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DOE OSTI2016

Current and future ozone risks to global terrestrial biodiversity and ecosystem processes

Abstract Risks associated with exposure of individual plant species to ozone (O 3 ) are well documented, but implications for terrestrial biodiversity and ecosystem processes have received insufficient attention. This is an important gap because feedbacks to the atmosphere may change as future O 3 levels increase or decrease, depending on air quality and climate policies. Global simulation of O 3 using the Community Earth System Model ( CESM ) revealed that in 2000, about 40% of the Global 200 terrestrial ecoregions ( ER ) were exposed to O 3 above thresholds for ecological risks, with highest exposures in North America and Southern Europe, where there is field evidence of adverse effects of O 3 , and in central Asia. Experimental studies show that O 3 can adversely affect the growth and flowering of plants and alter species composition and richness, although some communities can be resilient. Additional effects include changes in water flux regulation, pollination efficiency, and plant pathogen development. Recent research is unraveling a range of effects belowground, including changes in soil invertebrates, plant litter quantity and quality, decomposition, and nutrient cycling and carbon pools. Changes are likely slow and may take decades to become detectable. CESM simulations for 2050 show that O 3 exposure under emission scenario RCP 8.5 increases in all major biomes and that policies represented in scenario RCP 4.5 do not lead to a general reduction in O 3 risks; rather, 50% of ER s still show an increase in exposure. Although a conceptual model is lacking to extrapolate documented effects to ER s with limited or no local information, and there is uncertainty about interactions with nitrogen input and climate change, the analysis suggests that in many ER s, O 3 risks will persist for biodiversity at different trophic levels, and for a range of ecosystem processes and feedbacks, which deserves more attention when assessing ecological implications of future atmospheric pollution and climate change.

Fuhrer, Jürg↗

DOE OSTI2016

Paths to future growth in photovoltaics manufacturing

The past decade has seen rapid growth in the photovoltaics industry, followed in the past few years by a period of much slower growth. A simple model that is consistent with this historical record can be used to predict the future evolution of the industry. Two key parameters are identified that determine the outcome. One is the annual global investment in manufacturing capacity normalized to the manufacturing capacity for the previous year (capacity-normalized capital investment rate, CapIR, units dollar/W). The other is how much capital investment is required for each watt of annual manufacturing capacity, normalized to the service life of the assets (capacity-normalized capital demand rate, CapDR, units dollar/W). If these two parameters remain unchanged from the values they have held for the past few years, global manufacturing capacity will peak in the next few years and then decline. However, it only takes a modest improvement in CapIR to ensure future growth in photovoltaics. Here, several approaches are presented that can enable the required improvement in CapIR. If, in addition, there is an accompanying improvement in CapDR, the rate of growth can be substantially accelerated.

14 SOLAR ENERGY↗

DOE OSTI2019

Monitoring the effectiveness of floodplain habitat restoration: A review of methods and recommendations for future monitoring

Abstract Floodplains are some of the most ecologically important and human‐impacted habitats throughout the world. Large efforts are underway in North America, Europe, Australia, and elsewhere to restore floodplain habitats, not only to increase fish and aquatic biota but to restore ecological diversity. As the scale, number, and complexity of floodplain restoration projects has increased, so has the need for rigorous monitoring and evaluation to demonstrate effectiveness and guide future floodplain restoration efforts. Moreover, technological advances in remote sensing, genetics, and fish marking have been evolving rapidly and there is need to update guidance on the best methods for monitoring physical and biological response to floodplain restoration. A comprehensive review of the restoration literature located 180 papers that specifically examined the effectiveness of various floodplain restoration techniques. The various methods that were historically and currently used to evaluate the physical (channel and floodplain morphology, sediment, flow, water quality [temperature and nutrients]) and biological (fish, invertebrates, and aquatic and riparian plants) effectiveness of floodplain restoration were reviewed and used to provide recommendations for future monitoring. For each major physical and biological monitoring method, we discuss their importance, how they have historically been used to evaluate floodplain restoration, newer methodologies, and limitations or advantages of different methodologies and approaches. We then discuss monitoring the effectiveness of small (<2 km in main channel length) and large (>2 km of main channel length) floodplain projects, with recommendations for various study designs, parameters, and monitoring methodologies. This article is categorized under: Water and Life > Conservation, Management, and Awareness Water and Life > Methods

