Predicting quality parameters of wastewater treatment plants using artificial intelligence techniques

Foi obtido o balanço de massa, a partir dos valores médios das determinações de demanda química de oxigênio (DQO) e produção de metano (CH4), em dois reatores UASB de bancada com volume de 10,5 L tratando águas residuárias de suinocultura, submetidos a condições operacionais distintas no que diz respeito às concentrações de sólidos suspensos totais do afluente (SST de 500; 1.000; 1.500 e 2.000 mg L-1), tempo de detenção hidráulica (TDH de 30; 20; 12 e 8 h), taxas de carregamento orgânico volumétrico (TCOV de 0,8 a 8,0 kg DQO total (m³ d)-1) e temperatura (ambiente e controlada a 25º e 30ºC). Verificou-se que a DQO total removida convertida em CH4 variou de 28 a 51% e a relação DQO-CH4 por DQO dissolvida removida de 0,94 a 2,07; indicando alta participação da remoção física dos sólidos do afluente, de 49 a 72%, na remoção de DQO total nos reatores, a qual variou de 75 a 92%. A concentração de SST do afluente, a temperatura, o TDH e a TCOV influenciaram nesse desempenho dos reatores UASB.

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.

It is known that hydrogen peroxide interferes with chemical oxygen demand analysis by consuming oxidation agents such as potassium dichromate, thus leading to overestimation of the chemical oxygen demand measurements. The objective of the study was to investigate the effects of hydrogen peroxide interference and to determine true chemical oxygen demand values on interpreting treatment performance during ozone-based advanced oxidation of livestock wastewater in which hydrogen peroxide concentration and chemical oxygen demand values are dynamically changing. According to the chemical oxygen demand monitoring data, chemical oxygen demand values were always higher than the initial chemical oxygen demand load when hydrogen peroxide was involved and the treatment performance with ozone alone or ozone/ultraviolet was better than with coupled hydrogen peroxide. The extent of overestimation was proportional to the remaining hydrogen peroxide concentration and the average overestimation ratio in livestock wastewater was in the range of 0.50~0.58 mg per 1 mg of hydrogen peroxide, depending upon the quality of the wastewater treated. True chemical oxygen demand values were estimated by correlating the extent of overestimation with the remaining hydrogen peroxide concentration during treatment. The extent of overestimation decreased to zero gradually as the amount of hydrogen peroxide also approached zero as oxidation proceeded. The corrected chemical oxygen demand values indicated underlying tendency of oxidation, which could not be seen in the original chemical oxygen demand monitoring data. Application of ozone/hydrogen peroxide was more efficient for reducing chemical oxygen demand than ozone alone, as was ozone/hydrogen peroxide/ultraviolet compared to ozone/ultraviolet. When coupled with ozone, ultraviolet irradiation was more efficient than hydrogen peroxide for decreasing chemical oxygen demand during treatment of livestock wastewater.

[Introduction]: Vinasse is generated as a residue in the production of ethanol by fermentation-distillation of molasses/sugar cane juice, at a rate of 13 L/L of ethanol. It is an acid liquid, brown in color, characterized by high mineralization and Chemical Oxygen Demand (COD) values of up to 150 000 mg/L, being highly polluting. [Objective]: The objective of this research was to evaluate a vinasse treatment process with hydrogen peroxide as a source of hydroxyl radicals at laboratory scale. [Methodology]: The vinasse samples, from different distilleries in the province of Tucumán, were characterized following standardized techniques of Standard Methods. The oxidation tests were carried out with different peroxide/vinasses ratios, in a semi-batch reactor, under ambient conditions, measuring COD as an indicator parameter of the treatment. [Results]: After 5 days, an 85 % decrease in COD and an increase in the Biodegradability Index were achieved. The kinetics of the oxidative reaction was first order with respect to COD, with an apparent rate constant of 0.3694 1/day. [Conclusions]: Although the COD values allowed by local regulations (250 mg/L) were not reached, the proposed treatment is encouraging due to its simplicity, representing a potential option to the environmental challenge represented by vinaze in Latin America.

