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Technology Readiness Assessment for Stirling Power Convertor

Stirling-based power conversion system could represent a critical enabling technology for future NASA missions, offering significantly enhanced power efficiency over traditional thermoelectric systems. To ensure the successful infusion of this technology into deep space and planetary surface missions, a rigorous evaluation of its maturity and associated risks is essential. The objective of this Technology Readiness Assessment (TRA) is to determine the current technology readiness level (TRL) of the Stirling power convertor and identify key technical risks and challenges associated with its maturation and potential infusion into a targeted flight system. The evaluation process will rigorously follow the NASA TRA procedure: (1) determining the requirements that underpin the design, function, and performance; (2) finding and listing all new technology elements (NTEs) and critical technology elements (CTEs); (3) identifying the level of integration assumed for the assessment; and (4) assessing the TRL for each NTE and CTE. The overall subassembly TRL will then be determined via a roll-up using the “weakest link” criterion, culminating in a final (5) assessment of risks to further progression of maturity. This paper will present the results of a comprehensive technology readiness assessment (TRA) conducted on the Stirling-based dynamic power conversion subassembly, excluding the radioisotope heat source. The paper will also describe a detailed breakdown of the TRL roll-up and a matrix of identified risks and recommended mitigation paths, along with identified key technical risks and challenges to achieve the required long-duration performance. Key Words: Radioisotope Power Conversion, Technology Readiness Assessment

Radioisotope Power Conversion↗
DOE OSTI2012

A Resilient Condition Assessment Monitoring System

An architecture and supporting methods are presented for the implementation of a resilient condition assessment monitoring system that can adaptively accommodate both cyber and physical anomalies to a monitored system under observation. In particular, the architecture includes three layers: information, assessment, and sensor selection. The information layer estimates probability distributions of process variables based on sensor measurements and assessments of the quality of sensor data. Based on these estimates, the assessment layer then employs probabilistic reasoning methods to assess the plant health. The sensor selection layer selects sensors so that assessments of the plant condition can be made within desired time periods. Resilient features of the developed system are then illustrated by simulations of a simplified power plant model, where a large portion of the sensors are under attack.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

A PROVEN APPROACH FOR EFFECTIVE COMPUTER SECURITY SELF-ASSESSMENTS AT NUCLEAR FACILITIES

A proven method for conducting cybersecurity self-assessments at nuclear power plants is now available for international use. This method was originally developed by Pacific Northwest National Laboratory, under the sponsorship of the U.S. Nuclear Regulatory Commission (NRC), for use at U.S. nuclear power plants. The “Method,” described in NUREG/CR-6847 “Cyber Security Self-Assessment Method for U.S. Nuclear Power Plants,” was originally a limited release document that was withheld from public disclosure but is now publicly available. The Method provides a systematic, phased, and risk-informed approach to help decision makers and security specialists understand their relative cybersecurity posture. Completed Method assessments may be used to support or validate selection of computer security controls to mitigate cyber threats as well as demonstrate compliance with regulations or statutes enacted by competent authorities. The Method assesses the cybersecurity posture of key systems at a nuclear facility with a focus on protection of design base functions. It considers both physical and digital elements of system vulnerabilities and the resulting potential consequences from exploitation. It is well-suited for addressing blended cyberattacks. A semi-quantitative analytical approach is used in the evaluation of potential vulnerabilities, consequences, and risks and provides a technical basis for the selection of security controls to mitigate cyberattacks. The Method’s application at U.S. nuclear power plants has been very encouraging. The only nuclear plant in the United States that did not have adverse findings during its initial NRC computer security inspection prepared for inspection through the diligent application of this self-assessment method and the implementation of recommendations that came out of that self-assessment. Nuclear facilities around the world might find application of the Method extremely helpful for making cost-effective, risk-based decisions regarding computer security and for preparing to pass computer security inspections by their competent authorities.

