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At least 235 records · Page 13

Galaxy Alignments with Surrounding Structure in the Sloan Digital Sky Survey

Using data from the Sloan Digital Sky Survey Legacy Survey, we study the alignment of luminous galaxies with spectroscopic data with the surrounding larger-scale structure as defined by galaxies with only photometric data. We find that galaxies from the red sequence have a statistically significant tendency for their apparent long axes to align parallel to the projected surrounding structure. Red galaxies more luminous than the median of our sample (M r < –21.78) have a mean alignment angle $\langle$Φ$\rangle$ < 45°, indicating preferred parallel alignment, at a significance level >4.5σ on projected scales 0.1 Mpc < r p ≤ 7.5 Mpc. Fainter red galaxies have $\langle$Φ$\rangle$ < 45° at a significance level >4.3σ at scales 1 Mpc < r p < 3 Mpc. At a projected scale r p = 3.0 Mpc, the mean alignment angle decreases steadily with increasing luminosity for red galaxies with M r ≲ –22.5, reaching $\langle$Φ$\rangle$ = 40$^{°}_{.}$49 ± 0$^{°}_{.}$56 for the most luminous 1% (M r ~ –23.57). Galaxies from the blue sequence show no statistically significant tendency for their axes to align with larger-scale structure, regardless of galaxy luminosity. Galaxies in higher-density regions do not show a statistically significant difference in the mean alignment angle from galaxies in lower-density regions; this holds true for the faint blue, luminous blue, faint red, and luminous red subsets.

79 ASTRONOMY AND ASTROPHYSICS↗

The LSST AGN Data Challenge: Selection Methods

Abstract Development of the Rubin Observatory Legacy Survey of Space and Time (LSST) includes a series of Data Challenges (DCs) arranged by various LSST Scientific Collaborations that are taking place during the project's preoperational phase. The AGN Science Collaboration Data Challenge (AGNSC-DC) is a partial prototype of the expected LSST data on active galactic nuclei (AGNs), aimed at validating machine learning approaches for AGN selection and characterization in large surveys like LSST. The AGNSC-DC took place in 2021, focusing on accuracy, robustness, and scalability. The training and the blinded data sets were constructed to mimic the future LSST release catalogs using the data from the Sloan Digital Sky Survey Stripe 82 region and the XMM-Newton Large Scale Structure Survey region. Data features were divided into astrometry, photometry, color, morphology, redshift, and class label with the addition of variability features and images. We present the results of four submitted solutions to DCs using both classical and machine learning methods. We systematically test the performance of supervised models (support vector machine, random forest, extreme gradient boosting, artificial neural network, convolutional neural network) and unsupervised ones (deep embedding clustering) when applied to the problem of classifying/clustering sources as stars, galaxies, or AGNs. We obtained classification accuracy of 97.5% for supervised models and clustering accuracy of 96.0% for unsupervised ones and 95.0% with a classic approach for a blinded data set. We find that variability features significantly improve the accuracy of the trained models, and correlation analysis among different bands enables a fast and inexpensive first-order selection of quasar candidates.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A Storm Safari in Subtropical South America: Proyecto RELAMPAGO

In this article, we provide an overview of the experimental design, execution, education and public outreach, data collection, and initial scientific results from the Remote Sensing of Electrification, Lightning, and Mesoscale/Microscale Processes with Adaptive Ground Observations (RELAMPAGO) field campaign. RELAMPAGO was a major field campaign conducted in the Córdoba and Mendoza provinces in Argentina and western Rio Grande do Sul State in Brazil in 2018–19 that involved more than 200 scientists and students from the United States, Argentina, and Brazil. This campaign was motivated by the physical processes and societal impacts of deep convection that frequently initiates in this region, often along the complex terrain of the Sierras de Córdoba and Andes, and often grows rapidly upscale into dangerous storms that impact society. Observed storms during the experiment produced copious hail, intense flash flooding, extreme lightning flash rates, and other unusual lightning phenomena, but few tornadoes. The five distinct scientific foci of RELAMPAGO—convection initiation, severe weather, upscale growth, hydrometeorology, and lightning and electrification—are described, as are the deployment strategies to observe physical processes relevant to these foci. The campaign’s international cooperation, forecasting efforts, and mission planning strategies enabled a successful data collection effort. In addition, the legacy of RELAMPAGO in South America, including extensive multinational education, public outreach, and social media data gathering associated with the campaign, is summarized.

