Deserts can be considered as one of the main sources of dust emissions as they are highly vulnerable to wind erosion , i.e. T he lack of vegetative cover , as well as low soil wetness, contribute to the release of particle s by wind erosion . The present study examines the seasonal variation in sand and dust storms (SDSs) origina ting from war -impacted semi -arid bare lands affected by chemical warfare located in southwest Iran for the period of 2007 - 2018 . It employs a synthesis of satellite observations and Hybrid Single -Particle Lagrangian Integrated Trajectory ( HYSPLIT ) model trajectories. A regression analysis between annual /seasonal absorbing aerosol index distribution and selected parameters indicated strong correlation with surface skin temperature, topsoil layer wetness, and 10 -m wind speed . During both cold and warm periods, Kuwait and the Persian Gulf were highly vulnerable to episodic dust incursions as they were identified in the maximum impact zone (frequency of 100%). The Persian Gulf was affected by about 12% of the total air masses during the warm period , which increas ed to 74% during the cold period. Regarding the vulnerability to the high wind of war -impacted region s presumably contaminated with potentially toxic elements (PTEs) and toxic compounds , the particles of contaminated dust may have been continuously transported over by the strong winds , not only the surrounding region but also long distances including agricu ltural land and marine environment. The study area would possibly pose a danger to the environment and human health; therefore, a detailed site characterization to investigate the degree of contamination with PTEs and toxic compounds is warranted . Keywords : Absorbing aerosol index (AAI); Air pollution modelling; Particulate matter; Sand and dust storms (SDS) ; The Persian Gulf Journal Pre-proof Journal Pre-proof 3 1. Introduction Regional and long-range transportation of mineral dust is an essential component of the atmospheric circulation. It is caused by wind erosion and transported from a local scale to a global scale by air systems. Sand and dust storms (SDS s), which are the significant sources of airborne dust, are recognized as common phenomena originating from global deserts , and they cause serious adverse human health, climat e, environmental, and economic impacts (Ginoux, et al., 2012; Goudie, 2014) . Accordingly , research on sand and dust cycle s and routes are needed for specific issues concerning human health, weather, climate change, ecosystems, and air quality. The primary SDS origins over the globe are located around arid regions , which are typically found on alluvial sedimentation basins at lower elevations with annual precipitation <200 m m, and with limited vegetation cover (Ginoux et al., 2012; Prospero et al., 2002) . The most generative areas are detected in the north of Aral and Turkmenistan basins, the southern and eastern parts of Arabian Peninsula, the Syria -Iraqi desert, the Oman desert, and some closed inland areas of the Iranian plateau ( such as Sistan Basin , Hamoun Jaz -Mourian Lake, Kavir and Lut deserts). The Middle East region and the Arabian Peninsula are responsible for releasing significant amounts of dust mainly transported over the Arabian Sea with substantial intensity from June to August (Prijith et al., 2013) . Previous studies also showed that about 65% of the southwest Asian arid terrain has the potential to become a dust origin (Ginoux et al., 2012; Prospero et al., 2002) . Although the Thar, Iraqi , and Arabian deserts are primary dust origins in South Asia, a small area (Sista n basin ) with dried lakes (Hamoun) at the Iran -Afghanistan borders may also have a significant role (Karimi et al., 2012; Maghrabi et al., 2011; Prospero et al., 2002; Rashki et al., 2015, 2013) . Furthermore, researchers showed the southwest Iran (Khuzestan Province) turning into one of the significant sand and Journal Pre-proof Journal Pre-proof 4 dust source s in the region (Broomandi et al., 2018, 2017a; Cao et al., 2015; Esmaili et al., 2006; Salmabadi et al., 2020) . Excessive dust loading over South Asia impact s the regional environment (terrestrial and marine) as well as the climat e. It can easily alter the radiative forcing of the atmosphere and the biogeochemical cycles. Dust plumes can impact weather by affecting the hydrological cycle and cloud microphysics (Dipu et al., 2013) , and influenc e the atmospheric thermal structure by suppressing cyclone activity (Dunion and Velden, 2002; Lemaitre et al., 2010) . Studies also confirmed the impact of dust originating from southwest Asia and the Middle East on the acceleration of western H imalayas glacier melting (Prasad et al., 2009) . Jickells et al. (2005) estimated the amount of global dust deposition to the oceans be about 450 Tg .a-1, among which about 21% settles into the Pacific Ocean, 25% into the Indian Ocean and 47% settles into the Atlantic Ocean (Jickells et al., 2005; Wang et al., 2017) . By adding dissolved iron (Fe) to marin e ecosystem s, deposited d ust aerosols can impact marine productivity (Kessler et al., 2019; Ueda et al., 2020; Wang et al., 2017) . The amount of absorbed CO 2 by oceans can be altered by dissolved iron , which indirectly cause s climate change. As a result, climate change can affect dust origin, emission fluxes, transport , and deposition processes. Worldwide, i n most marine environments , dust aerosols (coming from major deserts) are responsible for the Fe input to the ocean surface (Kessler et al., 2019; Wang et al., 2017) . Desert dust is a complex matrix of minerals, with variable structure, size, and Fe content. Beside Fe content, multiple factors control the rate of Fe release from dust minerals such as weathering degree, mineral structure, size, and occurring reactions during transport ( in the atmosphere ) and deposition (in the ocean microlayer ) (Kessler et al., 2019) . Fe is an essential nutrient element for all living organisms and act s as a limiting