Odor, Air Quality, and Well-Being: Understanding the Urban Smellscape Using Crowd-sourced Science, Monitoring, and Modeling

Abstract

Odor exposure can adversely impact health and quality of life. It is challenging to study odors and their effects due to variability in individual sensitivity and perception, atmospheric physico-chemical processes, and emissions of mixtures of odorous contaminants. Here, we conduct quantitative and qualitative analyses of a 12-month data set from a web application collecting crowd-sourced odor reports, including spatiotemporal information, odor and self-reported impacts description (OSAC: odors, symptoms, actions in response, and potential causes), and demographics, in Vancouver, Canada. Spatiotemporal patterns highlight the influence of persistent sources (e.g., waste management) and transient events (e.g., accidents). Multiple linear regression models suggest that meteorological ventilation and air pollutants account for 60% of the variance in daily odor report counts. Users report diverse OSAC with strong seasonality and spatial variability. Reported symptoms, ranging from neurological to emotion-and mood-related, highlight the complexity of odor-related well-being impacts. Odors can trigger maladaptive behavior, where individuals are exposed to other environmental stressors (e.g., heat stress) or engage in risky behaviors to avoid or cope with odor impacts. Results from this project provide evidence that human-centered approaches can enrich understanding of the impacts of odorous emissions on health and well-being.