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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Pregnancy exposure to wind turbine noise and adverse birth outcomes: a nationwide cohort study

Highlights: • We identified all Danes exposed to wind turbine noise (WTN) from 1982 to 2013. • We then identified all live born singletons from mothers in this population. • We investigated preterm birth, low birth weight and small for gestational age. • We found no associations between WTN and the adverse birth outcomes. • Few women had high levels of WTN and independent replication is called for. Noise from wind turbines (WTs) is reported as more annoying than traffic noise at similar levels, raising concerns as to whether WT noise (WTN) may negatively affect health, as reported for traffic noise. We aimed to investigate whether residential WTN is associated with adverse birth outcomes. Based on national registries, we identified all Danish dwellings situated within ≤ 20 wt heights radius and a random selection of 25% of dwellings situated within 20–40 wt heights radius of a WT. We identified 135,795 pregnant women living in the dwellings from 1982 to 2013, and collected information on gestational age and birth weight from a national birth registry. Using data on WT type and simulated hourly wind at each WT, we estimated hourly outdoor and low frequency (LF) indoor WTN at the dwellings of the pregnant women and aggregated as mean nighttime WTN during pregnancy. We used logistic regression with adjustment for individual and area-level covariates for the analyses. We did not find evidence suggesting that mean pregnancy or trimester-specific exposure to outdoor or indoor LF WTN were associated with any of the three adverse birth outcomes investigated: preterm birth (n = 13,003), term small for gestational age (n = 12,220) or term low birth weight (n = 1127). However, the number of cases in the highest exposure categories of ≥ 42 dB outdoor WTN or ≥ 15 dB indoor LF WTN were low for all outcomes (n between 0 and 31). The present study does not support an association between nighttime WTN and adverse birth outcomes. However, there were few cases in the high exposure groups and the results call for reproduction.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Fibronectin amyloid-like aggregation alters its extracellular matrix incorporation and promotes a single and sparsed cell migration

Highlights: • Fibronectin can polymerize into amyloid-like aggregates. • Fibronectin amyloid-like aggregates promote a sparsed cell migration. • The supramolecular state of fibronectin could fine-tune cell phenotype. Fibronectin (Fn) is an extracellular matrix (ECM) multifunctional glycoprotein essential for regulating cells behaviors. Within ECM, Fn is found as polymerized fibrils. Apart from fibrils, Fn could also form other kind of supramolecular assemblies such as aggregates. To gain insight into the impact of Fn aggregates on cell behavior, we generated several Fn oligomeric assemblies. These assemblies displayed various amyloid-like properties but were not cytotoxic. In presence of the more amyloid-like structured assemblies of Fn, the cell-ECM networks were altered and the cell shapes shifted toward extended mesenchymal morphologies. Additionnaly, the Fn amyloid-like aggregates promoted a single-cell and sparsed migration of SKOV3 cancer cells, which was associated with a relocalization of αv integrins from plasma membrane to perinuclear vesicles. These data pointed out that the features of supramolecular Fn assemblies could represent a higher level of fine-tuning cell phenotype, and especially migration of cancer cells.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Impacts of Sub‐Grid Topographic Representations on Surface Energy Balance and Boundary Conditions in the E3SM Land Model: A Case Study in Sierra Nevada

Abstract Sub‐grid topographic heterogeneity has large impacts on surface energy balance and land‐atmosphere interactions. However, the impacts of representing sub‐grid topographic effects in land surface models (LSMs) on surface energy balance and boundary conditions remain unclear. This study analyzed and evaluated the impacts of sub‐grid topographic representations on surface energy balance, turbulent heat flux, and scalar (co‐)variances in the Energy Exascale Earth System Model (E3SM) land model (ELM). Three sub‐grid topographic representations in ELM were compared: (a) the default sub‐grid structure (D), (b) the recently developed sub‐grid topographic structure (T), and (c) high spatial resolution (1KM). Additionally, two different solar radiation schemes in ELM were compared: (a) the default plane‐parallel radiative transfer scheme (PP) and (b) the parameterization scheme (TOP) that accounts for sub‐grid topographic effects on solar radiation. A series of offline simulations with the three grid discretization structures (D, T, and 1KM) and two schemes of solar radiation (TOP and PP) were carried out using the Sierra Nevada, California. 1KM simulations with TOP well capture the spatial heterogeneity of surface fluxes compared to Moderate Resolution Imaging Spectroradiometer remote sensing data. There are significant differences between TOP and PP in the 1‐km simulated surface energy balance, but the differences in mean values and standard deviations become small when aggregated to the grid scale (i.e., 0.5°). The T configuration better mimics the 1KM simulations with TOP than the D configuration and better captures the sub‐grid topographic effects on surface energy balance and boundary conditions. These results underline the importance of representing sub‐grid topographic heterogeneities in LSMs and motivate future research to understand the sub‐grid topographic effects on land‐atmosphere interactions over mountainous areas.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Regional carbon fluxes from land use and land cover change in Asia, 1980–2009