54 ENVIRONMENTAL SCIENCES↗

Once in a blue stream: Detection of recent star formation in the NGC 7241 stellar stream with MEGARA

Aims.In this work we study the striking case of a narrow blue stream with a possible globular cluster-like progenitor around the NGC 7241 galaxy and its foreground dwarf companion. We want to figure out if the stream was generated by tidal interaction with NGC 7241 or if it first interacted with the foreground dwarf companion and later both fell together toward NGC 7241. Methods.We used four sets of observations, including a follow-up spectroscopic study of this stream based on data taken with the MEGARA instrument at the 10.4 m Gran Telescopio Canarias using the integral field spectroscopy mode, the Mount Lemmon 0.80 m telescope, the Telescopio NazionaleGalileo, the DESI Imaging Legacy surveys, and GALEX archival data. We also used high-resolution zoomed-in cosmological simulations. Results.Our data suggest that the compact object we detected in the stream is a foreground Milky Way halo star. Near this compact object we detect emission lines overlapping a less compact, bluer, and fainter blob of the stream that is clearly visible in both ultraviolet and optical deep images. From its heliocentric systemic radial velocity derived from the [O III]λ5007 Å lines (V syst = 1548.58 ± 1.80 km s −1 ) and new UV and optical broadband photometry, we conclude that this overdensity could be the actual core of the stream, with an absolute magnitude ofM g ∼ −10 and ag − r = 0.08 ± 0.11, consistent with a remnant of a low-mass dwarf satellite undergoing a current episode of star formation. From the width of the stream and assuming a circular orbit, we calculate that the progenitor mass can be typical of a dwarf galaxy, but it could also be substantially lower if the stream is on a very radial orbit or if it was created by tidal interaction with the companion dwarf instead of with NGC 7241. These estimates also suggest that this is one of the lowest mass streams detected to date beyond the Local Group. Finally, we find that blue stellar streams containing star formation regions are commonly predicted by high-resolution cosmological simulations of galaxies lighter than the Milky Way. This scenario is consistent with the processes explaining the bursty star formation history of some dwarf satellites, which are followed by a gas depletion and a fast quenching once they enter within the virial radius of their host galaxies for the first time. Thus, it is likely that the stream’s progenitor is undergoing a star formation burst comparable to those that have shaped the star formation history of several Local Group dwarfs in the last few gigayears.

Astronomy & Astrophysics↗

CIRCLEZ : Reliable photometric redshifts for active galactic nuclei computed solely using photometry from Legacy Survey Imaging for DESI

Photometric redshifts for galaxies hosting an accreting supermassive black hole in their center, known as active galactic nuclei (AGNs), are notoriously challenging. At present, they are most optimally computed via spectral energy distribution (SED) fittings, assuming that deep photometry for many wavelengths is available. However, for AGNs detected from all-sky surveys, the photometry is limited and provided by a range of instruments and studies. This makes the task of homogenizing the data challenging, presenting a dramatic drawback for the millions of AGNs that wide surveys such as SRG/eROSITA are poised to detect. This work aims to compute reliable photometric redshifts for X-ray-detected AGNs using only one dataset that covers a large area: the tenth data release of the Imaging Legacy Survey (LS10) for DESI. LS10 provides deep grizW1-W4 forced photometry within various apertures over the footprint of the eROSITA-DE survey, which avoids issues related to the cross-calibration of surveys. We present the results from CIRCLEZ, a machine-learning algorithm based on a fully connected neural network. CIRCLEZ is built on a training sample of 14 000 X-ray-detected AGNs and utilizes multi-aperture photometry, mapping the light distribution of the sources. The accuracy (σNMAD) and the fraction of outliers (η) reached in a test sample of 2913 AGNs are equal to 0.067 and 11.6%, respectively. The results are comparable to (or even better than) what was previously obtained for the same field, but with much less effort in this instance. We further tested the stability of the results by computing the photometric redshifts for the sources detected in CSC2 and Chandra-COSMOS Legacy, reaching a comparable accuracy as in eFEDS when limiting the magnitude of the counterparts to the depth of LS10. The method can be applied to fainter samples of AGNs using deeper optical data from future surveys (for example, LSST, Euclid), granting LS10-like information on the light distribution beyond the morphological type. Along with this paper, we have released an updated version of the photometric redshifts (including errors and probability distribution functions) for eROSITA/eFEDS.

