Mehrnaz Soleimanpour Makuei, Faezeh Ketabchi, Nicolás M. Peleato
The objective of this study was to examine the impact of unfiltered water conditions on UV disinfection. UV biodosimetry tests were conducted over a year using water samples from two treatment plants that apply UV without filtration. The influence of turbidity, absorbance, and zeta potential on UV dose–response curves was analyzed to evaluate relationships between unfiltered water quality and log-inactivation of surrogate organisms. It was observed that diminishing inactivation with increasing UV dose (tailing effect) was governed principally by the surface charge of particulate matter. The increased tailing level observed in raw waters was postulated to be due to having more neutral surface charges, resulting in elevated electrostatic attraction between particles and microorganisms that increased UV resistance. Inactivation at a dose of 35 mJ/cm2 in water samples with low turbidity levels (0.38 NTU) and relatively negative surface charge resulted in 3.0 log-removal in comparison with 2.2 and 2.0 log-removal for samples with turbidity levels of 1.57 and 0.61 NTU, respectively. The results of this study highlight the risks of UV disinfection of unfiltered supplies with respect to the effects of water quality characteristics on UV effectiveness and could be employed to optimize the estimation of UV disinfection potential.
{"title":"Impact of water characteristics on UV disinfection of unfiltered water","authors":"Mehrnaz Soleimanpour Makuei, Faezeh Ketabchi, Nicolás M. Peleato","doi":"10.2166/wqrj.2022.006","DOIUrl":"https://doi.org/10.2166/wqrj.2022.006","url":null,"abstract":"\u0000 The objective of this study was to examine the impact of unfiltered water conditions on UV disinfection. UV biodosimetry tests were conducted over a year using water samples from two treatment plants that apply UV without filtration. The influence of turbidity, absorbance, and zeta potential on UV dose–response curves was analyzed to evaluate relationships between unfiltered water quality and log-inactivation of surrogate organisms. It was observed that diminishing inactivation with increasing UV dose (tailing effect) was governed principally by the surface charge of particulate matter. The increased tailing level observed in raw waters was postulated to be due to having more neutral surface charges, resulting in elevated electrostatic attraction between particles and microorganisms that increased UV resistance. Inactivation at a dose of 35 mJ/cm2 in water samples with low turbidity levels (0.38 NTU) and relatively negative surface charge resulted in 3.0 log-removal in comparison with 2.2 and 2.0 log-removal for samples with turbidity levels of 1.57 and 0.61 NTU, respectively. The results of this study highlight the risks of UV disinfection of unfiltered supplies with respect to the effects of water quality characteristics on UV effectiveness and could be employed to optimize the estimation of UV disinfection potential.","PeriodicalId":23720,"journal":{"name":"Water Quality Research Journal","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45968409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yasmine Laftani, Baylassane Chatib, A. Boussaoud, M. Hachkar, Mohammed El Makhfouk
Generation of anion sulfate radicals (SO4•−) and hydroxyl radicals (HO•) by UV/Persulfate and the UV/Peroxydate processes have been successfully studied to degrade Ponceau S dye. Under [PS] = 0.06 mM; [H2O2] = 2 mM; [S2O82-] = 2 mM, the UV/Persulfate process was effective (kapp = 0.163 min−1) than the UV/Peroxydate process (kapp = 0.054 min−1). The lack of dissolved oxygen, the excess of hydrogen peroxide (H2O2) dosage at 2 mM, and the alkaline pH of 10.01 significantly reduced the UV/Peroxydate efficiency. The scavenging effect of the hydrogenocarbonates and nitrates on the PS dye degradation by the UV/Persulfate process was significant, whereas chlorides had a slight influence. The composition of seawater in chlorides, sulfates, carbonates, and bromides decreased the photoactivity of the studied processes. The presence of phenol showed that the reactive affinity of the (HO•) is more superior to the SO4•−. The UV/Persulfate process achieved 82.35% of chemical oxygen demand removal against 59.56% for the UV/Peroxydate in about 100 min. This study demonstrated that the UV/Persulfate process is a viable option for PS dye degradation. To the best of our knowledge, this is the first report for studying the PS dye degradation under some varying new operational factors. However, the identification of by-products, their nature, and their concentration requires special attention.
