Economic Information Sharing Mechanism of the Asia-Pacific (EiSMAP)
Projection of Environmental Risks in Projection of Environmental Risks in AsiaAsia--Pacific RegionPacific Region
October, 25October, 25thth 20072007
Yuzuru MatsuokaYuzuru MatsuokaGraduate School of EngineeringGraduate School of Engineering
Kyoto UniversityKyoto University
1.1. Impacts of Climate ChangeImpacts of Climate Change2.2. Projection of environmental risks Projection of environmental risks 3.3. Final remarksFinal remarks
Model family of Asia Pacific Integrated Models (AIM)Model family of Asia Pacific Integrated Models (AIM)
AIM/CountryIntegrated national
scale model for Environmental policy
AIM/LocalLinkage model
between regional emission and
economic activity
AIM/ClimateAtmospheric model
UD Ocean modelRadiative forcing modelGCM,RegCM interface
AIM/EnduseDetailed bottom-up type
energy service and energyconsumption model
AIM/EnergyGlobal multi-regional energy
supply model
AIM/MaterialMaterial balanced
Economic CGE model
AIM/Emission
AIM/CGEGlobal multi-regional CGE and process-based hybrid
model
Global Model
AIM/DatabaseAIM Family
AIM/Impact AIM/Land AIM/Air AIM/Water AIM/Agriculture AIM/Vegetation AIM/Health Etc.
AIM/EconometricsWorld Econometric model
for middle-term projection
AIM/LinkageAIM/Bottom-upAIM/Energy-EconomicsAIM/Land-Equilibrium
Other modeling activity
GCMsDGVMs
IPCC
GEO
MA
EMF
IEA
Other projects
Inter-governmental
Panel of Climate Change
Global Environmental
Outlook
Millennium Ecosystem
Assessment
Energy Modeling
Forum
International Energy Agency
1. Scenario analysis of GHGs emission, Climate Change, and its Impacts2. Scenario analysis of environment change caused by anthropogenic intervention3. Identify feasible and efficient counter-measures for environment protection
Four Scenarios to explore Future environmental risk(adopted in Global Environmental Outlook 3)
1990 2020 2050Population in Million 2798 4008 4696
GNP/GDP(mex) in TrillionUS$90 1.5 13.2 41.8
GNP/GDP(ppp) in Trillion(1990 prices) 5.3 22.4 49.3
Final Energy by Fuel in EJNon-commercial 24.2 13.2 6.7
Solids 18.5 27.8 16.7Liquids 12.6 59.8 112.0
Gas 1.5 8.7 22.0Electricity 4.1 24.1 69.8
Other (e.g H2) 0.6 10.2 24.8Total 61.5 143.8 252.0
Primary Energy by FuelCoal 29.8 47.4 47.7Oil 15.3 62.6 92.8
Gas 2.8 30.9 55.4Nuclear 0.3 3.7 20.9Biomass 24.3 28.0 46.1
Other Renewables 1.1 12.3 42.6Synfuel Trade 0 0 13.5
Total 73.6 184.9 319.0
Coal 0.0 1.2 2.7Oil 0.0 1.0 3.3
Gas 0.0 0.3 1.5
CO2 (as C) in GtC 1.2 3.1 4.2Other CO2 (as C) in GtC 0.3 0.3 -0.1Total CO2 (as C) in GtC 1.5 3.4 4.1
CH4 total (as CH4) in Mt CH4 127.1 222.6 265.9N2O total (as N) in Mt N2O-N 2.3 2.7 2.4
SOx total (as S) in MtS 17.3 31.3 24.4CO (as CO) in Mt CO 276.5 422.3 550.9
VOCs in Mt 47.8 75.3 92.2NOx (as N) in MtN 6.2 15.6 23.0
Anthropogenic Emissions
Cumulative Resource Use in ZJ
Market First scenario (MK): Market-driven developments coverage on the values and expectations that prevail in industrialized countries
Policy First scenario (PO): Strong actions are undertaken by governments in an attempt to reach specific social and environmental goals
Security First scenario (SC): Disparities, inequality and conflict are not improved, which are brought about by socio-economic and environmental stresses
Sustainability First scenario (SF): A world in which a new development paradigm emerges in response to the challenge of sustainability, supported by new, more equitable values and institutions.
Major parameters in B2 scenarioIn Asia Pacific region (except Japan)
Changes in runoff calculated under BaU scenario
-100 -10 0 10 100 (mm/year)
CCC
ECHAM4 CCSR/NIES
- Mean runoff changes between 1980s and 2050s
- Based on the results of the transient experiments of the CCC, ECHAM4, and CCSR/NIES climate models
Increase in northern high latitude region, Indian continent, and Bengal bayConfused results in mid-ChinaDecrease in South Europe, Central plain and Brazilian Plat.
