Environ. Sci. Techno/.1995, 29, 1816-1821
Modeling 1,3-Dichlompropene Vapoi-Phase Advection in the CHUAN CHEN,*' R I C H A R D E. G R E E N , * DONALD M . THOMAS,' A N D JAMES A. KNUTESON$ Hawaii Institute of Geophysics, School of Ocean and Earth Science and Technology, University of Hawaii, 2525 Correa Road, Honolulu, Hawaii 96822, Department of Agronomy and Soil Science, College of Tropical Agriculture and H u m a n Resources, University of Hawaii, Honolulu, Hawaii 96822, and Ecosystem Fate & Exposure Assessment, DowElanco, 9330 Zionsville Road, Indianapolis, Indiana 46268-1053.
*
The simulation model LEACHP, a pesticide version of LEACHM, was modified to include air flow driven by barometric pressure change a t the soil surface, resulting in LEACHV, a model describing volatilephase transport. LEACHV provides explicit simulation of vapor-phase advection, Development of LEACHV was aided by using input data appropriate to the conditions of an Imperial Valley field experiment in which the volatilization flux of 1,3-dichloropropene (1,3-D) was measured and by comparing simulated and measured data a t various stages of development. Sensitivity analysis was then conducted for the primary parameters in LEACHV. In a subsequent comparison of simulated and measured volatilization for a Salinas Valley field, without any curve fitting and parameter manipulation, the LEACHV simulation produced the same general pattern as the measurement in response to changes in barometric pressure.
Introduction Fumigant pesticides have had an important role in crop production for several decades. In addition to the potential of these chemicals to move to groundwater, volatilization to the above-ground atmosphere is a public health concern. In recent years, the use of one of the most effective fumigant nematicides, 1,3-dichloropropene (1,3-D),was temporarily suspended in California because of concerns about potential adverse effects on air quality. 1,3-Dis generally applied by shank injection into the soil; in some applications, the soil is bedded, and the beds are covered with polyethylene film to retain the fumigant. The importance of 1,3-D for nematode control and its safetywith respect to air pollution has led to a major effort to identify 1,3-Duse patterns which will satisfy regulatory guidelines for air quality. The effort involves the measurement of 1,3-D flux at field sites in a number of important agricultural areas in California, coupled with the modeling of atmospheric transport from fields to surrounding areas. Volatilization flux determinations are expensive and time-consuming, requiring the measurement of vertical gradients of wind, temperature, and 1,3-Dconcentrations in the air above a treated field to provide the necessary data for the aerodynamic method (1). Because it will not be possible to evaluate all relevant combinations of soil, microclimate, and fumigant application method by the field flux method, it would be very desirable to have a reliable model of fumigant transport in the soil to provide estimates of flux patterns. Although models have previously been developed to describe pesticide volatilization from soil, they lack one or more key mechanisms of chemical transport or are restricted to simple conditions. Early models of fumigant movement (2, 3) did not include nonsteady flow of water. Models involving analytical solutions, such as developed by Jury et al. ( 4 ) , are useful for comparison of chemicals with simplified conditions but cannot adequately accommodate site-specific conditions. Also, existing models describing chemical transport in soils attribute chemical fluxes to only convection and dispersion of the liquid phase and diffusion of the vapor phase. For organic chemicals with significant vapor pressures, such models usually require increasing the effective vapor-phase diffusion coefficient to achieve a computed flux that matches experimental results. Recent research on vapor movement in soils and other vadose zone materials has demonstrated the importance of vapor-phase advection as a mechanism of vapor transport. Relatively small changes in barometric pressure can result in advective gas fluxes that are much larger than diffusive gas fluxes (5-10). Barometric pressure changes usually have an inverse influence on volatile transport; when barometric pressure decreases, volatile flux from the soil to the atmosphere increases because of the air-pumping phenomenon and vice versa ( 7 ,11-16). This study developed a model (by modifymg an existing model) that describes fumigant volatilization from soils for conditions relevant to the agricultural use of 1,3-D. An * Corresponding authors e-mail addresses: cchen8mano.soest. hawaii.edu or
[email protected]. + Hawaii Institute of Geophysics. College of Tropical Agriculture and Human Resources. DowElanco.
