J. Pestic. Sci. 39(2), 105–114 (2014)
DOI: 10.1584/jpestics.D13-067

Original Article

Effects of organic carbon quality on the sorption behavior ofpesticides in Japanese soils
Yutaka Motoki,1,* Takashi Iwafune,2 Nobuyasu Seike,1Takashi Otani1 and Maki Asano1
1
National Institute for Agro-Environmental Sciences,
3–1–3 Kannondai, Tsukuba, Ibaraki 305–8604, Japan
2
Food and Agricultural Materials Inspection Center, Agricultural Chemicals Inspection Station,
2–772 Suzuki-cho, Kodaira, Tokyo 187–0011, Japan(Received September 24, 2013; Accepted March 18, 2014)
We analyzed the factors influencing pesticide sorption to soils by testing 17 pesticides with different polarity and chemical
structures in 8 soils, including major types in Japan. The soil–water distribution coefficients (Kd) were significantly positively
correlated with organic carbon (OC) content. However, the OC-normalized sorption coefficients (Koc) of many pesticides exhibited high variability among soils. Solid-state 13C nuclear magnetic resonance (NMR) was performed to elucidate the effect ofOC quality on Koc variability. The NMR results indicated that the aromatic carbon content in soil was positively correlated with
the Koc values of pesticides. The sorption pattern of pesticides to soils containing abundant aromatic carbon was influenced by
the differences in the molecular structures of pesticides, similar to that to activated carbon and graphite. The results indicate thearomatic carbon in soils, particularly black carbon, is an important factor influencing the sorption of pesticides to soils. © Pesticide Science Society of Japan
Keywords: pesticides, soil sorption, soil properties, organic carbon quality.
Electronic supplementary materials: The online version of this article contains supplementary materials (Supplemental Figures
S1–S3 and Supplemental Tables S1–S8), which are available at http://www.jstage.jst.go.jp/browse/jpestics/.

phobic interactions. Hence, soil sorption is strongly influenced
by OC content in soil. However, the Koc values of a pesticide
are highly variable, depending on the soil type.9–13) Soil OC isconsidered to comprise polysaccharides, lignin, tannins, aminoacids, and lipids as well as modified substances arising from theabiotic and biotic degradation of plant, microbial, and animal
remains in soils.14–16) Recent studies11–13) suggest that the variable physicochemical nature of soil OC is one reason for thevariability of Koc values. These studies investigated the relationship between Koc values and the chemical composition of OC bysolid-state 13C cross-polarization magic angle spinning nuclear
magnetic resonance (CPMAS NMR) spectroscopy, which provides the basic structural information of OC.17) The results ofthese studies demonstrate that Koc variability can be explainedby the difference in the OC quality of soils, i.e., the proportionsof aryl carbon, alkyl carbon, O-alkyl carbon, and carboxyl carbon in soil OC. Japanese arable land has a wide range of organiccarbon (up to 15%) because volcanic ash soil (i.e., Andosol) contains a large amount of organic carbon.18) Therefore, the variety of OC quality and variability of Koc values may be higher inJapanese soils than in non-Japanese soils.
In addition, recent studies report OC in soils includes black
carbon (BC) such as char and soot, which are products of theIntroduction
Soil sorption is one of the important processes in the fate andbehavior of pesticides in the environment. The soil–water distribution coefficient, Kd, and the organic carbon (OC)-normalized
sorption coefficient, Koc, are widely used to predict pesticidecontamination of groundwater1,2) and run-off properties frompaddy fields into rivers.3,4) Furthermore, sorption behavior affects the phyto- and bio-availability of pesticides in soils.5–7) The
pesticide regulatory system in Japan requires sorption studies
prior to the registration of newly developed pesticides. However,most data in registration dossiers are not disclosed in detail.
Japan is a typical volcanic country. Although volcanic ash
soils are widely distributed throughout Japan and cover approximately half of all upland fields,8) there is little available information on the sorption behavior of pesticides in Japanese volcanic
ash soils.
Nonionic pesticides generally sorb to soil particles via hydro* To whom correspondence should be addressed.
E-mail: ymotoki@affrc.go.jp
Published online April 27, 2014
© Pesticide Science Society of Japan

107

106 Y. Motoki et al.

Journal of Pesticide Sciencecients (log Kow), pKa, and octanol–water distribution coefficients(log D) between pH 4.5 and 7.5 were calculated using ACD/
ChemSketch 10.0 (ACD/Labs, Toronto, Canada) with ACD/logP
DB 10.0, ACD/pKa 10.0, and ACD/logD 10.0, respectively. The
log D values of all pesticides except imidacloprid and clothianidin calculated within the pH range showed the same predicted
log Kow value. Thus, it appears that almost all pesticides exist in
a neutral form within the above-mentioned pH range. All analytical standards (purity >97%) were purchased from Wako
Pure Chemical Industries, Ltd. (Osaka, Japan), Kanto Chemicals(Tokyo, Japan), and Dr. Ehrenstorfer GmbH (Augsburg, Germany). The pesticides were divided into 3 analytical groups on
the basis of the analytical methods described in section 4 below.
Stock solutions (100 µg/mL) of the pesticides were prepared in
acetone for each group.

incomplete combustion of vegetation by wildfires or humanactivity.19–22) BC strongly sorbs organic chemicals, including
pesticides. Yang et al.23) investigated the sorption of diuron on
soils amended with ash from the burning of crop residues; theyfound that diuron sorption increases with increasing soil wheat
ash content and is dominated by ash in soil with at least 0.05%
ash content. Likewise, Loganathan et al.24) show that the presence of 1% wheat char applied to soils controls the overall sorption of atrazine on soils. Although no quantification methods
for BC in soils have been established,25) Shindo et al.21) isolated
the charred plant fragments from Japanese Andosols by a specific gravity method and reported the percentage of OC content
of charred plant fragments in whole soil ranges from 3.4–33%.
However, there are no reports about the effect of BC-like materials present in Japanese Andosol on the sorption properties ofpesticides.
The objectives of this study are as follows: (i) to measure theKd values of 17 pesticides in 8 typical Japanese soils; (ii) to assess the relationships between Kd values and soil properties, particularly the contribution of OC to sorption properties and theextent of Koc variability in Japanese soils; and (iii) to investigate
the effects of the molecular nature of OC on Koc variability.

