Tracing and Quantifying Contributions of Proximal, Regional, and Global Sources to Primary Particulate Matter in an Urban Atmosphere Using Radiogenic Isotopes, Platinum Group Metals, and other Trace and Major Elements
Notice bibliographique
Résumé
This research focuses on rare earths, platinum group metals, and Sr, Nd, and Hf isotopes along with a wide spectrum of other trace and major elements to accurately trace and quantify contributions of various source categories to primary ambient airborne particulate matter (PM) in an urban atmosphere. The overarching goal of this research is to establish strong tracers for individual distal and proximal sources and quantify local, regional, and global sources influencing urban aerosols. The work principally focuses on natural mineral dust (from a remote desert and locally resuspended soil), anthropogenic mineral dust from construction activities, anthropogenic emissions from motor vehicles, both natural and anthropogenic biomass burning aerosols, and PM from oil combustion, petroleum refineries, coal combustion, and sea salt. The city of Houston, Texas, a representative urban metroplex which suffers pollution input from both local and distal sources (such as dust from the Saharan-Sahelian region and Central American biomass burning), was chosen as a test bed to prove our hypotheses. \n\nThe first part of the research demonstrates the superiority of coupled Sr-Nd-Hf isotopes compared with metal tracers to uniquely trace different natural and anthropogenic mineral dust sources with overlapping elemental composition and accurately isolate various urban PM sources. To achieve this, a novel high-yielding gravity flow column chromatography scheme was developed to separate Sr, Nd, and Hf prior to multi collector – inductively coupled plasma – mass spectrometry (MC-ICP-MS). Thereafter, we fingerprinted several sources including vehicular PM from an underwater tunnel, petroleum refinery PM from fluidized-bed catalytic cracking units, local soil, concrete/cement dust, and trans-Atlantic North African dust in Barbados. We also measured 87Sr/86Sr, 143Nd/144Nd, and 176Hf/177Hf ratios along with elemental concentrations in Houston aerosols, which aided in apportioning ambient PM2.5 to various sources during two North African dust events in the year 2017. A novel mathematical model was developed to unify elemental and isotopic mass balance equations for sources, which consequently demonstrated the superiority of the selected radiogenic isotopes in tracing and differentiating amongst various mineral sources. \n\nThe second part of the research demonstrates platinum group elements (PGEs – Rh, Pd, and Pt) in surface roads to be exclusively emitted from motor vehicles, since their relative abundances were coherent with catalytic converters. Therefore, PGEs were utilized to accurately quantify PM from vehicular emissions. Further, we used the estimates of vehicular contributions to determine the performance of other traffic-related metals as PM tracers for vehicles. \n\nThe third part of this research focuses on PM transported to Houston from distal locations and identifies two major sources (i) desert dust from North Africa and (ii) potassium-rich smoke particles linked to forest fires or anthropogenic agricultural burning in Central America, Canada, and southeastern United States. Additionally, the influence of Saharan dust and biomass burning episodes on concentrations of PM10, PM2.5, and anthropogenic metal tracers (rare earths, vanadium, and potassium) were evaluated, demonstrating the need to separate the non-mineral component of these metals.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| 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 | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 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) | 0,000 | 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 tête enseignante, 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 ».