Browsing by Subject "Air Quality"
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Item Engineering analysis of the air pollution regulatory process impacts on the agricultural industry(Texas A&M University, 2008-10-10) Lange, Jennifer MarieThe EPA press release dated February 23, 2004 states that the three Buckeye Egg Farm facilities had the potential to emit more than a combined total of 1850 tons per year of particulate matter (PM). This number was based on flowrate calculations that were three times higher than those measured as well as a failure to include particle size distributions in the emissions calculations. The annual PM emission for each facility was approximately 35 tons per year. The EPA was unjustified in requiring Buckeye Egg Farm to obtain Title V and PSD permits as the facilities could not have met the thresholds for these permits. Engineers need to be concerned with correctly measuring and calculating emission rates in order to enforce the current regulations. Consistency among regulators and regulations includes using the correct emission factors for regulatory permitting purposes. EPA has adopted AERMOD as the preferred dispersion model for regulatory use on the premise that it more accurately models the dispersion of pollutants near the surface of the Earth than ISCST3; therefore, it is inappropriate to use the same emission factor in both ISCST3 and AERMOD in an effort to equitably regulate PM sources. For cattle feedlots in Texas, the ISCST3 emission factor is 7 kg/1000 hd-day (16 lb/1000 hd-day) while the AERMOD emission factor is 5 kg/1000 hd-day (11 lb/1000 he-day). The EPA is considering implementing a crustal exclusion for the PM emitted by agricultural sources. Over the next five years, it will be critical to determine a definition of crustal particulate matter that researchers and regulators can agree upon. It will also be necessary to develop a standard procedure to determine the crustal mass fraction of particulate matter downwind from a source to use in the regulatory process. It is important to develop a procedure to determine the particulate matter mass fraction of crustal downwind from a source before the crustal exclusion can be implemented to ensure that the exclusion is being used correctly and consistently among all regulators. According to my findings, the mass fraction of crustal from cattle feedlot PM emissions in the Texas High Plains region is 52%.Item Evaluation of the TEOM method for the measurement of particulate matter for Texas cattle feedlots(2009-05-15) Skloss, Stewart JamesThe Tapered Element Oscillating Microbalance (TEOM) sampler is an EPA approved Federal Equivalent Method Sampler for measuring PM10 concentrations. The Center for Agricultural Air Quality Engineering and Science (CAAQES) owns two Rupprecht and Patashnick (R&P) Series1400a monitors. The R&P Series 1400a monitor uses the TEOM method to measure particulate matter (PM) concentrations and was approved by EPA in 1990 as an automated equivalent method PM10 sampler. Since its approval, many state air pollution regulatory agencies (SAPRAs) have located R&P Series 1400a monitors at community-oriented monitoring sites. Some SAPRAs have even located TEOM samplers at the property line of major sources to determine if the source is meeting its permit requirements for PMc emissions. This thesis presents the results of PM10 and TSP concentrations measured with TEOM and low-volume gravimetric samplers at two Texas cattle feedlots. The purpose of this research was to compare the performance of the R&P Series 1400a monitor to the low-volume gravimetric sampler when sampling PM from a feedlot. Furthermore, this research was conducted to avoid the inappropriate regulation of cattle feedlots that may occur in the future as a consequence of the TEOM sampler being used to measure PMc emissions. The results of this research demonstrate that relationship between the R&P Series 1400a monitor and the low-volume gravimetric sampler is linear. In general, it was observed that the TEOM sampler measured higher PM10 and TSP concentrations than the low-volume gravimetric sampler when sampling downwind from a cattle feedlot. The opposite results were observed when sampling was conducted upwind from the feedlot. The collected data demonstrates that the concentration difference between the two sampling methods is linearly dependent with the concentration intensity for the upwind sampling locations. This trend was shown to be statistically significant. Another linear relationship was observed between the concentration difference and the particle size (mass median diameter and geometric standard deviation) of the sampled dust. Although this trend was not statistically significant, it is believed that additional downwind concentration measurements would validate this relationship.Item Signal Timing Optimization to Improve Air Quality(2012-12-11) Lv, Jinpeng 1983-This study develops an optimization methodology for signal timing at intersections to reduce emissions based on MOVES, the latest emission model released by U.S. Environmental Protection Agency (EPA). The primary objective of this study is to bridge the gap that the research on signal optimization at intersections lags behind the development of emissions models. The methodology development includes four levels: the vehicle level, the movement level, the intersection level, and the arterial level. At the vehicle level, the emission function with respect to delay is derived for a vehicle driving through an intersection. Multiple acceleration models are evaluated, and the best one is selected in terms of emission estimations at an intersection. Piecewise functions are used to describe the relationship between emissions and intersection delay. At the movement level, emissions are modeled if the green time and red time of a movement are given. To account for randomness, the number of vehicle arrivals during a cycle is assumed to follow Poisson distributions. According to the numerical results, the relative difference of emission estimations with and without considering randomness is usually smaller than 5.0% at a typical intersection of two urban arterials. At the intersection level, an optimization problem is formulated to consider emissions at an intersection. The objective function is a linear combination of delay and emissions at an intersection, so that the tradeoff between the two could be examined with the optimization problem. In addition, a convex approximation is proposed to approximate the emission calculation; accordingly, the optimization problem can be solved more efficiently using the interior point algorithm (IPA). The case study proves that the optimization problem with this convex approximation can still find appropriate optimal signal timing plans when considering traffic emissions. At the arterial level, emissions are minimized at multiple intersections along an arterial. First, discrete models are developed to describe the bandwidth, stops, delay, and emissions at a particular intersection. Second, based on these discrete models, an optimization problem is formulated with the intersection offsets as decision variables. The simulation results indicate that the benefit of emission reduction become more and more significant as the number of intersections along the arterial increases.Item Using a Regional Chemical Transport Model for the Analysis of Gaseous and Particulate Air Pollutants in the Mexico City Metropolitan Area(2012-02-14) Ali, Sajjad GhulamAir quality in the Mexico City Metropolitan Area (MCMA) is the subject of many studies due to concerns from high emissions and their adverse effects on public health and the environment. In this study, a high resolution simulation is performed with the Community Multi-scale Air Quality modeling system (CMAQ) using meteorology generated by the Weather Research Forecasting system (WRF). The boundary conditions for CMAQ are provided by the Goddard Earth Observing System-CHEMistry model (GEOS-Chem). The simulation period was March 2-7, 2006. Hourly species concentrations of O3, NOx, CO, SO2, PM10, and PM2.5 for the period were provided by the Automatic Air Quality Monitoring Network (labeled as RAMA). Preliminary evaluation showed GEOS-Chem and CMAQ being in good agreement with their predicted concentrations. In comparison with the base case boundary conditions, the GEOS-Chem case performs better and predicts closer to the observed values of O3, NOx, PM10, PM2.5, and SO2. Particle trajectory analysis was performed using the HYbrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT) to ascertain the major sources of SO2 emitters and their impact on the MCMA.