79 ASTRONOMY AND ASTROPHYSICS↗

Target selection for the DESI Peculiar Velocity Survey

ABSTRACT We describe the target selection and characteristics of the DESI Peculiar Velocity Survey, the largest survey of peculiar velocities (PVs) using both the fundamental plane (FP) and the Tully–Fisher (TF) relationship planned to date. We detail how we identify suitable early-type galaxies (ETGs) for the FP and suitable late-type galaxies (LTGs) for the TF relation using the photometric data provided by the DESI Legacy Imaging Survey DR9. Subsequently, we provide targets for 373 533 ETGs and 118 637 LTGs within the Dark Energy Spectroscopic Instrument (DESI) 5-yr footprint. We validate these photometric selections using existing morphological classifications. Furthermore, we demonstrate using survey validation data that DESI is able to measure the spectroscopic properties to sufficient precision to obtain PVs for our targets. Based on realistic DESI fibre assignment simulations and spectroscopic success rates, we predict the final DESI PV Survey will obtain ∼133 000 FP-based and ∼53 000 TF-based PV measurements over an area of 14 000 deg2. We forecast the ability of using these data to measure the clustering of galaxy positions and PVs from the combined DESI PV and Bright Galaxy Surveys (BGS), which allows for cancellation of cosmic variance at low redshifts. With these forecasts, we anticipate a 4 per cent statistical measurement on the growth rate of structure at z < 0.15. This is over two times better than achievable with redshifts from the BGS alone. The combined DESI PV and BGS will enable the most precise tests to date of the time and scale dependence of large-scale structure growth at z < 0.15.

79 ASTRONOMY AND ASTROPHYSICS↗

Performance of the missing transverse momentum triggers for the ATLAS detector during Run-2 data taking

The factor of four increase in the LHC luminosity, from 0.5 × 10 34 cm -2 s -1 to 2.0 × 10 34 cm -2 s -1 , and the corresponding increase in pile-up collisions during the 2015–2018 data-taking period, presented a challenge for the ATLAS trigger, particularly for those algorithms that select events with missing transverse momentum. The output data rate at fixed threshold typically increases exponentially with the number of pile-up collisions, so the legacy algorithms from previous LHC data-taking periods had to be tuned and new approaches developed to maintain the high trigger efficiency achieved in earlier operations. A study of the trigger performance and comparisons with simulations show that these changes resulted in event selection efficiencies of > 98% for this period, meeting and in some cases exceeding the performance of similar triggers in earlier run periods, while at the same time keeping the necessary bandwidth within acceptable limits.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Results and forecasts on cosmic inflation from weak lensing

Here, we highlight the role of weak lensing measurements from current and upcoming stage-IV imaging surveys in the search for cosmic inflation, specifically in measuring the scalar spectral index n s . To do so, we combine the Dark Energy Survey 3 years of observation weak lensing and clustering data with Bicep/Keck, Planck, and Sloan Digital Sky Survey data in r⁢Λ⁢ CDM (cold dark matter) where r is the tensor-to-scalar ratio. While there is no significant improvement in constraining power, we obtain a 1⁢σ shift on n s . Additionally, we forecast a weak lensing and clustering data vector from the 10-year Legacy Survey of Space and Time by the Vera C. Rubin Observatory and show its combination with current data would improve their n s constraints by 25% in r⁢Λ⁢ CDM.

