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DOE OSTI2023

In-situ thermodynamics measurements at metal oxides-solution interfaces using Flow Adsorption Microcalorimetry.

Mineral-fluid interfaces are the principal sites of geochemical processes near Earth’s surface, hosting chemical reactions that play a fundamental role in (bio)geochemical cycles and in the fate and transport of anthropogenic contaminants, and that effectively control the compositions of soil and water environments. These complex interfaces are critical for our energy and environmental future. The mineral-fluid interface has been studied in an unprecedented level of detail with both experimental and computational approaches, separately and in combination. However, conspicuously missing from studies of the mineral-fluid interface are direct measurements of the energies of ion sorption and exchange. The literature on energetics and enthalpies of exchange, adsorption, dissolution, precipitation, and surface protonation reactions, especially those directly supported by experimental data, remains scarce despite their fundamental nature. The overarching goal of this project is to complete a systematic study of the thermodynamics properties of interfacial reactions at four MO surfaces (Rutile (α-TiO2), Quartz (SiO2), boehmite (γ-AlOOH) and goethite (α-FeOOH)) through the application and construction of novel flow adsorption microcalorimetry techniques and instrumentations. These unique and specialized microcalorimeters will operate at various temperatures and solution chemical compositions allowing for in-situ measurements across metal oxides and ligands of various characteristics. The overall research goal will be accomplished by completing the following three specific objectives (O): O1) Determine the energetics of surface protonation and deprotonation, ion exchange and ligand sorption reactions; O2) Investigate the surface charge thermodynamic properties under a range of temperature and solution chemical compositions; and O3) Develop predictive trends of the interplay between MO structure, surface coverage and surface reactivity. In addition to key thermodynamics parameters, calorimetric measurements provide a wealth of mechanistic information about reactions energetics and kinetics, surface charge characteristics, and structure-reactivity or selectivity relationships, all obtained in-situ and in real-time. This report includes science highlights from various projects completed over the performance period of the project. Also listed are dissemination opportunities, people supported on the grant and the impact on available physical resources and the discipline as a whole.

58 GEOSCIENCES↗

DOE OSTI2024

Challenges of COVID-19 Case Forecasting in the US, 2020–2021

During the COVID-19 pandemic, forecasting COVID-19 trends to support planning and response was a priority for scientists and decision makers alike. In the United States, COVID-19 forecasting was coordinated by a large group of universities, companies, and government entities led by the Centers for Disease Control and Prevention and the US COVID-19 Forecast Hub ( https://covid19forecasthub.org ). We evaluated approximately 9.7 million forecasts of weekly state-level COVID-19 cases for predictions 1–4 weeks into the future submitted by 24 teams from August 2020 to December 2021. We assessed coverage of central prediction intervals and weighted interval scores (WIS), adjusting for missing forecasts relative to a baseline forecast, and used a Gaussian generalized estimating equation (GEE) model to evaluate differences in skill across epidemic phases that were defined by the effective reproduction number. Overall, we found high variation in skill across individual models, with ensemble-based forecasts outperforming other approaches. Forecast skill relative to the baseline was generally higher for larger jurisdictions (e.g., states compared to counties). Over time, forecasts generally performed worst in periods of rapid changes in reported cases (either in increasing or decreasing epidemic phases) with 95% prediction interval coverage dropping below 50% during the growth phases of the winter 2020, Delta, and Omicron waves. Ideally, case forecasts could serve as a leading indicator of changes in transmission dynamics. However, while most COVID-19 case forecasts outperformed a naïve baseline model, even the most accurate case forecasts were unreliable in key phases. Further research could improve forecasts of leading indicators, like COVID-19 cases, by leveraging additional real-time data, addressing performance across phases, improving the characterization of forecast confidence, and ensuring that forecasts were coherent across spatial scales. In the meantime, it is critical for forecast users to appreciate current limitations and use a broad set of indicators to inform pandemic-related decision making.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Using observational mean-flow data to drive large-eddy simulations of a diurnal cycle at the SWiFT site

