Estimated Aerosol Health and Radiative Effects of the Residential Coal Ban in the Beijing-Tianjin-Hebei Region of China
Bibliographic record
Abstract
Particle-phase air pollution is a leading risk factor for premature death globally and impacts climate by scattering or absorbing radiation and changing cloud properties. Within the Beijing-Tianjin-Hebei region of China, where there are severe air quality problems, several municipalities have begun implementing a coal-to-electricity program that bans residential coal and provides subsidies for electricity and electric-powered heat pumps. We used GEOS-Chem to evaluate two complete residential coal-to-electricity transitions—a Beijing-off scenario and Beijing-Tianjin-Hebei-off scenario—each relative to a base case. We estimate that within China, the ambient fine particulate matter (PM2.5) reductions in the Beijing-off scenario could lead to 1,900 (95% CI: 1,200–2,700) premature deaths avoided annually, while the Beijing-Tianjin-Hebei-off scenario could lead to 13,700 (95% CI: 8,900–19,600) premature deaths avoided annually. Additionally, we estimate that the residential-coal-ban scenarios will result in a positive top-of-the-atmosphere aerosol direct radiative effect (DRE) (model domain average: Beijing-off: 0.023 W m–2; Beijing-Tianjin-Hebei-off: 0.30 W m–2) and a negligible cloud-albedo aerosol indirect effect (AIE) (Beijing-off: 0.0001 W m–2; Beijing-Tianjin-Hebei-off: 0.0027 W m–2). To evaluate the uncertainty of the radiative effects, we calculated the DRE under four black-carbon mixing-state assumptions and both the DRE and AIE assuming three different black-carbon-to-organic-aerosol (BC:OA) ratios for residential-coal emissions. Although the magnitude of our radiative forcing estimates varied across sensitivity cases, the domain average remained positive. When only considering the aerosol-related effects of the aforementioned coal-ban scenarios, we predict substantial health benefits, but do not anticipate a climate “co-benefit”, because removing aerosol emissions leads to a warming tendency. However, if the coal-to-electricity program results in less net greenhouse gas emissions due to the replacement heaters, the policy may be able to achieve health and climate “co-benefits”.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".