Performance assessment of low-cost environmental monitors and single sensors under variable indoor air quality and thermal conditions
Not Available
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
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Exploring Environmental and Aerosol Impacts on Maritime Tropical Convection using Airborne Radiometer, Radar, Lidar, and Dropsondes
The field deployment phase of NASA’s Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP2Ex) took place around the Philippines during August–October 2019, with the primary goal of jointly investigating aerosols and tropical meteorology at the micro-β to meso-β scales. A suite of instruments was deployed on NASA’s P-3B Orion aircraft to accomplish this mission, including: the Advanced Microwave Precipitation Radiometer (AMPR), Airborne Precipitation and cloud Radar 3rd Generation (APR-3), High Spectral Resolution Lidar 2 (HSRL2), and Advanced Vertical Atmospheric Profiling System (AVAPS) dropsondes. To examine potential aerosol influences on maritime tropical convection, P-3 flight segments throughout CAMP2Ex were binned into similar environmental groups using “low,” “medium,” and “high” values of nine AVAPS-derived parameters with known physical connections to convective frequency and/or intensity. Aerosol concentrations in each flight segment were evaluated using three HSRL2 variables at 355 and 532 nm: aerosol backscatter, aerosol extinction, and aerosol optical thickness. A set of radiometer- and radar-derived variables directly related to convective frequency and/or intensity was used to characterize convection, which included: AMPR-derived integrated cloud liquid water; polarization-corrected temperatures at 10.7, 19.35, 37.1, and 85.5 GHz; peak equivalent radar reflectivity factor (ZH); peak height of 30-dBZ ZH; and the number of radar data columns with composite ZH > 30 dBZ. The ZH analyses were performed using both Ku- and Ka-band APR-3 data. For each flight segment, correlation coefficients were calculated between each convective parameter and aerosol concentrations within the “low,” “medium,” and “high” groups for each environmental variable. The environmental stratification thresholds were then varied in a series of sensitivity tests. Several noteworthy correlations were observed between the convective and aerosol parameters within the environmental groups, especially when stratifying the environments based on their 850–500-hPa temperature lapse rate, 700–500-hPa temperature lapse rate, and K-Index. The convective parameters were often correlated most strongly with 355-nm extinction, 532-nm extinction, and 532-nm backscatter, while the presence of precipitation-sized liquid and ice hydrometeors contributed to some unexpected negative correlations. In general, as environmental conditions became more favorable for convection, a stronger correlation was observed between the convective parameters and aerosol concentrations. However, a “Goldilocks” zone of medium aerosol concentration was correlated most strongly with the convective parameters in many cases. These results stress the importance of considering environmental and aerosol conditions together when evaluating their impacts on convection. This presentation will provide a detailed discussion of these results and their implications, a summary of the limitations associated with such an analysis, and suggestions for future work.
Corey G. Amiot↗
Interannual variability of ecosystem iso/anisohydry is regulated by environmental dryness
Plants are characterized by the iso/anisohydry continuum depending on how they regulate leaf water potential (?L). However, how iso/anisohydry changes over time in response to year-to-year variations in environmental dryness and how such responses vary across different regions remains poorly characterized. We investigated how dryness, represented by aridity index, affects the interannual variability of ecosystem iso/anisohydry at the regional scale, estimated using satellite microwave vegetation optical depth (VOD) observations. This ecosystem-level analysis was further complemented with published field observations of ?L at the species level. We found different behaviors in the directionality and sensitivity of isohydricity (s) with respect to the interannual variation of dryness in different ecosystems. These behaviors can largely be differentiated by the average dryness of the ecosystem itself: in mesic ecosystems, s decreases in drier years, albeit at a higher rate; in xeric ecosystems, s increases in drier years, albeit at a lower rate. These results were supported by the species-level synthesis. Our study suggests that how plants adjust their water use across years – as revealed by their interannual variability in isohydricity – depends on the dryness of plants’ living environment. This finding advances our understanding of plant responses to drought at regional scales.
