Atmospheric Environment 66 (2013) 33e40

Contents lists available at SciVerse ScienceDirect

Atmospheric Environment
journal homepage: www.elsevier.com/locate/atmosenv

Assessment of methods for methyl iodide emission reduction and pest control
using a simulation modelbLifang Luo a, b, Daniel J. Ashworth a, b, Jirka Simunek, Richeng Xuan a, b, Scott R. Yates a, *ab

U.S. Salinity Laboratory, Riverside, 450 W. Big Springs Rd, Riverside, CA 92507, USA
Department of Environmental Sciences, University of California, Riverside, CA 92521, USAa r t i c l e i n f o

a b s t r a c t

Article history:
Received 15 November 2011
Received in revised form
28 March 2012
Accepted 30 March 2012

The increasing registration of the fumigant methyl iodide within the USA has led to more concerns about
its toxicity to workers and bystanders. Emission mitigation strategies are needed to protect the public
and environmental health while providing effective pest control. The effectiveness of various methods onemissions reduction and pest control was assessed using a process-based mathematical model in thisstudy. Firstly, comparisons between the simulated and laboratory measured emission ﬂuxes andcumulative emissions were made for methyl iodide (MeI) under four emission reduction treatments:
1) control, 2) using soil with high organic matter content (HOM), 3) being covered by virtually impermeable ﬁlm (VIF), and 4) irrigating soil surface following fumigation (Irrigation). Then the model
was extended to simulate a broader range of emission reduction strategies for MeI, including 5) being
covered by high density polyethylene (HDPE), 6) increasing injection depth from 30 cm to 46 cm (Deep),7) HDPE þ Deep, 8) adding a reagent at soil surface (Reagent), 9) Reagent þ Irrigation, and 10)
Reagent þ HDPE. Furthermore, the survivability of three types of soil-borne pests (citrus nematodes[Tylenchulus semipenetrans], barnyard seeds [Echinochloa crus-galli], fungi [Fusarium oxysporum]) was
also estimated for each scenario. Overall, the trend of the measured emission ﬂuxes as well as total
emission were reasonably reproduced by the model for treatments 1 through 4. Based on the numericalsimulation, the ranking of effectiveness in total emission reduction was VIF (82.4%) > Reagent þ HDPE
(73.2%) > Reagent þ Irrigation (43.0%) > Reagent (23.5%) > Deep þ HDPE (19.3%) > HOM (17.6%) > Deep
(13.0%) > Irrigation (11.9%) > HDPE (5.8%). The order for pest control efﬁcacy suggests, VIF had thehighest pest control efﬁcacy, followed by Deep þ HDPE, Irrigation, Reagent þ Irrigation, HDPE, Deep,
Reagent þ HDPE, Reagent, and HOM. Therefore, VIF is the optimal method disregarding the cost of the
ﬁlm since it maximizes efﬁcacy while minimizing volatility losses. Otherwise, the integrated methods
such as Deep þ HDPE and Reagent þ Irrigation, are recommended.
Ó 2012 Elsevier Ltd. All rights reserved.

Keywords:
Methyl iodide
Emission
Modeling
Pest control
Pesticide

1. Introduction
Fumigants are a group of highly volatile pesticides used todisinfest soils from soil-borne pests and pathogens before planting
crops. A signiﬁcant fraction (about 20e90%) of applied fumigants

Abbreviations: MeI, methyl iodide; VIF, virtually impermeable ﬁlm; HDPE, highdensity polyethylene ﬁlm; LDPE, low density polyethylene; MeBr, methyl bromide;CT, concentration-time index; 1,3-D, 1,3-dichloropropene; CP, chloropicrin; forfumigation treatment: HOM, using soil with high organic matter content; VIF, being
covered by virtually impermeable ﬁlm; Irrigation, irrigating soil surface following
fumigation; HDPE, being covered by high density polyethylene; Deep, increasing
injection depth from 30 cm to 46 cm; Reagent, adding a reagent at soil surface.
* Corresponding author. Tel.: þ1 951 369 4803; fax: þ1 951 342 4964.
E-mail address: Scott.Yates@ars.usda.gov (S.R. Yates).
1352-2310/$ e see front matter Ó 2012 Elsevier Ltd. All rights reserved.
doi:10.1016/j.atmosenv.2012.03.080

can be emitted into the atmosphere after fumigation (Yates et al.,2003), leading to health risks to agricultural workers and nearby
populations. Additionally, fumigant emissions can also contributeto ozone formation in the troposphere. In 2010, the U.S. Environmental Protection Agency proposed strengthening the national
ambient air quality standards for ozone, reducing the 8-hour
primary ozone standard to a lower level within the range of
0.060e0.070 ppm. Under such regulations, pesticide application
will need to minimize negative environmental effects while
maintaining efﬁcient pest control. Reduction of fumigants emission
losses is of great importance in terms of protecting environmental
and human health and maintaining crop productivity.
Methyl iodine (MeI) is considered to be an effective alternative
to the stratospheric ozone-depleting fumigant methyl bromide(MeBr), and has been increasingly adopted to control soil-borne
pathogens (Arysta Lifesciences, 2010). By 2010, 48 states had

