Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “.NET”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Beam Energy Dependence of Jet-Quenching Effects in Au+Au Collisions at √ s NN = 7.7, 11.5, 14.5, 19.6, 27, 39, and 62.4GeV

Here, we report measurements of the nuclear modification factor, RCP, for charged hadrons as well as identified π +(–) , K +(–) , and p(p¯) for Au+Au collision energies of √ s NN = 7.7, 11.5, 14.5, 19.6, 27, 39, and 62.4 GeV. We observe a clear high-p T net suppression in central collisions at 62.4 GeV for charged hadrons which evolves smoothly to a large net enhancement at lower energies. This trend is driven by the evolution of the pion spectra, but is also very similar for the kaon spectra. While the magnitude of the proton RCP at high p T does depend on collision energy, neither the proton nor the anti-proton RCP at high p T exhibit net suppression at any energy. As a result, a study of how the binary collision scaled high-p T yield evolves with centrality reveals a non-monotonic shape that is consistent with the idea that jet-quenching is increasing faster than the combined phenomena that lead to enhancement.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Influence of chemical composition and crystallographic orientation on the interfacial magnetism in BiFe O 3 / L a 1 - x S r x Mn O 3 superlattices

The emergence of magnetism unique to the interface between the multiferroic BiFeO 3 (BFO) and ferromagnetic La 1-x Sr x MnO 3 (LSMO) offers an opportunity to control magnetism in nanoscale heterostructures with electric fields. Here, we investigate the influence of chemical composition and crystallographic orientation on the interfacial magnetism of BFO/LSMO superlattices. Our results reveal that the induced net magnetic moment in the BFO layers increases monotonically with increasing saturation magnetization of the LSMO layers. For the (100)-BFO/LSMO (x=0.2) superlattice, the induced moment reaches a record high value of ~2.8μ B /Fe. No interfacial magnetization is observed at the (100)-BFO/LSMO interface when LSMO is an antiferromagnet. In contrast to (100)-oriented superlattices, no induced moment is observed in (111)-BFO layers. Our results suggest the interfacial structural reconstruction may not be a sufficient condition for the enhanced net moment in BFO layer. Instead, spin canting induced by interfacial exchange coupling is proposed in the (100)- but not in the (111)-BFO, leading to the large net magnetization at the (100)-oriented interface. Lastly, this work further demonstrates the importance of exchange coupling across heterointerfaces for spin canting in nominally antiferromagnets, providing a pathway to control the magnetic properties of artificial oxide heterostructures.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Small-angle neutron scattering measurements of δ-phase deuteride (hydride) precipitates in Zircaloy 4

Small-angle neutron scattering (SANS) measurements have been performed under ambient conditions to characterize deuteride (hydride) particles in Zircaloy 4, a fuel cladding material used in pressurized light-water nuclear reactors. Hydrogen pickup by the cladding leads to a rim structure in which large circumferential hydride plate-like particles preferentially form on the cooler water-side region of the cladding. Deuterium substitution has been used to increase the coherent response and decrease the incoherent background of the SANS measurements. Four bulk deuterium concentrations were investigated, approximately 100, 400, 500 and 1000 parts per million by weight (w.p.p.m.) deuterium, as well as a zero-deuterium-concentration reference sample. The net SANS response from the deuteride phase was determined at all concentration values after subtraction of the reference SANS response, which effectively subtracted the strong scattering from second-phase particles in as-received Zircaloy. The net SANS response consisted of strong Porod scattering from deuteride particles over the entire measured Q range (0.005–0.4 Å -1 ). The net SANS response was anisotropic at concentrations greater than 100 w.p.p.m. and required elliptical averaging analysis. A significant sample orientation effect on the intensity of the SANS response was observed, due to preferential alignment of deuteride particles. The effect of ex situ applied stress at elevated temperature on deuteride phase dissolution and reprecipitation was investigated; a weak effect was observed with SANS that could not be confirmed by optical microscopy.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Power-to-Gas Systems for Active Load Management at EV Charging Sites with High DER Penetration

Intermittent renewable systems and increasing electric vehicle (EV) penetrations increase load intermittency—and will require expensive distribution system infrastructure upgrades. Power-to-gas (P2G) systems are highly controllable loads that can be modulated to regulate the net load behind the meter. In this work, we present an active load management approach using P2G systems to regulate the net load for an EV charging station with high penetrations of renewable generation. The system also validates the feasibility of the proposed approach using a 750-kW electrolyzer operated with the distribution system in a real-time power-hardware-in-the-loop test. Finally, we evaluate the impact of the size of the P2G system on its ability to regulate the net load.

