TFA from HFO-1234yf: Accumulation and aquatic risk in terminal water bodies
Bibliographic record
Abstract
A next-generation mobile automobile air-conditioning (MAC) refrigerant, HFO-1234yf (CF(3) CF = CH(2)), is being developed with improved environmental characteristics. In the atmosphere, it ultimately forms trifluoroacetic acid (TFA(A); CF(3)COOH), which is subsequently scavenged by precipitation and deposited on land and water as trifluoroacetate (TFA; CF(3)COO(-)). Trifluoroacetate is environmentally stable and has the potential to accumulate in terminal water bodies, that is, aquatic systems receiving inflow but with little or no outflow and with high rates of evaporation. Previous studies have estimated the emission rates of HFO-1234yf and have modeled the deposition concentrations and rates of TFA across North America. The present study uses multimedia modeling and geographic information system (GIS)-based modeling to assess the potential concentrations of TFA in terminal water bodies over extended periods. After 10 years of emissions, predicted concentrations of TFA in terminal water bodies across North America are estimated to range between current background levels (i.e., 0.01-0.22 µg/L) and 1 to 6 µg/L. After 50 years of continuous emissions, aquatic concentrations of 1 to 15 µg/L are predicted, with extreme concentrations of up to 50 to 200 µg/L in settings such as the Sonoran Desert along the California/Arizona (USA) border. Based on the relative insensitivity of aquatic organisms to TFA, predicted concentrations of TFA in terminal water bodies are not expected to impair aquatic systems, even considering potential emissions over extended periods.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".