B. Owen et al., Use of a new generation urban scale dispersion model to estimate the concentration of oxides of nitrogen and sulphur dioxide in a large urban area, SCI TOTAL E, 235(1-3), 1999, pp. 277-291
This paper describes the use of urban emission inventory data and an urban
scale dispersion model (ADMS-Urban) to calculate concentrations of NOx and
SO2, in two areas of London, Central London and East London. Local authorit
ies in the UK are expected to undertake reviews of air quality in their are
as to determine whether air quality objectives set by the National Air Qual
ity Strategy will be achieved by 2005. The UK Government proposes that loca
l authorities in urban areas develop spatially disaggregated emission inven
tories in conjunction with dispersion models to assess compliance with the
air quality objectives laid down in the strategy. This paper examines the p
erformance of an urban emission inventory and a dispersion model (ADMS-Urba
n) to assess air quality from emission sources by comparing model predictio
ns with monitored concentrations at four locations. The model used has a GI
S interface and uses a spatially disaggregated urban emissions inventory to
provide an integrated emission inventory and dispersion modelling system.
The dispersion model used in this study is a second-generation Gaussian dis
persion model which is characterised by the use of boundary layer similarit
y profiles to parameterise the variation of turbulence with height within t
he boundary layer. In a large urban area such as London there are many diff
erent sources contributing to the concentrations in the atmosphere. This mo
delling study aims to examine and evaluate the consideration of both local
effects and emissions from the Greater London region. The emissions invento
ry data for the study are described by a 1 X 1 km grid covering the Greater
London Area which measures 60 km east to west and 45 km north to south. Pr
edicted concentrations for a summer and winter period have been calculated
and modelled and measured times series data have been compared. Statistical
analyses have been carried out to assist in the comparison of model predic
tions with monitored data. Although no absolute significance can be attache
d to the numerical values of these measures, taken cumulatively, some concl
usions regarding the emissions inventory data and the model performance can
be made. (C) 1999 Elsevier Science B.V. All rights reserved.