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Published on: December 4, 2016
Survey of methodologies for developing media screening values for ecological risk assessment
Mace G Barron1, Steven R Wharton
1Gulf Ecology Division, U.S. Environmental Protection Agency, 1 Sabine Island Drive, Gulf Breeze, Florida 32561, USA. barron.mace@epa.gov
This review examines 13 screening value (SV) compilations used in ecological risk assessment (ERA). Methodologies vary, often relying on outdated data, impacting risk assessment accuracy.
Area of Science:
- Environmental Science
- Ecotoxicology
- Risk Assessment
Background:
- Screening values (SVs) are crucial for ecological risk assessment (ERA).
- Numerous SV compilations exist, originating from various national and international agencies.
- Understanding the derivation of these SVs is essential for accurate risk characterization.
Purpose of the Study:
- To critically evaluate the methodologies behind 13 commonly used screening value compilations for ERA.
- To identify inconsistencies and limitations in the derivation of SVs for surface water, sediment, and soil.
- To inform risk assessors about the technical basis and uncertainties associated with SVs.
Main Methods:
- Systematic review of 13 SV compilations from diverse sources (e.g., government agencies, ORNL, international bodies).
- Analysis of methodologies used for deriving surface water, sediment, and soil SVs.
- Assessment of data sources, statistical approaches, and uncertainty factors employed.
Main Results:
- Surface water SVs primarily protect aquatic organisms using statistical assessments or uncertainty factors.
- Sediment SVs focus on benthic invertebrates, employing statistical interpretations or equilibrium partitioning.
- Soil SVs exhibit diverse derivations, often based on terrestrial toxicity or modeled ingestion/accumulation.
Conclusions:
- SV methodologies and conservatism vary significantly across compilations.
- Many SVs are based on secondary derivations, outdated values, or limited toxicity data.
- Risk assessors must critically evaluate SVs' technical basis and associated uncertainties for reliable ERA.
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