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Record W2913171508 · doi:10.1080/23744731.2018.1526012

IAQ and energy implications of high efficiency filters in residential buildings: A review (RP-1649)

2019· review· en· W2913171508 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueScience and Technology for the Built Environment · 2019
Typereview
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsUniversity of Toronto
FundersAmerican Society of Heating, Refrigerating and Air-Conditioning Engineers
KeywordsHVACEfficient energy useVentilation (architecture)Environmental scienceIndoor air qualityFilter (signal processing)Architectural engineeringEnvironmental engineeringAir conditioningEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

Exposure to airborne particulate matter (PM) in residential buildings can cause adverse health risks for building occupants. One approach to mitigate this exposure is the use of filters in HVAC systems. In this article, we present an integrated picture of the overall performance of higher efficiency residential filters by assessing the impacts of their use in residences that incorporate a forced air recirculating HVAC system. We answer two major research questions in this article: (1) What is the effectiveness of higher efficiency filters in reducing residential PM concentrations? (2) What is the impact of higher efficiency filters on system energy use? The results show that a high efficiency filter can be effective in reducing indoor PM concentrations if HVAC system runtime (the fraction of time an HVAC system operates) is high and if particle removal by the filter is greater than deposition and ventilation losses. In addition, higher efficiency filters generally only slightly change system energy use. Cost–benefit analyses of filters in residences show that increasing filter efficiency may not be as fruitful compared to doing so in commercial buildings due to operational differences of residential systems. Overall results suggest caution when assuming that higher efficiency filters perform better in residences when compared to lower efficiency filters.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.992
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.046
GPT teacher head0.339
Teacher spread0.293 · 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