What the heck is a kg of nitrogen equivalent?

Quantities and units for LCA impact categories are abstract, hard to grasp, especially for people unfamiliar with LCA. Can anyone suggest resources for helping to put context or scale to typical LCA impact results?

There are good examples for helping people grasp GHG values, e.g., ## kgCO2e is equivalent to burning XX gallons of gasoline, or YY passenger vehicles on the road for a year, or powering ZZ homes in [your favorite location].

But what about the other typical categories - eutrophication potential, acidification potential, etc? Are there any analagous examples to help provide even a little more of a concrete sense of what those values or units mean in the world?


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Hi Brook,

That’s tricky. There are equivalents for GHG emissions as you identified, as well as some other indicators such as litres of water used (equivalent volume of Olympic size swimming pools).
The reason why there aren’t as many other analogue values is probably because they are less consistent. E.g. the GHG emissions of an average car can be easily calculated using average fuel type and fuel efficiency. This becomes a bit harder for Nitrogen emissions (although it should be possible to have a decent stab at it).
As most studies report on GHG emissions as their main indicator, it is logical that this is the most reported analogous example. You may also need to consider the potentially confusing results of expressing both CO2 and N in analogues. Imagine a simple hypothetical process that burns 1 L of petrol and 1 L of diesel. The GHG emissions may be equivalent to driving a car for 15 km. The NOx emissions may be equivalent to driving a car for 20 km. You could get different analogue results for a process depending on how your analogue reference is defined. That would obviously be unhelpful.
You would also have to be wary of the uncertainty that is much higher in the non-GHG indicators than it is for carbon. e.g. NOx emissions of an engine are not only a result of the fuel used, but perhaps more so of the way the engine is run. That makes it incredibly difficult to come up with meaningful analogue equivalents.

Finally, LCA indicators are expressed in equivalents already. Translating these values to analogues adds a layer of interpretation/inaccuracy to the LCA results. Your best approach could be to find a reliable normalisation set (e.g. looking at the total impacts of an average global or North American person across the impact categories you are interested in.) That allows you to express results of an LCA according to how it relates to the annual impacts of an average person. For example, “the nitrogen emissions of the process are equal to 1.5 times the average person’s annual nitrogen emissions”.

Hope this helps.


This is very helpful, Rob. I appreciate you taking the time to respond. I will digest and may follow up again…

I also have not seen any analog translations for other categories than GWP, but I like using the Gulf of Mexico Dead Zone for explaining what eutrophication is. LCA’s normalization and weighing factors are supposed to help with understanding the scope of impacts across categories but there are issues with subjectivity and regional priorities. For example, eutrophication has regional effects (unlike GWP which has global effects). I like the idea of expressing impacts as as a ratio of annual impacts of an average person, like Rob mentioned. Another option would be to compare to the eutrophication impacts of growing different kinds of food - I believe most eutrophication impacts come from the agricultural sector. Lastly, as far as I know, the modeling of eutrophication related emissions in some background datasets is not very robust, resulting in large uncertainties. That covers eutrophication, now onto other categories…

Thanks, Vaclav.
To both of you – I appreciate the thought of using an average person’s impact as a reference point. I see normalization factors (average annual per capita impacts) for US/Canada in Table 2 here: https://www.researchgate.net/publication/245032686_Updated_US_and_Canadian_normalization_factors_for_TRACI_21
Sustainable Minds uses these numbers in this document:
Learn about SM Single Score results
The article is from 2013, the data from 2008.
Are there other sets of normalization factors you recommend looking at? Preferably USA or North America, but not necessarily.


Thank you for bringing this question up. We had this exact discussion here at LMN while trying to quantify an LCA study looking at the switch from a concrete structure to a CLT structure. While using CLT results in a 35% reduction in carbon emissions, our acidification and eutrophication numbers increase between 50% and 150%. But because these numbers are orders of magnitude less than the CO2eq numbers, it’s hard to put these changes into context. Using the numbers in the paper helps to bring this down to a per person level, but the question of impact remains. Are the emissions of one person for acidification and eutrophication of equal importance to those of their carbon emissions?

The importance of categories is usually addressed by using “weighing factors”. For example, the EPA’s BEES tool uses weighing factors to come up with a single score. See this BEES User Manual for how the tool weighs its impact categories (Table 2-8, also screencaptured here), and how the weights were created. As mentioned before though, weighing is generally based on someone’s consensus and is subjective to what people perceive as important to them. Weighing can be helpful for putting things into perspective but should be taken with a grain of salt.

We outlined this process a bit in the Carbon Leadership Forum’s LCA Practice Guide. See page 28.

Normalize per population and weight based on impacts importance (value judgement).

Understanding the numbers in context is important. For example, for most building materials the ozone depletion impacts are minimal so even if increased by 500% it wouldn’t matter. I use the analogy that if you have a ‘clean’ gymnasium, it might still have one grain of sand in it. If you increased the amount of sand on the gym floor by 500% you’d now have 5 grains of sand. I’d still call it clean.

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