Interactions between overlapping air quality regulations can have unintended impacts on polluting activities. We document one such potentially important interaction. Local regulators in areas constrained by one type of regulation—e.g., threshold-based local air quality standards—are incentivized to permit more local pollution in response to a decline in emissions induced by another kind of regulation—e.g., rules targeting power plant emissions. We combine a state-of-the-art particle trajectory model, machine learning, and an econometric model of local air pollution exposure to quantify the relationship between sustained reductions in upwind power-plant emissions of pollution (PM2.5) precursors and downwind pollution levels. We use this integrated air quality modeling framework to test whether pollution levels in constrained counties appear to "rebound" when emissions from upwind pollution sources decline. We document evidence that is consistent with a local emissions rebound.