中国典型区域电力行业CO<sub>2</sub>排放影响因素分析

贾敏; 郭静; 阮建辉; 蔡博峰; 王金南

doi:10.13205/j.hjgc.202508021

中国典型区域电力行业CO₂排放影响因素分析

doi: 10.13205/j.hjgc.202508021

1. 北方工业大学经济管理学院, 北京 100144;
2. 生态环境部环境规划院碳达峰碳中和研究中心, 北京 100043;
3. 中国地质大学经济管理学院, 北京 100083

基金项目:

国家自然科学基金项目“碳达峰、碳中和区域协同路径优化研究”（72140004）

详细信息

作者简介:
贾敏（1995—），女，博士，主要研究方向为能源政策评估、大数据分析、系统仿真优化。jiaminbju@126.com

通讯作者:
阮建辉（1997—），男，博士，主要研究方向为能源经济管理。13269112988@163.com

计量
- 文章访问数: 66
- HTML全文浏览量: 15
- PDF下载量: 2
- 被引次数: 0
出版历程
- 收稿日期: 2025-05-26
- 录用日期: 2025-08-20
- 修回日期: 2025-06-20

Analysis of CO₂ emissions influencing factors in power sector across representative regions of China

1. School of Economics and Management, North China University of Technology, Beijing 100144, China;
2. Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing 100043, China;
3. School of Economics and Management, China University of Geosciences, Beijing 100083, China

摘要

摘要: 精准测算电力行业CO₂排放量，深入挖掘电力行业异质性排放特征，对于电力行业CO₂减排至关重要。通过运用IPCC规范CO₂测算方法，基于电力行业2020年典型区域机组维度的能耗数据、发电量和发热量，对中国典型区域省份的电力行业CO₂排放量和排放强度进行测算，并从空间结构、燃料类型、年龄分组等维度展开了系统分析。结果表明：2020年，山东省、广东省、内蒙古自治区和江苏省电厂（发电机组）数量分别为324（489）、123（245）、165（255）和206（276）。从发电量和发热量看，山东省和江苏省在上述省份中占主导地位，且燃煤机组在各省电力供应中仍占主导位置。对于CO₂排放总量，2020年上述4省的电力机组的CO₂排放量存在显著差异，且CO₂排放强度越高的省份，对应的排放总量也较高；从机组燃料类型看，CO₂排放量主要来源于燃煤机组，其中，山东省和内蒙古自治区的CO₂排放主要来源于装机容量小于400 MW的机组，广东省和江苏省的CO₂排放主要来源于装机容量大于400 MW的机组；从机组年龄结构看，CO₂排放主要来源于年龄在15~20 a的机组，且新机组的能效水平显著高于老旧机组。对于CO₂排放强度，内蒙古自治区和山东省的CO₂排放强度水平较高；燃气机组的CO₂排放强度显著低于燃煤机组；对于燃煤机组，装机容量越大，机组CO₂排放强度越低；新机组的CO₂排放强度显著低于老旧机组。该研究结果可为我国电力行业制定差异化控制策略提供数据基础。
- 电力行业 /
- 碳排放 /
- 机组维度 /
- 燃料类型 /
- 机组年龄
Abstract: Accurately quantifying CO₂ emissions from the power sector and identifying heterogeneity across generation units are critical for formulating effective decarbonization strategies. Here， we apply the IPCC-recommended methodology to estimate unit-level CO₂ emissions and intensities in representative Chinese provinces using detailed 2020 data on energy consumption， power generation， and heat output. A spatially disaggregated assessment across Shandong， Guangdong， Inner Mongolia， and Jiangsu—comprising 324 （489）， 123 （245）， 165 （255）， and 206 （276） plants （units）， respectively—reveals that Shandong and Jiangsu dominate in both electricity and heat supply， with coal-fired units remaining the primary contributors. In terms of absolute emissions， provinces with higher emission intensities also tend to contribute more to total CO₂ emissions. Coal-fired generation accounts for the majority of emissions， with sub-400 MW units dominating in Shandong and Inner Mongolia， and units above 400 MW dominating in Guangdong and Jiangsu. Units aged 15 to 20 years emerge as the main emission sources， although newer units clearly outperform older ones in energy efficiency. Our findings show substantial variation in CO₂ emission intensities across regions and unit types. Inner Mongolia and Shandong exhibit the highest intensities， while gas-fired units consistently outperform coal-fired units in emission performance. Larger units emit less CO₂ per output unit， and newer installations demonstrate significantly lower intensities than the older counterparts. This study provides a robust empirical foundation to support differentiated control strategies in China’s power sector， with implications for both near-term policy interventions and long-term climate planning.
- power sector /
- CO₂ emissions /
- unit-level analysis /
- fuel type /
- unit age

HTML全文

参考文献(36)

