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.
2018
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No abstract has been registered
Abstract
We compare the food values in the USA and Norway using the best–worst scaling approach. The food values examined are aimed at capturing the main issues related to food consumption such as naturalness, taste, price, safety, convenience, nutrition,novelty, origin, fairness, appearance, environmental impact and animal welfare. Results show that respondents in both countries have mostly similar food values,with safety being the most important value; while convenience and novelty are the least important values. Specifically, US respondents consider price more important and naturalness less important than Norwegian respondents.
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No abstract has been registered
Authors
Callum Aidan Stephen Hill Andrew Norton Janka DibdiakovaAbstract
More than sixty environmental product declarations of insulation materials (glass wool, mineral wool, expanded polystyrene, extruded polystyrene, polyurethane, foam glass and cellulose) have been examined and the published information for global warming potential (GWP) and for embodied energy (EE) has been analysed and is presented. A peer-review literature survey of the data for GWP and EE associated with the different insulation products is also included. The data for GWP (kg carbon dioxide equivalents) and EE (megajoules) is reported in terms of product mass or as a functional unit (FU) (1 m2 of insulation with R = 1 m2 K/W). Data for some classes of insulation material (such as glass wool) exhibit a relatively narrow range of values when reported in terms of weight of product or as a functional unit. Other classes of insulation material exhibit much wider distributions of values (e.g., expanded polystyrene). When reported per weight of product, the hydrocarbon-based insulation materials exhibit higher GWP and EE values compared to inorganic or cellulosic equivalents. However, when compared on an FU basis this distinction is no longer apparent and some of the cellulosic based materials (obtained by refining of wood chips) show some of the highest EE values. The relationship between the EE and GWP per kg of insulation product has also been determined as being 15.8 MJ per kg CO2 equivalents.
Authors
Trygve S. AamlidAbstract
No abstract has been registered
Abstract
Productivity of a mechanized P. patula cut-to-length harvesting operation was estimated and modelled using two methods of data collection: manual time study and follow-up study using StanForD stem files. The objective of the study was to compare the productivity models derived using these two methods to test for equivalence. Manual time studies were completed on four different machines and their operators. Two Ponsse Bear harvesters fitted with H8 heads, and two Ponsse Beaver harvesters, fitted with H6 heads, were included. All machines were equipped with Ponsse Opti2 information system. All four operators had approximately 1 year of experience working with their respective machines. The four machines worked in separate four-tree-wide harvesting corridors, and they each harvested 200 trees. Individual tree diameter at breast height (DBH), and height measurements were made manually. Subsequently, data on the trees in each study were extracted from the StanForD stem reports from each of the harvesters. Cycle times in the stem reports were determined based on the difference between consecutive harvest timestamps. The two methods were compared in terms of their abilities to estimate equivalent measures for tree DBH, volume, and productivity. In all four cases, significant differences were found between the DBH and volume measures derived using the two methods. Subsequently, the volume measures from the manual methods were used as the basis for productivity calculations. Results of the productivity comparisons found no significant differences between the models developed from the two methods. These results suggest that equivalent productivity models can be developed in terms of time using either method, however volume discrepancies indicate a need to reconcile bark and volume functions with the high variability experienced in the country.
Authors
Bjørn Egil FløAbstract
No abstract has been registered
Authors
Xiao Huang Chaoqing Yu Jiarui Fang Guorui Huang Shaoqiang Ni Jim Hall Conrad Zorn Xiaomeng Huang Wenyuan ZhangAbstract
Crop models are widely used to evaluate the response of crop growth to drought. However, over large geographic regions, the most advanced models are often restricted by available computing resource. This limits capacity to undertake uncertainty analysis and prohibits the use of models in real-time ensemble forecasting systems. This study addresses these concerns by presenting an integrated system for the dynamic prediction and assessment of agricultural yield using the top-ranked Sunway TaihuLight supercomputer platform. This system enables parallelization and acceleration for the existing AquaCrop, DNDC (DeNitrification and DeComposition) and SWAP (Soil Water Atmosphere Plant) models, thus facilitating multi-model ensemble and parameter optimization and subsequent drought risk analysis in multiple regions and at multiple scales. The high computing capability also opens up the possibility of real-time simulation during droughts, providing the basis for more effective drought management. Initial testing with varying core group numbers shows that computation time can be reduced by between 2.6 and 3.6 times. Based on the powerful computing capacity, a county-level model parameter optimization (2043 counties for 1996–2007) by Bayesian inference and multi-model ensemble using BMA (Bayesian Model Average) method were performed, demonstrating the enhancements in predictive accuracy that can be achieved. An application of this system is presented predicting the impacts of the drought of May–July 2017 on maize yield in North and Northeast China. The spatial variability in yield losses is presented demonstrating new capability to provide high resolution information with associated uncertainty estimates.
Abstract
No abstract has been registered
Abstract
Forestry in coastal Norway has traditionally been a marginal activity with a low annual harvest rate. However, the region is now faced with large areas of spruce plantations that will reach harvest maturity within the next 25 years. Due to the poor infrastructure in the region, the current challenge is to harvest the maturing spruce plantations at an acceptable cost. Hence, there is considerable interest both from the forest sector and politicians to invest in infrastructure that can provide the basis for profitable forest sector development in coastal Norway. This paper presents a mathematical optimization model for timber transportation from stump to industry. The main decision variables are location of quays, upgrade of public road links, the length of new forest roads, and when the investments should happen. The main objective is to provide decision support for prioritization of infrastructure investments. The optimization model is combined with a dynamical forest resource model, providing details on available volumes and costs. A case study for coastal Norway is presented and solved to optimality. The instance includes 10 counties comprising more than 200 municipalities with forest resources, 53 possible new quays for timber export and 916 public road links that also can be upgraded. Compared with a no investment case, the optimal solution improved the objective by 23%. The study shows that consistent, informative and good analyses can be performed to evaluate trade-offs, prioritization, time and order of investment, and cost saving potentials of infrastructure investments in the forest industry. The solution seems reasonable based on present infrastructure and state of the forest.