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ABSTRACTWith the National Aeronautics and Space Administration (NASA) Psyche Mission, humans will soon have the first opportunity to explore a new kind of planetary body: one composed mostly of metal as opposed to stony minerals or ices. Identifying the composition of asteroids from Earth-based observations has been an ongoing challenge. Although optical reflectance spectra, radar, and orbital dynamics can constrain an asteroid’s mineralogy and bulk density, in many cases there is not a clear or precise match with analogous materials such as meteorites. Additionally, the surfaces of asteroids and other small, airless planetary bodies can be heavily modified over geologic time by exposure to the space environment. To accurately interpret remote sensing observations of metal-rich asteroids, it is therefore necessary to understand how the processes active on asteroid surfaces affect metallic materials. This dissertation represents a first step toward that understanding. In collaboration with many colleagues, I have performed laboratory experiments on iron meteorites to simulate solar wind ion irradiation, surface heating, micrometeoroid bombardment, and high-velocity impacts. Characterizing the meteorite surface’s physical and chemical properties before and after each experiment can constrain the effects of each process on a metal-rich surface in space. While additional work will be needed for a complete understanding, it is nevertheless possible to make some early predictions of what (16) Psyche’s surface regolith might look like when humans observe it up close. Moreover, the results of these experiments will inform future exploration beyond asteroid Psyche as humans attempt to understand how Earth’s celestial neighborhood came to be.
ContributorsChristoph, John Morgan M. (Author) / Elkins-Tanton, Linda (Thesis advisor) / Williams, David (Committee member) / Dukes, Catherine (Committee member) / Sharp, Thomas (Committee member) / Bell III, James (Committee member) / Arizona State University (Publisher)
Created2023
Description
Bicycle sharing systems (BSS) operate on five continents, and they change quickly with technological innovations. The newest “dockless” systems eliminate both docks and stations, and have become popular in China since their launch in 2016. The rapid increase in dockless system use has exposed its drawbacks. Without the order imposed by docks and stations, bike parking has become problematic. In the areas of densest use, the central business districts of large cities, dockless systems have resulted in chaotic piling of bikes and need for frequent rebalancing of bikes to other locations. In low-density zones, on the other hand, it may be difficult for customers to find a bike, and bikes may go unused for long periods. Using big data from the Mobike BSS in Beijing, I analyzed the relationship between building density and the efficiency of dockless BSS. Density is negatively correlated with bicycle idle time, and positively correlated with rebalancing. Understanding the effects of density on BSS efficiency can help BSS operators and municipalities improve the operating efficiency of BSS, increase regional cycling volume, and solve the bicycle rebalancing problem in dockless systems. It can also be useful to cities considering what kind of BSS to adopt.
ContributorsCui, Wencong (Author) / Kuby, Michael (Thesis advisor) / Salon, Deborah (Committee member) / Thigpen, Calvin (Committee member) / Arizona State University (Publisher)
Created2018
Description
Bicyclist and pedestrian safety is a growing concern in San Francisco, CA,
especially given the increasing numbers of residents choosing to bike and walk. Sharing
the roads with automobiles, these alternative road users are particularly vulnerable to
sustain serious injuries. With this in mind, it is important to identify the factors that
influence the severity of bicyclist and pedestrian injuries in automobile collisions. This
study uses traffic collision data gathered from California Highway Patrol’s Statewide
Integrated Traffic Records System (SWITRS) to predict the most important
determinants of injury severity, given that a collision has occurred. Multivariate binomial
logistic regression models were created for both pedestrian and bicyclist collisions, with
bicyclist/pedestrian/driver characteristics and built environment characteristics used as
the independent variables. Results suggest that bicycle infrastructure is not an important
predictor of bicyclist injury severity, but instead bicyclist age, race, sobriety, and speed
played significant roles. Pedestrian injuries were influenced by pedestrian and driver age
and sobriety, crosswalk use, speed limit, and the type of vehicle at fault in the collision.
