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Analyzing the Inflation Reduction Act and the Bipartisan Infrastructure Law for Their Effects on Nuclear Cost Data

Decarbonizing to meet aggressive climate change mitigation targets requires energy transition within all sectors. In the industrial sector, emissions will need to decrease by 65–90% by 2050 to avert global warming greater than 1.5°C (IPCC 2022). The Inflation Reduction Act (IRA), Bipartisan Infrastructure Law (BIL), and Defense Production Act (DPA) have clean energy requirements and provide financial incentives to accelerate the use of clean energy technologies in the industrial sector. It is important to note that IRA is the most extensive action ever taken by Congress and the U.S. government to combat climate change (US CBO 2021, 2022). The energy system provisions comprise most of the estimated climate and energy support. A better understanding of those provisions in the above mentioned acts and laws is crucial to assessing their impact on the equivalent energy costs to the power plant owners (impact on net revenue in $/MWh) across different energy technologies, market deployment potential offered to different energy technologies applications, and energy system research modeling. The purpose of the report is to shed light on IRA and BIL provisions with particular attention to impacts on the nuclear industry. The report also seeks to understand potential equivalent energy cost savings for nuclear energy technologies from other laws and programs in conjunction with IRA, BIL, loan program guarantees, and DPA. The report reviews recent legislation on energy policy and translates that policy to impacts on equivalent nuclear costs for the purpose of modeling policy in energy scenarios.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Economic Metrics for Commercial Reusable Space Transportation Systems

The success of any effort depends upon the effective initial definition of its purpose, in terms of the needs to be satisfied and the goals to be fulfilled. If the desired product is "A System" that is well-characterized, these high-level need and goal statements can be transformed into system requirements by traditional systems engineering techniques. The satisfaction of well-designed requirements can be tracked by fairly straightforward cost, schedule, and technical performance metrics. Unfortunately, some types of efforts, including those that NASA terms "Programs," tend to resist application of traditional systems engineering practices. In the NASA hierarchy of efforts, a "Program" is often an ongoing effort with broad, high-level goals and objectives. A NASA "project" is a finite effort, in terms of budget and schedule, that usually produces or involves one System. Programs usually contain more than one project and thus more than one System. Special care must be taken in the formulation of NASA Programs and their projects, to ensure that lower-level project requirements are traceable to top-level Program goals, feasible with the given cost and schedule constraints, and measurable against top-level goals. NASA Programs and projects are tasked to identify the advancement of technology as an explicit goal, which introduces more complicating factors. The justification for funding of technology development may be based on the technology's applicability to more than one System, Systems outside that Program or even external to NASA. Application of systems engineering to broad-based technology development, leading to effective measurement of the benefits, can be valid, but it requires that potential beneficiary Systems be organized into a hierarchical structure, creating a "system of Systems." In addition, these Systems evolve with the successful application of the technology, which creates the necessity for evolution of the benefit metrics to reflect the changing baseline. Still, economic metrics for technology development in these Programs and projects remain fairly straightforward, being based on reductions in acquisition and operating costs of the Systems. One of the most challenging requirements that NASA levies on its Programs is to plan for the commercialization of the developed technology. Some NASA Programs are created for the express purpose of developing technology for a particular industrial sector, such as aviation or space transportation, in financial partnership with that sector. With industrial investment, another set of goals, constraints and expectations are levied on the technology program. Economic benefit metrics then expand beyond cost and cost savings to include the marketability, profit, and investment return requirements of the private sector. Commercial investment criteria include low risk, potential for high return, and strategic alignment with existing product lines. These corporate criteria derive from top-level strategic plans and investment goals, which rank high among the most proprietary types of information in any business. As a result, top-level economic goals and objectives that industry partners bring to cooperative programs cannot usually be brought into technical processes, such as systems engineering, that are worked collaboratively between Industry and Government. In spite of these handicaps, the top-level economic goals and objectives of a joint technology program can be crafted in such a way that they accurately reflect the fiscal benefits from both Industry and Government perspectives. Valid economic metrics can then be designed that can track progress toward these goals and objectives, while maintaining the confidentiality necessary for the competitive process.