Reproducing realistic date- and site-specific unsteady wind conditions in large-eddy simulations is becoming increasingly useful in wind energy. How to run a large-eddy simulation to match observed conditions, however, remains an open research question. One approach that has received considerable attention is mesoscale-to-microscale coupling, in which information about the mesoscale weather, most commonly acquired from a mesoscale numerical weather model, is passed on to a microscale model. In this paper, we demonstrate how the recently developed profile-assimilation technique, a form of mesoscale-to-microscale coupling, can be used to drive large-eddy simulations solely based on observed mean-flow profiles at a single location, bypassing the need for auxiliary mesoscale simulations. The new approach is evaluated for a diurnal cycle at the Scaled Wind Farm Technology site. Observed mean-flow profiles from the ground up to a height of 2 km are reconstructed by aggregating measurements from multiple instruments, and gaps in the data are infilled with natural neighbor interpolation. We perform nine simulations using various forcing approaches to deal with data limitations. The results show that it is indeed possible to drive microscale large-eddy simulation with observations using the profile-assimilation technique, notwithstanding large gaps in virtual potential temperature measurements. However, profile assimilation with vertical smoothing of the error between the desired and actual profiles is required. Without that smoothing, the microscale simulations develop unrealistically high turbulence levels under many situations. Finally, we show that simulated mesoscale data can account for missing observations, although care is needed as both data sources are not necessarily compatible.

17 WIND ENERGY↗

DOE OSTI2019

Structured versus narrative reporting of pelvic MRI in perianal fistulizing disease: impact on clarity, completeness, and surgical planning

Objective: To evaluate clarity, completeness, and impact on surgical planning of MRI reporting of perianal fistulizing disease using a structured disease-specific template versus narrative reporting for planning of disease treatment by colorectal surgeons. Materials and methods: In this HIPAA-compliant, IRB-approved study with waiver of informed consent, a structured reporting template for perianal fistulizing disease MRIs was developed based on collaboration between colorectal surgeons and abdominal radiologists. The study population included 45 consecutive patients who underwent pelvic MRI for perianal fistulizing disease prior to implementation of structured reporting, and 60 consecutive patients who underwent pelvic MRI for perianal fistulizing disease after implementation of structured reporting. Objective evaluation of the reports for the presence of 12 key features was performed, as also subjective evaluation regarding the clarity and completeness of reports, and impact on surgical planning. Results: Significantly more key features were absent in narrative reports [mean: 6.3 ± 1.8 (range 3–11)] than in structured reports [mean: 0.3 ± 0.9 (range 1–5)] (p ≤ 0.001). The use of structured reporting also increased the percentage of completeness (72.5–88.3% for surgeon 1, and 61.2–81.3% for surgeon 2; p = 0.05 and 0.03, respectively), helpfulness in surgical planning (7.1 ± 1.5–7.6 ± 1.5 for surgeon 1, and 5.8 ± 1.4–7.1 ± 1.1 for surgeon 2; p = 0.05 and p < 0.001, respectively), and clarity (7.6 ± 1.3–8.3 ± 1.1 for surgeon 1, and 5.2 ± 1.4–7.1 ± 1.3 for surgeon 2; p = 0.006 and p < 0.001, respectively) of the reports. Conclusion: Structured MRI reports in patients with perianal fistulizing disease miss fewer key features than narrative reports. Moreover, structured reports were described as more complete and clear, and more helpful for treatment planning.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2014

Modeling X-ray emission around galaxies

Extended X-ray emission can be studied by spatial surface brightness measurements or by spectral analysis, but the two methods can disagree at low intensity levels. Here we present an improved method for spatial analysis that can be extended to include spectral information simultaneously. We construct a model for the entire image in a given energy band and generate a likelihood function to compare the model to the data. A critical goal is disentangling vignetted and unvignetted backgrounds through their different spatial distributions. Employing either maximum likelihood or Markov Chain Monte Carlo, we can derive probability distributions for the source and background parameters together, or we can fit and subtract the background, leaving the description of the source non-parametric. We calibrate this method against a variety of simulated images, and apply it to Chandra observations of the hot gaseous halo around the elliptical galaxy NGC 720. We follow the emission below a tenth of the background and infer a hot gas mass within 35 kpc of 4-5 × 10{sup 9} M {sub ☉}, with some indication that the profile continues to at least 50 kpc and that it steepens. We derive stronger constraints on the surface brightness profile than previous studies that employed the spectral method, and we show that the density profiles inferred from these studies are in conflict with the observed surface brightness profile. Contrary to a previous claim, we find that the X-ray halo does not contain the full complement of missing baryons within the virial radius.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Exploring the non-Gaussianity of the cosmic infrared background and its weak gravitational lensing

