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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7

GeoTGo: AI/ML software for development of community geothermal resources

For effective and equitable outcomes in achieving the national goal of net-zero carbon emissions, communities must be not only included, but even lead the implementation of innovative green-energy technologies. Collaborations with communities should happen through informed decision-making, community-centered research and engagement of stakeholders at the local, state, and regional levels. Community-led research and implementation are fundamental to achieving success. These collaborations include rule makers, environmental regulators, clean energy industries, and technology researchers and developers. Unfortunately, many green infrastructure initiatives still adhere to a top-down and expert-driven process of site selection and design without awareness and acknowledgment of public engagement needs. This can lead to costly delays, including lawsuits, and ultimately less than desired or lacking outcomes as well as missed opportunities1. Geothermal, like many new technologies whose social and economic impacts are not fully understood, often cause disproportionately high adverse effects on disadvantaged communities. These effects can be related to human health, environmental, climate, and other cumulative impacts, as well as the accompanying economic challenges of these impacts. We are focusing our work on the needs of the New Mexico Native American Pueblos and Tribes (NMP&T). To address these needs, we are developing a novel web-based interactive software and user friendly interface called GeoTGO (https://geotgo.com) that provides everything that is needed for communities to better understand and develop their geothermal resources. We will bridge the gap between technology advancements and community needs by facilitating the interactions between the geothermal industry, regulators, stakeholders, and end-users. GeoTGO will merge data, software (including data analysis, text mining, artificial intelligence, and modeling tools), knowledge, expertise, and experience to provide fast processing and dissemination of the latest information about cutting-edge geothermal technologies to users and communities. More information about the project is available at https://envitrace.com/projects/geotgo.html.

15 GEOTHERMAL ENERGY↗

Simple Hybrid Sea Ice Nudging Method for Improving Control Over Partitioning of Sea Ice Concentration and Thickness

Abstract To assess the effect of ocean‐atmosphere coupling in the climate response to forced sea ice loss, the Polar Amplification Model Intercomparison Project protocol includes centennial coupled atmosphere‐ocean general circulation model simulations with imposed sea ice loss. The protocol, which specifies sea ice concentration and thickness distribution targets, does not prescribe a method for achieving them. Although different methods for imposing sea ice loss (or growth) in models have been documented, testing of the method‐dependence of the resulting climate responses has been limited. Achieving the targeted sea ice state has proven to be challenging using the so‐called ghost‐flux nudging method, which induces ice melt from below, as this method does not constrain the partitioning between thickness and concentration. We propose, describe and test a simple method that combines the advantages of direct sea ice nudging and ghost‐flux nudging. The hybrid nudging method better captures the partitioning between thickness and concentration while conserving total water content. We document how this novel sea ice constraining method reaches specific targets, enhances surface turbulent heat flux responses to sea ice loss, and induces tropospheric warming for both polar regions.

54 ENVIRONMENTAL SCIENCES↗

Deployment Readiness Framework Subtask 1.2 Outreach Report: Common Themes Among Clean Energy Transition Technical Assistance Projects

Island and remote coastal communities face an uncertain energy future. These communities build, operate, and maintain energy infrastructure in extremely challenging environments and pay the highest prices for electricity and fuels. Moreover, climate change increasingly affects grid reliability, resiliency, and, ultimately, the cost of energy. Marine energy could address many of the challenges faced by island and remote coastal communities, but these communities often have limited resources and capacity to invest in complex energy and coastal resilience issues. The Deployment Readiness Framework (DRF) is being developed to support community-driven energy transitions in these coastal communities and to better understand the readiness of communities for marine energy demonstration and operation. Led by the National Renewable Energy Laboratory and Pacific Northwest National Laboratory, the DRF builds on the Energy Transitions Initiative Partnership Project (ETIPP) supported in part by the U.S. Department of Energy's Water Power Technologies Office. This report details the results from the stakeholder outreach and engagement effort linked to the previously reported literature review.

