Energy transition toward carbon-neutrality in China: Pathways, implications and uncertainties
Yong YANG1, Hui WANG2, Andreas LÖSCHEL3, Peng ZHOU2()
1. College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China 2. School of Economics and Management, China University of Petroleum (East China), Qingdao 266580, China 3. Ruhr-Universität Bochum, 44801 Bochum, Germany
Achieving carbon neutrality in China before 2060 requires a radical energy transition. To identify the possible transition pathways of China’s energy system, this study presents a scenario-based assessment using the Low Emissions Analysis Platform (LEAP) model. China could peak the carbon dioxide (CO2) emissions before 2030 with current policies, while carbon neutrality entails a reduction of 7.8 Gt CO2 in emissions in 2060 and requires an energy system overhaul. The assessment of the relationship between the energy transition and energy return on investment (EROI) reveals that energy transition may decrease the EROI, which would trigger increased energy investment, energy demand, and emissions. Uncertainty analysis further shows that the slow renewable energy integration policies and carbon capture and storage (CCS) penetration pace could hinder the emission mitigation, and the possible fossil fuel shortage calls for a much rapid proliferation of wind and solar power. Results suggest a continuation of the current preferential policies for renewables and further research and development on deployment of CCS. The results also indicate the need for backup capacities to enhance the energy security during the transition.
Only anthropogenic CO2 emissions from fossil fuel combustion, bioenergy combustion, and industrial processes are considered
Energy technologies
Most technologies are included, except for waste-based biofuels, synergetic fuels, and bioenergy with CCS
Electricity balance
All electricity generated is integrated well, and storage is ignored
Transmission loss
No loss is included, except for electricity
Input variables
Collective effects of transformation, such as activity level, energy intensity, and structure, are used
Carbon sinka)
Calculated based on the average amount of land carbon sink in China from 2009 to 2016b) and the projected growth of the Chinese forest stockc)
Tab.1
Parameters
2018a)
2030
2040
2050
2060
Population (billion persons)
BAUb)
13.95
14.50
14.49
14.02
13.33
CNSc)
13.95
14.37
13.82
12.94
11.75
Urbanization rated) (%)
59.58
70.00
75.00
80.00
80.00
Gross domestic product (GDP)e) (trillion yuan)f)
73.55
117.55
149.32
174.13
200.51
Carbon sink (Gt CO2e)
1.11
1.25
1.35
1.45
1.50
Tab.2
Key measures
Related sectors
Scenarios
BAU
CNS
ELE
All demand sectors
The energy intensity decreases slightly, the share of electricity increases, and fossil fuels still dominates
The energy intensity decreases drastically; Electricity will be the major fuel, except in Cement, Chemicals, Aviation, and Shipping
BHY
Transportation: Road, Aviation, Shipping, and PipelineIndustries: Iron and Steel, Cement, Chemicals
Share of biofuel is negligible;Share of hydrogen is below 10% in 2060
In 2060, the share of biofuel and hydrogen in:Aviation and Shipping > 70%;Other sub-sectors except Rail > 20%
NFT
Electricity generation, Heat production, Oil and Gas exploitation
In 2060:Installed capacity of fossil fuel power plants = 1610 GW;Share of coal in heat production = 40%;Share of natural gas in heat production = 41%
In 2060:Installed capacity of fossil fuel power plants = 300 GW;Share of non-fossil heat sources = 47%;Less crude oil and natural gas will be produced
DEC
All demand sectors
Demand for products and service across all sectors changes following current trends
Population < values under BAU;Demands in all sectors a) < values under BAU
DCCS
Energy supply, Iron and Steel, Chemicals, Cement
No CCS will be deployed
In 2060, the penetration ratio of CCS in:Energy supply = 90%;Iron and Steel = 59%;Chemicals = 50%; Cement = 50%
Tab.3
Key measures
Main data sources and references
ELE
Energy Transitions Commission: China 2050: A Fully Developed Rich Zero-carbon EconomyState Grid Corporation of China: China Energy & Electricity Outlook 2019Global Energy Interconnection Development and Cooperation Organization: Report on Carbon Neutrality in China before 2060
BHY
IEA: Energy Technology Perspective 2020China Hydrogen Alliance: White Paper on China Hydrogen and Fuel Cell Industry 2019Fuel Cells and Hydrogen Joint Undertaking: Hydrogen Roadmap Europe: A Sustainable Pathway for the European Energy Transition
NFT
Several energy transition outlooks respectively published by IEA, Economic and Technological Research Institute of China National Petroleum Corporation, Energy Information Administration, Institute of Energy Economics Japan, and DNV-GL Group in 2020Shell: The Energy Transformation Scenarios
DEC
Energy Transitions Commission: China 2050: A Fully Developed Rich Zero-carbon EconomyCorresponding data of European countries, like FranceResearch articles, such as Grubler et al. (2018)
DCCS
Huabao Securities: Report on Carbon Neutrality in Iron and Steel IndustryBoston Consulting Group: Climate Plan for China
Tab.4
Fig.2
Fig.3
Fig.4
Fig.5
Primary energy
EROI
Reference
Min
Mean
Max
Coal
26
31
35
Hu et al. (2013a)
Indigenous oil
8
10
14
Hu et al. (2013a); Cheng et al. (2018)
Indigenous natural gas
8
10
14
Hu et al. (2013a); Cheng et al. (2018)
Biomass
8
12
24
Wang et al. (2021a)
Hydro
38
57
73
Hu et al. (2013b); Zhang and Pang (2015); Li et al. (2017)
Wind
11
21
29
Chen et al. (2011); Yang and Chen (2013); Huang et al. (2017); Feng et al. (2020)
Solar
3.4
7.0
13.6
Lu and Yang (2010); Nishimura et al. (2010); Yue et al. (2014); Cao et al. (2016); Liu and van den Bergh (2020)
Geothermal
20
40
60
Chang et al. (2017); Liu (2017)
Nuclear
11
14
17
Hall et al. (2014)
Imported oil
4
7
14
Kong et al. (2016)
Imported natural gas
8
14
16
Kong et al. (2016; 2018)
Tab.5
Fig.6
Fig.7
Non-fossil energy sources
Potentiala)
Energy demand
Solar
Centralized
4.67–23.33b)
22.67
Distributed
> 1.58
Wind
27.52–88.92
12.70
Hydro
8.91–21.90
9.37
Biomass
57.53–101.24
4.57
Tab.6
Fig.8
Fig.9
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