H. Hamidifar, M. Ghorbani, M. Bakhshandeh, S. Gholami
Water supply is a crucial concern for planners across all countries, especially in rural communities. This paper proposes a multidimensional approach to examining the effective criteria for water supply projects in rural areas of Iran. The study compares alternative methods of project implementation and employs three multi-criteria decision-making (MCDM) methods: analytical hierarchy process (AHP), Fuzzy-AHP, and technique for order preference by similarity to ideal solution (TOPSIS) to prioritize criteria, sub-criteria, and alternatives. The results indicate that, among the five options analyzed, diverting water from the river and constructing temporary storage dams are the highest priorities, while pipeline branching to the nearby city or village is given the lowest priority. The study reveals that environmental and economic criteria are more critical than social-security and technical-management criteria, while negative environmental impacts and the possibility of risk-taking by subversive agents are the most important among the 14 sub-criteria studied.
{"title":"A multi-criteria multidimensional model for optimal selection of rural water supply systems","authors":"H. Hamidifar, M. Ghorbani, M. Bakhshandeh, S. Gholami","doi":"10.2166/aqua.2023.028","DOIUrl":"https://doi.org/10.2166/aqua.2023.028","url":null,"abstract":"\u0000 \u0000 Water supply is a crucial concern for planners across all countries, especially in rural communities. This paper proposes a multidimensional approach to examining the effective criteria for water supply projects in rural areas of Iran. The study compares alternative methods of project implementation and employs three multi-criteria decision-making (MCDM) methods: analytical hierarchy process (AHP), Fuzzy-AHP, and technique for order preference by similarity to ideal solution (TOPSIS) to prioritize criteria, sub-criteria, and alternatives. The results indicate that, among the five options analyzed, diverting water from the river and constructing temporary storage dams are the highest priorities, while pipeline branching to the nearby city or village is given the lowest priority. The study reveals that environmental and economic criteria are more critical than social-security and technical-management criteria, while negative environmental impacts and the possibility of risk-taking by subversive agents are the most important among the 14 sub-criteria studied.","PeriodicalId":34693,"journal":{"name":"AQUA-Water Infrastructure Ecosystems and Society","volume":"23 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91068358","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 Penman–Monteith evapotranspiration (ET) model has superior predictive ability than the other methods, but it is challenging to apply for several Indian stations, owing to the need for a large number of climatic variables. The study investigated an artificial neural network (ANN) model for calculating ET for various agro-climatic regions of India. Sensitivity analysis showed that the overall average change in ET0 values for 25% change in the climatic variables were 18, 16, 14, 7, 5, and 4%, respectively, for Tmax, RHmean, Rn, wind speed, Tmin, and sunshine hours. The dominant climatic variables were identified from the principal component analysis (PCA) and ET0 was computed using an ANN with dominant climatic variables. The ANN architecture with backpropagation technique had one hidden layer and neurons ranging from 10 to 30 for all climatic variables and from 5 to 10 for PCA variables. The new ET models were statistically compared with Penman–Monteith ET estimate, and found reliable. PCA variables guaranteed an estimate of ET0 accounting for 98% of the variability. The average values of coefficient of determination, standard error of estimate, and percentage efficiency were observed as 0.96, 0.24, and 94%, respectively.
