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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A broad specificity β-propeller enzyme from Rhodopseudomonas palustris that hydrolyzes many lactones including γ-valerolactone

Lactones are prevalent in biological and industrial settings, yet there is a lack of information regarding enzymes used to metabolize these compounds. One compound, γ-valerolactone (GVL), is used as a solvent to dissolve plant cell walls into sugars and aromatic molecules for subsequent microbial conversion to fuels and chemicals. Despite the promise of GVL as a renewable solvent for biomass deconstruction, residual GVL can be toxic to microbial fermentation. Here, we identified a Ca 2+ -dependent enzyme from Rhodopseudomonas palustris (Rpa3624) and showed that it can hydrolyze aliphatic and aromatic lactones and esters, including GVL. Maximum-likelihood phylogenetic analysis of other related lactonases with experimentally determined substrate preferences shows that Rpa3624 separates by sequence motifs into a subclade with preference for hydrophobic substrates. Additionally, we solved crystal structures of this β-propeller enzyme separately with either phosphate, an inhibitor, or a mixture of GVL and products to define an active site where calcium-bound water and calcium-bound aspartic and glutamic acid residues make close contact with substrate and product. Our kinetic characterization of WT and mutant enzymes combined with structural insights inform a reaction mechanism that centers around activation of a calcium-bound water molecule promoted by general base catalysis and close contacts with substrate and a potential intermediate. Similarity of Rpa3624 with other β-propeller lactonases suggests this mechanism may be relevant for other members of this emerging class of versatile catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1996

Excess nutrients in hydroponic solutions alter nutrient content of rice, wheat, and potato

Environment has significant effects on the nutrient content of field-grown crop plants. Little is known, however, about compositional changes caused by controlled environments in which plants receive only artificial radiation and soilless, hydroponic culture. This knowledge is essential for developing a safe, nutritious diet in a Controlled Ecological Life-Support System (CELSS). Three crops that are candidates for inclusion in a CELSS (rice, wheat, and white potato) were grown both in the field and in controlled environments where the hydroponic nutrient solution, photosynthetic photon flux (PPF), and CO2 level were manipulated to achieve rapid growth rates. Plants were harvested at maturity, separated into discrete parts, and dried prior to analysis. Plant materials were analyzed for proximate composition (protein, fat, ash, and carbohydrate), total nitrogen (N), nitrate, minerals, and amino-acid composition. The effect of environment on nutrient content varied by crop and plant part. Total N and nonprotein N (NPN) contents of plant biomass generally increased under controlled-environment conditions compared to field conditions, especially for leafy plant parts and roots. Nitrate levels were increased in hydroponically-grown vegetative tissues, but nitrate was excluded from grains and tubers. Mineral content changes in plant tissue included increased phosphorus and decreased levels of certain micronutrient elements under controlled-environment conditions. These findings suggest that cultivar selection, genetic manipulation, and environmental control could be important to obtain highly nutritious biomass in a CELSS.

NASA Discipline Number 61-20↗
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.

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

A carbon molecular sieve membrane-based reactive separation process for pre-combustion CO 2 capture

In this study, we discuss a hybrid system combining a membrane reactor (MR) and an adsorptive reactor (AR), with the MR's reject stream serving as the AR's feed. We apply this system for the water gas shift (WGS) reaction for H 2 generation and simultaneous CO 2 capture in the context of the Integrated Gas Combined Cycle (IGCC) process for power generation from coal and biomass. This MR-AR system attains a high conversion exceeding equilibrium, produces a pure H 2 product for power generation, and delivers a high-pressure CO 2 stream ready for sequestration. Specifically, in our study we use carbon molecular sieve membranes (CMSMs) and a commercial sour-shift WGS catalyst. Lab experiments were carried-out to determine the membrane characteristics, and the MR performance under IGCC-relevant conditions, i.e., for temperatures up to 250 °C and pressures up to 25 bar, employing a model coal gasifier syngas. The CMSM and the catalyst have displayed robust and stable performance during a long-term run (~750 h of syngas exposure). We evaluated the MR-AR system in multi-cycle runs and it has demonstrated superior performance to that of a conventional packed-bed reactor, producing a high-purity H 2 product directly useable in a turbine for power generation. We conclude from the study, that the CMSM-based MR-AR system is a good candidate technology for environmentally-benign power generation. We are currently constructing a pilot-scale system for field demonstration of the technology.

