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DOE OSTI2020

Impact of Miller Cycle Strategies on Combustion Characteristics, Emissions and Efficiency in Heavy-Duty Diesel Engines

This study experimentally investigated the potential of Miller cycle strategies as a means to improve fuel consumption and reduce NO x emissions in heavy-duty diesel engines. The experiments were conducted at constant engine speed, load, and engine-out NO x (1160 rev/min, 1.76 MPa net IMEP, 4.5 g/kWh) on a single cylinder research engine equipped with a fully-flexible hydraulic valve train system. Early Intake Valve Closing (EIVC) and Late Intake Valve Closing (LIVC) timing strategies were compared to a conventional intake valve profile. While the decrease in effective compression ratio associated with the use of Miller valve profiles was symmetric around bottom dead center, the decrease in volumetric efficiency (VE) was not. EIVC profiles were more effective at reducing VE than LIVC profiles. Despite this difference, EIVC and LIVC profiles with comparable VE decrease resulted in similar changes in combustion and emissions characteristics. Miller cycle operation at constant intake pressure resulted in lower peak cylinder pressure, higher exhaust temperatures and lower EGR requirements compared to the baseline case, albeit with a significant fuel consumption penalty. Increasing intake manifold pressure to match the baseline air-fuel ratio overcame the fuel consumption penalty, without compromising NO x emissions. Selected EIVC/LIVC profiles were compared to the baseline condition at three different overall turbocharger efficiencies (n TC ). At the baseline n TC , Miller cycle profiles can lower peak cylinder pressures and increase exhaust temperatures with a minimal penalty in BSFC and FSN. At higher n TC than baseline, Miller cycle can maintain the benefits of lower peak cylinder pressure and higher exhaust temperature without a BSFC or FSN penalty.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Demonstration of Ego Vehicle and System Level Benefits of Eco-Driving on Chassis Dynamometer

Eco-Driving with connected and automated vehicles has shown potential to reduce energy consumption of an individual (i.e., ego) vehicle by up to 15%. In a project funded by ARPA-E, a team led by Southwest Research Institute demonstrated an 8-12% reduction in energy consumption on a 2017 Prius Prime. This was demonstrated in simulation as well as chassis dynamometer testing. The authors presented a simulation study that demonstrated corridor-level energy consumption improvements by about 15%. This study was performed by modeling a six-kilometer-long urban corridor in Columbus, Ohio for traffic simulations. Five powertrain models consisting of two battery electric vehicles (BEVs), a hybrid electric vehicle (HEV), and two internal combustion engine (ICE) powered vehicles were developed. The design of experiment consisted of sweeps for various levels of traffic, penetration of smart vehicles, penetration of technology, and powertrain electrification. The large-scale simulation study consisted of doing approximately 96,000 powertrain simulations. A sophisticated clustering scheme was built and utilized to down select representative traces for each scenario from the simulation study for vehicle testing on a chassis dynamometer. Furthermore, this paper provides a summary of individual ego vehicle testing as well as a comprehensive overview of the method utilized for down selecting representative traces from large scale simulation studies that can be used to quantify corridor level benefits. Vehicle test results along with corresponding analyses are presented.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2017

Impact of uncoordinated plug-in electric vehicle charging on residential power demand - supplementary data