{"title":"Comparative photo-degradative treatment of dyeing industry wastewater containing diazo dye by UV/Peroxydate and UV/Persulfate − oxidation processes","authors":"Yasmine Laftani, Baylassane Chatib, A. Boussaoud, M. Hachkar, Mohammed El Makhfouk","doi":"10.2166/wqrj.2022.012","DOIUrl":"https://doi.org/10.2166/wqrj.2022.012","url":null,"abstract":"\u0000 Generation of anion sulfate radicals (SO4•−) and hydroxyl radicals (HO•) by UV/Persulfate and the UV/Peroxydate processes have been successfully studied to degrade Ponceau S dye. Under [PS] = 0.06 mM; [H2O2] = 2 mM; [S2O82-] = 2 mM, the UV/Persulfate process was effective (kapp = 0.163 min−1) than the UV/Peroxydate process (kapp = 0.054 min−1). The lack of dissolved oxygen, the excess of hydrogen peroxide (H2O2) dosage at 2 mM, and the alkaline pH of 10.01 significantly reduced the UV/Peroxydate efficiency. The scavenging effect of the hydrogenocarbonates and nitrates on the PS dye degradation by the UV/Persulfate process was significant, whereas chlorides had a slight influence. The composition of seawater in chlorides, sulfates, carbonates, and bromides decreased the photoactivity of the studied processes. The presence of phenol showed that the reactive affinity of the (HO•) is more superior to the SO4•−. The UV/Persulfate process achieved 82.35% of chemical oxygen demand removal against 59.56% for the UV/Peroxydate in about 100 min. This study demonstrated that the UV/Persulfate process is a viable option for PS dye degradation. To the best of our knowledge, this is the first report for studying the PS dye degradation under some varying new operational factors. However, the identification of by-products, their nature, and their concentration requires special attention.","PeriodicalId":23720,"journal":{"name":"Water Quality Research Journal","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43593576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The application of machine learning (ML) approaches to predict estuarine dissolved oxygen (DO) from a set of environmental covariates including nutrients remains unexplored due to nutrient data unavailability. Employing data from 12 southwest coastal Florida water quality stations, the applicability of four ML models – support vector machine (SVM), random forest (RF), decision tree, and Wang–Mendel – was examined in predicting DO under a limited nutrient data environment. Monthly water temperature, pH, salinity, total nitrogen (TN), and total phosphorus (TP) data were used for model development. The multiple linear regression model was trained as benchmarks to compare the ML model performances. The site-specific RF and SVM showed superior model efficiency (Nash–Sutcliffe Efficiency > 0.80) when all the predictor variables were used for model development. However, models trained without nutrients demonstrated reduced prediction accuracy. Modeling by synthesizing all site data under TN-limited, TP-limited, and TN- & TP-co-limited regimes illustrated a preferable performance of RF. Overall, the study rendered two crucial conclusions that could complement the existing approaches to estimate total daily loads for environmental management: (1) nutrients serve as a necessary predictor of estuarine DO dynamics and (2) RF performs better among the ML methods under a limited data environment.
