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

Abstract

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).

Fossil fuel combustion, biomass burning and biogenic sources of fine carbonaceous aerosol in the Carpathian Basin

“…There are several methods to apportion the particulate matter (PM) mass or carbonaceous species among some or all of their major sources. They include (1) source-specific marker methods (Fraser and Lakshmanan, 2000;Szidat et al, 2006Szidat et al, , 2009Minguillón et al, 2011;Zhang et al, 2012;Bernardoni et al, 2013), (2) multiwavelength optical methods (Sandradewi et al, 2008a, b;Zotter et al, 2017) and (3) various multivariate statistical methods based on online or offline data (Hopke, 2016;Maenhaut et al, 2016). Recently, the third approach also takes advantage of dedicated molecular tracers or fragments from mass spectrometry or advanced optical techniques (Forello et al, 2019;Stefenelli et al, 2019).…”

“…The formation, modelling utilisation, atmospheric processes and analytical determinations of these two markers together with their ad-vantages and limitations were described, evaluated and discussed in detail previously (e.g. Simoneit et al, 1999Simoneit et al, , 2004Fraser and Lakshmanan, 2000;Nolte et al, 2001;Pashynska et al, 2002;Zdráhal et al, 2002;Puxbaum et al, 2007;Saarikoski et al, 2008;Caseiro et al, 2009;Fabbri et al, 2009;Szidat et al, 2006Szidat et al, , 2009Favez et al, 2010;Hennigan et al, 2010;Hoffmann et al, 2010;Kourtchev et al, 2011;Piazzalunga et al, 2011;Maenhaut et al, 2012Maenhaut et al, , 2016Yttri et al, 2015). The coupled radiocarbon-LVG marker method, introduced recently (Salma et al, 2017), is a combination of the two marker methods.…”

Fossil fuel combustion, biomass burning and biogenic sources of fine carbonaceous aerosol in the Carpathian Basin

“…There are several methods to apportion the particulate matter (PM) mass or carbonaceous species among some or all major source types. They include source-specific marker methods (Fraser et al, 2000;Szidat et al, 2006Szidat et al, , 2009Minguillón et al, 2011;Zhang et al, 2012;Bernardoni et al, 2013), multi-wavelength optical methods (Sandradewi et al, 2008a(Sandradewi et al, , 2008bZotter et al, 2017;Forello et al, 2019) and various multivariate statistical https://doi.org/10.5194/acp-2019-792 Preprint. Discussion started: 20 November 2019 c Author(s) 2019.…”

Optical source apportionment and radiative forcing of light-absorbing carbonaceous aerosol at a tropical marine monsoon climate zone: the importance of ship emissions

“…Thus, this source factor was allocated to motor vehicle emissions. The third source factor was dominated by high contributions of K + , OC, EC, and Abspri(λ), which was an obvious feature of biomass burning (Forello et al, 2019). The fourth source factor was characterized by large loadings of several crustal materials, such as Ca 2+ , Ti, Fe, and Mn, and, therefore, it was identified as mineral dust.…”

“…source apportionment. In contrast, Forello et al (2019) coupled chemical species with multi-wavelength absorption in ME2 to directly perform the optical source apportionment. Compared with indirect approach, the additional optical data in receptor model can improve the performance of source apportionment, because each source has its own optical features.…”