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DOE OSTI2025

Impact of microkinetic modeling assumptions on predicted kinetics and mechanisms over undercoordinated sites

Accurate modeling of catalytic reactions on undercoordinated sites requires accounting for the structural and ensemble-specific nature of the active sites. This study examines how common microkinetic modeling (MKM) assumptions affect predicted kinetics and mechanisms on the stepped Pt(211) facet for the ethane dehydrogenation (EDH) and the ethane hydrogenolysis (EH). Six (211) MKMs were developed, differing in (i) the number of active sites represented, (ii) adsorbate site occupancy treatment, and (iii) inclusion of cross-facet interactions. These models are benchmarked against a particle-based microkinetic model (PB-MKM), which best represents step-edge behavior. MKM assumptions caused deviations in turnover frequencies exceeding ten orders of magnitude and led to contrasting mechanistic and selectivity predictions. Multi-site MKMs overestimate activity by inflating free site availability, single-site models underestimate activity, and uniform occupancy models overpredict coverage of multi-dentate intermediates, leading to reaction-specific artifacts. Overall, the Combined Site Edge Model (CSEM), a single-site MKM accounting for site occupancy and cross-facet interactions, most closely approximates PB-MKM predictions. All models predict similar kinetics when surfaces are clean or primarily occupied by monodentate species. This work provides practical guidance for selecting MKM frameworks for undercoordinated catalytic surfaces and highlights the critical role of modeling assumptions in catalytic predictions.

(211) facet↗

DOE OSTI2020

Mixed quantum–classical approach to model non-adiabatic electron–nuclear dynamics: Detailed balance and improved surface hopping method

We develop a density matrix formalism to describe coupled electron–nuclear dynamics. To this end, we introduce an effective Hamiltonian formalism that describes electronic transitions and small (quantum) nuclear fluctuations along a classical trajectory of the nuclei. Using this Hamiltonian, we derive equations of motion for the electronic occupation numbers and for the nuclear coordinates and momenta. We show that, in the limit, when the number of nuclear degrees of freedom coupled to a given electronic transition is sufficiently high (i.e., the strong decoherence limit), the equations of motion for the electronic occupation numbers become Markovian. Furthermore, the transition rates in these (rate) equations are asymmetric with respect to the lower-to-higher energy transitions and vice versa. In thermal equilibrium, such asymmetry corresponds to the detailed balance condition. We also study the equations for the electronic occupations in the non-Markovian regime and develop a surface hopping algorithm based on our formalism. To treat the decoherence effects, we introduce additional “virtual” nuclear wave packets whose interference with the “real” (physical) wave packets leads to the reduction in coupling between the electronic states (i.e., decoherence) as well as to the phase shifts that improve the accuracy of the numerical approach. Remarkably, the same phase shifts lead to the detailed balance condition in the strong decoherence limit.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2025

The CanBikeCO Full Pilot: Long-Term Results and Analysis From an E-Bike Program in Colorado, USA

Personal micromobility devices like bicycles, e-bikes, and scooters are low- or zero-energy alternatives to single-occupancy vehicles. However, a lack of data has led to a dearth of data-driven research on personally owned e-bike usage. We present longitudinal findings from the CanBikeCO program, focused on e-bike adoption and use across demographics, trip characteristics, and geographies in the state of Colorado. CanBikeCO recorded travel survey data from low-income individuals provided with personal e-bikes by the Colorado Energy Office in six communities across Colorado from July 2021 to December 2022. The data were collected using a custom instance of the National Renewable Energy Laboratory OpenPATH platform, which combines passive data collection with semantic information such as trip mode and purpose labels. To our knowledge, there are no prior travel survey data on personally owned e-bikes with this range and scope. Insights from this unique dataset include: (i) work trips were 17% more likely than average trips to be taken on an e-bike, (ii) e-bikes were most often reported to replace cars (34% of e-bike trips) and other personal micromobility devices (22%), and (iii) participants favored walking for trips less than 1 mile, e-bikes for trips of 1-3 miles, and e-bikes, cars, or shared rides for trips of 3-20 miles. The data used to generate these results have been made available in the Transportation Secure Data Center. We find e-bike use is appealing across age groups and may be related to characteristics of land use, urban form, occupation, income, and car ownership. We conclude for this population that the energy demand added by e-bike use (induced demand and replacing non-motorized modes) is outweighed by the reduction in energy demand from replacement of single-occupancy vehicle trips with e-bike trips. Our findings suggest considerable potential for energy savings from personal e-bike ownership.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Performance assessment of a real water source heat pump within a hardware-in-the-loop (HIL) testing environment

