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Atmospheric Drivers of Extreme Antarctic Snowfall
Get PDFAntarctica contains the larger of Earth's two ice sheets and holds ~60% of Earth's freshwater. Antarctica has a negative mass balance meaning it is losing ice and contributing to global sea level rise. Snowfall over Antarctica adds mass to the ice sheet and thus helps to mitigate Antarctica's contribution to sea level rise. Recent research highlights the importance of extreme precipitation events, in particular, to Antarctic mass balance variability. This dissertation examines the atmospheric mechanisms, including atmospheric rivers (ARs), modulating Antarctic snowfall events. First, we use a self-organizing map to identify atmospheric environments conducive to high precipitation ARs that reach Dronning Maud Land, East Antarctica. We find that ARs in this region are associated with low-high surface pressure couplets and anomalous moisture. High precipitation ARs, by comparison, are associated with more anomalous surface pressure couplets and an increase in dynamic lift that accompanies occluding cyclones. This regional study highlights the importance of synoptic-scale dynamic drivers in generating Antarctic AR precipitation and motivates a circumpolar investigation of such drivers across the Antarctic continent. To do so, we compare analog (environments with a low-high surface pressure couplet but no AR), AR, and top precipitation AR timesteps around Antarctica. We find that ARs are associated with more anomalous, poleward shifted low-high pressure couplets and larger moisture anomalies compared to analog timesteps. Top precipitation AR timesteps in every region are characterized by enhanced synoptic-scale pressure couplet anomalies but no significant increase in moisture availability. Instead, there is evidence that regionally-varying areas of tropical convection can excite Rossby wave trains that establish this anomalous dynamic environment near Antarctica. Finally, we broaden our scope beyond ARs to investigate atmospheric drivers during the top 15% of snowfall days across five regions around Antarctica. We employ a convolutional neural network to determine that the thermodynamic environment is the most important predictor of snowfall events in West Antarctica, but in East Antarctica the dynamic environment plays a more important role in identifying snowfall events. This dissertation highlights the importance of the synoptic-dynamic environment in driving Antarctic precipitation events, and submits the importance of considering multi-scale dynamics when evaluating Antarctic precipitation, and thus Antarctic surface mass balance, in present and future climates.</p
Cavitation Enhanced Photomechanical Propulsion
Get PDFPhotomechanical effects, where light induces mechanical motion in materials, have been widely explored for applications ranging from optical manipulation of particles to autonomous robotic movement. Traditionally, these effects arise from mechanisms such as radiation pressure, photo-responsive materials (e.g., photoisomerization), laser ablation, and thrust driven by cavitation bubbles. These mechanisms typically rely on material-specific interactions or mass transfer to the surrounding medium or are mostly limited to moving nano- or microscale objects. However, recent findings suggest that laser-induced cavitation can induce a photomechanical propulsion mechanism that can operate at much larger scales and does not depend on specific molecular properties or require external mass exchange. This thesis investigates the underlying physics of this phenomenon, challenges previous explanations based on thermophoretic instability, and develops a predictive framework for cavitation-enhanced photomechanical propulsion.
To understand this mechanism, we first established a transient heat transfer model based on finite element analysis to study laser-induced superheating and cavitation dynamics in liquid solutions. The model incorporates laser conditions, solution properties, and thermal conduction effects, allowing us to predict cavitation conditions and identify key factors influencing superheating volumes. Experimental validation using a pendulum-based propulsion setup confirms that propulsion strength depends on laser power density, solution concentration, and container properties. High-speed imaging of bubble formation inside a suspended cuvette further demonstrates that cavitation bubble expansion and liquid displacement drive this propulsion effect.
Building on these findings, we introduce a spring-mass interaction framework to model the propulsion mechanism, applying the Keller-Miksis equation to estimate inertial forces generated by bubble expansion. Experimental displacement data is compared with theoretical predictions, revealing a consistent force-response relationship across different bubble sizes. Our results indicate that bubble-induced liquid displacement generates force impulses through momentum transfer, inducing the propulsion effect through a repulsive force as the solution container presses against a rigid surface, like the release of a compressed spring.
This study establishes a predictive model for propulsion strength based on laser input conditions and solution properties. Integrating theoretical modeling with experimental validation advances our understanding of the underlying mechanism and lays the groundwork for future applications in laser-induced actuation and optofluidic propulsion systems.</p
Migration, Trade, and Long-Run Adjustments to Economic Change: Evidence From the 20th-Century U.S.
Get PDFEconomic adjustments can affect long-term aggregate and regional development through labor reallocation, capital investment, and structural change. This dissertation explores the role of such economic forces in shaping history by studying large-scale internal migration, environmental shock, and government investment in the 20th-century United States by combining empirical analysis with quantitative modeling.
