published_or_final_version / Public Administration / Master / Master of Public Administration

Mobile source emissions are a major contributor to global and local air pollution. Governments and regulatory agencies have been increasing the stringency of regulations in the transportation sector for the last ten years to help curb transportation sector air pollution. The need for regulations has been emphasized by scientific research on the impacts from ambient pollution, especially research on the effect of particulate matter on human health. The particulate emissions from diesel vehicles, diesel particulate matter (DPM) is considered a known or probable carcinogen in various countries and increased exposure to DPM is linked to increased cardiovascular health problems in humans. The toxicity of vehicle emissions and diesel particulate emissions in particular, in conjunction with an increased awareness of potential petroleum fuel shortages, international conflict over petroleum fuel sources and climate change science, have all contributed to the increase of biodiesel use as an additive to or replacement for petroleum fuel. The goal of this research is to determine how this increased use of biodiesel in the particular emission testing setup impacts urban air quality. To determine if biodiesel use contributes to a health or climate benefit, both the size range and general composition were investigated using a comprehensive comparison of the particulate component of the emissions in real time. The emissions from various biodiesel and diesel mixtures from a common diesel passenger vehicle were measured with a cavity ring-down transmissometer (CRDT) coupled with a condensation particle counter, a SMPS, a nephelometer, NOx, CO, CO2, and O3 measurements. From these data, key emission factors for several biodiesel and diesel fuel mixtures were developed. This approach reduces sampling artifacts and allows for the determination of optical properties, particle number concentration, and size distributions, along with several important gas phase species' concentrations. Findings indicate that biodiesel additions to diesel fuel do not necessarily have an air quality benefit for particulate emissions in this emission testing scenario. The often cited linear decrease in particulate emissions with increasing biodiesel content was not observed. Mixtures with half diesel and half biodiesel tended to have the highest particulate emissions in all size ranges. Mixtures with more than 50% biodiesel had slightly lower calculated mass for light absorbing carbon, but this reduction in mass is most likely a result of a shift in the size of the emission particles to a smaller size range, not a reduction in the total number of particles. Evaluation of the extensive optical properties from this experimental set-up indicates that biodiesel additions to diesel fuel has an impact on emission particle extinction in both visible and near-IR wavelengths. The B99 mixture had the smallest emission factor for extinction at 532 nm and at 1064 nm. For the extinction at 532 nm, the trend was not linear and the emission factor peaked at the B50 mixture. Results from intensive properties indicate that emissions from B5 and B25 mixtures have Ångström exponents close to 1, typical for black carbon emissions. The mixtures with a larger fraction of biodiesel have Ångström exponent values closer to 2, indicating more absorbing organic matter and/or smaller particle size in the emissions. Additional experimental testing should be completed to determine the application of these results and emission factors to other diesel vehicles or types of diesel and biodiesel fuel mixtures.

In 2009, Cobb County School District (CCSD) and Georgia Institute of Technology (Georgia Tech) received a competitive federal grant to implement an idle and tailpipe emission reduction program in the CCSD bus fleet. The project is designed to reduce school bus idling by installing GPS and idle detection systems in the bus, providing bus dispatchers with a web system to track vehicle activity and idling in real-time, and to automatically shut off the engine when idle thresholds at specific locations are exceeded. A team of Georgia Tech researchers is implementing the anti-idle program and estimating the emissions and fuel savings from the project using approved modeling methods. This thesis presents the results of the emission modeling process, as well as an analysis of baseline school bus idling activity. EPA's MOVES mobile source emission model was used to develop emission rates for school buses for each operating mode, which are defined by the instantaneous vehicle speed, acceleration and scaled tractive power. Local data for Cobb County and Atlanta were collected and input into the MOVES model. The pollutants modeled include carbon dioxide, carbon monoxide, particulate matter (coarse and fine), oxides of nitrogen, and gaseous hydrocarbons. The vehicle activity data collected through the GPS and communications equipment installed in the buses were classified into the operating mode bins for each second of recorded data, and multiplied by the corresponding emission rate to determine the total modal emissions before and after project implementation. Preliminary results suggest that thousands of gallons of diesel fuel and thousands of dollars can be saved with the project, improving overall fleet fuel efficiency by 2%, as well as reducing emissions in some categories by as much as 38%.

South Africa is coming under increasing pressure to conform to the rest of the world in terms of emissions regulations. The pressure is caused by a number of factors: international organisations requiring local companies to adhere to environmental conservation policies, evidence from within South Africa that efforts are being made to reduce environmental pollution in line with other countries and keeping abreast of the latest technologies that have been incorporated into vehicles to reduce emissions. In light of these problems associated with emiSSions, a study was initiated by the Department of Transport and the School of Bioresources Engineering and Environmental Hydrology at the University of Natal to investigate and develop a method of predicting emissions from a diesel engine. The main objective of this research was to incorporate this model into SimTrans in order to estimate emissions generated from a vehicle while it is travelling along specific routes in South Africa. SimTrans is a mechanistically based model, developed at the School, that simulates a vehicle travelling along a route, requiring input for the road profile and vehicle and engine specifications. After a preliminary investigation it was decided to use a neural network to predict emissions, as it provides accurate results and is more suitable for a quantitative analysis which is what was required for this study. The emissions that were predicted were NOx (Nitric oxide-NO and Nitric dioxide-N02), CO (carbon monoxide), HC (unbumt hydrocarbons) and particulates. The neural netWork was trained on emissions data obtained from an ADE 447Ti engine. These neural networks were then integrated into the existing SimTrans. Apart from the neural network, an algorithm to consider the effect of ambient conditions on the output of the engine was also included in the model. A sensitivity analysis was carried out using the model to prioritise the factors affecting emissions. Finally using the data for the ADE 447Ti engine, a trip with a Mercedes Benz 2644S-24 was simulated using different scenarios over the routes from Durban to Johannesburg and Cape Town to Johannesburg in South Africa to quantify the emissions that were generated. / Thesis (M.Sc.)-University of Natal, Pietermaritzburg, 2002.

Indiana University-Purdue University Indianapolis (IUPUI) / This paper presents a novel approach of particulate material (soot) measurement in a Diesel particulate filter using Electrical Capacitance Tomography. Modern Diesel Engines are equipped with Diesel Particulate Filters (DPF), as well as on-board technologies to evaluate the status of DPF because complete knowledge of DPF soot loading is very critical for robust efficient operation of the engine exhaust after treatment system. Emission regulations imposed upon all internal combustion engines including Diesel engines on gaseous as well as particulates (soot) emissions by Environment Regulatory Agencies. In course of time, soot will be deposited inside the DPFs which tend to clog the filter and hence generate a back pressure in the exhaust system, negatively impacting the fuel efficiency. To remove the soot build-up, regeneration of the DPF must be done as an engine exhaust after treatment process at pre-determined time intervals. Passive regeneration use exhaust heat and catalyst to burn the deposited soot but active regeneration use external energy in such as injection of diesel into an upstream DOC to burn the soot. Since the regeneration process consume fuel, a robust and efficient operation based on accurate knowledge of the particulate matter deposit (or soot load)becomes essential in order to keep the fuel consumption at a minimum. In this paper, we propose a sensing method for a DPF that can accurately measure in-situ soot load using Electrical Capacitance Tomography (ECT). Simulation results show that the proposed method offers an effective way to accurately estimate the soot load in DPF. The proposed method is expected to have a profound impact in improving overall PM filtering efficiency (and thereby fuel efficiency), and durability of a Diesel Particulate Filter (DPF) through appropriate closed loop regeneration operation.