Results for “environmental context” — Page 45

DOE OSTI2022

The impact of habitat fragmentation on domatia-dwelling mites and a mite-plant-fungus tritrophic interaction

Abstract Context Habitat fragmentation is a leading threat to biodiversity, yet the impacts of fragmentation on most taxa, let alone interactions among those taxa, remain largely unknown. Objectives We studied how three consequences of fragmentation—reduced patch connectivity, altered patch shape, and edge proximity—impact plant-dwelling mite communities and mite-plant-fungus interactions within a large-scale habitat fragmentation experiment. Methods We sampled mite communities from the leaves of Quercus nigra (a plant species that has foliar domatia which harbor fungivorous and predacious mites) near and far from edge within fragments of varying edge-to-area ratio (shape) and connectivity via corridors. We also performed a mite-exclusion experiment across these fragmentation treatments to test the effects of mite presence and fungal hyphal abundance on leaf surfaces. Results Habitat edges influenced the abundance and richness of leaf-dwelling mites; plants closer to the edge had higher mite abundance and species richness. Likewise, hyphal counts were higher on leaves near patch edges. Despite both mite and fungal abundance being higher at patch edges, leaf hyphal counts were not impacted by mite abundance on those leaves. Neither patch shape nor connectivity influenced mite abundance, mite species richness, or the influence of mites on leaf surface fungal abundance. Conclusion Our results suggest that mites and foliar fungi may be independently affected by edge-structured environmental gradients, like temperature, rather than trophic effects. We demonstrate that large-scale habitat fragmentation and particularly edge effects can have impacts on multiple levels of microscopic communities, even in the absence of cascading trophic effects.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Further understanding “severe” climate risk

What makes one climate risk more “severe” or “dangerous” than others? Acknowledging that the notion of dangerousness can substantially vary from one sociocultural context to another, this Perspective paper builds on recent literature to explore three notions that are estimated to be foundational to climate risk severity: the physical, ecological and social thresholds leading to transformational and possibly abrupt changes; the irreversibility of these changes; and the cascading effects within and across the systems affected. While not necessarily the most determining dimensions of risk, they deserve more attention and integration into frameworks to assess “severe” climate risk, such frameworks remaining under-developed. The paper also takes stock of issues related to the spatial scale(s) of and the evidence base for severe climate risks. It lands on four intertwined research directions across geographies, sectors and populations, that are hypothesized to play a critical role in the coming decade, from feeding the next IPCC cycle to more broadly supporting the development of anticipatory adaptation policies.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Unexpected Changes of Aerosol Burdens With Decreased Convection in the Context of Scale-Aware Convection Schemes

Atmospheric aerosols in global climate models (GCMs) can be removed by both large-scale and convective precipitation. As the horizontal resolution of GCMs increases, it is expected that large-scale precipitation increases and convective precipitation decreases if scale-aware convection schemes are well developed. Here, to explore its impact on aerosol burdens, this study develops a novel method and applies it to the National Center for Atmospheric Research Community Atmosphere Model version 5.3 to mimic the behavior of scale-aware convective schemes. Surprisingly, it is found that aerosol burden increases globally as convective precipitation decreases and large-scale precipitation increases, which can be attributed to the reduced light rain. In the light-rain intensity category, the decreased frequency of convective precipitation is not offset by the increased frequency of large-scale precipitation. Therefore, for aerosol simulations in high-resolution GCMs using scale-aware convection schemes, subgrid convection and large-scale condensation should be coordinated to assure light rain stays the same.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Extratropical shortwave cloud feedbacks in the context of the global circulation and hydrological cycle

Shortwave (SW) cloud feedback ($SW_{FB}$) is the primary driver of uncertainty in the effective climate sensitivity (ECS) predicted by global climate models (GCMs). ECS for several GCMs participating in the sixth assessment report exceed 5K, above the fifth assessment report ‘likely’ maximum (4.5K) due to extratropical $SW_{FB}$’s that are more positive than those simulated in the previous generation of GCMs. Here we show that across 57 GCMs Southern Ocean $SW_{FB}$ can be predicted from the sensitivity of column-integrated liquid water mass (LWP) to moisture convergence and to surface temperature. In this work, the response of LWP to moisture convergence and the response of albedo to LWP anti-correlate across GCMs. This is because GCMs that simulate a larger response of LWP to moisture convergence tend to have higher mean-state LWPs, which reduces the impact of additional LWP on albedo. Observational constraints suggest a modestly negative Southern Ocean $SW_{FB}$— inconsistent with extreme ECS.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2020

