IOT Based Smart Wastewater Treatment Model for Industry 4.0 Using Artificial Intelligence

Due to the population growth and reduction of water resources, wastewater treatment and reuse vital. As the secondary wastewater treatment processes enable removes a significant amount of P and N, nutrient-rich effluents can cause eutrophication in water bodies. On the other hand, nutrients removal in sewage treatment using mechanical methods is costly and complex. The aquaculture method using Azolla filiculoides could be an appropriate option for removing total phosphorus (TP), total nitrogen (TN), and chemical oxygen demand (COD) from wastewater. Synthetic wastewater has been prepared in the typical range of municipal wastewater. Two g fresh weight of an acclimatized A.filiculoides was floated in sample bowls each one containing 500 CC prepared wastewater. Total nitrogen, TP, and COD removal by Azolla filiculoides for 21-days were optimized and investigated using the response surface methodology (RSM). For this aim, the D-optimal method was used to optimize the three independent variables (TP concentration (10.8-84.6mg l- 1), TN concentration (20-99mg l- 1), and COD concentration (66.26-415mg l- 1)) for their maximum removal efficiency of them. Experiments were performed on 28 runs in which independent variables were measured using a HACH DR 5000 spectrometer. Predicted R-squared for COD, TP, TN removal, and Azolla mass (responses) have been equal to -0.0897, 0.8514, 0.7779, and 0.5645, respectively. The model was used to maximize Azolla growth and maximize removal efficiency of nitrogen, phosphorus, and COD that occurred in minimum concentrations of TN (20mg l- 1), TP (10.8mg l- 1), and COD (66.26mg l- 1). The removal efficiency of Azolla was obtained 77.5 % for COD, 66.8 % for TP, and 78.1 % for TN in the optimum condition of independent variables. Also, increase of Azolla mass was 239 %, with desirability of 0.66. The difference between model prediction and model validation testing for Azolla mass increase, COD, TN, and TP removal was equal to ± 11.6 %, ± 7.9 %, ± 0.0 %, and ± 1.9 %, respectively. Azolla could remove phosphorus in nitrogen deficiency or even lack of nitrogen. Results indicate that removal efficiency has an upward trend as the Azolla growth increases. This kind of fern has a significant effect on removing nitrogen, phosphorus, and COD from an aqueous solution. The removal efficiency of TN, TP, and COD at optimum operating conditions showed good agreement with model-predicted removal efficiency.

BACKGROUND: This study considers batch treatment of saline wastewater in an upflow anaerobic packed bed reactor by salt tolerant anaerobic organisms Halanaerobium lacusrosei.RESULTS: The effects of initial chemical oxygen demand (COD) concentration (COD0 = 1880–9570 mg L−1), salt concentration ([NaCl] = 30–100 g L−1) and liquid upflow velocity (Vup = 1.0–8.5 m h−1) on COD removal from salt (NaCl)‐containing synthetic wastewater were investigated. The results indicated that initial COD concentration significantly affects the effluent COD concentration and removal efficiency. COD removal was around 87% at about COD0 = 1880 mg L−1, and efficiency decreased to 43% on increasing COD0 to 9570 mg L−1 at 20 g L−1 salt concentration. COD removal was in the range 50–60% for [NaCl] = 30–60 g L−1 at COD0 = 5200 ± .100 mg L−1. However, removal efficiency dropped to 10% when salt concentration was increased to 100 g L−1. Increasing liquid upflow velocity from Vup = 1.0 m h−1 to 8.5 m h−1 provided a substantial improvement in COD removal. COD concentration decreased from 4343 mg L−1 to 321 mg L−1 at Vup = 8.5 m h−1, resulting in over 92% COD removal at 30 g L−1 salt‐containing synthetic wastewater.CONCLUSION: The experimental results showed that anaerobic treatment of saline wastewater is possible and could result in efficient COD removal by the utilization of halophilic anaerobic bacteria. Copyright © 2008 Society of Chemical Industry

In this work, the performance of a sequencing batch reactor (SBR) was studied for treating sanitary wastewater of Yazd power plant, Iran. For this purpose, at the first, a pilot system was designed, installed, and started up. Then the effects of retention time, pH, temperature, influent chemical oxygen demand (COD) concentration, and air flow rate were investigated on the effluent concentration of COD. In SBR reactor used in the Yazd power plant, the microalga was not used for the wastewater treatment. In this case, the COD effluent output was, at the best conditions, approximately 92 mg/L. In the studied SBR system, we used the Chlorella vulgaris microalgae and microorganisms, simultaneously. In this case, the COD level reached 34 mg/L. An artificial neural network (ANN) was developed by applying Levenberg‐Marquardt training algorithm to predict the effluent concentration of COD. The optimum conditions were obtained at pH = 8, temperature of 30°C, influent COD concentration of 600 mg/L, and air flow rate of 50 L/min. ANN predicted results were in good agreement with the experimental data with a validation coefficient of determination (R2) and validation mean square error of 0.962 and 0.0015, respectively.

