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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Inequality in the availability of residential air conditioning across 115 US metropolitan areas

Continued climate change is increasing the frequency, severity, and duration of populations’ high temperature exposures. Indoor cooling is a key adaptation, especially in urban areas, where heat extremes are intensified—the urban heat island effect (UHI)—making residential air conditioning (AC) availability critical to protecting human health. In the United States, the differences in residential AC prevalence from one metropolitan area to another is well understood, but its intra-urban variation is poorly characterized, obscuring neighborhood-scale variability in populations’ heat vulnerability and adaptive capacity. We address this gap by constructing empirically derived probabilities of residential AC for 45,995 census tracts across 115 metropolitan areas. Within cities, AC is unequally distributed, with census tracts in the urban “core” exhibiting systematically lower prevalence than their suburban counterparts. Moreover, this disparity correlates strongly with multiple indicators of social vulnerability and summer daytime surface UHI intensity, highlighting the challenges that vulnerable urban populations face in adapting to climate-change driven heat stress amplification.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Thermal, water, and land cover factors led to contrasting urban and rural vegetation resilience to extreme hot months

Abstract With continuing global warming and urbanization, it is increasingly important to understand the resilience of urban vegetation to extreme high temperatures, but few studies have examined urban vegetation at large scale or both concurrent and delayed responses. In this study, we performed an urban–rural comparison using the Enhanced Vegetation Index and months that exceed the historical 90th percentile in mean temperature (referred to as “hot months”) across 85 major cities in the contiguous United States. We found that hot months initially enhanced vegetation greenness but could cause a decline afterwards, especially for persistent (≥4 months) and intense (≥+2 °C) episodes in summer. The urban responses were more positive than rural in the western United States or in winter, but more negative during spring–autumn in the eastern United States. The east–west difference can be attributed to the higher optimal growth temperatures and lower water stress levels of the western urban vegetation than the rural. The urban responses also had smaller magnitudes than the rural responses, especially in deciduous forest biomes, and least in evergreen forest biomes. Within each biome, analysis at 1 km pixel level showed that impervious fraction and vegetation cover, local urban heat island intensity, and water stress were the key drivers of urban–rural differences. These findings advance our understanding of how prolonged exposure to warm extremes, particularly within urban environments, affects vegetation greenness and vitality. Urban planners and ecosystem managers should prioritize the long and intense events and the key drivers in fostering urban vegetation resilience to heat waves.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Global scale assessment of urban precipitation anomalies

Urbanization has accelerated dramatically across the world over the past decades. Urban influence on surface temperatures is now being considered as a correction term in climatological datasets. Although prior research has investigated urban influences on precipitation for specific cities or selected thunderstorm cases, a comprehensive examination of urban precipitation anomalies on a global scale remains limited. This research is a global analysis of urban precipitation anomalies for over one thousand cities worldwide. We find that more than 60% of the global cities and their downwind regions are receiving more precipitation than the surrounding rural areas. Moreover, the magnitude of these urban wet islands has nearly doubled in the past 20 y. Urban precipitation anomalies exhibit variations across different continents and climates, with cities in Africa, for example, exhibiting the largest urban annual and extreme precipitation anomalies. Cities are more prone to substantial urban precipitation anomalies under warm and humid climates compared to cold and dry climates. Cities with larger populations, pronounced urban heat island effects, and higher aerosol loads also show noticeable precipitation enhancements. This research maps global urban rainfall hotspots, establishing a foundation for the consideration of urban rainfall corrections in climatology datasets. This advancement holds promise for projecting extreme precipitation and fostering the development of more resilient cities in the future.

Science & Technology - Other Topics↗
DOE OSTI2023

How can we combine urban cooling strategies to effectively cool cities over the entire diurnal cycle?

