Abstract In this study, the prepared bio-adsorbents from Labeo rohita fishbones were used to remove the anionic acid dye Melioderm HF (High Fastness) Brown G (MHFB) from the aqueous solution. Scanning electron microscopy (SEM) and Fourier-transform infrared spectroscopy (FTIR) were used to analyze the morphology and chemical composition of fishbone powder (FBP) before and after MHFB dye adsorption. In a batch experiment, factors such as initial dye concentration (100–250 mg/mL), contact time (5–180 min), pH of the solution (2.0–8.0), and the adsorbent dosage (1.0–3.5 g/L) were analyzed for their impact on the dye adsorption process. The batch experiments were studied to evaluate the influence of different operational variables such as pH, adsorbent dosage, contact time, and initial concentration of dye and were found optimum at 2, 2 g/L, 120 min, and 200 ppm, respectively, for maximum dye removal (98.33%) at ambient temperature (298 K). The isotherm models demonstrated that dye molecules were adsorbed heterogeneously in multilayer following the Freundlich isotherm (R2 = 0.9300). The data were fitted for pseudo-second-order kinetics. Thus, L. rohita fishbone could be used as a bio-adsorbent to remove anionic dye from tannery effluents at a minimal cost.
{"title":"Process optimization of anionic dye (Melioderm HF Brown G) removal from aqueous solution utilizing adsorbent prepared from <i>Labeo rohita</i> fishbone","authors":"Md. Arafat Hossain, Plabon Islam Turzo, Md. Saidur Rahman Shakil, Fatema Tuj-Zohra","doi":"10.2166/wpt.2023.147","DOIUrl":"https://doi.org/10.2166/wpt.2023.147","url":null,"abstract":"Abstract In this study, the prepared bio-adsorbents from Labeo rohita fishbones were used to remove the anionic acid dye Melioderm HF (High Fastness) Brown G (MHFB) from the aqueous solution. Scanning electron microscopy (SEM) and Fourier-transform infrared spectroscopy (FTIR) were used to analyze the morphology and chemical composition of fishbone powder (FBP) before and after MHFB dye adsorption. In a batch experiment, factors such as initial dye concentration (100–250 mg/mL), contact time (5–180 min), pH of the solution (2.0–8.0), and the adsorbent dosage (1.0–3.5 g/L) were analyzed for their impact on the dye adsorption process. The batch experiments were studied to evaluate the influence of different operational variables such as pH, adsorbent dosage, contact time, and initial concentration of dye and were found optimum at 2, 2 g/L, 120 min, and 200 ppm, respectively, for maximum dye removal (98.33%) at ambient temperature (298 K). The isotherm models demonstrated that dye molecules were adsorbed heterogeneously in multilayer following the Freundlich isotherm (R2 = 0.9300). The data were fitted for pseudo-second-order kinetics. Thus, L. rohita fishbone could be used as a bio-adsorbent to remove anionic dye from tannery effluents at a minimal cost.","PeriodicalId":23794,"journal":{"name":"Water Practice and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135719543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Water from agricultural drainage systems can be reused when its quality is good or blended with irrigation canal water to overcome the water shortage. The primary goal of this research was to determine the quality of surface drainage water in the Kulifo and Hare irrigation projects for irrigation reuse. Water quality was evaluated in situ and in the laboratory during the irrigation season of 2022. Turbidity, TDS, pH, EC, and DO were analyzed in the field using an Aqua meter. Fifty-seven water samples were collected and analyzed for the major cation (Na+, Ca2+, K+, and Mg2+) and anion (HCO3−, CO32−, Cl−, and SO42−). The result of the drainage water quality index study, according to the water quality index for irrigation purpose reuse, ranged from 47.84 to 84.89. This indicated that the suitability of drainage water reuse for irrigation purposes was categorized as ‘poor to very poor,’ except in Shara community-managed farms. Therefore, to avoid the impact on soil quality for crop production due to the hazard of poor agricultural drainage water for irrigation reuse in the study area, it needs to be treated before being reused for irrigation purposes, except at the Shara irrigation community-managed farm.
