Aerosol classification in Europe, Middle East, North Africa and Arabian Peninsula based on AERONET Version 3

Journal Pre-proof Aerosol classification in Europe, Middle East, North Africa and Arabian Peninsula based on AERONET Version 3

Logothetis Stavros-Andreas, Salamalikis Vasileios, Kazantzidis Andreas PII:

S0169-8095(19)31470-X

DOI:

https://doi.org/10.1016/j.atmosres.2020.104893

Reference:

ATMOS 104893

To appear in:

Atmospheric Research

Received date:

5 November 2019

Revised date:

29 January 2020

Accepted date:

5 February 2020

Please cite this article as: L. Stavros-Andreas, S. Vasileios and K. Andreas, Aerosol classification in Europe, Middle East, North Africa and Arabian Peninsula based on AERONET Version 3, Atmospheric Research(2020), https://doi.org/10.1016/ j.atmosres.2020.104893

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© 2020 Published by Elsevier.

Journal Pre-proof Aerosol classification in Europe, Middle East, North Africa and Arabian Peninsula based on AERONET Version 3. Logothetis Stavros-Andreasa, Salamalikis Vasileiosa, Kazantzidis Andreasa,* a

Laboratory of Atmospheric Physics, Department of Physics, University of Patras, 26500

Patras, Greece *Corresponding Author at: Laboratory of Atmospheric Physics, Department of Physics,

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E-mail address: [email protected] (A. Kazantzidis)

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University of Patras, 26500 Patras, Greece

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Abstract

The aerosol optical properties from Version 3 (V3) of AERONET are used to classify the

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aerosol types in Europe, Middle East/North Africa (MENA) and Arabian Peninsula, during 2008-2017. Quality-assured data of Single Scattering Albedo (SSA), Fine Mode Fraction (FMF)

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and Angstrom Exponent (AE) from 39 stations are used to classify the aerosol types, based

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on threshold limits of these optical properties. The aerosol type depends on the location and

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the sources of each region of study; for example, in Atlantic, Arabian Peninsula and MENA, the dominant aerosol type is coarse absorbing due to dust from Sahara and Arabian deserts. However, in Arabian Peninsula, fine particles are also observed in autumn and winter. In addition, the lower percentages of coarse absorbing particles across MENA are observed in the East because of increased fine particle emissions from human activities. In the stations of the Group A of South Europe, a bimodal size distribution is revealed and the dominant aerosol types are the fine-slightly absorbing and non-absorbing, followed by coarse absorbing due to Sahara dust outbreaks. In the stations of the Group B of South Europe, fine slightly absorbing and non-absorbing particles are primarily observed since the stations are located in urban/industrial regions. In Central and East Europe, the prevailing aerosol type is

Journal Pre-proof fine-non absorbing which is followed by the fine slightly absorbing aerosols from urban/industrial sites. The results of the aerosol type characterization are presumed to give a better assessment of regional climate and local air pollution. The proposed method could be used to compare aerosol classification results from satellite and chemical transport models, as well as for the validation of satellite data and the improved performance of models and remote sensing algorithms in the future. Keywords:

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Aerosol; Climatology; Aerosol classification; AERONET; Aerosol optical properties

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1. Introduction

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Aerosols have an essential impact on energy budget of the Earth-Atmosphere system. Particularly, they affect directly, by absorption and scattering of solar radiation, and

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indirectly through their role as condensation nuclei in cloud formation. The direct radiative

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effect depends on aerosols physical and optical properties and the underlying surface condition (García et al., 2012). All necessary information of aerosol properties can be

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determined by ground-based or satellite remote sensing. Ground-based networks, like

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AErosol RObotic NETwork (AERONET, (Dubovik et al., 2000; Holben et al., 1998), SKYNET (Takamura and Nakajima, 2004) and European Aerosol Research LIdar NETtwork (EARLINET, Pappalardo et al., 2014) provide detailed information about aerosol microphysical and optical properties. In order to quantify the different influence of aerosol s on radiative balance, these properties can be used to categorize aerosols; this classification, provides a useful tool to assess and evaluate the global and regional changes in the Earth’s atmospheric conditions and climate. Several classification methods have been applied to discriminate the aerosols size and absorptivity. Some of them use the Single Scattering Albedo (SSA) to discriminate the aerosol absorptivity and Ångström Exponent (AE) and/or Fine Mode Fraction (FMF) to

Journal Pre-proof classify the particle size (Che et al., 2018; Dubovik et al., 2002; D M Giles et al., 2012; Lee et al., 2010; Zheng et al., 2017). Other studies use a graphical method that consists of δAE (AE440-670nm-AE670-870nm) as a function of AE440-870nm and Aerosol Optical Depth (AOD) (Basart et al., 2009; Gobbi et al., 2007; Guirado et al., 2014; Sicard et al., 2016). Additionally, some studies use statistical techniques such as Mahalanobis distance-based separations (Hamill et al., 2016) and multidimensional cluster analysis (Levy et al., 2007; Omar et al., 2005; Schmeisser et al., 2017) to determine distinct groups of sites with similar aerosol type. In

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non-statistical classification methods, the most significant part is the determination of threshold limits. For example, Lee et al. (2010) reports that an acceptable SSA’s threshold

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limit for the separation of absorbing from non-absorbing particles is 0.95. Concerning the

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particle size, aerosols with FMF values greater than 0.6 are in fine-mode and if it is lower

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than 0.4 are in coarse-mode. Mielonen et al. (2009) analyzes the separation of aerosol size depending of AE values: fine and coarse particles correspond to AE values greater than 1.2

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and lower than 0.6 respectively. Considering the division of aerosols in groups, the most

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common types are Urban/Industrial, Biomass Burning, Desert Dust, Maritime and Mixed (Dubovik et al., 2002; D M Giles et al., 2012; Hamill et al., 2016). Additionally, in Lee et al.

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(2010) classification method, a detailed study is applied to classify the fine particles in two types: the non-absorbing (NA) and Black Carbon (BC) particles. The latter is separated in three subtypes depending of particles absorptivity: the slightly absorbing (SA), moderately absorbing (MA) and highly-absorbing (HA). Based on Lee’s study, Zheng et al. (2017), adds one more aerosol type (the mixed non-absorbing particles) in Beijing which leads to better assess the effect of aerosol type on Earth-Atmosphere radiative balance when using surface and satellite observations of aerosol properties. In this study, we apply a modified classification method of Zheng et al. (2017), using the AERONET V3 dataset, across Europe, Middle East, North Africa and Arabian Peninsula. We add two new aerosol types, dedicated to mixed absorbing or non-absorbing aerosols, which

Journal Pre-proof are identified in these areas. An extensive description of aerosols properties and sources over these areas is provided. Data, methodology and site description are presented in Section 2 & 3. Results and conclusions are analyzed and discussed in Section 4 & 5, respectively.

2. Data and study area

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AERONET (Holben et al., 1998) is an association of ground-based remote sensing aerosol networks with more than 600 stations globally. Every AERONET station has a sun

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photometer which measures spectral sun irradiance, directly from sunlight path, and sky

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radiances. In every measurement, the aerosol optical depth (AOD) is provided at several wavelengths in the 340-1020 nm spectral region. AERONET Version 3 (V3) dataset is based

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on an automated data quality control algorithm including improved algorithms for cloud screening and quality control methods (Giles et al., 2019). Long-term monthly averages have

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been examined for the entire V3 and Version 2 (V2) databases and the two versions show an

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excellent agreement on average differences of 0.002 ± 0.02 (Giles et al., 2019). In V2 of

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AERONET, the database was supplied in three levels; Level 1.0 was defined as prescreened data, Level 1.5 provided near-real-time automatically cloud-cleared data, and Level 2.0 indicated an automatically cloud-cleared, manually quality-controlled data set with pre- and post-filed calibrations applied (Giles et al., 2019). Furthermore, in V3, the definitions of Level 1.5 and Level 2.0 have changed essentially. Thus, V3 Level 1.5 now defines near-real-time automatic cloud screening and automatic instrument anomaly quality controls and Level 2.0 also applies pre-field and post-field calibrations.

Journal Pre-proof In order to minimize the uncertainties of our measurements, we use AERONET data when the Solar Zenith Angle (SZA) > 50o and AOD440nm > 0.4, which is the AERONET criteria for reduced uncertainty of SSA retrievals. Information about the dominant size is provided by the volume size distribution (dV/dlnr), an AERONET inversion product, based on the division of particle radii into 22 bins between 0.05 and 15 μm. Dubovik et al. (2002, 2006) reports that the aerosols with radius smaller than 0.992 μm are considered as fine-mode particles,

𝑟𝑚𝑎𝑥 𝑑𝑁(𝑟) 𝑑𝑁(𝑟) ∫ 𝑑 ln 𝑟⁄ 𝑟2 𝑑 ln 𝑟 𝑑 ln 𝑟 𝑑 ln 𝑟 𝑟𝑚𝑖𝑛

(1)

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𝑟𝑚𝑖𝑛

𝑟3

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𝑟𝑚𝑎𝑥

𝑅𝑒𝑓𝑓 = ∫

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effective radii can be calculated from the following ratio:

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while being larger than 0.992 μm were considered as coarse-mode particles. The particles

Fig. 1. AERONET stations used for aerosol classification. The boundaries for each zone are represented by the yellow rectangles.