Cyber security, Nuclear security, Self-assessment↗
DOE OSTI2020

On the Formalization of Development and Assessment Process for Digital Twins in the Nearly Autonomous Management and Control System

In recent years, the autonomous control system has been encouraged in advanced reactors for restoring economic viability, simplifying the operation and maintenance, and enabling remote-site power generations [1]. Since the reactor is expected to be operated for a long period of time with a limited number of individuals onsite, it is recommended that the autonomous control system should have access to very realistic models of the state of processes in the whole lifecycle, together with these process behaviors in interaction with their environment in the real world. As a result, digital twin (DT) technology is suggested in autonomous control systems. DT is defined as a digital representation of a physical object or system, which contains a record for the histories of loads, operation and maintenance status, predictions for the near-term transient of important state variables, and decision-making process [2]. Since machine learning (ML) can recognize patterns within a complex system in real-time applications, it has been used to build DTs in the autonomous control systems for advanced reactors. Meanwhile, due to the rareness of operation data in accident scenarios, the development and assessment of DTs is expected to be mainly driven by simulations. Although the capability and feasibility of ML-based DTs are recognized in improving the safety and efficiency of reactor control, a major concern from the regulatory commission and the nuclear industry is whether the information from a DT is developed and assessed in accordance with expectation and requirements by the target decision. Such concerns not only affect the acceptance criteria for DTs, but also values that can be extracted from DTs and autonomous control system during operations. Inspired by the success of formal methods in improving the reliability and robustness of computer programming and software development, it is suggested that the development and assessment process (DAP) for both separate DTs and integral control system should be formalized in a transparent, consistent, and improvable manner. In this study, a digital-twin development and assessment process (DT-DAP) is proposed by adapting the evaluation model development and assessment process (EMDAP) [3] to requirements by the autonomous control system, ML algorithms, and DT technology. To demonstrate the framework, a baseline nearly autonomous management and control (NAMAC) system with ML-based DTs for diagnosis and prognosis is developed and assessed based on the framework. It is found that with selected testing methods and techniques, the DT-DAP can help identify errors in DTs and NAMAC which would otherwise be left unverified. Meanwhile, it is found that the DT-DAP can improve the DTs and NAMAC by continuously learning and iterating through different elements.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

A Comparison of Select USDOE and USEPA Risk and Dose Assessment Tools Utilized at Two FUSRAP Projects - 17388

The US Army Corps of Engineers (USACE) utilizes several computer programs and models to conduct risk and dose assessments at Formerly Utilized Sites Remedial Action Program (FUSRAP) projects. In the past, the USACE has primarily relied on the US Department of Energy (USDOE)'s Argonne National Lab (ANL) RESidual Radioactivity (RESRAD) computer code for performing dose and risk assessments involving radiological contamination in onsite soils and the US Environmental Protection Agency (USEPA) Preliminary Remediation Goal (PRG) and Dose Compliance Calculator (DCC) for radiological contamination in ground water. Recent USEPA guidance requires use of USEPA calculators for all media at National Priority List sites, which includes some FUSRAP sites. The USACE recently utilized both RESRAD and the USEPA PRG and DCC calculators in assessments at two FUSRAP projects for all media in order to evaluate differences in the models and determine adjustments to potentially resolve differences. The two projects involve soil and groundwater assessments and address typical FUSRAP contaminants such as uranium, radium, thorium and their progeny. This paper discusses differences between the models, lessons learned, and methods used to address stakeholder and other concerns regarding these assessments. The paper's discussions are useful for anyone performing risk or dose assessments for radiological contamination and especially those using RESRAD and the PRG and DCC calculators. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

Needs for integrated risk assessment to support optimal environmental management decisions - 15455

