the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Dynamics-based estimates of decline trend with fine temporal variations in China's PM2.5 emissions
Zhen Peng
Lili Lei
Zhe-Min Tan
Aijun Ding
Xingxia Kou
Abstract. Timely, continuous, and dynamics-based estimates of PM2.5 emissions with a high temporal resolution can be objectively and optimally obtained by assimilating observed surface PM2.5 concentrations using flow-dependent error statistics. Annual PM2.5 emissions in China have consistently decreased of approximately 3 % to 5 % from 2017 to 2020. Significant PM2.5 emission reductions occurred frequently in regions with large PM2.5 emissions. COVID-19 could cause a significant reduction of PM2.5 emissions in the north China plain and northeast of China in 2020. The magnitudes of PM2.5 emissions were greater in the winter than in the summer. PM2.5 emissions show an obvious diurnal variation that varies significantly with the season and urban population. Improved representations of PM2.5 emissions across time scales can benefit emission inventory, regulation policy and emission trading schemes, particularly for especially for high temporal resolution air quality forecasting and policy response to severe haze pollutions or rare human events with significant socioeconomic impacts.
Zhen Peng et al.
Status: open (until 09 Jun 2023)
Zhen Peng et al.
Zhen Peng et al.
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