-------
TABLE IS
REGIONAL AVAILABILITY OF CONTRACTORS -
NUMBER (PERCENT OF TOTAL)
Region No.
I
II
III
IV
V
VI
VII
VIII
IX
X
Bulk Testing
PLM
9(8.08%)
14(13.21%)
10(9.43%)
12(16.32%)
24(22.64%)
14(13.21%)
3(2.83%)
6(5.66%)
10(9.43%)
4(3.77%)
XRD
7(9.86%)
11(15.49%)
6(8.45%)
4(5.63%)
16(22.53%)
13(18.31%)
2(2.82%)
5(7.04%)
6(8.45%)
1(1.41%)
EM
7(17.5%)
3(7.50%)
4(10.00%)
2(5.00%)
6(15.00%)
8(20.00%)
2(5.00%)
2(5.00%)
5(12.50%)
1(2.50%)
Air
Monitoring
14(15.05%)
13(13.98%)
12(12.90%)
7(7.53%)
22(23.65%)
6(6.45%)
2(2.15%)
5(5.38%)
9(9.68%)
3(3.22%)
Air Sample
Quantification
OM (NIOSH)
11(10.00%)
13(11.82%)
12(10.91%)
10(9.09%)
26(23.64%)
13(11.82%)
4(3.64%)
9(8.18%)
10(9.09%)
2(1.82%)
EM
7(15.55%)
4(8.89%)
4(8.89%)
1(2.22%)
9(20.00%)
10(22.22%)
2(4.44%)
2(4.44%)
5(11.11%)
1(2.22%)
Removal
8(16.59%)
10(14.49%)
8(1.59%)
9(13.04%)
8(11.59%)
12(17.39%)
3(4.35%)
1(1.45%)
6(8.69%)
4(5.80%)
Disposal
6(16.59)
5(10.20%)
5(10.20%)
7(14.28%)
6(12.24%)
11(22.45%)
3(6.12%)
1(2.04%)
4(8.16%)
1(2.04%)
Encapsulation
7(8.75%)
13(16.25%)
8(10.00%)
8(10.00%)
11(13.75%)
15(18.75%)
2(2.50%)
2(2.50%)
10(12.50%)
4(5.00%)
Enclosure
6(13.95%)
2(4.65%)
3(6.09%)
5(11.63%)
7(16.28%)
11(25.58%)
2(4.65%)
2(4.65%)
5(11.63%)
0(0)
Marking
5(16.13%)
1(3.22%)
2(6.45%)
4(12.90%)
4(12.90%)
10(32.26%
2(6.45%)
1(3.22%)
2(6.45%)
0(0)
CD
TOTAL
106(100%) 71(100%) 40(100%)
93(100%)
110(100%)
45(100%) 69(100%)
49(100%)
80(100%)
43(100%) 31(100%)
NOTES: PLM *> Polarized Light Microscopy
XRD - X-Ray Diffraction
EM • Electron Microscopy
OM « Optical Microscopy
NOTE: Due to relatively high response rate(30%), and extensive survey coverage (646 firms), percentage figures are
expected to be representative of the universe of firms providing these services.
-------
III. ESTIMATION OF AFFECTED SCHOOL DISTRICT POPULATION
i
1
This chapter presents the results of our efforts to develop
population estimates of the number and degree to which school
districts, schools, and students may be affected by the possible
voluntary actions to control asbestos in schools. The following
sections discuss the methodological steps used to develop population
estimates. The steps include choosing a sample of school districts,
clustering and subsequent stratification of the universe of school
districts, collecting the data required for the completion of this
project, and, finally, development of the parameters needed for the
population estimates. The discussion of population estimates is
followed by a discussion of the limitations of these results.
1. DETAILED METHODOLOGICAL DISCUSSION
This section discusses the methbdological steps which were used
to develop the parameters by which population estimates were derived.
(1) Choice of Initial Sample of EPA Returns
It was jointly decided by EPA and Arthur Young & Company
that this project should use data provided by the EPA regional
offices from material obtained through the EPA Voluntary Program.
These returned forms provided a sample which contained a
significant portion of the data required by the study. Therefore,
it would be relatively easier to complete the data requirements
by obtaining the additional data in a follow up study to the
original EPA Voluntary Survey (OMB No. 158-R-0165). Tne time
constraints of this study made this an important consideration.
The limitation of using these data, however, is that they may not
represent the total population of school districts. The bias
could be that these respondents may have uncharacteristically
90
-------
active asbestos control programs, evidenced by their relatively
early response to the survey. Of the approximately 550 forms
returned by November 19, 1979/ 401 were used as the initial sample.
Usable forms were those of school districts which could be
identified as a public school system based on a tape of Public
School Systems from the National Center for Education Statistics,
Department of Education. Unusable survey forms, for the purposes
of this study, were those from Head Start Programs, private
schools, and from individual public schools.
(2) Choice of Cluster Variables
The population of public school systems is large (over 16,000
school districts) and very heterogeneous. It was evident at the
outset that any meaningful analysis would require a segmentation
of this universe into more homogeneous sets (clusters). This was
effected by identifying school district characteristics
(variables) which may govern the cost of compliance with the
proposed regulation. Practical considerations stipulated that
any data for the variables chosen be easily obtained. The time
and resource limitations of the project prevented a more thorough
analysis for potentially the best variables to use. The variables
chosen were EPA Region code, metro code (indicating the degree
of urbanization of the school district) (MTS), number of schools
built between 1945 and 1978 (NBLT), and the number of students
enrolled in each school district (NST).
"EPA region" signifies in which section of the country a
school district is located. School districts on the East coast
may, for instance, have more in common in terms of the cost of
labor required for certain control actions than with school
districts in the central and western parts of the United States.
Determining geographic location by individual states would have
created a minimum of fifty sections of the country which would
91
-------
have to be analyzed. This would have made any analysis much more
cumbersome instead of easier.
The metro code (MTS) is a numeric code identifying the
Standard Metropolitan Statistical Area (SMSA) in which (or near
which) the school district is located. The code identifies
districts within city limits (MTS = 1), within SMSA, but outside
city limits (suburbia, MTS = 2), and all other or outside SMSA
(rural, MTS =3). The metro code divides EPA regions into smaller
geographical areas in which there would be a similarity of age
and-structure of a school building. For example, the age and
structure of a school built in an inner-city area might be
different from a school building in a suburban or rural area.
Both of these factors are potentially important cost-influencing
factors.
The number of schools built or renovated between 1945 and
1978 (NBLT) was chosen because the probability of a school having
asbestos containing material is greater in schools which were
built or renovated between 1945 and 1978. It was during this
time period that the asbestos-containing materials were used the
most.
The number of students in a school district is an indication
of the size of the school district and the magnitude of the
asbestos problem if asbestos containing materials are present.
It is also related to the size of the school budget and, therefore,
the amount of funds potentially available for use in asbestos
detection and voluntary control actions.
•"/ •
v
The EPA Region, metro code (MTS) and number of students in
a school district (NST) were obtained from the Public School
Systems tape from the National Center of Education Statistics.
The number of schools built or renovated between 1945 and 1978
92
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(NBLT) was partially obtained from contacting each State
Department of Education. In instances where this information was
unavailable, the assumption was made that all schools in that
state had either been built or had major renovations since 1945.
(3) Cluster Analysis and Stratification
As mentioned earlier, any meaningful regulatory cost
analysis would require segmentation of the universe into
homogeneous groups based on variables which could affect the cost
of complying with the proposed regulation. Cluster analysis was
used to define a suitable range for each variable for purposes
of stratification.
The clustering process groups school districts based on a
distance criterion. !/ Distance is measured by the Euclidean
distance (the square root of the sum of squares of the differences
between the values of the variables for each pair of cases). The
variables whose values were used were the metro code (MTS), the
number of schools built between 1945 and 1978 (NBLT), and the
number of students in a school district (NST). The location
variable, EPA region, was not used at this point because the
distance between numbers is not meaningful numerically. For
example, the distance between Regions I and II has no relationship
to the distance between Regions II and III.
Each school district is initially placed in a cluster by
itself. At each step in the clustering process, the two clusters
-i/Engleman, Laszlo. Biomedical Computer Programs P-Series; 17.2
Cluster Analyses of Cases. (University of California Press, 1979) p.
633.
93
-------
with the shortest distance between them are combined into one
cluster. This process of combining clusters continues until all
of the cases are combined into a prespecified number of clusters.
The cluster analysis algorithm sometimes considers outliers
as a distinct cluster. These outliers usually consist of only
one or two cases. As these are usually too small to be useful,
they are disregarded.
From each cluster the ranges of the values of each variable
were individually measured. In this manner, the dividing point
between clusters for each variable is discerned and the concept
of how the population could be stratified into homogeneous units
is derived.
The clusters were developed without the location variable,
EPA region, which meant that each cluster included school
districts from the entire United States. It had been assumed
that geographic location would affect the cost of the labor
required for certain voluntary corrective actions. To divide
each cluster into smaller geographic areas, the EPA region
variable was added at this point. Each cluster was divided into
smaller geographic regions. The values of the other variables
remained the same. Now, however they identified school districts
within certain geographic boundaries rather than the entire
United States. The geographic breakdown consisted of East coast
(Regions I-V), Central (Regions VI-VIII), and tne West coast
(Regions IX-X), which included Alaska and Hawaii. This particular
breakdown was decided upon Because it expanded the number of
clusters only threefold and enabled states for which no data were
available to be averaged in with similar states for wnich data
were available. If smaller EPA region groups or individual states
had been used, the number of clusters developed would have been
too cumbersome to have been analyzed easily.
94
-------
(4) Bias Adjustments
Bias in the EPA voluntary survey sample could occur for one
or more of the following reasons:
Small sample size. The initial sample of 401 was
approximately 2.5% of the total population of school
districts.
Due to time and budgetary constraints, the clustering process
was limited to 250 records from the original 401. The records
that were chosen for clustering were the 250 most
classifiable records based on the chosen cluster variables.
By excluding 151 records additional biases may have been
introduced. This reduction also aggravated tne small sample
size problem reducing the sample from 2.5% of the population
to 1.6% of the population.
By design, the initial sample consisted entirely of school
districts who responded to the EPA voluntary survey form.
In order to qualitatively ascertain if there were any strong
biases, a small sample of 20 non-respondents was randomly chosen
and contacted by telephone. The purpose of the telephone
inquiries was to generally determine if the asbestos information
sent in by respondents differed from information obtained from
non-respondents. An EPA voluntary survey form was filled out for
each of the school districts contacted.
The data collected were visually compared with information
from respondents. Items from the EPA voluntary survey were used
for comparison. It was noted that the asbestos specific
information was generally similar. Noted also was that the ranges
of some of the cluster variables were restrictive resulting in
95
-------
the exclusion of non-respondent school districts from the
established clusters. For instance, the ranges for NBLT were 1-
4 and 6-10. This excluded cases where 5 schools per school
district were built or renovated or where more than:10 schools
per school district were built or renovated. Also excluded from
the established clusters were school districts in inner city
areas (MTS =1). This particular exclusion was due to the fact
that the first 250 classifiable school districts clusters were
only rural (MTS = 3) and suburban (MTS = 2) school districts.
Adjustments to the clusters were made to correct for the
exclusion of school districts mentioned above. The ranges of the
variables were extended using information obtained from the above
survey testing bias and from the original clusters. These changes
made it possible for the clusters to represent more of the
population. The changes made to the ranges of the variables are
as follows:
NST
The students enrolled in school districts were originally
divided into groups of 516 - 2700 and 3137 - 8807. These
ranges were restrictive as there are over 4000 school
districts with less than 300 students. The ranges were
changed to 1-2499 and 2500 and greater students in a school
district.
MTS
Inner city area schools were totally excluded from the
original cluster. These1* school districts generally have more
than 10,000 students enrolled and the majority of their
schools have either been built or have had extensive
renovations between 1945 and 1978. These school districts
96
-------
are also at the upper end of the ranges for NBLT and NST.
Therefore, all inner city schools were placed in one cluster.
This cluster was further divided into five clusters based
on EPA regions when it was discovered that this would make
the analysis of these school districts more meaningful due
to the variation in degree affected within units of that
cluster.
After the changes to the ranges of variables were made, the
original clusters, which represented only about 25% (4,000) of
the school districts, were extended to represent over 15,800
school districts (99%). The remaining 1% consisted of school
districts in United States territories.
In general, if a cluster represented less than 0.4%
(approximately 70 districts) of the total population, it was
considered too small to be sampled as the analysis would not be
meaningful. This eliminated 5 (345 school districts) of the 25
clusters. The range of variables in each cluster is presented
in Exhibit 4. The final population of school districts which are
represented by the remaining 20 clusters consists of
approximately 15,746 school districts (98% of the school district
universe).
As each cluster represented a unique group of school
districts in the population, it was necessary to have each cluster
adequately represented in the sample on which detailed
information would be collected. A minimum sample size of 1% of
each population cluster was set. It was necessary to limit the
sample size due to the time and resource limitations of the
project.
The school districts chosen for the sample on which detailed
information would be collected were comprised of respondents and
97
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Composition of Population strata
EXHIBIT 4
Population
Strata
1
2
3
4
1
5
6
7
8
9
10
11
12
13
14
1b
1E
17
tt
19
2i-
Metro
Code
3
3
3
3
3
3
3
2
2
1
2
3
i
^
'.
-
*•.
n
&
j
EPA
Region
1-5
6-8
9-10
1-5
6-8
6-8
9-10
1-5
6-8
1-10
9-10
6-8
6-8
I 50
1-5
t • 10
1 -B
i-b
8-10
1 • E
Number of
Schools Built
between 1945 &
1978 per School
District
jLs
.Is
J^5
_£.6
_>.6
X 5
A-5
IB
^5 '
J^_5
2. 6
le
_^. 6
^6
JL6
'. 6
-1_ 5
— 5
^5
Number of
Students per
School District
_^_ 1 and^.2499
^. 1 and^.2499
^_ 1 and^.2499
_>. 2500
_^_ 2500
_^. 2500
.2.2500
^. landjl.2499
^_ 1 and^.2499
y_ 1 and <_2499
i 1 andX.2499
.2. 2500
.2. 2500
_2 land ^.2499
2. 2500
^.2500
^. 2500
_/.2500
^.2500
Number of
School Districts
in Population
3105
4650
1011
670
224
69
51
1733
684
349
547
68
156
267
216
81
862
669
70
372
15.854
EPA Regions
REGIONAL OFFICES
Metro Code:
1 = District within City Limits
2 = District within SMSA outside City
3 = All other or District outside SMSA
-------
non-respondents to the EPA voluntary survey. The original sample
of 401 EPA voluntary survey respondents was stratified .using the
ranges of variables established for each population cluster. This
indicated how many clusters in the population could be adequately
represented in the sample using these respondents. In only two
clusters were several non-respondents included. To be assured
of an adequate amount of returns for each cluster, a random sample
consisting of two to three times the prescribed number of units
was drawn from each of the final clusters.
The final sample consisted of 300 school districts.
Responses were obtained from 246 school districts in 33 states.
Eighteen of these states had more than 1% of their school
districts represented in the sample.
(5) Data Collection
A review of the voluntary survey forms led to the conclusion
that many were not complete and that the data given were not
adequate to respond to the requirements of this study. These
forms would indicate that inspections were done and/or bulK
samples taken but not the results of these activities. In other
cases, the survey indicated an exposure problem, but did not
indicate the number of square feet affected and/or the number of
students affected.
A telephone survey was conducted to obtain the necessary
data. Letters were sent to superintendents of the school
districts and maintenance personnel about ten days in advance of
phone calls stating the purpose and information requirements of
the survey. The following data were requested from the
maintenance personnel.
An assessment of the schools in a school district which may
99
-------
require voluntary corrective action (by type of corrective
action) was requested for the development of population
estimates. A draft of an asbestos exposure assessment
algorithm, provided by EPA, was sent for use as a standard
procedure for assessing a school building. Using this
algorithm/ an indication of the number of buildings possibly
requiring each type of voluntary corrective action could be
obtained. For example, after reviewing conditions in a
school district, it may be found that of ten schools, it may
be recommended that three be 'encapsulated', six be 'deferred*
and one would not need any furtner action.
Total square footage of each affected school was obtained.
This was required to develop aggregate cost estimates.
Superintendents of the school districts were requested to
provide the following information on the number of affected
students and on any potential negative impacts based on the
maintenance superintendent's assessment of the schools in the
district for which voluntary corrective action may be
recommended:
Number of schools or parts of schools which may temporarily
close and the number of school days which could be lost as
a result of any recommended asbestos correction activity.
Number of schools or parts of schools where the potential
may exist for permanent closure, the potential number of
students that may be displaced, and tne expected change in
average class size and student/teacher ratio at other
schools due to these possible closings.
The number of jobs which may be lost if the asbestos problem
is considered severe enough by the maintenance personnel
100
-------
assessment to warrant either a long-term temporary school
closing or permanent school closing.
Any additional indirect costs (i.e., over and above the direct
cost of any detection and voluntary asbestos control
activities) as a result of corrective actions that may be
voluntarily taken.
The number of affected students was also requested as it
was required for the development of population estimates.
The number of affected students could be an entire school's
population if the area in question is the cafeteria or
auditorium. In other cases, affected students could be
limited to those students using that particular room. An
illustration would be choral students who are the only
students using the band and chorus rooms.
Information obtained from the school administrators
indicated that, in a number of instances, the information on the
EPA survey was no longer valid. This was due in part to new
information obtained by the school administrators in the interim
which caused the school to be assessed differently. In other
school districts, corrective action on the affected areas had
either begun or had been completed.
Each school district was carefully analyzed as to the
completeness and accuracy of information. In several instances,
certain assumptions about the available data were made:
. Where a school had more than one type of corrective action
recommended, an average of all asbestos, algorithm scores of
that school was used as the score for the school. For
instance, a school has four areas for which corrective action
is recommended. The asbestos algoritnm scores for these areas
101
-------
are 4, 20, 40, 36, with the average being 25. Therefore, the
entire school would be analyzed as needing encapsulation.
This was fairly restrictive, but it was the most logical.,
step to take, based on the information available. This was
done with the concurrence of EPA.
In some cases complete algorithm scores were not available
because the bulk samples had not been returned from the
laboratory or were not taken. Maintenance personnel were
asked, based on their knowledge of the school through plans
or specifications, whether they felt the friable material
in question contained asbestos. If an affirmative answer
was given, they were then asked for their estimate of the
concentration of asbestos in these materials. Using their
judgment in conjunction with the completed portions of the
algorithm, the voluntary corrective action was determined
for that school.
Potential costs incurred in correcting boiler room areas
and pipe wrappings are usually much lower than other areas
needing corrective action. This can be in part due to tape
being used to repair pipe jackets or just the damaged area
of the pipe wrapping being replaced. Therefore, to avoid
•-confusion in both assessing the seriousness of a problem
area and the cost of other voluntary corrective actions,
boiler rooms and pipes have been kept separate.
(6) Extrapolation
This section discusses the procedure used for extrapolating
sample level data to the universe of school districts. Each
sample cluster was analyzed as to the number of school districts,
schools, and students affected by the proposed regulation.
"Affected" was defined as those school districts and schools for
102
-------
which one or more asbestos control action may be recommended
based on the asbestos exposure assessment algorithm. Students
affected are those students who have had exposure to the asbestos
containing materials. The number of students affected in a school
depends on whether the problem area is in a cafeteria or a
specialized room like the band room.
A "rate of affectedness" was constructed for each of the
three areas (i.e., school districts, schools, and students) for
each sample cluster (See Exhibit 5). This is used subsequently
to estimate the affected population of school districts, schools,
and students. Each of these rates is described below:
The percentage of affected school districts is the ratio of
those school districts in a sample cluster for which
corrective action is recommended in at least one school
based on the asbestos assessment exposure algorithm to tne
total number of school districts in that cluster.
The percentage of affected schools is the ratio of all the
schools in a sample cluster for which corrective actions
are recommended to all the schools in the sample cluster.
The percentage of affected students is the ratio between
those students potentially affected by asbestos containing
materials in a sample cluster to the total number of students
in that same cluster.
The tally of affected students does not include students in
schools where asbestos containing materials are confined to
boiler rooms or pipes. It is unlikely that many students would
have reason to be exposed to these areas.
Using the rates developed, population estimates of the number
103
-------
The Number of School Districts, Schools, and Students In
Sample Affected by Asbestos control Measures
o
*>.
Sample
Strata
1
2
3
4
5
6
7
8
9
10(a) 4/
10 (b)
10(c)
10 (d)
10(e)
11
12
13
14
15
16
17
18
19
20
Total School
Districts in
Sample
32
23
9
36
11
3
2
16
7
12
1
5
17
2
15
4'
4
4
3
3
23
14
3
4
.«
31% '
26%
33%
36%
64%
0%
50%
69%
14%
83%
0%
40%
100%
100%
33%
75%
75%
25%
0%
100%
39%
43%
33%
50%
Estimate of
Affected School
Districts in
Sample
10
6
3
13
7
0
1
11
1
10
0
2
2
2
5
3
3
1
0
3
9
6 ;
1
2
Total Number
of Schools
in
Sample
111
65
18
512
128
38
12
62
21
812
33
266
75
163
41
19
23
39
.28
32
203
72
15
51
»z/
19%
11%
28%
20%
14%
0%
17%
35%
5%
11%
0%
2%
24%
7%
22%
21%
22%
3%
0%
28%
14%
19%
•71
57'!
Estimate of
Affected
Schools
21
7
5
102
18
0
2
22
1
87
0
6
18
12
9
4
5
1
0
9
28
14
1
29
Total
Students
in School
Districts
43^,870
12', 5 36
6,203
224,527
65 ',667
20,604
8,311
24,856
9,413
590,539
15,349
180,838
30,727
8'0,768
15,475
5,867
24,208
16,438
7,112
18,898
97,996
42,226
9,899
20,234
*2/
12%
5%
0%
4%
11%
0%
0%
33%
0%
11%
0%
0%
30%
15%
5%
22%
9%
0%
0%
29%
9%
17%
6%
32%
Estimate of
Affected
Students
5,118
596
0
9,165
7.175
0
0
8,117
0
65,893
0
0
9,140
12,027
744
1,285
2,179
0
0
5,414
9,352
7,004
625
6,450
U Percentage of Affected School Districts » Affected School Districts. 3J Percentage of Affected Students = Affected Students
Total School Districts^
2J Percentage of Affected Schools =• Affected Schools §
Total Schools c
Total Students s
4/ Sub-Strata where MTS = 1 (inner city areas),
10(a) - EPA Region 3.10(b) = EPA Region =5,
10(c) = EPA Region 6. 10(d) = EPA Region 7. and 1
10(e) - EPA Region 9-10
This percentage excludes
those schools with asbestos
containing materials ex-
clusively in the Boiler
Rooms and on Pipes.
DO
H
en
-------
of affected school districts, schools, and students can be derived
as follows (See Exhibit 6):
The ratio of affected school districts to total school
districts in the sample cluster is multiplied by the total
number of school districts in the population cluster to
estimate the number of affected school districts in the
population cluster.
The percentage of affected schools in the sample cluster is
multiplied by the total number of schools in the population
to obtain an estimate of the number of affected schools in
the population cluster.
The percentage of affected students in the sample cluster
is multiplied by the total number of students in the
population cluster to obtain an estimate of the number of
affected students in that cluster.
Two sets of percentages were developed for the degree to
which affected schools and school districts in a cluster would
be affected. "Degree affected" being defined as the specific
action (inspection, bulk sampling and voluntary corrective
actions) recommended in that school or school district. These
are described below. Symbols used identify variables used in the
next chapter.
Percent of schools (SA^.) for which a specific action is
recommended is the ratio of the number of schools for which
a specific control action (j) is recommended in a cluster
(i) to the total number of affected schools in that cluster.
This ratio indicates, on the average, what percentage of
affected schools for which a specific control action is
recommended (See Exhibit 7).
105
-------
The Number of school Districts, schools, and students In
the population Affected by Asbestos control Measures
M
O
O\
Population
Strata
1
2
3
4
5
6
7
8
9
10 (a) &
10 (b)
10 (c)
10{d)
10(e)
11
12
13
14
15
16
17
18
19
20
mf^tnn v
Total School
Districts in
Population
3,105
4,650
1,011
670
224
69
51
1,733
684
38
70
75
17
41
547
68
156
267
216
81
862
669
70
372
1 C 1 Af.
*
31%
26%
33%
36%
64%
0%
50%
69%
14%
83%
0%
40%
100%
100%
33%
75%
75%
25%
0%
100%
39%
43%
33%
50%
Estimate of
Affected School
Districts in
Population
970
1,213
337
242
142
0
26
1,191
98
32
0
30
17
41
182
51
117.
67
0
81
337
289
23
186
P r •"! »> *
Total Number
of Schools
in
Population
7,462
9,791
2,014
8,420
4,832
384
275
4,555
1,660
1,566
3,539
2,497
954
2,415
1,123
577
2,894
4,807
9,937
1,014
13,682
4,425
353
2,491
*-k i ^ f +%
%*
19%
11%
28%
20%
14%
0%
17%
35%
5%
11%
0%
2%
24%
12%
22%
21%
22%
3%
0%
28%
14%
19%
7%
57%
Estimate of
Affected
Schools
1,412
1,055
560
1,614
679
0
46
1,616
79
168
0
56
229
178
246
121
630
123
0
285
1,887
860
24
1,416
Total
Students
in School
Districts
2,691,124
1,949,125
504,358
3,947,294
1,964,797
219,808
161,997
2,024,747
486,436
1,064,751
2,263,282
1,690,524
524,108
1,623,641
388,863
101,079
1,919,292
2,986,076
370,299
449,343
8,159,773
2,999,695
295,536
1,360,623
%*
12%
5%
0%
4%
11%
0%
0%
33%
0%
11%
0%
0%
30%
15%
5%
22%
9%
0%
0%
29%
9%
17%
6%
32%
Estimate of
Affected
Students
313,954
92,667
0
161,125
214,680
0
0
661,203
0
118,826
0
0
155,922
241,760
18,696
22,138
174,423
0
0
4,128,730
778,442
497,557
18,659
433,726
91,667
13,347 40,145,871
4,032,508
V r»
Tolil School Olilricu.
. .
TolMStudMiu
UMM Khool, with wU.lo.
Allt.ua- «d..ut.
, «onlihiln|ii«l.iWi.,.
""»"""
••"•»••
.,
UHel-erAftetkMMOIdl-ifAR.tioa7.MKlf
101.1 -EPARtglont 10
X
2
H
-------
The Number and Degree to Which the Schools in the Sample are Affected
o
-J
/
1
2
3
4
5
6
7
8
9
10(a)
10 (b)
10 (c)
10(d)
10 (e)
11
12
13
14
15
16
17
18
19
20
TOTAL
/ •» .
21
7
5
102
18
0
2
22
1
88
0
6
18
12
9
4
5
1
0
9
28
14
1
29
402
r
15
43
55
*
3
3
12
18
ff %
15
100
66
/ •» ,
3
1
19
23
'/
29
8
22
8
75
25
11
11
7
/ -v
2
B
4
7
9
1
1
3
1
36
r »
5
15
45
4
7
17
50
40
21
50
/ ^
. 1
15
8
1
6
3
2
2
6
7
51
W
19
14
1
22
32
82
83
25
11
25
100
14
14
/ •»
4
1
1
4
7
72
15
3
1
1
1
4
2
116
' %
48
40
73
9
100
17
33
25
29
/
10
2
75
2
1
1
3
7
4
105
y
14
60
3
11
100
3
83
56
40
89
29
34
/ ^
1
3
3
2
2
3
5
5
2
8
8
10
52
V
20
/
1
1
-I/ Percentage of Affected Schools Needing a Specific Corrective Action =
(Number of Affected Scfioolijj) = SA ij
Total Affected Schools;
Where i-1 20
("Corrective Action
m
03
H
-j
-------
Percent of school districts (TSD^). The sample data on
corrective actions were first used to define the proportion
of all affected school districts in a cluster for which some
type of control action may be recommended. This factor or
multiplier is represented by SDA^., with i designating the
cluster, and j the voluntary asbestos corrective action.
A second factor was calculated using the total number of
schools in a cluster, regardless of whether they were
affected or not. This second factor or multiplier is the
proportion of total school districts in a cluster for which
a specific control action may be recommended. This factor
is represented by
This factor was developed specifically to extrapolate from
the school district to the state and national levels. By
using a ratio which is based on the entire number of school
districts per cluster, rather than the number of affected
school districts, it was felt that it would be easier to
construct state and national results. This is because the
number of affected school districts at those levels can only
be estimated, whereas, in using the total number of school
districts per cluster at these levels, a better estimate can
be obtained. ;;,r~T.
The two sets of factors or multipliers are presented in
Exhibits 8 and 9. In the following chapter on estimating
the costs of recommended asbestos control actions, SDA. . and
. are used to identify the proportion of school
districts, and states, and the proportion in each cluster
for which certain control actions may be recommended.
Extrapolated estimates of schools and school districts for
which specific type of control actions may be recommended can be
108
-------
Number of Affected School Districts in the Population
Requiring Specific Corrective Action
0°
j/ Nuinbur of School Districts will not add ii|i to the Total Afflicted School Districts.
Sonic will ruquiro inoro Ihitn ono corrective action and nru counted twico.
ii
2J Porcontiigu of School Districts Affected--! kj^ Percentage of Affected School Districts i j V = SUAij
Total Number of Affected School Districts j.