Cleaning up legacy waste from 50 years of nuclear weapons production and energy research still remains a challenge for the U.S. Department of Energy (DOE). The DOE environmental management program is currently forecasted to run through at least late 2060's with an estimated liability of $204 billion. Risks to human health of workers and the public, the ecological system, and nuclear safety of cleanup activities continue to drive the cost of DOE's cleanup programs. Currently, these risks are generally assessed and managed independently of each other. Except for DOE self-regulated on-site disposal activities of low-level radioactive waste, risks to human health and the environment are generally under the purview of U.S. Environmental Protection Agency and State regulatory agencies, while nuclear safety risks are regulated by DOE with oversight from the U.S. Nuclear Regulatory Commission and the Defense Nuclear Facilities Safety Board where appropriate. When managing health and environmental risks, the individual regulatory authorities often use an area-by-area (or unit-by-unit), contaminant-by-contaminant (chemical-by-chemical or radionuclide-by-radionuclide) approach, focusing on a single medium (soil, water, or air), a single source (e.g., a burial ground or a processing facility), and a single receptor (e.g, a groundwater well or a creek). This level of segregation in risk evaluations by risk category, geographical location, and operational unit, as well as the corresponding separation of regulatory authorities poses a significant challenge to reaching an optimal decision in prioritizing and managing cleanup activities. This management challenge adds another layer of complexity to large-scale cleanup effort at complex sites such as the Hanford site in eastern Washington. Therefore, to support a scientifically sound, operationally robust decision making process, there is a need for an integrated, holistic approach to risk assessment that addresses the combined effects of all major contributing factors. Previous studies have pointed out the need for integrated risk assessments that address multi-contaminant, multimedia, multi-pathway exposures, for the purposes of evaluating risks to human health and the environment. We believe that a comprehensive risk assessment should also take into nuclear safety risks that are associated with handling of nuclear material either retrieved from burial sites or to be decommissioned from nuclear facilities. Recent efforts, such as the Consortium for Risk Evaluation with Stakeholder Participation (CRESP)-led Hanford site-wide independent risk review that will categorize all types of risks at the Hanford site and the DOE complex-wide risk review mandated by the Fiscal Year 2014 Consolidated Appropriations Act ('Omnibus bill'), are beginning to more comprehensively address this need. This paper provides a categorization of various types of risks present at typical DOE sites, reviews the current risk assessment and management practices, and discusses the needs for integrating nuclear safety into performance and risk assessments for optimal cleanup decisions. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) for Analyzing Emerging Low-Carbon Technologies

Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 degrees Celsius or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics. The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Under baseline projections (i.e., no decarbonization goals), neither process reaches parity with the incumbent technology across several environmental metrics. Under the decarbonization scenarios, the underlying sectoral shifts result in declining impacts over time, compared to 2020 levels, except for metal depletion levels, which increase. The background shifts postulate a heavily decarbonized economy and energy system, which help technologies reach parity with SMR between 2040-2050 (RCP2.6) and 2030-2040 (RCP1.9) for global warming. Despite declines across several other metrics over time, neither PtH2 technology break even with SMR by 2100 besides for global warming.

decarbonizing↗
DOE OSTI2024

Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) for Analyzing Emerging Low-Carbon Technologies

Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 degrees C or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Under baseline projections (i.e., no decarbonization goals), neither process reaches parity with the incumbent technology across several environmental metrics. Under the decarbonization scenarios, the underlying sectoral shifts result in declining impacts over time, compared to 2020 levels, except for metal depletion levels, which increase. The background shifts postulate a heavily decarbonized economy and energy system, which help technologies reach parity with SMR between 2040-2050 (RCP2.6) and 2030-2040 (RCP1.9) for global warming. Despite declines across several other metrics over time, neither PtH2 technology break even with SMR by 2100 besides for global warming.

decarbonizing↗
DOE OSTI2016

Uncertainty quantification's role in modeling and simulation planning, and credibility assessment through the predictive capability maturity model

The importance of credible, trustworthy numerical simulations is obvious especially when using the results for making high-consequence decisions. Determining the credibility of such numerical predictions is much more difficult and requires a systematic approach to assessing predictive capability, associated uncertainties and overall confidence in the computational simulation process for the intended use of the model. This process begins with an evaluation of the computational modeling of the identified, important physics of the simulation for its intended use. This is commonly done through a Phenomena Identification Ranking Table (PIRT). Then an assessment of the evidence basis supporting the ability to computationally simulate these physics can be performed using various frameworks such as the Predictive Capability Maturity Model (PCMM). There were several critical activities that follow in the areas of code and solution verification, validation and uncertainty quantification, which will be described in detail in the following sections. Here, we introduce the subject matter for general applications but specifics are given for the failure prediction project. In addition, the first task that must be completed in the verification & validation procedure is to perform a credibility assessment to fully understand the requirements and limitations of the current computational simulation capability for the specific application intended use. The PIRT and PCMM are tools used at Sandia National Laboratories (SNL) to provide a consistent manner to perform such an assessment. Ideally, all stakeholders should be represented and contribute to perform an accurate credibility assessment. PIRTs and PCMMs are both described in brief detail below and the resulting assessments for an example project are given.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Relationship of left ventricular global longitudinal strain with cardiac autonomic denervation as assessed by {sup 123}I-mIBG scintigraphy in patients with heart failure with reduced ejection fraction submitted to cardiac resynchronization therapy

