Modeling the impact of sea-spray on particle concentrations in a coastal city
Bibliographic record
Abstract
An atmospheric chemistry-transport model is used to assess the impacts of sea-spray chemistry on the particle composition in and downwind of a coastal city--Vancouver, British Columbia. Reactions in/on sea-spray affect the entire particle ensemble and particularly the size distribution of particle nitrate. Urban air quality, and particularly airborne particles, is a major concern in terms of human health impacts. Sea-spray is known to be a major component of the particle ensemble at coastal sites yet relatively few air quality models include the interaction of gases with sea-spray and the fate of the particles produced. Sea-spray is not an inert addition to the particle ensemble because heterogeneous chemistry in/on sea-spray droplets changes the droplets composition and the particle size distribution, which impacts deposition and the ion balance in different particle size fractions. It is shown that the ISOPART model is capable of simulating gas and particle concentrations in the coastal metropolis of Vancouver and the surrounding valley. It is also demonstrated that to accurately simulate ambient concentrations of particles and reactive/soluble gases in a coastal valley it is absolutely critical to include heterogeneous chemistry in/on sea-spray. Partitioning of total particle-NO{sub 3}{sup -} between sea-spray and NH{sub 4}NO{sub 3} is highly sensitive to the amount of sea-spray present, and hence the initial vertical profile, sea-spray source functions [48] and the wind speed. When a fixed wind speed is used to initialize the sea-spray vertical profiles, as expected, the sea-spray concentration decays with distance inland, but the particle-NO{sub 3}{sup -} concentration decays more slowly because it is also a function of the uptake rate for HNO{sub 3}. The simulation results imply model analyses of air quality in coastal cities conducted without inclusion of sea-spray interactions may yield highly misleading results in terms of emission sensitivities of the PM size distribution. The sensitivity of the model results to the initial sea spray profile further suggests there would be great benefit in better definition of the vertical profile of size resolved sea-spray for use in such model studies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".