Search NASA⌕ Search

SEARCH · Search NASA

Results for “Environmental variabilities”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Interannual variability and trends of summertime PM2.5-based air quality in the Intermountain West

Abstract Summertime air quality is a growing public health concern in the populated region of Northern Utah. Whereas winter air pollution is highly linked with local atmospheric temperature inversions associated with upper atmospheric high-pressure and radiational cooling in valleys, the relationship between climate factors and the frequency of poor air quality during summer is still unknown. Analyzing the last 20 years of data, we demonstrated that summertime unhealthy days (as defined by PM2.5 air quality index level) in Northern Utah highly correlate with the number of dry-hot days, wildfire size, and an upper atmospheric ridge over the Northwestern United States. The persistent atmospheric ridge enhances lightning-caused fire burned areas in northwestern states and then transports the wildfire smoke toward Northern Utah. Similarly, climate model simulations confirm observational findings, such as an increasing trend of the upper atmospheric ridge and summertime dry days in the northwestern states. Such metrics developed in this study could be used to establish longer-term monitoring and seasonal forecasting for air quality and its compounding factors, which is currently limited to forecasting products for only several days.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Technical Background and Validation Report on the Residential Water Inhalation Risk Calculator Presented in the Risk Assessment Information System

Indoor air quality (IAQ) is critical for human health. Poor IAQ is linked to respiratory issues, cardiovascular diseases, and cancer. Indoor pollutants are emitted by typical household items such as cleaning products, personal care items, building materials, and tap water - an understudied volatile organic compound (VOC) source. This document presents the Residential Water Inhalation Risk Calculator (RWIRC), which estimates daily VOC exposure concentrations from various household water uses, such as showering and dishwashing, to assess exposure risks for the most vulnerable occupant. Integrated into the Risk Assessment Information System (RAIS) and sponsored by the US Department of Energy (DOE), the calculator divides a house into three compartments: shower, bathroom, and other spaces, accounting for daily water usage patterns and calculating VOC concentrations. Exposure data generated using the calculator can assist health assessors in estimating excess lifetime cancer risk (ELCR) and hazard index (HI) from VOC inhalation. Unlike traditional exposure models that utilize Andelman’s constant, the RWIRC continuously assesses variability in VOC concentrations and environmental conditions using differential equations to track VOC concentrations and air exchange between compartments. The calculator also provides unique volatilization fractions for each chemical and appliance, enhancing accuracy of the exposure concentration estimation. The RWIRC is accessible online and allows users to customize parameters (i.e., number of bathrooms, water temperature, and exhaust fan conditions) and input VOC characteristics (i.e., tap water and ambient air concentrations). This document provides a step-by-step guide on implementing the calculator. It also provides comparisons with the ATSDR-SHOWER calculator, using eight VOCs with varying physicochemical properties to reveal differences in algorithms and output concentrations. Simulations also assess how bathroom door positions and exhaust fan usage affect VOC exposure. The calculator results can enhance EPA risk screening levels for inhalation exposure to VOCs from tap water, offering a sophisticated tool for assessing inhalation risks and improving public health protection.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Cold Climate Field Study of the Effect of Defrost Controls on the Integrated Performance of a Ductless Air-Source Heat Pump

Residential heat pumps have advanced over the past decade to allow for operation at colder temperatures. However, the challenges of frost accumulation and defrosting the outdoor coil remain. The goal of this study was to evaluate the impact of the control algorithms that determine when a heat pump needs to defrost and when the base pan heater runs on the overall heating efficiency of the heat pump. In this study, which occurred during the 2023–2024 heating season, we measured the performance of a ductless air-source heat pump installed in Fairbanks, Alaska, USA. The heat pump was instrumented to measure the electrical input and the thermal output, as well as selected internal variables and indoor and outdoor environmental conditions. The heat pump was first operated with factory default control algorithms associated with the initiation of defrost and control of the base pan heater. These factory default algorithms focused on aggressively defrosting the outdoor coil and keeping the base pan ice-free. In the middle of the winter, these algorithms were changed to focus on reducing defrost cycles and increasing efficiency, while the heat pump continued to be operated and monitored. The results showed that significant increases in efficiency are possible by improving the defrost and base pan heater control algorithms.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1981

Economic evaluation of a solar hot-water-system

Analysis shows economic benefits at six representative sites using actual data from Tempe, Arizona and San Diego, California installations. Model is two-tank cascade water heater with flat-plate collector array for single-family residences. Performances are forecast for Albuquerque, New Mexico; Fort Worth, Texas; Madison, Wisconsin; and Washington, D.C. Costs are compared to net energy savings using variables for each site's environmental conditions, loads, fuel costs, and other economic factors; uncertainty analysis is included.

