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. 2024 Jan 17;12(1):81.
doi: 10.3390/toxics12010081.

The Variation in Chemical Composition and Source Apportionment of PM2.5 before, during, and after COVID-19 Restrictions in Zhengzhou, China

Jinting Huang  1   2 , Aomeng Cai  2   3 , Weisi Wang  4 , Kuan He  1 , Shuangshuang Zou  2 , Qingxia Ma  2   3
Affiliations

The Variation in Chemical Composition and Source Apportionment of PM2.5 before, during, and after COVID-19 Restrictions in Zhengzhou, China

Jinting Huang et al. Toxics. .

Abstract

Despite significant improvements in air quality during and after COVID-19 restrictions, haze continued to occur in Zhengzhou afterwards. This paper compares ionic compositions and sources of PM2.5 before (2019), during (2020), and after (2021) the restrictions to explore the reasons for the haze. The average concentration of PM2.5 decreased by 28.5% in 2020 and 27.9% in 2021, respectively, from 102.49 μg m-3 in 2019. The concentration of secondary inorganic aerosols (SIAs) was 51.87 μg m-3 in 2019, which decreased by 3.1% in 2020 and 12.8% in 2021. In contrast, the contributions of SIAs to PM2.5 increased from 50.61% (2019) to 68.6% (2020) and 61.2% (2021). SIAs contributed significantly to PM2.5 levels in 2020-2021. Despite a 22~62% decline in NOx levels in 2020-2021, the increased O3 caused a similar NO3- concentration (20.69~23.00 μg m-3) in 2020-2021 to that (22.93 μg m-3) in 2019, hindering PM2.5 reduction in Zhengzhou. Six PM2.5 sources, including secondary inorganic aerosols, industrial emissions, coal combustion, biomass burning, soil dust, and traffic emissions, were identified by the positive matrix factorization model in 2019-2021. Compared to 2019, the reduction in PM2.5 from the secondary aerosol source in 2020 and 2021 was small, and the contribution of secondary aerosol to PM2.5 increased by 13.32% in 2020 and 12.94% in 2021. In comparison, the primary emissions, including biomass burning, traffic, and dust, were reduced by 29.71% in 2020 and 27.7% in 2021. The results indicated that the secondary production did not significantly contribute to the PM2.5 decrease during and after the COVID-19 restrictions. Therefore, it is essential to understand the formation of secondary aerosols under high O3 and low precursor gases to mitigate air pollution in the future.

Keywords: haze; high O3; reduced PM2.5 level; stable NO3− level.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Location of the site (Zhengzhou) and topography in China.
Figure 2
Figure 2
Evolution of meteorological conditions (a,b), particulate matter (PM10 and PM2.5) (c), and gaseous pollutants (NO, NO2, SO2, CO, and O3) (d,e) in 2019, 2020, and 2021.
Figure 3
Figure 3
Change ratios of pollutant concentrations in 2020 and 2021 compared to 2019.
Figure 4
Figure 4
Average mass concentrations (a) and mass fractions (b) of PM2.5 constituents (SO42−, NO3−, NH4+, POA, SOA, EC, Cl−, K+, Na+, Ma2+, and Ca2+), NOR, and SOR in 2019, 2020, and 2021.
Figure 5
Figure 5
Correlations between NO3−, SO42−, and precursor gases in 2019 (a,d), 2020 (b,e), and 2021 (c,f). Symbols in (a–f) are scaled by conversion ratios (NOR and SOR) and colored by PM2.5 concentrations.
Figure 6
Figure 6
Correlations between conversion ratios (NOR and SOR) and RH in 2019 (a,d), 2020 (b,e), and 2021 (c,f). Symbols in (a–f) are scaled by O3 concentration and colored by O3/Ox. The oxidants (Ox) are the sum of NO2 and O3, a proxy for atmospheric oxidation caused by photochemical reactions.
Figure 7
Figure 7
Six sources’ profiles (bars) (in units of μg μg−1) and contribution percentages (black dots) from each source factor resolved from the PMF model in 2019 (a), 2020 (b), and 2021 (c).
Figure 8
Figure 8
NOR and SOR with RH in the daytime (08:00–19:00) (a,c) and nighttime (20:00–07:00) (b,d) in 2019 2020 and 2021.
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