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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Satellite-derived Cyanobacteria Frequency and Magnitude in Headwaters & Near-dam Reservoir Surface Waters of the Southern U.S.

Reservoirs are dominant features of the modern hydrologic landscape and provide vital services. However, the unique morphology of reservoirs can create suitable conditions for excessive algae growth and associated cyanobacteria blooms in shallow in-flow reservoir locations by providing warm water environments with relatively high nutrient inputs, deposition, and nutrient storage. Cyanobacteria harmful algal blooms (cyanoHAB) are costly water management issues and bloom recurrence is associated with economic costs and negative impacts to human, animal, and environmental health. As cyanoHAB occurrence varies substantially within different regions of a water body, understanding in-lake cyanoHAB spatial dynamics is essential to guide reservoir monitoring and mitigate potential public exposure to cyanotoxins. Cloud-based computational processing power and high temporal frequency of satellites enables advanced pixel-based spatial analysis of cyanoHAB frequency and quantitative assessment of reservoir headwater in-flows compared to near-dam surface waters of individual reservoirs. Additionally, extensive spatial coverage of satellite imagery allows for evaluation of spatial trends across many dozens of reservoir sites. Surface water cyanobacteria concentrations for sixty reservoirs in the southern U.S. were estimated using 300 m resolution European Space Agency (ESA) Ocean and Land Colour Instrument (OLCI) satellite sensor for a five year period (May 2016–April 2021). Of the reservoirs studied, spatial analysis of OLCI data revealed 98% had more frequent cyanoHAB occurrence above the concentration of >100,000 cells/mL in headwaters compared to near-dam surface waters (P < 0.001). Headwaters exhibited greater seasonal variability with more frequent and higher magnitude cyanoHABs occurring mid-summer to fall. Examination of reservoirs identified extremely high concentration cyanobacteria events (>1,000,000 cells/mL) occurring in 70% of headwater locations while only 30% of near-dam locations exceeded this threshold. Wilcoxon signed-rank tests of cyanoHAB magnitudes using paired-observations (dates with observations in both a reservoir's headwater and near-dam locations) confirmed significantly higher concentrations in headwater versus near-dam locations (p < 0.001).

Amber R Ignatius↗
NASA NTRS2022

Satellite-derived cyanobacteria frequency and magnitude in headwaters & near-dam reservoir surface waters of the Southern U.S.

Reservoirs are dominant features of the modern hydrologic landscape and provide vital services. However, the unique morphology of reservoirs can create suitable conditions for excessive algae growth and associated cyanobacteria blooms in shallow in-flow reservoir locations by providing warm water environments with relatively high nutrient inputs, deposition, and nutrient storage. Cyanobacteria harmful algal blooms (cyanoHAB) are costly water management issues and bloom recurrence is associated with economic costs and negative impacts to human, animal, and environmental health. As cyanoHAB occurrence varies substantially within different regions of a water body, understanding in-lake cyanoHAB spatial dynamics is essential to guide reservoir monitoring and mitigate potential public exposure to cyanotoxins. Cloud-based computational processing power and high temporal frequency of satellites enables advanced pixel-based spatial analysis of cyanoHAB frequency and quantitative assessment of reservoir headwater in-flows compared to near-dam surface waters of individual reservoirs. Additionally, extensive spatial coverage of satellite imagery allows for evaluation of spatial trends across many dozens of reservoir sites. Surface water cyanobacteria concentrations for sixty reservoirs in the southern U.S. were estimated using 300m resolution European Space Agency (ESA) Ocean and Land Colour Instrument (OLCI) satellite sensor for a five year period (May 2016–April 2021). Of the reservoirs studied, spatial analysis of OLCI data revealed 98% had more frequent cyanoHAB occurrence above the concentration of >100,000 cells/mL in headwaters compared to near-dam surface waters (P < 0.001). Headwaters exhibited greater seasonal variability with more frequent and higher magnitude cyanoHABs occurring mid-summer to fall. Examination of reservoirs identified extremely high concentration cyanobacteria events (>1,000,000 cells/mL) occurring in 70% of headwater locations while only 30% of near-dam locations exceeded this threshold. Wilcoxon signed-rank tests of cyanoHAB magnitudes using paired-observations (dates with observations in both a reservoir's headwater and near-dam locations) confirmed significantly higher concentrations in headwater versus near-dam locations (p < 0.001).