Wu, Genghong↗
Vermont Wildland Fires: Investigating the Role of Antecedent Conditions and Recent Environmental Trends in Exacerbating Fire Risk and Potential in Vermont
Under a changing climate, increases in dry conditions and extreme heat events are projected to exacerbate wildfire risk in the northeastern U.S. In recent years, Vermont has observed higher annual temperatures, more frequent heatwaves, increased annual precipitation, extreme flood events, and decreased snowfall. The mechanisms through which environmental factors contribute to increased fire risk in humid environments, such as Vermont, are poorly understood. The team partnered with the National Weather Service, the Vermont Division of Forests, and the University of Vermont to investigate phenological trends and antecedent conditions influencing wildland fire risk. For the phenological analysis, from 2001 to 2023, vegetation data, phenological dates, and snow water equivalent (SWE) values were accessed from Landsat 5Thematic Mapper (TM), Landsat 7Enhanced Thematic Mapper Plus (ETM+), Landsat 8Operational Land Imager (OLI), Landsat 9OLI-2, the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Snow Data Assimilation System (SNODAS), respectively. For the antecedent condition analysis, from 2008 to 2023, soil moisture, Environmental Stress Index, wind speed, minimum relative humidity, and daily precipitation data were obtained from the Global Land Data Assimilation System (GLDAS), SERVIR, gridMET Wind, gridMET Humidity, and NClimGrid, respectively. The study found that green-up dates over the study period remain relatively stable, while snowmelt dates appear increasingly variable. Minimum relative humidity was the most significant environmental variable correlated with wildfire risk in Vermont. Results from this study will inform the National Weather Service's preparation of fire forecasts before prescribed burns and support community outreach by the Vermont Agency of Natural Resources.
Wildland Fire↗
Malaria Modeling using Remote Sensing and GIS Technologies
Malaria has been with the human race since the ancient time. In spite of the advances of biomedical research and the completion of genomic mapping of Plasmodium falciparum, the exact mechanisms of how the various strains of parasites evade the human immune system and how they have adapted and become resistant to multiple drugs remain elusive. Perhaps because of these reasons, effective vaccines against malaria are still not available. Worldwide, approximately one to three millions deaths are attributed to malaria annually. With the increased availability of remotely sensed data, researchers in medical entomology, epidemiology and ecology have started to associate environmental and ecological variables with malaria transmission. In several studies, it has been shown that transmission correlates well with certain environmental and ecological parameters, and that remote sensing can be used to measure these determinants. In a NASA project, we have taken a holistic approach to examine how remote sensing and GIs can contribute to vector and malaria controls. To gain a better understanding of the interactions among the possible promoting factors, we have been developing a habitat model, a transmission model, and a risk prediction model, all using remote sensing data as input. Our objectives are: 1) To identify the potential breeding sites of major vector species and the locations for larvicide and insecticide applications in order to reduce costs, lessen the chance of developing pesticide resistance, and minimize the damage to the environment; 2) To develop a malaria transmission model characterizing the interactions among hosts, vectors, parasites, landcover and environment in order to identify the key factors that sustain or intensify malaria transmission, and 3) To develop a risk model to predict the occurrence of malaria and its transmission intensity using epidemiological data and satellite-derived or ground-measured environmental and meteorological data.
