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Optimisation of slow-pyrolysis process conditions to maximise char yield and heavy metal adsorption of biochar produced from different feedstocks

descriptionPublicationkeyboard_double_arrow_right Article , Journal 01 Aug 2016Publisher:Elsevier BVJournal:Bioresource Technology, volume 214, pages 574-581 (issn: 0960-8524,

Authors: Sian Thomas-Jones; William T. Perkins; A. Lewys-James; Joe Gallagher; S. Rao Ravella; Edward Hodgson;

doi: 10.1016/j.biortech.2016.05.009

pmid: 27179953

Optimisation of slow-pyrolysis process conditions to maximise char yield and heavy metal adsorption of biochar produced from different feedstocks

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Abstract

The objective of this work was to identify biomass feedstocks and optimum pyrolysis process conditions to produce a biochar capable of adsorbing metals from polluted groundwater. Taguchi experimental design was used to determine the effects of slow-pyrolysis process conditions on char yield and zinc adsorption. Treatments were repeated using six candidate feedstocks (Lolium perenne, Lolium perenne fibre, Miscanthus x giganteus, Salix viminalis, Fraxinus excelsior and Picea sitchensis) and the resultant chars were tested for metal adsorption performance. Chars produced from L. perenne and its extracted fibre displayed the greatest zinc adsorption performance and removed 83.27-92.96% respectively. Optimum process conditions in terms of both char yield and zinc adsorption performance were achieved from slow-pyrolysis at 300°C for 2h using a feedstock with a particle size of less than 1mm.

Related Organizations

Institute of Biological, Environmental and Rural Sciences
United Kingdom
Aberystwyth University
United Kingdom

Keywords

Hot Temperature, Salix, Zinc, Bioreactors, Fraxinus, Charcoal, Metals, Heavy, Lolium, Water Pollutants, Adsorption, Biomass, Picea, Environmental Pollution, Groundwater, Environmental Restoration and Remediation

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	63
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 1%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 10%