Flexible NOx abatement from power plants in the eastern United States
SUN, Lin; WEBSTER, Mort; MCGAUGHEY, Gary; MCDONALD-BULLER, Elena C.; THOMPSON, Tammy; PRINN, Ronald; ELLERMAN, A. Denny; ALLEN, David T.
Title: Flexible NOx abatement from power plants in the eastern United States
Author: SUN, Lin; WEBSTER, Mort; MCGAUGHEY, Gary; MCDONALD-BULLER, Elena C.; THOMPSON, Tammy; PRINN, Ronald; ELLERMAN, A. Denny; ALLEN, David T.
Citation: Environmental science & technology, 2012, Vol. 46, No. 10, pp. 5607–5615
Series/Number: [Climate Policy Research Unit]
ISSN: 0013-936X; 1520-5851
Emission controls that provide incentives for maximizing reductions in emissions of ozone precursors on days when ozone concentrations are highest have the potential to be cost-effective ozone management strategies. Conventional prescriptive emissions controls or cap-and-trade programs consider all emissions similarly regardless of when they occur, despite the fact that contributions to ozone formation may vary. In contrast, a time-differentiated approach targets emissions reductions on forecasted high ozone days without imposition of additional costs on lower ozone days. This work examines simulations of such dynamic air quality management strategies for NOx emissions from electric generating units. Results from a model of day-specific NOx pricing applied to the Pennsylvania–New Jersey–Maryland (PJM) portion of the northeastern U.S. electrical grid demonstrate (i) that sufficient flexibility in electricity generation is available to allow power production to be switched from high to low NOx emitting facilities, (ii) that the emission price required to induce EGUs to change their strategies for power generation are competitive with other control costs, (iii) that dispatching strategies, which can change the spatial and temporal distribution of emissions, lead to ozone concentration reductions comparable to other control technologies, and (iv) that air quality forecasting is sufficiently accurate to allow EGUs to adapt their power generation strategies.
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