Sulfur dioxide is an atmospheric pollutant emitted primarily through the combustion of fossil fuels in power plants and industrial facilities. This pollutant is present across the industrial Tehran–Karaj–Qazvin corridor. This study aimed to analyze the spatiotemporal pattern of SO₂ and identify areas, with emphasis on power plants and industrial centers, during 2018–2022. Total vertical column SO₂ was retrieved from TROPOMI observations aboard Sentinel-5P. Data processing was conducted in Google Earth Engine, while spatial analyses were performed in ArcGIS. Annual, seasonal, and monthly variations, as well as the five-year mean, were examined, and Hot Spot Analysis was applied. The results showed that the highest SO₂ concentrations were concentrated in industrial areas of Qazvin Province, southern Tehran, and eastern Alborz. Hot Spot Analysis revealed spatial clustering along the Tehran–Qazvin industrial corridor, where industrial zones, thermal power plants, and heavy freight traffic contribute to emissions. Areas surrounding power plants such as Shahid Rajaei were identified as SO₂ hotspots. In contrast, elevated and northern areas exhibited lower concentrations due to better atmospheric ventilation and limited emission sources. Annual SO₂ concentrations showed an increasing trend, reaching a maximum in 2021. Global Moran’s I confirmed strong and significant spatial autocorrelation, indicating clustered pollution patterns and the influence of emission sources. The highest concentrations occurred during the cold season, particularly in January and February, whereas July and August showed lower values. The findings suggest that industrial decentralization, fuel-use reform, and emission control can contribute to SO₂ management.
Introduction
Air pollution is one of the most pressing environmental challenges in urban and industrial areas and has become a global concern alongside rapid urbanization and the expansion of industrial activities. Among atmospheric pollutants, sulfur dioxide (SO₂) is of particular importance due to its widespread occurrence and substantial environmental and health impacts. It is primarily emitted through the combustion of fossil fuels in power plants, industrial facilities, and oil refineries. Exposure to elevated concentrations of SO₂ can adversely affect human health, particularly by contributing to respiratory disorders, cardiovascular complications, and overall deterioration of air quality. Consequently, understanding the spatiotemporal distribution of SO₂ has become an important priority for environmental researchers and policymakers worldwide. Iran, like many developing countries, faces persistent challenges associated with SO₂ pollution, particularly in densely populated and industrialized regions. The southern slopes of the Central Alborz, encompassing the metropolitan areas of Tehran, Karaj, and Qazvin, constitute one of the country’s major population and industrial centers and are therefore highly susceptible to air pollution. However, comprehensive assessment of SO₂ pollution in this region is constrained by the limited spatial coverage and temporal continuity of ground-based air quality monitoring stations, particularly in Karaj and Qazvin. Station-based observations are often characterized by spatial gaps and temporal discontinuities, limiting their ability to provide a consistent basis for long-term and spatially comprehensive assessments. In this context, satellite remote sensing provides an effective complementary approach for monitoring atmospheric pollutants over extensive areas and overcoming some of the limitations associated with conventional ground-based observations. In particular, Sentinel-5 satellite observations offer valuable capabilities for investigating the spatial and temporal variability of atmospheric SO₂ at regional scales. Accordingly, the present study employs Sentinel-5 observations to investigate the spatiotemporal distribution of SO₂ across the metropolitan areas of Tehran, Karaj, and Qazvin. The analysis focuses on the five-year mean concentration during 2018–2022, together with annual, seasonal, and monthly variations, to characterize the temporal behavior of the pollutant and identify areas with elevated SO₂ concentrations. Particular attention is given to the spatial correspondence between SO₂ hotspots and major emission sources, including power plants and industrial centers.
Material and Methods
Sentinel-5P/TROPOMI satellite observations were used to investigate the spatiotemporal variability of sulfur dioxide (SO₂) over the metropolitan areas of Tehran, Karaj, and Qazvin during 2018–2022. The analysis employed the Copernicus Sentinel-5P OFFL Level-3 SO₂ product (COPERNICUS/S5P/OFFL/L3_SO2), which provides total vertical column SO₂ measurements derived from TROPOMI observations. Unlike conventional ground-based monitoring, which is constrained by the limited spatial coverage and temporal continuity of monitoring stations, satellite observations provide spatially continuous measurements over broad areas, making them particularly suitable for assessing regional-scale patterns and temporal variability of atmospheric SO₂. The TROPOMI instrument, aboard Sentinel-5P since its launch in October 2017, provides high-resolution observations of atmospheric trace gases and enables consistent monitoring of SO₂ over the study area. The satellite data were processed using JavaScript within the Google Earth Engine (GEE) platform. Monthly, seasonal, annual, and five-year mean SO₂ fields were derived from the TROPOMI observations for 2018–2022, and annual means were subsequently used to assess temporal changes in SO₂ concentrations. The processed raster outputs were exported from GEE and analyzed in ArcMap to generate spatial distribution and classification maps. To identify statistically significant spatial concentrations of elevated and low SO₂ values, the Getis-Ord Gi* Hot Spot Analysis was applied after converting the raster observations into point features. In addition, Global Moran’s I was calculated to evaluate the overall degree of spatial autocorrelation and determine whether the observed SO₂ distribution exhibited clustered, random, or dispersed spatial patterns. The satellite product reports SO₂ as total vertical column density (mol m⁻²); therefore, the retrieved values were interpreted as column amounts rather than near-surface concentrations and were not directly compared with ambient air-quality standards expressed in units such as µg m⁻³ or ppb.
