Local versus regional soil screening levels to identify potentially polluted areas

Detalhes bibliográficos
Autor(a) principal: Boente, C.
Data de Publicação: 2019
Outros Autores: Gerassis, S., Albuquerque, M.T.D., Taboada, J., Gallego, J. R.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.11/6446
Resumo: 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.
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spelling Local versus regional soil screening levels to identify potentially polluted areasSoil pollutionPotentially toxic elementsSoil screening levelsGeostatisticsMachine learningSoil 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.SpringerRepositório Científico do Instituto Politécnico de Castelo BrancoBoente, C.Gerassis, S.Albuquerque, M.T.D.Taboada, J.Gallego, J. R.2020-03-31T00:30:23Z20192019-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.11/6446engBOENTE, 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-x1874-895310.1007/s11004-019-09792-xinfo:eu-repo/semantics/embargoedAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-03-25T01:47:17Zoai:repositorio.ipcb.pt:10400.11/6446Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T16:37:05.394227Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Local versus regional soil screening levels to identify potentially polluted areas
title Local versus regional soil screening levels to identify potentially polluted areas
spellingShingle Local versus regional soil screening levels to identify potentially polluted areas
Boente, C.
Soil pollution
Potentially toxic elements
Soil screening levels
Geostatistics
Machine learning
title_short Local versus regional soil screening levels to identify potentially polluted areas
title_full Local versus regional soil screening levels to identify potentially polluted areas
title_fullStr Local versus regional soil screening levels to identify potentially polluted areas
title_full_unstemmed Local versus regional soil screening levels to identify potentially polluted areas
title_sort Local versus regional soil screening levels to identify potentially polluted areas
author Boente, C.
author_facet Boente, C.
Gerassis, S.
Albuquerque, M.T.D.
Taboada, J.
Gallego, J. R.
author_role author
author2 Gerassis, S.
Albuquerque, M.T.D.
Taboada, J.
Gallego, J. R.
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Repositório Científico do Instituto Politécnico de Castelo Branco
dc.contributor.author.fl_str_mv Boente, C.
Gerassis, S.
Albuquerque, M.T.D.
Taboada, J.
Gallego, J. R.
dc.subject.por.fl_str_mv Soil pollution
Potentially toxic elements
Soil screening levels
Geostatistics
Machine learning
topic Soil pollution
Potentially toxic elements
Soil screening levels
Geostatistics
Machine learning
description 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.
publishDate 2019
dc.date.none.fl_str_mv 2019
2019-01-01T00:00:00Z
2020-03-31T00:30:23Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.11/6446
url http://hdl.handle.net/10400.11/6446
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 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
1874-8953
10.1007/s11004-019-09792-x
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dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
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