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

Process Feasibility Analysis of Waste Biomass Valorization to Biochar and Bio-Oil via Slow and Fast Pyrolysis

The United States has abundant biomass and waste feedstock to support the nation's energy addition and affordability targets. Pyrolysis, a thermochemical conversion process, decomposes lignocellulosic feedstocks into liquid, solid, and gaseous fuels that can contribute to the domestic production of biofuels, biopower, and bioproducts. Growing private sector interest in this technology is a key motivation for this comprehensive techno-economic process modeling analysis of a respective biorefinery that includes feedstock preprocessing, slow and fast pyrolysis, and product separation to bio-oil, biochar, and syngas hydrocarbons. Results show that biochar from slow pyrolysis could achieve minimum selling prices (MSPs) of $\$$188-$\$$260/t, competitive with reported market values, while bio-oil from fast pyrolysis is estimated to yield MSPs of $\$$6.49-$\$$9.68/GGE, approximately twice conventional fuel benchmarks. Sensitivity analysis identifies feedstock cost, product yield, and scale as primary cost drivers, while scenarios involving biochar carbon credits and high value applications may substantially improve economics. Overall, these results suggest that continued innovation in feedstock logistics, process integration, and market development will be critical to achieving economically viable and scalable bioproducts.

09 BIOMASS FUELS↗
DOE OSTI2023

Non-canonical d-xylose and l-arabinose metabolism via d-arabitol in the oleaginous yeast Rhodosporidium toruloides

Abstract R. toruloides is an oleaginous yeast, with diverse metabolic capacities and high tolerance for inhibitory compounds abundant in plant biomass hydrolysates. While R. toruloides grows on several pentose sugars and alcohols, further engineering of the native pathway is required for efficient conversion of biomass-derived sugars to higher value bioproducts. A previous high-throughput study inferred that R. toruloides possesses a non-canonical l -arabinose and d -xylose metabolism proceeding through d -arabitol and d -ribulose. In this study, we present a combination of genetic and metabolite data that refine and extend that model. Chiral separations definitively illustrate that d -arabitol is the enantiomer that accumulates under pentose metabolism. Deletion of putative d -arabitol-2-dehydrogenase (RTO4_9990) results in > 75% conversion of d -xylose to d -arabitol, and is growth-complemented on pentoses by heterologous xylulose kinase expression. Deletion of putative d -ribulose kinase (RTO4_14368) arrests all growth on any pentose tested. Analysis of several pentose dehydrogenase mutants elucidates a complex pathway with multiple enzymes mediating multiple different reactions in differing combinations, from which we also inferred a putative l -ribulose utilization pathway. Our results suggest that we have identified enzymes responsible for the majority of pathway flux, with additional unknown enzymes providing accessory activity at multiple steps. Further biochemical characterization of the enzymes described here will enable a more complete and quantitative understanding of R. toruloides pentose metabolism. These findings add to a growing understanding of the diversity and complexity of microbial pentose metabolism.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Integrated lignocellulosic biorefinery for efficient production of furans and photothermal materials

Integrated lignocellulosic biorefineries offer a great potential to valorize all the components in lignocellulose into products, including fuels, chemicals, and materials. However, because of lignocellulose recalcitrance, conversion of bioresources remains a techno-economic challenge for many lignocellulosic biorefineries. In this work, we have proposed a sustainable and profitable biorefinery strategy for lignocellulose fractionation and conversion. In this design, a biphasic solvent consisting of a molten salt hydrate LiCl·4H 2 O and γ-valerolactone (GVL) was initially used for separating hemicellulose from lignocellulose. More interestingly, 100 wt% of biorefinery products from lignin were directly converted to functional photothermal materials by coordinating with Fe 3+ for solar-thermal-electricity conversion. Attributed to this rational design, we report the techno-economic analysis predicts a revenue of 439.3 USD by processing 100 kg of lignocellulosic biomass using the above developed method.

