Reverse engineering of biochar

Bioresource Technology
Verónica L MoralesWei Zhang

Abstract

This study underpins quantitative relationships that account for the combined effects that starting biomass and peak pyrolysis temperature have on physico-chemical properties of biochar. Meta-data was assembled from published data of diverse biochar samples (n=102) to (i) obtain networks of intercorrelated properties and (ii) derive models that predict biochar properties. Assembled correlation networks provide a qualitative overview of the combinations of biochar properties likely to occur in a sample. Generalized Linear Models are constructed to account for situations of varying complexity, including: dependence of biochar properties on single or multiple predictor variables, where dependence on multiple variables can have additive and/or interactive effects; non-linear relation between the response and predictors; and non-Gaussian data distributions. The web-tool Biochar Engineering implements the derived models to maximize their utility and distribution. Provided examples illustrate the practical use of the networks, models and web-tool to engineer biochars with prescribed properties desirable for hypothetical scenarios.

References

Jun 30, 2005·Environmental Science & Technology·Dongqiang ZhuJoseph J Pignatello
Jan 27, 2010·Environmental Science & Technology·Marco KeiluweitMarkus Kleber
Mar 9, 2010·Bioresource Technology·Xinde Cao, Willie Harris
Sep 28, 2010·Journal of Environmental Management·Mustafa K HossainPeter F Nelson
May 6, 2011·Environmental Science & Technology·Xinde CaoWillie Harris
Apr 10, 2012·Bioresource Technology·Akio EndersJohannes Lehmann
Jul 4, 2012·Journal of Environmental Quality·Kurt A SpokasKristine A Nichols
May 15, 2013·Journal of Hazardous Materials·Ling ZhaoAndrew Zimmerman

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Citations

Apr 12, 2016·Journal of Environmental Quality·Cheng-Hua LiuWei Zhang

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