The Experts below are selected from a list of 174 Experts worldwide ranked by ideXlab platform
Tareq Al-ansari - One of the best experts on this subject based on the ideXlab platform.
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Sustainable Energy-Water-Food Nexus integration and optimisation in eco-industrial parks
Computers & Chemical Engineering, 2021Co-Authors: Jamileh Fouladi, Ahmed Alnouss, Tareq Al-ansariAbstract:Abstract In this study, a representation of the Energy-Water-Food (EWF) Nexus is developed to capture the trade-offs and synergies between sustainability dimensions within an industrial park. A unique systems approach based on thermodynamics is developed to optimise the Nexus and enhance resource efficiency. The case study involves various chemical processes operating in the State of Qatar, which is evaluated to ascertain resource efficiency enhancement possibilities across various scenarios, and considers multiple objectives to capture the trade-offs between minimising the total annual cost and environmental emissions. Furthermore, a sustainability metric is applied to compute the effect of each scenario on EWF resources. In this study, there is emphasis on capturing the synergetic potential from utilising biomass from the food sector. The results indicate that the global warming potential in the best performing scenario decreases by approximately 30 %, while the exergy efficiency of the system is enhanced by 28 %.
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Novel approaches for geospatial risk analytics in the energy–water–food Nexus using an EWF Nexus node
Computers & Chemical Engineering, 2020Co-Authors: Maryam Haji, Rajesh Govindan, Tareq Al-ansariAbstract:Abstract This study introduces a novel energy, water and food Nexus ‘Node’ methodology which includes: (a) decentralization using GIS-based approaches; (b) development of composite geospatial risk indicators using the Analytical Hierarchy Process; and (c) assessment of resource utilization. The methodology is applied to open fields agriculture, conventional greenhouses and hydroponic greenhouses in Qatar using the following nine risk factors: temperature, humidity, solar radiation, soil quality (As and Fe concentration), groundwater depth, groundwater recharge rate, groundwater salinity and groundwater pH. The analysis concludes that the critical factors that increase risk in open field farms are weather factors, such as temperature, solar radiation and humidity, with relative weights of 0.18527, 0.16860 and 0.15785, respectively, whilst groundwater factors have the highest impact on conventional and hydroponic greenhouses. Furthermore, although hydroponic greenhouses are more efficient in terms of water consumption in comparison to open fields, they consume more energy due to cooling and desalination requirements.
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Quantifying the energy, water and food Nexus: A review of the latest developments based on life-cycle assessment
Journal of Cleaner Production, 2018Co-Authors: Mehzabeen Mannan, Tareq Al-ansari, Hamish R Mackey, Sami G. Al-ghamdiAbstract:Abstract Energy, water and food resource scarcity caused by rapid population growth, climate change, imbalanced ecosystems, and economic diversification, is the biggest challenge for today's world. In recent decades, the importance of the interdependent relationship between these resources has been recognized as the Energy-Water-Food Nexus. Sustainable resource consumption and the capability to ascertain true resource consumption is crucial for modern day development. As such, wide-spread adoption of the Energy-Water-Food Nexus methodology for integrated resource modeling can significantly contribute toward resource productivity and continuity. This methodology has expanded over the years, from concept development to application in multiple case studies. The methodology has also enabled the identification of synergies and trade-offs within the sub-systems that constitute the overall Energy-Water-Food Nexus system, hence providing a mechanism for optimization in resource consumption and minimization in the total environmental burden in the system under evaluation. This paper has reviewed the interlinkages inherent in the Energy-Water-Food Nexus, and the progress in developing suitable quantification methods. Although there is no standardized methodology for analysis involving the Energy-Water-Food Nexus, the life-cycle assessment methodology has been used as an enabler for the quantification of environmental burdens of systems evaluated using the ‘Nexus’ approach. As such, this paper will provide an overview of the different applications in which the life cycle assessment methodology has been applied to Energy-Water-Food Nexus analysis. The paper concludes that an integrated life cycle assessment and Energy-Water-Food Nexus methodology is necessary to determine environmental burdens for different scenarios presented within systems operating within an Energy-Water-Food Nexus environment, essentially influencing Energy-Water-Food resource sectors.
