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Soil Biology & Biochemistry 57 (2013) 401e410

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Soil Biology & Biochemistry

journal homepage: www.elsevier .com/locate/soi lb io

Short-term CO2 and N2O emissions and microbial properties of biochar amendedsandy loam soils

Nele Ameloot a,*, Stefaan De Neve a, Kanagaratnam Jegajeevagan a, Güray Yildiz b, David Buchan a,Yvonne Nkwain Funkuin a, Wolter Prins b, Liesbeth Bouckaert a, Steven Sleutel a

aResearch Group of Soil Fertility and Nutrient Management, Department of Soil Management, Ghent University, Coupure Links 653, 9000 Gent, BelgiumbDepartment of Biosystems Engineering, Ghent University, Coupure Links 653, 9000 Gent, Belgium

a r t i c l e i n f o

Article history:Received 7 February 2012Received in revised form28 August 2012Accepted 22 October 2012Available online 12 November 2012

Keywords:CO2 mineralizationN2O emissionSlow pyrolysisPyrolysis temperaturePLFAMicrobial biomassDehydrogenase activityN mineralization

* Corresponding author. Tel.: þ32 9 264 6055; fax:E-mail address: n.ameloot@ugent.be (N. Ameloot)

0038-0717/$ e see front matter � 2012 Elsevier Ltd.http://dx.doi.org/10.1016/j.soilbio.2012.10.025

a b s t r a c t

Biochar produced during pyrolysis of biomass has the potential to reduce greenhouse gas (GHG) emis-sions from soils. In order to evaluate the effect of four different biochar additions on the emission of thegreenhouse gases CO2 and N2O, two incubation experiments were established in a temperate sandy loamsoil. Digestate, a waste-product of the wet fermentation of swine manure, and willow wood was slowlypyrolyzed at 350 �C and 700 �C, yielding four biochar types (DS350, DS700, WS350 and WS700). In thefirst incubation experiment (117 days), C mineralization was monitored in soil amended with biochar ata quantity of 10 Mg ha�1 on an area-basis (biochar to soil ratio of 1:69 on a mass basis) at 50% water filledpore space (WFPS). CO2 emissions from the 350 �C biochar treatments were significantly higher than thecontrol (no biochar) treatment, while we observed no significantly different net C mineralization in thetreatments with the 700 �C biochars compared to the control. After fitting a combined zero- plus first-order model to the cumulative C mineralization data, the parameter for the easily mineralizable C pool(CAf) positively correlated with the volatile matter (VM) contents of the biochars. Microbial biomasscarbon consistently increased due to all biochar additions, while the dehydrogenase activity increased inthe 350 �C biochar treatments but decreased in the 700 �C biochar treatments. Principal componentanalysis (PCA) of the extracted phospholipid fatty acids (PLFAs) demonstrated that divergent microbialcommunity structures established after the addition of all biochars. The markers for Gram-positive andGram-negative bacteria were more abundant in the 350 �C biochar treatments compared to the controland to the other biochar treatments. Net N mineralization was higher in the digestate biochar treatmentsthan in the willow biochar treatments and decreased with increasing pyrolysis temperatures andincreasing C:N ratio. In a second incubation experiment (15 days) N2O emissions were measured at WFPSof 70% and the same biochars were added in the same quantity as for C mineralization, with the additionof 40 mg KNO3eN kg�1. The cumulative N2O emission after 15 days was positively correlated with thevolatile matter content of the biochars and was significantly lower in the 700 �C biochar treatmentscompared to the control, while no significant differences were found for the 350 �C biochar treatments.This study suggests that volatile matter content could be an important property of biochars in explainingshort-term CO2 and N2O emissions from biochar-amended soils.

� 2012 Elsevier Ltd. All rights reserved.

1. Introduction

The search for new technologies to mitigate climate change hasled to a number of creative ideas, among which the pyrolysis ofbiomass residues seems to hold considerable potential. During thispyrolysis process in the absence of oxygen biomass residues areconverted into bio-oil, biochar and syngas, which are used as

þ32 9 264 6247..

All rights reserved.

renewable energy sources. Recently, biochar has gained muchattention as a soil amendment (Forbes et al., 2006; Lehmann et al.,2006; Fowles, 2007). Next to the high C sequestration potential ofthis product, several studies have shown improved chemical,physical and biological soil conditions and related higher produc-tivity rates in biochar amended soils (Glaser et al., 2002; Chan et al.,2007; Jeffery et al., 2011; Lehmann et al., 2011). Although biocharwas initially considered to be inert to biological and chemicaldegradation, recent studies suggest that biochar experiencesa biphasic decomposition when added to soil (Kuzyakov et al.,2009; Cross and Sohi, 2011). For example, two months after rye

N. Ameloot et al. / Soil Biology & Biochemistry 57 (2013) 401e410402

grass biochar additions degradation rates dropped from 2% to 0.2%(Kuzyakov et al., 2009). In general, labile compounds in the bio-chars consist of awide array of relatively small molecules, includingn-alkanoic acids, hydroxy and acetoxy acids, benzoic acids, diols,triols, and phenols (Graber et al., 2010) and are degraded rapidly,while the stable aromatic compounds are decomposed at a slowerrate (Kuzyakov et al., 2009; Zimmerman, 2010; Foereid et al., 2011).Biochar stability and the interaction between biochar and soil biotavaries depending on the biochar feedstock, the production method(gasification vs. pyrolysis (slow and fast), hydrothermal carbon-ization, catalytic fast pyrolysis), the pyrolysis residence times andthe pyrolysis temperature (Lehmann et al., 2011).

