The multi-wavelength absorption analyzer model (MWAA model) was recently proposed to provide a source (fossil fuel combustion vs. wood burning) and a component (black carbon BC vs. brown carbon BrC) apportionment of babs measured at different wavelengths, and to provide the BrC Ångström Absorption exponent (αBrC). This paper shows MWAA model performances and issues when applied to samples impacted by different sources. To this aim, the MWAA model was run on samples collected at a rural (Propata) and an urban (Milan) site in Italy during the winter period. Lower uncertainties on αBrC and a better correlation of the BrC absorption coefficient (babsBrC) with levoglucosan (tracer for wood burning) were obtained in Propata (compared to Milan). Nevertheless, the correlation previously mentioned improved, especially in Milan, when providing a priori information on αBrC to MWAA. Possible reasons for this improvement could be the more complex mixture of sources present in Milan and the aging processes, which can affect aerosol composition, particle mixing, and size distribution. OC and EC source apportionment showed that wood burning was the dominating contributor to the carbonaceous fractions in Propata, whereas a more complex situation was detected in Milan. Simultaneous babs(BC) apportionment and EC measurements allowed MAC determination, which gave analogous results at the two sites.
The Multi-Wavelength Absorption Analyzer (MWAA) Model as a Tool for Source and Component Apportionment Based on Aerosol Absorption Properties: Application to Samples Collected in Different Environments
CAPONI, LORENZO;Massabò, Dario
2017-01-01
Abstract
The multi-wavelength absorption analyzer model (MWAA model) was recently proposed to provide a source (fossil fuel combustion vs. wood burning) and a component (black carbon BC vs. brown carbon BrC) apportionment of babs measured at different wavelengths, and to provide the BrC Ångström Absorption exponent (αBrC). This paper shows MWAA model performances and issues when applied to samples impacted by different sources. To this aim, the MWAA model was run on samples collected at a rural (Propata) and an urban (Milan) site in Italy during the winter period. Lower uncertainties on αBrC and a better correlation of the BrC absorption coefficient (babsBrC) with levoglucosan (tracer for wood burning) were obtained in Propata (compared to Milan). Nevertheless, the correlation previously mentioned improved, especially in Milan, when providing a priori information on αBrC to MWAA. Possible reasons for this improvement could be the more complex mixture of sources present in Milan and the aging processes, which can affect aerosol composition, particle mixing, and size distribution. OC and EC source apportionment showed that wood burning was the dominating contributor to the carbonaceous fractions in Propata, whereas a more complex situation was detected in Milan. Simultaneous babs(BC) apportionment and EC measurements allowed MAC determination, which gave analogous results at the two sites.
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