期刊
WATER RESEARCH
卷 96, 期 -, 页码 155-165出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.watres.2016.03.046
关键词
Algae; Lagoons; Principal components analysis; Wastewater stabilization ponds
资金
- Natural Sciences and Engineering Research Council (NSERC) under a Collaborative Research and Development (CRD) grant
- NSERC under the Systems Training and Education in Water Assets Research and Development (STEWARD) Collaborative Research and Training Experience Program (CREATE)
- Canada Research Chair (CRC) program
The wastewater stabilization ponds (WSPs) at a wastewater treatment facility in eastern Ontario, Canada, have experienced excessive algae growth and high pH levels in the summer months. A full range of parameters were sampled from the system and the chemical dynamics in the three WSPs were assessed through multivariate statistical analysis. The study presents a novel approach for exploratory analysis of a comprehensive water chemistry dataset, incorporating principal components analysis (PCA) and principal components (PC) and partial least squares (PLS) regressions. The analyses showed strong correlations between chl-a and sunlight, temperature, organic matter, and nutrients, and weak and negative correlations between chl-a and pH and chl-a and DO. PCA reduced the data from 19 to 8 variables, with a good fit to the original data matrix (similarity measure of 0.73). Multivariate regressions to model system pH in terms of these key parameters were performed on the reduced variable set and the PCs generated, for which strong fits (R-2 > 0.79 with all data) were observed. The methodologies presented in this study are applicable to a wide range of natural and engineered systems where a large number of water chemistry parameters are monitored resulting in the generation of large data sets. (C) 2016 Elsevier Ltd. All rights reserved.
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