Fracionamento químico de fósforo em testemunho de sedimento do Reservatório Macela, Itabaiana-Sergipe

Detalhes bibliográficos
Ano de defesa: 2013
Autor(a) principal: Canuto, Fabiana Alves Bezerra lattes
Orientador(a): Passos, Elisangela de Andrade lattes
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Não Informado pela instituição
Programa de Pós-Graduação: Pós-Graduação em Química
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Palavras-chave em Inglês:
Área do conhecimento CNPq:
Link de acesso: https://ri.ufs.br/handle/riufs/6083
Resumo: This work concerns the fractionation of phosphorus present in sediments from the Macela Reservoir, located in the city of Itabaiana (Sergipe State, Brazil). Two sediment cores were obtained, each to a depth of approximately 30 cm, which were divided into 5 cm sections. The analytical method employed a Standards, Measurements, and Testing (SMT) protocol, in which the phosphorus was split into the fractions: total (PT), inorganic (PI), organic (PO), non-apatite (PNAP), and apatite (PAP). The technique was validated in terms of the limits of detection (DL) and quantification (QL) for each fraction. No significant contamination was observed. The accuracy was in the range 99-101%, and the relative standard deviation (RSD) was better than 2%. The measured phosphorus concentrations were in the ranges 441.60-1335.47 µg g-1 (PT), 409.54-1209.86 µg g-1 (PI), and 21.35-195.87 µg g-1 (PO). For the inorganic forms, the concentrations of PNAP and PAP were in the ranges 106.82-541.09 µg g-1 and 238.56-698.01 µg g-1, respectively. The concentrations of the phosphorus fractions were highest in Core 2. The contents of Fe, Al, Ca, and Corg were 3.45-4.95%, 4.85-7.73%, 1.02-1.89%, and 1.88-8.55%, respectively. Correlation analysis using the Spearman test identified iron and aluminum as the most important controlling factors for P in the sediments studied. The application of principal components analysis (PCA) and hierarchical clustering analysis (HCA) to the measured parameters divided the sediment samples into two groups, according to their similarities. This was also confirmed using analysis of variance (ANOVA, p<0.05).