Dust Storm Events Research Articles

The Economic Effects of Dust Storm

The Economic Effects of Dust Storm

Investigating the effects of dust storms on morbidity and mortality due to cardiovascular and respiratory diseases: A systematic review.

New epidemiological studies acknowledge the detrimental effects of dust storms on health. The aim of this study was to systematically review the effects of dust storms on the morbidity and mortality rates of cardiovascular and respiratory diseases. The results of this study were obtained based on articles published in English-language journals. For the purpose of this study, all articles published until the end of 2020 based on the search in the “Scopus,” “Web of Science,” and “PubMed” databases were selected. Articles were searched independently by two trained researchers. Dust storms are the cause of many diseases and health-related complications, of which cardiovascular and respiratory diseases are common. It is necessary to recognize and investigate the harmful effects of dust storms to prevent serious harms to human societies. In the reviewed articles, the impact of dust storms on several diseases, including cardiovascular and respiratory diseases, has been analyzed. Most of these articles acknowledge the effect of dust storms on increasing the incidence and mortality rate of these diseases, although in some articles this effect is not statistically significant. Many studies conducted around the world confirm the harmful effects of dust storms on cardiovascular and respiratory diseases, including increase in the number and duration of hospitalizations, as well as increase in mortality and exacerbation of these diseases. However, some studies do not consider the harmful effects of dust storms on the above diseases to be statistically significant.

Analysis of sand and dust storm events over Saudi Arabia in relation with meteorological parameters and ENSO

Sand and dust storm (SDS) events are closely associated with meteorological parameters. This study aims to analyze SDS events in relation to temperature, precipitation, and wind speed. In addition, since El Nino–Southern Oscillation Index (ENSO) cycle has a great impact on precipitation and temperature, the relationship between SDS events and ENSO cycles are also investigated. For this purpose, data for 30 years (1985–2014) from relevant organizations are retrieved and analyzed. Results of the study show that SDS, precipitation, and wind speed have a decreasing trend while temperature has an increasing trend in the KSA during the study period. The results of the study also reveal that SDS events have the highest correlation with temperature and lowest correlation with precipitation. Furthermore, the relationship between SDS events and ENSO shows that El Nino was dominant during the first two decades of the study period while La Nina prevailed in the last decade of the study period. It is envisaged that the outcome of the current endeavor will be very useful for aerosol-related research both at regional and at a global scale.

Effect of Dust Storms on Non-Accidental, Cardiovascular, and Respiratory Mortality: A Case of Dezful City in Iran.

Background:Despite the fact that Iran has been exposed to severe dust storms during the past 2 decades, few studies have investigated the health effects of these events in Iran. This study was conducted to assess the association between dust storms and daily non-accidental, cardiovascular, and respiratory mortality in Dezful City (Khuzestan Province, Iran) during 2014 to 2019.Methods:In this study, mortality, meteorological, and climatological data were obtained from the Dezful University of Medical Sciences, Iranian Meteorological Organization, and Department of Environment in Khuzestan Province, respectively. Days of dust storm were identified based on the daily concentration threshold of particulate matter with an aerodynamic diameter of less than 10 μm (PM10) according to Hoffmanns҆ definition, and then an ecological time-series was used to estimate the short-term effects of dust storms on daily mortality. Statistical analysis was performed using a distributed lag linear model (DLM) and a distributed lag non-linear model (DLNM) packages by R software and the study results were reported as excess mortality.Results:During the study period, 15 223 deaths were recorded, and 139 dust storms occurred in Dezful city. In addition, there was statistically significant excess risk of mortality due to dust storms in Dezful City (mortality in the group under 15 years of age, lag4: 34.17% and 15-64 years of age groups, lag5: 32.19%, lag6: 3.28%), also dust storms had statistically significant effects on respiratory mortality (lag6: 5.49%).Conclusion:The findings of the current study indicate that dust storms increase the risk of mortality with some lags. An evidence-based early warning system may be able to aware the people of the health effects of dust storms.

