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DOE OSTI2024

Technoeconomic Analysis of Kraft Pulp Mill Integration with an Advanced Nuclear Reactor

This study focuses on post-combustion capture and oxy-fuel combustion for the boilers at the mill, as well as steam integration with the nuclear power plant. The primary goal of the research outlined in this report is to design, analyze, and document the integration of industrial-scale HTGR with a reference Kraft Pulp Mill. The purpose is to deliver reliable, cost-effective, and sustainable clean energy alternatives while reducing CO2 emissions. Specifically, this study focuses on 6 different scenarios that include carbon capture equipment and some of them use nuclear power to meet the heat and electricity needs of the reference plant. Also, 2 of these scenarios are created while also producing clean hydrogen through integrated High-Temperature Steam Electrolysis (HTSE). This report offers a detailed techno-economic assessment of different scenarios for a Kraft Pulp Mill, including an analysis of tax credits (section 45V, 45Q, and 48E) provided by the Inflation Reduction Act (IRA) of 2022. The evaluation explores the potential economic benefits and challenges of incorporating different configurations, including nuclear energy, into Kraft Pulp Mill operations, with particular attention to energy efficiency, economic implications, and environmental impact. By assessing both the technical feasibility and economic viability, this analysis aims to identify existing gaps and propose solutions for the successful implementation of nuclear integration. The findings are intended to provide valuable insights for stakeholders considering the adoption of advanced nuclear reactors in the pulp and paper industries.

08 HYDROGEN↗

NASA NTRS2011

Growth of Three Lettuce Cultivars in NASA's HDU PEM During the 2010 DRATS Test

NASA's 2010 Desert Research and Technology Studies (DRATS) of the VEGGIE Food Production System in the Habitat Demonstration Unit (HDU) Pressurized Excursion Module (PEM) was the first operational evaluation of salad crop production technology in a NASA analog test. Rooting media and slow release fertilizers were evaluated for three lettuce cultivars that had shown promise as candidates for a surface based food production system. These tests involved comparing growth, color and quality of the lettuce cultivars grown under VEGGIE LED array (Orbitec, Madison, WI) or Biomass Production System for Education ((BSEe), Orbitec, Madison, WI) compact fluorescent lamps using a gravity feed water delivery system. Mission relevant conditions of CO2, temperature and RH were maintained using controlled environment chambers (EGC, Chagrin Falls, OH). Growth data was obtained for the two red leaf lettuce cultivars, Outredgeous and Firecracker, and the green Bibb lettuce cultivar, Flandria. Growth and quality was evaluated using different concentrations (7.5 g/L and 15 g/L) of commercial slow release fertilizer (Osmocote Plus 15-9-12, Scotts, Maryville, OH) and Nutricote 18-6-8 (Florikan, Sarasota, FL) in either a peat/vermiculite media (sunshine LP5 MiX, Sungro, Bellview, WA) or calcined montmorillonite clay [(arcillite,)Turface Proleague, Profile LLC, Buffalo Grove, IL]. The commercial peat/vermiculite mix generally resulted in larger plants than those grown in arcillite. Increasing the concentration of Osmocote from 7.5 to 15 g/L increased the height, dry mass, and leaf area of lettuce cultivars. In contrast, there was a decrease in growth parameters when concentration of Nutricote was increased from 7.5 to 15 g/L. The best growth was obtained with the 7.5 g/L Nutricote using a commercial peat/vermiculite mixture. This media was used for field testing VEGGIE plant system in the 2010 DRAT test. The VEGGIE nutrient delivery system worked well, was able to be maintained by multiple operators with a minimum of training, and supported excellent lettuce growth for the duration of the 14-day test. The operational DRAT field testing in the HDU identified light quality issues related to morphology and pigment development that will need to be addressed through additional testing. Feedback from the crew, ground support personnel, and human factors leads was uniformly positive on the psychological value of having the crop production system in the pressurized excursion module. Data are being used to design a plant atrium with LED lighting to evaluate salad crop growth during NASA's 2011 DRATS test.

