Application of Solid Phase Extraction (SPE) Media Rods to Assess Degree of NAPL Encapsulation in <i>In Situ</i> Deposited NAPL Sediments
Bibliographic record
Abstract
Oil-particle aggregates (OPAs) develop from solid particles attaching to and/or penetrating into the surface of a non-aqueous phase liquid (NAPL) bead suspended in the water column. In situ deposited NAPL (IDN) sediments result from the deposition of OPAs on the sediment bed at the bottom of the water body. The extent of solid particle coverage on the surface of the oil bead defines the degree of encapsulation of the OPA (i.e., fully or partially encapsulated). Since important properties such as NAPL mobility and contaminant flux are controlled by the degree of OPA encapsulation, the ability to measure this physical property is critical in characterizing NAPL fate and transport in IDN sediments.This paper describes a semi-quantitative method to measure the degree of encapsulation within IDN sediment using the fluorescence response from rods coated with solid phase extraction (SPE) media. Specifically, Direct Analysis in Real Time (DART®) technology, which was developed and is distributed by Dakota Technologies, was applied to measure the amount of contact between the SPE material coated on a vertical rod and the PAHs contained in the NAPL found in the surrounding IDN sediment. Based on laboratory results in this paper, the magnitude of the fluorescence response correlates with the degree of encapsulation. For the single NAPL and various sediment combinations prepared in the laboratory for this study, fully (or nearly fully) encapsulated IDN sediments produced a DART® response below 15% reference emitter (%RE), a defined internal standard, whereas partially encapsulated IDN sediments produced a DART® response that was generally above 30%RE and as high as several thousand %RE. This difference in fluorescence response enables DART® technology to be applied as a line of evidence to determine the degree of NAPL encapsulation in an IDN sediment in field screening programs.
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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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".