{"title":"ANN-based PCA to predict evapotranspiration: a case study in India","authors":"M. Abraham, S. Mohan","doi":"10.2166/aqua.2023.201","DOIUrl":"https://doi.org/10.2166/aqua.2023.201","url":null,"abstract":"\u0000 \u0000 The Penman–Monteith evapotranspiration (ET) model has superior predictive ability than the other methods, but it is challenging to apply for several Indian stations, owing to the need for a large number of climatic variables. The study investigated an artificial neural network (ANN) model for calculating ET for various agro-climatic regions of India. Sensitivity analysis showed that the overall average change in ET0 values for 25% change in the climatic variables were 18, 16, 14, 7, 5, and 4%, respectively, for Tmax, RHmean, Rn, wind speed, Tmin, and sunshine hours. The dominant climatic variables were identified from the principal component analysis (PCA) and ET0 was computed using an ANN with dominant climatic variables. The ANN architecture with backpropagation technique had one hidden layer and neurons ranging from 10 to 30 for all climatic variables and from 5 to 10 for PCA variables. The new ET models were statistically compared with Penman–Monteith ET estimate, and found reliable. PCA variables guaranteed an estimate of ET0 accounting for 98% of the variability. The average values of coefficient of determination, standard error of estimate, and percentage efficiency were observed as 0.96, 0.24, and 94%, respectively.","PeriodicalId":34693,"journal":{"name":"AQUA-Water Infrastructure Ecosystems and Society","volume":"9 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89392413","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}
Water is the most important renewable natural resource. Water management is very important for human life sustainability. Rainfall forecasting is one of the most important factors for the water management of an area. A time series is a collection of observations of a variable taken at regular intervals of time. A forecast, on the other hand, is simply a calculation of what happens in the future of the variable of interest based on past information under the assumption that the pattern followed in the past would continue in the future also. This work will aim at obtaining forecasting models for the time series dataset using conventional models and computational models. Varanasi City's annual climate data for a total of 113 years (1906–2018) will be used for the analysis. Initially, the individual model will be considered and used for forecasting. Later, hybrid models will be considered and a comparison between individual models and hybrid models would be obtained. The individual statistical models to be considered are moving average, exponential smoothing with one parameter, and the classical model autoregressive integrated moving average (ARIMA). The forecast is also done individually using the computational model k-nearest neighbor (kNN) and interpolation technique cubic spline.
{"title":"Climate change forecasting using data mining algorithms","authors":"Parul Khatri, Tripti Arjariya, Nikita Shivhare Mitra","doi":"10.2166/aqua.2023.046","DOIUrl":"https://doi.org/10.2166/aqua.2023.046","url":null,"abstract":"\u0000 \u0000 Water is the most important renewable natural resource. Water management is very important for human life sustainability. Rainfall forecasting is one of the most important factors for the water management of an area. A time series is a collection of observations of a variable taken at regular intervals of time. A forecast, on the other hand, is simply a calculation of what happens in the future of the variable of interest based on past information under the assumption that the pattern followed in the past would continue in the future also. This work will aim at obtaining forecasting models for the time series dataset using conventional models and computational models. Varanasi City's annual climate data for a total of 113 years (1906–2018) will be used for the analysis. Initially, the individual model will be considered and used for forecasting. Later, hybrid models will be considered and a comparison between individual models and hybrid models would be obtained. The individual statistical models to be considered are moving average, exponential smoothing with one parameter, and the classical model autoregressive integrated moving average (ARIMA). The forecast is also done individually using the computational model k-nearest neighbor (kNN) and interpolation technique cubic spline.","PeriodicalId":34693,"journal":{"name":"AQUA-Water Infrastructure Ecosystems and Society","volume":"95 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77321897","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}
Water supply and sanitation development in developing countries specifically in Ethiopia appear to be in substantial progress. Governments, international organizations, and other organizations are contributing to the development of water supply and sanitation systems. Water supply and sanitation challenges are linked to climate change effects and the quest for climate-resilient development. This paper evaluates the current challenges in water supply and sanitation development in developing countries and infrastructure resilience. The research is based on the data collected throughout the practical development task. Some of the findings were the climate change effect and temporary adaptation mechanisms, such as intermittent supply causing further pressure variation and water loss in the system. Resilient water supply and sanitation development require an integrated approach based on practical experiences, the latest technological development in water supply and sanitation system operation and management tools, and climate change adaptation. A seamless understanding of engineering, management, and technology is required for the development and management of water supply and sanitation systems. Dispersed skills may be available that were not effective at this time, which calls for a different approach to training provision and skill development as a package on design, management, and recent technological support.