16 TIDAL AND WAVE POWER↗

Evaluating SWAT + model uncertainties for human and natural outcomes: Application in a Great Lakes agricultural watershed

Nutrient exports from agricultural lands in the Great Lakes Region pose significant threats to water quality and ecological health through eutrophication, hypoxia, and harmful algal blooms. Climate change and agricultural adaptation practices complicate future nutrient loading due to intensified hydrologic cycles and land use decisions. Our research focuses on evaluating the Soil and Water Assessment Tool (SWAT) plus model parametric uncertainties for human and natural outcomes across different scales. These factors are integral to ensuring a balance between productive agricultural practices and maintaining the health of watershed hydrology. However, uncertainties in modeling such complex interactions pose significant challenges, limiting our ability to precisely determine critical factors that influence crop yield and soil moisture. Our analysis employs Sobol global sensitivity analysis to evaluate first-order, second order, and total-order indices for SWAT crop growth parameter, ensuring comprehensive assessment of individual and interactive effects on model outputs. The objective is to identify the parameters that significantly affect model outputs for crop yield and soil moisture and improve our understanding of their interactions at the basin and hydrological response unit (HRU) scale. Our case study, the Portage River Watershed, which drains into Lake Erie, is chosen to better capture finer scale interactions crucial for predicting nutrient loading under future climate scenarios. This foundational work is aimed at setting the stage for the future development of an agent-based model (ABM). The ABM model would incorporate SWAT outputs to dynamically simulate decision-making processes.

Bunyon, Enock↗

Review of Onsite Temperature and Solar Forecasting Models to Enable Better Building Design and Operations

Advanced building controls and energy optimization for new constructions and retrofits rely on accurate weather data. Traditionally, most studies utilize airport weather information as the decision inputs. However, most buildings are in environments that are quite different than those at the airport miles away. Tree cover, adjacent buildings, and micro-climate effects caused by the larger surrounding area can all yield deviations in air temperature, humidity, solar irradiance, and wind that are large enough to influence design and operation decisions. In order to overcome this challenge, there are many prior studies on developing weather forecasting algorithms from micro-to meso-scales. Additionally, this paper reviews and complies knowledge on common weather data resources, data processing methodologies and forecasting techniques of weather information. Commonly used statistical, machine learning and physical-based models are discussed and presented as two major categories: deterministic forecasting and probabilistic forecasting. Finally, evaluation metrics for forecasting errors are listed and discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Evaluating How Climate Adaptation Measures Affect the Interconnected Water‐Energy Resource Systems of the Western United States

Abstract The Western US faces increasing water stress from the impacts of climate change, making it difficult to meet water demands for the region's cities, agriculture, and hydropower generators. Existing literature suggests that climate adaptation measures such as water conservation, cropland retirement, wastewater recycling, and managed aquifer recharge can alleviate some of these challenges. Few analyses, however, compare the relative efficacy and system‐wide effects of these adaptations under different climate projections across the entire Western United States. Here we use a Western US‐wide water systems model to evaluate, by sector and sub‐region, how the widespread implementation of these adaptive measures impacts water demands, water deliveries, and electricity use related to the water system for three different climate projections. We find that wastewater recycling has greater potential to lower unmet indoor water demands than urban indoor water conservation measures. However, when implemented at scale, indoor water conservation reduces electricity use by an average of 683 Terawatt hours while wastewater recycling increases energy use by an average of 721 Terawatt hours, cumulatively from 2020 to 2070. Cropland retirement and aquifer recharge adaptations increase the ability to meet agricultural water demand, increase groundwater storage, and reduce summertime electricity use. While most of these findings are consistent across different climate projections, the benefits of aquifer recharge are sensitive to spatial variation of precipitation. Given the limitations and tradeoffs of each individually, the results suggest that a portfolio of adaptation measures will be needed for a climate‐resilient water and energy future in the Western US. Plain Language Summary The Western US faces increased water stress from the impacts of climate change, making it difficult to meet demands for cities, agriculture, and hydropower facilities. Adaptation measures like water conservation, retiring agricultural lands, recycling wastewater, and storing water underground can address these challenges. However, there is little modeling to understand the impact of these adaptations if they were implemented across the entire Western US while also considering climate change. We use a Western US‐wide water systems model to evaluate how implementing adaptation measures impacts groundwater levels, the ability to meet water demands, and electricity use related to water in three different possible climate futures. We find that recycling wastewater to drinking water standards does a better job of meeting urban water demands than water conservation measures. However, indoor water conservation reduces energy use for water while recycling wastewater increases energy use for water. Retiring agricultural lands and storing water underground both increase the ability to meet agricultural water demands, increase underground water storage, and reduce summertime energy use. No adaptation measures provides benefits across every metric we track. Therefore, multiple adaptation measures will likely be needed to achieve a climate‐resilient future for energy and water in the Western US. Key Points Water‐related climate change adaptations have different benefits and tradeoffs for interconnected water‐energy systems in the Western U.S. Wastewater recycling most increases urban water coverage, but has a significant tradeoff in the form of greater electricity use Cropland retirement and aquifer recharge benefit water and electricity systems most in the summer when those systems are most stressed

