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<p>Coal-fired power plants generate coal combustion residuals (CCRs), which are typically disposed of in landfills and surface impoundments that must be monitored to ensure that hazardous constituents such as arsenic (As) and selenium (Se) do not escape into the surrounding environment. Traditional methods for monitoring surface impoundments, such as sampling discharge of all outlets of hydraulic structures to approximate CCR concentrations, are highly resource-intensive and largely manual, posing a significant cost challenge for the stakeholders responsible for them. The use of grass species as bioindicators may offer a more efficient and sustainable method for long-term monitoring of CCR impoundments. In this study, we sought to determine whether three species of grass could serve as effective bioindicators for detecting changes in As and Se soil contamination profiles and provide an evaluation of three technologies used for evaluating plant health. <i>Lolium perenne</i>, <i>Panicum virgatum</i>, and <i>Paspalum notatum</i> were treated with As or Se and monitored with a spectroradiometer and multispectral camera to detect a spectral response to the chemical stress. Metal transfer analysis revealed that there was a significant change in metal concentrations in plant tissue across the grass species and different treatments, with <i>Paspalum virgatum</i> providing the best dose response after a week of Se treatment. <i>Lolium perenne</i> provided a response past the Se toxicity threshold of 5&#xa0;mg/kg. We then expanded this study to a field scale to determine if our results would translate to an environmentally relevant scale. Unmanned aerial vehicle (UAV) results suggested <i>Lolium perenne</i> was efficient in determining whether CCR was present in soils but lacked sensitivity to differentiate between low and high loadings. Monthly sampling also revealed that metal concentration in plant tissue decreased as plants underwent senescence. Data collected with the UAV proved to be the most proficient method of determining a dose response.</p>

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Grass is a tattletale: using grass as a biomonitoring tool for remote sensing of coal combustion residue contamination

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月9日

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  • Alice Goldstein-Plesser,
  • Anna Ulanova,
  • Maxwell Lutz,
  • Julie Parno,
  • Nicole Wuerslin,
  • Korynna Rankin,
  • Jazmine Hawkins,
  • Margaret Kurth,
  • Samuel Beal,
  • Timothy Cary,
  • Jeffrey Summers,
  • Taylor Rycroft,
  • Franz J. Lichtner

摘要

Coal-fired power plants generate coal combustion residuals (CCRs), which are typically disposed of in landfills and surface impoundments that must be monitored to ensure that hazardous constituents such as arsenic (As) and selenium (Se) do not escape into the surrounding environment. Traditional methods for monitoring surface impoundments, such as sampling discharge of all outlets of hydraulic structures to approximate CCR concentrations, are highly resource-intensive and largely manual, posing a significant cost challenge for the stakeholders responsible for them. The use of grass species as bioindicators may offer a more efficient and sustainable method for long-term monitoring of CCR impoundments. In this study, we sought to determine whether three species of grass could serve as effective bioindicators for detecting changes in As and Se soil contamination profiles and provide an evaluation of three technologies used for evaluating plant health. Lolium perenne, Panicum virgatum, and Paspalum notatum were treated with As or Se and monitored with a spectroradiometer and multispectral camera to detect a spectral response to the chemical stress. Metal transfer analysis revealed that there was a significant change in metal concentrations in plant tissue across the grass species and different treatments, with Paspalum virgatum providing the best dose response after a week of Se treatment. Lolium perenne provided a response past the Se toxicity threshold of 5 mg/kg. We then expanded this study to a field scale to determine if our results would translate to an environmentally relevant scale. Unmanned aerial vehicle (UAV) results suggested Lolium perenne was efficient in determining whether CCR was present in soils but lacked sensitivity to differentiate between low and high loadings. Monthly sampling also revealed that metal concentration in plant tissue decreased as plants underwent senescence. Data collected with the UAV proved to be the most proficient method of determining a dose response.