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

1132581(徐)。这个项目有两个主要目标。首先，将开发一个基于空间显式代理的LCA框架，通过克服在动态和不断发展的供应链中分析新兴技术所涉及的问题，来改进标准的LCA建模技术。这一目标的实现将推动生命周期分析方法的发展，并为环境可持续性分析提供一个新的工具。其次，这种改进的LCA建模框架将应用于美国柳枝稷生物能源系统（生物燃料和生物质电力），以检查各种政策情景下的未来供应链动态和进化，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路线图，以实现生物能源发展目标，同时满足市场需求并尽量减少对环境的影响。提出的基于空间显式代理的LCA建模框架将传统的LCA建模与基于代理的建模技术相结合，以允许环境干预数据库与供应链的动态和演变之间的反馈。通过结合地理空间数据和工具，该模型将具有空间显式。拟议的框架解决了LCA社区在生物能源LCA和一般LCA方法中确定的一些重大挑战，并且将普遍适用于生物能源案例研究以外的其他系统。该项目的成功将改善LCA方法分析动态新兴系统的状态。除了这种方法上的进步，这个项目的结果可能直接影响有关生物能源发展的决策。通过这个项目，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)为国家和州一级生物燃料和生物质电力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电力行业推进技术发展。4)教育下一代工程师和政策制定者理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。使用基于耦合代理的模型和LCA建立的技术可以用于任何开发系统。本研究中开发的方法可以解决试图预测未建立系统的环境影响的关键挑战之一，增加有助于理解开发复杂适应性系统和技术变化的总体效应的动态组件。该项目的教育影响包括本科和研究生课程的整合。一名博士生将接受培训，从事国际关注的前沿研究。硕士生将看到这项研究的各个方面被整合到澳大工程学院和自然资源与环境学院的工程可持续系统双学位课程的课程中。项目团队还将参加UM UROP计划，该计划为未被充分代表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，以达到教育目的，该团队将开发并将相关课程模块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.