physical properties and evaporation characteristics of nonaqueous insecticide formulations, spray...

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Physical propertiesand evaporationcharacteristics ofnonaqueous insecticideformulations, spraydiluents and adjuvant/co‐solvent mixturesAlam Sundaram aa Canadian Forest Service Forest PestManagement Institute , Natural ResourcesCanada , 1219 Queen Street East Box 490,Sault Ste. Marie, Ontario, Canada , P6A5M7Published online: 14 Nov 2008.

To cite this article: Alam Sundaram (1995) Physical properties andevaporation characteristics of nonaqueous insecticide formulations, spraydiluents and adjuvant/co‐solvent mixtures, Journal of EnvironmentalScience and Health, Part B: Pesticides, Food Contaminants, and AgriculturalWastes, 30:1, 113-138

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J. ENVIRON. SCI. HEALTH, B30(l), 113-138 (1995)

PHYSICAL PROPERTIES AND EVAPORATION CHARACTERISTICS OF

NONAQUEOUS INSECTICIDE FORMULATIONS, SPRAY DILUENTS

AND ADJUVANT/CO-SOLVENT MIXTURES

Key Words: Tebufenoride, permethrin, diflubenzuron, Bacillus thuringiensisvar. kurstaki petroleum solvents, paraffinic oils, vegetable oils,surfactant, hydroxylic solvents, viscosity, surface tension, evaporationrate, nonvolatile component, half-life of evaporation

Alam Sundaram

Natural Resources Canada, Canadian Forest ServiceForest Pest Management Institute, 1219 Queen Street East

Box 490, Sault Ste. Marie, Ontario, Canada P6A 5M7

ABSTRACT

Three chemical insecticides, tebufenozide, permethrin and diflubenzuron,

and a bacterial control agent, Bacillus thuringiensis var. kurstaki, were mixed with

oil-based carrier diluents or diluent oil mixtures to provide several spray

formulations. In addition, two adjuvants, Triton® X-114 and glycerol, were mixed

with hydroxylic co-solvents to provide adjuvant/co-solvent mixtures. All of these

liquids were tested for their evaporation behaviour using a gravimetric method.

The data were subjected to linear regression analysis to determine three volatility

parameters, i.e., evaporation rate (ER), nonvolatile components (NVC%) and half-

113

Copyright © 1995 by Marcel Dekker, Inc.

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114 SUNDARAM

life of evaporation, T1/2. In addition, a new equation was developed to determine

the fourth volatility parameter, mean loss of mass per min (MLMPM). Viscosity

(η) and surface tension (γ), were also measured to determine the relationships

of the two physical properties with the four volatility parameters.

Viscosity showed a better correlation with the volatility parameters than

surface tension. Correlation was even better between η and NVC%, than between

η and ER or T1/2. Correlation between η and NVC% was far better for the

insecticide spray formulations than for the diluent oils, diluent oil mixtures and

adjuvant/co-solvent mixtures. The present study also provided a new methodology

to determine the novel volatility parameter, MLMPM, which also showed a good

correlation with viscosity.

INTRODUCTION

In Canada, insecticides are sprayed over forests mostly by aircraft, and

it is important to obtain good coverage of target areas with minimum volume

of the spray liquid. The means of achieving this goal is to use the ultra-low-

volume (ULV) spraying technique (Maas, 1971) and to spray fine droplets, i.e.,

those smaller than about 120 urn in diameter, since coverage is inversely

proportional to droplet diameter. Obviously, there is a lower limit to the droplet

size that can be used. With droplets smaller than 80 p.m in diameter, the

percentage of dynamic catch falls off so rapidly that the expected increase in

coverage is just about nullified. This means that every effort should be made

to produce a spray with few droplets > 120 |j.m and few < 80 urn. This droplet

size spectrum has been found, in practice, to have definite advantages: the fine

spray results in a wider swath and a more uniform coverage. With such droplet

sizes, however, the fall time is quite large because of their low terminal

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PROPERTIES OF NONAQUEOUS INSECTICIDES 115

velocities (Amsden, 1962). In this transit period, the droplets would evaporate

if the spray liquid contained highly volatile ingredients, and the droplet diameter

could become too small to deposit on target trees efficiently. As a result,

pesticidal activity could be reduced, and off-target drift would be increased

(Matthews, 1979). Consequently, the volatility, i.e., the tendency to go into

vapour phase, of a spray mixture plays an important role in determining the

success or failure of an aerial spray operation. Because the major portion of a

spray mixture is the carrier liquid, the volatility of the final medium is largely

dictated by that of the carrier liquid. At times, adjuvants can interact with co-

solvents (hydroxylic solvents) and affect spray mixture volatility. Therefore, it

is important to know the evaporation characteristics of spray mixtures, carrier

liquids and adjuvant/co-solvent mixtures used in forestry spray operations.

