Comparisons between a new point kernel-based scheme and the infinite plane source assumption method for radiation calculation of deposited airborne radionuclides from nuclear power plants

Dynamic harmonization of source-oriented and receptor models for source apportionment

Millions of premature mortalities are caused by the air pollution of fine particulate matter with aerodynamic diameters less than 2.5 μm (PM_2.5) globally per year. To effectively control the dominant emission sources and abate air pollution, source apportionment of PM_2.5 is normally conducted to quantify the contributions of various sources, but the results of different methods might be inconsistent. In this study, we dynamically harmonized the results from the two dominant source apportionment methods, the source-oriented and receptor models, by updating the emission inventories of primary PM_2.5 from the major sectors based on the Bayesian Inference. An adjoint model was developed to efficiently construct the source-receptor sensitivity matrix, which was the critical information for the updates, and depicted the response of measurements to the changes in the emissions of various sources in different regions. The harmonized method was applied to a measurement campaign in Beijing from January to February 2021. The results suggested a significant reduction of primary PM_2.5 emissions in Beijing. Compared with the baseline emission inventory of 2017, the primary PM_2.5 emissions from the local residential combustion and industry in Beijing had significantly declined by about 90 % during the investigated period of the year, and the traffic emission decreased by about 50 %. The proposed methods successfully identified the temporally dynamic changes in the emissions induced by the Spring Festival. The methods could be a promising pathway for the harmonization of source-oriented and receptor source apportionment models.

Simulation code for estimating external gamma-ray doses from a radioactive plume and contaminated ground using a local-scale atmospheric dispersion model

In this study, we developed a simulation code powered by lattice dose-response functions (hereinafter SIBYL), which helps in the quick and accurate estimation of external gamma-ray doses emitted from a radioactive plume and contaminated ground. SIBYL couples with atmospheric dispersion models and calculates gamma-ray dose distributions inside a target area based on a map of activity concentrations using pre-evaluated dose-response functions. Moreover, SIBYL considers radiation shielding due to obstructions such as buildings. To examine the reliability of SIBYL, we investigated five typical cases for steady-state and unsteady-state plume dispersions by coupling the Gaussian plume model and the local-scale high-resolution atmospheric dispersion model using large eddy simulation. The results of this coupled model were compared with those of full Monte Carlo simulations using the particle and heavy-ion transport code system (PHITS). The dose-distribution maps calculated using SIBYL differed by up to 10% from those calculated using PHITS in most target locations. The exceptions were locations far from the radioactive contamination and those behind the intricate structures of building arrays. In addition, SIBYL's computation time using 96 parallel processing elements was several tens of minutes even for the most computationally expensive tasks of this study. The computation using SIBYL was approximately 100 times faster than the same calculation using PHITS under the same computation conditions. From the results of the case studies, we concluded that SIBYL can estimate a ground-level dose-distribution map within one hour with accuracy that is comparable to that of the full Monte Carlo simulation.

Fast evaluation of three-dimensional gamma dose rate fields on non-equispaced grids for complex atmospheric radionuclide distributions

The gamma dose rate caused by airborne radionuclides is a major concern in the mitigation of nuclear accidents. Unfortunately, there is no fast method for calculating the three-dimensional (3D) gamma dose rate field near the source, because the corresponding airborne radionuclide distribution is usually calculated on non-equispaced grids and existing fast methods are only suitable for equispaced grids. This paper presents a method that accurately calculates the 3D dose rate field on non-equispaced grids, accelerating the computation by around two orders of magnitude. This method splits the time-consuming 3D integral in the dose rate model into a large convolution with a regularized smooth function and a small correction term. A nonuniform fast Fourier transform (NFFT) is used to rapidly calculate the convolution, which significantly enhances the computational speed. Our approach is applied to different grids and is compared with the FFT-based convolution method in two complex air dispersion simulations and a field experiment. The results show that the proposed method is in good agreement with the original 3D integral method and avoids grid-dependent interpolation errors in the FFT-based convolution method. This method enables a coupled analysis of wind, radioactivity, and dose rate on arbitrary grids, which is important for simplifying the emergency response in the case of small modular reactors.