Measurement of biochar properties, including

aromatic carbon, and monitoring the

concentration of charred material in soil using

NIR spectroscopy

BAMBANG H. KUSUMO

With the collaboration of P. BISHOP,

R. CALVELO PEREIRA, M. CAMPS ARBESTAIN,

C.B. HEDLEY, M.J. HEDLEY, A.F. MAHMUD,

and T. WANG

Introduction

• Conversion of biomass to biochar increases the residence time of C

in soil relative to that of the original feedstock

• It is proposed as a strategy able to reduce the release of CO2 to the

atmosphere

• Techniques and protocols are required to monitor and confirm

biochar stability in soil over time

Biochar

Massey University Farm

Uniform Biochar ApplicationBiomass Biochar

Introduction

• Application rates of biochar to soil will reflect cost of production,

transport and application (≤10 t ha-1 ~ 1% topsoil)

• NIRS techniques have been successfully used to measure C in soil.

But not yet widely used to measure biochar properties

In situ NIRS Measurement

Landcare Research Palmerston North, NZ

1. Can NIRS be used to measure biochar stability

parameters, e.g., aromatic C and molar H/Corg

ratio?

2. Can NIRS be used to measure biochar

concentration in soil at low (narrow range) to high

(wide range) rates of application?

3. Can NIRS – discriminant analysis be used to detect

biochar in soil?

Questions ?

1. Can NIRS be used to measure

biochar stability parameters, e.g.,

aromatic C and molar H/Corg ratio?

1st Study

Eucalyptus Pine Willow Poplar Manure BiosolidEucalyptus

LeavesChickenmanure

Poultrylitter

Papersludge

Materials and Methods

(ParLes; Viscarra Rossel, 2008)

Pyrolysis 250, 350, 450, 550 °C

The biochar samples were scanned

Spectral pre-processing (ParLes)

PCA analysis (ParLes)

Discriminant Analysis (MINITAB 16)

PLSR was used to build calibration models

25 biochar samples were analysed

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

400 600 800 1000 1200 1400 1600 1800 2000 2200 2400

Ref

lect

ance

Wavelength (nm)

MAe250

MAe350

BSe550

MAe450

BSe250

BSe350

BSe450

EuW400A

EuW550A

EuW400

EuW550

EuL400A

EuL550A

PS550A

PL400

PL550A

CM400

CM550A

PI-400

PO-400

WI-400

PO-550

WI-550

M-C-1

M-C-2550oC

Water Absorption

OH Absorption

Vis-NIR Spectra of 25 Biochars

Higher maximum pyrolysis temperatures reduced NIR reflectance

- Pyrolysis removes water and alcohols from feedstock

0.00060.00040.00020.0000-0.0002-0.0004

0.0002

0.0001

0.0000

-0.0001

-0.0002

-0.0003

PC1 (37.2%)

PC

2 (

8.9

%)

Biosolid+Wood

Leaves

Manure

Manure+Wood

Paper sludge

Wood

Feedstock

Manure or may contain decomposed plant tissue

May contain wood/plant tissue

Unknown

PCA Score Plot of Biochar Spectral data based on:

Feedstock

0.00060.00040.00020.0000-0.0002-0.0004

0.0002

0.0001

0.0000

-0.0001

-0.0002

-0.0003

PC1 (37.2%)

PC

2 (

8.9

%)

Unknown

250

350

400

450

550

Temperature

250-350oC

400-450oC

550oC

Unknown

Temperature of Pyrolysis

0.00060.00040.00020.0000-0.0002-0.0004

0.0002

0.0001

0.0000

-0.0001

-0.0002

-0.0003

PC1 (37.2%)

PC

2 (

8.9

%)

< 35%

> 65%

35-65%

Aromatic C

< 35%

> 65%

35-65%

Aromatic C

0.00060.00040.00020.0000-0.0002-0.0004

0.0002

0.0001

0.0000

-0.0001

-0.0002

-0.0003

PC1 (37.2%)

PC

2 (

8.9

%)

