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Record W3192491017 · doi:10.1021/acs.est.1c02053

Modeling the Removal of Water-Soluble Trace Gases from Indoor Air via Air Conditioner Condensate

2021· article· en· W3192491017 on OpenAlexaff
Heather Schwartz‐Narbonne, Jonathan P. D. Abbatt, P. F. DeCarlo, Delphine K. Farmer, James M. Mattila, Chen Wang, D. J. Donaldson, Jeffrey A. Siegel

Bibliographic record

VenueEnvironmental Science & Technology · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicIndoor Air Quality and Microbial Exposure
Canadian institutionsThe Scarborough HospitalPublic Health OntarioUniversity of Toronto
FundersAlfred P. Sloan Foundation
KeywordsAir conditioningEnvironmental scienceTrace gasTRACE (psycholinguistics)Environmental engineeringIndoor airElectromagnetic coilRoom air distributionWaste managementChemistryMeteorologyEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

Water-soluble trace gas (WSTG) loss from indoor air via air conditioning (AC) units has been observed in several studies, but these results have been difficult to generalize. In the present study, we designed a box model that can be used to investigate and estimate WSTG removal due to partitioning to AC coil condensate. We compared the model output to measurements of a suite of organic acids cycling in an indoor environment and tested the model by varying the input AC parameters. These tests showed that WSTG loss via AC cycling is influenced by Henry's law constant of the compound in question, which is controlled by air and water temperatures and the condensate pH. Air conditioning unit specifications also impact WSTG loss through variations in the sensible heat ratio, the effective recirculation rate of air through the unit, and the timing of coil and fan operation. These findings have significant implications for indoor modeling. To accurately model the fate of indoor WSTGs, researchers must either measure or otherwise account for these unique environmental and operational characteristics.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.008
GPT teacher head0.211
Teacher spread0.203 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations13
Published2021
Admission routes1
Has abstractyes

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