Dynamic pricing is a trendy term that can be found in a variety of industries. In the utilities industry, the implementation of dynamic pricing structure is an economic stimulus to encourage demand reduction of electricity usage in peak hours, when the power system is strained and the cost of electric power is very high. This study investigated the rate structure of day-ahead hourly pricing programs in New York State, and evaluated the demand and emissions impacts of dynamic pricing programs in the summer of 2008. Different scenarios of dynamic pricing programs are modeled to evaluate the demand and emissions change for NOx and SO2 emissions in peak hours, as well as in off-peak hours. Three methods are proposed to evaluate NOx emission reduction in New York State. Hourly emissions changes from power production in the NPCC power system model are scaled to emissions in the National Emissions Inventory (NEI), in order to simulate potential emissions changes in historical days caused by dynamic pricing. The NEI and the simulated emissions are used as point source emissions input into Sparse Matrix Operator Kernel Emissions (SMOKE) modeling system. The processed emissions change from SMOKE is visualized using Visualization Environment for Rich Data Interpretation (VERDI). Results show that dynamic pricing programs can result in considerable emissions reduction in peak hours, while inducing a slight increase in off-peak hours. The i emissions reduction will have non-negligible environmental and social impacts for the New York State, especially for the metropolitan areas like New York City. ii