Results and Discussion
The spatial distribution of SO₂ during 2018–2022 revealed pronounced heterogeneity across the Tehran–Karaj–Qazvin metropolitan corridor, with the highest concentrations concentrated in industrial areas of Qazvin, southern Tehran, and eastern Alborz. These areas largely coincide with major industrial zones, thermal power plants, cement industries, and high-traffic corridors, indicating the dominant contribution of combustion-related and stationary sources to regional SO₂ loading. In contrast, the Alborz highlands, northern Tehran, and southern Qazvin generally exhibited lower SO₂ values, which can be associated with lower population and industrial densities and more favorable atmospheric ventilation. The Getis-Ord Gi* analysis further confirmed this spatial differentiation, identifying statistically significant hot spots at the 99% confidence level in northeastern Qazvin and central Tehran. Several of these hot spots spatially corresponded with major emission sources, including the Shahid Rajaei, Montazeri Qaim, Ba’ath, Parand, Rey, and Pakdasht power plants. Conversely, significant cold spots were predominantly detected over the Alborz mountain range, northern Tehran, and southern Qazvin, reinforcing the role of topography, emission-source density, and atmospheric ventilation in shaping the spatial distribution of SO₂. The Global Moran’s I results likewise indicated a non-random spatial structure, demonstrating that SO₂ concentrations tend to form spatially clustered patterns rather than being randomly distributed across the study area.Temporal analysis revealed substantial variability in SO₂ concentrations throughout the study period. Annual concentrations increased from 2019 and reached their highest levels in 2020, followed by a relative decline in 2021. This temporal variability likely reflects the combined influence of emission intensity, fossil-fuel consumption, atmospheric conditions, and changes in energy use and emission-control practices. In particular, periods characterized by atmospheric stability and temperature inversions can suppress vertical dispersion and promote the accumulation of SO₂ within the lower troposphere. The seasonal analysis showed that winter consistently recorded the highest SO₂ concentrations, whereas spring and summer generally exhibited lower values. The winter maximum can be attributed to increased fuel consumption for heating, greater reliance on fossil fuels, and the frequent occurrence of stable atmospheric conditions and temperature inversions. The use of higher-sulfur fuels, including fuel oil (mazut) during periods of natural-gas shortages, may further intensify SO₂ emissions from thermal power plants. Despite the generally lower concentrations during summer, elevated values persisted around major industrial sources, particularly the Shahid Rajaei power plant, highlighting the sustained influence of stationary emission sources independent of seasonal meteorological variability. The monthly analysis revealed a clear seasonal cycle, with SO₂ concentrations beginning to increase from September and reaching their maximum in January, followed by a gradual decline toward spring and summer. Concentrations remained comparatively low from approximately April to August, coinciding with stronger atmospheric mixing, more effective ventilation, and reduced heating-related fuel demand. The spatial distribution of hot spots remained relatively stable across seasons, with a persistent concentration of significant hot spots along the industrial corridor between Tehran and Qazvin. However, the number and extent of 99% confidence-level hot spots were comparatively lower during winter, which may reflect the broader regional accumulation of SO₂ under stagnant atmospheric conditions and consequently a reduction in the spatial contrast between highly polluted and less polluted areas. Overall, the consistent spatial correspondence between SO₂ hot spots and major industrial and power-generation facilities, together with the observed seasonal cycle, indicates that both emission sources and atmospheric dispersion conditions play complementary roles in controlling the regional distribution of SO₂. These findings demonstrate the value of Sentinel-5P/TROPOMI observations combined with spatial statistical techniques for identifying persistent pollution hotspots and characterizing regional-scale patterns that may not be adequately captured by the limited spatial coverage of ground-based monitoring networks.
Conclusion
The findings demonstrate that SO₂ distribution across the Tehran–Karaj–Qazvin metropolitan corridor is strongly associated with industrial activities, thermal power plants, and other combustion-related emission sources. Significant hot spots were consistently concentrated around major industrial and power-generation centers, particularly in southern Tehran and Qazvin, whereas mountainous and less industrialized areas generally exhibited lower concentrations. The pronounced seasonal cycle, characterized by maximum SO₂ levels in winter and January and lower concentrations during spring and summer, reflects the combined effects of increased fuel consumption, temperature inversions, and reduced atmospheric ventilation during the cold season. Overall, the integration of Sentinel-5P/TROPOMI observations with Getis-Ord Gi* and spatial autocorrelation analysis provides an effective framework for identifying persistent SO₂ hotspots and improving understanding of its regional spatiotemporal variability. The results can support more targeted air-quality monitoring and emission-control strategies, particularly around major industrial and power-generation sources and during periods of unfavorable atmospheric conditions.
Author Contributions
All authors contributed equally to the conceptualization of the article and writing of the original and subsequent drafts.
Data Availability Statement
The satellite-based sulfur dioxide (SO₂) data used in this study were obtained from the Sentinel-5 Precursor (Sentinel-5P) mission, specifically the TROPOMI instrument, via the Google Earth Engine platform (https://earthengine.google.com/). These data are publicly available and can be accessed through the Earth Engine Data Catalog under the product ID COPERNICUS/S5P/NRTI/L3_SO2. All data processing and analysis were performed using the Earth Engine Code Editor environment, and the procedures are reproducible based on the descriptions provided in the Methods section.
Acknowledgements
We are grateful to all the scientific consultants of this paper.
Ethical considerations
The authors avoided data fabrication, falsification, plagiarism, and misconduct.