34

L. Luo et al. / Atmospheric Environment 66 (2013) 33e40

registered MeI. Compared to other MeBr alternatives, MeI is morevolatile and toxic. Therefore, developing effective emission reduction methods is particularly important for MeI.
There have been many experimental efforts to determine theeffects of different application methods on reducing atmosphericfumigant emissions. These methods mainly fall into the following
categories: 1) covering the soil surface with plastic ﬁlms to restrict
the fumigant diffusion across the soileair interface, such as low
density polyethylene (LDPE), high density polyethylene (HDPE),
and virtually impermeable ﬁlms (VIF) (Yates et al., 2003; Ashworth
et al., 2009), 2) reducing the fumigant diffusion rate in soils bydecreasing the soil gas-phase pore space via surface irrigation orsoil compaction (Gao et al., 2008), 3) adding a soil amendment suchas soil organic matter or fertilizer to accelerate the degradation rateof fumigant in the soil (Yates et al., 2011a; Ashworth et al., 2009), 4)
injecting fumigants into deeper soil (Ashworth et al., 2009), and 5)
enhancing downward fumigant transport through drip-line application (Wang and Yates, 1999). Such experiments have provided
much needed scientiﬁc information for improving fumigant use
and for developing regulations. However, the experimental
methods to determine fumigant emissions from soil, especially inthe ﬁeld, are complex, time-consuming, and expensive; and often
cannot be suitably replicated.
Process-based mathematical models are relatively simple andcost-effective alternatives to expensive laboratory and ﬁeld
experiments and have been long used to simulate pesticidetransport and fate (Jury et al., 1983). There are numerous
computer programs such as CHAIN-2D (Simunek
and van
Genuchten, 1994), HYDRUS 1/2/3-D (Simunek
et al., 2008), and
SOLUTE (Yates, 2006) available to simulate volatile pesticidetransport by including a description of the volatilization process atthe soileair interface. Analytical solutions are also available toestimate soil concentrations, exposure estimates and volatilization losses from soil, provided that the soils are relatively homogeneous and gas-phase diffusive transport is the dominant
process (Yates, 2009).
However, a relatively small number of efforts have been
attempted to evaluate models for simulating fumigant transportand fate, and to determine the inﬂuences of different emission
reduction methods on emissions. This is due, in part, to lack ofobservational data (Shinde et al., 2000; Wang et al., 2004, 2007;
Cryer, 2005). The comparison of mathematical simulations toexperimental measurements enables determination of a model’sability to represent the actual fumigant behavior in soils and at thesoileair interface. Wang et al. (1997) simulated MeBr emissions
from a ﬁeld experiment by considering diurnal temperature effects.
They found that the model produced relatively accurate total
emissions but inaccurate timing of peak emission rates. Yates et al.
(2002) and Yates, (2006) reported that when the volatilization
boundary condition combined soil and atmosphere processes, the
SOLUTE simulation model provided more accurate descriptionsof the instantaneous emission rates for MeBr and a herbicide(Triallate).
Little is known of the effects of emission reduction strategies onpest control efﬁcacy. Using a numerical model, Wang et al. (2004)
evaluated 1,3-dichloropropene (1,3-D) efﬁcacies for controlling
nematodes for various soil types, ﬁeld geometry conﬁgurations,application depths, and application rates. Their results showed thatvalidation is an extremely challenging task for these types ofstudies. Luo et al. (2011) determined MeI dose-response curves forthree types of soil pests (i.e., nematode, weed seed, and fungus) andtested a 2-D model by comparing the simulated and observed
results. The model simultaneously predicted MeI volatilization,
degradation, soil concentration and percent mortality for nematode, weed seed and fungus. Overall, the model satisfactorily

predicted MeI movement as well as the soil zone where the three
types of pests were controlled.
The objective of this study was to predict MeI transport and fateunder sevaral emission reduction strategies and simultaneously
predict the resulting efﬁcacy against three types of soil pests using
a simulation model. Speciﬁcally, the model was evaluated against
experimental measurements of emission rates and loss for four
emission reduction treatments: 1) control, 2) using soil with highorganic matter content (HOM), 3) being covered by VIF (VIF), and4) irrigating soil surface following fumigation (Irrigation). Extensions of the model allowed simulating a broader range of emission
reduction methods, including 5) being covered by HDPE (HDPE),
6) increasing injection depth (Deep), 7) HDPE þ Deep, 8) addinga reagent at soil surface (Reagent), 9) Reagent þ Irrigation, and 10)
Reagent þ HDPE.
2. Methodology
2.1. Simulation model
To simulate fumigant fate and transport with consideration ofvariably-saturated soils and variable soil temperature, three governing processes: water ﬂow, heat transport, and solute fate andtransport were considered. For fumigant transport, the governing
equation describes the phase partition between liquid, gas, andsolid phase, convection, dispersion, diffusion and degradation
processes. Degradation was described using a ﬁrst-order decay
reaction, and included the ability to specify different degradation
rates in each phase (liquid, gas, and solid). The governing equation
for solute transport was written as follows (Simunek
and van
Genuchten, 1994):

h



vCg
vCg
vC
vCs
v
vC
Dg
þ q l þ rb¼
þ Dl l  qz Cl
vz
vt
vt
vt
vz
vz
 hmg Cg  qml Cl  rb ms Cs

ð1Þ

where Cg and Cl are gas- and liquid -phase concentrations(mg mL1), respectively; Cs is solid-phase concentrations (mg g1);
Dg and Dl are liquid- and gas-phase diffusion coefﬁcients in soils(cm2 s1), respectively; m is a ﬁrst-order degradation coefﬁcient(s1); q, rb, and h, respectively, are water content (cm3 cm3), bulk
density (g cm3), and air content (cm3 cm3); q is the Darcian ﬂux
density (cm s1); and the subscripts: l, s, and g indicate liquid-,
solid-, and gas- phases, respectively.
The partitioning between liquid- and gas-phase was assumed toobey Henry’s Law and the partitioning between liquid- and solidphase was assumed to be equilibrium adsorption as follows:

