Using Surrogate Parameters to Enhance Monitoring of Community Wastewater Management System Performance for Sustainable Operations.
Zhining ShiChristopher W K ChowJing GaoKe XingJixue LiuJiuyong LiPublished in: Sensors (Basel, Switzerland) (2024)
Community wastewater management systems (CWMS) are small-scale wastewater treatment systems typically in regional and rural areas with less sophisticated treatment processes and often managed by local governments or communities. Research and industrial applications have demonstrated that online UV-Vis sensors have great potential for improving wastewater monitoring and treatment processes. Existing studies on the development of surrogate parameters with models from spectral data for wastewater were largely limited to lab-based. In contrast, industrial applications of these sensors have primarily targeted large wastewater treatment plants (WWTPs), leaving a gap in research for small-scale WWTPs. This paper demonstrates the suitability of using a field-based online UV-Vis sensor combined with advanced data analytics for CWMSs as an early warning for process upset to support sustainable operations. An industry case study is provided to demonstrate the development of surrogate monitoring parameters for total suspended solids (TSSs) and chemical oxygen demand (COD) using the UV-Vis spectral data from an online UV-Vis sensor. Absorbances at a wavelength of 625 nm (UV 625 ) and absorbances at a wavelength of 265 nm (UV 265 ) were identified as surrogate parameters to measure TSSs and COD, respectively. This study contributes to the improvement of WWTP performance with a continuous monitoring system by developing a process monitoring framework and optimization strategy.
Keyphrases
- wastewater treatment
- antibiotic resistance genes
- big data
- electronic health record
- healthcare
- social media
- mental health
- optical coherence tomography
- aqueous solution
- photodynamic therapy
- magnetic resonance
- magnetic resonance imaging
- machine learning
- cancer therapy
- computed tomography
- combination therapy
- deep learning
- artificial intelligence
- low cost