The urban heat island effect generally peaks in the night/evening hours and, in some cases, an urban cool island effect during daytime has been reported. These patterns are observed mainly because of the widespread use of impervious and thermally massive materials (like concrete and asphalt) in the built environment and their ability to store energy during the daytime and release it at night. Unfortunately, most urban cooling strategies, such as cool (white), green, and blue spaces, provide better thermal performance during the daytime than at night. Hence, such solutions are not ideal for nighttime heat mitigation. In this study, we investigate the effect of the thermal storage capacity of existing buildings on nighttime urban air temperature for a hot arid city—Phoenix, and a hot humid city—Atlanta. The study uses regional scale atmospheric modeling to compare the nighttime urban cooling capability of thermally light buildings (Cross-laminated timber buildings in this case) with concrete buildings. The results show that the adoption of thermally light buildings reduce nighttime air temperatures, and slightly increases daytime air temperatures. On the other hand, cool roof adaption could reduce urban air temperature significantly during the daytime and slightly at night. Therefore, together with cool roofs, thermally light buildings may be able to cool the surrounding air by an average of about 1°C throughout the diurnal cycle, providing thermal comfort and reducing cooling demand during all hours.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Urban Forests as Main Regulator of the Evaporative Cooling Effect in Cities

Abstract Higher temperatures in urban areas expose a large fraction of the human population to potentially dangerous heat stress. Green spaces are promoted worldwide as local and city‐scale cooling strategies but the amount, type, and functioning of vegetation in cities lack quantification and their interaction with urban climate in different settings remains a matter of debate. Here we use state‐of‐the‐art remote sensing data from 145 city clusters to disentangle the drivers of surface urban heat islands (SUHI) intensity and quantify urban‐rural differences in vegetation cover, species composition, and evaporative cooling. We show that nighttime SUHIs are affected mostly by abiotic factors, while daytime SUHIs are highly correlated with vegetation characteristics and the wetness of the background climate. Magnitude and seasonality of daytime SUHIs are controlled by urban‐rural differences in plant transpiration and leaf area, which explain the dependence of SUHIs on wetness conditions. Leaf area differences are caused primarily by changes in vegetation type and a loss of in‐city forested areas, highlighting the importance of maintaining “natural reserves” as a sustainable heat mitigation policy.

Paschalis, Athanasios↗
DOE OSTI2021

Urban microclimate and its impact on building performance: A case study of San Francisco

Urban microclimate exerts an increasing influence on urban buildings, energy, and sustainability. This study uses 10-year measured hourly weather data at 27 sites in San Francisco, California, to (1) analyze and visualize the urban microclimate patterns and urban heat island effect; (2) simulate annual energy use and peak electricity demand of typical large office buildings and large hotels to investigate the influence of urban microclimate on building performance; (3) simulate indoor air temperature of a single-family house without air-conditioning during the record three-day heatwave of 2017, to quantify the divergence of climate resilience due to urban microclimate effect. Results show significant microclimate effects in San Francisco with up to 11 °C outdoor air temperature difference between the coastal and downtown areas on September 1, 2017, during the record three-day heatwave. The simulated energy results of the prototype large office and large hotel buildings using the 2017 weather data show over 100% difference in annual heating energy use and 65% difference in annual cooling energy use across different stations; as well as up to 30% difference in peak cooling electricity demand. The impacts on annual site or source energy use are minimal (less than 5%) as cooling and heating in a mild climate are a relatively small portion of overall building energy use in San Francisco. Results also show the microclimate effects influence indoor air temperature of unconditioned homes by up to 5 °C. Newer buildings and homes are much less affected by microclimate effects due to more stringent performance requirements of the building envelope and energy systems. Furthermore, these findings inform that San Francisco microclimate variations should be considered in urban energy planning, building energy codes and standards, as well as heat resilience policymaking.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

High‐Performance Low‐Emissivity Paints Enabled by N‐Doped Poly(benzodifurandione) (n‐PBDF) for Energy‐Efficient Buildings