factor in the growth of marine plankton (Wang et al., 2017) . Journal Pre-proof Journal Pre-proof 5 Also, Rashki et al. (2015) pointed out some supporting evidence that the Sistan dust storms influence some parts of the Arabian Sea, controlling the aerosol optical depth evolution over the marine environment. Dust deposition over the Arabian Sea can cool the ocean surface, influence the phytoplankton, and affect the chlorophyll bloo ming (Rashki et al., 2015; Singh et al., 2008) . Likewise , mineral dust has been suspected to be one of the most critical health risk factors for pulmonary dise ases including asthma and allergies in young as well as older adults and contributes to meningitis in Sistan province of Iran (Goudarzi et al., 2018; Merrifield et al., 2013; Miri et al., 2007; Mohammadi et al., 2015; Naimabadi et al., 2016) and in West Africa (Martiny and Chiapello, 2013) . While fossil fuel combustion, traffic emission s, upwind petroleum industry, and gas and oil drilling activities are the primary contributing anthropogenic sources in the Middle East, the war remains can be added to the list for southwest Iran, Iraq, and Syria . There exist some previous studies examining the SDS storms originating from southwest Iran (Shalamcheh region, (30° 45’N and 48° 15’E )), which is a war -impacted SDS source area (Broomandi et al., 2018, 2017a) . One of the critical anthropogenic origins of enriched trace elements in this area attributed to the remains of the Iraq-Iran war (Broomandi, et al., 2017) . For example, the high level s of Cl and S in this area were attributed to the use of mustard gas in Iraq - Iran war during 1980 –1988 , and Br, Mo, Zn, and Hg were other highly enriched trace elements detected in this war -impacted area (Broomandi et al., 2017a) . The presence of Pb, Cu, Hg, Br, Mo , and Zn in contaminated soils has previously been attributed to war activities (Wallace, 2018) . Due to a higher level of health risk exposure, The Hg contamination i n the Shalamcheh region represent s a significant concern as it could be washed out by atmospheric precipitation , potentially leading to regional underground water contamina tion (Broomandi et al., 2017a; Wallace, 2018) . A long-term analysis of the occurrence of dust storms still lacks over southwest Asia, including the Shalamcheh region, due to the limitation s of satellite imagery at the regional Journal Pre-proof Journal Pre-proof 6 scale (Rashki et al., 2015) . The identification of SDS pathways and origins uses specific techniques including satellite remote sensing, ground -based observations, trajectory analysis, and integrated approaches (Ashrafi et al., 2014; Broomandi et al., 2018; Rashki et al., 2015; Shao et al., 2011; Sorek -Hamer et al., 2013) and it i s a significant challenge to perf orm in some area s of the Middle East due to certain limitations including the reliability and availability of data . Recently, the development of Global Dust Detection Index (GDDI) model (Karimi et al., 2012) and the new Middle East Dust Index (MEDI) had a significant contribution in the identification of SDS sources in the Middle East (Samadi et al., 2014) . The employment of the satellite images for monitor ing SDS events is an appropriate method that is time -saving and cost -effective ; however , some ground sensors with systematic xerography are needed in continuous monitoring of the surfaces covered by dust during storms (Ekhtesasi and Gohari, 2012) . To the best of our knowledge, there exists no study examining the common dust transport pathways and impact zones over the region originated by the Shalamcheh during SDS events. The current research aims to assess the seasonal formation (during the cold and warm periods) and the prevalence of SDS s originated from southwest Iran (Shalamcheh region) under specific metrological conditions (e.g. , wind speeds >20 knots (kn, 1 kn = 1.852 km.h-1), horizontal visibility <1000 m) during 2007 -2018. By providing quantitative measures, it aims to conclude whether the region can be listed among potential glob al source s of SDS and further assesses the long-range transport pathways and possible deposition and exposure concentration impact s of identified SDSs over the area by identifying its impact zones . 2. Material and Methods Journal Pre-proof Journal Pre-proof 7 2.1. Study area The study area, Shalamcheh, is in southwest Iran in Khuzestan province (30° 45’ N and 48° 15’ E) (Figure 1) . The area is bare land that has been affected by chemical warfare , mainly mustard gas , during the Iraq-Iran War between 1980 and 1988 (Broomandi et al., 2017a) . There are two seasons in the region; t he warm period is from April to September, and the cold period is from October to March. During warm and cold periods, the average received rainfall values were 17.5 ± 1.9 mm and 130.2 ± 60.6 mm ; the average maximum temperature values were 46.1 ± 1.1 °C and 30.3 ± 1.1 °C, and t he average relative humidity values were 32.5 ± 4.8 %, and 62.0 ± 4.6 % , respectively (Broomandi et al., 2017a) . Journal Pre-proof Journal Pre-proof 8 Figure 1. Location of study area, Shalamcheh, situated in Khuzestan Province of Southwest Iran. The solid red star indicates the study area ( Shalamcheh) . The solid red triangle represents the location of the Abadan and Khorramshahr meteorological station (ABKH). 2.2. Satellite data , trajectory, and dispersion mode lling Ozone Monitoring Instrument (OMI) absorbing aerosol index (AAI) database (http://giovanni.sci.gsfc.nasa.gov ) was used (a) to evaluate the regional aerosol loads in the atmosphere and (b) to investigate the role of surface skin temperature and topsoil layer moisture in dust generation mechanism during 12 years ( between 2007 and 2018). Monthly averaged AAI values at the spatial resolution of 1° × 1°, daily surface skin temperature (the mean temperature of earth’s surf ace) at the spatial resolution of 0.25° × 0.25°, and topsoil layer moisture s ( the averaged value of water content in depth of 0 -10 cm underground) at the spatial resolution of 0.5° × 0.625° were used. All meteorological parameters including wind speed and horizontal visibility were daily averaged (24 hour based measurements) and taken from Abadan and Khoramshahr metrological station (3 0°.21′N, 48°. 