Page 51 - 2417

Page 4 of 22 François et al. Carbon Footprints 2026, 5, 22

time-horizon limitations as GWP [18,19] . Additionally, neither approach guarantees the existence of a
mathematical consistency between the static indicators of the background system and the dynamic indicators
of the foreground system. Other existing climate indicators do not rely on fixed time horizons or a reference
gas - such as the integrated global mean temperature change (iGMTC), the amplitude of the temperature
change (GMTCmax), the ΔT or the ΔT long-term - and therefore provide unbiased metrics of climate change,
peak
but their applications require a fully dynamic inventory [20,21] .

The goal of this research is to provide a user-friendly method enabling practitioners to conduct partially
dynamic LCAs for climate change impact based on EPDs, making it accessible to a wider range of
stakeholders. Beyond operational simplicity, the contribution of this work also lies in establishing analytical
coefficients that can be applied directly to static characterization factors to obtain their dynamic
counterparts. Because these coefficients depend on a consistent alignment of time horizons between static
and dynamic formulations, the method explicitly derives and formalizes the required compatibility
conditions. Although developed primarily for GWP - the only climate change indicator currently reported in
EPDs - the approach is extended to GTP to anticipate potential shifts in climate policy and impact
assessment practice.

The remainder of this article is structured as follows. Section 2 introduces the climate change modelling
principles underlying GWP and GTP indicators, including the definition of main time horizons. Section 3
derives mathematical expressions of so-called “delay factors” - coefficients that depend on the temporal
distribution of emissions and that scale the static characterization factor to obtain the dynamic one for the
same system. In parallel, their behaviors as a function of their input parameters are analyzed. Section 4
presents a simple application of the method, together with its associated worksheet-based tool , using EPD
[22]
data within the framework of the French RE2020 regulation. Section 5 discusses the physical meaning of
delay factors along with their operability and reliability.

PRINCIPLES OF CLIMATE CHANGE INDICATOR AND MAIN DYNAMIC METHODS
This section presents the principles and main equations, introducing unified notations and symbols. To
avoid repetition and verbosity in the text, all notations and their units are detailed in the Supplementary
Table 1.

General principles of climate change metrics modeling
Assessing and modelling the potential impacts of greenhouse gases (GHG) emissions on climate change rely
on a complex methodological process starting with the inventory of atmospheric GHG emissions. Higher
atmospheric concentrations of GHGs lead to stronger radiative forcing. Changes in energy intake changes
atmospheric temperature which in return affects climate conditions such as terrestrial and ocean
temperatures, or the sea level. Finally, these new climate conditions create potential damages on human
health, ecosystem quality or natural resources . Throughout this cause-effect chain, many indicators can be
[23]
suggested to represent climate change: from emissions accounting to damage indicators, including radiative
forcing, temperature, sea level or even precipitation metrics. The indicators used can be differentiated
according to their absolute or relative nature, or according to their underlying temporal approach -
instantaneous or cumulative.

The following equations are those provided by the IPCC. For the reader's convenience, the meaning and
units are fully detailed in the Supplementary Table 1.

Both GWP and GTP indicators are based on the Absolute Global Forcing Potential (AGFP). It represents the
amount of radiative power received by 1 m of Earth surface due to a pulse increase of 1 kg of a given GHG.
2
The AGFP is an instantaneous metric of the radiative forcing: