United States
Environmental Protection
Agency
Region 5
Water Division
230 South Dearborn Street
Chicago. Illinois 60604
January 1988
905R88109
Evaluation of Predicted and
Actual Impacts of Construction
Grants Projects in Three River
Basins of Region V
£5 Saginaw River Basin
s.
a? Naumee River Basin j
Lower Portion of Upper Mississippi River Basin'^"jj
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EVALUATION OF PREDICTED AND ACTUAL IMPACTS
OF CONSTRUCTION GRANTS PROJECTS IN THREE RIVER BASINS OF
REGION V
JANUARY 1988
Prepared by:
United States Environmental Protection Agency
Region V
Environmental Planning Section
230 South Dearborn Street
Chicago, Illinois 60604
and
Science Applications International Corporation
8400 Westpark Drive
McLean, Virginia 22102
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ABSTRACT
This investigation compares environmental predictions, obtained from National
Environmental Policy Act (NEPA) decision documents from 1975 to 1982, concern-
ing the impacts of Construction Grants projects, against the actual impacts
observed during site visits conducted in 1985. Forty-four projects located
in three river basins of USEPA Region V were evaluated. These projects
accounted for a total of 649 environmental predictions. These predictions
are categorized into four groups: 1) as predicted or better than predicted;
2) prediction not sustained; 3) not an issue; and 4) conclusion now would be
premature. An analysis of these predictions revealed the following:
- The study results find 21% of all predictions were quantitative, while 79%
were qualitative.
- The study finds 412 or 63.5% of the predictions were "as predicted or better
than predicted."
- The study finds that both quantitative and qualitative predictions were
greater than 60% "as predicted or better than predicted" and suggests that
both quantitative and qualitative predictions can be useful when evaluating
the same environmental issue.
- The study supports a minimum accuracy rate for NEPA predictions of 80% and
a potentially higher accuracy rate of 94%, depending upon the outcome of
various long-range predictions which can be best evaluated after 20 years
has elapsed.
11
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TABLE OF CONTENTS
Page
Title Page i
Abstract ii
Table of Contents ii i
List of Figures iv
List of Tables v
I. Purpose of Study 1
II. Introduction and Background 1
III. Methods 4
A. Sample Selection for the Study 6
B. Data Gathering Activities 10
C. Data Processing and Analysis Activities 11
IV. Results and Discussion 13
A. Overview of Predictions 13
1. Predictions Present or Implied 13
2. Quantitative vs. Qualitative Predictions 17
3. Accuracy Classification of Predictions 20
a. Accuracy Classification of Qualitative and Quantitative 23
Predictions
b. Accuracy Classification by Issue 26
c. Accuracy Classification by River Basin 30
B. Effectiveness in Making Accurate Predictions 33
V. Conclusions • 36
VI. Recommendations . 37
VII. Further Studies 38
Appendix A - Results and Discussion for Each Issue
Appendix B - Federal Statutes Pertinent to Environmental Review of Construction
Grants Projects
Note: Complete data base is available upon request from USEPA-Region V.
n i
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LIST OF FIGURES
Number Title Page
1 Monitoring and Evaluation Flowchart 5
2 Locations of the Saginaw, Maumee and Lower 8
Portion of the Upper Mississippi River Basins
3 Percentage of Impact Predictions Present in 16
NEPA Documents for Each Year of Study
4 Quantitative and Qualitative Predictions 18
5 Accuracy Classification of Quantitative and 25
Qualitative Predictions
6 Probability of Making on Inaccurate Prediction 29
7 Accuracy Classification By River Basin 31
8 Overall Accuracy of Predictions 33
A-l Accuracy Classification of Water Quality A-l
Predictions
A-2 Accuracy Classification of Wetlands A-3
Predictions
A-3 Accuracy Classification of Floodplain A-5
Predictions
A-4 Accuracy Classification of Biota Predictions A-6
A-5 Accuracy Classification of Socioeconomic A-7
Predictions
A-6 Accuracy Classification of Agriculture A-ll
Predictions
A-7 Accuracy Classification of Physical Environment A-13
Predictions
A-8 Accuracy Classification of Cultural Resource A-14
Predictions
A-9 Accuracy Classification of Solid Waste A-15
Predictions
A-10 ' Accuracy Classification of Energy Predictions A-16
A-ll Accuracy Classification of Air Quality A-17
Predictions
A-12 Accuracy Classification of Other/Recreation A-18
Predictions
IV
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LIST OF TABLES
Number Title Page
1 List of Projects for Study 9
2 NEPA Document By Year for Each River Basin 10
3 Prediction Present or Implied Per Issue 15
4 Count of Quantitative vs. Qualitative Predictions 19
Per Issue Per Year