Singhal, A↗

The COMBLE campaign: a study of marine boundary-layer clouds in Arctic cold-air outbreaks

One of the most intense air mass transformations on Earth happens when cold air flows from frozen surfaces to much warmer open water in cold-air outbreaks (CAOs), a process captured beautifully in satellite imagery. Despite the ubiquity of the CAO cloud regime over high-latitude oceans, we have a rather poor understanding of its properties, its role in energy and water cycles, and its treatment in weather and climate models. The Cold-air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) was conducted to better understand this regime and its representation in models. COMBLE aimed to examine the relations between surface fluxes, boundary-layer structure, aerosol, cloud and precipitation properties, and mesoscale circulations in marine CAOs. Processes affecting these properties largely fall in a range of scales where boundary-layer processes, convection, and precipitation are tightly coupled, which makes accurate representation of the CAO cloud regime in numerical weather prediction and global climate models most challenging. COMBLE deployed an Atmospheric Radiation Measurement Mobile Facility at a coastal site in northern Scandinavia (69°N), with additional instruments on Bear Island (75°N), from December 2019 to May 2020. CAO conditions were experienced 19% (21%) of the time at the main site (on Bear Island). A comprehensive suite of continuous in situ and remote sensing observations of atmospheric conditions, clouds, precipitation, and aerosol were collected. Because of the clouds’ well-defined origin, their shallow depth, and the broad range of observed temperature and aerosol concentrations, the COMBLE dataset provides a powerful modeling test bed for improving the representation of mixed-phase cloud processes in large-eddy simulations and large-scale models.

54 ENVIRONMENTAL SCIENCES↗

Exploring stages of resilience maturity as communities confront climate risks

Coastal communities are facing increased risks due to climate change, as evidenced by heightened shocks such as hurricanes and wildfires, and stressors including sea-level rise and drought. To confront these risks, many coastal communities are planning and designing their built environments in new ways, with the overall goal of increasing their resilience. However, resilience practices have been widely guided by an event-based timeframe, which may not be sufficient to confront the multiple and overlapping threats expected over the coming decades. To address this concern, this study investigated a long-term perspective on resilience progression, termed resilience maturity. To better understand resilience maturity in practice, this study drew directly on community perspectives, thereby identifying common challenges. Furthermore, variation in resilience maturity across communities provided an opportunity to identify existing successful strategies. Inductive qualitative analysis was used to examine perspectives from 15 interviews with local practitioners across 12 coastal communities. The analysis revealed that communities in early stages of resilience maturity often struggle with local stakeholder alignment and minimal dedicated resilience resources. In contrast, those further along the maturity path often face technology barriers and challenges in aligning regional stakeholders. Few examples of a fully mature resilience culture were found within the communities studied, underscoring systemic barriers to achieving advanced resilience maturity. Overall, these findings supported development of a practical framework for classifying community resilience efforts, identifying common obstacles, and informing localized resilience advancement.

Resilience maturity↗

Projections of future climate for U.S. national assessments: past, present, future

Climate assessments consolidate our understanding of possible future climate conditions as represented by climate projections, which are largely based on the output of global climate models. Over the past 30 years, the scientific insights gained from climate projections have been refined through model structural improvements, emerging constraints on climate feedbacks, and increased computational efficiency. Within the same period, the process of assessing and evaluating information from climate projections has become more defined and targeted to inform users. As the size and audience of climate assessments has expanded, the framing, relevancy, and accessibility of projections has become increasingly important. This paper reviews the use of climate projections in national climate assessments (NCA) while highlighting challenges and opportunities that have emerged over time. Reflections and lessons learned address the continuous process to understand the broadening assessment audience and evolving user needs. Insights for future NCA development include (1) identifying benchmarks and standards for evaluating downscaled datasets, (2) expanding efforts to gather research gaps and user needs to inform how climate projections are presented in the assessment (3) providing practitioner guidance on the use, interpretation, and reporting of climate projections and uncertainty to better inform decision-making.

