A Novel Approach to Improve the Air Quality Predictions of Air Pollution Dispersion Modelling systems

The aim of this research paper is the introduction of a novel mathematical approach to improve the accuracy of the results of air pollution dispersion models based on the calibration of input background concentrations. Using the Dunkirk area of the City of Nottingham in the UK as a case study, an air pollution model in ADMS-Roads was created for developing the mathematical approach. The iterative application of this approach to the input background concentrations effectively reduced the error between not only the annual mean, but also the hourly, calculated and monitored air pollution concentrations. The traffic flow profiles of the modelled road network were included in the air pollution model and their impact on the model results, after the application of the calibration approach, was investigated. The inclusion of the traffic flow profiles reduced further the error between the hourly, but not the annual means of, calculated and monitored concentrations.