Understanding these key determinants that lead to severe and fatal injuries can help
local communities implement appropriate safety measures for their most susceptible
road users.
especially given the increasing numbers of residents choosing to bike and walk. Sharing
the roads with automobiles, these alternative road users are particularly vulnerable to
sustain serious injuries. With this in mind, it is important to identify the factors that
influence the severity of bicyclist and pedestrian injuries in automobile collisions. This
study uses traffic collision data gathered from California Highway Patrol’s Statewide
Integrated Traffic Records System (SWITRS) to predict the most important
determinants of injury severity, given that a collision has occurred. Multivariate binomial
logistic regression models were created for both pedestrian and bicyclist collisions, with
bicyclist/pedestrian/driver characteristics and built environment characteristics used as
the independent variables. Results suggest that bicycle infrastructure is not an important
predictor of bicyclist injury severity, but instead bicyclist age, race, sobriety, and speed
played significant roles. Pedestrian injuries were influenced by pedestrian and driver age
and sobriety, crosswalk use, speed limit, and the type of vehicle at fault in the collision.
Understanding these key determinants that lead to severe and fatal injuries can help
local communities implement appropriate safety measures for their most susceptible
road users.
ContributorsMcIntyre, Andrew (Author) / Salon, Deborah (Thesis advisor) / Kuby, Mike (Committee member) / Chester, Mikhail (Committee member) / Arizona State University (Publisher)
Created2016
Description
With high potential for automobiles to cause air pollution and greenhouse gas emissions, there is concern that automobiles accessing or egressing public transportation may cause emissions similar to regular automobile use. Due to limited literature and research that evaluates and discusses environmental impacts from first and last mile portions of transit trips, there is a lack of understanding on this topic. This research aims to comprehensively evaluate the life cycle impacts of first and last mile trips on multimodal transit. A case study of transit and automobile travel in the greater Los Angeles region is evaluated by using a comprehensive life cycle assessment combined with regional household travel survey data to evaluate first-last mile trip impacts in multimodal transit focusing on automobile trips accessing or egressing transit. First and last mile automobile trips were found to increase total multimodal transit trip emissions by 2 to 12 times (most extreme cases were carbon monoxide and volatile organic compounds). High amounts of coal-fired energy generation can cause electric propelled rail trips with automobile access or egress to have similar or more emissions (commonly greenhouse gases, sulfur dioxide, and mono-nitrogen oxides) than competing automobile trips, however, most criteria air pollutants occur remotely. Methods to reduce first-last mile impacts depend on the characteristics of the transit systems and may include promoting first-last mile carpooling, adjusting station parking pricing and availability, and increased emphasis on walking and biking paths in areas with low access-egress trip distances.
ContributorsHoehne, Christopher G (Author) / Chester, Mikhail V (Thesis advisor) / Salon, Deborah (Committee member) / Zhou, Xuesong (Committee member) / Arizona State University (Publisher)
Created2016
Description
Economic inequality is always presented as how economic metrics vary amongst individuals in a group, amongst groups in a population, or amongst some regions. Economic inequality can substantially impact the social environment, socioeconomics as well as human living standard. Since economic inequality always plays an important role in our social environment, its study has attracted much attention from scholars in various research fields, such as development economics, sociology and political science. On the other hand, economic inequality can result from many factors, phenomena, and complex procedures, including policy, ethnic, education, globalization and etc. However, the spatial dimension in economic inequality research did not draw much attention from scholars until early 2000s. Spatial dependency, perform key roles in economic inequality analysis. The spatial econometric methods do not merely convey a consequence of the characters of the data exclusively. More importantly, they also respect and quantify the spatial effects in the economic inequality. As aforementioned, although regional economic inequality starts to attract scholars' attention in both economy and regional science domains, corresponding methodologies to examine such regional inequality remain in their preliminary phase, which need substantial further exploration. My thesis aims at contributing to the body of knowledge in the method development to support economic inequality studies by exploring the feasibility of a set of new analytical methods in use of regional inequality analysis. These methods include Theil's T statistic, geographical rank Markov and new methods applying graph theory. The thesis will also leverage these methods to compare the inequality between China and US, two large economic entities in the world, because of the long history of economic development as well as the corresponding evolution of inequality in US; the rapid economic development and consequent high variation of economic inequality in China.
