An integrated multi‐feedstock bioenergy (i.e., biofuel, biopower, or bioproduct) supply system has potential to reduce biomass supply system uncertainties and costs. This study identifies optimal configurations of multi‐feedstock biomass‐to‐biorefinery supply chains and pertinent feedstock combinations based on spatial distribution of feedstock and lowest delivered cost to the biorefinery. We used the Supply Characterization Model (SCM) to allocate feedstock supplies to candidate biorefinery facilities. Model runs were performed for herbaceous energy crops, agriculture residue, and woody biomass available in 2017, 2022, 2025, and 2030 as estimated by the Policy Analysis System (POLYSYS) and Forest Sustainable and Economic Analysis Model (ForSEAM) models. Three feedstock supply scenarios were compared: (a) an herbaceous scenario: switchgrass, miscanthus, biosorghum, and corn stover; (b) a woody scenario: coppice wood, noncoppice wood, whole trees, and forestry residues, and (c) a mixed scenario: a combination of all feedstocks in herbaceous and woody scenarios. By 2030 the analyses predicted that 323, 168, and 473 biorefineries were sited in the herbaceous, woody, and mixed scenario, respectively, in the conterminous USA. Feedstock mixes supplied to the biorefineries were mostly dominated by a single feedstock. The most prominent feedstock mixes identified were: (1) switchgrass and miscanthus; (2) coppice and noncoppice wood; and (3) coppice wood, noncoppice wood, switchgrass and miscanthus. Biorefineries using multi‐feedstock would be beneficial for growth of bioeconomy, however flexible and cost‐effective conversion platforms should be developed to efficiently utilize multiple feedstocks. This analysis identifies biorefinery locations and feedstock supply mixes while minimizing delivered feedstock costs based on spatial and temporal feedstock availability. © 2020 Society of Chemical Industry and John Wiley & Sons, Ltd

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评估美国选址单原料和多原料生物精炼厂的原料供应，并确定流行原料

集成的多原料生物能源（即生物燃料，生物能或生物产品）供应系统具有减少生物质供应系统不确定性和成本的潜力。这项研究基于原料的空间分布和最低的向生物精炼厂的交付成本，确定了多原料生物质到生物精炼厂供应链的最佳配置以及相关的原料组合。我们使用供应特征模型（SCM）将原料供应分配给候选生物精炼厂。根据政策分析系统（POLYSYS）和森林可持续与经济分析模型（ForSEAM）模型的估计，对2017年，2022年，2025年和2030年可用的草本能源作物，农业残渣和木质生物量进行了模型运行。比较了三种原料供应情景：（a）草本情景：柳枝,、芒草，高粱和玉米秸秆；（b）木本情景：小灌木林，非木本木材，整木和林业残留物，以及（c）混合情景：在草木和木本情景中所有原料的组合。到2030年，分析预测，在美国本土，分别有323、168和473个生物精炼厂位于草本，木本和混合方案中。供应给生物精炼厂的原料混合物主要由单一原料主导。确定的最突出的原料混合物为：（1）柳枝and和桔梗；（2）矮木和非矮木；（3）小灌木林木材，非小灌木林木材，柳枝mis和胡桃木。使用多种原料的生物精炼厂将有利于生物经济的发展，但是，应该开发灵活且具有成本效益的转化平台，以有效利用多种原料。该分析确定了生物精炼厂的位置和原料供应组合，同时根据空间和时间上的原料可用性，将交付的原料成本降至最低。©2020年化学工业协会和John Wiley＆Sons，Ltd