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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Securing Environmental IoT Data Using Masked Authentication Messaging Protocol in a DAG-Based Blockchain: IOTA Tangle

The demand for the digital monitoring of environmental ecosystems is high and growing rapidly as a means of protecting the public and managing the environment. However, before data, algorithms, and models can be mobilized at scale, there are considerable concerns associated with privacy and security that can negatively affect the adoption of technology within this domain. In this paper, we propose the advancement of electronic environmental monitoring through the capability provided by the blockchain. The blockchain’s use of a distributed ledger as its underlying infrastructure is an attractive approach to counter these privacy and security issues, although its performance and ability to manage sensor data must be assessed. We focus on a new distributed ledger technology for the IoT, called IOTA, that is based on a directed acyclic graph. IOTA overcomes the current limitations of the blockchain and offers a data communication protocol called masked authenticated messaging for secure data sharing among Internet of Things (IoT) devices. We show how the application layer employing the data communication protocol, MAM, can support the secure transmission, storage, and retrieval of encrypted environmental sensor data by using an immutable distributed ledger such as that shown in IOTA. Finally, we evaluate, compare, and analyze the performance of the MAM protocol against a non-protocol approach.

Gangwani, Pranav (ORCID:0000000159226002)↗
NASA NTRS2006

Utility of MODIS Aerosol Optical Depth for Estimating PM2.5 Exposure in Environmental Public Health Surveillance

As part of the National Environmental Public Health Tracking Network (EPHTN) the National Center for Environmental Health (NCEH) at the Centers for Disease Control and Prevention (CDC) is leading a project called Health and Environment Linked for Information Exchange (HELIX-Atlanta). The goal of developing the National Environmental Public Health Tracking Network is to improve the health of communities. Currently, few systems exist at the state or national level to concurrently track many of the exposures and health effects that might be associated with environmental hazards. An additional challenge is estimating exposure to environmental hazards such as particulate matter whose aerodynamic diameter is less than or equal to 2.5 micrometers (PM(2.5)) HELIX-Atlanta's goal is to examine the feasibility of building an integrated electronic health and environmental data network in five counties of Metropolitan Atlanta, GA (Clayton, Cobb, DeKalb, Fulton, and Gwinnett counties). Under HELIX-Atlanta, pilot projects are being conducted to develop methods to characterize exposure; link health and environmental data; analyze the relationship between health and environmental factors; and communicate findings. NASA Marshall Space Flight Center (NASA/MSFC) is collaborating with CDC to combine NASA earth science satellite observations related to air quality and environmental monitoring data to model surface estimates of PM(2.5) concentrations that can be linked with clinic visits for asthma. From 1999-2000 there were over 9,400 hospitalizations per year in Georgia with asthma as the primary diagnosis. The majority of these hospitalizations occurred in medical facilities in the five most populous Metro-Atlanta counties. Hospital charges resulting from asthma in Georgia are approximately $59 million dollars annually. There is evidence in the research literature that asthmatic persons are at increased risk of developing asthma exacerbations with exposure to environmental factors, including PM(2.5). Thus, HELIX-Atlanta is focusing on methods for characterizing population exposure to PM(2.5) for the Atlanta metropolitan area that could be used in on-going surveillance. While use of the Air Quality System, (AQS) PM(2.5) data alone could meet HELIX Atlanta, specifications, there are only five AQS sites in the Atlanta area, thus the spatial coverage is not ideal. Also, the AQS ground observations are made at time intervals ranging from one hour to six days leaving some temporal gaps. NASA Moderate Resolution Imaging Spectroradiometer (MODIS) satellite Aerosol Optical Depth (AOD) data have the potential for estimating daily ground level PM(2.5) at 10 km resolution over the metropolitan Atlanta area supplementing the AQS ground observations and filling their spatial and temporal gaps.

