Implementation and Evaluation of a Comprehensive Emission Model for Europe

  • Johannes Bieser
  • A. Aulinger
  • V. Matthias
  • M. Quante
Conference paper
Part of the NATO Science for Peace and Security Series C: Environmental Security book series (NAPSC)

Abstract

Temporal and spatial distributed emissions are an essential input parameter for Chemical Transport Models (CTM). In order to obtain consistent emissions for long-term CTM runs the US EPA emission model SMOKE has been adapted and modified. The modified version of the SMOKE emission model (SMOKE-EU) uses official and publicly available data sets and statistics to create emissions of CO, NOx, SO2, NH3, PM2.5, PM10, NMVOC. Currently it supports several photochemical mechanisms and a PM2.5 split. Additionally emissions of benzo[a]pyrene have been modelled. The temporal resolution of the emissions is 1 h. The resolution of the surrogates used for spatial disaggregation is 1 × 1 km². Vertical distribution is done via plume rise calculations. The area covered by the emission model is Europe including eastern Russia, North Africa and Turkey the currently implemented datasets allow for the calculation of emissions between 1970 and 2020. Emissions for the year 2000 on a 54 × 54 km² domain were evaluated by comparison to datasets from three commonly used emission models. Additionally SMOKE/EU emissions were used as input for the CMAQ4.6 CTM and the calculated air concentrations of Ozone, NH4, NO3 and SO4 were compared to EMEP measurements. O3: (NMB 0.71) (SD 0.68) (F2 0.83) (CORR 0.55) 48 Stations (hourly). NH4: (NMB 0.25) (SD 1.01) (F2 0.55) (CORR 0.53) 8 Stations (daily).NO3: (NMB 0.42) (SD 0.60) (F2 0.40) (CORR 0.45) 7 Stations (daily). SO4: (NMB 0.34) (SD 0.84) (F2 0.65) (CORR 0.55) 21 Stations (daily). Abbreviations: Normalized Mean Bias (NMB), Standard Deviation (SD), Factor of 2 (F2), Correlation (CORR). Using three different emission datasets as input for CMAQ showed that the SMOKE-EU model produces results comparable to those of commonly used European emissions data sets.