Journal Pre-proof The limits of integration divide Reff in three categories. Firstly, when rmin and rmax is 0.05 and 15 μm, Reff represents the total particles (R eff, total); Secondly, when rmin and rmax is 0.05 and 0.992 μm, Reff represents the fine particles (R eff, fine), and finally, when rmin and rmax is 0.992 and 15 μm, Reff represents the coarse particles (R eff, coarse). Correspondingly, the volume size distribution can be separated into the above three categories. In total, 39 AERONET stations are selected from the regions of Atlantic, Arabian Peninsula, North Africa Middle East, South, Central and East Europe. Table 1 includes all AERONET

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station names and their acronyms.

Acronym

Solar Village KAUST Campus

SLV KAC

Capo Verde

CVR

Blida Eilat SEDE BOKER Cairo EMA 2

BLI EIL SBK CAI

ATHENS-NOA IMS-METUERDEMLI Rome Tor Vergata

ATH IME

Sevastopol Brussels Lille CLUJ UBB

AERONET site Acronym Arabian Peninsula Kuwait University KWU Masdar Institute MAS Atlantic La Laguna LAL

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AERONET site

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Table 1 AERONET station names and their acronyms, used in this study.

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Middle East North Africa Nes Ziona NZA Granada GRA Tamanrasset INM TAM Tizi Ouzou TZO South Europe Burjassot BRJ Lecce University LCU

RTV

SEV BRU LIL CLB

Thessaloniki

TSL

Central and East Europe Bucharest Inoe BCI Kyiv KYV Minsk MIN

AERONET site

Acronym

Mezaira

MEZ

Santa Cruz Tenerife

SCT

Malaga Saada Oujda Ben Salem

MAL SAD OUJ BSL

Carpentras Modena

CRP MOD

CUT-TEPAK

CTP

Belsk Leipzig Moldova

BEL LEI MLD

The clustering of the stations (Fig. 1) is based on the dominant aerosol type for each region. For this reason, the stations of Granada (GRA) and Malaga (MAL) belong in MENA region although they are located in South Europe.

Journal Pre-proof 3. Methodology Lee et al. (2010), use the combination of FMF and SSA to classify the aerosol type. Influenced by Lee, Zheng et al. (2017) adds the AE in the classification method. In this study, aerosol s are classified using the optical properties of AERONET inversion product. Moreover, the optical properties are used in specific wavelengths. For the purpose of this study we used the SSA at 440 nm, FMF at 500 nm and AE between 440 and 870 nm. Thus, aerosols are

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categorized into ten types: Fine highly absorbing (SSA ≤ 0.85, FMF > 0.6 and AE >1.2).

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Fine moderately absorbing (0.85 < SSA ≤ 0.9, FMF > 0.6 and AE > 1.2).

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Fine slightly absorbing (0.9 < SSA ≤ 0.95, FMF > 0.6 and AE > 1.2).

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Fine non-absorbing (SSA > 0.95, FMF > 0.6 and AE > 1.2).

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Mixed absorbing (SSA ≤ 0.95, 0.4 ≤ FMF ≤ 0.6 and 0.6 ≤ ΑΕ ≤ 1.2).

VI.

Mixed non-absorbing (SSA > 0.95, 0.4 ≤ FMF ≤ 0.6 and 0.6 ≤ ΑΕ ≤ 1.2).

VII.

Coarse absorbing (SSA ≤ 0.95, FMF < 0.4 and AE < 0.6).

VIII.

Coarse non-absorbing (SSA > 0.95, FMF < 0.4 and AE < 0.6).

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Aerosols can be classified by their size and absorptivity: size can be determined by AE and FMF and absorptivity by SSA. Lee et al. (2010), suggests that the best threshold limit to distinguish absorbing from non-absorbing aerosols is the 0.95, although, the discrimination between fine and coarse particles is more complex. For instance, when the value s of FMF and AE are between 0.4-0.6 and 0.6-1.2, respectively, the aerosols size cannot be distinguished, and they are classified as mixed. So, fine aerosols are defined by FMF > 0.6 and AE > 1.2 whereas coarse particles respond to FMF < 0.4 and AE < 0.6. In this study, we modify the Zheng et al. (2017) classification method with the addition of two new aerosol types. The reason comes from the initial analysis of results that reveals a disagreement between FMF and AE in mixed particles (see Section 4.2). In particular, the FMF and AE

Journal Pre-proof sometimes do not have the same indication of particle size. Specifically, AE or FMF value define the aerosols size as mixed (Type V or Type VI) but the FMF or AE value, respectively, indicate non-mixed (Type I-IV or Type VII-VIII) particles. The new aerosol types are defined by their absorptivity as “Other absorbing” (Type IX) and “Other non-absorbing” (Type X). The number of major aerosol types according to their absorptivity and size is four: sea-salt (Type VIII), soil dust (Type VII), sulfate and nitrate (Type IV) and black carbon (Type I -III) particles (Lee et al., 2010). Generally, regarding to aerosol emissions, sulfate and nitrate are

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the most common types in urban-industrial regions due to fossil fuel combustion and industrial activities (Verma et al., 2012). On global scale, the main emission source of black

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carbon is the open burning of forests. In Europe, the main sources are diesel engines and

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residential coal (Bond et al., 2013). For soil dust and salt aerosols, the main sources are

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deserts and oceans, respectively. However, aerosol types in a specific region depend on season, emissions from close regions and global circulation. For example, regardless of the

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season, dust aerosols show up in Southern regions of Europe due to transport from the

4. Results

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2010).

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North Africa and the Arabian Peninsula, especially during spring and summer (Lee et al.,

The presented results are divided in two sections. Section 4.1 includes the aerosol microphysical and optical properties. The aerosol classification for all studied AERONET sites is presented in Section 4.2. 4.1 Aerosol microphysical and optical properties In this section, information about the geographical location, the number of data and the average aerosol optical properties for each region is provided. Moreover, a comprehensive analysis of seasonal and monthly variability of volume size distribution and SSA respectively, is performed.

Journal Pre-proof 4.1.1 Arabian Peninsula Five stations are included in the Arabian Peninsula (Table 2).The examination of size distribution reveals that coarse aerosols are dominant for all seasons. The effective radii of the total particles (Reff,

) are in the range of 0.52-0.63 μm and the total volume size

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distribution (Volume total) lie within 0.31 and 0.43 μm3μm-2. The lowest values of Reff, total and Volume total are observed in MAS whereas the highest in SLV. Moreover, the total AOD at 500nm lies in the range of 0.52-0.63. SSA at 440 nm has values between 0.82 and 0.98,

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globally (Eck et al., 2005). In Arabian Peninsula, the average values of SSA are confined in range from 0.89-0.93.

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Kuwait University KWU 47.97 29.32 42.0 236 729 2008-2010 0.63 ± 0.25 0.17 ± 0.08 0.46 ± 0.25 0.29 ± 0.16 0.36 ± 0.30 0.89 ± 0.03 0.95 ± 0.03 0.95 ± 0.04 0.96 ± 0.04 0.07 ± 0.03 0.67 ± 0.21 0.11 ± 0.03 1.85 ± 0.18 0.43 ± 0.22 0.05 ± 0.02 0.39 ± 0.22

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Acronym o Longitude ( ) o Latitude ( ) Altitude (m) Ndays Nmeas Years AOD500nm, total AOD500nm, fine AOD500nm, coarse FMF500nm AE440-870nm SSA440nm SSA675nm SSA870nm SSA1020nm AAOD440nm Reff, total (μm) Reff, fine (μm) Reff, coarse (μm) 3 -2 Volumetotal (μm μm ) 3 -2 Volumel fine (μm μm ) 3 -2 Volumecoarse (μm μm )

Solar Village SLV 46.40 24.91 764.0 608 1743 2008-2012 0.61 ± 0.24 0.15 ± 0.06 0.46 ± 0.22 0.27 ± 0.11 0.32 ± 0.25 0.90 ± 0.03 0.96 ± 0.03 0.96 ± 0.04 0.96 ± 0.04 0.06 ± 0.03 0.76 ± 0.21 0.11 ± 0.02 1.91 ± 0.17 0.43 ± 0.20 0.04 ± 0.02 0.39 ± 0.19

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Table 2 Geographical location, number of data and average aerosols optical parameters in Arabian Peninsula. Mezaira

MEZ 53.75 23.10 201.0 563 1379 2008-2017 0.57 ± 0.22 0.18 ± 0.07 0.39 ± 0.21 0.34 ± 0.15 0.46 ± 0.33 0.93 ± 0.02 0.97 ± 0.03 0.97 ± 0.03 0.97 ± 0.04 0.04 ± 0.02 0.65 ± 0.20 0.12 ± 0.02 1.84 ± 0.20 0.36 ± 0.18 0.05 ± 0.02 0.32 ± 0.17