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

Microwave-assisted catalytic gasification of mixed plastics and corn stover for low tar, hydrogen-rich syngas production

The challenge for efficient management of post-consumer plastic and biomass waste has grown over the past few decades due to their dramatic increases. In comparison to conventional gasification, microwave-assisted co-gasification of plastics and corn stover offers many benefits, including increased H 2 yield and gas components compared to unfavorable char/tar. Nonetheless, for future commercialization of the process and ease of product separation, further reduction of the undesirable tar is necessary, which can be achieved over the catalytic route. Here, in this work, we studied the catalytic effect of magnetite for microwave-assisted co-gasification of corn stover and plastic to make syngas with higher H 2 and lower tar selectivity over non-catalytic conditions. A 1:1:1 ratio of plastic-corn stover-magnetite was used to evaluate the reaction parameters such as temperature, space velocity, heating media, and catalytic cycles under gasification conditions. In comparison with the microwave non-catalytic route, a 100% increase in the total H 2 yield with 76% higher H 2 production efficiency (mmol/kWh) was achieved in the presence of the magnetite catalyst, while reducing the overall tar formation from 9% to 2%. When magnetite was reduced in situ during the reaction, it coupled with microwave and delivered oxygen radicals that cracked down plastic and corn stover intermediates generated from the synergistic effect under microwave heating. Soon after the oxygen transfer process initiated, magnetite reached its final oxidation state consisting of microwave-active Fe and Fe 3 C phases that continued coupling with microwaves along with the generated graphitic carbon to maintain the heat necessary to further reduce the generated tar and make additional gaseous products, as confirmed by XRD, Raman, and TGA analyses.

08 HYDROGEN↗
DOE OSTI2021

Lignin-Derived Chemicals from Pulping Liquors: Cooperative Research and Development CRADA Number CRD-17-00714 (Final Report)

National Renewable Energy Laboratory (NREL) has developed a robust portfolio for lignin valorization using a “biological funneling” approach, which adopts a microbial process to convert the inherent heterogeneity of lignin-rich streams into single high-value products. In parallel, Sustainable Fiber Technologies (SFT) has developed a proprietary, high-pH process to convert non-woody biomass into valuable pulp for myriad biomaterial applications. Therefore, by combining the expertise of both SFT and NREL, this project aimed to valorize co-products from an industrial pulping process of non-woody feedstocks. A detailed analytical characterization of an SFT pulping stream was used to aid the development of a bench-scale separations strategy to isolate a mixture of low molecular weight compounds, and ultimately to aid in bioreactor cultivations used to produce polyhydroxyalkanoate (PHA) biopolymers at titers, rates, and yields necessary for moving towards commercialization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Sustainable Lactic Acid Production from Lignocellulosic Biomass

Lignocellulosic biomass is a promising feedstock for sustainable biofuels and bioproducts. Among emerging bioproducts, lactic acid has attracted significant interest because of its growing application in many industries (e.g., packaging, medical, and pharmaceutical). In this study, BioSTEAM—an open-source platform—was leveraged for the design, simulation, and evaluation (via techno-economic analysis, TEA, and life cycle assessment, LCA) of lignocellulosic lactic acid biorefineries. With a minimum product selling price (MPSP) between 1.38 and 1.91 kg –1 (5th–95th percentiles, baseline at 1.57 kg –1 ), the biorefinery was capable of producing market-competitive lactic acid (market price between 1.7 and 2.1 kg –1 ), and its performance could be further enhanced (e.g., MPSP down to 1.09 kg –1 , global warming potential of 2.79 kg CO 2 -eq·kg –1 , and fossil energy consumption of 31.7 MJ·kg –1 ) with advancements in key technological parameters (fermentation yield and separation process conversions) and optimization in process operation. Sensitivity analyses focused on the fermentation unit (across titer, yield, and productivity; neutral vs low-pH fermentation) and feedstock characteristics (carbohydrate content and price) were also included to quantify their impact on the sustainability of the biorefinery. Overall, this research highlights the ability of agile TEA/LCA to screen promising biorefinery designs, prioritize research needs, and establish a road map for the continued development of bioproducts and biofuels.