{"title":"Evaluation of drainage water quality for irrigation reuse in Kulfo and Hare irrigation command areas, southern Ethiopia","authors":"Edmealem Temesgen, Guchie Gulie, Destaw Akili","doi":"10.2166/wpt.2023.146","DOIUrl":"https://doi.org/10.2166/wpt.2023.146","url":null,"abstract":"Abstract Water from agricultural drainage systems can be reused when its quality is good or blended with irrigation canal water to overcome the water shortage. The primary goal of this research was to determine the quality of surface drainage water in the Kulifo and Hare irrigation projects for irrigation reuse. Water quality was evaluated in situ and in the laboratory during the irrigation season of 2022. Turbidity, TDS, pH, EC, and DO were analyzed in the field using an Aqua meter. Fifty-seven water samples were collected and analyzed for the major cation (Na+, Ca2+, K+, and Mg2+) and anion (HCO3−, CO32−, Cl−, and SO42−). The result of the drainage water quality index study, according to the water quality index for irrigation purpose reuse, ranged from 47.84 to 84.89. This indicated that the suitability of drainage water reuse for irrigation purposes was categorized as ‘poor to very poor,’ except in Shara community-managed farms. Therefore, to avoid the impact on soil quality for crop production due to the hazard of poor agricultural drainage water for irrigation reuse in the study area, it needs to be treated before being reused for irrigation purposes, except at the Shara irrigation community-managed farm.","PeriodicalId":23794,"journal":{"name":"Water Practice and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135814788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Özlem Terzi, Ecir Uğur Küçüksille, Tahsin Baykal, Dilek Taylan
Abstract Estimation accuracy of streamflow values is of great importance in terms of long-term planning of water resources and taking measures against disasters such as drought and flood. The flow formed in a river basin has a complex physical structure that changes depending on the characteristics of the basin (such as topography and vegetation), meteorological factors (such as precipitation, evaporation and infiltration) and human activities. In recent years, deep and machine learning techniques have attracted attention thanks to their powerful learning capabilities and accurate and reliable modeling of these complex and nonlinear processes. In this paper, long short-term memory (LSTM), random forest regression (RFR) and extreme gradient boosting (XGBoost) approaches were applied to estimate daily streamflow values of Göksu River, Turkey. Hyperparameter optimization was realized for deep and machine learning algorithms. The daily flow values between the years 1990–2010 were used and various input parameters were tried in the modeling. Examining the performance (R2, RMSE and MAE) of the models, the XGBoost model having five input parameters provided more appropriate results than other models. The R2 value of the XGBoost model was obtained as 0.871 for the testing set. Also, it is shown that deep and machine learning algorithms are used successfully for streamflow estimation.
{"title":"Deep and machine learning for daily streamflow estimation: a focus on LSTM, RFR and XGBoost","authors":"Özlem Terzi, Ecir Uğur Küçüksille, Tahsin Baykal, Dilek Taylan","doi":"10.2166/wpt.2023.144","DOIUrl":"https://doi.org/10.2166/wpt.2023.144","url":null,"abstract":"Abstract Estimation accuracy of streamflow values is of great importance in terms of long-term planning of water resources and taking measures against disasters such as drought and flood. The flow formed in a river basin has a complex physical structure that changes depending on the characteristics of the basin (such as topography and vegetation), meteorological factors (such as precipitation, evaporation and infiltration) and human activities. In recent years, deep and machine learning techniques have attracted attention thanks to their powerful learning capabilities and accurate and reliable modeling of these complex and nonlinear processes. In this paper, long short-term memory (LSTM), random forest regression (RFR) and extreme gradient boosting (XGBoost) approaches were applied to estimate daily streamflow values of Göksu River, Turkey. Hyperparameter optimization was realized for deep and machine learning algorithms. The daily flow values between the years 1990–2010 were used and various input parameters were tried in the modeling. Examining the performance (R2, RMSE and MAE) of the models, the XGBoost model having five input parameters provided more appropriate results than other models. The R2 value of the XGBoost model was obtained as 0.871 for the testing set. Also, it is shown that deep and machine learning algorithms are used successfully for streamflow estimation.","PeriodicalId":23794,"journal":{"name":"Water Practice and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136060151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nevil K. Trambadia, Dhruvesh P. Patel, Vinodkumar M. Patel, Manoj J. Gundalia
Abstract Ghed region is located in the deep western part of Gujarat state, having the cup shape geometry. The Ozat River begins near the Gir forest's hilly part and moves towards the river mouth near Navi Bandar. The part before the river mouth is called Ghed, near the coastal line. The inundation in this region occurred due to higher coastal line and cup shape geometry with an area of more than 200 km2. This research emphasized early warning of the local community aside from the region during the peak flow condition. The hydrological engineering centre-river analysis system software developed the hydrodynamic model for FEWS (flood early warning system). The model has been validated with observed water depth data at four locations from the river reach area for more precision. In this regard, various statistics have been performed to compare the observed and modelled data. The result depicts the 19 h of leg time available to evacuate the local community. After that, water takes 115 h more time to reach the river mouth due to cup-shaped region filling. This research helps the administration with the decision-making system and establishes new hydraulic structures.