Treatment of domestic wastewater using microbial fuel cells (MFCs) will require reactors with multiple electrodes, but this presents unique challenges under continuous flow conditions due to large changes in the chemical oxygen demand (COD) concentration within the reactor. Domestic wastewater treatment was examined using a single-chamber MFC (130mL) with multiple graphite fiber brush anodes wired together and a single air cathode (cathode specific area of 27m(2)/m(3)). In fed-batch operation, where the COD concentration was spatially uniform in the reactor but changed over time, the maximum current density was 148 ± 8mA/m(2) (1,000Ω), the maximum power density was 120mW/m(2), and the overall COD removal was >90%. However, in continuous flow operation (8h hydraulic retention time, HRT), there was a 57% change in the COD concentration across the reactor (influent versus effluent) and the current density was only 20 ± 13mA/m(2). Two approaches were used to increase performance under continuous flow conditions. First, the anodes were separately wired to the cathode, which increased the current density to 55 ± 15mA/m(2). Second, two MFCs were hydraulically connected in series (each with half the original HRT) to avoid large changes in COD among the anodes in the same reactor. The second approach improved current density to 73 ± 13mA/m(2). These results show that current generation from wastewaters in MFCs with multiple anodes, under continuous flow conditions, can be improved using multiple reactors in series, as this minimizes changes in COD in each reactor.

The coinage refractory wastewater treated by electrocatalytic-membrane process (ECMP) integrated with chemical- or electro-coagulation techniques

Enhanced treatment of landfill leachate wastewater using sono(US)-ozone(O3)–electrocoagulation(EC) process: role of process parameters on color, COD and electrical energy consumption

Grey and neural network prediction of suspended solids and chemical oxygen demand in hospital wastewater treatment plant effluent

A novel laboratory bench-scale sequencing batch biofilm reactor (SBBR) system was developed for the treatment of synthetic domestic strength wastewater, comprising two side-by-side 18 l reactor tanks, each containing a plastic biofilm media module. Aerobic and anoxic conditions in the biofilms were effected by intermittent alternate pumping of wastewater between the two reactors. With a media surface area loading rate of 4.2 g chemical oxygen demand (COD)/m2.d, the average influent COD, total nitrogen (TN) and ammonium-nitrogen (NH4-N) concentrations of 1021 mg/l, 97 mg/l and 54 mg/l, respectively, reduced to average effluent concentrations of 72 mg COD/l, 17.8 mg TN/l, and 5.5 mg NH4-N /l. Using a similar alternating biofilm exposure arrangement, a 16 person equivalent pilot (PE) plant was constructed at a local village treatment works to remove organic carbon from highly variable settled municipal wastewater and comprised two reactors, one positioned above the other, each containing a module of cross-flow plastic media with a surface area of 100 m2. Two different pumping sequences (PS) in the aerobic phase were examined where the average influent COD concentrations were 220 and 237 mg/l for PS1 and PS2, respectively, and the final average effluent COD was consistently less than 125 mg/l--the European Urban Wastewater Treatment Directive limit--with the best performance occurring in PS1. Nitrification was evident during both PS1 and PS2 studies. A 300 PE package treatment plant was designed based on the bench-scale and pilot-scale studies, located at a local wastewater treatment works and treated municipal influent with average COD, suspended solids (SS) and TN concentrations of 295, 183 and 15 mg/l, respectively resulting in average effluent concentrations of 67 mg COD/l, 17 mg SS/l and 9 mg TN/l. The SBBR systems performed well, and were simple to construct and operate.

