Marginal abatement costs for greenhouse gas emissions in the United States using an energy systems approach
Bibliographic record
Abstract
Abstract Deep decarbonization requires fundamental changes in meeting energy service demands, with some efforts increasing overall costs. Examining abatement measures in isolation, however, fails to capture their interactive effects within the energy system. Here we show the abatement costs of decarbonization in the United States using an energy system optimization model to capture technological interactions, multi-decadal path dependence, and endogenous end-use technology selection. Energy-system-wide net-zero CO2-eq emissions are achieved in 2050 at a cost under $400 per tonne CO2-eq, led by emissions reductions in power generation, end-use electrification of ground transportation, space heating, and some industrial applications. Differences in mitigation costs and CO2 geological storage potential lead to regional heterogeneities in mitigation rates and residual emissions. The marginal abatement cost curves show that additional decarbonization comes at higher incremental costs, this cost penalty decreases over time, and substantially greater abatement occurs in future time periods at the same abatement cost.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".