RESEARCH TRIANGLE INSTITUTE
July 1986 RTI/2270/03-01F
PESTICIDE USAGE SURVEY OF HORTICULTURAL SPECIALTIES PRODUCERS
by
Robert M. Lucas
Frederick W. Immerman
and
Shelton M. Jones
Research Triangle Institute
Research Triangle Park, NC 27709
Contract No. 68-01-6646
Task Manager: Edward Brandt
Project Officer: Edward Brandt
Economic Analysis Branch
Benefits and Use Division
Office of Pesticide Programs
U.S. Environmental Protection Agency
401 M Street, SW
Washington, DC 20460
POST OFFICE BOX 12194 RESEARCH TRIANGLE PARK, N0RTHCAR0LINA 27709
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Disclaimer
This report was prepared under contract to an agency of
the United States Government. Neither the United States
Government nor any of Its employees, contractors,
subcontractors, or their employees makes any warranty,
expressed or Implied, or assumes any legal liability or
responsibility for any third party's use or the results
of such use of any information, apparatus, product, or
process disclosed in this report, or represents that its
use by such third party would not Infringe on privately
owned rights.
Publication of the data in this document does not
signify that the contents necessarily reflect the joint
or separate views and policies of each sponsoring
agency. Mention of trade names or commercial products
does not constitute endorsement or recommendation for
use.
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ACKNOWLEDGMENTS
The authors wish to thank and acknowledge the many persons who
contributed to the success of this project: the employees of the American
Association of Retired Persons, under the guidance of Ms. Norma Gillette,
for their essential contributions to planning and data collection
activities; Mr. Ray Brush of the American Association of Nurserymen for
sharing his expert knowledge in planning the study and review of results;
Mr. Edwin 0. Schneider for his assistance in resolving problems with
identifying products and active Ingredients; Ms. Linda Zarow and Mr. Edward
Brandt of the U.S. Environmental Protection Agency for their continued
support and patience throughout the conduct of the study; and staff of the
many horticultural establishments whose cooperation was critical to the
success of this study.
The authors also thank their many colleagues, too numerous to mention,
who contributed to this report.
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Table of Contents
Page
1. INTRODUCTION 1
1.1 Purpose 1
1.2 Overview and Limitations 1
2. SUMMARY OF RESULTS 10
2.1 Overvl ew 10
2.2 Summary of Pesticide Usage 11
2.3 Summary of Report Pest 17
2.4 Summary of Nursery Industry Characteristics 17
REFERENCES 45
APPENDIX A: Survey Design and Statistical Analysis A-l
APPENDIX B: National Nursery Pesticide Usage Survey
Questlonnal re B-l
APPENDIX C: User File Documentation C-l
APPENDIX D: Supplementary Pesticide Usage Information D-l
11
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List of Tables
Table Page
1.1 Comparison of Horticultural Establishments (HEs) 4
1.2 Summary of 1979 Census Counts and Survey Estimates 6
2.1 Pesticide Usage by Active Ingredient 14
2.2 Pesticide Usage by Active Ingredient and Class 15
2.3 Pesticide Usage by Active Ingredient, Class, and Census
Region 18
2.4 Pesticide Usage by Active Ingredient, Class and
Horticultural Site 20
2.5 Pesticide Usage and Number of Horticultural Establishments
(HEs) by Size 22
2.6 Pesticide Usage and Number of Horticultural Establishments
(HEs) by Size and Census Region 23
2.7 Pesticide Usage and Number of Horticultural Establishments
(HEs) by Size and Site 24
2.8 Frequency of Reported Target Pest by Horticultural Site.. 25
2.9 Frequency of Reported Target Pest by and Census Region... 26
2.10 Frequency of Reported Target Pest by Horticultural Site
and Census Region 27
2.11 Number of Horticultural Establishments (HEs) by Reported
Target Pest and Active Ingredient 29
2.12 Estimated Distribution of Horticultural Establishments
(HEs) by Type of Production/Activity 31
2.13 Estimated Distribution of Horticultural Establishments
(HEs) by Number of Locations 33
2.14 Number and Percent of Horticultural Establishments (HEs)
Using Chemical Pesticides by Census Region and Type of
Production/Activity 34
2.15 Number and Percent of Horticultural Establishments (HEs)
Applying Chemical Pesticides (Not Solely Using Contractors)
by Census Region and Type of Production/Activity 35
2.16 Number of Horticultural Establishments (HEs) Reporting
Side Effects Associated with Pesticide Use 36
111
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List of Tables
(continued)
Table Page
2.17 Number of Horticultural Establishments (HEs) Reporting
Side Effects by Pesticide Product 37
2.18 Number of Horticultural Establishments (HEs) by Amount
Spent on Pesticide Purchases 39
2.19 Number and Percent of Horticultural Establishments (HEs)
with Employees Certified to Apply Pesticides by Census
Region and Type of Production/Activity 40
2.20 Number and Percent of Horticultural Establishments (HEs)
Using Chemical and/or Integrated Pest Management (IPM)
Methods 41
2.21 Number of Pest Problems and Associated Dollar Loss by
Type of Pest 42
2.22 Pesticide Usage Compared to Previous Years 43
2.23 Number of Horticultural Establishments (HEs) That Used
Records to Answer Product Usage Questions by Census
Regi on 44
List of Figures
Figure Page
1 The Four Census Regions of the United States 12
1v
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1. INTRODUCTION
1.1 Purpose
The Pesticide Usage Survey of Horticultural Specialties Producers
(PUSHSP) is one of several nationwide surveys conducted by the U.S.
Environmental Protection Agency (EPA) to accurately collect data on
pesticide usage by various Industries and at different sites. The purpose
of the PUSHSP 1s to provide this quantitative pesticide usage data as Input
to EPA estimates of exposure, risks, and benefits.
Horticultural specialty producing establishments, Including
greenhouses, were selected as one sector for Investigation because they are
Important consumers of pesticides (e.g., 1nsect1c1des/m1t1c1des,
fungicides, herbicides and nematlddes). Also, they have a great potential
for economic loss due to the high cost value of the stock and the close
environment 1n which the stock are grown, creating a situation attractive
to pests.
The PUSHSP Involved a cooperative effort by the Research Triangle
Institute (RTI) and the American Association of Retired Persons (AARP).
RTI was responsible for survey design, sample selection, automated data
processing, and statistical data analysis. AARP was responsible for
questionnaire development, "field staff hiring and training, and
questionnaire administration. Data collection took place during the summer
of 1983 and represents Information for 1982.
1.2 Overview and Limitations
The target population for the PUSHSP consisted of all horticultural
establishments (HEs) in the 48 coterminous States and the District of
Columbia Involved in growing products belonging to the 13 commodity groups
1
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as defined in the 1979 Census of Horticulture Specialtis [1], with the
exception of cultivated mushrooms. HEs are defined in the Census as any
operation growing and selling $2,000 or more worth of horticultural
specialty products annually. Hence, strictly retail businesses such as
retail nurseries that buy plants for immediate resale were excluded from
the study. Data was collected from 574 HEs within 77 counties across the
48 coterminous States. The HEs were selected using valid probability
sampling techniques that permit scientific extrapolation of the data to all
HEs in the sampled population. The data can then be used to make national
and regional estimates for the horticultural specialties industry based on
characteristics recorded on the questionnaires. A brief summary of how the
HEs were selected is given below. A detailed description of the PUSHSP
survey design is given in Appendix A.
The HEs were selected in two stages. Counties (or groups of small
counties) were used as the primary or first-stage units. The first-stage
frame consisted of 3,062 county units. The frame was partitioned into four
geographic regions coinciding with the four U.S. Census Regions:
Northeast, North Central, South, and West. Approximately an equal number
of counties were selected from each stratum with probabilities proportional
to the total sales of horticultural products. The total sales were used as
a surrogate size measure because they were anticipated to be correlated
with pesticide usage. Within each sample county, lists of establishments
possibly involved in horticultural specialties production were constructed
using several sources. The sources including the Dun and Bradstreet DMI
computerized data files, the American Association of Nurserymen (AAN)
membership directory, and State 11 censure and dealer lists, were known to
contain many firms that were not eligible for the study. The firms from
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these three sources were partitioned Into two groups: likely eUglbles and
possible (not likely) eUglbles. AAN members were assigned by their AAN
roster codes. Firms on the Dun and Bradstreet DMI file with Standard
Industrial Classification (SIC) codes 0181, 0182, 0189, 0782, 0783, 5261,
5992, and 9999 were assigned on the basis of SIC codes. Firms on the State
lists were assigned by Information on the provided 11st. Some State lists
did not include sufficient Information to assign a firm to either group.
A total of 1,172 business establishments were selected from among the
79 counties (2 counties contained no eligible HEs). Screening these
business establishments Identified 685 eligible and 445 Ineligible
establishments. The eligibility of 26 establishments was not determined.
The remaining 16 establishments were found to be duplications. Of the 685
ellgibles, 574 HEs cooperated and provided the majority of the Information
requested resulting 1n a response rate of 83.8 percent. This response rate
compares favorably to other usage surveys and should not substantially
affect the quality of the data.
The sample was deliberately skewed toward larger firms to Improve the
precision of estimates of total pesticide usage. It was assumed that in
selecting the firms, their gross revenues would be positively correlated
with pesticide usage, thus why large firms were favored 1n the sampling
(see right most column, Table 1.1). Skewing the sample does not compromise
the statistical validity In this case. However, the statistical data
summaries must properly Incorporate how the HEs were selected (see Appendix
A). The statistical analysis reflects the reciprocals of their probability
of selection. Generally, small firms had larger weights than large firms.
Comparing the unweighted and weighted percent distribution by the gross
revenue categories 1n Table 2-1 clearly Illustrates the effects of the
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Table 1.1. Comparison of Horticultural EstabIishments (HEs)
Distribution by Survey Estimates
Dol lar
Category*
2,000 - 26,000
25,000 - 49,999
60,000 - 99,999
100,000 - 499,999
> 600,000
Total
Unclassified
Unwe i ghted
Samp 1 e
Size Percent
38 7.5
31 6.1
68 11.4
201 39.6
181 36.6
609 100.0
64
Weighted
Number
of HEs Percent
2,872 19.1
1,803 12.0
2,729 18.1
6,911 39.3
1,736 11.6
16,061 100.0
2,203
1979
Census Counts
Number
of HEs Percent
10,948 48.0
3, 196 14.3
2,892 12.9
4,060 18.2
1,261 6.6
22,347 100.0
Estimated
Usage Per
HE (pounds
AI)
72
17
135
139
938
320
'Dollar categories represent total gross revenue as indicated on Question 29 of the
questionnaire. Gross revenue includes horticultural and nonhorticuItura I sales for survey
estimates. The categories represent horticultural sales only for the 1979 Census counts.
AI = active ingredient.
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weights on the estimates. These estimates are much less skewed toward
larger firms than the unweighted estimates. The weighted percent do not
agree with the Census counts because the dollar categories are not
comparable. The Census categories are for horticultural sales only.
Survey categories are for gross revenue, horticultural and non
horticultural sales. This has the effect of promoting firms Into hlger
categories. In summary, the sample statistically reflects the size
distribution of the population of interest.
Another characteristic of HEs that can be compared to Census counts is
the type of commodites that the sample members produce. Table 1.2 was
constructed for this comparison.
The first column of numbers gives the Census counts from Table 1, p. 1
of the 1979 Census, for the 13 commodity groups. The order has been
rearranged for easy comparison with the Questionnaire categories. The
total of the column 1s 37,454 as compared to the number of HEs, 22,347,
reported by the Census. In the first column, HEs may be counted more than
once if they raise more than one commodity.
The second solumn of numbers gives the counts from Table 2, p. 2, of
the 1979 Census by the "Kind of Business" category. The third column of
numbers is the estimated target population size by Kind of Business
category that was calculated by excluding HEs In Alaska, Hawaii, and HEs
classified as growing cultivated mushrooms from the HE counts 1n column 2.
The total for the column is 21,164. The survey estimate of this number 1s
17,254 which 1s reasonably close to the Census count. The difference
between 21,164 and 17,254 is largely due to sampling error and HEs going
out of business since the Census. Some undercoverage of small firms could
also contribute to this difference. Undercoverage of small firms would not
severely bias pesticide usage estimates.
5
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T»bl« 1.2 Summary of 1979 Censua Count* »nd Survey Estimate*
CTV
Row Census
Number Commodity Group*
Nursery product!
rhizome*
Bedding plant*
Fol l*g* plant*
1 Subtotil
Petted flowering plants
Cut flower*
Unfinished stock
Cut cultivated green*
2 Subtotal
3 Sod
1The total , 37,464, exceed* the
2The number of establishments of
Number of
Estsbl Ishments
Growl ng
Commodity,
7,436
372
8,070
5,463
21,341
7,846
3,900
880
674
13,099
1,060
number of HE*, 22,
Census
Kind of
Business
Category
Bulbs, corns, or
er rhizome*
Bedding pl*nt*
Foliage planta
potted flowering
plant* snd/or
cut f lowere
Sod
347, becssuse HE*
the target population was calculated
li 1 .
Number of
Estsbl Ishmenta
Census Terget
Count Population2
6,267 6,203
169 169
3,947 3,926
2.347 2,273
12,710 12,660
6,486 6,943
6,486 6,943
973 970
can grew mere than one
Survey Question
Type of Eatlmste of
Code Horticultural Simple the Number of
Number Activity Size Establishments
01 nureery production
Including bedding
plant*, fol lag*
plant*, tree*.
achruba, and bulba
(excludea Christmas
tree*)
494 16,672
02 Floral production
Including potted
end cut flower*
246 6,367
03 Sad growing 38 1,198
commodity group.
by excluding sll establishments in the cultivated mushroom* category and all
Misclassifi cation hma occurod in this category. The true x*'uo '<* between 070 and 1.478.
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Table 1.2 Summary of 1979 Census Counts and survey Eatlm.toa
Re* Cansue
Numbor Comnodlty Groups
Vegetable aeoda
Flower aoeda
Greenhouse vegetables
4 Subbotsl
Cultivated mushrooms
C
Number of Survey Question
E.tihl l.hmenta Census Number of 2t Csteforlea Survey
Or o» Ing Kind of Estab 1.1 ahmenta TrP* of Estimate af
Commodity, Bualneaa Cenaua Target Code Horticultural Sample the Number of
Census Count Category Count Population9 Number Activity Slie Eatab 1 1 ahmenta
628 Vegetable and 441 439 04 production of aeed
866 Vegetables grown 638 638 table) and green-
under cover house vegetablea
(for nonagr Icul tura 1
use only)
1,478 970 970 87 3,8603
477 Cultivated 476 0
mushrooms
Other 723 714 06 Other 30 1,040
06 Landscape 132 6.924
Architecture/
maintenance
6 Total
1The total . 37,454. exceeda the
'The number of establishments of
37.4641 Total 22,347 21,164 Total 28.1273
number of HEs, 22. 347, becaause HEa can grow more than one commodity group.
the taroet oooulation was calculated by excluding all eatab 1 I ahmenta In the cultivated mushrooms cateoorv and all
astab Ii shmenbs in Alaska and Hawaii.
3Misclassification has occured in this category. The true value is between 970 and 1,478.
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The last column gives the weighted total of the number of firms
answering "yes" to the Question 2a categories of the questionnaire. The
weighted total estimates the number of HEs in the target population that
engages in the corresponding horticultural activity.
The subtotals and totals for the columns are not directly comparable
but sample estimates in the last column should be between the numbers in
column 1 and column 3. For example, a firm raising both bedding plants and
foilage plants would be counted twice in the row 1 total of 21,341 but only
once in the last row total of 15,672. The numbers in column 3 must be
smaller than the numbers in the last column. The reason is a firm
classified as a flower grower and counted in row 2 of the third column
could also grow other commodities such as foilage plants. This firm would
be counted in both row 1 and row 2 of the last column. So the sample
estimate of 15,672 for row 1, nursery productions, seems to be reasonable.
The floral (row 2) and sod (row 3) estimates also compare favorably with
the Census Counts. However, seed production (row 4} appears to be
substantially overestimated. This estimate was Inspected 1n detail and 1t
was determined that m1scalssif1cat1on had occurred. Eighty-seven (87) HEs
responded "yes" to the category 4; but only 5 Indicated that category 4 was
their only horticultural activity. The sum of weights for these 5 1s only
201, only 5 percent of the estimated total of 3,850 HEs. About 15 percent
of the HEs that responded yes to category 1 also responded yes to category
4. At most 5 percent ([528 + 84]712,710) of the 12,710 question 2a
category 1 firms could also raise seeds. With our sample size of 574, the
probability of having 15 percent of the sample correctly reporting category
4 activities when at most 5 percent belong to category 4 1a nearly zero.
This fact is convincing that some misclassification has caused the category
8
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4 estimate to be so large. What may have happened 1s that some HEs that
are raising vegetable bedding plants such as tomatoes or pepper for sale to
home gardeners have classified themselves 1n category 4 because of the
words "...greenhouse vegetables (for nonagricultural use only)."
In conclusion, the above comparisons support the fact that biases in
total pesticide usage estimates resulting from possible inadequacies in the
sampling frame and the sample design are not a dominant source of error.
The survey questionnaire was used to solicit Information on a variety
of topics including the HEs1 horticultural activities, pesticide usage by
EPA registration number, target pests, and firm size measured by gross
revenue. A copy of the PUSHSP questionnaire Is Included as Appendix B.