As the soil micro pores (<3 mm) provide protection againstbacterial grazing (Hassink et al., 1993; Strong et al., 2004), it hasbeen suggested that the porous structure of biochar likewiseprovides an aerated habitat in which soil bacteria are able toflourish safely (Lehmann et al., 2011). In this way and throughincreased CEC with associated adsorption of nutrients (NH4

þ) andDOC (Clough and Condron, 2010; Lehmann et al., 2011; Taghizadeh-Toosi et al., 2011b), biochar additions to soils may stimulate thenitrifying community. Additionally, the adsorption of allelopathicmolecules from the soil solution that may otherwise inhibit nitri-fication onto the biochar surface likewise influences nitrifyingbacteria (Wardle et al., 1998; Elmer and Pignatello, 2011). Theadsorption onto the biochar surface of compounds with a high C:Nratio that otherwise would increase N immobilization upondecomposition is likely to contribute to the stimulation of ammo-nification and nitrification (DeLuca et al., 2006; Gundale andDeLuca, 2006). However, N immobilization is also likely to occurwhen biochar compounds with a C:N ratio higher than the C:Nratios of the microorganisms are consumed (Kuzyakov et al., 2000;Gundale and DeLuca, 2007; DeLuca et al., 2009).

Nitrous oxide (N2O) is a potential GHG that is produced in thesoil as a resultant of nitrification, whereby nitrite is used as analternative electron acceptor while it is reduced to N2O. Alterna-tively, N2O is produced as a by-product during denitrification, inwhich specialized microorganisms reduce nitrate (NO3

�) to N2.Denitrification is the most important N2O emission process inagricultural soils (Dalal et al., 2003). The increased porosity ofbiochar amended soils may influence this anaerobic denitrificationprocess. A higher soil porosity implies increased O2 diffusion, whichsuppresses N2O and N2 emissions (Aulakh et al., 1991; Richardsonet al., 2009). Most authors have observed decreased N2O emis-sions from soils amended with biochar of various types (Rondonet al., 2005; Yanai et al., 2007; Spokas and Reicosky, 2009; VanZwieten et al., 2010; Bruun et al., 2011; Taghizadeh-Toosi et al.,2011a). However, there are also studies that reported no impacton N2O production, while some reported increased N2O emissionsafter the addition of biochar (Spokas and Reicosky, 2009; Scheeret al., 2011).

To produce the biochars, a digestate feedstock from a biogasinstallation and a woody feedstock (willow wood) were used.Manure processing is rapidly increasing in many regions withintensive livestock production, like Flanders, the Netherlands andDenmark (Lemmens et al., 2007) in order to reduce nutrient inputsto soil, nitrate leaching and eutrophication problems. Anaerobicdigestion or wet fermentation of manure for biogas production,probably is the most frequently used manure processing techniqueand produces a digestate (Lemmens et al., 2007). Via the wetfermentation of manure 813,000 Mg digestate year�1 is produced,of which on a yearly basis 22,000 Mg is dried by recuperating theheat produced during the fermentation process (Vlaco vzw, 2011).Given the rapid increase in production of these manure digestates,the pyrolysis of these feedstocks to biochar is a potential furtherstep in the processing of manure. While hydrothermal

carbonization (typically at low temperatures over an aqueoussolution of biomass) of maize digestate (from the biogas productionvia wet fermentation) has been reported (Mumme et al., 2011),pyrolysis of manure digestate to biochar and application of thesebiochar types to soils has not been done before.

We tested the hypothesis that the CO2 and N2O emissions fromsoils amended with biochar are determined by the type of feed-stock, and the pyrolysis temperature. To this end, we measured theCO2 and N2O emissions from soil amended with biochar from twocontrasting feedstocks (manure digestate and wood), produced attwo contrasting temperatures (slow pyrolysis at 350 �C and 700 �C).We then aimed to correlate the CO2 and N2O emissions under thedifferent scenarios to the biochar properties, themicrobial biomass,activity and community structure, and the chemical soil properties.

2. Material and methods

2.1. Soil characteristics

An inceptisol with sandy loam soil texture (clay <2 mm: 7%, silt2e50 mm: 44% and sand 50e2000 mm: 49%), representative forintensive agriculture in Flanders was collected from an arable fieldin Lendelede, Belgium. The soil had a soil organic carbon (SOC)content of 0.73%, a total N content of 0.063%, pHH2O (1:5) 6.4, anda bulk density of 1.6 g cm�3.

2.2. Biochar production and characterization

For this study, biochar samples were produced from a woodfeedstock from the municipal park maintenance service of the cityof Ghent, namely willow wood (Salix dasyclados) and from oneswine manure digestate feedstock (Biogas Tec, Belgium). Thefeedstock samples were oven dried at a temperature of 60 �C for atleast 24 h. Both feedstocks were slowly pyrolyzed at 350 �C and700 �C in the laboratory of thermo-chemical conversion of biomass(LTCB) at the department of Biosystems Engineering (GhentUniversity), yielding four types of slow pyrolysis biochar (DS350,DS700, WS350 and WS700). The temperatures were specificallyselected to include the extremes at which slow pyrolysis could beundertaken. The slow pyrolysis unit consisted of a cylindricalfurnace with a 30 cm high vertical stainless steel reactor (innerdiameter of 3.6 cm). The biomass was added into the reactor tube toa height of about 25 cm and flushed with N2 at a gas flow rate of800 ml min�1. After a residence time of 10 min at the selectedtemperature, the reactor tubewas cooled and the produced biocharwas collected, weighed and stored in polypropylene containers attemperatures of about�18 �C. All samples were analyzed for total Cand N contents by catalytic combustion (Variomax CNS analyzer,Elementar, Germany). The pHH2O was determined by weighing 1 gof biochar and adding 10 ml of H2O, well mixed and measured after18 h with a pH electrode (Thermo Orion, 420A plus). Moisturecontent, volatile matter and ash content were determined by theASTM D1762-84 standard testing method. All analyses were carriedout in duplicate. The surface area and total pore volume of thebiochars were determined by the BET method using a TriStar 3000analyzer (micromeritics) at the Department of inorganic andphysical chemistry, Ghent University.

