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We describe a new experimental methodology based on the contemporary use of two-stage continuous streaker samplers and optical particle counters. This is a complementary approach to size-segregated particulate matter (PM) sampling, and it is able to give information on the elemental size distribution and to assess the contribution of major PM source to size bins. PM samples in the fine and coarse fraction of PM10 have been collected by a two-stage streaker sampler and analyzed by particle-induced X-ray emission (PIXE) to obtain elemental concentration time series with hourly resolution. PM sources and profiles were singled out by positive matrix factorization (PMF). A multi-linear regression of size-segregated number of particles versus the sources, resolved by PMF, made possible the apportionment of size-segregated particles number in a fast and direct way. Results obtained in three sampling sites, located in different urban districts are discussed.

The “Carbonaceous Aerosol in Rome and Environs” (CARE) experiment took place at a Mediterranean urban background site in Rome (Italy) deploying a variety of instrumentation to assess aerosol physical-chemical and optical properties with high-time resolution (from 1 min to 2 h). In this study, aerosol optical properties, chemical composition, and size distribution data were examined with a focus on the analysis of several intensive optical properties obtained from multi-wavelength measurements of aerosol scattering and absorption coefficients. The spectral behaviour of several quantities related to both aerosol composition and size was explored, analysing their high-time resolved temporal patterns and combining them in order to extract the maximum information from all the available data. A methodology to separate aerosol types using optical data only is here proposed and applied to an urban area characterised by a complex mixture of particles. A key is given to correctly disentangle cases that could not be distinguished observing only one or few parameters, but that can be clearly separated using a suitable ensemble of optical properties. The SSCAAE, i.e. the wavelength dependence of the Single Scattering co-albedo 1-SSA (where SSA is the Single Scattering Albedo) - that efficiently responds to both aerosol size and chemical composition – resulted to be the best optical intensive parameter to look at for the discrimination between episodes characterised by specific aerosol types (e.g. sea salt, Saharan dust) and more mixed conditions dominated by local emissions. However, this study also highlighted that it is necessary to combine temporal patterns of different optical parameters to robustly associate SSCAAE features to specific aerosol types. In addition, the complete chemical speciation and the high-time resolved size distribution were used to confirm the aerosol types identified via a combination of aerosol optical properties. Look-up tables with most suitable ranges of values for optical variables were produced; therefore, these pieces of information can be used at the same site or at locations with similar features to quickly identify the occurrence of aerosol episodes. Graphical frameworks (both from the literature and newly designed) are also proposed; for each scheme features, advantages, and limitations are discussed.

In this source apportionment study, an original approach based on receptor modelling was tested to relate primary and secondary organic aerosol (OA) contributions - estimated from ACSM (Aerosol Chemical Speciation Monitor) measurements - to their emission sources. Moreover, thanks to the coupling of optical and chemical variables as input to the receptor model, information such as the impact of mineral dust to the aerosol absorption in the atmosphere and estimates for the absorption Ångström exponent (α) of the sources were retrieved. An advanced source apportionment study using the Multilinear Engine (ME-2) was performed on data collected during February 2017 in Rome (Italy), in the frame of the CARE (Carbonaceous Aerosol in Rome and Environs) experiment. A complete chemical characterisation (elements, non-refractory components, and carbonaceous components) was carried out, and the aerosol absorption coefficients b(λ) at 7 wavelengths (370, 470, 520, 590, 660, 880, and 950 nm) were retrieved by an Aethalometer AE33; all these variables (chemical + optical) were used as input to the receptor model. The final constrained solution consisted of nine factors which were assigned to major sources impacting on the investigated site (hereafter sources are referred to as: biomass burning, nitrate and aged aerosol, traffic exhaust, sulphate, mineral dust, marine aerosol, traffic non-exhaust, local source, and polluted marine aerosol), comprising both local urban sources and contributions from long-range transport. The bootstrap analysis supported the goodness of the solution. Total OA concentration from ACSM was apportioned by our receptor model and afterwards compared with HOA (hydrocarbon-like organic aerosol), BBOA (biomass burning-like organic aerosol), and OOA (oxygenated organic aerosol) concentrations obtained as results from an independent source apportionment study previously performed. As an original result of this work, insights on OA contributions were thus retrieved: (1) the contribution of organic aerosol assigned by ME-2 to the traffic exhaust source was fully comparable to HOA assessed by ACSM data analysis; (2) our source apportionment results gave the relevant indication that the OOA apportionment made on ACSM data likely includes a secondary OA contribution due to biomass burning. Other relevant results came from b apportionment obtained by our multi-variable source apportionment approach: traffic exhaust was the main contributor to aerosol absorption in the atmosphere, but mineral dust contribution was also notable when a not negligible mineral dust transport episode was registered at the measurement site. In addition, source dependent optical absorption parameters (i.e. the absorption Ångström exponent - α - and the mass absorption cross section at different wavelengths) were retrieved without any a-priori assumption. In perspective, our modelling approach paves the way to more powerful source apportionment approaches which have the potential of providing much more insights on aerosol properties and sources., The CARE experiment was realised under the patronage of the Councilor for environmental sustainability of Roma Capitale. The authors are grateful to all members of the research groups who participated to the CARE experiment.

