Air quality estimation using remote sensing and GIS-spatial technologies along Al-Shamal train pathway, Al-Qurayyat City in Saudi Arabia

Abstract

Air pollution is the atmospheric state in which specific elements concentrations has adverse impacts on human health as well as the environment including global warming, transportation, acidic rain, and ozone layer depletion. Currently, population around the world lives in urban areas coupled with population size in addition to the increasing levels of vehicles which led to deterioration in air quality. Additionally, the clean air is a critical and vital element for environment and health of any region. Therefore, the foci of this research are to detect the air pollution parameters and investigate the relationship with the meteorological parameters including temperature, and wind speed along Al-Shamal train pathway in Al-Qurayyat City in Saudi Arabia using satellite data. This study involved various field visits to distribute questionnaires to residents to gain information about their health status and get their opinions about air quality. The questionnaires analysis manifested poor air quality conditions and thermal pollution due to the rapid urbanization accompanied with the development of the industrial facilities. The main aim of the study was to shed light on using satellite data to detect the concentration of the primary air pollutants including NO2, SO2, and CO to constitute a pre-defensive step to control and improve the air quality in Saudi Arabia. The present study examined using Sentinel-5 Precursor, Moderate Resolution Imaging Spectroradiometer (MODIS), and The Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) satellite data to investigate and detect the air pollution parameters in the study area rather than using the traditional measurements from ground stations. The analysis of satellite images revealed an increase in the concentration of air pollution parameters compared to the standard limits of the WHO which can cause crucial negative impacts on the environment as well as human health. Pearson correlation coefficient was used to analyze the relation between various air pollutants with temperature and wind speed with values ranging between 0.0004 and 0.6604. The statistical analysis of air pollutants showed strong linear correlation that may by attributed to the same emission origin. CO and NO2 on roads have a strong correlation and are emitted by vehicles(R (Albugami et al., 2018) = 0.66). NO2 and CO do not seem to have strong correlation with either SO2 or AOD and their correlation coefficients are weaker, that indicating different emissions sources. The AOD in the study area originated mainly from the windblown dust, construction work, and suspension of particles and therefore do not emitted from traffic.

Keywords

• Sentinel-5 precursor
• Primary air pollutants
• Meteorological parameters
• Urbanization
• Al-Shamal train pathway