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DOE OSTI2022

Dataset for 'Ombadi, M. & Varadharajan, C. (2022). Urbanization and aridity mediate distinct salinity response to floods in rivers and streams across the Contiguous United States, Water Research'

This package contains data sets and code used to obtain the results in Ombadi, M., & Varadharajan, C. (2022). Urbanization and aridity mediate distinct salinity response to floods in rivers and streams across the Contiguous United States. Water Research, 118664. The folder "data" contains 259 .csv files, each of which has daily time series of concurrent streamflow (Q) and specific conductance (SC) for each of the sites used in this study originally downloaded from the USGS National Water Information System (NWIS; USGS, 2016). The number of data points in each of the files is at least 3650 (i.e. 10 years of daily measurements). The folder "RF_single_data" contains 259 .csv files, each of which include data used to train and test the Random Forest models at individual sites for predicting SC during days of floods. The folder "RF_regional_data" contains 3 .csv files, each of which include scaled data compiled from all sites within each climate zone (arid, temperate and wet). "metadata.csv" contains the physical properties of the 259 catchments corresponding to the sites used in this study; this data was extracted from GAGES-II dataset (Falcone et al., 2010). "RF_implementation.ipynb" is a Jupyter notebook with the code needed to implement the analysis using Random Forest models either for individual sites or for the regional models (for each climate zone). The code utilizes the data in the two folders: "RF_single_data" and "RF_regional_data" and the metadata.csv file.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2023

An Analysis of Degradation in Low-Cost Particulate Matter Sensors

Low-cost sensors (LCSs) are increasingly being used to measure fine particulate matter (PM 2.5 ) concentrations in cities around the world. One of the most commonly deployed LCSs is PurpleAir with ∼15 000 sensors deployed in the United States, alone. PurpleAir measurements are widely used by the public to evaluate PM 2.5 levels in their neighborhoods. PurpleAir measurements are also increasingly being integrated into models by researchers to develop large-scale estimates of PM 2.5 . However, the change in sensor performance over time has not been well studied. It is important to understand the lifespan of these sensors to determine when they should be serviced or replaced, and when measurements from these devices should or should not be used for various applications. This paper fills this gap by leveraging the fact that: (1) each PurpleAir sensor is composed of two identical sensors and the divergence between their measurements can be observed, and (2) there are numerous PurpleAir sensors within 50 meters of regulatory monitors allowing for the comparison of measurements between these instruments. We propose empirically-derived degradation outcomes for the PurpleAir sensors and evaluate how these outcomes change over time. On average, we find that the number of ‘flagged’ measurements, where the two sensors within each PurpleAir sensor disagree, increases with time to ∼4% after 4 years of operation. Approximately, 2 percent of all PurpleAir sensors were permanently degraded. The largest fraction of permanently degraded PurpleAir sensors appeared to be in the hot and humid climate zone, suggesting that sensors in these locations may need to be replaced more frequently. We also find that the bias of PurpleAir sensors, or the difference between corrected PM2.5 levels and the corresponding reference measurements, changed over time by −0.12 μg m −3 (95% CI: −0.13 μg m −3 , −0.10 μg m −3 ) per year. The average bias increases dramatically after 3.5 years. Further, climate zone is a significant modifier of the association between degradation outcomes and time.