< 0.7

> 0.7

Ratio

H/Corg

H/Corg

Observation Predicted group From group Square distance Proba

bility

Archaeological charcoal 1

(M-C-1)350oC

250oC 394.291 0.000

350oC 378.434 1.000

400oC 439.338 0.000

450oC 536.841 0.000

550oC 569.557 0.000

Archaeological charcoal 2

(M-C-2)250oC

250oC 1018.365 1.000

350oC 1279.314 0.000

400oC 1299.436 0.000

450oC 1469.148 0.000

550oC 1499.017 0.000

Put into groupTrue Group All Groups

250oC 350oC 400oC 450oC 550oC

250oC 3 0 0 0 0

350oC 0 3 0 0 0

400oC 0 0 6 0 0

450oC 0 0 2 2 1

550oC 0 0 0 0 8

Total number 3 3 8 2 9 25

Correct number 3 3 6 2 8 22

Proportion (%) 100 100 75.0 100 88.9 88.0

Linear Discriminant Analysis of Spectral Biochar Data based on

Temperature

NIRS can predict biochar Aromatic C(using band region: 780-2500 nm)

y = 0.8544x + 6.3034R² = 0.9261

RMSE = 5.336RPD = 3.62

0

10

20

30

40

50

60

70

80

90

0 10 20 30 40 50 60 70 80 90

NIR

S-P

red

icte

d A

rom

ati

c C

(%

)

13C NMR-Measured Aromatic C (%)

Vis-NIR Spectroscopy

13C NMR Spectroscopy

NIRS (780-2500 nm bands)

can predict Fixed C, H/Corg

Atomic Ratio, and

Fraction of Aromaticity (fa)

y = 0.8033x + 8.2847R² = 0.9155

RMSE = 6.009RPD = 3.26

0

10

20

30

40

50

60

70

80

90

0 10 20 30 40 50 60 70 80 90

NIR

S-P

red

icte

d F

ixe

d C

(%

)

Measured Fixed C (%)

y = 0.8694x + 0.0995R² = 0.921

RMSE = 0.041RPD = 3.56

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

1.1

0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1

NIR

S-P

red

icte

d f

a

Measured fa

y = 0.8843x + 0.0913R² = 0.9332

RMSE = 0.072RPD = 3.87

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6

NIR

S-P

red

icte

d H

/Co

rgA

tom

ic R

ati

o

Measured H/Corg Atomic Ratio

H/Corg

Fixed C

Fraction of Aromaticity

NIRS (780-2500 nm bands) can predict

Corg, H O & Ash content, Volatile Matter

content, O/Corg atomic ratio, and pH

r pH Corg (%) N (%) H (%) Ash (%) O (%) VM (%) FC (%) H /Corg O/Corg fa Aromatic C (%)

pH 1 0.128 0.237 -0.619* 0.144 -0.628* -0.579 0.287 -0.699* -0.457 0.683* 0.364

Corg (%) 0.128 1 -0.270 0.437 -0.916* -0.051 0.202 0.942* -0.579 -0.659* 0.123 0.916*

N (%) 0.237 -0.270 1 -0.078 0.317 -0.298 -0.103 -0.223 0.157 -0.167 -0.075 -0.265

H (%) -0.619* 0.437 -0.078 1 -0.618* 0.427 0.746* 0.208 0.439 -0.086 -0.760* 0.089

Ash (%) 0.144 -0.916* 0.317 -0.618* 1 -0.349 -0.451 -0.826* 0.348 0.347 0.115 -0.755*

O (%)1 -0.628* -0.051 -0.298 0.427 -0.349 1 0.594 -0.121 0.410 0.711* -0.479 -0.218

VM (%)2 -0.579 0.202 -0.103 0.746* -0.451 0.594 1 -0.083 0.424 0.215 -0.781* -0.140

FC (%)3 0.287 0.942* -0.223 0.208 -0.826* -0.121 -0.083 1 -0.715* -0.659* 0.373 0.971*

H /Corg -0.699* -0.579 0.157 0.439 0.348 0.410 0.424 -0.715* 1 0.593 -0.804* -0.783*

