Abstract
<jats:p>Air quality policy increasingly seeks to reduce both population exposure and exposure disparities. For emissions-control policy, this requires identifying which sources, sectors, and locations have the greatest benefit per unit emissions. Here we develop a source-oriented accounting framework that links exposure and disparity metrics to the emissions sources that drive them. Applied to fine particulate matter (PM2.5) in California, the framework separates emissions magnitude, populationweighted exposure influence, and disparity yield, allowing us to identify sources that matter most for exposure, disparity, or both. We find that industrial and transportation sources have disproportionately large impacts on population exposure and statewide racial/ethnic disparities relative to their emissions shares. Geographically, source locations in densely populated parts of the Greater Los Angeles Basin have especially high leverage for reducing statewide disparities. More broadly, we show that exposure reduction and disparity reduction are distinct targeting problems. All modeled emissions reductions lower population exposure, but only some reduce racial/ethnic disparities; whether a control improves distributional equity depends on where its exposure benefits accrue and which populations receive them. This framework provides a transparent basis for designing emissions-control strategies that deliver public health gains while advancing exposure equity.</jats:p>