79 ASTRONOMY AND ASTROPHYSICS↗

Forward modeling fluctuations in the DESI LRGs target sample using image simulations

We use the forward modeling pipeline, Obiwan, to study the imaging systematics of the Luminous Red Galaxies (LRGs) targeted by the Dark Energy Spectroscopic Instrument (DESI). Imaging systematics refers to the false fluctuation of galaxy densities due to varying observing conditions and astrophysical foregrounds corresponding to the imaging surveys from which DESI LRG target galaxies are selected. We update the Obiwan pipeline, which we previously developed to simulate the optical images used to target DESI data, to further simulate WISE images in the infrared. This addition allows simulating the DESI LRGs sample, which utilizes WISE data in the target selection. Deep DESI imaging data combined with a method to account for biases in their shapes is used to define a truth sample of potential LRG targets. We inject these data evenly throughout the DESI Legacy Imaging Survey footprint at declinations between -30 and 32.375 degrees. We simulate a total of 15 million galaxies to obtain a simulated LRG sample (Obiwan LRGs) that predicts the variations in target density due to imaging properties. We find that the simulations predict the trends with depth observed in the data, including how they depend on the intrinsic brightness of the galaxies. We observe that faint LRGs are the main contributing source of the imaging systematics trend induced by depth. We also find significant trends in the data against Galactic extinction that are not predicted by Obiwan. These trends depend strongly on the particular map of Galactic extinction chosen to test against, implying systematic contamination in the Galactic extinction maps is a likely root cause (e.g., Cosmic-Infrared Background, dust temperature correction). We additionally observe a morphological change of the DESI LRGs population evidenced by a correlation between OII emission line average intensity and the size of the z-band PSF. This effect most likely results from uncertainties in background subtraction. The detailed findings we present should be used to guide any observational systematics mitigation treatment for the clustering of the DESI LRGs sample.

79 ASTRONOMY AND ASTROPHYSICS↗

Discovering strongly lensed quasar candidates with catalogue-based methods from DESI Legacy Surveys

The Hubble tension, revealed by a ~5σ discrepancy between measurements of the Hubble-Lemaitre constant among observations of the early and local Universe, is one of the most significant problems in modern cosmology. In order to better understand the origin of this mismatch, independent techniques to measure H 0 , such as strong lensing time delays, are required. Notably, the sample size of such systems is key to minimising the statistical uncertainties and cosmic variance, which can be improved by exploring the datasets of large-scale sky surveys such as Dark Energy Spectroscopic Instrument (DESI). We identify possible strong lensing time-delay systems within DESI by selecting candidate multiply imaged lensed quasars from a catalogue of 24 440 816 candidate QSOs contained in the ninth data release of the DESI Legacy Imaging Surveys (DESI-LS). Using a friend-of-friends-like algorithm on spatial co-ordinates, our method generates an initial list of compact quasar groups. This list is subsequently filtered using a measure of the similarity of colours among a group’s members and the likelihood that they are quasars. A visual inspection finally selects candidate strong lensing systems based on the spatial configuration of the group members. We identified 620 new candidate multiply imaged lensed quasars (101 grade-A, 214 grade-B, 305 grade-C). This number excludes 53 known spectroscopically confirmed systems and existing candidate systems identified in other similar catalogues. When available, these new candidates will be further checked by combining the spectroscopic and photometric data from DESI.

