Three-dimensional spatial modelling of traffic-induced urban air pollution using the Graz Lagrangian model and GIS

Abstract

Air pollution is a significant global problem that affects climate, human, and ecosystem health. Traffic emissions are a major source of atmospheric pollution in large cities. The aim of this research was to support air quality analysis by spatially modelling traffic-induced air pollution dispersion in urban areas at the street level. The dispersion model called the Graz Lagrangian model (GRAL model) was adapted to determine the NOx concentration level based on traffic, meteorology, buildings, and street configuration data in one of Tehran’s high traffic routes. In this case, meteorological parameters such as wind speed and direction were considered significant factors. Later, using local and general auto-correlation analyses, temporal and spatial variations in the concentration of NOx were measured at different altitudes. The results showed that the average output concentration of NOx pollutants at different altitudes ranges from 64.5 to 426.6 ppb. The resulting Moran index equals to 0.7–0.9 which indicates a high level of positive spatial auto-correlation. The analysis of the local Moran index represents the overcame pollution clusters with high levels of concentration at low to medium heights and the rise in clusters with low pollution at higher heights, while there is no clear clustering in the middle sections. In addition, the study of pollutant concentration variations over time has shown that pollution peaks occur at 07:00–08:00 and 21:00–22:00.