DOI: 10.5281/zenodo.18200775
title: IMPACT World+ / a globally regionalized method for life cycle impact assessment

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Warning: There is a mistake in the climate change, ecosystem quality, marine ecosystem indicators. A v2.2.1 will be available soon.

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IMPACT World+ is a life cycle impact assessment method which characterizes thousands of substances spanning across various compartments and sub-compartments of the environment. It differentiates 19 impact categories at midpoint level and 36 impact categories at damage level. For more information on IW+, refer to our website and scientific article. For information on the updates of IMPACT World+, you can register to the newsletter of CIRAIG.

The v2.2 update radically changes the contributions to the ecosystem quality damage indicators as well as introduces new resources indicators based on the disipation of resources and not the extraction.

IMPACT World+ comes in three interpretation levels: midpoint, expert and footprint. You can find explanations for these three interpretation levels here.

The expert and midpoint versions of IMPACT World+ also come with two different implementations regarding how to account for biogenic carbon. One with the traditional biogenic carbon neutrality approach (e.g., where biogenic carbon dioxide is set at 0 and biogenic methane is set at 27kgCO2eq for GWP100) and one including the uptake of biogenic carbon dioxide, where the release of biogenic carbon is therefore set at the same CFs as fossil carbon, but the uptake is with a negative sign, i.e., a -1/+1 approach for biogenic carbon (look for the files marked “(incl. CO2 uptake)”).

While we provide the -/+1 approach, we must make it clear to the users that this approach is heavily dependent on the quality of the inventory you are using, and that there are still issues currently with the LCI databases (even in ecoinvent 3.10). Furthermore, if you are using this approach, you either MUST adopt a cradle-to-grave approach to both account for the uptake and release of biogenic carbon (otherwise you will only account for the uptake of the carbon and have skewed results) or if you adopt a cradle-to-gate approach because you need to provide results to someone downstream of your supply chain you MUST communicate with that downstream user to tell them that they should account for the release of biogenic carbon in a -1/+1 approach also, otherwise, you and your downstream user will double count the benefits of using biogenic products, which is incorrect. This is especially true is the case of food products where the carbon emissions post consumption are typically not included in the inventories, which could result in a substantial under estimation of the impacts of this product over its life cycle.

Description of the files

- The dev file is a file useful for developers and maintainers of databases/datasets who wish to link IW+ to their databases/datasets. It regroups all existing characterization factors of the IW+ LCIA method in an Excel format, using the terminology of IW+.

- The "ecoinvent" files are Excel files matching with "pure" ecoinvent and its flow name terminology (as in unaltered by various software). This is useful if you are using ecoinvent outside of LCA software.

- The exiobase file links IW+ to the Exiobase GMRIO database. Once the file is read through pandas (pandas.read_excel()), the resulting matrix can directly be multiplied to the environmental extensions of exiobase (S, F or F_Y if using the pymrio package). Note that since Exiobase changed its environmental flows with the introduction of their v3.9, there are two versions of files for exiobase: 3.8.2 and before and 3.9 and after.

- The openLCA files can be directly imported in the openLCA software as a JSON-LD file.

- The SimaPro files can be directly imported in the SimaPro software as a CSV file.

- The brightway2 files are ecoinvent-version dependent, so you need to select the correct file to work with the correct version of ecoinvent. Else, some of the ecoinvent flows which name did change in between versions of ecoinvent would not be characterized, leading to underestimated results. To import a file, you need to pass through brightway2 itself (it cannot be done through the activity-browser for now). The function to import a .bw2package file is bw2.BW2Package.import_file().

- Similarly to files for brightway2, there are files for brightway2.5, since some of the arguments of the Method object changed between bw2 and bw2.5.

- Finally, the source file regroups all the native information used by IW+ to derive the characterization factors, all the mappings that IW+ uses to conenct characterization models to the IW+ nomenclature, as well as many of the maps to calculate our spatialized CFs. This file is primarily useful for the IW+ internal team. It is provided for transparency, as well as for curious users or users who wish to generate all these files themselves through the open-access code of IW+. 

New indicators

The two indicators "Mineral resource use" and "Fossil and nuclear energy use" have been deleted and were replaced by two new indicators on resources. Both of these indicators come from the work of Greffe (2025) « Développement d'un modèle de caractérisation des impacts du cycle de vie de la dissipation des ressources abiotiques » Thèse. Montréal (Québec), Université du Québec à Montréal, Doctorat en sciences de l'environnement. The thesis is only available in French, however the chapter 6 (starting page 138) presenting the two indicators is in English and the documentation on our Github summarizes the core ideas. These two new categories shift from a mindset of assessing the potential impacts of extraction of resources (which is still used by many methods) to assessing the potential impacts of dissipation of resources.