Cg ¼ Kh Cl(2)

Cs ¼ Kd Cl(3)

where Kh is the Henry’s law constant (dimensionless), Kd is thelinear equilibrium sorption coefﬁcient (cm3 g1).
A volatile surface boundary condition was used to simulate thevolatilization process






vC
De l  qz Cl ¼ h Cg  Cair Z¼0
vz
Z¼0

(4)

where Cair is gas concentration in the atmosphere (mg mL1);
De ¼ Dl þ Kh Dg is effective dispersion coefﬁcient (cm2 s1); h isa mass transfer coefﬁcient (cm s1) deﬁned as h ¼ Dairg =b, where
2 1
Dair
g is the binary gas diffusion coefﬁcient in the air (cm s ) andb is the thickness of a stagnant boundary layer at the soil surface(cm) (Jury et al., 1983).

L. Luo et al. / Atmospheric Environment 66 (2013) 33e40

The degradation rate, Henry’s Law constant, vapor diffusion
coefﬁcient, and ﬁlm permeability are temperature-dependent. To
account for temperature effect, the Arrhenius equation was used inmodel simulations to calculate a value for these parameters at
a speciﬁc temperature and time:ðTTr ÞbT ¼ br eEa RTTr

(5)

where bT is a temperature-dependent parameter; br is the reference
value for the parameter at a reference temperature; Ea is theactivation energy for the parameter bT (J mol1); Tr is the reference
temperature (K); and R is the universal gas constant(8.314 J mol1 K1).
To quantitatively evaluate organism exposure to pesticides,
a concentration-time index, CT, which is the integral of concentration over time was used:ZtCTðtÞ ¼

CT ðx; y; z; tÞdt(6)0

A logistic doseeresponse curve was used to describe therelationship between organism mortality, y, and CT:

y ¼

100%


CT p
1þ
CT50

(7)

where p is the slope at the inﬂection point of the logistic curve,
CT50 is the effective CT required to give a 50% mortality.

2.2. Experiment description
A complete description of the laboratory soil column experiments with simulated shank injection of MeI is given by
Ashworth et al. (2011). Soils were collected from two ﬁelds ona farm near Buttonwillow, CA (ﬁne-loamy, mixed, thermic Typic
Haplargids; Milam series). The primary difference between thetwo soils was organic matter content since composted green
waste material was previously applied to one of the ﬁelds,
elevating organic matter content from 2.09 to 3.16%. The laboratory experiments were designed to reproduce the ﬁeld soil
and environmental conditions. Brieﬂy, soil was packed intocylindrical (12  150 cm) stainless steel columns, maintaining
ﬁeld-measured bulk density and moisture content of the soil.
Near-surface soil temperatures were manipulated by programming the ambient temperature of the room in which the column
experiments were conducted. A stainless steel ﬂux chamber
placed on the surface of the soil column was swept with clean air
to channel emitted fumigant through sorbent tubes after MeI
injection at 30 cm depth.
The experiments compared HOM, Irrigation and VIF treatments to a Control (bare soil). The higher organic matter soil
was used for HOM treatment and all other treatments used thelower organic matter soil. For the VIF treatment, the plastic ﬁlm
was applied over the soil surface and a seal was created between
the soil column and the ﬂux chamber using epoxy resin,
producing a leak-free barrier. On day 14, the VIF was ripped via
a sealable port in the sidewall of the ﬂux chamber. Irrigation
was performed by inserting a pronged irrigation device into
the volatilization chamber and evenly distributing 1 cm of water
onto the soil surface. This was performed 3 h after applicationof the MeI, and repeated daily for the ﬁrst ﬁve days of theexperiment.

35

2.3. Simulation scenarios and parameterization
MeI emission and pest control for other scenarios listed anddescribed in Table 1 were also evaluated. Model simulations of
the column experiments were carried out using Hydrus1D
(Simunek
et al., 2008), modiﬁed to include various fumigantrelated processes, such as temperature-dependent properties ofthe surface tarp and removal of the tarp at a speciﬁed time.
The relevant experimental conditions and model parameters are
given in Table 2. These simulation parameters included the properties of soil, fumigant and ﬁlm (if applicable) and initial andboundary conditions. The parameters were obtained from either
a direct experimental measurement or from the literature, whena measured value was not available. Default soil hydraulic properties and heat transport properties for the sandy loam soil in Hydrus
1D were used for all simulations.
Speciﬁcally, the ﬁrst-order degradation rate constant was
0.0026 h1 for the untreated soil based on the experimental
measurement (Ashworth et al., 2011). The activation energy of theﬁrst-order degradation rate constant was estimated from the datareported by Zheng et al. (2004). Henry’s constant was 0.23
(dimensionless) at 25  C (Gan and Yates, 1996). The activationenergy of Henry’s constant was not reported in the literature, so thevalue of MeBr was substituted for MeI (Yates et al., 2003) because of
the similarity between MeI and MeBr. Sorption coefﬁcient was set
to be zero based on the measurement of Gan et al. (1996). MeI
binary gas diffusion coefﬁcient, Dab, and its activation energy were
estimated using Fuller correlation (Reid et al., 1987). Tortuosity ofsoil pore space was calculated using the Moldrup et al. (2000)
method, which was implemented in Hydrus1D.
For the volatile boundary, a boundary layer thickness (b) of
0.5 cm was used to calculate mass transfer coefﬁcient (h) for the
non-tarped treatments (Jury et al., 1983). For HDPE and VIF, masstransfer coefﬁcients from Papiernik et al. (2011) were used todetermine b and its activation energy (Table 2). After removing VIF
at 14 days, b was changed from 370,531 cm (for VIF) to 0.5 cm (forbare soil). The atmosphere boundary for water, solute and heattransport was used for the soil surface and non-ﬂow boundary wasused for the bottom end of the soil column (Simunek
et al., 2005).
The survivability of three types of soil-borne pest was predictedbased on the doseeresponse curves from Luo et al. (2011). Specifically, for Eq. (7), the CT50 for citrus nematodes, barnyard weed
seeds, and fungi were 13.1, 185.9, and 1194.6 mg h mL1, respectively
and p for citrus nematodes, barnyard seeds, and fungi were 1.55,
4.89, and 13.1, respectively.
Table 1
Description of various MeI emission reduction strategies. Application depth is 30 cm
except for Deep, which is 46 cm.
#