ABSTRACT Gravitational lensing deflects the paths of photons, altering the statistics of cosmic backgrounds and distorting their information content. We take the cosmic infrared background (CIB), which provides plentiful information about galaxy formation and evolution, as an example to probe the effect of lensing on non-Gaussian statistics. Using the Websky simulations, we first quantify the non-Gaussianity of the CIB, revealing additional detail on top of its well-measured power spectrum. To achieve this, we use needlet-like multipole-band filters to calculate the variance and higher-point correlations. Using our simulations, we show the two-, three- and four-point spectra, and compare our calculated power spectra and bispectra to Planck values. We then lens the CIB, shell-by-shell with corresponding convergence maps, to capture the broad redshift extent of both the CIB and its lensing convergence. The lensing of the CIB changes the three- and four-point functions by a few tens of per cent at large scales, unlike with the power spectrum, which changes by less than two per cent. We expand our analyses to encompass the full intensity probability distribution functions (PDFs) involving all n-point correlations as a function of scale. In particular, we use the relative entropy between lensed and unlensed PDFs to create a spectrum of templates that can allow estimation of lensing. The underlying CIB model is missing the important role of star bursting, which we test by adding a stochastic lognormal term to the intensity distributions. The novel aspects of our filtering and lensing pipeline should prove useful for any radiant background, including line intensity maps.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Latent Stochastic Differential Equations for Modeling Quasar Variability and Inferring Black Hole Properties

Quasars are bright and unobscured active galactic nuclei (AGN) thought to be powered by the accretion of matter around supermassive black holes at the centers of galaxies. The temporal variability of a quasar’s brightness contains valuable information about its physical properties. The UV/optical variability is thought to be a stochastic process, often represented as a damped random walk described by a stochastic differential equation (SDE). Upcoming wide-field telescopes such as the Rubin Observatory Legacy Survey of Space and Time (LSST) are expected to observe tens of millions of AGN in multiple filters over a ten year period, so there is a need for efficient and automated modeling techniques that can handle the large volume of data. Latent SDEs are machine learning models well suited for modeling quasar variability, as they can explicitly capture the underlying stochastic dynamics. In this work, we adapt latent SDEs to jointly reconstruct multivariate quasar light curves and infer their physical properties such as the black hole mass, inclination angle, and temperature slope. Our model is trained on realistic simulations of LSST ten year quasar light curves, and we demonstrate its ability to reconstruct quasar light curves even in the presence of long seasonal gaps and irregular sampling across different bands, outperforming a multioutput Gaussian process regression baseline. Our method has the potential to provide a deeper understanding of the physical properties of quasars and is applicable to a wide range of other multivariate time series with missing data and irregular sampling.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

KCMP Minnesota Tall Tower Ammonia Observations and Emission Estimates Dataset 2017-2018

This data set contains NH3 mixing ratios, net ecosystem NH3 exchange, and supporting information measured at a tall tower (KCMP, 244 meter) site near St. Paul, Minnesota, USA. The data include NH3 and H2O mixing ratios measured at the 100 meter level, as well as NH3 mixing ratio measured at the 56 meter level. Wind data was measured using a sonic anemometer at the 185 meter level. Also included in this data set are values of wet N and NH3 deposition from 2016 - 2018. This data was collected to improve understanding of the ammonia and reactive nitrogen budget for the region.Ammonia mixing ratios were filtered for periods when the NH3 analyzer measured anomalous (i.e. 10 mmol mol-1) water vapor mixing ratios based on comparison with the IRGA (LI7000). Further, we filtered out NH3 observations obtained during strongly condensing conditions. These periods were identified when the water vapor mixing ratio differences between the 100 m and 56 m levels were more negative than -0.5 mmol mol-1 (i.e. when the water vapor gradient was strong and directed toward the land surface). Finally, we filtered out NH3 fluxes when the atmosphere was strongly stable (i.e. when (z-d)/L exceeded a value of +4.5) and subject to decoupling from the surface fluxes. Approximately 35.1% of the hourly flux data were either missing due to instrument failure or filtered according to the above quality control procedures.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Predictive analytics of selections of russet potatoes

