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Bathymetry map of the Arabian Sea and the Bay of Bengal showing the specified regions of interest -the ROI-1 in the Arabian Sea and the ROI-2 in the Bay of Bengal. The background of the subset
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The paper investigates the impact of atmospheric dust deposition on ocean biological productivity in association with oceanic supply of nutrients over specific regions of the Arabian Sea (20°N, 69°E) and the Bay of Bengal (20°N, 87°E) during wintertime (November–March) from the year 2012 to 2017 using satellite-based observations. During winter, se...
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... characteristics of the study region For the present study, two regions of interest (shown in Fig. 1), one in the Arabian Sea, i.e., the ROI-1 (20°N, 69°E), and the other one in the Bay of Bengal, i.e., the ROI-2 (20°N, 87°E), are selected for the detailed analysis. The ROI-1 is located near to the northwest coast of India in northeastern region of the Arabian Sea, while the ROI-2 is located near to the northeastern coast of India in ...
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... The total absorption of water is analysed, with absorption ranging from 2.944 to 4.558 m −1 . Chl-a are used as proxies for the phytoplankton biomass estimation (Tyagi et al. 2020). The relationship with bio-optical constituents such as chl-a and TSM is shown in table T1 and figure F4(c and d). ...
The neural network algorithm approach was adopted in Kolavai Lake to retrieve the inherent optical properties (IOP) of active constituents. The retrieval of IOP by absorption and the scattering of optically active constituents (OAC) through employing Sentinel-2 MSI reflectance and field measured the salinity and temperature. The result illustrates the relationship between the IOP and measured OAC’s concentrations and its sensitivity towards spectral wavelength. It shows that the phytoplankton absorption ap is highly related with chlorophyll-a concentration and has an R² value of 0.808. Furthermore, at the total absorption of water has high correlation with chl-a which indicates the significant dominance in the lentic water. Also, the pigment constituents are showing an R² value of 0.754. The total backscattering of water (btot) is strongly related to the total suspended matter with R value > 0.73. The spatial distribution of OAC in Kolavai Lake helps monitor the lake water quality. This approach is well-performed in estimating the inherent optical properties of optically active constituents that gives insight for assessing the relationship between IOP and water quality. The research has proved to be a good potential for monitoring lentic water quality through Sentinel-2 MSI.
... As such, incorporation of atmospheric dust into model simulations has become an essential step in improving capabilities for predicting future climate change (Adebiyi and Kok, 2020;Arimoto, 2001;Jin et al., 2021). Dust transport also supplies micronutrients to continental and marine ecosystems (Francis et al., 2019;Okin et al., 2004;Schulz et al., 2012;Suresh et al., 2021;Tyagi et al., 2020), which feeds back into the global carbon cycle (Falkowski et al., 2000). In addition, aeolian dust mobilization and transport can characterize atmospheric circulation patterns generally responsible for heat transport. ...
Greenland ice cores are high-resolution archives of atmospheric dust loadings, and a better understanding of the driving factors for Greenland ice core dust concentration changes across different timescales provides valuable insights into changes in atmospheric circulation pattern and benefits accurate prediction of the future climate change. In this review, based on the dust record of the NGRIP ice core, we systematically characterize the Greenland ice core dust concentration changes during the last glacial, and explore the major driving factors.
