During the COVID-19 lockdown in early
2020, observations in Beijing
indicate that secondary organic aerosol (SOA) concentrations increased
despite substantial emission reduction, but the reasons are not fully
explained. Here, we integrate the two-dimensional volatility basis
set into a state-of-the-art chemical transport model, which unprecedentedly
reproduces organic aerosol (OA) components resolved by the positive
matrix factorization based on aerosol mass spectrometer observations.
The model shows that, for Beijing, the emission reduction during the
lockdown lowered primary organic aerosol (POA)/SOA concentrations
by 50%/18%, while deteriorated meteorological conditions increased
them by 30%/119%, resulting in a net decrease in the POA concentration
and a net increase in the SOA concentration. Emission reduction and
meteorological changes both led to an increased OH concentration,
which accounts for their distinct effects on POA and SOA. SOA from
anthropogenic volatile organic compounds and organics with lower volatility
contributed 28 and 62%, respectively, to the net SOA increase. Different
from Beijing, the SOA concentration decreased in southern Hebei during
the lockdown because of more favorable meteorology. Our findings confirm
the effectiveness of organic emission reductions and meanwhile reveal
the challenge in controlling SOA pollution that calls for large organic
precursor emission reductions to rival the adverse impact of OH increase