Search Results (48)

Since dust aerosols are one of the major pollutants in Georgia, it is important to study the aeolian desert dust (ADD) invasion to Georgia from the neighboring deserts to find out its contribution to the dust pollution problem. Therefore, the main objective of this study is to investigate the history, frequency and routes of ADD invasions to the Caucasus (Georgia) using modern models and technologies for 1.5 years. Using WRF-Chem/dust, CAMS and HYSPLIT mathematical models; MODIS satellite images; and PM10 field data, 38 cases of not strong ADD invasions to Georgia were found, and two typical cases are presented and analyzed in this paper. The results of the modeling studies from 15 March 2023 to 15 September 2024 showed that the WRF-Chem/dust (GOCART) v.4.5.1 model simulated the ADD transport to Georgia from the surrounding deserts quite well. Daily monitoring of ADD migration routes showed that in the easternmost region of Georgia (the most vinicultural and agricultural region), the number of ADD invasions was approximately three times higher than in other regions of Georgia, which is a novelty of this study due to the lack of ground dust measurement stations in the easternmost region of Georgia. Full article

Understanding aeolian sediment transport and wind erosion enhances our knowledge of desert dune formation and sand migration. The Makran region of southern Sistan and Baluchistan is prone to wind-driven erosion alongside frequent sand and dust storms (SDSs). Hourly wind data from two meteorological stations spanning 1994–2020 were analyzed to study erosive winds and sand transport. Wind energy analysis using drift potential (DP) indicated low energy (DP < 200 in vector unit) and minimal spatial variation across the Makran dune fields. The effective winds transporting sand particles were towards the east from November to May, and in the northwestern direction from June to October. The DP showed a gradual decline in the study area from 1990 to 2022, with no significant temporal trends. The sand dune morphology analysis indicates that bimodal wind regimes primarily form linear dunes and sand sheets, while crescentic, transverse, and topographic dunes are also present. Full article

Surface mining in the southeastern Gobi Desert has significant environmental impacts, primarily due to the creation of large coal piles that are highly susceptible to aeolian processes. Using spaceborne remote sensing and numerical simulations, we investigated erosional processes and their environmental impacts. Our primary tool was Interferometric Synthetic Aperture Radar (InSAR) data from Sentinel-1 imagery collected between 2017 and 2022. We analyzed these data using phase angle information from the Small Baseline InSAR time series framework. The time series analyses revealed intensive aeolian erosion in the coal piles, represented as thin deformation patterns along the potential pathways of aerodynamic transportation. Further analysis of multispectral data, combined with correlations between wind patterns and trajectory simulations, highlighted the detrimental impact of coal dust on the surrounding environment and the mechanism of aeolian erosion. The lack of mitigation measures, such as water spray, appeared to exacerbate erosion and dust generation. This study demonstrates the feasibility of using publicly available remote sensing data to monitor coal mining activities and their environmental hazards. Our findings contribute to a better understanding of coal dust generation processes in surface mining operations as well as the aeolian erosion mechanism in desert environments. Full article

Some of the most severe aeolian damage occurs along the middle reaches of the Yarlung Zangbo River in Tibet. Dust emission amounts (DEAs) are often used to assess aeolian damage; however, the research on DEAs in this area is currently almost blank. This article uses field-measured wind speed data from 2021 to 2022 in the Shannan wide valley area, combined with the Gillette dust emission estimation model to quantitatively determine the contributions of three surface types (riverbank quicksand area, foothill sand dunes, and the river floodplain vegetation area) to DEAs in the research area. The influence of surface characteristics on DEAs is analyzed and discussed. The results show the following: (1) The threshold friction velocity ($u_{*t}$) in the riverbank quicksand area, foothill sand dunes, and the river floodplain vegetation area is 30.6 cm/s, 71.2 cm/s, and 85.6 cm/s, respectively, the threshold velocity ($u_t$) is 6.1 m/s, 7.0 m/s, and 7.5 m/s, respectively, and the vegetation area is 2.8 times and 1.3 times that of the quicksand area, respectively. (2) The DEAs were in the following order: the riverbank quicksand area (652.9 t/km²) > foothill sand dunes (326.5 t/km²) > the river floodplain vegetation area (107.8 t/km²), the riverbank quicksand area is about 6.1 times that of the river floodplain vegetation area, and DEAs are a significant seasonal distribution: winter (44.7%) > spring (28.3%) > autumn (15.7%) > summer (11.3%). (3) The DEAs from the dusty weather were in the following order: blowing sand (60.2%) > sandstorms (28.6%) > gusty winds (11.2%). (4) The DEAs increase with the increase in the average wind speed greater than 6.1 m/s, but the increase rate is obviously different, which showed that Changguo and Azha are greater than Sangyesi, Duopazhang, Sangri, and Senburi. At approximately the same average wind speed greater than 6.1 m/s, the DEAs in the quicksand area are much greater than in the vegetation area. Full article

