22 Overview of the Change in NO 2 Assessment Maps During the Last …
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model. This is done hour by hour, accounting for chemistry [6]. The emissions for the
Gaussian model are a combination of the known point sources and traffic emissions
on the major roads. These are calculated using the COPERT emission factors and
traffic flows and speeds provided by the Flanders Traffic Control Center (VVC). In
order to validate the model, independent validation datasets using passive samplers
were collected by the Flemish Environmental Agency (VMM). It was shown that
the combined RIO-IFDM model provides good validation results for the non-street
canyon locations in these datasets (Fig. 22.1). Furthermore, validation showed the
importance of good traffic data for this type of exercise.
22.5 Including Street Canyons
Measurements have shown that the concentrations were still strongly underestimated,
mainly for NO 2 and PM 10 , due to the presence of street canyons. Therefore, we have
added the street canyon model OSPM (Operational Street Pollution Model, [1]) to
the chain, resulting in the RIO-IFDM-OSPM model. However, it was found that the
location of traffic data that was available was sometimes slightly off (several meters
to sometimes about 20 m) the true location. For the open-road concentration fields
this was not so important, but when combining the road segments with the building
locations to determine the location of the street canyons, this was problematic.
This problem was solved using an in-house developed algorithm combining on
the one hand the VVC-dataset on traffic intensities having slightly incorrect road
locations with on the other hand a dataset with correct road locations but without
traffic intensities. This algorithm solves the large majority of the location problems
in the dataset. At some specific complex locations a one-time manual intervention
was needed.
Once the roads were shifted to their correct locations an in-house developed preprocessor was applied, providing it with the traffic data and the building heights. This
preprocessor crawls over all line segments and marks at regular distances (typically
20 m) a dot. At this location, the preprocessor checks if the location is a street canyon
location, and if so, determines the street canyon characteristics (such as width and
height of the buildings) which are then provided to the OSPM-model.
The same problem for possible double counting of emissions is present, as emissions are both present in the Gaussian IFDM-model as in the OSPM-model. Therefore, a similar method avoiding double counting as between RIO and IFDM is applied.
The RIO-IFDM-OSPM model results in two sets of concentration values: one at
non-street canyon-locations from the IFDM-model and one at street-canyon locations
for the OSPM-model. In order to make one map, and avoid concentrations spilling out
of the street canyons due to interpolation, a method for postprocessing was devised
which is similar to a jigsaw-puzzle. Indeed, the concentrations in and out of the street
canyons are treated separately and the result is then added together. The complete
description of this postprocessing can be found in [7].
143
model. This is done hour by hour, accounting for chemistry [6]. The emissions for the
Gaussian model are a combination of the known point sources and traffic emissions
on the major roads. These are calculated using the COPERT emission factors and
traffic flows and speeds provided by the Flanders Traffic Control Center (VVC). In
order to validate the model, independent validation datasets using passive samplers
were collected by the Flemish Environmental Agency (VMM). It was shown that
the combined RIO-IFDM model provides good validation results for the non-street
canyon locations in these datasets (Fig. 22.1). Furthermore, validation showed the
importance of good traffic data for this type of exercise.
22.5 Including Street Canyons
Measurements have shown that the concentrations were still strongly underestimated,
mainly for NO 2 and PM 10 , due to the presence of street canyons. Therefore, we have
added the street canyon model OSPM (Operational Street Pollution Model, [1]) to
the chain, resulting in the RIO-IFDM-OSPM model. However, it was found that the
location of traffic data that was available was sometimes slightly off (several meters
to sometimes about 20 m) the true location. For the open-road concentration fields
this was not so important, but when combining the road segments with the building
locations to determine the location of the street canyons, this was problematic.
This problem was solved using an in-house developed algorithm combining on
the one hand the VVC-dataset on traffic intensities having slightly incorrect road
locations with on the other hand a dataset with correct road locations but without
traffic intensities. This algorithm solves the large majority of the location problems
in the dataset. At some specific complex locations a one-time manual intervention
was needed.
Once the roads were shifted to their correct locations an in-house developed preprocessor was applied, providing it with the traffic data and the building heights. This
preprocessor crawls over all line segments and marks at regular distances (typically
20 m) a dot. At this location, the preprocessor checks if the location is a street canyon
location, and if so, determines the street canyon characteristics (such as width and
height of the buildings) which are then provided to the OSPM-model.
The same problem for possible double counting of emissions is present, as emissions are both present in the Gaussian IFDM-model as in the OSPM-model. Therefore, a similar method avoiding double counting as between RIO and IFDM is applied.
The RIO-IFDM-OSPM model results in two sets of concentration values: one at
non-street canyon-locations from the IFDM-model and one at street-canyon locations
for the OSPM-model. In order to make one map, and avoid concentrations spilling out
of the street canyons due to interpolation, a method for postprocessing was devised
which is similar to a jigsaw-puzzle. Indeed, the concentrations in and out of the street
canyons are treated separately and the result is then added together. The complete
description of this postprocessing can be found in [7].