1. China’s Energy system Optimization and co-benefit evaluation under INDC Commitments: based on China-MAPLE model
Xi Yang1, Fei Teng2
1Assitant Professor, academy of Chinese Energy Strategy, China University of Petroleum, Beijing China
2 Associate Professor, Institute of Energy, Environment and Economy, Tsinghua University, Beijing China
Tulsa Oct, 26th 2016

2. Outline Background 2. Introduction of China-MAPLE
3. Results of Scenarios analysis
Conclusion
Next step

3. Background

4. Background—Pressure of Carbon mitigation
China submitted its INDC (Intended Nationally Determined Contribution) in June 2015.
In the INDC, China promised to:
Peak its carbon emission by 2030;
To increase the share of non-fossil fuel consumption to around 20% by
Carbon emission per unit GDP will be reduced by 60%–65% in compared to 2005 level.
Forest volume in 2030 will increase to 4.5 billion m3
Source: NDRC, 2015

5. Background—Pressure of Air pollution
National Air Pollution Control Action Plan, China State Council.
In 2030, all cities should achieve national air quality standards.
The major air pollutants should be reduced by around 80% from year level (The New Climate Economy Report, 2014)
In 2013, air quality of 145 cities have exceeded national air quality standard.
Source: Ministry of Environment Protection, 2013;
China State Council, 2013

6. Background—Co-control
Local pollutant emissions are highly related to fossil fuel combustion.
Actions of energy conservation to reduce carbon emissions often reduce co- emitted air pollutants like SO2, NOx, and PM2.5 , bringing co-benefits for air quality.
Contribution of coal combustion to the SO2, NOx, and PM2.5 emissions in 2012
Data source: MEIC model database (MEIC, 2013)

7. Introduction of China-MAPLE

8. Introduction of China-MAPLE
China Multi-pollutant Abatement Planning and Long-term Benefit Evaluation (China-MAPLE) model
To evaluate the effects of the energy conservation policies and local pollutant control measures on energy system
Bottom-up model. Developed based on VEDA-TIMES. Minimizes the total energy system cost when simultaneously meeting the final energy service demands and external constraints.
5-year step,

9. Structure of China-MAPLE

10. Characters of China-MAPLE
China-MAPLE differs from other China bottom-up model in three aspects:
First, local pollutant control module has been integrated into the energy system framework in China-MAPLE.
Second, instead of based on fuel consumption or activity level, the link of local pollutant to energy module is based on technological level in MAPLE.
This approach can help distinguish the local pollutant reduction due to energy conservation and end-of-pipe control measures.
Third, instead of setting resource cost as fixed-cost or increasing rate, China-MAPLE introduces energy supply curve into the energy supply module.

11. Data source The data of the model mainly comes from:
China Statistical Yearbook, China Energy Statistical Yearbook, China Electric Power Yearbook, Yearbook of Industrial Statistics
China 21st Century Energy Technology Development, 2010 electric power production project cost briefing
China Iron and Steel Statistics, China Chemical Industry Yearbook, China Nonferrous Metals Industry Yearbook
Technical data on electricity production and economic analysis of the literature
Technical parameter from production line of major industrial sectors
As well as large amount of relevant reports and literature studies.

12. Results of Scenario Analysis
REF Scenario
EPC scenario versus REF scenario
COC scenario versus EPC scenario
Co-benefit evaluation

13. Design of Scenarios Abbreviation Scenarios Description REF
Reference Scenario
Taking the current energy policies, technologies and regulations into simulation.
DDP
Deep De-carbonization Scenario
Taking deep energy conservation measures and technologies into account, especially strict coal control measures in power sector and industries.
EPC
End-of-Pipe Control Scenario
The maximum level of end-of-pipe measures promotion; With the BATs (Best available Technologies) adopted and with maximum application rate among sectors.
COC
Co-Control Scenario
Combination of both DEC and EPC Scenarios.

14. Social-economic assumptions
Unit
2010
2020
2030
2040
2050
Population
Million
1360
1520
1890
1470
1420
GDP growth rate
%/per year
7.5
6.2
4.1
3.2
2.5
GDP per capita
Thousand RMB/ person
29.5
57.4
98.8
150.8
198.1
Urbanization %
51.1
58.2
67.1
72.4
75.2
GDP growth: Considering the recent economy “New-normal” in China. GDP growth rate will decrease, 2020 around 6.2%, 2030 around 4.1%. (Cao et al. 2013)
The model assumes the population growth scenario that having a second child is allowed publicly.
China’s total population will peak around 2025–2030, and then reduce to 1.42 billion by 2050.
(Zeng et al. 2013)
Source: Cao et al. 2013; Zeng et al. 2013; Word Bank, 2012.

