Mitigation and adaptation emissions embedded in the broader climate transition
Bibliographic record
Abstract
Climate change necessitates a global effort to reduce greenhouse gas emissions while adapting to increased climate risks. This broader climate transition will involve large-scale global interventions including renewable energy deployment, coastal protection and retreat, and enhanced space cooling, all of which will result in CO 2 emissions from energy and materials use. Yet, the magnitude of the emissions embedded in these interventions remains unconstrained, opening the potential for underaccounting of emissions and conflicts or synergies between mitigation and adaptation goals. Here, we use a suite of models to estimate the CO 2 emissions embedded in the broader climate transition. For a gradual decarbonization pathway limiting warming to 2 °C, selected adaptation-related interventions will emit ∼1.3 GtCO 2 through 2100, while emissions from energy used to deploy renewable capacity are much larger at ∼95 GtCO 2 . Together, these emissions are equivalent to over 2 y of current global emissions and 8.3% of the remaining carbon budget for 2 °C. Total embedded transition emissions are reduced by ∼80% to 21.2 GtCO 2 under a rapid pathway limiting warming to 1.5 °C. However, they roughly double to 185 GtCO 2 under a delayed pathway consistent with current policies (2.7 °C warming by 2100), mainly because a slower transition relies more on fossil fuel energy. Our results provide a holistic assessment of carbon emissions from the transition itself and suggest that these emissions can be minimized through more ambitious energy decarbonization. We argue that the emissions from mitigation, but likely much less so from adaptation, are of sufficient magnitude to merit greater consideration in climate science and policy.
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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) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".