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At least 649 records · Page 36

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↗

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↗

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↗

Drought shrinks terrestrial upland resilience to climate change

Abstract Aim Drought has been shown to alter terrestrial ecosystem carbon (C) and nitrogen (N) dynamics, and thus feedback to future climate. However, drought‐induced changes in terrestrial upland C and N pools and the drought response of soil carbon dioxide (CO 2 ) and nitrous oxide (N 2 O) fluxes are yet to be quantified. Location Global upland ecosystems. Time period 2000–2018. Major taxa studied Terrestrial C and N fluxes. Methods A meta‐analysis was conducted that compiled 1,344 measurements from 128 manipulative studies worldwide to obtain a general picture of terrestrial C and N cycling responses to soil drought stress and identify the primary driving factors. Results We showed that drought significantly decreased plant C pools, with stronger negative responses of aboveground than belowground C components. Drought significantly decreased soil respiration ( R S ) and N 2 O fluxes by 19% and 29%, respectively. There were non‐significant changes in soil organic C and N pools in response to drought; in contrast to a considerable decrease in soil dissolved organic C (−22%), there was a robust increase in soil nitrate‐N (26%) following short‐term drought impact. By relating net ecosystem productivity (NEP) to the difference between net primary production (NPP) and soil heterotrophic respiration ( R H ), drought was found to drive a decrease up to −37% in NEP, being equivalent to a reduction in terrestrial net C uptake of 2.91 t C/ha. Main conclusions Our study provides insights into soil release of CO 2 and N 2 O with a linkage to the changes in terrestrial C and N pools in response to drought across upland biomes. Our findings highlight that, despite the lowered soil C release rate, the capacity of upland biomes as a C sink to slow climate change would still be weakened due to a robust decline of plant‐derived C input to soil in a future drier climate.

Zheng, Yajing↗

Predicting the Dissolution Rate of Borosilicate Glasses using QSPR analysis based on molecular dynamics simulations

Quantitative Structure Property Relationship (QSPR) analysis based on molecular dynamics (MD) simulations is a promising approach for establishing the composition-property relationships of glass and other materials with complex structures. A series of 20 borosilicate and boroaluminosilicate glasses have been modeled by using MD simulations with recently developed effective potentials. Short- and medium-range structures of these glasses were analyzed and, based on these structural information, QSPR analysis of the initial dissolution rate (r0) was made and compared with measured r0 at 90°C and pH 9 using various structural descriptors such as percentage of bridging oxygen species, network connectivity and average ring size. The structural descriptors, Fnet, containing energetic information such as single bond strength and other structural information were also used. It was found that overall network connectivity, average ring size and Fnet give reasonable predictions of the r0 of studied glasses, given the conditions that the glasses are homogeneous and dissolve congruently. Modifying glass compositions to account preferential release of modifiers gives a better prediction for incongruently dissolving glasses. The results were compared with our recent work of predicting glass dissolution behavior from compositions using the topological-constraints-based models.

Du, Jincheng↗

Stomatal conductance, not biochemistry, drives low temperature acclimation of photosynthesis in Populus balsamifera , regardless of nitrogen availability

Low temperature thermal acclimation may require adjustments to nitrogen and water use to sustain photosynthesis due to slow enzyme functioning and high-water viscosity. However, understanding of photosynthetic acclimation to temperatures below 11°C is limited. Here, we acclimated Populus balsamifera to 6 °C and 10 °C (6A and 10A, respectively) and provided the trees with either high or low N fertilizer. We measured net CO 2 assimilation rates (A net ), stomatal conductance (g s ), maximum rates of Rubisco carboxylation (V cmax ) and electron transport (J max ), and dark respiration (R d ) at leaf temperatures of 2, 6, 10, 14 and 18 °C, along with leaf N concentrations. The 10A trees had higher A net than the 6A trees at warmer leaf temperatures, which was correlated with higher g s in the 10A trees. The instantaneous temperature responses of V cmax , J max and R d were similar for trees from both acclimation temperatures. While soil N availability increased leaf N concentrations, this had no effect on acclimation of photosynthesis or respiration. Our results indicate that acclimation below 11°C occurred primarily through changes in stomatal conductance, not photosynthetic biochemistry, and was unaffected by short-term N supply. Thermal acclimation of stomatal conductance should therefore be a priority for future carbon cycle model development.

