Validation of prediction models for estimating the moisture content of logging residues during storage. (November 2016)

• Record Type: Journal Article
• Authors: Routa, Johanna; Kolström, Marja; Ruotsalainen, Johanna; Sikanen, Lauri
• Is Part Of: Biomass and bioenergy. Volume 94(2016:Nov.)
• Page Start: 85
• Page End: 93
• Publication Date: 2016-11
• Subjects: Logging residues -- Quality -- Storing -- Drying models -- Natural drying -- Model validation -- Meteorological data; Biomass energy -- Periodicals; Biomass -- Periodicals; Energy-Generating Resources -- Periodicals; Bioénergie -- Périodiques; 333.9539
• DOI: 10.1016/j.biombioe.2016.08.019
• Languages: English
• ISSNs: 0961-9534

Abstract

Abstract: Increased use of forest biomass for energy and rising transportation costs are forcing biomass suppliers towards better moisture content management in the supply chain. Natural drying is used to decrease moisture content of energy wood. Drying is dependent on wood characteristics and weather conditions. Weather-dependent drying models for estimating the optimal storage time based on average moisture changes in fuel wood stacks stored outdoors have been developed for different stem wood and logging residues. Models are an easy option for estimating the moisture content of energy wood piles compared to sampling and measuring the moisture of samples. In this study, stand and roadside storage models for logging residues were validated against data from field studies and forest companies. Over 200 reference piles for the stand model, 23 piles for the roadside model and 10 piles for the combined model were studied. Results of the validation are promising. The difference between measured and modelled moisture was on average only 0.35%. The presented models can be implemented anywhere in Finland, because the Finnish Meteorological Institute has a weather observation service offering weather history data for every location in Finland. For international use, parameters need to be estimated on a case by case basis, but it should be possible to implement the approach also elsewhere. Highlights: Drying models for estimating the average moisture changes in fuel wood stacks stored outdoors have been developed. The models have been validated against real storages and the results are promising. With the local weather data, the models can be applied all over the country. The prediction models improve quality management of energy wood for power plants.