Geogenic versus anthropogenic behaviour and geochemical footprint of Al, Na, K and P in the Campania region (Southern Italy) soils through compositional data analysis and enrichment factor

Abstract

Geochemical studies that focus on environmental applications tend to approach the chemical elements as individual entities and may therefore offer only partial and sometimes biased interpretations of their distributions and behaviour. A potential alternative approach is to consider a compositional data analysis, where every element is part of a whole. In this study, an integrated methodology, which included compositional data analysis, multifractal data transformations and interpolation, as well as enrichment factor analysis, was applied to a geochemical dataset for the Campania region, in the south of Italy, focusing in particular on the behaviour, footprints and sources of a smaller pool of elements: Al, Na, K and P. The initial dataset included 3669 topsoil samples, collected at an average sampling density of 1 site per 2.3 km 2 , and analysed (after an aqua regia extraction) by a combination of ICP-AES and ICP-MS for 53 elements. Frequency based methods (Clr biplot, Enrichment Factor computation) and frequency spatial-method (fractal and multifractal plots) allowed identifying the relationships between the elements and their possible source patterns in Campania soils in relation to a natural occurring concentrations in geogenic material (rocks, soils and sediments) or human input. Results showed how the interpretation of concentration and behaviour of Al, Na, K and P was enhanced thanks to the application of data log-ratio transformation in univariate and multivariate analysis compared to the use of raw or log-normal data. Multivariate analyses with compositional biplot allowed the identification of four element associations and their potential association with the underling geology and/or human activities. When focusing on the smaller pool of elements (Al, P, K and Na), these relationships with the unique geology of the region were largely confirmed by multifractal interpolated maps. However, when the local background was used for the calculation of the enrichment factor, the resulting interpolated maps allowed to identify smaller areas where the greater concentrations of P could not be possibly associated to a mineralization (e.g., ultrapotassic rocks) but were more likely to be associated to anthropogenic input such as agriculture activities with potentially extensive use of phosphate fertilizers. The integrated approach of this study allowed a more robust qualitative and quantitative evaluation of elemental concentration, providing in particular new and vital information on the distribution and patterns of P in soils of the Campania region, but also a viable, more robust, methodological approach to regional environmental geochemistry studies.

Links between Cognitive Status and Trace Element Levels in Hair for an Environmentally Exposed Population: A Case Study in the Surroundings of the Estarreja Industrial Area

“…As previous reported, the enrichment factor (EF) for studied metals [55] has been employed for calculating differences between the metals originating from human activities and those from natural sources and it can also be used to assess and explain the contamination of metals in soils [108]. To access the degree of soil contamination through this factor, the local background values were used as it is easier to isolate anthropogenic factors from the geogenic ones, because when using generalized values, spurious enrichment due to natural local concentrations of elements may appear [109,110,111,112].…”

The Assessment of Water Compatibility of Adaptable Stick-Net Cage for Resilience Milkfish Cultivation in Tanjung Mas, Indonesia

“…Domestic waste may be one of the main factors that increase phosphate concentrations in the KJT water area. Various studies have shown that human activities, including household waste, have increased the concentration of contaminants in the oceans, such as nitrogen (Jickells et al, 2017), phosphate (Badawy et al, 2018;Thiombane et al, 2019), and heavy metals (Chu et al, 2019;Bessa et al, 2021). It is indicated by the distribution of phosphate levels at stations 1 to 5, which is higher than the other five observation stations.…”

A regional soil and river sediment geochemical study in Baoshan area, Yunnan province, southwest China

“…To assess the anthropogenic impacts, soil contamination assessment was done by calculation of the enrichment factor (EF), which is a widely used proxy (e.g. Akopyan et al, 2018;Barbieri, 2016;Bern et al, 2019;Cevik et al, 2009;Ghrefat et al, 2011;Liénard et al, 2014;Thiombane et al, 2019;Zhang et al, 2014). The deep soil of the NGSLQ program in China shows little effect of human activities.…”