Viscosity and surface tension of a spray mixture affect its volatility

(Sundaram, 1987), and it would be useful to determine the inter-relationships

between the viscosity, surface tension and the volatility parameters (i.e.,

evaporation rates and nonvolatile components), to understand the mechanism

of evaporation. Therefore, the objectives of the present study were to determine

the inter-relationships among viscosity, surface tension and volatility parameters

of nonaqueous insecticide mixtures and diluent oils used in forestry sprays.

MATERIALS AND METHODS

A gravimetric method involving Whatman No. 1 filter paper, similar to the

one reported earlier (Sundaram, 1985), was used in this study to determine

evaporation rates of several insecticide spray formulations, diluent oils and oil

mixtures (Tables 1 and 2). In addition, two spray modifier adjuvants, [Triton®

X-114 (a nonionic surfactant) and glycerol (trihydroxypropane)] were mixed

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116 SUNDARAM

TABLE 1. Pesticide formulations, petroleum solvents, adjuvants and otheringredients used in the study

Name

Exsol®-D

Sunspray® 6N

Abbreviation used

Ex-D

Sun-6N

Cyclosol® 63 Cycl-63

Insecticide diluent 585 ID-585

Source

Esso Chemical, Samia, Ont., Canada

Sunoco, Toronto, Ont., Canada

Shell Canada, Toronto, Ont., Canada

Fuel oil # 44

Arotex® 3470

Soybean oil

Canola oil

Corn oil

Glycerol

Triton® X-114

Tebufenozidea

Permethrinb

Diflubenzuron0

ABG-6203® d

Fuel-44

Aro-3470

Soy-oil

Can-oil

Corn-oil

GlyTrit-114

TE-tech

Perm

DFB

BTK

Texaco, Toronto, Ont., Canada

Canada Packers, Toronto, Ont., Canada

J.T. Baker Chemical, N.J., USA

Rohm and Haas, Ont., Canada» > it it

Chipman, Stoney Creek, Ont., Canada

Duphar, B.V., Weesp, The Netherlands

Abbott Laboratories, Long Grove,

Illinois, USA

a: Tebufenozide = /V'-t-butyl-/V-(3,5-dimethylbenzoyl)-N-(4-ethylbenzoyl)hydrazine. It is also described as RH-5992 or Mimic .

b: Permethrin = 3-phenoxybenzyl(1FtS)-c/s-frans-3-(2,2-dichlorovinyl)-2,2-dimethylcyclopropanecarboxylate.

c: Diflubenzuron = 1-(4-chlorophenyl)-3-(2,6-difluorobenzoyl)urea.

d: ABG-6203® was a dry powder of Bacillus thuringiensis var. kurstaki,containing 15000 lU/mg dry weight (data provided by Abbott).

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TABLE 2. Composition of diluent oil mixtures and insecticide spray mixturesused in the study

No. Liquid abbreviation Composition (w/w%)

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

CID-585

C-Fuel-44

C-6N-585

C-SO-585

C-CA-585

C-CO-585

585-6N-30

585-6N-40

585-6N-50

585-6N-60

585-6N-75

585-6N-85

PCy-1

PCy-2

PCy-585-1

PCy-585-2

TE-Cy-6N

TE-Cy-CA

TE-Cy-SO

TE-Cy-CO

BT-CA-585-1

BT-CA-585-2

BT-CA-585-3

DFB-CA-585

DFB-SO-585

Cycl-63 39.3/ID-585 60.7

Cycl-63 39.3/Fuel-44 60.7

Cycl-63 16.67/ID-585 50/Sun-6N 33.33

Cycl-63 16.67/ID-585 50/Soy-oil 33.33

Cycl-63 16.67/ID-585 50/Can-oil 33.33

Cycl-63 16.67/ID-585 50/Corn-oil33.33

ID-585 70/Sun-6N 30

ID-585 60/Sun-6N 40

ID-585 50/Sun-6N 50

ID-585 40/Sun-6N 60

ID-585 25/Sun-6N 75

ID-585 15/Sun-6N 85

Perm 4 / Cycl-63 96

Perm 8 / Cycl-63 92

Perm 4/Cycl-63 36 / ID-585 60

Perm 8/Cycl-63 56 / ID-585 36

TE-tech 5/Cycl-63 45 / Sun-6N 50

TE-tech 5/Cycl-63 55/Can-oil 40

TE-tech 10/Cycl-63 35 / Soy-oil 55

TE-tech 10/Cycl-63 50/Corn-oil 40

BTK 20/Can-oil 50/ID-585 30



DFB 4 / Can-oil 80 / ID-585 16

DFB 4 / Soy-oil 80 / ID-585 16

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118 SUNDARAM

with three hydroxylic co-solvents (methanol, ethanol and 1 -propanol) at different

proportions from 1.0 to 10% w/w, and their evaporation characteristics were

also investigated (Tables 3 and 4) to understand the adjuvant/co-solvent

interactions.

