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比较用于纳米材料环境风险评估的物种敏感度分布建模方法——以银和二氧化钛代表性材料为例。

Comparison of species sensitivity distribution modeling approaches for environmental risk assessment of nanomaterials - A case study for silver and titanium dioxide representative materials.

机构信息

Department of Environmental Engineering, Technical University of Denmark, Bygningstorvet, Building 115, DK-2800 Kgs., Lyngby, Denmark.

Empa - Swiss Federal Laboratories for Materials Science and Technology, Technology and Society Laboratory, CH-9014, St. Gallen, Switzerland; DLR Institute of Networked Energy Systems - Energy Systems Analysis, Carl-von-Ossietzky Str. 15, 26129, Oldenburg, Germany.

出版信息

Aquat Toxicol. 2020 Aug;225:105543. doi: 10.1016/j.aquatox.2020.105543. Epub 2020 Jun 12.

Abstract

Species sensitivity distributions (SSDs) are used in chemical safety assessments to derive predicted-no-effect-concentrations (PNECs) for substances with a sufficient amount of relevant and reliable ecotoxicity data available. For engineered nanomaterials (ENMs), ecotoxicity data are often compromised by poor reproducibility and the lack of nano-specific characterization needed describe an ENM under test exposure conditions. This may influence the outcome of SSD modelling and hence the regulatory decision-making. This study investigates how the outcome of SSD modelling is influenced by: 1) Selecting input data based on the nano-specific "nanoCRED" reliability criteria, 2) Direct SSD modelling avoiding extrapolation of data by including long-term/chronic NOECs only, and 3) Weighting data according to their nano-specific quality, the number of data available for each species, and the trophic level abundance in the ecosystem. Endpoints from freshwater ecotoxicity studies were collected for the representative nanomaterials NM-300 K (silver) and NM-105 (titanium dioxide), evaluated for regulatory reliability and scored according to the level of nano-specific characterization conducted. The compiled datasets are unique in exclusively dealing with representative ENMs showing minimal batch-to-batch variation. The majority of studies were evaluated as regulatory reliable, while the degree of nano-specific characterization varied greatly. The datasets for NM-300 K and NM-105 were used as input to the nano-weighted n-SSWD model, the probabilistic PSSD+, and the conventional SSD Generator by the US EPA. The conventional SSD generally yielded the most conservative, but least precise HC values, with 95 % confidence intervals up to 100-fold wider than the other models. The inclusion of regulatory reliable data only, had little effect on the HC generated by the conventional SSD and the PSSD+, whereas the n-SSWD estimated different HC values based on data segregated according to reliability, especially for NM-105. The n-SSWD weighting of data significantly affected the estimated HC values, however in different ways for the sub-datasets of NM-300 K and NM-105. For NM-300 K, the inclusion of NOECs only in the weighted n-SSWD yielded the most conservative HC of all datasets and models (a HC based on NOECs only could not be estimated for NM-105, due to limited number of data). Overall, the estimated HC values of all models are within a relatively limited concentration range of 25-100 ng Ag/L for NM-300 K and 1-15 μgTiO/L for NM-105.

摘要

物种敏感性分布 (SSD) 被用于化学安全评估中,以得出具有足够相关和可靠的生态毒性数据的物质的预测无效应浓度 (PNEC)。对于工程纳米材料 (ENM),生态毒性数据通常因再现性差和缺乏测试暴露条件下所需的纳米特定特性描述而受到影响。这可能会影响 SSD 建模的结果,从而影响监管决策。本研究调查了以下因素如何影响 SSD 建模的结果:1)根据纳米特定的“nanoCRED”可靠性标准选择输入数据,2)直接进行 SSD 建模,避免通过仅包括长期/慢性 NOEC 进行数据外推,以及 3)根据数据的纳米特定质量、每种物质的可用数据数量以及生态系统中的营养级丰度对数据进行加权。为 NM-300 K(银)和 NM-105(二氧化钛)这两种代表性纳米材料收集了淡水生态毒性研究的终点数据,根据监管可靠性进行了评估,并根据进行的纳米特定特性描述的水平进行了评分。所编译的数据集是独一无二的,专门用于处理显示最小批次间变化的代表性 ENM。大多数研究被评估为具有监管可靠性,而纳米特定特性描述的程度差异很大。NM-300 K 和 NM-105 的数据集被用作美国环保署的纳米加权 n-SSWD 模型、概率 PSSD+和常规 SSD 生成器的输入。常规 SSD 通常产生最保守但最不准确的 HC 值,95%置信区间比其他模型宽 100 倍。仅包含监管可靠的数据对常规 SSD 和 PSSD+生成的 HC 影响很小,而 n-SSWD 则根据可靠性对数据进行了分类,根据数据进行了分类,特别是对于 NM-105,估计了不同的 HC 值。n-SSWD 对数据的加权显著影响了估计的 HC 值,但对于 NM-300 K 和 NM-105 的子数据集,影响方式不同。对于 NM-300 K,仅在加权 n-SSWD 中包含 NOEC 会产生所有数据集和模型中最保守的 HC(由于数据有限,无法对 NM-105 进行仅基于 NOEC 的 HC 估计)。总体而言,所有模型估计的 HC 值都在相对有限的浓度范围内,对于 NM-300 K 为 25-100ng Ag/L,对于 NM-105 为 1-15μgTiO/L。

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