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The Savannah River National Laboratory, Atmospheric Technologies Group, conducts a best-in class Applied Meteorology Program to ensure the Department of Energy’s Savannah River Site is operated safely and complies with stringent environmental regulations.
The Savannah River National Laboratory (SRNL) Atmospheric Technologies Group performed atmospheric dispersion modeling and analysis of mercury emissions from the H-Tank Farm - Tank 42 ventilation system exhaust to evaluate potential worker exposures to mercury vapor. This analysis was used to establish a minimum stack height at which ambient mercury concentration would not exceed any worker exposure limit. The American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) was used as the dispersion modeling tool for this analysis. Results indicate that the default 10-foot stack results in ground level concentrations that significantly exceed exposure standards for the mercury discharge scenarios evaluated. For a discharge of 25 mg/m 3 , a 50-foot stack was necessary to raise the exhaust plume centerline from Tank 42H to a height that prevents mercury exposure problems for elevated receptors on buildings near the tank. If the discharge concentration is decreased to 10 mg/m 3 , the minimum stack height required to comply with exposure limits is of 40 feet.
The Savannah River National Laboratory (SRNL) Atmospheric Technologies Group performed atmospheric dispersion modeling and analysis of mercury emissions from the H-Tank Farm - Tank 37 ventilation system exhaust to evaluate whether the Short-Term Exposure Limit (STEL) for mercury is exceeded during salt dissolution activities. This analysis was also used to establish a minimum stack height at which ambient mercury concentration would not exceed this regulatory limit. The American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) was used as the dispersion modeling tool for this analysis. Results indicate that the default 10-foot stack results in ground level concentrations that significantly exceed the standards for the mercury discharge scenarios evaluated. A 35-foot stack was necessary to raise the exhaust plume centerline from Tank 37H to a height that prevents mercury exposure problems for the three discharge concentrations modeled.
The SRNL Atmospheric Technologies Group performed an analysis for mercury emissions from H-Tank Farm - Tank 40 ventilation system exhaust in order to assess whether the Short Term Exposure Limit (STEL), or Threshold Limit Value (TLV) levels for mercury will be exceeded during bulk sludge slurry mixing and sludge removal operations. The American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) was used as the main dispersion modelling tool for this analysis. The results indicated that a 45-foot stack is sufficient to raise the plume centerline from the Tank 40 release to prevent mercury exposure problems for any of the stack discharge scenarios provided. However, a 42-foot stack at Tank 40 is sufficient to prevent mercury exposure concerns in all emission scenarios except the 50 mg/m 3 release. At a 42-foot stack height, values exceeding the exposure standards are only measured on receptors located above 34 feet.
The Atmospheric Technology Group at SRNL developed a new method to detect signals from Weapons of Mass Destruction (WMD) activities in a time series of chemical measurements at a downwind location. This method was tested with radioxenon measured in Russia and Japan after the 2013 underground test in North Korea. This LDRD calculated the uncertainty in the method with the measured data and also for a case with the signal reduced to 1/10 its measured value. The research showed that the uncertainty in the calculated probability of origin from the NK test site was small enough to confirm the test. The method was also wellbehaved for small signal strengths.
The SRNL Atmospheric Technologies Group performed an analysis of mercury emissions from H-Tank Farm – Tank 41H ventilation system exhaust to assess worst case 15-minute and 8-hour average ground level concentrations and evaluate whether the Short-Term Exposure Limit (STEL), or Threshold Limit Value (TLV) levels for mercury will be exceeded during mixing operations. This analysis was also used to establish a minimum stack height at which ambient mercury concentration would not exceed the safety limits. The American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) was used as the dispersion modelling tool for this analysis. Results indicate that a stack height of 30-ft (for the 25 mg/m 3 emissions case) or 50-ft (for the 50 mg/m 3 emissions case) stacks results in ground level concentrations that do not exceed the STEL or TLV standards.
