Management of used nuclear fuel is a major technical challenge faced by nuclear energy producing nations worldwide. In Canada, the Nuclear Waste Management Organization is responsible for the design and implementation of a deep geological repository (DGR), which will be placed ~500 m below ground surface in a stable host rock to safely contain and isolate used fuel. Within a DGR, used nuclear fuel will be placed in used fuel containers (UFCs) that are encased in copper because of copper’s corrosion resistance. The UFCs will be surrounded by highly compacted bentonite to suppress the transport of corrosive agents to the UFC and limit the movement of radionuclides out of a DGR in the unlikely case of a breach. Over the design lifespan of one million years for the DGR, it is possible that sulfate-reducing bacteria near the bentonite-host rock interface can produce bisulfide (HS-) that can be transported to the UFC surface and potentially corrode the outer copper barrier. Therefore, it is crucial to understand HS- transport mechanisms through bentonite to assess the long-term performance of a DGR. This study aims to quantify HS- transport through bentonite using through-diffusion experiments under a range of anticipated DGR and bentonite conditions (e.g., temperature, ionic concentration, bentonite densities). In addition, as geochemical reactions/sorption are expected to affect HS- transport, batch experiments are being conducted to understand these processes independent of transport. The preliminary batch of experimental results show that ~85% of HS- was partitioned from the aqueous to solid phase within first hour and ~97% after 24 hours. However, this partitioning efficiency decreased with increased liquid-to-solid ratio because of the reduction in available reaction/sorption sites on the bentonite. This presentation shows the results from both transport and batch experiments performed on the bentonite under relevant DGR conditions.

The high sensitivity of the Visible Infrared Imaging Radiometer (VIIRS) Day Night Band (DNB) high gain stage (HGS) cannot directly use on-board calibration sources such as solar diffusers, so other calibration approaches are needed. A fully automated, NIST-traceable active point source called the Accurate Active Light Source (AALS) based on a 1-meter diameter integrating sphere illuminated with High Pressure Sodium (HPS) lamps has been developed to calibrate the VIIRS DNB HGS mode. This paper provides the theory and operation of the AALS. The AALS is housed in an environmentally controlled, moveable, enclosed trailer that protects the sphere and is being deployed in South Dakota during the summer and Mississippi during the winter. AALS Lambertian source radiance is measured by a NIST-traceable spectroradiometer. MODTRAN-based top of atmosphere (TOA) radiance is calculated using nighttime aerosol estimates and point source radiative transfer techniques that account for the VIIRS finite Point Spread Function (PSF). This new active point source complements current vicarious calibration techniques, which are based on lunar illumination of extended sources (clouds, playas, etc.), and helps improve our understanding of the point source radiative transfer needed to develop nighttime artificial light source applications. An uncertainty budget for TOA radiance indicates that accuracy under clear, moonless conditions should be comparable to daytime vicarious calibration methods. This paper shows that the major uncertainty is the ground-to-space atmospheric transmission and discusses approaches to reduce this error. Initial assessment of the VIIRS DNB HGS on the Suomi-NPP and NOAA-20 satellites are presented.

