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At least 181 records · Page 10

Evaluating Possible Formation Mechanisms of Criegee Intermediates during the Heterogeneous Autoxidation of Squalene

Organic molecules in the environment oxidatively degrade by a variety of free radical, microbial, and biogeochemical pathways. A significant pathway is heterogeneous autoxidation, in which degradation occurs via a network of carbon and oxygen centered free radicals. Recently, we found evidence for a new heterogeneous autoxidation mechanism of squalene that is initiated by hydroxyl (OH) radical addition to a carbon–carbon double bond and apparently propagated through pathways involving Criegee Intermediates (CI) produced from β-hydroxy peroxy radicals (β-OH-RO 2 •). It remains unclear, however, exactly how CI are formed from β-OH-RO 2 •, which could occur by a unimolecular or bimolecular pathway. Combining kinetic models and multiphase OH oxidation measurements of squalene, we evaluate the kinetic viability of three mechanistic scenarios. Scenario 1 assumes that CI are formed by the unimolecular bond scission of β-OH-RO 2 •, whereas Scenarios 2 and 3 test bimolecular pathways of β-OH-RO 2 • to yield CI. Scenario 1 best replicates the entire experimental data set, which includes effective uptake coefficients vs [OH] as well as the formation kinetics of the major products (i.e., aldehydes and secondary ozonides). Finally, although the unimolecular pathway appears to be kinetically viable, future high-level theory is needed to fully explain the mechanistic relationship between CI and β-OH-RO 2 • in the condensed phase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evidence for a cytokine-sensitive network of iron-associated genes that protects pancreatic islets against ferroptosis

Background/Objectives: The micronutrient iron is closely connected to inflammation and is among the complex factors contributing to beta-cell failure in diabetes. High levels of dietary iron increase the risk of developing type 2 diabetes, and excessive iron uptake by beta-cells can cause oxidative stress and inhibit function. Elevated levels of proinflammatory cytokines in obese individuals, such as interleukin (IL)-1beta and IL-6, increase the risk of developing type 2 diabetes, and there is evidence that these low levels of circulating cytokines can lead to islet dysfunction. Methods: In this study, gene microarray and other data were analyzed for expression differences in islets treated for 48 h with 10 pg/mL IL-1beta + 20 pg/mL IL-6 as a model of low-grade inflammation versus untreated. Results: Three iron-associated genes were among the most cytokine-sensitive in the mouse genome: Hamp, Steap4, and Lcn2. These proteins are all involved with increasing/retaining cellular iron. We hypothesized that increased cellular iron would lead to increased susceptibility to ferroptosis. Surprisingly, 24 h pre-exposure to low-grade inflammation, which upregulates this iron-gene network, prevented subsequent erastin-induced ferroptosis. We also found that Steap4 overexpression reduced islet dysfunction caused by high-dose proinflammatory cytokines (10× low-dose), suggesting an overall protective effect. Steap4 overexpression also upregulated Hamp and Lcn2, suggesting Steap4 regulates these cytokine-sensitive iron genes.; in contrast, ferritin and ferroportin gene expression, which are not sensitive to cytokines, were unchanged. Conclusions: These data suggest an inflammation-induced network of genes involved in cellular iron uptake and retention plays a protective role in islets against oxidative stress and ferroptosis.

IL-1β↗

Accurate field-level weak lensing inference for precision cosmology

We present miko, a catalog-to-cosmology pipeline for general flat-sky field-level inference, which provides access to cosmological information beyond the two-point statistics. In the context of weak lensing, we identify several new field-level analysis systematics (such as aliasing, Fourier mode-coupling, and density-induced shape noise), quantify their impact on cosmological constraints, and correct the biases to a percent level. Next, we find that model misspecification can lead to both absolute bias and incorrect uncertainty quantification for the inferred cosmological parameters in realistic simulations. The Gaussian map prior infers unbiased cosmological parameters, regardless of the true data distribution, but it yields overconfident uncertainties. The log-normal map prior quantifies the uncertainties accurately, although it requires careful calibration of the shift parameters for unbiased cosmological parameters. Here, we demonstrate systematics control down to the 2% level for both models, making them suitable for ongoing weak lensing surveys.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Projected Urban Morphology of the Los Angeles Area by the Year 2100

