At present, China's rural water resources are in short supply and the water pollution situation is severe. Family farms are an important part of China's agricultural modernization, and their development level is an important indicator to measure the degree of modernization of a country and a region. The application of agricultural Internet of Things technology in the field of agriculture is helpful for solving the problem of water shortage in family farms in water shortage areas. Based on questionnaire data, this paper used structural equation modeling (SEM) to study the relationship between family farm water financing willingness and behavior. The results showed that the standardization coefficients of Assumption 1, Assumption 2 and Assumption 3 were 0.332, 0.267 and 0.311, respectively. It can be seen that the water resource financing willingness of family farms was greatly affected by their water-saving technology ability, water management ability and government policy support. However, the standardization coefficient of Assumption 5 was 0.087. It can be seen that the water management capacity had no significant impact on the water resource financing behavior, and the water resource financing behavior of family farms was mainly affected by their water-saving technical capacity and government policy support.
{"title":"Evaluation of the willingness and behavior of family farm water resource financing based on the Internet of Things SEM model","authors":"Yaxin Wang, Xiongwang Zeng","doi":"10.2166/ws.2023.157","DOIUrl":"https://doi.org/10.2166/ws.2023.157","url":null,"abstract":"\u0000 At present, China's rural water resources are in short supply and the water pollution situation is severe. Family farms are an important part of China's agricultural modernization, and their development level is an important indicator to measure the degree of modernization of a country and a region. The application of agricultural Internet of Things technology in the field of agriculture is helpful for solving the problem of water shortage in family farms in water shortage areas. Based on questionnaire data, this paper used structural equation modeling (SEM) to study the relationship between family farm water financing willingness and behavior. The results showed that the standardization coefficients of Assumption 1, Assumption 2 and Assumption 3 were 0.332, 0.267 and 0.311, respectively. It can be seen that the water resource financing willingness of family farms was greatly affected by their water-saving technology ability, water management ability and government policy support. However, the standardization coefficient of Assumption 5 was 0.087. It can be seen that the water management capacity had no significant impact on the water resource financing behavior, and the water resource financing behavior of family farms was mainly affected by their water-saving technical capacity and government policy support.","PeriodicalId":17553,"journal":{"name":"Journal of Water Supply Research and Technology-aqua","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74096559","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}
Water allocation can be evaluated from various economic, environmental, food security, and climate aspects. This paper was conducted to develop an optimal water allocation strategy with an economic framework. A game theory has been used to determine the planning structure. A cooperative technique based on the core solution, Shepley value, and Nucleolus solution has been incorporated into the decision-making system and the results of the proposed model have been calculated based on the long-term information of the downstream cropping pattern in the Zhanghe irrigation network, Hubei province, China. Five components of rice planting including growth period, yield production, water consumption, selling price, and cultivated area have been evaluated to find the optimal scenarios. Results showed that the application of the co-operative game theory can improve the economic index and water-saving potential in agriculture. Furthermore, the proposed simulation confirmed that the economic effects were important for understanding and planning for irrigation efficiency and water-saving potential.
