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At least 1,351 records · Page 75

Enabling off-highway diesel engine downsizing and performance improvement using electrically assisted turbocharging

Internal combustion engine (ICE) downsizing through various turbocharging configurations is generally known by the powertrain design community as an effective means to reduce frictional losses, increase waste heat recovery, and improve fuel efficiency while increasing engine power density. However, often is the case that turbocharging strategies, including variable geometry turbochargers, and regulated two-stage turbochargers, incur the performance tradeoff between transient response and fuel economy (pumping losses) at high engine speeds. For off-highway vehicles having particularly transient and high-powered duty cycles, efforts to improve this tradeoff and increase operational flexibility have turned to evaluating various electrified air system architectures. In this study, a 4.5 L diesel-ICE configured with an electrically driven compressor (eBooster ® ) is placed in series with a conventional turbocharger and integrated into a 48 V mild-hybrid powertrain architecture. The objective of this powertrain configuration is to enable engine downsizing by 34%, replacing the current 6.8 L ICE platform with the hybridized 4.5 L ICE concept. The commercial 1-D simulation software GT-SUITE is used for powertrain system development and system optimization. Development and validation of the GT-SUITE model and air system controls is concurrently supported through experimental data collection. The simulation model development includes using machine learning methods for optimizing exhaust gas dilution, injection timing, and eBooster ® power to improve steady-state and transient brake-specific fuel consumption while minimizing criteria pollutant emissions. It was found that total specific fluid consumption over the standardized non-road transient engine duty cycle could be reduced by 18% over the current 6.8 L engine by using an optimized eBoosted 4.5 L engine. The hybridized 4.5 L engine concept concurrently showed sufficient transient response capability and nearly an order of magnitude reduction in duty cycle total soot production.

25 ENERGY STORAGE↗

Optimization of the deep neural network parameters for generating homogenized fuel assembly data for nodal codes

Homogenized fuel assembly (FA) data is a typical input data for nodal codes. Generating that data, however, could be time-consuming. One of promising ways to mitigate the computational burden of generating macroscopic cross-sections is to use trained artificial neural network (ANN) models for predicting nuclear data. However, there is a challenge to make the model support variable FA geometry. In this work, two most common types of FA were combined in one ANN model. Since there could be multiple ways of converting 2-dimensional FA data into 1-dimensional input vector for ANN, three different approaches of data flattening were evaluated. The input parameters included each fuel pin enrichment, fuel temperature, moderator temperature and boron concentration. The output parameters were 2-group macroscopic cross-sections (XS) and pin power distribution (HFF). A fully connected deep neural network (DNN) model was trained and tested using pre-generated data obtained with lattice physics code STREAM. The results of this study showed no statistically significant difference in the accuracy of XS and HFF generation for all 3 tested input vector orders. This means that fully connected DNN for XS generation demonstrated input sequence invariance. Results of comparing predicted XS data with reference solutions were found sufficiently close considering the reduction of computation time offered by ANN. Mean relative difference (MRD) for all output XS parameters was found below 0.7%, while HFF MRD was found higher compared to XS values, in some cases slightly exceeding 1%, mostly near guide tube locations. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Detecting Arsenic Contamination Using Satellite Imagery and Machine Learning

Arsenic, a potent carcinogen and neurotoxin, affects over 200 million people globally. Current detection methods are laborious, expensive, and unscalable, being difficult to implement in developing regions and during crises such as COVID-19. This study attempts to determine if a relationship exists between soil’s hyperspectral data and arsenic concentration using NASA’s Hyperion satellite. It is the first arsenic study to use satellite-based hyperspectral data and apply a classification approach. Four regression machine learning models are tested to determine this correlation in soil with bare land cover. Raw data are converted to reflectance, problematic atmospheric influences are removed, characteristic wavelengths are selected, and four noise reduction algorithms are tested. The combination of data augmentation, Genetic Algorithm, Second Derivative Transformation, and Random Forest regression (R 2 =0.840 and normalized root mean squared error (re-scaled to [0,1]) = 0.122) shows strong correlation, performing better than past models despite using noisier satellite data (versus lab-processed samples). Three binary classification machine learning models are then applied to identify high-risk shrub-covered regions in ten U.S. states, achieving strong accuracy (=0.693) and F1-score (=0.728). Overall, these results suggest that such a methodology is practical and can provide a sustainable alternative to arsenic contamination detection.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Cost reductions through earth resource satellites in developed countries

Data from detailed studies on the possible economic impact of the use of remote sensing technology in industry and agriculture are presented and analyzed. The utility of satellite surveillance in reduction of crop production forecast error, recognition and monitoring of crop diseases and insect infestations, and range management is evaluated. Application of satellite maps to facilitate land resource decisions, mineral exploration, geological studies, and water resource inventories is considered, as is the usefulness of early storm warning in the reduction of property damage. The cost of remote sensing is compared to that of conventional methods whenever possible.

