Ambient fine particulate matter in China: Its negative impacts and possible countermeasures
Bibliographic record
Abstract
In recent decades, China has experienced rapid economic development accompanied by increasing concentrations of ambient PM2.5, particulate matter of less than 2.5 μm in diameter. PM2.5 is now believed to be a carcinogen, causing higher lung cancer risks and generating losses to the economy and society. This meta-analysis evaluates the losses generated by ambient PM2.5 in Suzhou from 2014 to 2016 and predicts losses at different concentrations. Estimations of total losses in Beijing, Shanghai, Hangzhou, Guangzhou, Dalian, and Xiamen are also presented, with a total national loss in 2015. The authors then demonstrate that lowering ambient PM2.5 concentrations would be a realistic way for China to reduce the evaluated social losses in the short term. Possible legal measures are listed for lowering ambient PM2.5 concentrations.Implications: The present findings quantify the economic effects of ambient PM2.5 due to the increased incidence rate and mortality rate of lung cancer. Lowering ambient PM2.5 concentrations would be the most realistic way for China to reduce tghe evaluated social losses in the short term. Possible legal measures for lowering ambient PM2.5 concentrations to reduce the total losses are identified.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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".