We explore the application of machine learning algorithms specifically to enhance the selection process of Russet potato (Solanum tuberosum L.) clones in breeding trials by predicting their suitability for advancement. This study addresses the challenge of efficiently identifying high-yield, disease-resistant, and climate-resilient potato varieties that meet processing industry standards. Leveraging manually collected data from trials in the state of Oregon, we investigate the potential of a wide variety of state-of-the-art binary classification models. The dataset includes 1086 clones, with data on 38 attributes recorded for each clone, focusing on yield, size, appearance, and frying characteristics, with several control varieties planted consistently across four Oregon regions from 2013 to 2021. We conduct a comprehensive analysis of the dataset that includes preprocessing, feature engineering, and imputation to address missing values. We focus on several key metrics such as accuracy, F1-score, and Matthews correlation coefficient (MCC) for model evaluation. The top-performing models, namely a feedforward neural network classifier (Neural Net), a histogram-based gradient boosting classifier (HGBC), and a support vector machine classifier (SVM), demonstrate consistent and significant results. To further validate our findings, we conducted a simulation study using the aims, data-generating mechanisms, estimands, methods, and performance measures (ADEMP) framework, simulating different data-generating scenarios to assess model robustness and performance through true positive, true negative, false positive, and false negative distributions, area under the receiver operating characteristic curve (AUC-ROC) and MCC. The simulation results highlight that non-linear models like SVM and HGBC consistently show higher AUC-ROC and MCC than logistic regression, thus outperforming the traditional linear model across various distributions, and emphasizing the importance of model selection and tuning in agricultural trials. Variable selection further enhances model performance and identifies influential features in predicting trial outcomes. The findings emphasize the potential of machine learning in streamlining the selection process for potato varieties, offering benefits such as increased efficiency, substantial cost savings, and judicious resource utilization. Our study contributes insights into precision agriculture and showcases the relevance of advanced technologies for informed decision-making in breeding programs.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2013

Observing the next galactic supernova

No supernova (SN) in the Milky Way has been observed since the invention of the optical telescope, instruments for other wavelengths, neutrino detectors, or gravitational wave observatories. It would be a tragedy to miss the opportunity to fully characterize the next one. To aid preparations for its observations, we model the distance, extinction, and magnitude probability distributions of a successful Galactic core-collapse supernova (ccSN), its shock breakout radiation, and its massive star progenitor. We find, at very high probability (≅ 100%), that the next Galactic SN will easily be detectable in the near-IR and that near-IR photometry of the progenitor star very likely (≅ 92%) already exists in the Two Micron All Sky Survey. Most ccSNe (98%) will be easily observed in the optical, but a significant fraction (43%) will lack observations of the progenitor due to a combination of survey sensitivity and confusion. If neutrino detection experiments can quickly disseminate a likely position (∼3°), we show that a modestly priced IR camera system can probably detect the shock breakout radiation pulse even in daytime (64% for the cheapest design). Neutrino experiments should seriously consider adding such systems, both for their scientific return and as an added and internal layer of protection against false triggers. We find that shock breakouts from failed ccSNe of red supergiants may be more observable than those of successful SNe due to their lower radiation temperatures. We review the process by which neutrinos from a Galactic ccSN would be detected and announced. We provide new information on the EGADS system and its potential for providing instant neutrino alerts. We also discuss the distance, extinction, and magnitude probability distributions for the next Galactic Type Ia supernova (SN Ia). Based on our modeled observability, we find a Galactic ccSN rate of 3.2{sub −2.6}{sup +7.3} per century and a Galactic SN Ia rate of 1.4{sub −0.8}{sup +1.4} per century for a total Galactic SN rate of 4.6{sub −2.7}{sup +7.4} per century is needed to account for the SNe observed over the last millennium, which implies a Galactic star formation rate of 3.6{sub −3.0}{sup +8.3} M {sub ☉} yr{sup –1}.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2023

Potentially Underestimated Gas Flaring Activities—A New Approach to Detect Combustion Using Machine Learning and NASA’s Black Marble Product Suite

