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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 1,495 records · Page 83
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Biosynthesis of Minimal C-Phycocyanin Chromophore Assemblies in E. coli Provides a Platform to Dissect Protein-Mediated Tuning of Exciton Transfer

Cyanobacteria are arguably among the most evolutionarily successful organisms on Earth, inhabiting a wide range of ocean, freshwater, soil, and even desert environments on every continent. The cyanobacterial phycobilisome consists of stacks of disk-like light-collecting moieties, allophycocyanin (APC) and phycocyanin (CPC), with covalently bound phycocyanobilin (PCB) pigments. The ways in which the energies of the specific chromophores in these complexes are tuned by the protein to achieve its highly efficient and directional energy transfer are not fully understood, as complex combinations of decay pathways are occurring simultaneously and competitively through this elaborate light-harvesting system. This makes it difficult to extract information about isolated protein-pigment interactions. We provide herein a description of a useful new experimental platform in which we have recombinantly expressed a fully functioning CPC complex and selectively created minimal chromophore sets to study their individual contributions to the overall CPC spectra. Structural and computational analysis of this protein system have provided a greater understanding of how the protein environment serves to alter the photophysics of each of these chromophores. Introduction of a quencher into various positions within CPC confirmed the ability of the protein environment to tune the directionality of energy transport in this assembly. Further mutational analysis suggested the roles of key amino acids surrounding the chromophores, showcasing the utility of heterologous expression techniques for understanding the effects of structure on EET mechanisms in the phycobilisome.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

C–C Bond Formation during Electrochemical CO 2 Reduction on Pristine Cu(100) Unlikely to Involve Adsorbed CO at Any Potential

Formation of hydrocarbons containing two or more carbon atoms (C 2+ ) during heterogeneous electrochemical CO and CO 2 reduction (ECOR and ECO 2 R) only occurs, among pure metals, on Cu electrodes. Moreover, the activity and selectivity is facet dependent, with Cu(100) generally preferentially forming ethylene over methane. Previously, we found via quantum-mechanics-based modeling that, unlike standard density functional theory, more accurate correlated wavefunction methods predict that non-electroactive coupling pathways involving two adsorbed COs (*CO) or a *CO and a *COH to form C–C bonds on Cu(100) are kinetically inhibited, with the former also thermodynamically unfavorable. Here, we extend that embedded complete active space second order perturbation theory (ECASPT2) study, further showing that electrochemical coupling of two *COs to form an anionic dimer [OC*–*CO] (1+δ)– , followed by protonation to form [OC*–*COH] δ− , is not kinetically competitive with the reduction of *CO to *COH at relevant ECO/CO 2 R potentials. Our simulations therefore suggest that the ability of Cu(100) to electrochemically synthesize C 2+ molecules from CO and CO 2 is unlikely to be via *CO, at least on pristine Cu(100). Instead, hydrogenated CO species (*COH, *CH x OH, or *CH x ) are most likely to be the key intermediates in C–C bond formation.

Martirez, John Mark P. [Princeton Plasma Physics L↗
DOE OSTI2026

Selective Reduction of Carbon Dioxide in Water Using [M(bpy2+)(CO)3(I)]2+ (M = Mn, Re) Electrocatalysts with Pendent Cations

Manganese(I) carbonyl complexes are promising electrocatalysts for CO2 reduction, yet their application in homogeneous aqueous media remains limited by poor solubility and selectivity. Here, we report water-soluble Mn(I) and Re(I) complexes fac-[M(bpy2+)(CO)3X]2+ (X = I or Cl), featuring bipyridine ligands functionalized with -Ph-CH2-(NMe3)+ cationic ammonium groups that integrate water solubility with secondary-sphere stabilization. In bicarbonate buffer at pH 6.8, the Mn catalyst is completely selective for CO production at a low overpotential (η = 0.3 V), operating by a protonation-first mechanism with observed rates of ~10 s−1. Pulse radiolysis reveals that the one-electron reduced Mn species undergoes dimerization in the absence of CO2 but uniquely reacts competitively with CO2 through an initial pre-equilibrium followed by fast formation of a dinuclear CO2-bridged species (ΔGo = −12.4 kcal mol−1). At a higher 0.6 V over-potential, a faster reduction-first pathway (~100 s−1) is available upon reduction of the metallo-carboxylic acid intermediate, Mn-CO2H2+; however, this regime is functionally limited by the formation of a resistive, noncatalytic film on the electrode surface. Comparison to the analo-gous water-soluble Re catalyst (kobs = 440 s−1, η = 0.6 V) highlights the distinct mechanistic ad-vantages of earth-abundant Mn in low-potential catalysis. These results demonstrate how cati-onic second-sphere design enables selective, homogeneous CO2 reduction in water while reveal-ing competing radical and electrode-mediated processes that govern catalytic performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Di- and Tetrameric Molybdenum Sulfide Clusters Activate and Stabilize Dihydrogen as Hydrides