Whoro i= 1-20
j- corrective action
k= School District
1
2
3
4
5
6
7
8
9
lOa
lOb
LOc
lOd
IGe
11
12
13
14
15
16
17
18
19
20
TOTAL
970
1213
337
242
142
0
26
1191
98
32
0
,30
17
41
182
51
117
67
0
81
337
289
23
186
5672
67
50
53
43
23
-
33
59
50
14
-
4
24
11
64
33
17
11
-
31
35
43
-
45
648
607
178
104
33
9
706
49
4
1
4
4
117
17
20
7
25
116
124
85
2858
10%
20
45
97
5
84
186
14
3
5
2
6
6
6
5
4
168
7
7
.5
3
9
6
15
12
227.5
2
8
11
3
2
4
28
6
2
6
18
19
20
15
36
.6
.7
14
7
2
19
51
184.3
9
8
.3
8
18
10
20
11
10
6
3
8
82
101
1
12
218
3
3
4
18
9
11
24
486
46
28
32
9
5C
2
33
11
13
17
449
94
77
108
49
.5
61
7
43
48
936.5
17
25
3
4
33
2
3
21
11
29
13
45
202
84
6
6
9
.5
.8
38
13
23
44
85
511.3
1
00
-------
EXHIBIT 9
Percentage of School Districts in the Population
Requiring Specific Corrective Action
1
2
3
4
5
6
7
8
9
lOa
lOb
lOc
lOd
lOe
11
12
13
14
15
16
17
18
19
20
TOTAL
970
1213
337
242
142
0
26
1191
98
32
0
30
17
41
182
51
117
67
0
81
337
289
23
186
5672
21
13
18
16
15
17
41
7
11
2
24
11
21
25
17
3
31
17
18
23
3%
7
23
4%
1%
3%
1%
6
4
4
2
18
1%
3%
7%
2
2
4
21
5
2
2
8
3%
2%
.1%
5%
13
8
20
11
3
4
1
4
•
14%
9%
11%
6
7
1
11
3
5
7
4%
8%
1%
2%
17
1
1
7
8
29
5
23
21 See footnote 5 in Exhibit n
21 Percentage of Total School Districts =/k«i % Affected
\Total Number
Where i- 1-20
j» corrective action
k» School District
School Districts i j V
of School Districts i \J
TSDij
110
-------
derived in a manner similar to the one for population estimates
above. The above school and school district level rates,
and SDA^. are multiplied by the estimated population of total
affected schools and school districts to develop these estimates.
(See Exhibits 8,9 and 10).
2. RESULTS
The population estimates for the number of school districts,
schools and students affected for the individual clusters are presented
in Exhibit 5. Affected school districts and population being defined
as those for which at least one type of control action is recommended.
Affected students are those students exposed to asbestos-containing
material. National estimates of affected population are as follows:
School Districts: 5,672
Schools: 13,347
Students: 4,032,508.
The estimate for total school districts affected can also be
divided according to the degree to which they are affected. The number
of affected school districts will not add up to the total as some
school districts may have more than one control action recommended.
Estimates of school districts by type of recommended corrective action
are as follows:
Inspection: (includes initial inspection and re-
inspection) : 2858
Bulk sampling: 186
Removal (which includes disposal and air quantification) : 227.5
111
-------
The Number and Degree to Which the Schools in the Population are Affected
(1 *
I
•>.
I
4
r)
(
7
H
')
)0(d)
10(b)
U)(<:)
1U(,1)
1"(9)
11
1?
1 1
14
J5
U.
17
10
]')
20
TOTAL
1412
1055
560
1677
67'J
0
46
1016
7'l
168
0
56
229
178
246
121
630
12)
0
285
1B87
860
24
1416
11347
ff % / *
15
41
55
202
•152
HB2
IS 16
ff *"" / *
15
ll)l)
f,(>
202
24
928
Ii54
(
29
8
22
8
75
25
11
7
/ 0
iOl
1 12
1M
11
11J
.10
202
61
L023
r % /
5
15
45
4
7
17
50
40
11
21
f>0
67
247
302
73
12
38
61
252
32
404
430
1018
ff *
19
14
1
22
32
82
83
25
11
25
14
14
/
269
151
16
151
514
137
191
45
27
30
270
123
1924
ff %
4H
40
. 7J
<.
loo
17
33
25
29
/ •"
672
224
1213
147
79
9
82
472
246
3164
ff *
14
60
3
11
100
3
83
56
40
100
89
29
34
/
1'il
3U,
4M
75
4(>
6
47
137
252
123
253
539
4UI1
2502
ff %
20
/
126
126
-I/ Pircinlay* ol Affaclcd Sdiooli Needing • Specific Conecllv* Action -
(Number o« AHecled Schoolinl - SA|j Wlieiel-120
Tola! AKecled Scliooli) l-Correcllve Action
m
X
CO
H
-------
Marking: 184
Encapsulation: 486
Marking of Boiler Rooms and Pipes: 936.5
Encapsulation of Boiler Rooms and Pipes: 511
The estimate for total public schools affected can also be divided
according to the degree to which they are affected. These estimates
are as follows:
Initial Inspection: 1536
Bulk Sampling: 1154
Removal (Which includes disposal and air quantification):
1023
Marking (Includes reinspection): 1918
Encapsulation (Includes marking and reinspection): 1924
Marking of Boiler Rooms and Pipes (Includes reinspection):
3164
Encapsulation of Boiler Rooms and Pipes (Includes marking
and reinspection): 2502
Removal for Boiler Room Asbestos: 126.
3. LIMITATIONS OF DATA AND RESULTS
The data developed in this task have limitations which affect
113
-------
the reliability of the above population estimates. The limitations
which have been mentioned throughout this section are reiterated in
the following paragraphs:
Perhaps the most important limitation concerns the method
by which sample school districts were chosen and the size
of the sample. The sample was chosen, as previously
mentioned, from the group of school districts who responded
to EPA's asbestos survey. This suggests a bias in that this
small group of respondents may have uncharacteristically
active, asbestos control programs. A survey of non-
respondents was conducted to attempt to determine if
respondents were representative of the total population.
This survey did indicate areas of bias for which corrective
measures were taken, but it was qualitative at best and,
therefore, could not conclusively state whether bias existed.
Even if it could be proven that the above respondents did
not present an inordinately skewed picture of the
population, the size of the sample does not impart
statistical rigor to our estimates. As stated earlier, it
represents only 1.6% of a population of about 16,000 school
districts.
The variables that formed the bases for stratification were
chosen based on two conclusions. The first is that they may
affect the cost of complying with the regulation. The second
was a practical consideration that any data that are used
be readily available for the universe of school districts.
The time and resource constraints of this project made this
important. Therefore, certain potential variables, such as
weather, age of buildings, and even a more accurate location
indicator could not be included.
114
-------
There is a good likelihood of inconsistency in the
application of the asbestos exposure assessment algorithm.
The algorithm assumes that everyone using it will recognize
a situation for analysis and be consistent in the assessment
of that situation. This may not have been a valid assumption
in all cases, partly because the algorithm is somewhat
subjective, and partly because people inspecting the schools
for friable, potential asbestos-containing materials vary
from health and EPA inspectors to superintendents who may
not have an adequate technical background.
Finally, there is the possibility of data unreliability due
to incomplete test results. As was mentioned before, some
algorithm scores were incomplete due to pending bulk tests.
A decision, for the purposes of analysis, was made in these
cases, using the judgment of the maintenance personnel as a
guide. While necessary, the judgments, if made incorrectly,
could skew the population estimates.
The estimates presented should not be taken as statistically
rigorous due to the limitations mentioned above. They are presented,
however, as ballpark numbers which could be useful to EPA decision-
makers in determining the relative cost implications of the various
recommended asbestos control actions.
115
-------
IV. ESTIMATION OF TOTAL COSTS AND IMPACTS
OF VOLUNTARY ASBESTOS
CONTROL ACTIONS
This chapter presents the estimates of total costs and other
impacts associated with the various asbestos control activities. Total
costs are identified by cluster and individual asbestos control actions
at the school district, state, and national levels. Other impacts
analyzed are:
Community, impacts including possible student displacements,
change in class size, school days lost (loss due to non-
availability of part or all of a school because of corrective
activities), change in student/teacher ratios, school
closings, and job loss
Financial burdens on the most heavily impacted school
districts in the study sample
Sources of state, local, and federal funds or assistance
available to school districts to meet the cost of asbestos
corrective action(s)
Positive community impacts which include the estimated
number of students and teachers removed from asbestos risk;
and the estimated number of jobs created to control asbestos
due to the intended EPA regulation.
This chapter begins with a definition of the data sources used
116
-------
and a discussion of adjustments made to the data for use in deriving
cost estimates. This section is followed by a description of the
methodology used to develop school district cost estimates, and
extrapolate these estimates to the state and national levels. The
final section of the chapter reviews other impacts related to the
voluntary control actions including the operational impacts on school
districts, budget impacts, and positive impacts such as new jobs
created, and the number of students and teachers removed from asbestos
risk.
1. COST ESTIMATES BY SAMPLE CLUSTERS
This section reviews how estimates developed in Chapters II and
III were adjusted and formulated into school district cost estimates
for control actions. The remainder of the section discusses state and
national level cost extrapolations, and modifications to the school
district cost estimating procedure for extrapolation purposes.
(1) Data Sources
Estimates presented in Chapters II and III formed the basis
for the estimation of the total costs of voluntary asbestos
control actions. Chapter II presented unit cost estimates for
each corrective action by state; and Chapter III furnished
estimates of the number of school districts for which each
control action is recommended and the severity of the problem
(in terms of square feet of asbestos material to be controlled).
The combination of these two data sources resulted in total cost
estimates.
Although the estimates presented in Chapters II and III
provided the most essential information for estimating total
costs of the voluntary control actions, several intermediate steps
were necessary before the actual total cost estimates could be
117
-------
developed. These intermediate steps are discussed in the
following section.
(2) Adjustments To Unit Cost Estimates
Unit cost estimates were compiled in Chapter III for states
within EPA Regions. It was, therefore, necessary to convert state
unit cost estimates to cluster level figures. This process
involved identifying individual states and the number of these
states in each of the twenty clusters of our sample. Within a
cluster, each state's unit cost estimate (from Tables 1 to 12)
was weighted by the relative frequency of occurrence of the state
(i.e., the number of times a sample school district from a given
state appeared in the cluster, divided by the total number of
school districts in -the cluster). The weighted cost estimates
from each state were then totaled to produce a weighted average
cost estimate for each cluster. This computation was done for
each control action in the clusters. These unit cost estimates
for control action in each cluster are displayed in Table 16.
In developing weighted unit cost averages, it was sometimes
necessary to use EPA regional or national unit cost averages
where state data did not exist. In these cases the general rule
followed was that the corresponding EPA regional averages were
used. If EPA regional average did not exist, the national average
for the control action was used.
The cluster unit costs are limited, because they do not
represent each cluster exclusively. By using state average cost
estimates for a control action, a cluster's unit cost estimate is
comprised of cost estimate for work done in all school districts
by a contractor. This is regardless of whether the work done by
a contractor is for a school district which belongs to a
particular cluster or not. Ideally, contractors' cost estimates
110
-------
unit cost for voluntary Corrective Action Per Cluster
CORRECTIVE
ACTION
CLUSTER
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
INSPECTION
PER SCHOOL
19.31
12.13
76.22
12.75
15.56
9.57
95.09
16.76
19.25
23.65
69.68
12.80
20.18
50.90
11.28
25.61
18.10
20.50
16.14
16.84
BULK TESTING
PETROGRAPHIC
MICROSCOPY
PER SAMPLE
44.32
78.58
36.01
38.40
99.92
72.09
34.53
40.34
73.61
55.43
36.47
72.60
86.55
57.58
42.50
43.00
43.31
48.39
38.06
40.84
ELECTRON
MICROSCOPY
PER SAMPLE
181.84
114.16
194.09
164.94
120.14
108.33
195.68
174.03
108.33
160.47
199.40
108.33
129.16
204.87
140.00
169.23
170.85
191.12
184.87
158.88
X-RAY
DIFFRACTION
PER SAMPLE
67.55
96.17
64.55
71.25
92.30
87.08
65.00
73.32
85.10
79.80
64.00
86.42
117.88
64.25
95.00
65.00
63.17
61.37
65.00
67.64
ENCAPSULATION
PER FT2.
OF ASBESTOS
2.08
2.19
2.93
2.94
1.86
1.96
3.26
1.96
2.10
2.78
2.84
2.01
2.47
2.71
2.12
1.80
1.85
1.66
2.65
2.66
REMOVAL PER
FT. .OF ASBESTOS
5.06
5.76
8.10
6.94
5.26
1.96
9.50
4.16
4.87
7.57
8.05
4.91
7.20
7.07
5.00
3.50
4.79
4.09
7.00
5.91
DISPOSAL
PER FT? ASBESTOS
.43
.16
.68
.60
.11
.11
.84
.33
.09
.44
.68
.10
.15
.56
.07
.15
.36
.35
.56
.60
AIR QUANTIFICATION
AIR MONITORING
(SAMPLING)
PER HOUR
33.22
39.17
38.80
29.99
33.78
34.10
40.39
48.73
34.10
35.54
38.70
34.10
62.36
37.42
30.00
33.25
33.18
35.39
37.63
30.93
LAB COST -
ELECTRON MICRO-
SCOPY
PER SAMPLE
230.01
118.26
190.33
213.68
126.92
143.75
185.63
257.57
117.19
187.31
195.05
134.90
100.52
204.22
- 100.00
189.43
221.36
244.45
187.22
495.62
LAB COST -
OPTICAL
MICROSCOPY
PER SAMPLE
34.09
81.22
31.48
35.55
96.17
93.18
34.76
32.61
77.95
44.97
31.02
88.10
79.01
30.96
56.33
22.00
31.12
30.79
29.45
40.09
tr1
W
CTV
-------
should be differentiated by clusters within states, but this
approach would require more extensive surveys than were possible
during this study.
Cluster unit cost estimates, at this point, were not
standardized. That is, the control action cost estimates were
not always based on the same units. For example, inspection cost
estimates were given on a per school basis while bulk testing
cost estimates were given per sample tested. It was necessary
to standardize these varying units to a common standard unit.
The standard unit selected for control activity cost was
the affected school district, t/ Table 17 provides a summary
of the standardization methodology used for each control action.
In Table 17, the cluster unit costs for each control action was
adjusted to the school district scale by multiplying it by an
indicator of the amount of affected area in a school district.
These indicators of affected area included tne average number of
affected schools per school district, the average square footage
of asbestos per school district or some variation of these amounts
based on hours of sampling, number of samples, and square footage
standards for each test. The result of the standardization
process, is a set of affected school district unit cost estimates.
Affected school district unit cost estimates are represented by
ACij, where i designates a cluster and j a corrective activity.
Table 18 exhibits affected school district unit cost estimates
by cluster.
Each affected school district unit cost estimate assumes
that all of a school district's asbestos will be the subject of
^I/Affected school districts are those which require one or more
asbestos control action based on the asbestos exposure assessment
algorithm.
120
-------
TABLE 17
Standardization of Cluster Cost to
Affected School District Costs
ASBESTOS
CORRECTIVE
ACTION
Inspection
Bulk Testing:
Petrographic test
X-Ray Diffraction
Electron Microscopy
Encapsulation
Removal
Disposal
Air Quantification
Air Monitoring
Lab-optical
Microscopy
Uab-Electron
Microscopy
CLUSTER
UNIT COST
ADJUSTMENTS TO CLUSTER UNIT COSTS
Cost of inspection per
school
Cost of one
petrographic bulk test
Cost of one X-Ray
Diffraction bulk test
Cost of one Electron
Microscopy bulk test
Cost of encapsulation
per square foot of
asbestos
Cost of removal per
square foot of
asbestos
Cost of disposal per
square foot of
asbestos
Cost per hour of
Air monitoring
Lab cost per sample
of optical microscopy
test
Lab cost per sample
of electron micros-
test
Cost of inspection/sch.
Cost of one
petrographic bulk test
Cost of one X-Ray
X-Ray diffraction bulk
ten
Cost of one Electron
Microscopy bulk test
X Average number of affected ^
schools/school district in a
given cluster i
Average square footage^
of asbestos per school district
in a given cluster i
sooo.2/
Average square footage"
of asbestos per school district
in a given cluster i
5000-2/
Average square footage^*
of asbestos per school district
in a given cluster i
Cost of one Encapsulation X
per square foot of asbes-
tos
Cost of one removal per
square foot of asbestos
foot of asbestos
Cost of disposal per
square foot of asbestos
Cost per hour of 16 hrs.3/ X
Air monitoring
Lab cost per sample X 5
of optical microscopy Spl.
test
Lab cost per sample X 5
of electron microscopy Spl.
test
50002/
Average square footage of
asbestos per affected school
school districts in a given
cluster i
Average square footage of
asbestos per affected school
district in a given cluster i
Average square footage of
per affected school district
in a given cluster i
Average number of affected
schools per affected school
districts in a given duster i
Average number of affected
schools per affected school
district in a given cluster i
Average number of affected
schools par affected school
district in a given cluster i
AFFECTED SCHOOL DISTRICT
UNIT COSTS (ACjj)
Cost of inspecting all affected
schools in a school district in a
given cluster
Cost of petrographic bulk testing
in all affected schools in a school
district in a given cluster
Cost of X-Ray diffraction bulk
testing in all affected schools in a
in a school district in a given cluster
Cost of Electron Microscopy bulk
testing in all affected schools in a
given cluster
Cost of encapsulating all affected
schools in a school district in a
given duster i
Cost of removing asbestos from
all affected schools in a school
district in a given duster i
Cost of disposing of asbestos from
all affected schools in a school
district in a given duster i
Cost of air sampling in all affected
school in a school district in a given
duster!
Cost of optical lab test in a school
district in a given duster i
Costs of electron lab test in all
affected schools in a school
in a school district in a given
duster!
Source - Arthur Young & Company School Districts Sample. See Appendix A.
a One bulk test per 5000 square feet of asbestos is based on specification provided in "Asbestos
Containing Materials in School Buildings: A Guidance Document". Part 1 (Washington, D.C.: EPA-OTS, March 1979). p. 10.
Based on NIOSH: "Asbestos Fibers in Air: Analytical Method" (Method No. P&CAM239,3/30/77) which states that "If one have very little
idea of airborne fiber and paniculate levels, the best procedure is to take several long samples (as one 8-hour or two consecutive 4-hour samples) _
m conjunction with several short samples (as four consecutive 2-hour or eight consecutive 1-hour samples)". Any permutation of test combinations
would equal 16 total sample hours.
4/
Five, samples * one 8-hour sample plus four 2-hour samples. See footnote No. 3.
121
-------
AFFECTED SCHOOL DISTRICT UNIT COSTS.
CORRECTIVE
ACTION
CLUSTER
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
INSPECTION
PER SCHOOL
48.27
12.13
0
42.08
38.90
0
0
20.11
19.25
182.11
69.6(1
16.64
40.36
0
0
0
68.97
41.00
0
50.52
BULK TESTING
PETROGRAPHIC
MICROSCOPY
PER SAMPLE
558.43
220.02
0
39.80
1189.05
0
0
.• •*>
177.50
73.61
2616.30
36.47
384.78
86.55
0
0
0
381.13
416.16
0
40.84
ELECTRON
MICROSCOPY
PER SAMPLE
2291.18
319.65
0
230.92
1429.47
0
0
765.73
108.33
7574.18
199.40
574.15
129.16
0
0
0
1503.48
1643.63
0
158.88
X-RAY
DIFFRACTION
PER SAMPLE
851.13
269.28
0
102.23
1095.42
0
0
322.92
85.10
J767.13
64.00
457.35
117.88
0
0
0
558.49
524.99
0
67.64
in
ENCAPSULATION
PER FT. ASBESTO
130,555
30,660
0
21,092
110,372
0
0
42,060
1,680
656,180
852
54,899
12,350
0
0
0
81,779
71,003
0
9,166
REMOVAL. PER
FT? ABSESTOS
317,601
80,640
0
58,109
313,909
0
0
91,607
3,896
,786,79:
2415
129,924
36,000
0
0
0
211,742
74,942
0
20,366
ui
DISPOSAL PER
FT. OF ASBESTO
26,99(1
2,24C
0
4,304
6,527
0
0
7,267
72
103, 05C
204
2646
750
0
0
0
15,914
14,971
0
2,068
AIR QUANTIFICATION
AIR MONITOR-
ING (SAMPLING)
PER HOUR
1328.00
1253.44
0
1247.58
1251.20
0
0
1013.58
545.60
4378.53
619.20
818.40
1035.52
0
0
0
1592.64
1245.73
0
1484.64
3*IdWVS H3d
AdODSOHOIW
NOH1D3TS
- ISOD ssn
1
2875.13
1182.60
0
2777.84
1586.50
0
0
1674.21
585.95
7211.44
975.75
1011.75
1005.20
0
0
0
3320.40
2688.95
0
7434.30
LAB COST -
OPTICAL
MICROSCOPY
1
426.13
812.20
0
462.15
1202.13
0
0
211.97
389.75
1731.35
155.10
660.75
790.10
0
0
0
2116.80
340.67
0
601.35
g
f
w
M
CD
-------
the respective asbestos control activity. Thus, each unit cost
estimate does not account for the possibility that only a portion
of the asbestos may be removed, while other areas would be
encapsulated. In other words, the cost estimates in Table 18 are
mutually exclusive of one another and are calculated on the basis
of the average amount of total asbestos per school district in
each cluster.
2. EXTRAPOLATED COST ESTIMATES
The affected school district unit cost estimates in Table 18 are
the base from which school district, state, and national cost estimates
are developed. The following sections outline the methods used to
develop aggregate cost estimates.
(1) Cost Estimates for School Districts
To calculate average school district cost estimates by
cluster, the affected school district unit cost estimates of the
previous section must be modified to reflect the actual mix of
control activities recommended for a school district.—' In other
words, each AC., must be weighted by the frequency of the
corresponding control action. Mathematically, this is represented
as :
ACi;. x SDA^ = Cjj (1)
In this equation, AC^ . is as defined earlier, SDA^j is the
proportion of affected school districts in a cluster (j) for
—/See Section 1(6), Chapter III, which discusses the process of
identifying the mix of corrective activities in all affected school
districts and the total number of school districts in a sample cluster.
123
-------
which a control action (j) is recommended, and C^ is the cost
estimate for a control action (j) for an average affected school
district in a cluster (i).
Equation (1) was applied to each cluster and recommended
control activity to estimate average school district cost
estimates for control actions. These average school district
cost estimates are summarized in Table 19.
The school district cost estimates in Table 19 must be qualified.
Because these cost estimates are built from averages, it would
be unlikely to find an actual school district which has an
identical cost situation as those in Table 19. The school district
cost estimates are, however, considered reasonable for estimation
purposes.
(2) Aggregate Cost estimates for States
Aggregate state cost estimates for control activities in
individual clusters were developed in much the same way as school
district cost estimates. Equation (2) below describes the
calculation of aggregate state (k) costs for control action (j)
by cluster (i) .
AC.. X TSDij X SNik = SCijk (2)
In equation (2), AC^ is as defined earlier the affected school
district unit cost estimate for a control action (j) in cluster
(i). TSDj^ is the proportion of school districts in cluster (i)
for which control activity (j) is recommended, and SNife is the
total number of school districts from state (k) in cluster (i).
SNik *s not a sample total, but the universe total for each
cluster. The product of (AC^) and (TSDj^ X SNi)c) is basically
the product of the estimated cost per school district for a
124
-------
Cost of voluntary Corrective Actions by school District
NJ
01
CORRECTIVE
ACTION
CLUSTER
1
2
3
4
5
6
7
8
9
f 3
10 6
9-10
^
11
12
13
14
15
16
17
18
19
20
INSPECTION
31.29
6.06
0
18.14
9.00
0
0
11.91
9.63
24.89
8.01
43.58
19.50
44. 8J
5.55
6.93
0
0
0
20.74
17.56
0
22.97
BULK TESTING
PETRCG5APHIC
MICROSCOPY
56.
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
16.
19.
ELECTRON
MICROSCOPY
229.
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
68.
72.
X-RAY
DIFFRACTION
85.
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
27.
31.
2
SNCAPSULATIO
11,097.
2,554.
0
67.
9,006.
0
0
7,710.
0
66,471.
0
131,827.
70,211.
85.
3,047.
0
0
0
0
2,707.
5,915.
0
0
|
0
11,201
0
121.
15,287
0
0
0
0
29,839
0
0
111,675
0
7211.
1998.
0
0
0
9528.
7295.
0
0
DISPOSAL
0
311.
0
1627.
318.
0
0
0
0
1734.
0
0
6491.
0
149.
42.
0
0
0
716.
624.
0
0
AIR QUANTIFICATION
O
AIR MONITOR-
ING (SAMPLIN
0
174
0
35.
66.
0
0
0
0
73.
0
0
274.
0
45.
57.
0
0
0
72.
52.
0
0
LAB COST -
ELECTRON
MICROSCOPY
0
164.
0
78.
77.
0
0
0
0
120.
0
0
451.
0
56.
56.
0
0
0
149.
112.
0
0
LAB COST -
OPTICAL
MICROSCOPY
0
M3.
0
33.
59.
0
0
0
0
29.
0
0
108.
0
37.
44.
0
0
0
95.
14.
0
0
tr"
M
-------
control action and the number of school districts in a state for
which that control action is recommended. A table for each
cluster, listing states and their estimated control action costs
is presented in Appendix B. Table 20 below, summarizes the
individual tables by giving state total control activity cost
estimates aggregated over all clusters.
Of note in equation (2) is the replacement of SDA.. with
TSDij as a control action multiplier. For state cost estimates,
this figure is the proportion of all schools, as opposed to the
proportion of affected schools for school district cost
estimates. The reason for using different proportions is that
for school districts no extrapolation was necessary. The emphasis
at the school district level is on what control action is
recommended for how much of an average school district's asbestos
affected area. Whereas, with state and national aggregate cost
estimates, an extrapolation is necessary. Here, the intent was
to identify a multiplier from the sample points for which state
and national data were available.
(3) Aggregate Cost Estimates for the Nation
Aggregate national costs were developed in an identical
manner to total state costs. The only difference between the
methods, is that for national cost estimates the total number of
school districts in a cluster for the nation, N., replaced SN.^.
National cost estimates, NC^, for a control action (j) in a
cluster (i) are represented by:
AC^ X TSDi;j x Ni = NCij <3>
Aggregate national cost estimates for each voluntary control
activity are presented in Table 21. The bottom row in Table 21
represents the total national cost estimate for individual
control actions aggregated over all clusters.
126
-------
Summary
Cost of voluntary corrective Actions by State
Corn
-S
o
o
1
MI
MN
MS
MO
MT
NB
NV
Nil
NJ
NM
NY
NC
ND
OH
OK
OR
PA
RT
SC
SD
TN
TX
icliw
•- m
«. o B
546
' 433
154
524
581
1,109
13
155
573
87
768
137
321
641
616
328
526
37
95
185
138
1,058
c
4,756
3,613
1,186
3,077
1,854
2,704
0
1,453
4,891
277
6,731
1,092
824
2,354
1,091
187
4,632
319
796
523
665
9,268
BULK TESTING
Patrographic
Microscopy
3,760
5,301
1,032
0
0
0
0
1,961
1,513
0
4,747
412
0
3,306
0
38
1,616
138
474
0
0
0
Elactron
Microscopy
15,550
21,917
4,463
0
0
0
0
8,185
6,384
0
20,342
1,975
0
13,973
0
159
6,788
568
2,100
0
0
0
c
o
•a
II
5,736
8,087
1,575
0
0
0
0
2,993
2,310
0
7,246
630
0
5,046
0
63
2,466
211
725
0
0
0
e
i
1
ui
1,568,899
1,464,010
247,110
1,115,541
386,635
1,044,077
0
547,444
2,320,463
164,260
2,774,223
114,213
234,034
2,090,944
372,468
242,252
2,640,800
95,559
149,834
192,534
30,054
656,201
Removal
606,806
33,991
57,235
t
1,354,011
1,602,756
3,131,926
0
17,569
487,473
389,693
652,505
115,674
927,928
626,313
1,420,730
384,566
1,403,567
73,416
87,619
619,538
140,098
2,311,429
a
I
a
46,180
12,467
4,363
36,039
44,145
86,616
0
1,451
38,445
9,180
55,804
8,773
25,396
49,575
38,311
22,353
96,193
5,714
6,628
15,856
10,488
61,251
AIR QUANTIFICATION
Air Monhoring
(Sampling)
i
I
8,458
1,311
881
19,726
24,404
48,214
0
144
3,622
2,939
4,643
1,507
13,825
4,972
20,780
828
7,636
561
941
7,746
1,574
32,603
j|
17,996
2,786
1,940
18,832
23,094
45,543
0
310
7,649
3,629
10,030
3,286
13,104
10,570
19,786
1,363
15,505
1,183
2,026
7,586
3,393
31,191
Lab Cost-Optional
Microscopy
800
1,195
428
13,126
16,232
31,313
0
71
3,474
2,568
1,295
959
9,015
4,253
13,679
327
7,134
579
783
5,211
1,323
21,755
ro
-
B
f
M
-------
summary
Cost of voluntary Corrective Actions by state
Coif
Ap
a
o
g
tn
AL
AK
AZ
AR
CA
CO
CT
DE
D.C.
FL
GA
III
ID
IL
IN
IA
KS
KY
LA
ME
MD
MA
Ktivt
Number of
Scnool Oistr. in
Stata in dinar
1211
35
226
371
1,054
178
147
16
1
65
184
1
112
946
291
445
303
179
66
278
24
356
Inspection
1,210
0
113
1,687
1,096
836
1,269
146
21
530
1,768
0
22
5,521
2,286
1,932
1,514
1,651
423
2,727
203
2,752
BULK TESTING
j
Pctro graphic
Microscopy
453
0
38
0
254
0
803
91
0
178
1,444
0
0
7,388
1,684
0
0
1,413
0
4,339
2
2,459
Elactron !
