PM 2.5 , mass concentration of particles less than 2.5 mm in size; PM 2.5 absorbance, measurement of the blackness of PM 2.5 filters, this is a proxy for elemental carbon, which is the dominant light absorbing substance; PM 10 , mass concentration of particles less than 10 mm in size; PM coarse , mass concentration of the coarse fraction of particles between 2.5 mm and 10 mm in size; RB, regional background; RH, relative humidity; ST, Street; TRAPCA, Traffic-Related Air Pollution and Childhood Asthma; UB, urban background; US EPA, United States Environmental Protection Agency.

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:

No abstract

Abstract.To identify the relative contribution of local versus regional sources of particulate matter (PM) in the Greater Athens Area (GAA), simultaneous 24-h mass and chemical composition measurements of size segregated particulate matter (PM 1 , PM 2.5 and PM 10 ) were carried out from September 2005 to August 2006 at three locations: one urban (Goudi, Central Athens, "GOU"), one suburban (Lykovrissi, Athens, "LYK") in the GAA and one at a regional background site (Finokalia, Crete, "FKL").The two stations in the GAA exceeded the EU-legislated PM 10 limit values, both in terms of annual average (59.0 and 53.6 µg m −3 for Lykovrissi and Goudi, respectively) and of 24-h value. High levels of PM 2.5 and PM 1 were also found at both locations (23.5 and 18.6 for Lykovrissi, while 29.4 and 20.2 µg m −3 for Goudi, respectively).Significant correlations were observed between the same PM fractions at both GAA sites indicating important spatial homogeneity within GAA. During the warm season (April to September), the PM 1 ratio between GAA and FKL ranged from 1.1 to 1.3. On the other hand this ratio was significantly higher (1.6-1.7) during the cold season (October to March) highlighting the role of long-range transport and local sources during the warm and cold seasons respectively. Regarding the coarse fraction no seasonal trend was observed for both GAA sites with their ratio (GAA site/FKL) being higher than 2 indicating significant contribution from local sources such as soil and/or road dust.Chemical speciation data showed that on a yearly basis, ionic and crustal mass represent up to 67-70 % of the gravimetrically determined mass for PM 10 samples in the GAA Correspondence to: N. Mihalopoulos (mihalo@chemistry.uoc.gr) and 67 % for PM 1 samples in LYK. The unidentified mass might be attributed to organic matter (OM) and elemental carbon (EC), in agreement with the results reported by earlier studies in central Athens. At all sites, similar seasonal patterns were observed for nss-SO 2− 4 , a secondary compound, indicating significant contribution from regional sources in agreement with PM 1 observations. The contribution of local sources at both GAA sites was also estimated by considering mass and chemical composition measurements at Finokalia as representative of the regional background. Particulate Organic Matter (POM) and EC, seemed to be the main contributor of the local PM mass within the GAA (up to 62 % in PM 1 ). Dust from local sources contributed also significantly to the local PM 10 mass (up to 33 %).

Abstract. Submicron aerosol chemical composition was studied during a year-long period (26 July 2016–31 July 2017) and two wintertime intensive campaigns (18 December 2013–21 February 2014 and 23 December 2015–17 February 2016), at a central site in Athens, Greece, using an Aerosol Chemical Speciation Monitor (ACSM). Concurrent measurements included a particle-into-liquid sampler (PILS-IC), a scanning mobility particle sizer (SMPS), an AE-33 Aethalometer, and ion chromatography analysis on 24 or 12 h filter samples. The aim of the study was to characterize the seasonal variability of the main submicron aerosol constituents and decipher the sources of organic aerosol (OA). Organics were found to contribute almost half of the submicron mass, with 30 min resolution concentrations during wintertime reaching up to 200 µg m−3. During winter (all three campaigns combined), primary sources contributed about 33 % of the organic fraction, and comprised biomass burning (10 %), fossil fuel combustion (13 %), and cooking (10 %), while the remaining 67 % was attributed to secondary aerosol. The semi-volatile component of the oxidized organic aerosol (SV-OOA; 22 %) was found to be clearly linked to combustion sources, in particular biomass burning; part of the very oxidized, low-volatility component (LV-OOA; 44 %) could also be attributed to the oxidation of emissions from these primary combustion sources. These results, based on the combined contribution of biomass burning organic aerosol (BBOA) and SV-OOA, indicate the importance of increased biomass burning in the urban environment of Athens as a result of the economic recession. During summer, when concentrations of fine aerosols are considerably lower, more than 80 % of the organic fraction is attributed to secondary aerosol (SV-OOA 31 % and LV-OOA 53 %). In contrast to winter, SV-OOA appears to result from a well-mixed type of aerosol that is linked to fast photochemical processes and the oxidation of primary traffic and biogenic emissions. Finally, LV-OOA presents a more regional character in summer, owing to the oxidation of OA over the period of a few days.

No abstract

No abstract

Particulate atmospheric pollution in urban areas is considered to have significant impact on human health. Therefore, the ability to make accurate predictions of particulate ambient concentrations is important to improve public awareness and air quality management. This study examines the possibility of using neural network methods as tools for daily average particulate matter with aerodynamic diameter Ͻ10 m (PM 10 ) concentration forecasting, providing an alternative to statistical models widely used up to this day. Based on a data inventory, in a fixed central site in Athens, Greece, ranging over a two-year period, and using mainly meteorological variables as inputs, neural network models and multiple linear regression models were developed and evaluated. Comparison statistics used indicate that the neural network approach has an edge over regression models, expressed both in terms of prediction error (root mean square error values lower by 8.2-9.4%) and of episodic prediction ability (false alarm rate values lower by 7-13%). The results demonstrate that artificial neural networks (ANNs), if properly trained and formed, can provide adequate solutions to particulate pollution prognostic demands.