Use of Salt Lake City URBAN 2000 Field Data to Evaluate the Urban Hazard Prediction Assessment Capability (HPAC) Dispersion Model

Joseph C. Chang George Mason University, Fairfax, Virginia

Search for other papers by Joseph C. Chang in
Current site
Google Scholar
PubMed
Close
,
Steven R. Hanna Harvard School of Public Health, Boston, Massachusetts

Search for other papers by Steven R. Hanna in
Current site
Google Scholar
PubMed
Close
,
Zafer Boybeyi George Mason University, Fairfax, Virginia

Search for other papers by Zafer Boybeyi in
Current site
Google Scholar
PubMed
Close
, and
Pasquale Franzese George Mason University, Fairfax, Virginia

Search for other papers by Pasquale Franzese in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

After the terrorist incidents on 11 September 2001, there is a greatly heightened concern about the potential impacts of acts of terrorism involving the atmospheric release of chemical, biological, radiological, and nuclear (CBRN) materials in urban areas. In response to the need for an urban CBRN model, the Urban Hazard Prediction Assessment Capability (Urban HPAC) transport and dispersion model has been developed. Because HPAC is widely used by the Department of Defense community for planning, training, and operational and tactical purposes, it is of great importance that the new model be adequately evaluated with urban datasets to demonstrate its accuracy. This paper describes evaluations of Urban HPAC using the “URBAN 2000” urban tracer and meteorological field experiment data from Salt Lake City, Utah. Four Urban HPAC model configuration options and five plausible meteorological input data options—ranging from data-sparse to data-rich scenarios—were considered in the study, thus leading to a total of 20 possible model combinations. For the maximum concentrations along each sampling arc for each intensive operating period (IOP), the 20 Urban HPAC model combinations gave consistent mean overpredictions of about 50%, with a range over the 20 model combinations from no overprediction to a factor-of-4 overprediction in the mean. The median of the random scatter for the 20 model combinations was about a factor of 3 of the mean, with a range over the 20 model combinations between a factor of about 2 and 9. These performance measures satisfy previously established acceptance criteria for dispersion models.

Corresponding author address: Dr. Joseph Chang, School of Computational Sciences, MS 5B2, George Mason University, Fairfax, VA 22030-4444. jchang4@scs.gmu.edu

Abstract

After the terrorist incidents on 11 September 2001, there is a greatly heightened concern about the potential impacts of acts of terrorism involving the atmospheric release of chemical, biological, radiological, and nuclear (CBRN) materials in urban areas. In response to the need for an urban CBRN model, the Urban Hazard Prediction Assessment Capability (Urban HPAC) transport and dispersion model has been developed. Because HPAC is widely used by the Department of Defense community for planning, training, and operational and tactical purposes, it is of great importance that the new model be adequately evaluated with urban datasets to demonstrate its accuracy. This paper describes evaluations of Urban HPAC using the “URBAN 2000” urban tracer and meteorological field experiment data from Salt Lake City, Utah. Four Urban HPAC model configuration options and five plausible meteorological input data options—ranging from data-sparse to data-rich scenarios—were considered in the study, thus leading to a total of 20 possible model combinations. For the maximum concentrations along each sampling arc for each intensive operating period (IOP), the 20 Urban HPAC model combinations gave consistent mean overpredictions of about 50%, with a range over the 20 model combinations from no overprediction to a factor-of-4 overprediction in the mean. The median of the random scatter for the 20 model combinations was about a factor of 3 of the mean, with a range over the 20 model combinations between a factor of about 2 and 9. These performance measures satisfy previously established acceptance criteria for dispersion models.

Corresponding author address: Dr. Joseph Chang, School of Computational Sciences, MS 5B2, George Mason University, Fairfax, VA 22030-4444. jchang4@scs.gmu.edu

Save
  • Allwine, K. J., J. H. Shinn, G. E. Streit, K. L. Clawson, and M. Brown. 2002. Overview of URBAN 2000: A multiscale field study of dispersion through an urban environment. Bull. Amer. Meteor. Soc. 83:521536.

