Preprints
https://doi.org/10.5194/essd-2020-210
https://doi.org/10.5194/essd-2020-210

  24 Aug 2020

24 Aug 2020

Review status: a revised version of this preprint was accepted for the journal ESSD and is expected to appear here in due course.

Evaluation of anthropogenic CH4 emissions over China using bottom-up inventories

Xiaohui Lin1, Wen Zhang1, Monica Crippa2, Shushi Peng3, Pengfei Han4, Ning Zeng5, Lijun Yu1, and Guocheng Wang1 Xiaohui Lin et al.
  • 1State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
  • 2European Commission, Joint Research Centre (JRC), Ispra, Italy
  • 3Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China
  • 4State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
  • 5Department of Atmospheric and Oceanic Science, and Earth System Science Interdisciplinary Center, University of Maryland, College Park, Maryland, USA

Abstract. Atmospheric methane (CH4) is a potent greenhouse gas that is strongly influenced by several human activities. China, as one of the major agricultural and energy production countries, e.g., rice cultivation, ruminant feeding and coal production, contributes considerably to the global anthropogenic CH4 emissions. Understanding the characteristics of China's CH4 emissions is necessary for interpreting source contributions and for further climate change mitigation. However, the scarcity of data from some sources or years and spatially explicit information pose great challenges to completing an analysis of CH4 emissions. This study provides a comprehensive evaluation of China's anthropogenic CH4 emissions by synthesizing most of the currently available data (12 inventories). The results show that anthropogenic CH4 emissions differ widely among inventories, with values ranging from 41.9–57.5 Tg CH4 yr−1 in 2010. The discrepancy primarily resulted from the energy sector (27.3–60.0 % of total emissions), followed by the agricultural (26.9–50.8 %), and waste treatment (8.1–21.2 %) sectors. Temporally, emissions among inventories stabilized in the 1990s, but increased significantly thereafter, with annual average growth rates (AAGRs) of 1.8–3.9 % during 2000–2010, but slower AAGRs of 0.5–2.2 % during 2011–2015. Spatially, the growth of CH4 emissions could be attributed mostly to an increase in emissions from the energy sector (mainly from coal mining) in the northern and central inland regions, followed by waste treatment in the southern and eastern regions. The availability of detailed activity data for sectors or subsectors and the use of region-specific emission factors play important roles in understanding source contributions, and reducing the uncertainty of bottom-up inventories.

Xiaohui Lin et al.

 
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Status: closed
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Xiaohui Lin et al.

Xiaohui Lin et al.

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