Over the last decade, the global fight against climate change through electrification has led to an increase in research on building heating, ventilation, and air conditioning (HVAC) systems that utilize intelligent control algorithms to provide demand-side grid service while also maintaining the thermal comfort of building occupants. As the pivotal point between building electricity consumption and indoor thermal comfort, high-efficiency electrical vapor-compression heat pumps are at the center of these emerging studies, and various grid-interactive and occupant-comfort control algorithms have been developed for them. The impact of these algorithms on heat pump operation and performance when subjected to different weather conditions, building loads, and grid requests calls for investigation and verification via experimental testing with actual heat pumps integrated with real-time building and grid responses. This study introduces a Water-Source Heat Pump (WSHP) Hardware-in-The-Loop (HIL) Test Facility that is the first of its kind. This testbed utilizes a 2-ton variable speed water-to-air heat pump that is capable of interacting with a virtual environment currently comprised of an EnergyPlus (E+) building simulation, an agent-based occupant behavioral model, and a single U-tube ground-loop heat exchanger (GLHE) model. Detailed descriptions of the testbed’s physical design and operation, virtual environment, as well as their mutual communication is provided. An uncertainty analysis is also performed under manufacturer specified heating and cooling design conditions. This analysis shows that the total load across the WSHP’s demand side heat exchanger, i.e., the sum of its latent and sensible components, can be measured with a relative uncertainty of ± 10.4% and ± 3.6% in cooling and heating mode respectively. The WSHP’s coefficient of performance (COP) can be measured with relative uncertainties of ± 10.4% in cooling mode, and ± 3.7% in heating mode. A preliminary 24-h experimental demonstration is then performed utilizing the DOE prototype small commercial office building model in E+. The simulation takes place in Atlanta, GA on the date of 08/26/15 from 12:00 AM to 11:59 PM using TMY3 weather data. Here, the results from this demonstration show that over the course of this experiment the simulated outputs of zone dry-bulb temperature, zone humidity ratio, and WSHP inlet water temperature can be tracked by testbed emulators up to a root mean squared error (RMSE) of ± 0.27 °C, ± 0.376 g/kg, and ± 0.85 °C respectively. The WSHP’s dynamic behavioral characteristics and performance are also captured, and correspond well with the authors’ previous understanding of heat pump efficiency as a function of evaporator and condenser fluid inlet conditions respectively.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Performance of CMS muon reconstruction from proton-proton to heavy ion collisions

The performance of muon tracking, identification, triggering, momentum resolution, and momentum scale has been studied with the CMS detector at the LHC using data collected at √(s$_{NN}$) = 5.02 TeV in proton-proton (pp) and lead-lead(PbPb) collisions in 2017 and 2018, respectively, and at √(s$_{NN}$) = 8.16 TeV in proton-lead (pPb) collisions in 2016. Muon efficiencies, momentum resolutions, and momentum scales are compared by focusing on how the muon reconstruction performance varies from relatively small occupancy pp collisions to the larger occupancies of pPb collisions and, finally, to the highest track multiplicity PbPb collisions. We find the efficiencies of muon tracking, identification, and triggering to be above 90% throughout most of the track multiplicity range. The momentum resolution and scale are unaffected by the detector occupancy. The excellent muon reconstruction of the CMS detector enables precision studies across all available collision systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

