Seasonal air concentration variability, gas–particle partitioning, precipitation scavenging, and air–water equilibrium of organophosphate esters in southern Canada
Bibliographic record
Abstract
In response to increasing production and application volumes, organophosphate esters (OPEs) have emerged as pervasively detected contaminants in various environmental media, with concentrations often exceeding those of traditional organic contaminants. Despite the recognition of the atmosphere's important role in dispersing OPEs and a substantial number of studies quantifying OPEs in air, investigations into atmospheric phase distribution processes are rare. Using measurements of OPEs in the atmospheric gas and particle phase, in precipitation, and in surface water collected in southern Canada, we explored the seasonal concentration variability, gas–particle partitioning behaviour, precipitation scavenging, and air–water equilibrium status of OPEs. Whereas consistent seasonal trends were not observed for OPE concentrations in precipitation or atmospheric particles, gas phase concentrations of several OPEs were elevated during the summer in suburban Toronto and at two remote sites on Canada's eastern and western coast. Apparent enthalpies of air–surface exchange fell mainly within or slightly above the range of air–water and air–octanol enthalpies of exchange, indicating the influence of local air–surface exchange processes and/or seasonally variable source strength. While many OPEs were present with a notable fraction in both the gas and particle phase, no clear relationship with compound volatility was apparent, although there was a tendency for higher particle-bound fractions at a lower temperature. High precipitation scavenging ratios for OPEs measured at the two coastal sites are consistent with low air–water partitioning ratios and the association with particles. Although beset by large uncertainties, air–water equilibrium calculations suggest net deposition of gaseous OPEs from the atmosphere to the Salish Sea and the St. Lawrence River and St. Lawrence Estuary. The measured seasonal concentration variability is likely less a reflection of temperature-driven air–surface exchange and instead indicates that more OPEs enter or are formed in the atmosphere in summer. More research is needed to better understand the atmospheric gas–particle partitioning behaviour of the OPEs and how it may be influenced by transformation reactions.
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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 | 0.002 |
| Science and technology studies | 0.002 | 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".