The DPP and life-cycle assessment: measuring environmental footprint

DPP life cycle assessment: integrating environmental measurement into product information systems

The Digital Product Passport represents a fundamental shift in how manufacturers, regulators, and consumers approach environmental accountability across supply chains. At its core, a DPP is a digital information system that travels with a product throughout its lifecycle, aggregating data on materials, production processes, transportation, use phase, and end-of-life management. When integrated with Life Cycle Assessment (LCA) methodologies, DPPs create a standardized mechanism for measuring, verifying, and communicating a product’s environmental footprint—moving environmental claims from marketing assertions to auditable, data-driven evidence.

Life Cycle Assessment has been the scientific standard for quantifying environmental impacts since the 1990s, but its deployment has been fragmented. Traditional LCA studies are expensive, time-consuming, and often completed months or years after production decisions are made. Morganti et al. (2024) demonstrate how semantic data-driven frameworks can fundamentally change this dynamic by embedding LCA logic directly into digital product information systems. Their research on modular curtain wall systems shows that when DPP architectures are designed to capture production data at source—material composition, energy inputs, waste streams, supplier locations—the system can automatically calculate and update environmental metrics as products move through their lifecycle. This automation addresses a critical barrier: most manufacturers lack real-time visibility into their environmental performance, making it impossible to optimize for sustainability during design and production phases.

The structural requirements for LCA-integrated DPPs

Building a DPP that reliably measures environmental footprint requires three interdependent technical and organizational capabilities. First, the system must capture primary data at the point of production rather than relying on industry-average assumptions or secondary datasets. Heeß et al. (2024) identify this requirement in their analysis of hydrogen supply chains, where carbon intensity varies dramatically by production method and energy source. They demonstrate that effective DPPs for low-carbon markets demand comprehensive automated data collection mechanisms that eliminate manual reporting, which introduces both error and opportunity for misrepresentation. A hydrogen producer using renewable electricity has a fundamentally different environmental profile than one using fossil fuels, and this distinction must be embedded in the product data itself, not derived post-hoc through audits.

Second, DPP architectures must ensure data interoperability across multiple actors in the supply chain. Voulgaridis et al. (2024) develop a technological framework highlighting how DPPs function as enablers of the digital circular economy by establishing standardized formats and protocols that allow suppliers, manufacturers, logistics providers, and retailers to contribute verified environmental data without requiring proprietary integrations. This interoperability challenge is substantial: a garment manufacturer may source materials from ten different suppliers across five countries, each using different measurement systems and data formats. The DPP must normalize these inputs into a coherent environmental profile. Standards such as GS1 Digital Link and EPCIS 2.0 provide foundational infrastructure, but their application to LCA-specific data fields—embodied carbon per kilogram, water consumption, chemical toxicity categories, or end-of-life recyclability rates—requires sector-specific implementation guidance.

Third, the system architecture must balance transparency with privacy protection and competitive confidentiality. Heeß et al. (2024) emphasize that stakeholders across supply chains harbor legitimate concerns about data exposure when environmental metrics are disclosed publicly. A manufacturer may be willing to report total carbon emissions but reluctant to reveal specific process details or energy costs to competitors. Effective DPPs therefore employ decentralized verification mechanisms where data is validated by trusted intermediaries without full disclosure to end-users. A third-party auditor might verify that a carbon intensity claim is accurate without publishing the underlying production parameters. This structural approach aligns with regulatory expectations under the EU Data Act, which requires that data portability obligations do not compromise legitimate confidentiality interests.

Sectoral adaptation and implementation pathways

DPP life cycle assessment is not a one-size-fits-all proposition. Voulgaridis et al. (2024) propose a sector-adaptable framework recognizing that environmental hotspots differ substantially across industries. In apparel and footwear, water consumption and chemical use dominate environmental profiles; in electronics, embodied energy and rare material extraction are critical; in construction, the use phase (heating, cooling) may exceed production impacts by orders of magnitude. Effective DPPs therefore require customized data schemas and measurement boundaries tailored to sector-specific regulatory requirements and stakeholder priorities.

Morganti et al. (2024) provide a concrete implementation example in the building envelope sector, demonstrating how a semantic data framework can automatically aggregate environmental data from modular component suppliers and map it to standardized LCA impact categories. In their case study, the DPP captures material composition and weight for each curtain wall module, cross-references this against Environmental Product Declaration (EPD) databases, and calculates indicators including Global Warming Potential, water consumption, and end-of-life recyclability. As modules are assembled into larger systems, the DPP recursively aggregates impacts, providing project-level environmental metrics. Critically, this automation occurs in real-time, allowing designers to compare environmental performance of different material or supplier options before finalizing procurement decisions.

For electronics and other complex products, Psarommatis and May (2024) develop a comprehensive implementation template demonstrating how DPPs can enhance supply chain transparency while enabling sustainable manufacturing practices. Their framework addresses how environmental data flows upstream from component manufacturers to final assembly, and downstream through distribution and retail to consumers and repair services. The template clarifies responsibility boundaries—which party in the supply chain measures or estimates which impacts—and specifies data quality requirements for each LCA phase.