Treatment

Description

1.
2.

Control
HOM

3.

VIF

4.

Irrigation

5.

HDPE

6.
7.
8.

Deep
Deep þ HDPE
Reagent

9.

Reagent þ Irrigation

10.

Reagent þ HDPE

Bare surface.
Previously adding composted green wastematerial to the ﬁeld, elevating organic matter
content from 2.09 to 3.16%.
Covering soil surface with virtual impermeable
ﬁlm (VIF) and removing the ﬁlm at 14 days.
Being Irrigated 1 cm water each day at 10:30 am
for 5 days (rate was 2 cm h1).
Covering soil surface with high density
polyethylene ﬁlm (HDPE).
Increasing injection depth from 30 cm to 46 cm.
Combining treatments 5 & 6.
Adding a reagant at top 3 cm soil, with a MeI
degradation rate 100 times of that of Control.
Irrigating the soil surface with 2 cm water andadding the same reagent as listed in treatment 8.
Combining treatments 5 & 8.

36

L. Luo et al. / Atmospheric Environment 66 (2013) 33e40

Table 2
Experimental conditions and simulation model parameters for model simulations for ten treatments of MeI fumigation. The surface area of the column was 113.1 cm2.
Treatment/Data Type

Properties

MeI properties

Henry’s law constant at 25 Ca
0.23
370.5
Binary Gas diffusion coefﬁcient at 20 Cc
Binary water diffusion coefﬁcient at 20  C
0.115
Binary Gas diffusion coefﬁcientc
4403
Henry’s law constantd
26080
Degradation rate constante
39700
Initial soil temperature with depth
25e22
Temperature range
19e32
182.4
Initial mass, 150 mL of MeI
Initial water content:
0e15 cm deep,
10.5
15e30 cm deep,
13.5
30e45 cm deep,18
45e60 cm deep,
21>60 cm deep,
24
Organic matter content
2.7
Sorption coefﬁcient0
Degradation rate constantb
0.0026
Injection depth
300.0100Degradation rate constantb
Irrigated 1 cm water each day at 10:30 am for 5 days (rate was 2 cm h1)
EquivalentBoundary Layer Thickness, bref (cm)f
370,531102,000
Arrhenius Equation Activation Energy, Ea, for bf
f
Equivalent Boundary Layer Thickness, bref (cm)92.5
26,577
Arrhenius Equation Activation Energy, Ea, for bf
Injection depth
46
Degradation rate constant for top 3 cm soil
0.0026* 100

Activation energy for T-dependence

Heat transport
Initial concentration

All Treatments(unless other data provided)

HOM
Irrigation
VIF properties
HDPE properties
Deep
Reagent

Value

Units
dimensionless
cm2 h1
cm2 h1
J mol1
J mol1
J mol1C

C
mg
cm3 cm3
cm3 cm3
cm3 cm3
cm3 cm3
cm3 cm3%
cm3 g1
h1
cm
h1
cm
J mol1cm
J mol1cmh1a

Gan and Yates, (1996).
Ashworth et al. (2011).
Reid et al. (1987).
d
Yates et al. (2003) (the same as MeBr).
eZheng et al. (2004).
f
Papiernik et al. (2011) (Film FM5 for HDPE, the midpoint of the b range@20  C was used).
bc

3. Results and discussion
3.1. Methyl iodide emission
3.1.1. Comparison between observations and simulations
Simulated emission ﬂuxes of MeI for the Control, Irrigation,
HOM, and VIF treatments, together with the measured values, areshown in Fig. 1. The relatively simple trend in the emission ﬂuxes
for the Control, Irrigation and HOM treatments (i.e., large, very
early, initial peak, followed by rapid decline in emissions and thentailing) was well reproduced by the model. The simulated peaktime was consistent with that of measurement for each treatment(occurred very rapidly, 2e4 h sample period after fumigation
except for the VIF treatment). However, it is clear that the magnitude of the peak emission rate was underestimated for the Control
but was within the standard error bars, around 27% less than themeasured mean value. Similarly, the simulations also underestimated the peak for the HOM and Irrigation treatments, about
5% and 33% lower than the measured peak values, respectively. The
root mean square errors for emission ﬂuxes were 28.6, 7.7, 8.5, and3.6 mg m2 s1 for the Control, HOM, Irrigation, and VIF treatments,
respectively.
For the VIF treatment, the emission trend was different fromother treatments. During the ﬁrst 14 days, the emission rates werevery low, with a maximum peak about 0.02% of that of the control.
The ripping of VIF at 14 days caused a marked spike in emission
rates from 0.0003 mg m2 s1 (at 338 h) to around 30 mg m2 s1(at 340e344 h) according to measurements. The general pattern of
higher emissions was reproduced by the model. Nevertheless, incontrast to the other treatments, the model markedly overestimated the measured emission ﬂuxes. This could have beencaused by using a value for the mass transfer coefﬁcient that was

