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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Phoenix Dust Storm (PHX-DUST) Scale: A Cooperatively Developed Dust Storm Scale for Phoenix, Arizona

Using extensive localized meteorological and air quality data for central Arizona from 2010 to 2023, we create a postevent dust storm scale for use by the primary stakeholders in central Arizona for the Phoenix metropolitan area called the Phoenix Dust Storm (PHX-DUST) scale. To ensure usability across a wide spectrum of users, a core concept was to “keep it simple.” The PHX-DUST scale is based on (i) maximum dust concentration for particulate matter (PM10) across the network in micrograms per cubic meter which determines category, e.g., “category 5 (the highest observed category)” and category 4; (ii) the number of network monitors achieving dust concentrations above a threshold of 500 μg m−3 (categorized as “widespread” or “isolated,” as measures of spatial extent); (iii) a duration parameter (which determines “long duration” or “short duration”); and (iv) a measure of wind speed over the affected area (maximum wind gust recorded over the network, which may not be the maximum wind of the storm). Using this index for the 189 dust storms impacting the Phoenix metropolitan area for the period 2010–23, the most severe dust storm occurred on 5 July 2011 and is classified as a “Category 5, Widespread, Long-Duration High-Gust” event. This initial attempt at defining the PHX-DUST scale holds valuable applications for research, education, and applied analyses. It demonstrates that a consortium of interested groups can effectively work to create products benefiting the weather community and general public. Here, the PHX-DUST scale can also serve as a foundational framework for application in other regions where dust storms pose a threat to the well-being of populations, infrastructure, and ecosystems.

Atmosphere↗
DOE OSTI2026

Ultra-faint Milky Way Satellites Discovered in Carina, Phoenix, and Telescopium with DELVE Data Release 3

We report the discovery of three Milky Way satellite candidates: Carina IV, Phoenix III, and DELVE 7, in the third data release of the DECam Local Volume Exploration survey (DELVE). The candidate systems were identified by cross-matching results from two independent search algorithms. All three are extremely faint systems composed of old, metal-poor stellar populations (τ ≳ 10 Gyr, [Fe/H] ≲−1.4). Carina IV (M V = −2.8; r 1/2 = 40 pc) and Phoenix III (M V = −1.2; r 1/2 = 19 pc) have half-light radii that are consistent with the known population of dwarf galaxies, while DELVE 7 (M V = 1.2; r 1/2 = 2 pc) is very compact and seems more likely to be a star cluster, though its nature remains ambiguous without spectroscopic follow-up. The Gaia proper motions of stars in Carina IV ($M_{\star} = 2250^{+1180}_{-830} M_⊙$) indicate that it is unlikely to be associated with the LMC, while DECam CaHK photometry confirms that its member stars are metal poor. Phoenix III ($M_{\star} = 520^{+660}_{-290} M_⊙$) is the faintest known satellite in the extreme outer stellar halo (D GC > 100 kpc), while DELVE 7 ($M_{\star} = 60^{+120}_{-40} M_⊙$) is the faintest known satellite with D GC > 20 kpc.

Tan, Chin Yi [Univ. of Chicago, IL (United States)↗
DOE OSTI2025

Directly imaging the cooling flow in the Phoenix cluster

In the centres of many galaxy clusters, the hot (approximately 10 7 kelvin) intracluster medium can become dense enough that it should cool on short timescales. However, the low measured star formation rates in massive central galaxies and the absence of soft X-ray lines from the cooling gas suggest that most of this gas never cools. This is known as the cooling flow problem. The latest observations suggest that black hole jets are maintaining the vast majority of gas at high temperatures. A cooling flow has yet to be fully mapped through all the gas phases in any galaxy cluster. Here we present observations of the Phoenix cluster using the James Webb Space Telescope to map the [Ne vi] λ 7.652-μm emission line, enabling us to probe the gas at 10 5.5 kelvin on large scales. These data show extended [Ne vi] emission that is cospatial with the cooling peak in the intracluster medium, the coolest gas phases and the sites of active star formation. Taken together, these imply a recent episode of rapid cooling, causing a short-lived spike in the cooling rate, which we estimate to be 5,000–23,000 solar masses per year. As a result, these data provide a large-scale map of gas at temperatures between 10 5 kelvin and 10 6 kelvin in a cluster core, and highlight the critical role that black hole feedback has in not only regulating cooling but also promoting it.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Onboard/Origin-Destination Survey - Phoenix - 2015

