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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Oak Ridge National Laboratory Pilot Demonstration of an Attestation and Anomaly Detection Framework using Distributed Ledger Technology for Power Grid Infrastructure

This report summarizes the design and pilot demonstration of a framework called Grid Guard that was created to provide increased data and device trustworthiness to electric grid devices by leveraging distributed ledger technology (DLT), specifically blockchain. Grid Guard contains a combination of core cryptographic methods such as the secure hash algorithm (SHA), and asymmetric cryptography, private permissioned blockchain, baselining configuration data, consensus algorithm (Raft) and the Hyperledger Fabric (HLF) framework. The system implements a low energy, fast, and robust enhancement to system trustworthiness within and across electric grid systems such as substations, control centers and metering infrastructures. Blockchain is a distributed database structured that provides a practically unalterable (immutable) timeline of stored transactions. By relying on hashing and the Raft consensus algorithm, if an entity tries to illegitimately alter a record at one instance of the database the other ledger nodes are not altered. They work to cross-reference each other and easily locate any incorrectly added data and remove it. The bulk raw data is stored in an off-chain storage (outside of the blockchain ledger) and a hash of this baseline data is stored in the Blockchain ledger via hashing windows of time-series and configuration data, after aggregation and filtering. The bulk off-chain data repository is then considered to be trust-anchored using the hashes stored in the blockchain. To secure the electric grid testbed devices and data, device configuration baselines were compared to those baselines that had been previously stored in the ledger. Statistical baselines for device configurations, network communication patterns, and high-speed sensor data are calculated and then stored off-chain and hashes stored in the ledger. Measurements such as three-phase voltage and current, frequency, breaker status, protection scheme settings, network configuration settings (and other device configuration artifacts) and network traffic features (packet interarrival times) are compared every minute or other selected time windows. During phase 1 of the Grid Guard DLT project different DLT technologies were studies, and an assessment was performed on DLT technology vulnerabilities, uses, and key characteristics. DLT consensus protocols were studies (e.g., RAFT, named after Reliable, Replicated, Redundant, And Fault-Tolerant). Also, cryptography, public, private and permissioned or permissionless systems were assessed. Grid Guard implements a permissioned private DLT. Consensus algorithm selection and choice of DLT implementation depended heavily on the use-case. For this use-case, parameters were selected to measure performance and existing tools for assessment. Benchmarking was performed theoretically and practically. During phase 2 hashed transactions/blocks were inserted into the ledger every second. During phase 2 of the Grid Guard DLT project, a prototype framework was developed and demonstrated for attestation of critical substation devices and data using precision timing systems that use PTP and IRIG-B protocols) on a testbed of operational devices that emulated a distribution substation, control center, and power metering infrastructure using real Operational Technology (OT). The testbed includes OT devices such as protective relays, human machine interfaces (HMI), and power meters. To determine when to collect and compare system and network baselines, an initial examination of an anomaly detection capability to identify malicious manipulation of data streams was conducted. The resulting anomaly detection was demonstrated in a set of experiments and leveraged to trigger device artifact attestation checks. Attestation checks occur against device configuration baselines when compared with the immutable blockchain-stored baselines, which provided a cryptographically supported means by which to store baselines. The electrical substation-grid testbed was created to test the Grid Guard framework. The testbed emulates the operations of a portion of a power grid and SCADA systems as closely as possible. The testbed integrates real protocols, mainly IEC 61850 standard protocols, such as the Sampled Value (SV) and the GOOSE protocols. The testbed also supports DNP3 and other layer 2 and layer 3 protocols such as Telnet, SSH, SFTP/FTP and other proprietary protocols needed to connect to industrial control system equipment. The testbed emulates real power conditions using the OpalRT hardware-in-the-loop (HIL) device which can create fault situations that cannot be easily tested on real systems. The electrical substation-grid testbed was created using real measurement, communication, and protection devices that electrical utilities commonly use.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Integrating field observations and process-based modeling to predict watershed water quality under environmental perturbations

