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DOE OSTI2025

Análisis de Tareas del Inspector de Control de Calidad [Quality Control Inspector Job Task Analysis (Spanish Translation)]

El Laboratorio Nacional de Energía Renovable (NREL) ha sido contratado por el Programa de Asistencia para la Climatización (WAP) del Departamento de Energía de EE.UU. (DOE) para desarrollar y mantener los recursos en el marco del proyecto de Directrices para Profesionales de la Energía Doméstica (GHEP). El objetivo del proyecto GHEP es aumentar la calidad del trabajo realizado para la remodelación energética residencial en Estados Unidos a través de WAP y otros programas de remodelación residencial. Para cumplir el objetivo de “Establecer certificaciones nacionales de la mano de obra y normas de formación”, el DOE encargó al NREL el desarrollo de recursos GHEP, incluido un conjunto de certificaciones avanzadas, basadas en aptitud, para el personal de los profesionales de la energía doméstica (HEP). Desde 2010, el NREL ha reclutado voluntarios expertos en la materia de WAP y de la industria del mantenimiento del hogar para que formen parte de comités que desarrollen y actualicen programas de certificación y sus análisis de tareas (JTA) necesarios como base de programas de certificación y formación estandarizados. Las certificaciones HEP apoyan al WAP y al sector del mantenimiento de viviendas residenciales en general mediante el proceso de acreditación y el desarrollo de JTA definidos para auditores energéticos (EA) e inspectores de control de calidad (QCI). Este informe es un resumen de las actualizaciones más recientes (2022) del JTA del QCI. [The National Renewable Energy Laboratory (NREL) is contracted by the U.S. Department of Energy (DOE) Weatherization Assistance Program (WAP) to develop and maintain the resources under the Guidelines for Home Energy Professionals (GHEP) project. The purpose of the GHEP project is to increase the quality of work conducted for residential energy retrofits in the United States through the WAP network and other residential retrofit programs. This is the Spanish translation of NREL/TP-7A40-85789.]

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Análisis de Tareas del Auditor Energético [Energy Auditor Job Task Analysis (Spanish Translation)]

El Laboratorio Nacional de Energía Renovable (NREL), bajo el contrato con el Programa de Asistencia para la Climatización (WAP) del Departamento de Energía de EE.UU. (DOE), desarrolla y mantiene los recursos en el marco del proyecto Directrices para Profesionales de la Energía Doméstica (GHEP). El objetivo del proyecto GHEP es aumentar la calidad del trabajo de remodelación energética residencial realizado por WAP y otros programas de remodelación residencial en Estados Unidos. Para cumplir el objetivo de “Establecer certificaciones nacionales de la mano de obra y normas de formación”, el DOE encargó al NREL el desarrollo de recursos GHEP, incluido un conjunto de certificaciones avanzadas, basadas en aptitud, para el personal de los profesionales de la energía doméstica (HEP). Desde 2010, el NREL ha reclutado voluntarios expertos en la materia de WAP y de la industria del mantenimiento del hogar para que formen parte de comités que desarrollen y actualicen programas de certificación y sus análisis de tareas (JTA) necesarios como base de programas de certificación y formación estandarizados. Las certificaciones HEP apoyan al WAP y al sector del mantenimiento de viviendas residenciales en general mediante el proceso de acreditación y el desarrollo de JTA definidos para auditores energéticos (EA) e inspectores de control de calidad (QCI). Este informe es un resumen de las actualizaciones más recientes (2022) del JTA del EA. [The National Renewable Energy Laboratory (NREL) is contracted by the U.S. Department of Energy (DOE) Weatherization Assistance Program (WAP) to develop and maintain the resources under the Guidelines for Home Energy Professionals (GHEP) project. The purpose of the GHEP project is to increase the quality of work conducted for residential energy retrofits in the United States through the WAP network and other residential retrofit programs. This is the Spanish translation of NREL/TP-7A40-85300.]

