Wearable devices have seen tremendous growth in the recent decade in the consumer electronics space, which promotes research on their next-generation technologies and form factors for comprehensive physical, physiological and biochemical sensing, as well as high flexibility, conformity, and stretchability form factors toward more intimate human-machine interactions. However, the current development of wearable sensors and electronics has been hindered by the lack of efficient, autonomous economical, and practical energy systems. In particular, the power of wearable energy harvesters and the energy density of flexible energy storage devices cannot satisfy the demand of common wearable applications, which fundamentally challenges the concept of self-sustainable wearable devices. Aiming to address this challenge, in this dissertation, the concept of designing a microgrid-like wearable system was proposed, describing a new design concept for wearables that features reliable, practical, sustainable, and autonomous operation. The scenario-specific design considerations for eliminating the performance mismatch between components, minimizing individual disadvantaged characteristics, and maximizing the system’s energy reliability are discussed. Towards establishing high-performance microgrids on wearable platforms, advances in wearable bioenergy harvesters and batteries, along with implementations of the wearable microgrid concept into electronic textile and electronic skins platforms are presented. Such implementations include systematic integrations of energy harvesting, storage, and regulation modules into self-sustainable biosensing platforms, which operate independently on the human body without requiring external energy input. Separately, structural innovations to enable flexibility and stretchability in wearable electronics are introduced. Lastly, this dissertation summarizes existing challenges, theoretical limitations, and prospects of wearable microgrids for commercializing next-generation wearable electronics.
Never, in oil’s one and a half century of commercial extraction has the global oil industry’s future been so fraught. The renewable energy transition, an ongoing investment and volatility crisis, the decline in the quality of reserves and current production, renewed fears of geopolitical conflict, and the inherently anarchic character of capitalist oil production have all converged to cast a shadow over the future of oil, and energy as a whole. This dissertation is a combination of four distinct essays, each of which contributes to unraveling the current juncture. My argument, put simply, is that under this convergence, the capitalist renewable energy transition will be plagued by the greatest period of dysfunction the oil industry has ever seen, impacting billions of people around the world in their access to energy during this time. This, what I call, ‘Carbon Purgatory,’ deserves study as this tumultuous period of transition begins.
Global emergencies resulting from conflict, human rights violations, and natural disasters have displaced more than 90 million people worldwide, half of whom are under 18. While the United Nations’ Sustainable Development Goal 4 (SDG4) calls for sustainable (i.e. long-lasting) access to inclusive and quality education for all people by 2030, global education systems have thus far fallen short, particularly in emergency settings. In Myanmar, a country affected by multiple state-led conflicts and genocidal acts against ethnic minorities, access to quality and inclusive education is severely limited. In response to the state’s neglect of education amid war, several ethnic minority communities have created their own education systems. These community-based schools (CBS) are one type of non-state schooling (i.e. private or nongovernmental) where all financing and provision of education is owned and managed by local community actors. The research on CBS shows demonstrated benefits in the areas of culturally relevant curriculum and local ownership of organizational practices, though challenges like inconsistent quality and lack of attention to inclusivity have also been found. Few studies have been conducted on CBS operating amidst active conflict. Accordingly, this qualitative and participatory research study investigates, through an in-depth case study, the macro-level sociopolitical history of institutions, meso-level organizational practices, and micro-level curriculum development processes of CBS operating amidst emergencies in Myanmar. In my analysis, I draw from a range of academic and practitioner-based theoretical approaches to present findings on how these macro, meso, and micro level community-based education practices reflect sustainable access to quality and inclusive education in emergencies. Ultimately, I argue that a rich historical understanding of community and their sustained engagement with CBS, from visioning to implementation and refining, are necessary to best realize educational goals. I conclude with recommendations for CBS efforts in Myanmar specifically and how this case might inform and inspire practice and research surrounding other instances of community-based education in emergencies globally.
