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DOE OSTI2025

Integrating Contaminant Source Indicators, Water Quality Measures, and Ecotoxicity to Characterize Contaminant Mixtures and Per- and Polyfluoroalkyl Substance (PFAS) Variability in an Urban Watershed

Thousands of chemical contaminants threaten watersheds but are time and cost prohibitive to monitor. Identifying their sources, transport, and ecological risk is limited in heterogeneous urban watersheds. We present an integrative watershed approach using source-specific indicator compounds, common water quality measures, and ecotoxicity assays to examine the distribution of contaminant mixtures in an urbanized watershed. Indicator compound concentrations were temporally and spatially distributed for treated/untreated sewage (sucralose, artificial sweetener), road runoff (diphenyl-guanidine [DPG] and 6PPD-quinone [6PPD-Q], automobile tire additives), and lawncare runoff (aminomethanephosphonic acid (AMPA), major degradant of the herbicide glyphosate). Sucralose was predominately sourced from treated wastewater; measurable concentrations in tributaries indicated raw sewage inputs. DPG and 6PPD-Q concentrations correlated to road density during base flow and were elevated during stormflow. AMPA was measurable spring through fall, especially where lawns were dense. When specific sources dominated flow, water quality measures correlated with wastewater (sulfate, potassium, chloride, and sodium) and road runoff (chromium and lead) indicators. The limited behavioral toxicity observed in exposed zebrafish (Danio rerio) (18%) was not well explained by source-indicators. PFAS concentrations were highly variable spatially but not well explained by our source-specific indicator compounds. Here, more costly compound-specific monitoring may be necessary when multiple sources exist or when unexpected toxicity trends occur.

computer simulations↗

NASA NTRS1994

Real refractive indices of infrared-characterized nitric-acid/ice films: Implications for optical measurements of polar stratospheric clouds

The infrared spectra of nitric-acid/ice films representative of polar stratospheric clouds (PSCs) were collected with simultaneous optical interference measurements to determine the real refractive indices at lambda = 632 nm. Ice and amphorous nitric-acid/ice films were prepared by condensation of water and nitric acid vapors onto a wedged Al2O3 substrate. The real refractive indices of these films were determined from the optical interference of a reflected helium-neon laser during film growth. The indices of the amphorous films varied smoothly from n = 1.30 for ice to n = 1.49 for nitric acid, similar to observations in previous work. We were unable to obtain the refractive index of crystlline films during adsorption because of optical scattering caused by surface roughness. Therefore crystlline nitric acid hydrate films were prepared by annealing amphorous nitric-acid/ice films. Further heating caused desorption of the crystalline hydrate films. During desorption, the refractive indices for ice, NAM (nitric acid monohydrate), alpha- and beta-NAT (nitric acid trihydrate) films were measured using the optical interference technique. In agreement with earlier data, the real refractive indices for ice and NAM determined in desorption were n = 1.30 +/- 0.01 and n = 1.53 +/- 0.03, respectively. The real refractive indices for alpha- and beta-NAT were found to be n = 1.51 +/- 0.01 and n greater than or equal to 1.46, respectively. Our measurements also suggest that the shape of crystalline nitric acid particles may depend on whether they nucleate from the liquid or by vapor deposition. If confirmed by future studies, this observation may provide a means of distinguishing the nucleation mechanism of crystalline PSCs.

Middlebrook, Ann M.↗

NASA NTRS1996

Using Design Capability Indices to Satisfy Ranged Sets of Design Requirements

For robust design it is desirable to allow the design requirements to vary within a certain range rather than setting point targets. This is particularly important during the early stages of design when little is known about the system and its requirements. Toward this end, design capability indices are developed in this paper to assess the capability of a family of designs, represented by a range of top-level design specifications, to satisfy a ranged set of design requirements. Design capability indices are based on process capability indices from statistical process control and provide a single objective, alternate approach to the use of Taguchi's signal-to- noise ratio which is often used for robust design. Successful implementation of design capability indices ensures that a family of designs conforms to a given ranged set of design requirements. To demonstrate an application and the usefulness of design capability indices, the design of a solar powered irrigation system is presented. Our focus in this paper is on the development and implementation of design capability indices as an alternate approach to the use of the signal-to-noise ratio and not on the results of the example problem, per se.

