The optimization function that governs the dispatching of power generators to meet electricity demand minimizes the marginal cost of electricity generation without regard to the environmental or public health damages caused by power production. Although technologies exist for reducing the externalities resulting from electricity generation at power plants, current solutions typically raise the cost of power production or introduce operational challenges for the grid. This research quantifies the trade-offs and couplings between the cooling water, greenhouse gas emissions, and air quality impacts of different power generating technologies under business as usual market conditions, as well as a series of market-based interventions aimed to reduce the production of those externalities. Using publicly available data from the US Environmental Protection Agency (EPA) and the US Energy Information Administration (EIA) for power plant water use and emissions, a unit commitment and dispatch power market simulation model is modified to evaluate the production of environmental externalities from power production. Scenarios are developed to apply a set of fees for cooling water, carbon dioxide, nitrous oxide and sulfur oxide emissions, respectively. Trade-offs between environmental performance, overall generation costs, and shifts in the power plants dispatched to meet demand are quantified for each power market simulation. The results from this study will provide insight into the development of a novel market-based framework that modifies the optimization algorithms governing the dispatching of electricity onto the grid in efforts to achieve cost-effective improvements in its environmental performance without the need for new infrastructure investments.