Oil and gas extraction in the western United States generates significant volumes of produced water (PW) that is typically injected into deep disposal wells. Recently, crop irrigation has emerged as an attractive PW reuse option, but the impact on plant immune response is not known. In this study, we conducted a 3-month greenhouse pot study. Spring wheat (Triticum aestivum) was irrigated 3 times a week with 150 mL (∼80–100% of soil water holding capacity) with one of four irrigation treatments: tap water control, 10% PW dilution, 50% PW dilution, and salt water (NaCl50) control containing the same amount of total dissolved solids as PW50 to determine the effect on disease resistance. The wheat leaves were inoculated with either bacterial or fungal pathogens and changes in pathogenesis-related PR-1 and PR-5 gene expression were measured from the leaf tissue. PW50 experienced the largest relative suppression of PR-1 and PR-5 gene expression compared to noninfected wheat, followed by PW10, NaCl50, and the tap water control. A combination of PW contaminants (boron, total petroleum hydrocarbons, and NaCl) are likely reducing PR-gene expression by reallocating metabolic resources to fight abiotic stresses, which then makes it more challenging for the plants to produce PR genes to fight pathogens. This study provides the first evidence that plant disease resistance is reduced due to irrigation with reused PW, which could have negative implications for food security.

The US Atomic Energy Commission has supported a small program at the Oak Ridge National Laboratory (ORNL) to determine (i) how the heat in waste warm water from electric generating plant condensers can be transferred economically to controlled environments, such as in greenhouses or animal enclosures; and (ii) to suggest, in a conceptual effort, how the heat exchange system could be applied to an intensive food production complex which might be constructed near a power station. A heat-using complex consisting of enclosures for fish, poultry, swine, and vegetable plants has been conceived with the goal of maximizing the use of heat and the wastes from the various operations by recycling. It is hoped that the concept will prove to be sufficiently attractive that a utility or an agribusiness company will undertake a small demonstration based on some of these ideas.

During the past three decades, the Pisque watershed in Ecuador's Northern Andes has become the country's principal export-roses producing area. Recently, a new boom of local smallholders have established small rose greenhouses and joined the flower-export business. This has intensified water scarcity and material/discursive conflicts over water use priorities: water to defend local-national food sovereignty or production for export. This paper examines how including peasant flower farms in the capitalist dream – driven by a ‘mimetic desire’ and copying large-scale capitalist flower-farm practices and technologies – generates new intra-community conflicts over collective water rights, extending traditional class-based water conflicts. New allocation principles in Ecuador's progressive 2008 Constitution and 2014 Water Law prioritising food production over flowers' industrial water use are unlikely to benefit smallholder communities. Instead, decision-making power for peasant communities and their water users' associations on water use priority would enable water user prioritization according to smallholders' own preferences.

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.

Agroforestry systems are widely promoted for their economic and environmental benefits. Food, energy, water and land resources in agroforestry systems are inextricably intertwined and expected to be severely impacted by climate change. Socioeconomic development and increasing populations have posed unique challenges for meeting the demand for food, energy, water and land, and the challenge will become more pressing under projected resource shortages and eco-environmental deterioration. Thus, a method of optimizing and sustainably managing the water-land-food-energy nexus in agroforestry systems under climate change must be developed.This paper develops an optimization model framework for the sustainable management of limited water-land-food-energy resources in agroforestry systems under climate change. The aims are to (1) quantify the interactions and feedbacks within water, land, food and energy subsystems; (2) provide trade-offs among water and energy utilization efficiency, economic benefits and environmental protection in agroforestry systems; and (3) generate optimal policy options among water and land resources for different crops and woodlands in different regions under different climate change patterns.The model framework is based on multiobjective fractional programming, and compromise programming is used to solve it. Climate change patterns are obtained from atmospheric circulation models and representative concentration pathways. The above aims are investigated through an actual nexus management problem in northeast China. Spatiotemporal meteorological and report-based databases, life cycle assessments, Pearson correlation analyses, data envelopment analyses and analytic hierarchy processes are integrated to realize practical application.The results show that climate variation will change the water and land allocation patterns and these changes will be more pronounced for major grain-producing areas. The optimized water allocation decreased (especially for rice, e.g., the optimal average value of the irrigation quota of rice was 4226 m³/ha, while the corresponding actual irrigation requirement of rice was [4200–7200] m³/ha) to improve the water use efficiency, and surface water allocation accounted for two-thirds. Maize had the largest planting area, although planting soybean generated the most greenhouse gases (greenhouse gas emissions from field activities for rice, maize, and soybean were 43.46%, 84.06% and 91.16%, respectively); However, these gases can be absorbed by forests. The model improved the harmonious degree of the resource-economy-environment system from 0.24 to 0.56 after optimization.Integrated models contribute to the sustainable management of water, food, energy and land resources and can consider the complex dynamics under climate change. It can be used as a general model and extended to other agroforestry systems that show inefficient agricultural production.