We present a synthesis of the land-atmosphere carbon flux from land use and land cover change (LULCC) in Asia using multiple data sources and paying particular attention to deforestation and forest regrowth fluxes. The data sources are quasi-independent and include the U.N. Food and Agriculture Organization-Forest Resource Assessment (FAO-FRA 2015; country-level inventory estimates), the Emission Database for Global Atmospheric Research (EDGARv4.3), the 'Houghton' bookkeeping model that incorporates FAO-FRA data, an ensemble of 8 state-of-the-art Dynamic Global Vegetation Models (DGVM), and 2 recently published independent studies using primarily remote sensing techniques. The estimates are aggregated spatially to Southeast, East, and South Asia and temporally for three decades, 1980–1989, 1990–1999 and 2000–2009. Since 1980, net carbon emissions from LULCC in Asia were responsible for 20%–40% of global LULCC emissions, with emissions from Southeast Asia alone accounting for 15%–25% of global LULCC emissions during the same period. In the 2000s and for all Asia, three estimates (FAO-FRA, DGVM, Houghton) were in agreement of a net source of carbon to the atmosphere, with mean estimates ranging between 0.24 to 0.41 Pg C yr -1 , whereas EDGARv4.3 suggested a net carbon sink of -0.17 Pg C yr -1 . Three of 4 estimates suggest that LULCC carbon emissions declined by at least 34% in the preceding decade (1990–2000). Spread in the estimates is due to the inclusion of different flux components and their treatments, showing the importance to include emissions from carbon rich peatlands and land management, such as shifting cultivation and wood harvesting, which appear to be consistently underreported.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

IMG/M 4 version of the integrated metagenome comparative analysis system

IMG/M (http://img.jgi.doe.gov/m) provides support for comparative analysis of microbial community aggregate genomes (metagenomes) in the context of a comprehensive set of reference genomes from all three domains of life, as well as plasmids, viruses and genome fragments. IMG/M’s data content and analytical tools have expanded continuously since its first version was released in 2007. Since the last report published in the 2012 NAR Database Issue, IMG/M’s database architecture, annotation and data integration pipelines and analysis tools have been extended to cope with the rapid growth in the number and size of metagenome data sets handled by the system. IMG/M data marts provide support for the analysis of publicly available genomes, expert review of metagenome annotations (IMG/M ER: http://img.jgi.doe.gov/mer) and Human Microbiome Project (HMP)-specific metagenome samples (IMG/M HMP: http://img.jgi.doe.gov/ imgm_hmp).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

SU-E-I-10: Automatic Monitoring of Accumulated Dose Indices From DICOM RDSR to Improve Radiation Safety in X-Ray Angiography

