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

Author

Listed:
  • Sajdak, M.
  • Velázquez-Martí, B.
  • López-Cortés, I.
  • Fernández-Sarría, A.
  • Estornell, J.

Abstract

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 Münchh. 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 (R2 = 0.87), as well as for dry biomass and conical and parabolic crown volume (R2 = 0.78). The best result (R2 = 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.

Suggested Citation

  • Sajdak, M. & Velázquez-Martí, B. & López-Cortés, I. & Fernández-Sarría, A. & Estornell, J., 2014. "Prediction models for estimating pruned biomass obtained from Platanus hispanica Münchh. used for material surveys in urban forests," Renewable Energy, Elsevier, vol. 66(C), pages 178-184.
    • Handle: RePEc:eee:renene:v:66:y:2014:i:c:p:178-184
    DOI: 10.1016/j.renene.2013.12.005
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    References listed on IDEAS

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    1. Sajdak, M. & Velazquez-Marti, B., 2012. "Estimation of pruned biomass form dendrometric parameters on urban forests: Case study of Sophora japonica," Renewable Energy, Elsevier, vol. 47(C), pages 188-193.
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    1. Velázquez-Martí, B. & Gaibor-Cházvez, J. & Niño-Ruiz, Z. & Narbona-Sahuquillo, S., 2018. "Complete characterization of pruning waste from the lechero tree (Euphorbia laurifolia L.) as raw material for biofuel," Renewable Energy, Elsevier, vol. 129(PA), pages 629-637.
    2. Vanbeveren, Stefan P.P. & Spinelli, Raffaele & Eisenbies, Mark & Schweier, Janine & Mola-Yudego, Blas & Magagnotti, Natascia & Acuna, Mauricio & Dimitriou, Ioannis & Ceulemans, Reinhart, 2017. "Mechanised harvesting of short-rotation coppices," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 90-104.
    3. Alba Mondragón-Valero & Borja Velázquez-Martí & Domingo M. Salazar & Isabel López-Cortés, 2018. "Influence of Fertilization and Rootstocks in the Biomass Energy Characterization of Prunus dulcis (Miller)," Energies, MDPI, vol. 11(5), pages 1-12, May.
    4. Ferla, G. & Caputo, P. & Colaninno, N. & Morello, E., 2020. "Urban greenery management and energy planning: A GIS-based potential evaluation of pruning by-products for energy application for the city of Milan," Renewable Energy, Elsevier, vol. 160(C), pages 185-195.
    5. Velázquez- Martí, B. & Gaibor-Chávez, J. & Niño-Ruiz, Z. & Cortés-Rojas, E., 2018. "Development of biomass fast proximate analysis by thermogravimetric scale," Renewable Energy, Elsevier, vol. 126(C), pages 954-959.
    6. Hevia, Andrea & Crabiffosse, Alejandra & Álvarez-González, Juan Gabriel & Ruiz-González, Ana Daria & Majada, Juan, 2017. "Novel approach to assessing residual biomass from pruning: A case study in Atlantic Pinus pinaster Ait. timber forests," Renewable Energy, Elsevier, vol. 107(C), pages 620-628.

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