Size-segregated aerosol in a hot-spot pollution urban area: Chemical composition and three-way source apportionment

Bernardoni, V.; Elser, Miriam; Valli, G.; Valentini, S.; Bigi, Alessandro; Fermo, P.; Piazzalunga, A.; Vecchi, R.

doi:10.1016/j.envpol.2017.08.040

Cited by 29 publications

(35 citation statements)

References 51 publications

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“…Thus, the approach seems able to associate at least part of the secondary compounds rapidly formed in atmosphere to specific sources. This ability of receptor models has already been evidenced in other source apportionment studies based on chemical aerosol properties carried out in the area [44,63]. Multiple linear regression for OC source apportionment (Section 2.4.4) on Milan dataset resulted in k 1 = 0.33 ± 0.05, k 2 = 0.34 ± 0.07, and OC NC =1.1 ± 1.0, where uncertainties are the standard error of the regression.…”

Section: Results From the Milan Datasetmentioning

confidence: 52%

Section: Results From the Milan Datasetmentioning

confidence: 64%

“…Milan is situated in the Po Valley, which is one of the main hot-spot pollution areas in Europe. For this reason, different source apportionment studies by receptor models based on chemical characterization were carried out in the last decade on integrated aerosol size-fractions (e.g., [39][40][41][42]) and on suitably characterized [43] size-segregated samples [44]. These works evidenced that the site is impacted by a complex mixture of sources; traffic (both exhaust and non-exhaust), wood burning, re-suspended dust, and industry were identified as the main primary sources, but secondary compounds play a key role in explaining the total measured mass.…”

Section: Sites and Samplingmentioning

confidence: 99%

“…These works evidenced that the site is impacted by a complex mixture of sources; traffic (both exhaust and non-exhaust), wood burning, re-suspended dust, and industry were identified as the main primary sources, but secondary compounds play a key role in explaining the total measured mass. The influence of particle aging processes and the impact of both local and regional contributions were identified in the size-segregated study [44]. PM10 samples were collected on pre-fired quartz fiber filters (same filter type and treatment as in Propata) using an EPA inlet operating at 1 m 3 /h.…”

Section: Sites and Samplingmentioning

confidence: 99%

“…Massabò et al [20] proposed to determine k 1 on samples where little wood burning impact was expected, so that Equation (7) Real-world profiles have already been proven to have the potential to account for rapidly formed secondary compounds, thus limiting the problem of secondary OC apportionment only to secondary OC formed with great time-delay from precursor emissions (which can provide contribution to OC NC ) [44,63].…”

Section: Oc Source Apportionmentmentioning

confidence: 99%

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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

Bernardoni

Pileci

Caponi³

et al. 2017

Atmosphere

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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 b abs measured at different wavelengths, and to provide the BrC Ångström Absorption exponent (α BrC ). 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 α BrC and a better correlation of the BrC absorption coefficient (b abs BrC ) 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 α BrC 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 b abs (BC) apportionment and EC measurements allowed MAC determination, which gave analogous results at the two sites.

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Section: Results From the Milan Datasetmentioning

confidence: 52%

Section: Results From the Milan Datasetmentioning

confidence: 64%

Section: Sites and Samplingmentioning

confidence: 99%

Section: Sites and Samplingmentioning

confidence: 99%

Section: Oc Source Apportionmentmentioning

confidence: 99%

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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

Bernardoni

Pileci

Caponi³

et al. 2017

Atmosphere

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Characterisation of urban aerosol size distribution by radiocarbon and PIXE analyses in a middle-European urban environment for source identification: a pilot study

Angyal,

Szoboszlai,

Major

et al. 2024

Environ Sci Pollut Res

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This study, conducted in Debrecen, Hungary, aimed to analyse atmospheric particulate matter (APM or PM) through radiocarbon and PIXE analyses during the winter smog (23–25 January) and spring (15–18 May) seasons. The information presented in this pilot study aims to provide insight into the importance of utilising detailed characteristics of the mass size distributions of fossil carbon (ff) and contemporary carbon (fC) content. Additionally, it seeks to compare these characteristics with the size distributions of various elements to enable even more accurate PM source identification. In winter, APM concentrations were 86.27 μg/m3 (total), 17.07 μg/m3 (fC) and 10.4 μg/m3 (ff). In spring, these values changed to 29.5 μg/m3, 2.64 μg/m3 and 7.01 μg/m3, respectively. Notably, differences in mass size distribution patterns were observed between the two seasons, suggesting varied sources for contemporary carbon. Biomass burning emerged as a crucial source during the smog period, supported by similar MMAD (Mass Median Aerodynamic Diameter) values and a strong correlation (r = 0.95, p < 0.01) between potassium and fC. In spring, a significant change in the concentration and distribution of fC occurred, with a broad, coarse mode and a less prominent accumulation mode. Ff was found to have similar distributions as PM, with nearly the same MMADs, during both periods. Finally, a comprehensive comparison of modal characteristics identified specific sources for the various components, including biomass burning, vehicle exhaust, coal and oil combustion, vehicle non-exhaust, road dust, tyre abrasion, mineral dust and biogenic emission. This study showcases how using radiocarbon and PIXE analysis in size distribution data can enhance our understanding of the sources of PM and their effects on different size fractions of PM.

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Benthic macrofaunal dispersion within different mangrove habitats in Hara Biosphere Reserve, Persian Gulf

Vahidi

Fatemi

Danehkar

et al. 2019

Int. J. Environ. Sci. Technol.

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Size-segregated aerosol in a hot-spot pollution urban area: Chemical composition and three-way source apportionment

Cited by 29 publications

References 51 publications

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

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

Characterisation of urban aerosol size distribution by radiocarbon and PIXE analyses in a middle-European urban environment for source identification: a pilot study

Benthic macrofaunal dispersion within different mangrove habitats in Hara Biosphere Reserve, Persian Gulf

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