This data set is provided in support of a forthcoming paper: "Impact of uncoordinated plug-in electric vehicle charging on residential power demand," [1]. These files include electricity demand profiles for 200 households randomly selected among the ones available in the 2009 RECS data set for the Midwest region of the United States. The profiles have been generated using the modeling proposed by Muratori et al. [2], [3], that produces realistic patterns of residential power consumption, validated using metered data, with a resolution of 10 minutes. Households vary in size and number of occupants and the profiles represent total electricity use, in watts. The files also include in-home plug-in electric vehicle recharging profiles for 348 vehicles associated with the 200 households assuming both Level 1 (1920 W) and Level 2 (6600 W) residential charging infrastructure. The vehicle recharging profiles have been generated using the modeling proposed by Muratori et al. [4], that produces real-world recharging demand profiles, with a resolution of 10 minutes. [1] M. Muratori, "Impact of uncoordinated plug-in electric vehicle charging on residential power demand." Forthcoming. [2] M. Muratori, M. C. Roberts, R. Sioshansi, V. Marano, and G. Rizzoni, "A highly resolved modeling technique to simulate residential power demand," Applied Energy, vol. 107, no. 0, pp. 465 - 473, 2013. [3] M. Muratori, V. Marano, R. Sioshansi, and G. Rizzoni, "Energy consumption of residential HVAC systems: a simple physically-based model," in 2012 IEEE Power and Energy Society General Meeting. San Diego, CA, USA: IEEE, 22-26 July 2012. [4] M. Muratori, M. J. Moran, E. Serra, and G. Rizzoni, "Highly-resolved modeling of personal transportation energy consumption in the United States," Energy, vol. 58, no. 0, pp. 168-177, 2013.

2009 RECS↗

DOE OSTI2019

DEVELOPING A TRAFFIC SIGNAL ECO-COOPERATIVE ADAPTIVE CRUISE CONTROL SYSTEM FOR BATTERY ELECTRIC VEHICLES

This study developed an eco-driving strategy for battery electric vehicles (BEVs) in the vicinity of signalized intersections, known as BEV Eco-Cooperative Adaptive Cruise Control at Intersections (Eco-CACC-I). The system computes a real-time, energy-optimized vehicle trajectory using a BEV vehicle dynamics and energy consumption model. In the proposed approach, the relationship between vehicle speed, acceleration level, and tractive/resistance forces on the vehicle follows the vehicle dynamics model. The Virginia Tech Comprehensive Power-based Electric Vehicle Energy Consumption Model (VT-CPEM) is used to compute the instantaneous battery energy consumption, with the consideration of battery energy regeneration during braking. The Eco-CACC-I energy-optimum trajectory computation is formulated as an optimization problem with constraints. Considering that the optimization solution needs to be computed at a rapid frequency (e.g., 10 Hz) for real-time applications, an A-star algorithm was used here to expedite the computational speed. Lastly, the proposed BEV Eco-CACC-I system was tested in simulation by considering the impacts of various road grades, speed limits, and signal timings. Simulations for an Internal Combustion Engine Vehicles (ICEVs) was conducted to compare with the BEV test results. The results of the comparison indicate that the energy-optimum solution for BEVs is different from that for ICEVs and thus demonstrating the need for vehicle-tailored optimum trajectories.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Energy Demand Management in Buildings Using PCM-Integrated Wall

The buildings in the United States annually consume nearly 40% of total U.S. energy consumption and approximately 75% of U.S. electricity consumption. Almost half of the total U.S. energy consumption in buildings is attributed to the space conditioning through Heating, Ventilation, and Air Conditioning (HVAC) systems. Utilizing thermal energy storage in buildings, particularly integrating phase change material (PCM) in the walls, has been reported to be an effective method of managing the space heating and cooling loads. This presentation covers an in-depth discussion on the integration of a PCM to building walls, the key conditions required for effective utilization of the PCM, and effect of the PCM transition temperature and the PCM location on energy-saving potential of the PCM-integrated wall.

building↗

DOE OSTI2023

Efficient Air Dehumidification Can Save 15%-50% of Cooling Energy in Commercial Buildings

Current approach to dehumidification in commercial buildings with chilled/hot water AHU systems is to overcool return + supply air to dewpoint, and then reheat before supply to zone. This is energy inefficient, with reheat often being gas-fired. To reduce energy consumption, building operators will often operate at little-to-no outside air, sacrificing IAQ. Decarbonizing commercial buildings requires solutions to reduce and fully electrify dehumidification energy consumption. The Altaire ADAPT and Conservant HEDS systems aim to solve this problem by decoupling humidity control from cooling reduces energy consumption while enabling improved IAQ management.

commercial buildings↗

DOE OSTI2024

Integration of Decentralized Graph-Based Multi-Agent Reinforcement Learning with Digital Twin for Traffic Signal Optimization