2.3. C mineralization experiment

Soil mesocosms with 250 g of air died soil were prepared in6.8 cm diameter PVC tubes. The application rate of 10 Mg freshbiochar ha�1 was equivalent to the addition of 3.63 g biochar permesocosm (based on surface area ratio). Given the filling height of5 cm of soil in the tubes, this corresponded to a biochar to soil ratio

N. Ameloot et al. / Soil Biology & Biochemistry 57 (2013) 401e410 403

of 1:69. Soil was thoroughly mixed with the biochar and themixture was filled in the tubes, and slightly compacted to obtaina bulk density of 1.4 g cm�3. There were three replicates per biochartreatment. A control treatment (i.e. soil without biochar addition)in triplicate was also included. After biochar addition, demineral-ized water was added to the soils to achieve a fixed moisturecontent of 50% WFPS. The soil columns were placed in closed glassjars and put in an incubation cabinet at 25 �C. The emitted CO2 wastrapped in 15 ml 1 M NaOH. At day 1, 3, 5, 7, 10, 13, 17, 20, 24, 27 and31 the vials with NaOH were removed and titrated with HCl in thepresence of BaCl2. After 30 incubation days the samples weremeasured weekly. The water content of the mesocosms wasadjusted weekly in order to maintain a WFPS of 50%.

At the end of the incubation (after 117 days) the microbialbiomass carbon (Cmic), activity and community structure wasmeasured. Cmic was determined using the fumigationeextractionmethod (Joergensen and Mueller, 1996). Soil samples fumigatedwith chloroform and non-fumigated samples (10 g fresh soil) wereextracted with 30 ml 0.5 M K2SO4 and C contents of the extractswere determined with a TOC analyzer (TOC-VCPN, ShimadzuCorporation, Kyoto, Japan). For conversion from organic C in theextracts to Cmic in soil a kEC value of 0.45 was assumed (Joergensen,1996). Dehydrogenase activity (DA) was determined followinga procedure described in Moeskops et al. (2010). Phospholipid fattyacids (PLFAs) were extracted using a adjusted Bligh and Dyer (1959)e technique, modified byMoeskops et al. (2010). The nomenclatureof fatty acids and their contribution as specific biomarkers for thesoil microbial groups (Gram-positive and Gram-negative bacteria,fungi, AMF, protozoa and actinomycetes) were adapted fromMoeskops et al. (2010). For Gram-positive bacteria the sum of i15:0,a15:0, i16:0, a16:0, i17:0 and a17:0 was used. The PLFAs cy17:0 andcy19:0 were considered to be typical for Gram-negative bacteria,while the 20:4 and 20:5 PLFAs were indicative for eukaryotes(Buchan et al., 2012). The sum of 10Me16:0 and 10Me18:0 wasregarded as a measure for the actinomycetes. The total bacterialcommunity was proportional to the sum of the marker PLFAs forGram-positive and Gram-negative bacteria, plus15:0 and 17:0(Buchan et al., 2012). The sum of PLFA 18:2u6,9c and 18:1u9c wasconsidered as an indicator for saprotrophic fungi and 16:1u5 as theindicator for arbuscular mycorrhizal fungi (AMF) (Joergensen andWichern, 2008). At the end of the incubation, pHH2O (1:5) wasmeasured and mineral N content (NO3

� and NH4þ) was deter-

mined on 10 g fresh soil extractedwith 50ml 1MKCl andmeasuredcolorimetrically with a continuous flow auto-analyzer.

2.4. N2O emission experiment

Mesocosms with a height of 4.9 cm and a diameter of 3.35 cmwere incubated in triplicate per treatment. Per mesocosm 60.7 g(<2 mm) air-dried soil was mixed with 0.88 g of biochar (i.e. at thesame concentration as in the C mineralization experiment). Weadded demineralized water to obtain a moisture content of 70%WFPS. A quantity of nitrate equivalent to 40 mg N kg�1 soil wasadded from a KNO3 solution. The mesocosms were put in glass jarsclosed airtight with a lid with septum and incubated at 15 �C insidean incubation cabinet. After a 2-h incubation the concentration ofN2OeN in the headspace was measured by extracting 1 ml ofheadspace air with a gas-tight syringe. The N2OeN was measuredwith a Thermo Electron Trace GC Ultra gas chromatograph (Inter-science) equipped with an electron capture detector (ECD) and twopacked columns of Porabond Q (15 and 10 m). The operatingconditions were carrier gas N2 (29.9 ml min�1), injector tempera-ture of 200 �C, column and oven temperature of 30 �C and detector

temperature of 310 �C. Calibration curves for each treatment wereobtained before each measurement by injecting 200, 400, 600, 800and 1000 ml of the N2O standard gas (23 � 1.5 ml N2OeN l�1 He).After each measurement the jars were left open for 30 min toreplenish oxygen. N2O emissions were measured till the N2Oconcentrations in the headspace of the closed containers werebelow detection limit (for the DS350 treatment after 14 days, forthe others after approximately 15 days).

