The Forest Conservation Evaluation Tool: Accessible impact evaluation for Latin America
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Allen Blackman↗
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Social impact evaluation : Some implications of the specific decisional context approach for anticipatory project assessment with special reference to available alternatives and to techniques of evaluating the social impacts of the anticipated effects of such alternatives
The implications are explored of the specific decision context approach to anticipatory project assessment. More specifically, it is hypothesized that with respect to any given effect of a proposed project or action (mobility, job opportunities, air pollution, population distribution, etc.) such effect will likely differ in probability and/or magnitude from one decisional context to another; that the social desirability or undesirability of a given effect is a function (will differ with) each specific decisional context; that therefore the social impact of such effect will in all likelihood differ with each specific decisional context; and that the social significance of even the dame social impact of a given effect will vary from one decisional context to another when such social impact interacts with (competes with or reinforces) the social impacts of other effects. It also follows from this analysis that the respective roles of scientific method (demonstrable data) and adversarial system will not only differ with each specific decisional context but with each alternative course of action available to the decisional entity in each specific context.
Mayo, L. H.↗
Towards Learning-Based Architectures for Sensor Impact Evaluation in Building Controls
Advanced control algorithms for building systems are known to have significant potential in reducing energy consumption while optimizing thermal comfort. The success of such algorithms is critically contingent on several different types of sensor systems, which are in turn, used for continuous monitoring, identification and estimation of several important building states, such as temperatures, humidity, air quality, power consumption and occupancy status. Nonidealities in any of these sensors can lead to significant performance degradation of the control functionalities, and may lead to unwanted sub-optimal building operation. In this paper, we provide a simulation example with a high-fidelity building model, for a particular use-case of advanced optimization-based control in buildings, i.e., occupancy-based controls. We show how imperfections in occupancy sensing can offset performance. Subsequently, we discuss a novel learning-based architecture to efficiently evaluate the impact of sensor nonidealities for building systems, in context of advanced control algorithms.
Bhattacharya, Saptarshi↗
Sensor Impact Evaluation and Verification Technical Advisory Group Meeting Minutes
This report provides the technical advisory group meeting minutes and summary of detailed discussions for future development of sensor impact evaluations and verifications. Methods for sensor configuration/deployment have critical impacts on energy-efficient building control and thermal comfort. However, traditional sensor techniques for building operation and fault detection and diagnostics (FDD) are not optimal in terms of energy efficiency and thermal comfort, and their global effects are not thoroughly investigated. In an effort to address and overcome this limitation, a 3 year project, Sensor Impact Evaluation and Verification, was proposed. The multi-laboratory team—the US Department of Energy’s Oak Ridge National Laboratory (ORNL), Pacific Northwest National Laboratory (PNNL), and the National Renewable Energy Laboratory (NREL)—is conducting early-stage R&D to provide technical supports and guidelines for sensor design in building/HVAC systems to optimize building energy use, FDD, thermal comfort, and grid efficiency. The overall goal of this project is to develop a framework that enables quantitative evaluation of the impact of sensors on building HVAC control, FDD, and consequently, building energy efficiency and thermal comfort.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Selection of Vadose Zone Flow and Transport Properties with Gravel Fraction Corrections for the Hanford Site Composite Analysis and Cumulative Impact Evaluation
This environmental calculation file (ECF) is a compilation of hydrologic and radiological/chemical properties to be used for the updated Hanford Site Composite Analysis (CA) and Cumulative Impact Evaluation (CIE) vadose zone (VZ) modeling. The CA will provide an all-pathways dose projection to a hypothetical future member of the public from all planned low-level radioactive waste disposal facilities and potential contributions from all other projected end-state sources of radioactive material left at the Hanford Site following site closure. Its primary purpose is to support the decision-making process of the U.S. Department of Energy (DOE) under DOE O 435.1 Chg 1, Radioactive Waste Management, related to managing low-level waste disposal facilities at the Hanford Site. The CIE evaluates the effects of cleanup decisions regarding groundwater quality in the Hanford Site Central Plateau (DOE/RL-2018-69, Cumulative Impact Evaluation Technical Approach Document). Due to the complexity and large number of waste sites in source operable units (OUs), the computational tools used for the CIE must be capable of representing a range of site conditions and source terms in the VZ while also efficiently computing the impact that cleanup decisions have on the underlying aquifer. Waste-site proximity between and within source OUs has resulted in contaminants commingling in the vadose and saturated zones in complex ways. Plume commingling requires cleanup decisions to be evaluated considering the surrounding waste sites and existing groundwater contamination, therefore demonstrating the need to evaluate cumulative impacts from the VZ to groundwater.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Literature Review for Sensor Impact Evaluation and Verification Use Cases - Building Controls and Fault Detection and Diagnosis (FDD)