{"title":"Application of machine learning approaches in predicting estuarine dissolved oxygen (DO) under a limited data environment","authors":"M. A. Z. Siddik","doi":"10.2166/wqrj.2022.002","DOIUrl":"https://doi.org/10.2166/wqrj.2022.002","url":null,"abstract":"\u0000 The application of machine learning (ML) approaches to predict estuarine dissolved oxygen (DO) from a set of environmental covariates including nutrients remains unexplored due to nutrient data unavailability. Employing data from 12 southwest coastal Florida water quality stations, the applicability of four ML models – support vector machine (SVM), random forest (RF), decision tree, and Wang–Mendel – was examined in predicting DO under a limited nutrient data environment. Monthly water temperature, pH, salinity, total nitrogen (TN), and total phosphorus (TP) data were used for model development. The multiple linear regression model was trained as benchmarks to compare the ML model performances. The site-specific RF and SVM showed superior model efficiency (Nash–Sutcliffe Efficiency > 0.80) when all the predictor variables were used for model development. However, models trained without nutrients demonstrated reduced prediction accuracy. Modeling by synthesizing all site data under TN-limited, TP-limited, and TN- & TP-co-limited regimes illustrated a preferable performance of RF. Overall, the study rendered two crucial conclusions that could complement the existing approaches to estimate total daily loads for environmental management: (1) nutrients serve as a necessary predictor of estuarine DO dynamics and (2) RF performs better among the ML methods under a limited data environment.","PeriodicalId":23720,"journal":{"name":"Water Quality Research Journal","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45019755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The current paper deals with the performance evaluation of the application of three soft computing algorithms such as adaptive neuro-fuzzy inference system (ANFIS), backpropagation neural network (BPNN), and deep neural network (DNN) in predicting oxygen aeration efficiency (OAE20) of the gabion spillways. Besides, classical equations, namely multivariate linear and nonlinear regressions (MVLR and MVNLR), including previous studies, were also employed in predicting OAE20 of the gabion spillways. The analysis of results showed that the DNN demonstrated relatively lower error values (root mean square error, RMSE = 0.03465; mean square error, MSE = 0.00121; mean absolute error, MAE = 0.02721) and the highest value of correlation coefficient, CC = 0.9757, performed the best in predicting OAE20 of the gabion spillways; however, other applied models, such as ANFIS, BPNN, MVLR, and MVNLR, were giving comparable results evaluated to statistical appraisal metrics of the relative significance of input parameters based on sensitivity investigation, the porosity (n) of gabion materials was observed to be the most critical parameter, and gabion height (P) had the least impact over OAE20 of the spillways.
{"title":"Oxygen aeration efficiency of gabion spillway by soft computing models","authors":"Rathod Srinivas, N. K. Tiwari","doi":"10.2166/wqrj.2022.009","DOIUrl":"https://doi.org/10.2166/wqrj.2022.009","url":null,"abstract":"\u0000 The current paper deals with the performance evaluation of the application of three soft computing algorithms such as adaptive neuro-fuzzy inference system (ANFIS), backpropagation neural network (BPNN), and deep neural network (DNN) in predicting oxygen aeration efficiency (OAE20) of the gabion spillways. Besides, classical equations, namely multivariate linear and nonlinear regressions (MVLR and MVNLR), including previous studies, were also employed in predicting OAE20 of the gabion spillways. The analysis of results showed that the DNN demonstrated relatively lower error values (root mean square error, RMSE = 0.03465; mean square error, MSE = 0.00121; mean absolute error, MAE = 0.02721) and the highest value of correlation coefficient, CC = 0.9757, performed the best in predicting OAE20 of the gabion spillways; however, other applied models, such as ANFIS, BPNN, MVLR, and MVNLR, were giving comparable results evaluated to statistical appraisal metrics of the relative significance of input parameters based on sensitivity investigation, the porosity (n) of gabion materials was observed to be the most critical parameter, and gabion height (P) had the least impact over OAE20 of the spillways.","PeriodicalId":23720,"journal":{"name":"Water Quality Research Journal","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44152683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ipsita Som, Sourav Suman, Mouni Roy, Srimanta Gupta, R. Saha
In recent times, nano zerovalent iron (nZVI) particles have attracted significant attention from researchers for their effectiveness in removing phosphates, a hazardous contaminant, found in groundwater and surface water. nZVI possesses some excellent characteristics such as high reactivity, high surface area, and effective surface-to-volume ratio. In this study, nZVI was characterized by X-ray diffraction, Brunauer–Emmett–Teller (BET) surface area analyzer, Fourier transform infra-red (FT-IR), field emission scanning electron microscopy (FESEM), and transmission electron microscopy (TEM) techniques. The effect of variations in nZVI dosage, pH, ionic strength, and coexisting anions on the removal of phosphate from laboratory-based synthetic water was explored. A maximum phosphate removal efficiency of 96% was achieved at an initial phosphate concentration of 25 mg/L, a nZVI dosage of 560 mg/L, and a shaking rate of 500 rpm, and pH 2 was attained within 120 min. Kinetic and equilibrium studies revealed that the adsorption of phosphate follows a pseudo-2nd-order kinetic model and a Temkin isotherm model, respectively. A thermodynamic study confirmed that phosphate adsorption is a spontaneous and endothermic process. Finally, nZVI was proved to be stable up to five cycles. nZVI was further applied for the removal of phosphate from sewage water, which was collected from Saheb bandh, Purulia district of West Bengal, Eastern India.
