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At least 235 records · Page 13

Nitrogen dynamics and physiological N use efficiency in high‐biomass sorghum

Improving nitrogen (N) efficiency is essential for sustainable high-biomass sorghum ( Sorghum bicolor L. Moench) production. This study evaluated leaf and stem N dynamics, canopy N remobilization, and physiological nitrogen use efficiency (pNUE) in two photoperiod-sensitive sorghum hybrids under two N rates (0 and 168 kg-N ha −1 ) across multiple environments in Texas and Illinois. Leaf N concentrations increased with plant height in the canopy with steeper gradients under low-N conditions, indicating enhanced N remobilization when N is limited. Stem tissue showed less variation in N concentration across canopy nodal positions, with within-plant differences ranging from 1.2 to 7.6 g kg −1 , compared to 3.1 to 16.3 g kg −1 in leaves. While pNUE was generally higher under unfertilized conditions, it varied largely by site; however, genotypic differences were minimal within the given year. These results highlight the importance of integrating environmental and management factors into breeding and fertilization strategies to enhance N efficiency in high-biomass sorghum.

60 APPLIED LIFE SCIENCES↗

DarkNESS: A skipper-CCD nanosatellite for dark matter searches

The Dark matter Nanosatellite Equipped with Skipper Sensors (DarkNESS) deploys a recently developed skipper-CCD architecture with sub-electron readout noise in low Earth orbit (LEO) to investigate potential signatures of dark matter (DM). The mission addresses two interaction channels: electron recoils from strongly interacting sub-GeV DM and X-rays produced through decaying DM. Orbital observations avoid attenuation that limits ground-based measurements, extending sensitivity reach for both channels. The mission proceeds toward launch following laboratory validation of the instrument. A launch opportunity has been secured through Firefly Aerospace’s DREAM 2.0 program, awarded to the University of Illinois Urbana-Champaign (UIUC). As a result, this will constitute the first use of skipper-CCDs in space and evaluate their suitability for low-noise X-ray and single-photon detection in future space observatories.

Alpine, Phoenix [University of Illinois, Urbana-Ch↗

Soil fertility management for sustainable Miscanthus × giganteus production: Increased tiller weight from nitrogen management explains yield gains in aged miscanthus

Aging-related yield decline in Miscanthus × giganteus (miscanthus) remains a major constraint to sustainable biomass production. This study evaluated how nitrogen (N) management and soil fertility influence yield-component traits and productivity in aging miscanthus. Trials were conducted at two sites established in 2008 at the University of Illinois Energy Farm, Urbana, IL. (i) The Sun Grant trial received 0, 60, and 120 kg N ha −1 annually until 2015. Starting 2021, half of each plot received 60 or 120 kg N ha −1 , resulting in six legacy-contemporary treatments: 0N–0N, 0N–120N, 60N–0N, 60N–60N, 120N–0N, 120N–120N. (ii) The Energy Farm trial remained unfertilized until 2014, when one half of each plot received 56 kg N ha −1 , forming two treatments: 0N–0N, 0N–56N. Sun Grant trial results showed N fertilization increased tiller density (tillers m −2 ) and tiller weight (g tiller −1 ) in juvenile to early-mature miscanthus (2011–2015). After N withdrawal, both traits declined (20 % and 40 %), though legacy effects persisted in tiller weight in the aging stands (2020–2023). Contemporary N had little effect on tiller density but increased tiller weight by 34 %–77 %, resulting in 23 %–106 % higher machine-harvested biomass yield in 0–120N, 60-60N, and 120-120N plots. At the Energy Farm trial, 0N–56N plots yielded 59 %–108 % more biomass than 0N–0N. Soil total N increased (Sun Grant: 47 % by 2020; Energy Farm: 58 % by 2023), while Mehlich-3 P (42 %–44 %) and K (21 %–46 %) declined. These findings identify tiller weight as a key determinant of biomass yield in aging miscanthus and highlight the need for P and K management for long-term productivity.