Abstract Low‐emissivity (low‐e) paints reduce radiative heat exchange between buildings and the environment, stabilizing indoor climates and lowering air conditioning demand. However, low‐cost, durable, and colored low‐e paints have yet to be demonstrated. Here, an approach is proposed using n‐doped poly(benzodifurandione) (n‐PBDF), a transparent organic conducting polymer, coated over colored commercial paints. This achieves a low thermal emissivity of 0.19 in the mid‐infrared spectrum, attributed to the efficient charge transport of delocalized π‐electrons in n‐PBDF structure. The reduction in thermal emissivity aids in regulating building temperatures by minimizing heat transfer between buildings and their surroundings across diverse climate zones and seasons. The n‐PBDF coating preserves the underlying paint's color due to its high visible transparency, meeting aesthetic requirements. It also shows strong stability in accelerated indoor weathering tests, ensuring long‐term performance. Simulations estimate annual HVAC energy savings of over 10,800 kWh in San Francisco and 5,500 kWh in Chicago for the typical mid‐rise apartments. The paint's versatility, scalability, and durability make it suitable for buildings, vehicles, and greenhouses, aiding urban heat island mitigation.

Liu, Xiaojie [School of Mechanical Engineering and↗
DOE OSTI2023

A convection-permitting dynamically downscaled dataset over the Midwestern United States

Climate change is expected to have far-reaching effects at both the global and regional scale, but local effects are difficult to determine from coarse-resolution climate studies. Dynamical downscaling can provide insight into future climate projections on local scales. Here, we present a new dynamically downscaled dataset for Indiana and the surrounding regions. Output from the Community Earth System Model (CESM) version 1 is downscaled using the Weather Research and Forecasting model (WRF). Simulations are run with a 24-hr reinitialization strategy and a 12-hr spin-up window. WRF output is bias corrected to the National Centers for Environmental Protection/National Center for Atmospheric Research 40-year Reanalysis project (NCEP) using a modified quantile mapping method. Bias-corrected 2-m air temperature and accumulated precipitation are the initial focus, with additional variables planned for future releases. Regional climate change signals agree well with larger global studies, and local fine-scaled features are visible in the resulting dataset, such as urban heat islands, frontal passages, and orographic temperature gradients. This high-resolution climate dataset could be used for down-stream applications focused on impacts across the domain, such as urban planning, energy usage, water resources, agriculture and public health.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Self-cleaning and de-pollution efficacies of photocatalytic architectural membranes

Photocatalytic self-cleaning “cool” roofs and walls can maintain high albedos, saving building cooling energy, reducing peak power demand, and mitigating the urban heat island effect. Other environmental benefits result from their de-polluting properties. Specimens from two different photocatalytic architectural membranes and a non-photocatalytic control were exposed alongside vertically, facing west, for two years at three California sites, and retrieved quarterly for testing. Photocatalytic materials showed excellent self-cleaning performance, retaining albedos of 0.74 – 0.75. By contrast, the control material exhibited an albedo loss of up to 0.10, with appreciable soiling observed by scanning electron microscopy. De-pollution capacity was assessed by quantifying NO removal and NOx deposition rates at 60 °C. Furthermore, efficacy varied with exposure location, weather conditions, and the nature of the photocatalytic material. Seasonal effects were observed, with partial inhibition during the dry season and reactivation during the rainy season.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
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↗
DOE OSTI2025

Refining seasonal performance metrics for room air-conditioning in emerging markets: Integrating building simulations with real-world equipment performance data

