Abstract
Environmental pollution by heavy metals is a red-hot issue. It is being studied from many points of view, as it is not only an environmental problem but also a public health matter. The effect of pollution by heavy metals can be assessed directly, that is measuring heavy metal concentration in soils, or using indirect methods, that is measuring heavy metal contents on living beings of regional ecosystem, in particular on plants. One of the organisms that have proved to be the most faithfully and useful to do so are moss. So, heavy metal environmental pollution can be studied by taking moss samples and measuring their heavy metal contents. The aim of this work is to show the use of geostatistical tools in environmental pollution analysis applied to a case study of environmental pollution by heavy metals in Galicia (north west of Spain). To do so, two different information in that zone are available: on one hand, measures of heavy metal concentration in moss (Scleropodium purum), whose location points are known, also their level. On the other hand, situation of polluting sites (industrial areas and towns) and their classification taking into account their polluting capacity. This information allows assessing not only for the regional pollution, but also for its scattering. From this and using geostatistical tools, sampling network is being improved. Data set consists of 71 sample points where concentration of ten elements (Al, As, Co, Cr, Cu, Fe, Hg, Ni, Pb and Zn) is measured. For each of them classical statistical analysis is done. Furthermore, spatial variability is studied using a new methodology based on Fast Fourier Transform (FFT), which allows finding covariance matrix using all variables at the same time. FFT methodology improves the classical and tedious geostatistical methodology based on variogram and cross-variogram modelling to find data spatial variability. Finally contour maps of environmental pollution by heavy metals in Galicia are presented.
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References
Deutsch, C.V. and A.G. Journel (1998). Geostatistical software library and user’s guide-GSLIB. Oxford University Press, 1 CD + 369 pp.
Fernández, J.A., A. Rey and A. Carballeira (2000). An extended study of heavy metal deposition in Galicia (NW Spain) based on moss analysis. The Science of Total Environment, vol. 254, pp 31–44.
Hervada-Sala, C. and E. Jarauta-Bragulat (2001). Modifications to kb2d program in GSLIB to allow use of tabulated covariances calculated with Fast Fourier Transform method. Computers & Geosciences, vol.27, num. 07, pp 887–889.
Ma, X and Yao, T. (2001). A program for 2D modeling (cross)correlogram tables using Fast Fourier Transform. Computers & Geosciences, vol.27, num. 07, pp 763–774.
Yao, T. and A.G. Journel (1998). Automatic modelling of (cross)covariance tables using fast Fourier transform. Mathematical Geology, 30(6), 589 615.
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© 2004 Kluwer Academic Publishers
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Hervada-Sala, C., Jarauta-Bragulat, E. (2004). Optimal Regional Sampling Network to Analyse Environmental Pollution by Heavy Metals Using Indirect Methods. Case Study: Galicia (NW of Spain). In: Sanchez-Vila, X., Carrera, J., Gómez-Hernández, J.J. (eds) geoENV IV — Geostatistics for Environmental Applications. Quantitative Geology and Geostatistics, vol 13. Springer, Dordrecht. https://doi.org/10.1007/1-4020-2115-1_38
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DOI: https://doi.org/10.1007/1-4020-2115-1_38
Publisher Name: Springer, Dordrecht
Print ISBN: 978-1-4020-2007-0
Online ISBN: 978-1-4020-2115-2
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