ADVANCED PROPULSION SYSTEMS,POWER TRANSMISSION AND↗
DOE OSTI2024

Clustering Interval Load with Weather to Create Scenarios of Behind-the-Meter Solar Penetration

Forecasting load at the feeder level has become increasingly challenging with the penetration of behind-the-meter solar, as this self-generation is only visible to the utility as aggregated net-load. This work proposes a methodology for creation of scenarios of solar penetration at the feeder level for use by forecasters to test the robustness of their algorithm to progressively higher penetrations of solar. The algorithm draws on publicly available observations of weather condition (e.g., rainy/cloudy/fair) for use as proxies to sky clearness. These observations are used to mask and weight the interval deviations of similar native usage profiles from which average interval usage is calculated and subsequently added to interval net generation to reconstruct interval total generation. This approach improves the estimate of annual energy generation by 23%; where the net generation signal currently reflects 52% of total annual gener- ation, now 75% is captured. This methodology for creation of forecast testing scenarios is data driven and extensible to service territories which lack information on irradiance measurements and geocoordinates.

solar, load↗
DOE OSTI2023

Optimal Storage Response to Utility Tariff Structures and Potential Use of Capacity Charges

Energy storage is increasingly being deployed in behind-the-meter use cases, partially in response to falling lithium-ion prices and new utility tariff structures. Utilities are grappling with new tariff design in the presence of distributed energy resources (DER), trying to motivate, fairly price the contribution of, and, in some cases, discourage, certain operation of DER. There are opportunities for energy storage under emerging tariff structures, but utility net load management objectives for storage remain unclear. Diverse tariff structures motivate the use of energy storage to provide one or a combination of: energy arbitrage, energy shifting, solar self-consumption, and import shaving. This paper formulates a linear optimization to demonstrate the optimal storage tariff response, examining customer net load metrics under diverse utility tariff structures, such as time-of-use, net metering, feed-in tariffs, zero export tariffs, and demand charges. A key contribution of this paper is the introduction and examination of a capacity charge as mechanism that can both motivate reductions in both peak import, and exports, along with greater load levelling.

behind-the-meter↗
DOE OSTI2019

Estimation of Behind-the-Meter Solar Generation by Integrating Physical with Statistical Models

Accurate estimation of solar photovoltaic (PV) generation is crucial for distribution grid control and optimization. Unfortunately, most of the residential solar PV installations are behind-the-meter. Thus, utilities only have access to the net load readings. This paper presents an unsupervised framework for estimating solar PV generation by disaggregating the net load readings. The proposed framework synergistically combines a physical PV system performance model with a statistical model for load estimation. Specifically, our algorithm iteratively estimates solar PV generation with a physical model and electric load with the Hidden Markov model regression. The proposed algorithm is also capable of estimating the key technical parameters of the solar PV systems. Our proposed method is validated against net load and solar PV generation data gathered from residential customers located in Austin, Texas. The validation results show that our method reduces mean squared error by 44% compared to the state-of-the-art disaggregation algorithm.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Optimal Energy Storage Schedules for Load Leveling and Ramp Rate Control in Distribution Systems

Continued integration of distributed energy resources (DERs) into the grid, such as solar PVs, at a large-scale, contributes into the famous Duck Curve. New DER management algorithms are therefore deemed necessary to alleviate rapid variations within net load profiles of distribution systems. Herein this paper proposes a process to determine the optimal energy storage schedules for leveling the distribution circuit feederhead net load. A series of sensitivity analyses shows how the proposed method can be used to determine the optimal energy storage schedules with different capacities, state of charge requirements, and net load ramp rate limitations.