KAUST Campus KAC 39.10 22.30 11.2 292 780 2012-2015 0.62 ± 0.28 0.19 ± 0.07 0.43 ± 0.25 0.34 ± 0.13 0.44 ± 0.31 0.92 ± 0.02 0.97 ± 0.02 0.98 ± 0.02 0.98 ± 0.02 0.05 ± 0.03 0.69 ± 0.21 0.12 ± 0.03 1.83 ± 0.17 0.40 ± 0.22 0.05 ± 0.02 0.36 ± 0.22

Masdar Institute MAS 54.62 24.44 4.0 488 1122 2012-2017 0.52 ± 0.15 0.20 ± 0.09 0.32 ± 0.16 0.41 ± 0.18 0.61 ± 0.37 0.92 ± 0.02 0.97 ± 0.02 0.97 ± 0.03 0.97 ± 0.03 0.04 ± 0.02 0.56 ± 0.17 0.12 ± 0.02 1.89 ± 0.22 0.31 ± 0.13 0.05 ± 0.02 0.26 ± 0.13

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Fig. 2. Monthly variation in the single scattering albedo at 440, 675, 870 and 1020 nm at (a) SLV, (b) KWU, (c) MEZ, (d) KAC, (e) MAS. The monthly variation of SSA values at four wavelengths is presented in Fig. 2. The minimum

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average value of SSA (0.89 ± 0.03) is observed at KWU (Fig. 2) while the maximum average

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value (0.93 ± 0.02) is in MEZ (Fig. 2). Generally, the magnitude of SSA depends on the composition and particle size (Dubovik et al., 2000 & 2002; Dubovik and King, 2000) . Since there are consequential differences in the average effective radii for total, fine and coarse aerosols at all stations, the main reason for the non-similar SSA values is expected to be the aerosol composition.

Journal Pre-proof 4.1.2 Atlantic Three AERONET stations are included in the Atlantic region (Table 3). The stations of SCT and LAL are located at Eastern Sub-Tropical North Atlantic and the CVR is located at Eastern Tropical North Atlantic. The Reff, total ranges between 0.72-0.76 μm in all stations. Aerosols in coarse-mode have the key role in all stations and seasons. Table 3 Geographical location, number of data and average aerosols optical parameters in Atlantic.

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0.75 ± 0.32 0.17 ± 0.08 0.58 ± 0.24 0.22 ± 0.04 0.16 ± 0.07 0.90 ± 0.03 0.98 ± 0.01 0.99 ± 0.01 0.99 ± 0.01 0.08 ± 0.04 0.76 ± 0.23 0.12 ± 0.04 1.68 ± 0.10 0.52 ± 0.24 0.05 ± 0.02 0.47 ± 0.22

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AOD500nm, total AOD500nm, fine AOD500nm, coarse FMF500nm AE440-870nm SSA440nm SSA675nm SSA870nm SSA1020nm AAOD440nm Reff, total (μm) Reff, fine (μm) Reff, coarse (μm) Volume total (μm3μm-2) Volumel fine (μm3μm-2) Volume coarse (μm3 μm-2 )

La Laguna LAL -16.32 28.48 568.0 96 230 2008-2010, 2012-2013 20152017 0.66 ± 0.30 0.15 ± 0.08 0.50 ± 0.23 0.23 ± 0.05 0.15 ± 0.06 0.92 ± 0.02 0.98 ± 0.01 0.98 ± 0.02 0.98 ± 0.02 0.05 ± 0.03 0.75 ± 0.17 0.12 ± 0.03 1.59 ± 0.10 0.42 ± 0.21 0.04 ± 0.02 0.38 ± 0.19

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Acronym Longitude ( o) Latitude ( o) Altitude (m) Ndays Nmeas Years

Capo Verde CVR -22.93 16.73 60.0 31 60 2016-2017

Santa Cruz Tenerife SCT -16.24 28.47 52.0 183 444 2008-2016 0.64 ± 0.29 0.15 ± 0.07 0.49 ± 0.23 0.24 ± 0.04 0.19 ± 0.09 0.92 ± 0.02 0.98 ± 0.01 0.99 ± 0.01 0.99 ± 0.01 0.06 ± 0.03 0.72 ± 0.19 0.12 ± 0.03 1.60 ± 0.09 0.40 ± 0.20 0.04 ± 0.02 0.36 ± 0.19

Prospero et al. (2002) reported that the seasonal variability of aerosols is dominated by mineral dust emissions from North Africa reaching the maximum concentration values in summer. North African mineral dust emissions are also common during winter whereas in spring and autumn the activity is decreasing. In our study, however, the maximum values in volume size distribution are observed in spring at CVR and LAL and in winter at SCT. Furthermore, close SSA average values are revealed at all stations.

Journal Pre-proof The differences between CVR (SSA 440nm = 0.90 ± 0.03) and SCT, LAL (SSA440nm = 0.92 ± 0.02) could be attributed to different aerosol concentrations. Based on Table 3, the highest concentration leads to lowest values in SSA at CVR. The other two stations present higher SSA values accompanied by lower values of volume size distribution of total particles. Th e seasonal variation of SSA at close sites of LAL and SCT has the same pattern (Fig. 3). In general, SSA wavelength dependence is functional with aerosol s type (Cheng et al., 2006; Russell et al., 2010). Specifically, for coarse-mode aerosols, the SSA wavelength dependence

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is stronger than fine-mode. The SSA’s wavelength dependence (Fig. 3) is a consequence of

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mineral dust that from nearby deserts.

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Fig. 3. Monthly variations in the single scattering albedo at 440, 675, 870 and 1020 nm at (a) CVR, (b) LAL, (c) SCT. Lastly, it should be mentioned that the number of days between CVR (31) and LAL (96) were relative few, so, a solid conclusion could not be extracted. 4.1.3 Middle East – North Africa (MENA) For all twelve stations at MENA (Table 4), the Reff, total lies between 0.50 and 0.83 μm, a clearly wider range when compared with the previous regions. The maximum value (0.83 ± 0.20) is found at TAM in Southern Algeria while the minimum value (0.50 ± 0.16) is observed at CAI, Egypt.

Journal Pre-proof Considering Fig. 1, the stations are divided in two groups; The Eastern group is composed of four stations: NZA, SBK, EIL and CAI. This group, except CAI, presents values of Reff, total in a narrow range (0.65-0.69 μm). The Western group is composed of eight stations: BSL, ΤΑΜ, TZO, BLI, OUJ, GRA, MAL and SAD. In this group, except TAM, Reff, total lies between 0.52 and 0.72. Fig. 4 & 5 show the seasonal aerosol volume size distribution in MENA.

Acronym o Longitude ( ) o Latitude ( ) Altitude (m) Ndays Nmeas Years AOD 500nm, total AOD 500nm, fine AOD 500nm, coarse FMF500nm AE440-870nm SSA440nm SSA675nm SSA870nm SSA1020nm AAOD 440nm Reff, total (μm) Reff, fine (μm) Reff, coarse (μm) 3 -2 Volumetotal (μm μm ) 3 -2 Volumelfine (μm μm ) 3 -2 Volumecoarse (μm μm )

SBK 34.78 30.86 480.0 228 477 2009-2017 0.51 ± 0.20 0.18 ± 0.08 0.33 ± 0.21 0.39 ± 0.20 0.54 ± 0.41 0.92 ± 0.03 0.96 ± 0.02 0.96 ± 0.03 0.95 ± 0.03 0.04 ± 0.02 0.69 ± 0.18 0.13 ± 0.03 1.90 ± 0.26 0.32 ± 0.18 0.04 ± 0.01 0.28 ± 0.17

TAM 5.53 22.79 1377.0 311 569 2008-2009, 2011-2017 0.65 ± 0.25 0.13 ± 0.07 0.51 ± 0.20 0.21 ± 0.05 0.13 ± 0.07 0.89 ± 0.04 0.97 ± 0.03 0.97 ± 0.03 0.97 ± 0.03 0.07 ± 0.03 0.83 ± 0.20 0.12 ± 0.03 1.70 ± 0.12 0.45 ± 0.19 0.03 ± 0.02 0.42 ± 0.18

EIL 34.91 29.50 15.0 187 426 2008-2009, 2011-2017 0.53 ± 0.21 0.18 ± 0.08 0.35 ± 0.21 0.37 ± 0.18 0.53 ± 0.38 0.91 ± 0.02 0.97 ± 0.02 0.98 ± 0.02 0.98 ± 0.02 0.05 ± 0.02 0.65 ± 0.26 0.13 ± 0.02 1.86 ± 0.23 0.33 ± 0.17 0.05 ± 0.02 0.28 ± 0.17

