Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/3869
Full metadata record
DC FieldValueLanguage
dc.contributor.authorMurthy, Ganti S.en_US
dc.date.accessioned2022-03-17T01:00:00Z-
dc.date.accessioned2022-03-17T15:30:53Z-
dc.date.available2022-03-17T01:00:00Z-
dc.date.available2022-03-17T15:30:53Z-
dc.date.issued2021-
dc.identifier.citationTabatabaie, S. M. H., & Murthy, G. S. (2021). Development of an input-output model for food-energy-water nexus in the pacific northwest, USA. Resources, Conservation and Recycling, 168 doi:10.1016/j.resconrec.2020.105267en_US
dc.identifier.issn0921-3449-
dc.identifier.otherEID(2-s2.0-85095859154)-
dc.identifier.urihttps://doi.org/10.1016/j.resconrec.2020.105267-
dc.identifier.urihttps://dspace.iiti.ac.in/handle/123456789/3869-
dc.description.abstractWith growing populations and changing climate, the food, energy and water (FEW) security have become a global issue. In response, the concept of FEW nexus in which the interdependency between FEW sectors are taken into account in order to effectively manage the resources and provide FEW security has emerged. Thus, in order to understand the interdependency between FEW sectors a thorough quantitative framework is necessary. Although there are numerous studies on FEW nexus, there is limited research on developing mathematical equations to model the FEW nexus. The goal of this study was to develop an input-output (IO) model to quantify the interdependency between FEW sectors in the Pacific Northwest. The FEW sectors were divided into 21 subsectors and IO model was used to quantify the total output of each subsector. Intensity coefficients were calculated and further broken down to technology coefficients and allocation coefficients. The uncertainty analysis was used to quantify the effect of variation in technology coefficients and allocation coefficients on output of each subsector and the results showed that these two distributions are significantly different. The results of sensitivity analysis showed that agricultural crops, especially alfalfa has the highest sensitivity to water and energy consumption due to the fact that alfalfa production is energy and water intensive. The multi-objective optimization was used to minimize the cost and environmental impact of FEW system and the results showed that in order to minimize the cost and environmental impacts, more surface water and hydroelectricity and wind electricity should be utilized. © 2020en_US
dc.language.isoenen_US
dc.publisherElsevier B.V.en_US
dc.sourceResources, Conservation and Recyclingen_US
dc.subjectAgricultural robotsen_US
dc.subjectCropsen_US
dc.subjectEnergy utilizationen_US
dc.subjectMultiobjective optimizationen_US
dc.subjectSensitivity analysisen_US
dc.subjectSurface watersen_US
dc.subjectUncertainty analysisen_US
dc.subjectAgricultural cropsen_US
dc.subjectChanging climateen_US
dc.subjectInput output modelen_US
dc.subjectMathematical equationsen_US
dc.subjectPacific Northwesten_US
dc.subjectQuantitative frameworksen_US
dc.subjectWater and energiesen_US
dc.subjectWind electricityen_US
dc.subjectEnvironmental impacten_US
dc.subjectwateren_US
dc.subjectenergy useen_US
dc.subjectenvironmental impacten_US
dc.subjectenvironmental managementen_US
dc.subjectfood securityen_US
dc.subjectinput-output analysisen_US
dc.subjectoptimizationen_US
dc.subjectsensitivity analysisen_US
dc.subjectwater useen_US
dc.subjectalfalfaen_US
dc.subjectcropen_US
dc.subjectenergyen_US
dc.subjectenergy consumptionen_US
dc.subjectfooden_US
dc.subjectmodelen_US
dc.subjectprocess optimizationen_US
dc.subjectsensitivity analysisen_US
dc.subjecttechnologyen_US
dc.subjectuncertaintyen_US
dc.subjectUnited Statesen_US
dc.subjectPacific Northwesten_US
dc.subjectMedicago sativaen_US
dc.titleDevelopment of an input-output model for food-energy-water nexus in the pacific northwest, USAen_US
dc.typeJournal Articleen_US
Appears in Collections:Department of Biosciences and Biomedical Engineering

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Altmetric Badge: