Methodology of ecoinvent 3

Methodology of ecoinvent 3

What are global background activities and where do they come from?

Many users were missing international data in many areas of ecoinvent version 2. For ecoinvent version 3, we have prepared a framework for international datasets, to improve the international coverage of ecoinvent. One of the steps we have taken is to ensure that all activities in the ecoinvent database have a global dataset covering the average global production.

 

Such datasets already existed for some datasets in version 2; new is that we introduced global datasets for all activities covered by ecoinvent version 3. While we have made an effort to collect new data for these datasets (and are continuing to do so), it is important to realise that currently, many of these datasets are just extrapolated from one of the existing, regional datasets. These datasets are described as extrapolated in their comments fields and it is important to pay attention to the quality of these datasets.

 

The increased uncertainty from these extrapolations is quantified by the pedigree matrix approach, which is generally used in the ecoinvent database to describe uncertainty resulting from less than perfect data quality. It is more important than ever to consider these uncertainties in your work.

 

Therefore, every regional dataset present in the database also has a global dataset covering the average global production. Ideally this global dataset is created individually to accurately reflect the global average based on international data. In cases where data on an average global production were not available, the global dataset may have been extrapolated as a copy of the regional dataset, or as an average of regional data from several regions with adjusted uncertainty information.

In the past, processes with inadequate geographies were often used because they were the only ones available, e.g. jute fibres production in India had urea from Europe as an input. Now, thanks to the available global background datasets the user can use a product and the global average will always be available as an option with higher uncertainty values.

In this concrete example the market for urea is supplied by urea from production in Europe and by urea from production in the rest of the world. The rest of the world activity is generated automatically by the database service layer. In ecoinvent v3.2 (2015) and higher the RoW is generated as an exact copy of the GLO dataset with uncertainty adjusted. The newly generated RoW is then linked with activities of an adequate geographies creating RoW specific supply chain.

In the future, when for example production of urea from China will be supplied to the database, the market for urea will be automatically updated taking this new dataset into account. Subsequently the jute fibre production in India will be automatically updated as well. In other words the urea "mix" supplied to this activity will be updated. Should a specifically Indian dataset become available and the data show that Indian jute fibre production uses local urea only the specific dataset can also be directly linked to use this local input.

 

This way of structuring the database allows ecoinvent to easily integrate new datasets from all over the world and ensure that all the new datasets will be automatically and easily be integrated into the whole database.