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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Effects of surface treatments on ABS mechanical properties from fused filament fabrication

This paper examines the influence of surface treatments on the mechanical properties of acrylonitrile butadiene styrene (ABS) samples printed by fused filament fabrication (FFF). Prior efforts have applied brushing, painting, solvent dipping, infiltration, and vapor smoothing as post-processing surface treatments to improve the mechanical properties of FFF components. Additionally, because FFF can produce components with undesirable surface roughness, mechanical abrasion, epoxy coating, and acetone treatment may increase tensile strength by decreasing stress concentrations. Ridged surface texture may provide desirable tribological or handling properties. Based on these opportunities, this paper investigates abrasive media blasting, epoxy coating, acetone immersion, and ridged texturing surface treatments on the tensile strength and other mechanical properties of FFF ABS samples. ASTM D638-14 Type-I samples were printed, treated on all sample sides, and tested. From tensile tests, the elastic modulus, tensile strength, and fracture strain for both the untreated and treated ABS samples were calculated. For each sample, the surface finish and fracture macromorphology were observed with optical microscopy and the roughness values for the surface finish were calculated from profilometer data. Furthermore, samples were submerged in water and weighed periodically to measure mass changes due to water absorption. From surface profilometry and optical miscopy data, mechanical media blasting, epoxy coating, and immersion in all concentrations of acetone decreased surface roughness. Overall, on average, grit blasting with large beads and epoxy coating led to 2.6% and 1.2% increases in tensile strength, respectively; immersion in 40% acetone led to a 1.9% increase in tensile strength while treatment in 60% and 80% acetone decreased tensile strength by 4.9% and 1.9%, respectively. The study concludes that only grit blasting with large beads, immersion in 60% acetone, and the ridged texture significantly affected the tensile strength.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Understanding spatial and temporal drivers of variation in tree hydraulic processes and their consequences for climate feedbacks (Final Technical Report)

This is the final technical report from the first phase of a project that changed institutions. The grant was titled “Understanding spatial and temporal drivers of variation in tree hydraulic processes and their consequences for climate feedbacks.” The overall objectives of this project were to (1) provide model‐compatible datasets of key plant hydraulic traits and status for model evaluation, parameterization and validation and (2) use these data to pinpoint ecosystem responses to a changing hydroclimate by addressing both long‐term climatic drying and episodic extreme droughts. We planned to address the objectives with three research activities to quantify plant responses to chronic water stress and episodic drought: (1) generate high frequency observations of soil and plant hydraulic data across different landscape positions at multiple sites, (2) quantify plant hydraulic trait plasticity in response to experimental soil moisture reduction in situ in two central hardwood forests, and (3) simulate the carbon consequences of incorporating plant hydrodynamics and plant acclimation to water stress in the DOE‐sponsored plant hydrodynamics model FATES‐HYDRO. As of the transfer of this project to another institution, we had made substantial progress on activities 1 and 2, and started activity 3.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Data from : "Warming promotes loss of subsoil carbon through accelerated degradation of plant-derived organic matter". Blodgett warming experiment

This dataset contains data used for the paper: Warming promotes loss of subsoil carbon through accelerated degradation of plant-derived organic matter. Soil Biology and Biochemistry 156, 108185. doi:10.1016/j.soilbio.2021.108185On April 2018 (after 4.5 years of warming), we collected O-horizon (organic horizon) material and soil core down to 90 cm depth from a whole-soil warming experiment in a mixed-coniferous temperate forest, located at the University of California Blodgett experimental forest in the foothills of the Sierra Nevada, CA USA. The goal was to assess how 4.5 years of +4 °C whole-soil warming affected the quantity and quality of soil organic matter. Cores were collected from 6 experimental plots (three replicated blocks); samples were collected in 10 cm increments from 0 to 90 cm depth.This dataset contains a compressed (.zip) archive of the data used for this manuscript. The dataset includes files in .xlsx format, which can be accessed and processed using MS Excel or R. Carbon and nitrogen concentrations, as well as stable carbon isotope composition ((δ13C) and solvent extractable lipid biomarker (alkanoic acids and alkanes) data are provided as processed data files. Diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy data are provided as raw output and processed data files.The dataset files "Blodgett_warming_Data" and "Blodgett_warming_raw_data.xlsx" were updated on July 7, 2021. The following updates were made: (1) specification of the units of measurements in the dataset (the unit of measurement was missing in some parameters) and (2) the column name "pulled depth" was changed to "pooled depth" in the updated data files.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Abundance and Migration Success of Overshoot Steelhead in the Upper Columbia River