In this study, the performance of two types of source apportionment models was evaluated by assessing the results provided by 40 different groups in the framework of an intercomparison organised by FAIRMODE WG3 (Forum for air quality modelling in Europe, Working Group 3). The evaluation was based on two performance indicators: z-scores and the root mean square error weighted by the reference uncertainty (RMSEu), with pre-established acceptability criteria. By involving models based on completely different and independent input data, such as receptor models (RMs) and chemical transport models (CTMs), the intercomparison provided a unique opportunity for their cross-validation. In addition, comparing the CTM chemical profiles with those measured directly at the source contributed to corroborate the consistency of the tested model results. The most commonly used RM was the US EPA- PMF version 5. RMs showed very good performance for the overall dataset (91% of z-scores accepted) while more difficulties were observed with the source contribution time series (72% of RMSEu accepted). Industrial activities proved to be the most difficult sources to be quantified by RMs, with high variability in the estimated contributions. In the CTMs, the sum of computed source contributions was lower than the measured gravimetric PM10 mass concentrations. The performance tests pointed out the differences between the two CTM approaches used for source apportionment in this study: brute force (or emission reduction impact) and tagged species methods. The sources meeting the z-score and RMSEu acceptability criteria tests were 50% and 86%, respectively. The CTM source contributions to PM10 were in the majority of cases lower than the RM averages for the corresponding source. The CTMs and RMs source contributions for the overall dataset were more comparable (83% of the z-scores accepted) than their time series (successful RMSEu in the range 25% - 34%). The comparability between CTMs and RMs varied depending on the source: traffic/exhaust and industry were the source categories with the best results in the RMSEu tests while the most critical ones were soil dust and road dust. The differences between RMs and CTMs source reconstructions confirmed the importance of cross validating the results of these two families of models. © 2019 The Authors, The authors warmly thank J. Vercauteren (VMM) for providing the CHEMKAR dataset. The CARA program was funded by the French Ministry of environment . IMT Lille Douai participates in the CaPPA project funded by the ANR through the PIA under contract ANR-11-LABX-0005-01 , the “Hauts de France” Regional Council and the European Regional Development Fund (ERDF). The C2TN/IST author gratefully acknowledges the FCT support through the UID/Multi/04349/2013 project. J.L. Jaffrezo would like to thank F. Donnaz, F. Masson, and S. Ngo for the chemical analyses of the Lens samples performed at IGE (ECOC, ions, sugars). These were possible on the Air-O-Sol analytical platform supported by Labex OSUG@2020 (ANR10 LABX56). A. Angyal was supported by National Research, Development and Innovation Office – NKFIH , contract number PD 125086 . H. Jorquera acknowledges support from Grant CONICYT/FONDAP/15110020. P . Thunis commented on an early version of the manuscript.