Statistical Forecast of Daily Maximum Air Temperature in Arid Areas at Summertime

Based on historical observations of summers for the period from 2004 to 2018 with a focus on daily maximum and minimum air temperatures and wind speed recorded at 0600 GMT, a non-linear regression hypothesis is developed for forecasting daily maximum air temperature (Tmax) in arid areas such as Baghdad International airport station, which has a hot climate with no cloud cover or rain. Observations with dust storm events were excluded, thus this hypothesis could be used to predict daily Tmax on any day during summers characterized by fair weather. Using mean annual daily temperature range, daily minimum temperature, and the trend of maximum temperature with wind speed, Tmax was forecasted and then compared to those recorded by meteorological instruments. To improve the accuracy of the hypothesis, daily forecast errors, bias, and mean absolute error were analyzed to detect their characteristics through calculating relative frequencies of occurrence. At the end of this analysis, a value of (-0.45ºC) was added to the hypothesis as a bias term.

Investigating the culturable atmospheric fungal and bacterial microbiome in West Texas: implication of dust storms and origins of the air parcels.

Individuals often experience ailments such as allergies, asthma and respiratory tract infections throughout the year. Weather reports often include estimations of common allergens that can affect these individuals. To describe the local 'atmospheric microbiome' in Lubbock, Texas, USA, we examined the culturable fungal and bacterial microbiome present in the air on calm and dust storm days using internal transcribed spacer (ITS)-1 and 16S rRNA amplicon sequencing, respectively. While some types of airborne fungi were frequently present throughout the year, distinct differences were also observed between calm and dust storm days. We also observed the influence of the origin of air parcels and wind elevation of the air trajectory. The most abundant genera of fungi identified during the study period were Cryptococcus, Aureobasidium, Alternaria, Cladosporium and Filobasidium. This observation was not surprising considering the agricultural intensive environment of West Texas. Interestingly, Cladosporium, a common allergenic mold, was increased during days with dust storm events. The predominant bacterial genera observed were Bacillus, Pseudomonas, Psychrobacter, Massilia and Exiguobacterium. The relative abundance of the psychrophiles, Psychrobacter and Exiguobacterium, was surprising, given the semi-aridity of West Texas. Coupling our observations with back trajectories of the wind (Hybrid Single-Particle Lagrangian Integrated Trajectory models) demonstrated that dust storms, regional anthropogenic activity and origin of air parcels are important influences on the diversity and temporal presence of the atmospheric microbiome.

Efficient Heterogeneous Formation of Ammonium Nitrate on the Saline Mineral Particle Surface in the Atmosphere of East Asia during Dust Storm Periods.

To understand the chemical evolution of dust in the current East Asian atmosphere, the chemistry of PM2.5 and size-resolved aerosols in Shanghai, China, during the 2019 dust storm event was investigated. Our results showed that concentrations of SO42- in the city during the event highly correlated with Ca2+ and Na+ due to the direct emissions of CaSO4 and Na2SO4 from the upwind deserts. In contrast, during the event, NO3- linearly correlated with NH4+ at a molar ratio close to 1:1, and both almost entirely stayed in coarse particles, suggesting they accumulated on the dust surface as NH4NO3. Based on the field observations and laboratory smog chamber simulations, we found that NO2 and O3 in Shanghai during the dust period reacted to form N2O5, which subsequently hydrolyzed into HNO3 on the surface of saline mineral dusts (e.g., CaSO4 and Na2SO4) and was further neutralized by NH3 as NH4NO3. The relative abundances of NO3- and NH4+ in Shanghai during the dust event were notably higher than those a decade ago, indicating that this heterogeneous formation of NH4NO3 on dust was enhanced by the abundantly coexisting NOx, O3, and NH3 in the current East Asian atmosphere, which should be considered in future modeling studies.