Priyanka deSouza↗

DOE OSTI2025

Daytime urban heat stress in North America reduced by irrigation

There is considerable uncertainty regarding the impact of irrigation on heat stress, partly stemming from the choice of heat stress index. Moreover, existing simulations are at scales that cannot appropriately resolve population centres or clouds and thus the potential for human impacts. Using multi-year convection-permitting and urban-resolving regional climate simulations, we demonstrate that irrigation alleviates summertime heat stress across more than 1,600 urban clusters in North America. This holds true for most physiologically relevant heat stress indices. The impact of irrigation varies by climate zone, with more notable irrigation signals seen for arid urban clusters that are situated near heavily irrigated fields. Through a component attribution framework, we show that irrigation-induced changes in wet-bulb temperature, often used as a moist heat stress proxy in the geosciences, exhibit an opposite sign to the corresponding changes in wet bulb globe temperature—a more complete index for assessing both indoor and outdoor heat risk—across climate zones. In contrast, the local changes in both wet-bulb and wet bulb globe temperature due to urbanization have the same sign. Here, our results demonstrate a complex relationship between irrigation and heat stress, highlighting the importance of using appropriate heat stress indices when assessing the potential for population-scale human impacts.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Developing a Control Strategy for Minimum Airflow Setting Considering CO2 Level and Energy Consumption in a Variable Air Volume System

In an office building equipped with a Variable Air Volume (VAV) system, this paper introduces a novel method for controlling the minimum supply airflow fraction in each zone’s VAV box, having a capability to consider indoor CO2 level and energy consumption. The EnergyPlus simulation using the medium office prototype model was employed, which evaluated the performance of the energy and CO2 concentration for five VAV box airflow control strategies. The paper focuses on CO2 concentration-based airflow control method and compares it with other four methods including conventional single-max, reduced minimum single-max, demand-controlled ventilation(DCV), and dualmax control methods according to guidelines and common practices. The newly proposed control strategy directly correlates the minimum airflow fraction to CO2 concentration. A general trend emerged when comparing CO2 concentrations—lower minimum airflow fractions were associated with higher concentrations. The proposed control method effectively maintained low CO2 concentrations and enabled a lower airflow fraction contributing to energy consumption reduction. It was confirmed that heating energy consumption in climate zone 4A, 5B, and 6A showed a maximum saving of approximately 30% compared to the conventional single-max and dual max control strategies. It was found that cooling energy consumption in climate zone 4A and 6A can achieve a maximum saving of approximately 10% compared to the conventional control strategies. The proposed CO2 concentration-based control logic is promising as it not only improves the indoor air quality lowering the CO2 concentration in the occupied spaces, but also contributes to HVAC energy savings.

Lee, Jong Man↗

DOE OSTI2026

Hygrothermal Performance of Bio-Based Materials in Residential Building Wall Envelope Systems

In the United States, building envelope systems contribute approximately 28% of building energy consumption, with walls being a primary factor. As the construction industry explores new approaches to lower the energy intensity needed to manufacture materials and, in turn, reduce energy consumption, bio-based materials are gaining attention as a promising alternative. While prior studies have demonstrated that bio-based materials can decrease material energy intensity, their long-term hygrothermal behavior within a whole residential wall system is not yet fully understood. This study aims to evaluate the potential of replacing Oriented Strand Board (OSB) and drywall in residential wall systems with bio-based alternatives. The research focuses on two bio-based materials, assessing their hygrothermal performance under Chicago climate condition (Climate Zone 5). To achieve that, a series of laboratory experiments were conducted to measure key properties of the bio-based materials such as thickness, dimensions, density, thermal conductivity (as a function of temperature and humidity), moisture-dependent permeance and water vapor permeability (WVP), and sorption isotherms. These properties were then used in WUFI® simulations to predict the moisture durability of a standard residential wall system in Climate Zone 5. Results show that substituting OSB and drywall with bio-based materials can achieve acceptable moisture durability, effectively mitigating risks of mold growth and structural damage over time.

Palani, Hevar [ORNL] (ORCID:0000000220211994)↗

DOE OSTI2021

Italian prototype building models for urban scale building performance simulation

