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The influence of traffic volume and ambient outdoor PAH on indoor PAH exposure was quantified at the Baltimore Traffic Study site, an unoccupied attached 2nd-floor apartment in an inner-city neighborhood "hot spot" surrounded by urban roadways that together carry over 150,000 vehicles per day. Monitoring of outdoor and indoor particle-bound PAH and traffic volume was conducted continously for 12 months at 10-minute intervals (n = 52,560). Time-series modeling accounted for complex and extensive autocorrelation. Vehicle count (0.57 [SE=0.04] ng/m3 per 100 vehicles every ten minutes) and outdoor PAH (0.16 [0.001] ng/m3 per ng/m3 outdoor PAH) are statistically significant predictors of indoor PAH, in addition to a mean background indoor exposure without indoor sources of 9.07 ng/m3. Spring 2003 (9.99 [0.67] ng/m3) and Summer 2003 (9.27 [+/-1.27] ng/m3) are associated with the greatest increases in indoor PAH, relative to Summer 2002. An additional 1.64 [0.27] ng/m3 is attributable to work days. Winds from the SW-S-NE quarter, which would have entrained PAH from Baltimore's densely trafficked central business district and a nearby interstate highway, contribute significantly to indoor PAH (0.31 - 1.16 ng/m3). Dew point, outdoor temperature, and wind speed are also statistically significant predictors. Indoor PAH's short-term autocorrelation is ARMA[3,3], where lag 3 indicates that PAH concentrations are correlated for up to 30 minutes. Significant autoregressive correlation at lags 144 and 1008 indicate autocorrelations at diurnal and weekly cycles, respectively. In a separate time series model, it was established that outdoor PAH itself depends at a statistically significant on vehicle count at a rate of 3.17 [0.11] ng/m3 per 100 vehicles every ten minutes. Conclusion: local indoor & outdoor exposure to PAH from mobile sources is substantially modified by meteorologic and temporal conditions, including atmospheric transport processes. PAH concentration also demonstrates statistically significant autocorrelation at several timescales.