@article {1214625,
	title = {Bottom-up estimates of coal mine methane emissions in China: A gridded inventory, emission factors, and trends},
	journal = {Environmental Science and Technology Letters},
	year = {2019},
	abstract = {China has large but uncertain coal mine methane (CMM) emissions. Inverse modeling (top-down) analyses of atmospheric methane observations can help improve the emission estimates but require reliable emission patterns as prior information. To serve this urgent need, we developed a high-resolution (0.25{\textdegree} {\texttimes} 0.25{\textdegree}) methane emission inventory for China{\textquoteright}s coal mining using a recent publicly available database of more than 10000 coal mines in China for 2011. This number of coal mines is 25 and 2.5 times, respectively, more than the number available in the EDGAR v4.2 and EDGAR v4.3.2 gridded global inventories, which have been extensively used in past inverse analyses. Our inventory shows large differences with the EDGAR v4.2 as well as its more recent version, EDGAR v4.3.2. Our results suggest that China{\textquoteright}s CMM emissions have been decreasing since 2012 on the basis of coal mining activities and assuming time-invariant emission factors but that regional trends differ greatly. Use of our inventory as prior information in future inverse modeling analyses can help better quantify CMM emissions as well as more confidently guide the future mitigation of coal to gas in China.},
	url = {https://pubs.acs.org/doi/abs/10.1021/acs.estlett.9b00294},
	author = {Jianxiong Sheng and Shaojie Song and Yuzhong Zhang and Ronald G. Prinn and Greet Janssens-Maenhout}
}
