Nexus Optimization Research Articles

Optimization of the Water–Energy–Carbon Nexus in the Residential Water Uses of Shanghai, China

Residential water use in urban areas directly affects household energy consumption and associated carbon emissions. Reducing residential water use through water saving can lead to substantial energy saving and lower carbon emissions. Household choices in water appliances and fixtures and water-use behaviors shape water consumption patterns. This paper presents a study in Shanghai, China, where the water consumption structure of households was analyzed through a comprehensive survey. In addition, a season-differentiated water–energy–carbon nexus optimization model with Monte Carlo simulation was built to minimize the costs associated with water and energy usage while maximizing carbon emission reduction. The survey data revealed Shanghai’s water demand structure, thereby highlighting the water-use influence in the city on urban household energy consumption and carbon emissions, which are affected by seasonal temperature variations. The results provide useful insights into the intricate relationships among water use, energy consumption, and carbon emissions at the scale of urban households.

Food–energy–water nexus optimization brings substantial reduction of urban resource consumption and greenhouse gas emissions

Abstract Urban sustainability is a key to achieving the UN sustainable development goals (SDGs). Secure and efficient provision of food, energy, and water (FEW) resources is a critical strategy for urban sustainability. While there has been extensive discussion on the positive effects of the FEW nexus on resource efficiency and climate impacts, measuring the extent to which such synergy can benefit urban sustainability remains challenging. Here, we have developed a systematic and integrated optimization framework to explore the potential of the FEW nexus in reducing urban resource demand and greenhouse gas (GHG) emissions. Demonstrated using the Metropolis Beijing, we have identified that the optimized FEW nexus can reduce resource consumption and GHG emissions by 21.0 and 29.1%, respectively. These reductions come with increased costs compared to the siloed FEW management, but it still achieved a 16.8% reduction in economic cost compared to the business-as-usual scenario. These findings underscore the significant potential of FEW nexus management in enhancing urban resource efficiency and addressing climate impacts, while also identifying strategies to address trade-offs and increase synergies.

Multi-objective optimization and demand variation analysis on a water energy food nexus system

The interdependence of water, energy, and food resources demands a holistic approach to sustainable resource management. This study focuses on the mathematical optimization of the water-energy-food nexus system in Sinaloa state, Mexico. Using a multi-objective optimization model, we aimed to identify optimal resource allocation strategies and assess the implications of demand variation scenarios in the domestic sector. By considering various scenarios, ranging from reduced to increased demand, the study analyzes the trade-offs between resource consumption, economic benefits, and environmental impacts. The results reveal Pareto fronts that provide insights into efficient resource allocation, highlighting the relationships between water, energy, and food demand. The study provides recommendations for policymakers and contributes to knowledge on water-energy-food nexus optimization, emphasizing the need for integrated approaches to support sustainable resource management.

Climate, Land, Energy and Water System Nexus Optimization Modeling for Nepal

This paper introduces the amazing CLEWs Nepal model - a powerful tool that sheds light on the intricate interplay between climate policies and crucial resources like land, energy, and water. With more and more countries taking bold steps to combat climate change, it's crucial to understand the ripple effects of such decisions on other sectors. That's where CLEWs come in, providing decision-makers with valuable insights into the trade-offs and synergies involved in various climate policies.
 This paper examines the impact of the increasing global demand for power on greenhouse gas emissions, water usage, and hydropower production in Nepal. The study projects that by 2050, under current scenario and based on optimum growth rate, the country will only need to generate 9 GW of power, which can be mostly fulfilled by hydropower. However, there will be rise in CO2 emissions, particularly from the transport and biomass sectors. To mitigate the impact of this growth, the study recommends improving irrigated farming and forest conservation. The implementation of the Nationally Determined Contributions (NDC) can also contribute to reducing CO2 emissions and increasing hydropower production. We've calibrated the model to reveal fascinating insights into the long-term energy consumption patterns across different sectors, varying crop production based on irrigation levels, and total water usage in public and power sectors. And that's not all - we've also factored in the emissions produced while optimizing energy, food, and water demands for the public. Our model offers a range of policy options for Nepal, including an NDC scenario, which can help reduce CO2 emissions and preserve vital resources like water and land. We've also identified the costs and technology mix necessary to successfully implement these policies.