09 BIOMASS FUELS↗

DarkNESS: A skipper-CCD NanoSatellite for Dark Matter Searches

The Dark matter Nanosatellite Equipped with Skipper Sensors (DarkNESS) deploys a recently developed skipper-CCD architecture with sub-electron readout noise in low Earth orbit (LEO) to investigate potential signatures of dark matter (DM). The mission addresses two interaction channels: electron recoils from strongly interacting sub-GeV DM and X-rays produced through decaying DM. Orbital observations avoid attenuation that limits ground-based measurements, extending sensitivity reach for both channels. The mission proceeds toward launch following laboratory validation of the instrument. A launch opportunity has been secured through Firefly Aerospace's DREAM 2.0 program, awarded to the University of Illinois Urbana-Champaign (UIUC). This will constitute the first use of skipper-CCDs in space and evaluate their suitability for low-noise X-ray and single-photon detection in future space observatories.

Alpine, Phoenix [Illinois U., Urbana (main)] (ORCI↗

Agent-Based Model of Combined Community- and Jail-Based Take-Home Naloxone Distribution

Importance Opioid-related overdose accounts for almost 80 000 deaths annually across the US. People who use drugs leaving jails are at particularly high risk for opioid-related overdose and may benefit from take-home naloxone (THN) distribution. Objective To estimate the population impact of THN distribution at jail release to reverse opioid-related overdose among people with opioid use disorders. Design, Setting, and Participants This study developed the agent-based Justice-Community Circulation Model (JCCM) to model a synthetic population of individuals with and without a history of opioid use. Epidemiological data from 2014 to 2020 for Cook County, Illinois, were used to identify parameters pertinent to the synthetic population. Twenty-seven experimental scenarios were examined to capture diverse strategies of THN distribution and use. Sensitivity analysis was performed to identify critical mediating and moderating variables associated with population impact and a proxy metric for cost-effectiveness (ie, the direct costs of THN kits distributed per death averted). Data were analyzed between February 2022 and March 2024. Intervention Modeled interventions included 3 THN distribution channels: community facilities and practitioners; jail, at release; and social network or peers of persons released from jail. Main Outcomes and Measures The primary outcome was the percentage of opioid-related overdose deaths averted with THN in the modeled population relative to a baseline scenario with no intervention. Results Take-home naloxone distribution at jail release had the highest median (IQR) percentage of averted deaths at 11.70% (6.57%-15.75%). The probability of bystander presence at an opioid overdose showed the greatest proportional contribution (27.15%) to the variance in deaths averted in persons released from jail. The estimated costs of distributed THN kits were less than $\$$15 000 per averted death in all 27 scenarios. Conclusions and Relevance This study found that THN distribution at jail release is an economical and feasible approach to substantially reducing opioid-related overdose mortality. Training and preparation of proficient and willing bystanders are central factors in reaching the full potential of this intervention.

Tatara, Eric [Argonne National Laboratory (ANL), A↗

Artificial neural networks estimate evapotranspiration for Miscanthus × giganteus as effectively as empirical model but with fewer inputs

Estimating actual evapotranspiration (ET) is particularly crucial for addressing how vegetation affects the water balance of ecosystems. ET estimation can be complex with empirical models due to their many parameters and reliance on aridity. In contrast, artificial neural networks (ANNs) could potentially estimate ET with fewer and more common meteorological parameters. In this study, we trained two ANNs, one using a feed-forward approach (FFN) and the other a nonlinear auto-regressive network (NARX), to predict ET and compared them to the commonly used empirical model Granger and Gray (GG). We trained our models on a nine-year eddy covariance (EC) dataset for Miscanthu s × giganteus ( M . × giganteus ) from Illinois (UIEF), then tested them using out-of-sample data from both UIEF and a different location in Iowa (SABR) to compare the accuracy of FFN, NARX, and GG models in estimating daily ET. A combination of air temperature (T a ) and solar radiation (R s ) was chosen as inputs due to the highest R 2 for FFN (R 2 = 0.79, 0.81, and 0.79 for training, testing, and validation, respectively) and only T a for NARX (R 2 = 0.70 for out-of-sample validation). The predictive power of the FFN model was superior to the NARX and GG models at the UIEF site (R 2 = 0.84, 0.70, and 0.83 for out-of-sample validation, respectively). Our analysis showed that ANN approaches are as accurate as empirical approaches for estimating ET but use fewer inputs.

