In this source apportionment study, an original approach based on receptor modelling was tested to relate primary and secondary organic aerosol (OA) contributions - estimated from ACSM (Aerosol Chemical Speciation Monitor) measurements - to their emission sources. Moreover, thanks to the coupling of optical and chemical variables as input to the receptor model, information such as the impact of mineral dust to the aerosol absorption in the atmosphere and estimates for the absorption Ångström exponent (α) of the sources were retrieved. An advanced source apportionment study using the Multilinear Engine (ME-2) was performed on data collected during February 2017 in Rome (Italy), in the frame of the CARE (Carbonaceous Aerosol in Rome and Environs) experiment. A complete chemical characterisation (elements, non-refractory components, and carbonaceous components) was carried out, and the aerosol absorption coefficients bap(λ) at 7 wavelengths (370, 470, 520, 590, 660, 880, and 950 nm) were retrieved by an Aethalometer AE33; all these variables (chemical + optical) were used as input to the receptor model. The final constrained solution consisted of nine factors which were assigned to major sources impacting on the investigated site (hereafter sources are referred to as: biomass burning, nitrate and aged aerosol, traffic exhaust, sulphate, mineral dust, marine aerosol, traffic non-exhaust, local source, and polluted marine aerosol), comprising both local urban sources and contributions from long-range transport. The bootstrap analysis supported the goodness of the solution. Total OA concentration from ACSM was apportioned by our receptor model and afterwards compared with HOA (hydrocarbon-like organic aerosol), BBOA (biomass burning-like organic aerosol), and OOA (oxygenated organic aerosol) concentrations obtained as results from an independent source apportionment study previously performed. As an original result of this work, insights on OA contributions were thus retrieved: (1) the contribution of organic aerosol assigned by ME-2 to the traffic exhaust source was fully comparable to HOA assessed by ACSM data analysis; (2) our source apportionment results gave the relevant indication that the OOA apportionment made on ACSM data likely includes a secondary OA contribution due to biomass burning. Other relevant results came from bap apportionment obtained by our multi-variable source apportionment approach: traffic exhaust was the main contributor to aerosol absorption in the atmosphere, but mineral dust contribution was also notable when a not negligible mineral dust transport episode was registered at the measurement site. In addition, source dependent optical absorption parameters (i.e. the absorption Ångström exponent - α - and the mass absorption cross section at different wavelengths) were retrieved without any a-priori assumption. In perspective, our modelling approach paves the way to more powerful source apportionment approaches which have the potential of providing much more insights on aerosol properties and sources.

Gaining knowledge on source contribution to aerosol optical absorption properties and organics by receptor modelling

Gualtieri M.;Petralia E.;
2020

Abstract

In this source apportionment study, an original approach based on receptor modelling was tested to relate primary and secondary organic aerosol (OA) contributions - estimated from ACSM (Aerosol Chemical Speciation Monitor) measurements - to their emission sources. Moreover, thanks to the coupling of optical and chemical variables as input to the receptor model, information such as the impact of mineral dust to the aerosol absorption in the atmosphere and estimates for the absorption Ångström exponent (α) of the sources were retrieved. An advanced source apportionment study using the Multilinear Engine (ME-2) was performed on data collected during February 2017 in Rome (Italy), in the frame of the CARE (Carbonaceous Aerosol in Rome and Environs) experiment. A complete chemical characterisation (elements, non-refractory components, and carbonaceous components) was carried out, and the aerosol absorption coefficients bap(λ) at 7 wavelengths (370, 470, 520, 590, 660, 880, and 950 nm) were retrieved by an Aethalometer AE33; all these variables (chemical + optical) were used as input to the receptor model. The final constrained solution consisted of nine factors which were assigned to major sources impacting on the investigated site (hereafter sources are referred to as: biomass burning, nitrate and aged aerosol, traffic exhaust, sulphate, mineral dust, marine aerosol, traffic non-exhaust, local source, and polluted marine aerosol), comprising both local urban sources and contributions from long-range transport. The bootstrap analysis supported the goodness of the solution. Total OA concentration from ACSM was apportioned by our receptor model and afterwards compared with HOA (hydrocarbon-like organic aerosol), BBOA (biomass burning-like organic aerosol), and OOA (oxygenated organic aerosol) concentrations obtained as results from an independent source apportionment study previously performed. As an original result of this work, insights on OA contributions were thus retrieved: (1) the contribution of organic aerosol assigned by ME-2 to the traffic exhaust source was fully comparable to HOA assessed by ACSM data analysis; (2) our source apportionment results gave the relevant indication that the OOA apportionment made on ACSM data likely includes a secondary OA contribution due to biomass burning. Other relevant results came from bap apportionment obtained by our multi-variable source apportionment approach: traffic exhaust was the main contributor to aerosol absorption in the atmosphere, but mineral dust contribution was also notable when a not negligible mineral dust transport episode was registered at the measurement site. In addition, source dependent optical absorption parameters (i.e. the absorption Ångström exponent - α - and the mass absorption cross section at different wavelengths) were retrieved without any a-priori assumption. In perspective, our modelling approach paves the way to more powerful source apportionment approaches which have the potential of providing much more insights on aerosol properties and sources.
Advanced receptor modelling
High time resolution
Optical properties
Organic components
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.12079/55481
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 6
social impact