A water-energy-food-carbon nexus optimization model for sustainable agricultural development in the Yellow River Basin under uncertainty

Water scarcity, limited land resources and global warming are the most challenging issues facing sustainable agricultural development, and modern agriculture requires efficient and environmentally friendly agricultural water and land management practices. This paper proposes a water-energy-food-carbon nexus system optimization model, which aims to formulate a scientific and rational water and land resource allocation strategy for sustainable agricultural development to increase irrigation water productivity, reduce carbon emissions and enhance regional agriculture competitiveness. First, the carbon footprint life cycle assessment method was used to measure carbon sinks and carbon emissions across the ecosystem. Second, a multiobjective nonlinear programming model with the goal of maximizing irrigation water productivity, minimizing carbon emissions, and maximizing the competitiveness of low-carbon agriculture is established. Finally, an empirical study is performed in the Yellow River Basin, and an elitist nondominated sorting genetic algorithm is used to solve the model. The research results show that the water-energy-food-carbon nexus system optimization model based on uncertain conditions established in this paper, can maximize resource utilization efficiency and effectively measure the impact of regional agricultural production on the environment. It has reference significance for the realization of carbon neutrality in the region.

Towards sustainable circular agriculture: An integrated optimization framework for crop-livestock-biogas-crop recycling system management under uncertainty

ContextGrowing socio-economic development and population poses unprecedented challenges for agriculture in meeting increasing demand of food, water, and energy. Rethinking the future agricultural production to simultaneously safeguard resources security and regulate environmental pollution is essential. Circular agriculture opens up a new path for the high-efficiency and environmental-friendly production. An integrated energy-water-food nexus optimization approach for managing agricultural resources and wastes in line with the principles of sustainable circular agriculture management is lacking. ObjectiveThis study therefore proposes an integrated uncertain optimization model to manage agricultural crop-livestock-biogas-crop recycling systems from a cross-sectoral energy-water-food nexus perspective in the changing environment. The aims are to: (1) balance objectives of input reduction, output promotion, ensuring equity, and global warming mitigation; (2) generate sustainable resources allocation strategies based on efficiency and recycling; (3) assess the global warming mitigation potential of the recycling systems from a life cycle perspective; and (4) deal with interactions, complexities, uncertainties, and risks existed in the recycling systems. MethodsThe proposed model framework is based on a stochastic multi-objective programming, while triangular fuzzy numbers, fuzzy credibility constrained programming, Stewart model, analytic hierarchy process, and opportunity carbon footprint are integrated to enhance its practicability and feasibility. The model is verified through a real-world case study in the Zhanghe Irrigation District, Hubei province, China. Results and conclusionsResults show that optimal water and land resources allocation solutions are more efficient than current strategies, with water consumption per unit area decreasing by 13.63% and rice production per unit area improving by 22.06%. Paddy field and biogas leakage are two of the largest sources of GHG emission, calling for agronomic and engineering measures to improve farmland management and biogas generation technology. Livestock breeding contributes 10% of the total GHG emission, along with generating 76% of the total biogas, indicating the great significance of manure recycle. Overall, 4.26 × 108 kg CO2 is reduced in the recycling system, contributed by chemical fertilizer reduction, agricultural wastes recycle, and non-renewable energy replacement. SignificanceThe study offers a potential nexus optimization approach for sustainable management of agricultural recycling systems from a holistic perspective. It can be used as a general model to extend to other agricultural systems suffering from similar resources and environmental crisis.

