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Record W2460131763 · doi:10.1021/acs.est.6b00082

Seasonal and Diurnal Air Pollution from Residential Cooking and Space Heating in the Eastern Tibetan Plateau

2016· article· en· W2460131763 on OpenAlexafffund
Ellison Carter, Scott Archer‐Nicholls, Kun Ni, Alexandra Lai, Hongjiang Niu, Matthew H. Secrest, Sara Sauer, James J. Schauer, Majid Ezzati, Christine Wiedinmyer, Xudong Yang, Jill Baumgartner

Bibliographic record

VenueEnvironmental Science & Technology · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicEnergy and Environment Impacts
Canadian institutionsMcGill University
FundersMedical Research CouncilCanadian Institutes of Health ResearchBritish Heart FoundationWellcome TrustU.S. Environmental Protection Agency
KeywordsStoveEnvironmental sciencePlateau (mathematics)Indoor air qualityAir pollutionAir quality indexCombustionPollutionBiomass (ecology)SeasonalityPopulationBiomass burningAtmospheric sciencesMeteorologyEnvironmental engineeringGeographyEnvironmental healthAerosolEcologyChemistryMedicine

Abstract

fetched live from OpenAlex

Residential combustion of solid fuel is a major source of air pollution. In regions where space heating and cooking occur at the same time and using the same stoves and fuels, evaluating air-pollution patterns for household-energy-use scenarios with and without heating is essential to energy intervention design and estimation of its population health impacts as well as the development of residential emission inventories and air-quality models. We measured continuous and 48 h integrated indoor PM2.5 concentrations over 221 and 203 household-days and outdoor PM2.5 concentrations on a subset of those days (in summer and winter, respectively) in 204 households in the eastern Tibetan Plateau that burned biomass in traditional stoves and open fires. Using continuous indoor PM2.5 concentrations, we estimated mean daily hours of combustion activity, which increased from 5.4 h per day (95% CI: 5.0, 5.8) in summer to 8.9 h per day (95% CI: 8.1, 9.7) in winter, and effective air-exchange rates, which decreased from 18 ± 9 h(-1) in summer to 15 ± 7 h(-1) in winter. Indoor geometric-mean 48 h PM2.5 concentrations were over two times higher in winter (252 μg/m(3); 95% CI: 215, 295) than in summer (101 μg/m(3); 95%: 91, 112), whereas outdoor PM2.5 levels had little seasonal variability.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.291
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.005
GPT teacher head0.198
Teacher spread0.193 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations81
Published2016
Admission routes2
Has abstractyes

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