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DOE OSTI2020

Impacts of land use change and elevated CO 2 on the interannual variations and seasonal cycles of gross primary productivity in China

Climate change, rising CO 2 concentration, and landuse and land cover change (LULCC) are primary driving forces for terrestrialgross primary productivity (GPP), but their impacts on the temporal changesin GPP are uncertain. In this study, the effects of the three main factorson the interannual variation (IAV) and seasonal cycle amplitude (SCA) of GPPin China were investigated using 12 terrestrial biosphere models from theMulti-scale Synthesis and Terrestrial Model Intercomparison Project. Thesimulated ensemble mean value of China's GPP between 1981 and 2010, drivenby common climate forcing, LULCC and CO 2 data, was found to be7.4±1.8 Pg C yr -1 . In general, climate was the dominant controlfactor of the annual trends, IAV and seasonality of China's GPP. Theoverall rising CO2 led to enhanced plant photosynthesis, thusincreasing annual mean and IAV of China's total GPP, especially innortheastern and southern China, where vegetation is dense. LULCC decreasedthe IAV of China's total GPP by ~7%, whereas rising CO 2 induced an increase of 8 %. Compared to climate change andelevated CO 2 , LULCC showed less contributions to GPP's temporalvariation, and its impact acted locally, mainly in southwestern China.Furthermore, this study also examined subregional contributions to thetemporal changes in China's total GPP. Southern and southeastern Chinashowed higher contributions to China's annual GPP, whereas southwestern andcentral parts of China explained larger fractions of the IAV in China's GPP.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Hemispherically symmetric strategies for stratospheric aerosol injection

Stratospheric aerosol injection (SAI) comes with a wide range of possible design choices, such as the location and timing of the injection. Different stratospheric aerosol injection strategies can yield different climate responses; therefore, understanding the range of possible climate outcomes is crucial to making informed future decisions on SAI, along with the consideration of other factors. Yet, to date, there has been no systematic exploration of a broad range of SAI strategies. This limits the ability to determine which effects are robust across different strategies and which depend on specific injection choices. This study systematically explores how the choice of SAI strategy affects climate responses in one climate model. Here, we introduce four hemispherically symmetric injection strategies, all of which are designed to maintain the same global mean surface temperature: an annual injection at the Equator (EQ), an annual injection of equal amounts of SO 2 at 15° N and 15° S (15N+15S), an annual injection of equal amounts of SO 2 at 30° N and 30° S (30N+30S), and a polar injection strategy that injects equal amounts of SO 2 at 60° N and 60° S only during spring in each hemisphere (60N+60S). We compare these four hemispherically symmetric SAI strategies with a more complex injection strategy that injects different quantities of SO 2 at 30° N, 15° N, 15° S, and 30° S in order to maintain not only the global mean surface temperature but also its large-scale horizontal gradients. All five strategies are simulated using version 2 of the Community Earth System Model with the middle atmosphere version of the Whole Atmosphere Community Climate model, version 6, as the atmospheric component, CESM2(WACCM6-MA), with the global warming scenario, Shared Socioeconomic Pathway (SSP)2-4.5. We find that the choice of SAI strategy affects the spatial distribution of aerosol optical depths, injection efficiency, and various surface climate responses. In addition, injecting in the subtropics produces more global cooling per unit injection, with the EQ and the 60N+60S cases requiring, respectively, 59 % and 50 % more injection than the 30N+30S case to meet the same global mean temperature target. Injecting at higher latitudes results in larger Equator-to-pole temperature gradients. While all five strategies restore Arctic September sea ice, the high-latitude injection strategy is more effective due to the SAI-induced cooling occurring preferentially at higher latitudes. These results suggest trade-offs wherein different strategies appear better or worse, depending on which metrics are deemed important.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Historical and projected future runoff over the Mekong River basin

