Characterizing the origin and long-range transport behavior of persistent organic pollutants in the North American atmospheric environment using passive samplers
Bibliographic record
Abstract
Monitoring is recognized as an essential tool for identifying status and spatial and temporal trends of persistent organic pollutant (POPs) in the atmosphere. To investigate the origin and long-range transport behavior of POPs in air, a novel passive air sampler (PAS) was developed based on the polystyrene/divinylbenzene co-polymeric resin XAD. The PAS was characterized by sorption measurements of chlorobenzenes onto XAD at various temperatures, wind tunnel experiments and computer simulations of the uptake kinetics, and field calibration experiments under Arctic and temperate conditions. The performance of this PAS was evaluated by comparing PAS-derived concentrations with those measured by conventional HiVol samplers. These studies demonstrated the usefulness of XAD-based PAS for atmospheric POP monitoring. A PAS network was established across North America, consisting of 40 stations covering 72 degrees of latitude (10° to 82°N) from the Arctic to Costa Rica and 72 degrees of longitude (53° to 125°W) from Newfoundland to Vancouver Island. Four of these stations constituted an altitudinal transect in the southern Canadian Rocky Mountains, covering an elevational range of more than 1500m. Annually averaged air concentrations of organochlorine pesticides (OCPs), polychlorinated biphenyls (PCBs), and polybrominated diphenyl ethers (PBDEs) were determined in 2000/2001 at these stations, as was the enantiomeric composition of chiral OCPs. The distribution patterns of the POPs were found to depend on their physical-chemical properties, their emission history, and the environmental conditions. Evidence for global fractionation along latitude and altitude was observed. Multivariate statistical analysis allowed for a better understanding of the observed composition patterns of PCBs and PBDEs. Estimation of the long range transport potential of OCPs, empirically from network concentrations, and theoretically from model calculations yielded a comparable classification. In order to have consistent input data for these model simulations, a complete set of partitioning properties (aqueous solubility, octanol-water partition coefficient, vapor pressure, Henry's law constant, octanol-air partition coefficient) for fourteen OCPs was derived by compiling, evaluating, selecting, and adjusting all measured values reported in the literature. Large scale PAS networks are suitable for monitoring compliance with, and effectiveness of, regulatory control measures, and for establishing experimentally the atmospheric long-range transport behavior of POPs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".