Effects of the 2020 and 2021 lockdowns on air pollutants: A case study of PM2.5 in Kampala, Uganda.
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This research aimed at assessing the effect of the traffic free conditions experienced during the 2020 and 2021 lockdowns on PM2.5 concentration levels in Kampala city, Uganda while factoring in meteorological influences. The study adopted the following specific objectives: To establish the spatial variations in PM2.5 concentrations during 2019,2020 and 2021; To establish the temporal variations in PM2.5 concentrations and meteorological elements during 2017-2021 period; and to establish the relationship between meteorological elements and PM2.5 concentrations in Kampala. Data on Kampala’s PM2.5 concentrations were obtained from Air Quality Monitoring at the US. Embassy in Uganda (www.airnow.gov) and at Airqo (www.airqo.net) from College of Computing and Information Sciences, Makerere University. Kampala’s daily precipitation, temperature and wind speed datasets were obtained from the Uganda National Meteorological Authority (UNMA). Using the Inverse Distance Weighted (IDW) interpolation and trend analysis, the seasonal spatial variations in PM2.5 concentrations were established. On a spatial scale, PM2.5 concentration levels were observed to be lower for all stations during the 2020 lockdown which took place during MAM and the 2021 lockdown which took place during JJA compared to the concentration levels observed during the same time period in the lockdown free year of 2019. Reductions could be attributed to the reduction in traffic and industrial-based emissions resulting from the travel restrictions imposed during the lockdowns. High PM2.5 concentration peaks were observed during the dry season when the deviation from long-term mean was plotted. A monthly analysis then showed that the highest deviation from the long-term monthly mean was observed in June 2019 and the lowest deviation was observed in March 2017. However, in both temporal analyses, no exceptional deviations were experienced during the lockdown years. Therefore, on a temporal scale, the variation patterns of PM2.5 concentrations were not affected by the traffic free conditions experienced during the lock downs although some reductions were observed. A regression analysis was then performed at seasonal level to establish the influence of each meteorological element on the PM2.5 concentrations. Precipitation and PM2.5 concentrations had a significant relationship only during the DJF dry season. Temperature and PM2.5 concentrations did not have a significant relationship during both the wet and dry seasons. Windspeed had a significant negative relationship with PM2.5 concentrations only during the DJF dry season.