Assessment and Prediction of Urban Pollutants and its Influence on Human Health using Deep Learning Algorithm

Mumbai, the financial center of India, is a thriving city where the urban environment is constantly changing. Degradation of the environment is a result of these changes. Recent research reveals a recurring problem, wherein pollutant levels regularly exceed advised thresholds, thus having an adverse effect on human health. The research makes use of meteorological data from four weather stations (Powai, Sion, Colaba and Borivali) that span the years 2000–2023. The chosen contaminants for study are PM2.5, PM10, and air temperature. All of the contaminants are growing exponentially, according to the study. For future prediction, deep learning techniques are used. In comparison to the other algorithms, the results show that Bi-LSTM is more accurate. Based on this model, it appears that regular places will soon become hotspots and maybe dangerous. With the use of this model, Mumbai metropolitan planners and authorities may make timely and well-informed decisions that would promote the city's sustainable growth and citizens well-being.