This report summarizes a comprehensive literature review for the selected sensor suites used in building controls and fault detection and diagnostics (FDD), which is a Q2 deliverable of the Sensor Impact Evaluation and Verification project. The project’s overarching goal is to develop a framework for investigating the impact of sensor deployment and configuration for building energy optimization, fault detection and diagnosis (FDD), occupants’ thermal comfort, and potential grid efficiency. While the first phase of the literature review performed in Q1 reviewed the current methods of various sensor selection and placements and their impact, this report focuses on high impactful potential use cases for the selected sensor suites in building control and FDD. The use cases identified in this literature review will be further investigated and be included in the final sensor impact evaluation framework. For the review, the multi-laboratory team reviewed 241 research papers, technical reports, and books to identify existing technologies, the potential impact on energy savings and thermal comfort, and future research opportunities for the selected use cases in building controls and FDD. Along with the literature review, the team conducted a series of interviews with experts in sensors and controls area to identify the state-of-art sensor technologies, and the most impactful use cases in controls and FDD areas. The interview results will also be incorporated with the findings from the literature review in the next quarter, and the final use cases to be evaluated will be selected.
47 OTHER INSTRUMENTATION↗
Sensor Impacts Evaluation and Verification: Expert Interview Responses
The sensor configuration/deployment method has critical impacts on energy efficient building control and thermal comfort. However, traditional sensor techniques for building operation and fault detection and diagnostics (FDD) are not necessarily optimal in terms of energy efficiency and thermal comfort, and their global effects are not thoroughly investigated. In an effort to address and overcome this limitation, a multilaboratory and multiyear project, “Sensor Impact Evaluation and Verification,” was proposed. Its purpose is to develop a framework to investigate the impacts of sensor deployment and configuration on building energy optimization, FDD, occupant thermal comfort, and potentially grid efficiency. The first project task was a literature review to establish a solid knowledge of and a background related to sensor technologies and placement. To accomplish this task, an extensive review of previous research literature was performed. A series of expert interviews were conducted to augment the findings of the literature review. This report summarizes the interview design and interview results and findings. The interview was designed and performed to (1) investigate the current status and limitations of sensor configuration, (2) identify the research gaps and expectations for potential improvements in sensor configuration and deployment, and (3) integrate expert (e.g., researcher, building operation practitioner) knowledge and experience to develop use-case scenarios.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Sensor Impact Evaluation at Different Sensor Locations in a Multi-zone Office Building
FY 2022 Q1 deliverables include the development of an emulator that can evaluate the sensor impacts at different sensor locations (i.e., thermostat locations) in a multizone office building. This report presents the detailed procedure of developing the emulator and using the emulator for preliminary sensor impact analysis. In designing new multizone buildings or retrofitting existing buildings, the room thermostat locations or subzoning design has been often determined by best practices without considering the effects of this design in terms of energy or thermal comfort. In subzoning design, the total number of thermostats is usually smaller than the total number of rooms. As a result, one thermostat in one room often controls the indoor temperature of several other adjacent rooms. For example, five zones might share one thermostat located in one of the zones. Because the demands for thermal load in different zones could be different for the multizone buildings, this subzoning design can compromise control performance and waste building energy consumption. Furthermore, for multizone buildings, subzoning could introduce thermal discomfort for zones. This issue has not be thoroughly investigated in simulation/field studies, and the US Department of Energy’s Oak Ridge National Laboratory explored the impacts of subzoning design through modeling and experimental study.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Exploring Microsimulation Process for Energy Impact Evaluation of Connected and Automated Vehicles
In this paper, the authors present a microsimulation-based methodological approach for evaluating the energy impact of connected and automated vehicles (CAVs). They use an open-source micro-simulator, SUMO, and provide a way to set up a simulation environment that emulates real-world traffic dynamics. They also employ the Intelligent Driver Model to represent human drivers and calibrate its driving behavior using real-world traffic data and driving statistics. The authors conduct extensive simulation studies considering different penetration rates of CAVs, different car-following models, and varying car-following model parameters. Using the state-of-the-art Future Automotive System Technology Simulator (FASTSim), they estimate the fuel economy of each vehicle and analyze the energy impact of the given CAV implementation. Finally, the authors analyze the possible factors affecting the simulation results, and also discuss limitations and future work.
