5. Conclusions
To summarize, a university is a complex enterprise with a wide
variety of contributions to the CF. EEIO modeling has proven
effective in identifying both target areas and differences in the CF
across different faculties/departments. The high contribution of
indirect, scope 3 emissions clearly shows the need of including this
segment of the inventory in order to develop a complete CF. The
study of NTNU shows that the scope 3 contributions cover a quite
large set of elements, and that EEIO modeling combined with
financial data from the account system has proven a possible
solution for including these. Furthermore, dividing CF into faculties
using EEIO methodology enables us to compare universities around
the world more consistently. Using complete multi-regional EEIO
models matched to a set of universities in investigating this could
be an interesting possibility in further work.
However, when implementing mitigation actions, more specific
data are necessary to sufficiently track the effect. This is possible
either through hybridizing the EEIO model or through the establishment
of a set of indicators on the environmental performance of
the different areas, as previously indicated. Although indicators
would be an easy way to measure some key developments in the
mitigation strategy, only an EEIO model would capture the
complete CF in avoiding cut-offs and rebound effects.
The work with NTNU was followed by a similar analysis of the
student organization of NTNU (SiT). This includes student villages,
training centers, kindergartens, canteens, etc. Further work could
therefore also aim to link these calculations to cover a larger part of
the CF of a student’s life.
5. Conclusions
To summarize, a university is a complex enterprise with a wide
variety of contributions to the CF. EEIO modeling has proven
effective in identifying both target areas and differences in the CF
across different faculties/departments. The high contribution of
indirect, scope 3 emissions clearly shows the need of including this
segment of the inventory in order to develop a complete CF. The
study of NTNU shows that the scope 3 contributions cover a quite
large set of elements, and that EEIO modeling combined with
financial data from the account system has proven a possible
solution for including these. Furthermore, dividing CF into faculties
using EEIO methodology enables us to compare universities around
the world more consistently. Using complete multi-regional EEIO
models matched to a set of universities in investigating this could
be an interesting possibility in further work.
However, when implementing mitigation actions, more specific
data are necessary to sufficiently track the effect. This is possible
either through hybridizing the EEIO model or through the establishment
of a set of indicators on the environmental performance of
the different areas, as previously indicated. Although indicators
would be an easy way to measure some key developments in the
mitigation strategy, only an EEIO model would capture the
complete CF in avoiding cut-offs and rebound effects.
The work with NTNU was followed by a similar analysis of the
student organization of NTNU (SiT). This includes student villages,
training centers, kindergartens, canteens, etc. Further work could
therefore also aim to link these calculations to cover a larger part of
the CF of a student’s life.
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