Browsing by Author "Pawlowsky-Glahn, Vera"
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- Compositional baseline assessments to address soil pollution : an application in Langreo, SpainPublication . Boente, Carlos; Albuquerque, M.T.D.; Gallego, J.R.; Pawlowsky-Glahn, Vera; Egozcue, Juan JoséPotentially 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.
- Nova metodologia para a construção de Índices Composicionais de Poluição em solos: um estudo de caso em Langreo, EspanhaPublication . Albuquerque, M.T.D.; Boente, Carlos; Gallego, J.R.; Pawlowsky-Glahn, Vera; Egozcue, Juan JoséO complexo comportamento geoquímico de Elementos Potencialmente Tóxicos (EPT) em solos pode afetar severamente os ecossistemas e a saúde humana. No entanto, é necessário compreender primeiro o que se entende por um solo “limpo” para depois poder avaliar um solo “poluído “e correspondente grau de severidade associado. Tendo em conta que a composição química de um solo é composicional, os atributos variam juntos, é, neste trabalho, introduzida uma nova metodologia para a construção de Indicadores Composicionais com base no formalismo da Análise de Dados Composicionais (CoDa). Na identificação de um equilíbrio composicional é necessário definir os elementos poluentes e os não poluentes para depois construir um Indicador de Poluição Composicional (IPC). Apresenta-se como estudo de caso a região contaminada de Langreo, noroeste de Espanha, onde num conjunto de 150 amostras de solo georreferenciadas foram analisados, em cada amostra, 37 elementos químicos. Calcularam-se depois, três IPCs, com base no formalismo CoDa e no conhecimento pericial. Num último passo, foram construídos mapas de distribuição espacial e de probabilidade, de exceder um dado limite, para os três novos indicadores de poluição, através de um processo estocástico de simulação sequencial – Simulação Sequencial Gaussiana (SSG). Os padrões espaciais obtidos e correspondente variabilidade associada, permitiu uma melhor compreensão dos processos associados à distribuição e ao enriquecimento relativo em EPTs.
- Relations between river sediments and dissolved matterPublication . Egozcue, Juan José; Pawlowsky-Glahn, Vera; Fonseca, Rita; Albuquerque, Maria TeresaA typical but actually unsolved problem is relating dissolved ions in water and the chemical composition of the corresponding sediments. Our first assumption is that botH ion concentrations and the sediments are compositional in nature. Data from the 2022 and 2023 campaigns in the Trimpancho river (Mining System) (Huelva, Spain) are used to illustrate the possibilities and the challenges of such an analysis. The data consists of 23 sampling points recording both 14 dissolved ions (mg/L) and 10 elements (mg/kg) from the sediment. A first analysis of association using the proportionality index of parts (PIP) reveals that binary relations are weak, while the Aitchison-distance correlation indicates that there is some moderate correlation between dissolved ions and sediments. The relation was also examined using compositional canonical correlation. A surprising result was that up to three canonical functions exhibited very high correlations. A deeper evaluation suggested that these high correlations are due to overparametrization given the small sample size. Finally, after simplification of the canonical correlation model, some balances within dissolved ions and within sediments evidenced moderate correlations in accordance with the previous results. Results show that the main relations involve several elements and single element relations are irrelevant. For instance, the ion balance of Ca, Cu, Fe, Zn over Mg, Mn, Ni has a 0.7 Pearson correlation with the sediment balance Al, Mn over Cr.
- Soil pollution: A compositional baseline approach in Langreo, SpainPublication . Albuquerque, Maria Teresa; Boente, Carlos; Gallego, J.R.; Pawlowsky-Glahn, Vera; Egozcue, Juan José; Thomas-Agnan, Ch.; Pawlowsky-Glahn, VeraThe complex geochemical behavior associated to the spatial distribution of potentially toxic elements (PTE) in soils can affect ecosystems and/or human health. However, before considering the measurement of soil pollution, there is a need to understand what is meant by pollution-free soil. In many cases, this context, or the basis of pollution, is not defined or only partially known. Since the concentration of the chemical elements is compositional, as the attributes vary together, a new approach is introduced aiming at the construction of compositional indicators based on the principles of Compositional Data Analysis (CoDa). 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-polluted; 3) Computing the Aitchison distance from each sample point to the trimmed sample; 4) Finding a compositional balance able to predict the Aitchison distance computed in step 3. The identifi cation of a compositional balance, including pollutants and non-polluting elements, with sparse and simple properties, is crucial for building a Compositional Pollution Index (CI). A 150 soil samples dataset, from the contaminated region of Langreo, northwest Spain, corresponding to 37 chemical elements was used as a pilot survey. As a first approach, three CIs were obtained. The corresponding spatial distribution was computed using Gaussian sequential stochastic simu lation. The results of the 100 obtained scenarios are summarized through mean image maps and probability maps of exceeding a given threshold. The characterization of the spatial distribution and variability of the CIs allowed a better understanding of relative enrichment patterns and the fate of PTEs.