[PPT] - Emission Pathway for 6W/m2 Toshihiko Masui, Kenichi Matsumoto, PowerPoint Presentation

SLIDE 1

Emission Pathway for 6W/m2

Toshihiko Masui, Kenichi Matsumoto, Yasuaki Hijioka, Tsuguki Kinoshita, Toru Nozawa, Sawako Ishiwatari, Mikiko Kainuma (National Institute for Environmental Studies) Etsushi Kato (Japan Agency for Marine‐Earth Science and Technology) IAMC Meeting

Tsukuba, Japan September 15, 2009

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Flowchart of RCP6.0 Flowchart of RCP6.0

AIM/Impact [Policy] AIM/CGE [Global] Emission downscaling model Landuse downscaling model Population/GD P scenario GHG/Aerosol emission path Base year data Radiative forcing Population/GDP Downscaling model Pop./GDP Grid cell data Emission scenario [region] Global Region National Grid cell Land‐use change Ecosystem model Land‐cover/ land‐use Emission [fire, land‐ use change] Emission [others]

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production factor market capital labor land Final demand sector resource Production sectors produced commodity market food service energy ... trade

Japan China ...

Energy technology model: energy efficiency Agriculture model: land productivity ...

Annual parameter change

GHGs emissions GHGs emissions climate change

feedback

eg. land productivity change due to climate change

scenarios: population, GDP, ...

structure of AIM/CGE structure of AIM/CGE

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50 100 150 200 250 2000 2020 2040 2060 2080 2100 trillion US$2000

Results of AIM/CGE (Reference) Results of AIM/CGE (Reference)

2000 4000 6000 8000 10000 12000 2000 2020 2040 2060 2080 2100 miillion XAF XLM XRE XE10 XE15 XRA zaf xme rus bra arg mex usa can xsa ind xse tha idn kor jpn chn nzl aus

GDP Population

5000 10000 15000 20000 25000 30000 2000 2020 2040 2060 2080 2100 TgC XAF XLM XRE XE10 XE15 XRA zaf xme rus bra arg mex usa can xsa ind xse tha idn kor jpn chn nzl aus

CO2

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Results of AIM/CGE (6W/m Results of AIM/CGE (6W/m2

2)

)

50 100 150 200 250 2000 2020 2040 2060 2080 2100 trillion US$2000 2000 4000 6000 8000 10000 12000 2000 2020 2040 2060 2080 2100 miillion XAF XLM XRE XE10 XE15 XRA zaf xme rus bra arg mex usa can xsa ind xse tha idn kor jpn chn nzl aus

GDP Population

2000 4000 6000 8000 10000 12000 14000 16000 2000 2020 2040 2060 2080 2100 TgC XAF XLM XRE XE10 XE15 XRA zaf xme rus bra arg mex usa can xsa ind xse tha idn kor jpn chn nzl aus

CO2

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200 400 600 800 1000 1200 2000 2020 2040 2060 2080 2100 EJ Wind, Solar, Geoth., othe hydro nuclear coal biomass gas

il

100 200 300 400 500 600 700 800 900 1000 2000 2020 2040 2060 2080 2100 EJ Electricity Liquids Solids

ther

gas

Results of AIM/CGE (Reference) Results of AIM/CGE (Reference)

Primary energy Final energy

100 200 300 400 500 600 700 800 900 1000 2000 2020 2040 2060 2080 2100 EJ XAF XLM XRE XE10 XE15 XRA zaf xme rus bra arg mex usa can xsa ind xse tha idn kor jpn chn nzl aus 200 400 600 800 1000 1200 2000 2020 2040 2060 2080 2100 EJ XAF XLM XRE XE10 XE15 XRA zaf xme rus bra arg mex usa can xsa ind xse tha idn kor jpn chn nzl aus

Primary energy Final energy

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100 200 300 400 500 600 700 800 900 2000 2020 2040 2060 2080 2100 EJ Wind, Solar, Geoth., other hydro nuclear coal biomass gas

il

100 200 300 400 500 600 700 800 2000 2020 2040 2060 2080 2100 EJ Electricity Liquids Solids

ther

gas

Results of AIM/CGE (6W/m Results of AIM/CGE (6W/m2

2)

)

Primary energy Final energy

100 200 300 400 500 600 700 800 900 2000 2020 2040 2060 2080 2100 EJ XAF XLM XRE XE10 XE15 XRA zaf xme rus bra arg mex usa can xsa ind xse tha idn kor jpn chn nzl aus 100 200 300 400 500 600 700 800 2000 2020 2040 2060 2080 2100 EJ XAF XLM XRE XE10 XE15 XRA zaf xme rus bra arg mex usa can xsa ind xse tha idn kor jpn chn nzl aus