{"title":"Water infrastructure resilience and water supply and sanitation development challenges in developing countries","authors":"Abebe Tadesse Bulti, Gonse Amelo Yutura Amelo","doi":"10.2166/aqua.2023.037","DOIUrl":"https://doi.org/10.2166/aqua.2023.037","url":null,"abstract":"\u0000 Water supply and sanitation development in developing countries specifically in Ethiopia appear to be in substantial progress. Governments, international organizations, and other organizations are contributing to the development of water supply and sanitation systems. Water supply and sanitation challenges are linked to climate change effects and the quest for climate-resilient development. This paper evaluates the current challenges in water supply and sanitation development in developing countries and infrastructure resilience. The research is based on the data collected throughout the practical development task. Some of the findings were the climate change effect and temporary adaptation mechanisms, such as intermittent supply causing further pressure variation and water loss in the system. Resilient water supply and sanitation development require an integrated approach based on practical experiences, the latest technological development in water supply and sanitation system operation and management tools, and climate change adaptation. A seamless understanding of engineering, management, and technology is required for the development and management of water supply and sanitation systems. Dispersed skills may be available that were not effective at this time, which calls for a different approach to training provision and skill development as a package on design, management, and recent technological support.","PeriodicalId":34693,"journal":{"name":"AQUA-Water Infrastructure Ecosystems and Society","volume":"47 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77592487","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}
Accurate forecasting of hydrological processes and sustainable management of water resources is inevitable, especially for flood control and water resource shortage crisis in low-water areas with an arid and semi-arid climate, which is a limitation for residents and various structures. The present study uses different data preprocessing techniques to deal with complex data and extract hidden features from the stream time series. In the next step, the decomposed time series were used, as input data, to the artificial neural network (ANN) model for streamflow modeling and forecasting. The preprocessors employed, including discrete wavelet transform (DWT), empirical mode decomposition (EMD), complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), successive variational mode decomposition (SVMD), and multi-filter of the smoothing (MFS). These preprocessors were used in hybrid with the ANN model to forecast the daily streamflow. In general, the results showed that the optimal performance of hybrid models has two basic steps. The first step is choosing a suitable approach to utilizing the input data to the model. The second step is to use the appropriate preprocessor. Overall, the results show that the MFS-ANN model in short-term forecasting and the SVMD-ANN model in long-term forecasting performed better than other hybrid models.
{"title":"Performance evaluation of artificial neural network model in hybrids with various preprocessors for river streamflow forecasting","authors":"Sadegh Momeneh, Vahid Nourani","doi":"10.2166/aqua.2023.010","DOIUrl":"https://doi.org/10.2166/aqua.2023.010","url":null,"abstract":"\u0000 \u0000 Accurate forecasting of hydrological processes and sustainable management of water resources is inevitable, especially for flood control and water resource shortage crisis in low-water areas with an arid and semi-arid climate, which is a limitation for residents and various structures. The present study uses different data preprocessing techniques to deal with complex data and extract hidden features from the stream time series. In the next step, the decomposed time series were used, as input data, to the artificial neural network (ANN) model for streamflow modeling and forecasting. The preprocessors employed, including discrete wavelet transform (DWT), empirical mode decomposition (EMD), complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), successive variational mode decomposition (SVMD), and multi-filter of the smoothing (MFS). These preprocessors were used in hybrid with the ANN model to forecast the daily streamflow. In general, the results showed that the optimal performance of hybrid models has two basic steps. The first step is choosing a suitable approach to utilizing the input data to the model. The second step is to use the appropriate preprocessor. Overall, the results show that the MFS-ANN model in short-term forecasting and the SVMD-ANN model in long-term forecasting performed better than other hybrid models.","PeriodicalId":34693,"journal":{"name":"AQUA-Water Infrastructure Ecosystems and Society","volume":"26 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87379767","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}
Ayilobeni Kikon, B. M. Dodamani, S. Barma, Sujay Raghavendra Naganna
Drought is a natural hazard that is characterized by a low amount of precipitation in a region. In order to evaluate the drought-related issues that cause chaos for human well-being, drought indices have become increasingly important. In this study, the monthly precipitation data from 1964 to 2013 (about 50 years) of the Jodhpur district in the drought-prone Rajasthan state of India was used to derive the effective drought index (EDI). The machine learning models hybridized with evolutionary optimizers such as the genetic algorithm adaptive neuro-fuzzy inference system (GA-ANFIS) and particle swarm optimization ANFIS (PSO-ANFIS) were used in addition to the generalized regression neural network (GRNN) to predict the EDI index. Using the partial autocorrelation function (PACF), models for forecasting the monthly EDI were constructed with 2-, 3- and 5-input combinations to evaluate their outcomes based on various performance indices. The results of the different combination models were compared. With reference to 2-input and 3-input combination models, both GA-ANFIS and PSO-ANFIS show better performance results with R2 = 0.75, while among the models with 5-input combination, GA-ANFIS depicts better performance results compared to other models with R2 = 0.78. The results are presented suitably with the aid of scatter plots, Taylor's diagram and violin plots. Overall, the GA-ANFIS and PSO-ANFIS models outperformed the GRNN model.