ADVANCED PROPULSION SYSTEMS↗
Leveraging Real-World Driving Data for Design and Impact Evaluation of Energy Efficient Control Strategies
Modeling and simulation are crucial in the development of advanced energy efficient control strategies. Utilizing real-world driving data as the underlying basis for control design and simulation lends veracity to projected real-world energy savings. Standardized drive cycles are limited in their utility for evaluating advanced driving strategies that utilize connectivity and on-vehicle sensing, primarily because they are typically intended for evaluating emissions and fuel economy under controlled conditions. Real-world driving data, because of its scale, is a useful representation of various road types, driving styles, and driving environments. The scale of real-world data also presents challenges in effectively using it in simulations. A fast and efficient simulation methodology is necessary to handle the large number of simulations performed for design analysis and impact evaluation of control strategies. In this study, two methods are presented of leveraging real-world data in both design optimization of energy efficient control strategies and in evaluating the real-world impact of those control strategies upon large-scale deployment. Through these methodologies, strategies with highest impact on energy savings were selected to be implemented as control algorithms. The developed algorithms were incorporated into a vehicle dynamics and powertrain control architecture implemented on a Cadillac CT6 demonstration vehicle. The control algorithms were then exercised on real-world driving scenarios to determine their impact on collective energy savings. The methodology utilizes the large-scale driving data sets maintained by the National Renewable Energy Laboratory to extract real-world driving scenarios and efficient simulation software tools. The insights obtained through this research help in guiding technology selection for energy efficient driving controls.
ARPA-E↗
Vadose Zone Flow and Transport Parameters Data Package for the Hanford Site Composite Analysis and Cumulative Impact Evaluation
This report provides a description of the basis for the development and implementation of a conceptual model for vadose zone flow and transport for the composite analysis (CA) groundwater pathway analysis and the cumulative impact evaluation (CIE). The parameterization for a numerical model is intimately linked to the conceptual model framework. The report describes the basis for the selection of hydraulic and transport parameters for the hydrostratigraphic units (HSUs) identified in the 200 East and 200 West Areas. Whenever data are sparse or unavailable, surrogate hydraulic properties are chosen based on samples collected within the 200 Areas and nearby locations that are representative of sediments characteristic of the HSUs identified elsewhere.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Development of a simplified calibrated building simulation model of a supermarket for proposed ECMs and control strategies impact evaluation
Calibrated building energy simulation is an important pathway to more energy-efficient buildings, but the information requirements of some approaches to this problem are significant. This is particularly true for supermarkets and other so-called “big-box” retail stores. Another characteristic of supermarkets is the significant interaction between Heating Ventilating and Air Conditioning (HVAC) and refrigeration systems in these buildings. These buildings could contain a wide variety of systems and a degree of load diversity that makes calibrated modeling a challenge. This paper describes a simplified approach that uses OpenStudio and EnergyPlus to combine known building parameters with “typical” parameters, resulting in a simplified building that is amenable to calibration. This approach was applied to a big-box store located in Nashville, Tennessee, and a calibrated model was obtained that was used to study potential energy conservation measures. Further, the paper also explores the capabilities of whole-building energy modeling tools, such as EnergyPlus, for modeling the HVAC controls and sequences and their impact evaluation. Although some measures are precluded by the model simplicity, several measures were found to improve the efficiency of the model and demonstrate that the simplified modeling approach is effective. Practical Application: This paper introduces a hybrid approach of building energy model calibration using limited information available from the actual building in combination with characteristics of a “typical” building of the same type. This hybrid approach would also be applicable for other building types than discussed in this paper to calibrate the building energy model using limited information from the actual building.
