Editorial Type:
Article
Article Type:
Research Article

The Australian Air Quality Forecasting System. Part I: Project Description and Early Outcomes

M. E. Cope CSIRO Atmospheric Research, Aspendale, Victoria, Australia
CSIRO Energy Technology, Newcastle, New South Wales, Australia

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G. D. Hess Bureau of Meteorology Research Centre, Melbourne, Victoria, Australia

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S. Lee CSIRO Atmospheric Research, Aspendale, Victoria, Australia

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K. Tory Bureau of Meteorology Research Centre, Melbourne, Victoria, Australia

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M. Azzi CSIRO Energy Technology, Newcastle, New South Wales, Australia

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J. Carras CSIRO Energy Technology, Newcastle, New South Wales, Australia

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W. Lilley CSIRO Energy Technology, Newcastle, New South Wales, Australia

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P. C. Manins CSIRO Atmospheric Research, Aspendale, Victoria, Australia

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P. Nelson Graduate School of the Environment, Macquarie University, North Ryde, New South Wales, Australia

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L. Ng Environment Protection Agency of Victoria, Melbourne, Victoria, Australia

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K. Puri CSIRO Atmospheric Research, Aspendale, Victoria, Australia

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N. Wong Environment Protection Agency of Victoria, Melbourne, Victoria, Australia

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S. Walsh Environment Protection Agency of Victoria, Melbourne, Victoria, Australia

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M. Young Department of Environment and Conservation (NSW), Lidcombe, New South Wales, Australia

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Print Publication:
01 May 2004
DOI:
https://doi.org/10.1175/2093.1
Page(s):
649–662
Restricted access

Abstract

The Australian Air Quality Forecasting System (AAQFS) is the culmination of a 3-yr project to develop a numerical primitive equation system for generating high-resolution (1–5 km) short-term (24–36 h) forecasts for the Australian coastal cities of Melbourne and Sydney. Forecasts are generated 2 times per day for a range of primary and secondary air pollutants, including ozone, nitrogen dioxide, carbon monoxide, sulfur dioxide, and particles that are less than 10 μm in diameter (PM10). A preliminary assessment of system performance has been undertaken using forecasts generated over a 3-month demonstration period. For the priority pollutant ozone it was found that AAQFS achieved a coefficient of determination of 0.65 and 0.57 for forecasts of peak daily 1-h concentration in Melbourne and Sydney, respectively. The probability of detection and false-alarm rate were 0.71 and 0.55, respectively, for a 60-ppb forecast threshold in Melbourne. A similar level of skill was achieved for Sydney. System performance is also promising for the primary gaseous pollutants. Further development is required before the system can be used to forecast PM10 confidently, with a systematic overprediction of 24-h PM10 concentration occurring during the winter months.

Corresponding author address: M. E. Cope, CSIRO Atmospheric Research, PMB 1, Aspendale VIC 3195, Australia. martin.cope@csiro.au

Abstract

The Australian Air Quality Forecasting System (AAQFS) is the culmination of a 3-yr project to develop a numerical primitive equation system for generating high-resolution (1–5 km) short-term (24–36 h) forecasts for the Australian coastal cities of Melbourne and Sydney. Forecasts are generated 2 times per day for a range of primary and secondary air pollutants, including ozone, nitrogen dioxide, carbon monoxide, sulfur dioxide, and particles that are less than 10 μm in diameter (PM10). A preliminary assessment of system performance has been undertaken using forecasts generated over a 3-month demonstration period. For the priority pollutant ozone it was found that AAQFS achieved a coefficient of determination of 0.65 and 0.57 for forecasts of peak daily 1-h concentration in Melbourne and Sydney, respectively. The probability of detection and false-alarm rate were 0.71 and 0.55, respectively, for a 60-ppb forecast threshold in Melbourne. A similar level of skill was achieved for Sydney. System performance is also promising for the primary gaseous pollutants. Further development is required before the system can be used to forecast PM10 confidently, with a systematic overprediction of 24-h PM10 concentration occurring during the winter months.

Corresponding author address: M. E. Cope, CSIRO Atmospheric Research, PMB 1, Aspendale VIC 3195, Australia. martin.cope@csiro.au

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  • Adelman, Z. E. 1999. A reevaluation of the carbon bond-IV photochemical mechanism. M.S. thesis, Department of Environmental Sciences and Engineering, School of Public Health, University of North Carolina, 194 pp.

    • Search Google Scholar
    • Export Citation

  • Azzi, M., G. J. Johnson, and M. E. Cope. 1992. An introduction to the Generic Reaction Set photochemical smog mechanism. Proc. 11th Int. Clean Air Conf., Brisbane, QLD, Australia, Clean Air Society of Australia and New Zealand, 451–462.

    • Search Google Scholar
    • Export Citation

  • Brandt, J., H. J. Christensen, L. M. Frohn, F. Palmgren, R. Berkowicz, and Z. Zlatev. 2001. Operational air pollution forecasts from European to local scale. Atmos. Environ 35:S91–S98.

