Mineral Dust Cycle

In recent years, dust storms have become a significant issue in West Asia and the Middle East, causing concern among countries in the region. Iran is particularly impacted by these fine dust particles due to its geographical location and prevailing west-to-east wind patterns. To gain a comprehensive understanding of the local effects of fine dust, the town of Sarpol-e Zahab was selected as a research site. The study aimed to investigate the environmental, social, economic, political, and defense-security consequences of this weather phenomenon. The initial phase of the study involved analyzing trends, atmospheric patterns, and the source of dust storms using climate database information. Data from the Copernicus website was used to determine the frequency of dusty days. The NetCDF data was converted into a raster format using R software, and annual and monthly data for the years 2001–2020 were extracted for the Sarpol-e Zahab station coordinates using ARC GIS software. The MODIS sensor's Deep Blue algorithm was employed to calculate optical depth values and derive the AOD index for the period from 2001 to 2020. An in-depth analysis was conducted on a significant dust storm that occurred on April 2nd and 5th, 2008. Sea level pressure and geopotential height data were obtained from the NCEP/NCAR database and visualized using GRADS software. The HYSPLIT air parcel tracking model was used to track and monitor dust storms in the affected area. The analysis revealed a peak in dust storms between 1998 and 2020, with a severe storm occurring from April 2 to 5, 2008, originating in western Iraq and eastern Syria and moving towards western Iran. The second phase of the study focused on estimating the security implications of dust storms through expert interviews and literature review. Twenty experts from various fields provided input on the findings using the fuzzy Delphi method in three rounds. Following expert validation, a questionnaire was distributed to 350 individuals in the statistical community. The results of this section were analyzed using the PLS structural equation model. The study results suggest that the environmental and political aspects are more closely linked to the indicators in the appropriate dimension of the measurement model. The factor loading analysis of the items showed that the main effects of fine dust included a rise in illegal border movements and smuggling activities, a decline in the city's plant greenery, an increase in plant and animal pests, and a rise in street protests and urban riots. The structural model results showed that the political dimension was more strongly correlated with the other dimensions, highlighting its central influence on the impacts of dust storms in the study area. The highest correlations with environmental consequences were seen in indicators of rising pests, plant diseases, and decreasing plant greenness, scoring 0.89 and 0.88, respectively, all influenced by fine dust. In the cultural-social dimension, the most significant correlations were found in indices of a general increase in poverty and road accidents, scoring 0.87 and 0.86. In the economic dimension, increased medical expenses and decreased tourist numbers had a correlation of 0.85. The political dimension was affected by growing ethnic and religious dissatisfaction and street protests, with a correlation of 0.88. The defense-security dimension was notably impacted by the increase in illegal border crossings and security vulnerabilities, scoring 0.9 and 0.87. Indicators related to negative impacts on ancient and eco-tourism buildings and the cancellation of sporting events were excluded from the model due to scores below 0.7.

Determining the source of dust storms with use of coupling WRF and HYSPLIT models: A case study of Yazd province in central desert of Iran

Optical properties of dust and crop burning emissions over India using ground and satellite data

This paper revealed the intensifying transboundary dust events in southeastern Turkmenistan near the border of Iran, using long-term spatial and statistical data (1980–2023). This study introduced the definition of a new source of dust storms, which is called the Sarakhs-Badkhyz region, apart from the Karakum and Kyzylkum deserts. The mentioned dust source with a surface area of 100,000 km2 is located in southeastern Turkmenistan and northeastern Iran. The remotely sensed investigation of this study was supported with local and international re-analyzed datasets (e.g., IRIMO, Eumetsat, and NASA). A drastic temperature increase triggers evaporation and also dryness of the sandy deserts in southeastern Turkmenistan. Then, dried sandy grounds and high wind speeds are important factors in creating favorable conditions for dust storm formation. Additionally, the increase in the intensity of general atmospheric circulation and the more energetic activity of the frontal cyclones, associated with the cold air intrusion of the Siberian anticyclone, are important mechanisms in the dust events of the study area. The decrease in precipitation in recent years in addition to declining the water flows of the Tejen and Murghab rivers from their basins is the reason for the dryness of the sandy ground of the Sarakhs-Badkhyz region. As a result, the defined region is a susceptible zone to source sediments of dust storms in the Middle East. Future research should analyze the possible effects of the dust storms, raised from the Sarakhs-Badkhyz region, on the cultivation, construction, immigration, and healthcare situations of the inhabitants and settlements, dominantly in Mashhad, Mary, and Herat urban regions (with a total of 4.35 million inhabitants).

Starting in 2006, a new source of intense salt dust storms developed in Mar Chiquita (Córdoba, Argentina), the largest saline lake in South America. Storms originate from vast mudflats left by a 30-year expansion-retreat cycle of the lake due to changes in the regional rainfall regime. The annual frequency of salt dust storms correlated with the size of the salt mudflats. Events were restricted to the coldest months, and reached up to 800 km from the source. Occurrence of dust storms was associated with specific surface colors and textures easily identifiable in satellite images. High-emission surfaces were characterized by the presence of sodium sulfate hydrous/anhydrous crystals (mirabilite and thenardite), and a superficial and variable water table, which may result in the periodic development of a characteristic “fluffy” surface derived from salt precipitation-dissolution processes. HYSPLIT model simulation estimates a deposition maximum near the sources (of about 2.5 kg/ha/yr), and a decreasing trend from the emission area outwards, except for the relative secondary maximum modeled over the mountain ranges in southern Bolivia and northern Argentina due to an orographic effect. The 2009 total deposition of salt dust generated in Mar Chiquita was estimated at 6.5 million tons.

