Combining raw and compositional data to determine the spatial patterns of Potentially Toxic Elements in soils

[EN] When considering complex scenarios involving several attributes, such as in environmental characterization, a clearer picture of reality can be achieved through the dimensional reduction of data. In this context, maps facilitate the visualization of spatial patterns of contaminant distribution...

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Autores: Boente López, Carlos, Albuquerque, M.T.D., Fernández Braña, Alfredo Javier, Gerassis Davite, Saki, Sierra Fernández, Carlos, Rodríguez Gallego, José Luis
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2018
País:España
Institución:Universidad de León
Repositorio:BULERIA. Repositorio Institucional de la Universidad de León
OAI Identifier:oai:buleria.unileon.es:10612/26163
Acceso en línea:https://hdl.handle.net/10612/26163
Access Level:acceso abierto
Palabra clave:Ecología. Medio ambiente
Soil pollution
Compositional data
Ordinary kriging
Local G-clustering
Relative enrichment
2511.06 Conservación de Suelos
2511.04 Química de Suelos
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spelling Combining raw and compositional data to determine the spatial patterns of Potentially Toxic Elements in soilsBoente López, CarlosAlbuquerque, M.T.D.Fernández Braña, Alfredo JavierGerassis Davite, SakiSierra Fernández, CarlosRodríguez Gallego, José LuisEcología. Medio ambienteSoil pollutionCompositional dataOrdinary krigingLocal G-clusteringRelative enrichment2511.06 Conservación de Suelos2511.04 Química de Suelos[EN] When considering complex scenarios involving several attributes, such as in environmental characterization, a clearer picture of reality can be achieved through the dimensional reduction of data. In this context, maps facilitate the visualization of spatial patterns of contaminant distribution and the identification of enriched areas. A set, of 15 Potentially Toxic Elements (PTEs) – (As, Ba, Cd, Co, Cr, Cu, Hg, Mo, Ni, Pb, Sb, Se, Tl, V, and Zn), was measured in soil, collected in Langreo's municipality (80 km2), Spain. Relative enrichment (RE) is introduced here to refer to the proportion of elements present in a given context. Indeed, a novel approach is provided for research into PTE fate. This method involves studying the variability of PTE proportions throughout the study area, thereby allowing the identification of dissemination trends. Traditional geostatistical approaches commonly use raw data (concentrations) accepting that the elements analyzed make up the entirety of the soil. However, in geochemical studies the analyzed elements are just a fraction of the total soil composition. Therefore, considering compositional data is pivotal. The spatial characterization of PTEs considering raw and compositional data together allowed a broad discussion about, not only the PTEs concentration's distribution but also to reckon possible trends of relative enrichment (RE). Transformations to open closed data are widely used for this purpose. Spatial patterns have an indubitable interest. In this study, the Centered Log-ratio transformation (clr) was used, followed by its back-transformation, to build a set of compositional data that, combined with raw data, allowed to establish the sources of the PTEs and trends of spatial dissemination. Based on the obtained findings it was possible to conclude that the Langreo area is deeply affected by its industrial and mining legacy. City center is highly enriched in Pb and Hg and As shows enrichment in a northwesterly direction.SIC. Boente obtained a grant from the “Formación del Profesorado Universitario” program, financed by the “Ministerio de Educación, Cultura y Deporte de España” (FPU14/02215). M.T.D Albuquerque acknowledges a scholarship 567 SFRH/BSAB/127907/2016 from the Foundation for Science and Technology (Portugal).ElsevierExplotacion de MinasEscuela Superior y Tecnica de Ingenieros de Minas2018info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionhttps://hdl.handle.net/10612/26163reponame:BULERIA. Repositorio Institucional de la Universidad de Leóninstname:Universidad de LeónIngléshttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:buleria.unileon.es:10612/261632026-06-24T12:43:27Z
dc.title.none.fl_str_mv Combining raw and compositional data to determine the spatial patterns of Potentially Toxic Elements in soils
title Combining raw and compositional data to determine the spatial patterns of Potentially Toxic Elements in soils
