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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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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Towards COP27: Decarbonization patterns of residential building in China and India

As the two largest emerging emitters with the highest growth in operational carbon emissions from residential buildings, the historical emission patterns and decarbonization efforts of China and India warrant further exploration. This study aims to be the first to present a carbon intensity model considering end-use performances, assessing the operational decarbonization progress of residential building in India and China over the past two decades using the newest decomposing structural decomposition approach. Results indicate (1) the annual operational carbon intensity increased by 1.4% and 2.5% in China and India, respectively, between 2000 and 2020. Household expenditure-related energy intensity and emission factors were crucial in decarbonizing residential buildings. (2) Building electrification played a significant role in decarbonizing space cooling (–87.7 in China and – 130.2 kg of carbon dioxide (kgCO 2 ) per household in India) and appliances (~ –169.7 in China and ~ –43.4 kgCO 2 per household in India). (3) China and India collectively decarbonized 1498.3 and 399.7 M-tons of CO 2 in residential building operations, respectively. In terms of decarbonization intensity, India (164.8 kgCO 2 per household) nearly caught up with China (182.5 kgCO 2 per household) in 2020 and is expected to surpass China in the upcoming years, given the country's robust annual growth rate of 7.3%. Overall, this study provides an effective data-driven tool for investigating the building decarbonization potential in China and India, and offers valuable insights for other emerging economies seeking to decarbonize residential buildings in the forthcoming COP28 1 age.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Multi-objective sizing and dispatch for building thermal and battery storage towards economic and environmental synergy

The role of building thermal and battery storage is pivotal in advancing smart cities and achieving sustainability goals through effective energy management. Despite their significance, there are several limitations in the sizing approach and value stream analysis with various objectives for their widespread adoption in buildings. This work proposes a flexible and scalable multi-objective optimization framework for optimal sizing and dispatch of building thermal and battery storage, addressing conflicting objectives simultaneously using mixed-integer linear programming. The weighted-sum method is adapted, combining multiple objectives into a single function. The two-stage procedure iterates over different weights, generating optimal solutions and forming the Pareto front. Case studies are performed to assess the energy, economic, and environmental benefits of building energy storage systems for a large office building in three climate locations. The results demonstrate that the proposed framework efficiently determines optimal sizing and dispatch strategies, addressing the balance between economic viability and emission reduction. The dynamic relationship between time-of-use energy charges and emission factors leads to significantly different strategies based on whether economic or environmental concerns are prioritized. This research enhances our understanding of the benefits of TES and BES systems in buildings, providing valuable guidance to stakeholders.

25 ENERGY STORAGE↗
DOE OSTI2023

A scalable framework for quantifying field-level agricultural carbon outcomes

Agriculture contributes nearly a quarter of global greenhouse gas (GHG) emissions, which is motivating interest in adopting certain farming practices that have the potential to reduce GHG emissions or sequester carbon in soil. The related GHG emission (including N 2 O and CH 4 ) and changes in soil carbon stock are defined here as “agricultural carbon outcomes”. Accurate quantification of agricultural carbon outcomes is the basis for achieving emission reductions for agriculture, but existing approaches for measuring carbon outcomes (including direct measurements, emission factors, and process-based modeling) fall short of achieving the required accuracy and scalability necessary to support credible, verifiable, and cost-effective measurement and improvement of these carbon outcomes. Here we propose a foundational and scalable framework to quantify field-level carbon outcomes for farmland, which is based on the holistic carbon balance of the agroecosystem: Agroecosystem Carbon Outcomes = Environment (E) × Management (M) × Crop (C). Following a comprehensive review of the scientific challenges associated with existing approaches, as well as their tradeoffs between cost and accuracy, we propose that the most viable path for the quantification of field-level carbon outcomes in agricultural land is through an effective integration of various approaches (e.g. diverse observations, sensor/in-situ data, and modeling), defined as the “System-of-Systems” solution. Such a “System-of-Systems” solution should simultaneously comprise the following components: (1) scalable collection of ground truth data and cross-scale sensing of environment variables (E), management practices (M), and crop conditions (C) at the local field level; (2) advanced modeling with necessary processes to support the quantification of carbon outcomes; (3) systematic Model-Data Fusion (MDF), i.e. robust and efficient methods to integrate sensing data and models at each local farmland level; (4) high computation efficiency and artificial intelligence (AI) to scale to millions of individual fields with low cost; and (5) robust and multi-tier validation systems and infrastructures to ensure solution fidelity and true scalability, i.e. the ability of a solution to perform robustly with accepted accuracy on all targeted fields. In this regard, we provide here the detailed scientific rationale, current progress, and future research and development (R&D) priorities to achieve different components of the “System-of-Systems” solution, thus accomplishing the Environment×Management×Crop framework to quantify field-level agricultural carbon outcomes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Standoff detection of chemical plumes from high explosive open detonations using a swept-wavelength external cavity quantum cascade laser

