Evaluation of receptor and chemical transport models for PM10 source apportionment | Istituto di Scienze __br_

Author	C.A. Belis D. Pernigotti G. Pirovano O. Favez J.L. Jaffrezo J. Kuenen Denier Van Der Gon M. Reizer V. Riffault L.Y. Alleman M. Almeida F. Amato A. Angyal G. Argyropoulos S. Bande I. Beslic J.-L. Besombes M.C. Bove P. Brotto G. Calori D. Cesari C. Colombi D. Contini G. De Gennaro A. Di Gilio E. Diapouli El Haddad H. Elbern K. Eleftheriadis J. Ferreira M.G. Vivanco S. Gilardoni B. Golly S. Hellebust P.K. Hopke Y. Izadmanesh H. Jorquera K. Krajsek R. Kranenburg P. Lazzeri F. Lenartz F. Lucarelli K. Maciejewska A. Manders M. Manousakas M. Masiol M. Mircea D. Mooibroek S. Nava D. Oliveira M. Paglione M. Pandolfi M. Perrone E. Petralia A. Pietrodangelo S. Pillon P. Pokorná P. Prati D. Salameh C. Samara L. Samek D. Saraga S. Sauvage M. Schaap F. Scotto K. Sega G. Siour R. Tauler G. Valli R. Vecchi E. Venturini M. Vestenius A. Waked E. Yubero
Keywords	Air quality dust Emission control Lenses Mean square error Soil testing Time series Chemical transport models Intercomparisons PM10 Receptor model Source apportionment Quality control Air quality Atmospheric modeling industrial emission Particulate Matter Source apportionment Air quality article Europe performance Soil time series analysis uncertainty Europe United States
Year of Publication	2020
Journal	Atmospheric Environment: X
URL	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074932830&doi=10.1016%2fj.aeaoa.2019.100053&partnerID=40&md5=b2dc1bd3c4f6ec289b57bea36f41fd8c
DOI	10.1016/j.aeaoa.2019.100053
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