First, I study how the Second Great Migration (1940–1970) reshaped the American South between 1970 and 2010. The empirical analysis using shift-share instruments shows that out-migration induced capital investment and capital-augmenting technical change in the South. Labor was reallocated from agriculture to manufacturing and local services. To interpret these findings, I develop a dynamic spatial general equilibrium model that incorporates factor substitution, factor-biased technical change, and trade. The counterfactual analysis reveals labor-capital substitution as a key mechanism for adjusting to the out-migration.
Second, I examine how economic adjustments through trade and migration can propagate environmental shocks, using the 1930s Dust Bowl as a case study. The quantitative results show that the local agricultural collapse disproportionately affected the nontradable sector, hindering structural change toward services. Trade and migration mitigated the negative influences of the shock in the directly affected Great Plains region but also transmitted substantial welfare losses to other regions that were not directly impacted.
Third, Prof. Taylor Jaworski and I assess the long-run economic impact of World War II mobilization. Our model-based quantification suggests the largest likely aggregate welfare impact was modest. Additionally, industrial mobilization contributed to manufacturing growth relatively more in the Northeast and Midwest, compared to the South and West. </p
Engineering Fire-Resilient Forests: Applications of Satellite Remote Sensing To Assess Aspen’s Distribution and Potential To Reduce Fire Hazard
Get PDFAcross the United States and globally, wildfire impacts to the built environment and ecosystems are driving increasing costs to society. There is no “one-size-fits-all” solution to reducing wildfire hazard for communities. The convergence of climate- and human-driven changes in wildfire activity requires collective action, innovative science and technology, and intentional management to mitigate the fire hazard. Addressing where and how we build, increasing wildland fire use and prescribed burning, and targeted fuels mitigation in hazard hotspots all play a significant role. However, traditional fuel treatments such as thinning or clear cutting often require revisitation to maintain positive benefits, creating persistent management challenges for communities. The expansion of “fire-resistant” species, such as quaking aspen (Populus tremuloides Michx.), has been proposed as one potential solution (or another “tool in the toolbox”) to reducing fire hazard in some regions, particularly in the Southern Rockies. Beyond the potential for aspen to reduce fire hazard, its ability to respond readily in post-disturbance landscapes provides critical forest resilience at a time when that has become more challenging due to compound disturbance interactions, a more fire-conducive climate, and increased area burned at high severity. However, more information is needed to understand where, how, and when aspen might moderate fire behavior, especially in the context of recent extreme fire activity. The growing widespread availability of remote sensing and geospatial data before, during, and after wildfires offers a promising avenue for elucidating answers to these questions and informing management decisions for this important forest species.
In this dissertation, I present a series of studies which leverage remote sensing and geospatial analysis, environmental data science, statistical and machine learning and ecological principles to explore one potentially novel solution to wildfire hazard: the management of quaking aspen as a living fire break. To this end, we first developed new reproducible methods for mapping aspen at a higher spatial resolution than existing products, identifying an average patch size of 0.53 ha in the Southern Rockies. These new maps have major implications for management decision-making, as small patches may be disproportionally important for both maintaining and expanding existing aspen stands. Next, we demonstrate a novel application of satellite-derive fire radiative power (FRP) harmonized with burn severity, national wall-to-wall forest inventory, and geographic setting to elucidate the relationship between aspen forest composition and structure on fire intensity and severity in the Southern Rockies. We found that the proportion of forested area that is made up of aspen has a significant influence on both intensity and severity, with a -8.1% reduction for every unit increase in proportional aspen area. Further, we found that the influence of aspen dominance diminishes greatly under more extreme fire weather but may still offer a buffering effect where it co-occurs with other forest types, especially lodgepole. This demonstrates the capacity for aspen forests, especially in greater proportions, to reduce extreme fire behavior in some settings. Finally, we harmonized a suite of environmental data to map and prioritize firesheds in the Southern Rockies based on archetypes of aspen management now and into the future. This exercise identified 93 (5.4%) firesheds where aspen management for fire hazard reduction may be advantageous and successful and provides a rich database geared towards management prioritization and planning. This overall effort contributes new data and ecological understanding of aspen’s distribution and potential to reduce fire hazard.</p
Politically Polarizing Media in the United States
Get PDFThis dissertation explores political polarization in the United States, focusing on the role of social media and popular media. Ideological polarization refers to the division of political attitudes, while affective polarization is dislike toward the opposing political party. While it is often assumed that the American public is highly polarized, some scholars argue that the electorate is affectively polarized and ideologically sorted, meaning that voters increasingly align with the political party that best reflects their ideology.
