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Training dataset for the Generic Aquifer Component of NRAP-Open-IAM. Consists of the results of 62,500 STOMP-CO2 simulations of brine and CO2 leakage of varying rates and salinity into aquifers of varying thickness, depth, porosity, permeability, anisotropy and initial salinity. Described in report https://www.pnnl.gov/main/publications/external/technical_reports/PNNL-32590.pdf
Existing scientific literature shows that health and agricultural impacts attributable to air pollution are significant and should be considered in the integrated analysis of human and Earth-system interactions. The implementation of policies that affect the power sector, the composition of the vehicle fleet or the investments and deployment of different energy sources will in turn result in different levels of air pollution. Even though the various methodologies for estimating the impacts of air pollution, such as exposure-response functions, are extensively applied by the scientific community, they are normally not included in integrated assessment modeling outputs.
Ambitious international greenhouse gas emissions reduction targets demand a rapid transformation to a low-carbon economy. This transformation includes the accelerated adoption of carbon dioxide (CO2) capture and storage (CCS) technology. However, as with any large-scale engineering enterprise, the widespread commercial-scale deployment of geologic carbon storage (GCS) raises important questions about technology and cost-effectiveness, safety, environmental risk, and long-term liability. Effectively assessing and managing risks and liability associated with GCS projects is a key technical need throughout the project life cycle-from site selection and permitting to monitoring design, operational risk management, and post-operational site closure. This presentation highlights recent advancements in tools for quantitative risk assessment, being developed by the National Risk Assessment Partnership (NRAP). NRAP is a multi-year, multinational laboratory research collaboration sponsored by the U.S. Department of Energy's Office of Fossil Energy and Carbon Management. Our focus will be on these tools' applications in addressing critical stakeholder questions related to supporting permitting to ensure secure and environmentally protective storage; designing effective and efficient monitoring plans; evaluating the effectiveness of remedial actions and risk management alternatives; and informing liability assessment and investment decisions. This paper will detail the key functionality of NRAP’s Open-Source Integrated Assessment Model (NRAP-Open-IAM), a computational framework for assessing leakage risk and containment assurance. This model features streamlined workflows for calculating leakage risk profiles, delineating risk-based area of review, and assessing contingency plans and post-injection site care requirements. ORION is an open-source, observation-based ensemble forecasting toolkit to help operators assess the seismic hazard at a carbon storage site. The State of Stress Analysis Tool (SOSAT), designed to assess subsurface stress conditions and evaluate geomechanical risk resulting from CO2 injection in an area of interest will also be presented. We will also introduce a prototype model to evaluate storage project costs and liability associated with risk management. The Technoeconomic and Liability Evaluation for Storage (TALES) model uses results from forecasts of leakage and induced seismicity risk to estimate the lifecycle cost of managing risk. Finally, a preliminary example of how the NRAP Risk-based Adaptive Monitoring Plan (RAMP) tool can be used to design efficient and effective site monitoring plans and estimate the detectability of fluid leakage will be provided. The relevance of these tools for addressing key stakeholder questions amidst uncertainty will be emphasized.
In this report we take stratigraphic data from the ISGS-led Macon County Phase 2 CarbonSAFE’s proposed site in Christian County, Illinois, and conduct reservoir simulations to generate pressure and CO 2 saturation plume data as a function of time. We then use this plume data along with the stratigraphic data as inputs to the NRAP Open-source Integrated Assessment Model (NRAP-Open-IAM) to evaluate project risks. For this report we focus on the probabilistic risk associated with hypothetical leakage of CO 2 and brine along the injection well and one monitoring well. We also study the resulting impact to two overlying aquifers, which could be used to inform monitoring technology selection.