1816 ENVIRONMENTAL SCIENCE & TECHNOLOGY I VOL. 29, NO 7 , 1995
0013-936X/95/0929-1816$09.00/0
1995 American Chemical Society
existing numerical model of pesticide transport in soils, LEACHP, a pesticide version of LEACHM (17),was modified by adding explicit simulation of advective transport of the vapor phase. In LEACHP, volatilization across the soil surface is represented using concepts described by Liss (181for gas exchange across an air-water interface,a surface boundary layer. The volatile flux estimate is highly dependent on the empiricalvalues of the air-water interface, which does not consider any influence of advection through the boundary layer. An alternative approach, adopted in our later simulation and comparison, is to use the gas flux through the top soil segment (with advection) as an approximation of volatile flux to the atmosphere. The modification of LEACHP resulted in LEACHV, a new model with an improved capability for simulating volatile-phase transport. Sensitivity analysis of LEACHV was conducted by comparison of model results after variation of primary parameters. The starting parameters were measured or estimated from a 1,3-D volatilization field experiment conductedin the ImperialValleyof California (19). LEACHV was further evaluated with measured data from the Salinas Valley (20).
TABLE 1
List of Variables and Definitions b
cc
*
CG CL CL*
cs CT
foc @
g
H
JAG JCL JDG JDL Jl
k Ka Kad
KD KH* Koc
Model Description
Kw Kws
LEACHP is a pesticide application of the model LEACHM (LeachingEstimate and CHemistry Model, Version 3) (17). LEACHM is well-documented and widely used in research and various applications. LEACHP uses a numerical solution to the Richards equation as a means of predicting water contents,fluxes, and potentials. Once the water fluxes have been estimated in the subroutine WATFLO, the corresponding chemical fluxes can be estimated using a numerical solution to the convection-dispersion equation, taking into account concurrent sources and sinks of solute, sorption on the solid phase, and diffusion in the gas phase if the chemical is volatile. Expressed mathematically, using continuity relationships of mass over space and time, the convection-dispersion equation is described as
M Pa PW n vw
P Po 9a @a QB QW
R t
T
e
os Z
constant in Campbell hydraulic conductivity function concentration in gas phase (g m-3), CG = KH*CL saturated vapor density of the compound (g m-3) concentration in solution (g m-3) aqueous solubility (g m-3) concentration of chemical in the sorbed phase (mg kg-l of dry soil), CS= KDCL total solute concentration in all phases (liquid, gas, sorbed) (g m3, whole soil volume) organic carbon mass fraction of soil unspecified sources or sinks of solute (g m-3 d-l) 980 cm s - ~ ,the constant of gravitational acceleration air pressure head (cm), H = P + e a g z advection flux in the gas phase (mg m-2 d-l) convection flux in the liquid phase (mg m2d-l) diffusion flux in the gas phase (mg m-2 d-l) diffusion flux in the liquid phase (mg m-2 d-l) total solute flux (mg m-2 d-l) intrinsic permeability (cm2) air conductivity (mm d-l) air conductivity of a dry soil (mm d-l) partition coefficient (cm3g-l), KD= Kocfoc modified Henry's law constant, KH*= CG*/CL* organic carbon partition coefficient (cm3g-l) soil hydraulic conductivity (mm d-l) saturated hydraulic conductivity (mm d-l) molecular weight (g mol-') air dynamic viscosity (g s-l cm-l) water dynamic viscosity (g s-l cm-l) soil air-filled porosity (cm3~ m - n~=) 0s - 6' water kinematic viscosity (cm2s-l) vw = ,uw/ew barometric (air) pressure (lo2Pa) 8.5 x lo2 Pa, the maximum amplitude of P air flux through soil (mm d-l) air density (g ~ m - ~ ) soil bulk density (g ~ m - ~ ) water density (g ~ m - ~ ) gas constant = 8.314 x lo7 g cm2 s-l mol-' K-' time (day) temperature (K) volumetric water content (cm3~ m - ~ ) saturated volumetric water content (cm3~ m - ~ ) depth (mm)
air flow in soil. Adopting the derivation of the Richards equation for water flow (8,9), we can describe the air flow as Definitions of all variables are listed in Table 1. Numerous unit conversions are accomplished within the code of LEACHV. CT and IT can be expressed as
JT
= JDL + JCL + JDG + JAG
(3)
where the air-fled porosity, n = 8, - 8, here is a constant and can be obtained from the calculation of water content, 8, by the Richards equation. For an ideal gas, we have a relationship
LEACHP has a complete derivation of componentsJDL,ICL, MP (5) ea = and JDG. However, it assumes that air in soil is stagnant, and the advection effect of transport VAG)is approximated In addition, LEACHP applies the Campbell formula (21)to by adding an enhancement factor in the diffusion flux of describe the relationship between the soil hydraulic conthe gas phase. Consideration of air flow in soil,alternatively, ductivity, K,, and water content, 8 , as is the major modification of LEACHP in this modeling study.
