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Source apportionment (SA) techniques allocate the measured ambient pollutants with their potential source origin; thus, they are a powerful tool for designing air pollution mitigation strategies. Positive Matrix Factorization (PMF) is one of the most widely used SA approaches, and its multi-time resolution (MTR) methodology, which enables mixing different instrument data in their original time resolution, was the focus of this study. One year of co-located measurements in Barcelona, Spain, of non-refractory submicronic particulate matter (NR-PM1), black carbon (BC) and metals were obtained by a Q-ACSM (Aerodyne Research Inc.), an aethalometer (Aerosol d.o.o.) and fine offline quartz-fibre filters, respectively. These data were combined in a MTR PMF analysis preserving the high time resolution (30 min for the NR-PM1 and BC, and 24 h every 4th day for the offline samples). The MTR-PMF outcomes were assessed varying the time resolution of the high-resolution data subset and exploring the error weightings of both subsets. The time resolution assessment revealed that averaging the high-resolution data was disadvantageous in terms of model residuals and environmental interpretability. The MTR-PMF resolved eight PM1 sources: ammonium sulphate + heavy oil combustion (25%), ammonium nitrate + ammonium chloride (17%), aged secondary organic aerosol (SOA) (16%), traffic (14%), biomass burning (9%), fresh SOA (8%), cooking-like organic aerosol (5%), and industry (4%). The MTR-PMF technique identified two more sources relative to the 24 h base case data subset using the same species and four more with respect to the pseudo-conventional approach mimicking offline PMF, indicating that the combination of both high and low TR data is significantly beneficial for SA. Besides the higher number of sources, the MTR-PMF technique has enabled some sources disentanglement compared to the pseudo-conventional and base case PMF as well as the characterisation of their intra-day patterns.

Black carbon (BC) is recognized as the most important warming agent among atmospheric aerosol particles. The absorption efficiency of pure BC is rather well-known, nevertheless the mixing of BC with other aerosol particles can enhance the BC light absorption efficiency, thus directly affecting Earth's radiative balance. The effects on climate of the BC absorption enhancement due to the mixing with these aerosols are not yet well constrained because these effects depend on the availability of material for mixing with BC, thus creating regional variations. Here we present the mass absorption cross-section (MAC) and absorption enhancement of BC particles (Eabs), at different wavelengths (from 370 to 880nm for online measurements and at 637nm for offline measurements) measured at two sites in the western Mediterranean, namely Barcelona (BCN; urban background) and Montseny (MSY; regional background). The Eabs values ranged between 1.24 and 1.51 at the urban station, depending on the season and wavelength used as well as on the pure BC MAC used as a reference. The largest contribution to Eabs was due to the internal mixing of BC particles with other aerosol compounds, on average between a 91% and a 100% at 370 and 880nm, respectively. Additionally, 14.5% and 4.6% of the total enhancement at the short ultraviolet (UV) wavelength (370nm) was due to externally mixed brown carbon (BrC) particles during the cold and the warm period, respectively. On average, at the MSY station, a higher Eabs value was observed (1.83 at 637nm) compared to BCN (1.37 at 637nm), which was associated with the higher fraction of organic aerosols (OA) available for BC coating at the regional station, as denoted by the higher organic carbon to elemental carbon (OC:EC) ratio observed at MSY compared to BCN. At both BCN and MSY, Eabs showed an exponential increase with the amount of non-refractory (NR) material available for coating (RNR-PM). The Eabs at 637nm at the MSY regional station reached values

Particulate matter (PM) has become a major concern in terms of human health and climate impact. In particular, the source apportionment (SA) of organic aerosols (OA) present in submicron particles (PM1) has gained relevance as an atmospheric research field due to the diversity and complexity of its primary sources and secondary formation processes. Moreover, relatively simple but robust instruments such as the Aerosol Chemical Speciation Monitor (ACSM) are now widely available for the near-real-time online determination of the composition of the non-refractory PM1. One of the most used tools for SA purposes is the source-receptor positive matrix factorisation (PMF) model. Even though the recently developed rolling PMF technique has already been used for OA SA on ACSM datasets, no study has assessed its added value compared to the more common seasonal PMF method using a practical approach yet. In this paper, both techniques were applied to a synthetic dataset and to nine European ACSM datasets in order to spot the main output discrepancies between methods. The main advantage of the synthetic dataset approach was that the methods' outputs could be compared to the expected "true"values, i.e. the original synthetic dataset values. This approach revealed similar apportionment results amongst methods, although the rolling PMF profile's adaptability feature proved to be advantageous, as it generated output profiles that moved nearer to the truth points. Nevertheless, these results highlighted the impact of the profile anchor on the solution, as the use of a different anchor with respect to the truth led to significantly different results in both methods. In the multi-site study, while differences were generally not significant when considering year-long periods, their importance grew towards shorter time spans, as in intra-month or intra-day cycles. As far as correlation with external measurements is concerned, rolling PMF performed better than seasonal PMF globally for th