[他誌掲載論文]
Journal of Agricultural and Food Chemistry, 2016, 64, 4478～4486 より転載

Effect of Time-Dependent Sorption on the Dissipation of
Water-Extractable Pesticides in Soils
Yutaka Motoki1, Takashi Iwafune2, Nobuyasu Seike1, Keiya Inao1,
and Takashi Otani1
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・本論文の著作権は、American Chemical Society に帰属していますが、American Chemical Society の転載要件を満たしていることを確認の上転載しています.

Articlepubs.acs.org/JAFC

Eﬀect of Time-Dependent Sorption on the Dissipation of WaterExtractable Pesticides in Soils
Yutaka Motoki,†,§ Takashi Iwafune,‡ Nobuyasu Seike,*,† Keiya Inao,† and Takashi Otani††

National Institute for Agro-Environmental Sciences, 3-1-3 Kannondai, Tsukuba, Ibaraki 305-8604, Japan
Food and Agricultural Materials Inspection Center, Agricultural Chemicals Inspection Station, 2-772 Suzuki-cho, Kodaira, Tokyo
187-0011, Japan‡S Supporting Information*

ABSTRACT: The dissipation behavior of water-extractable pesticides in soils is important when assessing the phytoavailabilityof pesticides in soils. This process is less understood than pesticide extraction with organic solvents. To elucidate the dissipation
behavior of water-extractable pesticides in soils, we conducted an incubation study using 27 pesticides and ﬁve Japanese soils.
The rate of decrease of the level of pesticides in water extracts was faster in soils than that of total extracts (water extracts andacetone extracts). This suggests that time-dependent sorption contributed to the diﬀerence in the dissipation between thepesticides in water and total extracts from soils. Increased apparent sorption coeﬃcients (Kd,app) with time were positively andsigniﬁcantly correlated with Kd,app values of a 0 day incubation [Kd,app(t0)]. This empirical relationship suggests that Kd,app(t0)values can predict the time-dependent increase in Kd,app and the dissipation of water-extractable pesticides in soils.
KEYWORDS: pesticides, soil, fate, aging, time-dependent sorption, water extraction, phytoavailability■

INTRODUCTION
Recently in Japan, some agricultural chemicals that had been
applied to previously grown crops and then remained in the soil
were detected in succeeding crops. Selling or distributing crops
in Japan that contain pesticides above their maximal residue
limits (MRLs), or a concentration of 0.01 mg/kg if the MRL
has not been established, is prohibited.1 Thus, these farmers
suﬀer economic loss. When newly developed pesticides areregistered in Japan, soil dissipation studies in two ﬁelds having
diﬀerent soil types are required.2 These studies must be
performed to assess the risk of contamination succeeding crops
by pesticide residue in soils; that is, studies of residues insucceeding crops2 are required only if the half-lives of pesticides
in the soil are more than 100 days.
In soil dissipation studies, the extraction of pesticides fromsoils is conducted using organic solvents such as acetone.
However, the extractability of organic solvents is too high toassess the phytoavailability of residual pesticides in soil,3 i.e., theorganic solvent extracts soil-sorbed pesticides, which are nottaken up by the plant. Therefore, to estimate the plant uptakeof residual pesticides in soils, the concentrations ofphytoavailable pesticides in soils should be measured. Our
previous study indicated that the concentrations of pesticides
such as clothianidin, thiacloprid, procymidone, and tetraconazole in leafy vegetables cultivated in four diﬀerent soils
containing the pesticide residues were positively and signiﬁcantly correlated with the concentrations of water-extractablepesticides rather than total extractable pesticides (water extracts
and acetone extracts) in these soils.4 This result implies that theresidual levels of pesticides in crops are estimated using theconcentrations of water extracts from soils. In addition, thestudy showed that the coeﬃcients of determination (R2)
calculated using the concentrations of water extracts from soils
at harvest were higher than those at sowing. Therefore,© 2016 American Chemical Society

assessing the dissipation of water-extractable pesticides in soils
and predicting the concentration of the aqueous soil extracts at
harvesting time are important for estimating the residue levels
in crops before harvest, preferably before sowing, and forpreventing the production and distribution of pesticidecontaminated crops. On the other hand, the water-extractableconcentrations of pesticides can be calculated using thepesticide concentrations extracted with an organic solvent andthe soil sorption coeﬃcient (Kd), which describes the
distribution of pesticides between soil and water. Hence,
understanding the variability in Kd values is also important for
estimating the uptake concentrations of pesticides from soils bycrops.
Kd values measured by the batch equilibrium method5 arerequired for four diﬀerent soils under the Japanese registration
system.2 The registration data for the soil dissipation study andthe soil sorption study may be available for estimating theresidual concentrations of water-extractable pesticides in soils
and the uptake concentrations in crops. However, it wasreported that the Kd values of various pesticides, including
insecticides,6−9 fungicides,10,11 and herbicides,9,11−15 increased
with aging time. Hence, if the eﬀect of aging on the Kd values is
not considered, the concentrations of water-extractablepesticides predicted using the Kd values seem to be higher
than the actual values. Many previous studies6−8,10,12−15
describing and assessing time-dependent sorption have been
conducted on either individual pesticides or several pesticides,
and thus, the time-dependent changes in Kd values have not
Received: March 2, 2016
Revised: May 16, 2016
Accepted: May 19, 2016
Published: May 27, 2016
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Journal of Agricultural and Food Chemistry
Table 1. Properties of Test Soils
soilexperimentclassiﬁcationa

textureb

OCc (%)