Kiang, Richard↗
Regional Feedstock Partnership Biomass Quality Assessment Final Report
The United States (U.S.) Department of Energy (DOE) developed the Billion-Ton Vision to enable production of one-billion tons of sustainable, reliable biomass for the bioenergy industry by 2030 (Perlack et al., 2005). The Sun Grant Regional Feedstock Partnership (RFP) was organized to fill information gaps and validate biomass yield assumptions related to the Billion-Ton Study (Owens, 2018; Owens, Karlen, and Lacey, 2016). Along with the more than 130 scientific publications generated from these studies, yield and sustainability data from the RFP field trials not only validated the Billion-Ton estimates, but were critical in developing both the U.S. Billion-Ton Update report in 2011 and the 2016 Billion-Ton Report (DOE, 2011; 2016). The intention of this biomass quality assessment report is to build on these initial successes from the RFP field trials by focusing on variability in biomass quality data necessary to evaluate conversion performance. This report contains a summary of chemical quality results from samples collected as part of the RFP field trials. This report focuses on assessment of the impact of experimental agronomic designs on biomass properties followed by analyses of the impact of environmental and production variables on biomass properties. Datasets include species and other genetic variables, fertilizer treatments, harvest information, and yield, as well as other publicly available data such as precipitation, temperature, soil properties, and drought. The key outcomes from this chemical quality focused assessment have included: • Complete evaluation of the impacts of agronomic designs, genetics, and environmental conditions on chemical properties for Miscanthus, switchgrass, sorghum, energycane, mixed perennial grasses, and shrub willow short-rotation feedstocks • Over 30 peer review publications and technical reports focused on variability in quality data • Development of spatial and temporal environmental quality prediction maps for Miscanthus and switchgrass feedstocks allowing for comprehensive evaluation of variability in feedstock chemical quality across U.S. regions and over multiple harvest years
09 BIOMASS FUELS↗
Spatial variability in Arctic–boreal fire regimes influenced by environmental and human factors
Abstract Wildfire activity in Arctic and boreal regions is rapidly increasing, with severe consequences for climate and human health. Regional long-term variations in fire frequency and intensity characterize fire regimes. The spatial variability in Arctic–boreal fire regimes and their environmental and anthropogenic drivers, however, remain poorly understood. Here we present a fire tracking system to map the sub-daily evolution of all circumpolar Arctic–boreal fires between 2012 and 2023 using 375 m Visible Infrared Imaging Radiometer Suite active fire detections and the resulting dataset of the ignition time, location, size, duration, spread and intensity of individual fires. We use this dataset to classify the Arctic–boreal biomes into seven distinct ‘pyroregions’ with unique climatic and geographic environments. We find that these pyroregions exhibit varying responses to environmental drivers, with boreal North America, eastern Siberia and northern tundra regions showing the highest sensitivity to climate and lightning density. In addition, anthropogenic factors play an important role in influencing fire number and size, interacting with other factors. Understanding the spatial variability of fire regimes and its interconnected drivers in the Arctic–boreal domain is important for improving future predictions of fire activity and identifying areas at risk for extreme events.
Geology↗
Environmental drivers of tropospheric bromine and mercury variability in coastal East Antarctica
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54 ENVIRONMENTAL SCIENCES↗
A machine learning pipeline for identifying infiltration managed aquifer recharge locations from satellite imagery in the San Joaquin Valley, California
This study focuses on an agricultural region in California’s Central Valley, USA, where Managed Aquifer Recharge (MAR) is widely implemented to mitigate groundwater depletion under increasing water demand and climate variability. A deep learning and machine learning framework was developed to identify infiltration-MAR locations using satellite imagery and environmental data. The framework integrates surface water detection from Sentinel-2 imagery, geospatial delineation of water bodies, spatiotemporal tracking of water body dynamics, and supervised classification using meteorological, environmental, and topographic variables. The framework was applied to a 2379 km² study area southwest of Fresno, where 765 water bodies were detected, including 139 identified MAR sites based on publicly available datasets and expert knowledge. The classification model achieved an accuracy of 0.94 and an F1 score of 0.85. Feature importance analysis indicates that cropland, normalized difference vegetation index (NDVI), and evaporation are among the most influential predictors for infiltration-MAR. Notably, the framework suggests that engineered water management in infiltration-MAR systems can disrupt or even reverse the expected positive correlation between surface water extent and precipitation. These findings provide physically interpretable insights into the characteristics of existing infiltration-MAR facilities and demonstrate the potential of the proposed framework as a reproducible, interpretable, and potentially transferable tool for data-driven infiltration-MAR identification and inventory development under growing climatic and hydrological uncertainty.
