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Gridded estimates of CO2 emissions: uncertainty as a function of grid size

  • S. Hogue
  • D. Roten
  • E. Marland
  • G. MarlandEmail author
  • T. A. Boden
Original Article

Abstract

A crucial aspect of constructing a gridded model of anthropogenic fossil fuel CO2 (FFCO2) emissions involves careful consideration of uncertainty. Both the spatial resolution of the emissions estimates (grid scale) and the selection of proxy data to represent the spatial distribution of emissions, plus the quality of data on point sources of emissions, have important impacts on uncertainty. In earlier papers, we explored the uncertainties associated with grid selection and the available data on large point sources. In this work CO2 emissions data are spatially distributed using population density as the selected proxy, using three different treatments of large point sources, and with five levels of grid resolution (1o, 2o, 3o, 4o, and 5o). The methods of calculating uncertainty associated with grid size, proxy selection, and reported point-source emissions data are presented, with particular attention being drawn to grid size selection. We find that as the resolution becomes coarser, relative uncertainty (total uncertainty as a percentage of total emissions) at the grid cell level decreases. Relative uncertainty in most grid cells decreases as the portion of emissions attributed to specific point sources increases. Good data on large point sources is very important for spatially explicit emissions inventories.

Keywords

CO2 emissions Gridded inventories Emissions inventories as a function of scale U.S. CO2 emissions 

Notes

Acknowledgements

This work was aided by support from the Research Institute for Environment, Energy, and Economics at Appalachian State University. We are indebted to Rostyslav Bun for extremely insightful and constructive comments on an earlier draft of this paper. Suggestions from two anonymous reviewers have contributed significantly.

References

  1. Andres RJ, Boden TA, Bréon F–M, Ciais P, Davis S, Erickson D, Gregg JS, Jacobson A, Marland G, Miller J, Oda T, Olivier JGJ, Raupach MR, Rayner P, Treanton K (2012) A synthesis of carbon dioxide emissions from fossil-fuel combustion. Biogeosciences 9(5):1845–1871.  https://doi.org/10.5194/bg-9-1845-2012 CrossRefGoogle Scholar
  2. CARMA (2016) Carbon Monitoring for Action, www.CARMA.org
  3. Gurney KR, Mendoza DL, Zhou Y, Fischer ML, Miller CC, Geethakumar S, de la Rue du Can S (2009) High resolution fossil-fuel combustion CO2 emissions fluxes for the United States. Environ Sci Technol 43(14):5535–5541.  https://doi.org/10.1021/es900806c CrossRefGoogle Scholar
  4. Hogue S, Marland E, Andres RJ, Marland G, Woodard D (2016) Uncertainty in gridded CO2 emissions estimates. Earth’s Future 4(5):225–239.  https://doi.org/10.1002/2015EF000343 CrossRefGoogle Scholar
  5. Hutchins MG, Colby JD, Marland G, Marland E (2016) A comparison of five high-resolution spatially-explicit fossil fuel carbon dioxide emissions inventories. Mitig Adapt Strateg Glob Chang 22(6):947–972.  https://doi.org/10.1007/s11027-016-9709-9 CrossRefGoogle Scholar
  6. NIST (2015) Measuring smokestack emissions accurately, National Institute of Standards and Technology, U.S. Department of Commerce, November 23, 2015. Available at https://www.nist.gov/newsevents/news/2015/11/measuring-smokestack-emissions-accurately
  7. Oak Ridge National Laboratory (2015) Landscan. Oak Ridge National Laboratory. U.S. Department of Energy, Oak Ridge Available at http://web.ornl.gov/sci/landscan/ Google Scholar
  8. Oda T, Maksyutov S (2011) A very high-resolution (1 km x 1 km) global fossil fuel CO2 emission inventory derived using a point source database and satellite observations of night lights. Atmos Chem Phys 11(2):543–556.  https://doi.org/10.5194/acp-11-543-2011 CrossRefGoogle Scholar
  9. Quick JC (2014) Carbon dioxide emission tallies for 210 U.S. coal-fired power plants: a comparison of two accounting methods. J Air Waste Manag Assoc 64(1):73–79.  https://doi.org/10.1080/10962247.2013.833146 CrossRefGoogle Scholar
  10. Singer AM, Branham M, Hutchins MG, Welker J, Woodard DL, Badurek CA, Ruseva T, Marland E, Marland G (2014) The role of CO2 emissions from large point sources in emissions totals, responsibility, and policy. Environ Sci Policy 44:190–200.  https://doi.org/10.1016/j.envsci.2014.08.001 CrossRefGoogle Scholar
  11. U.S. Census Bureau (2011) Population Distribution and Change: 2000–2010, 2010 Census Briefs, U.S. Census Burreau, Washington D.C. Available at http://www.census.gov/prod/cen2010/briefs/c2010br-01.pdf
  12. U.S. Department of Energy/Energy Information Administration (2013) Energy-Related Carbon Dioxide Emissions at the State Level. U.S. DOE/EIA, Washington, D.C. Available at: http://www.eia.gov/environment/emissions/state/analysis/ Google Scholar
  13. U.S. E.P.A (2014) Clean Energy: eGRID, Ninth Edition With 2010 Data. U.S. Environmental Protection Agency, Washington, D.C. Available at: http://www.epa.gov/cleanenergy/energy-resources/egrid/ Google Scholar
  14. U.S. E.P.A (2015) Greenhouse Gas Reporting Program (GHGRP) 2011. U.S. Environmental Protection Agency, Washington, D.C. Available at: http://www2.epa.gov/ghgreporting Google Scholar
  15. Woodard D, Branham M, Buckingham G, Hogue S, Hutchins M, Gosky R, Marland G, Marland E (2015) A spatial uncertainty metric for anthropogenic CO2 emissions. GHG Measure Manag 4(2-4):139–160.  https://doi.org/10.1080/20430779.2014.1000793 Google Scholar

Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2017

Authors and Affiliations

  • S. Hogue
    • 1
  • D. Roten
    • 1
    • 2
  • E. Marland
    • 1
    • 3
  • G. Marland
    • 3
    Email author
  • T. A. Boden
    • 4
  1. 1.Department of Mathematical SciencesAppalachian State UniversityBooneUSA
  2. 2.Department of Physics and AstronomyAppalachian State UniversityBooneUSA
  3. 3.Research Institute for Energy, Environment, and EconomicsAppalachian State UniversityBooneUSA
  4. 4.Climate Change Science InstituteOak Ridge National LaboratoryOak RidgeUSA

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