A swept-wavelength external cavity quantum cascade laser (ECQCL) is used to perform standoff detection of combustion gases in a plume generated from an outdoor high-explosive (HE) open detonation. The swept-ECQCL system was located at a standoff distance of 830 m from a 41kg charge of LX-14(polymer-bonded high explosive) and was used to measure the infrared transmission/absorption through the post-detonation plume as it propagated through the beam path. The swept-ECQCL was operated continuously to record broadband absorption spectra at 200hz rate over a spectral range from 2050 to 2230 cm -1 (4.48 - 4.88 μm). Fitting of measured spectra was used to determine time-resolved column densities of CO, CO 2 , H 2 O, and N 2 O. Analysis of visible video imagery was used to provide timing correlations and to estimate plume dimensions, from which gas mixing ratios were estimated. Measured emission factors and modified combustion efficiency show good agreement with previously reported values.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

High temperature and pressure regime soot: Physical, optical and chemical signatures from high explosive detonations

Submicron particles are formed during the detonation and deflagration of carbon-rich energetic materials known as high explosives (HE) that can be lofted and transported long distances in the atmosphere. Particles include refractory species like soot, a.k.a. black carbon (BC), and have impacts to climate and human health at local, regional, and global scales. Here, we contrast detonation soot aerosol physical, optical and chemical properties that are formed more efficiently in terms of emission factors and ratios with traditional combustion sources from biomass burning and fossil fuels. We utilize ambient aerosol techniques for the first time to identify soot from two well-known HE's (1) Comp B-3: 40% trinitrotoluene (TNT) and 60% 1,3,5-trinitro-1,3,5-triazinane (RDX) and (2) PBX 9501: 95% 1,3,5,7-tetranitro-1,3,5,7-tetrazoctane (HMX) with 2.5% Estane and a 2.5% mixture of bis(2,2-dinitropropyl)-acetal (BDNPA) and bis(2,2-dinitropropyl)-formal (BDNPF). Size distributions, optical and chemical properties are presented. Aggregate soot had small mobility diameters (<100 nm) and unique optical and chemical signatures depending on the explosive composite composition, detonation atmosphere (e.g., air, argon) and pressure. Single-scattering albedos (SSA) from 0.3 to 0.8 and absorption Angstrom exponents (AAE) from 0.5 to 2.0 measured across 405–870 nm wavelengths depended on the explosive composite composition and detonation conditions. Comp B-3 detonation soot was similar to other combustion soot sources, whereas PBX 9501 soot had high scattering relative to absorption. Carbonaceous chemical signatures included the presence of fullerenes that were distinct from ambient and laboratory-generated soot surrogates and the detection of trace metals, including aluminum, copper, iron, and zinc.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Simulating energy performance of buildings: a study using eQUEST and Energy Star ® portfolio manager