{"title":"Effective phosphate removal from sewage water using zerovalent iron nanomaterial as an adsorbent","authors":"Ipsita Som, Sourav Suman, Mouni Roy, Srimanta Gupta, R. Saha","doi":"10.2166/wqrj.2022.007","DOIUrl":"https://doi.org/10.2166/wqrj.2022.007","url":null,"abstract":"\u0000 In recent times, nano zerovalent iron (nZVI) particles have attracted significant attention from researchers for their effectiveness in removing phosphates, a hazardous contaminant, found in groundwater and surface water. nZVI possesses some excellent characteristics such as high reactivity, high surface area, and effective surface-to-volume ratio. In this study, nZVI was characterized by X-ray diffraction, Brunauer–Emmett–Teller (BET) surface area analyzer, Fourier transform infra-red (FT-IR), field emission scanning electron microscopy (FESEM), and transmission electron microscopy (TEM) techniques. The effect of variations in nZVI dosage, pH, ionic strength, and coexisting anions on the removal of phosphate from laboratory-based synthetic water was explored. A maximum phosphate removal efficiency of 96% was achieved at an initial phosphate concentration of 25 mg/L, a nZVI dosage of 560 mg/L, and a shaking rate of 500 rpm, and pH 2 was attained within 120 min. Kinetic and equilibrium studies revealed that the adsorption of phosphate follows a pseudo-2nd-order kinetic model and a Temkin isotherm model, respectively. A thermodynamic study confirmed that phosphate adsorption is a spontaneous and endothermic process. Finally, nZVI was proved to be stable up to five cycles. nZVI was further applied for the removal of phosphate from sewage water, which was collected from Saheb bandh, Purulia district of West Bengal, Eastern India.","PeriodicalId":23720,"journal":{"name":"Water Quality Research Journal","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48239603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ting Xia, Shihong Wang, Hang Yan, Zaizhuang Gao, Yao Qiu, Fang Yuan, Guang-yong Huang, Jun Zhou
Montmorillonite modified lime-ceramic sand-lake sediment (LC-sediments) was synthesized and its algae removal efficiency was investigated in this study. Montmorillonite not only improved the morphology and surface area of original LC-sediments, but also promoted the algal removal rate due to its inherent properties such as accumulating an electric charge, acting as a flocculant, and displaying a local bridging effect. Based on parameter optimization including the ratio of raw materials, agent dosage, initial algae density, pH and, a determination of overlying water, the effect of hydrodynamic conditions on the algal removal process was researched. Under the optimal condition, the removal rates of turbidity, algae density and chlorophyll a could reach 86, 88 and 68%, respectively. As verified with a response surface model, it was shown that low disturbance (stirring) of the algae could promote algal removal by montmorillonite modified LC-sediment. Furthermore, a water column was utilized to approximatively simulate the flocculation and algae control in shallow lakes. This study solved the problem of reducing the dosage of lake sediment and improving the removal efficiency of algae without causing secondary pollution to the environment. It was expected to provide a certain theoretical basis for clay flocculation-based algae control in a real environment.
{"title":"Effect of hydrodynamic condition on algae control based on montmorillonite modified lime-ceramic sand-lake sediments","authors":"Ting Xia, Shihong Wang, Hang Yan, Zaizhuang Gao, Yao Qiu, Fang Yuan, Guang-yong Huang, Jun Zhou","doi":"10.2166/wqrj.2022.008","DOIUrl":"https://doi.org/10.2166/wqrj.2022.008","url":null,"abstract":"\u0000 Montmorillonite modified lime-ceramic sand-lake sediment (LC-sediments) was synthesized and its algae removal efficiency was investigated in this study. Montmorillonite not only improved the morphology and surface area of original LC-sediments, but also promoted the algal removal rate due to its inherent properties such as accumulating an electric charge, acting as a flocculant, and displaying a local bridging effect. Based on parameter optimization including the ratio of raw materials, agent dosage, initial algae density, pH and, a determination of overlying water, the effect of hydrodynamic conditions on the algal removal process was researched. Under the optimal condition, the removal rates of turbidity, algae density and chlorophyll a could reach 86, 88 and 68%, respectively. As verified with a response surface model, it was shown that low disturbance (stirring) of the algae could promote algal removal by montmorillonite modified LC-sediment. Furthermore, a water column was utilized to approximatively simulate the flocculation and algae control in shallow lakes. This study solved the problem of reducing the dosage of lake sediment and improving the removal efficiency of algae without causing secondary pollution to the environment. It was expected to provide a certain theoretical basis for clay flocculation-based algae control in a real environment.","PeriodicalId":23720,"journal":{"name":"Water Quality Research Journal","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46347172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mohammed Amarine, Sarah Jerroumi, B. Lekhlif, Y. Zouheir, Amine Chafik, El Mostafa Mliji, J. Echaabi
In this study, the denitrification of nitrate-contaminated groundwater by the heterotrophic denitrification (HD) method was studied to produce drinking water. Preliminary tests were carried out in a denitrification reactor, consisting of an opaque PVC column filled with a plastic packing, and fed with a synthetic solution based on glycerol, in which activated sludge bacteria were added. The performance of the reactor was monitored by measuring physicochemical parameters such as pH, turbidity, nitrates, and nitrites. This monitoring was carried out for different tests within the same reactor to evaluate the adaptation possibilities of the denitrifying bacteria. At the end of each test when the substrate was exhausted, a new synthetic solution was added to the reactor under discontinuous aeration (aeration period = 1 h). The results obtained showed that the nitrate removal efficiency reached a value of 99.42% after 8 h of treatment depending on the adaptation of the denitrifying bacteria. This experiment also showed that the concentration of produced nitrite depends on the aeration mode and it reached a value below the detection limit in the sequential aeration mode after 12 h of treatment under discontinuous aeration (aeration period = 1 h).
{"title":"Nitrate removal from groundwater using an activated sludge as a source of bacteria","authors":"Mohammed Amarine, Sarah Jerroumi, B. Lekhlif, Y. Zouheir, Amine Chafik, El Mostafa Mliji, J. Echaabi","doi":"10.2166/wqrj.2022.005","DOIUrl":"https://doi.org/10.2166/wqrj.2022.005","url":null,"abstract":"In this study, the denitrification of nitrate-contaminated groundwater by the heterotrophic denitrification (HD) method was studied to produce drinking water. Preliminary tests were carried out in a denitrification reactor, consisting of an opaque PVC column filled with a plastic packing, and fed with a synthetic solution based on glycerol, in which activated sludge bacteria were added. The performance of the reactor was monitored by measuring physicochemical parameters such as pH, turbidity, nitrates, and nitrites. This monitoring was carried out for different tests within the same reactor to evaluate the adaptation possibilities of the denitrifying bacteria. At the end of each test when the substrate was exhausted, a new synthetic solution was added to the reactor under discontinuous aeration (aeration period = 1 h). The results obtained showed that the nitrate removal efficiency reached a value of 99.42% after 8 h of treatment depending on the adaptation of the denitrifying bacteria. This experiment also showed that the concentration of produced nitrite depends on the aeration mode and it reached a value below the detection limit in the sequential aeration mode after 12 h of treatment under discontinuous aeration (aeration period = 1 h).","PeriodicalId":23720,"journal":{"name":"Water Quality Research Journal","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67976110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The standard k–ε model coupled with the mixture model was used to study two-phase flow in a large dissolved air flotation (DAF) unit. The numerical results can simulate fairly well the velocity vectors and air volume fraction distribution data of a DAF unit from the literature. The typical DAF structure parameters were analyzed in detail to investigate their predicted influences on the internal flow structure and removal effect. The simulations indicated that the short length of the separation zone was not conducive to the formation of a stratified flow pattern, and the turbulent kinetic energy at the bottom of the separation zone increased as the length decreased. With the increase in the height of the DAF tank, the horizontal flow structure in the separation zone would be disrupted and, the distribution range and the intensity of the turbulence kinetic energy increased. Further analysis showed that the formation of horizontal stratified flow facilitated the removal of bubbles, and the formation of stratified flow is related to the size of the DAF unit. Detailed analyses showed that the reduction of DAF height and the increase of separation zone length were beneficial to improve the bubble removal efficiency. Finally, a theoretical analysis was carried out to study the relationship between DAF parameters and the removal effect. The results revealed that when the horizontal flow structure was not destroyed and stratified flow occurred, the bubble removal efficiency was positively linearly related to the length of the separation zone. The removal efficiency increases as DAF height decreases.