2. Soils
Eight Japanese soils with various physicochemical properties
were used (Table 2). Soil samples were air-dried and passed
through a 2.0-mm sieve. The pH and electrical conductivity(EC) of soils were measured in a soil/water (1 : 5 w/v) mixture
by a multifunction water quality meter (MM-60R; DKK-TOA,
Tokyo, Japan). The OC content was determined by the dry
combustion method with a CN coder (MT-700; Yanaco, Kyoto,
Japan). The cation exchange capacity (CEC) was determined bya shaking extraction method.29) The particle size distribution
was analyzed by the pipette method with a pipette apparatus(DIK-2020; Daiki Rika, Saitama, Japan).30) Meanwhile, soil texture was determined according to the standards developed byMaterials and Methods
1. Pesticides
Seventeen pesticides with varying hydrophobicity were used insorption tests (Table 1). The chemical structures and dissociation constants (pKa) of the test pesticides are shown in Supplemental Table S1. The predicted octanol–water partition coeffi-

Table 1. Octanol–water partition coefficient (log Kow) and analytical groups of test compounds
Compoundlog Kowa)

log Kowb)

log Kowc)

log Kowd)

Analytical group

Imidacloprid

0.57

0.57

0.57

−0.43, 0.20

A

Dimethoate

0.70

0.70

0.98

0.48

A

Clothianidin

0.91

0.70

0.70

−0.15, 0.40, 0.40

A

Thiacloprid

1.26

0.74

1.26

0.55

A

Metalaxyl

1.65

1.75

1.75

2.15

A

Fosthiazate

1.68

1.68

1.68

0.94

A

Methidathion

2.57

2.20

2.20

2.03

A

Fenobucarb

2.78

2.67

2.67

3.04

B

Flutolanil

3.17

3.17

3.77

3.70

B

Procymidone

3.30

3.14

3.30

2.67

B

Fenitrothion

3.32

3.43

3.43

3.24

C

Tetraconazole

3.56

3.56

3.53

3.19

C

Chloroneb

3.58

—e)

1.90

3.58

B

Diazinon

3.69

3.30

3.42

3.81

C

Cadusafos

3.85

3.90

4.08

4.28

B

Tolclofos-methyl

4.56

4.56

4.56

4.03

C

Tetradifon

4.61

4.61

3.95

5.52

C

a)
log Kow values were obtained from the Footprint Pesticide Properties Database of IUPAC.26) b) log Kow values were obtained fromThe Pesticide Manual (16th ed.).27) c) log Kow values were obtained from The 2011 Pesticide Handbook.28) d) Predicted log Kow values
using ACD/ChemSketch 10.0 with ACD/logP DB 10.0. The chemical structures of imidacloprid and clothianidin have 2 and 3 possible tautomeric forms, respectively. e) No data.

108

Vol. 39, No. 2, 105–114 (2014)

Effects of organic carbon quality on soil sorption of pesticides 107
Table 2. Properties of test soils

Soil

Classification

TextureCECb)(cmol(+)/kg)OCa) (%)

Clay (%)

pH (H2O)ECc) (mS/cm)

S1

Sand-dune Regosol

sand

0.06

3.4

2.4

7.5

0.04

S2

Gray lowland soil

sandy loam

0.85

12.2

14.6

4.8

0.26
0.09

S3

Yellow soil

light clay

1.02

11.4

39.0

5.3

S4

Brown forest soil

light clay

1.15

17.2

35.5

4.7

0.09

S5

Gray lowland soil

silty clay

1.46

18.2

25.3

5.8

0.17

S6

Andosol

loam

4.32

26.3

11.3

6.4

0.28

S7

Andosol

loam

5.21

33.8

10.8

5.5

0.15

S8

Andosolsilty loam

8.65

35.4

1.8

5.8

0.05

a)

Organic carbon content. b) Cation exchange capacity. c) Electrical conductivity.

the International Society of Soil Science31); soils were classified
according to the criteria adopted by the Cultivated Soil Classification Committee.32)

The mass balance (MB, %) was calculated as follows:

MB =100 ⋅ (Ce ⋅ Valiq + mE ) / Ci ⋅ V 

where Valiq is the volume of the aliquot taken from the supernatant (mL) and mE is the mass of pesticides extracted from the remaining sample after removal of the aliquot of supernatant (µg).