This research utilizes social identity theory, which posits that individuals derive part of their self-image from the social groups they belong to, leading to ingroup favoritism and outgroup discrimination. This study examines how social media and popular media, through social identity, contribute to both ideological and affective polarization.
I use experimental research to investigate the effects of social media comments and popular media clips on polarization. The findings suggest that likeminded social media comments can increase ideological polarization among partisans, and documentary footage in popular media can also influence ideological polarization. The study also confirms the existence of affective polarization among Americans toward voters of the opposing political party.</p
Exploration of the Structure-Agency Dialectic Across Three STEM Education Contexts Focused on Equity and Identity Development
Get PDFEngaging with equity-focused reform in education necessitates a deep understanding of the structural and agentic factors that interact and co-constitute the meanings, processes, and outcomes of equity. This dissertation reports findings from three distinct research and development contexts organized to foster equity and identity development in STEM and STEM-rich learning environments. It seeks to answer an overarching question: How do structure-agency dialectics (of various levels) enable and constrain systematic changes toward STEM equity and identity development? The first article, Studying the Implementation of Equity Projects in Science Education in Divisive Political Contexts, analyzed data from a survey of science education leaders across the U.S. Using a conceptual framework that combines multiple equity projects for science education (Bell, 2019), politics of equity (Oakes & Lipton, 2002), and politics of policy implementation (McDonell & Weatherford, 2016), this study examined leaders’ perceptions and experiences in promoting equity within politically divisive environments, particularly in the context of laws passed to either support or prohibit the teaching of race, racism, and equity-related topics in K-12 classrooms. The second article, Organizing Outreach for Cultural Transformations: The Design of STEM Education Learning Pathways, focuses on the design and implementation of a collegiate outreach program. Engaging engineering students who worked together in air quality monitoring research and later mentored high school students through a similar curriculum, this study unpacked the unique participant structure (Philips, 1972) and activity structures (Lemke, 1990; Polman, 2004) that supported an ecology conducive to culturally transformative learning pathways for STEM students (Nasir et al., 2020). The third article, Configuring Emotions with Critical Data Literacy and Learning about Japanese American Forced Incarceration, was situated in the implementation of an interdisciplinary, project-based learning curriculum to foster data practices, identity, and agency. This study encapsulated how an 8th grade teacher and her students engaged with history lessons on the forced incarceration of Japanese Americans during World War II, integrating Social Studies, English Language Art, and data literacy. Merging emotional configurations (Vea, 2020; Pierson et al., 2023) with data feminism (D’Ignazio & Klein, 2019) frameworks, our analysis and storytelling unveiled classroom interactions and pathways that fostered expanded understandings of emotion, critical data literacy, and their intersection with learning.
Collectively, this dissertation makes visible the multiple pathways of agency and structure interactions, demonstrating that 1) structures can be both constraining and enabling to equitable participation, and 2) agency may interact with structures to frame and reframe historical, social, cultural, and material relations, which can, in some cases disrupt, but also reproduce, the status quo. Working alongside and bringing together perspectives and experiences of various partners, learners, and educators, I articulated new roles, relationships, emotions and embodiments, interactions, discursive practices, affordances, hindrances, and possibilities across implementation processes—and how they intertwine with existing structure and agency within a classroom, a program, and a policy system. By doing so, I hope that this work fosters understandings of current responsibilities, ethics, and commitments to equity, while simultaneously inspiring pathways towards new visions and practices for equity and social transformation. </p
Establishment of An In-Situ Methodology for Window Evaluation: Center of Glass U-Value
Get PDFInsulated Glass Units (IGUs) are often exposed to abnormal environmentalconditions such as increasing global air temperatures applying physical stress to window components, leading to potential degradation in their energy performance. A methodology to compare the thermal transmittance of the IGUs provided by the window manufacturer to the U-value in-situ has not been established. A hybrid in-situ evaluation approach consisting of quantitative interior infrared (IR) thermography and the heat flux method (HFM) is proposed to estimate the average center of glass U-value by 6.2% in comparison to the computer-simulated COG U-value. The in-situ results are affected by the temperature gradient across the glazing system, as well as outdoor wind speed. Understanding the effects of longwave sky irradiance and assessing the methodology with a smaller temperature gradient can further ensure the robustness of this proposed methodology.</p
Evolution of Mixed Bedrock-Alluvial Rivers and Applications to Neogene Landscape Evolution the High Plains, Colorado, USA
Get PDFAcross much of Earth’s surface, rivers are the primary agents of sediment transport and set the pace of bedrock erosion. Bedload sediment transport and bedrock erosion are closely interrelated: higher bedrock erosion rates can produce more sediment, but high fluxes of coarse sediment can mantle riverbeds and inhibit erosion. Moreover, sediment load is a dynamic quantity, constantly being modified by changes in local bedrock lithology, hillslope contributions, and attrition of grains in transport. Developing models that fully capture the feedbacks between sediment transport and bedrock erosion remains a challenge; however, the pursuit of such a model is critical to understanding how landscapes evolve over geologic time. This dissertation focuses on advancing our understanding of the behaviors of gravel-bed rivers – a class of rivers with morphologies adjusted to sediment flux over decadal or centennial timescales, but that also commonly incise bedrock over geologic timescales. This work explores the feasibility and implications of coupling dynamic channel geometry adjustment, sediment transport, bedload modification, and bedrock erosion in a fluvial model. The model then lends insight into how accounting for feedbacks between sediment flux and bedrock erosion can improve our understanding of landscape response to tectonic perturbations.