Shaw, Eric J.↗

Industrial process heat decarbonization: A user-centric perspective

Eliminating greenhouse gas emissions from industrial process heat (IPH) is considered a key element of decarbonizing the overall industrial sector. However, industrial users and the processes by which they may adopt and implement technologies for decarbonization have largely been overlooked in the United States by an emphasis on developing and commercializing new technologies. While recent deployment and demonstration programs are an indication that decarbonization policy is beginning to acknowledge industrial users, little research has been conducted to understand how users mediate technical and nontechnical requirements to decarbonize IPH. Our exploratory analysis uses interviews with industry representatives and document analysis to begin developing a user-centric perspective. Here, we find that successful adoption and implementation of decarbonized IPH technologies may require adaptation to diverse and potentially unique combinations of user requirements and local contexts. Instead of pursuing "crosscutting" IPH technologies, a more effective and expeditious approach may be to develop crosscutting decision-making that spans multiple technologies. This approach may offer unexplored opportunities to improve demonstration and deployment programs, but more user-centric research is needed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Energy Efficiency as a Foundational Technology Pillar for Industrial Decarbonization

The U.S. government aims to achieve net-zero greenhouse gas emissions by 2050 to reduce the severe impacts of climate change. The U.S. industrial sector will become a focal point for decarbonization since it accounts for 33% of the nation’s primary energy use and 30% of its energy-related CO2 emissions. Industrial emissions are also expected to increase by 15% through 2050, making the industrial sector a logical target for decarbonization efforts. Energy efficiency technology pathways provide low-cost, foundational routes to decarbonization that can be implemented immediately. Energy efficiency technology pathways, such as strategic energy management, system efficiency, smart manufacturing, material efficiency, and combined heat and power, are well established and would immediately reduce energy use and emissions. However, their role in the aggressive net-zero decarbonization pathway for the industrial sector is still unclear. This study aims to address energy efficiency pathways for decarbonization, and reviews studies related to these technologies for industrial decarbonization through 2050. This study identifies different strategies for the industrial sector in general and that are specific to six energy-intensive industries: iron and steel; chemical; food and beverage; petroleum refining; pulp and paper; and cement. Finally, a path toward the successful implementation of energy efficiency technologies is outlined.

Strategic energy management↗

Circular Economy Contributions to Decarbonizing the US Steel Sector

The potential benefits of the circular economy (CE) for decarbonization have recently attracted much attention in the academic and grey literature. The department of energy (DOE) industrial decarbonization roadmap highlight that in addition to the four pillars (energy efficiency, electrification, low-carbon fuels, feedstocks, and energy sources, and carbon capture, utilization, and storage (CCUS)) identified in the roadmap, "scenarios [...] will need to be developed that incorporate materials efficiency and circular economy strategies". Moreover, the roadmap identifies hard-to-abate CO2 emissions across the five industrial subsectors included in the analysis (iron & steel, chemical, food & beverage, refining, and cement manufacturing). Thus, additional options to decarbonize the industrial sector, like the CE, could prove beneficial to address those hard-to-abate emissions. Moreover, they may be less costly, require less R&D or incentives, and be more readily adopted than other strategies such as energy efficiency and CCUS. While the Industrial Decarbonization Roadmap includes some CE strategies (e.g., the increasing market share of steel from electric arc furnaces - which incorporate steel scrap), a deeper dive into what role the CE could play in the United States (US) industrial decarbonization is needed. In this work, we present several industrial decarbonization scenarios that incorporate materials efficiency and circular economy strategies for the iron & steel subsector. The scenarios identify barriers (including technical limits and constraints), opportunities, and R&D needs.Moreover, we estimate the contribution of those scenarios to reducing the industrial sector's CO2 emissions and their potential synergies with the Industrial Decarbonization Roadmap's four pillars. Iron & steel manufacturing was responsible for 90 million tons of industrial CO2 emissions in 2020 - 7% of the industrial sector's total process- related emissions. Besides recycling - which presents technical limitations due to trace contaminants - CE strategies on the demand side could lower iron & steel manufacturing emissions (e.g., the development of lighter products or business models that encourage a more intensive use). This study reviews barriers, opportunities, and trade-offs for 5 material efficiency strategies. Many topics explored in the review call for further research.