Context: A Focus on Arctic Ice Restoration Arctic ice loss has been linked to global climatic changes including droughts and wildfires and extreme winter weather. Since 1979 the Arctic has lost 75% of its ice volume, resulting in a loss of albedo that contributes significantly to global warming. Ice911’s mission is to develop and test methods to preserve and ultimately restore ice using a thin coating of high-albedo reflective materials applied to strategic areas of low-albedo ice in the Arctic, in order to reduce climate change impacts. Methods: Arctic Field Testing and Laboratory Safety Testing At Ice911’s Arctic lake test site in Ukpeagvik (Barrow), Alaska, working with UIC for science logistics and permits, a section of the winter ice was treated with 15,000 m2 of reflective hollow glass microsphere materials, using an agricultural spreader. Monitoring instrumentation included albedo and temperature measurement and cameras mounted on buoys. The treated area was observed and compared to control areas throughout the 2018 melt. Data was transmitted wirelessly and combined with on-site aerial drone footage. Laboratory safety testing and field evaluation of the fate of the materials continued, as part of the “first do no harm” obligation of the work. Results The data collection and wireless communication worked reliably in the field. Video footage taken during the melt was run through an image processing algorithm to compare albedo differential and results show higher reflectivity in areas with material applied, despite variable stream flows during the melt. The flotation for both the custom Ice911-built buoys and a purchased buoy were compromised by the variable stresses exerted during the ice melt in the lake, and improvements are being made to the Ice911 buoy design. Laboratory safety testing shows no deleterious impacts from the materials. At the field test site, after the melt the sand-like materials were blown to shore and joined the surrounding mud. Conclusion Field work, permitting, climate modeling and laboratory testing are ongoing to confirm material safety and performance and to improve deployment and monitoring, with the goal of readying the technology for a potential targeted deployment within a few years of a 10,000-100,000 km2 on sea ice at a location chosen to have a significant positive climate impact.

With the launch of the new Geostationary Operational Environmental Satellite-R (GOES-R) satellite series with the Advanced Baseline Imager (ABI) onboard both GOES-16, and -17 satellites, new capabilities are available at unprecedented temporal and spatial resolution from a geostationary-orbiting platform viewing North and South America. Measurements from three water vapor bands available from ABI presents a unique opportunity to assess the delineation in the vertical distribution of atmospheric moisture through multispectral (Red, Green, Blue, i.e., RGB) composites. Analysis of multispectral composites may provide improved capabilities to quickly identify specific features through qualitative analysis. The utilization of water vapor bands in the derivation of RGB imagery can be used to enhance thermodynamic and/or dynamical features associated with the development of significant weather events and hazards (e.g., cyclones, hurricanes, convection, turbulence) that are commonly found in single band water vapor analysis. The Air Mass RGB was developed with the launch of Meteosat Second Generation Spinning Enhanced Visible and Infrared Imager (SEVIRI) and is used to enhance regions of warm, dry, ozone rich stratospheric air associated with jet stream dynamics and tropopause folding that impact cyclone and hurricane intensity. With the launch of Himawari-8 Advanced Himawari Imager, the Japan Meteorological Agency developed a complimentary water vapor RGB, the Differential Water Vapor RGB, as a tool to assess the vertical distribution of water vapor in the atmosphere. This presentation will discuss the applications and advantages of the Air Mass and Differential Water Vapor RGB as complimentary tools for assessing thermodynamic and dynamical features associated with significant weather events.

The Array of Things (AoT) is a collaborative effort among leading scientists, universities, local government and communities in Chicago to collect real-time data on the city’s environment, infrastructure, and activity for research and public use. The AoT is composed of nodes that will measure and sense the urban environment of Chicago and provide openly accessible data in near real time. One component of each node is the ChemSense board, which uses chemical sensors to measure five gas-phase species: ozone, nitrogen dioxide, carbon monoxide, sulfur dioxide and hydrogen sulfide. In addition, the ChemSense board provides information on total reducing gases and total oxidizing gases. The nodes also include meteorological information and cameras that will provide pedestrian and traffic counts using computer vision algorithms. Because the ChemSense boards rely on low-cost sensors, characterizing the sensor responses is critical to understanding the applicability of the AoT for urban air quality issues. As a first step, a node with the ChemSense board was installed at an EPA air quality monitoring site within the City of Chicago, which is run by the Cook County Department of Environment and Sustainability. The EPA site has Federal Reference Method monitors for ozone, nitrogen dioxide and sulfur dioxide. After collecting collocation data for seven months, the results are promising for ozone, but much less so for sulfur dioxide. For nitrogen dioxide, unexplained spikes not observed in the EPA data drive a poor fit. Results from the collocation project will be used to consider larger issues for characterizing the air quality component of the AoT.

