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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Improvement of aerosol optical depth data for localized solar resource assessment

Solar irradiance, especially for direct normal irradiance (DNI), is sensitive to the atmospheric aerosols, which can strongly extinguish DNI over areas with elevated aerosol loadings. The National Solar Radiation Database (NSRDB), developed by the National Renewable Energy Laboratory (NREL), uses AOD from MERRA-2 reanalysis and is further downscaled from 0.5° to 2-km based on elevation. However, the elevation-based downscaling may not accurately represent AOD, especially over the areas with large AOD gradients. This study examined whether the 1-km MODIS MAIAC satellite-retrieved AOD product can better represent the AOD distribution and be used to improve solar irradiance assessment. We focused on areas with relatively high AOD over North America (California, and New York City, US, and Mexico City in Mexico, in particular). The evaluation of MAIAC AOD and MERRA-2 AOD against ground-truth AERONET AOD shows that MAIAC AOD exhibits smaller RMSE by about 0.05 and higher correlation coefficient by 0.1-0.6 than MERRA-2 AOD. In addition, MERRA-2 AOD shows larger negative bias. The simulated DNI using MAIAC AOD (DNIMAIAC) and using MERRA-2 AOD (DNINSRDB) were evaluated with DNI observations. The results show the performance of DNIMAIAC is better than that of DNINSRDB with smaller RMSE by 0.5-1.5%, smaller positive mean bias by 0.8-3.1% and comparable correlation for the 3 sites analyzed. Overall, 1-km MAIAC AOD shows higher accuracy than 2-km elevation-based MERRA-2 AOD, leading to better performance of the simulated DNI using MAIAC AOD. Therefore, 1-km MAIAC AOD can be used to improve the accuracy of solar resource assessment.

14 SOLAR ENERGY↗
DOE OSTI2022

Equal abundance of summertime natural and wintertime anthropogenic Arctic organic aerosols

Aerosols play an important yet uncertain role in modulating the radiation balance of the sensitive Arctic atmosphere. Organic aerosol is one of the most abundant, yet least understood, fractions of the Arctic aerosol mass. Here we use data from eight observatories that represent the entire Arctic to reveal the annual cycles in anthropogenic and biogenic sources of organic aerosol. We show that during winter, the organic aerosol in the Arctic is dominated by anthropogenic emissions, mainly from Eurasia, which consist of both direct combustion emissions and long-range transported, aged pollution. In summer, the decreasing anthropogenic pollution is replaced by natural emissions. These include marine secondary, biogenic secondary and primary biological emissions, which have the potential to be important to Arctic climate by modifying the cloud condensation nuclei properties and acting as ice-nucleating particles. Their source strength or atmospheric processing is sensitive to nutrient availability, solar radiation, temperature and snow cover. Our results provide a comprehensive understanding of the current pan-Arctic organic aerosol, which can be used to support modelling efforts that aim to quantify the climate impacts of emissions in this sensitive region.

58 GEOSCIENCES↗
DOE OSTI2025

Sensitivity of Simulated Polar Climate to Improved Partitioning of Spectral Solar Irradiance Between Visible and Near‐Infrared Bands

The solar radiative processes that contribute to Earth's surface and atmospheric energy budgets are strongly dependent on wavelength. For example, snow and water vapor become more absorptive as incident radiation shifts from visible (VIS) to near-infrared (NIR) wavelengths. Some earth system models (ESMs) aggregate solar radiation into just two bands (VIS and NIR) partitioned at 0.7 μm for transmission between the atmospheric and surface components. In the widely used radiative transfer model RRTMG_SW this partition is near the center of the overlap spectral band spanning 0.625–0.778 μm, whose flux is often approximated as being evenly divided between the VIS and NIR surface bands. Using a hyperspectral radiative transfer model, we show that the fractional downwelling surface flux within the overlap band is usually distributed about 55.5%:44.5% VIS:NIR. This improved approximation shifts as much as 4.27 W m −2 from the NIR to the VIS band, leading to an instantaneous decrease in surface absorption of up to 0.91 W m −2 over snow-covered surfaces. Century-long fully coupled ESM simulations show surface absorption over snow decreases by over 1.6 W m −2 . The coupled response in sea ice regions amplifies the initial forcing ten-fold, and increases seasonal sea ice area by up to 4.9%. These results highlight the importance of accurately representing the spectral distribution of solar radiation in the cryosphere.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Final Technical Report: Impact of Wildfires on Solar Generation, Reserves, and Energy Prices