The PUSHSP data can be used to estimate pesticide usage in the Industry
overall, by active ingredient (AI), and by subsets of the Industry such as
geographic region, firm size, and horticultural application site (e.g.,
greenhouses or outdoor woody plants). Profiles of the Industry can also be
estimated. Describing the distribution of the number of HEs by their gross
revenue and use of integrated pest management methods 1s possible along
with many other types of estimates. The documentation of the PUSHSP user
file given in Appendix C Includes a detailed description of the Information
that 1s available. Chapter 2 contains estimates of selected pesticide
usage and industry characteristics that were considered to be of major
interest.
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2. SUMMARY OF RESULTS
2.1 Overview
This chapter presents statistical summaries of data Hems collected for
PUSHSP. The summaries are grouped Into three categories: pesticide usage,
target pest Information, and Industry characteristics. Before the
summaries are presented, a discussion of the general approach to the data
analysis 1s appropriate.
The Initial step 1n generating pesticide usage estimates required
standardizing the product amounts reported 1n the questionnaire. The usage
was standardized by converting all usage amounts to pounds and then
multiplying the standardized amount by the concentration of the AIs 1n each
product. These two steps generated the pesticide usage analysis variable,
pounds of AI, that was used to estimate total usage by the Industry and
usage for selected subsets such as pesticide class, Census Region,
horticultural site, and size of firm.
The second component of the analysis estimated the frequency of
reported target pest by subsets, such as horticultural site and Census
Region. The target pest analysis also Includes the estimated frequency of
which products are used to control a pest.
The final component of the analysis Involves estimating the
distribution of HEs by characteristics reported on the questionnaire, such
as type of production or activity, number of locations, and use of
Integrated pest management methods.
The methods used to calculate the estimates reflect the survey design
and are described 1n Appendix A.
10
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2.2 Summary of Pesticide Usage
This section summarizes the pesticide usage distribution for selected
AIs by Census Region and horticultural site. Also, total pesticide usage,
estimated to be approximately 3.466 million pounds of active ingredients,
is also summarized by size of firm. The Census Regions are defined in
Figure 1. The horticulture sites of pesticide application comprise five
categories, defined as follows:
Greenhouses — includes all usage applied to treat pest infesting all
types of plants, both woody and herbaceous, grown within greenhouses or
weeds or grasses infecting growing areas in greenhouses.
Outdoor woody — includes all usage applied to control pest infesting
woody-stemmed plants such as azalea, boxwood, juniper, or trees (except
Christmas tress) outdoors or weeds or grasses infesting the outdoor
area in which they were grown.
Floral and other outdoor — Includes all usage applied to control pest
infesting nonwoody-stemmed floral plants (herbaceous plants) such as
carnations, chrysanthemums, other herbaceous plant grown outdoors or
turf grasses grown for sod (pesticides such as atrizine applied to turf
grasses were reported by sod farms in this usage site) or to control
weeds or grasses infesting outdoor areas where they were grown.
Soil — includes outdoor usage applied for soil sterilization (methyl
bromide) and herbicides applied to the soil for weed or grass control
in growing areas (mostly glyphosate and simazine).
Nonhorticultural — includes essentially only herbicide usage applied
outdoors for weed or grass control in nongrowing areas such as fence
rows, borders, or roadways.
The total usage estimate is the sum of the usage of 188 different AIs.
The detailed analysis summarized in this section was focused on a selected
subset of the most important pesticides. Two criteria were used to define
this "most Important" subset. The first criterion was based on the number
of HEs that reported using a specific pesticide, the minimum being 20 HEs.
The second limited analysis to the 10 most heavily used AIs within three
pesticide classes: 1nsect1c1de/m1t1cide, fungicide, and herbicide for
those pesticides meeting the first criterion. One exception to these rules
11
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EAS
SOUTH
CENTRAL
MISS
SOUTH
CENTRAL
Figure 1. The Four Census Regions of the United States
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was made for methyl bromide, which 1s a multipurpose pesticide and can be
used to effectively control several classes of pest. Because It was
Inappropriate to classify methyl bromide Into only one class, reporting It
for each class according to Its use was considered. However, such an
approach violated the 20-HE rule for the each class. One other exclusion
should be noted. One large HE 1n the West was excluded from the pesticide
usage analysis upon the advice of subject matter experts because of Its
unusual reported usage.
Table 2.1 presents the estimated usage of the top 20 AIs, accounting
for 45.4 percent of all pesticide usage In the Industry. (A listing of the
usage estimates for all AIs Is Included 1n Appendix D.) Table 2.2 presents
estimates of pesticide usage for the top 10 1nsect1c1des/mit1c1des,
fungicides and for the top 8 herbicides (only 8 herbicides were reported by
at least 20 HEs). These three pesticide classes Include 96.7 percent of
the total usage. The primary criterion previously mentioned for listing
particular pesticides, as in Tables 2.1 and 2.2, Is that at least 20 HEs
reported their use. Pesticides Included In the "other" category may be
used by less or more than 20 HEs. It 1s common and valid statistical
practice to group domains (AIs) with small sample sizes together so that
the sample size of their union is satisfactory. Therefore, including all
AIs that are excluded from the detailed analysis because they were reported
by fewer than 20 HEs in the other category 1s appropriate.
13
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Table 2.1 Pesticide Usage by Active Ingredient
Common
Name3
Glyphosate
Trifluralln
Slmazlne
EBDC
Malathion
Carbaryl
Benomyl
Captan
Dlazlnon
Acephate
Chlorothalonll
Copper hydroxide
Oryzalln
Z1neb
PCNB
Oxadlazon
Aldicarb
Dlenochlor
Dlcofol
Napropamlde
Oxydemetan-methyl
Subtotal
Other0
Total
AI
Code
103601
36101
80807
14504'
57701
56801
99101
81301
57801
103301
81901
23401
104201
14506
56502
109001
98301
27501
10501
103001
58702
Sample5
Number
of HEs
359
53
122
101
245
193
343
165
319
217
101
58
46
44
78
88
107
109
232
27
111
Estimated
usage
(1000s of pounds)
300
169
123
112
106
93
89
79
75
70
57
49
44
36
32
28
27
22
21
20
20
1,572
1,894
3,466
Percent
of
Total
8.7
4.9
3.6
3.2
3.1
2.7
2.6
2.3
2.2
2.0
1.6
1.4
1.3
1.0
0.9
0.8
0.8
0.6
0.6
0.6
0.6
45.4
54.6
100.0
aA pesticide 1s listed by name only 1f at least 20 HEs reported Its use.
^This number Includes only HEs that reported a positive usage of the AI.
C0ther pesticides reported may be used by less than 20 HEs.
AI = active Ingredients
HE = horticultural establishments
14
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Table 2.2 Pesticide Usage by Active Ingredient and Class
Pesticide
Class
Insecticide
or
mitlcide
Fungicide
Herbicide
Common
Name3
Malathion
Carbaryl
Dlazinon
Acephate
Aldicarb
Dlenochlor
Dicofol
Oxydemeton-methyl
Dimethoate
Oisulfoton
Subtotal
Otherc
Total
EBDC
Benomyl
Captan
Chlorothalonll
Copper hydroxide
Z1neb
PCNB
Terrazole
Metal axyl
Methyl thlophanate
Subtotal
Otherc
Total
Glyphosate
THfluralln
S1maz1ne
Oryzalln
Oxadiazon
Napropamide
AI
Code
57701
56801
57801
103301-
98301
27501
10501
58702
35001
32501
14504
99101
81301
81901
23401
14506
56502
84701
113501
102001
103601
36101
80807
104201
109001
103001
Sample^
Number
of HEs
245
193
319
217
107
109
232
111
70
32
101
343
165
101
58
44
78
160
100
69
359
53
122
46
88
27
Estimated
Usage
(1000s of
pounds)
106
93
75
70
27
22
21
20
19
19
472
215
687
112
89
79
57
49
36
32
15
11
9
489
390
879
300
169
123
44
28
20
Percent
of
Total
15.5
13.6
11.0
10.2
3.9
3.1
3.0
2.9
2.7
2.7
68.7
31.3
100.0
12.7
10.1
9.0
6.4
5.6
4.0
3.7
1.7
1.3
1.1
55.6
44.4
100.0
16.8
9.5
6.9
2.5
1.5
1.1
aA pesticide 1s listed by name only 1f at least 20 HEs reported Its use.
bThis number Includes only HEs that reported a positive usage of the AI.
C0ther pesticides reported may be used by less than 20 HEs.
15
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Table 2.2 Pesticide Usage by Active Ingredient and Class
(continued)
Pesticide
Class
Herbicide
Common
Name3
Paraquat d1 chloride
Dlquat dl bromide
Subtotal
Otherc
Total
Active
Ingredient
Code
61601
32201
Sample**
Number
of HEs
73
43
Estimated
Usage
(1000s of
pounds)
16
14
714
1,073
1,787
Percent
of
Total
0.9
0.8
40.0
60.0
100.0
aA pesticide 1s listed by name only 1f at least 20 HEs reported Its use.
bThis number Includes only HEs that reported a positive usage of the AI.
C0ther pesticides reported may be used by less than 20 HEs.
AI = active Ingredient
HE = horticultural establishments
16
-------
A separate listing of the estimated usage for 1nsect1c1des/nrit1cides,
fungicides, and herbicides and other pesticides 1s included in Appendix D.
Tables 2.3 and 2.4 present these same AIs by class and Census Region and by
class and horticultural site (greenhouses, outdoor woody plants, and floral
and other outdoor plants), respectively. Two other sites, soil and
nonhorticultural, were Included 1n the questionnaire. The usage reported
for these sites was minor for most AIs, resulting in their exclusion from
the detailed analysis.
Table 2.5 presents the total estimated usage and estimated number of
HEs by firm size as measured by gross revenues. Tables 2.6 and 2.7 present
this same information according to firm size, by Census Region, and by
horticultural site, respectively.
2.3 Summary of Report Pest
The questionnaire was used to solicit information on target pest by
horticultural site and pesticide product. Table 2.8 presents the number of
HEs reporting target pest(s) for each horticultural site. Table 2.9
presents the target pest information summarized over all sites by Census
Region. Table 2.10 presents the frequency of reporting target pest(s) by
Census Region and horticultural site. Table 2.11 displays the estimated
number of HEs by the five most frequently reported pests 1n each class of
insects, diseases, and among weeds or grass and the five most frequently
used pesticide products for each pest.
2.4 Summary of Nursery Industry Characteristics
This section Includes tables presenting estimates of the distribution
of HEs by selected characteristics. Table 2.12 presents the estimated
number of HEs involved In six categories of HE production/activities.
Approximately 6 percent of the HEs also engage in other activities. The
17
-------
Table 2.3 Pesticide Usage by Active Ingredient, Class, and Census Region
00
Census Reaion
Northeast
Pesticide
Class
Insecticide
or
miticide
Fung) cide
Common
Name
Malathion
Carbary 1
Di azi non
Acephate
Aldicarb
DIenoeh lor
Dlcofol
Oxydemeton-
methy 1
Dtmethoate
Di su 1 f oton
Subtota 1
Other
Total
EBDC
Benomy 1
Captan
Ch lorotha 1 onl 1
Copper
hydroxi de
Zineb
PCNB
Terrazo la
Metalaxy 1
Methyl
thi ophanate
AI
Code
67701
66801
67801
103301
98301
27601
10601
68702
36001
32601
14604
99101
81301
81901
23401
14606
66602
84701
113601
102001
Usage
(1000s of
pounds)
6.7
11.1
3.4
4.6
1.0
0.9
1.7
3.7
1.7
0.4
34.2
21.6
66.7
6.6
6.2
6.9
1.2
0.0
0.7
2.2
1.2
0.2
0.6
Samp le*
Number
of HEs
66
46
63
46
14
23
46
29
11
7
18
70
41
17
1
6
18
28
16
12
North Central
Usage
(1000s of
pounds)
16.4
44.1
18.1
8.7
7.3
6.8
10.2
6.7
6.8
7.3
131.3
32.9
164.2
3.3
21.7
6.1
4.9
1.6
0.6
3.9
4.7
0.7
3.4
Samp le*
Number
of HEs
67
62
83
62
61
34
76
23
19
16
17
101
60
26
8
9
23
64
24
21
South
Usage
(1000s of
pounds)
23.4
33.9
18.6
10.6
2.7
6.3
4.6
1.9
7.2
10.9
119.2
54.0
173.2
49.8
22.1
60.0
42.1
11.2
11.6
6.1
4.2
6.0
2.8
Samp le
Number
of HEs
49
41
64
44
19
20
67
12
24
9
63
77
25
38
24
6
11
39
28
17
West
Usage
(1000s of
pounds)
61.0
4.3
36.1
46.6
16.9
8.6
4.4
8.4
3.2
0.0
187.3
106.4
293.7
51.9
39.8
16.9
8.3
36.2
22.6
21.2
4.9
6.3
2.8
Samp 1 e*
Number
of HEs
73
44
117
75
23
32
54
47
16
1
13
95
49
21
25
24
26
39
33
19
*This number includes only HEs that reported a positive usage of the AI,
AI = active ingredient.
HE = horticultural establishment.
-------
Table 2.3 Pesticide Usage by Active Ingredient, Class, and Census Region (continued)
Census Reaion
Northeast
Pesticide
Class
Herbicide
A
>
Common
Name
Subtota 1
Other
Total
Glyphosate
Trlf lural In
Simaz ine
Oryza 1 i n
Oxadlazon
Napropamide
Paraquat
dichloride
Di quat
Subtotal
Other
Total
Active
Ingredient
Code
103801
36101
80807
104201
109001
103001
61601
32201
Usage
(1000s of
pounds)
23.9
9.9
33.9
24.7
3.6
20.7
6.7
1.2
3.6
3.8
0.1
63.4
71.1
134.6
Samp le*
Number
of HEs
62
7
32
13
12
9
20
6
North Central
Usage
(1000s of
pounds)
61.0
87.0
138.0
42.7
3.3
62.8
10.8
2.6
4.9
2.3
0.4
119.6
167.7
287.3
Samp le*
Number
of HEs
96
23
44
11
20
7
18
2
South
Usage
(1000s of
pounds)
203.7
34.6
238.2
139.2
4.4
12.2
11.0
6.1
0.6
6.7
0.2
179.3
712.9
892.2
Samp le
Number
of HEs
92
7
13
6
28
1
19
4
West
Usage
(1000s of
pounds)
210.0
258.7
468.7
93.6
167.6
37.8
16.7
17.8
10.9
4.4
13.1
351.8
121.0
472.8
Samp le*
Number
of HEs
120
16
33
16
28
10
16
31
•This number includes only HEs that reported a positive usage of the AI,
AI = active ingredient.
HE = horticultural establishment.
-------
Table 2.4 Pesticide Usage by Active Ingredient, Class, and Horticultural Site
Horticultural Site
Greenhouse
Pesticide Common
Class Name
Insecticide Ma lath ion
or Carbaryl
miticlde Dlazinon
Acephate
Aldicarb
D ienoch lor
Dicofol
Oxydemeton-methy 1
Dimethoate
D 1 su 1 f oton
Subtota 1
Other
PO Total
o
Fungicide EBDC
Benomy 1
Captan
Ch 1 orotha 1 oni 1
Copper hydroxide
Zineb
PCNB
Terrazo le
Metal axy 1
Methyl thiophanate
Subtota 1
Other
Total
AI
Code
67701
B6801
57801
103301
98301
27601
10601
68702
36001
32601
14604
99101
81301
81901
23401
14606
66602
84701
113601
102001
Usage
(1000a of
pounda)
63.4
8.2
18.6
20.6
16.8
17.1
6.6
7.0
3.2
0.4
149.6
83.8
233.3
11.9
67.1
31.2
12.4
6.3
20.8
17.2
9.6
6.4
6.8
179.7
23.3
203.0
Samp le*
Number
of HEs
166
81
197
132
89
102
139
66
23
11
46
266
130
66
24
27
66
141
130
67
Outdoor Woodv
Usage
(1000s of
pounds)
47.7
67.0
36.9
46.7
1.7
2.4
13.8
10.7
13.8
17.6
246.1
65.7
301.8
24.1
13.8
17.3
9.2
39.2
2.2
1.9
0.6
3.9
0.4
112.7
104.0
216.7
Samp 1 e*
Number
of HEs
142
117
146
109
13
14
126
64
47
22
69
126
66
36
41
16
11
18
33
9
Other Outdoor
Usage
(1000s of
pounds)
6.4
27.4
14.8
3.6
8.7
2.1
1.6
2.0
1.9
0.8
69.0
51.4
120.4
75.6
16.0
2.9
34.5
3.4
6.8
13.2
3.6
0.5
0.2
153.6
17.1
171.7
Samp le
Number
of HEs
34
37
56
27
6
6
24
13
9
4
26
45
18
19
6
6
6
9
9
6
*This number includes only HEs that reported a positive usage of the AI.
AI = active ingredient.
HE = horticultural establishment.