5 Examples of Predictions 20
6 Accuracy Classification of Quantitative and 24
Qualitative Predictions
7 Quantitative and Qualitative Predictions by Accuracy 26
Classification
8 Accuracy Classification of Predictions Per Issue 27
9 Accuracy Classification of Predictions By River Basin 30
A-l Accuracy Classification of Water Quality Sub-issues A-2
A-2 Accuracy Classification of Predictions for Socioeconomic A-8
Sub-issues
B-l Federal Regulations in Effect 8-2
B-2 Federal Regulations Affecting the Implementation B-4
of NEPA in the Construction Grants Program
B-3 Relevant Guidance Documents on Environmental Impact B-ll
Predictions and Review for Construction Grant
Projects, 1975-1982
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I. PURPOSE OF STUDY
The purpose of this study is to assess the effectiveness of the United
States Environmental Protection Agency (USEPA) Region V review processes
required under the National Environmental Policy Act (NEPA) in predicting
the environmental impacts of Federal Construction Grants projects for
wastewater treatment facilities. This study uses a sample of environmental
predictions obtained from 44 NEPA actions dated between 1975 and 1982.
These predictions, concerning the effects of construction and operation
of Construction Grants projects were then compared to actual impacts
observed during site visits conducted in 1985.
II. INTRODUCTION AND BACKGROUND
The enactment of the National Environmental Policy Act (NEPA), in 1969,
provided for the development of a process by which Federal agencies were
required to assess the environmental impacts of their actions. In addi-
tion, the Council on Environmental Quality has established regulations
(40 CFR Part 1500-1508) to guide Federal agencies in determinations of
whether Federal funds or approvals would involve a project that could
significantly affect the environment. USEPA has the environmental review
responsibility for the funding and construction of a wastewater treatment
plant as defined in 40 CFR Part 6 (Implementation of the National
Environmental Policy Act).
Throughout the 1970's, environmental impact assessment methodologies were
refined, areas of concern expanded and environmental data bases accumulated.
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Also, the intensiveness with which certain environmental issues were evaluated
changed with the passage of specific Federal legislation or requirements
such as those relating to wetlands and floodplains. Appendix B provides a
list of statutes and regulations pertinent to NEPA review.
The Federal Water Pollution Control Act (FWPCA, Public Law 92-500), as
amended by the Clean Water Act of 1977 (CWA, Public Law 95-217), established
a uniform, nationwide water pollution control program under which all State
water quality programs operate. Section 201 of the Act established Federal
criteria and funding for the development of wastewater management plans to
achieve the goals of the Act. Funding is provided to municipalities via
the Municipal Wastewater Treatment Construction Grants Program, which is
administered by USEPA.
the USEPA Construction Grants Program defined requirements for the faci-
lities planning process. The Facility Plan (FP) prepared by a municipality
must include an Environmental Information Document (EID) which addresses
the environmental impacts of the various alternatives. Following review
of a FP and prior to award of a Step 3 grant, the NEPA review is required.
Based on the NEPA review, a preliminary decision document is issued for
public comment. The process and responsibilities for the FP/EID and NEPA
reviews have changed over the years.
In 1978 USEPA began delegation, a process by which many of the administrative
functions of the Construction Grants Program were turned over to the State
agencies. Prior to delegation USEPA had primary responsibility for facility
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plan reviews. If after the review it was determined that a project would
not significantly impact the environment and that the more detailed Environ-
mental Impact Statement (EIS) was not needed, USEPA would complete its
NEPA review by issuing a negative declaration (negative dec). These
documents were often extremely brief since USEPA conducted the full FP
review and would therefore only need to document USEPA's decision that the
project would have no significant impact on the environment and that it
could proceed without an EIS.
USEPA, as the oversight agency for the Construction Grants Program has always
maintained final NEPA authority. However, in many cases where the facilities
plan review has been delegated, detailed reviews are accomplished at the
State level where a preliminary environmental assessment (EA) is prepared.