{"title":"ANFIS-based soft computing models for forecasting effective drought index over an arid region of India","authors":"Ayilobeni Kikon, B. M. Dodamani, S. Barma, Sujay Raghavendra Naganna","doi":"10.2166/aqua.2023.204","DOIUrl":"https://doi.org/10.2166/aqua.2023.204","url":null,"abstract":"\u0000 \u0000 Drought is a natural hazard that is characterized by a low amount of precipitation in a region. In order to evaluate the drought-related issues that cause chaos for human well-being, drought indices have become increasingly important. In this study, the monthly precipitation data from 1964 to 2013 (about 50 years) of the Jodhpur district in the drought-prone Rajasthan state of India was used to derive the effective drought index (EDI). The machine learning models hybridized with evolutionary optimizers such as the genetic algorithm adaptive neuro-fuzzy inference system (GA-ANFIS) and particle swarm optimization ANFIS (PSO-ANFIS) were used in addition to the generalized regression neural network (GRNN) to predict the EDI index. Using the partial autocorrelation function (PACF), models for forecasting the monthly EDI were constructed with 2-, 3- and 5-input combinations to evaluate their outcomes based on various performance indices. The results of the different combination models were compared. With reference to 2-input and 3-input combination models, both GA-ANFIS and PSO-ANFIS show better performance results with R2 = 0.75, while among the models with 5-input combination, GA-ANFIS depicts better performance results compared to other models with R2 = 0.78. The results are presented suitably with the aid of scatter plots, Taylor's diagram and violin plots. Overall, the GA-ANFIS and PSO-ANFIS models outperformed the GRNN model.","PeriodicalId":34693,"journal":{"name":"AQUA-Water Infrastructure Ecosystems and Society","volume":"26 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84613739","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}
Qiwei Lin, Wendan Chen, Fang-Sian Lin, Xuesong Wang, Hu Zhu
Arsenic compounds are classified as Class I carcinogens due to their high toxicity to the organism. Also, they are easily accumulated in water bodies, and both H2AsO4− and HAsO42− are present simultaneously and convert to each other in a wide pH range. Based on the strategy of simultaneous removal of protons to immobilize AsO43−, a monodispersed porous pinecone-like Mg(OH)2 (PLMH) was prepared via a facile and environmentally friendly ultrasound-assisted precipitation route for deep As(V) removal. The PLMH presents a porous and stable framework structure formed by crossed lamellae, and the As(V) solution can be completely immersed inside, which gives a ‘surface effect’ inside the microsphere and makes the As(V) capture performance much higher than the general adsorbents by the removal of protons to immobilize AsO43−. In addition, the PLMH has an extremely wide pH applicability range (pH 3–12), special pH effects, and symmetry phenomena. These performances indicate that the PLMH can be a good candidate for the treatment of real arsenic industrial wastewater.
{"title":"Exaggerated arsenic removal efficiency and pH adaptability by adsorption using monodispersed porous pinecone-like magnesium hydroxide","authors":"Qiwei Lin, Wendan Chen, Fang-Sian Lin, Xuesong Wang, Hu Zhu","doi":"10.2166/aqua.2023.012","DOIUrl":"https://doi.org/10.2166/aqua.2023.012","url":null,"abstract":"\u0000 \u0000 Arsenic compounds are classified as Class I carcinogens due to their high toxicity to the organism. Also, they are easily accumulated in water bodies, and both H2AsO4− and HAsO42− are present simultaneously and convert to each other in a wide pH range. Based on the strategy of simultaneous removal of protons to immobilize AsO43−, a monodispersed porous pinecone-like Mg(OH)2 (PLMH) was prepared via a facile and environmentally friendly ultrasound-assisted precipitation route for deep As(V) removal. The PLMH presents a porous and stable framework structure formed by crossed lamellae, and the As(V) solution can be completely immersed inside, which gives a ‘surface effect’ inside the microsphere and makes the As(V) capture performance much higher than the general adsorbents by the removal of protons to immobilize AsO43−. In addition, the PLMH has an extremely wide pH applicability range (pH 3–12), special pH effects, and symmetry phenomena. These performances indicate that the PLMH can be a good candidate for the treatment of real arsenic industrial wastewater.","PeriodicalId":34693,"journal":{"name":"AQUA-Water Infrastructure Ecosystems and Society","volume":"20 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87010033","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}
Anoop Narain Singh, Ankur Mudgal, R. P. Tripathi, P. J. Omar
Inadequate sewage treatment plant (STP) capacity, limited power supply, and discharge of partially treated and raw sewage create a significant sanitation problem in Varanasi city, India. This problem becomes severe during the lean period of the river (i.e. from February/March to June/July). To reduce the burden on STPs, sewage can be treated and filtered in a naturally occurring sand bed at the convex bank side of the river. In the present study, a 7-km stretch of the sand bed of River Ganga at Varanasi has been selected. This stretch is divided into three zones: entrance, middle, and exit zones. The objective of this research is to assess the filtration potential of selected sections in respective zones and to find out the most suitable zone, out of the three, for wastewater filtration. Seven basic parameters such as dissolved oxygen, biological oxygen demand, electrical conductivity, total dissolved solids, salinity, pH, and temperature were measured before and after filtration, through the sand bed of the three zones of River Ganga. Of the three selected zones of the river bend, filtration length and the amount of available sand were found to be maximum in the middle zone. Experimental results and survey work show that the sand bed in the middle zone of the river bend is best suited for wastewater disposal and filtration.