Chen, Wei↗

NASA NTRS2007

Study of Radiographic Linear Indications and Subsequent Microstructural Features in Gas Tungsten Arc Welds of Inconel 718

This study presents examples and considerations for differentiating linear radiographic indications produced by gas tungsten arc welds in a 0.05-in-thick sheet of Inconel 718. A series of welds with different structural features, including the enigma indications and other defect indications such as lack of fusion and penetration, were produced, radiographed, and examined metallographically. The enigma indications were produced by a large columnar grain running along the center of the weld nugget occurring when the weld speed was reduced sufficiently below nominal. Examples of respective indications, including the effect of changing the x-ray source location, are presented as an aid to differentiation. Enigma, nominal, and hot-weld specimens were tensile tested to demonstrate the harmlessness of the enigma indication. Statistical analysis showed that there is no difference between the strengths of these three weld conditions.

Walley, J. L.↗

NASA NTRS2009

Exploring Connections between Global Climate Indices and African Vegetation Phenology

Variations in agricultural production due to rainfall and temperature fluctuations are a primary cause of food insecurity on the continent in Africa. Agriculturally destructive droughts and floods are monitored from space using satellite remote sensing by organizations seeking to provide quantitative and predictive information about food security crises. Better knowledge on the relation between climate indices and food production may increase the use of these indices in famine early warning systems and climate outlook forums on the continent. Here we explore the relationship between phenology metrics derived from the 26 year AVHRR NDVI record and the North Atlantic Oscillation index (NAO), the Indian Ocean Dipole (IOD), the Pacific Decadal Oscillation (PDO), the Multivariate ENSO Index (MEI) and the Southern Oscillation Index (SOI). We explore spatial relationships between growing conditions as measured by the NDVI and the five climate indices in Eastern, Western and Southern Africa to determine the regions and periods when they have a significant impact. The focus is to provide a clear indication as to which climate index has the most impact on the three regions during the past quarter century. We found that the start of season and cumulative NDVI were significantly affected by variations in the climate indices. The particular climate index and the timing showing highest correlation depended heavily on the region examined. The research shows that climate indices can contribute to understanding growing season variability in Eastern, Western and Southern Africa.

Brown, Molly E.↗

NASA NTRS2011

New Local, National and Regional Cereal Price Indices for Improved Identification of Food Insecurity

Large price increases over a short time period can be indicative of a deteriorating food security situation. Food price indices developed by the United Nations Food and Agriculture Organization (FAO) are used to monitor food price trends at a global level, but largely reflect supply and demand conditions in export markets. However, reporting by the United States Agency for International Development (USAID)'s Famine Early Warning Systems Network (FEWS NET) indicates that staple cereal prices in many markets of the developing world, especially in surplus-producing areas, often have a delayed and variable response to international export market price trends. Here we present new price indices compiled for improved food security monitoring and assessment, and specifically for monitoring conditions of food access across diverse food insecure regions. We found that cereal price indices constructed using market prices within a food insecure region showed significant differences from the international cereals price, and had a variable price dispersion across markets within each marketshed. Using satellite-derived remote sensing information that estimates local production and the FAO Cereals Index as predictors, we were able to forecast movements of the local or national price indices in the remote, arid and semi-arid countries of the 38 countries examined. This work supports the need for improved decision-making about targeted aid and humanitarian relief, by providing earlier early warning of food security crises.

