Dataset on the physicochemical properties of raw and torrefied tropical hardwood sawdust under varying torrefaction conditions

TL;DR

This paper provides a dataset on the properties of tropical hardwood sawdust before and after torrefaction, a process that improves its energy value.

Contribution

The dataset includes detailed physicochemical measurements under varying torrefaction conditions for biomass research and modeling.

Findings

Torrefaction increased the higher heating value and altered elemental ratios of the sawdust.

Mass and energy yields decreased with higher torrefaction temperatures and longer durations.

The dataset supports modeling and comparative studies for biomass-to-energy applications.

Abstract

This article presents a dataset on the physicochemical properties of tropical hardwood sawdust subjected to torrefaction under different process conditions. The dataset includes measurements for raw sawdust and samples torrefied at varying temperatures and durations. Key parameters reported are mass yield, energy yield, higher heating value (HHV), enhancement factor of HHV, proximate analysis (volatile matter, fixed carbon, and ash content), ultimate analysis (C, H, N, O, and S content), and elemental ratios (H/C and O/C). The data were collected using standard analytical methods for biomass characterization. Torrefaction was conducted at controlled temperatures ranging from 240 °C to 330 °C for residence times of 15–60 min. Mass and energy yields were calculated based on the initial and final sample weights and calorific values. The HHV was determined using a bomb calorimeter, while proximate analysis was carried out according to ASTM procedures. Ultimate analysis was performed using a CHNS analyzer, and oxygen was estimated by difference. Atomic ratios were calculated to provide insights into fuel quality changes induced by torrefaction. The dataset is presented in tabular format, allowing easy integration into further statistical, thermodynamic, or modeling studies. It provides a valuable reference for researchers working on biomass upgrading, energy conversion, and sustainable fuel development. In particular, the data can support the development of empirical and predictive models for biomass torrefaction, facilitate comparative analysis with other feedstocks, and contribute to life cycle or techno-economic assessments of biomass-to-energy pathways. The dataset is hosted in an open-access format, ensuring reusability for energy engineers, material scientists, and policy researchers interested in renewable energy and biomass valorization.