Project Summary (2017-2020)

In semiarid environments such as the Southwestern U.S., mining sites are an important source of airborne metal(loid) contaminants. High-temperature smelting produces vapors that condense to form submicron particles contaminating mine tailings deposits that are susceptible to wind erosion. Dust and aerosol particles mobilize trace metal(loids), which then can accumulate in nearby soils, natural waters, and vegetation, leading to human exposure through inhalation and incidental dust ingestion. Specifically, acute and chronic exposures to arsenic and lead, two toxic elements present in many mining sites in arid and semiarid regions around the world, pose significant health risks, including cancer and non-malignant lung diseases. This project is directed towards a comprehensive understanding of the physical and chemical properties of dust and aerosols generated from mining sites, emphasizing their role in the transport of arsenic and lead to the local environment.

The researchers hypothesize that metal(loid) contaminant transport by atmospheric dust and aerosol from mining sites can be quantified by computational fluid dynamics models based on meteorological conditions and particle size distribution of particle emissions. The researchers are developing these models based on data collected from two Superfund sites in Arizona focusing on the role of aerosol and dust particle size distribution on the fate and transport of contaminants. This activity is important because smelting in particular appears to concentrate lead and arsenic in sub-micron particles, which are more susceptible to inhalation into the lungs than larger particles.

Particle size distribution also plays a role in the transport of particles through the outdoor/indoor barrier, and this is being examined at two Superfund mining sites. Simulations are complemented by indoor sampling, which help to establish the risks of indoor exposure to lead and arsenic. The flux and particle size range of dust emissions from contaminated sites is characterized using a laboratory-scale dust generator and a portable wind tunnel. The researchers are incorporating source apportionment into the modeling effort to ensure that natural sources of contamination are distinguished from mining sources.

The modeling effort is being extended to the assessment of remediation of mine tailings by phytostabilization. Preliminary data gathered at a Superfund site has shown that vegetated plots tend to attenuate dust generation from the tailings by intercepting dust transported by winds and by reducing dust and aerosol emissions. This framework can be generalized to other mining-related sites in Arizona, across the Southwest, and even across the U.S., to improve understanding of dust- and aerosol-associated exposure of populations to arsenic, lead and other contaminants, and will be used in UA SRP biomedical projects to better understand the effects of this understudied exposure route.