Watersheds play a critical role in supplying water resources needed for human use and ecosystem health. Understanding and predicting how, when, and where changes in the quantity and quality of water resources occur under different environmental stresses including extreme events is crucial for sustainable management of water resources under a changing environment. However, few studies have attempted to quantify or identify the factors and process interactions controlling the impact of extreme events across water-shed systems. Only few large-scale studies include coordinated monitoring and modeling efforts, which limits our ability to assess the large-scale impact of extreme events on water supply and quality. Methods are lacking to propagate uncertainty in process understanding through an integrated hydro-biogeochemical model framework and evaluate its importance, thus failing to take full advantage of the information potentially available through transformative advances in characterization technologies from high-resolution mass spectrometry to airborne and satellite-based remote sensing. There are consequent risks to our nations water security and to human and ecosystem health that may become exacerbated with the increasing frequency of extreme events that is projected for the coming decades. This paper reviews the current status of watershed science for both water quantity and quality and identifies critical gaps in our current knowledge and modeling capability in addressing the emergent needs in predicting watershed hydrologic and biogeochemical responses (i.e., water quantity and quality) under natural and anthropogenic perturbations. We highlight the need to (1) understand how environmental perturbations including extreme events like floods and droughts propagate through watershed systems and assess their short- and long-term impacts on watershed biogeochemistry, water quality and their recovery pathways; (2) develop and improve a watershed water quality model that reflects the state of scientific understanding gained from observations; and (3) construct a data-model fusion system for watershed characterization, process identification, and mechanistic model parameterization. A large base of modeling, monitoring and data capabilities have been built by various federal government agencies given the relevance of water to their critical missions. An emerging need is to build an integrated national capability for watershed water availability and quality that can address water-related missions across multiple federal agencies.

13 HYDRO ENERGY↗
DOE OSTI2022

Fundamentals of hydrogen storage in nanoporous materials

Abstract Physisorption of hydrogen in nanoporous materials offers an efficient and competitive alternative for hydrogen storage. At low temperatures (e.g. 77 K) and moderate pressures (below 100 bar) molecular H 2 adsorbs reversibly, with very fast kinetics, at high density on the inner surfaces of materials such as zeolites, activated carbons and metal–organic frameworks (MOFs). This review, by experts of Task 40 ‘Energy Storage and Conversion based on Hydrogen’ of the Hydrogen Technology Collaboration Programme of the International Energy Agency, covers the fundamentals of H 2 adsorption in nanoporous materials and assessment of their storage performance. The discussion includes recent work on H 2 adsorption at both low temperature and high pressure, new findings on the assessment of the hydrogen storage performance of materials, the correlation of volumetric and gravimetric H 2 storage capacities, usable capacity, and optimum operating temperature. The application of neutron scattering as an ideal tool for characterising H 2 adsorption is summarised and state-of-the-art computational methods, such as machine learning, are considered for the discovery of new MOFs for H 2 storage applications, as well as the modelling of flexible porous networks for optimised H 2 delivery. The discussion focuses moreover on additional important issues, such as sustainable materials synthesis and improved reproducibility of experimental H 2 adsorption isotherm data by interlaboratory exercises and reference materials.

08 HYDROGEN↗
DOE OSTI2026

Performance Assessment of a Heat Pump Integrated with Thermal Energy Storage in Cooling & Heating Modes

Thermal Energy Storage (TES) systems have demonstrated significant potential to manage the fluctuating nature of energy demand and shifting peak loads. This technology has made significant recent advances, including new research on the integration of TES with residential and commercial Heating, Ventilation, and Air-Conditioning (HVAC) systems. In this paper, we present the use of a novel laboratory assessment framework for a prototype heat pump system integrated with latent heat phase change material-based TES. The assessment framework consists of 22 total test points (11 heating, 11 cooling) using psychrometric conditions from AHRI Standard 210/240 and includes transient conditions to evaluate TES charging and discharging modes. In addition, both continuous mode and cyclic mode were evaluated for charging and discharging to explore the benefits to TES heat transfer from repeated transient operation. The ambient conditions evaluated include heating mode charging at cold-climate heat pump conditions when winter-peaking utilities may most require demand reduction (H4Full conditions, 5°F/-15°C) and cooling mode charging at high ambient temperature that may occur during times of day when excess solar power generation results in low-cost electricity (105°F/40.6°C). The work demonstrates the demand reduction capabilities of integrating TES with HVAC, including up to 44% in cooling mode and 60% in heating mode compared to conventional HVAC equipment without TES.

