The data gap

The 2023 DID list is, in practice, a hybrid system. Of its 265 entries, about 40 % (105 entries) point to a single, specific substance — for example, DID 2022 "C16–18 Fatty acid methyl Ester Sulphonate" maps uniquely to CAS 3076-26-4. The remainder describe chemical families of varying breadth: small groups of 2–5 CAS, medium groups of 6–10, and a tail of broad families covering 11 or more CAS each. A further 33 entries are too generic to be mapped to any specific CAS at all — ethoxylation series (EO 3–12), carbon-chain ranges (C14–20), or UVCB substances whose composition is defined by a process rather than a structure..

This distribution matters. When a DID already points to one CAS, a formulator knows exactly which environmental profile applies. When a DID covers twenty or more CAS, the choice becomes a judgment call — and two evaluators working in good faith can reach different conclusions. The exact choice changes the calculated Critical Dilution Volume (CDV) of the final product: a borderline CAS assigned to a different DID means different Toxicity Factors (TF) and Degradation Factors (DF), which in turn can decide whether a formulation passes the Ecolabel threshold or not.

Why it matters

This is not a documentation issue. It is a reproducibility issue. Two evaluators working on the same formulation, in good faith, can reach different CDV values because they make different CAS→DID attributions. For the industry, that means regulatory uncertainty. For the Ecolabel scheme itself, it means the scientific rigour of the underlying calculation is weakened by an arbitrary upstream decision.

The ambiguity does not stop at the Ecolabel itself. Any tool that uses the DID list as its environmental reference — whether it is an industry screening workflow, a consultancy spreadsheet, or a software platform — inherits the same upstream uncertainty. You cannot build reliable sustainability assessments on an ambiguous reference dataset.

Our approach

We rebuilt the mapping from scratch, using five independent sources and documenting every attribution:

• A.I.S.E. ESC Tool workbook — the industry-maintained reference, built on expert chemist consensus.
• HERA Risk Assessments — 40 technical reports covering the most-used household detergent substances.
• UBA Surfactants Suspect List (2018) — systematic CAS/name catalogue from the German Environment Agency, enriched with DTXSIDs.
• Explicit CAS numbers and IUPAC names in the DID list itself — sometimes the information is right there, just not machine-readable.
• OECD chemical-category tables and a web-assisted search — targeted queries against ECHA, PubChem and NIST, with every attributed CAS then verified against the ECHA published-substances database (EchaChem)and recorded with a direct link.

Every (DID, CAS) couple was then scored for reliability on a five-level scale — from very high (multi-source agreement with validated chemical structure) down to flagged (semantic inconsistency detected and awaiting expert review).

Concrete results

• 1,276 DID↔CAS couples mapped across the 265 DID entries, spanning 932 unique substances.
• At least one CAS attached to 232 of the 265 entries (87.5 %).
• 6.4 % of couples flagged for expert review — mismatches the automated pipeline accepted but structural validation caught.
• 33 DID entries classified as non-mappable by design — carbon-chain ranges (C14–20), ethoxylation series (EO 3–12), UVCB substances whose composition is too broad for a single-CAS attribution.

Every couple is traceable: anyone can re-open the dataset, see which of the sources supports a given attribution, follow the EchaChem link to the substance record, and audit the reasoning.

The policy implication

Here is the real lesson. Even with the most advanced tools available today, mapping a specific CAS to a family-based DID entry remains a perilous exercise. The ambiguity is not in the mapping tool — it is in the DID list itself.

The pragmatic recommendation is straightforward: the next revision of the DID list should be rebuilt starting from the CAS level, not from chemical families. And the good news is that about 40 % of entries already are CAS-level — the refactoring is not a methodological rupture, it is the extension of an existing practice to the whole list. A substance-first architecture — one DID per defined CAS, with families emerging as groupings rather than as foundations — would eliminate the reproducibility problem at its source. It would also give the European Commission's own ecodesign toolbox a solid footing, which is essential if these tools are to be accepted by the industry they target.

This is not a rebuttal of the DID list. It is a proposal for its evolution, consistent with the data-quality principles that the SSbD framework is built on.

What comes next

The complete dataset, the scoring methodology and the consolidation pipeline are described in a manuscript now submitted for peer review to Integrated Environmental Assessment and Management (IEAM). The mapping is also the substance backbone of EcoCalc.eu, the ecodesign platform we are finalizing for formulators, regulatory consultants and competent bodies — where the reliability score is surfaced directly to the user, not buried in a spreadsheet.

A companion paper, also submitted to IEAM, takes the next step: once every DID is traceable to specific CAS numbers, it becomes possible to recompute the DID-list Toxicity Factors (TF) and Degradation Factors (DF) per individual substance, traceably, from the same public data that underpin the EU Product Environmental Footprint (the EF Ecotox Explorer freshwater dataset and the HESI EnviroTox database). That study finds that only about half of the DID list can be independently reconstructed from current public data — a transparency finding made possible precisely by the CAS-level traceability introduced in the present work.

We welcome feedback — from cosmetic, detergent and paint formulators who have lived this pain, from evaluators in competent bodies, and from colleagues at the JRC and A.I.S.E. who have worked on the DID list over the years. Rebuilding a shared reference is everyone's job.

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About the author. Erwan Saouter is the founder of Net-Zero Impact SAS and a registered A.I.S.E. Charter for Sustainable Cleaning consultant. He has contributed to the JRC Product Environmental Footprint programme, acts as an evaluator for Horizon Europe SSbD calls, and is the developer of the EcoCalc.eu platform for chemical sustainability assessment..

Contact: saouter@net-zero-impact.eu — ssbd-expert.eu/insights