Monitoring changes in greenhouse gas (GHG) emission is critical for assessing climate mitigation efforts towards the Paris Agreement goal. A crucial aspect of science-based GHG monitoring is to provide objective information for quality assurance and uncertainty assessment of the reported emissions. Emission estimates from combustion events (gas flaring and biomass burning) are often calculated based on activity data (AD) from satellite observations, such as those detected from the visible infrared imaging radiometer suite (VIIRS) onboard the Suomi-NPP and NOAA-20 satellites. These estimates are often incorporated into carbon models for calculating emissions and removals. Consequently, errors and uncertainties associated with AD propagate into these models and impact emission estimates. Deriving uncertainty of AD is therefore crucial for transparency of emission estimates but remains a challenge due to the lack of evaluation data or alternate estimates. This work proposes a new approach using machine learning (ML) for combustion detection from NASA's Black Marble product suite and explores the assessment of potential uncertainties through comparison with existing detections. We jointly characterize combustion using thermal and light emission signals, with the latter improving detection of probable weaker combustion with less distinct thermal signatures. Being methodologically independent, the differences in ML-derived estimates with existing approaches can indicate the potential uncertainties in detection. The approach was applied to detect gas flares over the Eagle Ford Shale, Texas. We analyzed the spatio-temporal variations in detections and found that approximately 79.04% and 72.14% of the light emission-based detections are missed by ML-derived detections from VIIRS thermal bands and existing datasets, respectively. This improvement in combustion detection and scope for uncertainty assessment is essential for comprehensive monitoring of resulting emissions and we discuss the steps for extending this globally.

gas flaring↗

DOE OSTI2017

Assessing the urban carbon footprint: An overview

All cities present environmental sustainability issues, above all regarding greenhouse gas (GHG) emissions, and specifically carbon dioxide (CO{sub 2}), that directly affect climate change. Consequently, it is very important to quantify and report their Carbon Footprint (CF) for implementing national and international policies/strategies aimed at mitigating and adapting these concerns. The Urban Carbon Footprint (UCF), indeed, has been recognized as the more valuable choice to inform, specifically, decision makers about city environmental sustainability. Several accounting systems and inventory methods have been taken into account to perform UCF, highlighting the complexity of the topic and generating very often confusion among users. In this context, the authors aim to summarize what has been done and what is going on with UCFs, trying to classify them according to some principal dimensions. Thus, they divide UFCs in two main categories namely: “spatial” or “direct”, with a limited amount of data requested, and “economic” or “life cycle based”, more or less data inclusive according to the accounting systems considered. Furthermore, they observe that there is not a “global agreed-upon protocol” yet, neither is there a specific model shared among researchers, even if some steps have been made towards this direction (Relative Carbon Footprint - RCF, Publicly Available Specification – PAS 2070 and Global Protocol for Community scale - GPC). Consequently, it is necessary to complete and standardize, in the short term, the accounting and reporting frameworks, in order to compare different UCFs for adopting shared climate strategies and actions at global level. - Highlights: •Cities present environmental sustainability issues. •GHG emissions - specifically carbon dioxide - directly affect climate change. •UCF is a tool to support policy makers towards city environmental sustainability. •There is not a “global agreed-upon protocol” to perform UFC. •There are still missing points to be considered to provide a sharing model.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

Resilient, Rural, and Revolutionary: Salisbury Square's Direct-Current Affordable Microgrid Community: Preprint

The technology to interconnect buildings with a dedicated direct-current (DC) power distribution network is in place today; what is missing is a turnkey approach to designing a DC microgrid - and the business models allowing such systems to be deployed, owned, and operated at scale. To close this gap, the Salisbury Square Development Team, comprising clean-energy experts, has engineered a resilient community DC microgrid for an affordable housing community in Randolph, Vermont. Ten single-family, occupant-owned residences and 12 multifamily rental units will share locally generated and stored solar energy via a DC power distribution bus capable of operating during extended grid outages. With a DC power distribution network in place, each home will be equipped with high-efficiency DC lighting and appliances, operating alongside alternating current (AC) appliances, even during an islanded mode of operation. To obtain a comprehensive understanding of what is possible and achievable, the Team collaborated with the local utility, regulatory agencies, a national laboratory, energy-as-service providers, and vendors. The collaborators evaluated microgrid typologies, business models, and energy modeling, and analyzed electrification and resilience. Further, the Team applied the URBANoptTM (Urban Renewable Building and Neighborhood optimization, NREL 2022) software development kit (SDK) to Salisbury Square's single-family and multifamily buildings to validate workflows and identify needs for advanced capability. This paper addresses the barriers to entry, scalability, and impact on residents and system ownership. It also examines the analysis that informed the design and engineering of the DC microgrid and the opportunities to streamline the process.

