM

2

Sector-wide assessment

Multi-sector impact assessments under the unified framework• same scenario sets• same climate models• same economic model• covering 9 (6 +3) sectors

Takakura et al. (2019)

3

Overview

RCP

Future climate

Hot world

2℃ target

RCP8.5RCP6.0RCP4.5RCP2.6

SSP1: SustainabilitySSP2: Middle of the roadSSP3: Regional rivalrySSP4: InequalitySSP5: Fossil-fueled development

Climate model(ISIMIP’s 5GCMs)

Crop model

Hydrology model

Health model

・・・

GHG concentration

Population, GDP, Technology level, etc.

・・・GDP loss

Crop productivity

Water resource

Mortality/Morbidity

AIM/CGEmodel

SSP

Challenge for adaptation

Chal

leng

efo

rm

itiga

tion

SSP1

SSP5

SSP2

SSP3

SSP4CO2

emiss

ion

Glob

al m

ean

tem

pera

ture

rise

Bio/physical models Economic model

4

Included sectors

Sector Rationale Published paperAgricultural productivity Climate will affect agricultural productivity. Fujimori et al. (2018)

Sustainability

UndernourishmentChanges in food prices due to agricultural productivity change will worsen food access and mortality/morbidity because of hunger.

Hasegawa et al. (2016) Climatic Change

Cooling/heating demand

Higher temperature will increase cooling demand while decrease heating demand.

Park et al. (2018)Environ. Res. Lett.

Occupational-health cost

Workers’ exposure to heat will limit the capacity of labor activity and productivity.

Takakura et al. (2017)Environ. Res. Lett.

Hydropower generation

Changes in precipitation will change the water resources that can be used for hydropower generation.

Zhou et al. (2018)Climatic Change

Thermal power generation

Changes in river flows will change the water resources that can be used cooling thermal power generation plants.

Zhou et al. (2018)Energies

Assessment of additional 3 sectors (heat-related excess mortality, fluvial flooding, and coastal inundation) were also done, but their results have not been connected with the AIM/CGE model.

5

Considered scenarios

SSPs

SSP1SSP2SSP3SSP4SSP5

RCPsRCP2.6RCP4.5RCP6.0RCP8.5

GCMsGFDL-ESM2MHadGEM2-ES

IPSL-CM5A-LRMIROC-ESM-

CHEMNorESM1-M

× ×

Socioeconomicpathways

Emissionpathways

Climatemodels

• Total of 100 (5×4×5) scenario runs for each sector• Impact of climate-change mitigation were not considered

(focusing only on the impact of climate change).• Only autonomous adaptations were considered.• Inter-sectoral interactions were not considered.

6

Modeling

7

Incorporation of SSP scenarios

Economic model

(AIM/CGE)

Bio/physicalimpact models

SSP

（1） Socioeconomic assumptions were fed into the bio/physical impact models

Climate EconomicImpact

（2） Socioeconomic assumptions were fed into the economic model

（1） （2）

8

Research framework (Agricultural productivity)

SSPscenarios

RCPscenarios

Land usemodel

AIM/CGEmodel

Generalcirculation

models

Climateconditions

Cropproductivity

GDP loss

Land use

AIM/CGEmodel

(off-line)

Cropmodel

Technology level(represented byGDP per capita)

Changes in crop yields associated with climate change are computed with the crop yield model (CYGMA).

CYGMA is a biophysical global gridded crop model that can explicitly consider

- changes in agronomic technology- management driven by economic growth- changes in the biophysical response of a

crop to environmental conditions

The grid-cell simulated yields were aggregated into regions considering land use, and input to the AIM/CGE model.

9

Research framework (Undernutrition)

SSPscenarios

RCPscenarios

Land usemodel

AIM/CGEmodel

Generalcirculation

models

Climateconditions

Cropproductivity

Incomedistribution

Foodprice

Number ofpeople at

risk of hunger

Expenditurefor medical care

Mortality

GDP loss

Morbidity

Land use

AIM/CGEmodel

(off-line)

Population andLabor stock

Cropmodel

Non-marketvalue of lives lost

Value ofstatistical life

Technology level(represented byGDP per capita)

Income level(GDP per capita)

Climate change (agricultural productivity change) will affect food prices and food access → undernourishment

Prevalence of undernutrition, mortality and morbidity were estimated based on the calculated income distribution and food price.

Associated economic loss were computed with the AIM/CGE model with consideration of changes in

- labor force- population- expenditure for healthcare.

10

Research framework (Cooling/heating demand)

SSPscenarios

RCPscenarios

AIM/CGEmodel

Generalcirculation

models

Climateconditions

Economicactivity level

GDP loss

ACpenetration rate

Cost forAC device

installation

Energydemand for

cooling/heating

Populationdistribution

Technology andpro-environmental

mind level

Income level(GDP per capita)

Climate change will increase cooling demand and decrease heating demand.

