Analytical methods for PCBs and organochlorine pesticides in environmental monitoring and surveillance: a critical appraisal
Bibliographic record
Abstract
Analytical methods for the analysis of polychlorinated biphenyls (PCBs) and organochlorine pesticides (OCPs) are widely available and are the result of a vast amount of environmental analytical method development and research on persistent organic pollutants (POPs) over the past 30-40 years. This review summarizes procedures and examines new approaches for extraction, isolation, identification and quantification of individual congeners/isomers of the PCBs and OCPs. Critical to the successful application of this methodology is the collection, preparation, and storage of samples, as well as specific quality control and reporting criteria, and therefore these are also discussed. With the signing of the Stockholm convention on POPs and the development of global monitoring programs, there is an increased need for laboratories in developing countries to determine PCBs and OCPs. Thus, while this review attempts to summarize the current best practices for analysis of PCBs and OCPs, a major focus is the need for low-cost methods that can be easily implemented in developing countries. A "performance based" process is described whereby individual laboratories can adapt methods best suited to their situations. Access to modern capillary gas chromatography (GC) equipment with either electron capture or low-resolution mass spectrometry (MS) detection to separate and quantify OCP/PCBs is essential. However, screening of samples, especially in areas of known use of OCPs or PCBs, could be accomplished with bioanalytical methods such as specific commercially available enzyme-linked immunoabsorbent assays and thus this topic is also reviewed. New analytical techniques such two-dimensional GC (2D-GC) and "fast GC" using GC-ECD may be well-suited for broader use in routine PCB/OCP analysis in the near future given their relatively low costs and ability to provide high-resolution separations of PCB/OCPs. Procedures with low environmental impact (SPME, microscale, low solvent use, etc.) are increasingly being used and may be particularly suited to developing countries.
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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 | 0.013 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".