Valley Metro conducted an on-board transit survey during spring 2015. This project gathered updated travel behavior data from transit users that encompassed all rail and bus fixed-route services in the Phoenix metropolitan planning area. The study’s goal was to compile statistically accurate information about transit riders and how they use the transit system.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Quality-Controlled Meteorological Data from the Flood Control District of Maricopa County (FCDMC) Network, Phoenix, Arizona (1987-2024)

This dataset contains 15- or 30-minute interval meteorological data from the Flood Control District of Maricopa County (FCDMC), Arizona, USA, covering eight key variables across multiple sensor stations between 1987 and 2024. Each variable is stored as a separate CSV file, containing time-series data that have undergone rigorous quality control (QC) procedures and, where appropriate, short-gap interpolation for consistency. The quality control (QC) pipeline consisted of four sequential tests: (1) a range test to ensure all values fall within physically realistic limits, (2) a step test to identify abrupt and implausible changes between consecutive records, (3) a proximity test that validates flagged values from step test using data from nearby stations and exceedance probability thresholds, and (4) a persistence test to detect and remove periods of unrealistically constant readings. These thresholds were calibrated to Arizona’s environmental conditions and sensor specifications. After QC, short gaps (≤2 hours) were linearly interpolated to ensure consistent temporal resolution, except for wind variables. Due to a major upgrade in FCDMC’s data transmission system, only ALERT-2 protocol data (2016–2024) for wind variables are included; earlier ALERT-1 data were excluded because of irregular sampling and high missing rates. This dataset supports regional climate and infrastructure resilience studies by providing standardized, high-resolution meteorological data for the greater Phoenix metropolitan area.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Data & Code from Phoenix CPPP Phase 2 Analysis

This data and code package supports the analysis presented in “Beyond Surface Cooling: Comprehensive Field Assessment of Reflective Pavement Thermal Performance in Phoenix, Arizona” and provides fully reproducible workflows for evaluating the thermal performance of cool pavement treatments in a hot urban environment. The dataset integrates multi-modal field measurements collected across residential and nonresidential settings, including mobile air temperature traverses, stationary air temperature monitoring, residential mean radiant temperature (MRT) measurements, subsurface temperature profiles, and controlled testbed observations. The data package contains raw and processed datasets in comma-separated value (CSV) format, accompanying metadata files describing site characteristics and measurement protocols, and R scripts (.R files) used for data cleaning, time synchronization, spatial and temporal matching, quality control filtering, statistical comparison, and figure generation. All analyses were conducted using R (version ≥ 4.2.0) with commonly available packages (e.g., tidyverse, lubridate, data.table, ggplot2). No proprietary software is required to reproduce results. Field campaigns were designed to quantify the effects of high-reflectance pavement coatings on surface temperature, near-surface air temperature, subsurface heat propagation, and radiative heat exposure. Temporal alignment procedures include standardized timestamp conversion and nearest-neighbor matching of high-frequency sensor measurements to stop-based metadata within defined tolerance windows to ensure comparability across instruments. The workflows generate summary statistics, treatment–control contrasts, depth-dependent thermal gradients, and time-series visualizations used in the associated publication. By integrating mobile, stationary, radiative, and subsurface measurements within a unified and transparent processing framework, this package enables comprehensive evaluation of cool pavement performance across multiple thermal exposure pathways and supports reuse in future urban heat mitigation and climate resilience studies.