{"title":"Evaluation of economic scenarios of water allocation using a game theory","authors":"Jiahui Jin, Xiaohong Fang","doi":"10.2166/ws.2023.156","DOIUrl":"https://doi.org/10.2166/ws.2023.156","url":null,"abstract":"\u0000 Water allocation can be evaluated from various economic, environmental, food security, and climate aspects. This paper was conducted to develop an optimal water allocation strategy with an economic framework. A game theory has been used to determine the planning structure. A cooperative technique based on the core solution, Shepley value, and Nucleolus solution has been incorporated into the decision-making system and the results of the proposed model have been calculated based on the long-term information of the downstream cropping pattern in the Zhanghe irrigation network, Hubei province, China. Five components of rice planting including growth period, yield production, water consumption, selling price, and cultivated area have been evaluated to find the optimal scenarios. Results showed that the application of the co-operative game theory can improve the economic index and water-saving potential in agriculture. Furthermore, the proposed simulation confirmed that the economic effects were important for understanding and planning for irrigation efficiency and water-saving potential.","PeriodicalId":17553,"journal":{"name":"Journal of Water Supply Research and Technology-aqua","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74876929","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}
Green algae are natural competitors of cyanobacteria, but we still do not know why green algae have a competitive advantage in shallow lakes. In this study, we used qPCR to quantify and monitor green algae and cyanobacteria in Longhu Lake. Our results showed that green algae were dominant in Longhu Lake, accounting for 71.80–80.31%. The temporal and spatial dynamics of green algal blooms were consistent with that of total organic nitrogen (TON), indicating that organic nitrogen may be the key trigger of green algal blooms. Nitrogen and phosphorus were excessive, and the peak of ammonia nitrogen occurred during the blooms, implying that ammonia nitrogen may be one of the important factors stimulating green algal blooms. Spearman correlation analysis and RDA analysis showed that green algae and cyanobacteria were positively correlated with water temperature, TON, and ammonia nitrogen, indicating that they have similar favorable growth conditions in Longhu Lake. Our results indicated that the combined effects of elevated water temperature, excessive nitrogen and phosphorus, non-stratification, and short water retention time could favor the competitive dominance of green algae in Longhu Lake. The findings here improve our understanding of the competition between green algae and cyanobacteria in shallow lakes.
{"title":"Green algae outcompete cyanobacteria in a shallow lake, Longhu Lake","authors":"Jingjing Li, Xinyan Xiao, Xuanxuan Xian, Shuai Li, Xin Yu, Xian Zhang","doi":"10.2166/ws.2023.154","DOIUrl":"https://doi.org/10.2166/ws.2023.154","url":null,"abstract":"\u0000 \u0000 Green algae are natural competitors of cyanobacteria, but we still do not know why green algae have a competitive advantage in shallow lakes. In this study, we used qPCR to quantify and monitor green algae and cyanobacteria in Longhu Lake. Our results showed that green algae were dominant in Longhu Lake, accounting for 71.80–80.31%. The temporal and spatial dynamics of green algal blooms were consistent with that of total organic nitrogen (TON), indicating that organic nitrogen may be the key trigger of green algal blooms. Nitrogen and phosphorus were excessive, and the peak of ammonia nitrogen occurred during the blooms, implying that ammonia nitrogen may be one of the important factors stimulating green algal blooms. Spearman correlation analysis and RDA analysis showed that green algae and cyanobacteria were positively correlated with water temperature, TON, and ammonia nitrogen, indicating that they have similar favorable growth conditions in Longhu Lake. Our results indicated that the combined effects of elevated water temperature, excessive nitrogen and phosphorus, non-stratification, and short water retention time could favor the competitive dominance of green algae in Longhu Lake. The findings here improve our understanding of the competition between green algae and cyanobacteria in shallow lakes.","PeriodicalId":17553,"journal":{"name":"Journal of Water Supply Research and Technology-aqua","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2023-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84334449","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}
The shortage of water resources (WR) directly affects the economic development and ecological environment in the region, and optimizing the allocation of water resources engineering (WRE) projects is the most valid method to solve this problem. Traditional WR allocation methods can no longer solve the complex configuration problems of complex WRE projects, and the emergence of artificial intelligence (AI) technology has not provided new technologies and methods for optimizing WR allocation. This article conducted research on multi-objective optimization configuration of WRE based on AI technology. First, it introduced the current situation and future development direction of WR allocation, indicating the transformation of WR allocation from single-objective optimization to multi-objective optimization, and the importance of WR allocation, which should be coordinated from multiple aspects such as economy, society, and ecology. Experiments were conducted on its multi-objective genetic algorithm from three aspects: water use assurance rate, economic and ecological benefits, and execution efficiency.
