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Biochar Carbon Stability Test Method
:
An assessment of methods to determine biochar
carbon stability. International Biochar Initiative. September 20, 2013.
1
Biochar Carbon Stability Test Method: An assessment of methods to determine
biochar carbon stability
A. Budai
1
; A. R. Zimmerman
2
; A.L. Cowie
3
; J.B.W. Webber
4
; B.P. Singh
5
; B. Glaser
6
; C. A. Masiello
7
; D.
Andersson
8
; F. Shields
9
; J. Lehmann
10
; M. Camps Arbestain
11
; M. Williams
12
; S. Sohi
13
; S. Joseph
14
Abstract
Twenty seven methods currently used to characterize biochar were assessed in terms of their usefulness
to determine the stability of biochar carbon in the environment. The International Biochar Initiative (IBI),
which led the effort, gathered fourteen world-class experts in different fields of biochar relevant to
stability, who guided the process for obtaining a simple, yet reliable, measure for biochar stability.
Important requisites were defined for the test, including cost, repeatability and availability.
Identification of a cost-effective, scientifically valid test to measure the stable carbon component of
biochar is imperative to distinguish biochar from non-biochar (non-stable) materials, and to develop a
biochar offset protocol for carbon markets. The stability of biochar carbon in soils makes it a highly
promising product for consideration as a strategy for climate change mitigation. The definition of the
variable BC+100, which stands for the amount of biochar carbon that is expected to remain stable after
100 years, along with predictions of stability based on simple (Alpha) and more sophisticated (Beta)
1
Norwegian Institute for Agricultural and Environmental Research – Bioforsk, Høgskoleveien 7, N-1432 Ås, Norway
2
Department of Geological Science, University of Florida, 241 Williamson Hall, P. O. Box 112120, Gainesville,
Florida 32611-2120, United States
3
Rural Climate Solutions, University of New England, NSW Department of Primary Industries, Armidale 2351,
Australia
4
School of Physical Sciences, University of Kent, CT2 7NH, UK
5
NSW Department of Primary Industries, PO Box 100, Beecroft NSW 2119, Australia
6
Soil Biogeochemistry, Martin-Luther-Univ. Halle-Wittenberg, von-Seckendorff-Platz 3, 06120 Halle, Germany
7
Department of Earth Science, 6100 Main St. MS 126, Rice University, Houston, TX 77005, United States
8
EcoEra, Orkestergatan 21 181, 42139 Göteborg, Sweden
9
Control Laboratories, Inc., 42 Hangar Way, Watsonville, CA 95076, United States
10
Department of Crop and Soil Sciences, Cornell University, Ithaca, NY 14853, United States
11
Institute of Natural Resources, Massey University, Palmerston North 4442, New Zealand
12
Biochar Solutions Inc., PO Box 2048, Carbondale, CO 81623, United States
13
UK Biochar Research Centre (UKBRC), School of GeoSciences, University of Edinburgh, Crew Building, The King's
Buildings, Edinburgh, EH9 3JN, UK
14
School of Material Science and Engineering, University of New South Wales, 2052 Sydney, Australia
Biochar Carbon Stability Test Method
:
An assessment of methods to determine biochar
carbon stability. International Biochar Initiative. September 20, 2013.
2
methods, allowed to correlate a molar ratio (H/Corg) to the relative stability of biochar. The process for
identifying the Biochar Carbon Stability Test Method is summarized here, and the method itself is
available as a separate, technical document.
1. Introduction
The stability of biochar is of fundamental importance in the context of biochar use for environmental
management for two primary reasons: first, stability determines how long carbon applied to soil, as
biochar, will remain in soil and contribute to the mitigation of climate change; second, stability will
determine how long biochar will continue to provide benefits to soil, plant, and water quality (Lehmann
et al., 2006). Biochar production and application to soil can be, in many situations, a viable strategy for
climate change mitigation. Conversion of biomass C to biochar C via pyrolysis can lead to sequestration
of about 50% of the initial C compared to the low amounts retained after burning (3%) and biological
decomposition (<10–20% after 5–10 years) (Lehmann et al, 2006, figure 1), with the entirety of
uncharred biomass being most likely decomposed after a century, which is a relevant time frame for the
purpose of the stability test, as presented in subsequent sections.
Figure 1. Schematic of biochar and biomass degradation patterns. Source: Lehmann et al. (2006)
Biochar has been found to have a high stability or resistance to decomposition in soil. The Mean
Residence Time (MRT) of different biochars has been found to fall mostly in the centennial to millennial
scales, as shown in table 1, with some studies showing estimations of decadal scales.
Table 1. Mean Residence Time (MRT) of biochar across studies.
Publication Scale of estimated MRT (years)
Masiello and Druffel, 1998 Millennial (2,400 – 13,900)
Schmidt et al., 2002 Millennial (1,160 – 5,040)
Cheng et al., 2006 Millennial (1,000)
Biochar Carbon Stability Test Method
:
An assessment of methods to determine biochar
carbon stability. International Biochar Initiative. September 20, 2013.
3
Laird, 2008 Millennial (1,000's)
Cheng et al., 2008 Millennial (1,335)
Kuzyakov et al., 2009 Millennial (2,000)
Major et al., 2010 Millennial (3,264)
Novak et al., 2010 Millennial (1,400-51,000)
Liang et al., 2008 Centennial to millennial (100-10,000's)
Zimmerman, 2010 Centennial to millennial (100-100,000)
Baldock and Smernik, 2002 Centennial (100-500)
Lehmann et al., 2006 Centennial (100’s-1,000's)
Hammes et al., 2008 Centennial (200-600)
Schneider et al., 2011 Centennial (100’s)
Hamer et al. 2004 Decadal (10's)
Nguyen et al. 2008 Decadal (10's)
Objective
The goal of this effort was to develop a method for testing and quantifying the stability of carbon in
biochar, by specifying the amount of C that is predicted to remain present in soil 100 years
15
after land
application, which for the purposes of the stability test is termed BC
+100
. The fraction of carbon in
biochar that decomposes during the same time period is termed BC
-100
. Selection of methods was based
on the following:
• Only analytical tests for biochar stability that have been published in the peer-reviewed literature
before final issuance of this document were considered;
• Sampling procedures and test methods had to be considered cost-effective; and
• All assumptions made during the development of this test method followed the principle of
conservativeness, i.e. the methodology should in every instance utilize conservative approaches in
order to avoid over-estimating the stability of biochar carbon.
Scope of Work
The effort was built upon previous work completed by The International Biochar Initiative (IBI) to
develop “Standardized product definition and product testing guidelines for Biochar that is used in
soil” (aka IBI Biochar Standards). The present document constrains its scope to materials with
properties that satisfy the criteria for biochar as defined by the IBI Standards.
15
Global Warming Potential (GWP) of Greenhouse gases (GHG) is assessed over a 100-year time horizon. One
hundred years is commonly used to define permanence in carbon offset markets (e.g. Mechanisms under the
Kyoto Protocol (Clean Development Mechanism - CDM, Joint Implementation - JI), Australia’s Carbon Farming
Initiative).
Biochar Carbon Stability Test Method
:
An assessment of methods to determine biochar
carbon stability. International Biochar Initiative. September 20, 2013.