CECd (cmol(+) kg−1)

clay (%)

pH (H2O)

ECe (mS cm−1)flaboratory

Typic Udipsamments
Typic Hapludults
Typic Endoaquents
Typic Hapludands
Pachic Melanudands
Typic Hapludands

sandlight clay
silty clay
loam
silty loam
silty loam

0.06
1.02
1.46
5.21
8.65
4.93

3.4
11.4
18.2
33.8
35.4
26.0

2.4
39.0
25.3
10.8
1.8
7.3

7.5
5.3
5.8
5.5
5.8
6.3

0.04
0.09
0.17
0.15
0.05
0.31

LS1
LS2f
LS3f
LS4f
LS5f
FS

ﬁeld

a

According to U.S. Department of Agriculture Soil Taxonomy.17 bAccording to the International Society of Soil Science.19 cOrganic carbon content.
dCation exchange capacity. eElectrical conductivity. fData were obtained from our previous report.20 Soils LS1−LS5 correspond to soils S1, S3, S5,
S7, and S8, respectively, in the previous report.

Table 2. Hydrophobicities and Analytical Groups of Test Compounds
analytical groupd
compound

CAS Registry No.

pesticide type

dinotefuran
imidacloprid
dimethoate
clothianidin
thiacloprid
fosthiazate
metalaxyl
ethiprole
azoxystrobinmethidathion
fenobucarb
boscalid
ﬂutolanilprocymidone
fenitrothion
kresoxim-methyl
tetraconazole
chloroneb
diazinonpropiconazole
ﬁpronilcadusafos
diclocymet
triﬂoxystrobin
tolclofos-methyl
tetradifon
fenthion

165252-70-0
138261-41-3
60-51-5210880-92-5
111988-49-9
98886-44-3
57837-19-1
181587-01-9
131860-33-8
950-37-8
3766-81-2
188425-85-6
66332-96-5
32809-16-8
122-14-5
143390-89-0112281-77-3
2675-77-6
333-41-560207-90-1
120068-37-3
95465-99-9
139920-32-4
141517-21-7
57018-04-9
116-29-0
55-38-9

I
I
I
I
I
I
F
I
F
I
I
F
F
F
I
F
F
F
I
F
I
I
F
F
F
I
I

a

substance grouplog Powblog Swc

laboratory test

ﬁeld test

neonicotinoid
neonicotinoidorganophosphateneonicotinoid
neonicotinoidorganophosphate
phenylamide
phenylpyrazole
methoxyacrylateorganophosphatecarbamatepyridinecarboxamide
phenylbenzamide
dicarboximideorganophosphate
oximinoacetate
triazole
chlorophenylorganophosphate
triazole
phenylpyrazoleorganophosphatecarboxamide
oximinoacetateorganophosphatebridged diphenylorganophosphate−0.549
0.570
0.704
0.905
1.26
1.68
1.75
1.99
2.50
2.57
2.78
2.96
3.17
3.30
3.32
3.40
3.56
3.58
3.69
3.72
3.75
3.85
3.97
4.50
4.56
4.61
4.84

4.60
2.79
4.60
2.53
2.26
3.95
3.92
0.964
0.826
2.38
2.62
0.663
0.904
0.391
1.28
0.301
2.19
0.903
1.78
2.18
0.577
2.39
0.805
−0.215−0.150
−1.11
0.623

A
A
A
A
A
A
A
A
C
A
B
B
B
B
C
B
C
B
C
C
C
B
C
B
C
C
B

A
A
A
A
A
A

C
C
C

C

a

Abbreviations: I, insecticides; F, fungicides. bOctanol−water partition coeﬃcient obtained from the Pesticide Properties Database of IUPAC,21
except for the Pow of diclocymet, which was obtained from ref 22. cWater solubility (milligrams per liter) obtained from the Pesticide Properties
Database of IUPAC,21 except for the Sw of ethiprole, which was obtained from ref 22. dThe details of analytical methods are described in ourprevious report.20