{"title":"Research on the allocation of water resources engineering projects based on multi-objective optimization","authors":"Yongqin Lu, Lu Gan, Yonghua Chen, Ningyao Zheng","doi":"10.2166/ws.2023.153","DOIUrl":"https://doi.org/10.2166/ws.2023.153","url":null,"abstract":"\u0000 The shortage of water resources (WR) directly affects the economic development and ecological environment in the region, and optimizing the allocation of water resources engineering (WRE) projects is the most valid method to solve this problem. Traditional WR allocation methods can no longer solve the complex configuration problems of complex WRE projects, and the emergence of artificial intelligence (AI) technology has not provided new technologies and methods for optimizing WR allocation. This article conducted research on multi-objective optimization configuration of WRE based on AI technology. First, it introduced the current situation and future development direction of WR allocation, indicating the transformation of WR allocation from single-objective optimization to multi-objective optimization, and the importance of WR allocation, which should be coordinated from multiple aspects such as economy, society, and ecology. Experiments were conducted on its multi-objective genetic algorithm from three aspects: water use assurance rate, economic and ecological benefits, and execution efficiency.","PeriodicalId":17553,"journal":{"name":"Journal of Water Supply Research and Technology-aqua","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2023-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76048963","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}
Under the changing environment, the problems of the water cycle and water resources in the basin become extremely complex, and the coordination of water use efficiency and fairness is extremely difficult. This paper takes the Yellow River Basin as the key research area and creates a balanced allocation method and model of water resources that take into account the fairness and efficiency of water use. The dynamic equilibrium allocation of water resources increment brought by new water source projects and regulation projects is realized, and the fine-tuning optimization of the water distribution scheme is realized. The results show that the optimal adjustment strategy of the water diversion scheme is to increase the upstream water allocation, and the adjustment range is 2.13%. The water allocation in the middle reaches was slightly increased by 0.25% to reduce the downstream and Hebei Province, Tianjin water allocation, and the adjustment range is −3.81%. The optimization scheme reflects the principle of ecological priority, guarantees the basic ecological environment water use in the Yellow River, balances the fairness and efficiency of economic and social water use outside the river, and provides technical support for water resources security in water-shortage basins.
{"title":"Study on the method and model of water balance allocation of the Yellow River with overall fairness and efficiency","authors":"Yu Wang, Shaoming Peng, J. Wu, Fang Wan, Xiaokang Zheng, X. Zhou, Wenxiu Shang, Fei Zhang","doi":"10.2166/ws.2023.145","DOIUrl":"https://doi.org/10.2166/ws.2023.145","url":null,"abstract":"\u0000 Under the changing environment, the problems of the water cycle and water resources in the basin become extremely complex, and the coordination of water use efficiency and fairness is extremely difficult. This paper takes the Yellow River Basin as the key research area and creates a balanced allocation method and model of water resources that take into account the fairness and efficiency of water use. The dynamic equilibrium allocation of water resources increment brought by new water source projects and regulation projects is realized, and the fine-tuning optimization of the water distribution scheme is realized. The results show that the optimal adjustment strategy of the water diversion scheme is to increase the upstream water allocation, and the adjustment range is 2.13%. The water allocation in the middle reaches was slightly increased by 0.25% to reduce the downstream and Hebei Province, Tianjin water allocation, and the adjustment range is −3.81%. The optimization scheme reflects the principle of ecological priority, guarantees the basic ecological environment water use in the Yellow River, balances the fairness and efficiency of economic and social water use outside the river, and provides technical support for water resources security in water-shortage basins.","PeriodicalId":17553,"journal":{"name":"Journal of Water Supply Research and Technology-aqua","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2023-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76505165","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}
In the modern day, water is a crucial resource for advancing society and preserving ecological balance. Growth, which lessens poverty and increases equality, is often seen as inextricably linked to the effective use of water resources. Traditional water system management aims to optimize surface water and subsurface aquifers to meet conflicting needs. As a result, the special difficulties in water resource management (WRM) would be exacerbated by the added uncertainty brought on by climatic change. Managing the world's water supplies sustainably is crucial to the planet's continued existence and prosperity. However, ecological planning for sustainable water development is difficult because of complex impacts, random processes, and hydrological restrictions. The study was inspired to address the issues head-on by creating a hybrid AI algorithm for ecological water resource sustainability and digital finance (HAI-EWRS-DF) system for solving complex, multi-scale problems in WRM. Control mechanisms, including social, financial, and sustainability on ground-level and surface-level water resource facilities, are recommended to enhance WRM to increase the applicable revenue, promote community well-being, and pave the way for greater economic development.
