Analysis of activated sludge process using multivariate statistical tools - a PCA approach

被引:51
作者
Tomita, RK [1 ]
Park, SW [1 ]
Sotomayor, OAZ [1 ]
机构
[1] Univ Sao Paulo, LSCP, Dept Chem Engn, BR-05508900 Sao Paulo, Brazil
关键词
IWA-ASM1; PCA; multivariate statistical analysis; wastewater treatment monitoring;
D O I
10.1016/S1385-8947(02)00133-X
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Twelve original physical variables of an activated sludge wastewater treatment system are considered. These cross-correlated variables are transformed in new ones that are not correlated by the use of PCA (principal component analysis), a powerful tool for analysis, monitoring and diagnostics of wastewater treatment processes. Just three principal components explain most of the system total variability (78% of total variance). Thus, the ability to describe the overall characteristics of the process using only three principal components will make the analysis, monitoring and diagnostic of the system easier. Three groups of variables characterizing the system are detected. The first group identifies variables that represent micro-organisms and inert particulate matter arising from cellular decay, while the second group refers to substrates and flow rate. The third group is related to the pH. Based on these results, the present paper shows how to enlarge the ways of interpreting the characteristics of activated sludge wastewater treatment system. (C) 2002 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:283 / 290
页数:8
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