Microscopy
1
1
2,996
0
159
0
1,067
0
3,449
446
0
Q24
6,820
0
0
30,353
7,026
0
0
6,408
0
18,099
45
10,514
X-Ray
Diffraction
697
0
63
0
423
0
1,226
138
0
272
2,209
0
0
11,271
2,569
0
0
2,159
0
6,621
3
3,754
Encapsulation
209,636
0
161,286
232,684
2,248,891
149,300
502,627
24,328
62,768
64,938
364,150
0
79,982
3,262,903
685,962
1,421,501
711,718
378,047
251,796
939,170
74,082
1,150,891
1
ec
82,536
0
25.6,377
929,682
3,589,281
506,681
173,857
9,284
28,486
79,958
98,959
0
128,189
472,905
252,603
1,307,658
880,096
91,930
529,254
12,596
69,099
351,943
b
7,025
0
14,902
25,392
208,625
13,084
14,840
729
1,656
7,161
7,554
0
7,451
36,614
19,152
34,511
23,133
7,117
9,512
1,078
4,734
28,375
AIR QUANTIFICATION
Air Monitoring
(Sampling)
i
589
0
552
13,953
7,724
6,991
1,239
101
61
933
935
0
276
3,720
2,283
18,028
11,837
967
2,537
90
463
2,D99
1
Lab Cost-Eltctroni
Microscopy
i
1,270
0
909
13,230
12,721
6,744
2,674
219
101
1,994
2,771
0
454
7,853
4,852
17,337
11,379
2,088
2,834
194
960
5,527
i
i
Lab Cost-Optional)
Microscopy
1
191
0
218
9,123
3,054
4,738
367
62
24
892
858
0
109
3,859
2,315
11,978
7,880
699
2,145
24
390
1,984
to
00
I
f
W
to
o
-------
Summary
Cost of voluntary corrective Actions by state
Corrective
Ac
•a
o
o
1
UT
VT
VA
WA
WV
WI
WY
«B_
B •-
Number of
School Distr. i
State in Clustl
37
247
135
299
55
418
53
B
i
&
B
138
2,335
1,508
213
435
3,430
128
BULK TESTING
f*
£'s
0
4,067
646
49
140
4,690
0
£
ojj
jss
0
16,715
2,787
204
613
19,655
0
E
O
ii
X a
0
6,204
987
81
214
7,157
0
B
O
'g
I
8
B
Ul
78,537
828,438
883,675
561,085
227,815
1,449,323
86,509
oc
176,502
1,743
430,729
1
897,320
123,692
141,381
219,724
1
.a
a
3,990
129
27,103
52,156
7,819
11,835
5,329
AIR QUANTIFICATION
01
_B
If
II
-------
Cost of voluntary corrective Actions for the Nation
10
o
\ Ciiractlw
\ Aedm
Ctutm • \
]
2
3
4
5
6
7
a
9
3
10 6
7
9-10
11
12
13
14
15
16
17
18
19
20
,
30425.
7333.
0
4398.
1281.
0
0
14634.
935.
799.
249.
750-
809.
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0
0
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0
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0
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0
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0
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0
0
0
0
0
0
0
0
375.
343.
54470.
BULK TESTING
326418.
n
0
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B
il
81926.
0
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630.
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3136518.
0
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1285613.
0
0
9475613.
0
10733297.
0
25683247.
13672177.
15379.
156792.
0
0
0
0
916415.
1710036.
0
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77744279.
]
0
13499136.
0
1189330.
2179784.
0
0
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4871168.
0
0
21920254.
0
371063.
235872.
0
0
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3285389.
2106652.
0
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48858648.
,
0
374976.
0
28037.
45323.
0
0
0
0
283134.
0
0
1274101.
0
7557.
4914.
0
0
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246922.
180281 .
0
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2446045.
A •* Jin mftmmim
AIT MQMionng :
(Swiping) 1
! >
0
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0
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9381.
0
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0
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1 QUANTIFICAT
31
0
197667.
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11017.
0
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0
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ION
o t
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0
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0
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5177.
0
0
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4102.
0
0
214213.
NOTE: Total National Costs " Sum of all corrective activities and using the least cost methods
for bulk testing (petrographic microscopy) and air sample analysis
(optical Microscopy)
8
F
M
- $(80,642 + 54,470 + 77,744,279 + 48,858,648 + 2,446,045 + 334,054 + 214,213)
- $129.7 Million
-------
Total national cost estimates for each voluntary control
action (inspection, petrographic bulk testing, encapsulation,
removal, disposal, air sampling, and optical microscropy lab
tests), when added, provides a grand total national cost estimates
for voluntary asbestos control action of $129.7 million. This
figure represents the cost estimate to local school districts if
all of the indicated control actions were undertaken. This figure
would obviously be different if different choices of control
actions were eventually made. Of note is the fact that the least
expensive corrective actions were not chosen in all cases. Also
of note is that the above total national cost is based on the
least expensive (and most available) methods of bulk testing and
air quantification. Any change to alternative methods of bulk
test and air quantification will increase these total cost
estimates.
3. IMPACTS
In addition to the direct costs of the voluntary control
activities, other impacts are anticipated. These impacts fall into
three categories: (1) negative community impacts, (2) financial
impacts, and (3) positive community impacts. These impacts are expected
to be most severe for school districts, and are, therefore, analyzed
at that level. This section reviews the nature of these three impact
areas, and potential ways to lessen them through various forms of
funding and assistance.
(1) Negative Community Impacts
Six areas of negative community impacts were identified.
These include:
Students temporarily displaced to other classrooms whether
in the same building or another while asbestos-related work
takes place
131
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Change in class size due to student displacements
Change in student/teacher ratio due to job loss or student
displacement
Temporary or permanent school closings due to the severity
of the asbestos problem
Job loss due to school closings.
Information on negative community impacts was collected from
school districts in the study sample. As discussed earlier, the
school district administrators were asked by letter if they could
estimate the above negative impacts. In their letters, they were
asked to coordinate their answers to the responses of their
maintenance personnel (regarding the amount of possible
corrective action undertaken in their school districts).
Only a limited number of respondents addressed the negative
impacts question. Those who did respond all felt that there would
be no adverse community impacts of the types listed above. Even
those schools that appeared to have potentially significant
asbestos problems felt that there would be no negative community
impacts.
Many of the respondents stated that the reason for the lack
of negative impacts was that school districts would not need to
perform any voluntary corrective activities during school hours.
School districts, unlike other organizations and businesses, have
extended summer and holiday breaks during which to perform
corrective maintenance activities. This would not require them
to interrupt normal operations.
As a follow-up to the letters, the twenty most severely
132
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impacted school districts in the sample which may have extensive
removal or encapsulation situations, were contacted for
interviews. In the follow-up telephone interviews, the issue of
negative community impacts was investigated further by providing
these school districts with our estimates of their potential
costs. To simulate a worst case situation, we also imposed a
hypothetical time constraint, viz. that asbestos corrective
activity may have to be performed immediately.
As a result of the above interviews, some of the respondents'
perception of potential negative impacts were altered. Of the
twenty school districts contacted, one school indicated to
possibility of permanent closure, displacing fifty-two students
and with two teachers being furloughed. Seven of the remaining
school districts may temporarily close a total of twenty-three
buildings. These temporary closings could affect a maximum of
10,408 students. In most cases, no indication of the duration of
temporary closings could be determined (though two to three months
per building was average for two of the three respondents). In
no cases were the administrators able to estimate changes in the
student/teacher ratios or changes in class size. Once again, it
must be noted that these negative impacts were only seen as
alternatives in light of having to perform any voluntary
corrective actions immediately. If this condition did not exist
some of these negative impacts may not have been surfaced. It
is interesting to note that twelve of the twenty school districts
contacted foresaw no negative impacts even with this constraint
imposed. These school districts stated that the work was in
building areas such as gymnasiums or special activity rooms whicn
could be closed temporarily without displacing students.
Costs were a serious problem in only one case — the
potential closing identified above. Seventeen of the other school
administrators stated that the money could be raised from local
133
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budgets (primarily capital as opposed to operating budgets). The
remaining two school districts, (in New Mexico), are receiving
funding for removal from the state government—'' The school
districts which would finance corrective activities out of tneir
local budgets, all stated that it would result in a corresponding
decrease in some other already budgeted maintenance item. None
of the school districts felt that they would forego correcting
their asbestos problems if outside funding was not made available,
although in some cases it would not be corrected as soon.
In summary, the possible negative community impacts are
anticipated to be few and rare in occurrence. Although the
response rate was not as great as that for the impacts estimated
using the EPA algorithm, a consistent pattern was exhibited in
those responses that were received. The trend of these responses
suggests that the negative community impacts will be minimal.
(2) Financial Impacts on School Districts
The above twenty relatively severely impacted school
districts were analyzed regarding the budget impacts of their
voluntary asbestos corrective actions.
The school districts' 1978-79 total, operating, and capital
expenditures were analyzed to determine how much of a financial
burden the voluntary correction of an asbestos problem will
present. The voluntary correction costs for each school district
were estimated on the basis of their specific asbestos square
footage amounts and their specific responses to the "Exposure
Assessment Algorithm". The unit cost estimates which were used
to estimate total costs were those presented in Chapter II for
—/See section on State Financial Mechanisms for a discussion of
New Mexico's assistance program.
134
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the state in which the school district resides. State costs were
able to be used in these cases because of the limited number
being estimated as opposed to developing extrapolations, where
cluster unit costs were used. It was reasoned that state unit
costs would provide more accurate estimates for financial
comparison.
These cost estimates were then compared to expenditure
estimates for the same school districtsJl/ Three categories of
school district expenditures were compared to the asbestos
voluntary control cost estimates; total expenditures, operating
expenditures, and capital expenditures. The results of this
comparison are presented in Table 22.
The results in Table 22 are, as mentioned, for the school
districts in the samples which have the most severe asbestos
problems. In sixteen of the twenty cases, removal is recommended
for some or all of the asbestos. In the remaining four school
districts, extensive encapsulation is recommended.
Of interest are the large percentages of voluntary/
corrective cost estimates to total capital expenditures (the
range being from 0.09% to 158.62% of total annual capital
expenditures). In some school districts the cost of voluntarily
correcting the asbestos problems will far exceed the estimated
total annual capital expenditure amount. These patterns are of
—/ 1978-79 expenditures were estimated from 1977-78 total
expenditures per student. This figure was extrapolated to 1978-
79 on the basis of that school year's number of students.
Estimated 1978-79 total expenditures were then broken down into
operating and capital expenditures by using a 92% and 8%
distribution formulas. These distributions are based on average
distribution for the school districts in 1972 and 1977.
135
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AHIIKKTOS CONTROL COST AS A HJRCISNTAGB OF TOTAL RXPKNIUTORRS
Cluster
I)
2)
3)
4)
5)
fa)
7)
8)
'»)
H-*
CJ 10)
II)
12)
13)
14)
15)
10)
17)
18)
19)
20)
Tot .-I 1
AH|>I>HI ou
Cunl- rol
Costa
$ 267.113
1,492.208
515.252
26,212
86,192
38.524
7,632
120,212**
310,601
138,222
51.412
91.732
1,8)1,333
157,466
52,357
1,433,065
1.072*
177.204
97,501
34,840
Tot.il
Kx|)i>nil tturos
1978-79
$62,724,115
23. 602,188
4,586,990
21,203.972
18,057,074
7,526,216
22,190,530
97,252,693
14,401.800
3*173,078
.493,600
.721,875
22,901,480
7,385,952
4,231,720
31,750,779
15,485,312
2,877,645
4,687,161
8,372.653
Tol /i 1 AB|K;SI.OH
C.'oi ri»(jl. i vc C'ofil n
As .1 |V>t cciil.,->c]n of
Total Expend! Lures
.43%
6.32
1 1.23
.12
.48
.51
.03
.13
2.16
4.35
10.32
12.74
7.97
2.13
1 .23
4.52
.01
6.16
2.09
.42
ToU-i 1
Ope r ;il. iiiij
Kxpondi 1 ill eH
1978-79
$57,706,185
21,714,012
4.220,031
19.581,254
16,612,508
6,924, 119
20,415.287
89,472.477
13,249,656
2,919,232
454,106
664,125
21,142,961
6.795,076
3,893,182
29,210,716
14,246.487
2,647,433
4,312, 188
7,702,841
To l,il Ashostos
Corrective Costs
As a PPI c«nl-.• nl scliooln of I <.'<•! <* .id iona.
**Tliis >si>nl ly Ix-iiu) compl i>i oil in lliis Si'liool l)i sLr ii.-L.
W
-------
concern, given the response of the majority of school
administrators from this group who, when interviewed, stated that
their most likely source of funding for correcting asbestos
problems is the capital budget. It is also notable that, in terms
of flexibility, the capital budget is relatively inflexible,
especially for larger dollar amounts which may require as much
as a referendum.
(3) Positive Community Impacts
Positive community impacts include the number of students
and teachers removed from the risk of asbestos exposure, and the
number of jobs that may be created in the asbestos correction
industry if the voluntary control activities are undertaken. This
section estimates these impacts:
Students/Teachers Removed from Risk
The voluntary control activities, if undertaken, could result
in removing a number of students and teachers from the
potential risk of asbestos exposure. The earlier estimate
of the number of students affected by the proposed regulation
(see Exhibit 6), is the number of students removed from
potential risk. This estimate was 4,032,508 students
nationwide. The number of teachers removed from potential
risk of asbestos exposure is estimated to be 201,625.
The estimate of the number of teachers removed from risk is
based on the fall 1978 national student/teacher ratio for
primary and secondary public schools*—' A student/teacher
ratio of .05 was applied to the over 4 million students
potentially removed from risk.
—/Source: Digest of Education Statistics 1979, published by the
National Center for Education Statistics.
137
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Jobs Created
A second positive affect is the creation of jobs in the
asbestos control and testing industry. In Section 2(3)
above, it was estimated that it may cost $129.7 million to
voluntarily correct the nation's asbestos problems in public
primary and secondary schools. This amount does not truly
represent the actual number of man-hours created. To better
estimate jobs created, it is necessary to subtract non-labor
cost which may be included in the totals. The estimate for
encapsulation costs was reduced by twenty-five percent. The
percentage is based on New York City estimates of non-labor
costs associated with encapsulation. The coverage rate of
$30.00 per hour for bulk testing and all air quantification
testing and monitoring were reduced by 130 percent. This
percentage is an estimate by Tracor-Jitco, Inc. based on
their experience with testing. The national cost estimates
for inspection, removal, and disposal are unaffected because
they represent only labor costs.
By netting out these non-labor costs, the total national
labor cost estimates for all possible corrective actions is
$109.9 million. A straight labor rate of $9.79 per nour,
which is the national average for special trades
construction workers (BLS, Employment and Earnings; Sept.
1979), for encapsulation, removal, disposal, and inspection
activities; and a straight labor rate of $10.50 per hour
(Tracor-Jitco, Inc. estimates) for air quantification and
bulk testing by laboratory analyst was applied to the
estimated total national labor cost. The resulting man-
hours equivalent at this rate is 12,246,194 or 5888 man-years
(based on 2080 hours per year).
13G
-------
The man-years would not necessarily result in that number
of new jobs. This is because the industry as it now exists
would be able to absorb a portion of this new demand. A
more realistic number of new jobs should be somewhat lower.
4. FINANCIAL MECHANISMS AVAILABLE TO SCHOOL DISTRICTS
Local school districts are able to draw on three sources of
funding. These sources are: 1) local taxes and charges, 2)
indebtedness and debt transactions, 3) intergovernmental transfers or
revenues. All of these are possible sources that could be used by
school districts to perform various recommended asbestos corrective
actions.
Local Taxes and Charges
Local taxes and user charges are the largest source of school
district revenues. In 1972, taxes and charges accounted for
54.8 percent of school district's total revenues, nationally.
Making-up taxes and charges are property taxes and other
taxes (48.1%)r and current charges, sales, interest earned,
and miscellaneous revenues (6.7%) Jl/ Local taxes and charges
are used primarily in the school district's annual operating
budget.
Intergovernmental Revenues
Intergovernmental revenues from the Federal, state, and other
local governments account for 45.3 percent of local school
district's revenue sources. These revenues are usually
—/Sourcei 1972 Census of Governments: Finances of School Districts.
139
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distributed among the operating and capital budgets,
depending upon whether or not the intergovernmental revenues
are "earmarked" for a specific use. The largest percentage
of such transfers are from state governments (93.4%), with
the remainder coming from the Federal government and other
local governments.
Indebtedness and Debt Transactions
Long-term indebtedness, usually through the floating of bond
issues on the public market, is the third source of revenues
available to local school districts. This source is primarily
reserved for large scale capital improvement and building
projects. Very often a portion of the fund from a bond sale
will be set aside to finance equipment replacement and
physical plant improvements of minor nature.
Debt service on outstanding notes and issues are not usually
financed from existing bond issues, but from the general
operating budget. Funds from the sale of bonds or other
long-term indebtedness are apportioned yearly through a
capital improvements budget approved by the local school
board. A bo.nd issue most often requires a referendum vote
before a sale can be made.
The local capital improvement budget and operating budget are
the only direct means by which a local school district is able to
finance such special projects as asbestos control actions. Generally,
school districts would have to either expand one of these budgets or
redistribute funds within them. To expand these budgets, school
districts have increasingly been seeking greater intergovernmental
transfers. The following two sections review the availability of state
and Federal assistance for local asbestos corrective actions.
140
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State Assistance for Local School District's Asbestos Costs
Intergovernmental revenues from state governments provide
a substantial portion of the total amount of such transfers
to local school districts. Each state is in some way unique,
not only in terms of their approach to assisting local school
districts, but specifically on how they consider their funds'
availability for asbestos corrective costs. It is not
possible to provide a set of state funding sources which
are applicable to all states. For this reason each state
is addressed separately in this section.
The following list summarizes state financial aid available to
local school districts for asbestos corrective activities. These
summaries were obtained through telephone interviews with State
Departments of Education.
Alabama - No state program for asbestos control. There is a
minimum amount of state funding for capital outlays which amounts
to $64.87 per earned teacher unit. (The average school system
has 150-300 teachers); these funds could be appropriated for
asbestos corrective action.
Alaska - No state funds currently earmarked specifically for
asbestos corrective action. State does provide both capital and
operating funds for the local school district. It is possible
that asbestos corrective funds could come from this source,
depending on the outcome of State legislation.
California - No state funds are presently available for asbestos
corrective action. A bill will be introduced to the state
legislature which would provide matching funds to the school
districts for asbestos corrective action to be undertaken.
Funding would be retroactive to January 1, 1977. The bill will
141
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provide a 50/50 match between the state and local school
district(s). If the Federal government provides any funding, the
match will be adjusted to reflect a 50% Federal, 25% State, and
25% local distribution. Approximately $3-5 million is proposed
to be earmarked for asbestos corrective actions in the bill.
Connecticut - State bond funds are available to local school
districts for asbestos corrective action. Schools receive 30-
80% State aid under a reimbursement system.
Delaware - General Operating Fund: This fund is available to
local school districts for renovation of existing facilities as
well as construction of new facilities. Depending upon the amount
of outlay, asbestos removal could be funded through the operating
budget. Otherwise removal would be treated as a capital
improvement and funded through state bonds. The state would pay
up to sixty percent of the improvements. Bonds would normally
be retired at the end of 20 years. In the event of a sufficient
surplus in the general operating fund, no bonds would be required
and general funding would be used. If the general fund is used,
such a one-time removal would be treated separately from recurring
projects.
Hawaii - Hawaii schools are set up in one district. The state
legislature is considering $5.4 million in general obligation
bonds for asbestos corrective actions.
Illinois - There are no state funds for asbestos corrective
action. However, there is a Health and Life Safety Tax which the
local school districts can levy to raise funds to comply with
health and safety regulations.
Kentucky - There is no specific state funding program for asbestos
control in local school districts, however the state does
142
-------
distribute capital outlays to the local school districts for
maintenance and operations. Capital outlay funds could be used
for asbestos corrective action but many of the schools have
already depleted this source of funds.
Maine - There is no specific state funding program for asbestos
corrective actions, however the state subsidizes local school
districts' operating budgets which could fund asbestos control
to some extent. Asbestos corrective action would not be funded
through the capital improvements and construction funds which
are bonded at the local level and subsidized by the state.
Massachusetts - State legislature appropriated $2 million for
asbestos corrective action to be used for recommendations made
by the State Asbestos Commission. This is a reimbursement program
of which 25% of the cost of a bid is allocated and the rest is
determined by a sliding scale of 50-75% depending on the school
category (which varies from wealthy to poor districts).
Appropriation Requirements:
1. Work must be contracted (but not necessarily performed)
before July 1980.
2. All work must be certified by the Massachusetts Asbestos
Commission.
3. Maintain cost control over work and materials.
(The Massachusetts Asbestos Commission is appointed by the
legislature and is within the State Division of Occupational
Health)
Nebraska - No state funds are presently available for asbestos
143
-------
control. Some legislation is being introduced to fund laboratory
testing activities.
New Hampshire - Construction and Building Aid: This state fund
makes payments of from 30 percent to 55 percent of the principal
per year for capital expenditures which are used to change a
structure or capacity of a building. This fund was used in the
past by local school dist-ricts for structural changes to
accommodate increased student enrollments. Currently, this aid
package is also used for renovation and alteration but not
maintenance purposes. Renovation purposes could/ in certain
unspecified situations, possibly include asbestos corrective
actions and replacement activities.
New Jersey - General Fund: This fund is available to local school
districts to remodel old and build new facilities. Depending
upon the wealth of the county, the state may fund, through a bond
issue, a portion of between ten and fifty percent of such projects.
Funds designated for one remodeling program may be used for other
related programs, such as removal of friable containing materials.
Any substantial capital outlay is reimbursed by the state the
following year. Reimbursement is on the amount originally agreed
upon regardless of the use of funds.
New Mexico - There is no appropriation by the state legislature
for funding assistance for asbestos corrective actions. The
state's Department of Finance and Administration, though, has
transferred funds from other sources to help fund individual
school districts with their removal problems. This is a one-time
arrangement which will finance asbestos removal at $2.17 per
square foot (of asbestos) in Dora, Reserve, Quemado, and Ariams
school districts. These are the only districts receiving such
funds due to the immediacy of their asbestos problems and their
low tax-base capacity. The funds are to be used only for removal
144
-------
of asbestos. Replacement of ceilings, insulation, etc.. will be
paid for out of local school district budgets.
New York - No specific state funds are set aside for asbestos
control, but local school districts could draw from the "typical
building construction aid" fund provided by the state. This aid
varies from 0% (wealthy districts) to 95% (poor districts)
depending on need (average 49%). Legislature is currently
investigating the impact of asbestos containment and the
possibility of state aid.
Rhode Island - Reimbursement of Renovations: The state reimburses
local school districts after a renovation problem has been
corrected. The state health code identifies asbestos as a
potential health problem and thereby could be interpreted as
requiring schools with asbestos to be renovated. Renovations are
guaranteed by the state up to a minimum of thirty percent
reimbursement.
South Carolina - No state funds specifically for asbestos
corrective actions. The state does provide funds to local
district on a per person basis. For the last 3-4 years $30/per
pupil has been appropriated. Of this amount, only 15-20% is used
for capital improvements and construction as a supplemental
funding source. This money could be used for asbestos corrective
action.
Tennessee - General Fund: Available to local school districts
to rebuild old and construct new facilities. The source of funding
is dependent upon the amount of outlay. A major outlay for
asbestos corrective actions would require a bond issue.
Generally, for building and renovation, the state will match funds
on an issue to retire at the end of thirty years. Removal of
friable materials would be considered a renovation in that
construction would replace structures containing asbestos.
145
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Texas - No state funds available for asbestos corrective actions.
However, the states provide $7-8 million yearly in entitlement
funds to the school districts. This could be a source of funding
for asbestos reconstruction.
Utah - No specific state funding for asbestos corrective action.
The state does provide a general building fund of $13 million
for this school year ($17.5 million proposed for next year). Some
of this money is earmarked for critical needs - otherwise monies
could be used for asbestos control.
Vermont - The state provides construction aid to the local school
districts for meeting standards and regulations of any state
agency (i.e., asbestos corrective action). The school districts
are reimbursed 30%.
Washington - Capital Construction Fund: This fund is available
to local school districts to remodel old and build new facilities.
This is a matching grant which at present provides for a fifty
percent state and fifty percent local school district formula.
These monies can be applied to asbestos corrective actions in
very limited instances where water damage or other "Acts of God"
result in the need for remodeling a portion of a building which
contains friable asbestos.
Wyoming - No specific state funds for asbestos correction,
however, there is a State Capital Construction Entitlement Fund
which goes only to "foundation programs" (the poor half of the
local school districts). This fund provides from a few thousand
to $1 million annually per school district. Conceivably only a
small amount would be available for asbestos correction.
States which provide no funds which could be used for
asbestos control actions in school districts are the following:
146
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Arkansas Missouri
Colorado Montana
District of Columbia Nevada
Florida North Carolina
Georgia North Dakota
Idaho Ohio
Indiana Oklahoma
Iowa Oregon
Kansas Pennsylvania
Louisiana South Dakota
Maryland Virginia
Michigan West Virginia
Minnesota
Mississippi
Federal Assistance for Local School Districts' Asbestos
Costs
On May 16, 1980, the U.S. Congress passed the Asbestos School
Hazard Detection and Control Act of 1980 (PL 96-270). The
Act establishes as its primary purpose a Federal grant and
loan program to assist local educational agencies in
detecting and controlling asbestos hazards. It establishes
a direct grant program (effective for two years after the
effective date of this Act) to local educational agencies
for 50% of the cost of detecting the presence of asbestos
in schools. The Act also directs the Secretary of Education
to administer a long term loan program for 50% of the costs
of containing or removing asbestos materials in schools
which pose imminent hazards to school children and
employees. The corrective action loan program may be
utilized for qualifying projects that were on-going as of
January 1, 1976.
147
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The Act authorizes the Secretary to establish an Asbestos
Hazards School Safety Task Force to compile medical/
scientific, and technical information on the health hazards
of asbestos and the means to identify sample, and test
materials suspected of emitting asbestos fibers. The Task
Force will distribute this information to State educational
agencies, review grant and loan applications submitted to
the Secretary for asbestos detection and control programs,
review EPA guidelines, and assist the Secretary in
promulgating standards and safety procedures.
5. CONCLUSION
The total cost for the voluntary control of asbestos in primary
and secondary public schools in the nation is estimated at
approximately $129.7 million. This cost is not anticipated to cause
extensive negative community impacts. It will, however, provide the
equivalent of 5888 additional man-years of work for the asbestos
control and testing industry.
The reliability of these estimates are dependent upon the validity
of the unit cost estimates and the sample. The statistical validity
of the school district sample, as discussed in previous chapters is
questionable. Therefore, the inferences and estimates of this chapter
may be subject to variation.
148
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V. COST OF PROPOSED IDENTIFICATION AND NOTIFICATION RULE
The costs of EPA's proposed rule requiring school districts to
identify and file notification of asbestos containing materials in
their building are examined in this chapter. As noted previously in
this report, the proposed Identification and Notification Rule
mandates, among other requirements, the inspection and bulk testing of
materials which are friable and could contain asbestos. The inspection
and bulk testing process would be the responsibility of individual
school districts.
Earlier chapters of this report have presented cost estimates
for school district to conduct inspections and bulk tests. These
estimates could be improved for three reasons; one, the unit cost
averages used to calculate total costs may have been biased by the
presence of extreme sample points or outliers; two, the number of
affected schools is based on a sample of school districts which may
be unrepresentative in their knowledge of the asbestos "problem", they
can be redefined to include only those requirements of the proposed
rule. In the remainder of this chapter, these concerns are examined
and reestimated cost impacts developed.
1. ADJUSTMENTS TO UNIT COST DATA
The unit cost data estimates for the proposed inspection and bulk
testing requirements were initially presented in Tables 1 through 4
in Chapter II of this report. Through subsequent analysis and review
it was determined that these unit cost estimates could be improved by
eliminating extreme sample points or outliers from the samples. The
149
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inclusion of these outliers resulted in high unit cost variances and
average unit costs which may not be accurate for estimation purposes.
To reduce the variances and estimate more meaningful unit cost
averages, Category Two' responents (see Chapter II for definition) were
telephoned a second time.
The second series of telephone calls concentrated on laboratories
which perform bulk sample analysis and air sampling. Although air
sampling is not required under the proposed rule, many laboratories
perform both activities. To minimize the possibility of having to
contact the same persons multiple times in the future, data on both
activities were requested at this time. In this section, reestimated
unit costs were developed for all three methods of bulk testing and
for air sampling activities. However, only total costs for the
polarized light microscopy and X-ray diffraction methods of bulk
testing have been attributed to the cost of the proposed rule (see
Chapter VI). Adjustments to the inspection unit cost were not
necessary.
The second telephone contact with laboratory facilities focused
on verifying unit cost data previously compiled. Verification was
conducted for those laboratories which initially provided extremely
high or low unit cost estimates. Also, unit costs, obtained from
contractors who used secondary sources and price quotes from other
firms, were eliminated from the sample. Category Three respondents
(see Chapter II) were not recontacted because of their inability to
provide data during the first series of telephone calls.
As a result of the second series of telephone calls, average unit
cost estimate changes were made in the following five laboratory
analysis areas:
Polarized Light Microscopy Analysis Costs
150
-------
X-Ray Diffraction Analysis Costs
Electron Miscroscopy Analysis Costs
Costs of Air Filter Sample Analysis by Optical Microscopy
Costs of Air Filter sample Analysis by Electron Microscopy
Each of the above five average unit costs are discussed below. Tables
showing the final data at the state and EPA region levels of detail
are also presented.