been extensively evaluated using various pesticides with
diﬀerent physicochemical properties for a given soil.
Because the soil organic matter is a main sorbent of anonionic pesticide,16 it is likely to play an important role in thetime-dependent increase in the Kd values for nonionicpesticides. However, there is no report on the time-dependentchanges in Kd values in soils having a wide range of organiccarbon (OC) contents. On the other hand, Japan is a typicalvolcanic country; volcanic ash soil (andisol), which is one of the
major upland soils and is also widely distributed in othercircum-Paciﬁc regions such as the western coast of theAmerican continents, the Philippine Islands, and New
Zealand,17 contains high OC content. Therefore, Japanesesoils have a wide range of OC contents18 and are useful for

elucidating the relationships between the time-dependentchanges in Kd values and the OC content.
The aims of this study are to elucidate the dissipation
behavior of the concentrations of pesticides in water extracts
and total extracts (water extracts and acetone extracts) fromsoils and the time-dependent changes in the Kd values inlaboratory experiments using ﬁve Japanese soils with diﬀerent
OC contents and 27 pesticides with diﬀerent physicochemical
properties. Furthermore, we attempted to develop an
estimation method that can predict the dissipation of thewater-extractable pesticides using the initial Kd values (i.e., the 0
day values after application of pesticides), based on the resultsof the laboratory studies, and verify this estimation method in
the ﬁeld.
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Journal of Agricultural and Food Chemistry■water (milliliters), and Msoil is the soil’s dry mass (grams). The massfraction of total extractable pesticides in the soil, CT (micrograms pergram of DW), was represented as

MATERIALS AND METHODS

Soils and Pesticides. Five typical Japanese agricultural soils with awide range of OC contents were used in the laboratory studies. Soilsamples were air-dried and passed through a 2.0 mm sieve. The soil
properties are listed in Table 1. The methods for measuring thereported properties have been described previously.20 The 27
pesticides (chemical purity of >97.0%) were purchased from Wako
Pure Chemical Industries, Ltd. (Osaka, Japan), Kanto Chemicals(Tokyo, Japan), and Dr. Ehrenstorfer GmbH (Augsburg, Germany)(Table 2). Pesticides belonging to various chemical groups werechosen on the basis of hydrophobicity, i.e., the range of their octanol−
water partition coeﬃcients (log Pow) and water solubility (log Sw). To
permit simultaneous analysis, the pesticides were divided into three
analytical groups on the basis of the analytical methods described in
Pesticide Analysis. Stock solutions (100 μg/mL each) of the pesticides
were prepared in acetone for each group.
Laboratory Incubation. Air-dried soil equivalent to 8 g of dry
weight (DW) was placed in a 50 mL glass centrifuge tube. The watercontent of the soils was adjusted to approximately 60% of water
holding capacity (WHC). Duplicate samples were incubated at 25 ± 2°C in the dark. After a preincubation period of 10 days, 80 μL of an
acetone stock solution of each pesticide group was added dropwise toa soil sample in a test tube so that the sample concentration was 1 μg/
g of DW of the initial pesticide concentration. The soil samples were
thoroughly mixed using a microspatula, and the openings of the tubes
were covered with aluminum foil. The soil samples were incubated in
the dark at 25 ± 2 °C for 0, 2, 7, 14, 30, 60, and 120 days. The
moisture content was maintained at 50−60% of WHC by adding
distilled water once every 10 days. After each incubation period, thesoil samples were analyzed using a sequential extraction method using
distilled water and acetone.4
Sequential Extraction of Soils. Forty milliliters of distilled water
was added to the test tubes so that the soil/solution ratio wasapproximately 1/5. The tubes were agitated on a thermostat shaker(TAITEC, Saitama, Japan) for 24 h at 25 ± 2 °C in the dark. Afterbeing shaken, the mixtures were centrifuged at 1200g for 30 min.
Fifteen milliliters of supernatant was withdrawn and used to quantify
the water-extractable pesticides, and then 20 mL of supernatant was
discarded. Subsequently, 30 mL of acetone was added to the remaining
sample; the tubes were shaken in a thermostat shaker for 20 min at 25± 2 °C and centrifuged at 1200g for 10 min, and then the supernatant
was carefully decanted. This extraction procedure was repeated twice.
The collected supernatant was evaporated in a rotary evaporator to
reduce the volume to <15 mL, which was then used to quantify theacetone-extractable pesticides.
Pesticide Analysis. The aliquots (15 mL) of water extracts andconcentrates (<15 mL) of acetone extracts from soils were analyzed
using three diﬀerent methods for each analytical group, as described in
our previous report.20 In brief, the aliquots and concentrates werecleaned with a diatomite column (InertSep K-solute 20 mL; GL
Sciences, Tokyo, Japan) followed by these solid phase extraction(SPE) cartridges: a PSA column (500 mg; Supelco, Bellefonte, PA), an
Accell CM column (500 mg; Waters, Milford, MA), and an ENVICarb II/PSA column (500 mg/500 mg; Supelco) for groups A−C,
respectively (Table 2). The cleaned samples were analyzed by liquid
chromatography and tandem mass spectrometry (LC−MS/MS) forgroup A and gas chromatography and mass spectrometry (GC−MS)
for groups B and C. The LC−MS/MS and GC−MS operating
conditions are given in Supporting Information section SI-1. In thecase of the high matrix eﬀects of cleaned samples, the quantiﬁcation ofpesticides using GC−MS was performed using matrix-matchedstandards.23
The mass fraction of water-extractable pesticides in the soil, CW(micrograms per gram of DW), was calculated from
C W = Caq(Vadd + Vsw)/Msoil

