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At least 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

Mesosphere and Lower Thermosphere Temperatures Simulated by WACCM‐X With NAVGEM‐HA Meteorological Analyses and Compared to SABER Observations

Realistic modeling of the dynamics and variability in the upper mesosphere and lower thermosphere (UMLT) is critical to understand the coupling between different layers of the whole atmosphere system. Here we present simulations of the UMLT temperatures at ∼100 km altitude for one year during 2014 by the Whole Atmosphere Community Climate Model with thermosphere-ionosphere extension (WACCM-X) constrained below ∼90 km using meteorological analysis products of the high-altitude version of Navy Global Environmental Model (NAVGEM-HA). The model results are sampled at the same times and latitudes and longitudes as the satellite observations from Thermosphere Ionosphere and Mesosphere Electric Dynamics/Sounding of the Atmosphere using Broadband Emission Radiometry (TIMED/SABER). Comparisons show that the observed and modeled daily zonal mean temperatures are correlated (r ∼0.5–0.7) at most latitudes between ±50°. Both the observations and simulations show an annual variation at mid-latitudes in two hemispheres with the temperature maximum in summer and the minimum in winter, and at lower latitudes the semiannual variation becomes stronger having the temperature maximums at equinoxes and the minimums during solstices. However, the temperatures observed are on average ∼5–10 K (3%–5%) smaller than the model and the observations show a larger variability. Moreover, migrating tidal amplitudes are mostly overestimated by the model. Though differences are noticed, the WACCM-X simulations with NAVGEM-HA meteorological analyses are overall consistent with the SABER observations. These results support that whole atmosphere models informed by high altitude observations would help to simulate the UMLT variability and the atmosphere and ionosphere coupling.

Guiping Liu↗
DOE OSTI2023

Structuring Nutrient Yields throughout Mississippi/Atchafalaya River Basin Using Machine Learning Approaches

To minimize the eutrophication pressure along the Gulf of Mexico or reduce the size of the hypoxic zone in the Gulf of Mexico, it is important to understand the underlying temporal and spatial variations and correlations in excess nutrient loads, which are strongly associated with the formation of hypoxia. This study’s objective was to reveal and visualize structures in high-dimensional datasets of nutrient yield distributions throughout the Mississippi/Atchafalaya River Basin (MARB). For this purpose, the annual mean nutrient concentrations were collected from thirty-three US Geological Survey (USGS) water stations scattered in the upper and lower MARB from 1996 to 2020. Eight surface water quality indicators were selected to make comparisons among water stations along the MARB over the past two decades. Principal component analysis (PCA) was used to comprehensively evaluate the nutrient yields across thirty-three USGS monitoring stations and identify the major contributing nutrient loads. The results showed that all samples could be analyzed using two main components, which accounted for 81.6% of the total variance. The PCA results showed that yields of orthophosphate (OP), silica (SI), nitrate–nitrites (NO 3 -NO 2 ), and total suspended sediment (TSS) are major contributors to nutrient yields. It also showed that land-planted crops, density of population, domestic and industrial discharges, and precipitation are fundamental causes of excess nutrient loads in MARB. These factors are of great significance for the excess nutrient load management and pollution control of the Mississippi River. It was found that the average nutrient yields were stable within the sub-MARB area, but the large nitrogen yields in the upper MARB and the large phosphorus yields in the lower MARB were of great concern. t-distributed stochastic neighbor embedding (t-SNE) revealed interesting nonlinear and local structures in nutrient yield distributions. Clustering analysis (CA) showed the detailed development of similarities in the nutrient yield distribution. Moreover, PCA, t-SNE, and CA showed consistent clustering results. This study demonstrated that the integration of dimension reduction techniques, PCA, and t-SNE with CA techniques in machine learning are effective tools for the visualization of the structures of the correlations in high-dimensional datasets of nutrient yields and provide a comprehensive understanding of the correlations in the distributions of nutrient loads across the MARB.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Design and optimization of a fused-silica microfluidic device for separation of trivalent lanthanides by isotachophoresis

Abstract Elemental analysis of rare earths is essential in a variety of fields including environmental monitoring and nuclear safeguards; however, current techniques are often labor intensive, time consuming and/or costly to perform. The difficulty arises in preparing samples, which requires separating the very chemically and physically similar lanthanides. However, by transitioning these separations to the microscale, the speed, cost, and simplicity of sample preparation can be drastically reduced. Here, all fourteen non radioactive lanthanides (lanthanum through lutetium minus promethium) are separated by ITP in a serpentine fused silica microchannel in < 10 minutes with limits of detection on the order of picomoles. Electrophoretic electrodes are embedded in the microchip reservoirs so that voltage can be quickly applied and switched during operation. The limits of detection are quantified using a commercial C4D to calculate ITP zone lengths in combination with ITP theory. Optimization of experimental procedures and reproducibility based on statistical analysis of subsequent experimental results are addressed.

