A Food-Energy-Water Nexus approach for land use optimization

Conducting water-energy-food nexus studies: what, why, and how

The increasing pressure on resources and the persistent failure to address global malnutrition are evident challenges. A significant contributing factor is the decline in the quality of production resources, particularly water. As a result, many countries and their experts have prioritized the need to balance resource consumption. To address the research gap regarding balanced and optimal resource use, various methodologies have been developed over time, culminating in nexus studies. This study aimed to investigate the what, why, and how of conducting water-energy-food nexus (WEFN) studies. The research employed a sequential mixed-methods approach, integrating content analysis with the Analytical Network Process (ANP). The findings reveal that the objectives of WEFN studies encompass a wide range of interests, which can be systematically categorized into seven principal domains: system sustainability assessment, integration of planning and decision-making processes related to resource consumption, optimization of resource use, management of resource consumption systems, development of theoretical frameworks for the nexus, evaluation of the impacts of resource consumption, and assessment of associated risks. Notably, the results indicate that system sustainability assessment is the most critical reason for conducting WEFN studies. Furthermore, the analysis of WEFN methodologies identified simulation as the most effective technique within the Analytical Hierarchy Process (AHP) framework. In the context of the ANP technique, statistical analysis and simulation emerged as the most important methods. This research advocates for using a diagram to facilitate the selection of the optimal method for conducting a WEFN study.

Artificial intelligence can regulate light and climate systems to reduce energy use in plant factories and support sustainable food production

Plant factories with artificial lighting (PFALs) can boost food production per unit area but require resources such as carbon dioxide and energy to maintain optimal plant growth conditions. Here we use computational modelling and artificial intelligence (AI) to examine plant-environment interactions across ten diverse global locations with distinct climates. AI reduces energy use by optimizing lighting and climate regulation systems, with energy use in PFALs ranging from 6.42 kWh kg-1 in cooler climates to 7.26 kWh kg-1 in warmer climates, compared to 9.5-10.5 kWh kg-1 in PFALs using existing, non-AI-based technology. Outdoor temperatures between 0 °C and 25 °C favour ventilation-related energy use reduction, with outdoor humidity showing no clear pattern or effect on energy use. Ventilation-related energy savings negatively impact other resource utilization such as carbon dioxide use. AI can substantially enhance energy savings in PFALs and support sustainable food production.

A review of social-ecological system vulnerability in desertified regions: Assessment, simulation, and sustainable management

Desertified regions face considerable vulnerability due to the combined effects of climate change and human activities, which threaten regional ecological security and societal development. It is therefore necessary to assess, simulate, and manage the vulnerability of desertified regions from the perspective of the social-ecological system, to support desertification control and sustainable development. This study is a systematic review of the vulnerability of the social-ecological system in desertified regions (SESDR) based on a bibliometric analysis, and a summary of the research progresses in vulnerability assessment, simulation, and sustainable management is provided. It was found that SESDR vulnerability research started relatively late, but has developed rapidly in recent years, with an emphasis on the coupling between natural systems and human activities, and multi-scale interactions and dynamics. Using various indicators at different scales, SESDR vulnerability could be assessed in terms of exposure, sensitivity, and adaptability. Modeling the complex interactions among natural and human factors across multiple scales is essential to simulate the vulnerability dynamics of the SESDR. The sustainable management of SESDR vulnerability focuses on rational spatial planning to achieve the maximum benefits, with the right measures in the right places. Four priority research directions were proposed to develop a better understanding of the mechanisms of vulnerability and smart restoration of desertified land. The findings of this study will enable researchers, land managers, and policymakers to develop a more comprehensive understanding of SESDR vulnerability, thereby enabling them to better address the challenges posed by complex resource and environmental issues.

A review of interconnected challenges in the water-energy-food nexus: Urban pollution perspective towards sustainable development

The swift growth of cities worldwide poses significant challenges in ensuring a sufficient water, energy, and food supply. The Nexus has innovated valuable systems to address these challenges. However, a crucial issue is the potential for pollution resulting from these systems, which directly and indirectly impacts public health and the overall quality of urban living. This study comprehensively reviews the interconnected challenges of the water-energy-food (WEF) nexus and various forms of pollution in cities. The primary focus of this review article is to showcase the findings of WEF nexus studies regarding various pollutions across different geographical regions and spatial scales. It aims to examine the problems resulting from these pollutions, specifically their effects on human health and urban life. It also delves into the sources of pollution as identified in these studies. Furthermore, the article will highlight the proposed solutions from the research aimed at effectively mitigating pollution in each sector studied. This article is a systematic review which analyses research sources from the Scopus database. It extensively reviewed 2463 peer-reviewed published articles and focused explicitly on articles related to the WEF nexus that discussed pollution. Our study emphasizes, firstly, raising awareness about the crucial link between the WEF nexus, pollution, urban environments, and human health among policymakers and key stakeholders, including urban planners, industry partners and municipalities. This is to promote the development of policies that encourage sustainable practices and key stakeholders. Secondly, it evaluates WEF nexus and pollution research methods and findings, aiding in identifying research gaps technological innovation and potential, as well as enhancing decision-making. Lastly, it outlines future research challenges, providing a roadmap for researchers and policymakers to advance understanding in this domain and identify opportunities for resource efficiency and collaboration between different sectors.