The Mekong River (MR) crosses the borders and connects six countries, including China, Myanmar, Laos, Thailand, Cambodia, and Vietnam. It provides critical water resources and supports natural and agricultural ecosystems, socioeconomic development, and the livelihoods of the people living in this region. Understanding changes in the runoff of this important international river under projected climate change is critical for water resource management and climate change adaptation planning. However, research on long-term runoff dynamics for the MR and the underlying drivers of runoff variability remains scarce. Here, we analyse historical runoff variations from 1971 to 2020 based on runoff gauge data collected from eight hydrological stations along the MR. With these runoff data, we then evaluate the runoff simulation performance of five global hydrological models (GHMs) forced by four global climate models (GCMs) under the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP). Furthermore, based on the best simulation combination, we quantify the impact of future climate change on river runoff changes in the MR. The result shows that the annual runoff in the MR has not changed significantly in the past 5 decades, while the establishment of dams and reservoirs in the basin visibly affected the annual runoff distribution. The ensemble-averaged result of the Water Global Assessment and Prognosis version 2 (WaterGAP2; i.e. GHM) forced by four GCMs has the best runoff simulation performance. Under Representative Concentration Pathways (RCPs; i.e. RCP2.6, RCP6.0 and RCP8.5), the runoff of the MR is projected to increase significantly (p<0.05); e.g. 3.81 ± 3.47 m 3 s -1 a -1 (9 ± 8 % increase in 100 years) at the upper reach under RCP2.6 and 16.36 ± 12.44 m 3 s -1 a -1 (13 ±10 % increase in 100 years) at the lower reach under RCP6.0. In particular, under the RCP6.0 scenario, the increase in annual runoff is most pronounced in the middle and lower reaches, due to increased precipitation and snowmelt. Under the RCP8.5 scenario, the runoff distribution in different seasons varies obviously, increasing the risk of flooding in the wet season and drought in the dry season.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

The value of wake steering wind farm flow control in US energy markets

Abstract. Wind farm flow control represents a category of control strategies for achieving wind-plant-level objectives, such as increasing wind plant power production and/or reducing structural loads, by mitigating the impact of wake interactions between wind turbines. Wake steering is a wind farm flow control technology in which specific turbines are misaligned with the wind to deflect their wakes away from downstream turbines, thus increasing overall wind plant power production. In addition to promising results from simulation studies, wake steering has been shown to successfully increase energy production through several recent field trials. However, to better understand the benefits of wind farm flow control strategies such as wake steering, the value of the additional energy to the electrical grid should be evaluated – for example, by considering the price of electricity when the additional energy is produced. In this study, we investigate the potential for wake steering to increase the value of wind plant energy production by combining model predictions of power gains using the FLOw Redirection and Induction in Steady State (FLORIS) engineering wind farm flow control tool with historical electricity price data for 15 existing US wind plants in four different electricity market regions. Specifically, for each wind plant, we use FLORIS to estimate power gains from wake steering for a time series of hourly wind speeds and wind directions spanning the years 2018–2020, obtained from the ERA5 reanalysis dataset. The modeled power gains are then correlated with hourly electricity prices for the nearest transmission node. Through this process we find that wake steering increases annual energy production (AEP) between 0.4 % and 1.7 %, depending on the wind plant, with average increases in potential annual revenue (i.e., annual revenue of production, ARP) 4 % higher than the AEP gains. For most wind plants, ARP gain was found to exceed AEP gain. But the ratio between ARP gain and AEP gain is greater for wind plants in regions with high wind penetration because electricity prices tend to be relatively higher during periods with below-rated wind plant power production, when wake losses occur and wake steering is active; for wind plants in the Southwest Power Pool – the region with the highest wind penetration analyzed (31 %) – the increase in ARP from wake steering is 11 % higher than the AEP gain. Consequently, we expect the value of wake steering, and other types of wind farm flow control, to increase as wind penetration continues to grow.