NaY zeolite-encapsulated dimeric (Mo 2 S 4 ) and tetrameric (Mo 4 S 4 ) molybdenum sulfide clusters stabilize hydrogen as hydride binding to Mo atoms. Density functional theory (DFT) calculations and adsorption measurements suggest that stabilization of hydrogen as sulfhydryl (SH) groups, as typical for layered MoS 2 , is thermodynamically disfavored. Competitive adsorption of H 2 and ethene on Mo was probed by quantifying adsorbed CO on partly hydrogen and/or ethene covered samples with IR spectroscopy. During hydrogenation, experiment and theory suggest that Mo is covered predominately with ethene and sparsely with hydride. DFT calculations further predict that under reaction conditions, each Mo x S y cluster can activate only one H 2 , suggesting that the entire cluster (irrespective of its nuclearity) acts as one active site for hydrogenation. The nearly identical turnover frequencies (24.7 ± 3.3 mol ethane ·h -1 ·mol cluster -1 ), apparent activation energies (31-32 kJ·mol -1 ), and reaction orders (~0.5 in ethene and ~1.0 in H 2 ) show that the active sites in both clusters are catalytically indistinguishable.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

EF-Hand Battle Royale: Hetero-ion Complexation in Lanmodulin

The lanmodulin (LanM) protein has emerged as an effective means for rare earth element (REE) extraction and separation from complex feedstocks without the use of organic solvents. Whereas the binding of LanM to individual REEs has been well characterized, little is known about the thermodynamics of mixed metal binding complexes (i.e., heterogeneous ion complexes), which limits the ability to accurately predict separation performance for a given metal ion mixture. In this paper, we employ the law of mass action to establish a theory of perfect cooperativity for LanM-REE complexation at the two highest-affinity binding sites. The theory is then used to derive an equation that explains the nonintuitive REE binding behavior of LanM, where separation factors for binary pairs of ions vary widely based on the ratio of ions in the aqueous phase, a phenomenon that is distinct from single-ion-binding chemical chelators. We then experimentally validate this theory and perform the first quantitative characterization of LanM complexation with heterogeneous ion pairs using resin-immobilized LanM. Importantly, the resulting homogeneous and heterogeneous constants enable accurate prediction of the equilibrium state of LanM in the presence of mixtures of up to 10 REEs, confirming that the perfect cooperativity model is an accurate mechanistic description of REE complexation by LanM. We further employ the model to simulate separation performance over a range of homogeneous and heterogeneous binding constants, revealing important insights into how mixed binding differentially impacts REE separations based on the relative positioning of the ion pairs within the lanthanide series. In addition to informing REE separation process optimization, these results provide mathematical and experimental insight into competition dynamics in other ubiquitous and medically relevant, cooperative binding proteins, such as calmodulin.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Surface Hydration of Porous Nickel Hydroxides Facilitates the Reversible Adsorption of CO 2 from Ambient Air

Direct air capture (DAC) under humid ambient conditions typically requires the use of organic components, with sorbents that are purely inorganic in composition for the most part operating hundreds of degrees above room temperature. In this work, we report porous metal hydroxides as a novel class of water-tolerant, oxidatively and hydrothermally stable low-temperature sorbents that exhibit competitive DAC working capacities of 1.25 mmol/g over 5 consecutive temperature swing adsorption–desorption cycles in the presence of steam and oxygen. Aqueous miscible organic solvent treatments are used to create highly porous structures with surface areas exceeding 700 m 2 /g that capture CO 2 in the form of bicarbonates under dry conditions, and carbonates under wet conditions. Water exerts a facilitative rather than an inhibiting effect on CO 2 binding, and the presence of hydrating multilayers serves to stabilize carbonate species akin to moisture swing adsorbents except for the fact that solvation results in a remarkable (upto 10-fold) increase, not decrease, in DAC capacity. High-valent doping with cerium is used to improve DAC capacities by amplifying surface basicity, evidencing porous nickel hydroxides specifically (and porous metal hydroxides more generally) as a novel class of robust, earth-abundant DAC sorbents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Aqueous Carbon Capture Using Guanidinium-Functionalized Hollow Fiber Sorbent Contactors