Monitoring and Prediction of Dust and Investigating its Environmental Impacts in the Western Half of Iran and the Eastern Borders of Turkey and Iraq, Using Remote Sensing and GIS

In recent years, the damage caused by dust in different parts has increased dramatically. There are many dusty areas around the world. One of these regions in the southwest of Asia is Iran. The purpose of this study is to model and predict the hazardous dust phenomenon in dusty regions of Iran. For this purpose, dust data from 28 stations of intense dusty areas in Iran were collected at 29-year time intervals. Then, adaptive-network-based fuzzy inference systems (ANFIS) and the core of the radial base function (RBF) models were used for modelling and then the two models were compared to the future exact prediction. Finally, the dust data for all stations are prioritized using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) multivariate decision-making model and output data are mapped by ArcGIS software. According to the results of this study, RMSE of the ANFIS model was 10.5 and the RBF model was 2.18. Therefore, the accuracy of RBF was more than the ANFIS model for prediction of the dust simulated in years, so the RBF model was used to predict. Based on the dust data obtained from the output of the RBF model in both the mean and maximum of dust abundance, the western and southwestern stations of the study areas were more exposed to dust in the future. Also, according to TOPSIS model, in the prioritization of stations involved with dust for simulated years, Abadan, Masjed Soleyman and Ahwaz were ranked by the amount of 100, 95% and 81%, respectively. Dust is one of the atmospheric phenomena that have adverse environmental effects and consequences. Dust storms have detrimental effects on the health and economy of society and climate change. Understanding the nature, origin and effects of dust storms plays an important role in determining its control methods.

Seawater Pb concentration and isotopic composition response to daily time scale dust storms in the Gulf of Aqaba, Red Sea

Lead (Pb) is a primary tracer of natural and anthropogenic processes in the marine environment, with atmospheric deposition being one of its main sources to open ocean surface waters. However, the impact of short-term (daily) dust storms on the oceanic water column is poorly constrained due to the typically low sampling temporal resolution in deep open ocean settings. The Gulf of Aqaba (GoA), northern Red Sea, is a deep oligotrophic water body surrounded by hyper-arid deserts with no major tributaries, and hence its surface waters receive limited terrigenous input, except from settling atmospheric dust particles. The GoA is highly accessible and therefore provides the opportunity to study the dynamics of seawater Pb chemistry across abrupt and short periods of enhanced atmospheric deposition.Here, we report a highly resolved time series of vertical profiles of dissolved Pb concentrations and isotopic compositions across daily-timescale dust storm events that occurred during 2018. GoA Pb concentrations range between 19 and 85 pmol kg−1, and the isotopic compositions of 206Pb/207Pb and 208Pb/206Pb are in the range of 1.163–1.190 and 2.062–2.093, respectively. These compositions reflect a mixture of multiple end members: seafloor sediments and open Red Sea waters, which modulate the long-term deep-water composition of GoA Pb, and settling aerosols, which shift the seawater composition towards anthropogenic values. The results show that dust storms impose strong perturbations of seawater compositions towards the anthropogenic aerosols end member, inducing increases of up to 54% in the Pb inventory in the upper water column. We propose a short-term dissolution-scavenging mechanism, whereby upon dust-seawater impact, the majority of the aerosol's soluble anthropogenic phases rapidly dissolve. The peak in the aerosol derived isotopic shift in the mixed layer is reached after 3–4 days. Simultaneously, Pb is re-adsorbed onto the sinking dust mineral particulates. Post dust storm Pb leaching and scavenging rates are modeled, yielding quantitative constraints on the connection between increasing dust loads and seawater Pb concentrations and isotopic compositions. Our findings demonstrate the short-term variable Pb response to dust storms and should be applied when interpreting open ocean surface water Pb patterns.

Human Perception on the Effects of Dust Storm on the Health of Residents’ of Damaturu Metropolis, Yobe State