Schweickart, R. L.↗

Environmental degradation of 316 stainless steel in high temperature low cycle fatigue

Procedures based on modification of the conventional Strainrange Partitioning method are proposed to characterize the time-dependent degradation of engineering alloys in high-temperature, low-cycle fatigue. Creep-fatigue experiments were conducted in air using different waveforms of loading on 316 stainless steel at 816 C (1500 F) to determine the effect of exposure time on cyclic life. Reductions in the partitioned cyclic lives were observed with an increase in the time of exposure (or with the corresponding decrease in the steady-state creep rate) for all the waveforms involving creep strain. Excellent correlations of the experimental data were obtained by modifying the Conventional Strainrange Partitioning life relationships involving creep strain using a power-law term of either: (1) time of exposure, or (2) steady-state creep rate of the creep-fatigue test. Environmental degradation due to oxidation, material degradation due to the precipitation of carbides along the grain boundaries and detrimental deformation modes associated with the prolonged periods of creep were observed to be the main mechanisms responsible for life reductions at long exposure times.

Kalluri, Sreeramesh↗

An aerothermodynamic study of slender conical vehicles

A numerical study was performed to assess the applicability of some current techniques which can be used for aerothermal predictions over slender spherically blunted cones. Predictions using a viscous-shock-layer method and several engineering approaches were compared with experimental results from flight and ground-based tests, with each other, and with other detailed results. Good agreement was obtained in comparisons with laminar and turbulent heating data from the Reentry F flight vehicle and with the wind-tunnel data. In particular, the viscous-shock-layer method was shown to yield excellent comparisons and should be useful in providing detailed flowfield and surface values for slender blunted cones. Additional predictions were obtained with these methods for two 5-deg half-angle cones with different nose radii to illustrate the effects of nose bluntness and angle of attack on drag and heat transfer. These results demonstrate the benefit of nose blunting with respect to heating and drag for laminar and transitional flow at zero-lift conditions and the benefit of heating reduction at angle of attack. Detailed comparison of the engineering code predictions with the viscous-shock-layer results for these additional cases generally showed good agreement except for the laminar prodictions at angle of attack on the forward cone surface. Nonequilibrium calculations at 0-deg angle of attack showed that substantial benefits of low surface catalysis existed only in the nose-dominated region.

Thompson, R. A.↗

Issues on human acceleration tolerance after long-duration space flights

This report reviewed the literature on human tolerance to acceleration at 1 G and changes in tolerance after exposure to hypogravic fields. It was found that human tolerance decreased after exposure to hypokinetic and hypogravic fields, but the magnitude of such reduction ranged from 0 to 30 percent for plateau G forces and 30 to 70 percent for time tolerance on sustained G forces. A logistic regression model of the probability of individuals with 25 percent reduction in +Gz tolerance after 1 to 41 days of hypogravic exposures was constructed. The estimated values from the model showed a good correlation with the observed data. A brief review of the need for in-flight centrifuge during long-duration missions was also presented. Review of the available data showed that the use of countermeasures (such as anti-G suits, periodic acceleration, and exercise) reduced the decrement in acceleration tolerance after long-duration space flights. Areas of further research include quantification of the effect of countermeasures on tolerance, and methods to augment tolerance during and after exposures to hypogravic fields. Such data are essential for planning long-duration human missions.

Kumar, K. Vasantha↗

Weight minimization of a support structure

This paper addresses the weight minimization of a circular plate-like structure which resulted in a 26 percent weight reduction. The optimization was performed numerically with the COPES/ADS program using the modified method of feasible directions. Design parameters were the inner thickness and outer thickness of the plate with constraints on maximum yield stress and maximum transverse displacement. Also, constraints were specified for the upper and lower bounds of the fundamental frequency and plate thicknesses. The MSC/NASTRAN finite element program was used for the evaluation of response variables. Original and final designs of the plate were tested using an Instron tension-compression machine to compare finite element results to measured strain data. The difference between finite element strain components and measured strain data was within engineering accuracy.

