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The purpose of this survey is the detection of surface and subsurface Unexploded Ordnance (UXO) and in a broader sense the site characterization for identification of contaminated as well as clear areas.
The ice cloud detection sensitivity of the millimeter cloud radar (MMCR) and the Ka-band Zenith radar (KAZR) is investigated using a collocated Raman lidar (RL) at the Atmospheric Radiation Measurement Program Southern Great Plains site. Only profiles that are transparent to the RL with ice clouds only are considered in this study. The MMCR underestimates the RL ice cloud optical depth (COD) by 20%. The MMCR detects no ice clouds in 37% of the profiles. These profiles where ice cloud goes undetected by the MMCR typically contain very optically thin clouds, with a mean RL ice COD of 0.03. Higher ice cloud detection sensitivity is found for the KAZR, which underestimates the RL ice COD by 15%. The decrease in the ice COD bias for the KAZR compared to the MMCR is largely due to a decrease in the ice COD bias for the situation where the transparent profiles with ice clouds are detected by both the RL and cloud radar. The climatic net ice cloud radiative effects (CREs) from the RL at the top of the atmosphere (TOA) and the surface are 3.2 W m−2 and −0.6 W m−2, respectively. The ice CREs at the TOA and surface are underestimated for the MMCR by 0.7 W m−2 and 0.16 W m−2 (21% and 29%) and underestimated for the KAZR by 0.6 W m−2 and 0.14 W m−2 (17% and 24%). The ice clouds undetected by the cloud radars led to underestimating the climatic net cloud heating rates below 150 hPa by about 0–0.04 K day−1.
Clouds play an important role in the radiation budget over Arctic and Antarctic. Because of limited surface observing capabilities, it is necessary to detect clouds over large areas using satellite imagery. At low and mid-latitudes, satellite-observed visible (VIS; 0.65 micrometers) and infrared (IR; 11 micrometers) radiance data are used to derive cloud fraction, temperature, and optical depth. However, the extreme variability in the VIS surface albedo makes the detection of clouds from satellite a difficult process in polar regions. The IR data often show that the surface is nearly the same temperature or even colder than clouds, further complicating cloud detection. Also, the boundary layer can have large areas of haze, thin fog, or diamond dust that are not seen in standard satellite imagery. Other spectral radiances measured by satellite imagers provide additional information that can be used to more accurately discriminate clouds from snow and ice. Most techniques currently use a fixed reflectance or temperature threshold to decide between clouds and clear snow. Using a subjective approach, Minnis et al. (2001) found that the clear snow radiance signatures vary as a function of viewing and illumination conditions as well as snow condition. To routinely process satellite imagery over polar regions with an automated algorithm, it is necessary to account for this angular variability and the change in the background reflectance as snow melts, vegetation grows over land, and melt ponds form on pack ice. This paper documents the initial satellite-based cloud product over the Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) site at Barrow for use by the modeling community. Cloud amount and height are determined subjectively using an adaptation of the methodology of Minnis et al. (2001) and the radiation fields arc determined following the methods of Doelling et al. (2001) as applied to data taken during the Surface Heat and Energy Budget of the Arctic (SHEBA). The procedures and data produced in this empirically based analysis will also facilitate the development of the automated algorithm for future processing of satellite data over the ARM NSA domain. Results are presented for May, June, and July 1998. ARM surface data are use to partially validate the results taken directly over the ARM site.
Malfunctioning, or leaking, sewer systems increase the supply of water and nutrients to surface vegetation. Excess nutrients and harmful bacteria in the effluent pollute ground water and local water bodies and are dangerous to humans and the aquatic ecosystems. An airborne multispectral plant chlorophyll imaging system (PCIS) was used to identify growth patterns in the vegetation covering onsite and public sewer systems. The objective was to evaluate overall performance of the PCIS as well as to determine the best operational configuration for this application. The imaging system was flown in a light aircraft over selected locations Mobile County, Alabama. Calibration panels were used to help characterize instrument performance. Results demonstrated that the PCIS performed well and was capable of detecting septic leakage patterns from altitudes as high as 915 m. From 915 m, 6 of 18 sites were suspected to have sewage leakage. Subsequent ground inspections confirmed leakage on 3 of the 6 sites. From 610 m, 3 of 8 known leakage sites were detected. Tree cover and shadows near residential structures prevented detection of several known malfunctioning systems. Also some leakages known to occur in clear areas were not detected. False detections occurred in areas characterized by surface water drainage problems or recent excavation.
