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CHARACTERISING THE POLLUTION CONCENTRATION IN HIGHLY URBANIZED AREA: AN APPLICATION OF REMOTE SENSING
The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences ; XLVIII-4/W5-2022:45-52, 2022.
Article in English | ProQuest Central | ID: covidwho-2080751
ABSTRACT
According to estimates from the World Health Organization (WHO), air pollution contributes to about seven million deaths worldwide annually. Currently, more than 90% of people breathe air that exceeds the WHO’s recommended threshold of pollutants. This high degree of air pollution results in serious public health problems, such as pneumonia, acute asthma, chronic respiratory conditions, and shortness of breath. The execution of solutions to lower pollution exposure is therefore required, a study into the causes of air pollution. The “National Clean Air Programme (NCAP)”, a five-year action plan, has been launched by the Ministry of Environment, Forest and Climate Change (MOEFCC, 2019), Government of India. The program’s primary objective is to combat significant air pollution problems over the Indian subcontinent. As a result of economic growth, air pollution concentrations have consistently climbed to dangerous levels. To investigate influence of anthropogenic parameters on urban air, statistical analysis has been carried out for 8 Indian cities for pre- and post-COVID period using Sentinel-5P earth observatory data. These factors include population density, land use and total registered vehicles. The results of the investigation demonstrated that during the lockdown, air pollution levels in cities decreased. It is also discovered that pollutant levels have escalated once more since the lockdown limitations were lifted. It is clear from the findings that parameters affect pollution exposure. This demonstrates categorically that the pandemic has a beneficial effect on pollution exposure. A policy framework can be advised for policymakers based on the study done.
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Full text: Available Collection: Databases of international organizations Database: ProQuest Central Language: English Journal: The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: ProQuest Central Language: English Journal: The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences Year: 2022 Document Type: Article