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Fact sheet explaining the process of drilling a test hole to collect data for the North Dakota CarbonSAFE project. North Dakota CarbonSAFE is an Energy & Environmental Research Center project, conducted in partnership with the U.S. Department of Energy.
Although the probability of Earth microbes growing (dividing) in the Martian environment is extremely low, the probability of their survival on the Martian surface is unknown. During the course of landed missions to Mars terrestrial microbes may reach the surface of Mars via inadequately sterilized spacecraft landers, rovers, or through accidental impact of orbiters. This investigation studied the potential for Earth microbes to survive in the windblown dust on the surface of Mars. The rationale for the study comes from the fact that Mars regularly has huge dust storms that engulf the planet, shading the surface from solar UV radiation. These storms serve as a mechanism for global transfer of dust particles. If live organisms were to be transported to the surface of Mars they could be picked up with the dust during a dust storm and transported across the planet. Washed, dried spores of Bacillus subtilis strain HA 101 were aseptically mixed with sterile sieved (size range of 1-5microns) Mars soil standard (obtained from NASA Johnson Space Center, Houston, Texas, USA), or Fe-montmorillonite such that the number of microbes equals 5 x 10(exp 6)/g dry wt soil. The microbe soil mixture was placed in a spherical 8 L Mars simulation chamber equipped with a variable speed rotor, gas ports and an Oriel deuterium UV lamp emitting light of wave lengths 180-400 nm. The chamber was sealed, flushed with a simulated Martian atmosphere (96.9% CO2, 3% O2, 0.1% H2O), and the pressure brought to 10 torr. The lamp and rotor were switched on to begin the experiment. Periodically samples were collected from the chamber, and the numbers of microbial survivors g soil was determined using plate counts and the most probable number method (MPN). The data indicate that Bacillus subtilis spores dispersed with Mars analog soil in a Mars atmosphere (wind blown dust) survive exposure to 5.13 KJ m-2 UV radiation, suggesting that Mars wind blown dust has potential to the protect microbes from solar UV radiation.
This data package contains CO2 response (ACi) gas exchange and fitted Vcmax and Jmax parameters measured on sunlit canopy trees within the NGEE Tropics sites Parque Natural Metropolitano (PA-PNM) and Bosque Protector San Lorenzo (PA-SLZ) in Panama. Measurements were taken on a monthly basis from February to May of 2016. This data was collected as part of the 2016 El Niño-Southern Oscillation (ENSO) campaign. Included in this data package are two Excel files with data (2016ENSO_Panama_ACi, 2016ENSO_Panama_Fitted_Vcmax_Jmax) and three Excel files with associated metadata. Also included is a Word document (Metadata_description_2016_ENSO_Panama) with details such as data collection methods, equipment used, and site information and a pdf (NGEE_Tropics_ENSO_Aci_Protocol_V2). See related datasets for further sample details, leaf water potential, LMA, leaf spectra, diurnal gas exchange and leaf chemistry. VERSION 2 update. The identification of a species from the PNM site has been corrected as follows: the identification of the tree initially identified as Pseudosamanea guachapele (ALBIED) has been revised to Albizia adinocephala (ALBIAD). The updated data package includes revised data, metadata and protocol documents updated to reflect this change.
There is a need for a sensor at the airport that can remotely detect, identify, and track wind shears near the airport in order to assure aircraft safety. To determine the viability of a laser wind-shear system, the NASA pulsed coherent Doppler CO2 lidar (Jelalian et al., 1972) was installed in a semitrailer van with a rooftop-mounted hemispherical scanner and was used to monitor thunderstorm gust fronts. Wind shears associated with the gust fronts at the Kennedy Space Center (KSC) between 5 July and 4 August 1978 were measured and tracked. The most significant data collected at KSC are discussed. The wind shears were clearly visible in both real-time velocity vs. azimuth plots and in postprocessing displays of velocities vs. position. The results indicate that a lidar system cannot be used effectively when moderate precipitation exists between the sensor and the region of interest.
