Heavy-Duty Diesel Engine Performance and Comparative Emission Measurements for Different Biodiesel Blends Used in the Montreal BIOBUS Project
Bibliographic record
Abstract
This paper reports the emissions measurement results of the BIOBUS project1. Environment Canada's facilities at the Emissions Research and Measurement Division (ERMD) in Ottawa were used to conduct detailed emission measurements in order to compare the two engine types used by the urban transit bus operator in Montreal; Société des transports de Montréal (STM). The test engines were operated on 500 ppm sulphur diesel fuel, and biodiesel blends of 3 different origins (vegetable oil, animal fat and used cooking oil) at 2 different concentrations (5% and 20%). Tests were conducted using a 1998 and a 2000 model year, four-stroke, 250-HP, Cummins Diesel engines equipped with either a mechanical fuel injection pump or a computer-controlled electronic fuel injection system. All emissions tests were conducted with a degreened diesel oxidation catalyst in place, as is typical for the STM buses purchased from Nova Bus. Particle size distribution measurements and extensive chemical analysis were performed in addition to the regulated emissions. The biodiesel evaluation was a joint effort by the Canadian Renewable Fuels Association, the Fédération des producteurs de cultures commerciales du Québec, Rothsay/Laurenco, and STM, with the support of the Canadian Federal and Quebec Provincial governments. The use of biodiesel was evaluated in severe climatic conditions (from -31°C to +31°C) on 155 urban transit buses for one year from March 2002 to March 2003. In addition to assessing the viability of the fuel during routine operation of a bus fleet that operates in a cold climate, the project also endeavoured to evaluate the potential environmental benefits of biodiesel.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".