barriers↗

The Industrial Efficiency and Decarbonization Office

The Industrial Efficiency and Decarbonization Office (IEDO) supports innovation technologies and the adoption of practices to enable the industrial sector to cost-effectively reduce greenhouse gas (GHG) emissions. IEDO and its programs are critical to putting the Nation on a pathway to reduce CO2 emissions by 50% by 2030 when compared to 2005 levels, and to achieve net-zero carbon emissions by 2050. With 30% of primary energy-related emissions attributable to the industrial sector, IEDO builds upon a foundation of energy efficiency as a decarbonization pathway to include process electrification, use of low carbon fuels and feedstocks, and carbon capture to meet industrial emissions reductions targets. IEDO provides planning, management, and direction necessary for a balanced national program of research, development, demonstration, technical assistance, and workforce development to drive energy, materials and production efficiency, and decarbonization across the industrial sector.

Energy-Intensive Industries, Cross-Sector Technolo↗

CyTRICS Impact-Based Prioritization Process

Cyber Testing for Resilient Industrial Control Systems™ (CyTRICS™) is the Department of Energy’s (DOE’s) program for cybersecurity vulnerability testing, digital subcomponent enumeration, and forensic assessment. CyTRICS leverages best-in-class test facilities and analytic capabilities at six DOE National Laboratories and strategic partnerships with key stakeholders including technology developers, manufacturers, asset owners and operators, and interagency partners. During the program’s development, CyTRICS established a unique methodology for prioritizing digital components within operational technology (OT) and industrial control systems (ICS) in the Energy Sector Industrial Base (ESIB) for cyber vulnerability testing. The CyTRICS prioritization process leverages multiple characteristics of systems, components, and their contextual deployment to calculate a quantification of individual digital components for CyTRICS testing. The initial version of the CyTRICS prioritization process was premised largely upon the impact which could result to an energy sector industrial control system if the digital component under testing was compromised, either through malicious means, faulty engineering, or other modes. CyTRICS has termed this process the “CyTRICS Impact-based Prioritization Process.” This paper describes the factors identified for use in the Impact-based Prioritization process and identifies the rationale for inclusion. During development, three National Laboratories piloted this prioritization process and generated prioritization scores for seven systems. Following the piloting of the process, laboratory subject matter experts (SME) validated that the numerical scores generated by the prioritization process were consistent with their knowledge of the impact that may occur should any of these systems be disrupted. The following document explains how to perform the prioritization process to generate prioritization scores for energy sector systems. After outlining assumptions required to conduct the process, it describes how to identify and elicit data which can be leveraged to evaluate a system and assign numerical values for each factor. The prioritization process uses different weights on different factors; rationale for each weight is included within the paper. Additionally, the paper includes some recommendations for future enhancements to prioritization, including lessons learned from developing and piloting the process. Finally, a comprehensive appendix includes example documents to be leveraged by those looking to execute the prioritization process.