Classification↗
Variable-Speed Induction Motor Drives for Aircraft Environmental Control Compressors
New, more-efficient designs for aircraft jet engines are not capable of supplying the large quantities of bleed air necessary to provide pressurization and air conditioning for the environmental control systems (ECS) of the next generation of large passenger aircraft. System analysis and engineering have determined that electrically-driven ECS can help to maintain the improved fuel efficiencies; and electronic controllers and induction motors are now being developed in a NASA/NPD SBIR Program to drive both types of ECS compressors. Previous variable-speed induction motor/controller system developments and publications have primarily focused on field-oriented control, with large transient reserve power, for maximum acceleration and optimum response in actuator and robotics systems. The application area addressed herein is characterized by slowly-changing inputs and outputs, small reserve power capability for acceleration, and optimization for maximum efficiency. This paper therefore focuses on the differences between this case and the optimum response case, and shows the development of this new motor/controller approach. It starts with the creation of a new set of controller requirements. In response to those requirements, new control algorithms are being developed and implemented in an embedded computer, which is integrated into the motor controller closed loop. Buffered logic outputs are used to drive the power switches in a resonant-technology, power processor/motor-controller, at switching/resonant frequencies high enough to support efficient high-frequency induction motor operation at speeds up to 50,000-RPA
Mildice, J. W.↗
Toward Malaria Risk Prediction in Afghanistan Using Remote Sensing
Malaria causes more than one million deaths every year worldwide, with most of the mortality in Sub-Saharan Africa. It is also a significant public health concern in Afghanistan, with approximately 60% of the population, or nearly 14 million people, living in a malaria-endemic area. Malaria transmission has been shown to be dependent on a number of environmental and meteorological variables. For countries in the tropics and the subtropics, rainfall is normally the most important variable, except for regions with high altitude where temperature may also be important. Afghanistan s diverse landscape contributes to the heterogeneous malaria distribution. Understanding the environmental effects on malaria transmission is essential to the effective control of malaria in Afghanistan. Provincial malaria data gathered by Health Posts in 23 provinces during 2004-2007 are used in this study. Remotely sensed geophysical parameters, including precipitation from TRMM, and surface temperature and vegetation index from MODIS are used to derive the empirical relationship between malaria cases and these geophysical parameters. Both neural network methods and regression analyses are used to examine the environmental dependency of malaria transmission. And the trained models are used for predicting future transmission. While neural network methods are intrinsically more adaptive for nonlinear relationship, the regression approach lends itself in providing statistical significance measures. Our results indicate that NDVI is the strongest predictor. This reflects the role of irrigation, instead of precipitation, in Afghanistan for agricultural production. The second strongest prediction is surface temperature. Precipitation is not shown as a significant predictor, contrary to other malarious countries in the tropics or subtropics. With the regression approach, the malaria time series are modelled well, with average R2 of 0.845. For cumulative 6-month prediction of malaria cases, the average provincial accuracy reaches 91%. The developed predictive and early warning capabilities support the Third Strategic Approach of the WHO EMRO Malaria Control and Elimination Plan.
