SAI: Supporting Equitable Building Decarbonization

加强美国基础设施（SAI）是美国国家科学基金会的一个项目，旨在促进以人为本的基础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的创新，发展经济，创造就业机会，使公共部门提供的服务更有效率，加强社区，促进机会平等，保护自然环境，加强国家安全，并推动美国的领导地位。为了实现这些目标，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的基础设施的建设和维护能够改善生活和社会，并以技术和工程的进步为基础。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，住宅建筑消耗了21%的能源，而这种资源消耗给那些生活在服务水平低下的社区的居民带来了更大的负担，他们往往住在效率较低的住房里，将收入的很大一部分花在水电费上。改造住宅建筑以同时减少能源使用、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，而不是集中在受影响社区的观点和经验上。SAI研究项目通过建立社区参与流程和综合建模平台来满足这一需求，帮助服务不足社区的居民识别、规划和实施脱碳改造。通过将跨学科研究团队与当地社区合作，该项目将科学数据民主化，以满足社区需求，旨在提高公众对建筑脱碳的认识和代理。脱碳改造通常使用建筑能源模型进行评估。这些模型提供了丰富的信息，主要供建筑设计师使用，但这些信息对公众也有巨大的潜在价值。该项目将社区参与、参与式的心理学研究方法与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测试平台，该平台将俄亥俄州辛辛那提市正在翻新的独户住宅的居民作为主要利益相关者和共同开发伙伴。首先通过调查、焦点小组和建筑能源审计确定服务不足社区建筑脱碳的社会心理和技术需求以及障碍。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。然后，这个建模平台被用于社区研讨会，以检查它如何能够加强当地机构、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式，使公众参与科学模型和数据，可用于帮助其他地区的社区驱动的脱碳规划。该奖项由社会、行为和经济（SBE）科学理事会、工程理事会和数学和物理科学理事会支持。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识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.