Methodology for Assessing the Effects of Technological and Economic Changes on the Location, Timing and Ambient Air Quality Impacts of Power Sector EmissionsEPA Grant Number: R831836
Title: Methodology for Assessing the Effects of Technological and Economic Changes on the Location, Timing and Ambient Air Quality Impacts of Power Sector Emissions
Investigators: Ellis, Joseph H. , Burtraw, Dallas , Hobbs, Benjamin F. , Palmer, Karen
Institution: The Johns Hopkins University , Resources for the Future
EPA Project Officer: Chung, Serena
Project Period: February 1, 2005 through January 30, 2008 (Extended to January 30, 2009)
Project Amount: $648,733
RFA: Regional Development, Population Trend, and Technology Change Impacts on Future Air Pollution Emissions (2004) RFA Text | Recipients Lists
Research Category: Global Climate Change , Climate Change , Air
The purpose of the proposed work is to develop and demonstrate a methodology for creating geographically and temporally disaggregated emissions scenarios for the electric power sector on a multidecadal time-scale for use with the Models-3 Community Multiscale Air Quality Model (CMAQ) or other air quality model. The focus is on power generation for three reasons. First, this sector represents a large share of SOx, NOx, mercury and CO2 emissions in the US. Moreover, future shares are highly uncertain, depending upon technology change, fuel mix, electric load growth, regulation of the electricity sector and the evolution of environmental policy. Second, alternative scenarios concerning these key drivers can make huge differences in total emissions and their spatial and temporal distribution. Finally, emissions and associated ambient air concentrations are sensitive to the growth and distribution of electricity demands, which in turn are strongly linked to temperature and other climatic variables that may change significantly over the next few decades.
The sensitivity of the amounts, locations, and timing of power sector emissions to economic, demographic, and technological assumptions has two important implications. One is the need for a theoretically defensible, transparent and practical methodology for determining future temporal and spatial scenarios of emissions. This framework will be provided through the use of a sequence of models representing market-driven electricity supply and facility location constrained by land use and policy-based emissions limits. The Haiku model, developed by Resources for the Future, will be used to solve for regional technology, demand, and emissions totals and to disaggregate national totals (such as those that might result from IPCC scenarios) to regions. Finer-scaled regional models will then allocate specific generation facilities to the net96 national grid (comprised of 132 columns x 90 rows of 36x36 km cells) and will estimate their hourly emissions, using regional technology, energy, and emissions totals as boundary conditions.
The second implication is the need to test the robustness of emissions disaggregations to assumptions concerning electric load growth, technological change, and policies, such as emissions caps and regulatory reforms including time of day electricity pricing. We propose to systematically explore the sensitivity of both emissions and ambient air quality results to these uncertain drivers in order to assess which assumptions and model components matter most. Ambient air quality (tropospheric ozone and particulates) for an example set of scenarios will be simulated using MM5/MCIP/SMOKE/CMAQ. This will demonstrate the practicality of integrating the source disaggregation methodology with the SMOKE emissions processing system and subsequently, the CMAQ transport and fate model itself.
The results of this project with be scientifically credible modeling approaches that quantitatively lay out specific relationships between economic and population assumptions, power sector technology costs and efficiencies, locations of sources of air pollution, altered climate regimes the emissions thereby generated and associated ambient concentration fields for the entire U.S. .The methodology will be demonstrated for North America. The sensitivity of emissions and air quality results to key economic, technology, and demographic drivers will be assessed.