[1]	习近平.在第七十五届联合国大会一般性辩论上的讲话[EB/ OL]. [2025-05-16] http：//www. gov. cn/xinwen/2020-09/22/ content_5546168. htm，2020. XI J P. Statement at the General Debate of the 75th Session of the United Nations General Assembly [EB/OL]. [2025-05-16]. http：//www. gov. cn/xinwen/2020-09/22/content_5546168. htm， 2020.
[2]	国家统计局. 2022中国统计年鉴[M].北京：中国统计出版社，2022. NATIONAL BUREAU OF STATISTICS. China Statistical Yearbook 2022[M]. Beijing：China Statistics Press，2022.
[3]	CHEN Q，KANG C，MING H，et al. Assessing the low-carbon effects of inter-regional energy delivery in China’s electricity sector[J]. Renewable and Sustainable Energy Reviews，2014， 32：671-683.
[4]	WANG J，RODRIGUES J. F. D，HU M，et al. The evolution of Chinese industrial CO 2 emissions 2000-2050：a review and metaanalysis of historical drivers，projections and policy goals[J]. Renewable and Sustainable Energy Reviews， 2019， 116： 109433.
[5]	YANG L，LIN B. Carbon dioxide-emission in China’s power industry：Evidence and policy implications[J]. Renewable and Sustainable Energy Reviews，2016，60：258-267.
[6]	YAN Q，ZHANG Q，ZOU X. Decomposition analysis of carbon dioxide emissions in China’ s regional thermal electricity generation，2000–2020[J]. Energy，2016，112：788-794.
[7]	PENG X，CHEN H，ZHONG H，et al. Water-saving co-benefits of CO 2 reduction in China’s electricity sector[J]. iScience， 2023，26（2）：106035.
[8]	GU B，TAN X，ZENG Y，et al. CO₂ Emission reduction potential in China’s electricity sector：scenario analysis based on LMDI decomposition[J]. Energy Procedia，2015，75：2436-2447.
[9]	ZHAO X，CAI Q，ZHANG S，et al. The substitution of wind power for coal-fired power to realize China’s CO₂ emissions reduction targets in 2020 and 2030[J]. Energy，2017，120： 164-178.
[10]	JIANG X. T，SU M，LI R. Decomposition analysis in electricity sector output from carbon emissions in China[J]. Sustainability， 2018，10（9）：3251.
[11]	雷少波，仝晨华，肖斌，等.中国电力行业碳排放时空分布及影响因素研究[J].计量科学与技术，2024，68（11）：29-33，70. LEI S B，TONG C H，XIAO B，et al. Spatiotemporal distribution and influencing factors of carbon emissions in China’s power industry[J]. Metrology Science and Technology，2024，68（11）： 29-33，70.
[12]	刘亚莉，郭晓，戴文婷，等.“碳中和”愿景下我国碳排放现状和减排路径[J].地球环境学报，2023，14（6）：683-700. LIU Y L，GUO X，DAI W T，et al. Current status and mitigation pathways of carbon emissions in China under the vision of carbon neutrality[J]. Journal of Earth Environment，2023，14（6）： 683-700.
[13]	李旭东，谭青博，赵浩辰，等.碳达峰背景下中国电力行业碳排放因素和脱钩效应[J].中国电力，2024，57（5）：88-98. LI X D，TAN Q B，ZHAO H C，et al. Carbon emission factors and decoupling effects in China’s power industry under the background of carbon peaking[J]. China Electric Power，2024， 57（5）：88-98.
[14]	宁礼哲，任家琪，张哲，等. 2020年中国区域及省级电网电力碳足迹研究[J].环境工程，2023，41（3 ）：229-236. NING L Z，REN J Q，ZHANG Z，et al. Carbon footprint of regional and provincial power grids in China in 2020[J]. Environmental Engineering，2023，41（3）：229–236.
[15]	CHEN Q，FOLLY K. Short-term wind power forecasting based on spatial correlation and artificial neural network [C] // 2020 International SAUPEC/RobMech/PRASA Conference， Cape Town，South Africa：IEEE，2020：1-6.
[16]	林振福，黄彦璐，胡旭东，等. 基于电力流的南方区域电力碳排放核算研究[J]. 技术经济与管理研究，2024，（8）：109-114. LIN Z F，HUANG Y L，HU X D，et al. Accounting of power carbon emissions in southern China based on electricity flow[J]. Journal of Techno-Economics & Management Research，2024，（8）：109-114.
[17]	刘红琴，王高天，陈品文，等. 地区电力行业碳排放水平测算及其特点分析[J]. 生态经济，2018，34（4）：34-39. LIU H Q，WANG G T，CHEN P W，et al. Estimation and characteristic analysis of carbon emissions in regional power industry[J]. Ecological Economy，2018，34（4）：34-39.
[18]	JIA M，ZHANG Z，ZHANG L，et al. Optimization of electricity generation and assessment of provincial grid emission factors from 2020 to 2060 in China[J]. Applied Energy，2024，373：123838.
[19]	JI L，ZHANG B B，HUANG G H，et al. GHG-mitigation oriented and coal-consumption constrained inexact robust model for regional energy structure adjustment：a case study for Jiangsu Province，China[J]. Renewable Energy，2018，123：549-562.
