Browsing by Subject "air quality"
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Item Ambient Measurements of the NOx Reservoir Species N2O5 using Cavity Ring-down Spectroscopy(2012-10-19) Geidosch, Justine NicoleThe regulated control of pollutants is essential to maintaining good air quality in urban areas. A major concern is the formation of tropospheric ozone, which can be especially harmful to those with lung conditions and has been linked to the occurrence of asthma. Ozone is formed through reactions of oxidized volatile organic compounds with nitrogen oxides, and the accurate modeling of the process is necessary for smart and effective regulations. Ambient measurements are important to understanding the mechanisms involved in tropospheric chemistry. This dissertation describes the characterization of a novel instrument for the ambient measurement of dinitrogen pentoxide, N2O5, and the results of several field studies. This is an important intermediate in the major nighttime loss pathway of nitrogen oxides. The understanding of this process requires correct modeling formation, as any nitrogen oxides not removed at night will result in increased ozone formation at sunrise. Calibration studies have been performed in order to quantify the loss of reactive species within the instrument, and the sampling flow and N2O5 detection have been well characterized. The results of the laboratory measurements are presented. Results are presented from the SHARP Field Study in Houston, TX in the spring of 2009. N2O5 measurements are compared to measurements of other species, including nitric acid and nitryl chloride, which were performed by other research groups. Mixing ratios exceeding 300 ppt were observed following ozone exceedance days, and a dependence of the concentration on both wind speed and direction was noticed. There was a strong correlation determined between N2O5 with HNO3 and ClNO2 indicating both a fast heterogeneous hydrolysis and N2O5 as the primary source of the species. Observed atmospheric lifetimes for N2O5 were short, ranging from several seconds to several minutes. We have also investigated the presence of N2O5 in College Station, TX. Low mixing ratios peaking at approximately 20 ppt were observed, with longer atmospheric lifetimes of up to several hours. The role of biogenic emissions in the NO3-N2O5 equilibrium is discussed.Item Back-calculating emission rates for ammonia and particulate matter from area sources using dispersion modeling(Texas A&M University, 2004-11-15) Price, Jacqueline ElaineEngineering directly impacts current and future regulatory policy decisions. The foundation of air pollution control and air pollution dispersion modeling lies in the math, chemistry, and physics of the environment. Therefore, regulatory decision making must rely upon sound science and engineering as the core of appropriate policy making (objective analysis in lieu of subjective opinion). This research evaluated particulate matter and ammonia concentration data as well as two modeling methods, a backward Lagrangian stochastic model and a Gaussian plume dispersion model. This analysis assessed the uncertainty surrounding each sampling procedure in order to gain a better understanding of the uncertainty in the final emission rate calculation (a basis for federal regulation), and it assessed the differences between emission rates generated using two different dispersion models. First, this research evaluated the uncertainty encompassing the gravimetric sampling of particulate matter and the passive ammonia sampling technique at an animal feeding operation. Future research will be to further determine the wind velocity profile as well as determining the vertical temperature gradient during the modeling time period. This information will help quantify the uncertainty of the meteorological model inputs into the dispersion model, which will aid in understanding the propagated uncertainty in the dispersion modeling outputs. Next, an evaluation of the emission rates generated by both the Industrial Source Complex (Gaussian) model and the WindTrax (backward-Lagrangian stochastic) model revealed that the calculated emission concentrations from each model using the average emission rate generated by the model are extremely close in value. However, the average emission rates calculated by the models vary by a factor of 10. This is extremely troubling. In conclusion, current and future sources are regulated based on emission rate data from previous time periods. Emission factors are published for regulation of various sources, and these emission factors are derived based upon back-calculated model emission rates and site management practices. Thus, this factor of 10 ratio in the emission rates could prove troubling in terms of regulation if the model that the emission rate is back-calculated from is not used as the model to predict a future downwind pollutant concentration.