The levers are implemented in the model as scenarios, with a ramp up phase,
followed by another phase where they constantly deliver benefits. The level of
possible implementation is defined by an implementation rate and depends on the
current state and the maximum applicability. As an example: For the Lever
Automated train operation (ATO) metro, the current state is the share of metro lines
that have an ATO already and the maximum applicability would be 100% unless
there are historic lines that shall keep human drivers.
The efficiency of each lever has to be quantified depending on the city specific
conditions. And these conditions are assessed with individual parameters. In the
case of the ATO for metros, a simulation in FALKO [3] (a simulation tool for train
scheduling and simulation of energy consumption) was run for a typical metro line
to check which parameters have the most significant impact on energy consumption. It turned out that the distance between two consecutive stations has the most
significant correlation with the energy saving potential of an ATO. The city
transport system model is therefore fed with the average distance between stations.
All levers model relative changes and can be combined in scenarios, also
reflecting impacts of one lever on another lever. Some levers address the same
saving potential and are therefore modelled combined in one process or on global/
project level.
3 Results
The following section states first the results in terms of how appropriate and
practically feasible the above described methodology shows for the specific cause.
Afterwards, the relevance of individual methodological aspects is illustrated in the
form of actual modelling results from city projects.
3.1 Scope
The Scope of the model is in line with city’s requirements. Two large cities
requested two separate analyses for their inner city and outer city. Three cities, two
of them in Scandinavian countries, requested the exclusion of Scope 3 GHG
emissions in the energy upstream. Only one city in the south of Germany had Scope
3 GHG emissions from the energy upstream in their carbon accounting (WTW). All
but two cities could be convinced to include Scope 3 GHG emissions for this
relative comparison between levers. It allows a better symmetry between systems
for indicators that are only of relevance in their global context. Since the studies did
not aim to compare cities among each other, they did not have to fear an unfair
competition.
It was a common request that for air pollutants, Scope 1 emissions should be
reported individually. Especially traffic related urban emissions have a very high
198
F. A. Jaeger et al.
followed by another phase where they constantly deliver benefits. The level of
possible implementation is defined by an implementation rate and depends on the
current state and the maximum applicability. As an example: For the Lever
Automated train operation (ATO) metro, the current state is the share of metro lines
that have an ATO already and the maximum applicability would be 100% unless
there are historic lines that shall keep human drivers.
The efficiency of each lever has to be quantified depending on the city specific
conditions. And these conditions are assessed with individual parameters. In the
case of the ATO for metros, a simulation in FALKO [3] (a simulation tool for train
scheduling and simulation of energy consumption) was run for a typical metro line
to check which parameters have the most significant impact on energy consumption. It turned out that the distance between two consecutive stations has the most
significant correlation with the energy saving potential of an ATO. The city
transport system model is therefore fed with the average distance between stations.
All levers model relative changes and can be combined in scenarios, also
reflecting impacts of one lever on another lever. Some levers address the same
saving potential and are therefore modelled combined in one process or on global/
project level.
3 Results
The following section states first the results in terms of how appropriate and
practically feasible the above described methodology shows for the specific cause.
Afterwards, the relevance of individual methodological aspects is illustrated in the
form of actual modelling results from city projects.
3.1 Scope
The Scope of the model is in line with city’s requirements. Two large cities
requested two separate analyses for their inner city and outer city. Three cities, two
of them in Scandinavian countries, requested the exclusion of Scope 3 GHG
emissions in the energy upstream. Only one city in the south of Germany had Scope
3 GHG emissions from the energy upstream in their carbon accounting (WTW). All
but two cities could be convinced to include Scope 3 GHG emissions for this
relative comparison between levers. It allows a better symmetry between systems
for indicators that are only of relevance in their global context. Since the studies did
not aim to compare cities among each other, they did not have to fear an unfair
competition.
It was a common request that for air pollutants, Scope 1 emissions should be
reported individually. Especially traffic related urban emissions have a very high
198
F. A. Jaeger et al.