Buildings significantly impact worldwide energy consumption, emphasizing the need to reduce the cooling energy demand, especially in warm climates. Minimum energy performance standards (MEPS) and seasonal performance metrics such as the Cooling Seasonal Performance Factor (CSPF) are crucial for improving room air conditioning (RAC) efficiency. However, challenges remain, particularly in emerging markets like Brazil, where seasonal performance metrics have recently been introduced. This study assesses the factors influencing country-level seasonal efficiency metrics and proposes a framework to refine these calculations by considering local climates and expected RAC usage in real-world households via building simulations. Key considerations include outdoor air temperature binning for different climates, RAC usage patterns (i.e., daytime and nighttime usages), envelope thermal performance of households, and urban heat island (UHI) effects. The results reveal that CSPF values can vary significantly based on climate conditions, with observed CSPF ranging from 4.10 to 11.59 Wh/Wh across 577 Brazilian climates. The inclusion of UHI effects led to a reduction in CSPF values by up to 29% during nighttime operations in hot urban areas. Additionally, building envelope efficiency showed contrasting impacts on RAC performance, with CSPFs reaching up to 15.35 Wh/Wh under specific optimized conditions. These findings highlight the need for transparent policymaking in RAC performance databases, facilitating the application of approaches like those proposed in this study and supporting diverse stakeholders in decision-making.

Bavaresco, Mateus↗
DOE OSTI2021

Urbanization Amplifies Nighttime Heat Stress on Warmer Days Over the US

Abstract The impact of heat on human health is well‐recognized, with excess heat stress in urban areas (urban heat stress intensity, UHSI) adversely affecting rapidly growing urban populations. However, the physical associations of UHSI with urban heat island (UHI), urban‐induced change in moisture (UQI) and background temperature are not well understood. Multi‐year convection‐permitting simulations over the US show that UHI effect peaks during nighttime (2–5°C) but maximum UQI occurs in daytime (0.01–2 g kg −1 ), resulting in competing effects on UHSI. UHI dynamics dominate the diurnal variations in UHSI with intensified urban‐induced human discomfort during nighttime (3–5 hr day − 1 ). UHSI is very sensitive to the background temperature, especially over the southeastern US, with distinct nightime UHSI amplification of ∼0.5 hr day −1 degree − 1 rise in the background temperature. Spatial variability of UHSI is also dominated by the UHI with possible constrains from background moisture availability.

Sarangi, Chandan↗
DOE OSTI2024

Contrasting Effects of Urban Land Cover Change and Anthropogenic Heat on Summer Precipitation Over the Yangtze River Delta of China: Analyses From an Atmospheric Moisture Budget Perspective

Both urban land cover (ULC) change and anthropogenic heat (AH) emission are important causes of urban heat island, but their relative contributions to the changes in urban precipitation and the related mechanism remain unclear. Based on numerical simulations utilizing the latest realistic urban fraction and AH data over the Yangtze River Delta urban agglomeration, we found that ULC and AH resulted in nearly opposite effects on precipitation. Various dynamical and thermodynamic processes were involved according to the atmospheric moisture budget analyses. AH increased precipitation particularly during afternoon, and the increases were stronger during heavy precipitation events because of the enhanced moisture convergence effect together with the release of moisture storage previously accumulated in the atmosphere. Differently, ULC reduced mean precipitation mainly due to suppressed evaporation. During weak precipitation events, the suppressed evaporation was largely balanced by the intensified moisture convergence, but during heavy events, ULC caused more pronounced precipitation reduction because the moisture convergence response disappeared and failed to offset the evaporation effect. Here, the relative contributions of different dynamical and thermodynamic processes such as those related to circulation, moisture gradient, and background moisture availability to the temporal variation in the total moisture convergence were further quantified. Overall, our results help better understand the relative roles of different aspects of urbanization on precipitation, and suggest that compared to ULC, reduction in AH emission that is tightly related to the energy consumption structure could be more efficient for mitigating the risk of extreme precipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

More Heavy Precipitation in World Urban Regions Captured Through a Two‐Way Subgrid Land‐Atmosphere Coupling Framework in the NCAR CESM2