too high for the piece of ﬁlm actually used in the experiments. Evenso, the model seemed to capture the order-of-magnitude effect ofusing VIF, that is, a reduction in peak emission rates from the range
100e1000 to 0.1e1.0 mg m2 s1. Both the measured and simulated
showed a peak in the emission rate quickly after ripping the ﬁlm,
35.6 and 88.6 mg m2 s1 for the measured and simulated curve,
respectively.
Cumulative emissions of MeI, expressed as a percentage of theapplied mass, are also shown in Fig. 1 (insets). Considering thediscrepancies between the measured and simulated peak emission
ﬂuxes, the total emission losses are relatively accurately simulated.
The difference for the Control and Irrigation was relatively small,about 3e4%. The largest discrepancy was observed for the VIF
treatment, 9.6% difference within measured period (400 h). The
discrepancy became larger when the simulation time increased to
663 h, resulting in a total emission loss of 23.6% (i.e., 18.9% difference). The large variation in the measured emission values (Table 3)
indicates that the experimental uncertainty may mainly contributeto the discrepancy. After 14 days, a considerable amount of MeI still
resided in the soil (according to the measured MeI degradation rate,
about 41.2% of applied MeI remained in the soil). This led to a large
amount of MeI escaping into air after ripping.
The above results suggest that the simulation model, properly
parameterized, provides reasonably accurate MeI emissions thatare obtained from laboratory experimentation. The model provided
the same ranking as the experimental measurements in efﬁciencyof peak emission ﬂux reduction (i.e., VIF > Irrigation > HOM) andtotal emission loss reduction (i.e., VIF > HOM > Irrigation). The
HOM treatment led to a higher degradation rate, about four times
that of the control soil. However, the quick emission of MeI after
application resulted in limited reaction time and only a 20%
reduction in total emission. Similarly, the irrigation treatment did

L. Luo et al. / Atmospheric Environment 66 (2013) 33e40-1

Control

40

Simulated
Measured

20
0
0

200

Total emission (%)

400

60

2

600

80

Emission rate (µg m s )400

Total emission (%)

2

100

100

-1

Emission rate (µg m s )

800

37

100

200

300

400

Time (h)

300

200

80
60

HOM

40

Simulated
Measured

20
0

100

0

100

200

300

400

Time (h)

0

0
0

100

200

300

400

0

100

200

Time (h)
300

500

200

Simulated
Measured

20
0
0

100

200

300

400

Time (h)100

Total emission (%)

Irrigation

40

250

2

-1

Emission rate (µg m s )Total emission (%)

2-1

Emission rate (µg m s )

300

80
60

200
150

100

200

300

20
15
10
5
0
0

100

200

300

400

500

600

Time (h)Simulated
Measured
0

400

100

VIF

50
0

0
0

400

25

100

400

300

Time (h)

100

200

300

400

500

600

Time (h)Time (h)Fig. 1. Measured and simulated MeI emission ﬂuxes for the Control, Irrigation, HOM, and VIF treatments.

not lead to a considerable reduction in MeI emissions, despite
reducing the maximum peak emission ﬂux by about 35% relative to
the Control. Ashworth et al. (2011) suggested that the initial 1 cm
irrigation was insufﬁcient to effectively form a barrier of waterﬁlled pore space for MeI due to rapid MeI emissions.
3.1.2. Simulating a wider range of emission reduction strategies
Simulated emission ﬂuxes of MeI for the HDPE, Deep,
Deep þ HDPE, Reagent, Reagent þ Irrigation and Reagent þ HDPE
treatments are shown in Fig. 2. Despite reducing the peak emission
ﬂux by 40.5% relative to the Control, the HDPE treatment did notcause a signiﬁcant reduction in total emission. The simulated total
emission reduction by HDPE relative to the Control (5.8%) was
about the same as the previously observed value for MeI (6%; Ganet al., 1997). The Deep treatment substantially reduced the peakemission ﬂux compared to the control (by 30%). However, a total of
about 75.6% of the applied MeI was emitted into air (i.e., a 13%

reduction). Again, the data conﬁrms that HDPE alone and deep
injection alone are not effective methods for reducing MeI emissions (Ashworth et al., 2009).
Previous study has shown that thiourea accelerated the degradation of MeI in soil and has potential to serve as a reagent whenapplied at the soil surface. The degradation rate was signiﬁcantly
increased (about 12 times) when the mass ratio (thiourea vs. MeI)
was 2:1 (Zheng et al., 2004). Gas phase MeI concentration at soil
surface is typically less than 10 mg mL1 (Ashworth et al., 2011).
When a reagent is only distributed at the soil surface (e.g., 3 cm),the mass ratio of reagent vs. MeI is likely to be very high.
For example, Ashworth et al. (2009) used an application rateof 50 g m2 for ammonium thiosulfate, a reagent of 1,3dichloropropene (1,3-D) and chloropicrin (CP) (equivalent to1667 mg mL1 when assuming it is only distributed at the top 3 cm).
The higher mass ratio will result in more rapid degradation. Here,
we assume a degradation rate of 100 times greater in the top 3 cm

Table 3
Measured and simulated total emission losses of MeI from soil columns. The number in parentheses is the standard deviation of the mean (n ¼ 2). The data were not available
for the blank.
Treatment

Control
HOM
VIF
Irrigation
HDPE
Deep
Deep þ HEDP
Reagent
Reagent þ irrigation
Reagent þ HDPE
abTotal emissions

Peak emission

Measured(%)

Simulated(%)

83.3 (0.69)
63.2 (2.35)
5.7 (4.2)b81.6 (3.7)

86.9
71.57
15.3b
76.6
81.9
75.6
70.1
66.5
49.5
23.3

Compared to the Control.
Within 400 h after fumigation.