{"title":"Development of a 2D hydrodynamic model for inundation assessment and flood early warning system: a case of depressed Ghed region, India","authors":"Nevil K. Trambadia, Dhruvesh P. Patel, Vinodkumar M. Patel, Manoj J. Gundalia","doi":"10.2166/wpt.2023.145","DOIUrl":"https://doi.org/10.2166/wpt.2023.145","url":null,"abstract":"Abstract Ghed region is located in the deep western part of Gujarat state, having the cup shape geometry. The Ozat River begins near the Gir forest's hilly part and moves towards the river mouth near Navi Bandar. The part before the river mouth is called Ghed, near the coastal line. The inundation in this region occurred due to higher coastal line and cup shape geometry with an area of more than 200 km2. This research emphasized early warning of the local community aside from the region during the peak flow condition. The hydrological engineering centre-river analysis system software developed the hydrodynamic model for FEWS (flood early warning system). The model has been validated with observed water depth data at four locations from the river reach area for more precision. In this regard, various statistics have been performed to compare the observed and modelled data. The result depicts the 19 h of leg time available to evacuate the local community. After that, water takes 115 h more time to reach the river mouth due to cup-shaped region filling. This research helps the administration with the decision-making system and establishes new hydraulic structures.","PeriodicalId":23794,"journal":{"name":"Water Practice and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136130786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pritam Talukdar, Tarun Mokenepally, Vihangraj V. Kulkarni
Abstract Monitoring water quality metrics is essential for managing water quality and safeguarding aquatic life. The NIT Silchar Lake has been a place for many aquatic plants and migratory birds. The lake water is typically used on campus for horticultureal purposes. However, the peasants living close to campus use the lake water for drinking during situations like floods or famine. At four separate locations of the lake, the samples were collected for evaluation of seven water quality indicators. Temperature between 22.4 and 30.5 °C and dissolved oxygen concentrations between 8 and 13 mg/l were found, which were optimal conditions for aquatic life. The water quality index (WQI), which gives an overall evaluation of the state of the water quality, was created from the measured values (six parameters). The lake regions that ranged from good to excellent were identified using ‘weighted arithmetic water quality index’ (WAWQI) technique. Further we have compared the WAWQI with another method. A comparative analysis has been done by developing simple codes with the help of python programming language. The inverse distance weighted (IDW) interpolation in GIS was applied for spatial distribution of water quality parameters and WQI.