ContributorsWang, Sizhe (Author) / Rey, Sergio J (Thesis advisor) / Li, Wenwen (Committee member) / Salon, Deborah (Committee member) / Arizona State University (Publisher)
Created2016
Description
Transportation infrastructure in urban areas has significant impacts on socio-economic activities, land use, and real property values. This dissertation proposes a more comprehensive theory of the positive and negative relationships between property values and transportation investments that distinguishes different effects by mode (rail vs. road), by network component (nodes vs. links), and by distance from them. It hypothesizes that transportation investment generates improvement in accessibility that accrue only to the nodes such as highway exits and light rail stations. Simultaneously, it tests the hypothesis that both transport nodes and links emanate short-distance negative nuisance effects due to disamenities such as traffic and noise. It also tests the hypothesis that nodes of both modes generate a net effect combining accessibility and disamenities. For highways, the configuration at grade or above/below ground is also tested. In addition, this dissertation hypothesizes that the condition of road pavement may have an impact on residential property values adjacent to the road segments. As pavement condition improves, value of properties adjacent to a road are hypothesized to increase as well. A multiple-distance-bands approach is used to capture distance decay of amenities and disamenities from nodes and links; and pavement condition index (PCI) is used to test the relationship between road condition and residential property values. The hypotheses are tested using spatial hedonic models that are specific to each of residential and commercial property market. Results confirm that proximity to transport nodes are associated positively with both residential and commercial property values. As a function of distance from highway exits and light rail transit (LRT) stations, the distance-band coefficients form a conventional distance decay curve. However, contrary to our hypotheses, no net effect is evident. The accessibility effect for highway exits extends farther than for LRT stations in residential model as expected. The highway configuration effect on residential home values confirms that below-grade highways have relatively positive impacts on nearby houses compared to those at ground level or above. Lastly, results for the relationship between pavement condition and residential home values show that there is no significant effect between them.
Some differences in the effect of infrastructure on property values emerge between residential and commercial markets. In the commercial models, the accessibility effect for highway exits extends less than for LRT stations. Though coefficients for short distances (within 300m) from highways and LRT links were expected to be negative in both residential and commercial models, only commercial models show a significant negative relationship. Different effects by mode, network component, and distance on commercial submarkets (i.e., industrial, office, retail and service properties) are tested as well and the results vary based on types of submarket.
Consequently, findings of three individual paper confirm that transportation investments mostly have significant impacts on real-estate properties either in a positive or negative direction in accordance with the transport mode, network component, and distance, though effects for some conditions (e.g., proximity to links of highway and light rail, and pavement quality) do not significantly change home values. Results can be used for city authorities and planners for funding mechanisms of transport infrastructure or validity of investments as well as private developers for maximizing development profits or for locating developments.
Some differences in the effect of infrastructure on property values emerge between residential and commercial markets. In the commercial models, the accessibility effect for highway exits extends less than for LRT stations. Though coefficients for short distances (within 300m) from highways and LRT links were expected to be negative in both residential and commercial models, only commercial models show a significant negative relationship. Different effects by mode, network component, and distance on commercial submarkets (i.e., industrial, office, retail and service properties) are tested as well and the results vary based on types of submarket.
Consequently, findings of three individual paper confirm that transportation investments mostly have significant impacts on real-estate properties either in a positive or negative direction in accordance with the transport mode, network component, and distance, though effects for some conditions (e.g., proximity to links of highway and light rail, and pavement quality) do not significantly change home values. Results can be used for city authorities and planners for funding mechanisms of transport infrastructure or validity of investments as well as private developers for maximizing development profits or for locating developments.
