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François et al. Carbon Footprints 2026, 5, 22 Page 15 of 22

system is chosen for heating energy. Table 3 presents their main characteristics together with their
[32]
GWP100 values, as well as the associated discrete event time points (i.e., installation, replacement, disposal
and energy consumption). Using these data, it is possible to reconstruct a partially dynamic inventory in
accordance with the rules set forth by RE2020 [11,30] and explained below.

For materials with a long lifespan (greater than or equal to 50 years), the value of module A should be
reported at time zero, the value of Module B should be uniformly distributed over the entire lifespan of the
building, and the value of Module C should be reported at the end of the building’s life. The impact values
are multiplied by the amount of flow necessary for the building. The wall surface is set at 50 m in this
2
example.

For materials with a short lifespan (less than 50 years), the value of module A should be reported at time
zero, the value of module C should be reported at time 50, and the total value of modules A+B+C should be
reported at each time the component is renewed, defined by its service life duration. The impact values are
multiplied by the amount of flow necessary for the building. The area of the walls to be covered is set at 35
m in this example.
2
For energy, the estimated annual consumption, as determined by the thermal model of the regulation, is
multiplied by the total unit indicator of modules A+B+C and reported each year. In this example, we assume
an annual energy consumption of 2,500 kWh/year.

The dynamic inventory table resulting from this example is provided in the Supplementary Table 2.

This inventory is obtained by distributing static GWP100 indicator of background products over time
according to timeline scenarios described in Table 3. This timeline distribution of static GWP100 is assumed
to be equivalent to CO emissions. This is a strong assumption, as not all GHGs have the same degradation
2
curves and therefore do not have the same effects on climate change over time. However, this assumption
was considered acceptable by legislators, on the basis that CO is generally the main GHG emitted.
2

RESULTS
Results for RE2020 are calculated using the official method provided in an attached file. Results for the
present article are obtained by using the worksheet-based tool provided along with this article , and the
[22]
instruction manual is provided in the Supplementary Part 5, with illustrations in Supplementary Figures
5-18. Results are all detailed in the Supplementary Figures 19-22.

The static GWP100 indicator was equal to 6,963 kg CO eq for that case study, of which 12% originated from
2
the wood-frame wall, 3% from the wallpaper, 55% from the wood pellets, and 30% from to the foreground
emissions. The dynamic model for the RE2020 calculated gwp100 = 5,172 kg CO eq (thus a 26% reduction
2
compared to static indicator), whereas the present model obtained 6,001 kg CO eq (thus a 13,8% reduction
2
compared to static indicator). Both dynamic methods use the same approach with delay factors from
respectively the RE2020 regulation or from our method, illustrated in Figure 5 with the same THI of 100
[11]
years, associated with the static GWP100 indicators. The use of nondimensional delay factors ensures
comparability of results with the same reference gas, CO , and same integration period, 100 years. More than
2
the results themselves, which have limited significance in this context since the example provided is
simplistic and only intended to illustrate the approach, the dynamic gwp100 indicator obtained with the
present method is still higher than the one that would be obtained using the RE2020 model. This difference is
explained by two reasons: the compatibility criterion and the account of different GHGs in the foreground
system.