17 WIND ENERGY↗

DOE OSTI2024

Seasonal variability of wake impacts on US mid-Atlantic offshore wind plant power production

Abstract. The mid-Atlantic will experience rapid wind plant development due to its promising wind resource located near large population centers. Wind turbines and wind plants create wakes, or regions of reduced wind speed, that may negatively affect downwind turbines and plants. We evaluate wake variability and annual energy production with the first yearlong modeling assessment using the Weather Research and Forecasting model, deploying 12 MW turbines across the domain at a density of 3.14 MW km−2, matching the planned density of 3 MW km−2. Using a series of simulations with no wind plants, one wind plant, and complete build-out of lease areas, we calculate wake effects and distinguish the effect of wakes generated internally within one plant from those generated externally between plants. We also provide a first step towards uncertainty quantification by testing the amount of added turbulence kinetic energy (TKE) by 0 % and 100 %. We provide a sensitivity analysis by additionally comparing 25 % and 50 % for a short case study period. The strongest wakes, propagating 55 km, occur in summertime stable stratification, just when New England's grid demand peaks in summer. The seasonal variability of wakes in this offshore region is much stronger than the diurnal variability of wakes. Overall, yearlong simulated wake impacts reduce power output by a range between 38.2 % and 34.1 % (for 0 %–100 % added TKE). Internal wakes cause greater yearlong power losses, from 29.2 % to 25.7 %, compared to external wakes, from 14.7 % to 13.4 %. The overall impact is different from the linear sum of internal wakes and external wakes due to non-linear processes. Additional simulations quantify wake uncertainty by modifying the added amount of turbulent kinetic energy from wind turbines, introducing power output variability of 3.8 %. Finally, we compare annual energy production to New England grid demand and find that the lease areas can supply 58.8 % to 61.2 % of annual load. We note that the results of this assessment are not intended to make nor are they suitable to make commercial judgments about specific wind projects.

17 WIND ENERGY↗

DOE OSTI2023

Informed Feature Selection for Data Clustering of CSP Plant Production

To make concentrating solar power (CSP) more cost competitive, rigourous optimizations must be run to improve plant design and operations. However, these optimizaitons rely on time consuming annual simulations that solve an electricity dispatch scheduling problem to maximize plant revenue. To reduce the runtime of annual dispatch simulations of CSP plants, a data clustering approach is utilized. This approach assumes that like days of revenue and electricity generation can be identified using weather and price data. Although weather and price are important factors for electricity production, this work investigates how thermal energy storage (TES) inventory at the beginning of a day, denoted as Si, can be used as a supplemental feature to group like days. A framework for creating and training a deep neural network to predict Si is proposed. This model is validated and assessed using eleven sets of testing data that were not used during training. Then, the data clustering approach is performed three seperate times with features of weather and price along with either Si from the neural network, Si from the full annual simulation, or no Si. Ultimately, the results suggest that using Si as an additional clustering feature improves the data clustering simulation accuracy by 1.4%.

Tuman, Matthew J. (ORCID:000900038772051X)↗

DOE OSTI2026

Local Air Quality Impacts of a Peak-Shaving Diesel Generator Unit in Waynesville, North Carolina

The Waynesville Electric Department in Waynesville, North Carolina, operates a 2,000-kW diesel generator with a 4% capacity factor, emitting less than 1 ton annually of PM2.5, VOCs, carbon monoxide (CO), and sulfur dioxide (SO2), and approximately 1.8 tons of NO. The National Laboratory of the Rockies (NLR) conducted high-resolution, near-source air-quality modeling to evaluate the generator's impacts. Results indicate minimal effects on ambient pollutant concentrations: annual PM2.5 increases are below 0.0004 microgrm/m3 for local census tracts, while CO and SO2 levels increase by less than 0.00004 ppm and 0.0002 ppb, respectively. Estimated annual premature mortality attributable to PM2.5 exposure is less than 0.001 cases across Haywood County, with an associated economic impact of approximately $12,000. This report complements a separate technoeconomic analysis to inform Waynesville's investment strategies for demand reduction.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

An Assessment of Impacts on Electric End-Use Load Profile of a Typical Residential Building from a Ground Source Heat Pump Systems Integrated with Underground Thermal Energy Storage

