HFC-152a and HFC-134a emission estimates and characterization of CFCs, CFC replacements, and other halogenated solvents measured during the 2008 ARCTAS campaign (CARB phase) over the South Coast Air Basin of California
Bibliographic record
Abstract
Abstract. This work presents results from the NASA Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) study. Whole air samples were obtained on board research flights that flew over California during June 2008 and analyzed for selected volatile organic compounds, including several halogenated species. Samples collected over the South Coast Air Basin of California (SoCAB), which includes much of Los Angeles (LA) County, were compared with samples from inflow air masses over the Pacific Ocean. The levels of many halocarbon species were enhanced significantly over the SoCAB, including compounds regulated by the Montreal Protocol and subsequent amendments. Emissions estimates of HFC-152a (1,1-difluoroethane, CH3CHF2; 0.82 ± 0.11 Gg) and HFC-134a (1,1,1,2-tetrafluoroethane, CH2FCF3; 1.16 ± 0.22 Gg) in LA County for 2008 were obtained using the observed HFC:carbon monoxide (CO) enhancement ratio. Emission rates also were calculated for the SoCAB (1.60 ± 0.22 Gg yr−1 for HFC-152a and 2.12 ± 0.28 Gg yr−1 for HFC-134a) and then extrapolated to the United States (32 ± 4 Gg yr−1 for HFC-152a and 43 ± 6 Gg yr−1 for HFC-134a) using population data. In addition, emission rates of the two HFCs in LA County and SoCAB were calculated by a second method that utilizes air quality modeling. Emissions estimates obtained using both methods differ by less than 25% for the LA County and less than 45% for the SoCAB.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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 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".