cyanobacteria↗
NASA NTRS2022

Tropospheric and Stratospheric Ozone Profiles during the 2019 TROpomi vaLIdation eXperiment (TROLIX-19)

A TROPOspheric Monitoring Instrument (TROPOMI) validation campaign was held in the Netherlands based at the CESAR (Cabauw Experimental Site for Atmospheric Research) observatory during September 2019. The TROpomi vaLIdation eXperiment (TROLIX-19) consisted of active and passive remote sensing platforms in conjunction with several balloon-borne and surface chemical (e.g., ozone and nitrogen dioxide) measurements. The goal of this joint NASA-KNMI geophysical validation campaign was to make intensive observations in the TROPOMI domain in order to be able to establish the quality of the L2 satellite data products under realistic conditions, such as non-idealized conditions with varying cloud cover and a range of atmospheric conditions at a rural site. The research presented here focuses on using ozone lidars from NASA's Goddard Space Flight Center to better evaluate the characterization of ozone throughout TROLIX-19. Results of comparisons to the lidar systems with balloon, space-borne and ground-based passive measurements are shown. In addition, results are compared to a global coupled chemistry meteorology model to illustrate the vertical variability and columnar amounts of both tropospheric and stratospheric ozone during the campaign period.

ozone↗
DOE OSTI2016

Cosmic-Ray Moisture Probe on North Slope of Alaska Field Campaign Report

In September of 2014 a wide-area snow monitoring device was installed at the U.S. Department of Energy (DOE)’s Barrow, Alaska Atmospheric Radiation Measurement (ARM) Climate Research Facility site. The device is special in that it uses measurements of cosmic-ray neutrons as a proxy for snow water equivalent (SWE) depth. A unique characteristic of the technology is that it integrates over a wide area (as much as 40 ha), in contrast to conventional ground-based technologies, which essentially give point samples. Conventional point-scale technologies are problematic in the Arctic, both because extreme weather conditions are taxing on equipment, and because point measurements can fail to accurately characterize the average SWE over a larger area, even when excellent precision is obtained. The sensor installed in Barrow is, by far, the northernmost of a constellation of sites that makeup the U.S. COsmic ray Soil Moisture Observing System (COSMOS). The sensor is used for SWE measurements in winter and soil moisture measurements in summer. The ability of this type of sensor to operate in the Arctic had not been verified until now. The cosmic-ray sensor was installed on a tripod located approximately 150 m south of the ARM User Facility (Figure 1), and within boundaries of land managed by the ARM Facility. The sensor consists of both “bare” and “moderated” channels, where the moderated channel is the primary output used to calculate SWE. A QDL2100 data logger with pressure sensor was located inside of the User Facility, and a Campbell CS215 temperature and humidity sensor was attached to a rail on the upper deck of the User Facility, to enable near-real-time absolute humidity corrections to the data. The cosmic-ray sensors are connected to the data logger using an armored Cat5e cable that lies on top of the tundra. Data are retrieved hourly via Iridium satellite link.

"North Slope of Alaska, Barrow, soil moisture, cos↗
DOE OSTI2018

Randomization in Characterizing the Subsurface

Current methods for characterizing Earth’s subsurface, such as standard inverse techniques, are not sufficiently accurate to meet the needs of modern applications in the fields of energy exploration, environmental management, and global security. While increasing the quantity of field measurements and robustness of the applied data-/model-analysis methods can improve accuracy, such approaches can be computationally impractical for large data sets and complex site conditions. Thus, there is a need to develop economically-feasible and robust computational methods while maintaining accuracy. For example, in-field drilling for geothermal operations may yield high failure rates, resulting in unacceptably high costs; errors and/or large uncertainties in the estimated subsurface characteristics are the main impediment to the successful siting of an in-field well. This problem is not uniquely geothermal. Accurate characterization of uncertain subsurface properties is also essential for monitoring storage of carbon dioxide, estimating pathways of subsurface contaminant transport, and supervising ground-based nuclear-explosion tests.