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

The Cost of Saving Electricity: A Multi-Program Cost Curve for Programs Funded by U.S. Utility Customers

This study analyzed the cost performance of electricity efficiency programs implemented by 116 investor-owned utilities between 2009 and 2015 in 41 states, representing about three-quarters of the total spending on U.S. efficiency programs. We applied our typology to characterize efficiency programs along several dimensions (market sector, technology, delivery approach, and intervention strategy) and report the costs incurred by utilities and other program administrators to achieve electricity savings as a result of the programs. Such cost performance data can be used to compare relative costs of different types of efficiency programs, evaluate efficiency options alongside other electricity resources, benchmark local efficiency programs against regional and national cost estimates, and assess the costs of meeting state efficiency policies. The savings-weighted average cost of saved electricity for the period was $0.025/kilowatt-hour (kWh). The cost of saved electricity for programs that targeted residential customers was $0.021/kWh, compared to $0.025/kWh for programs for commercial and industrial customers. Ultimately, we developed an aggregate program savings “cost curve” for the actual electricity efficiency resource during the period that provides insights into the relative costs of various types of efficiency programs and the savings contribution of each program type to the efficiency resource at a national level.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Final Technical Report

Statement of the problem or situation that is being addressed in your application. The DOE and its national laboratories developed the Home Energy Score™ (HES) to encourage homeowners to improve their energy performance, lower costs and to share energy information through the MLS listing, appraisal, and financing channels. While the HES is an instrumental tool, it is currently underutilized and consists of technical, structural and sector barriers which need to be addressed in order to scale and many energy efficiency contractors are understandably overwhelmed by the added time and effort and lack of incentive to sell and deliver deep retrofit projects while simultaneously meeting the DOE HES program requirements; consequently, contractors may decide to forgo participation. Home Energy Rating System (HERS) Raters have the opportunity to play the critical Assessor role in producing a Home Energy Score (HES); this role has immense potential but currently is unfulfilled. Lastly, while utilities are interested in their customer base achieving greater energy efficiency, especially to help offset growing residential loads in states like California that are accelerating electrification, utilities do not have access to the market actors who are on the front line of influence to homeowners or review and approve their permits: HERS Raters, assessors, contractors and building departments. General statement of how this problem is being addressed: ConSol will integrate the Home Energy Score™ (HES) to its State of California, approved home energy rating services (HERS) platform (CHEERS) to develop a single tool for contractors nationwide to assess, record and install recommended cost, energy, and emissions saving measures to the 140 million single-family homes throughout the U.S. and 14 million homes in California (CHEERS+HES). The CHEERS high fidelity energy code permitting data will be integrated with HES for simple, accurate, easy-to-use home energy estimation and analysis and will directly gain access to the retrofit and renovations markets with the same upgraded platform. This innovative project will assist the utilities in supporting existing homes in their jurisdictions with HES and develop measures to improve energy efficiency and reduce emissions. How is this problem being addressed? What is the overall project approach? In effort to expand the Home Energy Score™ (HES) by increasing the use of aggregable home energy asset data, ConSol proposes to integrate the DOE HES via Application Programming Interface (API) to its State of California approved home energy rating services platform (CHEERS). Once the CHEERS platform and HES are integrated (CHEERS+HES), this enhanced platform will be instantly available and actively deployed via Phase 1 pilot to HERS Raters, assessors and contractors in California to market-test the solution, understand the rate of adoption and identify opportunities for improvement prior to scaling nationally. The CHEERS high fidelity energy code permitting data will be integrated with HES for simple, accurate, easy-to-use home energy estimation and analysis and will directly gain access to the retrofit and renovations markets with the same upgraded platform. This innovative project will assist the building industry and homeowners with an easy-to-use assessment if energy and carbon impacts of existing homes, and assist the utilities in supporting existing homes in their jurisdictions with HES to improve energy efficiency and reduce emissions. What is to be done in Phase I? During Phase I of this proposed project, ConSol will (1) design software architecture that links CHEERS to the Home Energy ScoreTM via API, (2) solicit partnership from one or more California utilities for a regional pilot, (3) test the new software with its HERS Raters and contractor network in the partnership utility jurisdiction, (4) launch a pilot version of the newly developed software with HERS Raters and contractors in the utility territory, and (5) explore California’s GoGreen energy efficiency homeowner lending program in parallel with the pilot. Commercial Applications and Other Benefits. Summarize the future applications or public benefits if the project is carried over into Phase II or Phase III and beyond. The CHEERS+HES commercialized product will be ready for national market scale following a successful Phase 1 performance. The CHEERS+HES adoption is estimated to reach a 5% adoption growth rate versus the 110,000 baseline, starting in Year 1 after Phase I completion, and continuing each year. As a direct benefit to the DOE, CHEERS will set a goal of 100,000 Home Energy Score assessments for existing home alterations within the first 10 years following Phase 1 performance. The technical benefits of this proposed project include the harmonized, automated, and seamless integration of the DOE HES into the widely used and market leading California energy registry, CHEERS. The social benefits include the aggregate energy, cost and GHG savings by allowing the broader public streamlined access to the CHEERS+HES measurement and the energy efficiency recommended measures that may result. Key Words: Home Energy ScoreTM (HES); Application Programming Interface (API); Home Energy Rating Services (HERS); HERS Raters; contractors; assessors; existing homes, energy asset data; cost, energy, and emissions saving measures; energy code (Title 24) compliance; document repository; utilities; pilot; newly developed software; energy efficiency; homeowner. Summary for Members of Congress: The DOE Home Energy Score™ (HES) is a tool to encourage homeowners to improve their energy performance, lower costs and share energy information but is underutilized and consists of barriers which need to be addressed in order to scale. In effort to expand the HES, CHEERS, Inc. will integrate the HES to its State of California, approved home energy rating services (HERS) platform (CHEERS) to develop a single tool for contractors nationwide to assess, record and install recommended cost, energy, and emissions saving measures to the 140 million single-family homes throughout the U.S. and 14 million homes in California.