Machine learning (ML) methods, particularly Reinforcement Learning (RL), have gained widespread attention for optimizing traffic signal control in intelligent transportation systems. However, existing ML approaches often exhibit limitations in scalability and adaptability, particularly within large traffic networks. This paper introduces an innovative solution by integrating decentralized graph-based multi-agent reinforcement learning (DGMARL) with a Digital Twin to enhance traffic signal optimization, targeting the reduction of traffic congestion and network-wide fuel consumption associated with vehicle stops and stop delays. In this approach, DGMARL agents are employed to learn traffic state patterns and make informed decisions regarding traffic signal control. The integration with a Digital Twin module further facilitates this process by simulating and replicating the real-time asymmetric traffic behaviors of a complex traffic network. The evaluation of this proposed methodology utilized PTV-Vissim, a traffic simulation software, which also serves as the simulation engine for the Digital Twin. The study focused on the Martin Luther King (MLK) Smart Corridor in Chattanooga, Tennessee, USA, by considering symmetric and asymmetric road layouts and traffic conditions. Comparative analysis against an actuated signal control baseline approach revealed significant improvements. Experiment results demonstrate a remarkable 55.38% reduction in Eco_PI, a developed performance measure capturing the cumulative impact of stops and penalized stop delays on fuel consumption, over a 24 h scenario. In a PM-peak-hour scenario, the average reduction in Eco_PI reached 38.94%, indicating the substantial improvement achieved in optimizing traffic flow and reducing fuel consumption during high-demand periods. These findings underscore the effectiveness of the integrated DGMARL and Digital Twin approach in optimizing traffic signals, contributing to a more sustainable and efficient traffic management system.

actuated signal control↗

DOE OSTI2024

Gaining Real-Time Water Leak Detection

Devens Reserve Forces Training Area is a United States Army Reserve (USAR) Installation that struggles with severe water leaks, often causing significant damage to the facility and requiring major renovation. Traditional water use is highly dependent on occupancy, so it can be difficult to benchmark a facility’s water use. It can be exceptionally difficult when occupancy is transient and/or varies. Pacific Northwest National Laboratory (PNNL) collaborated with Devens to implement real-time monitoring of their water consumption by utilizing the smart meter data from their existing 23 water meters. PNNL created a simple algorithm to calculate hourly water consumption and trigger an alert to be instantly emailed to Devens’ personnel when there appears to be a water leak in any building with a smart water meter. Here, this approach is expected to save hundreds of thousands of dollars in unnecessary water consumption costs and damages from leaks and was implemented with little-to-no costs or service disruptions. Next steps for this project include slow leak detection through nighttime monitoring and to extrapolate this water leak approach to the remainder 360 water meters on USAR’s Enterprise Building Control System so USAR sites across the country can be instantly notified of potential water leaks.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Low-Temperature Plasma Assisted Kinetics Study of Ethanol

Abstract: Non- equilibrium plasma assisted kinetics of ethanol at 0.5 atm over a temperature range of 523-1203 K were studied at stoichiometric conditions by using a plasma flow reactor (PFR). The effects of plasma chemistry on fuel and its influence on neutral chemistry is decoupled with both experimental and modelling efforts. Enhanced reactivity was observed experimentally in both plasma-assisted oxidation and pyrolysis cases with fuel consumption beginning at temperatures as low as 523 K. Absolute fuel consumption was observed at temperatures nearly 200 K earlier than pure thermal reactions highlighting the effectiveness of non-equilibrium plasma to promote reactivity. Modelling results illustrated the effect of electron impact reactions towards accelerating fuel consumption and promoting low temperature chemistry by generating excited state N2 and reactive O and OH radicals.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2015

Validating Savings Claims of Cold Climate Zero Energy Ready Homes

This report details the validation methods used to analyze consumption at each of these homes. It includes a detailed end-use examination of consumptions from the following categories: 1) Heating, 2) Cooling, 3) Lights, Appliances, and Miscellaneous Electric Loads (LAMELS) along with Domestic Hot Water Use, 4) Ventilation, and 5) PV generation. A utility bill disaggregation method, which allows a crude estimation of space conditioning loads based on outdoor air temperature, was also performed and the results compared to the actual measured data.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Enabling energy‐efficient manufacturing of pharmaceutical solid oral dosage forms via integrated techno‐economic analysis and advanced process modeling