Plants acclimate to temperature by adjusting their photosynthetic capacity over weeks to months. However, most evidence for photosynthetic acclimation derives from leaf-scale experiments. Here we address the scarcity of evidence for canopy-scale photosynthetic acclimation by examining the correlation between maximum photosynthetic rates (A max,2,000 ) and growth temperature $(\overline{T_{air}})$ across a range of concurrent temperatures and canopy foliage quantity, using data from >200 eddy covariance sites. We detect widespread thermal acclimation of canopy-scale photosynthesis, demonstrated by enhanced A max,2,000 under higher $\overline{T_{air}}$, across flux sites with adequate water availability. A 14-day period is identified as the most relevant timescale for acclimation across all sites, with a range of 12-25 days for different plant functional types. The mean apparent thermal acclimation rate across all ecosystems is 0.41 (-0.38-1.04 for 5th-95th percentile range) µmol m -2 s -1 °C -1 , with croplands showing the largest acclimation rates and grasslands the lowest. Incorporating an optimality-based prediction of leaf photosynthetic capacities into a biochemical photosynthesis model is shown to improve the representation of thermal acclimation. Our results underscore the critical need for enhanced understanding and modelling of canopy-scale photosynthetic capacity to accurately predict plant responses to warmer growing seasons.
Fe-based single-atomic site catalysts (SASCs), with the natural metalloproteases-like active site structure, have attracted widespread attention in biocatalysis and biosensing. Precisely, controlling the isolated single-atom Fe-N-C active site structure is crucial to improve the SASCs’ performance. In this work, we use a facile ion-imprinting method (IIM) to synthesize isolated Fe-N-C single-atomic site catalysts (IIM-Fe-SASC). With this method, the ion-imprinting process can precisely control ion at the atomic level and form numerous well-defined single-atomic Fe-N-C sites. The IIM-Fe-SASC shows better peroxidase-like activities than that of non-imprinted references. Due to its excellent properties, IIM-Fe-SASC is an ideal nanoprobe used in the colorimetric biosensing of hydrogen peroxide (H 2 O 2 ). Using IIM-Fe-SASC as the nanoprobe, in situ detection of H 2 O 2 generated from MDA-MB-231 cells has been successfully demonstrated with satisfactory sensitivity and specificity. This work opens a novel and easy route in designing advanced SASC and provides a sensitive tool for intracellular H 2 O 2 detection.
The detection and characterization of buried objects and materials is an important step in the restoration of burial sites containing chemical and radioactive waste materials at Department of Energy (DOE) and Department of Defense (DOD) facilities. By performing these tasks with remotely controlled sensors, it is possible to obtain improved data quality and consistency as well as enhanced safety for on-site workers. Therefore, the DOE Office of Technology Development and the US Army Environmental Center have jointly supported the development of the Remote Characterization System (RCS). One of the main components of the RCS is a small remotely driven survey vehicle that can transport various combinations of geophysical and radiological sensors. Currently implemented sensors include ground-penetrating radar, magnetometers, an electromagnetic induction sensor, and a sodium iodide radiation detector. The survey vehicle was constructed predominantly of non-metallic materials to minimize its effect on the operation of its geophysical sensors. The system operator controls the vehicle from a remote, truck-mounted, base station. Video images are transmitted to the base station by a radio link to give the operator necessary visual information. Vehicle control commands, tracking information, and sensor data are transmitted between the survey vehicle and the base station by means of a radio ethernet link. Precise vehicle tracking coordinates are provided by a differential Global Positioning System (GPS).