Buildings are the primary users of electricity, and a considerable amount of electric energy consumed in residential and commercial buildings is for meeting thermal demands (e.g., space heating/cooling, water heating, etc.). Therefore, integrating thermal energy storage with a building’s energy system has the potential to reshape the electric load profile of the building and mitigate the mismatch between the renewable power supply and the thermal demands of buildings. A novel ground-source heat pump system (GSHP) integrated with underground thermal energy storage (UTES) has been developed to enable flexible electric demand at buildings while meeting their thermal demands with an energy-efficient GSHP system. This paper assessed the potential impacts of the proposed system on the peak electrical demand and annual electricity consumption in a typical residential building at various climate zones in the United States. The results show that by replacing the conventional HVAC system (air conditioner and natural gas furnace) with the UTES integrated GSHP system, summer peak electric demand can be reduced by 27% to 50% depending on the weather. Although the winter peak electrical demand could be increased by up to 70% if the proposed system replaces natural gas furnace, the existing electricity supply system for single-family homes in most regions of the United States have adequate capacity for the replacement. While eliminating the natural gas consumption for space heating, the proposed system consumes more electricity on an annual basis in heating-dominated regions. However, it consumes less electricity in cooling dominated regions. The resulting variance in annual electricity consumption in various climate zones is within 15% compared with the baseline system.

Shi, Liang↗

DOE OSTI2020

The Cost of Comfort in Your Home: Peak-Time Energy and Cost Savings from Setpoint Adjustment of Space Heating and Cooling

This poster presents the tradeoff between energy costs and thermal comfort in homes. Residential heating and cooling systems use a thermostat control to maintain a comfortable temperature range, but tighter temperature control leads to higher annual energy costs. We estimate the impact of temperature setpoint adjustment on annual energy costs using a residential building model developed at NREL. We show that increasing the allowable temperature range reduces energy costs in all five of the climate zones in the U.S. Annual costs reduced by about $100, with larger savings in areas with more heating and/or cooling loads.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2021

Optimal Sizing of an Electric Vehicle Charging Station with Integration of PV and Energy Storage

This paper proposes an optimization model for the optimal configuration of an grid-connected electric vehicle (EV) extreme fast charging station considering integration of photovoltaic (PV) and energy storage. The proposed model minimizes the annualized net cost (i.e., maximizes the annualized net profit) of the extreme fast charging station, including investment and maintenance cost of charging ports, PV and energy storage, net cost of purchasing energy from utility and selling energy to EV customers, degradation cost of energy storage and demand charge. The decision variables are number of charging ports, capacity of invested PV and the power and energy ratings of invested energy storage. The Erlang-loss system is adopted to model the EV mobility. Results of numerical simulations indicate that investment of PV and energy storage could increase the annualized profit of the extreme fast charging station. In addition, the impacts of various parameters on the optimal solution are investigated by sensitivity analysis.

Liu, Guodong↗

DOE OSTI2020

Effect of Power Plant Capacity on the CAPEX, OPEX, and LCOC of the CO2 Capture Process in Pre-Combustion Applications - Abstract