15. REF Scenario—Primary energy consumption
Total :
(2030)5.96 billion tce;
(2050)7.29 billion tce.
In 2030:
Coal : 48.4%
Gas: 7.3%
Non-fossil: 17.3%

16. REF Scenario—Carbon emission
In 2030, total energy related CO2 emission 11.9 billion tons.
Million tons CO2

17. REF Scenario—Local pollutant emission
With the current end-of-pipe control measures, SO2、NOX and PM2.5 in 2030 will increase 163.2%，81.9% and 60.2% to 2010 level.
Air quality will deteriorate in 2030.
Necessity of end-of-pipe control measures

18. Strengthening End-of-Pipe Control Scenario
EPC vs. REF Scenario—end-of-pipe control measures
Reference Scenario
Strengthening End-of-Pipe Control Scenario
End-of-Pipe Control Technology
Application of End Treatment
Sector
Current Level
Best Available Technology
Best Promotion of Application
Electricity
SO2
FGD removal rate of 70%-80%;
FGD installation of 96% in
Wet FGD removal rate of 92%–98%; Dry FGD removal rate of 85%–92%
100% installation of FGD of coal power plant
NOX
Low NOx combustion technology with removal rate of less than 60%; SCR removal rate of 85%.
LNC installation of 75% by ; LNC installation of 84% by 2030; SCR+LNC installation of 12%.
SCR removal rate of 80%– 95%
100% installation of SCR of coal-based power plant by
PM2.5
Elec dust removal rate of 93%; Bag removal rate of 95%.
Elec installation of 80%; bag removal installation of 20% by 2030.
Elec and bag dust removal rate of 99.7%
Bag dust removal and elec dust removal rate of 100% by 2030
Industry Boiler
FGD removal rate of 65%–75%
FGD installation around 50%
FGD removal rate of 90%
FGD installation of 100% by 2030
Wet dust removal efficiency of 80%
Wet dust installation of 95% by 2030
Bag and dust removal rate of 99%
Bag dust removal installation 100% by 2030
Iron and Steel Sector
Sintering FGD efficiency of 80%
Sintering FGD installation of 40%
Wet FGD efficiency of 98%
WFGD installation of 100% by 2030
Sintering, Elec, and Bag efficiency of 90%
Installation of 80% by 2030
Sintering, bag, and emission (0.155– kg/t product）
Dust removal in Sintering process installation of 100% by 2030
 Building Sector
Coal stove and biomass stove efficiency of 40%.
Coal stove and biomass stove installation of 60%
Low-pollution coal and biomass stove efficiency of 70%.
Coal stove and biomass stove installation of 90%
Transportation
2030 EU IV and V standard
EU VI standard reduction of 80%
Shift from V to VI standard by 2030
EU VI standard reduction of 66%

19. EPC vs. REF Scenario—Local pollutant emission
Obvious reduction
Reduction PM>NOx>SO2;
SO2: 2020(51.5%),2030(68%);
NOx: 2020(43%),2030(61%);
PM2.5: 2020(54%),2030(73.4%);

20. EPC vs. REF Scenario—Reduction Effect
Reduction in 2030, compared to 2010 level（%）
SO2
NOx
PM2.5
Electricity generation
91.4%
92.3%
98.7%
Cement industry
90.0%
82.8%
99.3%
Industry boilers
75.2%
81.5%
96.6%
Non-mental industry
84.2%
90.2%
Other industry
Residential buildings
30.0%
10.0%
89.1%
Iron and steel Industry
92.5%
93.3%
Transportation
70.0%
National average level
68.1%
61.3%
73.4%
Target level
80.0%
National average: SO2 reduced by 68.1%, NOx reduced by 61.3%, PM2.5 reduced by 73.4%.
By sectors: iron and steel/electricity/cement > Industry boilers/industry process > residential/transport
Not enough to fulfill the air quality target.

