Modeling exhaled aerosol deposition in an impaction filter across clinically measured breath flowrates

Exhaled breath offers a non-invasive matrix for detecting recent drug use, but high intra and inter-study variability in collected drug mass currently hinders its transition into reliable quantitative clinical and forensic tools. To enable standardized, reproducible sampling protocols, we evaluated flowrate-dependent aerosol capture in an impaction filter device (Breath Explor). We expanded a computational fluid and particle dynamics (CFPD) model across a flowrate spectrum informed by clinical data from 38 participants (N=12,295 exhalations; mean flowrate 0.15 ± 0.04 L · s-1). We also enhanced the near-wall transport model to resolve turbulent aerosol dispersion at high resolution. CFPD simulations showed that turbulent forces account for up to 20% of mass deposition for submicrometer-size aerosols within this operational range. Crucially, capture efficiency varied more than two-fold-ranging from 42% at 0.05 L·s-1 to 90% at 0.3 L·s-1-at a constant exhaled volume. These findings demonstrate that breath flowrate directly impacts aerosol recovery, suggesting that participant flowrate guidance or mathematical recovery normalization could improve the reproducibility of drug quantification. Ultimately, this work demonstrates how combining real-world clinical data with CFPD modeling can inform standardized, quantitative breath diagnostics.