Methodology for PCF Calculations of Lubricants, Greases and other Specialties
Data gaps may arise when insufficient primary or specific secondary data is available to represent a particular process ina product's life cycle. In this case, data gaps should be filled with proxy data or, as a last resort, estimated data.
Proxy data:
Proxy data refer to primary or specific secondary data that reflect similar processes or products and can serve as a substitute or approximation. For instance, no primary or specific secondary data exists for PAO 6. However, specific secondary data for PAO 2 and PAO 40 as secondary data or supporting literature exists to support a study. As no data is available for PAO 6, specific secondary data for PAO 2 is used as proxy data for PAO 6.
Estimated data:
When no primary data, specific secondary data, or proxy data is available, the significance of the data missing in the data gap shall be evaluated. According to the cut-off criteria (cf. Section 3.2), missing data can be then cut-off from the product system if the significance of the missing data falls under the cut-off threshold. If the data gap is significant, a careful estimation shall be made, considering the knowledge of the missing data and any relevant information. A conservative approach should be applied by, e.g. selecting the value at the top of the potential range. Estimated data shall be replaced as soon as possible by primary or secondary data in the update of the PCF.
PCF:
PCFs should be regularly calculated to monitor progress. The validity period for PCFs is up to 5 years unless there are major production process or formulation changes (if the new PCF is expected to increase by over 20% compared to the original PCF). After 5 years, PCFs shall be recalculated. An internal review process for PCFs should be initiated prematurely, e.g. after 3 years may be suitable. The PCF calculation should always disclose the reference year and date of calculation/publication, as they determine the time boundary of the PCF value.
3.1.2 Data quality requirements
In the data collection phase, the lubricant manufacturer shall assess the quality of their data. This can be achieved by utilizing data quality indicators to evaluate activity data, emission factors and/or direct emissions data. A detailed description of the data quality indicators is shown in Table 2. For each indicator, three quality levels exist, where level 1 represents the highest data quality and level 3 the lowest.
Data Quality for the quality indicators Technological representativeness, Temporal representativeness, and Geographical representativeness are mandatory reporting requirements, while the quality indicators Completeness and Reliability are optional reporting requirements.
Version 1.2, 15.10.2025 © ATIEL and UEIL
Page 16 of 40 This document is a controlled document only in electronic form. Printed versions or copies are not subject to change service
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40
