Calculating the product carbon footprint: why digital twins are key

Today, there is simply no way for companies to avoid the topic of carbon footprints. Accurate calculations of greenhouse gas emissions in the form of corporate carbon footprints (CCF) and product carbon footprints (PCF) are at the core of crucial sustainability efforts and laws. This is particularly true in the European Union, where the PCF plays a key role in the European Green Deal. The idea behind it: if you want to reduce emissions, you must know where they are generated. Batteries are one of the first product classes to be affected in the EU, where the CO2 footprint of new batteries must be calculated and reported starting in 2025. The question of how exactly to calculate a PCF – and what is needed to do so – has become all the more pressing. Furthermore, reported carbon footprints can be used to set benchmarks for greenhouse gas emissions and to define industry incentives or restrictions.

Simple to explain, complex to calculate

Calculating a complete cradle-to-grave PCF is quickly explained – at least in theory: you take the emissions of all individual product parts throughout their entire life cycle and add them up:

1. Production:

emissions from resource extraction and energy consumption in manufacturing

2. Transport:

emissions for transport routes, both in the supply chain and during sales

3. Use:

emissions from energy consumption during use and abrasion

4. End-of-life:

emissions for return transport, recovery, and scrapping

In contrast to this complete calculation, cradle-to-gate approaches only consider emissions up to the products’ point of sale. This also includes the PCF adopted by the EU for batteries, which excludes the use phase from the calculation.

But whether cradle-to-gate or cradle-to-grave, the actual calculation of the PCF remains highly complex. Almost every product consists of many individual components, which in turn consist of hundreds or thousands of small individual parts such as screws. At the same time, no single producer can measure all emissions alone: scope 3 emissions from external sources (such as customer use, supply chain, and transport) account for around 80% of the average PCF. The PCF therefore requires digitalization and transparency along the entire life cycle, including the supply chain – where smaller companies often still have some catching up to do.

Data homogenization thanks to digital twins

To calculate the emissions, or at least estimate them accurately based on average values after the products leave the factory gates, one thing is decisive: a large amount of available data. This data must be collected for each of the thousands of product components and shared with the producer. This is where digital twins come into play. They accompany every product part, no matter how small, combining and storing all product and emission data throughout its entire life cycle. Semantic data homogenization is of crucial importance here: all digital twins must use the same semantics across all suppliers and companies, i.e. contextualize data meaningfully and store it with associated aspects.

These aspects describe the technical context of the data, i.e. which source it comes from, when it was collected, and which measuring unit applies. This is the only way to ensure that the data retains its meaning when it is exchanged between companies. Industry standards and open-source approaches are essential, as they allow all companies to work on the same basis. They also make it easier for small and medium-sized companies to enter the world of data homogenization in a non-invasive way.

Open source and interoperability: practical solutions

With the Bosch Semantic Stack, Bosch Connected Industry offers a portfolio for precisely this application. It includes the Digital Twin Registry for the easy creation and management of tens of thousands of twins, and the Aspect Model Catalog to map their aspects. The Bosch Semantic Stack uses open source solutions and relies on interoperability of all digital twins to provide the basis for participating in data ecosystems such as Catena-X. These in turn usually provide central specifications for calculating the PCF, simplifying the process for all companies and making it comparable.

An example from Bosch Rexroth illustrates how Bosch Semantic Stack can be used to calculate the PCF in practice. This Bosch division manufactures a wide variety of industrial equipment in batch sizes right down to one. The PLM portal consolidates all data of these products using digital twins and Bosch Semantic Stack. Further use cases, including the PCF, can be added to the portal in next to no time. The CO2 footprints can be determined as soon as all the necessary data for the calculation is available. In the future, customers will be able to conveniently access the PCF data of components that they have installed in their systems via the respective digital twin and use it for their own PCF calculation.

Next issue: the digital battery passport

For battery manufacturers in particular, the Product Carbon Footprint is not the only pressing sustainability use case. The digital product passport will become mandatory for them in 2027. That's why we're dedicating our next issue of Sustainability Insights entirely to the digital battery passport: what it is, how it can be implemented, and what role digital twins will play in it. Stay tuned!