{"title":"Numerical investigation of the multiphase flow patterns and removal effect in a large dissolved air flotation","authors":"J. Tang, Yun Long, Yu Fu, X. Long, Zuti Zhang","doi":"10.2166/wqrj.2022.024","DOIUrl":"https://doi.org/10.2166/wqrj.2022.024","url":null,"abstract":"\u0000 The standard k–ε model coupled with the mixture model was used to study two-phase flow in a large dissolved air flotation (DAF) unit. The numerical results can simulate fairly well the velocity vectors and air volume fraction distribution data of a DAF unit from the literature. The typical DAF structure parameters were analyzed in detail to investigate their predicted influences on the internal flow structure and removal effect. The simulations indicated that the short length of the separation zone was not conducive to the formation of a stratified flow pattern, and the turbulent kinetic energy at the bottom of the separation zone increased as the length decreased. With the increase in the height of the DAF tank, the horizontal flow structure in the separation zone would be disrupted and, the distribution range and the intensity of the turbulence kinetic energy increased. Further analysis showed that the formation of horizontal stratified flow facilitated the removal of bubbles, and the formation of stratified flow is related to the size of the DAF unit. Detailed analyses showed that the reduction of DAF height and the increase of separation zone length were beneficial to improve the bubble removal efficiency. Finally, a theoretical analysis was carried out to study the relationship between DAF parameters and the removal effect. The results revealed that when the horizontal flow structure was not destroyed and stratified flow occurred, the bubble removal efficiency was positively linearly related to the length of the separation zone. The removal efficiency increases as DAF height decreases.","PeriodicalId":23720,"journal":{"name":"Water Quality Research Journal","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46566616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the past years, there has been a lot of interest in water quality and its prediction as there are many pollutants that affect water quality. The techniques provided herein will help us in controlling and reducing the risks of water pollution. In this study, we will discuss concepts related to machine learning models and their applications for water quality classification (WQC). Three machine learning algorithms, J48, Naive Bayes, and multi-layer perceptron (MLP), were used for WQC prediction. The dataset used contains 10 features, and in order to evaluate the machine's algorithms and their performance, some accuracy measurements were used. Our study showed that the proposed models can accurately classify water quality. By analyzing the results, it was found that the MLP algorithm achieved the highest accuracy for WQC prediction as compared to other algorithms.
{"title":"Machine learning for water quality classification","authors":"Saleh Y. Abuzir, Yousef S. Abuzir","doi":"10.2166/wqrj.2022.004","DOIUrl":"https://doi.org/10.2166/wqrj.2022.004","url":null,"abstract":"\u0000 In the past years, there has been a lot of interest in water quality and its prediction as there are many pollutants that affect water quality. The techniques provided herein will help us in controlling and reducing the risks of water pollution. In this study, we will discuss concepts related to machine learning models and their applications for water quality classification (WQC). Three machine learning algorithms, J48, Naive Bayes, and multi-layer perceptron (MLP), were used for WQC prediction. The dataset used contains 10 features, and in order to evaluate the machine's algorithms and their performance, some accuracy measurements were used. Our study showed that the proposed models can accurately classify water quality. By analyzing the results, it was found that the MLP algorithm achieved the highest accuracy for WQC prediction as compared to other algorithms.","PeriodicalId":23720,"journal":{"name":"Water Quality Research Journal","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45283694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Corrigendum: Water Quality Research Journal 57 (1), 1–19: Methylene blue removal using prepared activated carbon from grape wood wastes: adsorption process analysis and modelling, Seyyed Alireza Mousavi, Davood Shahbazi, Arezoo Mahmoudi and Parastoo Darvishi, doi: 10.2166/wqrj.2021.015","authors":"","doi":"10.2166/wqrj.2022.001","DOIUrl":"https://doi.org/10.2166/wqrj.2022.001","url":null,"abstract":"","PeriodicalId":23720,"journal":{"name":"Water Quality Research Journal","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48298174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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