Currently, USEPA's responsibility is carried out based mainly on its review
of an EA. The Agency will then determine if an EIS or a Finding of No
Significant Impact (FNSI) is needed. The FNSI has since replaced the
negative dec as USEPA's formal NEPA action. USEPA supplies the FNSI and an
attached EA for issuance to the public for comment. If no substantive
comments emerge to cause a change of plans, the preliminary actions become
final after 30 days.
As part of an evaluation of program effectiveness of the Construction Grants
Program and NEPA in restoring the quality of the nation's waters and in
protecting the environment, USEPA-Region V undertook a program to evaluate
the accuracy of impact predictions made in NEPA documents. After some re-
search it was determined that a standardized methodology would be valuable.
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III. METHODS
A methodology for carrying out such an evaluation was developed in A_
Manual for Evaluating Predicted and Actual Impacts of Construction Grants
Projects. The Manual, prepared for USEPA by ESEI/ Ecolsciences of South
Bend, Indiana, was designed for use in evaluating the accuracy of predicted
impacts for a single project, a group of projects, or an entire program.
A flow chart from the Manual (Figure 1) shows the process of evaluating
the accuracy and effectiveness of the environmental impact assessment
system established by NEPA.
The Manual focused on the twelve environmental issues outlined in 40 CFR
Part fi as necessary to consider during a NEPA review. Also identified
were several sub-issues for better clarification of the issue being
addressed. The issues and sub-issues used for this study are as follows:
1. Water Quality
- Surface Water
- Groundwater
?.. Wetlands
3. Floodplains
4. Biota
-Terrestrial
-Aquatic
-Rare, Endangered, or Threatened
5. Socioeconomic
-Population
-Land-Use
-Employment
-Property Values
-User Charges
-Secondary Hevelopment
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IVIonitoring & Evaluation Flowchart
c
EPA Headquatara
Promulgations
SMA*
Regional Monitoring &
Evaluation Coordination
L
s
4
£
1
0oci«ion»
Social
feonomic
Indicator*
Data Gathering
Quality
Control
(•«
i
Decisions
Air Quality
thru
Watar Quality
Parameters
Data Processing
A
e
o
«
y
2
e
Figure 1
Source: A Manual for Evaluating Predicted and Actual Impacts of Construction
Grants Projects. EPA Region V Wat«r Divi3ion. J>r«p«r^ Ky
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6. Agriculture
7. Physical Environment
-Climate
-Topography
-Soils
8. Cultural Resources
9. Solid Waste
-Sludge
-Spoil Disposal
10. Energy
11. Ai r Quality
12. Other Issues
-Recreation
It was the intent of the Manual to develop a methodology which determines
the accuracy with which planning and environmental review documents (NEPA
documents) assessed predicted environmental effects of the Construction
Grants projects.
This study utilized the Manual to assess the effectiveness of the environ-
mental review process by comparing predictions concerning environmental
effects of Construction Grants projects in Region V with actual impacts
observed during visits to project sites.
A. Sample Selection for the Study
In order to evaluate the accuracy of predictions made in Region V, a
sample of NEPA documents had to be selected which would be manageable
and representative of a regional profile. Potential choices for a
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regional profile include using geographical boundaries such as States,
county, or river basins. Three river basins chosen for this study
include: the Saginaw River Basin of Michigan, the Maumee River Basin of
Ohio and Indiana, and the Lower Portion of the Upper Mississippi River
Basin of Wisconsin and Minnesota (Figure 2).
These three geographical areas were plotted in the STORET data base by
latitudinal and longitudinal coordinates and then redefined in GIGS (Grants
Information and Control System), the computer data base of the Construc-
tion Grants Program. Hundreds of projects were identified by GICS at var-
ious stages of administration and physical completion. The number of pro-
jects was reduced to a smaller and more cost-manageable sample size, yet
was still large enough to represent a regional profile. GICS was used
to provide a list of seventy (70) projects that were greater than 50 per-
cent physically complete. The criterion, 50 percent physically complete,
ensured identification of direct construction impacts to the environ-
ment, even though a project may not have been operational. A timeframe
for the study was determined to be between 1975 and 1982.
The final sample was reduced to 44 projects, all of which were complete
and operational. Table 1 presents the location, project name and year
of NEPA document for each project of this study. Table 2 presents the
distribution of projects by year of NEPA document for each river basin.
