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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Coast-Urban-Rural Atmospheric Gradient Experiment

Accurately representing the climate and weather variability within cities and providing well-tested representations of the impacts of urban systems on the atmospheric environment are challenges for current earth system models (ESMs). Field data for testing and developing these models are critical to addressing these limitations. The Atmospheric Radiation Measurement (ARM) user facility will support a field campaign aimed at understanding how different surface-atmosphere interactions around a city are influencing its climate. The Coast-Urban-Rural Atmospheric Gradient Experiment (CoURAGE) is expected to operate from December 2024 to November 2025 in and around Baltimore, Maryland. With its aging infrastructure, growing susceptibility to heat and flooding, and ongoing issues with air and water pollution, Baltimore is characteristic of many large industrial cities in the Eastern United States. ARM, a U.S. Department of Energy (DOE) Office of Science user facility, plans to deploy one of its three mobile observatories at Morgan State University’s Clifton Park site in downtown Baltimore. Ancillary ARM sites are also planned for rural Maryland, northwest of the city; and to the southern end of Kent Island in Chesapeake Bay. Data from CoURAGE will complement measurements from the Baltimore Social-Environmental Collaborative (BSEC), one of four DOE Urban Integrated Field Laboratories that will operate in cities across the United States to study urban climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Inferring building height from footprint morphology data

As cities continue to grow globally, characterizing the built environment is essential to understanding human populations, projecting energy usage, monitoring urban heat island impacts, preventing environmental degradation, and planning for urban development. Buildings are a key component of the built environment and there is currently a lack of data on building height at the global level. Current methodologies for developing building height models that utilize remote sensing are limited in scale due to the high cost of data acquisition. Other approaches that leverage 2D features are restricted based on the volume of ancillary data necessary to infer height. Here, we find, through a series of experiments covering 74.55 million buildings from the United States, France, and Germany, it is possible, with 95% accuracy, to infer building height within 3 m of the true height using footprint morphology data. Our results show that leveraging individual building footprints can lead to accurate building height predictions while not requiring ancillary data, thus making this method applicable wherever building footprints are available. The finding that it is possible to infer building height from footprint data alone provides researchers a new method to leverage in relation to various applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Equivalent Point Sources for Simulating Nuclear/Radiological Search Operations

Modeling and simulation can be used to estimate the detection of different types and strengths of radioactive sources. Simulations of shielded gamma-ray sources in complex environments, such as searches in urban areas using vehicle-mounted detectors, can demonstrate what source strengths and shielding combinations should be able to be detected. For faster calculations, gamma-emitting sources that could have different shielding layers can be simulated ahead of time, resulting in equivalent point source emission distributions that can be used in larger simulation models. Larger-scale models will then run faster using equivalent point sources because the shielding layers around the sources have already been accounted for. Accompanying this paper are 260 equivalent point source emission files for 72 sources with different shielding layers, formatted for three different Monte Carlo codes. Users wanting to request versions of the SCALE and/or MCNP software can find details here: https://rsicc.ornl.gov/

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

TRACER-ACE: Aerosol Characterization Experiment Field Campaign Report

An objective for the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Tracking Aerosol Convection Interactions Experiment (TRACER) is to provide high-temporal-and-spatial resolution observations of convective clouds in the Houston region, over a broad range of environmental and aerosol regimes (Jensen et al. 2022). The TRACER siting strategy was to deploy the first ARM Mobile Facility (AMF1), with its full suite of cloud, aerosol, precipitation, and atmospheric state measurement capabilities, in a region that experiences the full diversity of aerosol properties from the Houston domain including rural, urban, and industrial atmospheric aerosol environments (see Figure 1).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

MEP Metric Correlations with Socioeconomic and Built Environment Factors [Slides]

NREL's Mobility Energy Productivity tool, or MEP, quantifies the ability of an area's transportation system to connect individuals to goods, services, employment opportunities, and other activities while accounting for time, cost, and energy. However, the MEP tool itself does not examine correlations between mobility energy productivity and other sociodemographic and built environment variables relevant to the urban and transportation planning space. Examining these correlations could have two possible implications -- first, understanding what factors correlate with mobility energy productivity could help urban planners make equitable decisions in allocating transportation resources. Second, as the MEP has not been calculated for all urban areas in the US and is computationally expensive, if other publicly available variables were predictive enough of MEP then a simple model could be used to predict MEP instead of having to compute it for an area for which it has not been updated. A statistical analysis to investigate both of these questions is presented, with many significant associations found between the MEP and identified variables of interest.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Dynamic integration of GCAM-Demeter and CLUBS-Select: Datasets on urban extensification effects on land cover, crop yields, net primary production, and CO2 emissions