AIR TEMPERATURE↗
DOE OSTI2025

Cold Gas and Star Formation in the Phoenix Cluster with JWST

We present integral field unit observations of the Phoenix Cluster with the JWST Mid-infrared Instrument’s Medium Resolution Spectrometer. We focus this study on the molecular gas, dust, and star formation in the brightest cluster galaxy (BCG). We use precise spectral modeling to produce maps of the silicate dust, molecular gas, and polycyclic aromatic hydrocarbons (PAHs) in the inner ∼50 kpc of the cluster. We measure the optical depth from silicates by comparing the observed H 2 line ratios to those predicted by excitation models. We provide updated measurements of the total molecular gas mass of $1.9^{+0.5}_{-0.04}$ x 10 10 M ⊙ , which agrees with CO-based estimates, providing an estimate of the CO-to-H 2 conversion factor of α CO = 0.8 ± 0.2 M ⊙ pc -2 (K km s -1 ) -1 ; an updated stellar mass of M * = 2.6 ± 0.5 × 10 10 M ⊙ ; and star formation rates (SFRs) averaged over 10 and 100 Myr of $\langle$SFR$\rangle$ 10 = 1340 ± 100 M ⊙ yr −1 and $\langle$SFR$\rangle$ 100 = 740 ± 80 M ⊙ yr −1 , respectively. The H 2 emission seems to be powered predominantly by shocks and star formation within the central ∼20 kpc, induced by stellar feedback and radio jets from the active galactic nucleus. Additionally, we find nearly an order-of-magnitude drop in the SFRs estimated by PAH fluxes in cool core BCGs compared to field galaxies, suggesting that hot particles from the intracluster medium are destroying PAH grains even in the central-most tens of kiloparsecs.

Active galaxies↗
DOE OSTI2025

Investigating Building Energy Consumption and CO2 Emission in Phoenix Using AutoBEM and Future Typical Meteorological Year (fTMY) Weather Data

This research investigates the energy performance and CO2 emissions of each building stock across the Phoenix metropolitan area using the Automatic Building Energy Modeling (AutoBEM) framework and Model America v2 (MAv2) dataset from Oak Ridge National Laboratory (ORNL). Typical Meteorological Year (TMY) and Future Typical Meteorological Year (fTMY) files were used for AutoBEM simulation. The simulation results from TMY and fTMY were compared. It was found that a projected 10.28% increase in total CO2 emissions and a 9.30% rise in total energy consumption by 2080–2099 relative to current typical conditions. The results highlight the disparities in emissions among different building stocks and the influence of climate change on future energy demand. The findings underscore the necessity of targeted policy interventions and retrofitting strategies (eg. advanced HVAC systems, improved insulation, reflective roofing) to mitigate emissions in high-energy-use and emission-intensed buildings, particularly as climate conditions evolve. This study contributes to the growing understanding of building-sector emissions and their long-term implications under future climate scenarios.

Li, Hang [ORNL] (ORCID:0000000306001920)↗
DOE OSTI2026

Onboard/Origin-Destination Survey - Phoenix - 2007

In 2007, the Valley Metro Regional Public Transportation Authority, with consultant support, conducted an origin and destination survey of Valley Metro riders. The self-administered surveys were conducted among riders of fixed-route bus service: Local, Circulator, Limited, Rural, Express, and RAPID bus. Data collection was performed from October 8 through December 18, 2007. The objectives of the survey were to examine the demographics and travel behavior characteristics of Valley Metro riders. The survey data used for this analysis were appropriately weighted and expanded to represent the unlinked trips made by Valley Metro riders.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Understanding Multifamily Energy Use in the Phoenix Area: Building Stock Segmentation for Retrofit Planning

This report is an addendum to a publication series that focuses on approximately 100 different local geographies, or "clusters". This addendum expands the report series to include large multifamily building characteristics as well as energy and emission data for each local geography. The intention of this addendum is to help policymakers at the city, county, and state levels better understand building energy use and emissions in large multifamily buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Desert-Urban SysTem IntegratEd AtmospherIc Monsoon (DUSTIEAIM) in the Southwestern United States