Calibrated pressure measurements for species with mass-to-charge ratios up to 50 amu/e(-) were obtained trom the shuttle upper atmosphere mass spectrometer experiment during re-entry on the STS-35 mission. The principal experimental objective is to obtain measurements of freestream density in the hypersonic rarefied flow flight regime. Data were collected from 180 to about 87 km. However, data above 115 km were contaminated from a source of gas emanating from pressure transdueers connected in parallel to the mass spectrometer. At lower altitudes, the pressure transducer data are compared to the mass spectrometer total pressure with excellent agreement. Near the orifice entrance, a significant amount of CO2 was generated from chemical reactions. The freestream density in the rarefied flow flight regime is calculated using an orifice pressure coefficient model based upon direct simulation Monte Carlo results. This density, when compared with the 1976 U.S. Standard Atmosphere model, exhibits the wavelike nature seen on previous flights using accelerometry. Selected spectra are presented at higher altitudes (320 km) showing the effects of the ingestion of gases from a forward fuselage fuel dump.
The CheMin instrument on the Mars Science Laboratory (MSL) rover Curiosity uses a Co tube source and a CCD detector to acquire mineralogy from diffracted primary X-rays and chemical information from fluoresced X-rays. CheMin has been operating at the MSL Gale Crater field site since August 5, 2012 and has provided the first X-ray diffraction (XRD) analyses in situ on a body beyond Earth. Data from the first sample collected, the Rocknest eolian soil, identify a basaltic mineral suite, predominantly plagioclase (approx.An50), forsteritic olivine (approx.Fo58), augite and pigeonite, consistent with expectation that detrital grains on Mars would reflect widespread basaltic sources. Minor phases (each <2 wt% of the crystalline component) include sanidine, magnetite, quartz, anhydrite, hematite and ilmenite. Significantly, about a third of the sample is amorphous or poorly ordered in XRD. This amorphous component is attested to by a broad rise in background centered at approx.27deg 2(theta) (Co K(alpha)) and may include volcanic glass, impact glass, and poorly crystalline phases including iron oxyhydroxides; a rise at lower 2(theta) may indicate allophane or hisingerite. Constraints from phase chemistry of the crystalline components, compared with a Rocknest bulk composition from the APXS instrument on Curiosity, indicate that in sum the amorphous or poorly crystalline components are relatively Si, Al, Mg-poor and enriched in Ti, Cr, Fe, K, P, S, and Cl. All of the identified crystalline phases are volatile-free; H2O, SO2 and CO2 volatile releases from a split of this sample analyzed by the SAM instrument on Curiosity are associated with the amorphous or poorly ordered materials. The Rocknest eolian soil may be a mixture of local detritus, mostly crystalline, with a regional or global set of dominantly amorphous or poorly ordered components. The Rocknest sample was targeted by MSL for "first time analysis" to demonstrate that a loose deposit could be scooped, sieved to <150 microns, and delivered to instruments in the body of the rover. A drilled sample of sediment in outcrop is anticipated. At the time of writing this abstract, promising outcrops are in range and this talk will provide an update on data collected with the CheMin instrument.
We present an interactive data collection to aggregate, understand, and disseminate the data that are publicly available to support offshore GCS which can be leveraged by stakeholders to understand where GCS may be viable offshore, create GCS project analogs, and address challenges to GCS in offshore environments. The Offshore Geologic Carbon Storage Data Collection is an Experience Builder web application of multiple web mapping applications, aggregated into a single tool for each data type for access, visualization, and exploration. We also present a spatial inventory of global offshore GCS efforts to visualize the scale and locations of actualized and potential offshore GCS. It includes project location, project type and stage, CO2 storage resource potential, injection rate, reservoir and seal geology, and key literature references. Quantitative and qualitative comparisons of the distribution and magnitude of projects by their attributes lends spatial insight into the status of global GCS operations and storage resource potential, thereby enabling comparative assessments and cross-cutting knowledge transfer for projects in development. These datasets illuminate trends in ongoing offshore projects and can be leveraged by stakeholders to estimate storage resources, identify subsurface analogs, review regulations, and address challenges to offshore GCS. Additionally, opportunities for concurrent decarbonization strategies can be identified.
We present an interactive data collection to aggregate, understand, and disseminate the data that are publicly available to support offshore GCS which can be leveraged by stakeholders to understand where GCS may be viable offshore, create GCS project analogs, and address challenges to GCS in offshore environments. The Offshore Geologic Carbon Storage Data Collection is an Experience Builder web application of multiple web mapping applications, aggregated into a single tool for each data type for access, visualization, and exploration. We also present a spatial inventory of global offshore GCS efforts to visualize the scale and locations of actualized and potential offshore GCS. It includes project location, project type and stage, CO2 storage resource potential, injection rate, reservoir and seal geology, and key literature references. Quantitative and qualitative comparisons of the distribution and magnitude of projects by their attributes lends spatial insight into the status of global GCS operations and storage resource potential, thereby enabling comparative assessments and cross-cutting knowledge transfer for projects in development. These datasets illuminate trends in ongoing offshore projects and can be leveraged by stakeholders to estimate storage resources, identify subsurface analogs, review regulations, and address challenges to offshore GCS. Additionally, opportunities for concurrent decarbonization strategies can be identified.