O/Corg -0.457 -0.659* -0.167 -0.086 0.347 0.711* 0.215 -0.659* 0.593 1 -0.352 -0.694*

fa4 0.683* 0.123 -0.075 -0.760* 0.115 -0.479 -0.781* 0.373 -0.804* -0.352 1 0.489

Aromatic C (%) 0.364 0.916* -0.265 0.089 -0.755* -0.218 -0.140 0.971* -0.783* -0.694* 0.489 1

Correlation matrix among the reference data

of biochar properties

VM = volatile matter, FC = fixed carbon, fa = fraction of aromaticity

Independent NIRS prediction between

Aromatic C and fraction of aromaticity (fa)

Aromatic C & fa; r = 0.489 Aromatic C prediction; R2 = 0.926 fa prediction; R2 = 0.921

Fraction of aromaticity

Aromatic C

Aromatic Carbon

VIP Bands of Various Biochar Properties

2nd Study

2. Can NIRS be used to measure

biochar concentration in soil at low

(narrow range) to high (wide range)

rates of application?

Pine-350

Biosolids-

550

pH 7.2 8.2

C % 75.9 35.6

N % 0.3 1.4

Ash % 2.6 51.2

Vol Matter % 30.2 13.4

Fixed C % 63.2 30.6

Materials and Methods

Wide range;

0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 75, 100% Biochar

Narrow range;0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2.0, 2.1, 2.2, 2.3, 2.4, 2.5% Biochar

Soils/substrate:

- Alfisol (silt-loam

Tokomaru)

- Entisol (sandy soil

Motuiti)

- Quartz

Marked change in soil spectral reflectance when 5% biochar was added

Fraction of Aromaticity(BS-550) = 87%(PI-350) = 73%

Total of Aromatic C(BS-550) = 309.7 g kg-1

(PI-350) = 554.1 g kg-1

Biochar

SpectraUV-Vis-NIR

NMR

** *

*

Aromatic C

Predicting Wide Range (0-100%)

Biochar Concentration in Soil using NIRS

Better prediction when soil + biochar types

were separated

Using NIR (780-2500 nm)

Using NIR (780-2500 nm)

Sandy Soil

Using NIR (780-2500 nm)

Silt Loam Soil

Using Vis-NIR Bands

780-1200 & 2100-2500 nm

Can biochar, with low concentration (0-2.5%) in soil, be predicted well using NIRS (780-1200 & 2100-2500 nm) ?

780-1200 & 2100-2500 nm

Finely Ground

the Sandy Soil

780-1200 & 2100-2500 nm

Finely Ground

the Sandy Soil

780-1200 & 2100-2500 nm

780-1200 & 2100-2500 nm

Sandy Soil

780-1200 & 2100-2500 nm

Silt Loam Soil

Very important bands (780-1200, 1835-1925 & 2100-2500)

VIP Bands and PLSR Coefficients

*) UV-Vis-NIR bands = 350-2500; **) Vis-NIR bands = 400-2500 nm; ***) NIR bands = 780-2500 nm

# Finely ground Motuiti soil = passed through 0.180 mm sieve

Sample Bands UsedNumber of

Samples

Number of

Factors

For PLSR model

Leave-one-out cross-validation

R2 RMSECV RPD

Motuiti (fine) # + BS-550 UV-Vis-NIR*) 26 5 0.455 0.585 1.31

Motuiti (fine)# + BS-550 Vis-NIR**) 26 5 0.428 0.624 1.23

Motuiti (fine)# + BS-550 NIR***) 26 5 0.767 0.378 2.02

Motuiti (fine)# + BS-550 780-1200 &

2100-2500 nm

26 5 0.964 0.143 5.37

Effect of band region selection and grinding on prediction accuracyfor one soil and biochar type