25 ENERGY STORAGE↗
DOE OSTI2016

A Recursive Hypergraph Bipartitioning Framework for Reducing Bandwidth and Latency Costs Simultaneously

Intelligent partitioning models are commonly used for efficient parallelization of irregular applications on distributed systems. These models usually aim to minimize a single communication cost metric, which is either related to communication volume or message count. However, both volume- and message-related metrics should be taken into account during partitioning for a more efficient parallelization. There are only a few works that consider both of them and they usually address each in separate phases of a two-phase approach. In this work, we propose a recursive hypergraph bipartitioning framework that reduces the total volume and total message count in a single phase. In this framework, the standard hypergraph models, nets of which already capture the bandwidth cost, are augmented with message nets. The message nets encode the message count so that minimizing conventional cutsize captures the minimization of bandwidth and latency costs together. Our model provides a more accurate representation of the overall communication cost by incorporating both the bandwidth and the latency components into the partitioning objective. The use of the widely-adopted successful recursive bipartitioning framework provides the flexibility of using any existing hypergraph partitioner. In conclusion, the experiments on instances from different domains show that our model on the average achieves up to 52 percent reduction in total message count and hence results in 29 percent reduction in parallel running time compared to the model that considers only the total volume.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

A Data-Driven Methodology for Contextual Unit Commitment Using Regression Residuals

Day after day, system operators are faced with the challenge of taking unit commitment (UC) decisions under uncertain net load conditions. The standard operating procedure for taking UC decisions begins by leveraging auxiliary data on covariates (such as the day of the week or latest weather information) to generate a point prediction for net load, which is used in solving a deterministic UC problem. Such an approach, however, is known to deliver a notoriously poor out-of-sample (OOS) performance, as it completely disregards the stochastic nature of net load. While stochastic programming models explicitly represent uncertainty, they mostly do so using a generic set of scenarios that neglect covariate observations, squandering useful auxiliary data that could be harnessed to glean insights into uncertainty. In this article, we discuss a contextual stochastic optimization approach to UC, which effectively exploits covariate observations while explicitly assessing uncertainty so as to boost the OOS performance of UC decisions. The key thrust of our approach is to leverage regression models, along with their empirical residuals, to set up and solve sample average approximation problems. Not only do we prove that our approach satisfies the requisite conditions for asymptotic optimality and consistency laid out in (Kannan et al., 2022), but we also assess its performance on several case studies conducted using real-world data collected in California ISO and New York ISO grids. In conclusion, results show that the proposed approach can significantly improve OOS performance compared to alternative methods proposed in the literature under varying dataset sizes.

Yurdakul, Ogun↗
DOE OSTI2020

Responses of tundra plant community carbon flux to experimental warming, dominant species removal and elevation

1. Rising temperatures can influence ecosystem processes both directly and indirectly, through effects on plant species and communities. An improved understanding of direct versus indirect effects of warming on ecosystem processes is needed for robust predictions of the impacts of climate change on terrestrial ecosystem carbon (C) dynamics. 2. To explore potential direct and indirect effects of warming on C dynamics in arctic tundra heath, we established a warming (open top chambers) and dominant plant species (Empetrum hermaphroditum Hagerup) removal experiment at a high and low elevation site. We measured the individual and interactive effects of warming, dominant species removal and elevation on plant species cover, the normalized difference vegetation index (NDVI), leaf area index (LAI), temperature, soil moisture and instantaneous net ecosystem CO 2 exchange. 3. We hypothesized that ecosystems would be stronger CO 2 sinks at the low elevation site, and that warming and species removal would weaken the CO 2 sink because warming should increase ecosystem respiration (ER) and species removal should reduce gross primary productivity (GPP). Furthermore, we hypothesized that warming and species removal would have the greatest impact on processes at the high elevation where site temperature should be most limiting and dominant species may buffer the overall community to environmental stress more compared to the low elevation site where plants are more likely to compete with the dominant species. 4. The instantaneous CO 2 flux, which reflected a weak CO 2 sink, was similar at both elevations. Neither experimental warming nor dominant species removal significantly changed GPP or instantaneous net ecosystem CO 2 exchange even though species removal significantly reduced ER, NDVI and LAI. 5. Our results show that even the loss of dominant plant species may not result in significant landscape-scale responses of net ecosystem CO 2 exchange to warming. They also show that NDVI and LAI may be limited in their ability to predict changes in GPP in these tundra heaths systems. Our study highlights the need for more detailed vegetation analyses and ground-truthed measurements in order to accurately predict direct and indirect impacts of climatic change on ecosystem C dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

3D Deep Learning Joint Inversion of Active Seismic Full Waveform and Passive Seismic Traveltime Data for Reservoir Imaging and Uncertainty Quantification

Here, we present deep learning (DL) networks for three-dimensional (3D) joint inversion of active seismic full waveform and passive seismic traveltime data to image reservoirs and their properties and quantify imaging uncertainties. Active seismic full-waveform data can provide high-resolution monitoring images but are collected only intermittently because of their high acquisition cost. In contrast, passive seismic data can be gathered at relatively low cost between regular active surveys, although their imaging quality can be compromised by factors such as low signal-to-noise ratios and limited ray coverage of the target. Although these datasets are routinely acquired together at CO 2 storage sites, their combined inversion within a 3D DL framework has not been previously demonstrated. To our knowledge, this is the first study to address this gap, combining the strength of both data types. For efficient data storage and DL training with large 3D seismic datasets, we use a 3D data matrix in which a random number of passive seismic traveltime data are stored as parabolic envelopes using one-hot encoding and a 3D full-waveform data matrix in which multiple shot gathers are summed. Two network architectures are evaluated: a single-encoder U-Net for single-data type inversion and a dual-encoder U-Net for joint inversion of active and passive seismic data. We also evaluate the single-encoder U-Net for joint inversion by concatenating full-waveform data and traveltime data. We propose a systematic approach for selecting an optimal dropout rate that balances regularization during training and Monte Carlo dropout-based uncertainty quantification during prediction by examining the correlation coefficient between standard deviation and prediction error, along with the training misfit, across a range of dropout rates. 3D DL inversion experiments include five different network configurations, with evaluations under ideal, noisy and dropout-enabled conditions. Both model and data uncertainties are assessed, as well as their combined effects. Across all conditions, the networks consistently predict accurate CO 2 saturation models with low prediction errors, such as a structural similarity index of 0.993 and CO 2 difference of 1.1%. Uncertainty estimates show strong spatial correlation with prediction errors, confirming the effectiveness of the proposed dropout selection approach. The results demonstrate that our DL approach, utilizing compact data representations and appropriate uncertainty quantification, yields accurate subsurface images under various inversion conditions and provides valuable insights into the reliability of predictions.

Um, Evan Schankee [Lawrence Berkeley National Labo↗
DOE OSTI2015

Daily environmental conditions determine the competition–facilitation balance for plant water status

Summary Plants compete with their neighbours for a finite set of limiting resources, and this decreases individual plant performance, growth and survival. However, neighbouring plants also affect each other in positive ways. Positive facilitative effects can occur when neighbouring plants ameliorate harsh abiotic conditions (temperature, wind and high irradiation). Thus, when environmental conditions are severe, the importance of facilitation may increase. The co‐occurrence and masking effects of competition and facilitation among neighbouring plants have made it difficult to tease them apart in the past. We planted bur oak acorns ( Q uercus macrocarpa ) into an experimental diversity gradient in a central MN grassland that provided a gradient in plant biomass. We predicted that greater biomass of neighbours would increase both competition and facilitation as measured by impacts on the minimum leaf water potential reached on any given day. Under moderate conditions, competition should predominate, but under hot/dry conditions, facilitation should become more important. We measured temperature, humidity and soil moisture in these plots for two growing seasons, as well as oak seedling leaf water potential across a range of daily conditions. On cool/humid days, plant interactions were dominated by competition for soil water: leaf water potentials of juvenile oaks were lower in plots with greater herbaceous biomass (and higher diversity). Conversely, on hot/dry days, facilitation of the microclimate determined the net effect of plants on their neighbours: leaf water potentials of juvenile oaks were higher in plots with higher herbaceous diversity and biomass. Synthesis . In terms of plant water status, plant interactions among neighbours can flip from net negative (competition) to net positive (facilitation) depending on daily abiotic conditions. The relative importance of both positive and negative interactions for plant water status may affect the overall performance of plants over time.