This dataset provides projections of urban building morphologies for the Los Angeles urban area at 30-meter spatial resolution. It contains 192 raster files that detail two primary building attributes: building footprint fractions (ranging from 0 to 1) and average building heights (ranging from 0 to 75 meters). The projections account for a wide range of future pathways, covering two Shared Socioeconomic Pathway (SSP) scenarios (SSP3 and SSP5), two population scenarios, two developed land intensification scenarios, and four distinct levels of intensification. The dataset was created using dual Generative Adversarial Networks (GANs) trained on 2015 land cover and building properties from the National Land Cover Database (NLCD) and Model America datasets. Supporting information on the dataset has been described in the LAUrbanAreaMorphologyProjections2100_README.txt file.

Pandey, Bhartendu↗

Search for pair production of higgsinos in events with two Higgs bosons and missing transverse momentum in $\sqrt{𝑠}$ = 13 TeV 𝑝⁢𝑝 collisions at the ATLAS experiment

This paper presents a search for pair production of higgsinos, the supersymmetric partners of the Higgs bosons, in scenarios with gauge-mediated supersymmetry breaking. Each higgsino is assumed to decay into a Higgs boson and a nearly massless gravitino. The search targets events where each Higgs boson decays into $b\bar{b}$, leading to a reconstructed final state with at least three energetic 𝑏-jets and missing transverse momentum. Two complementary analysis channels are used, with each channel specifically targeting either low or high values of the higgsino mass. The low-mass (high-mass) channel exploits 126 (139) fb −1 of $\sqrt{𝑠}$ = 13 TeV data collected by the ATLAS detector during Run 2 of the Large Hadron Collider. No significant excess above the Standard Model prediction is found. At 95% confidence level, masses between 130 GeV and 940 GeV are excluded for higgsinos decaying exclusively into Higgs bosons and gravitinos. Exclusion limits as a function of the higgsino decay branching ratio to a Higgs boson are also reported.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Flaw Tolerance Assessment for DOE Standard SNF Dry Storage Canisters - 26550

The U.S. DOE has designed four spent nuclear fuel (SNF) dry storage canisters for storing DOE standardized SNFs. The DOE standard canisters are cylindrical shells with a diameter of 24 inches (610 m) or 18 inches (457 m), a wall thickness of 0.5 inches (12.7 m) or 0.375 inches (9.53 m), and a length of 15 feet (4.57 m) or 10 feet (3.05 m). These DOE canister geometries are completely different from commercial canisters. The latter may experience chloride-induced stress cracking corrosion (CI-SCC) because they are stored near coastal regions. The former may not experience CI-SCC but face different challenges because they are stored in the SNF storage facilities. Because of large residual stresses, mechanical flaws may occur in the DOE canisters during long-distance transportation or lifting handling. To date, only limited structural integrity analyses were carried out through drop tests on the DOE canisters, but a more general flaw tolerance assessment has not been performed. Therefore, the failure assessment diagram (FAD)-based fracture mechanics method, as codified by the latest API 579-1/ASME FFS-1-2021 Edition, is adopted in this work to assess surface flaw tolerance for DOE canisters under operation loading and welding residual stresses (WRS), where the new code-recommended WRS distributions are used. To more adequately consider the transverse distribution of WRS, an equivalent WRS distribution is proposed to account for the WRS reduction with distance from the weld centerline. Moreover, the closed-form solutions of stress intensity factor K, which serves as the crack driving force during subcritical crack growth, are developed from the tabular data of the K factors provided in API 579-1/ASME FFS-1 and used to determine more accurate flaw sizes at flaw instability. Subsequently, the Level 2 assessment procedures with 12 assessment steps, as codified and detailed in API 579-1 and ASME FFS-1, are followed to assess the flaw tolerance for the surface flaws in the DOE standard canisters with consideration of normal or accident operation loads combined with WRS. The assessment results show that the four designs of DOE standard canisters can tolerate all surface flaws that meet the code permitted maximum sizes of a flaw length of 8 inches (i.e., 200 mm) and a flaw depth of 80% wall thickness. This demonstrates that all designs of DOE standard canisters are robust and reliable.

