Activity-based travel demand models can be useful tools for understanding the individual level equity impacts of regional transportation plans, because of their ability to generate transportation measures at disaggregate (individual and household) levels. There are numerous population and environmental (transportation and land-use) factors that together shape the transportation equity outcomes for individuals. In a real world setting, for example, one’s income level, age, gender, ethnicity, residential location, work location, and access to various travel modes all play key roles in determining how one is affected by the transportation system. In such a complex system where numerous population, land-use, and transportation factors are at play, the influence of these factors on distributional outcomes can seem impossible to disentangle. In this presentation, I will discuss the usefulness of decomposing transportation equity outcomes using a set of distributional comparisons and scenario analyses. This demonstration uses the 2000 Bay Area Travel Survey and (activity-based) mode choice model. The findings show that activity based models in conjunction with distributional comparisons are capable of revealing the population and environmental factors that result in clear “winners and losers” due to transportation changes.