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At least 19 records

Persistent ocean anomalies as a response to Northern Hemisphere heating induced by biomass burning variability

Biomass burning aerosol (BBA) emissions in the Coupled Model Intercomparison Project Phase 6 (CMIP6) historical forcing fields have enhanced temporal variability during the years 1997–2014 compared to earlier periods. Recent studies document that the corresponding inhomogeneous shortwave forcing over this period can cause changes in clouds, permafrost, and soil moisture, which contribute to a net terrestrial Northern Hemisphere warming relative to earlier periods. Here, we investigate the ocean response to the hemispherically asymmetric warming, using a 100-member ensemble of the Community Earth System Model version 2 Large Ensemble forced by two different BBA emissions (CMIP6 default and temporally smoothed over 1990–2020). Differences between the two subensemble means show that ocean temperature anomalies occur during periods of high BBA variability and subsequently persist over multiple decades. In the North Atlantic, surface warming is efficiently compensated for by decreased northward oceanic heat transport due to a slowdown of the Atlantic Meridional Overturning Circulation. In the North Pacific, surface warming is compensated for by an anomalous cross-equatorial cell (CEC) that reduces northward oceanic heat transport. The heat that converges in the South Pacific through the anomalous CEC is shunted into the subsurface and contributes to formation of long-lasting ocean temperature anomalies. The anomalous CEC is maintained through latitude-dependent contributions from narrow western boundary currents and basin-wide near-surface Ekman transport. Furthermore, these results indicate that interannual variability in forcing fields may significantly change the background climate state over long timescales, presenting a potential uncertainty in CMIP6-class climate projections forced without interannual variability.

54 ENVIRONMENTAL SCIENCES↗

Understanding the Impact of Lignocellulosic Biomass Variability on the Size Reduction Process: A Review

The importance of size reduction to the commercial deployment of biomass utilization technologies cannot be overemphasized. Size reduction is necessary to create good flowing, easily digestible lignocellulosic biomass. However, inefficiencies and inconsistencies have not been well addressed for the process of size reduction. This has motivated quite a few research studies, some of which have reported the influence of process variables and pretreatment on the size reduction performance as well as the development of novel size reduction equipment and empirical mathematical models. In this Perspective, we present a systematic and critical evaluation of the state of lignocellulosic biomass size reduction research to provide insights for engineers and scientists for future development and investigation. We first briefly discuss the structural biology and failure mode of lignocellulosic biomass. Then, we present a comprehensive, data-driven picture of the interactions among lignocellulosic biomass attributes, size reduction process variables, pretreatment processes, and size reduction process performance (as defined by product characteristics and size reduction energy consumption). The sizing equipment tool wear issues are also summarized. Finally, we highlight some existing gaps and future research opportunities for lignocellulosic biomass size reduction to inform the development of newer technologies that could effectively produce high-value lignocellulosic biomass particles.

09 BIOMASS FUELS↗

Importance of incorporating spatial and temporal variability of biomass yield and quality in bioenergy supply chain

Abstract Biofuels made from biomass and waste residues will largely contribute to United States’ 2050 decarbonization goal in the aviation sector. While cellulosic biofuels have the potential fuel performance equivalent to petroleum-based jet fuel, the biofuel industry needs to overcome the supply chain barrier caused by temporal and spatial variability of biomass yield and quality. This study highlights the importance of incorporating spatial and temporal variability during biomass supply chain planning via optimization modeling that incorporates 10 years of drought index data, a primary factor contributing to yield and quality variability. The results imply that the cost of delivering biomass to biorefinery may be significantly underestimated if the multi-year temporal and spatial variation in biomass yield and quality is not captured. For long term sustainable biorefinery operations, the industry should optimize supply chain strategy by studying the variability of yield and quality of biomass in their supply sheds.