This study quantifies the potential impacts of wildfires on the California grid, specifically the impacts under three different wildfire scenarios: a "no wildfire" scenario and two wildfire-specific scenarios, "2020 wildfire" and "enhanced wildfire" (with both wildfire scenarios assuming spatial distribution of the wildfire location the same as the 2020 fires). The study combines each scenario with two solar energy infrastructures: one corresponding to the current solar installation and the other to future (midcentury) solar installation. The analysis is conducted using state-of-the-science modeling tools: primarily WRF-Chem for atmospheric modeling with chemistry to account for impacts of wildfires on solar radiation and PLEXOS for electricity market simulations. The analysis suggests that wildfires can significantly attenuate solar radiation at both short downwind distances as well as far from the emissions sources. Although the study is limited in scope, and the analysis studies only a few of the many factors that can affect photovoltaic generation and electricity markets, it indicates that wildfire smoke is an important factor that needs to be carefully considered and analyzed in planning the future grid.

electricity market↗
DOE OSTI2022

A dehydrated space-weathered skin cloaking the hydrated interior of Ryugu

Abstract Without a protective atmosphere, space-exposed surfaces of airless Solar System bodies gradually experience an alteration in composition, structure and optical properties through a collective process called space weathering. The return of samples from near-Earth asteroid (162173) Ryugu by Hayabusa2 provides the first opportunity for laboratory study of space-weathering signatures on the most abundant type of inner solar system body: a C-type asteroid, composed of materials largely unchanged since the formation of the Solar System. Weathered Ryugu grains show areas of surface amorphization and partial melting of phyllosilicates, in which reduction from Fe 3+ to Fe 2+ and dehydration developed. Space weathering probably contributed to dehydration by dehydroxylation of Ryugu surface phyllosilicates that had already lost interlayer water molecules and to weakening of the 2.7 µm hydroxyl (–OH) band in reflectance spectra. For C-type asteroids in general, this indicates that a weak 2.7 µm band can signify space-weathering-induced surface dehydration, rather than bulk volatile loss.

Astronomy & Astrophysics↗
DOE OSTI2025

Passive radiative thermal management using phase-change metasurfaces

Abstract Realizing innovative composite materials with passive thermal management capabilities and minimal ecological footprints is a challenging but much sought-after goal that would have a transformative effect on renewable energy sciences. We demonstrate an environmentally friendly metasurface utilizing vanadium dioxide (VO 2 ) that offers responsiveness to ambient temperature and potentially long-term stability. The metasurface enables passive thermal management by self-adjusting its absorptivity and emissivity response over a broad bandwidth ranging from visible to mid-infrared (IR) wavelengths. Above the VO 2 phase transition the metasurface exhibits increased mid-IR emissivity and reduced visible/near-IR absorptivity, creating an efficient radiative emission channel in the first atmospheric transparency window with reduced absorption of solar radiation. In contrast, below VO 2 ’s transition temperature, the metasurface increasingly absorbs sun light while minimizing mid-IR radiative heat losses. Moreover, a functional silicon layer eliminates the need for an additional capping layer commonly employed to protect VO 2 from environmental degradation. The additional protective layer often impedes the use and performance of VO 2 based devices in terrestrial as well as spacecraft applications. Therefore, the proposed durable and eco-friendly metasurface will be an excellent candidate for essential passive thermal regulation systems across residential and terrestrial applications.

