Skip to main content
SpringerLink
Log in

Statistical Models for Distributions of Ambient Fine Particulate Matter

  • Conference paper
Environmental Security and Environmental Management: The Role of Risk Assessment

Part of the book series: NATO Security through Science Series ((NASTC,volume 5))

  • 1258 Accesses

Abstract

This study evaluates the usefulness of structured non-linear regression models for the prediction of annual ambient fine particulate matter (FPM) concentration distributions. The method developed in this study provides a way to examine and display results for the yearly distribution of FPM when testing emissions control strategy performance. The models are developed using three daily gaseous pollutant concentrations (oxides of nitrogen (NOx), sulfur dioxide (SO2), and total hydrocarbons (THC)) and four meteorological measures (wind speed, temperature, relative humidity and precipitation) as explanatory variables. The models are fitted using data from the North Long Beach, Rubidoux (Riverside) and Azusa stations in Los Angeles County and Riverside County, CA for a recent 7-year period (1988–1994). The statistical model is tested for the year 1995 based on precursor concentrations and meteorological conditions in that year, and found to provide reasonably good prediction, though the annual average FPM concentration is overestimated by an average of 26 percent across the three stations. The response surfaces of PM2.5 concentrations with respect to all input variables are plotted, and the predicted changes in daily, annual average and annual 98th percentile base-year (1995) PM2.5 concentrations are predicted for different precursor reductions. The predicted effects of precursor reductions are further explored by comparing predicted and observed FPM concentrations for 1999 (though the absence of THC data for this year restricts this comparison to plausible ranges). The method developed in this study provides a way to examine and display results for the predicted concentration distributions when evaluating emission control strategy performance. The potential usefulness and limitations of a statistical model of this type are discussed.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

7. References

  1. Abu-Allaban, M., Gertler, A. W., and Lowenthal, D. H. (2002). A Preliminary Apportionment Of The Sources Of Ambient PM10, PM2.5, And VOCs in Cairo. Atmospheric Environment 36(35), 5549–5557.

    CAS  Google Scholar 

  2. Air Resources Board (1999). California Ambient Air Quality Data, 1980–1998. CD Number: PTSD-99-012-CD. December, 1999: Planning and Technical Support Division, Air Resources Board. California Environmental Protection Agency.

    Google Scholar 

  3. Ansari, A. S. and Pandis, S. N. (1998). Response Of Inorganic Pm To Precursor Concentrations. Environmental Science & Technology 32, 2706–2714.

    Article  CAS  Google Scholar 

  4. APHEIS (2004). Air Pollution and Health: A European Information System (APHEIS). Health Impact Assessment of Air Pollution and Communication Strategy. http://www.apheis.net/.

    Google Scholar 

  5. Bell, M. L., Cohen, A., Davis, D. L., Grant L., and Sun, G. (2002). Discussion Summary. ISEEf Workshop on Public Health Impacts of Fossil Fuels, Vancouver, Canada.

    Google Scholar 

  6. Blanchard, C. and Hidy, G. (2003). Effects Of Changes In Sulfate, Ammonia, and Nitric Acid On Particulate Nitrate Concentrations In The Southeastern United States. J. Air & Waste Manage. Assoc. 53(3), 283–290.

    CAS  Google Scholar 

  7. Calbo, J., Pan, W., Webster, M., Prinn, R. and Mcrae, G. (1998). Parameterization Of Urban Subgrid Scale Processes In Global Atmospheric Chemistry Models. Journal Of Geophysical Research-Atmospheres 103(D3), 3437–3451.

    CAS  Google Scholar 

  8. Chow, J. C., Watson, J. G., Fujita, E. M., Lu, Z. and Lawson, D. R. (1994). Temporal and Spatial Variations Of Pm2.5 and Pm10 Aerosol In The Southern California Air Quality Study. Atmospheric Environment 28(12), 2061–2080.

    Article  CAS  Google Scholar 

  9. Christoforou, C. S., Salmon, L. G., Hannigan, M. P., Solomon, P. A. and Cass, G. R. (2000). Trends In Fine Particle Concentration and Chemical Composition In Southern California. J. Air & Waste Manage. Assoc. 50, 43–53.

    CAS  Google Scholar 

  10. El-Metwally, A. A. and Ramadan, A. B. (2003). The Role of Air Pollutants and Sewage Waste on Acceleration of Degradation of Islamic Cultural Heritage of Cairo, in Linkov, I. and Ramadan, A. eds., Comparative Risk Assessment and Environmental Decision Making. Kluwer Academic Publishers, Dordrecht, pp. 367–374.

    Google Scholar 

  11. Gujarati, D. N. (1995) Basic Econometrics. New York: Mcgraw-Hill, Inc.

    Google Scholar 

  12. Hanna, S. R. and Davis, J. (2002). Evaluation Of A Photochemical Grid Model Using Estimates Of Concentration Probability Density Functions. Atmospheric Environment 36(11), 1793–1798.

    Article  CAS  Google Scholar 

  13. Hughes, L., Allen, J., Bhave, P., Kleeman, M., Cass, G., Liu, D., Fergenson, D., Morrical, B. and Prather, K. (2000). Evolution Of Atmospheric Particles Along Trajectories Crossing The Los Angeles Basin. Environmental Science & Technology 34(15), 3058–3068.

    Article  CAS  Google Scholar 

  14. Hughes, L. S., Allen, J. O., Salmon, L. G., Mayo, P. R., Johnson, R. J. and Cass, G. R. (2002). Evolution Of Nitrogen Species Air Pollutants Along Trajectories Crossing The Los Angeles Area. Environmental Science & Technology 36(18), 3928–3935.