The Taklimakan Desert in Northwest China is the major source of dust storms in China. The northeast edge of this desert is a typical arid area which houses a fragile oasis eco-environment. Frequent dust storms cause harmful effects on the oasis ecosystem and negative impacts on agriculture, transportation, and human health. In this study, the major source region, transport pathway, and the potential contribution of dust storms to particulate air pollution were identified by using both trajectory analysis and monitoring data. To assess the source regions of dust storms, 48 h backward trajectories of air masses arriving at the Bugur (Luntai) County, which is located at the northeast edge of Taklimakan Desert, China on the dusty season (spring) and non-dusty month (August, representing non-dusty season) in the period of 1999–2013, were determined using Hybrid Single Particle Lagrangian Integrated Trajectory model version 4 (HYSPLIT 4). The trajectories were categorized by k-means clustering into 5 clusters (1a–5a) in the dusty season and 2 clusters (1b and 2b) in the non-dusty season, which show distinct features in terms of the trajectory origins and the entry direction to the site. Daily levels of three air pollutants measured at a station located in Bugur County were analyzed by using Potential Source Contribution Function (PSCF) for each air mass cluster in dusty season. The results showed that TSP is the major pollutant, with an average concentration of 612 µg/m3, as compared to SO2 (23 µg/m3) and NO2 (32 µg/m3) in the dusty season. All pollutants were increased with the dust weather intensity, i.e., from suspended dust to dust storms. High levels of SO2 and NO2 were mostly associated with cluster 1a and cluster 5a which had trajectories passing over the anthropogenic source regions, while high TSP was mainly observed in cluster 4a, which has a longer pathway over the shifting sand desert area. Thus, on strong dust storm days, not only higher TSP but also higher SO2 and NO2 levels were observed as compared to normal days. The results of this study could be useful to forecast the potential occurrence of dust storms based on meteorological data. Research focusing on this dust-storm-prone region will help to understand the possible causes for the changes in the dust storm frequency and intensity, which can provide the basis for mitigation of the negative effects on human health and the environment.

Global vegetation growth is dynamically influenced and regulated by hydrological processes. Understanding vegetation responses to terrestrial water storage (TWS) dynamics is crucial for predicting ecosystem resilience and guiding water resource management under climate change. This study investigated global vegetation responses to a terrestrial water storage anomaly (TWSA) using NDVI and TWSA datasets from January 2004 to December 2023. We proposed a Pearson-ACF time lag analysis method that combined dynamic windowing and enhanced accuracy to capture spatial correlations and temporal lag effects in vegetation responses to TWS changes. The results showed the following: (1) Positive NDVI-TWSA correlations were prominent in low-latitude tropical regions, whereas negative responses occurred mainly north of 30°N and in South American rainforest, covering 38.96% of the global vegetated land. (2) Response patterns varied by vegetation type: shrubland, grassland, and cropland exhibited short lags (1–4 months), while tree cover, herbaceous wetland, mangroves, and moss and lichen typically presented delayed responses (8–9 months). (3) Significant bidirectional Granger causality was identified in 16.39% of vegetated regions, mainly in eastern Asia, central North America, and central South America. These findings underscored the vital role of vegetation in the global water cycle, providing support for vegetation prediction, water resource planning, and adaptive water management in water-scarce regions.

Chemical characteristics of atmospheric PM2.5 loads during air pollution episodes in Giza, Egypt

The “dust belt” region extending from the western Sahara to the Gobi Desert frequently generates severe dust storms that cause hazardous air quality and disrupt daily activities. Dust storm management systems with proactive mitigation strategies can minimize the detrimental impacts of dust storms. This study applies the HYSPLIT model to simulate dust storms in Saudi Arabia, specifically targeting the eastern region. The study’s main objective is to calibrate and validate the model’s dust storm prediction module for the eastern region of Saudi Arabia. The validated HYSPLIT model, with optimized parameters such as threshold friction velocity, particle release rate, and dry deposition velocity from model calibration studies, showed a strong linear correlation between measured and predicted values. It achieved an R2 of 0.9965, indicating excellent model accuracy. The main findings of the source apportionment approach, employing air particle backward trajectories and frequency analyses, indicated that the northern regions, specifically Iraq and Syria, were the primary sources of the severe dust storms observed in the receptor area. The outcomes of this study will be a reference for future research aimed at improving dust storm management systems and selecting sites for tree-planting campaigns under the “Saudi & Middle East Green Initiatives”.