25 ENERGY STORAGE↗
DOE OSTI2024

Embedded FPGA developments in 130 nm and 28 nm CMOS for machine learning in particle detector readout

Embedded field programmable gate array (eFPGA) technology allows the implementation of reconfigurable logic within the design of an application-specific integrated circuit (ASIC). This approach offers the low power and efficiency of an ASIC along with the ease of FPGA configuration, particularly beneficial for the use case of machine learning in the data pipeline of next-generation collider experiments. An open-source framework called "FABulous" was used to design eFPGAs using 130 nm and 28 nm CMOS technology nodes, which were subsequently fabricated and verified through testing. The capability of an eFPGA to act as a front-end readout chip was assessed using simulation of high energy particles passing through a silicon pixel sensor. A machine learning-based classifier, designed for reduction of sensor data at the source, was synthesized and configured onto the eFPGA. A successful proof-of-concept was demonstrated through reproduction of the expected algorithm result on the eFPGA with perfect accuracy. Finally, further development of the eFPGA technology and its application to collider detector readout is discussed.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Grid Architecture Mapping to Understand Transformation (GAMUT): Methods and Framework Architecture

Grid architecture (GA) is a concept that was developed to address the need for a comprehensive view of power grid challenges. GA can be viewed as a relatively consistent and fixed high-level approach; however, for any instantiation of grid structures, a combinatorial explosion results from each lower-layer expansion. This constitutes the main challenge with GA—it is a grid architect’s view of the system, which might not be very informative at the implementation level. Grid Architecture Mapping to Understand Transformation (GAMUT project) seeks to bridge that gap by integrating subject matter expertise across GA structures, providing users who lack expertise in GA approaches with valuable insights and informational materials. GAMUT seeks to answer feasibility questions for the approach. System-level expectations are that a GA baseline needs to be established in order for GA to be the common framework to which any lower layer approach is tied. This report explores a potential information ingestion and documentation framework to support GAMUT. The main concepts that enable the solution domain of GAMUT are discussed, and examples are provided. The solution domain leverages already-existing technology and concepts related to GA, knowledge management, and other relevant areas. To assess GAMUT building blocks and the overall approach, a feasibility assessment is proposed, rooted in systems engineering and GA architecture evaluation concepts.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

A Bayesian and HRA-Aided Method for the Novel Reliability Analysis of Software

Technological advancements and nuclear power plant modernization has inspired considerable research in the areas of safety and reliability, yet there remains a lack of consensus for the reliability assessment of digital instrumentation and control (I&C) systems. Motivated by the lack of consensus for reliability analysis methods, this work employs a novel framework that incorporates Bayesian, human reliability, and common-cause failure (CCF) modeling techniques. The novel framework allows the use of state-of-the-art or classical modeling techniques when accounting for human and CCF effects on system reliability. The Bayesian and HRA-Aided Method for the Reliability Analysis of Software (BAHAMAS) is demonstrated by a case study for the quantification of software hazards found in a previous analysis of a digital reactor trip system. The results demonstrate the ability of BAHAMAS to account for human activities during the software development life cycle and their influence on software reliability. BAHAMAS is a flexible tool for extending the coverage of conventional probabilistic risk assessments to include modernized digital I&C systems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Cybersecurity Resiliency of Marine Renewable Energy Systems Part 2: Cybersecurity Best Practices and Risk Management

Marine renewable energy (MRE) is an emerging source of power for marine applications, marine devices, and coastal communities. This energy source relies on industrial control systems and IT to support operations and maintenance activities, which create a pathway for an adversary to gain unauthorized access to systems and data and disrupt operations. Incorporating cybersecurity risk prevention measures and mitigation capabilities from inception, development, operation, to decommissioning of the MRE system and components is paramount to the protection of energy generation and the security of network architecture and infrastructure. To improve the resilience of MRE systems as a predictable, affordable, and reliable source of energy, cybersecurity guidance was developed to enable operators to assess cybersecurity risks and implement security measures commensurate with the risk. This publication is the second of a two-part series, with Part 1 addressing a framework to determine cybersecurity risk by assessing the vulnerability of an MRE system to potential cyber threats and the consequences a cyberattack would have on the end user. This Part 2 publication describes an approach to select appropriate cybersecurity best practices commensurate with the MRE system's cybersecurity risk. The guidance includes 86 cybersecurity best practices, which are associated with 36 cybersecurity domains and grouped into nine categories. The best practices follow the core functions of the National Institute of Science and Technology Cybersecurity Framework (e.g., identify, detect, protect, respond, and and recover) and insights from both maritime and energy industry guidance documents to identify security measures effective in protecting information and operational technology assets prevalent in MRE systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Operational Energy Life Cycle Data Development for the National Institute of Standards And Technology (NIST) Building Industry Reporting and Design for Sustainability (BIRDS) Neutral Environmental Software Tool (NEST)

