Notes

Pot: The Toxin-Producing Place with Potential Beneficial Utilizes.
In recent months, Covid-19 has caused significant global social and economic distress. Governments and health officials around the world have introduced mandatory preventive measures to combat Covid-19, i.e., hand sanitizers, gloves, and masks, which have contributed to large quantities of medical wastes. Social distancing and mandatory lockdown have also been put in place to protect people from Covid-19. This epidemic has caused severe demographic changes and unemployment, and economic activities have been shut down to save human lives. Transportation and travel industries are most severely hit as global tourism has fallen to almost zero in recent months; as a solution, economic institutes have introduced stimulus packages worth more than $6 trillion. However, restricted economic activities have also contributed towards a cleaner environment. However, environmental changes are not permanent, and the pollution level may rise again in the future. As a result, current research suggests that policymakers must introduce stringent environmental policies to promote clean energy.Amidst COVID-19 pandemic, extreme steps have been taken by countries globally. Lockdown enforcement has emerged as one of the mitigating measures to reduce the community spread of the virus. With a reduction in major anthropogenic activities, a visible improvement in air quality has been recorded in urban centres. Hazardous air quality in countries like India and China leads to high mortality rates from cardiovascular diseases. The present article deals with 6 megacities in India and 6 cities in Hubei province, China, where strict lockdown measures were imposed. The real-time concentration of PM2.5 and NO2 were recorded at different monitoring stations in the cities for 3 months, i.e. January, February, and March for China and February, March, and April for India. The concentration data is converted into AQI according to US EPA parameters and the monthly and weekly averages are calculated for all the cities. Cities in China and India after 1 week of lockdown recorded an average drop in AQIPM2.5 and AQINO2 of 11.32% and 48.61% and 20.21% and 59.26%, respectively. learn more The results indicate that the drop in AQINO2 was instantaneous as compared with the gradual drop in AQIPM2.5. The lockdown in China and India led to a final drop in AQIPM2.5 of 45.25% and 64.65% and in AQINO2 of 37.42% and 65.80%, respectively. This study will assist the policymakers in devising a pathway to curb down air pollutant concentration in various urban cities by utilising the benchmark levels of air pollution.The primary objective of the study is to analyse the relationship between COVID-19 and nitrogen dioxide in New York City during the global pandemic. Notably, the study has investigated the direct influence of lockdown circumstances (due to COVID-19) and plunge in the population of New York on its environmental contamination. The study utilized the Non-Linear Autoregressive Distributed Lag (NARDL) model to ascertain the asymmetric impact of COVID-19 on the environmental quality of the USA. The results reveal that lockdown has played a significant role in the environmental quality of the USA. Notably, an escalation in the registered cases of COVID-19 has a meaningful and indirect relationship with environmental pollution in the UAS. Besides, as the lockdown state goes normal, it results in an explosion in the environmental pollution in the USA. Also, deaths due to COVID-19 substantively improve the environmental quality in the short-term period as well as in the long-term period.Atmospheric particle pollution causes acute and chronic health effects. Predicting the concentrations of PM2.5 and PM10, therefore, is a prerequisite to avoid the consequences and mitigate the complications. This research utilized the machine learning (ML) models such as linear-support vector machine (L-SVM), medium Gaussian-support vector machine (M-SVM), Gaussian process regression (GPR), artificial neural network (ANN), random forest regression (RFR), and a time series model namely PROPHET. Atmospheric NOX, SO2, CO, and O3, along with meteorological variables from Dhaka, Chattogram, Rajshahi, and Sylhet for the period of 2013 to 2019, were utilized as exploratory variables. Results showed that the overall performance of GPR performed better particularly for Dhaka in predicting the concentration of both PM2.5 and PM10 while ANN performed best in case of Chattogram and Sylhet for predicting PM2.5. However, in terms of predicting PM10, M-SVM and RFR were selected respectively. Therefore, this study recommends utilizing "ensemble learning" models by combining several best models to advance application of ML in predicting pollutants' concentration in Bangladesh.Covid-19 pandemic has adversely affected all the aspects of life in adverse manner; however, a significant improvement has been observed in the air quality, due to restricted human activities amidst lockdown. Present study reports a comparison of air quality between the lockdown duration and before the lockdown duration in seven selected cities (Ajmer, Alwar, Bhiwadi, Jaipur, Jodhpur, Kota, and Udaipur) of Rajasthan (India). The period of analysis is 10 March 2020 to 20 March 2020 (before lockdown period) versus 25 March to 17 May 2020 (during lockdown period divided into three phases). In order to understand the variations in the level of pollutant accumulation amid the lockdown period, a trend analysis is performed for 24 h daily average data for five pollutants (PM2.5, PM10, NO2, SO2, and ozone). Fig. aGraphical abstract.This paper aims to examine the effects of the COVID-19 pandemic on PM2.5 emissions in eight selected US cities with populations of more than 1 million. To this end, the study employs an asymmetric Fourier causality test for the period of January 15, 2020 to May 4, 2020. The outcomes indicate that positive shocks in COVID-19 deaths cause negative shocks in PM2.5 emissions for New York, San Diego, and San Jose. Moreover, in terms of cases, positive shocks in COVID-19 cause negative shocks in PM2.5 emissions for Los Angeles, Chicago, Phoenix, Philadelphia, San Antonio, and San Jose. Overall, the findings of the study highlight that the pandemic reduces environmental pressure in the largest cities of the USA. This implies that one of the rare positive effects of the virus is to reduce air pollution. Therefore, for a better environment, US citizens should review the impact of current production and consumption activities on anthropogenic environmental problems.
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