Abstract
Open dumping is one of the most common solid waste disposal methods in developing countries. As they lack planning and basic environmental protection engineering measures, dumpsites represent environmental and health risks that should be investigated. However, several dumpsites are abandoned without appropriate land-use management, difficulting their proper environmental assessment. The use of non-invasive methods for waste mass delimitation and preliminary screening of contamination plumes, such as geophysical methods, is an interesting alternative for the study of the environmental impacts caused by dumpsites. The aim of the present study is to apply electrical resistivity tomography (ERT) for the delimitation of the waste mass and the identification of anomalies related to the presence of alterations in the physical and chemical properties of soils and groundwater in an inactive dumpsite in the municipality of Miracatu, State of São Paulo, Brazil. The study was based on the use of the python software ResIPy, which uses an R family of ERT inversion codes. The 3D inversion of data showed a good correlation between the most electrically conductive anomalies and the delimitation of the waste mass. The behavior of these anomalies, associated with the presence of waste, was confirmed by the physical characterization of the geological materials obtained from drillings and installation of monitoring wells. The present study shows that the ERT inversion code for electrical data can be an interesting open-source alternative for data processing in complex scenarios: environments that present considerable anthropic interference, such as dumpsites.
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LGN and CCG wrote the main manuscript text. AMB performed hydrochemical data analysis. OCBG carried out the geophysical acquisitions. LGN processing of geophysical data. All authors reviewed the manuscript.
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Netto, L.G., Guimarães, C.C., Barbosa, A.M. et al. Characterization of an inactive dumpsite using electrical resistivity tomography and hydrochemical data: a case study in Brazil. Environ Earth Sci 82, 529 (2023). https://doi.org/10.1007/s12665-023-11233-2
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DOI: https://doi.org/10.1007/s12665-023-11233-2