Assessment↗

An open-source framework for balancing computational speed and fidelity in production cost models

Studies of bulk power system operations need to incorporate uncertainty and sensitivity analyses, especially around exposure to weather and climate variability and extremes, but this remains a computational modeling challenge. Commercial production cost models (PCMs) have shorter runtimes, but also important limitations (opacity, license restrictions) that do not fully support stochastic simulation. Open-source PCMs represent a potential solution. They allow for multiple, simultaneous runs in high-performance computing environments and offer flexibility in model parameterization. Yet, developers must balance computational speed (i.e. runtime) with model fidelity (i.e. accuracy). In this paper, we present Grid Operations (GO), a framework for instantiating open-source, scale-adaptive PCMs. GO allows users to search across parameter spaces to identify model versions that appropriately balance computational speed and fidelity based on experimental needs and resource limits. Results provide generalizable insights on how to navigate the fidelity and computational speed tradeoff through parameter selection. We show that models with coarser network topologies can accurately mimic market operations, sometimes better than higher-resolution models. It is thus possible to conduct large simulation experiments that characterize operational risks related to climate and weather extremes while maintaining sufficient model accuracy.

42 ENGINEERING↗

Enabling Robust Exoplanet Atmospheric Retrievals with Gaussian Processes

Atmospheric retrievals are essential tools for interpreting exoplanet transmission and eclipse spectra, enabling quantitative constraints on the chemical composition, aerosol properties, and thermal structure of planetary atmospheres. The James Webb Space Telescope (JWST) offers unprecedented spectral precision, resolution, and wavelength coverage, unlocking transformative insights into the formation, evolution, climate, and potential habitability of planetary systems. However, this opportunity is accompanied by challenges: modeling assumptions and unaccounted-for noise or signal sources can bias retrieval outcomes and their interpretation. To address these limitations, we introduce a Gaussian process (GP)-aided atmospheric retrieval framework that flexibly accounts for unmodeled features and correlated noise in exoplanet spectra. We validate this method on synthetic JWST observations, and show that GP-aided retrievals reduce bias in inferred abundances and better capture model–data mismatches than traditional approaches. We also introduce the concept of mean squared error to quantify the trade-off between bias and variance, arguing that this metric more accurately reflects retrieval performance than bias alone. We then reanalyze the NIRISS/SOSS JWST transmission spectrum of WASP-96 b, finding that GP-aided retrievals yield broader constraints on CO 2 and H 2 O, possibly alleviating tension between previous retrieval results and equilibrium predictions. Our GP framework provides precise and accurate constraints while highlighting regions where models fail to explain the data. As JWST matures and future facilities come online, a deeper understanding of the limitations of both data and models will be essential, and GP-enabled retrievals like the one presented here offer a principled path forward.

Rotman, Yoav [Arizona State Univ., Tempe, AZ (Unit↗

Impacts of Resolution on Heavy‐Precipitating Storms in Climate Model Hindcasts

The present study investigates the impact of horizontal resolutions on heavy‐precipitating storms using the Energy Exascale Earth System Model version2 (E3SMv2) at low (∼100 km, LR) and high (∼25 km, HR) resolutions through short‐range hindcasts. The short‐range hindcast approach ensures a faithful comparison of model resolution in simulating the same storm events under a controlled large‐scale environment. Using a phenomenon‐based framework, we attribute precipitation to specific storm types: tropical cyclones (TCs), extratropical cyclones, atmospheric rivers, and mesoscale convective systems (MCSs). Our findings show that E3SM hindcasts with both HR and LR configurations significantly underestimate storm‐associated precipitation intensity but overestimate precipitation from other sources. Furthermore, both HR and LR hindcasts face significant challenges in accurately simulating extreme precipitation events, particularly over MCS hotspots. Nevertheless, HR simulations capture more detailed and intense precipitation patterns with an improved representation of storm dynamics. HR hindcasts produce 16% more storm precipitation compared to LR. For precipitation extremes, HR simulates a 33% higher 99th percentile precipitation magnitudes compared to LR, and most of the increment comes from these four heavy‐precipitating storm types. The increase in precipitation mainly comes from stratiform precipitation rather than convective precipitation. The improvement in HR simulations varies across different storm types with TC showing the largest improvement. The phenomenon‐based approach provides important insights into precipitation simulations especially for extremes. Our results emphasize the need for further refinement in high‐resolution models to improve the accuracy of precipitation predictions, which is crucial for better understanding and mitigating climate change impacts.

