Evaluating the impact of unmanned aerial vehicles (UAVs) on air quality management in smart cities: A comprehensive analysis of transportation-related pollution

Abstract

Urban environments face significant air pollution challenges affecting health and sustainability. Using unmanned aerial vehicles for air quality monitoring offers a promising solution. This research aims to improve these vehicles' ability to identify pollution sources and develop strategies, with a focus on transportation-related pollution. Detailed air pollution tests revealed that pollutant concentrations surged during morning rush hours, especially in high-traffic coastal areas, while areas away from traffic had much lower levels. Evening tests showed that pollutants from daytime traffic had dispersed throughout the urban area. The consistent northward shift in pollutant concentrations underscored the link between traffic patterns and pollutant distribution. Quantitative analyses and the resulting air pollutant maps showed average increases in pollutant concentrations between morning and evening hours in high-traffic areas: 12.1% for NO2, 5.3% for CO, 9.8% for PM10, and 11.4% for PM2.5. In contrast, the increases in pollutant concentrations in less trafficked urban regions were 45.9%, 48.2%, 32.7%, and 29.5%, respectively. This demonstrates how air pollution originating from areas with heavy traffic impacts other regions through environmental and geographical factors. The findings underscore the need for comprehensive air quality management strategies at the city level, targeting emissions in high-traffic areas and adapting to temporal fluctuations in pollutant levels.