The continuous monitoring of particulate matter (PM) is very vital to achieving sound environmental and public health bearing in mind the adverse health impacts of these particles. Exposure to fine particulate matter (PM2.5) can cause health problems such as asthma, bronchitis, lung inflammation and other respiratory and cardiovascular diseases. Thus, the exposure of a population to particulates could result in increased hospital visits and mortality and thereby have negative impacts on social and environmental sustainability. Particulate matter monitoring is becoming more compelling due to the increasing levels of emissions of the particles from both natural and human-induced sources. This is particularly important for countries with high levels of PM concentrations. The issue of increasing levels of emissions/concentrations of PM has attained international dimension as, for example, smokes from forest fires in Indonesia impacted air quality in Malaysia and Singapore.
Conventional PM monitoring is based on ground measurements that cover limited areas because huge resources are needed to maintain a wide network of measuring devices. Remote sensing is currently being used to improve the effectiveness of particulate monitoring. Satellite imagery supplements conventional methods of data gathering and provides an opportunity for wide area coverage. Particulate matter is estimated from satellite images through the derivation of aerosol optical depth (AOD). There are established relationships between AOD and PM2.5 concentrations. The relationships are explored to make quantitative estimates of PM2.5 from satellite images such as the Moderate Resolution Imaging Spectroradiometer (MODIS). The particulate matter estimate derived from MODIS can be calibrated by using ground measurements to compute the correlation between satellite-derived data and field data. Such correlations are very useful in establishing satellite-based continuous monitoring of particulate matter.
In an effort to establish a global continuous monitoring of PM2.5
, the Center for International Earth Science Information Network (CIESIN) produced a set of global annual average PM2.5
grids from MODIS and Multi-angle Imaging SpectroRadiometer (MISR), 2001 to 2010 [1
]. The data sets cover the world from Latitude 70°N to Latitude 60°S and have a spatial resolution of approximately 50 km. Zell and Weber [2
] used the data to compute country estimates of PM2.5
from 2002 to 2009. They computed 3-year moving averages for the countries and used CIESIN’s Global Rural-Urban Mapping Project (GRUMP) 1 km population grids to compute population-weighted PM2.5
exposures. The results have been adopted by Emerson et al.
] to assess air quality in the 2012 Environmental Performance Index Report.
The results indicated that air quality in Saudi Arabia is getting worse as the population-weighted average PM2.5 values increased from 13.70 µg/m3 in 2002 to 15.11 µg/m3 in 2009. The results might be higher than that if the average particulate values are weighted by recent population data. The GRUMP data is either an estimate or old data that might not properly depict current population. Most of the studies on particulate matter in Saudi Arabia focused on PM10 and a few cities. Thus, this paper uses more recent population data to explore the changes in PM2.5 concentrations and exposures from 2002 to 2009 at the cities level. It also assesses changes in PM2.5 exposures in selected Saudi Arabian cities.
1.2. Particulate Matter, Health Risks and Remote Sensing
The issues of concentrations of particulate matter have generated some research interest due to the implications for sustainable development. Some studies [4
] have highlighted the adverse impacts of high level of particulate matter concentrations on health. The health effects depend on the composition and size of the particles and the physiology of the exposed population. Zhou et al.
] documented the presence of trace metals, which have adverse health implications, in atmospheric fine particles in an industrial city in China. Related to the issue of trace metals in particulate matter is the association between particulate matter concentrations and cancer, particularly lung cancer. Studies [11
] showed a consistent association between particulate matter and lung cancer and the International Agency for Research on Cancer (IARC) has classified particulate matter as a carcinogenic pollutant [13
]. Franck et al.
] suggested in their study of the effect of particle size on heart-related disorders, that the smaller the particle sizes the worse the health effects of exposure. However, they noted that the effects of coarse particles (PM10
) last longer than the effects of finer particles. A recent study by Son and Bell [6
] highlighted the impacts of sub-daily exposures and concluded that exposures to PM10
were associated with cardiovascular mortality. They recommended 24 h averaging time as a metric for health research and regulations. However, remote sensing observations of PM are mainly suitable for monthly and yearly assessment. This is one of the challenges highlighted by Hoff and Christopher [14
] as militating against using satellite measurements as the sole system for PM monitoring.
In order to improve the use of satellite for PM monitoring, some research articles on satellite measurement of PM values have focused on the calibration of PM/AOD relationship since the relationship varies across regions and seasons. For instance, Li et al.
], Gupta and Christopher [16
], Kumar et al.
], Schaap et al.
], Natunen et al.
], Tian and Chen [20
] and Lee et al.
] have carried out calibration studies in Finland, China, India, The Netherlands, Canada and the United States. The studies confirmed the large spatial and temporal variations of PM/AOD relationship. The correlation coefficients ranged from 0.52 to 0.97. Hu found, by using 2003 and 2004 MODIS data of the United States, that PM/AOD correlation coefficients varied from 0.22 in the west to 0.67 in the east [5
]. Moreover, AOD distribution varies with land use structure or topography [22
]. Gupta et al.
] presented a global study of PM/AOD relationship by assessing the values at 26 locations in Delhi, Hong Kong, New York, Switzerland and Sydney. They suggested that aerosol vertical distribution data could refine their analysis. Vertical profiles were included in the study by Van Donkelaar et al.
], in which they presented a continuous surface of global estimates of fine particulate matter concentrations extended over 6 years (2001–2006). They noted that 80% of world population resides in areas where the World Health Organization (WHO) Air Quality Guide (AQG) of 10 µg/m3
is exceeded. Also, 50% of eastern Asian population resides in areas where the concentrations of fine particulate matter exceed WHO Air Quality Interim Target-3 of 35 µg/m3
]. Battelle Memorial Institute and CIESIN [1
] improved the work of Van Donkelaar et al.
] by using a faster algorithm for deriving PM2.5
data and extending the years of analysis to 2010.
In the context of Saudi Arabia, most studies have focused on measuring the concentrations and compositions of particulate matter in major cities [25
] and assessing the impacts of major events such as Hajj (pilgrimage) and dust storms [30
]. For example, Rushdi et al.
] showed that PM concentrations (both PM2.5
) were higher in 2007 than 2006 and the mean concentrations in industrial and suburban areas are higher than that of other urban land use areas. Riyadh city centre was reported to have the lowest concentrations of particulate matter. Aburas et al.
] and Khodeir et al.
] determined that the elemental composition of PM2.5
in Jeddah in 2008, 2009 and 2009 included carcinogenic elements such as lead, nickel, vanadium and selenium. These elements could pose health risks for the population of the city. In a departure from the trend of using ground measurements, Othman et al.
] developed a multispectral algorithm for generating PM10
concentrations from Landsat ETM+ imagery. They reported correlation coefficients that are greater than 0.8 in Makkah, Mina and Arafah. The PM10
concentration values were computed for Makkah and its neighbouring areas only. There is a need for more satellite-based study of particulate matter in Saudi Arabia, in order to improve the monitoring of particulates resulting from both natural and anthropogenic activities. The objectives of this study are to: (1) assess exposure to fine particulate matter in Saudi Arabia using satellite-derived PM2.5
values and recent population data, (2) analyze the exposure to PM2.5
for some selected Saudi Arabian cities using cluster analysis and (3) examine the differences in PM2.5
concentrations and exposures between Saudi industrial cities and other Saudi cities.