Background: Heart failure (HF) is associated with cardiac autonomic denervation (AD), which can be non-invasively assessed by {sup 123}I-metaiodobenzylguanidine ({sup 123}I-mIBG) scintigraphy and has prognostic implications. We aimed to study the relationship between myocardial contractility assessed by global longitudinal strain (GLS) and AD assessed by {sup 123}I-mIBG scintigraphy in advanced HF. Methods/Results: BETTER-HF is a prospective randomized clinical trial including HF patients (pts) submitted to cardiac resynchronization therapy (CRT) who are submitted to a clinical, echocardiographic, and scintigraphic assessment before and 6 months after CRT. 81 pts were included. An echocardiographic response (absolute increase in left ventricular ejection fraction ≥ 10%) was observed in 73.7% of pts. A higher baseline late heart-to-mediastinum ratio (HMR) was associated with a better echocardiographic response. There was a significant association between late HMR and GLS at baseline and 6 months. At baseline, GLS had an AUC of 0.715 for discrimination for a late HMR < 1.6. A GLS cut-off of − 9% maximized the likelihood of correctly classifying a pt as having severe AD (HMR < 1.6). Conclusion: Myocardial contractility as assessed by GLS is moderately correlated with AD as assessed by {sup 123}I-mIBG scintigraphy and has a good discrimination for the identification of severe cardiac denervation. GLS may allow for a more readily accessible estimation of the degree of AD in advanced HF pts.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2012

Integration of health into urban spatial planning through impact assessment: Identifying governance and policy barriers and facilitators

This article presents the results of a review of literature examining the barriers and facilitators in integrating health in spatial planning at the local, mainly urban level, through appraisals. Our literature review covered the UK and non UK experiences of appraisals used to consider health issues in the planning process. We were able to identify four main categories of obstacles and facilitators including first the different knowledge and conceptual understanding of health by different actors/stakeholders, second the types of governance arrangements, in particular partnerships, in place and the political context, third the way institutions work, the responsibilities they have and their capacity and resources and fourth the timeliness, comprehensiveness and inclusiveness of the appraisal process. The findings allowed us to draw some lessons on the governance and policy framework regarding the integration of health impact into spatial planning, in particular considering the pros and cons of integrating health impact assessment (HIA) into other forms of impact assessment of spatial planning decisions such as environmental impact assessment (EIA) and strategic environment assessment (SEA). In addition, the research uncovered a gap in the literature that tends to focus on the mainly voluntary HIA to assess health outcomes of planning decisions and neglect the analysis of regulatory mechanisms such as EIA and SEA. - Highlights: Black-Right-Pointing-Pointer Governance and policy barriers and facilitators to the integration of health into urban planning. Black-Right-Pointing-Pointer Review of literature on impact assessment methods used across the world. Black-Right-Pointing-Pointer Knowledge, partnerships, management/resources and processes can impede integration. Black-Right-Pointing-Pointer HIA evaluations prevail uncovering research opportunities for evaluating other techniques.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Multilevel and multi-user sustainability assessment of farming systems

Sustainability assessment is needed to build sustainable farming systems. A broad range of sustainability concepts, methodologies and applications already exists. They differ in level, focus, orientation, measurement, scale, presentation and intended end-users. In this paper we illustrate that a smart combination of existing methods with different levels of application can make sustainability assessment more profound, and that it can broaden the insights of different end-user groups. An overview of sustainability assessment tools on different levels and for different end-users shows the complementarities and the opportunities of using different methods. In a case-study, a combination of the sustainable value approach (SVA) and MOTIFS is used to perform a sustainability evaluation of farming systems in Flanders. SVA is used to evaluate sustainability at sector level, and is especially useful to support policy makers, while MOTIFS is used to support and guide farmers towards sustainability at farm level. The combined use of the two methods with complementary goals can widen the insights of both farmers and policy makers, without losing the particularities of the different approaches. To stimulate and support further research and applications, we propose guidelines for multilevel and multi-user sustainability assessments. - Highlights: Black-Right-Pointing-Pointer We give an overview of sustainability assessment tools for agricultural systems. Black-Right-Pointing-Pointer SVA and MOTIFS are used to evaluate the sustainability of dairy farming in Flanders. Black-Right-Pointing-Pointer Combination of methods with different levels broadens the insights of different end-user groups. Black-Right-Pointing-Pointer We propose guidelines for multilevel and multi-user sustainability assessments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

A multi-scale qualitative approach to assess the impact of urbanization on natural habitats and their connectivity

