Compositional baseline assessments to address soil pollution: An application in Langreo, Spain

C. Boente, M.T.D. Albuquerque, J.R. Gallego, V. Pawlowsky-Glahn, J.J. Egozcue Sci. Total Environ. 2022, 812, 152383

Potentially Toxic Elements (PTEs) are contaminants with high toxicity and complex geochemical behaviour and, therefore, high PTEs contents in soil may affect ecosystems and/or human health. However, before addressing the measurement of soil pollution, it is necessary to understand what is meant by pollution-free soil. Often, this background, or pollution baseline, is undefined or only partially known. Since the concentration of chemical elements is compositional, as the attributes vary together, here we present a novel approach to build compositional indicators based on Compositional Data (CoDa) principles. The steps of this new methodology are: 1) Exploratory data analysis through variation matrix, biplots or CoDa dendrograms; 2) Selection of geological background in terms of a trimmed subsample that can be assumed as non-pollutant; 3) Computing the spread Aitchison distance from each sample point to the trimmed sample; 4) Performing a compositional balance able to predict the Aitchison distance computed in step 3. Identifying a compositional balance, including pollutant and non-pollutant elements, with sparsity and simplicity as properties, is crucial for the construction of a Compositional Pollution Indicator (CI). Here we explored a database of 150 soil samples and 37 chemical elements from the contaminated region of Langreo, Northwestern Spain. There were obtained three Cis: the first two using elements obtained through CoDa analysis, and the third one selecting a list of pollutants and non-pollutants based on expert knowledge and previous studies. The three indicators went through a Stochastic Sequential Gaussian simulation. The results of the 100 computed simulations are summarized through mean image maps and probability maps of exceeding a given threshold, thus allowing characterization of the spatial distribution and variability of the CIs. A better understanding of the trends of relative enrichment and PTEs fate is discussed.