Kluberdanz, Donald J.↗

Thermodynamics of Minerals Stable near Earth's Surface

Project “Thermodynamics of Minerals Stable Near the Earth’s Surface” uses specialized calorimetric techniques to obtain new thermochemical data for solid phases of interest in the Earth’s “critical zone”, the near surface regions of the planet most directly affecting and affected by human activity. Major activity was in three areas: manganese oxide materials, aluminum clusters which are precursors to aluminum oxyhydroxide precipitates, and zeolites. All these classes of minerals are potential carriers of heavy metals and radionuclides in the environment, both within their crystal structures and as adsorbed layers or colloids. Their thermodynamic stability, as well as the sequence of stability of competing phases, governs the aqueous solubility of contaminants (and nutrients) in soil, groundwater, and sediments. The thermodynamics of these phases is strongly affected by particle size and crystallinity, since they often occur as very fine particles which do not coarsen in the near-surface environment. Many of these materials exhibit extensive polymorphism, multicomponent solid solution, and variable hydration states. Thus, one must define and systematize important thermodynamic variables, since one cannot make measurements on each and every possible phase, particle size, and composition. A major finding of the work on manganese oxides was labile water-induced oxidation-reduction reactions. These will be studied further by a combination of thermodynamic and synchrotron-based spectroscopic methods, the latter in collaboration with Peggy O’Day at UC Merced. The adsorption of other species, including simple organics, on such redox-active surfaces will also be investigated by a combination of thermochemical and spectroscopic studies. Studies of the energetics of water adsorption on mineral surfaces will be expanded to emphasize the adsorption of CO2 and small organic molecules, relevant to soil, groundwater, and the subsurface environment. Gas adsorption calorimetry, immersion calorimetry, and solution calorimetry will be combined with appropriate analytical and spectroscopic techniques to obtain a comprehensive picture of the interactions and their energetics. The evolution of aqueous aluminum clusters to form aluminum oxyhydroxide precipitates will be studied in detail by a combination of calorimetric and structural methods applied to aqueous samples aged at room temperature. The energetics of new classes of clusters will be explored. The project addresses several common themes relevant to the broad mission of the Department of Energy. Thermochemical data for minerals stable near the Earth’s surface, though still incomplete, are essential for understanding both natural and anthropogenic processes that affect our very existence on this planet. Such data contribute to the fundamental underpinning for mitigation and management strategies for the extraction and use of energy. Fundamental thermodynamic and mechanistic understanding is required to model processes ranging from heavy metal pollution to nuclear waste disposal to climate change.

58 GEOSCIENCES↗

Toward the analytic bootstrap of energy correlators

In this paper, we present a framework for the analytic bootstrap of three-point energy correlators, a crucial observable in $\mathcal{N}$ = 4 super Yang-Mills theory and quantum chromodynamics (QCD). Our approach combines spherical contour techniques, general physical constraints such as pole cancellations, and power correction data in the singular limits to determine its analytic expression. In contrast to previous bootstrap studies restricted to scattering amplitudes for supersymmetric theories, our framework makes use of the properties of Feynman integrals, marking a significant step toward bootstrapping realistic QCD observables. Using this method, we derive analytic expressions for leading-order three-point energy correlators in the multi-collinear limit with equal and unequal energy weights, where the latter are crucial ingredients for projected N -point energy correlators. We also apply the recently developed technique of analytic regression with lattice reduction as a way to bypass needing explicit expressions for the singular limits. Bridging theoretical advances in scattering amplitudes with the renewed interest in weighted cross-sections, our work opens the door to precision tests of QCD dynamics through analytic event-shape predictions.

jet substructure↗

Potassium carbonate decomposition modeling within rotating detonation engines for direct power extraction applications

