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Life cycle assessment is used to quantify the environmental impact of products and services and forms an important basis for political decisions. However, the necessary data is always difficult to capture completely. A study by the Paul Scherrer Institute PSI now shows that four established hybrid methods can be reduced to just two: a first step towards open-source software that could enable such analyses even without in-depth mathematical knowledge.
Anyone wanting to know how environmentally friendly a car, a piece of cheese, or a wind turbine is has to rely on life cycle assessment (LCA). This method captures the upstream supply chain of a product or service. “Life cycle assessment is ultimately a mathematical method: it is only as good as the data it is based on,” says Michael Weinold, who now works at ETH Zurich. He carried out the research at PSI’s Laboratory for Energy Systems Analysis.
The problem: conventional life cycle assessments cannot capture all processes that contribute to a product’s environmental impact. Where the boundary lines are drawn is decided by those who create the life cycle assessment. Weinold closely examined methods that can close these gaps using data from the global economy. In doing so, he encountered another problem: several methods exist for such “hybrid” life cycle assessments, and the differences between them had not yet been clearly defined.
Together with Guillaume Majeau-Bettez, a professor at the CIRAIG Life Cycle Assessment Research Centre in Canada, Weinold investigated the various methods. In two studies published in the Journal of Industrial Ecology, the researchers demonstrate that four established hybrid methods can be mathematically reduced to just two. They also provide recommendations on which method should be used and when.
The subjective influence
A life cycle assessment is supposed to capture data from a product’s entire life cycle – a process chain that includes not only manufacturing but also raw materials, energy supply, transportation, and many other activities. For example, when it comes to gasoline for a car, it’s not just the combustion that matters, but also the origin of the fuel. “For crude oil, this chain usually ends where the oil is extracted,” says Weinold. “Theoretically, however, research, administration, and real estate projects of the oil companies could also be included.”
Where should the line be drawn? The decision depends on those carrying out the analysis. “This makes the life cycle assessment, partly, a subjective process,” Weinold says. “And this is despite the fact that the procedure is standardised by ISO – where the system boundaries lie is not specified in the standard.”
This subjective component can have direct effects on the economy, for example with the new European Carbon Border Adjustment Mechanism. This scheme is designed to ensure that imported goods are financially charged according to their carbon footprint. This will, for example, make importing steel from China more expensive. “This is of great importance to the economy,” Weinold says. “The calculations must be as objective as possible – because ultimately, we all pay the costs as consumers.”
Combining detailed knowledge and completeness
The solution: combining detailed data on production processes with global economic data. This information is captured in so-called input-output tables. They show how economic sectors are interconnected and what the resulting environmental impacts are. The tables show, for example, how much money the US aviation industry spends on steel. If the CO₂ emissions from steel production are also known, it is possible to calculate how much of this can be attributed to aviation.
Methods that combine classic process data with input-output tables for the economy are called hybrid life cycle assessments (HLCAs). “The economic tables are, by definition, complete,” says Weinold. “Therefore with hybrid life cycle assessments, there’s no need to draw an arbitrary line any more.”
Just two methods instead of four
Since the 1970s, researchers have been developing various methods for creating hybrid life cycle assessments. “So far, four main methods and several variants thereof have been scientifically recognised,” Weinold explains. In a complex research project, he analysed the different procedures and ultimately was able to show that all of these methods can be mathematically reduced to two.
“That was no simple proof,” Weinold recalls. The authors of one of the four main methods were initially skeptical and requested additional calculations for various special cases. In the end, it turned out that the differently formulated methods are in agreement mathematically.
The two remaining methods differ in their complexity. In the simpler, “tiered HLCA” approach, the classic process assessment is supplemented with data from input-output tables. For example, in the life cycle assessment of cheese, specific data such as milk quantity or electricity consumption are used. Where there is a lack of such data, average data from the dairy sector is used. “This method is suitable for products whose production volumes are small in the overall economic context, such as Swiss watches,” Weinold says. “For processes that are relevant to the overall economy, the second method must be applied.”
Data flowing in two directions
In this so-called “integrated HLCA approach,” data can flow not only from the economic table into the process chain but also back again, which necessitates a reclassification of economic sectors.
Weinold explains what this means using the example of the expansion of wind energy in Switzerland: a pilot project with ten wind turbines has little impact on the nationwide energy system – a case for the tiered hybrid life cycle assessment. However, if one wants to analyse a scenario in which 20 percent of Swiss electricity production is covered by wind power, we are all involved as electricity consumers. “Then the integrated method is needed,” Weinold says.
Now Weinold’s findings are to be put into practice: the goal is to develop software for creating hybrid life cycle assessments that can be used even without in-depth mathematical knowledge. The model is Brightway, PSI-developed open-source software for traditional life cycle assessments, which is now one of the most widely used tools in this field.
Text: Barbara Vonarburg
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About PSI
The Paul Scherrer Institute PSI is the largest research institute for natural and engineering sciences in Switzerland. It is the central location of Switzerland’s large research facilities, available to both the scientific community and industry. Its research spans future technologies, energy and climate, health innovation and fundamentals of nature. The annual budget is CHF 450 million. PSI employs 2300 people; around a quarter of these are postdoctoral researchers, PhD students or apprentices. PSI is part of the ETH Domain, which also includes ETH Zurich and ETH Lausanne, as well as the other federal research institutes Empa, Eawag and WSL.
Dr. Michael Weinold
michael.weinold@psi.ch
[German, English]
Prof. Dr. Russell McKenna
PSI Center for Energy and Environmental Sciences
Paul Scherrer Institute PSI
+41 56 310 23 01
russell.mckenna@psi.ch
[English]
Mathematical Unification of Methods for Hybrid Life Cycle Assessment
Weinold MP, Majeau-Bettez G.
Journal of Industrial Ecology, 07.11.2026
DOI: 10.1007/s44498-026-00187-w
Critical analysis of the path-exchange method for hybrid life cycle assessment
Weinold MP, Majeau-Bettez G.
Journal of Industrial Ecology, 01.04.2026
DOI: https://doi.org/10.1007/s44498-026-00023-1
https://www.psi.ch/en/news/media-releases/making-life-cycle-assessment-more-accu... - Media Release Paul Scherrer Institute PSI
https://docs.brightway.dev/en/latest/ - Link zur am PSI entwickelten Open-Source-Software Brightway
“A life cycle assessment is ultimately a mathematical method: it is only as good as the data it is b ...
Quelle: Vanessa Döringer
Copyright: Vanessa Döringer/ecoinvent
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“A life cycle assessment is ultimately a mathematical method: it is only as good as the data it is b ...
Quelle: Vanessa Döringer
Copyright: Vanessa Döringer/ecoinvent
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