99 GENERAL AND MISCELLANEOUS↗

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↗

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↗

Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) for Prospective Impact Analysis of Novel 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. Additionally we compare our results by linking two other prospective models with LiAISON - GCAM (Global Change Assessment Model) and ReEDS (Regional Energy Deployment System) to analyze the effect of changing background scenarios using varying predictions in life cycle analysis.

decarbonizing↗

Towards Prospective LCA Using Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) Framework 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. Additionally we compare our results by linking two other prospective models with LiAISON - GCAM(Global Change Assessment Model) and ReEDS (Regional Energy Deployment System) to analyze the effect of changing background scenarios using varying predictions in life cycle analysis.

emissions↗

MEASUR Up: Identifying opportunities in a facility

The commercial and industrial sectors account for nearly half of the total U.S. energy consumption. To help these sectors reduce their energy intensity, the U.S. Department of Energy (DOE) designed the Better Buildings, Better Plants Initiative. Through this initiative, more than 900 industrial, commercial, public and residential organizations commit to long-term sustainability goals and share their proven energy efficiency strategies, which inspire others to tap into the continued potential for energy efficiency. Collectively, these organizations have saved 2.5 quadrillion BTUs of energy, equivalent to US$15.3 billion, and 155 million metric tons of carbon dioxide. Within the initiative, the Better Plants side of the program focuses specifically on the industrial sector. More than 270 industrial partners have taken advantage of the unique selection of resources offered including workforce development programs, information sharing, peer-to-peer networking, diagnostic tool loans and software tools. One of the most powerful tools off ered is a revitalization of the legacy DOE software tools used by industry for decades. These have been transformed into a new, free, opensource software tool suite: MEASUR (Manufacturing Energy Assessment Software for Utility Reduction)

Armstrong, Kristina↗

Global source apportionment of aerosols into major emission regions and sectors over 1850–2017

Anthropogenic emissions of aerosols and precursor gases have changed significantly in the past few decades around the world. In this study, the Explicit Aerosol Source Tagging (EAST) system is merged into the Energy Exascale Earth System Model version 1 (E3SMv1) to quantify the variations in anthropogenic aerosol concentrations, source contributions, and their subsequent radiative impact in four major emission regions across the globe during 1850–1980, 1980–2010, and 2010–2017. In North America and Europe, changes in anthropogenic PM 2.5 were mainly caused by changes in emissions from local energy and industrial sectors. The local industrial sector caused the largest increase in PM 2.5 in East Asia during 1980–2010 and decrease during 2010–2017. In South Asia, the increase in energy-related emissions dominated the rise in PM 2.5 levels during 1980–2017. During 1850–1980, the increases in emissions from North America contributed to the increase in the European PM 2.5 burden by 1.7 mg m -2 and the sources from the Europe were also responsible for the PM 2.5 burden increase in East Asia and South Asia by about 1.0 mg m -2 . During 1980–2010, East Asia contributed to an increase of 0.4–0.6 mg m -2 in the PM 2.5 burden in North America and Europe, while South Asia contributed about 0.3 mg m -2 . During 2010–2017, the contributions from East Asia to the PM 2.5 burdens in the North America, Europe, and South Asia declined by 0.3–0.6 mg m -2 due to the clean air actions in China, while the contributions from South Asia still increased due to the continuous increase in emissions in South Asia. The historical changes in aerosols had an impact on effective radiative forcing through aerosol–radiation interactions (ERF ari ). During 1980–2010, a decline in North American aerosols resulted in a positive ERF ari change (warming effect) in Europe and a decline in aerosols in Europe caused a warming effect in Russia and northern China. The changes in ERF ari from the increase and decrease in aerosols in China during 1980–2010 and 2010–2017, respectively, are comparable in magnitude. The continuous aerosol increases in South Asia from 1980 to 2017 resulted in negative ERF ari (cooling) changes in South Asia, Southeast Asia, and southern China.