2.5. Data analysis

The cumulative Cmineralizationwas plotted against the time (t)and a parallel zero plus first order kinetic model was fitted to thedata using the LevenbergeMarquardt algorithm:

CðtÞ ¼ CAf�1� EXP

��kf*t

��þ ks*t (1)

This model assumes that the organic matter consists of an easilymineralizable C pool (CAf), which is mineralized according to first-order kinetics, and a more resistant fraction that is mineralizedaccording to zero-order kinetics (Sleutel et al., 2005). In Equation(1), kf is the mineralization rate of the fast degradable C pool and ksthe mineralization rate of the slow C pool (Sleutel et al., 2005). Thebiological significance of the model should help us explaining theobserved patterns in the short term C mineralization after biocharadditions.

Net C mineralization (Cmin net) was calculated as follows:

Cmin net ¼ Cmin biochar treatment � Cmin controlCsoil þ Cbiochar

(2)

with Cmin biochar treatment and Cmin control the amount of CO2 emittedfrom the biochar and control treatment, and Csoil and Cbiochar theSOC content and the C content of the corresponding biochar,respectively. Our set up could not discriminate between soil CO2and biochar CO2. However, by subtracting the control CO2 from theemitted CO2 per treatment and expressing this relative to theamount of C in biochar and soil, we got an indication of the bulk CO2

mineralization from the different biochar treatments. Additionally,we specifically selected a soil with a low SOC content (0.73%) tominimize the potential priming of SOC or absorption of soil CO2onto the biochar.

Net N mineralization (3) was calculated as:

Nmin net ¼ Nmin biochar treatment � Nmin controlNsoil þ Nbiochar

(3)

with Nmin biochar treatment and Nmin control the amount of mineral N(NO3

� and NH4þ) at the end of the incubation in the biochar and

control treatment, and Nsoil and Nbiochar the N content of the soiland corresponding biochar, respectively.

Principal component analysis (PCA) was also undertaken on thenmol % composition of all PLFAs present in a proportion of morethan 1% of the total amount of PLFAs. Treatment effects on cumu-lative CO2 and N2O emissions, dehydrogenase activity and Cmicwere assessed by one-way ANOVA and Tukey’s post-hoc test in IBMSPSS Statistics 19 (SPSS inc.). Not all variables were normallydistributed, therefore non-parametrical correlation analyses werecarried out between the net C mineralized and the soil biologicalmeasures and biochar characteristics (C mineralization experi-ment) and between the cumulative N2O emission and biocharcharacteristics (N2O emission experiment).

Table

1Pe

rcen

tage

bioc

har

yield,C

andNco

ntent,C:N

ratio,

moisture

content,ashco

ntent,vo

latile

matter,an

dpHH

2Oof

theproducedbioc

hars(m

eanva

lues

�stan

darderror,n¼

2),surfacearea

,ave

rage

poresize

andporevo

lume

(mea

suredviaBET

analysis).Differentlettersindicatesign

ificantdifferencesbe

twee

nthetrea

tmen

ts(P

<0.05

).

Bioch

artype

Bioch

aryield(%)

Cco

ntent(%)

Nco

ntent(%)

C:N

(e)

Moisture

content(%)

Ash

content(%)

Volatile

matter(%)

pHH

2O1:10

(e)

Surface

area

(m2g�

1)

Ave

rage

poresize

(nm)

Pore

volume

(mm

3g�

1)

DS3

5061

39.7

�0.6b

2.15

�0.02

c18

.4�

0.6a

4.23

�0.24

b2.48

�0.64

b29

.19�

0.44

b10

.1�

0.27

b1.32

3.89

4.35

DS7

0031

35.6

�1.9a

1.03

�0.02

b34

.5�

1.9a

3.04

�0.06

ab2.75

�0.22

b10

.37�

1.89

a11

.6�

0.04

c9.02

6.74

15.66

WS3

5059

67.1

�0.05

d1.06

�0.00

6b63

.2�

0.05

a4.20

�0.33

b0.23

�0.03

a35

.64�

1.33

c8.1�

0.19

a0.68

4.21

1.01

WS7

0035

80.3

�0.02

e1.11

�0.05

b74

.9�

0.06

a2.85

�1.00

ab1.28

�0.15

ab14

.07�

0.01

a11

.1�

0.42

bc

2.17

7.06

5.09

N. Ameloot et al. / Soil Biology & Biochemistry 57 (2013) 401e410404

3. Results

3.1. Biochar production and characterization

The fraction recovered as biochar after pyrolysis (biochar yield),C and N content, ash and volatile matter content, pH and the resultsof the BET analysis for the five biochars are given in Table 1. Biocharyield decreased with increasing pyrolysis temperature. A higherrecovery at 350 �C may be attributed to a minimal condensation ofaliphatic compounds, and limited losses of CH4, H2 and CO(Demirbas, 2001, 2004). The C:N ratios of the digestate biocharswere lower than the C:N ratios of the willow wood biochars, whilethe C:N ratios of the biochars were highest at the highest pyrolysistemperature. The ash contents were highest in the digestate bio-chars, while the volatile contents of biochars decreased withincreasing pyrolysis temperature. Volatile matter contents of thebiochars, produced under the same pyrolysis temperatures, were inthe same range (20e30% for the 350 �C biochars, 10e15% for the700 �C biochar). The pHH2O of the digestate and WS700 biocharswas highest, while the WS350 had a lower pHH2O. The surface area,pore volume and average pore size was lower in the wood biocharsthan in the digestate biochars, and increased with increasingpyrolysis temperature.

