Many environmental policies have clear public health impacts and are designed to improve health outcomes either by reducing the environmental health risks individuals encounter in their daily lives, or by encouraging more healthy lifestyles. One way of testing the effectiveness of these policies is to examine the behavioral changes they induce. In this dissertation, I use the American Time Use Survey (ATUS) to estimate behavioral responses to several environmental policies by examining how individuals shift the amount of time they spend in various activities during the day. The ATUS is a nationally representative, federally administered survey on time use in the United States. The survey collects information on all activities performed by respondents during a designated 24-hour period. It was first administered in 2003 and has continued throughout every year since, allowing me to collect responses for an 8-year period, 2003-2010. Because each respondent provides detailed information on his/her activities during the designated 24-hour period, I am able to determine how much time each person spends in various morning, afternoon and, evening activities that may be affected by the policies of interest. Although the ATUS has been in existence for 9 years, it has been under utilized in the economic literature. Researchers have traditionally focused primarily on the budget constraint faced by individuals and households, ignoring the time constraint. Examining how time use is affected by exogenous policy changes has the potential to shed light on many economic questions. For example, the literature has found that as gas prices increase consumption decreases, however; at a very inelastic rate. Analysis of time-use data could add to these findings by examining what behaviors are most affected. Do the higher prices cause individuals to carpool or take public transit to work, or do they contribute to fewer recreational excursions? Do the higher prices make commutes longer or shorter? Does this affect the amount of time spent working during the day? Time use data sets . . .