The Multi-puff Approach And The Optimum Interpolation TechniqueTo Improve A Classical Gaussian Model

Abstract

The Gaussian plume model is the most common air pollution model. However, aiming to model the dispersion of air pollutants under non-homogeneous wind conditions, the puff-approach was applied in this work, by which a serious of discrete puffs is simulated as a continuous meandering plume. The developed model was applied to an urban area (the city of Lisbon) and evaluated by comparison with air quality data. It showed the capability to simulate the transport and dispersion of non-reactive pollutants from various sources under complex wind field and different atmospheric conditions. In addition, the modelling results were integrated with the observation data from the air quality-monitoring network in Lisbon by means of data assimilation. An optimal analytic result between the modelling result and the observation data was obtained by using optimal interpolation, which can provide a linear estimator by minimising the error covariance of the analytic result based on certain correlation functions. The correlation functions were determined from historical measurements from the air quality-monitoring network in Lisbon. The analytic result has shown that the modelling result can be improved by the technique of optimal interpolation in the sense of statistical approach.