13′E), which is the nearest station to the Shalamcheh (Ahvaz IRIMO, 2016) . The Hybrid Single -Particle Lagrangian Integrated Trajectory ( HYSPLIT ) model is for trajectory, dispersion, and depositio n calculations employing the Global Forecast System (GFS) meteorological forecast parameters of the Global Data Assimilation System (GDAS) as its initial background field . Using particle or puff approaches, it calculates trajectories as well as dispersion and deposition simulations (Ashrafi et al., 2014; Lu et al., 2018) . The trajectory computation in any Lagrangian model is based on the meteorological data (U, V, and W) , which has been interpolat ed to the grids of the model. Journal Pre-proof Journal Pre-proof 9 The t rajectory simulation s in the present study were forward s and backwards moving from and to the dust source (30° 45’ N and 48° 15’ E). They were run based on episodic events as suggested by de Villiers and van Heerden (2011) where a storm is classified either as sand and dust storm (e.g. 10 -m wind speed >20 kn with visibility <1000 m) or severe sand and dust storm (e.g., the 10 -m wind speed >30 k n with visibility <200 meters). The trajectories started at the height of one half of the mixed boundary layer . The h eight of mixing boundary layer and its mid -level were calculated by the HYSPLIT model and could be automatically selected using the method options (Draxler and Hess, 1997) . Table 1 summarizes the monthly frequency of the identified sand and dust storm s during the study period . 3. Results and Discussion 3.1. Sand and dust storm & severe sand and dust storm occurrences in Shalamcheh The mean values for OMI AAI data were calculated from the daily absorbing aerosol index records for the study area . Typically, AAI values are ranging from a minimum of 0 to a maximum of 40 where higher numbers (e.g. >20) may indicate episodic atmospheric aerosol loads from dust storm s or smoke emissions during the satellite scans . The daily average concentrations of absorbing aerosols are high during the warm perio d and especially in May, June, and July (with the highest value 27 in June); they can be attributed to mineral dust origins since no significant anthropogenic dust genera tion mechanisms are available in the region during the summertime . The average AAI as dust activity indicator during four months (April to July) was >20 which is close to the dust activities of primary global dust sources in the Middle East region (Arabia (southern Oman/Saudi border) with AAI values >21 and Journal Pre-proof Journal Pre-proof 10 average annual rainfall <100 mm (Goudie and Middleton, 2006; Shepherd et al., 2016) . There is much less dust activity in th e study area (especially in January) during the cold period. In addition to AAI data, wind and visibility data from ground -level measurements were also screened using the criteri on 10-m wind speed >20 kn, and all the potential events have been identified. The wi nd speeds are generally high during the warm period, especially in May, June, and July. Finally, sand and dust storm & sever e sand and dust storm occasions were verified by comparing the identified events with the matching daily AAI data . Table 1 summari zes the monthly frequenc ies of the storms for the study region . The total number of the sand and dust storms (sever e sand and dust storms ) were 79 (13) in total (61 (8) episodes during the warm period, and 18 (and 5) episodes during the cold period ). The highest prevalence values were recorded monthly in June (22 sand and dust storms and three severe sand and dust storms), and yearly in 2013 (17 sand and dust storms) and 2018 ( three sever e sand and dust storms). Apart from the surface wind speed, other parameters are also affecting the occurrence of sand and dust storms . For example, the topsoil layer wetness is an essential factor in sand and dust emission potential, and it can be characterized by a combination of topsoil layer wetness and surface skin temperature using satellite data . It is well associated with soil texture and aggregate stability, aggregates size distribution, and soil organic matter content ; it increases the strength of inter -particle bonds by develop ing a sticky film between particles (Aimar et al., 2012; Broomandi et al., 2017a; Liu et al., 2012) . The topsoil layer wetness has high variability both in temporal and spatial scale s. The wind emission prevails by the real wetness of the first top -centimeters of soil layer (Aimar et al., 2012) . The topsoil layer wetness and surface skin temperature from OMI have been studied to evaluate the impact o f the topsoil layer wetness on the dust generation mechanism . The daily averages of the surface skin temperature experienced a considerable increase during the Journal Pre-proof Journal Pre-proof 11 warm period , particularly in June, July, and August (with the highest value of 317.7 °K in July). The topsoil layer wetness had a notable reduction during the warm period , particularly from June to September (with the minimum value of 2 in September ). The study on the changes in topsoil wetness and surface skin temperature showed that the minimum value of wetness and maximum value of surface skin temperature were not recorded in June , whereas the highest wind speeds were experienced in June, confirming the critical role of 10 -m wind speed in generati ng sand and dust storms. Table 1. Monthly prevalence of dust storms (10 -m wind speed >20 knots (kn)) and severe dust storms (10 -m wind speed >30 kn) in the study area between 2007 -2018 (“ number of severe sand and dust storms ” (in bold)/“ number of sand and dust storms .” Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2007 --- --- --- --- --- 1 1 --- --- --- --- --- 2008 --- --- --- --- 2 1/3 1 --- 1 --- --- --- 2009 --- --- --- --- --- --- --- 2 --- --- --- --- 2010 --- --- --- 1/1 --- 1 1/2 --- --- --- --- --- 2011 --- --- 1 2 3 1/1 --- 1 --- --- 1 --- 2012 --- --- 2 --- --- 3 --- --- --- --- --- 1/2 2013 --- --- --- 2 2 8 1 --- --- 1 2 1 2014 --- --- 1 1 --- 2 --- --- --- --- --- --- 2015 --- 2/2 --- 1 --- 1 3 --- --- --- --- --- 2016 --- --- --- --- 1 --- 1 1 1/2 1/1 1 --- 2017 --- --- --- --- 1/2 1 --- --- --- --- 1 --- 2018 1/1 --- --- 1/3 --- 1/1 3 --- 1 --- --- 1 A regression analysis was applied to the retrieved data from satellite and ground - based measurements (Figure s 2 & 3 ). The regression analysis between annual & seasonal AAI distribution and surface skin temperature indicated a strong positive correlation, whereas a strong negative correlation was present between topsoil layer wetness and annual & seasonal AAI distribution. In June 2013 (the year with the highest annual occurrence of sand Journal Pre-proof Journal Pre-proof 12 and dust storms), the number of sand and dust storms reached its highest value (22). Finally, a strong correlation was also present between annual & seasonal AAI distribution and 10 -m wind spee d. The regression results show a lower tendency for dust emission following an increase in topsoil layer wetness and decrease in 10 -m wind speed and surface skin temperature . These results are in good agreement with the literature (Almazroui et al., 2012; Namdari et al., 2018; Shafiee et al., 2016a, 2016b; Singh and Oh, 2007) . Previous studies indicated t hat any increase in ambient air temperature causes a reduction in relative humidity, leading to a decrease in threshold wind speed to initiate dust emissions . Since previous studies confirm ed that rainfall and temperature are two meteorological parameters which indirectly change the threshold friction velocity and directly determine topsoil layer wetness , further investigation of multivariable regression analysis by applying more parameters (temperature, rainfall, relative humidity) is recommended. Journal Pre-proof Journal Pre-proof 13 Figure 2. The regression analysis ( p <0.001) between annual AAI & topsoil layer wetness (a), surface skin temperature ( b), and 10 -m wind speed ( c) between 2007 and 2018 in the study area, Shalamcheh, located in Khuzestan province, southwest Iran. y = -30.452x + 19.137 R² = 0.56 Correlation R value= -0.74 11121314151617 0.06 0.08 0.1 0.12 0.14 0.16 0.18 0.2 0.22AAI×10-1 Topsoil layer Wetness y = 1.0998x - 314.99 R² = 0.68 Correlation R value= 0.80 11121314151617 290 292 294 296 298 300 302 304AAI×10-1 Surface skin Temperature ( °K) b y = 1.1174x + 2.1953 R² = 0.55 Correlation Rvalue= 0.70 89101112131415161718 6 8 10 12 14AAI×10-1 Wind Speed (Knots) c a Journal Pre-proof Journal Pre-proof 14 y = -18.178x + 14.669 R² = 0.62 Correlation R value= -0.80 89101112131415 0.06 0.16 0.26 0.36AAI×10-1 Topsoil layer Wetness Cold period b y = -53.034x + 23.36 R² = 0.49 Correlation R value= -0.70 1516171819202122 0.06 0.08 0.1 0.12 0.14AAI×10-1 Topsoil layer Wetness Warm period a y = 1.281x - 361.96 R² = 0.60 Correlation R value=0.77 891011121314 288 289 290 291 292 293AAI×10-1 Surface skin Temperature ( °K) Cold period d y = 1.017x - 295.27 R² = 0.61 Correlation R value=0.78 141516171819202122 304 306 308 310 312AAI×10-1 Surface skin Temperature ( °K) Warm period c y = 1.2846x + 1.3673 R² = 0.54 Correlation R value= 0.74 1516171819202122 10 11 12 13 14 15AAI×10-1 Wind Speed (Knots) Warm period e Journal Pre-proof Journal Pre-proof 15 Figure 3. The regression analysis (p <0.001) between AAI & topsoil layer wetness (a & b), surface skin temperature (c & d), and 10 -m wind speed (e & f) during warm and cold periods between 2007 and 2018 in area of study, Shalamcheh, located in Khuzestan province, southwest Iran. 3.2. Trajectory analysis in combination with AAI, topsoil layer wetness , and surface skin temperature data The trajectory analysis was employed as a tool to assess the regional and long -range travel of the air parcels over the region for the identified events and episodes ( numbers given in Table 1). Figures 4 & 5 present typical examples of the combined backward and forward trajectories of dust particles arriving and leaving the study area in combination with AAI, topsoil layer wetness , and surface skin temperature during the severe SDS events ( 10-m wind speed >30 kn) during the warm and cold periods. Backward trajectory analysis showed that air particles are loaded with dust particles from the central parts of Iraq before reaching Shalamcheh. However, the a ir parcels were further loaded while passing over th e study area and deposited their load toward the Persian Gulf, Saudi Arabia, Yemen, and Arabian Sea (e.g. Figure 4a on 07/06/2008) . During the cold period, air particles were also loaded with dust particles passing some parts of the y = 0.725x + 4.4487 R² = 0.40 Correlation R value= 0.63 1011121314151617 6 8 10 12 14AAI×10-1 Wind Speed (Knots) Cold period f y = 1.2846x + 1.3673 R² = 0.54 1516171819202122 10 11 12 13 14 15AAI×10-1 Wind Speed (Knots) Warm period e Journal Pre-proof Journal Pre-proof 16 Saudi Arabia border before reaching the study area (e.g., see Figure 5 on 02/10/2016 ). They continue d their path toward central parts of Iran and then towards Central Asia after being further loaded over Shalamcheh area. During the warm and cold period s, the association between the dust activity (AAI) and topsoil characteristics ( topsoil layer wetness and surface skin temperature ) is statistically significant . Conversely, in some cases (e.g. Fig 4-b on 17/04/2010 in warm period & Fig 5 -b on 21/12/2012 in cold period ), despite strong wind and high surface skin temperature , the topsoil layer wetness was high and thus reduced the particle release. It is worth to mention that during both warm and cold seasons, we observed some anomalies in particle trajectories (e.g. Fig 4 -b on 17/04/2010 & Fig S1-e on 22/04/2018 in warm period and Fig 5-a on 02/10/2016 & Fig S2-b on 20.02/2015 in cold