Abstract Current global climate models (GCMs), limited to grid‐scale land‐atmosphere coupling, cannot represent subgrid urban‐rural precipitation contrasts. This study develops an innovative two‐way subgrid land‐atmosphere coupling framework in the National Center for Atmospheric Research (NCAR) Community Earth System Model version 2 (CESM2) to explicitly resolve land‐atmosphere interaction over subgrid individual land units. Results show that urban heat island (UHI) leads to the urban rainfall effect (URE), which in turn alleviates overestimated UHI over China in CESM2. The URE manifests as a shift toward more heavy precipitation and less light precipitation in world urban areas than in surrounding rural counterparts. This feature is consistent with available observations. In heavy precipitation situations, the UHI promotes atmospheric instability and enhances atmospheric water vapor holding capacity, resulting in more heavy precipitation in urban areas. Conversely, in light precipitation situations, the UHI and decreased evaporation from urban impermeable surfaces diminish atmospheric relative humidity, suppressing light precipitation.

Geology↗
DOE OSTI2023

Challenges resulting from urban density and climate change for the EU energy transition

Dense urban morphologies further amplify extreme climate events due to the urban heat island phenomenon, rendering cities more vulnerable to extreme climate events. Here we develop a modelling framework using multi-scale climate and energy system models to assess the compound impact of future climate variations and urban densification on renewable energy integration for 18 European cities. We observe a marked change in wind speed and temperature due to the aforementioned compound impact, resulting in a notable increase in both peak and annual energy demand. Therefore, an additional cost of 20–60% will be needed during the energy transition (without technology innovation in building) to guarantee climate resilience. Failure to consider extreme climate events will lower power supply reliability by up to 30%. Here, energy infrastructure in dense urban areas of southern Europe is more vulnerable to the compound impact, necessitating flexibility improvements at the design phase when improving renewable penetration levels.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

The High-resolution Urban Meteorology for Impacts Dataset (HUMID) daily for the Conterminous United States

Many current gridded surface meteorological datasets are inadequate for quantifying near surface spatiotemporal variability because they do not fully represent the impacts of land surface heterogeneity. Of note, explicit representation of the spatial structure and magnitude of local urban warming are usually lacking. Here we enhance the representation of spatial meteorological variability over urban areas in the conterminous United States (CONUS) by employing the High-Resolution Land Data Assimilation System (HRLDAS), which accounts for the fine-scale impacts of spatiotemporally varying land surfaces on weather. We also synthesize in situ meteorological data including local mesonets to create a 1 km grid spacing model-observation fusion product spanning 1981-2018 over the CONUS. Daily maximum, minimum, and mean values for a variety of temperature estimates, humidity, and surface energy budget terms, among others, are included. This High-resolution Urban Meteorology for Impacts Dataset (HUMID) will be useful for studies examining spatial variability of near surface meteorology and the impacts of urban heat islands across many disciplines including epidemiology, ecology, and climatology.

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 OSTI2024

Empirically Categorizing the Built Environment in Relation to Height

Buildings are a core component of the urban environment and affect human populations, energy usage, city development, city planning, and urban heat islands. Buildings span an enormous range of sizes, from a 2m tall shelter to the Burj Khalifa; and at the same time there are widely recognized categories of similar buildings, with homes, office buildings, or skyscrapers as some examples. Currently, there is no consistent method to quantitatively determine how a building should be categorized by its height, or how many categories there should be within the built environment. Additionally, these categories vary spatially, leading to multiple definitions at local scales of what it means to be a tall, medium, or short building. Here, we find across 17.59 million buildings in the United States, Germany, and Japan, that applying a K-nearest neighbor approach to quantitatively bin the built environment outperforms the current state-of-the-art, subjective domain knowledge. This was evidenced as our method of leveraging a K-nearest neighbor improved upon the existing approach of using domain knowledge by 10% with respect to precision, recall, F1-score and accuracy. Our results showcase the finding that it is possible to generate a global and consistent approach to categorizing the built environment in relation to height. This is significant in that there is now a quantitative way to categorize the built environment based on building height at a global scale, allowing researchers a consistent platform for comparison and collaboration across various applications.

Stipek, Clinton↗