Linking Data with Decision-Making

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Abstract

Air qualiity managers have long relied on atmospheric chemistry measurements and models to support decision-making. Today an even wider audience of policy, planning, and advocacy organizations are interested in air quality and climate data. By collaborating with these new communities, especially energy, health, and environmental justice. scientists can expand the impact of existing knowledge, data, and tools. The evolution of satellite data for air quality and health applications highlights these opportunities, with lessons learned over the past 10 years through iniatives of the NASA Applied Sciences Program. Atmospheric models play an important role interpretting satellite data, connecting emissions and impacts, and answering “what if?” questions relevant to policy and planning. Advanced regional models, including the EPA Community Multiscale Air Quality (CMAQ) model, are well-suited to policy applications, but may not be appropriate for all user needs. Simpler, reduced-form models, including COBRA, InMAP, and AERMOD, complement complex models to support a wider range of partners and problems. Traditional scientific frameworks are evolving to better support engagement and to expand the benefits of science to new issues and communities. Still, challenges remain, especially for early-career scientists balancing academic milestones with “real-world” engagement and societal impact.