Urban building energy modeling (UBEM) seeks to evaluate strategies to optimize building energy use at urban scale to support a city's building energy goals. Prototype building models are usually developed to represent typical urban building characteristics of a specific use type, construction year, and climate zone, as detailed characteristics of individual buildings at urban scale are difficult to obtain. This study investigated the Italian building stock, developing 46 building prototypes, based on construction year, for residential and office buildings. The study included 16 single-family buildings, 16 multi-family buildings, and 14 office buildings. Building envelope properties and heating, ventilation, and air conditioning system characteristics were defined according to existing building energy codes and standards for climatic zone E, which covers about half the Italian municipalities. Novel contributions of this study include (1) detailed specifications of prototype building energy models for Italian residential and office buildings that can be adopted by UBEM tools, and (2) a dataset in GeoJSON format of Italian urban buildings compiled from diverse data sources and national standards. Finally, the developed prototype building specifications, the building dataset, and the workflow can be applied to create other building prototypes and to support Italian national building energy efficiency and environmental goals.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Life-cycle cost-benefit analysis of a novel self-heating pavement made from coal-derived solid carbon

Winter weather events challenge the safety, efficiency, and sustainability of roadway networks, particularly road bridges vulnerable to climate impacts. Although effective, conventional de-icing methods incur high expenses and cause significant environmental contamination. To address these longstanding issues, a low-cost novel coal-derived carbon enabled smart pavement (CDC-SP) de-icing system was developed, aiming to alleviate traffic delays, severe corrosion, compromised safety, and environmental pollution. However, the economic performance of CDC-SP has not been quantified to guide decision-making. To this end, this paper presents a Life-Cycle Cost-Benefit Analysis (LCCBA) to assess the economic feasibility of the CDC-SP de-icing system for road bridges in five representative urban and rural areas across cool humid and cold humid climate zones. Given the variations and uncertainties of several factors that determine the costs and benefits, a sensitivity analysis was conducted to determine the system’s economic reliability. Additionally, a Monte Carlo simulation (MCS) was performed to quantify the impacts of important factors and identify the most beneficial scenarios. Furthermore, the CDC-SP de-icing systems have demonstrated substantial economic benefits and short payback periods, showing great applicability for rural and urban road bridges with different service levels across multiple climate zones as compared to conventional de-icing methods.

36 MATERIALS SCIENCE↗

NASA NTRS2022

Influence of Vegetation on Simulation of the Water Balance and Hydrological Response to El Niño–Southern Oscillation in Western Tropical South America

Land surface models (LSMs) rely on vegetation parameters for use in hydrological and energy balance analysis, monitoring, and forecasting. This study examines the influence that vegetation representation in the Noah-Multiparameterization (Noah-MP) LSM has on hydrological simulations across the diverse climate zones of western tropical South America (WTSA), with specific consideration of hydrological variability associated with El Niño–Southern Oscillation (ENSO). The influence of model representation of vegetation on simulated hydrology is evaluated through three simulation experiments that use 1) satellite-derived constant MODIS; 2) satellite-derived time-varying MODIS; and 3) the Noah-MP dynamic leaf model. We find substantial differences in vegetation fields between these simulations, with the Noah-MP dynamic leaf model diverging significantly from satellite-derived vegetation fields in many ecoregions. Impacts on simulated hydrology were, however, found to be modest across climate zones, except for select extreme events. Also, although impacts on hydrology under ENSO-induced variability were small, we find that the Noah-MP dynamic leaf model simulates a positive relationship between rainfall and vegetation in humid ecoregions of WTSA, where satellite observations may indicate the opposite. The relatively small sensitivity of simulated hydrology to vegetation scheme suggests that the performance of hydrological monitoring and forecasting in WTSA that uses Noah-MP is largely unaffected by the choice of vegetation scheme, such that using a simple climatological default is generally no worse than adopting more complicated options. The presence of some differences between the time-varying and constant MODIS simulations for hydrologic extremes, however, indicates that time-varying MODIS configuration might be more suitable for hydrological hazards applications.

