An Assessment of Mass Flows, Removal and Environmental Emissions of Bisphenols in a Sequencing Batch Reactor Wastewater Treatment Plant.

This study analyzed 16 bisphenols (BPs) in wastewater and sludge samples collected from different stages at a municipal wastewater treatment plant based on sequencing batch reactor technology. It also describes developing an analytical method for determining BPs in the solid phase of activated sludge based on solid-phase extraction and gas chromatography-mass spectrometry. Obtained concentrations are converted into mass flows, and the biodegradation of BPs and adsorption to primary and secondary sludge are determined. Ten of the sixteen BPs were present in the influent with concentrations up to 434 ng L-1 (BPS). Only five BPs with concentrations up to 79 ng L-1 (BPA) were determined in the plant effluent, accounting for 8 % of the total BPs determined in the influent. Eleven per cent of the total BPs were adsorbed on primary and secondary sludge. Overall, BPs biodegradation efficiency was 81%. The highest daily emissions via effluent release (1.48 g day-1) and sludge disposal (4.63 g day-1) were for BPA, while total emissions reached 2 g day-1 via effluent and 6 g day-1 via sludge disposal. The data show that the concentrations of BPs in sludge are not negligible, and their environmental emissions should be monitored and further studied.

Sequencing batch-reactor control using Gaussian-process models.

This paper presents a Gaussian-process (GP) model for the design of sequencing batch-reactor (SBR) control for wastewater treatment. The GP model is a probabilistic, nonparametric model with uncertainty predictions. In the case of SBR control, it is used for the on-line optimisation of the batch-phases duration. The control algorithm follows the course of the indirect process variables (pH, redox potential and dissolved oxygen concentration) and recognises the characteristic patterns in their time profile. The control algorithm uses GP-based regression to smooth the signals and GP-based classification for the pattern recognition. When tested on the signals from an SBR laboratory pilot plant, the control algorithm provided a satisfactory agreement between the proposed completion times and the actual termination times of the biodegradation processes. In a set of tested batches the final ammonia and nitrate concentrations were below 1 and 0.5 mg L(-1), respectively, while the aeration time was shortened considerably.

Modeling, identification, and validation of models for predictive ammonia control in a wastewater treatment plant--a case study.

The aim of this work is to develop the ammonia models that could be used for model predictive control (MPC) of nitrification process in a wastewater treatment plant. First, a reduced nonlinear model is presented, which is based on expression for nitrification reaction rate in activated sludge model No. 1 and modified for attached biomass processes, while second, a linear black-box model is shown. The data used for model identification were collected during several weeks of experiments on a real plant so that good identification data were obtained. The designed models were validated based on open loop simulations and predictions. Validation results show that the reduced nonlinear model performs better compared to the linear model, however, both models show relatively large errors compared to the real plant data. Hence, a closed loop simulation study was performed to see the differences between the performance of model predictive controller using previously estimated linear and nonlinear models and a standard proportional integral (PI) controller. From the simulation study results it was seen that in spite of relatively large model errors the MPC algorithms give better results in terms of ammonia removal compared to the PI controller, while MPC with the nonlinear model shows additional improvements over the MPC with the linear model.

Improvement of ammonia removal in activated sludge process with feedforward-feedback aeration controllers.

In the paper three linear aeration controllers that can be easily implemented are presented and evaluated on the activated sludge process pilot plant. Controllers differ according to the information that is used about the process, which can be oxygen in the last aerobic reactor, ammonia in the last aerobic reactor and ammonia in the influent. The aeration controllers that are addressed are: oxygen cascade PI controller, ammonia cascade PI controller and ammonia feedforward-cascade PI controller. Experiments show that, in comparison with the oxygen cascade PI controller, the ammonia cascade PI controller allows better control of effluent ammonia and airflow savings of around 23%, while the ammonia feedforward-cascade PI controller gives the best reduction of ammonia peaks and can save up to 45% of the airflow.