period) and they did not follow the same discussed above -mentioned pattern as others did. For the time frame studied in the present research , during the warm period, the topsoil layer wetness varied between 0.14 ± 0.09 (2011) and 0.06 ± 0.02 (2016) (Figure s 4 & S1). Despite the higher averaged value of topsoil layer wetness in 2011, the averaged 10 -m wind speed in 2011 (7.6 0 kn) was higher than that in 2016 (7.00 kn) resulting in a higher number of dust storms in 2011 compared to 2016. On the contrary , during the cold period, it range d between 0.30 ± 0.14 (2015) and 0.15 ± 0.09 (2010) (Figure s 5 & S2). However, the averaged 10-m wind speed in 2015 (5.00 kn) was higher than in 2010 (4.50 kn), leading to a higher number of dust storms in 2015 compared to 2010. According to Figure s 4, 5, S1 and S2, relatively high and persist ent AAI values are observed in the isolated origin areas such as north -eastern parts of Saudi Arabia, central parts of Iraq and Kuwait, and southw estern parts of Iran. The o bserved persistence of this specific area of intense dust activity suggests that locations in this area are specifically suitable for dust generation (Aimar et al., 2012; Broomandi et al., 2017b; Cao et al., 2015; Gholami et al., 2020; Shepherd et al., 2016) . Journal Pre-proof Journal Pre-proof 17 The monthly average anomaly of topsoil layer wetness (0-10 cm underground) during 2007 -2018 showed that there is a reduction in topsoil layer wetness in January, February, March, as well as in October ( four of the six months of the cold season) which is strongly and positively correlat ed with monthly average rainfall anomal ies during the same period (R2 = 0.65, p <0.001) . Previous research targeting the study area have pointed out that there are remarkable reduction s in annual and seasonal ( the cold and warm periods) anomaly values over 60 years (Broomandi et al., 2017a) . Their r egression analysis between yearly and seasonal meteorological param eters and the SDS occurrence also showed a positive correlation between SDS occurrence and wind speed ( R2 = 0.60, p <0.001) as well as SDS occurrence and temperature (R2 = 0.60, p<0.001) whereas the SDS occu rrence w as negatively correlated with the rainfall ( R2 = -0.50, p <0.001) as well as with relative humidity (R2 = - 0.70, p <0.001) (Broomandi et al., 2017a) . These reported h igh correlations between the soil properties and meteorological parameters indicate the increasing vulnerability of the study area with changing weather conditions in favor of wind erosion mechanism . a) SDS event on 07/06/2008 b) SDS event on 17/04/2010 Journal Pre-proof Journal Pre-proof 18 Figure 4. Warm period example s for backward -forward trajectories of dust particles arriving and leaving stud y area in combination with AAI, surface skin temperature (°K), and topsoil layer wetness (unitless) during a severe SDS event on (a) 07/06/2008 , and (b) 17/04/2010 a) SDS event on 02/10/2016 b) SDS event on 21/12/2012 Figure 5. Cold period example s for backward -forward trajectories of dust particles arriving and leaving the stud y area in combination with AAI, surface skin temperature (°K), and topsoil layer wetness (unitless) during severe SDS event s on (a) 02/10/2016 , and (b) 21/12/2012 . 3.3. Frequently impacted zones Journal Pre-proof Journal Pre-proof 19 The forward trajectories have been started at mid - atmospheric boundary layer ( ABL ) in order to capture its behavior under the ABL since t he air -mass altitude in the dust lifecycle has vital roles w ithin the ABL (Cavazos -Guerra and Todd, 2012; Meloni et al., 2008; Rashki et al., 2015) . It interacts with the atmospheric dynamics by influencing the heating process under ABL and the dust deposition processes at ground level (Gautam et al., 2013; Kaskaoutis et al., 2012; Rashki et al., 2015) . Generally, the air -mass forward pathways were similar in the cold and warm periods . The most significant difference was the observe d higher number s of events during the warm period , e.g., 22 sand and dust storms (three sever e sand and dust storms ) have been observed in June, and 12 sand and dust storms (one sever e sand and dust storm ) have been observed in July. The warm season trajectories also reached longer destinations along with broader spatial coverage , especially in July. Fig. 6 and 7 present 72 -hour air-mass forward trajectory frequencies , were originating from Shalamcheh during the sand and dust storm days of the warm and cold periods from 2007 to 2018. They show three frequency contours as the impact zones : (1) the maximum impact zone with 100% frequency (in both warm and cold periods) , (2) the medium impact zone with >10% frequency (cold period) & >1% (warm period) , and (3) the minimum impact zone with >1% frequency (cold period) & > 0.1% frequency (warm period) . During the warm period, the dust -loaded air masses move d northwards , reaching Iraq, Turkey, Azerbaijan, Armenia, Georgia, Russia , and then turning toward northeastwards and affecting Afghanistan, Turkmenistan, Uzbekistan, Kazakhstan, Kyrgyzstan , Mongolia , and China. The areas within the impact zone furthermore included Jordan, Israel, Lebanon, and Syria. Air masses during the se episodic events also moved to south and west , reaching Saudi Arabia, Emirates, Bahrain, Qatar, Yemen, Oman, Egypt, Eritrea, Sudan, Somalia, and Ethiopia. These systems also shift ed southeastwards , affecting Pakistan and India (Figure 6). Kuwait was highly vulnerable to dust -loaded air systems and was located within the Journal Pre-proof Journal Pre-proof 20 maximum impact zone. Saudi Arabia, Iraq, Bahrain, Qatar, Emirates, Yemen, Oman , Syria, Jordan, Turkey, Azerbaijan, Armenia, and Turkmenistan were in the medium -impact zone. Finally, the d ust-loaded air systems did hit not only the terrestrial environment but also the marine environment such as the Persian Gulf (frequency of 100%) ; Caspian Sea, Arabian Sea, Red Sea, Gulf of Aden (frequency >1%); and, the Black Sea (by frequency >0.1%) being