This paper presents data on elemental and mineralogical composition of mineral dust from various source regions of Africa collected during the African Monsoon Multidisciplinary Analyses (AMMA) SOP0/DABEX and Dust Ouflow and Deposition to the Ocean (DODO) DODO1 experiments (January–February 2006), and the DODO2 campaign (August 2006). Bulk filter samples were collected at the AMMA supersite of Banizoumbou, Niger, as well as on board the Facility for Airborne Atmospheric Measurements (FAAM) BAe‐146 aircraft. Both mineral dust and biomass burning in external mixing occurred in surface and elevated layers during the winter field phase of the campaign. However, mineral dust was overwhelming, accounting for 72% of the estimated aerosol mass in aged elevated biomass burning layers and up to 93% in plumes of mineral dust, which generally occurred in the boundary layer. A number of well‐defined episodes of advection of mineral dust could be identified both at the ground and on the aircraft. The elemental and mineralogical composition varied depending on source region. This variability could be well traced by the calcium content, which is enhanced in dust from North Africa but depleted in dust from the Sahel. Iron oxides in the form of hematite and goethite are enriched in dust emitted within Sahel and in Mauritania, whereas dust from the Bodélé depression is iron‐oxide depleted. Iron oxides represented between 2.4% and 4.5% of the total estimated dust oxide mass. This regional variability will have to be taken into account in estimating the optical properties of absorption of mineral dust from western Africa.

[1] North African dust is important for climate through its direct radiative effect on solar and terrestrial radiation and its role in the biogeochemical system. The Dust Outflow and Deposition to the Ocean project (DODO) aimed to characterize the physical and optical properties of airborne North African dust in two seasons and to use these observations to constrain model simulations, with the ultimate aim of being able to quantify the deposition of iron to the North Atlantic Ocean. The in situ properties of dust from airborne campaigns measured during February and August 2006, based at Dakar, Senegal, are presented here. Average values of the single scattering albedo (0.99, 0.98), mass specific extinction (0.85 m 2 g À1 , 1.14 m 2 g À1 ), asymmetry parameter (0.68, 0.68), and refractive index (1.53-0.0005i, 1.53-0.0014i) for the accumulation mode were found to differ by varying degrees between the dry and wet season, respectively. It is hypothesized that these differences are due to different source regions and transport processes which also differ between the DODO campaigns. Elemental ratios of Ca/Al were found to differ between the dry and wet season (1.1 and 0.5, respectively). Differences in vertical profiles are found between seasons and between land and ocean locations and reflect the different dynamics of the seasons. Using measurements of the coarse mode size distribution and illustrative Mie calculations, the optical properties are found to be very sensitive to the presence and amount of coarse mode of mineral dust, and the importance of accurate measurements of the coarse mode of dust is highlighted.

Abstract. 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 PM10 and PM2.5 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 PM10 and 1116 PM2.5 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 µg m−3 (16–32 %) to PM10 and 2.3 and 9.4 µg m−3 (15–36 %) to PM2.5, 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 PM2.5 (37–82 %) but also in PM10 (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 PM10 in POR-TR, MLN-UB and FI-UB, 7 % in ATH-SUB, to  <  2 % in BCN-UB. In PM2.5, 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 µg m−3 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 PM10 (5–12 % in PM2.5), 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 %).

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 0.5odo1 mm size bin). Contributions (e.g. Cu, elemental carbon and nitrogen oxides) to air pollution due to the large traffic volume registered during the same night were also singled out.The original application of Positive Matrix Factorisation and Multiple Linear Regression allowed, as far as we know, here for the first time, the quantification of the fireworks contribution to atmospheric particulate matter (PM) and the resolution of their chemical profile. The contribution of fireworks to the local environment in terms of PM 10 mass, elements and chemical components was assessed with 4-h time resolution. PM 10 mass apportioned by fireworks was up to 33.6 mg m À3 (about 50% of the total PM 10 mass). Major contributors were elemental and organic carbon (2.8 and 8.1 mg m À3, respectively) as well as metals like Mg, K, Sr, Ba, and Cu (0.4, 0.7, 0.07, 0.1, and 0.1 mg m À3 , respectively).

Daily time series measurements of elements or compounds are widely used to apportion the contribution of specific sources of particulate matter concentration in the atmosphere. We present results obtained for the urban area of Genoa (Italy) based on several hundred of PM10, PM2.5 and PM1 daily samples collected in sites with different geo-morphological and urbanization characteristics. Elemental concentrations of Na to Pb were obtained through Energy Dispersive X-Ray Fluorescence (ED-XRF), and the contributions of specific sources of particulate matter (PM) concentration were apportioned through Positive Matrix Factorization (PMF). By sampling at different sites we were able to obtain, in each PM fraction, the average and stable values for the tracers of specific sources, in particular traffic (Cu, Zn, Pb) and heavy oil combustion (V, Ni). We could also identify and quote the contamination of anthropogenic PM in "natural" sources (sea, soil dust). Sampling at several sites in the same urban area allowed us to resolve local characteristics as well as to quote average values. IntroductionIn recent years, atmospheric aerosols have been studied extensively (Charlson et al., 1992;Harrison et al., 2001;Satheesh and Moorthy, 2005 , 2002a,b;Stieb et al., 2002;Fernandez et al., 2003).Up to now, PM concentrations have been routinely monitored. However, this level of monitoring is insufficient and a measurement of the elemental and chemical composition of PM is recommended in order to achieve a more complete picture. Indeed concentration limits have been set in Europe for some toxic elements (Pb, Ni, Cd, Hg; see the recent European Directive 2004/107/CE). Element and/or compound measurements can also help to trace specific emission patterns. Thus, the knowledge of the chemical composition of particulate matter can be used to evaluate the impacts of the various pollution sources on air quality. Several "source apportionment" strategies have been developed; receptor models (Gordon, 1988) are presently considered the most effective approach. These models usually provide three pieces of information: the number of (major) sources of particulate matter, the source profiles and the mass contribution of each source to total PM. These models single out groups of elements with correlated concentration trends, which