Thermochemical biomass conversion systems have the potential to produce heat, power, fuels and other products from forest biomass at distributed scales that meet the needs of some forest industry facilities. However, many of these systems have not been deployed in this sector and the products they produce from forest biomass have not been adequately described or characterized with regards to chemical properties, possible uses, and markets. This paper characterizes the producer gas, biochar, and activated carbon of a 700 kg h⁻¹ prototype gasification system and a 225 kg h⁻¹ pyrolysis system used to process coniferous sawmill and forest residues. Producer gas from sawmill residues processed with the gasifier had higher energy content than gas from forest residues, with averages of 12.4 MJ m⁻³ and 9.8 MJ m⁻³, respectively. Gases from the pyrolysis system averaged 1.3 MJ m⁻³ for mill residues and 2.5 MJ m⁻³ for forest residues. Biochars produced have similar particle size distributions and bulk density, but vary in pH and carbon content. Biochars from both systems were successfully activated using steam activation, with resulting BET surface area in the range of commercial activated carbon. Results are discussed in the context of co-locating these systems with forest industry operations.

Global forests capture and store significant amounts of CO2 through photosynthesis. When carbon is removed from forests through harvest, a portion of the harvested carbon is stored in wood products, often for many decades. The United States Forest Service (USFS) and other agencies are interested in accurately accounting for carbon flux associated with harvested wood products (HWP) to meet greenhouse gas monitoring commitments and climate change adaptation and mitigation objectives. This paper uses the Intergovernmental Panel on Climate Change (IPCC) production accounting approach and the California Forest Project Protocol (CFPP) to estimate HWP carbon storage from 1906 to 2010 for the USFS Northern Region, which includes forests in northern Idaho, Montana, South Dakota, and eastern Washington.

Forest operations generate large quantities of forest biomass residues that can be used for production of bioenergy and bioproducts. However, a significant portion of recoverable residues are inaccessible to large chip vans, making use financially infeasible. New production systems must be developed to increase productivity and reduce costs to facilitate use of these materials. We present a comparison of two alternative systems to produce biomass fuel (i.e., “hog fuel”) from forest residues that are inaccessible to chip vans: (1) forwarding residues in fifth-wheel end-dump trailers to a concentration yard, where they can be stored and then ground directly into chip vans, and (2) grinding residues on the treatment unit and forwarding the hog fuel in high-sided dump trucks to a concentration yard, where it can be stored and then reloaded into chip vans using a front-end loader. To quantify the productivity and costs of these systems, work study data were collected for both systems on the same treatment unit in northern Idaho in July 2009. With standard machine rate calculations, the observed costs from roadside to loaded chip van were $23.62 per bone dry ton (BDT) for slash forwarding and $24.52 BDT⁻¹ for in-woods grinding. Results indicate that for harvest units with conditions similar to the test area, slash forwarding is most appropriate for sites with dispersed residues and long-distance in-woods grinder mobilization. For sites with densely piled roadside residues, in-wood grinding is likely to be a more productive and less costly option for residue recovery.

Accurate information is important for effective management of natural resources. In the field of forestry, field measurements of forest characteristics such as species composition, basal area, and stand density are used to inform and evaluate management activities. Quantifying these metrics accurately across large landscapes in a meaningful way is extremely important to facilitate informed decision-making. In this study, we present a remote sensing based methodology to estimate species composition, basal area and stand tree density for pine and hardwood tree species at the spatial resolution of a Forest Inventory Analysis (FIA) program plot (78 m by 70 m). Our methodology uses textural metrics derived at this spatial scale to relate plot summaries of forest characteristics to remotely sensed National Agricultural Imagery Program (NAIP) aerial imagery across broad extents. Our findings quantify strong relationships between NAIP imagery and FIA field data. On average, models of basal area and trees per acre accounted for 43% of the variation in the FIA data, while models identifying species composition had less than 15.2% error in predicted class probabilities. Moreover, these relationships can be used to spatially characterize the condition of forests at fine spatial resolutions across broad extents.

The western United States faces significant forest management challenges after severe bark beetle infestations have led to substantial mortality. Minimizing costs is vital for increasing the feasibility of management operations in affected forests. Multi‐transmitter Global Navigation Satellite System (GNSS)‐radio frequencies (RF) technology has applications in the quantification and analysis of harvest system production efficiency and provision of real‐time operational machine position, navigation, and timing. The aim of this study was to determine the accuracy with which multi‐transmitter GNSS‐RF captures the swinging and forwarding motions of ground based harvesting machines at varying transmission intervals. Assessing the accuracy of GNSS in capturing intricate machine movements is a first step toward development of a real‐time production model to assist timber harvesting of beetle‐killed lodgepole pine stands. In a complete randomized block experiment with four replicates, a log loader rotated to 18 predetermined angles with GNSS‐RF transponders collecting and sending data at two points along the machine boom (grapple and heel rack) and at three transmission intervals (2.5, 5.0, and 10.0 s). The 2.5 and 5.0 s intervals correctly identified 94% and 92% of cycles at the grapple and 92% and 89% of cycles at the heel, respectively. The 2.5 s interval successfully classified over 90% of individual cycle elements, while the 5.0 s interval returned statistically similar results. Predicted swing angles obtained the highest level of similarity to observed angles at the 2.5 s interval. Our results show that GNSS‐RF is useful for realtime, model‐based analysis of forest operations, including woody biomass production logistics.