frequent receptor s during the warm period s in 2007 -2018. During the cold period s, the episodic air masses dispersed northwards and then turned toward northeastwards, affecting Iraq, Turkey, Syria, Azerbaijan, Armenia, Georgia, Russia, Afghanistan, Turkmenistan, Kazakhstan, and Uzbekistan (Figure 7). They also move d southwards , reaching Saudi Arabia, Bahrain, Qatar, Emirates, Yemen, and Oman . Kuw ait was again highly vulnerable to episodic dust incursions and was located in the maximum impact zone . Saudi Arabia, Iraq, Bahrain, Qatar, Emirates, Yemen, and Oman were in the medium impact zone. Finally , the marine environment of the Persian Gulf (by frequency of 100%) ; Arabian Sea (by frequency >10%) ; Red Sea, Aral Sea, and Caspian Sea (by frequency >1%) have been affected by the events (Figure 7). Journal Pre-proof Journal Pre-proof 21 Figure 6. Forward trajectory frequency map for Shalamcheh (30° 45’ N and 48° 15’E ) using HYSPLIT -4 during the warm periods of the years between 2007 and 2018. Journal Pre-proof Journal Pre-proof 22 Figure 7. Forward trajectory frequency map for Shalamcheh (30° 45’ N and 48° 15’E ) using HYSPLIT -4 during the cold periods of the years between 2007 and 2018. 3.4. Regional transport pathways Although the frequency maps are quite informative tools to assess the potential impacts zones, they do not provide a clear idea of the main transport pathways. Therefore, the HYSPLIT -4 clustering algorithm was used to identify the main routes of the identi fied episodes. This method clusters all the provided trajectories utilizing the change in the total spatial variance (TSV) parameter to determine the optimum number of clusters (Lu et al., 2018) , and it has been used for the sand and dust storm events of the warm and cold periods during 2007 –2018. The trajectory cluster groups , along with their frequencies for the warm and cold periods , are presented in Figure 8. During the warm period, the most frequent Journal Pre-proof Journal Pre-proof 23 receptors of the air masses carrying dust particles were Saudi Arabia, Iraq, Yemen, Oman, Kyrgyzstan , and Emirates (12%, 12%, 20%, 21%, and 2%, respectively ). In the cold period, the most frequent receptor of the air masses carrying dust particles was Iraq (17%). In this time frame, local areas (Iran) also received dust particles (8%). Besides the terrestrial receptors, some marine environments were other main host s for the air masses carrying dust particles origin ated or enriched from Shalamcheh : During the warm period, the Persian Gulf and Arabian sea were affected (12% and 20%, respectively ). During the cold period , the Persian Gulf was the most frequent marine receptor of air masses (74%). a) Trajectory cluster groups for warm period Journal Pre-proof Journal Pre-proof 24 b) Trajectory cluster groups for cold period Figure 8. Trajectory cluster groups with their frequencies for (a) warm and (b) cold periods between 2007 and 2018 . 3.5. D ust deposition and potential impacts It should be stated that the following discussion ha s been constructed based on the information from the literature and its relation to our findings thus are hypothetical . The results from the present study do not provide direct evidence on the environmental and health impacts on receptors since this study does not include any analysis in the receptor points and areas. 3.5.1. Mineral content Journal Pre-proof Journal Pre-proof 25 The long -range transport of windblown dust occurs with high temporal and spatial variability influenced by wet and dry deposition processes (Mahowald et al., 2017; Zhang et al., 2018; Zheng et al., 2016) and this could be experienced across continents and oceans , causing concerns in both terrestrial and marine ecosystems (Kok et al., 2017; Zhang et al., 2018) with levels exceeding 100 g .m−2 deposition per year . Mineral dust particles contain macronutrients ( such as silica and phosphate) and micronutrients ( such as z inc and iron), which can enrich both terrestrial and marine ecosystems (Kohfeld and Tegen, 2007) . For example, in marine environments, the long-range transport and subsequent deposition of dust aerosols can stimulate the growth of certain aquatic organisms due to the influx of nutrients as well as sequestrate carbon in the deep sea (Molloy and Mihaltcheva, 2013) . Besides, dust particles by carrying the carbonates, are important sources of carbon for the alkaline carbon pool, capable of buffer ing the acidity of atmosphere and increas ing the alkalinity of seawater, hence influencing large -scale environmental and climatic changes . As a resul t, while sand and dust storms (SDS) events can impact the atmosphere, they can reduce the acid deposition from the atmosphere and help the mitigation of global warming (Wang et a l., 2017) . In the present study, the Persian Gulf could be the primary chronically affected marine ecosystem by the dust aerosol originated from Shalamcheh. The Persian Gulf (relatively shallow with a mean depth of 35 m) is located between Iran and the Arabian Peninsula. It is a semi -enclosed body of water that is only connected to the open waters through Hormuz Strait (Freije, 2015) . It includes a variety of relatively sensitive ecosystems that are associated with an environment that is naturally under high stress and with poor flushing characteristics, very high evaporation rates, UV exposure , salinity, and elevated temperatures. Thus, contaminants are subject to a slower dispersion, limited dilution, and thus remain in the system for more extended times (de Mora et al., 2004; Freije, 2015) . The seafood from the Persian Gulf (includin g fish and shrimp) is valuable and is subject to both Journal Pre-proof Journal Pre-proof 26 local consumption and export. As a result, it is essential to maintain good marine environmental quality for environmental, social , and economic reasons (Sheppard et al., 2010) . Moreover, maintaining seawater quality is vital since many of the Gulf countries depend on the desalinated gulf water as