We present an interactive data collection to aggregate, understand, and disseminate the data that are publicly available to support offshore GCS which can be leveraged by stakeholders to understand where GCS may be viable offshore, create GCS project analogs, and address challenges to GCS in offshore environments. The Offshore Geologic Carbon Storage Data Collection is an Experience Builder web application of multiple web mapping applications, aggregated into a single tool for each data type for access, visualization, and exploration. We also present a spatial inventory of global offshore GCS efforts to visualize the scale and locations of actualized and potential offshore GCS. It includes project location, project type and stage, CO2 storage resource potential, injection rate, reservoir and seal geology, and key literature references. Quantitative and qualitative comparisons of the distribution and magnitude of projects by their attributes lends spatial insight into the status of global GCS operations and storage resource potential, thereby enabling comparative assessments and cross-cutting knowledge transfer for projects in development. These datasets illuminate trends in ongoing offshore projects and can be leveraged by stakeholders to estimate storage resources, identify subsurface analogs, review regulations, and address challenges to offshore GCS. Additionally, opportunities for concurrent decarbonization strategies can be identified.
Here we evaluate if electromagnetic (EM) geophysical methods for monitoring geologic carbon storage (GCS) efforts at the Wyoming CarbonSAFE project adjacent to the Dry Fork Station power plant near Gillette, Wyoming. This first involved acquiring both electric and magnetic fields at eleven different locations ranging in distance from immediately adjacent to 4 km from the plant. Passive EM measurements were made to provide spectral EM noise measurements generated by electricity production at the plant and to determine if useful magnetotelluric (MT) data can be successfully collected in the region. The processed data indicate that useful MT data can be collected as long as the site is located more than 2km away from the power plant as well as active roads and rail lines. Controlled source EM data were collected using three different source configurations, two of which connected to steel casings used to complete the injection wells. Comparing the EM noise measurements to the CSEM data show measurable electric and magnetic field signals at all sites. Next a series of three-dimensional (3D) numerical models were built that simulate resistivity changes caused by the proposed CO2 injection at depths ranging from 2.4 to 3.0km. These models were used to simulate various EM measurement configurations. The modeling shows that casing-source CSEM monitoring can provide sensitivity to the injected CO 2 if source electrodes are connected to the bottom of one or both of the injection wells.
LongRunMIP is the first collection of millennial-length simulations of complex coupled climate models and enables investigations of how these models equilibrate in response to radiative perturbations.We present a model intercomparison project, LongRunMIP, the first collection of millennial-length (1000+ year) simulations of complex coupled climate models with a representation of ocean, atmosphere, sea ice, and land surface, and their interactions. Standard model simulations are generally only a few hundred years long. However, modeling the long-term equilibration in response to radiative forcing perturbation is important for understanding many climate phenomena, such as the evolution of ocean circulation, time-and temperature-dependent feedbacks, and the differentiation of forced signal and internal variability. The aim of LongRunMIP is to facilitate research into these questions by serving as an archive for simulations that capture as much of this equilibration as possible. The only requirement to participate in LongRunMIP is to contribute a simulation with elevated, constant CO2 forcing that lasts at least 1000 years. LongRunMIP is a MIP of opportunity in that the simulations were mostly performed prior to the conception of the archive without an agreed-upon set of experiments. For most models, the archive contains a preindustrial control simulation and simulations with an idealized (typically abrupt) CO2 forcing. We collect 2D surface and top-of-atmosphere fields, and 3D ocean temperature and salinity fields. Here, we document the collection of simulations and discuss initial results, including the evolution of surface and deep ocean temperature and cloud radiative effects. As of summer 2019, the collection includes 50 simulations of 15 models by 10 modeling centers. The data of LongRunMIP are publicly available. We encourage submission of more simulations in the future.