54 ENVIRONMENTAL SCIENCES↗

Evaluating Transfer and Pumping of Slurries from Pulsed Jet Mixed Vessels

Due to gravity, solids in slurries will settle if density differences between the solids and liquid are positive (i.e., particle has a negative buoyant force) unless rheological properties and flow conditions are adequate to overcome the gravitational effects. The rate of settling depends on the force balance of the particle, which includes the surface forces associated with fluid rheology. Given the same fluid and solid properties, particles that are larger and denser tend to settle faster. When pumping slurry into a vessel at concentrations precluding hindered settling with insufficient mixing, particle and density distributions can result in preferential settling, creating stratification in the solids concentration within the vessel. For vessels with transfer line inlets located in the lower portion of the tank, the stratified solids concentration may be detrimental to the transfer system performance. Elevated concentrations of solids in the slurry entrained at the inlet to the transfer line can result in the effective viscosity or slurry bulk density exceeding the design limits of the pump. These conditions could result in plugging of the transfer line or onset of cavitation of the pumps because of excessive pressure drop. These conditions can be exacerbated with periodic inlet conditions existing at the transfer line inlet. Periodic conditions can result when vessel mixing is intermittent such as with pulsed jet mixers (PJM). The transfer line inlet conditions are impacted by the periodic nature of the PJM operations with respect to suspension of solids and their transport to the inlet of the transfer line. A scaling approach is presented, and corresponding test requirements are developed for assessing the prevention of plugging the pipeline. Line plugging mechanisms are addressed that do not include plugging due to steady-state high-density slurry entering the transfer line and reducing the net positive suction head available (NPSHA) at the pump inlet to below that required for pump operation. Items considered include the transition to reduced relative flow velocities, such that the critical pipe velocity for solids deposition, Ucd, is not maintained, and segregation of heavy solids during the transport. The recommended requirements to prevent plugging include: • Limits for viscosity and density for entrained slurry to prevent the pressure drop in the pipeline from exceeding pump capacity. • Limits for viscosity and density for entrained slurry to prevent the net positive suction head available (NPSHA) from falling below the net positive suction head required (NPSHR) for operating the pump. • Transfer line velocity and flow rate requirements to maintain solids in suspension, while avoiding line plugging that results from deposition of solids within the transfer line. This paper describes the development of the scaling and testing requirements to verify that proposed approaches for transfer and pump out are appropriately developed

periodic flow, mixing, pipeline plugging, scaling,↗

Method for boosting dispersive spectrograph stability 1000× using interferometry with crossfaded pairs of delays

We demonstrate a key step along a technical route to achieving cm/s scale accuracy for astronomical spectrographs over long (multi-year) time scales, which is critical for the Doppler characterization of Earth sized exoplanets, and measurement of small cosmic redshift drift over many years. This same technique also enables searching exoplanet atmospheres for biosignificant molecules in direct planet imaging using, otherwise, insufficiently low resolution and drift prone dispersive (grating or prism) spectrographs. Using a method called crossfading for externally dispersed interferometers (EDIs) to get highly robust spectra, we recently demonstrated a factor of 1000 x reduction in the net shift of an EDI measured ThAr line to a deliberate simulated wavelength translation of the detector. This 1000 x gain in disperser stability can be combined with conventional stability gains afforded by fiber scramblers, vacuum tanks, and thermal control, to provide an additional 1 to 3 orders of magnitude reduction in the net point spread function shift drift. Crossfading combines high- and low-delay fringing signals that react oppositely in phase to cancel their net reaction to a detector wavelength drift. This can be implemented by an interferometer addition to a facility spectrograph.