Roni, Philip↗

DOE OSTI2020

Chapter 7: Predictive Analytics in Future Power Systems: A Panorama and State-of-the-Art of Deep Learning Applications

The challenges surrounding the optimal operation of power systems are growing in various dimensions, due in part to increasingly distributed energy resources and a progression towards large-scale transportation electrification. Currently, the increasing uncertainties associated with both renewable energy generation and demand are largely being managed by increasing operational reserves - potentially at the cost of suboptimal economic conditions - in order to maintain the reliability of the system. This chapter looks at the big picture role of forecasting in power systems from generation to consumption and provides a comprehensive review of traditional approaches for forecasting generation and load in various contexts. This chapter then takes a deep dive into the state-of-the-art machine learning and deep learning approaches for power systems forecasting. Furthermore, a case study of multi-time-horizon solar irradiance forecasting using deep learning is discussed in detail. Smart grids form the backbone of the future interdependent networks. For addressing the challenges associated with the operations of smart grid, development and wide adoption of machine learning and deep learning algorithms capable of producing better forecasting accuracies is urgently needed. Along with exploring the implementation and benefits of these approaches, this chapter also considers the strengths and limitations of deep learning algorithms for power systems forecasting applications. This chapter, thus, provides a panoramic view of state-of-the-art of predictive analytics in power systems in the context of future smart grid operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2016

Future collider signatures of the possible 750 GeV state

If the recent indications of a possible state Φ with mass ~ 750 GeV decaying into two photons reported by ATLAS and CMS in LHC collisions at 13 TeV were to become confirmed, the prospects for future collider physics at the LHC and beyond would be affected radically, as we explore in this paper. Even minimal scenarios for the Φ resonance and its γγ decays require additional particles with masses ≳$\frac{1}{2}$mΦ . We consider here two benchmark scenarios that exemplify the range of possibilities: one in which Φ is a singlet scalar or pseudoscalar boson whose production and γγ decays are due to loops of coloured and charged fermions, and another benchmark scenario in which Φ is a superposition of (nearly) degenerate CP-even and CP-odd Higgs bosons in a (possibly supersymmetric) two-Higgs doublet model also with additional fermions to account for the γγ decay rate. We explore the implications of these benchmark scenarios for the production of Φ and its new partners at colliders in future runs of the LHC and beyond, at higher-energy pp colliders and at e + e - and γγ colliders, with emphasis on the bosonic partners expected in the doublet scenario and the fermionic partners expected in both scenarios.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

From optimal observables to machine learning: an effective-field-theory analysis of e + e − → W + W − at future lepton colliders

We apply machine-learning techniques to the effective-field-theory analysis of the e + e − → W + W − processes at future lepton colliders, and demonstrate their advantages in comparison with conventional methods, such as optimal observables. In particular, we show that machine-learning methods are more robust to detector effects and backgrounds, and could in principle produce unbiased results with sufficient Monte Carlo simulation samples that accurately describe experiments. This is crucial for the analyses at future lepton colliders given the outstanding precision of the e + e − → W + W − measurement (~ 10−4 in terms of anomalous triple gauge couplings or even better) that can be reached. Our framework can be generalized to other effective-field-theory analyses, such as the one of e + e − → t t ¯ or similar processes at muon colliders.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2015

Superpartners at LHC and future colliders: predictions from constrained compactified M-theory

