Elsevier

Atmospheric Environment

Volume 265, 15 November 2021, 118716
Atmospheric Environment

Classification of aerosol types using AERONET version 3 data over Kuwait City

https://doi.org/10.1016/j.atmosenv.2021.118716Get rights and content

Highlights

  • Atmospheric particles of Kuwait City are classified using the PLDR and SSA parameters.

  • Pure and polluted dust plumes make up the predominant contribution of Kuwait aerosols.

  • The incidence rate of pure and polluted dust is more than 85% from March to October.

  • The annual average incidence rate of dust-free pollution aerosols is 15%.

Abstract

The particle linear depolarization ratio (PLDR) and single scattering albedo (SSA) at 1020 nm are retrieved by the AERONET (Aerosol Robotic Network) Version 3.0 level 1.5 inversion products are used to categorize different types of aerosols and investigate their temporal distribution for the atmospheric particles of Kuwait City. The results show that when PLDR increases in the atmosphere, the amount of SSA at 440, 670, 870, and 1020 nm wavelength channels and the contribution of coarse-mode particles increased. Also, the spectral behavior of SSA changes from a negative to positive slope by increasing PLDR. The highest density of aerosol incidence rate in the two-dimensional histogram diagram occurs in the range with low fine mode fraction and dust ratio. The main objective of this study is to present that the atmosphere of Kuwait City is strongly affected by pure dust (PD) and polluted dust plumes, namely, dust-dominated mixture (DDM), pollution dominated mixture (PDM), all with an occurrence frequency of 85%. The annual average incidence rate of different aerosol types is 32.2% for DDM, 31% for PD, 21.8% for PDM, 10.3% for SA, 2.5% for MA, 1.3% for WA, and 0.9% for NA, from 2006 to 2019. However, the distribution of different types of pollution particles varies with the seasons change. The incidence rate of pure and polluted dust is more than 85% from March to October. In addition, the annual average incidence rate of dust-free pollution aerosols (NA, WA, MA, and SA) is 15%. The highest amount of dust-free pollution particles in different months is related to the SA that constitutes about 40% in the cold months.

Introduction

Atmospheric aerosol particles affect the climate system by changing the radiative forcing of the earth's radiation budget via direct and indirect mechanisms (García et al., 2012; IPCC, 2013; Stocker et al., 2014). Aerosols scatter and absorb solar and thermal radiations and alter cloud properties in different ways (i.e., cloud albedo, cloud lifetime) (Twomey, 1974). They have short lifetimes, and their production sources are diverse and heterogeneous (Satheesh and Krishna Moorthy, 2005). Aerosols are one of the important sources of the uncertainty in calculating the atmospheric radiative forcing (Bellouin et al., 2013; Stocker et al., 2014). To reduce the error, it is necessary to study the aerosols in both earth and space continuously and to classify aerosols of different regions based on their physical and chemical properties (Eck et al., 1999, 2010; Dubovik et al., 2002; Satheesh and Srinivasan, 2006; Giles et al., 2012).

According to the properties inferred from the remote sensing measurement, several methods are used for the classification of different types of atmospheric particles (Schuster et al., 2006; Kim et al., 2007; Tesche et al., 2009; Lee et al., 2010; Giles et al., 2012). The AERONET (AErosol RObotic NETwork) is an automated network of ground-based remote sensing instruments to measure solar and celestial radiance that provides data on particle microphysical and optical characteristics (Holben et al., 1998). The parameters extracted from the AERONET database that are commonly used to classify various types of aerosols are aerosol optical depth (AOD), Angstrom exponent (AE), single scattering albedo (SSA), and fine mode fraction (FMF) (Lee et al., 2010; Giles et al., 2012; Zheng et al., 2017; Logothetis et al., 2020). AERONET introduces the particle linear depolarization ratio (δp or PLDR) parameter in the version 3 (V3) dataset as a standard product in different wavelength channels. PLDR is sensitive to the atmospheric particle shape (Cairo et al., 1999; Iwasaka et al., 2003; Noh et al., 2007, 2008, 2008; Tesche et al., 2009; Shimizu et al., 2016). Also, it is a useful parameter for separating nonspherical particles from spherical types in a mixture of various aerosol types. PLDR value for different aerosols varies around zero to 0.35. The PLDR values of nonspherical particles such as pure dust vary from 0.30 to 0.35 (Bohren and Huffman, 2008; Freudenthaler et al., 2009; Tesche et al., 2009; Burton et al., 2012, 2014, 2015; Shin et al., 2015, 2019). When dust is mixed with pollution particles, the PLDR value decreases. PLDR for spherical particles (urban and industrial pollutants) is close to zero (Shin et al., 2015). Shin et al. (2019) proposed to use the PLDR parameter to determine the predominant type of aerosols and suggested a PLDR threshold for separating spherical from nonspherical particles. The suggested method categorizes the atmospheric particles into four types: dust, dust-dominated mixture, pollution-dominated mixture, and pollution. The pollution is separated into four subtypes depending on particle absorptivity: the strongly absorbing (SA), moderately absorbing (MA), weakly absorbing (WA), and non-absorbing (NA).