79 ASTRONOMY AND ASTROPHYSICS↗

Synergistic Effects of a Chalkophore, Methanobactin, on Microbial Methylation of Mercury

Microbial production of the neurotoxin methylmercury (MeHg) is a significant health and environmental concern, as it can bioaccumulate and biomagnify in the food web. A chalkophore or a copper-binding compound, termed methanobactin (MB), has been shown to form strong complexes with mercury [as Hg(II)] and also enables some methanotrophs to degrade MeHg. It is unknown, however, if Hg(II) binding with MB can also impede Hg(II) methylation by other microbes. Contrary to expectations, MB produced by the methanotroph Methylosinus trichosporium OB3b (OB3b-MB) enhanced the rate and efficiency of Hg(II) methylation more than that observed with thiol compounds (such as cysteine) by the mercury-methylating bacteria Desulfovibrio desulfuricans ND132 and Geobacter sulfurreducens PCA. Compared to no-MB controls, OB3b-MB decreased the rates of Hg(II) sorption and internalization, but increased methylation by 5- to 7-fold, suggesting that Hg(II) complexation with OB3b-MB facilitated exchange and internal transfer of Hg(II) to the HgcAB proteins required for methylation. Conversely, addition of excess amounts of OB3b-MB or a different form of MB from Methylocystis strain SB2 (SB2-MB) inhibited Hg(II) methylation, likely due to greater binding of Hg(II). Collectively, our results underscore the complex roles of microbial exogenous metal-scavenging compounds in controlling net production and bioaccumulation of MeHg in the environment. Some anaerobic microorganisms convert inorganic mercury (Hg) into the neurotoxin methylmercury, which can bioaccumulate and biomagnify in the food web. While the genetic basis of microbial mercury methylation is known, factors that control net methylmercury production in the environment are still poorly understood. Here, it is shown that mercury methylation can be substantially enhanced by one form of an exogenous copper-binding compound (methanobactin) produced by some methanotrophs, but not by another. This novel finding illustrates that complex interactions exist between microbes and that these interactions can potentially affect the net production of methylmercury in situ .

54 ENVIRONMENTAL SCIENCES↗

NfoR: Chromate Reductase or Flavin Mononucleotide Reductase?

Soil bacteria can detoxify Cr(VI) ions by reduction. Within the last 2 decades, numerous reports of chromate reductase enzymes have been published. These reports describe catalytic reduction of chromate ions by specific enzymes. These enzymes each have sequence similarity to known redox-active flavoproteins. We investigated the enzyme NfoR from Staphylococcus aureus, which was reported to be upregulated in chromate-rich soils and to have chromate reductase activity (H. Han, Z. Ling, T. Zhou, R. Xu, et al., Sci Rep 7:15481, 2017, https://doi.org/10.1038/s41598-017-15588-y). We show that NfoR has structural similarity to known flavin mononucleotide (FMN) reductases and reduces FMN as a substrate. NfoR binds FMN with a dissociation constant of 0.4 μM. The enzyme then binds NADPH with a dissociation constant of 140 μM and reduces the flavin at a rate of 1,350 s -1 . Turnover of the enzyme is apparently limited by the rate of product release that occurs, with a net rate constant of 0.45 s -1 . The rate of product release limits the rate of observed chromate reduction, so the net rate of chromate reduction by NfoR is orders of magnitude lower than when this process occurs in solution. We propose that NfoR is an FMN reductase and that the criterion required to define chromate reduction as enzymatic has not been met. That NfoR expression is increased in the presence of chromate suggests that the survival adaption was to increase the net rate of chromate reduction by facile, adventitious redox processes.

59 BASIC BIOLOGICAL SCIENCES↗

Hydroxide Exchange Membrane Carbon Capture (HEMCC) Using Nickel Hydroxide Batteries and Flow-through Membranes