Brown, Molly E.↗

NASA NTRS2014

Investigation of Spiral Bevel Gear Condition Indicator Validation via AC-29-2C Using Fielded Rotorcraft HUMS Data

This report presents the analysis of gear condition indicator data collected on a helicopter when damage occurred in spiral bevel gears. The purpose of the data analysis was to use existing in-service helicopter HUMS flight data from faulted spiral bevel gears as a Case Study, to better understand the differences between HUMS data response in a helicopter and a component test rig, the NASA Glenn Spiral Bevel Gear Fatigue Rig. The reason spiral bevel gear sets were chosen to demonstrate differences in response between both systems was the availability of the helicopter data and the availability of a test rig that was capable of testing spiral bevel gear sets to failure. The objective of the analysis presented in this paper was to re-process helicopter HUMS data with the same analysis techniques applied to the spiral bevel rig test data. The damage modes experienced in the field were mapped to the failure modes created in the test rig. A total of forty helicopters were evaluated. Twenty helicopters, or tails, experienced damage to the spiral bevel gears in the nose gearbox. Vibration based gear condition indicators data was available before and after replacement. The other twenty tails had no known anomalies in the nose gearbox within the time frame of the datasets. These twenty tails were considered the baseline dataset. The HUMS gear condition indicators evaluated included gear condition indicators (CI) Figure of Merit 4 (FM4), Root Mean Square (RMS) or Diagnostic Algorithm 1 (DA1) and +/- 3 Sideband Index (SI3). Three additional condition indicators, not currently calculated on-board, were calculated from the archived data. These three indicators were +/- 1 Sideband Index (SI1), the DA1 of the difference signal (DiffDA1) and the peak-to-peak of the difference signal (DP2P). Results found the CI DP2P, not currently available in the on-board HUMS, performed the best, responding to varying levels of damage on thirteen of the fourteen helicopters evaluated. Two additional CIs also not in the on-board system, DiffDA1and SI1, also performed well responding to twelve and ten of the fourteen helicopters evaluated respectively. Of the three CIs currently available in the MSPU, DA1, FM4 and SI3, SI3, responded to eight, DA1 responded to six and FM4 responded to four of the fourteen helicopters evaluated. FM4, the poorest performing CI, was not as responsive to damage as the other five CIs. Conversely, when compared to the other two, it was the only CI that responded to damage on two helicopters. CI response could not be correlated to specific failure modes due to limited pictures and subjective descriptions found within the TDA. Flight regime did affect CI response to some gear faults. Due to the range of operating conditions for each regime, more studies are required to determine their sensitivity to regimes.

rotorcraft↗

NASA NTRS2016

Computational Modeling to Limit the Impact Displays and Indicator Lights Have on Habitable Volume Operational Lighting Constraints

The goal of this investigation is to determine design limitations and architectural solutions that limit the impact light from displays and indicator lamps have on the operational environment task lighting and lighting countermeasure spectrum constraints. It is concerning that this innovative architectural lighting system, could be compromised by spectrums from display systems, architectural materials, and structures that are not considered as part a full system design implementation. The introduction of many Commercial Off the Shelf (COTS) products to the spacecraft volume that contain LEDs, without consideration to the human factors and biological constraints, is another problem. Displays and indicators are a necessary part of the spacecraft and it is the goal of this research project to determine constraints and solutions that allow these systems to be integrated while minimizing how the lighting environment is modified by them. Due to the potentially broad scope of this endeavor, the project team developed constraints for the evaluation. The evaluation will be on a set of tasks that required significant exposure in the same environment while having a large chance of impacting the light spectrum the crew is expected to receive from the architectural lighting system. The team plans to use recent HRP research on "Net Habitable Volume" [1] to provide the boundary conditions for volume size. A Zemax ® lighting model was developed of a small enclosure that had high intensity overhead lighting and a standard intensity display with LED indicator arrays. The computer model demonstrated a work surface illuminated at a high level by the overhead light source compared to displays and indicators whose light is parallel to the work plane. The overhead lighting oversaturated spectral contributions from the display and indicator at the task work surface. Interestingly, when the observer looked at the displays and LEDs within the small enclosure, their spectral contribution was significant but could be reduced by reflecting overhead light from the wall(s) to the observer. Direct observation of displays and LEDs are an issue because the user's viewing area is a display, not an illuminated work surface. Since avionics command centers consume significant crew time, the tasks that seemed at higher risk for unwanted spectral contributions as an operational volume with significant quantity of displays and indicators that were either under direct observation of the crew or impacting a volume the crew may be required to sleep in.

