Aggarwal S.,Energy Innovation Policy and Technology LLC |
Burgess E.,Arizona State University
Electricity Journal | Year: 2014
New pressures in the electricity sector have led some analysts to reexamine the traditional utility business model and the regulatory compact that supports it. Performance-based regulation is one possible alternative to traditional regulation that starts with the outcomes that matter to customers, utilities, and other industry participants. This article describes examples of performance-oriented regulation and draws regulatory design principles from them. © 2014 Elsevier Inc.
Busch C.,Energy Innovation Policy and Technology LLC |
Gimon E.,Energy Innovation Policy and Technology LLC
Electricity Journal | Year: 2014
This article analyzes the level of greenhouse gas emissions attributable to electricity from natural-gas-fired power plants and coal-fired power plants, then compares the two. An analytical framework is employed that considers the key greenhouse gases released during the production and combustion of coal and natural gas: carbon dioxide and methane. © 2014 Elsevier Inc.
Rissman J.,Energy Innovation Policy and Technology LLC |
Arunachalam S.,University of North Carolina at Chapel Hill |
Woody M.,University of North Carolina at Chapel Hill |
West J.J.,University of North Carolina at Chapel Hill |
And 2 more authors.
Atmospheric Chemistry and Physics | Year: 2013
This study examined the impacts of aircraft emissions during the landing and takeoff cycle on PM2.5 concentrations during the months of June and July 2002 at the Hartsfield-Jackson Atlanta International Airport. Primary and secondary pollutants were modeled using the Advanced Modeling System for Transport, Emissions, Reactions, and Deposition of Atmospheric Matter (AMSTERDAM). AMSTERDAM is a modified version of the Community Multiscale Air Quality (CMAQ) model that incorporates a plume-in-grid process to simulate emissions sources of interest at a finer scale than can be achieved using CMAQ's model grid. Three fundamental issues were investigated: the effects of aircraft on PM2.5 concentrations throughout northern Georgia, the differences resulting from use of AMSTERDAM's plume-in-grid process rather than a traditional CMAQ simulation, and the concentrations observed in aircraft plumes at subgrid scales. Comparison of model results with an air quality monitor located in the vicinity of the airport found that normalized mean bias ranges from-77.5% to 6.2% and normalized mean error ranges from 40.4% to 77.5%, varying by species. Aircraft influence average PM2.5 concentrations by up to 0.232 μg m -3 near the airport and by 0.001-0.007 μg m-3 throughout the Atlanta metro area. The plume-in-grid process increases concentrations of secondary PM pollutants by 0.005-0.020 μg m-3 (compared to the traditional grid-based treatment) but reduces the concentration of non-reactive primary PM pollutants by up to 0.010 μg m-3, with changes concentrated near the airport. Examination of subgrid-scale results indicates that median aircraft contribution to grid cells is higher than median puff concentration in the airport's grid cell and outside of a 20 km × 20 km square area centered on the airport, while in a 12 km × 12 km square ring centered on the airport, puffs have median concentrations over an order of magnitude higher than aircraft contribution to the grid cells. Maximum puff impacts are seen within the 12 km × 12 km ring, not in the airport's own grid cell, while maximum grid cell impacts occur within the airport's grid cell. Twenty-one (21)% of all aircraft-related puffs from the Atlanta airport have at least 0.1 μg m-3 PM2.5 concentrations. Near the airport, median daily puff concentrations vary between 0.017 and 0.134 μg m-3 (0.05 and 0.35 μg m-3 at ground level), while maximum daily puff concentrations vary between 6.1 and 42.1 μg m-3 (7.5 and 42.1 μg m-3 at ground level) during the 2-month period. In contrast, median daily aircraft contribution to grid concentrations varies between 0.015 and 0.091 μg m-3 (0.09 and 0.40 μg m-3 at ground level), while the maximum varies between 0.75 and 2.55 μg m-3 (0.75 and 2.0 μg m-3 at ground level). Future researchers may consider using a plume-in-grid process, such as the one used here, to understand the impacts of aircraft emissions at other airports, for proposed future airports, for airport expansion projects under various future scenarios, and for other national-scale studies specifically when the maximum impacts at fine scales are of interest. © Author(s) 2013. CC Attribution 3.0 License.