Dynamic modeling of ozone and particulate matter for Southeast Texas

The formation of ozone and particulate matter in the lower level of earth's surface is dependent on various precursors and weather parameters. This work is to develop a dynamic relationship between ozone concentration and its precursors and weather parameters, and also between particulate matter and its precursors and weather parameters for Southeast Texas. The data was obtained from different monitoring sites of Texas Commission of Environmental Quality (TCEQ). Hourly data and the 8-hour moving average of hourly data were used for the modeling exercise. Aspen IQmodel and MS Excel regression analysis were used for the modeling of data. Compared to pseudo-steady state models, the dynamic models better predict the collected data. The values of R-squares obtained from the Excel regression analysis were better than those from Aspen IQmodel. The R-square obtained for the Excel dynamic ozone model using the hourly data was 0.8767 whereas the R-square obtained for the one using 8-hour moving average data was 0.9746. The values of R-square obtained for the Excel dynamic PM model using hourly data was 0.7786.