-------
Table 2.4 Pesticide Usage by Active Ingredient, Class, and Horticultural Site (continued)
ro
Horticultural Site
Greenhouse
Pesticide Common
Class Name
Herbicide Glyphosate
Trif luralin
Simazi ne
Oryza 1 In
Oxadl azon
Napropamide
Paraquat dichloride
Diquat di bromide
Subtotal
Other
Total
AI
Code
103601
36101
80807
104201
109001
103001
61601
32201
Usage
(1000s of
pounds)
16.3
2.7
2.9
0.3
0.9
0.4
1.4
6.1
29.2
66.2
84.4
Samp le*
Number
of HEs
90
4
18
6
11
3
29
23
Outdoor
Usage
(1000s of
pounds)
120.7
164.2
86.9
1.6
3.2
17.7
6.6
0.4
454.4
161.1
616. E
Woodv
Samp 1 e*
Number
of HEs
166
38
71
6
18
21
11
1
Other Outdoor
Usage
(1000s of
pounds)
61.7
0.9
10.0
8.2
1.4
0.0
0.1
0.9
82.8
673.8
766.6
Samp 1 e
Number
of HEs
60
5
14
6
16
0
6
6
•This number includes only HEs that reported a positive usage of the AZ.
AI = active ingredient.
HE = horticultural establishment.
-------
Table 2.5 Pesticide Usage and Number of Horticultural
Establishments (HEs) by Size
Type of
Size
Measure
Gross Revenue*
< $ 25,000
$ 25,000 to $ 49,999
$ 50,000 to $ 99,999
$100,000 to $499,999
$500,000 to $999,999
> $1 million
Refused/Unknown
Total
Sample
Number
of HEs
38
31
58
201
90
91
64
573
Estimated
Usage
(1000s of pounds)
206
30
368
821
399
935
706
3,466
Estimated
Number
of HEs
2,872
1,803
2,729
5,911
1,123
613
2,203
17,254
*Gross revenue Includes all revenue from both horticultural and
nonhortlcultural activities.
22
-------
Table 2.6 Pesticide Usage and Number of Horticultural
Establishments (HEs) by Size and Census Region
Size
Measure
Gross Revenue
<$ 25,000
$ 25,000 to $ 49,999
$ 50,000 to $ 99,999
$100,000 to $499,999
$500,000 to $999,999
>$1 Million
Refused/Unknown
Total
Gross Revenue
<$ 25,000
$ 25,000 to $ 49,999
$ 50,000 to $ 99,999
$100,000 to $499,999
$500,000 to $999,999
>$1 Million
Refused/Unknown
Total
Gross Revenue
<$ 25,000
$ 25,000 to $ 49,999
$ 50,000 to $ 99,999
$100,000 to $499,999
$500,000 to $999,999
>$1 Million
Refused/Unknown
Total
Gross Revenue
<$ 25,000
$ 25,000 to $ 49,999
$ 50,000 to $ 99,999
$100,000 to $499,999
$500,000 to $999,999
>1 Million
Refused/Unknown
Total
Sample*
Number
of HEs
10
8
15
41
13
16
_12
115
13
2
21
52
24
21
aa
151
10
9
7
49
21
19
_n
128
5
12
15
59
32
35
_21
180
Estimated Usage
(1000s of pounds)
Northeast
1.2
6.1
10.1
56.8
16.1
74.3
65.8
230.5
North Central
17.3
2.2
53.4
197.1
150.0
160.8
13.4
594.2
South
3.1
11.0
15.6
274.2
119.8
389.9
491.3
1,304.0
West
184.5
11.1
288.9
292.8
113.4
309.8
135.8
1,336.4
Estimated
Number
of HEs
352
362
439
966
114
74
576
2,883
1,241
81
946
1,243
443
128
515
4,600
764
756
421
1,447
284
113
669
4,455
514
603
923
2,254
281
298
442
5,316
23
-------
Table 2.7 Pesticide Usage and Number of Horticultural
Establishments (HEs) by Size and Site
Size
Measure
Gross Revenue
<$ 25,000
$ 25,000 to $ 49,999
$ 50,000 to $ 99,999
$100,000 to $499,999
$500,000 to $999,999
>$1 Million
Refused/Unknown
Total
Gross Revenue
<$ 25,000
$ 25,000 to $ 49,999
$ 50,000 to $ 99,999
$100,000 to $499,999
$500,000 to $999,999
>$1 Million
Refused/Unknown
Total
Gross Revenue
<$ 25,000
$ 25,000 to $ 49,999
$ 50,000 to $ 99,999
$100,000 to $499,999
$500,000 to $999,999
>$1 Million
Refused/Unknown
Total
Sampl e
Number
of HEs
16
18
33
132
53
54
_25
341
22
17
18
87
35
52
_2fi
257
6
10
14
47
23
25
ua
143
Total
Pesticide Usage
(1000s of pounds)
Greenhouses
1.1
8.6
70.1
192.7
100.2
135.0
17.5
525.2
Outdoor Woody
188.0
16.0
42.0
403.9
154.9
266.9
70.1
1,141.9
Floral and Other Outdoor
1.6
0.7
19.9
106.6
108.9
350.7
55.0
1,143.3
Estimated
Number
of HEs
966
1,169
1,565
4,189
632
382
1,120
10,023
1,760
1,059
1,124
2,776
393
269
677
8,058
344
1,006
729
1,320
292
243
1,042
4,990
*Th1s number Includes only HEs
horticultural site.
that reported positive usage data for the
24
-------
Table 2.8 Frequency of Reported Target Pest by Horticultural Site
Horticultural
Site
Greenhouses
Outdoor Woody
Floral and Other Outdoor
Target
Pest
ApMds
Mites
Damping off
Mealy bugs
Wh1tefl1es
ApMds
Annual broadleaf weeds
Annual grasses
Mites
Scales
ApMds
Annual broadleaf weeds
Annual grasses
Cutworms
Beetles
Sample
Number
of HEs
301
271
170
183
183
215
179
164
173
141
79
68
54
34
19
Estimated
Number
of HEs
9,133
6,587
5,624
5,131
4,557
5,954
5,596
5,465
4,100
3,213
3,531
2,079
1,419
1,404
1,377
HEs = horticultural establishments.
25
-------
Table 2.9 Frequency of Reported Target Pest by Census Region
Census
Region
Northeast
North Central
South
West
Target
Pest
Aphids
Mealy bugs
Annual broadleaf weeds
Damping off
Mites
Aphids
Annual broadleaf weeds
Mites
Annual grasses
Perennial grasses
Aphids
Annual grasses
Mites
Mealy bugs
Annual broadleaf weeds
Aphids
Annual broadleaf weeds
Annual grasses
Mites
Perennial grasses
Sampl e
Number
of HEs
118
59
74
45
94
167
139
135
121
85
116
117
109
105
123
203
166
141
150
95
Estimated
Number
of HEs
3,295
2,204
2,105
1,762
1,632
4,634
3,492
3,310
2,900
2,477
4,930
4,237
4,087
3,882
3,869
5,923
4,546
4,145
2,856
2,834
HEs = horticultural establishments.
26
-------
Table 2.10 Frequency of Reported Target Pest by
Horticultural Site and Census Region
Horticultural
Site
Greenhouses
Outdoor Woody
Floral and Other Outdoor
Greenhouses
Outdoor Woody
Target
Pest
Aphlds
Mealy bugs
Mites
Damping off
WhltefHes
Aphlds
Scales
Annual broadleaf
Annual grasses
Other Insects
Aphlds
Powdery mildew
Mealy bugs
Cutworms
Beetles
Aphlds
Mites
Whlteflles
DampUng off
Botrytls
Annual broadleaf
Aphlds
Annual grasses
Sample
Number
of HEs
Northeast
70
40
61
38
53
36
23
weeds 31
30
24
12
8
6
3
6
North Central
92
84
64
50
55
weeds 55
59
49
Perennial grasses 41
Floral and Other Outdoor
Mites
Aphlds
Annual broadleaf
Annual grasses
Other diseases
Cutworms
46
12
weeds 14
11
6
3
Estimated
Number
of HEs
1,861
1,364
1,255
1,237
1,070
688
607
577
522
376
746
692
671
584
573
2,400
1,923
1,465
1,449
1,410
1,702
1,627
1,512
1,294
1,158
464
352
291
240
231
HEs = horticultural establishments.
(continued)
27
-------
Table 2.10 Frequency of Reported Target Pest by
Horticultural Site and Census Region (continued)
Horticultural
Site
Greenhouses
Outdoor Woody
Floral and Other Outdoor
Greenhouses
Outdoor Woody
Floral and Other Outdoor
Target
Pest
Aphlds
Mites
Mealy bugs
Damping off
Root rot
Mites
Aphlds
Annual grasses
Annual broadleaf weeds
Mealy bugs
Aphlds
Bagworms
Annual grasses
Beetles
Annual broadleaf weeds
Aphlds
Damping off
Mites
Botrytl s
Phytophtora
Annual grasses
Aphlds
Annual broadleaf weeds
Perennial grasses
Powdery mildew
Aphlds
Annual broadleaf weeds
Mites
Mollusks
Perennial grasses
Sample
Number
of HEs
South
48
50
48
36
34
44
44
37
38
36
20
8
21
6
20
West
91
46
76
47
25
48
76
55
31
45
35
28
19
8
14
Estimated
Number
of HEs
2,060
1,986
1,978
1,185
953
1,802
1,703
1,482
1,445
1,296
1,146
957
828
734
635
2,812
1,753
1,423
1,380
1,197
1,949
1,936
1,872
1,177
1,157
1,174
597
587
487
433
HEs = horticultural establishments.
28
-------
Table 2.11 Number of Horticultural Establishments (HEs) by Reported
Target Pest and Active Ingredient
Target
Pest
Insects
Aphids
Mealy Bugs
Mites
Scales
Whiteflies
Diseases
Botrytis
Damping Off
Pesticide
Product
Dlazinon
Malathion
Acephate
Carbaryl
Oxydemeton-methyl
Malathion
Diazinon
Acephate
Aldicarb
Carbaryl
Dicofol
Dienochlor
Malathion
Diazinon
Aldicarb
Malathion
Diazinon
Dimethoate
Carbaryl
Acephate
Malathion
Aldicarb
Diazinon
Acephate
Resmethrin
Benomyl
Captan
Chlorothalonil
Zineb
Fenaminosulf
Benomyl
Captan
Tarrazole
Fenaminosulf
Methyl thiophanate
Active
Ingredient
Code
57801
57701
103301
56801
58702
57701
57801
103301
98301
56801
10501
27501
57701
56801
98301
57701
57801
35001
56801
103301
57701
98301
57801
103301
97801
99101
81301
81901
14506
34201
99101
81301
84701
34201
102001
Sample
Number
of HEs
159
168
126
71
88
100
68
60
34
25
176
95
79
54
65
67
41
25
23
20
56
46
40
48
31
125
48
41
14
8
82
55
66
26
28
Estimated
Number
of HEs
4,746
4,407
2,283
2,266
1,135
3,106
1,535
893
770
640
3,617
2,224
1,698
1,639
1,278
1,393
797
619
557
401
2,094
802
713
630
610
3,256
1,130
645
321
297
2,443
1,860
1,223
559
530
29
(continued)
-------
Table 2.11 Number of Horticultural Establishments (HEs) by Reported
Target Pest and Active Ingredient (continued)
Target
Pest
Leaf Spot
Powdery Mildew
Root Rot
Weeds and Grasses
Annual Grasses
Annual Broadleaf
Weeds
Perennial Grasses
Perennial
Broadleaf Weeds
Pesticide
Product
EBOC
Benomyl
Copper hydroxide
Streptomycin sulfate
Chlorothalonil
Benomyl
Captan
Triforlne
Terrazole
Karathane
Benomyl
Terrazole
Metal axyl
Fenamlnosulf
PCNB
Glyphosate
S1maz1ne
Oxadlazon
Tr1flural1n
Paraquat d1 chloride
Glyphosate
Oxadlazon
S1maz1ne
Trlfluralln
Paraquat dlchloride
Glyphosate
S1maz1ne
Paraquat
Prometon
Sodium metaborate
Glyphosate
S1m1z1ne
Oxadlazon
Paraquat dlchloride
2,4-D
Active
Ingredient
Code
14504
99101
23401
6310
81901
9901
81301
107901
84701
36001
99101
84701
113501
34201
56502
103601
80807
109001
36101
61601
103601
109001
80807
36101
61601
103601
80807
109001
80804
11104
103601
80807
109001
61601
30010
Sample
Number
of HEs
34
60
23
6
27
117
33
35
8
19
61
58
32
32
34
232
79
65
43
53
237
82
98
51
55
169
20
22
5
3
145
17
12
27
5
Estimated
Number
of HEs
796
744
698
576
378
2,616
960
446
231
230
2,350
1,183
783
732
698
6,971
1,772
1,619
1,160
751
6,447
2,597
2,245
1,328
841
4,047
927
278
178
107
3,328
500
376
345
158
30
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Table 2.12 Estimated Distribution of Horticultural Establishments (HEs) by Type of Production/Activity
Type of
Product i on /Act i v I ty
Nursery Stock
Floral
Sod growing
Seed
Landscap i ng
Other
Number of*
Samp le
HEs
494
246
38
87
132
30
Estimated*
Number
of HEs
16,672
6,367
1,198
3.8B0
6,924
1,040
Estimated*
Percent of
Nurseries
87
36
7
22
33
6
Estimated
Northeast
2,813
(106)
1,634
(60)
2
(2)
861
(19)
619
(24)
127
(8)
(Sample) Number
Census Region*
North Central
4,210
(136)
1,986
(77)
281
(12)
964
(30)
1,884
(46)
379
(12)
of HEs by
South
4,162
(111)
790
(32)
724
(16)
1,021
(12)
2,130
(29)
216
(7)
West
4,488
(142)
1,967
(77)
191
(9)
1,014
(26)
1,291
(33)
319
(6)
*Totals for this table will exceed survey totals because some HEs are involved in more than one activity.
-------
totals 1n Table 2.12 sum to more than 17,283 because many nurseries engage
In more than one type of activity. Table 2.13 presents the estimated
number of HEs by the number of production locations they use.
Approximately 84 percent of the HEs use only one location for production.
Table 2.14 presents the estimated number and percent of HEs using chemical
pesticides nationwide, by Census Region, and by type of production. Table
2.15 provides the corresponding estimated number of HEs that apply at least
some pesticides using their own personnel. It 1s evident that nearly all
HEs use and apply chemical pesticides. Table 2.16 summarizes the frequency
of reported side effects from chemical pesticides. Less than 10 percent of
the HEs reported adverse side effects. The most frequent side effect
reported was damage to plants. Table 2.17 gives a detailed breakdown of
side effect Information by pesticide product.
Table 2.18 summarizes the number of HEs by dollar expenditures for
chemical pesticides. Table 2.19 presents the number and percent of HEs
with employees certified to apply pesticides, nationwide, by Census Region,
and by type of production. Table 2.20 presents the number and percent of
HEs employing Integrated pest-management methods. Table 2.21 presents the
number of HEs and estimated dollar loss by type of pest. Table 2.22
reports pesticide usage In 1982 compared with previous years.
Approximately 73 percent of the HEs used the same amount of pesticide, 15
percent used more, and 8 percent used less.
Table 2.23 presents the number of HEs that used their records to obtain
the Information needed to complete the questionnaire, nationwide, and by
Census Region. Less than half of the HEs used their records to answer the
questions.
32
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Table 2.13 Estimated Distribution of Horticultural
Establishments (HEs) by Number of Locations
Estimated (Sample) Number of HEs by
Census Region
Sample Estimated
Number of Number Number
Locations of HEs of HEs Northeast North Central South West
1
2
3
4
X
Total
476
65
21
5
7
547
14,546
2,103
480
111
41
17,283
2,309
(96)
454
(12)
(1)
1
(1)
96
22
(5)
2,883
(115)
3,735
(125)
542
(16)
300
(7)
(2)
14
(1)
4,600
(151)
4,020
(HI)
405
(12)
25
4,455
(128)
4,483
702
(25)
(7) (9)
(0) (2)
(1) (0)
153
5,345
(180)
33
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Table 2.14 Number and Percent of Horticultural Establishments (HEs)
Using Chemical Pesticides by Census Region and
Type of Production/Activity
Sample Number Estimated Estimated*
Reporting Domain of HEs Number of HEs Percent of HEs
National 556 16,665 96
Census Region
Northeast 115 2,883 100
North Central 146 4,414 96
South 122 4,368 98
West 173 5,000 94
Tvoe of Production/Activity
Nursery Stock
Floral
Sod Growing
Seeds
Landscaping
Other
485
243
33
84
128
30
15,383
6,167
1,080
3,563
5,822
1,040
98
97
90
93
98
100
*Percents are calculated based on the total estimated number of HEs in the
reporting domain.
34
-------
Table 2.15 Number and Percent of Horticultural Establishments (HEs)
Applying Chemical Pesticides (Not Soley Using Contractors)
by Census Region and Type of Production/Activity
Sample Number Estimated Estimated*
Reporting Domain of HEs Number of HEs Percent of HEs
National 544 16,304 98
Census Region
Northeast 114 2,831 98
North Central 146 4,414 100
South 118 4,194 96
West 166 4,864 97
Tvoe of Production/Activity
Nursery Stock
Floral
Sod Growing
Seeds
Landscaping
Other
477
240
31
83
127
28
15,175
6,148
1,041
3,456
5,771
1,016
99
>99
96
97
99
98
*Percentage based on number of estimated HEs using chemical pesticides for
each reporting domain given 1n Table 2.14.