54 ENVIRONMENTAL SCIENCES↗

Rare Earth Permanent Magnets: Supply Chain Deep Dive Assessment

The report “America’s Strategy to Secure the Supply Chain for a Robust Clean Energy Transition” lays out the challenges and opportunities faced by the United States in the energy supply chain as well as the federal government plans to address these challenges and opportunities. It is accompanied by several issue-specific deep dive assessments, including this one, in response to Executive Order 14017 “America’s Supply Chains,” which directs the Secretary of Energy to submit a report on supply chains for the energy sector industrial base. The Executive Order is helping the federal government to build more secure and diverse U.S. supply chains, including energy supply chains. This report focuses on the supply chain for rare earth permanent magnets, specifically sintered neodymiumiron-boron (NdFeB) magnets, used in clean energy technologies. Sintered NdFeB magnets are the strongest magnets commercially available and provide a host of benefits to wide-ranging applications in consumer and industrial electronics, especially in advanced motor and drive systems. Within the Energy Sector Industrial Base, and clean energy in particular, NdFeB magnets are key intermediate components of permanent magnet synchronous (direct drive) generators in wind turbines (especially for offshore turbines) and electric synchronous traction motors for propulsion systems in battery and hybrid electric vehicles.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

U.S. Industrial and Commercial Motor System Market Assessment Report Volume 1: Characteristics of the Installed Base

Motor systems are an integral part of our industrial and commercial facilities. They provide the motive force behind the fans, pumps, compressors, chillers, and conveyors in these facilities. Given their centrality to any facility’s operations, they are a critical energy end use to understand, particularly when developing technologies and policies to meet sustainability goals, improve productivity, and enhance resilience. In the late 1990s, the U.S. Department of Energy (DOE) conducted two seminal studies to better understand the installed stock and energy savings opportunities of industrial and commercial motor systems. In the industrial sector, The United States Industrial Electric Motor Systems Market Opportunities Assessment used primary data collected through onsite assessments and led to a greater understanding of the installed base of motor systems, their characteristics, and the opportunities for energy savings (U.S. Department of Energy, 2002). Notable findings included the following: Industrial motor systems consumed 679 billion kilowatt-hours (kWh) in 1994, representing 23 percent of U.S. electricity consumption. Cost-effective energy efficiency measures could result in 62-104 billion kWh of energy savings annually. Sixty-two percent of the energy savings potential was from fan, pump, and compressor end use equipment. Nearly half of motor system electricity consumption was attributable to approximately 3,500 facilities, or 1.5 percent of U.S. manufacturing facilities. Opportunities for Energy Savings in the Residential and Commercial Sectors with High Efficiency Electric Motors provided an evaluation of the installed stock of motor driven equipment in U.S. commercial and residential buildings and opportunities for utilization of high efficiency motors and variable speed technologies (Arthur D. Little, 1999). Notable findings included the following: Commercial motor systems consumed 343 billion kWh in 1995, with refrigeration and space conditioning constituting 93 percent of the total. Cost-effective energy efficiency measures could result in 51 billion kWh of energy savings annually. Due in no small part to these seminal studies, motor system technologies and usage characteristics have changed drastically since the late 1990s. Greater awareness of cost-effective strategies for reducing motor system electricity consumption have been developed and deployed. This includes several software tools, literature, and utility and government programs promoting energy efficiency improvements in motor driven systems. Additionally, several rounds of energy efficiency standards have been enacted, resulting in improved installed motor efficiency. The cost of variable speed drives has dropped substantially, and combined with utility rebate programs, has led to their greater adoption. Further, since these results were published, the U.S. manufacturing sector has undergone a massive transformation. Due to global competition, some sectors have relocated operations overseas. Others have brought operations onshore to avail low cost and abundant natural gas. Additionally, automation and robotics have pervaded the entire sector. Consequently, these two reports likely do not represent the current state of motor driven systems in U.S. industrial and commercial facilities. As cited in recent studies, the lack of current information on motor system electricity consumption and use characteristics limits the ability to conduct analysis on energy savings potential, develop technologies to address energy and productivity gaps, and develop programs to promote energy efficiency practices and technologies for motor systems (International Energy Agency, 2007; UNIDO, 2010; McKane and Hasanbeigi, 2011; Waide and Brunner, 2011). Specifically, the lack of information affects a range of stakeholders: Governments must rely on outdated information when setting research agendas, developing policies, and designing energy efficiency programs and offerings. Utilities and energy efficiency programs cannot identify the current market needs or potential impact when designing rebate and energy efficiency programs. Electric grid planners cannot identify motor system usage characteristics when developing plans to support the resilience of the electric grid. Manufacturers of motors, motor driven equipment, and drives are hampered when developing technologies to meet the needs of their market. Motor system end users are limited in their ability to identify energy saving opportunities within their own facilities because they do not have reliable benchmark information. In response to the lack of current information and analysis on industrial and commercial motor systems, the DOE initiated an update to these two studies. Launched in 2016 and led by Lawrence Berkeley National Laboratory (LBNL), the Motor System Market Assessment (MSMA) provides an updated, more comprehensive assessment of the installed stock of motor systems in both the industrial and commercial sectors, a review of the supply chains supporting motor and drives in the U.S., and the performance improvement opportunity available from using best available technologies and maintenance and operation practices. The outcomes of the MSMA are documented in three U.S. Industrial and Commercial Motor System Market Assessment reports, with this report being the first listed: 1. Volume 1: Characteristics of the Installed Base (this report) documents the findings on the installed base of motor systems in the U.S. industrial and commercial sectors. Quantification of energy savings potential is not documented in this report but in Volume 3. 2. Volume 2: Motors and Drives Supply Chain Review reviews the state of supply chains for motors and drives installed in U.S. industrial and commercial facilities, focusing on advanced motor and drive technologies and their constituent materials. 3. Volume 3: Energy Savings Opportunity analyzes the energy performance improvement opportunity for the installed base of U.S. industrial and commercial motor systems. This report has been prepared as a reference for motor system stakeholders. It provides factual information as could be best determined by the assessment results and avoids speculating on any findings.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Current and Future Developments in Air Traffic Control