4
This test method considers only the carbon stabilized in biochar via pyrolysis. Neither biochar impacts
on plant productivity nor any effects on native soil carbon stocks or vice versa (i.e. positive or negative
priming) are included (Figure 2) because scientific evidence is insufficient at this time to determine the
direction and magnitude of these processes. Biochar may stabilize native soil organic carbon by sorbing
organic compounds (Smernik, 2009). There are, however, cases where biochar addition to soil can
produce an undesirable "positive priming effect” (Hamer et al., 2004; Wardle et al., 2008; Singh et al.,
2010; Kuzyakov, 2010; Zimmerman et al., 2011; Cross and Sohi, 2011; Woolf and Lehmann, 2012; Singh
et al., 2012), causing the release of additional CO
2
from soil. However, Woolf and Lehmann (2012)
estimated that no more than 3 to 4% of initial non-pyrogenic SOC might be mineralized due to priming
by biochar over 100 years. Even though this effect may be small compared to a possible negative
priming effect, neither effect was included in the methodology. Further support for this decision is
detailed in the Supplementary Information section.
Figure 2. Scope of work for the test method.
Even though there is evidence of increased net primary productivity (NPP) of soils after biochar addition
(Lehman et al., 2006; Major et al., 2010), carbon sequestration due to enhanced biomass production
was not included because insufficient data are available to quantify the effects of biochar additions to
soil on crop productivity, which is likely to vary widely between soil types, feedstock and environments
(Van Zweiten et al., 2010; Jeffrey et al., 2011). Additionally, the longevity of the impacts of biochar on
NPP is unknown, as most experiments have been short-term. Furthermore, C sequestered in biomass of
annual crops and pasture cannot be considered stable, mainly due to its fast turnover rate. The decision
not to include these also reflects the conservative approach of this effort.
Biochar Carbon Stability Test Method
:
An assessment of methods to determine biochar
carbon stability. International Biochar Initiative. September 20, 2013.
5
2. Definitions
Types of methods
Through a review made by the Expert Panel consisting of fourteen world-class biochar experts, test
methods were categorized into three groups: (1) Alpha methods, which may allow routine estimation of
the BC
+100
at minimal costs; (2) Beta methods, which directly quantify BC
+100
and may be used to
calibrate Alpha methods; and (3) Gamma methods, which may provide the physiochemical underpinning
for the Alpha and Beta methods. These categories of methods are justified and described below.
2.1 Alpha methods
Alpha methods are defined as those which provide a simple and reliable measure of the relative stability
of carbon in biochar, that are readily available, at a cost of less than 100 US dollars (USD) (defined as
feasible by the Expert Panel) and within a timeframe of minutes or hours to, at maximum, a few days.
Alpha methods are intended to be undertaken by a certified laboratory to be used by biochar producers.
Alpha methods do not provide an absolute measure of stability; rather, they assess a property (usually
chemical or physical) that is related to stability. Alpha methods must be calibrated through comparison
with Beta and/or Gamma methods.
Some Alpha methods have already been developed (“Alpha-1”) and were found to be strongly related to
the properties determined by the Beta and Gamma methods. It is expected that more Alpha methods
will emerge as biochar stability research continues to develop, which could be placed in a category
called “Alpha-2” methods.
The results of any Alpha method must correlate – ideally linearly – with results of at least one Beta
(calibration) method, as well as those of the applicable Gamma methods. Some possible Alpha-1
methods are briefly described and discussed below.
Hydrogen to organic Carbon molar ratio (H:C
org
) (Enders et al., 2012; IBI, 2012) and Oxygen to Carbon
molar ratio (O:C) (Spokas, 2010): Both ratios reflect physical-chemical properties of biochar related to
stability, as the proportion of elemental compounds (H and O) relative to carbon (C) present in biochar.
These elemental constituents of biochar can be measured routinely, using an elemental analyzer, based
on the manufacturer’s protocol.
Increasing production temperatures lead to lower H/C and O/C ratios (Krull et al., 2009; Spokas, 2010),
as the abundance of C relative to H and O increases during the pyrolysis process (Figure 3).
Biochar Carbon Stability Test Method
:
An assessment of methods to determine biochar
carbon stability. International Biochar Initiative. September 20, 2013.
6
Figure 3. Changes in biochar elemental composition with varying pyrolysis temperatures. Source: Krull et al. (2009).
Materials with low H/C and O/C values are graphite-like materials (i.e. soot, black carbon, activated
carbon), which exhibit high stability compared to uncharred biomass, which possesses high H/C and O/C
values (Figure 4) and low resistance to degradation. Hence, as biochars resemble graphite-like materials,
characterized by low ratios, they are expected to be more stable or inert, and less prone to degradation
(Masiello, 2004).
Figure 4. Physical characteristics and ratios related to biochar stability. Source: Adjusted from Hammes et al. (2007)
These two ratios can be plotted in a two-dimensional Van Krevelen diagram, which is a graphical
representation of biochars based on elemental composition. In a study by Schimmelpfenning and Glaser
(2012), different biochars are characterized based on the relation between the measured H/C and the
O/C ratios, and compared to different types of coals (figure 5).
Biochar Carbon Stability Test Method
:
An assessment of methods to determine biochar
carbon stability. International Biochar Initiative. September 20, 2013.
7
Figure 5. Van Krevelen diagram. Source: Schimmelpfennig and Glaser (2012)
The use of the molar H/C
org
ratio is proposed instead of the H/C ratio, as the former does not include
inorganic C present in biochar mostly in the form of carbonates (e.g. calcite and, to some extent,
dolomite) (Schumacher, 2002) and is not part of the condensed aromatic structure of C and thus is not
expected to remain in soil on a centennial scale.
Volatile matter content: The content of volatile matter (VM) in biochar has also been observed to be
related to biochar stability, calculated as mean residence time or half life (Enders et al., 2012;
Zimmerman, 2010; Spokas, 2010). Volatile matter content can be measured through different paths,
usually thermal treatment, e.g. the ASTM method D1762-84
16
(2007) (CDM SSM AMS.III-L; Major et al.,
2010b; DeGryze et al. 2010; Enders et al., 2012), also termed proximate analysis, which covers the
determination of moisture, volatile matter, and ash in a variety of materials.
VM is well correlated with elemental ratios (O/C and H/C), as shown in Figure 6, so it could be expected
to be a good predictor of biochar carbon stability. However, Spokas (2010) found a weak correlation
between VM content and the estimated biochar half-life using data from 37 biochar sample
measurements from different studies (Figure 7). Therefore volatile matter is discarded as a well-suited
predictor of stability.
16
Chemical analysis of wood charcoal
Biochar Carbon Stability Test Method
:
An assessment of methods to determine biochar
carbon stability. International Biochar Initiative. September 20, 2013.
8
Figure 6. Correlation of volatile matter and O/C molar ratio. Source: Spokas (2010) (R
2
= 0.76)
Figure 7. Comparison of volatile matter content with estimated biochar half life. Source: Spokas (2010) (R
2
not available)
2.2 Beta methods
Beta methods are those that (1) directly quantify BC loss over a period of time, and (2) demonstrate a
relationship with results of an Alpha method (a more conveniently measured parameter) and Gamma
values for a range of biochar types. At present, the Beta methods in use are laboratory and field-based
incubations as well as field chronosequence measurements, all of which must be combined with
modeling to estimate biochar C lost over the specific time interval of 100 years (BC
-100
).
Beta methods provide an absolute measure for the carbon that will remain in biochar for at least 100
years (at minimum that is, a conservative estimate of stability). Beta methods are not widely available or
obtainable at a cost or within the timeframes specified for Alpha methods. It is also not feasible to have
Biochar Carbon Stability Test Method
:
An assessment of methods to determine biochar
carbon stability. International Biochar Initiative. September 20, 2013.