Bottenus, Daniel R.↗
DOE OSTI2023

WaterTAP Technical Brief: Ion Exchange Model Demonstration and Optimization

Ion exchange is an important water treatment process for removal of targeted contaminants, including those associated with hardness. In this report, we introduce the ion exchange model developed for WaterTAP and present some example analysis of Ca 2+ removal for 0.1 MGD and 10 MGD systems. The model is a single-component, steady-state implementation that enables process optimization based on the influent ion concentration, resin capacity, and resin selectivity. Based on a survey of costing references for ion exchange, the WaterTAP ion exchange model returns reasonable estimates for the levelized cost of water (LCOW) of an ion exchange process, and performs as expected when critical design parameters, such as the resin capacity and selectivity, are varied.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Comparative Life Cycle Assessment of Bacterial and Thermochemical Retting of Hemp

The processes of hemp bast fiber retting, forming, and drying offer the opportunity for value-added products such as natural fiber-reinforced composites. A new process for the retting of raw bast fibers through enzyme-triggered self-cultured bacterial retting was developed in the lab-scale setup. This study focused on comparing the energy consumption and environmental impacts of this bacterial retting process with the thermochemical retting process currently widely used to obtain lignocellulosic fibers for composites. The gate-to-gate life cycle assessment (LCA) models of the two retting processes were constructed to run a comparison analysis using the TRACI (the tool for the reduction and assessment of chemical and other environmental impacts) method for environmental impacts and the cumulative energy demand (CED) method for energy consumptions. This work has demonstrated the advantages of the bacterial retting method from an environmental standpoint. The result of our research shows about a 24% gate-to-gate reduction in CED for bacterial retting and 20–25% lower environmental impacts relating to global warming, smog formation, acidification, carcinogenics, non-carcinogenics, respiratory effects, ecotoxicity, and fossil fuel depletion when compared to that of thermochemical retting.

Chemistry↗
DOE OSTI2024

ToF-SIMS evaluation of PEG-related mass peaks and applications in PEG detection in cosmetic products

Polyethylene glycols (PEGs) are used in industrial, medical, health care, and personal care applications. The cycling and disposal of synthetic polymers like PEGs pose significant environmental concerns. Detecting and monitoring PEGs in the real world calls for immediate attention. This study unveils the efficacy of time-of-flight secondary ion mass spectrometry (ToF-SIMS) as a reliable approach for precise analysis and identification of reference PEGs and PEGs used in cosmetic products. By comparing SIMS spectra, we show remarkable sensitivity in pinpointing distinctive ion peaks inherent to various PEG compounds. Moreover, the employment of principal component analysis effectively discriminates compositions among different samples. Notably, the application of SIMS two-dimensional image analysis visually portrays the spatial distribution of various PEGs as reference materials. The same is observed in authentic cosmetic products. The application of ToF-SIMS underscores its potential in distinguishing PEGs within intricate environmental context. ToF-SIMS provides an effective solution to studying emerging environmental challenges, offering straightforward sample preparation and superior detection of synthetic organics in mass spectral analysis. These features show that SIMS can serve as a promising alternative for evaluation and assessment of PEGs in terms of the source, emission, and transport of anthropogenic organics.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Interpreting T-History Data on Supercooling and Phase Change Enthalpy of a Salt-Hydrogel Complex for Building Thermal Management

