Light absorption by the ensemble of atmospheric particles is estimated through the aerosol absorption coefficient bap. Among aerosol components, the fraction of carbonaceous aerosol known as black carbon (BC) is considered the main responsible for light absorption in the atmosphere. One peculiar feature of BC is a wavelength-independent imaginary part of the refractive index over the visible and near-visible regions. Recently, literature studies focused on brown carbon (BrC), light-absorbing organic matter with increasing absorption towards lower wavelengths, especially in the UV region. In this work, a multi-wavelength measurement of bap (at λ=405 nm, 532 nm, 635 nm and 780 nm) on filter samples collected in Milan (Italy) in 2016 at different time resolutions (1 hour, 12 hours and 24 hours) was performed by our home-made polar photometer PP_UniMI[1,2,3]. This piece of information, together with the chemical speciation of the samples themselves, was exploited as input data in an advanced receptor model that is the multi-time model[4,5,6]. This modelling approach allows to use each experimental data in its original time schedule, avoiding the need to average high time resolution data over the longest sampling interval. Nevertheless, source apportionment studies carried out by multi-time model are still scarce in the literature and none of them has investigated the feasibility of introducing aerosol optical absorption properties yet. Information about the Ångström Absorption Exponent (α) of BC and BrC emission sources and an estimate of the Mass Absorption Coefficient (MAC) of BC were retrieved as model outputs and they were found to be compatible with literature values. Knowledge of the atmospheric value of the Ångström Absorption Exponent of sources is particularly important, since existing source apportionment optical models (i.e. the widespread Aethalometer modeland the more recent Multi-Wavelength Absorption Analyzer - MWAA - model[8,9]) need a priori assumption on this parameter. Moreover, coupling optical and chemical information strengthened the identification of BC and BrC emission sources such as traffic and biomass burning; this can be particularly useful in receptor modelling when important chemical tracers (e.g. EC, levoglucosan) are not available.
|Titolo:||Retrieving information on black and brown carbon emission sources exploiting aerosol optical properties in an advanced receptor model|
|Data di pubblicazione:||2019|
|Appare nelle tipologie:||04.03 - Poster|