Commercial buildings consume significant energy in the United States and exhibit high potential for energy use reduction through retrofits. Benchmarking and energy simulation are well established tools in the industry to identify potential improvements and measure performance. Analysis to identify most sensitive retrofit parameters to energy performance can optimize investment and available energy savings. Presented study demonstrates methodology using a static model to determine sensitivity of building design and retrofit parameters with respect to energy performance. Calibrated simulation energy models (eQUEST) of two distribution centers (A, B) are presented. A fractional factorial analysis is conducted on retrofit parameters of efficiency measures targeting the highest energy consumers, and the results are benchmarked using Energy Star® Portfolio Manager. A custom Microsoft Excel® based simulation model is created to simulate occupancy levels, lighting, plug loads, and other equipment used in various spaces throughout the day. For Building A, efficient lighting was the most influential parameter for energy savings, carbon savings and benchmarking score; whereas, for Building B, HVAC efficiency was most influential for energy and demand controlled ventilation and economizers was most influential for benchmarking score. While retrofit projects can save energy and carbon emissions, variation in source-site ratios and state grid emissions, benchmarking scores may not always reflect equivalent improvement. State grid emissions factors, natural gas composition are difficult to model and hence not considered in this study. In conclusion, the synergistic analysis presented, emphasizes the importance of benchmarking and efficiency retrofits in promoting sustainable building practices to reduce energy consumption.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Oak Ridge National Laboratory EPA Approval Letters and Historical Documentation for a Modification in Applying 40 CFR Part 61 Appendix D

Appendix D of Title 40 Part 61, “Methods for Estimating Radionuclide Emissions,” of the Code of Federal Regulations (CFR) provides a procedure that US Department of Energy (DOE) facility owners and operators can use to estimate radionuclide emissions to the atmosphere for dose calculations instead of measuring emissions for minor sources under 40 CFR Part 61, Subpart H, “National Emission Standards for Emissions of Radionuclides Other than Radon from Department of Energy Facilities.” The procedure assumes that any radioactive material heated above 100°C is completely vaporized and emitted to the atmosphere. In 1991, the DOE Oak Ridge Reservation (DOE-ORR) requested approval to use different release fractions (RFs) for uranium because of its high melting and boiling points (1,132°C and 3,818°C, respectively). In response to the request, Environmental Protection Agency (EPA) Region IV approved the use of modified RFs for elemental uranium provided no reaction had taken place to alter its chemical form. In 2015, DOE-ORR requested approval to use different RFs for radioactive tungsten, also because of its high melting and boiling points (3,410°C and 5,660°C, respectively). EPA Region IV approved the use of modified RFs for heated radioactive tungsten metal. In accordance with the two precedents set for heating uranium and radioactive tungsten metals, in 2016, DOE-ORR requested approval to use modified RFs in similar fashion for other radioactive solid metals and compounds with melting and boiling points above 500°C that might be heated above 100°C in future research projects and experiments, and again, the EPA Region IV granted approval to use modified RFs for the list of compounds. This document contains the EPA approval letters and historical documentation used in the process to obtain approval for the use of alternative Appendix D emission factors. The approval to DOE-ORR allows modifying the existing regulatory RFs to 1 when radioactive solid metals and compounds are heated to temperatures greater than or equal to the boiling point of the solid, to 10 -3 when radioactive solid metals and compounds are heated to temperatures greater than or equal to 90% of the melting point and less than the boiling point of the solid, and to 10 -6 when radioactive solid materials are heated to temperatures above ambient air temperature but below 90% of the melting point of the solid.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Producing Greener (Lower Carbon) Oil Through CO 2 -Enhanced Oil Recovery (CO 2 -EOR)

Conference presentation at at 22nd European IOR+ Symposium, The Hague, Netherlands, October 2–4, 2023. This study explored the sensitivity of the net life cycle greenhouse gas (GHG) emissions of a CO 2 -enhanced oil recovery (CO 2 -EOR) system to three critical input parameters: i) CO 2 capture efficiency (70%, 80%, 90%, and 95%), ii) electricity grid mix emission factor (400, 500, 600, and 700 kgCO 2 e/MWh), and iii) net CO 2 utilization rate (315, 421, 526, 789, and 1052 kgCO 2 /bbl [6, 8, 10, 15, and 20 Mcf/bbl]).