a source of potable water for both domestic and industrial use s (Freije, 2015) . The soils of Shalamcheh are mainly constituted of SiO 2 with a mean value of 29.2% , and the total Fe content ( as Fe2O3) of soil samples is 4.19% (ferric iron). SiO 2 and Fe 2O3 content of dust particles was 31.9% and 2.13% , respectively, over Khoramshahr city ( the nearest local terrestrial receptor) (Broomandi et al., 2017a) . The ferric form of Fe that is dominant in aerobic environments is less soluble and occurs primarily as insoluble precipitates. Therefore, to obtain ferric iron, many aerobic microorganisms need to produce chelating iron-binding proteins capable of exchanging soluble Fe soluble and transporting it into the cell. In marine environments, by conducting an Fe fertilization study, researchers witnessed an increase in phytoplankton growth by the rate of two to three times background values. They have also discussed the influen ce of aeolian Fe on marine primary productivity rates in the iron -limited waters of the North Pacific (Griffin and Kellogg, 2004) . In contrast to supplying Fe by dust deposition in marine environment, it might be crucial to consider the role of the deposited dust in the scavenging of dissolved iron. In regions with high Fe concentrations, dust deposition acts as a net sink of dissolved Fe if the scavenging removal would exceed the Fe input by dust deposition (Ye et al., 2011; Ye and Völker, 2017) . Generally, dust depositions act as a n Fe input comparing to lithogenic scavenging in most parts of the Atlantic, but dust deposition could act as a net sink of dissolved Fe in some areas in the western part of the subtropical North Atlantic. Interestingly, a decrease of about 3% is witnessed in the global net primary production and export production, especially in the areas with high-nutrient low -chlorophyll like equatorial Pacific Journal Pre-proof Journal Pre-proof 27 and the Southern Ocean. It shows that lithogenic scavenging can globally impact marine productivity, even if the amplitude of the total change is small (Ye and Völker, 2017) . Also, previous studies suggested a possible association among dust storms and Fe and P enrichments in oceans (Tagliabue et al., 2017) . Atmospheric dust fallout c ould result in the deposition of more than 60 Tg Fe and 1 Tg P into the world oceans (Mahowald et al., 2017) . Also, Fe in dust aerosols may couple with anthropogenic S in the atmosphere and ocean s, enhancing solubility and subsequent availability to aquatic organisms (Zhuang et al., 1992) . Beside s the Persian Gulf as the probable primary chronically affected marine ecosystem, Kuwait could be the main terrestrial ecosystem chronically affected by the dust aerosol originated from Shalamcheh. Since dust particle’s composition can vary from place to place due to the various origins, seasons, and weather condition s, it is critical to have a better understanding of PM sources and their characteristics to propose app ropriat e tailored mitigation strategies. Prev ious studies demonstrated that Kuwait city with a high rate of dust deposition (0.6 Kg.m-2.year-1) is ranked the first out of 56 dust deposition rates observed worldwide (Al-Awadhi and Alshuaibi, 2013; Al -Dousari and Al -Awadhi, 2012; Al - ThaniHanadi, 2018) . Using satellite data and meteorological data, settled dust in Kuwait with lower clay minerals and higher carbonates comparing to the dust in the Sahara Desert were mainly originated the drained marshes in southern Iraq and Iran, the Mesopotamian Flood Plain, the north -eastern desert of Saudi Arabia, a nd the western desert of Iraq (Al-Dousari and Al -Awadhi, 2012; Al -ThaniHanadi, 2018) . The deposited dust samples were mainly consisting of quartz (44%) , followed by a high amount of calcite (Al-Dousari and Al - Awadhi, 2012; Al -ThaniHanadi, 2018) . 3.5.2. War remains Journal Pre-proof Journal Pre-proof 28 Potentially toxic elements (PTEs) are ubiquitously used in and/or discharged by numer ous domestic and industrial sectors . They are mostly found in relatively low concentrations in soils, rocks, and in natural atmospheric and aquatic environments. Anthropogenic activities can dramatically disrupt and influence their distribution in natural systems. The Persian Gulf has previously faced substantial environmental stress over three decades via contamination by petroleum hydrocarbon s and PTEs: during the Iraq –Iran War between 1980 and 1988, and during the first and second Gulf War s in 1991 and 2003 . Therefore, it can be hypothesized that one of the primary anthropogenic sources of contaminants in the area is war remains. The EF values for selected trace and major elements from soil samples taken from Shalamcheh showed that Br, Cl, Mo, S, Zn , and Hg are of anthropogenic origin in the study area(Broomandi et al., 2017a) . The war remains from Iraq -Iran could be one of the critical anthropogenic sources of trace elements in this area. Furthermore , high values of Cl and S encountered in the local soils could be attributed to chemical warfare (the use of chemical agents such as m ustard gas) in the Iraq- Iran war during the period 1980 -1988 (Broomandi et al., 2017a; Ghanbarizadeh and Nejad, 2012) . It has been shown that the presence of Pb, Cu, Hg, Br, Mo , and Zn in contaminated soils could be linked to intense war activities (Wallace, 2018) . The enriched Hg in the location may also be linked to war activities (Broomandi et al., 2017a) . Previous studies estimated possible dry deposited amount s of certain elements (Br, Mo, S, Zn, Ni, Cr, Co, and Hg) over Ahvaz city as a local receptor of dust particles originated from Shalamcheh in 2010 (Broomandi et al., 2018) . Br, Mo, S, Zn and Hg identified as potential soil contaminants in the study area also had high EF values in the fallout dust particles over Ahvaz city in 2010. Their presence in Ahvaz airborne dust has been attributed to possible non-crustal sources such as fossil fuel combustion, traffic emission s, gas and Journal Pre-proof Journal Pre-proof 