Stutte, Gary W.↗

DOE OSTI2024

Miscanthus: An Environmental Choice for Marginal Lands

Miscanthus x giganteus, or Giant Miscanthus, is a tall, perennial grass originally from Asia. It is considered a sterile hybrid that has been bred to not produce viable seeds. Instead, rhizomes are planted to establish the crop. Here, the rhizome is an underground modified stem mass that puts out shoots and roots supporting new growth each year. This perennial crop takes two to three years to reach maturity, but established stands can reach upwards of 12 ft. tall with a very thick canopy (Pyter, 2007). Miscanthus has shown potential for high dry matter yields compared to other biomass crops, which could in turn lead to more efficient land use especially when applied to a bioenergy and bioproduct supply chain. In one study, switchgrass (Panicum virgatum) yielded 10.3 Mg/ha of biomass on average, while miscanthus yielded 22.4 Mg/ha (Heaton et al., 2004). Additionally, miscanthus production has been associated with many environmental benefits, including benefits to water quality, nutrient load removal, soil stabilization, and soil health (Bhardwaj et al., 2011; Hussain et al., 2019). Many of the possible practical and environmental benefits that are associated with miscanthus production may be attractive to stakeholders who are interested in alternative land use options, particularly in areas considered to be marginal in productivity.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Understanding Multilevel Selection May Facilitate Management of Arbuscular Mycorrhizae in Sustainable Agroecosystems

Studies in natural ecosystems show that adaptation of arbuscular mycorrhizal (AM) fungi and other microbial plant symbionts to local environmental conditions can help ameliorate stress and optimize plant fitness. This local adaptation arises from the process of multilevel selection, which is the simultaneous selection of a hierarchy of groups. Studies of multilevel selection in natural ecosystems may inform the creation of sustainable agroecosystems through developing strategies to effectively manage crop microbiomes including AM symbioses. Field experiments show that the species composition of AM fungal communities varies across environmental gradients, and that the biomass of AM fungi and their benefits for plants generally diminish when fertilization and irrigation eliminate nutrient and water limitations. Furthermore, pathogen protection by mycorrhizas is only important in environments prone to plant damage due to pathogens. Consequently, certain agricultural practices may inadvertently select for less beneficial root symbioses because the conventional agricultural practices of fertilization, irrigation, and use of pesticides can make these symbioses superfluous for optimizing crop performance. The purpose of this paper is to examine how multilevel selection influences the flow of matter, energy, and genetic information through mycorrhizal microbiomes in natural and agricultural ecosystems, and propose testable hypotheses about how mycorrhizae may be actively managed to increase agricultural sustainability.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2017

Description and Evaluation of the Multiscale Online Nonhydrostatic AtmospheRe CHemistry Model (NMMB-MONARCH) Version 1.0: Gas-Phase Chemistry at Global Scale

This paper presents a comprehensive description and benchmark evaluation of the tropospheric gas-phase chemistry component of the Multiscale Online Nonhydrostatic AtmospheRe CHemistry model (NMMBMONARCH), formerly known as NMMB/BSC-CTM, that can be run on both regional and global domains. Here, we provide an extensive evaluation of a global annual cycle simulation using a variety of background surface stations (EMEP, WDCGG and CASTNET), ozonesondes (WOUDC, CMD and SHADOZ), aircraft data (MOZAIC and several campaigns), and satellite observations (SCIAMACHY and MOPITT).We also include an extensive discussion of our results in comparison to other state-of-the-art models. We note that in this study, we omitted aerosol processes and some natural emissions (lightning and volcano emissions). The model shows a realistic oxidative capacity across the globe. The seasonal cycle for CO is fairly well represented at different locations (correlations around 0.3-0.7 in surface concentrations), although concentrations are underestimated in spring and winter in the Northern Hemisphere, and are overestimated throughout the year at 800 and 500 hPa in the Southern Hemisphere. Nitrogen species are well represented in almost all locations, particularly NO2 in Europe (root mean square error - RMSE - below 5 ppb). The modeled vertical distributions of NOx and HNO3 are in excellent agreement with the observed values and the spatial and seasonal trends of tropospheric NO2 columns correspond well to observations from SCIAMACHY, capturing the highly polluted areas and the biomass burning cycle throughout the year. Over Asia, the model underestimates NOx from March to August, probably due to an underestimation of NOx emissions in the region. Overall, the comparison of the modeled CO and NO2 with MOPITT and SCIAMACHY observations emphasizes the need for more accurate emission rates from anthropogenic and biomass burning sources (i.e., specification of temporal variability).

