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

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.


Introduction
Fine particulate matter is one of the important air quality parameters. Recently, fine particulate matter is receiving a lot of attention due to the health, environmental and social implications of increasing particulate matter concentrations. The International Agency for Research on Cancer (IARC) has 2 confirmed the carcinogenicity of PM 2.5 (Loomis et al., 2013). A positive relationship between exposure to PM2.5 and incidences of lung cancer has been found in areas with annual average levels of PM2.5 ranging from 10 to 30 μg/m 3 (Loomis et al., 2013;Hoek & Raaschou-Nielsen, 2014). Even in areas where the concentrations of PM2.5 are less than 10 μg/m 3 , there are risks of lung cancer (Loomis et al., 2013). The study by Franck et al. (2014), in Santiago de Chile, indicated that there was a significant impact of exposure to PM2.5 on cardiovascular hospital admissions. Nasser et al. (2015) concluded that particulate matter constitutes a risk factor for cardiovascular diseases in the Middle East countries that include Iran, Saudi Arabia, the United Arab Emirates and Qatar. These findings underscore the need to monitor particulate matter concentrations in order to establish means of controlling the concentrations.
Several authors have reported the monitoring of particulate matter at the global and local levels. Brauer (2016) highlighted about 20% increase in the global exposure to particulate matter and about 2.9 million deaths in 2013 attributed to exposure to fine particulate matter. Farahat (2016) examined the variations, causes and effects of the concentrations of pollutants (especially aerosols) over the Arabian Peninsula. In Saudi Arabia, studies (Al-Jeelani, 2009;Aburas et al., 2011;Munir et al., 2013;Rushdi et al., 2013;Shaltout et al., 2013;Habeebullah, 2013) have depicted particulate matter concentrations and compositions in the major cities of the Kingdom such as Riyadh, Jeddah and Makkah. El-Mubarak et al. (2014) identified polycyclic aromatic hydrocarbons (PAHs) in the particulate matter over the city of Riyadh. They found high PAHs and particulate matter concentrations that could be attributed to traffic emissions (El-Mubarak et al., 2014). Also, organic tracers, that could pose toxicity risks, were found in the particulate matter over Dhahran city, Saudi Arabia (Rushdi et al., 2014).

Study area
The location of the study is Saudi Arabia. The country covers an area of about 2 million km 2 making it the largest country in the Arabian Peninsula.

GIS Analysis
The analysis was carried out by using GIS Riyadh by the 10 km resolution data. However, the two cells from the previous study (Aina et al., 2014) was adopted to allow for comparison between the two data sets. Cluster analysis was carried out at the city level using an implementation 6 of Anselin local Moran's I statistic (Anselin, 1995)

in ArcGIS (Cluster and Outlier
Analysis tool). For the regional analysis, a shapefile of the administrative regions of Saudi Arabia was used to extract the PM2.5 values for the regions and ClusterPy (Duque et al., 2011) was used to carry out the cluster analysis (all the data are included from 1999-2011) using a self-organizing map (SOM) algorithm.

Results and Discussion
The new global data has some gaps (missing data) over Saudi Arabia (Figure 2).  Figures 3 and 4). In 2011, a large part of Saudi Arabia had concentrations above the WHO target of 35 μg/m 3 than in 1999 (Figures 3 and 4).

Conclusion
The study reexamines the PM 2.5 concentrations over Saudi Arabia using the new global satellite-derived data. It highlights the differences between the previous version of the data and the new version. Though the new version has some data gaps, it capable of depicting the particulate matter concentrations of the Kingdom.
It is probably more accurate than the previous version due to the higher values derived for Saudi cities. Aina et al. (2014) opined that the earlier version might have underestimated particulate matter concentrations. As regard the concentrations over Saudi Arabia, an increasing trend has been observed in all the cities and regions. Further research can be carried out to validate and improve the accuracy of the values derived for Saudi Arabia. Other satellite data, such as nighttime data, can be combined with particulate matter data to ascertain the effects of economic activities and urban expansion on particulate matter concentrations.