29 drilling activities, upstream petroleum industry (in Khuzestan or neighbo uring dust origin areas in Iraq and Saudi Arabia ), and remains of the Iraq-Iran war (Broomandi et al., 2018) . Therefore, the Persian Gulf, as the probable primary chronically affected marine ecosystem, by the dust aerosol originated from the war impacted area of Shalamcheh can be harmful to marine organisms and their ecosystem. According to the provided data by Paytan et al. (2009) , frequent sand and dust st orm events act as an essential source of both marine nutrient and terrestrial contaminants to the marine environments . The high levels of heavy metals (such as Cu and Pb), the toxic organic matter (such as polyaromatic hydrocarbon), and the interaction among dust particles and the contaminants during the transport can b ring harm to the marine organisms and ecosystems. Studies showed that the presence of toxic substances carried by dust particles c ould increase the coral mortality rate in the Caribbean Sea (Paytan et al., 2009; Wang et al., 2017) . 4. Conclusions , Implications , and Limitations The present research assessed the seasonal formation (cold and warm periods) and the prevalence of sand and dust storms (SDSs) originated from a potential SDS area (Shalamcheh region southwest Iran) during 2007 -2018; and, assessed the long -range transport pathways along with potential impact zones. The persistence of intense dust activity (especially du ring the warm period) suggests that th e study area is a potential dust generation source at a global scale. It is suggested that a decrease in topsoil layer wetness during the warm period resulted in increasing concentrations of absorbing aerosol in the atmospheric column . The saltation, resuspension, and/or creeping of sand particles start with certain controlling weather conditions (e.g., wind speed and topsoil layer wetness ), which are required to be at specific Journal Pre-proof Journal Pre-proof 30 thresholds based on the sand particle characteristics (e.g., size, shape, and density) of the topsoil. Following the resuspension process, they can be transport ed over long distances. Overall, t he results indicated that t he study area acts as an SDS source in the region. Based on the Total Zone Mapping Spectrometer data, the recorded severe and arid conditions in the area showed that it is a vulnerable dust source with a persistent average annual rainfall of under 100 mm (Goudie and Middleton, 2006) that makes the area a potential location prone to desertification. The susceptibility of the study area to turn into a permanent dust source with desertification has also been mentioned in other studies (Broomandi et al ., 2017a; Cao et al., 2015; Heidarian et al., 2018) . Dust -storm pathways from Sahara towards the tropical Atlantic, the Mediterranean, and the Middle East have been well documented (Awad and Mashat, 2013; Liu et al., 2012) . In Iran, those originating from the Sistan basin were also examined (Rashki et al., 2015) , but those originating from Shalamcheh have yet to be studied. To the best of our knowledge, the current study is the first that e xamines the dust -transport pathways and the regional areas affected by the Shalamcheh sand and dust storms in full scale. The trajectory mode lling ha s identified long -distance receptor areas (impact zones), indicating that numerous countries , as well as marine zones, receive dust from the area (Kuwait and the Persian Gulf under particular high impact ), which might significantly affect nutrient as well as potentially toxic element (PTE) profile of the environment. Regarding the high wind vulnerability of the study area, which is also a war -impacted region with a potential presence of PTEs and other toxic substances , contaminated dust particles may be transported over not only the surrounding region but also long distances , including agricultur al land and marine environment. Previous studies on the Persian Gulf have already reported elevated levels of 11 trace PTEs (including Zn, As, Cr, Cu, Pb, Ni, Cd, and Hg) , mainly in marine and coastal areas (Fowler et al., 2007; Freije, 2015; Juma and Al -Madany, Journal Pre-proof Journal Pre-proof 31 2008; Naser, 2009) . As the study area is now identified as a source of SDS and it is at the same time a war-impacted area, potentially contaminated , it is recommended to perform site characterization studies taking major war -impacted zones into account . It is highly recommended to t ake effective functional stabilizing methods to control the wind erosion on susceptible region s of the study area . One of the main limitations of the present study is the lack of on-site meteorological and air quality stations, which made the study rely on the closest available stations (Abadan and Khoramshahr meteorological stations, Khorramshahr air quality station). Also, for the time frame studied, the availability of PM 10 data, measured at Khorramshahr air quality station (the nearest station to the area of interest ), was below 50% which prevented our team from performing statistical analys es to investigate the relationship between measured ground - based PM 10 and retrieved AAI data. Finally, topsoil layer wetness and surface skin temperature values have not been measured in any of the ground stations ; thus, it was not possible to investigate the relationship between measured ground -based data and satellite - retrieved data. Acknowledg ement This project has received funding from the European Union’s Horizon 2020 research and innovation program Marie Skłodowska -Curie Actions Research and Innovation Staff Exchange (RISE) under grant agreement No. 778360 and NU project (Nazarbayev Research Fund SOE2017004). The authors would like to thank all reviewers for their time and appreciate their valuable comments which have significantly contributed to the improvement of the quality of this manuscript. Journal Pre-proof Journal Pre-proof 32 Conflict of interest The authors declare that they have no conflict of interest.