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Purpose Despite a mature debate on the importance of a timedependent account of carbon fluxes in life cycle assessments (LCA) of forestry products, static accounts of fluxes are still common. Time-explicit inventory of carbon fluxes is not available to LCA practitioners, since the most commonly used life cycle inventory (LCI) databases use a static approach. Existing forest models are typically applied to specific study fields for which the detailed input parameters required are available. This paper presents a simplified parametric model to obtain a time-explicit balanced account of the carbon fluxes in a forest for use in LCA. The model was applied to the case of spruce as an example. Methods The model calculated endogenous and exogenous carbon fluxes in tons of carbon per hectare. It was designed to allow users to choose (a) the carbon pools to be included in the analysis (aboveground and belowground carbon pools, only aboveground carbon or only carbon in stem); (b) a linear or sigmoidal dynamic function describing biomass growth; (c) a sigmoidal, negative exponential or linear dynamic function describing independently the decomposition of aboveground and belowground biomass; and (d) the forest management features such as stand type, rotation time, thinning frequency and intensity. Results and discussion The parametric model provides a time-dependent LCI of forest carbon fluxes per unit of product, taking into account the typically limited data available to LCA practitioners, while providing consistent and robust outcomes. The results obtained for the case study were validated with the more complex CO2FIX. The model ensures carbon balance within spatial and time delimitation defined by the user by accounting for the annual biomass degradation and production in each carbon pool. The inventory can be used in LCA studies and coupled with classic indicators (e.g. global warming potential) to accurately determine the climate impacts over time. The model is applicable globally and to any forest management practice. Conclusions This paper proposes a simplified and flexible forest model, which facilitates the implementation in LCA of time-dependent assessments of bio-based products.

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