South America↗

DOE OSTI2020

An Assessment of Impacts on Electric End-Use Load Profile of a Typical Residential Building from a Ground Source Heat Pump Systems Integrated with Underground Thermal Energy Storage

Buildings are the primary users of electricity, and a considerable amount of electric energy consumed in residential and commercial buildings is for meeting thermal demands (e.g., space heating/cooling, water heating, etc.). Therefore, integrating thermal energy storage with a building’s energy system has the potential to reshape the electric load profile of the building and mitigate the mismatch between the renewable power supply and the thermal demands of buildings. A novel ground-source heat pump system (GSHP) integrated with underground thermal energy storage (UTES) has been developed to enable flexible electric demand at buildings while meeting their thermal demands with an energy-efficient GSHP system. This paper assessed the potential impacts of the proposed system on the peak electrical demand and annual electricity consumption in a typical residential building at various climate zones in the United States. The results show that by replacing the conventional HVAC system (air conditioner and natural gas furnace) with the UTES integrated GSHP system, summer peak electric demand can be reduced by 27% to 50% depending on the weather. Although the winter peak electrical demand could be increased by up to 70% if the proposed system replaces natural gas furnace, the existing electricity supply system for single-family homes in most regions of the United States have adequate capacity for the replacement. While eliminating the natural gas consumption for space heating, the proposed system consumes more electricity on an annual basis in heating-dominated regions. However, it consumes less electricity in cooling dominated regions. The resulting variance in annual electricity consumption in various climate zones is within 15% compared with the baseline system.

Shi, Liang↗

DOE OSTI2023

Geospatial Characterization of Low-Temperature Heating and Cooling Demand in the United States: Preprint

Geothermal resources at temperatures below 150 degrees C have great potential as energy sources for various direct-use applications including heating and cooling in residential and commercial buildings. This study geospatially quantifies U.S. heating and cooling demand in residential, commercial, and manufacturing sectors; heating demand in the agricultural sector; and cooling demand in data centers at the county level through end-use energy consumption, expenditure, and commissioned power analyses. Heating and cooling demand in the residential sector was estimated using energy consumption data obtained from the U.S. Energy Information Administration accounting for different U.S. climate zones. For commercial sector analysis, the end-use major fuel energy intensity at the census division level was disaggregated to the county level with respect to principal building activities. Heating and cooling demand analysis for the manufacturing sector was based on end-use energy consumption for direct-use total process categorized by the North America Industry Classification System. Fuel expenditures in the U.S. Department of Agriculture Farm Production Expenditures were examined for heating demand analysis in the agricultural sector, particularly for the greenhouse, nursery, and floriculture production category. Lastly, commissioned power for data centers in the United States were explored for cooling demand analysis. Results indicated a significant fraction of U.S. primary energy consumption is used for low-temperature heating and cooling applications. Heating and cooling demand in residential and commercial sectors is significantly affected by the number of housing units and climate zone designations, while heating and cooling demand in manufacturing and agricultural sectors and data centers are mainly dependent on the number of facilities and their locations. Maps were generated visualizing where heating and cooling demand is high and, overlain with geothermal resource maps, can indicate locations where geothermal energy can supply this heating and cooling demand.

cooling demand↗

DOE OSTI2023

Geospatial Characterization of Low-Temperature Heating and Cooling Demand in the United States

cooling demand↗

DOE OSTI2024

Geospatial characterization of low-temperature heating and cooling demand in residential, commercial, manufacturing, agricultural, and data center sectors for potential geothermal applications in the United States

Thermal demand for heating and cooling has been predominantly supplied by fossil fuel combustion in the United States, although low-carbon alternatives are extensively available including geothermal, solar thermal, and waste heat. Here, this study analyzed end-use energy consumption, fuel expenditure, and data center commissioned power data to geospatially characterize the U.S. low-temperature heating and cooling demand at the county level in residential, commercial, manufacturing, agricultural, and data center sectors and understand potential opportunities for geothermal applications. In the analysis, the regional-scale energy consumption data was incorporated with system efficiencies to address actual demand and was then disaggregated with weighting factors to the county level. The results indicated that total low-temperature heating and cooling demand is 16.7 EJ, combining heating demand of 10.8 EJ and cooling demand of 5.9 EJ. Overall, 59.9 % (10 EJ) of the low-temperature heating and cooling demand occurred in the residential sector. The heating and cooling demand visualized in maps represented that the geospatial distribution of heating and cooling demand in the residential and commercial sectors is governed by the number of housing units and climate zone designations, while heating and cooling demand in the manufacturing, agricultural, and data center sectors is dependent on the number and location of facilities. The results also demonstrated that geothermal heat pumps are broadly used in the residential and commercial sectors for heating and cooling in the U.S. Midwest, South, and Northeast regions but are limited in the West, implying great decarbonization potential in the future.