Abstract Summer steelhead Oncorhynchus mykiss may enter freshwater almost a year before spawning and potentially make long migrations (>1,000 km) to interior headwater habitats. However, in response to suboptimal freshwater habitat conditions (e.g., warmer water temperatures), adult summer steelhead may exhibit complex behaviors during upstream migration in the Columbia River basin. Steelhead may migrate upstream of their natal tributary (hereafter, referred to as “overshoot”) and spend days to several months before subsequently migrating downstream (hereafter, referred to as “fallback”) to their natal tributary to spawn. An expansion of an existing Bayesian patch occupancy model, derived from observations of adult steelhead that were PIT-tagged to estimate population-specific abundance upstream of the tagging location, incorporated downstream detection locations to estimate the abundance of overshoot fallbacks. Overshoot steelhead abundance at the tagging location was estimated based on the relationship between the number of known overshoot fallbacks (i.e., the number of steelhead that overshot and successfully migrated downstream to their natal tributary) and their model-estimated abundance. During the study period (2010–2017), the annual mean proportion of overshoot steelhead that successfully migrated downstream of the tagging location (Priest Rapids Dam) was 0.59 (SD = 0.14). The number of dams encountered by overshoot steelhead during their downstream migration was negatively correlated with their downstream migration success probability. Improved downstream passage survival for adult steelhead will increase the abundance of affected populations while reducing potential genetic introgression of upstream populations (i.e., strays). This is the first study to estimate the abundance of overshoot and fallback steelhead, providing the data necessary for scientists to estimate potential conservation benefits of improved downstream survival. For example, surface flow passage routes (e.g., sluiceways and temporary spillway weirs) are very effective in guiding and passing adult steelhead downstream of Columbia River hydroelectric projects and data from this assessment show that changes in dam operations throughout the downstream migration period may maximize conservation benefits.

Murdoch, Andrew R. (ORCID:0000000324827689)↗
DOE OSTI2022

Droplet Evaporation-Based Approach for Microliter Fuel Property Measurements

Small-volume, high-throughput screening techniques are sought to enable downselection from a large candidate pool of bio-blendstocks to a select few, having physical properties consistent with requirements of downsized, turbo-boosted internal combustion engines. Herein, this work presents a droplet evaporation-based approach to predict heat of vaporization, vapor pressure, diffusion coefficient, and Lennard–Jones parameters for an unknown fuel. Two different schemes, considering the isothermal evaporation of a moving droplet in ambient air, are proposed, which combine droplet velocity and temperature measurements, with some known properties to predict unknown properties. The schemes utilize an inverse solution of a transient model of droplet evaporation solved in an iterative fashion. A baseline scheme, which only requires droplet size change measurements, is evaluated using test data for three liquid fuels, comprising of alkanes and alcohols, as obtained in a temperature-controlled chamber. Results yield temperature-dependent heat of vaporization and vapor pressure predictions within 10 % and 22 %, respectively, of reference values. The advanced scheme, which additionally requires droplet temperature measurement, is numerically evaluated in the current work and will be experimentally validated in future efforts. The advanced scheme is found to significantly improve prediction quality, with deviations less than 2 % and 1 % for heat of vaporization and vapor pressure, while also predicting diffusion coefficient and Lennard–Jones parameters within 5 % and 8 %, respectively. The combined set of approaches, which primarily track droplet evaporation, can be incorporated into a small-volume, high-throughput fuel screening process.

09 BIOMASS FUELS↗
DOE OSTI2024

Estimating irrigation water use from remotely sensed evapotranspiration data: Accuracy and uncertainties at field, water right, and regional scales

