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At least 1,369 records · Page 76

Warming of the Willamette River, 1850–present: the effects of climate change and river system alterations

Abstract. Using archival research methods, we recovered and combined data from multiple sources to produce a unique, 140-year record of daily water temperature (Tw) in the lower Willamette River, Oregon (1881–1890, 1941–present). Additional daily weather and river flow records from the 1850s onwards are used to develop and validate a statistical regression model of Tw for 1850–2020. The model simulates the time-lagged response of Tw to air temperature and river flow and is calibrated for three distinct time periods: the late 19th, mid-20th, and early 21st centuries. Results show that Tw has trended upwards at 1.1 ∘C per century since the mid-19th century, with the largest shift in January and February (1.3 ∘C per century) and the smallest in May and June (∼ 0.8 ∘C per century). The duration that the river exceeds the ecologically important threshold of 20 ∘C has increased by about 20 d since the 1800s, to about 60 d yr−1. Moreover, cold-water days below 2 ∘C have virtually disappeared, and the river no longer freezes. Since 1900, changes are primarily correlated with increases in air temperature (Tw increase of 0.81 ± 0.25 ∘C) but also occur due to alterations in the river system such as depth increases from reservoirs (0.34 ± 0.12 ∘C). Managed release of water affects Tw seasonally, with an average reduction of up to 0.56 ∘C estimated for September. River system changes have decreased variability (σ) in daily minimum Tw by 0.44 ∘C, increased thermal memory, reduced interannual variability, and reduced the response to short-term meteorological forcing (e.g., heat waves). These changes fundamentally alter the response of Tw to climate change, posing additional stressors on fauna.

54 ENVIRONMENTAL SCIENCES↗

Performance of Convection-Permitting and Convection-Parameterized Models in Reproducing the Extreme Precipitation Intensity Relationship with Surface Conditions

Here, this study investigates the warm-season extreme precipitation–temperature scaling relationship in CONUS404, a convection-permitting (4 km) Weather Research and Forecasting (WRF) Model simulation over the conterminous United States for the past four decades, and compares it with the WRF-Thermodynamic Global Warming (WRF-TGW) historical simulation at a coarser resolution (12 km) using parameterized convection. We also analyze the NCEP stage IV and NASA Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (IMERG) datasets as observational benchmarks. We examine how extreme precipitation intensity (EPI) varies with temperature and saturation deficit over representative regions based on hourly data. The stage IV and IMERG data show a similar pattern of EPI variation with temperature and saturation deficit, except that the EPI peak is lower in IMERG than in stage IV. Under dry and hot conditions, EPI decreases too rapidly with elevated saturation deficit in both CONUS404 and WRF-TGW compared to observations, but the performance of CONUS404 is superior to WRF-TGW. When the near-surface atmosphere is saturated or close to saturated, both CONUS404 and WRF-TGW produce higher peak values of EPI relative to the observational references; IMERG exhibits scaling rates close to the Clausius–Clapeyron (C–C) relationship, while CONUS404, WRF-TGW, and stage IV all demonstrate super-C–C scaling behaviors. Despite marked warming over the past four decades, in both CONUS404 and WRF-TGW, the scaling relationship between EPI and temperature in a saturated atmosphere remains stable and robust. This indicates a strong potential for the EPI–temperature scaling rate under saturation to be used as an emergent constraint in reducing uncertainties of future extreme precipitation projection.

Atmosphere↗

Technical and economic feasibility of an integrated ethanol and anthocyanin coproduction process using purple corn stover

