Department of Pesticide Regulation 

Paul E. Helliker, Director 

830 K Street l Sacramento, California 95814-3510 l www.cdpr.ca.gov 

PtY+XliOll MEMORANDUM 

TO: Randy Segawa, Senior Environmental Research Scientist 

Environmental Monitoring and 

Pest Management Branch 

FROM: Terri Barry, Senior Environmental Research 

Environmental Monitoring and 

Pest Management Branch 

(916) 324-4140 

DATE: December 2,1999 

SUBJECT: METHYL BROMIDE EMISSION RATIO GROUPINGS 

This memorandum describes the procedures used to group the Methyl Bromide application 

types, Each application type is assigned the mean emission ratio from the appropriate group. 

The group mean emission ratio, together with the size of the application, determines the buffer 

zone length for a particular permitted application. 

Materials and Methods 

Physical characteristics of the application methods were initially used to assign each application 

method to a group. The initial groupings were as follows: 1) broadcast/tarp/deep, 

2) broadcast/tarp/shallow, 3) broadcast/non-tarp/deep, 4) broadcast/non-tarp/shallow, 

5) bed/tarp/shallow, 6) hot-gas. This initial grouping resulted in several empty cells for all 

possible combinations of factors. For example, there are no bed/tarp/deep applications. 

Therefore, the initial analysis to investigate the effect of tarping and/or depth of injection on the 

emission ratio value was conducted only on broadcast application types. All analysis was 

conducted on both the unadjusted and the adjusted for 50% recovery emission ratios. 

Further grouping was based upon both physical characteristics of the application methods and 

the results from the statistical analysis of the broadcast application types. The application types 

represented in the monitoring data set were grouped into four types: 1) broadcast/non-tarp, 

2) broadcast/tarp, 3) bed/tarp, and 4) hot gas. Due to risk management concerns about high air 

concentrations associated with hot gas, the emission ratio for this method remains at 1 .O and this 

method was eliminated from further analysis. 

MINITAB statistical software, Release 12, was used for all analysis and graphical presentations 

(Minitab Inc., 1997). One and two-way analysis of variance (ANOVA) were used to perform the 

data analysis. The Anderson-Darling test for normality and Levene’s test for homogeneity of 

variance were used to screen for violations of the assumptions of ANOVA (Minitab Inc., 1997). 

When required, transformation techniques were employed. Mean separation was accomplished 

using Fisher’s pairwise comparison procedure. 

California Environmental Protection Agency 

Q winled an RCCY&d Papr 
Randy Segawa 

December2,1999 

Page 2 

Results and Discussion 

Broadcast Application Types. Results of analysis on the broadcast application types are shown 

in Tables 1 through 3 and Figures 1 and 2. Results from the statistical tests to detect violations 

of the assumptions of ANOVA are shown in Table 1. For both the unadjusted and the recovery 

adjusted emission ratios, the data met both the normality (A-squared=0.201, p=O.865, and 

A-squared=O. 192, p=O.885, respectively) and the homogeneity of variance assumptions 

(Levene’s Test Statistic=1.017, p=O.381, and Levene’s Test Statistic=1.031, p=O.377, 

respectively). The two-way ANOVA for both the unadjusted emission ratios and the recovery 

adjusted emission ratios (Tables 2 and 3, respectively) show no interaction between the factors 

tarp and depth of injection (Ft,ts=0.30, p=O.590, and F r,ts=O.30, p=O.590, respectively). 

Therefore, the effects of tarping and depth of injection may be interpreted separately. For both 

unadjusted and recovery adjusted emission ratios, there is a significant effect due to tarp 

(Ft,rs=6.32, p=O.O22, and Ft,ts=6.31, p=O.O22, respectively) but no significant effect due to depth 

of injection (Ft,ts=2.55, p=O.128, and F t,ts=2.57, p=O.126, respectively). Figures 1 and 2 clearly 

show the significant effect due to tarp and the non-significant effect due to depth of injection for 

both unadjusted and recovery adjusted emission ratios. For the unadjusted emission ratios, the 

mean for non-tarped applications is 0.19, while the mean for tarped applications is 0.12. The 

mean for shallow injections is 0.143, while the mean for deep injections is 0.145. For the 

recovery adjusted emission ratios, the mean for non-tarped applications is 0.37, while the mean 

for tarped applications is 0.24. The mean for shallow injections is 0.287, while the mean for 

deep injections is 0.290. These results indicate that for both the unadjusted and the recovery 

adjusted emission ratios, for the broadcast applications, there are only two distinguishable 

groups: non-tarp and tarp. 