Measured
reduction (%)aSimulated
reduction (%)a

24.1
93.2b
2.0

17.6
82.4b
11.9
5.8
13.0
19.3
23.5
43.0
73.2

Measured(mg m2 s1)

Simulated(mg m2 s1)

570.1 (148.6)
389.4 (16.4)
35.6 (44)379.9 (38.8)

417
370.5
88.53
256
248.3
126.6
81.8
312.6
87.1
93.1

Measured
reduction (%)aSimulated
reduction (%)a

31.7
93.8
33.4

11.2
78.8
38.6
40.5
69.6
80.4
25.0
79.1
77.7

38

L. Luo et al. / Atmospheric Environment 66 (2013) 33e40

0Control
HoM
Irrigation
VIF
HDPE
Deep
Deep+HDPE
Reagent
Reagent + Irrigation
Reagent + HDPE

Depth (cm)

-20

-40

-60

-80

-100
0

1000

2000

3000

4000

Concentration time (µg cm-3 h)Fig. 2. Predicted MeI emission ﬂuxes for the HDPE, Deep, Deep þ HDPE, Reagent,
Reagent þ Irrigation, and Reagent þ HDPE treatments.

soil than that of the control soil. Total emission and peak emission
ﬂux were reduced by 23.5% and 25.0%, respectively. The reduction
in total emission was more effective than the HDPE and Deep
treatments.
There are few studies to determine the effects of integrated
management practices on fumigant emissions. Using a simulation
model, three types of integrated methods were tested here. Whencoupling the HDPE and Deep treatments, the total emission
reduction was about the sum of each method alone (19.3%). The
peak emission rate was only about 20% of the Control. Whena reagent was applied together with irrigation at soil surface, lesspore space is available for fumigant diffusion, leading to anincreased reaction time in the soil and a reduction in emissions(total emission reduced by 43% and peak emission rate reduced by80%). The Reagent þ HDPE treatment signiﬁcantly reduced the total
emission (by 73.2%) and peak emission rate (by 77.7%). Clearly,
compared with irrigation (2 cm water), HDPE produced a betterbarrier for MeI emission when a reagent was available. Interestingly, Xuan et al. (2011) proposed the use of reactive ﬁlms consisting of a reagent between two ﬁlms as a method to reduce
fumigant atmospheric emission.
It is clear that coupling of different methods can lead toa signiﬁcant improvement in emission reduction and thus has
great potential to mitigate air pollution. For example, irrigation
is a common practice and usually required before fumigation.
Integration of this method to other emission reduction methods
provides a simple and economical mitigation strategy. Though
HDPE alone is not very effective in emission reduction, being used
together with other methods such as a reactive surface barrier, canlead to a signiﬁcant reduction in emissions.
3.2. Pest control
The predicted MeI concentration-time values in the soil proﬁlefor all treatments are shown in Fig. 3. Generally, the CT values wererelatively high within about 30 cm below the injection depth. As
expected, the HOM treatment reduced the CT values because of
more rapid degradation relative to the Control. However, thereduction was not signiﬁcant in the top 20 cm, probably due torapid volatilization of MeI into air for any treatment without
a surface barrier. The reduction in CT values became more evident
with increasing depth. The Deep treatment also slightly reduced
the CT values in the top 30 cm but notably raised the values of theFig. 3. Predicted MeI concentration-time values along soil depths for the Control,
irrigation, HOM, VIF, HDPE, Deep, Deep þ HDPE, Reagent, Reagent þ Irrigation, andReagent þ HDPE treatments.

