Uncertainty in dispersion modelling and urban air quality mapping |
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| Institution: | 1. Department of Environmental Science & Technology, Imperial College Faculty of Life Sciences, Prince Consort Road, London SW7 2BP, UK;2. Department of Environmental Sciences, Air Quality Management Resource Centre, University of the West of England, Frenchay Campus, Bristol BS16 1QY, UK;3. Cambridge Environmental Research Consultants, 3 Kings Parade, Cambridge CB2 1SJ, UK;4. University of Greenwich, Medway Campus, Chatham Maritime, Kent ME4 4TB, UK;5. Environmental Health Team, London Borough of Camden, Argyle Street, London WC1H 8EQ, UK;6. Westminster City Council Environmental Health, Westminster Council House, Marylebone Road, London NW1 5PT, UK;7. Environmental Health Service, Royal Borough of Kensington & Chelsea, 37 Pembroke Street, London W8 6PW, UK;1. Graduate School, Tokyo University of Marine Science and Technology 2-1-6, Etchujima, Koto-ku, Tokyo 135-8533, Japan;2. Tokyo University of Marine Science and Technology, Japan;3. Tokyo Metropolitan College of Industrial Technology, Japan;4. Basic Technology Research Center, Corporate Research and Development Center, NSK Ltd., Japan;1. Department of Engineering Physics, Polytechnique Montreal, Montreal, Quebec H3C 3A7, Canada;2. Corning Inc., Corning, NY 14830, USA;1. Department of Environmental Medicine, NYU School of Medicine, 57 Old Forge Road, Tuxedo, New York 10987, United States;2. Normandeau Associates, Inc., 30 International Drive, Suite 6, Portsmouth, New Hampshire 03801, United States;1. Mechanical Engineering, National University of Ireland, Galway, Newcastle Rd., Galway H91 HX31, Ireland;2. Civil Engineering, National University of Ireland, Galway, Newcastle Rd., Galway H91 HX31, Ireland;3. Faculty of Engineering, The University of Nottingham, Nottingham NG7 2RD, UK;1. Department of Mechanical Engineering, NSS College of Engineering, Palakkad 678008, India;2. ITMMEC, Indian Institute of Technology Delhi, Hauz-Khas, New Delhi 110016, India;3. Department of Mechanical Engineering, I.I.T. Delhi, New Delhi 110016, India |
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| Abstract: | The ADMS-urban atmospheric dispersion modelling system has been applied to review of air quality in central London in 1996/1997 and assessment of future air quality against air quality objectives in 2005. Model performance is assessed by in situ validation against monitoring data. This case study illustrates how scientific uncertainty needs to be considered when using model output in such a policy context. Model precision, carefully defined, is ±10% with bias between 0 and +12% (model over-prediction) for annual mean nitrogen dioxide and respirable particulate (PM10) concentrations and for the 90th percentile of daily mean PM10. As expected, the model is less accurate for the maximum and 99.8th percentile of hourly mean nitrogen dioxide concentrations and for total NOx. We propose probabilistic mapping techniques should be used to formalise and clarify how uncertainty is translated into the definition of an Air Quality Management Area (AQMA) on a map. This also identifies the extent to which air quality objectives have been defined for which current dispersion model performance is inadequate. It is recommended that the capabilities of modelling alongside measurement need to be considered at an early stage in the formulation of future air quality management policy. |
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