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A Hybrid Input-Output, Techno-Economic Life Cycle Modeling Approach to Enable Greener Supply Chains

A Hybrid Input-Output, Techno-Economic Life Cycle Modeling Approach to Enable Greener Supply Chains
一种混合输入-输出、技术经济生命周期建模方法,以实现更绿色的供应链
批准号:
1236837
负责人:
Eric Masanet
金额:
$31.09万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-09-01 至 2017-08-31

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中文摘要
翻译
1236837(Masanet)。 制造商、零售商和政府对了解产品的供应链能源和碳“足迹”以及减少此类足迹的方法越来越感兴趣。虽然人们对用于环境足迹估算的生命周期评估(LCA)方法给予了很大的关注,但很少关注用于分析设计、工艺和政策机会以减少产品环境足迹的稳健的定量方法。本研究将开发一种混合供应链建模方法,其目的是将投入产出LCA方法与部门级和过程级技术经济能源分析数据和方法相结合。该方法将允许对许多能源和排放源、终端使用技术以及构成产品供应链足迹的部门的离散技术和工艺改进机会进行环境和经济评估。这将通过几项关键任务来实现,其中包括:㈠制定方法,将部门能源数据分解为对工程分析有意义的最终用途类别; ㈡制定统计方法,为每个部门确定目前最终用途技术的基准; ㈢按最终用途得出技术经济成本曲线; ㈣开发直观的公共用途计算工具,以应用建模方法。这项工作将进一步发展分析和统计方法,以技术丰富的方式表征复杂的供应链,这对于详细设计,供应链参与,工艺和材料选择以及面向产品的政策决策至关重要。 这种新型建模方法的成功开发将对LCA和供应链环境管理社区产生巨大影响,并将进一步理想地适合作为包括大学预科生在内的多层次学生的教育工具。 制造商可以利用这些信息来了解其供应链中环境改善的最大机会在哪里,以及此类改善的成本可行性如何,政策制定者可以利用这些信息来确定提供最具成本效益的产品供应链和技术。有效的目标,以减少产品的具体影响,和LCA社区,以更好地在LCA中的过程级别上对技术变化和技术成本进行建模。它还将有助于在LCA和技术经济建模社区之间建立一座新的桥梁。该项目将开发案例研究,以可视化和分析推动绿色供应链实践的各种自由度,并将这些案例研究纳入大学预科科学课程的教学模块。较小的研究问题将被构造成适合本科生。参与者之间的定期会议将确保适当的沟通,并将制定正式的数据管理程序,以确保建模和模拟数据、材料、程序、软件和教育材料的适当存档。除了正常的期刊出版物外,还将开发一个网站来宣传该计划,传播有关教学模块的结果和信息,并分享学校的示范经验,并宣布外展活动,如PI研讨会,本科生研究开放和教师暑期活动。
英文摘要
1236837 (Masanet). There is growing interest among manufacturers, retailers, and governments in understanding the supply chain energy and carbon "footprints" of products, as well as in ways to reduce such footprints. While much attention has been paid to life-cycle assessment (LCA) methods for environmental footprint estimation, comparably little attention has been paid to robust, quantitative methods for analyzing design, process, and policy opportunities for reducing product environmental footprints. This research will develop a hybrid supply chain modeling approach, which aims to couple input-output LCA methods with sector- and process-level techno-economic energy analysis data and methods. The approach will allow for both environmental and economic assessment of discrete technology and process improvement opportunities across the many energy and emissions sources, end use technologies, and sectors that comprise a product's supply chain footprint. This will be accomplished through several key tasks that include: (i) developing methods for disaggregating sector energy data into end use categories meaningful for engineering analysis; (ii) developing statistical methods for benchmarking current end use technologies for each sector; (iii) deriving techno-economic cost curves by end use; and (iv) developing an intuitive public use computation tool for applying the modeling methods. The work will further the state of analytical and statistical methods in the characterization of complex supply chains in technology-rich fashion, which is critical for detailed design, supply chain engagement, process and materials selection, and product-oriented policy decisions. The successful development of this novel modeling approach would have a huge impact on the LCA and supply chain environmental management communities, and would further be ideally suitable as an educational tool for students at many levels, including pre-college students. Such information can be used by manufacturers to understand where the greatest opportunities for environmental improvement might be in their supply chains and how cost-feasible such improvements might be, by policy-makers to identify product supply chains and technologies that offer the most cost-effective and efficient targets for reducing product embodied impacts, and by the LCA community to better model technology variation and technology costs at the process level in LCAs. It will also help forge a new bridge between the LCA and techo-economic modeling communities. The project will develop case studies for visualizing and analyzing the various degrees of freedom for driving greener supply chain practices, and will incorporate these case studies into a teaching module with exercises for pre-college science classes. Smaller research problems will be structured to be suitable for undergraduate students. Regular meetings among participants will ensure proper communication, and a formal data management procedure will be in place to ensure proper archiving of modeling and simulation data, material, procedure, software, and educational material. In addition to normal journal publications, a website will be developed to advertise the program, disseminate results and information about teaching modules and sharing demonstration experience in schools, and announce outreach activities such as seminars by PI, research openings for undergraduates, and summer activities for teachers.
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