national institute for environmental studies (nies) tomoko

National Institute for Environmental Studies (NIES)Tomoko Hasegawa, Shinichiro Fujimori,Kiyoshi Takahashi and Toshihiko Masui

1The 20th AIM international workshop,

Tsukuba, January 23-24, 2015

Hasegawa, T., Fujimori, S., Takahashi, K., Masui, T., 2015. Scenarios for the risk of hunger in the twenty-first century using Shared Socioeconomic Pathways. Environmental Research Letters 10, 014010.

Article URLhttp://iopscience.iop.org/1748-9326/10/1/014010

Background• Climate change would increase the number of malnourished children.

• The climate impacts strongly depend on population and GDP.– Based on the SRES and CMIP3; Need updated.– Only population and GDP were considered; other socioeconomic indicators could be considered.

• A new interdisciplinary scenario framework (SSP+RCP) has recently been designed for climate change research.

• Scenarios for various fields (e.g. water use) have been developed based on SSPs.– No scenarios for risk of hunger consistent with SSPs have been developed.

2

Introduction

Objectives

1. Develop 21st‐century scenarios for the risk of hunger consistent with SSPs as a baseline of climate impact research on agriculture

2. Identify the elements strongly affecting future risk of hunger

• 7 socioeconomic indicators were considered:– Population, demographic change, GDP, equality of food distribution, crop yields, irrigation area, land productivity of livestock and wood products

3

Introduction

Shared Socioeconomic Pathways

4

Low population growth; high economic growth;high levels of education

and governance; globalization, international cooperation, technological

development, and environmental awareness.

Rapid population growth; Moderate economic growth; low levels of education and

governance; Regionalization;low environmental

awareness.

Low population growth; high economic growth;

high human development; low environmental awareness.

Method

Based on O’Neill et al. (2014)

A mixed world, with rapid technological

development in high income countries. In other regions, development proceeds

slowly. Inequality remains high.

• Economic model• Fundamental idea: • supply = demand, • balanced by price mechanism

Population & income growthIncrease in food demandIncrease in food priceProducers: increase in production (cropland expansion, yield growth)Consumers: decrease in consumption; shift to less expensive goods

AIM/CGE (Computable General Equilibrium)

Price

Quantity

Supply curveDemand curve

5

Domestic distribution of food energy(FAO,2008)

Method

Parameters related to food and hunger

6

Method

AIM/CGE

Parameters:Population, demographic changeGDPEquality of food distributionCrop yieldIrrigation areaLand productivity of livestock and wood productsIncome elasticity of food demandPrice elasticity of land use changePrice elasticity of trade

Endogenous variables:Food consumptionMeat consumptionLand use (Cropland, pasture, forest)

Each parameters were determined from the adaptation viewpoint

Hasegawa et al. 2015

7

AIM/CGE

Parameters:Population, demographic changeGDPEquality of food distributionCrop yieldIrrigation areaLand productivity of livestock and wood productsIncome elasticity of food demandPrice elasticity of land use changePrice elasticity of trade

Endogenous variables:Food consumptionMeat consumptionLand use (Cropland, pasture, forest)

Three approaches for assuming parameters1. Based on observed data

(Stylized fact)2. Based on existing studies3. Assumed in line with SSP

storylines if neither were available.

Method

Parameters related to food and hunger

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0 20000 40000 60000 80000

Coefficient of v

ariatio

n (CV) of the

dom

estic

distrib

ution of dietary ene

rgy consum

ption

GDP per capita [US$, 2005]

observed data

Optimistic

Median

Pessimistic

0.134

0.109 2

0.054

0.6894

0.6531 (Observed data; 0.61)

0.4609

y x

y x R

y x

−

−

−

= ⋅

= ⋅ =

= ⋅

Comparison with observed data:the improved equality of food distribution with income growth

8

Intermediate

Pessimistic

Optimistic

Equality

Inequality(2005)

Method


0

100

200

300

400

500

600

700

800

0 20000 40000 60000 80000

Meat‐ba

sed calorie

intake

[kcal/da

y/cap]

income [US$/person]

observed dataOptimisticMediumPessimistic

2

60.0 ln 399.8

87.8 ln 545.3(Observed data; 0.57)130 ln 833.0

y x

y x Ry x

= ⋅ −

= ⋅ − == ⋅ −

Comparison with observed data:increased meat consumption with income growth

9

(1980 ‐ 2009)