09 BIOMASS FUELS↗

Increased Variability of Biomass Burning Emissions in CMIP6 Amplifies Hydrologic Cycle in the CESM2 Large Ensemble

Abstract Historical simulations performed for the Coupled Model Intercomparison Project Phase 6 used biomass burning emissions between 1997 and 2014 containing higher spatial and temporal variability compared to emission inventories specified for earlier years, and compared to emissions used in previous (e.g., CMIP5) simulation intercomparisons. Using the Community Earth System Model version 2 Large Ensemble, we show this increased biomass burning emissions variability leads to amplification of the hydrologic cycle poleward of 40°N. Notably, the high variability of biomass burning emissions leads to increased latent heat fluxes, column‐integrated precipitable water, and precipitation. Greater ocean heat uptake, weaker meridional energy transport from the tropics, greater atmospheric shortwave and longwave absorption, and lower relative humidity act to moderate this hydrologic cycle amplification. Our results suggest it is not only the secular changes (on multidecadal timescales) in biomass burning emissions that impact the hydrologic cycle, but also the shorter timescale variability in emissions.

Heyblom, Kyle B.↗

Biomass Feedstock Flow Modeling at Exascale

Variable biomass feedstock handling in hoppers and screw conveyors can cause upstream failures and disrupt downstream conversion operations. Understanding how particle size, shape, and moisture content affect feedstock flowability is important for efficient biorefinery operation. We present the use of our open-source discrete element method (DEM) solver for predicting flows in large scale hoppers and assess its performance on state-of-the-art high performance computing platforms that use heterogenous computing architectures.

bioenergy↗

Characterizing Variability in Lignocellulosic Biomass: A Review

Feedstock variability is a significant barrier to the scale-up and commercialization of lignocellulosic biofuel technologies. Variability in feedstock characteristics and behavior creates numerous challenges to the biorefining industry by affecting continuous operation and biofuels yields. Recently, feedstock variability is understood and explained largely on the basis of chemical composition. Physical and mechanical properties and behavior of lignocellulosic feedstock in various unit operations, studied through advanced analytical methods, can further explain variability. Such studies will enable us in developing processes and designing equipment to improve operation and conversion performance. In this perspective, we review several advanced analytical methods that measure density, moisture content, thermal properties, flowability, grindability, rheology properties, and micromorphological characteristics. We also discuss the correlations and interactions among these properties that reflect the complexity of lignocellulosic biomass as a feedstock and the associated quality metrics and logistics of supplying consistent quality feedstock to a biorefinery. We further examine methods that have not traditionally been used to characterize lignocellulosic feedstocks but have the potential to bridge the gap in our explanation of feedstock variability.

09 BIOMASS FUELS↗

Quantifying the effects of varietal types × management on the spatial variability of sorghum biomass across US environments

Abstract Regional‐scale estimations of sorghum biomass production allow identification of optimum genotype×environment×management (G×E×M) combinations for bioenergy generation. The objective of this study was to determine the degree of contributions of G, E, and M toward variability in sorghum biomass in the United States. Using the Agricultural Production Systems sIMulator in a grid computing platform, biomass was simulated for irrigated and rainfed conditions for 30 years across the United States for four sorghum varietal types (grain—GS, sudangrass—SS, photosensitive—PS, and photo‐insensitive—PI). Simulated biomass was assessed by environments clustered using the sum of intercepted solar radiation ( ir ), mean of temperature stress factor ( tp ) and water stress factor ( sw ). Simulated biomass ranged from 5.8 t ha −1 (GS‐rainfed) to 27.5 t ha −1 (PI‐irrigated). Under high‐temperature environments (mean annual temperature = 25°C), rainfed biomass between 40 and 80 days after planting (DAP) was strongly correlated with sw ( r = 0.64–0.86) and irrigated biomass with ir ( r = 0.68–0.81). Under low‐temperature environments (mean annual temperature = 18°C) after 40 DAP, tp and ir had greater effects than sw ( r = 0.55–0.82). Biomass variance was mainly explained by varietal type (50%–76%) in all environments×irrigation combinations, except in the high‐ and mid‐temperature environments under rainfed conditions where rainfall had the major effect (25%–45%). However, when mean temperature during the growing season decreased from 25°C (high environments) to 18°C (low environments), the contribution of mean temperature to biomass variance increased from 7% to 34% (rainfed) and from 4% to 36% (irrigated). Varietal type had the larger interactions with other factors independently of the environment and irrigation. We demonstrated a need to quantify (i) the main G×E×M drivers of biomass variability based on environmental stress factors and (ii) the variance contribution of these drivers on sorghum biomass. Our regional‐scale estimations are key inputs for future robust biomass projections of energy sorghum genotypes integrating G×E×M under climate change scenarios.

