Carbon optimal bioenergy with carbon capture and storage supply chain modelling: How far is too far?
Carbon optimal bioenergy with carbon capture and storage supply chain modelling: How far is too far?
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DOI：
10.1016/j.seta.2021.101406
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发表时间：
2021-06
影响因子：
8
通讯作者：
Muir Freer;C. Gough;A. Welfle;A. Lea-Langton
中科院分区：
文献类型：
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作者：
Muir Freer;C. Gough;A. Welfle;A. Lea-Langton
碳导航系统（CNS）展示了一种新的方法，以高空间分辨率对具有碳捕获和储存（BECCS）供应链的特定碳效率生物能源进行建模。CNS模型能够搜索并将精确数量的生物质路由到选定的位置，将捕获的CO2路由到海上地质储存并将能源直接输出到最终用户。CNS模型是卡车、铁路、航运和二氧化碳兼容管道之间的多模式，以确保碳优化路由。该模型的操作和输出证明通过案例研究的方法，使用说明甜菜衍生的生物乙醇BECCS供应链。CNS模型计算了案例研究供应链的碳性能热图，揭示了BECCS设施的碳最优位置。还创建了一个BECCS供应链符号，它允许生成分类图，显示任何给定区域的BECCS供应链类型。CNS模型可以对任何BECCS供应链进行建模，也可以重新用于对任何其他供应链进行建模。本分析中提出的方法提供了一个有用的启发式，可以帮助碳效率的BECCS在英国的部署，并有可能被复制到其他国家或计算碳效率的跨国BECCS供应链。
The Carbon Navigation System (CNS) showcases a new methodology to model specific carbon-efficient bioenergy with carbon capture and storage (BECCS) supply chains at high spatial resolution. The CNS model is capable of searching and routing for a precise amount of biomass to a chosen location, route captured CO2for offshore geological storage and direct energy output to end-users. The CNS model is multi-modal between trucks, rails, shipping and CO2-compatible pipelines to ensure carbon-optimal routings. The model’s operation and outputs are demonstrated through a case study approach using an illustrative sugar beet derived bioethanol BECCS supply chain. The CNS model calculates carbon performance heatmaps for the case study supply chain, revealing the carbon-optimal position of the BECCS facility. A BECCS supply chain notation was also created, which allowed for the generation of classification maps that present the BECCS supply chain type for any given area. The CNS model can model any BECCS supply chain or be repurposed to model any other supply chain. The methodology presented in this analysis provides a useful heuristic that can aid the carbon-efficient deployment of BECCS in the UK and has the potential to be replicated for other countries or calculate carbon-efficient trans-national BECCS supply chains.