Please use this identifier to cite or link to this item: http://repositorio.ufla.br/jspui/handle/1/42637
Title: Principal component analysis as a criterion for monitoring variable organic load of swine wastewater in integrated biological reactors UASB, SABF and HSSF-CW
Keywords: Biological treatment
Multivariate analysis
Agroindustrial wastewater
Organic stabilization
Águas residuais - Tratamento biológico
Suinocultura
Análise multivariada
Estabilização de resíduos orgânicos
Issue Date: May-2020
Publisher: Elsevier
Citation: OLIVEIRA, J. F. de et al. Principal component analysis as a criterion for monitoring variable organic load of swine wastewater in integrated biological reactors UASB, SABF and HSSF-CW. Journal of Environmental Management, [S. I.], v. 262, May 2020. DOI: https://doi.org/10.1016/j.jenvman.2020.110386.
Abstract: The multivariate analysis to optimize the parameters of wastewater is essential to reduce costs. The aim of this study was to evaluate the use of multivariate and conventional analysis in biological system composed by upflow anaerobic sludge blanket (UASB), submerged aerated biological filters (SABF) and horizontal subsurface flow constructed wetland (HSSF-CW) reactors in the organic stabilization of swine wastewater (SW). Four loads were used in the system with alteration by COD concentration of untreated SW, and the data were evaluated by principal components (PCA). The average efficiency of COD and BOD removal increased from 45% in phase I to 67% in phase IV in the UASB, SABF and HSSF-CW reactors. The principal component analysis promoted the reduction of 13 original variables to 5, 8 and 5 principal components in the UASB, SABF and HSSF-CW reactors, respectively, optimizing the dynamics of interpretation of the data that influenced the most the stability of the wastewater system across the four phases. There was a strong negative effect of oxygen concentrations in the SABF reactor in relation to organic variables, optimizing the biological mechanisms of the HSSF-CW and, therefore, enabling better decision making and cost reduction with analysis at treatment plants.
URI: https://doi.org/10.1016/j.jenvman.2020.110386
http://repositorio.ufla.br/jspui/handle/1/42637
Appears in Collections:DEG - Artigos publicados em periódicos
DRH - Artigos publicados em periódicos

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