Phase change materials (PCMs) are promising materials for storing and discharging latent heat in buildings to regulate the thermal environment. Measurement of salt hydrate PCM thermal performance is often challenging because of supercooling and phase segregation. Though differential scanning calorimetry (DSC) has been widely used to measure thermal properties of various phase change materials, DSC uses milligrams of sample and is unrealistic for predicting large-scale materials performance. The T-history method [1], in contrast, handles higher volumes but the analysis typically requires a lumped capacitance assumption. Here, we report and analyze T-History data on a novel salt-hydrogel complex with high viscosity, that renders low Biot number sample preparation extremely challenging. We re-examine the standard T-history method and compared against DSC data in this complex material. We report details of an experimental setup, built with necessary additions to a controlled environmental chamber. We carefully examine the validity of the lumped capacitance assumption and suggest a modified analysis using a computational approach for reliable data. Experimental parameters such as ramp rate and temperature range of the environmental chamber are considered via computational modeling to understand the effect of ramp rate on supercooling [2]. Finally, we report thermal cycling experiments on the salt-hydrogel complex. Our modified approach to measuring supercooling and enthalpy of fusion at large scales is important in better understanding the performance of phase-change materials at scale for building thermal storage. References: [1] Marin, Jose M, Belen Zalba, Luisa F Cabeza, and Harald Mehling. “Determination of Enthalpy Temperature Curves of Phase Change Materials with the Temperature-History Method: Improvement to Temperature Dependent Properties.” Measurement Science and Technology 14, no. 2 (February 1, 2003): 184–89. https://doi.org/10.1088/0957-0233/14/2/305. [2] Safari, A., R. Saidur, F.A. Sulaiman, Yan Xu, and Joe Dong. “A Review on Supercooling of Phase Change Materials in Thermal Energy Storage Systems.” Renewable and Sustainable Energy Reviews 70 (April 2017): 905–19. https://doi.org/10.1016/j.rser.2016.11.272

thermodynamics↗
DOE OSTI2025

Economic and environmental performance of biomass gasification for renewable natural gas production in the context of the U.S. natural gas supply

Bioenergy technologies offer potential for reducing greenhouse gas (GHG) emissions. One such promising technology is biomass gasification, which is the conversion of biomass into renewable natural gas (RNG) for use with a natural gas combined-cycle power generation system. However, the associated economic and emission effects need to be better understood to enable optimal decision-making and avoid missed opportunities for enhancing efficiency and increasing system circularity. This analysis explores opportunities to (1) decarbonize natural-gas-based systems and (2) leverage the extensive US natural gas infrastructure to mobilize biomass resources to achieve environmental and economic benefits. Here, in this analysis, the research team used a spatially explicit biomass logistics model (integrated with relevant biomass availability, technoeconomic analysis, and life cycle assessment information) to simulate economically optimal biomass allocation for RNG production and use for decarbonization in the United States. Results show that the United States has the potential to produce 9203 million GJ of RNG within the expected range of $\$$12–30/GJ. Further analyses tested the overall RNG production system's sensitivity to economic and emissions parameters of nine different processes. The sensitivity analysis results indicate that the median carbon abatement cost of RNG is most sensitive to changes in emissions associated with conversion processes and land use changes. These findings provide a deeper understanding of RNG's economic and emission potential for decision-making and guiding future research.

09 BIOMASS FUELS↗
DOE OSTI2025

Vehicle-Cycle Inventory for Type C School Buses & Intra-City Transit Buses

This report documents the new inventory incorporated into the Research and Development version of Greenhouse gases, Regulated Emissions, and Energy use in Technologies (R&D GREET) 2025 model for the vehicle cycle of Type C school buses and intracity transit buses. The transportation sector contributes significantly to the United States’ energy consumption and resultant emissions (EPA, 2025a). However, public transit plays an important role in mitigating these impacts because it consumes a relatively low amount of energy per passenger (Congressional Budget Office, 2022). Public transit is widely used in the United States; more than 500,000 school buses (EPA, 2025b) and ~75,000 service buses (American Public Transportation Association, 2025) operate in the nation. These are primarily internal combustion engine vehicles (ICEVs) powered by diesel. Original equipment manufacturers (OEMs) are making efforts to electrify U.S. bus fleets by using batteries as a propulsion system to replace internal combustion engines. Electrification can reduce tailpipe emissions, such as particulate matter (with a diameter ≤10 µm [PM 10 ] and with a diameter ≤2.5 µm [PM 2.5 ]) and nitrogen oxides (Jonas et al., 2025; Martinez and Samaras, 2024; EPA, 2025b; Wayne et al., 2009). Hence, any energy and emission impact analysis of public transit must consider both conventional ICEVs and upcoming electric vehicle (EV) options for the school and transit buses that dominate this landscape. To understand the detailed environmental impact profiles of ICEV and EV school and transit buses, it is necessary to conduct a thorough analysis covering both vehicle manufacturing and vehicle use stages. The current literature lacks a detailed vehicle-cycle inventory for school and transit buses, which makes this kind of comparison difficult. To overcome this gap, we developed a comprehensive vehicle-cycle model for school and transit buses in Argonne’s R&D GREET 2025 model. The model is flexible in handling user inputs for key assumptions, such as component weights and material compositions, upstream energy sources for material processing, and vehicle operating parameters, to understand their impacts on energy use and emissions for both school and transit buses. This report is organized as follows: Section 2 provides details on the modeling approach and vehicle specifications (weights and composition of different vehicle components, and vehicle operating parameters) for both school and transit buses. Section 3 provides details on vehicle assembly, disposal, and recycling (ADR) approaches for the two buses. Section 4 includes details about their incorporation into the R&D GREET model.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