Broadcast and Bed Application Types. One-way ANOVA was conducted on the single factor 

of application type. The application types included were: 1)~ broadcast/non-tarp, 2) broadcast/ 

tarp, and 3) bed/tarp. Before the one-way ANOVA was conducted, the data was examined for 

violations of the assumptions of ANOVA. The results of that analysis are shown in Table 4. 

The Anderson-Darling Test indicates that, for both the unadjusted and the recovery adjusted 

emission ratios, the raw data violate the assumption of normality (A-squared=l.304, p=O.O02, 

and A-squared=1 .164, p=O.O04, respectively). However, for both the unadjusted and the 

recovery adjusted emission ratios, Levene’s Test indicates that the data do not violate the 

assumption of homogeneity of variance between groups (Levene’s Test Statistic=l.553, p=O.229, 

and Levene’s Test Statistic=0.648, p=O.53 1, respectively). The results in Table 5 show that for 

both the unadjusted and the recovery adjusted emission ratios, a logto transformation corrected 

the violation of the normality assumption (A-squared=0.381, p=O.379, and A-squared=0.485, 

p=O.211, respectively) and maintained homogeneous variances between groups (Levene’s Test 

Statistic=O.OllO, p=O.933, and Levene’s Test Statistic=0.105, p=O.900, respectively). 
Randy Segawa 

December 2, 1999 

Page 3 

The one-way ANOVA was conducted on both the raw emission ratios and the log,, transformed 

data. For both the unadjusted and the recovery adjusted emission ratios, the results obtained 

from both analysis were consistent. For simplicity, only results from analysis of the raw 

emission ratios are presented. Results from the one-way ANOVA on the raw emission ratios are 

shown in Tables 6 and 7. For both the unadjusted and the recovery adjusted emission ratios there 

is a significant difference between application types (F?,zs=21.81, p=O.OOO, and Fs,*s=21.26, 

p=O.OOO, respectively). Further, the Fisher’s pairwise comparison (p=O.O5) indicates that 

bed/tarp application type is significantly different from both the broadcast/non-tarp and the 

broadcast/tarp. Figures 3 and 4 show the main effects means for application type. These figures 

clearly show the difference between the bed/tarp and the two broadcast application types. For 

the unadjusted emission ratios, the mean for broadcast/non-tarp is 0.19, the mean for 

broadcast/tarp is 0.12, while the mean for bed/tarp is 0.43. ‘For the recovery adjusted emission 

ratios, the mean for broadcast/non-tarp is 0.24, the mean for broadcast/tarp is 0.37, while the 

mean for bed/tarp is 0.8 1. 

Conclusions 

Based upon the analysis discussed above, and the risk management decision to separate the hot 

gas method, the application types separate into four distinguishable groups. These groups are: 

1) broadcast/non-tarp, 2) broadcastitarp, 3) bed/tarp, and 4) hot gas. The mean unadjusted 

emission ratios and recovery adjusted emission ratios and their respective standard deviations 

and coefficients of variation (CV), for the four groups are shown in Table 8. Box-plots of the 

final groupings are shown in Figures 5 and 6. 
Randy Segawa 

December 2,1999 

Page 4 

References 

Minitab Inc. 1997. User’s Guide 2: Data analysis and quality tools. Release 12. Minitab 

statistical software 
Randy Segawa 

December 2, 1999 

Page 5 

Table 1. Results of tests for the violation of assumptions of ANOVA, broadcast application 

types only. 

Normality Homogeneity of Variance 

Anderson-Darling Test Levene’s Test 

unadjusted 

emission ratio 

Test Statistic 

0.201 

p-value 

0.865 

Test Statistic 

1.017 

p-value 

0.381 

adjusted 

emission ratio 

0.192 0.885 1.031 0.377 

Table 2. ANOVA results for unadjusted emission ratios broadcast application types only. 

Source 

tarp 

depth 

tarp*depth 

error 

total 

DF 

1 

1 

1 

18 

21 

Adj. MS F-ratio p-value 

0.0331 

0.0133 

0.0016 

0.0052 

6.32 0.022 

2.55 0.128 

0.30 0.590 

Table 3. ANOVA results for recovery adjusted emission ratios, broadcast application types only. 