3. Sorption experiment for soils
Sorption experiments were carried out using a batch equilibration technique.33) CaCl2 (25 mL, 0.01 M) in distilled water wasadded to 5 g of soil in a 50-mL glass centrifuge tube. The openings of the tubes were covered with Teflon sheets and closedwith screw-caps. The tubes were agitated on a thermostat shaker(Taitec, Saitama, Japan) in the dark for 24 hr at 25±2°C. Aftershaking, 25 µL of acetone stock solution was added to the tubes.
The final concentration of each pesticide in the aqueous phase
was 0.1 µg/mL. The soil–solution mixtures were shaken again for
24 hr under the same conditions. After equilibration, the mixtures were centrifuged at 1,200×g for 30 min. A 15-mL aliquotof the supernatant was taken and used to analyze the concentrations of pesticides to determine Kd values. In addition, the masses of pesticides in the remaining samples were analyzed to calculate mass balance. All sorption experiments were performed in
duplicate except for experiments involving group B pesticides on
soil S7, which were performed in triplicate.
The mass fraction of pesticides sorbed on the soil phase atequilibrium, x/m (µg/g), was calculated by subtracting the massconcentration of pesticides in the aqueous phase at equilibrium,
Ce (µg/mL), from the initial mass concentration of pesticides inaqueous phase, Ci (µg/mL), as follows:x / m = (Ci − Ce ) ⋅ V / M 

4. Pesticide analysis
An aliquot of approximately 15 mL taken from the supernatant
was analyzed to quantify pesticides using 3 different methods
for each analytical group (Supplemental Figures S1–S3). The
aliquots were cleaned with a diatomite column (Inertsep Ksolute 20 mL; GL Sciences, Tokyo, Japan) followed by the following mini-columns: a PSA column (500 mg; Supelco, Bellefonte,USA), an Accell CM column (500 mg; Waters, Milford, USA),and an ENVI-Carb II/PSA column (500 mg/500 mg; Supelco)
for groups A, B, and C, respectively. The cleaned samples wereanalyzed by liquid chromatography-tandem mass spectrometry(LC-MS/MS) for group A (Supplemental Tables S2 and S3) andgas chromatography-mass spectrometry (GC-MS) for groups B
and C (Supplemental Tables S4 and S5).
The pesticides in the remaining sample were extracted by acetone after the supernatant was removed, and acetone (30 mL)
was added to the remaining sample. The tubes were shaken in athermostat shaker for 20 min at 25±2°C and subsequently centrifuged at 1,200×g for 10 min. The supernatant was carefully
removed. This extraction procedure was repeated twice. The collected supernatant was evaporated to approximately 10 mL witha rotary evaporator and analyzed using the same corresponding
method as mentioned in the above methods for each analyticalgroup.
A recovery test of the pesticides was performed with deionized water and test soils. Deionized water (15 mL) spiked at
1 ng/mL for all group pesticides and each soil (5 g) spiked at 5
and 3 ng/g for group A and groups B and C, respectively, wereanalyzed using the above-mentioned methods; however, 10 mLof deionized water was added to soil samples prior to acetone
extraction. The mean recovery from the 4 replicates for group
A and 5 replicates for groups B and C ranged from 71.1 to117.0% for all compounds; the coefficients of variation (CVs)(1)

where V is the solution volume (mL) and M is the soil mass (g).
The soil–water distribution coefficient, Kd (mL/g), was calculated using the following equation:

K d = (x / m) / Ce 

(2)

The OC-normalized sorption coefficient, Koc (mL/g), was determined by dividing the Kd values by OC content in soil as follows:

K oc = K d ⋅ (100 / %OC) 

(4)

(3)

where %OC is the percentage of OC in the soil sample (g/g).

109

108 Y. Motoki et al.

Journal of Pesticide Science

were below 16.7% for all compounds (Supplemental Tables S6and S7). The limits of quantification (LOQs) for pesticide analysis were calculated according to Japanese Industrial Standard(JIS) K 0312.34) The LOQs for all compounds in deionized waterand all soil samples ranged from 0.27 to 0.87 ng/mL and 0.19 to
5.48 ng/g, respectively (Supplemental Tables S6 and S7).

contact time of 1 msec, and a 3-sec pulse interval. Fourier transformation was conducted using a broadening factor of 100 Hz.
The 13C chemical shift scale was referenced to that of tetramethylsilane (0 ppm) calibrated using adamantane (29.5 ppm).
The 13C NMR spectra were integrated into 4 chemical shift regions: 0–45 ppm, alkyl carbon; 45–110 ppm, O-alkyl carbon;
110–160 ppm, aromatic carbon; and 160–190 ppm, carboxyl carbon.39) The relative proportions of each carbon type were calculated on the basis of the total carbon signal between 0 and
190 ppm.

5. Sorption experiment for carbonaceous materials
In order to investigate the effect of the chemical structure of pesticides on activated carbon (AC) and graphite (GP) sorption,
which was employed as a model substance for BC,35,36) the ACacetone and GP-acetone distribution coefficients (KAC and KGP,
respectively) of cadusafos, chloroneb, and procymidone, whichhave different chemical structures, were measured by a batch
equilibration technique. Acetone solutions (5 mL, 1 µg/mL) of
each pesticide were added to 50 mg of AC (SS1; Ajinomoto FineTechno Company, Kanagawa, Japan) and 0.5 g of GP (ENVICarb; Supelco) in a 10-mL glass centrifuge tube. The tubes wereagitated on a thermostat shaker in the dark for 24 hr at 25±2°C.
After shaking, the mixtures were centrifuged at 1,200×g for
30 min. Aliquots of the supernatant (500 µL) were spiked with
200 µL of acetone solution (2.5 µg/mL) of the internal standard(13C6-labeled fenthion), filtered through a 0.45-µm PTFE filter,
and analyzed by GC-MS (Supplemental Tables S4 and S5). KAC
and KGP were calculated from formulas (1) and (2) in the same
way as Kd. All sorption experiments were performed in triplicate.

