Risk assessment of metals determined using remote sensing of dissolved organic carbon

由于采矿、废物和其他工业活动，金属会污染环境。为了控制这种污染，水管理人员需要工具来估计湖泊和溪流中不同浓度金属的风险。众所周知，湖泊的特定水化学可以影响金属的毒性作用；特别是溶解有机物（DOM）的存在可以降低铜、镍、铅和锌的毒性。这种效应可以使用已建立的生物配体模型（BLMs）进行定量预测。在此建模中，DOM由溶解有机碳（DOC; mg C/L）的可测量量表示。许多政府建议使用土地管理局的方法来建立特定地点的水质标准，或进行风险评估，但许多地方司法管辖区缺乏一致和准确测量DOC的能力。DOC不是常规测量的水质参数。遥感是一个活跃的研究领域，它可能能够解决这一实际数据差距，并帮助风险评估人员和水资源管理人员在确定地表水的金属风险时定量地考虑DOC。遥感DOC的基础是溶解有机物有颜色（简称CDOM）。尚未证明遥感可以准确地将CDOM的测量值转换为淡水环境中DOC的预测。作为原理证明，我们建议使用无人机和卫星遥感方法研究魁北克的偏远，未受影响的湖泊。估计的CDOM将转换为DOC，并最终通过BLM建模转换为金属风险估计。这一风险估计将与同一地点水体样品中实际测量到的影响浓度进行比较。这种比较将使我们能够评估遥感作为金属（包括铜、锌、铅和镍）工具的可行性和实用性，以及评估当前和未来矿物开采或废物处理活动的风险。

Metals can pollute the environment as a result of mining, waste and other industrial activities. To manage this pollution, water managers require tools to estimate risk of different concentrations of metals in lakes and streams. It is well established that specific water chemistry of a lake can influence the toxic effects of metals; in particular, the presence of dissolved organic matter (DOM) can decrease the toxicity of copper, nickel, lead and zinc. This effect, can quantitatively be predicted using established biotic ligand models (BLMs). For this modelling DOM is represented by the measurable quantity of dissolved organic carbon (DOC; mg C/L). Many governments recommend use of BLM approaches for establishing site-specific water quality criteria, or for risk assessment, but many local jurisdictions lack the ability to consistently and accurately measure DOC. DOC is not a routinely measured water quality parameter. Remote sensing is an active research field that might be able to address this practical data gap and help risk assessors, and water managers, to quantitatively take DOC into account when establishing metal risks for surface waters. The basis for remote sensing of DOC is that dissolved organic matter has colour (referred to as CDOM). It has not yet been demonstrated that remote sensing can accurately convert measurements of CDOM to a prediction of DOC in freshwater environments. As a proof of principle, we propose to study remote, un-impacted, lakes in Quebec using both drone- and satellite-based remote sensing methods. The estimated CDOM will be converted to DOC and ultimately, via BLM modelling, to metals risk estimates. This risk estimate will be compared to actual measured effect concentrations in samples of these same site waters. The comparison will allow us to assess the feasibility, and practicality, of remote sensing as a tool for metals, including copper, zinc, lead and nickel, risk assessment for current and future mineral extraction or waste disposal activities.