Spatiotemporal analysis of criteria air pollutants and volatile organic compounds from a moving vehicle
Notice bibliographique
Résumé
This thesis describes the on-road analysis of criteria air pollutants (CAPs) and volatile organic compounds (VOCs) from a moving vehicle. CAPs and VOCs have numerous direct and indirect effects on the environment and public health and are generated from a variety of point and diffuse sources. The concentration of these pollutants can vary on the scale of metres and seconds due to variable emission rates of sources, meteorology, and the topography of an area. CAPs are conventionally measured on a spatial scale of tens of kilometres and one hour or longer time resolution, which limits the understanding of their impact and leaving many communities lacking information regarding their air quality. VOCs are not measured as frequently as CAPs, owing to the difficulty, challenges, and cost associated with sampling. The Mobile Mass Spectrometry Lab (MMSL) was developed to collect high geospatial (15 – 1,500 m) and temporal (1 – 10 s) resolution measurements of CAPs (O3, NOx, PM2.5), CO2, CH4, and VOCs. CAPs and greenhouse gases were monitored using standard analyzers, while VOCs were measured using a proton-transfer reaction time-of-flight mass spectrometer (PTR-MS). PTR-MS is a real-time, direct, in situ technique that can monitor VOCs in the ambient atmosphere without sample collection. The PTR-MS monitored up to mass-to-charge 330 with a sample integration time of 1 or 10 seconds and had detection limits into the low- to mid-ppt. PTR-MS is a soft ionization technique that is selective to all compounds with a proton affinity less than water, which excludes the atmospheric matrix and includes most VOCs. The measurements provided by the PTR-MS provided a rich dataset for which to develop workflow and processing methods alongside sampling strategies for the collection of high geospatial and temporal VOC data. The first on-road deployment of the MMSL was performed across the Regional District of Nanaimo and the Alberni-Clayoquot Regional District in British Columbia, Canada, from July iv 2018 – April 2019 to monitor the geospatial and temporal variation in the concentration of CAPs and VOCs. VOCs detected in the areas include hydrocarbons like toluene, C2-benzenes, and terpenes, organic acids like acetic acid, oxygenated compounds like acetone and acetaldehyde, and reduced sulfur compounds like methanethiol and dimethyl sulfide. While observed concentrations of VOCs were mostly below detection limits, concentration excursions upwards of 2,200 ppb for C2-benzenes (reported as ethylbenzene) for instance, were observed across the various communities and industries that comprise central Vancouver Island. VOCs like monoterpenes, were observed near the wood industries up to 229 ppb. Combustion related VOCs, like toluene and C2-benzenes, were often observed on major transportation corridors and was found to vary significantly between seasons, with winter measurements often exceeding those made in the summer. Reduced sulfur compounds, common components of nuisance odours, were measured around a few industries like waste management and wood industries. The second on-road deployment of the MMSL focused on the analysis of VOCs in the community around a wastewater treatment plant (WWTP) to identify the source of odours in the area. VOCs were also monitored in the odour control process of the WWTP to identify the VOCs being emitted, how much were emitted, and where potential deficiencies were in the process in a unique study. Median emission rates at the facility for methanethiol, dimethyl sulfide, and dimethyl disulfide were determined to be 100, 19, and 21 kg yr-1, respectively. VOC monitoring in the community encompassed the WWTP and the other major industries in the area, including agricultural land, a composting facility, and a marina. The highest measurements of odorous reduced sulfur compounds were observed around the WWTP, upwards of 36 ppb for methanethiol. Unsupervised multivariate analysis was performed to identify groups of VOCs present and their potential sources. Three groups were identified, one of which was related to reduced sulfur compounds. This group was observed around the WWTP, indicating that the WWTP was the likely source of malodours in the community.
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 | 0,000 | 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 ».