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Tamanrasset INM

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MAL -4.48 36.71 56.0 57 145 2009-2016 0.46 ± 0.10 0.16 ± 0.08 0.30 ± 0.13 0.36 ± 0.19 0.47 ± 0.34 0.90 ± 0.02 0.96 ± 0.02 0.97 ± 0.02 0.97 ± 0.02 0.05 ± 0.02 0.57 ± 0.11 0.12 ± 0.03 1.75 ± 0.18 0.27 ± 0.10 0.04 ± 0.01 0.23 ± 0.10

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NZA 34.79 31.92 40.0 123 229 2008, 2010-2011, 2013-2015 0.54 ± 0.22 0.21 ± 0.10 0.33 ± 0.24 0.43 ± 0.24 0.59 ± 0.46 0.94 ± 0.03 0.97 ± 0.02 0.97 ± 0.03 0.97 ± 0.03 0.04 ± 0.02 0.65 ± 0.23 0.15 ± 0.04 1.87 ± 0.33 0.31 ± 0.21 0.04 ± 0.02 0.27 ± 0.21

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SEDE BOKER

Nes Zi ona

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BLI 2.88 36.51 230.0 68 134 2008-2010,2012 0.47 ± 0.15 0.18 ± 0.07 0.29 ± 0.14 0.41 ± 0.16 0.60 ± 0.34 0.90 ± 0.03 0.96 ± 0.02 0.96 ± 0.03 0.97 ± 0.02 0.05 ± 0.02 0.52 ± 0.14 0.12 ± 0.03 1.85 ± 0.26 0.27 ± 0.11 0.05 ± 0.02 0.22 ± 0.11

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Bl i da Acronym o Longitude ( ) o Latitude ( ) Altitude (m) Ndays Nmeas Years AOD 500nm, total AOD 500nm, fine AOD 500nm, coarse FMF500nm AE440-870nm SSA440nm SSA675nm SSA870nm SSA1020nm AAOD 440nm Reff, total (μm) Reff, fine (μm) Reff, coarse (μm) 3 -2 Volumetotal (μm μm ) 3 -2 Volumelfine (μm μm ) 3 -2 Volumecoarse (μm μm )

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Table 4 Geographical location, number of data and average aerosols optical parameters in Middle East North Africa.

Oujda OUJ -1.90 34.65 620.0 56 123 2011-2015 0.52 ± 0.15 0.12 ± 0.04 0.39 ± 0.14 0.25 ± 0.09 0.25 ± 0.18 0.89 ± 0.02 0.97 ± 0.02 0.97 ± 0.02 0.97 ± 0.02 0.06 ± 0.02 0.71 ± 0.17 0.11 ± 0.02 1.76 ± 0.16 0.35 ± 0.13 0.04 ± 0.01 0.31 ± 0.14

Cairo EMA 2 CAI 31.29 30.08 70.0 853 1684 2010-2017 0.54 ± 0.23 0.31 ± 0.22 0.23 ± 0.17 0.57 ± 0.22 0.91 ± 0.41 0.89 ± 0.04 0.92 ± 0.04 0.92 ± 0.05 0.92 ± 0.05 0.07 ± 0.03 0.50 ± 0.16 0.14 ± 0.04 2.31 ± 0.42 0.28 ± 0.14 0.07 ± 0.04 0.21 ± 0.14

Gra na da

Sa a da

GRA -3.61 37.16 680.0 89 183 2008, 2010-2013,2015-2017 0.50 ± 0.17 0.16 ± 0.12 0.34 ± 0.18 0.33 ± 0.23 0.40 ± 0.44 0.90 ± 0.03 0.97 ± 0.03 0.97 ± 0.04 0.97 ± 0.05 0.06 ± 0.02 0.58 ± 0.18 0.12 ± 0.03 1.77 ± 0.39 0.30 ± 0.14 0.04 ± 0.02 0.26 ± 0.14

Tizi Ouzou TZO 4.06 36.70 133.0 86 155 2012-2017 0.48 ± 0.11 0.17 ± 0.08 0.32 ± 0.11 0.35 ± 0.15 0.47 ± 0.29 0.89 ± 0.02 0.96 ± 0.02 0.96 ± 0.02 0.96 ± 0.02 0.06 ± 0.02 0.57 ± 0.20 0.11 ± 0.03 1.86 ± 0.22 0.31 ± 0.11 0.05 ± 0.02 0.26 ± 0.11

SAD -8.16 31.62 420.0 22 51 2017 0.65 ± 0.30 0.18 ± 0.09 0.46 ± 0.24 0.29 ± 0.08 0.31 ± 0.15 0.91 ± 0.02 0.97 ± 0.01 0.98 ± 0.02 0.98 ± 0.01 0.06 ± 0.03 0.72 ± 0.18 0.13 ± 0.03 1.80 ± 0.20 0.42 ± 0.22 0.05 ± 0.02 0.38 ± 0.20

Ben Salem BSL 9.91 35.55 130.0 21 43 2016-2017 0.67 ± 0.36 0.17 ± 0.11 0.50 ± 0.26 0.25 ± 0.08 0.22 ± 0.18 0.90 ± 0.02 0.98 ± 0.01 0.98 ± 0.02 0.98 ± 0.02 0.07 ± 0.03 0.72 ± 0.21 0.12 ± 0.03 1.73 ± 0.17 0.44 ± 0.25 0.04 ± 0.03 0.40 ± 0.23

Journal Pre-proof Coarse aerosols are the dominant aerosol size in all seasons with higher values during spring and autumn in the Eastern group. In the Western group, the higher values are not clearly

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observed in a particular season.

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Fig. 4. Seasonal variation in the aerosol volume size distribution at (a) BLI, (b) NZA, (c) MAL, (d) EIL, (e) GRA, (f) SAD.

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Fig. 5. Seasonal variation in the aerosol volume size distribution at (a) SBK, (b) TAM, (c) OUJ, (d) CAI, (e) TZO, (f) BSL. For instance, the higher values at MAL, SAD and TAM are reported in summer whereas the

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higher values at BLI and BSL are observed in spring. The TAM station presents the highest

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value of volume size distribution in coarse-mode (0.42 ± 0.18 μm3μm-2) and the lowest value in fine-mode aerosols (0.03 ± 0.02 μm3μm-2). On the contrary, the lowest volume size distribution in coarse (0.21 ± 0.14 μm3 μm-2 ) and higher in fine-mode aerosols (0.07 ± 0.04 μm3 μm-2 ) is revealed at CAI station. The average SSA440nm values lie within 0.89-0.91 and 0.89-0.94 in Western and Eastern group respectively. The highest value is observed in NZA (0.94 ± 0.03) and the lower ones are reported at TAM (0.89 ± 0.04), CAI (0.89 ± 0.04), TZO (0.89 ± 0.02) and OUJ (0.89 ± 0.02). The monthly SSA 440nm rarely exceeds 0.95, so absorbing aerosols are dominant at all stations.

Journal Pre-proof 4.1.4 South Europe South Europe consists of nine AERONET stations (Table 5). The Reff, total lies between 0.28 and 0.49 μm and depends on location. The stations have been divided into 2 groups depending on the results of the classification method (See Section 4.2.4). The Group A includes CTP, IME, ATH, BRJ, RTV and LCU; this group has R eff, total values in the range of 0.37-0.49 μm. Correspondingly, the Group B includes CRP, MOD and TSL stations and presents R eff, total values between 0.28 and 0.33 μm.

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These difference in Reff, total are linked to dust appearance. The maximum value (0.49 ± 0.17 μm), reported at CTP, is caused by dust transport (discussed in Section 4.3.2). On the

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contrary, the minimum value (0.28 ± 0.10 μm) is observed at TSL due to fine particles from

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local and regional pollution. Fig. 6 & 7 show the seasonal aerosol volume size distribution in

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Southern Europe.

Journal Pre-proof Table 5 Geographical location, number of data and average aerosols optical parameters in South Europe.