The SRNL Atmospheric Technologies Group performed an analysis of mercury emissions from the H-Tank Farm 242-25H Evaporator backup ventilation system exhaust to assess worst case15-minute and 8-hour average concentrations and evaluate whether the ACIGH Short-Term Exposure Limit (STEL), or Threshold Limit Value (TLV) levels for mercury are exceeded following a seismic event. This analysis was also used to establish a minimum stack height at which ambient mercury concentration would not exceed the regulatory limits. The American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) was used as the dispersion modelling tool for this analysis. Results indicate that a stack height of 20 ft result in ground level concentrations that exceed the STEL or TLV standards at ground level only in the areas immediately around the stack, and generally on the slope of the hill beneath the 242-25H and 242-9H buildings.
The SRNL Atmospheric Technologies Group performed an analysis of mercury emissions from the H-Tank Farm Tank 31-H to assess worst case 15-minute, 1-hour and 8-hour average concentrations and evaluate whether the ACIGH Short-Term Exposure Limit (STEL), PAC (Protection Action Criteria), or Threshold Limit Value (TLV) levels for mercury are exceeded. This analysis was also used to establish a minimum stack height at which ambient mercury concentration would not exceed the regulatory limits. The American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) was used as the dispersion modeling tool for this analysis. The PAC standard is not exceeded for any of the stack heights, or release scenario. A 92 ft stack for the 25 mg/m 3 modeling scenario and 95 ft for the 50 mg/m 3 are necessary to prevent all exceedances at all receptors. If the highest receptor on the Evaporator West Stack Platform is excluded from the domain, then the maximum heights are 35 ft and 52 ft for the 25 mg/m 3 and the 50 mg/m 3 modeling scenarios, respectively.
The SRNL Atmospheric Technologies Group performed an analysis of mercury emissions from the H-Tank Farm Tank 35-H to assess worst case 15-minute, 1-hour and 8-hour average concentrations and evaluate whether the ACIGH Short-Term Exposure Limit (STEL), PAC (Protection Action Criteria), or Threshold Limit Value (TLV) levels for mercury are exceeded. This analysis was also used to establish a minimum stack height at which ambient mercury concentration would not exceed the regulatory limits. The American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) was used as the dispersion modeling tool for this analysis. The PAC standard is not exceeded for any of the stack heights, or release scenario. A 100 ft stack for the 50 mg/m 3 modeling scenario and 110 ft for the 100 mg/m3 are necessary to prevent all exceedances at all receptors. If the highest receptor on the Evaporator West Stack Platform is excluded from the domain, then the maximum heights are 65 ft and 105 ft for the 50 mg/m 3 and the 100 mg/m 3 modeling scenarios, respectively.
The SRNL Atmospheric Technologies Group performed an analysis to determine the minimum stack height necessary to avoid exceedance of the ACGIH (American Conference of Governmental Industrial Hygienists) 15-minute Short-Term Exposure Limit (STEL) and 8-hour Time Weighted Average (TWA) ambient standards for worst case hazardous chemical emissions from the Z-Area Mega SDUs. The American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) was used as the dispersion modeling tool for this analysis. Receptors were placed to represent the breathing level concentrations that workers might have, placed 6-ft above the working surface (ground or SDU tank surface). Based on the analysis conducted, the minimum SDU exhaust release height to avoid exceeding STEL and TWA is 6 feet above the SDU roof level for flow rates between 300 and 1200 cfm. The configuration of Mega SDUs, while large structures, do not produce an aerodynamic wake that impacts the stack releases and causes exceedances to the worker exposure limits.
Weather forecasting is a tool in which the Savannah River Site relies on to complete daily tasks. The importance and integrity of forecasting systems and models is of the utmost importance to safety at SRS. By comparing and contrasting model bias, the meteorologists and employees of the Atmospheric Technologies Group will be equipped with bias data to create more accurate forecasts. Thus, furthering the safety of individuals at SRS.