A Review and Perspective on Cathodoluminescence Analysis of Halide Perovskites

Halide perovskite solar cells have achieved a certified efficiency of 25.2%, surpassing CdTe and CuInGaSe 2 , which have long been regarded as the most-efficient thin-film photovoltaic materials. As this exciting class of materials continues to mature, researchers will require characterization techniques capable of exposing the interplay among structure, chemistry, and optoelectronic properties to inform processing strategies and increase both device efficiencies and long-term stability. Cathodoluminescence microscopy is an ideal technique to provide such information due to the high spatial resolution and robust optical information acquired. Here, the current body of work related to cathodoluminescence analysis of halide perovskite materials for optoelectronic applications is surveyed. This review demonstrates how cathodoluminescence can monitor degradation due to environmental stressors, phase segregation resulting from material processing, and other halide perovskite-centric material issues. A persistent concern associated with e-beam-based analysis of halide perovskites is what effect the electron beam has on the material properties being probed. Addressing this, a detailed discussion is provided on the origin of the cathodoluminescence signal and a review of studies focused on revealing changes in the properties of halide perovskites resulting from e-beam excitation. Finally, a perspective on future opportunities to expand the role of cathodoluminescence analysis for halide perovskites is provided.

14 SOLAR ENERGY↗
DOE OSTI2023

Regional variability in the environmental controls of precipitation regimes in the tropics

The environmental factors that control precipitation regimes in Boreal winter rainfall in the tropics and their regional variabilities are examined using a simple statistical analysis and a machine learning model. Radar-derived precipitation from field campaigns at Darwin Australia, Manaus Brazil, and the Equatorial Indian Ocean, along with the corresponding large-scale environmental variables from ERA5 reanalysis, are used. The dependence of marginal distributions of frequencies of these regimes on five environmental variables are calculated. The variables are hourly column integrated precipitable water (PW), convective available potential energy (CAPE), convective inhibition (CIN), and lower and upper tropospheric wind shear. The simple machine learning model that predicts the probability of transition from suppressed to an active regime as a function of the environmental variables is designed and optimized for a potential application as a trigger function for convection parameterizations. To the first order the analysis shows an abrupt increase in the probability of an active regime near PW > 60 mm and CIN of <100 J kg -1 . The key differences in the frequencies of active regimes among the regions are found to be related to the fact that over Darwin there is strong variability in PW while CIN is generally low. Over Amazon, on the other hand, both PW and CIN are quite variable. Over the DYNAMO domain the comparatively frequent low PW is compensated for by consistently low CIN resulting in a moderate frequency of an active regime.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Environmental controls on the light use efficiency of terrestrial gross primary production