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56.0

LCU 18.11 40.33 30.0 112 219 2008-2017 0.42 ± 0.09 0.30 ± 0.12 0.12 ± 0.14 0.72 ± 0.27 1.33 ± 0.64 0.94 ± 0.02 0.96 ± 0.02 0.94 ± 0.03 0.94 ± 0.04 0.03 ± 0.01 0.37 ± 0.14 0.15 ± 0.03 2.04 ± 0.39 0.15 ± 0.10 0.05 ± 0.01 0.11 ± 0.10

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IME 34.26 36.56 3.0 301 517 2008-2017 0.47 ± 0.13 0.31 ± 0.11 0.15 ± 0.13 0.68 ± 0.19 1.19 ± 0.40 0.95 ± 0.03 0.95 ± 0.04 0.94 ± 0.04 0.94 ± 0.05 0.03 ± 0.02 0.42 ± 0.16 0.16 ± 0.02 2.17 ± 0.35 0.20 ± 0.09 0.07 ± 0.03 0.13 ± 0.10

Thes saloniki TSL

CUT-TEPAK CTP

12.65

22.96

33.04

41.84

40.63

34.67

130.0

60.0

22.0

50

190

66

100

429

135

2010-2017

2011-2017

2011, 2014-2017

0.45 ± 0.12

0.42 ± 0.08

0.45± 0.12

95

Nmeas

222

Years

2010-2017

AOD 500nm, total

0.46 ± 0.12

AOD 500nm, fine

0.42 ± 0.13

0.27 ± 0.14

0.37 ± 0.10

0.23 ± 0.09

AOD 500nm, coarse

0.05 ± 0.08

0.18 ± 0.19

0.06 ± 0.08

0.22 ± 0.17

FMF500nm

0.89 ± 0.16

0.63 ± 0.33

0.87 ± 0.17

0.55 ± 0.25

1.46 ± 0.34

1.05 ± 0.69

1.6. ± 0.40

0.95 ± 0.57

0.97 ± 0.02

0.93 ± 0.04

0.96 ± 0.02

0.94 ± 0.03

0.97 ± 0.02

0.96 ± 0.03

0.96 ± 0.02

0.96 ± 0.03

0.96 ± 0.03

0.96 ± 0.04

0.95 ± 0.03

0.96 ± 0.03

0.96 ± 0.03

0.95 ± 0.04

0.95 ± 0.04

0.96 ± 0.03

0.02 ± 0.01

0.04 ± 0.03

0.02 ± 0.01

0.03 ± 0.02

0.32 ± 0.09

0.46 ± 0.25

0.28 ± 0.10

0.49 ± 0.17

0.19 ± 0.04

0.15 ± 0.04

0.16 ± 0.02

0.14 ± 0.03

2.46 ± 0.47

2.17 ± 0.50

2.31 ± 0.42

1.93 ± 0.30

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Ndays

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44.63

Altitude (m)

Lecce Uni vers i ty

RTV

10.94

Latitude ( )

IMSMETUERDEMLI

Rome Tor Verga ta MOD

Longitude ( )

CRP 5.06 44.08 107.0 67 126 2008-2017 0.40 ± 0.06 0.32 ± 0.10 0.08 ± 0.10 0.80 ± 0.23 1.34 ± 0.44 0.93 ± 0.04 0.94 ± 0.04 0.92 ± 0.04 0.92 ± 0.05 0.03 ± 0.02 0.33 ± 0.11 0.17 ± 0.04 2.14 ± 0.53 0.12 ± 0.07 0.05 ± 0.02 0.07 ± 0.07

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Modena Acronym

BRJ -0.42 39.51 104.0 77 132 2009-2012, 2014-2017 0.45 ± 0.15 0.26 ± 0.12 0.20 ± 0.20 0.61 ± 0.29 1.00 ± 0.59 0.93 ± 0.03 0.96 ± 0.03 0.95 ± 0.03 0.95 ± 0.04 0.04 ± 0.02 0.46 ± 0.17 0.15 ± 0.05 2.04 ± 0.44 0.21 ± 0.14 0.05 ± 0.02 0.16 ± 0.15

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ATH 23.71 37.97 130.0 102 211 2008-2010, 2014-2017 0.42 ± 0.08 0.30 ± 0.12 0.12 ± 0.14 0.74 ± 0.28 1.31 ± 0.63 0.92 ± 0.03 0.93 ± 0.04 0.92 ± 0.05 0.91 ± 0.05 0.04 ± 0.01 0.40 ± 0.18 0.16 ± 0.03 2.16 ± 0.43 0.15 ± 0.09 0.05 ± 0.02 0.10 ± 0.10

Ca rpentra s

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Acronym o Longitude ( ) o Latitude ( ) Altitude (m) Ndays Nmeas Years AOD 500nm, total AOD 500nm, fine AOD 500nm, coarse FMF500nm AE440-870nm SSA440nm SSA675nm SSA870nm SSA1020nm AAOD 440nm Reff, total (μm) Reff, fine (μm) Reff, coarse (μm) 3 -2 Volumetotal (μm μm ) 3 -2 Volumelfine (μm μm ) 3 -2 Volumecoarse (μm μm )

Burja s s ot

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ATHENS-NOA

AE440-870nm SSA440nm

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SSA675nm SSA870nm SSA1020nm AAOD 440nm Reff, total (μm) Reff, fine (μm) Reff, coarse (μm) 3

-2

0.12 ± 0.06

0.20 ± 0.14

0.13 ± 0.05

0.21 ± 0.11

3

-2

0.07 ± 0.02

0.05 ± 0.02

0.07 ± 0.02

0.05 ± 0.01

0.05 ± 0.06

0.15 ± 0.15

0.06 ± 0.05

0.17 ± 0.11

Volumetotal (μm μm ) Volumelfine (μm μm ) 3

-2

Volumecoarse (μm μm )

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Fig. 6. Season variation in the aerosol volume size distribution at (a) ATH, (b) BRJ, (c) CRP, (d) IME, (e) LCU.

Fig. 7. Season variation in the aerosol volume size distribution at (a) MOD, (b) RTV, (c) TSL, (d) CTP. The major difference of South Europe from previous regions is the bimodal size distribution, as a result of simultaneous local pollution and low concentration of mineral dust.

Journal Pre-proof In most cities, the higher volumes of the coarse-mode particles are observed in summer (RTV and CRP) or spring (IME, ATH, LCU, MOD, TSL and CTP). Furthermore, higher volumes of fine-mode particles are observed in autumn (ATH, BRJ, CRP, IME, TSL and MOD), summer (CTP and LCU) and spring (RTV). CTP has the highest value of volume size d istribution in coarse-mode (0.16 ± 0.11 μm3 μm-2 ) while the lowest one (0.05 ± 0.06 μm3 μm-2) is reported at MOD. For fine-mode particles, the higher values are observed at IME (0.07 ± 0.03 μm3μm2

), MOD (0.07 ± 0.02 μm3 μm-2 ) and TSL (0.07 ± 0.02 μm3 μm-2). The average SSA values lie

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within 0.92 and 0.97 (Table 5) ; The highest value is observed at MOD (0.97 ± 0.02) whereas the lowest one at ATH (0.92 ± 0.03). The main difference with the previous regions is that

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the highest SSA values occur due to the increased concentration of fine-mode particles. In

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general, SSA wavelength dependence is lower compared to results from previous regions.

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4.1.5 Central and East Europe

The Central and East Europe group consists of ten AERONET sites (Table 6). The Reff, total

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ranges between 0.28 and 0.34 μm at all stations. The volume size distribution of total

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particles lies within 0.11 and 0.14 μm3 μm-2 indicating that fine-mode aerosols have a key

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role at all stations, mainly appear due aerosol anthropogenic sources. Coarse particles are rarely observed in Central and East Europe with the exception of dust transport from Saharan desert. Israelevich et al. (2012), reported that in Central Europe (5oE-25oE) dust appears in spring and summer, whereas in eastern Europe (25oE-40oE) dust occurs in spring and autumn. Considering the aerosol absorptivity, the average SSA values are in the narrow range 0.94-0.96 (Table 6). Fine-mode particles prevail with FMF values lie within 0.84 and 0.92. The lowest value is observed in SEV (0.84 ± 0.14) whereas the highest one in LIL (0.92 ± 0.13). The number of measurements is lower than other regions. All Central and East Europe stations do not have measurements in wintertime due to the increased number of cloudy days. Fig. 8 & 9 show the seasonal aerosol volume size distribution in all stations of Central and East Europe.

Journal Pre-proof Table 6 Geographical location, number of data and average optical parameters for aerosols in Central and East Europe.

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Longi tude ( o) La ti tude ( o) Al ti tude (m) Ndays Nmeas Yea rs

AOD 500nm, total AOD 500nm, fine AOD 500nm, coarse FMF 500nm AE440-870nm SSA440nm SSA675nm SSA870nm SSA1020nm AAOD 440nm R eff, total (μm) R eff, fine (μm) R eff, coarse (μm) 3 -2 Vol umetotal (μm μm ) 3 Vol umel fine (μm μm -2) Vol umecoarse (μm 3μm -2)

0.46 ± 0.14 0.40 ± 0.15 0.06 ± 0.10 0.87 ± 0.18 1.51 ± 0.39 0.96 ± 0.02 0.96 ± 0.03 0.94 ± 0.04 0.94 ± 0.05 0.02 ± 0.01 0.30 ± 0.10 0.18 ± 0.04 2.29 ± 0.46 0.13 ± 0.07 0.07 ± 0.03 0.06 ± 0.07

0.49 ± 0.20 0.45 ± 0.21 0.04 ± 0.06 0.92 ± 0.13 1.49 ± 0.30 0.96 ± 0.02 0.96 ± 0.03 0.94 ± 0.03 0.94 ± 0.04 0.02 ± 0.02 0.30 ± 0.08 0.20 ± 0.04 2.38 ± 0.44 0.11 ± 0.05 0.07 ± 0.03 0.04 ± 0.04