The method, in brief, involved the use of a Whatman No. 1 filter paper

mounted on four pins which were fixed to a circular polyurethane sponge glued

to a plastic sheet. This assembly was placed on the pan of a Mettler balance

of sensitivity 0.0001 g, in an environmental chamber maintained at 20 ± 1°C,

and at 70 ± 3% relative humidity (RH). A100-^L aliquot of each test liquid was

pipetted out onto the filter paper, and the doors of the balance were left open

to allow air circulation. Residual weights were recorded at different intervals of

time up to 180 min after the initial weighing. The results were converted into

percentage weight of the liquid film remaining at each interval of time, and are

presented in Tables 3 to 6.

In the previous study (Sundaram, 1985), the residual weight (%) at

different intervals up to 180 min were fitted into an exponential equation (1):

Y = A + B e~ k t (1)

where constant 'A' represents the nonvolatile components, and 'B,' the volatile

components, thus providing A + B for the entire amount. Constant 'k'

represents the rate constant. However, this type of data treatment provides

information on the overall evaporation behaviour of test liquids, but not during

the initial stages of evaporation. Nonaqueous spray droplets rarely evaporate

to the maximum extent under field conditions, and therefore, the initial

evaporation rates would play a more important role than those at the later

stages. In the present study, the residual weight (%) obtained during the first

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TABLE 3. Linear ievaporate,

regression equations, physical properties, Ty , the time for 50% of the volatile components toate, and mean loss of mass per min from the filter paper O

cn3Percentage Linear regression equation R

composition Y = (A + B)

Triton X-114 : MeOH (Data were0 : 100 Y = 90.3 -1 : 99 Y = 92.7 -3 : 97 Y = 92.1 -5 : 95 Y = 92.3 -7 :93 Y = 92.4 -

10 : 90 Y = 92.5 -Triton X-114: EtOH (Data were <

0 : 100 Y = 90.6 -1 : 99 Y = 88.2 -3 : 97 Y = 89.9 -5 : 95 Y = 89.9 -7 :93 Y = 91.0 -

10:90 Y = 91.6 -Triton X-114 : PrOH (Data were i

0 : 100 Y = 94.2 -1 : 99 Y = 95.7 -3 : 97 Y = 95.8 -5 :95 Y = 95.2 -7 : 93 Y = 97.1 -

10 : 90 Y = 95.2 -

- C t

obtained31.8 t23.9 t23.5 t22.9 t22.1 t20.9 t

obtained25.2 t22.3 t21.6 t20.6 t20.1 t18.7 t

attained25.3 t16.3 t14.6 t14.7 t14.2 t13.7 t

(%)

during the92.495.894.894.794.193.6

during the92.690.992.192.092.493.0

during the97.198.898.798.899.498.1

Viscosity(mPa.s)

! initial 4 mir0.6120.6470.6950.7410.7980.883

initial 4 min1.261.361.391.491.591.77

initial 6 min2.262.302.552.622.883.17

Surfacetension(mN/m)

I because22.322.422.422.522.622.6

because22.322.322.322.322.422.4

because22.622.622.722.722.822.8

Evap. Non-volatiles T,Aratea (w/w%) (min)

Loss of massper min (mg)

within this time the evaporation was complete)31.823.923.522.922.120.9

within this time25.222.321.620.620.118.7

within this time25.316.314.614.714.213.7

0.002.746.7310.513.719.1

1.572.031.981.951.951.94

32.828.127.326.425.123.2

the evaporation was complete)0.002.484.317.4811.614.5

1.982.182.222.242.202.28

28.726.425.825.3,24.823.6

the evaporation was complete)0.001.164.327.179.4012.5

1.983.043.283.163.203.16

24.013.212.512.411.511.2

RTI1to

oZo>

IGO

15cn

a: Evaporation rates are expressed in percentage decrease of weight of the liquid film per min.Dow

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TABLE 4. Linear regression equations, physical properties, Ty , the time for 50% of the volatile components toevaporate, and mean loss of mass per min from the filter paper

Percentage Linear regression equation R2 Viscosity Surface Evap. Non-volatiles T1/2 Loss of masscomposition Y = (A + B) - C t (%) (mPa.s) tension ratea (w/w%) (min) per min (mg)