This report provides a detailed description of a set of numerical simulations that represent reservoir behavior over time in response to different operational decision scenarios for detection of potential leakage and reduction or avoidance of leakage impact at a hypothetical geological carbon storage (GCS) site. These simulations serve as the basis for a series of GCS leakage risk forecasts that are to be developed using the National Risk Assessment Partnership’s Open-Source Integrated Assessment Model (NRAP-Open-IAM), and a demonstration of a simple decision support workflow for evaluation of mitigation strategies based on results of those system model forecasts. This risk assessment and decision support study is forthcoming. Four injection scenarios were considered: a constant rate carbon dioxide (CO 2 ) injection case (base case), a case with CO 2 injection rate adjustment, a case with early termination of injection operations, and a case with brine extraction. CO 2 injection operations were controlled to ensure that the pressure transient remains below the defined manageable reservoir fracture pressure, with consideration shown to hypothetical locations within the modeled spatial domain where the overburden was weaker and lower transient pressure increases were allowable. Additionally, a brine extraction alternative was considered as a reservoir management and risk mitigation option to reduce reservoir pressure, steer the plume away from any hypothetical geohazard such as fault as needed, and enhance storage capacity. Such operational actions contribute to risk management overtime. This study explores the potential utility of reservoir management for risk reduction at GCS sites. This study shows that the injection design may modify the time to CO 2 breakthrough at a legacy well; in particular, these results show that brine extraction can add value for mitigating risk both by delaying leakage and reducing pressure build-up. For the scenario considered, both pressure plots and pressure distributions demonstrate that pressure build-up was decreased by 3% with brine extraction. Additionally, extraction of brine afforded enhancement of CO 2 storage capacity by 5% compared to the base case. These findings suggest that brine extraction has substantial potential to steer the risk-related reservoir effects away from known geohazards (e.g., faults and legacy wells) by conducting pressure transient effects and CO 2 plume movement toward the production well. Injection rate adjustment scenarios considered in this study show potential value for managing both reservoir pressure transients and CO 2 plume behavior. Operational actions for reducing injection and/or early termination of injection (as compared to the base case), however, require careful design; tailoring both the extent and timing of injection rate adjustment over the injection and post-injection operational period must be thoroughly planned to balance maximizing storage and minimizing subsurface environmental risk. The study also gives preliminary consideration to the effectiveness that monitoring strategy may play in providing useful information to inform reservoir management decisions for risk reduction. Two types of monitoring were considered: 1) pressure build-up or pressure transient; and 2) potential leakage detection from a CO 2 mass or plume. Four hypothetical legacy wells, two plugged and two abandoned, were placed in the model domain. Monitoring along these wells was measured over time in individual stacked reservoir formations and shale formations to support risk mitigation decisions, especially operational decisions that assisted in risk reduction. These simulations will serve as the basis for a series of GCS leakage risk forecasts that are to be developed using NRAP’s Open-IAM, and demonstration of a simple decision support workflow for comparative assessment of mitigation alternatives based on results of those system model forecasts. This risk assessment and decision support study is forthcoming.
This report summarizes results of the individual legacy well leakage risk analysis of the Farnsworth Unit site (FWU) for Open Well scenario. NRAP tools Integrated Assessment Model for Carbon Storage (NRAP-IAM-CS) and Reservoir Reduced-Order Model Generator (RROMGen) were used (Dilmore et al., 2016; Pawar et al., 2016; King, 2016). This is part one of the additional analysis addressing SWP BP4 Subtask 7.4.1.2: Extend quantitative brine and CO2 leakage calculations (Chu et al., 2020).
Energy system projections from quantitative models inform actions ranging from short-term and local decisions, such as those about technology and infrastructure deployment, and global and long-term negotiations and targets. Computational limits require model designers to balance coverage and resolution (i.e., breadth versus depth). Some models, such as the Global Change Analysis Model (GCAM), represent all energy sources and uses with less resolution than models that focus on a single sector's energy use. GCAM balances global supply and demand of all energy carriers projecting prices using internal calculations for energy sources and costs of greenhouse gas mitigation while capturing interlinkages between the energy system, water, agriculture and land use, the economy, and the climate. This globally comprehensive model was used to frame the Long-Term Strategy of the United States: Pathways to Net-Zero Greenhouse Gas Emissions by 2050, which the White House released in 2021 and has been used to inform national and global economy-wide climate change mitigation discussions and strategy development for decades. Unlike GCAM, sectoral models focus on a portion of the energy sector and with greater detail and resolution. The Regional Energy Deployment System (ReEDS) electricity-sector model, for example, projects electricity system capacity expansion and operation with high-fidelity representation of emerging technologies for deep decarbonization, such as variable renewable energy and energy storage, and integration of these technologies into the electric grid. The Transportation Energy and Mobility Pathway Options (TEMPO) transportation-sector model enables analysis of household choices, with a focus on adoption, charging, and use of electric vehicles. The Scout buildings-sector model supports detailed consideration of the policies and markets that can accelerate the adoption of electrification and energy conservation measures in buildings. Such sector-specific models are instrumental in informing technology research, sectoral planning strategies, and sector-specific aspects of greenhouse gas mitigation strategies in the United States. The integrated multisector and sector-specific modeling approaches represented by GCAM and these sectoral models are complementary. The integrated multisector approach calculates energy pricing and resource allocation within the model, which is important for consistency when future conditions substantially diverge from current conditions in transformative scenarios. The sector-specific approach facilitates representation of granular details across spatial, temporal, technological, and market dimensions that enable exploration of particular interactions and trade-offs. This report presents the results of recent work to explore the differences and trade-offs between these approaches by comparing GCAM with the sector-specific ReEDS, TEMPO, and Scout models. The report compares both model structures and results, and it addresses their potential relevance and applications.
