This research identified and quantified source types contributing to ambient PAH and associated toxicity at the urban and intraurban scales, reflecting awareness of the variability in exposure toxicity and in source toxicity for PM-associated toxic pollutants. Source apportionment analysed vapour+particle PAH time-series data (2001-2010) from central site monitoring stations at urban (Hamilton, Toronto) and rural background (Egbert) sites in Southern Ontario, Canada. Receptor modeling by Positive Matrix Factorization (PMF) identified four source types: volatilized PAH/long-range transported coal combustion, vehicle traffic exhaust, space heating, biomass combustion. At Hamilton, local industry emissions were also identified, associated with iron/steel manufacturing. Apportionment of PAH toxicity using Benzo(a)Pyrene-toxicity equivalency factors identified traffic exhaust and local industry as ‘more toxic’ source types, contributing comparably little to ambient PAH yet disproportionately to PAH-associated toxicity. Intraurban investigation of PAH sources sampled vapour+particle PAH and PM2.5 from a dense network of >30 Hamilton sites over a two-week period in June-July and December 2009. Ambient PAH exhibited substantially greater spatial variability than PM2.5 and ‘hot spots’ of elevated pollutant levels were observed near/downwind of the business district and harbour-front. A combined PMF-Chemical Mass Balance (CMB) receptor modeling approach applied factors derived from the PMF model of Hamilton central site time-series data as ‘local source profiles’ in a CMB model of spatial field sampling data, explaining spatial variability observed for PAH and PAH toxicity in terms of sources. Contributions by space heating, volatilized PAH/transported coal combustion, wood combustion showed low intraurban variability, while vehicle traffic exhaust showed moderate variability, and local industry emissions contributed significantly only near the industrial harbour-front. Vehicle traffic exhaust contributed majority of PAH toxicity at all sites, even where ambient PAH concentrations were comparably low, and local industry emissions contributed significantly only near the industrial zone, explaining ‘toxicity hot spots’ as high contributions of local industry in addition to vehicle traffic. Findings recommend that efforts to reduce PAH exposures prioritize ‘more toxic’ source types such as vehicle traffic and local industry. PMF-CMB receptor modeling using local time-series PAH data to interpret intraurban variability in ambient PAH demonstrated a viable analysis method for other urban locations.