(mN/m)

Glycerol: MeOH (Data were obtained during the initial 4 min because within this time the evaporation was complete)0 : 1001 : 993 : 975:957 :93

10: 90Glycerol: EtOH

0 : 1001 :993 :975:957:93

10: 90Glycerol: PrOH

0: 1001 :993 :975:957 : 93

10:90

Y = 90.3Y = 97.3Y =. 96.3Y = 95.5Y = 95.8Y = 96.7

- 31.8 t- 21.6 t- 20.7 t- 19.9 t- 19.5 t- 18.9 t

(Data were obtained duringY = 90.6Y = 98.1Y = 97.2Y = 97.7Y = 96.8Y = 96.4

- 25.2 t- 17.9 t- 17.3 t- 16.6 t- 15.6 t- 14.7 t

(Data were obtained duringY = 94.2Y = 96.3Y = 95.2Y = 96.2Y = 95.4Y = 96.8

- 25.3 t- 15.5 t- 15.4 t- 14.5 t- 14.3 t- 13.1 t

92.499.499.098.698.798.7

the initial92.699.698.999.799.298.8

the initial97.198.998.499.198.799.3

0.6120.6390.7060.7830.8991.05

22.322.422.723.023.423.7

31.821.620.719.919.518.9

4 min because within this time1.261.281.431.591.731.94

22.322.322.622.823.123.5

25.217.917.316.615.614.7

6 min because within this time2.262.482.813.164.384.47

22.623.223.423.723.823.8

25.315.515.414.514.313.1

0.001.815.148.3011.816.8

the evaporation0.001.294.827.9011.2.16.4

the evaporation0.001.415.178.2211.116.2

1.572.282.302.302.262.20was1.982.762.762.782.842.84was1.983.183.083.163.103.20

32.819.719.519.4 -19.319.2

complete)28.715.615.414.714.614.3

complete)24.014.013.713.413.112.7

G

D>

a: Evaporation rates are expressed in percentage decrease of weight of the liquid film per min.

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TABLE 5. Linear regression equations, physical properties, T^ , the time for 50% of the volatile components toevaporate, and mean loss of mass per min averaged over the initial 10 min of evaporation

Liquidabbreviation

Ex-D°ID-585Fuel-44Aro-3470C-6N-585C-SO-585C-CA-585C-CO-585585-6N-30585-6N-40585-6N-50585-6N-60585-6N-75585-6N-85

Linear regression equationY = (A + B) - C t

Y = 89.2Y = 98.7Y = 100Y = 100Y = 98.9Y = 99.5Y = 99.7Y = 98.7Y = 99.4Y = 99.4Y = 99.4Y = 99.2Y = 99.7Y = 99.8

3.98 t1.56 t1.33 t1.23 t1.59 t1.56 t1.45 t1.68 t0.862 t0.802 t0.718 t0.607 t0.361 t0.245 t

R2 Viscosity Surface(mPa.s) tension

(mN/m)

91.997.299.010098.198.299.796.597.096.097.088.494.898.1

Evap. Non-volatilesratea

1.002.782.312.123.375.465.105.285.446.338.1011.517.922.4

27.329.830.035.231.330.032.532.729.429.629.930.130.931.5

3.981.561.331.231.591.561.451.680.860,800.720.600.360.25

0.0011.537.515.038.038.039.039.038.849.259.469.081.489.4

(min)

12.628.423.534.619.519.921.018.235.631.828.225.825.821.2


2.442.092.101.901.801.671.551.651.631.401.300.930.620.45

1I

O

z(Z>W

§en

a:b:

Evaporation rates are expressed in percentage decrease of weight of the liquid film per min.Ex-D evaporated completely in 5 min, and therefore, the loss of mass per min was averaged over the initial 5 min.D

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TABLE 6. Linear regression equations, physical properties, Ty , the time for 50% of the volatile components toevaporate, and loss of mass per min averaged over the initial 10 min of evaporation

Liquidabbreviation

CID-585C-Fuel-44PCy-1PCy-2PCy-585-1PCy-585-2TE-Cy-6NTE-Cy-CATE-Cy-SOTE-Cy-COBT-CA-585-1BT-CA-585-2BT-CA-585-3DFB-CA-585DFB-SO-585

LinearY =

Y =Y =Y =Y =Y =Y =Y =Y =Y =Y —

Y =Y =

Y =Y =Y =

regression equation(A +

98.8 •

99.2 •

99.8 •97.5 •

98.6 •

97.4 •10198.8 •

99.4 •

98.8 •

99.3 •

99.8 •99.8 •

99.8 •

100

B) - C t

- 2.45 t- 1.65 t- 2.42 t- 3.41 t- 2.19 t- 2.19 t- 2.20 t- 2.08 t- 1.69 t- 1.41 t- 1.17 t- 0.71 t- 0.58 t- 0.77 t- 0.54 t