Theoretical Development of Gas Advection Model Component
6
2b+3
I(, = G s (B,)
Commonly, gas advection VAG)is equal to qaCG or ~ ~ K H * C L .K, can also be approximated by the intrinsic permeability, Barometric pressure change is the driving force to cause k VOL. 29, NO. 7,1995 / ENVIRONMENTAL SCIENCE &TECHNOLOGY
1817
(7) Because the intrinsic permeability is roughly independent of fluid properties, the air conductivity of a dry soil, Kad, can be determined from eq 7:
Using the concept of relative permeability proposed by Bear (221,we can obtain the dry-soil air conductivity for a given soil for which the saturated hydraulic conductivity is known. Parameters such as pa, vw, p , , e,“, and ea vary with temperature. From eq 8, we assume that the relationship between the air-filled porosity, n, and the air conductivity, K3,is
Combining eqs 7-9 with eq 4 gives
widely applied in the measurement of volatilization of chemicals in relation to air quality. The soil at the site belongs to the Indio loam series, for which the bulk density is estimated to be 1.33 g ~ m in- the ~ upper horizon. An application volume of 113.2 L ha-’ (13697.0 mg m-Z)of TELONE I1 soil fumigant (trademark of DowElanco), containing 97.7% 1,3-dichloropropene, was injected to a soil depth of 30.5-45.7 cm (38.1 cm average). To match the input format of LEACHV, we assumed that all of the applied 1,3-D was initially distributed through a 10-cm depth segment of soil, resulting in an initial concentration of 8.51 mg kg-’ of dry soil; for a 5-cm segment, the concentration is 17.02 mg kg-l of dry soil. Continuous air monitoring of 1,3-Dconcentration and micrometeorlogical measurements required for the AD method were accomplished for a total of 8 days after chemical application. Diurnal barometric pressure change was also measured by DowElanco during the Imperial Valley field study. The maximum difference in barometric pressure during the course of the 8-day study was about 17.0 x 10‘ Pa, with a maximum of 1047 x lo2 Pa (770 mm mercury) and a minimum of 1030 x lo2Pa (757.5mmmercury) ( I 9 Figure 2-4, p 109). A diurnal air temperature measurement was also reported by Knuteson et al. (191, with an average temperature of 15.5 “C and an amplitude of 11.1 “C.
Sensitivity Analysis of the Modified LEACHM which can be solved numerically. In the context of this study, gravitational effects on the air pressure head can be neglected, so that a(P Qagz)/az= aP/az (approximately) and eq 10 can be simplified as
+
Surface and bottom boundary conditions are applied based on simulating conditions and site characteristics. A numerical solution of eq 11is incorporated as a subroutine, AIRFLOW, with LFACHP, resulting in a new model, LFACHV. Because eq 11 for air flow is a nonlinear differential equation and is not very stable for numerical convergence, a numeric smoothing technique and small time step are used to gain convergence and mass balance, especially when chemical concentration is low and the barometric pressure change is large. In addition, some computational problems are avoided by expressing barometric pressure changes relative to a standard pressure rather than in absolute terms.
