Browsing by Subject "dispersion modeling"
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Item Comparison of Aermod and ISCST3 Models for Particulate Emissions from Ground Level Sources(2010-07-14) Botlaguduru, Venkata Sai V.Emission factors (EFs) and results from dispersion models are key components in the air pollution regulatory process. The EPA preferred regulatory model changed from ISCST3 to AERMOD in November, 2007. Emission factors are used in conjunction with dispersion models to predict 24-hour concentrations that are compared to National Ambient Air Quality Standards (NAAQS) for determining the required control systems in permitting sources. This change in regulatory models has had an impact on the regulatory process and the industries regulated. In this study, EFs were developed for regulated particulate matter PM10 and PM2.5 from cotton harvesting. Measured concentrations of TSP and PM10 along with meteorological data were used in conjunction with the dispersion models ISCST3 and AERMOD, to determine the emission fluxes from cotton harvesting. The goal of this research was to document differences in emission factors as a consequence of the models used. The PM10 EFs developed for two-row and six-row pickers were 154 + 43 kg/km2 and 425 + 178 kg/km2, respectively. From the comparison between AERMOD and ISCST3, it was observed that AERMOD EFs were 1.8 times higher than ISCST3 EFs for Emission factors (EFs) and results from dispersion models are key components in the air pollution regulatory process. The EPA preferred regulatory model changed from ISCST3 to AERMOD in November, 2007. Emission factors are used in conjunction with dispersion models to predict 24-hour concentrations that are compared to National Ambient Air Quality Standards (NAAQS) for determining the required control systems in permitting sources. This change in regulatory models has had an impact on the regulatory process and the industries regulated. In this study, EFs were developed for regulated particulate matter PM10 and PM2.5 from cotton harvesting. Measured concentrations of TSP and PM10 along with meteorological data were used in conjunction with the dispersion models ISCST3 and AERMOD, to determine the emission fluxes from cotton harvesting. The goal of this research was to document differences in emission factors as a consequence of the models used. The PM10 EFs developed for two-row and six-row pickers were 154 + 43 kg/km2 and 425 + 178 kg/km2, respectively. From the comparison between AERMOD and ISCST3, it was observed that AERMOD EFs were 1.8 times higher than ISCST3 EFs for absence of solar radiation. Using AERMOD predictions of pollutant concentrations off property for regulatory purposes will likely affect a source?s ability to comply with limits set forth by State Air Pollution Regulatory Agencies (SAPRAs) and could lead to inappropriate regulation of the source.Item Modeling of Particulate Matter Emissions from Agricultural Operations(2013-01-02) Bairy, Jnana 1988-State Air Pollution Regulation Agencies (SAPRAs) issue and enforce permits that limit particulate matter emissions from all sources including layer and broiler facilities, cattle feedyards, dairies, cotton gins, and grain elevators. In this research, a process was developed to determine distances from emitting sources to where the estimated concentrations were less than the National Ambient Air Quality Standards (NAAQS). These distances are a function of emission rates and meteorological conditions. Different protocols were used to develop emission factors for cattle feedyards and layer houses. Dispersion modeling with American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) was conducted to determine the emissions of particulate matter. These data were used to determine the distances from the sources to where the concentrations of particulate matter (PM) would be less than the NAAQS. The current air-permitting process requires that concentrations from a source do not exceed the NAAQS at the property line and beyond for the facility to be in compliance with its permit conditions. Emission factors for particulate matter less than 10 micrometers (PM10) were developed for cattle feedyards using a reverse modeling protocol and Tapered Element Oscillating Microbalance (TEOM) sampler data. Corrections were applied to the TEOM measurements to account for TEOM vs. filter-based low-volume (FBLV) sampler bias and over-sampling of PM10 pre-collectors. Invalid concentrations and dust peaks larger than mean ? 3 times the standard deviation were excluded from this study. AERMOD predictions of downwind concentrations at cotton gins were observed for compliance with 24-hour PM10 and PM2.5 NAAQS at property lines. The emissions from three cotton gins were analyzed at 50 m and 100 m distances. TEOM and FBLV samplers were used to collect 24-hour PM10 measurements inside a laying hen house. The distances to the property lines at which the emissions of PM10 were below the 24-hour average PM10 standards were estimated using AERMOD. The results suggested that the special use of the NAAQS for as the property-line concentration not to be exceeded, could be problematic to agriculture. Emission factors that were comparable of published emission factors were obtained in this study. Large distances to property lines were required when minimum flow rate recommendations were not considered. Emission factors that are representative of the emissions in a particular facility are essential; else facilities could be inappropriately regulated.Item Study of the Effects of Obstacles in Liquefied Natural Gas (LNG) Vapor Dispersion using CFD Modeling(2012-10-19) Ruiz Vasquez, RobertoThe evaluation of the potential hazards related with the operation of an LNG terminal includes possible release scenarios with the consequent flammable vapor dispersion within the facility; therefore, it is important to know the behavior of this phenomenon through the application of advanced simulation tools. Computational Fluid Dynamic (CFD) tools are often used to estimate the exclusion zones in an event of accidental LNG spill. In practice these releases are more likely to occur in the confines of complex geometries with solid obstacles such as LNG terminals, and LNG processing plants. The objective of this research is to study the effects that different obstacles have over the LNG vapor dispersion and the safety distance reduction caused by enhanced mixing. Through parametric analysis it is demonstrated that height, width and shape of the obstacles play an important role in the vapor concentration reduction. The findings of this research may be applied in the design stage of an LNG terminal, to improve the design of passive barriers, and for designing better layout configurations for storage tanks. Simulations results performed with FLACS (Flame Acceleration Simulator), a CFD solver, confirmed that these applications help to reduce safety distances.