Climate change has increased fire PM2.5 and its associated health burden
Bibliographic record
Abstract
Climate change has influenced fire activities, altering the fire risk associated with air pollution and human health. However, the specific contribution of climate change to fire risks on air pollution and health burden has not yet been discovered. In this study, three fire-vegetation models were employed to simulate fire aerosol emissions under two simulations over the past six decades: an observation climate scenario and a counterfactual scenario where the long-term climate change trend is removed. Combining fire aerosol emissions with a chemical transport model and an avoidable mortality risk model, we calculated global fire PM2.5 and its associated mortality. By comparing the results under the two simulations, we demonstrated the climate change has increased the fire PM2.5 and its mortality. The findings indicated an increase in fire mortality over the six decades: 46,401 in the 1960s and 98,748 in the 2010s, with 3-8% attributed to climate change. Clear relationships were observed between the contribution of climate change to fire mortality and relative humidity or air temperature in some regions. This suggests that fire risks in these regions are sensitive to climate change and necessitate the development of adaptation strategies to mitigate risks in the future.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".