9
registry of direct observations of biochar for 100 years, in order to demonstrate the suitability of a Beta
method. Some Beta methods have been published and are presented below.
Incubation and field studies: Incubation studies of biochar under laboratory conditions (Zimmerman,
2010; Singh, 2012) and studies of biochar in soils (Major et al., 2010b; Cheng et al., 2008; Liang et al.,
2008; Kuzyakov et al., 2009) have recorded temporal biochar decomposition patterns (see figure 8).
Observations derived from incubation experiments are critical to the understanding of biochar behavior
and, therefore, stability. The incubations (3-5 years of duration) were undertaken in controlled
environmental conditions (e.g., moisture, temperature) and with addition of microbial inoculation and
nutrient solution in order to promote decomposition. Because these are closed systems and non-variant
conditions, estimates of stability based on these measurements can be considered conservative.
Mineralization rates have been observed to decrease until reaching a constant rate at around 600-700
days, indicating that remaining biochar carbon may exhibit a certain degree of stability. In order to
quantify stability a very conservative approach must be used for extrapolating measurements from
short- to medium-term studies to 100 years, which is done in this report, as explained in subsequent
sections.
Figure 8. Biochar mineralization rate. Source: Kuzyakov et al., 2009 (3.2 year incubation)
Both two-component (double exponential) models (e.g. Cheng et al., 2008; Zimmerman et al., 2011;
Singh et al., 2012) and power regression models (e.g. Zimmerman 2010) have been used to extrapolate
Biochar Carbon Stability Test Method
:
An assessment of methods to determine biochar
carbon stability. International Biochar Initiative. September 20, 2013.
10
measurements from incubations of freshly produced and aged biochar to predict the longer-term
stability of biochar. The second model may better represent the physical characteristics of biochar and
assumes an exponentially decreasing degradation rate, whereas the first assumes biochar is composed
of only two fractions – labile and stable. Thus, the two-component model is likely to underestimate
stability of biochar C and will yield a more conservative estimate of C sequestration, since the greater
the number of pools that are added, the greater predictions of stability will be.
Chronosquences: A biochar C loss rate can also be determined by using measurements of biochar
distribution from sites that vary in time interval since biochar was applied (a chronosequence).
However, results of these types of studies, thus far, range from no to complete C loss, and are likely
affected by erosion or translocation (Nguyen et al. 2008; Major et al. 2010b; Foereid et al. 2011).
2.3 Gamma methods
Gamma methods measure molecular properties relevant to biochar stability and can verify the
legitimacy of the Alpha and Beta methods through establishing strong relationships between the
properties measured by them. Thus, Gamma methods would provide safeguard against selection of
Alpha or Beta methods based on empirical correlations that do not reflect a functional relationship.
Some Gamma methods are briefly described below.
NMR spectroscopy (Brewer et al., 2011; McBeath et al., 2011): Direct polarization
13
C nuclear magnetic
resonance spectroscopy with magic angle spinning (DP/MAS
13
C NMR) is a well-established technique
for measuring the aromaticity (fraction of total carbon that is aromatic) of biochars. Aromaticity is
strnogly correlated to C stability. The
13
C NMR spectrum of aryl carbon (i.e. derived from condensed
aromatic carbon) is very characteristic, comprising a single resonance centered at approximately 130
ppm. Spinning side bands associated with the presence of aromatic carbon can be detected.
Pyrolysis Gas Chromatography mass spectrometry (Py GC/MS) – analytical pyrolysis (Kaal et al., 2008,
2009, 2012; Fabbri et al., 2012): Analytical pyrolysis is a technique that uses controlled invasive thermal
degradation to break down large molecules for identification. The resultant pyrolysis products are
separated and identified using gas chromatography and mass spectroscopy. The sum of the most
abundant fingerprints of charred material in pyrograms (i.e., monoaromatic hydrocarbons, polyaromatic
hydrocarbons, benzonitriles/total quantified peak area) is related to the proportion of condensed
aromatic carbon present in biochar.
Ring Current NMR (McBeath and Smernik, 2009; McBeath et al., 2011): This method gauges the degree
of aromatic condensation of biochars. It involves sorbing
13
C-labeled benzene to the biochar structure.
The
13
C NMR chemical shift of the sorbed benzene (relative to straight
13
C-benzene) is affected by
diamagnetic ring currents that are induced in the conjugated aromatic structures when the biochar is
placed in a magnetic field. These ring currents increase in magnitude with the increasing extent of
aromatic condensation.
Biochar Carbon Stability Test Method
:
An assessment of methods to determine biochar
carbon stability. International Biochar Initiative. September 20, 2013.
11
Benzene polycarboxylic acids (BPCA) (Glaser et al., 1998; Brodowski et al., 2005; Schneider et al., 2010):
The BPCA are molecules formed during the nitric acid oxidation of biochar. The maximum number of
carboxylic groups reflects the number of quaternary C atoms initially present. Biochar with a higher
degree of condensation should result in higher proportion of the penta (B5CA) and hexacarboxylic
(B6CA) benzoic acids relative to BPCAs with less quaternary carbon atoms (B3CA, B4CA). The ratio of
B6CA-C/total BPCA-C thus is positively related to the degree of condensed aromatic C present in
biochar; the larger the ratio the greater the aromaticity. The concentration of the sum of BPCA can be
used to quantify biochar in the environment, e.g. in soil amended with pure biochar or in mixture with
other organic materials.
Gamma methods are not expected to be used by biochar producers for determining biochar C stability.
This is mainly because of the high level of technical expertise required to perform these tests,
specialized expensive instruments, high costs per analysis, and low availability. Instead, Gamma
methods are intended to be used by scientists in order to calibrate Alpha and Beta methods for iterative
improvement of a simple biochar C stability test method.
3. Material and methods – Biochar Carbon Stability Test Method selection process
Twenty-eight test methodologies currently used to assess biochar characteristics, mostly related to
stability, were reviewed and evaluated by the Expert Panel. The process by which these were evaluated,
the criteria used for this purpose, the categories defined, and other details are presented in Section 2 of
the Supplementary Information. H/C
org
was selected as the preferred Alpha method for being cost-
effective, simple, replicable and published in peer-reviewed literature, in combination with the use of
modeled data from observations of carbon degradation from 3 to 5-year incubation studies
(Zimmerman, 2010 as extended in Zimmerman and Gao, 2013; and Singh et al., 2012) as the Beta
method used to calibrate the predictions and determine BC
+100
.
4. Results
In support of the selection of the proposed Alpha and Beta method, a strong relationship was found
between the H/ C
org
values of 31 biochar samples from the two mentioned studies and the predicted
BC
+100
values, based on the two-component model (figure 9).
The observed behavior for carbon in each of the 31 samples followed the pattern shown in figure 8,
where after some months, the turnover rate became stabilized, exhibiting little carbon loss. Q10
adjustments for harmonizing the data between both studies were not made, but if a low value were to
be used, e.g. Q10 = 2, harmonizing the data from 30°C and lack of soil minerals (Zimmerman, 2010) to
22°C (Singh et al., 2012), would yield higher BC
+100
values than the ones reported, thus complying with
the conservative principle. Grouping the predicted BC
+100
values, based on the two-component model,
results in figure 9.
Biochar Carbon Stability Test Method
:
An assessment of methods to determine biochar
carbon stability. International Biochar Initiative. September 20, 2013.
12
Figure 9. The correlation between H/ C
org
and biochar C predicted to remain after 100 years as predicted by a two-
component model (i.e. BC
+100
) was produced using data and calculations from Singh et al., 2012 (closed circles) and
Zimmerman, 2010 as extended in Zimmerman and Gao, 2013 (open circles)..
