From marker molecules to chemometric analysis: ISCC working group advances UCO characterisation
Used cooking oil (UCO) is a highly heterogeneous waste and residue material. Its composition varies depending on factors such as the original oil type, cooking conditions, sources, and collection and storage practices.
The growing importance of UCO in renewable fuel markets
In recent years, UCO has become an increasingly important feedstock for the production of renewable fuels. Under the European Union’s Renewable Energy Directive (REDIII), waste and residue-based feedstocks listed in Annex IX can contribute towards renewable energy targets in transport. UCO is one of the most widely used Annex IX Part B feedstocks and plays an important role in supporting the decarbonisation of the transport sector.
At the same time, its global supply chains and its highly variable nature have made UCO a feedstock with elevated integrity risks. Against this background, ISCC initiated the Working Group “Chemical Analytics of Feedstocks” to explore whether chemical analysis could contribute to the characterisation of UCO and provide complementary insights alongside established certification and auditing processes.
From a marker molecule…
Discussions with analytical experts showed at an early stage that a single marker molecule for authentic UCO is unlikely to exist. The work of the group, consisting of representatives from laboratories, Certification Bodies, energy companies, biofuel associations, and other technical experts, therefore began with the central question: How could the term “used” be chemically characterised across multiple parameters?
… to chemometric analysis
During cooking, oils and fats are exposed to heat, oxygen, and water. These processes lead to chemical changes linked to heat stress, oxidation, and hydrolytic degradation. The working group identified five analytical parameters that together help describe these changes and form the basis for a chemometric analysis intended to characterise authentic UCO, regardless of factors such as geographic origin or cooking practices:
- Polymerised Triglycerides (due to heat stress)
- Trans Fatty Acids (due to heat stress)
- FFA/Acid Number (due to hydrolytic degradation)
- Anisidine Value (due to oxidation)
- Peroxide Value (due to oxidation)
Putting the approach to the test
To test this approach, ISCC initiated an international inter-laboratory study. Eighteen UCO samples from five global regions were collected and analysed by nine independent laboratories. The study focused on the five selected parameters and aimed to assess variability in UCO materials, evaluate comparability across laboratories, investigate potential geographical patterns, and explore how analytical data could be used in future assessment approaches.
The results confirmed that UCO remains highly variable. Based on the available dataset, no universal standard values could or should be defined. This finding underlines the complexity of UCO as a waste and residue material and confirms the importance of careful interpretation when using analytical data.
At the same time, the study showed strong comparability between laboratories. Results generated by the participating laboratories were generally consistent, indicating that the selected analytical parameters can be measured in a comparable way across different laboratory settings.
The study did not show clear geographical patterns among the analysed samples. However, differences between household and restaurant UCO became visible.
Exploring statistical screening approaches
The analytical dataset also allowed the working group to explore statistical approaches for evaluating UCO samples, including a preliminary rapid screening method.
Based on the results of the inter-laboratory study, a standard vector reflecting the mean values observed for the five analytical parameters within the dataset was established, together with statistically derived ranges of expected variation. Using a statistical Z-score approach – a method that measures how closely a sample matches the expected analytical profile – the working group explored whether samples align with the UCO dataset or deviate significantly from it.
This work resulted in a preliminary rapid screening tool to help identify samples that may warrant further investigation. Rather than providing a definitive assessment of authenticity, the tool is intended as a risk-indication and screening mechanism based on the combined analytical profile of a sample.
The development of this rapid screening tool represents an important milestone in the working group’s work. At this stage, however, the screening tool is a research outcome of the working group, not embedded in certification processes.
Key takeaways and next steps
Overall, the working group’s findings mark an important step in developing a more science-based understanding of UCO characterisation. They also underline an important principle for future analytical work: before potential irregularities can be assessed, it is necessary to establish what constitutes a plausible analytical profile of authentic UCO. The working group’s results suggest that such an assessment cannot be based on a single marker compound or fixed threshold value. Instead, it requires a plausibility-based evaluation of multiple aggregate parameters, each reflecting characteristic features associated with the material’s “used” nature.
While these findings provide an important foundation, the collection and analysis of additional data will be necessary to further strengthen the scientific basis of this approach. Looking ahead, the working group will therefore continue to expand the dataset, validate the proposed chemometric approach to UCO characterisation, and strengthen the evidence base for its effectiveness. ISCC and the participating experts will also explore potential applications in selected operational processes. In addition, the group will investigate whether similar methodologies could be developed for other waste and residue feedstocks, contributing to more robust feedstock characterisation across certified supply chains.