54 ENVIRONMENTAL SCIENCES↗

Revenue-Maximizing Shared Parking and Electric Vehicle Charging Management in Multi-Unit Dwellings

In urban areas, searching for parking and electric vehicle (EV) charging can result in cruising, congestion, and environmental externalities. Recognizing the business opportunity of offering private parking and charging infrastructure access within multi-unit dwellings (MUDs) during daytime, we model a shared parking and EV charging management system. We maximize the revenue of MUD charging hubs in mixed land use, catering to public demand. Our approach accounts for the objectives of the two stakeholders involved: a demand model is fitted on the choices of EV charging users, and the supply model optimizes the allocation of parking and charging requests in an MUD parking lot. A binary integer linear programming model for the allocation of parking and charging spaces with a rolling horizon is integrated with matching rules that handle both parking and charging requests. In our numerical experiments in a neighborhood of Chicago, Illinois, we estimate the performance of the MUD parking and charging system with metrics that include revenue, number of matchings, and utilization rates. At any given time, MUDs with lower prices attract more charging requests, particularly those of longer duration, resulting in higher revenue and greater charging utilization. Dynamic pricing facilitates a more equitable distribution of requests; as MUD parking lots reach capacity and their fees increase, other MUDs become more competitive, attracting additional requests. Comparing our method against first-come-first-served and optimal-solution benchmarks, we demonstrate our model’s effectiveness in dynamically managing mixed parking and charging demand in MUD charging hubs.

electric vehicle, multi-unit dwelling, charging in↗

GEOPHIRES Simulations for Deep Direct Use (DDU) Projects

This folder contains the GEOPHIRES codes and input files for running the base case scenarios for the six deep direct-use (DDU) projects. The six DDU projects took place during 2017-2020 and were funded by the U.S. Department of Energy Geothermal Technologies Office. They investigated the potential of geothermal deep direct-use at six locations across the country. The projects were conducted by Cornell University, West Virginia University (WVU), University of Illinois (U of IL), Sandia National Laboratory (SNL), Portland State University (PSU), and National Renewable Energy Laboratory (NREL). Four projects (Cornell, WVU, U of IL, SNL) investigated geothermal for direct heating of a local campus or community, the project by PSU considered seasonal subsurface storage of solar heating, and the NREL project investigated geothermal heating for turbine inlet cooling using absorption chillers. To allow comparison of techno-economic results across the six DDU projects, GEOPHIRES simulations were set up and conducted for each project. The GEOPHIRES code was modified for each project to simulate the local application and incorporate project-specific assumptions and results such as reservoir production temperature or financing conditions. The base case input file is included which simulates the base case conditions assumed by each project team. The levelized cost of heat (LCOH) is calculated and matches the base case LCOH reported by the project teams.

15 GEOTHERMAL ENERGY↗

Prairie State Generating Company Site: Storage Field Development Plan

This Storage Field Development plan presents the Storage Complex characterization results, construction, monitoring, operational plans, and costs associated with the proposed Prairie State Energy Campus - Carbon Capture and Storage (PSEC-CCS) project in Washington County, Illinois, near Marissa. The proposed storage complex, known as the St. Peter-Everton Storage Complex, comprises the St. Peter Sandstone and Everton sandstone reservoirs, with the Maquoketa Shale serving as the primary confining unit and the Knox Group as lower confining unit. The lowermost Underground Source of Drinking Water (USDW) identified for the site is the Pennsylvanian section.

01 COAL, LIGNITE, AND PEAT↗

ISGS Seal wells

Computed tomography and core logger data described in Technical Report "Computed Tomography Scanning and Geophysical Measurements of the CarbonSAFE Seal Integrity Wells in the Illinois Basin" by Paronish et al., 2023

carbon storage↗

Advanced Characterization of Wastewaters with a Focus on the Environment & Economics (Final Technical Progress Report)

This project, funded by the U.S. Department of Energy under award DE-FE0032457 and conducted at the University of Illinois at Urbana-Champaign, focused on advancing the characterization of coal combustion residual (CCR) effluents. The primary objectives were to develop analytical methods for detecting major cations, anions, trace metals, and rare earth elements (REEs) in CCR wastewater, assess environmental impacts, and explore opportunities for resource recovery. The project advanced the development of a "One-Shot" analysis system designed to simultaneously analyze multiple analytes in CCR effluents.