15 GEOTHERMAL ENERGY↗

DOE OSTI2021

Poleward shift and intensified variability of Kuroshio-Oyashio extension and North Pacific Transition Zone under climate change

Not provided.

Meteorology & Atmospheric Sciences↗

DOE OSTI2020

Smart Ventilation for Advanced California Homes

This project investigated smart ventilation approaches to minimize energy use for providing indoor air quality (IAQ) in high performance new California homes. Evaluation criteria included annual ventilation-related energy, peak energy and time-of-use savings, and the indoor air quality relative to a minimally code-compliant ventilation system. The simulations used CONTAM’s air flow and contaminant transport model, combined with the EnergyPlus building loads model. House types representing the default California Energy Code compliance homes were investigated for four California climate zones, covering a wide range of climate types. Both single and multi-zone smart ventilation controls were investigated. Contaminant sources included contaminants emitted continuously and varying with time, temperature and relative humidity, episodic emissions from occupant activities and outdoor particles. Single-zone ventilation controls that varied ventilation depending on outdoor temperatures were able to consistently save half of ventilation-related energy without compromising long-term IAQ. Ventilation strategies that tracked occupancy were less successful, because this work included generic contaminants with constant background emission rates. Energy performance for occupancy controls improved with a one-hour pre-occupancy flush out strategy. The addition of zoning ventilation controls did not offer significant IAQ to energy improvements compared to non-zonal versions of the same ventilation system type. The best controls had HVAC energy savings of 10-20%, with individual cases reaching up to 40% savings. However, these savings cannot be achieved without worsening personal exposures for at least one contaminant. A metric is needed to assess the competing changes in exposure to different contaminants in order to determine the net-health impacts of a control strategy. Controls that directly sensed contaminants and controlled them to acceptable levels showed that the California OEHHA limit for formaldehyde completely dominates system performance, with homes not able to meet the limit even with continuous operation of a fan sized to twice the current code minimum.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Editorial: Plant-Soil Interactions Under Changing Climate

The health and well-being of plants and soil is crucial for all life on Earth. It is well-known that vegetation cover follows climatic zones, and plants respond to climatic drivers such as temperature and precipitation. It is also well-known that plant health depends on the properties and health of the soil, and that strong interactions among biota above and belowground dictate the functioning of both realms. Yet, soils and the processes occurring belowground are often considered a “black box,” and are treated very simplistically in our efforts to understand, quantify, and model the future of the planet. Our understanding of the interactions between plants and soils is also far from complete and offers some of the most important research frontiers in community ecology, biogeochemistry, and global change science.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Improved Representations of Land‐Atmosphere Interactions Over the Continental U.S. Through Dynamic Root Modeling

Previous studies have identified the oversimplified root system representation as a key factor leading to inaccuracies in vegetation‐atmosphere feedbacks. In this study, a dynamic root water uptake scheme in the Noah‐MP land surface model has been coupled to the Weather Research and Forecasting (WRF) model to investigate its impact on the surface hydroclimate variables and land‐atmosphere interactions. To evaluate the impact of the dynamic root, two coupled simulations were conducted, one with the dynamic root water uptake scheme (DynRt) and one with the static root water uptake scheme (StcRt), which is based on the default root representation in Noah‐MP, with slight modifications, primarily in vegetation‐related parameters. Both DynRt and StcRt simulations were conducted with a small ensemble of three members to account for variations in physical parameterizations, initial and boundary forcing and model setup. When compared with reference data sets, the DynRt simulations show improved results than the StcRt simulations, reducing biases in the simulated leaf area index, surface energy fluxes, soil moisture and precipitation. Two different mechanisms through which roots affect land‐atmosphere coupling have been identified. Over the transitional climate zone between the dry and wet climate, the dynamic root scheme affects surface climate and land‐atmosphere coupling mainly through changes in soil moisture through hydraulic redistribution by plant root system. Over the energy‐limited mesic zone, the dynamic root affects regional land‐atmosphere coupling mainly through changes in carbon allocation. This work highlights the importance of dynamic root representation in improving vegetation‐atmosphere simulations by enhancing predictions of water, energy, and carbon fluxes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Global meta-analysis shows pervasive phosphorus limitation of aboveground plant production in natural terrestrial ecosystems