Abstract Gross primary production (GPP) by terrestrial ecosystems is a key quantity in the global carbon cycle. The instantaneous controls of leaf‐level photosynthesis are well established, but there is still no consensus on the mechanisms by which canopy‐level GPP depends on spatial and temporal variation in the environment. The standard model of photosynthesis provides a robust mechanistic representation for C 3 species; however, additional assumptions are required to “scale up” from leaf to canopy. As a consequence, competing models make inconsistent predictions about how GPP will respond to continuing environmental change. This problem is addressed here by means of an empirical analysis of the light use efficiency (LUE) of GPP inferred from eddy covariance carbon dioxide flux measurements, in situ measurements of photosynthetically active radiation (PAR), and remotely sensed estimates of the fraction of PAR (fAPAR) absorbed by the vegetation canopy. Focusing on LUE allows potential drivers of GPP to be separated from its overriding dependence on light. GPP data from over 100 sites, collated over 20 years and located in a range of biomes and climate zones, were extracted from the FLUXNET2015 database and combined with remotely sensed fAPAR data to estimate daily LUE. Daytime air temperature, vapor pressure deficit, diffuse fraction of solar radiation, and soil moisture were shown to be salient predictors of LUE in a generalized linear mixed‐effects model. The same model design was fitted to site‐based LUE estimates generated by 16 terrestrial ecosystem models. The published models showed wide variation in the shape, the strength, and even the sign of the environmental effects on modeled LUE. These findings highlight important model deficiencies and suggest a need to progress beyond simple “goodness of fit” comparisons of inferred and predicted carbon fluxes toward an approach focused on the functional responses of the underlying dependencies.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1978

Mapping of chlorophyll a distributions in coastal zones

It is pointed out that chlorophyll a is an important environmental parameter for monitoring water quality, nutrient loads, and pollution effects in coastal zones. High chlorophyll a concentrations occur in areas which have high nutrient inflows from sources such as sewage treatment plants and industrial wastes. Low chlorophyll a concentrations may be due to the addition of toxic substances from industrial wastes or other sources. Remote sensing provides an opportunity to assess distributions of water quality parameters, such as chlorophyll a. A description is presented of the chlorophyll a analysis and a quantitative mapping of the James River, Virginia. An approach considered by Johnson (1977) was used in the analysis. An application of the multiple regression analysis technique to a data set collected over the New York Bight, an environmentally different area of the coastal zone, is also discussed.

Johnson, R. W.↗
NASA NTRS1992

Wind tunnel seeding particles for laser velocimeter

The design of an optimal air foil has been a major challenge for aerospace industries. The main objective is to reduce the drag force while increasing the lift force in various environmental air conditions. Experimental verification of theoretical and computational results is a crucial part of the analysis because of errors buried in the solutions, due to the assumptions made in theoretical work. Experimental studies are an integral part of a good design procedure; however, empirical data are not always error free due to environmental obstacles or poor execution, etc. The reduction of errors in empirical data is a major challenge in wind tunnel testing. One of the recent advances of particular interest is the use of a non-intrusive measurement technique known as laser velocimetry (LV) which allows for obtaining quantitative flow data without introducing flow disturbing probes. The laser velocimeter technique is based on measurement of scattered light by the particles present in the flow but not the velocity of the flow. Therefore, for an accurate flow velocity measurement with laser velocimeters, two criterion are investigated: (1) how well the particles track the local flow field, and (2) the requirement of light scattering efficiency to obtain signals with the LV. In order to demonstrate the concept of predicting the flow velocity by velocity measurement of particle seeding, the theoretical velocity of the gas flow is computed and compared with experimentally obtained velocity of particle seeding.

Ghorieshi, Anthony↗
NASA NTRS2026

Parametric-Based Heat Rejection Trade Study for Lunar and Martian Surface Operations

Establishing and maintaining a sustained presence on the lunar and/or Martian surfaces will require a diverse portfolio of surface elements (e.g., habitation, mobility, power generation, etc.). Many of these systems generate excess heat that must be rejected across a wide range of magnitudes, temperatures, and duty cycles and under variable environmental conditions. To identify the most promising heat rejection approaches for this diverse portfolio, a heat rejection trade study was conducted to evaluate the performance of different technology approaches across a spectrum of surface environments and heat-load requirements. The trade study consisted of three stages: (1) development of a parametric-based modeling framework, (2) creation of a database of heat rejection technologies, surface elements, and environmental conditions for the Moon and Mars, and (3) execution of a quantitative analysis of various heat rejection technologies across different operating conditions and surface elements. The modeling framework is developed in Python and Excel to prioritize small model size and hence low computational cost to enable large parametric sweeps while avoiding the reliance on proprietary software. Individual heat rejection processes are represented as simple Excel models, and a centralized Python script interfaces with the models to coordinate the parametric study. These simple sizing models were developed to take heat load requirements and environmental parameters as inputs and compute mass, power, and volume as outputs. Rather than assess each heat rejection technology separately for each surface element, a unified parametric space was developed to evaluate all technologies across all elements. This parametric space includes factors related to heat load (e.g., magnitude or temperature) and environment (e.g., surface temperature, sky temperature, solar flux). This effort generated a database containing information on over 60 heat rejection technologies and 30 surface elements. For each surface element, the expected heat rejection requirements were documented and analyzed to determine the most common needs shared across all elements. Environmental conditions at various lunar and Martian latitudes were also established for worst-case hot and worst-case cold scenarios. High-fidelity heat rejection models are currently under development. Preliminary trades between heat rejection technologies including radiators, venting technologies, convective coolers, and more have been conducted to identify promising options. This presentation will summarize the preliminary trade results and provide an overview and discussion of the expected heat loads and thermal environments for sustained surface operations on the Moon and Mars.