Source record↗
NASA NTRS1994

NASA/DOD Aerospace Knowledge Diffusion Research Project. Paper 38: Computer Mediated Communication (CMC) and the communication of technical information in aerospace

This paper discusses the use of computers as a medium for communication (CMC) used by aerospace engineers and scientists to obtain and/or provide technical information related to research and development activities. The data were obtained from a questionnaire survey that yielded 1006 mail responses. In addition to communication media, the research also investigates degrees of task uncertainty, environmental complexity, and other relevant variables that can affect aerospace workers' information-seeking strategies. While findings indicate that many individuals report CMC is an important function in their communication patterns, the research indicates that CMC is used less often and deemed less valuable than other more conventional media, such as paper documents, group meetings, telephone and face-to-face conversations. Fewer than one third of the individuals in the survey account for nearly eighty percent of the reported CMC use, and another twenty percent indicate they do not use the medium at all, its availability notwithstanding. These preliminary findings suggest that CMC is not as pervasive a communication medium among aerospace workers as the researcher expect a priori. The reasons underlying the reported media use are not yet fully known, and this suggests that continuing research in this area may be valuable.

Murphy, Daniel J.↗
NASA NTRS2014

Climate Scenarios for the NASA / USAID SERVIR Project: Challenges for Multiple Planning Horizons

SERVIR, an acronym meaning "to serve" in Spanish, is a joint venture between NASA and the U.S. Agency for International Development (USAID) which provides satellite-based Earth observation data, modeling, and science applications to help developing nations in Central America, East Africa and the Himalayas improve environmental decision making. Anticipating climate variability / climate change impacts has now become an important component of the SERVIR efforts to build capacity in these regions. Uncertainty in hydrometeorological components of climate variations and exposure to extreme events across scales from weather to climate are of particular concern. We report here on work to construct scenarios or outlooks that are being developed as input drivers for decision support systems (DSSs) in a variety of settings. These DSSs are being developed jointly by a broad array NASA Applied Science Team (AST) Investigations and user communities in the three SERVIR Hub Regions, Central America, East Africa and the Himalayas. Issues span hydrologic / water resources modeling, agricultural productivity, and forest carbon reserves. The scenarios needed for these efforts encompass seasonal forecasts, interannual outlooks, and likely decadal / multi-decadal trends. Providing these scenarios across the different AST efforts enables some level of integration in considering regional responses to climate events. We will discuss a number of challenges in developing this continuum of scenarios including the identification and "mining" of predictability, addressing multiple continental regions, issues of downscaling global model integrations to regional / local applications (i.e. hydrologic and crop modeling). We compare / contrast the role of the U.S. National Multi- Model Experiment initiative in seasonal forecasts and the CMIP-5 climate model experiments in supporting these efforts. Examples of these scenarios, their use, and an assessment of their utility as well as limitations will be presented.

Robertson, Franklin R.↗
NASA NTRS2019

Real-Time UAV Trajectory Prediction for Safety Monitoring in Low-Altitude Airspace

The rising number of small unmanned aerial vehicles (UAVs) expected in the next decade will enable a new series of commercial, service, and military operations in low altitude airspace as well as above densely populated areas. These operations may include on-demand delivery, medical transportation services, law enforcement operations, traffic surveillance and many more. Such unprecedented scenarios create the need for robust, efficient ways to monitor the UAV state in time to guarantee safety and mitigate contingencies throughout the operations. This work proposes a generalized monitoring and prediction methodology that utilizes realtime measurements of an autonomous UAV following a series of way-points. Two different methods, based on sinusoidal acceleration profiles and high-order splines, are utilized to generate the predicted path. The monitoring approach includes dynamic trajectory re-planning in the event of unexpected detour or hovering of the UAV during flight. It can be further extended to different vehicle types, to quantify uncertainty affecting the state variables, e.g., aerodynamic and other environmental effects, and can also be implemented to prognosticate safety-critical metrics which depend on the estimated flight path and required thrust. The proposed framework is implemented on a simplified, scalable UAV modeling and control system traversing 3D trajectories. Results presented include examples of real-time predictions of the UAV trajectories during flight and a critical analysis of the proposed scenarios under uncertainty constraints.

