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Spatiotemporal Estimation of Black Carbon Concentration in Tehran Using Aerosol Optical Depth Remote Sensing Data and Meteorological Parameters: Health Risk Assessment and Relationship With Green Spaces Publisher



Norzaee S1, 2 ; Kermani M1, 2 ; Ghorbanian A3 ; Jonidi Jafari A1, 2 ; Yunesian M4, 5 ; Shahsavani A6, 7 ; Farzadkia M1, 2 ; Rezaei Kalantary R1, 2
Authors
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Authors Affiliations
  1. 1. Research Center for Environmental Health Technology, Iran University of Medical Sciences, Tehran, Iran
  2. 2. Department of Environmental Health Engineering, School of Public Health, Iran University of Medical Sciences, Tehran, Iran
  3. 3. Department of Photogrammetry and Remote Sensing, Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, Tehran, 19967-15433, Iran
  4. 4. Department of Environmental Health, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
  5. 5. Center for Research Methodology and Data Analysis (CRMDA), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran
  6. 6. Department of Environmental Health Engineering, School of Public Health, Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
  7. 7. Air Quality and Climate Change Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran

Source: Sustainable Cities and Society Published:2024


Abstract

Black Carbon (BC) is an atmospheric pollutant with considerable adverse effects on human health, increasing the chance of cardiovascular disorders, respiratory issues, and cancers in exposed individuals. Accordingly, studying BC in urban areas is essential for understanding its associated health risks. In this study, the Multi-Angle Implementation of Atmospheric Correction (MAIAC) retrieved Aerosol Optical Depth (AOD) remote sensing data from the Moderate Resolution Imaging Spectroradiometer (MODIS), along with in situ observations of BC concentration and meteorological parameters were utilized to estimate BC concentration in Tehran. In this regard, an ensemble machine learning algorithm, Gradient Boosting Machine (GBM), was employed to estimate BC concentration from 2010 to 2021, enabling a spatiotemporal analysis of BC levels in Tehran. Subsequently, the carcinogenic and non-carcinogenic effects of BC on children and adults were examined, as well as its relationship to urban green spaces. The Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Adjusted R-squared (R2adj), values for BC estimation ranged from 0.80 to 1.59 μg/m3, 0.59 to 1.10 μg/m3, and 0.70 to 0.94, respectively, indicating the promising performance of the GBM algorithm. The estimated annual average BC concentration over 11 years was 6.18± 2.46 μg/m3. Spatial variations in BC concentration and hotspot analysis at 99% and 95% confidence levels, showed that hotspots were primarily concentrated in the central and southern parts of Tehran. In contrast, cold spots were more scattered across the western and northeastern parts of the city. The cancer risk (CR) from BC exposure exceeded the recommended risk levels (1 × 10⁻⁶ to 1 × 10⁻⁴) established by the US Environmental Protection Agency (US EPA), demonstrating severe health risks for people in Tehran exposed to the current levels of BC concentrations. The average Hazard Quotient (HQ) value across all areas of Tehran was below the threshold value of 1, indicating that the non-carcinogenic health risk remains within acceptable limits. Results regarding green spaces indicated that greenery significantly influences BC concentration, revealing a negative correlation between green space coverage and BC concentration. © 2024 Elsevier Ltd
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