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

文献类型：期刊论文

作者Nie, Yaling1,2,3,4; Avraamidou, Styliani3,4; Xiao, Xin1; Pistikopoulos, Efstratios N.3,4; Li, Jie5; Zeng, Yujiao1; Song, Fei1; Yu, Jie1; Zhu, Min1
刊名SCIENCE OF THE TOTAL ENVIRONMENT
出版日期2019-04-01
卷号659页码:7-19
关键词Land use Food-Energy-Water Nexus Data-driven modeling Multi-objective optimization Integrated assessment
ISSN号0048-9697
DOI10.1016/j.scitotenv.2018.12.242
英文摘要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. (c) 2018 Elsevier B.V. All rights reserved.
WOS关键词PRODUCTION SYSTEMS ; RESPONSE FUNCTIONS ; CROPPING SYSTEM ; YIELD RESPONSE ; NITROGEN USE ; MODEL ; AGRICULTURE ; UNCERTAINTY ; IRRIGATION ; TEXAS
资助项目STS Project of Chinese Academy of Sciences[KFJ-EW-STS-054-3] ; Program of China Scholarship Council[201604910976] ; National Natural Science Foundation of China[61603370] ; National Science Foundation under Grant Addressing Decision Support for Water Stressed FEW Nexus Decisions[1739977] ; Texas A & M Energy Institute
WOS研究方向Environmental Sciences & Ecology
语种英语
WOS记录号WOS:000457293700002
出版者ELSEVIER SCIENCE BV
资助机构STS Project of Chinese Academy of Sciences ; Program of China Scholarship Council ; National Natural Science Foundation of China ; National Science Foundation under Grant Addressing Decision Support for Water Stressed FEW Nexus Decisions ; Texas A & M Energy Institute
源URL[http://ir.ipe.ac.cn/handle/122111/27936]  
专题中国科学院过程工程研究所
通讯作者Xiao, Xin; Pistikopoulos, Efstratios N.; Li, Jie
作者单位1.Chinese Acad Sci, Inst Proc Engn, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Texas A&M Univ, Artie McFerrin Dept Chem Engn, College Stn, TX 77843 USA
4.Texas A&M Univ, Texas A&M Energy Inst, College Stn, TX 77843 USA
5.Univ Manchester, Sch Chem Engn & Analyt Sci, Manchester M13 9PL, Lancs, England
推荐引用方式
GB/T 7714		 Nie, Yaling,Avraamidou, Styliani,Xiao, Xin,et al. A Food-Energy-Water Nexus approach for land use optimization[J]. SCIENCE OF THE TOTAL ENVIRONMENT,2019,659:7-19.
APA Nie, Yaling.,Avraamidou, Styliani.,Xiao, Xin.,Pistikopoulos, Efstratios N..,Li, Jie.,...&Zhu, Min.(2019).A Food-Energy-Water Nexus approach for land use optimization.SCIENCE OF THE TOTAL ENVIRONMENT,659,7-19.
MLA Nie, Yaling,et al."A Food-Energy-Water Nexus approach for land use optimization".SCIENCE OF THE TOTAL ENVIRONMENT 659(2019):7-19.

入库方式： OAI收割

来源：过程工程研究所

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