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The recently developed Ion and Mass Balance (IMB) source apportionment methodology was applied to a traffic influenced urban aerosol, permitting the quantification of the contributions of 11 source components, or formation processes, which accounted for more than 96% of the measured aerosol mass loading. Main sources included exhaust and non-exhaust road vehicle emissions, biomass burning, secondary inorganic and organic pollutants, and primary soil and sea salt emissions. While in summer secondary carbonaceous matter is the predominant fraction, in winter biomass burning accounts, on average, for more than 40% of the PM2.5 aerosol. Comparison with Positive Matrix Factorization (PMF) showed the complementary characteristics of the two methodologies. PMF yielded 8 source profiles, including industry and oil combustion sources not discriminated by IMB. PMF is better at quantifying multiple component contributions to sources. IMB solves problems of collinearity between aerosol tracers and permits the discrimination of secondary formed pollutants.

Knowledge gaps in the optical properties of carbonaceous aerosols account for a significant fraction of the uncertainty of aerosol - light interactions in climate models. Both black carbon (BC) and brown carbon (BrC) can display a range of optical properties in ambient aerosol due to different sources and chemical transformation pathways. This study investigates the optical absorption properties of BC and BrC at an urban and a rural site in the Po Valley (Italy), a known European pollution hot spot. We observed spatial and seasonal variability of aerosol absorption coefficients, with the highest values measured in winter at the urban site of Milan (12 Mm–1 on average) and the lowest values in summer at the rural site of Motta Visconti (3 Mm–1 on average). The average aerosol Absorption Angstrom Exponent (AAE) measured during the two experiments across the 370–880 nm wavelength range was 1.1 and 1.2 at the urban and the rural site, respectively. The observed AAE values in winter (the average AAE during the two winter campaigns was 1.2) are consistent with the contribution of wood burning BrC, as confirmed by macro-tracer analysis. The BC mass absorption cross section (MACBC) did not show a specific seasonal or spatial variability across the two sites and maintained an average value of 10 ± 5 m2 g–1 at 880 nm. The optical properties of BrC, investigated off-line after extraction of organic aerosol (OA) indicate that wood burning was the dominant BrC source in winter, while secondary organic aerosol (SOA) from other anthropogenic emissions was the main source of BrC in summer.

This study presents a high–resolution (5 km) set of new simulations performed with CAMx v6.40 over the Po Valley area (Northern Italy), aimed to enhance organic aerosol (OA) levels prediction and to gain insight into the sensitivity of CAMx to different uncertain features of the input setup. In particular, we mainly investigated the role of (i) volatility distributions of organic emissions, (ii) parametrizations of semi– and intermediate–volatile organic compounds (S/IVOC) emissions and (iii) different aging schemes, by exploiting the latest experimental information available in the recent scientific literature. Model results were validated against two OA–specific datasets, available for both an urban site (Bologna, February 2013) and a rural one (Ispra, March 2013). We found out a remarkable performance enhancement of modelled OA levels when applying revisions in S/IVOC emission parametrizations together with the new volatility distributions, at both the validation sites. This performance enhancement is associated with a very significant improvement in secondary organic aerosol (SOA) prediction, mainly due to revised IVOC emissions. At Bologna urban site, mean fractional bias (MFB) of OA ranged from −80.1% in the worst run to −10.1% in the best one and index of agreement (IOA) from 0.52 to 0.75. Notable improvements but overall poorer metrics were found for Ispra site, where MFB ranges from −84.2% to −35% and IOA from 0.45 to 0.50. These findings indicate that organic matter in the semi– and intermediate–volatile range are most likely underestimated in official emission inventories for each main source category (i.e. biomass burning, diesel and gasoline vehicles exhaust). Finally, model results did not show a very pronounced sensitivity to aging processes, due to the low photochemical activity typically observed during winter–time. However, we give evidence that enabling aging processes for biomass burning related SOA, which is by default disabled in CAMx v6.40, can help in closing the gap between modelled and observed SOA concentrations.

