Analysis of tailing pond contamination in Galicia using generalized linear spatial models
We statistically analysed the chemical components present in waste water from mines in Galicia (NW Spain). These elements pose a risk to public health and the environment, most particularly in the event of a failure in the containment structure of a pond or dam. The statistical processing of the dat...
- Autores:
-
Taboada, Javier
Saavedra, Angeles
Paz, María
Bastante, Fernando G
Alejano, Leandro R.
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2015
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/60766
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/60766
http://bdigital.unal.edu.co/59098/
- Palabra clave:
- 62 Ingeniería y operaciones afines / Engineering
tailings pond
environmental risk
generalized linear spatial model
Markov-chain Monte Carlo
spatial statistics.
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
Summary: | We statistically analysed the chemical components present in waste water from mines in Galicia (NW Spain). These elements pose a risk to public health and the environment, most particularly in the event of a failure in the containment structure of a pond or dam. The statistical processing of the data, which started with an analysis of the typical contaminants present in mining ponds and dams, pointed to the potential limitations of using non-spatial models for spatially structured data. Our results indicate the greater potential of the generalized linear spatial model over the generalized linear model for analysis of spatially structured data. We also show how a misspecification of the model for analysing spatial data can lead to misleading conclusions, which might lead, in turn, to poorly designed protective or corrective measures. |
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