Research on COD measurement method based on UV-Vis absorption spectra of transmissive and reflective detection systems

The world's rapid industrialisation and population expansion have led to water pollution, causing significant disruption to the activities of humans, animals, and plants. Organic contamination content in water is commonly evaluated by measuring the chemical oxygen demand (COD). However, traditional COD detection methods often require additional reagents, resulting in secondary contamination and extended detection time. In this study, we propose and implement a reflective detection system that measures the UV-Vis absorption spectra of COD in water without contact measurement. We compared the modeling results of the transmissive and reflective detection systems using three regression analysis algorithms. We also assessed the modeling results using various spectral preprocessing and different feature selection bands. The results of the standard samples confirmed the viability of the reflective detection system for detecting COD, with the impressive coefficient of determination (R-2) of 0.98892, the root mean square error (RMSE) of 2.86776, and the detection time of only 47.6 s. For the transmissive detection system, the R-2 was 0.99976, the RMSE was 0.41979, and the detection time was 162.4 s. Overall, this study proposes two referenceable detection methods for measuring COD concentrations, which can be adapted to suit various job demands.

Automated summary

The rapid industrialization and population expansion worldwide have resulted in water pollution, causing significant disruptions to human, animal, and plant activities. Traditional methods for evaluating organic contamination in water typically require additional reagents and suffer from secondary contamination and extended detection time. In this study, a reflective detection system that measures the UV-Vis absorption spectra of chemical oxygen demand (COD) in water without contact measurement is proposed and implemented. Modeling results of the transmissive and reflective detection systems were compared using three regression analysis algorithms, and various spectral preprocessing and feature selection bands were assessed. The results confirm the viability of the reflective detection system, achieving an impressive coefficient of determination (R-2) of 0.98892, a root mean square error (RMSE) of 2.86776, and a detection time of only 47.6 s for COD detection. The transmissive detection system also showed promising results with an R-2 of 0.99976, an RMSE of 0.41979, and a detection time of 162.4 s. Overall, this study proposes two adaptable COD detection methods for different job demands.