Highly time‐resolved organic and elemental carbon measurements at the Baltimore Supersite in 2002
Bibliographic record
Abstract
Organic carbon (OC) and elemental carbon (EC) in fine particles (PM 2.5 ) were measured at the Baltimore Supersite at Ponca Street for 9.5 months in 2002 using a Sunset Laboratory carbon analyzer with 1‐hour time resolution. Monthly EC and CO diurnal averages were characterized by pronounced peaks in the early morning commute hours. OC concentration profiles were similar to CO and EC during the morning and evening rush hours, except when high ozone episodes occurred, i.e., generally in summer. Primary and secondary OC contributions were estimated during ozone episodes exceeding 100 ppb (1‐hour average). The largest 1‐hour ozone concentrations for the entire study period occurred between 11 and 13 August, during which secondary OC contributed, on average, ∼60% of the hourly OC concentrations and a maximum of 82%. Additionally, the annual EC emission rate is estimated for Maryland using published CO emission inventory data and a mean EC/CO ratio (0.0023 ± 0.0008) derived by regressing selected EC and CO measurements for each of the 9.5 months. The result, 2.31 ± 0.80 Gg EC yr −1 , is similar to the estimate (2.95 Gg EC yr −1 ), determined on the basis of the PM 2.5 emission inventory for Maryland and the mean EC abundance in PM 2.5 measured with a U.S. Environmental Protection Agency speciation monitor in 2002. Finally, the Baltimore Supersite and much of the northeastern United States experienced severe smoke fumigation in early July 2002 owing to uncontrolled forest fires in Quebec, during which time, CO, EC, and OC were predominately associated with the Canadian smoke. During this episode, EC emissions are estimated to be 4.75 Gg EC from Canadian Quebec natural fires in July, and an annual release rate of 9.94 Gg EC yr −1 is estimated for all Canadian boreal forest fires.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".