atmospheric chemistry↗

DOE OSTI2020

A Performance Comparison of Low-Cost Near-Infrared (NIR) Spectrometers to a Conventional Laboratory Spectrometer for Rapid Biomass Compositional Analysis

The performance of a conventional laboratory near-infrared (NIR) spectrometer and two NIR spectrometer prototypes (a Texas Instruments NIRSCAN Nano evaluation model (EVM) and an InnoSpectra NIR-M-R2 spectrometer) are compared by collecting reflectance spectra of 270 well-characterized herbaceous biomass samples, building calibration models using the partial least squares (PLS-2) algorithm to predict five constituents of the samples from the reflectance spectra, and comparing the resulting model statistics. The prediction models developed using spectra from the Foss XDS spectrometer were slightly better than the prediction models developed using spectra from either the TI NIRSCAN Nano EVM and the InnoSpectra NIR-M-R2 as measured by the root mean square error (RMSECV) and the correlation coefficient (R 2 _cv) for “leave-one-out” cross-validation (CV). The models built from the two prototype units were not statistically significantly different from each other (p = 0.05). The Foss spectrometer has a larger wavelength range (400–2500 nm) compared with the two prototypes (900–1700 nm). When the spectra from the Foss XDS spectrometer were truncated so their wavelength range matched the wavelength range of the two prototype units, the resulting model was not statistically significantly different from the models from either prototype.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

Implementing Spatio-Temporal 3D-Convolution Neural Networks and UAV Time Series Imagery to Better Predict Lodging Damage in Sorghum

Unmanned aerial vehicle (UAV)-based remote sensing is gaining momentum in a variety of agricultural and environmental applications. Very-high-resolution remote sensing image sets collected repeatedly throughout a crop growing season are becoming increasingly common. Analytical methods able to learn from both spatial and time dimensions of the data may allow for an improved estimation of crop traits, as well as the effects of genetics and the environment on these traits. Multispectral and geometric time series imagery was collected by UAV on 11 dates, along with ground-truth data, in a field trial of 866 genetically diverse biomass sorghum accessions. We compared the performance of Convolution Neural Network (CNN) architectures that used image data from single dates (two spatial dimensions, 2D) versus multiple dates (two spatial dimensions + temporal dimension, 3D) to estimate lodging detection and severity. Lodging was detected with 3D-CNN analysis of time series imagery with 0.88 accuracy, 0.92 Precision, and 0.83 Recall. This outperformed the best 2D-CNN on a single date with 0.85 accuracy, 0.84 Precision, and 0.76 Recall. The variation in lodging severity was estimated by the best 3D-CNN analysis with 9.4% mean absolute error (MAE), 11.9% root mean square error (RMSE), and goodness-of-fit (R2) of 0.76. This was a significant improvement over the best 2D-CNN analysis with 11.84% MAE, 14.91% RMSE, and 0.63 R2. The success of the improved 3D-CNN analysis approach depended on the inclusion of “before and after” data, i.e., images collected on dates before and after the lodging event. The integration of geometric and spectral features with 3D-CNN architecture was also key to the improved assessment of lodging severity, which is an important and difficult-to-assess phenomenon in bioenergy feedstocks such as biomass sorghum. This demonstrates that spatio-temporal CNN architectures based on UAV time series imagery have significant potential to enhance plant phenotyping capabilities in crop breeding and Precision agriculture applications.