Based on the previously published and own isotope geochemical data, we estimated the contributions of provenances for the Greenland ice core dust using Bayesian mixing model. The results show that the dust was primarily derived from the Asian sources (71.5%) during the last glacial. Dust contributions from Africa include 10% (6.9%–12.0%) for North Africa and 6.9% (4.6%–8.3%) for West Africa; East Central & Eastern European sources yield a contribution of 11.7% (8.3%–14.2%). Subsequently, we revealed the contributions of multiple influencing factors to the Greenland dust concentration changes on orbital scale using the Lindeman-Merenda-Gold method. Overall, the findings highlight a crucial role of the aeolian activity in sources in controlling the Greenland dust concentration changes during the last glacial (63%). A greater effect of the atmospheric transport efficiency is also found (31%); by contrast, the spilt of jet stream contributes little (5%). We further argue that the variations in contribution of intensity of aeolian activity in sources through MIS2–5 may be related to glacial grinding by high-altitude mountain glaciers, with more significant influences exerted on variations in the Greenland dust concentration during MIS4. Inversely, more contributions from the atmospheric transport efficiency (wet deposition and reduced atmospheric residence time of dust in transport pathways) are observed during MIS2 and MIS3 than those during MIS4 and maybe MIS5. The results about changes of the contributing proportions of intensities of the different source areas throughout MIS2–5 reveal the major roles of sediment availability, displacement of the westerlies, and the Northern Hemisphere ice volume. The variations in contribution of the split of jet stream through MIS2–5 also demonstrate its minor role in influencing the Greenland dust concentration changes. In addition, it is suggested that the 21-ka precessional period found in the Greenland dust records possibly reflects the integrated response of paleoclimate changes to Milankovitch forcing (northern summer insolation). As for variations in the last glacial maximum (LGM) dust concentration, the enhanced dust emissions induced by changes of the North Atlantic jet stream over the Central and Eastern Europe and the Tarim Basin promoted the sharp dust concentration increases during the early-LGM. Such a scenario was intimately related to more frequent Rossby-wave breakings under negative NAO/AO phases. Furthermore, loss of dust aerosol due to wet deposition en route and ice accumulation rates could also have affected the Greenland dust concentration changes during the LGM. The findings are thought to enable interpretation of the observed decoupled relationship between the CLP loess accumulation rates and the Greenland dust concentrations during the LGM.
... Although significant progress has been made in aerosol characterization over land through systematic measurements from several global networks and intensive research campaigns, their optical and physico-chemical properties over the oceanic regions need further investigation, especially in marine boundary layers highly affected by continental outflows and multiple sources (Smirnov et al., 2009;Kaskaoutis et al., 2010;Becagli et al., 2017). Dry and/or wet deposition of continental aerosols over oceans, apart from their effects on solar radiation and marine clouds (Chen et al., 2014;Zhou et al., 2015), may also influence various biological and chemical processes like carbon and phosphorus cycles, dimethyl-sulphide emissions, iron content and phytoplankton blooming (Mahowald et al., 2005;Carslaw et al., 2009;Tyagi et al., 2020). Numerous studies (Markowicz et al., 2002;di Sarra et al., 2011;Papadimas et al., 2012;di Biagio et al., 2016;Gkikas et al., 2018;Nabat et al., 2020) underlined the importance of aerosol radiative effects in the central and eastern Mediterranean, based on satellite data and measurements in coastal or island locations. ...
This study analyzes the aerosol optical properties (scattering, absorption coefficients, single scattering albedo), supported by chemical composition measurements, in the marine boundary layer of the East Mediterranean – Middle East (EMME) region, aiming to explore the spatio-temporal variability, aerosol mixing state, sources and dominant types. The measurements were taken during the AQABA (Air Quality and climate change in the Arabian Basin) cruise campaign (1st July – September 1, 2017) from the south of France to Kuwait and back. Both scattering and absorption coefficients for PM1 and PM10 particles maximized in the southern Red Sea, due to continental outflow from East Africa, and in the Arabian/Persian Gulf due to enhanced anthropogenic/industrial emissions, leading to 3-fold sulfate concentrations compared to the other regions. The East Mediterranean exhibited moderate aerosol loading, with high scattering Ångström Exponent (SAE) values (1.98, 1.30 for PM1 and PM10, respectively), which increased in the Suez Canal and the Arabian Gulf due to impact from combustion sources. The aerosol over the Gulf of Aden and the West Arabian Sea was dominated by coarse particles (SAE<1), with higher Ca²⁺ concentrations (dust influence). The absorption Ångström Exponent (AAE) remained close to 1, indicative of black carbon (BC) from fossil fuel combustion, while it increased in regions dominated by dust (Gulf of Aden, Arabian Sea). Contrasting aerosol types were identified between the sub-regions using the SAE vs. AAE classification scheme. The “BC-dominated” type prevailed over the East Mediterranean and Suez Canal, while dust mixtures dominated in the Gulf of Aden and the Arabian Sea. Over the Arabian Gulf, mixing of anthropogenic pollution with marine aerosols formed a type with fine particles and low spectral dependence of absorption (AAE<1). Spectral SSA significantly varied along the ship cruise, while it was used for determination of dust influence in the marine environment.