Proposed is an electrochemical nickel hydroxide based hydroxide exchange membrane carbon capture (HEMCC) device for Direct Air Capture (DAC) of CO2. DAC has been identified as one of the key net negative carbon technologies to achieve net zero carbon emissions. Net negative carbon technologies are required to offset continued emissions from dilute CO2 sources such as agriculture and construction. The majority of current DAC technologies at scale (>1 KT∙yr-1) are adsorbent based technologies with significant energy cost. The traditional DAC energy cost is primarily driven by the temperature swing required to regenerate the sorbent and has been shown to be 1.8 MWh·ton-1 at the system level. Electrochemical pH swing devices are a growing research area for carbon capture devices with the goal of lowering the energy cost required for DAC. A pH gradient is built by generating OH- at the cathode and consuming OH- at the anode. An acid-base equilibrium with CO2 allows for the capture of CO2 at the cathode and release at the anode. This extends from other electrochemical CO2 capture devices based on pKa shifts of an electrochemically active organic species allowing for the capture and release of CO2. Electrochemical CO2 capture is considered promising based on potentially low energy costs to capture CO2 in comparison with current temperature swing adsorption technologies. This work explores Ni(OH)2 electrodes to produce the pH gradient for CO2 capture and release. At the cathode NiOOH is reduced to Ni(OH)2 while at the anode Ni(OH)2 is oxidized to NiOOH. The symmetrical electrodes allow for a low voltage requirement; the thermodynamic potential difference of standard electrochemical reactions is zero. Most of the voltage observed is to produce the pH gradient with the remainder driving the polarization of the electrodes. There is a resistance component as well, but this is small in comparison due to the low current densities used in the device, nominally 2 mA·cm-1. Two similar devices are presented, a traditional MEA (membrane electrode assembly) and a flow-through MEA. The traditional MEA separates the two Ni(OH)2 electrodes with an 80μm Piperion® membrane. While the flow-through membrane separates the electrodes with a three piece membrane consisting of two 80μm Piperion® membranes with a porous membrane between them. In the traditional MEA system air is passed over the cathode for capture, while the flow-through MEA the air is passed through the porous membrane isolated from the electrodes. The traditional MEA has been used to establish a baseline performance of the device and has been shown to capture CO2 at an energy cost of 1 MWh·ton-1 at the device level. An understanding has been built around the components of that energy cost including the relationship of flux to current density, effect of a regeneration process, transient battery behavior, and gas losses coinciding with changing the polarization of the batteries. The flow-through MEA looks to address of transient battery behavior and gas losses. It allows for denser, higher capacity electrodes, which can lean on traditional Ni-MH battery technology used in alkaline batteries used today. The higher capacities, limit the transient battery effect on flux in the device. Gas losses are addressed by having a continuous inlet air stream to the device and continuous outlet product.

Buchen, James↗

Swap Path Network for Robust Person Search Pre-training

This code corresponds to the WACV25 conference paper, "Swap Path Network for Robust Person Search Pre-training". In that paper, we introduce a new model for the person search task called the Swap Path Net (SPNet). The person search task is a problem in computer vision, where we locate and rank matches to an image of a query person in a set of other images where we want to find them. We also introduce a novel pre-training algorithm specific to the Swap Path Net architecture. The code implements pre-training and fine-tuning of the Swap Path Net (SPNet). This includes ingesting image datasets and updating the weights of the SPNet neural network to train it for the person search task. The repository contains code, configs, and instructions to reproduce all results from the paper.

Jaffe, LucasW [Lawrence Livermore National Laborat↗

Integrating LEO and GEO Observations: Toward Optimal Summertime Satellite Precipitation Retrieval

Abstract Reliable quantitative precipitation estimation with a rich spatiotemporal resolution is vital for understanding the Earth’s hydrological cycle. Precipitation estimation over land and coastal regions is necessary for addressing the high degree of spatial heterogeneity of water availability and demand, and for resolving the extremes that modulate and amplify hazards such as flooding and landslides. Advancements in computation power along with unique high spatiotemporal and spectral resolution data streams from passive meteorological sensors aboard geosynchronous Earth-orbiting (GEO) and low Earth-orbiting (LEO) satellites offer exciting opportunities to retrieve information about surface precipitation phenomena using data-driven machine learning techniques. In this study, the capabilities of U-Net–like architecture are investigated to map instantaneous, summertime surface precipitation intensity at the spatial resolution of 2 km. The calibrated brightness temperature products from the Global Precipitation Measurement (GPM) Microwave Imager (GMI) radiometer are combined with multispectral images (visible, near-infrared, and infrared bands) from the Advanced Baseline Imager (ABI) aboard the GOES-R satellites as main inputs to the U-Net–like precipitation algorithm. Total precipitable water and 2-m temperature from the Global Forecast System (GFS) model are also used as auxiliary inputs to the model. The results show that the U-Net–like algorithm can capture fine-scale patterns and intensity of surface precipitation at high spatial resolution over stratiform and convective precipitation regimes. The evaluations reveal the potential of extracting relevant, high spatial features over complex surface types such as mountainous regions and coastlines. The algorithm allows users to interpret the inputs’ importance and can serve as a starting point for further exploration of precipitation systems within the field of hydrometeorology.