7. Molecular modeling
The molecular structures of pesticides were geometrically optimized using the PM7 semi-empirical Hamiltonian function(keywords: EF, PRECISE, GNORM=0.05, GRAPHF, MMOK)
in the MOPAC 2012 package40) using the Winmostar program(X-Ability, Tokyo, Japan).

Results and Discussion
1. Relationships between soil–water distribution coefficients (Kd)and soil properties
The Kd and MB values of the 17 pesticides with 8 soils areshown in Supplemental Table S8. The MB of the sorption test
ranged from 70.0 to 114.6% for all experiments. The MB of some
sorption tests, particularly methidathion, was less than 80%.
Similarly, the mean recovery of methidathion on 4 soil samples
was less than 80%. Therefore, it is possible that the extraction ofmethidathion from the soil samples was insufficient. However,Kd values were calculated using quantitative values in the aqueous phase, and the mean recovery of methidathion from deionized water was 88.8%; therefore, there is no effect of extraction
efficacy from soil samples on the variability of Kd values. The
Kd values varied considerably with respect to the soil type fora given pesticide, ranging from 1.41 to 582 mL/g for tolclofosmethyl, which had the highest ratio between minimum andmaximum values.
In order to determine which soil properties influence the variability of Kd values, linear regression analysis between Kd values and soil properties was performed (Table 3). The Kd valuesof almost all pesticides were more strongly correlated with OCcontent or CEC than other soil properties such as pH, clay content, and EC. Hydrophobic interactions are generally known toplay an important role in the sorption of nonionic pesticides insoils; furthermore, OC content is positively correlated with theKd values of nonionic pesticides.10) On the other hand, little is
known about the relationship between CEC and the Kd valuesof nonionic pesticides. Although the strength of CEC in soils is
closely associated with negatively charged sites of OC and clay
minerals, several studies show that the contribution of OC to
CEC in soils is greater than that in clay minerals.41,42) Indeed, theOC content of test soils in the present study was positively correlated with CEC (r=0.93, p<0.001); therefore, Kd values appear
to be positively correlated with CEC.

6. Solid-state 13C NMR analysis
In order to perform solid-state 13C NMR analysis, 7 test soils(except soil S1, for which it seemed difficult to characterize OC
because of low OC content) were passed through a 0.2-mm sieve
and treated with hydrofluoric acid (HF) to concentrate the OC
and remove paramagnetic minerals. Although HF is a strong
agent, Rumbel et al.37) report that the chemical composition ofsoil organic matter does not change after 10% HF treatment.
Thirty milliliters of 8% (w/w) aqueous HF solution was added to
10 g of soil in a polyethylene tube. The tubes were shaken for 2 hr
at room temperature and centrifuged at 3,800×g for 15 min, andthe supernatant was discarded. The treatment was repeated 7
times using different shaking times (5×2 hr and 2×16 hr). Afterthe final treatment, 30 mL of deionized water was added to theresidues. The tubes were shaken for 30 min at room temperatureand centrifuged at 3,800×g for 15 min, and the supernatant was
discarded. The residues were washed an additional 7 times anddried at 50°C for 2 days. The dried samples were subsequently
powdered using a mortar and pestle.
The solid-state 13C NMR spectra of the powdered samples
were collected using the CPMAS technique by an FT NMR
system (Alpha 300; JEOL, Tokyo, Japan); the analytical conditions of NMR have been described previously.38) The powderedsamples were transferred into a zirconia rotor (6 mm i.d.) with a
KEL-F cap (JEOL, Tokyo, Japan), and the 13C NMR signals were
measured at 75.45 MHz with magic angle spinning of 6 kHz, a

110

Vol. 39, No. 2, 105–114 (2014)

Effects of organic carbon quality on soil sorption of pesticides 109

Table 3. Correlation coefficients (r) between the Kd values of pesticides and soil properties
CompoundNo. soils

r
OC

CEC

Clay

pH

EC

Imidacloprid

8

0.69

0.77*

−0.39

−0.06

−0.10

Dimethoate

4

0.39

0.70

−0.46

0.11

−0.05

Clothianidin

7

0.77*

0.87*

−0.63

0.27

−0.29

Thiacloprid

7

0.73

0.85*

−0.61

0.26

−0.26

Metalaxyl

7

0.53

0.68

−0.20

−0.08

−0.08

Fosthiazate

6

0.59

0.80

−0.46

0.26

−0.26

Methidathion

8

0.92**

0.87**

−0.52

−0.02

−0.24

Fenobucarb

5

0.52

0.75

−0.57

−0.14

−0.05

Flutolanil

7

0.56

0.74

−0.52

0.27

−0.04

Procymidone

7

0.52

0.72

−0.47

0.25

−0.05

Fenitrothion

8

0.73*

0.82*

−0.41

−0.06

−0.01

Tetraconazole

8

0.69

0.83*

−0.32

−0.05

0.07

Chloroneb

7

0.60

0.77*

−0.52

0.21

−0.17

Diazinon

7

0.72

0.88*

−0.70

0.38

0.02

Cadusafos

7

0.57

0.76*

−0.52

0.31

−0.03

Tolclofos-methyl

8

0.68

0.81*

−0.35

−0.07

0.11

Tetradifon

8

0.81*

0.91**

−0.36

−0.06

0.23

* Significant at p<0.05; ** significant at p<0.01.

