Estimating distributions of airborne contaminants released by sources with dynamic strength and dynamic location by a probabilistic model

Abstract

Characteristics of contaminant release source usually contribute significant impacts to dispersion of airborne pollutants. It is necessary and also desirable to grasp detailed information of contaminant distributions under various release patterns of contaminant sources. This study developed a Markov chain based probabilistic model to simulate transport and dispersion of airborne contaminants released by sources with dynamic strengths and locations. The proposed model takes the dynamic source strengths and locations into account by replacing elements of the state vector with values in accord with specific functions, which indicate strength and location variations. The particle phase simulations need to be initialized by comprehensive data of the flow field, which can be solved by CFD tools in advance. For the first step, the developed model is validated by experiment data from a 2D turbulence duct flow with a particulate source instantaneously releasing airborne particles. Then the new model is adopted to simulate contaminant dispersion of gaseous (or particles with small diameters) contaminant released by sources with dynamic strength and location. Results indicate that the proposed model is capable of predicting the behaviors of contaminant sources under various release patterns. The effects of dynamic contaminant sources on downstream regions in unidirectional flow are limited by the distances between the target region and source location. Accuracy of the present model is significantly affected by temporal intervals (the specified time step Δt) for sources with dynamic strengths and spatial intervals (computational grid scales) for sources with dynamic locations.