Abstract The global pharmaceutical industry is a trillion‐dollar market. However, the pharmaceutical sector often lags in manufacturing innovation and automation which limits its potential to maximize energy efficiency. The integration of techno‐economic analysis (TEA) with advanced process models as part of an overarching smart manufacturing platform, can help industries create business models, which can be adapted for manufacturing to reduce energy consumption and operating costs while ensuring product quality which can further enable a more sustainable process operation. In this study, a rational design of experiment on three unit‐operations (wet granulation, drying, and milling) was performed on a batch (case 1) and continuous (case 2) pharmaceutical process to obtain experimental data. Process models for predicting product quality and energy efficiency of each of the three‐unit operations were developed. The experimental data were used to validate the models and good agreement was observed. The energy consumption of each unit operation was calculated using statistical models relating the power consumption and the process parameters. The developed process models and energy models were further integrated into a TEA framework, which quantified the energy and monetary cost of manufacturing for both batch and continuous manufacturing cases. With this integrated framework, energy costs savings of ~33% was obtained in the continuous manufacturing process (case 2) over the batch process (case 1).

Sampat, Chaitanya↗

DOE OSTI2014

Investigation of thermochemical biorefinery sizing and environmental sustainability impacts for conventional supply system and distributed pre-processing supply system designs

The 2011 US Billion-Ton Update estimates that by 2030 there will be enough agricultural and forest resources to sustainably provide at least one billion dry tons of biomass annually, enough to displace approximately 30% of the country's current petroleum consumption. A portion of these resources are inaccessible at current cost targets with conventional feedstock supply systems because of their remoteness or low yields. Reliable analyses and projections of US biofuels production depend on assumptions about the supply system and biorefinery capacity, which, in turn, depend upon economic value, feedstock logistics, and sustainability. A cross-functional team has examined combinations of advances in feedstock supply systems and biorefinery capacities with rigorous design information, improved crop yield and agronomic practices, and improved estimates of sustainable biomass availability. A previous report on biochemical refinery capacity noted that under advanced feedstock logistic supply systems that include depots and pre-processing operations there are cost advantages that support larger biorefineries up to 10 000 DMT/day facilities compared to the smaller 2000 DMT/day facilities. This report focuses on analyzing conventional versus advanced depot biomass supply systems for a thermochemical conversion and refinery sizing based on woody biomass. The results of this analysis demonstrate that the economies of scale enabled by advanced logistics offsets much of the added logistics costs from additional depot processing and transportation, resulting in a small overall increase to the minimum ethanol selling price compared to the conventional logistic supply system. While the overall costs do increase slightly for the advanced logistic supply systems, the ability to mitigate moisture and ash in the system will improve the storage and conversion processes. In addition, being able to draw on feedstocks from further distances will decrease the risk of biomass supply to the conversion facility.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2019