Application Programming Interface (API)↗
DOE OSTI2020

California Time-of-Use (TOU) Transition: Effects on Distributed Wind and Solar Economic Potential

Time-of-use (TOU) retail energy rates price electricity differently by the time of day, communicating to consumers the costs of supplying electricity diurnally. This study evaluates the impact of Decision D.15.07-001, which mandates a transition in 2020 to default TOU rates for residential ratepayers in California, on the economic viability of behind-the-meter distributed wind and solar systems. Previous studies have demonstrated that increasing wind and solar generation will materially affect the diurnal cost of wholesale electricity. As retail and wholesale prices become more aligned, this could affect the inter-technology economic viability of distributed generation. We assess economic viability through 'economic potential,' or the amount of generation capacity that exceeds a rate of return of 5.4%. In addition, we identify sensitivities of economic potential to capital costs and other techno-economic factors as well as the specific counties and sectors with substantial economic potential. We find that TOU implementation is projected to moderately increase economic potential of distributed wind and marginally decrease that of distributed solar. Over the long-term as variable renewable energy penetration increases in California, particularly utility-scale solar, net peak load and thus peak prices will shift later in the evening. To the extent that retail rates continue to evolve with wholesale prices, we find the changes could positively affect the value of wind generation more than that of solar generation. Over the scenarios considered, model results indicate realistic pathways to reaching a robust distributed wind market in California though solar economic potential was found to be substantially larger than that of wind.

17 WIND ENERGY↗
DOE OSTI2023

Enhancing flexibility for climate change using seasonal energy storage (aquifer thermal energy storage) in distributed energy systems

Long-term energy storage is expected to play a vital role in the deep decarbonization of building energy sectors, while enhancing the flexibility of buildings to withstand future climate variations. However, it is challenging to design distributed multi-energy systems (DMES) while taking into account the uncertainties introduced by climate change, since stochastic optimization of such systems is difficult. The present study introduces a stochastic optimization model to address this bottleneck, taking into account DMES including aquifer thermal energy storage (ATES) as the long-term thermal storage. For the first time, a novel optimization algorithm links ATES with the DMES optimization model with the support of a simplified geotechnical model. Subsequently, a case study was conducted, focusing on a residential district in Chicago where the impact of future climate condition, energy demand, and solar and wind energy potentials were evaluated using Weather Research and Forecasting (WRF) data (up to 2080) and the EnergyPlus model. The study revealed that ATES is an attractive way to improve the renewable energy penetration level and minimize the dependence on fossil fuels with reasonable support from the grid to assist the fluctuations in both demand and generation. Furthermore, ATES notably reduces fuel consumption and dependence while greatly enhancing the flexibility of the energy system to withstand fluctuations in demand and renewable energy generation brought by future climate variations. These qualities will make ATES an important part of distributed energy systems, even though it is not currently the lowest cost alternative due to lack of technology maturity. Furthermore, the design platform introduced in the present study can be used to design DMES enhancing flexibility to accommodate future climate variations.