Applicability of photovoltaic panel rainwater harvesting system in improving water-energy-food nexus performance in semi-arid areas

Growing food demand challenges the expansion of agriculture, while water and energy shortages have seriously jeopardized agricultural sustainability. Therefore, the water-energy-food (WEF) nexus must be integrated into sustainable agriculture management. However, despite the increasing sophistication of models for WEF optimization, more studies have considered only how to reduce resource consumption and less on how to increase resource supply. This paper outlines an agricultural WEF optimization model based on photovoltaic panel rainwater harvesting (PVRH). The model innovatively incorporates the PVRH system into the agricultural WEF nexus, providing a decision-making framework that exploits and conserves resources in parallel, while contributing to economic benefits. The model was applied in a rural case study in a semi-arid region of China. The results highlight the significant potential of the PVRH system to exploit water and energy, and the increased resources are allocated to irrigated alfalfa and vegetables, which would significantly increase revenue. However, the model does not recommend large-scale vegetable cultivation, which would increase water and energy consumption and reduce the WEF indicator values indicating agricultural sustainability. The final scheme will build a 98.92MWp PV power station, develop 1.31 × 108 kW·h of electricity and 1.97 × 107 m3 of rainwater into agricultural production. And through cropping restructuring, it will increase 23.61 % of economic revenue and save 57.74 % of water and 3.24 % of energy. In general, the model framework is transferable and applicable to similar agricultural areas under semi-arid climatic conditions.

The water-energy-food nexus in biodiversity conservation: A systematic review around sustainability transitions of agricultural systems

The Water Energy Food nexus is a powerful topic in agricultural systems to elucidate threats to biodiversity conservation and culture. This paper aimed to recapitulate nexus thinking research, focusing on social-ecological transitions of agriculture systems and biodiversity management within the Water-Energy-Food nexus. We developed a systematic review and a bibliometric analysis derived from 529 documents in the Scopus database. The ToS method identified a total of 81 relevant information in the sample of documents (529) categorised into roots (10), trunks (9) and leaves (62). This review paper situates types, focus, and highlights regarding biodiversity and prevalent thematic research areas such as "Food Nexus", "Environmental Flows", "Sustainability", "Transitions", and "Governance". Our results suggest that future research should focus on the nexus of "Water-Energy-Food-Biodiversity" and propose a transdisciplinary approach to elucidate the state of sustainability transitions in the agricultural systems at the landscape level. It could increase stakeholder interest in conservation, and sustainability management, to reverse biodiversity losses in ecosystems.

The importance of land in resource criticality assessment methods: A first step towards characterising supply risk

Land is a key resource for human activities under growing pressure. Resource criticality assessment methods investigate the extent to which a resource may become a limiting factor according to various dimensions, including geological, economic and geopolitical availability. They have been applied to resources like minerals, fossil fuels, biotic material or water, but none consider land resources, i.e. natural land units providing space and support for human activities. Based on two recognised criticality methods developed by i) the Yale University and ii) the Joint Research Centre of the European Commission, this study aims to develop spatialized land supply risk indexes at country level. The accessibility of raw resources can be quantified and compared using the supply risk index. The specific characteristics of land call for certain adaptations of the criticality approach, and are designed to ensure comparability between resources. The main adaptations include the definition of land stress and the internal land concentration index. Land stress represents the physical availability of land, while internal land concentration relates to the concentration of landowners within a country. Finally, land supply risk indexes are computed for 76 countries, including 24 European countries for which the results of the two criticality methods are compared. Comparison points to divergences in the countries ranking for land accessibility, thus underlining the importance of methodological choices in the construction of the indexes. Data quality is discussed for European countries with the JRC method, and the use of alternative data sources reveals that it may lead to differences in absolute values, although the ranking of countries with low or high land supply risk does not change. Finally, this work covers a gap in criticality methods by including land resources. These resources can be critical for certain countries, and are essential for human activities such as food or energy production.

Impact of the eco-efficiency of food production on the water-land-food system coordination in China: A discussion of the moderation effect of environmental regulation

The coordination of the water-land-food ("WLF") system is an essential guarantee for ecologically sustainable food production. Based on the perspective of symbiosis theory, we explore practical strategies for enhancing WLF system coordination in China. First, we applied the entropy TOPSIS method to measure WLF system coordination. Second, we used the global-Malmquist-Luenberger ("GML") index to calculate the eco-efficiency of food production. Third, we used the panel Tobit model to empirically explore the improvement path of WLF system coordination and test the moderating role of environmental regulation. Our research has led to the following five conclusions: (i) From 2003 to 2019, the coordination level of the WLF system in all regions of China showed a decreasing trend followed by an increasing trend, with the highest in the Northeast (0.380). The eco-efficiency of food production showed an upward trend in general, with the middle and lower reaches of the Yangtze River (2.101) and the northeastern region (1.888) at a higher level nationwide; (ii) The eco-efficiency of food production does effectively promote WLF system coordination, but with a specific time lag; (iii) The regression results of northern China and major grain-producing areas are consistent with the whole sample. However, the eco-efficiency of food production and its lagging term in southern regions and nonmajor grain-producing regions cannot effectively promote WLF system coordination; (iv) According to the quantile regression results, the promotion of eco-efficiency in food production is more pronounced in regions with higher WLF system coordination (at the 50 %-90 % quantile); and (v) Environmental regulation has a positive moderating effect on the ecological efficiency of food production on the coherence of the WLF system. Moreover, the regression results of grouping moderation show that environmental regulations can play a more vital, positive moderating role in the lower regions compared with higher WLF system coordination regions. Our research innovatively explores the influencing factors of WLF System Coordination. Our research also provides a reference for the formulation of food ecological planting strategies and government environmental regulation policies.