(1) Polarized Light Microscopy (PLM) Analysis Costs
In total, seventy-six laboratories provided usable
information in this cost category. A national average of $42.59
per sample was calculated with a range of $10.00 to $150.00 per
sample (see Table 23).
Unit costs for PLM analyses are often related to the number
of samples submitted. Discounts are allowed for larger numbers.
For example if more than one sample is submitted/ a 10% discount
is usually offered by most laboratories. Some laboratories offer
as high as 50 percent discounts if more than 100 samples are
submitted. Other laboratories set their unit price per sample
on a minimum number of samples submitted, for example, four. In
all cases, the unit costs provided include labor as well as
material costs.
The coefficient of variation (CV) for the nation is 58.79%
while that for the regions is 18.58%. The high variation from
state-to-state is mainly due to a wide range of values, e.g.,
$10.00 (North Carolina), $10.00 (Hawaii), $145.00 (Ohio), and
$150.00 (Connecticut).
151
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TABLE 23
COSTS PER SAMPLE OF TESTING FRIABLE MATERIALS
FOR ASBESTOS BY POLARIZED LIGHT MICROSCOPY
Mean (Sample Size)
- 1 Standard Deviation Range
Region I:
Connecticut
Maine
Massachusetts
New Hampshire
Rhode Island
Vermont
All Region I
Region II:
New Jersey
New York
All Region II
Region III;
Delaware
Dist. of Columbia
Maryland
Pennsylvania
Virginia
West Virginia
All Region III
Region IV:
Alabama
Florida
Georgia
Kentucky
Mississippi
North Carolina
South Carolina
Tennesse
All Region IV
Region V;
Illinois
Indiana
Michigan
Minnesota
Ohio
Wisconsin
All Region V
Region VI;
Arkansas
Louisiana
New Mexico
Oklahoma
Texas
All Region VI
Region VII:
Iowa
Kansas
Missouri
Nebraska
All Region VII
$ 95.00 ( 2)
a
47.60 ( 5)
a
a
a
61.14 ( 7)
41.00 ( 8)
38.75 ( 4)
40.25 (12)
50.00 ( 1)
a
40.00 ( 2)
36.00 ( 3)
37.50 ( 2)
a
39.12 ( 8)
a
43.00 ( 5)
40.00 ( 1)
a
23.33b(3)
c
40.00 ( 1)
36.50 (10)
57.50 ( 4)
50.00 ( 1)
33.33 ( 3)
25.00 ( 2)
57.14 ( 7)
27.50 ( 2)
46.58 (19)
a
25.00 C 1)
a
a
50.00 < 4)
45*00 ( 5)
a
a
50.00 ( 1)
a
50.00 ( 1)
+77.78
+29.60
+46.12
+16.37
+ 14.93
+ 15.25
+14.14
+ 5.29
+17.68
+10.16
+32.52
+12.58
+24.27
+25.33
+15.27
0
+ 42.41
•± 3.53
+30.42
+23.80
+23,45
(40.00-150.00)
(28.00-100.00)
(28.00-150.00)
(18.00- 75.00)
(25.00- 60 .00)
(18.00- 75 .00)
(30.00-50.00 )
(30.00-40.00 )
(25.00-50.00 )
(25.00-50.00 )
(20.00-100.00)
(10.00- 35.00)
(10.00-100.00)
(25.00-80.00 )
(20.00-50.00 )
(25.00-25.00 )
(20.00-145.00)
(25.00-30.00 )
(20.00-145.00)
(25.00- 75.00)
(25.00- 75.00)
152
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TABLE 23
Page 2
Mean (Sample Size)
— 1 Standard Deviation Range
Region VIII:
Colorado
Montana
North Dakota
South Dakota
Utah
Wyoming
All Region VIII
Region IX:
Arizona
California
Hawaii
Nevada
All Region IX
Region X:
Alaska
Idaho
Oregon
Washington
All Region X
All Nation
$ 46.25 (4)
a
a.
a
37.50 (2)
a
43.33 (6)
a
32.00 (5)
17.50 (2)
a
32.00 (7)
a
a
a
43.00 (1)
43.00 (1)
42.59 (76)
+14.93 (25.00-60.00 )
+17.68 (25.00-50.00 )
+14.72 (25.00-60.00 )
+ 4.47 (25.00-35.00 )
+10.61 (10.00-25.00 )
+ 4.47 (10.00-35 .00)
+25.04 (10.00-150.00)
a. No information was obtained from this state.
b. Services provided upon request and without charge to employers within the State
by the Consultative Services Section of the State Department of Labor.
c. Department of Health and Environmental Control have agreed to perform <* minimum
of bulk sample analysis for public schools.
153
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(2) X-Ray Diffraction (XRD) Analysis Costs
Table 24 summarizes the unit costs of testing friable
materials for asbestos by X-ray diffraction. A national average
of $70.00 per sample was estimated from 52 laboratories. The
comparison of the regional average costs per sample indicated
that Region VII has the highest cost, $200 (one laboratory) while
Region V shows the lowest cost, $54.64 (14 laboratories).
As in PLM analyses, unit costs for XRD are dependent on the
number of samples submitted. Discount ranges from 10% to 30% on
increasing number of samples. Costs include the cost for labor
as well as materials used in the laboratory.
There are significant national (CV = 49.74%) as well as
regional variations (CV = 52.87%). These are due to a combination
of insufficient sample size and a few extremely high costs. For
example, the States of Colorado, Massachusetts, Missouri and New
Jersey reported costs per sample greater than $145.00. For Region
VII, only one cost estimate was received, i.e., $200.00 per sample.
(3) Electron Microscopy (EM) Analysis Costs
The per sample costs of testing friable materials for
asbestos by electron microscopy is presented in Table 25. A total
of 20 laboratories provided cost information from which a national
average of $188.00 per sample was estimated. The per sample cost
ranges from $75 in Colorado to $350 in Illinois.
Unlike PLM and XRD analyses, the number of samples submitted
for EM analysis does not necessarily alter the unit costs. Only
a few laboratories indicated that discounts would be offered if
more than three to five samples were submitted. The reason for
a fixed unit cost for EM analyses is that EM is costly, time
154
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TABLE 24
COSTS PER SAMPLE OF TESTING FRIABLE
MATERIALS FOR ASBESTOS BY X-RAY DIFFRACTION
Mean (Sample Size)
— 1 Standard Deviation
Region I:
Connecticut
Maine
Massachusetts
Mew Hampshire
Rhode Island
Vermont
All Region I
Region II:
New Jersey
New York
All Region II
Region III:
Delaware
Dist. of Columbia
Maryland
Pennsylvania
Virginia
West Virginia
All Region III
Region IV:
Alabama
Florida
Georgia
Kentucky
Mississippi
North Carolina
South Carolina
Tennesse
All Region IV
Region V:
Illinois
Indiana
Michigan
Minnesota
Ohio
Wisconsin
All Region V
Region VI:
Arkansas
Louisiana
New Mexico
Oklahoma
Texas
All Region VI
Region VII;
Iowa
Kansas
Missouri
Nebraska
All Region VII
$ 100.00 ( B
a
96.67 ( 3)
100.00 ( 1)
a
a
98 . 00 ( 5)
85-00 ( 6)
47.50 ( 2)
75.62 < 8>
a
a
52.50 ( 2)
80.00 ( 2)
75.00 ( 1)
a
68.00 ( 5)
a
60.00 ( 1)
a
30.00 ( 1)
a
90.00 ( 1)
a
a
60.00 ( 3)
63.33 ( 3)
100.00 ( 1)
45.00 ( 5)
35.00 ( 2)
60.00 ( 3)
b
54.64 (14)
a
35.00 ( 1)
a
a
75.00 ( 5)
68.33 ( 6)
a
a'
200.00 ( 1)
a
200.00 ( 1)
+50.33 ( 50.00-150.00)
+ 35.64 ( 50.00-100.00)
+35.21 ( 60.00-150.00)
+ 17.68 ( 35.00- 60.00)
+35.09 ( 35.00-150.00)
+ 3.53 ( 50.00- 55.00)
+ 28.28 ( 60.00-100.00)
+ 20.19 ( 50.00-100.00)
+ 30.00 (30 .00- 90.00)
+ 20.21 ( 40.00- 75.00)
+ 7.07 ( 35.00- 50.00)
0 ( 35.00- 35.00)
+ 36.05 ( 30.00-100.00)
+ 23.57 ( 30.00-100.00)
+ 25.00 ( 50.00-100.00)
+ 27.69 ( 35.00-300.00)
155
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TABLE 24
Page 2
Mean (Sample Size) - 1 Standard Deviation Range
Region VIII:
Colorado
Montana
North Dakota
South Dakota
Utah
Wyoming
All Region VIII
Region IX:
Arizona
California
Hawaii
Nevada
All Region IX
Region X:
Alaska
Idaho
Oregon
Washington
All Region X
All Nation
$ 83.33 ( 3)
a
a
a
57.50 ( 2)
a
73.00 ( 5)
a
55.00 ( 3)
60.00 ( 1)
a
56.25 ( 4)
a
a
a
65.00 ( 1)
65.00 ( 1)
70.09 (52)
n
+ 57.73 ( 50.00-150.00)
+ 24.75 ( 40.00- 75.00)
+ 44.94 ( 40.00-150.00)
+ 8.65 ( 50.00- 65.00)
+ 7.50 ( 50.00- 65.00)
+ 34.86 (30 .00-200.00)
No information was obtained from this state.
156
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TABLE 25
COSTS PER SAMPLE OF TESTING FRIABLE
MATERIALS FOR ASBESTOS BY ELECTRON MICROSCOPY
Mean (Sample Size)
— 1 Standard Deviation
Region I;
Connecticut
Maine
Massachusetts
New Hampshire
Rhode Island
Vermont
All Region I
Region II:
Mew Jersev
New York '
All Region II
Region III:
Delaware
Dist. of Columbia
Maryland
Pennsylvania
Virginia
West Virginia
All Region III
Region IV:
Alabama
Florida
Georgia
Kentucky
Mississippi
North Carolina
South Carolina
Tennesse
All Region IV
Region V:
Illinois
Indiana
Michigan
Minnesota
Ohio
Wisconsin
All Region V
Region VI:
Arkansas
Louisiana
New Mexico
Oklahoma
Texas
All Region VI
Region VII:
Iowa
Kansas
Missouri
Nebraska
a
a
190.00 (2)
100.00 (1)
a
a
160.00 (3)
300.00 (1)
b
300.00 (1)
a
a
200.00 (2)
a
162.50 (2)
ci
181.25 (4)
a
a
a
a
d
180.00 ( 0
a
a
130.00 (1)
325.00 (2)
150.00 (1)
150.00 (1)
c
a
a
237.50 (4)
a
a
a
a
125.00 (2)
125.00 (2)
a
a
200.00 (1)
a
+155.56 ( 80.00-300.00)
+121.65 ( 80.00-300.00)
+ 70.71 (150.00-250.00)
+ 53.03 (125.00-200.00)
+ 55.43 (125.00-250.00)
+ 35.35 (300.00-350.00)
+103.08 (150.00-350.00)
+ 35.35 (100.00-150.00)
+ 35.35 (100.00-150.00)
All Region VII
200.00 ( U
157
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TABLE 25
Page 2
Mean (Sample Size) — 1 Standard Deviation Range
Region VIII:
Colorado
Montana
North Dakota
South Dakota
Utah
Wyoming
All Region VIII
Region IX:
Arizona
California
Hawaii
Nevada
All Region IX
Region X:
Alaska
Idaho
Oregon
Washington
All Region X
All Nation
$ 75.00
a
a
a
100.00
a
87.50
a
300.00
200.00
a
250.00
a
a
a
a
a
188. on
(1)
(1)
(2)
(1)
(1)
(2)
(2Q)
+17.68 ( 75.00-100.00)
+ 70.71 (200.00-300.00)
+ 85.28 ( 75.00-350.00)
a. No information was obtained from this state.
b. $60.00 per hour is charged by one contractor.
c. Analysis is available, but no cost was provided by contractors.
158
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consuming, and limited in availability. As with the other
analyses, each unit cost includes the cost for labor, material,
and other expenses which are required to perform the test.
A coefficient of variation of 45.36% represents the variation
from state-to-state across the nation, while a cofficient of
variation of 34.01% indicates the variation from region to region.
These variations are again probably due to insufficient sample
size. An important note regarding sample size here is that, since
availability of EM analysis is rather limited, the sample size
is unavoidably small.
(4) Costs of Air Filter Sample Analysis by Optical Microscopy
The costs of analyses of asbestos air samples by optical
microscopy (NIOSH Method) are summarized in Table 26. A national
average of $36.80 per sample with a standard deviation of $17.46
was estimated from 89 laboratories.
The unit cost includes the cost of labor and materials. As
in other analytical costs, discounts may be allowed depending on
the number of samples delivered for analysis.
State-to-state variation was found to be represented by a
coefficient of variation of 47.44%. The coefficient of variation
among regions is 23.43%. It is difficult to explain the large
f
variations in this case since optical microscopy has become such
a standardized test for asbestos air sample analysis.
(5) Cost Of Air Filter Sample Analysis By Electron Microscopy
Table 27 summarizes the costs of analyses of asbestos air
samples by electron microscopy. The cost per sample ranges from
$80.00 in Massachusetts to $350.00 in Pennsylvania. These costs
159
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TABLE 26
COST PER SAMPLE OF ANALYSES OF ASBESTOS AIR SAMPLE
BY OPTICAL MICROSCOPY (NIOSH METHOD)
Mean (Sample Size)
— 1 Standard Deviation
Region I;
Connecticut
Maine
Massachusetts
Mew Hampshire
Rhode Island
Vermont
All Region I
Region II;
Mew Jersey
Mew York
All Region II
Region III;
Delaware
Dist. of Columbia
Maryland
Pennsylvania
Virginia
West Virginia
All Region III
Region IV:
Slab ana
Florida
Georgia
Kentucky
Mississippi
North Carolina
South Carolina
Tennesse
All Region IV
Region V:
Illinois
Indiana
Michigan
Minnesota
Ohio
Wisconsin
All Region V
Region VI:
Arkansas
Louisiana
Mew Mexico
Oklahoma
Texas
All Region VI
Region VII;
Iowa
Kansas
Missouri
Nebraska
All Region VII
$ 47.50 (4)
a
48.40 (5)
a
a
a
48.00 (9)
36.43 (7)
48.33 ( 3)
4o.oo do)
50.00(1)
a
42.50 (2)
31.43 (7)
37.50 (2)
a
35.83 (12)
a
31.75 (4)
40.00 (1)
25.00 (1)
a
35.od>(2)
a
40.00 (1)
33.5* (9)
32.00 (5)
50.00 (1)
17.90 (5)
35.00 (2.)
40.17 (6)
26.25 (4)
31. U (23)
a
42.0o (])
a
a
47.50 (4)
46,40 ( 5)
25.00 (1)
a
50.00 (1)
70.00 (1)
43.33 (3)
+ 35.94
+ 31.31
+ 31.22
+ 12.15
± 25.17
± 16.50
+ 10.61
+ 11.80
± 17.68
+ 12.40
±14.22
± 14.14
± 11.07
+ 16.81
+ 3.47
+ 14.14
+ 9.39
± 6.29
+ 13.12
± 22.17
± 19.36
± 22.55
(20.00-100.00)
(22.00-100.00)
(20.00-100.00)
(15.00- 50.00)
(25.00- 75.00)
(25.00- 75.00)
(35.00- 50.00)
(15.00- 50.00)
(25.00- 50.00)
(15.00- 50.00)
(17.00- 50.00)
(25.00- 45.00)
(17.00- 50.00)
(20.00- 60.00)
(12.00- 20.00)
(25.00- 45.00)
(25.00- 50.00)
(20.00- 35.00)
(12.00- 60.00)
(25.00- 75.00)
(25. 00-. 75. 00)
(25.00- 70.00)
160
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TABLE 26
Page 2
Mean (Sample Size) — 1 Standard Deviation Range
Region VIII:
Colorado
Montana
North Dakota
South Dakota
Utah
Wyoming
All Region VIII
Region IX:
Arizona
California
Hawaii
Nevada
All Region IX
Region X;
Alaska
Idaho
Oregon
Washington
All Region X
All Nation
$ 45.83 (6)
a
a
a
37.50 (2)
15.00 (1)
40.55 (9)
a
30.33 (6)
25.00 (2)
a
29.00 (8)
a
a
a
22.00 (1)
22.00 (1)
36.80 (89)
+ 20.59 (20.00- 80.00)
+ 17.68 (25.00- 50.00)
+20.22 (20.00- 80.00)
+ 10.13 (22.00- 50.00)
+ 0 (25.00- 25.00)
+ 8.91 (22.00- 50.00)
+17.46 (12.00-100.00)
a. No information was obtained from this state.
b. "Services provided upon request and without charge to employers within the State
by the Consultative Services Section of the State Department of Labor."
161
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TABLE 27
COSTS PER SAMPLE OF ANALYSES OF ASBESTOS AIR SAMPLES
BY ELECTRON MICROSCOPY
Mean (Sample Size) — 1 Standard Deviation ' Range
Region I:
Connecticut
Maine
Massachusetts
New Hampshire
Rhode Island
Vermont
All Region I
Region II:
Sew Jersey
New York
All Region II
Region III:
Delaware
Dist. of Columbia
Maryland
Pennsylvania
Virginia
West Virginia
All Region Il-i-
Region IV:
Alabama
Florida
Georgia
Kentucky
Mississippi
North Carolina
South Carolina
Tennesse
All Region IV
Region V:
Illinois
Indiana
Michigan
Minnesota
Ohio
Wisconsin
All Region V
Region VI;
Arkansas
Louisiana
New Mexico
Oklahoma
Texas
All Region VI
Region VII;
Iowa
Kansas
Missouri
Nebraska
$ 266.67C(1)
a
190.00 (2)
100.00 (1)
a
a
186.67 (4)
283.33 (2)
a
283.33 (2)
a
a d
2 72. Sir (1)
308.33 (2)
200.00 (1)
a
272.29 (4)
a
a
a
a
a
a
a
a
a
325.00 (2)
100.00 (1)
150.00 (1)
a
a
100.00 (1)
200.00 (5)
a
a
a
a
125.00 (2)
125.00 (2>
a
a
200.00 (1)
a
+155.56 ( 80.00-300.00)
+112.74 ( 80.00-300.00)
+23.57 (266.67-300.00)
+23.57 (266. 67^300. 00)
+ 58.92 (266.67-350.00)
+61.36 (200.00-350.00)
+35.35 (300.00-350.00)
+117.26 (100.00-350.00)
+ 35.35 (100.00-150.00)
± 35.35 (100.00-150.00)
All Region VII
200.00 (1)
162
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TABLE 27
Page 2
Region VIII;
Colorado
Montana
North Dakota
South Dakota
Utah
Wyoming
All Region VIII
Mean (Sample Size) — 1 Standard Deviation Range
$ 75.00 (1)
a
a
a
100.00 (1)
a
87.50 (2)
+ 17.68
( 75.00-100.00)
Region IX;
Arizona
California
Hawaii
Nevada
All Region IX
270.00 (1)
a
a
270.00 (T)
Region X:
Alaska
Idaho
Oregon
Washington
All Region X
a
a
a
a
All Nation
204.64 (21)
+ 95.67
( 80.00-350.00)
a. No information was obtained from this state.
b. $60.00 per hour.
c. $100.00/sample for scanning EM; $300.00/sample for SEM + EDS; $400.00/sample for
transmission EM; (100.00 + 300.00 + 400.00) - 266.67/sample.
d. $320.00/sample Eor Transmission EM; $225.00/sample for Scanning EM; ($320.00 +
225.00) = $272.50/sample.
163
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give a national average of $204.64 with a standard deviation of
$95.67. Each unit cost includes labor as well as material costs.
j
The variation in state means is indicated by a coefficient
of variation of 46.75% while the variation among the regions is
shown by a coefficient of variation of 35.04%. The large
variations are likely due to insufficient sample size.
2. ADJUSTMENT TO THE ESTIMATES OF AFFECTED POPULATION
As noted earlier in this report (see Chapter III)/ estimates of
the number of school districts and public schools which would be
affected by the proposed rule were subject to data limitations.
The original sample of school districts was chosen from those
districts that had responded to EPA's voluntary survey. Because the
original sample was chosen from this base, sample bias may have been
introduced in the form of having districts which are knowledgeable of
and active in voluntary asbestos control programs. This may or may
not be characteristic of the average school district in the universe.
The following sections discuss the methodological steps used to
investigate this potential bias. The steps include developing a set
of questions and questioning procedures, choosing a non-respondent
sample, collecting responses and analyzing the variances between the
original survey data and the results of this non-respondent survey.
The results of the variance analysis are presented along with a
reevaluation of the original estimates of inspection and bulk testing
costs for the affected school districts and students. In the following
sections these procedural steps are discussed.
t
(1) Data Collection Instrument
A list of follow-up questions asked of the non-respondent
164
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sample is presented in Exhibit 11. This data collection effort
as well as that of the first study survey described in Chapter
III were considered follow-ups to the original EPA survey (OMB
No. 158-R0165).
The list of questions in Exhibit 11 was designed to provide
information which could be used to test for bias in the original
survey responses. Data on intended corrective actions were also
sought to help resolve the bias issue. However, a reestimation
of the corrective action results was not performed because the
data from the non-respondent survey was not directly compatable
to the original survey data. .Also, the revised population
estimates of asbestos removal and other corrective activities
are not included in the purview of the proposed rule.
(2) Sample of Non-Respondents
The sample of non-respondents was limited to approximately
120 school districts. For consistency, the sample of non-
respondent school districts were grouped into the same twenty-
four clusters utilized in the original survey. Each cluster in
the non-respondent survey had the same number of school districts.
By having the same number of non-respondent school districts in
each cluster, it was possible to obtain at least, a minimum
response from each, regardless of how small. This procedure
resulted in approximately five sample school districts in each
cluster for the non-respondent survey.
Prior to sample selection we examined the implications of
sampling five school districts in each cluster of the non-
respondent survey. With this allocation, we anticipated that a
difference of 30-35% in the percentage of affected districts
between the original and the non-respondent sample in each cluster
would be statistically significant at the 90% level of confidence.
165
-------
EXHIBIT 11
Non-Respondent School Districts Data Collection Instrument
1. Do you remember receiving an EPA Voluntary Asbestos Survey Report
last summer?
If no — skip to question #3
2. Do you remember what happened to it?
3. How many schools in your district were built or remodeled between
1945 - 1978?
4. How many of these schools have been inspected for friable
materials?
A. If none - ask: Have any plans been made to inspect the schools
for friable materials?
(1) Yes - ask: When? Based on your general knowledge of
the schools in your district, how many contain friable
materials?
(a) If plans for corrective actions have been made,
what are they?
(b) If no plans have been made, STOP.
(2) No - ask: based on construction records or your
knowledge of the* general condition of the Buildings,
how many have friable materials?
ft,
(a) If based on their knowledge of the schools, none
have friable materials, STOP.
166
-------
Exhibit 11(continued
(b) If some have friable materials, have any plans
been made to correct the situation?
If plans have been made, what are they?
If no plans have been made, STOP.
B. If any - go to Question 5.
5. How many of the inspected schools have any friable material?
6. Who conducted the inspection?
If the answer to Question 5 is none, STOP.
7. Were any bulk samples of this friable material taken?
If no — ask: Have any plans been made to bulk sample areas with
friable materials to check for asbestos content? If yes - ask
when.
8. In how many schools were samples taken?
9. What were the results of the analysis of the bulk samples?
If negative - STOP.
If results are not back - What does he suspect the results will
be based on construction plans or his knowledge of the schools?
10. Are you aware of EPA's suggested way of handling friable asbestos
materials?
If no - STOP.
11. What corrective method have you planned on using?
167
-------
Smaller differences might be due to sampling error, rather than
a real difference between the two percentages.
A simple rand'om sample of five or six school districts was
then selected from districts which had not responded to the
original survey. Certain states were excluded from the selection
process because a summary of the Voluntary EPA Survey data
indicated that no school districts in these states had responded.
It is believed by EPA that this was due to the Boards of Education
in these states having made other arrangements with the school
districts, and that to attempt to sample them again would be
futile. Therefore, the States of Alabama, Arkansas, Georgia,
Hawaii, Indiana, Rhode Island, Vermont, Florida and Maryland were
not included in the non-respondent sample.
(3) Data Collection
All data were collected by telephone. Names and telephone
numbers of the sample school district superintendents were
obtained from the State Boards of Education. A pretest of the
data collection instrument consisting of approximatley ten
percent of the school districts in the sample was made to evaluate
its effectiveness. As a result of the pretest, a minor change
was made, resulting in the addition of a question asking who had
inspected the public schools for friable materials. This would
provide a better basis for comparison with inspection data from
the original survey.
(4) Analysis
The data, once compiled, was analyzed to identify differences
between survey results. As a measure of such differences, the
proportion of affected school districts in each cluster of non-
respondent survey was computed and compared to the corresponding
168
-------
estimate of the original survey. The particular difference
measure used for each cluster was:
P
nr
where:
Di = the measure of difference between the original sample
and the non-respondent survey for cluster i
Poi = proportion of districts affected in the original
sample for cluster i
^nri = proportion of districts affected in the non-
respondent sample for cluster i
Nri = number of non-respondent districts sampled for cluster
i.
When the number of sample cases of non-respondents is over twenty,
the quantity Di wm be approximately normally distributed with
a mean of zero and standard deviation of one/ if po^ is treated
as a constant and thus not subject to sampling error. This is
equivalent to treating the original responding school districts
in each cluster as representing only themselves rather than as
representing all districts in that cluster. Comparing the values
of Dj to standard factors based on the normal distribution, gives
a rough indication of which differences may be important.
Comparison with the normal distribution is an approximation
because the sample sizes in each cluster are small, but the values
of D^ serve as a reasonable guide in examining the differences.
169
-------
Based on the values of D, eight (8) of the twenty-four (24)
clusters have differences that may be important (see Table 28).
This result is based on identifying the clusters with values of
D greater than 1.65, the factor from the standard normal
distribution appropriate for performing a significance test at
the 10% level. The particular clusters identified in this way
are the following: 2, 6, 10 (b) , 10 (d) , 10 (e) , 11, 12, and 13.
These eight clusters were further examined to see if the
difference was mainly due to one of the three factors mentioned
earlier. Values of Dj were calculated in the eight clusters
separately for the proportions of districts with schools needing
bulk testing, with schools needing inspection, and with schools
with exposure problems. In cluster 2, the difference appears to
be in the bulk sampling estimates. In clusters 6 and 10(b) the
apparent difference is in inspection estimates. In clusters 10(d)
and 10(e) the difference is apparently in the exposure estimates.
In the other clusters, the additional breakdown was not helpful
in explaining the overall difference.
From these results it appears advisable to revise the cost
estimates for the eight clusters. Three approaches to revision
are conceivable: (1) averaging of the percentages of affected
schools from the original and non-respondent samples, (2) pooling
data from the two samples, or (3) a weighting scheme for the two
samples other than pooling or simple averaging. The first
alternative seems to us to be preferable because it gives an
implicit weight to the non-respondent sample which is larger than
would be implied by the relative sizes of the non-respondent
sample and the original sample. Averaging gives each sample equal
weight. For instance, in cluster 2, 23 districts responded
originally and 5 non-respondents were contacted subsequently. In
this cluster the average of the proportions of districts affected
would be .41 (the average of .22 and .60). Weighting in proportion
170
-------
l-KOPORTIONS Of AWKCTKU SCHOOL 01STKICTS AND SCHOOLS IN OIUGIUAL AND NONKIiSI'ONUIiMT SAMI'IJJ
TOTAL AFFECTED SCHOOL UlSTIUCI'S
TOTAL AFFliCTKD SCHOOLS
STUATA
1
2
3
4
5
6
7
0
9
10(a)
10 (M
10(c)
10(d)
10(e)
11
12
13
14
15
16
17
18
20
ORIGINAL -
UAMl'LE
.13
.22
.11
.25
.45
0
.50
.18
.14
.66
0
.20
1.1)0
1.00
.20
.75
.50
.25
0
0
.35
.29
.33
.25
NOM-KESl-ONDUIT
SAMPI.B
.33
.60
.20
.40
.20
.40
.40
.20
.33
.40
.40
.40
.40
.20
.60
.33
.20
.25
.17
.20
.60
.25
0
.20
VALUE OF
d
1.04
1.73
.09
.68
1.40
1.B3
.46
.11
.99
1.30
1.83
.91
2.74
4.47
1.83
2.19
1.68
0
1.11
1.12
1.14
.21
0
.28
OKIGINAI. -/
SAMPLE
.11
.77
.17
.07
.09
0
.17
.31
.05
.10
0
.04
.24
.07
.15
.21
.17
.03
0
0
.15
.13
.07
.37
NOH-RESPOHIJIiNT
SAMPU:
.36
.23
.30
.02
.28
.61
.16
.08
i/,
of Affected School Districts in Original Sample = (Affected School Ijiatricta)
Total School Districta " ('o
of Affuclad Scliool Diatriuta in Noii-Kespondciit Sample « (Affected School Oiatrtcta)
Total School Districts '
1 ur
jlo diatricta in nonrcupondunt sdiuplt
d< - i> ) / J~|> II - i> .)/n \, n * number of
* l»roi>ortiun o( Affuutud Sclioola iu Uriijlnal Saini>lo ~ (At fuotud Sclmplu)
-M'iO|iUi.tiuii of Aftci:(i!i) Scltools in llo
Total School 0Q °
09
s
(-J
00
J
-------
to numbers of districts in the sample, on the other hand, would
give the original sample a weight of 5/28, resulting in a weighted
estimate of districts affected of .28. Equal weighting is
justifiable on the grounds that the non-respondent sample is a
random, probability sample from the entire cluster (excluding the
original respondents), while the original respondents can be said
to represent only themselves. Thus, from that point of view,
disproportionately weighting the non-respondent sample, compared
to its proportion of the combined sample, is a rational procedure.