Aspen Plus v8.8 was used to simulate the pre-combustion CO2 capture process from a typical fuel gas stream at different power plant capacities ranging from 54.3 to 543 MW. Polyethylene glycol polydimethyl siloxane (PEGPDMS-1) was used as a physical solvent to capture CO2 in a countercurrent packed-bed absorber containing a structured packing (Mellapak 250Y). The process pressure was 51.4 bar and the solvent temperature was varied from 10 to 40 oC. The internal diameter of the absorber ranged from 1.9 to 7 m and the packing height from 13.9 to 45.5 m. The physico-chemical properties were obtained and modeled using the Perturbed Chain-Statistical Associating Fluid Theory (PC-SAFT) Equation-of-State (EOS). Four process constraints were imposed in Aspen Plus: (1) no flooding in the absorber, (2) the absorber height to diameter ratio (H/D) is greater than or equal 6, (3) at least 90 mol% of the CO2 capture from the fuel gas stream, and (4) the CO2 stream destined to sequestration sites should contain less than 600 ppm water concentration and less than or equal 0.5 mol% of fuel gases (H2, CO, CH4). The plant lifetime was assumed to be 30 years with an annual discount rate of 10% and an annual maintenance cost of 4% of the total capital expenses. Seven power plants with different capacities were used and for each plant, the corresponding CO2 capture process was simulated. The absorber flooding was checked using the generalized pressure drop correlation (GPDC) by Leva [1] and the capital expenditure (CAPEX), operating expenditure (OPEX), and levelized costs per ton of CO2 captured (LCOC) were calculated [2-5]. Normalized by the largest power plant capacity (543 MW) used in the simulation, the results indicated that the capital and operating expenditures increased, however, the LCOC decreased with increasing plant capacity. This behavior was due to the increased annual tonnage of the CO2 captured with plant capacity as shown in Figure 1. The calculated CAPEX, OPEX, LCOC and the tonnage of CO2 captured for the 543 MW power plant were about 52 MM$, 22 MM$/year, 7.46 $/ton and 4 MM ton/year.

Ashkanani, Husain↗

DOE OSTI2020

An Energy Calculator for Simple Commercial Buildings

According to the EIA, simple commercial buildings account for 97% of total commercial building stock. However, most simple commercial buildings for example small- to mid-sized offices, retail, schools and warehouses do not benefit from the data-driven decision-making capabilities of whole-building energy modeling. The high cost of custom modeling limits the use of energy modeling of simple buildings for new construction or retrofit measures. Lack of tools providing helpful information on interactive savings estimates creates difficulties in meeting aggressive decarbonization and energy efficiency goals for simple building designers and utility program managers. This paper reviews a beta phase Simple Building Calculator with the ability to generate relatively accurate and interactive modeling results based on a limited but robust set of inputs. It can evaluate whole-building or single measure savings in new or existing buildings, compare measure package choices, or provide simplified performance modeling for energy codes and utility incentives. The tool combines physical (annual whole building prototype simulation) and statistical modeling techniques to predict annual energy performance. It supports a variety of building characteristics for envelope, HVAC, and lighting with parameters ranging from vintage to max tech configurations, as well as support for single-zone and simple multi-zone HVAC systems. The Simple Building Calculator was designed to provide immediate feedback for otherwise computationally intensive tasks like measure comparison, development of multiple measure package combinations, or verification that measures meet efficiency targets—all with the goal of providing a tool for quick annual energy simulation of simple commercial buildings.

Hart, Reid↗

DOE OSTI2022

High Efficiency Heat Pumps Can Pave the Path for Building Decarbonization in Cold Climates: Preprint

Heat pumps play an instrumental role in buildings decarbonization strategies. Recent advances in heat pump systems employ variable-speed compressor technology and electronically commutated fan motors. Inherently, the heating capacity and efficiency of heat pumps decrease with falling outdoor temperatures. Compared to single-speed heat pumps, variable speed systems can maintain higher heating and cooling efficiencies over a wider range of outdoor temperatures. The goal of this multi-phase project was to determine the energy savings of a high efficiency, variable-speed, air-source, split system heat pump designed for cold climate applications. The first project phase was to evaluate the performance of the heat pump in the laboratory under varying outdoor conditions in heating and cooling modes. The second phase was to translate the laboratory-measured performance into lookup tables for EnergyPlus hourly building simulation engine. Then, two sets of annual building simulations were performed using typical meteorological year weather from the Chicago-O'Hare airport for three different building types (a single-family residence, a strip mall, and a low-rise office building). The first set simulated a standard efficiency heat pump while the second set utilized the phase two performance tables to model a high efficiency heat pump. The high efficiency heat pump produced significant annual heating energy savings in all three buildings. The variable speed compressor and fan control also contributed to cooling energy savings. The simulated annual energy savings ranged from 22% to 35% over their respective baseline. The project's findings helped a Midwest electric utility, Commonwealth Edison (ComEd), design new incentives around high efficiency heat pumps.