The coproduction of high-value anthocyanin extract in the cellulosic ethanol process would diversify the co-product market, increase revenue, and potentially improve the economics of the process. The high anthocyanin concentration in the cob and structural carbohydrates in residual stover make purple corn stover an attractive source for anthocyanin and ethanol coproduction. In this study, we aimed to develop simulation models for processes integrating ethanol production and anthocyanin extraction using purple corn stover, to evaluate their techno-economic feasibility, and to compare their performance with the conventional ethanol production process using corn stover. The annual ethanol production for plants processing 2000 MT dry feedstock / day was 148.6 million L/year for the integrated processes compared with 222.6 million L/year for the conventional process. Anthocyanin production in the modified processes using dilute acid-based and water-based anthocyanin extraction processes was 1779 and 1099 MT/year, respectively. Capital investments for the integrated processes ($\$448.1$ to $\$443.8$ million) were higher than the conventional process ($\$371.9$ million). Due to high revenue from anthocyanin extract, the ethanol production cost for the integrated process using acid-based anthocyanin extraction ($\$0.36$/L) was 34.5% lower than conventional ethanol production ($\$0.55$/L). The ethanol production cost for the integrated process using water-based anthocyanin extraction ($\$0.68$/L) was higher than conventional ethanol production due to low ethanol and anthocyanin yields. The minimum ethanol selling price for the integrated process using acid-based anthocyanin extraction ($\$0.65$/L) was also lower than the conventional process ($\$0.72$/L), indicating an improvement in economic performance.

09 BIOMASS FUELS↗

Boosting the Oxygen Reduction Performance via Tuning the Synergy between Metal Core and Oxide Shell of Metal−Organic Frameworks‐Derived Co@CoO x

Abstract Co core@Co oxide shell (Co@CoO x ) catalysts represent a large family with promising oxygen reduction reaction (ORR) catalytic activity. However, inadequate understanding of Co@CoO x synergy prohibits further pursuit of catalytic performance enhancement. Herein, a Co zeolitic−imidazolate framework was converted into metallic Co, followed by controlled air treatment to form Co@CoO x . The composition and structure evolution as a function of air treatment temperature were studied thoroughly through conventional and synchrotron (both ex‐situ and in‐situ) characterizations, confirming the coexistence of CoO and Co 3 O 4 in the shell. The optimal catalyst showed an ORR half‐wave potential of 0.87 V (vs. RHE) in an alkaline half‐cell and delivered high discharge capacity in an aprotic Li−O 2 battery (7,124 mAh g Cat+C −1 ) and an aqueous Zn−air battery (694 mAh g Zn −1 ) with good performance retention after durability test. Modeling simulation and density functional theory calculation confirmed the charge donation from metal core to oxide shell and shed light on new insights of how metal@metal oxide synergy impacted the ORR via tuning the charge conductivity, oxygen affinity and intermediate transfer pathway. This work opens up a venue to boost ORR catalytic activity from an interfacial synergy perspective.

Wang, Hao↗

Carbon budget of the Harvard Forest Long-Term Ecological Research site: pattern, process, and response to global change

How, where, and why carbon (C) moves into and out of an ecosystem through time are long-standing questions in biogeochemistry. Here, we bring together hundreds of thousands of C-cycle observations at the Harvard Forest in central Massachusetts, USA, a mid-latitude landscape dominated by 80–120-yr-old closed-canopy forests. These data answered four questions: (1) where and how much C is presently stored in dominant forest types; (2) what are current rates of C accrual and loss; (3) what biotic and abiotic factors contribute to variability in these rates; and (4) how has climate change affected the forest’s C cycle? Harvard Forest is an active C sink resulting from forest regrowth following land abandonment. Soil and tree biomass comprise nearly equal portions of existing C stocks. Net primary production (NPP) averaged 680–750 g C·m –2 ·yr –1 ; belowground NPP contributed 38–47% of the total, but with large uncertainty. Mineral soil C measured in the same inventory plots in 1992 and 2013 was too heterogeneous to detect change in soil-C pools; however, radiocarbon data suggest a small but persistent sink of 10–30 g C·m –2 ·yr –1 . Net ecosystem production (NEP) in hardwood stands averaged ~300 g C·m –2 ·yr –1 . NEP in hemlock-dominated forests averaged ~450 g C·m –2 ·yr –1 until infestation by the hemlock woolly adelgid turned these stands into a net C source. Since 2000, NPP has increased by 26%. For the period 1992–2015, NEP increased 93%. The increase in mean annual temperature and growing season length alone accounted for ~30% of the increase in productivity. Interannual variations in GPP and NEP were also correlated with increases in red oak biomass, forest leaf area, and canopy-scale light-use efficiency. Compared to long-term global change experiments at the Harvard Forest, the C sink in regrowing biomass equaled or exceeded C cycle modifications imposed by soil warming, N saturation, and hemlock removal. Furthermore, the results of this synthesis and comparison to simulation models suggest that forests across the region are likely to accrue C for decades to come but may be disrupted if the frequency or severity of biotic and abiotic disturbances increases.