01 COAL, LIGNITE, AND PEAT↗

Qualitative Risk Assessment of Legacy Wells within the Estimated Prairie State Generating Company Area of Review

This report details the digitization of a legacy wellbore database, including data processing assumptions, parameter estimation, and risk assessment methodology. The database, comprising 6,454 documents, was provided by ISGS. It includes valuable data from the Prairie State Generating Company (PSGC) and One Earth Energy (OEE) sites of the CarbonSAFE Phase III – Illinois Storage Corridor project. The report focuses on wells within a 15-mile radius from the Lively Grove #1 (LG#1) well at PSGC site, evaluating subsurface conditions and potential risks. A total of 4,386 wellbores within 15 miles of the LG#1 well were filtered based on depth and formation codes. LG#1 is the stratigraphic well at the PSGC site drilled in 2021. Ninety-four (94) wells penetrating the Maquoketa Shale Group (the primary confining unit) within the estimated area-of-review (AoR) for the PSGC site were evaluated using a qualitative risk assessment (QRA) methodology. The QRA developed by Arbad et al. 2022 focuses on legacy wells within the AoR and categorizes them based on well construction details. The QRA identifies wells that need immediate attention by categorizing them based on penetration depth and protection. Wells within the AoR were categorized into nine groups based on penetrations and protections. These categories range from Type 1 wells, with no documentation, to Type 9 wells, which do not penetrate the primary confining unit or storage reservoir (unit). Well accessibility within the AoR varies based on well status, including Dry & Abandoned (DA), Plugged & Abandoned (PA), Injection (INJ), Oil/Gas Producing (PROD), and Observation (Obs) wells. Accessibility levels were determined by well construction, with DA wells being the least accessible and Observation wells the most accessible, impacting gas leakage detection possibilities. Remedial action priority of wells decreases from Type 1 to Type 9 wells. Type 1 to Type 6 wells with status DA and PA require immediate attention, while Type 7 and Type 8 wells are low priority. A risk matrix used to prioritize corrective actions for legacy wells is proposed to categorize wells within an AoR based on penetrations, protections, and accessibility. The methodology involves data acquisition, well categorization into nine types, and determining CO 2 leakage pathways using well schematics and geospatial mapping. This approach is particularly useful for managing the integrity of legacy wells throughout the lifecycle of a Carbon Capture and Storage (CCS) project. A qualitative risk assessment of 94 wells within the AoR of the PSGC site identified 54 wells with high priority for corrective action due to penetration of the primary containment seal. The assessment utilizes color-coded maps to categorize well types and prioritize corrective actions, providing a comprehensive analysis. Schematics of wells penetrating the primary confining unit were drawn, and leakage pathways were identified. Details of all wells penetrating the confining zone are provided in the appendix, including information on well types, plugging, and casing status.

01 COAL, LIGNITE, AND PEAT↗

Toward equitable environmental exposure modeling through convergence of data, open, and citizen sciences: an example of air pollution exposure modeling amidst increasing wildfire smoke

Exposure modeling is critical in environmental epidemiology and human health but may face challenges (e.g., skewed data, unequal error, context-insensitive validation, and computational demands). Modeling decisions reflect the intended use of the models and the values that modelers prioritize. We aimed to provide a conceptual framework and machine learning (ML) modeling protocols that address these issues. With 500m-gridded hourly PM 2.5 and O 3 levels in Illinois before, during, and after the 2023 Canadian wildfire season as a motivating example, we conducted modeling experiments to evaluate modeling methods, guided by three domains we propose based on theories of science: 1) Data Diversity, leveraging open and citizen science data to enhance inclusivity, parsimony, and representativeness; 2) Equitable Accuracy, ensuring fairly distributed uncertainties across subpopulations; and 3) Sustainable Modeling, balancing accuracy with reducing computational demands to promote accessibility for under-resourced researchers. Here, we found that ML with publicly available data can achieve high accuracy. Depending on methods, performance may vary substantially, even with identical input data. Large but skewed data may reduce performance. Misuse of cross-validation protocols can underestimate prediction error; although we observed R 2 s of ∼98 %, the modeled estimates varied significantly, indicating the need for careful model validation. By using new modeling protocols including representativeness-considered training and validation data and a new loss function, we achieved high agreement between estimates and ground-based measurements (e.g., R 2 = ∼90 % for PM 2.5 ; ∼80 % for O 3 ), equally distributed errors across sociodemographic strata and urban–rural divides, and reduction in computation time—from several weeks or months to a few days.