For this analysis, regionalized life cycle assessment (LCA) results for environmental impacts (using the Tool for Reduction and Assessment of Chemicals and Other Environmental Impacts [TRACI] 2.1) and cumulative energy demand (using the Federal Life Cycle Analysis Commons Elementary Flow List [FEDEFL] Inventory Methods v1.0.0) were evaluated for the production and utilization of electricity, natural gas, fuel oil, and propane as commodities within residential and commercial buildings. These results can used as a framework for future research into net zero, high-performance buildings, such as done here for the Building Industry Reporting and Design for Sustainability (BIRDS) database by the National Institute of Standards and Technology (NIST) Engineering Laboratory. The geographical results were assigned to each United States (U.S.) Zone Improvement Plan (ZIP) code based on the ZIP code location and corresponding Balancing Authority Area, natural gas basin, and Petroleum Administration for Defense Districts (PADDs). Additionally, previously developed models were utilized to develop future life cycle profiles. Projections were based on data available from the U.S. Energy Information Administration Annual Energy Outlook 2022 through 2050 (AEO 2022). Electricity LCA models were updated based on AEO 2022 projected annual generation mixes, while the natural gas baseline model was updated based on projected shares of natural gas types (conventional, shale, tight, and coalbed methane). Projections of crude oil production rates and export rates were applied to the petroleum baseline model in five-year increments to investigate their effects on the life cycle profile of fuel oil and propane. While only 100-year Global Warming Potential (GWP-100) with climate carbon feedback (CC-FB) and Cumulative Energy Demand are shown in Section 4: Results, the complete results, including Acidification Potential, Eutrophication Potential, Freshwater Ecotoxicity Potential, GWP-100 without inclusion of CC-FB, Human Health Impacts Potentials (Cancer, Non-Cancer), Ozone Depletion Potential, Particulate Matter Formation Potential, and Photochemical Smog Formation Potential, are tabulated for each ZIP code in the Excel worksheets that accompany this analysis. For the Excel spreadsheet tools associated with this report, please go to https://www.netl.doe.gov/energy-analysis/details?id=f8890fac-be55-44ac-aaa9-e2888bfabe93

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Sustainability in Directed Energy Deposition

Directed energy deposition (DED) additive manufacturing (AM) has been recognized as an efficient and sustainable technology in the field of advanced manufacturing. In the past few years, Considerable discussion has been made by researchers to promote DED AM for better performance in manufacturing. The discussions focus on basic theoretical research, process optimization and control, technology innovation, and industrial applications. However, this technology׳s environmental and economic benefits over traditional manufacturing processes are still to be seen and its sustainability is also a mystery. Here, this chapter presents a critical overview of the environmental sustainability of DED to provide a comprehensive understanding of the effects of materials, processing conditions, and geometric complexities on the energy consumption and environmental impacts of DED and provide a better guide for decision-makers in terms of selecting suitable manufacturing processes. In addition, this chapter proposes a novel framework for DED AM sustainability assessment and improvement based on the Life Cycle Assessment (LCA) method and multi-objective optimization. At last, future perspectives and recommendations for the sustainability of DED AM are put forward.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Overview and Recommendations for Cyber Risk Assessment in Nuclear Power Plants