Habitat loss and fragmentation are often concurrent to land conversion and urbanization. Simple application of GIS-based landscape pattern indicators may be not sufficient to support meaningful biodiversity impact assessment. A review of the literature reveals that habitat definition and habitat fragmentation are frequently inadequately considered in environmental assessment, notwithstanding the increasing number of tools and approaches reported in the landscape ecology literature. This paper presents an approach for assessing impacts on habitats on a local scale, where availability of species data is often limited, developed for an alpine valley in northern Italy. The perspective of the methodology is multiple scale and species-oriented, and provides both qualitative and quantitative definitions of impact significance. A qualitative decision model is used to assess ecological values in order to support land-use decisions at the local level. Building on recent studies in the same region, the methodology integrates various approaches, such as landscape graphs, object-oriented rule-based habitat assessment and expert knowledge. The results provide insights into future habitat loss and fragmentation caused by land-use changes, and aim at supporting decision-making in planning and suggesting possible ecological compensation. - Highlights: Black-Right-Pointing-Pointer Many environmental assessments inadequately consider habitat loss and fragmentation. Black-Right-Pointing-Pointer Species-perspective for defining habitat quality and connectivity is claimed. Black-Right-Pointing-Pointer Species-based tools are difficult to be applied with limited availability of data. Black-Right-Pointing-Pointer We propose a species-oriented and multiple scale-based qualitative approach. Black-Right-Pointing-Pointer Advantages include being species-oriented and providing value-based information.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Framework for assessing impacts of pile-driving noise from offshore wind farm construction on a harbour seal population

Offshore wind farm developments may impact protected marine mammal populations, requiring appropriate assessment under the EU Habitats Directive. We describe a framework developed to assess population level impacts of disturbance from piling noise on a protected harbour seal population in the vicinity of proposed wind farm developments in NE Scotland. Spatial patterns of seal distribution and received noise levels are integrated with available data on the potential impacts of noise to predict how many individuals are displaced or experience auditory injury. Expert judgement is used to link these impacts to changes in vital rates and applied to population models that compare population changes under baseline and construction scenarios over a 25 year period. We use published data and hypothetical piling scenarios to illustrate how the assessment framework has been used to support environmental assessments, explore the sensitivity of the framework to key assumptions, and discuss its potential application to other populations of marine mammals. -- Highlights: • We develop a framework to support Appropriate Assessment for harbour seal populations. • We assessed potential impacts of wind farm construction noise. • Data on distribution of seals and noise were used to predict effects on individuals. • Expert judgement linked these impacts to vital rates to model population change. • We explore the sensitivity of the framework to key assumptions and uncertainties.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Hybrid LCA model for assessing the embodied environmental impacts of buildings in South Korea

The assessment of the embodied environmental impacts of buildings can help decision-makers plan environment-friendly buildings and reduce environmental impacts. For a more comprehensive assessment of the embodied environmental impacts of buildings, a hybrid life cycle assessment model was developed in this study. The developed model can assess the embodied environmental impacts (global warming, ozone layer depletion, acidification, eutrophication, photochemical ozone creation, abiotic depletion, and human toxicity) generated directly and indirectly in the material manufacturing, transportation, and construction phases. To demonstrate the application and validity of the developed model, the environmental impacts of an elementary school building were assessed using the developed model and compared with the results of a previous model used in a case study. The embodied environmental impacts from the previous model were lower than those from the developed model by 4.6–25.2%. Particularly, human toxicity potential (13 kg C{sub 6}H{sub 6} eq.) calculated by the previous model was much lower (1965 kg C{sub 6}H{sub 6} eq.) than what was calculated by the developed model. The results indicated that the developed model can quantify the embodied environmental impacts of buildings more comprehensively, and can be used by decision-makers as a tool for selecting environment-friendly buildings. - Highlights: • The model was developed to assess the embodied environmental impacts of buildings. • The model evaluates GWP, ODP, AP, EP, POCP, ADP, and HTP as environmental impacts. • The model presents more comprehensive results than the previous model by 4.6–100%. • The model can present the HTP of buildings, which the previous models cannot do. • Decision-makers can use the model for selecting environment-friendly buildings.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Developing micro-level urban ecosystem indicators for sustainability assessment