Exposure assessment↗

Spatial inequities in access to medications for treatment of opioid use disorder highlight scarcity of methadone providers under counterfactual scenarios

Access to treatment and medication for opioid use disorder (MOUD) is essential in reducing opioid use and associated behavioral risks, such as syringe sharing among persons who inject drugs (PWID). Syringe sharing among PWID carries high risk of transmission of serious infections such as hepatitis C and HIV. MOUD resources, such as methadone provider clinics, however, are often unavailable to PWID due to barriers like long travel distance to the nearest methadone provider and the required frequency of clinic visits. The goal of this study is to examine the uncertainty in the effects of travel distance in initiating and continuing methadone treatment and how these interact with different spatial distributions of methadone providers to impact co-injection (syringe sharing) risks. A baseline scenario of spatial access was established using the existing locations of methadone providers in a geographical area of metropolitan Chicago, Illinois, USA. Next, different counterfactual scenarios redistributed the locations of methadone providers in this geographic area according to the densities of both the general adult population and according to the PWID population per zip code. We define different reasonable methadone access assumptions as the combinations of short, medium, and long travel distance preferences combined with three urban/suburban travel distance preference. Our modeling results show that when there is a low travel distance preference for accessing methadone providers, distributing providers near areas that have the greatest need (defined by density of PWID) is best at reducing syringe sharing behaviors. However, this strategy also decreases access across suburban locales, posing even greater difficulty in regions with fewer transit options and providers. As such, without an adequate number of providers to give equitable coverage across the region, spatial distribution cannot be optimized to provide equitable access to all PWID. Our study has important implications for increasing interest in methadone as a resurgent treatment for MOUD in the United States and for guiding policy toward improving access to MOUD among PWID.

59 BASIC BIOLOGICAL SCIENCES↗

AmeriFlux US-CU1 UIC Plant Research Laboratory Chicago

This is the AmeriFlux version of the carbon flux data for the site US-CU1 UIC Plant Research Laboratory Chicago. Site Description - The UIC Science and Engineering South building is located in Chicago, Illinois. It is situated near the UIC Plant Research Laboratory, a facility with a greenhouse, outdoor garden space, and open lawn areas and is close to a major highway, with several nearby structures and parking areas.

Raut, Bhupendra [Argonne National Laboratory]↗

Task 5 Field Scale Stress Modeling Scripts and Data

Project data and Matlab scripts for Task 5 of the project “A Non-Invasive Approach for Elucidating the Spatial Distribution of In Situ Stress in Deep Subsurface Geologic Formations Considered for CO2 Storage”. Project includes the static earth models, grids and other data used for simulation and calibration of the two case studies addressed in the project, referred to herein as the “FutureGen2” model (Illinois) and the “Perch” model (Otsego county, Michigan). Large Dataset, please contact EDXSupport@netl.doe.gov

FutureGen2↗

ISGS CarbonSAFE Lively Grove Core

Computed tomography and core logging data from the Lively Grove #1 Well core drilled by the Illinois State Geological Survey in 2021 under DE-FE0031892. Data description can be found in: Crandall, D.; Paronish, T.; Mitchell, N.; Jarvis, K.; Brown, S.; Moore, J.; Gill, M.; Blakley, C.; Okwen, R.; Korose, C.; Carman, C. Computed Tomography Scanning and Petrophysical Measurements of the Lively Grove #1 Well Core; DOE/NETL-2023/3877; NETL Technical Report Series; U.S. Department of Energy, National Energy Technology Laboratory: Morgantown, WV, 2023; p 61.

