Passive sampling methods for contaminated sediments: Scientific rationale supporting use of freely dissolved concentrations
Bibliographic record
Abstract
Abstract Passive sampling methods (PSMs) allow the quantification of the freely dissolved concentration (Cfree) of an organic contaminant even in complex matrices such as sediments. Cfree is directly related to a contaminant's chemical activity, which drives spontaneous processes including diffusive uptake into benthic organisms and exchange with the overlying water column. Consequently, Cfree provides a more relevant dose metric than total sediment concentration. Recent developments in PSMs have significantly improved our ability to reliably measure even very low levels of Cfree. Application of PSMs in sediments is preferably conducted in the equilibrium regime, where freely dissolved concentrations in the sediment are well-linked to the measured concentration in the sampler via analyte-specific partition ratios. The equilibrium condition can then be assured by measuring a time series or a single time point using passive samplers with different surface to volume ratios. Sampling in the kinetic regime is also possible and generally involves the application of performance reference compounds for the calibration. Based on previous research on hydrophobic organic contaminants, it is concluded that Cfree allows a direct assessment of 1) contaminant exchange and equilibrium status between sediment and overlying water, 2) benthic bioaccumulation, and 3) potential toxicity to benthic organisms. Thus, the use of PSMs to measure Cfree provides an improved basis for the mechanistic understanding of fate and transport processes in sediments and has the potential to significantly improve risk assessment and management of contaminated sediments. Integr Environ Assess Manag 2014;10:197–209. © 2014 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of SETAC. Key Points Passive sampling methods (PSMs) can quantify the freely dissolved concentration (Cfree) of a hydrophobic organic contaminant in sediment. Cfree is directly related to chemical activity, which drives diffusive uptake into benthic organisms and exchange across the sediment-water interface. Cfree and chemical activity offer a well-defined basis for the mechanistic understanding of fate and transport processes in sediments and for predicting adverse effects to benthic organisms. Recent developments in PSMs are advancing practical application to improve risk assessment and management of contaminated sediments.
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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 | 0.055 | 0.062 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.013 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".