79 ASTRONOMY AND ASTROPHYSICS↗

Modernizing the Nuclear Industry and New Ways of Working

Nuclear energy is recognized as the most feasible energy source towards achieving nation-wide net-zero goals (COP 208, MIT). Additionally, the demand for reliable, consistent energy supply is soaring with the construction of energy hungry data centers and AI tools. This means the construction of new nuclear and the continuation of current nuclear are a high national priority. However, this leaves the nuclear industry with a workforce challenge. The rising demand for nuclear power is threatened by an underpopulated workforce. There exist a few contributors to the decreased workforce such as skewed workforce demographics resulting in large-scale workforce retirement. Also, some plants have observed difficulty hiring and retaining skill sets that typically comprise the nuclear power workforce – specifically skilled craftsman. Those who are graduating with desirable skills are seeking employment in sectors that are more modern and culturally more aligned with younger generational values. Lastly, within the nuclear sector, skilled employees will be a competitive commodity as advanced plants come online offering work environments that incorporate modern technologies, skill sets, and opportunities for career advancement. These factors emphasize the need for legacy plants to modernize with a focus on the workplace environment and culture that meets younger generations’ skills, cultural expectations, and desire for advancement opportunities. Nuclear plants are actively engaged in deploying advancements that improve the management of systems, structures, and components as well as process improvements and technologies that can reduce the costs of operation and maintenance. However, the advancements must also be analyzed, reviewed and deployed in a manner that considers the impact on how people within the organization collaborate, communicate, make decisions, and solve problems. Neglecting to consider the cultural impact of modernization risks poor adoption, unrealized opportunities, or insignificant change toward helping attract new employees. The traditional way of working is not necessarily the way new generations want to engage with their employer. For instance, in a survey performed by North American Young Generation in Nuclear the top three reasons for younger nuclear employees to seek other job opportunities was seeking better work-life balance, a lack of advancement opportunities, and work culture and leadership style differences (Smyth et al. 2022). Integrated Operations for Nuclear (ION) is an approach for the nuclear industry to create long-term strategic modernization plans and analyze each advancement for the impact on people and processes and measure how those impacts flow up to support high-level, long-term plant goals and requirements. One principle of ION is to replace the current labor-centric operation style in legacy nuclear plants with data-centric collaborative operation styles. This paper will explain how transitioning operations to leverage centralized skills and responsibility, multi-skilled teams, and collaborative decision making can flatten the hierarchical structure in plants, enable greater individual efficacy while also offering more experiences and advancement opportunities to staff. Adopting the ION way of working shifts the industry mind-set towards more networked, collaborative, and modern way of working that will attract skilled, next-generation workers to operate the legacy nuclear fleet.

99 - GENERAL AND MISCELLANEOUS↗

The Atacama Cosmology Telescope: DR4 maps and cosmological parameters

In this paper, we present new arcminute-resolution maps of the Cosmic Microwave Background temperature and polarization anisotropy from the Atacama Cosmology Telescope, using data taken from 2013–2016 at 98 and 150 GHz. The maps cover more than 17,000 deg 2 , the deepest 600 deg 2 with noise levels below 10µK-arcmin. We use the power spectrum derived from almost 6,000 deg 2 of these maps to constrain cosmology. The ACT data enable a measurement of the angular scale of features in both the divergence-like polarization and the temperature anisotropy, tracing both the velocity and density at last-scattering. From these one can derive the distance to the last-scattering surface and thus infer the local expansion rate, H 0 . By combining ACT data with large-scale information from WMAP we measure H 0 = 67.6±1.1 km/s/Mpc, at 68% confidence, in excellent agreement with the independently-measured Planck satellite estimate (from ACT alone we find H 0 = 67.9 ± 1.5 km/s/Mpc). The ΛCDM model provides a good fit to the ACT data, and we find no evidence for deviations: both the spatial curvature, and the departure from the standard lensing signal in the spectrum, are zero to within 1σ; the number of relativistic species, the primordial Helium fraction, and the running of the spectral index are consistent with ΛCDM predictions to within 1.5–2.2σ. We compare ACT, WMAP, and Planck at the parameter level and find good consistency; we investigate how the constraints on the correlated spectral index and baryon density parameters readjust when adding CMB large-scale information that ACT does not measure. The DR4 products presented here will be publicly released on the NASA Legacy Archive for Microwave Background Data Analysis.

