Methodology for PCF Calculations of Lubricants, Greases and other Specialties
5 Sensitivity analysis, quality checks and interpretation
The results of the PCF calculation can be analyzed in terms of the goal and scope definition by identifying key aspects of the PCF results using various techniques including:
Contribution analysis: aims to identify significant issues in the PCF results by examining individual life cycle stages, processes and key flows.
Completeness check: ensures that all relevant information and data requirements specified in the goal and scope of the PCF calculation are available and complete.
Consistency check: evaluates the consistency of assumptions, methods and data with the goal and scope of the PCF calculation.
Quality assessment: involves validating the collected data for the PCF calculation by checking against scientific laws, comparing with other data sources and assessing the suitability of secondary data in terms of technology and geography.
Sensitivity analysis: to ensure the results are robust, sensitivity analysis shall be conducted using various modeling choices, such as an alternative allocation method for the foreground product system.
With the sensitivity analysis, the PCF values will vary. For significant variations of PCF, for instance, due to remaining methodological choices or the choice of background datasets (cf. Section 3.1), the decisive change and the range by which the PCF is expected to change should be reported.
The following checklist can be used for LCA practitioners to validate the PCF:
• Verify the overall mass balance, including raw material inputs, product outputs, wastes and emissions into the air and water.
• Confirm the realism of on-stage direct emissions, such as by using carbon balance.
• Evaluate utility consumption for plausibility. • Ensure allocation factors are in line with Section 3.3.
• Assess the appropriateness of secondary datasets selected for Scope 3. Check whether the technology represented in the LCI is appropriate, whether the application of proxies is appropriate and consider replacing the dataset with supplier data if available.
• Benchmark CO2-equivalents against own calculations, the same product from other plants or sites, existing LCA data and LCIs from third-party databases.
• Investigate and determine the cause of significant deviations from LCA benchmark data.
Version 1.2, 15.10.2025 © ATIEL and UEIL Page 31 of 40 This document is a controlled document only in electronic form. Printed versions or copies are not subject to change service
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