Analysis of cloud condensation nuclei composition and growth kinetics using a pumped counterflow virtual impactor and aerosol mass spectrometer
Bibliographic record
Abstract
Abstract. We present a new method of determining the size and composition of CCN-active aerosol particles. Method utility is illustrated through a series of ambient measurements. A continuous-flow thermal-gradient diffusion chamber (TGDC), pumped counterflow virtual impactor (PCVI), and Aerodyne time-of-flight mass spectrometer (AMS) are operated in series. Ambient particles are sampled into the TGDC, where a constant supersaturation is maintained, and CCN-active particles grow to ~2.5 ± 0.5 μm. The output flow from the TGDC is directed into the PCVI, where a counterflow of dry N2 gas opposes the particle-laden flow, creating a region of zero axial velocity. This stagnation plane can only be traversed by particles with sufficient momentum, which depends on their size. Particles that have activated in the TGDC cross the stagnation plane and are entrained in the PCVI output flow, while the unactivated particles are diverted to a pump. Because the input gas is replaced by the counterflow gas with better than 99 % efficiency at the stagnation plane, the output flow consists almost entirely of dry N2 and water evaporates from the activated particles. In this way, the system yields an ensemble of CCN-active particles whose chemical composition and size are analyzed using the AMS. Measurements of urban aerosol in downtown Toronto identified an external mixture of CCN-active particles consisting almost entirely of ammonium nitrate and ammonium sulfate, with CCN-inactive particles of the same size consisting of a mixture of ammonium nitrate, ammonium sulfate, and organics. We also discuss results from the first field deployment of the TGDC-PCVI-AMS system, conducted from mid-May to mid-June 2007 in Egbert, Ontario, a semirural site ~80 km north of Toronto influenced both by clean air masses from the north and emissions from the city. Organic-dominated particles sampled during a major biogenic event exhibited higher CCN activity and/or faster growth kinetics than urban outflow from Toronto, despite the latter having a higher inorganic content and higher O:C ratio. During both events, particles were largely internally mixed.
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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) | 0.001 | 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 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".