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 CO 2 -eq emissions are achieved in 2050 at a cost under $400 per tonne CO 2 -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 CO 2 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 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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".