Anthropogenic methane emissions in China estimated from GOSAT satellite observations

China's methane emissions are the largest anthropogenic source in the global methane budget according to the recent UNFCCC reports. However, China's emissions are poorly quantified in particular its major source sector of coal mining. Here we use 2010-2017 GOSAT satellite observations of methane columns in a top-down (inverse modeling) analysis to improve the estimates of China's methane emissions and trends. Our inversion uses a Lagrangian particle dispersion model (NAME) as the forward model (up to 25 km resolution) and optimizes emissions under a hierarchical Bayesian framework with the Markov Chain Monte Carlo (MCMC) algorithm. This method characterizes not only the probability density functions (pdfs) of posterior estimates but also the pdfs of prior and observational covariances, which are not accounted for in traditional Bayesian inversions. Our inversion uses WETCHART v1.2 for natural wetlands and EDGAR v4.3.2 for anthropogenic sources, except for oil/gas and coal mining sectors that we replace with state-of-the-art emission inventories having more accurate emission patterns (Scarpelli et al., 2019; Sheng et al., ES&T Letters, 2019). The inversion results show that total anthropogenic methane emissions in China are comparable to those reported in UNFCCC and have been stable since 2012, but that regional trends differ greatly. Our results also suggest that China's coal mine methane emissions have slowed since 2012, consistent with its coal mining activities. Furthermore, our results show no trends for the natural gas sector though increasing natural gas production and consumption in China. These findings would further assert climate benefits of coal-to-gas policy in China.