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Data for The Value of Reversible Carbon Storage in a Zero-Emissions World
Atmospheric carbon dioxide removal (CDR) is required to stabilize global temperature. CDR can be achieved via ecosystem-based approaches that are cost-effective but reversible (e.g., soil and forest management) or by more durable but expensive approaches (e.g., direct air capture coupled with geologic storage). Here, we examine trade-offs between these approaches, focusing on timing, climate impacts, and cost. We simulated reversible carbon accrual for a range of CDR contract structures using a general minimalist model of ecosystem carbon cycling, and parameterized it to simulate US agricultural soil management─specifically cover cropping─as a case study. We then quantified the resulting impact on atmospheric carbon and global temperature using a climate model emulator. We find that maintaining a patchwork of reversible CDR projects by replacing lapsed projects with new projects can reduce warming by 22–195 μ°C in 2100 and that the magnitude of this cooling effect depends on how effectively the patchwork is maintained. Long-term maintenance of reversible CDR projects requires institutional stability that cannot be guaranteed over multiple decades. Consequently, effective CDR ultimately requires replacing reversible projects with durable projects. To address this problem, we modeled the cost of replacing reversible agricultural soil CDR with geologic CDR. We found that using reversible CDR as a bridge to durable CDR is potentially more cost-effective as a global cooling strategy (0.20–0.81 billion USD per μ°C avoided) than perpetual maintenance of reversible CDR (0.32–1.31 billion USD per μ°C avoided) or an immediate transition to durable CDR (1.37–2.19 billion USD per μ°C avoided). However, we emphasize that institutional commitments to maintain reversible CDR projects cannot be guaranteed. Reliance on reversible CDR as a bridge to durable CDR therefore carries an unknown amount of risk and will only function if efforts to maintain reversible CDR are robust.
Hexadecimal to decimal conversion tables for hexadecimal values 0-3F,FFFF - Decimal values 0-262,143
Hexadecimal to decimal system conversion tables for advanced orbital programming systems
Temperature dependence of heat capacity at constant pressure and calculation of thermodynamic values. II. Calculations of thermodynamic values and equilibrium constants of the chemical reactions
Approximate formulas for calculating thermodynamic characteristics and equilibrium constants of chemical reactions
Two-dimensional, parabolic boundary value problems as the limiting case of one- dimensional boundary value problems
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The Economic Value of Remote Sensing of Earth Resources from Space: An ERTS Overview and the Value of Continuity of Service. Volume 1: Summary
An overview of the ERTS program is given to determine the magnitude of the benefits that can be reasonably expected to flow from an Earth Resources Survey (ERS) Program, and to assess the benefits foregone in the event of a one or two-year gap in ERS services. An independent evaluation of the benefits attributable to ERS-derived information in key application areas is presented. These include two case studies in agriculture-distribution, production and import/export, and one study in water management. The cost-effectiveness of satellites in an ERS system is studied by means of a land cover case study. The annual benefits achieveable from an ERS system are measured by the in-depth case studies to be in the range of $430 to $746 million. Benefits foregone in the event of a one-year gap in ERS service are estimated to be $147 to $220 million and $274 to $420 million for a two-year gap in ERS service.
The economic value of remote sensing of earth resources from space: An ERTS overview and the value of continuity of service. Volume 3: Intensive use of living resources: Agriculture. Part 1: Overview
Potential economic benefits obtainable from a state-of-the-art ERS system in the resource area of intensive use of living resources, agriculture, are studied. A spectrum of equal capability (cost saving), increased capability, and new capability benefits are quantified. These benefits are estimated via ECON developed models of the agricultural marketplace and include benefits of improved production and distribution of agricultural crops. It is shown that increased capability benefits and new capability benefits result from a reduction of losses due to disease and insect infestation given ERS's capability to distinguish crop vigor and from the improvement in world trade negotiations given ERS's worldwide surveying capability.
The economic value of remote sensing of earth resources from space: An ERTS overview and the value of continuity of service. Volume 6: Land use. Part 1: Introduction and overview
The utility of an ERS system as an effective tool in land use management is analyzed. The potential new capabilities of a space based ERS system are qualitatively examined. A variety of resource management functions are postulated within which ERTS activities might occur and the present ERS investigations in these areas are outlined.
The economic value of remote sensing of earth resources from space: An ERTS overview and the value of continuity of service. Volume 6: Land use. Part 2: The role of ERTS in the establishment and updating of a nationwide land cover information system
The utility of an ERS system as an effective tool in land use management is analyzed. The cost effectiveness of satellites as a component of an ERS system is presented based on various projected levels of demand. It is indicated that a cost savings potential of $7.9 to $37.1 million annually is attributable to the inclusion of ERS-like satellites in the ERTS system.
The economic value of remote sensing of earth resources from space: An ERTS overview and the value of continuity of service. Volume 7: Nonreplenishable natural resources: Minerals, fossil fuels and geothermal energy sources
The application of remotely-sensed information to the mineral, fossil fuel, and geothermal energy extraction industry is investigated. Public and private cost savings are documented in geologic mapping activities. Benefits and capabilities accruing to the ERS system are assessed. It is shown that remote sensing aids in resource extraction, as well as the monitoring of several dynamic phenomena, including disturbed lands, reclamation, erosion, glaciation, and volcanic and seismic activity.