Super learner ensemble model: A novel approach for predicting monthly copper price in future

To investigate the potential pollution risk of permeable brick paving systems in areas with high groundwater levels, a system was constructed by using ceramic permeable bricks as the surface and a Chinese character “well”-shaped frame as the base on the top of a 1.0 m clay layer. The concentrations of total suspended solids (TSS), total phosphorus (TP), ammonia nitrogen (NH4+-N), total nitrogen (TN), chemical oxygen demand (COD), and heavy metals (Zn, Cu, and Pb) at different underground depths were measured, the potential pollution of the groundwater was assessed, and the effectiveness of the fillers inside the frame for improving the quality of the groundwater was discussed. The results showed that NH4+-N and COD concentrations detected at the depth of 0.6 m were higher than that of the national standard for groundwater (GBT14848-2017), these two pollutants had the potential pollution risk. The pollution risk by heavy metals was comparatively low because most of the heavy metals were likely retained in the surface soil by adsorption, complexation, and precipitation, while the pollution risk by TSS and TP was negligible due to the good purification ability in the clay layer. The results suggest that the removal rates of TSS, TP, TN, COD, and heavy metals can be improved by appropriate fillers’ adjustment, such as iron filings, coal slag, or volcanic rocks. This research offers a new perspective on the potential risk of pollution and the governance of groundwater.

Used fixing reagent, from X-ray laboratories of hospitals is often contaminated with numerous chemicals. Silver (Ag (I)) ion is the major contaminant present in used fixing reagent. This work determined the Ag (I) ion and chemical oxygen demand (COD) in used fixing reagent of X-ray laboratory. The removal of Ag (I) ion was done by electrolysis and followed with the adsorption onto crab shell chitosan (CSC) and black rice husk ash (BRHA). The Ag (I) ions in an used fixing reagent was analyzed by flame atomic absorption spectrophotometry (FAAS) at λ = 540 nm. The COD was measured by reflux technique and the results indicated that the initial concentrations of Ag (I) ions and COD values were 5,634.66 ± 179.74 mg L-1 and 182,821.28 ± 5759.04 mg L-1, respectively. The optimum voltage and time for electrolysis were 2 volts and 10 hrs. After the electrolysis had been done, 82.28% of the Ag (I) ions were removed, while the COD was reduced by 51.76%. After the adsorption experiment was applied, 72.16% of the Ag (I) ions were adsorbed onto CSC and 51.83%. onto BRHA. The COD was reduced 37.04% and 34.08% by CSC and BRHA, respectively. Therefore, these two techniques, electrolysis and adsorption, are appropriated techniques for Ag (I) ions recovery and the COD reduction of the used fixing reagent discharged from X-ray laboratories.

The problem of agricultural pesticide utilization in the Arab countries is not only an issue of uncontrolled use, but it is also a problem pertaining to the handling, misuse and disposal of unwanted pesticides. Electrochemical measurements were performed using a computer controlled by Potentiostat/Galvanostat model PGZ 100 associated to ‘‘Volta-Master 4’’ software. The chemical oxygen demand (COD) is measured according to the standard methods for examination of water and wastewater. The COD values were determined by the open reflux, with dichromate titration method. All measurements were repeated in triplicate and all results were observed to be repeatable within a 5 % margin of experimental error. Kinetic studies were carried out to determine the COD reduction efficiency for electrooxidation pesticides at different supporting electrolytes. For this purpose, the removal rate of COD was assumed to obey a first-order kinetic as follows. The influence of the current density on the COD removal during the electrochemical oxidation of pesticide Azoxystrobin was 40 mg L -1 at the BDD anode.