Developing sustainable land-use patterns at watershed scale using nexus of soil, water, energy, and food

Aside from the many services that soil provides, it also stores water and makes it available to crops, which is critical for food security. However, the necessity of further studies for overcoming the existing gap in relation to the role of soil in the water, energy, and food nexus system has been preoccupying the experts and specialists around the world for some time. In this sense, the balance between many key ecosystem components based on the Soil, water, energy, and food (SWEF) nexus framework is one of the key characteristics of holistic and accommodative watershed management systems. To the best of our knowledge, the watershed scale is used as a planning unit for the first time in the current study to construct a conceptual model for adaptive management of optimum land-use/cover allocation using SWEF. The method was then used for the Shazand Watershed, Iran. Numerous metrics, such as soil erosion, soil organic carbon (SOC), water and energy use, mass efficiency, and economic efficiency, were investigated. Finally, a compound indicator was used to generate the SWEF nexus index (SWEFNI) for various land-uses/crops for the node year 2014. SWFENI ranged from 0.19 (worst) for rangeland to 0.78 (best) for almond plantations, according to the findings. The study's present approach may be tested worldwide.

Managing energy-water-carbon-food nexus for cleaner agricultural greenhouse production: A control system approach

Poverty, food insecurity and climate change are global issues facing humanity, threatening social, economic and environmental sustainability. Greenhouse cultivation provides a potential solution to these challenges. However, some greenhouses operate inefficiently and need to be optimized for more economical and cleaner crop production. In this paper, an economic model predictive control (EMPC) method for a greenhouse is proposed. The goal is to manage the energy-water‑carbon-food nexus for cleaner production and sustainable development. First, an optimization model that minimizes the greenhouse's operating costs, including costs associated with greenhouse heating/cooling, ventilation, irrigation, carbon dioxide (CO₂) supply and carbon emissions taking into account both the CO₂ equivalent (CO₂-eq) emissions caused by electrical energy consumption and the negative emissions caused by crop photosynthesis, is developed and solved. Then, a sensitivity analysis is carried out to study the impact of electricity price, supplied CO₂ price and social cost of carbon (SCC) on the optimization results. Finally, a model predictive control (MPC) controller is designed to track the optimal temperature, relative humidity, CO₂ concentration and incoming radiation power in presence of system disturbances. Simulation results show that the proposed approach increases the operating costs by R186 (R denotes the South African currency, Rand) but reduces the total cost by R827 and the carbon emissions by 1.16 tons when compared with a baseline method that minimizes operating costs only. The total cost is more sensitive to changes in SCC than that in electricity price and supplied CO₂ price. The MPC controller has good tracking performance under different levels of system disturbances. Greenhouse environmental factors are kept within specified ranges suitable for crop growth, which increases crop yields. This study can provide effective guidance for growers' decision-making to achieve sustainable development goals.

Assessment of food-energy-environmental pollution nexus in Iran: the nonlinear approach

Iran's agricultural production has expanded significantly in recent years. Environmental pollution caused by the use of energy and chemical fertilizers, depletion of groundwater resources, and soil erosion, on the other hand, demonstrates a lack of attention to the environmental dimension of production in this country. In addition to these issues, climate change has exacerbated the agriculture sector's difficulties. This study intends to investigate the asymmetric relationship between energy consumption, chemical fertilizer consumption, CO2 emissions, temperature changes, and production from 1961 to 2019 using the NARDL approach and Granger causality test in the frequency domain (Breitung and Candelon.). Short-term and long-term estimates revealed that the positive and negative shock effects of energy consumption on production are both positive. As a result, it was observed that the negative shock of increased energy consumption had a greater influence on agricultural output than the positive shock. In the long run, the positive shock of fertilizer use has a positive effect on and improves production. But the effect of a negative shock is insignificant. Furthermore, the negative shock of CO2 emission has a positive effect on production. Finally, positive and negative shocks in temperature changes were discovered to have an increasing and reducing influence on production. The results of the Granger causality test in the frequency domain test showed that there is a bidirectional causality relationship between energy consumption and agro-production in the long term. There is also unidirectional causality from CO2 emissions and fertilizer consumption to production and from production to climate change. According to the findings, reforming energy prices, investing in mechanized agriculture, shifting away from fossil fuel consumption towards renewable energy, and tending to green growth are all necessary to achieve multiple goals such as optimizing energy consumption, reducing environmental pollution, and improving efficiency.

