< Back to previous page

Project

Mitigation options through innovative wood product use

A smart use of harvested wood can contribute to mitigate climate change in two ways: increasing carbon stock and replacing products made from fossil energy intensive materials. In this dissertation we analysed and compared alternative uses of harvested wood to increase its climate change mitigation effect. To achieve this goal, we developed a wood product model and applied it with data from public databases and published literature.

The study has three parts. In the first part (Chapter 2), we analysed the state-of-the-art of wood product modelling. We found 41 different wood product models published in peer reviewed journals, and compared them based on the model characteristics including their components and assumptions, and on the model use characteristics describing how these models were applied with related assumptions. We used a set of indicators to classify the models and analyse their evolution. We identified the substitution effect and recycling as the two indicators contributing the most to the model evolution during the last years. We also realized that lack of data continues to be an important constraint for more accurate estimations.

The knowledge acquired in this first part raised new questions we tackled in the following parts. It also gave us the expertise to build a new improved wood product model to answer these questions. We realised that wood product models have been applied to estimate national carbon stock changes for its report to the United Nations Framework Convention on Climate Change, and also, together with forest growth models, to compare the amount of carbon stock in wood products with the other carbon pools in forest ecosystems and to predict how new forest management schemes could affect the carbon stored in all these pools. But we identified a knowledge gap on how different uses of harvested wood, keeping the same forest management, could affect the mitigation effect of wood products.

In the second part of the dissertation we focused our research on strategies to increase carbon stock and carbon stock change in wood products. Carbon stock is more sensitive to lifespan and recycling rate than any other parameter in wood product models. Therefore we started this part with an analysis on how an increment in product lifespan and recycling rate would affect the carbon stock change (chapter 3). This analysis was made from both a theoretical and a practical perspective. In the theoretical model exercise we found out that carbon stock is linearly dependent on lifespan and exponentially dependent on recycling rate. In the practical application, we used European (EU-28) production data of semi-finished products from FAOSTAT and found that the annual emission savings due to projected wood product use will be 57.67 Mt CO2 year-1 in 2030 under a business as usual scenario. But with similar relative increases of lifespan and recycling rate (about 20%) applied in 2017 we could increase the emission savings by 5 Mt CO2 year-1 in 2030, and by combining both increments we could achieve emission savings in 2030 by 67.62 Mt CO2 year-1. Results showed that changes in long-lived products are more significant than changes in short-lived products but their effects appear later in time. Our recommendation is to increase recycling rate of short-lived products because global objectives of reducing atmospheric carbon concentrations are due in a short-medium term. However, both strategies can be combined to achieve higher mitigation effects in long term.

Further in the second part (Chapter 4) we focused on the effect of cascade use of harvested wood on carbon stock. The origin of this part was the wrong allocation of recycled wood by some models we discovered in the first part. We realized that these models erroneously allocate recycled wood to the same product categories, which created infinite loops that overestimate carbon stock in wood products. Our main goal was to estimate how large this overestimation was, but we also analysed the effect of improved cascade chains and the uncertainty effect of the parameters used to allocate harvested wood to products in use. Using production data extracted from German yield tables, we found that carbon stock in Germany was overestimated by 16% due to the use of infinite recycling loops. We also found a standard deviation of about 25% on the results due to the uncertainty of the allocation parameters. Future model application can easily avoid the infinite recycling loops by allocating recycling wood to new product categories defined by cascade chains. But involved stakeholders should collaborate to better define the allocation parameters and reduce its uncertainty, which is a more complicated task.

In the third and last part of the dissertation (Chapter 5) we compared the carbon stock change with the substitution effect, which is the reduction of industrial emissions due to the use of wood as a substitute for energy intensive materials. For this study we used European production of semi-finished products from FAOSTAT database. We defined three alternative scenarios to compare the effect of carbon stock change with the substitution effect: a first scenario promoting material use of harvested wood through cascading, another one promoting energy use, and the third one promoting the use of engineered wood products. We learnt that the substitution effect was more effective than the carbon stock change in the long term, and that the material oriented scenario is the best to mitigate climate change. However, the optimal strategy could be the promotion of material use and the use of engineered wood products since both strategies contribute to mitigate climate change without creating trade-offs.

Date:1 Oct 2013 →  22 Mar 2017
Keywords:Climate change mitigation, Wood product model
Disciplines:Landscape architecture, Art studies and sciences, Physical geography and environmental geoscience, Communications technology, Geomatic engineering, Forestry sciences, Ecology, Environmental science and management, Other environmental sciences
Project type:PhD project