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 Source Contributions to VOC's to Ozone Formation in Southeast Texas Using a Source-oriented Air Quality Model(2011-08-08) Krishnan, AnupamaHouston-Galveston-Brazoria area is in severe non-attainment status for ozone compliance. Source-oriented mechanistic modeling was used to determine the major sources of VOCs that contributes to ozone formation during the Texas Air Quality Study (TexAQS) from August 16, 2000 to September 7, 2000. Environmental Protection Agency (EPA)?s Community Scale Air Quality Model (CMAQ) version 4.6 was used as a host model to include a revised Statewide Air Pollution Research Center (SAPRC99) photochemical mechanism with source-oriented extensions to track the contributions of Volatile Organic Compounds (VOCs) emissions from diesel engines, biogenic sources, highway gasoline vehicles, fuel combustion, off-highway gasoline engines, solvent utilization and petrochemical industries to ozone formation in the atmosphere. Source-oriented emissions needed to drive the model were generated using a revised Sparse Matrix Operator Kernel Emissions (SMOKE) model version 2.4. VOC/NOx ratios are found to be a critical factor in the formation of ozone. Highest ozone formation rates were observed for ratios from 5-15. The contributions of VOC to ozone formation were estimated based on the linear relationship between the rate of NO to NO2 conversion due to radicals generated from VOC oxidation and the rate of net ozone formation. Petroleum and other industrial sources are the largest anthropogenic sources in the urban Houston region and contribute to 45% of the ozone formation in the HGB area. Highway gasoline vehicles make contributions of approximately 28% to ozone formation. Wildfires contribute to as much 11% of ozone formation on days of high wildfire activity. The model results show that biogenic emissions account for a significant amount of ozone formation in the rural areas. Both highway and off-highway vehicles contribute significantly to ozone formation especially in the downwind region. Diesel vehicles do not contribute significantly to ozone formation due to their low VOC emissions.Item Using Local and Regional Air Quality Modeling and Source Apportionment Tools to Evaluate Vehicles and Biogenic Emission Factors(2014-07-25) Kota, Sri HCarbon Monoxide (CO), oxides of nitrogen (NO_(x)) and volatile organic compounds (VOCs) affect human health, and can also play a significant role in tropospheric ozone and secondary particulate matter formation. Correctly estimating the anthropogenic emission rates of these species is important for their effective control. Additionally, isoprene from biogenic sources also plays a key role in tropospheric ozone and secondary organic aerosol (SOA) formation. In this study, emission factors and inventories of CO, NO_(x) and VOCs from on-road vehicles estimated by vehicle emission factor models and biogenic emissions of isoprene estimated by a popular biogenic emission model are evaluated using local and regional scale air quality modeling and source apportionment tools supplemented by concentration and flux data collected at surface and in the upper air. The USEPA?s Motor Vehicle Emission Simulator (MOVES) model is evaluated. Local scale analysis indicates over-estimation of NO_(x) by approximately 15%, based on the curbside data collected near a high diesel traffic rural highway and the predicted NO_(x) by the TAMU Near-Road Model. The regional scale analysis conducted using the observed NO_(x) at a number of surface air quality monitoring sites in southeast Texas (ST) and a source-oriented Community Air Quality Model (SCMAQ), a regional chemical transport model, suggests an over-estimation of NO_(x) emissions by approximately 35-55% using the MOVES-based NEI. The near-road analysis also reveals that NO_(2)/NO_(x) ratio at curbside is approximately 29%, much higher than the generally used 5% ratio. This increase in ratio resulted in predicted 8-hour ozone increase in ST by as much as 6 ppb. While the near-road analysis didn?t reveal significant overestimation in CO emissions due to high background concentrations and low emissions, the regional analysis showed that CO emission were overestimated by approximately 60% by the MOVES model. Finally, VOC emissions estimated by the MOVES model were evaluated using fluxes of 18 VOCs measured on a tall tower in urban Houston during 2008. Vehicle contributions to the observed flux were determined using the Multilinear Engine (ME-2), a receptor-oriented source apportionment model. Emission factors of vehicle exhaust and evaporative emissions were estimated using a flux footprint model and the contributions resolved by ME-2. The MOVES model estimates vehicle exhaust emissions well, but severely under-estimates evaporative emissions from parked vehicles. The Model of Emissions of Gases and Aerosol from Nature (MEGAN) estimations of isoprene, the dominant biogenic VOC, in ST were also evaluated using SCMAQ. Comparison of predicted and observed isoprene concentrations at the surface layer and upper layers revealed a significant over-prediction of isoprene in urban areas and necessity of decreasing biogenic emission reduction by 2/3rd. The over-predictions of isoprene had negligible effects on predicted ozone concentrations in ST, but the isoprene generated SOA can be overestimated by as much as 50%.