Methane transport from the world's densest fossil source region systematically biases satellite-based emission estimates

<title>Abstract</title> <p> Accurately estimating and attributing methane (CH ₄ ) emissions is critical for climate change analysis and mitigation policy, but complex meteorology and terrain and incomplete knowledge of source geospatial distribution challenges current satellite-based and transport model-based methods. One of the most important coal mining regions in the world considering the amount and density of production is found in the high-elevation and mountainous regions of Shanxi China. We use Empirical Orthogonal Function (EOF) analysis of daily satellite observations to indentify the long-range transport of CH ₄ from this region, and WRF-STILT simulation to partition CH ₄ variability. We indentify 76 days that reveals a slow build-up and rapid release of methane from mining areas to the middle troposphere, followed by significant transport of these emissions over downwind agricultural areas. This atmospheric transport leads to existing methods using long-term local averages to underestimate coal mine area emissions by 37%, while overestimating agricultural methane emissions in Henan by 59%. These regional biases are sufficiently large to shift global fossil methane attribution up by 1.0-1.5% and agricultural methane attribution down by 0.3–0.5%, based on this single region alone. Our light-weight physically constrained emissions framework objectively identifies and differentiates typical local coal mine driven conditions that dominate the remaining 1144 days. Contrasting days with and without downwind transport from Shanxi enables more reliable emission estimates using existing satellite data. This finding is directly relevant to methane MRV frameworks and the Global Methane Pledge, as jurisdiction-bound emission controls alone cannot meet local methane targets when cross-administrative transport systematically misattributes sources. Our framework provides a diagnostic tool to correct this bias and support cross-administrative governance, offering a practical pathway to improve MRV systems under the Global Methane Pledge and to enable more effective transboundary methane mitigation. </p>