2. Variability of OC-normalized sorption coefficient (Koc)
Figure 1 shows the variability of the log Koc values of all experiments; numerical values of Koc are shown in Supplemental Table
S8. As mentioned above, the sorption process of test pesticides
in soils was clearly dominated by OC. However, the Koc values ofa given pesticide exhibited high variability among soils. The CVsof Koc values of a pesticide ranged from 36.6% for tetradifon to173% for metalaxyl. Gerstl et al.9,43) show that the Koc values ofpesticides on soils with low organic matter content (<0.5%) areappreciably high because of the contribution of the mineral fraction to the sorption process. In particular, the Koc value of soil
S1 (OC content=0.06%) for metalaxyl tended to be higher thanthose of other soils. Nevertheless, the reason for the variability
in Koc values remains unknown even though the Koc value of soil
S1 was excluded; this is because the CVs of the Koc values of apesticide ranged from 29.5% for tetradifon to 125% for imidacloprid. Wauchope et al.10) reviewed the variability of Koc values
in the literature and report the typical CV of the Koc values ofa given pesticide ranges from 40 to 60%. In the present study,
even though the Koc value of soil S1 was excluded, the CVs of the
Koc values for 11 pesticides exceeded 60%. The Koc values of soil
S7 for almost all pesticides were higher than those of other test
soils. Hence, it is clear that the contribution of soil S7 to Koc variability is high.
On the other hand, when Koc properties were analyzed withrespect to the type of pesticide, the Koc values of tolclofos-methyl
and tetradifon, which are highly lipophilic (log Kow=4.03–4.56
and 3.95–5.52, respectively), were higher than those of otherpesticides. These results suggest that log Koc values increase with
the increasing log Kow of pesticides.43–45) However, cadusafos

Fig. 1. Variability of the log Koc values of test soils.

(log Kow=3.83–4.28) had low Koc values for lipophilicity. Cadusafos is aliphatic, i.e., it has non-aromatic rings. Similarly, the Koc
values of dimethoate and fosthiazate, which have non-aromaticrings, were relatively low. These results imply that the interactions involving aromatic rings are important in the soil sorptionof pesticides.
3. Molecular nature of soil OC
The 13C NMR spectra and relative proportions of each carbon
type for 7 test soils are shown Figure 2 and Table 4, respectively. O-Alkyl carbons (45–110 ppm), which include various polar
components (e.g., polysaccharides, amino acids, lipids, etc.),
were the most prevalent carbon type in all soil samples except
soils S7 and S8, which is concordant with previous studies.12,13,46)111

110 Y. Motoki et al.

Journal of Pesticide Science

On the other hand, aromatic carbons (110–160 ppm), whichcorrespond to lignin, tannin, and aromatic amino acids, werethe carbon type exhibiting the greatest variability among test
soils, ranging from 12.6 to 41.3%. Two test Andosols (soils S7and S8) particularly exhibited greater proportions of aromatic
carbon than other soils. Mahieu et al.46) collected 13C CPMASNMR data on 311 soils from the literature and reported that themean, maximum, and minimum proportions of aromatic carbon were 20.0±6.0%, 44.5%, and 6.8%, respectively. Therefore,
the proportions of aromatic carbon in soils S7 and S8 (41.3%
and 33.9%, respectively) are considerably higher than those ofsoils in the literature.
Aromatic carbon content is generally considered to increase
as a result of the decomposition of OC. Inber et al.47) investigated changes in the OC structure of cattle manure during thecomposting process and found that the proportions of aromatic, alkyl, and carboxyl carbon increase, whereas that of Oalkyl carbon decreases. Similarly, the proportions of carboxyl
carbon in soils S7 and S8, which contained abundant aromatic
carbon, were higher than those in other soils, whereas the proportion of O-alkyl carbon was lower. However, the proportionsof alkyl carbon in soils S7 and S8 were lower than those in othersoils. These results imply that the degree of decomposition of
OC alone is insufficient to explain the difference in OC quality
among test soils.
Golchin et al.19) investigated the effects of artificial burningon the chemical nature of OC in soils; they found that a grassland site with a long history of annual burning had lower alkyl
and O-alkyl carbon contents but higher aromatic and carboxyl
carbon contents than forest sites that had no burning for many
decades. In addition, Sultana et al.48) report that the 13C NMR
spectra of charred plant materials isolated from Japanese Andosols using a specific gravity method exhibited a dominantpeak of aromatic carbon with the proportion of aromatic carbon ranging from 61 to 74%. There is no record that the present
test soils have been burned in the last several decades. However,grasslands containing Japanese Andosol, in which the dominant
vegetation is Japanese pampas grass, which was necessary fortraditional daily life, are thought to have been maintained byburning activity.19,21,49,50) These studies suggest that BC arisingfrom the burning of vegetation may be partly responsible forthe high proportion of aromatic carbon in soils S7 and S8 in thepresent study.

Fig. 2. Solid-state 13C NMR spectra of the soils.

Table 4. Proportions of each carbon region in NMR spectra (%)
Soil

Alkyl
(0–45 ppm)

O-Alkyl(45–110 ppm)

Aromatic(110–160 ppm)

Carboxyl(160–190 ppm)

S2

28.7

46.0

15.2

10.1

S3

26.0

48.0

17.3

8.7

S4

27.4

49.8

12.6

10.2

S5

24.8

44.7

18.6

11.8

S6

23.8

47.4

18.2

10.5

S7

16.9

27.3

41.3

14.5

S8

19.7

33.7

33.9

12.7

4. Effect of organic carbon quality on Koc variability of pesticides
The correlation coefficients between the log Koc values of pesticides and the proportions of each carbon type are shown in
Table 5. The log Koc values for almost all pesticides were positively correlated with aromatic and carboxyl carbon contents andnegatively correlated with O-alkyl and alkyl carbon contents.
The absolute values of r increased with increasing CVs (%) of
Koc values for a given pesticide. The correlation coefficients between the r values and CVs (%) for alkyl, O-alkyl, aromatic, andcarboxyl carbon were −0.88 (p<0.001), −0.90 (p<0.001), 0.89

