Experimental design of an optimal phase duration control strategy used in batch biological wastewater treatment

Is sequential batch reactor an efficient technology to protect recipient against non-steroidal anti-inflammatory drugs and paracetamol in treated wastewater?

The tested facility was a wastewater treatment plant (WWTP) in Swarzewo, where the wastewater treatment takes place in aeration chambers with activated sludge using sequential batch reactors (SBRs). The concentration of the following pharmaceuticals: ibuprofen, paracetamol, flurbiprofen, naproxen, diclofenac, and its metabolites 5OH-diclofenac and 4OH-diclofenac was tested in influents and effluents. Simultaneously, the conventional parameters were characterised. The removal of conventional pollutants was high (94.4-99.5%). At the same time, the removal of pharmaceuticals was variable. In the case of diclofenac and its metabolites, the concentration in the effluent was higher than in the influents. The risk quotients (RQs) calculated for analyzed pharmaceuticals suggest low environmental risk for selected species. However, negative impact for the biota due to the chronic presence of diclofenac cannot be excluded. It can be concluded that the SBRs, similarly to traditional flow activated sludge technology, are not efficient in the removal of target pharmaceuticals.

Table Olive Wastewater: Problem, Treatments and Future Strategy. A Review

The table olive industry produces a high quantity of wastewater annually. These wastewaters are very problematic because of their characteristics of high organic matter, high phenolic content, high salinity and conductivity. The quantities in which they are produced are also a serious problem. The worldwide production of table olives reached 2,550,000 tons in the last five campaigns, with the European Union contributing to 32% of total production. The problem of these wastewaters is focused on the Mediterranean area where the highest quantity of table olives is produced and to a lesser extent on the United States and South America. Countries like Spain produce around 540,000 tons of these wastewaters. At present, there is no standard treatment for these wastewaters with acceptable results and which is applied in the industry. Currently, the most common treatment is the storage of these wastewaters in large evaporation ponds where, during the dry season, the wastewater disappears due to evaporation. This is not a solution as the evaporation ponds depend completely on the climatology and have a high number of associated problems, such as bad odors, insect proliferation and the contamination of underground aquifers. Different studies have been carried out on table olive wastewater treatment, but the reality is that at the industrial level, none has been successfully applied. New and promising treatments are needed. The current review analyzes the situation of table olive wastewater treatment and the promising technologies for the future.

Advanced strategies to improve nitrification process in sequencing batch reactors - A review

The optimization of biological nitrogen removal (BNR) in sequencing batch reactors has become the aim of researchers worldwide in order to increase efficiency and reduce energy and operating costs. This research has focused on the nitrification phase as the limiting reaction rate of BNR. This paper analyzes different strategies and discusses different tools such as: factors for achieving partial nitrification, real-time control and monitoring for detecting characteristic patterns of nitrification/denitrification as end-points, use of modeling based on activated sludge models, and the use of data-driven modeling for estimating variables that cannot be easily measured experimentally or online. The discussion of this paper highlight the properties and scope of each of these strategies, as well as their advantages and disadvantages, which can be integrated into future works using these strategies according to legal and economic restrictions for a more stable and efficient BNR process in the long-term.

Dynamic control of nutrient-removal from industrial wastewater in a sequencing batch reactor, using common and low-cost online sensors

On-line control of the biological treatment process is an innovative tool to cope with variable concentrations of chemical oxygen demand and nutrients in industrial wastewater. In the present study we implemented a simple dynamic control strategy for nutrient-removal in a sequencing batch reactor (SBR) treating variable tank truck cleaning wastewater. The control system was based on derived signals from two low-cost and robust sensors that are very common in activated sludge plants, i.e. oxidation reduction potential (ORP) and dissolved oxygen. The amount of wastewater fed during anoxic filling phases, and the number of filling phases in the SBR cycle, were determined by the appearance of the 'nitrate knee' in the profile of the ORP. The phase length of the subsequent aerobic phases was controlled by the oxygen uptake rate measured online in the reactor. As a result, the sludge loading rate (F/M ratio), the volume exchange rate and the SBR cycle length adapted dynamically to the activity of the activated sludge and the actual characteristics of the wastewater, without affecting the final effluent quality.

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.

Biological nitrogen removal with a real-time control strategy using moving slope changes of pH(mV)- and ORP-time profiles

A new real-time control strategy using moving slope changes of oxidation-reduction potential (ORP)- and pH(mV)-time profiles was designed. Its effectiveness was evaluated by operating a farm-scale sequencing batch reactor (SBR) process using the strategy. The working volume of the SBR was 18 m(3), and the volumetric loading rate of influent was 1 m(3) cycle(-1). The SBR process comprised six phases: feeding → anoxic → anaerobic → aerobic → settle → discharge. The anoxic and aerobic phases were controlled by the developed real-time control strategy. The nitrogen break point (NBP) in the pH(mV)-time profile and the nitrate knee point (NKP) in the ORP-time profile were designated as real-time control points for the aerobic and anoxic phases, respectively. Through successful real-time control, the duration of the aerobic and anoxic phases could be optimized and this resulted in very high N removal and a flexible hydraulic retention time. Despite the large variation in the loading rate (0.5-1.8 kg NH(4)-N m(-3) cycle(-1)) due to influent strength fluctuation, complete removal of NH(4)-N (100%) was always achieved. The removal efficiencies of soluble nitrogen (NH(4)-N plus NO(x)-N), soluble total organic carbon, and soluble chemical oxygen demand were 98%, 90%, and 82%, respectively. Monitoring the ORP and pH(mV) revealed that pH(mV) is a more reliable control parameter than ORP for the real-time control of the oxic phase. In some cases, a false NBP momentarily appeared in the ORP-time profile but was not observed in the pH(mV)-time profile. In contrast, ORP was more the reliable control parameter for NKP detection in the anoxic phase, since the appearance of NKP in the pH(mV)-time profile was sometimes vague.