58 GEOSCIENCES↗
DOE OSTI2014

Identification and design of novel polymer-based mechanical transducers: A nano-structural model for thin film indentation

Mechanical characterization is important for understanding small-scale systems and developing devices, particularly at the interface of biology, medicine, and nanotechnology. Yet, monitoring sub-surface forces is challenging with current technologies like atomic force microscopes (AFMs) or optical tweezers due to their probe sizes and sophisticated feedback mechanisms. An alternative transducer design relying on the indentation mechanics of a compressible thin polymer would be an ideal system for more compact and versatile probes, facilitating measurements in situ or in vivo. However, application-specific tuning of a polymer's mechanical properties can be burdensome via experimental optimization. Therefore, efficient transducer design requires a fundamental understanding of how synthetic parameters such as the molecular weight and grafting density influence the bulk material properties that determine the force response. In this work, we apply molecular-level polymer scaling laws to a first order elastic foundation model, relating the conformational state of individual polymer chains to the macroscopic compression of thin film systems. A parameter sweep analysis was conducted to observe predicted model trends under various system conditions and to understand how nano-structural elements influence the material stiffness. We validate the model by comparing predicted force profiles to experimental AFM curves for a real polymer system and show that it has reasonable predictive power for initial estimates of the force response, displaying excellent agreement with experimental force curves. We also present an analysis of the force sensitivity of an example transducer system to demonstrate identification of synthetic protocols based on desired mechanical properties. These results highlight the usefulness of this simple model as an aid for the design of a new class of compact and tunable nanomechanical force transducers.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2010

Dynamics of microbial community composition and function during in-situ bioremediation of a uranium-contaminated aquifer

A pilot-scale system was established to examine the feasibility of in situ U(VI) immobilization at a highly contaminated aquifer (U.S. DOE Integrated Field Research Challenge site, Oak Ridge, TN). Ethanol was injected intermittently as an electron donor to stimulate microbial U(VI) reduction, and U(VI) concentrations fell to below the Environmental Protection Agency drinking water standard (0.03 mg liter{sup -1}). Microbial communities from three monitoring wells were examined during active U(VI) reduction and maintenance phases with GeoChip, a high-density, comprehensive functional gene array. The overall microbial community structure exhibited a considerable shift over the remediation phases examined. GeoChip-based analysis revealed that Fe(III)-reducing bacterial (FeRB), nitrate-reducing bacterial (NRB), and sulfate-reducing bacterial (SRB) functional populations reached their highest levels during the active U(VI) reduction phase (days 137 to 370), in which denitrification and Fe(III) and sulfate reduction occurred sequentially. A gradual decrease in these functional populations occurred when reduction reactions stabilized, suggesting that these functional populations could play an important role in both active U(VI) reduction and maintenance of the stability of reduced U(IV). These results suggest that addition of electron donors stimulated the microbial community to create biogeochemical conditions favorable to U(VI) reduction and prevent the reduced U(IV) from reoxidation and that functional FeRB, SRB, and NRB populations within this system played key roles in this process.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Developing an indicator for the chronic health impact of traffic-related pollutant emissions