A decision-making framework for the optimal design of renewable energy systems under energy-water-land nexus considerations

The optimal allocation of land for energy generation is of emergent concern due to an increasing demand for renewable power capacity, land scarcity, and the diminishing supply of water. Therefore, economically, socially and environmentally optimal design of new energy infrastructure systems require the holistic consideration of water, food and land resources. Despite huge efforts on the modeling and optimization of renewable energy systems, studies navigating the multi-faceted and interconnected food-energy-water-land nexus space, identifying opportunities for beneficial improvement, and systematically exploring interactions and trade-offs are still limited. In this work we present the foundations of a systems engineering decision-making framework for the trade-off analysis and optimization of water and land stressed renewable energy systems. The developed framework combines mathematical modeling, optimization, and data analytics to capture the interdependencies of the nexus elements and therefore facilitate informed decision making. The proposed framework has been adopted for a water-stressed region in south-central Texas. The optimal solutions of this case study highlight the significance of geographic factors and resource availability on the transition towards renewable energy generation.

An Input–Output Analysis of the Water–Energy–Food Nexus Based on the Intensity and Quantity Index System—A Case Study of 30 Provinces in China

In the study of the water–energy–food nexus (WEF nexus), the importance of the intensity and quantity index system has been widely recognized. In order to study the impact of WEF on the economy, this paper establishes an intensity index system and a quantity index system, taking account of the impact of environmental pollution. Using a DEA model and China’s provincial data from 2019, this paper calculated the efficiency of the WEF nexus with the developed intensity and quantity index systems. The results show that the efficiency is not high in areas with a high economic development level, and efficiency is not the lowest in areas with a relatively low economic development level. When considering environmental pollution, the efficiency of some provinces has increased significantly, indicating that the WEF nexus has not caused environmental damage and is conducive to sustainable economic development. In the two intensity index systems, the efficiency of the production system is significantly lower than that of the consumption system, indicating that there is a serious waste of cultivated land per capita. Compared with the intensity index system, the efficiency of the quantity index system is low, and the polarization is obvious. A high level of GDP does not mean a high level of economic development. There may be a low level of resource utilization technology or environmental pollution underlying it. It is unscientific to evaluate local economic development only by GDP. When evaluating the urban economy and national economy, we should conduct an overall study of WEF and reasonably allocate WEF resources, which will not only help to alleviate the current situation of resource shortage in various countries but also effectively promote the coordinated development of national and regional economies. At the same time, environmental protection should also be taken into account. Compared with the economic development model of developing the economy first and then solving environmental problems, developing and solving at the same time is more conducive to the sustainable development of the national economy.

Integrated model for Food-Energy-Water (FEW) nexus to study global sustainability: The water compartments and water stress analysis

Analysis of global sustainability is incomplete without an examination of the FEW nexus. Here, we modify the Generalized Global Sustainability Model (GGSM) to incorporate the global water system and project water stress on the global and regional levels. Five key water-consuming sectors considered here are agricultural, municipal, energy, industry, and livestock. The regions are created based on the continents, namely, Africa, Asia, Europe, North America, Oceania, and South America. The sectoral water use intensities and geographical distribution of the water demand were parameterized using historical data. A more realistic and novel indicator is proposed to assess the water situation: net water stress. It considers the water whose utility can be harvested, within economic and technological considerations, rather than the total renewable water resources. Simulation results indicate that overall global water availability is adequate to support the rising water demand in the next century. However, regional heterogeneity of water availability leads to high water stress in Africa. Africa’s maximum net water stress is 140%, so the water demand is expected to be more than total exploitable water resources. Africa might soon cross the 100% threshold/breakeven in 2022. For a population explosion scenario, the intensity of the water crisis for Africa and Asia is expected to rise further, and the maximum net water stress would reach 149% and 97%, respectively. The water use efficiency improvement for the agricultural sector, which reduces the water demand by 30%, could help to delay this crisis significantly.

Optimization of Spatial Pattern of Land Use: Progress, Frontiers, and Prospects

Due to high-intensity human disturbance and rapid climate change, optimizing the spatial pattern of land use has become a pivotal path to restoring ecosystem functions and realizing the sustainable development of human–land relationships. This review uses the literature analysis method combined with CiteSpace to determine current research progress and frontiers, challenges, and directions for further improvement in this field. The main conclusions include the following: (a) research on the optimization of spatial pattern of land use has transformed from pattern description orientation to sustainable development orientation to ecological restoration orientation. Its research paradigm has changed from pattern to function to well-being; (b) the research frontier mainly includes spatial pattern of land use that takes into account the unity of spatial structure and functional attributes, the ecological mechanism and feedback effect of change in spatial pattern of land, the theoretical framework and model construction of land use simulation and prediction based on multiple disciplines and fields, and the adaptive management of sustainable land use in the context of climate change; (c) based on current research challenges, we integrate the research on landscape ecology and ecosystem service flows to develop an “element sets–network structure–system functions–human well-being” conceptual model. We also propose the strengthening of future research on theoretical innovation, spatiotemporal mechanism selection, causal emergence mechanism, the transformation threshold, and uncertainty. We provide innovative ideas for achieving sustainable management of land systems and territorial spatial planning with the aim of improving the adaptability of land use spatial optimization. This is expected to strengthen the ability of land systems to cope with ecological security and climate risks.