Brussels

Kyiv

BRU 4.35 50.78 120.0 75 138 2008-2017 0.50 ± 0.26 0.45 ± 0.27 0.05 ± 0.06 0.90 ± 0.14 1.47 ± 0.33 0.96 ± 0.03 0.95 ± 0.03 0.94 ± 0.04 0.93 ± 0.05 0.02 ± 0.02 0.31 ± 0.08 0.20 ± 0.04 2.30 ± 0.44 0.12 ± 0.08 0.07 ± 0.04 0.05 ± 0.05 Moldova MLD 28.81 47.00 205.0 108 234 2008-2016

KYV 30.50 50.36 200.0 47 103 2014-2017 0.47 ± 0.15 0.42 ± 0.17 0.05 ± 0.06 0.88 ± 0.13 1.57 ± 0.28 0.95 ± 0.02 0.95 ± 0.03 0.94 ± 0.04 0.93 ± 0.04 0.02 ± 0.01 0.31 ± 0.06 0.17 ± 0.03 2.44 ± 0.45 0.12 ± 0.03 0.06 ± 0.02 0.06 ± 0.03 CLUJ UBB CLB 23.55 46.77 405.0 85 161 2010-2017

0.44 ± 0.10 0.39 ± 0.11 0.04 ± 0.05 0.90 ± 0.11 1.65 ± 0.26 0.94 ± 0.03 0.93 ± 0.04 0.91 ± 0.05 0.90 ± 0.05 0.03 ± 0.02 0.28 ± 0.07 0.16 ± 0.03 2.45 ± 0.42 0.12 ± 0.04 0.06 ± 0.02 0.05 ± 0.03

0.41 ± 0.07 0.36 ± 0.09 0.05 ± 0.07 0.87 ± 0.15 1.59± 0.35 0.95 ± 0.02 0.94 ± 0.03 0.92 ± 0.04 0.91 ± 0.05 0.02 ± 0.01 0.29 ± 0.09 0.16 ± 0.02 2.37 ± 0.47 0.12 ± 0.04 0.06 ± 0.02 0.05 ± 0.04

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BEL 20.79 51.83 190.0 98 210 2008-2016 0.44 ± 0.11 0.40 ± 0.12 0.04 ± 0.04 0.90 ± 0.10 1.64 ± 0.25 0.95 ± 0.02 0.94 ± 0.03 0.92 ± 0.04 0.91 ± 0.05 0.03 ± 0.01 0.28 ± 0.06 0.17 ± 0.03 2.37 ± 0.44 0.11 ± 0.03 0.06 ± 0.02 0.05 ± 0.02 Minsk MIN 27.60 53.92 235.0 42 98 2008-2011, 2014, 2016 0.48 ± 0.15 0.43 ± 0.16 0.05 ± 0.05 0.90 ± 0.11 1.61 ± 0.24 0.95 ± 0.03 0.94 ± 0.03 0.93 ± 0.05 0.93 ± 0.05 0.03 ± 0.02 0.28 ± 0.07 0.16 ± 0.02 2.33 ± 0.44 0.13 ± 0.04 0.07 ± 0.02 0.06 ± 0.03

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BCI 26.03 44.34 89.0 135 274 2008-2016 0.44 ± 0.11 0.37 ± 0.11 0.07 ± 0.11 0.85 ± 0.17 1.51 ± 0.37 0.96 ± 0.02 0.96 ± 0.03 0.95 ± 0.03 0.94 ± 0.04 0.02 ± 0.01 0.32 ± 0.11 0.16 ± 0.02 2.39 ± 0.44 0.13 ± 0.07 0.06 ± 0.02 0.07 ± 0.07 Lille LIL 3.141 50.61 60.0 96 228 2008-2017

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Acronym

SEV 33.52 44.62 80.0 60 153 2008-2013 0.42 ± 0.09 0.36 ± 0.11 0.07 ± 0.07 0.84 ± 0.14 1.53 ± 0.32 0.95 ± 0.03 0.94 ± 0.04 0.93 ± 0.04 0.93 ± 0.05 0.03 ± 0.02 0.34 ± 0.12 0.15 ± 0.02 2.34 ± 0.34 0.14 ± 0.05 0.06 ± 0.03 0.08 ± 0.05 Leipzig LEI 12.43 51.35 125.0 77 160 2008-2017

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Longi tude ( ) La ti tude ( o) Al ti tude (m) Ndays Nmeas Yea rs AOD 500nm, total AOD 500nm, fine AOD 500nm, coarse FMF 500nm AE440-870nm SSA440nm SSA675nm SSA870nm SSA1020nm AAOD 440nm R eff, total (μm) R eff, fine (μm) R eff, coarse (μm) Vol umetotal (μm 3μm -2) Vol umel fine (μm 3μm -2) 3 -2 Vol umecoarse (μm μm )

Belsk

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Acronym

Bucharest Inoe

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Sevastopol

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Fig. 8. Season variation in the aerosol volume size distribution at (a) SEV, (b) BCI, (c) BEL, (d) BRU, (e) KYV

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4.2 Classification

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Fig. 9. Season variation in the aerosol volume size distribution at (a) LEI, (b) LIL, (c) MIN, (d) MLD, (e) CLB.

3).

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In this section, the results of the proposed classification method are presented (see Section

4.2.1 Arabian Peninsula

Across the Arabian Peninsula, the dominant aerosol type is coarse absorbing (Type VII) and, secondly, the mixed absorbing one (Type V). Based in Fig. 10 the stations with the percentages of type VII in ascending order are MAS (55.7%), MEZ (68.60%), KAC (68.97%), SLV (83.48%) and KWU (86.15%). Prospero et al. (2002) reported that there are two leading natural sources in Arabian Peninsula: the first area is located in a valley between the Tigris and Euphrates rivers, where dust is caused by the deserts of Iraq, northeast of Saudi Arabia and the south of Iran; the second area is close to the coast of Oman. SLV and KWU stations

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Fig. 10. Heatmap with the percentages of aerosol type at every station in Arabian Peninsula.

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are affected by the first source and MEZ and MAS are affected by the second one. In

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addition, when the percentage of type VII is getting lower, the percentage of type V

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increases. In Fig. 11, the spreading of aerosols optical properties is presented.

Fig. 11. Scatter plot between AE440-870nm and SSA440nm at (a) SLV, (b) KWU, (c) MEZ, (d) KAC, (e) MAS. The solid and dashed lines separate the aerosol type. The color bar represents the value of FMF500nm. The yellow circle indicates the Aerosol Type IX & X.

Journal Pre-proof Stations with higher percentage of mixed absorbing aerosols have wider dispersion in scatter plots. This can be also noticed from the average values of FMF at 500 nm: the mean values for SLV, KWU, MEZ, KAC and MAS are 0.27 ± 0.11, 0.29 ± 0.16, 0.34 ± 0.15, 0.34 ± 0.13 and 0.41 ± 0.18, respectively (Table 2) .In MAS, the highest mean value of FMF is observed (10.07%). The lowest FMF values (< 0.3) at all stations are observed in April and May due to dust outbreaks (Kaskaoutis et al., 2007). All stations have the coarse absorbing and mixed absorbing particles as their main aerosol type during all seasons. During winter, the

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percentages of Type V for SLV, KWU, MEZ, KAC and MAS are 8.16, 5.88, 20.75, 32.84 and 37.74% respectively. For Type VII, the corresponding percentage values are 87.76, 36.76,

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48.11, 46.27 and 25.47%.

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Consequently, small particles are observed in all stations. The higher percentages are found

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in KWU and MAS. KUW has 40.0% of fine-mode aerosols (Type I~ 7.35%, Type II~ 5.88%, Type III~ 19.12%, Type IV~ 17.65%) whereas MAS has 24.53% of fine-mode particles (Type II~

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0.94%, Type III~ 13.1%, Type IV~ 10.38%) and the highest ratio of Type V (37.74%). During

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spring, the only stations that have non-zero percentages of Type V aerosols are KWU (1.37%)

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and MEZ (6.41%). Percentages of 99.02, 96.59, 87.95, 90.53 and 78.75% are revealed for Type VII, showing the dust domination in this season. During autumn, the highe st percentages of Type V are observed (28.12, 17.39, 33.68, 54.10 and 32.62%). For aerosol Type VII, percentages of 63.26, 74.53, 33.66, 15.57 and 25.23% are revealed. In summary, higher percentages of coarse absorbing particles are observed in spring for all stations whereas fine particles are observed in autumn and winter. Furthermore, the stations with the percentages of Other aerosol type (IX & X) are between 2.61 (KWU) and 6.5% (MAS). As we can see in Fig. 11, the discrepancy between AE and FMF appears mainly in two ways, firstly, when the FMF indicates particles in coarse-mode and AE in mixed-mode and, secondly, when the FMF indicates particles in fine-mode and AE, again, in mixed-mode.