As part of the growing suite of technologies aimed at combatting rising temperatures, negative emissions technologies have become a powerful tool in the global effort to minimize the consequences of human-induced climate change. Among these, carbon removal from aqueous sources, which contain much higher carbon concentrations than the atmosphere, remains largely unexplored. Indeed, developing robust and efficient carbon capture materials for usage in complex aqueous environments remains a significant challenge. Here, we explore the potential of functionalizing polyvinylidene fluoride (PVDF) hollow fiber contactors grafted with a guanidinium-derived polymer sorbent for carbon removal from aqueous sources, including saline waters. Computational screening against amine-based analogs is utilized to identify guanidinium as a promising motif for bicarbonate (HCO 3 – ) ions binding. To leverage this finding, synthesis of a guanidinium polymer and subsequent covalent grafting onto PVDF hollow fibers is employed to structured polymer–sorbent–grafted hollow fiber contactors. Our prototype achieves an initial HCO 3 – removal of 34% with an increase to 98% after four cycles. The functionalized fibers demonstrate aqueous stability over 13 adsorption/desorption cycles in model NaHCO 3 solutions where regeneration is facilitated by a mild pH swing. Importantly, the system maintains selective performance in the presence of competitive chloride ions over multiple cycles; carbon removal remained above 10% even at high (10:1) NaCl/NaHCO 3 ratios. These findings demonstrate the feasibility of sorbent-based aqueous carbon removal and highlight its potential as a promising approach for negative emissions.

carbon capture↗
DOE OSTI2020

High Mass Analysis with a Fourier Transform Ion Cyclotron Resonance Mass Spectrometer: From Inorganic Salt Clusters to Antibody Conjugates and Beyond

Analysis of proteins and complexes under native mass spectrometric (MS) and solution conditions was typically performed using time-of-flight (ToF) analyzers, due to their routine high m/z transmission and detection capabilities. However, over recent years, the ability of Orbitrap-based mass spectrometers to transmit and detect a range of high molecular weight species is well documented. Herein, we describe how a 15 Tesla Fourier transform ion cyclotron resonance mass spectrometer (15 T FT-ICR MS) is more than capable of analyzing a wide range of ions in the high m/z scale (>5000), in both positive and negative instrument polarities, ranging from the inorganic cesium iodide salt clusters; a humanized IgG1k monoclonal antibody (mAb; 148.2 kDa); an IgG1-mertansine drug conjugate (148.5 kDa, drug-to-antibody ratio; DAR 2.26); an IgG1-siRNA conjugate (159.1 kDa; ribonucleic acid to antibody ratio; RAR 1); the membrane protein aquaporin-Z (97.2 kDa) liberated from a C8E4 detergent micelle; the empty MSP1D1-nanodisc (142.5 kDa) and the tetradecameric chaperone protein complex GroEL (806.2 kDa; GroEL dimer at 1.6 MDa). We also investigate different regions of the FT-ICR MS that impact ion transmission and desolvation. Finally, we demonstrate how the transmission of these species and resultant spectra are highly consistent with those previously generated on both quadrupole-ToF (Q-ToF) and Orbitrap instrumentation. This article serves as an impactful example of how FT-ICR mass analyzers are competitive to Q-ToFs and Orbitraps for high mass detection at high m/z.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Aerosol Impacts on Mesoscale Convective Systems Forming Under Different Vertical Wind Shear Conditions