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-8-
United States
Environmental Protection Agency
Region V
Figure 2: Locations of the Saginaw (1), Maumee (2), and Lower
Portion of the Upper Mississippi (3) River Basins
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TABLE 1: List of Projects for Study
LOCATION PROJECT NAME
Ada, OH
Cridersville, OH
Fort Wayne, IN
Harrod, OH
Kali da, OH
Monroeville, IN
Montpelier, OH
Napoleon, OH
Ridgeville Corners, OH
Toledo, OH
Toledo, OH
Toledo, OH
Uniopoli s, OH
Weston, OH
YEAR OF NEPA DOCUMENT
Ada Sewage Treatment Plant 1976
Cridersville, Village of 1977
Fort Wayne, City of 1980
Harrod, Village of 1977
Kalida, Village of 1976
Monroeville Sewage Disp Authority 1980
Montpelier Sewage Treatment Plant 1980
Napoleon, City of 1977
Henry County 1976
Toledo, City of (Bayview) 1980
Toledo, City of (Ten Mile Creek) 1977
Toledo-Wai bridge 1980
Uniopolis, Village of 1977
Weston, Village of 1979
Burton, MI
Cass, MI
Chesaning, MI
Durand, MI
Gladwin, MI
Holly, MI
Howell, MI
Lapeer, MI
St. Louis, MI
Tittabawasee TWP, MI
Genessee County (Davison Segment) 1978
Saginaw County WWTP 1977
Chesaning, Village of 1975
Durand, City of 1976
Gladwin, City of 1976
Oakland County Dept. of Public Works 1977
Howell, City of 1976
Lapeer, City of 1976
St. Louis, City of 1976
Tittabawasse Township WWTP 1979
Alma, WI
Augusta, WI
Bangor, WI
Barron, WI
Birchwood, WI
Bruce, WI
Butternut, WI
Coon Valley, WI
Cornell, WI
Cumberland, WI
Desoto, WI
Fountain City, WI
Goodhue, MN
Phillips, WI
Plum City, WI
Rochester, MN
Rushford, MN
Shell Lake,
Strum, WI
Westby, WI
WI
Alma Municipal WWTP
Augusta, City of
Bangor, Vi1lage of
Barren, City of
Birchwood, Village of
Bruce, Village of
Butternut, Village of
Coon Valley Municipal WWTP
Cornell, City of
Cumberland, City of
Desoto, Village of
Fountain City, City of
Goodhue, City of
Phillips, City of
Plum City, Village of
Rochester, City of
Rushford, City of
Shell Lake, City of
Strum, Village of
Westby Sewage Treatment Plant
1980
1977
1978
1980
1982
1980
1981
1981
1980
1978
1978
1979
1982
1980
1979
1978
1980
1980
1980
1980
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TABLE 2: NEPA Documents By Year For Each River Basin
River Basin
Maumee
Saginaw
Upper
Mississippi
Total
1975
0
1
0
1
1976
3
5
0
8
1977
5
2
1
8
1978
0
1
4
5
1979
1
1
2
4
1980
5
0
9
14
1981
0
0
2
2
1982
0
0
2
2
Total
14
10
20
44
B. Data Gathering Activities
Once the sample had been selected, a review of background files for each
project was conducted by a Field Group. The Field Group was comprised
of several personnel from Science Applications International Corporation
(SAIC), a consultant to USEPA. SAIC staff performing the field investiga-
tions are referred to as field investigators.
The field investigators reviewed files at USEPA and at State pollution
control agencies to get an overview of each project and to document the pre-
dictions for the twelve issues outlined in 40 CFR Part 6. NEPA predictions
existed for all years in the timeframe of this study. Emphasis was on
predictions made in public notices. Public notices of NEPA decisions were
found in Negative Declarations (Negative Decs) between the years 1975 and
1979 or in Environmental Assessment/Findings of No Significant Impact
(EA/FNSI) between 1979 and 1982. At times, Facilities Plans were consulted
in lieu of a Negative Dec or an EA/FNSI when additional information was
desired. None of the projects in the sample investigated by this study
were the subject of an EIS.
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Field visits to each Construction Grants project site were made in the
autumn of 1985, by one or two field investigators from SAIC. Each visit
consisted of an inspection of the wastewater treatment system and interviews
with plant operators, local officials, and area planning agencies, when
available. The object of each field visit was to complete an environmental
inventory while documenting the actual impacts that occurred during construc-
tion and any other impacts related to the operation of the facility. Following
the visit, the actual impacts on all twelve environmental issues were recorded.
