Climate Impacts of Air Quality Policy: Switching to a Natural Gas-Fueled Public Transportation System in New Delhi
Bibliographic record
Abstract
Between 2001 and 2003, public transport vehicles in New Delhi were required to switch their fuel to natural gas in an attemptto reduce their air pollution impacts. This study examines the climatic impacts of New Delhi's fuel switching policy, and outlines implications for such efforts in rapidly industrializing countries. Natural gas is mostly composed of methane, an important greenhouse gas. Emitted aerosols (black carbon, particulate organic carbon, and sulfate) also cause radiative forcing. We find that methane and black carbon emissions are critical contributors to the change in carbon dioxide equivalent [CO2(e)] emissions. In New Delhi, the switch to natural gas results in a 30% increase in CO2(e) when the impact of aerosols is not considered. However, when aerosol emissions are taken into account in our model, the net effect of the switch is estimated to be a 10% reduction in CO2(e), and there may be as much as a 30% reduction in CO2(e). There is significant potential for emissions reductions through the United Nations Framework Convention on Climate Change (UNFCCC) Clean Development Mechanism for such fuel switching projects.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".