DOE standard canister↗

Compressed Liquid (${{p}}$-${{\rho}}$-${{T}}$) Measurements of trans-1,2-Dichloroethene [R-1130(E)]

Pressure-density-temperature (${{p}}$-${{\rho}}$-${{T}}$) data for the refrigerant R-1130(E) (trans-1,2-dichloroethene) were measured in the compressed liquid phase using an automated vibrating-tube densimeter. Overall, the measurements covered temperatures from 270 K to 410 K and pressures from 0.5 MPa to 30 MPa. Relative combined, expanded (95% confidence level) uncertainties ranged from approximately 0.05% to 0.06%. Here, we present measurement results, along with comparisons to available literature data and to a generalized extended corresponding states model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Soil and groundwater environmental sensor data, Wax Lake Delta, Louisiana, March 2023 - March 2024

This study evaluates how environmental parameters that integrate biogeochemical processes vary with water table fluctuations in the freshwater Wax Lake Delta (WLD) in Louisiana, U.S.A. This data package contains seven *.csv files and one Excel file that compiles all the data from the individual .csv files. This dataset reports high frequency (15-min) observations of water level, soil redox potential, specific conductance, and pH made for one year along elevation transects located on the older, proximal (OT) and younger, distal (YT) ends of a deltaic island. Water depth relative to the ground surface (cm; HOBO U20L-04; error ± 0.4 cm), water pH and temperature (HOBO MX2501), and specific conductance and temperature (HOBO U24-001) sensors were installed in March 2023. Water depth was corrected for barometric pressure recorded by a separate logger secured to a platform above the highest water level. Soil redox probes (SWAP ORP-40-4-B) were also installed in March 2023. Each probe had four Pt sensors (2 mm width) placed at 10 cm, 20 cm, 30 cm, and 40 cm below the ground surface. Redox data were referenced to an external Ag0/AgCl (3M KCl) reference probe placed in saturated ground and recorded on CR1000X dataloggers (Campbell Scientific) powered by solar panels. A second reference probe was positioned near the primary reference probe for backup and data correction. The tops of the soil redox probes and soil moisture probes were flush with the soil surface so that sensors are reported at their indicated depths below ground surface. Here, we report data collected between 15 March 2023 to 15 March 2024 for all sensors, with some differences due to exact dates of sensor placement or data gaps associated with sensor malfunction. For example, water depth at OT4 was not recorded between March to November 2023. Data flags indicate whether a value is valid (1) or was excluded from data analysis in the associated manuscript (-1).

EARTH SCIENCE > LAND SURFACE > SOILS↗

NGEE Arctic Phase 4 Plant Functional Type Framework for Pan-Arctic Vegetation

The NGEE-Arctic research team identified a common set of hierarchical plant functional types (PFTs) for pan-arctic vegetation that we will use across our research activities. Interdisciplinary work within a large team requires agreement regarding levels of functional organization so that knowledge, data, and technologies can be shared and combined effectively. The team has identified plant functional types as a crucial area where such interoperability is needed. PFTs are used to represent plant pools and fluxes within models, summarize observational data, and map vegetation across the landscape. Within each of these applications, varying levels of PFT specificity are needed according to the specific scientific research goal, computational limitations, and data availability. By agreeing on a specific hierarchical framework for grouping variables in our vegetation data, we ensure the resulting research products will be robust, flexible, and scalable. In this document, we lay out the agreed upon PFT framework with definitions and references to existing literature. Table 1 included in the "NGA700_Phase4PFTFramework_about*" file outlines the relationship between NGEE-Arctic Phase 4, Tier 1 PFTs and the PFTs used within prominent arctic literature as well as publications by the NGEE-Arctic team during phases 1-3.This dataset consists of a table detailing a hierarchical PFT framework that spans 4 tiers with the most granular PFTs listed in tier 1 and the most general PFTs in tier 4. The PFTs within each tier has a single column in the dataset where the PFTs are named and a separate column where the characteristics used to define that PFT are listed. Grey fill of the cells is used to indicate where a given PFT starts to “lose” tier 1 details as you look from left to right. Note the excel file has merged cells to indicate grouping of PFTs across the Tiers- it will not translate into a delimited filetype (.csv, .txt, etc) without modification thus the hierarchical PFT framework table is available in three different file formats: 1) NGA700_Phase4PTS.xlsx – maintains the merged cells and grey fill; 2) NGA700_Phase4PTS.csv – merged cells are split, and grey fill is removed; 3) NGA700_Phase4PTS.pdf – image of the table with merged cells and grey fill. Metadata document included as a *.pdf and file-level metadata and data dictionary as *.csv files.