Energy Systems in the Food Supply Chain and in the Food Loss and Waste Valorization Processes: A Systematic Review

The intensity in energy consumption due to food production systems represents a major issue in a context of natural resources depletion and an increasing worldwide population. In this framework, at least a third of global food production is being lost or wasted. Moreover, about 38% of the energy embedded in total food production is being lost. Consequently, the assessment of energy consumption in food systems, and in food loss and waste valorization systems, is an increasing trend in recent years. In this line, this work presents a systematic review, selecting 74 articles from a search of 16,930 papers regarding the key words “energy assessment food”. The aim was to determine the current and historical trends in this field of research. Results pointed to a worldwide acceleration in trends since 2014, standing out in China and other Asian countries. Concerning the topics of the publications, energy consumption in the food sector is a research field which has existed since 1979. Moreover, the study of energy valorization systems using food loss and waste is an increasing trend since 2010. Additionally, publications focused on the water–energy–food nexus appeared firstly in 2014 and have grown exponentially. Moreover, life cycle assessment highlights as the most widespread methodology used.

Optimization of Production–Living–Ecological Space in National Key Poverty-Stricken City of Southwest China

Trade-offs and conflicts among different sectors of production, living, and ecology have become important issues in regional sustainable development planning due to both the versatility and limitation of land resources, especially in poverty-stricken mountainous areas. This study builds an optimization model to assist policymakers in simulating land demand and allocation in the future. The model takes socioeconomic and demographic development into consideration and couples local planning policy with land use data from the perspective of system integration. The model was employed for a case study of Zhaotong city to optimize production–living–ecological (PLE) space. The results show that the model provides a feasible method to explore the sustainable development pattern of territorial space, especially in distressed regions.

Regional conditions shape the food-energy-land nexus of low-carbon indoor farming

Modern greenhouses and vertical farming projects promise increased food output per unit area relative to open-field farming. However, their high energy consumption calls for a low-carbon power supply such as solar photovoltaic and wind, which adds to cost and overall land footprint. Here we use geospatial and mathematical modelling to compare open-field and two indoor farming methods for vegetable production in nine city-regions chosen globally with varying land availability, climatic conditions and population density. We find that renewable electricity supply is more costly for greenhouses per unit energy demand satisfied, which is due to the greater fluctuation in their energy demand profile. However, greenhouses have a lower energy demand per unit food output, which makes them the least land-intensive option in most of the analysed regions. Our results challenge the land-savings claims of vertical farming compared with open-field production. We also show that regionalizing vegetable supply is feasible in most regions and give recommendations based on the regional context.

A Neural Network Based Superstructure Optimization Approach to Reverse Osmosis Desalination Plants

An ever-growing population together with globally depleting water resources pose immense stresses for water supply systems. Desalination technologies can reduce these stresses by generating fresh water from saline water sources. Reverse osmosis (RO), as the industry leading desalination technology, typically involves a complex network of membrane modules that separate unwanted particles from water. The optimal design and operation of these complex RO systems can be computationally expensive. In this work, we present a modeling and optimization strategy for addressing the optimal operation of an industrial-scale RO plant. We employ a feed-forward artificial neural network (ANN) surrogate modeling representation with rectified linear units as activation functions to capture the membrane behavior accurately. Several ANN set-ups and surrogate models are presented and evaluated, based on collected data from the H2Oaks RO desalination plant in South-Central Texas. The developed ANN is then transformed into a mixed-integer linear programming formulation for the purpose of minimizing energy consumption while maximizing water utilization. Trade-offs between the two competing objectives are visualized in a Pareto front, where indirect savings can be uncovered by comparing energy consumption for an array of water recoveries and feed flows.

Modeling and Optimization of Water–Food–Energy Nexus for Malaysia’s Agricultural Sector

The water–food–energy (WFE) nexus is a strategic system that integrates different separated sectors by using their interconnectedness to reduce trade-offs and allow sustainable development by preventing future resource insecurity. Traditionally, the water, energy, and food sectors operate individually and result in different challenges such as resource scarcity, conflicts in the uses of upstream and downstream hydro systems, and power supply crises due to serious water pollution. Reports so far have only implemented the WFE nexus in countries and cities outside of Malaysia. In addition, there is yet to be a model in literature revolving only on optimizing the agricultural sector’s resources distribution. Hence, this paper aims to develop the first systematic and integrated model for optimal planning of resource allocation in Malaysia’s agricultural sector. The novelty and contribution of this research could be concluded as: (1) multi-objective planning incorporating economic and environmental factors such as economic benefits and carbon emission limit, (2) focusing on the agricultural sector considering geologically-specific crops, livestock, and residents, (3) considering the potential waste recycle systems including wastewater treatment and biomass treatment. The superstructure framework developed based on the case study in Perak, Malaysia aids the implementation of the WFE nexus system locally where trade-offs and synergies between the different sub-units are modelled. From the results, it can be concluded that irrigated paddy crops could contribute to a higher profit compared to palm oil and rubber crops. Thus, future development can be focused on irrigated paddy crops while meeting other constraints and demands to ensure the resources are optimally utilized. The multi-objective optimization solved using MINIMAX algorithm also provides decision-makers with a guideline on how to implement WFE nexus locally in the agricultural sector.

