A comprehensive modelling approach to estimate the transmissibility of coronavirus and its variants from infected subjects in indoor environments.

A central issue in assessing the airborne risk of COVID-19 infections in indoor spaces pertains to linking the viral load in infected subjects to the lung deposition probability in exposed individuals through comprehensive aerosol dynamics modelling. In this paper, we achieve this by combining aerosol processes (evaporation, dispersion, settling, lung deposition) with a novel double Poisson model to estimate the probability that at least one carrier particle containing at least one virion will be deposited in the lungs and infect a susceptible individual. Multiple emission scenarios are considered. Unlike the hitherto used single Poisson models, the double Poisson model accounts for fluctuations in the number of carrier particles deposited in the lung in addition to the fluctuations in the virion number per carrier particle. The model demonstrates that the risk of infection for 10-min indoor exposure increases from 1 to 50% as the viral load in the droplets ejected from the infected subject increases from 2 × 108 to 2 × 1010 RNA copies/mL. Being based on well-established aerosol science and statistical principles, the present approach puts airborne risk assessment methodology on a sound formalistic footing, thereby reducing avoidable epistemic uncertainties in estimating relative transmissibilities of different coronavirus variants quantified by different viral loads.

Relationship Between the Mobility of Aggregates and Fluid Penetration Depth Across a Range of Fractal Dimensions Using Stokesian Dynamics.

The hydrodynamic behavior of fractal aggregates plays an important role in various applications in industry and the environment, and has been a topic of interest over the past several decades. Despite this, crucial aspects such as the relationship of the mobility radius, Rm, with respect to the fractal dimension, df, and the fluid penetration depth, δ, have largely remained unexplored. Herein, we examine these aspects across a wide range of df's through a Stokesian dynamics approach. It takes into account all orders of monomer-monomer interactions to construct the resistance matrix for the entire cluster, which is assumed to be rigid. Statistical fractals created using algorithms such as diffusion limited aggregation (DLA), cluster-cluster aggregation (CCA), tunable Monte Carlo algorithm, and a deterministic Vicsek fractal, with df varying from 1.76 to 3, and the number of monomers ranging from 20 to 10 240 are considered. While confirming the expected asymptotic cluster-size independence of the hydrodynamic ratio, ß = Rm/Rg (where Rg is the radius of gyration of the cluster), this study reveals a monotonically increasing trend for ß with increasing df. The decay of the fluid velocity within the aggregate is quantified via the concept of penetration depth (δ). Analysis shows that the dimensionless penetration depth (δ* = δ/Rg) approaches asymptotic constancy with respect to cluster size in contrast to a weak dependency of the form δ* ∼ (Rg/a)-(df - 1)/2, predicted by the mean-field theory (a being the monomer radius). Furthermore, the penetration depth is found to decrease rapidly, in an exponential manner, with increasing ß. This establishes a quantitative relationship between the resistance experienced by the cluster and the degree of penetration of fluid into it. The implications of these results are further discussed.

Modeling the viral load dependence of residence times of virus-laden droplets from COVID-19-infected subjects in indoor environments.

In the ongoing COVID-19 pandemic situation, exposure assessment and control strategies for aerosol transmission path are feebly understood. A recent study pointed out that Poissonian fluctuations in viral loading of airborne droplets significantly modifies the size spectrum of the virus-laden droplets (termed as "virusol") (Anand and Mayya, 2020). Herein we develop the theory of residence time of the virusols, as contrasted with complete droplet system in indoor air using a comprehensive "Falling-to-Mixing-Plate-out" model that considers all the important processes namely, indoor dispersion of the emitted puff, droplet evaporation, gravitational settling, and plate out mechanisms at indoor surfaces. This model fills the existing gap between Wells falling drop model (Wells, 1934) and the stirred chamber models (Lai and Nazarofff, 2000). The analytical solutions are obtained for both 1-D and 3-D problems for non-evaporating falling droplets, used mainly for benchmarking the numerical formulation. The effect of various parameters is examined in detail. Significantly, the mean residence time of virusols is found to increase nonlinearly with the viral load in the ejecta, ranging from about 100 to 150 s at low viral loads (<104 /ml) to about 1100-1250 s at high viral loads (>1011 /ml). The implications are discussed.

DOSE ASSESSMENT FOR ATMOSPHERIC DISCHARGE OF LONG-LIVED RADIONUCLIDES IN NUCLEAR POWER PLANT DECOMMISSIONING.

Decommissioning of nuclear power plants is a multistage process involving complex operations like radiological characterization, decontamination and dismantling of plant equipment, demolition of structures, and processing and disposal of waste. Radioactive effluents released into the environment may result in exposure of population through various exposure pathways. The present study estimates the public dose due to atmospheric discharge of important radionuclides during proposed decommissioning activities of Indian Pressurized Heavy Water Reactors. This study shows that major dose contributing radionuclides are 60Co followed by 94Nb, 134Cs, 154Eu, 152Eu, 133Ba, 99Tc, 93Mo and 41Ca. It is found that infant dose is higher than adult dose and major fraction of total dose (~98%) is through ground shine and ingestion; other pathways such as inhalation and plume shine contribute only a small fraction. This study will be helpful in carrying out radiological impact assessment for decommissioning operations which is an important regulatory requirement.