Keywords: dispersion climatology, factory emissions, mean concentrations, 98th percentile concentration, power station emissions, sequential data, statistical analysis, meteorological data, meteorological pre-, processing, atmospheric dispersion models, air pollution, environmental pollution, modelling, UK, United Kingdom
Investigating the importance of pre-processing in estimating dispersion climatology
This study investigates the sensitivity of dispersion modelling results to the way that climatologies are described. The study investigates the sensitivity of the dispersion predictions to the number of years of data used; using hour by hour or statistical data; using different variables (e.g. surface heat flux or the Monin-Obukhov length); using different category boundaries for statistically analysing the data; using different meteorological sites; and using different periods of data. The short-range dispersion model ADMS v1.5 has been used in this study, using mainly meteorological data collected at a site in Wattisham, UK (this site was chosen because it is flat, with relatively uncomplex terrain). The model has been run with these data using the emission characteristics typical of a high-level power station emission and of a low-level factory source in the UK.