Economic activity across sectors can impact human health through multiple exposure pathways. Many health risks are well-documented, for example, the risk of air pollution on health outcomes across the lifespan. Major policies, however, continue to emerge without a full consideration of their health implications. Lacking is an understanding of how policy decision making (outside of the health sector) can have specific and measurable public health implications. To fill this gap, our proposed Center for Health, Energy, and Environmental Research (CHEER) will catalyze rigorous, innovative, community-driven, policy-relevant, transdisciplinary research. Our overarching aim is to better understand the positive and negative health impacts of cross-sector policy choices across energy, transportation, land use, and infrastructure. Achieving this goal requires engagement across community, scientific, and policy sectors. We posit that a truly community engaged approach to decision-making will increase both the efficacy and durability associated with specific policy solution pathways proposed with human health in mind. Our key innovation is in developing and employing a linked pathway that starts and ends with communities while it generates robust estimates of the health impacts of contemplated cross-sector policies. Innovations in community engagement will include: participatory web-based technologies, including web-based mapping and storytelling, crowd-sourcing and artificial intelligence, and utilization of low-cost air pollution monitors, which are increasingly being used by citizen scientists and communities. Innovations coming from our primary research project will include development of a new, high-resolution Scenario Health Risk for Energy model to support decision-making by policy makers and community partners, balancing representation of complex processes with the speed and ease-of-use required for public utilization. We also will conduct a Pilot Target Trial to assess the likely impacts of variable air pollution scenarios on asthma burden of Milwaukee public school children. The proposed Data Science Core will prioritize authentic, multi-directional, equitable community engagement and data sharing. Innovations will stem from: Establishing a Data Repository that will foster team science and provide a single point of access for all stakeholders; creating a Data Commons that provides linkage, integration, mapping, metadata management, and computerized routines for reusable data, metadata, and software artifacts for collaborative research and data sharing; and Providing Digital Engagement tools using advanced technologies (e.g., natural language processing) to ensure that community voices are utilized efficiently to inform research and policy development. Our Wisconsin-based community, government, and university environments have the track record, expertise, foundations, and institutional support for high productivity and policy impact of this Cente...