Abstract
Abstract. The application of regional-scale air quality models is an important tool in air quality assessment and management. For this reason, the understanding of model abilities and performances is mandatory. The main objective of this research was to investigate the spatial and temporal variability of background particulate matter (PM) concentrations, to evaluate the regional air quality modelling performance in simulating PM concentrations during statically stable conditions and to investigate processes that contribute to regionally increased PM concentrations with a focus on eastern and central Europe. The temporal and spatial variability of observed PM was analysed at 310 rural background stations in Europe during 2011. Two different regional air quality modelling systems (offline coupled European Monitoring and Evaluation Programme, EMEP, and online coupled Weather Research and Forecasting with Chemistry) were applied to simulate the transport of pollutants and to further investigate the processes that contributed to increased concentrations during high-pollution episodes. Background PM measurements from rural background stations, wind speed, surface pressure and ambient temperature data from 920 meteorological stations across Europe, classified according to the elevation, were used for the evaluation of individual model performance. Among the sea-level stations (up to 200 m), the best modelling performance, in terms of meteorology and chemistry, was found for both models. The underestimated modelled PM concentrations in some cases indicated the importance of the accurate assessment of regional air pollution transport under statically stable atmospheric conditions and the necessity of further model improvements.
Highlights
The increased concentration of particulate matter (PM) in the ambient environment is associated with a significant impact on human health (Anderson, 2009; Heal et al, 2012; Peters et al, 2001; Pope et al, 2002; Samet et al, 2000; Samoli et al, 2005)
The p value is common variable used in hypothesis testing, the smaller the p value, the stronger is the evidence that the hypothesis needs to be rejected (Heiman, 2001)
Two different regional Air quality models (AQMs), namely, EMEP and WRF-Chem, were applied to evaluate their individual state-of-the-art performance and to investigate the processes that contributed to a high (PM10)d concentration during pollution episodes that occurred in Europe
Summary
The increased concentration of particulate matter (PM) in the ambient environment is associated with a significant impact on human health (Anderson, 2009; Heal et al, 2012; Peters et al, 2001; Pope et al, 2002; Samet et al, 2000; Samoli et al, 2005). Continuous exposure to PM is considered to be among the top 10 most significant risk factors for public health globally, including Europe (Prank et al, 2016). Putaud et al, 2010) These affect various meteorological processes such as cloud formation and radiation. Andreae et al, 2005; Jiang et al, 2013) that has an influence on Earth’s heat balance through the direct radiative effects and cloud processes (Prank et al, 2016). European aerosol phenomenology studies (Van Dingenen et al, 2004; Putaud et al, 2004, 2010) have shown that the annual background concentrations of PM with an aerodynamic di-
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