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March 21, 2026ACS ES&T Air

Reconciling Bottom–Up and Top–Down Approaches to Quantify Sub-Regional Methane Emissions with Improved Inventory and Three-Year High-Resolution Satellite Measurements

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Authors

CHCheng HeXLXin LuSLShun Li

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Overview

Investigative modeling optimizes methane emissions in a developed region, indicating improved accuracy for emissions tracking.

Key Points

  • The study aims to reconcile bottom-up and top-down methods to optimize methane emissions estimates at a sub-regional level.
  • Utilized a biogeochemical model to calculate rice emissions based on satellite data.
  • Integrated bottom-up inventories with newly available observations to enhance emission estimates.
  • Applied three years of TROPOMI satellite data for precise emissions estimation.
  • Achieved a reduction in emission uncertainty by 57% in the Greater Bay Area.
  • Estimated total emissions averaged 2.70 Tg a–1 for the years 2019 to 2021.
  • Identified waste treatment as the largest anthropogenic methane source at 1.13 Tg a–1.

Cite This Study

He et al. (2026) studied this question.

synapsesocial.com/papers/69be35166e48c4981c6733b4https://doi.org/10.1021/acsestair.5c00446
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Satellite-based monitoring of methane emissions from China's rice hub2024
  2. 2High-resolution inversion of urban methane emissions in the Chengdu–Chongqing economic circle using ground-based observations and a dynamic error Bayesian framework2026
  3. 3Emerging Trends, Sectoral, and Regional Patterns in China’s Methane Emissions: A Satellite-Constrained Perspective2026
  4. 4Unraveling the sources of uncertainty in China's top-down methane emission estimates2024
  5. 5The added value of new ground-based observations in improving China's methane emission quantification2026