Compilation of a NOx Emission Inventory for the Balkan Region Using Satellite Tropospheric NO2 Columns

  • I. Zyrichidou
  • M. E. Koukouli
  • D. Balis
  • K. Markakis
  • I. Kioutsioukis
  • A. Poupkou
  • D. Melas
  • K. F. Boersma
  • M. van Roozendael
Conference paper
Part of the Springer Atmospheric Sciences book series (SPRINGERATMO)

Abstract

The important improvements in the quality of space-born tropospheric trace gas estimates have permitted their use, in combination with inverse atmospheric modelling, to obtain evolved top-down pollutant emission estimates. In this study, inverse modeling is applied to the case of tropospheric nitrogen dioxide (NO2) columns as seen by the OMI/Aura instrument and estimated by the Comprehensive Air Quality Model with extensions (CAMx). The main idea is to use the a priori information from the bottom up emission inventory used in the CAMx model, the tropospheric NO2 quantities estimated by the CAMx runs and the tropospheric NO2 columns deduced by the satellite observations to create an a posteriori NOx emission inventory. This new inventory, constrained in the top-down manner by the satellite estimates, can be used anew in the CAMx model to produce a new modeled NOx product. This work has identified biases in the original emission inventory for instance due to missing emission sources or over-estimation of the spread of emission sources and has proved an improved bottom-up emissions inventory.

Keywords

Emission Inventory Balkan Peninsula Balkan Region Mass Balance Method Biomass Burning Emission 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

The research study was financed by the EU research projects: Monitoring Atmospheric Composition and Climate: Grant Agreement no. 218793 and Global and regional Earth-system Monitoring using Satellite and in-situ data, contract no.: 516099.

References

  1. Boersma KF et al (2007) Near-real time retrieval of tropospheric NO2 from OMI. Atmos Chem Phys 7:2103–2118. doi: 10.5194/acp-7-2103-2007 CrossRefGoogle Scholar
  2. Flemming J (2008) Technical description of the coupled forecast system IFS-CTM for global reactive gases forecast and assimilation in GEMS, available at http://gems.ecmwf.int/do/get/PublicDocuments/1534/1052?showfile
  3. Friedrich R (1997) GENEMIS: assessment, improvement, temporal and spatial disaggregation of European emission data. In: Ebel A, Friedrich R, Rhode H (eds) Tropospheric modelling and emission estimation (Part 2). Springer, New YorkGoogle Scholar
  4. Jaegle L et al (2005) Global partitioning of NOx sources using satellite observations: relative roles of fossil fuel combustion, biomass burning and soil emissions. Faraday Discuss 130:407–423. doi: 10.1039/b502128f CrossRefGoogle Scholar
  5. Levelt PF et al (2006) The ozone monitoring instrument. IEEE Trans Geosci Remote Sens 44(5):1093–1101. doi: 10.1109/TGRS.2006.872333 CrossRefGoogle Scholar
  6. Logan JA (1983) Nitrogen oxides in the troposphere: global and regional budgets. J Geophys Res 88:10785–10807. doi: 10.1029/JC088iC15p10785 CrossRefGoogle Scholar
  7. Markakis K et al (2010) A computational approach based on GIS technology for the development of an anthropogenic emission inventory of gaseous pollutants in Greece. Water Air Soil Poll 207:157–180. doi: 10.1007/s11270-009-0126-5 CrossRefGoogle Scholar
  8. Martin RV et al (2003) Global inventory of nitrogen oxide emissions constrained by space-based observations of NO2 columns. J Geophys Res 108(D17):4537. doi: 10.1029/2003JD003453 CrossRefGoogle Scholar
  9. Poupkou A et al (2010) A model for European biogenic volatile organic compound emissions: software development and first validation. Environ Model Softw 25:1845–1856CrossRefGoogle Scholar
  10. Prather MJ, Ehhalt D (2001) In: Climate change 2001: the science of climate change, intergovernmental panel on climate change. Cambridge University Press, Cambridge, p 241Google Scholar
  11. Van der A RJ et al (2008) Trends, seasonal variability and dominant NOx source derived from a ten year record of NO2 measured from space. J Geophys Res 113:D04302. doi:10.1029/2007JD009021Google Scholar
  12. Streets DG et al (2003) An inventory of gaseous and primary aerosol emissions in Asia in the year 2000. J Geophys Res 108(D21):8809. doi: 10.1029/2002JD003093 CrossRefGoogle Scholar
  13. Visschedijk A, Zandveld P, van der Gon DH (2007) A high resolution gridded European emission database for the EU integrated project GEMS. TNO report 2007-A-R0233/BGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • I. Zyrichidou
    • 1
  • M. E. Koukouli
    • 1
  • D. Balis
    • 1
  • K. Markakis
    • 1
  • I. Kioutsioukis
    • 1
  • A. Poupkou
    • 1
  • D. Melas
    • 1
  • K. F. Boersma
    • 2
  • M. van Roozendael
    • 3
  1. 1.Laboratory of Atmospheric Physics, Physics DepartmentAristotle University of ThessalonikiThessalinikiGreece
  2. 2.Royal Netherlands Meteorological ServiceDe BiltThe Netherlands
  3. 3.Belgian Institute for Space AeronomyBrusselsBelgium

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