Development of a regression model to forecast ground-level ozone concentration in Louisville, KY

To support ozone forecasting and episodic air pollution control initiatives in the Louisville metropolitan area, a multiple-linear regression model to predict daily domain-peak ground-level ozone concentration [O 3] has been developed and validated. Using only surface meteorological data from 1993–1...

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Bibliographic Details
Published in:Atmospheric environment (1994) 1998-08, Vol.32 (14), p.2637-2647
Main Authors: Hubbard, Milton C., Cobourn, W.Geoffrey
Format: Article
Language:English
Subjects:
air pollution
air quality
Applied sciences
Atmospheric pollution
Exact sciences and technology
Photochemical ozone
Pollutants physicochemistry study: properties, effects, reactions, transport and distribution
Pollution
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Summary:To support ozone forecasting and episodic air pollution control initiatives in the Louisville metropolitan area, a multiple-linear regression model to predict daily domain-peak ground-level ozone concentration [O 3] has been developed and validated. Using only surface meteorological data from 1993–1996 and making extensive use of parametric transformations to improve accuracy, the ten parameter model has a standard error of prediction of 12.1 ppb and an explained variance of 0.70. Retrospective ozone forecasts were made for each day of the four ozone seasons (May–September) using archival meteorological data as input to the model. For the period 1993–1996 examined, 50% of days were forecast to within ±7.6 ppb, and on 80% of days the accuracy was within ±14.8 ppb. The model correctly predicted 74, 80, and 40% of occurrences of the daily “good” ([O 3]⩽60 ppb), “moderate” (60
ISSN:1352-2310
1873-2844
DOI:10.1016/S1352-2310(97)00444-5