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Providing reliable observations of aerosol particles' absorption properties at spatial and temporal resolutions suited to climate models is of utter importance to better understand the effects that atmospheric particles have on climate. Nowadays, one of the instruments most widely used in international monitoring networks for in situ surface measurements of light absorption properties of atmospheric aerosol particles is the multi-wavelength dual-spot Aethalometer, AE33. The AE33 derives the absorption coefficients of aerosol particles at seven different wavelengths from the measurements of the optical attenuation of light through a filter where particles are continuously collected. An accurate determination of the absorption coefficients from the AE33 instrument relies on the quantification of the non-linear processes related to the sample collection on the filter. The multiple-scattering correction factor (C), which depends on the filter tape used and on the optical properties of the collected particles, is the parameter with both the greatest uncertainty and the greatest impact on the absorption coefficients derived from the AE33 measurements. Here we present an in-depth analysis of the AE33 multiple-scattering correction factor C and its wavelength dependence for two different and widely used filter tapes, namely the old, and most referenced, TFE-coated glass, or M8020, filter tape and the currently, and most widely used, M8060 filter tape. For performing this analysis, we compared the attenuation measurements from AE33 with the absorption coefficients measured with different filter-based techniques. On-line co-located multi-angle absorption photometer (MAAP) measurements and off-line PP_UniMI polar photometer measurements were employed as reference absorption measurements for this work. To this aim, we used data from three different measurement stations located in the north-east of Spain, namely an urban background station (Barcelona, BCN), a regional background station (Montseny, MSY) and a mountaintop station (Montsec d'Ares, MSA). The median C values (at 637 nm) measured at the three stations ranged between 2.29 (at BCN and MSY, lowest 5th percentile of 1.97 and highest 95th percentile of 2.68) and 2.51 (at MSA, lowest 5th percentile of 2.06 and highest 95th percentile of 3.06). The analysis of the cross-sensitivity to scattering, for the two filter tapes considered here, revealed a large increase in the C factor when the single-scattering albedo (SSA) of the collected particles was above a given threshold, up to a 3-fold increase above the average C values. The SSA threshold appeared to be site dependent and ranged between 0.90 to 0.95 for the stations considered in the study. The results of the cross-sensitivity to scattering displayed a fitted constant multiple-scattering parameter, Cf , of 2.21 and 1.96, and a cross-sensitivity factor, ms , of 1.8 % and 3.4 % for the MSY and MSA stations, respectively, for the TFE-coated glass filter tape. For the M8060 filter tape, Cf values of 2.50, 1.96 and 1.82 and ms values of 1.6 %, 3.0 % and 4.9 % for the BCN, MSY and MSA stations, respectively, were obtained. SSA variations also influenced the spectral dependence of C , which showed an increase with wavelength when SSA was above the site-dependent threshold. Below the SSA threshold, no statistically significant dependence of C on the wavelength was observed. For the measurement stations considered here, the wavelength dependence of C was to some extent driven by the presence of dust particles during Saharan dust outbreaks that had the potential to increase the SSA above the average values. At the mountaintop station, an omission of the wavelength dependence of the C factor led to an underestimation of the absorption Ångström exponent (AAE) by up to 12 %. Differences in the absorption coefficient determined from AE33 measurements at BCN, MSY and MSA of around 35 %–40 % can be expected when using the site-dependent experimentally obtained C value instead of the nominal C value. Due to the fundamental role that the SSA of the particles collected on the filter tape has in the multiple-scattering parameter C , we present a methodology that allows the recognition of the conditions upon which the use of a constant and wavelength-independent C is feasible. [ABSTRACT FROM AUTHOR]

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 %). [ABSTRACT FROM AUTHOR]

In this paper, a new methodology coupling aerosol optical and chemical parameters in the same source apportionment study is reported. In addition to results on source contributions, this approach provides information such as estimates for the atmospheric absorption Ångström exponent (α) of the sources and mass absorption cross sections (MACs) for fossil fuel emissions at different wavelengths. A multi-time resolution source apportionment study using the Multilinear Engine (ME-2) was performed on a PM 10 dataset with different time resolutions (24, 12, and 1 h) collected during two different seasons in Milan (Italy) in 2016. Samples were optically analysed by an in-house polar photometer to retrieve the aerosol absorption coefficient bap (in Mm -1) at four wavelengths (λ=405 , 532, 635, and 780 nm) and were chemically characterized for elements, ions, levoglucosan, and carbonaceous components. The dataset joining chemically speciated and optical data was the input for the multi-time resolution receptor model; this approach was proven to strengthen the identification of sources, thus being particularly useful when important chemical markers (e.g. levoglucosan, elemental carbon) are not available. The final solution consisted of eight factors (nitrate, sulfate, resuspended dust, biomass burning, construction works, traffic, industry, aged sea salt); the implemented constraints led to a better physical description of factors and the bootstrap analysis supported the goodness of the solution. As for bap apportionment, consistent with what was expected, biomass burning and traffic were the main contributors to aerosol absorption in the atmosphere. A relevant feature of the approach proposed in this work is the possibility of retrieving a lot of other information about optical parameters; for example, in contrast to the more traditional approach used by optical source apportionment models, here we obtained source-dependent α values without any a priori assumption (α biomass burning =1.83 and α fossil fuels =0.80). In addition, the MACs estimated for fossil fuel emissions were consistent with literature values. It is worth noting that the approach presented here can also be applied using more common receptor models (e.g. EPA PMF instead of multi-time resolution ME-2) if the dataset comprises variables with the same time resolution as well as optical data retrieved by widespread instrumentation (e.g. an Aethalometer instead of in-house instrumentation). [ABSTRACT FROM AUTHOR]