The emphasis of each visit was to document the findings by way of an
evaluation form in order to input the data into a computer for analysis. A
narrative report was also prepared for each project, which summarized the
project and/or field visit.
C. Data Processing and Analysis Activities
A Task Group, comprised of USEPA-Region V staff, conducted a review of
the preliminary data prepared by the Field Group (narrative reports,
evaluation forms, and computer data). The first of three tasks was
to ensure that the data stored in the computer was accurate and uniform.
This was done by reviewing the narrative reports and computer data for
each project to ensure consistency. Adjustments were made to language
and format of entries to achieve the necessary consistencies for cross-
tabulations of the data.
The second task was to evaluate the predictions made for each project
and each issue. The Task Group categorized each prediction into
quantitative or qualitative groups in order to prepare for an analysis
to determine if the qualitative or quantitative nature of a prediction
has any impact on overall effectiveness.
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A quantitative prediction was assumed to be a numerical based prediction
that could be measured and compared to actual findings. This study
assumed that the use of the word "no" in a prediction, when not mod-
ified by an adjective, rendered the prediction quantitative or to mean
"zero" (e.g. no wetlands will be impacted). Qualitative predictions, on
the other hand, were predictions that did not reference numerically
measurable parameters. Although, in cases where a qualified numerical
value was included, the prediction was considered qualitative.
The third and most significant task was to compare the accuracy of
each prediction, by issue, with the actual impact, and to code each
prediction using the following system.
Code Explanation
A AS PREDICTED OR BETTER THAN PREDICTED
This code represents an accurate prediction of impacts. If no
prediction was made and the investigator mentioned that no impact
had occurred, the prediction was coded "A".
B PREDICTION NOT SUSTAINED
This code represents an inaccurate prediction of impacts. In
such cases, where the actual findings were worse than predicted,
the prediction was coded "B".
C NO IMPACT CONCERNS
This code represents parameters that were considered not an
issue. If no impact or no significant impact was implied as a
prediction and the field investigator did not find any actual
impacts, the prediction was coded "C".
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0 CONCLUSION NOW WOULD BE PREMATURE
This code represents a prediction in which the accuracy could
not be determined. For example, this coding was entered for
situations where the timeframe of the predictions extended
beyond 1985, or in cases where chemical or biological data
was not available. In such cases the prediction was coded "D".
The accuracy coding and quantitative/qualitative coding for each predic-
tion was then entered into the computer data base. The data base was
reviewed again for consistency by the Task Group and additional revisions
were made. The data base is available upon request from USEPA-Region V.
IV. RESULTS AND DISCUSSION
The data base was used to conduct cross-tabulations and derive findings
on trends in the data. The evaluation of specific trends in environmental
predictions is provided in the following sections: Overview of Predictions
and Effectiveness in Making Accurate Predictions.
A. Overview of Predictions
1. Predictions Present or Implied
A total of 649 predictions were recorded for the 44 projects. Of the 649
predictions, 410 were actual prediction statements made in NEPA documents
(prediction present) and 239 were implied or absent. An implied prediction
reflects a situation in which no impact or no significant impact relative
to that issue was expected and thus no statement was included in the NEPA
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document (prediction implied). Table 3 presents a detailed chart of the
number of predictions present or implied in NEPA documents for each of the
twelve issues outlined in 40 CFR Part 6 and the Manual. Note also that the
total number of predictions was greater than 528 (12 issues X 44 projects),
because for several projects more than 12 predictions were made due to the
various sub-issues.
Figure 3 shows the trend of percentages for predictions made from 1975
to 1982. The percentage of predictions present increased from 1976 to
1981. This is due to the fact that prior to delegation to the States
in 1979, USEPA had full review of a project and thus would typically
prepare a NEPA document for public notice which included statements
that the FP review process had resulted in predictions of no significant
impacts from the project. As delegation occurred between 1979 and
1982 with project files and facilities plan review responsibility
transferred to the State agencies, an increased need to document each
40 CFR Part 6 issue in specific prediction statements was apparent in
the State prepared preliminary NEPA document to allow USEPA to review
and approve projects for public notice.
It should be noted that the trend indicates a large jump from 1975 to 1976.
This can be attributed to the fact that only one project from 1975, for which
a negative declaration was issued, was part of the study. The results for
1982, in Figure 3, are somewhat misleading since data for one of the two
projects for that year was misrepresented in the computer data base. This
inconsistency was discovered late in the data analysis phase of the study.
