16 Mar 2023
 | 16 Mar 2023

The Lagrangian Atmospheric Radionuclide Transport Model (ARTM) – Sensitivity studies and evaluation using airborne measurements of power plant emissions

Robert Hanfland, Dominik Brunner, Christiane Voigt, Alina Fiehn, Anke Roiger, and Margit Pattantyús-Ábrahám

Abstract. The Atmospheric Radionuclide Transport Model (ARTM) operates at the meso-γ-scale and simulates the dispersion of radionuclides originating from nuclear facilities under routine operation within the planetary boundary layer. This study presents the extension and validation of this Lagrangian particle dispersion model and consists of three parts: i) a sensitivity study that aims to assess the impact of key input parameters on the simulation results; ii) the evaluation of the mixing prop- erties of five different turbulence models using the well-mixed criterion; and iii) a comparison of model results to airborne observations of carbon dioxide (CO2) emissions from a power plant and the evaluation of related uncertainties. In the sensitiv- ity study, we analyse the effects of stability class, roughness length, zero-plane displacement factor and source height on the three-dimensional plume extent as well as the distance between source and maximum concentration at the ground. The results show that the stability class is the most sensitive input parameter as expected. The five turbulence models are the default turbu- lence models of ARTM 2.8.0 and ARTM 3.0.0, one alternative built-in turbulence model of ARTM and two further turbulence models implemented for this study. The well-mixed condition tests showed that all five turbulence models are able to preserve an initially well-mixed atmospheric boundary layer reasonably well. The models deviate only 6 % from the expected uniform concentration below 80 % of the mixing layer height except for the default turbulence model of ARTM 3.0.0 with deviations by up to 18 %, respectively. CO2 observations along a flight path in the vicinity of the lignite power plant Bełchatów, Poland measured by the DLR Cessna aircraft during the CoMet campaign in 2018 allow to evaluate the model performance for the different turbulence models under unstable boundary layer conditions. All simulated mixing ratios are in the same order of magnitude as the airborne in situ data. An extensive uncertainty analysis using probability distribution functions, statistical tests and direct spatio-temporal comparisons of measurements and model results help to quantify the model uncertainties. With the default turbulence setups of ARTM version 2.8.0 and 3.0.0, the plume widths are underestimated by up to 50 % resulting in a strong overestimation of the maximum plume CO2 mixing ratios. The comparison of the three alternative turbulence models shows a good agreement of the peak plume CO2 concentrations, the CO2 distribution within the plumes and the plume width with 30 % deviations in peak CO2 concentration and less than 25 % deviation of the measured CO2 plume width. Uncertainties of the simulations may arise from the different spatial and temporal resolution of simulations and measurements in addition to the turbulence parametrisation and boundary conditions. The results of this work may help to improve the accurate representa- tion of real plumes in very unstable atmospheric conditions by the selection of distinct turbulence models. Further comparisons at different stability regimes are required for a final assessment of model uncertainties.

Robert Hanfland et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-245', Anonymous Referee #1, 26 May 2023
  • RC2: 'Comment on egusphere-2023-245', Anonymous Referee #2, 11 Sep 2023

Robert Hanfland et al.

Robert Hanfland et al.


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Short summary
In order to simulate the 3D structure of the exhaust plume within the planetary boundary layer in agreement with real plumes, we analysed the turbulence properties of five different turbulence models to understand their abilities of mixing and compared their simulated 3D dispersion patterns with airborn in situ measurements. The deviations between simulations and observation are quantified revealing one turbulence model that agrees best under the given atmosperic conditions.