We report that recently, there has been a significant interest in detonation-based combustion systems, such as rotating detonation engines (RDE), due to potential performance advantages in propulsion and energy applications. This includes improvements in thermodynamic efficiency, inherently high gas velocities, and the possibility of achieving an increase in total pressure (i.e. pressure gain) through the combustion process. Due to approximating a constant volume combustion process, these devices also tend to exhibit extremely high local gas temperatures relative to a comparable constant pressure combustor. These advantages overlap well with desirable performance characteristics of direct power extraction (DPE) technologies, such as a magnetohydrodynamic (MHD) generator. Typically, in DPE systems hot combustion products are seeded with an easily ionizable material such as potassium carbonate (K 2 CO 3 ) in order to boost the electrical conductivity. However, due to the short gas residence times within an RDE, it was unclear whether forming an electrically conductive combustion plasma would be feasible for integration with a downstream MHD generator. A model is presented which describes the heating, decomposition, and ionization of solid K 2 CO 3 particles and aqueous solutions of K 2 CO 3 in water, for a given initial particle diameter. This model was combined with available computational fluid dynamics (CFD) data for an oxygen-methane RDE in a one-way coupled Eulerian-Lagrangian framework to predict particle trajectories and the corresponding heating, decomposition, and ionization histories. Electrical conductivities were computed using a previously developed model, and a method was proposed to determine an equivalent average electrical conductivity. Results show that particle sizes below ~30 µm are able to fully decompose before reaching the exit of the RDE. While the one-way coupled nature of the simulations precluded rigorous evaluation of the effects of seed material on detonability, a substantial temperature reduction is expected at the detonation wave front due to heating and decomposition. A preliminary comparison is presented between the RDE and an equivalent constant pressure adiabatic combustor, showing a potential performance advantage for the RDE.

42 ENGINEERING↗

Fourier method for 3-dimensional data fusion of X-ray Computed Tomography and ultrasound

X-ray Computed Tomography (CT) is essential for nondestructive inspection of many manufactured components but is susceptible to various forms of artifacts and noise. In particular, multi-detector row cone-beam CT systems can suffer from so called “cone-beam” artifacts and partial volume effects, particularly on planar edges at the periphery of the field of view in the cone angle dimension. Uni-directional ultrasonic testing methods generally have extremely accurate in-plane depth resolution but poorer lateral resolution due to physical and geometric constraints. This paper presents a novel technique called Computed Tomographic Fusion (CT-F) which uses three-dimensional Fourier filtering to combine x-ray cone-beam CT reconstructions and ultrasound data in the frequency space. The result is a single image with improved accuracy and quality. CT-F mitigates artifacts while allowing for rapid, accurate characterization of large three-dimensional CT volumes. Finally, using simulations and experiments, we demonstrate artifact reduction and edge contrast improvement in volumetric reconstructions.

42 ENGINEERING↗

Enabling Microscale Processing: Combined Raman and Absorbance Spectroscopy for Microfluidic On-Line Monitoring

Microfluidics have many potential applications including characterization of chemical processes on a reduced scale, spanning the study of reaction kinetics using on-chip liquid–liquid extractions, sample pretreatment to simplify off-chip analysis, and for portable spectroscopic analyses. The use of in situ characterization of process streams from laboratory-scale and microscale experiments on the same chemical system can provide comprehensive understanding and in-depth analysis of any similarities or differences between process conditions at different scales. A well-characterized extraction of Nd(NO 3 ) 3 from an aqueous phase of varying NO 3– (aq) concentration with tributyl phosphate (TBP) in dodecane was the focus of this microscale study and was compared to an earlier laboratory-scale study utilizing counter current extraction equipment. Here, we verify that this same extraction process can be followed on the microscale using spectroscopic methods adapted for microfluidic measurement. Concentration of Nd (based on UV–vis) and nitrate (based on Raman) was chemometrically measured during the flow experiment, and resulting data were used to determine the distribution ratio for Nd. Extraction distributions measured on the microscale were compared favorably with those determined on the laboratory scale in the earlier study. Both micro-Raman and micro-UV–vis spectroscopy can be used to determine fundamental parameters with significantly reduced sample size as compared to traditional laboratory-scale approaches. This leads naturally to time, cost, and waste reductions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Automated Adsorption Workflow for Semiconductor Surfaces and the Application to Zinc Telluride

