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An overview is presented of an investigation which was conducted to determine the actual effects of the Skylab environment on flight films. Examples of the flight film performance data are provided. Attention is given to the Skylab film, the environmental parameters, a major events profile of the Skylab mission, and a film environmental effects analysis. Representative Skylab film environmental response data are shown in a graph.
This presentation provides an overview of modeling spectral irradiance in the plane of array using geostationary operational environmental satellite data.
The term verification implies compliance verification in the language of treaty negotiation and implementation, particularly in the fields of disarmament and arms control. The term monitoring on the other hand, in both environmental and arms control treaties, has a much broader interpretation which allows for use of supporting data sources that are not necessarily acceptable or adequate for direct verification. There are many ways that satellite Earth observation (EO) data can support international environmental agreements, from national forest inventories to use in geographic information system (GIs) tools. Though only a few references to satellite EO data and their use exist in the treaties themselves, an expanding list of applications can be considered in support of multilateral environmental agreements (MEAs). This paper explores the current uses of satellite Earth observation data which support monitoring activities of major environmental treaties and draws conclusions about future missions and their data use. The scope of the study includes all phases of environmental treaty fulfillment - development, monitoring, and enforcement - and includes a multinational perspective on the use of satellite Earth observation data for treaty support.
Lawrence Livermore National Laboratory's (LLNL) Project Management Office (PMO) is proposing to install a series of modular trailers and install associated underground utilities in the 1400 Block at the Livermore Site. This Sampling and Analysis Plan (SAP) outlines the processes and procedures to collect environmental and geotechnical soil samples from the project area and to send the samples to the appropriate laboratory or laboratories for analysis or testing. The resulting environmental laboratory data will determine whether excavated soils can be reused on the project, or which type of landfill or landfills the soils may be sent for disposal. This SAP has been prepared and is organized to be consistent with LLNL's Soils Screening and Management Plan (SSMP) (LLNL, 2019), as well as the U.S. Environmental Protection Agency's (EPA) Data Quality Objectives programs (EPA, 2006).
This dataset supports a broader study examining the drivers of temporal variability in sediment respiration rates in the Yakima River Basin. The dataset provides periodic (bi-weekly or monthly) in situ hydrological and water chemistry sensor data, handheld sensor water chemistry data, general environmental context photos, and field metadata collected at six sites across the Yakima River Basin in Washington, USA. Sample and sensor data from previous years (2021-2022) can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1898912 and https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1892054, respectively. Related sample data from 2022-2024 are available at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2562910. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions This dataset contains a folder of environmental context photographs and videos and (1) file-level metadata; (2) data dictionary; (3) readme; (4) field metadata; (5) field protocols; (6) international generic sample number (IGSN) mapping file; (7) handheld sensor data; and (8) two sensor subfolders. Each sensor subfolder (BarotrollAtm and MantaRiverData) contains a subfolder containing sensor time series data and plots. The BarotrollAtm Data subfolder contains In Situ Rugged BaroTROLL sensor pressure and air temperature data. The MantaRiverData subfolder contains Eureka Manta+ 35B multisonde temperature, specific conductance, and chlorophyll A. All files are .csv, .pdf, .jpg, .jpeg, .mp4, .png, or .mov.
Representation of soil organic carbon (SOC) dynamics in Earth system models (ESMs) is a key source of uncertainty in predicting carbon climate feedbacks. The magnitude of this uncertainty can be reduced by accurate representation of environmental controllers of SOC stocks in ESMs. In this study, we used data of environmental factors, field SOC observations, ESM projections and machine learning approaches to identify dominant environmental controllers of SOC stocks and derive functional relationships between environmental factors and SOC stocks. Our derived functional relationships predicted SOC stocks with similar accuracy as the machine learning approach. We used the derived relationships to benchmark the coupled model intercomparison project phase six ESM representation of SOC stocks. We found divergent environmental control representation in ESMs in comparison to field observations. Representation of SOC in ESMs can be improved by including additional environmental factors and representing their functional relationships with SOC consistent with observations.
