Fuels for Urban Transit Buses: A Cost-Effectiveness Analysis
Bibliographic record
Abstract
Public transit agencies have begun to adopt alternative propulsion technologies to reduce urban transit bus emissions associated with conventional diesel (CD) engines. Among the most popular alternatives are emission controlled diesel buses (ECD), defined here to be buses with continuously regenerating diesel particle filters burning low-sulfur diesel fuel, and buses burning compressed natural gas (CNG). This study uses a series of simplifying assumptions to arrive at first-order estimates for the incremental cost-effectiveness (CE) of ECD and CNG relative to CD. The CE ratio numerator reflects acquisition and operating costs. The denominator reflects health losses (mortality and morbidity) due to primary particulate matter (PM), secondary PM, and ozone exposure, measured as quality adjusted life years (QALYs). We find that CNG provides larger health benefits than does ECD (nine vs six QALYs annually per 1000 buses) but that ECD is more cost-effective than CNG (dollar 270 000 per QALY for ECD vs dollar 1.7 million to dollar 2.4 million for CNG). These estimates are subject to much uncertainty. We identify assumptions that contribute most to this uncertainty and propose potential research directions to refine our estimates.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".