Primary energy Final energy

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20 40 60 80 100 120 2000 2020 2040 2060 2080 2100 TgSO2 XAF XLM XRE XE10 XE15 XRA zaf xme rus bra arg mex usa can xsa ind xse tha idn kor jpn chn nzl aus 20 40 60 80 100 120 2000 2020 2040 2060 2080 2100 TgSO2 SAV AWB RES IND WST ENE ISH TRA LUC 50 100 150 200 250 300 350 400 2000 2020 2040 2060 2080 2100 TgCH4 SAV AGR AWB RES IND WST ENE ISH TRA LUC

Results of AIM/CGE (Reference) Results of AIM/CGE (Reference)

50 100 150 200 250 300 350 400 2000 2020 2040 2060 2080 2100 TgCH4 XAF XLM XRE XE10 XE15 XRA zaf xme rus bra arg mex usa can xsa ind xse tha idn kor jpn chn nzl aus

CH4 CH4 SO2 SO2

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50 100 150 200 250 300 350 400 2000 2020 2040 2060 2080 2100 TgCH4 SAV AGR AWB RES IND WST ENE ISH TRA LUC 20 40 60 80 100 120 2000 2020 2040 2060 2080 2100 TgSO2 SAV AWB RES IND WST ENE ISH TRA LUC 20 40 60 80 100 120 2000 2020 2040 2060 2080 2100 TgSO2 XAF XLM XRE XE10 XE15 XRA zaf xme rus bra arg mex usa can xsa ind xse tha idn kor jpn chn nzl aus

Results of AIM/CGE (6W/m Results of AIM/CGE (6W/m2

2)

)

SO2 SO2 CH4

50 100 150 200 250 300 350 400 2000 2020 2040 2060 2080 2100 TgCH4 XAF XLM XRE XE10 XE15 XRA zaf xme rus bra arg mex usa can xsa ind xse tha idn kor jpn chn nzl aus

CH4

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Spatial explicit population/GDP scenario Spatial explicit population/GDP scenario

Data Data Population Population GDP GDP

UN population

（UN Long range）

UN population

（UN Long range）

224 countries Population data (2000-2050) 183 countries GDP data (2000-2100) 224 countries Population data (2000-2100) ３０ second Grid cell pop. (2000-2100)

UN population

（UN shot range)

UN population

（UN shot range)

IFs GDP scenario IFs GDP scenario

224 countries GDP data (2000-2100)

UN Urbanization UN Urbanization

30 second Grid cell GDP (2000-2100)

Income gap Income gap

GTAP GDP in 2001 GTAP GDP in 2001

IIASA Population scenario Population rank‐size rule Urban area rank‐size rule

Data Data

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Population scenario Population scenario

2000 2050 2100

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Landuse Landuse downscaling model downscaling model

1. Urban (GDP, crop price…)
2. Cropland (yield, slope angle…)
3. Pasture (NPP, slope angle…)
4. Harvest forest (population density..)

Geophysical constraint ・Built‐up area < 5 degree ・Forest < 20 degree etc.

0.5 degree 1km

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Results (Land Results (Land-

use scenario)

use scenario)

Cropland Cropland

2000 2000 2050 2050 2100 2100

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Results (Land Results (Land-

use scenario)

use scenario)

0.00E+00 5.00E+06 1.00E+07 1.50E+07 2.00E+07 2.50E+07 3.00E+07 3.50E+07 4.00E+07 2000 2005 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 P a s t u r e [ k m 2 ] XAF XLM XRE XE0 XE5 XRA zaf xme rus bra arg mex usa can xsa ind xse tha idn kor jpn chn nzl aus

Pasture Pasture

2000 2000 2050 2050 2100 2100

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Sector region indicator for downscale

electricity Japan population electricity China population … … … agriculture USA agricultural area … … …

Summed up

From IAM

AIM 24 region

・Power plant & energy conv. （by population）・Industry: process & combustion（by GDP）・Solvent use（by GDP）・Residential & commercial （by rural pop）・Waste（by population）・Agriculture: waste （by agriculture）・International shipping ・Aviation ・Transportation (road & railroad) ・Agriculture : Animal & Soil

Downscale by indicator Global distribution Regional distribution

Emission downscaling model Emission downscaling model

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：spatially explicit indicator for region and for sector ：regional emissions for region and for sector estimated by IAM

Case 1 Case 1

 

 

       

r s r s r s r s r s s

dxdy t y x w t y x w t t e t e t t y x E t y x E ) , , ( ) , , ( ) ( ) ( ) , , ( ) , , (

