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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. [ABSTRACT FROM AUTHOR]

As scientists seek to better understand the linkages between energy, water, and land systems, they confront a critical question of scale for their analysis. Many studies exploring this nexus restrict themselves to a small area in order to capture fine-scale processes, whereas other studies focus on interactions between energy, water, and land over broader domains but apply coarse resolution methods. Detailed studies of a narrow domain can be misleading if the policy intervention considered is broad-based and has impacts on energy, land, and agricultural markets. Regional studies with aggregate low-resolution representations may miss critical feedbacks driven by the dynamic interactions between subsystems. This study applies a novel, gridded energy-land-water modeling system to analyze the local environmental impacts of biomass cofiring of coal power plants across the upper MISO region. We use this framework to examine the impacts of a hypothetical biomass cofiring technology mandate of coal-fired power plants using corn residues. We find that this scenario has a significant impact on land allocation, fertilizer applications, and nitrogen leaching. The effects also impact regions not involved in cofiring through agricultural markets. Further, some MISO coal-fired plants would cease generation because the competition for biomass increases the cost of this feedstock and because the higher operating costs of cofiring renders them uncompetitive with other generation sources. These factors are not captured by analyses undertaken at the level of an individual power plant. We also show that a region-wide analysis of this cofiring mandate would have registered only a modest increase in nitrate leaching (just +5% across the upper MISO region). Such aggregate analyses would have obscured the extremely large increases in leaching at particular locations, as much as +60%. Many of these locations are already pollution hotspots. Fine-scale analysis, nested within a broader framework, is necessary to capture these critical environmental interactions within the energy, land, and water nexus.

Cap and trade programs have historically been designed to achieve annual or seasonal reductions in emissions of nitrogen oxides and sulfur dioxide from power plants. Emissions reductions may not be temporally coincident with meteorological conditions conducive to the formation of peak ozone and fine particulate matter concentrations. Integrated power system and air quality modeling methods were developed to evaluate time-differentiated emissions price signals on high ozone days in the Mid-Atlantic portion of the Pennsylvania-New Jersey-Maryland (PJM) Interconnection and Electric Reliability Council of Texas (ERCOT) grids. Sufficient flexibility exists in the two grids with marked differences in demand and fuel generation mix to accommodate time-differentiated emissions pricing alone or in combination with a season-wide program. System-wide emissions reductions and production costs from time-differentiated pricing are shown to be competitive with those of a season-wide program on high ozone days and would be more cost-effective if the primary policy goal was to target emissions reductions on these days. Time-differentiated pricing layered as a complement to the Cross-State Air Pollution Rule had particularly pronounced benefits for the Mid-Atlantic PJM system that relies heavily on coal-fired generation. Time-differentiated pricing aimed at reducing ozone concentrations had particulate matter reduction co-benefits, but if particulate matter reductions are the primary objective, other approaches to time-differentiated pricing may lead to greater benefits.

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 NO(x) emissions from electric generating units. Results from a model of day-specific NO(x) 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 NO(x) 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.