Purpose: To investigate the potential benefits of automatic monitoring of accumulated patient and staff dose indicators, i.e., CAK and KAP, from DICOM Radiation Dose Structured Reports (RDSR) in x-ray angiography (XA). Methods: Recently RDSR has enabled the convenient aggregation of dose indices and technique parameters for XA procedures. The information contained in RDSR objects for three XA systems, dedicated to different types of clinical procedures, has been collected and aggregated in a database for over one year using a system developed with open-source software at the Karolinska University Hospital. Patient weight was complemented to the RDSR data via an interface with the Hospital Information System (HIS). Results: The linearly approximated trend in KAP over a time period of a year for cerebrovascular, pelvic/peripheral vascular, and cardiovascular procedures showed a decrease of 12%, 20%, and 14%, respectively. The decrease was mainly due to hardware/software upgrades and new low-dose imaging protocols, and partially due to ongoing systematic radiation safety education of the clinical staff. The CAK was in excess of 3 Gy for 15 procedures, and exceeded 5 Gy for 3 procedures. The dose indices have also shown a significant dependence on patient weight for cardiovascular and pelvic/peripheral vascular procedures; a 10 kg shift in mean patient weight can result in a dose index increase of 25%. Conclusion: Automatic monitoring of accumulated dose indices can be utilized to notify the clinical staff and medical physicists when the dose index has exceeded a predetermined action level. This allows for convenient and systematic follow-up of patients in risk of developing deterministic skin injuries. Furthermore, trend analyses of dose indices over time is a valuable resource for the identification of potential positive or negative effects (dose increase/decrease) from changes in hardware, software, and clinical work habits.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1988

Does vector-free gravity simulate microgravity? Functional and morphologic attributes of clinorotated nerve and muscle grown in cell culture

Cocultured Xenopus neurons and myocytes were subjected to non-vectorial gravity by clinostat rotation to determine if microgravity, during space flights, may affect cell development and communications. Clinorotated cells showed changes consistent with the hypothesis that cell differentiation, in microgravity, is altered by interference with cytoskeleton-related mechanisms. We found: increases in the myocyte and its nuclear area, "fragmentation" of nucleoli, appearance of neuritic "aneurysms", decreased growth in the presence of "trophic" factors, and decreased yolk utilization. The effects were most notable at 1-10 rpm and depended on the onset and duration of rotation. Some parameters returned to near control values within 48 hrs after cessation of rotation. Cells from cultures rotated at higher speeds (>50 rpm) appeared comparable to controls. Compensation by centrifugal forces may account for this finding. Our data are consistent, in principle, with effects on other, flighted cells and suggest that "vector-free" gravity may simulate certain aspects of microgravity. The distribution of acetylcholine receptor aggregates, on myocytes, was also altered. This indicates that brain development, in microgravity, may also be affected.

NASA Discipline Cell Biology↗
NASA NTRS1997

Lewis Investigates Frequency Sharing Between Future NASA Space Systems and Local Multipoint Distribution Systems in the 27-GHz Band

At the request of the Federal Communications Commission (FCC), the NASA Lewis Research Center undertook an intensive study to examine the feasibility of frequency sharing between future NASA space services and proposed Local Multipoint Distribution Systems (LMDS) in the 25.25- to 27.5-GHz band. This follows NASA's earlier involvement in the FCC's 1994 Negotiated Rule Making Committee which studied frequency sharing between Ka-band Fixed Satellite Services and LMDS in the 27.5- to 29.5-GHz band. LMDS is a terrestrial, cellular, wireless communication service primarily intended to provide television distribution from hub stations located within relatively small cells to fixed subscriber receivers. Some proposed systems, however, also plan to offer interactive services via subscriber-to-hub transmissions. LMDS providers anticipate that their systems will be a cost-effective alternative to cable television systems, especially in urban areas. LMDS proponents have expressed an interest in using frequencies below 27.5 GHz. NASA, however, plans to operate three types of space systems below 27.5 GHz. The H, I, and J follow-on satellites for the Tracking and Data Relay Satellite System (TDRSS), which are planned for launch beginning in 1999, are designed to receive high-data-rate transmissions (up to 800 Mbps) from low-Earth orbiting "user" spacecraft in the 25.25- to 27.5-GHz band. In this case, the potential interference is the aggregate interference from LMDS transmitters (both hubs and subscribers) into the TDRSS tracking receive beams as they sweep over the Earth's surface while tracking lower altitude user spacecraft.

