A Food-Energy-Water Nexus approach for land use optimization
| Autor: | Yujiao Zeng, Jie Li, Min Zhu, Jie Yu, Fei Song, Styliani Avraamidou, Yaling Nie, Efstratios N. Pistikopoulos, Xin Xiao |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Environmental Engineering
010504 meteorology & atmospheric sciences media_common.quotation_subject 010501 environmental sciences 01 natural sciences Multi-objective optimization Supply and demand Agricultural land Data-driven modeling Environmental Chemistry Integrated assessment Waste Management and Disposal 0105 earth and related environmental sciences media_common 2. Zero hunger Land use 15. Life on land Environmental economics Pollution Interdependence Food-Energy-Water Nexus 13. Climate action Sustainability Food energy Business Nexus (standard) |
| Zdroj: | Nie, Y, Avraamidou, S, Xiao, X, Pistikopoulos, E N, Li, J, Zeng, Y, Song, F, Yu, J & Zhu, M 2019, ' A Food-Energy-Water Nexus approach for land use optimization ', Science of the Total Environment, vol. 659, pp. 7-19 . https://doi.org/10.1016/j.scitotenv.2018.12.242 |
| DOI: | 10.1016/j.scitotenv.2018.12.242 |
| Popis: | Allocation and management of agricultural land is of emergent concern due to land scarcity, diminishing supply of energy and water, and the increasing demand of food globally. To achieve social, economic and environmental goals in a specific agricultural land area, people and society must make decisions subject to the demand and supply of food, energy and water (FEW). Interdependence among these three elements, the Food-Energy-Water Nexus (FEW-N), requires that they be addressed concertedly. Despite global efforts on data, models and techniques, studies navigating the multi-faceted FEW-N space, identifying opportunities for synergistic benefits, and exploring interactions and trade-offs in agricultural land use system are still limited. Taking an experimental station in China as a model system, we present the foundations of a systematic engineering framework and quantitative decision-making tools for the trade-off analysis and optimization of stressed interconnected FEW-N networks. The framework combines data analytics and mixed-integer nonlinear modeling and optimization methods establishing the interdependencies and potentially competing interests among the FEW elements in the system, along with policy, sustainability, and feedback from various stakeholders. A multi-objective optimization strategy is followed for the trade-off analysis empowered by the introduction of composite FEW-N metrics as means to facilitate decision-making and compare alternative process and technological options. We found the framework works effectively to balance multiple objectives and benchmark the competitions for systematic decisions. The optimal solutions tend to promote the food production with reduced consumption of water and energy, and have a robust performance with alternative pathways under different climate scenarios. |
| Databáze: | OpenAIRE |
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