Ojeda, Jonathan J.↗

Final Report: Process Intensification of Hydrogen Production through Sorption-Enhanced Gasification of Biomass

The University of Utah, in partnership with Idaho National Laboratory (INL), evaluated Sorption-Enhanced Gasification (SEG) as a transformative pathway for producing hydrogen with the potential for negative CO 2 emissions. SEG integrates gasification, water-gas shift, and in-situ carbon capture within a dual fluidized bed reactor to enable efficient clean hydrogen production. Key challenges related to biomass variability and process complexity were addressed through feedstock engineering, reaction optimization, and process validation. A co-pelletized biomass–limestone feedstock was developed to simplify feeding and introduction of makeup limestone. Kinetic and sorbent studies identified optimal operating conditions and confirmed the suitability of low-cost limestone, while catalysts were developed to reduce tar formation. Reactor modeling and techno-economic analysis indicated that SEG can achieve competitive hydrogen production costs, particularly when combined with carbon incentives, supporting its potential for scale-up and carbon-negative operation.

08 HYDROGEN↗

Corn Stover Fractions from Different Harvest Conditions

There is a lot of variability in biomass. This variability can make it difficult to process the biomass into a consistent format for handling and conversion. As a result, bioenergy feedstocks are often under- or over-converted. Corn stover in particular can be harvested in different ways, baled in different ways, and has significant intrinsic variability due to its very different anatomies. These factors could cause variability in the fractions of corn stover. The fractions of corn stover are leaf, husk, cob, and stalk.

09 BIOMASS FUELS↗

Effects of forest degradation classification on the uncertainty of aboveground carbon estimates in the Amazon

Tropical forests are critical for the global carbon budget, yet they have been threatened by deforestation and forest degradation by fire, selective logging, and fragmentation. Existing uncertainties on land cover classification and in biomass estimates hinder accurate attribution of carbon emissions to specific forest classes. In this study, we used textural metrics derived from PlanetScope images to implement a probabilistic classification framework to identify intact, logged and burned forests in three Amazonian sites. We also estimated biomass for these forest classes using airborne lidar and compared biomass uncertainties using the lidar-derived estimates only to biomass uncertainties considering the forest degradation classification as well. Our classification approach reached overall accuracy of 0.86, with accuracy at individual sites varying from 0.69 to 0.93. Logged forests showed variable biomass changes, while burned forests showed an average carbon loss of 35%. We found that including uncertainty in forest degradation classification significantly increased uncertainty and decreased estimates of mean carbon density in two of the three test sites. Our findings indicate that the attribution of biomass changes to forest degradation classes needs to account for the uncertainty in forest degradation classification. By combining very high-resolution images with lidar data, we could attribute carbon stock changes to specific pathways of forest degradation. This approach also allows quantifying uncertainties of carbon emissions associated with forest degradation through logging and fire. Both the attribution and uncertainty quantification provide critical information for national greenhouse gas inventories.

54 ENVIRONMENTAL SCIENCES↗

Nth-plant scenario for forest resources and short rotation woody crops: Biorefineries and depots in the contiguous US

