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.

Abstract. Numerical models that combine weather forecasting and atmospheric chemistry are here referred to as chemical weather forecasting models. Eighteen operational chemical weather forecasting models on regional and continental scales in Europe are described and compared in this article. Topics discussed in this article include how weather forecasting and atmospheric chemistry models are integrated into chemical weather forecasting systems, how physical processes are incorporated into the models through parameterization schemes, how the model architecture affects the predicted variables, and how air chemistry and aerosol processes are formulated. In addition, we discuss sensitivity analysis and evaluation of the models, user operational requirements, such as model availability and documentation, and output availability and dissemination. In this manner, this article allows for the evaluation of the relative strengths and weaknesses of the various modelling systems and modelling approaches. Finally, this article highlights the most prominent gaps of knowledge for chemical weather forecasting models and suggests potential priorities for future research Published by Copernicus Publications on behalf of the European Geosciences Union. J. Kukkonen et al.: A review of operational, regional-scale, chemical weather forecasting models in Europedirections, for the following selected focus areas: emission inventories, the integration of numerical weather prediction and atmospheric chemical transport models, boundary conditions and nesting of models, data assimilation of the various chemical species, improved understanding and parameterization of physical processes, better evaluation of models against data and the construction of model ensembles.

Abstract.We discuss the capability of current state-of-theart chemistry and transport models to reproduce air quality trends and interannual variability. Documenting these strengths and weaknesses on the basis of historical simulations is essential before the models are used to investigate future air quality projections. To achieve this, a coordinated modelling exercise was performed in the framework of the CityZEN European Project. It involved six regional and global chemistry-transport models (BOLCHEM, CHIMERE, EMEP, EURAD, OSLOCTM2 and MOZART) simulating air quality over the past decade in the Western European anthropogenic emissions hotspots.Comparisons between models and observations allow assessing the skills of the models to capture the trends in basic atmospheric constituents (NO 2 , O 3 , and PM 10 ). We find that the trends of primary constituents are well reproduced (except in some countries -owing to their sensitivity to the emission inventory) although capturing the more moderate trends of secondary species such as O 3 is more challenging. Apart from the long term trend, the modelled monthly variCorrespondence to: A. Colette (augustin.colette@ineris.fr) ability is consistent with the observations but the year-to-year variability is generally underestimated.A comparison of simulations where anthropogenic emissions are kept constant is also investigated. We find that the magnitude of the emission-driven trend exceeds the natural variability for primary compounds. We can thus conclude that emission management strategies have had a significant impact over the past 10 yr, hence supporting further emission reductions.

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.