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China’s Future Emissions: Perspectives from the Asian Modeling Exercise
Jae Edmonds, Jiyong Eom and Kate CalvinPresented to the 2011 EPRI Global Climate
Change Research SeminarMay 26, 2011
Acknowledgements
Thanks to EPRI for long-term research support
Thanks to Rich Richels for the invitation to present at this meeting.
Overview of the Presentation
China’s economic and emissions growth historically.
Potential future Chinese emissions—from the perspective of GCAM.
Importance of local air quality policy for climate change.
Fossil Fuel CO2 Emissions in the Old Days
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
1949
1954
1959
1964
1969
1974
1979
1984
1989
1994
TgC/
y ROW
USA
FSU & E. EurChina
050
100150200250300350400450500
ER 2000scenario
2000observed
1999observed
Exa
joul
es p
er Y
ear
Year 2000 Global Primary Energy
China, South &East Asis, & AfricaEE&FSU
Latin America
Japan, Australia &NZCanada & WesternEuropeUS
435 415 401
We generally overestimated growth in the OECD and completely failed to foresee the collapse of the Soviet Union
Retrospective of GCAM scenarios
050
100150200250300350400450500
ER 2000scenario
2000observed
1999observed
Exa
joul
es p
er Y
ear
Year 2000 Global Primary Energy
China, South &East Asis, & AfricaEE&FSU
Latin America
Japan, Australia &NZCanada & WesternEuropeUS
435 415 401
We grossly underestimated economic growth in China.
Estimating energy and economic growth in China is a long-standing problem.
Fossil Fuel CO2 Emissions in the Old Days ... And Today
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
1949
1954
1959
1964
1969
1974
1979
1984
1989
1994
TgC/
y ROW
USA
FSU & E. EurChina
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
1999200020012002200320042005
ROW
USA
China
The Importance of a China FocusBlanford, Richels & Rutherford showed how much expectations of future Chinese emissions have changed.
Asia
ExerciseModelingThe Asia Modeling Exercise
Kate Calvin has lead the exercise.Over 50 People are Attending the Fourth Meeting:
Representing Australia, China, Europe, India, Japan, Korea, Nepal, Thailand, USA
26 Participating Models:AIM-CGE, AIM-Enduse, China MARKAL, DNE21+, EPPA, GCAM, GCAM-IIM, GEM-E3, GRAPE, GTEM, IAMC, IMAGE, IPAC, iPETS, KEI-Linkages, MARIA-23, MERGE, MESSAGE, Nepal MARKAL, PECE, Phoenix, POLES, REMIND, TIAM-World, TIMES-VTT, WITCH
The CPO
Project
To better articulate the role of Asia in addressing climate change.
Asia
ExerciseModelingThe Asia Modeling Exercise
Some emerging observations
Data is a big issue—history is uncertain
Modelers exhibit a variety of definitions for “China”China 22 vs. China 23China bundled with other countries
To say nothing of the variety of future scenarios that the modelers have developed.
