Modeling of environmental aspects related to reverse osmosis desalination supply chain

open access journalBackground: This study aimed to model optimization of strategic environmental management decisions in the operation of reverse osmosis desalination, emphasizing the costs required for the environmental protection during the production of freshwater using reverse osmosis technology. Methods: This analytical research was conducted in five cities of Hormozgan province in Iran for 18 months from February 2018 to September 2019. The research includes eight phases of defining the research problem, data collection, preliminary data analysis and decision criteria, mathematical modeling, model validation, information preparation, analysis and finally discussion, conclusions and suggestions. The main environmental issues were the carbon dioxide (CO2) release rate due to power demand and rejected brine water (RBW) were entered the mathematical model. Results: The desalination plants of Abu Musa, Bandar Abbas, Qeshm, Sirik, and Hormoz with water production flow rate of 2100, 89 000, 5300, 3300 and 1500 m3/d can generate 2360.82, 100053.80, 5958.260, 3709.86 and 1686.30 tons/year of CO2 emissions respectively. This output requires 1.35, 57.47,3.42, 2.13 and 0.97 million USD for controlling the process, respectively. For reduction of the negative effect of RBW 0.75, 22.79, 1.78, 1.15 and 0.55 million USD respectively, is needed. Conclusion: Recommendations for environmental impacts protection of RBW, for desalination capacity up to 50 000 m3/d, are; (a) for desalination capacity up to 50 000 m3/d; dilution the RBW using raw water before entering into the sea, (b) for capacity of 50 000-100 000 m3/d; dispersing RBW in sea using diffuser, and (c) for capacity more than 100 000 m3/d; hybrid water desalination plants and power plant. Application of power plant cooling water to dilute RBW may reduce cost

Integration of environmental aspects in modelling and optimisation of water supply chains

Climate change becomes increasingly more relevant in the context of water systems planning. Tools are necessary to provide the most economic investment option considering the reliability of the infrastructure from technical and environmental perspectives. Accordingly, in this work, an optimisation approach, formulated as a spatially-explicit multi-period Mixed Integer Linear Programming (MILP) model, is proposed for the design of water supply chains at regional and national scales. The optimisation framework encompasses decisions such as installation of new purification plants, capacity expansion, and raw water trading schemes. The objective is to minimise the total cost incurring from capital and operating expenditures. Assessment of available resources for withdrawal is performed based on hydrological balances, governmental rules and sustainable limits. In the light of the increasing importance of reliability of water supply, a second objective, seeking to maximise the reliability of the supply chains, is introduced. The epsilon-constraint method is used as a solution procedure for the multi-objective formulation. Nash bargaining approach is applied to investigate the fair trade-offs between the two objectives and find the Pareto optimality. The models' capability is addressed through a case study based on Australia. The impact of variability in key input parameters is tackled through the implementation of a rigorous global sensitivity analysis (GSA). The findings suggest that variations in water demand can be more disruptive for the water supply chain than scenarios in which rainfalls are reduced. The frameworks can facilitate governmental multi-aspect decision making processes for the adequate and strategic investments of regional water supply infrastructure

Sustainability ranking of desalination plants using Mamdani Fuzzy Logic Inference Systems

As water desalination continues to expand globally, desalination plants are continually under pressure to meet the requirements of sustainable development. However, the majority of desalination sustainability research has focused on new desalination projects, with limited research on sustainability performance of existing desalination plants. This is particularly important while considering countries with limited resources for freshwater such as the United Arab Emirates (UAE) as it is heavily reliant on existing desalination infrastructure. In this regard, the current research deals with the sustainability analysis of desalination processes using a generic sustainability ranking framework based on Mamdani Fuzzy Logic Inference Systems. The fuzzy-based models were validated using data from two typical desalination plants in the UAE. The promising results obtained from the fuzzy ranking framework suggest this more in-depth sustainability analysis should be beneficial due to its flexibility and adaptability in meeting the requirements of desalination sustainability

China's roadmap to low-carbon electricity and water: Disentangling greenhouse gas (GHG) emissions from electricity-water nexus via renewable wind and solar power generation, and carbon capture and storage

Electricity and water form an intricate nexus, in that water is crucial for power generation, and electricity (or other primary forms of energy) is the key enabler for water purification and waste-water treatment. Nonetheless, both energy conversion and water purification result in substantial amounts of greenhouse gas (GHG) emissions. These negative interactions with potential “snowball” effect, can be decoupled via the deployment of renewable power generation, and carbon capture from fossil-fuelled technologies. However, such retrofits pose new challenges as wind and solar energy exhibit intermittent generation patterns. In addition, integrating thermal power plants with carbon capture and storage (CCS) imposes energy penalties and increases water requirements. In the present research, an optimization framework is developed which enables systematic decision-making for the retrofit of existing power and water infrastructure as well as investment in renewable and green technologies. A key aspect of the applied framework is the simultaneous optimization of design and operational decisions in the presence of uncertainties in the water demand, electricity demand, as well as wind and solar power availability. The proposed methodology is demonstrated for the case of the water-electricity nexus in China, and provides in-depth insights into regional characteristics of low carbon electricity generation, and their implications for water purification and wastewater treatment, demonstrating a roadmap towards sustainable energy and electricity