{"title":"Quantitative analysis and management of sustainable development of ecological water resources and digital financial system based on an intelligent algorithm","authors":"Qiuju Chen, Shuai Fu","doi":"10.2166/ws.2023.152","DOIUrl":"https://doi.org/10.2166/ws.2023.152","url":null,"abstract":"\u0000 \u0000 In the modern day, water is a crucial resource for advancing society and preserving ecological balance. Growth, which lessens poverty and increases equality, is often seen as inextricably linked to the effective use of water resources. Traditional water system management aims to optimize surface water and subsurface aquifers to meet conflicting needs. As a result, the special difficulties in water resource management (WRM) would be exacerbated by the added uncertainty brought on by climatic change. Managing the world's water supplies sustainably is crucial to the planet's continued existence and prosperity. However, ecological planning for sustainable water development is difficult because of complex impacts, random processes, and hydrological restrictions. The study was inspired to address the issues head-on by creating a hybrid AI algorithm for ecological water resource sustainability and digital finance (HAI-EWRS-DF) system for solving complex, multi-scale problems in WRM. Control mechanisms, including social, financial, and sustainability on ground-level and surface-level water resource facilities, are recommended to enhance WRM to increase the applicable revenue, promote community well-being, and pave the way for greater economic development.","PeriodicalId":17553,"journal":{"name":"Journal of Water Supply Research and Technology-aqua","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2023-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81192402","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}
Zhigang Ye, Ping Miao, Ning Li, Yong Wang, Wenli Zhang, Shan Yin
In the current century, the sustainable production of agricultural products is one of the main challenges facing humanity. The amount of water consumption, energy, and net income as important components of the sustainability of agricultural systems is of special priority and importance. This study used linear and multi-objective programming models with the aim of maximizing five indicators of cost efficiency (CE), irrigation efficiency (IE), energy productivity (EP), energy efficiency (EE), and food efficiency (FE) to determine the cropping pattern of small-scale farms cultivated per hectare in the agricultural year. There are 160 questionnaires classified by random sampling method in agricultural sectors in Inner Mongolia, China. The results showed that determining the cropping pattern using multi-objective planning increases irrigation efficiency and energy efficiency compared with linear modeling. Considering the conditions of limited water resources in the region and the policies of the country in the agricultural sector, cropping patterns with the objective functions of maximization of IE and CE were proposed.