3.2. C mineralization from biochar amended soils

After 117 days of incubation, the cumulative CO2 emissions fromthe 350 �C biochar treatments were higher compared to the controltreatment and the other biochar treatments (Fig. 1). Although theerror bars overlap, a lower 117-days cumulative CO2 emission (Cmin)was observed in the DS700 biochar treatments compared to thecontrol, while the WS700 biochar treatments and the control hada similar CO2 emission pattern. A significant positive non-parametrical correlation existed between the parameter CAf(Table 2) and the volatile matter content of the biochars (n ¼ 4,r ¼ 1.00, P < 0.01). The cumulative amount of emitted CO2 waspositively correlatedwith the total PLFAs (Table 3). At the end of theincubation, the net amount of C mineralized (expressed asa percentage C present in added biochar and soil OC) was highest inthe DS350 treatment, followed by the WS350, DS700, and WS700treatments (Table 2).

PCA of the major PLFAs (all PLFAs present in a proportion ofmore than 1% of the total amount of PLFAs) satisfactorily discrim-inated the different biochar treatments from each other and fromthe control. The first two principal components (PCs) togetherexplained 65.8% of the total variation in the data (Fig. 2). The PCscorrelated meaningfully with the individual PLFAs (loading plot inFig. 3). High negative loadings on the PC1 axis, as was the case forthe DS350, WS350, corresponded to high contents of a15:0, i15:0and i16:0 all marker PLFAs for Gram-positive bacteria. The PLFAs10Me16:0 (an indicator for actinomycetes), and 20:4 and 20:5(proposed indicators for eukaryotes) positively loaded PC1 (48.7%of total variation). PC2 explained 17.1% of the variation in the datawith mainly positive loadings from 16:1u5 (AMF), 16:1u7 and18:1u7 (Gram-negative bacteria), and negative loadings from 16:0.PC2 primarily discriminated both digestate biochar treatmentsfrom all other treatments, including the control. The biomarker forGram-negative bacteria cy19:0 was absent in all treatments, whilecy17:0 was absent in the 700 �C biochar treatments.

Compared to the control, dehydrogenase enzyme activity wassignificantly (P < 0.05) higher in the 350 �C biochar treatments,while it was lower in the 700 �C biochar treatments (Fig. 4). Thedehydrogenase activity correlated positively with the cumulativeamount of emitted CO2 and with the total PLFAs (Table 3). Biocharapplication increased Cmic compared to the control treatment,

Fig. 1. Cumulative C mineralization (mg C 100 g�1 soil) from the different treatments after 117 days (C mineralization experiment). Error bars indicate standard deviations (n ¼ 3).

N. Ameloot et al. / Soil Biology & Biochemistry 57 (2013) 401e410 405

although only significantly (P < 0.05) for the DS350, WS350 andWS700 treatments (Fig. 5). Cmic was positively correlated with thetotal extracted PLFA, the cumulative CO2 emission and with the pH(Table 3). At the end of the incubation experiment pH hadincreased in all biochar treatments (Table 4), with the lowest pH inthe WS350 treatment, followed by the WS700, DS350 and DS700treatments. The pH at the end of the incubation correlatedsignificantly with the Cmic (Table 3). At the end of the incubationthere was only a significantly (P < 0.05) higher mineral N contentin the DS350 treatment compared to the control (Table 4). Themineral N content at the end of the incubation in all treatmentsmainly consisted of NO3

�eN (data not shown), and shows thatproduced NH4

þ was rapidly nitrified, immobilized or adsorbedonto the biochar surface. For a given feedstock, highertemperature during slow pyrolysis resulted in lower absolute Nmineralization rates. Net N mineralization rates were in theorder DS350 > DS700 > WS350 > WS700 (Table 4). Net Nimmobilization (Nnet min < 0) occurred in the WS700 treatments.There was neither N mineralization nor immobilization in theWS350 treatments (Nnet min ¼ 0), while net N mineralizationoccurred in the other biochar treatments (DS350 > DS700). Net Nmineralization decreased with increasing pyrolysis temperature,while the woody biochars had lower Nnet min rates than thedigestate biochars. The amount of N mineralized was not corre-lated with other soil biological and chemical parameters (Table 3).

Table 2Parameters of the parallel zero and first order kinetic model of the C mineralizationdata � standard errors (Equation (1)) and the net mineralized C (Cnet min) (Equation(2)). Different letters indicate significant differences after one way ANOVA and post-hoc Tukey tests (P < 0.05).

Biochar type CAf kf ks Cnet min (%)

Control 32.2 � 3.2 3.63 � 0.33 1.04 � 0.28 e

DS350 55.4 � 2.1 4.65 � 0.19 0.62 � 0.05 3.45 � 0.15c

DS700 33.9 � 2.8 3.57 � 0.26 0.70 � 0.12 0.30 � 0.53a

WS350 61.0 � 10.5 4.25 � 0.87 0.46 � 0.13 2.15 � 0.11b

WS700 35.5 � 3.1 3.37 � 0.29 0.71 � 0.13 0.14 � 0.31a

3.3. N2O emission from biochar amended soils

The cumulative N2O emission after 15 days was significantlylower in the 700 �C biochar treatments compared to the control,while no significant differences were found for the 350 �C biochartreatments (Fig. 6). Biochars produced under the same pyrolysistemperatures had similar N2O emission patterns. We calculated theN2O fluxes, relative to the amount of mineral N from the KNO3solution and mineralized from the different treatments (Table 4)(assuming a linear N mineralization over time like Oelmann et al.,2005). There was no significant difference between the N2O fluxof the DS350, WS350 and control treatment (3.61 � 0.05a,3.34 � 0.07a and 3.42 � 0.08a, respectively), however the N2O fluxwas significantly lower in the DS700 and WS700 treatments(1.62 � 0.04b and 1.71 � 0.07b, respectively). The N2O fluxes werethus reduced by 50% due to the addition of the 700 �C biocharscompared to the 350 �C biochar and control treatments. There wasa positive correlation between the cumulative N2O emission andthe volatile matter content of the biochars (n ¼ 4, r ¼ 0.961,P < 0.05) and a negative correlation between the cumulative N2Oemission and the average pore size of the biochars (n ¼ 4,r ¼ �0.996, P > 0.01).