The vertical axis represents the percentage of organic carbon present in biochar that is expected to
remain in soil after 100 years. Thus, a biochar sample with a H/Corg value of 0.6 would be predicted to
have a BC
+100
of 65.6% indicating that 65.6% of the organic carbon measured in biochar will likely remain
stable for at least a century. The statistical basis for this inference is presented in the following.
The blue and red lines in the plot represent the 95% confidence upper and lower intervals, and the 95%
prediction intervals, respectively. The correlation measure shows a modest value (R
2
= 0.5). However, as
biochar is composed of various constituents, it is notable that this one parameter (H/C
org
) explains 50%
of the variation in the carbon stability of the biochar samples assessed. Furthermore, every individual
sample but one falls within the 95% prediction interval, which predicts the range in which values of
future samples will fall. Additionally, a p-value below 0.0001 indicates the strong statistical significance
of the calculations. Thus, this regression model is judged adequate for determining BC
+100
based on
H/C
org
measurements.
Defining cut-offs every 0.1 for H/C
org
values in the range of 0.4 to 0.7 for the biochar samples, the
equivalent mean, upper limit and lower limit BC
+100
values are obtained for analysis (table 2). Two
distinct levels can be evidenced: for an H/C
org
value of 0.4, the lower limit of the confidence interval of
BC
+100
is above 70% (in a range of 88-72%). From this it is concluded that at least 70% of the C
org
measured in biochar is predicted to remain in soil for 100 years with 95% confidence, for an H/C
org
value
lower or equal to 0.4. Confidence intervals are considered over prediction intervals, as they exhibit the
probability that they will contain the true predicted parameter value, for the selected confidence level.
Biochar Carbon Stability Test Method
:
An assessment of methods to determine biochar
carbon stability. International Biochar Initiative. September 20, 2013.
13
On the other hand, for an H/C
org
value of 0.7, a BC
+100
of 50% can be conservatively expected. If a cut-off
of BC
+100
is defined at 50%, most (17 out of 19) of the observed values in the 0.4-0.7 H/C
org
range would
fall above this point, therefore underestimating stability. Thus, cut-offs at values of H/C
org
of 0.4 and 0.7
are defined to characterize “highly stable” (BC
+100
of 70%) and “stable” (BC
+100
of 50%) C
org
in biochars,
respectively.
Table 2. H/C
org
and BC
+100
equivalences at 95% confidence
BC
+100
(%)
H/C
org
Mean
Lower limit Upper limit Chosen value
0.4
80.5
72.6
88.2
70
0.5
73.1
67.1
78.9
50
0.6
65.6
60.5
70.6
50
0.7
58.2
52.5
63.8
50
Biochar materials that obtain H/C
org
values higher than 0.7 are not considered to be biochar, as these
materials would not meet the definition of biochar as defined by the IBI Standards.
5. Discussion
The comments in this section seek to provide guidance as to the possible next steps for the continuous
improvement of the predictability of different Alpha, Beta and Gamma methods.
The members of the Expert Panel agreed upon the necessity of continued collaboration to further refine
the proposed method. There emerged an interest to start the exchange of biochar samples to run
different laboratory tests in the form of a ring trial. Additional funding would be needed for this very
desirable initiative. As stated earlier in this document, as new findings emerge, they should be
incorporated into the proposed methodology, with the aim of obtaining the most precise and, at the
same time, economically feasible method for determining BC
+100.
5.1 Fate of biochar
5.1.1 Biochar transport mechanisms
The physical movement of biochar away from the point of soil application appears to occur at a
similar rate to or possibly faster than for other organic carbon in soil (Rumpel et al., 2005;
Guggenberger et al., 2008; Major et al., 2010). Eroded biochar C is considered to remain
sequestered as it is typically buried in lower horizons of soil or in lake or ocean sediments
(France-Lanord and Derry, 1997; Galy et al., 2007; Van Oost et al., 2007).
Biochar can move from the topsoil into the subsoil i.e. translocation (Major et al., 2010). It is not
clear whether this transport occurs at the same rate as other organic matter in soil (Leifeld,
Biochar Carbon Stability Test Method
:
An assessment of methods to determine biochar
carbon stability. International Biochar Initiative. September 20, 2013.
14
2007). It may be assumed that different pathways operate for particulate biochars in
comparison to dissolved organic C (Zhang et al., 2010). Biochar in subsoils can be considered
stabilized to a greater degree than biochar in topsoils, as evidenced by the great age of organic
carbon found in subsoils in general, and because microbial activity sharply decreases with depth
(Rumpel and Koegel-Knabner, 2011).
Some studies indicate that a significant fraction of land-applied biochar can be exported within
the first few years following amendment, even when biochar is incorporated into soil (Rumpel et
al., 2009; Major et al., 2010). However, physical transport of biochar offsite does not necessarily
result in a CO
2
flux to the atmosphere, as the final fate of charcoal erosion from the land surface
may be deposition in marine sediments. The intrinsic refractivity of charcoal in marine
environments may lead to its long-term storage in sediments (Masiello, 2004). It is reasonable
to assume that mobilized biochar does not decompose, and remains a long-term carbon sink as
it transits to the sea floor.
5.1.2 Combustion
Biochar can be combusted, either unintentionally due to inappropriate handling during
transport, storage or application, or intentionally, by diverting it from the intended land
application to a use as fuel, since many biochars can possess a significant energy value. This
potential will need to be managed within the Biochar Protocol development. Another
theoretical oxidation by combustion is through vegetation fires. Re-burning of previously
deposited pyrogenic carbon from vegetation fires has been observed in Mediterranean forests
(Knicker et al., 2006). It is unlikely that vegetation fires will lead to a significant re-burning of
applied biochar that is incorporated into the soil. Temperatures during fires decrease
dramatically with depth, and mixtures of biochar and soil will exhibit no greater combustibility
than that of other organic matter in soil.
5.2 Resolution of information on carbon stability
Although there is a clear correlation between the H/C
org
ratios and BC
+100
over a wide range of values
at a 95% confidence level (Fig. 9), variability will remain in the stability predictions. Future
refinement and a greater data set with longer-term incubation experiments, including field data, will
allow better constraint of the relationship. For the purpose of this first methodology, as mentioned
previously, a very conservative approach was chosen (e.g. via the selection of the model to obtain
BC
+100
and the conditions of the incubation experiments) and thus predictability can be further
improved over time.
The second analytical constraint stems from the quantification of inorganic and organic C (and H) in
the biochar. Some uncertainties in the standard method using acidification and repeated
determination of total C led to an initial recommendation of restricting the methodology to class 1
Biochar Carbon Stability Test Method
:
An assessment of methods to determine biochar
carbon stability. International Biochar Initiative. September 20, 2013.
15
biochars (as defined in the IBI Biochar Standards). For these biochars, which by definition contain
more than 60% organic carbon, the proportion of inorganic carbon is likely negligible and organic
carbon is roughly equivalent to total carbon. However, data analysis determined that this restriction
yielded no change in the prediction results. Nevertheless, a method for calculating inorganic carbon
in the sample was included, allowing the calculation of organic carbon by difference to total carbon.
This exemplifies how the conservative approach mentioned was operationalized in the decisions
made to arrive at a test method.