54 ENVIRONMENTAL SCIENCES↗

Videos, photos, and AI-derived grain size data associated with “High-throughput AI Video Surveys Enable Reproducible Multiscale Sediment Size Mapping, with Implications for Hydrobiogeochemical Parameterization”

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the manuscript “High-throughput AI Video Surveys Enable Reproducible Multiscale Sediment Size Mapping, with Implications for Hydrobiogeochemical Parameterization” under review. This data package includes five data types: 1) raw photos and videos from drone survey and walking smartphone surveys; 2) images derived from raw videos; 3) manual labeling of reference scales; 4) metadata for all images and photo resolution derived from artificial intelligence (AI) models or manual labels, 5) grain size data obtained from AI models for all photos, 6) metadata and grain size data after quality control, 7) summaries of sample efficiency for all data, and 8) computational fluid dynamics (CFD) data used to support hydro-biogeochemical (HBGC) parameter estimation. Such data is used to 1) demonstrate significant improvements in accuracy, efficiency, and quality control for grain size data collection with the help of AI models, 2) study the spatial heterogeneity of grain size and observation reproducibility based on tens of thousands of data points generated by the AI models, and 3) evaluate the impacts of grain size heterogeneity on key HBGC parameters across sediment-to-reach and hourly-to-yearly scales. In particular, the data package contains 116 folders and 179696 files. The files include 41 videos in .mov format, 64047 photos in .jpg format, 13541 video-derived photos in .png format, 12747 segmentation mask data in .tif format, 12747 segmentation data in .json format, 24771 .csv files that with metadata and grain size for each individual photo as well as water depth and velocity data from CFD and observation, 51791 .txt files of raw AI predicted labels, and 11 flight record data in .srt format. The summary for all metadata and grain size statistics information is included in “Scales_V3_NG.csv” and “Statistics_V3_NG.csv”. The summary for data that pass data quality control (QC) level 0-2 is included in “QCStatistics_V3_NG.csv”. The QC level 0 represents photos whose photo resolution is positive, excluding photos that miss reference scale. The QC level 1 means reference scale circularity uncertainty is less than 5% for smartphone images while representing photo resolution is larger than 0.44 mm/pixel for drone images. The QC level 2 means excluding photos whose grain number is less than 100, a minimum number of grains recommended by classic literature. The summary for each video’s name, length, frame rates, survey area, grain number, survey efficiency, etc. can be found in “QCSummary_V3_NG.csv”. The summary for site name, GPS coordinates, and number of images at each site can be found in “SitesSummary_V3_*.csv” files. Overall computational efficiency summary is reported in Table 4 of accompanying manuscript. Additionally, the nitrate concentration data used in this work was downloaded from an existing dataset published on ESS-DIVE (Boat-Dragged Sensor Hanford Reach.csv; Conner A. et al., 2020). We thank the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, Cowiche Canyon Conservatory, Port of Benton, and the Confederated Tribes and Bands of the Yakama Nation for access to field locations where the data were collected. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate data collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗

Global Carbon Budget 2025

Accurate assessment of anthropogenic carbon dioxide (CO 2 ) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesise datasets and methodologies to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO 2 emissions (E FOS ) are based on energy and cement production data. Emissions from land-use change (E LUC ) are estimated by bookkeeping models based on land-use data. The global atmospheric CO 2 growth rate (G ATM ) is computed from changes in concentration measured at surface stations. The global net uptake of CO 2 by the ocean (S OCEAN ) is estimated with global ocean biogeochemistry models and observation-based fCO 2 -products. The global net uptake of CO 2 by the land (S LAND ) is estimated with dynamic global vegetation models. Additional lines of evidence are provided by atmospheric inversions, atmospheric oxygen measurements, ocean interior observation-based estimates, and Earth System Models. This year, we introduced corrections on the E LUC , S OCEAN and S LAND estimates. The sum of all sources and sinks results in the carbon budget imbalance (B IM ), a measure of imperfect data and incomplete understanding of the contemporary carbon cycle. All uncertainties are reported as ± 1σ. For the year 2024, E FOS increased by 1.1 % relative to 2023, with fossil emissions at 10.3 ± 0.5 GtC yr −1 (including the cement carbonation sink, 0.2 GtC yr −1 ), E LUC was 1.3 ± 0.7 GtC yr −1 , for total anthropogenic CO 2 emissions of 11.6 ± 0.9 GtC yr −1 (42.4 ± 3.2 GtCO2 yr −1 ). Also, for 2024, G ATM was 7.9 ± 0.2 GtC yr−1 (3.73 ± 0.1 ppm yr −1 ), 2.2 GtC above the 2023 growth rate. SOCEAN was 3.4 ± 0.4 GtC yr −1 and S LAND was 1.9 ± 1.1 GtC yr −1 , leaving a large negative B IM (−1.7 GtC yr −1 ), suggesting that the total sink or G ATM is strongly overestimated in 2024. The global atmospheric CO 2 concentration averaged over 2024 reached 422.8 ± 0.1 ppm. Preliminary data for 2025 suggest an increase in E FOS relative to 2024 of +1.0 % (0.2 % to 1.7 %) globally, and atmospheric CO 2 concentration increasing by 2.1 ppm reaching 425.6 ppm, 53 % above the pre-industrial level (around 278 ppm in 1750). Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2024, with a near-zero overall budget imbalance, although discrepancies of up to around 1 GtC yr −1 persist for the representation of annual to decadal variability in CO 2 fluxes. Comparison of estimates from multiple approaches and observations shows: (1) a persistent large uncertainty in the estimate of land-use change emissions, (2) a low agreement between the different methods on the magnitude of the land CO 2 flux in the northern extra-tropics, and (3) a discrepancy between the different methods on the mean ocean sink. This living data update documents changes in methods and datasets applied to this most-recent global carbon budget as well as evolving community understanding of the global carbon cycle. The data presented in this work are available at https://doi.org/10.18160/GCP-2025 (Friedlingstein et al., 2025c).

54 ENVIRONMENTAL SCIENCES↗

Search for a heavy neutral lepton with the MAGNETO-𝜈 experiment using 241 Pu 𝛽 − decays

The MAGNETO-𝜈 experiment searches for keV-scale heavy neutral leptons (HNLs) through precise measurements of the 𝛽 − -decay spectrum of 241 Pu. We present spectra comprising a total of 194 million 𝛽 − decays recorded using decay energy spectrometry with metallic magnetic calorimeters, representing the most statistically precise measurement of 241 Pu 𝛽 − decay to date. The 𝛽-endpoint energy was determined using 𝛾 rays and x-rays from an external 133 Ba calibration source, yielding 𝑄 𝛽 = 22.273⁢ (33) ⁢keV. The measured spectrum shows no statistically significant deviation from the allowed 𝛽-decay model. From a subset of the high-statistics data, we set an upper limit on the mixing of an 11.5-keV HNL with the electron neutrino, |𝑈 𝑒⁢4 | 2 < 1.31 × 10 −3 at the 95% confidence level.

A ≥ 220↗

Validation of the ESPRESSO wavelength calibration using iodine absorption cell spectra

ABSTRACT High-quality wavelength calibration is crucial for science cases like radial-velocity studies of exoplanets, the search for a possible variation of fundamental constants, and the redshift drift experiment. However, for state-of-the-art spectrographs, it has become difficult to verify the wavelength calibration on sky because no astrophysical source provides spectra with sufficiently stable or accurate wavelength information. We therefore propose to use iodine absorption cells to validate the wavelength calibration. Observing a bright and featureless star through the iodine cell emulates an astrophysical target with exactly known spectral features that can be analysed like any other science target, allowing to verify the wavelength calibration derived from the internal calibration sources and to identify systematics in the data processing. As demonstration, we temporarily installed an $\mathrm{I_2}$ absorption cell at ESPRESSO. Employing a full forward modelling approach of the $\mathrm{I_2}$ spectrum, including the instrumental line-spread function, we demonstrate wavelength calibration accuracy at the level of a few $\mathrm{m\,s^{-1}}$. We also show that wavelength measurements do depend on the geometry of the light-injection into the spectrograph fibers. This highlights the importance of probing exactly the same light path as science targets, something not possible with internal calibration sources alone. We also demonstrate excellent radial-velocity stability at the ${{< 20\, \mathrm{cm\,s^{-1}}}}$ level in a full end-to-end fashion, from sky to data product. Our study therefore showcases the great potential of absorption cells for the verification and long-term monitoring of the wavelength calibration as well as the unique insights they can provide.