The datasets provide background data from McManamay et al. (2024) Nature Communications Earth and Environment. We integrate projected dynamic non-urban lands from GCAM-Demeter with projected dynamic urban lands from SELECT from 2015 to 2100 at 1-km resolution to examine stress to the land system, compromised crop production, and losses in Net Primary Production (NPP), that can arise from the competition over land resources. These datasets include changes to non-urban land use and land cover, estimated losses in crop yields, losses in NPP, and increases in CO2 emissions.

Earth Systems↗
DOE OSTI2023

Impact of Urban Representation on Simulation of Hurricane Rainfall

Abstract Taking the examples of Hurricane Florence (2018) over the Carolinas and Hurricane Harvey (2017) over the Texas Gulf Coast, the study attempts to understand the performance of slab, single‐layer Urban Canopy Model (UCM), and Building Environment Parameterization (BEP) in simulating hurricane rainfall using the Weather Research and Forecasting (WRF) model. The WRF model simulations showed that for an intense, large‐scale event such as a hurricane, the model quantitative precipitation forecast over the urban domain was sensitive to the model urban physics. The spatial and temporal verification using the modified Kling‐Gupta efficiency and Method for Object based Diagnostic and Evaluation in Time Domain suggests that UCM performance is superior to the BEP scheme. Additionally, using the BEP urban physics scheme over UCM for landfalling hurricane rainfall simulations has helped simulate heavy rainfall hotspots.

Geology↗
DOE OSTI2020

Suspect and Nontarget Screening for Contaminants of Emerging Concern in an Urban Estuary

This study used suspect and nontarget screening with high-resolution mass spectrometry to characterize the occurrence of contaminants of emerging concern (CECs) in the nearshore marine environment of Puget Sound (WA). In total, 87 non-polymeric CECs were identified; those confirmed with reference standards (45) included pharmaceuticals, herbicides, vehicle-related compounds, plasticizers, and flame retardants. Eight polyfluoroalkyl substances were detected; perfluorooctanesulfonic acid (PFOS) concentrations were as high as 72-140 ng/L at one location. Low levels of methamphetamine were detected in 41% of the samples. Transformation products of pesticides were tentatively identified, including two novel transformation products of tebuthiuron. While a hydrodynamic simulation, analytical results, and dilution calculations demonstrated the prevalence of wastewater effluent to nearshore marine environments, the identity and abundance of selected CECs revealed the additional contributions from stormwater and localized urban and industrial sources. For the confirmed CECs, risk quotients were calculated based on concentrations and predicted toxicities, and eight CECs had risk quotients >1. Dilution in the marine estuarine environment lowered the risks of most wastewater-derived CECs, but dilution alone is insufficient to mitigate risks of localized inputs. These findings highlighted the necessity of suspect and nontarget screening and revealed the importance of localized contamination sources in urban marine environments.

Tian, Zhenyu↗
DOE OSTI2025

Leveraging Open-Source Satellite-Derived Building Footprints for Height Inference

At a global scale, cities are growing and characterizing the built environment is essential for deeper understanding of human population patterns, urban development, energy usage, climate change impacts, among others. Buildings are a key component of the built environment and significant progress has been made in recent years to scale building footprint extractions from satellite datum and other remotely sensed products. Billions of building footprints have recently been released by companies such as Microsoft and Google at a global scale. However, research has shown that depending on the methods leveraged to produce a footprint dataset, discrepancies can arise in both the number and shape of footprints produced. Therefore, each footprint dataset should be examined and used on a case-by-case study. In this work, we find through two experiments on Oak Ridge National Laboratory and Microsoft footprints within the same geographic extent that our approach of inferring height from footprint morphology features is source agnostic. Regardless of the differences associated with the methods used to produce a building footprint dataset, our approach of inferring height was able to overcome these discrepancies between the products and generalize, as evidenced by 98% of our results being within 3m of the ground-truthed height. This signifies that our approach can be applied to the billions of open-source footprints which are freely available to infer height, a key building metric. This work impacts the broader domain of urban science in which building height is a key, and limiting factor.

