Predicting the effluent quality of an industrial wastewater treatment plant by way of optical monitoring
| Autor: | Elisa Koivuranta, Jani Tomperi, Kauko Leiviskä |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Biochemical oxygen demand
Engineering digital imaging 02 engineering and technology 010501 environmental sciences cross-validation 01 natural sciences modelling Industrial wastewater treatment pulp and paper industry Safety Risk Reliability and Quality Process engineering Waste Management and Disposal Effluent 0105 earth and related environmental sciences Suspended solids business.industry Process Chemistry and Technology Chemical oxygen demand Environmental engineering 021001 nanoscience & nanotechnology Wastewater activated sludge process Sewage treatment 0210 nano-technology business Predictive modelling variable selection Biotechnology |
| Zdroj: | Journal of Water Process Engineering. 16:283-289 |
| ISSN: | 2214-7144 |
| DOI: | 10.1016/j.jwpe.2017.02.004 |
| Popis: | Wastewater samples taken from the aeration tank of a full-scale activated sludge plant were analyzed using an automatic optical monitoring device. Five variable selection methods were utilized to find the optimal subsets of input variables to develop predictive models for the important parameters of the wastewater treatment process efficiency and the quality of the effluent, including suspended solids, biochemical oxygen demand, chemical oxygen demand, total nitrogen and total phosphorus. The dependencies between the selected variables were also inspected. The study showed that the models based solely on the optical monitoring variables can be used to predict the level of the effluent quality parameters hours before the traditional sampling and analyses. Thus, predictive modelling based on the optical monitoring variables is a potential tool to be used assistance in a process control, keeping the process in a stable operating condition and avoiding environmental risks and economic losses. |
| Databáze: | OpenAIRE |
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