Growth in bioenergy interests in the southeastern United States has created a need for cost-effective woody biomass harvesting systems. We evaluated three operational systems for their potential production and cost: horizontal grinders fed with residue from roundwood harvests, horizontal grinders fed with residue from clean chipping harvests, and whole tree chippers fed with entire stems. We evaluated three contractors operating each of the three system types over the course of approximately one working week each. Utilization rates for chippers and grinders were 44% and 38% respectively. Hourly production ranged between 22 – 30 metric green tonnes (gt)/SMH and 64 – 70 gt/PMH and did not differ significantly between the three systems. Delivered costs per gt of material were also very similar for the three systems and ranged between $22.68 and $23.81.
It is well-known that machine operators vary in their performance when undertaking mechanized forestry harvesting operations. Nevertheless, the human factor is still largely disregarded in productivity calculations. In the present study, operator performance is evaluated by analysing archived production data collected automatically by computers on-board single grip harvesters driven by 32 operators working in 3,351 stands over a period of three years. The experimental conditions were all approximately the same. The effect of the operators is modelled by a multilinear regression analysis. Seventeen operators were found to have performance levels that differed significantly from the mean model. Together, ‘tree volume’ and ‘operator’ explained 84% of the overall variance. However, since 37.3% of the variance in productivity is explained by the operator, the influence of the operator on productivity is quite large. The minimum and maximum significant mean productivity values for all the operators differed by a factor of 2.2, which reduced to a factor of 1.8 if only data from experienced operators were analysed, although this still demonstrates that the best operators are nearly twice as productive as the worst. The operator, therefore, has an important influence on productivity and should be considered a key factor in productivity models.
Landings are an integral part of modern whole-tree harvesting operations in pine plantations in New Zealand. However, little information has been published about size of landings and the factors that influence landing characteristics. A representative sample of 142 landings was measured using Global Positioning System (GPS); 12 were recently constructed (unused), 38 were live, and the remaining 92 were older and closed out. The average landing size was 3900 m2 (0.96 acres), with a range from 1370 to 12540 m2. On average the number of log-sorts cut was 11, the landings were in use for four weeks, estimated daily production was 287 tons/day, 47% were manual processing (53% mechanized), and 79% were grapple loader (21% front-end loader). A regression equation to model landing size indicates that number of log sorts and production levels are the two main factors that determine landing size. Landings do tend to ‘grow’ over time, with used landings on average being 900 m2 larger than recently constructed landings. The most recently constructed landings were much larger than the company design; whereas either 40x60 m or 40x80 m were common specifications. A comparable study in 1987 showed the average landing to be just over 1900 m2 (0.47 acres), indicating landing size has nearly doubled in the last 20 years. Landings serviced by front-end loaders were on average 1100 m2 larger than those serviced by grapple loader, but this result is compounded by the fact that front-end loaders are more commonly used in high-production systems.
Woody biomass has been considered of low value because the cost of removal generally exceeded market price. New, valued-added markets to offset removal costs are necessary for utilization to be effective. In recent years the use of biomass as feedstock for biofuel production in the United States has been on the rise. A variety of liquid fuels can be produced from woody biomass; ethanol is one of the most promising. This study presents a two-stage approach to selecting woody biomass-based biofuel plants using Geographical Information System (GIS) spatial analysis and the multi-criteria analysis ranking algorithm of compromise programming. Site suitability was evaluated to minimize direct cost for investors and potential negative environmental impacts. The first step was to create a site suitability index using a linear fuzzy logic prediction model. The model involved 15 variables in three factor groups: (1) general physical conditions, (2) costs, and (3) environmental factors. The weights of the cost factors were determined using pairwise comparisons in the Analytical Hierarchy Process (AHP). The value of site suitability was reclassified into three categories (non-suitable, low-suitable, and high-suitable) using different classification methods. With a feasible plant location defined as an industrial site within the most suitable area, the second stage of the analysis used compromise programming to compare the potential sites. The criteria used to rank the potential sites included fuzzy distance to woody biomass, highways, railways, commercial airports, communities, and available parcel size. The AHP was used to compute the relative importance of each criterion. The top ten suitable sites were determined, and sensitivity analyses were conducted to derive the most preferred sites. The approach was successful in taking a large amount of non-commensurate spatial data and integrating a site-based ranking algorithm to find the top locations for biomass plants. It also has great potential and applicability to other suitability and site selection studies.