25 ENERGY STORAGE↗
DOE OSTI2019

Preliminary Routing for a National Laboratory Lab-Wide Commuting Program

There is a growing interest in reducing the amount of vehicle miles traveled (VMT), both in public and private sector organizations, in an effort to reduce overall carbon emissions. The Oak Ridge National Laboratory (ORNL), located in Oak Ridge, Tennessee, and located within close proximity to Knoxville, Tennessee, has more than 4,500 employees, most of which live in and around Knoxville. ORNL is currently developing a pilot commuting program for all employees, which incorporates the use of park-and-ride facilities. This study outlines the methodology behind the preliminary geoanalysis and routing used in developing a lab-wide commuting program. Due to privacy concerns, the data used for the study included numbers of employee residences per zip code rather than actual residential addresses. Commuting configurations by clustered zip code area and vehicle type were developed based on number of residences in a limited area, and the desire to minimize VMT. Central locations were selected using ArcGIS software. Satellite imagery was used to locate actual, suitable parking facilities to accommodate the specified number of residents involved in each commuting configuration. Optimized routing, and estimations of travel times, were performed using TransCAD GIS software. Energy estimates in kilowatt-hours (kwh) and gallons of gasoline, and gallons of gasoline equivalent, were all determined based on the scenarios. Standard petroleum-fueled vehicles were used in the initial estimates. Standard electric vehicles were also used in alternative scenarios to estimate potential additional energy and fuel savings. Furthermore the initial findings from this work will be used to develop a pilot program for ORNL.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Centering Energy and Environmental Justice in the Buildings Energy Sector

We face incredible challenges for decarbonizing our economy and raising the standard of living for all members of our society at the same time. Historical energy efficiency efforts have been effective in making small steps, but they fall far short of the massive changes we need to make, and they completely miss helping communities of disadvantage (e.g. low-income, African American, Hispanic American, Native American and tribal nations, etc). Business as usual efforts do not take the time to connect with and understand the challenges of these historical underinvested communities and therefore have not been effective at helping these communities. The Biden Harris Administration has set ambitious goals for decarbonization of our economy that include a requirement that 40% of efforts support energy and environmental justice communities. If we are to meet our decarbonization goals, it is imperative that we change our approach to research, development, and deployment of new technologies. The Department of Energy has set energy justice as a priority and is working with the national laboratories to change our approaches. This paper starts with definitions of what we mean by energy and environmental justice and how they apply to building technologies and deployment efforts. We provide several examples of how historical efforts have succeeded and how they have failed to account for challenges of communities of disadvantage. We identify market and technology barriers to decarbonization and energy efficiency for specific technologies and how these barriers are exacerbated for disadvantaged communities. From these examples, we propose a new framework for integrating energy and environmental justice into all aspects of technology development, deployment, and policy efforts within the building energy sector.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Choosing the Best Carbon Factor for the Job: Exploring Available Carbon Emissions Factors and the Impact of Factor Selection

Over 600 local governments in the United States, including nearly half of the largest 100 cities, have enacted climate action plans that include carbon reduction goals and greenhouse gas inventories (Markolf et al. 2020). The magnitude of these goals ranges from modest reduction targets to carbon neutrality. None will be met without significant contributions from the buildings sector. Understanding how energy efficiency and building electrification impact greenhouse gas emissions requires local, time-sensitive, and forward-looking carbon emissions factors for electricity use in buildings. There are a variety of emissions factors currently available from various sources, including average emissions factors and historical short-run marginal emissions factors. Long-run marginal emissions factors and future-year short-run marginal emissions factors are also now available from the National Renewable Energy Laboratory's (NREL's) Cambium data sets. In this paper, we describe the different carbon emissions factors available, including both conventional sources and newly available options. We discuss the types of analyses each emissions factor is best suited to support. Then, using residential energy efficiency and electrification load profiles, we demonstrate how different conclusions result from different choices of carbon emissions factors. For two grid regions, we explore takeaways of using current versus future-year emissions, short-run versus long-run, and levelized versus single-year values. We include a framework for selecting the best carbon emissions factor for the job.