R2

(%)

98.598.999.796.497.994.599.798.798.596.696.099.498.597.598.6

Viscosity(mPa.s)

1.462.311.822.401.852.1819.922.823.226.232.939.744.140.037.8

Surfacetension(mISI/m)

29.930.029.031.527.227.927.530.531.732.533.033.734.034.234.5

Evap.ratea

2.451.652.423.412.192.192.202.081.691.411.170.710.580.770.54

Non-volatiles(w/w%)

8.0027.05.209.0512.214.557.047.067.054.075.582.693.787.688.3

(min)

18.822.119.613.320.019.59.8

12.79.8

16.310.512.35.48.1

10.8


2.511.502.522.422.302.211.301.350.801.100.400.360.140.300.25

a: Evaporation rates are expressed in percentage decrease of weight of the liquid film per min.

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ten min of evaporation was fitted into a linear regression equation (2):

Y = (A + B) - Ct (2)

where the constant 'C represents the slope, i.e., the percent decrease in

weight per min. The following relationships can be derived from equation (2):

Y = A when t = ° ° (3)

Y = A + B = 100, when t = 0 (4)

To obtain Ty , the half-life of evaporation, i.e., the time required for 50% of the

volatile portion to evaporate, equation (5) was used:

T1/2= (100-A)/2C (5)

A second method was also used for data treatment, to determine the

mean loss of mass per min (MLMPM), during the initial 10 min of evaporation.

The equation of the type,

- 1 " Mf 1 - M:MLMPM = \ (6)

n ho tj + 1 ~ tj

where M( = the mass of liquid film in the ith min,

(in the n min study, MQ Mf Mn)

and tj = the time at which Mf was measured, i.e., at the ith min.

(in the n min study, t0 tf tn)

For the insecticide formulations, diluent oils, oil mixtures and adjuvant/co-

solvent mixtures tested in this study, the Ty values, nonvolatile components

(NVC%) and the mean loss of mass per min (MLMPM) were calculated and

listed in Tables 3 to 6.

In a previous study, viscosities of nonaqueous pesticide formulations and

diluent oils showed an inverse relationship with their volatilities when the

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124 SUNDARAM

exponential equation (1) was used for data treatment (Sundaram, 1987).

Therefore, in the present study, the inter-relationship between viscosity and

volatility was investigated using equations (2) to (6) for data treatment. Viscosity

was measured using three different sizes of Cannon-Fenske [ASTM size 50

(capillary of 0.3 mm i.d.) for liquids of viscosity range of 0.5 to 2 mPa.s; size 100

(0.4 mm i.d.) for 2.0 to 15; size 150 (0.5 mm i.d.) for 7 to 35; and size 200 (0.6

mm i.d.) for 35 to 100 mPa.s] type of gravity flow viscometer (Anon., 1979;

Schramm, 1981). Surface tension was determined using the Surface Tensiomat

(Model 21, Fisher Scientific, Toronto, Ont., Canada). All measurements were

made in an environmental chamber maintained at 20 ± 1°C and 70 ± 3%

relative humidity (RH). The data are given in Tables 3 to 6.

RESULTS AND DISCUSSION

During the initial stages, all liquids evaporated according to a linear

relationship between the residual weight percent (Y) and time 't'. During the

second stage, however, a curvilinear decrease was noted in Y, and at the

final stage of evaporation, an asymptotic limit was obtained for all liquids tested.

These limiting values represented the nonvolatile components. Tables 3 to 6

present the linear relationships [equation (1)], the coefficients of determination

(R2%), evaporation rates (ER), nonvolatile components (NVC%), and Ty values,

along with the physical properties (viscosity, T), and surface tension, 7) and

the mean loss of mass per min (MLMPM).

To determine the relationships between physical properties and volatility

parameters, the liquids tested in this study were divided into two major

categories: (1) diluent oils, oil mixtures, and insecticide formulations; and (2)

adjuvant/co-solvent mixtures.

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1. Diluent Oils, Oil Mixtures and Insecticide Formulations

In general, when viscosity of these liquids increased gradually, the ly

values and the NVC% also increased correspondingly (Tables 5 and 6). Similar

trend was also noted with the surface tension values. To examine the

relationships among the physical properties and volatility parameters, four plots

were constructed, two for the diluent oils and their mixtures (Figures 1 and 2),

and the other two for the insecticide spray mixtures (Figures 3 and 4). Figures

1 and 3 present the plots of viscosity versus evaporation rate, percent nonvolatile

components, half-life of evaporation and the mass of liquid lost per min, along

with the correlation coefficients between r\ and volatility parameters. Figures 2

and 4 present similar plots for surface tension versus the volatility parameters.

