Development of a dust deposition forecasting model for mine tailings impoundments using in situ observations and particle transport simulations

Michael Stovern, Kyle P. Rine, MacKenzie R. Russell, Omar Félix, Matt King, A. Eduardo Sáez, Eric A. Betterton

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Mine tailings impoundments in arid and semiarid environments are susceptible to wind erosion due to their fine grain silt and sandy composition and lack of vegetative coverage. Aeolian transport of particulate matter from these mine tailings impoundments are potential hazards to human health due to the presence of metal and metalloid contaminants. Predicting windblown transport of mine tailings material can be a useful tool in characterizing the risk and environmental impact on neighboring communities. This work presents a model that can be used to forecast the transport and deposition of windblown dust from mine tailings impoundments. The deposition forecast model uses in situ observations from a tailings field site and theoretical simulations of aerosol transport to parameterize the model. It includes a method for simulating deposition patterns for several different size fractions and can be translated to other regions and applied to different windblown dust sources. The model was developed using data from the Iron King Mine tailings in Dewey-Humboldt, Arizona, a Superfund site that is heavily contaminated with lead and arsenic. A preliminary verification of the model was conducted using topsoil measurements of lead and arsenic as tracers of windblown dust from the tailings impoundment. The tailings tracers support the predicted deposition patterns generated by the deposition forecasting model.

Original languageEnglish (US)
Pages (from-to)155-167
Number of pages13
JournalAeolian Research
Volume18
DOIs
StatePublished - Sep 1 2015

Keywords

  • Aerosol transport
  • Deposition
  • Dust
  • Superfund
  • Wind erosion

ASJC Scopus subject areas

  • Geology
  • Earth-Surface Processes

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