Paper Contents
Abstract
Particulate Matter (PM) pollution, specifically PM2.5 and PM10, has become a critical environmental issue worldwide due to its adverse effects on human health and ecosystems. This study conducts a trend analysis of PM2.5 and PM10 concentrations based on various parameters such as meteorological conditions, industrial activities, vehicular emissions, and geographical factors. Utilizing data collected from air quality monitoring stations over a specified period, statistical techniques including regression analysis and time series modeling are employed to discern patterns and trends. The research aims to investigate the relationships between PM2.5 and PM10 concentrations and the influencing factors, thus providing insights into pollution dynamics. By analyzing temporal and spatial variations, the study seeks to identify key contributors to PM pollution and understand the underlying mechanisms driving its fluctuations. Furthermore, the environmental impacts of elevated PM levels are thoroughly examined. These impacts encompass respiratory and cardiovascular diseases in humans, degradation of air quality, visibility reduction, deposition on surfaces leading to corrosion, and detrimental effects on vegetation and ecosystems. The study also explores the economic ramifications associated with PM pollution, including healthcare costs and productivity losses. In conclusion, this research contributes to a comprehensive understanding of PM pollution dynamics, facilitating the development of effective mitigation strategies and policy interventions. This study provides important insights for policymakers, urban planners, and environmental scientists by providing an understanding of the complex interactions between particle concentrations and a variety of parameters.
Copyright
Copyright © 2025 Rutuja Yashwant Shinde . This is an open access article distributed under the Creative Commons Attribution License.