5.3 Future improvements to Alpha, Beta and Gamma methods
Alpha: The choice amongst routine analytical procedures that would reflect a robust, repeatable,
and analytically sound result was limited to those that had been used in the peer-reviewed
literature. These included the Standard Test Method for Chemical Analysis of Wood Charcoal, so-
called proximate analysis (ASTM-D1762-84, 2007) and elemental ratios of O, H and C. Structural
information beyond stoichiometric relationships between elements may provide better estimates of
stability and may be attainable through spectroscopy or automated thermogravimetry. However,
these have not been sufficiently developed or are not available at a sufficiently low cost or time
requirement to be included at present, or both.
Beta: Longer periods of observation will likely provide evidence to improve precision of predictions
of BC
+100
(Lehmann et al., 2009; Zimmerman et al., 2012), likely increasing the stable carbon
component calculated, since the current proposed method is highly conservative. The known long-
term incubations experiments will continue and a revised future methodology will reflect
improvements based on longer periods of observation. Only a few long-term field experiments have
been published beyond a few years (Major et al., 2010), but are expected to be available for up to
10 year-periods in the coming years. However, pitfalls of field experiments are that these often do
not distinguish between mineralization and physical loss by erosion and leaching, and the
capabilities to estimate these differential losses over long periods of time are typically low.
Therefore, these experiments often give at best a minimum mean residence time. A third approach
is the use of aged biochars as proxies for biochar that has weathered in soil for long periods of time.
Examples are biochar-type materials from Terra Preta (Liang et al., 2008), from charcoal storage
sites (Cheng et al., 2010) or possibly archaeological deposits. The challenge using this approach is to
develop adequate proxies for the starting material to assess its properties.
Gamma: Great progress has been made over the past years in understanding the change in the
chemical form of fused aromatic carbons beyond aromaticity. Advancement in this area may come
from NMR studies (Mao et al., 2012), measurements of adsorbed C-13-benzene (McBeath et al.,
2012) and wet chemical methods such as BPCA (Glaser et al., 1998; Brodowski et al., 2005;
Schneider et al., 2010). To improve predictability of biochar decomposition, next steps may include
systematically relating structural information to improved Alpha-type methods, as defined in this
document
Biochar Carbon Stability Test Method
:
An assessment of methods to determine biochar
carbon stability. International Biochar Initiative. September 20, 2013.
16
6. Conclusions
One of the most important properties of biochar – if not the most important one – is its stability, as it
allows all other ancillary environmental benefits, especially in the agronomic field (i.e. soil amelioration),
to persist in time. Mainly, the stability of the carbon component in biochar makes it particularly useful as
a long-term climate change mitigation strategy, and thus having a scientifically valid methodology for
the quantification of stable carbon will allow unlocking the potential benefits of biochar. That is what
makes this effort, oriented by an Expert Panel, ground-breaking, and as such can contribute to the
development of policies and programs that promote the deployment of biochar systems.
Given that this is the first such methodology to be developed, and that the science is rapidly evolving,
the Panel necessarily devised a conservative methodology that is likely to underestimate the amount of
stable carbon in biochar to a period of 100 years. But with continued research and development, some
of which is described herein, we are confident that the test methodology will grow more robust and
more rigorous over time, allowing for a more complete and precise estimation of stable carbon in
biochar.
Acknowledgements
The International Biochar Initiative wishes to express its gratitude toward Dr. Dominic Woolf from
Cornell University and PhD student Tao Wang from Massey University, who assisted in the development
of the test method, dedicating their scarce time and vast expertise to this effort, in the pursuit of the
continuity of the development of biochar science, in order to translate it into action.
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Supplementary Information Section 1
Priming of SOC mineralization by black carbon
Priming can be defined as any change (positive or negative, persistent or ephemeral) in the turnover
rate of soil organic matter caused by the addition of a new substrate (Woolf and Lehmann 2012).
Increased or decreased turnover rates are defined as positive or negative priming, respectively. Only
positive priming is considered in this assessment protocol, because this is a risk factor that might reduce
the net C sequestration of biochar systems. Negative priming is not considered here due to application
of the precautionary principle, whereby detrimental feedbacks should be included in the assessment
protocol if there exists a non-negligible probability that they may be realised, whereas beneficial
feedbacks should not be included unless they are unequivocal.
Addition of biochar to soils has been shown to alter the mineralization rate of non-pyrogenic SOC
(npSOC). Positive priming of npSOC has been reported by Abiven and Andreoli (2010); Cross and Sohi
(2011); Hamer et al. (2004); Jones et al. (2011); Keith et al. (2011); Liang et al. (2010); Luo et al. (2011);
Novak et al. (2010); Spokas and Reicosky (2009); Wardle et al. (2008); Zimmerman et al. (2011).
Negative priming of npSOC mineralization has been reported by Keith et al. (2011); Kuzyakov et al.
(2009); Liang et al. (2010); Spokas and Reicosky (2009); and Zimmerman et al. (2011). Zimmerman et al.
(2011) found that initial positive priming gave way to net negative priming over time. Where it has been
possible to discriminate between labile- and stable-SOC decomposition, either no priming of stable SOC
(Cross and Sohi 2011; Jones et al. 2011) or an increase in the stabilized SOC fraction (i.e. negative
priming; Liang et al. 2010) was observed.
Only a few studies have allowed discrimination between priming of labile- or stable-npSOC
decomposition. Where it has been possible to discriminate between labile- and stable-npSOC
decomposition, either zero or negative priming of stable npSOC has been reported. Liang et al. (2010)
added organic matter (AOM) with a distinct
13
C isotopic signature (from a C
4
plant) to BC-rich Anthrosols
and BC-poor adjacent soils. They found a 19–340% increase in AOM-carbon in the organo-mineral
fraction (assumed to indicate an increase in C stabilised by mineral associations) after 1.5 yr in BC-rich
relative to adjacent soils. Cross and Sohi (2011) compared the priming effect in a silty-clay loam from
Rothamsted Research, U.K., where three different management practices had been maintained for >60
years: (1) bare fallow (soil kept completely bare with regular cultivation), (2) continuous arable (wheat)
and (3) managed grassland. The fallow soil was assumed to contain only stable npSOC due to the long
period without organic matter inputs. Slight (no p statistic given, may not be significant) negative
priming was observed from additions of BC to the fallow soil. Jones et al. (2011) found negative priming
of a
14
C label that had been applied to the soil (Ah horizon, Typic Dystrochrept) 6 years prior to addition
of BC in an incubation study. Due to the long interval between applying the radiocarbon label and the
subsequent incubation trial, the
14
C was assumed to be present only in stable npSOC.
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ii
Wardle et al. (2008) conducted a 10 year litterbag study with charcoal in a boreal-forest litter-layer in
which positive priming was observed only during the first year. Other studies have observed positive
priming over a period of a few weeks to months in short-term incubations (Luo et al. 2011; Keith et al.
2011; Zimmerman et al. 2011). Nonetheless, the precautionary principle suggests that we should
consider the possibility that priming effects might persist long term. Woolf and Lehmann (2012)
modeled the impact of biochar on priming over 100 years in a system designed to probe the upper
bounds of priming impacts on npSOC. Specifically, they assumed
17
:
1. priming effects up to and including the largest that have been measured in any published short-
term study;
2. that priming effects persist long-term;
3. that BC stocks accumulate in soil at a high rate (because they are produced from the abundant
residues from a high-NPP crop; the BC is produced in an engineered pyrolysis system that gives
high yields of BC per unit biomass feedstock; and the BC is produced under controlled conditions
which ensure that it decomposes only slowly).