Al-Hamdan, Mohammad↗
DOE OSTI2026

Soil and groundwater environmental sensor data, Wax Lake Delta, Louisiana, March 2023 - March 2024

This study evaluates how environmental parameters that integrate biogeochemical processes vary with water table fluctuations in the freshwater Wax Lake Delta (WLD) in Louisiana, U.S.A. This data package contains seven *.csv files and one Excel file that compiles all the data from the individual .csv files. This dataset reports high frequency (15-min) observations of water level, soil redox potential, specific conductance, and pH made for one year along elevation transects located on the older, proximal (OT) and younger, distal (YT) ends of a deltaic island. Water depth relative to the ground surface (cm; HOBO U20L-04; error ± 0.4 cm), water pH and temperature (HOBO MX2501), and specific conductance and temperature (HOBO U24-001) sensors were installed in March 2023. Water depth was corrected for barometric pressure recorded by a separate logger secured to a platform above the highest water level. Soil redox probes (SWAP ORP-40-4-B) were also installed in March 2023. Each probe had four Pt sensors (2 mm width) placed at 10 cm, 20 cm, 30 cm, and 40 cm below the ground surface. Redox data were referenced to an external Ag0/AgCl (3M KCl) reference probe placed in saturated ground and recorded on CR1000X dataloggers (Campbell Scientific) powered by solar panels. A second reference probe was positioned near the primary reference probe for backup and data correction. The tops of the soil redox probes and soil moisture probes were flush with the soil surface so that sensors are reported at their indicated depths below ground surface. Here, we report data collected between 15 March 2023 to 15 March 2024 for all sensors, with some differences due to exact dates of sensor placement or data gaps associated with sensor malfunction. For example, water depth at OT4 was not recorded between March to November 2023. Data flags indicate whether a value is valid (1) or was excluded from data analysis in the associated manuscript (-1).

EARTH SCIENCE > LAND SURFACE > SOILS↗
NASA NTRS2016

Reanalyzing Environmental Lidar Data for Archaeology: Mesoamerican Applications and Implications

This paper presents a preliminary archaeological assessment of extensive transects of lidar recently collected by environmental scientists over southern Mexico using the G-LiHT system of NASA's Goddard Space Flight Center. In particular, this article offers the results of a first phase of research, consisting of: 1) characterization and classification of the cultural and ecological context of the samples, and 2) bare earth processing and visual inspection of a sample of the flight paths for identification of probable anthropogenic Precolumbian features. These initial results demonstrate that significant contributions to understanding variations in Precolumbian land-use and settlement patterns and change is possible with truly multi-regional lidar surveys not originally captured for archaeological prospection. We point to future directions for the development of archaeological applications of this robust data set. Finally, we offer the potential for enriching archaeological research through tightly coupled collaborations with environmental science and monitoring. Archaeologists in the neotropics can acquire more data, better realize the full potential of lidar surveys, and better contribute to interdisciplinary studies of human-environmental dynamic systems through regionally focused and collaborative scientific research.

Golden, Charles↗
NASA NTRS1991

SEAPAK user's guide, version 2.0. Volume 2: Descriptions of programs

The SEAPAK is a user-interactive satellite data analysis package that was developed for the processing and interpretation of Nimbus-7/Coastal Zone Color Scanner (CZCS) and the NOAA Advanced Very High Resolution Radiometer (AVHRR) data. Significant revisions were made since version 1.0, and the ancillary environmental data analysis module was greatly expanded. The package continues to be user friendly and user interactive. Also, because the scientific goals of the ocean color research being conducted have shifted to large space and time scales, batch processing capabilities for both satellite and ancillary environmental data analyses were enhanced, thus allowing for large quantities of data to be ingested and analyzed.

