Abstract
Lifespan data is needed to increase accuracy in biogenic stored carbon calculations for wood products. Timber in the built environment, and wood in products all around us, can act as a store for biogenic carbon which was sequestered in wood during tree growth through photosynthesis in the forest (Hill 2019, Spear 2024). The calculations used to quantify this storage vary. In all cases it is recognised that the significance of carbon storage is sensitive to the time frame and supporting data is needed (Braun et al. 2016, Eberhardt et al. 2024, Spear and Hart 2025).
Lifespan for wood products is a complex topic. Service life is a result of multiple influences – from the inherent durability of the timber to the protection given by treatments , but also heavily influenced by in-use conditions. Such aspects are included in the ISO 15686 factor method. There is also a substantial societal and consumer psychological influence on whether wood products are removed or replaced ‘early’ or ‘late’ (Alfredsen et al. 2025). Modelling the population residence times in the harvested wood products pool can be done in several ways. While the Tier 1 approach (using first order decay and half lives to amalgamate all types of material within the semifinished product categories ‘sawnwood’, ‘wood based panels’, and ‘paper and paperboard’) remains popular, Tier 2 and 3 options are becoming possible as more data emerges (IPCC 2014). Lifespans of individual products can be modelled (Spear 2023). Data often confirms that a sigmoidal function (such as normal distribution, gamma distribution or chi squared distribution) fits buildings or products (Spear and Hart 2025). However such models require input data to enable curve fitting. Collating and reviewing lifespan and service life data from multiple studies and sources has shown that observational data from surveys or experiments are seldom well aligned with nominal service life, or design life, for buildings or components. The terms have different meanings. Attempts to combine reference values with factors for environmental conditions exist but no definitive set of factor values exist for reference service life calculations.
Lifespan for wood products is a complex topic. Service life is a result of multiple influences – from the inherent durability of the timber to the protection given by treatments , but also heavily influenced by in-use conditions. Such aspects are included in the ISO 15686 factor method. There is also a substantial societal and consumer psychological influence on whether wood products are removed or replaced ‘early’ or ‘late’ (Alfredsen et al. 2025). Modelling the population residence times in the harvested wood products pool can be done in several ways. While the Tier 1 approach (using first order decay and half lives to amalgamate all types of material within the semifinished product categories ‘sawnwood’, ‘wood based panels’, and ‘paper and paperboard’) remains popular, Tier 2 and 3 options are becoming possible as more data emerges (IPCC 2014). Lifespans of individual products can be modelled (Spear 2023). Data often confirms that a sigmoidal function (such as normal distribution, gamma distribution or chi squared distribution) fits buildings or products (Spear and Hart 2025). However such models require input data to enable curve fitting. Collating and reviewing lifespan and service life data from multiple studies and sources has shown that observational data from surveys or experiments are seldom well aligned with nominal service life, or design life, for buildings or components. The terms have different meanings. Attempts to combine reference values with factors for environmental conditions exist but no definitive set of factor values exist for reference service life calculations.
| Original language | English |
|---|---|
| Pages | 193-195 |
| Number of pages | 3 |
| Publication status | Published - 15 Sept 2026 |
| Event | 22nd Annual Meeting of the Northern European Network for Wood Science and Engineering (WSE) - Riga Technical University, Riga, Latvia Duration: 15 Sept 2026 → 16 Sept 2026 https://sites.google.com/kki.lv/wse2026/?pli=1&authuser=0 |
Conference
| Conference | 22nd Annual Meeting of the Northern European Network for Wood Science and Engineering (WSE) |
|---|---|
| Abbreviated title | WSE |
| Country/Territory | Latvia |
| City | Riga |
| Period | 15/09/26 → 16/09/26 |
| Internet address |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
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SDG 13 Climate Action
Keywords
- biogenic carbon storage
- HWP pool
- lifespan
- modelling
- service life
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