Electrical measurements, and environmental test data on multicoder
Management of environmental issues can require integration of multiple types of data and information, conducting data analysis and interpretation, and providing data visualization for effective communications. These data elements are important for site management to support regulator interactions and provide defensibility for remedial decisions. Databases and information repositories are core elements of managing data; however, efficient data access and analysis also enable effective site management. The U.S. Department of Energy (DOE) Hanford Site is an example of a complex site with a voluminous quantity of environmental data and a need for efficient site management. Different tiers of data and information tools have been developed and deployed to address site needs. These tools are configured for ready access via the web site interfaces and meet the rigorous quality requirements for environmental site management. Evolving efforts are focused on an integrated platform to meet site environmental management needs. In this platform, users can access site information at multiple levels of detail based on their need and permissions, so that data and associated analyses are presented within the context of the site mission and the user's management or technical needs. This concept is not only applicable at individual sites like Hanford but also applicable at other sites within the DOE complex. An integrated web-based architecture that links data visualization, data analytics, and management tools can provide holistic access to large data sets, minimize complexity, and maximize interactivity and technical communication. (authors)
Across the Department of Energy’s Environmental and Legacy Management sites, complex groundwater plumes exist that will require long-term monitoring to ensure remedial actions that have been put in place remain effective decades into the future. The current monitoring paradigm predominantly consists of groundwater well sampling, whereby samples are collected, concentrations analyzed, and plume anomalies are detected after they have occurred. The Advanced Long Term Environmental Monitoring Systems (ALTEMIS) program is a multi-lab, multi-institution team of researchers that is deploying spatially integrative technologies (i.e., real-time in situ sensor networks), coupled with artificial intelligence and machine learning, to establish a more proactive monitoring paradigm. Within this approach, plume anomalies can be predicted, and corrective actions can be established prior to the occurrence, offering a more cost-effective and robust approach to long-term monitoring. The team has deployed a variety of different in situ sensing technologies at the Savannah River Site’s F-Area Hazardous Waste Management Facility around the F-Area Seepage Basins, which are unlined basins that received 7 billion liters of acidic low-level radioactive waste from the 1950s until the late 1980s. The technologies and techniques that the team is deploying are intended to ensure that the remedial actions that have been taken by the site remain effective decades into the future. Foundational to this approach is a robust, integrated data management and analysis plan to ensure accurate and timely reporting from the variety of sensor systems that are in place. This report will outline the data management plan that has been implemented by the ALTEMIS team at the Savannah River Site and will serve as a blueprint as the technology is translated to new sites across the DOE Complex.
The Ocean Data Acquisition System (ODAS) is a low cost instrument with potential commercial application. It is easily mounted on a small aircraft and flown over the coastal zone ocean to remotely measure sea surface temperature and three channels of ocean color information. From this data, chlorophyll levels can be derived for use by ocean scientists, fisheries, and environmental offices. Data can be transmitted to shipboard for real-time use with sea truth measurements, ocean productivity estimates and fishing fleet direction. The aircraft portion of the system has two primary instruments: an IR radiometer to measure sea surface temperature and a three channel visible spectro-radiometer for 460, 490, and 520 nm wavelength measurements from which chlorophyll concentration can be derived. The aircraft package contains a LORAN-C unit for aircraft location information, clock, on-board data processor and formatter, digital data storage, packet radio terminal controller, and radio transceiver for data transmission to a ship. The shipboard package contains a transceiver, packet terminal controller, data processing and storage capability, and printer. Both raw data and chlorophyll concentrations are available for real-time analysis.
A chlorophyll fluorescence measuring system having at least one spectrometer coupled to a data logger. The data logger provides direct control of the spectrometer and includes on-board memory for storage of target and reference spectrum data obtained by the spectrometer. The data logger may be coupled to an external computer that receives and analyzes target and reference spectrum data to determine SIF using a spectral fitting algorithm. The system may include a spectrometer aiming system coupled to and controlled by the data logger. The system may also include one or more environmental sensors configured to measure environment variables. The environmental sensors may be coupled to the data logger for control and data storage. The environmental data may be communicated to the external computer for use in the spectral fitting algorithm. The data logger may be connected to a network for remote monitoring and control.
