The outbreak of COVID-19 has now created the largest pandemic and the World health organization (WHO) has declared social distancing as the key precaution to confront such type of infections. Most of the countries have taken protective measures by the nationwide lockdown. The purpose of this study is to understand the effect of lockdown on air pollutants and to analyze pre-monsoon (April and May) cloud-to-ground and inter-cloud lightning activity in relation to air pollutants i.e. suspended Particulate matter (PM 10 ), Nitrogen dioxides (NO 2 ) Sulfur dioxide (SO 2 ), Ozone (O 3 ) and Aerosol concentration (AC) in a polluted tropical urban megacities like Kolkata. After the strict lockdown the pollutants rate has reduced by more than 40% from the pre-lockdown period in the Kolkata megacity. So, decreases of PM 10 , NO 2 , SO 2 , O 3 and AC have a greater effect on cloud lightning flashes in the pre-monsoon period. In the previous year (2019), the pre-monsoon average result shows a strong positive relation between the lightning and air pollutants; PM 10 (R 2 = 0.63), NO 2 (R 2 = 0.63), SO 2 (R 2 = 0.76), O 3 (R 2 = 0.68) and AC (R 2 = 0.83). The association was relatively low during the lock-down period (pre-monsoon 2020) and the R 2 values were 0.62, 0.60, 0.71, 0.64 and 0.80 respectively. Another thing is that the pre-monsoon (2020) lightning strikes decreased by 49.16% compared to the average of previous years (2010 to 2019). The overall study shows that the reduction of surface pollution in the thunderstorm environment is strongly related to the reduction of lightning activity where PM 10 and AC are the key pollutants in the Kolkata megacity.

Due to the outbreak of Coronavirus, humans all over the world are facing several health problems. The present study has explored the spatio-temporal pattern of Coronavirus spread in India including spatial clustering, identification of hotspot, spatial heterogeneity, and homogeneity, spatial trend, and direction of COVID-19 cases using spatial statistical analysis during the period of 30th January to 20 June 2020. Besides, the polynomial regression model has been used for predictions of COVID-19 affected population and related deaths. The study found positive spatial heterogeneity in COVID-19 cases in India. The study has also identified seventeen epicentres across the country with high incidence rates. The directional distribution of ellipse polygon shows that the spread of COVID-19 now trending towards the east but the concentration of cases is mainly in the western part of the country. The country's trend of COVID-19 follows a fourth-order polynomial growth and is characterized by an increasing trend. The prediction results show that as on 14 th October India will reach 14,660,400 COVID-19 cases and the death toll will cross 152,945. Therefore, a 'spacespecific' policy strategy would be a more suitable strategy for reducing the spatial spread of the virus in India. Moreover, the study has broadly found out seven sectors, where Govt. of India lacks in terms of confronting the ongoing pandemic. The study has also recommended some appropriate policies which would be immensely useful for the administration to initiate strategic planning.

The COVID-19 pandemic forced India as a whole to lockdown from 24 March 2020 to 14 April 2020 (first phase), extended to 3 May 2020 (second phase) and further extended to 17 May 2020 (third phase) and 31 May 2020 (fourth phase) with only some limited relaxation in non-hot spot areas. This lockdown has strictly controlled human activities in the entire India. Although this long lockdown has had a serious impact on the social and economic fronts, it has many positive impacts on environment. During this lockdown phase, a drastic fall in emissions of major pollutants has been observed throughout all the parts of India. Therefore, in this research study we have tried to establish a relationship among the fall in emission of pollutants and their impact on reducing regional temperature. This analysis was tested through the application of Mann–Kendall and Sen’s slope statistical index with air quality index and temperature data for several stations across the country, during the lockdown period. After the analysis, it has been observed that daily emissions of pollutants (PM 10 , PM 2.5 , CO, NO 2 , SO 2 and NH 3 ) decreased by − 1– − 2%, allowing to reduce the average daily temperature by 0.3 °C compared with the year of 2019. Moreover, this lockdown period reduces overall emissions of pollutants by − 51– − 72% on an average and hence decreases the average monthly temperature by 2 °C. The same findings have been found in the four megacities in India, i.e., Delhi, Kolkata, Mumbai and Chennai; the rate of temperature fall in the aforementioned megacities is close to 3 °C, 2.5 °C, 2 °C and 2 °C, respectively. It is a clear indicator that a major change occurs in air quality, and as a result it reduced lower atmospheric temperature due to the effect of lockdown. It is also a clear indicator that a major change in air quality and favorable temperature can be expected if the strict implementations of several pollution management measures have been implemented by the concern authority in the coming years.

The long-term lockdown due to COVID-19 has beneficial impact on the natural environment. India has enforced a lockdown on 24th March 2020 and was subsequently extended in various phases. The lockdown due to the sudden spurt of the COVID-19 pandemic has shown a significant decline in concentration of air pollutants across India. The present article dealt with scenarios of air quality concentration of air pollutants, and effect on climatic variability during the COVID-19 lockdown period in Kolkata Metropolitan Area, India. The result showed that the air pollutants are significantly reduced and the air quality index (AQI) was improved during the lockdown months. Aerosol concentrations decreased by − 54.94% from the period of pre-lockdown. The major air pollutants like particulate matters (PM 2.5 , PM 10 ), sulphur dioxide (SO 2 ), carbon monoxide (CO) and Ozone (O 3 ) were observed the maximum reduction ( − 40 to  − 60%) in the COVID-19 lockdown period. The AQI has been improved by 54.94% in the lockdown period. On the other hand, Sen’s slope rank and the Mann–Kendal trend test showed the daily decreased of air pollutants rate is  − 0.051 to  − 1.586 μg /m3. The increasing trend of daily minimum, average, and maximum temperature from the month of March to May in this year (2020s) are 0.091, 0.118, and 0.106 °C which is lowest than the 2016s to 2019s trend. Therefore, this research has an enormous opportunity to explain the effects of the lockdown on air quality and climate variability, and it can also be helpful for policymakers and decision-makers to enact appropriate measures to control air pollution.

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