Dust storms are among nature’s most violent and unpredictable phenomena. High winds lift dirt or sand particles into the air, unleashing a turbulent, suffocating cloud that reduces visibility to almost nothing in a matter of seconds and cause property damage, injuries, and deaths. Damaturu Metropolis has been experiencing dust storm most frequently more especially during the onset of the rainy season. The study examined the human perception on the effects of dust storm on the health of residents’ of Damaturu metropolis with the aim of identifying and examining the causes, frequency, effects of dust storm on human health and socio-economic life of resident and their coping strategies. A total of one hundred (100) copies of interview schedules were administered to residents of Damaturu metropolis. The result indicated that desertification and deforestation are the main cause of dust storm and the frequency of its occurrence is more often and it occurs most frequently in the second quarter of the year at the onset of the rainy season. Its duration of occurrence ranges from thirty minutes to an hour, although sometimes it varies. The identified health effects associated with dust storms include asthma, allergic reaction, injury and Road Traffic Accident (R.T.A). The socio-economic and livelihood of the community is equally affected during the dust storm episodes. The coping mechanisms adopted by residents during the dust storm, includes closing doors and windows and using face masks. The study recommended that residents should remain indoors, wear face masks, plant trees and cover crops, among others.

Determination of Lidar Ratio for Major Aerosol Types over Western North Pacific Based on Long-Term MPLNET Data

East Asia is the most complex region in the world for aerosol studies, as it encounters a lot of varieties of aerosols, and aerosol classification can be a challenge in this region. In the present study, we focused on the relationship between aerosol types and aerosol optical properties. We analyzed the long-term (2005–2012) data of vertical profiles of aerosol extinction coefficients, lidar ratio (Sp), and other aerosol optical properties obtained from a NASA Micro-Pulse Lidar Network and Aerosol Robotic Network site in northern Taiwan, which frequently receives Asian continental outflows. Based on aerosol extinction vertical profiles, the profiles were classified into two types: type 1 (single-layer structure) and type 2 (two-layer structure). Fall season (October–November) was the prevailing season for the Type 1, whereas type 2 mainly happened in spring (March–April). In type 1, air masses normally originated from three regional sectors, i.e., Asia continental (AC), Pacific Ocean (PO), and Southeast Asia (SA). The mean Sp values were 39 ± 17 sr, 30 ± 12 sr, and 38 ± 18 sr for the AC, PO, and SA sectors, respectively. The Sp results suggested that aerosols from the AC sector contained dust and anthropogenic particles, and aerosols from the PO sector were most likely sea salts. We further combined the EPA dust event database and backward trajectory analysis for type 2. Results showed that Sp was 41 ± 14 sr and 53 ± 21 sr for dust storm and biomass-burning events, respectively. The Sp for biomass-burning events in type 2 showed two peaks patterns. The first peak occurred within range of 30–50 sr corresponding to urban pollutant, and the second peak occurred within range of 60–80 sr in relation to biomass burning. Finally, our study summarized the Sp values for four major aerosol types over northern Taiwan, viz., urban (42 ± 18 sr), dust (34 ± 6 sr), biomass-burning (69 ± 12 sr), and oceanic (30 ± 12 sr). Our findings provide useful references for aerosol classification and air pollution identification over the western North Pacific.

Fully Interactive and Refined Resolution Simulations of the Martian Dust Cycle by the MarsWRF Model

AbstractThe MarsWRF model is set up with fully interactive dust at 5° × 5° and 2° × 2 resolution. The latter allows for a better representation of topography and other surface properties. An infinite reservoir of surface dust is assumed for both resolutions. For 5° × 5°, surface dust lifting by wind stress takes place over broad areas, occurring in about 20% of the model's grid cells. For 2° × 2°, it is more spatially restricted, occurring in less than 5% of the grid cells, and somewhat reminiscent of the corridors Acidalia‐Chryse, Utopia‐Isidis, and Arcadia‐West of Tharsis. The onset times of major dust storms—large regional storms or global dust storm events (GDEs)—do not exhibit much interannual variability, typically occurring at around Ls 260°. However, their magnitude does show significant interannual variability—with only small regional storms in some years, large regional storms in others, and some years with GDEs—owing to the interaction between major dust lifting regions at low latitudes. The latter is consistent with observed GDEs having several active dust lifting centers. The agreement between the model's surface dust distribution and observation‐based dust cover index maps is potentially better for 2° × 2°. For the latter, there is also significant surface dust lifting by wind stress in the aphelion season that is largely confined to the Hellas basin. It has a recurring time pattern of 2–7 sols, possibly resulting from the interaction between midlatitude baroclinic systems and local downslope flows.