The AIRUSE-LIFE+ project aims at characterizing similarities and heterogeneities in particulate matter (PM) sources and contributions in urban areas from southern Europe. Once the main PMx sources are identified, AIRUSE aims at developing and testing the efficiency of specific and non-specific measures to improve urban air quality. This article reports the results of the source apportionment of PM and PM conducted at three urban background sites (Barcelona, Florence and Milan, BCN-UB, FI-UB and MLN-UB), one suburban background site (Athens, ATH-SUB) and one traffic site (Porto, POR-TR). After collecting 1047 PM and 1116 PM 24 h samples during 12 months (from January 2013 on) simultaneously at the five cities, these were analysed for the contents of OC, EC, anions, cations, major and trace elements and levoglucosan. The USEPA PMF5 receptor model was applied to these data sets in a harmonized way for each city. The sum of vehicle exhaust (VEX) and non-exhaust (NEX) contributes between 3.9 and 10.8 μ (16-32 %) to PM and 2.3 and 9.4 μ (15-36 %) to PM, although a fraction of secondary nitrate is also traffic-related but could not be estimated. Important contributions arise from secondary particles (nitrate, sulfate and organics) in PM (37-82 %) but also in PM (40-71 %), mostly at background sites, revealing the importance of abating gaseous precursors in designing air quality plans. Biomass burning (BB) contributions vary widely, from 14-24 % of PM in POR-TR, MLN-UB and FI-UB, 7 % in ATH-SUB, to < 2 % in BCN-UB. In PM, BB is the second most important source in MLN-UB (21 %) and in POR-TR (18 %), the third one in FI-UB (21 %) and ATH-SUB (11 %), but is again negligible (< 2 %) in BCN-UB. This large variability among cities is mostly due to the degree of penetration of biomass for residential heating. In Barcelona natural gas is very well supplied across the city and is used as fuel in 96 % of homes, while in other cities, PM levels increase on an annual basis by 1-9 μ due to biomass burning influence. Other significant sources are the following. - Local dust, 7-12 % of PM10 at SUB and UB sites and 19 % at the TR site, revealing a contribution from road dust resuspension. In PM2.5 percentages decrease to 2-7 % at SUB-UB sites and 15 % at the TR site. - Industry, mainly metallurgy, contributing 4-11 % of PM (5-12 % in PM), but only at BCN-UB, POR-TR and MLN-UB. No clear impact of industrial emissions was found in FI-UB and ATH-SUB. - Natural contributions from sea salt (13 % of PM10 in POR-TR, but only 2-7 % in the other cities) and Saharan dust (14 % in ATH-SUB, but less than 4 % in the other cities). During high pollution days, the largest sources (i.e. excluding secondary aerosol factors) of PM10 and PM2.5 are VEX + NEX in BCN-UB (27-22 %) and POR-TR (31-33 %), BB in FI-UB (30-33 %) and MLN-UB (35-26 %) and Saharan dust in ATH-SUB (52-45 %). During those days, there are also quite important industrial contributions in BCN-UB (17-18 %) and local dust in POR-TR (28-20 %)., Acknowledgements.This work was funded by the AIRUSE LIFE+(ENV/ES/584) EU project. Fulvio Amato is a beneficiary of theJuan de la Cierva postdoctoral grant (JCI-2012-13473) from theSpanish Ministry of Economy and Competitiveness. Danilo Custó-dio acknowledges the doctoral fellowship SFRH/BD/76283/2011from the Portuguese Science Foundation. Support is acknowledgedto Generalitat de Catalunya 2014 SGR33 and to AXA Research Fund

Air pollution represents a critical issue in Milan urban area (Northern Italy). Here, the levels of fine particles increase, overcoming the legal limits, mostly in wintertime, due to favourable calm weather conditions and large heating and vehicular traffic emissions. The main goal of this work is to quantify the aerosol removal effect due to precipitation at the ground. At first, the scavenging coefficients have been calculated for aerosol particles with diameter between 0.25 and 3 μm. The average values of this coefficient vary between 2 × 10 - 5 and 5 × 10 - 5 s −1 . Then, the aerosol removal induced separately by precipitation and wind have been compared through the introduction of a removal index. As a matter of fact, while precipitation leads to a proper wet scavenging of the particles from the atmosphere, high wind speeds cause enhanced particle dispersion and dilution, that locally bring to a tangible decrease of aerosol particles’ number. The removal triggered by these two forcings showed comparable average values, but different trends. The removal efficiency of precipitation lightly increases with the increase of particle diameters and vice versa happens with strong winds.

