Effective emergency planning and response in the event of a hazardous chemical or biological material release in an urban area requires accurate definition of population exposure. Quantifying the complex plume dispersal in an urban environment is an important aspect in the accuracy of exposure assessments, but an equally important issue is the quantification of the population distribution underlying that plume. The definition of the exposed population is problematic because population is not static. The spatial distribution of population shifts throughout the day according to the work, shopping and mobility habits of urban citizens. Currently, the vast majority of available population datasets are based on residential populations with no accounting for daily migrations to workplaces or shopping zones. These residential population databases are most accurate for the purposes of exposure assessment when analysts can assume the majority of the population is in their homes. This assumption may be valid at night, but during the day it may be significantly inaccurate. Therefore, the use of these population data in population dosage and casualty estimates will produce considerable error for daytime release scenarios. In this research, we demonstrate a method for estimating urban daytime and nighttime population using US Census, infrastructure, and business demographic data in a GIS.