Meteorology & Atmospheric Sciences↗

Development of a triple-moment ice-phase cloud microphysics scheme and its application to the Single Column Atmosphere Model

Parameterization of cloud microphysics is critical for accurate simulation of weather and climate, in which the characteristics of cloud particle spectrum inevitably further affect climate simulation by changing the cloud evolution and cloud radiation effects. The popular currently used double-moment cloud microphysics schemes in numerical models can predict the intercept (N 0 ) and slope (λ) parameters of cloud particle spectrum but cannot predict the spectral shape parameter (μ), which hinders accurate description of cloud physical processes in climate models. Therefore, in the present study, we built upon the ideas of previously developed triple-moment cloud microphysics scheme, considered radar reflectivity factor as the third predictor in addition to number and mass concentration, and introduced its related prediction equation to the Single Column Atmosphere Model Version 5.3 (SCAM5.3). Moreover, the relevant microphysical process formulas in the model were revised, and a triple-moment ice-cloud microphysics scheme was constructed to predict the μ of ice particle spectrum. Based on this model, a 29-day case of the Atmospheric Radiation Measurement Program in the summer of 1997 (ARM97) was simulated, and the differences in cloud fraction and radiation simulations between the double- and triple-moment schemes were analysed. The μ of ice particle spectrum predicted by the triple-moment scheme mainly ranged from 0 to 4; the peak value was around 2, and at least 85% of the μ values were greater than the default 0. Therefore, the μ=0 setting in the double-moment scheme is unreasonable. Moreover, the developed triple-moment ice-cloud microphysics scheme yielded a narrower ice particle spectrum, which was closer to the observation results of previous studies, than the double-moment cloud microphysics scheme (e.g., height=233 hPa). Furthermore, compared with the double-moment scheme, the triple-moment scheme achieved closer simulations of the cloud fraction observations, particularly for ice clouds in the upper levels. Considering the close association between cloud fraction and radiation, the error with the triple-moment scheme was smaller than that with the double-moment scheme regardless of the shortwave (surface downward shortwave radiation, net downward shortwave radiation at the top of the atmosphere, and net shortwave radiation at the surface) or longwave (surface downward longwave radiation and net longwave radiation at the surface) flux density. Finally, the improvement mechanism of the triple-moment scheme on cloud fraction and radiation simulations was explored. The major reason is that the triple-moment scheme weakens the autoconversion of ice crystal to form snow and enhances the growth process of ice crystal deposition, thereby increasing the mass concentration of ice crystals and ice cloud fraction. Overall, the developed triple-moment ice-cloud microphysics scheme can help improve the simulation ability of models for cloud-climate feedback and other processes.

54 ENVIRONMENTAL SCIENCES↗

Crystal structure of the Arabidopsis SPIRAL2 C-terminal domain reveals a p80-Katanin-like domain

Epidermal cells of dark-grown plant seedlings reorient their cortical microtubule arrays in response to blue light from a net lateral orientation to a net longitudinal orientation with respect to the long axis of cells. The molecular mechanism underlying this microtubule array reorientation involves katanin, a microtubule severing enzyme, and a plant-specific microtubule associated protein called SPIRAL2. Katanin preferentially severs longitudinal microtubules, generating seeds that amplify the longitudinal array. Upon severing, SPIRAL2 binds nascent microtubule minus ends and limits their dynamics, thereby stabilizing the longitudinal array while the lateral array undergoes net depolymerization. To date, no experimental structural information is available for SPIRAL2 to help inform its mechanism. To gain insight into SPIRAL2 structure and function, we determined a 1.8 Å resolution crystal structure of the Arabidopsis thaliana SPIRAL2 C-terminal domain. The domain is composed of seven core α-helices, arranged in an α-solenoid. Amino-acid sequence conservation maps primarily to one face of the domain involving helices α1, α3, α5, and an extended loop, the α6-α7 loop. The domain fold is similar to, yet structurally distinct from the C-terminal domain of Ge-1 (an mRNA decapping complex factor involved in P-body localization) and, surprisingly, the C-terminal domain of the katanin p80 regulatory subunit. The katanin p80 C-terminal domain heterodimerizes with the MIT domain of the katanin p60 catalytic subunit, and in metazoans, binds the microtubule minus-end factors CAMSAP3 and ASPM. Structural analysis predicts that SPIRAL2 does not engage katanin p60 in a mode homologous to katanin p80. The SPIRAL2 structure highlights an interesting evolutionary convergence of domain architecture and microtubule minus-end localization between SPIRAL2 and katanin complexes, and establishes a foundation upon which structure-function analysis can be conducted to elucidate the role of this domain in the regulation of plant microtubule arrays.