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Core Model Proposal #368: Adding fugitive CO2 emissions from fossil resources

This Core Model Proposal adds fugitive CO2 emissions from coal, crude oil, and natural gas resources to the data system. It also includes an improved method to replace outlier emissions factors for fossil resources. Lastly, it makes some minor changes to the data system and Model Interface headers to fix some inconsistencies in how resource technologies are named in the XMLs.

core model proposal↗
DOE OSTI2025

DOE Early Career Project Annual Report: Disentangling the factors controlling the emission of bioparticles that act as ice nucleating particles

This report describes the accomplishments, progress, and obstacles encountered during the first project year of the U.S. Department of Energy Biological and Environmental Research program Early Career project, “Disentangling the factors controlling the emission of bioparticles that act as ice nucleating particles.”

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Simulations of aerosol pH in China using WRF-Chem (v4.0): sensitivities of aerosol pH and its temporal variations during haze episodes

Aerosol pH is a fundamental property of aerosols in terms of atmospheric chemistry and its impact on air quality, climate, and health. Precise estimation of aerosol pH in chemical transport models (CTMs) is critical for aerosol modeling and thus influences policy development that partially relies on results from model simulations. We report the Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem) simulated PM 2.5 pH over China during a period with heavy haze episodes in Beijing, and explore the sensitivity of the modeled aerosol pH to factors including emissions of nonvolatile cations (NVCs) and NH 3 , aerosol phase state assumption, and heterogeneous production of sulfate. We find that default WRF-Chem could predict spatial patterns of PM 2.5 pH over China similar to other CTMs, but with generally lower pH values, largely due to the underestimation of alkaline species (NVCs and NH 3 ) and the difference in thermodynamic treatments between different models. Increasing NH 3 emissions in the model would improve the modeled pH in comparison with offline thermodynamic model calculations of pH constrained by observations. In addition, we find that the aerosol phase state assumption and heterogeneous sulfate production are important in aerosol pH predictions for regions with low relative humidity (RH) and high anthropogenic SO 2 emissions, respectively. These factors should be better constrained in model simulations of aerosol pH in the future. Analysis of the modeled temporal trend of PM 2.5 pH in Beijing over a haze episode reveals a clear decrease in pH from 5.2 ± 0.9 in a clean period to 3.6 ± 0.5 in a heavily polluted period. The increased acidity under more polluted conditions is largely due to the formation and accumulation of secondary species including sulfuric acid and nitric acid, even though being modified by alkaline species (NVCs, NH 3 ). Our result suggests that NO 2 oxidation is unlikely to be important for heterogeneous sulfate production during the Beijing haze as the effective pH for NO 2 oxidation of S(IV) is at a higher pH of ~6.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Regional Emissions Analysis of Light-Duty Battery Electric Vehicles

Light-duty battery electric vehicles (BEVs) can reduce both greenhouse gas (GHG) and criteria air pollutant (CAPs) emissions, when compared to gasoline vehicles. However, research has found that while today’s BEVs typically reduce GHGs, they can increase certain CAPs, though with significant regional variability based on the electric grid mix. In addition, the environmental performance of electric and gasoline vehicles is not static, as key factors driving emissions have undergone significant changes recently and are expected to continue to evolve. In this study, we perform a cradle-to-grave life cycle analysis using state-level generation mix and vehicle operation emission data. We generated state-level emission factors using a projection from 2020 to 2050 for three light-duty vehicle types. We found that BEVs currently provide GHG benefits in nearly every state, with the median state’s benefit being between approximately 50% to 60% lower than gasoline counterparts. However, gasoline vehicles currently have lower total NOx, urban NOx, total PM 2.5 , and urban PM 2.5 in 33%; 15%; 70%; and 10% of states, respectively. BEV emissions will decrease in 2050 due to a cleaner grid, but the relative benefits when compared to gasoline vehicles do not change significantly, as gasoline vehicles are also improving over this time.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

PNNL Dose-per-Unit-Release Factors for Calculating Radionuclide Emissions Potential-to-Emit Doses

Revised PNNL-Richland campus dose-per-unit release factors based on the Environmental Protection Agency code CAP88-PC Version 4.1.1 code are provided. In addition to maximum receptor dose factors, maximum air concentration dose factors are provided. The PNNL-Sequim campus dose-per-unit release factors are included, as well, based on the Environmental Protection Agency code COMPLY Version 1.7.1.

