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Sci Rep ; 11(1): 4285, 2021 02 19.
Artículo en Inglés | MEDLINE | ID: covidwho-1091457

RESUMEN

On January 30, 2020, India recorded its first COVID-19 positive case in Kerala, which was followed by a nationwide lockdown extended in four different phases from 25th March to 31st May, 2020, and an unlock period thereafter. The lockdown has led to colossal economic loss to India; however, it has come as a respite to the environment. Utilizing the air quality index (AQI) data recorded during this adverse time, the present study is undertaken to assess the impact of lockdown on the air quality of Ankleshwar and Vapi, Gujarat, India. The AQI data obtained from the Central Pollution Control Board was assessed for four lockdown phases. We compared air quality data for the unlock phase with a coinciding period in 2019 to determine the changes in pollutant concentrations during the lockdown, analyzing daily AQI data for six pollutants (PM10, PM2.5, CO, NO2, O3, and SO2). A meta-analysis of continuous data was performed to determine the mean and standard deviation of each lockdown phase, and their differences were computed in percentage in comparison to 2019; along with the linear correlation analysis and linear regression analysis to determine the relationship among the air pollutants and their trend for the lockdown days. The results revealed different patterns of gradual to a rapid reduction in most of the pollutant concentrations (PM10, PM2.5, CO, SO2), and an increment in ozone concentration was observed due to a drastic reduction in NO2 by 80.18%. Later, increases in other pollutants were also observed as the restrictions were eased during phase-4 and unlock 1. The comparison between the two cities found that factors like distance from the Arabian coast and different industrial setups played a vital role in different emission trends.


Asunto(s)
Contaminación del Aire/estadística & datos numéricos , COVID-19/prevención & control , Control de Enfermedades Transmisibles/normas , Monitoreo del Ambiente/estadística & datos numéricos , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , COVID-19/epidemiología , COVID-19/transmisión , COVID-19/virología , Ciudades/estadística & datos numéricos , Humanos , India , Industrias/normas , Material Particulado/análisis
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