Surface adsorption is a crucial step in numerous processes, including heterogeneous catalysis, where the adsorption of key species is often used as a descriptor of efficiency. We present here an automated adsorption workflow for semiconductors which employs density functional theory calculations to generate adsorption data in a high-throughput manner. Starting from a bulk structure, the workflow performs an exhaustive surface search, followed by an adsorption structure construction step, which generates a minimal energy landscape to determine the optimal adsorbate-surface distance. An extensive set of energy-based, charge-based, geometric, and electronic descriptors tailored toward catalysis research are computed and saved to a personal user database. Finally, the application of the workflow to zinc telluride, a promising CO 2 reduction photocatalyst, is presented as a case study to illustrate the capabilities of this method and its potential as a material discovery tool.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Valuing Residential Energy Efficiency: Analysis for a Prototypical Southeastern Utility [Slides]

The increasing amount of variable renewable energy resources and shifts towards more end-use and vehicle electrification suggests profound changes to power system planning and operation. Specifically, renewable energy is expected to shift net peak demand from late afternoon to early evening and end-use electrification may significantly increase winter peak demand. Residential energy efficiency is likely to align well with these shifts as it tends to produce savings in the early evening (e.g., from lighting measures) and coincident with heating loads (e.g., from envelope and space conditioning measures). Despite the opportunity to decrease system costs and emissions, residential energy efficiency is often limited by static valuation methods and its economic potential is considerably less than its technical potential. Using hourly residential energy efficiency characterizations, utility program cost data, and a capacity expansion model, we estimate the benefits of residential energy efficiency for a prototypical, summer-peaking utility in the Southeastern region. We first establish the cost-effective residential energy efficiency portfolio through “competition” with supply-side resources in a forward-looking capacity expansion model. Importantly, we then evaluate several scenarios intended to drive an increasing amount of cost-effective residential energy efficiency through measure cost reductions, increased customer adoption, policy goals (e.g., carbon price), and delivery of an integrated package of measures. The results quantify total system cost and emissions reductions, fossil-fuel plant retirements, and peak demand reductions. Results suggest the design and prioritization of policies and programs to access the untapped amount of cost-effective residential energy efficiency.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Investigation of Antarctic crust and upper mantle using MAGSAT and other geophysical data

Antarctica is the perfect proving ground for testing data reduction procedures which are alternatives to the standard procedure employing polynomial fitting. Unreduced data (observed values minus corefield model theo each pass) were averaged in 3 degree bins. The resulting map was then high pass filtered using a finite Fourier transform filter so that spectral peaks between 4200 km and 5280 km were diminished by 1/3, peaks corresponding to wavelengths greater than or equal to 5280 km were diminished by 1/2, and the d.c. component was set equal to zero. The surface subtracted in this way differs from the polynomials used in the standard method in that it is static over the 5 north data window. The map produced is presented and the effects of the static model are compared to those of the dynamic mode.

