EGU21-11969, updated on 04 Mar 2021
https://doi.org/10.5194/egusphere-egu21-11969
EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Evaluating the influence of COVID-19 pandemic on NO2 concentration variation in selected regions in China using TROPOMI data, surface measurements and modeling approaches

Zikang Jia1, Yijia Yuan1, Qianyu Pan1, Jianbing Jin2, and Song Gao1,3
Zikang Jia et al.
  • 1Duke Kunshan University, Kunshan, China (zj50@duke.edu)
  • 2Nanjing University of Information Science & Technology, Nanjing, China (jianbing.jin@nuist.edu.cn)
  • 3Duke University, Durham, NC, USA (song.gao212@duke.edu)

During the COVID-19 pandemic outbreak at the beginning of 2020, many Chinese urban agglomerations experienced noticeable air quality improvement. For example, recent analysis of surface measurements suggested that the concentration of NO2 decreased by on average 30% during the pandemic lockdown period in China in 2020 compared to 2019, although how much of this reduction is due to the pandemic or other factors (such as weather variation) is uncertain. We apply TROPOMI (Tropospheric Ozone Monitoring Instrument) NO2 Level 2 data (converted to Level 3 data) to analyzing the spatial and temporal evolution of NO2 in major Chinese city clusters including Jing-Jin-Ji and Yantze River Delta. These observational results are compared with monitoring station data, as well as predicted results from machine learning techniques and a chemical transport model (SILAM), taking meteorological factors into account. We then evaluate the impact of COVID-19 and lockdown measures on the concentration of NO2 comprehensively. For example, initial results indicate the NO2 concentration in Shanghai area decreased by about 37% during late January to early March in 2020, comparing the prediction by a machine learning technique (random forest) and the observed surface data, partly due to the pandemic control measures. It is expected the COVID-19 pandemic would be a long-term challenge accompanying the human development. Based on these findings, relevant mechanism of NO2 pollution and control, affected by the pandemic and periodic lockdown measures in China, will be discussed.

How to cite: Jia, Z., Yuan, Y., Pan, Q., Jin, J., and Gao, S.: Evaluating the influence of COVID-19 pandemic on NO2 concentration variation in selected regions in China using TROPOMI data, surface measurements and modeling approaches, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11969, https://doi.org/10.5194/egusphere-egu21-11969, 2021.

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