Effluent parameters prediction of a biological nutrient removal (BNR) process using different machine learning methods: A case study.

This paper proposes a novel targeted blend of machine learning (ML) based approaches for controlling wastewater treatment plant (WWTP) operation by predicting distributions of key effluent parameters of a biological nutrient removal (BNR) process. Two years of data were collected from Plajyolu wastewater treatment plant in Kocaeli, Türkiye and the effluent parameters were predicted using six machine learning algorithms to compare their performances. Based on mean absolute percentage error (MAPE) metric only, support vector regression machine (SVRM) with linear kernel method showed a good agreement for COD and BOD5, with the MAPE values of about 9% and 0.9%, respectively. Random Forest (RF) and EXtreme Gradient Boosting (XGBoost) regression were found to be the best algorithms for TN and TP effluent parameters, with the MAPE values of about 34% and 27%, respectively. Further, when the results were evaluated together according to all the performance metrics, RF, SVRM (with both linear kernel and RBF kernel), and Hybrid Regression algorithms generally made more successful predictions than Light GBM and XGBoost algorithms for all the parameters. Through this case study we demonstrated selective application of ML algorithms can be used to predict different effluent parameters more effectively. Wider implementation of this approach can potentially reduce the resource demands for active monitoring the environmental performance of WWTPs.

Atmospheric plasma-based approaches for the degradation of dimethyl phthalate (DMP) in water.

Cold plasma based treatment of contaminated water is becoming a promising novel green remediation option. This study assessed the performance of two different cold plasma reactors, using, respectively, a self-pulsing discharge (SPD) and a multipin corona discharge (MCD), in the degradation of dimethyl phthalate (DMP), a persistent and ubiquitous pollutant of the aquatic environment. The process kinetics and energy efficiency, as well as the main plasma generated reactive species were determined under various operating conditions concerning the plasma feed gas and flowrate, the voltage polarity, the input power, the DMP initial concentration, the liquid conductivity, and the aqueous matrix used to prepare DMP solutions for these experiments. The MCD reactor, operated with air as plasma feed gas and negative voltage polarity, gave the best results in terms of rate and energy efficiency. Moreover, variations in plasma input power and in the liquid conductivity have limited effect on DMP degradation rate, making this reactor suitable for treating liquids with a range of initial conductivities The effects of DMP initial concentration on its rate of degradation and on the process energy efficiency were also investigated. Differences in the efficiency of production and distribution of plasma generated reactive species, notably •OH and H2O2, observed for the two tested reactors are discussed in terms of different extension of the plasma/liquid interface and diffusion into the bulk solution. It is proposed that among the reactive species, •OH foremost, and O3 to a lesser extent, play a pivotal role in DMP degradation, while the contribution of H2O2 appears to be limited. The rate of DMP degradation was not drastically different in Milli-Q water and in tap water, a positive outcome in view of practical applications of the technology. The lower rate observed in tap than in Milli-Q water is attributed to the presence of bicarbonate and carbonate, which are known scavengers of hydroxyl radicals.

Electrochemically activated persulfate and peroxymonosulfate for furfural removal: optimization using Box-Behnken design.

Furfural removal by electrochemically activated peroxydisulfate (E-PS) and peroxymonosulfate (E-PMS) was investigated. The effect of different anodes was investigated for the electrochemical activation of oxidants. Box Behnken Design was applied to determine optimum operating conditions, which were determined as follows; PS concentration: 2.3 mM, applied current: 1.15 A, pH: 3.5, and reaction time: 118.3 min for E-PS process; PMS concentration: 1.8 mM, applied current: 1.05 A, pH: 3.3, and reaction time: 107.8 min for E-PMS process. The results of the study showed that the E-PMS process is more advantageous in terms of the chemical and electricity costs to be used.

Degradation of oxytetracycline in aqueous solution by heat-activated peroxydisulfate and peroxymonosulfate oxidation.