Atmospheric rivers (ARs) are large and narrow filaments of poleward horizontal water vapor transport. AR carry over 90% of moisture from the tropics to higher latitudes but cover only between 2% and 10% of the earth’s surface. When ARs are forced upwards frequently lead to heavy precipitation. ARs are associated with up to half of the extreme events in the top 2% of the precipitation and wind distribution across most mid-latitude regions. ARs can lead to hydrological hazards, and a better understanding of AR can help in the study, forecasting, and communication of flooding. Because of its direct relationship with horizontal vapor transport, extreme precipitation, and overall AR impacts over land, the AR size is an important characteristic that needs to be better understood. Furthermore, most of the ARs research work focuses on midlatitudes and polar regions. It is not until recently that ARs in tropical latitudes are starting to generate interest within the scientific AR community. We develop and implement five size estimation methods independent of the AR detection algorithms and use them to characterize the size of ARs. We create North American landfalling AR composites using ERA5 reanalysis data in the 1980-2017 period. To study how AR size changes with future climate scenarios, we use data from the Coupled Model Intercomparison Project 5 and 6 (CMIP5/6) to create historical and future AR composites in the 1950-2100 period. We apply our size estimation methods to study how AR size responds to climate change. Additionally, we use data from the ERA-20C reanalysis to study the relationship between lower latitude ARs and the extreme precipitation in Central-Western Mexico (CWM) during the dry season (November-March) in the 1900-2010 period.North American landfall ARs (NALFARs) that originate in the Northwest Pacific (WP) (100◦E-180◦E) have larger sizes and are more zonally oriented than those from the Northeast Pacific (EP) (180◦E-240◦E). ARs become smaller through their life cycle, mainly due to reductions in their width. They also become more meridionally oriented towards the end of their life cycle. NALFARs become smaller through their life cycle, mainly due to reductions in their width. They also become more meridionally oriented towards the end of their life cycle. Overall, the size estimation methods developed in this work provide a range of AR areas (between 7x1011m2 and 1013 m2) that is several orders of magnitude narrower than the current estimation by the AR detectors from the Atmospheric River Tracking Method Intercomparison Project (ARTMIP).From a global AR size analysis, we show an increase between 10% and 21% in the background IVT field among CMIP5/6 models. According to our results, AR width is more sensitive to climate change and has a larger contribution than length to the change in the AR area. We find a mean AR area of 3.15x106 (2.32x106-3.98x106) km2 for historical runs, and 3.42x106 (2.73x106-4.11x106) km2 for future runs. Most size estimation methods and CMIP5/6 models show positive trends in AR area, length, and width, between historical and strong radiative forcing future simulations (CMIP5: RCP-8.5, CMIP6: SSP-858). Regardless of the individual sign in AR size change, the mean AR cross-section water vapor transport increases between 8% and 37% for future simulations. Additionally, our results suggest that NALFARs are more likely to penetrate further inland under climate change.Regarding landfalling ARs in CWM, our results suggest that more than 25% of the extreme dry-season precipitation is associated with AR-like events, with up to 75% in December and January. This AR-associated precipitation is associated with an enhanced mean vertically integrated water vapor (IWV) and horizontal vapor transport (IVT) fields (30 kg m−2 and IVT 400 kg m−1s−1, respectively). The meteorological state of the atmosphere shows “ideal” conditions for orographic precipitation due to landfalling ARs: a high plume of horizontal vapor transport perpendicular to the mountain range. These events are associated with a weakening of the westward equatorial IVT and a tropospheric wave pattern, observable in the mean sea level pressure and geopotential height anomalies.We believe that the size estimation methods developed in this work provide statistical constraints for AR size and geometry, and how they change in future climates. These results could help as a reference for tuning existing ARDTs or designing new AR detection algorithms. Furthermore, we demonstrate the relationship between ARs and winter rainfall in CWM. This relationship leaves the question open of how similar are these tropical ARs to the more studied higher latitude ARs and how they will respond in a warming world.
How and why do countries respond differently to the dilemma of pursuing global climate reform through national legislation? This dissertation project explores the socio-political foundations of national carbon price policies, which resonate with global ideals and prioritize a global challenge over national economic benefits. An investigation into carbon prices in France, the United States, and Nordic countries reveals key sites of trade-offs. In France, this project traces the formation of their carbon tax, comparatively neoliberal by design, and the backlash from the populist Yellow Vest movement. In the United States, this project investigates the demise of a proposed carbon price, revealing how economic growth models complicate effective climate reform and empower business-elites to block regulatory reforms. In Nordic countries, this project compares the socio-politics of their relatively strong policies. All in all, this project explores the conditions under which such a law can be adopted, but it also emphasizes that enactment is not the end of the story. Rather, policies, themselves, reshape continuing political controversies over climate change. Carbon pricing thus becomes a case study in the trade-offs between global norms and national interests, highlighting the importance of national growth models, business-elite power, neoliberalism, and populist movements.
Precipitation characteristics have a great influence on tropical ecosystems under a changing climate. It has been widely suggested that precipitation changes are expected to impact the populations and communities of tropical birds. Here I investigated the changes of the precipitation regime, length of the dry season (defined as months with precipitation lower than the annual mean), and the vapor pressure deficit in the tropical South America projected for 2080 – 2100 under emission scenario SSP5-8.5. It has been found that most of the studied area will experience decreasing annual precipitation (up to 37%) and increasing vapor pressure deficit (up to 190%) compared to 1970 – 2000, with seasonal variations. Furthermore, dry seasons are expected to extend over most regions and the monthly averaged precipitation within dry seasons is projected to decrease especially in Central Amazon. The protection areas identified to experience lower impacts concentrate along the east side of the Andes and northeastern Amazon.