112

Vol. 39, No. 2, 105–114 (2014)

Effects of organic carbon quality on soil sorption of pesticides 111

Table 5. Coefficients of variation (CV) of Koc values and correlation coefficients (r) between the log Koc values of pesticides andproportions of each carbon type
Compoundr

No. soils

CV (%) of
Koc values

Alkyl

O-AlkylAromatic

Carboxyl

Imidacloprid

7

124.9

−0.91**−0.95**

0.93**

0.97**

Dimethoate

4

82.4

−0.57

−0.63

0.60

0.73

Clothianidin

7

113.8

−0.99**−0.94**

0.97**

0.91**

Thiacloprid

7

115.4

−0.92**−0.95**

0.94**

0.97**

Metalaxyl

6

70.2

−0.28

−0.32

0.28

0.54

Fosthiazate

6

46.9

−0.05

−0.12

0.07

0.27

Methidathion

7

93.8

−0.97**−0.97**

0.98**

0.91**

Fenobucarb

5

92.2

−0.80

−0.73

0.76

0.67

Flutolanil

7

65.9

−0.30

−0.41

0.39

0.29

Procymidone

7

84.9

−0.58

−0.55

0.57

0.52

Fenitrothion

7

76.3

−0.66

−0.80*

0.75

0.78*

Tetraconazole

7

50.2

−0.42

−0.25

0.30

0.30

Chloroneb

7

117.0

−0.86*−0.91**

0.89**

Diazinon

7

48.7

0.51

0.31

−0.40

−0.23

Cadusafos

7

59.9

−0.38

−0.41

0.40

0.40

Tolclofos-methyl

7

45.8

−0.19

−0.30

0.26

0.28

Tetradifon

7

29.5

0.40

0.34

−0.36

−0.37

0.92*** Significant at p<0.05; ** significant at p<0.01.

a torsional structure between the 2 ring planes exhibit lower
sorption than planar aromatics such as non-ortho PCBs.51,52)
This is because planar aromatics can strongly adsorb to planargraphene surfaces of BC via π–π interactions. Focusing on themolecular structures of the test compounds (Fig. 3), the Kd values of chloroneb (a planar aromatic) on soil S7 were higher thanthose of cadusafos (aliphatic) and procymidone (non-planar aromatic with a torsional structure); this is in spite of the fact that
the Kow value of chloroneb (log Kow=1.90–3.58) is of the sameorder of magnitude as that of procymidone (log Kow=2.67–3.30)
and lower than that of cadusafos (log Kow=3.83–4.28) (Fig. 4).
Figure 4 also shows the KAC and the KGP of chloroneb, cadusafos, and procymidone, verifying the effects of the chemical
structures of the pesticides on BC sorption. Similar to the results for soil S7, the sorption of chloroneb to AC and GP was
significantly greater than that of the other 2 compounds. Although AC and GP differ with respect to surface area, porosity,and the presence of an acid functional group, they have common structure—a graphene layer—from a molecular perspective.36) Sultana et al.48) also report that charred plant materials
isolated from Japanese Andosols by a specific gravity method
have 14- to 52-ring condensed aromatic structures. This implies
that the graphene layer of carbonaceous materials is involved in
the different sorption properties of the 3 compounds. Although
the KAC and KGP values were measured using acetone as a liquid
phase, the results of the sorption test of PCBs using activatedcarbon and acetone52) exhibited a similar trend to those usingsoot and water.51) In other words, the sorption strength of pla-

(p<0.001), and 0.90 (p<0.001), respectively.
Similar to the present results, several reports demonstrate
negative correlations between O-alkyl carbon content, which
includes many polar components, and the Koc values of somepesticides such as atrazine,11) carbaryl,12) diuron,11,13) and phosalone.12) In addition, Mitchell et al.11) show that the Koc valuesof atrazine and diuron in soils from which the O-alkyl carbon
components were removed by acid-hydrolysis are higher thanthose in untreated soils. They suggest that the hydrolyzable Oalkyl carbon component in soil might block affinity sorption
sites such as aromatic and/or alkyl domains.
In contrast to O-alkyl carbon, these previous studies also
show that aromatic carbon content is positively correlated with
the Koc values of these pesticides, which is concordant with thepresent results. As discussed above, the aromatic carbon contents of test soils exhibited the greatest variability among carbon
types, and the high aromatic carbon contents in soils S7 and S8
were involved in the presence of BC. Because the Koc values ofalmost all pesticides on soil S7, which had the greatest aromatic
carbon content, were substantially higher than those on othersoils, it is possible the BC contained in soil S7 greatly affects thesorption behavior of pesticides. The sorption of organic chemicals on BC is influenced by hydrophobicity, the presence of aromatic rings, and the planarity of the molecular structure.51–53) Inother words, given the same log Kow value, the sorption of planar
aromatics on BC is higher than that of aliphatics.52) In addition,even if a compound has aromatic rings, non-planar aromatics
such as ortho-substituted polychlorinated biphenyls (PCBs) with113

112 Y. Motoki et al.

Journal of Pesticide ScienceFig. 3. Molecular structures of pesticides optimized according to thePM7 semi-empirical Hamiltonian method. ○: hydrogen atom, ●: oxygen
Cl : chlorine atom, Ⓝ: nitroatom, ●: carbon atom, Ⓟ: phosphorus atom, ○gen atom, Ⓢ: sulfur atom.

nar PCBs is higher than that of non-planar PCBs. On the other
hand, although the overall structures of some pesticides suchas imidacloprid and thiacloprid are non-planar, these pesticides
exhibited relatively high Koc values (Fig. 1). This is probably because these pesticides can take on a planar conformation on thesurface of one part of their molecular structures (as shown in
Fig. 3) that can sorb to the planar graphene layer of BC via π–πinteraction with parallel-displaced orientation.54–56) These results
support the hypothesis that BC in soil strongly contributes tothe Koc variability of pesticides on soil S7 if the conformation of
the pesticide can be planar.