Particle number size distributions (PNSDs) have been collected periodically in Milan urban area, Italy, during 2011 and 2012 in winter and summer months. Moreover, comparable PNSD measurements were carried out in the rural mountain site of Oga-San Colombano (2250 m a.s.l.), Italy, during February 2005 and August 2011. The aerosol data have been measured through the use of Optical Particle Counters in the size range 0.3–25 µm, mainly belonging to the coarse mode (PMcoarse), with a time resolution of one minute. The comparison of the PNSDs collected in the two sites has been done in terms of total number concentration, showing higher numbers in Milan (often exceeding 103 cm−3 in winter season) compared to Oga-San Colombano (not greater than 2 ∙ 102 cm−3), as expected. The skewness-kurtosis plane has been used in order to provide a synoptic view, and select the best distribution family describing the empirical PNSD pattern. The four-parameter Johnson SB (JSB) distribution has been tested for this aim, due to its great flexibility and ability of assuming different shapes. The PNSD pattern has been found to be generally invariant under site and season changes. Nevertheless, several PNSDs belonging to Milan winter season (generally more than 30 %) clearly deviate from the standard empirical pattern. The seasonal increase of the concentration of primary aerosols due to combustion processes in winter and the influence of weather variables, such as precipitation and wind speed, throughout the year, could be considered plausible explanations of PNSD dynamics.

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Traditional aerosol mechanisms underestimate the observed organic aerosol concentration, especially due to the lack of information on secondary organic aerosol (SOA) formation and processing. In this study we evaluate the chemical and transport model CAMx during a one-month in winter (February 2013) over a 5 km resolution domain, covering the whole Po valley (Northern Italy). This works aims at investigating the effects of chemical and physical atmospheric processing on modelling results and, in particular, to evaluate the CAMx sensitivity to organic aerosol (OA) modelling schemes: we will compare the recent 1.5D-VBS algorithm (CAMx-VBS) with the traditional Odum 2-product model (CAMx-SOAP). Additionally, the thorough diagnostic analysis of the reproduction of meteorology, precursors and aerosol components was intended to point put strength and weaknesses of the modelling system and address its improvement. Firstly, we evaluate model performance for criteria PM concentration. PM10 concentration was underestimated both by CAMx-SOAP and even more by CAMx-VBS, with the latter showing a bias ranging between −4.7 and −7.1 μg m−3. PM2.5 model performance was to some extent better than PM10, showing a mean bias ranging between −0.5 μg m−3 at rural sites and −5.5 μg m−3 at urban and suburban sites. CAMx performance for OA was clearly worse than for the other PM compounds (negative bias ranging between −40% and −75%). The comparisons of model results with OA sources (identified by PMF analysis) shows that the VBS scheme underestimates freshly emitted organic aerosol while SOAP overestimates. The VBS scheme correctly reproduces biomass burning (BBOA) contributions to primary OA concentrations (POA). In contrast VBS slightly underestimates the contribution from fossil-fuel combustion (HOA), indicating that POA emissions related to road transport are either underestimated or associated to higher volatility classes. The VBS scheme under-predictes the SOA too, but to a lesser extent than CAMx-SOAP. SOA underestimation can be related to corresponding underestimation of either aging processes or precursor emissions. This indicates that improvements in the emission inventories for semi- and intermediate-volatility organic compounds are needed for further progress in this area. Finally, the comparison between modelled and observed SOA sources points out the urgency to include processing of OA in particle water phase into SOA formation mechanisms, to reconcile model results and observations.