Following our previous study of wind shear effect on mesoscale convective system (MCS) organization under a clean atmospheric condition using the Weather Research and Forecasting model coupled with Spectral-Bin Microphysics, we conduct sensitivity simulations by increasing cloud condensation nuclei (CCN) concentration and investigate aerosol impacts on MCSs forming under different wind shear conditions. We find that, aerosols induce stronger updrafts and downdrafts in all MCSs. The stronger updrafts and enlarged convective core area contribute to larger vertical mass fluxes and enhance precipitation, indicating convective invigoration. Increased updraft speed below 8-km altitude mainly results from enhanced condensational heating, and increased water loading effect is not large enough to overcome the increase in thermal buoyancy. Interestingly, above 8-km altitude we see reduced updraft speed by the increased aerosols due to reduced vertical pressure perturbation gradient force, and weakened depositional growth due to competition of water vapor by enhanced condensation. The accumulated rainfall and mean rain rate are increased, with an increased occurrence frequency of heavy rain. The increase of rain rate is seen in both convective and stratiform regions, with a more significant increase in convective rain rate. In general, we see a higher frequency of deep convective cloud in the polluted condition because of invigorated convection, and more stratiform/anvil clouds, but a lower frequency of shallow warm clouds. The unanimously invigorated MCSs by aerosols under various wind shear conditions revealed by this study has an important implication in weather and climate at warm and humid regions that are influenced by pollution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Getting to the Root of Plant–Mediated Methane Emissions and Oxidation in a Thermokarst Bog

Vascular plants are important in the wetland methane cycle, but their effect on production, oxidation, and transport has high uncertainty, limiting our ability to predict emissions. In a permafrost–thaw bog in Interior Alaska, we used plant manipulation treatments, field–deployed planar optical oxygen sensors, direct measurements of methane oxidation, and microbial DNA analyses to disentangle mechanisms by which vascular vegetation affect methane emissions. Vegetation operated on top of baseline methane emissions, which varied with proximity to the thawing permafrost margin. Emissions from vegetated plots increased over the season, resulting in cumulative seasonal methane emissions that were 4.1–5.2 g m –2 season –1 greater than unvegetated plots. Mass balance calculations signify these greater emissions were due to increased methane production (3.0–3.5 g m –2 season –1 ) and decreased methane oxidation (1.1–1.6 g m –2 season –1 ). Minimal oxidation occurred along the plant–transport pathway, and oxidation was suppressed outside the plant pathway. Our data indicate suppression of methane oxidation was stimulated by root exudates fueling competition among microbes for electron acceptors. This contention is supported by the fact that methane oxidation and relative abundance of methanotrophs decreased over the season in the presence of vegetation, but methane oxidation remained steady in unvegetated treatments; oxygen was not detected around plant roots but was detected around silicone tubes mimicking aerenchyma; and oxygen injection experiments suggested that oxygen consumption was faster in the presence of vascular vegetation. In conclusion, root exudates are known to fuel methane production, and our work provides evidence they also decrease methane oxidation.

58 GEOSCIENCES↗
DOE OSTI2022

Modeling the Economic and Environmental Impacts of Land Scarcity Under Deep Uncertainty

Abstract Land scarcity is increasing over time, driven by complex multisector dynamics. The impacts of land scarcity on the economy and environment are multi‐faceted and regional, so any action to convert land will contain inherent tradeoffs. These impacts are complicated by the deeply uncertain evolution of the various sectors influencing land scarcity. A need therefore exists to provide multi‐metric and multi‐sector assessments that are robust to myriad uncertainties. Land conservation effectively limits the supply of productive land, while biofuel consumption increases the demand and competition for that land, and how these dynamics individually and jointly propagate to economic and environmental impacts is an important open question. To address this, we adopt the Global Change Analysis Model (GCAM) that has representations of various important systems including the climate, macroeconomic, energy, agriculture and land, and water resources systems. Various scenarios of increased land demand (from biofuels) and decreased land supply (from conservation) under various socioeconomic scenarios drawn from the SSPs were simulated using GCAM. We find that while biofuel consumption and land conservation reduce carbon emissions, this comes at the cost of higher food prices, reduced crop production, and increased water withdrawals. Additionally, some regions experience these tradeoffs more severely than others and are more heavily impacted from the same biofuel mandate or by an additional percent of protected land. These and other findings highlight the importance of multisector modeling frameworks that capture many cross‐sector linkages, and acknowledge the important uncertainties confronting the human‐Earth system when making any analysis of land scarcity impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Improving Seasonal Forecast Using Probabilistic Deep Learning

