Hi Lazlo,

This is a great question. The specific example you provided also gives us an opportunity to explain the pitfalls of generic data (and in some cases EPDs).

Acidification (kgCO4eq) is the result of sulphur (or other acid soluble compounds) pollution. The content of sulphur in the exhaust of different supply chains will differ dramatically. For example, the sulphur content of iron ore (key ingredient of steel) varies dramatically within the same mineral deposit so even a single source blast furnace operation will produce different acidification results depending on what parts of the mineral deposit their feed stock is coming from. Blast furnaces that source iron ore from the open market (the majority) tend to target very consistent feedstock as it is expensive to change setting within the furnace to deal with fluctuating contaminants and iron content. But even in this case, depending on the quality of steel being manufactured, the local environmental regulations (and a host of other factors) the sulphur content of the feed-stock will change significantly.

Another key ingredient to the steel making process is coking coal. This also has significant variations in sulphur content. So the combination of the Iron Ore and Coking Coal feedstock to a steel plant at any point in time will drive acidification impacts.

Manufacturing processes will also have various measures to mitigate contaminants like scrubbers.

And transport of the raw materials could also drive acidification where dirty fuels (or engines) are used.

Once you account for all these variables there’ll be significant deviations from the mean acidification potential for steel production. EPDs will pin point the impacts of a particular plant (at a particular time). Generic LCI data should be more of an average impact across a region.

Deviations in Global Warming Potential are generally lower between products (as energy requirements generally fluctuate less than contaminant levels).

So things to watch out for when trying to compare products:

  • Is it a fair comparison (same transport distances?)
  • Is it geographically relevant or comparable
  • Is it temporally relevant or comparable (not old data, or a short window of production

EPDs are a great move for the construction sector and will hopefully drive manufacturers to source cleaner feed stocks by paying a premium, and install scrubbers and other mitigating technologies to reduce the impact of their products. As such we definitely need to be encouraging their production and use. It is important however to ensure we’re making fair comparisons and EPDs present some problems in this regard when indicators or life cycle modules are missing, or assumed transport distances are not relevant for the project we’re working on.

I don’t think this answer necessarily solves your problem however hopefully sheds some light on the complexity of LCI data.

To get more specific on what is driving the difference in the products it would be necessary to deep dive and understand the variables. If this is critical for your project we can ask the data suppliers to provide more information.