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Record W2416515631 · doi:10.1021/acs.est.5b06208

Health and Climate-Relevant Pollutant Concentrations from a Carbon-Finance Approved Cookstove Intervention in Rural India

2016· article· en· W2416515631 on OpenAlexafffund
Ther W. Aung, Grishma Jain, Karthik Sethuraman, Jill Baumgartner, Conor C. O. Reynolds, Andrew P. Grieshop, Julian Marshall, Michael Bräuer

Bibliographic record

VenueEnvironmental Science & Technology · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicEnergy and Environment Impacts
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health ResearchInstitute on the Environment, University of Minnesota
KeywordsStovePsychological interventionEnvironmental healthEnvironmental scienceIntervention (counseling)Leverage (statistics)MedicineWaste managementEngineeringMathematics

Abstract

fetched live from OpenAlex

Efforts to introduce more efficient stoves increasingly leverage carbon-finance to scale up dissemination of interventions. We conducted a randomized intervention study to evaluate a Clean Development Mechanism approved stove replacement impact on fuelwood usage, and climate and health-relevant air pollutants. We randomly assigned 187 households to either receive the intervention or to continue using traditional stoves. Measurements of fine particulate matter (PM2.5) and absorbance were conducted in cooking areas, village center and at upwind background site. There were minor and overlapping seasonal differences (post- minus preintervention change) between control and intervention groups for median (95% CI) fuel use (-0.60 (-1.02, -0.22) vs -0.52 (-1.07, 0.00) kg day(-1)), and 24 h absorbance (35 (18, 60) vs 36 (22, 50) × 10(-6) m(-1)); for 24 h PM2.5, there was a higher (139 (61,229) vs 73(-6, 156) μg m(-3))) increase in control compared to intervention homes between the two seasons. Forty percent of the intervention homes continued using traditional stoves. For intervention homes, absorbance-to-mass ratios suggest a higher proportion of black carbon in PM2.5 emitted from intervention compared with traditional stoves. Absent of field-based evaluation, stove interventions may be pursued that fail to realize expected carbon reductions or anticipated health and climate cobenefits.

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)0.000
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 score0.335
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
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 head0.004
GPT teacher head0.205
Teacher spread0.201 · 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

Citations88
Published2016
Admission routes2
Has abstractyes

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