Assessing the impact of land cover on air quality parameters in Jordan: A spatiotemporal study using remote sensing and cloud computing (2019–2022)

Abstract

This study aimed to analyze the spatiotemporal concentration of air pollutants in the tropospheric layer of Jordan, in the Middle East, for 2019–2022. The study utilized remotely sensed data from two satellite systems, Sentinel-5P and Landsat-9, to retrieve information about the concentration of nitrogen dioxide (NO₂), sulfur dioxide (SO₂), and carbon monoxide (CO) and land use types, respectively. The Google Earth Engine (GEE) platform and JavaScript were used to produce monthly short-term average concentration maps and time series for the three pollutants. Pearson correlation analysis was performed to evaluate the performance of Sentinel-5P data against ground-based monitoring stations in estimating NO₂, SO₂, and CO concentration at a regional scale. Results revealed a moderate correlation, with r-values of 0.42, 0.43, and 0.40, for NO₂, SO₂, and CO, respectively. The spatiotemporal analysis showed a higher concentration of SO₂ and NO₂ in the northern and middle regions of the country, coinciding with the spatial distribution of built-up areas and the main urban centers. On a temporal scale, the highest concentration of the three pollutants was observed in the winter months for all governorates of Jordan. For instance, it was found that the highest value of NO₂ was in Balqa Governorate in December 2022, 1.57 * 10^4 mol/m². The highest average monthly SO₂ values were observed in Jerash Governorate in December 2019, 7.36 * 10^4 mol/m². CO concentrations were mainly concentrated in the western parts of the Jordan rift valley.