Stipek, Clinton [ORNL] (ORCID:0000000280501096)↗
DOE OSTI2021

Evaluating the performance of WRF urban schemes and PBL schemes over Dallas-Fort Worth during a dry summer and a wet summer

This study evaluated the Weather Research and Forecasting (WRF) model sensitivity to different planetary boundary layer (PBL) schemes (the YSU and MYJ schemes) and urban schemes including the bulk scheme (BULK), single-layer urban canopy model (UCM), multi-layer building environment parameterization (BEP) model, and multi-layer building energy model (BEM). Daily reinitialization simulations were conducted over Dallas-Fort Worth during a dry summer month (July 2011) and a wet summer month (July 2015) with weaker (stronger) daytime (nocturnal) UHI in 2011 than 2015. All urban schemes overestimated the urban daytime 2m temperature in both summers, but BEP and BEM still reproduced the daytime urban cool island in dry summer. All urban schemes reproduced the nocturnal urban heat island, with BEP producing the weakest one due to its unrealistic urban cooling. BULK and UCM overestimated the urban canopy wind speed, while BEP and BEM underestimated it. The urban schemes showed prominent impact on daytime PBL profiles. UCM+MYJ showed a superior performance than other configurations. The relatively large (small) aspect ratio between building height and road width in UCM (BEM) was responsible for the overprediction (underprediction) of urban canopy temperature. The relatively low (high) building height in UCM (BEM) was responsible for the overprediction (underprediction) of urban canopy wind speed. Improving urban schemes and providing realistic urban parameters were critical for improving urban canopy simulation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Exploring the Spatial Relationship Between Demographic Indicators and the Built Environment of a City

In addition to global and regional drivers of urbanization, neighborhood development in urban areas across the United States has been shown to be influenced by various local socio-economic factors. These factors, despite varying across socio-economic groups, have large implications regarding a population’s vulnerability to extreme climate events, including heat waves resulting in adverse health impacts. Additionally, the demographics of an urban area can shape its infrastructural characteristics, causing different populations groups to face varying levels of risks and benefits. As a result, the urban morphology and socio-economic characteristics of a city are deeply intertwined; however, their interactions on a finer scale are not yet fully understood. This research aims to better understand the relationships between various socio-economic factors and the built environment of a city, considering variability in building types, and temperature patterns. This research focuses on the city of Las Vegas, NV, and uses spatial data analysis to understand the correlation between of socio-economic characteristics, building morphology, building characteristics, and temperature data to understand the correlation between these various factors. Results of these research shows there is a distinct pattern of clustering of socio-economic characteristics with the city and there is a distinct correlation between age and cost, socio-economic characteristics, and locations of high heat distribution within the city.

Singh, Ridhima↗
DOE OSTI2026

A Comprehensive Comparison of Building Height Products at a Global Level

The built environment continues to expand due to increasing human populations with some projections indicating additional growth of 2.5 billion persons by 2050. Buildings are a key component of the built environment and information on building height and urban morphology in general can help to better understand and address a host of development and urban planning issues including energy consumption, urbanization, population dynamics, urban heat islands, environmental degradation, and others. To date, several approaches have been developed to address the need for mapping building height at scale. These approaches can be grouped into two main categories: 1) directly measure height from remote sensing products or 2) indirectly estimate height from footprint morphology features at the building-by-building level. Due to a number of these global height datasets now being available for consumption and use across domains, there is a critical need to understand the differences displayed between these products and how the use of these may influence the outcome when applied. In this analysis, we compare and evaluate 5 global building height datasets: Global Human Settlement, World Settlement Footprint 3D, Global Building Morphology dataset, three-dimensional Global Building Footprints, and an approach developed at Oak Ridge National Laboratory (ORNL). Our analysis shows that, across 5 cities at a global scale with high-quality building height reference data, the approach developed by ORNL of inferring height at the building-by-building level is more accurate and consistent. This was evidenced by the ORNL product improving upon the baseline in all 5 cities, the only product to do so. These findings will aid researchers in choosing a global building height product that best meets their needs and provides global availability, consistency, and accuracy.