The path toward realizing the potential of seasonal forecasting and its socioeconomic benefits relies on improving general circulation model (GCM) based dynamical forecast systems. To improve dynamical seasonal forecasts, it is crucial to set up forecast benchmarks, and clarify forecast limitations posed by model initialization errors, formulation deficiencies, and internal climate variability. With huge costs in generating large forecast ensembles, and limited observations for forecast verification, the seasonal forecast benchmarking and diagnosing task proves challenging. Here, we develop a probabilistic deep learning-based statistical forecast methodology, drawing on a wealth of climate simulations to enhance seasonal forecast capability and forecast diagnosis. By explicitly modeling the internal climate variability and GCM formulation differences, the proposed Conditional Generative Forecasting (CGF) methodology enables bypassing crucial barriers in dynamical forecast, and offers a top-down viewpoint to examine how complicated GCMs encode the seasonal predictability information. We apply the CGF methodology for global seasonal forecast of precipitation and 2 m air temperature, based on a unique data set consisting 52,201 years of climate simulation. Results show that the CGF methodology can faithfully represent the seasonal predictability information encoded in GCMs. We successfully apply this learned relationship in real-world seasonal forecast, achieving competitive performance compared to dynamical forecasts. Using this CGF as benchmark, we reveal the impact of insufficient forecast spread sampling that limits the skill of the considered dynamical forecast system. Finally, we introduce different strategies for composing ensembles using the CGF methodology, highlighting the potential for leveraging the strengths of multiple GCMs to achieve advantgeous seasonal forecast.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Trade and Climate Mitigation Interactions Create Agro–Economic Opportunities With Social and Environmental Trade–Offs in Latin America and the Caribbean

The Latin America and the Caribbean (LAC) region plays key roles in both meeting global agricultural demands and maintaining carbon sinks due to its abundant land and water resources. In this study we use the Global Change Analysis Model (GCAM) to evaluate the opportunities and challenges posed by two global-scale drivers: agricultural market integration (i.e., reduction of trade barriers) and land-based climate mitigation policy. We evaluate their potential individual and combined impacts on agricultural production and trade revenues across LAC’s economies through mid-century, as well as the resulting impacts on agricultural consumers and integrated land-water-climate systems across the region’s diverse sub-regions. Increased global market integration results in increased agricultural production and trade revenues for many LAC economies driven by their evolving comparative advantages. Climate mitigation measures on CO 2 and non-CO 2 greenhouse gases increase revenues due to increased agricultural prices from land competition and emissions abatement. The combined outcomes from both drivers are complex and sometimes non-linear, highlighting the importance of understanding the interactions between multiple drivers. Our results show that increased agricultural production and trade opportunities pose significant trade-offs that require careful multi-sectoral planning, such as emissions reduction challenges, potential loss of livestock production when pursuing land-based climate mitigation strategies, increased consumer expenditures, and changes in land-use or water withdrawals, resulting in deforestation or water scarcity pressures. There is considerable heterogeneity in economic and environmental outcomes across LAC sub-regions and agricultural commodities, illustrating the value of considering outcomes at finer scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Whistler Waves Associated With Electron Beams in Magnetopause Reconnection Diffusion Regions

Abstract Whistler waves are often observed in magnetopause reconnection associated with electron beams. We analyze seven MMS crossings surrounding the electron diffusion region (EDR) to study the role of electron beams in whistler excitation. Waves have two major types: (a) Narrow‐band waves with high ellipticities and (b) broad‐band waves that are more electrostatic with significant variations in ellipticities and wave normal angles. While both types of waves are associated with electron beams, the key difference is the anisotropy of the background population, with perpendicular and parallel anisotropies, respectively. The linear instability analysis suggests that the first type of wave is mainly due to the background anisotropy, with the beam contributing additional cyclotron resonance to enhance the wave growth. The second type of broadband waves are excited via Landau resonance, and as seen in one event, the beam anisotropy induces an additional cyclotron mode. The results are supported by particle‐in‐cell simulations. We infer that the first type occurs downstream of the central EDR, where background electrons experience Betatron acceleration to form the perpendicular anisotropy; the second type occurs in the central EDR of guide field reconnection. A parametric study is conducted with linear instability analysis. A beam anisotropy alone of above ∼3 likely excites the cyclotron mode waves. Large beam drifts cause Doppler shifts and may lead to left‐hand polarizations in the ion frame. Future studies are needed to determine whether the observation covers a broader parameter regime and to understand the competition between whistler and other instabilities.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

