RESUMEN
Geostatistical and spatially constrained multivariate analysis methods (MULTISPATI-PCA) have been applied at the scale of France to differentiate the influence of natural background from the pollution due to human activities on the content of 8 trace elements in the topsoil. The results of MULTISPATI-PCA evidence strong spatial structures attributed to different natural and artificial processes. The first axis can be interpreted as an axis of global richness in trace elements. Axis 2 reflects geochemical anomalies in Tl and Pb. Axis 3 exhibits on one hand natural pedogeogenic anomalies and on the other hand, it shows high values attributable to anthropogenic contamination. Finally, axis 4 is driven by anthropogenic copper contamination. At the French territory scale, we show that the main factors controlling trace elements distribution in the topsoil are soil texture, variations in parent material geology and weathering, and various anthropogenic sources.
Asunto(s)
Monitoreo del Ambiente , Contaminantes del Suelo/análisis , Suelo/análisis , Oligoelementos/análisis , Francia , Geografía , Análisis MultivarianteRESUMEN
This paper presents a survey on soil Pb contamination around Paris (France) using the French soil monitoring network. The first aim of this study is to estimate the total amount of anthropogenic Pb inputs in soils and to distinguish Pb due to diffuse pollution from geochemical background Pb. Secondly, this study tries to find the main controlling factors of the spatial distribution of anthropogenic Pb. We used the technique of relative topsoil enhancement to evaluate the anthropogenic stock of Pb and we performed lognormal kriging to map Pb regional distribution. The results show a strong gradient of anthropogenic stock of Pb around the urban Paris area. We estimate a total amount of anthropogenic stock of Pb close to 143,000 metric tons, which corresponds to an average accumulation of 5.9 t km(-2). Our study suggests that a grid-based survey can help to quantify diffuse Pb contamination by using robust techniques of calculation and that it might also be used to validate predictions of deposition models.