Some characterizartion factors need correction in EF3.1 for exiobase 3.9.4

Question

Hi,

I am working with the latest version of exiobase (3.9.4, academic). When comparing impacts (LCIA method 3.1) of some products with ecoinvent, I have found that in some categories exiobase provides very different impacts.

Specifically, in the Resource use, minerals and metals category, the impact is several orders of magnitude greater. Given the result, I checked the characterization factors in this category in the EF3.1 methods included in the exiobase database and those available for ecoinvent. For example, for gold:

exiobase:

Domestic Extraction Used - Metal Ores - Gold ores Elementary flows/material 52 kg Sb eq./kg

ecoinvent:

Gold Elementary flows/Resource/in ground 52 kg Sb-Eq/kg

It can be seen that exiobase collects fewer elementary flows, but CF for these are identical to those used in ecoinvent. However, there is one critical difference: while the elementary flows in ecoinvent appear to be of the metal, the elementary flows in exiobase are of the metal ore. The characterization factor for the ore cannot be the same as that for the metal, but rather the metal concentration in the ore (the ore grade) multiplied by the characterization factor.

Has anyone detected any similar misalignment in any other impact category? These would be differences between the elementary flows in exiobase and those considered in EF3.1.

Thanks in advance,

Gorka

Answer 1

I don't know how reliable an input/output database is for resource depletion characterization. Also the difference of ore grades in different regions is typically not reflected in the characterization factors, but in the mining processes itself. Otherwise an elementary flow would be needed for each possible ore grade. This might be different in exiobase, since I don't know the database very well.

I'm not working with exiobase, but want to highlight that already for climate change impacts, the differences between an input/output database like exiobase and a LCA database like ecoinvent can be orders of magnitude. See this paper here as an example:   https://doi.org/10.1111/jiec.13271

Answer 2

Hi Gorka,

I worked on the implementation of the EF3.1 method into the Exiobase. As you identified, the characterisation factors (CFs) used for the mineral ore depletion in the Exiobase were mapped directly to the CFs representing the depletion of metals in an elemental form from the EF3.1 method. 

This mapping choice was made since no information on the grade of the ores is available from the Exiobase files. The same mapping approach was also suggested by the JRC researchers in this paper (mapping information available in the SI).

However, you are right that the current CFs will lead to an overestimation of the "Resource use, minerals and metals" impacts. Therefore, I would advise you to treat these results with caution, and if you are interested in the depletion of specific ores (as represented by the elementary flows in the Exiobase), you can use the inventory of elementary flows to assess it directly.

As for potential misalignment for other impact categories, most elementary flows between the EF3.1 and the Exiobase could be mapped as being identical, with the exception of a few flows that exist in an aggregated form in the Exiobase but only in a disaggregated form in EF3.1 method. For these, average CFs were calculated based on the CFs of the flows belonging to the respective group (this was the case e.g. for the PCDD/Fs flow). 

I hope this helps.

Kind wishes,

Tomas

Comments

Thanks for your clarifications, Conrad & Tomas!
The papers provided are also very useful.
Gorka