carbon emissions factors↗
DOE OSTI2024

Choosing the Best Carbon Factor for the Job: Exploring Available Carbon Emissions Factors and the Impact of Factor Selection: Preprint

Over 600 local governments in the United States, including nearly half of the largest 100 cities, have enacted climate action plans that include carbon reduction goals and greenhouse gas inventories (Markolf et al. 2020). The magnitude of these goals ranges from modest reduction targets to carbon neutrality. None will be met without significant contributions from the buildings sector. Understanding how energy efficiency and building electrification impact greenhouse gas emissions requires local, time-sensitive, and forward-looking carbon emissions factors for electricity use in buildings. There are a variety of emissions factors currently available from various sources, including average emissions factors and historical short-run marginal emissions factors. Long-run marginal emissions factors and future-year short-run marginal emissions factors are also now available from the National Renewable Energy Laboratory's (NREL's) Cambium data sets. In this paper, we describe the different carbon emissions factors available, including both conventional sources and newly available options. We discuss the types of analyses each emissions factor is best suited to support. Then, using residential energy efficiency and electrification load profiles, we demonstrate how different conclusions result from different choices of carbon emissions factors. For two grid regions, we explore takeaways of using current versus future-year emissions, short-run versus long-run, and levelized versus single-year values. We include a framework for selecting the best carbon emissions factor for the job.

carbon emissions factors↗
DOE OSTI2016

Energy Efficiency Building Systems Regional Innovation Cluster Initiative

The Consortium for Building Energy Innovation (CBEI) was established through a Funding Opportunity Announcement led by the U.S. Department of Energy, under a cooperative agreement managed by the National Energy Technology Laboratory. CBEI is led by The Pennsylvania State University and is composed of partners from academia, the private sector, and economic development agencies. The Consortium has included as many as 24 different partners over the five years, but 14 have been core to the work over the five year cooperative agreement. CBEI primarily focused on developing energy efficiency solutions for the small and medium commercial building market, with a focus on buildings less than 50,000 square feet. This market has been underserved by the energy efficiency industry, which has focused on larger commercial buildings where the scale of an individual retrofit lends itself to the use of sophisticated modeling tools and more advanced solutions. Owners/operators and retrofit providers for larger buildings have a greater level of understanding of, and experience with different solutions. In contrast, smaller commercial building retrofits, like residential retrofits, often have owners with less knowledge about energy management and less time to learn about it. This market segment is also served by retrofit providers that are smaller and often focused on particular building systems, e.g. heating, ventilation and air conditioning (HVAC), lighting, roofing, or insulation. The size of a smaller commercial building retrofit does not lend itself, from a cost perspective, to the application of multiple, sophisticated design and modeling tools, which means that they are less likely to have integrated solutions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

U.S. Solar Photovoltaic System Cost Benchmark: Q1 2017

NREL has been modeling U.S. photovoltaic (PV) system costs since 2009. This year, our report benchmarks costs of U.S. solar PV for residential, commercial, and utility-scale systems built in the first quarter of 2017 (Q1 2017). Costs are represented from the perspective of the developer/installer, thus all hardware costs represent the price at which components are purchased by the developer/installer, not accounting for preexisting supply agreements or other contracts. Importantly, the benchmark this year (2017) also represents the sales price paid to the installer; therefore, it includes profit in the cost of the hardware, along with the profit the installer/developer receives, as a separate cost category. However, it does not include any additional net profit, such as a developer fee or price gross-up, which are common in the marketplace. We adopt this approach owing to the wide variation in developer profits in all three sectors, where project pricing is highly dependent on region and project specifics such as local retail electricity rate structures, local rebate and incentive structures, competitive environment, and overall project or deal structures.