35
-------
Table 2.16 Number of Horticultural Establishments (HEs) Reporting
Side Effects Associated with Pesticide Use
No
Side Effects
Some Side Effects
Plant Damage
(Dollar Amount of Loss
Nausea
Dizziness
Skin Rash
Other
Sample Number
of HEs
530
71
51
(49,370)a
6
6
4
7
Estimated Number
of HEs
15,799
1,484
1,203
(458,455)b
177
144
78
179
Unweighted sum of reported dollar loss,
^Estimated total dollar loss.
36
-------
Table 2.17 Number of Horticultural Establishments (HEs)
Reporting Side Effects by Pesticide Product
Side
Effects
Plant Damage
Nausea
Dizziness
Skin Rash
Pesticide
Product
Malathlon
Carbaryl
D1az1non
Acephate
Dlmethoate
Dlcofol
Oxydemeton-methyl
Aldlcarb
Dlenochlor
Cyhexatln
Dlnocap
Fembutatln-oxide
Oxamyl
Other Insecticides
Copper sulfate, basic
Dodine
Cyclohex1m1de
Metal axyl
Other fungicides
Glyphosate
S1maz1ne
Oxadlazon
Dlquat
3-4-D/mecoprop/d1 camba
Malathlon
Aldlcarb
Oxamyl
Malathlon
Aldlcarb
Oxamyl
Other herbicides
Oxydemeton-methyl
Aldlcarb
Oxamyl
Benomyl
Sample
Number
of HEs
4
1
2
5
8
4
1
4
1
2
1
1
1
3
3
1
1
1
1
1
1
2
1
1
2
3
1
1
3
1
1
1
1
1
1
Estimated
Number
of HEs
93
22
208
42
232
59
7
99
5
32
5
3
3
140
13
91
3
5
3
23
16
16
3
78
136
38
3
91
38
3
12
10
3
3
63
(continued)
37
-------
Table 2.17 Number of Horticultural Establishments (HEs)
Reporting Side Effects by Pesticide Product
Side
Effects
Pesticide
Product
Sampl e
Number
of HEs
Estimated
Number
of HEs
Other D1az1non 1 121
Aldlcarb 1 7
Copper hydroxide 1 3
Methylbrom1de/chlorop1cr1n 1 3
Other fuglcides 1 35
Paraquat 1 7
Diquat 1 3
38
-------
Table 2.18 Number of Horticultural Establishments (HEs)
by Amount Spent on Pesticide Purchases
Amount
Spent on Purchase
of Pesticides
Sample
Number
of HEs
Estimated
Number
of HEs
Percent
Applied to
Horticultural
Products
$0 to $100
$101 to $500
$501 to $1,000
$1,001 to $5,000
$5,001 to $10,000
$10,001 to $50,000
> $50,000
Unknown
Total
59
113
52
139
49
56
9
97
574
2,535
4,991
1,711
3,823
853
547
72
2,751
17,283
89
85
65
90
75
69
85
79
83
39
-------
Table 2.19 Number and Percent of Horticultural Establishments (HEs)
with Employees Certified to Apply Pesticides by Census Region and
Type of Production/Activity
Sample Number Estimated Estimated*
Reporting Domain of HEs Number of HEs Percent of HEs
National 409 11,631 67
Census Region
Northeast 98 2,219 77
North Central 115 2,745 60
South 103 3,671 82
West 93 2,996 56
Tvoe of Production/Activity
Nursery Stock
Floral
Sod Growing
Seeds
Landscaping
Other
357
183
26
64
94
22
10,742
4,246
995
2,565
4,424
749
69
67
83
67
75
72
^Percentage based on number of estimated HEs using chemical pesticides for
each reporting domain given 1n Table 2.14.
40
-------
Table 2.20 Number and Percent of Horticultural Establishments (HEs)
Using Chemical and/or Integrated Pest Management (IPM)
Methods
Method
Relying Solely on Nonchemical Methods
Apply Pesticides on a Regular Fixed
Schedule
Percent of Control Activities using
Chemical Methods Incorporating IPM
Method
0-24 percent
25-49 percent
50-74 percent
75-100 percent
Selection and Timing of Pesticides
Biological Controls
Cultural Control
Monitoring and Scouting
Other
Sample
Number
of HEs
16
183
358
54
33
109
367
74
214
504
40
Estimated
Number
of HEs
535
5,182
9,400
1,806
886
4,264
9,895
1,964
4,958
15,362
922
Estimated
Percent
of HEs
3
30
54
10
5
25
57
11
29
89
5
41
-------
Table 2.21 Number of Pest Problems and Associated Dollar
Loss by Type of Pest
Type
of
Pest
Leaf Miners
Weevils
Leaf Spot
Verticil Hum Wilt
WhitefHes
Borers
Fusarium Wilt
Perennial Broadleaf Weeds
Mites
Mealy Bugs
Subtotal
Other
Total
Sample
Number
of HEs
15
16
4
4
13
7
5
5
5
_7_
81
_55
136
Estimated
Number
of HEs
432
925
17
206
238
162
56
134
168
111
2,449
1,167
3,616
Dollar
Loss
(thousands)
$2,602
1,791
1,006
337
232
157
156
73
67
6fi
$6,487
2,605
$9,092
HEs = horticultural establishments.
42
-------
Table 2.22 Pesticide Usage Compared to Previous Years
Relative Amount Sample Number Estimated Number
of HEs of HEs of HEs
Same 446 12,654
Unknown 16 652
More: 72 2,540
More pest 25 1,452
More productlon/land/plants 29 792
Outside contractor 0 0
New pest control program 10 224
Lower cost 0 0
Other 8 69
Less: 40 1,437
Less pest 7 491
Less production/land/plants 8 493
Outside contractor 1 1
New pest control program 6 97
Higher cost 2 24
Other 16 331
Total 574 17,283
HEs - horticultural establishments.
43
-------
Table 2.23 Number of Horticultural Establishments (HEs) That Used
Records to Answer Product Usage Questions by Census Region
Reporting Sample Number Estimated Number
Domain of HEs of HEs
National
No records used 341 10,970
Records used 230 6,246
Census Region
Northeast
No records used 60 1,660
Records used 54 1,192
North Central
No records used 103 3,186
Records used 48 1,414
South
No records used 64 2,522
Records used 64 1,934
West
No records used 114 3,602
Records used 64 1,706
44
-------
REFERENCES
1. 1978 Census of Agriculture. Vol. 5, Part 7. 1979 Census of
Horticultural Specialties. Bureau of the Census, U.S. Department of
Commerce.
45
-------
APPENDIX A
SURVEY DESIGN AND STATISTICAL ANALYSIS
-------
Survey Design and Statistical Analysis
A.I Overview
This appendix includes descriptions of the four major statistical
components of the Pesticide Usage Survey Horticultural Specialties
Producers (PUSHSP). These four components are:
• Sample selection
• Sampling weight calculations
• Statistical analysis of the data
• Quality control.
Field activities such as recruitment of Interviews and supervision and
administration of the questionnaire were done by the American Association
of Retired Persons (AARP) and are not discussed in this report.
A.2 Survey Design
A.2.1 Target Population
The target population for the PUSHSP will consist of all horticultural
establishments (HEs) 1n the 48 coterminous States and the District of
Columbia that were operating 1n 1982. The 1979 Census of Horticultural
Specialties1 defines an HE as an operation that grows and sells $2,000 or
more worth of horticultural products In 1 year. This and other Census
definitions will be used to facilitate the survey in two ways: (1} to make
comparable the survey and the census Information and (2) to use definitions
and reporting categories that are familiar to establishments. The Census
defines the following nine nonmutually exclusive categories of
horticultural products:
I/ 1978 Census of Agriculture, Vol. 5, Part 7. 1979 Census of
Horticulture Specialties. Bureau of the Census, U.S. Department of
Commerce.
-------
• Potted flowering plants/cut flowers
• Bedding plants (Includes flowering, foliar, and vegetable types)
• Foliage plants
Sod
• Bulbs, corns, or rhizomes
• Nursery products (Includes plants, shrubs, trees, and other plants
usually used in landscaping)
• Vegetable and flower seeds
• Vegetables grown under cover.
The following additional comments about these categories are necessary for
clarification. Plants that were bought and resold within 30 days by
landscape businesses or garden center outlets, evergreens that were grown
and cut for use as Christmas trees, and cultivated mushrooms were excluded
in determining the eligibility of establishments.
HEs 1n Alaska, Hawaii, and other territorial properties were excluded
because the travel costs associated with field efforts in these areas were
deemed excessive compared with their expected contributions to the national
estimates.
A.2.2 Sample Selection
The PUSHSP survey design was a stratified two-phase, two-stage design
Intended to yield 1,060 samples distributed in approximately equal numbers
1n 103 primary sampling units (PSUs). The methods used to select each
stage and each phase are described below. The approaches were used
according to reasons given 1n the OMB Review package that was submitted
prior to conduct of the survey.
A.2.2.1 Selection of First-Stage, First-Phase Sample. The PSUs of
HEPUS are a subsample of the PSUs that were selected for the National
Household Pesticide Usage Survey (NHPUS). Using the NHPUS PSUs as a basis
A-3
-------
for the PUSHSP sample was judged to be the most efficient method of
obtaining a first-stage sample of counties or county equivalents for
PUSHSP.
The sampling frame used for NHPUS consisted of counties, county
equivalents, and their aggregates. This frame contained 3,062 PSUs that
were stratified by geographical areas (Census divisions), urbanization,
precipitation, temperature, and the ethnic composition of the population.
These factors were judged to be helpful 1n controlling the selection of
counties for the PUSHSP project for these reasons:
• The sample can be allocated by Census Regions to facilitate
desired sample sizes for regional estimates.
• Because the types and prevalence of pests often depend on climatic
factors such as precipitation and temperature, the types and
amounts of pesticides used in counties would also depend on the
same factors.
• The types and amounts of horticultural products produced were
considered to be related to both urbaniclty and ethnic composition
of the local markets and the type and level of pesticide usage.
In the NHPUS protocol, selection of the first-stage sample proceeded in
six steps:
1. Form the basic file of 3,109 counties (or equivalents) in the 48
coterminous States.
2. Augment the county-level characteristics for use 1n estimating
size measures (i.e., number of nonfarm housing units) and/or
defining frame stratification.
3. Estimate the number of nonfarm housing units in the counties.
4. Cluster the counties Into primary sampling units having at least
600 nonfarm housing units.
5. Indirectly stratify the frame via frame serpentining.
6. Select the first-stage sample.
A summary of the descriptors of particular Interest that were relative to
the first-stage design include:
A-4
-------
• Size measures were estimated based on the Advanced Reports of the
1980 Census of Population and Housing data and 1978 Census of
Agriculture data.
• The final first-stage frame contained 3,062 PSUs (3,017
single-county PSUs, 43 PSUs containing two counties each, and two
PSUs containing three counties each).
• Potential stratification (control) variables on the frame included
Standard Metropolitan Statistical Area (SMSA)/non-SMSA status,
Census Division, climatic division (Including average rainfall and
precipitation), and 1980 population counts by ethnic grouping.
• Frame serpentining was initially based on four categorical
variables: Census Division (nine levels), urbanidty (two
levels), climate (maximum three levels), and ethnicity (maximum
three levels). Frame units within the 83 cells so defined were
then sorted In alternating fashion by number of nonfami housing
units.
• Indirect strata were formed by selecting a starting point on the
serpentined frame at random and constructing 180 equal-sized zones
based on nonfarm housing units.
• One PSU per zone was selected with probability minimum replacement
(PMR), giving rise to 166 distinct sample PSUs.
• All sample PSUs were composed of a single county.
It should be noted that most of the auxiliary frame variables were
available only 1n hardcopy form. Moreover, PMR selection of the
first-stage sample guarantees that population domains defined at this level
are expected to be represented 1n proportion to their relative size. Frame
serpentining under a PMR selection procedure was Intended to reduce the
variability placed on controlling the realized sample sizes in each Census
Division, followed by control with respect to urban/rural, climate, and
ethnic composition. Such control 1s Intended to better guarantee the
separate estimates of major parameters of interest to the study that can be
made at the Census Division level. In addition, it was hoped to improve
the precision of study parameter estimates through the formation of more
homogeneous strata (i.e., Insofar as geographic location, climate,
urbanicity, and ethnicity Impact on the same).
A-5
-------
This section on first-stage sample selection concludes with the
following description of the selection of the 104 PSUs for HEPUS.
A.2.2.2 Selection of First-Stage, Second-Phase Sample. To select the
HEPUS subsample, the size measure TS(1)/NFHU(1) was used, where TS(i)
represents the total sales of horticultural products for PSU i and NFHU(i)
is the number of nonfarm housing units in PSU 1 (the size measure used in
NHPUS, 1=1,...,180. Selecting the subsample strictly by PMR using this
size measure would have resulted in several counties being allocated a very
large proportion of the sample of horticultural establishments. If the
strict PMR allocation were followed, a large sampling fraction within some
counties would have resulted in the same or similar information obtained on
usages within the county.
A compromise was employed by reducing the sampling rates within large
counties and thus freeing resources to collect data from additional
counties. The positive benefit is that data were collected from counties
that were geographically more dispersed and thus were more likely to differ
In climate, type of horticultural production, and pesticide usage. The
negative aspect is that by reducing the sampling rates in large counties,
the probability of an HE being selected 1s reduced and Its sampling weight,
if selected, 1s increased. The variance of parameter estimates will
increase because of the unequal weighting that results. The sampling
fraction was never reduced below 1/4 of the rate as that for PMR only.
To select the sample, the 180 PSUs were ordered using the same criteria
originally used in the NHPUS just described. The size measures were
modified by dividing by 1, 2, or 4 to reflect the desired reduced sampling
rate for the large counties. The frame was stratified by Census Region and
A-6
-------
the sample was selected by PMR with modified size measures. The sample
allocation and the number of distinct counties are given 1n Table A.I.
A.2.3 Selection of Second-Stage Sample
The selection of the second-stage sample Involved several steps. The
sampling frames for the PSUs selected were constructed using several
sources. The Membership Directory of the American Association of
Nurserymen (AAN) and the Dun and Bradstreet DMI computerized data file were
used to construct from two to six strata within each PSU. The
establishments 1n these first two to six strata represented from 50 to 90
percent of nursery product sales, depending on the county. To supplement
the DMI source, the State 11 censure and dealer 11st were used to construct
up to five additional strata. Table A.2 describes the 11 strata possible.
All 11 strata were required because of the multiple sources used 1n
constructing the second-stage frames. The DMI file and AAN list were used
to construct strata 11, 12, 13, 21, 22, and 23. Units from these sources
were assigned to the appropriate stratum depending upon their size measure
(If available) and the Standard Industrial Classification (SIC) codes (for
DMI file) or AAN code. State lists were used to supplement the DMI and AAN
sources for the remaining five strata. Units were assigned to strata 31
through 35 depending upon their size measure (1f available), SIC codes, or
classification on the State 11 censure 11st (1f available).
For the first six strata, lists were edited to minimize duplicate
listing to the extent feasible. The units selected for the last five
A-7
-------
Table A.I Summary of First-Stage Sample
Number of Number of
Stratum PSUs Allocated Distinct Counties
Northeast 25 19
North Central 25 20
South 26 22
West 27 18
Total 103 79
A-8
-------
Table A.2 Second-Stage Strata for HEPUS
Stratum Description
11 Self-representing, likely eUglbles
12 Not self-representing, likely eUglbles with
size measure
13 Not self-representing, likely eUglbles with no
size measure
21 Self-representing, possible eUglbles
22 Not self-representing, possible eUglbles with
size measure
23 Not self-representing, possible eUglbles with
no size measure
31 Not self-representing, likely eUglbles
(telephone screening component [TSC])
32 Not self-representing, possible eUglbles (TSC)
33 Likely/possible eUglbles (TSC)
34 Self-representing, likely eUglbles (TSC)
35 Self-representing, possible eUglbles (TSC)
A-9
-------
strata were compared with the frames for strata 11 through 23 to minimize
multiplicities to the extent feasible.
Units in self-representing strata (11, 21, 34, 35) were selected with
certainty; units in strata 12 and 22 were selected with probability
proportional to their size; and units in strata 13, 23, 31, 32, and 33 were
selected with equal probabilities. For sample units in strata 11 through
23, names, addresses, and telephone numbers were sent to AARP supervisory
personnel for distribution to the field. Units 1n strata 31 through 35
were first screened by telephone to inquire about eligibility before being
sent to the field.
A.3 Weight Calculation
The probability that a unit was selected in the sample was documented
for each stage and phase of selection. The sampling weight (W(s)) was
calculated for each unit (with minor exception) using the formula:
W(s) = W(l) W(2) W(3),
where W(l), W(2), and W(3) were the Inverse of the probability of selection
for stage one (phase one), stage one (phase two), and stage two,
respectively. The W(3)'s were adjusted to account for recognized
multiplicities.
The weight calculation for two HEs, ID numbers 7671 and 10851, were
modified from the above formula to adjust for their incorrect
classification. These two HEs were selected with a small probability In
the second stage because they were Incorrectly classified as small HEs.
Their second stage selection probabilities were changed to 1, making them
certainty units that more accurately reflect their size. This modification
of the weight introduces a statistical bias but should substantially reduce
the variance of estimates to which they contribute. Hence, the accuracy
A-10
-------
(as measured by mean squared error) of the estimates to which they
contribute should be Improved.
Analytical weights for each cooperating HE were calculated by ratio
adjusting the sampling weights for nonresponse within weighting classes.