3D-convolution neural networks↗

NASA NTRSDate not supplied

Impact of Space Radiation on Plants: from Arabidopsis thaliana to Crops

One of the major concerns for long-term exploration missions beyond the Earth’s magnetosphere is radiation risk, primarily from solar particle events (SPE) and galactic cosmic rays (GCR). With the goal of manned Mars exploration, the production of fresh food during long-duration space missions provides critical nutritional supplementation and may also benefit astronauts’ behavioral health. However, the effects of space radiation on plants and plant propagules have not been sufficiently investigated and characterized. In this study, we evaluated the effect of simulated GCR (using dry seeds) or SPE (using hydrated seeds) on seeds of Arabidopsis, Mizuna mustard, ‘Outredgeous’ red romaine lettuce, and ‘Red Robin’ dwarf tomato. Seeds were exposed to various doses of simulated space radiation scenarios, either acutely or at a low dose rate (LDR), using the NASA Space Radiation Laboratory (NSRL) facility at Brookhaven National Lab (BNL). Exposure to simulated GCR or SPE at the levels tested had no significant impact on the germination rate in Arabidopsis and crop seeds; however, GCR reduced the viability of lettuce and tomato seeds. Overall, the morphological changes of the seedlings cultured from irradiated seeds were dose- and ion quality- dependent, with heavier ions causing more severe damage. These changes ranged from cotyledon deformation, shortened root length, smaller seedling size, and other signs of stress, depending on the seed types. Both 40 and 80 cGy (LDR) exposures of GCR or SPE significantly affected tomato early seedling development, delayed tomato fruiting, and reduced the total yield of tomato. Altered nutritional values were also found in edible biomass, especially for the GCR 80 cGy (LDR) groups. For both GCR and SPE, 40 cGy showed some effects, but to a much lesser extent compared with 80 cGy, which can be considered as the “maximum permissible exposure” for the seed types we evaluated in this study. The impact of space radiation on seeds potentially affects the ability of plants to adapt to other environmental stresses (e.g. microgravity, water stress, and hardware constraints) as well as susceptibility to plant diseases, which need to be furtherly investigated. This research is funded by NASA’s Human Research Program.

J T Richards↗

NASA NTRSDate not supplied

Impact of Space Radiation on Plant Seeds: from Arabidopsis thaliana to Crops

J T Richards↗

NASA NTRSDate not supplied

Impact of Space Radiation on Plant Seeds: from Arabidopsis thaliana to Crops

One of the major concerns for long-term exploration missions beyond the Earth’s magnetosphere is radiation risk, primarily from solar particle events (SPE) and galactic cosmic rays (GCR). With the goal of manned Mars exploration, the production of fresh food during long-duration space missions provides critical nutritional supplementation and may also benefit astronauts’ behavioral health. However, the effects of space radiation on plants and plant propagules have not been sufficiently investigated and characterized. This is the final report of our project to summarize the findings of the effect of space radiation exposure on plant seeds from morphometrics, nutritional values, to molecular machenisms. In this study, we evaluated the effect of simulated GCR (using dry seeds) or SPE (using hydrated seeds) on seeds of Arabidopsis, Mizuna mustard, ‘Outredgeous’ red romaine lettuce, and ‘Red Robin’ dwarf tomato. Seeds were exposed to various doses of simulated space radiation scenarios, either acutely or at a low dose rate (LDR), using the NASA Space Radiation Laboratory (NSRL) facility at Brookhaven National Lab (BNL). Exposure to simulated GCR or SPE at the levels tested had no significant impact on the germination rate in Arabidopsis and crop seeds; however, GCR reduced the viability of lettuce and tomato seeds. Overall, the morphological changes of the seedlings cultured from irradiated seeds were dose- and ion quality- dependent, with heavier ions causing more severe damage. These changes ranged from cotyledon deformation, shortened root length, smaller seedling size, and other signs of stress, depending on the seed types. Both 40 and 80 cGy (LDR) exposures of GCR or SPE significantly affected tomato early seedling development, delayed tomato fruiting, and reduced the total yield of tomato. Altered nutritional values were also found in edible biomass, especially for the GCR 80 cGy (LDR) groups. Underlying mechanisms were furtherly evaluated using transcriptomic analysis. For both GCR and SPE, 40 cGy showed some effects, but to a much lesser extent compared with 80 cGy, which can be considered as the “maximum permissible exposure” for the seed types we evaluated in this study. The impact of space radiation on seeds potentially affects the ability of plants to adapt to other environmental stresses (e.g. microgravity, water stress, and hardware constraints) as well as susceptibility to plant diseases, which need to be furtherly investigated. This research is funded by NASA’s Human Research Program.

