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Energy Water Food Nexus

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "B: Energy and Environment".

Deadline for manuscript submissions: closed (15 December 2023) | Viewed by 19139

Special Issue Editors


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Guest Editor
Department of Hydraulic and Environmental Engineering, Universitat Politècnica de València, 46022 València, Valencia, Spain
Interests: fluid mechanics; computational fluid dynamics; environment sustainability;numerical modeling; CFD simulation; water quality; numerical simulation; modeling and simulation environmental; impact assessment; energy systems; energy demand; energetic implications in engineering facilities; renewable energy sources
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Guest Editor
Department of Civil Engineering, University of Lisbon, IST—Tecnico Lisboa/CERIS, Av. Rovisco Pais, 1649-004 Lisbon, Portugal
Interests: hydropower; hydraulic transients; energy efficiency; eco-design projects; pumped-storage; water–energy–food nexus; hybrid energy solutions; renewable energy sources; energy recovery; hydrodynamics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear colleagues,

Global trends of population growth, rising living standards, and the rapidly increasing urbanized world create a huge demand for water, food, and energy. Additionally, climate change has significant impacts on water and food availability. In recent years, the "nexus" has emerged as a powerful concept to capture these interactions of resources and it is now a key feature of policymaking. This nexus will be also a new approach in supporting energy–water–food satisfaction, with smart water-energy grids. Water, energy, and food are essential for human well-being, poverty reduction, and sustainable development. Water can function as the main link, creating and integrating the other two. Agriculture accounts for 70% of total global freshwater withdrawals, making it the largest user of water. On the one hand, water is used along the entire food supply chain, and it is used to produce or transport energy in different ways. On the other hand, the food production and supply chain consumes about 30% of total energy consumed globally. Energy is required to produce, transport, and distribute food, as well as to extract, pump, lift, collect, transport, and treat water. Cities, industry, and other users claim increasingly more water, energy, and land resources, and at the same time, face problems of resource scarcity. It is expected to be exacerbated in the near future, as 60% more food will need to feed the world population in 2050. Global energy consumption is projected to grow by up to 50% by 2035. Total global water withdrawals for irrigation are projected to increase by 10% by 2050.

Innovative integrated solutions in terms of technical, economic, and social impacts are desirable. Energy recovery, pumped storage hydropower solutions, hybrid energy systems, water–energy–food management, under secure and safety scenarios, as well in terms of best operation and management and control towards more sustainable and flexible integrated solutions are required.

Prof. Dr. P. Amparo López Jiménez
Prof. Dr. Helena M. Ramos
Guest Editors

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Keywords

  • energy–water–food nexus
  • urban, industrial, and agriculture efficiency
  • energy and water efficiency
  • resources management and storage
  • smart grids
  • chain values
  • pumped storage hydropower
  • hybrid energy solutions
  • water management and efficiency
  • flexibility in integrated solutions
  • water demand and energy and food demand characterization
  • sustainable development
  • climate change and implications
  • smart irrigation solutions
  • water scarcity
  • dynamics of nexus interactions
  • integrity of ecosystems
  • limit resources sustainability
  • clean water and sanitation
  • affordable and clean energy
  • sustainable cities and communities
  • climate action
  • responsible consumption and production
  • zero hunger

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Published Papers (4 papers)

