Air pollution is a universal problem in all agglomerations, world wide.
Depending on the economic structure (local industry), but also location and climate zone
(affecting dust from natural sources in arid areas, and summer ozone on warmer climes)
The main driving forces vary; a major contributor, in most any case, is traffic,
that contributes between half and three quarter of emissions.
And different from emission that are contributed by high industrial stacks,
that disperse before the reach the ground level and thus contribute to population exposure
to pollution, ground level emission from traffic are immediately "effective".
CityWare utilizes major components of the AirWare
system, which in turn uses the prognostic meteorological models MM5 and WRF
to generate the dynamic boundary conditions and inputs for the dispersion, fate and transport modeling.
Hourly nowcasts, forecast over several days, scenario analysis and EIA,
and the multi-criteria optimization of emission control strategies are the main functions.
Several model are used, that include nested grid 3D Eulerian photochemical codes like CMAx,
CFD tools for high-resolution, highly transient near fields modeling with 3D obstacle
(buildings) explicitly considered, a Lagrangian (Gaussian puff) model based on INPUFF,
and the classical regulatory Gaussian model system AERMOD.
The range of models of different scope, resolution, technology, helps to cover a wide
range of situations, but also supports intercomparison of model results as part of model validation exercises.
The fate and transport models for ambient air quality are coupled (provide dynamic boundary conditions)
with a dynamic indoor air pollution model.
For the simulation of line sources
(traffic) for very large (city wide) road networks with thousands of segments,
a highly efficient computational kernel and convolution model including a local mixing zone
approach to represent traffic induced local turbulence is used.
For mobile emission sources
(road transport, shipping, aircraft/airport )
a very high resolution dynamic 3D multi-puff model (Lagrangian/Gaussian) is used.
The same 3D model framework is also used for dynamic noise modelling.
Regulatory compliance, but also more complex exposure and impact functions
are the key performance indicators produced, together with the more complex spatially
distributed and dynamic model results in the form of thematic maps and animations.
The dispersion models use city wide emission inventories, and like to
monitoring networks where available to use real-time observations for
model validation and data assimilation.
Observed or predicted violation of air quality standards are used to trigger
a number of control and emission reduction strategies, that can include measures
such as traffic restrictions (from selective road closure to speed limits to adaptive road pricing),
reduction of production levels of major industrial emitters such as powerplants,
or temporary fuel changes (from oil to gas) where feasible.