A robust water-food-land nexus optimization model for sustainable agricultural development in the Yangtze River Basin

Stable and sustainable grain production is an important guarantee for national security, economic development and social stability. Water and land are essential resources in irrigated agricultural systems. There is intricate relationship in Water, land and food nexus with large uncertainties involved therein. Sustainable agricultural development requires effective and coordinated management of the water-food-land nexus. This paper developed a robust optimization model to optimize the allocation of limited resources and maximize irrigation water productivity in water-food-land nexus system. The proposed optimization model fully considers the system uncertainties to assist decision-makers in developing more effective water and land resource allocation plans. The model is demonstrated to solve a real-world nexus management problem in the Yangtze River basin. The results show that the robust optimization method can solve the uncertainty disturbance and meet the target requirements, thus verifying the effectiveness and feasibility of the model in water-food-land nexus system. The model could be applied to similar river basins that have limited resources.

Energy-Water-Carbon Nexus Optimization for the Path of Achieving Carbon Emission Peak in China Considering Multiple Uncertainties: A Case Study in Inner Mongolia

The Chinese government has launched a guideline for carbon emissions up to the peak (CEUP) in the 2030 target. The electric power sector has to make its own contributions to the national CO2 emissions mitigation target. In this study, a patron–client interactive optimized (PCIO) model is proposed to investigate the regional energy–water–carbon nexus optimization under the policy background of the CEUP target. Inner Mongolia, the largest energy base in China, which is also facing the prominent contradiction including the energy production and serious environmental problems, is chosen as a case study. Multiple uncertainties, including the fuel price uncertainty and output of the wind and solar power, are considered to make the optimization process more realistic. Results show that coal-fired power will gradually be substituted by the gas, wind, and solar power in Inner Mongolia to reach the CEUP target. The CO2 capture and storage technology and air-cooling systems will play important roles, especially under the strict water policy scenario. However, the achievement of the CEUP and water-saving target will be at the expense of high system costs. The PCIO model makes it possible for the decision-maker to make flexible strategies to balance the CEUP target and saving system costs. The results have demonstrated the validity of the PCIO model in addressing the hierarchical programming problems.

A Robust Neutrosophic Modeling and Optimization Approach for Integrated Energy-Food-Water Security Nexus Management under Uncertainty

Natural resources are a boon for human beings, and their conservation for future uses is indispensable. Most importantly, energy-food-water security (EFWS) nexus management is the utmost need of our time. An effective managerial policy for the current distribution and conservation to meet future demand is necessary and challenging. Thus, this paper investigates an interconnected and dynamic EFWS nexus optimization model by considering the socio-economic and environmental objectives with the optimal energy supply, electricity conversion, food production, water resources allocation, and CO2 emissions control in the multi-period time horizons. Due to real-life complexity, various parameters are taken as intuitionistic fuzzy numbers. A novel method called interactive neutrosophic programming approach (INPA) is suggested to solve the EFWS nexus model. To verify and validate the proposed EFWS model, a synthetic computational study is performed. The obtained solution results are compared with other optimization approaches, and the outcomes are also evaluated with significant practical implications. The study reveals that the food production processes require more water resources than electricity production, although recycled water has not been used for food production purposes. The use of a coal-fired plant is not a prominent electricity conversion source. However, natural gas power plants’ service is also optimally executed with a marginal rate of production. Finally, conclusions and future research are addressed. This current study emphasizes how the proposed EFWS nexus model would be reliable and beneficial in real-world applications and help policy-makers identify, modify, and implement the optimal EFWS nexus policy and strategies for the future conservation of these resources.