In the frame of the EMEP/ACTRIS/COLOSSAL campaign in Milan during winter 2018, equivalent black carbon measurements using the Aethalometer 31 (AE31), the Aethalometer 33 (AE33), and a Multi-Angle Absorption Photometer (MAAP) were carried out together with levoglucosan analyses on 12 h resolved PM2.5 samples collected in parallel. From AE31 and AE33 data, the loading-corrected aerosol attenuation coefficients (bATN) were calculated at seven wavelengths (λ, where λ values are 370, 470, 520, 590, 660, 880, and 950 nm). The aerosol absorption coefficient at 637 nm (babs_MAAP) was determined by MAAP measurements. Furthermore, babs was also measured at four wavelengths (405, 532, 635, 780 nm) on the 12 h resolved PM2.5 samples by a polar photometer (PP_UniMI). After comparing PP_UniMI and MAAP results, we exploited PP_UniMI data to evaluate the filter multiple-scattering enhancement parameter at different wavelengths for AE31 and AE33. We obtained instrument- and wavelength-dependent multiple-scattering enhancement parameters by linear regression of the Aethalometer bATN against the babs measured by PP_UniMI. We found significant dependence of the multiple-scattering enhancement parameter on filter material, hence on the instrument, with a difference of up to 30 % between the AE31 and the AE33 tapes. The wavelength dependence and day–night variations were small – the difference between the smallest and largest value was up to 6 %. Data from the different instruments were used as input to the so-called “Aethalometer model” for optical source apportionment, and instrument dependence of the results was investigated. Inconsistencies among the source apportionment were found fixing the AE31 and AE33 multiple-scattering enhancement parameters to their usual values. In contrast, optimised multiple-scattering enhancement parameters led to a 5 % agreement among the approaches. Also, the component apportionment “MWAA model” (Multi-Wavelength Absorption Analyzer model) was applied to the dataset. It was less sensitive to the instrument and the number of wavelengths, whereas significant differences in the determination of the absorption Ångström exponent for brown carbon were found (up to 22 %).

The concentration of carbonates in atmospheric Particulate Matter (PM) is usually quite low. The surroundings of marble quarries are peculiar sites where the impact of carbonates in PM levels can be significant. We present here the results of a PM10 sampling campaign performed in Carrara (Italy). The town lies between the famous marble quarries and the harbour: about 1000 trucks per day transport marble blocks and debris from the quarries to the harbour passing through the town centre. PM10 was collected on daily basis on PTFE filters analyzed by Energy-Dispersive X-Ray Fluorescence (ED-XRF) and Ion-Chromatography (IC). Carbonate concentration was measured by a non-destructive Infrared Spectroscopy analysis (FT-IR). Time series of elemental (Na–Pb by ED-XRF), ionic (SO42−, NH4+ by ion-chromatography) and carbonate (by FT-IR) concentration values were merged in a unique data set and a PMF analysis singled out the major PM10 sources in the area. Marble transportation turned out to be the major pollution source in the town accounting to PM10 for about 36%; this corresponded to a CaCO3 average level of about 8 μg m−3 during working days. The FT-IR analysis was a crucial part of the work and an ad-hoc analytical procedure was specifically set up, calibrated, and tested as described in the text.

The performance and the uncertainty of receptor models (RMs) were assessed in intercomparison exercises employing real-world and synthetic input datasets. To that end, the results obtained by different practitioners using ten different RMs were compared with a reference. In order to explain the differences in the performances and uncertainties of the different approaches, the apportioned mass, the number of sources, the chemical profiles, the contribution-to-species and the time trends of the sources were all evaluated using the methodology described in Bells et al. (2015). In this study, 87% of the 344 source contribution estimates (SCEs) reported by participants in 47 different source apportionment model results met the 50% standard uncertainty quality objective established for the performance test. In addition, 68% of the SCE uncertainties reported in the results were coherent with the analytical uncertainties in the input data. The most used models, EPA-PMF v.3, PMF2 and EPA-CMB 8.2, presented quite satisfactory performances in the estimation of SCEs while unconstrained models, that do not account for the uncertainty in the input data (e.g. APCS and FA-MLRA), showed below average performance. Sources with well-defined chemical profiles and seasonal time trends, that make appreciable contributions (>10%), were those better quantified by the models while those with contributions to the PM mass close to 1% represented a challenge. The results of the assessment indicate that RMs are capable of estimating the contribution of the major pollution source categories over a given time window with a level of accuracy that is in line with the needs of air quality management. (C) 2015 The Authors. Published by Elsevier Ltd.