Phoenix, Arizona, is the fifth-largest city in the United States with about 1.6 million residents. It is also considered to be the hottest major city in the country, having set a record of 31 consecutive days with temperatures above 110 F (43 C) in summer 2023. Phoenix depends on the Colorado River for over a third of its water supply, but there are questions about how much water will eventually be available to serve the rapidly growing metropolitan area, especially in such extreme heat. Current earth system models struggle to accurately capture precipitation in the Southwestern United States, especially in relation to the summertime North American Monsoon.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Data Center Waste Heat as an Emerging Urban Thermal Hazard: First Field Measurements of Neighborhood-Scale Air Temperature Impacts

Data centers are among the fastest-growing sources of concentrated anthropogenic heat in urban environments. Despite heat flux densities that exceed peak solar irradiance by a factor of 2–6, their thermal impacts on adjacent communities have never been directly measured or reported in the peer-reviewed literature. This short communication addresses that gap by presenting the first vehicle-based traverse measurements of air temperature in residential neighborhoods downwind of operational data centers. Five traverses at four facilities in the Phoenix, Arizona metropolitan area, ranging from a 36 MW single-building data center in Mesa to a 169 MW colocation campus in Chandler, reveal downwind air temperature warming as high as 2.2 °C, with average downwind air temperatures 0.7–0.9 °C warmer than corresponding upwind areas. Thermal signatures were detectable at distances up to 500 m from facility perimeters. The 36 MW Mesa facility rejects waste heat equivalent to the electricity consumption of approximately 40,000 households, while the 169 MW Chandler campus is equivalent to over 180,000 households, both concentrated into footprints smaller than a single residential subdivision. With U.S. data center capacity projected to more than double by 2030, these findings establish data center anthropogenic waste heat as a previously undocumented urban thermal hazard demanding attention from the data center and urban planning communities.

Phoenix↗
DOE OSTI2026

Assessing the Application of a Genomic Network Analysis in Population Ecology: Inferring Patterns of Dispersal and Geographic Structure in the Emerging Pathogen, Coccidioides

A challenge in population ecology studies is identifying how to best group individuals into populations, especially when individual origin is unknown. Machine learning has improved upon traditional methods of identifying population structure and is more efficient at handling large, complex datasets. We demonstrate the applicability of a machine learning method to identify hierarchical population structure in an emerging pathogen, Coccidioides spp., the causative agent of Valley fever. We compared the network clusters to structure identified by traditional tools as a validation of the network performance. We used publicly available whole-genome data for 48 C. immitis and 102 C. posadasii, resulting in 168,211 genome-wide SNPs among the two species. The network analysis grouped samples into populations comparable to the literature for these species but also identified fine-scale geographic structure and travel-associated cases not reported thus far. Exploring different resolutions in the network made it easy to identify unique genotypes specific to California and possibly Nevada, as well as Phoenix- and Tucson-acquired infections in non-endemic areas, regardless of reported travel history. The present study provides a promising example of how a ML-based network analysis can improve our ability to understand pathogen ecology, group cases into populations and infer travel-associated infections.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Updated sustainability status of cadmium telluride thin‐film photovoltaic systems and projections

