Analysis of tailing pond contamination in Galicia using generalized linear spatial models

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Auteur principal: Javier Taboada
Format: Artículo científico
Langue:en
Publié: Universidad Nacional de Colombia 2015
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author Javier Taboada
author_facet Javier Taboada
contents Analysis of tailing pond contamination in Galicia using generalized linear spatial models Javier Taboada Ángeles Saavedra María Paz Fernando G. Bastante Leandro R. Alejano Ingeniería Tailings pond environmental risk spatial statistics Markovchain Monte Carlo generalized linear spatial model We statistically analysed the chemical components present in wa ste water from mines in Galicia (NW Spain). These elements pose a risk to public health and the environme nt, most particularly in the event of a failure in the contai nment structure of a pond or da m. The statistical processing of the data, which started with an a nalysis of the typical contamina nts present in mining ponds and dams, pointed to the potential limita tions of using nonspatial model s for spatially st ructured data. Our results indicate the greater potential of the generalized l inear spatial model over the generalized linear model for analy sis of spatially structured data. We also show h ow a misspecification of the mod el for analysing spatial data can lead to misleading conclusion s, which might lead, in turn, to poorly de signed protective or correctiv e measures. 2015 artículo científico 0012-7353 https://www.redalyc.org/articulo.oa?id=49635366010 en http://www.redalyc.org/revista.oa?id=496 Dyna application/pdf Universidad Nacional de Colombia Dyna (Colombia) Num.189 Vol.82
format Artículo científico
id redalyc_49635366010
institution Redalyc
language en
publishDate 2015
publisher Universidad Nacional de Colombia
spellingShingle Analysis of tailing pond contamination in Galicia using generalized linear spatial models
Javier Taboada
Ingeniería
Tailings pond
environmental risk
spatial statistics
Markovchain Monte Carlo
generalized linear spatial model
Analysis of tailing pond contamination in Galicia using generalized linear spatial models Javier Taboada Ángeles Saavedra María Paz Fernando G. Bastante Leandro R. Alejano Ingeniería Tailings pond environmental risk spatial statistics Markovchain Monte Carlo generalized linear spatial model We statistically analysed the chemical components present in wa ste water from mines in Galicia (NW Spain). These elements pose a risk to public health and the environme nt, most particularly in the event of a failure in the contai nment structure of a pond or da m. The statistical processing of the data, which started with an a nalysis of the typical contamina nts present in mining ponds and dams, pointed to the potential limita tions of using nonspatial model s for spatially st ructured data. Our results indicate the greater potential of the generalized l inear spatial model over the generalized linear model for analy sis of spatially structured data. We also show h ow a misspecification of the mod el for analysing spatial data can lead to misleading conclusion s, which might lead, in turn, to poorly de signed protective or correctiv e measures. 2015 artículo científico 0012-7353 https://www.redalyc.org/articulo.oa?id=49635366010 en http://www.redalyc.org/revista.oa?id=496 Dyna application/pdf Universidad Nacional de Colombia Dyna (Colombia) Num.189 Vol.82
title Analysis of tailing pond contamination in Galicia using generalized linear spatial models
topic Ingeniería
Tailings pond
environmental risk
spatial statistics
Markovchain Monte Carlo
generalized linear spatial model
url https://www.redalyc.org/articulo.oa?id=49635366010