{"title":"Assessment of wastewater treatment potential of sand beds of River Ganga at Varanasi, India","authors":"Anoop Narain Singh, Ankur Mudgal, R. P. Tripathi, P. J. Omar","doi":"10.2166/aqua.2023.200","DOIUrl":"https://doi.org/10.2166/aqua.2023.200","url":null,"abstract":"\u0000 Inadequate sewage treatment plant (STP) capacity, limited power supply, and discharge of partially treated and raw sewage create a significant sanitation problem in Varanasi city, India. This problem becomes severe during the lean period of the river (i.e. from February/March to June/July). To reduce the burden on STPs, sewage can be treated and filtered in a naturally occurring sand bed at the convex bank side of the river. In the present study, a 7-km stretch of the sand bed of River Ganga at Varanasi has been selected. This stretch is divided into three zones: entrance, middle, and exit zones. The objective of this research is to assess the filtration potential of selected sections in respective zones and to find out the most suitable zone, out of the three, for wastewater filtration. Seven basic parameters such as dissolved oxygen, biological oxygen demand, electrical conductivity, total dissolved solids, salinity, pH, and temperature were measured before and after filtration, through the sand bed of the three zones of River Ganga. Of the three selected zones of the river bend, filtration length and the amount of available sand were found to be maximum in the middle zone. Experimental results and survey work show that the sand bed in the middle zone of the river bend is best suited for wastewater disposal and filtration.","PeriodicalId":34693,"journal":{"name":"AQUA-Water Infrastructure Ecosystems and Society","volume":"102 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79887740","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}
J. A. Oyetade, A. Hilonga, Revocatus Lazaro Machunda
Effluents resulting from the frequent use of industrial azo dyes in textile operations have posed great toxicological impacts on man and the environment. The limitations of conventional treatment infrastructure necessitate the use of rapid Fenton-mediated catalytic systematic process to tackle the attendant treatment limitations. The study applied in situ Fenton-mediation process with constructed low power UV-LED reactor for rapid catalytic treatment of dye-laden effluent using enhanced acid and alkali TiO2-nanoparticles (Nps) (1–5%, i.e. 1–5 M) at definite experimental conditions, respectively. A comprehensive instrumental study was done to access the morphological, functional and elemental constituents of these nanocatalysts. The performance of the respective catalyst was evaluated using methylene blue (MB) dye at definite experimental conditions of pH, dosage, concentration and irradiation time. The results revealed a mesoporous structural nanocatalyst with increasing surface area after enhanced modification. The optimal experimental conditions of pH and concentration were recorded as 5 and 10 mg/L, respectively. While the most efficient nanocatalyst was 3 wt% alkali-modified TiO2 (3% Ak-TiO2) having a degradation efficiency of 89.15% at 90 min of irradiation using 50 mg dosage in contrast to higher irradiation time and catalyst dosage for other catalysts.