Water resources management is a non-trivial process requiring a holistic understanding of the factors driving the dynamics of human-water systems. Policy-induced or autonomous behavioral changes in human systems may affect water and land management, which may affect water systems and feedback to human systems, further impacting water and land management. Currently, hydro-economic models lack the ability to describe such dynamics either because they do not account for the multi-factor/multi-output nature of these systems, and/or are not designed to operate at a river basin scale. This paper presents a flexible and replicable methodological framework for integrating a microeconomic multi-factor/multi-output Positive Multi-Attribute Utility Programming (PMAUP) model with an eco-hydrologic model, the Soil and Water Assessment Tool (SWAT). The connection between the models occurs in a sequential modular approach through a common spatial unit, the “Hydrologic-Economic Representative Units” (HERUs), derived from the boundaries of decision-making entities and hydrologic responsive units. The resulting SWAT-PMAUP model aims to provide the means for exploring the dynamics between the behavior of socio-economic agents and their connection with the water system through water and land management. The integrated model is illustrated by simulating the impacts of irrigation restriction policies on the Río Mundo sub-basin in south-eastern Spain. The results suggest that agents’ adaptation strategies in response to the irrigation restrictions have broad economic impacts and subsequent consequences on surface and groundwater resources. We suggest that the integrated modeling framework can be a valuable tool to support decision-making in water resources management across a wide range of scales.

NOAA National Centers for Environmental Information (NCEI) hosts and provides access to one of the most significant archives on Earth, with comprehensive oceanic, atmospheric, and geophysical data. From the depths of the ocean to the surface of the sun and from million-year-old ice core records to near-real-time satellite images, NCEI is the Nation’s leading authority for environmental information. These data are impressively heterogeneous in terms of platforms, instruments, formats, and user communities. As a federal agency, NCEI must follow laws, mandates, guidance, best practices, and national and international standards. This presentation will showcase the policies that support the framework of NCEI’s data preservation and stewardship mission with a look toward current gaps and future needs for data policies.

Seawater rare earth element (REE) concentrations are increasingly applied to reconstruct water mass histories by exploiting relative changes in the distinctive normalised patterns. However, the mechanisms by which water masses gain their REE patterns are yet to be fully explained. To examine this, we collected water samples along the Extended Ellett Line (EEL), an oceanographic transect between Iceland and Scotland, and measured dissolved REE by offline automated chromatography (SeaFAST) and ICP-MS. The proximity to two continental boundaries, the incipient spring bloom coincident with the timing of the cruise, and the importance of deep water circulation in this climatically sensitive gateway region make it an ideal location to investigate sources of REE to seawater and the effects of vertical cycling and lateral advection on their distribution. The deep waters have REE concentrations closest to typical North Atlantic seawater and are dominated by lateral advection. Comparison to published seawater REE concentrations of the same water masses in other locations provides a first measure of the temporal and spatial stability of the seawater REE signature. We demonstrate the REE pattern is replicated for Iceland-Scotland Overflow Water (ISOW) in the Iceland Basin from adjacent stations sampled 16 years previously. A recently published Labrador Sea Water dissolved REE signature is reproduced in the Rockall Trough but shows greater light and mid REE alteration in the Iceland Basin, possibly due to the dominant effect of ISOW and/or continental inputs. An obvious concentration gradient from seafloor sediments to the overlying water column in the Rockall Trough, but not the Iceland Basin, highlights release of light and mid REE from resuspended sediments and pore waters, possibly a seasonal effect associated with the timing of the spring bloom in each basin. This study highlights the need for fully constrained REE sources and sinks, including the temporary nature of some sources, to achieve a balanced budget of seawater REE. In this contribution, I discuss some of the potential mechanisms and their implications for the longevity of the seawater REE signature.

