UMD Theses and Dissertations

Permanent URI for this collectionhttp://hdl.handle.net/1903/3

New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a given thesis/dissertation in DRUM.

More information is available at Theses and Dissertations at University of Maryland Libraries.

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    EXPLORING AND ASSESSING LAND-BASED CLIMATE SOLUTIONS USING EARTH OBSERVATIONS, EARTH SYSTEM MODELS, AND INTEGRATED ASSESSMENT MODELS
    (2024) Gao, Xueyuan; Wang, Dongdong; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Anthropogenic greenhouse gas (GHG) emissions have led the global mean temperature to increase by approximately 1.1 °C since the industrial revolution, resulting in mass ice sheet melt, sea level rise, and an increase in extreme climate events, and exposing natural and human systems to uncertainties and the risks of unsustainable development. Meeting the Paris Agreement’s climate goal of keeping temperature increases well below 2 °C — even 1.5 °C — will require removing CO2 from the atmosphere beyond reducing GHG emissions. Therefore, carbon dioxide removal and the sustainable management of global carbon cycles are one of the most urgent society needs and will become the major focus of climate action worldwide. However, research on carbon dioxide removal remains in an early stage with large knowledge gaps. The global potential and scalability, full climate consequences, and potential side effects of currently suggested carbon sequestration options — afforestation and reforestation, bioenergy with carbon capture and storage (BECCS), direct air carbon capture — are uncertain. Moreover, although about 120 national governments have a net-zero emission target, few have actionable plans for developing carbon dioxide removal.This dissertation examines two major categories of land-based carbon removal and sequestration methods: nature-based solutions that rely on the natural carbon uptake of the land ecosystem, and technology-based solutions, especially BECCS. These two options were investigated using four studies with satellite and in-situ observations, Earth system models (climate models), and integrated assessment models (policy models). Study 1 provides evidence that land ecosystem is an important carbon sink, Study 2 assesses the carbon sequestration potential of forest sustainable management via numerical experiments, Study 3 monitors recent tropical landscape restoration efforts, and Study 4 extends to BECCS and explores the impacts of future climate changes on its efficacy. Overall, this dissertation (1) improved monitoring, reporting, and verification of biomass-based carbon sequestration efforts using Earth observations, (2) improved projections on biomass-based carbon sequestration potential using Earth system models and socio-economic models, and (3) provided guidance on scaling up biomass-based carbon sequestration methods to address the climate crisis.
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    EXPLORING RECENT DIRECTIONS IN INTEGRATED ASSESSMENT MODELING RESEARCH: IMPLICATIONS FOR SCENARIO ANALYSES OF CLIMATE CHANGE MITIGATION AND IMPACTS USING THE GCAM MODEL
    (2021) Santos da Silva, Silvia Regina; Miralles-Wilhelm, Fernando R.; Atmospheric and Oceanic Sciences; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Integrated assessment models (IAMs) are essential analytical tools in climate change science. There is wide recognition of the need of credible IAM scenarios for guidance on developing climate change mitigation and adaptation measures. This dissertation employs the Global Change Analysis Model (GCAM), a state-of-the-art IAM, in three studies that develop meaningful scenario analyses of climate change mitigation and impacts to address key gaps in the contemporary IAM research. The first study deals with the challenge of reconciling mitigation strategies consistent with the Paris Agreement climate goals with constraints on energy-water-land (EWL) resources. The study highlights the fact that mitigation strategies can have unintended repercussions for the EWL sectors, which can undermine their overall effectiveness. In Latin American countries used as case studies, increased water demands for crop and biomass irrigation and for electricity generation stand out as potential trade-offs resulting from climate mitigation policies. The second study demonstrates that scenarios that explore the consequences of climate change impacts on renewable energy for the electric power sector need to adopt a comprehensive modeling approach that accounts for climate change impacts in all renewables. Using such an approach, the findings from this study show that climate impacts on renewables can result in additional capital investment requirements in Latin America. Conversely, accounting for climate impacts only on hydropower – a primary focus of previous studies – can significantly underestimate investment estimates, particularly in scenarios with high intermittent renewable deployment. The last study demonstrates that GCAM projections of solar photovoltaics and wind onshore electricity generation can be largely affected by methodological uncertainties in the computation of global renewable energy potentials – used to produce resource cost-supply curves that are key input assumptions to IAMs. Consequently, the role of these renewables in the modeled long-term scenarios can be under- or overestimated with potential implications for decision-making on energy planning, climate change mitigation and on the adaptation efforts to climate impacts on these renewables. The three studies encompass questions that have received little or no attention by the IAM community, and contribute with relevant approaches and insights that offer improvements relative to prior analyses. Importantly, these results help to enhance the value of GCAM scenarios to decision-making and identify research opportunities that might help improve GCAM as well as other IAM projections.