The averaging procedure was the basis for all cost estimate
revisions.
i
(5) Revisions of Affected Population and Cost Estimates
A reestimation of the original affected population data (see
Table 5 through 10 in Chapter III) was necessary because of a
bias found in eight (8) of the clusters and because the proposed
rule has revised requirements regarding inspection and bulk
testing. Exhibit 12 provides estimates of the number of public
schools and school districts affected by the proposed "rule".
Exhibit 13 presents estimates of the number of schools requiring
inspection, bulk testing and those with exposure problems (i.e.,
schools with buildings that have friable asbestos-containing
materials). Exhibit 14 provides similar (to Exhibit 13) data at
the school district level.
It should be noted that estimates of the number of affected
schools and school districts are different from the original
estimates even in some clusters where bias was not found. This
is because the proposed rule differs in terms of regulatory scope
from that of the original study.
The data in Exhibit 14 on the proportion of school districts
in each cluster requiring either inspection or bulk testing were
172
-------
ESTIMATES OF THK NM.'UIKR Of SCHOOL DISTRICTS. SCHOOLS AMU STUI>UITS
AFU'OTIJi B» RL'LK 1 IN Till: SAMPLE AMD POPULATION
POPULATION
-J
10
STRATA
1
2-'
3
4
5
6^
7
8
9
10 (a I
10
.20
,7n
.U*
.J.,
.54
.35
.25
0
.67
.38
.29
.31
.25
VITAL
SCHOOL
DISTRICTS
32
,e
9
30
11
a
2
16
7
12
0
5
7
7
.1
l.<
•>
4
i
)
23
14
3
4
AFFECTED
SCHOOL
DISTRICTS
4
1
9
5
1
M
1
•)
1
1
.)
2
a
4
1
1
TOTAL
SCHOOL
DISTRICTS
1.105
4,o5u
l.nll
f.7n
224
i'M
51
1,733
u84
)8
70
75
17
41
547
BU
156
267
Slli
81
862
669
70
372
ESTIMATES-'
OP AFFECTED
3CHOM. DISTRICTS
4i>4
-,1/J
112
168
Iu3
U
J«5
•J75
JC
:r
-•1
14
U
Ji
.•111
»7
55
C7
ii
54
328
1-J4
21
91
v<
tm'AL
t SCHOOLS
..5
.31
.17
. .i
.119
. 11
.17
.2'!
.1.5
.U'J
.lb1-'
.
-------
EXHIBIT 13
ESTIMATES OF THE NUMBER AND DECREE TO WHICH SCHOOLS IN THE SAMPLE
AND POPULATION ARE AFFECTED BY RULE I
TOTAL
AFFECTED
SCHOOLS
SCHOOLS
NEEDING
I/INSPEC-
TION
SAMPLE
SCHOOLS
NEEDING
1/BOLK
~ TESTING
SCHOOLS
WITH
I/EXPOSURE
PM3BLLMS
POPULATION
SCHOOLS SCHOOLS SCHOOLS
TOTAL NEEDING 2/ NEEDING 2/ WITH 2/
AFFECTED INSPEC- BULK ~ EXPOSURE
SCHOOLS TION TESTING PROBLEMS
3
4
5
7
a
9
10 (a)
10 (c)
10{d)-X
10 (
e)-7
14
15
16
17
18
19
20
TOTAL
3
27
12
2
18
1
75
10
1
0
0
21
9
1
19
.33
.40
.50
.61 11
.39
.50
.41
.44
.16 1 1.00
.30 .7ii
1.00
l.ilO
1.00
1.00
.61 11 .37
1.00
1.00
.11 .11
.50 5 .50
1.00
.50
6
3
27
12
2
18
1
75
e
.50
1.00
1.90
1
19
.'A
1.00
1.00
1 .DO
1.00
J71
JM3S
342
444
435
47
1.121
83
141
100
124
435
144
376
144
•J
1,415
575
25
922
11,508
123
1,214
43
60
•m
49fi
218
202
13
••it*
140
50
72
3,165
25
922
2,336
373
2,124
342
444
435
47
489
83
141
140
SO
124
217
291
135
376
144
1,415
575
8,545
'Percentage of Affected Schools Needing a Specific Action • (Number of Affected Schools .
Total Affected Schools .
Where: i - 1-20
j « specific action
-Estimates of Schools in Population Requiring a Specific Action - (Total Affected (Percentage of Affected Schools Needing
Schools
) the Specific Action (ie. Inspection))
Affected Schools Requiring
'Weighted Average of Original Study Sample and Son-Respondent Sample - (Affected Schools Requiring a Specific Action) + A Specific Action
Total Schools
Total Schools
.,
Mr
In these strata the fact that no schools were affected in one of the samples leads to an inconsistency in the sum of
the number of schools requiring a specific action and the estimated total number of affected schools whc- the
calculation in footnote 3 is performed. In these strata the number needing a specific action was doubled.
174
-------
ESTIMATES OF THE PERCENTAGE OF A SCHOOL
cn
STRATA
3
4
i
8
9
10 (a)
10 (b) ?/
I0(c)
10(d) &
10 (e) -X
11 2/
12 2/
13 2/
14
15
16
17
18
19
20
Percentage of a Scl
requiring a Specif:
Where: i = 1-
j = specific action
k = school district
DISTRICT
REQUIRED
INSPECTION -/
2.0%
2.7
0
2.3
0
8.1
0
19.8
0
0
11.8
0
0
0
7.5
5.0
2.1
0
0
0
1.3
0
20.0
0
tool District
.c Action :
>n
WHICH WILL ON THE AVERAGE BE
TO TAKE A SPECIFIC ACTION
BULK TESTING -'
4.2%
2.68
0
.8
0
0
0
17.9
0
0
1.54
0
0
0
0
5.7
0
0
0
0
0
0
6.7
22.5
( T. (Schools Req. Specific Action)
k=l Total Schools
EXPOSURE PROBLEMS
4.3%
7.5
8.3
6.0
13.5
0
50.0
29.3
7.1
0
1.54
0
4.1
2.4
6.4
10.8
3.7
2.8
0
0
10.7
10.6
0
0
I/
Total School Districts
-/Percentage of a School District Requiring a Specific Action
( I Affected Schools
Of
fdtal Schools o
Affected Schools nr )
Total Schools nr
(Total Districts + Total Districts)
o nr
-------
utilized to reestimate total (national) costs. Total costs by
cluster for inspection and bulk testing (both polarized light
microscopy and X-ray diffraction) are presented in Exhibit 15.
The methodology utilized for the cost estimation is similar
to that employed in the draft report, except for revisions made
to the bulk testing costing procedure. The changes in the costing
methodology (from those employed in Chapter IV above) are several.
First, in the revised bulk testing formula, the number of bulk
samples required on the average in an affected public school has
been assumed to range between three and seven. The cost for each
bulk test is, therefore, presented in terms of this range, rather
than according to the number of square feet of asbestos, the
multiplier used in the original analysis. Second, Exhibit 15
incorporates the revised unit cost estimates. These revised unit
cost estimates, as discussed, were developed without outliers in
the sample of testing laoratories. Finally, the inspection costs
are substantially different from the original estimates. This
is due in part to changes as a result of bias correction and, in
part to the fact that the costs reestimates are specific only to
the proposed rule. They do not include those school districts
(as in the original study) that required periodic reinspection
of encapsulated or enclosed asbestos containing materials.
176
-------
TOTAL NATIONAL COSTS FOR
10
INSPECTION AND BULK TESTING
TOTAL INSPECTION COST TOTAL PETROGRAPHIC MICROSCOPY COST TOTAL X-RAY DIFFRACTION COST
CLUSTER
1
2
3
4
5
6
7
8
9
1
2
3
4
11
12
13
14
15
16
17
18
19
20
TOTAL
3-test minimum 7-test maximum
$ 2,398
1,523
0
511
0
0
0
7,477
0
0
1,231
0
0
11,434
144
264
0
0
0
608
0
0
0
$25,590
$30,680
17,650
0
1,542
0
0
0
46,699
0
0
834
0
0
0
1,775
0
0
0
0
0
0
0
29,989
$129,169
$71,587
41,183
0
3,598
0
0
0
108,963
0
0
1,946
0
0
0
4,141
0
0
0
0
0
0
0
69,974
$301,392
3-test minimum 7-test maximum
$53,700
32,967
0
2,978
0
0
0
88,145
0
0
1,620
0
0
0
2,686
0
0
0
0
0
0
0
50,893
$232,989
$125,301
76,923
0
6,489
0
0
0
205,680
0
0
3,780
0
0
0
6,267
0
0
0
0
0
0
0
118,750
$543,190
EXHIBIT
-------
VI. SUMMARY
The original survey and subsequent non-respondent survey provided
data to estimate the population affected and the cost of the proposed
rule. In this chapter, a summary of the survey and analysis results
are presented. These results are presented in the form of national
totals and include the number of affected public schools, school
districts and students. The number of affected public schools is
broken-down by required inspection and bulk testing activities under
the proposed rule, and the estimated cost of compliance. Finally, the
results of a risk analysis to estimate the number of students and
teaching and non-teaching staff at risk are presented.
1.
ESTIMATED POPULATIONS AFFECTED
The revised population estimates for the number of school
districts and public schools affected for the individual clusters are
presented in Exhibit 12. The national totals are presented below:
Affected Schobl Districts:
5,442 out of an estimated U.S.
total of 15,854 (34%)
Affected Public Schools:
11,588 out of an estimated
U.S. total of 91,667 (12.6%)
Affected Students:
2,992,347 out of an estimated
U.S. total of 40.1 million
students (7%).
178
-------
The estimate for total schools affected was further divided
according to the type of activity required of them under the proposed
rule. The number of affected schools add up to more than the total,
as some schools will require more than one type of action. Estimates
of schools needing a specific action (or with exposure problems) are
as follows (see exhibit 13):
Inspection: 3,165
Bulk Testing: 2,936
Exposure problems: 8,545
2. ESTIMATED COSTS OF THE PROPOSED RULE
The estimated total national costs for inspection and bulk testing
as required in the proposed rule are as follows (see exhibit 15):
Total National Inspection Cost: $25,590
Total National Bulk Testing Cost:
For Petrographic Microscopy Testing
Three tests per affected school - $129,169
Seven tests per affected school - $301,392
For X-Ray Diffraction Testing
Three tests per affected school - $232,989
Seven tests per affected school - $543,190
179
-------
Two sets of bulk testing costs, based on three samples and seven
samples per sampling area,were developed because most bulk testing
situations are expected to fall within this range. Three samples is
the minimum number required under the proposed rule. The need, according
to EPA estimates, may increase to as much as seven samples in instances
where sampling areas are large or where re-tests have to be conducted
due to inconclusive initial tests.
3. POPULATIONS POTENTIALLY AT RISK
There are a large number of students and teachers and non-teaching
staff that are at risk and that can potentially benefit from this rule.
The estimated number of students that are at risk is assumed to be
the number of students affected by the proposed rule. This estimate
is 2,992,347 students nationwide. This estimate was used as a basis
for determining the number of teachers and support staff also at risk.
Categories of educational staff were established to determine
the estimated potential number being exposed to asbestos risk and who
could benefit from the rule. The staff categorizations were based on
National Center for Education Statistics classifications.
For each category of educational staff, a staff to student ratio
was developed. These ratios use the actual number of students
nationwide, and the number of employees in each staff category
(teachers, professional staff, etc.) for the universe of primary and
secondary public schools. These data were obtained from the National
Center for Education Statistics. On the basis of these ratios and our
national estimate of students potentially at risk and benefitting from
the proposed rule, the number of staff potentially at risk was estimated
The results of this analysis are displayed in Exhibit 16.
180
-------
EXHIBIT 16
STUDENTS AND STAFF AT RISK
FROM ASBESTOS
Educational Staff
Category
Students
Classroom teachers _!/
Officials/Administrative
& Non-professional workers _2/
Professional/Educational 3/
Staff Category
to Student Ratio
N/A
0.5
.035
.005
Estimated Number
Removed from
Potential Risk
2,992,347
149,617
104,732
14,962
Total Students & Staff Removed from Potential Risk 3,261,658
\J "Classroom teachers" is defined as "a person employed to instruct
pupils in a situation where the teacher and the pupils are in the
presents of each other."
_2/ Category included as official & administrator are:
~~ ^
Superintendent, Assistant^ Deputy, Associate Superintendents,
Principals, Assistant Principals, Admin. Assistant, Admin. Interns,
Foremen, Ombudsmen, Supervisor, Manager, Director, Tax
Assessor/Collector.
And included as non-professional workers are:
Teaching Aides, Teaching Interns, Teaching Assistants. Bookkeeper,
Clerk, Messenger, Records Manager, Technical Staff, Office/Clerical,
Crafts and Trades, Operative, Laborers, Service Workers.
3_/ Categories inlcuded as professional/educators are:
Curriculum Specialists, Counselors, Librarians, Media Specialists,
Remidial Specialists, Accountants, Analysts, Architects,
Audiologists, Auditory Personnel, Dentists,
Dietitians/Nutritionists, Editors, Engineers, Evaluators, Legal
Workers, Negotiators, Opthamologists, Optometrists, Personnel Dept.
Physician Planner, Psychiatrists/Psychologists/Public/Community
Relations, Nurse, Registrar Research & Devp., Social Workers,
Statisticians, Therapists.
181
-------
APPENDIX A
Estimated Average Asbestos Square Footage
per Affected School District by Cluster
182
-------
APPENDIX A
Estimated Average Asbestos Scruare Footage
Per Affected School District By Cluster
AVERAGE SQUARE AVERAGE NUMBER
FOOTAGE OF ASBESTOS OF AFFECTED
PER AFFECTED SCHOOL SCHOOL PER AFFECTED
CLUSTER DISTRICT SCHOOL DISTRICT
1 62,767 2.5
2 14,000 2
30 0
4 7,174 2.6
5 59,340 2.5
60 0
70 0
8 22,021 1-3
9 800 1
10 236,036 7.7
11 300 1
12 26,461 1-5
13 5,000 2
14 0 0
15 0 0
16 0 0
17 44,205 3
18 42,773 2.2
19 0 0
20 3,446 3
183
-------
APPENDIX B
State Level Cost Estimates by Cluster
Corrective Action
184
-------
STATE CODE INDEX
STATE NAME STATE CODE
Alabama .....,,... 10
Alaska „ 11
Arizona 12
Arkansas . . . . ...... 13
California „ . 14
Colorado 15
Connecticut 16
Delaware <,... 17
District of Columbia .... 18
Florida 19
Georgia 20
Hawaii 21
Idaho 22
Illinois 23
Indiana 24
Iowa o 25
Kansas 26
Kentucky „ . 27
Louisiana 28
Maine . 30
Maryland ..... 31
Massachusetts 31
Michigan ..... 32
Minnesota ......... 33
Mississippi ........ 34
Missouri 35
Montana .......... 36
Nebraska ..... 37
Nevada . 38
New Hampshire 39
New Jersey 40
New Mexico . 41
New York 42
North Carolina 43
North Dakota 44
Ohio 45
Oklahoma 46
Oregon e 47
Pennsylvania , 48
Rhode Island 49
South Carolina 50
South Dakota 51
Tennessee » » 52
Texas 53
Utah . . 54
Vermont ..<,.. 55
Virginia 56
Washington 57
West Virginia ; 58 '
Wisconsin .„. ° <>.... 59
Wyoming .<,».<> 60
185
-------
Cost of Corrective Actions by State
CLUSTER
Corr
Ac
I
10
16
17
19
20
23
24
27
29
31
32
33
34
39
40
42
43
45
48
49
50
55
active
ion
Number of
School Distr. in
State in Cluster
23
46
5
10
81
427
97
80
250
141
217
306
59
113
87
272
23
190
93
8
27
235
Inspection
225.
451.
49.
98.
794.
4185.
951.
784.
2450.
1382.
2127.
2999.
578.
. 1107.
853.
2666.
225.
186.
911.
78.
265.
2303.
BULK TESTING
1
Petrograpbic
Microscopy
398.
796.
87.
173.
1401.
7387.
1678.
1384.
4325.
2439.
3754.
5294.
1021.
1955.
1505.
4706.
398.
3287.
1609.
138.
467.
4066.
Electron
Microscopy
1634.
3267.
355.
710.
5753.
30330.
6890.
5682.
17758.
10015.
15414.
21735.
4191.
8026.
6180.
19320.
1634.
13496.
6606.
568.
1918.
16692.
X-Ray
Diffraction
607.
1214.
132.
264.
2138.
11269.
2560.
2111.
6598.
3721.
5727.
8075.
1557.
2982.
2296.
7178.
607.
5014.
2454.
211.
713.
6202.
Encapsulation
81075.
162150.
17625.
35250.
285525.
1505175.
341925.
282000.
881250.
497025.
764925.
1078650.
207975.
398325.
306675.
958800.
81075.
669750.
327825.
28200.
95175.
828375.
Removal
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
s
a
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
AIR QUANTIFICATION
Air Monitoring
(Sampling)
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
o •
0
0
0
Lab Cost-Electron
Microscopy
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Lab Cost-Optical
Microscopy
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
^ 0
0
0
0
0
0
0
00
o\
-------
Cost of corrective Actions by state
CLUSTER 1 Cont'd
Corn
Ac
i
o
56
58
59
wtive
ion
Number of
School Dim. ii
Sttte in Cluste
37
. 8
270
e
_o
1
363.
78.
2646.
BULK TESTING
||
640.
138.
4671.
>.
a.
E S
Ss
2628.
568.
19178.
B
ll
X 0
976.
211.
7125.
e
o
|
UJ
130425.
28200.
951750.
IT
0
0
0
-a
M
O
.a
a
0
0
0
AIR QUANTIFICATION
B
11
it
3»
0
0
0
B
It
J|
Xt 0
3s
0
0
0
g
•n
a.
9 ^
« §
0 g
-S .H
-« S
0
0
0
00
-------
Cost of Corrective Actions by State
CLUSTER 2
Corr
Ac
5
I
13
15
25
26
28
35
36
37
41
44
46
51
53
,54
60
Mtive
ion
Number of
School Distr. in
State in Cluster
299
126
363
239
4
389
534
1060
58
301
433
149
641
16
38
1
1
471.
199.
572.
377.
6.
613.
842.
1672.
91.,
475.
683.
235.
1011.
25.
60.
BULK TESTING
l!
o *
li
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
B g
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
X-Riy
Diffractian
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Encapsulation
201681.
84990.
244851.
161210.
2698.
262388.
360194.
714991.
39122.
203031.
292067.
100503.
432367.
10792.
25632.
Removal
868009.
365783.
1053804.
693827.
11612.
1129283.
1550223.
3077222.
168376.
873815.
1257016.
432553.
1860849.
46449.
110316.
1
.§•
a
24111.
10161.
29272.
19273.
323.
31369.
43062.
85478.
4677.
24273.
34917.
12015.
51690.
1290.
3064.
AIR QUANTIFICATION
Air Monitoring
(Sampling)
13492.
5686.
16380.
10785.
180.
17553.
24096.
47831.
2617.
13582.
19539.
6723.
28924.
722.
1715.
Lab Cost-Electron
Microscopy
12730.
5364.
15454.
10175.
170.
16561.
22734.
45128.
2469.
12815.
18434.
6343.
27290.
681.
1618.
1
Lab Cost-Optical
Microscopy
8743.
3684.
.10614.
6988.
117.
11374.
15614.
30994.
1696.
8801.
12661.
4357.
18742.
468.
1111.
00
00
-------
cost of corrective Actions by state
CLUSTER 3
Corn
Ac
|
o
I
11
12
14
22
38
47
57
ctira
on
Numbtr of
School Distr. i
State in Clusta
30
.133
385
88
7
194
174
c
o
1
I
0
0
0
0
0
0
0
BULK TESTING
11
JS
£
0
0
0
0
0
0
0
>
B.
c 2
5s
0
0
0
0
0
0
0
e
ll
X 0
0
0
0
0
0
0
0
e
o
IM
0
0
0
0
0
0
0
1
1
K
0
0
0
0
0
0
0
a
a
1
a
0
0
0
0
0
0
0
AIR QUANTIFICATION
_c
If
<5
0
0
0
0
0
0
0
g
S
S £
Is
0 o
J3 U
2s
0
0
0
0
0
0
0
•g
V
9£
i§
0 0
Ji
0
0
0
0
0
0
0
00
vo
-------
Cost of Corrective Actions by state
CLUSTER
Corr
Ac
0>
•a
e
o
I
17
19
20
23
24
27
30
31
32
33
34
39
40
43
45
48
49
50
52
55
56
58
59
active
Ion
Number of
School Oistr. in
Statt in Cluster
4
27
24
25
48
35
12
4
35
16
56
2
3
79
44
61
2
35
64
3
48
33
10
c
o
26.
178.
158.
165.
317.
231.
79.
26.
231.
106.
370.
13.
20.
521.
290.
403.
13.
231.
422.
20.
317.
218.
66.
BULK TESTING
Petrographic
Microscopy
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Electron
Microscopy
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
X-Ray
Diffraction
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Encapsulation
84.
570.
506.
528.
1013.
739.
253.
84.
739.
338.
717.
42.
63.
1667.
928.
1287.
42.
739.
1350.
63.
1013.
696.
211.
Removal
2324.
581.
13946.
14528.
27893.
20339.
6973.
2324.
20339.
9298.
32542.
1162.
1743.
45907.
25568.
35447.
1162.
20339.
37190.
1743.
27893.
19176.
5811.
.a
o
172.
1161.
1032.
1075.
2064.
1505.
516.
172.
1505.
688.
2408.
86.
129.
3397.
1892.
2623.
86.
1505.
2752.
129.
2064.
1419.
430.
AIR QUANTIFICATION
Ol
If
J|
50.
337.
300.
312.
599.
437.
150.
50.
437.
200.
699.
25.
37.
986.
549.
761.
25.
437.
799.
37.
599.
412.
125.
Lab Cost-Electron
Microscopy
111.
750.
667.
695.
1333.
972.
333.
111.
972.
445.
1556.
56.
83.
2195.
1222.
1695.
56.
972.
1778.
83.
1333,
917.
279.
Lab Cost-Optical
Microscopy
18.
124.
110.
115.
221.
161.
55.
18.
161.
74.
258.
9.
14.
363.
202.
281.
9.
161.
294.
14.
221.
152.
46.
vo
o
-------
Cost of corrective Actions by state
CLUSTER 5
Corn
Act
|
o
13
15
25
26
28
35
36
37
41
44
46
51
53
54
60
ictive
on
Number of
School Dim. in
State in Cluster
5
10
15
15
43
17
3
5
21
5
12
8
39
11
9
B
29.
57.
86.
86.
246.
97.
17.
29.
120.
29.
69.
46.
223.
63.
51.
BULK TESTING
•J &
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
«= 8
— IS
ui S
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
B
X O
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Encapsulation
28697.
57393.
86090.
86090.
246792.
97569.
17218.
28697.
120526.
28697.
68872.
45915.
223834.
63133.
51654.
Removal
48656.
97312.
145968.
145968.
418441.
165430.
29194.
48656.
204355.
48656.
116774.
77849.
379516.
107043.
87581.
1
.8
O
1012.
2023.
3035.
3035.
8700.
3440.
607.
1012.
4249.
1012.
2428.
1619.
7891.
2226.
1821.
AIR QUANTIFICATION
Air Monitoring
(Sampling)
209.
419.
628.
628.
1801.
712.
126.
209.
880.
209.
503.
335.
1634.
461.
377.
Lab Cost-Electron
Microscopy
246.
492.
738.
738.
2115.
836.
148.
246.
1033.
246.
590.
393.
1918.
541.
443.
Lab Cost-Optical
Microscopy
186.
373.
559.
559.
1602.
634.
112.
186.
783.
186.
447.
298.
1453.
410.
335.
vo
-------
Cost of Corrective Actions by State
CLUSTER
Corr
Ac
«
3
13
15
25
26
28
35
36
37
41
44
46
51
53
i 60
Mtive
ion
Numbar of
School Dim. in
Stata in Cluster
17
3
1
2
1
4
2
4
3
2
3
2
23
2
•. s
•
0
0
0
0
0
0
0
0
0
0
0
0
0
0
BULK TESTING
Petroorapbic
Microscopy
0
0
0
o
0
0
0
0
0
0
0
0
0
0
Electron
Microscopy
0
0
0
0
0
0
0
0
0
0
0
0
0
0
X-Ray
j D iff fiction
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Encapsulation
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Removal
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
.§•
a
0
0
0
0
0
0
0
0
0
0
0
0
0
0
AIR QUANTIFICATION
Air Monitoring
(Sampling)
0
0
0
0
0
0
0
0
0
0
0
0
0
0
e
Lab Cost-Electroi
Microscopy
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Lab Cost-Optical
Microscopy
0
0
0
0
0
0
0
0
0
0
0
0
0
0
vo
-------
Cost of corrective Actions by State
Cluster 7
Corn
Acl
•0
0
a
12
14
22
38
47
57
ctive
ion
•- £
jjs
Z CO
-------
Cost of Corrective Actions by State
Cluster 8
Corr
Ac
1
o
10
16
17
19
20
23
24
27
29
31
32
33
34
39
40
42
43
45
48
49
50
56
58
59
ictive
lion
B t»
•s|J
•Q O *~
all
12
38
1
1
9
297
51
12
9
86.
115
60
5
26 •],
337 *
243
1
212
123
7
6
6
1
75
§
1
V
I
98.
312.
8.
8.
74.
2435.
418.
98.
74.
705.
943.
492.
41.
213.
' 2763.
1993.
8.
1738.
1009.
57.
49.
49.
8.
615.
BULK TESTING
'•= S:
jj,|
5 S
Is
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
5
B u
u *"
ii
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
B
_o
£•1
^M
x'o
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
B
o
i
i
B
u
B
111
63595.
201385.
5300.
5300.
47696.
L573981.
270280.
63595.
47696.
455766.
609454.
317976.
26498.
137790.
L785965.
L287803.
5300.
L123515.
651851.
37097.
31798.
31798.
5300.
397470.
™
i
g
ec
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
a
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
AIR QUANTIFICATION
.s
S~s
Jf
E
•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
g
£
SI
Is
A G
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
I 1
0 §
•O h
" .S
-•s
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
VD
-------
Cost of Corrective Actions by state
?Cluster 9
Corn
Ac
O)
3
1
1.3
15
25
26
35
36
37
41
44
46
51
53
ictive
ion
C *•
Ill
ill
44
18
1 32
33
75
37
34
2
12
145
6
249
e
I
1157.
473.
842.
868.
1973.
973.
894.
53.
316.
3814.
158.
6549.
BULK TESTING
If
i; o
0
0
0
0
0
0
0
0
0
0
0
0
sir
Ii
0
0
0
0
0
0
0
0
0
0
0
0
1
x 5
0
0
0
0
0
0
0
0
0
0
0
0
e
0
•g
M
cx
i
ui
0
0
0
0
0
0
0
0
0
0
0
0
1
1
ec
0
0
0
0
0
0
0
0
0
0
0
0
a
a
1
O
0
0
0
0
0
0
0
0
0
0
0
0
AIR QUANTIFICATION
a>
e
11
il
0
0
0
0
0
0
0
0
0
0
0
0
e
||
a ;=
0
0
0
0
0
0
0
0
0
0
0
0
m
(O
a.
l!
3i
0
0
0
0
0
0
0
0
0
0
0
0
in
-------
Cost of Corrective Actions by state
CLUSTER 10 REGION 3
Corr
Ac
•B
O
cj
18
30
48
56
58
active
ion
c ,_
*~ 3
•~ s 1
ill
= •5 a
Z CO CO
1
1
22
11
3
B
e
B
• 21
21
463
231
63
BULK TESTING
O
'•££:
ll
JS
i
0
0
0
0
0
£
a §
sis
0
0
0
0
0
B
ll
x o
0
0
0
0
0
B
a
M
o.
i
UJ
62,768
62,768
1,380,892
690,446
188,303
i
cc
28,486
28,486
626,700
313,350
85,459
1
.§•
a
1,656
1,656
36,427
18,213
4,967
AIR QUANTIFICATION
e
If
c .S
61
61
1349
674
184
B
g
u
3 >:
K B
Jl
.a o
"2
101
101
2221
1111
303
8
^
5 £
i §
- 1
24
24
533
267
73
I-1
vo
-------
Cost of Corrective Actions by state
CLUSTER 10 REGION 6
Corn
Ac
at
•a
CJ
13
28
41
46
53
ctitre
on
B fc-
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s- =
S o •"
EOS
a -g fl
xaS
5
5
1
5
59
B
1
I
105
105
21
105
1241
BULK TESTING
(U
li
0
0
0
0
0
-
B S
ii
0
0
0
0
0
B
0
li
X 0
0
0
0
0
0
B
i
1
3
ui
0
0
0
0
0
1
oc
0
0
0
0
0
s
1
o
0
0
0
0
0
AIR QUANTIFICATION
it
0
0
0
0
0
B
o
fc
.a o
0
0
0
0
0
3
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5 1
0
0
0
0
0
to
-------
Cost of corrective Actions by State
CLUSTER 10
KKUION 7
Corr
Ac
•a
o
o
S
25
26
35
37
ectiue
iun
C *-
£ K
•sja
£ c
jj-i o
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7
3
5
2
C
1
309
132
220
88
BULK TESTING
0
if
S °
Sj
a. S
0
0
0
0
SS
0
0
0
0
C
o
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II
X O
0
0
0
0
a
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M
4J
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1,051,361
450,583
750,972
300,389
o
a>
0 0
3!