UAV trajectory prognosis↗
NASA NTRS2020

Groundwater Drought: Environmental Controls and Monitoring

Arising from a long-term deficit of precipitation, groundwater drought often lags meteorological drought by months to years, depending on climate and subsurface hydrogeological conditions. Due to the paucity of in situ groundwater data in many parts of the world, global monitoring of groundwater storage variations and drought may be best achieved using satellite observations and/or groundwater time series simulated by hydrological models. The Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow On (GRACE-FO) missions have greatly benefitted the modeling and monitoring of groundwater storage changes and drought at the global scale. In this chapter, we first review environmental controls on the temporal variability of groundwater using in situ data. We then describe an approach that infuses GRACE and GRACE-FO observations into a land surface model for assessing groundwater storage changes and drought globally. We also discuss characteristics of simulated groundwater drought and the limitations of current groundwater drought monitoring approaches.

Bailing Li↗
NASA NTRS2021

Snowfall in the Northern Great Lakes: Lessons Learned from a Multisensor Observatory

A multisensor snowfall observational suite has been deployed at the Marquette, Michigan, National Weather Service Weather Forecast Office (KMQT) since 2014. Micro Rain Radar (MRR; profiling radar), Precipitation Imaging Package (PIP; snow particle imager), and ancillary ground-based meteorological observations illustrate the unique capabilities of these combined instruments to document radar and concomitant microphysical properties associated with northern Great Lakes snowfall regimes. Lake-effect, lake-orographic, and transition event case studies are presented that illustrate the variety of snowfall events that occur at KMQT. Case studies and multiyear analyses reveal the ubiquity of snowfall produced by shallow events. These shallow snowfall features and their distinctive microphysical fingerprints are often difficult to discern with conventional remote sensing instruments, thus highlighting the scientific and potential operational value of MRR and PIP observations. The importance of near-surface lake-orographic snowfall enhancement processes in extreme snowfall events and regime-dependent snow particle microphysical variability controlled by regime and environmental factors are also highlighted.

Lake effects↗
DOE OSTI2021

Evaluating the effects of a low-carbon energy transition on existing U.S. fossil energy communities

On-going efforts and the growing movement to transition from our current energy systems towards low-carbon and renewable sources have uncovered a range of challenges and concerns communities may face under this transition. An understanding of the current relationships and dynamics within communities can offer critical insights that stakeholders, as well as decision and policy makers can use to better support and affect the outcome of these transitions. To support this need, the National Energy Technology Laboratory has been developing a data-driven framework to aid in the characterization of fossil energy communities across the U.S. and offer insights to comprehensively address energy transaction concerns by different stakeholder groups and various stages associated with a low-carbon energy system. This presentation will offer details on our current work to integrate multiple environmental, social, and economic data variables, as well as key trends and insights that are being used to characterize these communities at a local and regional scale. These insights will be used to evaluate with alternative opportunities, including, but not limited to, hydrogen, rare earth elements and critical minerals, and energy storage, that could be aid in the transition for these communities from conventional energy resources.

Bauer, Jennifer↗
DOE OSTI2022

An independent analysis of bias sources and variability in wind plant pre-construction energy yield estimation methods

The wind resource assessment community has long had the goal of reducing the bias between wind plant pre-construction energy yield assessment (EYA) and the observed annual energy production (AEP). This comparison is typically made between the 50% probability of exceedance (P50) value of the EYA and the long-term corrected operational AEP (hereafter OA P50), and is known as the P50 bias. The industry has critically lacked an independent analysis of bias reduction investigated across multiple consultants to identify the greatest sources of uncertainty and variance in the EYA process and the best opportunities for uncertainty reduction. The present study addresses this gap by benchmarking consultant methodologies against each other and against operational data at a scale not seen before in industry collaborations. We consider data from 10 wind plants and evaluate discrepancies between eight consultancies in the steps taken from estimates of gross to net energy. Consultants tend to overestimate the gross energy produced at the turbines and then compensate by further overestimating downstream losses, leading to a mean P50 bias near zero, still with significant variability among the individual wind plants. Within our data sample, we find that consultant estimates of all loss categories, except environmental losses, tend to reduce the project-to-project variability of the P50 bias. The disagreement between consultants, however, remains flat throughout the addition of losses. Finally, we find that differences in consultants’ estimates of project performance can lead to differences up to $10/MWh in the levelized cost of energy for a wind plant.