Electrochemical Process for Diazinon Removal from Aqueous Media: Design of Experiments, Optimization, and DLLME-GC-FID Method for Diazinon Determination

In the present study, electrochemical process was studied via removal of diazinon (O,O-diethyl O-2-isopropyl-6-methylpyrimidin-4-yl phosphorothioate) as an insecticide/ acaricide organic case study. Influences of three operational parameters including initial ferrous ion concentration, initial hydrogen peroxide concentration, and initial diazinon concentration were measured and optimized in diazinon removal process. Response surface methodology (RSM) was used to design the experiments. The experimental data collected in a laboratory-scaled batch reactor equipped with four graphite bar electrodes as cathode and an aluminum sheet electrode as an anode. Quantitative analysis of diazinon was done with gas chromatography equipped with flame photometric detector. Disperse liquid–liquid microextraction was used prior to gas chromatography in order to extraction and preconcentration of diazinon from aqueous media to extraction phase. Acetone and chlorobenzene were used as disperser and extraction solvent, respectively. Maximum diazinon removal efficiency of 87% (0.85mg mass removal) in C0 of 2mg/L and 80% (120mg mass removal) in C0 of 300mg/L was achieved under different experimental conditions. The obtained experimental data were used for model building by RSM approach. Finally, optimization process was carried out using RSM algorithm. © 2015, King Fahd University of Petroleum & Minerals

Ocean Energy in Belgium - 2019

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Modeling of environmental aspects related to reverse osmosis desalination supply chain

Background: This study aimed to model optimization of strategic environmental management decisions in the operation of reverse osmosis desalination, emphasizing the costs required for the environmental protection during the production of freshwater using reverse osmosis technology. Methods: This analytical research was conducted in five cities of Hormozgan province in Iran for 18 months from February 2018 to September 2019. The research includes eight phases of defining the research problem, data collection, preliminary data analysis and decision criteria, mathematical modeling, model validation, information preparation, analysis and finally discussion, conclusions and suggestions. The main environmental issues were the carbon dioxide (CO2) release rate due to power demand and rejected brine water (RBW) were entered the mathematical model. Results: The desalination plants of Abu Musa, Bandar Abbas, Qeshm, Sirik, and Hormoz with water production flow rate of 2100, 89 000, 5300, 3300 and 1500 m3/d can generate 2360.82, 100053.80, 5958.260, 3709.86 and 1686.30 tons/year of CO2 emissions respectively. This output requires 1.35, 57.47, 3.42, 2.13 and 0.97 million USD for controlling the process, respectively. For reduction of the negative effect of RBW 0.75, 22.79, 1.78, 1.15 and 0.55 million USD respectively, is needed. Conclusion: Recommendations for environmental impacts protection of RBW, for desalination capacity up to 50 000 m3/d, are; (a) for desalination capacity up to 50 000 m3/d; dilution the RBW using raw water before entering into the sea, (b) for capacity of 50 000-100 000 m3/d; dispersing RBW in sea using diffuser, and (c) for capacity more than 100 000 m3/d; hybrid water desalination plants and power plant. Application of power plant cooling water to dilute RBW may reduce cost. Keywords: Mathematical modeling, Freshwater, Osmosis, Brine, Seawater

AI and OR in management of operations: history and trends

The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested

Key physicochemical characteristics governing organic micropollutant adsorption and transport in ion-exchange membranes during reverse electrodialysis

The co-generation of electricity and electrodialysis of seawater in a hybrid system is a promising approach to overcome water scarcity. Reverse electrodialysis harvests energy from the salinity gradient, where seawater is used as a high salinity stream while secondary treated wastewater can be used as a sustainable low salinity stream. Treated wastewater contains organic micropollutants, which can be transported to the seawater stream. The current research establishes a connection between adsorption and transport of organic micropollutants in ion exchange membranes, using a cross-flow stack in adsorption and zero-current experiments. To mimic the composition of treated wastewater, a mixture of nineteen organic micropollutants of varied physicochemical characteristics (e.g. size, charge, polarity, hydrogen donor/acceptor count, hydrophobicity) at environmentally relevant concentrations was used. Depending on the charge, micropollutants develop different types of mechanisms responsible for short-distance interactions with ion-exchange membranes, which has a direct influence in their transport behavior. This study provides a rational basis for the optimization/design of next-generation ion-exchange membranes, in which the permeability toward organic micropollutants should be also included. This investigation highly contributes to understanding the potential hazard posed by organic micropollutants in reverse electrodialysis in seawater desalination systems, where treated wastewater is used as a low salinity stream