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Estimating environmental exposure of emerging agricultural contaminants using spatial data analysis and geographic information system.

机译：使用空间数据分析和地理信息系统估算新兴农业污染物的环境暴露。

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Agricultural activities generate a wide range of potential contaminants that can degrade the quality of both surface and ground water, resulting in significant public health and environmental impacts. Amongst potential contaminants connected with farming, livestock antibiotics and hormones and soybean rust fungicides have only recently emerged as concerns. The use of antibiotics and hormones as growth promoters and anti-bacterial agents in the feed of most livestock, and the use of fungicides to control soybean rust are believed to play a leading role in the release of these substances into the environment. While livestock antibiotics/hormones are increasingly being found in water bodies, and have already been observed to cause extreme biological responses at low (ng/l) concentrations, fungicides are more of a future threat in states such as Indiana as they will likely be used to control soybean rust (a potentially devastating disease for soybeans in US) and may reach water resources and impact "off target" species such as fish and humans. Therefore, it is essential to assess the possible environmental impacts of these potential contaminants and identify areas that are most vulnerable to contamination. This study focuses on developing and applying modeling techniques to estimate the potential magnitude and spatial patterns of water resources contamination by these emerging agricultural contaminants. This was achieved by developing a mathematical screening tool as a first step to estimate the possibility of contamination of shallow groundwater. Model results for the State of Indiana demonstrate that transport rates and paths are highly sensitive to soil patterns and characteristics, and illustrate how this approach can be used to create spatial maps of leached fractions beyond a control plane. This was followed by a statewide risk assessment of both livestock antibiotics/hormones and the soybean rust fungicides. Assessment results indicate the regions in Indiana that are vulnerable to contamination by these two groups of compounds. The outputs of this study demonstrate the scale of the potential risk posed by these emerging contaminants and also establish a framework for developing comprehensive management and mitigation plans.
机译：农业活动会产生各种各样的潜在污染物，这些污染物会降低地表水和地下水的质量，从而对公众健康和环境造成重大影响。在与农业有关的潜在污染物中，牲畜抗生素和激素以及大豆锈菌杀真菌剂只是最近才引起人们的关注。人们认为，在大多数牲畜的饲料中使用抗生素和激素作为生长促进剂和抗菌剂，以及使用杀真菌剂控制大豆锈病，在将这些物质释放到环境中起着主导作用。尽管在水体中越来越多地发现牲畜抗生素/激素，并且已经观察到在低浓度（ng / l）时会引起极端的生物反应，但在印第安纳州等州，杀菌剂更可能成为未来的威胁，因为它们很可能会被使用来控制大豆锈病（在美国可能是毁灭性的大豆疾病），并可能达到水资源并影响“脱靶”物种，例如鱼类和人类。因此，必须评估这些潜在污染物可能对环境造成的影响，并确定最容易受到污染的区域。这项研究的重点是开发和应用建模技术来估算这些新兴农业污染物对水资源污染的潜在规模和空间格局。这是通过开发数学筛选工具作为第一步来估算浅层地下水污染的可能性而实现的。印第安纳州的模型结果表明，运输速率和路径对土壤模式和特征高度敏感，并说明了如何使用此方法来创建控制平面以外的浸出部分的空间图。接下来是对牲畜抗生素/激素和大豆锈菌杀真菌剂进行全州风险评估。评估结果表明，印第安那州的这两类化合物容易受到污染。这项研究的结果表明了这些新兴污染物所构成的潜在风险的规模，并为制定综合管理和缓解计划建立了框架。

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