Journal of Atmospheric Chemistry

, Volume 70, Issue 1, pp 91–104 | Cite as

Differences in the variability of measured and simulated tropospheric ozone mixing ratios over the Paso del Norte Region

  • William R. Stockwell
  • Rosa M. Fitzgerald
  • Duanjun Lu
  • Roberto Perea


The objective of this study is to present differences in the variability of observed and ozone-mixing ratios simulated by a three-dimensional atmospheric chemical model using two chemical mechanisms. In this study the Comprehensive Air Quality Model with Extensions is used to make ozone simulations with the Carbon Bond mechanism, versions 4 and 5. The Paso del Norte region is used as a test-bed for these simulations. The shared variance between the simulations and measurements is typical for air quality models ranging from 0.51 to 0.86 for both mechanisms. The smallest mean normalized gross error is about 31 % with CB4 but the normalized bias is over 30 % as well. Boundary conditions, emissions and other factors affect the levels of ozone of the simulated mixing ratios and therefore error and bias but these factors have a much less affect on the simulated ozone variability. The differences in the ozone variability of the measurements and the simulations are very large and different for the two chemical mechanisms. There are many more instances of low ozone mixing ratios in the measurements than in the simulated ozone. One possible explanation is that these differences are due to problems associated with comparing point measurements with grid averages. A more disturbing possibility is that the bias could be due to the procedures used in the development and testing of air quality modeling systems. Air quality mechanisms are evaluated against environmental chamber data where the chemistry occurs at high concentrations and this may lead to a systematic positive bias in ozone simulations.


Air quality modeling Ozone Chemical mechanisms 



The authors thank the National Oceanic and Atmospheric Administration for a grant to Howard University’s NOAA Center for Atmospheric Sciences, the National Aeronautics and Space Administration for a grant to “Howard University Beltsville Center for Climate System Observation” and the U.S. Environmental Protection Agency for research support through the Oak Ridge Institute for Science and Engineering. The opinions expressed in this publication are those of the authors alone and do not reflect the policy of any government agency.


