2012, Sally Liu, L.-J., Tsai, Ming-Yi, Keidel, Dirk, Gemperli, Armin, Ineichen, Alex, Hazenkamp-von Arx, Marianne, Bayer-Oglesby, Lucy, Rochat, Thierry, Künzli, Nino, Ackermann-Liebrich, Ursula, Straehl, Peter, Schwartz, Joel, Schindler, Christian

Although recent air pollution epidemiologic studies have embraced land-use regression models for estimating outdoor traffic exposure, few have examined the spatio-temporal variability of traffic related pollution over a long term period and the optimal methods to take these factors into account for exposure estimates. We used home outdoor NO2 measurements taken from eight geographically diverse areas to examine spatio-temporal variations, construct, and evaluate models that could best predict the within-city contrasts in observations. Passive NO2 measurements were taken outside of up to 100 residences per area over three seasons in 1993 and 2003 as part of the Swiss cohort study on air pollution and lung and heart disease in adults (SAPALDIA). The spatio-temporal variation of NO2 differed by area and year. Regression models constructed using the annual NO2 means from central monitoring stations and geographic parameters predicted home outdoor NO2 levels better than a dispersion model. However, both the regression and dispersion models underestimated the within-city contrasts of NO2 levels. Our results indicated that the best models should be constructed for individual areas and years, and would use the dispersion estimates as the urban background, geographic information system (GIS) parameters to enhance local characteristics, and temporal and meteorological variables to capture changing local dynamics. Such models would be powerful tools for assessing health effects from long-term exposure to air pollution in a large cohort

2002, Götschi, Thomas, Bayer-Oglesby, Lucy, Mathys, Patrick, Monn, Christian, Manalis, Nikos, Koistinen, Kimmo, Jantunen, Matti, Hänninen, Otto, Polanska, Liba, Künzli, Nino

Recent studies on separated particle-size fractions highlight the health significance of particulate matter smaller than 2.5 μm (PM2.5), but gravimetric methods do not identify specific particle sources. Diesel exhaust particles (DEP) contain elemental carbon (EC), the dominant light-absorbing substance in the atmosphere. Black smoke (BS) is a measure for light absorption of PM and, thus, an alternative way to estimating EC concentrations, which may serve as a proxy for diesel exhaust emissions. We analyzed PM2.5 and BS data collected within the EXPOLIS study (Air Pollution Exposure Distribution within Adult Urban Populations in Europe) in Athens, Basel, Helsinki, and Prague. 186 indoor/outdoor filter pairs were sampled and analyzed. PM2.5 and BS levels were lowest in Helsinki, moderate in Basel, and remarkably higher in Athens and Prague. In each city, Spearman correlation coefficients of indoor versus outdoor were higher for BS (range rSpearman:  0.57−0.86) than for PM2.5 (0.05−0.69). In a BS linear regression model (all data), outdoor levels explained clearly more of indoor variation (86%) than in the corresponding PM2.5 model (59%). In conclusion, ambient BS seizes a health-relevant fraction of fine particles to which people are exposed indoors and outdoors and exposure to which can be assessed by monitoring outdoor concentrations. BS measured on PM2.5 filters can be recommended as a valid and cheap additional indicator in studies on combustion-related air pollution and health.