CarbonSafe↗

Residential Building Energy Efficiency Field Studies: Low-Rise Multifamily

In recent years, the U.S. Department of Energy (DOE) has conducted a series of research studies to validate energy efficient building technologies in the field. Much of the work has focused on single-family construction, and some has also addressed commercial energy codes. The work detailed in this DOE-funded study (EE0007616) focuses on low-rise multifamily buildings (three stories or fewer above grade) in various regions of the United States, and reports on how state-level building codes are being implemented, both in terms of observed characteristics and also in terms of estimated energy impacts. Nearly 100 buildings across four states—Illinois, Minnesota, Oregon, and Washington—were sampled, which represent a range of climate types from mild temperature to very cold continental. Both common entry and outdoor entry buildings were included, and a parallel research project evaluated envelope air tightness and current still-evolving air tightness testing methods. Finally, a set of structured interviews of building designers and other relevant professionals was carried to out to gain more insight into this market. To the greatest extent possible, the methodology developed under the project for low-rise multifamily buildings mirrored the approach established by Pacific Northwest National Laboratory (PNNL) for single-family residential buildings (https://www.energy.gov/eere/buildings/downloads/residential-building-energy-code-field-study). This included the general approach to sampling, recruitment, and data collection, as well as data analysis and presentation. The range of permitting dates for the sites encompassed two energy code cycles in most regions. All states in the study had adopted a variation of the International Energy Conservation Code (IECC) for the structure of their state code. The low-rise multifamily occupancy presents a hybrid building type: most of the building’s conditioned floor area was covered by the residential chapter of the code while portions of the building (such as corridors and common spaces) fell under the commercial code chapter. The key items assessed in this work were: Building Shell—exterior wall insulation, ceiling insulation, foundation insulation, windows. Common Areas—HVAC and lighting. Living Units—lighting, ventilation. A few items were not assessed in detail, given their relative paucity in this occupancy type; these included duct leakage, pipe insulation, and hot water circulation controls. Building characteristics were collected via a combination of architectural, mechanical, electrical, and plumbing plan reviews and field inspections, and entered into a spreadsheet-based tool that was later queried to build a database. Data went through quality control both upon arrival and via a later semi-automated review and assurance process. Most of the data are presented graphically so that the reader can quickly assess compliance with the applicable energy codes (both by state and by code year). As a final step, EnergyPlus™ simulations were created for all buildings in the study to estimate both the as-found energy use intensity (EUI) and the energy and CO 2 that could be saved if features that were found to not meet code minimums were brought up to code. The savings estimates were tabulated for each of the four states in the study. The research team found that the single-family approach was largely applicable to low-rise multifamily buildings. This applies to both the data collection and the prototype EUI analysis. Most of the occupied space is living units and falls under residential energy codes, and many characteristics use similar envelope construction and relatively straightforward mechanical systems and lighting. One of the most challenging aspects of this work was to build an effective spreadsheet-based data collection instrument that could allow efficient collection of both building plan and field data. The research team is of the view that other methods could be equally effective if the work is done carefully with diligent quality control. The primary findings for the work center around the thermal envelope and mechanical systems and lighting at the sites: For thermal envelope components, the majority of buildings met or were better than the prescriptive code.This suggests that building designers and builders are aware of code requirements. In some cases, surveyed buildings were designed to qualify for energy efficiency certification programs. These buildings made up at least 20% of sampled buildings in each state. Almost all buildings met mechanical system efficiency requirements (for both living units and common areas). In some cases, sites employed systems that were considerably more efficient than required by the applicable energy code. Dwelling units had a majority of high-efficacy lighting, often in excess of the state’s residential code requirements. While high-efficacy fixtures were also typical in common areas (corridors and stairwells), lighting power densities (LPDs) in these areas were sometimes higher than levels dictated by the applicable part of the state commercial energy code. The simulation models run on a series of low-rise multifamily prototypes, informed by a composite of the field data collected, calculated annual EUIs of between 20 and 50 kBtu/ft2-yr, with the range representing the effects of both building characteristics and building location (climate zone). A detailed process (based on simulations of prototype buildings) was used to estimate the amount of avoided energy use that would occur if 100% adherence to energy codes were attained. The results indicated modest savings are attainable for items such as window thermal performance and common area lighting. The result is overall only a modest potential for additional energy savings, averaging about 10% of EUI.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