The galaxy–halo connection of emission-line galaxies in IllustrisTNG

ABSTRACT We employ the hydrodynamical simulation IllustrisTNG-300-1 to explore the halo occupation distribution (HOD) and environmental dependence of luminous star-forming emission-line galaxies (ELGs) at z ∼ 1. Such galaxies are key targets for current and upcoming cosmological surveys. We select model galaxies through cuts in colour–colour space allowing for a direct comparison with the Extended Baryon Oscillation Spectroscopic Survey and the Dark Energy Spectroscopic Instrument (DESI) surveys and then compare them with galaxies selected based on specific star formation rate (sSFR) and stellar mass. We demonstrate that the ELG populations are twice more likely to reside in lower density regions (sheets) compared with the mass-selected populations and twice less likely to occupy the densest regions of the cosmic web (knots). We also show that the colour-selected and sSFR-selected ELGs exhibit very similar occupation and clustering statistics, finding that the agreement is best for lower redshifts. In contrast with the mass-selected sample, the occupation of haloes by a central ELG peaks at ∼20 per cent. We furthermore explore the dependence of the HOD and the autocorrelation on environment, noticing that at fixed halo mass, galaxies in high-density regions cluster about 10 times more strongly than low-density ones. This result suggests that we should model carefully the galaxy–halo relation and implement assembly bias effects into our models (estimated at ∼4 per cent of the clustering of the DESI colour-selected sample at z = 0.8). Finally, we apply a simple mock recipe to recover the clustering on large scales (r ≳ 1 Mpc h−1) to within 1 per cent by augmenting the HOD model with an environment dependence, demonstrating the power of adopting flexible population models.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

A new constraint on galaxy–halo connections of [O ii ] emitters via HOD modelling with angular clustering and luminosity functions from the Subaru HSC survey

ABSTRACT Establishing a robust connection model between emission-line galaxies (ELGs) and their host dark haloes is of paramount importance in anticipation of upcoming redshift surveys. We propose a novel halo occupation distribution (HOD) framework that incorporates galaxy luminosity, a key observable reflecting ELG star-formation activity, into the galaxy occupation model. This innovation enables prediction of galaxy luminosity functions (LFs) and facilitates joint analyses using both angular correlation functions (ACFs) and LFs. Using physical information from luminosity, our model provides more robust constraints on the ELG–halo connection compared to methods relying solely on ACF and number density constraints. Our model was applied to $\rm [O\, {\small II}]$-emitting galaxies observed at two redshift slices at $z=1.193$ and 1.471 from the Subaru Hyper Suprime-Cam PDR2. Our model effectively reproduces observed ACFs and LFs observed in both redshift slices. Compared to the established Geach et al. HOD model, our approach offers a more nuanced depiction of ELG occupation across halo mass ranges, suggesting a more realistic representation of ELG environments. Our findings suggest that ELGs at $z\sim 1.4$ may evolve into Milky-Way-like galaxies, as their inferred halo masses evolve accordingly based on the extended Press–Schechter formalism, highlighting their role as potential building blocks in galaxy formation scenarios. By incorporating the LF as a constraint linking galaxy luminosity to halo properties, our HOD model provides a more precise understanding of ELG-host halo relationships. Furthermore, this approach facilitates the generation of high-quality ELG mock catalogues for future surveys. As the LF is a fundamental observable, our framework is potentially applicable to diverse galaxy populations, offering a versatile tool for analysing data from next-generation galaxy surveys.

Ishikawa, Shogo (ORCID:0000000221184211)↗

DOE OSTI2026

Scattering Processes from Quantum Simulation Algorithms for Scalar Field Theories

We provide practical simulation methods for scalar field theories on a quantum computer that yield improved asymptotics as well as concrete gate estimates for the simulation and physical qubit estimates using the surface code. We achieve these improvements through two optimizations. First, we consider a finite volume approach for estimating the elements of the S-matrix. This approach is appropriate in general for 1+1D and for certain low-energy elastic collisions in higher dimensions. Second, we implement our approach using a series of different fault-tolerant simulation algorithms for Hamiltonians formulated both in the field occupation basis and field amplitude basis. Our algorithms are based on either second-order Trotterization or qubitization. The cost of Trotterization in occupation basis scales as O ( λ N 7 | Ω | 3 / ( M 5 / 2 ϵ 3 / 2 ) ) where λ is the coupling strength, N is the occupation cutoff, | Ω | is the volume of the spatial lattice, M is the mass of the particles and ϵ is the uncertainty in the energy calculation used for the S -matrix determination. Qubitization in the field basis scales as O ( | Ω | 2 ( k 2 Λ + k M 2 ) / ϵ ) , where k is the cutoff in the field and Λ is a scaled coupling constant. We find in both cases that the bounds suggest physically meaningful simulations can be performed using on the order of 4 × 10 6 physical qubits and 10 12 T -gates which corresponds to roughly one day on a superconducting quantum computer with surface code and a cycle time of 100 ns. This places the simulation of scalar field theory within striking distance of the gate counts for the best available chemistry simulation results.

