金属风险评估中的人群建模:将毒性测试推断至人群水平。

IF 3.6 4区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES
Karel P. J. Viaene, Karel Vlaeminck, Simon Hansul, Sharon Janssen, Kristi Weighman, Patrick Van Sprang, Karel A. C. De Schamphelaere
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引用次数: 0

摘要

种群模型是生态风险评估的有用工具,可提高生态的真实性。本研究利用种群模型将四种金属(银、铜、镍、锌)的毒性测试结果外推至种群水平。共涉及三种初级生产者、五种无脊椎动物和五种鱼类。基于生态建模的实验室至种群效应外推因子(ECOPEX 因子),定义为种群水平上预测的 10%效应浓度(EC10)与实验室毒性试验观察到的 EC10 之比,范围从 0.7 到 78.6 不等,中位数为 2.8(n = 27)。在大多数情况下,种群模型显示的效应浓度明显较高(27 个案例中有 14 个案例的 ECOPEX 因子大于 2),但在某些情况下,观察到的结果恰恰相反(27 个案例中有 3 个案例的 ECOPEX 因子大于 2)。我们确定了造成 ECOPEX 因子变化的五个主要因素:(1) 毒性模型的不确定性;(2) 金属毒性机制的不确定性;(3) 试验设计的不确定性;(4) 环境因素的影响;(5) 所选人群终点的影响。不确定性的部分原因是缺乏适当的校准数据。尽管如此,使用群体模型进行外推通常会减少试验之间 EC10 值的变异性。为了探索种群模型在监管背景下的适用性,我们在铜的物种敏感性分布中加入了种群外推法,从而使 5%物种的有害浓度增加了 1.5 到 2 倍。 此外,我们还利用监测到的锌浓度,在假设的《水框架指令》案例中应用了鱼类种群模型。本文还就在(金属)风险评估中进一步使用种群模型提出了建议。环境毒物化学 2024;00:1-21。© 2024 SETAC.
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Population Modeling in Metal Risk Assessment: Extrapolation of Toxicity Tests to the Population Level

Population models can be a useful tool for ecological risk assessment to increase ecological realism. In the present study, population models were used to extrapolate toxicity test results of four metals (Ag, Cu, Ni, Zn) to the population level. In total, three primary producers, five invertebrate species, and five fish species were covered. The ecological modeling–based laboratory to population effect extrapolation factor (ECOPEX factor), defined as the ratio of the predicted 10% effect concentration (EC10) at the population level and the observed EC10 for the laboratory toxicity test, ranged from 0.7 to 78.6, with a median of 2.8 (n = 27). Population modeling indicated clearly higher effect concentrations in most of the cases (ECOPEX factor >2 in 14 out of 27 cases), but in some cases the opposite was observed (in three out of 27 cases). We identified five main contributors to the variability in ECOPEX factors: (1) uncertainty about the toxicity model, (2) uncertainty about the toxicity mechanism of the metal, (3) uncertainty caused by test design, (4) impact of environmental factors, and (5) impact of population endpoint chosen. Part of the uncertainty results from a lack of proper calibration data. Nonetheless, extrapolation with population models typically reduced the variability in EC10 values between tests. To explore the applicability of population models in a regulatory context, we included population extrapolations in a species sensitivity distribution for Cu, which increased the hazardous concentration for 5% of species by a factor 1.5 to 2. Furthermore, we applied a fish population model in a hypothetical Water Framework Directive case using monitored Zn concentrations. This article includes recommendations for further use of population models in (metal) risk assessment. Environ Toxicol Chem 2024;43:2308–2328. © 2024 SETAC

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来源期刊
CiteScore
7.40
自引率
9.80%
发文量
265
审稿时长
3.4 months
期刊介绍: The Society of Environmental Toxicology and Chemistry (SETAC) publishes two journals: Environmental Toxicology and Chemistry (ET&C) and Integrated Environmental Assessment and Management (IEAM). Environmental Toxicology and Chemistry is dedicated to furthering scientific knowledge and disseminating information on environmental toxicology and chemistry, including the application of these sciences to risk assessment.[...] Environmental Toxicology and Chemistry is interdisciplinary in scope and integrates the fields of environmental toxicology; environmental, analytical, and molecular chemistry; ecology; physiology; biochemistry; microbiology; genetics; genomics; environmental engineering; chemical, environmental, and biological modeling; epidemiology; and earth sciences. ET&C seeks to publish papers describing original experimental or theoretical work that significantly advances understanding in the area of environmental toxicology, environmental chemistry and hazard/risk assessment. Emphasis is given to papers that enhance capabilities for the prediction, measurement, and assessment of the fate and effects of chemicals in the environment, rather than simply providing additional data. The scientific impact of papers is judged in terms of the breadth and depth of the findings and the expected influence on existing or future scientific practice. Methodological papers must make clear not only how the work differs from existing practice, but the significance of these differences to the field. Site-based research or monitoring must have regional or global implications beyond the particular site, such as evaluating processes, mechanisms, or theory under a natural environmental setting.
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