59 BASIC BIOLOGICAL SCIENCES↗

Prospects for silvicultural enhancement of fire resistance in mesic westside forests of the Pacific Northwest

Increasing wildfire activity in mesic, temperate Pacific Northwest forests west of the Cascade Range crest has stimulated interest in understanding whether alternative forest management practices could reduce risk of stand-replacing fire. To explore how management can enhance fire resistance in these forests and assess tradeoffs among resistance enhancement, carbon sequestration and storage, and economic returns, we conducted 40-year simulations of stand development with BioSum, a framework for conducting landscape analysis with the Forest Vegetation Simulator (FVS), utilizing a statistically representative and spatially balanced sample of Forest Inventory and Analysis (FIA) plots. Simulation outcomes under business-as-usual silviculture were contrasted with fire-aware silviculture, and treatment optimization logic was developed and applied to represent landscape-scale outcomes under business-as-usual and fire-focused management scenarios. Simulation results indicate that fire-aware prescriptions and fire-focused management can meaningfully enhance stand- and landscape-scale fire resistance of westside forests under less than extreme fire weather, but at the cost of lower economic returns and reduced net carbon storage and sequestration over the 40-year analysis window. Shifting from business-as-usual regeneration harvests with short rotations to fire-aware, episodic selection harvest improved fire resistance the most, especially in young privately-owned forests, and with only modest tradeoffs in carbon and economic outcomes. While fire-aware treatments generally reduced net present value from forest operations over business-as-usual, most treatments still generated positive net present value and could be implemented without subsidy. Fire-aware prescriptions that removed and utilized non-merchantable harvest residues instead of burning them, via either pile or broadcast burning, partially mitigated carbon emissions associated with fire-aware treatments, with about the same improvement in fire resistance. Given the currently limited institutional and financial capacity to implement fire resistance enhancing treatments at scale, the insights from this analysis may aid managers seeking to elevate fire resistance to prioritize where and how to manage.

Science & Technology - Other Topics↗

A Novel Framework to Evaluate the Costs and Potential of Bioenergy in Decarbonization of the U.S. Economy

The long-term strategy of the United States targets reaching economy-wide net-zero emissions by 2050 and a carbon-neutral electricity grid by 2035 (U.S. Department of State and U.S. Executive Office of the President, 2021). Meeting these targets would require considerable changes to the energy system. Some key characteristics of illustrative net-zero energy systems include increased penetration of renewable energy and carbon sources, use of CO2 capture and storage (CCS) in hard-to-abate sectors, and a greater role for energy carriers such as electricity and hydrogen (Davis et al, 2018). Another common feature of such energy systems is the need for carbon dioxide removal (CDR) approaches (Horowitz et al, 2022). Across all these characteristics of net-zero energy systems, bioenergy and biomass feedstock is anticipated to play an important role. Biomass feedstock serves as a renewable carbon source. This can enable conversion of such feedstock into fuels and energy carriers for hard-to-abate sectors such as aviation. Indeed, the U.S. Government has a target to meet all jet fuel demand by 2050 from sustainable aviation fuel (SAF), where biofuel pathways are likely to have an important role (EERE, 2020). Bioenergy is also highly versatile with the possibility to convert feedstock into electricity, hydrogen, liquid fuels, heat or high-value products, based on biomass type, demand and technology availability (Clarke et al, 2022). Combination of bioenergy with CCS can also nominally deliver CDR (Fuhrman et al, 2023). As such, the share of bioenergy is expected to grow by at least five time across scenarios studied for the long-term strategy of the U.S. between 2020 and 2050 (Horowitz et al, 2022). Notwithstanding the role of bioenergy in the energy systems, its deployment, costs and scalability are influenced by a number of factors. Some of these factors pertain to policy interventions such as imposition of a binding decarbonization target either at an economy-wide level or the sectoral level. Resource availability and type of biomass feedstock also varies considerably across regions. From a technological perspective, the readiness of bioenergy conversion pathways is subject to high variability. This influences the costs of deployment. Moreover, the sourcing of feedstock, grid carbon intensity, and co-product handling approaches all affect the life cycle efficacy of bioenergy. The latter, in turn, is particularly important in determining the extent to which bioenergy with CCS or BECCS can effectively deliver CDR (Fajardy and Mac Dowell, 2017).