cold climate heat pump↗

DOE OSTI2022

Technoeconomic Analysis of Changing PV System Layout and Convection Heat Transfer

This work includes analysis of potential economic improvements for PV systems for changing system parameters such as ground coverage ratio that alter the convective cooling consideration on PV modules through a newly proposed convective curve fit. Accounting for the spatial layout of the system in the convection heat transfer calculations allows for more accuracy in convective cooling load and subsequent module temperature calculations. The changing heat transfer considerations can be shown to improve system LCOE along with improved incident irradiance from increased row spacing despite the additional system costs incurred with increased module spacing. State-level analyses show that the impact of decreasing system GCR is greatest for climates with cold average annual ambient temperatures and moderate to high average annual wind speeds. Further waterfall analysis of changing system parameters reveals that the changing heat transfer dynamics have a non-negligible impact on system LCOE when compared to the changes in incident irradiance that serve as the primary driver of annual energy performance changes.

ENERGY PLANNING, POLICY, AND ECONOMY,SOLAR ENERGY↗

DOE OSTI2022

How Does Home Energy Score Affect Home Value and Mortgage Performance?

Energy-efficient homes save their occupants money through lower energy bills. These savings might be capitalized into higher home sale prices. They also improve the household’s net cash flow, which might make households better able to pay mortgage debt. The U.S. Department of Energy (DOE)’s Home Energy Score (HES) assigns a 1-10 score to homes and estimates annual energy bills based on modeled energy consumption. In this paper we investigated the relationship between HES metrics and two housing market outcomes: home sale price and mortgage performance. We found that the relationship was only statistically significant in places with a mandatory HES assessment at the time of sale. Using a sample of 26,291 home sales that occurred after HES assessments, we found that a one-point increase in HES in these locations was associated with a 0.5% increase in sale price, and an increase in $100 of estimated annual energy bills was associated with a 0.4% decrease. This magnitude of effect is consistent with estimated magnitudes of home sale premiums for other green or energy-efficient home certifications in the literature. We also found that a one-point increase in HES was associated with a 5.5% reduction in the odds of a loan going 30 days delinquent if the loan originated after the assessment occurred. Similarly, we found that a $100 decrease in estimated annual energy bills was associated with a 2.3% decrease in the odds of a loan going delinquent if it originated after the assessment occurred. Our results suggest that HES provides a valuable signal for housing market transactions in specific situations.

Pigman, Margaret↗

DOE OSTI2022

Large-Scale Simulation of Regional Demand Flexibility Implementation and Customer Economic Impact

The Distribution System Operator with Transactive (DSO+T) study conducted a large-scale simulation of over 60,000 customers in a region the size of Texas to demonstrate the effective coordination of distributed energy resources (DERs) in commercial and residential buildings. The integrated simulation included both the bulk (wholesale generation and transmission) and distribution systems. The DERs (including batteries, electric vehicles, air conditioning, and water heaters) participated in a transactive energy retail market that was integrated into an existing competitive wholesale market. The engineering and economic performance of the resulting demand flexibility was evaluated over annual simulations for both moderate and high renewable generation scenarios. A detailed parametric cost model was developed to enable detailed economic analysis of key stakeholders. In addition, fixed and dynamic customer tariffs were designed and applied to the customer population. This allowed the impact on annual customer bills to be analyzed for various building types (residential versus commercial; single- versus multi-family). This paper presents results showing the relative flexibility of batteries, electric vehicles, and building loads throughout the year and under different renewable scenarios. This feeds a detailed breakdown of the impact this flexibility has on the operating costs of the grid and the resulting net economic benefit. Finally, the study showed that practically all customer classes (including non-participating customers) save money under the proposed demand flexibility scheme. The study found overall net annual economic savings of $3.3-5.0B for a region the size of Texas equating to average customer bill savings of 10-16%.

