(Project 1: Sez, Betterton, Sorooshian) In semiarid environments such as the Southwestern US, mining sites are an important source of airborne metal(loid) contaminants. High-temperature smelting produces vapors that condense to form sub- micron particles which may be transported by wind, while contaminated tailings deposits are susceptible to wind erosion. Dust and aerosol particles mobilize trace metal(loids), which then can accumulate in soils, natural waters, and vegetation, leading to human exposure through inhalation and incidental dust ingestion. In particular, 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 aerosol generated from mining sites, emphasizing their role in the transport of arsenic and lead to the local environment and the associated human health risks. We 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. We will develop 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 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 will be examined at two Superfund mining sites. Simulations will be complemented by indoor sampling, which will help to establish the risks of indoor exposure to lead and arsenic. The flux and particle size range of dust emissions from contaminated sites will be characterized using a laboratory-scale dust generator and a portable wind tunnel. We will then incorporate source apportionment into the modeling effort to ensure that natural sources of contamination are distinguished from mining sources. The modeling effort will be 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 US, to improve our 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.
(Project 1: Sez, Betterton, Sorooshian) The field data and analysis on arsenic and lead transport by atmospheric dust and aerosol at a smelter site and at a Superfund mine tailings site in Arizona will complement current efforts by the principal stakeholders (EPA, ATSDR, Arizona Department of Environmental Quality and Arizona Department of Health Services) to assess the extent of contamination at these sites. In particular, the focus on transport of contaminants by particle size will help stakeholders assess the sources of contamination and the risk of human health effects due to contaminant exposure. The development of a predictive tool that can determine the extent of contaminant dispersion in response to forecast wind events will prove useful in assessing human exposure and remediation options.
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