A NOVEL PSEUDO-STATIONARY MODELING OF POLLUTANT MEASUREMENT PREDICTION FROM INDUSTRIAL EMISSIONS

摘要

Pollutant measurement prediction is a topic of great interest in the area of environmental measurements and health protection. Stationary description of pollutants is an approach in which the amount of pollutant per time unit is considered constant. But in many circumstances, this quantity is subject to a flow delay. In this paper we introduce a novel pseudo-stationary modeling based on Delay Differential Equations (DDE) that can better reflect forced and spontaneous emissions of pollutants from industrial plants and natural processes respectively. Emissions of Volatile Organic Compouund (VOC) from industrial plants and leakage of decayed radioactive wastes are respectively a concrete example. The concentration of VOC that are present in the atmosphere can be predicted by using mathematical models. Among the deterministic models that utilize an Eulerian approach, the Gaussian model can be interpreted as a simple solution to the problem. However, the variables that are present in such model, and which are subjected to simplifying assumptions, may not objectively represent reality. The purpose of this work is to utilize a delay logistic equation for the modeling of the data regarding VOC emissions, and to demonstrate its efficiency through a comparison with the classical Gaussian Plume Model.