Multiyear wildfire smoke exposure (MultiWiSE) metrics: a data-driven approach to characterizing episodic PM2.5 exposures for epidemiologic research

BACKGROUND: Population exposure to wildfire smoke (WFS) has increased across North America. The health effects of short-term WFS exposure are widely documented, but little is known about longer-term exposures. Most epidemiologic studies use multiyear averages to characterize long-term air pollution exposure, but these do not reflect the episodic nature of WFS which may be associated with distinct health risks. OBJECTIVE: We developed twelve data-driven Multiyear Wildfire Smoke Exposure (MultiWiSE) metrics that characterize the frequency, intensity, and duration of episodic WFS for application in epidemiologic studies examining the effects of longer-term exposures. METHODS: estimates from the Canadian Optimized Statistical Smoke Exposure Model for 2010-2023. RESULTS: exposure, with a mean (range) of 45.2 (17-80) WFS-impacted weeks and 8.2 (3-15) WFS episodes. WFS episodes lasted up to 24 weeks, with an average recovery of 78.2 (41.1-178.5) weeks between episodes. Eleven metrics were positively correlated, with correlations ranging from 0.20 to 0.99 and a mean of 0.70, indicating they capture both overlapping and distinct features of multiyear WFS exposure. SIGNIFICANCE: . They can be used in epidemiologic studies for a more nuanced and actionable understanding of the health risks of longer-term exposures. IMPACT STATEMENT: Population exposure to wildfire smoke (WFS) has increased across North America. While the health effects of short-term exposure are widely documented, little is known about the effects of longer-term exposure. Most studies use multiyear averages to characterize long-term air pollution exposure, which do not capture the episodic nature of WFS. To support epidemiologic research on multiyear exposures, we developed twelve Multiyear Wildfire Smoke Exposure (MultiWiSE) metrics that can be calculated using any long time series of daily fine particulate matter. These data-driven metrics characterize the frequency, intensity, and duration of episodic WFS exposure across large and variably smoke-impacted regions.