This analysis takes an integrated, innovative approach to develop plausible, high-ambition pathways through 2035 to inform the third U.S. NDC target setting. This approach combines: (1) an extensive consultation and engagement process with a broad set of federal and subnational stakeholders to build a robust U.S. policy platform; and (2) an open-source, field-leading integrated assessment model focused on the U.S. containing subnational details. The modeling tool assesses existing and possible new policies from both federal and subnational levels to assess the overall emissions reduction potential and the policy pathways to deliver the ambition needed for 2035 and leading on to 2050. In addition, we highlight how different actors can contribute to the needed transition in each sector and showcase successful implementation stories by various subnational actors.
Incorporating the interdependencies between water, energy and food (WEF) within an integrated approach of planning and management could help nations worldwide to address sustainability concerns. This is a topic of great importance for the Middle East and North Africa (MENA) region, where water is a very limited resource. In this study, we develop an analytical framework to analyze the water-energy-food nexus in the MENA region to inform the formulation of integrated strategies for water, energy and food activities. Our approach is based on an integrated assessment model for the MENA region, which explicitly represents WEF sectors within an economic framework, in tandem with a set of relevant scenarios addressing three key dimensions (socioeconomics, climate and water-management). Using this framework, our study analyzes the current and projected status of water resources in the region, and the potential implications for the agriculture and electricity sectors. Our scenarios demonstrate that water scarcity worsens by the end of the 21st century in most MENA countries, mostly due to growing demands. The impacts of growing scarcity on agriculture are significant, with production projected to drop by 60 percent by 2050 in some countries. On the other hand, and to a lesser extent, water-saving technologies and fuel-switching in the power sector play a key role in mitigating the effects of water scarcity on electricity generation in some parts of the MENA region. Our analysis then underscores the need to reduce the dependence of MENA’s agricultural and energy sectors on water, and transition to renewable energies to reduce water scarcity.
The Integrated Medical Model (IMM) is a decision support tool that is useful to mission planners and medical system designers in assessing risks and designing medical systems for space flight missions. The IMM provides an evidence based approach for optimizing medical resources and minimizing risks within space flight operational constraints. The mathematical relationships among mission and crew profiles, medical condition incidence data, in-flight medical resources, potential crew functional impairments, and clinical end-states are established to determine probable mission outcomes. Stochastic computational methods are used to forecast probability distributions of crew health and medical resource utilization, as well as estimates of medical evacuation and loss of crew life. The IMM has been used in support of the International Space Station (ISS) medical kit redesign, the medical component of the ISS Probabilistic Risk Assessment, and the development of the Constellation Medical Conditions List. The IMM also will be used to refine medical requirements for the Constellation program. The IMM outputs for ISS and Constellation design reference missions will be presented to demonstrate the potential of the IMM in assessing risks, planning missions, and designing medical systems. The implementation of the IMM verification and validation plan will be reviewed. Additional planned capabilities of the IMM, including optimization techniques and the inclusion of a mission timeline, will be discussed. Given the space flight constraints of mass, volume, and crew medical training, the IMM is a valuable risk assessment and decision support tool for medical system design and mission planning.
The Integrated Medical Model (IMM) is a decision support tool that is useful to space flight mission planners and medical system designers in assessing risks and optimizing medical systems. The IMM employs an evidence-based, probabilistic risk assessment (PRA) approach within the operational constraints of space flight.
Decision makers need accurate information to address climate variability and change and accelerate transformation to sustainability. A stakeholder-driven, science-based multi-model approach has been developed and used by the Agricultural Model Intercomparison and Improvement Project (AgMIP) to generate actionable information for adaptation planning processes. For a range of mid-century climate projections—likely to be hotter, drier, and more variable—contrasting future socio-economic scenarios (Representative Agricultural Pathways, RAPs) were co-developed with stakeholders to portray a sustainable development scenario and a rapid economic growth pathway. The unique characteristic of this application is the integration of a multi-modeling approach with stakeholder engagement to co-develop scenarios and adaptation strategies. Distribution of outcomes were simulated with climate, crop, livestock, and economic impact assessment models for smallholder crop livestock farmers in a typical dryland agro-ecological zone in Zimbabwe, characterized by low and erratic rainfall and nutrient depleted soils. Results showed that in Nkayi District, Western Zimbabwe, climate change would threaten most of the farms, and, in particular, those with large cattle herds due to feed shortages. Adaptation strategies that showed the most promise included diversification using legume production, soil fertility improvement, and investment in conducive market environments. The switch to more legumes in the farming systems reduced the vulnerability of the very poor as well as the more resourced farmers. Overall, the sustainable development scenario consistently addressed institutional failures and motivated productivity-enhancing, environmentally sound technologies and inclusive development approaches. This yielded more favorable outcomes than investment in quick economic wins from commercializing agriculture.
