Evaluation of the effects and interactions of initial chlorine and sulphur contents on the release of potassium compounds during biomass combustion

Cao, Wenhan and Li, Jun and Zhang, Xiaolei (2022) Evaluation of the effects and interactions of initial chlorine and sulphur contents on the release of potassium compounds during biomass combustion. Journal of the Energy Institute, 101. pp. 178-186. ISSN 1746-0220 (https://doi.org/10.1016/j.joei.2022.01.014)

[thumbnail of Cao-etal-JEI-2022-chlorine-and-sulphur-contents-on-the-release-of-potassium-compounds-during-biomass-combustion]
Preview
 Text. Filename: Cao_etal_JEI_2022_chlorine_and_sulphur_contents_on_the_release_of_potassium_compounds_during_biomass_combustion.pdf
Final Published Version
License: Creative Commons Attribution 4.0 logo
Download (3MB)| Preview

Abstract

In biomass combustion, understanding the effects of chlorine and sulphur release on the release of potassium compounds can help improve and predict the potassium release mechanisms. In this work, a kinetic model is applied to investigate the influences of S and Cl contents on the release of major potassium compounds during combustion. The results indicated that increasing the initial Cl from 3.8 × 10−5 mol/g biomass to 1.5 × 10−4 mol/g biomass promotes the maximum release of HCl and KCl by 518% and 273%, respectively, while inhibits the maximum release of KOH and K2SO4 by 99% and 68%, respectively. Cl in the biomass has directly influence the release of HCl, but indirectly impact the release of KCl; while its existence inhibits the formations of KOH and K2SO4 by adapting the contents of moisture, KO and KSO3. Raising the initial S from 2.7 × 10−5 mol/g biomass to 1.1 × 10−4 mol/g biomass only significantly affects the release of KOH and K2SO4 when temperature exceeds 1300 K, the maximum release of K2SO4 increased by 117%, while the release of KOH shifts from raise to decline. During combustion, S affects the formation and evaporation of K2SO4 by controlling the formations of intermediate S species. The results showed the model can accurately predict the major potassium compounds in various scenarios, and support the improvement of ash control technologies.

CORE (COnnecting REpositories)