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Impacts of Mixing on AcceptableIndoor Air Quality in Homes

2010· article· en· W2135240370 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueHVAC&R Research · 2010
Typearticle
Languageen
FieldMedicine
TopicInfection Control and Ventilation
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental scienceIndoor air qualityVentilation (architecture)Mixing (physics)Environmental engineeringPollutantAir quality indexPopulationHVACAir conditioningWaste managementEngineeringMeteorologyEnvironmental healthGeographyMechanical engineering

Abstract

fetched live from OpenAlex

Ventilation reduces occupant exposure to indoor contaminants by diluting or removing them. In a multizone environment, such as a house, every zone will have different dilution rates and contaminant source strengths. The total ventilation rate is the most important factor in determining occupant exposure to given contaminant sources, but the zone-specific distribution of exhaust and supply air and the mixing of ventilation air can play significant roles. Different types of ventilation systems will provide different amounts of mixing depending on several factors, such as air leakage, air distribution system, and contaminant source and occupant locations. Most US and Canadian homes have central forced-air heating, ventilation, and air-conditioning systems, which tend to mix the air; thus, the indoor air in different zones tends to be well mixed for significant fractions of the year. This article reports recent results of investigations to determine the impact of air mixing on exposures of residential occupants to prototypical contaminants of concern. We summarize existing literature and extend past analyses to determine the parameters that affect air mixing as well as the impacts of mixing on occupant exposure, and draw conclusions that are relevant for standards development and for practitioners designing and installing home ventilation systems. The primary conclusion is that mixing will not substantially affect the mean indoor air quality across a broad population of occupants, homes, and ventilation systems, but it can reduce the number of occupants who are exposed to extreme pollutant levels. If the policy objective is to minimize the number of people exposed above a given pollutant threshold, some amount of mixing will be of net benefit even though it does not benefit average exposure. If the policy is to minimize exposure on average, then mixing air in homes is detrimental and should not be encouraged. We also conclude that most homes in the US have adequate mixing already, but that new, high-performance homes may require additional mixing. Also, our results suggest that some differentiation should be made in policies and standards for systems that provide continuous exhaust, thereby reducing relative dose for occupants overall.

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.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.224
Threshold uncertainty score0.791

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.098
GPT teacher head0.469
Teacher spread0.371 · 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