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

تحليل متكامل لانبعاثات الميثان المعاصرة واتجاهات التركيز فوق الصين باستخدام الملاحظات في الموقع والأقمار الصناعية والمحاكاة النموذجية
Authors: H. Tan; L. Zhang; X. Lu; Y. Zhao; B. Yao; R. J. Parker; R. J. Parker; +2 Authors

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

Abstract

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 ratio 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 ratio 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 recent 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 11.4 % of the mean surface mixing ratio and drive 68.3 % 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 better assess the driving factors of CH4 mixing ratios and support the emission mitigation in China.

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Keywords

Atmospheric Science, China, Atmospheric sciences, Emission inventory, QC1-999, Astronomy, Organic chemistry, Stratospheric Chemistry and Climate Change Impacts, Greenhouse gas, Emission Modeling, Environmental science, Meteorology, Atmospheric Aerosols and their Impacts, Climate change, QD1-999, Biology, Climatology, Global and Planetary Change, Geography, Ecology, Mixing ratio, Physics, Geology, FOS: Earth and related environmental sciences, Air quality index, Earth and Planetary Sciences, Chemistry, Archaeology, Emissions, Satellite, FOS: Biological sciences, Global Methane Emissions and Impacts, Environmental Science, Physical Sciences, Methane

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Average
Average
Average
gold