Modelling trace metal background to evaluate anthropogenic contamination in arable soils of south-western France

Abstract

The trace metal (TM) content in arable soils has been monitored across a region of France characterised by a large proportion of calcareous soils. Within this particular geological context, the objectives were to first determine the natural levels of trace metals in the soils and secondly, to assess which sites were significantly contaminated. Because no universal contamination assessment method is currently available, four different methods were applied and compared in order to facilitate the best diagnosis of contamination. First, the TM geochemical background was determined by using basic descriptive statistics and linear regression models calculated with semi-conservative major elements as predictors. The natural concentrations of trace metals varied greatly due to the high soil heterogeneity encountered on the regional scale and were more-or-less accurately modelled according to the considered TM. Second, the basic descriptive statistics and the linear regression methods were then compared with the enrichment factor (EF) method and multivariate analysis (PCA), in order to evaluate whether the concentrations measured in soils were abnormally high or not. The advantages and disadvantages of each method were discussed and their results used to identify the most probable contamination cases, the influence of the soils characteristics, as well as the agricultural land cover. The basic descriptive method was good as a first and easy approach to describe the TM ambient concentrations, but may misinterpret the natural anomalies as contaminations. Based on geochemical associations, the linear regression method provided more realistic results even if the relationships between major and trace metals were not significant for the most mobile TM. The EF method was useful to identify high point source contaminations, but it was not suitable when considering a large dataset of low TM concentrations. Finally, the PCA method was a good preliminary tool for the description of the global TM concentrations in a studied area, but it could only give indication on the highest contaminated points. By comparing the results of the different methods in the studied region, we estimated that 24% of the arable soils were contaminated by at least one trace metal, mainly Cu in vineyards/orchards and Cd, Pb and/or Zn in grazing lands. In addition, the calcareous soils exhibited globally higher natural and anthropogenic TM concentrations than non-calcareous soils, probably because of the lower TM mobility at alkaline pH.

Ecological changes in historically polluted soils: Metal(loid) bioaccumulation in microarthropods and their impact on community structure

“…On the one hand, we used the values representing the average metal contents measured in the agricultural soils of the Midi-Pyrénées region for calcareous and non-calcareous soils (Réseau de Mesures de la Qualité des Sols, Redon et al, 2013). On the other hand, we used the impact statement values for sensitive areas (VCI) determined by the BRGM (2002), which is a threshold value for proven pollution.…”

Heavy Metals of Santiago Island (Cape Verde) Alluvial Deposits: Baseline Value Maps and Human Health Risk Assessment

“…Geochemical surveys were developed in the last century [1,2,3,4,5,6] mainly as a means of geochemical prospecting of ore deposits [7,8]. Geochemical databases have been carried out in many regions [9,10,11,12,13], countries [7,14,15,16,17,18], multinational regions [19] and, more recently, continents [20,21,22], at various scales, ranging from high to very low density (e.g., >1 sample/km 2 to 1 sample/10,000 km 2 , respectively). Geochemical surveys application has expanded to also encompass environmental monitoring, land-use decision support, natural resource management, and medical geology [7,23].…”

Are conventional statistical techniques exhaustive for defining metal background concentrations in harbour sediments? A case study: The Coastal Area of Bari (Southeast Italy)

“…Within this framework, to gain insight into the most suitable method to be used in assessing metal and metalloid RGB concentrations in harbour sediments (sediments subjected to additional phenomena compared to simple coastal sediments), a specific area (110 km in length) of the southeast Italian coastline known as the Coastal Area of Bari (CAB) was chosen as a case study for the application of three different conventional statistical methods: (i) linear regression analysis (Covelli and Fontonlan, 1997) following geochemical normalization (Redon et al, 2013); (ii) data processing with the construction of a cumulative frequency distribution Jiang et al, 2013); and (iii) the 2r analysis technique (Lepeltier, 1969;Bouer and Bor, 1995;Matschullat et al, 2000). The dataset consisted of 158 sediment samples collected at different depths (up to 3.50 m) from nearly uncontaminated areas in 3 major ports, 4 minor ports and 6 marine transects from the nearshore area (200 m and 500 m from the coast) covering the entire 110 km of the CAB coastline.…”