Current and future energy demands, end uses, and cost used to characterize typical applications services in the industrial sector of the United States are examined. A review and evaluation of existing industrial energy data bases was undertaken to assess their potential for supporting SERI research market suitability analysis; (2) market development; (3) end use matching; (4) industrial application studies; and (5) identification of cost and performance goals for solar systems and typical information requirements for industrial energy end use. The focus was on fuels and electric energy used for heat and power purchased by the manufacturing subsector and listed by 2, 3, and 4 digit SIC, primary fuel. The effects of federal and state industrial energy conservation programs on future industrial sector demands were assessed.

Jackson, Joseph↗

Smart Manufacturing Pathways for Industrial Decarbonization and Thermal Process Intensification

Rapid decarbonization is fast becoming the primary environmental and sustainability initiative for many economic sectors. Industry consumes more than 30 % of all primary energy in the United States and accounts for nearly 25 % of all greenhouse gas (GHG) emissions. More than 70 % of energy consumed by the industrial sector is related to thermal processes, which are also the largest contributors of carbon emissions, overwhelmingly due to the combustion of fossil fuels. Thermal process intensification (TPI) seeks to dramatically improve the energy performance of thermal systems through technology pillars focusing on alternative energy sources and processes, supplemental technologies, and waste heat management. The impacts of TPI have significant overlap with the goals of industrial decarbonization (ID) that seeks to phase out all GHG emissions from industrial activities. Emerging supplemental technologies such as smart manufacturing (SM) and the industrial internet of things (IoT) enable significant opportunities for the optimization of manufacturing processes. Combining strategies for TPI and ID with SM and IoT can open and enhance existing opportunities for saving time and energy via approaches such as tighter control of temperature zones, better adjustment of thermal systems for variations in production levels and feedstock properties, and increased process throughput. Data collected by smart processes will also enable new advanced solutions such as digital twins and machine learning algorithms to further improve thermal system savings. Herein, this paper examines the individual pathways of TPI, ID, and SM and how the combination of all three can accelerate energy and GHG reductions.

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