ContributorsSeo, Kihwan (Author) / Michael, Kuby (Thesis advisor) / Golub, Aaron (Committee member) / Salon, Deborah (Committee member) / Arizona State University (Publisher)
Created2016
Description
Informal public transport is commonplace in the developing world, but the service exists in the United States as well, and is understudied. Often called "dollar vans", New York's commuter vans serve approximately 120,000 people every day (King and Goldwyn, 2014). While this is a tiny fraction of the New York transit rider population, it is comparable to the total number of commuters who ride transit in smaller cities such as Minneapolis/St Paul and Phoenix. The first part of this study reports on the use of commuter vans in Eastern Queens based on a combination of surveys and a ridership tally, all conducted in summer 2016. It answers four research questions: How many people ride the vans? Who rides the commuter vans? Why do they ride commuter vans? Do commuter vans complement or compete against formal transit? Commuter van ridership in Eastern Queens was approximately 55,000 with a high percentage of female ridership. Time and cost savings were the main factors influencing commuter van ridership. Possession of a MetroCard was shown to negatively affect the frequency of commuter van ridership. The results show evidence of commuter vans playing both a competing and complementary role to MTA bus and subway transit. The second part of this study presents a SWOT analysis results of commuter vans, and the policy implications. It answers 2 research questions: What are the main strengths, weaknesses, opportunities and threats of commuter vans in Eastern Queens? and How do the current policies, rules and regulations affect commuter van operation? The SWOT analysis results show that the commuter van industry is resilient, performs a necessary service, and, with small adjustments that will help reduce operating costs and loss of profits have a chance of thriving in Eastern Queens and the rest of New York City. The study also discusses the mismatch between policy and practice offering recommendations for improvement to ensure that commuter vans continue to serve residents of New York City.
ContributorsMusili, Catherine (Author) / Salon, Deborah (Thesis advisor) / King, David (Committee member) / Kelley, Jason (Committee member) / Arizona State University (Publisher)
Created2017
Description
Walking and bicycling bring many merits to people, both physically and mentally.
However, not everyone has an opportunity to enjoy healthy and safe bicycling and
walking. Many studies suggested that access to healthy walking and bicycling is heavily
related to socio-economic status. Low income population and racial minorities have
poorer transportation that results in less walking and bicycling, as well as less access to
public transportation. They are also under higher risks of being hit by vehicles while
walking and bicycling. This research quantifies the relationship between socioeconomic
factors and bicyclist and pedestrian involved traffic crash rates in order to establish an
understanding of how equitable access to safe bicycling and walking is in Phoenix. The
crash rates involving both bicyclists and pedestrians were categorized into two groups,
minor crashes and severe crashes. Then, the OLS model was used to analyze minor and
severe bicycle crash rates, and minor and severe pedestrian crash rates, respectively.
There are four main results, (1) The median income of an area is always negatively
related to the crash rates of bicyclists and pedestrians. The reason behind the negative
correlation is that there is a very small proportion of people choosing to walk or ride
bicycles as their commuting methods in the high-income areas. Consequently, there are
low crash rates of pedestrians and bicyclists. (2) The minor bicycle crash rates are more
related to socio-economic determinants than the severe crash rates. (3) A higher
population density reduces both the minor and the severe crash rates of bicyclists and
pedestrians in Phoenix. (4) A higher pedestrian commuting ratio does not reduce bicyclist
and pedestrian crash rates in Phoenix. The findings from this study can provide a
reference value for the government and other researchers and encourage better future
decisions from policy makers.
However, not everyone has an opportunity to enjoy healthy and safe bicycling and
walking. Many studies suggested that access to healthy walking and bicycling is heavily
related to socio-economic status. Low income population and racial minorities have
poorer transportation that results in less walking and bicycling, as well as less access to
public transportation. They are also under higher risks of being hit by vehicles while
walking and bicycling. This research quantifies the relationship between socioeconomic
factors and bicyclist and pedestrian involved traffic crash rates in order to establish an
understanding of how equitable access to safe bicycling and walking is in Phoenix. The
crash rates involving both bicyclists and pedestrians were categorized into two groups,
minor crashes and severe crashes. Then, the OLS model was used to analyze minor and
severe bicycle crash rates, and minor and severe pedestrian crash rates, respectively.
There are four main results, (1) The median income of an area is always negatively
related to the crash rates of bicyclists and pedestrians. The reason behind the negative
correlation is that there is a very small proportion of people choosing to walk or ride
bicycles as their commuting methods in the high-income areas. Consequently, there are
low crash rates of pedestrians and bicyclists. (2) The minor bicycle crash rates are more
related to socio-economic determinants than the severe crash rates. (3) A higher
population density reduces both the minor and the severe crash rates of bicyclists and
pedestrians in Phoenix. (4) A higher pedestrian commuting ratio does not reduce bicyclist
and pedestrian crash rates in Phoenix. The findings from this study can provide a
reference value for the government and other researchers and encourage better future
decisions from policy makers.
