Authors
Jia Fu, Xianzhe Liu, Linlin Yi, Zhenzhong Hu, Kezhi Tu, Xian Li, Cheng Zhang, Bo Zhao, Jun Han, Zehua Li, Guangqian Luo, Kaiyuan Li, Hong Yao
Published in
Bioresource technology. Pages 135990. Oct 02, 2026. Epub Oct 02, 2026.
Abstract
Dechlorination pretreatment is required for the energy recovery of chlorine-containing multi-source organic solid wastes (MSW). Gas-pressurized torrefaction (GP) enables efficient dechlorination and MSW upgrading at low temperatures, yet high dechlorination efficiency (DCE) often comes at the expense of char yield (CY), creating a persistent dilemma between chlorine removal and energy recovery. In this study, LSBT models were developed to jointly predict DCE and CY using feedstock properties and torrefaction variables. The final models achieved test-set R2 values of 0.94 for DCE and 0.96 for CY. Temperature was the primary predictor, while volatile matter was a key feedstock-related variable. Within the coverage of the compiled dataset, the models identified a temperature-pressure interaction that was consistent with the enhanced dechlorination observed under closed GP conditions, particularly for organic-chlorine feedstocks. Model-based optimization indicated that, relative to AP torrefaction, GP could reduce the predicted DCE-qualification temperature by 30-60 °C for selected feedstocks. The predicted operating windows also indicated higher CY and more selective chlorine removal for PVC and corn stalks. This work establishes a data-driven predictive framework for operating condition optimization of torrefaction, paving the way toward sustainable and selective upgrading of chlorine-rich organic solid wastes.
PMID:
42826802
Bibliographic data and abstract were imported from PubMed on 03 Oct 2026.
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