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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Hu et al. (2026) studied this question.
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