Five dust storms that occurred in 2008 (15 March, 11 April, 28 April, 25, May and 26 June) in addition to the many sand dunes disseminated in the Western Desert of Iraq are sampled. The worse dust storm that occurred in Iraq in 11 April, 2008 covered 75% of the Iraq area and deposited 6.9 million tons approximately as a total weight of fallout during just 8 h, declining temperature 6°C. During the episodes of dust storms, visibility decreased enormously, no more than 30 m. Many people were taken to hospitals after sustaining breathing problems. Some of them died. Clay fraction is the dominant part in the dust storms forming 70% besides a little silt (20.6%) and sand (9.4%), then classified as mature arkose of clay to sandy clay, whereas sand dunes are formed from 72.7% sand, 25.1% silt and 2.19% clay, then classified as mature arkose of silty sand. Sand dunes have much maturity. Mineralogical composition of dust storms and sand dunes are Quartz (49.2%, 67.1%), feldspar (4.9%, 20.9%), calcite (38%, 5%), gypsum (4.8%, 0.4%), dolomite (0.8%, 1%) and heavy minerals (3.2%, 6.6%), respectively. Heavy mineral suites in the dust storms are represented by zircon, pyroxene, hornblende, chlorite and magnetite; whereas the sand dunes are represented by zircon, tourmaline, garnet and pyroxene, concentrated within sand fraction. Heavy minerals according to satellite images revealed the dry land of Sahara Desert in North Africa and the Arabian Peninsula as well as Syria and Jordan were a major source of the dust storms that have occurred in Asia, including Iraq.

Rare earth elements of aeolian deposits in Northern China and their implications for determining the provenance of dust storms in Beijing

Brown carbon (BrC) consists of those organic compounds in atmospheric aerosols that absorb solar radiation and may play an important role in planetary radiative forcing and climate. However, little is known about the production and loss mechanisms of BrC in the atmosphere. Here, we study how the light absorptivity of BrC from wood smoke and secondary BrC generated from the reaction of ammonium sulfate with methylglyoxal changes under photolytic aging by UVA radiation in the aqueous phase. Owing to its chemical complexity, BrC is separated by molecular weight using size exclusion chromatography, and the response of each molecular weight fraction to aging is studied. Photolytic aging induced significant changes in the light absorptivity of BrC for all molecular weight fractions; secondary BrC was rapidly photoblenched, whereas for wood smoke BrC, both photoenhancement and photobleaching were observed. Initially, large biomass burning BrC molecules were rapidly photoenhanced, followed by slow photolysis. As a result, large BrC molecules dominated the total light absorption of aged biomass burning BrC. These experimental results further support earlier observations that large molecular weight BrC compounds from biomass burning can be relatively long-lived components in atmospheric aerosols, thus more likely to have larger impacts on aerosol radiative forcing and could serve as biomass burning tracers.

Introduction: Many countries encounter dust storms phenomenon that is one of the meteorological problems leading to many disturbances. Materials and methods: Although the dust storm is historically recorded as an old event in some provinces of Iran, but it becomes a new event in some parts such as Ilam province. Results: After statistical investigation of dust storms in Ilam province, the dust storm from 3td to 6th July 2016 are studied. The source of this dust storm was the eastern areas of Syria and central Iraq base on the satellite images, the outputs of HYSPLIT and WRF-Chem models. Conclusion: Model outputs in intensity of surface dust concentration of MACC-ECMWF, NASA-GEOS, NCEP-NGAC, NMMB-BSC, and BSCDREAM8b models are compared to the observation data in Ilam city and results show that NASA-GEOS model has better performance. In display of dust dispersion on Iran, the middle of all models is more compatible with reality.

Dust storms are important phenomena over large regions of the arid and semi-arid areas of the Middle East. Due to the influences of dust aerosols on climate and human daily activities, dust detection plays a crucial role in environmental and climatic studies. Detection of dust storms is critical to accurately understand dust, their properties and distribution. Currently, remotely sensed data such as MODIS (Moderate Resolution Imaging Spectroradiometer) with appropriate temporal and spectral resolutions have been widely used for this purpose. This paper investigates the capability of two physical-based methods, and random forests (RF) classifier, for the first time, to detect dust storms using MODIS imagery. Since the physical-based approaches are empirical, they suffer from certain drawbacks such as high variability of thresholds depending on the underlying surface. Therefore, classification-based approaches could be deployed as an alternative. In this paper, the most relevant bands are chosen based on the physical effects of the major classes, particularly dust, cloud and snow, on both emissive infrared and reflective bands. In order to verify the capability of the methods, OMAERUV AAOD (aerosol absorption optical depth) product from OMI (Ozone Monitoring Instrument) sensor is exploited. In addition, some small regions are selected manually to be considered as ground truth for measuring the probability of false detection (POFD) and probability of missing detection (POMD). The dust class generated by RF is consistent qualitatively with the location and extent of dust observed in OMERAUV and MODIS true colour images. Quantitatively, the dust classes generated for eight dust outbreaks in the Middle East are found to be accurate from 7% and 6% of POFD and POMD respectively. Moreover, results demonstrate the sound capability of RF in classifying dust plumes over both water and land simultaneously. The performance of the physical-based approaches is found weaker than RF due to empirical thresholds that are not always true.

Identification of dust storm source areas in West Asia using multiple environmental datasets