09 BIOMASS FUELS↗
DOE OSTI2021

Liquefying Lignins: Determining Phase-Transition Temperatures in the Presence of Aqueous Organic Solvents

Under appropriate conditions of temperature and solvent composition, single-phase aqueous organic solvents are capable of liquefying lignin to form a lignin-rich liquid phase separate from the solvent phase, creating liquid–liquid equilibrium. The extent to which this phenomenon occurs when Kraft lignin is combined with the solvents methanol, ethanol, isopropanol, and acetone was determined, with solid–liquid (SL) to liquid–liquid (LL) phase-transition temperatures being measured over the range of applicable organic–water compositions. Lignins tested from a variety of biomass sources were all discovered to form this liquid–liquid equilibrium with aqueous ethanol solutions. Furthermore, the formation of such phase behavior between lignin and economical, green solvents creates new opportunities for the large-scale purification and fractionation of raw bulk (i.e., technical) lignins.

09 BIOMASS FUELS↗
NASA NTRS2016

Aircraft-Measured Indirect Cloud Effects from Biomass Burning Smoke in the Arctic and Subarctic

The incidence of wildfires in the Arctic and subarctic is increasing; in boreal North America, for example, the burned area is expected to increase by 200-300 over the next 50-100 years, which previous studies suggest could have a large effect on cloud microphysics, lifetime, albedo, and precipitation. However, the interactions between smoke particles and clouds remain poorly quantified due to confounding meteorological influences and remote sensing limitations. Here, we use data from several aircraft campaigns in the Arctic and subarctic to explore cloud microphysics in liquid-phase clouds influenced by biomass burning. Median cloud droplet radii in smoky clouds were 50 smaller than in background clouds. Based on the relationship between cloud droplet number (N(liq))/ and various biomass burning tracers (BBt/ across the multi-campaign dataset, we calculated the magnitude of subarctic and Arctic smoke aerosol-cloud interactions (ACI, where ACI = (1/3) x dln(N(liq))/dln(BBt)) to be 0.12 out of a maximum possible value of 0.33 that would be obtained if all aerosols were to nucleate cloud droplets. Interestingly, in a separate subarctic case study with low liquid water content (0.02 gm/ cu m) and very high aerosol concentrations (2000-3000 cu m) in the most polluted clouds, the estimated ACI value was only 0.06. In this case, competition for water vapor by the high concentration of CCN strongly limited the formation of droplets and reduced the cloud albedo effect, which highlights the importance of cloud feedbacks across scales. Using our calculated ACI values, we estimate that the smoke-driven cloud albedo effect may decrease shortwave radiative flux by 2 and 4 W/sq or more under some low and homogeneous cloud cover conditions in the subarctic, although the changes should be smaller in high surface albedo regions of the Arctic. We lastly show evidence to suggest that numerous northern latitude background Aitken particles can interact with combustion particles, perhaps impacting their properties as cloud condensation and ice nuclei. However, the influence of background particles on smoke-driven indirect effects is currently unclear.

Arctic↗
DOE OSTI2022

Effects of experimental nitrogen deposition on soil organic carbon storage in Southern California drylands