Hardy, Andrew [Toronto U.] (ORCID:0000000235817382↗

DOE OSTI2022

Orbital magnetization of Floquet topological systems

A general expression for the orbital magnetization of a Floquet system is derived. The expression holds for a clean system, and is valid for any driving protocol, and arbitrary occupation of the bands. The orbital magnetization is shown to be large not only for Chern insulators, but also for anomalous phases where the Chern number does not fully account for the topology. In addition, the orbital magnetization is shown to take significant values both for a thermal equilibrium occupation of the Floquet bands, and for occupations determined by a quantum quench from an initial state with zero orbital magnetization. For the latter case, the orbital magnetization is shown to be highly sensitive to van Hove singularities of the Floquet bands.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

Capturing the ground state of uranium dioxide from first principles: Crystal distortion, magnetic structure, and phonons

Uranium dioxide (UO 2 ) remains a formidable challenge for first-principles approaches due to the complex interplay among spin-orbit coupling, Mott physics, magnetic ordering, and crystal distortions. Here we use DFT+U to explore UO 2 at zero temperature, incorporating all the aforementioned phenomena. The technical challenge is to navigate the many metastable electronic states produced by DFT+U, which is accomplished using f-orbital occupation matrix control to search for the ground state. We restrict our search to the high-symmetry ferromagnetic phase, including spin-orbit coupling, which produces a previously unreported occupation matrix. This newfound occupation matrix is then used as an initialization to explore the broken symmetry phases. We find the oxygen cage distortion of the 3k antiferromagnetic state to be in excellent agreement with experiments, and both the spin-orbit coupling and the Hubbard U are critical ingredients. Further, we demonstrate that only select phonon modes have a strong dependence on the Hubbard U, whereas magnetic ordering has only a small influence overall. We perform measurements of the phonon dispersion curves using inelastic neutron scattering, and our calculations show good agreement when using reasonable values of U. The quantitative success of DFT+U warrants exploration of thermal transport and other observables within this level of theory.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Single classical field description of interacting scalar fields

In this report we test the degree to which interacting Bosonic systems can be approximated by a classical field as total occupation number is increased. This is done with our publicly available code repository, QIBS, a new massively parallel solver for these systems. We use a number of toy models well studied in the literature and track when the classical field description admits quantum corrections, called the quantum breaktime. This allows us to test claims in the literature regarding the rate of convergence of these systems to the classical evolution. We test a number of initial conditions, including coherent states, number eigenstates, and field number states. We find that of these initial conditions, only number eigenstates do not converge to the classical evolution as occupation number is increased. We find that systems most similar to scalar field dark matter exhibit a logarithmic enhancement in the quantum breaktime with total occupation number. Systems with contact interactions or with field number state initial conditions, and linear dispersions, exhibit a power law enhancement. Finally, we find that the breaktime scaling depends on both model interactions and initial conditions.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

A Comfort Model Simplification for Tight Integration with Grid Service Optimizations

Localized generation, storage, and intelligent power electronics are increasingly being integrated into building. The excess storage, thermal, and generation capacity can be used to develop new markets for ancillary services such as peak reduction, voltage and frequency support, or load flattening. Widespread participation in these markets will make the power grid more resilient. However, widespread participation in these markets will require a simple and intuitive control over the excess capacity by the building occupants. Most importantly for adopting these technologies, participation in these markets should not require sacrificing occupant comfort. Many of the proposed control and optimization technologies for supplying the ancillary services do not explicitly incorporate occupant comfort into their models and when they do, generally utilize a rigid constraint on the indoor air temperature set a priori. This reduces flexibility in using excess thermal capacity. It also cannot take into account uncertainties in local factors that affect thermal comfort such as clothing insulation or relative humidity. In this paper we present and justify some assumptions that simplify the standard predictors of thermal comfort. We also develop a regression model of the thermal comfort that is linear with respect to the indoor air temperature. Next we develop the concept of thermal comfort variation that eliminates the dependence of the thermal comfort on uncertain thermal comfort factors. Then, we present a quadratic program utilizing the thermal comfort variation in both the objective function and as a constraint. Finally, we show the results of a time-of-use cost optimization that utilizes the simplified thermal comfort model.

