Canadian optimal biomass processing framework

加拿大最佳生物质加工框架

• 批准号: RGPIN-2022-05152
• 负责人: Kantor, Ivan
• 金额: $ 1.89万
• 依托单位: Concordia University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=746899
• 关键词: Canadian; optimal; biomass; processing; framework

Canada has rich biomass resources and a history of producing and exporting forestry and agricultural products. With an increasing global need to find sustainable solutions to produce the material and energy demanded by society, concepts of biomass-to-chemicals and biomass-to-fuels are viable options for a future sustainable chemical sector combined with the current activities. The goal of this research project is therefore to identify the best solutions for biomass transformation throughout Canada, considering different types of biomass and availability of regional resources, with specific constraints imposed by geographical context and surrounding potential interconnections. The solutions are generated using an optimization framework based on process integration, consequently enabling assessment of integrating novel biomass processing routes with existing processes (e.g. pulping) and cross-sectorally to explore industrial symbiosis opportunities. The long-term goal of this research programme is therefore to develop the necessary tools and methods to support decision-making toward a more sustainable industrial economy, with specific focus on the use and transformation of biomass feedstock into value-added products and how to integrate these processes with other processes and sectors of the economy (Obj0). The foundational aspects to be developed within this initial phase of the research program include an ontology to classify resource properties and provide system recommendations (Obj1), a comprehensive geographical framework to quantify resource availability and product demands (Obj2), and a modelbase of conversion technologies to provide options for a superstructure optimization framework to select transition pathways toward a sustainable industrial economy in Canada (Obj3). This initial phase of the research is a crucial foundation for future expansion of the work and to make the transition to a more sustainable industrial economy in Canada. The techniques and skills that will be used and developed by the researchers during this initial phase of the research programme are highly relevant in the industrial, government and academic domains. Specifically, ontology is the basis for knowledge graphs and recommender systems, which are highly-valued parts of many commercial platforms and are a burgeoning area of academic research. Database development and management, and associated techniques of data treatment are also highly-relevant in industry, academia and government and extend to machine learning and analytics applications. Finally, modelling and optimization skills have extensive demand in industrial and academic domains, and are increasingly used to improve various aspects of design and operation of industrial processes. Overall, the three doctoral students involved in this programme will emerge as highly-qualified contributors to the Canadian workforce, and will be well-suited for a variety of future positions.

加拿大拥有丰富的生物质资源，有着生产和出口林业和农产品的历史。随着全球越来越需要寻找可持续解决方案来生产社会所需的材料和能源，生物质转化为化学品和生物质转化为燃料的概念是未来可持续化学行业与当前活动相结合的可行选择。因此，该研究项目的目标是确定整个加拿大生物质转化的最佳解决方案，考虑不同类型的生物质和区域资源的可用性，以及地理环境和周围潜在互连所施加的具体限制。这些解决方案是使用基于工艺集成的优化框架生成的，从而能够评估新型生物质加工路线与现有工艺（例如制浆）的集成，并跨部门探索工业共生机会。因此，该研究计划的长期目标是开发必要的工具和方法来支持决策，实现更可持续的工业经济，特别关注生物质原料的使用和转化为增值产品，以及如何将这些过程与其他过程和经济部门整合（Obj0）。研究计划初始阶段要开发的基础方面包括对资源属性进行分类并提供系统建议的本体论（Obj1）、量化资源可用性和产品需求的综合地理框架（Obj2）以及转换技术模型库，为上层建筑优化框架提供选项，以选择加拿大可持续工业经济的转型路径（Obj3）。该研究的初始阶段是未来工作扩展以及加拿大向更可持续的工业经济转型的重要基础。研究人员在研究项目的初始阶段将使用和开发的技术和技能与工业、政府和学术领域高度相关。具体来说，本体是知识图谱和推荐系统的基础，知识图谱和推荐系统是许多商业平台中非常有价值的部分，也是学术研究的一个新兴领域。数据库开发和管理以及相关的数据处理技术也与工业界、学术界和政府高度相关，并扩展到机器学习和分析应用。最后，建模和优化技能在工业和学术领域有着广泛的需求，并且越来越多地用于改进工业流程设计和操作的各个方面。总体而言，参与该计划的三名博士生将成为加拿大劳动力的高素质贡献者，并且非常适合未来的各种职位。