Browsing by Subject "Air quality modeling"
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Item The characterization of regional ozone transport(2010-05) Dionisio, Mariana Costa; Allen, David T.; McDonald-Buller, Elena C.; Bonnecaze, Roger T.; Webber, Michael E.; Edgar, Thomas F.Among the most ubiquitous and persistent air quality problems facing urban areas are high concentrations of gas phase oxidants and fine particulate matter. Ozone and particulate matter concentrations in urban areas are significantly influenced by other factors in addition to local emissions, such as regional transport spanning distances as large as 1000 kilometers. Despite the importance of regional transport in meeting air quality standards, to date most analyses of regional transport have focused only on short duration episodes, or semi-quantitative assessments. The development and evaluation of seasonal, quantitative assessments of regional pollutant transport, based on modeling calculations and observational data is the topic of this dissertation. The observational data available through the Texas Air Quality Studies in 2000 and 2006 provide a unique opportunity to develop, evaluate, and improve methods for characterizing regional air pollutant transport. Measurements collected during these studies are used as the primary observational basis for characterizing regional ozone transport and to evaluate the performance of photochemical models. Results suggest that measurements (from aircraft and surface monitors) and the photochemical model provide consistent estimates of the magnitude of ozone transport. On this basis, photochemical modeling is used to determine potential impacts of regional ozone transport in Texas, under varying meteorological and photochemical conditions, as well as to characterize the dominant chemical and physical processes within urban plumes. While qualitative studies and limited quantitative analyses have been performed to assess regional ozone transport, this work includes the first detailed quantitative characterization of the importance of ozone transport over the course of an entire ozone season using both photochemical modeling and ambient data. Results demonstrate that urban plumes in Texas are capable of transporting significant amounts of ozone over distances spanning hundreds of kilometers. Furthermore, on a seasonal basis, there are a number of days characterized by high contributions from inter-city transport coinciding with high total ozone concentrations, suggesting that the role of inter-city transport will remain significant for many areas to demonstrate attainment of the NAAQS for ozone. Results also indicate that reductions in the impacts of inter-city transport are possible by decreases in emissions from source regions.Item Neighborhood scale air quality modeling in Corpus Christi using AERMOD and CALPUFF(2010-12) Kim, Hyun Suk; Allen, David T.; McDonald-Buller, ElenaAmbient monitoring and air quality modeling of air toxics concentrations at the neighborhood-scale level is a key element for human exposure and health risk assessments. Since 2005, The University of Texas at Austin (UT) has operated a dense ambient monitoring network that includes both hourly automated gas chromatographs as well as threshold triggered canister samples and meteorological data in the Corpus Christi area. Although Corpus Christi is in attainment with the National Ambient Air Quality Standards for both ozone and fine particulate matter, its significant petroleum refining complex has resulted in concerns about exposure to air toxics. The seven site network, incorporating both the industrial and residential areas in Corpus Christi, provided a unique opportunity to further the development and understanding of air quality modeling for toxic air pollutants at the neighborhood-scale level. Two air dispersion models, AERMOD and CALPUFF, were used to predict air concentrations of benzene for one of the UT operated monitoring sites (Oak Park monitoring site: C634) and the predictions were compared to the observed benzene concentration data at the Oak Park monitoring site to evaluate model performance. AERMOD and CALPUFF were also used to predict benzene concentrations in populated areas and at sensitive receptor locations such as schools and hospitals. Both AERMOD and CALPUFF were able to reproduce the early morning high benzene concentration and the northern wind effect except under strong NNE wind conditions, where the observed data indicated elevated high benzene concentration which AERMOD and CALPUFF failed to predict. These under-predictions could be due to the NNE strong wind condition at that time of these occurrences or could be attributed to different types of emissions other than the point sources emissions from the 2005 TCEQ Photochemical Modeling inventory, such as mobile sources or accidental emission events. These preliminary analyses could be expanded by modeling longer periods, by including other emission sources and by inter-comparisons with observed data from other CCNAT monitoring sites. In addition, fundamentally different modeling approaches (eulerian, rather than lagrangian) could be considered.