Fig. 4. (A) Soil–water distribution coefficients (Kd) for soil S7, (B) activated carbon (AC)-acetone distribution coefficients (KAC), (C) graphite(GP)-acetone distribution coefficients (KGP). Columns with the same letterare not significantly different at p<0.05 by ANOVA with Tukey’s multiple
range test for (A) and (B) and unpaired 2-sided t-tests for (C). Error bars
indicate standard deviations (n=3). ND: not detectable.

5. Conclusion
The present study suggests that the Koc values of Japanese soils
are highly variable, because aromatic carbon content differed
greatly among soils, especially Andosols. The log Koc values ofsome pesticides were positively correlated with aromatic carbon
content measured by solid-state 13C NMR. However, because 13C
NMR is a qualitative technique, the prediction of log Koc on thebasis of aromatic carbon contents is inadequate. On the other114

Vol. 39, No. 2, 105–114 (2014)

Effects of organic carbon quality on soil sorption of pesticides 11319) A. Golchin, P. Clarke, J. A. Baldock, T. Higashi, J. O. Skjemstad andJ. M. Oades: Geoderma 76, 155–174 (1997).
20) J. A. González-Pérez, F. J. González-Vila, G. Almendros and H.
Knicker: Environ. Int. 30, 855–870 (2004).
21) H. Shindo, T. Honna, S. Yamamoto and H. Honma: Org. Geochem.
35, 235–241 (2004).
22) M. J. Simpson and P. G. Hatcher: Org. Geochem. 35, 923–935 (2004).
23) Y. Yang and G. Sheng: Environ. Sci. Technol. 37, 3635–3639 (2003).
24) V. A. Loganathan, Y. Feng, G. D. Sheng and T. P. Clement: Soil Sci.
Soc. Am. J. 73, 967–974 (2008).
25) K. Hammes, M. W. I. Schmidt, R. J. Smernik, L. A. Currie, W. P. Ball,
T. H. Nguyen, P. Louchouarn, S. Houel, Ö. Gustafsson, M. Elmquist,
et al.: Global Biogeochem. Cycles 21(GB3016), 1–18 (2007).
26) http://sitem.herts.ac.uk/aeru/iupac/ (Accessed 6 Aug., 2013)27) C. MacBean: “The Pesticide Manual,” 16th Ed., British Crop Protection Council, Surrey, 2012.
28) The 2011 Pesticide Handbook Editorial Committee: “The 2011 Pesticide Handbook,” Japan Plant Protection Association, Tokyo, 2011 (inJapanese).
29) J. Muramoto, I. Goto and M. Ninaki: Jpn. J. Soil Sci. Plant Nutr. 63,
210–215 (1992) (in Japanese with English summary).
30) Methods of Soil Analysis (Dojou Kankyou Bunsekihou) Editorial
Committee: “Methods of Soil Analysis (Dojou Kankyou Bunsekihou),” Hakuyuusha, Tokyo, pp. 24–29, 1997 (in Japanese).
31) A Glossary of Pesticide Editorial Committee: “A Glossary of Pesticide,” Japan Plant Protection Association, Tokyo, pp. 128–129, 2009
(in Japanese).
32) Cultivated Soil Classification Committee: Misc. Publ. Natl. Inst.
Agro-Environ. Sci. 17, 31–55 (1995) (in Japanese).
33) OECD: “Guidelines for Testing of Chemicals,” Section 1 (106),
OECD, Paris, 2000.
34) Japanese Standards Association: JIS K 0312, Tokyo, Japan (2005) (inJapanese).
35) Ö. Gustafsson, F. Haghseta, C. Chan, J. MacFarlane and P. M.
Gschwend: Environ. Sci. Technol. 31, 203–209 (1997).
36) Y. Sanada, M. Suzuki and K. Fujimoto: “Activated Carbon. New Edition,” Kodansha Scientific, Tokyo, 1992 (in Japanese).
37) C. Rumpel, N. Rabia, S. Derenne, K. Quenea, K. Eusterhues, I. KögelKnabner and A. Mariotti: Org. Geochem. 37, 1437–1451 (2006).
38) S. Hiradate, T. Yonezawa and H. Takesako: Geoderma 132, 196–205(2006).
39) K. Ono, K. Hirai, S. Morita, K. Ohse and S. Hiradate: Geoderma 151,
351–356 (2009).
40) http://openmopac.net/ (Accessed 6 Aug., 2013)41) J. K. Syers, A. S. Campbell and T. W. Walker: Plant Soil 33, 104–112(1970).
42) R. L. Parfitt, D. J. Giltrap and J. S. Whitton: Commun. Soil Sci. Plant
Anal. 26, 1343–1355 (1995).
43) Z. Gerstl and U. Mingelgrin: J. Environ. Sci. Health B 19, 297–312(1984).
44) A. Sabljić, H. Güsten, H. Verhaar and J. Hermens: Chemosphere 31,4489–4514 (1995).
45) L. Nemeth-Konda, G. Füleky, G. Morovjan and P. Csokan: Chemosphere 48, 545–552 (2002).
46) N. Mahieu, E. W. Randall and D. S. Powlson: Soil Sci. Soc. Am. J. 63,
307–319 (1999).
47) Y. Inbar, Y. Chen and Y. Hadar: Soil Sci. Soc. Am. J. 53, 1695–1701(1989).
48) N. Sultana, K. Ikeya, H. Shindo, S. Nishimura and A. Watanabe: Soil
Sci. Plant Nutr. 56, 793–799 (2010).

