Skip to main content
Log in

Methodology for designing air quality monitoring networks: II. Application to Las Vegas, Nevada, for carbon monoxide

  • Published:
Environmental Monitoring and Assessment Aims and scope Submit manuscript

Abstract

An objective methodology presented in a companion paper (Liu et al., 1986) for determining the optimum number and disposition of ambient air quality stations in a monitoring network for carbon monoxide is applied to the Las Vegas, Nevada, area. The methodology utilizes an air quality simulation model to produce temporally-varying air quality patterns for each of a limited number of meteorological scenarios representative of the region of interest. These air quality patterns in turn serve as the data base in a two-step procedure for the identification and ranking of the most desirable monitoring locations (step 1) and the removal of redundancies in spatial coverage among the desired locations (step 2.)

The performance of the air quality simulation model, a key element in the design methodology, was evaluated in the Las Vegas area in a special field measurement program. In the Las Vegas demonstration for carbon monoxide, 19 stations covering concentration maxima and 3 stations covering background concentrations in rural areas were identified and ranked. A 10-station network, for example, consisting of 7 stations for peak average concentrations and 3 stations for background concentrations, was selected for a desired minimum detection capability of 50% of concentration variations. Networks with fewer stations would be selected if smaller minimum detection capabilities of concentration variations are acceptable, and vice versa. Background stations could, of course, be deleted for networks with the sole purpose of discerning peak concentrations.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Ames, J., Meyers, T. C., Reid, L. E., Whitney, D. C., Golding, S. H., Hayes, S. R., and Reynolds, S. D.: 1978, ‘The Users Manual for the SAI Airshed Model’, Systems Applications, Inc., San Rafael, California. Prepared for U.S. Environmental Protection Agency, Research Triangle Park, North Carolina under Contract No. 68-02-2429.

    Google Scholar 

  • David, F. N.: 1938, Tables of the Ordinates and Probability Integral of the Distribution of the Correlation Coefficient in Small Samples, The Biometrika Office, Cambridge University Press, Cambridge, England.

    Google Scholar 

  • Haltiner, G. J.: 1971, Numerical Weather Prediction, John Wiley and Sons, Inc., New York. New York.

    Google Scholar 

  • Hoel, P. G.: 1962, Introduction to Mathematical Statistics, 3rd Edition. John Wiley and Sons, Inc., New York.

    Google Scholar 

  • Johnson, W. B., Ludwig, F. L., Dabberdt, W. F., and Allen, R. J.: 1973, ‘An Urban Diffusion Model for Carbon Monoxide’, J. Air Pollut. Control Assoc., 23, 490–498.

    Google Scholar 

  • Koch, R. C. and Thayer, S. D.: 1972, ‘Validity of the Multiple Source Gaussian Plume Urban Diffusion Model Using Hourly Inputs of Data’, In Proceedings of Conference on Urban Environmental and Second Conference on Biometeorology, Phyladelphia, Pennsylvania, 64–68.

  • Liu, M. K., Whitney, D. C., and Roth, P. M.: 1976a, ‘Effects of Atmospheric Parameters on the Concentration of Photochemical Air Pollutants’, J. Appl. Meteorol. 15, 829–835.

    Google Scholar 

  • Liu, M. K., Whitney, D. C., Seinfeld, J. H. and Roth, P. M.: 1976b, ‘Continued Research in Mesoscale Air Pollution Simulation Modeling, Vol. I—Assessment of Prior Model Evaluation Studies and Ananlysis of Model Validity and Sensitivity’, EPA-600/4-76-016A, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina. Liu, M. K. and Yocke, M. A.: 1980, ‘Siting of Wind Turbine Generators in Complex Terrain’, J. Energy 4, 10–16.

    Google Scholar 

  • Liu, M. K., Behar, J. V., McElroy, J. L., Avrin, J., and Pollack, R. I.: 1986, ‘Methodology for Designing Air Quality Monitoring Networks: I Theoretical Aspects’, Environmental Monitoring and Assessment 6, 1–11.

    Google Scholar 

  • Ludwig, F. L., Berg, N. J., and Hoffman, A. H.: 1976, ‘The Selection of Sites for Air Pollutant Monitoring’, Paper presented at the 69th Annual Meeting of the Air Pollut. Control Assoc., Portland, Oregon.