DER↗

DOE OSTI2019

Dreaming awake: disentangling the underlying physics in case of a SUSY-like discovery at the LHC

The purpose of this review is to investigate what kind of physics can be extracted at the Large Hadron Collider (LHC), assuming a discovery is made in events with missing transverse momentum, as generically expected in supersymmetry (SUSY) with R-parity conservation. To set the scene, we first discuss the collider phenomenology of the six possible electroweakino benchmark scenarios, as they provide valuable insight into what one might be facing at the LHC. We review the existing methods for mass reconstruction from measured kinematic endpoints in the distributions of suitable variables, e.g. the invariant masses of various sets of visible decay products, as well as the M T2 and the M 2 types of variables. We propose to extend the application of these methods to the various topologies of fully hadronic final states, possibly with hadronically reconstructed massive bosons (W, Z or h). We test the idea with a simplified simulation of events in the main electroweakino benchmark scenarios. We find that the fully hadronic events allow the complete determination of the relevant mass spectrum. For comparison, we also review the potential of the standard kinematic endpoint methods for final states involving leptons from the decays of (on-shell or off-shell) sleptons. We find that with 300 fb -1 , the statistics for the leptonic events is very marginal and they look less promising than the fully hadronic channels. This corresponds to a complete reversal of the usual paradigm, where leptonic events comprised the gold-plated SUSY channels. Finally, we put together all available information and summarize what level of understanding of the underlying physics can be achieved. We show that, as a by-product of the mass reconstruction, it is also possible to determine the production cross sections and decay branching ratios, which in turn enable us to pinpoint the underlying model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Coupling Metabolic Source Isotopic Pair Labeling and Genome Wide Association for Metabolite and Gene Annotation in Plants (Final Technical Report)

In this project, we applied our labeling pipeline to Arabidopsis and sorghum by feeding tissues with isotopically labeled versions of commercially available amino acids to identify all metabolite features that incorporate the label. In sorghum, we fed five accessions, sampled across the diversity of sorghum, to identify the precursor-of-origin for metabolites that vary between accessions as well as those that may be missing from a single reference genotype. This provided us with precursor-of-origin annotation for thousands of unknown metabolites. We then used GWA to map genes responsible for the synthesis of precursor-of-origin classified metabolites. For sorghum leaf and root ducible metabolites, we performed untargeted metabolomics on leaf and root tissues from 300 diverse genotyped sorghum inbred lines. The amino acid precursor-of-origin metabolite library were then used to identify the corresponding metabolites in the GWA data sets and to identify novel gene-metabolite associations. Finally, we utilized existing and newly generated sequenced EMS mutants of sorghum to validate the predicted gene-metabolite relationships that our labelling analysis identified. In parallel, we conducted similar feeding experiments in Arabidopsis to categorize metabolites based on precursor-of-origin, identify those that vary across our existing Arabidopsis metabolite GWA dataset, and identify genes required for the synthesis of each metabolite. To provide an independent test of gene annotation and pathway involvement, we tested the GWA gene-metabolite associations in Arabidopsis by analyzing the metabolic phenotypes of gene knockouts. Genes of particular interest from both sorghum and Arabidopsis were studied in detail by directly measuring the activity of the corresponding enzymes following heterologous expression. In summary, this work classified as-yet-unknown amino acid-derived metabolites and identified genes involved in their production generated through “omics” technologies. This information was used to validate gene function and identify new metabolism in Arabidopsis and sorghum.