Todd, Austin C.↗
DOE OSTI2020

Mercury Speciation via Diffusive Gradients Thin-Films Technology

Objectives: Develop and test various diffusive gradient in thin films (DGT) samplers for mercury - SRNL is developing reactive DGTS (rDGTs). Test chemistry to differentiate methylmercury from total and/or inorganic mercury in environmental samples. Fabricate and test rDGT samplers for deployment. Deploy the rDGTs in variable settings. Mercury is a persistent-bioaccumulative-toxic environmental pollutant. Mercury exists in different species such as elemental, inorganic, and methyl. Mercury speciation determine mercury behavior and toxicity. For example, methylmercury strongly accumulates in biota such as fish resulting in potential human health impacts. DGTs are innovative samplers to measure water concentration by diffusion and capture. Types of Hg DGTs used: Total Hg, Inorganic Hg, and Methyl Hg. Deployment Sites: Upper Three Runs, Lower Three Runs, Steele Creek, East Fork Poplar Creek (SRNL Sites), Horizons Creek, NOA Creek, Bruners Creek (ORNL Sites). DGT concentration estimates closely matched alternative measurements for soluble mercury at each Oak Ridge site - DGTs did not respond to particulate mercury. DGTs provide a representative measure for biota uptake since they are left out longer which allows for an average exposure concentration. DMA-80 provided an efficient and quick analysis. Variability in site location made a difference in Hg species. DGT preparations and sampling wasn't as quick and simple as microcolumn technology. Copper reagent degraded agarose gel - more work and cleaner data are needed to assess speciation in rDGTs. Future Work: Use cross-linked polyacrylamide for the collection layer for a stronger plastic. Make a copper diffusion layer without agarose. Test copper separation in lab using realistic stream conditions such as high organic carbon.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Session 3: Agrivoltaics Pathways [Slides]

This presentation was developed for a webinar series for the USAID's South Asia Group for Energy (SAGE) and South Asia Regional Energy Partnership (SAREP). The presentation includes insights into agrivoltaic site assessment planning, including what is needed for a farm assessment, solar panel system design from the agricultural perspective, variables that go into crop selection, and environmental impact, sustainability, and agritourism, technical parameters for developing an agrivoltaics project, including what makes up a PV feasibility study, understanding variables that go into technology and equipment selection, agrivoltaic installation and agricultural integration, and monitoring and maintenance throughout the life of the project, and agrivoltaic financial planning, risk mitigation, and debt equity issues.

14 SOLAR ENERGY↗
DOE OSTI2023

Biogeophysical Effects of Land-Use and Land-Cover Change Not Detectable in Warmest Month

Land-use and land-cover changes (hereafter simply “land use”) alter climates biogeophysically by affecting surface fluxes of energy and water. Yet, near-surface temperature responses to land use across observational versus model-based studies and spatial-temporal scales can be inconsistent. Here we assess the prevalence of the historical land use signal of daily maximum temperatures averaged over the warmest month of the year (t LU ) using regularized optimal fingerprinting for detection and attribution. We use observations from the Climatic Research Unit and Berkeley Earth alongside historical simulations with and without land use from phase 6 of the Coupled Model Intercomparison Project to reconstruct an experiment representing the effects of land use on climate. To assess the signal of land use at spatially resolved continental and global scales, we aggregate all input data across reference regions and continents, respectively. At both scales, land use does not comprise a significantly detectable set of forcings for two of four Earth system models and their multimodel mean. Furthermore, using a principal component analysis, we find that t LU is mostly composed of the nonlocal effects of land use rather than its local effects. These findings show that, at scales relevant for climate attribution, uncertainties in Earth system model representations of land use are too high relative to the effects of internal variability to confidently assess land use.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Costs of mitigating the environmental impacts of hydropower projects in the United States

Developers are required to mitigate the environmental impacts of hydropower projects in the United States (U.S.) but there is very little accessible information on the associated costs. This work compiles and analyses a dataset of environmental impacts mitigation costs for 182 hydropower projects based on documents obtained from the U.S. Federal Energy Regulatory Commission (FERC). The analysis shows that environmental costs vary wildly across hydropower project classes and mitigation measures, even when normalized by plant capacity. Capital costs per kilowatt are generally higher for relicensed conventional hydropower plants, and lower for new and relicensed pumped storage hydropower plants, relative to other project classes. Smaller plants tend to spend a higher share of total project costs on mitigating environmental impacts than larger plants, and measures related to Aquatic Species, Project Operations, and Recreation have the highest capital cost per kilowatt. These findings mean that environmental costs could become a key decision variable for new hydropower developments in the U.S. due to the small scale of most of the remaining potential and the increasing stringency of environmental requirements. Therefore, technologies to reduce the environmental impacts and costs of hydropower would be important for future project developments.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