The weight adjustments were done so that the sum of weights of cooperating
HEs would accurately approximate the number of eligible HEs In the target
population. The weight adjustments were done 1n two steps. The first step
adjusted the weights within each Census Division for successfully screened
sample units to compensate for those that refused screening or were not
screened for other reasons. The second step adjusted the weights for
cooperating HEs to compensate for eligible HEs that refuse to complete the
questionnaire. The weighting classes for the second adjustments were
defined by Census Division and second stage strata.
The weight calculations and adjustments were quality checked to reduce
errors and omissions to acceptable levels using standard Research Triangle
Institute (RTI) quality control procedures.
A.4 Quality Control
A comprehensive quality control procedure was Implemented to minimize
errors and omissions 1n the data resulting from implementation of the
HEPUS. The quality control procedures are discussed 1n detail In the HEPUS
Quality Assurance Plan.2
27 Pierson, S., and R. Lucas, 1983. National Nursery Pesticide Usage
Survey Quality Assurance Plan. Research Triangle Institute, Research
Triangle Park, NC 27709. RTI/2506/08-01F. Prepared for the Office of
Pesticide Programs, U.S. EPA, under contract 68-01646.
A-ll
-------
An additional Important quality control activity was performed to
enhance the accuracy and utility of the data because correct Environmental
Protection Agency (EPA) registration numbers (reg. nos.) were essential in
calculating the amounts of active Ingredients (AI) applied by the sample
HEs. To minimize errors due to incorrect or missing reg. nos., the reg.
nos. recorded on the questionnaire were computer matched with EPA computer
accessible data files containing reg. nos. and AI code and their percent.
Approximately 79 percent of the reg. nos. matched Initially. The
21-percent that did not match (Including Incorrect numbers and missing
data) were reviewed by an outside expert consultant who was able to make
educated judgments on the correct reg. nos. for approximately an additional
10 percent. Hence, a total of approximately 89 percent of the pesticide
data collected 1n the survey were usable In estimating total usage and
usage patterns. Hence, estimates of total usage derived from the data will
likely understate the true levels. The effects of the unknown registration
numbers on estimates such as means or proportions 1s likely to be less than
that of totals.
A.5 Statistical Analysis
The survey design and associated probability mechanism to select the
sample members in PUSHSP define the appropriate methods of statistical
analysis used in summarizing the data collected 1n the survey. The
estimates presented 1n Chapter 2 properly account for these factors. The
numerical calculation of the estimates and their variances would normally
be computed using existing software (SESUDAAN)3 specifically prepared for
37 Shah, B.V., 1979. SESUDAAN: Standard Errors Program for Computing of
Standardized Rates from Sample Survey Data. Research Triangle
Institute, Research Triangle Park, NC 27709. RTI/1789/00-01F.
A-12
-------
analysis of data collected using complex survey data. The formulae can be
obtained from the documentation for SESUDAAN. However, because of
modifications to the EPA computer Installation, the National Computation
Center, the existing software 1s not working. This precluded the
calculation of parameter variance estimates. The point estimates presented
in Chapter 2, totals and percentages, were calculated using Statistical
Analysis Software (SAS) programs. The formula used to estimate totals was:
T = E W(1) D(1) Y(1)
1=1
where W(1) was the analytical weight for the unit 1, Y(1) the response for
unit 1, D(1) an Indicator random variable taking on the values 0 or 1
depending 1f unit 1 1s in the domain of Interest or not, and n the number
of cooperating n HEs. Percentages were calculated by dividing
n
T by E W(1).
1=1
A-13
-------
APPENDIX B
NATIONAL NURSERY PESTICIDE USAGE SURVEY QUESTIONNAIRE
-------
OMB * 20700-0015
Expires-5/31/84
NATIONAL NURSERY PESTICIDE USAGE SURVEY
Field Assignment and Control Form ,
Control # _J
A. ASSIGNMENT INFORMATION
1. Firm Name:
2. Address:
3. Telephone: i_
4. Contact Person: _
Title:
Telephone: i_
B. RECORD OF CALLS
Day
of Week
Date
Mode
P T
P T
P T
P T
P T
P T
P T
P T
Time
am
pm
am
pm
am
pm
am
pm
am
pm
am
pm
am
pm
am
pm
Notes
Result
Code'
Initials
•Result Codes (CIRCLE THE FINAL RESULT CODE)
018 Questionnaire fully completed
026 Appointment made
117 Respondent not in; call back
121 Temporarily away
125 Refusal
133 Breakoff; partial data
198 Unable to locate
202 Unable to contact
237 Out of business
261 Ineligible
307 Other (Specify in notes above)
C. PRIOR TELEPHONE SCREENING RESULTS
This nursery was: D Previously screened by telephone D Not previously screened
B—2
-------
1. Does this firm engage in any horticultural production? By horticultural production I mean the
actual growth or production of plants, flowers, trees, sod or seeds, as opposed to a business
whose only horticultural activity is buying plants for immediate resale and/or use.
01 Yes
02 No - TERMINATE INTERVIEW AND SAY:
Thank you for your time, however since your firm is not involved in any horticultural produc-
tion we will not need to ask further questions for this study. I appreciate your cooperation and
time.
2. a. In which of the following horticultural activities was this firm involved during 1982? READ
EACH CATEGORY AND CIRCLE YES OR NO.
Yes No
1. Nursery production including bedding plants, foliage plants,
trees (flowering and shade), shrubs, and bulbs (exclude
2. Floral production including potted and cut flowers
3. Sod growing
4. Production of seed (flower and vegetable) and greenhouse
vegetables (for non-agricultural use only)
5. Landscape architecture/ maintenance (including plant rentals) .
6. Other (SPECIFY!:
01
01
01
01
01
02
02
02
02
02
b. Did this firm grow and sell at least $2,000 worth of horticultural products during 1982?
01 Yes
02 No - TERMINATE INTERVIEW AND SAY:
Thank you for your time, however since your firm's total horticultural sales are less than
$2,000 we will not need to ask further questions for this study. I appreciate your cooperation
and time.
B-3
-------
( 2548
Control #
3. Does this firm conduct any horticultural business, including wholesale or retail sales and/or
production, at any location other than this one?
01 Yes - SKIP TO Q.7 ON PAGE 4
02 No
4. Does this firm sell its horticultural products on a retail basis only, on a wholesale basis only,
or on both a wholesale and retail basis?
01 Retail Only
02 Wholesale Only
03 Both
5. I need to get some specific information about the pesticide products used by your firm in its
horticultural activities, such as the product names and EPA registration numbers, amounts
used, money spent for product purchase, pests being controlled, and so forth. Can you or
someone else supply this type of pesticide usage information for your firm?
01 RESPONDENT CAN SUPPLY ALL INFORMATION - SKIP TO Q.10 ON
PAGES
02 OTHER PERSON(S) OR SOME COMBINATION OF RESPONDENT AND
OTHER PERSON(S)
6. a. LIST NAMES OF ALL PERSONS WHOM YOU WILL NEED TO INTERVIEW IN ORDER
TO OBTAIN THE INFORMATION. FOR EACH PERSON LISTED, DESCRIBE THE
SPECIFIC BUSINESS SEGMENT(S) FOR WHICH THE PERSON WILL REPORT
PESTICIDE USAGE.
Reporting Segment
Name (Example: Greenhouses)
D i:
D 2.
b. Which of the above persons are available to provide this information? IN THE CHART
ABOVE, PLACE A CHECK IN THE BOX BESIDE EACH PERSON WHOM YOU WILL
INTERVIEW.
ARRANGE TO INTERVIEW PERSONS WHO ARE AVAILABLE, IN A GROUP IF POSSI-
BLE, OR IF NO, THEN SEPARATELY.
BEGIN INTERVIEW AT Q.10 ON PAGE 5.
B-4
-------
7. a. What are the names and addresses of these other locations? RECORD NAMES AND
ADDRESSES ON CHART BELOW. IF MORE THAN TWO OTHER LOCATIONS, USE
SEPARATE SHEET AND CHECK THIS BOX D.
b. Is horticultural production or wholesale or retail sales conducted there? CHECK ALL
THAT APPLY FOR EACH LOCATION ON CHART BELOW.
c. What percent of your firm's total horticultural production activities takes place at each of
these locations? RECORD PERCENT FOR EACH LOCATION ON CHART BELOW.
a. Name:
Address:
Location
b. D Horticultural Production
D Wholesale Sales
D Retail Sales
c. Percent of
Production
a. Name:
Address:
Location
b. D Horticultural Production
D Wholesale Sales
D Retail Sales
c. Percent of
Production
n
8. I need to get some specific information about the pesticide products used by your firm in its
horticultural activities at these locations, such as the product names and EPA registration
numbers, amounts used, money spent for product purchase, pests being controlled, and so
forth. Who would I need to speak with in order to get this type of pesticide usage information
for all your firm's locations?
01 RESPONDENT CAN SUPPLY ALL INFORMATION - SKIP TO Q.10 ON
PAGES
02 OTHER PERSON(S) OR SOME COMBINATION OF RESPONDENT AND
OTHER PERSON(S)
B-5
-------
9. a. LIST NAMES OF ALL PERSONS WHOM YOU WILL NEED TO INTERVIEW IN ORDER
TO OBTAIN THE INFORMATION. FOR EACH PERSON LISTED, DESCRIBE THE
SPECIFIC BUSINESS SEGMENT AND PHYSICAL LOCATION(S) FOR WHICH THE
PERSON WILL REPORT PESTICIDE USAGE.
Reporting Segment—
Activities and Locations
(Example: Greenhouses at
Name Locations 1 and 2)
D i.
D 2.
D 3.
b. Which of the above persons are available to provide this information? IN THE CHART
ABOVE, PLACE A CHECK IN THE BOX BESIDE EACH PERSON WHOM YOU WILL
INTERVIEW.
ARRANGE TO INTERVIEW PERSONS WHO ARE AVAILABLE, EITHER IN A GROUP
INTERVIEW OR SEPARATELY. FOR THE REST OF THE QUESTIONNAIRE, ALL
QUESTIONS WILL REFER TO THE BUSINESS SEGMENT(S) AND LOCATION(S)
IDENTIFIED IN Q.9 ABOVE.
BEGIN INTERVIEW AT Q.10 ON PAGE 5.
10. Were any chemical pesticides used in this firm's horticultural activities during 1982? Include
pesticides applied by other firms.
01 Yes
02 No - SKIP TO Q.25
11. Were any of these pesticides applied by you or other employees of this firm, as opposed to
being applied by a contractor or hired firm?
01 Yes
02 No - SKIP TO Q.20
Now I need to obtain specific information about the pesticide products used in your horticul-
tural activities during 1982, such as the names and EPA registration numbers of products, the
amounts used, and the money spent on pesticide purchases.
12. I am interested in obtaining this pesticide information for calendar year 1982, from January 1
to December 31. Is this information available for that time period?
01 Yes - SKIP TO Q. 14
02 No
13. For what time period can you supply this information?
B-6
to
-------
14. Now I'm going to ask you some questions about the types and amounts of various pesticides
which you use during the year. Hand handbook to respondent.
Reading from the list of pesticides, please tell me the names and numbers of any of those which
you used in the calendar year 1982. For each one used, I will ask you how much you use, where
you used it, etc. So could you first look at the insecticides.
FOR EACH SEPARATE PESTICIDE PRODUCT:
A. RECORD PESTICIDE CODE NUMBER IN COLUMN A.
B. RECORD EPA REGISTRATION NUMBER IN COLUMN B. IF EPA REGISTRATION NUMBER IS NOT AVAILABLE
RECORD PERCENT ACTIVE INGREDIENT, MANUFACTURER, BRAND NAME OR ANY OTHER IDENTIFYING
INFORMATION AVAILABLE.
I Read the column headings and record in the columns—after insecticides, go to fungicides, etc.
A
Pesticide
i>
Enter Code)
B
EPA Reg.
it
From Label)
C
:ormulanon
Code
inter Code *)
D
Concentration
Code
(Circle)
R C
R C
R C
R C
R C
R C
R C
K C
R C
R C
R C
R C
R C
R C
R C
R C
R C
R C
R C
R B-c?
E
Total
Amount
Unit Code
Fill in Unit Codes)
bs . gal , oz . etc.)
Green House
1
%
2.
Principal
Target Pests
3.
Times
•"
-------
C. LOOK AT FORMULATION CODE LIST. What code corresponds to the formulation of this product? RECORD CODE IN
COLUMN C.
D. Is this product a concentrate or ready-to-use? CIRCLE CODE IN COLUMN D. (READY-TO-USE = R; CONCEN-
TRATE = C)
E. To the best of your knowledge, what is the total amount of this pesticide that was applied by your firm during (1982 OR
TIME PERIOD)? (IF CONCENTRATE, ADD: Give me the actual amount used before the concentrate was mixed.) IN
COLUMN E ENTER AMOUNT AND THE CORRESPONDING MEASUREMENT UNIT CODE.
F. 1. What percent of the total amount used was applied to each of the following categories? READ EACH CATEGORY IN
COLUMN F AND ENTER PERCENTAGE.
2. FOR EACH CATEGORY WHERE APPLIED, ASK: What was the principal pest you were trying to control with this
product at (READ SITE CATEGORY). ENTER UP TO FOUR PEST CODES FOR EACH APPLICABLE SITE IN
COLUMN F. DO NOT UNDER ANY CIRCUMSTANCES ENTER MORE THAN FOUR CODES. IF THERE ARE
MORE THAN FOUR TARGET PESTS, HAVE RESPONDENT CHOOSE THE PRINCIPAL FOUR PESTS.
3. FOR EACH CATEGORY WHERE APPLIED, ASK: How many times during (1982 OR TIME PERIOD) was this
product applied to (READ EACH SITE CATEGORY). ENTER NUMBER FOR EACH APPLICABLE SITE IN
COLUMN F.
Control* f. £548
F
SITE USAGE CHART
Percent Applied. Target Pests, Times Applied
Outdoor Woody
2.
Principal
Target Pests
3.
Times
Floral and
Other Outdoor
1.
%
2.
Principal
Target Pests
3.
Times
Soil
1.
%
2.
Principal
Target Pests
3.
Times
Non-Horticultural
1
%
2.
Principal
Target Pests
3
Times
B-8
-------
15. Arc there any pesticide products applied by your firm during (1982 or TIME PERIOD) that we
have not listed?
01 No
02 Yes - FOR EACH ADDITIONAL PRODUCT REPEAT Q.14A-F
INTERVIEWER CHECKPOINT:
CHECK TO SEE THAT AT LEAST ONE ENTRY ON THE CHART HAS BEEN MADE FOR
EACH PESTICIDE CODE CHECKED BY THE RESPONDENT. ADD ANY MISSING PROD-
UCTS TO THE CHART BEFORE GOING TO THE NEXT SECTION.
16. Were any undesirable side effects associated with the use of any of these products during
(PERIOD)? This would include side effects to humans or plants? IF MORE THAN TWO SIDE
EFFECTS, USE SEPARATE SHEET AND CHECK THIS BOX D.
01 Yes - ASK FOR DESCRIPTION OF SIDE EFFECT(S); ENTER THE PESTICIDE
CODE NUMBER AND COMPLETE THE CHART BELOW.
02 No
Pesticide
Code DESCRIPTION
01 Plant Damage — Dollar Amount of Loss $ I I I I I
02 Nausea
03 Dizziness
04 Skin Rash
05 Other (SPECIFY)
01 Plant Damage — Dollar Amount of Loss $ I I I I I
02 Nausea
03 Dizziness
04 Skin Rash
05 Other (SPECIFY)
B-9
-------
17. Approximately how much money was spent during this time period for the purchase of
pesticides? Exclude money paid to contractors or outside firms for pesticide application.
ROUND TO NEAREST DOLLAR.
DK - Don't Know
I I I I DC £7""""" [Circle]
I I I I I RE - Refused L J
18. What percentage of this amount was for pesticides:
a. applied to horticultural products on your business's property?
i—-—,—- DK - Don't Know r~. . .
rm % RE - Refused fCirde]
b. applied to the property of others, for example, for landscape maintenance?
,—-—-—, DK - Don't Know ,„. . ,
rm % RE - Refused [CircIe]
c. purchased and later sold over-the-counter to other firms or individuals?
i—,—,—- DK - Don't Know ,„. . ,
FTTH % RE - Refused [Circle]
d. used in non-horticultural areas?
,—-—,—, DK - Don't Know .„. .
I I I I % RE - Refused [Circle]
19. Are you or any of your employees certified to apply pesticides?
01 Yes
02 No
20. Did this firm hire or contract with any firm(s) to apply pesticides for horticultural purposes to
any of its business locations during (PERIOD)?
01 Yes
02 No - SKIPTOQ.24
21. Did your firm furnish any of the pesticides applied by the other firm(s)?
01 Yes
02 No - SKIP TO Q.23
22. When you told me about your firm's pesticide usage earlier, did you include these pesticides
that your firm supplied to contractors?
01 Yes
02 No
B-10
-------
23. What was the total cost of this/these contract(s) with another/other firm(s) for (PERIOD)?
.Mill
24. During (1982 or TIME PERIOD) did you consult any of the following types of individuals or
materials about a pest problem you had? IF YES, PROBE FOR FREQUENCY AND CIRCLE
CODE.