The present work is a study of the performance and effect of operational parameters on biohydrogen production from palm oil mill effluent by dark fermentation in batch mode. The process parameters examined are pH (5, 5.5, and 6), temperature (30, 35, and 40 °C), substrate concentration (5000, 12 500, and 20 000 mg L−1) and inoculum volume (20, 25, and 30 mL). The inoculum concentration prepared was 10 000 mg L−1 volatile suspended solids. The experiments were designed by response surface methodology (RSM). The highest chemical oxygen demand (COD) removal, hydrogen percentage (H2%) and hydrogen yield (HY) obtained were 58.3%, 80%, and 4.83 mol H2/mole of COD consumed, respectively. Based on the experimental data obtained with the RSM design, gene expression programming (GEP) was developed to predict the COD removal, hydrogen production, and hydrogen yield as process responses. The projected models were assessed based on the correlation coefficient (R2), root mean square error, mean absolute relative error, scatter index, and BIAS. The results demonstrate that the GEP model outperformed the RSM model and was superior in predicting the response variables. Partial derivative sensitivity analysis was also employed to assess the effect of each variable on COD%, H2%, and HY prediction. The prediction uncertainty for COD%, H2%, and HY was quantified, and the results were ±0.11, ±0.17, and 0.015, respectively. According to the results, the GEP model is more efficient than the RSM model in predicting the experimental data for biological hydrogen production in the dark fermentation process.

A study was conducted to characterize Modjo tannery effluent (wastewater) and determine its impact on the Modjo River using some physicochemical parameters. Accordingly, three tannery wastewater samples along wastewater channel at different distances have been taken and three river water samples (one upstream and two downstream) were collected along the river to determine its impact on the river. The samples have been analyzed for temperature, pH, electrical conductivity (EC), total dissolved solids (TDS), total suspended solid (TSS), chloride(Cl﹣), biological oxygen demand (BOD5), chemical oxygen demand (COD), total ammonia (as N), total nitrogen, total phosphorus and sulphide. The result of tannery wastewater showed that the values of temperature, pH, EC, TDS, TSS, Cl﹣, BOD5, COD, total ammonia, total nitrogen, total phosphorus and sulphide along the wastewater channel ranged from 26.97℃ to 24.93℃, 9.33 to 8.33, 15,670.00 to 14,496.67 mg·L﹣1, 9370.00 to 8723.33 mg·L﹣1, 4979.33 to 2647.67 mg·L﹣1, 6111.67 to 5555.78 mg·L﹣1 , 960.34 to 842.00 mg·L﹣1, 2011.00 to 1950.75 mg·L﹣1, 520.44 to 401.23 mg·L﹣1, 720.46 to 665.43 mg·L﹣1, 30.12 to 19.55 mg·L﹣1, 35.56 to 21.05 mg·L﹣1 respectively. And most of the effluent characteristics except pH and temperature were beyond the provisional discharge limit of tannery effluent to water body set by the Ethiopian Environmental Protection Authority (EEPA) and Federal Environmental Protection Agency (FEPA). Analysis of variance (ANOVA) also showed that variation among sampling points was statistically significant (p < 0.5). Similarly the levels of all these physicochemical parameters in the downstream site of the river were higher as compared to the values obtained from the upstream site (control). This indicated that the downstream site of the river was polluted as the result of the direct discharge of the tannery effluent to it.

Typically, the industrial evaporation process is operated at a high evaporation rate in a nonequilibrium stable or dynamic state within a temperature range of 323 to 393 K. During this process, both the solubility and the crystallization of salt are affected by organic impurities in the system. In this work, glutaraldehyde, one of the main organic compounds in wastewater produced from the coal chemical, was selected as a representative organic impurity, and the chemical oxygen demand (COD) of glutaraldehyde solution was used to simulate the COD of highly saline coal chemical wastewater. The stable and metastable solid–liquid equilibria of the (Na2SO4–NaCl–H2O) system containing the organic impurity at 333.15 K were studied. The results showed that the solubility and supersolubility of Na2SO4 increased with the increase of COD. However, the solubility and supersolubility of NaCl had begun to increase when the COD value is around 450 mg L–1. When the COD value reached to 3290 mg L–1 (the content of actual wastewater), the solubility and supersolubility of both Na2SO4 and NaCl exhibited a dramatic change. Meanwhile, the metastable zone widened and the salt-forming zone moved remarkably. These results suggest that when the removal of organic impurities in the system cannot be achieved cost-effectively, the effect of organic impurities on NaCl salts in the system can be significantly decreased by reducing the COD value to within 450 mg L–1 before salt crystallization.