An improved dust identification index (IDII) based on MODIS observation

ABSTRACT Satellite remote sensing may serve as an ideal technique to detect dust storms for high temporal and spatial scales. In this paper, we propose an improved dust identification index (IDII) based on Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. The IDII algorithm was used to monitor 129 dust storm events over the West Asia region from 2016 to 2018. Ground-based observations of synoptic stations, RGB images, and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), and Ozone Monitoring Instrument (OMI) were implemented for validating IDII algorithm. In addition, the performance of the proposed algorithm was compared with the Global Dust Detection Index (GDDI). The results show that the accuracy (Ac), Probability Of Correct positive Detection (POCD), and Probability Of False-positive Detection (POFD) for the IDII and GDDI are 82%, 85%, 33%, and 71%, 74%, 27%, respectively. Also over the water as a challenging object, it is clearly seen that the IDII performs much better than GDDI method. Our results suggest that the proposed approach can deal with the common limitations of dust detection algorithms, i.e. dust detection over different surfaces (land and water), seasonal changes, and similarity between dust and other objects like clouds.

Wind flow and sediment flux profiles for vegetated surfaces in a wind tunnel and field-scale windbreak

Despite many studies describing wind speed and sediment flux profiles in various situations, wind tunnel observations in the presence of live vegetation are infrequent and rarely combined with field measurements. To investigate the structure of wind speed and sediment flux profiles in morphologically different vegetation and various plant densities, wind velocity and sediment flux profiles were obtained over a multi-row windbreak in an arid environment and over unplanted surfaces and canopies of two types of plants in a wind tunnel. Although the two plant types in the wind tunnel have different morphology, the profiles of wind velocity and sediment flux showed structures similar to those for other plant types reported in previous studies which indicates that profile structures are likely common for homogeneous canopies even with different plant morphology and in various wind velocities. The horizontal profiles of wind speed and vertical profiles of sediment flux in the wind tunnel closely matched the profiles in the field-scale windbreak. The vertical profiles of wind speed within the wind-tunnel vegetation exhibited a deflection which was not reflected within the multi-row windbreak where profiles were nearly uniform without inflections, which was likely a response to different plant spacing and patterns. Wind-tunnel vegetation reduced wind speed significantly even in low density. Lowest wind speeds were observed beyond the wind-tunnel canopies and at the beginning of the windbreak. No difference in the size of the sheltered zone is observed between the two plant types in the wind tunnel either in different wind velocities or in various density configurations, or within the windbreak in various wind speeds and different dust storm events. The sheltered area was greater for the windbreak than for the wind-tunnel canopies, suggesting that wind tunnel studies may under-estimate the sheltered area afforded by a multi-row windbreak.

Influence of chemical aging on physico-chemical properties of mineral dust particles: A case study of 2016 dust storms over Delhi

The physico-chemical properties of dust particles collected During Dust Storm (DDS) and After Dust Storm (ADS) events were studied using Scanning Electron Microscope coupled with Energy Dispersive X-ray Spectroscopy (SEM-EDS), X-ray Fluorescence Spectroscopy (XRF) and X-ray Photoelectron Spectroscopy (XPS). Morphological and compositional change in dust particles were observed as they react with the anthropogenic pollutants present in the urban environment. The calcite rich particles were observed to transform into calcium chloride, calcium nitrate, and calcium sulfate on reacting with the chlorides, nitrates, and sulfates present in the urban atmosphere. The frequency distributions of Aspect Ratio (AR) for the DDS and ADS particles were observed to be bimodal (mode peaks at 1.2 and 1.5) and monomodal (mode peak at 1.1), respectively. The highly irregular shaped solid dust particles were observed to transform into nearly spherical semisolid particles in the urban environment. XPS analysis confirms the high concentration of oxides, nitrates, and chlorides at the surface of ADS samples which show the signatures of mineral dust particles aging. Species with a high value of imaginary part of refractive index (like Cr metal, Fe metal, Cr2O3, FeO, Fe2O3) were observed at the surface of dust particles. At 550 nm wavelength, the light-absorbing potential of the observed species along with black carbon (BC) was found to vary in the order; Cr metal > Fe metal > Cr2O3> FeO > BC > Fe2O3> FeOOH. The presence of the aforementioned species on the surface of ADS particles will tremendously affect the particle optical and radiative properties compared to that of DDS particles. The present work could reduce the uncertainty in the radiation budget estimations of mineral dust and assessment of their climatic impacts over Delhi.