{"title":"Optimizing water efficiency and energy productivity in choosing a cropping pattern","authors":"Zhigang Ye, Ping Miao, Ning Li, Yong Wang, Wenli Zhang, Shan Yin","doi":"10.2166/ws.2023.148","DOIUrl":"https://doi.org/10.2166/ws.2023.148","url":null,"abstract":"\u0000 In the current century, the sustainable production of agricultural products is one of the main challenges facing humanity. The amount of water consumption, energy, and net income as important components of the sustainability of agricultural systems is of special priority and importance. This study used linear and multi-objective programming models with the aim of maximizing five indicators of cost efficiency (CE), irrigation efficiency (IE), energy productivity (EP), energy efficiency (EE), and food efficiency (FE) to determine the cropping pattern of small-scale farms cultivated per hectare in the agricultural year. There are 160 questionnaires classified by random sampling method in agricultural sectors in Inner Mongolia, China. The results showed that determining the cropping pattern using multi-objective planning increases irrigation efficiency and energy efficiency compared with linear modeling. Considering the conditions of limited water resources in the region and the policies of the country in the agricultural sector, cropping patterns with the objective functions of maximization of IE and CE were proposed.","PeriodicalId":17553,"journal":{"name":"Journal of Water Supply Research and Technology-aqua","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2023-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88396366","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}
In this study, the effect of economic growth, energy consumption, biological capacity, and trade liberalization on the economic water footprint of consumption as an indicator of environmental degradation was investigated. An optimization framework was developed to find the maximum values of economic water footprint based on environmental, ecological, energy, and technical constraints. The results of the study showed that the simulated relationship can be used together to estimate long-term relationships between variables, there is a positive and significant relationship between ecological footprint and biological capacity and a negative and significant relationship between trade globalization and economic water footprint. The middle form of the ecological footprint N also increases energy consumption leading to an increase in the economic water footprint. Moreover, the results showed that there is a relationship with economic growth, and this indicates that the increase in economic growth in this region will lead to further destruction of the environment.
{"title":"The effect of water footprint and economic growth on environmental degradation: applications of optimization modeling","authors":"Yunrong Li, Y. Dou","doi":"10.2166/ws.2023.149","DOIUrl":"https://doi.org/10.2166/ws.2023.149","url":null,"abstract":"\u0000 In this study, the effect of economic growth, energy consumption, biological capacity, and trade liberalization on the economic water footprint of consumption as an indicator of environmental degradation was investigated. An optimization framework was developed to find the maximum values of economic water footprint based on environmental, ecological, energy, and technical constraints. The results of the study showed that the simulated relationship can be used together to estimate long-term relationships between variables, there is a positive and significant relationship between ecological footprint and biological capacity and a negative and significant relationship between trade globalization and economic water footprint. The middle form of the ecological footprint N also increases energy consumption leading to an increase in the economic water footprint. Moreover, the results showed that there is a relationship with economic growth, and this indicates that the increase in economic growth in this region will lead to further destruction of the environment.","PeriodicalId":17553,"journal":{"name":"Journal of Water Supply Research and Technology-aqua","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2023-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83456825","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}
The precise correction of water and energy balance is a significant difficulty in studying turbulence energy balance and water flow for agricultural purposes. The need for efficient water and energy management is growing as the world struggles to keep up with rising water and energy demands. This research examines artificial intelligence (AI)'s impact on the water flow and energy balance confluence subnetwork of sensing elements from all the original network's nodes. The study proposed an AI-based optimized sensor energy balance model (AI-SEBM) that uses pressure data to maintain energy balance in turbines and save water with the optimized energy source for agriculture usage. This research explores the potential for installing Kalpan hydraulic turbines, which are most effective during half-load operation, and to forecast all loads with little computing effort to balance energy in turbulence. To anticipate daily pressure readings and energy consumption across all nodes in the network, an AI-based optimization wireless sensor network is designed for communication and linked to an energy balance system. Sensors are strategically deployed at the network's nerve centres. The maximum flow algorithm is used for a grid representing the water and energy balance to determine the positions of the virtual nodes.
