von Stackelberg Katherine, Williams Marc A, Clough Jonathan, Johnson Mark S
NEK Associates, Allston, Massachusetts, USA.
US Army Public Health Center, Aberdeen Proving Ground, Maryland.
Integr Environ Assess Manag. 2017 Nov;13(6):1023-1037. doi: 10.1002/ieam.1927. Epub 2017 May 11.
Bioaccumulation models quantify the relationship between sediment and water exposure concentrations and resulting tissue levels of chemicals in aquatic organisms and represent a key link in the suite of tools used to support decision making at contaminated sediment sites. Predicted concentrations in the aquatic food web provide exposure estimates for human health and ecological risk assessments, which, in turn, provide risk-based frameworks for evaluating potential remedial activities and other management alternatives based on the fish consumption pathway. Despite the widespread use of bioaccumulation models to support remedial decision making, concerns remain about the predictive power of these models. A review of the available literature finds the increased mathematical complexity of typical bioaccumulation model applications is not matched by the deterministic exposure concentrations used to drive the models. We tested a spatially explicit exposure model (FishRand) at 2 nominally contaminated sites and compared results to estimates of bioaccumulation based on conventional, nonspatial techniques, and monitoring data. Differences in predicted fish tissue concentrations across applications were evident, although these demonstration sites were only mildly contaminated and would not warrant management actions on the basis of fish consumption. Nonetheless, predicted tissue concentrations based on the spatially explicit exposure characterization consistently outperformed conventional, nonspatial techniques across a variety of model performance metrics. These results demonstrate the improved predictive power as well as greater flexibility in evaluating the impacts of food web exposure and fish foraging behavior in a heterogeneous exposure environment. Integr Environ Assess Manag 2017;13:1023-1037. © 2017 SETAC.
生物累积模型量化了沉积物和水体暴露浓度与水生生物体内化学物质最终组织水平之间的关系,是用于支持污染沉积物场地决策的一系列工具中的关键环节。水生食物网中的预测浓度为人类健康和生态风险评估提供了暴露估计,进而为基于鱼类消费途径评估潜在的修复活动和其他管理方案提供了基于风险的框架。尽管生物累积模型被广泛用于支持修复决策,但人们对这些模型的预测能力仍存在担忧。对现有文献的回顾发现,典型生物累积模型应用中增加的数学复杂性与用于驱动模型的确定性暴露浓度并不匹配。我们在2个名义上受污染的场地测试了一个空间明确的暴露模型(FishRand),并将结果与基于传统非空间技术的生物累积估计值和监测数据进行了比较。尽管这些示范场地只是轻度污染,基于鱼类消费并不需要采取管理行动,但不同应用中预测的鱼类组织浓度差异明显。尽管如此,基于空间明确的暴露特征预测的组织浓度在各种模型性能指标上始终优于传统的非空间技术。这些结果表明,在评估异质暴露环境中食物网暴露和鱼类觅食行为的影响时,预测能力有所提高,灵活性也更大。《综合环境评估与管理》2017年;13:1023 - 1037。©2017 SETAC。