Mitigation and Adaptation Emissions Embedded in the Broader Climate Transition
Bibliographic record
Abstract
Climate change necessitates an immediate and sustained global effort to reduce greenhouse gas emissions while adapting to the increased climate risks caused by historical emissions. This broader climate transition will involve mass global interventions including renewable energy deployment, coastal protection and retreat, and enhanced space cooling, which will result in CO2 emissions from energy and materials use. Yet, the magnitude of these emissions remains largely unconstrained, leaving open the potential for under-accounting of emissions and conflicts or synergies between mitigation and adaptation goals. Here, we use a suite of models to estimate the CO2 emissions embedded in the broader climate transition. For a pathway limiting warming to 2°C, we estimate that selected adaptations will emit ~1.5GtCO2 through 2100. Emissions from energy used to deploy renewable capacity are much larger at ~95GtCO2, equivalent to over two years of current global emissions and ~8% of the remaining carbon budget for 2°C. These embedded transition emissions are reduced by 80% to 20GtCO2 under a rapid decarbonization scenario limiting warming to 1.5°C. However, they roughly double to 185GtCO2 under a low-ambition transition consistent with current policies (2.7°C warming by 2100), mainly because a slower transition relies more on fossil fuels. Under this status-quo, the emissions embedded in the transition total nearly half the remaining carbon budget for 1.5°C. Our results provide the first holistic assessment of the carbon emissions embedded in the transition itself, and suggest that these emissions can be largely minimized through rapid energy decarbonization, an underappreciated benefit of enhanced climate ambition.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".