Evaluating the reliability of environmental concentration data to characterize exposure in environmental risk assessments

可靠性(半导体) 计算机科学 环境数据 样品(材料) 风险评估 数据质量 数据挖掘 风险分析(工程) 工程类 功率(物理) 法学 政治学 色谱法 运营管理 化学 公制(单位) 量子力学 计算机安全 物理 医学
作者
Michelle L. Hladik,Arjen Markus,Dennis R. Helsel,Lisa H. Nowell,Stefano Polesello,Heinz Rüdel,Drew Szabo,Iain Wilson
出处
期刊:Integrated Environmental Assessment and Management [Wiley]
卷期号:20 (4): 981-1003 被引量:3
标识
DOI:10.1002/ieam.4893
摘要

Abstract Environmental risk assessments often rely on measured concentrations in environmental matrices to characterize exposure of the population of interest—typically, humans, aquatic biota, or other wildlife. Yet, there is limited guidance available on how to report and evaluate exposure datasets for reliability and relevance, despite their importance to regulatory decision‐making. This paper is the second of a four‐paper series detailing the outcomes of a Society of Environmental Toxicology and Chemistry Technical Workshop that has developed Criteria for Reporting and Evaluating Exposure Datasets (CREED). It presents specific criteria to systematically evaluate the reliability of environmental exposure datasets. These criteria can help risk assessors understand and characterize uncertainties when existing data are used in various types of assessments and can serve as guidance on best practice for the reporting of data for data generators (to maximize utility of their datasets). Although most reliability criteria are universal, some practices may need to be evaluated considering the purpose of the assessment. Reliability refers to the inherent quality of the dataset and evaluation criteria address the identification of analytes, study sites, environmental matrices, sampling dates, sample collection methods, analytical method performance, data handling or aggregation, treatment of censored data, and generation of summary statistics. Each criterion is evaluated as “fully met,” “partly met,” “not met or inappropriate,” “not reported,” or “not applicable” for the dataset being reviewed. The evaluation concludes with a scheme for scoring the dataset as reliable with or without restrictions, not reliable, or not assignable, and is demonstrated with three case studies representing both organic and inorganic constituents, and different study designs and assessment purposes. Reliability evaluation can be used in conjunction with relevance evaluation (assessed separately) to determine the extent to which environmental monitoring datasets are “fit for purpose,” that is, suitable for use in various types of assessments. Integr Environ Assess Manag 2024;20:981–1003. © 2024 Society of Environmental Toxicology & Chemistry (SETAC). This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.
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