Seasonality of the Water-Soluble Inorganic Ion Composition and Water Uptake Behavior of Urban Grime
Bibliographic record
Abstract
Abstract Impervious surfaces, especially in urban environments, are coated with a film composed of a complex mixture of substances, referred to as urban grime. Despite its ubiquity, the factors that dictate urban grime composition are still not well understood. Here, we present the first study of the seasonal variation in composition of water-soluble inorganic ions present in urban grime, performed by analyzing samples collected in Toronto for 4-week intervals over the course of a year. A clear seasonality in the composition is evident, with NaCl dominating in the winter months and Ca2+ and NO3– dominant in the summer. We compare the grime composition to the water-soluble ion composition of PM2.5 and PM10 in order to infer chemistry occurring within the grime and find evidence that chemistry occurring within the urban grime matrix could provide a source of ClNO2 and NH3 to the urban atmosphere. The uptake of water by urban grime also shows a clear seasonality, which may be driven by the changing proportions of nitrate salts and/or oxidized organic compounds over the year.
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) | 0.001 | 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".