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- Member of: ASU Electronic Theses and Dissertations
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Environmental heat is a growing concern in cities as a consequence of rapid urbanization and climate change, threatening human health and urban vitality. The transportation system is naturally embedded in the issue of urban heat and human heat exposure. Research has established how heat poses a threat to urban inhabitants and how urban infrastructure design can lead to increased urban heat. Yet there are gaps in understanding how urban communities accumulate heat exposure, and how significantly the urban transportation system influences or exacerbates the many issues of urban heat. This dissertation focuses on advancing the understanding of how modern urban transportation influences urban heat and human heat exposure through three research objectives: 1) Investigate how human activity results in different outdoor heat exposure; 2) Quantify the growth and extent of urban parking infrastructure; and 3) Model and analyze how pavements and vehicles contribute to urban heat.
In the urban US, traveling outdoors (e.g. biking or walking) is the most frequent activity to cause heat exposure during hot periods. However, outdoor travel durations are often very short, and other longer activities such as outdoor housework and recreation contribute more to cumulative urban heat exposure. In Phoenix, parking and roadway pavement infrastructure contributes significantly to the urban heat balance, especially during summer afternoons, and vehicles only contribute significantly in local areas with high density rush hour vehicle travel. Future development of urban areas (especially those with concerns of extreme heat) should focus on ensuring access and mobility for its inhabitants without sacrificing thermal comfort. This may require urban redesign of transportation systems to be less auto-centric, but without clear pathways to mitigating impacts of urban heat, it may be difficult to promote transitions to travel modes that inherently necessitate heat exposure. Transportation planners and engineers need to be cognizant of the pathways to increased urban heat and human heat exposure when planning and designing urban transportation systems.

Lifecycle assessment (LCA), the preferred framework to identify and address environmental hotspots in PV manufacturing and recycling, doesn’t account for time-sensitive climate impact of PV manufacturing GHG emissions and underestimates the climate benefit of manufacturing improvements. Furthermore, LCA is inherently retrospective by relying on inventory data collected from commercial-scale processes that have matured over time and this approach cannot evaluate environmentally promising pilot-scale alternatives based on lab-scale data. Also, prospective-LCAs that rely on hotspot analysis to guide future environmental improvements, (1) don’t account for stake-holder inputs to guide environmental choices in a specific decision context, and (2) may fail in a comparative context where the mutual differences in the environmental impacts of the alternatives and not the environmental hotspots of a particular alternative determine the environmentally preferable alternative
This thesis addresses the aforementioned problematic aspects by (1)using the time-sensitive radiative-forcing metric to identify PV manufacturing improvements with the highest climate benefit, (2)identifying the environmental hotspots in the incumbent CdTe-PV recycling process, and (3)applying the anticipatory-LCA framework to identify the most environmentally favorable alternative to address the recycling hotspot and significant stakeholder inputs that can impact the choice of the preferred recycling alternative.
The results show that using low-carbon electricity is the most significant PV manufacturing improvement and is equivalent to increasing the mono-Si and multi-Si module efficiency from a baseline of 17% to 21.7% and 16% to 18.7%, respectively. The elimination of the ethylene-vinyl acetate encapsulant through mechanical and chemical processes is the most significant environmental hotspot for CdTe PV recycling. Thermal delamination is the most promising environmental alternative to address this hotspot. The most significant stake-holder input to influence the choice of the environmentally preferable recycling alternative is the weight assigned to the different environmental impact categories.

This study used urban form/socio-economic data combined with self-reported on-road FFCO2 emissions for a sample of global cities to estimate relationships within a multivariate regression framework based on an adjusted STIRPAT model. The on-road high-resolution (whole-city) regression FFCO2 model robustness was evaluated by introducing artificial error, conducting cross-validation, and assessing relationship sensitivity under various model specifications. Results indicated that fuel economy, vehicle ownership, road density and population density were statistically significant factors that correlate with on-road FFCO2 emissions. Of these four variables, fuel economy and vehicle ownership had the most robust relationships.
A second regression model was constructed to examine the relationship between global on-road FFCO2 emissions and urban form factors (described by population
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density, road density, and distance to activity centers) at sub-city spatial scales (1 km2). Results showed that: 1) Road density is the most significant (p<2.66e-037) predictor of on-road FFCO2 emissions at the 1 km2 spatial scale; 2) The correlation between population density and on-road FFCO2 emissions for interstates/freeways varies little by city type. For arterials, on-road FFCO2 emissions show a stronger relationship to population density in clustered cities (slope = 0.24) than dispersed cities (slope = 0.13). FFCO2 3) The distance to activity centers has a significant positive relationship with on-road FFCO2 emission for the interstate and freeway toad types, but an insignificant relationship with the arterial road type.


Motivated by the need for cities to prepare and be resilient to unpredictable future weather conditions, this dissertation advances a novel infrastructure development theory of “safe-to-fail” to increase the adaptive capacity of cities to climate change. Current infrastructure development is primarily reliant on identifying probable risks to engineered systems and making infrastructure reliable to maintain its function up to a designed system capacity. However, alterations happening in the earth system (e.g., atmosphere, oceans, land, and ice) and in human systems (e.g., greenhouse gas emission, population, land-use, technology, and natural resource use) are increasing the uncertainties in weather predictions and risk calculations and making it difficult for engineered infrastructure to maintain intended design thresholds in non-stationary future. This dissertation presents a new way to develop safe-to-fail infrastructure that departs from the current practice of risk calculation and is able to manage failure consequences when unpredicted risks overwhelm engineered systems.
This dissertation 1) defines infrastructure failure, refines existing safe-to-fail theory, and compares decision considerations for safe-to-fail vs. fail-safe infrastructure development under non-stationary climate; 2) suggests an approach to integrate the estimation of infrastructure failure impacts with extreme weather risks; 3) provides a decision tool to implement resilience strategies into safe-to-fail infrastructure development; and, 4) recognizes diverse perspectives for adopting safe-to-fail theory into practice in various decision contexts.
Overall, this dissertation advances safe-to-fail theory to help guide climate adaptation decisions that consider infrastructure failure and their consequences. The results of this dissertation demonstrate an emerging need for stakeholders, including policy makers, planners, engineers, and community members, to understand an impending “infrastructure trolley problem”, where the adaptive capacity of some regions is improved at the expense of others. Safe-to-fail further engages stakeholders to bring their knowledge into the prioritization of various failure costs based on their institutional, regional, financial, and social capacity to withstand failures. This approach connects to sustainability, where city practitioners deliberately think of and include the future cost of social, environmental and economic attributes in planning and decision-making.

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.


Pluvial Flood Risk Modeling, Assessment, and Management under Evolving Urban Climates and Land Cover

