气候变化领域集成服务门户(CCPortal): Elevating urban sustainability: An intelligent framework for optimizing water-energy-food nexus synergies in metabolic landscapes

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DOI	10.1016/j.apenergy.2024.122849
	Elevating urban sustainability: An intelligent framework for optimizing water-energy-food nexus synergies in metabolic landscapes
	Zhou, Yanlai; Chang, Fi-John; Chang, Li-Chiu; Herricks, Edwin
发表日期	2024
ISSN	0306-2619
EISSN	1872-9118
起始页码	360
卷号	360
英文摘要	As global urbanization accelerates, harmonizing water, energy, and food (WEF) resources within urban contexts is pivotal for sustainable development. This study introduces the Intelligent Urban Metabolism Framework (IUMF) for synergizing WEF dynamics, with a focus on socio-technological linkages and environmental concerns arising from climate change. Through a pioneering fusion of system dynamics simulation, machine learning surrogate, metaheuristic optimization, and multi-criteria decision making techniques, IUMF offers a transformative approach to resource management under climate uncertainty. Leveraging comprehensive data sourced from Taipei, Taiwan, this study demonstrates noteworthy enhancements in WEF nexus synergies, including a 9% boost in water supply, an 8% rise in energy benefits, and a significant 13.8% increase in food production. The cases corresponding to the best solutions under the scenario depicting a wet year and high solar radiation intensity would attain the largest benefits: 873 million m3 of water supply (water sector), 90.3 million USD of power benefits (energy sector), and 79 million kg of food production (food sector). These advancements are achieved while reducing computational runtime from 20 h to 30 min. By fostering a user-friendly interface and embracing an intelligent framework, IUMF catalyzes urban sustainability efforts. Our study highlights the potential of intelligent frameworks in addressing complex urban challenges and guiding the evolution of resourceefficient systems and offers a blueprint for a more resilient and sustainable urban future.
英文关键词	Nexus optimization; Water-energy-food (WEF); Renewable energy; Urban metabolism; Artificial intelligence (AI)
语种	英语
WOS研究方向	Energy & Fuels ; Engineering
WOS类目	Energy & Fuels ; Engineering, Chemical
WOS记录号	WOS:001197775500001
来源期刊	APPLIED ENERGY
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/296941
作者单位	Wuhan University; National Taiwan University; Tamkang University; University of Illinois System; University of Illinois Urbana-Champaign
推荐引用方式 GB/T 7714	Zhou, Yanlai,Chang, Fi-John,Chang, Li-Chiu,et al. Elevating urban sustainability: An intelligent framework for optimizing water-energy-food nexus synergies in metabolic landscapes[J],2024,360.
APA	Zhou, Yanlai,Chang, Fi-John,Chang, Li-Chiu,&Herricks, Edwin.(2024).Elevating urban sustainability: An intelligent framework for optimizing water-energy-food nexus synergies in metabolic landscapes.APPLIED ENERGY,360.
MLA	Zhou, Yanlai,et al."Elevating urban sustainability: An intelligent framework for optimizing water-energy-food nexus synergies in metabolic landscapes".APPLIED ENERGY 360(2024).