Yes, Often
(More than Yes, Few
Category 5 times) (1-5 Times) Never
Salesperson or distributor 01 02 03
USDA bulletins 01 02 03
Extension specialist (university or county) 01 02 03
State association newsletter 01 02 03
Chemical company representative 01 02 03
Other nurserymen 01 02 03
Nursery magazines 01 02 03
Other (SPECIFY)
01 02 03
25. In recent years new methods for controlling pests have been developed which consist of inte-
grated plans using an optimal combination of biological, chemical, and nonchemical
methods. Some of these plans rely exclusively on biological and nonchemical methods, while
other plans incorporate chemical methods.
a. Did your firm rely solely on non-chemical, biological, or cultural pest control methods dur-
ing 1982?
01 Yes - GO TO C. ON FOLLOWING PAGE
02 No
b. Approximately what percentage of your pest control activities incorporate chemicals with
non-chemical, biological, or cultural pest control methods?
01 0 - 24%
02 25-49%
(Circle only one code)
03 50-74% _ ,,
B—11
04 75 - 100%
-------
c. Do you apply pesticides on a regular fb = i sched'da withou- record tc a p.iric'_Lar ixs:
problem?
01 Yas
02 No
d. Which of the following 1PM methods did your firm use?
01 Selection and timing of pesticides
01 Biorational or biological controls
01 Cultural control methods (Circle all that apply)
01 Monitoring or scouting
01 Other (SPECIFY)
26. During (1982 OR TIME PERIOD) did you have any pest problems for which no effective con-
trol methods were available?
01 Yes
02 No - SKIP TO Q.28
27. What were the problem pests and what plants were being affected? What was the estimated
dollar loss because no effective control existed?
Pests Plants Affected Dollar Loss
(Wholesale
replacement
costs only)
$
$
$
$
B-12
-------
28. Now I'd like to ask a few financial questions in order to characterize your business in relation
to other nursery businesses. This information, as with all information you have given me, will
be held in strict confidence.
Is this firm a partnership, corporation, or sole proprietorship?
01 Partnership
02 Corporation
03 Sole proprietorship
04 Other (SPECIFY)
29. What was the approximate total gross revenues for this business during 1982? Tell me which
revenue category applies to this business. CIRCLE ONE CODE. REMEMBER TO OBTAIN
REVENUE AMOUNT ONLY FOR THE ACTIVITIES/LOCATIONS LISTED IN Q.6 OR Q.9.
01 Less than $25.000
02 $25,000 to $49,999
03 $50,000 to $99,999
04 $100,000 to $499,999
05 $500,000 to $999,999
06 Above $1 million
07 REFUSED [DO NOT READ. Check only after respondent refuses.]
30. What percent of this revenue was from horticultural sales?
-I—| DK - Don't Know r~. . .
JJ % RE - Refused [Cirde]
31. Has this firm been involved in a split or merger involving another firm since January 1, 1982?
01 Yes
02 No
B-13
-------
32. I need some specific information about your firm's activities. [REMEMBER TO OBTAIN THIS
INFORMATION ONLY FOR THE ACTIVITIES/LOCATIONS LISTED IN Q.6 OR Q.9]
a. How many greenhouses do you have? Include plastic and glass covered greenhouses as
well as coldframes.
Greenhouses
b. How much ground space is covered by these greenhouses?
-i |—I 01 Square Feet
J.I I 02 Acres
c. How much growing space do you have in open areas?
1 1 | i i i I i—1 01 Sc*uare
I I I I I I I . LJ 02 Acres
33. Have you used about the same amount of pesticides this year as you did during each of the
previous three years?
01 Yes
02 No - Kxpl.iin
34. a. Did you use records to answer the product usage questions?
01 Yes -
02 No - (SKIP B. BELOW)
b. What records or information sources did you consult?
01 Purchase Records
02 Usage Records
03 Inventory Records
04 Other (SPECIFY)
(NORMAL END)
We have come to the end of my questions. Thank you very much for your cooperation and time. (Go
to Records or place where pesticides are stored and obtain EPA Registration Numbers.)
B-14
-------
APPENDIX C
USER FILE DOCUMENTATION
-------
User File Documentation
C.I Overview
This appendix describes the user file constructed for the PUSHSP. The
proper analysis and Interpretation of data on this file depends on an
understanding of the sample design, the survey questionnaire, and the data
editing after the data has been collected. Potential users of this file
are strongly urged to review the questionnaire (see Appendix B) and other
sections of this report prior to performing analyses.
The user file 1s stored on-line at Environmental Protection Agency's
(EPA's) National Computing Center 1n DSN=FWIBFSD.NNPUS.SAS.USERFILE and 1s
partitioned Into five SAS datasets, as shown in Table C.I. The
five-dataset configuration was chosen for ease of use and to decrease the
amount of redundant Information and storage requirements for the file. The
datasets can be merged by using record Identification (ID) variables
created specifically for this purpose (see Table C.2). The ID variable 1s
an arbitrary, unique Identifier of a sampling unit; the AIJ.INK variable
identifies a single line of response to Question 14 (e.g., each product
reported by a respondent was assigned an arbitrary AI_LINK number).
Some nurseries were represented 1n the sample by more than one sampling
unit and are therefore represented on the datasets by multiple records. To
obtain accurate, unweighted counts or estimates, it is therefore necessary
to subset the datasets to a single record per respondent. This can be done
by removing the last digit of the ID (e.g., NEWID=INT (ID/10;) and keeping
only one record per NEWID (e.g., DATA WORK2; SET WORK1, BY NEWID; IF
FIRST.NEWID;).
-------
Table C.I SAS Datasets in the Horticultural Establishment Pesticide Usage Survey User File
o
i
to
SAS
dataset name
PRODUCTS
AIAMTS
Record-level
Product within sampling
unit
Active ingredient within
Number of
observations
7289
7893
Sorted
ID, AI_
ID, AI_
by
LINK
LINK
General description
Data from Question 14.
Active ingredient
MAINQUEX
SIDE EFF
PROBPEST
product within sampling
unit
Sampling unit
Product within sampling
unit
Pest within sampling unit
671
70
184
ID
ID, AIJLINK
ID
amount for products
assigned valid EPA
registration numbers.
Data from most fixed
length nonusage ques-
tions .
Data from Question 16.
Data from Question 27.
-------
Table C.2 Variables for Merging the SAS Datasets 1n the
Pesticide Usage Survey of Horticultural Specialties Producers User File
Dataset 1 Dataset 2 Merge by
PRODUCTS AIAMTS ID, AIJ.INK
PRODUCTS MAINQUEX ID
MAINQUEX PROBPEST ID
PRODUCTS SIDE_EFF ID, AIJ.INK
C-4
-------
Only observations for eligible, cooperating respondents are Included in
the datasets. The nonresponse-adjusted weight is included on the PRODUCTS,
AIAMTS, and MAINQUEX datasets as the variable WEIGHT and can be used to
compute weighted totals and proportions.
The following sections provide detailed descriptions of the datasets.
C.2 Datasets
C.2.1 The PRODUCTS Dataset
This dataset contains one observation for each product reported in
Question 14 by an eligible, cooperating respondent. Variables on this file
are listed in Table C.3. The pesticide and target pest codes shown in
Exhibit C-l are identical to those that were used by the field
Interviewers. The meanings of the CONFID and UNITCODE codes are given 1n
Table C.4
C.2.2 The AIAMTS Dataset
For each observation on the PRODUCTS dataset having an EPA registration
number matching an entry in the EPA product database, there are one or more
active ingredient-level observations on the AIAMTS dataset that give the
pounds of active Ingredient corresponding to the reported usage. The
transformation of the reported product usage into pounds of active
ingredient usage was accomplished by first standardizing the product usage
to units of pounds and then applying the percent active Ingredient
information (variable PERCENT) from the EPA database. Standard EPA active
ingredient codes are used to Identify active ingredients 1n this dataset
(variable AICODE); the variables are listed in Table C.5.
C.2.3 The MAINQUEX Dataset
Most of the nonusage questions (I.e., questions other than Question 14)
are represented on this dataset. Table C.6 lists the variables 1n this
dataset. In general, the codes used for the variables are identical to the
C-5
-------
Table C.3
CONTENTS OF SAS DATA SET PRODUCTS
TRACKS USED=7S SUBEXTENTS=1 GBSERVATIONS=72S9 CREATED BY OS JOB FWINURS ON CPUID 03-3081-O22779
AT 13:36 FRIDAY. SEPTEMBER 23, 1984 BY SAS RELEASE S2.4 DSNAME=FUIBFSD.NNPUS.SAS.USERFILE BLKSIZE=19016 LRECL=196
OBSERVATIONS PER TRACk=97 GENERATED BY PROC SORT
ALPHABETIC LIST OF VARIABLES
« VARIABLE TYPE LENGTH POSITION FORMAT INFORMAT LABEL
NO. TO LINK AI RECORD TO REG.NUM RECORD
REPORTED AMOUNT
PRODUCT AMOUNT IN POUNDS
CENSUS REGION
CONCENTRATION CODE
CONFIDENCE CODE FOR REG-NUM
FLORAL AND OTHER OUTDOOR: TARGET PEST 1
FLORAL AND OTHER OUTDOOR:
FLORAL AND OTHER OUTDOOR:
FLORAL AND OTHER OUTDOOR:
FLORAL AND OTHER OUTDOOR:
FLORAL AND OTHER OUTDOOR:
FORMULATION CODE
GREEN HOUSE: TARGET PEST 1
GREEN HOUSE: TARGET FEST 2
GREEN HOUSE: TARGET PEST 3
GREEN HOUSE: TARGET PEST 4
GREEN HOUSE: PERCENT
GREEN HOUSE: TIMES APPLIED
UNICUE SAMPLING UNIT IDENTIFIER
NON-HORTICULTURAL: TARGET PEST 1
TARGET PEST 2
TARGET FEST 3
TARGET PEST 4
PERCENT
TIMES APPLIED
39
4
41
42
3
38
19
10
il
22
13
23
•^
7
? S
01 9
10
6
11
44
31
32
33
34
30
35
37
13
14
15
16
12
17
1
•Ji,
Z5
26
27
28
_1
1?
40
5
43
AI_LINK
AMT
AMTLBS
CENREG
CONC
CONFID
FOOP1
FOOP2
FOGF3
FOOF 4
FOOPCT
FOOTA
FORK
GHP1
GHP2
GHP3
GHP4
GHPC T
GHTA
ID
NHP1
NHP:.-
NHP3
NHP4
NH(- C T
NUT A
OREG_NUM
OWP1
OWP2
OWP3
OWF4
OWFCT
OWTA
PC ODE
hkG_NUM
£P1
£P2
SP3
SP4
•It LT
Slfi
UN I TC ODE
UNI IS
WEIGHT
NUM
NUM
NUM
NUM
CHAR
NUM
CHAR
CHAR
CHAR
CHAR
NUM
NUM
NUM
CHAR
CHAR
CHAR
CHAR
NUM
NUM
NUM
CHAR
CHAR
CHAR
CHAR
NUM
NUM
NUM
CHAR
CHAR
CHAR
CHAR
NUM
NUM
CHAR
NUM
CHAR
CHAR
CHAR
CHAR
NUM
NUM
NUM
CHAR
NUM
3
S
S
*>
2
2
4
4
4
4
8
f*
2
4
4
4
4
8
*-t
3
4
4
4
4
8
•>
6
4
4
4
4
e
2
3
S
4
4
4
4
e
^
2
5
S
170
11
175
183
9
16S
S4
33
92
96
76
100
7
32
36
40
44
24
43
193
136
140
144
143
123
152
162
53
62
66
70
50
74
4
154
110
114
US
122
102
126
173
19
135
TARGET PEST 2
TARGET PEST 3
TARGET PEST 4
PERCENT
TIMES APPLIED
NON-HORTIC UL TUR AL:
NON-HORTIC ULTURAL s
NON-HORTICULTURAL:
NON-HORTICULTURAL:
NON-HORTICULTURAL:
REPORTED EPA REGISTRATION NUMBER
OUTDOOR WOODY: TARGET PEST 1
TARGET PEST 2
TARGET PEST 3
TARGET PEST 4
PERCENT
TIMES APPLIED
OUTDOOR WOODY:
OUTDOOR WOODY:
OUTDOOR WOODY:
OUTDOOR WOODY:
OUTDOOR WOODY:
PESTICIDE CODE
ANALYSIS EPA REGISTRATION NUMBER
SOIL: TARGET PEST 1
TARGET PEST 2
TARGET FEST 3
TARGET PEST 4
PEftCliMT
TII1IIL APPLIED
STANDARDIZED UNIT CODE
REPORTED UNITS
NONNESPONSE- ADJUSTED SAMPLING WEIGHT
SOIL:
SOIL:
SOIL:
•i.O IL:
-------
Exhibit C-l
HANDBOOK OF PESTICIDES
AND TARGET PESTS
A. INSECTICIDES
B. FUNGICIDES
C. HERBICIDES
C-7
-------
Exhibit C-l (continued)
A. Insecticides
Trade Name
A-l Cythion
A-2 Malathion
A-3 Sevin
A-4 Spectracide
A-5 Diazinon
A-6 Orthane
A-7 Lindane
A-8 Cygon
A-9 Dimcthodate
A-10 Dicofol
A- 11 Kelthane
A-12 Metasystox
A-13 Temik
A-14 Dipel
A-l 5 Thuricide
A-l 6 Pentac
A-17 Marlate
A-l 8 Methoxychlor
A-19 Systox
A-20 Plictran
A-21 Guthion
A-22 Karathane
A-23 Dursban
A-24 Thiodan
A-25 Tiovel
Common Name
malathion
malathion
carbaryl
diazinon
diazinon
acephate
lindane
dimethoate
dimethoate
dicofol
dicofol
•
oxydemeton-methyl
aldicarb
bacillus thuringiensis
bacillus thuringiensis
dienochlor
methoxychlor
methoxychlor
demeton
cyhexatin
azinphas-methyl
dinocap
chlorpyrifos
endosulfan
endosulfan
Trade Name
A-26 Omite
A-27 Vendex
A-28 Toxaphene
A-29 Vydate-L
A-30 Pirimor
A-31 Lannate
A-32 Nudrin
A-33 Morestan
A-34 Ethion
A-35 Synthrin
A-36 Dylox
A-37 Proxol
A-38 Disyston
A-39 Bladafum
A-40 Dithione
A-41 Imidan
A-42 Superior Oils
A-43 Dormant Oils
A-44 VolckOils
A-45 Ambush
A-46 Pounce
A-47 Pramex
A-48 Enstar
A-49 Mesurol
A-50 Methyl Bromide
Common Name
propargite
fembutatin-oxide
toxaphene
oxamyl
pirimicarb
methomyl
methomyl
oxythioquinox
ethion
resmethrin
trichlofon
trichlofon
disulfoton
sulfotepp
sulfotepp
phosmet
petroleum oils
petroleum oils
petroleum oils
permethrin
permethrin
permethrin
Kinoprene
mercaptodimethur
bromomethane
C-8
-------
Exhibit C-l (continued)
Trade Name
A-51 Zectran
A-52 Dyfonate
A-53 Dymet
A-54 Thimet
A-55 Parathion
A-56 Penncap M
A-57 Methyl Parathion
A-58 Baam
A-59 Arscnate of Lead
A-60 Furadan
A-61 Trithion
A-62 Acaraben
A-63 Sumithion
A-64 Dasanit
A-65 Metaldehyde
A-66 Azodrin
A-67 Dibrom
A-68 Zolone
A-69 Phosphamidon
A-70 Rotenone
A-71 TedionV-18
Common Name
mexacarbate
fonofos
dymet
phorate
parathion
methyl parathron
(encapsulated)
methyl parathion
amitraz
arsenate of lead
carbofuran
carbophenothion
chlorobenzilate
fenitrothian
fensulfothion
metaldehyde
monocrotophos
nalid
phosalone
phosphamidon
rotenone
tetradifon
A-73 Other (specify)
r.-i
Insects
A-76
A-77
A-78
A-79
A-80
A-81
A-82
A-83
A-84
A-85
A-86
A-87
A-88
A-89
A-90
A-91
A-92
A-93
A-94
A-95
A-96
A-97
A-98
A-99
A-100
A-101
Aphids
Bagworms
Beetles
Borers
Caseborers
Clearwing Moths
Curculios
Cutworms
Fruit Flies
Leaf Cutters
Leaf Hoppers
Leaf Miners
Leaf Rollers
Mealy Bugs
Mites
Pear Psyllids
Root Worms
Sawflies
Scales
Spittlebug
Thrips
Webworms
Weevils
Whiteflies
Wireworms
Other
-------
Exhibit C.I Handbook of Pesticides and Target Pest (continued)
A102 Mollusks (slugs, snails, etc.)
A103 Nematodes
A104 Other Worm
A105 Caterpillar/centipede
A106 Rodents (mice, rabbits, etc.)