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Research

22 pages, 1208 KiB  
Article
Issues in Implementation of EU Regulations in Terms of Evaluation of Water Losses: Towards Energy Efficiency Optimization in Water Supply Systems
by Agnieszka Ociepa-Kubicka, Iwona Deska and Ewa Ociepa
Energies 2024, 17(3), 633; https://doi.org/10.3390/en17030633 - 28 Jan 2024
Cited by 4 | Viewed by 1999
Abstract
The water and sewage sector is responsible for approximately 3.5% of energy consumption in the European Union (EU). Leaks causing water losses in water distribution systems (WDSs) are responsible for approximately 24% of water consumption in the EU, which contributes to additional energy [...] Read more.
The water and sewage sector is responsible for approximately 3.5% of energy consumption in the European Union (EU). Leaks causing water losses in water distribution systems (WDSs) are responsible for approximately 24% of water consumption in the EU, which contributes to additional energy losses and emissions of greenhouse gases (GHGs). The implementation of the Directive of the European Parliament and the EU Council on the quality of drinking water (Directive (EU) 2020/2184) introduces the obligation to report water losses by large water utilities in EU Member States. The reported indicator will be the infrastructure leakage index (ILI) which is the ratio between current annual real loss (CARL) and unavoidable annual real loss (UARL). The paper presents a comparative analysis of selected water loss performance indicators calculated for 12 Polish WDSs. Results show that values of calculated indicators were diverse. The overestimation of both the reported value of operating pressure and total length of service connections may lead to the overestimation of UARL and thus to the underestimation of ILI. Obtaining a satisfactory, but incorrect, value of ILI may result in the abandonment of activities aimed at water loss reduction. Water losses in water distribution systems (WDSs) contribute to a significant increase in both energy consumption and GHG emissions. Total approximated electrical energy related to CARL consumed in 2021 by eleven utilities (except for one company) amounted to 3.276 GWh and total approximated carbon emissions amounted to 2807.84 MgCO2eq. In the case of four WDSs, reduction of ILI to the value of 1.5 may reduce GHG emissions by 31–54%. It can be concluded that the implementation of Directive (EU) 2020/2184 will require unification of methodology for calculation of parameters used in ILI evaluation in all EU Member States. Full article
(This article belongs to the Special Issue Energy Water Food Nexus)
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18 pages, 4610 KiB  
Article
Sustainable Water-Energy Nexus towards Developing Countries’ Water Sector Efficiency
by Helena M. Ramos, Jorge G. Morillo, Juan A. Rodríguez Diaz, Armando Carravetta and Aonghus McNabola
Energies 2021, 14(12), 3525; https://doi.org/10.3390/en14123525 - 13 Jun 2021
Cited by 15 | Viewed by 3318
Abstract
Water management and energy recovery can improve a system’s sustainability and efficiency in a cost-effective solution. This research assesses the renewable energy sources used in the water sector, as well as the related water sector performance indicators within Portuguese water management systems. A [...] Read more.
Water management and energy recovery can improve a system’s sustainability and efficiency in a cost-effective solution. This research assesses the renewable energy sources used in the water sector, as well as the related water sector performance indicators within Portuguese water management systems. A deep analysis of 432 water entities in Portugal, based on ERSAR data base, was conducted in order to identify factors to be improved regarding the system efficiency. On the other hand, the potential energy recovery developed in the REDAWN project was also used as a reference for the application of micro hydropower (MHP) solutions in the water sector. A water and energy nexus model was then developed to improve the systems efficiency and sustainability. A real case study in Africa, the Nampula water supply system, located in Mozambique, was selected as a promising potential for energy recovery. The application of a pump-as-turbine (PAT) allows the reduction in system costs and environmental impacts while increasing its efficiency. The proposed MHP has a capacity to generate ~23 MWh/year, providing significant savings. The developed economic analysis indicates the project is profitable, with an IRR ~40% depending on the energy selling price. This project can avoid the emission of more than 12 tCO2 to the atmosphere, and it can help to reduce the system’s real losses by more than 10,000 m3/year. Consequently, it creates a total economic benefit of 7604 EUR/year. Full article
(This article belongs to the Special Issue Energy Water Food Nexus)
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21 pages, 817 KiB  
Article
Crop Yield Estimation Using Deep Learning Based on Climate Big Data and Irrigation Scheduling
by Khadijeh Alibabaei, Pedro D. Gaspar and Tânia M. Lima
Energies 2021, 14(11), 3004; https://doi.org/10.3390/en14113004 - 22 May 2021
Cited by 75 | Viewed by 6453
