In this paper particle categorization and absorption
properties were discussed to understand transport mechanisms at different
geographic locations and possible radiative impacts on climate. The long-term
Aerosol Robotic Network (AERONET) data set (1999–2015) is used to estimate
aerosol optical depth (AOD), single scattering albedo (SSA), and the
absorption Ångström exponent (
Location map of the AERONET stations used in this study with numbers on the map representing stations' locations: 1 – Solar Village; 2 – Bahrain; 3 – Mezaira; 4 – Cairo; 5 – Sedé Boqer; 6 – Ben Salem, 7 – Tamanrasset; and 8 – Saada.
Natural and anthropogenic aerosols suspended in the atmosphere are characterized by their diverse sources, varying particle dynamics, lifetimes, interactive mechanisms, and surface and column distributions. Identifying mixtures containing multiple aerosol types like dust, carbon, sea salt, sulfate, or nitrogen is challenging for spaceborne and in situ observations (Chin et al., 2002; Farahat, 2016). Optical techniques are used to estimate particle sizes; however, determining particle types requires more information regarding aerosol sources, trajectories, regional topography, and atmospheric conditions. As for radiative impacts, aerosol characterization and types are major input parameters for obtaining precise climate predictions (Ramanathan et al., 1989; Satheesh and Moorthy, 2005; Farahat et al., 2015). For instance, particle absorption characteristics are used in assessing aerosol emission sources, types, and interaction phases (El-Askary et al., 2015). Aerosol categorization also helps identify dominant aerosol types over a certain geographic location, while climatology effects due to aerosols' spatial and temporal distribution is carried out by examining aerosol sizes along with their absorption characteristics using modeling, satellites, and ground-based measurements (El-Askary, 2006; Kaskaoutis et al., 2012; Aboel Fetouh et al., 2013; Vukovic et al., 2014; Sprigg et al., 2014). It is noteworthy that aerosol optical and microphysical properties can provide significant information to categorize aerosol types. For example, parameters like aerosol optical depth (AOD), the Ångström exponent (AE), aerosol loading, and particle effective radius and different viewing angles are used to depict information regarding aerosol dominant types, emission sources, dust layers, and trajectories (Reid et al., 1999; Kaskaoutis and Kambezidis, 2006; Agarwal et al., 2007; Gobbi et al., 2007; Kalapureddy and Devara, 2008; Russell et al., 2010). Analyzing the derivatives of the AE and particle effective radius is also used to attain information regarding aerosol sizes and types since the particle types are directly correlated with sizes and optical properties (Gerasopoulos et al., 2003, 2011; Alados-Arboledas et al., 2003). The Aerosol Robotic Network (AERONET) data retrievals have been used widely to determine dominant aerosol types and categorization within mixing scenarios through investigating particle size distribution and optical and microphysical properties (Kaufman et al., 1994; Holben et al., 1998; Omar et al., 2005; Qin and Mitchell, 2009; Russell et al., 2010). These studies helped partition major aerosol types including dust, anthropogenic industrial pollution, and mixed and biomass burning aerosols. The absorption Ångström exponent (AAE), defined as the dependence of aerosol optical depth on wavelength as well as single scattering albedo (SSA), defined, as the ratio of scattering to extinction efficiency of aerosol particles, is used to categorize aerosol types. For instance, SSA for dust particles containing hematite and clay results in small absorption over the visible to near-infrared band and strong absorption around 440 nm (Sokolik and Toon, 1999). On the other hand, for organic carbon (OC), the SSA increases with increasing wavelength where the OC exhibits strong absorption in the visible and ultraviolet range, while for aerosols composed of black carbon (BC) particles, the SSA is inversely proportional to the wavelength. Sulfate and other hygroscopic aerosols do not show significant SSA spectral dependence (Dubovik et al., 2002). Therefore, mixed aerosol containing sulfates, BC, and OC could produce an indistinct SSA–wavelength dependence due to the varying spectral effects of aerosol mixtures in the atmosphere (Dubovik et al., 2002).
Previous studies categorizing aerosol types over some of the AERONET sites presented in this work.