    • Search Google Scholar
    • Export Citation
  • Anthes, R. A., Y-H. Kuo, E-Y. Hsie, S. Low-Nam, and T. W. Bettge. 1989. Estimation of skill and uncertainty in regional numerical models. Quart. J. Roy. Meteor. Soc. 115., 763–806.

    • Search Google Scholar
    • Export Citation
  • ARIA Technologies 2001. General design manual, MINERVE Wind Field Model, version 7.0. ARIA Technologies, 72 pp.

  • Bacon, D. Coauthors 2000. A dynamically adapting weather and dispersion model: The Operational Multiscale Environment Model with Grid Adaptivity (OMEGA). Mon. Wea. Rev. 128:20442076.

    • Search Google Scholar
    • Export Citation
  • Boybeyi, Z. and D. P. Bacon. 1996. The accurate representation of meteorology in mesoscale dispersion models. Environmental Modeling III, P. Zannetti, Ed., Computational Mechanics Publications, 109–143.

    • Search Google Scholar
    • Export Citation
  • Briggs, G. A. 1973. Diffusion estimation for small emissions. Atmospheric Turbulence and Diffusion Laboratory, National Oceanic and Atmospheric Administration ATDL Contribution File 79.

  • Chang, J. C. and S. R. Hanna. 2004. Air quality model performance evaluation. Meteor. Atmos. Phys. 87:167196.

  • Chang, J. C., P. Franzese, K. Chayantrakom, and S. R. Hanna. 2003a. Evaluations of CALPUFF, HPAC, and VLSTRACK with two mesoscale field datasets. J. Appl. Meteor. 42:453466.

    • Search Google Scholar
    • Export Citation
  • Chang, J. C., S. R. Hanna, Z. Boybeyi, P. Franzese, S. Warner, and N. Platt. 2003b. Independent evaluation of Urban HPAC with the Urban 2000 field data. Report prepared for the Defense Threat Reduction Agency by George Mason University and the Institute for Defense Analyses, 40 pp.

  • Cimorelli, A. J. Coauthors 2002. AERMOD: Description of model formulation (version 02222). U.S. Environmental Protection Agency, OAQPS, EPA-454/R-02-002d, 85 pp.

  • Cionco, R. M. 1972. A wind-profile index for canopy flow. Bound.-Layer Meteor. 3:255263.

  • Doran, J. C., J. D. Fast, and J. Horel. 2002. The VTMX 2000 Campaign. Bull. Amer. Meteor. Soc. 83:537551.

  • Draxler, R. R. and G. D. Hess. 1997. Description of the HYSPLIT-4 modeling system. NOAA Tech. Memo. ERL ARL-224, 24 pp.

  • DTRA 2001. The HPAC user’s guide, version 4.0.3. Prepared for Defense Threat Reduction Agency, Contract DSWA01-98-C-0110, by Science Applications International Corporation, Rep. HPAC-UGUIDE-02-U-RAC0, 602 pp.

  • Efron, B. 1987. Better bootstrap confidence intervals. J. Amer. Stat. Assoc. 82:171185.

  • Efron, B. and R. J. Tibshirani. 1993. An Introduction to Bootstrap. Statistics and Applied Probability Monogr., No. 57, Chapman & Hall, 436 pp.

    • Search Google Scholar
    • Export Citation
  • EPA 1995. Description of model algorithms. Vol. II, User’s guide for the Industrial Source Complex (ISC3) dispersion models, Environmental Protection Agency, OAQPS, EPA-454/B-95-003b, 128 pp.

  • Hall, D. J., R. Macdonald, S. Walker, and A. M. Spanton. 1998. Measurements of dispersion within simulated urban arrays—A small scale wind tunnel study. Building Research Establishment, Ltd., Rep. CR 244/98, 70 pp.

  • Hall, D. J., A. M. Spanton, I. H. Griffiths, M. Hargrave, and S. Walker. 2002. The Urban Dispersion Model (UDM): Version 2.2. Defence Science and Technology Laboratory Tech. Doc. DSTL/TR04774, 106 pp.