Mcclain, Charles R.↗
NASA NTRS2011

Modeling Ionosphere Environments: Creating an ISS Electron Density Tool

The International Space Station (ISS) maintains an altitude typically between 300 km and 400 km in low Earth orbit (LEO) which itself is situated in the Earth's ionosphere. The ionosphere is a region of partially ionized gas (plasma) formed by the photoionization of neutral atoms and molecules in the upper atmosphere of Earth. It is important to understand what electron density the spacecraft is/will be operating in because the ionized gas along the ISS orbit interacts with the electrical power system resulting in charging of the vehicle. One instrument that is already operational onboard the ISS with a goal of monitoring electron density, electron temperature, and ISS floating potential is the Floating Potential Measurement Unit (FPMU). Although this tool is a valuable addition to the ISS, there are limitations concerning the data collection periods. The FPMU uses the Ku band communication frequency to transmit data from orbit. Use of this band for FPMU data runs is often terminated due to necessary observation of higher priority Extravehicular Activities (EVAs) and other operations on ISS. Thus, large gaps are present in FPMU data. The purpose of this study is to solve the issue of missing environmental data by implementing a secondary electron density data source, derived from the COSMIC satellite constellation, to create a model of ISS orbital environments. Extrapolating data specific to ISS orbital altitudes, we model the ionospheric electron density along the ISS orbit track to supply a set of data when the FPMU is unavailable. This computer model also provides an additional new source of electron density data that is used to confirm FPMU is operating correctly and supplements the original environmental data taken by FPMU.

Gurgew, Danielle N.↗
NASA NTRS2000

Microbial Impact on Success of Human Exploration Missions

The purpose of this study is to identify microbiological risks associated with space exploration and identify potential countermeasures available. Identification of microbial risks associated with space habitation requires knowledge of the sources and expected types of microbial agents. Crew data along with environmental data from water, surfaces, air, and free condensate are utilized in risk examination. Data from terrestrial models are also used. Microbial risks to crew health include bacteria, fungi, protozoa, and viruses. Adverse effects of microbes include: infections, allergic reactions, toxin production, release of volatiles, food spoilage, plant disease, material degradation, and environmental contamination. Risk is difficult to assess because of unknown potential changes in microbes (e.g., mutation) and the human host (e.g., immune changes). Prevention of adverse microbial impacts is preferred over remediation. Preventative measures include engineering measures (e.g., air filtration), crew microbial screening, acceptability standards, and active verification by onboard monitoring. Microbiological agents are important risks to human health and performance during space flight and risks increase with mission duration. Acceptable risk level must be defined. Prevention must be given high priority. Careful screening of crewmembers and payloads is an important element of any risk mitigation plan. Improved quantitation of microbiological risks is a high priority.

Pierson, Duane L.↗
DOE OSTI2021

Seismic Ambient Noise Analyses Reveal Changing Temperature and Water Signals to 10s of Meters Depth in the Critical Zone

The critical zone sustains terrestrial life, but we have few tools to explore it efficiently beyond the first few meters of the subsurface. Using analyses of high-frequency ambient seismic noise from densely spaced seismometers deployed in the forested Shale Hills subcatchment of the Susquehanna Shale Hills Critical Zone Observatory (SSHCZO), we show that temporal changes in seismic velocities at depths from ~1 m to tens of m can be detected. Furthermore, these changes are driven by variations at the land surface. The Moving-Window Cross-Spectral (MWCS) method was employed to measure seismic-velocity changes in coda waves at hourly resolution in 10 different frequency bands. We observed a diurnal signal, a seasonal signal, and a meteorological-event-based signal. These signals were compared to time-series measurements of precipitation, well water levels, soil moisture, soil temperature, air temperature, latent heat flux, and air pressure in the heavily instrumented catchment. Most of the velocity changes can be explained by variations in temperature that result in thermoelastic strains that propagate to depth. But some double minima in seismic velocity time-series observed after large rain events were attributed in part to the effects of water infiltration. These results show that high-frequency ambient noise data may in some locations be used to detect changes in the critical zone from ~1 to ~100 m or greater depth with hourly resolution. But interpretation of such data requires multiple environmental data sets to deconvolve the complex interrelationships among thermoelastic and hydrological effects in the subsurface critical zone.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1983

Pacific area data collection stations

The installation of environmental data collection systems at several remotely located sites in islands in the Pacific Ocean is summarized. The effort was designed to enhance the ability to collect hydrological information. The data collection station consists of a data acquisition system for handling data, a transmitter for uplinking information to the GOES-W geostationary satellite, and a variety of environmental sensors for data accumulation. Each system was assembled, tested, and deployed on designated islands. The concept of using microprocessors for handling data at remote sites and relaying it via a satellite link is a cost effective approach. Such systems require high reliability and proven performance in the field.

