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.KeywordsHeavy MetalFast Fourier TransformHeavy Metal ConcentrationHeavy Metal ContentMoss SampleThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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