AN UNCERTAIN FUTURE
11
12
Population2005 2010 2020 2030 2040 2050
Popul at i on 1307.56 1360.00 1440.00 1470.00 1470.00 1440.00Ur bani zat i on r at e 43% 49% 63% 70% 74% 79%Ur ban Popul at i on 562.12 666.40 907.20 1029.00 1087.80 1137.60Per son per Househol d 2.96 2.88 2.80 2.75 2.70 2.65Ur ban Househol d 189.91 221.94 288.00 336.76 364.78 380.38Rur al Popul at i on 745.44 693.60 532.80 441.00 382.20 302.40Per son per Househol d 4.08 3.80 3.50 3.40 3.20 3.00Rur al Househol d 182.71 189.68 181.03 159.97 151.59 144.00
0.00
200.00
400.00
600.00
800.00
1000.00
1200.00
1400.00
1600.00
2000 2005 2010 2020 2030 2040 2050
mill
ion
Population
Rural
Urban
0.00
100.00
200.00
300.00
400.00
500.00
600.00
2000 2005 2010 2020 2030 2040 2050
mill
ion
Number of Household
Rural
Urban
Courtesy Jiang Kejun
13
0 10, 000 20, 000 30, 000 40, 000 50, 000 60, 000 70, 000
1
3
5
7
9
11
13
15
- 70, 000 - 60, 000 - 50, 000 - 40, 000 - 30, 000 - 20, 000 - 10, 000 0
0- 4岁
10- 14岁
20- 24岁
30- 34岁
40- 44岁
50- 54岁
60- 64岁
70- 74岁
0 10, 000 20, 000 30, 000 40, 000 50, 000 60, 000 70, 000
1
3
5
7
9
11
13
15
- 70, 000 - 60, 000 - 50, 000 - 40, 000 - 30, 000 - 20, 000 - 10, 000 0
0- 4岁
10- 14岁
20- 24岁
30- 34岁
40- 44岁
50- 54岁
60- 64岁
70- 74岁
2005年人口结构
2030年人口结构
Courtesy Jiang Kejun
14
0 10, 000 20, 000 30, 000 40, 000 50, 000 60, 000 70, 000
1
3
5
7
9
11
13
15
- 70, 000 - 60, 000 - 50, 000 - 40, 000 - 30, 000 - 20, 000 - 10, 000 0
0- 4岁
10- 14岁
20- 24岁
30- 34岁
40- 44岁
50- 54岁
60- 64岁
70- 74岁
2050年人口结构
Courtesy Jiang Kejun
Populations for the SSPs [billion]
(Based on UN World Population Prospects: The 2008 Revision – Long Range Projections, released in 2011)
SSP6 SSP9 SSP13
15
Global
Constructed GDP Scenarios [trillion 2000 USD]
16
Global
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
9.0
SSP13 RCP8.5 SSP9 SSP6 RCP6.0 RCP4.5 RCP2.6
[W/m
2]
Reference Scenario 2100 Radiative Forcing
2005 level
17
Jae, these are updated global temperature figures that you might want to use.
18
Jae, these are updated global temperature figures that you might want to use.
19
Per capita GDP in China Per capita GDP = labor productivity × employed labor force (work-age population times labor force participation rates x employment rate)Per capita GDP in SSP9 becomes the highest because of the two competing effects: labor productivity vs. demographic composition
20
× =
Per capita GDPEmployed labor forceLabor productivity
Fossil Fuel CO2 Emissions in China
21
37
29
22
15
7
0
MTC
O2 /y
China’s Primary Energy Consumption [EJ]: Reference Scenarios
Coal remains important regardless of the alternative SSPs.
China’s Final Energy Consumption [EJ]: Reference Scenarios
China’s Energy Consumption between 2005-2095
The same trend as global energy consumptionOverall, the growth is much faster than the global average.
Mitigation under the Three SSPs We assumed a common global price of carbon applied to ALL emissions (fossil fuel and land-use change).
RCP 2.6 is an overshoot scenarioOther stabilization scenarios are “not-to-exceed”.
We observe difference in the initial price required to stabilize among the SSPs. Of course, the big difference in price is between stabilization goals
25
Power Generation by the World and China (SSP9)
Power Generation by the World and China (SSP9)
Power Generation by the World and China (SSP9)
State-of-the-art bottom-up assessments of CCS deployment opportunities for China (2010)
2,309 GtCO2Capacity
1,600 CO2sources emitting 3,890 MtCO2/yr
Dahowski, RT, Dooley, JJ, Davidson, CL, Bachu, S and Gupta, N. Building the Cost Curves for CO2 Storage: North America. Technical Report 2005/3. International Energy Agency Greenhouse Gas R&D Programme. Dahowski RT, X Li, CL Davidson, N Wei, and JJ Dooley. 2010. Regional Opportunities for Carbon Dioxide Capture and Storage in China: A Comprehensive CO2 Storage Cost Curve and Analysis of the Potential for Large Scale Carbon Dioxide Capture and Storage in the People’s Republic of China . PNNL-19091, Pacific Northwest National Laboratory, Richland, WA.
