  Few studies have linked specific sources of ambient particulate matter
smaller than 2.5 $\mu$m (PM2.5) and asthma. In this study, we estimated the
contributions of specific sources to PM2.5 and examined their association with
daily asthma hospital utilization in Cincinnati, Ohio, USA. We used Poisson
regression models to estimate the daily number of asthma ED visits the day of
and one, and two days following separate increases in PM2.5 and its source
components, adjusting for temporal trends, holidays, temperature, and humidity.
In addition, we used a model-based clustering method to group days with similar
source-specific contributions into six distinct clusters. Specifically,
elevated PM2.5 concentrations occurring on days characterized by low
contributions of coal combustion showed a significantly reduced risk of
hospital utilization for asthma (rate ratio: 0.86, 95% CI: [0.77, 0.95])
compared to other clusters. Reducing the contribution of coal combustion to
PM2.5 levels could be an effective intervention for reducing asthma-related
hospital utilization.