This paper provides a comprehensive assessment of the up-to-date life-cycle sustainability status of cadmium-telluride based photovoltaic (PV) systems. Current production modules (Series 6 and Series 7) are analyzed in terms of their energy performance and environmental footprint and compared with the older series 4 module production and current single-crystalline Silicon (sc-Si) module production. For fixed-tilt systems with Series 6 modules operating under average US irradiation of 1800 kWh/m 2 /year, the global warming potential (GWP) is reduced from 16 g CO 2eq /kWh in Series 4 systems to 10 CO 2 eq /kWh in Series 6 systems. For operation in US-SW irradiation of 2300 kWh/m 2 /year, the GWP is reduced from 11 to 8 CO 2eq /kWh and for 1-axis tracking systems operating in Phoenix, Arizona, with point-of array irradiation of 3051 kWh/m 2 /year the GWP is reduced to 6.5 CO 2eq /kWh. Similar reductions have happened in all environmental indicators. Energy payback times (EPBT) of currently installed systems range from 0.6 years for fixed–tilt ground–mounted installations at average US irradiation at latitude tilt installations to 0.3 years for one-axis trackers at high US-SW irradiation, considering average fossil-fuel dominated electricity grids with fuel to electricity conversion efficiency of 0.3. The resulting energy return on energy investment (EROI) also depends on the conversion efficiency of the electricity grid and on the operation life expectance. For a 30-year operational life and grid conversion efficiency of 0.3, EROI ranges from 50 (at US average irradiation) to 70 for US-SW irradiation. The EROI declines with increased grid conversion efficiency; for CdTe PV operating in south California with grid conversion efficiency of 49%, the EROI is about 50 and is projected to fall to 30 when the state's 2030 target of 80% renewable energy penetration materializes. Material alternatives that show a potential of further reductions in degradation rates and materials for enhanced encapsulation that would enable longer operation lives have also been investigated. A degradation rate of 0.3%/year, which has been verified by accelerated testing, is assumed in 30-year scenarios; this is projected to be reduced to 0.2%/year in the near-term and potentially to 0.1%/year in the longer term. With such low degradation rates and enhanced edge-sealing, modules can last 40- to 50-years. Consequently, all impact indicators will be proportionally reduced while EROI will increase. This detailed LCA was conducted according to ISO standards and IEA PVPS Task 12 guidelines. Furthermore, the study revealed that the choices of system models, methods and temporal system boundaries can significantly impact the results and points out to the need to include assumptions regarding these choices in the “transparency in reporting” requirements listed in the IEA PVPS Task 12 Guidelines.

14 SOLAR ENERGY↗
DOE OSTI2025

Experimental characterization and potential energy savings of insulated cladding for U.S. residential buildings

This study evaluates a novel insulated cladding composed of foamed cement and vinyl siding that is designed as a retrofit product to enhance thermal performance in U.S. residential buildings. Experimental measurements showed that foamed cement exhibits a thermal conductivity of 0.0334–0.0365 W/m-K (R-value of 4.0–4.3 °F⋅ft 2 ⋅h/BTU), which is significantly higher than that of conventional fiber cement boards. Although mechanical testing confirmed the material’s brittleness and low strength, it also indicated its suitability for nonstructural insulation applications. Water vapor permeability testing demonstrated effective moisture resistance with the polymer coating. To evaluate the insulated cladding’s energy performance, we used the U.S. Department of Energy’s prototype single-family building model and simulated across 50 locations spanning 16 International Energy Conservation Code climate zones. The R-7 (R-value of 7 °F⋅ft 2 ⋅h/BTU per inch) retrofit cladding resulted in heating energy savings up to 275 therms (Fairbanks, AK) and cooling energy savings up to 1,547 kWh (Phoenix, AZ). The energy cost savings varied by region, but the highest annual cost savings ($\$$434/year) were observed in Santa Maria, CA, and the highest annual cost savings percentage (37 %) were noted in Monterey, CA. On a national scale, the insulated retrofit provided an average annual energy cost reduction of 16 %, highlighting the cladding system’s broad applicability and financial viability.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Citizen science coupled with machine learning to quantify green-blue infrastructure cooling potential in Maricopa County, Arizona

Here, this study investigates the spatiotemporal cooling performance of green and blue infrastructure (GBI) in the Dobson Ranch urban neighborhood in Phoenix, Arizona. We leveraged citizen science near-surface (2 m) air temperature (Tair) measurements to train a highly accurate Tair predicting LightGBM machine learning model (R 2 : 0.986, MAE: 0.251 °C, RMSE: 0.585 °C). On June 16, 2024, the park area exhibited approximately 1 °C cooling effect (relative to the neighborhood mean) during both day and night. In contrast, the nearby artificial lake exhibited a stronger cooling effect of 2.4 °C during the day but a slight warming of 0.3 °C at night. At 00:00, locations 50 m downwind of the park were 0.3 °C warmer than the park, while locations 50 m upwind were 0.8 °C warmer. At 11:00, we observed that the downwind area is 0.8 °C cooler and the upwind area is 0.6 °C warmer—at the same 50 m distances relative to the park. We also observed 1 °C cooler and warmer effects respectively at the same 50 m downwind and upwind locations at 19:00 on June 17, 2024. Our data-driven analysis highlights potential limitations of car-traverse measurements, showing that failure to account for temporal variations during the traverse can lead to overestimation of Tair at night and underestimation during the day. Our analysis also showed only a weak correlation (coefficient: 0.48) between Landsat-derived land surface temperature (LST) and model predicted Tair at the time of the local Landsat overpass (∼11.00). This highlights the potential error of relying solely on LST for human thermal exposure analysis—particularly within the heterogenous built-environment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