A Quantitative Hydroclimatic Context for the European Great Famine of 1315–1317

The European Great Famine of 1315–1317 triggered one of the worst population collapses in European history and ranks as the single worst European famine in mortality as a proportion of population. Historical records point to torrential rainfall, land saturation, crop failure, and prolonged flooding as important causes of the famine. Here we use the tree-ring based Old World Drought Atlas (OWDA) to show that the average of each growing season preceding the Great Famine years (1314–1316) was the fifth wettest over Europe from 1300 to 2012 C.E. The spatial and temporal characteristics of our OWDA-estimated anomalies are in excellent agreement with available historical accounts. We also characterize a mode of European hydroclimate variability that is associated with the Great Famine, which we term the “Great Famine mode.” This mode emerges as the leading mode of European hydroclimate variability from 1300–2012 and is strongly associated with extreme wet and dry events in Europe over the last millennium.

Environmental impact↗

DOE OSTI2023

Evaluating the incentive for soil organic carbon sequestration from carinata production in the Southeast United States

Soil organic carbon (SOC) can be increased by cultivating bioenergy crops to produce low-carbon fuels, improving soil quality and agricultural productivity. This study evaluates the incentives for farmers to sequester SOC by adopting a bioenergy crop, carinata. Two agricultural management scenarios – business as usual (BaU) and a climate-smart (no-till) practice – were simulated using an agent-based modeling approach to account for farmers’ carinata adoption rates within their context of traditional crop rotations, the associated profitability, influences of neighboring farmers, as well as their individual attitudes. Here, using the state of Georgia, US, as a case study, the results show that farmers allocated 1056 × 10 3 acres (23.8%; 2.47 acres is equivalent to 1 ha) of farmlands by 2050 at a contract price of $\$6.5$ per bushel of carinata seeds and with an incentive of $50Mg -1 CO2e SOC sequestered under the BaU scenario. In contrast, at the same contract price and SOC incentive rate, farmers allocated 1152 × 10 3 acres (25.9%) of land under the no-till scenario, while the SOC sequestration was 483.83 × 10 3 Mg CO2e, which is nearly four times the amount under the BaU scenario. Thus, this study demonstrated combinations of seed prices and SOC incentives that encourage farmers to adopt carinata with climate-smart practices to attain higher SOC sequestration benefits.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

An Architectural Survey of the U12G Tunnel Historic District, Nevada National Security Site, Nye County, Nevada

