Department Of Environmental Science And Technology

The coronavirus disease?2019 (COVID-19) has emerged as a deadliest disease in the 21st century. Initially in India, this disease was concentrated in major urban cities like Mumbai, Delhi, Gujarat, and Chennai, which were the national hotspots for the COVID-19 pandemic. However, in subsequent months, returning migrants (mainly day labour) brought the disease back to their home; this vector triggered significant spread to semi-urban and rural areas. This highlighted serious concerns in rural India, where access to sophisticated healthcare and mitigation strategies were lacking. There is little data on this new pattern of disease spread. This article provides a short review for tracking the spread of COVID-19 into major rural states in India based on understanding urban-rural workforce migration relative to the growing proportion of the nation's COVID-19 caseload between May-September 2020. � 2021 John Wiley & Sons Ltd.

The present�study aims to�examine the changes in air quality during different phases of the COVID-19 pandemic, including the lockdown (LD1�4) and unlock period (UL1�2) (post-lockdown) as compared to�pre-lockdown (PL1�3) and to�establish the relationships of the environmental and demographic variables with COVID-19 cases in the state of Maharashtra, the worst-hit state in India. Atmospheric pollutants such as PM2.5, PM10, NOx, and CO were substantially reduced during the lockdown and unlock�phases with the greatest reduction in cities having larger traffic volumes. Compared with the immediate pre-lockdown period (PL3), the averaged PM2.5 and PM10 reduced by up to 51% and 47% respectively during the lockdown periods, which resulted in �satisfactory� level of air quality index (AQI) as a result of reduced�vehicular traffic and industrial closing. These parameters continued to reduce as much as 80% during the unlock periods due to the additive impact of weather (rainfall and temperature) combined with the lockdown conditions. Kendall�s correlation matrix showed a significant negative correlation between temperature and air pollutants (r= ? 0.35 to ? 057). Conversely, SO2 and O3 did not improve, and in some cases, they increased during the lockdown and unlocking. COVID-19 spreading incidences were strongly and positively correlated with temperature (r < 0.62) and dew point (r < 0.73). Thus, this indicates that the increase in temperature and dew point cannot weaken the transmission of this virus. The number of COVID-19 cases relative to air pollutants was negatively correlated (r = ? 0.33 to ? 0.74), which may be�a mere coincidence as a result of lockdown. However, based on pre-lockdown�air quality data and demographic factors, it�was found that�particulate matter (PM2.5 and PM10) and population density are closely linked with higher morbidity and mortality although a more in-depth research is required in this direction to validate this finding. The onset of COVID-19 has allowed us to determine that �immediate� changes in air quality within densely populated/industrialized areas can improve livelihood based on pollution mitigation. These findings could be used by policymakers to set new benchmarks for air�pollution that would improve the quality of life for major sectors of the World�s population. COVID-19 has shown us that we can make changes when necessary, and findings may pave the way for future research to inform policy on the tough choices we will have to make between quality of life and survival.�Also, our results will enrich the ongoing discussion on the role of environmental factors on the transmission of COVID-19 and will help to take necessary steps for its control. � 2020, ISB.

Department Of Environmental Science And Technology

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