... Removal of fertile top sediments may increase soil salinity with deleterious effects on agriculture [15][16][17][18], while dust deposition can also affect terrestrial and oceanic biochemical cycles and distress forests and agriculture productivity, thus increasing food production costs [19][20][21]. The SDSs also contain iron, a limiting nutrient in the marine environment, so when dust is deposited onto the sea, it can act as a fertilizer for the growth of phytoplankton or algae [22,23]. The rates of fluvial and Aeolian erosion may be of a similar magnitude to rates of Aeolian deposition resulted from SDSs [24]. ...
Dust storms represent a major environmental challenge in the Middle East. The southwest part of Iran is highly affected by dust events transported from neighboring desert regions, mostly from the Iraqi plains and Saudi Arabia, as well as from local dust storms. This study analyzes the spatio-temporal distribution of dust days at five meteorological stations located in southwestern Iran covering a period of 22 years (from 1997 to 2018). Dust codes (06, 07, 30 to 35) from meteorological observations are analyzed at each station, indicating that 84% of the dust events are not of local origin. The average number of dust days maximizes in June and July (188 and 193, respectively), while the dust activity weakens after August. The dust events exhibit large inter-annual variability, with statistically significant increasing trends in all of five stations. Spatial distributions of the aerosol optical depth (AOD), dust loading, and surface dust concentrations from a moderate resolution imaging spectroradiometer (MODIS) and Modern-Era Retrospective analysis for Research and Applications (MERRA-2) retrievals reveal high dust accumulation over southwest Iran and surrounding regions. Furthermore, the spatial distribution of the (MODIS)-AOD trend (%) over southwest Iran indicates a large spatial heterogeneity during 2000–2018 with trends ranging mostly between −9% and 9% (not statistically significant). 2009 was the most active dust year, followed by 2011 and 2008, due to prolonged drought conditions in the fertile crescent and the enhanced dust emissions in the Iraqi plains during this period. In these years, the AOD was much higher than the 19-year average (2000 to 2018), while July 2009 was the dustiest month with about 25–30 dust days in each station. The years with highest dust activity were associated with less precipitation, negative anomalies of the vegetation health index (VHI) and normalized difference vegetation index (NDVI) over the Iraqi plains and southwest Iran, and favorable meteorological dynamics triggering stronger winds.
... Dispersed dust particles across seawaters have considerable impacts on their climate (Knippertz and Stuut, 2014;Gassó et al., 2010). In addition, monitoring dust over waters, provides valuable information about transported dust to that region and activities of the influential dust sources (Tyagi et al., 2020;Schulz et al., 2012;Singh et al., 2008). Open waters in the south of the Iran Plateau as a large water region are located on the earth dust belt and surrounded by some major dust sources (Prospero et al., 2002). ...
Satellite recordings by CALIPSO and Aqua-MODIS, available data on the Aerosol Robotic Net-work (AERONET), and synoptic stations have been used to investigate dust storms over the Persian Gulf and the Oman Sea from January 2007 to December 2019. We found that the depo-larization of lidar signals by atmospheric dust particles is quite sensitive to their origins (deserts, or alluvial sediments). In the CALIPSO data set, the depolarization just over the thickness of an aerosol layer is called as the integrated depolarization ratio (IPDR). The IPDR and MODIS aerosol optical depth (AOD) over the mentioned waters are in correlation with the changes in the wind pattern over the region and activities of different dust sources in the neighborhoods of the waters. This investigation shows that the highest IPDR values belong to the dust particles which are originating from the Arabian Peninsula and impacting almost all regions in the south of the Iran Plateau from February to May. Also, these waters are under considerable influence of the Mesopotamian region and dust sources at the east side of the plateau. These sources are almost composed of alluvial sediments, and the IPDR for particles rising from them, is not high as those from the Arabian desert. Even though intense dust plumes raised from sources in the East of the Plateau impact these waters very frequently in summertime, but largest dust particles belong to the plumes originating from the Arabian desert in spring.
... H. Gholami et al. Atmospheric Pollution Research xxx (xxxx) Athira et al., 2018, Burtman and Molnar, 1993, Buslov et al., 2007, Capinha et al., 2021, Chen et al., 2018, De Grave et al., 2012, De Pelsmaeker et al., 2018, Ducea et al., 2003, Dumitru et al., 2001, Hu et al., 2015, Jolivet et al., 2010, Kingma and Ba, 2014, Li et al., 2021b, Nhu et al., 2020, Niu et al., 2020, Panahi et al., 2021, Samal et al., 2021, Thomas et al., 1993, Tieleman and Hinton, 2012, Tyagi et al., 2020, Utkin, 2020, Wang et al., 2020b, Xiao et al., 2015, Yakubchuk, 2004, Zhai and Cheng, 2020, Zhi et al., 2020 Gholami et al. Atmospheric Pollution Research xxx (xxxx) ...