Here, we study a realistic top-down M-theory compactification with low-scale effective Supersymmetry, consistent with phenomenological constraints. A combination of top-down and generic phenomenological constraints fix the spectrum. The gluino mass is predicted to be about 1.5 TeV. Three and only three superpartner channels, $\sim\atop{g}$$\sim\atop{g}$, X$0\atop{2}$X$±\atop{1}$ and X$+\atop{1}$X$-\atop{1}$ (where X$0\atop{2}$X$±\atop{1}$ are Wino-like), are expected to be observable at LHC-14. We also investigate the prospects of finding heavy squarks and Higgsinos at future colliders. Gluino-stop-top, gluino-sbottom-bottom associated production and first generation squark associated production should be observable at a 100 TeV collider, along with direct production of heavy Higgsinos. Within this framework the discovery of a single sparticle is sufficient to determine uniquely the SUSY spectrum, yielding a number of concrete testable predictions for LHC-14 and future colliders, and determination of M 3/2 and thereby other fundamental quantities.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Learning physics at future $e^–e^+$ colliders with machine

Information deformation and loss in jet clustering are one of the major limitations for precisely measuring hadronic events at future $e^–e^+$ colliders. Because of their dominance in data, the measurements of such events are crucial for advancing the precision frontier of Higgs and electroweak physics in the next decades. We show that this difficulty can be well-addressed by synergizing the event-level information into the data analysis, with the techniques of deep neutral network. In relation to this, we introduce a CMB-like observable scheme, where the event-level kinematics is encoded as Fox-Wolfram (FW) moments at leading order and multi-spectra of spherical harmonics at higher orders. Then we develop a series of jet-level (w/ and w/o the FW moments) and event-level classifiers, and analyze their sensitivity performance comparatively with two-jet and four-jet events. As an application, we analyze measuring Higgs decay width at $e^–e^+$ colliders with the data of 5ab –1 @240GeV. The precision obtained is significantly better than the baseline ones presented in documents. We expect this strategy to be applied to many other hadronic- event measurements at future $e^–e^+$ colliders, and to open a new angle for evaluating their physics capability.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2013

The Changing Face of Vascular Interventional Radiology: The Future Role of Pharmacotherapies and Molecular Imaging

Interventional radiology has had to evolve constantly because there is the ever-present competition and threat from other specialties within medicine, surgery, and research. The development of new technologies, techniques, and therapies is vital to broaden the horizon of interventional radiology and to ensure its continued success in the future. In part, this change will be due to improved chronic disease prevention altering what we treat and in whom. The most important of these strategies are the therapeutic use of statins, Beta-blockers, angiotensin-converting enzyme inhibitors, and substances that interfere with mast cell degeneration. Molecular imaging and therapeutic strategies will move away from conventional techniques and nano and microparticle molecular technology, tissue factor imaging, gene therapy, endothelial progenitor cells, and photodynamic therapy will become an important part of interventional radiology of the future. This review looks at these new and exciting technologies.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2025

The Observed and Projected Changes of Global Monsoons: Current Status and Future Perspectives

The global monsoon system, encompassing the Asian-Australian, African, and American monsoons, sustains two-thirds of the world’s population by regulating water resources and agriculture. Monsoon anomalies pose severe risks, including floods and droughts. Recent research associated with the implementation of the Global Monsoons Model Intercomparison Project under the umbrella of CMIP6 has advanced our understanding of its historical variability and driving mechanisms. Observational data reveal a 20th-century shift: increased rainfall pre-1950s, followed by aridification and partial recovery post-1980s, driven by both internal variability (e.g., Atlantic Multidecadal Oscillation) and external forcings (greenhouse gases, aerosols), while ENSO drives interannual variability through ocean-atmosphere interactions. Future projections under greenhouse forcing suggest long-term monsoon intensification, though regional disparities and model uncertainties persist. Models indicate robust trends but struggle to quantify extremes, where thermodynamic effects (warming-induced moisture rise) uniformly boost heavy rainfall, while dynamical shifts (circulation changes) create spatial heterogeneity. Volcanic eruptions and proposed solar radiation modification (SRM) further complicate predictions: tropical eruptions suppress monsoons, whereas high-latitude events alter cross-equatorial flows, highlighting unresolved feedbacks. The emergent constraint approach is booming in terms of correcting future projections and reducing uncertainty with respect to the global monsoons. Critical challenges remain. Model biases and sparse 20th-century observational data hinder accurate attribution. The interplay between natural variability and anthropogenic forcings, along with nonlinear extreme precipitation risks under warming, demands deeper mechanistic insights. Additionally, SRM’s regional impacts and hemispheric monsoon interactions require systematic evaluation. Addressing these gaps necessitates enhanced observational networks, refined climate models, and interdisciplinary efforts to disentangle multiscale drivers, ultimately improving resilience strategies for monsoon-dependent regions.