Estimating the US potential of woody material is of vital importance to ensure cost-effective supply logistics and develop a sustainable bioenergy and bioproducts industry. We analyzed a mature conversion technology for woody resources for the contiguous US that takes advantage of economies of scale: the nth-plant. Here, we developed a database to quantify the total accessible woody biomass within a distributed network of preprocessing depots and biorefineries considering both quality specifications for conversion and a target cost to compete with fossil fuels. We considered two categories of woody biomass: 1) forest residues from trees, tops and limbs produced from conventional thinning and timber harvesting operations as well as non-timber tree removal; and 2) short rotation woody crops such as poplar, willow, pine, and eucalyptus. A mixed integer linear programming model was developed to analyze scenarios with woody feedstock blends at variable biomass ash contents and cost targets at the biorefinery. When considering a target cost of 85.51 dollars/dry ton (2016$) at the biorefinery, the maximum accessible biomass from forest residues in 2040 remained constant at 106 million dry tons regardless of ash targets. Including short rotation woody crops as part of the blend increased the total accessible biomass to 153 and 195 million dry tons at ash targets of 1% and 1.75%, respectively. We concluded from our analysis that woody resources could address about 55% of EPA’s (Environmental Protection Agency) target of 16 billion gallons of cellulosic biofuel.

09 BIOMASS FUELS↗

Estimating the influence of field inventory sampling intensity on forest landscape model performance for determining high-severity wildfire risk

Abstract Historically, fire has been essential in Southwestern US forests. However, a century of fire-exclusion and changing climate created forests which are more susceptible to uncharacteristically severe wildfires. Forest managers use a combination of thinning and prescribed burning to reduce forest density to help mitigate the risk of high-severity fires. These treatments are laborious and expensive, therefore optimizing their impact is crucial. Landscape simulation models can be useful in identifying high risk areas and assessing treatment effects, but uncertainties in these models can limit their utility in decision making. In this study we examined underlying uncertainties in the initial vegetation layer by leveraging a previous study from the Santa Fe fireshed and using new inventory plots from 111 stands to interpolate the initial forest conditions. We found that more inventory plots resulted in a different geographic distribution and wider range of the modelled biomass. This changed the location of areas with high probability of high-severity fires, shifting the optimal location for management. The increased range of biomass variability from using a larger number of plots to interpolate the initial vegetation layer also influenced ecosystem carbon dynamics, resulting in simulated forest conditions that had higher rates of carbon uptake. We conclude that the initial forest layer significantly affects fire and carbon dynamics and is dependent on both number of plots, and sufficient representation of the range of forest types and biomass density.

Science & Technology - Other Topics↗

Discrete-Element and Material-Point Method (DEM and MPM) Based Solvers for Sustainable Technologies

We present the use of discrete element method (DEM) and material point method (MPM) in three relevant green technology applications that include biomass feedstock handling, lithium-ion battery manufacturing, and high-pressure reverse osmosis. Our open-source DEM and MPM solvers are developed using performance portable grid and particle management library, AMReX, thus enabling superior performance on NVIDIA and AMD GPUs with > 100 million particles. Our DEM solver resolves the motion of individual particles in a granular system and includes a bonded sphere method for modeling non-spherical particles along with Hertzian and liquid bridge-based contact models. We simulate highly variable biomass feedstock flows in large-scale hoppers for biofuel production and electrode calendering in battery manufacturing using DEM. Our simulations predict flow blockage in large scale biomass hoppers and electrode microstructure variations, thus providing valuable information for biofuel and battery manufacturers, respectively. The second half of the talk will be on MPM and its application towards pore resolved simulations of reverse osmosis membranes under compressive loads. We present a validation study of our MPM simulations with membrane microscopy imaging thus providing useful insights on membrane stability under high pressure conditions. We also present a spectral stability analysis of using linear hat, quadratic and cubic spline basis in MPM indicating regions of numerical stability.

BIOMASS FUELS,MATHEMATICS AND COMPUTING↗

Enhancing biomass flowability for entrained flow Gasification: The role of densification and torrefaction