The U.S. Department of Energy (DOE), in conjunction with the National Nuclear Security Administration Nevada Field Office (NNSA/NFO), proposes to demolish six buildings and three storage areas located at the U12g Tunnel portal area in Area 12 of the Nevada National Security Site (NNSS). The buildings are 12-358 (Signal Vault); 12-201800 (Storage Quonset Hut); 12-202555 (Walker Shack); 12-868 (Pipe Assembly); 12-B100933 (Electrical Shop); 12-B100944 (Conference Room); and Storage Area 1; Storage Area 2; and Storage Area 3. The buildings and storage areas were selected for demolition as part of the DOE’s Real Property Efficiency Plan to reduce the footprint of unused and non-operational facilities on the NNSS. They are all vacant and have no proposed uses for current or upcoming NNSS missions. Demolition activities constitute an undertaking subject to review under Section 106 of the National Historic Preservation Act (NHPA) (54 United States Code [USC] § 306101) and its implementing regulations, 36 Code of Federal Regulations (CFR) Part 800. Identification efforts began with resources proposed for demolition in federal Fiscal Year (FY) 23. Four buildings were proposed to be demolished in FY23 (12-358, 12-868, 12-201800, and 12-202555). These buildings and the U12g Tunnel Historic District (SHPO No. D444) were recorded in Identification, Evaluation, and Finding of Adverse Effect for the Proposed Demolition of Five Buildings in Area 12, Nevada National Security Site, Nye County, Nevada (Menocal et al. 2023). Identification efforts indicated three buildings (12-358, 12-201800, and 12-868) supported nuclear testing in the U12g Tunnel. The fourth building post-dated the use of U12g Tunnel for nuclear testing activities. The report recommended that three of the four buildings (12-358, 12-201800, 12-868) and the U12g Tunnel Historic District may be eligible for the National Register of Historic Places (NRHP). The report also found that the undertaking would have an adverse effect on the three buildings and on the historic district. The Nevada State Historic Preservation Office (SHPO) concurred with the report’s findings (Reed 2023). The U12g Tunnel was determined eligible as a historic district under the Secretary of the Interior’s (SOI) Significance Criterion A, at the local level, in the context of the Cold War as an underground testing environment for the development of nuclear weapons and to assess the effects of a nuclear explosion on materials and equipment with a period of significance from 1959 to 1971. It was also determined eligible under Significance Criterion C for embodying the distinctive characters of a horizontal tunnel complex used for nuclear testing and as a significant and distinguishable entity. The three buildings were determined to be contributing elements of the district. The undertaking was expanded with the addition of two buildings and three storage areas proposed to be demolished and located within U12g Tunnel Historic District in FY24. These five resources (12-B100933, 12-B100944, and Storage Areas 1, 2, and 3) were recorded in Supplemental Identification, Evaluation, and Finding of Effect for Additional Proposed Demolition at U12g Tunnel, Area 12, Nevada national Security Site, Nye County, Nevada (Brannan et al. 2024). Identification efforts indicated that the two buildings and Storage Area 1 supported nuclear testing in the U12g Tunnel. Storage Area 1 and Storage Area 2 post-dated the nuclear testing activities at U12g Tunnel and were not recommended as contributing elements to the district. The report also found that the undertaking would have an adverse effect on the newly identified buildings and one storage area and on the historic district. The SHPO concurred that the expanded undertaking would result in adverse effects to historic properties (Reed 2025). To resolve these adverse effects, NNSA/NFO, in consultation with the SHPO, is following standard mitigation as stipulated in the 2024 Programmatic Agreement DE-GM58-22NA25554 Among the U.S. Department of Energy and the Nevada State Historic Preservation Officer and the Advisory Council on Historic Preservation Concerning the Protection of Historic Properties on the Nevada National Security Site, Nye County, Nevada (hereafter referred to as the NNSS PA). The standard mitigation measures are outlined in Appendix D of the NNSS PA. As such, this architectural survey has been prepared in accordance with Appendix D of the NNSS PA and follows the report format outlined in Appendix F. It includes a historic context that describes the district’s origin, history, and support functions, its significance in the context of nuclear testing on the NNSS, and identifies contributing and non-contributing elements within the district. The report is accompanied by Architectural Resource Assessment (ARA) forms for individual resources and a Historic District Resource Assessment (HDRA) for the U12g Tunnel Historic District. In total, this architectural report identified 32 primary resources within the district boundary. Six of the primary resources were previously identified as contributing elements. An additional 17 resources are recommended as contributing elements to the district for a total of 23 contributing elements. The other nine resources identified are recommended as non-contributing elements to the district.

12-201800↗

DOE OSTI2020

Context for interpreting equilibrium climate sensitivity and transient climate response from the CMIP6 Earth system models

For the current generation of earth system models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6), the range of equilibrium climate sensitivity (ECS, a hypothetical value of global warming at equilibrium for a doubling of CO 2 ) is 1.8°C to 5.6°C, the largest of any generation of models dating to the 1990s. Meanwhile, the range of transient climate response (TCR, the surface temperature warming around the time of CO 2 doubling in a 1% per year CO 2 increase simulation) for the CMIP6 models of 1.7°C (1.3°C to 3.0°C) is only slightly larger than for the CMIP3 and CMIP5 models. Here we review and synthesize the latest developments in ECS and TCR values in CMIP, compile possible reasons for the current values as supplied by the modeling groups, and highlight future directions. Cloud feedbacks and cloud-aerosol interactions are the most likely contributors to the high values and increased range of ECS in CMIP6.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRSDate not supplied

More Data Needed for Failure Rate Estimation, Validation, and Uncertainty Reduction

