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SBIR Phase I: A Decision-Support Tool for Identifying Carbon Dioxide (CO2) Capture Opportunities for the Nation’s Energy Transition

SBIR Phase I: A Decision-Support Tool for Identifying Carbon Dioxide (CO2) Capture Opportunities for the Nation’s Energy Transition
SBIR 第一阶段:用于识别二氧化碳 (CO2) 捕获国家能源转型机会的决策支持工具
批准号:
2216541
负责人:
Jeffrey Bennett
金额:
$27.5万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2023
资助国家:
美国
项目状态:
已结题
起止时间:
2023-02-15 至 2024-01-31

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中文摘要
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英文摘要
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is in providing much-needed decision-support tool to progress the United States towards a net-zero carbon dioxide (CO2) emissions economy. The Princeton Net Zero America study suggests that a of minimum 0.9 gigatons /year of CO2 sequestration is required to transition the country to a net-zero economy, which is 1.3 times larger than the country’s oil production on a volume-equivalent basis. One of the many substantial challenges to achieving this feat is identifying and profiling capturable CO2 streams from emitters across the United States. Software that could robustly address this challenge would provide benefits to society and the country. For example, climate change is recognized as the largest threat facing humanity and the security of the United States; Transitioning the US economy to net-zero CO2 emissions is one of the largest wealth creation opportunities of our generation. The proposed CO2 National Capture Opportunities and Readiness Data software will enable users to identify sources of CO2 (e.g., cement manufacturers and ethanol refineries) that could be profitably turned into carbon capture and sequestration (CCS) projects. The database would provide the break-even CO2 capture cost, technology readiness level (TRL), and lifecycle CO2 emissions of any prospective CCS project across the country by integrating the latest public data and scientific research into a single end-user platform. A novel integration of advances in multiple disciplines is required for successful project completion: 1) big data fusion, 2) CO2 capture stream characterization, 3) lifecycle assessment, 4) advanced techno-economic assessments, and 5) software engineering. Additionally, this project will also advance the status-quo by creating dynamic results that can be easily re-generated as needed (e.g., with new technologies deployed or policies enacted).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.
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Quantitative Reasoning and Mathematical Skills: A Prototype Course in Mathematical, Scientific, and Technological Literacy
  • 批准号:
    9150560
  • 项目类别:
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  • 资助金额:
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  • 财政年份:
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  • 负责人:
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国内基金
海外基金
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基于数字增强干涉的Phase-OTDR高灵敏度定量测量技术研究