Based on the type of plots and correlation coefficients obtained (Figures 1

to 4), the liquids belonging to this category can be further divided into two

groups: (i) diluent oils and their mixtures, and (ii) insecticide formulations,

i. Diluent oils and oil mixtures

The plots for diluent oils and their mixtures (Figures 1 and 2) indicated that

viscosity (T|) was inversely correlated with the evaporation rate (ER) and the

mean loss of mass per min (MLMPM), but showed a direct correlation with the

nonvolatile components percent (NVC%) (Figure 1). Correlation was, however,

poor between viscosity and ly values. Correlation was consistently poor

between surface tension and any of the four volatility parameters (Figure 2). The

numerical value of the correlation coefficient (referred to as \'f\ in this paper)

between i] and EB (0.683) was lower than those (0.912) between r\ and NVC%,

or MLMPM (Figure 1). The obvious reason is that viscosities of liquids are

affected by the concentrations of nonvolatile components present in the residual

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126 SUNDARAM

A- -

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'r' = 0.912

DD 'r1 = 0.077

D• a

•r1 = - 0.912

" • " ' •»• .

i i i i

10 15

Viscosity (mPa.s)

20 25

Figure 1. Viscosity vs evaporation rate, percent

nonvolatiles, half—life and mass lost/min for

diluent—oil mixtures

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4.5

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26 28 30 32 34 36Surface tension (mN/m)

Figure 2. Surface tension vs evaporation rate,

nonvolatiles (%), half—life and mass lost/min

for diluent—oil mixtures

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128 SUNDARAM

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° o

.805

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.983

1 1 1

0.907

- o

a

10 20 30 40 50

Viscosity (mPa.s)

Figure 3. Viscosity vs evaporation rate, percent

nonvolatiles, half—life and mass lost/min

for insecticide spray mixtures

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26 28 30 32 34

Surface tension (mN/m)

36

Figure 4. Surface tension vs evaporation rate,

nonvolatiles (%), half—life and mass lost/min

for insecticide spray mixtures

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130 SUNDARAM

film, and also by the amount of volatile components lost, an observation in

agreement with that of Sundaram and Leung (1986) and Sundaram (1987).

ii. Insecticide formulations

Similar to the plots of diluent oils and their mixtures, those of insecticide

formulations (Figures 3 and 4) indicated that viscosity (TJ) was inversely

correlated with the ER and MLMPM, but showed a direct correlation with the

NVC% (Figure 3). The |Y | values ranged from 0.805 to 0.983. Good correlation

(inverse) was also found between viscosity and ly (Y = - 0.805), an observation

in contrast to the finding on diluent oils and their mixtures [with an Y value of

0.077 (Figure 1)]. Correlation was also moderate between surface tension and

all of the four volatility parameters (Figure 4), because the |Y| values ranged

from 0.663 to 0.809. The correlation coefficient between f\ and ER (- 0.907) was,

again, lower than those (+ 0.983) between r\ and NVC%, or MLMPM, obviously

for the reasons described above.

In general, the correlation coefficients for the diluent oils and oil mixtures

were lower than those for the insecticide formulations. For example, the |Y|

value between T| and ER was 0.683 for the oil mixtures, but was 0.907 for the

insecticide formulations. Similarly, the |Y| value between TI and

NVC%, and Tl and MLMPM, was 0.912 for the oil mixtures, but was greater

(0.983) for the insecticide formulations. Also, the |Y| values

between T| and ly was 0.077 for the oil mixtures, but was 0.805 for the

insecticide formulations, thus indicating a consistently better correlation for the

insecticide formulations than for the diluent oils and their mixtures.

Similar trend was noted between surface tension (y) and the volatility

parameters. For example, the plots of y versus ER, NVC%, ly, or MLMPM

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(Figure 2) indicate very poor relationship for the oil mixtures, but the

corresponding plots for the insecticide formulations (Figure 4) showed a slightly

better relationship, although the Y values were still lower than the

corresponding values for the viscosity plots (Figures 1 and 3).

2. Adjuvant/Co-solvent Mixtures

a. Inter-relationships between physical properties and volatility parameters

Figures 5 to 7 present relationships between viscosity and volatility

parameters for the adjuvant/co-solvent mixtures. Because the surface tension

values showed little variation among the different mixtures, similar plots were not

provided for the relationships involving surface tensions.

