Experimental investigation of ion–ion recombination under atmospheric conditions
Bibliographic record
Abstract
Abstract. We present the results of laboratory measurements of the ion–ion recombination coefficient at different temperatures, relative humidities and concentrations of ozone and sulfur dioxide. The experiments were carried out using the Cosmics Leaving OUtdoor Droplets (CLOUD) chamber at CERN, the walls of which are made of conductive material, making it possible to measure small ions. We produced ions in the chamber using a 3.5 GeV c−1 beam of positively charged pions (π+) generated by the CERN Proton Synchrotron (PS). When the PS was switched off, galactic cosmic rays were the only ionization source in the chamber. The range of the ion production rate varied from 2 to 100 cm−3 s−1, covering the typical range of ionization throughout the troposphere. The temperature ranged from −55 to 20 °C, the relative humidity (RH) from 0 to 70 %, the SO2 concentration from 0 to 40 ppb, and the ozone concentration from 200 to 700 ppb. The best agreement of the retrieved ion–ion recombination coefficient with the commonly used literature value of 1.6 × 10−6 cm3 s−1 was found at a temperature of 5 °C and a RH of 40 % (1.5 ± 0.6) × 10−6 cm3 s−1. At 20 °C and 40 % RH, the retrieved ion–ion recombination coefficient was instead (2.3 ± 0.7) × 10−6 cm3 s−1. We observed no dependency of the ion–ion recombination coefficient on ozone concentration and a weak variation with sulfur dioxide concentration. However, we observed a more than fourfold increase in the ion–ion recombination coefficient with decreasing temperature. We compared our results with three different models and found an overall agreement for temperatures above 0 °C, but a disagreement at lower temperatures. We observed a strong increase in the recombination coefficient for decreasing relative humidities, which has not been reported previously.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".