Statistical optimization of surface water quality parameters in environmental monitoring in mining activities in the Amazon

• Autor(a) principal: Silva, Shara Alexandre da
• Data de Publicação: 2020
• Outros Autores: Azevedo, Luiz Eduardo Chaves de, Lima, Gabriel Villas Boas de Amorim, Pereira, Marina Morhy, Araújo, Ivan Roberto Santos
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Research, Society and Development
• Texto Completo: https://rsdjournal.org/index.php/rsd/article/view/2596
• topic: Gran Proyectos Mineros; Amazonía oriental; Análisis de componentes principales.; Grandes Projetos de Mineração; Amazônia Oriental; Análise de Componentes Principais.; Large Mining Projects; Eastern Amazon; Principal Component Analysis.

Mining represents most of the economy of the state of Pará, an activity whose environmental impacts on water bodies need special attention. In this sense, this study sought to optimize a monitoring network for a Large Mining Project (GPM) located in the Eastern Amazon, selecting which parameters effectively influenced the water quality in the region. For this purpose, water quality reports provided by environmental agencies were used to model a statistical treatment by Principal Component Analysis (ACP) in the parameters considered by the company. The results showed that, of the 60 parameters originally adopted, only 12 represent significant alterations identified, proving that the reduction of the analyzed variables does not imply the network compromise. Thus, it was possible to verify that this method is valid to reduce maintenance costs of the monitoring network and to make the process of evaluation of technical reports by the State more agile, benefiting both parties in an environmental licensing process.