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《地球科学与环境学报》[ISSN:1672-6561/CN:61-1423/P]

卷:

第47卷

期数:

2025年第06期

页码:

1099-1113

栏目:

环境与可持续发展

出版日期:

2025-12-10

文章信息/Info

Title:

Dynamic Tracking and Attribution of Provincial Power Sector Carbon Emissions in China Based on Multi-source Data

文章编号:

1672-6561(2025)06-1099-15

作者:

宋晅任¹; 钱 啸²; 王函韵³; 黄继华³; 窦新宇¹; 柯丕煜¹; 刘 竹^1*

(1. 清华大学 地球系统科学系,北京 100084; 2. 国网浙江省电力有限公司,浙江 杭州 310016; 3. 国网浙江省电力有限公司湖州供电公司,浙江 杭州 317101)

Author(s):

SONG Xuan-ren¹;  QIAN Xiao²;  WANG Han-yun³;  HUANG Ji-hua³;  DOU Xin-yu¹;  KE Pi-yu¹;  LIU Zhu^1*

(1. Department of Earth System Science, Tsinghua University, Beijing 100084, China; 2. State Grid Zhejiang Electric Power Co., Ltd., Hangzhou 310016, Zhejiang, China; 3. Huzhou Power Supply Company, State Grid Zhejiang Electric Power Co., Ltd., Hangzhou 317101, Zhejiang, China)

关键词:

电力行业;  碳排放;  省级尺度;  时空特征;  Kaya恒等式;  对数平均迪氏指数分解模型;  驱动因素

Keywords:

power industry;  carbon emission;  provincial scale;  spatiotemporal characteristic;  Kaya identity;  LMDI decomposition model;  driving factor

分类号:

X322; F426.61

DOI:

10.19814/j.jese.2025.05035

文献标志码:

A

摘要:

在全球气候变化与能源转型的共同驱动下,电力行业碳排放已成为应对气候变暖的关键问题之一。现有研究虽然在全球及部分国家层面开展了多角度的探索,但针对中国省级尺度,尤其是近实时碳排放核算与驱动因素分析仍相对不足。构建了覆盖中国31个省(自治区、直辖市)的电力生产近实时数据体系,并对2019～2024年日尺度碳排放时间序列进行了系统分析; 采用Kaya恒等式、对数平均迪氏指数(LMDI)分解模型、归一化季节指数构建及时间序列分析等方法,深入探讨了宏观社会经济因素、气候因素和重大突发公共卫生事件对各省级行政单位电力碳排放的影响。结果表明:2019～2024年全国日均电力碳排放量整体呈上升趋势。虽然2020年初受重大突发公共卫生事件的影响出现短暂下降,但随后迅速反弹并持续增长; 各省级行政单位电力碳排放量在时间上呈现波动性,在空间分布上表现出显著差异; 经济规模增长是多数地区电力碳排放量增加的主要驱动因素,而能源强度与碳强度的持续改善在一定程度上减缓了电力碳排放量的增长,部分地区甚至出现下降; 从时间特征来看,电力碳排放量存在明显的季节性波动,受夏季空调制冷与冬季采暖需求共同作用,大多数省级行政单位在夏季和冬季均出现电力碳排放高峰; 此外,法定节假日和重大突发公共卫生事件等对日尺度电力碳排放量曲线也产生了显著扰动。本研究建立的电力碳排放量估算体系与分析方法,有助于更全面地识别和理解电力碳排放量的动态变化特征,并为区域差异化碳减排政策的制定提供科学支撑。

Abstract:

Driven by global climate change and energy transition, carbon emissions from the power sector have become a key issue in addressing global warming. Although existing studies have explored this topic from multiple perspectives at the global and national levels, the research focusing on the provincial scale in China, especially on near-real-time carbon emission accounting and driving factor analysis, remains relatively limited. A near-real-time data system for power generation in 31 provinces of China was constructed, and daily carbon emission time series from 2019 to 2024 was analyzed; by applying the Kaya identity, the logarithmic mean Divisia index(LMDI)decomposition model, the normalized seasonal index, and the time series analysis, the impacts of macroeconomic factors, climatic conditions, and major public health emergencies on provincial power sector carbon emissions were investigated. The results show that national daily average power sector carbon emissions exhibit an overall upward trend from 2019 to 2024; although emissions decline briefly in early 2020 due to major public health emergencies, they quickly rebound and continue to increase; provincial power sector carbon emissions show substantial fluctuations and clear spatial heterogeneity; economic growth is the main driving factor of increased power sector emissions in most regions, while improvements in energy intensity and carbon intensity help mitigate power sector carbon emission growth and even contribute to reductions in some provinces; from a temporal perspective, power sector carbon emissions display pronounced seasonal variations, with most provinces experiencing carbon emission peaks in both summer and winter due to cooling and heating demands; in addition, statutory holidays and major public health emergencies significantly disturb the daily power sector carbon emission curves. The proposed emission estimation framework and analytical approach enhance the understanding of dynamic carbon emission patterns in the power sector and provide scientific support for developing region-specific mitigation policies.

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相似文献/References:

[1]赵文静,王承武*.乌鲁木齐都市圈土地利用碳排放与生态系统服务交互特征[J].地球科学与环境学报,2025,47(02):260.[doi:10.19814/j.jese.2024.08036]
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备注/Memo

备注/Memo:

收稿日期:2025-05-29; 修回日期:2025-07-18投稿网址:http:∥jese.chd.edu.cn/
基金项目:国家电网有限公司总部管理科技项目(1400-202219426A-2-0-ZN); 国家自然科学基金(71874097,72140002,41921005)
*通信作者:刘 竹(1985-),男,云南昆明人,教授,博士研究生导师,理学博士,E-mail:zhuliu@tsinghua.edu.cn。

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更新日期/Last Update: 2025-12-10