Towards the optimization of sustainable food-energy-water systems: A stochastic approach

Ebrahim Karan, Somayeh Asadi, Rabi Mohtar, Mahad Baawain

Research output: Contribution to journalArticle

33 Scopus citations

Abstract

The interlinkage between the food, energy and water (FEW) supply systems, known as the nexus, has received considerable attention in recent years. Despite this intense interest, there is little work focusing on how to design a sustainable FEW system that can consistently meet its food, energy, and water demands. In an effort to better understand the dynamics among the nexus, the scope of the study is limited to a small-scale FEW system that can consistently yield food for a family of four (two adults and two children) and collect or recycle its own water and supply its own energy needs through solar panels (electricity demand). In order to determine the influence of each component (i.e. food, water, or energy) on the system's output and identify the weakest link of the system (e.g. water scarcity, energy shortage, inconsistent supply of food, etc.), a quantitative modeling is used to calculate the total cost of sustainable FEW systems. The impact of each design decision variable (e.g. size of the system, water recycling capacity, solar system) on the system's output is formulated and then optimized. The model is analyzed for two different climate scenarios; a cloudy and humid scenario and sunny and arid scenario. In both scenarios, the energy component represents a large portion of the system's total cost (around 86% in the humid climate and 73% in the arid climate). This shows that innovative energy production technologies are needed to improve the sustainability of FEW systems at a reasonable cost.

Original languageEnglish (US)
Pages (from-to)662-674
Number of pages13
JournalJournal of Cleaner Production
Volume171
DOIs
StatePublished - Jan 10 2018

All Science Journal Classification (ASJC) codes

  • Renewable Energy, Sustainability and the Environment
  • Environmental Science(all)
  • Strategy and Management
  • Industrial and Manufacturing Engineering

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