Wright, Alexandra↗
DOE OSTI2016

Unchanged carbon balance driven by equivalent responses of production and respiration to climate change in a mixed‐grass prairie

Abstract Responses of grassland carbon (C) cycling to climate change and land use remain a major uncertainty in model prediction of future climate. To explore the impacts of global change on ecosystem C fluxes and the consequent changes in C storage, we have conducted a field experiment with warming (+3 °C), altered precipitation (doubled and halved), and annual clipping at the end of growing seasons in a mixed‐grass prairie in Oklahoma, USA , from 2009 to 2013. Results showed that although ecosystem respiration ( ER ) and gross primary production ( GPP ) negatively responded to warming, net ecosystem exchange of CO 2 ( NEE ) did not significantly change under warming. Doubled precipitation stimulated and halved precipitation suppressed ER and GPP equivalently, with the net outcome being unchanged in NEE . These results indicate that warming and altered precipitation do not necessarily have profound impacts on ecosystem C storage. In addition, we found that clipping enhanced NEE due to a stronger positive response of GPP compared to ER , indicating that clipping could potentially be an effective land practice that could increase C storage. No significant interactions between warming, altered precipitation, and clipping were observed. Meanwhile, we found that belowground net primary production ( BNPP ) in general was sensitive to climate change and land use though no significant changes were found in NPP across treatments. Moreover, negative correlations of the ER / GPP ratio with soil temperature and moisture did not differ across treatments, highlighting the roles of abiotic factors in mediating ecosystem C fluxes in this grassland. Importantly, our results suggest that belowground C cycling (e.g., BNPP ) could respond to climate change with no alterations in ecosystem C storage in the same period.

Xu, Xia↗
DOE OSTI2016

Ecosystem fluxes of hydrogen in a mid-latitude forest driven by soil microorganisms and plants

Molecular hydrogen (H 2 ) is an atmospheric trace gas with a large microbe-mediated soil sink, yet cycling of this compound throughout ecosystems is poorly understood. Measurements of the sources and sinks of H 2 in various ecosystems are sparse, resulting in large uncertainties in the global H 2 budget. Constraining the H 2 cycle is critical to understanding its role in atmospheric chemistry and climate. We measured H 2 fluxes at high frequency in a temperate mixed deciduous forest for 15 months using a tower-based flux-gradient approach to determine both the soil-atmosphere and the net ecosystem flux of H 2 . We also found that Harvard Forest is a net H 2 sink (-1.4 ± 1.1 kg H 2 ha -1 ) with soils as the dominant H 2 sink (-2.0 ± 1.0 kg H 2 ha -1 ) and aboveground canopy emissions as the dominant H 2 source (+0.6 ± 0.8 kg H 2 ha -1 ). Aboveground emissions of H 2 were an unexpected and substantial component of the ecosystem H 2 flux, reducing net ecosystem uptake by 30% of that calculated from soil uptake alone. Soil uptake was highly seasonal (July maximum, February minimum), positively correlated with soil temperature and negatively correlated with environmental variables relevant to diffusion into soils (i.e., soil moisture, snow depth, snow density). Soil microbial H 2 uptake was correlated with rhizosphere respiration rates (r = 0.8, P < 0.001), and H 2 metabolism yielded up to 2% of the energy gleaned by microbes from carbon substrate respiration. Here, we elucidate key processes controlling the biosphere–atmosphere exchange of H 2 and raise new questions regarding the role of aboveground biomass as a source of atmospheric H 2 and mechanisms linking soil H 2 and carbon cycling. Our results should be incorporated into modeling efforts to predict the response of the H 2 soil sink to changes in anthropogenic H 2 emissions and shifting soil conditions with climate and land-use change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

The physics and ecology of mining carbon dioxide from the atmosphere by ecosystems

Abstract Reforesting and managing ecosystems have been proposed as ways to mitigate global warming and offset anthropogenic carbon emissions. The intent of our opinion piece is to provide a perspective on how well plants and ecosystems sequester carbon. The ability of individual plants and ecosystems to mine carbon dioxide from the atmosphere, as defined by rates and cumulative amounts, is limited by laws of physics and ecological principles. Consequently, the rates and amount of net carbon uptake are slow and low compared to the rates and amounts of carbon dioxide we release by fossil fuels combustion. Managing ecosystems to sequester carbon can also cause unintended consequences to arise. In this paper, we articulate a series of key take‐home points. First, the potential amount of carbon an ecosystem can assimilate on an annual basis scales with absorbed sunlight, which varies with latitude, leaf area index and available water. Second, efforts to improve photosynthesis will come with the cost of more respiration. Third, the rates and amount of net carbon uptake are relatively slow and low, compared to the rates and amounts and rates of carbon dioxide we release by fossil fuels combustion. Fourth, huge amounts of land area for ecosystems will be needed to be an effective carbon sink to mitigate anthropogenic carbon emissions. Fifth, the effectiveness of using this land as a carbon sink will depend on its ability to remain as a permanent carbon sink. Sixth, converting land to forests or wetlands may have unintended costs that warm the local climate, such as changing albedo, increasing surface roughness or releasing other greenhouse gases. We based our analysis on 1,163 site‐years of direct eddy covariance measurements of gross and net carbon fluxes from 155 sites across the globe.