Abstract
Deep learning has already been successfully used in the development of decision support systems in various domains. Therefore, there is an incentive to apply it in other important domains such as agriculture. Fertilizers, electricity, chemicals, human labor, and water are the components of [...] Read more.
Deep learning has already been successfully used in the development of decision support systems in various domains. Therefore, there is an incentive to apply it in other important domains such as agriculture. Fertilizers, electricity, chemicals, human labor, and water are the components of total energy consumption in agriculture. Yield estimates are critical for food security, crop management, irrigation scheduling, and estimating labor requirements for harvesting and storage. Therefore, estimating product yield can reduce energy consumption. Two deep learning models, Long Short-Term Memory and Gated Recurrent Units, have been developed for the analysis of time-series data such as agricultural datasets. In this paper, the capabilities of these models and their extensions, called Bidirectional Long Short-Term Memory and Bidirectional Gated Recurrent Units, to predict end-of-season yields are investigated. The models use historical data, including climate data, irrigation scheduling, and soil water content, to estimate end-of-season yield. The application of this technique was tested for tomato and potato yields at a site in Portugal. The Bidirectional Long Short-Term memory outperformed the Gated Recurrent Units network, the Long Short-Term Memory, and the Bidirectional Gated Recurrent Units network on the validation dataset. The model was able to capture the nonlinear relationship between irrigation amount, climate data, and soil water content and predict yield with an MSE of 0.017 to 0.039. The performance of the Bidirectional Long Short-Term Memory in the test was compared with the most commonly used deep learning method, the Convolutional Neural Network, and machine learning methods including a Multi-Layer Perceptrons model and Random Forest Regression. The Bidirectional Long Short-Term Memory outperformed the other models with an R2 score between 0.97 and 0.99. The results show that analyzing agricultural data with the Long Short-Term Memory model improves the performance of the model in terms of accuracy. The Convolutional Neural Network model achieved the second-best performance. Therefore, the deep learning model has a remarkable ability to predict the yield at the end of the season. Full article
(This article belongs to the Special Issue Energy Water Food Nexus)
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22 pages, 2620 KiB  
Article
Assessing Future Water Demand and Associated Energy Input with Plausible Scenarios for Water Service Providers (WSPs) in Sub-Saharan Africa
by Pauline Macharia, Nzula Kitaka, Paul Yillia and Norbert Kreuzinger
Energies 2021, 14(8), 2169; https://doi.org/10.3390/en14082169 - 13 Apr 2021
Cited by 1 | Viewed by 2962
Abstract
This study examined the current state of water demand and associated energy input for water supply against a projected increase in water demand in sub-Saharan Africa. Three plausible scenarios, namely, Current State Extends (CSE), Current State Improves (CSI) and [...] Read more.
This study examined the current state of water demand and associated energy input for water supply against a projected increase in water demand in sub-Saharan Africa. Three plausible scenarios, namely, Current State Extends (CSE), Current State Improves (CSI) and Current State Deteriorates (CSD) were developed and applied using nine quantifiable indicators for water demand projections and the associated impact on energy input for water supply for five Water Service Providers (WSPs) in Kenya to demonstrate the feasibility of the approach based on real data in sub-Saharan Africa. Currently, the daily per capita water-use in the service area of four of the five WSPs was below minimum daily requirement of 50 L/p/d. Further, non-revenue water losses were up to three times higher than the regulated benchmark (range 26–63%). Calculations showed a leakage reduction potential of up to 70% and energy savings of up to 12 MWh/a. The projected water demand is expected to increase by at least twelve times the current demand to achieve universal coverage and an average daily per capita consumption of 120 L/p/d for the urban population by 2030. Consequently, the energy input could increase almost twelve-folds with the CSI scenario or up to fifty-folds with the CSE scenario for WSPs where desalination or additional groundwater abstraction is proposed. The approach used can be applied for other WSPs which are experiencing a similar evolution of their water supply and demand drivers in sub-Saharan Africa. WSPs in the sub-region should explore aggressive strategies to jointly address persistent water losses and associated energy input. This would reduce the current water supply-demand gap and minimize the energy input that will be associated with exploring additional water sources that are typically energy intensive. Full article
(This article belongs to the Special Issue Energy Water Food Nexus)
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