J T Richards↗

NASA NTRSDate not supplied

Impact of Space Radiation on Plant Seeds: from Arabidopsis thaliana to Crops

One of the major concerns for long-term exploration missions beyond the Earth’s magnetosphere is radiation risk, primarily from solar particle events (SPE) and galactic cosmic rays (GCR). With the goal of manned Mars exploration, the production of fresh food during long-duration space missions provides critical nutritional supplementation and may also benefit astronauts’ behavioral health. However, the effects of space radiation on plants and plant propagules have not been sufficiently investigated and characterized. This is the final report of our project to summarize the findings of the effect of space radiation exposure on plant seeds from morphometrics, nutritiaonal values, to molecular machenisms. In this study, we evaluated the effect of simulated GCR (using dry seeds) or SPE (using hydrated seeds) on seeds of Arabidopsis, Mizuna mustard, ‘Outredgeous’ red romaine lettuce, and ‘Red Robin’ dwarf tomato. Seeds were exposed to various doses of simulated space radiation scenarios, either acutely or at a low dose rate (LDR), using the NASA Space Radiation Laboratory (NSRL) facility at Brookhaven National Lab (BNL). Exposure to simulated GCR or SPE at the levels tested had no significant impact on the germination rate in Arabidopsis and crop seeds; however, GCR reduced the viability of lettuce and tomato seeds. Overall, the morphological changes of the seedlings cultured from irradiated seeds were dose- and ion quality- dependent, with heavier ions causing more severe damage. These changes ranged from cotyledon deformation, shortened root length, smaller seedling size, and other signs of stress, depending on the seed types. Both 40 and 80 cGy (LDR) exposures of GCR or SPE significantly affected tomato early seedling development, delayed tomato fruiting, and reduced the total yield of tomato. Altered nutritional values were also found in edible biomass, especially for the GCR 80 cGy (LDR) groups. Underlying mechanisms were furtherly evaluated using transcriptomic analysis. For both GCR and SPE, 40 cGy showed some effects, but to a much lesser extent compared with 80 cGy, which can be considered as the “maximum permissible exposure” for the seed types we evaluated in this study. The impact of space radiation on seeds potentially affects the ability of plants to adapt to other environmental stresses (e.g. microgravity, water stress, and hardware constraints) as well as susceptibility to plant diseases, which need to be furtherly investigated. This research is funded by NASA’s Human Research Program.

J.T. Richards↗

DOE OSTI2021

BETO 2021 Peer Review: 2.1.0.100 - Biochemical Platform Analysis

The objective of this project is to perform techno-economic analysis (TEA) to guide Biochemical Platform efforts, utilizing models for purposes of setting future R&D targets and tracking performance progress against those targets. Outcomes of our work are leveraged by BETO to guide program plans, as well as by other NREL/partner projects to quantify the impact of research on key technology barriers and to prioritize future efforts. This project provides high impact and relevance through establishing “bottom-up” TEA models as a basis for understanding the technical feasibility to meet “top-down” BETO cost targets. By providing a framework to translate technical performance to cost reductions in a biorefinery, our TEA models may be leveraged to maximize the efficiency of research funding towards the most economically impactful priorities, ultimately in support of BETO’s 2030 fuel cost targets below $2.5/GGE. In order to mitigate a key risk/challenge to this project in overly-constraining our analyses to a singular technology focus or TEA metric, our approach continuously re-assesses opportunities for better optimization and alternative technology pathway options, while maintaining close interaction with other BETO analysis partners. We have made numerous recent accomplishments rooted around identifying and working with the researchers to solve key technical and TEA/LCA challenges, reflected through notable improvements in State-of-Technology (SOT) updates over prior benchmarks.