54 ENVIRONMENTAL SCIENCES↗

Yesterday’s extremes, today’s new normal: flood risk in the Kathmandu Valley, Nepal

Unplanned urban growth has left many cities increasingly vulnerable to extreme rainfall events, particularly in regions with inadequate drainage infrastructures and development encroaching on natural floodplains. Here, in this perspective paper, we examine the September 2024 floods that struck Central Nepal, triggered by a persistent low-pressure system and enhanced by converging moisture flows from the Arabian Sea and the Bay of Bengal which led to widespread catastrophic damage. In the Kathmandu Valley, floodwaters expanded to more than 2.5 times the bankfull water extent, causing significant damage to housing, transportation network, and critical infrastructure, displacing thousands of residents, and severely disrupting urban services. This event highlights the urgent need for improved flood management strategies that integrate both structural and non-structural measures into the infrastructure development. While early warning systems provided critical lead time, challenges remain in reducing forecasting uncertainties and improving communication across government agencies and with local communities. A forward-looking approach is essential, including probabilistic flood forecasting systems, sustainable floodplain management, risk-sensitive land use planning, climate- and disaster- resilient infrastructure development, and the integration of nature-based solutions like urban green and blue spaces to mitigate flood impacts. By involving local communities in planning and preparedness efforts, particularly through citizen science initiatives, and engagement with underserved and disadvantaged communities, Nepal can better adapt to the growing risks posed by extreme rainfall and urban flooding and enhance long-term disaster resilience in rapidly urbanizing areas like Kathmandu Valley.

Kathmandu Valley↗

Multi-Scale Seismic Measurements for Site Characterization and CO2 Monitoring in an Enhanced Oil Recovery/Carbon Capture, Utilization, and Sequestration Project, Farnsworth Field, Texas

To address the challenges of climate change, significantly more geologic carbon sequestration projects are beginning. The characterization of the subsurface and the migration of the plume of supercritical carbon dioxide are two elements of carbon sequestration that can be addressed through the use of the available seismic methods in the oil and gas industry. In an enhanced oil recovery site in Farnsworth, TX, we employed three separate seismic techniques. The three-dimensional (3D) surface seismic survey required significant planning, design, and processing, but produces both a better understanding of the subsurface structure and a three-dimensional velocity model, which is essential for the second technique, a timelapse vertical seismic profile, and the third technique, cross-well seismic tomography. The timelapse 3D Vertical Seismic Profile (3D VSP) revealed both significant changes in the reservoir between the second and third surveys and geo-bodies that may represent the extent of the underground carbon dioxide. The asymmetry of the primary geo-body may indicate the preferential migration of the carbon dioxide. The third technique, cross-well seismic tomography, suggested a strong correlation between the well logs and the tomographic velocities, but did not observe changes in the injection interval.

Energy & Fuels↗

Controls and relationships of soil organic carbon abundance and persistence vary across pedo–climatic regions

One of the largest uncertainties in the terrestrial carbon cycle is the timing and magnitude of soil organic carbon (SOC) response to climate and vegetation change. This uncertainty prevents models from adequately capturing SOC dynamics and challenges the assessment of management and climate change effects on soils. Reducing these uncertainties requires simultaneous investigation of factors controlling the amount (SOC abundance) and duration (SOC persistence) of stored C. We present a global synthesis of SOC and radiocarbon profiles (n Profile = 597) to assess the timescales of SOC storage. We use a combination of statistical and depth–resolved compartment models to explore key factors controlling the relationships between SOC abundance and persistence across pedo–climatic regions and with soil depth. This allows us to better understand (i) how SOC abundance and persistence covary across pedo–climatic regions and (ii) how the depth dependence of SOC dynamics relates to climatic and mineralogical controls on SOC abundance and persistence. We show that SOC abundance and persistence are differently related; the controls on these relationships differ substantially between major pedo–climatic regions and soil depth. For example, large amounts of persistent SOC can reflect climatic constraints on soils (e.g., in tundra/polar regions) or mineral absorption, reflected in slower decomposition and vertical transport rates. In contrast, lower SOC abundance can be found with lower SOC persistence (e.g., in highly weathered tropical soils) or higher SOC persistence (e.g., in drier and less productive regions). We relate variable patterns of SOC abundance and persistence to differences in the processes constraining plant C input, microbial decomposition, vertical C transport and mineral SOC stabilization potential. This process–oriented grouping of SOC abundance and persistence provides a valuable benchmark for global C models, highlighting that pedo–climatic boundary conditions are crucial for predicting the effects of climate change and soil management on future C abundance and persistence.