In 2013, the Office of Science and Technology Policy (OSTP) issued a memorandum directing Federal agencies with over $100 million in annual research and development expenditures to develop a plan to support increased access to federally funded research results. In response, the US Geological Survey developed a Public Access Plan and published four new data management policies. The policies focus on review and approval of scientific data supporting scholarly conclusions, requirements for metadata, preservation, and data management planning. The new policies, in conjunction with the Public Access Plan, represent a shift in culture in how the USGS manages and provides access to its science data. The USGS recognizes that successful implementation of these new policies requires multiple pillars of support, from USGS leadership and staff buy-in, to effective tools. Active community engagement in the Bureau is stimulated through the Community for Data Integration (CDI), an open forum for community discussion and engagement, and an important component creating buy-in and contributing to the success of the new policies. Also critical are a suite of tools available to scientists to ensure their ability to implement the policies. Finally, support from leadership that manifests in the Fundamental Science Practices Advisory Council (FSPAC), a committee of representatives from across the Bureau who preside over policies and guidance is a critical component. While far from complete, the USGS has shifted its approach to science data management by engaging the community, offering tools to support policy, and providing leadership support for the quality and scientific integrity of USGS science data.

Shallow soil temperatures influence ecosystem carbon cycling and the temperature of deeper soil layers where permafrost thaw occurs. Vegetation affects shallow soil temperatures via impacts on the surface energy balance, hydrology, and soil characteristics. Vegetation may influence the degree to which soil temperatures rise with increases in air temperature under global climate change. However, variability in vegetative influences on soil temperature are not well quantified at a pan-Arctic scale. We compiled data from 235 sites across high latitude permafrost regions to examine the influence of air temperatures and vegetation on shallow soil temperatures. Annual thermal regimes varied across vegetation types characterized by dominant plant functional cover. The overall magnitude of soil temperature maxima and minima varied across plant functional types. Ecosystems dominated by vegetation with tall statured canopies such as evergreen needleleaf boreal forests and tall shrub tundra tended to have warmer soil warmer temperatures than tundra sites dominated short statured vegetation such as graminoid or short shrub species. Soil temperatures increased with air temperature similarly within tundra vegetation types, and rising air temperatures from global climate change may result in similar increases in soil temperatures regardless of vegetation type in the tundra. Soil temperatures were highly variable and decoupled from air temperature in boreal forest sites.

EarthResourceML (http://www.earthresourceml.org) is the international data model and standard for mineral resources data. EarthResourceML (ERML) was initially developed for the Australian Chief Government Geologists Committee (CGGC) but is now under the governance of the Commission for Geoscience Information (CGI), a commission of the International Union of Geological Sciences (IUGS). ERML/INSPIRE MR data models are the preferred standard for mineral resources data sharing initiatives and projects, such as the European Union’s INSPIRE directive, and EU-projects (Minerals4EU, ProSUM) and the Australian AuScope, and Geoscience Portal projects. The current version of ERML v2.0 was released in August 2014 and ERML v3.0 will be published 2018. Current ERML v.2.0 and INSPIRE Mineral Resource data models are practically identical. The main elements of the ERML/INSPIRE models cover mineral occurrences, mines, and mining activity. The standard describes the geological characteristics and settings of mineral occurrences, their contained commodities, and their mineral reserve, resource and endowment. It is also able to describe mineral exploration, mines and mining activities, processing/transformation activities, with the production of concentrates and refined products, and waste material characterization. ERML/INSPIRE utilises the GeoSciML v4.1 Mapped Feature model to describe spatial representations of mineral occurrences and mines, and the GeoSciML Earth Material model to describe host- and associated materials. ERML Lite v. 1.0 version was accepted and released in August 2016. The new version 2.0 of ERML Lite was published June 2018. ERML Lite 2.0 delivers a user-friendly designed and simplified flat view of key elements of the full ERML/INSPIRE data models. The CGI Geoscience Terminology Working Group (http://resource.geosciml.org/def/voc/) and INSPIRE code list register (http://inspire.ec.europa.eu/codelist/) provides a range of standard vocabularies that can be used to populate ERML/INSPIRE data services. ERML Lite test service will be demonstrated at the AGU meeting at Onegeology portal and data providers are from Oceania (AUSGIN and New Zealand), Europe (Minerals4EU, FODD, and Finland) and Arctic (60°- 90°) data (Nordic Countries, Russia, Alaska, and Canada). The ERML and ERML Lite data models enable comparison of mineral resource information from different jurisdictions. With increasing participation from geological surveys these data model will assist global resources estimates and exploration targeting.