42 ENGINEERING↗
A Multi-Criteria Impact Evaluation Methodology Applied to FLEX Strategies in Nuclear Power Plants
As responses to Fukushima Dai-ichi nuclear accident, several advanced, near-term technologies have been or are being introduced to enhance safety of operating nuclear power plants (NPPs) as well as improving their sustainability. Examples include Accident-Tolerant Fuel designs, Diverse and Flexible Coping Strategies (FLEX), and passive cooling system designs. The combinations of these technologies, coupled with enhancements to plant components and systems and improved fuel cycle efficiency, constitute a concept of Enhanced Resilient Plant Systems, which is proposed and being explored by Idaho National Laboratory (INL) under the Risk-Informed Systems Analysis Pathway of the U.S. Department of Energy’s Light Water Reactor Sustainability Program. To decide if introducing a technology is necessary or worthy, the impacts of this technology on NPPs should be evaluated, preferably in a quantitative manner, and provided to decision makers. This paper summarizes an on-going work conducted by the authors on developing a multi-criteria impact evaluation methodology. This methodology is expected to be applicable to evaluate a variety of technologies, while FLEX strategy is adopted as a case study for this paper.
99 GENERAL AND MISCELLANEOUS↗
Hypervelocity Impact Evaluation of Metal Foam Core Sandwich Structures
A series of hypervelocity impact (HVI) tests were conducted by the NASA Johnson Space Center (JSC) Hypervelocity Impact Technology Facility (HITF) [1], building 267 (Houston, Texas) between January 2003 and December 2005 to test the HVI performance of metal foams, as compared to the metal honeycomb panels currently in service. The HITF testing was conducted at the NASA JSC White Sands Testing Facility (WSTF) at Las Cruces, New Mexico. Eric L. Christiansen, Ph.D., and NASA Lead for Micro-Meteoroid Orbital Debris (MMOD) Protection requested these hypervelocity impact tests as part of shielding research conducted for the JSC Center Director Discretionary Fund (CDDF) project. The structure tested is a metal foam sandwich structure; a metal foam core between two metal facesheets. Aluminum and Titanium metals were tested for foam sandwich and honeycomb sandwich structures. Aluminum honeycomb core material is currently used in Orbiter Vehicle (OV) radiator panels and in other places in space structures. It has many desirable characteristics and performs well by many measures, especially when normalized by density. Aluminum honeycomb does not perform well in Hypervelocity Impact (HVI) Testing. This is a concern, as honeycomb panels are often exposed to space environments, and take on the role of Micrometeoroid / Orbital Debris (MMOD) shielding. Therefore, information on possible replacement core materials which perform adequately in all necessary functions of the material would be useful. In this report, HVI data is gathered for these two core materials in certain configurations and compared to gain understanding of the metal foam HVI performance.
Yasensky, John↗
Social impact evaluation: Some implications of the specific decisional context approach for Anticipatory Project Assessment (ARA)
An anticipatory project assessment is discussed which is characterized as the capacity to perform, and the disposition to take into account in relevant decisional areas, the following operations: identification of the significant effects which will result from the introduction of a specified project configuration into alternative projected future social environments during the planning, implementation, and operational states; evaluation of such effects in terms of social impacts on affected participants and social value-institutional processes in accord with specified concepts of social justice.
Mayo, L. H.↗
Evaluating Impacts of the Inflation Reduction Act and Bipartisan Infrastructure Law on the U.S. Power System
The Inflation Reduction Act of 2022 (IRA) and the Infrastructure Investment and Jobs Act of 2021, commonly referred to as the 'Bipartisan Infrastructure Law (BIL),' collectively represent the largest commitment of the U.S. Federal Government to invest in the modernization and decarbonization of the U.S. energy system. The Congressional Budget Office (CBO) estimates that total support for the broad range of climate and clean energy programs, tax credits, and other incentives authorized through the two laws will exceed $430 billion from 2022 through 2031 (CRS 2022; CBO 2021, 2022). While the climate and clean energy provisions are numerous and have the potential to impact all aspects of the U.S. energy system from fuel and electricity production to final consumption in industry, transportation, and buildings, the provisions relevant to the electricity sector - in particular the suite of tax credits for clean generation, storage, and carbon dioxide ( CO 2 ) capture and storage - are expected to be some of the most consequential in terms of emissions reduction and clean energy deployment (Larsen et al. 2022; Jenkins, Mayfield, et al. 2022; Mahajan et al. 2022; Zhao et al. 2022). In this report, we detail the methods and results of a study estimating the potential impacts of key provisions of IRA and BIL on the contiguous U.S. power sector from present day through 2030. The analysis employs an advanced power system planning model, the Regional Energy Deployment System (ReEDS), to evaluate how major provisions from both laws impact investment in