Melin, Alexander↗

DOE OSTI2025

Ecovoltaic solar energy development can promote grassland bird communities

Ecologically informed photovoltaic (PV) developments that co-prioritize PV electricity generation with ecosystem function (‘ecovoltaics’) have emerged as a promising land sharing strategy to minimize ecological conflicts associated with PV solar energy development. While habitat-focused ecovoltaic designs can conceptually benefit biodiversity by offsetting or enhancing impacts of PV development, foundational field research is needed to examine how wildlife respond to these novel ecosystems. We conducted passive acoustic monitoring (PAM) in 2023 and 2024 at 13 solar facilities and paired control sites to investigate avian community responses to ecovoltaic facilities in the Midwestern United States. Compared to control sites (row crop agricultural fields), we found that ecovoltaic sites supported more grassland bird species throughout a 17-week monitoring period between May and September. Grassland bird communities on ecovoltaic sites were also more stable than on agricultural controls, as measured by the Jaccard dissimilarity index. We also used PAM-based weekly species occurrences in an occupancy-modelling framework to investigate the influence of PV development and other landscape variables on grassland bird occupancy. 10 out of 13 modelled grassland bird species had greater predicted occupancy probabilities (ψ) on PV sites than control sites. Synthesis and applications. Our findings suggest that properly sited and developed ecovoltaic solar facilities in human altered landscapes can improve habitat for birds and other wildlife, but further research is needed to understand which species may benefit most from these novel ecosystems.

14 SOLAR ENERGY↗

DOE OSTI2021

Control of airborne infectious disease in buildings: Evidence and research priorities

The evolution of SARS-CoV-2 virus has resulted in variants likely to be more readily transmitted through respiratory aerosols, underscoring the increased potential for indoor environmental controls to mitigate risk. Use of tight-fitting face masks to trap infectious aerosol in exhaled breath and reduce inhalation exposure to contaminated air is of critical importance for disease control. Administrative controls including the regulation of occupancy and interpersonal spacing are also important, while presenting social and economic challenges. Indoor engineering controls including ventilation, exhaust, air flow control, filtration, and disinfection by germicidal ultraviolet irradiation can reduce reliance on stringent occupancy restrictions. However, the effects of controls-individually and in combination-on reducing infectious aerosol transfer indoors remain to be clearly characterized to the extent needed to support widespread implementation by building operators. We review aerobiologic and epidemiologic evidence of indoor environmental controls against transmission and present a quantitative aerosol transfer scenario illustrating relative differences in exposure at close-interactive, room, and building scales. We identify an overarching need for investment to implement building controls and evaluate their effectiveness on infection in well-characterized and real-world settings, supported by specific, methodological advances. Finally, improved understanding of engineering control effectiveness guides implementation at scale while considering occupant comfort, operational challenges, and energy costs.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

A Stochastic Multi-Criteria Decision-Making Algorithm for Dynamic Load Prioritization in Grid-Interactive Efficient Buildings

Increasing deployment of advanced sensing, controls, and communication infrastructure enables buildings to provide services to the power grid, leading to the concept of grid-interactive efficient buildings. Since occupant activities and preferences primarily drive the availability and operational flexibility of building devices, there is a critical need to develop occupant-centric approaches that prioritize devices for providing grid services, while maintaining the desired end-use quality of service. In this paper, we present a decision-making framework that facilitates a building owner/operator to effectively prioritize loads for curtailment service under uncertainties, while minimizing any adverse impact on the occupants. The proposed framework uses a stochastic (Markov) model to represent the probabilistic behavior of device usage from power consumption data, and a load prioritization algorithm that dynamically ranks building loads using a stochastic multi-criteria decision-making algorithm. The proposed load prioritization framework is illustrated via numerical simulations in a residential building use-case, including plug-loads, air-conditioners, and plug-in electric vehicle chargers, in the context of load curtailment as a grid service. Suitable metrics are proposed to evaluate the closed-loop performance of the proposed prioritization algorithm under various scenarios and design choices. Scalability of the proposed algorithm is established via computational analysis, while time-series plots are used for intuitive explanation of the ranking choices.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Poster Abstract: Leveraging Large Language Models to Reveal Interpretable Cooling Behaviors from Smart Thermostat Data

