Local versus regional soil screening levels to identify potentially polluted areas

Boente, Carlos; Gerassis, Saki; Albuquerque, M.T.D.; Taboada, Javier; Gallego, J.R.

Publication

Local versus regional soil screening levels to identify potentially polluted areas

2019Journal article

dc.contributor.author	Boente, Carlos
dc.contributor.author	Gerassis, Saki
dc.contributor.author	Albuquerque, M.T.D.
dc.contributor.author	Taboada, Javier
dc.contributor.author	Gallego, J.R.
dc.date.accessioned	2019-04-08T09:59:58Z
dc.date.available	2020-03-31T00:30:23Z
dc.date.issued	2019
dc.description.abstract	Soil screening levels (SSLs) are reference threshold values required by environmental laws, established based on soil geochemical background data from often-extensive sampling areas. Such areas are often inappropriate for interpreting the true risk of pollution in small areas, since they overlook local factors (e.g., geology, industry, and traffic), which are unfeasible to encompass in large-scale samplings. To solve this issue, the calculation of local SSLs is proposed herein, performed on amajor scale closer to the area of interest. To exemplify this proposal, a soil sampling campaign was performed in the Municipality of Langreo, one of the most industrialized areas in the Principality of Asturias (northwestern Spain). Sampling allowed the measurement of local soil screening levels for several inorganic contaminants. Afterwards, a soil pollution index was calculated, referred to both regional and local thresholds, to assess the degree of contamination. Both pollution indicators were subjected to a methodology based on a Bayesian network analysis, followed by a stochastic sequential Gaussian simulation approach. The methodologies used showed differences in the identification of potentially polluted areas depending on the soil screening levels (regional or local) used. It was concluded that, in urban/industrial cores, local soil screening levels facilitate the identification of polluted areas and also reduce the uncertainty associated with sampling density and diffuse contamination. Thus, the use of local levels circumvents false-positive areas that would be classified as polluted were regional soil screening levels to be used.	pt_PT
dc.description.version	info:eu-repo/semantics/publishedVersion	pt_PT
dc.identifier.citation	BOENTE, C. [et al.] (2019) - Local versus regional soil screening levels to identify potentially polluted areas. Mathematical Geosciences. ISSN 1874-8953. https://doi.org/10.1007/s11004-019-09792-x	pt_PT
dc.identifier.doi	10.1007/s11004-019-09792-x	pt_PT
dc.identifier.issn	1874-8953
dc.identifier.uri	http://hdl.handle.net/10400.11/6446
dc.language.iso	eng	pt_PT
dc.peerreviewed	yes	pt_PT
dc.publisher	Springer	pt_PT
dc.relation.publisherversion	https://link.springer.com/article/10.1007%2Fs11004-019-09792-x	pt_PT
dc.rights.uri	http://creativecommons.org/licenses/by-nc/4.0/	pt_PT
dc.subject	Soil pollution	pt_PT
dc.subject	Potentially toxic elements	pt_PT
dc.subject	Soil screening levels	pt_PT
dc.subject	Geostatistics	pt_PT
dc.subject	Machine learning	pt_PT
dc.title	Local versus regional soil screening levels to identify potentially polluted areas	pt_PT
dc.type	journal article
dspace.entity.type	Publication
oaire.citation.title	Mathematical Geosciences	pt_PT
person.familyName	Albuquerque
person.givenName	Maria Teresa
person.identifier.ciencia-id	5A1C-8956-4C0A
person.identifier.orcid	0000-0002-8782-6133
person.identifier.rid	B-1536-2013
person.identifier.scopus-author-id	55507421600
rcaap.rights	embargoedAccess	pt_PT
rcaap.type	article	pt_PT
relation.isAuthorOfPublication	e2c2d171-e148-4c23-9cf8-0eb6d810c15e
relation.isAuthorOfPublication.latestForDiscovery	e2c2d171-e148-4c23-9cf8-0eb6d810c15e