Irrigated agriculture is the dominant user of water globally, but most water withdrawals are not monitored or reported. As a result, it is largely unknown when, where, and how much water is used for irrigation. Here, we evaluated the ability of remotely sensed evapotranspiration (ET) data, integrated with other datasets, to calculate irrigation water withdrawals and applications in an intensively irrigated portion of the United States. We compared irrigation calculations based on an ensemble of satellite-driven ET models from OpenET with reported groundwater withdrawals from hundreds of farmer irrigation application records and a statewide flowmeter database at three spatial scales (field, water right group, and management area). At the field scale, we found that ET-based calculations of irrigation agreed best with reported irrigation when the OpenET ensemble mean was aggregated to the growing season timescale (bias = 1.6–4.9%, R 2 = 0.53–0.74), and agreement between calculated and reported irrigation was better for multi-year averages than for individual years. At the water right group scale, linking pumping wells to specific irrigated fields was the primary source of uncertainty. At the management area scale, calculated irrigation exhibited similar temporal patterns as flowmeter data but tended to be positively biased with more interannual variability. Disagreement between calculated and reported irrigation was strongly correlated with annual precipitation, and calculated and reported irrigation agreed more closely after statistically adjusting for annual precipitation. The selection of an ET model was also an important consideration, as variability across ET models was larger than the potential impacts of conservation measures employed in the region. From these results, we suggest key practices for working with ET-based irrigation data that include accurately accounting for changes in soil moisture, deep percolation, and runoff; careful verification of irrigated area and well-field linkages; and conducting application-specific evaluations of uncertainty.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Explainable machine learning to quantify the value of proximal remote sensing in latent energy flux estimation

Proximal remote sensing has the potential to provide critical information on vegetation biophysical factors that can predict land-atmosphere exchange of water and energy. Latent energy (LE) flux is traditionally estimated using process-based models which rely on vegetation parameters that change during the growing season. Data-driven models have the potential to address these issues by offering flexible predictor selection and more efficient utilization of the information in predictor sets. These models require careful choice of predictors to avoid redundancy and allow robust cross-validation. In this study we present a systematic and comprehensive evaluation of machine learning (ML) models to assess the capability of meteorological and proximal sensing data for predicting LE at a half-hourly temporal resolution across multiple growing seasons for an agricultural system. The results presented here demonstrate that a model using four environmental predictors in combination with two proximal sensing variables can capture 88 % of the variability in LE. ML models using only three predictors (one meteorological and two proximal remote sensing) captured 81 % of LE variability, offering the best trade-off between performance and complexity. An ML model utilizing only two predictors, one proximal remote sensing variable and downwelling radiation, captured 77 % of LE variability. These results demonstrate the power of proximal remote sensing and meteorological observations to estimate land-atmosphere water vapor exchange, providing a solution where more direct methods such as eddy covariance are not available and for evaluations of agronomic management and genotypic variations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

COVID-19 pandemic ramifications on residential Smart homes energy use load profiles

The COVID-19 pandemic has significantly affected people’s behavioral patterns and schedules because of stay-at-home orders and a reduction of social interactions. Therefore, the shape of electrical loads associated with residential buildings has also changed. In this paper, we quantify the changes and perform a detailed analysis on how the load shapes have changed, and we make potential recommendations for utilities to handle peak load and demand response. Our analysis incorporates data from before and after the onset of the COVID-19 pandemic, from an Alabama Power Smart Neighborhood with energy-efficient/smart devices, using around 40 advanced metering infrastructure data points. This paper highlights the energy usage pattern changes between weekdays and weekends pre– and post–COVID-19 pandemic times. The weekend usage patterns look similar pre– and post–COVID-19 pandemic, but weekday patterns show significant changes. We also compare energy use of the Smart Neighborhood with a traditional neighborhood to better understand how energy-efficient/smart devices can provide energy savings, especially because of increased work-from-home situations. HVAC and water heating remain the largest consumers of electricity in residential homes, and our findings indicate an even further increase in energy use by these systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Towards the next generation of Geospatial Artificial Intelligence

Geospatial Artificial Intelligence (GeoAI), as the integration of geospatial studies and AI, has become one of the fastest-developing research directions in spatial data science and geography. This rapid change in the field calls for a deeper understanding of the recent developments and envision where the field is going in the near future. In this work, we provide a quantitative analysis of the GeoAI literature from the spatial, temporal, and semantic aspects. We briefly discuss the history of AI and GeoAI by highlighting some pioneering work. Then we discuss the current landscape of GeoAI by selecting five representative subdomains including remote sensing, urban computing, Earth system science, cartography, and geospatial semantics. Finally, we highlight several unique future research directions of GeoAI which are classified into two groups: GeoAI method development challenges and GeoAI Ethics challenges. Topics include heterogeneity-aware GeoAI, knowledge-guided GeoAI, spatial representation learning, geo-foundation models, fairness-aware GeoAI, privacy-aware GeoAI, as well as interpretable and explainable GeoAI. We hope our review of GeoAI’s past, present, and future is comprehensive and can enlighten the next generation of GeoAI research.