air emission↗

Evaluation of Steam Cycle Upgrades to Improve the Competitiveness of U.S. Coal Power Plants (Final Scientific / Technical Report)

Increasing the competitiveness of the existing pulverized-coal utility fleet in the United States may be achieved by decreasing heat rate, via increases in steam cycle efficiency through upgraded steam temperatures and use of latest technology available in steam turbine and blading design. The average net plant efficiency of the US coal-fired fleet is approximately 33% (HHV). Plant efficiency increases to approximately 41.4% (HHV) at 1,350°F (732°C) steam temperature. However, achieving these Advanced Ultra-Super Critical (AUSC) steam conditions requires the use of advanced high-temperature materials. While there has been a significant amount of DOE-funded materials R&D, most of the related design work has focused on new (greenfield) units, rather than on opportunities to retrofit this advanced technology to the existing utility fleet. If technology, based upon the advanced materials required for AUSC steam conditions, may be applied to the existing fleet, using an economically viable retrofit, a higher capacity factor can be expected as a result of the increased plant competitiveness. The Electric Power Research Institute (EPRI) was awarded a project by the US Department of Energy to examine the technical and economic feasibility of a series of steam cycle upgrades to the two most prevalent types of U.S. coal power plants: 2,400 psig (16.6 MPa) subcritical and 3,500 psig (24.1 MPa) supercritical pulverized coal units. The nine upgrade options that were originally being considered included increasing the main and reheat steam temperatures from 1,000°F (538°C) to 1,100°, 1,200°, and 1,350°F (593°C, 649°C, and 732°C) while holding the steam pressures constant at their original design values, and cases where just the main steam or reheat steam temperatures were increased. The objective was to minimize the modifications required to the existing power plant while still providing a significant improvement in heat rate. The upgrade options assumed that the boiler enclosure envelope remained unchanged from each base case, and that all applicable OEM design guidelines for normal commercial units were imposed. For the highest temperature supercritical case, an option of using a low-pressure molten salt loop to transfer heat from the furnace to the steam was examined. The first major task of the work scope was designed to examine the technical feasibility of various upgrade options, while the subsequent work determined economic viability of the technically feasible upgrade options. Prior to evaluating the effect of these increased temperatures, a “base case” model of a subcritical and supercritical PC boiler was created, which was used for comparative purposes. Upgrade options were evaluated at full-load, part-load and dynamic transient conditions. Once the technical feasibility of each upgrade option was evaluated, the economic value of the heat rate improvement of each feasible option was determined by detailed modeling of unit dispatch in several regional power markets. The dispatch model was used to estimate the amount of revenue from power sales the upgraded unit would receive in comparison to a non-upgraded version of the same power plant. As a parallel task to the dispatch analysis, the capital cost of implementing the upgrades was estimated. The capital cost estimates were then compared to the increased revenue estimated by the dispatch modeling to determine the economic attractiveness of each upgrade option. Several upgrade options were determined to be technically feasible. The net present value (NPV) of the costs for steam cycle upgrades considered in this study ranged from approximately $\$$111 to $\$$130 million. The economic modeling results show that the unit dispatch changes resulting from steam cycle upgrades are relatively small, due largely to heat rate (and operating cost) changes being relatively small. Additionally, the cost of each upgrade exceeds the net revenue increases associated with the upgrade case. Note that the breakeven values are higher for subcritical retrofits, but the capital costs for the subcritical upgrades are also slightly higher. In typical new pulverized coal plants, fuel accounts for approximately 25% of the cost of electricity (COE), while capital costs represent around 50% of the COE. Therefore, in order to improve the heat rate by 4% one can only afford to increase the capital cost by 2%, at the same cost of electricity. The conclusion of this study is that without a cost for emitting CO 2 , it will be difficult to pay for significant efficiency improvements on plants firing low cost coals.

01 COAL, LIGNITE, AND PEAT↗