Digital instrumentation and control (I&C) systems are being deployed in nuclear power plants (NPPs) for both existing and advanced reactor designs. As I&C systems become more digitized to allow features like near autonomous control and remote operation, they introduce greater cyber risk to NPPs. Cyberattacks targeting industrial control systems (ICSs) are growing in both qualities and capabilities, which indicates that cybersecurity needs to be an integral part of risk assessment in the industry. Although there are some risk assessment methods in traditional information technology (IT) cybersecurity, the differences between IT and ICS cybersecurity make it infeasible to apply these risk assessment methods directly to ICSs. Some research has focused on risk assessment methods for ICSs, but few studies focus on applications to NPPs. Ideal risk frameworks for the nuclear industry are dynamic and account for system dependencies; this survey review focuses on such risk assessment methods both in and outside the nuclear field. In this article, the major challenges in cybersecurity risk assessment research are pointed out, and further research suggestions and considerations for cyber risk assessment in I&C systems are identified.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Progress and prospects of thermo-mechanical energy storage – A critical review

The share of electricity generated by intermittent renewable energy sources is increasing (now at 26% of global electricity generation) and the requirements of affordable, reliable and secure energy supply designate grid-scale storage as an imperative component of most energy transition pathways. The most widely deployed bulk energy storage solution is pumped-hydro energy storage (PHES), however, this technology is geographically constrained. Alternatively, flow batteries are location independent and have higher energy densities than PHES, but remain associated with high costs and low lifetimes, which highlights the importance of developing and utilizing additional larger-scale, longer-duration and long-lifetime energy storage alternatives. Here, we review a class of promising bulk energy storage technologies based on thermo-mechanical principles, which includes: compressed-air energy storage (CAES), liquid-air energy storage (LAES) and pumped-thermal electricity storage (PTES). The thermodynamic principles upon which these thermo-mechanical energy storage (TMES) technologies are based are discussed and a synopsis of recent progress in their development is presented, assessing their ability to provide reliable and cost-effective solutions. The current performance and future prospects of TMES systems are examined within a unified framework and a thermoeconomic analysis is conducted to explore their competitiveness relative to each other as well as when compared to PHES and flow battery systems. This includes carefully selected thermodynamic and economic methodologies for estimating the component costs of each configuration in order to provide a detailed and fair comparison at various system sizes. The analysis reveals that the technical and economic characteristics of TMES systems are such that, especially at higher discharge power ratings and longer discharge durations, they can offer promising performance (round-trip efficiencies higher than 60%) along with high lifetimes (> 30 years), low specific costs (often below 100 $/kWh), low ecological footprints and unique sector-coupling features compared to other storage options. TMES systems have significant potential for further progress and the thermoeconomic comparisons in this paper can be used as a benchmark for their future evolution.

25 ENERGY STORAGE↗
DOE OSTI2023

Electrical Fault Detection, Power Quality, Distributed Energy Resource Use Cases, and Cyber Event Applications with the Cyber Grid Guard System Using Distributed Ledger Technology

Electrical utilities continue to deploy more intelligent electronic devices (IEDs) inside and outside electrical substation and are associated with distributed energy resources (DERs). The integrity and confidentiality of data from IEDs is crucial, and distributed ledger technology (DLT) could improve the resilience of microgrids by helping to make these data more secure. The most popular applications using blockchain technology for electrical utilities is in the field is based on energy trading. However, the dynamism of the penetration of customer owned DERs and the deployment of sensors with IEDs have led to the identification of new applications using DLT that are focused on other areas, such as monitoring, operation and management of the grid and its assets. In addition, the majority of studies on electrical grid applications with blockchain were validated with software simulations. Although general monitoring of power systems for using DLT could be evaluated in operational electric grids, other DLT research applications such as defense against cyber-attacks and/or electrical fault detection are not likely to be performed in a real infrastructure because of possible risks to the network/equipment security. This report summarizes the application of power system applications using distributed ledger technology (DLT), providing a secure DLT framework for collecting data from IEDs like power meters and protective relays inside and outside of an electrical substation and/or between two different electrical utilities. In this study, the use case scenarios were created and assessed for different power system application by using DLT. The electrical fault detection for faulted phases (1), power quality monitoring of phase voltage magnitudes, frequency levels and load power factor (2), DERs use case monitoring (3), and cyber-event applications (4) were performed in a test bed with a Cyber-Grid Guard (CGG) system using DLT. It had a real-time simulator with power meters and protective relays in-the-loop. The first section of this report presents a literature review of power system applications using blockchain at research level. The second section shows the theory and equations used on this report. The third section shows the description of the test bed, equipment, architecture, and electrical grid diagrams. The fourth section shows the experimental models and use case scenarios that were performed for the electrical fault detection, power quality, DERs use case, and cyber event applications with the CGG system using DLT. The fifth section shows the results collected from the tests based on comparing the time stamped events of the analog signals from the IEDs, DLT computer and real time simulator. The sixth section performed the discussion of the results for the use case scenarios. Finally, section seven presents the conclusions for this report were presented.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Risk Management for Distributed Energy Resources