C T = [Caq(Valiq + Vdisc) + mE]/Msoil(2)

where Valiq is the volume of the aliquot taken from the supernatant(milliliters), Vdisc is the volume of the discarded supernatant(milliliters), and mE is the mass of the pesticides extracted by acetone
from the remaining sample after Valiq and Vdisc were removed(micrograms).
Two kinetic models were used to describe the dissipation in CW andCT with time: a single-ﬁrst-order (SFO; eq 3) model and a doubleﬁrst-order in parallel (DFOP; eq 4) model.24 The DFOP model
describes the dissipation as a sum of two ﬁrst-order dissipation steps
each in diﬀerent parts of the soil compartment. The dissipation
parameters were obtained by using the least-squares method with
Microsoft Excel Add-Inn Solver.

C(t ) = C0e−kt(3)

C(t ) = C0[f e−k1t + (1 − f )e−k 2t ](4)

where C(t) is the CW or CT value after t days, C0 is the CW or CT value
at time zero, k is the rate constant (inverse days), f is the fraction of C0
applied to the ﬁrst compartment, and k1 and k2 are the rate constantsin the ﬁrst and second compartments, respectively.
For the SFO model, DT50 (days), which is the time taken for a 50%
decrease in CW or CT, was calculated using

DT50 = ln 2/k(5)

For the DFOP model, the DT50 values were calculated by using thegoal-seek function in Microsoft Excel.24
The apparent sorption coeﬃcients (Kd,app, milliliters per gram) after
diﬀerent incubation periods, taking the dissipation of CT and CW withtime into consideration, were determined using
Kd,app = Csorb/Caq = (C T − C W )/Caq(6)

where Csorb is the mass fraction of soil-sorbed pesticides (micrograms
per gram of DW).
Pesticide recovery tests were conducted with distilled water and alltest soils.20 Samples of distilled water (15 mL) spiked with a pesticideconcentration of 1 ng/mL for all group pesticides were analyzed using
the methods mentioned above. Each soil (5 g) spiked with 5 and 3 ng/
g for group A and groups B and C, respectively, was mixed with 10 mLof distilled water and subsequently extracted three times with 30 mL ofacetone for 20 min at 25 ± 2 °C. The acetone extracts were analyzed
in a similar way. The mean recovery from the four replicates for group
A and ﬁve replicates for groups B and C ranged from 73.2 to 117.0%
for all compounds; the coeﬃcients of variation (CVs) were ≤19.0%.
The limits of quantiﬁcation (LOQs) were calculated in accordancewith Japanese Industrial Standard (JIS) K 0312.25 The LOQs for allcompounds in distilled water and all test soils were in the ranges of0.14−1.29 ng/mL and 0.23−5.93 ng/g, respectively.
Field Studies. Field studies were conducted in our experimentalﬁeld located in Tsukuba City, Japan, and started on May 12, 2015. The
daily mean temperature of Tsukuba City during the experiment ranged
from 16 to 30 °C (mean of 23 °C). The characteristics of the ﬁeld soil
(FS) are listed in Table 1. Ten pesticides, dinotefuran, imidacloprid,
clothianidin, thiacloprid, fosthiazate, metalaxyl, fenobucarb, ﬂutolanil,procymidone, and tolclofos-methyl, were used in the ﬁeld study (Table2). One liter of a mixed solution of the 10 pesticides (200 mg/L each),prepared by water dilution of commercial formulations (i.e.,emulsiﬁable concentrates, water-soluble powders, and water-dispersible powders), was evenly applied to triplicate plots (1 m × 1 m)using a watering can. Subsequently, the soil surface (approximately 0−
20 cm depth) was tilled with a walking-type tilling apparatus. The
initial concentration of pesticides in the 0−20 cm soil depth after
tilling was calculated using the actual bulk density (0.45 g/cm3) andwas 2.2 μg/g of DW for each pesticide. Four cores were taken fromeach plot 0 (immediately after tilling), 2, 7, 14, 21, 28, 35, 42, 49, 56,(1)where Caq (micrograms per milliliter) is the mass concentration ofpesticide in the aqueous phase after shaking for 24 h, Vadd is thevolume of distilled water added (milliliters), Vsw is the volume of soil
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Journal of Agricultural and Food Chemistry63, 70, 77, and 84 days after application of the pesticides using
cylindrical cans (8 cm inner diameter, 10 cm depth). The cores werecombined for each plot and were mixed well. An approximately 15 g
sample of the soil was dried at 105 °C to measure the moisture
content, and an aliquot equivalent to 5 g of DW was analyzed using asequential extraction method in the same way that was used in thelaboratory experiment; i.e., the samples were ﬁrst extracted three times
with 25 mL of distilled water for 24 h at 25 ± 2 °C and subsequently
with 30 mL of acetone for 20 min at 25 ± 2 °C.

