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U.S. Department of Energy
Office of Scientific and Technical Information

Development of an ozone forecasting model for the San Joaquin Valley

Conference ·
OSTI ID:362006
 [1]
  1. ENVIRON International Corp., Novato, CA (United States)

In an effort to limit incidences of high ambient ozone concentrations, the San Joaquin Valley Unified Air Pollution Control District in central California developed a Spare the Air program similar to programs currently in-use or under development at a number of other districts around the country. Under this type of voluntary program, a Spare the Air alert is declared whenever weather conditions conducive to the formation of ozone levels close to or above the National Ambient Air Quality Standard for ozone are expected to occur. The alerts urge the public to take steps that reduce ozone precursor emissions and shift emissions from morning/midday hours to the late afternoon or early evening. Implementation of these types of programs requires that accurate forecasts of meteorological conditions conducive to peak ozone events be made at least one day in advance to allow sufficient time for air quality district personnel to contact major employers and alert the news media. A statistical forecast model for same day and next day peak ozone concentrations in the San Joaquin Valley was developed for this purpose. A five year historical database of ozone concentrations and associated meteorological parameters from stations throughout central and southern California and western Nevada was assembled and analyzed. Several types of statistical forecast models were fitted to these data and evaluated. These included linear and log-linear regression models, logistic regression models, and a neural network model. Models were developed for both same-day and next-day peak ozone predictions. The selected statistical models were then implemented in a Microsoft Access database program which allows the user to enter the relevant meteorological parameters, compute and output the forecast ozone levels, and store all of the relevant data for future analysis.

OSTI ID:
362006
Report Number(s):
CONF-980632--
Country of Publication:
United States
Language:
English