Abstract
Air pollution produces major environmental health problems with a vast number of entropies that can affect healthy, sustainable environments across the globe. Millions of people are dying prematurely each year as a direct cause of poor air quality. According to recent studies, living within 50 meters of any significant road can increase the risk of lung cancer by up to 10%. World Health Organization declares that approximately 3.7 million people died worldwide in 2012 due to outdoor air pollution. In this analysis, we analyzed air pollutants that were released into the air from a wide range of sources, such as motor vehicles, industrial combustion processes, etc. We analyzed the Sentinel-5 precursor data, which provides time series data on a multitude of trace gaseous compounds such as CO, NO2, SO2, O3, PM10, PM2.5 aerosols, etc. with efficient statistics and special resolution. For better comparison, we have trained our statistical atmospheric data with deep learning methodology and analyzed them to obtain a reference for air quality in India. This study describes the scientific aspects and probable atmospheric composition entropy due to pollution. We also presented the overall operational product outcomes and emissions from the energy sectors, which involves the advancement of data analysis in a particular coordinate system.
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