42 ENGINEERING↗
DOE OSTI2023

A dynamic parameterization of sulfuric acid–dimethylamine nucleation and its application in three-dimensional modeling

Sulfuric acid (SA) is a governing gaseous precursor for atmospheric new particle formation (NPF), a major source of global ultrafine particles, in environments studied around the world. In polluted urban atmospheres with high condensation sinks (CSs), the formation of stable SA–amine clusters, such as SA–dimethylamine (DMA) clusters, usually initializes intense NPF events. Coagulation scavenging and cluster evaporation are dominant sink processes of SA–amine clusters in urban atmospheres, yet these loss processes are not quantitatively included in the present parameterizations of SA–amine nucleation. We herein report a parameterization of SA–DMA nucleation, based on cluster dynamic simulations and quantum chemistry calculations, with certain simplifications to greatly reduce the computational costs. Compared with previous SA–DMA nucleation parameterizations, this new parameterization was able to reproduce the dependences of particle formation rates on temperature and CSs. We then incorporated it in a three-dimensional (3-D) chemical transport model to simulate the evolution of the particle number size distributions. Simulation results showed good consistency with the observations in the occurrence of NPF events and particle number size distributions in wintertime Beijing and represented a significant improvement compared to that using a parameterization without coagulation scavenging. Quantitative analysis shows that SA–DMA nucleation contributes significantly to nucleation rates and aerosol population during the 3-D simulations in Beijing (>99 % and >60 %, respectively). These results broaden the understanding of NPF in urban atmospheres and stress the necessity of including the effects of coagulation scavenging and cluster stability in simulating SA–DMA nucleation in 3-D simulations. Representing these processes is thus likely to improve model performance in particle source apportionment and quantification of aerosol effects on air quality, human health, and climate.

Li, Yuyang↗
DOE OSTI2023

TRACER-Coastal Urban Boundary-Layer Interactions with Convection (TRACER-CUBIC) Field Campaign Report

To better understand the complicated web of processes governing convective cloud life cycle and aerosol-convection interactions, the U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) user facility supported deployment of a variety of advanced atmospheric measurement systems to the greater Houston, Texas, area from 1 October 2021 to 30 September 2022 as part of the Tracking Aerosol Convection Interactions Experiment (TRACER). Houston was selected as a study area because isolated convection and a variety of aerosol conditions are common in this region. This one-year ARM Mobile Facility (AMF) deployment featured a four-month intensive operational period (IOP) during summer 2022 (1 June–30 September). The ARM instrumentation was deployed at three sites along an east-west transect from La Porte, Texas to an ancillary site in a less-polluted rural region southwest of downtown Houston (Figure 1). At the La Porte Site, which is located near the Houston ship channel in an area that experiences significant pollution, the first ARM Mobile Facility (AMF1) was deployed. During the IOP, the ARM tethered balloon system (TBS) operated at the ancillary site. The second-generation C-Band Scanning ARM Precipitation Radar (CSAPR) operated near Pearland, Texas, roughly halfway between the Laporte and ancillary sites. As part of the TRACER- Coastal Urban Boundary-Layer Interactions with Convection (CUBIC) project, three boundary-layer profiling systems) were deployed along a north-south transect spanning from the University of Houston Coastal Center to the Aldine site north of downtown Houston (also blue dot in Figure 1) during the TRACER IOP. These systems included the National Oceanic and Atmospheric Administration (NOAA) National Severe Storms Laboratory CLAMPS2 (C2), which was deployed at the UHCC, the University of Wisconsin SPARC, which was deployed at the ARM CSAPR site near Pearland (orange diamond in middle of map in Figure 1), and the University of Oklahoma CLAMPS1 (C1), which was deployed at Aldine. These three systems have been successfully operated in various field campaigns, providing data sets that collectively offer new insights into atmospheric-boundary-layer (ABL) processes, sea-breeze (SB) circulations, and convection initiation (CI). For the TRACER IOP window, these systems ran continuously between 1 June and 26 September, 2022. Due to commitments to NOAA projects, the Doppler lidar at the UHCC site was not available until 24 June 2022. The CLAMPS and SPARC profiling systems are self-contained platforms that have benefited from several years of development and deployment. Instruments and data processing were maintained remotely, which made the 4-month deployment for the TRACER-CUBIC IOP period possible. The same basic instrument configuration comprises each system: a scanning Doppler wind lidar for flow characterization and passive profiler(s) for characterizing planetary-boundary-layer (PBL) thermodynamic properties. Each platform includes a Halo Streamline Doppler wind lidar, an Atmospheric Emitted Radiance Interferometer (AERI), and a surface meteorology station. CLAMPS1 and CLAMPS2 each also include a microwave radiometer (MWR, Figure 1d). The TRACER-CUBIC hypotheses included (i) Interactions of SB and urban circulations and how they affect the PBL structure in the Houston environment, causing spatially (horizontally and vertically) and temporally highly variable flow patterns, (ii) heat, moisture, and aerosol transport and mixing depend on these flow dynamics, and (iii) an improved understanding of the flow patterns and PBL structure are critical for investigating the processes leading to CI. To test these hypotheses, the project aimed at (i) characterizing SB circulations and their impacts on the diurnal evolution of the structure of the ABL, (ii) studying the evolution of Houston’s complex urban boundary layer, and (iii) identifying effects of urban-induced circulations on pre-convective environments. TRACER-CUBIC observations generally provide good coverage during the summer IOP. Initial screening of the data indicates a good number of cases with bay-breeze (BB) and/or SB signatures, local CI, and interesting boundary-layer features such as strong nocturnal low-level jets (LLJs, Table 1). The numbers listed in rows 3-5 in this table will be further updated as part of ongoing in-depth analyses and systematic identification of local circulations and CI events. More detailed information about the data availability and quality for each instrument is provided in the “readme” files that were submitted to the ARM Data Center along with each archived data sets. These “readme” files also provide instrument descriptions, information about the data collection and processing procedures, data formats, and any additional information relevant for further data analysis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

