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PM2.5 and PM10 during COVID-19 lockdown in Kuwait: Mixed effect of dust and meteorological covariates

ABSTRACT: This study investigated the impact of COVID-19 lockdown on particulate matter concentrations, specifically PM2.5 and PM10, in Kuwait. We studied the variations in PM2.5 and PM10 between the lockdown in 2020 with the corresponding periods of the years 2017–2019, and also investigated the differences in PM variations between the ‘curfew’ and ‘non curfew’ hours. We applied mixed-effect regression to investigate the factors that dictate PM variability (i.e., dust and meteorological covariates), and also processed satellite-based aerosol optical depths (AOD) to determine the spatial variability in aerosol loads. The results showed low PM2.5 concentration during the lockdown (33 μg/m3) compared to the corresponding previous three years (2017–2019); however, the PM10 concentration (122.5 μg/m3) increased relative to 2017 (116.6 μg/m3), and 2019 (92.8 μg/m3). After removing the ‘dust effects’, both PM2.5 and PM10 levels dropped by 18% and 31%, respectively. The mixed-effect regression model showed that high temperature and high wind speed were the main contributors to high PM2.5 and PM10, respectively, in addition to the dust haze and blowing dust. This study highlights that the reductions of anthropogenic source emissions are overwhelmed by dust events and adverse meteorology in arid regions, and that the lockdown did not reduce the high concentrations of PM in Kuwait.

SUBMITTER: Al-Hemoud A

PROVIDER: S-EPMC8282454 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:The impacts of the meteorological condition and emissions reduction on the aerosol concentration over the Beijing–Tianjin–Hebei (BTH) region during the COVID-19 lockdown were analyzed by conducting three numerical experiments, including one with the meteorological field in 2019 and MEIC-2019 (2019 monthly Multi-resolution Emissions Inventory for China), one with the meteorological field in 2020 and MEIC-2019, and one with the meteorological field in 2020 and MEIC-2020, via a WRF-Chem model. The numerical experiments were performed from 3 to 16 February in 2019 and in 2020, during which a severe fog–haze event (3–16 February 2020) occurred in the BTH region, with a simulated maximum daily PM2.5 of 245 μg m−3 in Tangshan and 175 μg m−3 in Beijing. The results indicate that the daily PM2.5 decreased by 5–150 μg m−3 due to the emissions reduction and increased by 10–175 μg m−3 due to the meteorological condition in Beijing, Shijiazhuang, Cangzhou, Handan, Hengshui, Chengde, Zhangjiakou, and Tangshan from 7 to 14 February. For the horizontal distribution, PM2.5 and different aerosol species concentrations from 7 to 14 February 2020 increased compared with those during the same period in 2019, indicating that the accumulation of pollutants caused by the unfavorable meteorological condition offset the decreases caused by the emissions reduction, leading to the high aerosol concentration during the COVID-19 lockdown. 摘要本研究从气象条件和减排两方面探讨了COVID-19封锁期间严重雾霾发生的原因[研究目的], 并定量的分析了气象条件和减排对PM2.5浓度的相对影响[创新点].使用WRF-Chem在2019年2月3日–16日和2020年2月3日–16日进行了三个数值模拟试验, 分别为2019年气象场与MEIC-2019 (2019年中国多分辨率月度排放清单) ,2020年气象场与MEIC-2019,2020年气象场与MEIC-2020[研究方法].结果表明COVID-19封锁期间严重雾霾的原因是不利气象条件增加的PM2.5浓度大于减排减少的PM2.5浓度[重要结论]. Graphical abstract Image, graphical abstract

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PM2.5 and PM10 during COVID-19 lockdown in Kuwait: Mixed effect of dust and meteorological covariates

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