Food-energy-water-waste nexus systems optimization for New York State under the COVID-19 pandemic to alleviate health and environmental concerns

This article addresses food-energy-water-waste nexus optimization to alleviate the public health and environmental concerns from increasing food waste generation during the COVID-19 pandemic using waste-to-energy technologies. Food waste increase has become a severe global problem during the pandemic. It could alleviate health and environmental concerns by converting the food waste into electricity and heat through food-energy-water-waste nexus systems using waste-to-energy facilities, such as anaerobic digesters and combined heat and power units in wastewater treatment plants. To design efficient nexus systems, a multi-period multi-objective optimization model is proposed, while considering various impacts of the pandemic. A case study for New York State is presented. The optimized systems show a potential of reducing the food waste disposal amounts by 38%. The Pareto-optimal solutions illustrate a clear trade-off between the objectives. The minimum total cost is $27.1 million; the optimal unit processing profit is $11.9 per ton processed food waste. Spatial analyses reveal a clear correlation between facility selections and their processing capacities. Electricity price and biogas yield are the most important factors for the economic objectives, based on sensitivity analysis.

A load-complementarity combined flexible clustering approach for large-scale urban energy-water nexus optimization

Modeling and optimization of a large-scale urban energy-water nexus system with sufficient spatial resolutions is a complex challenge. By proper clustering technique, a large-scale problem could possibly be divided into small ones with high spatial resolution and accuracy. Existing literature tends to lower the complexity of large-scale urban energy system problem by accumulating demand profiles on the spatial dimension. This study proposes a flexible clustering approach based on density clustering method with combined index assessment process. The flexible approach considers not only the spatial dimensions but also the complementarity effect of different demand profile and control the computational time of system design and optimization. The approach can increase the clustering flexibility by providing more clustering options than conventional method, take advantages of complementarity effect to further improve the system economic performance and control the solving time in an acceptable range. The proposed approach is evaluated by a case study of a new business district in Shanghai, China with a proposed future energy-water nexus system. After three combined index assessment, 45 new clustering maps are generated by the flexible clustering approach and the final optimal solution obtained by the proposed approach can further obtain 6.74% cost savings compared with conventional clustering approach.

On the optimization of water-energy nexus in shale gas network under price uncertainties

This study develops a framework for water-energy nexus optimization in shale gas production and distribution network under uncertainty. Sustainable design of the network is achieved through treatment of wastewater using thermal membrane distillation, whereby a comprehensive design model is integrated within the network to account for energy requirement of the unit. The proposed model also accounts for the problem of scheduling hydraulic fracturing using a continuous time formulation. Various uncertainties are associated with the network. Among different uncertain variables, uncertainties associated with price and demand are crucial as they can affect the optimal configuration significantly. Incorporation of uncertainty in the model seeks to meet the demand of natural gas consumers whilst accounting for the uncertainties associated with the price of final products. Uncertainties are modelled via randomly generated scenarios using beta distribution of the price generated using historical data. The stochastic model is applied to a case study through the maximization of net profit. Three different scenarios are considered for analysis. Results from the three different scenarios show 14.39%, 11.49%, and 12.34% increase in profit respectively as compared to the deterministic approach. Solving all the scenarios together gives an ensemble-average solution with 13.74% increase in expected profit. Savings in the freshwater requirement for fracturing and the energy associated with water management amounted to 23.2% and 42.7%, respectively.

The impact of clean development mechanism on energy-water-carbon nexus optimization in Hebei, China: A hierarchical model based discussion

Clean development mechanism (CDM) is an important principle in CO2 emissions mitigation since it was proposed. However, there will be a long way for the large-scale application of CDM in China, for thermal power is still in the dominant position, while renewable power is far from being competitive. In this study, a mix integer bi-level hierarchical programming model (MIBLHP) is developed to investigate the potential impact of the CDM application on the regional energy-water-carbon nexus optimization in electric power system in China. The model integrates the advantages of bi-level programming and mix integer liner programming in dealing with conflicting objectives with hierarchical and sequential decision making process and help to achieve the optimized strategies with the highest overall system satisfaction degree. Results show that CDM will play an important role in the regional energy-water-carbon nexus optimization, the MIBLHP is able to stabilize the increasing trend of system cost and make better tradeoffs between the economic and environmental goals. Optimal strategies including power generation and capacity expansion path, system cost control, CO2 emissions abatement strategies, water consumption and waste water discharge are presented. The system would reach the supreme satisfaction degrees (λ = 0.934) when the CO2 reduction level is 40%, which means that every part of the system has achieved the best condition. The proposed model has great potential in dealing with similar regional planning problems in energy-water-carbon nexus optimization.