sup3ruhi (Super Resolution for Renewable Resource Data and Urban Heat Islands) [SWR-25-05]

Urban heat is a growing concern, particularly in dense metropolitan areas where high temperatures increase the risk of heat-related illness and drive energy expenses for cooling. Estimating the effects of urban heat remains a challenge due to limitations in describing the built environment, computational constraints, and the need for high-resolution data. This software presents open-source, computationally efficient machine learning methods that enhance the accuracy of urban temperature estimates compared to historical reanalysis data. Models trained using this software have been applied to urban microclimates in Los Angeles and Seattle showing greater accuracy and less bias when compared to low-resolution reanalysis datasets like ERA5 and even when compared to high-resolution mesoscale numerical weather models like WRF with an urban canopy model. Initial findings highlight how machine learning can support urban heat resilience planning by enabling improved assessments of local heat islands, mitigation strategies, and their energy implications. This software is an extension of (sup3r). This software supports the following publication: Buster, Grant, et al. Tackling Extreme Urban Heat: A Machine Learning Approach to Assess the Impacts of Climate Change and the Efficacy of Climate Adaptation Strategies in Urban Microclimates. arXiv:2411.05952, arXiv, 8 Nov. 2024. arXiv.org, https://doi.org/10.48550/arXiv.2411.05952. And has related public data records available at: Buster, Grant, Cox, Jordan, Benton, Brandon, and King, Ryan. Super-Resolution for Renewable Resource Data and Urban Heat Islands (Sup3rUHI). United States: N.p., 16 Oct, 2024. Web. https://data.openei.org/submissions/6220.

Buster, Grant [National Renewable Energy Laborator↗
DOE OSTI2025

A segmented approach to modeling building height: Delineating high-rise and low-rise buildings for enhanced height estimation

Understanding building height is imperative to the overall study of energy efficiency, population distribution, urban morphologies, emergency response, among others. Currently, existing approaches for modeling building height at scale are hindered by two pervasive issues. First, there is no consistent approach to quantify what a high-rise building is at a macro scale, leaving researchers unable to accurately compare results across geographies and domains. Second, high-rise buildings represent a small fraction of the built environment, implying data imbalance challenges that negatively affect current approaches. This is a problem of practical relevance since information on high-rise buildings is important for studies on urban heat islands, population dynamics, and pollution dispersion. Here, we introduce a novel approach to map building height which first identifies two distinct distributions within the built environment, with one being composed of low-rise buildings and one composed of high-rise buildings. We then develop an ensemble scheme where discrete specialist models are trained for each subset of low-rise buildings and high-rise buildings to infer building height from morphology features. For experiments mapping heights of 4.85 million buildings in Japan, we show an increase of 34 % in accuracy within 3m error when compared to the current state-of-the-art when modeling high-rise buildings, which based on KNN experimentation we define as any building > 12m . Our findings show that such an ensemble framework outperforms the current state-of-the-art approaches, which is especially relevant in relation to inferring height for high-rise buildings, a prominent issue of existing approaches for mapping the built environment.

97 MATHEMATICS AND COMPUTING↗