Prediction models for estimating pruned biomass obtained from Platanus hispanica Münchh. used for material surveys in urban forests

The amount of urban biomass waste derived from pruning operations represents a potential source of bioenergy little studied or considered in local bio-economies. This research focused on direct quantification of lignocellulosic residual biomass yielded during tree pruning, characterization of basic tree parameters and development of indirect biomass prediction models. Sample individuals of 30 Platanus hispanica Munchh. with mean diameter at breast height 23.56 cm, crown diameter 8.44 m, crown base height 3.76 m, and total height 11.57 m were examined. Wood formed 43.34% of pruned biomass before the drying process and wood moisture content in wet basis reached 40.16%. Mean quantity of dry biomass obtained per tree was 23.98 kg and standard deviation was 15.16 kg. Allometric relationships were analyzed. Significant coefficients of determination were observed for dry biomass and diameter at breast height (R-2 = 0.87), as well as for dry biomass and conical and parabolic crown volume (R-2 = 0.78). The best result (R-2 = 0.93) was obtained from a multiple regression model with several explicative variables. Indirect biomass prediction equations and characteristics of yielded residuals derived from this research can be useful for biomass planning and management purposes. These equations can be implemented for urban inventories, and the application of logistic models. The significance of this topic is beyond doubt for urban environment, especially for the possibilities of reducing carbon dioxide emissions and perspectives of biomass utilization as a biofuel. (C) 2013 Elsevier Ltd. All rights reserved.Sajdak, M.; Velázquez Martí, B.; López Cortés, I.; Fernández Sarriá, A.; Estornell Cremades, J. (2014). Prediction models for estimating pruned biomass obtained from Platanus hispanica Münchh. used for material surveys in urban forests. Renewable Energy. 66:178-184. doi:10.1016/j.renene.2013.12.005S1781846