On the Scaling and Growth Limit of Fluvial Dunes

Abstract Bedforms emerge in a variety of shapes and sizes when a granular erodible surface is subject to a strong enough shear flow, as observed in topographic data from submarine canyons, rivers, deserts, and planetary bodies. The two salient features of bedforms are the ability to collectively transport particles, and to generate form drag thus increasing flow resistance. These two mechanisms are in competition and contribute to force bedforms of increasing size migrating more slowly. In a dedicated large‐scale open channel flow facility, hierarchies of fluvial bedforms were generated and measured in equilibrium conditions. The corresponding scale‐dependent migration velocity and mass flux contributions were quantified in the wave number and frequency domains. Experimental results are paired with a validated set of theoretical models to demonstrate that ripples or dunes reach an equilibrium state when drag partitioning ensures high enough frictional drag to sustain the bedload transport of sediment, and low enough form drag to enable the migration of the largest bedform size. This mechanism is inferred to constrain the growth of bedforms when sediment supply is not the limiting factor.

58 GEOSCIENCES↗
DOE OSTI2022

Learning Coagulation Processes With Combinatorial Neural Networks

Abstract Simulating the evolution of a coagulating aerosol or cloud of droplets in a key problem in atmospheric science. We present a proof of concept for modeling coagulation processes using a novel combinatorial neural network (CombNN) architecture. Using two types of data from a high‐detail particle‐resolved aerosol simulation, we show that CombNN models outperform standard neural networks and are competitive in accuracy with traditional state‐of‐the‐art sectional models. These CombNN models could have application in learning coarse‐grained coagulation models for multi‐species aerosols and for learning coagulation models from observed size‐distribution data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Agrivoltaics in Color: Going From Light Spectra to Biomass

Abstract Agrivoltaics (AV), conceived in the early 1980s, promise to ameliorate competition between solar energy generation and crop production for arable land. The premise behind AV is that excess light not used in photosynthesis can be used for energy production. There are opportunities for maximizing photosynthesis by targeting particular wavelengths (e.g., red) to be transmitted through semi‐transparent photovoltaic (PV) cells depending on crop type and environmental conditions. Camporese and Abou Najm (2022, https://doi.org/10.1029/2022EF002900 ) developed a numerical model that accommodates the various wavelengths of the incoming light spectrum to predict photosynthesis, stomatal conductance, and transpiration. This commentary seeks to place those and other recent findings about the modifications to the plant micro‐environment by PV cells in the context of maximum attainable aboveground biomass.

Katul, Gabriel G.↗
DOE OSTI2023

Compounding Uncertainties in Economic and Population Growth Increase Tail Risks for Relevant Outcomes Across Sectors

Understanding the long-term effects of population and GDP changes requires a multisectoral and regional understanding of the coupled human-Earth system, as the long-term evolution of this coupled system is influenced by human decisions and the Earth system. This study investigates the impact of compounding economic and population growth uncertainties on long-term multisectoral outcomes. We use the Global Change Analysis Model (GCAM) to explore the influence of compounding and feedback between future GDP and population growth on four key sectors: final energy consumption, water withdrawal, staple food prices, and CO 2 emissions. The results show that uncertainties in GDP and population compound, resulting in a magnification of tail risks for outcomes across sectors and regions. Compounding uncertainties significantly impact metrics such as CO 2 emissions and final energy consumption, particularly at the upper tail at both global and regional levels. However, the impact of staple food prices and water withdrawal depends on regional factors. Additionally, an alternative low-carbon transition scenario could compound uncertainties and increase tail risk, particularly in staple food prices, highlighting the influence of emergent constraints on land availability and food-energy competition for land use. The findings underscore the importance of considering and adequately accounting for compounding uncertainties in key drivers of multisectoral systems to enhance our comprehensive understanding of the complex nature of multisectoral systems. The paper provides valuable insights into the potential implications of compounding uncertainties.

54 ENVIRONMENTAL SCIENCES↗