  1. Berkowicz, R., Palmgren, F., Hertel, O., Vignati, E.: Using measurements of air pollution in streets for evaluation of urban air quality – meterological analysis and model calculations. Sci. Total. Environ. 189, 259–265 (1996)CrossRefGoogle Scholar
  2. Byun, D., Ching, J.K.S.: Science algorithms of the EPA Models-3 Community Multiscale Air Quality Model (CMAQ) modeling system. EPA/600/R-99/030. US Environmental Protection Agency, Office of Research and Development, Washington (1999)Google Scholar
  3. Byun, D., Schere, K.L.: 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 (2006)CrossRefGoogle Scholar
  4. Cai, C., Kelly, J.T., Avise, J.C., Kaduwela, A.P., Stockwell, W.R.: Photochemical modeling in California with the SAPRC07C and SAPRC99 chemical mechanisms: model intercomparison and response to emission reductions. J. Air Waste Manag. Assoc. 61, 559–572 (2011)CrossRefGoogle Scholar
  5. Carter, W.P.L.: Development of the SAPRC-07 chemical mechanism. Atmos. Environ. 44, 5324–5335 (2010)CrossRefGoogle Scholar
  6. Carter, W.P.L., Lurmann, F.W.: Evaluation of the RADM Gas-phase Chemical Mechanism. U.S. Environmental Protection Agency Cooperative Agreement CR- 814558-01-0. Statewide Air Pollution Research Center, University of California, Riverside (1989)Google Scholar
  7. Carter, W.P.L., Luo, D., Malkina, I.L., Fitz, D.: The University of California, Riverside Environmental Chamber Data Base for evaluating oxidant mechanisms, vols. 1 and 2. Statewide Air Pollution Research Center, University of California, Riverside (1995)Google Scholar
  8. Colella, P., Woodward, P.R.: The piecewise parabolic method (PPM) for gas-dynamical simulations. J. Comp. Phys. 54, 174–201 (1984)CrossRefGoogle Scholar
  9. Derwent, R.G.: Evaluation of a number of chemical mechanisms for their application in models describing the formation of photochemical ozone in Europe. Atmos. Environ. 24A, 2615–2624 (1990)Google Scholar
  10. Derwent, R.G.: Evaluation of the chemical mechanisms employed in the EMEP photochemical oxidant model. Atmos. Environ. 27A, 277–279 (1993)Google Scholar
  11. Emery, C., Jung, J., Johnson, J., Yarwood, G., Madronich, S., Grell, G.: Improving the Characterization of Clouds and their impact on photolysis rates within the CAMx Photochemical Grid Model. Prepared for the Texas Commission on Environmental Quality, Austin, TX. ENVIRON International Corporation, Novato, CA (2010)Google Scholar
  12. ENVIRON: User’s Guide to the Comprehensive AirQuality Model with Extensions (CAMx). Version 5.2, (2010)
  13. ENVIRON: CAMX Support Software. (2012)
  14. EPA: Guidance on the Use of models and other analyses for demonstrating attainment of air quality goals for ozone, PM2.5, and Regional Haze, EPA-454/B-07-002. U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards, Research Triangle Park, North Carolina (2007)Google Scholar
  15. Gilliland, A.B., Hogrefe, C., Pinder, R.W., Godowitch, J.L., Rao, S.T.: Dynamic evaluation of regional air quality models: assessing changes in O3 stemming from emissions and meteorology. Atmos. Environ. 42, 5110–5123 (2008)CrossRefGoogle Scholar
  16. Gery, M.W., Whitten, G.Z., Killus, J.P., Dodge, M.C.: A photochemical kinetics mechanism for urban and regional scale computer modeling. J. Geophys. Res. 94, 12925–12956 (1989)CrossRefGoogle Scholar
  17. Goliff, W.S., Stockwell, W.R., Lawson, C.V.: The regional atmospheric chemistry mechanism Version 2. Atmos. Environ. 68, 174–185 (2013)CrossRefGoogle Scholar
  18. Henderson, B.H., Pinder, R.W., Crooks, J., Cohen, R.C., Wennberg, P.O., Hutzell, W.T., Sarwar, G., Goliff, W.S., Stockwell, W.R., Fahr, A., Mathur, R., Carlton, A.G., Vizuete, W.G.: Evaluation of simulated photochemical partitioning of oxidized nitrogen in the upper troposphere. Atmos. Chem. Phys. 11, 275–291 (2011)CrossRefGoogle Scholar
  19. Hough, A.M.: An intercomparison of mechanisms for the production of photochemical oxidants. J. Geophys. Res. 93, 3789–3812 (1988)CrossRefGoogle Scholar
  20. Houyoux, M.R., Vukovich, J.M., Coats, C.J.: Emission inventory development and processing for the seasonal model for regional air quality (SMRAQ) project. J. Geophys. Res. 105, 9079–9090 (2001)CrossRefGoogle Scholar
  21. Hutzell, W.T., Luecken, D.J., Appel, K.W., Carter, W.P.L.: Interpreting predictions from the SAPRC07 mechanism based on regional and continental simulations. Atmos. Environ. 46, 417–429 (2012)CrossRefGoogle Scholar
  22. Jackson, B., Chou, D., Gurer, K., Kaduwela, A.: Comparison of ozone simulations using MM5 and CALMET/MM5 hybrid meteorological fields for the July/August 2000 CCOS episode. Atmos. Environ. 40, 2812–2822 (2006)CrossRefGoogle Scholar
  23. Kim, Y., Sartelet, K., Seigneur, C.: Formation of secondary aerosols over Europe: comparison of two gas-phase chemical mechanisms. Atmos. Chem. Phys. 11, 583–598 (2011)CrossRefGoogle Scholar
