loading page

Quantifying and attributing methane emissions from coal mine aggregation areas using high-frequency ground-based observations
  • +7
  • Fan Lu,
  • Kai Qin,
  • Jason Blake Cohen,
  • Qiansi Tu,
  • Chang Ye,
  • Yanan Shan,
  • Pravash Tiwari,
  • Qin He,
  • Qing Xu,
  • Shuo Wang
Fan Lu
China University of Mining and Technology
Author Profile
Kai Qin
China University of Mining and Technology
Author Profile
Jason Blake Cohen
China University of Mining and Technology

Corresponding Author:[email protected]

Author Profile
Qiansi Tu
Tongji University
Author Profile
Chang Ye
China University of Mining and Technology
Author Profile
Yanan Shan
China University of Mining and Technology
Author Profile
Pravash Tiwari
China University of Mining and Technology
Author Profile
Qin He
China University of Mining and Technology
Author Profile
Qing Xu
China University of Mining and Technology
Author Profile
Shuo Wang
China University of Mining and Technology
Author Profile

Abstract

This work introduces the results of an intensive 15-day surface observation campaign of methane (CH4) and adapts a new analytical method to compute and attribute CH4 emissions. The selected area has a high atmospheric concentration of CH4 (campaign-wide minimum/mean/standard deviation/max observations: 2.0, 2.9, 1.3, and 16 ppm) due to a rapid increase in the mining, production, and use of coal over the past decade. Observations made in concentric circles at 1km, 3km, and 5km around a high production high gas coal mine were used with the mass conserving model free emissions estimation approach adapted to CH4, yielding emissions of 0.73, 0.28, and 0.15 ppm/min respectively. Attribution used a 2-box mass conserving model to identify the known mine’s emissions from 0.042-5.3 ppm/min, and a previously unidentified mine’s emission from 0.22-7.9 ppm/min. These results demonstrate the importance of quantifying the spatial distribution of methane in terms of control of regional-scale CH4 emissions.
04 Dec 2023Submitted to ESS Open Archive
10 Dec 2023Published in ESS Open Archive