On-line optical monitoring of activated sludge floc morphology

Koivuranta, Elisa; Stoor, Tuomas; Hattuniemi, Joni; Niinimäki, Jouko

doi:10.1016/j.jwpe.2014.12.009

Cited by 24 publications

(22 citation statements)

References 27 publications

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“…The differences between the results of the municipal and the industrial cases are most likely due to the nature of the processes. Based on the optical monitoring of the treatment process, in the industrial ASP the settling problem was caused by dispersed growth [5] and in the municipal ASP the poor settling was caused by filamentous bulking [6]. The selected input variables for developing predictive models of treated wastewater quality parameters are presented in Table 2.…”

Section: Resultsmentioning

confidence: 99%

“…Optical monitoring of floc morphological characteristics is a potential tool to be used as assistance in process control as it gives fast objective information about the quality of wastewater and the state of the treatment process, reveals some of the reason for settling problems and combined to a predictive modelling shows the quality of effluent in advance hours before it is noticed by traditional process measurements. [3,2,[4][5][6][7][8] In this study, the results of the automatic optical monitoring of wastewater samples taken from a fullscale industrial active sludge process during a period over one year were utilized to develop predictive models for the effluent quality parameters (suspended solids, biological oxygen demand, chemical oxygen demand, nitrogen and phosphorus). Five variable selection methods were used for selecting the optimal subsets of input variables for each developed model.…”

Section: Introductionmentioning

confidence: 99%

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Predicting the effluent quality of an industrial wastewater treatment plant by way of optical monitoring

Tomperi

Koivuranta

Leiviskä

2017

Journal of Water Process Engineering

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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.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Predicting the effluent quality of an industrial wastewater treatment plant by way of optical monitoring

Tomperi

Koivuranta

Leiviskä

2017

Journal of Water Process Engineering

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“…It has been reported that SBRs require less area, are flexible to operate and can be operated automatically [5,6]. However, solid-liquid separation, or sludge bulking, is still one of the most problematic issues with SBRs and ASPs in general [7,8].…”

Section: Introductionmentioning

confidence: 99%

Improving sludge settleability by introducing an innovative, two-stage settling sequencing batch reactor

Alattabi

Harris

Alkhaddar

et al. 2017

Journal of Water Process Engineering

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Improving sludge settleability by introducing an innovative, two-stage settling sequencing batch reactor http://researchonline.ljmu.ac.uk/id/eprint/7679/ Article LJMU has developed LJMU Research Online for users to access the research output of the University more effectively. (2017) Improving sludge settleability by introducing an innovative, two-stage settling sequencing batch reactor. Journal of Water Process Engineering, 20. pp. 207-216. ISSN 2214-7144 LJMU Research Online Improving sludge settleability by introducing an innovative, two-stage settling sequencing batch reactor Abstract Sludge settleability is considered one of the main drawbacks of sequencing batch reactors. The aim of this study therefore is to improve sludge settleability by introducing a novel, two-stage settling sequencing batch reactor (TSSBR) separated by an anoxic stage. The performance of the TSSBR was compared with that of a normal operating sequencing batch reactor (NOSBR), operating with the same cycle time. The results show a significant improvement in sludge settleability and nitrogen compound removal rates for the TSSBR over the NOSBR. The average removal efficiencies of NH3-N, NO3-N and NO2-N have been improved from 76.6%,86.4% and 87.3% respectively for the NOSBR to 89.2%, 95.2% and 96% respectively for the TSSBR. In addition, the average SVI30 for the NOSBR has been reduced from 42.04 ml/g to 31.17 ml/g for the TSSBR. After three months of operation, there was an overgrowth of filamentous bacteria inside the NOSBR reactor, while the morphological characteristics of the sludge inside the TSSBR reactor indicated a better and homogenous growth of filamentous bacteria.

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“…To replace the slow, irregular, and subjective manual microscopic analysis of wastewater samples, a smallscale optical monitoring device and an image analysis method were developed (Koivuranta et al, 2013) and proved functional for monitoring the floc morphology reliably in-situ in full-scale municipal ASP (Koivuranta et al, 2015). The device consists of an imaging unit, a sample handling unit, and a control PC with an electronics unit.…”

Section: Optical Monitoring and Image Analysismentioning

confidence: 99%

“…Thus, there is a demand for new real-time monitoring tools and methods to be used in process control in parallel with the traditional offline analysis of wastewater samples and expert knowledge. The novel on-line optical monitoring method gives fast, objective information about the state of the wastewater treatment process, reveals some of the reasons for settling problems, and combined to a predictive model, shows the quality of effluent in advance (Koivuranta et al, 2015;Tomperi et al, 2017). In this study, a variogram method is utilized for finding the optimal subset of variables to develop predictive models for BOD, COD, and SS in biologically treated wastewater.…”

Section: Introductionmentioning

confidence: 99%

A Variogram-Based Tool for Variable Selection in a Wastewater Treatment Effluent Prediction

Ohenoja

Tomperi

2018

Linköping Electronic Conference Proceedings

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In this study, a variogram method was utilized as a variable selection tool for finding the optimal subsets of variables for developing predictive models for the quality of wastewater treatment effluent. The quality of effluent was here assessed by biological and chemical oxygen demand and suspended solids in biologically treated wastewater. The dataset included, in addition to traditional process measurements, results of a novel optical monitoring device which was used for imaging an activated sludge process in-situ during a period of over one year. The study showed that the variogram based method has potential in fast and computationally easy variable selection. The developed models can be used for proactive monitoring and estimating the quality of effluent in several stages hours before in comparison to laboratory analysis taken from treated wastewater.

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On-line optical monitoring of activated sludge floc morphology

Cited by 24 publications

References 27 publications

Predicting the effluent quality of an industrial wastewater treatment plant by way of optical monitoring

Predicting the effluent quality of an industrial wastewater treatment plant by way of optical monitoring

Improving sludge settleability by introducing an innovative, two-stage settling sequencing batch reactor

A Variogram-Based Tool for Variable Selection in a Wastewater Treatment Effluent Prediction

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