Spatial mapping of dust sources in arid and semi-arid regions is necessary to mitigate on-site and off-site impacts. In this study, we apply a novel integrated modelling approach including leave one feature out (LOFO) – as a technique for feature selection -, deep learning (DL) models (gcForest and bidirectional long short-term memory (Bi-LSTM)), game theory (GT) and a Gaussian copula-based multivariate (GCBM) model for mapping dust sources in Central Asia (CA). Eight factors (precipitation, cation exchange capacity, bulk density, wind speed, slope, silt content, lithology and coarse fragment content) were selected by LOFO as effective for controlling dust emissions, and were used in the novel modelling process. Six statistical indicators were utilized to assess the performance of the two DL models and a hybrid copula-gcForest model, while a sensitivity analysis of the models was also carried out. The hybrid copula-gcForest model was identified as the most accurate, predicting that 16%, 7.1%, 9.5% and 67.4% of the study area is grouped at low, moderate, high and very high susceptibility classes for dust emissions, respectively. Based on permutation feature importance measure (PFIM) and Shapely Additive exPlanations (SHAP), bulk density, precipitation and coarse fragment content were evaluated as the three most important factors with the highest contributions to the predictive model output. The study area suffers from intense wind erosion and the generated spatial maps of dust sources may be helpful for mitigating and controlling dust phenomena in CA.
... Stronger Levar winds facilitate dust emissions from the dry lands in Central Asia (Zhang et al., 2020), but mostly from the Hamoun dried beds in Sistan, thus causing massive dust storms over southwest Asia that may affect the northern part of the Arabian Sea Rashki et al., 2015;Tyagi et al., 2019;Kumar et al., 2020). Therefore, changes in Levar intensity are a regulatory factor for dust emissions and long-range transport over southwest Asia that may affect Fig. 13. ...
Levar wind is the dominant meteorological and climatic feature in east Iran, blowing from Central Asia to the northern coast of the Arabian Sea. It is also known as “120-days wind” due to its mean duration in the summer season. Although violent and responsible for massive dust storms in southwest Asia, long-term climatology and atmospheric dynamics that facilitate genesis and dissipation of Levar have not been well documented. This study uses the two-phase regression method for determining the onset, dissipation and duration of Levar during a 41-years period (1972–2012), based on identification of the change points in wind data series at Zabol meteorological station. The mean duration of the Levar period is estimated to 135 ± 24 days, with a remarkable inter-annual variability. The mean Levar onset is determined around 22 May ±23 days, while the withdrawal on 8 October ±25 days. On average, the onset and dissipation of Levar occur between wind speeds of 4.6–7.7 ms⁻¹ in spring and 3.9–6.7 ms⁻¹ in autumn, respectively. A comprehensive analysis is performed for the first time to examine meteorological dynamics that are associated with onset, duration and withdrawal of Levar. The early onset years are characterized by stronger winds during May, while no considerable changes in wind are detected between early and late withdrawal years. Changes in the mean sea-level pressure (MSLP) dipole between the Caspian Sea and India/Pakistan forces the onset of Levar. Therefore, early (late) onset (withdrawal) of Levar are driven by changes in MSLP over these areas, while local dynamics and topography also play an important role. Levar seems to be modulated by CasHKI (Caspian Sea Hindu Kush Index), while changes in the Caspian-Sea High (majorly) and in the Indian/Pakistan monsoon thermal low (secondarily) affect the Levar intensity.
... On 28 May, the HYSPLIT air trajectories show that the dust storm originated from the Sistan Basin affected the south-eastern parts of Iran, western Pakistan and dust flanks might also reach over the Thar desert in India. For both Sistan dust storms, particle deposition over the north Arabian Sea may affect the ocean biogeochemistry processes through transport of micronutrients on dust particles (Singh et al., 2008;Richon et al., 2018;Kumar et al., 2020;Tyagi et al., 2020). On 14 July 2016, the MSLP pattern was dominated by the intense Indian-Pakistan thermal low, which was extended over the eastern Arabian Peninsula forming a secondary, but also intense, core of low pressure according to ERA-Interim (Fig. 4b). ...
