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deCastro B.R.1, Breysse P.N.2, Buckley T.J.3, Wang L.4, Mihalic J.N.2, Geyh A.S.2
1Westat, Rockville, MD.
2Johns Hopkins Bloomberg School of Public Health, Department of Environmental Health Sciences, Baltimore, MD.
3Ohio State University School of Public Health, Division of Environmental Health Sciences, Columbus, OH.
4Johns Hopkins Bloomberg School of Public Health, Department of Epidemiology, Baltimore, MD.
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.