Seq. SS 

0.0909 

0.0473 

0.0063 

0.3762 

0.5208 

p-value 

0.022 

Adj. SS Adj. MS F-ratio 

0.1318 0.1318 I- 6.31 

0.0537 0.0537 2.57 0.126 

0.0063 0.0063 0.30 0.590 

0.3762 0.0209 
Randy Segawa 

December 2, 1999 

Page 6 

Table 4. Results of tests for the violation of assumptions of ANOVA, broadcast and bed 

application types only. 

Normality Homogeneity of Variance 

Anderson-Darling Test Levene’s Test 

Test Statistic p-value Test Statistic p-value 

unadjusted 

emission ratio 

1.304 0.002 1.553 0.229 

adjusted 

emission ratio 

1.164 0.004 0.648 0.531 

Table 5. Results of tests for the violation of assumptions of ANOVA on logrc transformed data, 

broadcast and bed application types only. 

Normality Homogeneity of Variance 

Anderson-Darling Test Levene’s Test 

unadjusted 

emission ratio 

Test Statistic p-value Test Statistic p-value 

0.381 0.379 0.070 0.933 

adjusted 

emission ratio 

0.485 0.211 0.105 0.900 
Randy Segawa 

December 2, 1999 

Page 7 

Table 6. ANOVA results for unadjusted emission ratios, broadcast and bed application types 

only. 

0.5509 

0.3536 

0.9045 

MS 

0.2755 

0.0126 

F-ratio p-value 

21.81 0.000 

Table 7. ANOVA results for recovery adjusted emission ratios, broadcast and bed application 

types only. 

Source 

aw. We 

r 

error 

total 

DF ss 

2 1.8102 

28 1.1920 

30 3.0022 

MS 

0.9051 

0.0426 

F-ratio 

21.26 

p-value 

0.000 

i 

Table 8. Summary table of unadjusted emission ratios and recovery adjusted emission ratios for 

broadcast and bed application types only. 

Unadjusted emission ratio recovery adjusted emission ratio 

n em. ratio st. dev. cv em. ratio st. dev. cv 

broadcast/ 8 0.19 0.087 46% 0.37 0.174 47% 

non-tarp 

broadcast/ 14 0.12 0.065 54% 0.24 0.129 52% 

tarp 

bed/tarp 9 0.43 0.175 41% 0.81 0.309 38% 
Randy Segawa 

December 2, 1999 

Page 8 

Figure 1. Main effects plots for the unadjusted emission ratios. Data shown are treatment 

means. For tarp code, non-tarp = 0, tarp = 1. For depth code, shallow = 0, deep = 1. 

Main Effects Plot - Data Means for unadj em ratio 
/ 

Randy Segawa 

December 2, 1999 

Page 9 

Figure 2. Main effects plots for the recovery adjusted emission ratios. Data shown are treatment 

means. For tarp code, non-tarp = 0, tarp = 1. For depth code, shallow = 0, deep = 1. 

Main Effects Plot - Data Means for adj em ratio 

tarp code depth code 
Randy Segawa 

December 2, 1999 

Page 10 

Figure 3. Main effects plots for the unadjusted emission ratios. Data shown are treatment 

means. For app. code, broadcast/non-tarp = 0, broadcast/tarp = 1, bed/tarp = 2. 

Main Effects Plot - Data Means for unadj em ratio 

, 

0 

, 

1 

wp. We 

2 
Randy Segawa 

December 2, 1999 

Page 11 

Figure 4. Main effects plots for the adjusted emission ratios. Data shown are treatment means, 

For app. code, broadcast/non-tarp = 0, broadcast/tarp = 1, bed/tarp = 2. 

Main Effects Plot - Data Means for adj em ratio 
Randy Segawa 

December 2, 1999 

Page 12 

Figure 5. Box-plot of the final groupings of application types for unadjusted emission ratios. 

For app. code, broadcast/non-tarp = 0, broadcast/tarp = 1, bed/tarp = 2, hot gas = 3. 

Boxplots of unadj em by app. type 

(means am indicated by solid circles) 
. . . 

Randy Segawa 

December 2, 1999 

Page 13 

Figure 6. Box-plot of the final groupings of application types for recovery adjusted emission 

ratios. For app. code, broadcast/non-tarp = 0, broadcast/tarp = 1, bed/tarp = 2, hot gas = 3. 

Boxplots of adj em ratio by app. type 

(means are indicated by solid circles)