Sustainability assessment is increasingly being viewed as an important tool to aid in the shift towards sustainable urban ecosystems. An urban ecosystem is a dynamic system and requires regular monitoring and assessment through a set of relevant indicators. An indicator is a parameter which provides information about the state of the environment by producing a quantitative value. Indicator-based sustainability assessment needs to be considered on all spatial scales to provide efficient information of urban ecosystem sustainability. The detailed data is necessary to assess environmental change in urban ecosystems at local scale and easily transfer this information to the national and global scales. This paper proposes a set of key micro-level urban ecosystem indicators for monitoring the sustainability of residential developments. The proposed indicator framework measures the sustainability performance of urban ecosystem in 3 main categories including: natural environment, built environment, and socio-economic environment which are made up of 9 sub-categories, consisting of 23 indicators. This paper also describes theoretical foundations for the selection of each indicator with reference to the literature [Turkish] Highlights: • As the impacts of environmental problems have multi-scale characteristics, sustainability assessment needs to be considered on all scales. • The detailed data is necessary to assess local environmental change in urban ecosystems to provide insights into the national and global scales. • This paper proposes a set of key micro-level urban ecosystem indicators for monitoring the sustainability of residential developments. • This paper also describes theoretical foundations for the selection of each indicator with reference to the literature.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Consideration of climate change on environmental impact assessment in Spain

Most of the projects subject to environmental impact assessment (EIA) are closely related to climate change, as they contribute to or are affected by it. The growing certainty about climate change and its impacts makes its consideration an essential part of the EIA process, as well as in strategic environmental assessment (SEA). This paper examines how climate change (CC) has been taken into account in EIA in Spain through the analysis of 1713 environmental records of decision (RODs) of projects submitted for EIA. In 2013 Spain approved one of the most advanced laws in terms of CC consideration in environmental assessment, although it had not yet accumulated extensive practice on the issue. This contrasts with the situation of countries like Canada or the USA, which have a significant body of experience without specific legal requirements. Only 14% of the RODs analysed included references to CC, and in more than half of the cases it was a mere citation. Thermal power plants, which are subject to specific GHG regulations, show the highest consideration, while transport infrastructures, which are important contributors to CC, show a very low consideration. Almost all the references are related to their contribution to CC, while consideration of the effects of CC is minimal. The increasingly common incorporation of CC into SEA, should not imply its exclusion from EIA, because both processes have different aims and uses. Including the obligation to consider CC in the EIA regulations is highly desirable, but probably not enough without other measures, such as practical guidance, training and motivational programmes for practitioners and evaluators. But even these actions cannot ensure effective and adequate assessments of CC. Probably more resources should be spent on creating greater awareness in all the agents involved in EIA. - Highlights: • We analyse how the climate change is considered in EIA in Spain. • Few projects seriously assess climate change. • Transport infrastructure projects barely consider climate change. • Assessing climate change in SEA should not imply that it is excluded from EIA.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

A game theory perspective on environmental assessment: What games are played and what does this tell us about decision making rationality and legitimacy?

Game theory provides a useful theoretical framework to examine the decision process operating in the context of environmental assessment, and to examine the rationality and legitimacy of decision-making subject to Environmental Assessment (EA). The research uses a case study of the Environmental Impact Assessment and Sustainability Appraisal processes undertaken in England. To these are applied an analytical framework, based on the concept of decision windows to identify the decisions to be assessed. The conditions for legitimacy are defined, based on game theory, in relation to the timing of decision information, the behaviour type (competitive, reciprocal, equity) exhibited by the decision maker, and the level of public engagement; as, together, these control the type of rationality which can be brought to bear on the decision. Instrumental rationality is based on self-interest of individuals, whereas deliberative rationality seeks broader consensus and is more likely to underpin legitimate decisions. The results indicate that the Sustainability Appraisal process, conducted at plan level, is better than EIA, conducted at project level, but still fails to provide conditions that facilitate legitimacy. Game theory also suggests that Sustainability Appraisal is likely to deliver ‘least worst’ outcomes rather than best outcomes when the goals of the assessment process are considered; this may explain the propensity of such ‘least worst’ decisions in practise. On the basis of what can be learned from applying this game theory perspective, it is suggested that environmental assessment processes need to be redesigned and better integrated into decision making in order to guarantee the legitimacy of the decisions made. - Highlights: • Decision legitimacy is defined in terms of game theory. • Game theory is applied to EIA and SA decision windows. • Game theory suggests least worst outcomes prevail. • SA is more likely to be perceived legitimate than EIA.

54 ENVIRONMENTAL SCIENCES↗