Application of Artificial Neural Network for predicting biomass growth during domestic wastewater treatment through a biological process.

The biological treatment process is responsible for removing organic and inorganic matter in wastewater. This process relies heavily on microorganisms to successfully remove organic and inorganic matter. The aim of the study was to model biomass growth in the biological treatment process. Multilayer perceptron (MLP) Artificial Neural Network (ANN) algorithm was used to model biomass growth. Three metrics: coefficient of determination (R 2), root mean squared error (RMSE), and mean squared error (MSE) were used to evaluate the performance of the model. Sensitivity analysis was applied to confirm variables that have a strong influence on biomass growth. The results of the study showed that MLP ANN algorithm was able to model biomass growth successfully. R 2 values were 0.844, 0.853, and 0.823 during training, validation, and testing phases, respectively. RMSE values were 0.7476, 1.1641, and 0.7798 during training, validation, and testing phases respectively. MSE values were 0.5589, 1.3551, and 0.6081 during training, validation, and testing phases, respectively. Sensitivity analysis results showed that temperature (47.2%) and dissolved oxygen (DO) concentration (40.2%) were the biggest drivers of biomass growth. Aeration period (4.3%), chemical oxygen demand (COD) concentration (3.2%), and oxygen uptake rate (OUR) (5.1%) contributed minimally. The biomass growth model can be applied at different wastewater treatment plants by different plant managers/operators in order to achieve optimum biomass growth. The optimum biomass growth will improve the removal of organic and inorganic matter in the biological treatment process.

Effect of dissolved gases on sonochemical oxidation in a 20 kHz probe system: Continuous monitoring of dissolved oxygen concentration and sonochemical oxidation activity.

Dissolved gases have a substantial influence on acoustic cavitation and sonochemical oxidation reactions. Little research on the changes in dissolved gases and the resultant changes in sonochemical oxidation has been reported, and most studies have focused only on the initial dissolved gas conditions. In this study, the dissolved oxygen (DO) concentration was measured continuously during ultrasonic irradiation using an optical sensor in different gas modes (saturation/open, saturation/closed, and sparging/closed modes). Simultaneously, the resulting changes in sonochemical oxidation were quantified using KI dosimetry. In the saturation/open mode using five gas conditions of Ar and O2, the DO concentration decreased rapidly when O2 was present because of active gas exchange with the atmosphere, and the DO concentration increased when 100% Ar was used. As a result, the order of the zero-order reaction constant for the first 10 min (k0-10) decreased in the order Ar:O2 (75:25) > 100% Ar ≈ Ar:O2 (50:50) > Ar:O2 (25:75) > 100% O2, whereas that during the last 10 min (k20-30) when the DO concentration was relatively stable, decreased in the order 100% Ar > Ar:O2 (75:25) > Ar:O2 (50:50) ≈ Ar:O2 (20:75) > 100% O2. In the saturation/closed mode, the DO concentration decreased to approximately 70-80% of the initial level because of ultrasonic degassing, and there was no influence of gases other than Ar and O2. Consequently, k0-10 and k20-30 decreased in the order Ar:O2 (75:25) > Ar:O2 (50:50) > Ar:O2 (25:75) > 100% Ar > 100% O2. In the sparging/closed mode, the DO concentration was maintained at approximately 90% of the initial level because of the more active gas adsorption induced by gas sparging, and the values of k0-10 and k20-30 were almost the same as those in the saturation/closed mode. In the saturation/open and sparging/closed modes, the Ar:O2 (75:25) condition was most favorable for enhancing sonochemical oxidation. However, a comparison of k0-10 and k20-30 indicated that there would be an optimal dissolved gas condition that was different from the initial gas condition. In addition, the mass-transfer and ultrasonic-degassing coefficients were calculated using changes in the DO concentration in the three modes.

Model-based strategy for nitrogen removal enhancement in full-scale wastewater treatment plants by GPS-X integrated with response surface methodology.

