Characterization of Alkylated Polycyclic Aromatic Hydrocarbons in Urban and Industrial Settings
Notice bibliographique
Résumé
Polycyclic aromatic compounds (PACs) are a large class of toxic pollutants that include unsubstituted polycyclic aromatic hydrocarbons (PAHs), alkylated PAHs (alk-PAHs), dibenzothiophenes (DBTs), and heteroatoms (contain N, S, O-atoms). The majority of research and monitoring data has historically focused on 16 unsubstituted priority PAHs. Recently, concern has been raised regarding alk-PAHs, as some are more toxic than their unsubstituted analogues, and research is needed to quantify alk-PAHs under different environmental settings. This thesis consists of three measurement campaigns of PACs in air to serve the objectives of this thesis. For the first time in Canada, twenty-two alk-PAHs and five unsubstituted priority PAHs were measured individually at two urban and semi-urban locations in Toronto using three types of samplers (high volume air sampler (HiVol), and two Integrated Organic GAs and Particle (IOGAP) systems with stainless steel (SS) and glass (GL) denuders, separately. In general, PACs are more abundant at the urban site (>3 times) than in the semi-urban area. Regardless of the site environment, alk-PAHs are more prevalent (>3 times) than unsubstituted PAHs. Alk-PAHs contributed 87% (urban) and 55% (semi-urban) of the mean toxic equivalences (TEQ) in air samples. Some alk-PAHs (e.g., 7,12-dimethylbenz[a]anthracene) had a significant impact on toxicity in urban air samples (63 % of TEQ). The toxic effect of alkylated and gaseous PAHs, which are not routinely included in many air-monitoring programs, were significant and should not be neglected. Total concentrations and particle/gas partitioning measured with IOGAP-SS compared well with IOGAP-GL, previously shown to be efficient in capturing gas and particle-phase PAHs. HiVol agrees well with IOGAP-SS when measuring less volatile PACs. Incorporating XAD-resin (divinylbenzene–styrene copolymer) in the HiVol sampling train increased sampling efficiency for highly volatile compounds and is recommended for routine monitoring purposes due to its ease of use. An industrial site with a tailings pond (Suncor Tailings Pond) in Alberta was monitored and modelled. Fluxes of 5 parent and 22 alk-PAHs were estimated, based on the measured co-located air and water concentrations using a two-film fugacity-based model (FUG), an inverse dispersion model (DISP), and a simple box model (BOX). Correlation between the estimated flux results of BOX and DISP model was statistically significant (r = 0.99 and p < 0.05) and Pearson correlation coefficient between FUG and DISP results ranged from 0.54 to 0.85. In this first-ever assessment of PAC fluxes from this tailings pond in Canada, the three models confirmed volatilization fluxes of PACs, indicating the selected Suncor tailings pond is a source of PAC emissions to the atmosphere. The finding addressed a critical data gap identified in the Joint Oil Sands Monitoring Emissions Inventory Compilation Report (Government of Alberta and Canada, 2016), which lacks consistent real-world monitoring of tailings pond fugitive emission of organic chemicals.
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».