The goal of this study is to develop an emission based indicator for the health impact of the air pollution caused by traffic. This indicator must make it possible to compare different situations, for example different Urban Travel Plans, or technical innovations. Our work is based on a literature survey of methods for evaluating health impacts and, more particularly, those which relate to the atmospheric pollution caused by transport. We then define a health impact indicator based on the traffic emissions, named IISCEP for Chronic health impact indicator of pollutant emission. Here health is understood in a restricted meaning, excluding well-being. Only primary pollutants can be considered, as the inputs are emission data and an indicator must be simple. The indicator is calculated as the sum of each pollutant emission multiplied by a dispersion and exposition factor and a substance specific toxicity factor taking account of the severity. Last, two examples are shown using the IISCEP: comparison between petrol and diesel vehicles, and Nantes urban district in 2008 vs 2002. Even if it could still be improved, IISCEP is a straightforward indicator which can be used to gauge the chronic effects of inhaling primary pollutants. It can only be used in comparisons, between different scenarios or different technologies. The quality of the emissions data and the choice of the pollutants that are considered are the two essential factors that determine its validity and reliability. - Highlights: Black-Right-Pointing-Pointer The goal of the study is to develop an emission based indicator for the health impact of the air pollution caused by traffic. Black-Right-Pointing-Pointer It is based on a literature survey of methods for evaluating health impacts related to the atmospheric pollution. Black-Right-Pointing-Pointer We define a composite indicator based on the traffic emissions and on local data as dispersion conditions and population. Black-Right-Pointing-Pointer The indicator is a combination of pollutant emission, dispersion, exposition factor, and substance specific toxicity factor. Black-Right-Pointing-Pointer Applications are global (e.g. comparison of vehicle technologies) or local (e.g. comparison of populations or areas).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Sensor Network Demonstration for In Situ Decommissioning - 13332

Florida International University's (FIU's) Applied Research Center is currently supporting the Department of Energy's (DOE) Environmental Management Office of D and D and Facility Engineering program. FIU is supporting DOE's initiative to improve safety, reduce technical risks, and limit uncertainty within D and D operations by identifying technologies suitable to meet specific facility D and D requirements, assessing the readiness of those technologies for field deployment, and conducting feasibility studies and large scale demonstrations of promising technologies. During FY11, FIU collaborated with Savannah River National Laboratory in the development of an experimental test site for the demonstration of multiple sensor systems for potential use in the in situ decommissioning process. In situ decommissioning is a process in which the above ground portion of a facility is dismantled and removed, and the underground portion is filled with a cementious material such as grout. In such a scenario, the question remains on how to effectively monitor the structural health of the grout (cracking, flexing, and sinking), as well as track possible migration of contaminants within and out of the grouted monolith. The right types of sensors can aid personnel in better understanding the conditions within the entombed structure. Without sensors embedded in and around the monolith, it will be very difficult to estimate structural integrity and contaminant transport. Yet, to fully utilize the appropriate sensors and the provided data, their performance and reliability must be evaluated outside a laboratory setting. To this end, a large scale experimental setup and demonstration was conducted at FIU. In order to evaluate a large suite of sensor systems, FIU personnel designed and purchased a pre-cast concrete open-top cube, which served as a mock-up of an in situ DOE decommissioned facility. The inside of the cube measures 10 ft x 10 ft x 8 ft. In order to ensure that the individual sensors would be immobilized during the grout pouring activities, a set of nine sensor racks were designed. The 270 sensors provided by Idaho National Laboratory (INL), Mississippi State University (MSU), University of Houston (UH), and University of South Carolina (USC) were secured to these racks based on predetermined locations. Once sensor racks were installed inside the test cube, connected and debugged, approximately 32 cubic yards of special grout material was used to entomb the sensors. MSU provided and demonstrated four types of fiber loop ring-down (FLR) sensors for detection of water, temperature, cracks, and movement of fluids. INL provided and demonstrated time differenced 3D electrical resistivity tomography (ERT), advanced tensiometers for moisture content, and thermocouples for temperature measurements. University of Houston provided smart aggregate (SA) sensors, which detect crack severity and water presence. An additional UH sensor system demonstrated was a Fiber Bragg Grating (FBG) fiber optic system measuring strain, presence of water, and temperature. USC provided a system which measured acoustic emissions during cracking, as well as temperature and pH sensors. All systems were connected to a Sensor Remote Access System (SRAS) data networking and collection system designed, developed and provided by FIU. The purpose of SRAS was to collect and allow download of the raw sensor data from all the sensor system, as well as allow upload of the processed data and any analysis reports and graphs. All this information was made available to the research teams via the Deactivation and Decommissioning Knowledge Management and Information Tool (D and D KM-IT). As a current research effort, FIU is performing an energy analysis, and transferring several sensor systems to a Photovoltaic (PV) System to continuously monitor energy consumption parameters and overall power demands. Also, One final component of this research is focusing on developing an integrated data network to capture, log and analyze sensor system data in near real time from a single interface. FIU personnel and DOE Fellows monitored the progress and condition of the sensors for a period of six months. During this time, the sensors recorded data pertaining to strain, compression, temperature, crack detection, moisture presence, fluid mobility, shock resistance, monolith movement, and electrical resistivity. In addition, FIU regularly observed the curing process of the grout and documented the cube condition via the nine racks of sensors. The sensors held up throughout the curing process, withstood the natural elements for six months, and monitored the integrity of the grout. The large scale experiment and demonstration conducted at FIU was the first of its kind to demonstrate the feasibility of state of the art sensors for in situ decommissioning applications. These efforts successfully measured the durability, performance, and precision of the sensors in question as well as monitored and recorded the curing process of the selected grout material under natural environmental conditions. The current energy analysis work is resulting in data on the constraints placed by some of the sensor systems on a power network that requires high reliability and low losses. In addition, a sensor system demonstration has determined that it is feasible to develop an integrated data network where data can be accessed in near real-time from all systems, thereby allowing for larger-scale integrated system testing to be performed. Information collected during the execution of this research project will aid decision makers in the identification of sensors to be used in nuclear facilities selected for in situ decommissioning. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1985