In this paper, a polar photometer (PP_UniMI) was set up to measure the aerosol absorption coefficient (σ ap ) at four wavelengths (λ) on 1-h resolved aerosol samples collected using a streaker sampler. Due to the characteristics of such samples (small deposit area, low aerosol load, and limited substrate thickness − 10 μm), the main technical developments aimed at reaching suitable limits of detection (LODs). To this aim, multiple scattering between the sample and a suitable substrate were exploited to amplify the system sensitivity to absorbing particle load. In the paper, the development and test of this innovative approach is presented. LODs for σ ap in the range 5.0–11.6 Mm −1 were reached, depending on the wavelength. Such values were suitable for the analysis of 1-hour resolved samples collected at an urban background site in Milan (Italy) during a test campaign of 1-week carried out in winter 2015. The methodology was validated comparing σ ap measurements performed by PP_UniMI at λ=635 nm on the streaker sample to the data obtained by a Multi-Angle Absorption Photometer (MAAP) operated in parallel. Agreement within 10% was found. To check the results obtained at other wavelengths, Ångström Absorption Exponent (AAE) was calculated from σ ap measurements at 4-λ. The AAE values resulted in the range of expectations for aerosol emitted by fossil fuel combustion (0.8–1.2) and wood burning (0.9–3.5), which are the main sources contributing to absorbing aerosol in urban areas in winter. The analytical methodology can be extended to samples collected with high time resolution using other high-time resolution samplers (e.g. drum rotating impactors). This is – as far as we know – the first time that σ ap measurements are performed on streaker samples collected with 1-h resolution. Our results thus set PP_UniMI as an important tool for the community performing high time resolved sampling to widen the characterisation of such samples and to further develop source apportionment studies. [ABSTRACT FROM AUTHOR]

In this study, the applicability of a benchtop polar photometer (PP_UniMI) to retrieve multi-wavelength aerosol absorption coefficient data by off-line measurements of the Multi-Angle Absorption Photometer (MAAP) sample spots is presented. MAAP is a widespread single wavelength online instrument providing the aerosol absorption coefficient and the equivalent black carbon concentration. In this work, MAAP samples collected during four different campaigns were analysed off-line with PP_UniMI. First of all, data from PP_UniMI and MAAP were compared to investigate contributions to measurement uncertainties. In particular, the role of the following assumptions performed in the MAAP was investigated: 1) reconstructing angular distribution of light scattered by filter samples from measurements at three fixed angles using analytical functions; 2) setting the fraction of the back-scattered radiation by the blank filter (B M) at a fixed value B M = 0.7; 3) assuming a fixed value for the asymmetry factor g = 0.75. Samples collected at several sites showed an agreement within 5% when data from the two instruments were retrieved using the same approximations (i.e. backscattered radiation from the filter matrix B M set at a fixed value, phase functions reconstructed by analytical functions from measurements at 3 angles, same asymmetry factor) in the data retrieval algorithm. Conversely, larger differences (14% on average) between off-line measurements and averaged MAAP data were obtained when the high-angular resolved information available by PP_UniMI was exploited. By analysing the role of MAAP assumptions for σ ap retrieval, it resulted that fixing B M = 0.7 was the main responsible for the detected differences. Indeed, high-angular resolved off-line measurements by PP_UniMI allow to directly measure B M , obtaining B M = 0.88 on white spots. It is noteworthy that the observed results were similar at all investigated sites, so they proved to be independent of the aerosol type and can likely be attributed to instrumental effects. Moreover, a sensitivity test was carried out also to check the impact of the fixed value used for the asymmetry factor (set at g = 0.75 in both instruments). Varying g values within the typical range for ambient aerosol (0.50–0.75) the estimate of aerosol absorbance ABS (directly obtained from PP_UniMI measurements and linked to σ ap) was affected by 8% at most, thus being a minor source of uncertainty in the calculation. The effect of the variability in blank spots used for off-line analyses was also evaluated and resulted in a contribution smaller than 3% to the uncertainty of the methodology employed. Finally, the possibility of exploiting multi-wavelength assessment of absorption coefficients is an added value of PP_UniMI; indeed, it allows to estimate the contribution of different aerosol sources and components to the absorption coefficient using MAAP tapes used in present or past campaigns. Image 1 • MAAP sample spots were analysed off-line by a benchtop multi-λ polar photometer. • The effect of different assumptions in MAAP radiative transfer scheme was tested. • A fixed blank spot backscattered fraction can cause 12% σ ap overestimation. • The other hypotheses had smaller impacts (less than 8%). [ABSTRACT FROM AUTHOR]