Quantifying the effect of anthropogenic land use change on dust emission is a contentious issue. In this research, 1508 dust point sources were detected in the Southern High Plains and Chihuahuan Desert regions of the United States for 2001-2016, encompassing a period of extreme drought. These points were subjected to quantitative and spatio-temporal analysis. Point pattern analysis showed a significant cluster of these points in West Texas (Nearest Neighbor Ratio = 0.33, р < 0.001) where cultivated lands and grasslands are dominant land cover. Spatial observation suggests that the geographic center of dust points in these regions shifts away from bare soil and shrublands toward grasslands and cultivated lands as drought level increases, while it shifts away from grasslands and cultivated lands towards bare soil and shrublands in cases of no drought. Chi-square test captured a significant association between land use type and drought level on dust emission (χ2 (6) = 47.33, р < 0.001). However, Cramer’s V value (0.13, р < 0.001) indicates that the association captured by the chi-square is weak, suggesting that other factors, perhaps meteorological variables, are at play in the spatial distribution of dust sources in this region. The proportion of dust points differs significantly during severe/exceptional droughts versus no drought or abnormally dry/moderate drought in both cultivated lands and grasslands. The proportion of dust points in bare lands and shrublands, however, did not significantly change between no drought and severe-exceptional drought. These results suggest anthropogenic land use in southwestern U.S. is significantly associated with drought in terms of dust emission. Human activity amplifies of the effects of drought by increasing soil erodibility; thus, adopting land management practices to resist wind erosion is crucial. Further investigations on a global scale should provide more information on this association.

In connection to drought, the southwestern United States is experiencing an increase in blowing dust, an increase in incidence of valley fever, an increase in visibility-related traffic accidents, reduction in solar panel efficiency, and earlier mountain snowmelt. The response of the land surface to the wind is greatly dependent on the proportion of land cover, soil and sediment characteristics, weather conditions, and spatial distribution of vegetation, all factors affecting aeolian processes. Combined use of optical and radar satellite imagery products can provide invaluable benefits in characterizing surface properties of desert playas (ephemeral lakes)- the preferred landform for wind erosion. As a home for high temporal coverage of Landsat optical images and a cloud computing platform, Google Earth Engine (GEE) provides a multi-petabyte catalog of satellite imagery, powerful algorithms, and application programming interface capabilities. Processing and analyzing moderate to high spatial resolution images from Landsat and Sentinel-2 in GEE are crucial resources for extracting contributions of different endmembers to pixel mixtures. Radar images, with the capability to penetrate through clouds, darkness, and rain, have a power to detect the extent and levels of changes in land cover and soil moisture. In this study, we identified the fractional abundance of soil, vegetation, and water endmembers of each pixel of images using the spectral unmixing algorithm in GEE in Lordsburg Playa (New Mexico, USA), which is prone to aeolian erosion. Here, we used Landsat-8 and Landsat-5 at 30 meters spatial resolution and Sentinel-2 Multispectral instrument at 10-20 meters resolution. By employing Interferometric Synthetic Aperture Radar (InSAR) techniques, we explored the changes in the water level of the playa and the possible hot spots of erosion-inducing sediment loading to the playa. In this data recipe, we analyzed a pair of Sentinel-1 images that bracket a monsoon day with high rainfall event and a pair of images representing dry day and monsoon day. The results from this approach clearly show locations prone to the change in phase and displacement due to water and thus sediment loading susceptible to wind.

Dust is a meteorological phenomenon that has a strong impact on the environment, air quality, and human health. In the USA one of the most widely used databases of information on dust events is the Storm Events Database (SED). This project aims to examine the reliability and usefulness of the SED as a source for documenting the climatology of dust storms (DS) across the USA. While SED provides information potentially useful for understanding the frequency, distribution, and importance of DS across the USA, our analysis of DS from 2000 to 2020 shows that many DS were missing while some recorded events of less severe blowing dust (BLDU) in the SED were incorrectly reported as DS. Although the dust records from SED have been widely utilized to study dust related physical and societal issues, the limitations found in this study need to be taken into consideration in future studies.

Inspired by Comrie (2021), we discuss a few issues related to dust storms and Coccidioidomycosis (Valley fever). There is inconsistency in the term “dust storm” as used by science communities, and the dust data from NOAA Storm Events Database are from diverse sources, unsuitable for assessing dust-Coccidioidomycosis relationships. Population exposure to dust or Coccidioides needs to consider the frequency, magnitude, duration, and spatial coverage of dust events. Given abundant evidence that dust storms are a viable driver to transport Coccidioides, it is in best public interest to advocate that dust storms may put people at risk for contracting Valley fever.