In the age of global warming, there is a crucial need to accurately assess uncertainty levels when analyzing observed changes in the climate. For many climate problems, the development of statistical methods that appropriately account for uncertainty is challenging due to the complexity of the underlying climate processes and the various sources of uncertainty involved. This thesis addresses methodological challenges in modeling uncertainty for two climate problems with important real-world applications. The first problem is concerned with quantifying the heat content of the global ocean and its change over time. Understanding the trend in ocean heat content is particularly important as it informs estimates of transient climate sensitivity, a physical parameter that largely determines the amount of warming that will be expected in the years to come. This problem is nevertheless made difficult by the challenge of representing the complex covariance structure of the ocean heat content field, as well as the challenge of quantifying the uncertainty in the estimation of this structure. The second problem is concerned with separating the influence of warming caused by human activities from natural variability in the observed climate, a problem that is often referred to as climate change ``detection and attribution''. While various sources of uncertainty in this problem have been addressed in the literature, recent results have suggested that commonly-used methods under-estimate uncertainty in their conclusions. Producing reliable detection and attribution confidence intervals is difficult in part due to the challenge of modeling the uncertainty in the estimation of the natural variability covariance structure from limited climate model simulations.This thesis proposes methods for addressing statistical challenges in these two problems with respect to three overarching themes. The first theme is the use of spatially-coherent statistical models to represent the covariance structures of the underlying physical processes. For the ocean heat content problem, a novel cylindrical kernel-convolution Gaussian process model is developed to flexibly represent the complex spatial correlation patterns of the global ocean heat content field. For the detection and attribution problem, a Laplacian basis vector parameterization of the covariance matrix is proposed to enforce spatially-coherent correlation patterns. This parameterization is also able to avoid the uncertainty in the traditional approach of estimating principal component vectors from limited numbers of climate model runs. The second theme is the use of hierarchical Bayesian models to propagate the uncertainty in estimating the covariance structure to the final results. In the ocean heat content problem, the spatially-varying parameter fields describing the kernel-convolution Gaussian process are themselves modeled as Gaussian processes in a hierarchical framework. This allows for the uncertainty in estimating these parameters to be propagated to the final posterior distribution for the ocean heat content trend. In the detection and attribution problem, the parameters of the Laplacian parameterization of the covariance matrix, as well as the number of Laplacians to use, are both represented in a Bayesian hierarchical framework that prioritizes the accurate modeling of uncertainty. Finally, the third theme concerns the evaluation of the statistical properties of the Bayesian posterior distributions. For the ocean heat content problem, this is done using cross-validation on the observations with respect to a metric for evaluating both the mean and uncertainty implied by the posterior predictive distributions. For the detection and attribution problem, climate model simulations are used to evaluate the accuracy of the posterior means and credible intervals produced by the proposed methods in the context where the true value can be assumed to be known.Chapter 1 begins by introducing the broader context and implications of the two climate problems and proceeds to give a brief overview of the three statistical themes. Chapter 2 develops the proposed methodology for the ocean heat content problem in a restricted context focusing on spatial variability. A cross-validation study is presented showing that the proposed framework achieves higher accuracy in the predictive posterior distributions than a commonly-used previous method as well as simpler Bayesian approaches. This framework is then extended to the full spatio-temporal context in Chapter 3 and is applied to the quantification of the trend in ocean heat content from 2007 to 2021. The detection and attribution problem is addressed in Chapter 5, where a climate model validation study shows that the proposed approach achieves higher accuracy in the posterior mean and more accurate credible intervals than a traditional approach. While the validation results for each of these proposed methods show quantitative improvements over previous approaches, the results suggest several promising opportunities for additional improvements and extensions. Several of these potential avenues for future research are discussed in Chapter 6.
The Fukushima nuclear disaster of March 2011 provoked a profound reassessment by the Japanese public, political and business leaders, and civic organizations of their nation’s reliance on nuclear power. In response to the disaster, the Japanese government passed sweeping administrative reforms to the prevailing institutions that governed the electric power sector over much of the postwar period. These reforms included a Feed-in Tariff (FIT) for renewable energy projects and the deregulation of the electric power sector, which opened both power generation and retail electricity sales to outside entrants. This dissertation examines how these changes to the regulatory regime governing Japan’s electric power system are transforming socio-ecological relations in Japan. Bringing together literatures in Marxist state theory, science and technology studies, and geopolitical economy, it addresses the following questions: what role have the legal regimes of electric power policy played in shaping and stabilizing uneven power relations between the Japanese public and monopoly utilities, as well as between power producing and power consuming regions, that characterize the geopolitical economy of the electric power system in Japan? How are these power relations changing as a result of regulatory reforms of Japan’s electric power sector since 2011? And how do spatial, material, and political economic factors either permit or constrain these transformations? To answer these questions, it takes a hybrid approach, tracing both the historical geography of this system over the twentieth century and examining more narrowly the impact of recent regulatory reforms—particularly the widespread and rapid buildout of renewable energy since 2011—on the institutional, ecological, and material dynamics of this system. It begins by presenting a “geohistorical institutionalist” account of the development of state policy regarding the electric power system over the long twentieth century, which reorganized geopolitical economic relations across the territory of Japan and established relations of dependence between power producing and power consuming regions. It then traces the impact of post-2011 electricity sector reforms, which were responsible for a rapid buildout of solar photovoltaics across the country and made Japan one of the leaders of the global energy transition. While this rapid growth of renewables has increased competition and undermined the profitability of Japan’s former regional monopolies, this dissertation further details how the utilities attempt to protect their fixed capital investments in centralized generation stations by appealing to the material limitations of Japan’s power grid. As scholars and energy transition advocates argue for interventionist state action to produce the conditions for a transition to renewable energy, this dissertation reveals the political economic and geomaterial constraints that limit the potential of state action to bring about energy transitions.