Aeolian sediments accumulated along the desert-loess transition zone of the Tengger Desert include heterogeneous textures and complex component structures in their grain-size distributions (GSD). However, the sources of these aeolian sediments have not been resolved due to the lack of large reference GSD sample datasets from adjacent regions that contain various types of sediments; such datasets could be used for fingerprinting based on grain-size properties. This lack of knowledge hinders our understanding of the mechanism of aeolian dust releases in these regions and the effects of forcing of atmospheric circulations on the transportation and accumulation of sediments in this region. In this study, we employed a multi-scale grain-size analysis method, i.e., a combination of the single-sample unmixing (SSU) and the parametric end-member modelling (PEMM) techniques, to resolve the component structures of sediments that had accumulated along the desert-loess transition zone of the Tengger Desert. We have also analyzed the component structures of GSDs of various types of sediments, including mobile and fixed sand dunes, lake sediments, and loess sediments from surrounding regions. Our results demonstrate that the patterns observed in coarser fractions of sediments (i.e., sediments with a mode grain size of >100 μm) from the transition zone match well with the patterns of component structures of several types of sediments from the interior of the Tengger Desert, and the patterns seen in the finer fractions (i.e., fine, medium, and coarse silts with a modal size of <63 μm) were broadly consistent with those of loess sediments from the Qilian Mountains. The deflation/erosion of loess from the Qilian Mountains by wind was the most important mechanism underlying the production of these finer grain-size fractions. The East Asia winter monsoon (EAWM) played a key role in transportation of the aeolian dust from these source regions to the desert-loess transition zone of the desert. Full article

Grain collisions in aeolian events, e.g., due to saltation, result in atmospheric aerosols. They may regularly be electrically charged, but individual charge balances in collisions including small grains are not easily obtained on the ground. We therefore approach this problem in terms of microgravity, which allows for the observation of collisions and the determination of small charges. In a drop tower experiment, ∼1 mm dust aggregates are traced before and after a collision within the electric field of a plate capacitor. The sum of the electric charge of two particles (total charge) before and after the collision often strongly deviates from charge conservation. Due to the average low collision velocities of 0.2 m/s, there is no large scale fragmentation. However, we do observe small charged particles emerging from collisions. The smallest of these particles are as small as the current resolution limit of the optical system, i.e., they are at least as small as tens of µm. In the given setting, these small fragments may carry 1 nC/m²–1 µC/m² which is between 1% and ten times the surface charge density of the large aggregates. These first experiments indicate that collisions of charged aggregates regularly shed charged grains into the atmosphere, likely down to the suspendable aerosol size. Full article

Terra rossa is a reddish clay soil which is often present on the surface of limestone in regions with a Mediterranean-type climate. Its genesis is a controversial subject in terms of the origin of the parent material, from the residuum of underlying (carbonate/dolomite) bedrock in the absence/presence of an external silicate contribution (e.g., aeolian dust). Within this context the main goal of the present work was the understanding of the geochemical processes leading to the formation of the terra rossa starting from the carbonate bedrock. We report the results of a multi-method analysis on a terra rossa deposit occupying the bottom of a Quaternary karst depression on Mesozoic limestones exposed in the Murge area (Apulia Foreland, southern Italy). Geological, petrographic, textural, and chemical data were collected on karst products (reddish calcite incrustations and nodules, and fine-grained portion of terra rossa) by a detailed field mapping, optical microscopy, XRF and fusion ICP/MS analyses and by scanning electron microscope. New collected data show that the mineralogical composition of reddish incrustations and nodules is comparable, consisting of fibrous and impure calcite, detrital fragments of quartz, K-feldspar, zircon and authigenic minerals as (Mn, Ba, Ca) phases, (Al, Si, Mn, Fe, Mg, Ba, Ca) minerals, Fe-kaolinite and anatase. The prevailing minerals, instead, in the fine-grained portion of terra rossa are hematite, kaolinite, and goethite. Based on the chemical composition, and especially on REE patterns, a progressive interaction of silicate aqueous solutions (with Al, Si, Fe), containing pelite material, with the calcareous bedrock, as a source of carbonic acid, was the process driving the formation of terra rossa. Obtained results add new elements to the definition of the long-lasting question about the genetic processes responsible for the formation of terra rossa, corroborating their polygenetic origin, as result of limestone alteration in conjunction with the chemical interaction with allochthonous siliciclastic material. Full article

