|Table of Contents|

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

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

Issue:
2025年第06期
Page:
1099-1113
Research Field:
环境与可持续发展
Publishing date:

Info

Title:
Dynamic Tracking and Attribution of Provincial Power Sector Carbon Emissions in China Based on Multi-source Data
Author(s):
SONG Xuan-ren1;  QIAN Xiao2;  WANG Han-yun3;  HUANG Ji-hua3;  DOU Xin-yu1;  KE Pi-yu1;  LIU Zhu1*
(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)
Keywords:
power industry;  carbon emission;  provincial scale;  spatiotemporal characteristic;  Kaya identity;  LMDI decomposition model;  driving factor
PACS:
X322; F426.61
DOI:
10.19814/j.jese.2025.05035
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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Last Update: 2025-12-10