Frequent heatwaves and hot summers increasingly challenge occupant comfort, health, and energy grid stability. Addressing these challenges requires a detailed understanding of household cooling behaviors, such as thermostat adjustments and adaptive responses to extreme conditions. Traditional analyses often rely on aggregated numerical metrics that overlook subtle but important household-specific variations. In this study, we introduce a generalizable methodology that integrates large language models (LLMs) with vision capabilities to enable scalable and detailed analysis of residential thermostat data. Using Ecobee's Donate Your Data (DYD) dataset—which provides five-minute records of indoor temperatures, thermostat setpoints, and HVAC runtimes—we focus on two U.S. cities with contrasting summer climates : Austin (TX) and Phoenix (AZ). Because raw time-series data are not well suited for direct LLM analysis, we transform them into visual representations, such as daily indoor temperature trajectories and weekly runtime histograms, to better capture behavioral variations. Leveraging LLMs' visual interpretation, we extract descriptive behavioral features, including temperature preferences, time-of-day cooling orientation, anticipatory versus reactive heatwave responses, and behavioral consistency. These semantic features support unsupervised clustering to identify distinct occupant archetypes at scale, revealing differences—such as morning-centric anticipatory coolers versus households that shift toward warmer setpoints during heatwaves—that can inform demand response, resilience planning, and health-aware interventions. By converting raw numerical data into interpretable behavioral patterns, this methodology enables scalable and practical analysis of occupant behavior, supporting actionable insights for comfort, resilience, and energy management.

Nihar, Kopal↗

DOE OSTI2025

Thermal Resilience of Buildings and Communities: A Multistakeholder Review of Metrics and Approaches

Increasing temperature-related hazards require a collective effort to assess and enhance the thermal resilience of buildings and communities to protect occupants’ safety and minimize property or infrastructure damage. However, limited coordination across stakeholders and lack of standardized procedures for resilience assessment undermine the effectiveness of extreme temperature mitigation and adaptation strategies across the building life cycle. This review examines the current literature on resilience metrics to address thermal stress and risk due to extreme indoor environments. Stakeholders of thermal resilience include architects and engineers, occupants, property owners, real estate developers, urban planners, and policymakers. Additionally, motivations for measuring thermal resilience are emphasized, such as safeguarding occupant health and survivability, protecting property, and ensuring business continuity during extreme weather events. This review provides actionable insights and identifies future research needs for enhancing resilience through tailored metrics for stakeholders during the planning, design, construction, operation, and retrofitting phases of buildings and communities.

building life cycle↗

DOE OSTI2021

The legacy of weapons grade plutonium production: Health status of Hanford complex workers who manage the waste

The extent and etiology of health effects in workers who maintain underground storage tanks at the Hanford Nuclear Reservation (Hanford) have been subjects of controversy and concern for several decades. Hanford is a decommissioned nuclear production complex managed by the US Department of Energy in southeast Washington State. This integration-of-evidence review evaluates the relationship between exposure to vapors from mixed chemical and radioactive waste stored in underground storage tanks at Hanford and worker health. Hanford workers’ health information was gathered from technical reports, media reports, and published literature, including the systematic search of seven databases. This review describes the health status and health concerns of Hanford tank farm workers based on the integration of the available health effects data from disparate sources. In interviews with external groups, Hanford workers reported both irritant-type symptoms and diseases that they believe are attributable to tank farm vapors. However, the results of this integration-of-evidence review indicated that no pervasive pattern of occupational disease was identified that can be associated with exposure to tank farm vapors. Inhalation exposure to asbestos and beryllium is associated with lung disease from various types of nuclear industry work but not from work on tank farms. This review concluded that while irritant-type symptoms and isolated cases of occupational disease are plausible under certain conditions, the currently available data do not support a pervasive pattern of occupational disease associated with vapor exposure.

Cherry, Debra↗