40 CFR 61 Subpart H↗
DOE OSTI2022

Higher than expected N 2 O emissions from soybean crops in the Pampas Region of Argentina: Estimates from DayCent simulations and field measurements

In developing countries, agriculture generally represents a large fraction of GHG emissions reported in National Inventories, and emissions are typically estimated using Tier 1 IPCC guidelines. However, field data and locally adapted simulation models can improve the accuracy of IPCC estimations. In this report we aimed to quantify anthropogenic N2O emissions from croplands of Argentina through field measurements, model simulations and IPCC guidelines. Here we measured N 2 O emissions and their controlling factors in 62 plots of the Pampas Region with corn, soybean and wheat/soybean crops and in unmanaged grasslands. We accounted for gross emissions from crops and background emissions from unmanaged grasslands to calculate net anthropogenic emissions from crops as the difference between them. We calibrated and evaluated the DayCent model and then simulated different weather and management scenarios. Finally, we applied IPCC guidelines to estimate anthropogenic N 2 O emissions at the same plots. The DayCent model accurately simulated annual N 2 O emission for all crops as compared to measured data (RMSE = 1.4 g N ha -1 day -1 ). Measured and simulated emissions in soybean crops were higher than in corn and wheat/soybean crops. Gross N 2 O emissions ranged from 1.4 to 5.1 kg N ha -1 yr -1 for current environmental (soil and weather) and management (crops and fertilizer doses) conditions. Background emissions ranged between 1.1 and 1.3 kg N ha -1 yr -1 , and therefore net anthropogenic emissions ranged from 0.3 to 4.0 kg N ha-1 yr -1 . IPCC Tier 1 emission factors underestimated N2O releases from soybean, that were on average 4.87 times greater when estimated with DayCent and observations (0.53 vs 2.47 and 2.69 kg N ha -1 yr -1 , respectively). On the contrary, IPCC estimates for corn and wheat/soybean crops were similar to modeled and measured values. Our results suggest that N 2 O emissions from the vast 15 million ha of soybean croplands in the Pampas Region may be substantially underestimated.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Field emission microscopy of carbon nanotube fibers: Evaluating and interpreting spatial emission

In this work, the authors quantify field emission properties of cathodes made from carbon nanotube (CNT) fibers. The cathodes were arranged in different configurations to determine the effect of cathode geometry on the emission properties. Various geometries were investigated including (1) flat cut fiber tip, (2) folded fiber, (3) looped fiber, and (4) fibers wound around a cylinder. The authors employ a custom field emission microscope to quantify I-V characteristics in combination with laterally resolved field-dependent electron emission area. Additionally, they look at the very early emission stages, first when a CNT fiber is turned on for the first time, which is then followed by multiple ramp-up/down runs. Upon the first turn on, all fibers demonstrated limited and discrete emission area. During ramping runs, all CNT fibers underwent multiple (minor and/or major) breakdowns, which improved emission properties in that turn-on field decreased and field enhancement factor and emission area both increased. It is proposed that breakdowns are responsible for removing initially undesirable emission sites caused by stray fibers higher than average. This initial breakdown process gives way to a larger emission area that is created when the CNT fiber subcomponents unfold and align with the electric field. Overall, the authors' results form the basis for careful evaluation of CNT fiber cathodes for dc or low frequency pulsed power systems in which large uniform area emission is required or for narrow beam high frequency applications in which high brightness is a must.

Image processing↗