58 GEOSCIENCES↗
DOE OSTI2025

Magnetic structure evolution of LiFe 1- x Co x PO 4 olivines upon delithiation

We present a comprehensive study of the nuclear and magnetic structures of the mixed olivine solid solution series LiFe 1-x Co x PO 4 as well as their delithiated counterparts, for metal concentrations x = 0.2 - 0.6. Through neutron powder diffraction studies, we find that the LiFe 1-x Co x PO 4 series orders in the magnetic space group Pnma', consistent with their Li(Fe/Co)PO 4 parent structures. After chemical delithiation using peracetic acid, however, the removal of over 30% of the lithium from the lattice results in a transition from an A y -type to an A x -type antiferromagnetic structure. The magnetic space group consistent with A x antiferromagnetism was found to be Pn'm'a'. Interestingly, magnetic susceptibility measurements of both series reveal that delithiation increases the magnetic transition temperature, T N , from 50 K to 115 K. We find through analysis of the diffraction data that the unit cell parameters change linearly as a function of x; consequently, the exchange pathways between the Fe/Co magnetic cations are affected by the delithiation. Here, we discuss how exchange pathways, metal oxidation states, and d-orbital occupation all contribute to the observed magnetic symmetries and trends in T N in both series.

Antiferromagnet↗
DOE OSTI2023

Validation of the single-event method for low-energy electron transport via stopping power calculations with $\mathrm{MCNP}$

Monte Carlo simulations of low-energy ( <50 keV) electron transport in matter are essential for a broad range of application fields. Several Monte Carlo codes have developed specialized treatments for this case, but a comprehensive validation of low-energy electron transport for general-purpose simulations remains lacking in the literature. One approach to accomplish this validation is calculation of stopping power using low-energy electron transport physics, as stopping power is a fundamental radiation transport quantity which must be simulated accurately for nearly any application. Here in this work, we use the Monte Carlo N-Particle (MCNP) radiation transport code with the single-event method for electron transport to calculate stopping powers of low-energy electrons (50 eV to 30 keV) in 41 elemental solids, 14 compound solids, and five rare gas solids, comparing simulation results to published semi-empirical stopping power calculations from optical measurements. In general, the simulations give good agreement (typically within ±10%) with semi-empirical stopping power values at higher energies: 300 eV and above for most elemental solids, 1 keV and above for compound solids, and 400 eV and above for rare gas solids. Agreement between MCNP and semi-empirical values is worse below these energies. The most significant source of error is the EPRDATA14 cross section data, which does not account for changes in electronic structure due to solid-state bonding, particularly in compound materials. The simplistic model of atomic excitation used to generate the EPRDATA14 cross sections is another key source of error. Additionally, the breakdown of the continuous slowing-down approximation introduces significant uncertainty at low energies, although this is a limitation of the calculation method and not of the simulation procedure. Accounting for these and other uncertainty sources, the single event method in MCNP is robust and able to give good accuracy for a variety of low-energy electron transport problems through diverse kinds of materials.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2022

Investigating the Role of Copper in Arsenic Doped Cd(Se,Te) Photovoltaics

The open circuit voltage (VOC) deficit in Cd(Se,Te)-based photovoltaics remains a critical obstacle for pushing the technology closer to theoretical performance limits. Arsenic doping has become a dominant and promising route to achieve the higher p-type carrier concentrations necessary for higher VOC, but challenges associated with this alternate defect chemistry and higher doping density have hindered progress. Here we show that while arsenic doping enables high carrier concentrations (>1016 cm-3), co-doping with copper can provide a boost to VOC without a significant change to carrier concentration. A large data set is initially used to explore current-voltage and capacitance-voltage trends associated with arsenic doped devices with and without copper. A smaller subset is then used to probe these trends using a wide variety of characterization techniques. Copper is found to facilitate reduced interface recombination and potentially improved bulk absorber characteristics, though the mechanisms for these improvements are not yet clear. Despite the improved performance of co-doped devices, VOC is still far below its potential especially for highly doped devices. Low emitter doping in conjunction with high absorber doping seems to be a plausible cause for this significant deficit, though other device properties may exacerbate this problem.