deeper soil. Reagent had little effect on the CT values in the soil
proﬁle, since enhanced degradation only occurred near the soil
surface. With a barrier of water or ﬁlm at soil surface, the CT values
were elevated in the soil proﬁle. The VIF treatment was the mosteffective to contain MeI in the soil, having at least 3 times higher CT
values than other treatments.
Survivability of three types of soil pests with different sensitivity
to MeI were predicted (Fig. 4). Overall, control of soil pests was best
between 30 and 60 cm. The VIF treatment had the highest efﬁcacy
with nearly full control of all three types of pests. Control of fungi
within the top 20 cm soil was very limited for other treatments.
Fungus control for the Deep treatments (Deep and Deep þ HDPE)
was the next best, with more than 60% fungi killed within 40e60 cm.
Compared to the Control, the HDPE and Irrigation treatments
showed an increase in fungus mortality but were still relatively
ineffective compared to the VIF treatment. For nematodes and weed
seeds, there was also relatively poor control near the soil surface. As
expected, the HOM, Deep and Reagent treatments weakened
nematode and seed control within the top 30 cm soil relative to theControl. Except for VIF, HDPE, and Deep þ HDPE treatments, morethan 40% of the seeds in the top 15 m soil were still alive following
fumigation. Because citrus nematode is the most sensitive to MeI
among the three types of soil pests (Luo et al., 2011), more than 90%
of nematodes were killed for all treatments for the top 100 cm soil.
It has been reported that the lethal CT values decrease with soil
temperature (Xue et al., 2000) and even temperature alone cansuppress soil pests (Yates et al., 2011b). Therefore, modeling soil
pest survival can be improved by considering the effect of soil
temperature and its synergy with fumigants. Future research isneeded to develop a database of organism survival as a function oftemperature and fumigant concentration. Moreover, pest control
efﬁcacy for different treatments should not be simply compared byusing the average pest mortality of the whole proﬁle or any depth.
For example, since pest control in the top 15 cm soil is typically themost critical for crop plant growth, especially the early stage,emphasis should be made to increase the CT values in the vicinity ofthe soil surface. To achieve this, covering the soil surface withimpermeable ﬁlms is a highly effective practice because impermeable tarps at the soil surface maintain fumigant concentrations
and simultaneously increase surface daytime soil temperatures up
to 14  C (Yates et al., 2011b); these may act together to enhance thepest control for the surface soil layer.

L. Luo et al. / Atmospheric Environment 66 (2013) 33e40

0-20

Citrus Nematodes

Depth (cm)[Tylenchulus semipenetrans]-40

Control
HoM
Irrigation
VIF
HDPE
Deep
Deep+HDPE
Reagent
Reagent + Irrigation
Reagent + HDPE

-60

-80

-100
90

92

94

96

98

100

Mortality %0

Fungi[Fusarium oxysporum]

Depth (cm)

-20

-40

39

emission reduction methods on pest control. The comparisons
between the model simulation and laboratory experimentation for
the Control, HOM, Irrigation and VIF imply that simulation models
provide reasonably accurate emissions of MeI. In summary,the ranking of effectiveness was VIF > Reagent þ HDPE >Reagent þ Irrigation > Reagent > Deep þ HDPE > HOM > Deep >Irrigation > HDPE for total emission reduction, and Deep þ
HDPE > Reagent þ Irrigation > VIF > Reagent þ HDPE > Deep >Irrigation > HDPE > Reagent > HOM for peak emission rate reduction. For pest control, the ranking of effectiveness was different fromthe above. Generally, VIF had the highest pest control efﬁcacy,followed by Deep þ HDPE, Irrigation, Reagent þ Irrigation, HDPE,
Deep, Reagent þ HDPE, Reagent, and HOM.
When both atmospheric emission reduction and pest control
efﬁcacy are considered, VIF is the best method among nine treatments due to its ability to contain MeI within the soil. When VIF isused, a much lower dosage is required to achieve the same level ofpest control, compared to other methods. This should partly offset
the cost of VIF since it is expected that VIF is likely to be more
expensive than other ﬁlms such as HDPE. However, attention
should be paid to the high emission rate and risk potential whenremoving the VIF after about two weeks. When VIF is not available,
integrated methods such as Deep þ HDPE and Reagent þ Irrigation,
are recommended.
Acknowledgements

-60

-80

-100
0

20

40

60

80

100

Mortality %0

References

Barnyard weed seeds-20

The authors thank Q. Zhang for her technical assistance in
conducting these experiments. Part of the research described was
supported by California Air Resources Board (agreement #07-332).
The use of trade, ﬁrm, or corporation names in this paper is for the
information and convenience of the reader. Such use does notconstitute an ofﬁcial endorsement or approval by the United States
Department of Agriculture or the Agricultural Research Service ofany product or service to the exclusion of others that may besuitable.

Depth (cm)

[Echinochloa crus-galli]
-40

-60

-80

-100
0

20

40

60

80

100

Mortality %Fig. 4. Predicted MeI mortality of three types of soil pests (citrus nematodes[Tylenchulus semipenetrans], barnyard seeds [Echinochloa crus-galli], fungi [Fusarium
oxysporum]) along soil depths for the Control, Irrigation, HOM, VIF, HDPE, Deep,
Deep þ HDPE, Reagent, Reagent þ Irrigation, and Reagent þ HDPE treatments (notice
the different x-axis for citrus nematodes).

4. Conclusions
With the registration of MeI, there is great potential of excessive
atmospheric emissions following soil fumigation. This can becomea serious concern due to the high toxicity of this fumigant. In thisstudy, numerical simulations were performed to simulate shankinjection of MeI in soil and to determine the effects of different