Sonophotocatalytic treatment of AB113 dye and real textile wastewater using ZnO/persulfate: Modeling by response surface methodology and artificial neural network

Effect of nitrate on electricity generation in single-chamber air cathode microbial fuel cells

In this research, performance of continuous electrocoagulation/flotation (ECF) process in treating compost leachate, a complex structure and high pollutant load, has been investigated. The effects of initial chemical oxygen demand (COD) concentration, voltage, hydraulic retention time (HRT), and electrode distance (ED) on COD and total suspended solid (TSS) removals were surveyed. The comparison results among some initial batch experiments for various configurations (Al–Al, Al–Fe, Fe–Fe, and Fe–Al) showed that Al–Al bears higher COD and TSS removals. The variables’ interactive effects on COD and TSS removal efficiency in continuous runs for Al–Al configuration were analyzed and correlated by response surface methodology (RSM). Ultimately, experimental results analysis showed that continuous ECF could effectively reduce COD and TSS by 96 and 99 %, respectively, at the optimum conditions of influent COD 13,600 mg/L, voltage 19 V, HRT 75 min, and ED 3 cm. Confirmation tests showed 95 % confidence interval for reasonable agreement of the predicted values from fitted correlations and experimental results. Also, according to outcomes analysis, COD concentration and HRT were, respectively, the most effective items for both COD and TSS removals. Observations showed that applied continuous ECF could efficiently satisfy direct discharge standards at optimal and controlled conditions.

Side-by-side comparison of horizontal subsurface flow and free water surface flow constructed wetlands and artificial neural network (ANN) modelling approach

The management of excess activated sludge imposes great cost on wastewater treatment plants and represents significant technical challenges. This paper investigates a new technology, sonication and cryptic growth, to reduce the amount of excess sludge from the wastewater treatment system. Subsequent Biological Reactors (SBRs) were used for the study. The results show that the amount of excess sludge could be reduced by 58.8%. The optimal sludge sonication ratio was 1/7, the ultrasonic intensity was 1.6 W/mL, the irradiation time was 15 min and the ultrasonic frequency was 25 kHz. The SBR sludge characteristics, settlability, activity, size and organic content, were stable. The effluent Chemical Oxygen Demand (COD) and Total Nitrogen (TN) concentrations were stable. However, increase in phosphorus concentration in the effluent was observed.

The microbial community diversity in anaerobic-, anoxic- and oxic-biological zones of a conventional Carrousel oxidation ditch system for domestic wastewater treatment was systematically investigated. The monitored results of the activated sludge sampled from six full-scale WWTPs indicated that Proteobacteria, Chloroflexi, Bacteroidetes, Actinobacteria, Verrucomicrobia, Acidobacteria and Nitrospirae were dominant phyla, and Nitrospira was the most abundant and ubiquitous genus across the three biological zones. The anaerobic-, anoxic- and oxic-zones shared approximately similar percentages across the 50 most abundant genera, and three genera (i.e. uncultured bacterium PeM15, Methanosaeta and Bellilinea) presented statistically significantly differential abundance in the anoxic-zone. Illumina high-throughput sequences related to ammonium oxidizer organisms and denitrifiers with top50 abundance in all samples were Nitrospira, uncultured Nitrosomonadaceae, Dechloromonas, Thauera, Denitratisoma, Rhodocyclaceae (norank) and Comamonadaceae (norank). Moreover, environmental variables such as water temperature, water volume, influent ammonium nitrogen, influent chemical oxygen demand (COD) and effluent COD exhibited significant correlation to the microbial community according to the Monte Carlo permutation test analysis (p < 0.05). The abundance of Nitrospira, uncultured Nitrosomonadaceae and Denitratisoma presented strong positive correlations with the influent/effluent concentration of COD and ammonium nitrogen, while Dechloromonas, Thauera, Rhodocyclaceae (norank) and Comamonadaceae (norank) showed positive correlations with water volume and temperature. The established relationship between microbial community and environmental variables in different biologically functional zones of the six representative WWTPs at different geographical locations made the present work of potential use for evaluation of practical wastewater treatment processes.

A simple method based on the mathematical treatment of spectral absorbance profiles in conjunction with artificial neural networks (ANNs) is demonstrated for rapidly estimating chemical oxygen demand (COD) values of wastewater samples. In order to improve spectroscopic analysis and ANN training time as well as to reduce the storage space of the trained ANN algorithm, it is necessary to decrease the ANN input vector size by extracting unique characteristics from the raw input pattern. Key features from the spectral absorbance pattern were therefore selected to obtain the spectral absorbance profile, reducing the ANN input vector from 160 to 10 selected inputs. The results indicate that the COD values obtained from the selected absorbance profiles agreed well with those obtained from the entire absorbance pattern. The spectral absorbance profile technique was also compared to COD values estimated by a multiple linear regression (MLR) model to validate whether ANNs were better and more robust models for rapid COD analysis. It was found that the ANN model predicted COD values closer to standard COD values than the MLR model.