A107 Ants
A108 Deer
A109 Midges
A110 Fungus Gnat
Alll P111 Bugs
C-10
-------
Exhibit C-l (continued)
B. Fungicides
Trade Name
B-l Benlate
B-2 Captan
B-3 Amobam
B-4 Dithane M-45
B-5 Fore
B-6 Manzate
B-7 Dithane Z-78
B-8 Polyram-Z
B-9 Carbamate
B-10 Terrazole
B-ll Truban
B-12 Agrimycin
B-13 Agri-strep
B-14 Terraclor
B-15 Bancot
B-16 Bravo
B-17 Daconil2787
B-l 8 Dixon
B-l 9 Lesan
B-20 Tri-Basic Copper
Sulfate
B-21 Kocide
B-22 Cyprex
B-23 Acti-dione
B-24 Ridomil
B-25 Subdue 5SP
B-26 Plantvax
Common Name
benomyl
captan
amoban
mancozeb
mancozeb
maneb
zineb
zineb
ferbam
terrazole
ethazol
streptomycin
streptomycin
PCNB
bancot
chlorothalonil
chlorothalonil
fenaminosulf
fenaminosulf
copper sulfate, basic
copper hydroxide
dodine
cycloheximide
metalaxyl
metalaxyl
oxycarboxin
Trade Name
B-27 Formaldehyde
B-28 Formalin
B-29 Rovral
B-30 Chipco 26019
B-31 Botran
B-32 Citcop4E
B-33 Triforine
B-34 Funginex
B-35 Phaltan
B-36 Bordeaux
mixture
B-37 Tusan75
B-38 Thylate
B-39 Bayleton
B-40 Difolatan
B-41 Karathane
B-42 Lime Sulfur
B-43 Pipron
B-44 COCS
B-45 DowfumeMC-2
Common Name
methanal
methanal
iprodione
iprodione
DCNA
copper resinate
triforine
triforine
folpet
hydrated lime/
copper sulfate
thiram
thiram
triadimefon
captafol
dinocap
calcium polysulfides
piperalin
copper oxychloride
sulfate
methyl bromide/
chloropicrin
B-46 Dowfume MC-33 methyl bromide/
chloropicrin
B-47 Morsedren
B-48 Du-Ter
methyl mercury
triphenyltin hydroxide
B-49 Other (specify)
C-ll
-------
Exhibit C-l (continued)
Diseases
B-50 Anthracnose
B-51 Bacterial Wilt
B-52 Bark Canker
B-53 Black Knot
B-54 Botrytis
B-55 Brown Rot
B-56 Crown Gall
B-57 Crown Rot
B-58 Damping Off
B-59 Dieback
B-60 Downy Mildew
B-61 Fire Blight
B-62 Fusarium Wilt
B-63 Hairy Root
B-64 Leaf Blight
B-65 Leaf Scorch
B-66 Leaf Spot
B-67 Needle Blight
B-68 Needle Cast
B-69 Needle Rust
B-70 Orange Rust
B-71 Petal Blight
B-72 Phytophtora
B-73 Powdery Mildew
B-74 Pythium
C-
Diseases
B-75 Root Rot
B-76 Rust
B-77 Rust Gall
B-78 Stem Rot
B-79 Stem Canker
B-80 Trunk Canker
B-81 Twig Blight
B-82 Twig Canker
B-83 Verticillium Wilt
B-84 Witches' Broom
B-85 Other (specify)
2
-------
Exhibit C-l (continued)
C. Herbicides
Trade Name
C-l Roundup
C-2 Princep
C-3 Ronstar
C-4 Treflan
C-5 Paraquat
C-6 Casoron
C-7 Surflan
C-8 2,4-D
C-9 Dacthal
C-10 Devrinol
C-ll Kerb
C-12 Dymid
C-13 Enide
C-14 Dowpon
C-15 Estam
C-l 6 Lasso
C-17 Aatrex
C-18 Pramitol
C-19 Diquat
C-20 Trimec
C-21 Banvel
C-22 Phytar560
C-23 Rad-E-Cate25
C-24 MSMA
Common Name
glyphosate
simazine
oxadiazon
trifluralin
paraquat
dichlobenil
oryzalin
2,4-D
DCPA
napropamide
pronamide
diphenamid
diphenamid
dalapon
EPTC
alachlor
atrazine
prometon
diquat
2,4-D/ mecoprop/
dicamba
dianat
cacodylic acid
cacodylic acid
MSMA
Trade Name
C-25 Basagran
C-26 Tupusan
C-27 Karmex
C-28 Hyvar
C-29 Goal
C-30 Tenoran
C-31 Spike
C-32 Cytrol-
Amitrole-T
C-33 Furloe
C-35 Weedor
C-36 Endothal
C-38 Lorox
C-39 Dual
C-40 Tok
C-41 Asulox
C-42 Balan
C-43 Dinitro
C-44 Premerge
C-45 Vapam
C-46 Amizine
C-47 Animate
C-48 Modown
Common Name
bentazon
siduron
diuron
bromacil
oxyfluorfen
chloroxuron
tebuthiuron
amitrole
chloropropham
C-34 Chloro-IPC chloropropham
MCPA
endothal
C-37 BromOgas methyl bromide
C-25 Basagran
bentazon
C-49 Amiben
linuron
metolachlor
nitrofen
asulam
benefin
dinoseb or DNBP
dinoseb or DNBP
metam-sodium
amitrole/princep
ammonium sulfamate
bifenox
chloramben
C-13
-------
Exhibit C-l (continued)
Trade Name
Common Name
C-50 Telone
dichloropropene
C-51 Velpar
hexazinone
C-52 Sencor
metribuzin
C-53 Planavin
nitralin
C-54 Other (specify)
C-]
Weeds
C-60 Pre-emergence • annual grasses
C-61 Pre-emergence - annual weeds
C-62 Annual grasses - summer
C-63 Annual grasses - winter
C-64 Annual broadleaf weeds - summer
C-65 Annual broadleaf weeds • winter
C-66 Perennial grasses
C-67 Perennial broadleaf weeds
C-68 Digitarius (Smooth Crab. Soft Crab)
C-69 Goose grass (Head Crab, Crow's Foot,
Silver Crab)
C-70 Poison Ivy
C-71 Mustard
C-72 Wild Onion (Garlic)
C-73 Other (specify)
-------
Table C.4 Description of the CONFID and UNITCODE Variables
Variable
Code
Definition
CONFID
1
2
3
4
5
No Imputation possible, due to lack of
data
Imputation assumed to be perfect*
Some doubt about accuracy of Imputation
Substantial doubt about accuracy of
Imputation
Imputation considered to be "generic"
Imputation done by RTI to make assignments
consistent
No Imputation done, reported reg. number
looks o.k. but doesn't match EPA product
files
No Imputation done, reported reg. number
matches EPA product files
UNITCODE 1
2
3
4
5
6
7
8
9
Fluid ounces
Gallons
Pounds
Dry ounces
Pints
Quarts
Tablespoons
Teaspoons
Tons
*The imputed registration number is assumed to be the registration number
of the product used by the respondent.
C-15
-------
Table C.5
CONTENTS OF SAS DATA SET AIAMTS
TRACKS U£ED=::i £UtEXTENTS=l OBSERVATIONS=7393 CREATED BY OS JOB FWINURS ON CPUID 03-3031-022779
flf li: I-.A FRI1JAY. SEPTEMBER 2S. 1*S4 BY SAS RELEASE 82.4 DSNAME=FWIBFSD.NNPUS.SAS.USERFILE BLKSI ZE=19OAO LRECL=43
FER ihh>CK=o"'7 GENERATED BY PROC SORT
ALPHABETIC LIST OF VARIABLES
« VARIABLE TYPE LENGTH POSITION FORMAT INFORMAT LABEL
HO. TO LINK AI RECORD TO REG_NUM RECORD
STANDARD EPA ACTIVE INGREDIENT CODE
FOUNDS OF ACTIVE INGREDIENT
CENSUS REGION
UNIQUE SAMPLING UNIT IDENTIFIER
PCT BY WEIGHT OF AI IN THE FKODUCT
ANALYSIS EPA REGISTRATION NUMBER
NfiNRESPONSE-AP. IUSTEFI SAMKLI Mr. WFIGHT
JL'
-.
*j
t,
s
4
1
7
AI_LINI:
AICODE
A1L13S
CENREG
Ui
PERCENT
REG-MUM
WEIGHT
NIJM
NUM
NIJM
NUM
NUM
NIJM
NUI1
NIIM
3
4
S
-t
3
S
S
S
12
15
27
:-.5
45
19
4
37
o
I
-------
Table C.6
o
i
CONTENTS OF SAS DATA SET MAINOUEX
1 HACKS UEED-17 SULEXTENTS=1 OG£ERVATIONS=671 CREATED BY OS JOB FW1NURS ON CPUID 03-3081 -022779
m 13:3.6 FRIDAY. iEF'TEI-lbER 28, 19.S4 BY SAS RELEASE 32.4 DSNAME=FWIbFSD. HNF-US. SAS. USERFILE BLi:SIZE=13967 LRECL=441
I'BiERVATlONi PER TRACI.-='*: GENERATED BY PROC SORT
ALPHABETIC LIST OF VARIABLES
II VARIABLE TYPE LENGTH POSITION FORMAT INFORMAT LABEL
CENSUS REGION
UNIOUE SAMPLING UNIT IDENTIFIER
NUMBER OF SEPARATE LOCATIONS
NUMBER OF PRODUCTION LOCATIONS
SALES:RETAIL/WHOLESALE/BUTH
ANY PESTICIDE USAGE"
WERE PESTICIDES APPLIED BY YOU •>
10 INFO AVAILABE FOR ALL OF 1932 ?
ANY EMPLOYEES CERT 10 APPLY PESTICIDES ~'
ANY OUTSIDE CONTRACTOR APPLICATIONS'1
DID YOU FURNISH FES1CDES FOR CONTRACTOR''
DID YOU INCLUDE PESTICDE LISAGC EARLIER "
UNCONTROLLABLE PEST PROBLEMS''
PARTNERSHIP/CORP/SOLE PROPIETORSHIP
TOTAL GROSS REVENUES
X GROSS REVENUE PROM HORTICULTURAL SALE
BEGINNING MONTH FOR DATA
END I ML. MONTH FOR DATA
BEGINNING YEAR FOR DATA
ENDING YEAR FOR DATA
•/. APPLIED TO HORT PRODUCTS
•/. APPLIED TO THE PROPERTY OF OTHERS
•/. PURCHASED & LATER SOLD OVER Fl IE COUNTER
X USED IN NON-HORTICULTURAL AREAS
NURSERY PRODUCTION
FLORAL PRODUCTION
SOD GROWING
SEED PRODUCTION
LANDSCAPE ARCHITECTURE/MAINTENANCE
OTHER
CON'SULTN WITH SALESPERSON OR DISTRIBUTOR
CONSULTN WITH USDA BULLETINS
CONSULTN WITH EXTENSION SPECIALIST
CONSULTN WITH STATE ASSOt NEWSLETTER
CONSULTN WITH Cl IEM CO REP
CONSULTN WITH OTHER NURSERYMEN
CONSULTN WITH NURSERY MAGAZINES
CONSULTN WITH OTHER-CODED CATEGORY
CUNSULTN WITH OTHER FREQUENCY
RELY bOLELY ON NLiNCHCMICAL METHODS ~-
7. Ft ACTIVITIES USING CHIIMICAL METHODS
REGULAR,FIXED APPLICATION SCHEDULE ~'
IPM METHODS-';LLbL IN {. TIMING OF FSTCDS
IPM METHODS-BIOLOGICAL CONTROL?
1TI1 METHODS-CULTURAL CONTROL MEIHUD:.
ir-M METHOriS-MONJTOKINr, OR ICuUTING
ll'M METHOUa-UIHtR
SAME AMOUNT OF USE AS LAST YCAR '•
EXPLANATION FOR NEGATIVE O33 RESPONSE
USE OF RECORDS TO ANS PROD U:fi.jE O "
CATEGORIZED 1'ESTICIDE PURCHASING COET
CATEGORIZED CONTRACTOR COSTS
CATEGORIZED NUMBER OF GKLLNHGUSES
CATLGLiKIZCD &KULNIIUU..L .[ACE.
t/ilL'-OM/LlJ Ul LN (II.L/. ijUOWlNG OT-AI.C
riniiKi • rrnj I.-MKJII ill" .r.Mi L IN'. wiIlGin
S4
56
47
43
7
S
•:;
10
I-"'
I'O
11
1.*^.*
40
41
41'
45
11
13
12
14
15
16
17
13
1
2
3
4
5
6
^3
24
^5
26
27
23
2"?
30
31
3.2
S3
34
S5
?6
37
35
S9
44
45
46
49
50
&1
i*!.1
S3
1 •
CCNRCG
I LI
LOCA'INi
PROD_LOC
O4
010
Oil
OH'
or;
ceo
021
O22
016
CIS
cc--'
0^0
013M1
0 1 J.M2
013Y1
013Y2
018-1
O1S_2
O1S_3
01S_4
02A1
02A2
02A3
02A4
02A5
02A6
O24_l
024 _2
O24_3
024_4
O24_5
024_6
O24_7
024 _S
O24_9
OZ5A
025B
02T-C
025D1
025lii
02t.US
02-;.Li4
C'i'JDS
OSSA
033B
034 A
RO17
RO1 3
RO32A
R032D
R0.3IC
i ii i rii r
NUM
NUM
NUM
NUM
NUM
NUM
NUM
NUM
NUM
NUli
IJUM
NUM
NUM
NUM
NUM
NUM
NUM
NUM
NUM
NUM
NUM
NUM
NUM
NUM
NUM
NUM
NUM
NUM
NUM
NUM
NUM
NUM
NUM
NUM
NUM
NUM
NUM
NUM
NUM
NUM
NUM
NUM
NUM
NUM
NUM
NUM
NUM
NUM
Nur-
NUM
NUM
NUM
NUM
NUM
NUM
Ml IM
o
3
S
S
«_•
3
3
S
o
S
S
S
S
S
S
S
S
S
3
8
S
S
S
S
3
8
8
8
S
8
S
8
8
S
S
8
8
S
S
8
S
8
S
8
8
8
S
£
S
S
8
S
&
S
3
f.
413
4?G
372
c-eo
52
dO
63
76
143
156
164
172
316
324
332
340
&4
1OO
92
1OS
116
124
132
140
4
12
20
23
36
44
ISO
183
19*>
2O4
212
220
223
236
144
151'
240
263
276
234
292
300
303
343
356
364
3&S
396
404
4\2
420
/|-n
-------
codes used in the questionnaire, but the following variables depart from
this rule:
• LOCATNS. This variable was created based on the responses to
Questions 3 and 7 and reflects the number of distinct locations
reported on by the respondent.
• PROD LOG. This variable was also created based on the responses
to Questions 3 and 7 and indicates the number of locations at
which there is some horticultural production. Production is
assumed to occur at the location at which the respondent was
interviewed.
04. The codes used for this variable are those shown in the
questionnaire, but were set based on responses over all locations
reported on.
• RQ1Z. To better protect respondent confidentiality, responses to
Question 17 were categorized and are reported as codes by this
variable. The definitions of the codes are given in Table C.7.
• RQ21. Coded responses to Question 23 are reported by this
variable, and the definitions are provided in Table C.7.
• Q2i_S. Responses to the "other" section of Question 24 were
categorized using the definitions shown 1n Table C.8 and are
reported by this variable.
• RQ22A. These were coded responses to Question 23a; the
definitions are provided 1n Table C.9.
• RQ22B. Responses to Question 23b were standardized to square
feet, then categorized using the definitions 1n Table C.9. Coded
responses are given by this variable.
• RQ32£. Responses to Question 23c were also standardized to square
feet. The coded responses reported by this variable are defined
in Table c.9.
C.2.4 The SIDE_EFF Dataset
This dataset contains the responses to Question 16. Information
provided in Question 16 was compared with and linked to particular Question
14 responses and the corresponding REG_NUM assigned to the record. The
variables in the dataset are shown In Table C.10. Each side effect
variable (I.e., PLANT, NAUSEA, DIZZY, SKINRASH, and OTHER) is coded "1", if
the respondent Indicated that 1t has occurred, or "0", otherwise.
C-18
-------
Table C.7 Codes for Categorized Sales Variables
Variable Code Definition
RQ17 0 Missing Data
1 $0 - $100
2 $101 - $500
3 $501 - $1,000
4 $1,001 - $5,000
5 $5,001 - $10,000
6 $10,001 -$50,000
> $50,000
RQ32 0 Missing Data
1 $0 - $250
2 $251 - $500
3 $501 - $1,000
4 $1,000 - $5,000
5 $5,001 -$10,000
6 > $10,000
C-19
-------
Table C.8 Codes for Variables Q24_8
• Missing Data
11 Trade Associations and Shows
12 State Inspector
13 Pest Control Contractors
14 Other Consultants
15 Pesticide Labels and Directions
C-20
-------
Table C.9 Codes for Question 32 Variables
Variable Code
RQ32A 0
1
2
3
4
5
6
7
RQ32B 0
1
2
3
4
5
6
7
RQ32C 0
1
2
3
4
5
6
Definition
Missing Data
0 Greenhouses
1-2
3-5
6-10
11-20
21-50
>50
Missing Data
0 - 1,000 sq. ft.
1,001 - 5,000 " "
5,001 - 10,000 " "
10,001 - 50,000 " "
50,001 - 100,000 "
100,001 - 500,000 "
> 500,000 " "
Missing Data
0 - 1,000 sq. ft.