Timber Resources Inventory and Monitoring Joint Research Project

Primary objectives were to develop remote sensing analysis techniques for extracting forest related information from LANDSAT Multispectral Scanner (MMS) and Thematic Mapper data and to determine the extent to which International Paper Company information needs can be addressed with remote sensing information. The company actively manages 8.4 million acres of forest land. Traditionally, their forest inventories, updated on a three year cycle, are conducted through field surveys and aerial photography. The results reside in a digital forest data base containing 240 descriptive parameteres for individual forest stands. The information in the data base is used to develop seasonal and long range management strategies. Forest stand condition assessements (species composition, age, and density stratification) and identification of silvicultural activities (site preparation, planting, thinning, and harvest) are addressed.

Hill, C. L.↗
DOE OSTI2019

HVAC load Disaggregation using Low-resolution Smart Meter Data

Traditional non-intrusive load monitoring (NILM) methods are effective for load disaggregation using high resolution smart meter data collected by power quality meters. However, smart meter data collected and stored by utilities are normally 15-, 30- or 60-minute in granularity, making most NILM methods ineffective. This paper presents a novel sequential energy disaggregation (SED) algorithm for extracting heating, ventilation, and air conditioning (HVAC) energy consumptions from residential and small commercial building loads using 30 min smart meter data. Large, infrequently-used loads are first detected and removed from the total building energy consumption. Then, base energy consumption curves, defined as the energy consumption without heating and cooling loads, are identified using the mild-day method. After that, the heating and cooling loads are extracted using an average value subtracting method. Simulation results with real data show that the proposed SED method is computationally efficient, simple to implement and robust in performance across different types of buildings.

Liang, Ming↗
DOE OSTI2024

Experimental and Modeled Assessment of Interventions to Reduce PM2.5 in a Residence during a Wildfire Event

Increasingly large and frequent wildfires affect air quality even indoors by emitting and dispersing fine/ultrafine particulate matter known to pose health risks to residents. With this health threat, we are working to help the building science community develop simplified tools that may be used to estimate impacts to large numbers of homes based on high-level housing characteristics. In addition to reviewing literature sources, we performed an experiment to evaluate interventions to mitigate degraded indoor air quality. We instrumented one residence for one week during an extreme wildfire event in the Pacific Northwest. Outdoor ambient concentrations of PM2.5 reached historic levels, sustained at over 200 μg/m3 for multiple days. Outdoor and indoor PM2.5 were monitored, and data regarding building characteristics, infiltration, and mechanical system operation were gathered to be consistent with the type of information commonly known for residential energy models. Two conditions were studied: a high-capture minimum efficiency rated value (MERV 13) filter integrated into a central forced air (CFA) system, and a CFA with MERV 13 filtration operating with a portable air cleaner (PAC). With intermittent CFA operation and no PAC, indoor corrected concentrations of PM2.5 reached 280 μg/m3, and indoor/outdoor (I/O) ratios reached a mean of 0.55. The measured I/O ratio was reduced to a mean of 0.22 when both intermittent CFA and the PAC were in operation. Data gathered from the test home were used in a modeling exercise to assess expected I/O ratios from both interventions. The mean modeled I/O ratio for the CFA with an MERV 13 filter was 0.48, and 0.28 when the PAC was added. The model overpredicted the MERV 13 performance and underpredicted the CFA with an MERV 13 filter plus a PAC, though both conditions were predicted within 0.15 standard deviation. The results illustrate the ways that models can be used to estimate indoor PM2.5 concentrations in residences during extreme wildfire smoke events.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
NASA NTRS1986