42 ENGINEERING↗
DOE OSTI2021

Smart Methane Emission Detection System Development (Final Report)

Working with the Department of Energy's National Energy Technology Laboratory, Southwest Research Institute® (SwRI®) developed a system to identify methane leaks reliably, accurately, and autonomously at critical midstream sections of the natural gas distribution network in real-time for the purpose of mitigating methane emissions using Optical Gas Imaging (OGI) cameras. SwRI's Smart Leak Detection – Methane (SLED/M) adds a high degree of automation to the process of methane leak detection to minimize sources of human error, minimize response time to a leak event, and maximize midstream visibility. Furthermore, SwRI has been working towards integrating Quantitative OGI (QOGI) capabilities into this existing technology. By leveraging Deep Learning, SwRI now has the capability to estimate fugitive emission leak rates quickly and reliably, which allows operators to detect emissions, quantify leak rate, prioritize repairs, and validate the repairs in a single instrument. The next generation QOGI technology leverages the same cameras used in Leak Detection and Repair (LDAR) programs, with improvements in safety and speed for traditional quantification-based repairs, ultimately leading to less overhead cost for the operators. The goals for this research were to develop two types of models with the following goals: Run in real-time on the edge (≥ 12 Hz), Classification: Achieve less than 5% false positive detection, Classification: Achieve ≥ 95% methane plume detection rate, Regression: achieve ≤ 10 standard cubic feet per hour (scfh) prediction > 70% of the time. In order to achieve these results, multiple infrared (IR) and other sensors were investigated in tandem with the midwave IR (MWIR) OGI to provide additional information to train the underlying models. Information on atmospheric conditions including humidity, temperature, pressure, and solar radiation was provided by a weather station. Several machine learning and deep learning architectures and methods, including looking at quantized classification networks and regressions networks, were explored. As further data was collected, curated, and labeled, it allowed for more refined regressive networks to be adequately trained, leading to better insight into the true flow rates being observed. An important valuable deliverable of this research effort was the development of an advanced network which underwent multiple iterations capable of giving a continuous output. The current network has a predicted mean average percentage error (MAPE) of 12.3% just outside our target goal of 10.00%, but an accuracy of 97.78% at ±50 scfh, well within the overall goal for the Department of Energy (DOE) program. Upon closer inspection, it was observed that more than 10% of datapoints contributing to the MAPE predictions were the result of low flow rate predictions and are beyond the sensitivity of instrument measurement as a result of normal operational variation and noise.

03 NATURAL GAS↗
DOE OSTI2020

Progress on the National Solar Radiation Data Base (NSRDB): A new DNI computation

This study introduces a new technique to compute direct normal irradiance (DNI) for improving the National Solar Radiation Data Base (NSRDB). A finite-surface integration algorithm is developed to compute solar radiation in differential solid angles and efficiently infer its contribution to a surface perpendicular to the solar direction. A lookup table of cloud bi-directional transmittance distribution function (BTDF) is developed by use of the discrete ordinates radiative transfer (DISORT) model for possible solar and observing directions and various cloud optical and microphysical properties. In each solar incident direction, DNI is given by the cloud BTDFs from approximately 200 differential solid angles. The simulated DNI is calibrated and evaluated using surface observations at the National Renewable Energy Laboratory's (NREL's) Solar Energy Research Laboratory (SRRL) and the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) facility.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Smart Methane Emission Detection System Development (Final Report)