biochemical↗

NASA NTRS1994

Using optical-microwave synergy for estimating surface energy fluxes over semi-arid rangeland

First results of the Walnut Gulch '92 (Arizona, U.S.) experiment concerning the combined use of radar backscattering (ERS-1) and thermal infrared (LANDSAT TM (Thematic Mapper)) data to estimate surface sensible heat flux are reported. The first step investigates the potential use of ERS-1 SAR (Synthetic Aperture Radar) images for surface soil moisture monitoring of the watershed using five calibrated images acquired during the year 1992 (dry to wet conditions). Results show that despite the typical low level of biomass of semi arid rangeland, an attenuation of the soil backscatter (up to 2 dB) can occur during the rainy season mainly due to the vegetation characteristics. A statistical relationship is then used to retrieve the volumetric surface soil moisture from ERS-1 backscattering (sensitivity of 0.23 dB/% moisture) with a resulting root mean square error of 1.3% of soil moisture. In a second step a semi empirical approach based on energy balance relates soil temperatures to this estimated surface soil moisture. Vegetation temperature is then deduced from soil temperatures and LANDSAT TM composite temperature in order to estimate sensible heat flux according to a two layer type model providing an RMSE of 29 W/sq m.

Troufleau, D.↗

NASA NTRS2020

Modelling climate change impacts on maize yields under low nitrogen input conditions in sub‐Saharan Africa

Smallholder farmers in sub‐Saharan Africa (SSA) currently grow rainfed maize with limited inputs including fertilizer. Climate change may exacerbate current production constraints. Crop models can help quantify the potential impact of climate change on maize yields, but a comprehensive multimodel assessment of simulation accuracy and uncertainty in these low‐input systems is currently lacking. We evaluated the impact of varying [CO2], temperature and rainfall conditions on maize yield, for different nitrogen (N) inputs (0, 80, 160 kg N/ha) for five environments in SSA, including cool subhumid Ethiopia, cool semi‐arid Rwanda, hot subhumid Ghana and hot semi‐arid Mali and Benin using an ensemble of 25 maize models. Models were calibrated with measured grain yield, plant biomass, plant N, leaf area index, harvest index and in‐season soil water content from 2‐year experiments in each country to assess their ability to simulate observed yield. Simulated responses to climate change factors were explored and compared between models. Calibrated models reproduced measured grain yield variations well with average relative root mean square error of 26%, although uncertainty in model prediction was substantial (CV = 28%). Model ensembles gave greater accuracy than any model taken at random. Nitrogen fertilization controlled the response to variations in [CO2], temperature and rainfall. Without N fertilizer input, maize (i) benefited less from an increase in atmospheric [CO2], (ii) was less affected by higher temperature or decreasing rainfall and (iii) was more affected by increased rainfall because N leaching was more critical. The model inter-comparison revealed that simulation of daily soil N supply and N leaching plays a crucial role in simulating climate change impacts for low-input systems. Climate change and N input interactions have strong implications for the design of robust adaptation practices across SSA, because the impact of climate change will be modified if farmers intensify maize production with more mineral fertilizer.