Under this set of highly conservative assumptions, Woolf and Lehmann (2012) found that no more than
3 to 4% of initial npSOC might be mineralised due to priming by BC over 100 years. In absolute
quantities, this loss of npSOC was greatest in soils with the highest initial stocks of npSOC. Biochar
production was also positively correlated with initial npSOC, due to the greater production of crop
residues for feedstock on more fertile soils. Table S1 shows the initial npSOC (npSOC
0
), potential loss of
npSOC due to positive priming over 100 yrs (Δ npSOC
p+
), BC remaining in soil after 100 years (BC
+100
), and
Δ npSOC
p+
expressed as a percentage of BC
+100
, (denoted as RPL = Relative Priming Loss) for each of the
locations studied in Woolf and Lehmann (2012).
Table S1. Loss of soil carbon over 100 yr due to positive priming caused by BC at three study locations. Source:
Woolf and Lehmann, 2012
Site
npSOC
0
(kg C m
-2
, in top
0.15m of soil profile)
Δ npSOC
p+
(kg C m
-2
)
BC
+100
(kg C m
-2
)
RPL
Colombia
0.94
0.037
3.31
1.1%
Kenya
1.56
0.05
3.29
1.5%
Iowa
6.29
0.26
5.95
4.4%
A linear regression of RPL versus npSOC
0
yields the relationship
17
In this paper, biochar is added gradually over 100 years and not in one large treatment in year zero. However,
the model has been run using initial large application of biochar to soil and priming results were similar in
magnitude.
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iii
RPL = 0.0062 npSOC
0
+ 0.0053 (R
2
= 0.99992)
From which it follows that the maximum npSOC
0
for which RPL is less than 5% is 7.2 kg C m
-2
in the top
0.15m of the soil profile. I.e. for soils starting with less that 7.2 kg npSOC m
-2
, cumulative priming losses
will be less than 5% of the BC remaining after 100 years. If a 5% threshold for positive priming
enhancement due to the addition of biochar to soil would be defined as a condition to disregard the
effect of priming for biochar carbon stability estimations, biochar should not be applied to soils with
more than 7.2 kg npSOC m
-2
. However, soils with such concentrations are rarely found within
agricultural soils, and are more frequent in forestland or peat soils (Davidson and Ackerman, 1993),
where biochar would not likely be applied. In the case that biochar were applied to soils with
concentrations higher than 7.2 kg npSOC m
-2
it could lead to positive priming, which is factored into the
calculations of stable carbon, with a discount factor of 5%, although – as stated – it would be rare to find
soils with organic carbon content higher than the stated limit, in order to maintain a conservative
approach to stability estimations. Additionally, it would not make much sense to apply a carbonaceous-
rich material to a carbon-rich soil, if agronomic and environmental benefits are sought from biochar use.
Biochar Carbon Stability Test Method
:
An assessment of methods to determine biochar
carbon stability. International Biochar Initiative. September 20, 2013.
iv
Supplementary Information Section 2
Selection process of the test method
Twenty-eight test methodologies were identified through an assessment of the peer-reviewed literature
of existing techniques to determine biochar carbon stability in soil (shown in Table S2). These were
grouped into five categories related to characterization approaches for physical-chemical properties of
biochar, as defined in the scope of work.
Table S2. Test methods available for characterization of physical-chemical properties of biochar related to stability
Category Test Source
Microbial Incubations Short-term Incubation
(<50 d)
Suggested by Expert Panel
Long-term Incubation
(>1 y)
Liang et al 2008, Hammes
et al 2008, Singh and
Cowie 2008, Kuzyakov et al
2009, Zimmerman 2010,
Singh 2012
Incubation data
modeled with 2
component model
DeGryze et al 2010
Incubation data
modeled with Power
model
Zimmerman 2010
Volatile matter / stable
carbon
Proximate analysis
(ASTM D1762-84)
Major et al 2010, Lehmann
et al 2011,
Schmimmelpfennig and
Glaser 2012
Modified Proximate
Analysis (e.g. Wang et al
2011)
Wang et al 2011, Enders et
al 2012
Ultimate analysis
(resident carbon)
DeGryze et al 2010
Modified Ultimate
Analysis (e.g. DeGryze et
al 2010)
McLaughlin et al 2009
Lower temperature
volatile matter
measurement (e.g.
Enders et al., 2012)
Enders et al 2012
Biochar Carbon Stability Test Method
:
An assessment of methods to determine biochar
carbon stability. International Biochar Initiative. September 20, 2013.
v
NMR Relaxation
(mobility of labile
components)
Suggested by Expert Panel
(multiple citations)
NMR Cryoporometry
(pore size distribution
and volumes)
Suggested by Expert Panel
(multiple citations)
Thermogravimetric
analysis (TGA) including
R50 approach
Hammes et al 2007,
Calvelo Pereira et al 2011
C functional group
chemistry (aromaticity)
Scanning Transmission
X-ray Microscopy
(STXM)
Liang et al 2008
Near-Edge X-ray Fine
Structure Spectroscopy
(NEXAFS)
Lehmann et al 2005, Liang
et al 2008
X-ray photoelectron
spectroscopy
Nishimaya et al 1998,
Schneider et al 201,
Soil density
fractionation
Sohi et al 2001, Liang et al
2008
Alkyl-to-aromatic ratio
(13C NMR)
Miknis et al 1981, Liang et
al 2008, Brewer et al 2009
Cyclic voltammetry Joseph et al, 2010
Dichromate oxidation Hammes et al 2008,
Rumpel et al 2009,
Manning and Lopez-Capel
2010
Infrared diffuse
reflectance
spectroscopy in the
near- or mid-infrared
spectral range
(NIRS/MIRS)
Bellon-Maurel and
McBratney 2011
Benzene ring-current or
benzenepolycarboxylic
acids
Glaser et al 1998,
Brodowski et al 2005,
Schneider et al 2010,
McBeath et al 2011,
Schimmelpfennig and
Glaser 2012
Biochar Carbon Stability Test Method
:
An assessment of methods to determine biochar
carbon stability. International Biochar Initiative. September 20, 2013.
vi
Elemental ratios H/C
org
O/C
org
ratios, Van
Krevelen diagram
Baldock and Smernik 2002,
Hammes et al 2007,
Spokas 2010,
Schimmelpfennig and
Glaser 2012, Harvey et al
2012; Enders et al., 2012
Other Soluble C fraction Zimmerman et al 2012
Electrochemical
Impedance
Spectroscopy
Suggested by Expert Panel
Microscopic
examination
Suggested by Expert Panel
Molecular fin/gerprints
by py-GC/MS
Kaal et al 2012
In order to quantitatively evaluate these methods, an evaluation matrix was completed by the experts.
Eight of the experts evaluated the methodologies on the basis of seven criteria, on a scale from 1 to 5,
with 5 being the highest value for each criterion. When referring to cost, the “highest” score equates to
“least expensive” (e.g. a score of 5 for this criterion means that it is very inexpensive). The 7 criteria
were given the same relative weight (1/7 or 14% each). The results are provided in Table S3.
Biochar Carbon Stability Test Method
:
An assessment of methods to determine biochar
carbon stability. International Biochar Initiative. September 20, 2013.
vii
Table S3. Ranking of test methods based on scoring by experts.