Application of water-energy-food nexus approach for designating optimal agricultural management pattern at a watershed scale

The increasing demands of the population and the need for development obliged the optimal use and adaptive management of the watershed resources. Accordingly, it is necessary to adopt comprehensive measures to reach sustainable development goals. This objective can be achieved by the application of interdisciplinary and professional approaches through establishing dynamic and optimal balance in supply and demand resources. However, such important optimization approaches have been rarely practiced at the watershed scale. The present study has been therefore formulated to apply a linear water-energy-food nexus optimization for the Shazand watershed, Markazi Province, Iran. This approach was applied for planning 14 crops planted in orchard, irrigated farms, and rain-fed farms, between 2006 and 2014, and targeting water-energy-food nexus index (WEFNI) maximization. The connections among the water, energy, and food were then evaluated through determining the amount of consumption, mass productivity, and economic productivity of water and energy. The results of WEFNIs revealed that almond has the highest WEFNI with values of 0.92, 0.76, 0.76, 0.83, 0.86, 0.86, 0.87, 0.87, and 0.88. Whilst, potato with WEFNI of 0.05, 0.05, 0.05, 0.06, 0.09, 0.10 and 0.11, sugar cane with WEFNI of 0.10 and cucumber with WEFNI of 0.13 had the lowest scores and the corresponding lowest performance among the study crops. The outcomes of optimization study explained that the current situation of land use in the Shazand Watershed is unsuitable to minimize water and energy consumption and maximize benefit. The results can be used as an effective tool for designating proper soil and water resource management strategies in the region.

Scenario analysis of a sustainable water-food nexus optimization with consideration of population-economy regulation in Beijing-Tianjin-Hebei region

In the process of urban agglomeration, water-food security can be deemed as a key to support urban development and human living, but which can be challenged by expanded population growth, accelerated industrialization, unbalance regional economic development and diversity of weather (due to climate changes). In this study, a water resources allocation and food production (WF) optimization is developed for regional sustainability under multiple uncertainties. A hybrid two-stage fuzzy programming with Laplace criterion (TSFL) is proposed into a WF optimization to handle hybrid indeterminacies, which can increase the robustness of decision-making. The WF optimization with proposed TSFL method can be applied to a practical case of Beijing-Tianjin-Hebei (BTH) region. The obtained results associated with water deficits, optimal water allocations, inadequate capacities of food production, rational irrigation schedules, sound livestock scales, optimized agricultural possessing layouts and system benefits under various population-economy regulation scenarios can be obtained. The results can reflect the tradeoff between economic development and water-food safety; meanwhile, they can display risk violation of WF plan under various credibility levels and Laplace criterions (based on TSFL method). All above results can facilitate to produce an optimized water-food plan to support the synergetic development of BTH region in a robust manner.

The water-food-energy nexus optimization approach to combat agricultural drought: a case study in the United States

The frequent recent drought events in the Great Plains of United States have led to significant crop yield reductions and crop price surges. Using an integrated water-food-energy nexus modelling and optimization approach, this study laid the basis for developing an effective agricultural drought management system by combining real-time drought monitoring with real-time irrigation management. The proposed water-food-energy simulation and optimization method is spatially explicit and was applied to one major corn region in Nebraska. The crop simulations, validated with yield statistics, showed that a drought year like 2012 can potentially reduce the corn yield by 50% as compared to a wet year like 2009. The simulation results show that irrigation can play a key role in halting crop losses due to drought and in sustaining high yields of up to 20t/ha. Nevertheless, the water-food-energy relationship shows that significant investments on water and energy are required to limit the negative effects of drought. The multi-criteria optimization problem developed in this study shows that the optimal crop yield does not necessarily correspond to the maximum yield, resulting in potential water and energy savings.