  • Lund, I. A.: 1963, ‘Map-Pattern Classification by Statistical Techniques’, J. Appl. Meteorol. 2, 56–65.

    Google Scholar 

  • McElroy, J. L., Behar, J. V., Dunn, L. M., Lem, P. N., Pitchford, A. M., Fisher, N. T., Liu, M. K., Jerskey, T. N., Meyer, J. P., Ames, J., and Lundberg, G.: 1978, ‘Carbon Monoxide Monitoring Network Design Methodology-Application in the Las Vegas Valley’, EPA-600/14-78-053, U.S. Environmental Protection Agency, Las Vegas Nevada.

    Google Scholar 

  • Meyers, J. P.: 1971, ‘Discriminant Analysis in Laterite and Lateritic Soils and Other Problem Soils of Africa. An Engineering Study for Agency for International Development’, AID/csd-2164.

  • Naylor, M. H.: 1984, Personal Communication. Director Air Pollution Control Division, Clark Co. Health District.

  • Nelson, S. P. and Weibel, M. L.: 1980, ‘Three-Dimensional Shuman Filter’, J. Appl. Meteorol. 19, 464–469.

    Google Scholar 

  • Ott, W. R.: 1975, ‘Development of Criteria for Siting Monitoring Stations’, Paper presented at 68th Annual Meeting of the Air Pollut. Control Assoc., Boston, Massachusetts.

  • Ott, W. R. and Thom, G. C.: 1976, ‘A Critical Review of Air Pollution Index Systems in the United States and Canada’, J. Air Pollut. Control Assoc. 26, 460–470.

    Google Scholar 

  • Reynolds, S. D., Roth, P. M., and Seinfeld, J. H.: 1973, ‘Mathematical Modeling of Photochemical Air Pollution—I: Formation of the Model’, Atmos. Environment 7, 1033–1061.

    Google Scholar 

  • Reynolds, S. D., Roth, P. M., and Seinfeld, J. H.: 1974, ‘Mathematical Modeling of Photochemical Air Pollution—III: Evaluation of the Model’, Atmos. Environment, 8, 563–596.

    Google Scholar 

  • Roach, G. E., and MacDonald, A. E.: 1975, ‘Map-Type Precipitation Probabilities for the Western Region’, U.S. Department of Commerce, NOAA, NWS, Comm-75-10428.

  • Roth, P. M., Roberts, P. J. W., Liu, M. K., Reynolds, S. D., and Seinfeld, J. H.: 1974, ‘Mathematical Modeling of Photochemical Air Pollution—II: A Model and Inventory of Pollutant Emissions’, Atmos Environment 8, 97–130.

    Google Scholar 

  • Shirr, C. C. and Shieh, L. J.: 1974, ‘A Generalized Urban Air Pollution Model and Its Application to the Study of SO2 Distributions in the St. Louis Metropolitan Area’, J. Appl. Meteorol. 13, 185–203.

    Google Scholar 

  • Shuman, F. G.: 1957, ‘Numerical Methods in Weather Prediction—II: Smoothing the Filtering’, Mon. Wea. Review 85, 357–361.

    Google Scholar 

  • Slater, H. H. and Tikvart, J. A.: 1974, ‘Application of a Multiple-Source Urban Model’, in Proceedings of 5th Meeting NATO/CCMS Expert Panel on Air Pollution Modeling, Roskilde, Denmark, Chapter 14.

  • U.S. Environmental Protection Agency: 1976, ‘Compilation of Air Pollutant Emissions Factors, AP-42, and Supplements 1 through 5, Second Edition’.

Download references

Author information

Authors and Affiliations

Authors

Additional information

Although the research described in this article has been funded wholly or in part by the United States Environmental Protection Agency through Contract No. 68-03-2446 to Systems Application, Inc., it has not been subjected to Agency review and therefore does not necessarily reflect the views of the Agency and no official endorsement should be inferred.

Rights and permissions

Reprints and permissions

About this article

Cite this article

McElroy, J.L., Behar, J.V., Meyers, T.C. et al. Methodology for designing air quality monitoring networks: II. Application to Las Vegas, Nevada, for carbon monoxide. Environ Monit Assess 6, 13–34 (1986). https://doi.org/10.1007/BF00394285

Download citation

  • Received:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF00394285

Keywords

Navigation