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生物群落的异质性和化学风险评估中的暴露:利用两个景观尺度案例研究探索方法学的能力和挑战。

Heterogeneity in biological assemblages and exposure in chemical risk assessment: Exploring capabilities and challenges in methodology with two landscape-scale case studies.

机构信息

Applied Analysis Solutions LLC, Berryville, VA 22611, USA.

The University of Sheffield, Sheffield S10 2TN, UK.

出版信息

Ecotoxicol Environ Saf. 2022 Nov;246:114143. doi: 10.1016/j.ecoenv.2022.114143. Epub 2022 Oct 3.

Abstract

Chemical exposure concentrations and the composition of ecological receptors (e.g., species) vary in space and time, resulting in landscape-scale (e.g. catchment) heterogeneity. Current regulatory, prospective chemical risk assessment frameworks do not directly address this heterogeneity because they assume that reasonably worst-case chemical exposure concentrations co-occur (spatially and temporally) with biological species that are the most sensitive to the chemical's toxicity. Whilst current approaches may parameterise fate models with site-specific data and aim to be protective, a more precise understanding of when and where chemical exposure and species sensitivity co-occur enables risk assessments to be better tailored and applied mitigation more efficient. We use two aquatic case studies covering different spatial and temporal resolution to explore how geo-referenced data and spatial tools might be used to account for landscape heterogeneity of chemical exposure and ecological assemblages in prospective risk assessment. Each case study followed a stepwise approach: i) estimate and establish spatial chemical exposure distributions using local environmental information and environmental fate models; ii) derive toxicity thresholds for different taxonomic groups and determine geo-referenced distributions of exposure-toxicity ratios (i.e., potential risk); iii) overlay risk data with the ecological status of biomonitoring sites to determine if relationships exist. We focus on demonstrating whether the integration of relevant data and potential approaches is feasible rather than making comprehensive and refined risk assessments of specific chemicals. The case studies indicate that geo-referenced predicted environmental concentration estimations can be achieved with available data, models and tools but establishing the distribution of species assemblages is reliant on the availability of a few sources of biomonitoring data and tools. Linking large sets of geo-referenced exposure and biomonitoring data is feasible but assessment of risk will often be limited by the availability of ecotoxicity data. The studies highlight the important influence that choices for aggregating data and for the selection of statistical metrics have on assessing and interpreting risk at different spatial scales and patterns of distribution within the landscape. Finally, we discuss approaches and development needs that could help to address environmental heterogeneity in chemical risk assessment.

摘要

化学物质暴露浓度和生态受体(如物种)的组成在空间和时间上存在差异,导致景观尺度(如集水区)的异质性。当前的监管、前瞻性化学风险评估框架并没有直接解决这种异质性,因为它们假设合理的最差情况下化学物质暴露浓度与对化学物质毒性最敏感的生物物种同时存在(在空间和时间上)。虽然当前的方法可以使用特定地点的数据参数化命运模型,并旨在具有保护作用,但更准确地了解化学物质暴露和物种敏感性何时何地同时发生,可以使风险评估更好地适应,并更有效地应用缓解措施。我们使用两个涵盖不同空间和时间分辨率的水生案例研究,探讨如何使用地理参考数据和空间工具来解释前瞻性风险评估中化学物质暴露和生态组合的景观异质性。每个案例研究都遵循一个逐步的方法:i)使用当地环境信息和环境命运模型估计和建立空间化学暴露分布;ii)为不同分类群确定毒性阈值,并确定暴露-毒性比的地理参考分布(即潜在风险);iii)将风险数据与生物监测站点的生态状况进行叠加,以确定是否存在关系。我们专注于展示整合相关数据和潜在方法是否可行,而不是对特定化学物质进行全面和精细的风险评估。案例研究表明,利用现有数据、模型和工具可以实现地理参考预测环境浓度估计,但建立物种组合分布依赖于少数生物监测数据和工具的可用性。链接大量地理参考暴露和生物监测数据是可行的,但风险评估通常会受到生态毒性数据可用性的限制。这些研究强调了在不同空间尺度和景观内的分布模式下评估和解释风险时,数据聚合和统计度量选择的重要影响。最后,我们讨论了有助于解决化学风险评估中环境异质性的方法和发展需求。

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