  24. Kuhn, M., Builtjes, O.J.H., Poppe, D., Simpson, D., Stockwell, W.R., Andersson-Sköld, Y., Baart, A., Das, M., Fiedler, F., Hov, O., Kirchner, F., Makar, P.A., Milford, J.B., Roemer, M.G.M., Ruhnke, R., Strand, A., Vogel, B., Vogel, H.: Intercomparison of the gas-phase chemistry in several chemistry and transport models. Atmos. Environ. 32, 693–709 (1998)CrossRefGoogle Scholar
  25. Lu, D., Reddy, R.S., Fitzgerald, R., Stockwell, W.R., Williams, Q.L., Tchounwou, P.B.: Sensitivity modeling study for an ozone occurrence during the 1996 Paso del Norte ozone campaign. Int. J. Environ. Res. Publ. Health 5, 181–203 (2008)CrossRefGoogle Scholar
  26. Lu, D., Fitzgerald, R., Stockwell, W.R., Reddy, R.S., White, L.: Numerical simulation for a wind dust event in the US/Mexico border region. Air Qual. Atmos. Health (2012). doi: 10.1007/s11869-012-0174-7 Google Scholar
  27. Lu, D., Reddy, R.S., Fitzgerald, R., Stockwell, W.R., Williams, Q.L., Tchounwou, P.B.: Multiscale comparison of air quality modeling for an ozone occurrence during the 1996 Paso Del Norte ozone campaign. WIT Trans. Biomed. Health 15, 47–58 (2011). doi: 10.2495/EHR110051 CrossRefGoogle Scholar
  28. Luecken, D.J., Phillips, S., Sarwar, G., Jang, C.: Effects of using the CB05 vs. SAPRC99 vs. CB4 chemical mechanism on model predictions: ozone and gas-phase photochemical precursor concentrations. Atmos. Environ. 42, 5805–5820 (2008)CrossRefGoogle Scholar
  29. MacDonalda, C.P., Roberts, P.T., Main, H.H., Dye, T.S., Coe, D.L., Yarbrough, J.: The 1996 Paso del Norte Ozone Study: analysis of meteorological and air quality data that influence local ozone concentrations. Sci. Total. Environ. 276, 93–109 (2001)CrossRefGoogle Scholar
  30. Madronich, S.: The Tropospheric Visible Ultra-violet (TUV) model web page. National Center for Atmospheric Research, Boulder, CO., (2002)
  31. NMED, Database of New Mexico Environment Department (NMED) monitoring stations (2012)
  32. Olson, J., Prather, M., Berntsen, T., Carmichael, G., Chatfield, R., Connell, P., Derwent, R., Horowitz, L., Jin, S., Kanakidou, M., Kasibhatla, P., Kotomarthi, R., Kuhn, M., Law, K., Sillman, S., Penner, J., Pediski, L., Sillmann, S., Stordal, F., Thompson, A., Wild, O.: Results from the intergovernmental panel on climatic change photochemical model intercomparison (Photocomp). J. Geophys. Res. 102, 5979–5991 (1997)CrossRefGoogle Scholar
  33. Pleim, J.: A combined local and nonlocal closure model for the atmospheric boundary layer. Part I: Model description and testing. J. Appl. Met. Clim. 46, 1383–1395 (2007)CrossRefGoogle Scholar
  34. Russell, A., Dennis, R.: NARSTO critical review of photochemical models and modeling. Atmos. Environ. 34, 2283–2324 (2000)CrossRefGoogle Scholar
  35. Sarwar, G., Luecken, D., Yarwood, G., Whitten, G.Z., Carter, W.P.L.: Impact of an updated carbon bond mechanism on predictions from the CMAQ modeling system: preliminary assessment. J. Appl. Met. Clim. 47, 3–14 (2008). doi: 10.1175/2007JAMC1393.1 CrossRefGoogle Scholar
  36. Skamarock, W.C., Klemp, J.B., Dudhia, J.: Prototypes for the WRF (Weather Research and Forecasting) model. Reprints, Ninth Conf. on Meso-scale Processes, Fort Lauderdale, FL, Amer. Meteor. Soc., J11-J15 (2001)Google Scholar
  37. Stockwell, W.R., Artz, R.S., Meagher, J.F., Petersen, R.A., Schere, K.L., Grell, G.A., Peckham, S.E., Stein, A.F., Pierce, R.V., O’Sullivan, J.M., Whung, P.-Y.: The scientific basis of NOAA’s air quality forecasting program. Environmental Manager December 20–27 (2002)Google Scholar
  38. TCEQ: Database of Texas Commission for Environmental Quality (TCEQ) monitoring stations. (2012)
  39. Thompson, A.M.: The oxidizing capacity of the earth’s atmosphere: probable past and future changes. Science 256, 1157–1165 (1992)CrossRefGoogle Scholar
  40. West, J.J., Zavala, M.A., Molina, M.J., San Martini, F., McRae, G.J., Sosa-Iglesias, G., Arriaga-Colina, J.L.: Modeling ozone photochemistry and evaluation of hydrocarbon emissions in the Mexico City metropolitan area. J. Geophys. Res. 109, D19312 (2004). doi: 10.1029/2004JD004614 CrossRefGoogle Scholar
  41. Yarwood, G., Rao, S., Yocke, M., and G.Z. Whitten: Updates to the Carbon Bond chemical mechanism: CB05. Final Report to the US EPA, RT-0400675, 8 December 2005,, (2005)
  42. Zhang, L., Gong, S., Padro, J., Barrie, L.: A size-segregated particle dry deposition scheme for an atmospheric aerosol module. Atmos. Environ. 35, 549–560 (2001)CrossRefGoogle Scholar
  43. Zhang, L., Brook, J.R., Vet, R.: A revised parameterization for gaseous dry deposition in air-quality models. Atmos. Chem. Phys. 3, 2067–2082 (2003)CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • William R. Stockwell
    • 1
  • Rosa M. Fitzgerald
    • 2
  • Duanjun Lu
    • 3
  • Roberto Perea
    • 2
  1. 1.Department of ChemistryHoward UniversityWashingtonUSA
  2. 2.Department of PhysicsUniversity of Texas El PasoEl PasoUSA
  3. 3.Department of Physics, Atmospheric Science and GeoscienceJackson State UniversityJacksonUSA

Personalised recommendations