Both transportation costs and market values of woody biomass are strongly linked to the amount of moisture in the woody biomass. Therefore, managing moisture in the woody biomass well can lead to significant advantages in the woody biomass energy business. In this study, two prediction models were developed to estimate moisture content for Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) and hybrid poplar (Populus spp.) woody biomass. Experimental data for the Douglas-fir model were collected over four different seasons at two different in-forest study sites in Oregon (Corvallis and Butte Falls) between December 2010 and December 2011. Three woody biomass bundles consisting of 3-meter length logs (30 to 385 mm diameter) were built each season at each study site; a total of 24 Douglas-fir bundles (1,316 to 3,621 kg weight) were built over the period. Experimental data for the hybrid poplar model were collected in two drying trials at two off-forest study sites in Oregon (Clatskanie and Boardman) between April 2011 and January 2012. Two types of woody bundles consisting of 3-meter length logs were built each trial: small (28 to 128 mm diameter, 2,268 to 5,389 kg weight) and large (75 to 230 mm diameter, 3,901 to 7,013 kg weight). A total of eight hybrid poplar bundles were built over the period. These data were used to develop linear mixed effects multiple regression models for predicting the moisture content of Douglas-fir and hybrid poplar biomass, respectively. The major factors considered in this study for predicting woody biomass moisture content change were cumulative precipitation, evapotranspiration (ET₀), and biomass piece size. The Food and Agriculture Organization (FAO) Penman-Monteith method, which requires temperature, solar radiation, wind, and relative humidity data, was used to calculate ET₀. The developed models can be easily applied to any location where historic weather data are available to calculate estimated air-drying times for Douglas-fir and hybrid poplar biomass at any time of the year. Oregon has been split into nine climate zones. Use of the model was demonstrated for four climate zones, two in which air-drying data were collected, and two in which it was not collected. Considerable differences in predicted drying times were observed between the four climate zones. / Graduation date: 2013

Woody biomass transportation costs and market values/costs are strongly correlated with the woody biomass moisture content. Properly managing moisture content can potentially lead to economic and environmental advantages in biomass energy markets. Good management requires accurate moisture content measurements. Therefore, availability of accurate, precise, reliable, and efficient tools to assess woody biomass moisture content is essential. In this study, six different tools (Fibre-Gen HM200, IML Hammer, Humimeter BLW, Timbermaster, Humimeter HM1 and Wile Bio Meter) were evaluated. The six tools employed three different measurement technologies; acoustic, conductance, and capacitance. Woody biomass samples were collected over one season (summer 2011) at three different locations in western Oregon (Corvallis, Dallas, and Clatskanie) for three softwood species and three hardwood species: Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco), Ponderosa pine (Pinus ponderosa L.), western hemlock (Tsuga heterophylla (Raf.) Sarg.), hybrid poplar (Populus spp.), Madrone (Arbutus spp.), and Garryana Oak (Quercus garryana Dougl. ex Hook). Twenty 3-meter long log (20 to 400mm diameter) specimens were collected per species; 18 specimens were divided into two different treatments (open vs. covered), and the two remaining specimens were chipped. In addition, approximately 100 kilograms per species of hogfuel (limbs and tops) were collected and chipped. Moisture content measurements of logs, chips, and hogfuel were made regularly over a four month period. These data was used to develop multiple linear regression models for assessing the moisture content of the six species using the six tools. The major factors considered in the regression models were species (6), treatment (2), and tools (6). The data were also used to estimate the sample size needed for each tool. The best tool from each technology type was identified. The results generated from this study show that (1) none of the tools are accurate without calibration for different species, (2) the best model/tool combination could only explain about 80% of the variability in measurements, (3) further product development is required in some cases to ensure that the tools are robust for industrial application, and (4) there is a wide range in efficiency of the tools (i.e., 50 minute tool efficiency range). The Fibre-Gen HM200 and Wile Bio Meter were the most accurate, precise and efficient tools tested. The cost of transporting woody biomass from the forest to woody biomass plants is "optimized" when the moisture content drops to approximately 30% (wet basis). Validation of the models developed for three of the tools tested (Fibre-Gen HM200, Humimeter BLW and the Wile Bio Meter) indicates that the tools are accurate below 35% MC (wet basis). This suggests they could be used for making threshold transportation decisions, i.e., determining when to haul. / Graduation date: 2013