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Aquat Toxicol. 2023 Mar;256:106389. doi: 10.1016/j.aquatox.2022.106389. Epub 2023 Jan 6.
Oil fate and exposure modeling addresses the complexities of oil composition, weathering, partitioning in the environment, and the distributions and behaviors of aquatic biota to estimate exposure histories, i.e., oil component concentrations and environmental conditions experienced over time. Several approaches with increasing levels of complexity (i.e., aquatic toxicity model tiers, corresponding to varying purposes and applications) have been and continue to be developed to predict adverse effects resulting from these exposures. At Tiers 1 and 2, toxicity-based screening thresholds for assumed representative oil component compositions are used to inform spill response and risk evaluations, requiring limited toxicity data, analytical oil characterizations, and computer resources. Concentration-response relationships are employed in Tier 3 to quantify effects of assumed oil component mixture compositions. Oil spill modeling capabilities presently allow predictions of spatial and temporal compositional changes during exposure, which support mixture-based modeling frameworks. Such approaches rely on summed effects of components using toxic units to enable more realistic analyses (Tier 4). This review provides guidance for toxicological studies to inform the development of, provide input to, and validate Tier 4 aquatic toxicity models for assessing oil spill effects on aquatic biota. Evaluation of organisms' exposure histories using a toxic unit model reflects the current state-of the-science and provides an improved approach for quantifying effects of oil constituents on aquatic organisms. Since the mixture compositions in toxicity tests are not representative of field exposures, modelers rely on studies using single compounds to build toxicity models accounting for the additive effects of dynamic mixture exposures that occur after spills. Single compound toxicity data are needed to quantify the influence of exposure duration and modifying environmental factors (e.g., temperature, light) on observed effects for advancing use of this framework. Well-characterized whole oil bioassay data should be used to validate and refine these models.
油运移和暴露模型旨在解决油成分、风化、在环境中的分配以及水生生物的分布和行为的复杂性,以估算暴露史,即随时间经历的油成分浓度和环境条件。已经并将继续开发几种具有越来越复杂程度的方法(即水生毒性模型级别,对应于不同的目的和应用),以预测这些暴露导致的不良影响。在第 1 级和第 2 级,基于毒性的假定代表性油成分组成的筛选阈值用于通知溢油应急和风险评估,需要有限的毒性数据、分析油特性和计算机资源。第 3 级采用浓度-反应关系来量化假定油成分混合物组成的影响。目前,溢油建模能力允许预测暴露期间的时空组成变化,支持基于混合物的建模框架。这些方法依赖于使用毒性单位的组件总和效应来实现更现实的分析(第 4 级)。本综述为毒理学研究提供了指导,以告知第四级水生毒性模型的开发、为其提供输入并验证这些模型,用于评估溢油对水生生物的影响。使用毒性单位模型评估生物体的暴露史反映了当前的科学现状,并为量化油成分对水生生物的影响提供了一种改进的方法。由于毒性测试中的混合物组成不能代表现场暴露情况,因此模型构建者依赖于使用单一化合物的研究来构建毒性模型,以解释溢油后发生的动态混合物暴露的加性效应。需要单化合物毒性数据来量化暴露持续时间和环境因素(例如温度、光照)对观察到的影响的影响,以推进该框架的使用。应使用特征良好的全油生物测定数据来验证和改进这些模型。