Analysis of Air Quality Changes and Influencing Factors in Changchun during the COVID-19 Pandemic in 2020

Abstract

To study the air quality changes during the Corona Virus Disease 2019 (COVID-19) lockdown in Changchun, we analyzed the changes in pollution of six major pollutants (PM2.5, PM10, SO2, NO2, O3, CO) and correlated them with meteorological parameters, using meteorological data and pollutants concentration data. Regional transport pathways and potential source areas of pollutants were analyzed using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model and Potential Source Contribution Function (PSCF). The results showed that the concentrations of PM2.5, PM10, SO2, NO2, CO were 30.5%-53.8% lower in the Level I period and 49.4%-65.0% lower in the Level II period than in the Pre-lockdown period, respectively.Conversely, O3 increased 59.6% and 58.1% during Level I and Level II, respectively, compared to the Pre-lockdown period. During the 55-day lockdown, daily average concentrations of each pollutant were lower than in previous years on 36-55 days, while O3 was higher on 35 days. The pollutants that decreased in concentration during the lockdown also showed an increase during the Level III period (up to 188.5%). The maximum daily growth rate of PM2.5 during the lockdown period in 2020 was 16.0%, which was higher than this value in the same period of previous years (21.8%, 21.4%, 17.4%). This shows that the change trend of pollutants during the lockdown period is smoother than in previous years. Temperature and O3 were positively correlated before the lockdown and during Level Ⅰ and weakly negatively correlated during Level Ⅱ and Level Ⅲ.Despite the prevalence of northwest winds in winter, a high percentage of trajectories from other directions (up to 36.8%) was observed during the lockdown. Simultaneously, the lockdown reduced the potential source area for PM2.5 (WPSCF≥0.000007), but rebounded after the lockdown was lifted. In conclusion, the lockdown only temporarily reduced the air pollution in Changchun.

Spatiotemporal impact of COVID-19 on Taiwan air quality in the absence of a lockdown: Influence of urban public transportation use and meteorological conditions

“…Conversely, the change trends of the NO 2 and CO concentrations (major pollutants emitted from transportation) that demonstrate substantial correlations with roadway and air transportation were congruent with the transportation usage volume, except during the wet season (May to August). Similar findings were reported by Gao et al (2021) and Tian et al (2021) in China and Canada during the COVID-19 period, respectively, where NO 2 and CO were fairly correlated with the traffic volume, advocating for the importance of proper public transportation planning in addressing NO 2 and CO pollution. There was no statistical correlation observed between O 3 and traffic volume; however, high concentration up to 62 ppm observed in April may have been caused by reduced mobility ( Siciliano et al, 2020 ).…”

Spatial Characteristics and Regional Transmission Analysis of PM2.5 Pollution in Northeast China, 2016–2020

“…Higher PM 2.5 concentrations were concentrated in three provincial capitals and surrounding cities, of which Jilin Province is sandwiched in the middle and has slightly better indicators than the other two provinces caused by the transmission from the highly polluted regions [ 42 ]. Previous studies concerning the perennial air mass trajectory movement pattern prove have shown that more than 60% of the polluted air masses come from Inner Mongolia in the north direction of Northeast China [ 43 ]. In contrast, Liaoning Province borders Bohai Bay and variable weather systems following the reduction of local emissions have resulted in the region being more affected by meteorological transport.…”

Impacts of Strategic Mobility Restrictions Policies during 2020 COVID-19 Outbreak on Brazil’s Regional Air Quality

“…In all the five States studied, the concentration of O3 was higher in 2020 than the average from 2015 to 2019. This increase has also been observed worldwide and may be related to the chemical formation regime of O3 (Collivignarelli et al, 2020;Dutta and Jinsart, 2021;Gao et al, 2021;Grange et al, 2021;Lu et al, 2013;Sharma et al, 2020;Sicard et al, 2020), which in large cities is usually Volatile Organic Compounds (VOC) limited. According to Siciliano et al (2020), who evaluated the increase of O3 in Rio de Janeiro city, the greatest concentrations result from higher ratios of non-methane hydrocarbons (NMHC) and nitrogen oxides (NOx), i.e., more significant reduction of NOx than of NMHC.…”