    Article  CAS  Google Scholar 

  15. Kleeman, M. J. and Cass, G. R. (1999). Effect Of Emissions Control Strategies On The Size and Composition Distribution Of Urban Particulate Air Pollution. Environmental Science & Technology 33(1), 177–189.

    Article  CAS  Google Scholar 

  16. Kleeman, M. J. and Cass, G. R. (2001). A 3D Eulerian Source-Oriented Model For An Externally Mixed Aerosol. Environmental Science & Technology 35, 4843–4848.

    Google Scholar 

  17. Kleeman, M. J., Hughes, L. S., Allen, J. O. and Cass, G. R. (1999). Source Contributions To The Size and Composition Of Atmospheric Particles: Southern California In September 1996. Environmental Science & Technology 33, 4331–4341.

    CAS  Google Scholar 

  18. Lebanon Ministry of Environment (1997). Automotive Fuel Strategies For Clean Air In Lebanon: Lead Phasing Out and Diesel Fuel Policy.

    Google Scholar 

  19. Lefohn, A. S., Shadwick, D. S. and Ziman, S. D. (1998). The Difficult Challenge Of Attaining EPA’s New Ozone Standard. Environmental Science & Technology 32(11), 276a–282a.

    CAS  Google Scholar 

  20. Meng, Z., Dabdub, D. and Seinfeld, J. H. (1997). Chemical Coupling Between Atmospheric Ozone and Particulate Matter. Science 277(4), 116–119.

    CAS  Google Scholar 

  21. Mysliwiec, M. and Kleeman, M. J. (2002). Source Apportionment Of Secondary Airborne Particulate Matter In A Polluted Atmosphere. Environmental Science & Technology 36(24), 5376–5384.

    Article  CAS  Google Scholar 

  22. Pai, P., Vijayaraghavan, K. and Seigneur, C. (2000). Particulate Matter Modeling In The Los Angeles Basin Using Saqm-Aero. J. Air & Waste Manage. Assoc. 50(1), 32–42.

    CAS  Google Scholar 

  23. Pun, B. and Seigneur, C. (2001). Sensitivity Of Particulate Matter Nitrate Formation To Precursor Emissions In The California San Joaquin Valley. Environmental Science & Technology 35(14), 2979–2987.

    Article  CAS  Google Scholar 

  24. Seigneur, C. (2001). Current Status Of Air Quality Models For Particulate Matter. Journal Of Air & Waste Management Association 51(11), 1508–1521.

    CAS  Google Scholar 

  25. Seigneur, C., Pai, P., Hopke, P. K. and Grosjean, D. (1999). Modeling Atmospheric Particulate Matter. Environmental Science & Technology 33(3), 80a–86a.

    CAS  Google Scholar 

  26. Seinfeld, J. and Pandis, S. N. (1998) Atmospheric Chemistry and Physics. New York: John Wiley and Son, Inc.

    Google Scholar 

  27. Soubbotina, T. P. and Sheram, K. A. (2000). Beyond Economic Growth: Meeting the Challenge of Global Development. Washington, D. C., The World Bank.

    Google Scholar 

  28. U.S. EPA (1996a). Air Quality Criteria for Particulate Matter. Vols. I–III, Washington Dc: Office Of Research and Development, U.S. Environmental Protection Agency.

    Google Scholar 

  29. U.S. EPA (1996b). Review Of The National Ambient Air Quality Standards For Particulate Matter: Policy Assessment Of Scientific and Technical Information, OAQPS Staff Paper, Research Triangle Park, NC: Office Of Air Quality Planning and Standards, U.S. Environmental Protection Agency.

    Google Scholar 

  30. U.S. EPA (1997). National Ambient Air Quality Standards For Particulate Matter. Final Rule: Federal Registry.

    Google Scholar 

  31. West, J. J., Ansari, A. S. and Pandis, S. N. (1999). Marginal PM2.5: Nonlinear Aerosol Mass Response To Sulfate Reductions In The Eastern United States. J. Air & Waste Manage. Assoc. 49, 1415–1424.

    CAS  Google Scholar 

  32. Winner, D. A. and Cass, G. R. (2000). Effect Of Emission Control On The Long-Term Frequency Distribution Of Regional Ozone Concentrations. Environmental Science & Technology 34, 2612–2617.

    Article  CAS  Google Scholar 

  33. Yeh, S. and Small, M. J. (2002). Incorporating Exposure Models In Probabilistic Assessment Of The Risks Of Premature Mortality From Particulate Matter. Journal Of Exposure Analysis and Environmental Epidemiology 12(6), 389–403.

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. National Risk Management Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, 109 TW Alexander Drive, RTP, NC, 27711, USA

    S. Yeh (ORISE Research Fellow)

  2. Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, PA, 15213, USA

    M. Small

Authors
  1. S. Yeh
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. M. Small
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Carnegie Mellon University, Pittsburgh, PA, USA

    Benoit Morel  & Igor Linkov  & 

  2. Cambridge Environmental, Inc., Cambridge, Massachusetts, USA

    Igor Linkov

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer

About this paper

Cite this paper

Yeh, S., Small, M. (2006). Statistical Models for Distributions of Ambient Fine Particulate Matter. In: Morel, B., Linkov, I. (eds) Environmental Security and Environmental Management: The Role of Risk Assessment. NATO Security through Science Series, vol 5. Springer, Dordrecht. https://doi.org/10.1007/1-4020-3893-3_10

Download citation

Publish with us

Policies and ethics

Search

Navigation