Working with the Department of Energy’s National Energy Technology Laboratory, Southwest Research Institute® (SwRI®) developed a system to identify methane leaks reliably, accurately, and autonomously at critical midstream sections of the natural gas distribution network in real- time for the purpose of mitigating methane emissions using Optical Gas Imaging (OGI) cameras. SwRI’s Smart Leak Detection – Methane (SLED/M) adds a high degree of automation to the process of methane leak detection to minimize sources of human error, minimize response time to a leak event, and maximize midstream visibility. Furthermore, SwRI has been working towards integrating Quantitative OGI (QOGI) capabilities into this existing technology. By leveraging Deep Learning, SwRI now has the capability to estimate fugitive emission leak rates quickly and reliably, which allows operators to detect emissions, quantify leak rate, prioritize repairs, and validate the repairs in a single instrument. The next generation QOGI technology leverages the same cameras used in Leak Detection and Repair (LDAR) programs, with improvements in safety and speed for traditional quantification-based repairs, ultimately leading to less overhead cost for the operators. The goals for this research were to develop two types of models with the following goals: 1. Run in real-time on the edge (≥ 12 Hz) 2. Classification: Achieve less than 5% false positive detection 3. Classification: Achieve ≥ 95% methane plume detection rate 4. Regression: achieve ≤ 10 standard cubic feet per hour (scfh) prediction > 70% of the time In order to achieve these results, multiple infrared (IR) and other sensors were investigated in tandem with the midwave IR (MWIR) OGI to provide additional information to train the underlying models. Information on atmospheric conditions including humidity, temperature, pressure, and solar radiation was provided by a weather station. Several machine learning and deep learning architectures and methods, including looking at quantized classification networks and regressions networks, were explored. As further data was collected, curated, and labeled, it allowed for more refined regressive networks to be adequately trained, leading to better insight into the true flow rates being observed. An important valuable deliverable of this research effort was the development of an advanced network which underwent multiple iterations capable of giving a continuous output. The current network has a predicted mean average percentage error (MAPE) of 12.3% just outside our target goal of 10.00%, but an accuracy of 97.78% at ±50 scfh, well within the overall goal for the Department of Energy (DOE) program. Upon closer inspection, it was observed that more than 10% of datapoints contributing to the MAPE predictions were the result of low flow rate predictions and are beyond the sensitivity of instrument measurement as a result of normal operational variation and noise.

03 NATURAL GAS↗
DOE OSTI2023

Impact of Wildfires on Solar Resource Availability in California in a Changing Climate

Wildfires can emit large amounts of atmospheric particulate matters and influence not only air quality but also availability of photovoltaic (PV) generation due to scattering and absorption of solar radiation. Under anthropogenic changing climate, wildfire activity is projected to increase over western North America due to drier and warmer climate, implying increasing impact on solar resource and larger uncertainty in solar generation especially in regions with faster PV penetration. This study focuses on quantifying the impact of wildfires on aerosol optical depth (AOD) and thus solar resource over California using National Solar Radiation Database (NSRDB), developed by the National Renewable Energy Laboratory (NREL). This assessment includes historical analysis and estimation of solar resource under wildfire scenarios (2020 wildfire and an enhanced wildfire scenario based on 2020 wildfires). Historical analysis for the period of July-October 2019/2020 (low/high fire activity period) shows that the averaged global horizontal irradiance (GHI) and direct normal irradiance (DNI) are reduced by about 30 and 90 W m-2 (5.6 and 15.3%), respectively, during high fire activity period. To create AOD dataset for enhanced fire scenario, 165% increase in burn area (in around 2050) is selected based on comprehensive literature review, which is further applied to the Fire INventory from NCAR (FINN) fire emission. WRF-Chem model with the enhanced FINN emissions is used to simulate and represent a preserving spatial distribution of burned areas and wildfire-emitted aerosols. Our initial analysis suggests that the"enhanced 2020 wildfire" AOD can increase by a factor of 1.3 - 2, which can significantly reduce solar irradiance and increase uncertainty in generation and reliability of power system in extreme wildfire events under a high solar penetration scenario. Overall, this study provides an estimate of the impacts of wildfires on solar resource to make informed decisions on reserve planning, generation scheduling, and reliability investments.

aerosol optical depth↗
DOE OSTI2022

Aerodynamic Analysis of Wind Loading on Parabolic Trough Collectors Using High-Fidelity CFD Modeling

Wind loading on parabolic solar collector support structures is the key driver for material costs. As identified by NREL's CSP Best Practices project [1], ability to predict wind-loading in deep-arrays and the impact of edge effects has potential to decrease levelized cost of electricity (LCoE) by 15%. In this study, we present a high-fidelity computational model that can model the flow around deep arrays of parabolic troughs under varying turbulent inflow conditions. Ability to accurately reproduce atmospheric boundary layer (ABL) profiles is first demonstrated through Large Eddy Simulation (LES) simulations and compared against wind tunnel measurements. Thereafter, unsteady turbulent flow past single row and six row configurations is computed using hybrid RANS/LES simulations. Investigations of wind loading, through parametric tilt angle variations of single row and on waked collectors in six-row configuration, are used to highlight design considerations for parabolic troughs only possible through high-fidelity unsteady calculations.

