Belis, C. A., Pernigotti, D., Pirovano, G., Favez, O., Jaffrezo, J. L., Kuenen, J., van Der Gon, H. Denier, Reizer, M., Riffault, V, Alleman, L. Y., Almeida, M., Amato, F., Angyal, A., Argyropoulos, G., Bande, S., Beslic, I, Besombes, J-L, Bove, M. C., Brotto, P., Calori, G., Cesari, D., Colombi, C., Contini, D., De Gennaro, G., Di Gilio, A., Diapouli, E., El Haddad, I, Elbern, H., Eleftheriadis, K., Ferreira, J., Vivanco, M. Garcia, Gilardoni, S., Golly, B., Hellebust, S., Hopke, P. K., Izadmanesh, Y., Jorquera, H., Krajsek, K., Kranenburg, R., Lazzeri, P., Lenartz, F., Lucarelli, F., Maciejewska, K., Manders, A., Manousakas, M., Masiol, M., Mircea, M., Mooibroek, D., Nava, S., Oliveira, D., Paglione, M., Pandolfi, M., Perrone, M., Petralia, E., Pietrodangelo, A., Pillon, S., Pokorna, P., Prati, P., Salameh, D., Samara, C., Samek, L., Saraga, D., Sauvage, S., Schaap, M., Scotto, F., Sega, K., Siour, G., Tauler, R., Valli, G., Vecchi, R., Venturini, E., Vestenius, M., Waked, A. and Yubero, E. (2020). Evaluation of receptor and chemical transport models for PM10 source apportionment. Atmos. Environ-X, 5. OXFORD: ELSEVIER SCI LTD. ISSN 2590-1621

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Abstract

In this study, the performance of two types of source apportionment models was evaluated by assessing the results provided by 40 different groups in the framework of an intercomparison organised by FAIRMODE WG3 (Forum for air quality modelling in Europe, Working Group 3). The evaluation was based on two performance indicators: z-scores and the root mean square error weighted by the reference uncertainty (RMSEu), with pre-established acceptability criteria. By involving models based on completely different and independent input data, such as receptor models (RMs) and chemical transport models (CTMs), the intercomparison provided a unique opportunity for their cross-validation. In addition, comparing the CTM chemical profiles with those measured directly at the source contributed to corroborate the consistency of the tested model results. The most commonly used RM was the US EPA- PMF version 5. RMs showed very good performance for the overall dataset (91% of z-scores accepted) while more difficulties were observed with the source contribution time series (72% of RMSEu accepted). Industrial activities proved to be the most difficult sources to be quantified by RMs, with high variability in the estimated contributions. In the CTMs, the sum of computed source contributions was lower than the measured gravimetric PM10 mass concentrations. The performance tests pointed out the differences between the two CTM approaches used for source apportionment in this study: brute force (or emission reduction impact) and tagged species methods. The sources meeting the z-score and RMSEu acceptability criteria tests were 50% and 86%, respectively. The CTM source contributions to PM10 were in the majority of cases lower than the RM averages for the corresponding source. The CTMs and RMs source contributions for the overall dataset were more comparable (83% of the z-scores accepted) than their time series (successful RMSEu in the range 25% - 34%). The comparability between CTMs and RMs varied depending on the source: traffic/exhaust and industry were the source categories with the best results in the RMSEu tests while the most critical ones were soil dust and road dust. The differences between RMs and CTMs source reconstructions confirmed the importance of cross validating the results of these two families of models.

Item Type: Journal Article
Creators:
CreatorsEmailORCIDORCID Put Code
Belis, C. A.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Pernigotti, D.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Pirovano, G.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Favez, O.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Jaffrezo, J. L.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Kuenen, J.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
van Der Gon, H. DenierUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Reizer, M.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Riffault, VUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Alleman, L. Y.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Almeida, M.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Amato, F.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Angyal, A.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Argyropoulos, G.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Bande, S.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Beslic, IUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Besombes, J-LUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Bove, M. C.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Brotto, P.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Calori, G.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Cesari, D.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Colombi, C.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Contini, D.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
De Gennaro, G.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Di Gilio, A.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Diapouli, E.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
El Haddad, IUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Elbern, H.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Eleftheriadis, K.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Ferreira, J.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Vivanco, M. GarciaUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Gilardoni, S.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Golly, B.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Hellebust, S.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Hopke, P. K.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Izadmanesh, Y.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Jorquera, H.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Krajsek, K.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Kranenburg, R.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Lazzeri, P.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Lenartz, F.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Lucarelli, F.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Maciejewska, K.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Manders, A.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Manousakas, M.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Masiol, M.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Mircea, M.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Mooibroek, D.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Nava, S.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Oliveira, D.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Paglione, M.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Pandolfi, M.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Perrone, M.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Petralia, E.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Pietrodangelo, A.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Pillon, S.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Pokorna, P.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Prati, P.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Salameh, D.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Samara, C.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Samek, L.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Saraga, D.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Sauvage, S.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Schaap, M.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Scotto, F.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Sega, K.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Siour, G.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Tauler, R.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Valli, G.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Vecchi, R.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Venturini, E.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Vestenius, M.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Waked, A.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Yubero, E.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
URN: urn:nbn:de:hbz:38-350916
DOI: 10.1016/j.aeaoa.2019.100053
Journal or Publication Title: Atmos. Environ-X
Volume: 5
Date: 2020
Publisher: ELSEVIER SCI LTD
Place of Publication: OXFORD
ISSN: 2590-1621
Language: English
Faculty: Unspecified
Divisions: Unspecified
Subjects: no entry
Uncontrolled Keywords:
KeywordsLanguage
POSITIVE MATRIX FACTORIZATION; PARTICULATE MATTER; GOVERNING EQUATIONS; AIR-POLLUTANTS; PART I; PERFORMANCE; EUROPE; METHODOLOGY; UNCERTAINTY; RESOLUTIONMultiple languages
Environmental Sciences; Meteorology & Atmospheric SciencesMultiple languages
URI: http://kups.ub.uni-koeln.de/id/eprint/35091

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