Mobile Sensing and Modeling Air Pollution Hotspots in Urban Neighborhoods

Abstract

Most Indian cities have seen rapid urbanization due to huge migration of population leading to a substantial rise in construction activities, vehicular emissions, and uncontrolled growth. Some such cities also house many pollutions causing industries that result in deterioration of air quality. These cities have pollution hotspots where pollution levels are much higher than permitted limits. Air pollution is highly location-centric and varies greatly on moving away from the hotspots. Because these Air Quality Index(AQI) data are typically unavailable, the long-term impact of these hotspots on adjacent neighborhoods is unknown. If the fluctuation in pollution in adjacent neighborhoods as we move away from hotspots can be modeled and projected, this information will be extremely beneficial for the government, and city administrations in better planning development activities as well as issuing suitable recommendations to sensitive establishments such as educational institutes, hospitals, and old age homes, among others. In this work, we have collected the real-time AQI data at the hotspot and its neighborhoods on a specific route over a period and tried to develop a mathematical model which forecasts the variation of AQI with distance.