0
0
0
0
8
fi
1 »
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0
0
0
0
CO
-------
Cost of corrective Actions by State
CLUSTER 10 REGIONS 9-10
Corrc
Act
o
1
12
14
22
47
57
ictive
ion
l°-s
ill
Zf/f £
2
28
1
3
7
|
i
39
553
20
59
138
BULK TESTING
f |
ii
0
0
0
0
0
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0
0
0
0
0
B
ec:f
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0
0
0
0
0
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159,909
2,238,719
79,954
239,863
559,680
1
i
ec
256,377
3,589,281
128,189
384,566
897,320
*
£
a
14,902
208,625
7,451
22,353
52,156
AIR QUANTIFICATION
C
•j;
11
5"
552
7724
276
828
1931
B
5
Ul £
31
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909
12,721
454
1,363
3,180
8
^
ii
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2s
218
3,054
109
327
764
10
vo
-------
Cost of Corrective Actions by State
Cluster 11
Corrective
Action
01
•n
3
12
14
22
47
57
B •-
ill
li§
Z
-------
cost of corrective Actions by state
Cluster 12
- — -Corrective
Ac
o>
13
O
U
i
13
15
25
26
28
35
36
41
44
46
51
54
60
on
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Q *•*
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1
3
17
6
1
2
4
2
1
5
20
2
4
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0
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4.
13.
71.
25.
4.
8.
17.
a.
4.
21.
84.
8.
17.
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o
iU
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0
0
0
0
0
0
0
0
0
0
0
0
0
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0
0
0
0
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0
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CL
8
B
UJ
2306.
6917.
39199.
13835.
2306.
4612.
9223
4612.
2306.
11529.
46116.
4612.
9223.
T5
i
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5457.
16370.
92766.
32741.
5457.
10914.
21827.
10914.
5457.
27284.
109136.
10914.
21827.
.
S
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b
111.
333.
1889.
667.
111.
222.
444.
222.
111.
556.
2222.
222.
444.
AIR QUANTIFICATION
o>
B
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S-S
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<£
34.
103.
585.
206.
34.
69.
138.
69.
34.
172.
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69.
138.
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43.
128.
723.
255.
43.
85.
170.
85.
43.
213.
850.
85.
170.
•&
u
'£
-------
Cost of corrective Actions by State
Cluster 13
Correctiva
Action
a
•a
o
u
13
15
25
26
28
35
36
37
41
46
53
54
C *-
• ti
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Hi
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5
18
10
5
12
32
1
4
1
13
47
8
c
a
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e
26.
94.
52.
26.
62.
166.
5.
21.
5.
68.
244.
42.
BULK TESTING
.-
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II
0
0
0
0
0
0
0
0
0
0
0
0
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0
0
0
0
0
0
0
0
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0
0
0
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0
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0
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cc
7560.
27216.
15120
7560.
93744.
48384.
1512.
6048.
1512.
19656.
71064.
12096.
8
0
a.
.2
a
158.
567.
315.
158.
378.
1008
31.5
126.
31.5
410.
1670.
252.
AIR QUANTIFICATION
e
It
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218.
783.
435.
218.
522.
1392.
44.
174.
44.
566.
2045.
348.
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31
211.
760.
422.
211.
506.
1350.
42.
169.
42.
549.
1983.
338.
_
0
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a.
0 a
TX g
5s
J3 0
2s
166.
598.
332.
166.
398.
1062.
33.
133.
33.
432.
1560.
266.
NJ
O
-------
Cost of corrective Actions by state
Cluster 14
. — -Corre
Ac
-a
o
O
11
12
14
21
22
38
47
57
ctive
on
£ •
ij|
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E ° S
3 -g S
Z
DC
0
0
0
0
0
0
0
0
a
o
JO.
o
0
0
0
0
0
0
0
0
AIR QUANTIFICATION
01
ll
if
0
0
0
0
0
0
0
0
e
o
fc
cS S
-a o
2s
0
0
0
0
0
0
0
0
•a
a
If
0
0
0
0
0
0
0
0
to
o
UJ
-------
Cost of corrective Actions by State
Cluster
15
Corn
Ac
State Code
19
23
24
31
32
33
34
39
42
45
48
50
52
55
56
58
ictive
ten
Number of
School Oistr. in
State in Ouster
1
70
29
1
16
1
15
2
1
3
17
1
47
8
2
3
e
1
&
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
BULK TESTING
i*
li
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
5
c 8
ii
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
c
e
li
X 0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
e
i
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
i
OC
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
la
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
AIR QUANTIFICATION
?
s?
£3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
e
Si
Ji
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2s
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
TB
Ir
S o
Jg
.a u
2s
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
,
-------
cost of corrective Actions by state
CLUSTER 16
- — Corrective
Action
0
•a
o
o
11
12
14
22
38
47
57
Number of
School Distr. i
State in Cluste
4
5
20
17
2
16
17
e
o
0
0
0
0
0
0
0
BULK TESTING
1!
e g
li
0
0
0
0
0
0
0
0.
5l
0
0
0
0
0
0
0
e
.0
cr 3:
x a
0
0
0
0
0
0
0
e
i
I
§
Ul
0
0
0
0
0
0
0
i
DC
0
0
0
0
0
0
0
i
s
o
0
0
0
0
0
0
0
AIR QUANTIFICATION
.E
11
11
0
0
0
0
0
0
0
e
o
o 8"
o S
.a u
2s
0
0
0
0
0
0
0
ID
CJ
It
li
jj U
2s
0
0
0
0
0
0
0
fo
o
Cn
-------
Cost of Corrective Actions by State
Cluster
17
Corr
Ac
O)
•o
O
0
I
10
16
17
19
20
23
24
27
30
31
32
33
34
39
40
42
43
45
48
49
50
52
56
58
59
active
ion
B >-
$
.3o~
E J S
= -S a
•E <3» c/»
1
1
1
2Q
19
93
54 .
13
8
42
139
27
4
1
82
1
15
94
159
14
16
27
21
5
5
Inspection
9.
9.
9.
180.
171.
837.
486.
117.
72.
378.
1251.
243.
36.
9.
738.
9.
135.
846.
1431.
126.
144.
243.
189.
45.
45.
BULK TESTING
Petrographic
Microscopy
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
Electron
Microscopy
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
X-Ray
Diffraction
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
Encapsulation
1063.
1063.
1063.
21262.
20199.
98868.
57407.
13820.
8505.
44650.
147771.
28704.
4252.
1063.
87174.
1063.
15947.
99931.
169033.
14883.
17010.
28704.
22325.
5316.
5316.
Removal
3811.
3811.
3811.
76228.
72417.
354460.
205816.
49548.
30491.
160079.
529785.
102908.
15246.
3811.
312535.
3811.
57171.
358272.
606013.
53360.
60982.
102908.
80039.
19057.
19057.
1
o.
.a
o
287 .
287.
287.
5730.
5444.
26645.
15471.
3725.
2292.
12033.
39824.
7736.
1146.
287.
23493.
287.
4298.
26931.
45554.
4011.
4584.
7736.
6017.
1433.
1433.
AIR QUANTIFICATION
Air Monitoring
(Sampling)
29.
29.
29.
574.
545.
2669.
1550.
373.
230.
1205.
3989.
775.
115.
29.
2353.
29.
431.
2698.
4563.
402.
459.
775.
603.
144.
144.
Lab Cost-Electron
Microscopy
60.
60.
60.
1196.
1136.
5561.
3229.
777.
478.
2512.
8312.
1615.
239.
60.
4904.
60.
897.
5621.
9508.
837.
957.
1615.
1256.
299.
299.
Lab Cost-Optical
Microscopy
38.
38.
38.
762.
724.
3543.
2057.
495.
305.
1600.
5296.
1029.
152.
38.
3124.
38.
572.
3581.
6058.
533.
610.
1029.
800.
191.
191.
-------
Cost of corrective Actions by State
Cluster 18
" Corn
Ac
-a
3
v»
10
16
17
19
20
23
24
27
29
30
31
32
33
34
39
40
42
43
45
48
49
50
56
59
ictive
on
B |2
•11
HI
J-SS
Z Jf e/»
25
54
1
1
4
33
6
7
4
1
60
18
15
3
4
55
206
4
77
43
6
2
3
37
Inspection
188.
405.
8.
8.
30.
248.
45.
53.
30.
8.
450.
135.
113.
23.
30.
413.
1545.
30.
578.
323.
45.
15.
23.
278.
BULK TESTING
Petrognphic
Microscopy
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Electron
Microscopy
1
! 1
i
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
X-Ray
Diffraction
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
o
Encapsulation
63903.
138029.
2556.
2556.
10224.
84351.
15337.
17893.
10224.
2556.
153366.
46010.
38342.
7668.
10224.
140586.
526557.
10224.
"196820.
109912.
15337.
5112.
7668.
94576.
Removal
78725.
170046.
3149.
3149.
12596.
103917.
18894.
22043.
12596.
3149.
188940.
56682.
47235.
9447.
12596.
173195.
648694.
12596.
242473.
135407.
18894.
6298.
9447.
116513.
*ia
M
o
n.
_£
O
6738.
14553.
270.
270.
1078.
8894.
1617.
1887.
1078.
270.
16170.
4851.
4043.
809.
1078.
14823.
55517.
1078.
20752.
11589.
1617-
539.
809.
9972.
AIR QUANTIFICATION
Air Monitoring
(Sampling)
560.
1210.
22.
22.
90.
739.
134.
157.
90.
22.
1344.
4032.
336.
67.
90.
1232.
4614.
90.
1725.
963.
134.
45.
67.
829.
Lab Cost-Electron
Microscopy
1210.
2614.
48.
48.
968.
1597.
290.
339.
194.
48.
2904.
8712.
726.
145.
194.
2662.
9970.
194.
3727.
20B1.
290.
97.
145.
1791.
Lab Cost-Optical
Microscopy
153.
329.
6.
6.
24.
201.
37.
43.
24.
6.
366.
110.
92.
18.
24.
336.
1257.
24.
470.
2t>2.
37.
12.
6.
22h.
NJ
O
-------
Cost of corrective Actions by State
Cluster
19
Corn
Ac
Of
•o
0
o
in
12
14
47
57
ictive
ion
e fc
Number of
School Oistr.
State in Clusu
7
47
7
9
c
o
•fi
1
0
0
0
0
BULK TESTING
ti
JG
S
38.
254.
38.
49.
0 f
ii
159.
1067.
159.
204.
c
•p
11
X 0
63.
423.
63.
81.
e
o
1
"a
IA
a.
3
Ul
0
0
0
0
o
-------
cost of corrective Actions by State
Cluster 20
Jlorre
Ac
u
|
10
16
17
19
20
23
24
27
29
30
31
32
33
Btive
on
Number of
School Distr. in
State in Ouster
60
8
. 4
5
47
1
6
32
15
2
22
6
8
1
&
JZ
690.
92.
46.
58.
541.
12.
69.
368.
173.
23.
253.
69.
92.
BULK TESTING
t|
5 u
2x
55.
7.
4.
5.
43.
1.
6.
29.
14.
2.
20.
6.
7.
c g
u! S
1362.
182.
91.
114.
1067.
23.
136.
726.
341.
45.
499.
136.
182.
•a
x 5
90.
12.
6.
8.
71.
2.
9.
48.
23.
3.
33.
9.
12.
e
1
e
UJ
0
0
0
0
0
0
0
0
0
0
0
0
0
1
* S:
K g
o B
o e
SI
0
0
0
0
0
0
0
0
0
0
0
0
0
(Q
u
•0
VS.
ii
4= iS
2s
0
0
0
0
0
0
0
0
0
0
0
0
0
K>
O
VO
-------
Cost of Corrective Actions by State
CLUSTER
20 Cont'd
Corn
Ac
3
1
34
39
40
42
43
45
48
50
55
56
58
59
ictive
lion
Number of
School Distr. in
Stttt in Ouster
12
7
9
45
15
21
8
8
1
7
2
21
Inspection
138.
81.
104.
518.
173.
242.
92.
92.
12.
81.
23.
242.
BULK TESTING
I*
li
11.
6.
8.
41.
14.
19.
7.
7.
1.
6.
2.
19.
e S
uJX
272.
159.
204.
1022.
341.
477.
182.
182.
23.
159.
45.
477.
X-Ray
Diffraction
18.
11.
14.
68.
23.
32.
12.
12.
2.
11.
3.
32.
e
i
I
§
Ul
0
0
0
0
0
0
0
0
0
0
0
0
i
E
0
0
0
0
0
0
0
0
0
0
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O
-------
APPENDIX C
Detailed Listings of Affected Schools
and Students in the New York Public
School System
211
-------
APPENDIX C
DETAILED LISTINGS OF AFFECTED SCHOOLS AND STUDENTS IN
THE NEW YORK CITY PUBLIC SCHOOL SYSTEM
New York City Schools Asbestos Task Force was officially organized
in November 1978. This task force is responsible for the organization
and execution of asbestos control for the five boroughs of New York
City. This responsibility includes inspection of schools, bulk
sampling, identification of the type of corrective action needed,
development of a corrective action schedule, and selection and
monitoring of contractors engaged to perform the asbestos corrective
work.
The events that led to the formation of this task force began in
1977 when an asbestos problem caused school closings in New Jersey.
The New York Board of Education began an assessment of the degree of
asbestos hazard by reviewing building plans and specifications for
asbestos materials in New York schools, and by conducting visual
inspections. This survey was the basis of Phase One of its
comprehensive asbestos control program. Phase One involved the removal
of all materials suspected of containing asbestos in what were
considered the twelve worst-case schools. The term suspected is used
because laboratory tests were not made on bulk samples of the
questionable material. As a result of this survey, which produced 185
suspect schools, and the work done in Phase One, the need for a long
term unit to work on the asbestos problem was recognized.
212
-------
In the remainder of this Appendix we discuss the city's asbestos
abatement program, provide detailed listings of affected schools and
students by school district, and finally discuss the financial
implications of the program.
1. ASBESTOS ABATEMENT
The Task Force has developed an asbestos abatement program. The
steps in the program are: inspection, bulk testing, identifying the
corrective action for a situation, and continual monitoring of areas
which were encapsulated or enclosed.
Sawyer's Algorithm is used as a guide when inspecting a building
for the seriousness of the asbestos problem in areas with friable
material. Whenever there is any indication that an area which contains
asbestos which has not been corrected is deteriorating, another
inspection is done. The inspectors have technical backgrounds and are
knowledgeable in the use and appearance of asbestos-containing
materials.
Bulk samples are taken from all materials suspected of containing
asbestos. The potential friability of a material is considered to be
as important as its current friable state. When a bulk sample is
taken, it is divided into three parts. One is kept in the Office of
the Task Force and the other two are sent to different laboratories
for testing. The test identifies the number of asbestos fibers in the
sample. By comparing the results from the two laboratories, more
reliability can be placed on the results. There have been instances
when the results reported by the laboratories varied greatly. When
this occurs, a third laboratory test is done. Currently, New York City
has approximately 500 samples on which results are pending.
213
-------
When the results of the bulk sample are returned, Sawyer's asbestos
algorithm is completed. The algorithm score indicates when an area
will be corrected. The higher the algorithm score, the higher the
priority and the sooner it will be corrected. This score, however,
does not necessarily indicate how it will be corrected.
The decision of how an area will be corrected is based upon
certain general rules of thumb. With some exceptions, areas that are
judged to need removal are those that contain sprayed-on fireproofing,
insulation, or acoustical materials. Areas exempt from removal are
areas located behind dropped ceilings, and boiler and mechanical rooms.
Mechanical and boiler rooms are the most difficult areas in which to
remove or structurally contain materials. Most of the sprayed-on fire-
proofing and insulation located in these areas is encapsulated. These
materials are generally very friable and the encapsulation material
makes them very hard.
Hard acoustical plaster materials which are located in high
activity areas (exits, cafeterias, shops, etc.) are generally enclosed
with a physical barrier, generally sheet rock. Low activity areas with
acoustical plaster (offices and libraries) are generally painted with
two coats of approved sealer.
Areas where encapsulation and/or enclosure were used as a
corrective measure are kept under periodic surveillance for
deterioration. Surveillance is also necessary when work is done in
that area. An Asbestos Program Form is published for all schools. The
Form will indicate if there are any asbestos materials in the school
and where they are located. A copy of each asbestos program form is
placed in a main book and in the custodian's office. The custodian
also uses an 'asbestos1 stamp on each page of his sign-in book. This
stamp indicates there are asbestos containing materials in the school.
214
-------
In the areas where the asbestos is located, labels are placed which
indicate that before any work commences in that area, the custodian
should be notified.
Since it is difficult to visually recognize materials which have
replaced asbestos containing materials in boiler rooms, sections where
removal has taken place are painted blue.
2. DETAILED LISTINGS
Approximately 65 of the schools have had asbestos problems
corrected. Another 120 schools may still need correction. This figure
may change as there are a number of bulk sample results pending.
The following tables give detailed listings by school district
of affected schools and students in the New York City Public School
System.
The general location and number of the school districts are as
follows:
Manhattan, districts 1-6
Brooklyn, districts 13-23, 32
Bronx, districts 7-12
Queens, districts 24-30
Staten Island, district, 31
High Schools, divided by borough, district 78.
215
-------
Data on each affected school include affected square footage type
of corrective action to be taken and the number of students affected.
The number of affected students is the actual enrollment of that
school. Square footage is based on estimates of the average size of
affected areas. These averages are provided in a table following this
page. The corrective action listed may be what is actually scheduled
to be done or estimates based on general rules of thumb discussed
above.
In instances, where bulk tests were pending, data were collected
and placed in the potentially affected columns (right hand columns)
of the detailed listings. Listed is information on potentially
affected square feet, corrective action expected and number of students
affected.
3. FINANCING NEW YORK CITY'S ASBESTOS CONTROL PROGRAM
The New York City Central School district's asbestos control
program is funded through the local capital improvements budget. These
are at present no outside funds used for corrective actions. Until
FY1980, funds used in the program were reclassified from other programs
in the budget. The funds for asbestos control were most often
reclassified from the "Modernization and Construction" line item. In
FY1980 asbestos control was given a separate line item entitled, "E-
1891, Upgrading of Building Environment (Asbestos)".
In FY1980, $5 million was appropriated for asbestos control
activities. The amount proposed for FY1981 is $2.8 million; for FY1982,
$3.5 million; and for FY1983, $2.8 million. At the end of this period,
it is anticipated that all necessary work will have been completed.
The 1981, 1982, and 1983 proposed amounts for asbestos control action
are, respectively, 2.1%, 2.1%, and 2.2% of the proposed total school
system capital improvement budget.
216
-------
AVERAGE SQUARE FOOTAGE OF ROOMS
in NEW YORK CITY PUBLIC SCHOOLS
ROOMS
Auditorium Ceilings
Auditorium Walls (3)
Band Room, Music Room
Cafeteria (Teacher)
Cafeteria (Student)
Classroom
Corridors
Custodians Workshop
Dressing Room off Stage
Exits/Vestibuls
Gymnasium (Small)
Kitchen
Serving Area
Kindergarten
Library
Lobby
Locker Room
Medical Suite
Offices - Principal
- Secretary
- Custodians
Shops
Sound Room
Store Rooms
AVERAGE SQUARE FOOTAGE
5000
2000
1500
700
4000
700
1500
300
200
150
3500
1500
150
900
1500
700
1500
700
400
200
300 '
1500
150
350
217
-------
School District:
Borough: Manhattan
School
P-15
P-19
P-20
P-22
P-25
P-34
J-56
J-60
P-61
P-63
P-71
P-97
P-110
P-137
P-140
P-142
P-188
Actual
Total
Total Stude
ACTUAL
Removal
Sq. Ft.
its in Dis
Sncap.
Sq. Ft.
300
300
rict
Enclos.
Sq. Ft.
1500
1650
3150
Boilers
& Pipes
X
X
X
X
2:
Total
Af-gggfaatl
A£.^CWUSU
Sq. Ft.
1500
300
1650
3450
t.
L8
Total
Stud&vbs
462
N/A
896
1,358
L2,064
POTENTIAL
Encap.
Sq. Ft.
Enclos.
Sq. Ft.
Total
Affected
Sq. Ft.
-------
School District: 2
Borough: Manhattan
School
p-l
P-2
P-3
P-6
P-ll
J-17
P-26
P-33
P-40
P-41
P-42
P-51
P-59
J-65
1-70
J-104
J-lll
J-114
P-116
P-124
P-126
P-130
P-l 51
P-167
P-183
P-190
P-?
P
P- Annex
P, 217
A tual
Tt*
Toical Stude
ACTUAL
Reuuval
Sq. Ft.
its in Dist
Encao.
Sq. Ft.
5000
300
5000
10,300
rict
Enclos.
Sq. Ft.
2000
2000
Boilers
& Pipes
X
2
Total
Affected
Sq. Ft.
5000
2000
300
5000
12,300
19
Total
1™ !•• i JjtMifer-t
students
363
430
840
511
2144
20961
POTENTIAL
Encap.
Sq. Ft.
Enclos.
Sq. Ft.
Total
Affected
Sq. Ft.
•
-------
School District: 3
Borough: Manhattan
School
P-9
1-44
J-54
P-75
P-76
P-84
P-87
1-88
P-113
J-118
P-144
P-145
P-149/207
P-163
P-165
P-166
P-179
P-180
P-185/208
P-191
P-199
Actual
Total
Total Stuc
ACTUAL
BsDoval
Sq. Ft.
/
ents in Di
Encap.
Sq. Ft.
5000
5000
2200
12,200
strict
Enclos.
Sq. Ft.
1500
1500
3000
Vn\\t*£<*
& Pipes
X
22
Total
Affected
Sq. Ft.
1500
5000
1500
5000
2200
15,200
0
.
Total
S-frrfen+^s
"
N/A
871
N/A
339
287
1497
16,143
POTENTIAL
Encap.
Sq. Ft-
Enclos.
Sq. Ft.
Total
Affected
Sq. Ft.
-------
School District: 4
Borough: Manhattan
School
P-7
J-13
1-45
P-50
P-57
P-72
P-83
P-85(Vacan
P-96
99
P-101
P-102
P-108
P-109
P-112/206
J-117
P-121
P-146
P-155
P-171
Actual
Total
Total Stud<
ACTUAL
Heroval
Sq. Ft.
)
nts in Dis
Encap.
Sq. Ft.
150
14400
5000
19,550
rict
Enclos.
Sq. Ft.
8500
1500
1500
1500
13,000
Boilers
& Pipes
X
X
X
22]
Total
Affected
Sq. Ft.
8650
15900
1500
5000
1500
32,550
L
Total
Students
706
709
423
1023
610
3471
15,395
POTENTIAL
Encap.
Sq. Ft.
Enclos.
Sq. Ft.
Total
Affected
Sq. Ft.
-------
School District:
Borough: Manhattan
School
1-10/200
P-30/31
P-36
J-43
P-46
P-79
P-92
P-123
P-125
P-129
P-133
P-154
P-156
P-161
P-175
P-197
1-201
1-136
P-194
1-195
Actual
Total
Total Stude
ACTUAL
Renewal
Sq. Ft.
nts in Dis
Encap.
Sq. Ft.
5000
5000
5000
5000
20,000
.rict
Enclos.
Sq. Ft.
700
4000
4700
Boilers
& Pipes
X
X
X
2
Total
Affected
Sq. Ft.
5000
5000
5000
5700
4000
24,700
22
ri
Total
Students
596
608
692
757
523
3,176
14,047
POTENTIAL
Encap.
Sq. Ft.
Enclos.
Sq. Ft.
Total
Affected
Sq. Ft.
-------
School District: 6
Borough: Manhattan
School
P-28
J-52
P-98
P-115
P-128
P-132
J-143
P-152
P-153
1-164
P-173
P-187
P-189
P-192
Actual
Total
Total Stud
ACTUAL
Resnoval
Sq. Ft.
aits in Dis
Encap.
Sq. Ft.
5000
5000
5000
5000
1500
21,500
trict
Enclos.
Sq. Ft.
1500
1,500
Boilers
& Pipes
X
X
22
Total
Affected
Sq. Ft.
5000
5000
5000
5000
3000
23,000
3
Total
Students
1201
1223
1416
1169
1378
6,387
19,622
POTENTIAL
Sq. Ft.
Enclos.
Sq. Ft.
Total
Affected
Sq. Ft.
-------
School District: 7
Borough: Bronx
School
P-I
P-5
P-18
P-lS(old)
P-25
P-27
P-29
P-30
P-31
P-40
P-43
P-49
P-65
P-124
1-139
1-149
1-151
P-154
1-155
P-156
P-157
P-161
1-162
1-183
1-184
Actual
Total
Total Stude
ACTUAL
Removal
Sq. Ft.
its in Dis
Encap.
Sq. Ft.
5000
5000
5900
15,900
rict
Enclos.
Sq. Ft.
1400
800
2200
Boilers
& Pipes
•X
X
X
X
X
X
22
Ttotal
Affected
Sq. Ft.
6400
5800
5900
18,100
4
i
Total
Students
505
918
625
2,048
1.6,541
POTENTIAL
Encap.
Sq. Ft.
Enclos.
Sq. Ft.
Total
Affected
Sq. Ft.
-------
School District:
Borough: Bronx
School
P-14
P-36
P-39
P-48
1-52
P-60
P-62
P-69
P-71
P-72
1-74
P-75
P-93
P-100
J-101
P-107
P-119
J-120
J-123
J-125
P-130
1-131
P-138
P-140
P-146
P-152
1-174
P-182
1-192
Actual
Total
Total Studei
ACTUAL
Seroval
Sq. Ft.
ts in Dist
Encao.
Sq. Ft.
5400
5000
5000
15,400
ict
Enclos.
Sq. Ft.
3000
3000
Rn-jlo-p^
& Pipes
X
2
Total
Affected
Sq. Ft.
8400
5000
5000
8,400
25
Total
Students
510
781
1483
2,774
23,138
POTENTIAL
Encap.
Sq. Ft.
Enclos.
Sq. Ft.
Total
Affected
Sq. Ft.
-------
School District: 9
Borough: Bronx
School
P-2
P-4
P-ll
1-22
P-28
P-35
P-42
P-53
P-55
P-58
P-63
P-64
P-70
P-73
1-82
P-88
P-90
P-104
P-109
P-110
P-114
P-126
P-132
1-145
P-147
1-148
P-163
1-166
P/I-229
J-117
Actual
Total
Total Stud
* Boiler RC
ACTUAL
Removal
Sq. Ft.
nts in Dis
>ms and Pi
Encap.
Sq. Ft.
*
1500
5000
5000
11, LOO
.rict
es Only
Enclos.
Sq. Ft.
1500
1500
Poilfr^
& Pipes
X
X
X
X
X
X
X
X
X
X
Total
Affected
Sq. Ft.
1500
1500
5000
5000
13,000
226
Total
Students
644
1143
715
1044
3546
31,650
POTENTIAL
Encap.
Sq. Ft.
Enclos.
Sq. Ft.
Total
Affected
Sq. Ft.
-------
School District:
10
Borough: Bronx
School
P-7
P-8
P-9/115 Ax
P-24
P-26
P-32
P-33
J-45
P-46
P-56
P-59
P-79
P/J-80
P-81
P-85
P-86
P-91
P-94
P-95
J-115
J-118
P-122
I-L37
J-141
J-143
P-205A
P-205B
Actual
Total
Total Stud*
ACTUAL
Removal
Sq. Ft.
nts in Dis
Encap.
Sq. Ft.
5000
7850
5000
5000
22,850
rict
•
Enclos.
Sq. Ft.
13250
13,250
Boilers
& Pipes
X
X
X
X
X
X
227
Total
Affected
Sq. Ft.
5000
21100
5000
5000
36,100
r
Total
Students
770
1297
1430
1055
4552
27979
POTENTIAL
Encap.
Sq. Ft.
Enclos.
Sq. Ft.
Total
Affected
Sq. Ft.
-------
School District: 11
Borough: Bronx
School
P-15 (Close
P-16
P-19
P-21
P-41
P-68
P-76
P-78
P-83
P-87
P-89
P-96
P-97
P-103
P-105
P-106
P-108
P-lll
P-112
J-113
P-121
J-127
J-135
J-142
1-144
P-153
P-160
P-175
P-178
P-180
1-181
Actual
Total
Total Stude
ACTUAL
BgiPval
Sq. Ft.
d)
its in Dis
Encap.
Sq. Ft.
1500
700
2200
rict
Enclos.
Sq. Ft.
7000
7000
Boiler?
& Pipes
X
X
X
X
X
Total
Affected
Sq. Ft.
1500
7700
9,200
228
Total
Students
616
1039
1655
22,697
POTENTIAL
Encap.
Sq. Ft.
Enclos.
Sq. Ft.
Total
Affected
Sq. Ft.
-------
School District: 12
Borough: Bronx
School
P-6
P-44
P-47
P-50
P-57
P-61
P-6 6
P-67
P-77
1-84
P-92
J-98
P-99
P-102
1-116
P-129/234
P-150
1-158
1-167
1-193
P-198
P-134
J-136
Total Stuc
* No Scho<
ACTUAL
Rsnoval
Sq. Ft.
ents in Di;
1 Affected
Encap.
Sq. Ft
trict
•
Enclos.
Sq. Ft.
Boilers
& Pipes
22
Total
Affected
Sq. Ft.
9
Total
Students
16,693
POTENTIAL
Bicap.
Sq. Ft.
Enclos.
Sq. Ft.
Total
Affected
Sq. Ft.
-------
School District: 13
Borough: Brooklyn
School
P-3
P-8
P-9
P-ll
P-20
P-44
P-46
P-54
P-56
P-67
P-85
P-93
P-93Annex
1-117
P-133
P-256
1-258
J-265
P-270
J-282
P-287
I/J-294
P-305
P-307
Actual
Total
Students PC
Total Stude
ACTUAL
Removal
Sq. Ft.
tentially
its in Dis
Encap.