■

RESULTS AND DISCUSSION
Dissipation Behavior of Water-Extractable and Total
Extractable Pesticides in Laboratory Studies. The

Figure 2. Time-dependent changes in the apparent sorption
coeﬃcient (Kd,app) of tetraconazole.

Figure 3. Fitted parameter b for eq 7 plotted as a function of apparent
sorption coeﬃcient for the 0 day incubation [Kd,app(t0)].

Figure 1. Comparison of DT50 values between water extracts (CW)
and total extracts (CT) from soil: (○) neonicotinoids, (□)
organophosphates, (▲) fungicides, and (×) others. The dashed line
shows the 1/1 line.

applicability of a sequential extraction method was veriﬁed on
the basis of the mass balance (MB, %), which was calculated by
dividing the CT value by the initial concentration of pesticides
in soil, of the sample after incubation for 0 days (Supporting
Information section SI-2). The MB diﬀered depending on thetype of pesticide and type of soil. From the results of recovery
tests, i.e., the mean recovery of pesticide in water and soil
samples was ≥73.2% (see Materials and Methods, Pesticide
Analysis), when the MB was <70%, the method was judged to
be inapplicable because of biodegradation or hydrolysis during
the 24 h water extraction. The MB of several pesticides,
especially in LS5, was <70%, and these samples were excluded
from the succeeding data analysis.

Figure 4. Comparison between measured and calculated b values foreq 7. The solid line shows the 1/1 line, and the dashed lines show the
1/5 and 5/1 lines.

Figure 1 shows a comparison of the DT50 values of CW and
CT. The DT50 values were calculated using two kinetic models,
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Figure 5. Comparisons between calculated and measured concentrations of water extracts from soil: (●) measured values, () values predictedusing apparent sorption coeﬃcients calculated by eq 9, and (---) values predicted using the apparent sorption coeﬃcient of the 0 day incubation[Kd,app(t0) (milliliters per gram)]. DT50 (days) indicates the values of total extracts from soil calculated by eq 5. Error bars indicate the standard error.
The measured values of fenobucarb were less than the LOQ on day 28 and after 28 days.

SFO and DFOP. The goodness of ﬁt to the individual models
was veriﬁed using the model error calculated by the χ2 value,24
and the DT50 values calculated by the model that had thesmaller error level were adopted in Figure 1. The DT50 valuesof CT were greater than those of CW for all test soils except soil
LS1. The details of the DT50 values and error levels for eachmodel are summarized in Supporting Information section SI-2.
The error levels of the two models of CT were approximately
equal to each other. In contrast, the error levels of the DFOP
model of CW were smaller than those of the SFO model,
especially for soil LS4. Furthermore, previous research26 on thedissipation of pharmaceuticals, which are organic chemicals aswell as pesticides, in soil pore-water was better ﬁtted to thebiphasic DFOP and ﬁrst-order multicompartment (FOMC)
models rather than the SFO model. Although our chemicals are
not classiﬁed as pharmaceuticals, these results suggest that thedissipation of water-elutable or water-extractable organic
chemicals in soils is better described by biphasic models.
For the DT50 of CT, many fungicides showed relatively highvalues among the tested compounds, and in particular, thevalues of metalaxyl, boscalid, procymidone, tetraconazole, anddiclocymet were >120 days for all soil samples (Supporting
Information section SI-2). Japanese registration data also show
long DT50 values (>100 days) for boscalid and diclocymet
under laboratory conditions.27 On the other hand, the DT50
values of organophosphorus compounds such as dimethoate,
fosthiazate, methidathion, fenitrothion, diazinon, tolclofosmethyl, and fenthion were relatively low. It was reported thatthe organophosphorus pesticides such as diazinon, dimethoate,
and fenitrothion could be easily degraded by microorganisms;
in other words, the DT50 values of these pesticides were ≤41days.28 Focusing on the diﬀerences among test soils, we found
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The dissipation of CW showed a behavior diﬀerent from thatof CT. The reason for this is that the dissipation of CW, which is
the readily bioavailable fraction, is more aﬀected bybiodegradation than that of CT. Furthermore, the dissipationof CW is also aﬀected by the soil sorption, making theinvestigation of sorption properties, especially time-dependentchanges in Kd, necessary for better understanding thecontribution of soil sorption to the dissipation of CW.
Time-Dependent Sorption in Laboratory Studies. As
mentioned in previous reports,6−15 the Kd,app values of many
pesticides increased with an increase in incubation time. It issuggested that the time-dependent changes in soil sorption are
attributed to the slow diﬀusion of pesticides into organic matterand the nanopore structures in soil particles.3 The pesticides are
considered to move from the surface site of the soil particles tothe interior sites, i.e., less accessible sites, with aging time.
According to previous reports,10,12,14 the changes in Kd,app withtime could be represented as

