what kind of secondary datasets can be used are listed in the DNM, based on the
level of operational control the company performing the study has.
• Reduction of costs. One of the barriers towards a wider implementation of
LCA, especially in Small and Medium Enterprises (SMEs) has been the cost of
implementing such studies, due to a number of factors, including the amount
of data to be collected/found, the time requested to do calculations, the costs of
verification, the cost to access to secondary LCI database. The implementation
of PEF will bring down many of the costs of performing a PEF/LCA study, up
to 80%, depending on the specific situations. This result will be achieved thank
to the availability of common rules (PEFCRs/OEFSRs), high quality secondary
LCI datasets available for free to any user around the world, free availability of
the models used, the availability of user-friendly software, of e-learning packages developed in several languages, and clear verification rules.
• Harmonisation of secondary data sources. By having clear modelling
requirements for secondary dataset tendered, the PEF initiative is steering the
harmonisation of existing LCI commercial databases. The Commission will
make available more than 8000 secondary LCI datasets coming from 6 different
data providers. They will all have the same modelling requirements for the
foreground data, the same energy and transport datasets for the background.
Moreover, they will all use the same format and nomenclature, therefore making
them directly usable in most of the LCA software available on the market.
The second presentation was delivered by Mr Erwin M. Schau from the
European Commission Joint Research Centre. He focused his presentation on the
concept of classes of performance, based on the example of the PEFCR on olive oil.
One of the novelty introduced by the PEF method is the concept of benchmark,
corresponding to the PEF profile of the average product sold in Europe.
Each PEFCR includes one or more representative products. Each of them is
modelled based on the different production techniques and their respective “weight”
in terms of consumption based European market. The representative product
therefore represents the weighted average for that group and its PEF profile, calculated and reported in the PEFCR, it is the benchmark for that product
group. Therefore, by having this reference publicly available, each producer will be
able to know if their own product score better or worse than the benchmark. Once
the benchmark is available, the next logical step is to consider the possibility of
developing classes of environmental performance. During the pilot phase the
stakeholders leading the development of PEFCRs were invited to test this concept,
in particular trying to develop 5 classes of performance, where the benchmark is
always class C. This is an optional requirement. The approach taken to define the
classes of performance was to identify the most relevant parameters (in terms of
activity data and emissions) and then identify the theoretical minimum and maximum values possible for such parameters. Once these were identified the calculations were run to identify the range of performance that could be achieved with
different combinations of the various parameters. Mr. Schau highlighted the pros
and cons of this approach, clearly stating that the ideal solution would be to base the
Special Session on Product Environmental Footprint
517
level of operational control the company performing the study has.
• Reduction of costs. One of the barriers towards a wider implementation of
LCA, especially in Small and Medium Enterprises (SMEs) has been the cost of
implementing such studies, due to a number of factors, including the amount
of data to be collected/found, the time requested to do calculations, the costs of
verification, the cost to access to secondary LCI database. The implementation
of PEF will bring down many of the costs of performing a PEF/LCA study, up
to 80%, depending on the specific situations. This result will be achieved thank
to the availability of common rules (PEFCRs/OEFSRs), high quality secondary
LCI datasets available for free to any user around the world, free availability of
the models used, the availability of user-friendly software, of e-learning packages developed in several languages, and clear verification rules.
• Harmonisation of secondary data sources. By having clear modelling
requirements for secondary dataset tendered, the PEF initiative is steering the
harmonisation of existing LCI commercial databases. The Commission will
make available more than 8000 secondary LCI datasets coming from 6 different
data providers. They will all have the same modelling requirements for the
foreground data, the same energy and transport datasets for the background.
Moreover, they will all use the same format and nomenclature, therefore making
them directly usable in most of the LCA software available on the market.
The second presentation was delivered by Mr Erwin M. Schau from the
European Commission Joint Research Centre. He focused his presentation on the
concept of classes of performance, based on the example of the PEFCR on olive oil.
One of the novelty introduced by the PEF method is the concept of benchmark,
corresponding to the PEF profile of the average product sold in Europe.
Each PEFCR includes one or more representative products. Each of them is
modelled based on the different production techniques and their respective “weight”
in terms of consumption based European market. The representative product
therefore represents the weighted average for that group and its PEF profile, calculated and reported in the PEFCR, it is the benchmark for that product
group. Therefore, by having this reference publicly available, each producer will be
able to know if their own product score better or worse than the benchmark. Once
the benchmark is available, the next logical step is to consider the possibility of
developing classes of environmental performance. During the pilot phase the
stakeholders leading the development of PEFCRs were invited to test this concept,
in particular trying to develop 5 classes of performance, where the benchmark is
always class C. This is an optional requirement. The approach taken to define the
classes of performance was to identify the most relevant parameters (in terms of
activity data and emissions) and then identify the theoretical minimum and maximum values possible for such parameters. Once these were identified the calculations were run to identify the range of performance that could be achieved with
different combinations of the various parameters. Mr. Schau highlighted the pros
and cons of this approach, clearly stating that the ideal solution would be to base the
Special Session on Product Environmental Footprint
517