A study of the greenhouse gas emissions inventory and driving factors decomposition in Tongzhou, China
Abstract
District-and county-level greenhouse gas (GHG) inventories remain insufficiently developed, limiting the formulation of targeted mitigation policies at the grassroots governance scale. Taking Tongzhou District, Beijing, as a representative rapidly urbanizing megacity sub-center, this study developed an integrated district-level GHG emissions inventory covering energy activities, agricultural production, LUCF, and waste treatment from 2018 to 2020, and applied the Logarithmic Mean Divisia Index (LMDI) method to identify sector-specific driving mechanisms. The results show that total GHG emissions excluding LUCF followed a “rise-then-decline” trajectory. Energy activities remained the dominant source, accounting for more than 94% of total emissions. The LMDI results revealed heterogeneous sectoral drivers: energy-sector changes were mainly influenced by energy intensity and emission intensity effects; agricultural emission reductions were primarily associated with African Swine Fever-induced contraction of livestock breeding; and waste-sector fluctuations were mainly driven by changes in municipal solid waste incineration, medical waste treatment, and wastewater-related emissions. These findings suggest that district-level mitigation should adopt differentiated strategies across energy, agriculture, and waste sectors.
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BibTeX
@article{hu2026study,
title = {{A study of the greenhouse gas emissions inventory and driving factors decomposition in Tongzhou, China}},
author = {Xiaoyi Hu and Wei Wen and Tao Yang and Xiaoqi Liu and Liyao Shen and Shaorui Wang},
journal = {Scientific Reports},
year = {2026},
month = oct,
doi = {10.1038/s41598-026-73432-8},
url = {https://www.nature.com/articles/s41598-026-73432-8},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - A study of the greenhouse gas emissions inventory and driving factors decomposition in Tongzhou, China
AU - Xiaoyi Hu
AU - Wei Wen
AU - Tao Yang
AU - Xiaoqi Liu
AU - Liyao Shen
AU - Shaorui Wang
PY - 2026
DA - 2026/10/07
JO - Scientific Reports
DO - 10.1038/s41598-026-73432-8
UR - https://www.nature.com/articles/s41598-026-73432-8
AB - District-and county-level greenhouse gas (GHG) inventories remain insufficiently developed, limiting the formulation of targeted mitigation policies at the grassroots governance scale. Taking Tongzhou District, Beijing, as a representative rapidly urbanizing megacity sub-center, this study developed an integrated district-level GHG emissions inventory covering energy activities, agricultural production, LUCF, and waste treatment from 2018 to 2020, and applied the Logarithmic Mean Divisia Index (LMDI) method to identify sector-specific driving mechanisms. The results show that total GHG emissions excluding LUCF followed a “rise-then-decline” trajectory. Energy activities remained the dominant source, accounting for more than 94% of total emissions. The LMDI results revealed heterogeneous sectoral drivers: energy-sector changes were mainly influenced by energy intensity and emission intensity effects; agricultural emission reductions were primarily associated with African Swine Fever-induced contraction of livestock breeding; and waste-sector fluctuations were mainly driven by changes in municipal solid waste incineration, medical waste treatment, and wastewater-related emissions. These findings suggest that district-level mitigation should adopt differentiated strategies across energy, agriculture, and waste sectors.
SN - 2045-2322
ER -