54 ENVIRONMENTAL SCIENCES↗

Onshore U.S. Carbon Pipeline Deployment: Siting, Safety, and Regulation

Carbon capture, utilization, and storage (CCUS) technology has significant potential to reduce greenhouse gas (GHG) emissions and mitigate the impact of climate change, particularly in hard to decarbonize industrial and commercial sectors. CCUS involves capturing carbon dioxide (CO 2 ) from industrial processes or power generation and utilizing it for other purposes, such as enhanced oil recovery (EOR), or storing the captured CO 2 underground. CCUS technology can reduce the environmental impact of continued fossil fuel use while smoothing the transition to a low-carbon economy. CCUS can create new economic opportunities, such as the development of new industries and job creation, and can enhance energy security by diversifying energy sources. For these reasons, enabling CCUS has become a key objective of the Biden-Harris administration’s clean energy policy and has received bipartisan support. Despite its environmental and economic potential, CCUS faces multiple barriers to widespread deployment. One of the main challenges is the high cost and technical difficulty of implementing and operating large-scale CCUS infrastructure. CCUS remains a relatively expensive way to reduce carbon emissions (e.g., compared to solar photovoltaic technology’s displacement of coal generation). Additionally, financial incentives and supportive policies like those enacted to support solar photovoltaic development, especially at the state level, are inconsistent or nonexistent, which can discourage investment in CCUS projects. There are also technical challenges associated with safe and secure underground CO 2 storage and the development of new carbon utilization technologies. Public opposition to various aspects of CCUS technologies, ranging from concerns that CCUS will extend reliance on fossil fuels to CCUS infrastructure being sited in disadvantaged communities, is a growing challenge. This paper focuses on another significant barrier to broad CCUS deployment: the need for considerable expansion of the dedicated land-based CO 2 pipeline network in the United States to meet CCUS goals and the unique regulatory challenges to its development. To reach carbon emissions targets in the United States by 2050, CCUS technology will need to be supported by tens of thousands of miles of CO 2 pipelines. Estimates range from a minimum of roughly 29,000 pipeline miles (according to a 2020 Great Plains Institute study) to 66,000 pipeline miles (as per a 2021 Princeton University–led study). As of October 2022, however, the U.S. Department of Transportation (U.S. DOT) reports fewer than 5,400 miles of U.S. pipelines carrying CO 2 . This deficit—and what it means for the prospect of moving substantially larger quantities of CO 2 from source to use or storage—threatens to stifle the development of CCUS projects and technologies identified as an important tool to meet emissions targets. The current regulatory landscape facing CO 2 pipeline development can best be described as uncertain. At the federal level, the U.S. DOT Pipeline and Hazardous Materials Safety Administration (PHMSA) oversees safety regulation of pipelines transporting hazardous materials, including CO 2 upon commencement of operation. However, PHMSA’s definition of CO 2 as “a fluid consisting of more than 90 percent CO 2 molecules compressed to a supercritical state” has not been updated since its 1991 addition to the Federal Register. Because CO 2 can be transported in a gaseous, liquid, or supercritical state (indeed, the physical state of CO 2 can fluctuate within a single pipeline due to environmental changes), doubts persist about the extent of PHMSA’s purview—and raise questions about what, if anything, states should do to address this apparent gap. PHMSA has begun a major revision of its existing rules, but the agency does not expect a first draft before 2024. Economic oversight of CO 2 pipelines is even less clear. The Federal Energy Regulatory Commission (FERC) and Surface Transportation Board (STB)—which regulate the rates of interstate oil/natural gas and non-energy pipelines, respectively—have both declined jurisdiction over interstate CO 2 pipelines. This presumably leaves economic regulation to state and/or local governments, but few if any states have the laws or resources in place to oversee just and reasonable rates. Further, the interstate nature of CO 2 pipeline development creates questions around how different states should align their rate-making decisions. Onshore U.S. Carbon Pipeline Deployment: Siting, Safety, and Regulation Currently, regulatory responsibilities regarding CO 2 pipeline siting and permitting fall to state and local governments. The variety of laws and regulations across the country, however, creates a maze of requirements for pipeline developers to navigate. To secure necessary permits, most states require pipeline companies to be “common carriers” that provide transport service to the public at uniform rates. However, the specific definition of that term varies. Some states require clear evidence that a pipeline services the public, while others automatically deem any pipeline company transporting energy products or hazardous materials to be a “common carrier”—with little consideration for accessibility to third parties. Other states have eschewed common-carrier terminology entirely, placing private and publicly accessible pipelines on equal footing. Much like the variation in common-carrier requirements, laws governing eminent domain authority to secure rights-of-way (ROW) to commence construction on a planned pipeline route differ by state. Several states have no laws or rules governing CO 2 pipelines. In addition to creating questions about whether long-standing rules for other pipelines (e.g., natural gas or petroleum products) apply to CO 2 , this policy vacuum leaves local governments as the sole authority over sections of pipe within their boundaries. With dozens of counties along a given route, the probability of inconsistent regulation of the same pipeline is significant. Even in states with CO 2 pipeline laws in place, local regulatory attempts to address rising concerns over pipeline routing and safety have triggered lawsuits by pipeline companies seeking to delimit areas of federal, state, and local government responsibility. Meanwhile, legislators across the country have introduced bills to restrict the application of eminent domain to CO 2 pipeline projects, which could threaten a key means of securing ROW that companies cannot secure through negotiation with landowners. Taken separately, any of these regulatory issues—the narrow federal definition of CO 2 , FERC’s and STB’s decisions that CO 2 pipelines are not within their jurisdiction, and the considerable variation in state and local governments’ laws regulating CO 2 pipeline technologies—are extremely difficult to resolve. Adding the required scale of CO 2 pipeline expansion and the currently identified narrow window of time in which to reach climate target goals, the task becomes even more difficult—and raises a host of urgent questions for regulators. How should CO 2 be defined in federal regulations to ensure consistent safety standards across the country? What is the potential impact radius of a CO 2 pipeline rupture, and how should that inform local emergency response? In the absence of centralized federal oversight, what should state legislatures do to increase alignment for interstate CO 2 pipeline projects? This paper intends to serve as a primer for regulators and stakeholders who seek to better understand the regulatory challenges and opportunities facing this critical infrastructure.