Sq. Ft.
f fee ted
rict
Enclos.
Sq. Ft.
1500
2700'
700
4700
4000
13,600
Boilers
& Pipes
X
X
2;
Total
Affected
Sq. Ft.
1500
2700
700
4
4700
4000
13,600
30
Total
Students
1368
892
746
1126
1077
1206
5338
1077
18707
POTENTIAL
Encao.
Sq. Ft.
6111
6100
12,211
Enclos.
Sq. Ft.
700
10,400
11,100
Total
Affected
Sq. Ft.
6811
16,500
23,311
-------
School District: 14
Borough:
Brooklyn
School
P-16
P-17
P-18
P-19
P-19Annex
P-23
1-33
P-34
1-49
J-50
P-59
1-71
P-84
P-110
P-120
P-122
J-126
P-132
P-147
P-157
P-168
P-196
P-250
P-257
P-297
1-318
Actual
Total
Total Stud
ACTUAL
RgTPval
Sq. Ft.
nts in Dis
Encap.
Sq. Ft.
3300
5000
8300
trict
Enclos.
Sq. Ft.
8650
1500
10,150
Boilers
& Pipes
X
X
X
X
X
23
•total
Affected
Sq. Ft.
11,950
6500
18,450
1
Total
Students
830
725
1555
20,350
POTENTIAL
Encap.
Sq. Ft.
Enclos.
Sq. Ft.
•total
Affected
Sq. Ft.
-------
School District: 15
Borough:
Brooklyn
School
P-l
P-10
P-15
P-27
P-29
P-32
P-38
P-39
P-51
P-58
J-88
P-94
P-107
P-124
P-130
P-131
J-136
J-142
J-146
P-154
P-169
P-172
P-230
P-261
J-293
P-321
P-369
Actual
Total
Total Stud
ACTUAL
Removal
Sq. Ft.
nts in Dis
Encap.
Sq. Ft.
3650
500C
8650
.rict
Enclos.
Sq. Ft.
Boilers
& Pipes
X
X
X
X
X
X
X
23
Total
Affected
Sq. Ft.
3650
5000
8650
2
Total
Students
761
1220
1981
22,374
POTENTIAL
Encap.
Sq. Ft.
Enclos.
Sq. Ft.
Total
Affected
Sq. Ft.
-------
School District: 16
Boro ugh: Brooklyn
School
P-5
P-21
P-25
P-26
P-28
J-35
P-40
P-57
P-81
P-243
P-262
P-304
P-308
P-309
1-324
P-335
Total Stude
ACTUAL
Removal
Sq. Ft.
its in Dist
Encap.
Sq. Ft.
rict
•
Eaclos.
Sq. Ft.
Boilers
& Pipes
X
2:
Total
Affected
Sq. Ft.
33
Total
Students
12,152
POTENTIAL
Sq. Ft.
Enclos.
Sq. Ft.
Total
Affected
Sq. Ft.
-------
School District:
17
Borough:
Brooklyn
School
P-42
J-61
P-91
P-92
P-138
P-161
P-167
P-181
P-189
P-191
1-210
P-221
P-241
1-246
P-249
P-289
P-2S9Annex
P-316
1-320
1-391
P-397Annex
P-398
1-390
Actual
Total
Students Po
Total Stude
ACTUAL
Removal
Sq. Ft.
:entially A
its in Dist
Encap.
Sq. Ft.
Cfected
cict
Enclos.
Sq. Ft.
1500
6000
7500
Boilers
& Pipes
X
X
22
Total
Affected
Sq. Ft.
1500
6000
7500
4
Total
Students
N/A
1692
1690
2080
3772
1690
25990
POTENTIAL
Encao.
Sq. Ft.
Enclos.
Sq. Ft.
4700
4700
9400
Total
Affected
Sq. Ft.
4700
4700
9400
-------
School District: is
Borough: Brooklyn
School
J-68
P-114
P-115
P-135
P-208
P-211
P-219
J-232
P-233
P-235
P-242
P-244
J-252
J-252 Anx
P-268
P-272
P-276
P-279
P-285
Actual
Total
Total Stud
ACTUAL
Reserved
Sq. Ft.
wits in Dis
Encap.
Sq. Ft.
5000
5000
trict
-
End os.
Sq. Ft.
700
4000
4700
Boilers
& Pipes
X
X
2
Total
Affected
Sq. Ft.
700
9000
9700
35
Total
Students
N/A
993
993
17204
POTENTIAL
Encap.
Sq. Ft.
Enclos.
Sq. Ft.
Total
Affected
Sq. Ft.
-------
School District:
19
Borough: Brooklyn
School
P-13
P-63
P-65
P-72
P-76
P-108
P-149
P-158
P-158Anx.
P-159
J-166
P-I-171
P-174
P-190
P-202
P-213
P-214
P-218
P-224
P-260
P-273
1-292
1-302
P-306
P-328
P-345
P-346
Actual
Total
Students Po
Total Stude
ACTUAL
BsoDval
Sq. Ft.
235
235
:entially
its in Dis
Encap.
Sq. Ft.
ffected
rict
Enclos.
Sq. Ft.
1500
1500
Boilers
& Pipes
X
X
X
X
23
Total
Affected
Sq. Ft.
1785
1785
6
Total
Students
626
995
1355
2976
LI, 621
24700
POTENTIAL
Encao.
Sq. Ft.
2200
7200
5000
14,400
Enclos.
Sq. Ft.
1500
5700
6400
4000
17,600
Total
Affected
Sq. Ft.
3700
12,900
6400
9000
32,000
-------
School District: 20
Borough: Brooklyn
School
P-48
J-62
P-102
P-104
P105
P-112
P-118
P-127
P-140
P-160
P-163
P-164
P-170
P-176
P-179
P-180
P-185
P-186
P-192
P-200
J-201
P-204
P-205
J-220
1-223
1-227
P-229
P-247
J-259
Students I
Total Stuc
ACTUAL
RenDvsl
Sq. Ft.
otentially
ents in Di;
Encap.
Sq. Ft.
Affecte<
trict
Enclos.
Sq. Ft.
Boilers
& Pipes
23'
Total
Affected
Sq. Ft.
7
Total
Students
1775
1055
670
1369
1178
6047
24,156
POTENTIAL
Encap.
Sq. Ft.
5000
5000
5000
15,000
Enclos.
Sq. Ft.
7200
1500
8700
Total
Affected
Sq. Ft.
7200
5000
5000
5000
1500
23,700
-------
School District: 21
Borough: Brooklyn
School
J-43
P-90
P-199
J-281
P-288
1-303
P-329
P-95
1-96
P-97
P-99
P-100
P-101
P-121
P-128
P-153
P-177
P-188
P-209
P-212
P-215
P-216
P-225
P-226
P-228
P-238
J-239
P-248
P-253
Actual
Total
Students P
Total Stud
ACTUAL
Removal
Sq. Ft.
tentially
nts in Dis
Encap.
Sq. Ft.
5000
i
5000
Effected
:rict
Snclos.
Sq. 'Ft.
Boilers
& Pipes
X
Total
Affected
Sq. Ft.
5000
5000
238
ii
Total
Students
1012
495
1560
790
614
1152
874
790
5707
22,791
POTENTIAL
Encap.
Sq. Ft.
5000
5000
5000
5150
20150
Enclos.
Sq. Ft.
1500
3700
2000
7200
Total
Affected
Sq. Ft.
6500
3700
5000
5000
5150
2000
27350
-------
School District: 22
Borough: Brooklyn
School
P-14
P-52
1-78
P-89
P-119
P-134
P-139
P-152
P-193
P-194
P-195
P-197
P-198
P-203
P-206
P-207
P-217
P-222
J-234
P-236
J-240
P-251
P-254
P-255
P-269
P-269(Anx)
P-277
J-278
P-312
Actual
Total
Students P
Total Stud
ACTUAL
Raioval
Sq. Ft.
>tentially
ents in Dis
Encap.
Sq. Ft.
1500
1500
Affecte<
trict
Enclos.
Sq. Ft.
2200
2200
Boilers
& Pipes
X
X
X
Total
Affected
Sq. Ft.
1500
2200
3700
239
Total
Students
1075
730
1462
578
401
1007
925
944
1181
764
764
798
1192
2537
9284
25,140
POTENTIAL
Encao.
Sq. Ft.
150
700
1500
1500
5000
5000
5000
5000
6900
7200
400
2200
40,550
Enclos.
Sq. Ft.
3000
3000
4300
1500
8300
6800
6500
4000
37,400
Total
Affected
Sq. Ft.
150
3700
4500
5800
5000
5000
5000
6500
15,200
14,000
6900
6200
77,950
-------
School District: 23
Borough: Brooklyn
School
P-41
1-55
P-73
P-137
P-150
P-155
P-156
P-165
P-175
P-178
P-183
P-184
1-263
1-271
1-275
P-284
P-298
P-327
P-332
P-396
Actual
Total
Total Stud
ACTUAL
Removal
Sq. Ft.
snts in Di
Encap.
Sq. Ft.
trict
Enclos.
Sq. Ft.
150
150
Boilers
& Pipes
X
24
Total
Affected
Sq. Ft.
150
150
0
Total
Students
1741
1741
14,062
POTENTIAL
Encap.
Sq. Ft.
Enclos.
Sq. Ft.
Total
Affected
Sq. Ft.
-------
School District: 24
Borough:
Queens
School
P-12
P-13
P-14
P-19
P-49
J-61
P-68
P-71
J-73
P-75
P-81
P-87
P-88
P-89
P-91
J-93
P-102
P-113
J-119
J-125
P-128
P-143
P-153
P-199
P-229
J-77
Actual
Total
Total Stude
ACTUAL
Renoval
Sq. Ft.
ts in Dist
Encao.
Sq. Ft
1450
5000
150
5000
5000
7200
23,800
rict
Enclos.
Sq. Ft.
2200
700
700
8300
1,900
Boilers
& Pipes
X
24
Total
Affected
Sq. Ft.
1450
7200
850
5000
700
5000
15,500
35,700
1
Total
Students
1079
2051
1136
945
1777
583
739
8,310
24,470
POTENTIAL
Encap.
Sq. Ft.
Enclos
Sq. Ft.
Total
Affected
Sq. Ft.
-------
School District: 25
Borough: Queens
School
P-20
P-22
P-24
P-29
P-32
P-79
P-107
P-120
P-129
P-154
P-163
P-164
P-165
P-168
P-169
P-184
J-185
J-189
P-193
J-194
P-200
P-201
P-209
P-214
J-218
P-219
1-237
P-21
Actual
Total
Tbtal Stude
ACTUAL
PesDval
Sq. Ft.
ts in Dist
Uncap.
Sq. Ft.
5000
5000
3300
13 , 300
rict
Enclos.
Sq. Ft.
3000
3500
2200
2200
3000
13,900
Boiler**
& Pipes
X
X
X
X
24
Total
Affected
Sq. Ft.
8000
5000
3500
2200
2200
6300
27,200
2
Total
Students
1061
841
837
675
1177
583
5,174
22,665
POTENTIAL
Sq. Ft.
Enclos.
Sq. Ft.
Total
Affected
Sq. Ft.
-------
School District: 26
Borough: Queens
School
P-18
P-26
P-31
P-41
P-46
J-67
1-74
P-94
P-98
P-115
P-130
P-133
P-158
P-162
J-172
P-173
P-177
P-178
P-179
P-186
P-188
P-191
P-203
P-205
P-213
J-216
P-221
187
P-159
Actual
Total
Students Po
Total Stude
ACTUAL
Removal
Sq. Ft.
:entially R
its in Dist
Encap.
Sq. Ft.
5000
12,900
5000
4000
26,900
ffected
rict
Enclos.
Sq. Ft.
2900
18,200
2000
500
23,600
b
Boilers
& Pipes
X
X
X
243
Total
Affected
Sq. Ft.
2900
5000
31,100
7000
4000
500
50,500
Total
Students
702
245
801
426
401
332
316
404
1040
404
2907
2164
L3,962
POTENTIAL
Encao.
Sq. Ft.
6500
6500
6500
19 , 500
Enclos.
Sq. Ft.
3800
3000
5300
4500
16,600
Total
Affected
Sq. Ft.
10,300
3000
11,800
11,000
36,100
-------
School District:
27
Borough: Queens
School
P-42
P-45
P-47
P-51
1-53
P-60
P-62
P-63
P-64
P-66
P-90
P-96
P-97
P-100
P-104
P-105
P-106
P-108
P-114
P-123
P-124
P-146
P-155
J-180
P-183
P-197
J-198
1-202
P-207
1-210
P-215
P-223
P-225
J-226
P-232
Actual *\
Total Stuc
ACTUAL
RenDval
Sq. Ft.
Jtal
ents in Di
Encap.
Sq. Ft.
5000
5000
trict
Tfrclos.
Sq. Ft.
150
700
1500
2350
B°iJLers
& Pipes
X
X
X
Total
Affected
Sq. Ft.
5000
150
700
1500
7350
Total
« ^^ _J ^-^_^^-_
acuoencs
651
959
1778
924
4312
30,124
POTENTIAL
Encap.
Sq. Ft.
Enclos.
Sq. Ft.
Total
Affected
Sq. Ft.
244
-------
School District: 28
Borough: Queens
•
School
1-8
P-30
P-40
P-48
P-50
P-54
P-55
1-72
P-80
P-86
P-99
P-101
P-117
P-121
P-139
P-140
1-142
P-144
J-157
P-160
P-174
J-190
P-196
P-206
J-217
P-220
P-82
Actual
Total
Total Stude
ACTUAL
Henoval
Sq. Ft.
ts in Dist
Encap.
Sq. Ft.
5550
5000
5000
5000
20,550
rict
Enclos.
Sq. Ft.
2100
12,050
3500
17,650
Boilers
& Pipes
X
X
2'
Total
Affected
Sq. Ft.
2100
17,600
5000
5000
8500
38,200
45
Total
Students
473
1241
564
1153
1462
4,893
1,332
POTENTIAL
Encap.
Sq. Ft.
Enclos.
Sq. Ft.
Total
Affected
Sq. Ft.
-------
School District:
29
Borough: Queens
School
P-15
P-33
P-34
P-35
P-36
P-37
P-38
P-52
J-59
P-95
J-109
P-116
P-118
P-132
P-134
P-135
P-136
P-138
P-147
P-156
P-176
P-181
1-192
1-195
1-231
J-231
1-238
P-251
Actual
Total
Total Stude
ACTUAL
Removal
Sq. Ft.
its in Dis
Encap.
So. Ft.
150
700
5000
5850
rict
i
Enclos.
Sq. Ft.
500
800
1300
Rni 1 «»T-« |
& Pipes 1
Total
Affected
Sq. Ft.
X
X
X
X
X
•1
150
700
5500
800
7,150
A r
Total
Students
378
1591
952
527
3448
25,079
POTENTIAL
Encap.
Sq. Ft.
Enclos.
Sq. Ft.
Total
Affected
Sq. Ft.
246
-------
School District: 30
Borough: Queens
School
P-2
J-10
P-ll
P-17
P-69
P-70
P-76
P-84
P-85
P-92
P-lll
P-112
P-122
1-126
P-127
J-141
J-145
P-148
P-149
P-150
P-151
P-152
P-166
P-171
J-204
1-227
Actual
Total
Total Stude
ACTUAL
Eenoval
Sq. Ft.
•
ts in Dist
Encap.
Sq. Pt.
300
5000
5000
5000
5000
5000
25,300
rict
Enclos.
Sq. Pt.
2000
4000
1500
7,500
Boilers
& Pipes
X
X
X
X
X
X
total
Affected
Sq. Pt.
2000
4000
300
1500
5000
5000
5000
5000
5000
32,800
Total
Students
1734
692
597
1315
715
861
993
1041
711
8,659
22,389
POTENTIAL
Encap.
Sq. Ft.
Enclos.
Sq. Ft.
Total
Affected
Sq. Pt.
247
-------
School District: 31
Page 1 of 2
Borough: Staten Island (Richmond)
School
P-I
J-2
P-3
P-4
P-5
1-7
P-8
P-ll
P-13
P-14
P-15
P-16
P-19
P-20
P-21
1-22
P-23
1-24
P-25
P-26
1-27
P-28
P-29
P-30
P-31
P-32
1-34
P-35
P-36(old)
P-36 (new)
P-38
P-39
P-40
P-41
P-42
P-44
P-45
ACTUAL
Rpiinval
Sq. Ft.
Encap.
Sq. Ft.
700
5700
3000
2000
5000
Enclos.
Sq. Ft.
500
1500
Boilers
& Pipes
X
X
X
X
X
X
X
X
X
X
X
X
Total
Affected
Sq. Ft.
1200
7200
3000
2000
5000
Total
Students
1703
1085
674
1126
658
POTENTIAL
Encap.
Sq. Ft.
Enclos.
Sq. Ft.
Total
Affected
Sq. Ft.
243
-------
Page 2 of 2
School District: 31
Borough: staten Island
School
P-46
P-48
J-49
P-50
J-51
P-52
P-53
P-54
P-55
P-57
P-60
1-61
P-69
1-72
P-18
Actual
Total
Total StucU
ACTUAL
Rpurrval
Sq. Ft.
nts in Dis
Encap.
Sq. Ft.
40
16,440
rict
Enclos.
Sq. Ft.
700
300
2,000
Boilers
& Pipes
X
24
Total
Affected
Sq. Ft.
740
300
19,440
Q
Total
Students
314
845
6,405
36,217
POTENTIAL
Encap.
Sq. Ft.
Enclos.
Sq. Ft.
Total
Affected
Sq. Ft.
I
|
I
-------
School District: 32
Borough:
Brooklyn
School
P-45
P-75
P-86
P-106
1-111
P-116
P-123
P-145
P-151
J-162
P-274
P-274(Anx)
1-291
J-296
P-299
P-377
1-383
P-384
* No Schoo
ACTUAL
RenDVal
Sq. Ft.
3 Affected
Encap.
Sq. Ft.
Enclos.
Sq. Ft.
Boilers
& Pipes
7=;
Total
Affected
Sq. Ft.
n
Total
Students
POTENTIAL
Encap.
Sq. Ft.
Enclos.
Sq. Ft.
Total
Affected
Sq. Ft.
-------
School District: 78
Borough: Bronx
School
Bronx HS
Sci.
Dewitt Cli
Grace Dodg
J.F. Kenne
H.H. Lehmar1
James Monrc
Morris
Morris (An:
T. Rooseve]
A.E. Smith
S.Bronx HS
A.Stevensor
H . S . Truman
Walton HS
C. Columbus
Evander
Childes
Jane Addams
S . Gompers
Wm. Taft
Roberta
Clements
Satellite
Academy
Actual
Total
Total Stude
ACTUAL
Removal
Sq. Ft.
iton
iy
e
)
t
its in Dist
Encap.
Sq. Ft.
5150
400
5000
1500
12,050
rict
Enclos.
Sq. Ft.
700
600
1300
Bn-Q
-------
School District:
78
Borough: Brooklyn
School
Bay Ridge
Boys & Gir]
Boys HS (oJ
Brookl-yn
Tech
Bushwick
Canarsie
J . Dewey
E. NY Voc.
Erasmus Ha]
W Grady
John Jay
T. Jefferso
Lafayette
F. K. Lane
A. Lincoln
J Madison
E.R. Murrow
Prospect
Heights
FD Rooseve;
Sheepshead
Bay
S. Shore
S.J. Tilden
New Uretch
G. Westingh
Voc- Tech.
ACTUAL
BenDval
Sq. Ft.
)
a
•
iuse
Encap.
Sq. Ft.
3000
4000
5000
1500
5000
150
Enclos.
Sq. Ft.
2000
1650
2350
4000
Boilers
& Pipes
X
X
X
X
X
X
X
X
Total
Affected
Sq. Ft.
3000
4000
2000
5000
1650
2350
4000
1500
5000
150
252
Total
Students
2952
3422
N/A
4077
N/A
3928
3495
3275
3117
4586
2952
N/A
POTENTIAL
Encap.
Sq. Ft.
4500
400
Enclos.
Sq. Ft.
3000
4200
Total
Affected
Sq. Ft.
4500
3400
4200
-------
School District: 78
Borough: Brooklyn
School
Prod. Ctr.
E. Whitney
G. Wingate
Bay Ridge
Annex
Ft. Hamiltc
Midwood
Alex. Hand:
riara Barto
Eastern
Dist.
Sirls HS
(Old)
Sara Hale
City As
School
Ebbets
Field Schoo
Pacific HS
PM HS
W. Murrow
Actual
Total
Potentially
Total Studei
ACTUAL
Beooval
Sq. Ft.
n
ton
n
Affected S
ts in Dist
Encap.
Sq. Ft.
1550
5000
25,200
udents
ict
Knclos.
Sq. Ft.
24000
6200
40,200
Boilers
& Pipes
X
25
Total
Affected
Sq. Ft.
25,550
11,200
65,400
3
Total
Students
N/A
3459
27,691
3,45
7,572
87,371
POTENTIAL
Sq. Ft.
700
5,600
Enclos.
Sq. Ft.
6000
13,200
Total
Affected
Sq. Ft.
6700
18,800
-------
School District: 78
Borough:
Manhattan
School
HS Art &
Design
L.D. Brand*
B. Franklin
Chas. Hughe
ML King
J. Richman
Seward Park
Stuyvesant
G. Washingt
M.D. Bacon
Washington
Irving
Bergtraum
Chelsea
LaGuardia
School of
Perf. Arts
Maritime
Trades
Voc . Tech .
Brandeis (A
Bacon (Anx)
Norman Thorn
Park East
Seward Park
(Anx)
Actual
Total
Total Stude
ACTUAL
Removal
Sq. Ft.
LS
5
n
IX)
IS
ts in Dis
Encap.
Sq. Ft.
450
2200
2650
rict
Enclos.
Sq. Ft.
3000
250
4700
700
8650
Boilers
& Pipes
X
X
X-
X
X
Total
Affected
Sq. Ft.
450
3000
250
6900
700
11,300
254
Total
Students
4219
3543
3298
2397
2503
15,960
39,502
POTENTIAL
Encap.
Sq. Ft.
Enclos.
Sq. Ft.
Total
Affected
Sq. Ft.
-------
School District:
78
Borough: Queens
School
J . Adams
Bayside
Beach Chanr
J . Browne
B . Cardozo
B. Clevelar
T. Edison
Far Rockawa
Flushing
Forest Hill
Hillcrest
A. Jackson
Jamaica
Jamaica (old
F. Lewis
Long Island
City
Newtown
Richmond Hi
Springfield
Gardens
M. VanBuren
A. Martin
Queens Voc.
Richmond ;.
Hill (Anex)
WC Bryant
Actual To
Students Po
Total Stude
ACTUAL
Removal
Sq. Ft.
el
d
y
5
LI
:al
.entially A
Encap.
Sq. Ft.
150
5000
1500
6650
ffected
its in District
Enclos.
Sq. Ft.
2650
2650
Boilers
& Pipes
X
Total
Affected
Sq. Ft.
2800
5000
1500
9300
Total
Students
3718
3849
N/A
N/A
2265
2741
3297
4680
3425
2035
3844
29,854
24,380
65587
POTENTIAL
Encap.
Sq. Ft.
5000
5000
1500
11,500
Enclos.
Sq. Ft.
850
10850
700
4000
6100
1400
23,900
Total
Affected
Sq. Ft.
5000
5000
850
12350
700
4000
6100
1400
35,400
255
-------
School District: 78
Borough: Staten Island (Richmond)
School
Curtis
New Dorp
Port.
Richmond
Tottenvill*
S. Wagner
McKee Voc.
Actual
Total
Students P<
Total Stud«
ACTUAL
BtfU'jyaJL
Sq. Ft.
tentially
nts in Dis
Encap.
Sq. Ft.
5000
5000
Effected
:rict
Find OS.
Sq. Ft.
^OilT5
& Pipes
X
25(
Total
Affected
Sq. Ft.
5000
5000
Total
Students
2801
2982
3032
N/A
8815
16,065
POTENTIAL
Encap.
Sq. Ft.
5000
1500
2100
8600
Enclos.
Sq. Ft.
Total
Affected
Sq. Ft.
5000
1500
2100
8600
-------
APPENDIX D
Data Collection Instruments
257
-------
ARTHUR YOUNG X COMPANY
IO25 CONNECTICUT AVENUE N W
WASHINGTON. D. C 2OO36
LETTER SENT TO SUPERINTENDENTS OF SCHOOL DISTRICTS
THAT HAD RESPONDED TO THE EPA VOLUNTARY SURVEY
The Environmental Protection Agency (EPA) has identified low-
level non-industrial exposure to friable asbestos as potentially
hazardous. Based on a preliminary survey of States in 1973, EPA feels
that the potential for this type of exposure may be widespread in
schools. In response to a law suit by the Environmental Defense Fund
in May 1979, EPA has decided to develop a regulation that would require
primary and secondary schools to take certain measures to control
asbestos exposure in their buildings. Arthur Young & Company has been
contracted by EPA to develop estimates of the number of students and
staff potentially exposed to friable asbestos and estimates of cost
and other negative economic impacts of protective measures against
asbestos in primary and secondary schools.
Eased on a review of available data sources, including the results
of a recent EPA survey to which you responded, we have determined that
direct contact with the school districts is necessary to meet the data
requirements of this project. We have selected a sample of school
districts from which to obtain the required data. This sample was
randomly chosen from certain classifications of school districts that
responded to the above mentioned EPA survey.
In conducting this study we feel that its success, and the
reliability of its results are strongly dependent upon information
provided by this sample of school districts. Your school district is
one of those selected in this sample. We are, therefore, requesting
your valuable assistance in providing accurate estimates of the
negative economic impacts of this regulation as identified below.
In a separate letter addressed to the building maintenance chief
in your district (see Attachment), we have requested that he assess
the friable asbestos exposure potential in buildings in your school
district. He is also requested to provide figures on the number (or
percentage) of buildings requiring certain types of corrective actions.
258
-------
ARTHUR YOUNG & COMPANY
Page Two
We would appreciate it if you could coordinate the efforts of
the maintenance chief with yours, to provide us with an indication of
potential negative impacts of performing the corrective actions within
your district.
Specifically, it would be helpful if you could use the results
of the maintenance chief's assessment to determine the magnitude of
potential negative impacts in your district's schools. Information on
the following negative impacts in your school district is desired:
Number of schools or parts of schools that may temporarily
close and the number of schools day that could be lost as
a result of any required asbestos correction activity.
Number of schools or parts of schools that may permanently
close, the number of students displaced, and the expected
change in average class size and student/teacher ratio at
your other schools due to these possible closings.
The number of jobs that could be lost if the asbestos problem
is considered severe enough by your maintenance chief's
assessment to warrant either a long-tarm temporary school
closing or permanent school closing.
Any additional indirect costs (ie. over and above the direct
cost of asbestos control).
We would appreciate receiving your responses by December 19, 1979.
We are confident that by using estimates developed by school district
officials, such as yourselves, the validity and eventual usefulness of
the study results will be increased. Also, it would be advantageous
to the school districts to provide early notice to SPA of any areas
where severe impacts or dislocations are possible. The agency's
regulatory strategy could be affected by such early, pre-proposal
findings. We will be contacting you and your maintenance chief in the
next few weeks to answer any questions you may have.
We would greatly appreciate any help you are able to provide us
on this study and look forward to working with you towards its success.
If you have any questions or suggestions, please do not hesitate to
call Mr. Philip Mathias at (202) 828-7000. In his absence you can call
Steve Schoepke or Susan Wright at the same telephone number.
Very truly yours,
ARTHUR YOUKG & COMPANY
3y:
Dimitri A. Plionis
Princioal
259
-------
ARTHUR YOUNG X COMPANY
IO25 CONNECTICUT AVENUE. N. W.
WASHINGTON. O. C. 3OO36
LETTER SENT TO THE MAINTENANCE PERSONNEL OF
SCHOOL DISTRICTS THAT HAD RESPONDED
TO THE EPA VOLUNTARY SURVEY
The Environmental Protection Agency (EPA) has identified low-
level non-industrial exposure to friable asbestos as potentially
hazardous. Based on a preliminary survey of States in 1978, EPA feels
that the potential for this type of exposure may be widespread in
schools. In response to a law suit by the Evironmental Defense Fund
in May 1979, EPA has decided to develop a regulation that would require
primary and secondary schools to take certain measures to control
asbestos exposure in their buildings. Arthur Young & Company has been
contracted by EPA to develop estimates of the number of students and
staff potentially exposed to friable asbestos and estimates of cost
and other negative economic impacts of protective measures against
asbestos in primary and secondary schools.
In its proposed regulation, EPA is considering the use of a
procedure called the "Asbestos Exposure Assessment Algorithm", a copy
of which is attached, to determine the corrective action required. The
Asbestos Exposure Assessment Algorithm is designed to provide an
indication of the extent or degree of an asbestos condition. To score
an area, it is necessary to judge and score eight factors: 1) the
condition of the asbestos material; 2) the presence of water damage;
3) the percentage of exposed surface area; 4) the accessibility of
the asbestos area to students; 5) the student or other activity levels
and movement; 6) the level of air plenum or direct air stream on the
asbestos; 7) the friability of the asbestos and; 8) the asbestos
content.
Based on a review of available data sources, we have determined
that direct contact with the school districts is necessary to meet
the data requirements of this project. We have selected a sample of
school districts from which to obtain the required data. This sanple
was randomly chosen from certain classifications of school districts.
260
-------
ARTHUR YOUNG s COMPANY
Page Two
Your school district has been selected in cur sample. We are,
therefore, requesting you to kindly assist us in our efforts on this
important project by applying the "Asbestos Exposure Assessment
Algorithm" to your school buildings.