A systems engineering framework for the optimization of food supply chains under circular economy considerations

The current linear "take-make-waste-extractive" model leads to the depletion of natural resources and environmental degradation. Circular Economy (CE) aims to address these impacts by building supply chains that are restorative, regenerative, and environmentally benign. This can be achieved through the re-utilization of products and materials, the extensive usage of renewable energy sources, and ultimately by closing any open material loops. Such a transition towards environmental, economic and social advancements requires analytical tools for quantitative evaluation of the alternative pathways. Here, we present a novel CE system engineering framework and decision-making tool for the modeling and optimization of food supply chains. First, the alternative pathways for the production of the desired product and the valorization of wastes and by-products are identified. Then, a Resource-Task-Network representation that captures all these pathways is utilized, based on which a mixed-integer linear programming model is developed. This approach allows the holistic modeling and optimization of the entire food supply chain, taking into account any of its special characteristics, potential constraints as well as different objectives. Considering that typically CE introduces multiple, often conflicting objectives, we deploy here a multi-objective optimization strategy for trade-off analysis. A representative case study for the supply chain of coffee is discussed, illustrating the steps and the applicability of the framework. Single and multi-objective optimization formulations under five different coffee-product demand scenarios are presented. The production of instant coffee as the only final product is shown to be the least energy and environmental efficient scenario. On the contrary, the production solely of whole beans sets a hypothetical upper bound on the optimal energy and environmental utilization. In both problems presented, the amount of energy generated is significant due to the utilization of waste generated for the production of excess energy.

A land-use decision approach integrating thermal regulation, stormwater management, and economic benefits based on urbanization stage identification

Driven by global climate change and urbanization, urban heat island (UHI) and urban storm flood (USF) have become the most frequent and influential hazards in recent decades. Land-use optimization can effectively cope with these hazards. However, the trade-offs between multi-hazard mitigation and economic development impose many limitations in practice. Furthermore, current region-based optimization methods no longer meet the precise management demand, and both subdivision and spatial heterogeneity identification have the potential for wider applicability. Hence, a systematic integration of climate adaptation and urban construction through land-use planning is urgently required. This paper proposes a new land-use decision approach for improving climate adaptability of urbanization. This approach involves multi-objective optimization, spatial subdivision, and urbanization stage identification, which enable the simultaneous achievement of environmental and economic benefits. Taking Xiamen as case study, the results showed that excessive pursuit of land economic output (LEO) limits the chance of mitigating UHI and USF. Improving the LEO per unit area of construction land could disrupt the link between land exploitation and the increasing side effects of climate hazards. Future urbanization hotspots in Xiamen will likely emerge at the urban fringe in Tong'an District and Xiang'an District. Within each developing unit, the upper limit of construction land was 81.06 hm² and the green space was recommended to be 7.29-21.94 hm². Construction land and bare land contributed most to UHI and USF, while forest and grassland were highly efficient in heat and runoff mitigation. The developed approach proved to be effective and practicable, especially for reducing the impacts of extreme UHI and USF.

Resilience analysis of the nexus across water supply, power generation and environmental systems from a stochastic perspective

Effects of external disturbances such as the population change on dynamics of water supply, power generation and environmental (WPE) systems have seldom been investigated. Following the WPE nexus profiled in the study of Feng et al. (2016), this study incorporated stochasticity of population, water supply and power generation into the modeling of the dynamical system in the Hehuang region of China, and further quantified resilience measures to understand the system's ability to withstand stochastic disturbances. First, the stochastic differential equations were used to improve the simulation of stochasticity in the WPE nexus. Next, the transient probability distribution functions (pdfs) of system variables, obtained by Monte Carlo simulation, were used to describe the evolutionary process of the system. Finally, the stationary pdfs of variables which reflect stable states of the system were derived to calculate four resilience measures. It is shown that: (1) The system approached a stable state after Year 2400 by calculating the L2 norm of the difference between transient and stationary pdfs. (2) The environmental system was identified as the most vulnerable subsystem because of its long convergence time. (3) The water supply system did not change greatly and it would remain stable at its current low level, i.e., water consumption per capita would be less than 80m³. The method adopted in this study is conducive to avoiding risk and the results provide valuable insights for regional management of a WPE nexus.

Dilemma and solution of land scarcity, agro-production, and environmental risk for typical grain-producing areas in rapid urbanizing process in China

How to satisfy food production sustainably in the rapid urbanizing process is a vital problem for major grain-producing areas. Taking two national grain-producing regions in China, Shandong and Dongting Lake Region as examples, this study uses step-by-step prediction and a double-objective linear programming model to analyze the dilemma of land scarcity, food demand, and environmental load. It is found that food demand by 2030 will induce partial regional cropland deficiency and heterogeneous agro-environmental risk among cities. The double-objective linear programming model finds possible solutions in different scenarios: on the premise of keeping the current cropland area unchanged, the upper threshold of crop yield by 2030 will be 2539.06 × 10⁴ t in Dongting and 7175.13 × 104 t in Shandong, respectively. On the condition of guaranteeing food self-sufficiency and minimizing the environmental load, the lower threshold of arable land area should be 99.47 × 10⁴ ha in Dongting and 436.85 × 10⁴ ha in Shandong. Pollutant reduction will be realized by reallocation of agro-production task and optimized practices. The food carbon impact can be reduced by up to 1.27 kg CO₂ eq/kg. This study contributes to feasible pathways towards adequate agro-production, lessened land scarcity, and minimal environmental risk for rapid urbanizing cities in a sustainable way.

