Passive sampling methods for contaminated sediments: Risk assessment and management
Bibliographic record
Abstract
Abstract This paper details how activity-based passive sampling methods (PSMs), which provide information on bioavailability in terms of freely dissolved contaminant concentrations (Cfree), can be used to better inform risk management decision making at multiple points in the process of assessing and managing contaminated sediment sites. PSMs can increase certainty in site investigation and management, because Cfree is a better predictor of bioavailability than total bulk sediment concentration (Ctotal) for 4 key endpoints included in conceptual site models (benthic organism toxicity, bioaccumulation, sediment flux, and water column exposures). The use of passive sampling devices (PSDs) presents challenges with respect to representative sampling for estimating average concentrations and other metrics relevant for exposure and risk assessment. These challenges can be addressed by designing studies that account for sources of variation associated with PSMs and considering appropriate spatial scales to meet study objectives. Possible applications of PSMs include: quantifying spatial and temporal trends in bioavailable contaminants, identifying and evaluating contaminant source contributions, calibrating site-specific models, and, improving weight-of-evidence based decision frameworks. PSM data can be used to assist in delineating sediment management zones based on likelihood of exposure effects, monitor remedy effectiveness, and, evaluate risk reduction after sediment treatment, disposal, or beneficial reuse after management actions. Examples are provided illustrating why PSMs and freely dissolved contaminant concentrations (Cfree) should be incorporated into contaminated sediment investigations and study designs to better focus on and understand contaminant bioavailability, more accurately estimate exposure to sediment-associated contaminants, and better inform risk management decisions. Research and communication needs for encouraging broader use are discussed. Integr Environ Assess Manag 2014;10:224–236. © 2014 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of SETAC. Key Points The freely dissolved concentration (Cfree) of a hydrophobic organic contaminant in sediment is a better predictor of bioavailability than the total concentration in bulk sediment. Passive sampling methods (PSMs) that target Cfree reduce uncertainty in site investigations by characterizing spatial and temporal contaminant trends, source contributions, calibrating models, and improving weight-of-evidence based decision frameworks. PSMs can help delineate sediment management zones, assess remedy effectiveness, and evaluate risk reduction following management action. Cfree can be used to better inform risk management decision making.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".