Reeve, Hayden M.↗

DOE OSTI2020

Low Level Radon Concentration and Radon Daughter Dose Monitoring in an Arid-zone Waste Store - 20081

Radioactive waste containing predominantly soil and rubble from the clean-up of a former uranium and thorium minerals processing research facility is currently stored at the Woomera Test Range in South Australia awaiting final disposal. Prior to commencing any manipulation of the nearly 10,000 waste drums (205 L or 55 gallon each), radon concentration monitoring and radon daughter dosimetry has been undertaken to (i) gain understanding of the temporal and spatial variation of radon and its daughters within the storage facility, which could provide insights into the radiological source term and (ii) confirm that radiological risks to workers are below the guideline values. A time series of nearly 12 months of detailed observations shows low level radon concentrations with annual average values that are slightly above the average radon concentrations in Australian homes. Peak values in summer are about three times higher than the annual average based on the CRM measurements. Both radon concentrations and annual effective dose are well below the regulatory limits. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Analysis of Exposure during Transportation of Waste to the Nevada National Security Site (NNSS) - 20445

Safety is a priority for the U.S. Department of Energy (DOE) Environmental Management (EM) Nevada Program. This commitment to safety is integrated into requirements and work procedures at DOE sites across the U.S. that generate low-level radioactive waste, mixed low-level radioactive waste, and classified waste that is transported to the Nevada National Security Site (NNSS) for permanent disposal. Generators of this waste are responsible for ensuring it is packaged and transported in a safe and compliant manner. These generators and their contracted commercial carriers must comply with U.S. Department of Transportation (DOT) regulations; the Nevada National Security Site Waste Acceptance Criteria (NNSSWAC); and other applicable federal, state, and local regulations and requirements. This includes packaging and shipping the waste to meet DOT regulatory radiation dose limits to ensure public safety during transportation. NNSS waste generators have a solid safety record for complying with these stringent regulations as demonstrated by the fact that no shipments exceeding DOT dose rate limits were received at the NNSS Area 5 Radioactive Waste Management Complex (RWMC) during FY 2014 through FY 2018. A 2005 study conducted by the Desert Research Institute validated shipments to the NNSS comply with DOT radiation dose limits. In response to recent Nevada stakeholder requests for an updated study, an analysis was conducted to verify and provide evidence that the public continues to be safe from exposure to radioactive waste shipment to the NNSS. Radiation exposure from radioactive waste shipments in transit to the NNSS was evaluated. Three studies were performed: 1. Confirm compliance of waste shipments to the DOT radiation limits using dose rate surveys taken at the generator site and at the disposal site. 2. Estimate the dose to the public from waste shipments using the dosimetry results for disposal site personnel by comparing time of exposure for various individuals/scenarios. 3. Estimate the truck driver dose using the receipt dose rate surveys and time of exposure, and from dosimetry results. Study 1 confirmed compliance with the DOT dose rate limits for a sample of waste shipments (123 of 1,038) received during fiscal year (FY) 2017. Study 2 showed that the average annual radiation equivalent dose for disposal site personnel during FY 2017 was approximately 6.7% [0.415 mSv (41.5 millirem)] of the annual average dose that a person living in the U.S. receives from all sources [6.2 mSv (620 mrem)]. Maximum dose to a member of the public, a person resting/sleeping in an adjacent truck at a rest area to a waste shipment, was 0.0166 mSv (1.66 mrem), which is less than the dose received from a person taking a round trip from the east coast to the west coast of the continental U.S. on an airplane [0.07 mSv (7 mrem) per round trip]. Study 3 showed that the truck driver who made the most shipments of radioactive waste to the NNSS, who drove the most hours (estimated time of exposure 2,520 hours), during FY 2017 had a total dose of 0.15 mSv (15 mrem), which was obtained from their personal dosimeter. The annual dose recorded for disposal site personnel, the dose estimates for the public, and the truck driver dose were all a small percentage of the average radiation dose a person receives from all sources (e.g., background and medical radiation). At these levels, risk should only be described qualitatively. Radiation exposure from radioactive waste shipments to the NNSS were shown to be compliant with the DOT dose rate limits, safe, and very low (i.e., within background levels). (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