Impacts of intentional mycoplasma contamination on CHO cell bioreactor cultures

Mycoplasma contamination events in biomanufacturing facilities can result in loss of production and costly cleanups. Mycoplasma may survive in mammalian cell cultures with only subtle changes to the culture and may penetrate the 0.2 µm filters often used in the primary clarification of harvested cell culture fluid. Culture cell-based and indicator cell-based assays that are used to detect mycoplasma are highly sensitive but can take up to 28 days to complete and cannot be used for real-time decision making during the biomanufacturing process. To support real-time measurements of mycoplasma contamination, there is a push to explore nucleic acid testing. However, cell-based methods measure growth or colony forming units and nucleic acid testing measures genome copy number; this has led to ambiguity regarding how to compare the sensitivity of the methods. In addition, the high risk of conducting experiments wherein one deliberately spikes mycoplasma into bioreactors has dissuaded commercial groups from performing studies to explore the multiple variables associated with the upstream effects of a mycoplasma contamination in a manufacturing setting. Here we studied the ability of Mycoplasma arginini to persist in a single-use, perfusion rocking bioreactor system containing a Chinese hamster ovary (CHO) DG44 cell line expressing a model monoclonal immunoglobulin G1 (IgG1) antibody. We examined M. arginini growth and detection by culture methods, as well as the effects of M. arginini on mammalian cell health, metabolism, and productivity. We compared process parameters and controls normally measured in bioreactors including dissolved oxygen, gas mix, and base addition to maintain pH, to examine parameter changes as potential indicators of contamination. Our work showed that M. arginini affects CHO cell growth profile, viability, nutrient consumption, oxygen use, and waste production at varying timepoints after M. arginini introduction to the culture. Importantly, how the M. arginini contamination impacts the CHO cells is influenced by the concentration of CHO cells and rate of perfusion at the time of M. arginini spike. Careful evaluation of dissolved oxygen, pH control parameters, ammonia, and arginine over time may be used to indicate Mycoplasma contamination events in biomanufacturing facilities can result in loss of production and costly cleanups. Mycoplasma may survive in mammalian cell cultures with only subtle changes to the culture and may penetrate the 0.2 µm filters often used in the primary clarification of harvested cell culture fluid. Culture cell-based and indicator cell-based assays that are used to detect mycoplasma are highly sensitive but can take up to 28 days to complete and cannot be used for real-time decision making during the biomanufacturing process. To support real-time measurements of mycoplasma contamination, there is a push to explore nucleic acid testing. However, cell-based methods measure growth or colony forming units and nucleic acid testing measures genome copy number; this has led to ambiguity regarding how to compare the sensitivity of the methods. In addition, the high risk of conducting experiments wherein one deliberately spikes mycoplasma into bioreactors has dissuaded commercial groups from performing studies to explore the multiple variables associated with the upstream effects of a mycoplasma contamination in a manufacturing setting. Here we studied the ability of Mycoplasma arginini to persist in a single-use, perfusion rocking bioreactor system containing a Chinese hamster ovary (CHO) DG44 cell line expressing a model monoclonal immunoglobulin G1 (IgG1) antibody. We examined M. arginini growth and detection by culture methods, as well as the effects of M. arginini on mammalian cell health, metabolism, and productivity. We compared process parameters and controls normally measured in bioreactors including dissolved oxygen, gas mix, and base addition to maintain pH, to examine parameter changes as potential indicators of contamination. Our work showed that M. arginini affects CHO cell growth profile, viability, nutrient consumption, oxygen use, and waste production at varying timepoints after M. arginini introduction to the culture. Importantly, how the M. arginini contamination impacts the CHO cells is influenced by the concentration of CHO cells and rate of perfusion at the time of M. arginini spike. Careful evaluation of dissolved oxygen, pH control parameters, ammonia, and arginine over time may be used to indicate Mycoplasma contamination events in biomanufacturing facilities can result in loss of production and costly cleanups. Mycoplasma may survive in mammalian cell cultures with only subtle changes to the culture and may penetrate the 0.2 µm filters often used in the primary clarification of harvested cell culture fluid. Culture cell-based and indicator cell-based assays that are used to detect mycoplasma are highly sensitive but can take up to 28 days to complete and cannot be used for real-time decision making during the biomanufacturing process. To support real-time measurements of mycoplasma contamination, there is a push to explore nucleic acid testing. However, cell-based methods measure growth or colony forming units and nucleic acid testing measures genome copy number; this has led to ambiguity regarding how to compare the sensitivity of the methods. In addition, the high risk of conducting experiments wherein one deliberately spikes mycoplasma into bioreactors has dissuaded commercial groups from performing studies to explore the multiple variables associated with the upstream effects of a mycoplasma contamination in a manufacturing setting. Here we studied the ability of Mycoplasma arginini to persist in a single-use, perfusion rocking bioreactor system containing a Chinese hamster ovary (CHO) DG44 cell line expressing a model monoclonal immunoglobulin G1 (IgG1) antibody. We examined M. arginini growth and detection by culture methods, as well as the effects of M. arginini on mammalian cell health, metabolism, and productivity. We compared process parameters and controls normally measured in bioreactors including dissolved oxygen, gas mix, and base addition to maintain pH, to examine parameter changes as potential indicators of contamination. Our work showed that M. arginini affects CHO cell growth profile, viability, nutrient consumption, oxygen use, and waste production at varying timepoints after M. arginini introduction to the culture. Importantly, how the M. arginini contamination impacts the CHO cells is influenced by the concentration of CHO cells and rate of perfusion at the time of M. arginini spike. Careful evaluation of dissolved oxygen, pH control parameters, ammonia, and arginine over time may be used to indicate mycoplasma contamination in CHO cell cultures in a bioreactor before a read-out from a traditional method.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Life Cycle Analysis of Decentralized Preprocessing Systems for Fast Pyrolysis Biorefineries with Blended Feedstocks in the Southeastern United States

