Calibration Transfer Between a Bench Scanning and a Submersible Diode Array Spectrophotometer for In Situ Wastewater Quality Monitoring in Sewer Systems

Abstract

Online monitoring programs based on spectroscopy have a high application potential for the detection of hazardous wastewater discharges in sewer systems. Wastewater hydraulics poses a challenge for in situ spectroscopy, especially when the system includes storm water connections leading to rapid changes in water depth, velocity, and in the water quality matrix. Thus, there is a need to optimize and fix the location of in situ instruments, limiting their availability for calibration. In this context, the development of calibration models on bench spectrophotometers to estimate wastewater quality parameters from spectra acquired with in situ instruments could be very useful. However, spectra contain information not only from the samples, but also from the spectrophotometer generally invalidating this approach. The use of calibration transfer methods is a promising solution to this problem. In this study, calibration models were developed using interval partial least squares (iPLS), for the estimation of total suspended solids (TSS) and chemical oxygen demand (COD) in sewage from Ultraviolet-visible spectra acquired in a bench scanning spectrophotometer. The feasibility of calibration transfer to a submersible, diode array equipment, to be subsequently operated in situ, was assessed using three procedures: slope and bias correction (SBC); single wavelength standardization (SWS) on mean spectra; and local centering (LC). The results showed that SBC was the most adequate for the available data, adding insignificant error to the base model estimates. Single wavelength standardization was a close second best, potentially more robust, and independent of the base iPLS model. Local centering was shown to be inadequate for the samples and instruments used.

Development and Testing of an IoT Spectroscopic Nutrient Monitoring System for Use in Micro Indoor Smart Hydroponics

“…This finding was as expected and in-line with previous work using UV-Vis to detect nitrogen in hydroponic solutions via spectrophotometry [30]. Considering the extensive work carried out to measure nitrogen with the IR and nearinfrared (NIR) spectrum [58][59][60][61], we expected to see the IR range among the most accurate wavelengths. Surprisingly, for both models, the IR wavelengths were not present.…”

“…The cause of these vast differences was unknown; there may have been issues related to a difference in sensitivity between the sensors depending on the manufacturer, or they could have resulted from the tank size or material anomalies. Differences in submerged applications can be addressed in future studies through local calibration prior to application, as demonstrated in Brito et al [58] and Maribas et al [59].…”

“…Two notable areas for future studies are finding a common calibration and determining optimal pathlengths. Maribas et al [58] and Brito et al [59] established successful calibration models for target solutions, which may solve issues of irregular readings in future research. Next, future studies attempting to determine the optimal mirror distance for this application may eliminate the differences identified between the sensors and provide more accurate readings [47,48,62].…”

Global calibration model of UV-Vis spectroscopy for COD estimation in the effluent of rural sewage treatment facilities

“…Therefore, a series of specic wavelengths could be selected, by which the absorbance could replace the spectral data to establish the model without signicantly reducing the model accuracy. 38 In this study, lasso regressions and stepwise regression were used to select the specic wavelengths from the optimal wavelength intervals. Using the lasso regressions, the specic wavelengths were discovered to be 251, 356, 357, 362, and 363 nm.…”