Wind erosion, transport and deposition of particulate matter can have significant impacts on the environment. It is observed that about 40% of the global land area and 30% of the earth's population lives in semiarid environments which are especially susceptible to wind erosion and airborne transport of contaminants. With the increased desertification caused by land use changes, anthropogenic activities and projected climate change impacts windblown dust will likely become more significant. An important anthropogenic source of windblown dust in this region is associated with mining operations including tailings impoundments. Tailings are especially susceptible to erosion due to their fine grain composition, lack of vegetative coverage and high height compared to the surrounding topography. This study is focused on emissions, dispersion and deposition of windblown dust from the Iron King mine tailings in Dewey-Humboldt, Arizona, a Superfund site. The tailings impoundment is heavily contaminated with lead and arsenic and is located directly adjacent to the town of Dewey-Humboldt. The study includes in situ field measurements, computational fluid dynamic modeling and the development of a windblown dust deposition forecasting model that predicts deposition patterns of dust originating from the tailings impoundment. Two instrumented eddy flux towers were setup on the tailings impoundment to monitor the aeolian and meteorological conditions. The in situ observations were used in conjunction with a computational fluid dynamic (CFD) model to simulate the transport of windblown dust from the mine tailings to the surrounding region. The CFD model simulations include gaseous plume dispersion to simulate the transport of the fine aerosols, while individual particle transport was used to track the trajectories of larger particles and to monitor their deposition locations. The CFD simulations were used to estimate deposition of tailings dust and identify topographic mechanisms that influence deposition. Simulation results indicated that particles preferentially deposit in regions of topographic upslope. In addition, turbulent wind fields enhanced deposition in the wake region downwind of the tailings. This study also describes a deposition forecasting model (DFM) that can be used to forecast the transport and deposition of windblown dust originating from a mine tailings impoundment. The DFM uses in situ observations from the tailings and theoretical simulations of aerosol transport to parameterize the model. The model was verified through the use of inverted-disc deposition samplers. The deposition forecasting model was initialized using data from an operational Weather Research and Forecasting (WRF) model and the forecast deposition patterns were compared to the inverted-disc samples through gravimetric, chemical composition and lead isotopic analysis. The DFM was verified over several month-long observing periods by comparing transects of arsenic and lead tracers measured by the samplers to the DFM PM₂₇ forecast. Results from the sampling periods indicated that the DFM was able to accurately capture the regional deposition patterns of the tailings dust up to 1 km. Lead isotopes were used for source apportionment and showed spatial patterns consistent with the DFM and the observed weather conditions. By providing reasonably accurate estimates of contaminant deposition rates, the DFM can improve the assessment of human health impacts caused by windblown dust from the Iron King tailings impoundment.

Windblown dust events can be defined as windblown dust emitted from the Earth's surface to the atmosphere. These events have significant impact on local air quality. Predicting the location and magnitude of these events is vital for Utah air quality assessment and planning. Previous modeling studies have focused only on past dust events. This work utilized a state-of-the-science software framework based on the Community Multiscale Air Quality (CMAQ) v5.3.1 modeling system to predict dust events in Utah. The framework was verified using previous studies for dust events in April 2017 and March 2010. Once verified, the framework was used to predict the impact of future land use properties on dust events. Two scenarios were studied – shrinking of the Great Salt Lake and the addition of large-scale solar farms west of the Wasatch Front. Both showed increases in dust concentrations overpopulated areas using the meteorological conditions from the April 2017 dust event. Such information from future impact studies can assess potential impacts from climate change and can guide government water and land use policies to mitigate dust event impacts.