{"title":"Application of artificial intelligence and communication technology to water and energy balance models","authors":"Guanxiong Zhang, Ye-Cheng Jin, Bingqiang Wang","doi":"10.2166/ws.2023.147","DOIUrl":"https://doi.org/10.2166/ws.2023.147","url":null,"abstract":"\u0000 \u0000 The precise correction of water and energy balance is a significant difficulty in studying turbulence energy balance and water flow for agricultural purposes. The need for efficient water and energy management is growing as the world struggles to keep up with rising water and energy demands. This research examines artificial intelligence (AI)'s impact on the water flow and energy balance confluence subnetwork of sensing elements from all the original network's nodes. The study proposed an AI-based optimized sensor energy balance model (AI-SEBM) that uses pressure data to maintain energy balance in turbines and save water with the optimized energy source for agriculture usage. This research explores the potential for installing Kalpan hydraulic turbines, which are most effective during half-load operation, and to forecast all loads with little computing effort to balance energy in turbulence. To anticipate daily pressure readings and energy consumption across all nodes in the network, an AI-based optimization wireless sensor network is designed for communication and linked to an energy balance system. Sensors are strategically deployed at the network's nerve centres. The maximum flow algorithm is used for a grid representing the water and energy balance to determine the positions of the virtual nodes.","PeriodicalId":17553,"journal":{"name":"Journal of Water Supply Research and Technology-aqua","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2023-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81267201","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}
Oscar Ezekiel Njau, P. Otter, Revocatus Lazaro Machunda, A. Rugaika, K. Wydra, Karoli Nicholas Njau
The consecutive removal of fluoride (defluoridation) and pathogens (disinfection) in drinking water through combined electrocoagulation-inline-electrolytic disinfection (EC–ECl2) process with aluminum and dimension-stable mixed oxide electrodes was reported in this study. Laboratory trials were conducted on the effects of flow rate, initial pH, current density, and supporting electrolytes for defluoridation and disinfection processes. The results have shown that with a flow rate of 10 L/h, initial pH of 6, the current density of 9.4 mA/cm2 (EC cell) and 3.1 mA/cm2 (ECl2 cell), supporting electrolyte concentration of 165 mg/L, and electrolysis time of 50 min, a defluoridation rate of 88% (initial concentration of 12.3 mg/L) and complete disinfection (initial fecal coliforms of 19,700 colony-forming units per 100 mL (CFU/100 mL)) can be reached. The final concentration of fluoride and pathogens in treated water was 1.44 mg/L and 0 CFU/100 mL, which are within the acceptable limit of the World Health Organization and the Tanzania Bureau of Standards of 1.5 mg/L and 0 CFU/100 mL, respectively. The EC–ECl2 system is a promising approach for consecutive defluoridation and disinfection of water to save millions from fluorosis and waterborne diseases. However, optimization potential with regard to energetic efficiency and system complexity was identified.
{"title":"Removal of fluoride and pathogens from water using the combined electrocoagulation-inline-electrolytic disinfection process","authors":"Oscar Ezekiel Njau, P. Otter, Revocatus Lazaro Machunda, A. Rugaika, K. Wydra, Karoli Nicholas Njau","doi":"10.2166/ws.2023.146","DOIUrl":"https://doi.org/10.2166/ws.2023.146","url":null,"abstract":"\u0000 \u0000 The consecutive removal of fluoride (defluoridation) and pathogens (disinfection) in drinking water through combined electrocoagulation-inline-electrolytic disinfection (EC–ECl2) process with aluminum and dimension-stable mixed oxide electrodes was reported in this study. Laboratory trials were conducted on the effects of flow rate, initial pH, current density, and supporting electrolytes for defluoridation and disinfection processes. The results have shown that with a flow rate of 10 L/h, initial pH of 6, the current density of 9.4 mA/cm2 (EC cell) and 3.1 mA/cm2 (ECl2 cell), supporting electrolyte concentration of 165 mg/L, and electrolysis time of 50 min, a defluoridation rate of 88% (initial concentration of 12.3 mg/L) and complete disinfection (initial fecal coliforms of 19,700 colony-forming units per 100 mL (CFU/100 mL)) can be reached. The final concentration of fluoride and pathogens in treated water was 1.44 mg/L and 0 CFU/100 mL, which are within the acceptable limit of the World Health Organization and the Tanzania Bureau of Standards of 1.5 mg/L and 0 CFU/100 mL, respectively. The EC–ECl2 system is a promising approach for consecutive defluoridation and disinfection of water to save millions from fluorosis and waterborne diseases. However, optimization potential with regard to energetic efficiency and system complexity was identified.","PeriodicalId":17553,"journal":{"name":"Journal of Water Supply Research and Technology-aqua","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74014248","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}