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<p>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 <span class="inline-formula">CH₄</span>, the second most important human-influenced greenhouse gas, in China. Here we analyze the sources contributing to the atmospheric <span class="inline-formula">CH₄</span> 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 <span class="inline-formula">CH₄</span> mixing ratios over China and the Pacific region. The EDGAR and CEDS estimates show considerable differences reflecting large uncertainties in estimates of Chinese <span class="inline-formula">CH₄</span> emissions. Chinese <span class="inline-formula">CH₄</span> emission estimates based on EDGAR and natural sources increase from 46.7 <span class="inline-formula">Tg</span> per annum (<span class="inline-formula">Tg a⁻¹</span>) in 1980 to 69.8 <span class="inline-formula">Tg a⁻¹</span> in 2012 with an increase rate of 0.7 <span class="inline-formula">Tg a⁻²</span>, and estimates with CEDS increase from 32.9 <span class="inline-formula">Tg a⁻¹</span> in 1980 and 76.7 <span class="inline-formula">Tg a⁻¹</span> in 2014 (a much stronger trend of 1.3 <span class="inline-formula">Tg a⁻²</span> over the period). Both surface, aircraft, and satellite measurements indicate <span class="inline-formula">CH₄</span> increase rates of 7.0–8.4 <span class="inline-formula">ppbv a⁻¹</span> 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 <span class="inline-formula">CH₄</span> mixing ratios and trends over China. Model results over China are sensitive to the global OH level, with a 10 <span class="inline-formula">%</span> increase in the global tropospheric volume-weighted mean OH concentration presenting a similar effect to that of a 47 <span class="inline-formula">Tg a⁻¹</span> decrease in global <span class="inline-formula">CH₄</span> emissions. We further apply a tagged tracer simulation to quantify the source contributions from different emission sectors and regions. We find that domestic <span class="inline-formula">CH₄</span> emissions account for 14.0 <span class="inline-formula">%</span> of the mean surface mixing ratio and drive 66.7 <span class="inline-formula">%</span> of the surface trend (mainly via the energy sector) in China over 2007–2018. We emphasize that intensive <span class="inline-formula">CH₄</span> measurements covering eastern China will help us better assess the driving factors of <span class="inline-formula">CH₄</span> mixing ratios and support the emission mitigation in China.</p>