Validation test for CAP88 predictions of tritium dispersion at Los Alamos National Laboratory.

Gaussian plume models, such as CAP88, are used regularly for estimating downwind concentrations from stack emissions. At many facilities, the U.S. Environmental Protection Agency (U.S. EPA) requires that CAP88 be used to demonstrate compliance with air quality regulations for public protection from emissions of radionuclides. Gaussian plume models have the advantage of being relatively simple and their use pragmatic; however, these models are based on simplifying assumptions and generally they are not capable of incorporating dynamic meteorological conditions or complex topography. These limitations encourage validation tests to understand the capabilities and limitations of the model for the specific application. Los Alamos National Laboratory (LANL) has complex topography but is required to use CAP88 for compliance with the Clean Air Act Subpart H. The purpose of this study was to test the accuracy of the CAP88 predictions against ambient air measurements using released tritium as a tracer. Stack emissions of tritium from two LANL stacks were measured and the dispersion modeled with CAP88 using local meteorology. Ambient air measurements of tritium were made at various distances and directions from the stacks. Model predictions and ambient air measurements were compared over the course of a full year's data. Comparative results were consistent with other studies and showed the CAP88 predictions of downwind tritium concentrations were on average about three times higher than those measured, and the accuracy of the model predictions were generally more consistent for annual averages than for bi-weekly data.

Addressing nuclides not in the CAP88-PC Version-3 library.

Versions of the computer program, CAP88, are widely used to calculate the radiological doses from radionuclides emitted into the air. CAP88-PC Version-3 includes an extensive library of radionuclides, but there are many more that are not included. Surrogates are often used to substitute for nuclides not in the library, though the results are usually overestimates. This paper addresses nuclides that are not in the library and describes methods to obtain more accurate results.

Modeling aeolian transport of soil-bound plutonium: considering infrequent but normal environmental disturbances is critical in estimating future dose.

Dose assessments typically consider environmental systems as static through time, but environmental disturbances such as drought and fire are normal, albeit infrequent, events that can impact dose-influential attributes of many environmental systems. These phenomena occur over time frames of decades or longer, and are likely to be exacerbated under projected warmer, drier climate. As with other types of dose assessment, the impacts of environmental disturbances are often overlooked when evaluating dose from aeolian transport of radionuclides and other contaminants. Especially lacking are predictions that account for potential changing vegetation cover effects on radionuclide transport over the long time frames required by regulations. A recently developed dynamic wind-transport model that included vegetation succession and environmental disturbance provides more realistic long-term predictability. This study utilized the model to estimate emission rates for aeolian transport, and compare atmospheric dispersion and deposition rates of airborne plutonium-contaminated soil into neighboring areas with and without environmental disturbances. Specifically, the objective of this study was to utilize the model results as input for a widely used dose assessment model (CAP-88). Our case study focused on low levels of residual plutonium found in soils from past operations at Los Alamos National Laboratory (LANL), in Los Alamos, NM, located in the semiarid southwestern USA. Calculations were conducted for different disturbance scenarios based on conditions associated with current climate, and a potential future drier and warmer climate. Known soil and sediment concentrations of plutonium were used to model dispersal and deposition of windblown residual plutonium, as a function of distance and direction. Environmental disturbances that affected vegetation cover included ground fire, crown fire, and drought, with reoccurrence rates for current climate based on site historical patterns. Using site-specific meteorology, accumulation rates of plutonium in soil were modeled in a variety of directions and distances from LANL sources. Model results suggest that without disturbances, areas downwind to the contaminated watershed would accumulate LANL-derived plutonium at a relatively slow rate (<0.01 Bq m(-2) yr(-1)). However, model results under more realistic assumptions that include environmental disturbances show accumulation rates more than an order-of-magnitude faster. More generally, this assessment highlights the broader need in radioecology and environmental health physics to consider infrequent but normal environmental disturbances in longer-term dose assessments.

Operational experience of continuous air monitoring of smoke for ²³9Pu during a wildfire.

Smoke from a wildfire in northern New Mexico that moved along the border of the Los Alamos National Laboratory (LANL) was monitored for ²³9Pu in the event that the fire might cross into LANL property containing locations with low, but greater than background, levels of ²³9Pu and other alpha-emitting radionuclides. Three Environmental Continuous Air Monitors (ECAMs) in operation at LANL at the time of the fire provided near real-time measurements of the ²³9Pu in the smoke. Sampling data from routine measurements of PM-10 and PM-2.5 concentrations in the city of Los Alamos showed that smoke in the air rose during the fire to several hundred µg m⁻³, which produced limited visibility (several hundred meters) and resulted in poor air quality alerts for about a week-long period. Previous studies have shown that airborne dust can significantly impair continuous air monitors, so the purpose of this study was to assess the performance of the ECAMs under smoky conditions, which is important for many emergency response scenarios. Additionally, ECAMs are not required to be tested in smoke by ANSI standards, so there is little to no published data on performance of any ECAM while sampling smoke. Results show that the deployed ECAMs had reduced flow as the filter clogged with fine particles, but the goodness-of-fit parameter of the peak shape fitting algorithms and the minimum detectable concentration and dose were not impacted until the flow was reduced by more than about 20%, and even then they were within tolerable limits. Overall, ECAM performance was not impacted during the fire even under heavy smoke conditions and fluctuating radon levels, though changing the filters to limit any reductions in flow to less than 20% would maintain optimal ECAM performance.

Corrections for measurements of tritium in subterranean vapor using silica gel.

Hazardous contaminants buried within vadose zones can accumulate in soil gas. The concentrations and spatial extent of these contaminants are measured to evaluate potential transport to groundwater for public risk evaluation. Tritium is an important contaminant found and monitored for in vadose zones across numerous sites within the US nuclear weapons complex, including Los Alamos National Laboratory. The extraction, collection, and laboratory analysis of tritium from subterranean soil gas presents numerous technical challenges that have not been fully studied. Particularly, the lack of moisture in the soil gas in the vadose zone makes it difficult to obtain enough sample (e.g., > 5 g) to provide for the required measurement sensitivity, and often, only small amounts of moisture can be collected. Further, although silica gel has high affinity for water vapor and is prebaked prior to sampling, there is still sufficient residual moisture in the prebaked gel to dilute the relatively small amount of sampled moisture; thereby, significantly lowering the "true" tritium concentration in the soil gas. This paper provides an evaluation of the magnitude of the bias from dilution, provides methods to correct past measurements by applying a correction factor (CF), and evaluates the uncertainty of the CF values. For this, 10,000 Monte Carlo calculations were performed, and distribution parameters of CF values were determined and evaluated. The mean and standard deviation of the distribution of CF values were 1.53 ± 0.36, and the minimum, median, and maximum values were 1.14, 1.43, and 5.27, respectively.