Rector, R. C.↗
NASA NTRS2016

JPSS-1 VIIRS Version 2 At-Launch Relative Spectral Response Characterization and Performance

The relative spectral response (RSR) characterization of the JPSS-1 VIIRS spectral bands has achieved at launch status in the VIIRS Data Analysis Working Group February 2016 Version 2 RSR release. The Version 2 release improves upon the June 2015 Version 1 release by including December 2014 NIST TSIRCUS spectral measurements of VIIRS VisNIR bands in the analysis plus correcting CO2 influence on the band M13 RSR. The T-SIRCUS based characterization is merged with the summer 2014 SpMA based characterization of VisNIR bands (Version 1 release) to yield a fused RSR for these bands, combining the strengths of the T-SIRCUS and the SpMA measurement systems. The M13 RSR is updated by applying a model-based correction to mitigate CO2 attenuation of the SpMA source signal that occurred during M13 spectral measurements. The Version 2 release carries forward the Version 1 RSR for those bands that were not updated (M8-M12, M14-M16AB, I3-I5, DNBMGS). The Version 2 release includes band average (overall detectors and subsamples) RSR plus supporting RSR for each detector and subsample. The at-launch band average RSR have been used to populate Look-Up Tables supporting the sensor data record and environmental data record at-launch science products. Spectral performance metrics show that JPSS-1VIIRS RSR are compliant on specifications with a few minor exceptions. The Version 2 release, which replaces the Version 1 release, is currently available on the password-protected NASA JPSS-1 eRooms under EAR99 control.

Chris Moeller↗
NASA NTRSDate not supplied

Natural Language Processing for Extracting Rich Disease Data Aligned To Satellite Meteorological Data

Global climate change is redefining our understanding of how diseases spread. In Sri Lanka, vector-borne diseases such as dengue fever, encephalitis, and leptospirosis historically surged during the monsoon seasons when temperatures were high enough for mosquito eggs to hatch. Unfortunately, due to rising temperatures and more erratic rainfall patterns, mosquito eggs can now hatch year-round and are increasingly unpredictable, leading to an alarmingly increasing number of hospitalizations and deaths. More data is needed to adapt our response to these diseases in an increasingly warmer world. In the contemporary landscape, a wealth of disease information is available, yet accessibility remains limited due to unstructured data formats such as PDFs. Therefore, converting unstructured disease reports into structured formats is necessary for effectively leveraging data. This paper introduces a comprehensive framework for collecting unstructured disease reports and transforming them into analyzable formats. By creating separate models tailored to each data format, we can ensure accuracy compared to general models. These straightforward models enhance accessibility and empower other researchers to use our tools. The returned structured data can then be harnessed for analysis, statistical purposes, and informing evidence-based public health interventions, thus facilitating more informed decision-making in healthcare. We deploy this framework to produce geospatial data for Sri Lanka and Brazil for many different conditions and align these data with satellite environmental data, providing for the first time a structured, aligned powerful dataset for disease modeling.

Open Source Open Science↗
NASA NTRS2012

Asthma and Air Quality in the Presence of Fires - A Foundation for Public Health Policy in Florida

Outdoor air quality and its associated impacts on respiratory problems in Florida are of public health significance. Air quality in Florida can be poor during the extended wildfire season, threatening persons with compromised respiratory systems each year. Studies have demonstrated that particulate matter, which is generally elevated in the vicinity of wildfires, is associated with increases in hospital admissions and occurrences of acute asthma exacerbations. However, few studies have examined the modifying effect of socio-demographic characteristics of cities or regional areas on the relationship between air quality and health outcomes. In an ongoing university/multi-agency project, asthma hospital/emergency room (patient) data are being used to create a health outcome indicator of human response to environmental air quality. Environmental data are derived from satellite measurements, with special attention being given to the effect of wildfires and prescribed burns on air quality. This presentation will focus on the environmental data sets particulate matter, location of fires, smoke plumes that are being collected and processed for linkage with health data. After this linkage has been performed, space-time models of asthma rates as a function of air quality data and socio-demographic variables will be developed and validated. The Florida Department of Health (FDOH) will work with county health department staff and representatives from the medical community to establish a protocol with triggers for issuing public health advisories/alerts based on the developed and validated health outcome indicators. From this effort, a science-based policy for issuing public health advisories/alerts for asthma relating to air quality will be developed, giving FDOH the ability to (1) predict, with stated levels of uncertainty, case load of hospital admissions based on air quality, (2) reduce asthma exacerbations by forewarning asthmatics to limit outside activities on poor air quality days, (3) apply management practices on the rates of hospital/emergency room visits for asthma, and (4) provide information that would help translate interventions into policy decisions, thereby reducing the economic burden and increasing well being of asthmatics. Further, the results of the study will be incorporated into Florida s Environmental Public Health Tracking (EPHT) program, which is part of the Centers for Disease Control and Prevention's (CDC's) EPHT network.