The currently planned schedule for advanced Environmental Control and Life Support System (ECLSS) development and test activities to support human exploration missions is unlikely to generate sufficient data to enable statistically-supportable, precise Orbital Replacement Unit (ORU) failure rate estimates to meet existing crew safety expectations. Accurate and precise failure rate estimates are critical for missions beyond Low Earth Orbit (LEO) because current risk mitigation approaches –namely regular resupply and rapid abort capabilities –will not be available. Safe operations will depend on mission planners’ ability to accurately forecast spares demand and efficiently provide the necessary resources. However, even after more than a decade of International Space Station (ISS) ECLSS operations, a significant amount of uncertainty remains in failure rate estimates. Uncertain or inaccurate failure rates result in increased risk and spares mass. A Bayesian estimation approach, such as the one currently implemented by the ISS Program, can reduce uncertainty by incorporating engineering judgement into failure rate estimates. However, experience on the ISS and with other complex systems shows that these prior failure rate estimates are often inaccurate. In addition, prior estimates are typically point values; some level of uncertainty must be added to convert these into probability distributions for Bayesian updating, and there are several potential methods for doing so. Due to the low rate of data collection, any inaccuracy in theseprior estimates currently hasa strong influence on the end result. This paper examines the challenges associated with failure rate estimation, validation, and uncertainty reduction in the context of ECLSS development for beyond-LEO missions. A variety of techniques for generating and updating Bayesian priors are discussed and evaluated using both real-world and simulated data. Potential solutions for improving failure rate estimation, including testing additional units, are analyzed and discussed, and a set of recommendations are provided for next-generation system development activities.

Reliability↗

NASA NTRSDate not supplied

More Data Needed for Failure Rate Estimation, Validation, and Uncertainty Reduction

The currently planned schedule for advanced Environmental Control and Life Support System (ECLSS) development and test activities to support human exploration missions is unlikely to generate sufficient data to enable statistically-supportable, precise Orbital Replacement Unit (ORU) failure rate estimates to meet existing crew safety expectations. Accurate and precise failure rate estimates are critical for missions beyond Low Earth Orbit (LEO) because current risk mitigation approaches –namely regular resupply and rapid abort capabilities –will not be available. Safe operations will depend on mission planners’ ability to accurately forecast spares demand and efficiently provide the necessary resources. However, even after more than a decade of International Space Station (ISS) ECLSS operations, a significant amount of uncertainty remains in failure rate estimates. Uncertain or inaccurate failure rates result in increased risk and spares mass. A Bayesian estimation approach, such as the one currently implemented by the ISS Program, can reduce uncertainty by incorporating engineering judgement into failure rate estimates. However, experience on the ISS and with other complex systems shows that these prior failure rate estimates are often inaccurate. In addition, prior estimates are typically point values; some level of uncertainty must be added to convert these into probability distributions for Bayesian updating, and there are several potential methods for doing so. Due to the low rate of data collection, any inaccuracy in theseprior estimates currently hasa strong influence on the end result. This paper examines the challenges associated with failure rate estimation, validation, and uncertainty reduction in the context of ECLSS development for beyond-LEO missions. A variety of techniques for generating and updating Bayesian priors are discussed and evaluated using both real-world and simulated data. Potential solutions for improving failure rate estimation, including testing additional units, are analyzed and discussed, and a set of recommendations are provided for next-generation system development activities.

Reliability↗

DOE OSTI2022

Capabilities of an Acoustic Camera to Inform Fish Collision Risk with Current Energy Converter Turbines

A diversified energy portfolio may include marine energy in the form of current energy converters (CECs) such as tidal or in-river turbines. New technology development in the research stage typically requires monitoring for environmental effects. A significant environmental effect of concern for CECs is the risk of moving parts (e.g., turbine blades) colliding with animals such as fishes. CECs are installed in energetic locations in which it is difficult to operate sensors to fulfill monitoring requirements for informing collision risk. Collecting data (i.e., about blade strikes or near-misses) that inform interactions of fishes with CECs is usually attempted using active acoustic sensors or video cameras (VCs). Limitations of low-light conditions or water turbidity that preclude effective use of VCs are overcome by using high-resolution multibeam echosounders (or acoustic cameras (ACs)). We used an AC at two sites to test its ability to detect artificial and real fish targets and determine if strike, near-miss, and near-field behavior could be observed. Interactions with fish and artificial targets with turbines have been documented but strike confirmation with an AC is novel. The first site was in a tidal estuary with a 25 kW turbine and water clarity sufficient to allow VC data to be collected concurrently with AC data showing turbine blade strike on tethered artificial fish targets. The second site was a turbid, debris-laden river with a 5 kW turbine where only AC data were collected due to high water turbidity. Data collection at the second site coincided with downstream Pacific salmon (Oncorhynchus spp.) smolt migration. Physical fish capture downstream of the turbine was performed with an incline plane trap (IPT) to provide context for the AC observations, by comparing fish catches. Discrimination between debris and fishes in the AC data was not possible, because active movement of fishes was not discernable. Nineteen fishes were released upstream of the turbine to provide known times of possible fish/turbine interactions, but detection was difficult to confirm in the AC data. ACs have been used extensively in past studies to count large migratory fish such as Pacific salmon, but their application for small fish targets has been limited. The results from these two field campaigns demonstrate the ability of ACs to detect targets in turbid water and observe blade strikes, as well as their limitations such as the difficulty of distinguishing small fishes from debris in a high-energy turbid river. Recommendations are presented for future applications associated with CEC device testing.