Source record↗
NASA NTRS2015

How the Assumed Size Distribution of Dust Minerals Affects the Predicted Ice Forming Nuclei

The formation of ice in clouds depends on the availability of ice forming nuclei (IFN). Dust aerosol particles are considered the most important source of IFN at a global scale. Recent laboratory studies have demonstrated that the mineral feldspar provides the most efficient dust IFN for immersion freezing and together with kaolinite for deposition ice nucleation, and that the phyllosilicates illite and montmorillonite (a member of the smectite group) are of secondary importance.A few studies have applied global models that simulate mineral specific dust to predict the number and geographical distribution of IFN. These studies have been based on the simple assumption that the mineral composition of soil as provided in data sets from the literature translates directly into the mineral composition of the dust aerosols. However, these tables are based on measurements of wet-sieved soil where dust aggregates are destroyed to a large degree. In consequence, the size distribution of dust is shifted to smaller sizes, and phyllosilicates like illite, kaolinite, and smectite are only found in the size range 2 m. In contrast, in measurements of the mineral composition of dust aerosols, the largest mass fraction of these phyllosilicates is found in the size range 2 m as part of dust aggregates. Conversely, the mass fraction of feldspar is smaller in this size range, varying with the geographical location. This may have a significant effect on the predicted IFN number and its geographical distribution.An improved mineral specific dust aerosol module has been recently implemented in the NASA GISS Earth System ModelE2. The dust module takes into consideration the disaggregated state of wet-sieved soil, on which the tables of soil mineral fractions are based. To simulate the atmospheric cycle of the minerals, the mass size distribution of each mineral in aggregates that are emitted from undispersed parent soil is reconstructed. In the current study, we test the null-hypothesis that simulating the presence of a large mass fraction of phyllosilicates in dust aerosols in the size range 2 m, in comparison to a simple model assumption where this is neglected, does not yield a significant effect on the magnitude and geographical distribution of the predicted IFN number. Results from sensitivity experiments are presented as well.

Dust↗
NASA NTRS2015

Human Factors Assessment of Disturbances to Scheduled Performance-Based Navigation Arrival Operations

The introduction of Performance-Based Navigation (PBN) specifications to air traffic management has resulted in many benefits during nominal operations, including shorter flight paths, reduced fuel costs, and improved terminal area arrival rates. However, these benefits become less noticeable during off-nominal operations where aircraft are routinely interrupted from staying on PBN procedures due to disturbances such as missed approaches. This human-in-the-loop (HITL) study used multiple types of disturbance events to perturb the arrival schedule. Perturbed schedules were managed with different types of schedule adjustments, including a condition with no adjustments. The study collected data on a host of dependent variables, including human factors measures on controller workload and system performance measures such as schedule nonconformance (nc). Initial analyses showed strong correlations between aggregated controller workload and aggregated nc, as well as benefits of both automatic and manual schedule adjustments for increasing system performance, such as reduced PBN procedure interruptions. The goal of this paper is to further test these initial findings. The results indicated that an increase in schedule nonconformance correlated with an increase in controller workload at specific time intervals, and automated schedule adjustments consistently reduced controller workload associated with nonconformance.

Human factors↗
DOE OSTI2024

Leveraging NREL's ResStock & ComStock Dataset to Evaluate Building Stock Electrification: Preprint

Residential and commercial buildings accounted for 40% of U.S. energy consumption in 2022 and represent a significant opportunity for decarbonization through energy efficiency and electrification, and for grid planning. Building stock energy modeling is a powerful tool that can evaluate what-if scenarios as utilities, municipalities, policymakers, building owners and others work towards equitable building decarbonization and climate goals. This presentation will highlight several high-impact use cases of the National Renewable Energy Laboratory (NREL)'s highly granular, bottom-up building stock energy modeling tools, ResStock and ComStock. These use cases cover a wide range of project scale, from neighborhood electrification analysis and municipality long-term energy planning, to state energy code development and national policy evaluation. This presentation will showcase specific real-world applications for which ResStock and ComStock have been utilized across the country, including California codes and standards cost-effectiveness analysis, New York City affordable housing electrification cost gap analysis, and California targeted electrification and gas decommissioning analysis. For each use case, this presentation will illustrate how ResStock and ComStock played a crucial role in accurately characterizing regional building stocks, providing discrete and aggregated end-use load shapes, and calculating lifecycle consumption, emissions, and costs for a variety of building electrification strategies and scenarios. Finally, this presentation will demonstrate how the data provided by ResStock and ComStock can help unlock significant outcomes for these use cases, including but not limited to, customer bill impact, incentive and program design, and energy equity analyses.

