Semivolatile Organic Compounds in Window Films from Lower Manhattan after the September 11th World Trade Center Attacks
Bibliographic record
Abstract
The September 11th World Trade Center (WTC) terrorist attacks resulted in the large-scale release of contaminants that were deposited on the environment of New York City (NYC). Six weeks after the attacks, samples of an organic film on window surfaces were collected and analyzed for polybrominated diphenyl ethers (PBDE), polychlorinated biphenyls (PCB), polychlorinated naphthalenes (PCN), polycyclic aromatic hydrocarbons (PAH), and organochlorine pesticides (OCPs). Concentrations dropped by an order of magnitude within 1 km of the WTC and reached background concentrations by 3.5 km. Concentrations within 1 km of the WTC averaged 3280 ng/m2 for sigmaPBDE, 900 ng/m2 for sigmaPCB, 33 ng/m2 for sigmaPCN, and 77100 ng/m2 for sigmaPAH. Congener profiles of the sites nearest the WTC suggested a combination of combustion and evaporative sources of all compounds, whereas the background sites exhibited profiles consistent with evaporative sources. PBDE profiles showed enrichment in lower molecular weight congeners near the WTC, suggesting that these congeners were formed as a result of the combustion conditions. Homologue fractions of PCN combustion markers were approximately 2-9 times greater at near WTC sites compared to background NYC. Gas-phase air concentrations were back-calculated from measured film concentrations using the film-air partition coefficient (KFA), and calculated air concentrations followed spatial trends observed in films.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".