Air quality dispersion modeling is performed for the Savannah River Site (SRS) to demonstrate compliance with applicable regulations. The AMS/EPA Regulatory Model (AERMOD) modeling system is an EPA recommended model for air quality applications with a data preprocessor (AERMET) to incorporate meteorological data collected on site. AERMET parameterizes or calculates meteorological variables that are not directly measured onsite. One of the parameters estimated by AERMET is the atmospheric mixing height. While the mixing height is not currently a measurement input into AERMET, SRS has the capability to measure the local mixing height. The Savannah River National Laboratory (SRNL) operates a Vaisala CL31 Lidar Ceilometer which estimates mixing height from aerosol backscatter. This study compares the parameterized mixing height from AERMET to the ceilometer estimated mixing height for the current regulatory period at SRS incorporating data from 2015-2019. Results from this study showed the average daily minimum values (morning) from AERMET were an order of magnitude lower than the commonly used Holzworth (1972) method and the ceilometer estimated mixing heights. Additionally, on average, the ceilometer exhibited a daily maximum mixing height value that occurred 1-3 hours later than the AERMET estimated maximum. This difference is likely due to the nighttime atmospheric mixing height assumptions and calculations used by AERMET. The AERMET algorithm cuts off mixing height growth at sunset while the ceilometer data show ongoing evening convection typical of the southeastern United States. These results suggest that the AERMET parametrization scheme assumptions may not be representative of a forested landscape and evening convection which could account for more mixing overnight. The results obtained in this study are significant for air dispersion modeling applications for regulatory purposes and worker safety. Mixing height can impact model estimated pollutant concentrations. A greater mixing height will provide more volume for pollutant dispersion. This report documents efforts to quantify the dependence of mixing height inputs toward a conservative estimated pollutant concentration.
Climate change is mostly the result of elevated carbon dioxide emissions. Over the past two decades, research groups have been searching for new technologies that capture carbon dioxide from the atmosphere as an effective way of reversing climate change. Dr Radu Custelcean and his colleagues at the Oak Ridge National Laboratory in the US specialise in this endeavour. The team is developing novel materials and methods that filter carbon dioxide out of the air in an energy-efficient manner.
Increased output of greenhouse gases, particularly carbon dioxide (CO₂), into the atmosphere from anthropogenic sources is of great concern. A potential technology to reduce CO₂ emissions is geologic carbon sequestration. This technology is currently being evaluated in the United States and throughout the world. The geology of the Illinois Basin exhibits outstanding potential as a carbon sequestration target, as demonstrated by the ongoing Illinois Basin – Decatur Project that is using the Mt. Simon Sandstone reservoir and Eau Claire Shale seal system to store and contain 1 million tonnes of CO₂. The Knox Group-Maquoketa Shale reservoir and seal system, located stratigraphically above the Mt. Simon Sandstone-Eau Claire Shale reservoir and seal system, has little economic value as a resource for fossil fuels or as a potable water source, making it ideal as a potential carbon sequestration target. In order for a reservoir-seal system to be effective, it must be able to contain the injected CO₂ without the potential for the release of harmful contaminants liberated by the reaction between CO₂-formation fluids and reservoir and seal rocks. This study examines portions of the Knox Group (Potosi Dolomite, Gunter Sandstone, New Richmond Sandstone) and St. Peter Sandstone, and Maquoketa Shale from various locations around the Illinois Basin. A total of 14 rock and fluid samples were exposed to simulated sequestration conditions (9101–9860 kPa [1320–1430 psi] and 32°–42°C [90°– 108°F]) for varying amounts of time (6 hours to 4 months). Knox Group reservoir rocks exhibited dissolution of dolomite in the presence of CO₂ as indicated by petrographic examination, X-ray diffraction analysis, and fluid chemistry analysis. These reactions equilibrated rapidly, and geochemical modeling confirmed that these reactions reached equilibrium within the time frames of the experiments. Pre-reaction sample mineralogy and postreaction fluid geochemistry from this study suggests only limited potential for the release of United States Environmental Protection Agency regulated inorganic contaminants into potable water sources. Short-term core flood experiments further verify that the carbonate reactions occurring in Knox Group reservoir samples reach equilibrium rapidly. The core flood experiments also lend insight to pressure changes that may occur during CO₂ injection. The Maquoketa Shale experiments reveal that this rock is initially chemically reactive when in contact with CO₂ and brine. However, due to the conservative nature of silicate and clay reaction kinetics and the rapid equilibration of carbonate reactions that occur in the shale, these reactions would not present a significant risk to the competency of the shale as an effective seal rock.