hand, because the sorption properties of pesticides in Andosols
with the greatest aromatic carbon contents exhibited trends similar to those in AC and GP, it is possible that BC in soil affects
the sorption properties of pesticides. Several studies report thatquantifying soot content in sediments and determining soot–water distribution coefficients accurately predicts the sorption ofpolycyclic aromatic hydrocarbons (PAHs) on sediments.35,57–59)
These results imply that the sorption of pesticides on soils canalso be predicted if it is possible to quantify BC in soils and assess the sorption of isolated BC. Unfortunately, no methods forquantifying BC in soils have been established.25) Therefore, further studies are required to isolate and precisely quantify BC in
soil contributing to the sorption behavior of pesticides.

Acknowledgements
The authors thank Dr. S. Hiradate of the National Institutefor Agro-Environmental Sciences for technical support in NMR
analysis. The test soils were kindly supplied by Aichi Agricultural Research Center, Fukushima Agricultural Technology Centre,
Tochigi Prefectural Agricultural Experiment Station, and NARO
Agricultural Research Center. This study was financially supported by a Grant-in-Aid from the Ministry of the Environment(MOE), Japan. The opinions expressed in this paper are solely
those of the authors and do not necessarily reflect the views of
MOE.
References
1) J. J. Boesten: Pest Manag. Sci. 60, 971–980 (2004).
2) R. P. Scorza Júnior and J. J. Boesten: Pest Manag. Sci. 61, 432–448(2005).
3) K. Inao and Y. Kitamura: Pestic. Sci. 55, 38–46 (1999).
4) H. Watanabe and K. Takagi: Environ. Technol. 21, 1379–1391 (2000).
5) J. W. Kelsey, B. D. Kottler and M. Alexander: Environ. Sci. Technol.
31, 214–217 (1997).
6) H. J. Pedersen, P. Kudsk and A. Helweg: Pestic. Sci. 44, 131–136(1995).
7) C. T. Chiou, G. Sheng and M. Manes: Environ. Sci. Technol. 35, 1437–
1444 (2001).
8) Ministry of Agriculture: Fishery and Forestry and Japanese Societyof Soil Science and Plant Nutrient: “Current Status and Countermeasures of Arable Soils,” Hakuyuusha, Tokyo, 1991 (in Japanese).
9) Z. Gerstl: J. Contam. Hydrol. 6, 357–375 (1990).
10) R. D. Wauchope, S. Yeh, J. B. Linders, R. Kloskowski, K. Tanaka, B.
Rubin, A. Katayama, W. Kördel, Z. Gerstl, M. Lane and J. B. Unsworth: Pest Manag. Sci. 58, 419–445 (2002).
11) P. J. Mitchell and M. J. Simpson: Environ. Sci. Technol. 47, 412–419(2013).
12) R. Ahmad, R. S. Kookana, A. M. Alston and J. O. Skjemstad: Environ.
Sci. Technol. 35, 878–884 (2001).
13) A. G. Ahangara, R. J. Smernika, R. S. Kookanaa and D. J. Chittleborougha: Chemosphere 70, 1153–1160 (2008).
14) I. Kögel-Knabner: Soil Biol. Biochem. 34, 139–162 (2002).
15) P. N. Nelson and J. A. Baldock: Biochemistry 72, 1–34 (2005).
16) M. J. Simpson and A. J. Simpson: J. Chem. Ecol. 38, 768–784 (2012).
17) C. M. Preston: Soil Sci. 161, 144–166 (1996).
18) H. Obara: Pedologist 44, 134–142 (2000) (in Japanese).

115114 Y. Motoki et al.

Journal of Pesticide Science49) S. Hiradate, T. Nakadai, H. Shindo and T. Yoneyama: Geoderma 119,133–141 (2004).
50) I. Yamane: Pedologist 17, 84–94 (1973) (in Japanese with English
summary).
51) T. D. Bucheli and O. V. Gustafsson: Chemosphere 53, 515–522 (2003).
52) A. Kawashima, M. Katayama and K. Honda: J. Environ. Chem. 19,
519–525 (2009) (in Japanese with English summary).
53) A. Sobek, N. Stamm and T. D. Bucheli: Environ. Sci. Technol. 43,
8147–8152 (2009).
54) G. B. McGaughey, M. Gagné and A. K. Rappé: J. Biol. Chem. 273,

15458–15463 (1998).
55) F. Ortmann, W. G. Schmidt and F. Bechstedt: Phys. Rev. Lett. 95,
186101-1–186101 (2005).
56) S. Grimme: Angew. Chem. Int. Ed. 47, 3430–3434 (2008).
57) T. D. Bucheli and Ö. Gustafsson: Environ. Sci. Technol. 34, 5144–5151(2000).
58) A. Accardi-Dey and P. M. Gschwend: Environ. Sci. Technol. 37, 99–
106 (2003).
59) R. Lohmann, J. K. MacFarlane and P. M. Gschwend: Environ. Sci.
Technol. 39, 141–148 (2005).

116