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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 (, where values are 370, 470, 520, 590, 660, 880, and 950 nm). The aerosol absorption coefficient at 637 nm (babsMAAP) 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 (PPUniMI). After comparing PPUniMI and MAAP results, we exploited PPUniMI data to evaluate the filter multiplescattering 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 PPUniMI. 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.

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 ran

Electrophysiological alterations of the neuromuscular junction (NMJ) and motor unit potential (MUP) with unloading are poorly studied. We aimed to investigate these aspects and the underlying molecular mechanisms with short-term unloading and active recovery (AR). Eleven healthy males underwent a 10-day unilateral lower limb suspension (ULLS) period, followed by 21-day AR based on resistance exercise. Quadriceps femoris (QF) cross-sectional area (CSA) and isometric maximum voluntary contraction (MVC) were evaluated. Intramuscular electromyographic recordings were obtained during 10% and 25% MVC isometric contractions from the vastus lateralis (VL). Biomarkers of NMJ molecular instability (serum c-terminal agrin fragment, CAF), axonal damage (neurofilament light chain) and denervation status were assessed from blood samples and VL biopsies. NMJ and ion channel transcriptomic profiles were investigated by RNA-sequencing. QF CSA and MVC decreased with ULLS. Increased CAF and altered NMJ transcriptome with unloading suggested the emergence of NMJ molecular instability, which was not associated with impaired NMJ transmission stability. Instead, increased MUP complexity and decreased motor unit firing rates were found after ULLS. Downregulation of ion channel gene expression was found together with increased neurofilament light chain concentration and partial denervation. The AR period restored most of these neuromuscular alterations. In conclusion, the human NMJ is destabilized at the molecular level but shows functional resilience to a 10-day unloading period at least at relatively low contraction intensities. However, MUP properties are altered by ULLS, possibly due to alterations in ion channel dynamics and initial axonal damage and denervation. These changes are fully reversed by 21 days of AR. (Figure presented.). Key points: We used integrative electrophysiological and molecular approaches to comprehensively investigate changes in neuromuscular integrity and functi

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 va