    • Search Google Scholar
    • Export Citation

  • Cardelino, C. Coauthors 2001. Ozone predictions in Atlanta, Georgia: Analysis of the 1999 ozone season. J. Air Waste Manage. Assoc 51:1227–1236.

    • Search Google Scholar
    • Export Citation

  • Carruthers, D. J., H. A. Edmunds, A. E. Lester, C. A. McHugh, and R. J. Singles. 2000. Use and validation of ADMS-urban in contrasting urban and industrial locations. Int. J. Environ. Pollut 14:364–374.

    • Search Google Scholar
    • Export Citation

  • Cope, M. E. and D. Hess. 1998. The application of an integrated meteorological air quality modelling system to a photochemical smog event in Perth Australia. Air Pollution Modeling and Its Application XII, S.-E. Gryning and H. Chaumerliac, Eds., Plenum Press, 609–615.

    • Search Google Scholar
    • Export Citation

  • De Leeuw, F. 2000. Criteria for evaluation of smog forecast systems. Environ. Monit. Assess 60:1–14.

  • Dewundege, P. 2001. A semi automated expert system for smog forecasting over Melbourne airshed. Clean Air 35:35–40.

  • Draxler, R. R. 2000. Meteorological factors of ozone predictability at Houston, Texas. J. Air Waste Manage. Assoc 50:259–271.

  • EPA Victoria, 1999. Air emissions inventory, Port Phillip region. EPA Victoria Publ. 632, 48 pp.

  • EPA Victoria, 2000. Melbourne mortality study. Effects of ambient air pollution on daily mortality in Melbourne 1991–1996. EPA Victoria Publ. 709, 118 pp.

    • Search Google Scholar
    • Export Citation

  • Ferguson, S. A., D. V. Sandberg, and R. Ottmar. 1998. Wild-land biomass emissions affected by land-use changes. Preprints, Second Symp. on Fire and Forest Meteorology, Phoenix, AZ, Amer. Meteor. Soc., 71–74.

    • Search Google Scholar
    • Export Citation

  • Fine, P. M., G. R. Cass, and B. R. T. Simoneit. 2001. Chemical characterization of fine particle emissions from fireplace combustion of woods grown in the northeastern United States. Environ. Sci. Technol 35:2665–2675.

    • Search Google Scholar
    • Export Citation

  • Gery, M. W., G. Z. Whitten, J. P. Killus, and M. C. Dodge. 1989. A photochemical kinetics mechanism for urban and regional scale computer modeling. J. Geophys. Res 94:12925–12956.

    • Search Google Scholar
    • Export Citation

  • Griffin, R. J., D. Dabdub, and J. H. Seinfeld. 2002. Secondary organic aerosol 1. Atmospheric chemical mechanism for production of molecular constituents. J. Geophys. Res.,107, 4332, doi: 10.1029/2001JD000541.

    • Search Google Scholar
    • Export Citation

  • Harley, R. A., A. G. Russell, G. J. McRae, G. R. Cass, and J. H. Seinfeld. 1993. Photochemical modeling of the southern California air quality study. Environ. Sci. Technol 27:378–388.

    • Search Google Scholar
    • Export Citation

  • Hess, G. D., M. E. Cope, S. Lee, P. C. Manins, G. A. Mills, K. Puri, and K. Tory. 2000. The Australian Air Quality Forecasting System. AMOS Bull 13:67–73.

    • Search Google Scholar
    • Export Citation

  • Hess, G. D., K. J. Tory, M. E. Cope, S. Lee, K. Puri, P. C. Manins, and M. Young. 2004. The Australian Air Quality Forecasting System. Part II: Case study of a Sydney 7-day photochemical smog event. J. Appl. Meteor 43:663–679.

    • Search Google Scholar
    • Export Citation

  • Hurley, P. 2000. The Air Pollution Model (TAPM): Summary of some recent verification work in Australia. Proc. 15th Int. Clean Air and Environment Conf., Brighton Beach, NSW, Australia, Clean Air Society of Australia and New Zealand, 90–103.

    • Search Google Scholar
    • Export Citation

  • Lee, S., M. Cope, K. Tory, D. Hess, and L. Ng. 2002. The Australian Air Quality Forecasting System: Modelling of a severe smoke event in Melbourne, Australia. Air Pollution Modelling and Its Application XV, C. Borrego and G. Schayes, Eds., Kluwer Academic/Plenum, 95–114.

    • Search Google Scholar
    • Export Citation

  • Lu, H. and Y. Shao. 2001. Toward quantitative prediction of dust storms: An integrated wind erosion modelling system and its applications. Environ. Modell. Software 16:233–249.

    • Search Google Scholar
    • Export Citation

  • Manins, P. C. 2001. Air quality forecasting for Australia's major cities—Final report. Project Management Committee, CSIRO Atmospheric Research, 341 pp. [Available online at http://www.dar.csiro.au/information/aaqfs.html.].