Model simulation is an effective approach to optimize the operational performance of wastewater treatment plants (WWTPs). This study presents a novel strategy to enhance the total nitrogen (TN) removal in WWTPs by GPS-X integrated with response surface methodology. The sensitivities of 61 parameters were screened and analyzed, and 6 critical parameters (i.e., µmax A, KA/a, µmax H, KH/ss, YH and µmaxPAO) were selected for further adjustment. The accuracy of GPS-X for WWTPs modeling was validated by static and dynamic simulations with actual operational data. The results showed that the DO concentration diffused in different biological compartments exhibited significant effects on the denitrification rate. The TN removal is also associated with SRT. The significance and optimization orders of key parameters were analyzed. With the optimization of DO in biological units and SRT, the nitrification and denitrification rates were improved to 97.1 and 85.3% respectively, saving 17.9% energy consumption.

Denitrification characterization of dissolved oxygen microprofiles in lake surface sediment through analyzing abundance, expression, community composition and enzymatic activities of denitrifier functional genes.

The responses of denitrifiers and denitrification ability to dissolved oxygen (DO) concent in different layers of surface lake sediments are still poorly understood. Here, the optimal denitrification condition was constructed based on response surface methodology (RSM) to analyze the denitrification characteristics of surface sediments. The aerobic zone (AEZ), hypoxic zone (HYZ), up-anoxic zone (ANZ-1) and sub-anoxic zone (ANZ-2) were partitioned based on the oxygen contents, and sediments were collected using a customized-designed sub-millimeter scale sampling device. Integrated real-time quantitative PCR, Illumina Miseq-based sequencing and denitrifying enzyme activities analysis revealed that denitrification characteristics varied among different DO layers. Among the four layers, the DNA abundance and RNA expression levels of norB, nirS and nosZ were the highest at the aerobic layer, hypoxic layer and up-axoic layer, respectively. The hypoxia and up-anaerobic layer were the active nitrogen removal layers, since these two layers displayed the highest DNA abundance, RNA expression level and enzyme activities of denitrification functional genes. The abundance of major denitrifying bacteria showed significant differences among layers, with Azoarcus, Pseudogulbenkiania and Rhizobium identified as the main nirS, nirK and nosZ-based denitrifiers. Pearson's correlation revealed that the response of denitrifiers to environmental factors differed greatly among DO layers. Furthermore, napA showed higher DNA abundance and RNA expression level in the aerobic and hypoxic layers than anaerobic layers, indicating that aerobic denitrifiers might play important roles at these layers.

Enhanced nitrogen removal of the simultaneous partial nitrification, anammox and denitrification (SNAD) biofilm reactor for treating mainstream wastewater under low dissolved oxygen (DO) concentration.

The simultaneous partial nitrification, anammox and denitrification (SNAD) process for treating mainstream wastewater was investigated under different intermittent aeration modes. By controlling the aeration time of 20, 60 and 180 min during the intermittent modes, the oxygen concentration remained 3.50, 1.45 and 0.70 mg·L-1. Correspondingly, the reactor achieved the nitrogen removal rate of 0.17, 0.29 and 0.30 kg N·m-3·d-1. Meanwhile, the average total inorganic nitrogen (TIN) removal efficiency reached 93.4%, 87.5% and 92.7%. The effluent NO3--N concentration was very low. High-throughput sequencing analysis indicated that the proportion of nitrite oxidization bacteria (NOB), anammox bacteria and denitrification bacteria was 0.15%, 0.33% and 8.78%. Candidatus Anammoxoglobus was the abundant anammox bacteria genus. Further study on the unclassified sequences revealed the possibility of the high relative abundance of Nitrosomonas-related genus and Candidatus Kuenenia-related genus on the SNAD biofilm.

[Operation of the AAO Process Under Low Dissolved Oxygen Conditions and Its Simulation].

The anaerobic-anoxic-oxic (AAO) process was used to investigate the variation of the parameters of water quality when the dissolved oxygen (DO) in the aerobic tank was controlled at a low concentration. The results indicated the system still had good phosphorus and nitrogen removal efficiencies when the DO concentration in the aerobic tank was decreased from 2.00 mg·L-1 to 1.00 mg·L-1 and 0.50 mg·L-1, and the effluent indexes could meet the first class A standard for the "discharge standard of pollutants for municipal wastewater treatment plant" (GB18918-2002) of China. The activated sludge model of the AAO process was developed by BioWin 4.1 software. The sensitivities of the model parameters were analyzed, and the model parameters, such as amount of polyhydroxyalkanoate (PHA) stored per unit of acetate or the propionate sequestered by phosphorus accumulating bacteria (YP/PHA,seq), the amount of phosphorus stored per unit of PHA oxidized in aerobic conditions by phosphorus accumulating bacteria (YP/PHA,aerobic), the maximum specific growth rate of ammonia oxidizing bacteria (µmax,A), and the maximum specific growth rate of nitrite oxidizing bacteria (µmax,N), were calibrated and validated by the dynamic simulation. In addition, the energy consumption of the aeration was simulated and evaluated. The results showed that when the DO concentration in the aerobic tank was decreased from 2.00 mg·L-1 to 1.00 mg·L-1 and 0.50 mg·L-1, the air flow could be reduced by 23.8% and 38.1%, and the oxygen transfer efficiency could be increased by 7.2% and 11.7%, respectively.

