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Abstract:

Air pollution is the leading environmental agent that poses a severe threat to human health and is one of the most severe problems in cities. Of the pollutants, particulate matter (PM), especially particles less than 2.5 microns in diameter, has the most profound health impacts. Urbanization and industrialization in cities have made the air quality up there worse and worse. Our study was based on the Aerosol Optical Depth (AOD) feature, a parameter obtained by remote sensing that relates to the presence of airborne particles potentially associated with PM. In this study, the PM_2.5 concentration data from the ground monitoring station and the MODIS AOD product of 3 km resolution were correlated to build a suitable regression function to simulate the spatial distribution of PM_2.5 concentrations. Next, the AOD was retrieved from the Landsat image based on the characteristics of the decrease in atmospheric clarity caused by the pollution particles. Landsat AOD has a 600m higher resolution than MODIS AOD. Research results on air quality (AQ) were simulated on Landsat AOD image through PM_2.5 concentration distribution and air quality index (AQI), in which AQI was determined based on USEPA standards. The analysis shows that the linear regression function between PM_2.5 concentration and MODIS AOD correlated best with the correlation coefficient R=0.9. Then PM_2.5 distribution was established on Landsat AOD image with higher spatial resolution. Case analysis for March of 2018 reflected that the average concentration of PM_2.5 across Ho Chi Minh City (HCMC) was higher than the allowable threshold specified in QCVN05:2013/BTNMT. PM_2.5 concentration in central districts tended to be higher than in suburban districts. The study also found that the city average AQI-PM_2.5 was around 97.38, peaking at 159, which was in the Unhealthy range, especially for sensitive groups. The result of the study provides potential solutions for AQ monitoring at the city level with a detailed spatial distribution.