China’s Power Generation by the SSPs
China’s Power Generation by the SSPs
China’s Power Generation by the SSPs
Global Land Use Greater population leads to greater crop land use, rapidly displacing the land use for forest, pasture, and bio-energy.
33
China’s food consumption
34
China’s food consumption
35
China’s land use change emissions
INTERACTIONS WITH OTHER ISSUES
37
Chinese Air Quality
China is the largest fossil fuel CO2 emitter.It has severe local air quality issues.It is also the world’s largest sulfur emitter.
38
True-color MODIS image from October 22, 2010
Source: http://earthobservatory.nasa.gov/IOTD/view.php?id=193439
40
CO2
CH4
N2ONon-CFC Halocarbons
CFCs
Solar irradianceLinear contrails
Total Aerosols (Cloud effects)
Total Aerosols (direct)
Surface Albedo (BC on snow )
Surface Albedo (land)
Strat H2O from CH4
Ozone (trop)
Ozone (strat)
Total Anthropogenic (All gases and short-lived
species)
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
W/m
2
Radiative Forcing 2005
278 (0 W/m2)
335 (1 W/m2)
400 (2 W/m2)
550 (3.7 W/m2)
650 (4.5 W/m2)
450 (2.6 W/m2)
383 ppm-e (1.7 W/m2)
Radiative Forcing: Aerosols are estimated reduce radiative forcing by almost as much as CO2 increases it!
0
20
40
60
80
100
120
140
160
TgSO
2/yr
Without Additional Controls
CHINESE Sulfur Emissions
CHINA Sulfur Emissions
41
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
degr
ees
C
Without Additional Controls
CHINESE Sulfur EmissionsCHINESE Sulfur Emissions and GLOBALMean Surface Temperature with Accelerated Sulfur Emissions Policies
0
20
40
60
80
100
120
140
160
TgSO
2/yr
With Emissions Controls
Without Additional Controls
CHINA Sulfur Emissions
Global Mean Surface Temperature Change
from Preindustrial
42
CHINESE Sulfur EmissionsCHINESE Sulfur Emissions and GLOBALMean Surface Temperature with Accelerated Sulfur Emissions Policies
0
20
40
60
80
100
120
140
160
TgSO
2/yr
With Emissions Controls
Without Additional Controls
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
degr
ees
C
With Emissions ControlsWithout Additional Controls
CHINA Sulfur Emissions
Global Mean Surface Temperature Change
from Preindustrial
43
Rate of Climate Change With and Without Accelerated Chinese Sulfur Controls
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
2005 2015 2025 2035 2045 2055 2065 2075 2085 2095
degr
ees
C/de
cade
Reference CHINA Emissions Controls
Global Mean Surface Temperature Change
44
Rate of Climate Change With and Without Accelerated Chinese Sulfur Controls
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
2005 2015 2025 2035 2045 2055 2065 2075 2085 2095
degr
ees
C/de
cade
Reference CHINA Emissions Controls
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
2005 2015 2025 2035 2045 2055 2065 2075 2085 2095
degr
ees
C/de
cade
With CHINA SULFUR Emissions ControlsReference CHINA Emissions Controls
Global Mean Surface Temperature Change
45
Key Points
China has been surprisingly successful historically—with higher energy and emissions than modelers assumed.We should not forget that the future of China is uncertain.We have begun to look at different potential developments—beginning with the demographictransition.Demographics alone lead to increasingly divergent scenarios with increasingly divergent scales.Assumptions about Chinese local air quality policy could be played out in climate change experienced by the rest of the world.
DISCUSSION
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