Aerosol Transport and Source Attribution Using Sunphotometers, Models and In-Situ Chemical Composition Measurements
Bibliographic record
Abstract
Understanding of chemical, physical, and radiative processes-emissions, transport, deposition, and modification of aerosol optical properties due to ageing-is of major importance to global and regional climate simulations and projections as well as health impairment. This paper presents aerosol optical properties retrieved with the Multifilter Rotating Shadowband Radiometers (MFRSRs) and the source attribution based on back trajectories and in situ aerosol chemical composition analysis obtained during the Aerosol Life Cycle Intensive Observational Period at Brookhaven National Laboratory on Long Island, NY, during July and August 2011. The aerosol optical properties retrieved with the MFRSR exhibit excellent agreement with those obtained with a colocated Cimel sunphotometer. Apportioning aerosol optical depths by size modes reveals several episodes of high loading of fine aerosol (diameter less than 2.5 μm). Analysis of optical and physical properties of aerosols as well as their chemical composition obtained by an in situ high-resolution time-of-flight aerosol mass spectrometer together with back trajectories indicates that the principal source of high concentrations of fine aerosols observed during July 18-24 was forest fires in western Canada, consistent with reports by the Canadian Forest Service and satellite observations by the Moderate Resolution Imaging Spectroradiometer (MODIS).
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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".