Blending biomass feedstock is an enticing approach to mitigate supply chain risks that are common challenges for large-scale biomass utilization. Understanding the potential environmental benefits of biofuels produced from blended biomass and identifying driving parameters are critical for the supply chain design. Herein, a cradle-to-gate life cycle analysis model for fast pyrolysis biorefineries converting blended feedstocks (pine residues and switchgrass) with traditional centralized and alternative decentralized preprocessing sites, so-called depots, is explained. Different scenarios are developed to investigate the impacts of parameters such as feedstock blending ratios, biorefinery and depot capacities, preprocessing technologies, and allocation methods. The life-cycle energy consumption and global warming potential (GWP) of biofuel production with depots vary between 0.7–1.1 MJ MJ -1 and 43.2–76.6 g CO 2 eq. MJ -1 , respectively. The results are driven by biorefinery processes and depot preprocesses. A decentralized design reduces the energy consumption of the biorefinery but increases the overall life-cycle energy and GWP. Such increases can be significantly mitigated by increasing switchgrass content as the energy consumption at the depot is driven largely by the higher moisture content of pine feedstocks. Allocation methods have a further impact on the results but do not change the major trends and overall conclusions.

09 BIOMASS FUELS↗

DOE OSTI2020

Microwave‐assisted hydrodistillation of the essential oil from Algerian Pimpinella anisum seeds

Abstract Essential oils (EOs) from anise seeds ( Pimpinella anisum ) collected in the Algerian region were extracted by microwave‐assisted hydrodistillation (MAHD) and hydrodistillation (HD). The oil yield (%), chemical composition, energetic consumption and the antimicrobial properties were evaluated of the obtained EO. The yields obtained by both processes were 2.81 ± 0.01% for 90 minutes and 3.30 ± 0.05% for 330 minutes for MAHD and HD, respectively. The determination of the chemical composition of EOs by GC‐MS revealed the presence of a majority compound, trans ‐anethole 81.52% and 91.31% for MAHD and HD, respectively. The other main compounds present in the oils for MAHD and HD were, respectively: methyl chavicol (estragole) (0.63%‐1.39%), cis ‐anethole (0.23%‐0.34%), anisaldehyde (1.1%‐1.57%), anisyl methyl ketone (0.28%‐0.13%), trans ‐methyl isoellgenol (0.31%‐0.17%), γ ‐himachalene (0.5%‐0.36%), trans ‐pseudoisoeugenyl 2‐methylbutyrate (6.53%‐2.53%) and epoxy‐pseudoisoeugenyl 2‐methylbutyrate (2.01%‐0.56%). The EO obtained by MAHD detected other compounds, fenchone 0.41%, limonene 0.68%, cis ‐jasmolacatone extra C 0.41%, trans ‐isolongifolanone 0.2% and α ‐himachalene 0.16%. The energetic consumption by MAHD was significantly less than HD. Theoretical data from mathematical modelling were compared with practical data, and the coefficient of determination was between 0.93 and 0.97. The sensibility of bacterial strains to the essential oil obtained by MAHD is marked relatively to that obtained by HD, and for the sensibility of fungal strains, it was conserved. The MAHD process revealed a good yield of anise seeds EOs while reducing extraction time and energetic consumption. The EO extracted by this process revealed the presence of other compounds while improving antibacterial activity.