Crop simulation model↗

NASA NTRS1997

Density and composition of microorganisms during long-term (418 day) growth of potato using biologically reclaimed nutrients from inedible plant biomass

A study evaluating alternative methods for long term operation of biomass production systems was recently completed at the Kennedy Space Center (KSC). The 418-day study evaluated repeated batch versus mixed-aged production of potato grown on either standard 1/2-strength Hoagland's nutrient solution or solutions including nutrients recycled from inedible plant material. The long term effects of closure and recycling on microbial dynamics were evaluated by monitoring the microbial communities associated with various habitats within the plant growth system (i.e., plant roots, nutrient solution, biofilms within the hydroponic systems, atmosphere, and atmospheric condensate). Plate count methods were used to enumerate and characterize microorganisms. Microscopic staining methods were used to estunate total cell densities. The primary finding was that the density and composition of microbial communities associated with controlled environmental plant growth systems are stable during long term operation. Continuous production resulted in slightly greater stability. Nutrient recycling, despite the addition of soluble organic material from the waste processing system, did not significantly increase microbial density in any of the habitats.

NASA Center KSC↗

NASA NTRSDate not supplied

Validation of Remotely Sensed and Modeled Soil Moisture at Forested and Unforested Sites

Soil moisture is an important driver for forest ecosystems, influencing fire occurrence and extent, insect and pathogen impacts, and tree growth, which creates a need for regular, globally extensive soil moisture information that only satellite-based sensors or models can achieve. However, the reliability of soil moisture measurements in forests is not well understood due to a lack of suitable validation sites (especially relative to unforested ecosystems) and interference caused by high vegetation water content on remotely sensed measurements; although recent studies have started to address this gap [1], [2], [3], [4]. Here we validate the performance of multiyear remotely sensed (SMAP/Sentinel), remotely sensed data assimilation modelled (SMAP-L4), and modelled (NLDAS) surface and root zone (0-1 m) soil moisture datasets with data from in-situ sensors at 39 National Ecological Observatory Network (NEON) sites throughout the contiguous US. Due to differences in spatial resolution, NEON soil moisture (~0.2 km measurement zone) correlations were expected to be stronger with the SMAP/Sentinel product (3 km resolution) than with coarser resolution SMAP-L4 (9 km resolution) or NLDAS products (13 km resolution). However, given the sensitivity of satellite measurements to vegetation water content we expected a deterioration in the correlations based on remotely sensed measurements (SMAP/Sentinel and SMAP-L4) as aboveground biomass increased, whereas the model-based data (NLDAS) was expected to be largely insensitive to vegetation type. We recognize that the SMAP/Sentinel product was developed for unforested regions, therefore our application is outside its primary use case. Soil moisture is measured at up to 8 depths in five soil plots spaced up to 40 m apart at each NEON terrestrial site. Correlation parameters were calculated for the three remotely sensed and modelled data products relative to in-situ measurement following Entekhabi et al. [5]. The datasets comprised 94 (SMAP-L4), 28 (SMAP/Sentinel), and 106 (NLDAS) sites-years for surface soils and 13 (SMAP-L4) and 14 (NLDAS) site-years for the root zone. At unforested sites, the performance of the three remotely sensed and modelled data products was similar for surface soils (Table 1). For example, unbiased RMSD (ubRMSD), which SMAP uses as its primary performance metric [6], ranged from 0.05 to 0.06 m3 m-3 (Table 1), indicating the ability of all three products to track changes in soil moisture over time. The performance of the three products deteriorated at forested sites, however, while the difference in performance was modest for SMAP-L4 and NLDAS, the deterioration in SMAP/Sentinel performance was substantial. For instance, SMAP/Sentinel ubRMSD increased from 0.06 to 0.11 m3 m-3 and absolute mean difference (Abs MD; which includes measurement bias and spatial representativeness errors) increased from 0.06 to 0.16 m3 m-3, indicating both a reduction in ability to track temporal changes and absolute amounts of soil moisture in forest ecosystems. SMAP-L4 and NLDAS had lower unbiased RMSD for root zone (0-1 m) than surface soils at both forested and unforested sites (Tables 1 and 2; SMAP/Sentinel does not produce a root zone measurement). However, in most cases the correlation coefficient (r) was lower for the root zone than surface soils, suggesting the lower unbiased RMSD may be attributed to greater temporal stability of soil moisture in the root zone rather than improved data product performance. Mean difference and absolute mean difference, which encompass measurement bias and spatial representativeness errors, were greater for root zone than surface soils at unforested sites for both data products, but the opposite was generally true at forested sites. As with surface soils, there was relatively little change in the performance of SMAP-L4 and NLDAS between the unforested and forested sites. In summary, all three data products were able to adequately represent soil moisture at unforested sites, at least when aggregating across sites. However, while the performance of all three products deteriorated at forested sites, SMAP-L4 and NLDAS maintained sufficient performance to remain suitable for some use cases (ubRMSD <0.06 m3 m-3 and RMSD <0.13 m3 m-3). In contrast, the relatively poorer performance of the SMAP/Sentinel product at forested sites seems insufficient for most use cases (ubRMSD >0.1 m3 m-3 and RMSD >0.2 m3 m-3). We attribute the large reduction in the performance of the SMAP/Sentinel product in forests to its use of C-band wavelengths, which are particularly sensitive to vegetation interference, and apparently outweighed any gains provided by its higher spatial resolution. A combined SMAP/NISAR soil moisture product may provide improved performance relative to SMAP/Sentinel due to NISAR’s use of L-band wavelengths, which are less sensitive to vegetation (NISAR is scheduled for launch in early 2024).

