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Experimental Evaluation and Modeling of Photocatalytic Oxidation Air Cleaners

2013· dissertation· en· W24589696 on OpenAlexfundno aff
Lexuan Zhong

Bibliographic record

VenueCirculation · 2013
Typedissertation
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsnot available
FundersConcordia UniversityNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsPhotocatalysisIndoor air qualityOzonePollutantUltravioletRelative humidityEnvironmental scienceMaterials scienceAirflowHumidityAir quality indexProcess engineeringEnvironmental engineeringChemical engineeringEnvironmental chemistryChemistryMeteorologyEngineeringCatalysisOrganic chemistryMechanical engineeringOptoelectronics

Abstract

fetched live from OpenAlex

Heterogeneous ultraviolet photocatalytic oxidation (UV-PCO), as a promising advanced oxidation technology, has been suggested as an alternative and energy efficient method to improve indoor air quality (IAQ) through the photocatalytic degradation of indoor air pollutants. However, the complicated PCO reaction mechanisms and unexpected intermediates still need to be further explored in order for this technology to be successfully applied in mechanically ventilated buildings. \nTwo main objectives of this study include the development of methodologies to evaluate the performance of PCO systems and the development of a reliable mathematical model to fully simulate the performance of these systems. \nA pilot four-parallel duct system was set-up to equitably and thoroughly evaluate the performance of UV-PCO air cleaners under the conditions relevant to the actual applications for a wide range of indoor air pollutants. This study investigated the UV-PCO removal efficiency of two types of air filters (fiberglass fibers coated with TiO2 (TiO2/FGFs) and carbon cloth fibers loaded with TiO2 (TiO2/CCFs)) under ultraviolet C (UVC) and vacuum ultraviolet (VUV) illumination. A systematic parametric evaluation of the effects of various kinetic parameters, such as types of pollutants, inlet concentration, airflow rate, light intensity, and relative humidity that influence the PCO performance, was conducted. In addition, gas-phase ozonation with a variety of chemical compounds was first examined when ozone was produced by VUV. Moreover, the formation of by-products generated from incomplete conversion was investigated to evaluate its impact on IAQ. \nA time-dependent model was proposed for predicting the performance of an in-duct PCO air cleaner under the conditions relevant to the actual applications. A comprehensive model was developed by integrating light scattering model, reaction kinetic model, mass balance as well as optional ozonation model. The UV-PCO model and the UV-PCO ozonation integrated model were validated with experimental results; there was a good agreement between the model prediction and the experiment result. The relative rate-limiting process between physical interactions and photochemical interactions was fully investigated through simulation analysis. Depending on the physical properties of the catalyst, reactor geometries, operation conditions, as well as environmental conditions, the photochemical reaction occurring on the fixed active sites at the catalyst surface is the dominating process for this PCO system.

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)0.001
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 score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.076
GPT teacher head0.362
Teacher spread0.287 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

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