Quantifying Vehicle Emission Factors for Various Ambient Conditions using an On-Road, Real-Time Emissions System
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<div class="htmlview paragraph">This paper demonstrates vehicle emission factor measurement using an on-board, on-road system and examines the effects of ambient temperature on those emission factors. Vehicle operating parameters, fuel consumption and emissions were measured on-road using a portable measurement system designed for ease of use with a range of vehicles, drivers and driving situations. The results reported here come from repeated trips over a 17.4 km urban / suburban route with a particular driver and vehicle. As such, the emission factors developed here do not represent the current on-road fleet. However, they show the strong influence of actual operating conditions (particularly ambient temperature) and of the vehicle control system's response to non-standard conditions. This leads to an appreciation for on-road testing as a means to illustrate vehicle emission behavior in real conditions and to highlight conditions which may require more detailed study.</div> <div class="htmlview paragraph">A series of trips over a one year period, (with an ambient temperature range of -25 to +20°C), were analyzed to develop emission factor models with one, two or three emission factors. The results emphasize the inadequacy of using a single “grams-per-mile” emission factor to model emissions of vehicles operating over a range of trip lengths and ambient conditions. A two-emission-factor model provides adequate information to accommodate short trip lengths and a three-emission-factor model can fit the detailed behavior but is generally not required.</div>
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 it