[20]	ZHENG B， TONG D， LI M， et al. Trends in China’s anthropogenic emissions since 2010 as the consequence of clean air actions[J]. Atmospheric Chemistry and Physics，2018，18（19）：14095-14111.
[21]	KUROKAWA J，OHARA T. Long-term historical trends in air pollutant emissions in Asia：Regional Emission inventory in ASia （REAS） version 3[J]. Atmospheric Chemistry and Physics， 2020，20（21）：12761-12793.
[22]	FAN T，LIU X，WU C，et al. Comparison of the Anthropogenic Emission Inventory for CMIP6 Models with a country-level inventory over China and the simulations of the aerosol properties [J]. Advances in Atmospheric Sciences，2022，39（1）：80-96.
[23]	Datahub. Community Emissions Data System（CEDS）[EB/OL]. [2025-05-16]. https：//github. com/JGCRI/CEDS，2024.
[24]	HOESLY R M，SMITH S J，FENG L，et al. Historical（1750– 2014）anthropogenic emissions of reactive gases and aerosols from the Community Emissions Data System（CEDS）[J]. Geoscientific Model Development，2018，11（1）：369-408.
[25]	XIE P， GAO S， SUN F. An analysis of the decoupling relationship between CO₂ emission in power industry and GDP in China based on LMDI method[J]. Journal of Cleaner Production， 2019，211：598-606.
[26]	吴杏平，康重庆，袁启恒. 我国碳排放影响因素及电力碳排放核算方法研究综述[J]. 中国电机工程学报，2024，44（增刊1）： 1-18. WU X P，KANG C Q，YUAN Q H. A review of influencing factors of carbon emissions and accounting methods for power sector emissions in China[J]. Proceedings of the CSEE，2024 ，44（S1）：1-18.
[27]	郭森，王宇慧，周劲松，等. 数字经济发展对我国省级电力行业碳排放影响研究[J]. 智慧电力，2024，52（11）：32-39. GUO S，WANG Y H，ZHOU J S，et al. Impact of digital economy development on carbon emissions in China’s provincial power industry[J]. Smart Power，2024，52（11）：32–39.
[28]	郑雅丽，师玮，王维鹃，等. 中国环境规制对电力行业碳排放的影响[J]. 环境科学，2025，46（6）：3496-3508. ZHENG Y L， SHI W， WANG W J， et al. Impact of environmental regulation on carbon emissions in China’s power industry[J]. Environmental Science，2025，46（6）：3496-3508.
[29]	WANG W，TANG Q，GAO B. Exploration of CO₂ emission reduction pathways：identification of influencing factors of CO₂ emission and CO 2 emission reduction potential of power industry [J]. Clean Technologies and Environmental Policy，2023，25（5）：1589-1603.
[30]	MENG M， JING K， MANDER S. Scenario analysis of CO₂ emissions from China's electric power industry[J]. Journal of Cleaner Production，2017，142：3101-3108..
[31]	TAO Y，WEN Z，XU L，et al. Technology options：can Chinese power industry reach the CO₂ emission peak before 2030？[J]. Resources，Conservation and Recycling，2019，147：85-94.
[32]	IPCC. 2006 IPCC Guidelines for National Greenhouse Gas Inventories [EB/OL]. [2025-05-16]. https：//www. ipcc. ch/ report/2006-ipcc-guidelines-for-national-greenhouse-gasinventories/，2007.
[33]	CAI B，LIANG，S，ZHOU，J，et al. China High Resolution Emission Database （CHRED） with point emission sources， gridded emission data，and supplementary socioeconomic data [J]. Resources， Conservation and Recycling. 2018， 129， 232-239.
[34]	国家应对气候变化协调小组办公室. 中华人民共和国温室气体清单2005[M]. 北京：中国环境科学出版社，2007. Office of the Coordination Group on national Climate change responses. The People’s Republic of China National Greenhouse Gas Inventory 2005[M]. Beijing：China Environmental Science Press，2007.
[35]	国家应对气候变化协调小组办公室. 中华人民共和国温室气体清单2008[M]. 北京：中国计划出版社，2014. Office of the Coordination Group on National Climate Change Responses. The People’s Republic of China National Greenhouse Gas Inventory 2008[M]. Beijing：China Planning Press，2014.
[36]	中华人民共和国生态环境部. 中国区域电网排放因子[EB/ OL]. [2025-05-16]. http：//www. ncsc. org. cn/SY/tjkhybg/ 202003/t20200323_770098. shtml，2020. Ministry of Ecology and Environment of the People's Republic of China. Emission factors for regional power grids in China. [EB/ OL]. [2025-05-16] http：//www. ncsc. org. cn/SY/tjkhybg/ 202003/t20200323_770098. shtml，2020.