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Introduction to life-cycle analysis and the Energy-Water-Food Nexus
Qatar Foundation Annual Research Forum Proceedings, 2012Co-Authors: Tareq Al-ansari, Anna Korre, Nilay ShahAbstract:There is a growing momentum to analyse the broader interdependencies of the energy, water and food systems rather than evaluating them in isolation. As such, the objective of this research is to introduce a methodology which can integrate energy, water and food in one resource model at an appropriate scale and resolution, essentially describing one resource in terms of its constituents. The Nexus can be evaluated using industrial ecology based tools such life cycle analysis (LCA) and material flow analysis (MFA). Industrial ecology is a multidimensional approach to system design such as the food system. Moreover, industrial ecology seeks to use the natural ecosystem as models for the human driven industrial systems, thus developing similarities between industrial systems and naturally occurring ones. Life cycle analysis is defined as the compilation and evaluation of the inputs, outputs and potential environmental impacts of a product system throughout its lifecycle. Qatar is an ideal case study for devel...
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Comparing the convergence and divergence within Industrial Ecology, Circular Economy, and the Energy-Water-Food Nexus based on resource management objectives
Sustainable Production and Consumption, 1Co-Authors: Nayla Ahmad Al-thani, Tareq Al-ansariAbstract:Abstract The increasing need to conserve resources has led to the development of several concepts, tools, and frameworks to support optimum resource management (RM) in the past few decades. However, system designers and policy makers often find it difficult to navigate the wide array of available concepts. Energy-Water-Food Nexus (EWF Nexus), circular economy (CE), and industrial ecology (IE) are discussed in terms of their conceptual development, representative tools used to conduct analysis therein, and the performance indicators deployed to measure progress and performance. Unlike previous literature that focused on one or two of the aforementioned concepts in parallel, this review assesses the three concepts together based on the RM objectives. This review considers three popular concepts that support sustainable RM in terms of potential areas for convergence and divergence. The review is conducted in four stages: (i) identifying the research objective and relevant keywords after extracting articles from well-known databases; (ii) screening articles obtained from stage (i) by removing duplicates and applying predefined inclusion and exclusion criteria; (iii) reviewing the screened articles for eligibility; and (iv) defining the final list of articles to be included in the review and analysing them. The outcomes of this review suggest that the CE and EWF Nexus are more flexible in terms of application scale (i.e. micro, meso, and macro), whereas IE is applied within industrial parks. Most EWF Nexus studies focus on managing interlinkages and synergies between the three resources; however, CE and IE are more likely to focus on closing material/energy loops within defined system boundaries. This review sets the premise for future work, which can help align the three guiding concepts into a combined holistic effort to manage resources depending on the problem considered, either through a single framework or a coordinated effort wherein all three concepts are deployed.
Yang Hong - One of the best experts on this subject based on the ideXlab platform.
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improving water quantity simulation forecasting to solve the energy water food Nexus issue by using heterogeneous computing accelerated global optimization method
Applied Energy, 2018Co-Authors: Mengjie Zhang, Yunzhong Jiang, Jiren Li, Liuqian Ding, Xiaoyan He, Ke Liang, Yang Hong, Hao Wang, Chaochao LiAbstract:Abstract With continuous population increase and economic growth, challenges on securing sufficient energy, water, and food supplies are amplifying. Water plays the most important role in the Energy-Water-Food (E-W-F) Nexus issue such as energy supply (clean hydropower energy generation), water supply (drinking water), and food supply (agricultural irrigation water). Therefore, water quantity simulation & forecasting become an important issue in E-W-F Nexus problem. Water quantity simulation & forecasting model, such as rainfall-runoff (RR) hydrological model has become a useful tool which can significantly improve efficiency of the hydropower energy generation, water supply management, and agricultural irrigation water utilization. The accuracy and reliability of the water quantity simulation & forecasting model are significantly affected by the model parameters. Therefore, demand of effective and fast model parameter optimization tool for solving the E-W-F Nexus problem increases significantly. The shuffled complex evolution developed at University of Arizona (SCE-UA) has been recognized as an effective global model parameter optimization method for more than 20 years and is highly suited to solve the E-W-F Nexus problem. However, the computational efficiency of the SCE-UA dramatically deteriorates when applied to complex E-W-F Nexus problem. For the purpose of solving this conundrum, a fast parallel SCE-UA was proposed in this paper. The parallel SCE-UA was implemented on the novel heterogeneous computing hardware and software systems which were constituted by the Intel multi-core CPU, NVIDIA many-core GPU, and PGI Accelerator Visual Fortran (with OpenMP and CUDA). Performance comparisons between the parallel and serial SCE-UA were carried out based on two case studies, the Griewank benchmark function optimization and a real world IHACRES RR hydrological model parameter optimization. Comparison results indicated that the parallel SCE-UA outperformed the serial one and has good application prospects for solving the water quantity simulation & forecasting model parameter calibration in the E-W-F Nexus problem.