21. DDP Scenario—Primary Energy Consumption and Carbon emission
In 2030, 6.12 billion tce (REF) to 5.86 billion tce (DDP);
In 2050, 7.29 billion tce (REF); 6.17 billion tce (DDP)
Carbon emission peaking in 2030 reduced from 11.9 to 10.6 billion ton, reduced by 1.3 billion ton.
Carbon intensity (per GDP) 60% reduction 2030/2010.
 billion ton
2010
2020
2030
2040
2050
REF Scenario
7.84
10.88
11.88
12.87
13.91
DDP Scenario
10.44
10.58
9.96
7.70

22. DDP Scenario—Electricity generation

23. COC vs. EPC Scenario—local pollutant reduction
Source control:
SO2 in 2030 reduced 14%；
Nox in 2030 reduced 17.9%；
PM2.5 in 2030 reduced 8.51%.
SO2：power generation 20%, industry 67%；
NOx：transport 24%、industry 40% and power 20%；
PM25：residential 69%、industry 20%, power generation 7%

24. COC vs. EPC Scenario—local pollutant reduction
In 2030, SO2, NOx, PM2.5 reduced to 21.15%、22.44% and 16.68% of 2010 level
Contribution of end-of-pipe measures 69%-76%; Contribution from source control 24%-31%.

25. COC vs. EPC Scenario—contribution from source control
contribution of source control and end-of-pipe control measures in Electricity sector and building sector

26. Monetary Co-benefit evaluation
Case study in Cement Industry

27. Mitigation Technologies
Co-benefit evaluation—cement sector
Num
Mitigation Technologies 1
Mining optimization 2
New steel tape hoist 3
Vertical mill for Raw material Grinding 4
Roller Press for Raw material Grinding 5
Power system of ore transportation 6
Purelow-temperature
Cogeneration technology 7
Co-grinding system 8
The fourth-generation grate cooler technology 9
New efficient burner 10
Efficient precalciner pre-heater system 11
Fan inverter technology with High-temperature 12
New efficient drying technology 13
Alternative fuel technology for cement production 14
Energy management system for online
detection and analysis 15
Increase in pre-heater stages 16
carbon capture and storage (CCS)
for cement production 17
Oxy-fuel technology for Cement clinker 18
Pentane media pure low
temperatureCogeneration technology

28. Co-benefit evaluation—cement sector
Co-benefit in cement sector is around RMB/tCO2; consistent with result of studies on developed countries 2-128$/tCO2
Large variance of environmental effect among provinces (income/population intensity)

29. Co-benefit evaluation—MACCs of all sectors
Revised Marginal Abatement Cost Curve compared to Original curve in 2030
in the case of a carbon tax level below 120 RMB/ton CO2, the carbon emissions mitigation cost can be balanced by the environmental benefit.

30. Co-benefit evaluation—MACCs of all sectors
Mitigation Cost
Contribution of carbon mitigation cost and co-benefit to GDP
-Even with the most strict end-of-pipe measures in 2030, one unit ton of carbon abatement can still have 25RMB environmental co-benefit.

31. Conclusion

32. Conclusion
In REF scenario, with the current effort, in 2030, the primary energy consumption will reach 6.12 billion tce, with carbon emission of billion tons. And the air quality will further deviate.
In EPC scenario, with strict end-of-pipe control, in 2030, the SO2, Nox and PM2.5 will be reduced to 68.1%，61.3%, and 73.4%, compare to 2010 level. However, still not enough to achieve air quality target.
In COC scenario, the carbon emission in 2030 will be reduced 1.5 billion tons. Typical local pollutant SO2, NOx and PM2.5 will be reduced to 78.9%，77.6%, and 83.3%, compare to 2010 level. Roughly fulfill the air quality target.
The average environmental co-benefit is around RMB/ton CO2; Co- benefit in electricity generation sector is around RMB/ton CO2. In building sector the co-benefit is about RMB/ton CO2
The study of co-benefits will effectively help the climate negotiations to get out from the “zero-sum game” dilemma, and promote their motivation to make carbon mitigation commitment.

33. Next step

34. Current work Next step Non-CO2 GHG in China-MAPLE;
Model training; Data transparency
Detailed supply curve for China-MAPLE;
Health damage of co-benefit evaluation;
Natural gas and energy security co-benefit evaluation.
Next step

35. Thank you for your attention! Any comments? yangxi@cup.edu.cn