Emission data: one factor vs. one factor per year, and how interpolation works
Emission data for a module in the library can either be a single combined factor, or several year-stamped factors for the same module. A single factor is the normal state for most building products, where one value covers the whole service life. One factor per year is today used mainly for B6 Operational energy, where the emissions of the delivered energy (for example district heating or electricity) change over time as production becomes cleaner.
How interpolation works
Section titled “How interpolation works”When a calculation needs a value for a particular year, and the module has several year-stamped data points, LCAbyg picks between four cases:
| Situation | Behaviour |
|---|---|
| The year matches a data point exactly | The value for that year is used directly |
| The year falls below all data points | The lowest (earliest) data point is used |
| The year falls above all data points | The highest (latest) data point is used |
| The year falls between two data points | Linear interpolation between the two nearest points |
If data is missing entirely for the module, it contributes nothing in that year.
Why it is set up this way
Section titled “Why it is set up this way”A study period can stretch across 50 years, while a library typically only has data points for the years where a new measurement or forecast has been made, for example every five or ten years. Linear interpolation between the points gives a reasonable estimate for the years in between, without the library having to contain a data point for every single year.