We considered both the cost of cooling/heating energy use and the cost of cooling/heating device installation and management.

Energy demand for cooling/heating was calculated as a function of cooling/heating degree days, socioeconomic conditions, and economic activity level

11

Research framework (Occupational-health cost)

SSPscenarios

RCPscenarios

AIM/CGEmodel

Generalcirculation

models

Climateconditions

GDP loss

ACpenetration rate

Populationdistribution

Indoor laborproductivity

Outdoor laborproductivity

Income level(GDP per capita)

Workers’ exposure to heat can cause economic loss by reduction of the per-hour workable time (labor capacity).

The labor capacity was calculated from the estimated heat stress index (WBGT) and used as the labor productivity coefficient in the AIM/CGE model.

Different assumptions were used for the different industrial sectors and socioeconomic conditions

- work location (indoor or outdoor)- intensity of work- availability of air conditioners

12

Research framework (Hydropower generation)

SSPscenarios

RCPscenarios

AIM/CGEmodel

Generalcirculation

models

Climateconditions

GDP loss

Waterdemands

AIM/CGEmodel

(off-line)

Hydrologicalmodel

Upper boundaryof hydroelectric

genera�on capacity

Theoreticalhydroelectric

generation potential

The hydroelectric power generation capacity will be affected by changes in precipitations.

The grid-based theoretical hydroelectric power potential was projected using the H08 global hydrological model.

Variations in theoretical hydroelectric power potential were assumed to lead to the hydropower generation potential variation.

13

Research framework (Thermal power generation)

SSPscenarios

RCPscenarios

AIM/CGEmodel

Generalcirculation

models

Climateconditions

GDP loss

Waterdemands

AIM/CGEmodel

(off-line)

Hydrologicalmodel

Capital productivityof thermal powergeneration sectors

Cooling watersufficiency forthermal power

genera�on

Lower river flow causes cooling water shortages leading to changes in the usable thermal power generation capacity.

We used the H08 global hydrology model to calculate the magnitude of regional usable capacity changes.

Cooling water shortage index were assumed to affect the thermal power generation potential.

14

Results

15

Overall results (sector by sector)

Agriculturalproductivity

Undernourishment

Cooling/heatingdemand

Occupational-healthcost

Hydropowergeneration

Thermal powergeneration

GD

P lo

ss ra

te co

mpa

red

to n

o-cl

imat

e-ch

ange

cond

ition

(%)

SSP1 SSP2 SSP3 SSP4 SSP5

• Great divergences in the simulated economic impact among sectors both- magnitudes- how sensitive to

socioeconomic conditions

• Larger impacts are expected under SSP3.

• Relatively smaller impacts are expected under SSP1 or SSP5.

period:2080-2099

16

Aggregated economic impacts (global)

• Aggregated economic impact equivalent to- 6.6% (3.9–8.6%) of the global total GDP @ SSP3-RCP8.5- 0.8% (0.5–1.2%) @ SSP1-RCP2.6 and 0.8% (0.4–1.2%) @ SSP2-RCP2.6

• In global scale, modification of the impacts by the variation in SSP is modest.

Takakura et al. (2019)

boxplot period:2080-2099

17

Aggregated economic impacts (regional)

• Larger impacts for developing regions such as Asia and Africa• All regions are more adversely affected under SSP3• Adverse effects are concentrated in developing regions under SSP4• While the results are consistent with the SSP storyline, socioeconomic development

alone does not cancel the impacts of climate change without the stringent mitigation.

Takakura et al. (2019)period:2080-2099

18

Unmet challenges in modeling

Adaptation• We considered only autonomous adaptation, e.g.,

- reduction of vulnerability due to increase in the income level- changes in the industrial structure- economy’s response to the shock through the market mechanisms represented by the AIM/CGE model.

• Non-autonomous adaptation is difficult to model and is not considered.

Interaction• We ran the model sector by sector.

- possible interactions among sectors were not incorporated.• Incorporating multi-sector ‘shocks’ into the CGE model simultaneously is possible,

but it will induce greater uncertainty in the results and it will be harder to interpret and validate.

19

Concluding remarks

• We have conducted impact assessments under the unified scenarios by using the same modeling framework.- sector-wide, process-based, bottom-up approach considering variations in exposure and vulnerability represented by SSP scenarios

• While the results showed modification of impacts by SSPs, socioeconomic development alone does not cancel the impacts of climate change. Climate-change mitigation and proactive adaptations are inevitable to minimize the impacts.

• If we consider proactive adaptations to climate change and their differences in difficulties to implement the adaptation measures among SSPs, the results may differ from the current one. Further model developments and analysis particularly focusing on adaptation are necessary to plan and implement effective adaptation measures.

ご清聴ありがとうございました

Asia-Pacific Integrated Modelhttp://www-iam.nies.go.jp/aim/index.html

This research was supported by the Environment Research andTechnology Development Fund (S-14) of the EnvironmentalRestoration and Conservation Agency of Japan.