Probabilistic Physics-Based Risk Tools Used to Analyze the International Space Station Electrical Power System Output

This paper describes the methods employed to apply probabilistic modeling techniques to the International Space Station (ISS) power system. These techniques were used to quantify the probabilistic variation in the power output, also called the response variable, due to variations (uncertainties) associated with knowledge of the influencing factors called the random variables. These uncertainties can be due to unknown environmental conditions, variation in the performance of electrical power system components or sensor tolerances. Uncertainties in these variables, cause corresponding variations in the power output, but the magnitude of that effect varies with the ISS operating conditions, e.g. whether or not the solar panels are actively tracking the sun. Therefore, it is important to quantify the influence of these uncertainties on the power output for optimizing the power available for experiments.

Patel, Bhogila M.↗
DOE OSTI2023

Data to Accompany: PM2.5 is insufficient to explain personal PAH exposure

Fine particulate matter (PM2.5) air quality index (AQI) data from outdoor stationary monitors and Hazard Mapping System (HMS) smoke density data from satellites are often used as proxies for personal chemical exposure. Silicone wristbands can quantify more individualized exposure data than stationary air monitors or smoke satellites. However, it is not understood how these proxy measurements compare to chemical data measured from wristbands. We hypothesized that predictive models for personal chemical exposure would be significantly improved by expanding beyond stationary PM2.5 AQI data or satellite HMS data to also include environmental and behavioral information. In Eugene, Oregon, participants wore daily wristbands, carried a phone that recorded locations, and answered daily questionnaires for a seven-day period in multiple seasons. We gathered publicly available daily PM2.5 AQI data and HMS data. We analyzed wristbands for 94 organic chemicals, including 53 polycyclic aromatic hydrocarbons (PAHs). Wristband chemical detections and concentrations, behavioral variables (e.g., time spent indoors), and environmental conditions (e.g., PM2.5 AQI) significantly differed between seasons. Machine learning models were fit to predict personal chemical exposure using PM2.5 AQI only, HMS only, and a multivariate feature set including PM2.5 AQI, HMS, and other environmental and behavioral information. On average, the multivariate models increased predictive accuracy by approximately 70% compared to either the AQI model or the HMS model for all chemicals modeled. This study provides evidence that PM2.5 AQI data alone or HMS data alone is insufficient to explain personal chemical exposures. Our results identify additional key predictors of personal chemical exposure.

Bramer, Lisa M↗
DOE OSTI2020

Marine Corps Base Camp Lejeune Climate Forecasts

Critical military training and testing on lands along the nation’s coastal and estuarine shorelines are increasingly placed at risk because of encroachment pressures in surrounding areas, impairments due to other anthropogenic disturbances, and changes in climate and sea level. The U.S. Department of Defense (DoD) intends to enhance and sustain its training and testing assets and also optimize its stewardship of natural resources through the development and application of an ecosystem-based management approach on DoD installations. To accomplish this goal, particularly for installations in estuarine/coastal environments, the Strategic Environmental Research and Development Program (SERDP) launched the Defense Coastal/Estuarine Research Program (DCERP) as a 10-year effort at Marine Corps Base Camp Lejeune (MCBCL) in North Carolina. The results of the second 5 years of the program (DCERP2) are presented in the DCERP2 Final Report.There were four overarching objectives of DCERP2. The first objective was to understand the effects of climate change impacts, including warming temperatures, variability in the hydrological cycle, storm events, and sea level rise on the coastal ecosystems at MCBCL from observations and measurements made over the 10-year program. The second objective was to understand the carbon cycle of the coastal and terrestrial ecosystems at MCBCL through a highly integrated sampling program. The third objective was to develop models, tools, and indicators to evaluate current and projected future ecosystem state changes and translate scientific findings into actionable information for installation managers. The last objective was to recommend adaptive management strategies to sustain ecosystem natural resources within the context of an active military installation.There are 252 mean change files represented in this dataset (12 months * 3 future time periods * 7 variables ). The mean change is calculated by taking the mean of the differences between the future projected average (e.g., 2046-2065) and the climate model baseline (e.g., 1979-1999). The differences were calculated for each downscaled GCM and then averaged across all models to obtain the mean change. This mean of the differences was calculated for each month, each future time period, and each variable.

54 ENVIRONMENTAL SCIENCES↗