In this study we investigate aerosol characteristics over North Africa and
the Middle East using eight AERONET sites in the region, namely, Solar
Village (24
AERONET is an array of sun photometers globally distributed to measure
columnar spectral AOD and water vapor in a wavelength range of 340 to 1640 nm
and temporal resolution of 600 to 900 s. The network also retrieves columnar
optical aerosol properties (e.g., aerosol size distribution, volume mean
radius, volume concentration, and multi wavelength single scattering albedo
at 440, 675, 870, and 1020 nm (Holben et al., 1998)). This takes place by
fitting measurements of the spectral AOD and sky radiances to radiative
transfer calculations (Dubovik and King, 2000). AERONET data retrievals
comprise 1–2 % estimated uncertainty (Eck et al., 1999) with the
highest uncertainty near UV wavelengths (Holben et at., 1998). We used the
AERONET Version 2, Level 2.0 products that contain retrievals for 116 different
aerosol parameters including, aerosol volume size distribution (AVSD; d
The AERONET inversion code provides aerosol optical properties by measuring
spectral direct beam and diffuse solar radiation. Water vapor and columnar
spectral AOD characteristics can be retrieved from the AERONET direct-sun
measurements with a temporal resolution of
Characteristics of the single scattering albedo (SSA) at
Aerosols absorption and physical properties categorized by aerosol types, for sample stations, using AERONET Version 2, Level 2.0 data retrievals. Some locations may experience other aerosol types during different seasons (Cairo, for instance). The spectral single scattering albedo (SSA) is listed first followed by the standard deviations based on monthly values. EMA: Egyptian Meteorology Authority.
AERONET data retrievals Version 2, Level 2.0 (Smirnov et al., 2000, 2002) are
used to derive the extinction Ångström exponent (
Aerosol absorption properties over the eight locations under investigation
are represented in Fig. 2 and Table 2. The SSA spectral behavior agrees
with Giles et al. (2012) and Dubovik et al. (2002) but with an average decrease
of 0.02 at the Solar Village and Bahrain sites. The averaged optical
properties, with aerosol data listed and volume size distribution at each
site (Table 2), shows there is a lower SSA variability at
Solar Village, Mezaira, and Bahrain compared to the other sites. The small SSA
variability at those three sites is attributed to physical (size and shape)
similarities between particle grains produced by the vast sand area
surrounding the sites. The SSA standard deviations calculated for this study
are 0.004 lower and 0.008 greater than Dubovik et al. (2002) for the Solar
Village and Bahrain sites, respectively. The difference between Table 2 and
Dubovik et al. (2002) for these two sites is due to applying improved
Level 2.0 AERONET data retrievals and utilizing a larger data set. Pure dust could be
distinguished for values of
Cairo is known for its widespread biomass burning activities observed during fall
when episodes of ash burning from agriculture waste take place (El-Askary and
Kafatos, 2008; Marey et al., 2010, 2011); however, other factors could also
contribute to pollution, such as traffic and industry. Compared to other
particle types, the biomass particles are known to have the largest SSA
variability due to various combustion phases and fuel types (Eck et al.,
2003); however, only a small SSA difference (
The similarity in the SSA characteristics between the Saada,
Tamanrasset, and Ben Salem sites, on the one hand, and Solar Village, Bahrain,
and Mezaira (Fig. 2) with a strong absorption at 440 nm, on the other hand, is an indication
of the dust dominance contribution to the Saada, Tamanrasset, and Ben Salem sites. The increased absorption at these three sites could also be
due to increased hematite percentage in the dust that could lead to an increased absorption in the blue to near-infrared wavelength band (Sokolik
and Toon. 1999). The average SSA values for all locations are
Figure 2d–f show that both small and large particles exist with large particles dominating , as is shown by the two peaks at
Absorption aerosol optical depth (
Seasonal dust domination over study locations. EMA: Egyptian Meteorology Authority.
Seasonal pollution domination over study locations.
Continued.
Continued.
Seasonal mixing particle domination over study locations.
Seasonal clear events over study locations.
The AERONET Lev 2, Ver 2.0 data retrievals are used along with Eq. 2 to
calculate average absorption aerosol optical depth (
The above results can give a general indication regarding aerosol categorizations at different locations and possible particle transport mechanism; however, they do not show the seasonality effect on particle dominance over a certain location. Long-range frequency of occurrence of clean, mixed, dust, and pollution aerosol categories along with their AOD and Ångström exponent measurements over the Solar Village, Bahrain, Mezaira, Sedé Boqer, Cairo, Saada, Tamanrasset, and Ben Salem stations can provide detailed information of the aerosol categorization and transport patterns among sites. Tables 3–6 and Fig. 4a–c show the effect of seasonality in determining the dominant aerosol particles at each location. Table 3 shows that natural dust particles dominate over the Solar Village, Bahrain, and Mezaira sites during March–June where dust storms events are active during these months. Anthropogenic aerosols dominate over the sites mostly during September–December (Table 4) due to common windstorms (Said and Kadry, 1994) blowing during these months, which help in transporting pollutants and other anthropogenic aerosols. A mixed aerosol pattern is observed all year around over the three sites but mostly during July and August (Table 5), and the air is mostly clean during November and December (Table 6). AOD values and Ångström exponents played a major role in defining the abovementioned four aerosol categories represented in Tables 3–6.
