SAI: Supporting Equitable Building Decarbonization

加强美国基础设施(SAI)是一项NSF计划，旨在刺激以人类为中心的基础性研究和潜在的变革性研究，以加强美国的基础设施。有效的基础设施为社会经济活力和广泛的生活质量改善提供了坚实的基础。强大、可靠和有效的基础设施刺激私营部门创新，增长经济，创造就业机会，提高公共部门服务提供效率，加强社区力量，促进机会均等，保护自然环境，增强国家安全，推动美国的领导地位。要实现这些目标，需要来自科学和工程学科的专业知识。SAI侧重于人类推理和决策、治理以及社会和文化过程的知识如何使有效基础设施的建设和维护能够改善生活和社会，并建立在技术和工程进步的基础上。减少家庭碳排放对于实现美国的气候目标至关重要。它还可以在减少社会不平等方面发挥关键作用。在美国，住宅建筑占能源消耗的21%，这种资源使用给服务不足社区的居民带来了更大的负担，他们经常住在效率较低的住房中，并将收入的更高比例花在水电费上。改造住宅建筑以同时减少能源消耗、降低碳排放和解决能源不平等问题，不仅是一项工程任务，也是一项社会挑战。然而，目前大多数关于建筑脱碳的研究都集中在技术解决方案上，而不是以受影响社区的视角和经验为中心。该SAI研究项目通过建立社区参与流程和集成建模平台来满足这一需求，以帮助服务不足社区的居民识别、规划和实施脱碳改造。通过与当地社区合作，将跨学科研究团队聚集在一起，该项目将满足社区需求的科学数据民主化，旨在提高公众对建筑脱碳的认识和机构。脱碳改造通常使用建筑能源模型进行评估。这些模型提供了大量的信息，主要供建筑设计师使用，但这些信息对公众也具有巨大的潜在价值。该项目将心理学中的社区参与、参与式研究方法与工程学中的建筑能源建模工具相结合，以支持公平的脱碳。该项目的一个核心组成部分是其示范试验台，它让俄亥俄州辛辛那提目前正在翻新的独栋住宅的居民成为主要利益相关者和共同开发合作伙伴。通过调查、焦点小组和建筑能源审计，首先确定了在服务不足的社区中建筑脱碳的心理和技术需求以及障碍，并共同结合背景进行了分析。与社区合作开发了一个创新的建筑能源建模平台，以预测家庭碳排放并了解改造成本和收益。这一建模平台随后被用于社区研讨会，以检查它如何加强地方机构、决策和围绕脱碳的行动。该项目的一个关键成果是其可复制的模型，为公众提供科学模型和数据，可用于帮助其他地方的社区驱动的脱碳规划。该奖项得到了社会、行为和经济委员会(SBE)、工程委员会和数学和物理科学委员会的支持。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

Strengthening American Infrastructure (SAI) is an NSF Program seeking to stimulate human-centered fundamental and potentially transformative research that strengthens America’s infrastructure. Effective infrastructure provides a strong foundation for socioeconomic vitality and broad quality of life improvement. Strong, reliable, and effective infrastructure spurs private-sector innovation, grows the economy, creates jobs, makes public-sector service provision more efficient, strengthens communities, promotes equal opportunity, protects the natural environment, enhances national security, and fuels American leadership. To achieve these goals requires expertise from across the science and engineering disciplines. SAI focuses on how knowledge of human reasoning and decision-making, governance, and social and cultural processes enables the building and maintenance of effective infrastructure that improves lives and society and builds on advances in technology and engineering.Reducing carbon emissions from homes is essential for meeting U.S. climate targets. It can also play a critical role in reducing social inequalities. Residential buildings are responsible for 21% of energy use in the U.S., and this resource use places greater burdens on residents in underserved communities who often live in less efficient housing and spend a higher proportion of their income on utility bills. Retrofitting residential buildings to simultaneously reduce energy use, lower carbon emissions, and address energy inequality is not only an engineering task but also a social challenge. However, most current research on building decarbonization focuses on technological solutions and does not center the perspectives and experiences of impacted communities. This SAI research project meets this need by establishing a community-engaged process and integrated modeling platform to help residents in underserved communities identify, plan, and implement decarbonization retrofits. By bringing together an interdisciplinary research team in partnership with the local community, this project democratizes scientific data for community needs and aims to advance public awareness and agency around building decarbonization.Decarbonization retrofits are typically evaluated using building energy models. These models provide a wealth of information that is used mainly by building designers, but this information also has enormous potential value to the public. This project integrates community-engaged, participatory research methods from psychology with building energy modeling tools from engineering to support equitable decarbonization. A core component of this project is its demonstration testbed, which engages residents in single-family homes currently under renovation in Cincinnati, Ohio as primary stakeholders and co-development partners. The psychosocial and technical needs for and barriers to building decarbonization in underserved communities are first identified and jointly contextualized through surveys, focus groups, and building energy audits. An innovative building energy modeling platform is developed in collaboration with the community to predict household carbon emissions and to understand retrofit costs and benefits. This modeling platform is then used in community workshops to examine how it can enhance local agency, decision-making, and action around decarbonization. A key outcome of this project is its replicable model for engaging the public with scientific models and data, which can be used to aid community-driven decarbonization planning in other locations.This award is supported by the Directorate for Social, Behavioral, and Economic (SBE) Sciences, the Directorate for Engineering, and the Directorate for Mathematical and Physical Sciences.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.