An interlaboratory comparison was performed to evaluate the analytical methods for quantification of anhydrosugars - levoglucosan, mannosan, galactosan - and biosugars - arabitol, glucose and mannitol - in atmospheric aerosol. The performance of 10 laboratories in Italy currently involved in such analyses was investigated on twenty-six PM (particulate matter) ambient filters, three synthetic PM filters and three aqueous standard solutions. An acceptable interlaboratory variability was found, determined as the mean relative standard deviation (RSD%) of the results from the participating laboratories, with the mean RSD% values ranging from 25% to 46% and decreasing with increasing sugar concentration. The investigated methods show good accuracy, evaluated as the percentage error (ε%) related to mean values, since method biases ranged within ±20% for most of the analytes measured in the different laboratories. The detailed investigation (ANOVA analysis at p 0.05) of the contribution of each laboratory to the total variability and the measurement accuracy shows that comparable results are generated by the different methods, despite the great diversity in terms of extraction conditions, chromatographic separation - more recent LC (liquid chromatography) and EC (exchange chromatography) methods compared to more widespread GC (gas chromatography) - and detection systems, namely PAD (pulsed amperometric detection) or mass spectrometry.

Seven fuels (four types of wood pellets and three agro-fuels) were tested in an automatic pellet stove (9.5 kWth) in order to determine emission factors (EFs) of gaseous compounds, such as carbon monoxide (CO), methane (CH4), formaldehyde (HCHO), and total organic carbon (TOC). Particulate matter (PM10) EFs and the corresponding chemical compositions for each fuel were also obtained. Samples were analysed for organic carbon (OC) and elemental carbon (EC), anhydrosugars and 57 chemical elements. The fuel type clearly affected the gaseous and particulate emissions. The CO EFs ranged from 90.9 ± 19.3 (pellets type IV) to 1480 ± 125 mg MJ−1 (olive pit). Wood pellets presented the lowest TOC emission factor among all fuels. HCHO and CH4 EFs ranged from 1.01 ± 0.11 to 36.9 ± 6.3 mg MJ−1 and from 0.23 ± 0.03 to 28.7 ± 5.7 mg MJ−1, respectively. Olive pit was the fuel with highest emissions of these volatile organic compounds. The PM10 EFs ranged from 26.6 ± 3.14 to 169 ± 23.6 mg MJ−1. The lowest PM10 emission factor was found for wood pellets type I (fuel with low ash content), whist the highest was observed during the combustion of an agricultural fuel (olive pit). The OC content of PM10 ranged from 8 wt.% (pellets type III) to 29 wt.% (olive pit). Variable EC particle mass fractions, ranging from 3 wt.% (olive pit) to 47 wt.% (shell of pine nuts), were also observed. The carbonaceous content of particulate matter was lower than that reported previously during the combustion of several wood fuels in traditional woodstoves and fireplaces. Levoglucosan was the most abundant anhydrosugar, comprising 0.02–3.03 wt.% of the particle mass. Mannosan and galactosan were not detected in almost all samples. Elements represented 11–32 wt.% of the PM10 mass emitted, showing great variability depending on the type of biofuel used.

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Municipal solid waste incinerator (MSWI) fly ash was investigated to study metal distribution on the particle surface. A detailed investigation into the distribution of chlorine, copper, iron, and zinc was carried out by electron microscopy coupled with X-ray fluorescence spectroscopy. Compositional and leaching test data were used to identify the correlation of significant variables and to formulate a hypothesis about metals speciation. The presence of copper chloride, iron, and zinc oxides was inferred. The iron and zinc accumulation in the submicron nuclei indicates that these metals came from the condensation of volatile species. As far as concerns copper, morphological data together with the element correlation study suggest that this element accumulates on particles involved in heterogeneous condensation processes. Furthermore, during such processes, particles of small size containing copper are formed.

INTRODUCTION Polyciclic aromatic hydrocarbons (PAHs) are produced by high-temperature reactions such as incomplete combustion and pyrolysis of fossil fuels and other organic materials. Studies have estimated that mobile sources are the major contributors to PAHs content of urban and suburban aerosol (Nielsen T., 1996). High concentrations of PM10 are associated to adverse health effects and PAHs, primarily adsorbed to fine particles, account for most of the mutagenic potency that can be assigned to specific compounds (Hanningan et al., 1998). PAHs can be found both in the gas and in the particulate phase, and for more volatile PAHs this is a function of temperature: PAHs with a higher molecular weight, which are more toxic, are always primarily associated with particulate phase (e.g B[a]P more than 90% in the particulate phase) (Odabasi M., 1999)