Bentley, C. R.↗

Ambulation Increases Decompression Sickness in Spacewalk Simulations

Musculoskeletal activity has the potential to both improve and compromise decompression safety. Exercise enhances inert gas elimination during oxygen breathing prior to decompression (prebreathe), but it may also promote bubble nuclei formation (nucleation), which can lead to gas phase separation and bubble growth and increase the risk of decompression sickness (DCS). The timing, pattern and intensity of musculoskeletal activity and the level of tissue supersaturation may be critical to the net effect. Understanding the relationships is important to evaluate exercise prebreathe protocols and quantify decompression risk in gravity and microgravity environments. Data gathered during NASA's Prebreathe Reduction Program (PRP) studies combined oxygen prebreathe and exercise followed by low pressure (4.3 psi; altitude equivalent of 30,300 ft [9,235 m]) microgravity simulation to produce two protocols used by astronauts preparing for extravehicular activity. Both the Phase II/CEVIS (cycle ergometer vibration isolation system) and ISLE (in-suit light exercise) trials eliminated ambulation to more closely simulate the microgravity environment. The CEVIS results (35 male, 10 female) serve as control data for this NASA/Duke study to investigate the influence of ambulation exercise on bubble formation and the subsequent risk of DCS. METHODS Four experiments will replicate the CEVIS exercise-enhanced oxygen prebreathe protocol, each with a different exception. The first of these is currently underway. Experiment 1 - Subjects complete controlled ambulation (walking in place with fixed cadence and step height) during both preflight and at 4.3 psi instead of remaining nonambulatory throughout. Experiment 2 - Subjects remain non-ambulatory during the preflight period and ambulatory at 4.3 psi. Experiment 3 - Subjects ambulate during the preflight period and remain non-ambulatory at 4.3 psi. Experiment 4 - The order of heavy and light exercise employed in the CEVIS protocol is reversed, with the light exercise occurring first (subjects remain non-ambulatory throughout). Decompression stress is assessed with non-invasive ultrasound during each of 14 epochs of a 4 hour simulated spacewalk at 4.3 psi; aural Doppler is used to monitor bubbles (Spencer grade 0-IV scale) passing through the pulmonary artery, and two-dimensional echocardiographic imaging is used to look for left ventricular gas emboli (LVGE; the presence of which is a test termination criterion). Venous blood is collected at baseline and twice following repressurization to determine if the decompression stress is correlated with microparticles (cell fragments) accumulation. The plan is to test 25-50 subjects in each experiment. Fisher Exact Tests (one-tailed) are used to compare test and control groups. Trials are suspended when the DCS or grade IV VGE observations reach 70% confidence of DCS risk >15% and grade IV VGE risk >20%. RESULTS Experiment 1 was concluded with 20 complete trials (15 male, 5 female) since the statistical outcome would not change with five additional trials. The observed DCS was significantly greater in Experiment 1 than in CEVIS trials (4/20 [20%] vs. 0/45 [0%], respectively, p=0.007), as was the frequency of peak grade IV VGE (6/21 [29%; including one additional subject that presented grade IV VGE but whose trial was ended before completion when LVGE were observed] vs. 3/45 [7%], respectively, p=0.024). Experiment 3 trials are now underway, with 11 trials completed (10 male, 1 female). Preliminary results indicate no difference in observed DCS between Experiment 3 and CEVIS trials (1/11 [9%] vs. 0/45 [0%], respectively, p=0.196), or between Experiment 3 and Experiment 1 trials (p=0.405). The frequency of peak grade IV VGE in Experiment 3 (2/11 [18%]) did not differ from CEVIS or Experiment 1 trials (p=0.251 and p=0.425, respectively). Microparticle patterns are widely variable and still under analysis. DISCUSSION The results of the Experiment 1 trials support the thesis that decompression stress is increased by ambulation exercise, given the higher incidence of DCS and grade IV VGE when compared to the non-ambulatory PRP CEVIS trials. Experiment 3 trials are incomplete, but suggest that the effect of ambulation during ground level preflight oxygen breathing alone, when subjects are undersaturated with inert gas, may not differ in risk from ambulation at both preflight and spacesuit pressures, the latter when subjects are supersaturated with inert gas. Further trials are needed to confirm the relative effects of ambulation in undersaturated vs. supersaturated states and to determine whether light exercise facilitates the removal of heavy exercise-induced nucleation (Experiment 4).

Pollock, N. W.↗

Assessing the methane mitigation potential of innovative management in US rice production

Abstract Rice is an important global crop while also contributing significant anthropogenic methane (CH 4 ) emissions. To support the future of rice production, more information is needed on the impacts of sustainability-driven management used to grow rice with lower associated methane emissions. Recent support for the impacts of different growing practices in the US has prompted the application of a regional methodology (Tier 2) to estimate methane emissions in different rice growing regions. The methodology estimates rice methane emissions from the US Mid-South (MdS) and California (Cal) using region-specific scaling factors applied to a region-specific baseline flux. In our study, we leverage land cover data and soil clay content to estimate methane emissions using this approach, while also examining how changes in common production practices can affect overall emissions in the US. Our results indicated US rice cultivation produced between 0.32 and 0.45 Tg CH 4 annually, which were approximately 7% and 42% lower on average compared to Food and Agriculture Organization of the UN (FAO) and US Environmental Protection Agency (EPA) inventories, respectively. Our estimates were 63% greater on average compared to similar methods that lack regional context. Introducing aeration events into irrigation resulted in the greatest methane reductions across both regions. When accounting for differences between baseline and reduction scenarios, the US MdS typically had higher mitigation potential compared to Cal. The differences in cumulative mitigation potential across the 2008–2020 period were likely driven by lower production area clay content for the US MdS compared to Cal. The added spatial representation in the Tier 2 approach is useful in surveying how impactful methane-reducing practices might be within and across regions.

Environmental Sciences & Ecology↗