Pollutant Emissions and Energy Efficiency of Chinese Gasifier Cooking Stoves and Implications for Future Intervention Studies
Bibliographic record
Abstract
Household air pollution from solid fuel combustion is the leading environmental health risk factor globally. In China, almost half of all homes use solid fuel to meet their household energy demands. Gasifier cookstoves offer a potentially affordable, efficient, and low-polluting alternative to current solid fuel combustion technology, but pollutant emissions and energy efficiency performance of this class of stoves are poorly characterized. In this study, four Chinese gasifier cookstoves were evaluated for their pollutant emissions and efficiency using the internationally recognized water boiling test (WBT), version 4.1.2. WBT performance indicators included PM2.5, CO, and CO2 emissions and overall thermal efficiency. Laboratory investigation also included evaluation of pollutant emissions (PM2.5 and CO) under stove operating conditions designed to simulate common Chinese cooking practices. High power average overall thermal efficiencies ranged from 22 to 33%. High power average PM2.5 emissions ranged from 120 to 430 mg/MJ of useful energy, and CO emissions ranged from 1 to 30 g/MJ of useful energy. Compared with several widely disseminated "improved" cookstoves selected from the literature, on average, the four Chinese gasifier cookstoves had lower PM2.5 emissions and higher CO emissions. The recent International Organization for Standardization (ISO) International Workshop Agreement on tiered cookstove ranking was developed to help classify stove performance and identify the best-performing stoves. The results from this study highlight potential ways to further improve this approach. Medium power stove operation emitted nearly twice as much PM2.5 as was emitted during high power stove operation, and the lighting phase of a cooking event contributed 45% and 34% of total PM2.5 emissions (combined lighting and cooking). Future approaches to laboratory-based testing of advanced cookstoves could improve to include greater differentiation between different modes of stove operation, beyond those evaluated with the WBT.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".