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 – implemented through the Multilinear Engine algorithm – 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.