building stock modeling↗
NASA NTRS2026

Hydrology Copilot: A Cloud-Native Ai System for Hydrological Data Analysis

The emergence of AI-driven Earth observation systems promises to broaden access to petabyte-scale geospatial data beyond domain specialists. However, translating this vision into operational scientific infrastructure requires addressing fundamental challenges in data virtualization, code transparency, and domain-specific reasoning. We present Hydrology Copilot, a cloud-native AI framework for natural-language-driven analysis of Earth observation data. To demonstrate operational capabilities at scale, we implement the system using NASA's North American Land Data Assimilation System version 3 (NLDAS-3), which provides surface meteorological forcing and land-surface model output across North and Central America at 1-km resolution, from which drought diagnostics are derived. The system integrates five core contributions: (1) scalable data virtualization using Kerchunk-based cloud optimized access, achieving a 1.5 to 4.6 times improvement in I/O latency across benchmark queries spanning regional single-day extractions (4.6 times speedup) to continental monthly aggregations (1.5 times speedup); (2) transparent code generation through Microsoft Azure AI Foundry agents that expose executable Python workflows for scientific verification; (3) persistent conversational memory enabling multi-turn analytical discourse across sessions; (4) intelligent query validation that enforces dataset boundaries and resolves ambiguous requests before execution; and (5) a multi-agent architecture coordinating query parsing, code generation, and visualization. We evaluate the system through drought-monitoring workflows, demonstrating reliable code generation, accurate results validated against reference computations and the operational U.S. Drought Monitor, and efficient operation across increasingly complex tasks. By bridging natural-language interfaces with rigorous hydrological analysis, Hydrology Copilot advances beyond proof-of-concept demonstrations to provide a deployable framework for operational Earth science applications.

Data virtualization↗
DOE OSTI2020

A Novel and Practical Method to Quantify the Quality of Mobility: The Mobility Energy Productivity Metric: Preprint

Recent technology innovations are enabling fundamental improvements in mobility systems, including options for new travel modes, methods, and opportunities to connect people with goods, services, and employment. A desire to quantify and compare both existing and emerging transportation options motivated development of the mobility energy productivity (MEP) metric described herein. The MEP metric fundamentally measures the potential of a city's transportation system to connect a person to a variety of services and activities that define a high-quality of life, relative to the convenience, cost and energy needed to provide these connections. Fundamentally derived from accessibility theory, the MEP advances practice by using readily available travel time data (either from web-based application programming interfaces (APIs) or outputs from an urban transportation model) combined with established parameters that reflect the energy intensity and cost of various travel modes, and relative frequency of activity engagement. The construction of the MEP metric allows for aggregation and disaggregation to the appropriate spatial, modal, and trip purpose resolution, as analysis needs dictate. The MEP could be used to compare alternative futures related to technology, infrastructure investment, or policy, providing a much-needed tool for planners, researchers, and analysts.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2016

