Scale-dependent bias in methane inventories: Satellite observations reveal overestimation from large coal mines in China

Accurate quantification of China's coal mine methane (CMM) emissions is important for methane mitigation, yet bottom-up inventories remain subject to substantial uncertainty. Using TROPOMI observations from 2020 to 2024 and the Integrated Methane Inversion (IMI) framework, we performed annual inversions of regional methane emissions in Shanxi, a major coal-producing region of China, and integrated Global Energy Monitor (GEM) mine data to examine statistical relationships between mine attributes and posterior emission adjustments. Posterior methane emissions were estimated at 6.02-6.45 Tg yr −1 , averaging approximately 52% lower than the HEMCO-based prior, and exhibited pronounced spatial heterogeneity, with approximately 10% of grid cells contributing about 80% of total posterior emissions. After accounting for spatial differences in observational sensitivity using averaging kernel sensitivity (AKS), coal mine capacity remained the most stable GEM statistical explanatory variable for grid-scale posterior emission variability. Higher-capacity grids generally exhibited lower scaling correction factors (SCF) and stronger downward posterior adjustments, although the statistical significance of this relationship varied among years. Residual analyses further showed generally positive associations between the fraction of high-gas mines and local SCF deviations, whereas other mine attributes showed weaker cross-year consistency. These results suggest that conventional inventories may exhibit scale-related differences in required corrections across grids with different coal mine capacities, while local emission heterogeneity may also be associated with mine gas characteristics. This study provides observational constraints for evaluating and improving coal mine methane inventories and for supporting more targeted methane mitigation management in China's coal sector.