A comparative study on the environmental impact of greenhouses: A probabilistic approach

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.

A Flashforward Look into Solutions for Fruit and Vegetable Production

One of the most important challenges facing current and future generations is how climate change and continuous population growth adversely affect food security. To address this, the food system needs a complete transformation where more is produced in non-optimal and space-limited areas while reducing negative environmental impacts. Fruits and vegetables, essential for human health, are high-value-added crops, which are grown in both greenhouses and open field environments. Here, we review potential practices to reduce the impact of climate variation and ecosystem damages on fruit and vegetable crop yield, as well as highlight current bottlenecks for indoor and outdoor agrosystems. To obtain sustainability, high-tech greenhouses are increasingly important and biotechnological means are becoming instrumental in designing the crops of tomorrow. We discuss key traits that need to be studied to improve agrosystem sustainability and fruit yield.

Growth, Fruit Yield, and Bioactive Compounds of Cherry Tomato in Response to Specific White-Based Full-Spectrum Supplemental LED Lighting

Supplemental artificial light in greenhouses is fundamental to achieving sustainable crop production with high yield and quality. This study’s purpose was to investigate the efficacy of supplemental light (SL) sources on the vegetative and reproductive growth of cherry tomatoes. Four types of light sources were applied, including high-pressure sodium lamps (HPS), a narrow-spectrum LED light (NSL), and two specific full-spectrum LED lights (SFL1 and SFL2) with a shorter blue peak wavelength (436 nm) and/or green peak wavelength (526 nm). The control was the natural light condition. Shoot fresh and dry weight and leaf area in the SFL1 and SFL2 treatments were greater than those in the control. The HPS and NSL treatments also enhanced tomato growth, but they were less efficient compared to the SFL treatments. The SFL1 and SFL2 treatments showed higher fruit yields by 73.1% and 70.7%, respectively, than the control. The SL sources did not affect the effective photochemical quantum yield of photosystem II (Y (II)). However, they did trigger the increased electron transport rate (ETR) and non-photochemical quenching (NPQ). The SFL treatments enhanced tomato growth, fruit yield, and efficient use of light and energy, suggesting that the specific full spectrum based on the short-wavelength blue and/or green peak can be successfully applied for the cultivation of cherry tomato and other crops in greenhouses.

Research on the Operational Strategy of the Hybrid Wind/PV/Small-Hydropower/Facility-Agriculture System Based on a Microgrid

The use of renewable energy sources, such as wind, photovoltaics (PV), and hydropower, to supply facility agriculture may effectively mitigate food and environmental pollution problems and ensure continuity of the energy supply. The operating conditions of a hybrid system are complex, so the operating strategy is very important for system configuration and scheduling purposes. In the current study, first, a hybrid wind/PV/small-hydropower/facility-agricultural system was constructed. Then, the chaotic particle swarm method was applied to optimize hybrid system operation, and a scheduling strategy of the hybrid system was proposed. Finally, combined with an example, according to wind and PV power output and load curves, supply-to-load curves for wind, PV, and small hydropower were obtained. The operational strategy proposed in this study maximizes the utilization of wind and solar resources and rationally allocates hydropower resources. The aforementioned operational strategy provides a basis for hybrid system capacity allocation and scheduling.

A Supervisory Control Strategy for Improving Energy Efficiency of Artificial Lighting Systems in Greenhouses

Artificial lighting systems are used in commercial greenhouses to ensure year-round yields. Current Light Emitting Diode (LED) technologies improved the system efficiency. Nevertheless, having artificial lighting systems extended for hectares with power densities over 50W/m2 causes energy and power demand of greenhouses to be really significant. The present paper introduces an innovative supervisory and predictive control strategy to optimize the energy performance of the artificial lights of greenhouses. The controller has been implemented in a multi-span plastic greenhouse located in North Italy. The proposed control strategy has been tested on a greenhouse of 1 hectare with a lighting system with a nominal power density of 50 Wm−2 requiring an overall power supply of 1 MW for a period of 80 days. The results have been compared with the data coming from another greenhouse of 1 hectare in the same conditions implementing a state-of-the-art strategy for artificial lighting control. Results outlines that potential 19.4% cost savings are achievable. Moreover, the algorithm can be used to transform the greenhouse in a viable source of energy flexibility for grid reliability.