Clark, T. E.↗

NASA NTRS2021

Observations of Greenhouse Gases as Climate Indicators

Humans have significantly altered the energy balance of the Earth’s climate system mainly not only by extracting and burning fossil fuels but also by altering the biosphere and using halocarbons. The 3rd US National Climate Assessment pointed to a need for a system of indicators of climate and global change based on long-term data that could be used to support assessments and this led to the development of the National Climate Indicators System (NCIS). Here we identify a representative set of key atmospheric indicators of changes in atmospheric radiative forcing due to greenhouse gases (GHGs), and we evaluate atmospheric composition measurements, including non-CO2GHGs for use as climate change indicators in support of the US National Climate Assessment. GHG abundances and their changes over time can provide valuable information on the success of climate mitigation policies, as well as insights into possible carbon-climate feedback processes that may ultimately affect the success of those policies. To ensure that reliable information for assessing GHG emission changes can be provided on policy-relevant scales, expanded observational efforts are needed. Furthermore, the ability to detect trends resulting from changing emissions requires a commitment to supporting long-term observations. Long-term measurements of greenhouse gases, aerosols, and clouds and related climate indicators used with a dimming/brightening index could provide a foundation for quantifying forcing and its attribution and reducing error in existing indicators that do not account for complicated cloud processes.

greenhouse gases↗

NASA NTRS2020

Evaluating impacts of snow, surface water, soil and vegetation on empirical vegetation and snow indices for the Utqiaġvik tundra ecosystem in Alaska with the LVS3 model

Satellite observations for the Arctic and boreal region may contain information of vegetation, soil, snow, snowmelt, and/or other surface water bodies. We investigated the impacts of vegetation, soil, snow and surface water on empirical vegetation/snow indices on a tundra ecosystem area located around Utqiaġvik (formerly Barrow) of Alaska with the Moderate Resolution Imaging Spectrometer (MODIS) images in 2001–2014. Empirical vegetation indices, such as normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), the index of near infrared of vegetation (NIRv), and modified EVI (EVI2), have been used to monitor vegetation. Normalized difference snow index (NDSI) has been widely applied to monitor snow. The vegetation cover fraction (VGCF), the soil cover fraction (SOILCF), the snow cover fraction (SNOWCF), the surface water body cover fraction (WaterBodyCF), the fractional absorption of photosynthetically active radiation (PAR) by vegetation chlorophyll (fAPARchl), the fractional absorption of PAR by non-chlorophyll components of the vegetation (fAPARnon-chl), and the fractional absorption of PAR by the entire canopy (fAPARcanopy) are retrieved with the MODIS images and a coupled Leaf-Vegetation-Soil-Snow-Surface water body radiative transfer model, LVS3. The vegetation indices (NDVI, EVI, EVI2 and NIRv) differ from VGCF, fAPARchl, fAPARnon-chl, and fAPARcanopy. In addition to vegetation, we find that soil, snow and surface water also have impacts on vegetation indices NDVI, EVI (EVI2), and NIRv. Presence of snow makes lower the observed values of NDVI, EVI2 and NIRv. After snowmelt is gone, the vegetation indices (NDVI, EVI, EVI2 and NIRv) linearly decrease with SOILCF and WaterBodyCF, and WaterBodyCF has stronger impacts on these vegetation indices than SOILCF. The relationship between EVI and snow is complicated. NDSI non-linearly increases with SNOWCF, but linearly increases with sum of SNOWCF and WaterBodyCF (sum = 0.5893 × NDSI +0.4342, R2 = 0.976). NDSI linearly decreases with VGCF, and the relationship between NDSI and SOILCF is complex. Retrievals of VGCF, fAPARchl, fAPARnon-chl and fAPARcanopy with the LVS3 model provide alternatives for vegetation monitoring and ecological modeling.