Expanding on Successful Concepts, Models, and Organization

In her letter to the editor1 regarding our recent Feature Article “Completing the Link between Exposure Science and Toxicology for Improved Environmental Health Decision Making: The Aggregate Exposure Pathway Framework” 2, Dr. von Göetz expressed several concerns about terminology, and the perception that we propose the replacement of successful approaches and models for exposure assessment with a concept. We are glad to have the opportunity to address these issues here. If the goal of the AEP framework was to replace existing exposure models or databases for organizing exposure data with a concept, we would share Dr. von Göetz concerns. Instead, the outcome we promote is broader use of an organizational framework for exposure science. The framework would support improved generation, organization, and interpretation of data as well as modeling and prediction, not replacement of models. The field of toxicology has seen the benefits of wide use of one or more organizational frameworks (e.g., mode and mechanism of action, adverse outcome pathway). These frameworks influence how experiments are designed, data are collected, curated, stored and interpreted and ultimately how data are used in risk assessment. Exposure science is poised to similarly benefit from broader use of a parallel organizational framework, which Dr. von Göetz correctly points out, is currently used in the exposure modeling community. In our view, the concepts used so effectively in the exposure modeling community, expanded upon in the AEP framework, could see wider adoption by the field as a whole. The value of such a framework was recognized by the National Academy of Sciences.3 Replacement of models, databases, or any application with the AEP framework was not proposed in our article. The positive role broader more consistent use of such a framework might have in enabling and advancing “general activities such as data acquisition, organization…,” and exposure modeling was discussed in some detail. Like Dr. von Göetz, we recognized the challenges associated with acceptance of the terminology, definitions, and structure proposed in the paper. To address these challenges, an expert workshop was held in May, 2016 to consider and revise the “basic elements” outlined in the paper. The attendees produced revisions to the terminology (e.g., key events) that align with terminology currently in use in the field. We were also careful in our paper to acknowledge a point raised by Dr. von Göetz, that the term AEP implies aggregation, providing these clarifications: “The simplest form of an AEP represents a single source and a single pathway and may more commonly be referred to as an exposure pathway,”; and “An aggregate exposure pathway may represent multiple sources and transfer through single pathways to the TSE, single sources and transfer through multiple pathways to the target site exposure (TSE), or any combination of these.” These clarifications address the concern that the AEP term is not accurate or logical, and further expands upon the word “aggregate” in a broader context. Our use of AEP is consistent with the definition for “aggregate exposure”, which refers to the combined exposures to a single chemical across multiple routes and pathways.3 The AEP framework embraces existing methods for collection, prediction, organization, and interpretation of human and ecological exposure data cited by Dr. von Göetz. We remain hopeful that wider recognition and use of an organizing concept for exposure information across the exposure science, toxicology and epidemiology communities advances the development of the kind of infrastructure and models Dr. von Göetz discusses. This outcome would be a step forward, rather than a step backward.

exposure science↗
NASA NTRS2014

Linking Excessive Heat with Daily Heat-Related Mortality over the Coterminous United States

In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. This research seeks to provide historical and future measures of climate-driven extreme heat events to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The focus of research is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM outputs, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons for 2040 and 2090 are compared to the recent past period of 1981- 2000. We characterize regional-scale temperature and humidity conditions using GCM outputs for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM outputs are analyzed to develop a 'heat stress climatology' based on statistics of extreme heat indicators. Differences between the two future and the past period are used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes are combined with the historical meteorological data, which is hourly and at a spatial scale (12 km) much finer than that of GCMs, to create future climate realizations. From these realizations, we compute the daily heat stress measures and related spatially-specific climatological fields, such as the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices, and a new heat stress variable developed as part of this research that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. Outputs are aggregated to the county level, which is a popular scale of analysis for public health interests. County-level statistics are made available to public health researchers by the Centers for Disease Control and Prevention (CDC) via the Wide-ranging Online Data for Epidemiologic Research (WONDER) system. This addition of heat stress measures to CDC WONDER allows decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. Through CDC WONDER, users are able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S.

Quattrochi, Dale A.↗
DOE OSTI2016

Estimating the National Carbon Abatement Potential of City Policies: A Data-Driven Approach

Cities are increasingly taking actions such as building code enforcement, urban planning, and public transit expansion to reduce emissions of carbon dioxide in their communities and municipal operations. However, many cities lack the quantitative information needed to estimate policy impacts and prioritize city actions in terms of carbon abatement potential and cost effectiveness. This report fills this research gap by providing methodologies to assess the carbon abatement potential of a variety of city actions. The methodologies are applied to an energy use data set of 23,458 cities compiled for the U.S. Department of Energy City Energy Profile tool. The analysis develops a national estimate of the carbon abatement potential of realizable city actions in six specific policy areas encompassing the most commonly implemented city actions. The results of this analysis suggest that, in aggregate, cities could reduce nationwide carbon emissions by about 210 million metric tons of carbon dioxide (MMT CO2) per year in a 'moderate abatement scenario' by 2035 and 480 MMT CO2/year in a 'high abatement scenario' by 2035 through these common actions typically within a city's control in the six policy areas. The aggregate carbon abatement potential of these specific areas equates to a reduction of 3%-7% relative to 2013 U.S. emissions. At the city level, the results suggest the average city could reduce carbon emissions by 7% (moderate) to 19% (high) relative to current city-level emissions. In the context of U.S. climate commitments under the 21st session of the Conference of the Parties (COP21), the estimated national abatement potential of the city actions analyzed in this report equates to about 15%-35% of the remaining carbon abatement necessary to achieve the U.S. COP21 target. Additional city actions outside the scope of this report, such as community choice aggregation (city-level purchasing of renewable energy), zero energy districts, and multi-level governance strategies, could significantly augment the carbon abatement contributions of city actions toward national climate targets. The results suggest that cities may play a pivotal role in progress toward national climate targets. In addition to providing carbon and emissions estimates, this report estimates the national net economic impacts of policies for which cost and benefit data are available. Impact metrics include employment, worker earnings, and gross domestic product (GDP). For the policy areas studied, the economic analysis demonstrates that city carbon abatement may be achieved with only minimal and generally slightly positive economic impacts. Employment impacts range from 0.04% to 0.13% of U.S, employment during implementation and zero to 0.1% thereafter. GDP estimates show net impacts of 0.02% to 0.07% of GDP during implementation and impacts from -0.02% to zero thereafter. This report quantitatively demonstrates the material impact of a limited set of local policy areas on national carbon abatement potential. The magnitude of estimated carbon reductions from city policies, 3%-7% of national emissions by 2035, suggests an important role for city-led actions in reaching U.S. climate goals. Multi-level governance at the city, state, and national levels could augment the carbon abatement potential of city actions and make cities a key component of long-term U.S. climate strategies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Quantifying cover crop effects on soil health and productivity