16 TIDAL AND WAVE POWER↗

NASA NTRSDate not supplied

More Data Needed for Failure Rate Estimation, Validation, and Uncertainty Reduction

Current Environmental Control and Life Support System (ECLSS) development and test activities are not generating data fast enough to provide statistically-supportable precise Orbital Replacement Unit (ORU) failure rate estimates for future missions. Accurate and precise failure rate estimates are critical for missions beyond Low Earth Orbit (LEO) because current risk mitigation approaches – namely regular resupply and rapid abort capabilities – will not be available. Safe operations will depend on mission planners’ ability to accurately forecast spares demand and efficiently provide the necessary resources. However, even after more than a decade of operations on board the International Space Station (ISS), a significant amount of uncertainty remains in failure rate estimates. Uncertain or inaccurate failure rates result in increased risk and spares mass for future missions. A Bayesian failure rate estimation approach, such as the one currently implemented by the ISS Program, can help reduce uncertainty by incorporating engineering judgement into failure rate estimates. However, experience on the ISS and with other complex systems shows that these prior failure rate estimates are often inaccurate. In addition, prior failure rate estimates are typically point values; some level of uncertainty must be added to convert these into probability distributions for Bayesian updating, and there are several potential methods for doing so. Due to the low rate of data collection, these subjective (and often inaccurate) prior estimates currently have a strong influence on the end result. This paper examines the challenges associated with failure rate estimation, validation, and uncertainty reduction in the context of ECLSS development for beyond-LEO missions. A variety of techniques for generating and updating Bayesian priors are discussed and evaluated using both real-world and simulated data. Potential solutions for improving failure rate estimation, including testing additional units, are analyzed and discussed, and a set of recommendations are provided for next-generation system development activities.

Supportability↗

DOE OSTI2020

Bioprocessing Separations Consortium Three-Year Overview: Technical Advances, Process Economics Influence, and State of the Science

The Bioprocessing Separations Consortium solves separations challenges that are unique to bioprocessing. To do this, the Consortium uses two methods: applying existing technologies to new challenges and developing new technologies that may address these unique challenges better than today’s commercial technologies. In its research and development, the Consortium leverages its three core capabilities: materials development and evaluation, process development, and analysis and computation. In its first three years, from 2016 to 2019, the Consortium addressed four critical challenges in biochemical and thermochemical processing. First, the Consortium targeted the fractionation of lignin to enable valorization of this portion of biomass that offers diverse, complex, and valuable building blocks and products. Second, Consortium researchers developed technologies to enable process intensification, which can reduce equipment needs, energy consumption, and waste generation, thereby cutting bioprocessing capital costs and rendering processes more efficient. Third, the Consortium sought to recover carbon from dilute aqueous streams that are common to bioprocessing; recovering dilute carbon can improve process efficiency and economics. Finally, Consortium researchers designed and developed new materials and catalysts to reduce targeted foulants and poisons in bioprocessing streams that can limit the lifetime of downstream catalysts or fermenting microorganisms. Table 1 lists the technologies that were examined and places them in the context of the Consortium’s capabilities, types of bioprocesses, and critical challenges in bioprocessing separations. Overall, across these projects, we have developed separations technologies for 10 bioprocesses, addressed 9 target compounds in bioprocessing, developed 10 materials, and evaluated 4 processes for cost and sustainability.