CdSeTe↗
DOE OSTI2025

Application of Amber Suppression To Study the Role of Tyr M210 in Electron Transfer in Rhodobacter sphaeroides Photosynthetic Reaction Centers

The initial light-induced electron transfer (ET) steps in the bacterial photosynthetic reaction center (RC) have been extensively studied and provide a paradigm for connecting structure and function. Although RCs have local pseudo-C 2 symmetry, ET only occurs along the A branch of chromophores. Tyrosine M210 is a key symmetry-breaking residue adjacent to bacteriochlorophyll B A that bridges primary electron donor P and bacteriopheophytin acceptor H A . Here, we used amber suppression to incorporate phenylalanine variants with different electron-withdrawing/donating capabilities at position M210. X-ray data generally reveal no appreciable structural changes due to the mutations. P* decay and P + H A - formation are multi-exponential (~2-9, ~10-60, and ~100-300 ps) and temperature dependent. The 1020 nm transient-absorption band of P + B A - is barely resolved for a few variants at 295 K and for none at 77 K. The results indicate a change from two-step ET for wild-type RCs to dominance of one-step superexchange ET for the mutants. Resonance Stark spectroscopy reveals that the free energy of P + B A - changes by -57 to +66 meV among the phenylalanine variants. Because P+BA apparently lies above P* in all phenylalanine variants, the perturbations primarily affect the energy denominator for superexchange mixing. The findings deepen insight into primary ET in the bacterial RC.

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

Streamflow Response to Glacier Mass Loss Varies With Basin Precipitation Across Alaska

Abstract Diminishing glaciers affect streamflow, and given the extent of glaciers in Alaska and adjacent Canada, continued glacier mass loss is likely to have profound effects on ecosystems sensitive to runoff. The effects of glacier mass loss on streamflow are likely to vary across the wide ranges of basin size, glacier cover, and precipitation in this region. In this study, we use U.S. Geological Survey (USGS) streamflow data with satellite‐based glacier volume change estimates to quantify how glacier mass loss subsidized streamflow over the 2000–2019 period for 116 glacierized basins. We examine interannual variability in that subsidy at three USGS‐monitored glaciers to explore the ability of the subsidy to buffer streamflow derived solely from precipitation. We found the relative importance of percent glacier cover on streamflow magnitude increases in drier basins. In the driest basins, glaciers produced 40 times greater percent glacier mass loss subsidies to streamflow for the percent glacier cover compared to the wettest basins. While the subsidy from glacier mass loss buffers interannual variability in streamflow to varying degrees, it can also increase streamflow variability. Smaller amounts of percent glacier cover are needed to produce summer‐melt‐dominated seasonal flow regimes in drier basins than in wetter basins. Decreasing glacier cover will eventually decrease summer streamflow, increasing spring streamflow in drier basins, and attenuating seasonality with increasing spring and autumnal streamflow in wetter basins. Quantifying the downstream effects of continued glacier mass loss without the computational expense of a hydrological model is broadly applicable in this changing climate.

Curran, Janet H. [U.S. Geological Survey Alaska Sc↗
DOE OSTI2023

A crucial role for dynamic expression of components encoding the negative arm of the circadian clock

In the Neurospora circadian system, the White Collar Complex (WCC) drives expression of the principal circadian negative arm component frequency ( frq ). FRQ interacts with FRH (FRQ-interacting RNA helicase) and CKI, forming a stable complex that represses its own expression by inhibiting WCC. In this study, a genetic screen identified a gene, designated as brd-8 , that encodes a conserved auxiliary subunit of the NuA4 histone acetylation complex. Loss of brd-8 reduces H4 acetylation and RNA polymerase (Pol) II occupancy at frq and other known circadian genes, and leads to a long circadian period, delayed phase, and defective overt circadian output at some temperatures. In addition to strongly associating with the NuA4 histone acetyltransferase complex, BRD-8 is also found complexed with the transcription elongation regulator BYE-1. Expression of brd-8, bye-1, histone h2a.z , and several NuA4 subunits is controlled by the circadian clock, indicating that the molecular clock both regulates the basic chromatin status and is regulated by changes in chromatin. Taken together, our data identify auxiliary elements of the fungal NuA4 complex having homology to mammalian components, which along with conventional NuA4 subunits, are required for timely and dynamic frq expression and thereby a normal and persistent circadian rhythm.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A biomass map of the Brazilian Amazon from multisource remote sensing

