Spatiotemporal analysis of fine particulate matter (PM2.5) in Saudi Arabia using remote sensing data

Fine particulate matter (PM2.5) can penetrate deeper into the respiratory systems and cause various health problems. In this paper satellite-derived PM2.5 concentrations, which provide better spatial coverage in the form of satellite-imageries are used to analyse the spatial and temporal distributions of PM2.5 in Saudi Arabia. PM2.5 concentrations (mu g/m(3)) are estimated using the relationship between Aerosol Optical Depth (AOD) and PM2.5 concentrations from satellite images, such as those of the Moderate Resolution Imaging Spectroradiometer (MODIS). PM2.5 concentrations varied both temporally and spatially and there was a negative south to north trend in PM2.5 levels. Dammam showed the highest whereas Tabuk showed the lowest PM2.5 concentrations. Temporally all cities demonstrated a positive trend, except At-Taif and Madinah. The positive trend was significant only in Dammam, Hofuf, Khobar, and Nijran. In most of the cities due to lack of data, ground level PM2.5 concentrations could not be compared with satellite-derived data, except in Makkah, where a comparison is made between observed and satellite-derived data for years 2001-2007. Both sets of data in Makkah showed positive trends, however satellite-derived concentrations were lower roughly by a factor of 2.5. Remote sensing successfully supplements the ground level air quality monitoring programme and helps better understand the spatial variability of atmospheric pollutants, especially on a large scale, such as regional or global scale. Further comparison between observed and satellite-derived data is required over a larger spatial and temporal resolution. (C) 2016 National Authority for Remote Sensing and Space Sciences. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).