Development of Europe-Wide Models for Particle Elemental Composition Using Supervised Linear Regression and Random Forest.
Chen J, de Hoogh K, Gulliver J, Hoffmann B, Hertel O, Ketzel M, Weinmayr G, Bauwelinck M, van Donkelaar A, Hvidtfeldt UA, Atkinson R, Janssen NAH, Martin RV, Samoli E, Andersen ZJ, Oftedal BM, Stafoggia M, Bellander T, Strak M, Wolf K, Vienneau D, Brunekreef B, Hoek G.
Chen J, et al. Among authors: martin rv.
Environ Sci Technol. 2020 Dec 15;54(24):15698-15709. doi: 10.1021/acs.est.0c06595. Epub 2020 Nov 25.
Environ Sci Technol. 2020.
PMID: 33237771
Free PMC article.
Models differed substantially between elements regarding major predictor variables, broadly reflecting known sources. Agreement between the two algorithm predictions was generally high at the overall European level and varied substantially at the national level. ...
Models differed substantially between elements regarding major predictor variables, broadly reflecting known sources. Agreement betwe …