Abstract. 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 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 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).
Natural climate solutions for Canada
