CAREER: Biochar Systems for Sustainable Applications in the Food-Energy-Water Nexus

职业：生物炭系统在食品-能源-水关系中的可持续应用

• 批准号: 2038439
• 负责人: Yuan Yao
• 金额: $ 51.94万
• 依托单位: Yale University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2038439&HistoricalAwards=false
• 关键词: CAREER; Biochar; Systems; Sustainable; Applications

Biochar is a carbon-rich solid byproduct of thermochemical biomass conversions. It has potential applications in food, energy, and water systems. This project aims to advance potential biochar applications by (1) using artificial intelligence (machine learning) approaches to predict process data and life cycle assessment (LCA) of various combinations of biomass feedstocks, conversion pathways, and applications of biochar; (2) building an integrated framework for modeling and analysis of biochar systems in the food-energy-water (FEW) nexus; and (3) demonstrating the framework through real-world case studies in different geographic, temporal, and socioeconomic contexts. The educational and outreach objectives include (1) attracting underrepresented students to STEM fields by developing a multimedia package for FEW and biochar sustainability; (2) developing both in-class and online courses and providing training and professional development opportunities to integrate research and education activities for undergraduate and graduate students; (3) developing an international network of scholars for FEW, biochar sustainability, and interdisciplinary research communities with a long-term goal of forming an international research and education program.This project targets bridging knowledge gaps for biochar production and effective applications in enhancing FEW sustainability by integrating LCA, technico-economic analysis (TEA), Geographic Information System (GIS), machine learning, and dynamic modeling. Understanding the impacts of using various biomass substrates for different biochar applications on the environment, economics, and communities will lay a foundation for the further design and implementation of large-scale biochar systems under different socioeconomic, climate change, and resource limiting conditions. Integration of advanced modeling tools including LCA, GIS, and machine learning that are commonly used in different disciplines is an important feature of the approach. Through integration of advanced modeling methods from engineering, environmental science, natural science, and data science, this project seeks to demonstrate how transdisciplinary research can create improved societal outcomes.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

生物炭是热化学生物质转化的一种富含碳的固体副产品。它在食品、能源和水系统中有潜在的应用。该项目旨在通过以下方式促进生物炭的潜在应用：(1)使用人工智能(机器学习)方法预测生物质原料、转化途径和生物炭应用的各种组合的过程数据和生命周期评估(LCA)；(2)建立一个在食品-能源-水(少数)关系中对生物炭系统进行建模和分析的综合框架；以及(3)通过在不同地理、时间和社会经济背景下的真实案例研究来展示该框架。教育和外联目标包括：(1)通过为少数人和生物碳可持续性开发多媒体包，吸引代表人数不足的学生进入STEM领域；(2)开发课堂和在线课程，并为本科生和研究生提供培训和专业发展机会，将研究和教育活动结合起来；(3)为生物碳生产、生物碳可持续性和跨学科研究社区建立一个国际学者网络，长期目标是形成一个国际研究和教育计划。该项目旨在通过整合生命周期评价、技术经济分析(TEA)、地理信息系统(GIS)、机器学习和动态建模，弥合生物碳生产方面的知识差距，并有效地应用于增强生物碳生产的可持续性。了解不同生物质基质用于不同生物炭应用对环境、经济和社区的影响，将为进一步设计和实施不同社会经济、气候变化和资源限制条件下的大规模生物炭系统奠定基础。该方法的一个重要特征是集成了不同学科中常用的高级建模工具，包括生命周期分析、地理信息系统和机器学习。通过整合工程学、环境科学、自然科学和数据科学的先进建模方法，该项目试图展示跨学科研究如何创造更好的社会结果。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Applications of artificial intelligence‐based modeling for bioenergy systems: A review

• DOI: 10.1111/gcbb.12816
• 发表时间: 2021-05
• 期刊: GCB Bioenergy
• 作者: Mochen Liao;Yuan Yao

Soil organic carbon change can reduce the climate benefits of biofuel produced from forest residues

• DOI: 10.1016/j.joule.2023.12.018
• 发表时间: 2024-01
• 期刊: Joule
• 影响因子: 39.8
• 作者: Kai Lan;Bingquan Zhang;Tessa Lee;Yuan Yao

Dynamic Life Cycle Assessment of Energy Technologies under Different Greenhouse Gas Concentration Pathways

不同温室气体浓度路径下能源技术的动态生命周期评估

• DOI: 10.1021/acs.est.1c05923
• 发表时间: 2022
• 期刊: Environmental Science & Technology
• 影响因子: 11.4
• 作者: Lan, Kai;Yao, Yuan
• 通讯作者: Yao, Yuan

Machine learning for sustainable development and applications of biomass and biomass-derived carbonaceous materials in water and agricultural systems: A review

• DOI: 10.1016/j.resconrec.2022.106847
• 发表时间: 2023-03
• 期刊: Resources, Conservation and Recycling
• 作者: H. Wang;Yuan Yao

An integrated techno-economic and environmental assessment for carbon capture in hydrogen production by biomass gasification

• DOI: 10.1016/j.resconrec.2022.106693
• 发表时间: 2023-01
• 期刊: Resources, Conservation and Recycling
• 作者: Na Wu;Kai Lan;Yuan Yao