Total inorganic nitrogen removal during the partial/complete nitrification for treating domestic wastewater: Removal pathways and main influencing factors.

Achieving nitrite accumulation was considered as the prerequisite of ANAMMOX, which hindered the application of ANAMMOX. In this study, total inorganic nitrogen (TIN) removal during the partial/complete nitrification was studied in a lab-scale sequencing batch reactor (SBR) for treating domestic wastewater. The results showed TIN was removed by denitrification, ANAMMOX and N2O emission during the partial/complete nitrification. AOB, AOA, Nitrobacter (NB), Nitrospira (NS), AnAOB and DNB were coexisted in the partial/complete nitrification. The microbial competition among these functional communities determined the type of nitrification, TIN removal and pathways. Since low DO concentrations benefits Nitrospira growth, the partial nitrification was damaged. After long-term operation, AOB gradually accommodated the low DO concentration. When Vmax,AOB (the maximum specific reaction rate of AOB) higher than Vmax,NOB (the maximum specific reaction rate of NOB), a part of nitrite was reduced by DNB and AnAOB. Therefore, TIN was removed during the complete nitrification.

Nitrite accumulation performance of aerobic MBBR treating Lurgi coal gasification waste water by adjusting pollutant load and DO concentration.

An aerobic moving bed biofilm reactor (MBBR) was adopted to treat Lurgi coal gasification waste water (LCGW) in about 10 months. The pollutant load and dissolve oxygen (DO) concentration were adjusted by trying to maximize the accumulation of [Formula: see text] in the MBBR for LCGW treatment. The highest [Formula: see text] accumulation proportion [Formula: see text] was 73.9%, but was not stable with influent chemical oxygen demand (COD) and DO concentrations of around 1000 and 1.5 mg/L, respectively. Around 1500 mg/L of influent COD concentration and 1.5 mg/L of DO concentration were proper operation conditions for the aerobic MBBR to achieve relatively stable [Formula: see text] accumulation, with [Formula: see text] ratio at 53% and [Formula: see text] ratio at just 4.3% in the effluent. More specifically, free ammonia concentration and DO concentration affected [Formula: see text] accumulation much more obvious than phenols concentration. The activity and quantity of nitrifying bacteria growth in suspended sludge and biofilm of the MBBR were monitored simultaneously to explain the variations of [Formula: see text] accumulation performance under different operation conditions. An aerobic moving bed biofilm reactor (MBBR) was adopted to treat Lurgi coal gasification waste water (LCGW)in about 10 months. The pollutant load and dissolve oxygen (DO) concentration were adjusted by trying to maximize the accumulation of NO(−)(2)−N in the MBBR for LCGW treatment. The highest NO(−)(2)−N accumulation proportion(NO(−)(2)−Neffluent/TN effluent) was 73.9%, but was not stable with influent chemical oxygen demand (COD) and DO concentrations of around 1000 and 1.5 mg/L, respectively. Around 1500 mg/L of influent COD concentration and 1.5 mg/L of DO concentration were proper operation conditions for the aerobic MBBR to achieve relatively stable NO(−)(2)−N accumulation,with NO(−)(2)−N/TN ratio at 53% and NO(-)(3)−N/TN ratio at just 4.3% in the effluent. More specifically, free ammonia concentration and DO concentration affected NO(2)(−)N accumulation much more obvious than phenols concentration. The activity and quantity of nitrifying bacteria growth in suspended sludge and biofilm of the MBBR were monitored simultaneously toexplain the variations of NO(−)(2)−N accumulation performance under different operation conditions.