ContributorsWu, Feiyi (Author) / Nelson, Trisalyn (Thesis advisor) / Salon, Deborah (Committee member) / Kuby, Michael (Committee member) / Arizona State University (Publisher)
Created2020
Description
Since the mid-2000s, the domestic aviation industry has been influenced by new, rapidly growing ultra low-cost carriers (ULCCs) such as Allegiant Air, Spirit Airlines, and Frontier Airlines. These carriers augment the existing low-cost airline model by operating largely point-to-point routes with a minimum of passenger amenities. Existing literature, however, is limited for North American ULCCs, often lumping them together with mainstream low-cost carriers. The pattern of markets served by ULCCs is incongruous with the models of other airlines and requires further research to examine causal factors. This paper sought to establish conclusions about ULCCs and the relevant market factors used for airport choice decisions.The relationship between ULCC operations and airport choice factors was analyzed using three methods: a collection of 2019 flight data to establish existing conditions and statistics, two regression analyses to evaluate airport market variables, and three case studies examining distinct scenarios through qualitative interviews with airport managers. ULCC enplanement data was assembled for every domestic airport offering scheduled ULCC service in 2019. Independent variable data informed by previous research were collected for every Part 139 airport in the U.S. The first regression analysis estimated a OLS regression model to analyze the log of enplanements. The second model estimated a binary logistic equation for ULCC service as a 0-1 dependent variable. Case studies for Bellingham, Washington, Waco, Texas, and Lincoln, Nebraska were selected based on compelling airport factors and relevant ULCC experience.
Results of the research methods confirm certain theories regarding ULCC airport choice, but left others unanswered. Maps of enplanements and market share revealed concentrations of ULCC operations on the East Coast. Each regression analysis showed a strong and positive relationship between population figures and the existence and quantity of ULCC operations. Tourism employment was only significantly related to enplanements. Other factors including distance and competition variables were significantly associated to ULCC service. Case studies revealed the importance of airport fees and costs in ULCC decision-making; factors that proved difficult to investigate quantitatively in this research. Further research may shed light on this complex and ever- changing subset of the domestic commercial aviation industry.
ContributorsTaplin, Drew (Author) / Kuby, Michael (Thesis advisor) / King, David (Committee member) / Salon, Deborah (Committee member) / Arizona State University (Publisher)
Created2021
Description
Urban areas across the Unites States are facing a housing affordability crisis. One approach some cities and states have taken is to reduce or eliminate single-family zoning. Single-family zoning prevents the construction of more-affordable apartments in vast swaths of the American urban landscape. This policy shift has already occurred in Minneapolis, Sacramento, and Oregon, and is under discussion in California, Massachusetts, and North Carolina, among others. Independent of any effects on housing affordability, changes to land use will have effects on transport. I evaluate these effects using a microsimulation framework. In order for land use policies to have an effect on transport, they need to first have an effect on land use, so I first build an economic model to simulate where development will occur given a loosening of single-family zoning. Transport outcomes will vary depending on which households live in which parts of the region, so I use an equilibrium sorting model to forecast how residents will re-sort across the region in response to the land use changes induced by new land-use policies. This model also jointly forecasts how many vehicles each household will choose to own. Finally, I apply an activity-based travel demand microsimulation model to forecast the changes in transport associated with the forecast changes from the previous models. I find that while there is opportunity for economically-feasible redevelopment of single-family homes into multifamily structures, the amount of redevelopment that will occur varies greatly depending on the exact expectations of developers about future market conditions. Redevelopment is focused in higher-income neighborhoods. The transport effects of the redevelopment are minimal. Average car ownership across the region does not change hardly at all, although residents of new housing units do have somewhat lower car ownership. Vehicles kilometers traveled, mode choice, and congestion change very little as well. This does not mean that upzoning does not affect transport in general, but that more nuanced proposals may be necessary to promote desirable transport outcomes. Alternatively, the results suggest that upzoning will not worsen transport outcomes, promising for those who support upzoning on affordability grounds.
ContributorsConway, Matthew Wigginton (Author) / Salon, Deborah (Thesis advisor) / Pfeiffer, Deirdre (Committee member) / Fotheringham, A Stewart (Committee member) / van Eggermond, Michael AB (Committee member) / Arizona State University (Publisher)
Created2021