A GIS-based method for identifying the optimal location for a facility to convert forest biomass to biofuel
A GIS-based method for identifying the optimal location for a facility to convert forest biomass to biofuel
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DOI：
10.1016/j.biombioe.2011.06.006
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发表时间：
2011-10
影响因子：
6
通讯作者：
Fengli Zhang;Dana M. Johnson;J. Sutherland
中科院分区：
文献类型：
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作者：
Fengli Zhang;Dana M. Johnson;J. Sutherland
人们对从木质生物质中生产生物燃料越来越感兴趣。生产生物燃料的经济成功的关键是确定设施的最佳位置。由于生物质的分布特性和与运输相关的重大成本，对木质生物质原料的选址决定尤为重要。本研究介绍了一种基于多个属性的两阶段方法来确定生物燃料生产的最佳位置。第一阶段使用地理信息系统方法确定可行的生物燃料设施位置。该方法采用县边界、以县为基础的纸浆木材分布、人口普查、城市和村庄分布以及铁路和州/联邦公路运输网络。在第二阶段，使用总运输成本模型选择首选地点。该方法应用于密歇根州上半岛，以确定生物燃料生产设施的位置。通过两阶段方法的应用，生物燃料生产的最佳地点被确定为巴拉加县的L 'anse村。此外，还研究了运输成本和生物燃料生产的最佳地点对几个关键变量变化的敏感性。这些额外的变量包括燃料价格、运输距离和纸浆木材的可用性。通过应用基于有限原料可用性的敏感性分析，伊什佩明市成为生产设施的另一个可行地点。
There is growing interest in the production of biofuels from woody biomass. Critical to the financial success of producing biofuel is identifying the optimal location for the facility. The location decision is especially important for woody biomass feedstock owing to the distributed nature of biomass and the significant costs associated with transportation. This study introduces a two-stage methodology to identify the best location for biofuel production based on multiple attributes. Stage I uses a Geographic Information System approach to identify feasible biofuel facility locations. The approach employs county boundaries, a county-based pulpwood distribution, a population census, city and village distributions, and railroad and state/federal road transportation networks. In Stage II, the preferred location is selected using a total transportation cost model. The methodology is applied to the Upper Peninsula of Michigan to locate a biofuel production facility. Through the application of the two-stage methodology, the best possible location for biofuel production was identified as the Village of L’anse in Baraga County. Also investigated are the sensitivity of transportation cost and the optimal site for biofuel production to changes in several key variables. These additional variables included fuel price, transportation distance, and pulpwood availability. By applying sensitivity analysis based on limited availability of feedstock, the City of Ishpeming emerged as another viable location for the production facility.