{"title":"Lake water quality assessment using spatial interpolation and the development of the WQI on an educational campus, Assam, India","authors":"Pritam Talukdar, Tarun Mokenepally, Vihangraj V. Kulkarni","doi":"10.2166/wpt.2023.138","DOIUrl":"https://doi.org/10.2166/wpt.2023.138","url":null,"abstract":"Abstract Monitoring water quality metrics is essential for managing water quality and safeguarding aquatic life. The NIT Silchar Lake has been a place for many aquatic plants and migratory birds. The lake water is typically used on campus for horticultureal purposes. However, the peasants living close to campus use the lake water for drinking during situations like floods or famine. At four separate locations of the lake, the samples were collected for evaluation of seven water quality indicators. Temperature between 22.4 and 30.5 °C and dissolved oxygen concentrations between 8 and 13 mg/l were found, which were optimal conditions for aquatic life. The water quality index (WQI), which gives an overall evaluation of the state of the water quality, was created from the measured values (six parameters). The lake regions that ranged from good to excellent were identified using ‘weighted arithmetic water quality index’ (WAWQI) technique. Further we have compared the WAWQI with another method. A comparative analysis has been done by developing simple codes with the help of python programming language. The inverse distance weighted (IDW) interpolation in GIS was applied for spatial distribution of water quality parameters and WQI.","PeriodicalId":23794,"journal":{"name":"Water Practice and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135014417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Heavy metal pollution damages the ecosystems and presents a major problem for public health. Thus, an urgent need was developed to decrease the high levels of heavy metals in the soil and aquatic environments. With this aim, numerous physicochemical strategies were developed. However, they are money-consuming, require the use of energy and chemical additives and can release secondary compounds that can pollute and cause great damage to the environment. Then, biological methods based on the investigation of bacteria, fungi and plants along with their derived secondary active metabolites became the best alternatives. Using plant capacities, different phytoremediation strategies were developed such as phytoextraction, phytovolatilization, rhizofiltration and phytostabilization. Regarding bioremediation, bacterial biosorption of heavy metals, biolixiviation and lagooning offer great potential for their environmental cleaning. Additionally, the use of secondary active metabolites, such as biosurfactants, is well-studied. Generally, they are a class of structurally very varied molecules commonly synthesized by many microorganisms with amphiphilic character. Owing to their anionic charge, they have the capacity to sequestrate heavy metals permitting their elimination. Glycolipids and lipopeptides are among the most recognized biosurfactants with interesting heavy metal chelating properties.
{"title":"Bioremediation of heavy metal-contaminated environment: developed strategies and potential use of biosurfactants as chelators","authors":"Mnif Inès, Salwa Mekki, Ghribi Dhouha","doi":"10.2166/wpt.2023.140","DOIUrl":"https://doi.org/10.2166/wpt.2023.140","url":null,"abstract":"Abstract Heavy metal pollution damages the ecosystems and presents a major problem for public health. Thus, an urgent need was developed to decrease the high levels of heavy metals in the soil and aquatic environments. With this aim, numerous physicochemical strategies were developed. However, they are money-consuming, require the use of energy and chemical additives and can release secondary compounds that can pollute and cause great damage to the environment. Then, biological methods based on the investigation of bacteria, fungi and plants along with their derived secondary active metabolites became the best alternatives. Using plant capacities, different phytoremediation strategies were developed such as phytoextraction, phytovolatilization, rhizofiltration and phytostabilization. Regarding bioremediation, bacterial biosorption of heavy metals, biolixiviation and lagooning offer great potential for their environmental cleaning. Additionally, the use of secondary active metabolites, such as biosurfactants, is well-studied. Generally, they are a class of structurally very varied molecules commonly synthesized by many microorganisms with amphiphilic character. Owing to their anionic charge, they have the capacity to sequestrate heavy metals permitting their elimination. Glycolipids and lipopeptides are among the most recognized biosurfactants with interesting heavy metal chelating properties.","PeriodicalId":23794,"journal":{"name":"Water Practice and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135885251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract The present study deals with treating the textile wastewater of Jodhpur city in Rajasthan, India employing a photocatalysis technique. Jodhpur has a number of textile industries and efficient treatment of its effluents has been a major problem in the region. An effort has been made to resolve this issue through this study. A wastewater treatment unit was setup which involved coagulation and flocculation, sand filter, photoreactor, and activated carbon filter processes. ZnO-based semiconductor, coated on galvanized iron (GI) plates, served as a photoreactor. The water quality parameters removal efficiency at the end of each process operation was recorded for different detention periods in the photoreactor. Water quality parameters analyzed were biochemical oxygen demand (BOD), total dissolved solids (TDS), total suspended solids (TSS), and pH. The optimal retention time for the photoreactor was found and the BOD of the wastewater reduced to 25 from 740 mg/l (97% reduction), and TSS from 1,430 to 12 mg/l (99% reduction) for the corresponding retention time. TDS reduction efficiency was 25% and pH changed from 9.2 in raw wastewater to 8.4 in treated wastewater. Results show that the pilot treatment plant was efficient for BOD and TSS removal from the textile wastewater.
