The coronavirus disease 2019 (COVID-19), which became a global pandemic by March 2020, forced almost all countries over the world to impose the lockdown as a measure of social distancing to control the spread of infection. India also strictly implemented a countrywide lockdown, starting from 24 March to 12 May 2020. This measure resulted in the reduction of the sources of air pollution in general: industrial, commercial, and vehicular pollution in particular, with visible improvement in ambient air quality. In this study, the impact of COVID-19 lockdown on the ambient concentration of air pollutants over the city of Bangalore (India) is assessed using Continuous Ambient Air Quality Measurement (CAAQM) data from 10 monitoring stations spread across the city. The data was obtained from Central Pollution Control Board (CPCB) and Karnataka State Pollution Control Board (KSPCB). The analysis of the relative changes in the ambient concentration of six major air pollutants (NO, NO 2 , NO X , PM 2.5 , O 3 , and SO 2 ) has been carried out for two periods: March–May 2020 (COVID-19 lockdown) and the corresponding period of 2019 during when there was no lockdown. The analysis revealed significant reduction in the concentration of ambient air pollutants at both daily and monthly intervals. This can be attributed to the reduction in sources of emission; vehicular traffic, industrial, and other activities. The average reduction in the concentration of NO, NO 2 , NO X , PM 2.5 , and O 3 between 01 March and 12 May 2020 was found to be 63%, 48%, 48%, 18%, and 23% respectively when compared to the same period in 2019. Similarly, the comparative analysis of pollutant concentrations between pre-lockdown (01–23 March 2020) and lockdown (24 March–12 May 2020) periods has shown a huge reduction in the ambient concentration of air pollutants, 47.3% (NO), 49% (NO 2 ), 49% (NO X ), 10% (SO 2 ), 37.7% (PM 2.5 ), and 15.6% (O 3 ), resulting in improved air quality over Bangalore during the COVID-19 lockdown period. It is shown that the strict lockdown resulted in a significant reduction in the pollution levels. Such lockdowns may be useful as emergency intervention strategies to control air pollution in megacities when ambient air quality deteriorates dangerously.

BackgroundThe Corona virus disease 2019 (COVID-19) mainly caused by the novel severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) became a global pandemic by March 2020. Actually, there is no strong evidence of weather and COVD-19 spread relation as it is a new virus. This study mainly focuses on the tropical weather impact on the spatio-temporal spread of COVID-19 during the early stages i.e. March-May 2020 in India, which is a large country where the disease has shown an exponential growth.Methods This study is an attempt to assess the relationship of major environmental parameters like solar radiation, air temperature and relative humidity with the positive cases of COVID-19 for the period March-May 2020 which is the summer season or pre-monsoon season over India. The time series and significant correlation analysis at daily, weekly scale and the spatial analysis of weather and COVID-19 cases are presented.ResultsThe results show a significant correlation of solar radiation and atmospheric temperature with COVID-19 cases, both at daily and weekly scale in India whereas relative humidity has low correlation in the study period. But the temperature humidity index (THI), a measure of the thermal stress, shows positive correlation with the disease spread. ConclusionsThese results could be a good input for developing the integrated modelling framework for the COVID-19 forecasting using state of art numerical weather prediction model and disease process modelling.

The Coronavirus disease 2019 (COVID-19), which became a global pandemic by March 2020 (WHO, 2020), forced almost all countries over the world to impose the lockdown as a measure of social distancing to control the spread of infection. India also strictly implemented a countrywide lockdown, starting from 24th March onwards. This measure resulted in the reduction of the sources of air pollution in general; industrial, commercial, and vehicular pollution in particular, with visible improvement in Ambient Air Quality. In this study, the impact of COVID-19 lockdown on the ambient concentration of air pollutants over the city of Bengaluru (India) is assessed using Continuous Ambient Air Quality Measurement (CAAQM) data from 10 monitoring stations spread across the city. The data was obtained from Central Pollution Control Board (CPCB) and Karnataka State Pollution Control Board (KSPCB). The analysis of the relative changes in the ambient concentration of six major air pollutants (NO, NO2, NOX, PM2.5, O3, and SO2) been carried out for two periods; March-May 2020 (COVID-19 lockdown) and the corresponding period of 2019 which was Non-COVID. The analysis revealed significant reduction in the concentration of ambient air pollutants at both daily and monthly intervals. This can be attributed to the reduction in sources of emission; vehicular traffic, industrial, and other activities. The average reduction in the concentration of NO, NO2, NOX, PM2.5, and O3 between 1st March to 12th May 2020 was found to be 63%, 48%, 48%, 18%, and 23% respectively when compared to the same period in 2019. Similarly, the comparative analysis of pollutant concentrations between pre-lockdown (March 01- March 23) and lockdown (Mar 24-May 12) period, shown a huge reduction in the ambient concentration of air pollutants; 47.3% (NO), 49% (NO2), 49% (NOX), 10% (SO2), 37.7% (PM2.5), and 15.6% (O3), resulting in improved air quality over Bangalore during the COVID-19 lockdown period. It is shown that the strict lockdown resulted in a significant reduction in the pollution levels. Such lockdowns may be useful as emergency intervention strategies to control air pollution in megacities when ambient air quality deteriorates dangerously.

The Corona virus disease 2019 (COVID-19) mainly caused by the novel severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) became a global pandemic by March 2020. Actual there is no strong evidence of weather and COVD-19 spread relation as it is a new virus. This study is mainly focussed on the tropical weather impact on the spatio-temporal spread of COVID-19 during the early stages i.e. March-May 2020 in India, which is a large country where the disease has shown an exponential growth. This study is an attempt to assess the relationship of major environmental parameters like solar radiation, air temperature and humidity with the positive cases of COVID-19 for the period March-May 2020 which is the summer season or pre-monsoon season over India. The time series and significant correlation analysis at daily, weekly scale and the spatial analysis of weather and COVID-19 cases are presented. The results show significant correlation of solar radiation and atmospheric temperature with COVID-19 cases both at daily and weekly scale in India whereas humidity has low correlation in the study period. But the temperature humidity index (THI) a measure of the thermal stress shows positive correlation with the disease spread. These results can be a good input for developing the integrated modelling framework for the COVID-19 forecasting using state of art numerical weather prediction model and disease process modelling.