Modeling residual biomass from mechanized wood harvesting with data measured by forest harvester.

The lack of accurate models for estimating residual biomass in wood harvesting operations results in underutilization of this co-product by forestry companies. Due to the lack of this information, forestry operations planning, such as chipping and transport logistics, are influenced, with a consequent increase in costs. Thereby, the aim of this study was to propose and evaluate statistical models to estimate residual biomass of Eucalyptus sp. in wood harvesting operations by means of tree variables measured from harvester processing head. Generalized linear models were composed through stepwise procedure for estimating residual biomass by tree covariates: diameter at breast height, commercial height, commercial limit diameter, and stem commercial volume, considering also their transformations and combinations. Residual biomass distributions with positive skew support the application of generalized linear model and Gamma distribution in random component, since normality assumption in traditional linear regression was a requirement not satisfied in this study. By stepwise procedure, tree variables associated to forest biomass were selected, whose linear combinations resulted in models with high statistical efficiency and accuracy. Thus, models developed in this study are innovative tools to estimate residual biomass in mechanized wood harvesting, in which can be inserted into harvester's hardware to provide real-time information.

Energy balance and CO2 emission in mechanized biomass harvesting in pine stands under thinning.

Biomass is an important component of the Brazilian energy matrix, with a potential contribution of co-products from thinned forests. The aim of this work was to evaluate the energy balance and CO2 potential emission in mechanized biomass harvesting operations in Pinus taeda stands at 9 and 10 years-old and under thinning, searching to support the use of co-product biomass from thinning as a renewable energy source. Thinning was carried out through cut-to-length harvesting method, in which large logs for sawmill and small logs for energy were produced. In addition, tops, needles, barks, and branches were considered as co-products. The balance between consumed energy and emitted CO2 by machines for thinning in relationship to the energy and CO2 in thinned biomass was estimated. Thus, dry matter, energy potential, and CO2 potential emission were evaluated and compared considering thinning stand ages as treatments. Mechanized thinning consumes a large energy and produces CO2, however, the energy consumed by machines is lower than 1% of the estimated energy potential in thinned biomass, while the CO2 emission is lower than 0.5% of the biomass. Therefore, the use of co-product biomass of thinning is an important way to mitigate greenhouse gas emission.