AutoBEM: A scalable framework for nationwide building energy simulation and retrofit evaluation in the United States

This paper presents AutoBEM, an integrated, automated framework for nationwide building energy modeling and retrofit evaluation in the United States. Unlike prior UBEM platforms that either rely primarily on representative stock sampling or operate at city scale, AutoBEM automates the generation of building-resolved, physics-based EnergyPlus/OpenStudio simulation models at national scale using GIS-derived geometry, prototype-based assumptions, and standardized scalable workflows. Leveraging the Model America dataset and high-performance computing, AutoBEM generates and simulates energy models for 122.9 million buildings, representing 97.8% of the U.S. building stock. These models are being made publicly and freely available as the Model America v1.0 (MAv1) dataset. AutoBEM supports detailed, building-level assessments of energy consumption, CO2 emissions, and post-processed anthropogenic heat emissions (AHE), and evaluates 151 energy conservation measures (ECMs) using localized utility pricing and building characteristics. In addition, AutoBEM incorporates both typical and future climate conditions through integration with Typical Meteorological Year (TMY) and Future TMY (fTMY) weather data derived from IPCC scenarios. In a case study of Phoenix, Arizona, AutoBEM identified several high-efficiency HVAC upgrades and selected envelope measures with short modeled payback periods (1.5 years) for certain building types and standards. Simulations under future climate scenarios (SSP5–RCP8.5) project an 11.3% increase in electricity use and a 32% reduction in natural gas demand by 2100, underscoring the need for climate-adaptive retrofit planning. By enabling reproducible, bottom-up, and location-specific analysis at scale, AutoBEM provides a step toward a national digital twin of the built environment and supports data-driven screening and planning for decarbonization, resilience, and energy equity.

Li, Hang [ORNL] (ORCID:0000000306001920)↗
DOE OSTI2025

Prioritizing urban heat adaptation infrastructure based on multiple outcomes: Comfort, health, and energy

Globally, cities face increasing extreme heat, impacting comfort, health, and energy consumption. Infrastructure-based heat adaptation strategies can improve these outcomes, but each strategy has a unique mix of benefits and drawbacks. Here, we apply an urbanized meteorological model (WRF) with the newly integrated multilayer BEP-Tree street tree model to dynamically downscale Earth System Model projections and a 3-D microclimate model (TUF-Pedestrian) to simulate the street-scale radiation environment impacting pedestrians. We evaluate the performance of five heat adaptation strategies (street trees, cool roofs, green roofs, rooftop photovoltaics (PV), and reflective pavements) during extreme heat events in three cities with contrasting background climates (Toronto, Phoenix, and Miami), under contemporary and end-of-century projected climates, based on three metrics: outdoor heat stress, air conditioning (AC) energy use, and ventilation of vehicular air pollution. No single adaptation strategy improves all three outcomes. While street trees inhibit ventilation, they reduce outdoor heat stress four times more effectively than the next best strategy via shade provision, fully offsetting heat stress increases under a high-emissions end-of-century climate scenario in all cities studied. Cool roofs and green roofs moderately reduce heat stress and energy use. Alternatively, rooftop PV with energy storage can generate sufficient power for space cooling but have marginal effects on heat stress. Reflective pavements are the least effective across metrics. Where the ventilation of street-level emissions is of less concern, our results clearly support the combination of street trees and rooftop PV as a highly complementary and effective means of adaptive mitigation across different climates and neighborhood densities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