Heavy metals in European soils: a geostatistical analysis of the FOREGS Geochemical database
Summary: The paper presents results of mapping concentrations of eight critical heavy metals (arsenic, cadmium, chromium, copper, mercury, nickel, lead and zinc) using the 1588 georeferenced topsoil samples from the FOREGS Geochemical database. The concentrations were interpolated using block regression-kriging over the 26 European countries that contributed to the database. Fully-automated techniques were used to estimate the regression model, fit the variograms and run the predictions. The original concentrations were transformed to logits to improve their normality and avoid making predictions outside physical range. A large amount of auxiliary raster maps was used to improve the predictions: DEM-parameters, MODIS NDVI time series, night light image, geological and land cover maps, cumulative earthquake magnitude map. These were first converted to 36 principal components and then used to explain spatial distribution of heavy metals. The study revealed that the FOREGS Geochemical database is suitable for geostatistical analyses: the predictors explained from 21% (Cr) up to 36% (Pb) of variability; the residuals showed clear auto-correlation structure. High concentrations of Cd, Cu, Hg, Pb and Zn can be linked with human activities, i.e. industrialization and intensive agriculture. A significant correlation between the contents of Ni (r=0.40) and Cr (r=0.29) and the magnitude of earthquakes was also observed. The PCA of the mapped heavy metals revealed that the administrative units (NUTS level3) with highest overall concentrations are: (1) Liege (Arrondissement) (BE), Attiki (GR), Darlington (UK), Coventry (UK), Sunderland (UK), Kozani (GR), Grevena (GR), Hartlepool & Stockton (UK), Huy (BE), Aachen (DE) (As, Cd, Hg and Pb) and (2) central Greece and Liguria region in Italy (Cr, Cu and Ni). Automation of the geostatistical mapping and use of auxiliary spatial layers opens a possibility to develop mapping systems that can automatically update outputs by including new field observations and higher quality auxiliary maps. This approach also demonstrates the benefits of organizing joint European monitoring projects, in comparison to merging of national monitoring projects.
Links:
Geochemical Atlas of Europe