Qingyuan Zhang↗

NASA NTRS2021

Climate Drivers of Arctic Tundra Variability and Change Using an Indicators Framework

This study applies an indicators framework to investigate climate drivers of tundra vegetation trends and variability over the 1982–2019 period. Previously known indicators relevant for tundra productivity (summer warmth index (SWI), coastal spring sea-ice (SI) area, coastal summer open-water (OW)) and three additional indicators (continentality, summer precipitation, and the Arctic Dipole (AD): second mode of sea level pressure variability) are analyzed with maximum annual Normalized Difference Vegetation Index (MaxNDVI) and the sum of summer bi-weekly (time-integrated) NDVI (TI-NDVI) from the Advanced Very High Resolution Radiometer time-series. Climatological mean, trends, and correlations between variables are presented. Changes in SI continue to drive variations in the other indicators. As spring SI has decreased, summer OW, summer warmth, MaxNDVI, and TI-NDVI have increased. However, the initial very strong upward trends in previous studies for MaxNDVI and TI-NDVI are weakening and becoming spatially and temporally more variable as the ice retreats from the coastal areas. TI-NDVI has declined over the last decade particularly over High Arctic regions and southwest Alaska. The continentality index (CI) (maximum minus minimum monthly temperatures) is decreasing across the tundra, more so over North America than Eurasia. The relationship has weakened between SI and SWI and TI-NDVI, as the maritime influence of OW has increased along with total precipitation. The winter AD is correlated in Eurasia with spring SI, summer OW, MaxNDVI, TI-NDVI, the CI and total summer precipitation. This winter connection to tundra emphasizes the role of SI in driving the summer indicators. The winter (DJF) AD drives SI variations which in turn shape summer OW, the atmospheric SWI and NDVI anomalies. The winter and spring indicators represent potential predictors of tundra vegetation productivity a season or two in advance of the growing season.

Uma S. Bhatt↗

DOE OSTI2021

An Indicator-based Approach to Sustainable Management of Natural Resources (Chapter 12)

Assessing the sustainability of natural resource management choices for agricultural and forest lands requires quantification of potential changes to a set of environmental and socioeconomic indicators selected to characterize reference scenarios relative to projected future scenarios. Correctly framing the questions with local stakeholders is a critical first step in the sustainability assessment, and the questions that can be addressed are often limited by data availability. Selecting and prioritizing indicators with stakeholders to address their needs and concerns improves the likelihood of investment in monitoring and evaluation of those indicators over time. Computational techniques for analyzing interactions between the selected indicators are inherently affected by the scales and formats of the assembled indicator datasets. Data analytics have the potential to improve understanding of the potential synergies and tradeoffs involved with meeting multiple environmental and socioeconomic goals simultaneously, but timely and appropriate indicator datasets are not always available—even in this new era of “big data.” Continued improvements in data science and data analytics are needed to broaden understanding and acceptance of problems and to provide valuable information for natural resource management. Advances in these areas will enable society to design future landscapes that meet multiple objectives, including the provisioning of agricultural and forest resources along with a variety of ecosystem services (e.g., clean water and healthy soils).

Parish, Esther↗

DOE OSTI2020

A Comprehensive System of Energy Intensity Indicators for the U.S.: Methods, Data and Key Trends

This report describes a comprehensive system of energy intensity indicators for the United States that has been developed for the Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE) over the past decade. This system of indicators is hierarchical in nature, beginning with detailed indexes of energy intensity for various sectors of the economy, which are ultimately aggregated to an overall energy intensity index for the economy as a whole. The aggregation of energy intensity indexes to higher levels in the hierarchy is performed with a version of the Log Mean Divisia index (LMDI) method. Based upon the data and methods in the system of indicators, the economy-wide energy intensity index shows a decline of about 16% in 2014 relative to a 1985 base year. Discussion of energy intensity indicators for each of the broad end-use sectors of the economy—residential, commercial, industrial, and transportation—is presented in the report. An analysis of recent changes in the efficiency of electricity generation in the U.S. is also included. A detailed appendix describes the data sources and methodology behind the energy intensity indicators for each sector.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

