Real-time prediction of size-resolved ultrafine particulate matter on freeways

Ultrafine particulate matter (UFP; diameter <0.1 μm) concentrations are relatively high on the freeway, and time spent on freeways can contribute a significant fraction of total daily UFP exposure. We model real-time size-resolved UFP concentrations in summer time on-freeway air. Particle concentrations (32 bins, 5.5 to 600 nm) were measured on Minnesota freeways during summer 2006 and 2007 ( Johnson, J. P.; Kittelson, D. B.; Watts, W. F. Environ. Sci. Technol. 2009 , 43 , 5358 - 5364 ). Here, we develop and apply two-way stratified multilinear regressions, using an approach analogous to mobile-monitoring land-use regression but using real-time meteorological and traffic data. Our models offer the strongest predictions in the 10-100 nm size range (adj-R(2): 0.79-0.89, average adj-R(2): 0.85) and acceptable but weaker predictions in the 130-200 nm range (adj-R(2): 0.41-0.62, average adj-R(2): 0.52). The aggregate model for total particle counts performs well (adj-R(2) = 0.77). Bootstrap resampling (n = 1000) indicates that the proposed models are robust to minor perturbations in input data. The proposed models are based on readily available real-time information (traffic and meteorological parameters) and can thus be exploited to offer spatiotemporally resolved prediction of UFPs on freeways within similar geographic and meteorological environments. The approach developed here provides an important step toward modeling population exposure to UFP.