Crosson, William↗
NASA NTRS1991

SEAPAK user's guide, version 2.0. Volume 1: System description

The SEAPAK is a user interactive satellite data analysis package that was developed for the processing and interpretation of Nimbus-7/Coastal Zone Color Scanner (CZCS) and the NOAA Advanced Very High Resolution Radiometer (AVHRR) data. Significant revisions were made to version 1.0 of the guide, and the ancillary environmental data analysis module was expanded. The package continues to emphasize user friendliness and user interactive data analyses. Additionally, because the scientific goals of the ocean color research being conducted have shifted to large space and time scales, batch processing capabilities for both satellite and ancillary environmental data analyses were enhanced, thus allowing large quantities of data to be ingested and analyzed in background.

Mcclain, Charles R.↗
DOE OSTI2026

Raw soil carbon dioxide, moisture, temperature and micrometeorological data in the East River Watershed, Colorado June 2021-June 2024. (DE-SC0021139)

This dataset contains raw data from four tripod stations along an elevation gradient on Snodgrass Mountain in the East River Watershed, CO, USA. Each station contains a datalogger connected to 3 soil Carbon Dioxide CO2 gas probes, 3 soil temperature/moisture sensors and a micrometeorological station. Sensors are scanned every minute, and the 30 minute average is reported. The file snodgrass_soil_ESS.csv contains raw data, a row of column descriptors, and units of measurements. some data processing and QA/QC was done to filter out data from sensors that went bad and extreme outliers. CO2 sensors that went bad were replaced with new sensors as soon as possible. This research was performed to investigate the ecohydrological linkages of belowground carbon processes in the East River watershed forested communities to better understand how these ecosystems will respond to a changing cold-season moisture input. This is the second version of this data set and was modified on 10/01/2024. The primary change in the data was the addition of data from the fall of 2022 to June of 2024. In addition, minor QA/QC was done to filter out data from sensors that went bad and extreme outliers. THe filtered data are now NA's in this data frame and primarily the CO2 sensors. Limited to no QA/QC has been done on the other environmental data. This is now the third version of the data set, and was modified 03/25/2026. The primary change in the data was the addition of data from the June of 2024 to December 2025. Further r QA/QC was done with the new data to filter out bad data from faulty sensors and extreme outliers. The filtered data are now NA's in this data frame and primarily the CO2 sensors. Limited to no QA/QC has been done on the other environmental data. ##This additional data was funded under DE-SC0024218( Responses of Plant and Microbial Respiration Sources to Changing Cold Season Climate Drivers in the East River Watershed)

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Block Island Environmental Monitoring Data (Weather, Waves & Sensor Depth)

This dataset contains meteorological, oceanographic, and sensor-depth data collected near Block Island during the 2016 and 2017 RODEO field seasons to provide environmental context for concurrent acoustic and survey operations. It includes buoy-derived wind and wave time series, in-situ water temperature logger records, and depth (pressure) records from a sensor mounted on the vertical line array.