Nobita Hill is an area that will be used as a tourist destination located in Kampung Jua Nan XX Village, at the foot of Nobita Hill, precisely in RW III, there are many houses with poor well water quality. The purpose of this study is to determine the use of zeolite (adsorbent) to purify well water based on Fe metal content parameters, BOD, COD, TSS values and also to determine the effect of adsorbent mass, sample volume, contact time and stirring time on the adsorption process. Determination of Fe content using atomic absorption spectrophotometry (AAS). Determination of the value of Biological Oxygen Demand (BOD) using the Iodometric titration method, determining the value of Chemical Oxygen Demand (COD) using the visible spectrophotometric method and determining the value of Total Suspended Solids (TSS) using the gravimetric method. Zeolite was characterized by X-Ray Fluorescence (XRF) before and after adsorption. Analysis of the concentration of Fe in well water before adsorption 2.1 mg/L. 40 mL of well water was adsorbed with 0.1 g of zeolite for 45 minutes at a stirring speed of 200 rpm, Fe decreased by 96.1%, from 2.1 mg/L to 0.1 mg/L. COD, BOD and TSS values also decreased 57.1%, 63.9% and 67.5% respectively. Characterization using XRF showed a decrease in Si and Al content and an increase in Fe metal content in the adsorbent after adsorption.

This work provides physicochemical solutions for the treatment of process wastewaters of fine chemical industries, that is, pharmaceutical industry. Economical methods are recommended for practical use, which can reduce the disposal ratio of the process wastewaters with higher values of chemical oxygen demand (COD) and Adsorbable Organically Bound Halogens (AOX) than the corresponding emission limits. Such treatment alternatives are also the part of environmental sustainability. The work reviews the theoretical background of the problem and gives options for using the waste management hierarchy chart. Then the general features of pharmaceutical process wastewaters and the treatment methods are summarized. In the algorithm developed for process wastewater treatment, the distillation is the core of the physicochemical treatment alternatives. In the case of the real industrial case studies, the distillation and membrane filtration laboratory experiments and cost calculations prove the efficiency of the selected physicochemical treatment options.

ABSTRACTThe prediction of pollutants removal efficiency from the generated effluent of a treatment plant is valuable and can reduce the time, sampling and energy required during performance assessment. The present study aims to predict the effect of different input parameters on the treatment efficiency of the developed microbial‐based anaerobic process for textile effluent using machine leaning algorithms. The decolourisation and chemical oxygen demand (COD) reduction of the treated effluent were predicted on the basis of the three different input parameters pH, COD and colour value of the textile wastewater. The effectiveness of different machine learning algorithms, support vector machines (SVM), random forest (RF), gradient boost regressor (GBR), AdaBoost, extreme gradient boosting (XGB) regressor and voting regressor, were evaluated based on the correlation coefficient (R2) value. The results revealed that the RF achieved the highest accuracy for decolourisation (training data R2: ∼0.85 and test data R2: ∼0.84) as well as COD reduction (training data R2: ∼0.87 and test data R2: ∼0.94) compared to the other algorithms. These results were validated experimentally, confirming that RF can be used as a tool to predict the performance efficiency of a microbial‐based treatment system.

Untreated coking effluent presents a great challenge for sustainable development of the steel industry and environment preservation. In this study, an internal micro-electrolysis method using Fe/C materials was employed for pretreatment of real coking wastewater with high mass concentration. The Fe/C materials were prepared by Fe powder and graphite powder; and the characteristics of surface morphology, structure, composition of the synthesized materials were examined by Scanning electron microscopy (SEM), X-ray diffraction (XRD) and Energy Dispersive X-ray Spectroscopy (EDS). The effects of factors namely dosage of Fe/C material, treatment time, initial pH and temperature were investigated via chemical oxygen demand (COD) and phenol removal efficiencies. Optimal treatment efficiency was attained at pH of 4, Fe/C dosage of 40 g/L, treatment time of 360 minutes and temperature of 25°C. After the internal electrolysis process, the values of COD, BOD5, and phenol of the wastewater were 6500, 4850 and 0.1 mg/L, respectively.