Sand and dust storms are hazardous to the environment and have a significant role in desertification. Under the influence of climate change and human activities, dust storms and aeolian processes have been common phenomena in the Southern Balkash deserts in Kazakhstan, Central Asia. However, knowledge gaps on spatial and temporal characteristics of dust storms and aeolian process in the Southern Balkash deserts still exist. Therefore, in present study, meteorological observations and numerous cartographic materials were used to identify the powerful sources with the highest frequency of dust storms and aeolian processes in the Southern Balkash deserts. The result showed that the Southern Balkash deserts were covered mainly by transverse parabolic sands (48%), dome dunes (24%), and transverse dome dunes (23%), where the aeolian processes occurred to a significant degree. Significant and strong degrees of aeolian processes occurred in most of the Southern Balkash deserts. The eastern part of the Taukum and the northern part of the Zhamankum and Karakum deserts were prone to aeolian processes to a substantial degree. The Moiynkum, Bestas, Saryesikatyrau, and Taukum deserts had the most frequent storms, occuring, on average, 17 to 43 days/per year. The occurrence of dust storms has been of a stable decreasing trend since the 1990s, except for 2008–2009. Aeolian dust in the Southern Balkash deserts flowed mainly from the western and southwestern to the eastern and northeastern. The results of the present study shed light on the temporal and spatial characteristics of dust storms and aeolian processes in the Southern Balkash deserts. This is of great importance in helping to monitor and predict dust storms and motion patterns of aeolian dust in this region. Full article

Aeolian sand flow is a major cause of land desertification, and it is prone to developing into a dust storm coupled with strong wind and thermal instability. The microbially induced calcite precipitation (MICP) technique can significantly improve the strength and integrity of sandy soils, whereas it easily leads to brittle destruction. To effectively inhibit land desertification, a method coupled with MICP and basalt fiberreinforcement (BFR) was put forward to enhance the strength and toughness of aeolian sand. Based on a permeability test and an unconfined compressive strength (UCS) test, the effects of initial dry density (ρ_d), fiber length (FL), and fiber content (FC) on the characteristics of permeability, strength, and CaCO₃ production were analyzed, and the consolidation mechanism of the MICP-BFR method was explored. The experiments indicated that the permeability coefficient of aeolian sand increased first, then decreased, and subsequently increased with the increase in FC, whereas it exhibited a tendency to decrease first and then increase with the increase in FL. The UCS increased with the increase in the initial dry density, while it increased first and then decreased with the increase in FL and FC. Furthermore, the UCS increased linearly with the increase in CaCO₃ generation, and the maximum correlation coefficient reached 0.852. The CaCO₃ crystals played the roles of providing bonding, filling, and anchoring effects, and the spatial mesh structure formed by the fibers acted as a bridge effect to enhance the strength and brittle damage of aeolian sand. The findings could supply a guideline for sand solidification in desert areas. Full article

