Archetypes of Spatial Concentration Variability of Organic Contaminants in the Atmosphere: Implications for Identifying Sources and Mapping the Gaseous Outdoor Inhalation Exposome

Whereas inhalation exposure to organic contaminants can negatively impact human health, knowledge of their spatial variability in the ambient atmosphere remains limited. We analyzed the extracts of passive air samplers deployed at 119 unique sites in Southern Canada between 2019 and 2022 for 353 org...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Environmental science & technology 2024-10, Vol.58 (41), p.18273-18283
Hauptverfasser: Zhan, Faqiang, Li, Yuening, Shunthirasingham, Chubashini, Oh, Jenny, Lei, Ying Duan, Lu, Zhe, Ben Chaaben, Amina, Lee, Kelsey, Gobas, Frank A. P. C., Hung, Hayley, Breivik, Knut, Wania, Frank
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Whereas inhalation exposure to organic contaminants can negatively impact human health, knowledge of their spatial variability in the ambient atmosphere remains limited. We analyzed the extracts of passive air samplers deployed at 119 unique sites in Southern Canada between 2019 and 2022 for 353 organic vapors. Hierarchical clustering of the obtained data set revealed four archetypes of spatial concentration variability in the outdoor atmosphere, which are indicative of common sources and similar atmospheric dispersion behavior. “Point Source” signatures are characterized by elevated concentration in the vicinity of major release locations. A “Population” signature applies to compounds whose air concentrations are highly correlated with population density, and is associated with emissions from consumer products. The “Water Source” signature applies to substances with elevated levels in the vicinity of water bodies from which they evaporate. Another group of compounds displays a “Uniform” signature, indicative of a lack of major sources within the study area. We illustrate how such a data set, and the derived spatial patterns, can be applied to support the identification of sources, the quantification of atmospheric emissions, the modeling of air quality, and the investigation of potential inequities in inhalation exposure.
ISSN:0013-936X
1520-5851
1520-5851
DOI:10.1021/acs.est.4c05204