09 BIOMASS FUELS↗

DOE OSTI2020

Multiple elements of soil biodiversity drive ecosystem functions across biomes

The role of soil biodiversity in regulating multiple ecosystem functions is poorly understood, limiting our ability to predict how soil biodiversity loss might affect human wellbeing and ecosystem sustainability. Furthermore, combining a global observational study with an experimental microcosm study, we provide evidence that soil biodiversity (bacteria, fungi, protists and invertebrates) is significantly and positively associated with multiple ecosystem functions. These functions include nutrient cycling, decomposition, plant production, and reduced potential for pathogenicity and belowground biological warfare. Our findings also reveal the context dependency of such relationships and the importance of the connectedness, biodiversity and nature of the globally distributed dominant phylotypes within the soil network in maintaining multiple functions. Moreover, our results suggest that the positive association between plant diversity and multifunctionality across biomes is indirectly driven by soil biodiversity. Together, our results provide insights into the importance of soil biodiversity for maintaining soil functionality locally and across biomes, as well as providing strong support for the inclusion of soil biodiversity in conservation and management programmes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Data-Informed Evaluation Framework for Integrated Energy Systems: Insights from Power, Process Heat, and Hydrogen Production Applications

The multi-criteria decision analysis (MCDA) framework provides a systematic evaluation of the diverse preferences and performance metrics associated with alternative solutions. This approach is advantageous over a single-criterion methodology, which are only valid under conditions that assume ceteris paribus or an "apples-to-apples" comparison. However, selecting suitable technologies for integrated energy systems (IES) can be likened to an "apples-to-oranges" comparison, given the heterogeneous factors at stake. These factors include economics and performance parameters, geological compatibility, and environmental impacts. Consequently, past research has often employed a mixture of qualitative and quantitative criteria tailored to the specific interests of each study. While the method proves effective in handling the intricate interplay of criteria, the resulting rankings and scores can vary from study to study. This inconsistency is introduced from the use of subjectively defined thresholds and weights. As a result, decision-makers frequently find it challenging to establish clear connections between specific criteria and the resulting scores, as the transformation of criteria into ordinal scores results in a substantial loss of information. To address this challenge, we introduce a data-informed IES evaluation framework that offers comprehensive, interpretable, and traceable evaluations backed by quantifiable rationale. First, we identified key IES evaluation criteria from a decade of literature, focusing on relevant IES applications in power, process heat, and hydrogen production. We leveraged state-of-the-art cost estimates from the Idaho National Laboratory (INL) and technical data from 78 reactor designs from the International Atomic Energy Agency (IAEA) and the Organization for Economic Co-operation and Development - Nuclear Energy Agency (OECD-NEA). Lastly, we established thresholds by analyzing the mean, variance, root mean square, and slope of values across alternatives, categorizing the preferences of decision-makers into distinct utility functions, such as linear, saturating, exponential, and stepwise. Our approach yielded two main outcomes: (1) it provided consistent assessments across different stakeholder groups and (2) it visualized uncertainties in the decision-making context via comprehensive sensitivity analysis. To demonstrate the impact of our framework, we conducted case studies on 6 reactor designs (AP1000, NuScale, BWRX-300, Xe-100, eVinci, iMSR) for the three applications. Our data-driven framework proved to be highly effective in addressing heterogenous uncertainties faced by varied decision-makers? preferences and IES applications, as well as cost and technical estimates of advanced reactors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Developing a sustainability science approach for water systems

We convened a workshop to enable scientists who study water systems from both social science and physical science perspectives to develop a shared language. This shared language is necessary to bridge a divide between these disciplines’ different conceptual frameworks. As a result of this workshop, we argue that we should view socio-hydrological systems as structurally co-constituted of social, engineered, and natural elements and study the “characteristic management challenges” that emerge from this structure and reoccur across time, space, and socioeconomic contexts. This approach is in contrast to theories that view these systems as separately conceptualized natural and social domains connected by bi-directional feedbacks, as is prevalent in much of the water systems research arising from the physical sciences. A focus on emergent characteristic management challenges encourages us to go beyond searching for evidence of feedbacks and instead ask questions such as: What types of innovations have successfully been used to address these challenges? What structural components of the system affect its resilience to hydrological events and through what mechanisms? Are there differences between successful and unsuccessful strategies to solve one of the characteristic management challenges? If so, how are these differences affected by institutional structure and ecological and economic contexts? To answer these questions, social processes must now take center stage in the study and practice of water management. We also argue that water systems are an important class of coupled systems with relevance for sustainability science because they are particularly amenable to the kinds of systematic comparisons that allow knowledge to accumulate. Indeed, the characteristic management challenges we identify are few in number and recur over most of human history and in most geographical locations. This recurrence should allow us to accumulate knowledge to answer the above questions by studying the long historical record of institutional innovations to manage water systems.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Data-Informed Evaluation Framework for Integrated Energy Systems: Insights from Power, Process Heat, and Hydrogen Production Applications