    • Search Google Scholar
    • Export Citation

  • Manins, P. C., M. E. Cope, G. D. Hess, P. F. Nelson, K. Puri, N. Wong, and M. Young. 2002. The Australian Air Quality Forecasting System: Prognostic air quality forecasting in Australia. Clean Air 36:43–48.

    • Search Google Scholar
    • Export Citation

  • McHenry, J. N., N. Seaman, C. Coats, D. Stauffer, A. Lario-Gibbs, J. Vukovich, E. Hayes, and N. Wheeler. 2000. The NCSC-PSU numerical air quality prediction project: Initial evaluation, status, and prospects. Preprints, Symp. on Atmospheric Chemistry Issues in the 21st Century, Long Beach, CA, Amer. Meteor. Soc., 95– 102.

    • Search Google Scholar
    • Export Citation

  • Monahan, E. C., E. Spiel, and K. L. Davidson. 1986. A model of marine aerosol generation via whitecaps and wave disruption. Ocean Whitecaps and Their Role in Air–Sea Exchange Processes, E. C. Monahan and G. Mac Niocaill, Eds., Reidel, 167– 174.

    • Search Google Scholar
    • Export Citation

  • Morgan, P. 1986. Forecasting air pollution episodes in Melbourne. Proc. Seventh World Clean Air Congress, Vol. 2, Sydney, NSW, Australia, World Clean Air Congress, 315–322.

    • Search Google Scholar
    • Export Citation

  • Nelson, P. F., P. C. Nancarrow, B. Halliburton, A. R. Tibbett, D. Chase, and T. Trieu. 2001. Biogenic emissions from trees and grasses. CSIRO Energy Technology Investigation Rep. ET/297, 63 pp.

    • Search Google Scholar
    • Export Citation

  • Ng, Y. L. and M. Minchin. 2000. Spatial and temporal allocation of emissions from wood combustion. Proc. 15th Int. Clean Air Environment Conf., Brighton Beach, NSW, Australia, Clean Air Society of Australia and New Zealand, 288–291.

    • Search Google Scholar
    • Export Citation

  • Ng, Y. L., S. Walsh, and N. Wong. 2000. Emissions model for the Australian Air Quality Forecasting System. Proc. 15th Int. Clean Air Environment Conf., Brighton Beach, NSW, Australia, Clean Air Society of Australia and New Zealand, 275–280.

    • Search Google Scholar
    • Export Citation

  • Ohara, T., A. Fujita, T. Kizu, and S. Okamoto. 1998. Advanced air quality forecasting system for Chiba Prefecture. Air Pollution Modeling and Its Application XII, S.-E. Gryning and H. Chaumerliac, Eds., Plenum Press, 625–633.

    • Search Google Scholar
    • Export Citation

  • Puri, K., G. Dietachmayer, G. A. Mills, N. E. Davidson, R. A. Bowen, and L. W. Logan. 1998. The new BMRC Limited Area Prediction System, LAPS. Aust. Meteor. Mag 47:203–233.

    • Search Google Scholar
    • Export Citation

  • Rufeger, W., P. Mieth, and T. Lux. 1997. Applying the DYMOS system in conurbations. Proc. Modsim 97, Vol. 4, Hobart, TAS, Australia, International Congress on Modelling and Simulation, 1797–1801.

    • Search Google Scholar
    • Export Citation

  • Seigneur, C. Coauthors 2000. Guidance for the performance evaluation of three-dimensional air quality modeling systems for particulate matter and visibility. J. Air Waste Manage. Assoc 50:588–599.

    • Search Google Scholar
    • Export Citation

  • Tonnesen, S. and H. E. Jeffries. 1994. Inhibition of odd oxygen production in the carbon bond four and generic reaction set mechanisms. Atmos. Environ 28:1339–1349.

    • Search Google Scholar
    • Export Citation

  • Toon, O. B., R. P. Turco, D. Westphal, R. Malone, and M. S. Liu. 1988. A multidimensional model for aerosols: Description of computational analogs. J. Atmos. Sci 45:2123–2143.

    • Search Google Scholar
    • Export Citation

  • Tory, K. J., M. E. Cope, G. D. Hess, S. Lee, K. Puri, P. C. Manins, and N. Wong. 2004. The Australian Air Quality Forecasting System. Part III: Case study of a Melbourne 4-day photochemical smog event. J. Appl. Meteor 43:680–695.

    • Search Google Scholar
    • Export Citation

  • Venkatram, A., P. Karamchandani, P. Pai, and R. Goldstein. 1994. The development and application of a simplified ozone modeling system (SOMS). Atmos. Environ 28:3665–3678.

    • Search Google Scholar
    • Export Citation

  • Walter, B. 1997. Combining ozone visualization with atmospheric light scattering. Proc. Modsim 97, Vol. 4, Hobart, TAS, Australia, International Congress on Modelling and Simulation, 1820– 1826.

    • Search Google Scholar
    • Export Citation
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