Integration with circular economy strategies

The fundamental value of DPP-integrated LCA emerges when environmental measurement is connected to circular economy design decisions. Voulgaridis et al. (2024) position DPPs as core enablers of the digital circular economy, noting that lifecycle traceability directly supports three circular strategies: design for disassembly, material recovery optimization, and remanufacturing. When a DPP accurately documents material composition, material grades, and assembly methods, end-of-life processors can make informed decisions about which components warrant recovery versus recycling versus disposal. A printed circuit board assembly documented in a DPP might contain rare earth elements worth recovering, but only if their location and concentration are specified precisely.

This circular integration also creates feedback loops that drive continuous environmental improvement. Morganti et al. (2024) demonstrate how LCA data embedded in DPPs can reveal whether design modifications reduce impacts. If a curtain wall manufacturer tests a new aluminum alloy with lower embodied carbon but higher recyclability, the DPP framework can automatically update impact calculations across all projects using that material. Over time, these incremental optimizations compound into substantial environmental gains across entire product families.

Heeß et al. (2024) extend this logic to emerging markets, showing how DPPs create the foundation for low-carbon certification schemes. In hydrogen supply chains, a producer operating with 100% renewable electricity can document this through automated energy data feeds integrated into the DPP, enabling buyers to identify and preferentially source low-carbon hydrogen. Without DPP-enabled verification, such claims rely on periodic third-party audits vulnerable to gaming and misrepresentation. With DPPs, verification becomes continuous and tamper-evident through distributed ledger or cryptographic techniques.

Regulatory alignment and market-driven adoption

DPP life cycle assessment gains regulatory urgency through emerging EU frameworks. The Digital Product Passport requirements under the ESPR (Ecodesign for Sustainable Products Regulation) mandate that certain product categories document environmental information in standardized formats accessible to consumers and regulators. The EU Data Act creates additional requirements for data access and portability that affect how environmental data flows through supply chains and is made available to third-party sustainability assessment services. When properly architected, DPP systems satisfy these regulatory mandates while simultaneously generating the primary data required for accurate LCA.

Market adoption accelerates when DPPs reduce costs and complexity for all parties. Psarommatis and May (2024) document how streamlined DPP implementation reduces the administrative burden of LCA compared to traditional approaches. Rather than hiring specialized consultants for each LCA study, manufacturers integrate environmental data capture into existing ERP and production planning systems. Suppliers report environmental metrics once in standardized formats, which multiple customers can access and incorporate into their own LCA calculations without re-collecting primary data. This efficiency gain addresses a longstanding barrier to LCA adoption: the expense of detailed measurement for small and medium enterprises.

FAQ

How does a DPP-integrated LCA differ from traditional Life Cycle Assessment studies?

Traditional LCA is typically a retrospective study conducted after production, relying on average industry data and estimation for many lifecycle stages. DPP-integrated LCA captures primary data at source in real-time, automatically calculates environmental metrics as the product moves through its lifecycle, and enables continuous optimization rather than one-time reporting. Morganti et al. (2024) demonstrate this allows designers to compare environmental options before finalizing decisions, rather than discovering impacts months after production.

What data governance challenges must DPP systems overcome to ensure environmental claims are trustworthy?

Heeß et al. (2024) identify three core challenges: securing primary data at source to eliminate manipulation, establishing decentralized verification mechanisms that validate claims without exposing competitive secrets, and ensuring interoperability across supply chain actors using different systems. Balancing transparency with confidentiality requires architectural choices like third-party audit intermediaries and cryptographic verification rather than public disclosure of all parameters.

Can DPP life cycle assessment frameworks work across different industry sectors?

Yes, but with sector-specific customization. Voulgaridis et al. (2024) propose an adaptable framework recognizing that environmental hotspots differ—water for apparel, energy for electronics, use-phase impacts for buildings. Effective implementation requires tailored data schemas and measurement boundaries reflecting each sector’s regulatory requirements and stakeholder priorities, as demonstrated in construction (Morganti et al., 2024) and hydrogen markets (Heeß et al., 2024).

References

• Morganti L.; Esnarrizaga P.E.; Pracucci A.; Zaffagnini T.; Cortes V.G.; Rudenå A.; Brunklaus B.; Larraz J.A. (2024). Data-driven and LCA-based Framework for environmental and circular assessment of Modular Curtain Walls. Journal of Facade Design and Engineering. https://doi.org/10.47982/jfde.2024.305
• Heeß P.; Rockstuhl J.; Körner M.-F.; Strüker J. (2024). Enhancing trust in global supply chains: Conceptualizing Digital Product Passports for a low-carbon hydrogen market. Electronic Markets. https://doi.org/10.1007/s12525-024-00690-7
• Voulgaridis K.; Lagkas T.; Angelopoulos C.M.; Boulogeorgos A.-A.A.; Argyriou V.; Sarigiannidis P. (2024). Digital product passports as enablers of digital circular economy: a framework based on technological perspective. Telecommunication Systems. https://doi.org/10.1007/s11235-024-01104-x
• Psarommatis F.; May G. (2024). Digital Product Passport: A Pathway to Circularity and Sustainability in Modern Manufacturing. Sustainability (Switzerland). https://doi.org/10.3390/su16010396