A multi-criteria decision support tool for biorefinery siting: Using economic, environmental, and social metrics for a refined siting analysis

被引:31
|
作者
Martinkus, Natalie [1 ]
Latta, Greg [2 ]
Rijkhoff, Sanne A. M. [3 ]
Mueller, Daniel [1 ]
Hoard, Season [1 ]
Sasatani, Daisuke [1 ]
Pierobon, Francesca [1 ]
Wolcott, Michael [1 ]
机构
[1] Washington State Univ, Pullman, WA 99164 USA
[2] Univ Idaho, Moscow, ID 83843 USA
[3] Texas A&M Univ Corpus Christi, Corpus Christi, TX USA
来源
BIOMASS & BIOENERGY | 2019年 / 128卷
基金
美国食品与农业研究所;
关键词
Decision support tool; Biofuel supply chain; Multi-criteria decision analysis; Supply chain logistics; Facility siting; LIFE-CYCLE ASSESSMENT; SUPPLY CHAINS; BIOFUEL PRODUCTION; BIOMASS; DESIGN; AVAILABILITY; OPTIMIZATION; COLLECTION; FACILITIES; SYSTEMS;
D O I
10.1016/j.biombioe.2019.105330
中图分类号
S2 [农业工程];
学科分类号
0828 ;
摘要
Facility siting has traditionally been performed using economic metrics alone to determine suitable locations for a new facility. In this era of climate change concerns and political discord, a more holistic approach to biorefinery siting may yield alternative locations that meet stakeholder goals for community acceptance and reduced environmental impacts. A multi-criteria decision support tool (DST) that incorporates economic, environmental, and social metrics concurrently is introduced to assess the repurpose potential of existing facilities as a wood-based biorefinery. Economic siting criteria are represented by biorefinery operational cost components that vary geospatially. The environmental criterion is the Global Warming Potential of the supply chain, as measured through greenhouse gases emitted from the feedstock procurement, preprocessing, and transport equipment. Social criteria are represented by 1) the number of regional jobs created through the installation of a biofuel supply chain, and 2) county-level social assets that may influence biorefinery project success. Weights and scale values are derived for each set of metrics. An overall facility score is produced by summing the three metric scores. Additionally, overall user-defined metric weights are used to adjust the importance of the three metrics, thus altering the overall facility scores. The DST is applied to a case study in Western Oregon and Western Washington to refine a list of candidate pulp mills down to a select few for further investigation. It was found that the mills scored differently when overall metric weights were adjusted. Therefore, different stakeholder preferences may yield a different priority list of facilities.
引用
收藏
页数:11
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