Color labels:
Category Method / procedure Cost [1] Availability
[2]
Calibration
against
stability [3]
Repeatability
[4]
Reflection of
material property
[5]
Publications -
impact
[6]
Robustness
[7]
AVERAGE Votes casted Highest Lo west
Elemental ratios C,H,N Van Krevelen
diagram 4.00 3.75 4.75 4.50 4.75 3.50 4.50 4.25 5 5 [1,3,4,5,6,7] 1 [1]
Elemental ratios H/C
org
(ratio) 4.14 3.67 4.33 4.67 3.83 3.17 4.00 3.97 7 5 [1,3,4,5,7] 1 [6]
Elemental ratios O/C
org
(ratio) 4.00 3.67 4.17 4.17 3. 83 3.33 4.00 3.88 7 5 [1,2,3,4,5,6] 2 [5,6]
Microbial
Incubations
Incubation data modeled
with 2 component model 3.67 3. 67 4.00 4.00 3.67 3.50 3.50 3.71 6 5 [1,2,3,4,5,6] 1 [1,2,3,6]
C functional group
chemistry
(aromaticity)
Infrared diffuse
reflectance spectroscopy
in the near- or mid-
infrared spectral range
(NIRS/MIRS)
4.40 3.40 3.00 4.00 4.40 3.00 3.60 3.69 5
5
[1,2,3,4,5,6,7] 1 [3,6]
Volatile matter /
stable carbon
Modified Ultimate
Analysis (e.g. DeGryze et
al 2010)
3.67 3.33 3.33 4.00 3.67 3.67 3.67 3.62 3 5 [1,2,4,5,6] 1 [2]
Microbial
Incubations
Incubation data modeled
with Power model 3.50 3.50 3.83 3.83 3.83 3.33 3.50 3.62 6
5
[1,2,3,4,5,6,7] 1 [1,2,6,7]
Volatile matter /
stable carbon
Ultimate analysis
(resident carbon) 4.20 4.20 3.00 3.60 3.40 3.20 3.40 3.57 5 5 [1,2,4,5,6] 2 [3,4,5,6]
Volatile matter /
stable carbon
Lower temperature
volatile matter
mreasurment (e.g.
Enders et al., 2012)
4.20 3.80 3.40 3.80 3.40 2.60 3.40 3.51 5 5 [1,2,4] 1 [2,6]
Volatile matter /
stable carbon
Proximate analysis
(ASTM D1762-84) 4.43 4.17 3.33 3.33 3.17 3.17 3.00 3.51 7 5 [1,2] 1 [5]
Volatile matter /
stable carbon
Thermogravimetric
analysis (TGA) including
R50 approach 3.43 2.57 3.86 3.86 3.71 3.14 3.86 3.49 7 5 [1,7] 1 [2,6]
C functional group
chemistry
(aromaticity)
Alkyl-to-aromatic ratio
(13C CP/DP NMR) 2.20 2.20 4.00 3.60 4.40 3.60 4.20 3.46 5 5 [3,5,6,7] 1 [2]
Microbial
Incubations
Long-term Incubation (>1
y) 2.29 3.14 4.00 3.00 3.57 4.14 3.71 3.41 7 5 [1,2,3,6,7] 1 [2,5]
C functional group
chemistry
(aromaticity)
Benzene ring-current
3.00 2.25 4.00 3.50 4.00 3.00 4.00 3.39 5 5 [1,2,3,5,7] 1 [2]
Volatile matter /
stable carbon
Modified Proximate
Analysis (e.g. Wang et al
2011)
4.33 3.67 3.17 3.67 3.17 2.67 3.00 3.38 6 5 [2] 1 [1,5]
C functional group
chemistry
(aromaticity)
Dichromate oxidation
3.83 3.83 3.17 3.50 2.83 3.00 2.83 3.29 6 5 [2] 1 [1,6,7]
Microbial
Incubations
Short-term Incubation
(<50 d) 3.57 3.43 2.43 3.29 2.86 3.57 3.29 3.20 7 5 [1,2,6] 1 [3,5,7]
Volatile matter /
stable carbon
NMRC 1.86 1.83 3.33 3.67 4.33 2.83 3.50 3.05 7 5 [1,3,4,5,7] 1 [1,2,6]
Volatile matter /
stable carbon
NMRR 2.14 2.00 3.17 3.50 4.17 2.67 3.50 3.02 7 5 [ 1,3,5,7] 1 [1,2,6]
C functional group
chemistry
(aromaticity)
Cyclic voltammetry
2.67 2.33 2.67 3.33 3.33 3.00 2.67 2.86 3 3 [all] 1 [6,7]
Other Soluble C fraction 4.20 3.60 2.40 3.00 2.20 1.80 2.40 2.80 5 5 [2] 1 [1,3,5,7]
Other Pyrolysis GC/MS 2.25 1.80 2.80 3.20 3.60 2.60 3.00 2.75 6 5 [1,5] 1 [2,3,6]
C functional group
chemistry
(aromaticity)
X-ray photoelectron
spectroscopy 1.71 1.33 2.67 3.33 3.83 2.67 2.67 2.60 7 5 [1] 1 [2,3,6]
C functional group
chemistry
(aromaticity)
STXM
1.80 1.75 2.50 2.75 3. 50 2.50 3.00 2.54 5 5 [1] 1 [2,6]
C functional group
chemistry
(aromaticity)
NEXAFS
1.33 1.20 2.80 2.40 4. 20 2.60 3.00 2.50 6 5 [1,3] 1 [1,2,6]
C functional group
chemistry
(aromaticity)
Soil density fractionation
2.00 2.25 1.75 2.50 3. 25 3.00 2.75 2.50 4 4 [1] 1 [3,6,7]
Other Microscopic examination 2.40 2.75 2.00 2.75 2.25 1.75 2.00 2.27 5 5 [2] 1 [2,3,6,7]
Other Electrochemical
Impedance Spectroscopy 2.00 2.00 2.00 3.00 2.00 1.50 1.50 2.00 2 5 [1] 1 [2,3,6,7]
Assessment criteria
Biochar Carbon Stability Test Method
:
An assessment of methods to determine biochar
carbon stability. International Biochar Initiative. September 20, 2013.
viii
Criteria besides cost [1] include: [2] availability, referred to how common it is to find a laboratory that
can perform the analyzed test; [3] calibration against stability, for those methods that have been
correlated with other types of direct measurements of stability in published literature; [4] repeatability,
as in the ability of the test to be performed periodically while maintaining precision without demanding
extensive resources; [5] reflection of material property, or how well a test represents what is being
measured; [6] publications – impact, as to the frequency with which the test can be found in published
literature; and [7] robustness, meaning the precision, consistency and flexibility of the test.
Out of the twenty-eight methods evaluated (including three elemental ratios), ten obtained an overall
score above 3.5 (green label), seventeen between 2 and 3.5 (yellow label) and only one below 2 (red
label). The top 10 scored methods were further analyzed. A detail of the rankings for this sub-group is
provided in table S4.
Table S4. Frequency of scores of the top 10 test methods.
Although further processing of the data was performed and presented to the Expert Panel with concrete
proposals of test methods to be used for biochar C stability measurements, it was considered by the
experts that this approach was useful only to frame the discussion and to discard some test methods,
but that it was not the most appropriate path to officially select the final test method(s) to be used to
calculate BC
+100
. An in-depth analysis of the top-scoring methods was carried out in order to reduce the
list to less than five suitable methods.