54 ENVIRONMENTAL SCIENCES↗

Trade-offs of forest management scenarios on forest carbon exchange and threatened and endangered species habitat

Management of forest lands under climate warming poses challenges to managers, some of which are difficult to predict. Examining the trade-offs associated with forest stewardship choices is essential to avoid consequences with loss of natural capital. We utilized LANDIS-II process model simulations for three forested sites located in disparate parts of the United States with the purpose of understanding the trade-offs imposed by management choices under climate warming and associated wildfire. There were only small trade-offs that emerged from the simulations, between habitat area for threatened and endangered species (TES), net ecosystem exchange for CO2 (NEE), and risk of wildfire. Stand management in the form of thinning and prescribed burning typically increased NEE while simultaneously increasing habitat for TES, while reducing the risk of wildfire. These benefits were also observed under a climate warming scenario; however, the benefits were greatly outweighed by the negative impacts f warming on both TES habitat and NEE. Balancing these ecosystem services via thinning and burning treatments is a strategic approach to mitigate risks of wildfire both currently and under a warming future climate.

54 ENVIRONMENTAL SCIENCES↗

Machine Learning Techniques for Data Reduction of Climate Applications

Scientists conduct large-scale simulations to compute derived quantities-of-interest (QoI) from primary data. Often, QoI are linked to specific features, regions, or time intervals, such that data can be adaptively reduced without compromising the integrity of QoI. For many spatiotemporal applications, these QoI are binary in nature and represent presence or absence of a physical phenomenon. We present a pipelined compression approach that first uses neural-network-based techniques to derive regions where QoI are highly likely to be present. Then, we employ a Guaranteed Autoencoder (GAE) to compress data with differential error bounds. GAE uses QoI information to apply low-error compression to only these regions. This results in overall high compression ratios while still achieving downstream goals of simulation or data collections. Experimental results are presented for climate data generated from the E3SM Simulation model for downstream quantities such as tropical cyclone and atmospheric river detection and tracking. These results show that our approach is superior to comparable methods in the literature.

Li, Xiao [University of Florida]↗

Maximizing ENSO as a source of western US hydroclimate predictability

Abstract Until recently, the El Niño–Southern Oscillation (ENSO) was considered a reliable source of winter precipitation predictability in the western US, with a historically strong link between extreme El Niño events and extremely wet seasons. However, the 2015–2016 El Niño challenged our understanding of the ENSO-precipitation relationship. California precipitation was near-average during the 2015–2016 El Niño, which was characterized by warm sea surface temperature (SST) anomalies of similar magnitude compared to the extreme 1997–1998 and 1982–1983 El Niño events. We demonstrate that this precipitation response can be explained by El Niño’s spatial pattern, rather than internal atmospheric variability. In addition, observations and large-ensembles of regional and global climate model simulations indicate that extremes in seasonal and daily precipitation during strong El Niño events are better explained using the ENSO Longitude Index (ELI), which captures the diversity of ENSO’s spatial patterns in a single metric, compared to the traditional Niño3.4 index, which measures SST anomalies in a fixed region and therefore fails to capture ENSO diversity. The physically-based ELI better explains western US precipitation variability because it tracks the zonal shifts in tropical Pacific deep convection that drive teleconnections through the response in the extratropical wave-train, integrated vapor transport, and atmospheric rivers. This research provides evidence that ELI improves the value of ENSO as a predictor of California’s seasonal hydroclimate extremes compared to traditional ENSO indices, especially during strong El Niño events.