After you have completed the assessment of buildings in your
district, you can obtain, based on the attached documentation, an
indication of either: the percentage of buildings in the district
requiring corrective action, by type of action; or the number of
buildings requiring each type of corrective action. Your participation
in this study would consist of a numerical presentation of the results
of that assessment. For example, after reviewing conditions in your
school buildings, you may have found that seventy-five out of 100
schools require "inspection", ten require "encapulation", five require
"removal," and twenty require "deferred action" (see attachment for
details). We.would need these numbers or percentages such as: 75%-
inspection, 10%-encapulation, 5%-removal, and 20%-deferred action.
We sincerely feel that it will be to your school district's
advantage to review asbestos conditions in your school buildings at
this time. First it will allow you to assess the magnitude of the
potential hazard, if any, for your district. Second, you will be able
to assess your situation using a specific procedure that is currently
recommended by EPA, and determine in advance any corrective measures
that may be ne'cessary to comply with a future EPA asbestos regulation.
The result of the assessment of asbestos exposure in your district
must be received no later than December 21, 1979. We recognize that
this schedule is quite restrictive; but because of EPA's intended
regulation schedule, we must begin the analysis phase of the study at
that time. We also recognize, though, the importance of your particular
school district's input to the final results of the study. Because of
this, our staff will be in contact with you in about one week to assist
with any questions you may have.
We appreciate any help you are able to give us on this project
and look forward to your participation in it. If there are any
questions or suggestions relevant to this matter, please do not
hesitate to call Philip Mathias at (202) 828-7000. In his
261
-------
ARTHUR YOUNG & COMPANY
Page Three
absence, you can call Steve Schoepke or Susan Wright at the same
telephone number.
Very truly yours,
ARTHUR YOUNG & COMPANY
By:
Diinitri A. Plionis
Principal
262
-------
ARTHUR YOUNG & COMPANY
IO35 CONNECTICUT AVENUE N w
WASHINGTON O C 2OO36
LETTER SENT TO PuPERINTENDENTS OF SCHOOL DISTRICTS THAT
HAD NOT RESPONDED TO THE EPA VOLUNTARY SURVEY
The Environmental Protection Agency (EPA) has identified low-
level non-industrial exposure to friable asbestos as potentially
hazardous. Based on a preliminary survey of States in 1978, EPA feels
that the potential for this type of exposure may be widespread in
schools. In response to a law suit by the Environmental Defense Fund
in .May 1979, EPA has decided to develop a regulation that would require
primary and secondary schools to take certain measures to control
asbestos exposure in their buildings. Arthur Young & Company has been
contracted by EPA to develop estimates of the number of students and
staff potentially exposed to friable asbestos and estimates of cost
and other negative economic impacts of protective measures against
asbestos in primary and secondary schools.
Based on a review of available data sources, we have determined
that direct contact with the school districts is necessary to meet
the data requirements o.f this project. We have selected a sample of
school districts from which to obtain the required data. This sample
was randomly chosen from certain classifications of school districts.
In conducting this study we feel that its success, and the
reliability of its results are strongly dependent upon information
provided by this sample of school districts. Your school district is
one of those selected in this sample. We are, therefore, requesting
your valuable assistance in providing accurate estimates of the
negative economic impacts of this regulation as identified below.
In
in your
the friable
a separate letter addressed to the building maintenance chief
district (see Attachment), we have requested that he assess
asbestos exposure potential in buildings in your school
district. He is also requested to provide figures on the number (or
percentage) of buildings requiring certain types of corrective actions.
263
-------
ARTHUR YOUNG & COMPANY
Page Two
We would appreciate it if you could coordinate the efforts of
the maintenance chief with yours, to provide us with an indication of
potential negative impacts of performing the corrective actions within
your district.
Specifically, it would be helpful if you could use the results
of the maintenance chief's assessment to determine the magnitude of
potential negative impacts in your district's schools. Information on
the following negative impacts in your school district is desired:
Number of schools or parts of schools that may temporarily
close and the number of schools day that could be lost as
a result of any required asbestos correction activity.
Number of schools or parts of schools that may permanently
close, the number of students displaced, and the expected
change in average class size and student/teacher ratio at
your other schools due to these possible closings.
The number of jobs that could be lost if the asbestos problem
is considered severe enough by your maintenance chiefs
assessment to warrant either a long-terra temporary school
closing or permanent school closing.
Any additional indirect costs (ie. over and above the direct
cost of asbestos control).
We would appreciate receiving your responses by December 21, 1979.
We are confident that by using estimates developed by school district
officials, such as yourselves, the validity and eventual usefulness of
the study results will be increased. Also, it would be advantageous
to the school districts to provide early notice to EPA of any areas
where severe impacts or dislocations are possible. The agency's
regulatory strategy could be affected by such early, pre-proposal
findings. We will be contacting you and your maintenance chief in the
next few weeks to answer any questions you may have.
We would greatly appreciate any help you are able to provide us
on this study and look forward to working with you towards its success.
If you have any questions or suggestions, please do not hesitate to
call Mr. Philip Mathias at (202) 828-7000. In his absence you can call
Steve Schoepke or Susan Wright at the same telephone number.
Very truly yours,
ARTHUR YOUIIG * COMPANY
By:
Dimitri A. Plionis
264 Principal
-------
ARTHUR YOUNG & COMPANY
IO25 CONNECTICUT AVENUE N W
WASHINGTON. D C 3OO36
LETTER SENT TO THE MAINTENANCE PERSONNEL OF
SCHOOL DISTRICTS THAT HAD NOT RESPONDED
TO THE EPA VOLUNTARY SURVEY
The Environmental Protection Agency (SPA) has identified low-
level non-industrial exposure to friable asbestos as potentially
hazardous. Based on a preliminary survey of States in 1978, EPA feels
that the potential for this type of exposure may be widespread in
schools. In response to a law suit by the Evironnental Defense Fund
in May 1979, EPA has decided to develop a regulation that would require
primary and secondary schools to take certain measures to control
asbestos exposure in their buildings. Arthur Young & Company has been
contracted by EPA to develop estimates of the number of students and
staff potentially exposed to friable asbestos and estimates of cost
and other negative economic impacts of protective measures against
asbestos in primary and recovery schools.
In its proposed regulation, EPA is considering the use of a
procedure called the "Asbestos Exposure Assessment Algorithm", a copy
of which is attached, to determine the corrective action required. The
Asbestos Exposure Assessment Algorithm is designed to provide an
indication of the extent or degree of an asbestos condition. To score
an area, it is necessary to judge and score eight factors: 1) the
condition of the asbestos material; 2) the presence of water damage;
3) the percentage of exposed surface area; 4) the accessibility o£
the asbestos are'a to students; 5) the student or other activity levels
and movement; 6) the level of air plenum or direct air stream on the
asbestos; 7) the friability of the asbestos and; 8) the asbestos
content.
Based on a review of available data sources, including the results
of a recent EPA survey, to which you have responded, we have determined
that direct contact with the school districts is necessary to meet
the data requirements of this project. We have selected a sample of
school districts from which to obtain the required data. This sample
was randomly chosen from certain classifications of school districts
that responded to the above mentioned EPA survey.
265
-------
ARTHUR YOUNG s COMPANY
Page 2
November 21, 1979
Your school district has been selected in our sample. We are,
•ihersfore, requesting you to kindly assist us in our efforts on this
important project by applying the "Asbestos Exposure Assessment
Algorithm" to your school buildings.
After you have completed the assessment of buildings in your
district, you can obtain, based on the attached documentation, an
indication of either: the percentage of buildings in the district
requiring corrective action, by type of action; or the number of
buildings requiring each type of corrective action. Your participation
in this study would consist of a numerical presentation of the results
of that assessment. For example, after reviewing conditions in your
school buildings, you may have found that seventy-five out of 100
schools require "inspection", ten require "encapslation", five require
"removal," and twenty require "deferred action" (see attachment for
details). We would need these numbers or percentages such as: 75%-
inspection, 10%-encapulation, 5%-ramoval, and 20%-deferred action.
We feel that your efforts on this matter should be greatly
facilitated by your previous work on the above mentioned EPA survey.
Information you developed for your response to that survey should
provide the majority of the data required to complete the algorithm(s)
for your district. Also, we sincerely feel that it will be to your
school district's advantage to review asbestos conditions in your
school buildings at this time. First it will allow you to assess the
magnitude of the potential hazard, if any, for your district. Second,
you will be able to assess your situation using a specific procedure
that is currently recommended by EPA, and determine in advance any
corrective measures that may be necessary to comply with a future EFA
asbestos regulation.
The result of the assessment of asbestos exposure in your district
must be received no later than December 19, 1973. We recognize that
this schedule is quite restrictive; but because of EPA's intended
regulation schedule, we must begin the analysis phase of the study at
that time. We also recognize, though, the importance of your particular
school district's input to the final results of the study. Because of
this, our staff will be in contact with you in about one week to assist
with any questions you may have.
We appreciate any help you are able to give us on this project
and look forward to your participation in it. If there are any
questions or suggestions relevant to this matter, please do not
hesitate to call Philip Mathias at (202) 328-7000. In his
266
-------
ARTHUR YOUNG & COMPANY
Page 3
November 21, 1979
absence, you can call Steve Schoepke or Susan Wright at the same
telephone number.
Very truly yours,
ARTHUR 20UNG & COMPANY
By:
D. PIionis
Principal
267
-------
JltCO TracorJitco.Inc.
1776 East Jefferson Street
Rockville. Maryland 20852
Telephone 301: 881-2305
LETTERS SENT TO LABORATORIES
AND CONTRACTORS
November 1, 1979
Tracer Jitco, Inc., is under contract with the Environmental Protection
Agency to determine the economic impact of regulations to control asbestos
exposures in school buildings. As part of this cost impact study, we will
be providing the EPA with a list of laboratories and contractors who are
available to provide services relating to this asbestos problem.
In order to be included on the EPA list of contractors available to
provide services, please submit the name, address and telephone number of
a person who may be contacted along with the appropriate unit cost (per
sample, per square foot, per hour, etc.) and subcosts, if applicable, of
each of the following services that you perform:
1. Bulk sample analysis by:
a. polarized light microscopy
b. x-ray diffraction
c. electron microscopy
2. In-school air sampling
3. Air sample filter analysis by:
a. OSHA optical microscopy method
b. electron microscopy
4. Removal (EPA, OSHA approved methods)
5. Encapsulation (EPA, OSHA approved method)
6. Enclosure (EPA, OSHA approved method)
7. Disposal (EPA approved method)
8. Marking of areas containing asbestos
Please mail your reply no later than November 13. A self-addressed,
stamped envelope is enclosed for your convenience.
Sincerely,
Joseph J. Beres
Industrial Hygienist
JJB:dp
Enclosure
268
-------
Tnicor Jitco Tr^or MCO. me.
1776 East Jefferson Street
Rockville. Maryland 20852
Tetepnone30l: 881-2305
LETTER SENT TO THE MAINTENANCE PERSONNEL OF
SCHOOL DISTRICTS THAT HAD NOT RESPONDED
TO THE EPA VOLUNTARY SURVEY
October 24, 1979
Dear :
Tracer Jitco, Inc., is under contract with the Environmental Protection
Agency to assist in determining the economic impact of regulations con-
cerning the handling of asbestos in schools. Fart of this economic impact
relates to inspection, testing, removal and other activities being con-
ducted by school districts. You would be of great assistance to the
success of this program by providing as much of the following information
as possible:
1. Names and addresses of schools surveyed for asbestos.
2. Number of students in each school surveyed.
3. Square footage of each school surveyed.
4. Amount of time spent surveying at each school.
5. Hourly rate of person performing survey.
If a school or schools ha'd bulk samples analyzed by polarized light
microscopy, please provide:
6. Names, addresses, and phone numbers of laboratories providing
this service.
7. Cost of analysis per sample.
If removal, encapsulation, or enclosure of asbestos was performed,
8. Type of service and name, address, and phone number of
contractor(s) performing this service.
Please mail your reply by Monday, November 5 using the self-addressed,
stamped envelope provided for your convenience.
Sincerely,
Joseph J. Beres
Industrial Hygienist
JJB:wpc
Enclosure 269
-------
Trocor Jitco
1776 East Jefferson Street
Rockville. Maryland 20852
Telephone 301: 881-2305
LETTER SENT TO EPA REGIONAL ASBESTOS
COORDINATORS, OSHA AND NIOSH PERSONNEL
October 30, 1979
Dear :
Tracer Jitco, Inc., is under contract with EPA to determine the economic
impact of its regulations on controlling asbestos in schools. We are
accomplishing this by contacting EPA Regional Asbestos Coordinators, OSHA and
NIOSH personnel, school superintendents and contractors for information.
One of the objects of our cost impact study is to determine the regional
availability as well as the cost of the following services:
1. Bulk sample analysis
2. Air monitoring surveys
3. Air filter sample analysis
4. Removal of asbestos
5. Disposal
6. Enclosure
7. Encapsulation
If you are aware of any laboratories and contractors that provide these
services, please send us the names, addresses and phone numbers of as many as
possible. Any information you may have regarding marking costs will be of
great value.
I am enclosing a self-addressed, stamped envelope for your use. Thank you for
your cooperation.
Sincerely,
Joseph J. Beres
Industrial Hygienist
JJB: dp
Enclosure
270
-------
APPENDIX E
Draft Asbestos Exposure Assessment
Algorithm
271
-------
Only the scores indicated can be assigned to a factor. For
example, "1", "3", and "4" are not acceptable scores for Factor
I: Material Condition. The scores have been intentionally
weighted to reflect severity of the individual factors effect on
exposure potential.
The area to be evaluated should be any part of the school
where the factors remain uniform. For example, an auditorium
with both an inaccessibile ceiling surface in the stage area and
a very accessible and damaged surface in the audience area
constitutes two different areas. The scores for the two areas
may exhibit a wide variation in scale number, a different
assessment, and possibly different corrective actions.
Step 2: Exposure Number Calculation
The Exposure Number is derived from the Factor Scores by a
formula. After entering the chosen Factor Scores on lines 1
through 3 of Table II:
a. Sum factors 1 throuah 6 and enter occosite
SUM;
b. Multiply Factor 7 times factor 8, and enter
opposite PRODUCT;
c. Multiply SUM times PRODUCT.and enter opposite
EXPOSURE NUMBER.
This number represents the result of your assessment for
each area of the building. The Exposure Number must now be com-
pared to the Corrective Action Scale, which is Step 3.
Step 3: Comparison of Exposure Number to Corrective Action Scale
Table III, Corrective Action Scale, presents four types of
corrective action, a brief description of each, and a range of
Exposure Numbers for which that Corrective Action is
appropriate. Compare the Exposure Number derived in Step 2 to
the ranges in Table III to determine whether action is needed.
For example, an Exposure Number of 90 clearly indicates that the
asbestos should be removed. An Exposure Number of 10, however,
might suggest encapsulation or deferral of action. In this case
it is necessary to further analyze the situation, perhaps to con-
sider factors such as the length of time that action could be
deferred or development of a management plan which would
significantly reduce potential exposure.
Table 1: Factor Description and Scores
FACTOR ONE. CONDITION OF MATERIAL:
The condition of the asbestos materials may indicate the
possibility of fibers being released to the area(i.e.
contamination) and the potential for future fiber release. An
assessment of the condition depends upon a combination of the
272
-------
ASBESTOS EXPOSURE ASSESSMENT
ALGORITHM
There are three steps in applying the guide: (1) the eight factors
are assigned a numerical value corresponding to their proper
description; (2) the numerical values are combined by a mathematical
formula to produce the Exposure Number; and (3) the Exposure Number
is compared to the Corrective Action Scale. These three steps should
be performed for each area of the building in which asbestos has been
found. The three steps of the exposure guide are described below.
Step 1: Factor Score Selection
Table I presents a list of the eight factors, a brief description
of the range or extent to which a particular condition applies, and a
numerical "Factor Score" corresponding to that description. The
official making the assessment must first select the description best
fitting the situation in that area.
273
-------
quality of the installation, adhesion of the material to the
underlying substrata, deterioration, vandalism and/or damage.
This factor is comprised of three levels:
A. NO DAMAGE: material is intact and shows no signs of
deterioration. SCORE 0.
3. MODERATE DAMAGE: Visual inspection and physical contact
indicate that the material is breaking up into layers or
beginning to come loose from the-substrate. There may
be small areas (less than 10% of the total area) where
the material is deteriorating. There may be signs of
accidental or intentional damage. SCORE 2
C. SEVERE DAMAGE: The material is non-cohesive. Pieces
are'disloged and debris in the area is evident. Parts
of the material may be hanging from the ceilings or may
have fallen to the floor. Inspect for severe accidental
or intentional damage SCORE 5.
FACTOR TWO: WATER DAMAGE
Water can dislodge, delaminate, and disturb friable asbestos
materials that are otherwise in good condition. Water can carry
fibers as a slurry to other areas where evaporation will leave a
collection of fibers that can become reentrained (res'uspended) in
the air. This factor is comprised of three levels:
A. NO WATER DAMAGE: No water stains or evidence of the
material being disturbed by water. No stains or
buckling on the floor, ceiling or walls to indicate past
water damage. SCORE 0
3. MINOR WATER DAMAGE: Small areas of the material or
adjacent floor and/or walls show water stains and
ceiling material may be slightly buckled. However,
pieces have not fallen from the ceiling and the damage
affects 10 percent or less of the material. SCORE 1
C. MODERATE TO*MAJOR WATER DAMAGE: Water has dislodged
some of the material and caused the material to break
away, or become saturated with the potential to fall.
and/or
More than 10 percent of the material has been
affected. SCORE 2.
FACTOR THREE: EXPOSED SURFACE AREA
The exposed surface area of friable material has an effect
on potential fiber fallout levels and the possibility for contact
and damage. A useful criterion for determining the amount of
exposed material is whether the friable material is visible.
Asbestos material above a suspended ceiling is not
considered exposed unless: (1) the ceiling panels are removed for
regular maintenance, (2) the panels are damaged (i.e. due to
vandalism, or maintenance) (3) the space above the ceiling
comprises an air plenum.
274
-------
Areas with louvers, grids/ or other open ceiling systems
should be considered exposed. This factor is comprised of three
levels;
A. MATERIAL NOT EXPOSED: (For example, all asbestos
materials are contained behind a solid suspended ceiling
which is very hard to open and shows no sign of
damage. The plenum is not used for air conveyance.)
SCORE 0
B. TEN PERCENT OR LESS OF THE MATERIAL IS EXPOSED:(a
susbended ceiling is opended occassionally or has
damaged or missing panels, for example) SCORE 1
C. GREATER. THAN 10 PERCENT OF THE MATERIAL IS EXPOSED:
SCORE 4
FACTOR FOUR: ACCESSIBILITY
If the asbestos material can be reached, it is accessible
and subject to accidental or intentional contact and damage.
Material which is accessible (within reach) is most likely to be
disturbed in the future either by accident or intentionally ar.c,
therefore, this factor is one of the most important indicators of
exposure potential.
The proximity of the frrable'material to heating,
ventilation, lighting, and plumbing systems requiring maintenance
or repair indicates accessibility.
Also, the behavior of the student population should be
considered in evaluating accessibility- For example, students
involved in sport activities may accidently cause damage to the
material on the walls and ceilings of gymnasiums. Material that
is easily accessible is also subject to damage by vandalism. The
presence of damage is the most obvious indicator for
accessibility.
This factor is comprised of three levels:
A. NOT ACCESSIBLE: The material is located, above a
suspended ceiling or is concealed by ducts or piping.
The building occupants cannot contact the material.
Maintenance is not required for the ducts, piping or
electrical systems near the asbestos materials SCORE 0.
B. RARELY ACCESSIBLE: The material is contacted only curing
abnormal activity such as infrequent maintenance or
repair. Building occupants rarely touch the material or
throw objects ag*ainst it. SCORE 1.
C. ACCESSIBLE: Material is contacted frequently due to
routine maintenance and/or the building occupants can
contact the 'material during normal activity, (curing
this activity occupants could touch and dislodge the
material or easily throw objects against it.) "SCORE 4.
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FACTOR FIVE. ACTIVITY AND MOVEMENT
This factor combines the effects of general causes that may
result in contact or damage to friable material. These causes
include air movement, building vibration from machinery or any
other source, and activity levels of students or building
workers. This factor is also an indication of future exposure
potential. This factor is comprised of three levels:
A. NONE OR LOW ACTIVITY: In areas such as administrative
offices, libraries, some classrooms, rarely used storage
rooms, and fire exists. The population is quiet and
non-destructive. SCORE 0
3. MODERATE ACTIVITY: Activities that could create regular
vibration in cafeterias, corridors, classrooms or other
areas. This vibration could result in fibers being
released frcm the material to the immediate area.
SCORE 1
C. HIGH ACTIVITY LEVEL: Occupants in cafeterias and
corridors are vandalous or disruptive in their
activities. Also,all gymnasiums and rooms containing
machinery are subject to high vibration and air movement
levels. Areas ajacent to very high sources 'of vibration
(highways, engine shops, etc.] should be scored as "high
activity level" SCORE* 2
FACTOR SIX. AIR PLENUM OR DIRECT AIR STREAM
Friable asbestos-containing material within an air plenum or
in an air stream if undisturbed, has a low potential of
contaminating the building's environment. However, it must be
considered since contamination may result from contact or damage
during maintenance, repairs, renovations, or if- the air stream is
very turbulent. This factor is comprised of two levels:
A. NO AIR PLENUM OR DIRECT AIR STREAM PRESENT: SCORE 0.
B. AIR PLENUM OR DIRECT AIR STREAM PRESENT: SCORE 1.
An air plenum exists when the return (or, in rare cases,
conditioned) air leaves a room or hall through vents in a
suspended ceiling and travels at low speed and pressure through
the space between the actual ceiling and the suspended ceiling.
For the purpose of scoring this factor, a plenum is present if
asbestos material is also found in that space. A direct air
stream is present when ducts for the heating or air conditioning
system blow directly on asbestos material.
FACTOR SEVEN. FRIA3ILITY
The term friable is applied to material that can be
crumbled, pulverized, or reduced to powder in the hand. In order
to score the material in question it must be touched. The
asses^os-containing material can vary in degree of friability.
The more'friable the material, the greater the potential for
asbestos fiber release and contamination. Sorayed asbestos
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.material is generally more friable that most trowelled
materials. This factor is comprised of these levels:
A. LOW FRIABILITY: material that is difficult yet possible
to damage by hand. This would include most "trowelled"
materials and manufactured items such as very soft
ceiling tiles. SCORE 1
3. MODERATE FRIABILITY: Fairly easy to dislodge and crush
or pulverize by hand. Material may be removed in small
or large pieces. SCORE 2
C. HIGH FRIABILITY: The material is fluffy, spongy, or
flaking and may have pieces hanging down. SCORE 3
FACTOR EIGHT: ASBESTOS CONTENT
The percentage for all types of asbestos present in a given
sample should be added for the total asbestos content. While all
asbestos materials present an exposure potential, those with a
high percentage of asbestos car. release more fibers. This factor
is comprised of three levels:
A. TRACE AMOUNTS TO ONE PERCENT:' SCORE 0.
B. ONE PERCENT TO FIFTY PERCENT: SCORE 2.
C. FIFTY PERCENT PLUS: SCORE 3.
These levels of asbestos content must be derived from
results of bulk sample analysis. Building records or assumptions
are not reliable or acceptable
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Table II. Exposure Number Calculation
Factor Factor Score
1. Material Condition
2. Water Damage *
3. Exposed Surface Area +
4. Accessibility +
5. Activity and Movement •*•
6. Air Plenum +
SUM [1 + 2 + 3-5-4 + 5 + 6]
7. Percent Content
8. Friability
PRODUCT [7x8]
Exposure Number = PRODUCT x SUM
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Table III. Corrective Action Scale
EXPOSURE NUMBER RANGE
CORRECTIVE ACTION
0-12
Advantage:
Disadvantages:
DEFERRED ACTION
There is no direct cost associated
(1) The potential for exposure may
increase.
(2) A management system is required.
Precautions are necessary to prevent
damage during maintenance or
renovation.
(3) It is necessary to have continous
inspection and reevaluation.
When Appropriate: When there is negligible exposure
potential.
When Inappropriate:
(1) When there is definite or
questionable exposure potential.
(2) Continuing inspection is doubtful
10-50
Advantage :
ENCAPSULATION
(1) It controls fiber release
(2) It is a rapid and economical method
Disadvantages
(1) The asbestos source remains.
(2) If the material is damaged or
deteriorating the additional weight
of the sealant may cause layers of
the material to break away from the
underlying surface.
(3) A management system is required.
Precautions are necessary to prevent
damage during maintence or
renovation.
(4) Continuing inspection and iaaintenar.es
for damage or deterioration to
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encapsulated surface. (i.e. future
potential for fiber release is
possible).
(5) Encapsulated material is very
difficult to remove if it becomes
necessarv.
When Appropriate:
(1) When removal is not feasible
(2) The material still retains bonding
integrity.
(3) Damage to the material is not
probable.
(4) Accessibility to material is limited
(5) The surface in question is complex
(i.e. pipes, lines and ducts).
(6) When economic or time constraints ar;
present.
When Inappropriate: (1) When removal is feasible
(2) Material does not adhere well to the
substrate. The weight of the sealant
may cause futher damage.
(3) When the material is deteriorating or
damaged.
(4) Damage to the material is probable
(5) Water damage or the potential for
water damage is evident.
(6) High accessibility present
(7) When continuing inspection and
maintenance of encapsulated material
is doubtful.
10-50
Advantage:
ENCLOSURE
(1) It controls fiber release
(2) May be the most rapid/ economical and
uncomplicated method.
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Disadvantage:
(1) The asbestos source remains
(2) Fiber fall out continues behind the
enclosure
(3) Maybe costly if enclosure disturbs
functions of other systems (e.g.
enclosure may require lighting
changes).
(4) Management system required.
Precautions necessary for entry into
enclosure for maintenance or
renovation.
(5) Continuing inspection, and maintenance
of damage to enclosure system
recuired.
When Appropriate:
(1) Removal is not feasible.
(2) Disturbance or entry into enclosed
area is not likely -
(3) Economic constraints are present
When Inappropriate: (1) Removal is feasible
(2) Damaged or deteriorating material
causes high level of fiber fallout.
(3) Water damage to enclosure is likely
(4) Entry into enclosure probable for
repairs and maintenance.
40 and over
Advantace:
REMOVAL
(1) It eliminates the asbestos source
(2) Ends the exposure and precludes the
development of future problems.
Disadvantages
(1) Usually the most costly, complicated
and time consuming method.
(2) Replacement with substitute material
may be necessary.
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(3) Higher potential for worker exposu:
during removal
When Appropriate:
(1) High exposure exsists
(2) Material is deteriorating, high
accessible and has severe water
damage.
(3) Open material surfaces.
When Inappropriate: (1)
When removal is not feasible because
of cost/ location of material and
kind of surface to which material has
been applied (e.g. removal of
material from complex surfaces such
as pipes/ lines and ducts).
Summary:
(1) If exposure number is 0-12 usually
can defer action.
(2) If exposure number is approximately
40 or over removal is probably the
best corrective action.
(3) If the exposure number is 10-50 and
has high water damage or
accessibility factor, removal is
probable the best corrective
procedure.
(4) If the exposure number is 10-50 and
the water damage and accessibility
factors are low, then the constraints
(i.e. economic, time and complicated
surfaces) need to be examined. The
three corrective actions possible are
encapsulation/ enclosure and removal.
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TECHNICAL REPORT DATA
re-jj /ii^ntcriais or, :ne reverse neiore ew.
4 TITLE A.\D SUBTITLE'
Economic Impact Analysis of Proposed
Identification and Notification Rule on Friable
Asbestos Containing Materials in Schools
[ September- 3.
|6. ?=RF'o.=tMING ORGANIZATION CODE
7 AUTHOR(S)
Susan Wright, Stephen Schoepke, Ph?lip Hathias !
9. V'triFORMING ORGANIZATION NAME AND ADDRESS
Arthur Young and Company
1025 Connecticut Ave., K.W.
Washington, B.C. 20036
10. PROGRAM E-E.V.S \7 NO.
B2CL2S
n.COMT = ACT 3RA.M7 ,\C.
68-01-3930
Research Request #2
12. Sf>ONsbRINCj~AGgNCY MAMH AND ADORESS
U.S. Environmental Protection Agency
Office of Toxic Substances
401 M St. S.W.
Washington, D.C. 20460
13. TYPE O= SE?b=.T AND FSRiCD COVE/
Final.
. 5?ONbORl\3
^ CODE
3. SL'f ?.£,V:EMTARY I-W
16. A3STRAC1
This study exsiriines the economic impact of the detection and
notification of schools which have areas contaminated with
fria'r-'.e 2sbestos-coi)t^ini..-,g materials. The problem is identified
by gerr.-aphic area and by square footage of asbestos-contai'i.,r
materi = ":s per school. unit costs are examined by region fci
inspection and anaiy~-S of samples by X-ray diffraction, e". -. :'.ron
micr: s .-:>py, and op._icT^ -icroscopy. The total impacts of
Asbett-^s Schools Ru".e "o. 1 are also presented and discussec.
Possib'.e courses of action for correction of the problem are _lso
examiried, which may bs done voluntarily by the school or rr?,- -.-ac
by f\: .jre EPA rego'.slxons.
17.
KEY WORDS AND DOCUMENT ANALYSIS
b. IDENTi-IERS/OPEN ENDED TEF.S'S
CCSATi
3. O!57F:iBUTION STATEVirNT
Distribution unlimited
i 19. S£CURJTV <-' ass Tin: ft-e^on,
unclassified
I 2O. SECURH Y CLASS ;~-:ii ps^e;
i unclassified
EPA FO-:TI 2T20-1 (9-73)
GOVERNMENT PRINTING OFF ICEi 1980-34t- 085/4610
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