Table 3. Statistical Analysis of the Measured and Predicted
Concentrations of Water Extracts from Soil
uniform sorptiona

time-dependent
sorptionb

soil

compound

RMSEc

NSEd

RMSEc

NSEd

FS

dinotefuran
imidacloprid
clothianidin
thiacloprid
fosthiazate
metalaxyl
fenobucarb
ﬂutolanilprocymidone
tolclofos-methyl

58.8
80.7
71.1
70.4
44.8
60.0
15.7
87.9
82.6
74.7

0.78
0.05
0.20
0.82
0.92
0.82
0.97
−0.21
0.71
0.73

53.1
52.5
51.0
64.4
36.0
51.3
14.5
51.2
62.9
63.9

0.97
0.88
0.90
0.87
0.97
0.95
0.95
0.88
0.87
0.84

a

Prediction using the apparent sorption coeﬃcient for the 0 day
incubation. bPrediction using apparent sorption coeﬃcients calculated
by eq 9. cRoot-mean-square error (%). dNash−Sutcliﬀe modeleﬃciency.

Kd,app = a + bt 0.5(7)where a and b are empirical parameters and t is the time ofincubation. Although this empirical equation has no theoreticalbasis, it is suggested that the amounts of sorbed chemicals,
which are controlled by diﬀusion, are proportional to the squareroot of time.35,36 Figure 2 shows an example of tetraconazole toillustrate the time-dependent changes in sorption. The detailsof the linear regression analysis for all pesticides are
summarized in Supporting Information section SI-3. The soil
samples, except for soil LS1, exhibited signiﬁcant positive
correlation (P < 0.05) between the Kd,app values and the squareroot of time for many pesticides. In the case of soil LS1, which
has the lowest OC content, the time-dependent increase in
Kd,app was not observed for many pesticides and the coeﬃcientof determination values (R2) were extremely low.
Parameters a and b play an important role in the predictionof time-dependent changes in the Kd,app values. When a good ﬁt
to eq 7 was achieved, the a and b values were relatively high,with the condition that the OC content of soils and the log Pow
of pesticides were both high and the log Sw of the pesticides waslow (Supporting Information section SI-3), i.e., the condition of
an increasing level of soil sorption of nonionic pesticides,16 andthe a values, which represent Kd,app at time zero, wereapproximated as the measured Kd,app values of the 0 day
incubation sample [Kd,app(t0)] (Supporting Information sectionSI-3). Moreover, the b values were proportional to the Kd,app(t0)values, as shown in Figure 3. The linear regression equation
describing the relationship between b and Kd,app(t0) is

soil LS5 indicated relatively low DT50 values of CT for various
pesticides as well as organophosphates. The dissipation of apesticide is thought to be aﬀected by photolysis, hydrolysis
depending on soil pH, and biodegradation.29 In this study, theincubation of soil samples was conducted in a dark place, andthe pH of soil LS5 was almost the same as the pH of soils LS3and LS4. Therefore, hydrolysis and photolysis seemed not to bea direct cause of the fast dissipation of pesticides in soil LS5,and thus, biodegradation is thought to be the main contributor
to dissipation.
Unlike the dissipation behavior of CT, the DT50 values of CW
for many pesticides tended to decrease in the following order ofsoils: LS1 ≥ LS2 ≥ LS3 ≥ LS5 ≥ LS4. The DT50 values of CW
in soil LS1 with an extremely low OC content were longer thanthose of the other soils and exhibited a trend similar to those of
CT. On the other hand, the dissipation of CW of two andisols(LS4 and LS5) having high OC content was faster than that ofother soils. The OC content tends to be positively correlatedwith microbial activity in soils, and a positive correlation
between the degradation rate of weakly sorbed compoundswith high bioavailability and OC contents of soils has often
been reported.30,31 Because CW is the readily bioavailable
fraction,9,13 the DT50 of CW seemed to vary depending on
microbial activity, which is inﬂuenced by the OC content of thesoils. However, if we focus on the results of soils LS4 and LS5,
the DT50 values of soil LS4 for many pesticides, especially forhardly degradable fungicides, were lower than those of soil LS5,
which had the highest OC content (Supporting Information
section SI-2). Furthermore, it is known that the dominantsorbent in soils of nonionic pesticides is organic matter
consisting of OC.16 Therefore, there is a possibility that thesorption of pesticides to OC aﬀects the dissipation of CW; i.e.,
the DT50 values decrease with an increase in the Kd values.
According to our previous report,20 the Kd values obtained in
the standard batch sorption tests5 were higher for soil LS4 thanfor soil LS5 because of the diﬀerence in the organic carbon
quality; i.e., soil LS4 had an aromatic carbon content higher
than that of soil LS5 and an O-alkyl carbon content lower thanthat of soil LS5. Several reports show that the OC-normalized
sorption coeﬃcients (Koc) of pesticides were positively
correlated with aromatic carbon content and negatively
correlated with O-alkyl carbon content.20,32−34