Intermediate

Pessimistic

Optimistic

Method


0500

1000150020002500300035004000

2005

2010

2020

2030

2040

2050

2060

2070

2080

2090

2100

Carolie intake [kcal /pe

rson

/day]

The 21st‐century Scenarios of risk of hunger using SSPs

10

Food consumption per capita

0

2000

4000

6000

8000

10000

12000

SSP1 SSP2 SSP3 SSP4 SSP5

2005 2100

Land

use [M

ha] Food crops

Pasture

Grassland

Managed forest

Primary forest

SSP1SSP2SSP3SSP4SSP5

Land use change

Population at risk of hunger

Results

0100200300400500600700800900

2005

2010

2020

2030

2040

2050

2060

2070

2080

2090

2100

Popu

latio

n at risk of h

unger

[million]

SSP3

SSP4

SSP2

SSP5

SSP1


Decomposition analysisWhat strongly affects future risk of hunger?

• Change in hunger risk was decomposed into three factors;

11

Change in pop. at risk of hunger

= ＋＋＋Residual Population growth

Inequality of food distribution

Food consumption

＊See discussion paper for more detail @http://www.nies.go.jp/social/dp/dpindex.html.

Method

12

Factors affecting future hunger risk(global, at 2005 level)

• Population, inequality of food distribution causes large differences in hunger risk among SSPs

‐1500

‐1000

‐500

0

500

1000

2005 2020 2035 2050 2065 2080 2095

Change in pop

ulation at risk of

hunger [m

illion]

a) SSP1

‐1500

‐1000

‐500

0

500

1000

2005 2020 2035 2050 2065 2080 2095Ch

ange in pop

ulation at risk of

hunger [m

illion]

b) SSP2

‐1500

‐1000

‐500

0

500

1000

2005 2020 2035 2050 2065 2080 2095

Change in pop

ulation at risk of

hunger [m

illion]

c) SSP3

‐1500

‐1000

‐500

0

500

1000

2005 2020 2035 2050 2065 2080 2095

Change in pop

ulation at risk of

hunger [m

illion]

d) SSP4

‐1500

‐1000

‐500

0

500

1000

2005 2020 2035 2050 2065 2080 2095

Change in pop

ulation at risk of

hunger [m

illion]

e) SSP5residual

per‐capita calorie(domestic production)inequality of food distribution

population

net change

Result


• 21st‐century risk of hunger differs among SSPs• Regional distribution depends greatly on population growth, equality in food

distribution and increase in food consumption• Regions with greater population

growth face higher risk of hunger.

Regional population at risk of hunger and its factors (SSP3, 2100）

Hasegawa et al. in review

The most pessimistic scenario (SSP3)

Rest of Africa, 39%

India, 23%

Rest of Asia, 16%Middle

East

Southeast Asia

Rest of South America

China Brazil North Africa Former

Soviet Union

0100200300400500600700800900

2005

2010

2020

2030

2040

2050

2060

2070

2080

2090

2100

Popu

latio

n at risk of h

unger

[million]

SSP3

SSP4

SSP2

SSP5SSP1

‐500

‐250

0

250

500

Chan

ge in

pop

ulation at risk of

hunger [m

illion]

residual

trade

per‐capita calorie

inequality of fooddistribution

population

(Relative to 2005)

Comparison of the population at risk of hunger with existing studies

14

• Pop. at risk of hunger in this study was lower than in existing studies.

• Improvements in food distribution equality was considered in this study whereas it was not for existing studies.

• Inequality of food distribution influences long‐term assessments of hunger risk.

0

200

400

600

800

1000

1200

1990 2020 2050 2080

Popu

latio

n at risk of h

unger [million]

A1A2B1B2

• Lines: this study• Dots: existing studies

Result & discussion

SSP3

SSP4

SSP2

SSP5

SSP1


ConclusionWe developed scenarios for hunger risk in the 21stcentury using SSPs. Factors affecting future hunger risk were investigated.

• Risk of hunger without climate change in the 21stcentury differed among SSPs

• Factors influencing the future reduction of hunger risk were population, inequality of food distribution, and per‐capita food consumption.

• Inequality of food distribution greatly influences long‐term assessments of hunger risk.

15

Conclusion

Thank you for your attention!

16

AcknowledgmentsThis research was supported by the Environment Research andTechnology Development Fund (2–1402) of the Ministry of theEnvironment, Japan, and the climate change research program of theNational Institute for Environmental Studies.

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