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Assessment of air quality before and during the COVID-19 and its potential health impacts in an arid oasis city: Urumqi, China.
- Source :
-
Stochastic Environmental Research & Risk Assessment . Apr2023, Vol. 37 Issue 4, p1265-1279. 15p. - Publication Year :
- 2023
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Abstract
- As a key node city of the "Silk Road Economic Belt" Urumqi has been listed as one of the ten most polluted cities in the world, posing a serious threat to the urban environment and residents' health. This study analyzed the air quality before and during the COVID-19 (Coronavirus disease 2019) pandemic and its potential health effects based on the data of PM2.5, PM10, SO2, NO2, CO, and O3_8h levels from 10 air quality monitoring stations in Urumqi from January 1, 2017, to December 31, 2021. As per the results, the concentrations of the air pollutants PM2.5, PM10, SO2, NO2, CO, and O3_8h in Urumqi from 2017 to 2021 showed a cyclical trend, and the implementation of COVID-19 prevention and control measures could effectively reduce the concentration(ρ) of air pollutants. The mean value of ρ(PM2.5) decreased from 2017 to 2021, whereas ρ(O3_8h) showed a waveform change trend (increased in 2017–2018, decreased in 2018–2020, and increased after 2020). Meanwhile, the maximum annual average values of ρ(PM2.5) and ρ(O3_8h) for the six monitoring stations during 2017–2021 occurred at sites S2 (74.37 µg m−3) and S6 (91.80 µg m−3), respectively; rapid industrialization had a greater impact on PM2.5 and O3_8h concentrations compared to commercial and residential areas. In addition, the air quality index data series can characterize the fluctuation trend of PM2.5. The high pollution levels (Class IV and V) of the air pollutants PM2.5 and O3_8h in Urumqi have been decreasing annually, and good days can account for 80–95% of the total number of days in the year, indicating that the number of days with a potential threat to residents' health is gradually decreasing. Therefore, more attention should be paid in controlling and managing air pollution in Urumqi. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 14363240
- Volume :
- 37
- Issue :
- 4
- Database :
- Academic Search Index
- Journal :
- Stochastic Environmental Research & Risk Assessment
- Publication Type :
- Academic Journal
- Accession number :
- 162970804
- Full Text :
- https://doi.org/10.1007/s00477-022-02338-4