For the Triton X-114 mixtures with methanol and ethanol co-solvents (Figure

5), the plots of r\ versus ER and MLMPM showed inverse correlation, whereas

those of T| versus NVC% showed a direct correlation. The |Y| values were

high, ranging from 0.985 to 0.998. However, the plot of r\ versus ly

was inverse for the Triton/methanol mixtures but was direct for the Triton/ethanol

mixtures, the reason for which is unclear. For the glycerol mixtures with methanol

and ethanol, the plots of r\ versus the volatility parameters were similar to those

of the Triton/methanol and Triton/ethanol mixtures, with the \'f\

values ranging from 0.861 to 0.999 (Figure 6). Also, for the

Triton/propanol and glycerol/propanol mixtures, the plots of T)

versus ER, MLMPM and NVC% were similar (Figure 7) to those of the

corresponding methanol and ethanol mixtures (Figures 5 and 6), but the plots of

T] versus ly showed very poor correlation with low Y values (0.321 for

Triton/propanol and 0.093 for glycerol/propanol mixtures) (Figure 7). The reason

for this is not clear.

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132 SUNDARAM

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0.60 0.75 0.90Viscosity (mPa.s)

1.35 1.50 1.65 1.80

Viscosity (mPa.s)

Figure 5. Viscosity versus volatility parameters

for various mixtures of Triton X—114 and

methanol (a to d), and Triton X —114 and

ethanol (e to h)

b. Adjuvant/co-solvent interactions and their effect on volatility parameters

The effect of adjuvant concentrations on the four volatility parameters , ER,

NVC%, Ty and MLMPM is presented in Tables 3 and 4. The data indicate that

when the adjuvant concentration increased gradually from 1 to 10% (w/w), the

ER values showed a progressive decrease indicating that the rate at which the

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Viscosity (mPa.s)


for various glycerol/methanol mixtures

(a to d), and glycerol/ethanol mixtures

(e to h)

co-solvent molecules escape into the ambient air is influenced by the

concentration of the adjuvant. This trend was noted with both Triton X-114 and

glycerol mixtures. The data indicate a gradual increase in interactive forces

between adjuvant and co-solvent molecules when adjuvant concentrations

increased. This finding is further substantiated by the NVC% values. For

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134 SUNDARAM

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2.1 2.B 3.5 4.2Viscosity (mPa.s)


for various Triton X— 11 4/propanol mix-

tures (a to d), and glycerol/propanol

mixtures (e to h)

example, the nonvolatile components in the various mixtures should theoretically

be 1.0 to 10.0 when the adjuvant concentrations increased from 1.0 to 10%,

because the co-solvents would theoretically volatilize completely, leaving Triton

X-114 or glycerol molecules behind which are nonvolatile. However, the data in

Tables 3 and 4 indicate consistently higher NVC% than the theoretical values.

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This behaviour is due to inter-molecular interactions between the adjuvant and

co-solvent molecules, making it difficult for the co-solvent molecules to escape

into the ambient air. The higher the adjuvant proportion, the greater the

interaction, and the greater the difficulty for the co-solvent molecules to escape.

This phenomenon could have contributed to the gradual increase in the

measured NVC%, when adjuvant levels increased progressively.

The role of co-solvent type on the ER values is evident in Tables 3 and 4.

Adjuvant mixtures containing MeOH evaporated faster than those of EtOH, which

in turn evaporated faster than those of PrOH. This is understandable because the

boiling points (b.p.) of the co-solvents increase in the order of MeOH < EtOH <

PrOH (Sundaram and Leung, 1986), and consequently, their rates of evaporation

are expected to decrease in the order of MeOH > EtOH > PrOH, because of the

inverse relationships between ER and boiling points.

Table 7 presents information on the relationships between ANVC%

(i.e..observed NVC% minus theoretical values) and adjuvant concentrations in the

Triton X-114 and glycerol mixtures. The data indicate that at low Triton X-114

levels from 1 to 3%, the ANVC% values were somewhat similar for the three co-

solvents, MeOH, EtOH and PrOH. However, when the adjuvant levels increased

from 5 to 10%, the increase in ANVC% values was the highest for MeOH,

moderate for EtOH, and was the least for PrOH. The data thus indicate that

Triton X-114 interacted the most with MeOH and the least with the PrOH. This

is further demonstrated in the slopes of the linear regression equations (Table 7)

constructed between the observed ANVC% and adjuvant concentration. The

slope was the highest (0.802) for the MeOH mixtures, lower (0.426) for the EtOH

mixtures, and least (0.252) for the PrOH mixtures. The reason is that Triton X-

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136 SUNDARAM

Table 7. Linear regression equations for the relationships between ANVC%(observed minus theoretical) and the amount of adjuvants present inthe adjuvant/co-solvent mixtures

