Several recent studies have used simulation models to quantify the potential effects of recent environmental regulations on power plants, including the Mercury and Air Toxics Standards (MATS), one of the US Environmental Protection Agency’s most expensive regulations. These studies have produced inconsistent results about the effects on the industry, making general conclusions difficult. We attempt to reconcile these differences by representing the variety of assumptions in these studies within a common modeling platform. We find that the assumptions, and their differences from the way MATS will be implemented, make a substantial impact on projected retirement of coal-fired capacity and generation, investments that are required, and emissions reductions. Almost uniformly, the actual regulation, when examined in its final form and in isolation, provides more flexibility than is represented in most models. We find this leads to a smaller impact on the composition of the electricity generating fleet than most studies have predicted.
The release of the US Environmental Protection Agency’s (EPA) Mercury and Air Toxics Standards (MATS) has sparked debate about how the electricity industry will respond. Will coal plants retire in large numbers? Will natural gas generation expand? New research suggests that the economic impacts of MATS may be less than previously estimated.
Several studies have used economic models to predict the effects of MATS, which aims to curb the emissions of mercury and other toxic air pollutants from power plants. But the results from these models vary widely. The range of predictions has contributed to a sense of uncertainty about how MATS will change the electricity sector.
In a new RFF discussion paper, “Mercury and Air Toxics Standards Analysis Deconstructed: Changing Assumptions, Changing Results,” authors Blair Beasley, Matt Woerman, Anthony Paul, Dallas Burtraw, and Karen Palmer help to reconcile the differences among nine studies that analyzed the impacts of MATS. The authors break down the key assumptions made by the studies’ modeling teams and highlight the impact of these assumptions by representing them within a common modeling platform, RFF’s Haiku electricity market model.
The authors find that when modeling assumptions closely mirror the actual requirements and flexibilities of the final MATS rule, the predicted impact on the electricity sector is less severe. They write that “In particular, the way researchers modeled the acid gas requirements under MATS had a large impact on the forecasted amount of coal-fired capacity and generation going forward, as well as the pollution controls that would be installed at these units and their emissions of acid gases.”