The multi-criteria decision analysis (MCDA) framework provides a systematic evaluation of the diverse preferences and performance metrics associated with alternative solutions. This approach is advantageous over a single-criterion methodology, which are only valid under conditions that assume ceteris paribus or an "apples-to-apples" comparison. However, selecting suitable technologies for integrated energy systems (IES) can be likened to an "apples-to-oranges" comparison, given the heterogeneous factors at stake. These factors include economics and performance parameters, geological compatibility, and environmental impacts. Consequently, past research has often employed a mixture of qualitative and quantitative criteria tailored to the specific interests of each study. While the method proves effective in handling the intricate interplay of criteria, the resulting rankings and scores can vary from study to study. This inconsistency is introduced from the use of subjectively defined thresholds and weights. As a result, decision-makers frequently find it challenging to establish clear connections between specific criteria and the resulting scores, as the transformation of criteria into ordinal scores results in a substantial loss of information. To address this challenge, we introduce a data-informed IES evaluation framework that offers comprehensive, interpretable, and traceable evaluations backed by quantifiable rationale. First, we identified key IES evaluation criteria from a decade of literature, focusing on relevant IES applications in power, process heat, and hydrogen production. We leveraged state-of-the-art cost estimates from the Idaho National Laboratory (INL) and technical data from 78 reactor designs from the International Atomic Energy Agency (IAEA) and the Organization for Economic Co-operation and Development - Nuclear Energy Agency (OECD-NEA). Lastly, we established thresholds by analyzing the mean, variance, root mean square, and slope of values across alternatives, categorizing the preferences of decision-makers into distinct utility functions, such as linear, saturating, exponential, and stepwise. Our approach yielded two main outcomes: (1) it provided consistent assessments across different stakeholder groups and (2) it visualized uncertainties in the decision-making context via comprehensive sensitivity analysis. To demonstrate the impact of our framework, we conducted case studies on 6 reactor designs (AP1000, NuScale, BWRX-300, Xe-100, eVinci, iMSR) for the three applications. Our data-driven framework proved to be highly effective in addressing heterogenous uncertainties faced by varied decision-makers? preferences and IES applications, as well as cost and technical estimates of advanced reactors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Emerging concepts in intermediate carbon dioxide emplacement to support carbon dioxide removal

Substantial upscaling of carbon dioxide capture is possible in the coming decades but existing solutions for storage are projected to be limited in annual capacity by as much as 2–10 GtCO 2 per year until mid-century. Temporary storage of CO 2 in a solid or liquid state could prove useful for filling this gap in capacity, until more permanent and ideally lucrative CO 2 sequestration options come online. There are several concepts for reversible solid-state and chemical CO 2 storage, but their advantages and limitations have yet to be reviewed in this context. This article focuses on the physical and chemical aspects of CO 2 storage via liquid and solid chemical carriers and sorbents, and gives an overview of the energetics around their use, as well as prospects for their future development. Exciting opportunities for coupling capture and medium to high maturity multi-year storage technologies could support carbon removal in the coming decades. Highlights of the analysis are the remarkable storage capacity of oxalic acid and formic acid (CO 2 -density of 1857 kg m –3 and 1152 kg m –3 , compared with condensed liquid CO 2 at 993–1096 kg m –3 , respectively), the relative scalability and compatibility of carbonate salts for stationary storage with direct air capture, and the potential promise of multiple carriers for CO 2 transportation. Solid sorbents do not achieve such ultra-high storage capacities, but could improve storage over compressed gas tanks on a capacity and energetics basis.

54 ENVIRONMENTAL SCIENCES↗