climate extreme events↗

DOE OSTI2021

Projected future daily characteristics of African precipitation based on global (CMIP5, CMIP6) and regional (CORDEX, CORDEX-CORE) climate models

In this work, we provide an assessment of future daily characteristics of African precipitation by explicitly comparing the results of large ensembles of global (CMIP5, CMIP6) and regional (CORDEX, CORE) climate models, specifically highlighting the similarities and inconsistencies between them. Results for seasonal mean precipitation are not always consistent amongst ensembles: in particular, global models tend to project a wetter future compared to regional models, especially over the Eastern Sahel, Central and East Africa. However, results for other precipitation characteristics are more consistent. In general, all ensembles project an increase in maximum precipitation intensity during the wet season over all regions and emission scenarios (except the West Sahel for CORE) and a decrease in precipitation frequency (under the Representative Concentration Pathways RCP8.5) especially over the West Sahel, the Atlas region, southern central Africa, East Africa and southern Africa. Depending on the season, the length of dry spells is projected to increase consistently by all ensembles and for most (if not all) models over southern Africa, the Ethiopian highlands and the Atlas region. Discrepancies exist between global and regional models on the projected change in precipitation characteristics over specific regions and seasons. For instance, over the Eastern Sahel in July–August most global models show an increase in precipitation frequency but regional models project a robust decrease. Global and regional models also project an opposite sign in the change of the length of dry spells. CORE results show a marked drying over the regions affected by the West Africa monsoon throughout the year, accompanied by a decrease in mean precipitation intensity between May and July that is not present in the other ensembles. This enhanced drying may be related to specific physical mechanisms that are better resolved by the higher resolution models and highlights the importance of a process-based evaluation of the mechanisms controlling precipitation over the region.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Hierarchical sensitivity analysis for simulating barrier island geomorphologic responses to future storms and sea-level rise

This paper presents a new application of an advanced hierarchical sensitivity analysis of a new climate model of barrier island geomorphological evolution. The implemented sensitivity analysis in this study integrates a hierarchical uncertainty framework with a variance-based global sensitivity analysis to decompose the different model input uncertainties. The analysis can provide quantitative and accurate measurements for the relative importance of uncertain model input factors while considering their dependence relationships. The climate model used in this research was the barrier island profile (BIP) model, which is a new computer code developed to simulate barrier island morphological evolution over periods ranging from years to decades under the impacts of accelerated future sea-level rise and long-term changes in the storm climate. In the application of the model, the BIP model was used to evaluate the responses of a series of barrier island cross-sections derived for Santa Rosa Island, Florida, to random storm events and five potential accelerated rates of sea-level rise projected over the next century. The uncertain model input factors thus include the scenario uncertainty caused by alternative future sea-level rise scenarios and the parametric uncertainties of random storm parameters and dune characteristics. The study results reveal that the occurrence of storms is the most important factor for the evolution of sand dunes on the barrier island and the impact of sea-level rise is essential to the morphological change of the island backshore environment. The analysis can provide helpful insights for coastal management and planning. This hierarchical sensitivity analysis is mathematically general and rigorous and can be applied to a wide range of climate models.

