The Clean Air Act requires the use of complex photochemical models to predict future ozone concentrations and the impact of current and future regulations. In many instances uncertainty in the data input parameters used to operate these models results in uncertainty in the prediction of future air quality. The degree of this uncertainty is often greater than the degreee of air quality improvements proposed by regulations. This study evaluates the sensitivity of a photochemical model to predict future ozone air quality with respect to the uncertainty of several critical input parameters. These parameters are: Transported ozone (ozone aloft) Biogenic emissions (naturally occurring in nature) and anthropogenic (man-made) emissions of oxides of nitrogen (NOx), volatile organic compounds (VOCs) and carbon monoxide (CO). Global sensitivity analyses were done using the United States Environmental Protection Agency (USEPA) Empirical Kinetic Modeling Approach (EKMA) photochemical model to assess the sensitivity in predictions of past (1990), present (1999), and future year (2010) air quality downwind of New York City. Our results show that for present and future years, the uncertainty in the model's prediction of future air quality, (a consequence of the uncertainty in biogenic emissions and ozone aloft) is significantly greater than the difference in emissions as a result of different control strategies proposed by industry and the regulatory agencies for mobile source emissions. The model therefore is not accurate enough to be used to predict changes in air quality that are driven by the proposed more stringent regulations.
Library of Congress Subject Headings
Atmospheric ozone--Mathematical models; Ozone--Environmental aspects; Air quality management; Air--Pollution
Department, Program, or Center
Civil Engineering Technology Environmental Management and Safety (CAST)
Wimer, Daniel, "A Global sensitivity analysis of photochemical models used for predicting tropospheric ozone" (2002). Thesis. Rochester Institute of Technology. Accessed from
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