Reverse engineering of biochar

Veronica L. Morales, Francisco J. Perez-Reche, Simona M. Hapca, Kelly L. Hanley, Johannes Lehmann, Wei Zhang

    Research output: Contribution to journalArticle

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    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.
    Original languageEnglish
    Pages (from-to)163–174
    Number of pages12
    JournalBioresource Technology
    Volume183
    Early online date18 Feb 2015
    DOIs
    Publication statusPublished - May 2015

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    Reverse engineering
    engineering
    metadata
    Metadata
    pyrolysis
    Chemical properties
    chemical property
    Biomass
    Pyrolysis
    Engineers
    biochar
    biomass
    temperature
    Temperature
    distribution
    effect

    Cite this

    Morales, V. L., Perez-Reche, F. J., Hapca, S. M., Hanley, K. L., Lehmann, J., & Zhang, W. (2015). Reverse engineering of biochar. Bioresource Technology, 183, 163–174. https://doi.org/10.1016/j.biortech.2015.02.043
    Morales, Veronica L. ; Perez-Reche, Francisco J. ; Hapca, Simona M. ; Hanley, Kelly L. ; Lehmann, Johannes ; Zhang, Wei. / Reverse engineering of biochar. In: Bioresource Technology. 2015 ; Vol. 183. pp. 163–174.
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    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.",
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    Morales, VL, Perez-Reche, FJ, Hapca, SM, Hanley, KL, Lehmann, J & Zhang, W 2015, 'Reverse engineering of biochar', Bioresource Technology, vol. 183, pp. 163–174. https://doi.org/10.1016/j.biortech.2015.02.043

    Reverse engineering of biochar. / Morales, Veronica L.; Perez-Reche, Francisco J.; Hapca, Simona M.; Hanley, Kelly L.; Lehmann, Johannes; Zhang, Wei.

    In: Bioresource Technology, Vol. 183, 05.2015, p. 163–174.

    Research output: Contribution to journalArticle

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    AU - Morales, Veronica L.

    AU - Perez-Reche, Francisco J.

    AU - Hapca, Simona M.

    AU - Hanley, Kelly L.

    AU - Lehmann, Johannes

    AU - Zhang, Wei

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    AB - 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.

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    Morales VL, Perez-Reche FJ, Hapca SM, Hanley KL, Lehmann J, Zhang W. Reverse engineering of biochar. Bioresource Technology. 2015 May;183:163–174. https://doi.org/10.1016/j.biortech.2015.02.043