In several studies, investigators have reported associations among air pollution, weather, and daily deaths, usually from all causes. In the current study, we focused on the difference in lag time between exposure to total suspended particulates or extreme weather and cause-specific mortality in an effort to understand the potential underlying mechanism. We used a robust Poisson regression in a generalized additive model to investigate the association between air pollution and daily mortality. We used a loess smooth function to model season, weather, and humidity; indicator variables for hot days were also used. To examine the relationship in a currently meaningful range, we excluded all days with a total suspended particulate concentration higher than 200 microg/m3. We found a significant association on the concurrent day, both for respiratory infection deaths (11% increase/100 microg/m3 increase in total suspended particulate; 95% confidence interval = 5, 17) and for heart-failure deaths (7% increase; 95% confidence interval = 3, 11). The associations with myocardial infarction (i.e., 10% increase; 95% confidence interval = 3, 18) and chronic obstructive pulmonary disease (12% increase, 95% confidence interval = 6, 17) were found for the means of 3 and 4 d prior to death. We observed an effect of cold weather at lag 1 for respiratory infections and an effect of hot weather at lag 0 for heart failure and myocardial infarctions. The association for all causes and cause-specific deaths was almost identical to that noted previously in Philadelphia, Pennsylvania. Smoothed functions of total suspended particulates suggested a higher slope at lower concentrations, and this finding may account for differences noted between European and U.S. studies. Given that both the dependence between weather and daily mortality and the lag between exposure and death varies by cause of death, analyses by specific causes of death would be very useful in the future.

Biomass burning (BB) is a significant source of atmospheric particles in many parts of the world. Whereas many studies have demonstrated the importance of BB emissions in central and northern Europe, especially in rural areas, its impact in urban air quality of southern European countries has been sparsely investigated. In this study, highly time resolved multi-wavelength absorption coefficients together with levoglucosan (BB tracer) mass concentrations were combined to apportion carbonaceous aerosol sources. The Aethalometer model takes advantage of the different spectral behaviour of BB and fossil fuel (FF) combustion aerosols. The model was found to be more sensitive to the assumed value of the aerosol Ångström exponent (AAE) for FF (AAEff) than to the AAE for BB (AAEbb). As result of various sensitivity tests the model was optimized with AAEff = 1.1 and AAEbb = 2. The Aethalometer model and levoglucosan tracer estimates were in good agreement. The Aethalometer model was further applied to data from three sites in Granada urban area to evaluate the spatial variation of CMff and CMbb (carbonaceous matter from FF or BB origin, respectively) concentrations within the city. The results showed that CMbb was lower in the city centre while it has an unexpected profound impact on the CM levels measured in the suburbs (about 40%). Analysis of BB tracers with respect to wind speed suggested that BB was dominated by sources outside the city, to the west in a rural area. Distinguishing whether it corresponds to agricultural waste burning or with biomass burning for domestic heating was not possible. This study also shows that although traffic restrictions measures contribute to reduce carbonaceous concentrations, the extent of the reduction is very local. Other sources such as BB, which can contribute to CM as much as traffic emissions, should be targeted to reduce air pollution., This research was partially supported by the Andalusia Regional Government through projects P10-RNM-6299 and P12-RNM-2409, by the Spanish Ministry of Economy and Competitiveness and FEDER through project CGL2013_45410-R; by EUREKA and the Slovenian Ministry of Economic Development and Technology grants (Eurostars grant E!4825 FC Aeth, JR-KROP grant 3211-11-000519); and by European Union's Horizon 2020 Research and Innovation Programme under grant agreement No. 654109, ACTRIS-2. The authors would like to thank Air Quality Service from Junta de Andalucía (Consejería de Medio Ambiente y Ordenación del Territorio) and Vicerrectorado de Política Científica e Investigación from the University of Granada for their support in the installation of the Aethalometer at PC and GV, respectively., G. Titos was partially funded by Programa del Plan Propio de Investigación “Contrato Puente” of the University of Granada and by the Spanish Ministry of Economy and Competitiveness under postdoctoral program Juan de la Cierva – Formación (FJCI-2014-20819).