Published in

European Geosciences Union, Atmospheric Chemistry and Physics, 2(22), p. 1229-1249, 2022

DOI: 10.5194/acp-22-1229-2022

Links

Tools

Export citation

Search in Google Scholar

An integrated analysis of contemporary methane emissions and concentration trends over China using in situ and satellite observations and model simulations

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

Full text: Download

Green circle
Preprint: archiving allowed
Green circle
Postprint: archiving allowed
Green circle
Published version: archiving allowed
Data provided by SHERPA/RoMEO

Abstract

China, being one of the major emitters of greenhouse gases, has taken strong actions to tackle climate change, e.g., to achieve carbon neutrality by 2060. It also becomes important to better understand the changes in the atmospheric mixing ratios and emissions of CH4, the second most important human-influenced greenhouse gas, in China. Here we analyze the sources contributing to the atmospheric CH4 mixing ratios and their trends in China over 2007–2018 using the GEOS-Chem model simulations driven by two commonly used global anthropogenic emission inventories: the Emissions Database for Global Atmospheric Research (EDGAR v4.3.2) and the Community Emissions Data System (CEDS). The model results are interpreted with an ensemble of surface, aircraft, and satellite observations of CH4 mixing ratios over China and the Pacific region. The EDGAR and CEDS estimates show considerable differences reflecting large uncertainties in estimates of Chinese CH4 emissions. Chinese CH4 emission estimates based on EDGAR and natural sources increase from 46.7 Tg per annum (Tg a−1) in 1980 to 69.8 Tg a−1 in 2012 with an increase rate of 0.7 Tg a−2, and estimates with CEDS increase from 32.9 Tg a−1 in 1980 and 76.7 Tg a−1 in 2014 (a much stronger trend of 1.3 Tg a−2 over the period). Both surface, aircraft, and satellite measurements indicate CH4 increase rates of 7.0–8.4 ppbv a−1 over China in the past decade. We find that the model simulation using the CEDS inventory and interannually varying OH levels can best reproduce these observed CH4 mixing ratios and trends over China. Model results over China are sensitive to the global OH level, with a 10 % increase in the global tropospheric volume-weighted mean OH concentration presenting a similar effect to that of a 47 Tg a−1 decrease in global CH4 emissions. We further apply a tagged tracer simulation to quantify the source contributions from different emission sectors and regions. We find that domestic CH4 emissions account for 14.0 % of the mean surface mixing ratio and drive 66.7 % of the surface trend (mainly via the energy sector) in China over 2007–2018. We emphasize that intensive CH4 measurements covering eastern China will help us better assess the driving factors of CH4 mixing ratios and support the emission mitigation in China.