Journal Pre-proof 4.2.2 Atlantic In the Atlantic, fine particles are quasi inexistent in all stations ( Fig. 12). Particularly, the region of Atlantic shows that the dominant aerosol type is coarse absorbing (Type VII). The stations with the percentages of type VII in descending order (Fig. 12) are CVR (100%), SCT

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(96.40%) and LAL (89.57%).

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Fig. 12. Heatmap with the percentages of aerosol type at every station in Atlantic. Considerably, Santa Cruz is affected exclusively by mineral dust particles from the western

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arid areas (Sahara, Morocco, Tunisia, Mauritania and northern and eastern Algeria,

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(Prospero et al., 2002)). The proximity among the those areas and their regional atmospheric circulation leads to the dust climatology of Atlantic (Alonso-Pérez et al., 2007; Basart et al., 2009; Querol et al., 2004; Viana et al., 2002). As a result, the station of Santa Cruz includes very high percentages of coarse absorbing aerosols. Moreover, this region is affected by anthropogenic aerosols from Europe or Africa due to local pollution (Díaz et al., 2006; Rodríguez et al., 2011; Viana et al., 2002). Rodríguez et al. (2011) reported that major pollutants are the nitrate and ammonium sulphate particles, connected to emmisions from oil refineries and power plants in Algeria, Marocco and Tunisia. Besides the dispersion of pollutants, transported from Europe or/and Africa, local emissions of fine aerosols could be noticeable, too.

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Fig. 13. Scatter plot between AE440-870nm and SSA440nm at (a) CVR, (b) LAL, (c) SCT. The solid and dashed lines separate the aerosol type. The color bar represents the value of FMF500nm. The yellow circle indicates the Aerosol Type IX & X.

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Therefore, the ratio of aerosols type I-IV at SCT is evident but lower than those regions who have comparable urban and industrial development in continental environments (Basart et

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al., 2009; Rodríguez et al., 2008; Rodríguez and Guerra, 2001). Concerning local pollution,

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the pollutants are mixed with the high concentration of coarse aerosols, so the proportion of

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anthropogenic aerosols is non-significant (Fig. 12). Saharan dust from West Africa has an impact on the yearly climatology of CVR (Basart et al., 2009). The latter is in the West African

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Saharan dust outflow which is responsible for the high percentage of type VII (98.36%).

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Concerning the location of the stations, we expect high percentages of aerosol type VIII (seasalt/marine). Contrary to expectations, low values (<10%) are revealed. This could be

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attributed to the fact that AOD440nm for this aerosol type is less than 0.4 (see Section 2). In Fig. 13, the domination of type VII in every station is observed while AE and FMF take very low values. In particular, the mean FMF at CVR, LAL and SCT are 0.22 ± 0.04, 0.23 ± 0.05 and 0.24 ± 0.04, respectively (Table 3). Lastly, the percentages of Other aerosol type are extremely low.

Journal Pre-proof 4.2.3 Middle East – North Africa

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The dominant aerosol type at all ΜΕΝΑ stations is the coarse absorbing (Type VII, Fig. 14).

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Fig. 14. Heatmap with the percentages of aerosol type at every station in Middle East North Africa.

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The highest percentage of aerosol type VII (99.12%) is observed in TAM. Guirado et al. (2014) reported that Type VII is the dominated aerosols type at the dry-cool (autumn and

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winter) and wet-hot seasons (spring and summer). Moreover, it is concluded that the annual

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variability of AOD and AE is related to the convective boundary layer thermodynamic characteristics. Since TAM is not located in an urban/industrial area, the main aerosol

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composition is the mineral dust from Sahara desert. Stations located on the western side of MENA have percentages over 70% of type VII due to dust advections from Western Sahara. The only station of Western group where the percentage of type VII is below 70% is B LI (54.48%). The latter presents the highest percentage (29.85%) of mixed absorbing aerosols (Type V), as a result of the presence of fine and coarse absorbing aerosols at the same time. These well mixed aerosols (Type V) are observed mainly in summer due to pollutant outbreaks and burning biomass from urban and industrial areas in Europe (Pace et al., 2006). For the Eastern group of stations in MENA, coarse aerosols are still the dominant type with lower percentages. The megacity of Cairo (CAI), the capital of Egypt, is an exception. Coarse absorbing aerosols at CAI, NZA, SBK and EIL have percentages of 25.89, 50.22, 55.56 and

Journal Pre-proof 60.08% (Fig. 14) respectively due to mineral dust which comes from Sahara, Anatolian plateau and Negev deserts (Andreae et al., 2002; Basart et al., 2009; Derimian et al., 2006; Kubilay et al., 2003). In addition, Eastern Mediterranean contains aerosols due to human activity (El-Metwally et al., 2008; El-Metwally and Alfaro, 2013; Mallet et al., 2013) and the mixing of the dust with fine absorbing aerosols (Type I-III) leads to the increase of the percentage of aerosols type V. Particularly, Type V has ratios of 23.62, 22.07, 21.17 and 6.11% in CAI, EIL, SBK and NZA, due to well-mixed absorbing aerosols. As well as that, mixed

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non-absorbing aerosols (Type VI) exist mostly at NZA (8.73%) and SBK (3.56%). The percentages of fine absorbing particles in descending order are (Type I-III) 28.92, 4.37, 4.23

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and 2.52% (Fig. 14) at CAI, NZA, EIL and SBK, respectively.

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Obviously, Cairo is a main source of fine absorbing aerosols. El-Metwally et al. (2008)

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reported that aerosols in this region can be divided into three categories: firstly, black carbon by anthropogenic combustion activities, secondly, aerosols by biomass burning in the

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Nile-delta (less absorbing than black carbon), and, finally, mineral dust (discussed above).

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The implied classification method for CAI indicates the three above categories. The first

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category is related to the aerosols type I-II (11.22%). These types correspond to aerosols with high absorptivity (SSA = 0.86 ± 0.04, FMF = 0.77 ± 0.08, AE = 1.33 ± 0.09, Reff, fine = 0.15 ± 0.02 μm) such as black carbon and they are observed throughout the year with maximum values in spring. The second category is related to aerosol type III (17.70%). Fine slightly absorbing aerosols (SSA= 0.92 ± 0.01, FMF = 0.79 ± 0.09, AE = 1.36 ± 0.09, Reff, fine = 0.17 ± 0.03 μm) are reported throughout the year with higher values in summer and autumn. On the contrary, the only stations at western group who has percentage of fine particles (Types I-IV) above 4% are GRA (11.48%), BLI (5.23%) and MAL (4.83%) due to local and transported pollution from Central and Eastern Europe (Basart et al., 2009; Querol et al., 2004).

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Fig. 15. Scatter plot between AE440-870nm and SSA 440nm at (a) BLI, (b) NZA, (c) MAL, (d) EIL, (e) GRA, (f) SAD. The solid and dashed lines separate the aerosol type. The color bar represents the value of FMF500nm. The yellow circle indicates the Aerosol Type IX & X.

Fig. 16. Scatter plot between AE440-870nm and SSA440nm at (a) SBK, (b) TAM, (c) OUJ, (d) CAI, (e) TZO, (f) BSL. The solid and dashed lines separate the aerosol type. The color b ar represents the value of FMF500nm. The yellow circle indicates the Aerosol Type IX & X.

Journal Pre-proof It can be seen in Fig. 15 & 16 that all stations in Eastern group present higher dispersion than Western ones due different concentrations of fine aerosols. Additionally, the stations in Eastern group have appreciable percentages of Other aerosol types (IX & X).

4.2.4 South Europe The dominant aerosol type in South Europe shows is fine non-absorbing (Type IV, See Fig. 17) and fine absorbing (Type I-III, See Fig. 17) while some stations present high values of

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coarse absorbing aerosols (Type VII, See Fig. 17).

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Fig. 17. Heatmap with the percentages of aerosol type at every station in South Europe. In the Group B of South Europe, fine-mode particles are dominant because all stations are located nearby to industrial and urban air pollution sources (Basart et al., 2009). Types I-IV at CRP, MOD and TSL express the percentages of 73.02, 85.14 and 88.12%. Particularly, the prevailing type at most stations is the fine non-absorbing (Type IV). Specifically, TSL and MOD express percentages of 63.17 and 77.03% whereas in CRP the dominant aerosol type is the fine slightly absorbing (43.65%). The highest value of Type IV is reported in Modena (MOD), Northwest Italy, one of the most industrialized cities in Italy. Moreover, the highest value of fine particles is in TSL, which is connected with local urban and industrial sources, regional sources from Central and Eastern Europe and biomass burning from Black Sea,

Journal Pre-proof primarily in summer (Gerasopoulos et al., 2003; Kazadzis et al., 2007; Salisbury et al., 2003). Higher percentages of fine particles in TSL are observed in summer (91.76%) and autumn (96.22%): summer has 71.54% of type IV and 20.2% of type III whereas autumn has 56.60% of type IV and 38.68% of type II-III. In the Group A of South Europe, the dominant particle size, with smaller ratio, is fine particles. Particularly, at CTP, BRJ, RTV, IME, LCU and ATH the percentages of fine particles are 48.89, 50.00, 52.00, 63.44, 64.75 and 69.19%. Specifically, the prevailing type of CTP, BRJ, RTV, IME, LCU is fine non-absorbing (Type IV) whereas in ATH

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the dominant aerosols type is fine slightly absorbing (54.50%). ATH presents the lowest value of SSA (0.92 ± 0.03) in South Europe, indicating the high absorptivity of the station due

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to high fraction of fine absorbing (61.13%) and coarse absorbing (19.91%) aerosols. The

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influence of fine absorbing aerosols is significant during summertime (70.34%), due to

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atmospheric stability and absence of precipitation.