spellingShingle Combining raw and compositional data to determine the spatial patterns of Potentially Toxic Elements in soils
Boente López, Carlos
Ecología. Medio ambiente
Soil pollution
Compositional data
Ordinary kriging
Local G-clustering
Relative enrichment
2511.06 Conservación de Suelos
2511.04 Química de Suelos
title_short Combining raw and compositional data to determine the spatial patterns of Potentially Toxic Elements in soils
title_full Combining raw and compositional data to determine the spatial patterns of Potentially Toxic Elements in soils
title_fullStr Combining raw and compositional data to determine the spatial patterns of Potentially Toxic Elements in soils
title_full_unstemmed Combining raw and compositional data to determine the spatial patterns of Potentially Toxic Elements in soils
title_sort Combining raw and compositional data to determine the spatial patterns of Potentially Toxic Elements in soils
dc.creator.none.fl_str_mv Boente López, Carlos
Albuquerque, M.T.D.
Fernández Braña, Alfredo Javier
Gerassis Davite, Saki
Sierra Fernández, Carlos
Rodríguez Gallego, José Luis
author Boente López, Carlos
author_facet Boente López, Carlos
Albuquerque, M.T.D.
Fernández Braña, Alfredo Javier
Gerassis Davite, Saki
Sierra Fernández, Carlos
Rodríguez Gallego, José Luis
author_role author
author2 Albuquerque, M.T.D.
Fernández Braña, Alfredo Javier
Gerassis Davite, Saki
Sierra Fernández, Carlos
Rodríguez Gallego, José Luis
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Explotacion de Minas
Escuela Superior y Tecnica de Ingenieros de Minas
dc.subject.none.fl_str_mv Ecología. Medio ambiente
Soil pollution
Compositional data
Ordinary kriging
Local G-clustering
Relative enrichment
2511.06 Conservación de Suelos
2511.04 Química de Suelos
topic Ecología. Medio ambiente
Soil pollution
Compositional data
Ordinary kriging
Local G-clustering
Relative enrichment
2511.06 Conservación de Suelos
2511.04 Química de Suelos
description [EN] When considering complex scenarios involving several attributes, such as in environmental characterization, a clearer picture of reality can be achieved through the dimensional reduction of data. In this context, maps facilitate the visualization of spatial patterns of contaminant distribution and the identification of enriched areas. A set, of 15 Potentially Toxic Elements (PTEs) – (As, Ba, Cd, Co, Cr, Cu, Hg, Mo, Ni, Pb, Sb, Se, Tl, V, and Zn), was measured in soil, collected in Langreo's municipality (80 km2), Spain. Relative enrichment (RE) is introduced here to refer to the proportion of elements present in a given context. Indeed, a novel approach is provided for research into PTE fate. This method involves studying the variability of PTE proportions throughout the study area, thereby allowing the identification of dissemination trends. Traditional geostatistical approaches commonly use raw data (concentrations) accepting that the elements analyzed make up the entirety of the soil. However, in geochemical studies the analyzed elements are just a fraction of the total soil composition. Therefore, considering compositional data is pivotal. The spatial characterization of PTEs considering raw and compositional data together allowed a broad discussion about, not only the PTEs concentration's distribution but also to reckon possible trends of relative enrichment (RE). Transformations to open closed data are widely used for this purpose. Spatial patterns have an indubitable interest. In this study, the Centered Log-ratio transformation (clr) was used, followed by its back-transformation, to build a set of compositional data that, combined with raw data, allowed to establish the sources of the PTEs and trends of spatial dissemination. Based on the obtained findings it was possible to conclude that the Langreo area is deeply affected by its industrial and mining legacy. City center is highly enriched in Pb and Hg and As shows enrichment in a northwesterly direction.
publishDate 2018
dc.date.none.fl_str_mv 2018
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/10612/26163
url https://hdl.handle.net/10612/26163
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:BULERIA. Repositorio Institucional de la Universidad de León
instname:Universidad de León
instname_str Universidad de León
reponame_str BULERIA. Repositorio Institucional de la Universidad de León
collection BULERIA. Repositorio Institucional de la Universidad de León
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,81155

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