The performance and the uncertainty of receptor models (RMs) were assessed in intercomparison exercises employing real-world and synthetic input datasets. To that end, the results obtained by different practitioners using ten different RMs were compared with a reference. In order to explain the differences in the performances and uncertainties of the different approaches, the apportioned mass, the number of sources, the chemical profiles, the contribution-to-species and the time trends of the sources were all evaluated using the methodology described in Belis et al. (2015). In this study, 87% of the 344 source contribution estimates (SCEs) reported by participants in 47 different source apportionment model results met the 50% standard uncertainty quality objective established for the performance test. In addition, 68% of the SCE uncertainties reported in the results were coherent with the analytical uncertainties in the input data. The most used models, EPA-PMF v.3, PMF2 and EPA-CMB 8.2, presented quite satisfactory performances in the estimation of SCEs while unconstrained models, that do not account for the uncertainty in the input data (e.g. APCS and FA-MLRA), showed below average performance. Sources with well-defined chemical profiles and seasonal time trends, that make appreciable contributions (>10%), were those better quantified by the models while those with contributions to the PM mass close to 1% represented a challenge. The results of the assessment indicate that RMs are capable of estimating the contribution of the major pollution source categories over a given time window with a level of accuracy that is in line with the needs of air quality management.

Belis, C., Karagulian, F., Amato, F., Almeida, M., Artaxo, P., Beddows, D., et al. (2015). A new methodology to assess the performance and uncertainty of source apportionment models II: The results of two European intercomparison exercises. ATMOSPHERIC ENVIRONMENT, 123, 240-250 [10.1016/j.atmosenv.2015.10.068].

A new methodology to assess the performance and uncertainty of source apportionment models II: The results of two European intercomparison exercises

PERRONE, MARIA GRAZIA;
2015

Abstract

The performance and the uncertainty of receptor models (RMs) were assessed in intercomparison exercises employing real-world and synthetic input datasets. To that end, the results obtained by different practitioners using ten different RMs were compared with a reference. In order to explain the differences in the performances and uncertainties of the different approaches, the apportioned mass, the number of sources, the chemical profiles, the contribution-to-species and the time trends of the sources were all evaluated using the methodology described in Belis et al. (2015). In this study, 87% of the 344 source contribution estimates (SCEs) reported by participants in 47 different source apportionment model results met the 50% standard uncertainty quality objective established for the performance test. In addition, 68% of the SCE uncertainties reported in the results were coherent with the analytical uncertainties in the input data. The most used models, EPA-PMF v.3, PMF2 and EPA-CMB 8.2, presented quite satisfactory performances in the estimation of SCEs while unconstrained models, that do not account for the uncertainty in the input data (e.g. APCS and FA-MLRA), showed below average performance. Sources with well-defined chemical profiles and seasonal time trends, that make appreciable contributions (>10%), were those better quantified by the models while those with contributions to the PM mass close to 1% represented a challenge. The results of the assessment indicate that RMs are capable of estimating the contribution of the major pollution source categories over a given time window with a level of accuracy that is in line with the needs of air quality management.
Articolo in rivista - Articolo scientifico
Intercomparison exercise; Model performance indicators; Model uncertainty; Particulate matter; Receptor models; Source apportionment;
Intercomparison exercise; Model performance indicators; Model uncertainty; Particulate matter; Receptor models; Source apportionment
English
240
250
11
Belis, C., Karagulian, F., Amato, F., Almeida, M., Artaxo, P., Beddows, D., et al. (2015). A new methodology to assess the performance and uncertainty of source apportionment models II: The results of two European intercomparison exercises. ATMOSPHERIC ENVIRONMENT, 123, 240-250 [10.1016/j.atmosenv.2015.10.068].
Belis, C; Karagulian, F; Amato, F; Almeida, M; Artaxo, P; Beddows, D; Bernardoni, V; Bove, M; Carbone, S; Cesari, D; Contini, D; Cuccia, E; Diapouli, E; Eleftheriadis, K; Favez, O; El Haddad, I; Harrison, R; Hellebust, S; Hovorka, J; Jang, E; Jorquera, H; Kammermeier, T; Karl, M; Lucarelli, F; Mooibroek, D; Nava, S; Nøjgaard, J; Paatero, P; Pandolfi, M; Perrone, M; Petit, J; Pietrodangelo, A; Pokorná, P; Prati, P; Prevot, A; Quass, U; Querol, X; Saraga, D; Sciare, J; Sfetsos, A; Valli, G; Vecchi, R; Vestenius, M; Yubero, E; Hopke, P
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/134823
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