Dai, Heng↗

DOE OSTI2013

A new scenario framework for climate change research. Background, process, and future directions

The scientific community is developing new integrated global, regional, and sectoral scenarios to facilitate interdisciplinary research and assessment to explore the range of possible future climates and related physical changes could pose to human and natural systems; how these could interact with social, economic, and environmental development pathways; the degree to which mitigation and adaptation policies can avoid and reduce those risks; the costs and benefits of various policy mixes; residual impacts under alternative pathways; and the relationship with sustainable development. This paper provides the background to, and process of, developing the conceptual framework for these scenarios, described in three other papers in this Special Issue (van Vuuren et al.; O'Neill et al.; Kriegler et al.). The paper also discusses research needs to further develop and apply this framework. The goal is to encourage climate change researchers from a broad range of perspectives and disciplines to work together to develop policy-relevant scenarios and explore the implications of different possible futures for the challenges and opportunities human and natural systems could face with increasing climate change.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Benefits of mitigation for future heat extremes under RCP4.5 compared to RCP8.5

We investigate changes in statistics of extreme daily temperature using ensembles from the Community Earth System Model (CESM) under a high and a lower emission scenarios, . The ensembles provide large samples for a robust application of extreme value theory. We estimate return values and return periods for annual maxima of the daily high and low temperatures as well as the 3-day averages of the same variables in current and future climate. Results indicate statistically significant increases (compared to the reference period of 1996–2005) in extreme temperatures over all land areas as early as 2025 under both scenarios, with statistically significant differences between them becoming pervasive over the globe by 2050. The substantially smaller changes, for all indices, produced under the lower emission case translate into sizeable benefits from emission mitigation: By 2075, in terms of reduced changes in 1-day heat extremes, about 95 % of land regions would see benefits of 1 °C or more under the lower emissions scenario, and 50 % or more of the land areas would benefit by at least 2 °C. 6 % of the land area would benefit by 3 °C or more in projected extreme minimum temperatures and 13 % would benefit by this amount for extreme maximum temperature. Benefits for 3-day metrics are similar. The future frequency of current extremes is also greatly reduced by mitigation: by the end of the century, under RCP8.5 more than half the land area experiences the current 20-year events every year while only between about 10 and 25 % of the area is affected by such severe changes under RCP4.5.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Conceptual process design and techno-economic assessment of ex situ catalytic fast pyrolysis of biomass: A fixed bed reactor implementation scenario for future feasibility

Ex situ catalytic fast pyrolysis of biomass is a promising route for the production of fungible liquid biofuels. There is significant ongoing research on the design and development of catalysts for this process. However, there are a limited number of studies investigating process configurations and their effects on biorefinery economics. Herein we present a conceptual process design with techno-economic assessment; it includes the production of upgraded bio-oil via fixed bed ex situ catalytic fast pyrolysis followed by final hydroprocessing to hydrocarbon fuel blendstocks. This study builds upon previous work using fluidized bed systems, as detailed in a recent design report led by the National Renewable Energy Laboratory (NREL/TP-5100-62455); overall yields are assumed to be similar, and are based on enabling future feasibility. Assuming similar yields provides a basis for easy comparison and for studying the impacts of areas of focus in this study, namely, fixed bed reactor configurations and their catalyst development requirements, and the impacts of an inline hot gas filter. A comparison with the fluidized bed system shows that there is potential for higher capital costs and lower catalyst costs in the fixed bed system, leading to comparable overall costs. The key catalyst requirement is to enable the effective transformation of highly oxygenated biomass into hydrocarbons products with properties suitable for blending into current fuels. Potential catalyst materials are discussed, along with their suitability for deoxygenation, hydrogenation and C–C coupling chemistry. This chemistry is necessary during pyrolysis vapor upgrading for improved bio-oil quality, which enables efficient downstream hydroprocessing; C–C coupling helps increase the proportion of diesel/jet fuel range product. One potential benefit of fixed bed upgrading over fluidized bed upgrading is catalyst flexibility, providing greater control over chemistry and product composition. Since this study is based on future projections, the impacts of uncertainties in the underlying assumptions are quantified via sensitivity analysis. As a result, this analysis indicates that catalyst researchers should prioritize by: carbon efficiency > catalyst cost > catalyst lifetime, after initially testing for basic operational feasibility.

