(446d) Biomass Pyrolysis: Can a Single Severity Factor Describe the Effect of Pyrolysis Conditions on the Final Biochar Product? | AIChE

(446d) Biomass Pyrolysis: Can a Single Severity Factor Describe the Effect of Pyrolysis Conditions on the Final Biochar Product?


Zygourakis, K. - Presenter, Rice University
Gai, L., Rice University
The amendment of soils with biochar has been heralded as a sustainable method for increasing crop yield and preventing pollution problems caused by fertilizer runoff. However, the available experimental results are highly variable. While some studies report significant beneficial effects with up to 60% higher yield after biochar addition, other studies report that biochar amendments either has no net effect or can even lower agricultural productivity by up to 30% [1]. A major reason for this variability is biochar heterogeneity. Numerous biomass feedstocks were used in these studies to produce biochars in multiple types of reactors under varying temperature and oxygen conditions, leading to thousands of biochars with widely varying properties.

Understanding the heterogeneity of biochars is a major challenge for this research. Although the maximum temperature is often used as a metric of the charring intensity or severity of slow pyrolysis conditions, the literature is full of studies reporting that multiple factors control the properties of biochars produced from the same feedstock. These factors include the peak pyrolysis temperature, the treatment time at that temperature, the heating rate, the particle size, the presence or absence of oxygen and others. Since not all these conditions are carefully controlled or even reported, it becomes almost impossible to compare biochars produced under different environmental conditions or in different laboratories. And, the problem becomes even more difficult when different feedstocks are used.

This study presents an approach that combines experimental results and reaction modeling to relate some key properties of biochars to charring intensity metrics that combine (a) the full pyrolysis temperature history and (b) the kinetics of pyrolysis reactions. To achieve very accurate control of the temperature history of our biochars, we used a thermogravimetric analyzer (TGA) to produce 71 biochar samples from slash pine wood under nitrogen and a variety of slow pyrolysis conditions. Two different particle sizes (210-250 and 850-1000 microns) were used and the initial amount of feedstock varied between 130 and 230 mg. Proximate analysis was used to determine the fixed carbon content, volatiles and ash of the produced biochars. Additional TGA experiments were carried out to identify the network of pyrolysis reactions and estimate the kinetic constants. After running a series of step isothermal and/or constant heating rate TGA runs, the weight vs. time data sets were post-processed with an optimization technique to estimate (a) the reaction network (i.e. number of parallel and sequential pyrolysis reactions), and (b) the kinetic constants (i.e. activation energy, pre-exponential factor and order) of each reaction.

As expected, the peak pyrolysis temperature was not a good metric for characterizing total biochar yield, volatiles or fixed carbon content. Fixed C showed a good correlation with peak temperature only for the longest processing times (3 hours) used in our experiments. The charring intensity metric (CITT) defined as the integral of the temperature history T(t) of pyrolysis [2] also did a rather inadequate job in describing total biochar yield, volatiles or fixed carbon content. However, much better correlations were obtained when biochar properties were plotted vs. the charring severity function (CSF) defined as the integral over temperature of the kinetic rate constant of the reaction leading to the formation of char, the highly aromatic and crystalline biochar component that is the final product of the pyrolysis reactions.

Numerical simulations with the pine reaction network revealed that the same value of the CITT metric (the temperature-based charring intensity) can give us multiple concentrations of char and, thus, multiple total biochar yields, volatile contents etc. Clearly, we cannot infer the temperature history of a biochar from the properties of the final biochar product. We reached the same conclusion for the CSF metric. In the case of the CSF metric, however, our simulations revealed much smaller ranges of biochar properties for the same CSF value.

Our experiments also revealed the smaller particle size fraction (210-250 microns) contained a larger proportion of biomass that undergoes pyrolysis at lower temperatures. This was the result of the grinding. The different chemical composition of the two size fractions resulted in significant differences in the properties of the final biochar products, differences that could not have been predicted by the small variations in the effective heating rates resulting from the different particle sizes. The initial mass of the biochar sample also had a rather significant effect on the properties of the final biochar product due to the subtle temperature variations within the pyrolyzing biomass sample we have identified in earlier work.


[1] Crane-Droesch, A; S. Abiven; S. Jeffery; M.S. Torn. “Heterogeneous global crop yield response to biochar: a meta-regression analysis.” Environmental Research Letters 8 (2013) 044049.

[2] Pyle, L.A; W.C. Hockaday; T. Boutton; K. Zygourakis; C.A. Masiello, “Chemical and Isotopic Thresholds in Charring: Implications for the Interpretation of Charcoal Mass and Isotopic Data,” Environmental Science & Technology, 49 (24), 14057-14064 (2015).