Document Type : Original Article
Authors
Department of Human Environment, College of Environment, Karaj, Iran
Abstract
Introduction:
Tehran metropolis, with an area of 750 km2, a population of more than 8 million people, and about 4 million vehicles is associated with the problem of air pollution. A thorough study of the spatial distribution of pollutants such as CO and NO2 in Tehran is significant for identifying the risks, probabilities, and risks of these contaminants. Therefore, mathematical and computational methods such as the confidence level method can be useful. The main goals of this research were to investigate the changes in air pollution levels in terms of CO and NO2 concentration, study the radius of impacts of fixed pollution stations, and calculate the level of reliability by investigating the probability of air pollution and the map of the risk of air pollution in different parts of the urban area of Tehran.
Material and methods:
In this study, Tehran's air pollution data in October, November, and December 2017 was used in spatial modeling. Using geostatistics and indicator kriging methods, data were analyzed and maps of the distribution of pollution concentration, and also two-dual maps (0 and 1) of the probability of pollution and risk of pollution in Tehran's for the study period were produced by ArcGIS Software.
Results and discussion:
The resulting maps showed the highest NO2 emissions areas (Ghaem Park, Razi Park, and the municipality of district 16) and areas with the least risk of NO2 pollution (Shahid Beheshti University, Pasdaran, Science, and Technology University, and Shad Abad). Moreover, the highest CO emission areas were the municipality of districts 11, 15, and 16, Ray station, Sharif University, Fatah Square, Health Park, and Razi Park). Aghdasyeh station, Shahid Beheshti University, municipality of district 2, Rose Park, Science and Technology University, Golbargh, Shad Abad, and Masoudieh had the lowest CO emissions.
Conclusion:
The indicator kriging was a useful method for assessing the risk of contamination by providing a possibility map. The hazardous maps produced in this study were useful tools for identifying areas with CO and NO2 contaminations. The results of this study can play an effective role in urban management decisions by correctly identifying the amount of air pollution in an appropriate spatial distribution.
Keywords