Oxytetracycline (OTC) is a broad-spectrum antibiotic that resists biodegradation and poses a risk to the ecosystem. This study investigated the degradation of OTC by heat-activated peroxydisulfate (PDS) and peroxymonosulfate (PMS) processes. Response surface methodology (RSM) was used to evaluate the effect of process parameters, namely initial pH, oxidant concentration, temperature, and reaction time on the OTC removal efficiency. According to the results of the RSM models, all four independent variables were significant for both PDS and PMS processes. The optimum process parameters for the heat-activated PDS process were pH 8.9, PDS concentration 3.9 mM, temperature 72.9°C, and reaction time 26.5 min. For the heat-activated PMS process, optimum conditions were pH 9.0, PMS concentration 4.0 mM, temperature 75.0°C, and reaction time 20.0 min. The predicted OTC removal efficiencies for the PDS and PMS processes were 89.7% and 84.0%, respectively. As a result of the validation experiments conducted at optimum conditions, the obtained OTC removal efficiencies for the PDS and PMS processes were 87.6 ± 4.2 and 80.2± 4.6, respectively. PDS process has higher kinetic constants at all pH values than the PMS process. Both processes were effective in OTC removal from aqueous solution and RSM was efficient in process optimization.

Biodegradation of Emerging Pharmaceuticals from Domestic Wastewater by Membrane Bioreactor: The Effect of Solid Retention Time.

Although conventional biological treatment plants can remove basic pollutants, they are ineffective at removing recalcitrant pollutants. Membrane bioreactors contain promising technology and have the advantages of better effluent quality and lower sludge production compared to those of conventional biological treatment processes. In this study, the removal of pharmaceutical compounds by membrane bioreactors under different solid retention times (SRTs) was investigated. To study the effect of SRT on the removal of emerging pharmaceuticals, the levels of pharmaceuticals were measured over 96 days for the following retention times: 20, 30, and 40-day SRT. It was found that the 40-day SRT had the optimum performance in terms of the pharmaceuticals' elimination. The removal efficiencies of the chemical oxygen demand (COD) for each selected SRT were higher than 96% at steady-state conditions. The highest degradation efficiency was observed for paracetamol. Paracetamol was the most removed compound followed by ranitidine, atenolol, bezafibrate, diclofenac, and carbamazepine. The microbial community at the phylum level was also analyzed to understand the biodegradability of pharmaceuticals. It was noticed that the Proteobacteria phylum increased from 46.8% to 60.0% after 96 days with the pharmaceuticals. The Actinobacteria class, which can metabolize paracetamol, carbamazepine, and atenolol, was also increased from 9.1% to 17.9% after adding pharmaceuticals. The by-products of diclofenac, bezafibrate, and carbamazepine were observed in the effluent samples.

Borohydride method modification in synthesizing nano zero valent iron and its application in DDT removal.

Among the methods used in the literature for the synthesizing of nano zero valent iron (nZVI), borohydride is the most commonly used method; it is seen that different variables are used together. In this study, optimum nano zero valent iron (nZVI) synthesizing method using borohydride method has been modified by using multiple optimization method in terms of both particle size and zeta potential. Selected independent variables are selected as iron sulfate concentration, ethanol ratio, and flow rate of borohydride solution. With the optimum synthesis method determined, the lowest particle size was obtained as 70 nm only when the particle size was taken into consideration, whereas 88.2 nm nZVI could be produced when both the particle size and the zeta potential were taken into consideration. In addition, the removal of DDT, which is the most commonly used persistent organic pollutant pesticides in the world, was investigated by nZVI synthesized. Different initial DDT concentration was investigated by expressing oxidation reduction potential (ORP) difference, removal rates, and oxidation byproducts. When DDD and DDE concentrations are considered, it is found that DDT is more likely to oxidize in DDD in all studied initial DDT concentrations. Removal rate was higher than 80% with initial concentrations lower than 125 µg/L, which is a high concentration that could be found in surface waters.