1,001 - 10,000 " "
10,001 - 100,000 " "
100,001 - 1,000,000 " "
1,000,001 - 10,000,000 "
> 10,000,000 "
C-21
-------
Table C.10
CONTENTS OF SA':. DATA SET S1UE_EFF
TCvAU.i U=ED=2 J.UBEXIEMT£=1 OEOERVATION=.=70 CREATED BY OS JuU FUII4URS ON CPUID 03-3081-02.2779
4VT 11:^4- FFilDAY, SEPTEMBER 23, 1934 BY £A£ RCLEAtE 52.4 D-=NAME=FWIBF£Li. NNPUS.SA3. USERFILE BLKSI/E=19053 LRECL=43
OBSERVATIONS F'EIV Tr\ACK=443 GEHEIVAIC.D BY I^ROC SORT
ALPHABETIC LIST OF VARIABLES
« VARIABLE TYPE LENGTH POSITION FORMAT INFORMAT LABEL
NO. TO LINK AI RECORD TO REG-NUM RECORD
1 IF DIZZINESS
DOLLAR AMOUNT OF PLANT DAMAGE
UNICUE SAMPLING UNIT IDENTIFIER
1 IF NAUSEA
1 IF O7IIER SIDE EFFECT
HE&TIC1DE CODC
1 IF PLANT DAMAGE
ANALYSIS EPA REGISTRATION NUMBER
1 IF SKIN RASH
NONRESPONSE-ADJUSTED SAMPLING WEIGHT
c/
5
1
11
4
7
1
^
.=•
L
10
Al-LINK
nizzY
DOLLUSS
ID
NAU'EEA
O't 1 IER
rcouiE
FLrJNf
RE&_NUM
SI INRASH
WEIGHT
NUM
NUM
NUM
NUM,
MUM
NUM
UlfiK
NUM
NUM
MUM
NUM
3
2
4
3
^
-•
3
2
S
-.
a
29
15
9
40
13
19
4
7
i-1
17
32
o
i\s
-------
C.2.5 The PRQBPEST Dataset
Responses to Question 27 are continued 1n this dataset. Table C.ll
lists the variables In this dataset. Pests are reported using the target
pest codes 1n Exhibit C-l. The data on plants affected were categorized by
the sites listed in Question 14 and are reported as such 1n the PROBSITE
variable.
C-23
-------
Table C.ll
CONTENTS OK SAS DATA SET PROBPEST
TRACK.:. U'=.ED=^ SULLX1tlJT&=l OBiEKVATIONS=lS4 CREATED BV OS JUD FWINURS ON CPUID 03-3031-022779
AT J3:ifr FRILiAV, = EP (IZMtER itf, 1?:..4 BY £AS RELEASE 32.4 DSIJAKE=FWIBFSD. NMPUS. &AS.USERFILE BLKS1 ZE=19065
•OBSERVATIONS F'EK TRACl =;.3'5- GENERATED BY PROC SORT
ALPHABETIC LIST OF VARIABLES
« VAMABLE TYPE LENGTH POSITION FORMAT INFORMfiF LABEL
LRECL=4?
COiT
ID
PEST
FROBSITE
WEIGHT
NUM
NUI1
CHAR
CHAR
NLIM
4
3
5
9
46
4
13
33
DOLLAR LOSS D'JE TO PROBLEM
UNIQUE SAMPLING UNIT IDENTIFIER
TARGET PEif CODE
ilTE AT WHICH PROBLEM OCCURRED
WOHRE&PONSC-ADJUSTED SAMPLING WCIGHT
O
ro
-------
APPENDIX D
SUPPLEMENTARY PESTICIDE USAGE INFORMATION
-------
Supplementary Pesticide Usage Information
This appendix contains listings of pesticide usage estimates for all
active ingredients reported 1n PUSHSP. Exhibit D.I lists all the active
ingredients in descending order by their estimated usage; separate listings
for each class of pesticides (1nsect1c1des/mitic1des, fungicides,
herbicides, nematicides, and others) are included as Exhibits D.2, D.3,
D.4, D.5, and D.6, respectively. The active Ingredients in the class list
are also listed in descending order by their estimated usage. Some active
ingredients appear 1n more than one of the class listings because they can
be used to treat more than one class of pest.
-------
Exhibit 0.1
Pesticide Usage by Active Ingredient
D-3
-------
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-------
Exhibit D.2
Insecticide Usage by Active Ingredient
D-8
-------
ANl) BlTii;-iiJt UhAbL fOK ALL ACTlHb iMi.HtM.LN IS
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10
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12
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21 1-otusij.uB oj.eate (loaea 079009 previous
22 Ohilu
23 Sodiuih
24 LlHDAMt
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bUTUlUN
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Dimethyl u-p-nitropbeoyi.
2b
27 Hevi.ui.hus
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-------
AMI* HlTlULDt USAk.ii l?Uh ALL ACliVh UlUhbLJ. JJI T2» 10:2b
?,
UBS LHLaiCiL * AlLUliE USAGt CUbUbAbJi PEKCJSNT Ht S M
57 PlttHUNlfL bUTOllUE b7b01 ,Vb2 0.00 1 1
tot PXhU'ibHIHS bVOOt b Obb,VOb 0.00 12 13
bJ BAXUuN K7bO^ 3 bbb.VOy 0.00 1 2
b4 BttfLA'lK aaiOl 0 bBo.710 0.00 1 1
03 bAClLLOS POPlLLiAK AfaU b. LEHlldUtiUOS S4b01 0 bbb.VIU 0.00 1 1
bo lecusol UbIOl 0 bbb,71b 0.00 1 J
07 COP1>£H IHit'lHAhOi^hlME COUPLEX ^HIUJ . . 00
b9 AHUHU 11b>t01 . . . b C
===== ==^=== ===
bdb, 710 100.00 2b
-------
Exhibit D.3
Fungicide Usage by Active Ingredient
D-ll
-------
FUNGICIDE USAGE FOR ALL ACTIVE INGREDIENTS
10:35 THURSDAY. SEPTEMBER 26. 1965
DBS CHEMICAL
1 METHYL BROMIDE
2 EBDC. AS A COORDINATION PRODUCT
3 BENLATE
4 CAPTAN
5 BRAVO
6 COPPER HYDROXIDE
7 ZINEB
8 PCNB
9 MANEB
10 TERRAZOLE
11 DIFOLATAN
12 Metalaxyl
13 METHYL THIOPHANATE
14 CALCIUM POLVSULFIDE
15 LESAN
16 CHLOROPICRIN
17 FERBAM
18 DODINE (DODECYLGUANIDINE ACETATE)
19 STREPTOMYCIN SULFATE
20 THIRAM (TETRAMETHTLTHIURAN DISULFIDE)
21 COPPER SULFATE PENTAHYORATE
22 METHOMVL
23 IPRODINE
24 BASIC COPPER SULFATE
25 Cuprous oxide
4 26 Formaldehyde
27 TRIFORINE
-1, 28 TRIADIMEFON
29 K4RATHANE
30 D/RENE
31 FOLPET
32 Meltatox
33 Tecesol
34 BENDIOCARB
35 COPPER SALTS OF FATTY AND ROSIN ACIDS
36 SULFUR
37 Ronilan
38 Potassium ricinoleate
39 Phygon
40 ThIabendazole
41 COPPER OXYCHLORIDE SULFATE
42 Cooper as metallic from cuprous and cupr
43 ACTIDIONE
44 Auramine
45 Malachite green
AICODE USAGE CUMUSAGE PERCENT HE_S
53201
14504
99101
81301
81901
23401
14506
56502
14505
84701
81701
113501
102001
76702
34201
81501
34801
44301
6310
79801
24401
90301
109801
8101
25601
43001
107901
109901
36001
80811
81601
110401
80101
105201
23104
77501
113201
79023
29601
60101
23503
42403
43401
39501
39504
294
111
88
78
56
49
35
32
20
15
13
11
9
9
8
6
5
5
5
4
3
2
1
1
1
1
,786
.623
,896
.848
,550
.009
.536
,432
.745
.043
.139
.253
.460
.054
,975
,016
,639
,379
,239
,242
,235
,262
.817
.409
.047
.016
887
886
869
763
651
517
447
323
211
194
187
51
46
17
8
a
0
.
•
294
406
495
574
630
679
715
747
768
783
796
807
817
826
835
841
847
852
857
861
865
867
869
870
871
872
873
B74
875
876
876
877
877
877
878
878
878
878
878
878
878
878
878
.786
.409
,305
,152
,703
.712
,248
,680
,425
.468
.607
.859
.319
.373
.348
,364
.003
,383
.621
,863
,098
,360
,178
.587
,634
,650
.537
.423
.292
.056
,706
.223
,670
.993
,204
,398
,584
.635
.681
,699
,707
.715
.715
.
•
33
12
10
8
6
5
4
3
2
1
1
1
1
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
.55
.70
.12
.97
.44
.58
.04
.69
.36
.71
.50
.28
.08
.03
.02
.68
.64
.61
.60
.48
.37
.26
.21
.16
.12
.12
.10
.10
.10
.09
.07
.06
.05
.04
.02
.02
.02
.01
.01
.00
.00
.00
.00
m
•
11
101
343
165
101
58
44
78
6
160
7
100
69
10
71
11
17
9
51
6
2
3
15
17
1
1
59
14
19
2
8
8
2
1
2
4
4
1
1
1
2
1
11
0
0
15
129
415
195
137
77
54
92
6
192
12
132
82
12
88
15
25
12
67
9
3
4
19
19
1
1
63
ia
22
4
10
8
2
1
3
4
5
1
1
2
2
1
12
0
0
878,715
100.00 1597 1972
-------
Exhibit D.4
Herbicide Usage by Active Ingredient
D-13
-------
HERBICIDE USAGE FOR ALL ACTIVE INGREDIENTS
10i40 THURSDAY. SEPTEMBER 26, 1985
OBS CHEMICAL
AICODE USAGE CUMUSAGE PERCENT HE_S
1 DACTHAL
2 ROUNDUP
3 TRIFLURALIN
4 ATRAZINE
E SIHAZINE
6 D-D Mixture (Use 2 code nos. 029001 and
7 METHYL BROMIDE
8 ALACHLOR
9 EPTAM
10 SURFLAN
11 SODIUM METABORATE
12 SODIUM CHLORATE
13 OXADIAZON
14 BUTYL 2.4-DICHLOROPHENOXYACETATE
15 ASULAM (METHYL SULFANILYLCARBAMATE)
16 DICHLOROPHENOXVACETIC ACID. ALKANOLAMINE
17 DEVRINOL
18 PARAQUAT DICHLORIDE
19 METOLACHLOR
20 AMHATE
21 DIQUAT DIBROMIDE
22 DIPHENAMID
23 Avadex
24 BENEFIN
25 DIETHYLAMINE 2.4-DICHLOROPHENDXVACETATE
._, 26 DIURON
I 27 DIMETHYLAMINE DICAMBA
^ 28 Dimethylamine 2-nethy1-4-chlorophenoxyac
*" 29 PROHAMIDE
30 MONOSODIUM METHANEARSONATE
31 PROMETON
32 CHLOROPICRIN
33 Alkanolx amine dinoseb ( 2-sec-buty1-4,6
34 Dimethylamine 4-C2,4-dlchlorophenoxy)but
3b DIMETHYLAMINE 2-(2-METHVL-4-CHLOROPHENOX
36 riETRIBUZIN
37 OXVFLUORFEN
38 AMITROLE (3-AMINO-S-TRIAZOLE)
39 BENTAZON,SODIUM SALT OF
40 SODIUM ARSENITE
41 OCTYLAMINC 2,4-DICHLOROPHENOXYACETATE
42 Proul
43 DALAPON, SODIUM SALT OF
44 BUTOXYETHYL 2.4-DICHLOROPHENOXVACETATE
45 SODIUM CACODYLATE
46 BETASAN
47 ISOOCTYL 2-(2-METHYl-4-CHLOROPHENOXY)PRO
48 Ami beni ammonium salt of
49 DALAPON,MAGNESIUM SALT OF
50 SIDURON
51 CACODYLIC ACID
52 HYVAR X
53 DURSBAN
54 Chloroprophan
55 PROPACHLOR
56 DICHLOROPHENOXYACETIC ACID, OCTYL ESTER
78701
103601
36101
80803
80807
29001
53201
90501
41401
104201
11104
73301
109001
30056
106901
30010
103001
61601
108801
5501
32201
36601
78801
84301
30019
35505
29802
30516
101701
13803
80804
81501
37511
30819
31519
101101
111601
4401
103901
13603
30030
108501
28902
30053
12502
9801
31563
29902
28903
35509
12501
12301
18301
19101
30063
413
300
168
151
123
63
52
50
49
44
42
33
27
27
22
21
19
16
14
13
13
12
12
11
9
7
6
6
6
4
4
4
3
3
3
3
3
3
1
1
1
,602 413
,105 713
.882 882
,728 1,034
.480
.984
,036
.755
,975
,185
.472
.940
.603
,238
,813
,163
,932
,092
,645
,827
,812
.681
.227
,950
,907
,636
.972
,899
,127
,760
.415
,201
.599
,540
.196
,159
,076
.020
,509
.130
.084
843
590
482
371
245
192
177
98
91
63
47
,157
.221
,273
.324
,374
,418
.461
,495
,522
,549
,572
,593
,613
.629
.644
.658
.672
.684
.697
.709
.719
,726
.733
,740
,746
,751
,755
,760
.763
,767
,770
,773
,776
.779
,781
.782
,783
,784
,784
.785
.785
.785
.786
.786
.786
,786
.786
,786
44 1.786
26 1,786
24 1>786
23 1,786
,602
,707
,589
,317
,797
.781
,816
,571
,546
,731
,203
,143
,746
.984
,797
,959
,892
.984
,628
,455
,268
,949
.176
,126
,033
,669
,641
,540
,667
,428
,843
,044
,642
,182
,378
.538
,613
,633
,142
,272
,356
,200
,790
.272
,643
,888
,081
,258
,356
,447
.510
,557
,601
,626
,650
,673
23
16
9
8
6
3
2
2
2
2
2
1
1
1
1
1
1
0
0
0
0
0
0
0
a
0
a
0
0
0
a
0
0
0
0
a
0
a
a
a
a
0
a
a
0
a
a
a
a
a
a
0
0
0
0
0
.15
.80
.45
.49
.91
.58
.91
.84
.80
.47
.38
.90
.54
.52
.28
.18
.12
.90
.82
.77
.77
.71
.68
.67
.55
.43
.39
.39
.34
.27
.25
.24
.20
.20
.18
.18
.17
.17
.08
.06
.06
.05
.03
.03
.02
.01
.01
.01
.01
.01
.00
.00
.00
.00
.00
.00
18
359
53
12
122
4
9
14
9
46
7
7
88
1
3
8
27
73
6
6
43
7
8
3
13
12
13
2
13
3
11
10
1
1
10
2
17
10
6
1
4
11
2
2
6
1
1
1
2
1
6
2
1
1
1
22
433
70
15
153
4
10
22
11
59
9
9
118
1
4
13
38
87
6
6
50
11
8
5
15
18
17
4
24
3
14
10
3
1
11
2
20
13
7
1
6
13
2
3
6
1
1
2
2
1
6
4
1
1
1
-------
HERBICIDE USAGE FOR AJ.L ACTIVE INGREDIENTS 10:40 THURSDAY, SEPTEMBER 26, 1985
DBS CHEMICAL AICODE USAGE CUMUSAGE PERCENT HE_S -N
57 BUTOXYETHYL 2-<2,4-DICHLOROPHENOXY)PROPI 31453 16 1.786,689 0.00 1 I
58 CICHLOROPHENOXYACETIC ACID, N-OLEYL-1.3- 30029 11 1,786,700 0.00 1 3
59 DICHLOROPHENOXYACETIC ACID 30001 9 1,786,709 0.00 1 3
60 BRAVO 81901 3 1,786,711 0.00 1 1
61 TRICLOPYR, TRIETHVLAMINE SALT OF 116002 1 1,786,712 0.00 1 1
62 TDK 38201 1 1,786,713 0.00 1 1
1,786.713 100.00 1107 1388
O
M
Ln
-------
Exhibit D.5
Nematicide Usage by Active Ingredient
D-16
-------
NENATICIDE USAGE FOR *ALL ACTIVE INGREDIENTS
DBS CHEMICAL AICODE USAGE CUMUSAGE PERCENT HE_S N
10:44 THURSDAY. SEPTEMBER 26, 1905
1 METAM-SODIUM 3900J
2 Bay 25141 32701
100.869 100.869
4.015 104.884
96.17
3.83
16
4
19
8
104,884
100.00 20 27
I
M
•«J
-------
Exhibit D.6
Other Pesticide Usage by Active Ingredient
D-18
-------
OTHER PESTICIDE USAGE>(. FOR ALL ACTIVE INGREDIINTS
DBS CHEMICAL AICODE USAGE CUMUSAGE PERCENT HE*_S N
1 METALDEHYDE
2 MESUROL
3 KINOPRENE
4 CHLORFLURENOL
5 Santophen
6 Hyamine 3500
7 PENTACHLOROPHENOL
8 Mar
9 FLOREL
10 Hormodin
11 WARFARIN
12 DIPHACINONE
10:51 THURSDAY, SEPTEMBER 26, 1985
53001
100501
107501
98801
62201
69105
63001
35101
99801
46701
86002
67701
6,106 1
2,407 (
501
42
38
14
6
c
4
1 «
0 «
0 '.
9,122
1,106
1,512
,013
,055
.093
,107
,112
,117
,121
1,121
(.121
1,122
66.93
26.38
5.49
0.46
0.42
0.16
0.06
0.05
0.04
0.01
0.00
0.00
99.99
41
1'
li
8'
I 50
t 25
i 19
1
1
1
1
1
1
1
1
2
' 104
------- |