Born in the 1950s, the Savannah River Plant was constructed as a plutonium and tritium production plant. As the Cold War era came and went, a change of direction was signaled when the name of the facility changed from Savannah River Plant to Savannah River Site (1989) – the main mission at Savannah River shifted from “production” to “cleanup.” The Department of Energy is responsible for managing the 310 square miles of land that is the Savannah River Site and the cleanup/remediation activities that occur. The Savannah River National Laboratory utilizes unmanned aircraft systems to assist with some of those environmental monitoring and remediation activities. One function of unmanned aircraft systems at the Savannah River National Laboratory is conducting aerial photography and videography. Various infrastructure evaluations have been performed with unmanned aircraft – facility rooftop inspections, water tower lock verifications, earthen dam surveys, etc. An unmanned aircraft system has been used for progress footage of remediation projects – Dunbarton Bay remediation, Saltstone Disposal Unit construction, etc. Thermal cameras on an unmanned aircraft system are used to help identify cracks/leaks in structures from vantage points not readily accessible by personnel. Virtual tours of different waste units are conducted with unmanned aircraft systems for Site groups and federal/state regulators to save costs and travel time. Additionally, advanced remote sensing technologies are used on unmanned aircraft systems at the Savannah River Site. Light Detection and Ranging uses laser pulses to measure distances to the Earth's surface or other targets to create highly detailed topographic maps that accurately portray terrain (e.g., elevation changes, slopes, and contours). Data collection with a Light Detection and Ranging unit mounted on an unmanned aircraft system is quick and efficient – large-area surveys are conducted in shorter time frames. Because Light Detection and Ranging can penetrate through foliage and vegetation to ground level, it is being used in conjunction with a watershed model to study the General Separations Area of the Site to determine stormwater flow volume and direction, monitor stream stability, and forecast river flow behavior. A hyperspectral camera captures a wide spectrum of electromagnetic wavelengths across numerous narrow bands, beyond what the human eye can see. It provides detailed spectral information about the objects or surfaces in an image, which can be used to identify and analyze materials based on their spectral signatures. A hyperspectral camera mounted on an unmanned aircraft system has been used at the Savannah River Site for non-destructive evaluation of concrete and concrete structures. Unmanned aircraft systems at the Savannah River Site are also used for the application of herbicide on identified rooftops. P-Reactor and R-Reactor are entombed nuclear reactors at the Savannah River Site. Unwanted vegetation is often present on these rooftops – over time roots can penetrate seams, cracks, and joints of the general roof and concrete caps, leading to water ingress and deterioration of the structural components. For time and cost efficiencies as well as in the interest of personnel safety, an unmanned aircraft is used to dispense herbicide on rooftop areas where vegetation is noticed to help alleviate the issues/hazards.
Tissue-specific dirigent protein gene expression and associated dirigent (site) localization were examined in various organs of Forsythia intermedia using tissue printing, in situ mRNA hybridization and immunolabeling techniques, respectively. Dirigent protein gene expression was primarily noted in the undifferentiated cambial regions of stem sections, whereas dirigent protein sites were detected mainly in the vascular cambium and ray parenchyma cell initials. Immunolocalization also revealed cross-reactivity with particular regions of the lignified cell walls, these being coincident with the known sites of initiation of lignin deposition. These latter regions are considered to harbor contiguous arrays of dirigent (monomer binding) sites for initiation of lignin biopolymer assembly. Dirigent protein mRNA expression was also localized in the vascular regions of roots and petioles, whereas in leaves the dirigent sites were primarily associated with the palisade layers and the vascular bundle. That is, dirigent protein mediated lignan biosynthesis was initiated primarily in the cambium and ray cell initial regions of stems as well as in the leaf palisade layers, this being in accordance with the occurrence of the lignans for defense purposes. Within lignified secondary xylem cell walls, however, dirigent sites were primarily localized in the S(1) sublayer and compound middle lamella, these being coincident with previously established sites for initiation of macromolecular lignin biosynthesis. Once initiation occurs, lignification is proposed to continue through template polymerization.
Spring formation is a predicted consequence of the interaction of former Martian aquifers with structures common to Mars, including basin margins, Tharsis structures, and other structural deformation characteristics. The arid environment and high abundance of water soluble compounds in the crust will have likewise encouraged spring deposit formation at spring sites. Such spring deposits may be recognized from morphological criteria if the characteristics of formation and preservation are understood. An important first step in the current Mars exploration strategy [10] is the detection of sites where there is evidence for past or present near-surface water on Mars. This study evaluates the large-scale morphology of spring deposits and the physical processes of their formation, growth, and evolution in terms that relate to (1) their identification in image data, (2) their formation, evolution, and preservation in the environment of Mars, and (3) their potential as sites of long-term or late stage shallow groundwater emergence at the surface of Mars.