Sample Bands Used

Number

of

Samples

Number of

Factors

For PLSR

model

Leave-one-out cross-validation

R2 RMSECV RPD

Motuiti (coarse) + BS-550 UV-Vis-NIR*) 26 5 0.414 0.612 1.25

Motuiti (coarse) + BS-550 Vis-NIR**) 26 5 0.687 0.426 1.79

Motuiti (coarse) + BS-550 NIR***) 26 5 0.463 0.559 1.37

Motuiti (coarse) + BS-550 780-1200 &

2100-2500 nm

26 5 0.961 0.149 5.14

Sample Bands UsedNumber of

Samples

Number of

Factors

for PLSR

model

Leave-one-out cross-validation

R2 RMSECV RPD

Tokomaru (fine)+PI-350 and

Motuiti (fine) # +BS-550 UV-Vis-NIR*) 52 4 0.213 0.677 1.12

Tokomaru (fine) +PI-350

and Motuiti (fine) # +BS-550 Vis-NIR**) 52 4 0.232 0.686 1.10

Tokomaru (fine)+PI-350 and

Motuiti (fine) # +BS-550 NIR***) 52 4 0.858 0.228 2.63

Tokomaru (fine) +PI-350

and Motuiti (fine) # +BS-550780-1200 &

2100-2500 nm52 4 0.954 0.168 4.55

*) UV-Vis-NIR bands = 350-2500; **) Vis-NIR bands = 400-2500 nm; ***) NIR bands = 780-2500 nm

# Finely ground Motuiti soil = passed through 0.180 mm sieve

Effect of band region selection and grinding on prediction

accuracy of two soils and biochars

3rd Study

3. Can NIRS detect biochar in situ

in field soil?

BIOCHARBIOCHAR

BIOCHARBIO

CH

AR

• Core samples were scanned every 1 cm

Materials and Methods

6_22-BC*

Spectrum containing

biochar

Spectra with and without biochar

19_17-BC*

19_18-BC*

Spectra with and without biochar

0.030.020.010.00-0.01

0.002

0.001

0.000

-0.001

-0.002

PC1 (65.3% variance)

PC

2 (

5.5

% v

ari

an

ce

)

BC

NIL

Group

BC (Biochar)NIL

Marked influence of biochar in soil spectral reflectance

PCA Score Plot of 1690 Pre-Processed Spectral Data

(780-1200 & 2100-2500 nm) with and without Biochar

Put into groupTrue Group All

groupsBiochar NIL

Biochar 26 1

NIL 1 1662

Total number 27 1663 1690

Correct number 26 1662 1688

Correct

proportion (%)

96.3 99.9 99.9

•R to Log(1/R)•Wavelet detrending• Smoothing

(Savitzky-Golay•1st Derivative•Mean Centre

Raw Spectral Data

Pre-Processed

PCA

Scores of Principal

Components

Discriminant Analysis

Response Variables (e.g. NIL, biochar)

Result of Classification

Summary of Classification

Summary of Classification; Separate Calibration and validation set

Put into group

Calibration set (1000 spectra) Validation set (690 spectra)

True Group True Group

Biochar NIL All Biochar NIL All

Biochar 19 0 5 1

NIL 2 979 1 683

Total number 21 979 1000 6 684 690

Correct number 19 979 998 5 683 688

Correct proportion (%) 90.5 100 99.8 83.3 99.9 99.7

Measured vs. Predicted Total C from the Soil Cores

(using selected band region: 780-1200 & 2100-2500 nm)

NIRS prediction on cores without biochar

NIRS prediction on cores with biochar

Effect of added biochar on soil C (elemental analysis data)

Biochar

Effect of added biochar on soil C (NIRS-

predicted data)

CONCLUSIONS

• NIR reflectance spectroscopy has a potential use for

predicting biochar C aromaticity and other biochar properties

• Successful prediction of molar H/Corg indicates that NIRS can

be used as a quick assessment for C stability

• NIRS was able to predict biochar at low (narrow range, 0–2.5%

BC) and high (wide range, 0–100% BC) application rates

• Grinding the coarse soil and selecting the important bands

(780-1200 & 2100-2500 nm) improved the prediction accuracy

• NIRS – Discriminant Analysis can be used to detect biochar in

field soil

THANK YOU

Core C2

C2_46is grouped into

“containing biochar”