3.5-5 Green
2-3.5 Yellow
0-2 Red
Criteria
Value
5
4
3
2
1
5
4
3
2
1
5
4
3
2
1
5
4
3
2
1
5
4
3
2
1
5
4
3
2
1
5
4
3
2
1
Votes
Avg value
Highest Lowest
1C,H,N Van Krevelen
diagram 1 3 1 3 1 3 1 3 1 3 1 1 2 1 2 2 54.25 5 [1,3,4,5,6,7] 1 [6]
2H/C
org
(ratio) 2 4 1 4 2 2 4 4 2 2 2 1 1 4 1 1 1 4 1 73.97 5 [1,3,4,5,7] 1 [6]
3O/C
org
(ratio) 1 5 1 3 3 2 3 1 3 1 2 2 2 1 1 3 2 1 1 4 1 73.88 5 [1,2,3,4,5,6] 2 [5,6]
4
Incubation data
modeled with 2
component model 3 1 1 1 4 2 3 2 1 3 2 1 1 3 1 1 2 1 2 1 4 1 1
63.71 5 [1,2,3,4,5,6] 1 [1,2,3,6]
5
Infrared diffuse
reflectance
spectroscopy in the
near- or mid-infrared
spectral range
(NIRS/MIRS) 4 1 2 1 2 1 1 1 1 1 1 3 1 3 1 1 2 1 2 1 1 3
53.69 5 [1,2,3,4,5,6,7] 1 [3,6]
6
Modified Ultimate
Analysis (e.g. DeGryze
et al 2010) 1 2 1 1 1 2 1 1 1 1 1 2 1 2 2 1
33.62 5 [1,2,4,5,6] 1 [2]
7
Incubation data
modeled with Power
model 2 2 1 1 3 1 2 2 2 1 1 3 2 1 2 2 1 1 2 1 1 1 1 1 3 1 1
63.60 5 [1,2,3,4,5,6,7] 1 [1,2,6,7]
8Ultimate analysis
(resident carbon) 2 2 1 2 2 1 2 2 1 1 2 1 1 1 1 2 1 1 3 1 2 3 53.57 5 [1,2,4,5,6] 2 [3,4,5,6]
9
Lower temperature
volatile matter
mreasurment (e.g.
Enders et al., 2012) 3 2 2 2 1 3 1 1 1 2 2 2 3 4 1 2 3
53.51 5 [1,2,4] 1 [2,6]
10
Proximate analysis
(ASTM D1762-84)
4 2 1 2 3 1 3 2 1 3 2 1 3 2 1 2 3 1 1 4 1
73.51 5 [1,2] 1 [5]
[6] [7]
Method
[1] [2] [3] [4] [5]
Biochar Carbon Stability Test Method
:
An assessment of methods to determine biochar
carbon stability. International Biochar Initiative. September 20, 2013.
ix
Among the five highest scoring methods, the NIRS/MIRS method was discarded since, although there
are scientific publications about its use to characterize other biogenic material and soils, currently there
are no references that directly relate it with biochar C stability. It was included in the list of methods as a
suggestion by the Expert Panel, and seems to be promising according to its overall score, but in order to
comply with the premise of conservativeness, it was discarded.
The described analysis resulted in the conclusion that methods related to elemental composition –either
elemental ratios or measurements of volatile and fixed matter- were to be considered as suitable Alpha
methods. These are: (modified) proximate and ultimate analyses, and H/C
org
.
Among proximate and ultimate analysis, the first measures moisture content, volatile matter, fixed
carbon and ash; whereas the second determines the amount of carbon, hydrogen, oxygen, nitrogen and
sulfur. Since there are more publications relating proximate analysis with biochar stability (e.g. Spokas
2010, Enders et al 2012) than relating ultimate analysis with biochar stability, it was considered that
proximate analysis would be more suitable as a proposed method, and that it would allow for
calibration to be performed more swiftly. Thus, ultimate analysis was discarded.
Among elemental ratios, as shown in figure 2, H/
Corg
and O/C
org
are correlated. Since O is usually
calculated by subtracting C, N and H from the full weight of a sample (i.e. it is derived rather than
measured), H/C
org
was considered simpler and more robust than O/C
org
, which thus was discarded. A Van
Krevelen diagram requires a calculation of O/C
org
to plot it against H/C
org
, and therefore was discarded as
well.
This analysis led to the following preliminary conclusion: either proximate analysis, H/C
org
or a
combination of both would be best used as the method to determine BC
+100
. A modification of the
proximate analysis was considered feasible, as the one proposed by Enders et al. (2012). The
quantification of H and C would be realized with the use of an elemental analyzer, and the threshold for
a material qualifying as biochar to determine recalcitrance would be the threshold indicated in the IBI
Standards (<0.7). The remaining question was whether the definitive test methodology should use one
or a combination of these test methods.
In order to provide an answer to this question, a key input was the analysis of pyrolyzed material
containing a high proportion of ash. Through the experience of the experts, the H/C
org
was considered to
provide flawed results when analyzing high-ash biochar, by yielding values under the defined threshold
for H/C
org
(<0.7) but which were actually not stable. Thus, an additional test was deemed necessary to
eliminate this possible source of error, and proximate analysis was the preferred option, as it reports the
ash content in biochar. A maximum value of 80% of ash content was proposed by the experts.
A combination of H/C
org
and proximate analysis was then considered robust enough for an Alpha
method to determine BC
+100
. However, in order to simplify the proposed test method without sacrificing
Biochar Carbon Stability Test Method
:
An assessment of methods to determine biochar
carbon stability. International Biochar Initiative. September 20, 2013.
x
precision, it was stated that by restricting biochars to “Class 1” as defined in the IBI Standards (organic
carbon content above 60%), a similar level of correlation between H/C
org
and BC
+100
could be yielded.
Through this logic, it was agreed that H/C
org
would be the sole measure of biochar stability.
The proposed Alpha method can and should be further improved as the science of biochar continues to
accumulate, as this is a first attempt at estimating BC
+100
. For that, it is suggested that information from
observations of incubation experiments with laboratory-produced biochars and with charcoal from
archaeological sites be made available, in order to establish parameters to calibrate this alpha-type test
method to a beta-type. The beta method will not necessarily be used by biochar producers; rather, it
should be performed in laboratories to propose amendments and modular updates to the alpha
method, which is devised to be used by producers.
The Beta method to which the selected Alpha method is calibrated is the use of recorded measurements
of biochar degradation from incubation experiments, combined with modeling to predict BC
+100
. Given
an observed behavior of biochar degradation across experiments (Kuzyakov et al 2009, etc., Cheng et al.,
2008, Liang et al., 2008, Major et al., 2010), a two-component double exponential model was deemed
appropriate to estimate the amount of carbon likely to be degraded in a time horizon of 100 years. The
second possible model was the Power model (Zimmerman, 2010), which was considered by the Expert
Panel as more appropriate from a biophysical standpoint (it better reflects the physical and chemical
composition of biochar) and which actually yielded higher results for predicted stable carbon (ranging
80-97% vs 60-80% for the two-component model). However the Power model was discarded in favor of
the more conservative double exponential model.
The two-component model was selected since it is a minimum adaptation to the concept of multiple
pools, and is likely to underestimate BC
+100
, as explained previously. The two pools are simplified to
represent two main components of biochar – a relatively stable and a more labile fraction – which have
different turnover rates.
Correlation between the chosen alpha and beta methods was performed using data from from two
incubation experiments led by two members of the Expert Panel (Singh et al., 2012; Zimmerman, 2010,
as extended in Zimmerman and Gao, 2013) on a range of laboratory-produced biochars conducted over
3 to 5 years under conditions that favor decomposition (e.g. adequate temperature conditions
18
). In
vitro experiments may also inhibit decomposition over time by, e.g. not allowing influx of new nutrients
or removal of microbial metabolites.
18
Singh et al. (2012) incubated at 22°C and Zimmerman (2010) incubated at 32°C