Gasification presents a key strategy in addressing future energy demands while minimizing environmental impact. This has been recognized as a promising method to convert biomass to higher value products such as biofuels or hydrogen. Among gasification technologies, high-temperature and high-pressure reactors, particularly the R-GAS® system, emerge as an advanced option boasting superior conversion efficiency. However, akin to conventional high-temperature and high-pressure gasifiers, R-GAS® necessitates small particle sizes for optimal carbon conversion, a requirement yet to be fully explored for biomass. Hence, this study investigated the effectiveness of combined mechanical and thermal preprocessing techniques in modifying the physicochemical properties of biomass to suit gasification systems. Mechanical techniques including densification and pulverization, alongside thermal techniques such as torrefaction and steam explosion, were examined. The results demonstrate that torrefaction fosters producing of uniform granular material, enhancing flowability and reducing energy requirements for pulverization compared to steam explosion. Notably, torrefied corn stover exhibited lower internal friction angles and effective cohesion (40.09 ± 0.22° and 0.56 ± 0.01 kPa, respectively) compared to steam exploded corn stover (41.87 ± 0.65° and 0.83 ± 0.06 kPa, respectively), indicative of improved flowability. Additionally, pulverization of torrefied corn stover required approximately 16 % less energy than steam exploded corn stover and 91 % less energy than raw corn stover. Furthermore, the torrefaction-induced alterations in particle size, shape, and packing densities emphasize its potential to optimize flow and handling processes for gasification. These findings underline that densification followed by torrefaction effectively addresses biomass variability, leading to more efficient and sustainable energy conversion.

09 - BIOMASS FUELS↗

Stem respiration and growth in a central Amazon rainforest

Tropical forests cycle a large amount of CO 2 between the land and atmosphere, with a substantial portion of the return flux due tree respiratory processes. However, in situ estimates of woody tissue respiratory fluxes and carbon use efficiencies (CUEW) and their dependencies on physiological processes including stem wood production (Pw) and transpiration in tropical forests remain scarce. In this work, we synthesize monthly Pw and daytime stem CO 2 efflux (ES) measurements over one year from 80 trees with variable biomass accumulation rates in the central Amazon. On average, carbon flux to woody tissues, expressed in the same stem area normalized units as ES, averaged 0.90 ± 1.2 µmol m -2 s -1 for Pw, and 0.55 ± 0.33 µmol m -2 s -1 for daytime ES. A positive linear correlation was found between stem growth rates and stem CO 2 efflux, with respiratory carbon loss equivalent to 15 ± 3% of stem carbon accrual. CUEW of stems was non-linearly correlated with growth and was as high as 77-87% for a fast-growing tree. Diurnal measurements of stem CO 2 efflux for three individuals showed a daytime reduction of ES by 15-50% during periods of high sap flow and transpiration. The results demonstrate that high daytime ES fluxes are associated with high CUE W during fast tree growth, reaching higher values than previously observed in the Amazon Basin (e.g. maximum CUEW up to 77-87%, versus 30-56%). The observations are consistent with the emerging view that diurnal dynamics of stem water status influences growth processes and associated respiratory metabolism.

54 ENVIRONMENTAL SCIENCES↗

Investigating Thaw and Plant Productivity Constraints on Old Soil Carbon Respiration From Permafrost

Isotopic radiocarbon (Δ 14 C) signatures of ecosystem respiration (Reco) can identify old soil carbon (C) loss and serve as an early indicator of permafrost destabilization in a warming climate. Warming also stimulates plant productivity causing plant respiration to dominate Reco Δ 14 C signatures and potentially obscuring old soil C loss. Here, we investigate how a wide spatio-temporal gradient of permafrost thaw and plant productivity affects Reco Δ 14 C patterns and isotopic partitioning. Spatial gradients came from a warming experiment with doubling thaw depth and variable biomass, and a vegetation removal manipulation to eliminate plant contributions. We sampled in August and September to capture transitions from high to low plant productivity, decreased surface soil temperature, and relatively small seasonal thaw extensions. We found that surface processes dominate spatial variation in old soil C loss and a process-based partitioning approach was crucial for constraining old soil C loss. Resampling the same plots in different times of the year revealed that old soil C losses tripled with cooling surface temperature, and the largest old soil C losses were detected when the organic-to-mineral soil horizons thawed (~50–60 cm). We suggest that the measured increase in old soil respiration over the season and when the organic-to-mineral horizon thawed, may be explained by mobilization of nitrogen that stimulates microbial decomposition at depth. Our results suggest that soil C in the organic to mineral horizon may be an important source of soil C loss as the entire Arctic region warms and could lead to nonlinearities in projected permafrost climate feedbacks.

54 ENVIRONMENTAL SCIENCES↗