54 ENVIRONMENTAL SCIENCES↗

Phosphorus recycling by mineral-catalyzed ribonucleotide cleavage on iron and manganese oxides

Abstract Phosphorus is an essential element influencing both food security via plant fertilization, and water pollution through excessive phosphorus use, yet the phosphorus cycle in ecosystems is poorly known. In particular, beyond adsorption, the role of iron and manganese oxides in catalyzing the abiotic dephosphorylation of biomolecules is debated. Here, we studied the reactions of ribonucleotides, containing different phosphate bonding, with goethite, hematite, and birnessite. We employed both high-resolution mass spectrometry of solution species and molecular modeling simulations of ribonucleotide-mineral complexes. Results disclose an up to fivefold preferential hydrolytic cleavage of a phosphoanhydride bond over a phosphoester bond, indicating that mineral-catalyzed reactions reflect the hierarchy reported for the activity of phosphatase enzymes. The fourfold higher catalytic reactivity of goethite and birnessite versus hematite is explained by mineral-specific binding rather than surface area differences. Corresponding simulated adsorbate conformations at the water–mineral interfaces are proposed. Overall, our findings provide new insights on the catalytic recycling of organic phosphorus species by mineral oxides.

58 GEOSCIENCES↗

Climate science to inform adaptation policy: Heat waves over India in the 1.5°C and 2°C warmer worlds

Developing a better scientific understanding of anthropogenic climate change and climate variability, especially the prediction/projection of climate futures with useful temporal and geographical resolution and quantified uncertainties, and using that knowledge to inform adaptation planning and action will become crucially important in the coming years. Generating such policy-relevant knowledge may be particularly important for developing countries such as India. It is with this backdrop that, in this paper, we analyze future heat waves in India by using observations and a large number of model simulations of historical, + 1.5 °C, and + 2.0 °C warmer worlds. In both the future scenarios, there is an increased probability of heat waves during June and July when the Indian monsoon is in full swing and humidity is high, which makes the heat events even more of a health risk. While the highest temperatures in heat waves may not increase much in future climates, the duration and areal extent of the heat waves will most likely increase, leading to the emergence of new heat wave-prone zones in India. The results indicate that the joint frequencies of the longest duration and large area events could be nearly threefold greater in the + 1.5 °C and fivefold greater in the + 2.0 °C future scenarios compared to historical simulations. Thus, overall, the study indicates a substantial increase in the risk of heat events that typically elicit warnings from forecasters. The likely widespread and persistent nature of heat wave events in the future, as revealed by this study, will require planning and adaptation measures beyond the short-term disaster planning frameworks currently in place. Exploring what these measures might look like is beyond the scope of this study, but it underlines the importance of developing climate knowledge with high temporal and geographical resolution capable of informing adaptation policy and planning.

+1.5 °C and +2.0 °C↗

Multi-segment Winding Application for Axial Short Circuit Force Reduction Under Tap Changer Operation in HTS Transformers

High-temperature superconducting (HTS) transformers have remarkable appealing advantages over conventional ones. But higher brittleness of HTS windings with respect to copper windings makes HTS transformers more vulnerable in short circuit and inrush current situations. During tap changer operation, appreciable asymmetry and non-uniform distribution of ampere-turn along the windings causes high axial component of short circuit forces and makes the situation more severe. In this paper, multi-segment winding method is employed for reduction of axial short circuit forces. An analytical method is presented for calculation of axial component of short circuit forces under tap changer operation. Analytical method shows that with utilizing HLHLHLH asymmetrical multi-segment windings, during tap changer operation, the axial component of short circuit forces reduces significantly. The results of the analytical method are compared with the results of finite element method (FEM) model simulations, and the consistency is demonstrated.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Characterization of Fe-6Si Soft Magnetic Alloy Produced by Laser-Directed Energy Deposition Additive Manufacturing