Artificial intelligence control of a sequencing batch reactor for nitrogen removal via nitrite from landfill leachate

Leachate generated in old landfills is a high-strength wastewater, which is particularly difficult to treat owing to its low biochemical oxygen demand/total Kjeldahl nitrogen ratio. This paper seeks to demonstrate that reliable leachate treatment by means of sequencing batch reactors (SBRs) is indeed possible by means of the application of a smart control system. This study assesses the results of a computer-controlled bench-scale SBR treating raw sanitary landfill leachate to achieve nitrogen removal through the nitrite shortcut. Significant improvements have been obtained by introducing a fuzzy inferential system based on simple process measurements (i.e. dissolved oxygen, oxidation-reduction potential and pH). The paper analyzes the results of a test period of over 280 consecutive days of operation, during which the fuzzy control system correctly recognized over 97% of the SBR phase transitions and provided smart adjustments of the process operating conditions in terms of phase length and external COD addition. In spite of time-varying process conditions, the application of fuzzy logic provided stable nitrogen removal via nitrite through continuous adjustments of the main process parameters and resulted in a decreased hydraulic retention time, an increased loading rate, a saving in the external COD addition and considerable aeration energy conservation.

Long-term effect of dissolved oxygen on partial nitrification performance and microbial community structure

In this study, the performance of partial nitrification via nitrite and microbial community structure were investigated and compared in two sequencing batch reactors (SBR) with different dissolved oxygen (DO) levels. Both reactors achieved stable partial nitrification with nitrite accumulation ratio of above 95% by using real-time aeration duration control. Compared with high DO (above 3 mg/l on average) SBR, simultaneous nitrification and denitrification (SND) via nitrite was carried out in low DO (0.4-0.8 mg/l) SBR. The average efficiencies of SND in high DO and low DO reactor were 7.7% and 44.9%, and the specific SND rates were 0.20 and 0.83 mg N/(mg MLSS h), respectively. Low DO did not produce sludge with poorer settling properties but attained lower turbidities of the effluent than high DO. Fluorescence in situ hybridization (FISH) analysis in both the reactors showed that ammonia-oxidizing bacteria (AOB) were the dominant nitrifying bacteria and nitrite-oxidizing bacteria (NOB) did not be recovered in spite of exposing nitrifying sludge to high DO. The morphology of the sludge from both two reactors according to scanning electron microscope indicated that small rod-shaped and spherical clusters were dominant, although filamentous bacteria and few long rod-shaped coexisted in the low DO reactor. By selecting properly DO level and adopting process control method is not only of benefit to the achievement of novel biological nitrogen removal technology, but also favorable to sludge population optimization.

Control of SBR switching by fuzzy pattern recognition

The sequencing batch reactor (SBR) is a widely used process for biological removal of nutrients (nitrogen and phosphorus) from wastewater. It is based on the metabolism of specialised bacteria, which under alternate anaerobic/aerobic conditions uptake phosphorus and perform denitrification. Intermittent operation is normally operated on a fixed switching schedule with ample margin for possible inaccuracies, with the result that the process operation is highly inefficient. This paper proposes a switching strategy based on the indirect observation of process state through simple physico-chemical measurements and the use of an inferential engine to determine the most appropriate switching schedule. In this way the duration of each phase is limited to the time strictly necessary for the actual loading conditions. Experimental results show that the treatment cycle can be significantly shortened, with the results that more wastewater can be treated. The switching strategy is based on innovative data-processing techniques applied to simple process signals including pH, oxido-reduction potential (ORP) and dissolved oxygen (DO). They include wavelet filtering for signal denoising and fuzzy clustering for features extraction and decision-making. The formation of a knowledge-base and its adaptation during the operation are also discussed.

Characteristics of microfiltration membranes in a membrane coupled sequencing batch reactor system

Factors affecting filtration performance were investigated in a sequencing batch reactor (SBR) coupled with a submerged microfiltration module. Special bioreactors for aerobic and anoxic phases were specifically designed in order to differentiate the effect of dissolved oxygen (DO) from that of mixing intensity, on membrane filterability. When the filterability of a submerged microfilter was examined at each SBR phase, DO concentration, as well as mixing intensity proved to have a major influence on the membrane performance regardless of the SBR phase. A higher DO concentration resulted in a slower rise in TMP, corresponding to less membrane fouling, which was investigated in depth through a series of analyses including resistance measurements and compressibility of the cake layer as well as particle sizes as a functions of DO for both aerobic and anoxic phases in SBR.