Table 3Spearmans’ rho values of the non-parametrical correlations (n ¼ 15) between thedehydrogenase activity (DA) (mg TPF g�1), the microbial biomass carbon (Cmic)(mg Cmic g�1), the cumulative C mineralization (Cmin) (mg CO2eC g�1), the total PLFAs(nmol g�1), the mineral N content (Nmin ¼ NO3

�eN þ NH4þeN) (mg N g�1) and the

pHH2O at the end of incubation experiment 1.

Cmic Cmin Total PLFAs Nmin pHH2O

DA 0.464 0.689** 0.696** 0.236 �0.398Cmic 0.675** 0.750** 0.061 0.689**Cmin 0. 846** 0.414 0.194Total PLFA 0.168 0.097Nmin 0.448

**Correlation is significant at 0.01 level.

Fig. 2. PCA ordination based on mol % PLFA of individual PLFAs from the biocharamended and control samples; the first and second principle components are given.Percentage of variance explained by each component is indicated within parenthesison each axis.

Fig. 4. Dehydrogenase enzyme activity (mg TPF g�1 soil) of the different biochartreatments and the control treatments after 117 days (incubation experiment 1). Errorbars indicate standard deviations (n ¼ 3). Different letters indicate significant differ-ences between the treatments (P < 0.05).

N. Ameloot et al. / Soil Biology & Biochemistry 57 (2013) 401e410406

4. Discussion

Feedstocks for producing biochar will have alternative uses inmost cases. It is therefore important to question the rationale forusing a particular feedstock for making biochar.We used feedstocksfrom willow wood and swine manure digestate. The willow woodwas obtained from a municipal park maintenance service and itsalternative use is in the production of green waste compost that iscommonly applied to agricultural land. In this sense, the final

Fig. 3. Plot of correlation of the primary loading PLFAs with PC1 and PC2.

destination is similar as for the biochar, and there is no competitionfor e.g. bioenergy production. The swine manure digestate needs tobe dried prior to pyrolysis, which obviously is an energy consumingstep. However, drying is a mandatory step in manure processing inFlanders, irrespective of its final destination. At this moment, muchof the dried digestate is exported, and biochar production fromdigested swine manure does not require additional energyconsumption (as compared to alternative uses) prior to pyrolysis.

Fig. 5. Microbial biomass C (mg Cmic g�1 soil) of the different biochar treatments andthe control after 117 days (incubation experiment 1). Error bars indicate standarddeviations (n ¼ 3). Different letters indicate significant differences between thetreatments (P < 0.05).

Table 4The pHH2O (1:5), mineral N content (Nmin) and the net N mineralized (Nnet min)(Equation (3)) at the end of the C mineralization experiment. Different lettersindicate significant differences between the treatments (P < 0.05).

Treatment pHH2O Nmin (mg N g�1) Nnet min (%)

Control 5.97 � 0.01a 46.9 � 5.5ab e

DS350 7.15 � 0.04e 75.5 � 4.9c 3.04 � 0.52d

DS700 7.51 � 0.01f 50.2 � 1.2b 0.42 � 0.16bc

WS350 6.45 � 0.03c 44.7 � 4.6ab �0.28 � 0.59ab

WS700 6.88 � 0.07d 38.7 � 2.4a �1.03 � 0.31a

N. Ameloot et al. / Soil Biology & Biochemistry 57 (2013) 401e410 407

The application rate of 10 Mg of biochar ha�1 was area-based,and was equivalent to a biochar to soil ratio of 1:69 on a massbasis. Given the filling height of the soil in the tubes (5 cm), fieldincorporation of biochar at the same concentration to a depth of e.g.25 cm would result in an application rate of 50 Mg ha�1. Otherauthors have applied similar or even higher amounts of biochar, e.g.40 Mg ha�1 (Augustenborg et al., 2012), 50 Mg ha�1 (Chan et al.,2008), 90 Mg ha�1 (Zimmerman et al., 2011) and 180 Mg ha�1

(Zavalloni et al., 2011). Such application rates are high, but biocharapplication does not need to be repeated yearly because of itsrecalcitrance in soil.

Enhanced C mineralization of biochar amended soils may be dueto (i) biochar consumption by microorganisms, to (ii) increasednative SOM mineralization (priming) or to (iii) abiotic release ofbiochar-C (Bruun et al., 2008; Cross and Sohi, 2011; Foereid et al.,2011; Jones et al., 2011). In our study, we observed higher net Cmineralization from low temperature biochars compared to thecontrol and the treatments with high temperature biochars, whichhas been previously observed by others (Zimmerman, 2010; Crossand Sohi, 2011). Furthermore, volatile matter content decreasedwith increasing pyrolysis temperature. This decreasing volatilematter contentmaybe attributed to lower recondensation of volatilecompounds into the aromatic biochar matrix (Smith et al., 2010;Cross and Sohi, 2011).