The economic value of remote sensing of earth resources from space: An ERTS overview and the value of continuity of service. Volume 9: Oceans
The impact of remote sensing upon marine activities and oceanography is presented. The present capabilities of the current Earth Resources Technology Satellite (ERTS-1), as demonstrated by the principal investigators are discussed. Cost savings benefits are quantified in the area of nautical and hygrographic mapping and charting. Benefits are found in aiding coastal zone management and in the fields of weather (marine) prediction, fishery harvesting and management, and potential uses for ocean vegetation. Difficulties in quantification are explained, the primary factor being that remotely sensed information will be of greater benefit as input to forecasting models which have not yet been constructed.
The economic value of remote sensing of earth resources from space: An ERTS overview and the value of continuity of service. Volume 10: Industry
The economic benefits of an ERS system in the area of industrial resources are discussed. Contributions of ERTS imagery to the improvement of shipping routes, detection of previously unknown and potentially active faults in construction areas, and monitoring industrial pollution are described. Due to lack of economic research concerning the subject of ERS applications in this resource area the benefit estimations reported are regarded as tentative and preliminary.
Organic S13C values vary slightly with salinity in microbial mats at Guerrero Negro, Baja California Sur, Mexico: Implications for stromatolite S13C values
Stromatolites, layered sedimentary rock structures produced by communities of microorganisms, constitute the most abundant early evidence of life on Earth. Microbial mats, which are found most frequently in hypersaline marine or hot spring environments, serve as useful modern analogs of stromatolitic communities. Biochemical studies of mats were conducted to assist in the interpretations of stromatolites. The data suggest that salinity effects are insufficient by themselves to cause the C-13 differences observed betwwen Precambrain stromatolites and modern microbial mats.
A Review of Value of Solar Studies In Theory and In Practice
This brief summarizes a collection of state- and utility-commissioned value-of-solar (VoS) studies and related literature, with a focus on who commissioned the study, which value and cost categories were discussed and/or quantified, and the methods used. Our objective is to compile information on prior VoS studies to inform state regulators and other stakeholders that may pursue related studies or integrate findings into rate design. The brief is organized into three parts: 1) an introduction to distributed solar photovoltaic (DPV) compensation; 2) a review of theoretical research on VoS; and 3) a review of VoS studies. The vast majority of VoS studies have served an informational role of quantifying the net benefits of PV. Three studies were commissioned in states or utility service territories that subsequently implemented VoS tariffs in California, New York, and Austin, Texas. When applied as a tariff, VoS aims to compensate PV output as efficiently as possible by doing so at rates that reflect the marginal benefits and costs of PV through value and cost categories that may vary temporally and/or geographically. This could lead to higher compensation in locations and times where more PV output is more valuable and consequently drive adoption in those locations to provide more societal benefits. Value and cost factors can be broadly grouped into five categories: generation, transmission, distribution, other utility, and other social categories. Those conducting VoS studies must weigh various tradeoffs when deciding which categories to include and quantify. Tradeoffs include prioritizing values based on their magnitude of value or cost impact, as well as taking into account the feasibility of data collection and accurate quantification. Values of higher magnitude and estimation feasibility are quantified in the majority of studies, including the earliest of studies conducted in the 2000s and 2010s. Additionally, some values of higher magnitude but low feasibility in the earliest of studies have become quantifiable in recent years. There are some values with low average system-wide levels but very high magnitude in specific locations or hours. The value magnitude in some cases can be tied to DPV penetration with low value in areas with little congestion and/or low penetration and vice versa. In these cases, values that are easier to quantify are often incorporated, while those that are more difficult are often addressed via a placeholder value. The placeholder value is paired with a discussion around data needs and methods to improve future estimates, as well as a conversation about when these value categories may increase in magnitude and necessitate more rigorous quantification. This brief summarizes findings from two meta-analyses of VoS studies that took place between 2005 and 2018, as well as findings from four additional studies published from 2018 to 2023. Table ES-1 summarizes the various value and cost categories included in each respective study and whether they were quantified, discussed, or omitted. Values such as avoided energy, capacity, transmission capacity, line losses, and avoided environmental costs are quantified in every study. Some categories were deemed harder to quantify and less impactful at the time of the study, so they were discussed but not quantified (e.g., ancillary services). Other categories, including many at the distribution level, were very locationally and/or temporally specific and dependent on high DPV penetration. These were sometimes quantified and at other times discussed. Notably, when it came to utility costs, integration costs were discussed in all cases, though they were deemed to have a small impact. Other utility costs were omitted for the most part; however, the utility-commissioned study (by NorthWestern Energy in Montana) included both lost utility revenue and programmatic/administrative cost categories. While there are some similarities across studies, each had fairly unique methods that are detailed in the body of this brief.