Ephemeral and dried lakes in southwest and central Asia, such as the Aral Sea and Hamouns in east Iran, are major sources of dust storms with an increasing tendency during the last decades due to anthropogenic influence and climate change. This study examines two characteristic dust-storm events originated from these areas on 12–15 July 2016 and 27–28 May 2018. Thermal low-pressure systems over topographic-low areas and the Caspian Sea High, along with pressure gradients and intense surface winds over the dust sources facilitated the dust outbreaks and transport. Three models (DREAM-NMME-MACC, CAMS and WRF-Chem) are synergized to simulate the spatial distribution of AOD and surface dust concentrations during the dust events. The results show that DREAM-NMME-MACC and WRF-Chem exhibit the highest discrepancies (R = 0.15–0.58; RMSE = 83%–125%) in representing the spatial and temporal distribution of dust compared to Terra-MODIS AODs, while CAMS reveals the best performance (R = 0.29–0.77; RSME = 67%–124%). All models significantly underestimate the high MODIS AODs, especially near the source areas, due to different dust schemes, soil conditions, meteorology and dynamic processes for dust emissions that they comprise. Furthermore, notable differences between the models are revealed in simulations of the PM10 concentrations in Zabol, east Iran, as the models fail to reproduce the temporal evolution and high intensity of the dust event. In general, all models represent better the dust storm originated from Sistan (13–14 July 2016) rather than the Aralkum dust storm (27–28 May 2018), indicating an incapability in representing the soil characteristics in a progressively drying terrain.
... Apart from supplying nutrients to Arabian Sea, which significantly modulate primary productivity (Kumar et al., 2008;Banerjee and Prasanna Kumar, 2014;Shafeeque et al., 2017;Guieu et al., 2019;Bali et al., 2019;Tyagi et al., 2019), these dust particles can also impact on mesoscale processes leading to the break monsoon period during the rainy season over Indian subcontinent (Vinoj et al., 2014;Jin et al., 2016;Dave et al., 2017). In addition, studies have shown that absorbing dust aerosols over the Arabian Sea can enhance the southwest monsoon flow by heating the troposphere (Jin et al., 2015). ...
The Arabian Sea is an enclosed basin surrounded by land and is prone to receive large amount of aeolian dust from the continent. This can significantly impact surface water biogeochemical processes. In this study, an attempt has been made to quantify the amount of dust transported from Middle East region to Indian subcontinent (sampling site is Goa; 15.45°N 73.80°E; located in the northeast Arabian Sea) via the Arabian Sea. We identified a dust storm episode (02–10 April 2015) in the Arabian Peninsula and its propagation to the study site (Goa) using satellite data (MODIS and CALIPSO). The impact of the dust storm at Goa has been computed using ambient particulate matter concentration and satellite retrieved optical parameter. These observations were further substantiated using ground-based micro-pulse lidar measurement. The daily averaged lidar profile shows relatively high depolarization ratio (0.1–0.25), as well as high daily average backscatter coefficient (up to 0.08 Sr⁻¹ Km⁻¹) and extinction coefficient (up to 0.9 Km⁻¹) during the storm period compared to non-dusty days. During this period, a two-layer (rich in non-spherical particle) structure with significantly high linear depolarization ratio is observed, indicating the impact of the dust storm at the coastal region of India. Ambient mass concentration of dust estimated using CALIPSO profile are comparable with the gravimetric mass measured from high volume sample collection. The back-trajectory analysis further supports the advection of air-mass from the Middle East to Eastern Arabian Sea. This study highlight the significant role of long-range transport in impacting dust load at the remote/receptor sites.
... Dispersed dust particles across seawaters have considerable impacts on their climate (Knippertz and Stuut, 2014;Gassó et al., 2010). In addition, monitoring dust over waters, provides valuable information about transported dust to that region and activities of the influential dust sources (Tyagi et al., 2020;Schulz et al., 2012;Singh et al., 2008). Open waters in the south of the Iran Plateau as a large water region are located on the earth dust belt and surrounded by some major dust sources (Prospero et al., 2002). ...