The Amazon Forest, the largest contiguous tropical forest in the world, stores a significant fraction of the carbon on land. Changes in climate and land use affect total carbon stocks, making it critical to continuously update and revise the best estimates for the region, particularly considering changes in forest dynamics. Forest inventory data cover only a tiny fraction of the Amazon region, and the coverage is not sufficient to ensure reliable data interpolation and validation. This paper presents a new forest above-ground biomass map for the Brazilian Amazon and the associated uncertainty both with a resolution of 250 meters and baseline for the satellite dataset the year of 2016 (i.e., the year of the satellite observation). A significant increase in data availability from forest inventories and remote sensing has enabled progress towards high-resolution biomass estimates. This work uses the largest airborne LiDAR database ever collected in the Amazon, mapping 360,000 km 2 through transects distributed in all vegetation categories in the region. The map uses airborne laser scanning (ALS) data calibrated by field forest inventories that are extrapolated to the region using a machine learning approach with inputs from Synthetic Aperture Radar (PALSAR), vegetation indices obtained from the Moderate-Resolution Imaging Spectroradiometer (MODIS) satellite, and precipitation information from the Tropical Rainfall Measuring Mission (TRMM). A total of 174 field inventories geolocated using a Differential Global Positioning System (DGPS) were used to validate the biomass estimations. The experimental design allowed for a comprehensive representation of several vegetation types, producing an above-ground biomass map varying from a maximum value of 518 Mg ha -1 , a mean of 174 Mg ha -1 , and a standard deviation of 102 Mg ha -1 . This unique dataset enabled a better representation of the regional distribution of the forest biomass and structure, providing further studies and critical information for decision-making concerning forest conservation, planning, carbon emissions estimate, and mechanisms for supporting carbon emissions reductions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Depth-resolved carbon dioxide and methane concentrations in 522 lakes, ponds, and reservoirs worldwide

Lakes, ponds, and reservoirs (hereafter: “lakes”) are important sources of the greenhouse gases carbon dioxide (CO 2 ) and methane (CH 4 ). Emissions of CO 2 and CH 4 from lakes are regulated in part by in-lake processes, including the production and storage of gases in the lower parts of the water column (bottom waters). However, while substantial efforts have been made to improve estimates of greenhouse gas emissions from lakes, limited data on gas concentrations along depth profiles have prevented the incorporation of bottom-water processes in global emission estimates. Here, we present GHG-depths: the largest existing dataset of depth-profile CO 2 and CH 4 measurements worldwide, including 522 lakes across 38 countries and all seven continents. These data include contributions from 45 research teams and 56 published studies, totaling 2558 discrete sampling events. As global change continues to alter biogeochemical cycling in lakes, these data can help improve mechanistic models to better predict greenhouse gas production and emission from lakes worldwide.

Rabaey, Joseph S. [University of Minnesota, Duluth↗
DOE OSTI2025

Nature-based climate solutions can help mitigate the radiative forcing that follows deforestation

Widespread expansion of agriculture and forestry has altered the surface of the Earth, the composition of the atmosphere, and as a result, the climate. Here we quantify the radiative forcing caused by the historical deforestation of an ecoregion in the U.S. Upper Midwest and the adoption of eight nature-based climate solutions. We combined regional forest inventory data with over three decades of remote sensing and in situ data from a replicated land use change experiment. Deforestation of the region caused net global warming (1626 ± 44 µW m -2 ), mainly from the 76 % reduction of ecosystem carbon stocks, but also from the 84 % reduction of the soil methane sink and the 115 % increase in soil nitrous oxide emissions. The associated albedo increase offset 24 % of this greenhouse gas induced warming. For the adoption of nature-based climate solutions, we found that conservation agriculture can provide -39 to -76 ± 31 µW m -2 of climate mitigation over a 100-year time period while short/medium length forestry rotations can provide more at -296 to -881 ± 44 µW m -2 and natural forest regeneration can provide the most at -1555 ± 44 µW m -2 . As the impacts of climate change on nature and society intensify, consideration should be given to the climate mitigation, habitat, and ecosystem services that nature-based climate solutions can provide.

54 ENVIRONMENTAL SCIENCES↗