UC Irvine

Introduction: Wildfires, intensified by climate change, emit diverse pollutants, including PM2.5, fine particulate matter, which are implicated in respiratory health effects. The pollutant, fine particulate matter, refers to particles with an aerodynamic diameter of 2.5 micrometers or less (PM2.5). PM2.5 particles from wildfires can deeply penetrate the respiratory system and bloodstream, presenting substantial health hazards. Current regulatory frameworks often fail to differentiate between wildfire specific and ambient PM2.5, despite evidence indicating elevated health risks from wildfires. The concept of "smoke waves," representing periods of varying durations and heightened PM2.5 concentrations resulting from wildfires, offers a novel approach to characterizing exposure. This study seeks to examine the association between wildfire specific PM2.5 exposure and respiratory health outcomes.Methods: A time series analysis was conducted to assess the association of wildfire- specific PM2.5 exposure with respiratory health risk by examining respiratory-related hospitalizations and emergency department visits across various zip codes in the years 2017, 2018, and 2020. Daily concentrations of PM2.5 were analyzed alongside daily 6 hospitalization and emergency visit data. The Generalized Estimating Equations (GEE) model with Poisson regression was employed, with the primary exposure variable being wildfire specific PM2.5 exposure and the outcome variable being respiratory health risk. An autoregressive covariance structure (AR (1)) was included, and an offset term was incorporated by taking the logarithm of the total population. Demographic, temporal, and meteorological covariates were accounted for in the main analysis. All statistical analyses were conducted using SAS 9.4 (SAS Institute Inc.). Results: In the primary investigation, a notable positive association was observed between overall respiratory diseases and the presence of wildfire specific PM2.5 particulate matter. This association persisted across various lag periods with relative risk estimates ranging from 1.022 to 1.048 across various lag times. Upon disaggregating the data to examine disease-specific outcomes like asthma and chronic obstructive pulmonary disease (COPD), a consistent positive relationship emerged with wildfire-specific PM2.5 levels for emergency department visits and hospitalizations across all lag periods with relative risk estimates ranging from 1.025 to 1.048 across various lag times. Conclusion: We observed a strong association between wildfire specific PM2.5 exposure and respiratory health outcomes, showing a consistent positive association across different lag periods. Elevated risks were observed for overall respiratory disease, including asthma and COPD. It was also found that personal behaviors may assist in mitigating risk during smoke waves with increased intensity and similar duration. These results support discerning wildfire PM2.5 from ambient levels and highlight the need to further understand this association and its potential consequences.