A critical problem involved in quantitative multi-temporal sensing of the physical processes with Landsat is the fact that variations in the spectral signatures for a given target of interest result from a combined effect of target properties and the environmental factors such as sun angles, atmospheric conditions, etc. at the time of an overpass. In an attempt to solve the problem, a transformation procedure is developed to remove the environmental effects from the MSS radiance data. Mathematical derivation of the transformation procedure is elaborated and an example of testing the procedure is illustrated using suspended sediments reflectance data obtained by Landsat MSS during four different overpasses over the lower Mississippi River valley.
The main objective is to conduct data analyses of SEPAC data and computer modeling to investigate spacecraft environment effects associated with injection of electron beam, plasma clouds, and neutral gas clouds from the Shuttle Orbiter. To understand the dependence of spacecraft charging potential on beam density and other plasma parameters, a two dimensional electrostatic particle code was used to simulate the injection of electron beams from an infinite conductor into a plasma. The ionization effects on spacecraft charging are examined by including interactions of electrons with neutral gases. A survey of the simulation results is presented and discussed.
The problem of experiment design is defined as an information system consisting of information source, measurement unit, environmental disturbances, data handling and storage, and the mathematical analysis and usage of data. Based on today's concept of effective computability, general guidelines for the definition of the relevant information content in data classes are derived. The lack of a universally applicable information theory and corresponding mathematical or system structure is restricting the solvable problem classes to a small set. It is expected that a new relativity theory of information, generally described by a universal algebra of relations will lead to new mathematical models and system structures capable of modeling any well defined practical problem isomorphic to an equivalence relation at any corresponding level of abstractness.
Under NASA's Earth Science Applications Program, the Infusing satellite Data into Environmental Applications (IDEA) project examined the relationship between satellite observations and surface monitors of air pollutants to facilitate a more capable and integrated observing network. This report provides a comparison of satellite aerosol optical depth to surface monitor fine particle concentration observations for the month of September 2003 at more than 300 individual locations in the continental US. During September 2003, IDEA provided prototype, near real-time data-fusion products to the Environmental Protection Agency (EPA) directed toward improving the accuracy of EPA s next-day Air Quality Index (AQI) forecasts. Researchers from NASA Langley Research Center and EPA used data from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument combined with EPA ground network data to create a NASA-data-enhanced Forecast Tool. Air quality forecasters used this tool to prepare their forecasts of particle pollution, or particulate matter less than 2.5 microns in diameter (PM2.5), for the next-day AQI. The archived data provide a rich resource for further studies and analysis. The IDEA project uses data sets and models developed for tropospheric chemistry research to assist federal, state, and local agencies in making decisions concerning air quality management to protect public health.
Presenting a data mining approach to instantaneous estimation of fuel consumption in order to reduce the environmental impact of aviation.
Time courses of compound concentrations in plasma are used in chemical safety analysis to evaluate the relationship between external administered doses and internal tissue exposures. This type of experimental data is rarely available for the thousands of non-pharmaceutical chemicals to which people may potentially be unknowingly exposed but is necessary to properly assess the risk of such exposures. In vitro assays and in silico models are often used to craft an understanding of a chemical’s pharmacokinetics; however, the certainty of the quantitative application of these estimates for chemical safety evaluations cannot be determined without in vivo data for external validation. To address this need, we present a public database of chemical time-series concentration data from 567 studies in humans or test animals for 144 environmentally-relevant chemicals and their metabolites (187 analytes total). All major administration routes are incorporated, with concentrations measured in blood/plasma, tissues, and excreta. We also include calculated pharmacokinetic parameters for some studies, and a bibliography of additional source documents to support future extraction of time-series. In addition to pharmacokinetic model calibration and validation, these data may be used for analyses of diferential chemical distribution across chemicals, species, doses, or routes, and for meta-analyses on pharmacokinetic studies.
Crewmembers live and work in a closed environment that is monitored to ensure their health and safety. Quarterly monitoring of the microorganisms in the International Space Station (ISS) environment supports crew safety and contributes to a large set of environmental microbial data from the air, surface, and water samples that are collected. This study leverages quarterly operational Environmental Health System (EHS) sampling by collecting additional microbial samples from the surface of the station’s Veggie plant production system. Longer exploration missions may require spaceflight-based systems for growth of plants, and this investigation is expected to provide additional data to help establish requirements to protect these systems, plants, and crew, mitigating adverse microbial exposure.