Land Use Regression (LUR) models have been used increasingly for modeling small-scale spatial variation in air pollution concentrations and estimating individual exposure for participants of cohort studies. Within the ESCAPE project, concentrations of PM(2.5), PM(2.5) absorbance, PM(10), and PM(coarse) were measured in 20 European study areas at 20 sites per area. GIS-derived predictor variables (e.g., traffic intensity, population, and land-use) were evaluated to model spatial variation of annual average concentrations for each study area. The median model explained variance (R(2)) was 71% for PM(2.5) (range across study areas 35-94%). Model R(2) was higher for PM(2.5) absorbance (median 89%, range 56-97%) and lower for PM(coarse) (median 68%, range 32- 81%). Models included between two and five predictor variables, with various traffic indicators as the most common predictors. Lower R(2) was related to small concentration variability or limited availability of predictor variables, especially traffic intensity. Cross validation R(2) results were on average 8-11% lower than model R(2). Careful selection of monitoring sites, examination of influential observations and skewed variable distributions were essential for developing stable LUR models. The final LUR models are used to estimate air pollution concentrations at the home addresses of participants in the health studies involved in ESCAPE.

h i g h l i g h t s < LUR models were developed in 36 study areas in Europe using a standardized approach. < NO 2 models explained a large fraction of concentration variability (median R 2 82%). < Local traffic intensity data were important predictors for LUR model development.

PM 2.5 : mass concentration of particles less than 2.5 µm in size PM 10 : mass concentration of particles less than 10 µm in size RB: Regional Background site SOP: Standard Operating Procedure ST: Street site TRAPCA: Traffic-Related Air Pollution and Childhood Asthma UB: Urban Background site ABSTRACT The ESCAPE study (European Study of Cohorts for Air Pollution Effects) investigates long-term effects on human health of exposure to air pollution in Europe. Various health endpoints are analysed by using prospective cohort studies in the study areas. This paper documents the spatial variation of measured NO 2 and NO x concentrations between and within 36 study areas across Europe. In 36 study areas NO 2 and NO x were measured using standardized methods between October 2008 and April 2011. In each study area 14 to 80 sites were selected, which represented a wide range of regional, urban and nearby traffic related pollution contrast. The measurements were conducted for two weeks per site in three different seasons, using Ogawa badges. Results for each site were adjusted for temporal variation using data obtained from a routine monitor background site, which operated continuously, and averaged. Substantial spatial variability was found in NO 2 and NO x concentrations between and within study areas. Analysis of variance showed that 40% of the overall NO 2 variance is attributable to the variability between the study areas and 60% is caused by the variability within the study areas. The corresponding values for NO x are 30% (between the study areas) and 70% (within the study areas). The within-area spatial variability was mostly determined by the differences between traffic and urban background concentrations. The traffic/urban background concentration ratio varied between 1.09 and 3.16 across Europe. The NO 2 / NO x ratio varied between 0.47 (Verona) and 0.72 (Heraklion) across study areas. In study areas in southern Europe the highest median concentrations were observed (Barcelona: NO 2 55 µg/m³), followed by densely populated areas in Western Europe (Ruhr area, The Netherlands). The lowest concentrations were observed in all areas in Northern Europe (e.g. Umeå: NO 2 7 µg/m³). In conclusion, we found significant contrast in annual average NO 2 and NO x concentration between and especially within 36 study areas across Europe. Epidemiological studies should therefore characterize intra-urban contrasts. The use of traffic indicators such as "living close to major road" as an exposure variable in epidemiological studies results in different actual NO 2 contrasts. We would like to thank Kees Meliefste, Geert de Vrieze, Marjan Tewis (IRAS, Utrecht University, The Netherlands) for the sampler preparation, analysis and data management. Furthermore, we thank all those who were responsible for air pollution measurements, data management and project supervision in all study areas and especially:

Background: Recent studies have shown an association of short-term exposure to fine particulate matter (PM) with transient increases in blood pressure (BP), but it is unclear whether long-term exposure has an effect on arterial BP and hypertension.Objectives: We investigated the cross-sectional association of residential long-term PM exposure with arterial BP and hypertension, taking short-term variations of PM and long-term road traffic noise exposure into account.Methods: We used baseline data (2000–2003) on 4,291 participants, 45–75 years of age, from the Heinz Nixdorf Recall Study, a population-based prospective cohort in Germany. Urban background exposure to PM with aerodynamic diameter ≤ 2.5 μm (PM2.5) and ≤ 10 μm (PM10) was assessed with a dispersion and chemistry transport model. We used generalized additive models, adjusting for short-term PM, meteorology, traffic proximity, and individual risk factors.Results: An interquartile increase in PM2.5 (2.4 μg/m3) was associated with estimated increases in mean systolic and diastolic BP of 1.4 mmHg [95% confidence interval (CI): 0.5, 2.3] and 0.9 mmHg (95% CI: 0.4, 1.4), respectively. The observed relationship was independent of long-term exposure to road traffic noise and robust to the inclusion of many potential confounders. Residential proximity to high traffic and traffic noise exposure showed a tendency toward higher BP and an elevated prevalence of hypertension.Conclusions: We found an association of long-term exposure to PM with increased arterial BP in a population-based sample. This finding supports our hypothesis that long-term PM exposure may promote atherosclerosis, with air-pollution–induced increases in BP being one possible biological pathway.

Our study shows a clear association of long-term exposure to PM(2.5) with atherosclerosis. This finding strengthens the hypothesized role of PM(2.5) as a risk factor for atherogenesis.