Society faces the need to overhaul energy and transportation systems to meet climate change and other challenges. These decisions typically have very large “co-benefits” in terms of air quality improvements. Over the past decades, engineers have developed detailed three-dimensional chemical transport models (CTMs) that predict ambient air pollution concentrations from emissions, atmospheric transport, and known chemical processes. These CTMs have been used by the US EPA for regulatory planning but are generally too unwieldy and computationally demanding for many systems-level planning purposes, especially ones where rapid screening or uncertainty analysis are required. Although several reduced-form tools have been developed, these are either based on very simple air quality models or lack seasonal and spatial detail in their results. This seminar will present recent results from our group that derives air pollution impact metrics with seasonal and spatial resolution using a state-of-the-art CTM.