Atmospheric nitrogen (N) deposition is enriching soils with N across biomes. Soil N enrichment can increase plant productivity and affect microbial activity, thereby increasing soil organic carbon (SOC), but such responses vary across biomes. Drylands cover ~45% of Earth's land area and store ~33% of global SOC contained in the top 1 m of soil. Nitrogen fertilization could, therefore, disproportionately impact carbon (C) cycling, yet whether dryland SOC storage increases with N remains unclear. To understand how N enrichment may change SOC storage, we separated SOC into plant–derived, particulate organic C (POC), and largely microbially derived, mineral–associated organic C (MAOC) at four N deposition experimental sites in Southern California. Theory suggests that N enrichment increases the efficiency by which microbes build MAOC (C stabilization efficiency) if soil pH stays constant. But if soils acidify, a common response to N enrichment, then microbial biomass and enzymatic organic matter decay may decrease, increasing POC but not MAOC. We found that N enrichment had no effect on C fractions except for a decrease in MAOC at one site. Specifically, despite reported increases in plant biomass in three sites and decreases in microbial biomass and extracellular enzyme activities in two sites that acidified, POC did not increase. Furthermore, microbial C use and stabilization efficiency increased in a non–acidified site, but without increasing MAOC. Instead, MAOC decreased by 16% at one of the sites that acidified, likely because it lost 47% of the exchangeable calcium (Ca) relative to controls. Indeed, MAOC was strongly and positively affected by Ca, which directly and, through its positive effect on microbial biomass, explained 58% of variation in MAOC. Finally, long–term effects of N fertilization on dryland SOC storage appear abiotic in nature, such that drylands where Ca–stabilization of SOC is prevalent and soils acidify, are most at risk for significant C loss.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

How Does Escherichia coli Allocate Proteome?

Microorganisms are shown to actively partition their intracellular resources, such as pro- teins, for growth optimization. Recent experiments have begun to reveal molecular com- ponents unpinning the partition; however, it remains unclear quantitatively how individual parts orchestrate to yield precise resource allocation that is both robust and dynamic. Here we developed a coarse-grained mathematical framework that centers on guanosine pentaphosphate (ppGpp)-mediated regulation, and used it to systematically uncover the design principles of proteome allocation in Escherichia coli. Our results showed that cellular ability of resource partition lies in an ultrasensitive, negative feedback control- ling topology with the ultrasensitivity arising from zero-order amino acid kinetics and the negative feedback from ppGpp-controlled ribosome synthesis. In addition, together with the time-scale separation between slow ribosome kinetics and fast turnovers of ppGpp and amino acids, the network topology confers the organism an optimization mechanism which mimics sliding mode control, a nonlinear optimization strategy that is widely used in man-made systems. We further showed that such a controlling mechanism is robust against parameter variations and molecular fluctuations, and is also efficient for biomass production over time. Furthermore, this work elucidates the fundamental controlling mechanism of E. coli proteome allocation, thereby providing insights into quantitative microbial physiology as well as the design of synthetic gene networks.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Arctic shrub size and leaf traits, northern Alaska, summer 2017 (Version 2.0)

This data package contains leaf and size trait and environmental data collected from 170 plots of rapidly expanding shrub genera (Alnus, Betula, and Salix) and a widespread sedge (Eriophorum vaginatum) along a latitudinal and climate gradient in northern Alaska. The trait data were collected in summer 2017 and include leaf area, specific leaf area, leaf nitrogen concentration, leaf delta 15N, leaf delta 13C, shrub height, aboveground biomass, and the ratio of root biomass to aboveground biomass. These raw data support a submitted manuscript that examines the intraspecific variations of size, leaf and root traits of shrubs across the graminoid-dominated nutrient-poor arctic tundra and reveals the environmental drivers of deciduous shrub traits in tundra ecosystems (Fraterrigo et al., submitted). Data are presented by site (n=5) and patch (shrub or sedge plot) in separate csv files. The location data are provided in the “plot coordinates” file; all other files contain the data in the file title. Detailed methods are in the submitted manuscript. A companion data package contains root trait data collected simultaneously from the same plots (Fraterrigo and Chen, 2020). See the "Related references" section for more information.2023/07/20 Update: The latest version of this dataset publication is version 2.0. The latest version of the data package was updated to correct the leaf size trait.csv file.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

AI-powered municipal solid waste management: a comprehensive review from generation to utilization