Boumahdi, Yamina↗

DOE OSTI2020

Isolation and characterization of lignocellulosic nanofibers from four kinds of organosolv-fractionated lignocellulosic materials

The objective of this research was to investigate the presence of residual lignin in cellulose fibers on the efficiency and energy consumption during nanofibers processing. Four kinds of lignin-containing cellulose nanofibers (LCNFs) from switchgrass, yellow poplar, hybrid poplar, and pine, respectively, were isolated via organosolv fractionation coupling mechanical grinding. Nanofibrils were observed after organosolv fractionation. The details of their morphological features, chemical structures, water retention value (WRV), and thermal degradation characteristics were revealed and compared. Mean diameters of nanofibers separated from switchgrass, yellow poplar, hybrid poplar, and pine were 27.9 nm, 25.4 nm, 24.6 nm, and 21.5 nm, respectively. The presence of lignin for the four types of LCNFs led to a decrease in energy consumption and an increase in WRV, among which pine nanofibers show the best with an average energy consumption of 0.511 kWh/kg and a WRV of 537%. It was also demonstrated that increasing lignin content for LCNFs could contribute to the sample’s thermal stability. In conclusion, exact benefits of residual lignin for nanofiber will facilitate its preparation process and extend its application.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Scavenging dynamics on Guam and implications for invasive species management

Deployment of mouse carcasses laced with acetaminophen has become a common management tool to control invasive brown tree snakes (Boiga irregularis; BTS) on Guam. Additionally, anticoagulant rodenticides may be used to control invasive rats (Rattus spp.) if their populations increase due to predator release in the wake of BTS eradication. However, there has been little research examining how scavengers on Guam could be incidentally exposed to toxicants by scavenging carcasses of animals that die from these population control strategies. Furthermore, there is a limited understanding of how the proliferation of invasive species on Guam has influenced the composition of the scavenger community. We investigated these topics by examining scavenger consumption of mouse, rat, and BTS carcasses on Guam in both a coastal and upland site during the wet (May–Aug 2016) and dry season (Jan–Apr 2017). We documented carcass consumption by 9 species, which scavenged 48% of carcasses. Interactions between season, habitat, and carcass type influenced probability of scavenging, and appeared to be driven by consumption by the two main scavenger species, BTS and cane toads (Rhinella marina), both of which are invasive on Guam. Baiting programs should consider the potential for toxin exposure to land crabs (Coenobita spp., Birgus latro), native species that scavenged at every combination of carcass type, habitat, and season. Altogether, 60% of scavenging events were attributed to species considered pests that are recent introductions to Guam. Invasive species on Guam are the primary scavengers of small vertebrate carrion, suggesting a substantial role in trophic dynamics that extends beyond predation.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2013

The effect of climate change, population distribution, and climate mitigation on building energy use in the U.S. and China

A changing climate will affect the energy system in a number of ways, one of which is through changes in demands for heating and cooling in buildings. Understanding the potential effect of climate on heating and cooling demands must take into account not only the manner in which the building sector might evolve over time - including, for example, movements from rural to urban environments in developing countries - but also important uncertainty about the nature of climate change itself and the growth and movements of populations over time. In this study, we explored the uncertainty in climate change impacts on heating and cooling by constructing estimates of heating and cooling degree days for both a reference (no-policy) scenario and a climate mitigation scenario built from 0.5 degree latitude by 0.5 degree longitude resolution output from three different Global Climate Models (GCMs) and three gridded scenarios of population distribution. The implications that changing climate and population distribution might have for building energy consumption in the U.S. and China were then explored by using the heating and cooling degree days results as inputs to a detailed, building energy model, nested in the long-term global integrated assessment framework, Global Change Assessment Model (GCAM). Across the climate models and population distribution scenarios, the results indicate that unabated climate change would cause total final energy consumption to decrease modestly in both U.S. and China buildings by the end of the century, as decreased heating consumption is more than balanced by increased cooling using primarily electricity. However, the results also indicate that when indirect emissions from the power sector are also taken into account, climate change may have negligible effect on building sector CO2 emissions in the two countries. The variation in results due to variation of population distribution is noticeably smaller than variation due to the use of different climate models.

Zhou, Yuyu↗