Safi, N.↗
Variable Pressure - Scanning Electron Microscopy (VP-SEM)
Variable Pressure (or Environmental) Scanning Electron Microscopy (VP-SEM) combined with Energy Dispersive X-ray Spectroscopy (EDS) is one of the most powerful methods for characterizing the sub-micron topography and chemical composition of uncoated samples. Terrestrially, VP-SEM is extensively used to non-destructively study geologic and manufactured materials with high spatial resolution (tens of nanometers) and large depth-of-field. An SEM offers a geologist a first survey of microscopic mineral phases via secondary electron imaging (SEI), which provides a topographic look at a sample, as well as backscattered electron (BEI) imaging, which contrasts the phases present based on their geochemistry (atomic number). A VP-SEM utilizes a gas in the sample chamber as a charge dissipation and signal amplification method, allowing analysis of a sample without preparation in the form of a conductive coating. A miniaturized VP-SEM operating in-situ on a lander or rover would be able to use the CO2-rich Martian atmosphere (e.g., Nier et al., 1976; Williams 2016) as an imaging medium for this purpose. Adaptation of a VP-SEM for in-situ Mars surface studies will provide a new imaging capability (via SEI) that is at least an order of magnitude higher resolution than the Mars Hand Lens Imager (MAHLI) on the Mars Science Laboratory (Williams et al., 2015), and equal to or better than the achieved resolution of the Atomic Force Microscope on the Phoenix Mars lander (Pike et al., 2011). In addition, the MVP-SEM is capable of BSI and simultaneous chemical analysis of the imaged region. In this sense, the MVP-SEM can be regarded as an instrument suite that will provide a new set of information not achievable by any other instrument. The Miniaturized Variable Pressure Scanning Electron Microscope (MVP-SEM) was designed, built, and benchtop tested by a team at NASA’s Marshall Space Flight Center and Jet Propulsion Laboratory (JPL), Jacobs Space Exploration Group, Applied Physics Technologies, Inc. (AP-Tech), and Creare LLC, working with a team of technical and science collaborators. Benchtop testing was successful, proving concept feasibility. To date, the MVP-SEM has achieved an imaging resolution of <100 nm in the lab, and with continued optimization, even better performance (~50 nm resolution) is possible. Use in-situ on the lunar or other planetary surfaces would require some redesign to optimize instrument performance, but such an instrument would be equally useful.
Variable Pressure Scanning Electron Microscopy↗
Miniature Variable Pressure - Scanning Electron Microscopy (MVP-SEM)
Variable Pressure (or Environmental) Scanning Electron Microscopy (VP-SEM) combined with Energy Dispersive X-ray Spectroscopy (EDS) is one of the most powerful methods for characterizing the sub-micron topography and chemical composition of uncoated samples. Terrestrially, VP-SEM is extensively used to non-destructively study geologic and manufactured materials with high spatial resolution (tens of nanometers) and large depth-of-field. An SEM offers a geologist a first survey of microscopic mineral phases via secondary electron imaging (SEI), which provides a topographic look at a sample, as well as backscattered electron (BEI) imaging, which contrasts the phases present based on their geochemistry (atomic number). A VP-SEM utilizes a gas in the sample chamber as a charge dissipation and signal amplification method, allowing analysis of a sample without preparation in the form of a conductive coating. A miniaturized VP-SEM operating in-situ on a lander or rover would be able to use the CO2-rich Martian atmosphere (e.g., Nier et al., 1976; Williams 2016) as an imaging medium for this purpose. Adaptation of a VP-SEM for in-situ Mars surface studies will provide a new imaging capability (via SEI) that is at least an order of magnitude higher resolution than the Mars Hand Lens Imager (MAHLI) on the Mars Science Laboratory (Williams et al., 2015), and equal to or better than the achieved resolution of the Atomic Force Microscope on the Phoenix Mars lander (Pike et al., 2011). In addition, the MVP-SEM is capable of BSI and simultaneous chemical analysis of the imaged region. In this sense, the MVP-SEM can be regarded as an instrument suite that will provide a new set of information not achievable by any other instrument. The Miniaturized Variable Pressure Scanning Electron Microscope (MVP-SEM) was designed, built, and benchtop tested by a team at NASA’s Marshall Space Flight Center and Jet Propulsion Laboratory (JPL), Jacobs Space Exploration Group, Applied Physics Technologies, Inc. (AP-Tech), and Creare LLC, working with a team of technical and science collaborators. Benchtop testing was successful, proving concept feasibility. To date, the MVP-SEM has achieved an imaging resolution of <100 nm in the lab, and with continued optimization, even better performance (~50 nm resolution) is possible. Use in-situ on the lunar or other planetary surfaces would require some redesign to optimize instrument performance, but such an instrument would be equally useful.
