Accuracy and reliability of an automated air quality forecast system for ozone in seven Kentucky metropolitan areas |
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| Institution: | 1. Université Laval, Département de génie civil et de génie des eaux, 1065, avenue de la Médecine, Québec, QC G1V0A6, Canada;2. Hydro-Quebec Research Institute, Unité expertise mécanique, métallurgie et hydroéolienne, 1800, boulevard Lionel Boulet, Varennes, QC J3X1S1, Canada;3. Ouranos Inc., 550, rue Sherbrooke W., West Tower, 19th floor, Montreal, QC H3A1B9, Canada;1. Department of Statistical Science at Duke University, Box 90251, Durham NC 27708-0251, USA;2. US Environmental Protection Agency, National Exposure Research Laboratory, Research Triangle Park, NC 27711, USA;1. Miami Cardiac and Vascular Institute, Miami, Florida;2. Department of Radiology, Division of Vascular and Interventional Radiology, Mayo Clinic, 200 1st Street SW, Rochester, MN 55905;3. Department of Radiology, Division of Cardiovascular and Interventional Radiology, Medical University Vienna, Vienna, Austria;4. Center for Research and Grants, Baptist Health South Florida, Coral Gables, Florida. |
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| Abstract: | An automated forecast system for ozone in seven Kentucky metropolitan areas has been operational since 2004. The forecast system automatically downloads the required input data twice each day, produces next-day forecasts of metro area peak 8-h average ozone concentration using a computer coded hybrid nonlinear regression (NLR) model, and posts the results on a website. The automated models were similar to previous NLR models, first applied to forecasting ozone in the Louisville metro area. The forecast system operated reliably during the 2004 and 2005 O3 seasons, producing at least one forecast per day better than 99% of the time. The forecast accuracy of the automated system was good. For all 2004 and 2005 forecasts, the mean absolute error was equal to 8.7 ppb, or 15.6% of the overall mean concentration. The overall detection rate of air quality standard exceedences was 56%, and the overall false alarm rate was 42%. In Louisville, the performance of the automated system was comparable to that of expert forecasters using the NLR model as a forecast tool. |
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