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

Bernardoni, V.; Pileci, Rosaria E.; Caponi, Lorenzo; Massabò, Dario

doi:10.3390/atmos8110218

Cited by 35 publications

(33 citation statements)

References 69 publications

(96 reference statements)

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“…The aerosol absorption coefficient (b ap ) at the four wavelengths λ = 405, 532, 635, and 780 nm was measured on both low and high time resolution samples with the in-house polar photometer PP_UniMI (Vecchi et al, 2014;Bernardoni et al, 2017c).…”

Section: Aerosol Light-absorption Coefficient Measurementsmentioning

confidence: 99%

“…Uncertainties on b ap were quantified in 15 % and MDL was in the range 1-10 Mm −1 depending on sampling duration and wavelength as already reported in and Bernardoni et al (2017c). The pre-treatment procedure for experimental uncertainties and MDLs was the same used for chemical variables in order to create suitable input matrices required by the multi-time resolution model (see also Sect.…”

Section: Aerosol Light-absorption Coefficient Measurementsmentioning

confidence: 99%

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

Forello

Bernardoni

Calzolai³

et al. 2019

Atmos. Chem. Phys.

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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).

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Section: Aerosol Light-absorption Coefficient Measurementsmentioning

confidence: 99%

Section: Aerosol Light-absorption Coefficient Measurementsmentioning

confidence: 99%

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

Forello

Bernardoni

Calzolai³

et al. 2019

Atmos. Chem. Phys.

Self Cite

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“…Thus, in order to improve the forcing effect knowledge of aerosols on climate change, it is very important to study aerosol's optical properties (e.g., extinction and absorption coefficients, single scattering albedo, and asymmetry parameter) and their temporal and spatial variability. On the other hand, the wavelength dependency of scattering and absorption of radiation by aerosols has been recognized as a powerful tool to distinguish aerosol types [8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Characterization of In Situ Aerosol Optical Properties at Three Observatories in the Central Mediterranean

et al. 2018

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In this work, results of scattering and backscattering coefficients, scattering Ångström exponent (SAE), single scattering albedo (SSA), and asymmetry parameter (g) of atmospheric aerosols are presented. All these parameters were measured during the month of April 2016 in Southern Italy on three different Global Atmosphere Watch observatories in the Central Mediterranean. This is the first time, to our knowledge, that optical aerosol properties were studied at the same time, even if in a brief intensive measurement campaign, at three sites in the South of Italy. In order to obtain a characteristic value for aerosol optical properties, different kinds of particle sources (i.e., dust, marine, and anthropic) have been identified and studied. In the measurement period, one event of a long-range transport of Saharan dust from Northern Africa was observed at all observatories. During the Saharan dust transport event, a minimum value of the SAE (0.69 ± 0.34) and a relatively higher values of SSA were observed. During the dust event, g increased up to 0.69. Marine aerosol contribution and anthropic/urban aerosol intrusion were analysed. From this analysis, SAE average values were 0.70, 0.84, and 1.22, respectively, for dust, marine, and anthropic particles. On the other hand, the SSA minimum value was 0.86 for anthropic particles, and it increased for dust (0.88) and marine (0.93) aerosols. The asymmetry parameter had a limited variability for the three types of aerosol from 0.62 to 0.58, as reported also in literature.

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“…This is the approach presented by Bernardoni et al [40], who applied the recently proposed MWAA model (Multi Wavelength Absorption Analyzer) to provide a source (fossil fuel combustion vs. biomass burning) as well as a component (BC vs. BrC) apportionment of the aerosol absorption coefficient. In addition, the BrC Ångström absorption exponent (α BrC ) is a noteworthy output of the model.…”

Section: Advanced Measurement Methods and Optical Propertiesmentioning

confidence: 99%

Carbonaceous Aerosols in the Atmosphere

2018

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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

Cited by 35 publications

References 69 publications

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

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

Characterization of In Situ Aerosol Optical Properties at Three Observatories in the Central Mediterranean

Carbonaceous Aerosols in the Atmosphere

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