A case study in the Solukhumbu region in northern Nepal reveals that the high number of seasonal tourists—which has doubled in 20 years—has led to growing water, food, and energy demands that have modified agropastoral practices and the use of local resources. This has induced new patterns in the movement of goods, people, and animals in the Everest region and the reconfiguration of the water–energy–food nexus. We use this concept of nexus to analyze ongoing interactions and transformations. Key changes involve (1) massive imports of consumer goods; (2) use of local resources with new techniques (hydropower plants, improved mills, greenhouses, and pipes for domestic networks) that depend on imported materials, which are newly accessible to Sherpas as a result of economic benefits generated by tourism; (3) commodification of local resources (water, hydropower, vegetables, fodder, and flour); (4) an increasing number of electrical appliances; and (5) new uses of water, especially for tourist-related services, including hot showers, watering of greenhouses, bottling of water, and production of electricity for cell phones, rice cookers, and other electric appliances. These new uses, on top of traditional ones such as mill operation, compete in some places during spring when water supplies are low and the tourist demand is high. A transfer of pressure from one resource (the forest) to another (water) has also resulted from the government ban on woodcutting, incentives to develop hydropower, and the competition between lodges to upgrade their amenities by offering better services (such as hot showers, plugs to recharge batteries, internet connections, and local vegetables). Our research finds that water is now central to the proper running of the tourist industry and the region's economy but is under seasonal pressure.

Water, energy and nutrients are interlinked extensively with food and each other as shown in the monitoring, analysis and evaluation framework for the Water Energy Nutrient Food (WENF) nexus by Haitsma Mulier et al. (2022). This study aims to contribute to the quantification of the Water Energy Nutrient Food nexus regarding urban agriculture. It investigates the water, energy and nutrient demand of urban farms along with the presence of those resources in urban waters at three case study sites. Demands for water and nutrients (nitrogen & phosphorus) at a greenhouse in Amsterdam and a community farm and a container farm in East-Boston could be met by resources present in urban waters (rainwater and wastewater) in the direct vicinity. Whether enough energy is available to operate each of these farms is related to the type of agriculture.

Management of water-food-energy nexus (WEFN) is of great importance to achieve the Sustainable Development Goals. The development of WEFN management strategies is challenged by extensive uncertainties in different system components. Also, agricultural activities would contribute a large portion of the total GHG emissions in many countries, which are affecting the promised carbon neutrality in future. In this study, an inexact fractional fuzzy chance constraint programming method was developed towards planning the water-food-energy nexus system under consideration of both uncertainties and greenhouse gases (GHG) emission. An inexact fractional fuzzy chance constraint programming-based water-energy-food nexus (IFFCCP-WEFN) model has been established under consideration of various restrictions and GHG emissions. Solutions of the planting areas for different crops in different periods have been generated. These results imply that the corn cultivation would be prioritized to satisfy cereal demand due to its relatively lower GHG emission intensity. But the residual resources, after satisfying cereal demand, would tend to be allocated to vegetable planting. Comparison has been conducted among the IFFCCP-WEFN model and WEFN models based the inexact fuzzy chance constraint programming approach with and without GHG emissions. The results indicate that, the results from IFFCCP-WEFN model would achieve a highest unit benefit and lowest total GHG emissions. The total GHG emissions can be 11% less at most than GHG emissions from the resulting crop structures of the other two comparable models. Consequently, the developed IFFCCP-WEFN model can help decision-makers identify the desirable planting structure for crops with a priority of low GHG emission rate. The major contributions in this study include (i) the inexact fractional fuzzy chance constraint programming method to deal with interval and fuzzy parameters, reflect decision makers’ preferences and handle conflicts among contradictory objectives, (ii) the IFFCCP-WEFN model to achieve a maximized unit benefit with respect GHG emissions

Securing the growing populations' demand for food energy and water whilst adapting to climate change is extremely challenging. In this regard, bioenergy coupled with carbon capture and storage or utilisation (BECCS/U) is an attractive solution for meeting both the population demand, and offsetting CO₂ emissions. The purpose of this study is to evaluate the effectiveness of BECCS/U pathways utilising CO₂ for agricultural enrichment in enhancing food systems and reducing GHG emissions within the energy, water and food nexus concept. The study bridges negative emissions with CO₂ fertilisation within an integrated system. It consists of a source of CO₂ represented by a biomass-based integrated gasification combined cycle with carbon capture, a CO₂ network for a sustainable CO₂ supply, and a CO₂ sink characterised by agricultural greenhouses. A techno-economic and environmental analysis of each of these subsystems is conducted, feeding to an overall performance analysis of the integrated BECCS/U pathway. Results reveal synergetic opportunities between the energy, water and food subsectors, whereby CO₂ is captured from an energy sub-system and is efficiently utilised to enhance food sub-systems by improving productivity and reducing crop water requirements. Thus, the proposed integrated BECCS/U system is able to improve food availability by enhancing the food system, increasing the yield by 13.8%, whilst reducing crop water requirements by 28%. System outputs resulted in a levelised cost of 0.35 $/kg of agricultural produce when the system is scaled-up, and an abatement of the related environmental burdens throughout the supply chain by achieving negative CO₂ emissions of 24.6 kg/m².year of cultivated land.