Factorial kriging of a geochemical dataset for heavy-metal spatial-variability characterization

Abstract

Gómez-Hernández, JJ. (2014). Factorial kriging of a geochemical dataset for the heavy-metal spatial-pattern characterization The Wallonian Region. Environmental Earth Sciences. 71(7):3161-3170. doi:10.1007/s12665-013-2704-5.Noname manuscript No. Abstract Characterizing the spatial patterns of variability is a fundamental aspect when investigating the origin of the spreading of a multivariate phenomenon. In this paper, a large multivariate dataset from the southeast of Belgium has been analyzed using factorial kriging. The purpose of the study was to explore and retrieve possible scales of spatial variability of heavy metals. This is achieved by decomposing the variance-covariance matrix of the multivariate sample into coregionalization matrices, which are, in turn, decomposed into transformation matrices, which serve to decompose each regionalized variable as a sum of independent factors. Then, factorial cokriging produces maps of the principal factors, which can be compared with the underlying lithology. This comparison identified a few point scale concentrations, which may reflect anthropogenic contamination, it also identified local and regional scale anomalies clearly corresponding to known mineralizations and underlying geology. The results from this analysis could serve to guide the authorities in locating those areas which need remediation.

Environmental Controls to Soil Heavy Metal Pollution Vary at Multiple Scales in a Highly Urbanizing Region in Southern China

“…The soil pollution in space is an outcome of several natural and anthropogenic processes performing at multiple spatial scales [9]. Different influencing factors generally have different spatial spreads [10]. Some of the influence is more likely to be observed at site-or short-distances (e.g., sewage irrigation, agrochemical additions, and traffic or mining or industrial emissions, etc.)…”

“…The combined effect of different influencing factors operating at different spatial scales yielded nested/mixed information for soil pollution from different scales [14]. Identifying the spatial variability of soil pollution at distinct scales and scale-related influencing factors is critical for mitigation purposes [10].…”

Spatial variability of hydraulic conductivity and solute transport parameters and their spatial correlations to soil properties

“…Some effort has been made to characterize the spatial variation of the correlation among variables and to use this information for estimation purposes (Benamghar and Gómez-Hernández, 2014;Bevington et al, 2016;Goovaerts, 1998;Guagliardi et al, 2013).…”