World Library  

Add to Book Shelf
Flag as Inappropriate
Email this Book

Esp V2.0: Enhanced Method for Exploring Emission Impacts of Future Scenarios in the United States – Addressing Spatial Allocation : Volume 8, Issue 1 (13/01/2015)

By Ran, L.

Click here to view

Book Id: WPLBN0004009847
Format Type: PDF Article :
File Size: Pages 38
Reproduction Date: 2015

Title: Esp V2.0: Enhanced Method for Exploring Emission Impacts of Future Scenarios in the United States – Addressing Spatial Allocation : Volume 8, Issue 1 (13/01/2015)  
Author: Ran, L.
Volume: Vol. 8, Issue 1
Language: English
Subject: Science, Geoscientific, Model
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


APA MLA Chicago

Loughlin, D. H., Yang, D., Adelman, Z., Nolte, C. G., Baek, B. H., & Ran, L. (2015). Esp V2.0: Enhanced Method for Exploring Emission Impacts of Future Scenarios in the United States – Addressing Spatial Allocation : Volume 8, Issue 1 (13/01/2015). Retrieved from

Description: University of North Carolina at Chapel Hill, Institute for the Environment, 100 Europa Dr., Chapel Hill, NC 27517, USA. The Emission Scenario Projection (ESP) method produces future-year air pollutant emissions for mesoscale air quality modeling applications. We present ESP v2.0, which expands upon ESP v1.0 by spatially allocating future-year emissions to account for projected population and land use changes. In ESP v2.0, US Census Division-level emission growth factors are developed using an energy system model. Regional factors for population-related emissions are spatially disaggregated to the county level using population growth and migration projections. The county-level growth factors are then applied to grow a base-year emission inventory to the future. Spatial surrogates are updated to account for future population and land use changes, and these surrogates are used to map projected county-level emissions to a modeling grid for use within an air quality model. We evaluate ESP v2.0 by comparing US 12 km emissions for 2005 with projections for 2050. We also evaluate the individual and combined effects of county-level disaggregation and of updating spatial surrogates. Results suggest that the common practice of modeling future emissions without considering spatial redistribution over-predicts emissions in the urban core and under-predicts emissions in suburban and exurban areas. In addition to improving multi-decadal emission projections, a strength of ESP v2.0 is that it can be applied to assess the emissions and air quality implications of alternative energy, population and land use scenarios.

ESP v2.0: enhanced method for exploring emission impacts of future scenarios in the United States – addressing spatial allocation

Akhtar, F., Pinder, R. Loughlin, D., and Henze, D.: GLIMPSE: a rapid decision framework for energy and environmental policy, Environ. Sci. Technol., 47, 12011–12019, doi:10.1021/es402283j, 2013.; Avise, J., Chen, J., Lamb, B., Wiedinmyer, C., Guenther, A., Salathé, E., and Mass, C.: Attribution of projected changes in summertime US ozone and PM2.5 concentrations to global changes, Atmos. Chem. Phys., 9, 1111–1124, doi:10.5194/acp-9-1111-2009, 2009.; Avise, J., Gonzalez-Abraham, R., Chung, S. H. Chen, J., Lamb, B., Salathé, E. P., Zhang, Y., Nolte, C. G., Loughlin, D. H., Guenther, A., Wiedinmyer, C., and Duhl, T.: Evaluating the effects of climate change on summertime ozone using a relative response factor approach for policymakers, J. Air Waste Manage., 62, 1061–1074, 2012.; Bierwagen, B. G., Theobald, D. M., Pyke, C. R., Choate, A., Groth, P., Thomas, J. V., and Morefield, P.: National housing and impervious surface scenarios for integrated climate impact assessments, P. Natl. Acad. Sci. USA, 107, 20887–20892, 2010.; Byun, D. and Schere, K.: Review of the governing equations, computational algorithms, and other components of the Models-3 Community Multiscale Air Quality (CMAQ) modeling system, Appl. Mech. Rev., 59, 51–77, doi:10.1115/1.2128636, 2006.; Fishbone, L. G. and Abilock, H.: MARKAL: a linear programming model for energy-systems analysis: technical description of the BNL version, Journal of Energy Research, 5, 353–375, 1981.; Hogrefe, C., Lynn, B., Civerolo, K., Ku, K.-Y., Rosenthal, J., Rosenzweig, C., Goldberg, R., Gaffin, S., Knowlton, K., and Kinney, L.: Simulating changes in regional air pollution over the eastern United States due to changes in global and regional climate and emissions, J. Geophys. Res., 109, D22301, doi:10.1029/2004JD004690, 2004.; Houyoux, M. R., Vukovich, J. M., Coats, C. J., Wheeler, N. J., and Kasibhatla, P. S.: Emission inventory development and processing for the Seasonal Model for Regional Air Quality (SMRAQ) project, J. Geophys. Res.-Atmos., 105, 9079–9090, 2000.; Houyoux, M. R., Strum, M., Mason, R., and Eyth, A.: Data management using the emissions modeling framework, in: Proceedings of the Fifteenth International Emission Inventory Conference, 2006.; IPCC 2000, Intergovernmental Panel on Climate Change (IPCC): Special Report on Emissions Scenarios, edited by: Nakicenovic, N. and Swart, R., Cambridge Univ. Press, New York, 612 pp., 2000.; Loughlin, D. H., Benjey, W. G., and Nolte, C. G.: ESP v1.0: methodology for exploring emission impacts of future scenarios in the United States, Geosci. Model Dev., 4, 287–297, doi:10.5194/gmd-4-287-2011, 2011.; Loulou, R., Goldstein, G., and Noble, K.: Documentation for the MARKAL family of models, available at: h (last access: December 2014), 389 pp., 2004.; Morris, R. E., Koo, B., Guenther, A., Yarwood, G., McNally, D., Tesche, T. W., and Brewer, P.: Model sensitivity evaluation for organic carbon using two multi-pollutant air quality models that simulate regional haze in the southeastern United States, Atmos. Environ., 40, 4960–4972, 2006.; Nolte, C. G., Gilliland, A. B., Hogrefe, C., and Mickley, L. J.: Linking global to regional models to assess future climate impacts on surface ozone levels in the United States, J. Geophys. Res.-Atmos., 113, D14307, doi:10.1029/2007JD008497, 2008.; Post, E. S., Grambsch, A., Weaver, C., Morefield, P., Huang, J., Leung, L.-Y., Nolte, C. G., Adams, P., Liang, X.-Z., Zhu, J.-H., and Mahoney, H.: Variation in estimated ozone-related health impac


Click To View

Additional Books

  • Clm4-betr, a Generic Biogeochemical Tran... (by )
  • Multi-model Ensemble: Technique and Vali... (by )
  • Using Model Reduction to Predict the Soi... (by )
  • A Simplified Treatment of Surfactant Eff... (by )
  • Adding a Dynamical Cryosphere Into ILove... (by )
  • The Csiro Mk3L Climate System Model V1.0... (by )
  • The Coupled Atmosphere–chemistry–ocean M... (by )
  • Tropical Troposphere to Stratosphere Tra... (by )
  • Simulation of Variability in Atmospheric... (by )
  • A Statistical Downscaling Method for Dai... (by )
  • A Description of the Famous (Version Xdb... (by )
  • Orchidee-src V1.0: an Extension of the L... (by )
Scroll Left
Scroll Right


Copyright © World Library Foundation. All rights reserved. eBooks from World eBook Library are sponsored by the World Library Foundation,
a 501c(4) Member's Support Non-Profit Organization, and is NOT affiliated with any governmental agency or department.