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The use of various advanced oxidation methods in the treatment of wastewater has become the subject of many studies published in recent years. In particular, it is exceedingly significant to compare these treatment methods for industrial wastewater to reduce environmental effects and optimize plant operations and economics. The present study is the first to deal with the treatability of real epoxy paint wastewater (EPW) using MW- and UV-assisted Fenton processes within an optimization framework. A three-factor, three-level Box–Behnken experimental design combined with response surface methodology (RSM) was conducted for maximizing the chemical oxygen demand (COD) and color removal efficiencies of ultraviolet (UV)/Fenton and microwave (MW)/Fenton processes in the treatment of the real epoxy paint wastewater (EPW, initial COD = 4600 ± 90 mg/L, initial color = 114 ± 4 Pt-Co), based on 15 different experimental runs. Three independent variables (reaction time ranging from 20 to 60 min (UV) and from 5 to 15 min (MW), power ranging from 20 to 40 W (UV) and from 300 to 600 W (MW), and H2O2/Fe2+ ratio ranging from 0.2 to 0.6 (for both UV and MW)) were consecutively coded as A, B, and C at three levels (−1, 0, and 1), and four second-order polynomial regression equations were then derived to estimate the responses (COD and color removals) of two distinct systems. The significance of the independent model components and their interrelations were appraised by means of a variance analysis with 99% confidence limits (α = 0.01). The standardized differences of the independent variables and the consistency between the actual and predicted values were also investigated by preparing normal probability residual plots and experiment-model plots for all processes. The optimal operating conditions were attained by solving the quadratic regression models and analyzing the surface and contour plots. UV/Fenton and MW/Fenton processes, which constitute combined Fenton processes, were performed using advanced oxidation methods, while Fenton processes were utilized as the standard method for wastewater treatment. When UV/Fenton and MW/Fenton processes were applied separately, the COD removal efficiencies were determined to be 96.4% and 95.3%, respectively. For the color parameter, the removal efficiencies after the application of both processes were found to exceed 97.5%. While these efficiencies were achieved in 1 h with a 38 W UV unit, they were achieved in 15 min with a MW power of 570 W. According to the RSM-based regression analysis results, the R2 values for both processes were greater than 0.97 and p values were less than 0.003. [ABSTRACT FROM AUTHOR]

This computational study explores the potential of several soft-computing techniques for wind turbine (WT) output power (kW) estimation based on seven input variables of wind speed (m/s), wind direction (°), air temperature (°C), pitch angle (°), generator temperature (°C), rotating speed of the generator (rpm), and voltage of the network (V). In the present analysis, a nonlinear regression-based model (NRM), three decision tree-based methods (random forest (RF), random tree (RT), and reduced error pruning tree (REPT) models), and multilayer perceptron-based soft-computing approach (artificial neural network (ANN) model) were simultaneously implemented for the first time in the prediction of WT output power (WTOP). To identify the top-performing soft computing technique, the applied models' predictive success was compared using over 30 distinct statistical goodness-of-fit parameters. The performance assessment indices corroborated the superiority of the RF-based model over other data-intelligent models in predicting WTOP. It was seen from the results that the proposed RF-based model obtained the narrowest uncertainty bands and the lowest quantities of increased uncertainty values across all sets. Although the determination coefficient values of all competitive decision tree-based models were satisfactory, the lower percentile deviations and higher overall accuracy score of the RF-based model indicated its superior performance and higher accuracy over other competitive approaches. The generator's rotational speed was shown to be the most useful parameter for RF-based model prediction of WTOP, according to a sensitivity study. This study highlighted the significance and capability of the implemented soft-computing strategy for better management and reliable operation of wind farms in wind energy forecasting. [ABSTRACT FROM AUTHOR]

The study investigated the pretreatment of real paracetamol (PCT) wastewater of a pharmaceutical industry by Fenton process. At the best experimental conditions (COD/H2O2 = 1/1, Fe+2/H2O2 = 1/70, settling method:centrifuging, pH 6 at settling step), 92.7, 92.7, 95.5, 99.1, 99.9 and 99.4% of chemical oxygen demand (COD), total organic carbon (TOC), 5-day biological oxygen demand (BOD5), PCT, para-amino phenol (PAP) and aniline were removed, respectively. Changes in the concentrations of these parameters were also investigated for both oxidation and settling steps of Fenton process. It was found that COD and TOC were removed at the settling step (precipitation) whereas PCT, PAP and aniline were removed at the oxidation step. Mass balance calculations were also studied to show the mass distributions of COD in different phases (gas + foam, effluent and sludge). Fenton process was found as an effective method for the pretreatment of real PCT wastewater for discharging in a determined collective treatment plant.

The operation conditions for the implementation of the Fenton process are of utmost importance because there are problems related to the proportion of H2O2 dosage to COD and Fe2+ dosage to the specified H2O2 amount. The relevant lite-rature shows that COD/H2O2 ratios range between 0.0084 and 113.9. Similarly, the COD/Fe2+ ratio varies between 0.079 and 292.6, while the H2O2/Fe2+ ratio varies between 0.09 and 287. Moreover, the ratio of the maximum value to the minimum value used in the operations on the basis of COD is 13560 for COD/ /H2O2 (0.0084-113.9), 2210 for COD/Fe2+ (0.079-174.7), and finally 3190 for H2O2/Fe2+ (0,09-287). The aim of this study was to re-evaluate these values that significantly differ from each other with specific emphasis on textile wastewater and considering stoichiometric ratios. Results showed that values ranging between 0.43 and 4.0 for COD/H2O2 and those ranging between 0.75 and 3.0 for H2O2/Fe2+ are more suitable. The results showed that in a Fenton process con-ducted by dosing H2O2 at different times, the TOC reduction efficiencies inc-reased from 80.8 up to 88.9%. Similarly, the color reduction efficiency also rose from 96.5 to 98.7%. This article has been corrected. Link to the correction 10.2298/CICEQ170425016E

A high pH, low solubility of bound plant nutrients, and negative impacts on microbial communities are common drawbacks of biomass ash (BA) vermicomposting. In this study, nutrient-rich BA mixed with cow manure was tested at three different application rates to obtain final nitrogen (N), phosphorus (P), and potassium (K) contents of 3.5%, 7.0%, and 10.0% for bio-based fertilizers via vermicomposting. The results showed that all BA blends made with cow manure increased fermentation temperatures and allowed successful worm activity during the subsequent vermicomposting phase. The order of indicator enzyme activities in all vermicomposting samples was urease (220 μg NH4 g−1 h−1) > β-glucosidase (95 μg PNP g−1 h−1) > alkaline phosphatase (91 μg PNP g−1 h−1) > arylsulfatase (83 μg PNP g−1 h−1) > acid phosphatase (60 μg PNP g−1 h−1). As an indicator of nutrient bioavailability, high correlations were observed between enzyme activities and microbial diversity in vermicompost samples. Determination coefficients (R2) obtained from multiple linear regressions between enzyme activities and bacterial population for T0, T1, T2, and T3 were determined as 0.90, 0.65, 0.73, and 0.90, respectively. According to a novel metagenome-based approach proposed within the scope of the present study, the stimulatory effects of Flavobacteriales, Burkholderiales, Saccharimonadales, and Pseudomonadales on enzyme activities for the nutrient solubility were found to be significant and positive. The findings of this study demonstrated that worm composting could be a sustainable bio-based technology for the production of slow-release fertilizer from nutrient-rich waste material. [ABSTRACT FROM AUTHOR]