Exploiting multi-wavelength aerosol absorption coefficients in a multi-time resolution source apportionment study to retrieve source-dependent absorption parameters

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 Angstrom exponent (alpha) 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 PM10 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 b(ap) (in Mm 1) at four wavelengths (lambda = 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 b(ap) 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 alpha values without any a priori assumption (alpha biomass burning = 1:83 and alpha 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)

DEVELOPMENT AND OPTIMISATION OF EXPERIMENTAL AND MODELLING APPROACHES TO CHARACTERISE HIGH-TIME RESOLUTION ATMOSPHERIC AEROSOL AND ITS SOURCES

Atmospheric aerosol impacts on local, regional, and global scale causing adverse effects on human health, affecting visibility, and influencing the climate. For this reason, the scientific community is strongly interested in the physical-chemical characterisation of aerosol and its emission sources. Thanks to technological improvements in this field, high time resolution measurements and analyses have become increasingly important since processes involved in aerosol emission, transformation and removal in the atmosphere take place on short time scales (in the order of one hour). The research presented in this PhD thesis mainly focuses on the implementation of modelling and experimental approaches in order to expand the knowledge about properties of atmospheric aerosol and its sources with high time resolution. Main PhD activities are shortly summarised in the following: A source apportionment study was performed on a dataset with different time resolutions (24, 12, and 1 hour) collected in Milan (Italy) in 2016. This advanced multi-time resolution approach \u2013 implemented through the Multilinear Engine algorithm \u2013 is still scarcely available in the literature, although it allows to get rid of the limited chemical characterisation typical of high-time resolution data and the poor temporal details of low-time resolution samples. In addition, as an original contribution, in this source apportionment study chemical variables were joined to the aerosol absorption coefficient measured at different wavelengths as input to the model. This original approach was proved effective in order to (1) strengthen source identification; (2) retrieve source-dependent optical absorption parameters, i.e. source-specific absorption Angstrom exponents and mass absorption cross sections at different wavelengths, as results of the model. It is noteworthy that, at the state of the art, in source apportionment models based on optical absorption data (e.g. Aethalometer model) values for the absorption Angstrom exponents are fixed a priori by the modeller, thus carrying a large part of uncertainties in the model results. In the frame of the international collaborative project CARE (Carbonaceous Aerosol in Rome and Environs), a high time resolution (one and two hours) dataset collected in Rome (Italy) in 2017 was used as input in an advanced receptor model. Different measurement techniques provided the optical (absorption and scattering coefficients) and chemical characterisation (elements, elemental and organic carbon, non- refractory components such as organic aerosol, nitrate, sulphate, ammonium) of atmospheric aerosol. In particular, an ACSM (Aerosol Chemical Speciation Monitor) detected the organic aerosol (OA) fraction. Results from the source apportionment analysis of this high time resolution dataset were a posteriori compared to ACSM separation of the organic fraction in terms of HOA (hydrocarbon-like organic aerosol), BBOA (biomass burning-like organic aerosol), and OOA (oxygenated organic aerosol) provided in a previous literature work. In this study, the original contribution consisted in analysing the whole dataset with a multi-time resolution and a multi-variable approach, by the application of the Multilinear Engine algorithm. This approach based on receptor modelling resulted to be effective in relating primary and secondary OA contributions to their emission sources, highlighting the possibility to obtain a source-dependent separation of the OOA fraction, which is typically associated in the literature to not-well specified secondary processes. This is of particular interest for the receptor modelling community, since the assessment of the origin of secondary compounds is one of the main limitations of this type of models. Additionally, since in this study also the optical absorption coefficient retrieved at 7 wavelengths by an Aethalometer was used as input to the model, the methodology previously proposed was further tested on a different site impacted by different sources. It allowed e.g. to retrieve optical absorption contribution from mineral dust, besides the typical fossil fuel and biomass burning contributions retrieved by more widespread models based on optical absorption data such as the Aethalometer model. Contribution to the INFN (National Institute of Nuclear Physics) experiment TRACCIA (Time Resolved Aerosol Characterization Challenging Improvements and Ambitions), devoted to the realisation of the new high time resolution sampler STRAS (Size and Time Resolved Aerosol Sampler), in collaboration with other Italian research groups (INFN-Florence, INFN-Genoa, INFN-Lecce). The contribution of this PhD activity was in the sampler design phase (e.g. sizing of the sampler characteristics to obtain the proper cut-off diameter), and in the preliminary testing phase to verify the collection efficiency of the sampler. Preliminary tests were performed both on field and in the atmospheric simulation chamber ChAMBRe (Chamber for Aerosol Modelling and Bio-aerosol Research, partner of the H2020 EUROCHAMP2020 project and member of the Joint Research Unit ACTRIS-IT), where particles with certified dimensions were injected to study STRAS experimental cut-off diameter

