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 PM_2.5 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 PM_2.5 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 PM_2.5, 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 PM_2.5 (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 PM_2.5, 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 PM_2.5 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 PM_2.5), 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 PM_2.5 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 %).

Sampling campaigns using the same equipment and methodology were conducted to assess and compare the air quality at three South European subway systems (Barcelona, Athens and Oporto), focusing on concentrations and chemical composition of PM2.5 on subway platforms, as well as PM2.5 concentrations inside trains. Experimental results showed that the mean PM2.5 concentrations widely varied among the European subway systems, and even among different platforms within the same underground system, which might be associated to distinct station and tunnel designs and ventilation systems. In all cases PM2.5 concentrations on the platforms were higher than those in the urban ambient air, evidencing that there is generation of PM2.5 associated with the subway systems operation. Subway PM2.5 consisted of elemental iron, total carbon, crustal matter, secondary inorganic compounds, insoluble sulphate, halite and trace elements. Of all metals, Fe was the most abundant, accounting for 29-43% of the total PM2.5 mass (41-61% if Fe2O3 is considered), indicating the existence of an Fe source in the subway system, which could have its origin in mechanical friction and wear processes between rails, wheels and brakes. The trace elements with the highest enrichment in the subway PM2.5 were Ba, Cu, Mn, Zn, Cr, Sb, Sr, Ni, Sn, Co, Zr and Mo. Similar PM2.5 diurnal trends were observed on platforms from different subway systems, with higher concentrations during subway operating hours than during the transport service interruption, and lower levels on weekends than on weekdays. PM2.5 concentrations depended largely on the operation and frequency of the trains and the ventilation system, and were lower inside the trains, when air conditioning system was operating properly, than on the platforms. However, the PM2.5 concentrations increased considerably when the train windows were open. The PM2.5 levels inside the trains decreased with the trains passage in aboveground sections.

Recent toxicological results highlight the importance of separating exposure to indoor- and outdoor-generated particles, due to their different physicochemical and toxicological properties. In this framework, a number of studies have attempted to estimate the relative contribution of particles of indoor and outdoor origins to indoor concentrations, using either statistical analysis of indoor and outdoor concentration time-series or mass balance equations. The aim of this work is to review and compare the methodologies developed in order to determine the ambient particle infiltration factor (F _INF) (i.e., the fraction of ambient particles that enter indoors and remains suspended). The different approaches are grouped into four categories according to their methodological principles: (1) steady-state assumption using the steady-state form of the mass balance equation; (2) dynamic solution of the mass balance equation using complex statistical techniques; (3) experimental studies using conditions that simplify model calculations (e.g., decreasing the number of unknowns); and (4) infiltration surrogates using a particulate matter (PM) constituent with no indoor sources to act as surrogate of indoor PM of outdoor origin. Examination of the various methodologies and results reveals that estimating infiltration parameters is still challenging. The main difficulty lies in the separate calculation of penetration efficiency (P) and deposition rate (k). The values for these two parameters that are reported in the literature vary significantly. Deposition rate presents the widest range of values, both between studies and size fractions. Penetration efficiency seems to be more accurately calculated through the application of dynamic models. Overall, estimates of the infiltration factor generated using dynamic models and infiltration surrogates show good agreement. This is a strong argument in favor of the latter methodology, which is simple and easy to apply when chemical speciation data are available.

A comparison exercise on thermal-optical elemental carbon/organic carbon (ECOC) analysers was carried out among 17 European laboratories. Contrary to previous comparison exercises, the 17 participants made use of an identical instrument set-up, after correcting for temperature offsets with the application of a recently developed temperature calibration kit (Sunset Laboratory Inc, OR, US). Temperature offsets reported by participants ranged from −93 to +100 °C per temperature step. Five filter samples and two sucrose solutions were analysed with both the EUSAAR2 and NIOSH870 thermal protocols. z scores were calculated for total carbon (TC); nine outliers and three stragglers were identified. Three outliers and eight stragglers were found for EC. Overall, the participants provided results between the warning levels with the exception of two laboratories that showed poor performance, the causes of which were identified and corrected through the course of the comparison exercise. The TC repeatability and reproducibility (expressed as relative standard deviations) were 11 and 15% for EUSAAR2 and 9.2 and 12% for NIOSH870; the standard deviations for EC were 15 and 20% for EUSAAR2 and 20 and 26% for NIOSH870. TC was in good agreement between the two protocols, TC_NIOSH870 = 0.98 × TC_EUSAAR2 (R² = 1.00, robust means). Transmittance (TOT) calculated EC for NIOSH870 was found to be 20% lower than for EUSAAR2, EC_NIOSH870 = 0.80 × EC_EUSAAR2 (R² = 0.96, robust means). The thermograms and laser signal values were compared and similar peak patterns were observed per sample and protocol for most participants. Notable deviations from the typical patterns indicated either the absence or inaccurate application of the temperature calibration procedure and/or pre-oxidation during the inert phase of the analysis. Low or zero pyrolytic organic carbon (POC), as reported by a few participants, is suggested as an indicator of an instrument-specific pre-oxidation. A sample-specific pre-oxidation effect was observed for filter G, for all participants and both thermal protocols, indicating the presence of oxygen donors on the suspended particulate matter. POC (TOT) levels were lower for NIOSH870 than for EUSAAR2, which is related to the heating profile differences of the two thermal protocols.