Work

Online monitoring of greywater reuse system using excitation-emission matrix (EEM) and K-PARAFACs

Year: 2024

Type: article

Abstract: but by the cluster-specific model that best fitted the EEM signal of the sample with the least numerical error. The proposed strategy demonstrates its robustness by successfully predicting the TCC trend in test datasets. Our findings suggest that K-PARAFACs is a promising tool that enables robust qualitative monitoring of water reuse systems with background DOM variability.

Source: Water Research

DOI: 10.1016/j.watres.2024.122604

Authors: Yongmin Hu, Eberhard Morgenroth, Céline Jacquin

Institutions: ETH Zurich, Institute of Environmental Engineering, Swiss Federal Institute of Aquatic Science and Technology

Language: English

Topic: Water Quality Monitoring and Analysis

Subfield: Waste Management and Disposal

Field: Environmental Science

Domain: Physical Sciences

SDG: Clean water and sanitation

Open Access status: hybrid

Estimated APC paid: $4,520