Schmidt, Tobias M. (ORCID:0000000248337273)↗

Verification of the ENDF/B-VII.1 Based MC 2 -3 Library Rev.1

The MC 2 -3 code, developed by Argonne National Laboratory under the DOE-NE NEAMS program, is a multigroup cross section generation code for fast reactor applications. Last year, the ENDF/B-VII.0 (E70) MC 2 -3 library, which has been extensively used, verified, and validated over a long period, was intensively reverified and updated to support the commercial grade dedication (CGD) requirement of the TerraPower Natrium project. This year, the ENDF/B-VII.1 (E71) MC 2 -3 library, the preliminary version of which was generated several years ago, was regenerated and rigorously verified to support the Natrium project as well as the completion of verification of the E71 library. The E71 library was verified using the process developed during the verification of the E70 library, including comparisons of cross sections with the NJOY-generated cross sections, comparisons of the resolved resonance cross sections with those using the PEDNF library, and comparison of total cross sections with the sum of partial cross sections. Additional verifications were conducted to ensure that the benchmark problem solutions with the E71 library are reasonable compared to the corresponding Monte Carlo solutions. Furthermore, the E71 gamma library was generated, which includes data for prompt gamma, delayed gamma, and delayed beta as well as neutron and gamma heating. The gamma library was verified at the level of individual isotopes. The EBR-II core solutions from MC 2 -3/ DIF3D and MCNP were compared, demonstrating that those solutions in terms of k-effective and assembly powers were in good agreement.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Back Trajectories during SAIL

This data set contains air mass back trajectories generated during the Surface Atmosphere Integrated Field Laboratory (SAIL) campaign using the Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT, Stein et al. 2015, Rolph et al. 2017). For each hour from January 1, 2021 to June 30, 2023, a 96-hour back trajectory was initiated at the SAIL sampling site, starting 100 m above ground level. The calculations used the GDAS meteorological data set with model vertical velocity. The files within this dataset show location and meteorological parameters of the back trajectory analysis. There are 21 columns within each data file. The first 2 columns pertain to back trajectory parameters: the trajectory number (which is always 1) and the meteorological grid number. The next 9 columns pertain to spatiotemporal information: the year, month, day, hour (0-23), and minute of the trajectory, the previous time of the trajectory (in negative hours), and the airmass location (latitude, longitude, and height in m AGL). The rest of the parameters within each file pertains to surface and meteorological characteristics of the airmass: pressure (in hPa), potential temperature (in K), temperature (in K), precipitation rate (in mm/hr), mixing depth (in m), relative humidity (in % relative to liquid water), specific humidity (in g/kg), H2O mixing ratio (in g/kg), underlying terrain height (in meters above sea level), and incoming radiation (in W/m^2).

back trajectory↗

WholeTraveler Anonymized Data Phase 1

Phase 1 of the WholeTraveler Study data collection consisted of an online-only survey. This survey captured data on three categories of observable variation in the population relevant to transportation decisions. First, the survey collected traditional demographic data such as age, gender, income, and education level. Second, it collected data across personality, psychological, and preference categories. This included: 1. The "Big Five" inventory personality traits: openness to new experience, conscientiousness, extroversion, agreeableness, and neuroticism; 2. Risk and time preferences; and 3. Environmental preferences. Third, the survey collected data on historical behavior patterns including: 1. Adoption of (as well as interest in) new technologies or innovations (e.g., smartphones, PEVs, solar panels, adaptive cruise control [ACC]); 2. Car ownership history and current car ownership status; 3. Recent mode use across different time scales (e.g., previous week, previous month, previous year); and 4. Timing of major life events such as starting a family as well as overall lifecycle trajectory patterns. Data from Phase 1 and Phase 2 are linked by a unique respondent identifier. Anonymized versions of the Phase 1 and Phase 2 data are both available on Livewire.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Chemically Enabled CO 2 -Enhanced Oil Recovery in Multi-Porosity, Hydrothermally Altered Carbonates in the Southern Michigan Basin (Final Technical Report)

