Can inert pool models improve predictions of biochar long-term persistence in soils?

Abstract

The long-term persistence of biochar in soil is often predicted by extrapolating mineralization data from shortterm laboratory incubations. Single first-order, double first-order, triple first-order and power models have been employed for this purpose, all of which have an inherent assumption that biochar is biodegradable. However, recent insights challenge this assumption by suggesting that a large fraction of biochar is inert. If so, it would make sense to reflect this in the models used, by incorporating an inert carbon (C) pool. We hypothesized that such inert pool models would fit better to incubation data than existing models and give more reliable long-term predictions. We evaluated this by fitting the models to data from a recently compiled extensive dataset of biochar incubations. The inclusion of an inert pool enhanced the model fits over first-order models in most cases. However, inert pool models overestimated biochar persistence compared to the measured outcomes. By contrast, the double first-order model, which has been the most widely used to date, underestimated biochar persistence even in the short term. The power model in general outperformed all other models and gave the most reliable predictions, although it was sensitive to increasing or fluctuating mineralization rates in the datasets.

Keywords

Biochar carbon modeling; Biochar persistence; Carbon sequestration; Inert pool model

Published in

Geoderma
2024, volume: 452, article number: 117093

SLU Authors

• Li, Haichao

  • Department of Soil and Environment, Swedish University of Agricultural Sciences
    

• Azzi, Elias

  • Department of Energy and Technology, Swedish University of Agricultural Sciences
    

• Sundberg, Cecilia

  • Department of Energy and Technology, Swedish University of Agricultural Sciences
    

• Karltun, Erik

  • Department of Soil and Environment, Swedish University of Agricultural Sciences
    

• Cederlund, Harald

  • Department of Molecular Sciences, Swedish University of Agricultural Sciences
    

UKÄ Subject classification

Soil Science
Environmental Sciences

Publication identifier

• DOI: https://doi.org/10.1016/j.geoderma.2024.117093

Permanent link to this page (URI)

https://res.slu.se/id/publ/133169