The social cost of carbon of different automotive powertrains: A comparative case study of Thailand
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
Global carbon dioxide (CO2) emissions have continuously grown over the past decade. In recent years, nations worldwide have encouraged the use of electric vehicles to reduce the use of fossil fuels in the global transportation sector. To encourage people to transition to electric vehicles, the total cost of ownership (TCO) is the main focus of devising appropriate incentives or subsidies. However, most TCOs emphasize the expenses an owner must incur, regardless of the hidden cost that society must pay. Consequently, the social cost of carbon plays a significant role in the assessment of the losses from the point of view of society. This study reveals the social cost over the lifetime of electric vehicles (EVs), compared to an internal combustion engine vehicle (ICEV). In this study, the energy consumption of the considered vehicles was obtained from a real-world driving test. The CO2 emissions from energy consumption and battery production are evaluated. The social cost model was developed based on the CO2 emissions. A sensitivity analysis validates the social cost model via case scenarios by considering assumptions and conditions suitable for Thailand’s context. The social cost model can be applied with the TCO model for government policymakers and manufacturer planners to estimate the appropriate subsidy to incentivize EV buyers and minimize the social costs.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 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 it