Percentagecomposition

ANVC% Linear regression equationY = P + Q X

Coeff. ofdeter. (R2)

Triton X-114 : MeOH mixtures1357

10

Triton

: 99: 97: 95: 93: 90

X-114:

1.743.735.506.709.10

EtOH mixtures

ANVC% = 1.18+ 0.802 adjuv. concn. 0.994

1357

10

Triton1357

10

X

9997959390

-114:9997959390

1.481.312.484.604.50

PrOH mixtures0.161.322.172.402.50

ANVC% = 0.712 + 0.416 adjuv. concn. 0.829

ANVC% = 0.398 + 0.252 adjuv. concn. 0.803

Glvcerol : MeOH mixtures1357

10

9997959390

Glycerol : EtOH1357

10

9997959390

Glvcerol : PrOH1357

10

9997959390

0.812.143.30 A4.806.80

mixtures0.291.822.90 A4.206.40

mixtures0.412.173.22 A4.106.20

ANVC% = 0.106 + 0.666 adjuv. concn. 0.999

ANVC% = 0.339 + 0.666 adjuv. concn. 0.997

ANVC% = 0.023 + 0.615 adjuv. concn. 0.989

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114 is a polymeric molecule (octylphenoxypolyethoxyethanol) with an average

MW of 536, and the co-solvents have the MWs of 32, 46 and 60 for MeOH,

EtOH, and PrOH respectively. As a result, the dipole-dipole interactions and

hydrogen bonding would be the strongest for MeOH, less strong for EtOH and

the least for PrOH.

In the case of glycerol/co-solvent mixtures, however, such a difference in the

slopes of the equations were not evident, because the slopes were similar for the

three co-solvents, ranging from 0.615 to 0.666 only. The data thus indicate

similar inter-intermolecular interactions occurring between glycerol and any of the

co-solvent molecules, an observation in contrast with the one found in Triton X-

114/co-solvent mixtures. The reason is that glycerol contains three hydroxyl

groups and is also a smaller molecule (MW 92) than Triton X-114. These

properties contribute to strong hydrogen bonding between Triton X-114 and the

three hydroxylic co-solvent molecules, regardless of the co-solvent type or their

molecular weights.

CONCLUSIONS

The present study indicated that between the two physical properties

investigated, viscosity (r\) showed a better correlation with volatility than surface

tension. Correlation was even better between t| and nonvolatile components

(MVC%), than between r[ and evaporation rate (ER) or half-life of evaporation

{Ty). Correlation between T) and NVC% was far better for the insecticide

formulations than for the diluent oils, oil mixtures and adjuvant/co-solvent

mixtures. The present study also provided a new method to determine a novel

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138 SUNDARAM

volatility parameter, mean loss of mass of per min (MLMPM), which also showed

a good correlation with viscosity, similar to that between NVC% and viscosity.

The investigation on adjuvant/co-solvent interactions indicated that the rates

of evaporation decreased when adjuvant concentration increased in the mixtures,

thus indicating that the co-solvent molecules found it increasingly difficult to

escape into ambient air when the adjuvant concentration increased. The

observed NVC% values were consistently higher than the theoretical ones,

indicating strong inter-molecular interactions between the adjuvants and co-

solvents. Triton X-114 being a long polymeric molecule, the inter-molecular

interactions were the highest for MeOH, lower for EtOH and the least for PrOH.

However, such differences in inter-molecular interactions were not observed

between glycerol (a smaller molecule with three OH groups) and the co-solvents.

REFERENCES

Amsden, R.C., Agric. Aviat., 4, 88-93 (1962).

Anon., "Measurement Services - Viscosity," Department of Industry, NationalPhysical Laboratory, Middlesex TW110LW, England, 1979, 26 pp.

Maas, W., "ULV Application and Formulation Techniques," Philips-Duphar B.V.,Crop Protection Division, Amsterdam, The Netherlands, 1971, 164 pp.

Matthews, G.A., "Pesticide Application Methods," Longman Inc., New York, 1979,336 pp.

Schramm, G., "Introduction to Practical Viscometry," Gebruder HAAKE GmbH,D-7500 Karlsruhe 41, Dieselstrasse 4, West Germany, 1981, 119 pp.

Sundaram, A., Pestic. Sci., 16, 397-403 (1985).

Sundaram, A. and Leung, J.W., J. Environ. Sci. Health, B21, 165-190 (1986).

Sundaram, A., Pestic. Sci., 20, 105-118 (1987).

Received: August 26, 1994

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physical properties and evaporation characteristics of nonaqueous insecticide formulations, spray...

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