Transport of aerosols and trace gases during dust and crop-residue burning events in Indo-Gangetic Plain: Influence on surface ozone levels over downwind region

Abstract The present study addresses the influence of long-range transport from dust storm (event 1) and crop-residue burning (event 2) sources over Indo-Gangetic Plain (IGP) using ground-based measurements and satellite observations. In the present study, the spatial distribution and temporal variation of ambient particulate matter (PM) were assessed at 15 air quality monitoring stations situated in Rajasthan, north-western-Indo-Gangetic Plain (NW-IGP) and downwind region. During the dust event, the daily average mass concentrations of PM2.5 and PM10 were 1.2–3.3 and 2.2–4.6 times higher than the National Ambient Air Quality Standards (NAAQS 60 μg/m3 for PM2.5 and 100 μg/m3 for PM10) across stations in the vicinity of the Thar Desert. Stations in NW-IGP showed enhancement in PM2.5 and PM10 during crop-residue burning period. Agra being a downwind site was influenced by both the events and enhancement in PM levels was observed, however ozone (O3) showed different variations during event 1 and 2. During the dust event, 6.1% reduction in the mean O3 level compared to the study period was found while a significant enhancement (15.1%) during event 2 was observed at Agra. To determine the possible reasons for different O3 trends, the variation of O3 precursors carbon monoxide (CO) and nitrogen oxides (NOx) along with the meteorological parameters was also assessed. CO and NOx levels during event 1 were reduced similar to O3 whereas during event 2 an enhancement in CO and NOx levels was observed. Satellite observations and backward air-mass trajectories suggested transport of aerosols from Thar Desert resulted in reduced O3 levels during dust event while transport of O3 precursors enhanced photochemical production of O3 during crop-residue burning period at Agra.

Classification of aerosols over Saudi Arabia from 2004–2016

Knowledge of aerosol size and composition is very important for investigating the radiative forcing impacts of aerosols, distinguishing aerosol sources, and identifying harmful particulate types in air quality monitoring. The ability to identify aerosol type synoptically would greatly contribute to the knowledge of aerosol type distribution at both regional and global scales, especially where there are no data on chemical composition. In this study, aerosol classification techniques were based on aerosol optical properties from remotely-observed data from the Ozone Monitoring Instrument (OMI) and Aerosol Robotic Network (AERONET) over Saudi Arabia for the period 2004–2016 and validated using data from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO). For this purpose, the OMI-based Aerosol Absorption Optical Depth (AAOD) and Ultra-Violet Aerosol Index (UVAI), and AERONET-based AAOD, Ångström Exponent (AE), Absorption Ångström Exponent (AAE), Fine Mode Fraction (FMF), and Single Scattering Albedo (SSA) were obtained. Spatial analysis of the satellite-based OMI-AAOD showed the dominance of absorbing aerosols over the study area, but with high seasonal variability. The study found significant underestimation by OMI AAOD suggesting that the OMAERUV product may need improvement over bright desert surfaces such as the study area. Aerosols were classified into (i) Dust, (ii) Black Carbon (BC), and (iii) Mixed (BC and Dust) based on the relationships technique, between the aerosol absorption properties (AAE, SSA, and UVAI) and size parameters (AE and FMF). Additionally, the AE vs. UVAI and FMF vs. UVAI relationships misclassified the aerosol types over the study area, and the FMF vs. AE, FMF vs. AAE and FMF vs. SSA relationships were found to be robust. As expected, the dust aerosol type was dominant both annually and seasonally due to frequent dust storm events. Also, fine particulates such as BC and Mixed (BC and Dust) were observed, likely due to industrial activities (cement, petrochemical, fertilizer), water desalination plants, and electric energy generation. This is the first study to classify aerosol types over Saudi Arabia using several different aerosol property relationships, as well as over more than one site, and using data over a much longer time-period than previous studies. This enables classification and recognition of specific aerosol types over the Arabian Peninsula and similar desert regions.