A Comprehensive System of Energy Intensity Indicators for the U.S.: Methods, Data and Key Trends

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

2020 Review Panel Workshop on Energy Intensity Indicators: Summary Findings and Meeting Notes

On January 28-29, 2020, the U.S. Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy (EERE), in coordination with Pacific Northwest National Laboratory (PNNL), sponsored an expert workshop focused on energy intensity indicators. The intent of the workshop was to support a comprehensive review of the EERE Energy Intensity Indicators (EII), a national system of indicators used to track changes in the energy intensity of economic sectors. One goal of the workshop was to gather input from a panel of experts who have experience and knowledge related to the EII methodological approach and key data sources used to calculate indicators for each of the end-use sectors of the economy—transportation, residential, commercial, industrial, and electricity. The current EERE EII methodology is documented in a 2017 PNNL report, A Comprehensive System of Energy Intensity Indicators for the U.S.: Methods, Data and Key Trends, which is available online. The workshop also included a presentation by Dr. Beng Ang, who discussed the Log Mean Divisia index (LMDI) approach to decomposition analysis, which was followed by a discussion concerning the methodological approaches that could be applied to future EII efforts.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Functional Filaments: Creating and Degrading pH-Indicating PLA Filaments for 3D Printing

With the rapid pace of advancements in additive manufacturing and techniques such as fused filament fabrication (FFF), the feedstocks used in these techniques should advance as well. While available filaments can be used to print highly customizable parts, the creation of the end part is often the only function of a given feedstock. In this study, novel FFF filaments with inherent environmental sensing functionalities were created by melt-blending poly(lactic acid) (PLA), poly(ethylene glycol) (PEG), and pH indicator powders (bromothymol blue, phenolphthalein, and thymol blue). The new PLA-PEG-indicator filaments were universally more crystalline than the PLA-only filaments (33–41% vs. 19% crystallinity), but changes in thermal stability and mechanical characteristics depended upon the indicator used; filaments containing bromothymol blue and thymol blue were more thermally stable, had higher tensile strength, and were less ductile than PLA-only filaments, while filaments containing phenolphthalein were less thermally stable, had lower tensile strength, and were more ductile. When the indicator-filled filaments were exposed to acidic, neutral, and basic solutions, all filaments functioned as effective pH sensors, though the bromothymol blue-containing filament was only successful as a base indicator. The biodegradability of the new filaments was evaluated by characterizing filament samples after aging in soil and soil slurry mixtures; the amount of physical deterioration and changes in filament crystallinity suggested that the bromothymol blue filament degraded faster than PLA-only filaments, while the phenolphthalein and thymol blue filaments saw decreases in degradation rates.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

Behavioral Indicators in Air Traffic Control: Detecting and Preventing Performance Decline

Air traffic controllers are responsible for the safety and efficiency of air traffic and therefore must maintain a consistently high standard of performance. However, performance can be negatively affected by factors such as workload and fatigue, potentially leading to performance decline and performance-related incidents. Real-time identification of negative influences would facilitate timely implementation of supportive strategies prior to performance decline. The current study aimed to explore the concept of ‘behavioral indicators’ to identify when a controller was reaching a performance limit. A second aim was to capture behavioral indicators associated with performance influencing factors. A total of 65 controllers spanning Tower, Approach and Enroute facilities across the United States of America were interviewed. Findings revealed that controllers were familiar with the concept of behavioral indicators, and that indicators were associated with specific performance-influencing factors. Implications for implementing behavioral indicators training in control environments are discussed.

air traffic control↗

NASA NTRSDate not supplied

Behavioral Indicators: How You Know When You are Losing the Flick and What to Do About It?

behavioral indicators↗