  • Hanna, S. R., D. G. Strimaitis, and J. C. Chang. 1991. Evaluation of commonly-used hazardous gas dispersion models. Vol. II, Hazard Response Modeling Uncertainty (A Quantitative Method), Rep. A119/A120 prepared by Earth Tech, Inc., for Engineering and Services Laboratory, Air Force Engineering and Services Center, and for the American Petroleum Institute, 334 pp.

  • Hanna, S. R., J. C. Chang, and D. G. Strimaitis. 1993. Hazardous gas model evaluation with field observations. Atmos. Environ. 27A:22652285.

    • Search Google Scholar
    • Export Citation
  • Hanna, S. R., R. Britter, and P. Franzese. 2003. A baseline urban dispersion model evaluated with Salt Lake City and Los Angeles tracer data. Atmos. Environ. 37:50695082.

    • Search Google Scholar
    • Export Citation
  • Lim, D. W., D. S. Henn, and R. I. Sykes. 2002. UWM version 1.0 technical documentation. Titan Research and Technology Division Tech. Doc., 37 pp.

  • Macdonald, R. W., D. J. Hall, S. Walker, and A. M. Spanton. 1998. Wind tunnel measurements of wind speed within simulated urban arrays. Building Research Establishment Rep. CR 243/98, 65 pp.

  • McElroy, J. L. and F. Pooler. 1968. St. Louis dispersion study. U.S. Public Health Service, National Air Pollution Control Administration Rep. AP-53, 51 pp.

  • Nasstrom, J. S., G. Sugiyama, D. Ermak, and J. M. Leone Jr.. 2000. A real-time atmospheric dispersion modeling system. Proc. 11th Joint Conf. on the Application of Air Pollution Meteorology with the Air and Waste Management Association, Long Beach, CA, Amer. Meteor. Soc., CD-ROM, 5.1.

  • NOAA 2004. ALOHA (Areal Locations of Hazardous Atmospheres) user’s manual. NOAA Hazardous Materials Response Division, 224 pp.

  • Puhakka, T., K. Jylhä, P. Saarikivi, J. Koistinen, and J. Koivukoski. 1990. Meteorological factors influencing the radioactive deposition in Finland after the Chernobyl accident. J. Appl. Meteor. 29:813829.

    • Search Google Scholar
    • Export Citation
  • Scire, J. S., D. G. Strimaitis, and R. J. Yamartino. 2000. A user’s guide for the CALPUFF dispersion model (version 5.0). Earth Tech, Inc., 521 pp. [Available online at http://www.src.com.].

  • Sharan, M., S. G. Gopalakrishnan, R. T. McNider, and M. P. Singh. 1996. Bhopha gas leak: A numerical investigation of the prevailing meteorological conditions. J. Appl. Meteor. 35:16371657.

    • Search Google Scholar
    • Export Citation
  • Sykes, R. I. Coauthors 2000. PC-SCIPUFF version 1.3 technical documentation. Titan-ARAP Rep. 725, 259 pp.

  • Warner, S., N. Platt, and J. F. Heagy. 2001. Application of user-oriented measure of effectiveness to HPAC probabilistic predictions of Prairie Grass field trials. Institute for Defense Analyses Paper P-3554, 275 pp. [Available from Steve Warner at , or Steve Warner, Institute for Defense Analyses, 4850 Mark Center Drive, Alexandria, VA 22311-1882.].

  • Warner, S., N. Platt, and J. F. Heagy. 2004. Comparison of transport and dispersion model predictions of the URBAN 2000 field experiment. J. Appl. Meteor. 43:829846.

    • Search Google Scholar
    • Export Citation
  • Winkenwerder Jr, W. 2002. Case narrative: U.S. demolition operations at Khamisiyah. Special Assistant to the Under Secretary of Defense (Personnel and Readiness) for Gulf War Illnesses, Medical Readiness, and Military Deployments, U.S. Department of Defense (DOD) Final Rep. 2001137-0000055, 242 pp. [Available online at http://www.gulflink.osd.mil/khamisiyah_iii/.].

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 573 122 11
PDF Downloads 1146 78 7