This dissertation is organized across five chapters. In the first chapter, I introduce the reader to several themes that will recur throughout this work: some basics of fluvial geomorphology, the role of sediment in modulating bedrock erosion rates, the idea of an “equilibrium” channel, and a brief overview of the High Plains landscape in Colorado. The second chapter focuses on developing a mathematical model that allows for bedrock erosion and equilibrium channel adjustments to proceed simultaneously; Chapter 3 then uses a slightly modified version of that model to explore how river profiles in one dimension respond to variations in sediment load. Chapter 4 applies a two-dimensional implementation of the model to investigate if disturbing a fluvial system via long-wavelength tilting of the land surface can produce erosional patterns similar to those observed on the High Plains today. Finally, Chapter 5 offers concluding remarks, identifies several new questions raised by this work, and outlines opportunities for future study.</p
Leveraging Genome-Wide CRISPR Screens To Identify Non-Canonical Regulation of Membrane Trafficking
Get PDFMaintaining surface protein homeostasis is crucial for cell survival and physiology. Two general pathways, endocytosis and exocytosis, regulate the surface expression of diverse proteins that function at the cell surface. Cells have therefore evolved complex mechanisms to regulate these processes, and direct cargo towards or away from these processes. To elucidate non-canonical regulators of cargo trafficking, we leveraged CRISPR-Cas9 genetic mutations, surface protein reporters, and fluorescence activated cell sorting to conduct an unbiased forward genetic screen. COMMD3, one of 16 subunits of the Commander complex was a significant regulator, while other complex subunits were not. It was determined that COMMD3 uniquely regulates endosomal trafficking of the transferrin receptor in a Commander-independent manner, in addition to its canonical role in the Commander complex. This study employs unbiased genetic screens and targeted subunit deletions and mutations to provide insight into non-canonical regulation. We also show that a non-canonical essential open reading frame (ORF) screen identified upMettl9_25aa whose deletion phenocopies disruption of the canonical Mettl9 ORF. This unbiased screening strategy represents a powerful model for the interrogation of subunit specific and non-canonical effects on trafficking processes and cell physiolog.</p
Improving Understanding of Localized Sources and Transport of Air Pollution
Get PDFUnderstanding the sources, chemistry, and transport of air pollutants is an essential step in forming an accurate picture of local air quality. However, providing accurate estimates of the magnitudes and relative composition of pollutant emissions is both time and resource intensive, requiring extensive scientific equipment and prior knowledge of air quality. In this work, we explore the use of several techniques to assess the sources contributing to particulate phase pollution, as well as the magnitudes of various pollutants emitted by those sources. Leveraging source receptor modeling techniques, we investigate how various pollutant sources, including wildfires, motor vehicles, and industrial activity impact pollutant compositions and concentrations in urban areas. Distributive inequalities of air pollution are discussed within the context of environmental justice. Along these lines, we study how meteorological events such as persistent cold air pools impact the distribution of particulates from urban sources. We then investigate how low cost sensors (LCS) can be employed in novel configurations to quantify emissions from common pollutant sources. Additional focus is placed on the calibration of LCS, including the positives and negatives of multilinear regression and machine learning models. We further investigate the use of data weighting in colocation applications to improve our ability to quantify pollutant peaks using LCS. Novel configurations for these sensors, including both ground based and aerial mobile monitoring, are investigated in detail. Finally, we leverage a dense LCS network within Salt Lake City, Utah to understand the small-scale spatiotemporal variability of common air pollutants associated with traffic related air pollution using spatial interpolation and meteorological data.</p
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