17 WIND ENERGY↗
NASA NTRS1996

Towards the Interoperability of Web, Database, and Mass Storage Technologies for Petabyte Archives

At the San Diego Supercomputer Center, a massive data analysis system (MDAS) is being developed to support data-intensive applications that manipulate terabyte sized data sets. The objective is to support scientific application access to data whether it is located at a Web site, stored as an object in a database, and/or storage in an archival storage system. We are developing a suite of demonstration programs which illustrate how Web, database (DBMS), and archival storage (mass storage) technologies can be integrated. An application presentation interface is being designed that integrates data access to all of these sources. We have developed a data movement interface between the Illustra object-relational database and the NSL UniTree archival storage system running in a production mode at the San Diego Supercomputer Center. With this interface, an Illustra client can transparently access data on UniTree under the control of the Illustr DBMS server. The current implementation is based on the creation of a new DBMS storage manager class, and a set of library functions that allow the manipulation and migration of data stored as Illustra 'large objects'. We have extended this interface to allow a Web client application to control data movement between its local disk, the Web server, the DBMS Illustra server, and the UniTree mass storage environment. This paper describes some of the current approaches successfully integrating these technologies. This framework is measured against a representative sample of environmental data extracted from the San Diego Ba Environmental Data Repository. Practical lessons are drawn and critical research areas are highlighted.

Moore, Reagan↗
NASA NTRS1980

STS-1 mission contamination evaluation approach

The space transportation system 1 mission will be the first opportunity to assess the induced environment of the orbiter payload bay region. Two tools were developed to aid in this assessment. The shuttle payload contamination evaluation computer program was developed to provide an analytical tool for prediction of the induced molecular contamination environment of the space shuttle orbiter during its onorbit operations. An induced environment contamination monitor was constructed and tested to measure the space shuttle orbiter contamination environment inside the payload bay during ascent and descent and inside and outside the payload bay during the onorbit phase. Measurements are to be performed during the four orbital flight test series. Measurements planned for the first flight are described and predicted environmental data are discussed. The results indicate that the expected data are within the measurement range of the induced environment contamination monitor instruments evaluated, and therefore it is expected that useful contamination environmental data will be available after the first flight.

Jacobs, S.↗
DOE OSTI2024

Geophysical and Environmental Monitoring Data, and Subsurface Flow Modelling Results for Chicken Bone Meadow, Mt. Snodgrass, Crested Butte, CO

This dataset includes geoelectrical monitoring data acquired between October 2021 and November 2022, soil moisture and temperature data, groundwater data obtained from borehole SNIB covering the period from June 2021 to September 2022, and hydrological modelling results. The data were acquired to investigate how variations in bedrock type and topography, and vegetation cover control subsurface flow dynamics. To provide insights into the subsurface flow dynamics and their controls, a monitoring transect was installed at the Chicken Bone Meadow, Mt. Snodgrass, Crested Butte, CO, measuring the spatio-temporal variations of soil moisture, soil and snow temperature, subsurface electrical resistivity variations, and groundwater dynamics. Field data are organized in a folder structure, with Electrical Resistivity Tomography (ERT) data being provided as one file per measurement, and data of the soil moisture and temperature sensors being provided as text files covering the entire monitoring period. The ‘Locations.csv’ file contains the location of all sensors, given in NAD83 – UTM Zone 13N. ERT monitoring data has been processed to filter data based on reciprocal errors (data with errors > 30% were removed), a linear error model was fitted to each survey, and to ensure a constant set of measurements for time-lapse inversion, filtered data were interpolated and assigned a 100% measurement error. Soil moisture and temperature data were acquired at 15 min intervals, and averaged to provide 1h data. Weather data and borehole data (groundwater depth, conductivity and temperature) were acquired at 30 min intervals, and are provided as daily measurements; all measurements are averaged, except of precipitation values, which are given as daily accumulation. The hydrological model was set up along the ERT monitoring transect, and net infiltration was used as surface boundary condition and derived from the weather data. Four different results are provided, (1) results for a parameterization using hydraulic permeability and porosity as derived from the ERT data through petrophysical relationships, and (2) three simplified model results, using 1 to 3 geological layers above the bedrock. Modelling was performed using PFLOTRAN, and for each model the PFLOTRAN input files are provided. The result files include weekly hydrological modelling results (e.g., saturation, velocities, pressures), as well as the model parameterization. The dataset additionally includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata; and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.

54 ENVIRONMENTAL SCIENCES↗