Other stations in the Group B have fine absorbing and non-absorbing aerosols. Specifically,

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at LCU, the percentage values of type IV and III are 44.29 and 23.74%, respectively; this site

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is mainly affected by pollutants transported from Central and Eastern Europe and Atlantic

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Ocean (Lelieveld et al., 2002). Moreover, fine absorbing aerosols from forest fires can also be very effective during summer (Perrone et al., 2005). RTV has percentages of type IV and III equal to 29.70 and 22.00%, respectively, In contrast with LCU, this site is mainly affected by local pollution (Basart et al., 2009). At BRJ, 30.30 and 18.18% of aerosols are classified as type IV and III respectively. Segura et al. (2017) reported that the location of the site (5km northwest of urban city of Valencia) has a significant impact on the contribution of fine particles due to urban and industrial activities and biomass burning. At IME and CTP stations, 41.01 and 35.56% of aerosols are classified as type IV and 21.66 and 13.33% as type III. Fine mode particles at these sites appear mainly by local pollution as well as by transport of pollutants from Central and Eastern Europe, Southeastern Europe and Eastern group of MENA. Besides the high contribution of fine particles, this group of stations reveals

Journal Pre-proof significant percentages of coarse absorbing aerosols (type VII): RTV, CTP, BRJ, LCU, ATH and IME present percentages of 37.00, 35.56, 34.09, 22.83, 19.91 and 12.57% of type VII. High fractions of coarse absorbing aerosols are observed in RTV and LCU, influenced by Saharan dust (Basart et al., 2009). CTP and IME include coarse absorbing aerosols which are coming from deserts in Anatolian Plateau, Arabian Peninsula and North African (Andreae et al., 2002; Basart et al., 2009; Derimian et al., 2006; Kubilay et al., 2003). This is closely related to dust outbreaks from Saharan desert and nearby deserts. At BRJ,

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dust from Saharan desert is observed mainly in winter (Type VII ~37.50%) and summer (Type VII ~40.28%) whereas in ATH these events occur strongly in spring (Type VII~46.15%)

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(Kaskaoutis et al., 2012). It can be seen in Fig. 15 & 19 that all stations in Group A present

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higher dispersion than Group B ones due to appearance of coarse absorbing aerosols.

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Considering the Other aerosol type, all stations in South-Europe reveal relatively lower

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percentages (3.65-10.84%) than MENA.

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Fig. 18. Scatter plot between AE440-870nm and SSA440nm at (a) ATH, (b) BRJ, (c) CRP, (d) IME, (e) LCU. The solid and dashed lines separate the aerosol type. The color bar represents the value of FMF500nm. The yellow circle indicates the Aerosol Type IX & X.

Fig. 19. Scatter plot between AE440-870nm and SSA 440nm at (a) MOD, (b) RTV, (c) TSL, (d) CTP. The solid and dashed lines separate the aerosol type. The color bar represent the value of FMF500nm. The yellow circle indicates the Aerosol Type IX & X.

Journal Pre-proof 4.2.5 Central and East Europe In Central and East Europe, fine-mode aerosols are dominant. Specifically, the dominant

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aerosol type for all stations in this region is fine non-absorbing (Type IV, See Fig. 18).

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Fig. 18. Heatmap with the percentages of aerosol type at every station in Central and East Europe. Particularly, sites at LIL (65.35%), LEI (64.38%), KYV (58.25%), BEL (56.19%), BCI (53.28%),

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MIN (52.04%) and BRU (50.72%) reveal percentages of type IV higher than 50% whereas

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sites at CLB (46.58%), SEV (45.75%) and MLD (42.31%) are lower. These ratios of type IV are in accordance with previous studies which classify this region as a source of urban-industrial

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aerosols (Dubovik et al., 2002; D. M. Giles et al., 2012; Hamill et al., 2016; Lee et al., 2010) . For all stations, the second aerosol type is fine slightly absorbing (type III). Lee et al. 2010 reports that the dominant aerosol type in Europe is fine absorbing (black carbon) followed by fine non-absorbing. Our study shows that in Central and Eastern Europe fine non-absorbing aerosols are followed by fine absorbing. The only exception is MLD that has 53.41% of fine absorbing particles (Type I-III). The seasonal analysis reveals that the percentage of aerosol type IV is increased in summer and autumn while the dominant aerosol type differs among the stations in spring. Coarse absorbing aerosols are also observed in this season at many stations. Similarly, the prevailing of fine-mode particles among the stations can be easily

Journal Pre-proof observed in Fig. 19 & 22. At all stations of Central and East Europe, the Other aerosol type is

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appeared with percentages up to 11.6%.

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Fig. 19. Scatter plot between AE440-870nm and SSA440nm (a) SEV, (b) BCI, (c) BEL, (d) BRU, (e) KYV. The solid and dashed lines separate the aerosol type. The color bar represents the value of FMF500nm. The yellow circle indicates the Aerosol Type IX & X.

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5. Conclusions

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Fig. 20. Scatter plot between AE440-870nm and SSA 440nm at (a) LEI, (b) LIL, (c) MIN, (d) MLD, (e) CLB. The solid and dashed lines separate the aerosol type. The color bar represents the value of FMF500nm. The yellow circle indicates the Aerosol Type IX & X.

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A comprehensive study of the aerosol classification using Level 2.0 retrievals from AERONET

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V3 is performed for 39 stations in Atlantic, Arabian Peninsula, MENA, South Europe and Central and East Europe between 2008-2017. Specifically, a classification method is applied with the addition of 2 new aerosol types (other absorbing IX, other non-absorbing X). Coarse absorbing aerosols (Type VII, SSA~ 0.89-0.93, FMF~ 0.27-0.41) are dominant at sites located in the Arabian Peninsula. Moreover, the local and/or regional pollution leads to increase of mixed absorbing aerosols (Type V) at many stations. As in Arabian Peninsula, coarse absorbing aerosols (Type VII, SSA~ 0.90-0.92, FMF~ 0.22-0.24) are dominant in the Atlantic due to dust transport from the African desert areas. However, fine-mode particles are not observed in the region of Atlantic. Contrary to previous regions, in MENA, the magnitude of coarse absorbing aerosols depends on the location. The Eastern group (Type VII, SSA~ 0.890.94, FMF~ 0.37-0.57) presents lower percentages of coarse absorbing aerosols. Cairo (CAI),

Journal Pre-proof has 25.89% of Type VII and 23.52% of Type V and this is a result of heavy urban pollution. The Western group (Type VII, SSA~ 0.89-0.91, FMF~ 0.21-0.41) has higher percentages of coarse absorbing particles due to dust advections from Western Sahara with the exception of BLI station, where fine absorbing particles are also revealed. Differing from the previous regions, in South Europe, the dominant aerosol type is fine absorbing and non-absorbing particles (Types I-IV). The main difference among the previous regions is the bimodal aerosol size distribution in many stations. For all stations in Group A of South Europe, the prevailing

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aerosol type is fine non-absorbing (IV) with only exception the station in Athens (ATH, type III). This group of stations provides also high ratios of coarse absorbing aerosols (Type VII)

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due to Saharan dust outbreaks. In the Group B South Europe, lower ratios of coarse

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absorbing aerosols (Type VII, SSA~ 0.93-0.97, FMF~ 0.72-0.94) are revealed, as a result of the

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very high percentages of fine particles (73.02-88.12%). Finally, the dominant aerosol type across Central and East Europe is fine non-absorbing (Type IV).

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This study aims to provide important information about the aerosol type in the above-

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mentioned regions for better assessment of regional climate and local air pollution studies.

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Such an aerosol classification could be used for the validation and improved performance of chemical transport models and satellite remote sensing algorithms. As a future step, the proposed classification will be also used to better assess of aerosol effect in radiative balance.

Acknowledgements We acknowledge support of this work by the project “PANhellenic infrastructure for Atmospheric Composition and climatE change” (MIS 5021516) which is implemented under the Action “Reinforcement of the Research and Innovation Infrastructure”, funded by the Operational Programme "Competitiveness, Entrepreneurship and Innovation" (NSRF 20142020) and co-financed by Greece and the European Union (European Regional Development

Journal Pre-proof Fund). We gratefully acknowledge the data provided by AERONET network and we wish to express our appreciation to the operators of stations for thei r efforts on running the instruments.

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