In a preliminary study, Wilderson (1991) used satellite data to classify different types of dust storms for the Iraq and Kuwait regions into three categories (pre-frontal, post-frontal, and Shamal types). The Shamal type is a northwest wind that usually happens in summer. After installing a large number of the AERONET sun-photometers (about 20) around 1998 in the Persian Gulf countries and Saudi Arabia, it became possible to quantitatively study the optical and microphysical properties of mineral dust in this region. Smirnov et al. (2002) used one-year measurements between July 1998 and July 1999 to investigate the optical properties of atmospheric particles at the Bahrain site in the Persian Gulf. Kim et al. (2011) studied the seasonal behavior of the optical properties of mineral dust in North Africa and the Arabian Peninsula using AERONET data. Their results showed that the absorption of the Arabian Peninsula dust is higher than the Saharan dust in the short wavelength channels. Masoumi et al. (2019) showed that dust is the primary type of aerosol in the Kuwait atmosphere, especially in the dry months of the year, from March to October. Kuwait dust events also originate mainly from the North Arabian Peninsula in March and April, from the Tigris-Euphrates basin through the Shamal wind in June and July, and from both sources in May. Logothetis et al. (2020) classified various types of aerosols of 39 sites of AERONET by using direct sun products such as SSA, FMF, and AE. Their results show that the dominant percentage of Kuwait aerosols are 86.15% of coarse absorbing particles (soil dust) and 5.76% of mixed absorbing particles.

The main objective of this study is to classify the various types of aerosols in Kuwait City using the PLDR (shape-dependent) and SSA parameters obtained from the AERONET V3 dataset for the measurement period from 2006 to 2019. Also, we are going to investigate the monthly and annual incidence frequency of aerosol types for the mentioned period. The results are effective in improving chemical transport modeling and calibration of satellite measurements. The rest of the manuscript is prepared as follows: in section 2, the data and methodology are explained. The results are discussed in section 3, and the conclusion is presented in the last section of the article.

Section snippets

Site description

Kuwait is situated in the Middle East, and the northern hemisphere dust belt (Prospero et al., 2002). It is located in the Arabian Peninsula at the Persian Gulf's tip and is bordered by Iraq and Saudi Arabia. Its atmosphere is influenced by dust storms that originate from natural resources located in the Tigris-Euphrates Basin, northeastern Saudi Arabia, and southern Iran (Prospero et al., 2002; Achilleos et al., 2019; Logothetis et al., 2020). The dominant aerosols of Kuwait's atmosphere are

Aerosol optical depth and Angstrom exponent

To extract more information about aerosols of the site, AOD and AE have been investigated through sun-photometer measurements for 1650 days from 2006 up to 2019. The average value of daily AOD at 440 nm in the measurement period is almost high (0.46) due to the addition of dust to urban-industrial pollution in the atmosphere. The results coincidence with Kokkalis et al. (2018) study. Also, Fig. 1 (a) (Fig. 1 (b)) shows that the monthly average value of AOD (AE) increases (decreases) sharply

Conclusion

In this work, we use PLDR and SSA at 1020 nm obtained from AERONET V3 level 1.5 inversion products to classify different aerosol types in mixed aerosol plumes. Also, their temporal distribution is investigated at the Kuwait university site between 2006 and 2019. The results show that with increasing PLDR: (a) the values of AE decrease, (b) the amount of SSA in each wavelength channel increases, (c) the spectral behavior of SSA changes from negative to positive slope, (d) the contribution of

CRediT authorship contribution statement

Faeze Khademi: Methodology, Software, Validation, Investigation, Data curation, Writing – original draft, Visualization. Ali Bayat: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Data curation, Writing – review & editing, Visualization, Supervision.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgement

We thank the principal investigators and their staff for establishing and maintaining the AERONET Kuwait university site used in this investigation. The authors are also grateful to Hamed Douroudgari and Hamid Reza Khalesifard for their valuable discussions and comments on the manuscript. The authors are also grateful to the referees for their valuable comments and suggestions to help the manuscript improve.

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