{"title":"Performance evaluation of in situ Fenton-mediated photocatalysis of industrial dye effluent with enhanced TiO2 nanoparticle","authors":"J. A. Oyetade, A. Hilonga, Revocatus Lazaro Machunda","doi":"10.2166/aqua.2023.027","DOIUrl":"https://doi.org/10.2166/aqua.2023.027","url":null,"abstract":"\u0000 \u0000 Effluents resulting from the frequent use of industrial azo dyes in textile operations have posed great toxicological impacts on man and the environment. The limitations of conventional treatment infrastructure necessitate the use of rapid Fenton-mediated catalytic systematic process to tackle the attendant treatment limitations. The study applied in situ Fenton-mediation process with constructed low power UV-LED reactor for rapid catalytic treatment of dye-laden effluent using enhanced acid and alkali TiO2-nanoparticles (Nps) (1–5%, i.e. 1–5 M) at definite experimental conditions, respectively. A comprehensive instrumental study was done to access the morphological, functional and elemental constituents of these nanocatalysts. The performance of the respective catalyst was evaluated using methylene blue (MB) dye at definite experimental conditions of pH, dosage, concentration and irradiation time. The results revealed a mesoporous structural nanocatalyst with increasing surface area after enhanced modification. The optimal experimental conditions of pH and concentration were recorded as 5 and 10 mg/L, respectively. While the most efficient nanocatalyst was 3 wt% alkali-modified TiO2 (3% Ak-TiO2) having a degradation efficiency of 89.15% at 90 min of irradiation using 50 mg dosage in contrast to higher irradiation time and catalyst dosage for other catalysts.","PeriodicalId":34693,"journal":{"name":"AQUA-Water Infrastructure Ecosystems and Society","volume":"48 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88198472","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}
Iram Shahzadi, S. Mubarak, A. Farooq, Naqi Hussain
Solid waste management (SWM) is one of the biggest concerns of society and agricultural waste is generated in vast amount. In this study removal of Cu and Cr from wastewater using chemically modified apple peels was studied by following batch sorption experiments. Effects of metal concentration, adsorbent dose, pH, temperature and contact duration on the adsorption of Cu & Cr were investigated by using atomic adsorption spectrophotometer (AAS). SEM & EDX analysis of the adsorbents were recorded to study the morphology of the prepared adsorbents. Qmax value of apple peels is 25 for Cr & 22 for Cu, while for apple peel charcoal it is 33 for Cr & 47 for Cu, for treated apple peels Qmax is 50 for Cr & 52 for Cu adsorption. The data was processed using pseudo first, second order kinetic and intraparticle diffusion. Results depicted that the calculated adsorption capacities (qecal) were found to be close to the experimental values (qecal) by following pseudo-second order kinetics. The applicability of the Langmuir and Freundlich adsorption isotherms was tested. Results showed that Langmuir model is best fitted on adsorption data because regression factor R2 values are good for Langmuir model.
{"title":"Apple peels as a potential adsorbent for removal of Cu and Cr from wastewater","authors":"Iram Shahzadi, S. Mubarak, A. Farooq, Naqi Hussain","doi":"10.2166/aqua.2023.216","DOIUrl":"https://doi.org/10.2166/aqua.2023.216","url":null,"abstract":"\u0000 \u0000 Solid waste management (SWM) is one of the biggest concerns of society and agricultural waste is generated in vast amount. In this study removal of Cu and Cr from wastewater using chemically modified apple peels was studied by following batch sorption experiments. Effects of metal concentration, adsorbent dose, pH, temperature and contact duration on the adsorption of Cu & Cr were investigated by using atomic adsorption spectrophotometer (AAS). SEM & EDX analysis of the adsorbents were recorded to study the morphology of the prepared adsorbents. Qmax value of apple peels is 25 for Cr & 22 for Cu, while for apple peel charcoal it is 33 for Cr & 47 for Cu, for treated apple peels Qmax is 50 for Cr & 52 for Cu adsorption. The data was processed using pseudo first, second order kinetic and intraparticle diffusion. Results depicted that the calculated adsorption capacities (qecal) were found to be close to the experimental values (qecal) by following pseudo-second order kinetics. The applicability of the Langmuir and Freundlich adsorption isotherms was tested. Results showed that Langmuir model is best fitted on adsorption data because regression factor R2 values are good for Langmuir model.","PeriodicalId":34693,"journal":{"name":"AQUA-Water Infrastructure Ecosystems and Society","volume":"5 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73087458","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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