Preprint Conference Paper Version 1 Preserved in Portico This version is not peer-reviewed

Examining the Spatio-temporal Dynamics of PM2.5 in Saudi Arabia Using Satellite-derived Data: A Cluster Study

Version 1 : Received: 1 December 2016 / Approved: 1 December 2016 / Online: 1 December 2016 (15:25:56 CET)

How to cite: Aina, Y.; Adam, E.; Ahmed, F. Examining the Spatio-temporal Dynamics of PM2.5 in Saudi Arabia Using Satellite-derived Data: A Cluster Study. Preprints 2016, 2016120011. https://doi.org/10.20944/preprints201612.0011.v1 Aina, Y.; Adam, E.; Ahmed, F. Examining the Spatio-temporal Dynamics of PM2.5 in Saudi Arabia Using Satellite-derived Data: A Cluster Study. Preprints 2016, 2016120011. https://doi.org/10.20944/preprints201612.0011.v1

Abstract

The study of the concentrations and effects of fine particulate matter in urban areas have been of great interest to researchers in recent times. This is due to the acknowledgment of the far-reaching impacts of fine particulate matter on public health. Remote sensing data have been used to monitor the trend of concentrations of particulate matter by deriving aerosol optical depth (AOD) from satellite images. The Center for International Earth Science Information Network (CIESIN) has released the second version of its global PM2.5 data with improvement in spatial resolution. This paper revisits the study of spatial and temporal variations in particulate matter in Saudi Arabia by exploring the cluster analysis of the new data. Cluster analysis of the PM2.5 values of Saudi cities is performed by using Anselin local Moran’s I statistic. Also, the analysis is carried out at the regional level by using self-organizing map (SOM). The results show an increasing trend in the concentrations of particulate matter in Saudi Arabia, especially in some selected urban areas. The eastern and south-western parts of the Kingdom have significantly clustering high values. Some of the PM2.5 values have passed the threshold indicated by the World Health Organization (WHO) standard and targets posing health risks to Saudi urban population.

Keywords

satellite data; fine particulate matter; air pollution; geographic information system; health risks; spatial analysis; Saudi Arabia

Subject

Environmental and Earth Sciences, Environmental Science

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