Spatio-temporal analysis of impact of environmental parameters on air pollution in districts of Tabriz Metropolis: A seasonal perspective

Year 2025, Volume: 7 Issue: 1, 24 - 42, 30.06.2025

Mir Ali Seyed Mosaffayi , Sajjad Moshiri , Bohadir Abdumuminov , Khalil Valizadeh Kamran , Bakhtiar Feizizadeh

https://doi.org/10.51489/tuzal.1649288

Abstract

Air pollution has become a significant challenge in Tabriz over the years, prompting this study to investigate the spatio-temporal relationships between environmental parameters - sum of vegetation cover area (SVCA) and mean land surface temperature (MLST) and air pollutants (CO, SO₂, NO₂) across the ten districts of Tabriz metropolitan area on a seasonal basis. The data used in this research were derived from satellite images on the Google Earth Engine (GEE) platform, with SVCA data obtained from Sentinel-2, MLST from Landsat-8, and air pollutants from Sentinel-5 images. The Modified Geographically Weighted Regression (MGWR) model was employed to analyze the relationships between environmental parameters and air pollutants, with environmental parameters as independent variables and air pollutants as dependent variables. Data analysis reveals a significant and strong relationship between the SVCA and air pollutants during spring and winter, with an R2 value exceeding 0.7, while this relationship is not significant in autumn. Additionally, the MLST has a clear and substantial impact on air pollution during summer and winter. From a spatial distribution perspective, western districts of Tabriz (6, 7, and 4) exhibit the strongest correlation between environmental parameters and air pollutants due to their proximity to heavy industries, whereas eastern districts (5, 9, and 2) show the weakest correlation. Overall, both SVCA and MLST simultaneously influence Tabriz's air pollution, with SVCA playing a significant role particularly in spring and winter, and MLST being a key factor during summer and winter.

Keywords

Environmental parameters , Air pollutants , Modified geographically weighted regression (MGWR) , Tabriz metropolitan areas

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