Concepts for space maintenance of OTV engines

Concepts for space maintainability of OTV engines are examined. The advanced efforts are based on work recently completed for NASA Lewis Research Center Space Propulsion Technology Division. An engine design is developed which is driven by space maintenance requirements and by a failure modes and effects analysis. Modularity within the engine is shown to offer cost benefits and improved space maintenance capabilities. Space-operable disconnects are conceptualized for both engine change-out and for module replacement. Through FME mitigation the modules are conceptualized to contain the most often replaced engine components. A preliminary space maintenance plan is developed around a controls and condition monitoring system using advanced sensors, controls, and conditioning monitoring concepts.

Martinez, A.↗
NASA NTRS2002

Global Precipitation Analyses (3-Hourly to Monthly) Using TRMM, SSM/I and other Satellite Information

Global precipitation analysis covering the last few decades and the impact of the new TRMM precipitation observations are discussed. The 20+ year, monthly, globally complete precipitation analysis of the World Climate Research Program's (WCRP/GEWEX) Global Precipitation Climatology Project (GPCP) is used to explore global and regional variations and trends and is compared to the much shorter TRMM(Tropical Rainfall Measuring Mission) tropical data set. The GPCP data set shows no significant trend in precipitation over the twenty years, unlike the positive trend in global surface temperatures over the past century. Regional trends are also analyzed. A trend pattern that is a combination of both El Nino and La Nina precipitation features is evident in the 20-year data set. This pattern is related to an increase with time in the number of combined months of El Nino and La Nina during the 20 year period. Monthly anomalies of precipitation are related to ENS0 variations with clear signals extending into middle and high latitudes of both hemispheres. The GPCP daily, 1 deg. latitude-longitude analysis, which is available from January 1997 to the present is described and the evolution of precipitation patterns on this time scale related to El Nino and La Nina is discussed. Finally, a TRMM-based 3-hr analysis is described that uses TRMM to calibrate polar-orbit microwave observations from SSM/I and geosynchronous IR observations and merges the various calibrated observations into a final, 3-hr resolution map. This TRMM standard product will be available for the entire TRMM period (January 1998-present). A real-time version of this merged product is being produced and is available at 0.25 deg. latitude-longitude resolution over the latitude range from 5O deg. N-50 deg. S. Examples are shown, including its use in monitoring flood conditions.

Adler, Robert F.↗
NASA NTRS2004

Resource Management in the Microgravity Science Division

In the Microgravity Science Division, the primary responsibilities of the Business Management Office are resource management and data collection. Resource management involves working with a budget to do a number of specific projects, while data collection involves collecting information such as the status of projects and workforce hours. This summer in the Business Management Office I assisted Margie Allen with resource planning and the implementation of specific microgravity projects. One of the main duties of a Project Control Specialists, such as my mentor, is to monitor and analyze project manager s financial plans. Project managers work from the bottom up to determine how much money their project will cost. They then set up a twelve month operating plan which shows when money will be spent. I assisted my mentor in checking for variances in her data against those of the project managers. In order to successfully check for those variances, we had to understand: where the project is including plans vs. actual performance, why it is in its present condition, and what the future impact will be based on known budgetary parameters. Our objective was to make sure that the plan, or estimated resources input, are a valid reflection of the actual cost. To help with my understanding of the process, over the course of my tenure I had to obtain skills in Microsoft Excel and Microsoft Access.

