Adequacy analysis of drinking water treatment technologies in regard to the parameter turbidity, considering the quality of natural waters treated by large-scale WTPs in Brazil

被引:5
作者
Ventura Melo, Livia Duarte [1 ]
da Costa, Elizangela Pinheiro [1 ]
Pinto, Carolina Cristiane [1 ]
Barroso, Gabriela Rodrigues [1 ]
Oliveira, Silvia Correa [1 ]
机构
[1] Univ Fed Minas Gerais, Escola Engn, Campus Pampulha,Ave Antonio Carlos 6627 Bloco 1, BR-31270901 Belo Horizonte, MG, Brazil
关键词
Large-scale WTPs; Turbidity; Nonparametric statistical analysis; Multivariate; Cluster analysis; MULTIVARIATE STATISTICAL TECHNIQUES; PERFORMANCE ASSESSMENT; TREATMENT PLANTS; RIVER;
D O I
10.1007/s10661-019-7526-9
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This paper seeks to present a performance evaluation of large-scale water treatment plants and verify the adjustment of the treatment to the parameter turbidity of natural waters. Nonparametric and multivariate statistical tools were used to analyze raw water and treated water turbidity of a large on-line monitoring databank for the period from 2013 to 2015, from six large-scale treatment plants utilizing different technologies. Cluster analysis was able to differentiate adequately groups of treatment plants with similar raw and treated water quality. Considering the effluent turbidity as a marker parameter, the results indicated that selection of the technology to be applied must be well studied to always seek the best solution, and that other factors than only the raw water characteristics should be evaluated. It was also demonstrated that utilization of the same treatment technology does not always result in the same effluent quality, since there are many factors related to operation, maintenance, raw water variability, climatic interferences, and others.
引用
收藏
页数:12
相关论文
共 1 条
  • [1] Adequacy analysis of drinking water treatment technologies in regard to the parameter turbidity, considering the quality of natural waters treated by large-scale WTPs in Brazil
    Lívia Duarte Ventura Melo
    Elizângela Pinheiro da Costa
    Carolina Cristiane Pinto
    Gabriela Rodrigues Barroso
    Sílvia Corrêa Oliveira
    Environmental Monitoring and Assessment, 2019, 191