Affiliation:
1. US Geological Survey California Water Science Center Sacramento California USA
2. Deltares Delft The Netherlands
3. Practical Stats LLC Castle Rock Colorado USA
4. CNR IRSA (National Research Council—Water Research Institute) Italy
5. Fraunhofer Institute for Molecular Biology and Applied Ecology (Fraunhofer IME) Schmallenberg Germany
6. Department of Materials and Environmental Chemistry (MMK) Stockholm University Stockholm Sweden
7. WCA Environment Ltd. Oxfordshire UK
Abstract
AbstractEnvironmental 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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