Innovative Instrumentation for the Study of Atmospheric Aerosol Optical Properties

Aerosol optical properties (i.e. scattering and absorption) are of great im-portance to assess aerosol effects e.g. on visibility and Earth radiation bal-ance. In this paper, we present innovative optical instrumentation developed at the Department of Physics of the University of Milan: a multi-wavelength polar photometer (PP_UniMI) and a Single Particle Extinction and Scatter-ing (SPES). PP_UniMI is a filter-based device providing the aerosol absorp-tion coefficient of aerosol at 4 wavelengths (\uf06c). Such measurements are of interest to have insights into the \uf06c-dependent behavior of aerosol absorption properties, which is still poorly understood especially for what concerns weakly absorbing aerosol components. SPES allows to determine the size and refractive index of single particles. In case of absorbing particles, also in-formation on the imaginary part of the refractive index \u2013 very important es-pecially in the field of global models \u2013 can be provided with little assump-tions. We describe the main features of the two instruments and their ad-vantages and limitations. Examples of application are also presented

Applicability of benchtop multi-wavelength polar photometers to off-line measurements of the Multi-Angle Absorption Photometer (MAAP) samples

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 (BM) at a fixed value BM = 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 BM 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 \u3c3ap retrieval, it resulted that fixing BM = 0.7 was the main responsible for the detected differences. Indeed, high-angular resolved off-line measurements by PP_UniMI allow to directly measure BM, obtaining BM = 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\u20130.75) the estimate of aerosol absorbance ABS (directly obtained from PP_UniMI measurements and linked to \u3c3ap) 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

Classifying aerosol particles through the combination of optical and physical-chemical properties: Results from a wintertime campaign in Rome (Italy)

The \u201cCarbonaceous Aerosol in Rome and Environs\u201d (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 \u2013 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 ranges of values for optical variables were produced; therefore, these pieces of information can be used at the same site or at locations with similar features to quickly identify the occurrence of aerosol episodes. Graphical frameworks (both from the literature and newly designed) are also proposed; for each scheme features, advantages, and limitations are discussed

Gaining knowledge on source contribution to aerosol optical absorption properties and organics by receptor modelling

In this source apportionment study, an original approach based on receptor modelling was tested to relate primary and secondary organic aerosol (OA) contributions - estimated from ACSM (Aerosol Chemical Speciation Monitor) measurements - to their emission sources. Moreover, thanks to the coupling of optical and chemical variables as input to the receptor model, information such as the impact of mineral dust to the aerosol absorption in the atmosphere and estimates for the absorption \uc5ngstr\uf6m exponent (\u3b1) of the sources were retrieved. An advanced source apportionment study using the Multilinear Engine (ME-2) was performed on data collected during February 2017 in Rome (Italy), in the frame of the CARE (Carbonaceous Aerosol in Rome and Environs) experiment. A complete chemical characterisation (elements, non-refractory components, and carbonaceous components) was carried out, and the aerosol absorption coefficients bap(\u3bb) at 7 wavelengths (370, 470, 520, 590, 660, 880, and 950 nm) were retrieved by an Aethalometer AE33; all these variables (chemical + optical) were used as input to the receptor model. The final constrained solution consisted of nine factors which were assigned to major sources impacting on the investigated site (hereafter sources are referred to as: biomass burning, nitrate and aged aerosol, traffic exhaust, sulphate, mineral dust, marine aerosol, traffic non-exhaust, local source, and polluted marine aerosol), comprising both local urban sources and contributions from long-range transport. The bootstrap analysis supported the goodness of the solution. Total OA concentration from ACSM was apportioned by our receptor model and afterwards compared with HOA (hydrocarbon-like organic aerosol), BBOA (biomass burning-like organic aerosol), and OOA (oxygenated organic aerosol) concentrations obtained as results from an independent source apportionment study previously performed. As an original result of this work, insights on OA contributions were thus retrieved: (1) the contribution of organic aerosol assigned by ME-2 to the traffic exhaust source was fully comparable to HOA assessed by ACSM data analysis; (2) our source apportionment results gave the relevant indication that the OOA apportionment made on ACSM data likely includes a secondary OA contribution due to biomass burning. Other relevant results came from bap apportionment obtained by our multi-variable source apportionment approach: traffic exhaust was the main contributor to aerosol absorption in the atmosphere, but mineral dust contribution was also notable when a not negligible mineral dust transport episode was registered at the measurement site. In addition, source dependent optical absorption parameters (i.e. the absorption \uc5ngstr\uf6m exponent - \u3b1 - and the mass absorption cross section at different wavelengths) were retrieved without any a-priori assumption. In perspective, our modelling approach paves the way to more powerful source apportionment approaches which have the potential of providing much more insights on aerosol properties and sources