Enhancing Urban Sustainability through Air Pollution Analysis and Accessibility Estimation: A Case Study of Tehran Metropolis

The increase in motor vehicles has greatly increased air pollution in the Tehran metropolis and turned it into a challenge. By analyzing transportation pollutants, low-carbon cities and sustainable development strategies for urban districts can be achieved. This study deals with the spatio-temporal analysis of pollutants and transportation accessibility in the urban districts of Tehran. The concentrations of CO and NO۲ pollutants were extracted from the Sentinel-۵P satellite using coding in the GEE environment. OSM data were used to calculate the accessibility of the ۲۲ urban districts. Moran's global autocorrelation indicated a clustered spatial distribution pattern of pollutants. The high autocorrelation value equal to ۰.۹۴ for CO and NO۲ pollutants indicated their cumulative state in the atmosphere. By performing LISA, most clusters of these pollutants were identified in the central districts and southern suburbs. The average accessibility indicator of the ۲۲ districts was ۲۴.۸۲ km/km۲. About half of Tehran's urban districts had a high density of road transport networks. These districts are located in CO and NO۲ clusters owing to the high traffic volume of motor vehicles. The results of this study emphasize the factors that aggravate Tehran's air pollution, including the clustered pattern of pollutants in the atmosphere and dense transportation network in urban districts. By integrating air pollution analysis and accessibility estimations into urban planning frameworks, cities can strive to achieve long-term sustainability goals.

Keywords:

Sustainable Development , Sentinel-۵P , Pollutant Clustering , Accessibility