Urban sources of synthetic musk compounds to the environment
Bibliographic record
Abstract
The occurrence and potential sources of synthetic musk compounds (SMCs) in the urban and surrounding environment were investigated. We analyzed air, soils and surface waters from a wide array of land-use types and urban densities including air from wastewater treatment plants (WWTPs), indoor, urban, rural, and remote Arctic sites; surface waters from urban and rural tributaries; and effluents of three WWTPs. In air, the median sum concentration of six selected polycyclic musks (Σ6PCMs) (i.e., galaxolide, tonalide, cashmeran, celestolide, phantolide, traseolide) were the highest from WWTP on-site > indoor > urban > WWTP off-site > rural. SMCs were not found in remote Arctic air indicating low potential for long-range atmospheric transport. SMCs were not found in soils, likely because of their high volatility and fast biodegradation rate. Galaxolide (HHCB) and tonalide (AHTN) were the two most abundant SMCs in air, tributaries and WWTP effluents. Σ6PCM concentrations in air taken along urban-rural transects and in tributary water were positively correlated with population density. In WWTP on-site air, trace levels of the toxic nitro-musks, namely musk xylene and musk ketone were detected and macrocyclic musks accounted for ∼10% of the total SMCs measured. In WWTP effluents, the concentrations of Σ6PCMs were proportional to the population served. We conclude that sources of SMCs to the outdoor urban environment and hence the surrounding region, originate from releases from indoor air, and temperature-dependent volatilization from WWTPs during treatment.
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 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".