Variable Pressure Scanning Electron Microscopy↗
Environmental drivers of tropospheric bromine and mercury variability in coastal East Antarctica
Not Available
Page, Neil C. (ORCID:0009000333567046)↗
To what extent can decommissioning options for marine artificial structures move us toward environmental targets?
Switching from fossil fuels to renewable energy is key to international energy transition efforts and the move toward net zero. For many nations, this requires decommissioning of hundreds of oil and gas infrastructure in the marine environment. Current international, regional and national legislation largely dictates that structures must be completely removed at end-of-life although, increasingly, alternative decommissioning options are being promoted and implemented. Yet, a paucity of real-world case studies describing the impacts of decommissioning on the environment make decision-making with respect to which option(s) might be optimal for meeting international and regional strategic environmental targets challenging. To address this gap, we draw together international expertise and judgment from marine environmental scientists on marine artificial structures as an alternative source of evidence that explores how different decommissioning options might ameliorate pressures that drive environmental status toward (or away) from environmental objectives. Synthesis reveals that for 37 United Nations and Oslo-Paris Commissions (OSPAR) global and regional environmental targets, experts consider repurposing or abandoning individual structures, or abandoning multiple structures across a region, as the options that would most strongly contribute toward targets. This collective view suggests complete removal may not be best for the environment or society. However, different decommissioning options act in different ways and make variable contributions toward environmental targets, such that policy makers and managers would likely need to prioritise some targets over others considering political, social, economic, and ecological contexts. Current policy may not result in optimal outcomes for the environment or society.
54 ENVIRONMENTAL SCIENCES↗
Using AI to predict calibration constants for the central drift chamber in GlueX at Jefferson Lab
The AI for Experimental Controls project team at Jefferson Lab has developed an AI system to control and calibrate a large drift chamber system in near-real time. The AI system will monitor environmental and experimental variables to recommend voltage settings that maintain consistent dE/dx gain and optimal resolution throughout the experiment. At present, calibrations are performed after data have been recorded and require a considerable amount of time and attention from experts. The calibrations currently require multiple iterations and depend on accurate tracking information. Our approach uses environmental data, such as atmospheric pressure and gas temperature, and beam conditions, such as the flux of incident particles, as inputs to a Gaussian Process Regression (GPR) model. For the data taken during the GlueX 2020 run period, the GPR is able to predict the existing gain correction factors to within 3.5%. This talk will briefly describe the development, testing, and future plans for this system at Jefferson Lab.
Jeske, Torri↗
Environmental criteria for human comfort. A study of the related literature
The data presented has for the most part been extracted from existing in-house and memoranda reports. The variables considered are motion, noise, temperature and pressure. The report is broken down into chapters for each of the environmental variables and criteria proposed based on the existing literature.
Jacobson, I. D.↗
Transient Liquefaction on the Lunar or Martian Surface Operational Demonstration
As developments of local production of cryogenic fluids on the Lunar or Martian Surface progress, it is important to understand transient system responses to help with the balancing of process plant power and understanding system level operations. During the Cryogenic Fluid In-situ Liquefaction for Landers (CryoFILL) testing, a series of transient oxygen liquefaction tests were completed. These tests included varying liquefaction flow rate, environmental temperature, tank fill level, and effective cryocooler lift while allowing the tank pressure to respond to the input controls. An additional transient test was run at the 90% fill level to determine the impact of injecting the gaseous oxygen at the bottom of the tank, allowing the vapor to bubble up through the liquid. Tests were run in a cyclical nature varying one variable at a time. The control variable was set in a manner to increase tank pressure for a period of time and then subsequently changed in a manner to decrease the tank pressure back to its original value with multiple cycles run for all tests. Tank pressure and system temperature responses were tracked as a function of time with an emphasis on repeatability. Results indicate that of the four variables tested, the environmental temperature is the least important. As expected, the bubbling of the liquefaction gas significantly decreased the pressurization and depressurization rates in the tank at the 90% full level.
Liquefaction↗