Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 5.154 IF 5.154
  • IF 5-year value: 5.697 IF 5-year
    5.697
  • CiteScore value: 5.56 CiteScore
    5.56
  • SNIP value: 1.761 SNIP 1.761
  • IPP value: 5.30 IPP 5.30
  • SJR value: 3.164 SJR 3.164
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 59 Scimago H
    index 59
  • h5-index value: 49 h5-index 49
Volume 8, issue 6
Geosci. Model Dev., 8, 1775-1787, 2015
https://doi.org/10.5194/gmd-8-1775-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 8, 1775-1787, 2015
https://doi.org/10.5194/gmd-8-1775-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Model description paper 17 Jun 2015

Model description paper | 17 Jun 2015

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

L. Ran1, D. H. Loughlin2, D. Yang1, Z. Adelman1, B. H. Baek1, and C. G. Nolte2 L. Ran et al.
  • 1University of North Carolina at Chapel Hill, Institute for the Environment, 100 Europa Dr., Chapel Hill, NC 27517, USA
  • 2US Environmental Protection Agency, Office of Research and Development, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, USA

Abstract. 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 non-power sector 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.

Publications Copernicus
Download
Short summary
We present and demonstrate Version 2.0 of the Emission Scenario Projection (ESP) method. This method produces multi-decadal air pollutant emission projections suitable for air quality modeling. The method focuses on energy-related emissions, including those from the electric sector, buildings, industry and transportation. ESP v2.0 enhances ESP v1.0 by taking population growth, migration and land use change into consideration.
We present and demonstrate Version 2.0 of the Emission Scenario Projection (ESP) method. This...
Citation
Share