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Improving water quantity simulation & forecasting to solve the Energy-Water-Food Nexus issue by using heterogeneous computing accelerated global optimization method
Applied Energy, 2018Co-Authors: Guangyuan Kan, Yunzhong Jiang, Liuqian Ding, Ke Liang, Yang Hong, Mengjie Zhang, Hao Wang, Depeng ZuoAbstract:Abstract With continuous population increase and economic growth, challenges on securing sufficient energy, water, and food supplies are amplifying. Water plays the most important role in the Energy-Water-Food (E-W-F) Nexus issue such as energy supply (clean hydropower energy generation), water supply (drinking water), and food supply (agricultural irrigation water). Therefore, water quantity simulation & forecasting become an important issue in E-W-F Nexus problem. Water quantity simulation & forecasting model, such as rainfall-runoff (RR) hydrological model has become a useful tool which can significantly improve efficiency of the hydropower energy generation, water supply management, and agricultural irrigation water utilization. The accuracy and reliability of the water quantity simulation & forecasting model are significantly affected by the model parameters. Therefore, demand of effective and fast model parameter optimization tool for solving the E-W-F Nexus problem increases significantly. The shuffled complex evolution developed at University of Arizona (SCE-UA) has been recognized as an effective global model parameter optimization method for more than 20 years and is highly suited to solve the E-W-F Nexus problem. However, the computational efficiency of the SCE-UA dramatically deteriorates when applied to complex E-W-F Nexus problem. For the purpose of solving this conundrum, a fast parallel SCE-UA was proposed in this paper. The parallel SCE-UA was implemented on the novel heterogeneous computing hardware and software systems which were constituted by the Intel multi-core CPU, NVIDIA many-core GPU, and PGI Accelerator Visual Fortran (with OpenMP and CUDA). Performance comparisons between the parallel and serial SCE-UA were carried out based on two case studies, the Griewank benchmark function optimization and a real world IHACRES RR hydrological model parameter optimization. Comparison results indicated that the parallel SCE-UA outperformed the serial one and has good application prospects for solving the water quantity simulation & forecasting model parameter calibration in the E-W-F Nexus problem.
Mengjie Zhang - One of the best experts on this subject based on the ideXlab platform.