This is the Final Technical Report for the project "Chemically Enabled CO 2 -Enhanced Oil Recovery in Multi-Porosity, Hydrothermally Altered Carbonates in the Southern Michigan Basin." Over the course of six years of collaboration between Battelle and project partners, all stated objectives of the program have been completed, including full geological characterization of the TBR trend (See companion report for Task2), laboratory and modeling experiments to determine the optimum composition and design of CO 2 -EOR operations in the TBR trend, execution of a field test of chemically-enhanced CO 2 in a TBR well, and integration of the data and learnings gathered during these efforts into a full-trend development plan. Detailed reporting on these activities, their outcomes, and implications for trend-wide development is provided in the report. This report and encompassed data will provide TBR field operators with detailed information on what worked, what did not work, and how to proceed with production optimization of their TBR assets using chemically-enhanced CO 2 -EOR. CO 2 -EOR is a relatively well understood and broadly implemented strategy for increasing incremental production across the oil and gas industry, but its application has been primarily focused on reservoirs with limited heterogeneity. The intention of this project was show first that the same physical mechanisms that improve recovery factors in homogeneous reservoirs (namely wettability alteration, viscosity alteration, oil swelling, and mobility control) are at play in heterogeneous reservoirs. This was proven by the project’s laboratory studies and dynamic simulations, with the potential exception of mobility control, which needs further study. The second intention was to demonstrate via direct field testing that CO 2 -EOR can work in a strongly heterogeneous reservoir. While the field test strategy implemented during this project did not succeed in producing oil, data gathered during the test sheds light on what may work for field operators who try chemically-enhanced CO 2 -EOR within their own reservoirs, significantly reducing the level of uncertainty carried by first-of-a-kind commercial efforts that could (and should) follow this test. Simultaneously, the project has identified several large-volume ethanol plants and other sources of CO 2 emissions in the region and provided a handrail that CO 2 emitters and field operators can leverage to capture, transport, and inject that CO 2 into their fields. This project has also shown that, in many cases, the economics of CO 2 -EOR in the TBR are attractive. And finally, by completing a project of this scope in the southern Michigan Basin, the project has contributed to the knowledge base and operational experience of field operators, state regulatory agencies, local service companies, and state universities, with CO 2 -EOR projects which should allow follow-on projects to proceed safely and efficiently.

02 PETROLEUM↗

Computer-Based Procedures Among Older Adults: Findings from the Rancor Microworld Simulator

As with many industries worldwide, nuclear energy is experiencing an aging workforce; older than other energy sources and the national average. For example, while almost one in three nuclear industry professionals are 55+ years, for oil and gas that number is one in five. The challenges brought about by an aging workforce are one of the industry’s top concerns. However, the industry lacks for empirical research that examines the effects of developmental aging in older workers, as well as the interactions between aging and new digital technologies. We present the results of an experiment that tested three different computer-based procedures in a sample of 30 older adults (55+ years). While the industry has traditionally relied on paper-based procedures, these are being modernized by digital technology. Participants were randomly assigned to one of three procedure-types that varied by the level of digitalization, based on the IEEE Standard-1786. Type 1 essentially represents a digital representation of a paper-based procedure, Type 2 adds embedded indicators, and Type 3 adds soft controls. Participants performed two different operational scenarios (startup and loss of feedwater) on a simplified nuclear power plant simulator. Results revealed a weak signal that Type 2 may produce lower workload and lower completion times in some instances. However, there were no significant effects of procedure-type across any other outcomes, including simulator log data, situation awareness, and preference ratings. We discuss our findings in terms of optimal levels of digitalization/automation for an aging nuclear workforce and suggest pathways for future directions.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