The dataset presented here supports the research paper entitled “A calculator to quantify cover crop effects on soil health and productivity”. Soil health (sometimes used synonymously with soil quality) is a concept that describes soil as a living system to sustain plants, animals, and human. Soil physical, chemical, and biological properties, along with their interactions, are required to quantify soil health. The use of cover crops in agricultural rotations may enhance soil health, yet there has been little progress in understanding how external factors such as climate, soil type, and agronomic practices affect soil and cash crop responses. In response, this dataset compiles measurements from 281 studies and provides an analysis of field-measured changes in 38 soil health indicators due to cover crop usage. Environmental and background indicators were also compiled to assess how climatic and management practices affect soil and cash crop responses to cover crops, with specific categories including climate type (tropical, arid, temperate, and continental), soil texture (coarse, medium, and fine), cover crop type (legume, grass, multi-species mixture, and other), and cash crop type (corn, soybean, wheat, vegetable, corn-soybean rotation, corn-soybean-wheat rotation, and other). An unbalanced analysis of variation was used to determine the hierarchy of most to least important factors that affected responsiveness of each soil health indicator. Based on the hierarchy structure, a soil health calculator was then developed to quantify the response of 13 parameters – erosion, runoff, weed suppression, soil aggregate stability, leaching, infiltration, microbial biomass carbon, soil bulk density, soil organic carbon, soil nitrogen, microbial biomass nitrogen, cash crop yield, and saturated hydraulic conductivity – to cover crops. The presented data in the calculator report the mean change in parameter values based on all combinations of climate, soil texture, cover crop type, and cash crop type.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Synthesis and thermodynamics of uranium-incorporated α-Fe 2 O 3 nanoparticles

Hematite nanoparticles were synthesized with U(VI) in circumneutral water through a coprecipitation and hydrothermal treatment process. XRD, TEM, and EXAFS analyses reveal that uranium may aggregate along grain boundaries and occupy Fe sites within hematite. The described synthesis method produces crystalline, single-phase iron oxide nanoparticles absent of surface-bound uranyl complexes. EXAFS data were comparable to spectra from existing studies whose syntheses were more representative of naturally occurring, extended aging processes. Herein this work provides and validates an accelerated method of synthesizing uranium-immobilized iron oxide nanoparticles for further mechanistic studies. High temperature oxide melt solution calorimetry measurements were performed to calculate the thermodynamic stability of uranium-incorporated iron oxide nanoparticles. Increasing uranium content within hematite resulted in more positive formation enthalpies. Standard formation enthalpies of U x Fe 2–2x O 3 were as high as 76.88 ± 2.83 kJ/mol relative to their binary oxides, or -764.04 ± 3.74 kJ/mol relative to their constituent elements, at x = 0.037. Data on the thermodynamic stability of uranium retention pathways may assist in predicting waste uranyl remobilization, as well as in developing more effective methods to retain uranium captured from aqueous environments.

36 MATERIALS SCIENCE↗