Casselle, Justine↗
NASA NTRS2011

A Systematic Approach for Engagement Analysis Under Multitasking Environments

An overload condition can lead to high stress for an operator and further cause substantial drops in performance. On the other extreme, in automated systems, an operator may become underloaded; in which case, it is difficult for the operator to maintain sustained attention. When an unexpected event occurs, either internal or external to the automated system, a disengaged operation may neglect, misunderstand, or respond slowly/inappropriately to the situation. In this paper, we discuss a systematic approach monitor for extremes of cognitive workload and engagement in multitasking environments. Inferences of cognitive workload ar engagement are based on subjective evaluations, objective performance measures, physiological signals, and task analysis results. The systematic approach developed In this paper aggregates these types of information collected under the multitasking environment and can provide a real-time assessment or engagement.

Zhang, Guangfan↗
NASA NTRS2021

Impact of Random and Periodic Surface Roughness on P- and L-band Radiometry

L-band passive microwave remote sensing is currently considered a robust technique for global monitoring of soil moisture. However, soil roughness complicates the relationship between brightness temperature and soil moisture, with current soil moisture retrieval algorithms typically assuming a constant roughness parameter globally, leading to a potential degradation in retrieval accuracy. This current investigation established a tower-based experiment site in Victoria, Australia. P-band (~40-cm wavelength/0.75 GHz) was compared with L-band (~21-cm wavelength/1.41 GHz) over random and periodic soil surfaces to determine if there is an improvement in brightness temperature simulation and soil moisture retrieval accuracy for bare soil conditions, due to reduced roughness impact when using a longer wavelength. The results showed that P-band was less impacted by random and periodic roughness than L-band, evidenced by more comparable statistics across different roughness conditions. The roughness effect from smooth surfaces (e.g., 0.8-cm root-mean-square height and 11.1-cm correlation length) could be potentially ignored at both P- and L-band with satisfactory simulation and retrieval performance. However, for rougher soil (e.g., 1.6-cm root-mean-square height and 6.8-cm correlation length), the roughness impact needed to be accounted for at both P- and L-band, with P-band observations showing less impact than L-band. Moreover, a sinusoidal soil surface with 10-cm amplitude and 80-cm period substantially impacted the brightness temperature simulation and soil moisture retrieval at both P- and L-band, which could not be fully accounted for using the SMOS and SMAP default roughness parameters. However, when retrieving roughness parameters along with soil moisture, the ubRMSE at P-band over periodic soil was improved to a similar level (0.01-0.02 m3/m3) as that of smooth flat soil (0.01 m3/m3), while L-band showed higher ubRMSE over the periodic soil (0.03-0.04 m3/m3) than over smooth flat soil (0.01 m3/m3). Accordingly, periodic roughness effects were reduced by using observations at P-band.

Soil roughness↗
NASA NTRS2022

Global Fine Scale Changes in Ambient NO2 During COVID-19 Lockdowns

Nitrogen dioxide (NO2) is an important contributor to air pollution and can adversely affect human health(1–9) . A decrease in NO2 concentrations has been reported as a result of lockdown measures to reduce the spread of COVID-19(10–20). Questions remain, however, regarding the relationship of satellite-derived atmospheric column NO2 data with health-relevant ambient ground-level concentrations, and the representativeness of limited ground-based monitoring data for global assessment. Here we derive spatially resolved, global ground-level NO2 concentrations from NO2 column densities observed by the TROPOMI satellite instrument at sufficiently fine resolution (approximately one kilometre) to allow assessment of individual cities during COVID-19 lockdowns in 2020 compared to 2019. We apply these estimates to quantify NO2 changes in more than 200 cities, including 65 cities without available ground monitoring, largely in lower-income regions. Mean country-level population-weighted NO2 concentrations are 29% ± 3% lower in countries with strict lockdown conditions than in those without. Relative to long-term trends, NO2 decreases during COVID-19 lockdowns exceed recent Ozone Monitoring Instrument (OMI)-derived year-to-year decreases from emission controls, comparable to 15 ± 4 years of reductions globally. Our case studies indicate that the sensitivity of NO2 to lockdowns varies by country and emissions sector, demonstrating the critical need for spatially resolved observational information provided by these satellite-derived surface concentration estimates.

Ground level NO2↗