Experiment Description and Estimated Parameters LFACHV,with the new advectivecomponent of vapor-phase transport, was developed and tested (including sensitivity analysis) using the conditions and measured results of the Imperial Valley experiment (19). Subsequently, the model was evaluated with field-measured fluxes obtained in the Salinas Valley (20). Experimental measurements of 1,3-Dfluxin the Imperial Valley were obtained on a large plot (60 705 m2). An aerodynamicvertical-profile flux (AD) method ( 1 )was used to compute 1,3-D fluxes. The method requires accurate vertical gradient measurements of horizontal wind speed, air temperature, and pesticide concentrations. A basic assumption is that the volatile flux density is the same throughout the boundary layer. The method has been 1818
ENVIRONMENTAL SCIENCE & TECHNOLOGY 1 VOL. 29. NO. 7.1995
Development of LEACHV was facilitated by evaluation of the model by comparison with ImperialValleyexperimental data (19). Sensitivity analysis with input data from the Imperial Valley site as the starting point provided a means of identifying the most critical inputs. Of particular interest was the impact of soil air conductivity, chemical sorption, chemical degradation, non-uniform distribution of the initial chemical application, and the potential for rapid movement of 1,3-Dthrough shank traces. Simulations of scenarios of interest were conducted. Relevant input parameters for the standard run and variation in the sensitivity tests are shown in Table 2. Barometric Pressure. In LEACHV, input data of barometric pressure change come from either actual measurement or simulated sinusoidal data. Figure 1 presents two curves,which represent approximatelythe measured results of barometric pressure change with a 6-h interval. One curve is with high-frequency diurnal change (smallwaves), represented by
I
tI
P = Po 0.9 cos -nt
f 0.04 sin (2x0
+ 0.06 cos (4x0
I
(12)
where PO= 8.5 x lo2 Pa (half of 17 x lo2 Pa pressure);the other is expressed by P = Po cos (nt/4) without highfrequency change. Figure 1 also shows the simulated gasphase fluxes corresponding to the diurnal change of barometric pressure with and without small pressure waves. The simulated gas-phase flux is very sensitive to barometric pressure change. A fluctuation of about 10%in barometric pressure at higher frequency resulted in an apparent response of 1,3-D gas flux without a time lag. Soil Air Conductivity. From eqs 8 and 9, soil air conductivity can be calculated from the soil hydraulic conductivity. The midpoint value of the soil-saturated hydraulic conductivity from the ImperialValleyexperiment was used for the standard run. Simulated results indicated that the gas flux is very sensitive to changes of soil air
;
TABLE 2
;
Initial C (mg kg-2
initial C (mg k g - 2
Scenarios of Sensitivity Analysis for LEACHV parameter variable
comments
option
barometric pressure ( i ) P = PO cos ( n f / 4 ) (iil P = eq 12 soil air conductivity
sensitive (standard) sensitive (standard)
li) K, = 700 mm d-' (iil K,, = 100 mm d-' (iiil K, = 1200 mm d-'
t
t
Care 1: Thin-layer at Depth
chemical sorption iil KO, = 50 cm3g-'
(standard)
Depth.
Care 2
Thick-layer at
0
Initial C (mg k g - l )
sensitive (standard)
( i i ) KO, = 20 cm3 g-' iiiil GC= 80 cm3g-'
-0
chemical degradation ii) ratea = 0.4 d-' (ii) rate = 0.112 day-' (iiil rate = 0.058 d-' initial chemical distribution case 1: thin layer at depth case 2: thick layer at depth case 3: uniform distribution in orofile case 4 linear increase with depth in profile air temperature (il av T = 115.5 "C amplitude = 11.0 "C (iil av T = 15.5 "C amplitude = 21.0 "C
sensitive (hn = 1.7 dl (standard) (tin = 6 dl (tqn = 12 dl
not sensitive (standard)
t Care 3
not sensitive (standard)
Uniform Disttibufion in Profile.
Linear increme with Depth in Profile.
C ~ p e4
FIGURE 2. Alternative initial 1.3-D concentration distributions in the soil profile tor Imperial Valley simulations.
First-order rate coefficient. 10
160 -J
-20
c
4
-20
0
2
4
6
8
10
0
2
.
6
8
10
lime Way1
FIGURE 3. Simulated 13-D volatile fluxes for different initial 1.3-0 distributions in the soil profile. 40
12
Time (day)
FIGURE 1. Simulated 1.3-D volatile flux in relation to barometric pressure at the Imperial Valleysite,with andwithout high-frequency
diurnal pressure changes.