The adequate odorization of natural gas is critical to identify gas leaks and to reduce accidents. To ensure odorization, natural gas utility companies collect samples to be processed at core facilities or a trained human technician smells a diluted natural gas sample. In this work, we report a detection platform that addresses the lack of mobile solutions capable of providing quantitative analysis of mercaptans, a class of compounds used to odorize natural gas. Detailed description of the platform hardware and software components is provided. Designed to be portable, the platform hardware facilitates extraction of mercaptans from natural gas, separation of individual mercaptan species, and quantification of odorant concentration, with results reported at point-of-sampling. The software was developed to accommodate skilled users as well as minimally trained operators. Detection and quantification of six commonly used mercaptan compounds (ethyl mercaptan, dimethyl sulfide, n-propylmercaptan, isopropyl mercaptan, tert–butyl mercaptan, and tetrahydrothiophene) at typical odorizing concentrations of 0.1–5 ppm was performed using the device. We demonstrate the potential of this technology to ensure natural gas odorizing concentrations throughout distribution systems.
This paper outlines a modeling technique to map lightning detection efficiency variations over a region surveyed by a sparse array of ground based detectors. A reliable flash peak current distribution (PCD) for the region serves as the technique's base. This distribution is recast as an event probability distribution function. The technique then uses the PCD together with information regarding: site signal detection thresholds, type of solution algorithm used, and range attenuation; to formulate the probability that a flash at a specified location will yield a solution. Applying this technique to the full region produces detection efficiency contour maps specific to the parameters employed. These contours facilitate a comparative analysis of each parameter's effect on the network's detection efficiency. In an alternate application, this modeling technique gives an estimate of the number, strength, and distribution of events going undetected. This approach leads to a variety of event density contour maps. This application is also illustrated. The technique's base PCD can be empirical or analytical. A process for formulating an empirical PCD specific to the region and network being studied is presented. A new method for producing an analytical representation of the empirical PCD is also introduced.
Files used to perform the Persistent Scatterer InSAR analysis with SARPROZ. The data is sourced from ESAs Sentinel-1 project and covers Brady Hot Springs and Desert Peak geothermal areas. The original titles are included for the Sentinel-1 data. The naming guide is included as a link in this submission. The data contains SAR (Radar) data from the Sentinel 1A satellite between July 2017 and December 2019. The data is necessary to replicate our results, and can be used for further PSInSAR, DInSAR and other modern interferometric analyses to determine line of sight, vertical and, possibly, East-West horizontal displacement. These displacement analysis show the soil deformation in time (including average displacement velocity), which can be used to indicate subsoil phenomena: temperature changes, subsidence, uplift, and inform other analyses like seismicity and porosity.
Accessible surfaces of the most likely astrobiological habitats (Mars, Europa, Titan) in the solar system beyond Earth are exposed to various chemical and hydrologic weathering processes directly or indirectly induced by interaction with the overlying space environment. These processes can be both beneficial, through provision of chemical compounds and energy, and destructive, through chemical dissociation or burial, to detectable presence of biosignatures. Orbital, suborbital, and surface platforms carrying astrobiological instrumentation must survive, and preferably exploit, space environment interactions to reach these habitats and search for evidence of life or its precursors. Experience from Mars suggests that any detection of biosignatures must be accompanied by characterization of the local chemical environment and energy sources including irradiation by solar ultraviolet photons and energetic particles from the space environment. Orbital and suborbital surveys of surface chemistry and astrobiological potential in the context of the space environment should precede targeted in-situ measurements to maximize probability of biosignature detection through site selection. The Space Physics of Life (SPOL) investigation has recently been proposed to the NASA Astrobiology Institute and is briefly described in this presentation. SPOL is the astrobiologically relevant study of the interactions and relationships of potentially? or previously inhabited, bodies of the solar system with the surrounding environments. This requires an interdisciplinary effort in space physics, planetary science, and radiation biology. The proposed investigation addresses the search for habitable environments, chemical resources to support life, and techniques for detection of organic and inorganic signs of life in the context of the space environment.
To facilitate locating archaeological sites before they are compromised or destroyed, we are developing approaches for generating maps of probable archaeological sites, through detecting subtle anomalies in vegetative cover, soil chemistry, and soil moisture by analyzing remotely sensed data from multiple sources. We previously reported some success in this effort with a statistical analysis of slope, radar, and Ikonos data (including tasseled cap and NDVI transforms) with Student's t-test. We report here on new developments in our work, performing an analysis of 8-band multispectral Worldview-2 data. The Worldview-2 analysis begins by computing medians and median absolute deviations for the pixels in various annuli around each site of interest on the 28 band difference ratios. We then use principle components analysis followed by linear discriminant analysis to train a classifier which assigns a posterior probability that a location is an archaeological site. We tested the procedure using leave-one-out cross validation with a second leave-one-out step to choose parameters on a 9,859x23,000 subset of the WorldView-2 data over the western portion of Ft. Irwin, CA, USA. We used 100 known non-sites and trained one classifier for lithic sites (n=33) and one classifier for habitation sites (n=16). We then analyzed convex combinations of scores from the Archaeological Predictive Model (APM) and our scores. We found that that the combined scores had a higher area under the ROC curve than either individual method, indicating that including WorldView-2 data in analysis improved the predictive power of the provided APM.
