A three-dimensional numerical simulation of sulfate transport and redistribution
Bibliographic record
Abstract
We have utilized a relatively sophisticated dynamic cloud model combined with standard bulk-parameterized microphysics and simple sulfur chemistry to explore the impact of deep convection on modification and transport of a suite of pollutants. Two base run simulation parameters are used to initialize the cloud-chemistry model. The simulation of the 6 July 1995 case, with continental polluted field initialization, has revealed that a convective storm generates strong vertical transport of gases and particulate compounds from the planetary boundary layer (PBL) to the upper troposphere (UT), perturbation of aerosol physical and chemical properties, modification of pollutant concentration, and change of the spatial distributions of chemical species. The early formation of precipitation and enhanced scavenging contributed to a registration of approximately 2.5 times the concentration of sulfate in the precipitation near the surface than in the air found at this level. The Spring case numerical experiment on 3 April 2000 with a chemical background taken from Macedonia, provided insight into the potential influence of the long-range transport of atmospheric pollutants and ascertained quantitativequalitative information about processes by which acidic species are incorporated into precipitation. The model-computed parameters are in good agreement with observation. The average equivalent cloud water pH and rainwater pH when the higher acid precipitation occurs are about 5.0 and 4.5, respectively. The results from a number of sensitivity tests of cloud chemistry of the physical processes for the continental nonpolluted and continental polluted environments, indicate that nucleation and impact scavenging of aerosols account for between 20%24% of the total sulfur mass removed by wet deposition. Liquid-phase oxidation contributes about 20%28% of the sulfur content in precipitation. It means that neglecting liquid-phase oxidation when considering the chemistry in these clouds may lead to underestimates of about 20%28% in sulfate wet deposition. Neglect of the ice phase when considering the chemistry in continental nonpolluted and continental polluted clouds may lead to overestimates of about 112%130% of the total sulfur mass removed by wet deposition. The assumption of Henry's law equilibrium for those types of clouds gives an overestimation of about 100%120%, respectively. PACS Nos.: 51.10.+y, 92.60.Sz
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".