The application of wavelet decomposition to quantify the local and regional sources of ultrafine particles in cities

This study explores the application of wavelet decomposition as a means to distinguish between local and regional sources of ultrafine particles (UFP). Particle number concentrations were measured at a central site, two downtown sites, and four residential sites located across Toronto, Canada. Using a wavelet decomposition algorithm, particle concentration time series were separated into two signals: high frequency local-to-neighbourhood scale sources and low frequency urban-to-regional scale sources and processes. At the field sites, local-neighbourhood sources contributed between 13 and 32% of the total particle concentration. The urban-regional signal at each field site exhibited stronger correlation and greater homogeneity with respect to the central site than the original concentration time series. In contrast, the high frequency local-neighbourhood source signals exhibited limited correlation and high heterogeneity with respect to the central site. Traffic volume within a 2.5 km buffer explained 87% of the variability in the local-neighbourhood level signal observed between field sites while no significant association with traffic was found for the original particle number concentration data. This study has demonstrated that wavelet decomposition can be a useful tool for estimating exposure to UFP from local-neighbourhood and urban-regional scale sources and processes.