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%.

For Heavy-duty vehicles (HDVs), the distribution of vehicle miles traveled (VMT) by vehicle type is the most significant parameters for onroad mobile source emissions modeling used in the development of air quality management and regional transportation plans. There are two approaches for the development of the HDV VMT distribution; one approach uses HDV registration data and annual mileage accumulation rates, and another uses HDV VMT counts/observations collected with the FHWA truck classification. For the purpose of emissions modeling, the FHWA truck classes are converted to those used by the MOBILE6.2 emissions rate model by using either the EPA guidance or the National Research Council conversion factors. However, both these approaches have uncertainties in the development of onroad HDV VMT distributions that can lead to large unknowns in the modeled HDV emissions. This dissertation reports a new heavy-duty vehicle visual classification and activity estimation method that minimizes uncertainties in current HDV conversion methods and the vehicle registration based HDV VMT estimation guidance. The HDV visual classification scheme called the X-scheme, which classifies HDV/truck classes by vehicle physical characteristics (the number of axles, gross vehicle weight ratings, tractor-trailer configurations, etc.) converts FHWA truck classes into EPA HDV classes without losing the original resolution of HDV/truck activity and emission characteristics. The new HDV activity estimation method using publicly available HDV activity databases minimizes uncertainties in the vehicle registration based VMT estimation method suggested by EPA. The analysis of emissions impact with the new method indicates that emissions with the EPA HDV VMT estimation guidance are underestimated by 22.9% and 25.0% for oxides of nitrogen and fine particulate matter respectively within the 20-county Atlanta metropolitan area. Because the new heavy-duty vehicle visual classification and activity estimation method has the ability to provide accurate HDV activity and emissions estimates, this method has the potential to significantly influence policymaking processes in regional air quality management and transportation planning. In addition, the ability to estimate link-specific emissions benefits Federal and local agencies in the development of project (microscale), regional (mesoscale), and national (macroscale) level air quality management and transportation plans.

Environmental indicators were developed and evaluated to assess the impact of mobile sources on emissions, air quality, exposure and health. Different levels of indicators are discussed, from single species to multipollutant indicators. Carbon monoxide (CO), Nitrogen oxides (NOx) and elemental carbon (EC) were chosen as indicators of mobile sources because emissions of these pollutants are largely attributed to mobile sources and ambient concentrations have a close response to the change in mobile source emissions. These pollutants were used in the construction of the integrated mobile source indicators (IMSI). The IMSI have larger spatial representativeness and stronger associations with cardiovascular diseases (CVD) than single pollutants. The use of IMSI in epidemiologic modeling constitutes an alternative approach to assess the health impact of pollutant mixtures and can provide support for the setting of multipollutant air quality standards. The human health benefits of reducing mobile sources emissions were more consistent using multipollutant indicators. Indicator values and uncertainties, in the form of indicator sets, are presented with their associated outcomes and attributes to be useful for policy makers who are interested not only in the value of the indicators, but also in their associated uncertainties and their applicability at other times and other regions.

Thesis (Ph.D)--Public Policy, Georgia Institute of Technology, 2009. / Committee Chair: Noonan, Douglas; Committee Member: Castillo, Marco; Committee Member: Chang, Michael; Committee Member: Cozzens, Susan; Committee Member: Rodgers, Michael. Part of the SMARTech Electronic Thesis and Dissertation Collection.

published_or_final_version / Transport Policy and Planning / Master / Master of Arts in Transport Policy and Planning

published_or_final_version / Politics and Public Administration / Master / Master of Public Administration

The United States Environmental Protection Agency has estimated that over 111 million people reside in areas that exceed the National Ambient Air Quality Standards for ozone. One major source of the chemical precursors (nitrogen dioxides and volatile organic compounds (VOCs)) for ozone are motor vehicles. The overall goal of this research is to improve the knowledge base related to VOC refueling and evaporative emissions from motor vehicles. Refueling, running loss, hot soak, and diurnal loss total and speciated VOC emissions were investigated. A total of 12 uncontrolled refueling events were completed and involved the determination of volumetric flow rates of gasoline vapor during refueling, as well as total and speciated VOC concentrations. Total VOC emissions were compared with two commonly used algorithms. Speciated VOC vapor profiles were compared with two published gasoline vapor profiles and theoretical predictions based on knowledge of liquid composition and environmental conditions. An evaluation of refueling emissions impacts on ozone formation potentials using MIR was completed and results were compared against speciated emissions and MOBILE-based total VOC emissions estimates coupled with a default speciation profile. Refueling VOC emissions and resultant ozone formation potential may be underestimated in existing emission inventories, particularly during the summer ozone season, A model was developed to predict the speciation of VOCs associated with evaporative emissions from motor vehicles. Model-predicted speciation profiles were evaluated using SHED studies. Running loss, hot soak and diurnal emissions were included in each test. Total VOC emissions measured during each test were compared against MOBILE6 predicted emissions. An evaluation of evaporative emissions impacts on ozone formation potentials using MIR was completed, comparing measured and predicted emissions. The measured:predicted speciation results ranged between 0.93 and 1.11 and had an average value of 1.02. For the conditions tested, MOBILE6 underestimated evaporative emissions in 20 of 24 comparisons. MOBILE6-based ozone formation potentials may be underestimated.

published_or_final_version / abstract / toc / Transport Policy and Planning / Master / Master of Arts in Transport Policy and Planning

High Occupancy Toll (HOT) lanes were recently proposed for I-85 in Atlanta as a way to relieve congestion and provide a reliable commute time for single occupant drivers that are willing to pay a toll. It is important to evaluate the air quality impacts of such a proposal to meet environmental regulations, such as the National Environmental Policy Act (NEPA) and Transportation Conformity Regulations. The goal of this study is to understand how vehicle mass emissions change as a result of implementing HOT lanes on I-85 in Atlanta . This is done by considering a number of factors affect mass vehicle emissions, such as vehicle activity, vehicle speeds, vehicle age distributions, and vehicle class distributions. These factors are incorporated into a base scenario, which models the current condition on I-85 with HOV lanes, and a future scenario, which models the implementation of HOT lanes on this corridor. The base scenario mainly uses data from a data collection effort by Georgia Tech during the summer of 2007 on the I-85 corridor, while the future scenario makes alterations to these data using information from other cities that have already implemented HOT lanes. The MOBILE-Matrix modeling tool, which was recently developed by Georgia Tech [16], was used to run the emissions analysis using the input factors from these data sources. This tool calculated mass emissions for five pollutants: HC, NOx, CO, PM2.5, and PM10. The results show very small increases in mass emissions for NOx, CO, PM2.5, and PM10, and very small decreases in mass emissions for HC. Therefore, the implementation of HOT lanes on I-85 in Atlanta is unlikely to violate the Transportation Conformity Rule. For NEPA purposes, this analysis could be used to make the case that air quality impacts are not significant, and therefore further detailed analyses are not required.