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Repositorio de la Universidad de Oviedo. > Producción Bibliográfica de UniOvi: RECOPILA > Artículos >

Please use this identifier to cite or link to this item: http://hdl.handle.net/10651/51804

Title: A coupled multivariate statistics, geostatistical and machine-learning approach to address soil pollution in a prototypical Hg-mining site in a natural reserve
Author(s): Boente López, Carlos
Albuquerque, M. T. D.
Gerassis, S.
Rodríguez-Valdés, E.
Rodríguez Gallego, José Luis
Issue date: 2019
Publisher version: http://dx.doi.org/10.1016/j.chemosphere.2018.11.172
Citation: Chemosphere, 218, p. 767-777 (2019); doi:10.1016/j.chemosphere.2018.11.172
Format extent: p. 767-777
URI: http://hdl.handle.net/10651/51804
ISSN: 0045-6535
Sponsored: Carlos Boente obtained a grant from the“Formación del Profesorado Universitario” program,financed by the “Ministerio de Educación, Cultura y Deporte de España”. The authors thank the Principality of Asturias for co-financing this research, the “Servicio Científico-Técnico de Ensayos Medioambientales” of the University of Oviedo, and also Alvaro Dapía, Nora Matanzas, Diego Baragaño and Nerea García for their support during the sampling works
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