Note that current LCI datasets do not include dissipation flows. We thus had to estimate these dissipation flows through proxies with emissions in the environment of components embedding resources. Since not all dissipative flows are reported in life cycle inventory datasets, the potential impact score of a system of products obtained with those methods is potentially underestimated. We recommend users to go through the documentation of these two new indicators to really understand their ins and outs. These constitute exploratory indicators, not due to the quality of the research, but simply due to the lack of reporting dissipation flows in LCI datasets. The IMPACT World+ team highlights this lack as a clear limitation of a paradigm shift for resource assessment towards dissipation, for which interest is growing rapidly.

- Resources Services Loss

This first category assesses the potential deficit of resources when looking at the future usage of resources in the next 100 years. According to the model of Greffe (2025), a marginal dissipative flow of only three resources may lead to a potential deficit under a business-as-usual trajectory: copper, cobalt and lithium. Thus, only elementary flows containing those three elements have are characterized by this indicator.

- Resources Services Loss (adaptation)

This second category assesses the additional effort to extract resources, resulting from the adaptation to a marginal dissipative flow of resources. This additional cost is assessed in terms of MJ, i.e., the additional energy required to extract the resource, because of dissipation.

Updated indicators

- Climate change, ecosystem quality (damage indicator)

The update is double as both the fate factor and the effect of factors were updated. The fate factor is updated to exactly reflect that AGTP values available in the IPCC AR6. The calculation of the effect factor is now based on the work of Trisos (2020) (https://doi.org/10.1038/s41586-020-2189-9), while taking advantage of the work of Iordan-Vasquez (2023) (https://doi.org/10.1016/j.resconrec.2023.107159). One of the biggest consequences of this change is the introduction of marine species into the covered taxa. As a result, these damage indicators have been split between indicators assessing the effects of climate change on terrestrial species and other indicators assessing the effects of climate change on marine species. These indicators can be added to calculate the overall effets of climate change on ecosystem quality. This update dramatically increases the effect factor, when compared to the one historically used in previous versions of IW+. The new effect factor (combining both terrestrial and marine species) is 13 times higher than the previous CF. As a result, climate change, is now the categrory that contributes the most  to the ecosystem quality damage indicator, for virtually all human activities. We are aware that such a drastic change warrants doubts and interrogations. The complete methodology is available on our Github and all the necessary data to replicate our CFs are available in the source database, in order to ensure complete transparency in our methodology.

- Land occupation/transformation

The land indicators have been updated by relying on the local CFs of Chaudhary (2015) (http://dx.doi.org/10.1021/acs.est.5b02507) instead of de Baan 2012. Moreover, maps were updated to offer better precision on geographical information and cover all geographies of ecoinvent. Detailed information on this update is available on our Github.

- Climate change, human health (damage indicators)

With the update of the fate factor to match with IPCC AR6 values (see section on climate change, ecosystem quality), the CFs for the "climate change, human health, short term" and "climate change, human health, long term" indicators were slightly decreased overall.

- Acidification and eutrophication indicators

The maps to generate these indicators have been updated and now cover more of the new geographies from the ecoinvent database (such as the different states of the US or regions in Australia). This update slightly changed the overall global values, but drastically corrected some of the region-specific CFs.

- Plastics physical effect on biota

This indicator has been renamed to "Physical effects on biota". The reason being that we now introduced CFs for non-plastic fibers, namely: cotton, linen, viscose, rayon, lyocell and modal. These CFs are still based on the work of the MariLCA group (https://doi.org/10.1093/inteam/vjag007).

Corrections

In this section we only provide information on the major corrections that were made. For a full report of all the changes please refer to our Github.

- Water scarcity

The global flow for water scarcity was using the December value (38.5 m3 world-eq) instead of using the annual value (39.2 m3 world-eq). The correction is minor as it only concerns the global water flow (the many region-specific water flows were correct) and the switched values are very close.

- Fisheries

Bycatches elementary flows (e.g., Pelagic fish, discarded) were linked to the wrong compartment. There were linked to the resource (or raw) compartment while the bycatches are considered as emissions by ecoinvent, which means they are actually linked to water emissions.

- Marine & terrestrial ecotoxicity

Nearly all CFs for these two categories had no "unspecified" sub-compartment equivalents, resulting in a drastic underestimation of the impact. Their contribution to the ecosystem quality damage indicator still remains low, even after the correction.