Vertically resolved chemical characteristics and sources of submicron aerosols measured on a Tall Tower in a suburban area near Denver, Colorado in winter
Bibliographic record
Abstract
Abstract The Nitrogen, Aerosol Composition, and Halogens on a Tall Tower study was conducted at the Boulder Atmospheric Observatory in Colorado during February–March 2011. A compact time‐of‐flight aerosol mass spectrometer was installed in a moving carriage on the tower, obtaining vertical profiles of submicron nonrefractory aerosol mass concentrations ( ) from 0–265 m above ground level. The average was 4.6 ± 5.7 µg/m3, with average contributions of nitrate, organics, sulfate, ammonium, and chloride of 35%, 26%, 20%, 17%, and 1%, respectively. Positive Matrix Factorization analysis of the organic aerosol (OA) mass spectra indicated that average contributions of oxygenated organic aerosol (OOA)‐I, OOA‐II, and hydrocarbon‐like organic aerosol (surrogates for aged and fresh secondary OA and primary OA, respectively) to OA mass were 52%, 32%, and 16%, respectively. There was considerable variability in the vertical profiles of aerosol mass loading and composition, especially at the lowest heights. Below 40 m, the highest concentrations were composed of mostly nitrate (30–46%) and were associated with winds from the northeast where there are large agricultural facilities. When winds were southerly, mass distributions near the surface had small, fresh OA, indicating the influence of nearby Denver urban emissions at the site. The largest contribution to OA mass at these heights was OOA‐II (~43%). Between 40 and 120 m, trajectory cluster analysis indicated that during high‐altitude long‐range transport events, daytime aerosol composition was dominated by sulfate, whereas during low‐altitude transport events, the contributions of sulfate, nitrate, and OA were comparable. OOA‐I contributed the most (53–68%) to OA mass at these tower heights.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 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 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".