Abstract Commercial electrical steels, Fe-Si alloys with < 4 wt.% Si, are inexpensive and efficient materials for electrical power conversion. Further efficiency improvements require increasing the silicon concentration to 6 wt.%, at which point the material becomes brittle and difficult to form by conventional rolling and sheet fabrication methods. Additive manufacturing stands to overcome challenges with commercial manufacturing techniques by leveraging near-net-shape fabrication. The wide array of process conditions provides additive manufacturing with increased flexibility, enabling control over the microstructure and mechanical properties. This work explores the microstructures and magnetic properties of ring-shaped Fe-Si alloys produced using concentric and cross-hatch tool paths on a laser-directed energy deposition additive manufacturing system. Concentric-built samples exhibit elongated grain structures while cross-hatch-built samples comprise lower aspect ratio grain structures. Thermal finite element analysis simulations model the stress conditions produced by the different scan path geometries. Microhardness measurements probe the mechanical properties as a function of anneal temperature, providing a qualitative understanding of the intergranular defect density. Soft magnetic properties measured under quasistatic and AC conditions show frequency- and microstructure-dependent coercivity and permeability. Finally, analysis of the core loss quantifies how the build strategies and thermal treatments influence efficiency in electrical power conversion applications. Understanding the influences of scan path geometry and thermal treatment provides a pathway towards application of additively manufactured soft magnetic materials.

Adamczyk, Jesse M.↗

Reassessing the Climate Change Narrative

Abstract We note that the atmosphere has distinct tropical and extratropical regimes. The tropical regime is significantly dependent on the greenhouse effect and is characterized by temperatures that are largely horizontally homogenized. The extratropical regime is dominated by large scale unstable convective eddies that transport heat between the tropics and the poles (leaving the poles warmer than they otherwise would be) and serve to determine the temperature difference between the tropics and the poles. Changes in tropical temperature and in the tropics-to-pole temperature difference both contribute to changes in global mean temperature. It turns out that changes in global mean temperature associated with major climate change (i.e., the last glacial maximum and the warm period of the Eocene about 50 million years ago) were associated primarily with changes in the tropics-to-pole temperature differences. By contrast, changes in global mean temperature over the past 150 years or so are almost entirely associated with changes in tropical temperature. Thus, there is no intrinsic amplification associated with a change in the tropics-to-pole temperature difference. However, model simulations of climate behave differently from both observations and from each other. In particular, they all show more significant contributions for the tropics-to-pole temperature difference – sometimes much more significant. They also show excessive tropical warming.

Meteorology & Atmospheric Sciences↗

Shortened Duration of Global Warming Slowdowns with Elevated Greenhouse Gas Emissions

Continuous emissions of anthropogenic greenhouse gases (GHGs) and aerosols in the last 160 years have resulted in an increasing trend of global mean surface temperatures (GMSTs). Due to interactions with natural variability, rates of the combined anthropogenically and naturally induced warming trends are characterized by significant slowdowns and speedups on decadal timescales. In this work, by analyzing observed and model-simulated data, we investigate how the duration of these episodes will change with different strengths of GHG and aerosol forcing. We found that the duration of warming slowdowns can be more than 30 yr with a slower rate of anthropogenic emissions but would shorten to about 5 yr with a higher one. This duration reduction depends on both the magnitude of the climate response to anthropogenic forcing and the strength of the internal variability. Moreover, the warming slowdowns can still occur even towards the end of this century under high emissions scenarios but with significantly shortened duration.

54 ENVIRONMENTAL SCIENCES↗

Sensitivity Analysis of an Electrospray Dehumidification System

Electrically enhanced condensation achieved by an electrospray system can enhance dehumidification in HVAC applications if successfully scaled up. The first step towards scale-up is identifying critical design and operating parameters that significantly impact dehumidification for the electrospray system. Sensitivity analysis is one approach for identifying critical parameters. This paper presents a methodology that can efficiently perform quantitative sensitivity analysis on a computationally expensive high fidelity simulation model, which is a computational fluid dynamics (CFD) model of the electrospray system. The methodology employs surrogate modeling and Sobol sensitivity analysis. We estimate the main and total effect Sobol sensitivity indices of four operating parameters of the electrospray system. The results reveal that the most important parameter is the size of the sprayed droplets, followed by the volumetric flow rate of the bulk air and injected water in the system. The water injection velocity of the spray was found to have little to no impact on dehumidification.