Most of the mass loss from the Antarctic Ice Sheet occurs through glaciers and ice streams, where fast-flow is partially controlled by rapid ice deformation in the margins. Deformation drives thermomechanical and recrystallization processes that influence further deformation, a feedback which may destabilize glaciers. However, few models account for the feedback between deformation and recrystallization. We derive an idealized model for ice temperature and grain-size that partitions deformational work into dissipated heat and changes in strain and surface energy, all of which drive dynamic recrystallization. Under conditions common in glacier shear margins, we show that a large portion of deformational work is stored as elastic energy, with the remainder dissipated as heat. This result revises our current picture of the amount of heat generated in glacier shear margins and suggests that changes in internal strain through dynamic recrystallization of ice likely play an important role in facilitating fast-flowing glacial ice.

Wet bulb globe temperature (WBGT) is a widely applied heat stress index. However, most applications of WBGT within the heat stress impacts literature do not use WBGT at all, but one of the ad hoc approximations, typically the simplified WBGT (sWBGT) or the environmental stress index (ESI). Surprisingly little is known about how well these approximations work for the global climate and climate change settings that they are being applied to. Here we assess the bias distribution as a function of temperature, humidity, wind speed and radiative conditions of both sWBGT and ESI relative to a well-validated, explicit physical model for WBGT developed by Liljegren, within an idealized context and the more realistic setting of ERA5 reanalysis data. sWBGT greatly overestimates heat stress in hot-humid areas. ESI has much smaller biases in the range of standard climatological conditions. However, both metrics may substantially underestimate extreme heat especially over subtropical dry regions. These systematic biases demonstrate that sWBGT-derived estimates of heat stress and its health and labor consequences are significantly overestimated over much of the world today. We recommend discontinuing the use of sWBGT. ESI may be acceptable for assessing average heat stress or integrated impact over a long period like a year, but less suitable for health applications, extreme heat stress analysis, or as an operational index for heat warning, heatwave forecasting or guiding activity modification at workplace. Nevertheless, Liljegren’s approach should be preferred over these ad hoc approximations and we provide a Python implementation to encourage its widespread use.

Magnetotelluric exploration is one of geophysical methods for investigating the Earth’s deep interior. This method measures natural geoelectric and geomagnetic field values. Impedance is expressed by the relation between the measured electric fields and magnetic fields, and it is used to estimate the electromagnetic properties of the Earth’s deep interior. In the early stage, the geophysical responses at receiver was simply considered as responses from one-dimensional structure and the impedance was used in the form of scalar. As we consider three-dimensional structure nowadays, the impedance is mainly used in the form of matrix. Each component of the matrix is determined by various factors such as underground structure and surrounding environment. It is very important to know how these components reflect those factors since the components of the impedance are the basic information to estimate the interior of the earth. In this study, we focus on the topographic effects and correction with three-dimensional earth model for Gyeongju sites. As the Gyeongju area is surrounded by several mountains and faults, it has highly complicate topographies. However, the conventional topographic correction is not perfect for complex area because it is calculated in homogeneous earth model. In this study, we use the finite element methods using hexahedral and tetrahedral elements to examine the topographic correction method in complex topographies and three-dimensional anomalies. ACKNOWLEDGMENTS This work was supported by the Nuclear Safety Research Program through the Korea Foundation Of Nuclear Safety(KoFONS), granted financial resource from the Nuclear Safety and Security Commission(NSSC), Republic of Korea (No.1705010) and Korea Institute of Energy Technology Evaluation and Planning(KETEP) and the Ministry of Trade, Industry & Energy(MOTIE) of the Republic of Korea (No. 20168510030830).

