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Air quality co-benefit evaluation of China's carbon peaking effort based on China-MAPLE model
Xi Yang1, Fei Teng2
1Academy of Chinese Energy Strategy, China University of Petroleum, Beijing 102249 China
2 Institute of Energy, Environment and Economy, Tsinghua University, Beijing 100084 China
IEW Cork June, 1st 2016
1. Background
2. Introduction of China-MAPLE
3. Results of Scenarios analysis
4. Conclusion
5. Next step
Outline
2
Background
3
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 2030.
• Carbon emission per unit GDP will be reduced by 60%–65% in 2030 compared to 2005 level.
• Forest volume in 2030 will increase to 4.5 billion m3
4
Background—Pressure of Carbon mitigation
Source: NDRC, 2015
• National Air Pollution Control Action Plan, 2013. 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 2010 level (The New Climate Economy Report, 2014)
5
Background—Pressure of Air pollution
Source: Ministry of Environment Protection, 2013;China State Council, 2013
In 2013, air quality of 145 cities have exceeded national air quality standard.
• 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)
6
Background—Co-control
Introduction of China-MAPLE
7
• 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, 2010-2050.
8
Introduction of China-MAPLE
9
Structure 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.
10
Characters of China-MAPLE
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.
11
Data source
Results of Scenario Analysis
12
REF ScenarioEPC scenario versus REF scenarioCOC scenario versus EPC scenarioCo-benefit evaluation
Design of Scenarios
13
Abbreviation
Scenarios Description
REF Reference Scenario
Taking the current energy policies, technologies andregulations into simulation.
DDP Deep De-carbonization Scenario
Taking deep energy conservation measures andtechnologies into account, especially strict coal controlmeasures 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 andwith 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.
REF Scenario—Primary energy consumption
0
1000
2000
3000
4000
5000
6000
7000
8000
2010 2015 2020 2025 2030 2035 2040 2045 2050
Pri
mar
y En
ergy
Co
nsu
mp
tio
n（
Mill
ion
tce）
Coal Gas Oil Nuclear Hydro Biomass Wind Solar Other
67%57% 53% 50% 48% 46% 46% 45% 45%
3%
5%6%
6% 7% 7% 8% 9% 9%
20%
20% 26% 26% 28% 27% 26% 26% 26%
1%
3% 3% 3% 4% 5% 5% 6% 6%
8%8% 7% 7% 7% 7% 7% 6% 6%
1%7% 5% 6% 7% 7% 6% 6% 6%
0% 0% 0% 1% 1% 1% 1% 1% 2%
2 0 1 0 2 0 1 5 2 0 2 0 2 0 2 5 2 0 3 0 2 0 3 5 2 0 4 0 2 0 4 5 2 0 5 0
Total : (2030)5.96 billion tce;(2050)7.29 billion tce.
In 2030:Coal : 48.4%Gas: 7.3%Non-fossil: 17.3%
Million tons CO2
16
In 2030, total energy related CO2 emission 11.9 billion tons.
REF Scenario—Carbon emission
0
2
4
6
8
10
12
14
2010 2015 2020 2025 2030 2035 2040 2045 2050
Ener
gy-r
elat
ed C
O2
em
issi
on
(b
illio
n t
on
)
Agriculture Electricity Industry Tranportation Buildings
17
• 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
REF Scenario—Local pollutant emission
0
2000
4000
6000
8000
10000
12000
2010 2015 2020 2025 2030 2035 2040 2045 2050
SO2
Em
issi
on（
!0^4
to
n）
Cement Electricity Industry Boilers Non-Ferrous
Iron and Steel Other Industry Buildings Transportation
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
2010 2015 2020 2025 2030 2035 2040 2045 2050
NO
x em
issi
on（
10
^4 t
on）
Cement Electricity Industry Boilers Non-Ferrous
Iron and Steel Other Industry Buildings Transportation
0
200
400
600
800
1000
1200
1400
1600
1800
2010 2015 2020 2025 2030 2035 2040 2045 2050
PM
2.5
em
issi
on（
10
^4 t
on）
Cement Electricity Industry Boilers Non-Ferrous
Iron and Steel Other Industry Buildings Transportation
• Obvious reduction
18
• Reduction PM>NOx>SO2;
• SO2: 2020(51.5%),2030(68%);• NOx: 2020(43%),2030(61%);• PM2.5: 2020(54%),2030(73.4%);
EPC vs. REF Scenario—Local pollutant emission
0
500
1000
1500
2000
2500
3000
3500
2010 2015 2020 2025 2030
SO2
em
issi
on
(1
0^4
to
n)
SO2 emission
Electricity Cement CokingIndustry Boiler Nonmetallic Industry Other IndustryResidential Iron and steel Transportation
0
500
1000
1500
2000
2500
3000
3500
2010 2015 2020 2025 2030
No
x em
issi
on
(10
^4 t
on
)
NOx emission
Electricity Cement Coking
Industry Boiler Nonmetallic Industry Other Industry
Residential Iron and steel Transportation
0
200
400
600
800
1000
1200
2010 2015 2020 2025 2030
PM
2.5
em
issi
on
(1
0^4
to
n)
PM2.5 emission
Cement Electricity Industry BoilerNonmetallic Industry Other Industry ResidentialIron and steel Transportation
19
Reduction in 2030, compared to 2010 level（%）
• 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.
