Asian Journal of Atmospheric Environment (Dec 2023)

Update of the year 2019 modeling emission inventory in China

  • Seoyeon Kim,
  • Jinseok Kim,
  • Hyejung Hu,
  • Meongdo Jang,
  • Jae-Bum Lee,
  • Sung Chul Hong,
  • Okgil Kim,
  • Jung-Hun Woo

DOI
https://doi.org/10.1007/s44273-023-00012-x
Journal volume & issue
Vol. 17, no. 1
pp. 1 – 14

Abstract

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Abstract Using updated emission inventories can enhance the accuracy of air quality forecast models. Given China’s rapid economic growth and Korea’s geographical and meteorological position on the windward side of China, updating China’s emission inventory has become particularly crucial for Korea’s air quality modeling. This study aimed to develop an updated version of China’s Emission Inventory in Comprehensive Regional Emissions for Atmospheric Transport Experiments version 3 for the base year of 2019 (CREATEv3 (YR 2019)). To achieve this goal, we utilized the Chinese emission inventory of CREATEv3 for the base year of 2015 (CREATEv3 (YR 2015)) as a framework to incorporate the latest Chinese emission data from the Multi-resolution Emission Inventory Model for Climate and Air Pollution Research for the base year of 2019 (MEIC COVID-19 (YR 2019)) and update the inventory. The updated China’s annual emissions are now reflected in CREATEv3 (YR 2019), and the amounts are as follows: 132 Tg for CO, 21 Tg for NO x , 8 Tg for SO2, 7 Tg for PM2.5, 9 Tg for NH3, and 28 Tg for volatile organic compound (VOC). By comparing previous Chinese emission inventories with the updated inventory developed in this study, it was found that SO2, NO x , VOC, and NH3 emissions were decreased. Therefore, using the updated inventory seemingly reduces the impact of China’s fine dust on Korea. By comparing emissions by pollutant and region in China using CREATEv3 (YR 2019), it was found that regions with high emissions of targeted pollutants strongly correlated with major industries operating in those areas. This study is expected to provide insights into China’s emission changes in 2019 and support air quality forecasting.

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