Indicators of Land, Water, Energy and Food (LWEF) Nexus Resource Drivers: A Perspective on Environmental Degradation in the Gidabo Watershed, Southern Ethiopia

In Ethiopia, land, water, energy and food (LWEF) nexus resources are under pressure due to population growth, urbanization and unplanned consumption. The effect of this pressure has been a widely discussed topic in nexus resource literature. The evidence shows the predominantly negative impact of this; however, the impact of these factors is less explored from a local scale. As a result, securing nexus resources is becoming a serious challenge for the country. This necessitates the identification of the driving factors for the sustainable utilization of scarce LWEF nexus resources. Our study provides a systemic look at the driving factor indicators that induce nexus resource degradation. We use the Analytical Hierarchical Process (AHP) to develop the indicators’ weights, and use a Path Analysis Model (PAM) to quantitatively estimate the effect of the driving factor indicators on the LWEF nexus resources. The results indicate that social (48%), economic (19%), and policy and institutional changes (14%) are the major nexus resource driving factor indicators. The path analysis results indicate that among the social driving factor indicators, population growth and consumption patterns have a significant direct effect on the LWEF nexus, with path coefficients of 0.15 and 0.089, respectively. Similarly, the potential of LWEF nexus resources is also influenced by the institutional and policy change drivers, such as outdated legislation and poor institutional structure, with path coefficients of 0.46 and 0.39, respectively. This implies that population growth and consumption patterns are the leading social drivers, while outdated legislation and poor institutional structures are the institutional and policies change drivers which have a potential impact on LWEF nexus resource degradation. Similarly, other driving factors such as environmental, economic and technological factors also affect nexus resources to varying degrees. The findings of our study show the benefits of managing the identified driving factors for the protection of LWEF nexus resources, which have close links with human health and the environment. In order to alleviate the adverse effects of driving factors, all stakeholders need to show permanent individual and collective commitment. Furthermore, we underline the necessity of applying LWEF nexus approaches to the management of these drivers, and to optimize the environmental and social outcomes.

Evaluation of environmental consequences affecting human health in the current and optimal cropping patterns in the eastern Lorestan Province, Iran

Planning for optimal use of resources and reduction of environmental impacts, in addition to resource protection, is associated with increasing farmers' revenues and boosting the regional economy. Given the limited resources and environmental impacts of agricultural activities on human health, it is necessary to determine an appropriate cropping pattern. The present research aimed to maximize net profit and minimize environmental impacts, including the releases of carcinogens, noncarcinogens, ozone layer depletion, ionizing radiation, and respiratory inorganics and organics on human health. In this study, an optimal cropping pattern of irrigated and rainfed crops was proposed for the east of Lorestan Province using multi-objective nonlinear programming (MOP). Results showed that the cropping areas of chickpea, rapeseed, and potatoes decreased by 50% in the irrigated crop of MOP model and that of lentil in the MOP model of rainfed crops compared with the current pattern. Another important result was increases in the cropping areas of lentil and bean in the MOP pattern of irrigated crops and wheat in the rainfed MOP model. The environmental impacts of agricultural sector on human health can be reduced by determining an optimal cropping pattern. The implementation of this model in the region reduced the emissions of carcinogens (4%), noncarcinogens (9%), respiratory inorganics (17%), ionizing radiation (14%), ozone layer depletion (17%), and respiratory organics (15%) compared with the existing situation along with an increased net profit of $968,483. According to the findings, consideration of environmental objectives affecting human health is essential in the optimization of the cropping pattern. In addition to optimal use of water and land resources, using the proposed model helps to increase profits and reduce environmental consequences on human health.

An ecological footprint approach for cropland use sustainability based on multi-objective optimization modelling

Croplands are heterogeneous in productivity and their sustainable use holds a prominent place in supporting a virtual society-economy-ecology-environment circle. This study developed a model for the evaluation of cropland use sustainability by integrating the revised ecological footprint model with multi-objective optimization. The model enabled to gain insights into changes of the supply-demand balance of cropland use ecologically from a planning perspective, and also enables policy makers to determine the optimal patterns of cropland use in order to reconcile contradictions between multiple dimensions in agroecosystems, such as resource utilization, economy, society, and environment. The model was demonstrated by solving a real-world problem of cropland use management in Heilongjiang Province, northeast China. Results of demonstration were found to be satisfactory for generating sustainable cropland use patterns in promoting the equilibrium of water use efficiency, net economic benefit, land resource allocation equity, and greenhouse gas emissions. Then, whether various cropland use patterns were ecologically safe based on crop ecological footprint and crop ecological carrying capacity were determined. The status and scenario-based trend of cropland use sustainability provided alternatives for policy makers to allocate cropland efficiently and sustainably. The model is applicable for similar planting-centered regions with limited land and water resources.

DOMINO: Data-driven Optimization of bi-level Mixed-Integer NOnlinear Problems

The Data-driven Optimization of bi-level Mixed-Integer NOnlinear problems (DOMINO) framework is presented for addressing the optimization of bi-level mixed-integer nonlinear programming problems. In this framework, bi-level optimization problems are approximated as single-level optimization problems by collecting samples of the upper-level objective and solving the lower-level problem to global optimality at those sampling points. This process is done through the integration of the DOMINO framework with a grey-box optimization solver to perform design of experiments on the upper-level objective, and to consecutively approximate and optimize bi-level mixed-integer nonlinear programming problems that are challenging to solve using exact methods. The performance of DOMINO is assessed through solving numerous bi-level benchmark problems, a land allocation problem in Food-Energy-Water Nexus, and through employing different data-driven optimization methodologies, including both local and global methods. Although this data-driven approach cannot provide a theoretical guarantee to global optimality, we present an algorithmic advancement that can guarantee feasibility to large-scale bi-level optimization problems when the lower-level problem is solved to global optimality at convergence.