Effective and secure carbon subsurface storage, involving the deep underground injection of CO 2 into geological formations where it is permanently trapped, is paramount to mitigating CO 2 emissions (Figure I). Ensuring the integrity of these storage sites and detecting potential leakage through the casing annulus necessitates robust monitoring. This work provides the first integrated demonstration of a wireless casing-annulus monitoring architecture that can operate in highly attenuating cement-brine environments relevant to CO 2 storage. This project focused on developing and validating a novel sensor system for integration with autonomous monitoring near the cement reservoir interface. The goal was a fully integrated Technology Readiness Level (TRL) 4/5 field validation of a distributed wireless intelligent sensor system providing real-time, direct subsurface formation measurements to enhance fluid movement monitoring in the cemented casing annulus. Achieving this objective required the development and integration of 1) wireless autonomous microsensor technology by California Institute of Technology (Caltech); 2) sensor packaging and emplacement technology by Research Triangle Institute (RTI); and 3) smart well completions using wireless active casing collars and NOV pipe by the Sandia National Lab (SNL). The collaboration with the Caltech team in this project aimed to develop millimeter-scale radio frequency identification (RFID) sensors capable of detecting CO 2 , pH, and/or methane levels. These sensors are engineered to be impervious to fluids, allowing them to be mixed with cement and installed within the casing annulus. They operate using RFID protocols at frequencies of 902–928 MHz for both power and communication. A Sandia National Laboratories’ team engaged their expertise in the development of a Smart Collar system designed for the wireless data collection from these RFID sensors embedded in the cement annulus and transmission of this information to the ground surface via IntelliPipe/IntelliServ NOV drill pipe. This is accomplished through inductive coupling at the collar, which facilitates data transfer through each segment of the pipe. Because the system cannot transmit a direct current signal to power the Smart Collar, both power and communication were implemented using alternating current and electromagnetic signals at varying frequencies. Furthermore, the developed microsensor technology had to be demonstrated and validated in comparison with reference transducer measurements in a field test site at The University of Texas at Austin (UT-Austin). Although the full sensor suite did not reach field-deployment readiness, the system-level integration achieved in this project establishes a validated pathway for future incorporation of advanced microsensors.
Our previous studies of severe acute respiratory syndrome coronavirus 2 main protease (MPro) precursor monomer indicate that the initial N-terminal nonstructural protein (nsp)4/nsp5 cleavage occurs intramolecularly, with a small fraction of the active site loop equilibrium being in the active state. To understand the influence of dimer formation of MPro upon N-terminal cleavage on the subsequent C-terminal nsp5/nsp6 intermolecular cleavage kinetics, the stepwise processing of a monomeric, inactive precursor containing the native terminal cleavage sites of MPro (MBP- (−6) MPro C145A(+3) -GB1-6H, 86.2 kDa) by mature WT MPro (MPro WT ) was investigated. Differential scanning fluorimetry and analytical ultracentrifugation measurements of various MPro constructs suggest that the C145A mutation decreases the dimer dissociation constant (K dimer ) by ∼26-fold, relative to WT C145 and H41A. The monomeric precursor’s nsp4–nsp5 site appears to saturate MProWT’s active sites and cleave faster, followed by a slower first-order cleavage at the C-terminal site. No detectable product resulting from the C-terminal cleavage is observed until most of the N-terminal cleavage is complete. The initial intermediate product (termed MPro C145A-IP ) is a homodimer with an estimated K dimer of <0.05 μM. In contrast, the first-order kinetics observed for the cleavage of the monomeric form of the intermediate product is at least 300 times faster than that of the dimer form. Room-temperature X-ray structure of the MPro C145A-IP –ensitrelvir complex is like that of the MPro WT –ensitrelvir complex and reveals a dynamic C-terminal region including MPro residues 302 to 306. These results are interpreted from the point of view of a mechanism in which nsp5–nsp6 cleavage may occur from a monomeric intermediate, and dimer formation restricts this cleavage.