Keywords

Emissions Emission modelling 

References

  1. 1.
    Andersson C, Langner J (2005) Inter-annual variations of ozone and nitrogen dioxide over Europe during 1958–2003 Simulated with a regional CTM. Water Air Soil Pollut 7:15–23CrossRefGoogle Scholar
  2. 2.
    Bieser J, Aulinger A, Matthias V, Quante M, Builtjes P (2010) SMOKE for Europe – adaptation, modification and evaluation of a comprehensive emission model for Europe. GMDD 3(3):949–1007Google Scholar
  3. 3.
    Borge R, Lumbreras J, Encarnacion R (2008) Development of a high-resolution emission inventory for Spain using the SMOKE modelling system: a case study for the years 2000 and 2010. Environ Modell Softw 23:1026–1044CrossRefGoogle Scholar
  4. 4.
    Builtjes PJH, van Loon M, Schaap M, Teeuwisse S, Visschedijk AJH, Bloos JP (2003) Abschlussbericht zum FE-Vorhaben 298 41 252: “Modellierung und Prüfung von Strategien zur Verminderung der Belatung durch Ozon” Contribution of TNO-MEP. TNO-report R2003/166Google Scholar
  5. 5.
    Byun DW, Ching JKS (1999) Science algorithms of the EPA Models-3 community multi-scale air quality (CMAQ) modeling system. EPA/600/R-99/030, US EPA National Exposure Research Laboratory, Research Triangle ParkGoogle Scholar
  6. 6.
    Byun DW, Schere (2006) 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(2):51–77CrossRefGoogle Scholar
  7. 7.
    European Commission (2000) Commission Decision 2000/479/EC of 17 July 2000 on the implementation of a European pollutant emission register (EPER) according to Article 15 of council directive 96/61/EC concerning integrated pollution prevention and control (IPPC). Off J Eur Commun L 192:36–43Google Scholar
  8. 8.
    Guenther A, Geron C, Pierce T, Lamb B, Harley P, Fall R (2000) Natural emissions of non-methane volatile organic compounds, carbon monoxide, and oxides of nitrogen from North America. Atmos Environ 34:2205–2230CrossRefGoogle Scholar
  9. 9.
    Hanna SR, Davis JM (2001) Uncertainties in predicted ozone concentrations due to input uncertainties for the UAM-V photochemical grid model applied to the July 1995 OTAG domain. Atmos Environ 35(5):891–903CrossRefGoogle Scholar
  10. 10.
    Horowitz LW, Walters S, Mauzerall DL, Emmons LK, Rasch PJ, Granier C, Tie X, Lamarque J-F, Schultz MG, Tyndall GS, Orlando JJ, Brasseur GP (2003) A global simulation of tropospheric ozone and related tracers: description and evaluation of MOZART, version 2. J Geophys Res 108:4784. doi:10.1029/2002JD002853Google Scholar
  11. 11.
    Houyoux MR et al (2000) Emission inventory development and processing for the seasonal model for regional air quality (SMRAQ) project. J Geophys Res 105(D7):9079–9090CrossRefGoogle Scholar
  12. 12.
    Maes J, Vliegen J, van de Vel K, Janssen S, Deutsch F, de Ridder K, Mensink C (2009) Spatial surrogates for the disaggregation of CORINAIR emission inventories. Atmos Environ 43:1246–1254CrossRefGoogle Scholar
  13. 13.
    MCNC-environmental modeling center: sparse matrix operational kernel emissions modeling system, http://envpro.ncsc.org/products/smoke/. Accessed 8 May 2008
  14. 14.
    Niemeier U, Granier C, Kornblueh L, Walters S, Brasseur GP (2006) Global impact of road traffic on atmospheric chemical composition and on ozone climate forcing. J Geophys Res 111(D09):301. doi:10.1029/2005JD006407Google Scholar
  15. 15.
    Passant N (2002) Speciation of UK emissions of non-methane volatile organic compounds, AEA Technology, AEAT/R/ENV/0545, Feb 2002Google Scholar
  16. 16.
    Pierce T, Geron C, Bender L, Dennis R, Tonnesen G, Guenther A (1998) Influence of increased isoprene emissions on regional ozone modeling.J Geophys Res 103:25611–25629CrossRefGoogle Scholar
  17. 17.
    Pregger T, Friedrich R (2009) Effective pollutant emission height for atmospheric transport modelling based on real-world information. Environ Pollut 157:552–560CrossRefGoogle Scholar
  18. 18.
    Rockel B, Geyer B (2008) The performance of the regional climate model CLM in different climate regions, based on the example of precipitation. Meteorol Z 17(4):487–498CrossRefGoogle Scholar
  19. 19.
    Rockel B, Will A, Hense A (2008) The regional climate model COSMO-CLM (CCLM). Meteorol Z 17:347–348CrossRefGoogle Scholar
  20. 20.
    Russell D (2000) NARSTO critical review of photochemical models and modelling. Atmos Environ 34(12–14):2261–2282Google Scholar
  21. 21.
    Schwede D, Pouliot G, Pierce T (2005) Changes to the biogenic emissions inventory system version 3 (BEIS3). In: 4th CMAS Models-3 users’ conference, Chapel Hill, 26–28 Sept 2005Google Scholar
  22. 22.
    Sedac (2010) Gridded population of the world version 3, http://sedac.ciesin.columbia.edu/gpw/global.jsp. Accessed 1 Jan 2010
  23. 23.
    Sofiev M, Miranda A I, Sokhi R (2009) Review of the capabilities of meteorological and chemistry-transport models for describing and predicting air pollution episodes, (WMO/TD-No. 1502), Technical report, COST 728 and GURME, Geneva.Google Scholar
  24. 24.
    UNC Carolina Environmental Program (2005) sparse matrix operator kernel emissions (SMOKE) Modeling systemGoogle Scholar
  25. 25.
    U.S. Environmental Protection Agency (2009) community multiscale air quality modeling system, http://www.epa.gov/asmdnerl/models3/. Accessed 12 Aug 2009
  26. 26.
    Vestreng V, Mareckova K, Kakareka S, Malchykhina A, Kukharchyk T (2007) Inventory review 2007. Emission data reported to LRTAP convention and NEC directive. MSC-W Technical report 1 Jul 2007Google Scholar
  27. 27.
  28. 28.
    Yu Y, Sokhi RS, Kitwiroon N, Middleton DR, Fisher B (2008) Performance characteristics of MM5-SMOKE-CMAQ for a summer photochemical episode in southeast England, United Kingdom. Atmos Environ 42:4870–4883CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Johannes Bieser
    • 1
    • 2
  • A. Aulinger
    • 1
  • V. Matthias
    • 1
  • M. Quante
    • 1
    • 2
  1. 1.Helmoltz Zentrum GeesthachtInstitute for Coastal ResearchGeesthachtGermany
  2. 2.Institute of Ecology and Environmental ChemistryLeuphana University LüneburgLüneburgGermany

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