Table 1.
Air pollution variation due to COVID-19 lockdown measures in different countries.
| Author | Country | Area covered | Environmental pollution | Conclusions |
|---|---|---|---|---|
| Wu et al., 2020a | USA | 3000 cities | PM2.5 | An increase of 1 μg/m3 of PM2.5 explained an 8% increase of COVID-19 mortality rate |
| Bashir et al., 2020a | USA | California | PM2.5, PM10, SO2, NO2, Pb, VOC and CO | PM2.5, PM10, SO2, NO2, and CO have a significant correlation with COVID-19 |
| Yongjian et al., 2020 | China | 120 cities | PM2.5, PM10, NO2 and O3 | Confirmed cases increase by 2.24%, 1.76%, 6.94% and 4.76%, respectively |
| Yao et al., 2020 | China | 49 cities | PM2.5 and PM10 | PM2.5 and PM10 increased 0.24% and 0.26% the case fatality of COVID-19, respectively |
| Zhang et al., 2020 | China | 219 cities | Air quality index | Air pollution has exerted a positive impact on the transmission and infection by COVID-19 |
| Xu et al., 2020a | China | 33 locations | Air quality index (AQI) | There is a direct correlation between AQI and confirmed COVID-19 cases |
| Fattorini and Regoli, 2020 | Italy | 71 provinces | NO2, O3, PM2.5 and PM10 | Significant correlation between poor air quality and COVID-19 cases |
| Zoran et al., 2020 | Italy | Milan | PM2.5 and PM10 | New COVID-19 cases have positively correlated with PM2.5 and PM10 |
| Filippini et al., 2020 | Italy | 28 provinces of Northern Italy | NO2 | High NO2 levels were associated with COVID-19 spread |
| Saha et al., 2020 | India | 25 cities | PM2.5, PM10, NO2, SO2, CO, and O3 | Significant correlation between poor air quality and COVID-19 deaths |
| Pansini and Fornacca, 2020 | China, Italy and USA | Countrywide | PM2.5, PM10, O3, NO2, SO2 and CO | Significant correlation between air quality and COVID-19 spread and mortality |
| Travaglio et al., 2020 | England | Countrywide | O3, NO and NO2 | Ozone, nitrogen oxide and nitrogen dioxide are significantly associated with COVID-19 deaths |
| Andree, 2020 | Netherlands | 355 municipalities | PM2.5 and PM10 | PM2.5 can be a significant predictor of the number of confirmed COVID-19 cases |
| Magazzino and Schneider, 2020 | French | Paris, Lyon, and Marseille | PM2.5 and PM10 | Suggests that there are certain conditions that increase the likelihood of the spread and aggravation of the disease |
| Suhaimi et al., 2020 | Malaysia | Kuala Lumpur | PM2.5, PM10, SO2, NO2, CO and O3 | Air pollutant influenced the incidence of COVID-19 cases |
| Ogen, 2020 | Italy, Spain, France and Germany | 66 administrative regions | NO2 | The long-term exposure to nitrogen dioxide may contribute to fatality caused by COVID-19 |