Development of a Solid-Phase Microextraction-Based Method for Sampling of Persistent Chlorinated Hydrocarbons in an Urbanized Coastal Environment
Bibliographic record
Abstract
Solid-phase microextraction (SPME) has been used as an in situ sampling technique for a wide range of volatile organic chemicals, but SPME field sampling of nonvolatile organic pollutants has not been reported. This paper describes the development of an SPME-based sampling method employing a poly(dimethylsiloxane) (PDMS)-coated (100-microm thickness) fiber as the sorbent phase. The laboratory-calibrated PDMS-coated fibers were used to construct SPME samplers, and field tests were conducted at three coastal locations off southern California to determine the equilibrium sampling time and compare the efficacy of the SPME samplers with that of an Infiltrex 100 water pumping system (Axys Environmental Systems Ltd., Sidney, British Columbia, Canada). p,p'-DDE and o,p'-DDE were the components consistently detected in the SPME samples among 42 polychlorinated biphenyl congeners and 17 chlorinated pesticidestargeted. SPME samplers deployed attwo locations with moderate and high levels of contamination for 18 and 30 d, respectively, attained statistically identical concentrations of p,p'-DDE and o,p'-DDE. In addition, SPME samplers deployed for 23 and 43 d, respectively, at a location of low contamination also contained statistically identical concentrations of p,p'-DDE. These results indicate that equilibrium could be reached within 18 to 23 d. The concentrations of p,p'-DDE, o,p'-DDE, or p,p'-DDD obtained with the SPME samplers and the Infiltrex 100 system were virtually identical. In particular, two water column concentration profiles of p,p'-DDE and o,p'-DDE acquired by the SPME samplers at a highly contaminated site on the Palos Verdes Shelf overlapped with the profiles obtained by the Infiltrex 100 system in 1997. The field tests not only reveal the advantages of the SPME samplers compared to the Infiltrex 100 system and other integrative passive devices but also indicate the need to improve the sensitivity of the SPME-based sampling technique.
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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) | 0.001 | 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".