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Initially, this could be interpreted as inconsistent to have two delay factors with contradictory variations that
are supposed to represent the same impact category, climate change. However, these two factors are closely
related, both based on the decay curve of radiative forcing. GWP integrates this radiative forcing decay curve,
it reflects a cumulated value of radiative forcing, whereas GTP estimates temperature changes induced by the
radiative forcing decay curve and the climate impulse response . Yet the GTP is positioned further down
[28]
the cause-effect chain than the GWP. Delaying an emission reduces the cumulative radiative forcing,
represented by the GWP, but nevertheless causes a delayed temperature rise, represented by the GTP. These
results regarding the GTP call into question the relevance of using the GWP as a dynamic indicator as it
produces the illusion of a declining impact as it decreases cumulative radiative forcing, whereas in most cases
it is actually an increasing impact as it increases temperature. Expressed differently, distributing emissions
over time diminishes the temperature peak compared with an instantaneous release, as illustrated by the
AGTP temporal profiles from the worksheet tool . Simultaneously, the temperature peak is shifted to a later
[22]
point in time, leading to long-term temperatures that surpass those of the instantaneous-pulse scenario. This
interaction between peak reduction and temporal shifting reinforces the need for indicators that complement
GWP [20,21] . These results also justify why this article has renamed “discount factors” into “delay factors”, a
more generic and neutral expression that does not indicate any benefit or drawback from delaying emissions.

Applicability of the provided tool
Delay factors are especially interesting for partially dynamic approaches, i.e. based on EPDs. As EPDs are
built to evaluate a single unit of a product, the start and end times of system activities are much clearer, at
least in the foreground system. There is clearly a time duration after which no more emissions are
considered. A crucial distinction is that life cycle duration is not necessarily equal to product life. For
example, in the case of landfilling, emissions may occur for several years after the landfilling process itself. It
is up to the user to define the dynamic inventory to be used with the tool. Simplified approaches, such as
those used in the French RE2020 regulation , impose a duration of 50 years and approximate the duration
[11]
of the life cycle as that of the product’s lifespan, i.e. consider that all operations prior to the building's
delivery date are considered to occur at time zero, and that all operations subsequent to the product’s
end-of-life occur 50 years later.

For practitioners wishing to perform partial dynamic calculations based on EPDs, the spreadsheet format is
relevant. Compared with other spreadsheet tools such as dynCO 2 [12] , the developed tool provides GTP
[22]
calculation, and the compatibility between static and dynamic indicators defined by Equation 14 is ensured,
since the dynamic indicator is calculated according to the product life cycle duration and impact time
horizon chosen by the user. The tool not only provides the value of compatible static and dynamic
indicators, it also provides a temporal visualization of the various intermediate quantities in the calculation:
inventory, remaining atmospheric concentrations as a function of time, AGWP and AGTP. Such graphical
representations are important, as they allow seeing how the impact evolves over time, and not just at the final
value, which remains dependent on the chosen THI. Graphical representation is indeed an important aspect
of the tool added value. With today’s regulatory changes, industry players tend to think that it is worthwhile
to store carbon in CO -based products, inducing delayed CO emissions. This outcome is mainly explained
2
2
by the choice of a short integration time (T), and to the lack of compatibility between static and dynamic
indicators. The complete graphical visualization shows that this is not the case: with longer THI it is observed
that the dynamic GWP tends towards the static GWP value, while for the GTP temporarily storing carbon in
products to delay emissions contributes to raising temperatures rather than lowering them on the short and
intermediate terms. Such observation is in line with previous work , which shows that carbon storage must
[34]
last at least 1,000 years for the effects on climate change to be beneficial. The analysis of the delay factors β
built here, completes this work, showing that benefits are only possible for GHGs with very long lifetimes,
which are not meant to be stored.