The paper examines the essence of discrepancies between the IAGA approved PC index and the approach put forward by Stauning (2020). The IAGA endorsed PC index was designed to serve as a proxy for energy that enters into the magnetosphere during solar wind-magnetosphere coupling. It means that the ground-based PC index should be indicative of the magnetosphere state in the real time. With this aim a special “running QDC derivation” procedure has been elaborated (Troshichev et al., 2006) to determine a proper quiet daily curve (QDC) as a level of reference for evaluation of magnetic disturbances generated by solar wind. The most significant evidence of validity of the IAGA endorsed PC index is the statistically justified correspondence between the PC index changes and development of disturbances in the magnetosphere (with correlation as high as R=0.94). The alternative procedure (Stauning, 2011) also used QDC as level of reference, but this QDC does not consist with the PC index designation. The announcement (Stauning, 2020) on invalid IAGA-endorsed PC index series seems be devoid of any background.

Most faults in Iceland strike roughly parallel to the divergent plate boundary, a part of the Mid-Atlantic Rift, which would be expected to lead to primarily normal faulting. However, several studies have observed a significant component of rift-parallel strike-slip faulting in Iceland. To investigate these fault kinematics, we use the boundary element method to model fault slip and crustal stress patterns of the Icelandic tectonic system, including a spherical hotspot and uniaxial stress that represents rifting. On a network of faults, we estimate the slip required to relieve traction imposed by hotspot inflation and remote stress and compare the model results with observed slip kinematics, crustal seismicity, and geodetic data. We note a good fit between model-predicted and observed deformation metrics, with both indicating significant components of normal and strike-slip faulting as well as consistency between recent data and longer-term records of geologic fault slip. Possible stress permutations between steeply plunging σ1 and σ2 axes are common in our models, suggesting that localized stress perturbations may impact strike-slip faulting. Some increases in model complexity, including older hotspot configurations and allowing fault opening to simulate dike intrusion, show improvement to model fit in select regions. This work provides new insight into the physical mechanisms driving faulting styles within Iceland away from the current active plate boundary, implying that a significant portion of observed strike-slip faulting is likely caused by the combined effects of tectonic rifting, hotspot impacts, and mechanical interactions across the fault network.

Extreme weather events are triggered by atmospheric circulation patterns and shaped by slower components, including soil moisture and sea-surface temperature, and by the background climate. This separation of factors is exploited by the storyline approach where an atmosphere model is nudged toward the observed dynamics using different climate boundary conditions to explore their influence. The storyline approach disregards rather uncertain climatic changes in the frequency and intensity of dynamical conditions, but focuses on the thermodynamic influence of climate on extreme events. Here we demonstrate an advanced storyline approach that employs a coupled climate model (AWI-CM-1-1-MR) where the large-scale free-troposphere dynamics are nudged toward ERA5 data. Five-member ensembles are run for present-day (2017–2019), pre-industrial, +2K, and +4K climates branching off from CMIP6 historical and scenario simulations of the same model. In contrast to previous studies, which employed atmosphere-only models, feedbacks between extreme events and the ocean and sea-ice state, and the dependence of such feedbacks on the climate, are consistently simulated. Our setup is capable of reproducing observed anomalies of relevant unconstrained parameters, including near-surface temperature, cloud cover, soil moisture, sea-surface temperature, and sea-ice concentration. Focusing on the July 2019 European heatwave, we find that the strongest warming amplification expands from southern to central Europe over the course of the 21st century. The warming reaches up to 10 K in the 4K warmer climate, suggesting that an analogous event would entail peak temperatures around 50 ºC in central Europe.

Soil carbon cycling and ecosystem functioning can strongly depend on how microbial communities regulate their metabolism and adapt to changing environmental conditions to improve their fitness. Investing in extracellular enzymes is an important strategy for the acquisition of resources, but the principle behind the trade-offs between enzyme production and growth is not entirely clear. Here we show that the enzyme production rate per unit biomass may be regulated in order to maximize the biomass specific growth rate. Based on this optimality hypothesis, we derive mathematical expressions for the biomass specific enzyme production rate and the microbial carbon use efficiency, and verify them with experimental observations. As a result of this analysis, we also find that the optimal enzyme production rate decays hyperbolically with the soil organic carbon content. We then show that integrating the optimal extracellular enzyme production into microbial models may change considerably soil carbon projections under global warming, underscoring the need to improve parameterization of microbial processes.