42 ENGINEERING↗

Hydrologic Regionalization under Data Scarcity: Implications for Streamflow Prediction

Continuous streamflow prediction is crucial in many applications of water resources planning and management. However, streamflow prediction is challenging, particularly in data-scarce regions. Here, we demonstrate an approach to regionalize the flow duration curve for predicting daily streamflow in the data-scare region of the central Himalayas. We developed a regression-based model to estimate streamflow at various segments of a flow duration curve by incorporating basin characteristics and climate variables. This study analyzes the sensitivities of proximity and characteristics between the donor (gauged) and receptor (ungauged) basins for time-series streamflow prediction. Our results show that regionalization techniques perform better in low to medium flows over high flows. Our findings are significant in the central Himalayan regional context to inform operational and management decisions in water sector projects like hydropower plants, which generally rely on low-to-medium streamflow information. Although the quantitative results are region-specific, the approach and insights are generalizable to the Himalayan region.

54 ENVIRONMENTAL SCIENCES↗

Knowledge-guided machine learning can improve carbon cycle quantification in agroecosystems

Abstract Accurate and cost-effective quantification of the carbon cycle for agroecosystems at decision-relevant scales is critical to mitigating climate change and ensuring sustainable food production. However, conventional process-based or data-driven modeling approaches alone have large prediction uncertainties due to the complex biogeochemical processes to model and the lack of observations to constrain many key state and flux variables. Here we propose a Knowledge-Guided Machine Learning (KGML) framework that addresses the above challenges by integrating knowledge embedded in a process-based model, high-resolution remote sensing observations, and machine learning (ML) techniques. Using the U.S. Corn Belt as a testbed, we demonstrate that KGML can outperform conventional process-based and black-box ML models in quantifying carbon cycle dynamics. Our high-resolution approach quantitatively reveals 86% more spatial detail of soil organic carbon changes than conventional coarse-resolution approaches. Moreover, we outline a protocol for improving KGML via various paths, which can be generalized to develop hybrid models to better predict complex earth system dynamics.

54 ENVIRONMENTAL SCIENCES↗