Spatial variability of chemical element, ash content, and calorific value of black spruce (Picea mariana) from Labrador

Abstract

Woody biomass residues from lumber production are an important renewable energy source, but their fuel quality depends on chemical composition and spatial variation. This study analyzed black spruce (Picea mariana) residues from Labrador to assess gross calorific value, carbon, hydrogen, and ash content. 14 trees provided 52 samples with triplicate tests. Variability was examined using fixed- and mixed-effects models, with paired t-tests and regression analyses applied to radial contrasts.

Results showed that radial effects were most consistent: inner wood averaged ~0.3 MJ·kg⁻¹ higher GCV, while outer wood contained ~11% more ash. Carbon decreased by ~1.4% from bottom to top, hydrogen remained stable (6.09–6.19%), and ash was ~13% higher in the top sections. Regression models explained little of the GCV variance (R² < 0.1). These findings indicate that elemental composition alone cannot fully predict energy potential but provide baseline data for evaluating lumber residues as solid biofuels in boreal forests.