14 SOLAR ENERGY↗
DOE OSTI2018

The Demand-Side Grid (dsgrid) Model

This presentation gives a high-level overview of the recently published demand-side grid (dsgrid) model documentation. The general modeling philosophy and technical approach of dsgrid is described, as is an initial data set covering 2012 contiguous United States (CONUS) electricity demand. The initial data set describes about 80% of electrical load at an hourly level by county, subsector and end use. Coarser models and data sets are used to describe the remainder. Model residuals are calculated at different levels of aggregation by leveraging historical electricity sector data and a model of 2012 distributed generation. Overall, the dsgrid model has been developed to support analysis of future load scenarios, including interactive effects between energy efficiency, electrification, demand response, renewable energy, battery energy (or other forms of) storage, and future grid conditions broadly construed. Planned future work includes the development of future load scenarios and physically realistic estimates of the flexible load resource.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

U.S. Solar Photovoltaic System Cost Benchmark: Q1 2017

NREL has been modeling U.S. photovoltaic (PV) system costs since 2009. This year, our report benchmarks costs of U.S. solar PV for residential, commercial, and utility-scale systems built in the first quarter of 2017 (Q1 2017). Costs are represented from the perspective of the developer/installer, thus all hardware costs represent the price at which components are purchased by the developer/installer, not accounting for preexisting supply agreements or other contracts. Importantly, the benchmark this year (2017) also represents the sales price paid to the installer; therefore, it includes profit in the cost of the hardware, along with the profit the installer/developer receives, as a separate cost category. However, it does not include any additional net profit, such as a developer fee or price gross-up, which are common in the marketplace. We adopt this approach owing to the wide variation in developer profits in all three sectors, where project pricing is highly dependent on region and project specifics such as local retail electricity rate structures, local rebate and incentive structures, competitive environment, and overall project or deal structures.

14 SOLAR ENERGY↗
DOE OSTI2020

MFRED, 10 second interval real and reactive power for groups of 390 US apartments of varying size and vintage

Abstract Building electricity is a major component of global energy use and its environmental impacts. Detailed data on residential electricity use have many interrelated research applications, from energy conservation to non-intrusive load monitoring, energy storage, integration of renewables, and electric vs. fossil-based heating. The dataset presented here, Multifamily Residential Electricity Dataset (MFRED), contains the electricity use of 390 apartments, ranging from studios to four-bedroom units. All apartments are located in the Northeastern United States (IECC-climate-zone 4 A), but differ in their heating/cooling system and construction year (early to late 20 th century). To adhere to privacy guidelines, data were averaged across 15 apartments each, based on annual electricity use. MFRED includes real and reactive power, at 10-second resolution, for January to December 2019 (246 million data points). The annual average real power per apartment is 343 W (3.27 W/m 2 of floor area), with strong variation between seasons and apartment size. Considering its large number of apartments, high time resolution, real and reactive power, and 12-month duration, MFRED is currently unique for the multifamily-sector.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

U.S. Solar Photovoltaic System Cost Benchmark: Q1 2017

This report benchmarks U.S. solar photovoltaic (PV) system installed costs as of the first quarter of 2017 (Q1 2017). We use a bottom-up methodology, accounting for all system and projectdevelopment costs incurred during the installation to model the costs for residential, commercial, and utility-scale systems. In general, we attempt to model the typical installation techniques and business operations from an installed-cost perspective. Costs are represented from the perspective of the developer/installer; thus, all hardware costs represent the price at which components are purchased by the developer/installer, not accounting for preexisting supply agreements or other contracts. Importantly, the benchmark also represents the sales price paid to the installer; therefore, it includes profit in the cost of the hardware, 1 along with the profit the installer/developer receives, as a separate cost category. However, it does not include any additional net profit, such as a developer fee or price gross-up, which is common in the marketplace. We adopt this approach owing to the wide variation in developer profits in all three sectors, where project pricing is highly dependent on region and project specifics such as local retail electricity rate structures, local rebate and incentive structures, competitive environment, and overall project or deal structures. Finally, our benchmarks are national averages weighted by state installed capacities.