The Southern States Energy Board (SSEB) managed the overall Southeast Regional Carbon Sequestration Partnership (SECARB) Phase III project and The Bureau of Economic Geology (BEG), at the University of Texas at Austin, managed all activities associated with the Early Test field site near Cranfield, Mississippi (the Early Test or Cranfield Project). The SECARB project at Cranfield was focused downdip of the oil rim and on demonstrating the stacked nature of the storage potential at this location: enhanced oil recovery (EOR) up-dip and saline downdip. Because the injection for EOR continued after the SECARB project ended, no actual post-injection period occurred. However, information collected during the SECARB-monitored injection period, including pressure and CO2 plume position, was utilized in an EOR carbon lifecycle assessment. The carbon lifecycle assessment provided insight on tracking injection fronts and production efficiencies across the field. To complete the post injection assessment, taking into account the continuing EOR period after closeout of SECARB field activities, this report provides data and analysis done under another DOE-funded project. The follow up project focused on the carbon lifecycle of EOR and included an assessment of EOR at as-operated and under possible future scenarios. This work was published by Hossieni et al. (2018) and Hosseininoosheri (2019).
Introduction: Given the long time intervals required for data transmission to and from ocean worlds targets, low bandwidth for data transmission, time required for data processing and analysis, and potentially extreme radiation environments (e.g., Europa), it is clear that ocean worlds missions will need more autonomous flight instruments and software in order to achieve established science goals. Protracted time intervals for data analysis (e.g., Europa Lander) strongly motivates the development of rapid, consistent and streamlined methods for interpreting data from flight mass spectrometers to e.g., determine how mass spectra from a plume or surface liquid/ice relates to the surface/subsurface. Since mass spectrometry also has the potential to correctly identify biosignatures[1], it is imperative that such methods for interpreting data are consistent and accurate. We used 848 isotope ratio mass spectra from laboratory analyses of CO2 that interacted with ocean worlds-relevant seawaters as a ‘training’ dataset for ‘unsupervised’ machine learning. In unsupervised learning, characteristics of the data are not labeled or linked, and any similarities found only result from the neural network. CO2 isotopologues analyzed for this dataset mimic the remote measurements of CO2 by a flight mass spectrometer, and are detailed in Theiling [2]. From this dataset, we used measured features of the spectra, such as retention time, intensity, and (isotopologue) mass ratios as inputs for our autoencoder neural network. Our neural network was trained to find similarities in these and other spectral features for seawaters of a particular composition and amount of initial CO2. Successful training then created an output of these similarities for various seawaters, which included MgSO4, Na2SO4, NaCl, MgCl2, KCl, and NaHCO3, and combinations of these salts. We then applied dimensionality reduction techniques such as Principal Component Analysis (PCA), T-Distributed Stochastic Neighbor Embedding (TSNE), and Uniform Manifold Approximation and Projection (UMAP) to demonstrate latent data features as a two-dimensional projection in a unitless, high-dimensional space. In this projection, a data point represents the combined effect of spectral features such as intensity, retention time, and isotope ratio. Our initial UMAP demonstrates data clustering (organization of the data by the neural network) based on the amount of CO2 that had initially interacted with each seawater. Further training using more ‘supervised’ learning techniques demonstrate strong clustering of preliminary data based on initial CO2 concentration, seawater chemical composition, and ionic strength (salinity). Our preliminary work therefore suggests that machine learning has the potential to identify compositional variants of an ocean world seawater based on mass spectra from volatile CO2 measurements. Acknowledgments: This work was funded through a Strategic Task Group at NASA Goddard Space Flight Center. The training dataset was collected through funding from the Oklahoma Space Grant Consortium. References: [1] Pappalardo, R. et al. (2013) Astrobiology, 13, 740–773. [2] Theiling (2020) Icarus, 114216.
This data package contains Photosynthetic CO2 response (ACi curves) and Light Response (AQ) of mature sunlit canopy leaves of 11 species from PA-SLZ, February 2020. Branches were cut from the top of the canopy and re-cut under water. Fitted Vcmax and Jmax photosynthetic parameters were derived from measured data as well as the convexity, light use efficiency and apparent quantum yield. This data was collected as a collaboration between Brookhaven National Laboratory (BNL) and Pacific Northwest National Laboratory (PNNL), and is a subset of the 2020 BNL Panama campaign. The species included in this dataset are: Apeiba membranacea, Carapa guianensis, Cespedesia spathulate, Jacaranda copaia, Lonchocarpus heptaphyllus, Pera arboea, Pourouma bicolore, Symphonia globulifera, Tachigali versicolor, Tapirira guianensis, and Virola sebifera. The files included in this data package are in .csv and .pdf format, with two Excel files containing additional metadata.
