ABSTRACT
This study utilized MODIS true color satellite imagery to analyse blowing sand and dust events dynamics in the Middle East from 2010 to 2021, focusing on Syria, Iraq, and Jordan. A total of 4923 dust point sources were detected, with a significant concentration (~90 %) located within the Tigris-Euphrates Basin (Nearest Neighbor Ratio = 0.41, Ñ < 0.001). Land cover analysis revealed that bare land, comprising most of the study area, was the predominant source of dust emissions. Wetlands, though only constituting about 1 % of the area, showed the highest frequency of dust sources per unit area, highlighting their role as critical dust emission hotspots. The study emphasizes the impact of drought and anthropogenic factors, such as poor land management, on blowing dust intensity. It suggests the necessity of strategic land management practices, including re-vegetation of arid areas, reducing soil exposure, and implementing wind erosion control measures. To effectively address the transboundary nature of dust emissions, the findings underscore the importance of fostering regional cooperation through mechanisms such as shared environmental monitoring and data exchange platforms, joint management of cross-border natural resources, and collaborative policy making.
ABSTRACT
Dust models are essential for understanding the impact of mineral dust on Earth's systems, human health, and global economies, but dust emission modelling has large uncertainties. Satellite observations of dust emission point sources (DPS) provide a valuable dichotomous inventory of regional dust emissions. We develop a framework for evaluating dust emission model performance using existing DPS data before routine calibration of dust models. To illustrate this framework's utility and arising insights, we evaluated the albedo-based dust emission model (AEM) with its areal (MODIS 500 m) estimates of soil surface wind friction velocity (us∗) and common, poorly constrained grain-scale entrainment threshold (u∗ts) adjusted by a function of soil moisture (H). The AEM simulations are reduced to its frequency of occurrence, P(us∗>u∗tsH). The spatio-temporal variability in observed dust emission frequency is described by the collation of nine existing DPS datasets. Observed dust emission occurs rarely, even in North Africa and the Middle East, where DPS frequency averages 1.8 %, (~7 days y-1), indicating extreme, large wind speed events. The AEM coincided with observed dust emission ~71.4 %, but simulated dust emission ~27.4 % when no dust emission was observed, while dust emission occurrence was over-estimated by up to 2 orders of magnitude. For estimates to match observations, results showed that grain-scale u∗ts needed restricted sediment supply and compatibility with areal us∗. Failure to predict dust emission during observed events, was due to us∗ being too small because reanalysis winds (ERA5-Land) were averaged across 11 km pixels, and inconsistent with us∗ across 0.5 km pixels representing local maxima. Assumed infinite sediment supply caused the AEM to simulate dust emission whenever P(us∗>u∗tsH), producing false positives when wind speeds were large. The dust emission model scales of existing parameterisations need harmonising and a new parameterisation for u∗ts is required to restrict sediment supply over space and time.
ABSTRACT
Establishing mineral dust impacts on Earth's systems requires numerical models of the dust cycle. Differences between dust optical depth (DOD) measurements and modelling the cycle of dust emission, atmospheric transport, and deposition of dust indicate large model uncertainty due partially to unrealistic model assumptions about dust emission frequency. Calibrating dust cycle models to DOD measurements typically in North Africa, are routinely used to reduce dust model magnitude. This calibration forces modelled dust emissions to match atmospheric DOD but may hide the correct magnitude and frequency of dust emission events at source, compensating biases in other modelled processes of the dust cycle. Therefore, it is essential to improve physically based dust emission modules. Here we use a global collation of satellite observations from previous studies of dust emission point source (DPS) dichotomous frequency data. We show that these DPS data have little-to-no relation with MODIS DOD frequency. We calibrate the albedo-based dust emission model using the frequency distribution of those DPS data. The global dust emission uncertainty constrained by DPS data (±3.8 kg m-2 y-1) provides a benchmark for dust emission model development. Our calibrated model results reveal much less global dust emission (29.1 ± 14.9 Tg y-1) than previous estimates, and show seasonally shifting dust emission predominance within and between hemispheres, as opposed to a persistent North African dust emission primacy widely interpreted from DOD measurements. Earth's largest dust emissions, proceed seasonally from East Asian deserts in boreal spring, to Middle Eastern and North African deserts in boreal summer and then Australian shrublands in boreal autumn-winter. This new analysis of dust emissions, from global sources of varying geochemical properties, have far-reaching implications for current and future dust-climate effects. For more reliable coupled representation of dust-climate projections, our findings suggest the need to re-evaluate dust cycle modelling and benefit from the albedo-based parameterisation.