14 SOLAR ENERGY↗
DOE OSTI2014

Emerging Technologies in the Built Environment: Geographic Information Science (GIS), 3D Printing, and Additive Manufacturing

Abstract 1: Geographic information systems emerged as a computer application in the late 1960s, led in part by projects at ORNL. The concept of a GIS has shifted through time in response to new applications and new technologies, and is now part of a much larger world of geospatial technology. This presentation discusses the relationship of GIS and estimating hourly and seasonal energy consumption profiles in the building sector at spatial scales down to the individual parcel. The method combines annual building energy simulations for city-specific prototypical buildings and commonly available geospatial data in a GIS framework. Abstract 2: This presentation focuses on 3D printing technologies and how they have rapidly evolved over the past couple of years. At a basic level, 3D printing produces physical models quickly and easily from 3D CAD, BIM (Building Information Models), and other digital data. Many AEC firms have adopted 3D printing as part of commercial building design development and project delivery. This presentation includes an overview of 3D printing, discusses its current use in building design, and talks about its future in relation to the HVAC industry. Abstract 3: This presentation discusses additive manufacturing and how it is revolutionizing the design of commercial and residential facilities. Additive manufacturing utilizes a broad range of direct manufacturing technologies, including electron beam melting, ultrasonic, extrusion, and laser metal deposition for rapid prototyping. While there is some overlap with the 3D printing talk, this presentation focuses on the materials aspect of additive manufacturing and also some of the more advanced technologies involved with rapid prototyping. These technologies include design of carbon fiber composites, lightweight metals processing, transient field processing, and more.

New, Joshua Ryan↗
DOE OSTI2016

Depleted and enriched uranium exposure quantified in former factory workers and local residents of NL Industries, Colonie, NY USA

Background: Between 1958 and 1982, NL Industries manufactured components of enriched (EU) and depleted uranium (DU) at a factory in Colonie NY, USA. More than 5 metric tons of DU was deposited as microscopic DU oxide particles on the plant site and surrounding residential community. A prior study involving a small number of individuals (n=23) indicated some residents were exposed to DU and former workers to both DU and EU, most probably through inhalation of aerosol particles. Objectives: Our aim was to measure total uranium [U] and the uranium isotope ratios: {sup 234}U/{sup 238}U; {sup 235}U/{sup 238}U; and {sup 236}U/{sup 238}U, in the urine of a cohort of former workers and nearby residents of the NLI factory, to characterize individual exposure to natural uranium (NU), DU, and EU more than 3 decades after production ceased. Methods: We conducted a biomonitoring study in a larger cohort of 32 former workers and 99 residents, who may have been exposed during its period of operation, by measuring Total U, NU, DU, and EU in urine using Sector Field Inductively Coupled Plasma - Mass Spectrometry (SF-ICP-MS). Results: Among workers, 84% were exposed to DU, 9% to EU and DU, and 6% to natural uranium (NU) only. For those exposed to DU, urinary isotopic and [U] compositions result from binary mixing of NU and the DU plant feedstock. Among residents, 8% show evidence of DU exposure, whereas none shows evidence of EU exposure. For residents, the [U] geometric mean is significantly below the value reported for NHANES. There is no significant difference in [U] between exposed and unexposed residents, suggesting that [U] alone is not a reliable indicator of exposure to DU in this group. Conclusions: Ninety four percent of workers tested showed evidence of exposure to DU, EU or both, and were still excreting DU and EU decades after leaving the workforce. The study demonstrates the advantage of measuring multiple isotopic ratios (e.g., {sup 236}U/{sup 238}U and {sup 235}U/{sup 238}U) over a single ratio ({sup 235}U/{sup 238}U) in determining sources of uranium exposure. - Highlights: • Biomonitoring study of residents and former workers exposed to DU in Colonie NY. • Urine (99 residents+32 former workers) analyzed for depleted uranium (DU). • DU detected in 84% of workers and 8% of residents >30 years after plant closed. • Enriched uranium detected in 6% of former workers based on isotope ratios.

54 ENVIRONMENTAL SCIENCES↗