and operation of utility-scale generation, storage, and transmission, and, in turn, how those changes impact power system costs, emissions, and climate and health damages. While not exhaustive in capturing every provision, the analysis estimates the possible scale of power-sector impacts that could result from the modeled provisions in IRA and BIL. The study is structured around two scenarios to evaluate the potential impacts of both laws on the power sector: 1) No New Policy: A counter-factual scenario that reflects all Federal and state policies enacted as of September 2022, with exception to IRA and BIL, and assumes load growth consistent with the Energy Information Administration's Annual Energy Outlook 2022 (AEO22) Reference case (EIA 2022a); 2) IRA-BIL: A scenario reflecting all Federal and state policies enacted as of September 2022, including key IRA and BIL provisions, most notably the investment and production tax credits for zero-carbon emitting electricity generation and storage (ITC and PTC), the tax credit for CO 2 capture and storage (45Q), and the tax credit for existing nuclear plants (described further in Section 2.3). To account for the impacts of IRA and BIL on electrification, assumes increased load growth consistent with a scaled version of the Medium Electrification scenario from the Electrification Futures Study (Mai et al. 2018). These scenarios are simulated across seven sets of assumptions with varying projected future electricity market conditions, including technology costs and performance, natural gas prices, and the degree of availability, feasibility, and cost of development of renewable resources, electricity transmission, and CO 2 pipeline, injection, and storage infrastructure. In addition, we simulate two sensitivities on the 'policy' treatment in which we vary key assumptions pertaining to the realized value of the clean electricity ITC and PTC: 1) the cost of monetization of tax credits, and 2) the level of bonus crediting realized by project developers. We demonstrate that IRA and BIL have the collective potential to drive substantial growth in clean electricity by 2030, while reducing costs for consumers, mitigating climate change, and decreasing the human health impacts of power sector emissions. However, we also demonstrate that if expected cost improvements of clean technologies are not realized and/or constraints on deployment driven by factors such as supply-chain challenges, regulatory hurdles, and the social acceptability of energy infrastructure development limit the rate of clean energy and associated infrastructure deployment (such as transmission), then the share of clean generation achieved and the associated emissions benefits realized may be substantively reduced.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Application of Remote Sensing for Ex-Ante Decision Support and Evaluating Impact
Deforestation is an environmental stressor that dramatically threatens biodiversity while having adverse, deep-rooted socioeconomic impacts. Interventions to address deforestation require considerable long-term investments; therefore, assessing their impact is crucial. The UN Convention on Biological Diversity encourages establishing Protected Areas (PAs) as a strategy to conserve biodiversity, secure ecosystem services, support local livelihoods, and reduce climate change impacts. The Global Environment Facility (GEF) has supported the conservation and management of PAs, yet site accessibility and data availability present challenges in assessing PAs using traditional evaluation methods. We present a novel application of satellite Earth observations for evaluating the effectiveness and impact of PAs as a deforestation mitigation strategy. Geospatial analysis and ecological forecasting methodologies provide an efficient way to quantify land cover change, estimate above-ground carbon stock, and evaluate ecosystem services provided by the PAs ex-ante. We demonstrate the value of a geospatial approach through evaluation of GEF-supported PAs in Kenya.
Remote sensing↗
Socioeconomic Impact Evaluation for Near Real-time Flood Detection in the Lower Mekong River Basin
Flood events pose a severe threat to communities in the Lower Mekong River Basin. The combination of population growth, urbanization, and economic development exacerbate the impacts of these events. Flood damage assessments, critical for understanding the effects of flooding on the local population and informing decision-makers about future risks, are frequently used to quantify the economic losses due to storms. Remote sensing systems provide a valuable tool for monitoring flood conditions and assessing their severity more rapidly than traditional post-event evaluations. The frequency and severity of extreme flood events are projected to increase, further highlighting the need for improved flood monitoring and impact analysis. In this study we integrate a socioeconomic damage assessment model with a near real-time flood remote sensing and decision support tool (NASA's Project Mekong). Direct damages to populations, infrastructure, and land cover are assessed using the 2011 Southeast Asian flood as a case study. Improved land use/land cover and flood depth assessments result in rapid loss estimates throughout the Mekong River Basin. Results suggest that rapid initial estimates of flood impacts can provide valuable information to governments, international agencies, and disaster responders in the wake of extreme flood events.
Mekong Basin↗