In this work, a methodology based on the macro-tracer approach was improved to obtain a more reliable estimate of the wood burning impact on PM10 and OC concentrations. Indeed, literature emission factors were weighed by the wood consumption data available for the investigated region and these tailored factors were used in the calculation. Moreover, an alternative approach using the chemical profile of the wood burning source obtained by the Positive Matrix Factorization was introduced. As far as we know, this is the first time that PMF-derived emission ratios instead of source emission factors are used in the macro-tracer method. A critical comparison of the results obtained by the two approaches was carried out. The results suggest that PMF-derived emission ratios can be a feasible alternative to the widely used wood smoke emission factors, which show a high variability. The proposed methodology was applied to a trial dataset of wintertime PM10 samples - characterised for anhydrosugars, organic, and elemental carbon e collected in the frame of a regional project. The results gave a preliminary estimate of the wood smoke contribution to PM10 and OC in different sites in Lombardy (Northern Italy)., JRC.H.2-Climate change and air quality

In this work Positive Matrix Factorization (PMF) was applied to 4-hour resolved PM10 data collected in Milan (Italy) during summer and winter 2006. PM10 characterisation included elements (Mg-Pb), main inorganic ions (NH 4+, NO 3-, SO 42-), levoglucosan and its isomers (mannosan and galactosan), and organic and elemental carbon (OC and EC).PMF resolved seven factors that were assigned to construction works, re-suspended dust, secondary sulphate, traffic, industry, secondary nitrate, and wood burning. Multi Linear Regression was applied to obtain the PM10 source apportionment. The 4-hour temporal resolution allowed the estimation of the factor contributions during peculiar episodes, which would have not been detected with the traditional 24-hour sampling strategy. © 2011 Elsevier B.V.

Nowadays, high-time resolved aerosol studies are mandatory to better understand atmospheric processes, such as formation, removal, transport, deposition or chemical reactions. This work focuses on PM10 physical and chemical characterisation with high-time resolution: elements (from Na to Pb), ions and OC/EC fractions concentration were determined during two weeks in summer and two in winter 2006 with 4-hours resolution. Further measurements aimed at hourly elemental characterisation of fine and coarse fractions and at the determination of particles number concentration in the 0.25-32 μm size range in 31 bins. The chemical mass closure was carried out in both seasons, enhancing intra-day differences in PM10 composition. In Milan, the highest contribution came from organic matter (34% and 33% in summer and winter, respectively); other important contributors were secondary inorganic compounds (16% and 24% in summer and winter, respectively) and, in summer, crustal matter (14%). Temporal trends showed strong variations in PM10 composition during contiguous time-slots and diurnal variations in different components contribution were identified. Moreover, peculiar phenomena, which would have hardly been detected with 24-hours samplings, were evidenced. Particles removal due to precipitations, aerosol local production and long range transport were studied in detail. © Springer Science+Business Media B.V. 2008.

In a few cases, atmospheric particulate matter characterization was taken into account together with aerobiological monitoring but never in an archive. The aim of this study was to estimate the air quality, by means of both chemical-physical and microbiological studies, at the Ca' Granda Historical Archive (Milan, Italy) that houses an important collection of documents from the 12th century. Temperature and relative humidity were measured in the rooms. Particulate matter (PM2.5) concentrations were quantified and the chemical composition, in terms of ionic components, elements, and carbonaceous fraction (total, organic, and elemental carbon) determined. The gaseous pollutants NO(2), SO(2), and O(3) and indoor acidity were also measured. Aerobiological monitoring (aerobic heterotrophic bacteria and fungi) was performed as volumes stored in the Archive were composed of organic materials, a potential energy and carbon source. In this paper, we present our findings and propose some guidelines for a better preservation of the documents.

During collection on filter-based aerosol samplers, organic and inorganic aerosol compounds both contribute to positive and negative artefacts, significantly affecting chemical analyses results for single species and PM mass concentrations, Up to now, Studies on organic or inorganic artefacts have been conducted in Europe but very scarce data are available for both in a single study. The field study was carried out in Milan, which is located in the Po valley (Northern Italy) one of the major pollution hot spots in Europe. As sampling artefacts depend on many factors, such as filter type, face velocity, sampling duration, and ambient conditions, in this field study two different filter types have been considered (i.e. quartz fibre filters and Teflon filters) for the assessment of both inorganic and organic artefacts during two different seasons (performing also some samplings at different flow-rates). Results showed that positive artefacts due to OC adsorption on quartz filters accounted for 39\% of the OC measured concentration in Summer, and 23\% in winter. Negative artefact due to nitrate volatilisation by the filters was 51\% on Teflon and 22\% on the quartz filters in summer, and no or negligible losses were observed in winter. A significant improvement in the PM mass comparability obtained in parallel samplings on different filters was obtained taking into account the artefact estimates performed in this study. (C) 2008 Elsevier Ltd. All rights reserved.

