Ozone Uptake Kinetics and Implications for the Extent of Modification of Airborne Pollen
Bibliographic record
Abstract
Ground-level ozone, a highly reactive air pollutant, is known to cause significant damage to biological surfaces. Understanding the interaction between ozone and pollen is crucial, as it may influence pollen allergenicity and reproductive viability. Measurements were conducted to determine the kinetics and extent of ozone uptake for 12 different types of tree pollen (Birch, Sycamore Maple, Box Elder Maple, Alder Gray, Cypress, Ash, Mulberry, Juniper, White Pine, Lombardy Poplar, Red Oak, and Black Oak). The results revealed an initial rapid uptake of ozone, followed by a gradual decline due to the saturation of surface reaction sites and the depletion of reactive substances. The geometric initial uptake coefficients (γ 0 -geo) ranged from 0.4 to 6.4 × 10 –5, and surface saturation was reached under our experimental conditions on a time scale of 1500–10,000 s. Using the integrated uptake of ozone over the observation period, we calculated surface site concentrations of 10 14 –10 16 sites cm –2 . Most experiments were performed under dry conditions, but tests with Birch at intermediate relative humidities, up to 60%, showed that the presence of water may decrease the uptake coefficient by a factor of 2. When Ash, Birch and Black Oak pollen grains were manually crushed to mimic subpollen particles, they were found to take up orders of magnitude more ozone for the same mass of pollen. For pollen grains washed in acetone to extract soluble molecules from the pollen coat, the cumulative ozone uptake for some pollen types was significantly reduced. This reduction was interpreted to arise as a loss of reactive surface sites and lipids with C═C bonds, which are crucial for ozone interactions. The presence of highly antioxidant molecules, like carotenoids in Ash, was confirmed spectroscopically, and linked to the extremely high cumulative uptake of ozone, suggesting a protective role for the pollen coat. A box model representing diurnally varying emissions, ozone oxidation and deposition was used to estimate the typical extent of oxidation of airborne pollen. The model indicated that surface oxidation peaked in the afternoon and evening concurrent with high ozone levels, and the percent oxidation ranged from 24% to 97% depending on the pollen species. Sensitivity analysis suggested that conclusively determining whether pollen grains are fully oxidized or unoxidized in the atmosphere is challenging. Instead, the extent of oxidation falls within a range that warrants further investigation into its impact on pollen and human exposure.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".