60 APPLIED LIFE SCIENCES↗

Simulating image coaddition with the Nancy Grace Roman Space Telescope – I. Simulation methodology and general results

The upcoming Nancy Grace Roman Space Telescope will carry out a wide-area survey in the near-infrared. A key science objective is the measurement of cosmic structure via weak gravitational lensing. Roman data will be undersampled, which introduces new challenges in the measurement of source galaxy shapes; a potential solution is to use linear algebra-based coaddition techniques such as imcom that combine multiple undersampled images to produce a single oversampled output mosaic with a desired ‘target’ point spread function (PSF). We present here an initial application of imcom to 0.64 square degrees of simulated Roman data, based on the Roman branch of the Legacy Survey of Space and Time (LSST) Dark Energy Science Collaboration (DESC) Data Challenge 2 (DC2) simulation. We show that imcom runs successfully on simulated data that includes features such as plate scale distortions, chip gaps, detector defects, and cosmic ray masks. We simultaneously propagate grids of injected sources and simulated noise fields as well as the full simulation. We quantify the residual deviations of the PSF from the target (the ‘leakage’), as well as noise properties of the output images; we discuss how the overall tiling pattern as well as Moiré patterns appear in the final leakage and noise maps. We include appendices on interpolation algorithms and the interaction of undersampling with image processing operations that may be of broader applicability. The companion paper (‘Paper II’) explores the implications for weak lensing analyses.

79 ASTRONOMY AND ASTROPHYSICS↗

Multifidelity uncertainty quantification with models based on dissimilar parameters

Multifidelity uncertainty quantification (MF UQ) sampling approaches have been shown to significantly reduce the variance of statistical estimators while preserving the bias of the highest-fidelity model, provided that the low-fidelity models are well correlated. However, maintaining a high level of correlation can be challenging, especially when models depend on different input uncertain parameters, which drastically reduces the correlation. Existing MF UQ approaches do not adequately address this issue. In this work, we propose a new sampling strategy that exploits a shared space to improve the correlation among models with dissimilar parameterization. We achieve this by transforming the original coordinates onto an auxiliary manifold using the adaptive basis (AB) method (Tipireddy and Ghanem, 2014). The AB method has two main benefits: (1) it provides an effective tool to identify the low-dimensional manifold on which each model can be represented, and (2) it enables easy transformation of polynomial chaos representations from high- to low-dimensional spaces. This latter feature is used to identify a shared manifold among models without requiring additional evaluations. Here we present two algorithmic flavors of the new estimator to cover different analysis scenarios, including those with legacy and non-legacy high-fidelity (HF) data. We provide numerical results for analytical examples, a direct field acoustic test, and a finite element model of a nuclear fuel assembly. For all examples, we compare the proposed strategy against both single-fidelity and MF estimators based on the original model parameterization.

42 ENGINEERING↗

Pegasus V/Andromeda XXXIV–a newly discovered ultrafaint dwarf galaxy on the outskirts of Andromeda

ABSTRACT We report the discovery of an ultrafaint dwarf in the constellation of Pegasus. Pegasus V (Peg V)/Andromeda XXXIV was initially identified in the public imaging data release of the DESI Legacy Imaging Surveys and confirmed with deep imaging from Gemini/GMOS-N. The colour–magnitude diagram shows a sparse red giant branch (RGB) population and a strong overdensity of blue horizontal branch stars. We measure a distance to Peg V of $D=692^{+33}_{-31}$ kpc, making it a distant satellite of Andromeda with MV = −6.3 ± 0.2 and a half-light radius of rhalf = 89 ± 41 pc. It is located ∼260 kpc from Andromeda in the outskirts of its halo. The RGB is well fitted by a metal-poor isochrone with [Fe/H] = −3.2, suggesting it is very metal poor. This, combined with its blue horizontal branch, could imply that it is a reionization fossil. This is the first detection of an ultrafaint dwarf outside the deep Pan-Andromeda Archaeological Survey area, and points to a rich, faint satellite population in the outskirts of our nearest neighbour.

