If Anthropogenic CO<sub>2</sub> Emissions Cease, Will Atmospheric CO<sub>2</sub> Concentration Continue to Increase?
Bibliographic record
Abstract
If anthropogenic CO2 emissions were to suddenly cease, the evolution of the atmospheric CO2 concentration would depend on the magnitude and sign of natural carbon sources and sinks. Experiments using Earth system models indicate that the overall carbon sinks dominate, such that upon the cessation of anthropogenic emissions, atmospheric CO2 levels decrease over time. However, these models have typically neglected the permafrost carbon pool, which has the potential to introduce an additional terrestrial source of carbon to the atmosphere. Here, the authors use the University of Victoria Earth System Climate Model (UVic ESCM), which has recently been expanded to include permafrost carbon stocks and exchanges with the atmosphere. In a scenario of zeroed CO2 and sulfate aerosol emissions, whether the warming induced by specified constant concentrations of non-CO2 greenhouse gases could slow the CO2 decline following zero emissions or even reverse this trend and cause CO2 to increase over time is assessed. It is found that a radiative forcing from non-CO2 gases of approximately 0.6 W m−2 results in a near balance of CO2 emissions from the terrestrial biosphere and uptake of CO2 by the oceans, resulting in near-constant atmospheric CO2 concentrations for at least a century after emissions are eliminated. At higher values of non-CO2 radiative forcing, CO2 concentrations increase over time, regardless of when emissions cease during the twenty-first century. Given that the present-day radiative forcing from non-CO2 greenhouse gases is about 0.95 W m−2, the results suggest that if all CO2 and aerosols emissions were eliminated without also decreasing non-CO2 greenhouse gas emissions CO2 levels would increase over time, resulting in a small increase in climate warming associated with this positive permafrost–carbon feedback.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".