ABSTRACT
Exploring the effects of drought and land use/land cover (LULC) on aeolian dust emission is important to enhance dust models to account for anthropogenic land surface change. Hitherto, there has been no systematic effort to quantitatively estimate associations between LULC and drought with the number of dust point sources as a surrogate for emission on both local and global levels. Previously, we created a dataset of dust emission point sources in the southwestern United States (U.S.) during the years 2001-2016, including a period of extreme drought. However, that work did not investigate the effects of drought on the detected dust point sources. Here, we used that dataset to test the hypothesis that there is a statistically significant association between drought level and LULC that may contribute to the number of dust point sources in the Southern Great Plains and Chihuahuan Desert regions of the U.S. The spatio-temporal analysis showed that the geographic mean center for all the dust points, as well as the majority of the annual geographic mean centers between 2001 and 2016, is located in the Southern High Plains. Areas suffering from severe to exceptional drought tend to attract the annual geographic mean center of dust points. The chi-square analysis results showed a significant association between land cover type (as defined in the National Land Cover Database) and drought level with the number of dust point sources (χ2 (6) = 45.54, Ñ < 0.001), thus supporting the proposed hypothesis. Results from this study indicate that human activities in dust-prone regions have clear potential to worsen the negative impacts of drought by changing LULC and increasing erodibility in multiple ways. This study paves the way for future efforts that can utilize more data and conduct more robust statistical analysis of the drought-LULC-dust linkage on both regional and global scales.
Subject(s)
Conservation of Natural Resources , Droughts , Dust , Humans , Southwestern United StatesABSTRACT
Despite the widespread media attention of chain-reaction traffic incidents and property damage caused by windblown dust in the U.S. and elsewhere in the world, very few studies have provided in-depth analysis on this issue. Remote sensing and field observations reveal that wind erosion in the southwestern U.S. typically occurs in localized source areas, characterized as "hotspots", while most of the landscape is not eroding. In this study, we identified the spatial and temporal distribution patterns of hotspots that may contribute dust blowing onto highways in the southwestern U.S. We further classified the hotspots for the potential of blowing dust production based upon field observations and wind erosion modeling. Results of land use and land cover show that shrubland, grassland, and cropland accounted for 42%, 31%, and 21% of the overall study area, respectively. However, of the 620 total hotspots identified, 164 (26%), 141 (22%), and 234 (38%) are located on shrubland, grassland, and cropland, respectively. Barren land represented 0.9% of the land area but 8% of the dust hotspots. While a majority of these hotspots are located close to highways, we focused on 55 of them, which are located <1km to adjacent highways and accessible via non-private roads. Field investigations and laboratory analysis showed that soils at these hotspot sites are dominated by sand and silt particles with threshold shear velocities ranging from 0.17-0.78m s-1, largely depending on the land use of the hotspot sites. Dust emission modeling showed that 13 hotspot sites could produce annual emissions >3.79kg m-2, yielding highly hazardous dust emissions to ground transportation with visibility <200m. Results of location, timing, and magnitude of the dust production at the hotspots are critical information for highway authorities to make informed and timely management decisions when wind events strike.
ABSTRACT
Every year in the United States, at least 250,000 deaths are attributed to lack of physical activity. Because of the health benefits of physical activity, national guidelines recommend participation in 30 minutes of accumulated moderate-intensity physical activity such as walking fast on five or more days of the week. However, most Americans fail to achieve this goal and report that their physicians have not counseled them to increase physical activity. Because 84 percent of Americans consult a physician each year, even brief physician counseling that leads to modest activity changes could affect the population's health. Some physicians report that they do not deliver physical activity counseling because of limitations in time, reimbursement, knowledge, confidence, and practical tools. The five A's (Assess, Advise, Agree, Assist, Arrange) model can help physicians deliver brief, individually tailored physical activity messages to patients.