EPC vs. REF Scenario—Reduction Effect
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% 81.5% 90.2%
Other industry 84.2% 81.5% 90.2%
Residential
buildings
30.0% 10.0% 89.1%
Iron and steel
Industry
92.3% 92.5% 93.3%
Transportation 10.0% 70.0% 70.0%
National
average level
68.1% 61.3% 73.4%
Target level 80.0% 80.0% 80.0%
• 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.
20
DDP Scenario—Primary Energy Consumption and Carbon emission
billion ton 2010 2020 2030 2040 2050
REF Scenario 7.84 10.88 11.88 12.87 13.91
DDP Scenario 7.84 10.44 10.58 9.96 7.70
0
1000
2000
3000
4000
5000
6000
7000
8000
REF/DDP REF DDP REF DDP REF DDP REF DDP
2010 2020 2030 2040 2050
Pri
mar
y en
ergy
Co
nsu
mp
tio
n (
mill
ion
to
n)
Coal Gas Oil Nuclear Hydro Biomass Wind Solar Other
• 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)
21
0
2000
4000
6000
8000
10000
12000
14000
REF/DEC REF DEC REF DEC REF DEC REF DEC
2010 2020 2030 2040 2050
Elec
tric
ity
Gen
erat
ion
(TW
h) Other
Wave
Solar
Wind
Biomass
Hydro
Nuclear
Gas
Oil
Coal
DDP Scenario—Electricity generation
• 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%.
22
COC vs. EPC Scenario—local pollutant reduction
27%
10%5%
36%
10%6% 7%
1% 1%
18%
3%
2%
4%
1%1%
0%
0% 0%
14%
3%
2%
10%
2%2%
7%
1% 1%
19%
10%
9%
15%
5%5%
4%
1% 1%
13%
5%
3%
6%
2%2%
15%
12%7%
8%
1%
1%
3%
1%1%
47%
4%
4%
0%
0%
0%
21%
18%
5%
5%
1%
1%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2 0 1 0 EP C 2 0 3 0 C O C 2 0 3 0 2 0 1 0 EP C 2 0 3 0 C O C 2 0 3 0 2 0 1 0 EP C 2 0 3 0 C O C 2 0 3 0
S O 2 N O X P M 2 5
Electricity Cement Sintering Industry Boilers and process NonMentallic Industry Buildings Steel making Transportation
Monetary Co-benefit evaluation
23
Case study in Cement Industry
24
Co-benefit evaluation—cement sector
, 2( ) /i j CO
j
EMC C MED Q
MEDi , j
= Ni , j
´VSLi, j
MEDi , j
=MED
i ,EU´D
j´ PPP
j
DEU
´ PPPEU
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
25
• Co-benefit in cement sector is around 19.9-256.7RMB/tCO2; consistent with result of studies on developed countries 2-128$/tCO2
• Large variance of environmental effect among provinces (income/population intensity)
Co-benefit evaluation—cement sector
Conclusion
26
• In REF scenario, with the current effort, in 2030, the primary energy consumption
will reach 6.12 billion tce, with carbon emission of 11.98 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 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.
27
Conclusion
Next step
28
• Non-CO2 GHG in China-MAPLE;
• Data transparency
• Detailed supply curve for China-MAPLE;
• Health damage of co-benefit evaluation;
• Natural gas and energy security co-benefit evaluation.
29
Current work
Next step