Removable Weighing Lysimeter for Use in Horticultural Crops

Water resources management is a priority issue in agriculture, especially in areas with water supply problems. Recently, one of the most widespread technologies for measuring crop water requirements are weighing lysimeters. Nevertheless, this type of lysimeters are of large dimensions and require a civil work for their installation. In this article, we present a weighing lysimeter prototype (1000 × 600 mm and 350 mm depth) designed to be used in agricultural farming of horticultural crops. We described the design details that includes ease of assembly, carriage and minimum soil alteration. Structural design results and construction process are also provided showing their performance under different tractors scenarios. The measurements accuracy results show the outcomes of the prototype after being tested. Finally, we discuss our design and measurements results by comparing them with other weighing lysimeters. In comparison, the prototype designed is an accurate and reliable device which reduces the surface and depth of the current weighing lysimeters.

Evaluation of the Water–Energy–Land Nexus (WELN) Using Exergy-Based Indicators: The Chilean Electricity System Case

The competition and interlinkages between energy, water, and land resources are increasing globally and are exacerbated by climate change and a rapid increase in the world population. The nexus concept has emerged for a comprehensive understanding related to the management and efficiency of resource use. This paper assesses water–energy–land nexus (WELN) efficiency through integration of the principles of Life Cycle Assessment (LCA) and exergy analysis, using the Chilean energy sector (CES) as a study case. The cumulative exergy consumption (CExC) and cumulative degree of perfection (CDP) are used as indicators for WELN efficiency. The results show the production of 1 MWh of electricity required 17.3 GJex, with the energy component of WELN (fossil and renewable energy sources) being the main contributor (99%). Furthermore, the renewable energy technologies depicted higher CDP of the water–energy–land nexus due to lower CExC and higher technology efficiency concerning non-renewables. The water and land resources contributed slightly to total exergy flow due to low quality in comparison with the energy component. Nevertheless, water availability and competition for land occupation constitute important issues for reducing environmental pressures and local conflicts. This study demonstrated the feasibility of exergy analysis for the evaluation of WELN efficiency through a single indicator, which could facilitate the comparison and integration with different processes and multi-scales.

Optimization of the National Land Space Based on the Coordination of Urban-Agricultural-Ecological Functions in the Karst Areas of Southwest China

National land spatial planning is dominated by urban-agricultural-ecological functions and has become a Chinese national strategic issue. However, the three functional spaces have serious conflicts in the karst areas, causing inconsistencies in regional development and triggering poverty and a more serious situation for the ecological environment. In this study, we used the gray multi-objective dynamic programming model and the conversion of land use and its effects at small region extent model to simulate the developmental structures of future land use in the karst areas of Southwest China under a socioeconomic development scenario, an arable land protection scenario and an ecological security scenario. Finally, based on the coordination of the urban-agricultural-ecological functions, we used a functional space classification method to optimize the spatial structures of the national land space for 2035 year and to identify different functional areas. The results showed that the three scenarios with different objectives had differences in the quantities and spatial structures of land use but that the area of forestland was the largest and the area of water was the smallest in each scenario. The optimization of the national land space was divided into seven functional areas—urban space, agricultural space, ecological space, urban-agricultural space, urban-ecological space, agricultural-ecological space and urban-agricultural-ecological space. The ecological space was the largest and the urban-ecological space was the smallest among seven functional areas. The different types of functional spaces had significant differentiation characteristics in the layouts. The urban-agricultural space, urban-ecological space, agricultural-ecological space and urban-agricultural-ecological space can effectively alleviate the impacts of human activities and agricultural production activities in karst areas, promote the improvement of rocky desertification and improve the quality of the regional ecological environment. The results of this research can provide support for decisions about the balanced development of the national land space and the improvement of environmental quality in the karst areas.

Water-energy-food nexus of bioethanol in Pakistan: A life cycle approach evaluating footprint indicators and energy performance

Water, energy, and food are the most basic and essential sectors for human welfare. However, an inextricable nexus and competition exists among these sectors. Production of molasses-based bioethanol is an interesting case resulting in the production of different food and energy materials while consuming water, energy, land, and other raw materials, throughout its life cycle. This paper briefly describes the nexus among water, energy, and food for bioethanol in Pakistan and its environmental implications. A life cycle approach has been used for evaluating four footprint categories including the carbon, ecological, water scarcity, and energy footprints along with an energy analysis of bioethanol. In comparison to conventional gasoline, bioethanol would have benefits in terms of lesser greenhouse gas emissions, better use of productive land, and superior energy performance, but, this will be at the expense of higher impacts in terms of water scarcity. Therefore, considering only a single aspect could result in inadvertent trade-offs that may go unnoticed. The quantified values would help accomplish integrated resource management along with their utilization within limits so as to be available for other uses. This study could help in developing strategies for optimal management of resources to maximize the synergies and minimize the possible trade-offs.