Publications
NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.
2023
Abstract
The materials used in construction have a significant environmental impact and this is becoming more important as operational energy requirements continue to fall. It is therefore becoming increasingly important to take into account the environmental burdens associated with materials used in construction. Life cycle assessment (LCA) and Environmental Product Declarations (EPD) are useful tools for this purpose. When comparing the results of numerous LCA studies of different construction materials, the main question is often ‘Which material is better for the environment?’. The answer, however, is usually not as simple – but why is it so difficult to decide which material has the lowest environmental impact? To answer this question, we have to consider what life cycle assessment is and how an LCA is undertaken. The report covers the stages of an LCA, from defining the goal and scope of the respective study to the creation of the life cycle inventory (LCI), the life cycle impact assessment (LCIA) to the reporting and interpretation of the results. Additionally, the report goes in detail into how to approach published LCA studies, how to work with EPDs and the much-discussed issue of Carbon storage in buildings. In the final chapter, the report assesses the comparability of published studies evaluating the environmental impact of different building materials.
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No abstract has been registered
Abstract
The aim of this study was to analyze the accuracy of predictions of dominant height, mean height, basal area, and volume from the nationwide forest attribute map (SR16). The analysis took advantage of field observations from 33 different forest inventory projects across Norway used for validation. Forest attributes for more than 5000 plots were predicted using non-stratified and stratified models of SR16 and the predictions were compared against corresponding ground reference values. Finally, the effect of different factors that might have influenced the prediction errors were analyzed using partial least squared regression (PLSR) to determine under which conditions the SR16 is less apt. The overall results across all plots were adequate (RMSE of 10%, MD of 2% for dominant and mean height; RMSE of 28%, MD of 4% for basal area; RMSE of 31%, MD of 5% for volume). However, when the accuracy was assessed locally for each inventory project, large differences in accuracy were observed. The MD% values for some inventory projects were substantial (>30% for basal area and volume). The results showed that stratification did not necessarily improve the results and that factors related to the forest structure had the greatest impact on the PLSR analysis.
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Authors
Jaime Candelas Bielza Lennart Noordermeer Erik Næsset Terje Gobakken Johannes Breidenbach Hans Ole ØrkaAbstract
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Martijn Vermeer Jacob Alexander Hay David Volgyes Zsofia Koma Johannes Breidenbach Daniele Stefano Maria FantinAbstract
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Lone Ross Lizhen Huang Erik Trømborg Roja Modaresi Hanne Kathrine Sjølie Kristina Bringedal GeddeAbstract
No abstract has been registered