09 BIOMASS FUELS↗

DOE OSTI2014

Overview of the forthcoming AAPM TG-158 Report, 'Measurements and calculations of doses outside the treatment volume from External Beam Radiation Therapy' - Paper 85

The evolution of techniques and technology in radiotherapy has greatly improved our ability to deliver higher tumor doses while minimizing the dose to the adjacent organs at risk. However, this improved conformality has not removed the problem of doses to normal tissues outside the target volume. Whether these out-of-field doses arise from photons, electrons, protons or neutrons, there are unique challenges that many medical physicists may have limited knowledge about or experience with. With modern treatment planning systems, high dose regions and areas within the primary beam path are typically well described. However, their accuracy beyond a few centimeters outside the treatment field edge are usually poor. In these cases, alternate methods are required to assess the out-of-field dose. Such assessments require additional care to avoid potentially large errors associated with a variety of unique complications in performing dosimetry outside the treatment field. Furthermore, physicists will not always have an a priori estimate of the expected dose, and, as a result, large dosimetric errors are more easily missed. Low radiation doses outside the treatment volume are a concern because they can cause deleterious effects to the patient. The risk of late effects from the secondary radiation may be more evident today because of the success of cancer screening and modern therapies that have increased the number of cancer patients who survive and live long enough for the adverse radiation effects on healthy tissues to manifest. Simultaneously, radiotherapy procedures have become more complex, making the estimation of low out-of-field doses even more challenging. Over the past 30 years, numerous studies have been published detailing non-target doses from various radiotherapy treatments (for a detailed review see Xu et al. However, dosimetry data were obtained using a variety of measurement or computational techniques. An overview of dosimetry techniques for measuring low-level non-target doses is not available. Improved, or at least valid, dosimetry is important for several reasons. In clinical care (e.g. fetal dose estimates), large dose errors can lead to inappropriate or unnecessary treatment decisions, with potentially serious consequences to the patient. In a broader sense of somatic effects, more accurate dosimetry will improve patient risk assessment, understanding of dose responses, treatment planning, and design of the radiation delivery machines. Once reliable dosimetry data are available, it is then the clinician's responsibility to assess the risk vs. benefit of the radiotherapy treatment to make a sound and informed assessment of all possible treatment outcomes. (author)

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2012

Lands with Wilderness Characteristics, Resource Management Plan Constraints, and Land Exchanges: Cross-Jurisdictional Management and Impacts on Unconventional Fuel Development in Utah's Uinta Basin

