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. The rapid response to the COVID-19 pandemic led to unprecedented decreases ineconomic activities, thereby reducing the pollutant emissions. A random forest(RF) model was applied to determine the respective contributions ofmeteorology and anthropogenic emissions to the changes in air quality. Theresult suggested that the strict lockdown measures significantly decreased primarycomponents such as Cr (−67 %) and Fe (−61 %) inPM2.5 (p&lt;0.01), whereas the higher relative humidity (RH) andNH3 level and the lower air temperature (T) remarkably enhancedthe production of secondary aerosol, including SO42-(29 %), NO3- (29 %), and NH4+(21 %) (p&lt;0.05). The positive matrix factorization (PMF) resultsuggested that the contribution ratios of secondary formation (SF), industrialprocess (IP), biomass burning (BB), coal combustion (CC), and road dust (RD)changed from 36 %, 27 %, 21 %,12 %, and 4 % before the COVID-19 outbreak to44 %, 20 %, 20 %, 9 %, and7 %, respectively. The rapid increase in the contribution ratioderived from SF to PM2.5 implied that the intermittent haze events duringthe COVID-19 period were characterized by secondary aerosol pollution, which wasmainly contributed by the unfavorable meteorological conditions and highNH3 level.

atmospheric chemistry and physics

Substantial changes in gaseous pollutants and chemical compositions in fine particles in the North China Plain during the COVID-19 lockdown period: anthropogenic vs. meteorological influences