Abstract
Methane (CH4) emissions from the coal industry represent a substantial portion of anthropogenic CH4 emissions from energy-related activities. China ranks as the world's largest coal producer, where Shanxi Province is one of its major coal production regions and accounts for 20.7% of the national total coal production. The inherent variability in coal properties, geological conditions, and mining techniques across coal mines introduces significant fluctuations in CH4 emission characteristics and emission factors (EFs), creating considerable uncertainty when estimating CH4 emissions in this major coal mining region using traditional emission inventories, thereby introducing large bias in estimating national total CH4 emissions of China. In this study, we applied a top-down approach to estimate CH4 emissions in the Taiyuan-Jinzhong Metropolitan (TJM) area of Shanxi Province, using atmospheric CH4 concentration observed from a 30-meter tower between March 2018 and February 2019. Building upon our previous work, we integrated five emission inventories-EDGAR, GFEI-coal, PRO-coal, GFEI-fuel, and a satellite-based CH4 emission product-with two inversion methods. Additionally, satellite xCH4 data were utilized to identify significant emission outliers, which were then calibrated when estimating the CH4 emission and EF for the region. Our results revealed notable disparities in the magnitude of CH4 emissions among the five inventories for the TJM region. After applying the MSF and SFBI methods to constrain the prior emission inventories, the posterior CH4 emissions for the TJM region were estimated at 1.1×106t, 1.0×106t, 1.1×106t, 1.3×106t, and 1.5×106t, respectively, across the five inventories. The derived coal mine CH4 EF for the TJM region was 9.6 (±1.35) m3/t, significantly lower than the previously reported value of 23.2 (±4.9) m3/t, highlighting the substantial impact of emission outliers on posterior CH4 emissions. A comparative analysis with EFs from other studies demonstrated that this value closely aligns with the EF values for coal with low CH4 content. However, it is important to note that substantial regional variability of coal mining activities can result in significant uncertainty in EFs across different areas. Therefore, we underscore the necessity of establishing a more extensive atmospheric CH4 observation network to enhance the assessment of regional variations in CH4 EFs and emissions from coal mining activities.
Published Version
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