Passive sampling methods for contaminated sediments: Practical guidance for selection, calibration, and implementation
Why this work is in the frame
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Bibliographic record
Abstract
Abstract This article provides practical guidance on the use of passive sampling methods (PSMs) that target the freely dissolved concentration (Cfree) for improved exposure assessment of hydrophobic organic chemicals in sediments. Primary considerations for selecting a PSM for a specific application include clear delineation of measurement goals for Cfree, whether laboratory-based “ex situ” and/or field-based “in situ” application is desired, and ultimately which PSM is best-suited to fulfill the measurement objectives. Guidelines for proper calibration and validation of PSMs, including use of provisional values for polymer–water partition coefficients, determination of equilibrium status, and confirmation of nondepletive measurement conditions are defined. A hypothetical example is described to illustrate how the measurement of Cfree afforded by PSMs reduces uncertainty in assessing narcotic toxicity for sediments contaminated with polycyclic aromatic hydrocarbons. The article concludes with a discussion of future research that will improve the quality and robustness of Cfree measurements using PSMs, providing a sound scientific basis to support risk assessment and contaminated sediment management decisions. Integr Environ Assess Manag 2014;10:210–223. © 2014 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of SETAC. Key Points Specific guidance is provided for the use of passive sampling methods for measuring freely dissolved concentrations in contaminated sediment site assessments. Guidelines are provided for proper calibration and validation of passive sampling methods including use of provisional values for polymer-water partition coefficients. Determination of equilibrium status and confirmation of non-depletive measurement conditions are defined. Further development is needed for the use of non-equilibrium passive sampling methods in the field and the validation of performance reference compound use in static sediment environments.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it