Phosphorus (P) limitation of aboveground plant production is usually assumed to occur in tropical regions but rarely elsewhere. Here we report that such P limitation is more widespread and much stronger than previously estimated. In our global meta-analysis, almost half (46.2%) of 652 P-addition field experiments reveal a significant P limitation on aboveground plant production. Globally, P additions increase aboveground plant production by 34.9% in natural terrestrial ecosystems, which is 7.0–15.9% higher than previously suggested. In croplands, by contrast, P additions increase aboveground plant production by only 13.9%, probably because of historical fertilizations. The magnitude of P limitation also differs among climate zones and regions, and is driven by climate, ecosystem properties, and fertilization regimes. In addition to confirming that P limitation is widespread in tropical regions, our study demonstrates that P limitation often occurs in other regions. This suggests that previous studies have underestimated the importance of altered P supply on aboveground plant production in natural terrestrial ecosystems.

Science & Technology - Other Topics↗

NASA NTRS2015

Integrated Assessments of the Impact of Climate Change on Agriculture: An Overview of AgMIP Regional Research in South Asia

South Asia encompasses a wide and highly varied geographic region, and includes climate zones ranging from the mountainous Himalayan territory to the tropical lowland and coastal zones along alluvial floodplains. The region's climate is dominated by a monsoonal circulation that heralds the arrival of seasonal rainfall, upon which much of the regional agriculture relies. The spatial and temporal distribution of this rainfall is, however, not uniform over the region. Northern South Asia, central India, and the west coast receive much of their rainfall during the southwest monsoon season, between June and September. These rains partly result from the moisture transport accompanying the monsoonal winds, which move in the southwesterly direction from the equatorial Indian Ocean. Regions further south, such as south/southeast India and Sri Lanka, may receive rains from both the southwest monsoon, and also during the northeast monsoon season between October and December (with northeasterly monsoon wind flow and moisture flux), which results in a bi- or multi-modal rainfall distribution. In addition, rainfall across South Asia displays a large amount of intraseasonal and interannual variability. Interannual variability is influenced by many drivers, both natural (e.g., El Ni-Southern Oscillation; ENSO) and man-made (e.g., rising temperatures due to increasing greenhouse gas concentrations), and it is challenging to obtaining accurate time-series of annual rainfall, even amongst various observed data products, which display inconsistencies amongst themselves. These climatic and rainfall variations can further complicate South Asia's agricultural and water management. Agriculture employs at least 65 of the workforce in most South Asian countries, and nearly 80 of South Asia's poor inhabit rural areas. Understanding the response of current agricultural production to climate variability and future climate change is of utmost importance in securing food and livelihoods for South Asia's growing population. In order to assess the future of food and livelihood security across South Asia, the Agricultural Model Intercomparison and Improvement Project (AgMIP) has undertaken integrated climate-crop-economic assessments of the impact of climate change on food security and poverty in South Asia, encompassing Bangladesh, India, Nepal, Pakistan, and Sri Lanka. AgMIP has funded, on a competitive basis, four South Asian regional research teams (RRTs) and one South Asian coordination team (CT) to undertake climate-crop-economic integrated assessments of food security for many districts in each of these countries, with the goal of characterizing the state of food security and poverty across the region, and projecting how these are subject to change under future climate change conditions.

mountains↗