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Double pulse laser-induced breakdown spectroscopy (DP LIBS) has attracted much attention for analyzing trace elements due to its higher sensitivity when compared to single pulse laser-induced breakdown spectroscopy (SP LIBS). However, the development of quantitative methods in LIBS for the analysis of complex samples, such as sediments, is a great challenge due to the matrix effects that are very accentuated in this technique. In this study, different spectral treatments and calibration strategies were investigated to obtain calibration models that allow determinations with satisfactory accuracy and precision of Cr, Cu, and Ni in river sediments from different hydrographic basins. The best model developed for Cr was using MMC without spectral normalization and for Cu and Ni it was using MMC with spectral normalization, and using inverse regression, an increase in the accuracy of the determinations of all analytes was obtained. These models showed limit of quantification (LOQ) of 7.87 mg kg -1 , 1.62 mg kg -1 , and 2.21 mg kg -1 and root mean square error of prediction (RMSEP) of 7.54 mg kg -1 , 14.53 mg kg -1 , and 8.29 mg kg -1 for Cr, Cu, and Ni, respectively. Therefore, the models have adequate sensitivity and precision for the quantification of the potentially toxic elements (PTEs) evaluated, since, according to Brazilian legislation, the lower concentration of threshold effect level (TEL) for Cr, Cu, and Ni is <37.3 mg kg -1 , <35.7 mg kg -1 , and <18 mg kg -1 , respectively. The concentrations of Cr, Cu, and Ni determined by DP LIBS allowed to obtain a partial ecological risk assessment of the studied sediments. Also, the chemometric tool Kohonen self-organizing map (KSOM) were used for data interpretation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Risk assessment is considered an essential tool to assist in the management and mitigation of polluted areas, especially those associated with economic activities that significantly degrade the environment, such as mining. However, most of the methodologies of risk assessment adopt the deterministic approach of using a fixed value for ascertaining the hazards derived from exposure to chemical pollutants. However, this is not the case of the Human, Ecological and Radiological Risk (HERisk) code, which allows space-time assessments of ecological, radiological, and human health risks. Indeed, this work aims to describe this new software (enhanced version of HHRISK), which not only improves the performance of the code but also increases its applicability and versatility. To showcase its usefulness in evaluating ecological pollution and human health risk were studied the contents of potentially toxic elements (Co, Cu, Fe, Mn, Ni, Pb, and Zn) in soils and surface waters from the nickel mining area in the municipality of Itagibá (Bahia, Brazil). The obtained results showed that metals are non-homogeneous distributed, suggesting the presence of local enrichment sources, mainly related to human activities. The statistical analyses carried out revealed that mining and agricultural activities are possibly responsible for the contents of these pollutants in both soils and surface waters. The calculated ecological indices of pollution confirmed anthropogenic pollution around the mining area, especially in the locations closest to sterile waste piles. The results of the human health risk assessment revealed that the ingestion of meat and contaminated water are the main routes for entering the potentially toxic elements to the human body and that Co is the chemical specie that poses the highest risk in the entire region. The hazard index (HI) values indicated that the whole area around the mine should be considered as a high risk for human health., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)