ABSTRACT
The variation in ambient air pollution hampers indoor air quality (IAQ), and even the short-term variation is very hazardous for the exposed population. Technological interventions including sensors, smartphones and other gadgets are implemented to build smart environments. However, these interventions are still not fully explored in developing countries like India. The COVID-19 pandemic has made it very important to keep a tab on the air we breathe in as those already suffering from respiratory troubles are prone to fall victim to the deadly disease. In such a scenario, even a rise in pollution for a short duration is dangerous to the exposed pollution. Such short-term exposure facilitated by the meteorological creates a disaster for environmental health. The short-term rise in the concentration of pollutants makes things worse for the exposed people, even indoors. It is therefore critical to come up with a concrete solution to predict the IAQ instantly and warn the exposed population which can be only achieved by technological interventions and futuristic Internet of Things-based computational predictions. This chapter is intended to elaborate the health hazards linked to short-term rise in pollutants, which often goes unnoticed but has a critical impact and how with the help of IoT-based applications, the short-term variation can be predicted through different strategies. Similarly, the assessment of the health impact associated with short-term exposure to air pollution is also significant, and different exposure assessment models and computational strategies are discussed in the course of the study. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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. © 2022 Technoscience Publications. All rights reserved.