Polychlorinated Naphthalenes in the Global Atmospheric Passive Sampling (GAPS) Study
Bibliographic record
Abstract
Air concentrations of polychlorinated naphthalenes (PCNs) were measured as part of the Global Atmospheric Passive Sampling (GAPS) study to assess their spatial distribution on a worldwide basis for the first sampling period between December 2004 and March 2005. Results from more than 40 sites on seven continents show that PCNs are widespread, and highest levels are detected in urban/industrial locations consistent with other air sampling studies. The geometric mean air concentration of sigmaPCN is 1.6 pg/m3, ranging from below detection limit to 32 pg/m3. With technical PCN mixtures largely no longer produced, combustion inputs may be contributing increasingly to contemporary PCN air burden globally. Enrichment of combustion-related congeners, e.g., PCN-52/60, -50, -51,-54, and -66/67, is observed in the congeneric compositions of air at nearly all sites compared to relatively minor contribution of these congeners in technical PCN formulations. Further evidence of current combustion sources influencing global PCN levels is a higher relative abundance of combustion-related congeners quantified by sigmaPCNcombustion/sigmaPCN. The relative contribution by combustion sources and emissions from technical PCN mixtures is expected to vary among sites since it depends on the combustion sources and the technical mixture used in a particular country or region.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".