conductivity, as estimated fromthe soil-saturated hydraulic conductivity. Chemical Sorption. Simulated chemicalsorption in the soil is dependent on both sorption coefficient (&,) of the chemical and organic carbon content (foJ distribution in thesoil profile. Thesoilorganic matter datawereobtained from the Imperial Valley study (19), but the sorption coefficient was not measured. Wauchope et al. (23)gave a K cvalue of 32 cm3 g-l for 1.3-D presumably this was a composite value for the cis and trans isomers which likely differ by about 25% the trans isomer being larger. Simulations demonstrated a high sensitivity of gas flux to sorption. 1,3-DDegradation. Measurement of 1,3-Ddegradation in a soil is difficult. No 1,3-D degradation data were available for the Imperial Valley experimental site. Assuming fmt-order degradation, we assigned half-lives of 1.7, 6 and 12 days (Table 21, based on experimental data
of Wolt et al. (24) and Van Dijk (25). Degradation kinetics definitely had a strong impact on vapor transport. Initial Chemical Distribution. The initial 1,3-D concentration distribution in the soil profile for all above simulations was calculated by assuming that all of the applied chemicalwas disuibuteduniformlythrougha5-cm depth increment at a depth of 40 cm in the profile. The initial concentration computed in this way was 17.02 mg kg-Lofdrysoil. Because of the potentialofrapid movement of 1,3-D through shank traces, different patterns of initial concentration distribution were evaluated by simulation. Figure 2 illustrates four cases of initial 1,3-D concentration distribution in the soil profile with the same total mass. Cases 3 and 4 simulate rougbly the possible impact of rapid redistribution of fumigant in injector shank traces or through other preferential flow paths. Figure 3 provides a comparison of 1,3-Dvapor flux fat the four initial distribution cases. The results indicate that cases 1,2, and 4 differ verylittle in their impact. Case3 evidences anearliervolatile flux but smaller peak value than other cases, probably because of the initially lower uniform 1,3-D concentration from the 45-cm depth up to the soil surface. Ah Temperature. Simulation with variations of air temperature (Table 2) did not result in a sensitivevariation VOL. 29,
NO. 7.1995 I ENVIRONMENTAL SCiENCE &TECHNOLOGY m 1819
100
A iz,
6
Barometric Pressure Change 1
,-0 :.6
ySimulated
Flux
'
.12
n
Conclusions
2 5E
g
0. -18
-E"
-24
d
Measured Flux
' 0 E
e
-20 0
5
10
15
Time (day)
FIGURE 4. Simulated and measured 1.3-0 volatilization in relation to barometric pressure change at Salinas Valley site.
of volatile flux as expected. Possible reasons were (1) the variation of air temperature change in LEACHVwas diurnal, which frequency was too high to affect longer-term heat transfer through the soil, because soil strongly attenuated short-period temperature variations with increasing depth and (2) the soil heat conductivity parameter was probably too low, and heat capacity was too high. The lack of fieldmeasured soil temperature data precluded an assessment of the modeling results.
Comparisons of Simulated and Field=Measured Results DowElanco data from a second 1,3-D field experiment conducted in the Salinas Valley in California (20) provided a means of further evaluating LEACHV. The experimental setup and measurement procedure were the same as those for the ImperialValley site. In the experiment, 115.1L ha-' (13923.3mg m-? of TELONE I1 soil fumigant (containing 96.6% 1,3-dichloropropene)was applied to a 40065-m2 rectangular plot by subsoil injection to a depth of 30.545.7 cm. Continuous air monitoring was scheduled for a total of 14 days starting at 7:OO AM on September 25, 1991. Barometric pressure was also monitored at hourly intervals. There was no precipitation during the experiment. Input parameters for simulation were either measured or estimated from the field experiment. Initial soil water content was assumed to be close to field capacity. The AIRFLOW subroutine was modified for the Salinas Valley simulations to allow input of measured barometric pressure data rather than having a mathematical function represent pressure change over time. Figure 4 compares simulated and field-measured 1,3-D vapor fluxes. Without any curve fitting and parameter manipulation, the simulation produced the same general pattern over time as the measurement in response to changes of barometric pressure. The volatile fluxes of the simulation responded more strongly to changes of barometric pressure than did measured fluxes. Even so, the total mass of 1,3-Dvolatilized was similar for the measurement and simulation. Volatile loss of 1,3-Dduring the 14day period was 12.4% of 1,3-D applied for the field measurement and 10.3% for the LEACHV simulation. Although the closeness of the simulated and field-derived results provided some basis for confidence in LEACHV, our judgment must be tempered by inherent uncertainty in the aerodynamic method by which field fluxes were determined ( I ) . 1820 m E N V I R O N M E N T A L SCIENCE &TECHNOLOGY / VOL. 29. NO. 7 , 1995
Our simulations indicate that LEACHV, which was modified from LEACHP with the subroutine AIRFLOW to include advective vapor movement, produced a promising representation of 1,3-D volatile flux over a 2-week period after fumigant injection. LEACHVis sensitive to key factors that impact volatile chemical transport through a soil profile. Barometric pressure changes over the measurement period were shown to drive advective vapor movement in model simulations. The model has the potential for estimation of field fumigant movement through unsaturated soil, at least for conditions similar to those of the two California sites used in the model development and evaluation. The use of LEACHV, a 1-dimensional model, may be less satisfactoryon finer texturedsoils in which lateral dispersion is limited and perhaps for other application scenarios which might require a two-dimensional model.