-500 0 +500 (kg/ha)
Change in the potential productivity of rice from 1990 to 2050 under the BaU scenario and stabilization scenarios
-20
-15
-10
-5
0
2000 2050 2100
Potential productivity change in rice (%)
-20
-15
-10
-5
0
2000 2050 2100
Thailand-20
-15
-10
-5
0
2000 2050 2100
India
Brazil
BaU
GHGs 550ppmCO2eq
GHGs 475ppmCO2eq
Potential productivity change in rice (%)
Potential productivity change in rice (%)
Change of potential productivity of rice
in the top 10 countries
Mitigation of climate change, not to exceed 2 ℃ from present
0.0
1.0
2.0
3.0
4.0
5.0
1990
2000
2010
2020
2030
2040
2050
2060
2070
2080
2090
2100
2110
2120
2130
2140
2150
2160
2170
2180
2190
2200
Year
Tem
pera
ture
incr
ease
(199
0=0)
BaU GHG-500ppmv GHG-600ppmv
0.0
0.2
0.4
0.6
1990
2000
2010
2020
2030
2040
2050
2060
2070
2080
2090
2100
2110
2120
2130
2140
2150
2160
2170
2180
2190
2200
Year
Sea
leve
l ris
e (m
)
BaU GHG-500ppmv GHG-600ppmv
0
5
10
15
20
1990
2000
2010
2020
2030
2040
2050
2060
2070
2080
2090
2100
2110
2120
2130
2140
2150
2160
2170
2180
2190
2200
Year
CO
2 eq
uiva
lent
em
issi
on(G
tCeq
/yr)
BaU GHG-500ppmv GHG-600ppmv
300
600
900
1200
1990
2000
2010
2020
2030
2040
2050
2060
2070
2080
2090
2100
2110
2120
2130
2140
2150
2160
2170
2180
2190
2200
Year
CO
2 eq
uiva
lent
con
cent
ratio
n(p
pmv)
BaU GHG-500ppmv GHG-600ppmvBaU(SF) BaU(SF)
BaU(SF) BaU(SF)
Regional allocation cap using C&C scheme under the GHG-500ppm case
Carbon price without trading under C&C cap constraint with GHG-500ppm, as compared with the BaU
Change without trading under C&C cap constraint with GHG-500ppm, as compared with the BaU
Economic impacts of GHGEconomic impacts of GHG--500ppm under C&C scheme500ppm under C&C scheme
Selected studies reporting GDP losses (FAR,IPCC WG3)
10~90% range
Less than 3%
0
5
10
15
20
25
30
35
2000 2010 2020 2030 2040 2050
Per C
apita
Em
issi
on (t
-CO
2e/c
apita
)
USACanadaJapanAustraliaNew ZealandW-EUE-EURussiaother CISKoreaChinaIndiaother AsiaMexicoBrazilother LAMEAfrica
• Up to now, I talked about climate change impacts. However it is only a part of concerns from the point of whole Asian environmental risks.
• Besides climate change, risks by unsafe water and sanitation, urban air pollution, and also indoor air pollution from household use of solid fuels are now suffering people’s health.
• Coupling socio-economic scenarios used in climate change projection, and environmental/health impact assessment models in AIM model family, we projected future changes of these risks.
• In order to conduct such assessment work, we need spatially detailed information, e.g. polluters spatial distributions, pollutant transport processesand so on.
Air pollutant emission sources in year 2000
LPSs by cement production LPSs by steel production
LPSs by electricity generationResidential household activity
Emission inventories in year 2000
Emission from Japanand S.Korea is large
0
>10000
NOx(kg/km2)emission
0
>10000
SO2(kg/km2)emission
Emission from East part of China, S.Korea, and India is large
Japan: small Desulfurization technology
Low sulfur fuel
0
>10000
CO2(Mg/km2)emission
Emission from East part of China, S.Korea, Japan, and India is large
0
>1000
NH3(kg/km2)emission
NH3(kg/km2)emission
NH3(kg/km2)emission
Total
Unsafe water a
nd sanitation
Indoor air pollution
Urban air pollution
Climate change
1380
653
522
132
73
939
77503
356
3
117
4637
33
1
181
018
0
0
500
1000
1500
2000
2500M
orta
lity
(000
s)
Factors
Bangladesh, Bhutan, N.Korea, India,Maldives, Myanmar, Nepal
Indonesia, Sri Lanka, Thailand
China, Malaysia, Micronesia, Mongolia, PapuaNew Guinea, Philippines, S.Korea, Viet Nam
Australia, Brunei, Japan, New Zealand, Singapore
year 2000
Excess mortality attributed to1) Unsafe water and insufficient sanitation 2) Indoor air pollution3) Urban air pollution, and4) Climate change
Health risks attributed to environmental factors
year 2000 situation ( estimated by WHO)
Total
Unsafe water a
nd sanitation
Indoor air pollution
Urban air pollution
Climate change
1849
602887
224
137
1225
56
682
482
5
149
3958
51
2
200
019
0
0
500
1000
1500
2000
2500M
orta
lity
(000
s)
Factors
Bangladesh, Bhutan, N.Korea, India,Maldives, Myanmar, Nepal