Data showed that high pollution over Cairo during the autumn months (Table 4, Fig. 4e) as a result of yearly events where farmers burn their leftover rice straw, causing severe pollution and 2 to 3 months of potential complications for respiratory and heart disease patients (Marey et al., 2010). It is interesting to observe similar pollution patterns over Sedé Boqer (Fig. 4c) during the same time of the year indicating a possible aerosol transport between different sites. Data show that dust particles dominate over Cairo during the spring season with the yearly khamsin sandstorm blowing over the country during this time. These results agree with a high fine-particle concentration found over Cairo (Fig. 2f).
Dust particles dominate over the Saada site (Table 3, Fig. 4f) during July and August, which is not the usual sand storm season (February–April) over Morocco (Goudie and Middleton, 2001). However, this could be attributed to the effect of single dust events sweeping off the coast of Morocco, like the ones on 15 August 2005 and on 7 August 2015.
Tamanrasset site data indicate that dust dominates (Fig. 4g) during March–April, which falls within the yearly dust storm events over Algeria and in October–November where individual dust events blow through the Sahara. Clear weather conditions are also found all year around. The Ben Salem (Fig. 4h) station does not provide enough data during the study period but most of the data collected point to a mixing aerosol particle pattern during May–July. Time series of the AOD and Ångström exponent show a data gap over the Mezaira, Cairo, Saada, and Ben Salem stations where the sun photometers were not operating for an extended period.
Over the Solar Village, large dust events were recorded during March–July with peak AOD observed in June 2009 (0.84), May 2009 (0.68), May 2006 (0.67), May 2003 (0.65), May 2011 (0,63), and March 2012 (0.59). It is clear that March is the month with the most frequent dust activity as major dust storms frequently blow during this time of the year. This would also indicate a higher probability of dust transportation within Saudi Arabia and the Arabian Peninsula during March. The major dust event that took place in March 2009 over Saudi Arabia could have contributed to the high AOD observed during this period, with a widespread heavy atmospheric dust load which was reported in Alharbi et al. (2013) and Farahat et al. (2016), who also suggested that the major plume of the March 2009 dust outbreak originated from several dust source areas extending across two regions – the Qasīm region lying some 500 km northwest of Riyadh within an active dust source region (Alharbi, 2009) and the Ad Dibdibah and Aş Şummān Plateau region, which is a major source of frequent dust storms in Saudi Arabia. Parts of it are in Iraq, and the south of Kuwait covers the northeastern part of the Ad Dahnā Desert. Alharbi et al. (2013) and Farahat et al. (2016) also reported that this storm was associated with an increase in AOD, wind speed, and a reduction in temperature and visibility, for few days following the storm. Similar AOD pattern was observed over the Bahrain and Mezaira stations with peak AOD observed in March 2012 (0.59) and June 2010 (0.49) over Mezaira and in May 2006 (0.45) over Bahrain. It is important to mention that the Bahrain station did not produce any data after October 2006.
Measurements and occurrence for different aerosol particle
categories and their corresponding absorption Ångström exponents
(monthly average) over
Based on the available data, dust dominates over Cairo during March and
April, which is coincident with khamsin storms, in which major dust
plumes are transported from the Sahara to eastern Europe. It is clear
that most of the year pollution episodes took place over Cairo with peak
pollution during November–January with another peak (
Pollution dominates over the Solar Village, Bahrain, and Mezaira sites from October to December with
Compared to the Solar Village, Bahrain, and Mezaira sites, lower AOD values are
recorded at the Tamanrasset and Saada sites during the dust
season, but higher pollution is observed during November–February with
A combination of ground-based aerosol-related parameters was used in this
analysis to study different sources of aerosol loadings over eight different
cities in North Africa and the Gulf region. Our analysis involved a study of the
AOD and SSA, as well as other derived parameters and trajectory models.
Natural vs. anthropogenic aerosols are well distinguished using our
derived Ångström exponent. We also identified possible mixed and
clean atmospheric conditions using the calculated
All data used in this study are publicly available at the Aerosol Robotic
Network (AERONET, 2016) homepage:
The authors would like to acknowledge the support provided by the Deanship
of Scientific Research (DSR) at the King Fahd University of Petroleum and
Minerals (KFUPM) for funding this work through project no. IN121064. The
authors would like to also extend their thanks and appreciation to the
principle investigators and their staff for establishing and maintaining the
different AERONET sites (