GPS FOM Chimney Analysis using Generalized Extreme Value Distribution
Many a time an objective of a statistical analysis is to estimate a limit value like 3-sigma 95% confidence upper limit from a data sample. The generalized Extreme Value Distribution method can be profitably employed in many situations for such an estimate. . .. It is well known that according to the Central Limit theorem the mean value of a large data set is normally distributed irrespective of the distribution of the data from which the mean value is derived. In a somewhat similar fashion it is observed that many times the extreme value of a data set has a distribution that can be formulated with a Generalized Distribution. In space shuttle entry with 3-string GPS navigation the Figure Of Merit (FOM) value gives a measure of GPS navigated state accuracy. A GPS navigated state with FOM of 6 or higher is deemed unacceptable and is said to form a FOM 6 or higher chimney. A FOM chimney is a period of time during which the FOM value stays higher than 5. A longer period of FOM of value 6 or higher causes navigated state to accumulate more error for a lack of state update. For an acceptable landing it is imperative that the state error remains low and hence at low altitude during entry GPS data of FOM greater than 5 must not last more than 138 seconds. I To test the GPS performAnce many entry test cases were simulated at the Avionics Development Laboratory. Only high value FoM chimneys are consequential. The extreme value statistical technique is applied to analyze high value FOM chimneys. The Maximum likelihood method is used to determine parameters that characterize the GEV distribution, and then the limit value statistics are estimated.
Redefining fuel heating value for engines: Accounting for heat of vaporization
Defining a fuel's heating value (i.e., energy content) is fundamental for calculating engine efficiency and for life cycle analysis comparisons between different fuels. Traditional definitions of lower heating value and higher heating value account for the effect of water vapor versus liquid water in the exhaust, which is important when the fuel is used in a furnace or boiler. In an engine, it is equally important to properly account for the energy required to vaporize liquid fuel. Heat of vaporization has a small effect for common hydrocarbon fuels, typically less than 1% of lower heating value, but the effect is much larger for other important fuels such as ethanol (3.4% of lower heating value) and methanol (5.9% of lower heating value). This paper defines a new type of fuel heating value that more accurately reflects the useful fuel energy content for engines. Vaporized heating value is defined as the heating value when starting with a vaporized fuel instead of a liquid fuel. It can be calculated by adding the fuel's heat of vaporization to the traditional lower heating value. This paper illustrates the rationale and benefits of using vaporized heating value using data from the literature.
Empirical Indicators of Transmission Value in the Southeast United States
Concurrent differences in energy price between different parts of the electric grid are a key indicator of the value of additional transmission. In areas without a wholesale electricity market, such as the Southeast, an alternative indicator to price is the Federal Energy Regulatory Commission’s (FERC) system lambda data. This economic metric represents the minimized marginal production costs of thermal generators, including fuel and other variable operation and maintenance expenses. Balancing Authorities report a single system lambda for their entire balancing area. Most Southeastern lambdas exhibit sufficient price variation to support a transmission valuation analysis, although incomplete accounting of congestion costs or scarcity rents during peak load hours may underestimate the true value of transmission capacity. With transmission value defined as the annual average hourly absolute price difference between two regions and FERC’s system lambda data used as a price proxy, we find the following results in the Southeast region during 2012-2023 (reported in $\$2024$/MWh): Intra‐regional findings: Annual averages historically span $\$2$–$\$28$/MWh and average $\$12$/MWh in SERTP and span $\$4$–$\$19$/MWh and average $\$9$/MWh in FRCC, disregarding transmission value driven by anomalous data. The ranges of transmission value reported here are large, spanning an order of magnitude in some cases. Much of this variation is driven by year-to-year changes, with 2022 having a particularly high intra-regional transmission value due to elevated natural gas prices. Inter‐regional corridors: Annual average transmission values across three broader regions range from $\$6$ to $\$28$/MWh with a long-term average of $\$11$/MWh. Much of the transmission value is concentrated in a small portion of hours. Across all regions, severe weather—particularly polar vortex events in January 2018, February 2021, and December 2022—drives the largest price spreads. Seasonal patterns also emerge, with summer afternoons and fall mornings contributing consistently to transmission value, as for example between MISO and SOCO in 2023.
Environment Modeling Using Runtime Values for JPF-Android
Software applications are developed to be executed in a specific environment. This environment includes external native libraries to add functionality to the application and drivers to fire the application execution. For testing and verification, the environment of an application is simplified abstracted using models or stubs. Empty stubs, returning default values, are simple to generate automatically, but they do not perform well when the application expects specific return values. Symbolic execution is used to find input parameters for drivers and return values for library stubs, but it struggles to detect the values of complex objects. In this work-in-progress paper, we explore an approach to generate drivers and stubs based on values collected during runtime instead of using default values. Entry-points and methods that need to be modeled are instrumented to log their parameters and return values. The instrumented applications are then executed using a driver and instrumented libraries. The values collected during runtime are used to generate driver and stub values on- the-fly that improve coverage during verification by enabling the execution of code that previously crashed or was missed. We are implementing this approach to improve the environment model of JPF-Android, our model checking and analysis tool for Android applications.