Health and air pollution co-benefits of climate change mitigation
Bibliographic record
Abstract
Case study: Phasing out coal-fired electric power generation in Canada Health and air quality co-benefits of climate change mitigation Technical brief Key messagesMany sources of greenhouse gas (GHG) emissions, particularly fossil fuel combustion, are also major sources of air pollutants, both indoors and outdoors.Thus, actions to address climate change through reducing GHG emissions can also reduce exposures to harmful air pollutants resulting from those same sources (e.g.particulate matter [PM], nitrogen oxides).The term co-benefits refer to the positive consequences for public health and the environment of reducing GHG emissions.Furthermore, actions focused on reducing short-lived climate pollutants (SLCPs) can also lead to improved air quality as ground-level ozone and black carbon are health-damaging air pollutants.Key climate change mitigation actions that can reduce air pollution are taken in many sectors including energy production, transport, agriculture and industry.Some examples include decreasing energy use; transitioning energy sources from fossil fuels, such as coal, to cleaner and renewable energy sources; improving energy security; and transitioning households away from polluting fuels such as biomass to electricity or other clean-burning forms of energy.Other actions that benefit both climate change mitigation and air quality include promoting cleaner transportation, reducing waste burning and reducing the likelihood and severity of wildfires.However, there are barriers to the adoption of climate change mitigation policies.One concerns policy assessment approaches used to evaluate the costs and benefits of climate mitigation actions.Policy makers often weigh the potentially high short-term costs -both financial and political of implementing climate change mitigation policies against their longer-term benefits with limited consideration given to the more immediate co-benefits these policies can offer, particularly improvements in air quality and public health.A more comprehensive assessment is needed, one that considers the wider shorter-term benefits of these policies, in order to make a stronger case for political and public support of the adoption of ambitious climate change mitigation policies. Air Quality, Energy and Health Science and Policy SummariesView from the polar ice rim highlighting effects of climate change.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 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".