The South American low-level jet (SALLJ) east of the Andes plays an important role in transporting moisture from the Amazon Basin towards the subtropics, influencing the development of convection and precipitation over the La Plata Basin. This research presents a comprehensive analysis of the spatial and temporal variability of the SALLJ across multiple time scales. A new algorithm is introduced for detecting low-level jet events based on seasonal-percentile thresholds of wind speed and wind shear. The algorithm was applied to ERA-Interim reanalysis data to develop a 38-year dataset of SALLJ days (1979-2016). Although the SALLJ occurs year-round, seasonal composites show that moisture transport associated with the jet is largest during austral summer. Trends in the SALLJ were analyzed over the climatological period and revealed an intensification of the northwesterly moisture flux over the SALLJ region in recent decades. The second part of this research examines the large-scale atmospheric influences that modulate the strength and direction of the SALLJ and consequently, influence local precipitation regimes. By applying principal component analysis and k-means clustering to atmospheric fields associated with SALLJ days, we identified four distinct subtypes of SALLJ events. Composites of SALLJ types revealed noticeable differences in the exit region of the jet and the location and intensity of precipitation. In part, these differences may be influenced by the behavior of barotropic wave trains as they cross over the Andes from the extratropical Pacific. To explore the potential predictability of the SALLJ, we investigated the influence of global climate variability on the strength and frequency of SALLJ events. On interannual time scales, the warm phase of the El Nino Southern Oscillation was found to enhance the strength and frequency of the SALLJ. On subseasonal scales, significant relationships were found between the frequency of SALLJ subtypes and certain phases of the Madden Julian Oscillation. This information provides valuable insight that can be used to improve weather forecasts and subseasonal-to-seasonal climate predictions over South America.
Our understanding of the ocean historically has moved forward in parallel with our ability to make observations. In the thesis, high-resolution observations of the California Current System made by Spray underwater gliders are used to discuss extreme events, eddy across-shore transport, and the annual cycle of dissolved oxygen in the upper ocean. The time scales covered in the thesis include annual to interannual changes while the spatial scales are mesoscale and larger. The availability of high-resolution ocean glider data for over 13 years provides the backbone to conduct analyses over these time and spatial scales. The thesis starts by examining temperature and salinity extremes from 2014-2019 in the California Current System and its source waters. The 2014-2019 period was anomalously warm. In addition, a salinity anomaly from 2017-2019 in the California Current System was found to have formed in the North Pacific Subtropical Gyre in 2015 and subsequently advected into the source waters of the California Current. Next, the thesis examines the offshore propagation of subthermocline eddies from the coast. Subthermocline eddies are observed to propagate at near the local first baroclinic Rossby wave speed. It is estimated that the subthermocline eddies are important to the salt budget in the California Current System and are difficult to track with surface observations alone. The thesis next discusses dissolved oxygen observations collected from 2017 to 2020. First, the thesis considers the procedure to correct for drift in the optical sensors used to make dissolved oxygen observations. A model is fit to changes in the gain correction coefficient over time and predicts the drift for 5 years after sensor calibration. Second, the thesis describes the annual cycle of dissolved oxygen in the upper 500 m of the central and southern California Current System. A subsurface dissolved oxygen maximum is described in the oligotrophic region on the offshore edge of the California Current System. During seasonal coastal upwelling, heave of isopycnals is the primary mechanism that deoxygenates the water column, while mixing and biological sources and sinks also cause changes. Evidence of ventilation is found along sloping isopycnals which oxygenates the ocean above 300 m. The collection of work in the thesis is relevant to extreme climate events and climate change in the oceans, including impacts to the biological environment. The thesis also touches on basic research questions related to geostrophic turbulence. The discoveries in the thesis are made possible by the high-resolution ocean data collected by autonomous Spray gliders used together in a network to create sustained observations of a regional ocean.