Unbalanced emission reductions of different species and sectors in China during COVID-19 lockdown derived by multi-species surface observation assimilation
- 1State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
- 2CAS-TWAS Center of Excellence for Climate and Environment Sciences (ICCES), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
- 3University of Chinese Academy of Sciences, Beijing 100049, China
- 4Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
- 5Institute of Surface-Earth System Science, Tianjin University, Tianjin 300072, China
- 6Department of Geography, State Key Laboratory of Environmental and Biological Analysis, Hong Kong Baptist University, Hong Kong SAR, China
- 7State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention andControl, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
- 8Chengdu University of Information Technology, Chengdu 610225, China
- 9National Institute for Environmental Studies, Onogawa, Tsukuba 305-8506, Japan
- 10Center for Global and Regional Environmental Research, University of Iowa, Iowa City, IA 52242, USA
Abstract. The unprecedented lockdown of human activities during the COVID-19 pandemic have significantly influenced the social life in China. However, understanding of the impact of this unique event on the emissions of different species is still insufficient, prohibiting the proper assessment of the environmental impacts of COVID-19 restrictions. Here we developed a multi-air pollutant inversion system to simultaneously estimate the emissions of NOx, SO2, CO, PM2.5 and PM10 in China during COVID-19 restrictions with high temporal (daily) and horizontal (15 km) resolutions. Subsequently, contributions of emission changes versus meteorology variations during COVID-19 lockdown were separated and quantified. The results demonstrated that the inversion system effectively reproduced the actual emission variations of multi-air pollutants in China during different periods of COVID-19 lockdown, which indicate that the lockdown is largely a nationwide road traffic control measurement with NOx emissions decreased substantially by ~40 %. However, emissions of other air pollutants were found only decreased by ~10 %, both because power generation and heavy industrial processes were not halted during lockdown, and residential activities may actually have increased due to the stay-at-home orders. Consequently, although obvious reductions of PM2.5 concentrations occurred over North China Plain (NCP) during lockdown period, the emission change only accounted for 8.6 % of PM2.5 reductions, and even led to substantial increases of O3. The meteorological variation instead dominated the changes in PM2.5 concentrations over NCP, which contributed 90 % of the PM2.5 reductions over most parts of NCP region. Meanwhile, our results also suggest that the local stagnant meteorological conditions together with inefficient reductions in PM2.5 emissions were the main drivers of the unexpected COVID-19 haze in Beijing. These results highlighted that traffic control as a separate pollution control measure has limited effects on the coordinated control of O3 and PM2.5 concentrations under current complex air pollution conditions in China. More comprehensive and balanced regulations for multiple precursors from different sectors are required to address O3 and PM2.5 pollution in China.
Lei Kong et al.
Lei Kong et al.
Lei Kong et al.
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