Heat Rejection↗
DOE OSTI2020

Chapter 14: Sustainable Biomass Conversion Process Assessment

Process intensification and integration for sustainable design play an essential role in addressing and alleviating severe sustainable development challenges. It is prudent to evaluate a process design in its early stage development to ensure the process can achieve sustainability goals. The primary goal of a sustainability evaluation is to assess the impact of systems on areas sought to be protected and maintained over time, such as human well-being and ecosystems (Schaubroeck, T. and Rugani, B. (2017). A revision of what life cycle sustainability assessment should entail: towards modeling the net impact on human well-being. Journal of Industrial Ecology 21 (6): 1464-1477). Parenthetically, sustainable process design to convert biomass to fuels and chemicals plays an integral part in the bioeconomy sustainability. It is recognized that the integration of sustainability in process design is core to the mission in developing renewable fuels and should be considered a necessary practice in biorefinery design. This study demonstrates the use of Gauging Reaction Effectiveness for ENvironmental Sustainability of Chemistries with a multi-Objective Process Evaluator (GREENSCOPE) as a tool to help track progress on process sustainability performance attributed to conversion improvement. With the incorporation of a wide range of indicators, GREENSCOPE captures the multi-dimensional aspect of the process design and operation. As opposed to conventional techno-economic analysis and life cycle assessment (in which the focuses are limited to economic and environmental aspects), GREENSCOPE enables the consideration of process intensification and integration for sustainable design. A high-octane gasoline production from woody biomass feedstock is used as a case study to demonstrate the approach.

biomass↗
DOE OSTI2024

Environmental Dependence of Type Ia Supernovae in Low-redshift Galaxy Clusters

Abstract We present an analysis of 102 Type Ia supernovae (SNe Ia) in nearby ( z < 0.1), x-ray-selected galaxy clusters. This is the largest such sample to date and is based on archival data primarily from ZTF and ATLAS. We divide our SNe Ia into an inner cluster sample projected within r 500 of the cluster center and an outer cluster sample projected between r 500 and 2 r 500 . We compare these to field samples of SNe Ia at similar redshifts in both quiescent and star-forming host galaxies. Based on SALT3 fits to the light curves, we find that the inner cluster SNe Ia have a higher fraction of fast-evolving objects (SALT3 x 1 < −1) than the outer cluster or field quiescent samples. This implies an intrinsically different population of SNe Ia occurs in inner cluster environments, beyond known correlations based on host galaxy alone. Our cluster samples show a strongly bimodal x 1 distribution with a fast-evolving component that dominates the inner cluster objects (≳75%) but is just a small fraction of SNe Ia in field star-forming galaxies (≲10%). We do not see strong evidence for variations in the color (SALT3 c ) distributions among the samples and find only minor differences in SN Ia standardization parameters and Hubble residuals. We suggest that the age of the stellar population drives the observed distributions, with the oldest populations nearly exclusively producing fast-evolving SNe Ia.

Larison, Conor (ORCID:0000000320374619)↗
NASA NTRS1974

Remote sensing by ERTS satellite of vegetational resources believed to be under possible threat of environmental stress

The distribution of natural vegetation types on North Merritt Island, Florida, was studied by analysis of ERTS multispectral scanner data on the image-100 computer system. The boundaries of six distinct plant associations were located on photos made on the image analyzer, with an insignificant mean error of -24.38 meters. The six plant associations are described; each had a characteristic spectral signature. The difference in average reflectance grey level between the lowest of the four spectral scanning bands and the highest spectral scanning band for the six vegetation types was determined. The decreasing trend of the differences is strongly negatively correlated with height of land.

Poonai, P.↗