24 Oct 2023
 | 24 Oct 2023

Quantifying CH4 emissions from coal mine aggregation areas in Shanxi, China using TROPOMI observations and the wind-assigned anomaly method

Qiansi Tu, Frank Hase, Kai Qin, Jason Blake Cohen, Farahnaz Khosrawi, Xinrui Zou, Matthias Schneider, and Fan Lu

Abstract. China stands out as a major contributor to anthropogenic methane (CH4) emissions, with coal mine methane (CMM) playing a crucial role. To control and reduce CH4 emissions, China has made a dedicated commitment and formulated an ambitious mitigation plan. To verify the process made, the consistent acquisition of independent CH4 emission data is required. This paper aims to implement a wind-assigned anomaly method for the precise determination of regional-scale CMM emissions within the coal-rich Shanxi province. We use the TROPOspheric Monitoring Instrument (TROPOMI) CH4 observations from May 2018 to May 2023, coupled with ERA5 wind covering the Changzhi, Jincheng and Yangquan regions. The derived emission strengths are 8.4× 1026 ± 1.6 × 1025 molec. s-1 (0.706 ± 0.013 Tg yr-1), 1.4 × 1027 ± 1.9 × 1025 molec. s-1 (1.176 ± 0.016 Tg yr-1), and 4.9 × 1026± 1.8 × 1025 molec. s-1 (0.412 ± 0.015 Tg yr-1), respectively. Our results exhibit biases of -18 %, 8 %, and 14 % when compared to the bottom-up inventory. Larger discrepancies are found when comparing the estimates to the CAMS-GLOB-ANT and EDGARv7.0 inventories. This suggests that the two inventories may be overestimating the CH4 emissions in the Jincheng and Yangquan regions. Our estimates provide a comprehensive characterization of the regions within the Shanxi province, contribute to the validation of emission inventories, and help to develop climate mitigation strategies.

Qiansi Tu et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-2155', Anonymous Referee #2, 10 Nov 2023
  • RC2: 'Comment on egusphere-2023-2155', Anonymous Referee #1, 14 Nov 2023

Qiansi Tu et al.

Qiansi Tu et al.


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Short summary
Four-year satellite observations of XCH4 are used to derive CH4 emissions in three regions of China’s coal-rich Shanxi province. The wind-assigned anomalies for two opposite wind directions are calculated and the estimated emission rates are comparable to the current bottom-up inventory but lower than the CAMS and EDGAR inventories. This research enhances the understanding of emissions in Shanxi and supports climate mitigation strategies by validating emission inventories.