{"title":"Assessment of solar photocatalytic degradation of textile wastewater by ZnO-based reactors","authors":"Jyoti Chaubey, Vineet Jain, Suresh Kumar Singh, Apoorva Jain, H. Arora","doi":"10.2166/wpt.2023.141","DOIUrl":"https://doi.org/10.2166/wpt.2023.141","url":null,"abstract":"Abstract The present study deals with treating the textile wastewater of Jodhpur city in Rajasthan, India employing a photocatalysis technique. Jodhpur has a number of textile industries and efficient treatment of its effluents has been a major problem in the region. An effort has been made to resolve this issue through this study. A wastewater treatment unit was setup which involved coagulation and flocculation, sand filter, photoreactor, and activated carbon filter processes. ZnO-based semiconductor, coated on galvanized iron (GI) plates, served as a photoreactor. The water quality parameters removal efficiency at the end of each process operation was recorded for different detention periods in the photoreactor. Water quality parameters analyzed were biochemical oxygen demand (BOD), total dissolved solids (TDS), total suspended solids (TSS), and pH. The optimal retention time for the photoreactor was found and the BOD of the wastewater reduced to 25 from 740 mg/l (97% reduction), and TSS from 1,430 to 12 mg/l (99% reduction) for the corresponding retention time. TDS reduction efficiency was 25% and pH changed from 9.2 in raw wastewater to 8.4 in treated wastewater. Results show that the pilot treatment plant was efficient for BOD and TSS removal from the textile wastewater.","PeriodicalId":23794,"journal":{"name":"Water Practice and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135298588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Vijay Kaushik, Munendra Kumar, Bandita Naik, Abbas Parsaie
Abstract Estimating the water surface elevation of river systems is one of the most complicated tasks in formulating hydraulic models for flood control and floodplain management. Consequently, utilizing simulation models to calibrate and validate the experimental data is crucial. HEC-RAS is used to calibrate and verify the water surface profiles for various converging compound channels in this investigation. Based on experimental data for converging channels (θ = 5°, 9°, and 12.38°), two distinct flow regimes were evaluated for validation. The predicted water surface profiles for two relative depths (β = 0.25 and 0.30) follow the same variational pattern as the experimental findings and are slightly lower than the observed values. The MAPE for the simulated and experimental results is less than 3%, indicating the predicted HEC-RAS value performance and accuracy. Therefore, our findings imply that in the case of non-prismatic rivers, the proposed HEC-RAS models are reliable for predicting water surface profiles with a high generalization capacity and do not exhibit overtraining. However, the results demonstrated that numerous variables impacting the water surface profile should be carefully considered since this would increase the disparities between HEC-RAS and experimental data.