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improving water quantity simulation forecasting to solve the energy water food Nexus issue by using heterogeneous computing accelerated global optimization method
Applied Energy, 2018Co-Authors: Mengjie Zhang, Yunzhong Jiang, Jiren Li, Liuqian Ding, Xiaoyan He, Ke Liang, Yang Hong, Hao Wang, Chaochao LiAbstract:Abstract With continuous population increase and economic growth, challenges on securing sufficient energy, water, and food supplies are amplifying. Water plays the most important role in the Energy-Water-Food (E-W-F) Nexus issue such as energy supply (clean hydropower energy generation), water supply (drinking water), and food supply (agricultural irrigation water). Therefore, water quantity simulation & forecasting become an important issue in E-W-F Nexus problem. Water quantity simulation & forecasting model, such as rainfall-runoff (RR) hydrological model has become a useful tool which can significantly improve efficiency of the hydropower energy generation, water supply management, and agricultural irrigation water utilization. The accuracy and reliability of the water quantity simulation & forecasting model are significantly affected by the model parameters. Therefore, demand of effective and fast model parameter optimization tool for solving the E-W-F Nexus problem increases significantly. The shuffled complex evolution developed at University of Arizona (SCE-UA) has been recognized as an effective global model parameter optimization method for more than 20 years and is highly suited to solve the E-W-F Nexus problem. However, the computational efficiency of the SCE-UA dramatically deteriorates when applied to complex E-W-F Nexus problem. For the purpose of solving this conundrum, a fast parallel SCE-UA was proposed in this paper. The parallel SCE-UA was implemented on the novel heterogeneous computing hardware and software systems which were constituted by the Intel multi-core CPU, NVIDIA many-core GPU, and PGI Accelerator Visual Fortran (with OpenMP and CUDA). Performance comparisons between the parallel and serial SCE-UA were carried out based on two case studies, the Griewank benchmark function optimization and a real world IHACRES RR hydrological model parameter optimization. Comparison results indicated that the parallel SCE-UA outperformed the serial one and has good application prospects for solving the water quantity simulation & forecasting model parameter calibration in the E-W-F Nexus problem.
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Improving water quantity simulation & forecasting to solve the Energy-Water-Food Nexus issue by using heterogeneous computing accelerated global optimization method
Applied Energy, 2018Co-Authors: Guangyuan Kan, Yunzhong Jiang, Liuqian Ding, Ke Liang, Yang Hong, Mengjie Zhang, Hao Wang, Depeng ZuoAbstract:Abstract With continuous population increase and economic growth, challenges on securing sufficient energy, water, and food supplies are amplifying. Water plays the most important role in the Energy-Water-Food (E-W-F) Nexus issue such as energy supply (clean hydropower energy generation), water supply (drinking water), and food supply (agricultural irrigation water). Therefore, water quantity simulation & forecasting become an important issue in E-W-F Nexus problem. Water quantity simulation & forecasting model, such as rainfall-runoff (RR) hydrological model has become a useful tool which can significantly improve efficiency of the hydropower energy generation, water supply management, and agricultural irrigation water utilization. The accuracy and reliability of the water quantity simulation & forecasting model are significantly affected by the model parameters. Therefore, demand of effective and fast model parameter optimization tool for solving the E-W-F Nexus problem increases significantly. The shuffled complex evolution developed at University of Arizona (SCE-UA) has been recognized as an effective global model parameter optimization method for more than 20 years and is highly suited to solve the E-W-F Nexus problem. However, the computational efficiency of the SCE-UA dramatically deteriorates when applied to complex E-W-F Nexus problem. For the purpose of solving this conundrum, a fast parallel SCE-UA was proposed in this paper. The parallel SCE-UA was implemented on the novel heterogeneous computing hardware and software systems which were constituted by the Intel multi-core CPU, NVIDIA many-core GPU, and PGI Accelerator Visual Fortran (with OpenMP and CUDA). Performance comparisons between the parallel and serial SCE-UA were carried out based on two case studies, the Griewank benchmark function optimization and a real world IHACRES RR hydrological model parameter optimization. Comparison results indicated that the parallel SCE-UA outperformed the serial one and has good application prospects for solving the water quantity simulation & forecasting model parameter calibration in the E-W-F Nexus problem.
Nilay Shah - One of the best experts on this subject based on the ideXlab platform.