Edward Ayres↗

DOE OSTI2024

Depth and microtopography influence microbial biogeochemical processes in a forested peatland

Background and aims: Peat-accumulating wetlands have undulating surfaces of raised areas (hummocks) and depressions (hollows). Hummock-hollow microtopography in relation to the water table influences the distribution of plant species, root density, and microbial community composition, which could in turn alter carbon (C) and nitrogen (N) cycling within peatlands. We used paired hummock and hollow cores from a boreal, forested peatland to assess how microtopography influences peatland microbial function and, in turn, ecosystem C and N cycling. Methods: The peat was analyzed for microbial biomass and potential enzyme activity in 10 cm depth increments relative to the water table, resulting in two increments for hollows and three for hummocks, which has a raised increment above the water table. Results: Across hummocks and hollows, microbial C and N and fungal biomass generally decreased with depth from the peat surface. In contrast, potential enzyme activity often increased with depth, but this varied within enzyme functional groups according to topography, depth, or both. The potential enzyme activity of C-N degrading peptidases, for example, differed across the five topography × depth increments with the lowest rate in the aerated hummocks. Hummocks compose approximately 66% of the land area at our study site and would therefore underestimate C turnover by an average of 25% if solely used to extrapolate patterns across a forested bog. Conclusion: In conclusion, our results suggest that asynchrony in C and N cycling across the undulating surface of forested peatlands impacts our ability to accurately predict biogeochemical cycling across this important ecosystem.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1984

Alterations in internal partitioning of carbon in soybean plants in response to nitrogen stress

Alterations in internal partitioning of carbon were evaluated in plants exposed to limited nitrogen supply. Vegetative, nonnodulated soybean plants (Glycine max (L.) Merrill, 'Ransom') were grown for 21 days with 1.0 mM NO3- and then exposed to solutions containing 1.0, 0.1, or 0.0 mM NO3- for a 25-day treatment period. In nitrogen-limited plants, there were decreases in emergence of new leaves and in the expansion rate and final area at full expansion of individual leaves. As indicated by alterations in accumulation of dry weight, a larger proportion of available carbon in the plant was partitioned to the roots with decreased availability of nitrogen. Partitioning of reduced nitrogen to the root also was increased and, in plants devoid of an external supply, considerable redistribution of reduced nitrogen from leaves to the root occurred. The general decrease in growth potential and sink strength for nutrients in leaves of nitrogen-limited plants suggested that factors other than simply availability of nitrogen likely were involved in the restriction of growth in the leaf canopy and the associated increase in carbon allocation to the roots.

Soybeans/growth & development/metabolism↗