Indonesia, Sri Lanka, Thailand
China, Malaysia, Micronesia, Mongolia, PapuaNew Guinea, Philippines, S.Korea, Viet Nam
Australia, Brunei, Japan, New Zealand, Singapore
year 2030
1) Unsafe water and insufficient sanitation : decrease 10-20%, far from eradication
2) Indoor and urban air pollution : 40-70% increase mainly caused by population and emission increase
3) Climate change : 50-90% increase caused by the escalation of climate change
BaU scenariokeeping current investments for
next 30 years
Total
Unsafe water a
nd sanitation
Indoor air pollution
Urban air pollution
Climate change
520
38 301
76105
402
4 231
163
4
412
2017
1
70
07
0
0
500
1000
1500
2000
2500M
orta
lity
(000
s)
Factors
Bangladesh, Bhutan, N.Korea, India,Maldives, Myanmar, Nepal
Indonesia, Sri Lanka, Thailand
China, Malaysia, Micronesia, Mongolia, PapuaNew Guinea, Philippines, S.Korea, Viet Nam
Australia, Brunei, Japan, New Zealand, Singapore
year 2030
Excess mortality attributed t1) Unsafe water and
insufficient sanitation 2) Indoor air pollution3) Urban air pollution, and4) Climate change
Policy First ScenarioDoubling of regional Investment/GDP
ratio for next 30 years
1) Unsafe water and insufficient sanitation : nearly eradicated2) Indoor and urban air pollution : 50% decrease3) Climate change : intensive adaptation suppresses increase by
10-40%
Effects of CO2 emission reduction to infant mortality changes An example of co-benefit to air pollution
Increase of infant mortality by PM between 1990 and 2020 (Security First scenario)
Person/km2
PM concentration in ambient air in 2020 (Security First scenario)
2020 2050 2020 2050 2020 2050Cambodia 3,211 4,848 2,166 3,017 4,081 6,559Vietnam 3,620 5,820 1,794 2,251 5,107 8,325Laos 294 452 150 190 389 637China 29,630 44,949 14,477 19,482 40,071 63,610Afghanista 64,867 26,896 62,693 24,117 66,601 29,307India 117,494 191,781 79,017 112,248 156,290 289,783Thai 1,547 2,259 1,097 1,491 1,944 2,927Nepal 3,131 4,586 2,252 3,039 3,941 5,985Pakistan 135,107 149,503 126,227 134,248 142,914 163,305Philippine 6,478 9,819 4,468 6,218 8,310 13,237Bhutan 2,715 2,964 2,556 2,685 2,845 3,213Malaysia 281 397 203 272 345 509Korea, S 1,631 2,623 1,091 1,559 2,161 3,756Taiwan 1,556 2,367 1,072 1,494 2,000 3,205Total 371,562 449,264 299,262 312,310 436,998 594,360
Market First (MK) Policy First (PO)
BaUSecurity First
Projection schemeNo countermeasure assumed except CO2 emission reduction measures
Infant mortality by PM
Global and local policy linkages and their co-benefits
GlobalWarming
Abatement
Acid RainAbatement
Eco-tourismDevelopment
World NatureConservation
WorldResource
Development
WorldResourceRecycling
MarinePollutionControl
Air PollutionControl × ×BiodiversityConservation × × ×Reforestation × × × ×Soil Recovery × ×Food Production ×Recycling × × ×WasteManagement × × ×Water PollutionControl
Air pollutionlink ×
Water ResourceManagement ×
Cou
ntry
/Loc
al P
olic
ies
Global/Regional/Subregional Policies
NaturalResourceRecoverylink
RecyclingPromotion
link
Waterpollution
Preventionlink
BiodiversityProtection
link
Linking and integrating environmental measures at both the local and global levels often provides advantages and co-benefits not only for the developing, but also for developed countries.Examples of such linkages are;
Final remarks
• Climate change will impact on water runoff, health, and crop productivity in Asia-Pacific region by 2050.
• Health impacts caused by climate change increase 50-90% in 2030, and half of it can be reduced by adaptation.
• In order to restrict global temperature change less then 2 C, stabilization of GHG 500ppm is necessary. It requires 50% reduction of global emission by 2050. GDP changes caused by this reduction are less than 2% in 2020, and less than 4% in 2030, even if no carbon trade.
• Health risk of indoor and outdoor air pollution will be doubled under BaU countermeasures in Asia-Pacific region by 2030.
• Doubling of regional investment per GDP will halve air pollutionrisk, and nearly eradicate unsafe water and sanitation problems by 2030.
• Suitable policy linkages may benefit for local and global environmental problems