aerodynamics↗
DOE OSTI2019

Solar-Forecast GridAPPS-D Application [SWR-18-36]

Persistent model serves as the baseline in the intra-hour forecasting of solar radiation due to the extensive computing efforts from the numerical weather prediction (NWP) models and the lack of surface observations in cloud as well as other atmospheric properties. The smart persistent model actively updates the extraterrestrial solar radiation with time and is an important improvement from the persistent model while the cloud conditions are assumed unchanged by giving constant clear-sky indexes. We developed a Physics-based Smart Persistent model for Intra-hour solar forecasting (PSPI) to further improve the accuracy of the smart persistent model. We used a cloud retrieval technique developed by Xie and Liu (2013) to estimate cloudy fraction and cloud albedo using surface-based observations of solar radiation. The solar radiation in future time steps is accurately given by actively computing individual cloud albedo related to the future solar position. Our evaluation studies indicated that the PSPI model significantly increased the accuracy in the short-term forecast of solar radiation, especially in thin cloud conditions or those covered by broken clouds.

Xie, Yu↗
DOE OSTI2021

Strong Local Evaporative Cooling Over Land Due to Atmospheric Aerosols

Abstract Aerosols can enhance terrestrial productivity through increased absorption of solar radiation by the shaded portion of the plant canopy—the diffuse radiation fertilization effect. Although this process can, in principle, alter surface evaporation due to the coupling between plant water loss and carbon uptake, with the potential to change the surface temperature, aerosol‐climate interactions have been traditionally viewed in light of the radiative effects within the atmosphere. Here, we develop a modeling framework that combines global atmosphere and land model simulations with a conceptual diagnostic tool to investigate these interactions from a surface energy budget perspective. Aerosols increase the terrestrial evaporative fraction, or the portion of net incoming energy consumed by evaporation, by over 4% globally and as much as ∼40% regionally. The main mechanism for this is the increase in energy allocation from sensible to latent heat due to global dimming (reduction in global shortwave radiation) and slightly augmented by diffuse radiation fertilization. In regions with moderately dense vegetation (leaf area index >2), the local surface cooling response to aerosols is dominated by this evaporative pathway, not the reduction in incident radiation. Diffuse radiation fertilization alone has a stronger impact on gross primary productivity (+2.18 Pg C y −1 or +1.8%) than on land evaporation (+0.18 W m −2 or +0.48%) and surface temperature (−0.01 K). Our results suggest that it is important for land surface models to distinguish between quantity (change in total magnitude) and quality (change in diffuse fraction) of radiative forcing for properly simulating surface climate.

Chakraborty, TC↗
DOE OSTI2023

Atmospheric Humidity Underlies Irreproducibility of Formamidinium Lead Iodide Perovskites

Metal halide perovskite solar cells (PSCs) are infamous for their batch-to-batch and lab-to-lab irreproducibility in terms of stability and performance. Reproducible fabrication of PSCs is a critical requirement for market viability and practical commercialization. PSC irreproducibility plagues all levels of the community; from institutional research laboratories, start-up companies, to large established corporations. Here, in this work, the critical function of atmospheric humidity to regulate the crystallization and stabilization of formamidinium lead triiodide (FAPbI 3 ) perovskites is unraveled. It is demonstrated that the humidity content during processing induces profound variations in perovskite stoichiometry, thermodynamic stability, and optoelectronic quality. Almost counterintuitively, it is shown that the presence of humidity is perhaps indispensable to reproduce phase-stable and efficient FAPbI 3 -based PSCs.

