Using wood as a building material affects the carbon balance through several mechanisms. This paper describes a modelling approach that integrates a wood product substitution model, a global partial equilibrium model, a regional forest model and a stand-level model. Three different scenarios were compared with a businessas-usual scenario over a 23-year period (2008-2030). Two scenarios assumed an additional one million apartment flats per year will be built of wood instead of non-wood materials by 2030. These scenarios had little effect on markets and forest management and reduced annual carbon emissions by 0.2-0.5% of the total 1990 European GHG emissions. However, the scenarios are associated with high specific CO 2 emission reductions per unit of wood used. The third scenario, an extreme assumption that all European countries will consume 1-m 3 sawn wood per capita by 2030, had large effects on carbon emission, volumes and trade flows. The price changes of this scenario, however, also affected forest management in ways that greatly deviated from the partial equilibrium model projections. Our results suggest that increased wood construction will have a minor impact on forest management and forest carbon stocks. To analyse larger perturbations on the demand side, a market equilibrium model seems crucial. However, for that analytical system to work properly, the market and forest regional models must be better synchronized than here, in particular regarding assumptions on timber supply behaviour. Also, bioenergy as a commodity in market and forest models needs to be considered to study new market developments; those modules are currently missing.

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In any decision-making situation under uncertainty, the decision-maker can either choose between different alternatives with the current information or reduce the uncertainty by collecting more information. The value of the information can be defined as the difference between the expected value of an activity with and without the information. We examined the value of additional information in a case of competitive bidding for a given block of timber. Our main focus was on the uncertainty of roundwood quality, and volume was assumed to be known with certainty. The uncertainty of quality was described with the uncertainty of dimensions of living and dead crown. The prior information concerning the crown dimensions was obtained from statistical models or from an assumed uniform distribution. The value of each tree was calculated by predicting the proportions of different lumber grades and by-products as a function of the dimensions of the stem and the crown. The results showed that, if only uniform distribution was available as prior information, the quality information had a high value for the timber buyer. However, if the prior information from the statistical models was used, investing in quality information was profitable only for the stands with the highest volume.

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