, , , ,

r

s x

y t

) , , ( t y x Es ) (

, t

e

s r

r

s

) , , (

,

t y x w s

r

s

：region ：sector ：longitude ：latitude ：year ：gridded emissions from a sector s Changes in regional emissions are downscaled according to spatially explicit indicators for each sector and each region. ENE（total population）, IND（GDP）, SLV（GDP）, DOM（rural population）, WST（total population） & AWB（cropland area）

SLIDE 17

Spatial explicit emission scenarios Spatial explicit emission scenarios

Case 1 (Industry, NO2)

2000 2000 2050 2050 2100 2100

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：global emissions for sector estimated by IAM ：gridded emissions from a sector

Case 2 Case 2

) ( ) ( ) , , ( ) , , ( t e t e t y x E t y x E

s s s s

  s x

y t

) , , ( t y x Es ) (t es

s

：sector ：longitude ：latitude ：year

s

Global distribution at year 2000 is scaled by world total emissions. SHP & AIR

SLIDE 19

Spatial explicit emission scenarios Spatial explicit emission scenarios

2000 2000 2050 2050 2100 2100

Case 2 (International shipping, SO2)

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： spatially explicit indicator for region and for sector ：regional emissions for region and for sector estimated by IAM

Case 3 Case 3



 

r s r s r s r s

t e t e t y x E t y x E ) ( ) ( ) , , ( ) , , (

, , ,

r

s x

y t

) , , ( t y x Es ) (

, t

e

s r

r

s

) , , (

,

t y x w s

r

s

：region ：sector ：longitude ：latitude ：year ：gridded emissions from a sector s

) , , (

,

t y x E

s r

：gridded emissions region and for sector s

r

Regional distribution at year 2000 is scaled by regional total emissions for each region. TRA & AGR

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Spatial explicit emission scenarios Spatial explicit emission scenarios

2000 2000 2050 2050 2100 2100

Case 3 (Agriculture, NH3)

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200 400 600 800 1000 1200 1400 2000 2020 2040 2060 2080 2100 CO2 emission [TgC/yr] Year

6W stabilize Reference

Ecosystem model Ecosystem model

Assessing carbon cycle

Transition Matrix (λ)

agriculture agriculture primary forest primary forest 2nd forest 2nd forest Forest Harvesting (λPS ) Natural Disturbance Forest Harvesting (λss ) Land clearing Land abandonment (λSA ) (λP

A)

(λAS )

CO2 emission by landuse change

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Spatial explicit emission scenarios Spatial explicit emission scenarios

2000 2000 2050 2050 2100 2100

Case 4 (savanna burning, BC)

SLIDE 24

Emissions from landuse

change are diverse among models.

Extension to 2300.

Emission Pathway for 6W/m2

Flowchart of RCP6.0 Flowchart of RCP6.0

structure of AIM/CGE structure of AIM/CGE

Results of AIM/CGE (Reference) Results of AIM/CGE (Reference)

Results of AIM/CGE (6W/m Results of AIM/CGE (6W/m2

)

Results of AIM/CGE (Reference) Results of AIM/CGE (Reference)

Results of AIM/CGE (6W/m Results of AIM/CGE (6W/m2

)

Results of AIM/CGE (Reference) Results of AIM/CGE (Reference)

Results of AIM/CGE (6W/m Results of AIM/CGE (6W/m2

)

Spatial explicit population/GDP scenario Spatial explicit population/GDP scenario

Data Data Population Population GDP GDP

Data Data

Population scenario Population scenario

Landuse Landuse downscaling model downscaling model

Results (Land Results (Land-

use scenario)

Cropland Cropland

Results (Land Results (Land-

use scenario)

Pasture Pasture

Emission downscaling model Emission downscaling model

Case 1 Case 1

 

 

       

dxdy t y x w t y x w t t e t e t t y x E t y x E ) , , ( ) , , ( ) ( ) ( ) , , ( ) , , (

r

s x

y t

) , , ( t y x Es ) (

e

r

s

) , , (

t y x w s

r

s

Spatial explicit emission scenarios Spatial explicit emission scenarios

Case 2 Case 2

) ( ) ( ) , , ( ) , , ( t e t e t y x E t y x E

  s x

y t

) , , ( t y x Es ) (t es

s

s

Spatial explicit emission scenarios Spatial explicit emission scenarios

Case 3 Case 3



 

t e t e t y x E t y x E ) ( ) ( ) , , ( ) , , (

r

s x

y t

) , , ( t y x Es ) (

e

r

s

) , , (

t y x w s

r

s

) , , (

t y x E

r

Spatial explicit emission scenarios Spatial explicit emission scenarios

Ecosystem model Ecosystem model

Spatial explicit emission scenarios Spatial explicit emission scenarios

change are diverse among models.

Remaining works Remaining works