14 SOLAR ENERGY↗
DOE OSTI2022

Short-term solar radiation forecast using total sky imager via transfer learning

Ground-based sky cameras, which capture hemispherical images, have been extensively used for localized monitoring of clouds. This paper proposes a short-term forecasting approach based on transfer learning using Total Sky-Imager (TSI) images of the Southern Great Plains (SGP) site obtained from the Atmospheric Radiation Measurement (ARM) dataset. An accurate estimation of solar irradiance using TSI is key for short-term solar energy generation forecasting and optimal energy consumption planning. We make use of deep neural network architectures such as AlexNet and ResNet-101 to extract the underlying deep convolution features from TSI images and then train using an ensemble learning approach to model and forecast solar radiation. We demonstrate the performance of the proposed approach by showcasing the best and worst cases. Thus, the transfer learning approach significantly reduces the time and resources required for modeling solar radiation. We outperform with reference to another state-of-art technique for solar modeling using TSI images at different forecast lead times.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Sea ice and atmospheric circulation shape the high-latitude lapse rate feedback

Abstract Arctic amplification of anthropogenic climate change is widely attributed to the sea-ice albedo feedback, with its attendant increase in absorbed solar radiation, and to the effect of the vertical structure of atmospheric warming on Earth’s outgoing longwave radiation. The latter lapse rate feedback is subject, at high latitudes, to a myriad of local and remote influences whose relative contributions remain unquantified. The distinct controls on the high-latitude lapse rate feedback are here partitioned into “upper” and “lower” contributions originating above and below a characteristic climatological isentropic surface that separates the high-latitude lower troposphere from the rest of the atmosphere. This decomposition clarifies how the positive high-latitude lapse rate feedback over polar oceans arises primarily as an atmospheric response to local sea ice loss and is reduced in subpolar latitudes by an increase in poleward atmospheric energy transport. The separation of the locally driven component of the high-latitude lapse rate feedback further reveals how it and the sea-ice albedo feedback together dominate Arctic amplification as a coupled mechanism operating across the seasonal cycle.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Meteorological Conditions and Atmospheric Components Concentration in Urban Sites in Knoxville, USA. 2024

This dataset, which contains five csv files, reports several meteorological conditions such as temperature, wind speed, solar radiation, and net radiation measured in Cumberland Estates Park (CEP) and Socially Equal Energy Efficient Development (SEEED) sites in Knoxville, Tennessee, USA. Also, hourly concentration of particulate matter (PM) with different aerodynamic diameter and inorganic gases such as ozone and nitrogen dioxide measured in the two are included in this dataset. The concentrations of PM and inorganic gases were monitored using the MODULAIR, a low-cost sensor equipped with a solar power module. The measurement of the concentration of biogenic and anthropogenic volatile organic compounds (VOCs) of the two sites was determined using a High-Resolution Proton Transfer Reaction Time of Flight Mass Spectrometer (PTR-ToF-MS). The VOCs were collected using miniature canister (400 mL) equipped with female RAVEqc valve to 1/4” male compression fitting and an integrated passive air sampling kit. This work is a part of a larger study which investigates the impact of soil moisture and plant evapotranspiration on ambient temperature and relative humidity in several city parks in Knoxville, Tennessee.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Atmospheric Escape From TOI-700 d: Venus versus Earth Analogs

The recent discovery of an Earth-sized planet (TOI-700 d) in the habitable zone of an early-type M-dwarf by the Transiting Exoplanet Survey Satellite constitutes an important advance. In this Letter, we assess the feasibility of this planet to retain an atmosphere – one of the chief ingredients for surface habitability – over long timescales by employing state-of-the-art magnetohydrodynamic models to simulate the stellar wind and the associated rates of atmospheric escape. We take two major factors into consideration, namely, the planetary atmospheric composition and magnetic field. In all cases, we determine that the atmospheric ion escape rates are potentially a few orders of magnitude higher than the inner Solar system planets, but TOI-700 d is nevertheless capable of retaining a 1 bar atmosphere over gigayear timescales for certain regions of the parameter space. The simulations show that the unmagnetized TOI-700 d with a 1 bar Earth-like atmosphere could be stripped away rather quickly (< 1 gigayear), while the unmagnetized TOI-700 d with a 1 bar CO 2 -dominated atmosphere could persist for many billions of years; we find that the magnetized Earth-like case falls in between these two scenarios. We also discuss the prospects for detecting radio emission of the planet (thereby constraining its magnetic field) and discerning the presence of an atmosphere.

79 ASTRONOMY AND ASTROPHYSICS↗