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Sustainable planning of the Energy-Water-Food Nexus using decision making tools
Energy Policy, 2018Co-Authors: Niclas Bieber, Jen Ho Ker, Koen H. Van Dam, Rembrandt H.e.m. Koppelaar, Charalampos Triantafyllidis, Xiaonan Wang, Nilay ShahAbstract:Developing countries struggle to implement suitable electric power and water services, failing to match infrastructure with urban expansion. Integrated modelling of urban water and power systems would facilitate the investment and planning processes, but there is a crucial gap to be filled with regards to extending models to incorporate the food supply in developing contexts. In this paper, a holistic methodology and platform to support the resilient and sustainable planning at city region level for multiple sectors was developed for applications in urban energy systems (UES) and the Energy-Water-Food Nexus, combining agent-based modelling - to simulate and forecast resource demands on spatial and temporal scales - with resource network optimization, which incorporates capital expenditures, operational costs, environmental impacts and the opportunity cost of food production foregone (OPF). Via a scenario based approach, innovative water supply and energy deployment policies are presented, which address the provision of clean energy for every citizen and demonstrate the potential effects of climate change. The results highlighted the vulnerability of Ghanas power generation infrastructure and the need for diversification. Feed-in tariffs and investment into supporting infrastructure and agriculture intensification will effectively increase the share of renewable energy and reduce carbon emissions.
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Introduction to life-cycle analysis and the Energy-Water-Food Nexus
Qatar Foundation Annual Research Forum Proceedings, 2012Co-Authors: Tareq Al-ansari, Anna Korre, Nilay ShahAbstract:There is a growing momentum to analyse the broader interdependencies of the energy, water and food systems rather than evaluating them in isolation. As such, the objective of this research is to introduce a methodology which can integrate energy, water and food in one resource model at an appropriate scale and resolution, essentially describing one resource in terms of its constituents. The Nexus can be evaluated using industrial ecology based tools such life cycle analysis (LCA) and material flow analysis (MFA). Industrial ecology is a multidimensional approach to system design such as the food system. Moreover, industrial ecology seeks to use the natural ecosystem as models for the human driven industrial systems, thus developing similarities between industrial systems and naturally occurring ones. Life cycle analysis is defined as the compilation and evaluation of the inputs, outputs and potential environmental impacts of a product system throughout its lifecycle. Qatar is an ideal case study for devel...
Depeng Zuo - One of the best experts on this subject based on the ideXlab platform.
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Improving water quantity simulation & forecasting to solve the Energy-Water-Food Nexus issue by using heterogeneous computing accelerated global optimization method
Applied Energy, 2018Co-Authors: Guangyuan Kan, Yunzhong Jiang, Liuqian Ding, Ke Liang, Yang Hong, Mengjie Zhang, Hao Wang, Depeng ZuoAbstract:Abstract With continuous population increase and economic growth, challenges on securing sufficient energy, water, and food supplies are amplifying. Water plays the most important role in the Energy-Water-Food (E-W-F) Nexus issue such as energy supply (clean hydropower energy generation), water supply (drinking water), and food supply (agricultural irrigation water). Therefore, water quantity simulation & forecasting become an important issue in E-W-F Nexus problem. Water quantity simulation & forecasting model, such as rainfall-runoff (RR) hydrological model has become a useful tool which can significantly improve efficiency of the hydropower energy generation, water supply management, and agricultural irrigation water utilization. The accuracy and reliability of the water quantity simulation & forecasting model are significantly affected by the model parameters. Therefore, demand of effective and fast model parameter optimization tool for solving the E-W-F Nexus problem increases significantly. The shuffled complex evolution developed at University of Arizona (SCE-UA) has been recognized as an effective global model parameter optimization method for more than 20 years and is highly suited to solve the E-W-F Nexus problem. However, the computational efficiency of the SCE-UA dramatically deteriorates when applied to complex E-W-F Nexus problem. For the purpose of solving this conundrum, a fast parallel SCE-UA was proposed in this paper. The parallel SCE-UA was implemented on the novel heterogeneous computing hardware and software systems which were constituted by the Intel multi-core CPU, NVIDIA many-core GPU, and PGI Accelerator Visual Fortran (with OpenMP and CUDA). Performance comparisons between the parallel and serial SCE-UA were carried out based on two case studies, the Griewank benchmark function optimization and a real world IHACRES RR hydrological model parameter optimization. Comparison results indicated that the parallel SCE-UA outperformed the serial one and has good application prospects for solving the water quantity simulation & forecasting model parameter calibration in the E-W-F Nexus problem.