Sub-micron sized particles are of increasing concern owing to their effects on human health and on the environment. Up to now there are still very few studies on PM I (i.e. particulate matter with aerodynamic diameter smaller than 1 mu m) chemical characterisation; the sub-micron sized fraction is not under regulations although it is of interest because it is almost exclusively associated to anthropogenic sources. To perform the first large-scale assessment of sub-micron sized aerosol concentrations, composition and sources, two monitoring campaigns at three urban sites in Italy were carried out during the wintertime and summertime of 2004. Chemical characterisation (elements, soluble ionic fraction, elemental and organic carbon) was carried out on PM1 samples: major contributions were due to organic matter (about 30\% in summer and 50\% in winter) and ammonium sulphate (about 10\% in winter and 40\% in summer). During the cold season, nitrates also contributed up to 30\% in Milan (lower contributions were registered at the other two urban sites). Chemical mass closure was achieved with an unaccounted mass in the range 14-22\%. Positive Matrix Factorisation (PMF) was applied to identify the major submicron sized particles' sources. (c) 2007 Elsevier Ltd. All rights reserved.

Fireworks are one of the most unusual sources of pollution in atmosphere; although transient, these pollution episodes are responsible for high concentrations of particles (especially metals and organic compounds) and gases. In this paper, results of a study on chemical-physical properties of airborne particles (elements, ions, organic and elemental carbon and particles size distributions) collected during a fireworks episode in Milan (Italy) are reported. Elements typically emitted during pyrotechnic displays increased in 1 h as follows: Sr (120 times), Mg (22 times), Ba (12 times), K (11 times), and Cu (6 times). In our case study, Sr was recognised as the best fireworks tracer because its concentration was very high during the event and lower than, or comparable with, minimum detection limits during other time intervals, suggesting that it was mainly due to pyrotechnic displays. In addition, particles number concentrations increased significantly during the episode (up to 6.7 times in 1 h for the 0.5

{[1] Atmospheric aerosols in the PM(10) and PM(1) fractions have been sampled at the Global Atmospheric Watch station Mount Cimone, Italy ( 2165 m above mean sea level) for 3 months during summer 2004, and simultaneous size distributions have been derived by means of an optical particle counter. Samples have been analyzed by X-ray fluorescence, ion chromatography, and thermal-optical methodology in order to quantify their elemental, ionic, and carbonaceous constituents. The concentration of PM10 was 16.1 +/- 9.8 mu g m(-)3 ( average and standard deviation). Source apportionment allowed us to identify, quantify and characterize the following aerosol classes: anthropogenic pollution ( 10 mu g m(-3)), mineral dust ( 4 mu g m(-3)), and sea salt ( 0.2 mu g m(-3)). Pollution has been further split into ammonium sulfate (44\%), organic matter (42\%), and other compounds (14\%). The nitrate/sulfate ratio in the polluted aerosol was 0.1. Fine particles have been completely related to the polluted aerosol component, and they represented 70\% in weight of pollution. Coarse particles characterized the dust and salt components, and crustal oxides have been found to be the largest responsible for the aerosol concentration variations that occurred during the campaign. Nitrate has also been found in the coarse particles, representing similar to 10\% of mineral dust. The analysis of the transport mechanisms responsible for aerosol fluctuations permitted us to identify the origin of the major aerosol components: Pollution has been ascribed to regional transport driven by boundary layer meteorology, whereas mineral dust has been related to long-range transport events originating in the Sahara and Sahel. A particularly significant Saharan episode has been identified on 10 August 2004 ( PM(10) daily concentration, 69.9 mu g m(-3)). Average elemental ratios for the African dust events were as follows: Si/Al = 2.31, Fe/Ca = 0.94, Ca/Al = 0.90, K/Ca = 0.44, Ti/Ca = 0.11, and Ti/Fe = 0.12.}