The National Institute of Standards and Technology will be hosting on Tuesday, February 2 and Wednesday, February 3, 2021, the second workshop in a new series focusing on the Open Security Controls Assessment Language. NREL extended the scope of the DERCF to include the NIST Risk Management Framework (RMF), addressing the challenges faced by federal energy managers when complying with the NIST RMF for DER systems. The NIST RMF is a cyclical process designed to incorporate principles of security and risk management into an organization’s system policies and procedures. The DER-RM will be downloadable application that runs locally and documents all the major requirements for achieving Authority to Operate the DER.

cybersecurity↗
DOE OSTI2020

Advances in GDSA Framework Development and Process Model Integration

The Spent Fuel and Waste Science and Technology (SFWST) Campaign of the U.S. Department of Energy (DOE) Office of Nuclear Energy (NE), Office of Spent Fuel & Waste Disposition (SFWD) is conducting research and development (R&D) on geologic disposal of spent nuclear fuel (SNF) and highlevel nuclear waste (HLW). A high priority for SFWST disposal R&D is to develop a disposal system modeling and analysis capability for evaluating disposal system performance for nuclear waste in geologic media. This report describes fiscal year (FY) 2020 advances of the Geologic Disposal Safety Assessment (GDSA) Framework and PFLOTRAN development groups of the SFWST Campaign. The common mission of these groups is to develop a geologic disposal system modeling capability for nuclear waste that can be used to probabilistically assess the performance of disposal options and generic sites. The capability is a framework called GDSA Framework that employs high-performance computing (HPC) capable codes PFLOTRAN and Dakota.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Assessing the behavioral realism of energy system models in light of the consumer adoption literature

Effective policymaking to achieve net zero greenhouse gas emissions demands an understanding of the complex drivers of, and barriers to, consumer adoption behavior via behaviorally realistic energy system models. Existing models tend to oversimplify by focusing on homogenized financial factors while neglecting consumer heterogeneity and non-monetary influences. This study develops and applies a comprehensive framework for evaluating the behavioral realism of consumer adoption models, informed by the adoption literature. It introduces a typology for factors influencing low-carbon technology adoption decisions: monetary and non-monetary factors relating to household characteristics, psychology, technological attributes, and contextual conditions. Next, reviews of the consumer adoption and decision-making literature identify the most influential adoption factor categories for distributed solar photovoltaics, electric vehicles, and air-source heat pumps. Finally, the extent to which a selection of energy system models accounts for these adoption factors is assessed. Existing models predominantly emphasize the economic aspects of technology, which are generally identified as the most important factors. Where the models fall short — in considering moderately important factor categories — sector-specific and agent-based models can offer more behaviorally realistic insights. This study sheds light on which types of factors are most important for consumer adoption decisions and investigates how well current models rise to the challenge of behavioral realism. The end-to-end analysis presented enables internally consistent comparisons across models and energy technologies. This research advances timely conversations on consumer adoption. It could inform more behaviorally realistic energy system modeling, and thereby more effective decarbonization policymaking.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Environmental and Social Justice Implications of a Circular Plastics Economy

A consideration of environmental justice (EJ) and social justice (SJ) is critical to minimize the impacts of technology deployment on local communities. SJ and EJ impacts occur in specific geographic locations but can cover a wide range of effects (e.g., air pollution, access to clean water, jobs, wages, and education), making it challenging to determine which metrics are appropriate to evaluate and which data are required. Thus, there is currently a gap in the analysis community's ability to provide useful and universal EJ and SJ metrics for emerging technologies. Here, we present a draft framework for evaluating the human health, local environment, and job implications of processes that are at an early or middle technology readiness level (TRL). Using a case study on enzymatic polyethylene terephthalate (PET) recycling (middle TRL), we demonstrate how to qualitatively and quantitatively assess these EJ and SJ metrics for a circular economy context and how to communicate the results in a manner beneficial to both researchers and local communities.

circular economy↗