Fig. 6. Cumulative N2O emissions (mg N g�1 soil) from the different treatments after 15

The model parameter for the easily mineralizable C pool (CAf)was positively correlated with the higher volatile matter content inthese biochars. This correlation should be interpreted with caution,because the volatile matter content was much larger than theamount of easily mineralizable C and the amount of C mineralizedover the entire incubation. However, if this correlation is causal, itsuggests that microbial consumption of labile biochar componentswas a driver of increased (net) C mineralization in soils amendedwith low temperature biochars. For the treatments with the lowtemperature biochars, the higher C mineralization was logicallyaccompanied by an increase in Cmic and in dehydrogenase activity.Dehydrogenase is an intracellular enzyme participating in theprocesses of oxidative phosphorylation of microorganisms,assumed to be linked with microbial respiratory processes (Alefand Nannipieri, 1995; Insam, 2001) and has often been correlatedto the availability of organic matter in the soil (Serra-Wittling et al.,1995; Moeskops et al., 2010). It is probably the higher availability ofvolatiles in the low temperature biochars, which triggered thesehigher dehydrogenase enzyme activities. In a sandy loam soil witha texture comparable to the soil we used, increased enzymeactivities of b-glucosidase and b-N-acetylglucosaminidase wereobserved after the addition of 2% (w:w) fast pyrolysis 500 �C bio-char, with 40% volatile compounds (Smith et al., 2010; Bailey et al.,2011). These and our results suggest volatile compounds of thebiochars to be involved in the enzymatic stimulation after biocharadditions to the soil. For the treatments with the high temperaturebiochars, however, the increased microbial biomass C co-occurredwith a lower C mineralization rate and dehydrogenase enzymeactivity. Bailey et al. (2011) suggested that enzymes may be inac-tivated in biochar amended soils, by blocking or absorption of thesubstrate. A much lower dehydrogenase activity in the hightemperature biochar treatments compared to the unamendedcontrol soil would support this hypothesis although dehydrogenaseis an intracellular enzyme. The increased Cmic together with thelower C mineralization rates after the addition of the 700 �C bio-chars imply that the microbial community was less active in these

days (N2O emission experiment). Error bars indicate standard deviations (n ¼ 3).

N. Ameloot et al. / Soil Biology & Biochemistry 57 (2013) 401e410408

treatments compared to the control. This higher Cmic seemscontradictory given the fact that these biochars have the lowestvolatile matter content and are thus the most stable biochars. Onepossible explanation is that during fumigation with chloroform,some biochar compounds might have been released from the700 �C biochars, leading to higher K2SO4 extractable OC in thefumigated samples, as Bruun et al. (2008) and Kuzyakov et al.(2009) suggested. However, the Cmic was significantly correlatedwith the total PLFA concentration (Table 3), which does not involvefumigation. Furthermore, we observed that Cmic was positivelycorrelated with the pH at the end of the incubation, suggesting thatthe liming potential of biochar is of importance in the stimulationof microbial biomass after the addition of biochar. Additionally,higher Cmic might be due to the protection of micro-organisms inthe biochar pores of the 700 �C biochar treatments compared to theunamended control (Table 1). Increased porosity with increasingpyrolysis temperatures has been reported by other authors, and isdue to dehydroxylation during pyrolysis at higher temperatures(Daud et al., 2001; Chan et al., 2008; Downie et al., 2009). Averagepore size was higher in the 700 �C (Table 1) than in the 350 �Cbiochars. Although the pore size was small to have biologicalsignificance (Hassink et al., 1993), most probably the amount oflarge pores (>50 nm) will have increased also. This might haveresulted in increased protection from bacterial grazers.

For the slow temperature biochars, the magnitude of N miner-alization decreased with increasing biochar C:N ratio, as was alsoobserved with other organic amendments (Kuzyakov et al., 2000).

The PCA of the relative PLFA concentrations after 117 days ofincubation resulted in a clear discrimination between most treat-ments, showing that different microbial communities establishedafter the addition of the different biochars. The PCA scores plot(Fig. 2) and the PCA loading plot (Fig. 3) suggest that Gram-positivebacteria are relatively more abundant in the low temperature slowpyrolysis biochar treatments, which seemed to have the largestimpact on the microbial community structure. Actinomycetes andeukaryotes were relatively more abundant in the control treatmentand the DS700 treatment. The second PC was positively loaded byPLFA biomarkers for AMF and Gram-negative bacteria and nega-tively by the 16:0 PLFA and differentiated the digestate biochartreatments from the other treatments. Fungal stimulation due tothe addition of fresh digestate has been reported by Elfstrand et al.(2007), which they attributed to the high C:N ratios of these soilamendments. However, the digestate biochars did not have higherC:N ratios and the fungal biomarkers were not more abundant inthe digestate biochar treatments, and it is thereforemore likely thatlower values of the 16:0 PLFA, universally occurring in themembranes of all organisms (Denef et al., 2009), in the digestatebiochar treatments were mainly responsible for the high positiveloadings on the PC2. The few published studies on the effect ofbiochar on PLFA soil profiles showed divergent microbial commu-nity structures after several biochar additions compared to controltreatments (Birk et al., 2009; Steinbeiss et al., 2009). Unlike Birket al. (2009), we did not find a significant positive correlationbetween the soil pH and the Gram-negative bacterial abundance,but the absence of Gram-negative bacteria in the 700 �C treatmentsmatches with the decreased Gram-negative abundance in charcoalamended tropical soils (Birk et al., 2009). Steinbeiss et al. (2009)reported increasing Gram-negative bacterial abundance in anagricultural loamy soil with hydrothermal biochars compared tothe control, with a higher increase in the treatment with the leaststable material. Likewise we observed higher Gram-negativeabundance in the treatments with 350 �C biochars. This suggeststhat the occurrence of Gram-negative bacteria in biochar treat-ments is closely related to the content of easily available substrate(VM) in the biochar. All biochar treatments increased the Gram-

positive bacterial abundance in our study, except the DS700treatment. Increased abundance of Gram-positive bacteria due tothe presence of biochar was also observed by Birk et al. (2009) andSteinbeiss et al. (2009). Despite the absence of plants, we observeda remarkable increase in the 16:1u5 AMF marker PLFA in the lowtemperature biochar treatments compared to the control treat-ment. Furthermore, a positive non-parametrical correlationbetween the concentration of 16:1u5 PLFA and the pH (n ¼ 15;r ¼ 0.713; P < 0.01), suggests that the AMF stimulation was linkedto the liming potential of the biochars. Similar conclusions havebeen drawn by Warnock et al. (2007) through reviewing theavailable literature dealing with the effect of biochar on AMF.However, as a cautionary remark, it should be emphasized that16:1u5 is a poor indicator of AMF in soils with a high bacterialbiomass (Frostegård et al., 2011), as was the case in our data.

