Organic Composition, Chemistry, and Photochemistry of Urban Film in Leipzig, Germany
Bibliographic record
Abstract
In polluted urban environments, windows and building surfaces are coated with a complex film of chemicals. Despite its high surface-to-volume ratio and direct exposure to sunlight, few studies have directly investigated the role that this “urban film” may play in promoting the chemistry and photochemistry of semivolatile organic species contained within it. Here, we report results from a field investigation of the organic composition of urban film and particulate matter (PM10) samples collected at an urban site in Leipzig, Germany, in which we provide clear evidence for the influence of anthropogenic processes on film composition. In this study, we find that the ratio of water-soluble organic carbon (WSOC) to the total ionic content of film samples decreases with atmospheric exposure time, which suggests that urban film growth proceeds first via the condensation of semivolatile species, and that the coating thus formed enhances the dry deposition of particles. Further, we find that the polycyclic aromatic hydrocarbon (PAH) abundance profiles in light-exposed films are different from those in films collected under light-shielded conditions, which represents the first direct evidence that urban films serve as a photochemical sink for semivolatile organic pollutants. Finally, we find that the PAH and n-alkane profiles of urban film samples differ substantially from colocated PM10 samples, which we suggest reflects both the contribution of settled coarse particulate matter to the overall film composition and the influence of in-film oxidative processes. Together, these results highlight the unique reactive environment afforded by urban film and underscore the need for further studies of urban surface chemistry.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".