{"title":"Modeling of water surface profile in non-prismatic compound channels","authors":"Vijay Kaushik, Munendra Kumar, Bandita Naik, Abbas Parsaie","doi":"10.2166/wpt.2023.142","DOIUrl":"https://doi.org/10.2166/wpt.2023.142","url":null,"abstract":"Abstract Estimating the water surface elevation of river systems is one of the most complicated tasks in formulating hydraulic models for flood control and floodplain management. Consequently, utilizing simulation models to calibrate and validate the experimental data is crucial. HEC-RAS is used to calibrate and verify the water surface profiles for various converging compound channels in this investigation. Based on experimental data for converging channels (θ = 5°, 9°, and 12.38°), two distinct flow regimes were evaluated for validation. The predicted water surface profiles for two relative depths (β = 0.25 and 0.30) follow the same variational pattern as the experimental findings and are slightly lower than the observed values. The MAPE for the simulated and experimental results is less than 3%, indicating the predicted HEC-RAS value performance and accuracy. Therefore, our findings imply that in the case of non-prismatic rivers, the proposed HEC-RAS models are reliable for predicting water surface profiles with a high generalization capacity and do not exhibit overtraining. However, the results demonstrated that numerous variables impacting the water surface profile should be carefully considered since this would increase the disparities between HEC-RAS and experimental data.","PeriodicalId":23794,"journal":{"name":"Water Practice and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135299873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sahl Yasin, M. S. Suliman, Abdelhafeez M. A. Mohammed
Abstract In this study, nickel nanoparticles (NiNPs) were synthesized and utilized for removing dispersed oil from oilfield-produced water in Sudan. The synthesis process involved using two concentration of hydrazine as a reducing agent and sodium hydroxide as solvent. Physiochemical characterizations, such as X-ray diffraction (XRD) and transmission electron microscopy (TEM), confirmed the successful preparation of NiNPs. The TEM analysis revealed an average particle size ranging from 70 to 90 nm, with a change in morphology from star-shaped to monodispersed spherical particles. The crystal structure analysis confirmed the face-centered-cubic (FCC) configuration of the NiNPs, validating their structural properties. Significantly, the NiNPs demonstrated an impressive capability to remove oil form produced water, achieving a remarkable efficiency of 98% in eliminating dispersed oil from produced water. The oil removal process followed Freundlich isotherms, as evidenced by the high value of the linear regression coefficient. Additionally, the kinetics of the oil removal process conformed well to the pseudo-second-order model, indicating a rapid reaction. This study successfully demonstrated the efficient removal of dispersed oil from produced water using nickel nanoparticles, which interacted physically with the oil particles. These findings highlight the potential of NiNPs as an effective adsorbent for treating oilfield-produced water and mitigating environmental contamination.
{"title":"The role of metallic nickel nanoparticles to remove dispersed oil from produced water in Sudan oil field plant","authors":"Sahl Yasin, M. S. Suliman, Abdelhafeez M. A. Mohammed","doi":"10.2166/wpt.2023.139","DOIUrl":"https://doi.org/10.2166/wpt.2023.139","url":null,"abstract":"Abstract In this study, nickel nanoparticles (NiNPs) were synthesized and utilized for removing dispersed oil from oilfield-produced water in Sudan. The synthesis process involved using two concentration of hydrazine as a reducing agent and sodium hydroxide as solvent. Physiochemical characterizations, such as X-ray diffraction (XRD) and transmission electron microscopy (TEM), confirmed the successful preparation of NiNPs. The TEM analysis revealed an average particle size ranging from 70 to 90 nm, with a change in morphology from star-shaped to monodispersed spherical particles. The crystal structure analysis confirmed the face-centered-cubic (FCC) configuration of the NiNPs, validating their structural properties. Significantly, the NiNPs demonstrated an impressive capability to remove oil form produced water, achieving a remarkable efficiency of 98% in eliminating dispersed oil from produced water. The oil removal process followed Freundlich isotherms, as evidenced by the high value of the linear regression coefficient. Additionally, the kinetics of the oil removal process conformed well to the pseudo-second-order model, indicating a rapid reaction. This study successfully demonstrated the efficient removal of dispersed oil from produced water using nickel nanoparticles, which interacted physically with the oil particles. These findings highlight the potential of NiNPs as an effective adsorbent for treating oilfield-produced water and mitigating environmental contamination.","PeriodicalId":23794,"journal":{"name":"Water Practice and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135299971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Retraction: <i>Water Practice and Technology</i> 18 (6): 1529–1542: Isotopes and geochemical tools for investigating the source of metal pollution in Uchhali Lake, Abdul Ghaffar, https://doi.org/10.2166/wpt.2023.093","authors":"","doi":"10.2166/wpt.2023.143","DOIUrl":"https://doi.org/10.2166/wpt.2023.143","url":null,"abstract":"","PeriodicalId":23794,"journal":{"name":"Water Practice and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134994556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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