Notice bibliographique
Résumé
Portable air cleaners (PACs) are appliances that use filtration to reduce indoor concentrations of particulate matter (PM), a harmful air pollutant associated with an array of adverse health outcomes. PACs may be particularly beneficial in homes, where people receive a substantial portion of their exposure to PM. However, any benefit from using a PAC is contingent on indoor concentrations consistently being lowered by the device. This work examines how PAC performance is affected by environmental and behavioural factors, and how these factors can be addressed to improve PAC efficacy. A review of 41 randomized interventions identified that device size and operation, the background loss rate (i.e., other particle removal mechanisms), and the strength of PM sources affected measured concentration reductions. Following this, two field studies were performed to further explore these specific factors. A method for processing continuous PM measurements was used to estimate variation in the background loss rate over one year in 16 apartments in a multifamily building. Background loss rate varied widely and was significantly increased by opening windows and exterior doors. A randomized crossover trial was performed in 60 apartments in three multifamily buildings, evaluating PAC performance when operating constantly and with device automation. Median weekly concentrations were reduced in all 60 apartments with constant air cleaning, while automation was similarly effective in homes where concentrations were relatively high. Weekly concentrations were significantly increased by PM-generating activities and significantly reduced when the exterior door was frequently opened, affecting measurements of PAC performance within and between homes. Noise was consistently identified as a factor that negatively impacted satisfaction. This was followed by an evaluation of two control strategies for PAC automation, which may help to address concerns about noise by reducing how often the device operates. There was no meaningful difference between a threshold-based strategy and one that achieves optimal performance based on balancing concentration reduction and runtime (model predictive control). This simpler threshold-based strategy can effectively automate PACs, so long as an appropriate threshold is selected. Together, this thesis provides a basis for improving guidelines for PAC selection and operation as well as for evaluating PAC performance.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».