09 BIOMASS FUELS↗

DOE OSTI2018

3D MRI in Musculoskeletal Imaging: Current and Future Applications

Purpose of Review: This article addresses current clinical applications, recent literature, and potential future applications of 3-dimensional magnetic resonance imaging (3D MRI) for musculoskeletal (MSK) applications. Recent Findings: The main advantage of 3D MRI over standard 2-dimensional MRI is its ability to reduce partial volume averaging artifacts and create multiplanar reconstruction (MPRs) in any plane with any slice thickness from a single high-resolution isotropic acquisition. 3D MRI acquisitions are particularly useful for the evaluation of articular cartilage, which is prone to volume averaging artifacts, and for the assessment of longitudinally coursing structures such as peripheral nerves and tendons, which are better visualized with non-orthogonal MPRs. 3D MRI is also useful for surface and volumetric analysis of bone and cartilage for preoperative and longitudinal assessments. Current research is focused on decreasing acquisition times and automating segmentation through machine learning, thus overcoming some of the current limitations of 3D MRI and providing new applications for this technique. Summary: 3D MRI is widely used in MSK imaging today, and its use is likely to continue to increase in the future, with recent advancements focused on accelerated acquisition techniques and quantitative imaging.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2022

Beam–beam effects and mitigation in a future proton–proton collider

The beam–beam effects in a hadron collider with an unprecedented energy scale were studied. These effects are strongly related to the attainable luminosity of the collider. Long-range interactions were identified as the major factor limiting the dynamic aperture, which is strongly dependent on the crossing angle, β*, and bunch population. Different mitigation methods of the beam–beam effects were addressed, with a focus on the compensation of long-range interactions by electric current wires. The CEPC-SPPC project is a two-stage large circular collider, with a first-stage circular electron–positron collider (CEPC) and a second-stage super proton–proton collider (SPPC). The design of the SPPC aims to achieve a center-of-mass energy of 75 TeV and peak luminosity of approximately 1 × 10$^{35}$ cm$^{-2}$ s$^{-1}$. We studied the beam–beam effects in the SPPC and tested the effectiveness of the mitigation methods. We found that with compensation using electric current wires, the dynamic aperture is at an acceptable level. Moreover, considering the significant emittance damping in this future proton–proton collider, the beam–beam effects and compensation are more complicated and are studied using long-term tracking. It was found that with a smaller emittance, the head-on interactions with a crossing angle become more prominent in reducing the beam stability, and combined head-on and long-range compensation is needed to improve the beam quality. When the reduction in population owing to burn-off was included, it was found that the coupling between the transverse and longitudinal planes at smaller emittance is the main driving source of the instabilities. Thus, crab cavities and emittance control are also necessary than just the compensation of the long-range interactions to improve the beam stability. This study serves as an example for studying the beam–beam effects in future proton–proton colliders.

43 PARTICLE ACCELERATORS↗

DOE OSTI2026

Future foundries: A convergent manufacturing platform

This article introduces the Future Foundries platform developed at Oak Ridge National Laboratory, a first-generation research system designed to demonstrate convergent manufacturing. Convergent manufacturing brings together additive, subtractive, and transformative processes in a digitally interconnected environment to enable end-to-end production workflows. By linking traditionally discrete steps, convergent platforms accelerate production, improve repeatability, and support high-mix, low-volume manufacturing. The Future Foundries platform exemplifies this vision in practice by combining four modular, vendor-agnostic process cells that include robotic WAAM, induction heating, optical metrology, and machining, coordinated through an automated pallet handler and a ROS 2-based digital thread. This architecture provides the flexibility and scalability needed for agile production in small and medium-sized manufacturing enterprises and for field deployable manufacturing. Two case studies illustrate the platform’s capabilities. The first presents an integrated workflow for fabricating, transforming, and repairing critical replacement components, showing how consolidated thermal, additive, inspection, and machining operations reduce manual part handling and streamline process flow. The second case study highlights coordinated multi-part production enabled by automated pallet logistics and multi-cell scheduling. Together, these examples showcase convergent manufacturing as a practical and scalable strategy for strengthening domestic casting and forging capacity, improving supply-chain resilience, and enabling rapid, adaptable production of mission-critical components.

Convergent manufacturing↗