Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/23724
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dc.contributor.authorXu, Y-
dc.contributor.authorTan, J-
dc.contributor.authorWang, X-
dc.contributor.authorLi, W-
dc.contributor.authorHe, X-
dc.contributor.authorHu, X-
dc.contributor.authorFan, Y-
dc.date.accessioned2021-12-11T13:48:53Z-
dc.date.available2021-12-11T13:48:53Z-
dc.date.issued2021-11-18-
dc.identifierORCID iD: Yurui Fan https://orcid.org/0000-0002-0532-4026-
dc.identifier107323-
dc.identifier.citationXu, Y. et al. (2021) 'Synergetic management of water-energy-food nexus system and GHG emissions under multiple uncertainties: An inexact fractional fuzzy chance constraint programming method', Agricultural Water Management, 262, 107323, pp. 1-17. doi: 10.1016/j.agwat.2021.107323.en_US
dc.identifier.issn0378-3774-
dc.identifier.urihttps://bura.brunel.ac.uk/handle/2438/23724-
dc.description.abstractManagement of water-food-energy nexus (WEFN) is of great importance to achieve the Sustainable Development Goals. The development of WEFN management strategies is challenged by extensive uncertainties in different system components. Also, agricultural activities would contribute a large portion of the total GHG emissions in many countries, which are affecting the promised carbon neutrality in future. In this study, an inexact fractional fuzzy chance constraint programming method was developed towards planning the water-food-energy nexus system under consideration of both uncertainties and greenhouse gases (GHG) emission. An inexact fractional fuzzy chance constraint programming-based water-energy-food nexus (IFFCCP-WEFN) model has been established under consideration of various restrictions and GHG emissions. Solutions of the planting areas for different crops in different periods have been generated. These results imply that the corn cultivation would be prioritized to satisfy cereal demand due to its relatively lower GHG emission intensity. But the residual resources, after satisfying cereal demand, would tend to be allocated to vegetable planting. Comparison has been conducted among the IFFCCP-WEFN model and WEFN models based the inexact fuzzy chance constraint programming approach with and without GHG emissions. The results indicate that, the results from IFFCCP-WEFN model would achieve a highest unit benefit and lowest total GHG emissions. The total GHG emissions can be 11% less at most than GHG emissions from the resulting crop structures of the other two comparable models. Consequently, the developed IFFCCP-WEFN model can help decision-makers identify the desirable planting structure for crops with a priority of low GHG emission rate. The major contributions in this study include (i) the inexact fractional fuzzy chance constraint programming method to deal with interval and fuzzy parameters, reflect decision makers’ preferences and handle conflicts among contradictory objectives, (ii) the IFFCCP-WEFN model to achieve a maximized unit benefit with respect GHG emissions-
dc.description.sponsorshipNational Natural Science Foundation of China, China (Grant No. 62073134)-
dc.format.extent1 - 17-
dc.format.mediumPrint-Electronic-
dc.language.isoen_USen_US
dc.publisherElsevieren_US
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/-
dc.rights.uriCopyright © 2021 Elsevier. All rights reserved. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/10.1016/j.agwat.2021.107323, archived on this repository under a Creative Commons CC BY-NC-ND attribution licence (https://creativecommons.org/licenses/by-nc-nd/4.0/).-
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/-
dc.subjectinexact fractional programmingen_US
dc.subjectfuzzy chance constrainten_US
dc.subjectuncertaintyen_US
dc.subjectwater-energy-food nexus systemen_US
dc.subjectdecision makingen_US
dc.subjectGHG emissionen_US
dc.titleSynergetic management of water-energy-food nexus system and GHG emissions under multiple uncertainties: An inexact fractional fuzzy chance constraint programming methoden_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.1016/j.agwat.2021.107323-
dc.relation.isPartOfAgricultural Water Management-
pubs.publication-statusPublished-
pubs.volume262-
dc.identifier.eissn1873-2283-
dc.rights.holderElsevier-
Appears in Collections:Dept of Mechanical and Aerospace Engineering Research Papers

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