High aerosol levels pose severe air pollution and climate change challenges in Iran. Although regional aerosol optical depth (AOD) trends have been analyzed during the dusty season over Iran, the specific factors that are driving the spatio-temporal variations in winter AOD and the influence of meteorological dynamics on winter AOD trends remain unclear. This study analyzes the long-term AOD trends over Iran in winter during the period 2000–2020 using the updated Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) and the Moderate Resolution Imaging Spectroradiometer (MODIS) datasets. Our results showed that the winter AOD exhibited a significant upward trend during the period 2000–2010 followed by a significant decrease during the period 2010–2018. We found that the winter AOD trends are important over this arid region due to multiple meteorological mechanisms which also affect the following spring/summer dusty period. Ground-based observations from Aerosol Robotic Network data (AERONET) in the Middle East region display trends comparable to those of both MERRA-2 and MODIS and indicated that aeolian dust and the meteorological dynamics associated with it play a central role in winter AOD changes. Furthermore, this study indicated that a significant downward trend in winter sea level pressure (SLP) during the early period (2000–2010) induced hot and dry winds which originated in the desert regions in Iraq and Arabia and blew toward Iran, reducing relative humidity (RH) and raising the temperature and thus promoting soil drying and dust AOD accumulation. In contrast, a significant increase in winter SLP during the late period (2010–2018) induced cold and wet winds from northwestern regions which increased RH and lowered the temperature, thus reducing dust AOD. This suggests that the changes in AOD over Iran are highly influenced by seasonal meteorological variabilities. These results also highlight the importance of examining wintertime climatic variations and their effects on the dust aerosol changes over the Middle East. Full article

The Souss Basin is a dryland environment featuring soil, surface and climatic conditions enhancing processes of wind erosion and mineral and organic dust emissions while subject to frequent grazing, tillage and driving. The fine-grained compacted surfaces are covered by physical and biological crusts and stone cover and are sparsely vegetated by open argan woodland and patchily distributed bushes. Wind-tunnel experiments and soil sampling were conducted on the deeply incised alluvial fans originating from High Atlas and Anti-Atlas mountains to investigate the dryland ecosystem, including the open argan woodland, for information on local wind-induced relocation processes and associated dust emission potential. To investigate possible connections between dryland environmental traits and dust emissions, we used two approaches: (a) surface categories (stone cover, crust and cohesionless sand) and (b) Land Cover Classes (wasteland, woodland and wadi). The results indicate omnipresent dynamic aeolian surface processes on a local to regional scale. Wind impact is a powerful trigger for the on-site relocation of available mineral and organic dust and may be crucial to explain the heterogeneous spatial distribution of soil organic carbon and nutrients associated with mineral fines. Aeolian dust flux showed statistically significant relations with surface categories and, to some extent, with Land Cover Classes. While wind erosion processes are key to understanding on-site sediment and nutrient dynamics between fertile dryland islands, the results also indicate a considerable dust emission potential under increasing climate impact and anthropogenic pressure. Full article

This study encompasses the grain size distribution of the playa lakes (Pachpadra, Pokhran, and Didwana) of the Thar Desert in Rajasthan, India. The grain size of sediment particles is the most fundamental feature, giving essential information regarding their origin, transport history, and depositional conditions. The aeolian and fluvial transport processes were evaluated through environmentally sensitive grain size subpopulations to identify the differential sedimentary sources and dynamics in the playas. End-member modelling further determined the sediment grain size distribution through statistical analysis. The playa sediments mainly consist of very fine sand (46–54%) and very coarse silt (22–37%). The results show that the average fine fraction of Pachpadra, Pokhran, and Didwana playa was 46.29%, 66.11%, and 66.28%, respectively. In contrast, the average coarser fraction deposition in Pachpadra, Pokhran, and Didwana corresponds to 53.71%, 33.89%, and 33.72%, respectively. This suggests that the playas mostly contain aeolian sediment rather than fluvial sediment transported by dust/sand storms. Additionally, the textural pattern and depositional distribution of the sediments determined through the Passega CM diagram and bivariate plots indicate that 82% of the samples were poorly sorted, and 18% were very poorly sorted. Furthermore, an environmentally sensitive grain size component (ESGSC) was also assessed to identify the spatial variability and transport processes of sediment between these playas. Three ESGSCs in Pokhran (250 µ, 31 µ, and 2 µ) and Pachpadra (125 µ, 31 µ, and 4 µ), while two ESGSCs in Didwana playa (125 µ and 16 µ) were identified, indicating sediment deposition with moderate velocity in a low energy environment with a mixed sediment population transported by aeolian and fluvial activities. Full article

With the desiccation of the Aral Sea, salt–alkali dust storms have increased in frequency and the surrounding environment has deteriorated. In order to increase our understanding of the characteristics and potential impact zone of atmospheric aerosols in the Aral Sea region, we evaluated seasonal and diurnal variation of aerosols and identified the zone most frequently impacted by aerosols from the Aral Sea region using CALIPSO data and the HYSPLIT model. The results showed that polluted dust and dust were the two most commonly observed aerosol subtypes in the Aral Sea region with the two accounting for over 75% of observed aerosols. Occurrence frequencies of polluted dust, clean continental, polluted continental/smoke, and elevated smoke showed obvious seasonal and diurnal variations, while occurrence frequency of dust only showed obvious seasonal variation. Vertically, the occurrence frequencies of all aerosol subtypes except dust showed significant diurnal variation at all levels. The thickness of polluted dust layers and dust layers exhibited same seasonal and diurnal variations with a value of more than 1.0 km year-round, and the layer thickness of clean continental and polluted continental/smoke shared the same seasonal and diurnal variation features. The zone most severely impacted by aerosols from the Aral Sea region, covering an area of approximately 2 million km², was mainly distributed in the vicinity of the Aral Sea region, including western Kazakhstan, and most of Uzbekistan and Turkmenistan. The results provide direct support for positioning monitoring of aeolian dust deposition and human health protection in the Aral Sea region. Full article

Asian aeolian dust is a primary factor in Northern Hemisphere atmospheric dynamics. Predicting past and future changes in atmospheric circulation patterns relies in part on sound knowledge of Central Asian dust properties and the dust cycle. Unfortunately for that region, data are too sparse to constrain the variation in dust composition over time. Here, we evaluate the potential of a Tibetan ice core to provide a comprehensive paleo-atmospheric dust record and thereby reduce uncertainties regarding mineral aerosols’ feedback on the climate system. We present the first datasets of the mineralogical, geochemical, and Sr-Nd isotope composition of aeolian dust preserved in pre-Holocene layers of two ice cores from the Guliya ice cap (Kunlun Mountains). The composition of samples from the Summit (GS; 6710 m a.s.l.) and Plateau (GP; 6200 m a.s.l.) cores reveals that the characteristics of the dust in the cores’ deepest ice layers are significantly different. The deepest GS layers reveal isotopic values that correspond to aeolian particles from the Taklimakan desert, contain a mix of fine and coarse grains, and include weathering-sensitive material suggestive of a dry climate at the source. The deep GP layers primarily consist of unusual nodules of well size-sorted grey clay enriched in weathering-resistant minerals and elements typically found in geothermal waters, suggesting that the dust preserved in the oldest GP layers originates from a wet and possibly anoxic source. The variability of the dust composition highlighted here attests to its relevance as a paleo-environmental messenger and warrants further exploration of the particularly heterogenous Guliya glacial dust archive. Full article

Accurately predicting ambient dust plays a crucial role in air quality management and hazard mitigation. Dust emission is a complex, non-linear response to several climatic variables. This study explores the accuracy of Artificial Intelligence (AI) models: an adaptive-network-based fuzzy inference system (ANFIS) and a multi-layered perceptron artificial neural network (mlp-NN), over the Southwestern United States (SWUS), based on the observed dust data from IMPROVE stations. The ambient fine dust (PM2.5) and coarse dust (PM10) concentrations on monthly and seasonal timescales from 1990–2020 are modeled using average daily maximum wind speed (W), average precipitation (P), and average air temperature (T) available from the North American Regional Reanalysis (NARR) dataset. The model’s performance is measured using correlation (r), root mean square error (RMSE), and percentage bias (% BIAS). The ANFIS model generally performs better than the mlp-NN model in predicting regional dustiness over the SWUS region, with r = 0.77 and 0.83 for monthly and seasonal fine dust, respectively. AI models perform better in predicting regional dustiness on a seasonal timescale than the monthly timescale for both fine dust and coarse dust. AI models better predict fine dust than coarse dust on both monthly and seasonal timescales. Compared to precipitation, air temperature is the more important predictor of regional dustiness on both monthly and seasonal timescales. The relative importance of air temperature is higher on the monthly timescale than the seasonal timescale for PM2.5 and vice versa for PM10. The findings of this study demonstrate that the AI models can predict monthly and seasonal fine and coarse dust, based on the limited climatic data, with good accuracy and with potential implications for research in data sparse regions. Full article