One of the main culprits of global warming is the increased amount of carbon dioxide, or CO2, in the atmosphere. NASA's global climate reports a 13% increase in atmospheric CO2 from 2000 to present. Adsorptive CO2 capture by nitrogen groups of amine-containing solvents is one of the most mature technologies deployed in petrochemical and natural gas processing plants to purify industrial gases. However, key challenges in widespread application include solvent induced reactor corrosion, amine degradation, and high regeneration energy for repeated cycling. An alternative approach is to immobilize amines on solid supports. Key performance metrics of solid amine-based CO2 adsorbents include the CO2 adsorption capacity and stability to degradation over hundreds of thousands of regeneration cycles. Our research aims to develop descriptors for CO2 capture capacity and stability against oxygen-induced degradation for amines bound to porous silica supports using experimental and computational techniques. We experimentally measure the change in CO2-uptake using solid amine adsorbents with varying chemical compositions and exposure to varying gas streams and use high-performance computers to simulate the nature and strength of CO2-adsorption and oxidative degradation reaction mechanisms. Insights from our work can facilitate the development of stable solid amine adsorbents for large-scale CO2 capture processes.
Accurately modeling wind farm performance in complex atmospheric flows remains a challenge. This paper presents the modeling results of the American WAKE experimeNt (AWAKEN) wind farm benchmark, a collaborative effort involving 16 research groups from academia and industry within the International Energy Agency Wind Technology Collaboration Programme Task 57. The study evaluates a diverse suite of simulation tools, ranging from fast-running engineering wake models to high-fidelity large-eddy simulations, against a diurnal case study observed during the AWAKEN campaign. The benchmark utilized a three-phase structure to progressively assess model performance as observational data availability increased. Initial blind predictions showed that higher-fidelity models did not uniformly outperform simpler simulation tools. A distinct spatial bias was observed where models struggled to resolve the interplay between a low-level jet, wakes, and terrain-induced flow acceleration. In subsequent phases, leveraging additional measurements for model improvement led to a reduction in mean absolute error across the model ensemble; however, this effect was most pronounced in engineering wake models, where targeted calibration reduced error by up to 40~\%. Overall, the study demonstrates that inflow characterization remains a primary prerequisite for accuracy, particularly for models relying on coarse forcing datasets. While the limited ability to resolve local terrain-flow interactions under single-day conditions represent a recognized constraint, the overall findings on wake modeling and real-world validation still provide valuable guidance for model application and for mitigating this limitation.
An efficient, column chromatography-free route for scale-up preparation of protected carbonyl containing biomass molecules is established. Then the protection group effect is investigated in multiple systems especially under a reducing atmosphere.
Context: This webinar was hosted by the MultiSector Dynamics Community of Practice (MSD CoP; https://multisectordynamics.org). Talk #1: Behavioral Generative Agents for Energy Operations Presenter: Dr. Cong Chen (Thayer School of Engineering, Dartmouth College) Abstract: Accurately modeling consumer behavior in energy operations remains challenging due to inherent uncertainties, behavioral complexities, and limited empirical data. This talk introduces a novel approach leveraging generative agents--artificial agents powered by large language models--to realistically simulate customer decision-making in dynamic energy operations. Talk #2: Simulating multiple human perspectives in socio-ecological systems using large language models Presenter: Dr. Yongchao Zeng (Institute of Meteorology and Climate Research, Atmospheric Environmental Research (IMK-IFU) of the Karlsruhe Institute of Technology in Germany) Abstract: Understanding socio-ecological systems requires insights from diverse stakeholder perspectives. This talk describes a novel simulation system called HoPeS (Human-oriented Perspective Shifting). HoPeS enables model users to not only explore simulated socio-ecological systems (SESs) from a third-person observer's perspective but also take any of the simulated stakeholder roles, like playing an RPG game. By shifting multiple perspectives, model users can reflect and integrate the situated knowledge learned through the participatory simulation, approximating a more holistic and less biased understanding of SESs. Moderators: Jim Yoon (MSD CoP Human Systems Modeling Working Group Co-Chair); Stefano Galelli (MSD CoP Using AI to Enhance MSD Research Working Group Co-Chair); Patrick M. Reed (MSD CoP Facilitation Team) This webinar was held on: November 13th, 2025 from 12-1 PM EST.