Arysta Lifesciences, 2010. California announces proposed decision to register Midasfor commercial use [accessed 8.11.11]. http://www.arystalifescience.us/assets/ﬁles/News%20Releases/2010/US%20Ag/163-California_Registers_Midas.pdf.
Ashworth, D.J., Ernst, F., Xuan, R., Yates, S.R., 2009. Laboratory assessment of emission
reduction strategies for the agricultural fumigants 1,3-dichloropropene andchloropicrin. Environmental Science and Technology 43, 5073e5078.
Ashworth, D.J., Luo, L., Xuan, R., Yates, S.R., 2011. Irrigation, organic matter addition,and tarping as methods of reducing emissions of methyl iodide from agricultural soil. Environmental Science and Technology 45, 1384e1390.
Cryer, S.A., 2005. Predicting soil fumigant air concentrations under regional anddiverse agronomic conditions. Journal of Environmental Quality 34, 2197e2207.
Gan, J., Yates, S.R., 1996. Degradation and phase partition of methyl iodide in soil.
Journal of Agricultural and Food Chemistry 44, 4001e4008.
Gan, J., Yates, S.R., Ohr, H.D., Sims, J.J., 1997. Volatilization and distribution of methyl
iodide and methyl bromide after subsoil application. Journal of Environmental
Quality 26, 1107e1115.
Gao, S., Trout, T.J., Schneider, S., 2008. Evaluation of fumigation and surface
seal methods on fumigant emissions in an orchard replant ﬁeld. Journal ofEnvironmental Quality 37, 369e377.
Jury, W.A., Spencer, W.F., Farmer, W.J., 1983. Behavior assessment model for traceorganics in the soil. I. Model description. Journal of Environmental Quality 12,558e564.
Luo, L., Yates, S.R., Ashworth, D.J., 2011. Predicting methyl iodide emission, soil
concentration, and pest control in a two-dimensional chamber system. Journalof Environmental Quality 40 (1), 109e117.
Moldrup, P., Olesen, T., Gamst, J., Schjønning, P., Yamaguchi, T., Rolston, D.E., 2000.
Predicting the gas diffusion coefﬁcient in repacked soil: water-induced linear
reduction model. Soil Science Society America Journal 64, 1588e1594.
Papiernik, S.K., Yates, S.R., Chellemi, D.O., 2011. A standardized approach forestimating the permeability of plastic ﬁlms to soil fumigants under various
ﬁeld and environmental conditions. Journal of Environmental Quality 40,1375e1382.
Reid, R.C., Prausnitz, J.M., Polling, B.E., 1987. The Properties of Gases and Liquids,
fourth ed. McGraw-Hill, New York.

40

L. Luo et al. / Atmospheric Environment 66 (2013) 33e40

Shinde, D., Hornsby, A.G., Mansell, R.S., Savabi, M.R., 2000. A simulation model forfate and transport of methyl bromide during fumigation in plastic-mulchedvegetable soil beds. Pest Management Science 56, 899e908.
Wang, D., Yates, S.R., 1999. Spatial and temporal distributions of 1,3-dichloropropene
in soil under drip and shank application and implications for pest control efﬁcacy
using concentration-time index. Pesticide Science 55, 154e160.
Wang, D., Yates, S.R., Gan, J., 1997. Temperature effect on methyl bromide volatilization in soil fumigation. Journal of Environmental Quality 26, 1072e1079.
Wang, D., He, J.M., Knuteson, J.A., 2004. Concentration-time exposure index formodeling soil fumigation under various management scenarios. Journal ofEnvironmental Quality 33, 685e694.
Wang, D., He, J., Knuteson, J., 2007. DripFume: a visual basic program for simulating
distribution and atmospheric volatilization of soil fumigants applied throughdrip irrigation. Computers and Electronics in Agriculture 56, 111e119.
Xuan, R.A., Ashworth, D.A., Luo, L.F., Yates, S.R., 2011. Reactive ﬁlms for mitigating
methyl bromide emissions from fumigated soil. Environmental Science andTechnology 45 (6), 2317e2322.
Xue, S.K., Gan, J., Yates, S.R., Becker, J.O., 2000. Nematode response to methyl
bromide and 1,3-dichloropropene soil fumigation at different temperatures.
Pest Management Science 56, 737e742.
Yates, S.R., 2006. Measuring herbicide volatilizations from bare soil. Environmental
Science and Technology 40, 3223e3228.
Yates, S.R., 2009. Analytical solution describing pesticide volatilization from soil
affected by a change in surface condition. Journal of Environmental Quality 38,
259e267.

Yates, S.R., Wang, D., Papiernik, S.K., Gan, J., 2002. Predicting pesticide volatilizationfrom soils. Environmetrics 13, 569e578.
Yates, S.R., Gan, J., Papiernik, S.K., 2003. Environmental fate of methyl bromide as a soil
fumigant. Reviews of Environmental Contamination & Toxicology 177, 45e122.
Yates, S.R., Knuteson, J., Zheng, W., Wang, Q., 2011a. Effect of organic material on ﬁ
eld-scale emissions of 1,3-dichloropropene. Journal of Environmental Quality
40, 1470e1479.
Yates, S.R., Ashworth, D.J., Yates, M.D., Luo, L.F., 2011b. Active solarization asa nonchemical alternative to soil fumigation for controlling pests. Soil Science
Society of America Journal 75, 9e16.
Zheng, W., Papiernik, S.K., Guo, M., Yates, S.R., 2004. Remediation of methyl iodide
in aqueous solution and soils amended with thiourea. Environmental Scienceand Technology 38, 1188e1194.

Simunek,J., van Genuchten, M.Th., 1994. The CHAIN_2D Code for Simulating
Two-Dimensional Movement of Water Flow, Heat, and Multiple Solutes
in Variably-Saturated Porous Media, Version 1.1. United States Salinity Laboratory
Research Report #136. United States Salinity Laboratory, Riverside, CA.

Simunek,J., van Genuchten, M.Th., Sejna,M., 2005. The Hydrus-1D Software
Package for Simulating the One-dimensional Movement of Water, Heat, andMultiple Solutes in Variably-saturated Media. Version 3.0, HYDRUS Software
Series 1. Department of Environmental Sciences, University of California
Riverside, Riverside, CA.

Simunek,J., van Genuchten, Th., M., Sejna,M., 2008. Development and applicationsof the HYDRUS and STANMOD software packages, and related codes. Vadose
Zone Journal 7 (2), 587e600.