Utah is rich in oil shale and oil sands resources. Chief among the challenges facing prospective unconventional fuel developers is the ability to access these resources. Access is heavily dependent upon land ownership and applicable management requirements. Understanding constraints on resource access and the prospect of consolidating resource holdings across a fragmented management landscape is critical to understanding the role Utah’s unconventional fuel resources may play in our nation’s energy policy. This Topical Report explains the historic roots of the “crazy quilt” of western land ownership, how current controversies over management of federal public land with wilderness character could impact access to unconventional fuels resources, and how land exchanges could improve management efficiency. Upon admission to the Union, the State of Utah received the right to title to more than one-ninth of all land within the newly formed state. This land is held in trust to support public schools and institutions, and is managed to generate revenue for trust beneficiaries. State trust lands are scattered across the state in mostly discontinuous 640-acre parcels, many of which are surrounded by federal land and too small to develop on their own. Where state trust lands are developable but surrounded by federal land, federal land management objectives can complicate state trust land development. The difficulty generating revenue from state trust lands can frustrate state and local government officials as well as citizens advocating for economic development. Likewise, the prospect of industrial development of inholdings within prized conservation landscapes creates management challenges for federal agencies. One major tension involves whether certain federal public lands possess wilderness character, and if so, whether management of those lands should emphasize wilderness values over other uses. On December 22, 2010, Secretary of the Interior Ken Salazar issued Secretarial Order 3310, Protecting Wilderness Characteristics on Lands Managed by the Bureau of Land Management. Supporters argue that the Order merely provides guidance regarding implementation of existing legal obligations without creating new rights or duties. Opponents describe Order 3310 as subverting congressional authority to designate Wilderness Areas and as closing millions of acres of public lands to energy development and commodity production. While opponents succeeded in temporarily defunding the Order’s implementation and forcing the Bureau of Land Management (BLM) to adopt a more collaborative approach, the fundamental questions remain: Which federal public lands possess wilderness characteristics and how should those lands be managed? The closely related question is: How might management of such resources impact unconventional fuel development within Utah? These questions remain pressing independent of the Order because the BLM, which manages the majority of federal land in Utah, is statutorily obligated to maintain an up-to-date inventory of federal public lands and the resources they contain, including lands with wilderness characteristics. The BLM is also legally obligated to develop and periodically update land use plans, relying on information obtained in its public lands inventory. The BLM cannot sidestep these hard choices, and failure to consider wilderness characteristics during the planning process will derail the planning effort. Based on an analysis of the most recent inventory data, lands with wilderness characteristics — whether already subject to mandatory protection under the Wilderness Act, subject to discretionary protections as part of BLM Resource Management Plan revisions, or potentially subject to new protections under Order 3310 — are unlikely to profoundly impact oil shale development within Utah’s Uinta Basin. Lands with wilderness characteristics are likely to v have a greater impact on oil sands resources, particularly those resources found in the southern part of the state. Management requirements independent of lands with wilderness characteristics far overshadow the challenges posed by wilderness issues. Wilderness character issues aside, a need to improve management integration remains. In researching past efforts to manage across the fragmented landscape we found that unilateral actions have been deeply divisive and engendered distrust among those impacted by the action. This distrust can linger for decades. Collaborative efforts, whether intended to protect lands, foster development, or do both, can represent an attractive alternative to unilateral action. Such collaborative efforts are more likely to succeed when they respond to strong incentives to act, evidence widespread involvement and support, and benefit from a committed champion. Projects are all but certain to fail where participants overreach or one of these elements is missing. For more than three decades, the state and federal government have cooperatively pursued land exchanges in order to “block up” isolated state trust lands and eliminate inholdings. These efforts can advance both conservation and development objectives, and are generally conducted in conjunction with efforts to protect extraordinary federal lands. Congress recognized the value of such exchanges and, as part of the Energy Policy Act of 2005, directed the Department of the Interior to pursue land exchanges as a means of facilitating environmentally responsible oil shale and oil sands recovery. But land exchanges are not without their challenges. Federal law requires equalizing the value of the lands and resources to be exchanged, and various means of equalizing value have been attempted. More flexible approaches have a higher likelihood of success, but are often criticized as resulting in an economic windfall for one party. Today challenges associated with appraisal and valuation stand as the most significant obstacles in the way of large-scale exchanges. Greater reliance on revenue sharing provisions that prevent an economic windfall to one party and avoid challenges inherent in valuing oil shale and oil sands resources may mark a promising path forward. The success or failure of these efforts could profoundly impact both the prospect of unconventional fuel development and wilderness character protection.

04 OIL SHALES AND TAR SANDS↗

DOE OSTI2015

Short timescale photometric and polarimetric behavior of two BL Lacertae type objects

Context. Blazars are astrophysical sources whose emission is dominated by non-thermal processes, typically interpreted as synchrotron and inverse Compton emission. Although the general picture is rather robust and consistent with observations, many aspects are still unexplored. Aims. Polarimetric monitoring can offer a wealth of information about the physical processes in blazars. Models with largely different physical ingredients can often provide almost indistinguishable predictions for the total flux, but usually are characterized by markedly different polarization properties. We explore, with a pilot study, the possibility to derive structural information about the emitting regions of blazars by means of a joint analysis of rapid variability of the total and polarized flux at optical wavelengths. Methods. Short timescale (from tens of seconds to a couple of minutes) optical linear polarimetry and photometry for two blazars, BL Lacertae and PKS 1424+240, was carried out with the PAOLO polarimeter at the 3.6 m Telescopio Nazionale Galileo. Several hours of almost continuous observations were obtained for both sources. Results. Our intense monitoring allowed us to draw strongly different scenarios for BL Lacertae and PKS 1424+240, with the former characterized by intense variability on time-scales from hours to a few minutes and the latter practically constant in total flux. Essentially the same behavior is observed for the polarized flux and the position angle. The variability time-scales turned out to be as short as a few minutes, although involving only a few percent variation of the flux. The polarization variability time-scale is generally consistent with the total flux variability. Total and polarized flux appear to be essentially uncorrelated. However, even during our relatively short monitoring, different regimes can be singled out. Conclusions. No simple scenario is able to satisfactorily model the very rich phenomenology exhibited in our data. As a result, detailed numerical simulations show that the emitting region should be characterized by some symmetry, and the inclusion of turbulence for the magnetic field may constitute the missing ingredient for a more complete interpretation of the data.

1424+240↗