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, Avelino E Saez, Eric Betterton

Research output: Contribution to journalArticle

6 Citations (Scopus)

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

Fingerprint

impoundment
tailings
dust
simulation
arsenic
tracer
Superfund
in situ
particle
wind erosion
topsoil
particulate matter
silt
environmental impact
hazard
aerosol
iron
pollutant
metal

Keywords

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

ASJC Scopus subject areas

  • Earth-Surface Processes
  • Geology

Cite this

Development of a dust deposition forecasting model for mine tailings impoundments using in situ observations and particle transport simulations. / Stovern, Michael; Rine, Kyle P.; Russell, MacKenzie R.; Félix, Omar; King, Matt; Saez, Avelino E; Betterton, Eric.

In: Aeolian Research, Vol. 18, 01.09.2015, p. 155-167.

Research output: Contribution to journalArticle

@article{f74ee9936a6e40158075edb1a2e721cc,
title = "Development of a dust deposition forecasting model for mine tailings impoundments using in situ observations and particle transport simulations",
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.",
keywords = "Aerosol transport, Deposition, Dust, Superfund, Wind erosion",
author = "Michael Stovern and Rine, {Kyle P.} and Russell, {MacKenzie R.} and Omar F{\'e}lix and Matt King and Saez, {Avelino E} and Eric Betterton",
year = "2015",
month = "9",
day = "1",
doi = "10.1016/j.aeolia.2015.07.003",
language = "English (US)",
volume = "18",
pages = "155--167",
journal = "Aeolian Research",
issn = "1875-9637",
publisher = "Elsevier Limited",

}

TY - JOUR

T1 - Development of a dust deposition forecasting model for mine tailings impoundments using in situ observations and particle transport simulations

AU - Stovern, Michael

AU - Rine, Kyle P.

AU - Russell, MacKenzie R.

AU - Félix, Omar

AU - King, Matt

AU - Saez, Avelino E

AU - Betterton, Eric

PY - 2015/9/1

Y1 - 2015/9/1

N2 - 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.

AB - 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.

KW - Aerosol transport

KW - Deposition

KW - Dust

KW - Superfund

KW - Wind erosion

UR - http://www.scopus.com/inward/record.url?scp=84939430478&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84939430478&partnerID=8YFLogxK

U2 - 10.1016/j.aeolia.2015.07.003

DO - 10.1016/j.aeolia.2015.07.003

M3 - Article

AN - SCOPUS:84939430478

VL - 18

SP - 155

EP - 167

JO - Aeolian Research

JF - Aeolian Research

SN - 1875-9637

ER -