log b = − 0.532 + 1.005 × log Kd,app(t 0)(8)with R2 = 0.838, P < 0.001, and n = 116. Thus, eq 8 suggeststhat parameter b can be estimated using the Kd,app(t0) values
that roughly indicate the degree of sorption to the surface sitesof soil particles. Li et al.37 investigated the soil sorption ofatrazine using batch experiments combined with an online
microﬁltration (MF)−high-performance liquid chromatography
technique; they showed that the intraparticle diﬀusion rate wasproportional to labile surface sorption, i.e., labile surface
coverage. In the study presented here, it is hard to clearly
distinguish labile surface sorption from nonlabile sorption
caused by intraparticle diﬀusion because Kd,app(t0) is likely toinclude a small degree of nonlabile sorption occurring rapidly
during the water extraction time of 24 h. However, the positive
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Journal of Agricultural and Food Chemistrycorrelation between the Kd,app(t0) values and the b values of eq7, i.e., the increased rate of Kd,app, implies that a slow diﬀusion
process contributes to the time-dependent increase in Kd,app.
However, Supporting Information section SI-3 also shows thatthe easily degradable pesticides such as methidathion,
fenitrothion, kresoxim-methyl, and fenthion, which have low
DT50 values of CT (Supporting Information section SI-2),
exhibit relatively high b values for Kd,app(t0). Cox et al.6 andKoskinen et al.8 reported that the time-dependent increase in
Kd values for imidacloprid and its metabolites was due todegradation in solution and on labile sites when the
degradation rate was higher than the rate of desorption fromsoil. Thus, the time-dependent increase in Kd,app in this study
was thought to be aﬀected not only by diﬀusion into nonlabilesites but also by fast dissipation in solution and on labile sites.
Although two reasons may contribute to the time-dependent
increase in Kd,app, the empirical relationships between Kd,app(t0)and the parameters of eq 7 (a and b) allow us to rewrite eq 7 byusing Kd,app(t0) as
1.005 0.5

Kd,app = Kd,app(t0) + 0.294Kd,app(t0)tdissipation of CT using the time-dependent Kd,app. The
predicted CW was determined using the following equation:r
C W = CTr + Kd,app(10)
where CT was calculated using the SFO model (eq 3) and r is
the ratio of solution to soil (milliliters per gram) of water
extraction (the mean value of the ﬁeld study was 5.6). The
Kd,app calculated by eq 9 and Kd,app(t0) were used in eq 10 withand without consideration of time-dependent sorption,
respectively. The goodness of ﬁt to each estimation method
was assessed using the root-mean-square error (RMSE) and theNash−Sutcliﬀe model eﬃciency (NSE) calculated by thefollowing equation:38,39
RMSE =

100
O̅

n

1
∑ (Pi − Oi)2
n i=1

(11)

n
⎡ n
⎤ n
NSE = ⎢∑ (Oi − O̅ )2 − ∑ (Oi − Pi)2 ⎥ /∑ (Oi − O̅ )2⎢⎣ i = 1⎥⎦ i = 1
i=1

(9)

(12)