79 ASTRONOMY AND ASTROPHYSICS↗

Fungal and bacterial growth variation due to drought and nitrogen addition experimental treatments. Loma Ridge Experimental Project. 2010-2012

Terrestrial ecosystem models assume that microbial communities respond instantaneously, or are immediately resilient, to environmental change. Here we tested this assumption by quantifying the resilience of a leaf litter community to changes in precipitation or nitrogen availability. By manipulating composition within a global change experiment, we decoupled the legacies of abiotic parameters versus that of the microbial community itself. After one rainy season, more variation in fungal composition could be explained by the original microbial inoculum than the litterbag environment (18% versus 5.5% of total variation). This compositional legacy persisted for 3 years, when 6% of the variability in fungal composition was still explained by the microbial origin. In contrast, bacterial composition was generally more resilient than fungal composition. Microbial functioning (measured as decomposition rate) was not immediately resilient to the global change manipulations; decomposition depended on both the contemporary environment and rainfall the year prior. Finally, using metagenomic sequencing, we showed that changes in precipitation, but not nitrogen availability, altered the potential for bacterial carbohydrate degradation, suggesting why the functional consequences of the two experiments may have differed. Predictions of how terrestrial ecosystem processes respond to environmental change may thus be improved by considering the legacies of microbial communities. This data package includes ten csv files (five data files and their corresponding data dictionaries) and one file-level metadata excel file. Data files contains information about which plots were exposed to treatments related to drought and nitrogen, information about litter bags reciprocal transplants manipulation for water input and nitrogen, detail information about water addition, precipitation records, and litter variables collected. Data dictionary files include detail explanation for each column in the data files. The file-level metadata file describes each file mentioned above. All the analyses were done using the R software.

54 ENVIRONMENTAL SCIENCES↗

H-2-SALT: Storing Fossil Energy as Hydrogen in Salt Caverns

Hydrogen storage in subsurface caverns is known as perhaps largest and longest-term energy storage system. While few such systems are currently in service (e.g., Texas; Teesside, UK), they are envisioned as being a pillar of the current energy transition that will allow intermittent power production from renewable sources (e.g., wind, solar) to be balanced with demand at grid-scale. In addition, hydrogen energy storage can allow existing fossil power plants to run more economically either by minimizing startups/shutdowns or by allowing them to take advantage of arbitrage. Finally, stored hydrogen can feed a variety of non-power users such as pipeline gas, heating, transportation, and manufacturing. The H-2-SALT paper study assessed the feasibility of a power-to-hydrogen system utilizing salt cavern storage of hydrogen in bedded salt in central Kansas, where over 750 such caverns have been constructed to date, of which approximately 350 are still in service. Legacy well and salt cavern data were collected to develop a regional geological database for two sites in Central Kansas and adjacent areas for use in more detailed geological and geomechanical site characterization efforts. This study found commercial viability and competitiveness of large-scale, electrolytic H 2 production and storage ($1.78 per kg H 2 ) that can be used for both electrical power supply to the grid during high-priced electricity periods (including co-firing with NG and fuel cell power production) and sale of H 2 for various industries, such as petrochemicals or transportation. The commercial potential of the H-2-SALT system is also relatively high because each of its components operate commercially today. It is recommended that a stratigraphic test well be drilled to collect log data and core samples that can reduce uncertainty surrounding geological and geomechanical properties of the salt beds that will be required for further cavern and energy storage system design studies.

03 NATURAL GAS↗

Strategic Qualitative Risk Assessment of Thousands of Legacy Wells within the Area of Review (AoR) of a Potential CO2 Storage Site

The subsurface confinement of anthropogenic carbon dioxide (CO2) demands robust risk assessment methodologies to identify potential leakage pathways. Legacy wells within the Area of Review (AoR) represent one potential leakage pathway. Robust methodologies require enormous amounts of data, which are not available for many old legacy wells. This study strategically categorizes 4386 legacy wells within the AoR of a potential CO2 storage site in the Illinois basin and identifies the high-risk wells by leveraging publicly available data—reports and well logs submitted to state regulatory agencies. Wells were categorized based on their proximity to the injection well location, depth, the mechanical integrity of well barriers, and the accessibility to these wells throughout the project lifecycle. Wells posing immediate risks were identified, guiding prioritized corrective actions and monitoring plans. Out of 4386 wells, 54 have high priority for corrective action, 10 have medium priority, and the remainder are of low priority. Case study results from the Illinois basin demonstrate the effectiveness and applicability of this approach, to assess the risk associated with legacy wells within the AoR of potential CO2 storage site, strategically categorizing over 4000 such wells despite data limitations.

Arbad, Nachiket (ORCID:0000000215353656)↗