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Impacts of TROPOMI-Derived NO X Emissions on NO2 and O3 Simulations in the NCP during COVID-19.
Zhu, Yizhi; Liu, Cheng; Hu, Qihou; Teng, Jiahua; You, Daian; Zhang, Chengxin; Ou, Jinping; Liu, Ting; Lin, Jinan; Xu, Tianyi; Hong, Xinhua.
  • Zhu Y; Key Lab of Environmental Optics & Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China.
  • Liu C; Key Lab of Environmental Optics & Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China.
  • Hu Q; Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China.
  • Teng J; Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China.
  • You D; Key Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes, University of Science and Technology of China, Hefei 230026, China.
  • Zhang C; Key Lab of Environmental Optics & Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China.
  • Ou J; China Satellite Application Center for Ecology and Environment, MEE, Beijing 100094, China.
  • Liu T; China Satellite Application Center for Ecology and Environment, MEE, Beijing 100094, China.
  • Lin J; Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China.
  • Xu T; Key Lab of Environmental Optics & Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China.
  • Hong X; School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, China.
ACS Environ Au ; 2(5): 441-454, 2022 Sep 21.
Article in English | MEDLINE | ID: covidwho-2062151
ABSTRACT
NO2 and O3 simulations have great uncertainties during the COVID-19 epidemic, but their biases and spatial distributions can be improved with NO2 assimilations. This study adopted two top-down NO X inversions and estimated their impacts on NO2 and O3 simulation for three periods the normal operation period (P1), the epidemic lockdown period following the Spring Festival (P2), and back to work period (P3) in the North China Plain (NCP). Two TROPOspheric Monitoring Instrument (TROPOMI) NO2 retrievals came from the Royal Netherlands Meteorological Institute (KNMI) and the University of Science and Technology of China (USTC), respectively. Compared to the prior NO X emissions, the two TROPOMI posteriors greatly reduced the biases between simulations with in situ measurements (NO2 MREs prior 85%, KNMI -27%, USTC -15%; O3 MREs Prior -39%, KNMI 18%, USTC 11%). The NO X budgets from the USTC posterior were 17-31% higher than those from the KNMI one. Consequently, surface NO2 levels constrained by USTC-TROPOMI were 9-20% higher than those by the KNMI one, and O3 is 6-12% lower. Moreover, USTC posterior simulations showed more significant changes in adjacent periods (surface NO2 P2 vs P1, -46%, P3 vs P2, +25%; surface O3 P2 vs P1, +75%, P3 vs P2, +18%) than the KNMI one. For the transport flux in Beijing (BJ), the O3 flux differed by 5-6% between the two posteriori simulations, but the difference of NO2 flux between P2 and P3 was significant, where the USTC posterior NO2 flux was 1.5-2 times higher than the KNMI one. Overall, our results highlight the discrepancies in NO2 and O3 simulations constrained by two TROPOMI products and demonstrate that the USTC posterior has lower bias in the NCP during COVD-19.

Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies Language: English Journal: ACS Environ Au Year: 2022 Document Type: Article Affiliation country: Acsenvironau.2c00013

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies Language: English Journal: ACS Environ Au Year: 2022 Document Type: Article Affiliation country: Acsenvironau.2c00013