Baldocchi, Dennis↗
DOE OSTI2019

Intensified inundation shifts a freshwater wetland from a CO 2 sink to a source

Abstract Climate change has altered global precipitation patterns and has led to greater variation in hydrological conditions. Wetlands are important globally for their soil carbon storage. Given that wetland carbon processes are primarily driven by hydrology, a comprehensive understanding of the effect of inundation is needed. In this study, we evaluated the effect of water level (WL) and inundation duration (ID) on carbon dioxide (CO 2 ) fluxes by analysing a 10‐year (2008–2017) eddy covariance dataset from a seasonally inundated freshwater marl prairie in the Everglades National Park. Both gross primary production (GPP) and ecosystem respiration (ER) rates showed declines under inundation. While GPP rates decreased almost linearly as WL and ID increased, ER rates were less responsive to WL increase beyond 30 cm and extended inundation periods. The unequal responses between GPP and ER caused a weaker net ecosystem CO 2 sink strength as inundation intensity increased. Eventually, the ecosystem tended to become a net CO 2 source on a daily basis when either WL exceeded 46 cm or inundation lasted longer than 7 months. Particularly, with an extended period of high‐WLs in 2016 (i.e., WL remained >40 cm for >9 months), the ecosystem became a CO 2 source, as opposed to being a sink or neutral for CO 2 in other years. Furthermore, the extreme inundation in 2016 was followed by a 4‐month postinundation period with lower net ecosystem CO 2 uptake compared to other years. Given that inundation plays a key role in controlling ecosystem CO 2 balance, we suggest that a future with more intensive inundation caused by climate change or water management activities can weaken the CO 2 sink strength of the Everglades freshwater marl prairies and similar wetlands globally, creating a positive feedback to climate change.

Zhao, Junbin↗
DOE OSTI2025

Combining Eddy Covariance Towers, Field Measurements, and the MEMS 2 Ecosystem Model Improves Confidence in the Climate Impacts of Bioenergy With Carbon Capture and Storage

ABSTRACT Carbon dioxide removal technologies such as bioenergy with carbon capture and storage (BECCS) are required if the effects of climate change are to be reversed over the next century. However, BECCS demands extensive land use change that may create positive or negative radiative forcing impacts upstream of the BECCS facility through changes to in situ greenhouse gas fluxes and land surface albedo. When quantifying these upstream climate impacts, even at a single site, different methods can give different estimates. Here we show how three common methods for estimating the net ecosystem carbon balance of bioenergy crops established on former grassland or former cropland can differ in their central estimates and uncertainty. We place these net ecosystem carbon balance forcings in the context of associated radiative forcings from changes to soil N 2 O and CH 4 fluxes, land surface albedo, embedded fossil fuel use, and geologically stored carbon. Results from long term eddy covariance measurements, a soil and plant carbon inventory, and the MEMS 2 process‐based ecosystem model all agree that establishing perennials such as switchgrass or mixed prairie on former cropland resulted in net negative radiative forcing (i.e., global cooling) of −26.5 to −39.6 fW m −2 over 100 years. Establishing these perennials on former grassland sites had similar climate mitigation impacts of −19.3 to −42.5 fW m −2 . However, the largest climate mitigation came from establishing corn for BECCS on former cropland or grassland, with radiative forcings from −38.4 to −50.5 fW m −2 , due to its higher plant productivity and therefore more geologically stored carbon. Our results highlight the strengths and limitations of each method for quantifying the field scale climate impacts of BECCS and show that utilizing multiple methods can increase confidence in the final radiative forcing estimates.

Falvo, Grant [Department of Plant, Soil and Microb↗