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Pilot-Scale Anaerobic Treatment of Printing and Dyeing Wastewater and Performance Prediction Based on Support Vector Regression
| Content Provider | MDPI |
|---|---|
| Author | DeQi, Xiong Qi, Zhixin Wang, Zhennan Chen, Meiting |
| Copyright Year | 2022 |
| Description | Printing and dyeing wastewater is characterized with complex water quality and poor biodegradability. In this study, a pilot-scale anaerobic baffled reactor (ABR) with packing was verified to effectively degrade the complex organic pollutants in the wastewater through the hydrolysis and acidification of anaerobic microorganisms. At a hydraulic retention time (HRT) of 12 h and an organic loading rate (OLR) of 2.0–2.5 kg $COD/(m^{3}$·d), the ABR stabilized the fluctuation range of pH and achieved an average colority removal rate of 10.5%, which provided favorable conditions for subsequent aerobic treatment. During the early operation period, the reactor increased the alkalinity of the wastewater; after 97 days of operation, the volatile fatty acid (VFA) content in the wastewater decreased. To demonstrate the suitability of the support vector regression (SVR) technology in predicting the performance of the reactor, two SVR algorithms with three kernel functions were employed to relate the chemical oxygen demand (COD) removal rate to its influencing factors, and the predictions of both the training and validation groups agreed with the measurements. The results obtained from this study can contribute to the design and optimal operation of the anaerobic treatment project of the industrial wastewater treatment plant. |
| Starting Page | 99 |
| e-ISSN | 23115637 |
| DOI | 10.3390/fermentation8030099 |
| Journal | Fermentation |
| Issue Number | 3 |
| Volume Number | 8 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2022-02-26 |
| Access Restriction | Open |
| Subject Keyword | Fermentation Environmental Engineering Printing and Dyeing Wastewater Anaerobic Treatment Support Vector Regression Pilot-scale Reactor Performance Prediction |
| Content Type | Text |
| Resource Type | Article |