Retrievals of aerosol layer height during dust events over the taklimakan and gobi desert

This study retrieves and evaluates aerosol layer height (ALH) during spring dust storm events observed over the Taklimakan and Gobi Desert. A novel strategy is proposed to identify single- or multi-layered aerosol scenarios in wide-swath passive sensor images from Ozone Mapping and Profiler Suite (OMPS) and Moderate Resolution Imaging Spectroradiometer (MODIS), aided by profiles of Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), and use different sets of look-up tables (LUTs) to retrieve ALH accordingly. The strategy combines the advantage of two independent methods–the ability to expand three-dimensional atmospheric structure using the spectral radiance matching (SRM) method, and the ability to estimate ALH over a long distance using the aerosol single-scattering albedo and height estimation (ASHE) method. From 2012 to 2016, ALH during 4 severe dust storms is retrieved over the Taklimakan and Gobi Desert. Analysis shows that the average height and occurrence frequency retrieved fall in the same range with results from previous studies. Comparisons with ALH inferred from CALIOP profiles indicate that the combined ASHE-SRM method has improved the overall performance. The estimated ALH correlates well (R = 0.68) with those measured by CALIOP, except for areas with potential cloud contamination, but slightly overestimated over the multi-layered area; the mean absolute difference (MAD) is 1.34±1.02 km. The reason of general overestimation is exanimated with a case study of dust storm occurred on April 23, 2012. With additional ALH information retrieved over broad area, the ASHE-SRM method has great potential to improving our understanding of aerosols and related impacts.

Introducing the causes, origins and effects of dust in Iran

This study provides an overview of the cause, source, origin and effects of dust storms. Desertification and climate change are the most important envi- ronmental challenges in arid regions of the world, and their effects, includ- ing air pollution, affect people all over the world. Although air pollution is a harmful and pathogenic phenomenon for all people and at all ages, a wide range of people, including the elderly, pregnant women, children and the sick, are more vulnerable. Dust is one of the environmental problems that ulti- mately causes respiratory and skin diseases in humans. Iran is also one of the countries in the arid and semi-arid region, which is surrounded by dust storms. The internal source of dust storms includes southwest, east and cen- tral Iran. In general, there are two approaches to environmental change. The first approach is to ignore these changes and continue the current situation, which will only result in more environmental degradation. Another approach is to identify these changes from the past to the present and to develop an environmental management program to control these changes and to plan to improve the environmental situation.

Joint Modeling of Severe Dust Storm Events in Arid and Hyper Arid Regions Based on Copula Theory: A Case Study in the Yazd Province, Iran

Natural disasters such as dust storms are random phenomena created by complicated mechanisms involving many parameters. In this study, we used copula theory for bivariate modeling of dust storms. Copula theory is a suitable method for multivariate modeling of natural disasters. We identified 40 severe dust storms, as defined by the World Meteorological Organization, during 1982–2017 in Yazd province, central Iran. We used parameters at two spatial vertical levels (near-surface and upper atmosphere) that included surface maximum wind speed, and geopotential height and vertical velocity at 500, 850, and 1000 hPa. We compared two bivariate models based on the pairs of maximum wind speed–geopotential height and maximum wind speed–vertical velocity. We determined the bivariate return period using Student t and Gaussian copulas, which were considered as the most suitable functions for these variables. The results obtained for maximum wind speed–geopotential height indicated that the maximum return period was consistent with the observed frequency of severe dust storms. The bivariate modeling of dust storms based on maximum wind speed and geopotential height better described the conditions of severe dust storms than modeling based on maximum wind speed and vertical velocity. The finding of this study can be useful to improve risk management and mitigate the impacts of severe dust storms.