The accumulation of municipal solid waste (MSW) continues to rise due to burgeoning population, rapid global urbanization and economic growth, intensifying ecological concerns associated with landfills and greenhouse gas (GHG) emissions. Over the past 2 decades, global waste generation has surged by 50%, with one-third remaining uncollected and about 70% sent to landfills. This review examines the critical role of integrating emerging technologies, such as advanced sensors and artificial intelligence (AI), into end-to-end MSW management to alleviate landfill burdens. The suitability of various AI tools for different stages of MSW management is assessed, alongside the deployment of advanced sensors including hyperspectral cameras, computer vision systems, and internet of things (IoT) devices for material identification. Applications of genetic algorithms and reinforcement learning for optimizing collection routes, reducing costs, and lowering emissions are highlighted. Life cycle assessment (LCA) across all stages of MSW management is also reviewed, along with future trends in leveraging generative AI, natural language processing (NLP), and agent-based AI systems to analyze waste generation patterns and public sentiment. Efficient collection and handling can be enhanced through route optimization with geographic information systems and real-time bin-level monitoring. Furthermore, sensor-embedded, real-time object detection systems paired with robotics enable material characterization and automated sorting, thereby lowering costs and diverting waste from landfills into value-added products for diverse industrial sectors including packaging, chemicals, textiles, metals and glass, transportation, and electronics industries. Without intervention, global waste is projected to reach 4.54 billion tons by 2050, contributing direct economic costs of $\$$400 billion and roughly 2.38 billion tons of CO 2 -equivalent emissions annually. This review demonstrates how AI-driven, end-to-end solutions for MSW management can mitigate economic and environmental challenges, while directly supporting the United Nations Sustainable Development (UNDP) goals related to innovation and infrastructure (SDG 9), sustainable cities (SDG 11), responsible consumption and production (SDG 12), and climate action (SDG 13).

09 BIOMASS FUELS↗
NASA NTRS2019

Modelling above-ground biomass stock over Norway using national forest inventory data with ArcticDEM and Sentinel-2 data

Boreal forests constitute a large portion of the global forest area, yet they are undersampled through field surveys, and only a few remotely sensed data sources provide structural information wall-to-wall throughout the boreal domain. ArcticDEM is a collection of high-resolution (2 m) space-borne stereogrammetric digital surface models (DSM) covering the entire land area north of 60° of latitude. The free-availability of ArcticDEM data offers new possibilities for aboveground biomass mapping (AGB) across boreal forests, and thus it is necessary to evaluate the potential for these data to map AGB over alternative open-data sources (i.e., Sentinel-2). This study was performed over the entire land area of Norway north of 60° of latitude, and the Norwegian national forest inventory (NFI) was used as a source of field data composed of accurately geolocated field plots (n=7710) systematically distributed across the study area. Separate random forest models were fitted using NFI data, and corresponding remotely sensed data consisting of either: i) a canopy height model (ArcticCHM) obtained by subtracting a high-quality digital terrain model (DTM) from the ArcticDEM DSM height values, ii) Sentinel-2 (S2), or iii) a combination of the two (ArcticCHM+S2). Furthermore, we assessed the effect of the forest- and terrain-specific factors on the models’ predictive accuracy. The best model (,i.e., ArcticCHM+S2) explained nearly 60% of the variance of the training set, which translated in the largest accuracy in terms of root mean square error (RMSE=41.4 t/ha). This result highlights the synergy between 3D and multispectral data in AGB modelling. Furthermore, this study showed that despite the importance of ArcticCHM variables, the S2 model performed slightly better than ArcticCHM model. This finding highlights some of the limitations of ArcticDEM, which, despite the unprecedented spatial resolution, is highly heterogeneous due to the blending of multiple acquisitions across different years and seasons. We found that both forest- and terrain-specific characteristics affected the uncertainty of the ArcticCHM+S2 model and concluded that the combined use of ArcticCHM and Sentinel-2 represents a viable solution for AGB mapping across boreal forests. The synergy between the two data sources allowed for a reduction of the saturation effects typical of multispectral data while ensuring the spatial consistency in the output predictions due to the removal of artifacts and data voids present in ArcticCHM data. While the main contribution of this study is to provide the first evidence of the best-case-scenario (i.e., availability of accurate terrain models) that ArcticDEM data can provide for large-scale AGB modelling, it remains critically important for other studies to investigate how ArcticDEM may be used in areas where no DTMs are available as is the case for large portions of the boreal zone.

space-borne imagery↗