Developing a Spatially-Explicit Agent-Based Life Cycle Analysis Framework for Improving the Environmental Sustainability of Bioenergy Systems

1132581（徐）。 该项目有两个主要目标。首先，一个空间上明确的代理为基础的LCA框架将开发，以改善标准的LCA建模技术，通过克服与分析新兴技术与动态和不断发展的供应链所涉及的问题。这一目标的实现将推动LCA方法的发展，为环境可持续性分析提供新的工具。 其次，将改进的LCA建模框架应用于美国柳枝稷生物能源系统（生物燃料和生物质发电），以研究各种政策情景下的未来供应链动态和演变，并评估相关的生命周期环境影响。这项工作的完成将为国家和选定的州提供一个路线图，以实现生物能源的发展目标，同时满足市场需求和最大限度地减少对环境的影响。 建议的空间显式基于代理的LCA建模框架将传统的LCA建模与基于代理的建模技术，以允许环境干预数据库和供应链的动态和演化之间的反馈。该模型将通过纳入地理空间数据和工具，在空间上是明确的。拟议的框架解决了一些重大的挑战，确定了LCA社区在生物能源LCA和LCA方法一般，并将普遍适用于其他系统以外的生物能源案例研究。该项目的成功将改善LCA方法分析动态新兴系统的状态。 除了这一方法上的进步，该项目的结果可能直接影响有关生物能源开发的决定。通过该项目，我们将能够1）了解整个生物能源供应链将如何应对不同的政策干预，2）为国家和州一级的生物燃料和生物质发电的开发和部署提供决策支持信息，3）指导生物燃料和生物质发电行业推进技术开发，以及4）教育下一代工程师和政策制定者了解生物能源系统中的复杂问题并获得多学科技能。 这项研究的影响可能比提供柳枝稷生物能源开发及其环境影响的关键信息更广泛。所建立的基于Agent的耦合模型和LCA技术可用于任何开发系统。在这项研究中开发的方法可以解决的关键挑战之一，试图预测一个非既定的系统的环境影响，增加动态组件，帮助了解发展复杂的适应系统和技术变革的总效应。 该项目的教育影响包括整合本科和研究生课程和课程。一名博士生将接受培训，从事国际上感兴趣的前沿研究。硕士生将看到这项研究的各个方面融入工程的UM学院和自然资源与环境学院之间的工程可持续系统双学位课程。项目团队还将参加UM UROP计划，该计划为代表性不足的少数民族本科生提供指导和研究经验。为了广泛传播研究成果用于教育目的，该团队将开发相关课程模块并提交给可持续工程中心的电子图书馆供同行评审。该项目开发的模型将通过OpenABM联盟与科学界共享。

1132581 (Xu). This project has two major goals. First, a spatially-explicit agent-based LCA framework will be developed to improve the standard LCA modeling technique by overcoming the issues involved with analyzing emerging technologies with dynamic and evolving supply chains. The achievement of this goal will advance LCA methodology and provide a new tool for environmental sustainability analysis. Second, this improved LCA modeling framework will be applied to the U.S. switchgrass bioenergy system (biofuels and biomass electricity) to examine the future supply chain dynamics and evolution under a variety of policy scenarios and evaluate the associated life cycle environmental impacts. The completion of this work will provide a roadmap for the nation and selected states to achieve bioenergy development goals while meeting market demand and minimizing environmental impact. The proposed spatially-explicit agent-based LCA modeling framework will integrate conventional LCA modeling with an agent-based modeling technique to allow feedback between the environmental intervention database and the dynamics and evolution of supply chain. The model will be spatially-explicit by incorporating geospatial data and tools. The proposed framework addresses some of the grand challenges identified by the LCA community in both bioenergy LCA and LCA methodology in general, and will be generally applicable to other systems beyond the bioenergy case study. The success of this project will improve the state of the LCA method to analyze dynamic, emerging systems. In addition to this methodological advancement, results of this project may directly impact decisions pertaining to bioenergy development. Through this project, we will be able to 1) understand how the entire bioenergy supply chain will respond to different policy interventions, 2) provide decision support information for the development and deployment of biofuels and biomass electricity at national and state levels, 3) guide the biofuel and biomass electricity industries to advance technology development, and 4) educate the next generation of engineers and policy makers for understanding complex issues in the bioenergy system and obtaining multidisciplinary skills. The impacts of this research are potentiallly broader than providing critical information about switchgrass bioenergy development and its environmental impacts. The techniques established using a coupled agent-based model with LCA can be used for any developing system. The method developed in this research can address one of the key challenges of trying to predict the environmental impacts of a non-established system, adding dynamic components that assist in the understanding of developing complex adaptive systems and the aggregate effect of a technology change. The educational impact of this project includes integration of undergraduate and graduate courses and curricula. One PhD student will be trained working on cutting edge research on a topic of intense international interest. Master's students will see aspects of this research integrated into the curriculum of the Engineering Sustainable Systems dual degree program between the UM College of Engineering and School of Natural Resources and Environment. The project team will also participate in the UM UROP program which provides mentoring and research experiences for underrepresented minority undergraduate students. To broadly disseminate research results for educational purposes, the team will develop and submit relevant course modules to the Center for Sustainable Engineering's electronic library for peer review. The models developed in this project will be shared with the scientific community through the OpenABM Consortium.