Integrated weighted geospatial analysis and spatiotemporal assessment of key criteria air pollutants for hotspot identification and air quality risk assessment.

Abstract

Air pollution remains a pressing concern in urban India, affecting human wellbeing and ecosystem sustainability. This investigation explores the spatial and temporal variations in 10 μm particulate matter (PM10), nitric oxides (NOX), and sulfur dioxide (SO2) air pollution in Navi Mumbai, India, from 2014-2023. Data from 23 monitoring points were analyzed using geographic information systems-based methods, including inverse distance weighting and weighted overlay analysis, to generate a comprehensive pollution index. Findings indicate high seasonal variation, with elevated PM10 and NOX levels during premonsoon and winter due to traffic, industrial activity, and unfavorable meteorological conditions. Monsoon rains significantly reduced pollutant levels. Industrial hotspots, particularly in Taloja and Kalamboli, and traffic-heavy corridors, such as Vashi and Nerul, remained persistent pollution sources. A noticeable drop in pollutant concentrations in 2020 coincided with the COVID-19 lockdown, although levels surged in subsequent years. The weighted overlay analysis proved effective in identifying pollution hotspots and offering a comprehensive understanding of air quality risks. Global comparisons highlight the specific challenges of coastal satellite cities, where industrial and harbor emissions contribute to seasonal smog. This study emphasizes the need for targeted emission controls and urban planning interventions to improve air quality and sustainability in rapidly growing regions.