The 2003 opportunity has the potential to carry out for the first time in Mars exploration history, coordinated measurements from the surface and from orbit that can address fundamental issues associated with the Martian global circulation and climate system. Coordinated measurements are defined here to mean collecting meteorological data from a network of 12-16 globally distributed surface stations simultaneously with an orbiter carrying an atmospheric sounder. With such measurements it is possible to define the horizontally varying (barotropic) and vertically varying (baroclinic) components of the global circulation from which the full 3-dimensional horizontal wind field can be reconstructed. It is also possible to precisely define the CO2 cycle, the main component of the current climate system. InterMarsNet, as currently envisioned, consists of 3-4 landers with a supporting communications orbiter that may carry some instrumentation. The landers are likely to touch down in low latitudes and will probably be configured to optimize seismological objectives. We propose to augment the InterMarsNet meteorological objectives by flying an additional 10-15 "MicroMet" landers equipped to measure surface pressure and nothing else. Surface pressure is the most fundamental meteorological parameter and it is the easiest to measure. The sensors are light, operate with minimal power, and do not require orientation or deployment. Consequently the landers can be very small (< 10 kg) and 10-15 of them can be delivered by a Med-lite launcher. This would enable global network science for meteorology and, when combined wAh the more sophisticated measurements from the InterMarsNet landers and the simultaneous temperature and dust profiling measurements from an atmospheric sounder aboard the orbiter, it would enable us to reconstruct global scale circulation patterns.
Sedimentary basins comprise extensive porous sandstone and carbonate reservoirs capable of hosting economically significant greenfield and brownfield residual oil zones (ROZs). Several basins in the United States, including the intracratonic Illinois Basin (ILB), have stacked, predominantly siliciclastic ROZs that are potential targets for tertiary recovery of petroleum and for storing large volumes of anthropogenic carbon in the subsurface. The rocks in these basins share facies and depositional settings with many reservoirs that have already been major producers in primary production and, in some cases, as carbon dioxide enhanced oil recovery (CO 2 -EOR)targets. The lessons learned from field data collection and testing of these intervals in a basin like the ILB have broad applications to analogous basins with potential ROZs.
This data set reports the results of elemental analyses of foliar and stem/woody twig plant tissues collected from within the experimental treatment plots at the SPRUCE Experiment Site since 2017. Tissue samples for plant collections from the SPRUCE experimental plots are used to characterize the chemical (elemental) characteristics of plants in the bog, both prior to and following the initialization of the SPRUCE experimental warming and CO2 treatments. The experimental work was conducted in a Picea mariana [black spruce] – Sphagnum spp. bog forest in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF).
Cyanobacteria are photosynthetic organisms capable of high growth rate and represent a promising bioplatform for harnessing the sun’s energy to make biofuel. Additionally, the process of photosynthesis absorbs CO2 from the environment. Understanding the metabolic processes involved in photosynthesis could lead to solutions to the recent rise of CO2 concentration in Earth’s atmosphere and the associated climate change. More research on the transcriptional regulation of these cells is needed to learn how to harness the untapped potential of cyanobacteria for these applications. Transcriptional analysis via RNA-seq provides an understanding of how gene expression changes at the mRNA level under diverse growing conditions. I systematically collected and analyzed RNA-Seq data obtained under a variety of conditions and available on the NCBI database for three cyanobacteria model organisms: Synechococcus elongatus sp. PCC 7942, Synechococcus sp. PCC 7002, and Synechocystis sp. PCC 6803. For each organism, the data was mapped to a reference genome to characterize the RNA expression profile. Samples were checked for quality based on the number of reads and the correlation of the expression profile between labeled replicates. All samples were transformed into transcripts per million reads, followed by a log transformation to account for the wide range of sample sizes. Gene co-expression networks were generated and analyzed for each species using Cytoscape. These networks provide a base level of gene expression for each species. The network topology and high-betweeness nodes of these networks need to be analyzed further to provide insight on potential ways to harness cyanobacteria genetics. Additionally, these datasets can be used together to form a core genome network analysis- one that includes only the genes that are homologous between the three species. This project has prepared the way for a more in-depth study on photosynthetic microbes on a genetic level.