This study incorporates the energy demands of water abstraction, treatment, distribution, and post-use (wastewater) treatment into the Global Change Assessment Model (GCAM), an integrated human-Earth systems model, and analyzes a range of scenarios that estimate the future evolution of this demand of energy. The study builds on prior research on the historical demands of energy-for-water, fitting these demands of energy into existing nation-level energy balances, where demands for energy-for-water have heretofore been aggregated with other energy use in the commercial and public services, industrial, agricultural, and/or electric power sectors. This development allows for improved projections of future energy demands in general, and in this study, allows for assessment of the energy implications of different scenarios of improvements in water access and water quality that are consistent with the Sustainable Development Goals. In our baseline scenario, energy-for-water approximately doubles from 2010 to 2050, and in the scenario with the greatest level of water access, standards for treatment of wastewater, and irrigation expansion, the consequent energy-for-water demands increase three-fold from 2010 to 2050. Note also that these increases do not consider future scarcity-driven increases in energy requirements per unit of water abstraction, treatment, and distribution.
This slide presentation reviews the Integrated Medical Model (IMM) and its use as a risk assessment and decision support tool for human space flight missions. The IMM is an integrated, quantified, evidence-based decision support tool useful to NASA crew health and mission planners. It is intended to assist in optimizing crew health, safety and mission success within the constraints of the space flight environment for in-flight operations. It uses ISS data to assist in planning for the Exploration Program and it is not intended to assist in post flight research. The IMM was used to update Probability Risk Assessment (PRA) for the purpose of updating forecasts for the conditions requiring evacuation (EVAC) or Loss of Crew Life (LOC) for the ISS. The IMM validation approach includes comparison with actual events and involves both qualitative and quantitaive approaches. The results of these comparisons are reviewed. Another use of the IMM is to optimize the medical kits taking into consideration the specific mission and the crew profile. An example of the use of the IMM to optimize the medical kits is reviewed.
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The Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) is a computational model that provides human health and medical risk predictions for crewed spaceflight missions. MEDPRAT utilizes discrete event modeling and dynamic probabilistic simulation to predict critical mission outcomes (total medical events, crew health index, quality time lost, loss of crew life, removal to definitive care), condition occurrences, and resource consumption. Input parameters for MEDPRAT include crew attributes (e.g., sex), types of mission activities (e.g., whether and where crew members perform an extravehicular activity (EVA)), available resources, treatment information, and probability distributions for medical conditions. As an evolution of the Integrated Medical Model (IMM), MEDPRAT provides enhanced capabilities and higher fidelity, and incorporates more appropriate assumptions for long-duration spaceflight. IMM is the currently accepted standard for quantifying spaceflight mission medical risk in NASA operations that uses a probabilistic risk assessment (PRA) approach. MEDPRAT builds on the same logical foundation as IMM but implements the model architecture through highly optimized Monte Carlo sampling methods. An analysis is performed comparing the outputs from IMM with those from MEDPRAT V1.0 and V2.0 for the same reference missions in order to quantify similarities and differences in the model outcomes. The juxtaposition between IMM and MEDPRAT V1.0 and 2.0 shown in this report demonstrates that these two models generate very similar results; where differences in outcomes are shown, these are in accordance with the underlying assumptions and differences in the model architectures. This validation effort further establishes the credibility and reliability of the MEDPRAT software.
The Integrated Medical Model (IMM) Project has been developing a probabilistic risk assessment tool, the IMM, to help evaluate in-flight crew health needs and impacts to the mission due to medical events. This package is a follow-up to a data package provided in June 2009. The IMM currently represents 83 medical conditions and associated ISS resources required to mitigate medical events. IMM end state forecasts relevant to the ISS PRA model include evacuation (EVAC) and loss of crew life (LOCL). The current version of the IMM provides the basis for the operational version of IMM expected in the January 2011 timeframe. The objectives of this data package are: 1. To provide a preliminary understanding of medical risk data used to update the ISS PRA Model. The IMM has had limited validation and an initial characterization of maturity has been completed using NASA STD 7009 Standard for Models and Simulation. The IMM has been internally validated by IMM personnel but has not been validated by an independent body external to the IMM Project. 2. To support a continued dialogue between the ISS PRA and IMM teams. To ensure accurate data interpretation, and that IMM output format and content meets the needs of the ISS Risk Management Office and ISS PRA Model, periodic discussions are anticipated between the risk teams. 3. To help assess the differences between the current ISS PRA and IMM medical risk forecasts of EVAC and LOCL. Follow-on activities are anticipated based on the differences between the current ISS PRA medical risk data and the latest medical risk data produced by IMM.