Young, David↗

Feature extraction for subtle anomaly detection using semi-supervised learning

The demand for automated and effective monitoring techniques has soared with the increased digitization of industrial monitoring systems. State-of-the-art machine learning methods are effectively detecting abrupt changes in system states. However, these methods lack comparable maturity in detecting subtle changes that may be signs of incipient faults. This manuscript argues that the current anomaly detection methods can be enhanced by exploring weak patterns to enable subtle variation detection. Specifically, the concept of semi-supervised learning is employed, with labels representing knowledge about some anomalous conditions of a system. The basic idea is to extract a candidate set of weak patterns discarded by state-of-the-art baselining algorithms. With few labeled anomalous data, the algorithm selects the weak patterns and allows for their possible fusion using the highest sensitivity to the labeled anomalies. Here, the method’s applicability is demonstrated using a representative pressurized water reactor (PWR) model simulated by Dymola.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Fuel performance analysis of Cr-coated Zircaloy-4 cladding during a prototypical LOCA event using BISON

Here, deformation and failure of chromium (Cr) coated Zircaloy-4 (Zry-4) were studied in loss-of-coolant accident (LOCA) conditions using the BISON fuel performance code. The BISON validation model simulating Halden research reactor experiments was extended to include Cr coatings and higher rod internal pressures to simulate high-burnup fuel. The transient simulations show Cr coatings help relieve stress in the Zry-4 substrate during the transient, delaying the onset of high-temperature creep, which leads to ballooning and bursting of the cladding. A nominal Cr coating thickness of 30 µm delays clad failure by 26 seconds and increases the clad burst temperature by 40 K. A parametric study showed that time to failure and burst temperature both increase with coating thickness, and Cr-coated cladding offers burst resistance under a wide range of rod internal pressures simulating high-burnup fuel. Results indicate that a thin Cr coating provides resistance against ballooning and bursting of cladding during LOCA events.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Bioalcohol production from acidogenic products via a two-step process: A case study of butyric acid to butanol

This article presents the full study (lab-scale experimental study and large-scale techno-economic analysis) results of a two-step catalytic process for the conversion of organic waste–derived butyric acid to butanol. Butanol from biomass resources like organic waste promise to become an attractive and sustainable fuel and industrial precursor due to an increase in greenhouse gas content in the atmosphere. Therefore, research in this field is important for energy applications and reduction in greenhouse gas emissions. In this regard, a two-step process was applied in this study to produce butanol from butyric acid that can potentially be derived from organic waste. The two-step process consists of the (1) esterification of butyric acid to methyl butyrate and (2) hydrogenolysis of this methyl butyrate to butanol. The first reaction, esterification of butyric acid, was optimized using carbon-based catalysts. The production of butanol from methyl butyrate via hydrogenolysis was investigated using bimetallic Pt–Co catalysts. The hydrogenolysis of methyl butyrate on these catalysts under optimal conditions of 250 °C, 5 MPa H 2 , and a feed/catalyst weight ratio of 11.2 led to 54.1% selectivity toward 1-butanol. Based on the experimental results, an integrated process simulation model was developed to determine the economic potential of the two-step production of butanol from butyric acid. Using this model, the techno-economic feasibility of the two-step process was analyzed. Here, the minimum selling price (MSP) of 1-butanol produced from butyric acid using this process was US dollars 3.388 per gallon of gasoline equivalent (GGE). This MSP is in the range of recent biofuel market prices of US dollars 2.03/GGE to US dollars 3.83/GGE.

09 BIOMASS FUELS↗