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Risk-Trace: Software for Spatially Explicit Exposure Assessment

机译:风险追踪:用于空间显式暴露评估的软件

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Large areas of valuable habitats have been physically disturbed and/or contaminated by hazardous pollutants as a result of industrial activities. This paper presents a methodological approach and a software prototype for spatially explicit risk assessment of contaminated terrestrial ecosystems, to be implemented as a part of a risk-based decision protocol to support the assessment of ecological value and site reuse options. Exposure estimates for wildlife in areas containing spatially localized contaminants are functions of spatial factors, such as the receptor's average foraging area, the size of the habitat being assessed, and the distribution of contamination. Species exhibiting different foraging strategies may experience significantly different chemical exposures from the same site, even if their foraging areas overlap. Currently, exposure estimates and subsequent human health and ecological risk projections usually assume a static and continuous exposure of an ecological receptor to a contaminant concentration represented by some descriptive statistic, such as the mean or maximum concentration. These assumptions are generally overly conservative and ignore some of the major advantages offered by advanced risk assessment techniques, such as the ability to account for site-specific conditions and to conduct iterative analyses. We developed a spatially explicit foraging model that provides a time series estimation of soil and food contamination that receptors may encounter in their daily movements. The model currently inputs information on: the geospatial parameters of the contaminated area, surrounding land, and the habitat types found in each; density and distribution of ecological receptors; receptor home range; maps of contamination concentrations and habitat disturbance; and receptor's foraging range. The model also employs habitat quality factors that account for differential attraction to various habitat types within the site. This paper presents a software prototype that calculates chemical accumulation by a receptor foraging in areas having specified contamination patterns and habitat parameters.
机译:工业活动的结果是,大面积的宝贵栖息地受到了有害污染物的物理干扰和/或污染。本文提出了一种方法方法和软件原型,用于对受污染的陆地生态系统进行空间显式风险评估,并将其作为基于风险的决策协议的一部分来实施,以支持对生态价值和场地再利用选择的评估。包含空间局部污染物的区域中野生动植物的暴露估计是空间因素的函数,例如受体的平均觅食面积,被评估的栖息地的大小以及污染的分布。表现出不同觅食策略的物种即使在觅食区域重叠的情况下,也可能在同一地点遭受不同的化学暴露。当前,暴露估计以及随后的人类健康和生态风险预测通常假定生态受体静态和连续地暴露于某种描述性统计数据所代表的污染物浓度,例如平均浓度或最大浓度。这些假设通常过于保守,而忽略了先进风险评估技术所提供的一些主要优势,例如考虑特定地点条件和进行迭代分析的能力。我们开发了空间明确的觅食模型,该模型提供了受体在日常运动中可能遇到的土壤和食物污染的时间序列估算。该模型当前输入有关以下方面的信息:受污染区域,周围土地的地理空间参数以及每个区域的栖息地类型;生态受体的密度和分布;受体起始范围污染浓度和栖息地干扰图;和受体的觅食范围。该模型还采用了栖息地质量因子,该因子解释了场地内不同栖息地类型的吸引力。本文提出了一个软件原型,该软件原型可以通过在具有特定污染模式和栖息地参数的区域中觅食受体来计算化学积累。

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