Conditions necessary for N2O emissions to occur in soils are a)anaerobic conditions, b) decomposable organic carbon, c) mineralN supply, d) low pH and e) the presence of denitrifying organismslike Pseudomonas nautica, Achromobacter cycloclastes, and Para-coccus denitrificans (Kammann et al., 1998; Simek and Cooper,2002; Dalal et al., 2003; Richardson et al., 2009). Biochar addi-tions to soil may decrease N2O emissions as a result of severalpossible mechanisms. Firstly, N2O emissions can be decreasedcompared to the control due to an increase in soil pH by theaddition biochars (Table 4) (Simek and Cooper, 2002). Secondly, theaddition of porous biochars (Table 1) may increase soil aeration(Downie et al., 2009), which suppresses denitrification as has beensuggested by other authors (Yanai et al., 2007; Singh et al., 2010;Van Zwieten et al., 2010; Taghizadeh-Toosi et al., 2011a). A thirdmechanismmay be the retention of NO3

� onto the biochar surface,as was observed in the short term by Cheng et al. (2008), whichshould decrease the N2O emissions (Karhu et al., 2011). Thesignificant reduction in N2O emissions from the 700 �C biochartreatments compared to the control could thus be explained bythese mechanisms. In the 350 �C biochar treatments significant netN mineralization occurred, while the high amounts of volatilebiochar compounds likely acted as decomposable organic carbonsource for denitrifying organisms (there was a positive correlationbetween the volatile matter content of the biochars and the N2Oemissions from biochar-amended soils). The production of NO3

�

through mineralization and nitrification and the provision ofa readily available substrate may explain why we observed noreduction in N2O emission from the 350 �C biochar treatmentscompared to the control.

Volatile matter content seems thus to be an important biocharcharacteristic explaining N2O and CO2 emissions from biocharamended soils, in the short term. From the moment this readilyavailable substrate is depleted, C mineralization rates of theremaining aromatic biochar matrix will most probably drop(Kuzyakov et al., 2009; Cross and Sohi, 2011). In the long term, weexpect Cmineralization rates to drop to rates equal to or lower thanthe control. We expect that once the readily available substrate isdepleted N2O emissions in the 350 �C biochar treatments willdecrease. However, the long term N2O emissions from biocharamended soils may still be influenced indirectly as a result ofpossible alterations in physical and chemical soil propertiesfollowing biochar addition.

5. Conclusions

This study demonstrates that slow pyrolysis temperatures shapethe differences in GHG emission from slow pyrolysis biocharamended soils, independently from the biochar feedstock. CO2 andNO2 emissions were higher in the 350 �C biochar treatmentscompared to the 700 �C bicohar treatments. Pyrolysis at 350 �C

N. Ameloot et al. / Soil Biology & Biochemistry 57 (2013) 401e410 409

resulted in biochars with higher volatile matter contents than thecorresponding 700 �C biochars. This volatile matter content of thebiochar was correlated to the short term CO2 and NO2 emissionsfrom soils amended with biochar and stimulated the soil microor-ganisms by the provision of a readily available substrate. Thereforewe suggest that this is an important biochar property, influencingthe differences in the short term emissions from biochar amendedsoils. The correlations observed here between volatile matter andN2O and CO2 emissions, however, should be interpreted withcaution and are only tentative. Additional research involving moretypes of biochar and/or different pyrolysis conditions are needed toconfirm the observations in this study.

Microbial biomass carbon (Cmic) and dehydrogenase enzymeactivities were clearly correlated to C mineralization. All biochars,except the DS700, increased the abundance of Gram-positivebacteria, while there was a higher abundance of Gram-negativebacteria in the 350 �C biochar treatments than in the other bio-char treatments.

In the 700 �C biochar treatments N2O fluxes were reduced by50% compared to the control, while there was no significantlydifferent N2O flux in the 350 �C biochar treatments compared to thecontrol.We suggest that N2O emissions frombiochar amended soilswere suppressed due to the addition of biochar by an increase in (i)soil pH, (ii) soil aeration and (iii) short term retention of nitrate ontothe internal biochar surface. In the 350 �C biochars, these denitri-fication suppressing mechanisms were counteracted by the provi-sion of easily available substrate through volatile biocharcompounds.

Acknowledgments

The authors acknowledge the financial support for this work bythe Research Foundation, Flanders (FWO project 3G010008) and bythe Special Research Fund of Ghent University (BOF-UGent project01J16907). K. Jegajeevagan is the recipient of a VLIR-UOS PhDscholarship. We want to thank Renzo De Roose from Biogastec andViooltje Lebuf and Frederik Accoe from VCM, to provide us with thedigestate feedstock and helpful advice. Thanks to Tom Planckaert,Luc Deboosere, Tina Coddens, Mathieu Schatteman and SofieSchepens for the lab assistance. We gratefully acknowledge thecritical comments and suggestions of two anonymous reviewerswho helped to improve the quality of the paper.

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