Thus, it appears to be possible to estimate the time-dependentchanges in the Kd,app values based on the Kd,app(t0) values.
The soil sorption, given as Kd,app values, of pesticides
increased with time. The rate of the increase in Kd,app with time
was high when Kd,app(t0), which represented the initial sorption
strength, was high. As mentioned in Dissipation Behavior of
Water-Extractable and Total Extractable Pesticides in Laboratory Studies, the DT50 values of CW decreased with increasing
Kd values without previous incubation. Therefore, it issuggested that the dissipation of CW is inﬂuenced by thetime-dependent increase in soil sorption. Taking this into
account is important for predicting the dissipation of CW.
Prediction of Water-Extractable Pesticides in a Field.
The ﬁeld study was conducted to validate the estimation
method of the time-dependent Kd,app based on Kd,app(t0)suggested by the laboratory study. The time-dependent changes
in the Kd,app values in the ﬁeld study were ﬁtted to eq 7.
Supporting Information section SI-4 shows the details of thelinear regression analysis between the Kd,app values and thesquare root of time. Figure 4 shows that measured b values for
all pesticides, except for fenobucarb and procymidone, are ingood agreement with predicted b values using eq 8. The
measured b values of fenobucarb and procymidone exceeded
the predicted values by ≥10-fold. The Kd,app values offenobucarb and procymidone were extremely high on days 14
and 49 and after 14 and 49 days, respectively, and the ﬁt to eq 7
for these two pesticides was poor (R2 < 0.3), as shown in
Supporting Information section SI-4. This is likely because theCaq values, i.e., the concentrations of pesticides in the aqueous
phase, for two pesticides decreased up to a level near the LOQwith time.
As discussed in Dissipation Behavior of Water-Extractable
and Total Extractable Pesticides in Laboratory Studies, thedissipation behaviors of CW and CT diﬀered from each other;i.e., the dissipation of CT could be described by the SFO model,
whereas the dissipation of CW was more rapid than that of CT
and was better ﬁtted to the biphasic model. As the reason for
this, the time-dependent increase in soil sorption was thought
to aﬀect the dissipation of CW. Therefore, the prediction ofdissipation of CW was performed by compensating for thewhere Pi and Oi are the predicted and observed values,
respectively, O̅ is the average of the observed values, and n is
the number of observations.
Figure 5 shows the comparison between the measured CW
and the predicted CW values with and without consideration of
the increase in Kd,app with time. In the case of pesticides having
low Kd,app(t0) values (<1 mL/g), such as dinotefuran, metalaxyl,
and fosthiazate, the predicted values with and without
consideration of the time-dependent Kd,app almost coincidedwith each other. On the other hand, when the Kd,app(t0) valuesof pesticides were >6 mL/g, the CW values predicted using theKd,app(t0) values overestimated the measured values. The
diﬀerences between the values predicted using the Kd,app(t0)values and the measured values, especially for clothianidin,
imidacloprid, and ﬂutoranil, were larger than those for otherpesticides. In contrast, the CW values predicted using Kd,app
estimated by eq 9 showed good agreement with the measured
CW values. Table 3 shows RMSE and NSE values for eachpesticide. The RMSE values calculated using the CW values
predicted by time-dependent Kd,app were lower than thosepredicted by the Kd,app(t0) values. Furthermore, the NSE values
were closer to 1 when the time-dependent increase in Kd,app wasconsidered. In particular, the NSE values of clothianidin,
imidacloprid, and ﬂutoranil were obviously improved with theconsideration of time-dependent sorption. These threepesticides had DT50 values of CT higher than those of otherpesticides. When the dissipation of CT was slow, the predictionof CW using Kd,app(t0) was inadequate and the consideration oftime-dependent sorption was required for prediction of CW.
Thus, the estimation method of CW using the dissipation of CT
and the time-dependent Kd,app, which was calculated by eq 9,
was capable of reproducing the biphasic dissipation of themeasured CW.
Our results demonstrate that dissipation of CW was fasterthan that of CT, and the time-dependent increase in Kd,app
aﬀected the diﬀerence in the dissipation rate between CW and
CT. Therefore, it is possible that the dissipation of CW, which
can be used to assess phytoavailability, is predicted bycorrecting the dissipation of CT by time-dependent Kd,app.
The increased rates of Kd,app with time were proportional to
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Kd,app(t0) values, and this empirical relationship suggests that
Kd,app(t0) plays an important role in the prediction of the timedependent increase in Kd,app and dissipation of CW. The
estimation method, which predicted the dissipation of CW using
the time-dependent Kd,app calculated on the basis of Kd,app(t0),
was demonstrated in the ﬁeld study. These results imply thatthe residual concentrations in leafy vegetables cultivated inpesticide-contaminated soils can be estimated before sowing byusing the correlations between the CW values at harvesting time,
which were predicted by the estimation method describedabove, and the uptake concentrations for the vegetables
reported in our previous study.4■

ASSOCIATED CONTENT

S Supporting Information*

The Supporting Information is available free of charge on the
ACS Publications website at DOI: 10.1021/acs.jafc.6b01028.

■

Sections SI-1−SI-4, including Tables S1−S7 (PDF)

AUTHOR INFORMATION

Corresponding Author*Telephone and fax: +81 29 838 8329. E-mail: seike@aﬀrc.go.
jp.
Present Address§

Y.M.: Food and Agricultural Materials Inspection Center,
Agricultural Chemicals Inspection Station, 2-772 Suzuki-cho,
Kodaira, Tokyo 187-0011, Japan.

Funding

This research was supported by the Environmental Research
and Technology Development Fund (5-1302) of the Ministryof the Environment, Japan.
Notes

The authors declare no competing ﬁnancial interest.

■

ACKNOWLEDGMENTS
We thank Shintaro Kanbayashi (Wesada University, Tokyo,
Japan) for his help with laboratory studies. The test soils werekindly supplied by Aichi Agricultural Research Center andTochigi Prefectural Agricultural Experiment Station.

■

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