Development of variable pathlength UV-vis spectroscopy combined with partial-least-squares regression for wastewater chemical oxygen demand (COD) monitoring.
To overcome the challenging task to select an appropriate pathlength for wastewater chemical oxygen demand (COD) monitoring with high accuracy by UV-vis spectroscopy in wastewater treatment process, a variable pathlength approach combined with partial-least squares regression (PLSR) was developed in this study. Two new strategies were proposed to extract relevant information of UV-vis spectral data from variable pathlength measurements. The first strategy was by data fusion with two data fusion levels: low-level data fusion (LLDF) and mid-level data fusion (MLDF). Predictive accuracy was found to improve, indicated by the lower root-mean-square errors of prediction (RMSEP) compared with those obtained for single pathlength measurements. Both fusion levels were found to deliver very robust PLSR models with residual predictive deviations (RPD) greater than 3 (i.e. 3.22 and 3.29, respectively). The second strategy involved calculating the slopes of absorbance against pathlength at each wavelength to generate slope-derived spectra. Without the requirement to select the optimal pathlength, the predictive accuracy (RMSEP) was improved by 20-43% as compared to single pathlength spectroscopy. Comparing to nine-factor models from fusion strategy, the PLSR model from slope-derived spectroscopy was found to be more parsimonious with only five factors and more robust with residual predictive deviation (RPD) of 3.72. It also offered excellent correlation of predicted and measured COD values with R(2) of 0.936. In sum, variable pathlength spectroscopy with the two proposed data analysis strategies proved to be successful in enhancing prediction performance of COD in wastewater and showed high potential to be applied in on-line water quality monitoring.
Department of Chemistry, National University of Singapore, 3 Science Drive 3, Singapore 117543, Singapore.
Baisheng
B
Chen
NUS Environmental Research Institute (NERI), #02-01, T-Lab Building (TL), 5A Engineering Drive 1, Singapore 117411, Singapore.
Huanan
H
Wu
Department of Chemistry, National University of Singapore, 3 Science Drive 3, Singapore 117543, Singapore; NUS Environmental Research Institute (NERI), #02-01, T-Lab Building (TL), 5A Engineering Drive 1, Singapore 117411, Singapore; Shenzhen Engineering Laboratory for Eco-efficient Polysilicate Materials, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, PR China. Electronic address: chmlifys@nus.edu.sg.
Sam Fong Yau
SF
Li
D057919:Biological Oxygen Demand Analysis / Q000379:methods*; D016018:Least-Squares Analysis; D013056:Spectrophotometry, Ultraviolet / Q000379:methods*; D014865:Waste Disposal, Fluid / Q000379:methods; D062065:Wastewater / Q000032:analysis*; D060753:Water Quality
D062065:Wastewater
Chemical oxygen demand (COD); Data fusion; Partial-least-squares regression (PLSR); Slope-derived spectroscopy; Wastewater quality monitoring