Acknowledgments Funding for this work was provided by DowElanco. Deep appreciation goes to J. D. Wok for making the funding possible. This paper is Contribution No. 4061 of the College of Tropical Agriculture and Human Resources, University of Hawaii.
Literature Cited (1) Majewski, M. S.; Glotfelty, D. E.; PawU, K. T.; Seiber, 1. N.Environ. Sci. Technol. 1990, 24, 1490-1497. (2)Hemwell, J. B. Soil Sci. 1959, 88, 184-190. (3) Leistra, M. A. Difusion and adsorption of the nematicide 1 3 dichloropropene in soil; Research Report 769; Center for Agricultural Publishing and Documentation: Wageningen, The Netherlands, 1988. (4)Jury, W. A.; Farmer, W. I.; Spencer, W. F. J. Environ. Qual. 1984, 13, 567-572. (5) Thorstenson, D. C.; Pollock, D. W. Rei). Geophys. 1989, 27 ( I ) , 61-78. (6) Thorstenson, D. C.; Pollock, D. W. Wuter Resour. Res. 1989, 25 (31, 477-507. (7) Chen, C.;Thomas,D. M.J. Environ. Qual. 1994,23 ( I ) , 173-179. ( 8 ) Massmann, I. W. J. Environ. Eng. 1989, 115 ( l ) , 129-149. (9) Massmann, J.; Farrier, D. F. Water Resour. Res. 1992, 28 (31, 777-791. (10) Farrier, D. J. M.S. Thesis, Michigan Technological Ilniversity, 1990. (11) Nilson, R. H.; Peterson, E. W.; Lie, K. H. J. Geophys. Res. 1991, 96 (B13), 21,933-21,948. (12) Thomas, D. M.; Cotter, J. M.; Holford, D. 1. Radioanal. N'ucl. Chem. 1992, 161 (21, 313-323. (13) Goh, T. B.; Oscarson, D. W.; Cheslock, M.: Shaykewich, C. Health P h p . 1991, 61 (3), 395-365. (14) Schery, S. D.; Gaeddert, D. H.; Wilkening, M. H. J. Geophys. Res. 1984, 89 (D5), 7299-7309. 115) Washington, J. W.; Rose, A. W. 1. Geophys. Res. 1992, 97 (B6), 9145-9159. (16) Tsang, Y. W.; Narasimhan, T. N. J. Geophys. Res. 1992, 97 (B6), 9161-9170. (17) Hutson, J. L.; Wagenet, R. J. LEACHM, LeachingEstimation And CHemistry Model, Version 3 Department of Soil, Crop and Atmospheric Sciences, Cornel1 University: Ithaca, NY. 1992. (18) Liss, P. S. Deep-sea Res. 1973, 20, 221-238. (19) Knuteson, J. A.; Petty, D. G.; Shurdut, B. A. Field volatility of 1,3-dichloropropene in the Imperial Valley of Southern California. Unpublished report of DowElanco, North American Environmental Chemistry Laboratory, Midland, MI 1992. (20) Knuteson, I. A.; Petty, D. G.; Shurdut, B. A. Field volatility of 1,3-dichloropropenein Salinas Valley California. Unpublished report of DowElanco, North American Environmental Chemistr?, Laboratory, Midland, MI 1992. (21) Campbell, G. Soil Sci. 1974, 117, 311-314. (22) Bear, J. Dynamics offluids in porous media: Elsevier: N e w York, 1972: p 459.
(23) Wauchope, R. D.; Buttler, T. M.; Hornsby, A. G.; AugustijnBeckers, P. W. M.; Burt, J. P. Rev. Environ. Contam. Toxicol. 1992, 123, 1-164. (24) Wok, J. D.; Holbrook, D. L.; Batzer, F. R.; Baker, J. L.; Peterson, J. R. Acta Hortic. 1993, 334, 361-371. (25) Van Dijk, H. Pestic. Sci. 1980, 1 1 , 625-632.
Received for review OctoFer 4, 1994. Revised m n w c r i p t received March 9, 1995. Accepted March 31, 1995.@ ES940621Q @
Abstract published in Advance ACS Abstracts, May 1, 1995.
VOL. 29, NO. 7, 1995 /ENVIRONMENTAL SCIENCE &TECHNOLOGY
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