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