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FIGURE 3: Percentage of Impact Predictions Present in
NEPA Documents for Each Year of the Study
100%
90
80
£ 70
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OJ
60
50
40
30
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a.
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n=14
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n= Number of Projects for the Year
TP= Total Present and Implied Predictions for the Year
% Predictions # of Predictions Present
Present= TP
NOTE: The dashed line for the 1982 data reflects that there was an inconsistency
in the data base for that year. This inconsistency concerns the Goodhue, MN
project, for which data from a 1977 Negative Dec was encoded instead of the
1982 FNSI.
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As we explored the data further it was important to document how the trend
of predictions present or implied affected accuracy in making predictions.
2. Quantitative vs. Qualitative Predictions
Figure 4 presents the breakdown of predictions as qualitative or quantita-
tive. Over 21% of all predictions (present or implied) in the study's NEPA
documents for all years were quantitative. Every implied prediction in the
documents was considered to be qualitative.
Table 4 presents the overall breakdown of qualitative and quantitative pre-
dictions for each issue over all NEPA document years. Issues for which
a significant portion of the predictions were quantitative include socio-
economic issues (50% quantitative), cultural resource issues (55%), other/
recreation issues (29%), and agriculture issues (20%).
Socioeconomic issues lend themselves to quantitative predictions because
they often refer to factors such as population figures, user charges, and
property values. Cultural resource and other/recreation issues involve
quantitative predictions which are stated using the word "no." For example,
the predictions are phrased as "no cultural resource will be impacted" or
"no impacts will occur to a cultural resource." Predictions concerning
agricultural issues are often quantitative by virtue of reference to the
number of acres of farm land expected to be impacted by a project.
Between 1975 and 1979, there was a noticeable increase in quantitative pre-
dictions, with the greatest amount of quantitative predictions occurring in
1979. The prediction statements contain no quantitative information for any
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FIGURE 4: Quantitative and Qualitative Predictions
QUALITATIVE - 78.6% (510)
QUANTITATIVE - 21.4% (139)
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-20-
issue in 1975, and less than five quantitative predictions over the eight year
timeframe of this study for water quality, physical environment, energy, air
quality and other/recreation. Since 1979, a slight decrease in quantitative
predictions has occurred.
3. Accuracy Classification of Predictions
In order to better illustrate the coding and how it was used, Table 5 pre-
sents five examples of predictions that fell into each accuracy coding
category.
TABLE 5: Examples of Predictions
CODE A: AS PREDICTED OR BETTER THAT PREDICTED
1. Issue: Water Quality/Surface Year: 1980
Prediction: Project would alleviate surface water pollution to Brown Ditch
Actual Impact: Facility easily meets their NPDES limits for all parameters
Ditch is no longer covered with black film. Healthy vegeta
tion exists around outfall. Surface water quality in Brown
Brown Ditch significantly improved.
2. Issue: Water Quality/Ground Year: 1977
Prediction: Water Quality enhanced: elimination of improperly treated sept
tank effluent.
Actual Impact: Water Quality improved. Houses adjacent to new lines have
hook-up, thereby eliminating on-site systems.
3. Issue: Biota Year: 1977
Prediction: No significant wildlife will be affected by the project.
Actual Impact: No habitat was affected by the plant expansion. Fishing am
trapping have improved. Fish presently caught downstream di
not have a film on their scales, taste better when cooked.
Some change in aquatic plant species, more diversity.
-------
-21-
4. Issue: Socio/User Charge Year: 1977
Prediction: Increased financial burden for residents. Estimated costs-$156/
Yr.
Actual Impact: User charges are $19.15/month. Prediction was $21/month.
5. Issue: Cultural Resource Year: 1982
Prediction: No historical or cultural impacts.
Actual Impact: No artifacts found dunng construction. Area around site
appears to have been previously disturbed.
CODE B: PREDICTION NOT SUSTAINED
1. Issue: Socio/User Charge Year: 1980
Prediction: Estimated monthly user charge: $6.00
Actual Impact: Average user charge about $13.50. Increase is over 1% of
their income.
2. Issue: Air Quality Year: 1980
Prediction: (No prediction present)
Actual Impact: Frequent odor complaints from nearby commercial establish-
ments and residences. Major source of odors could be
overloaded RBC or poorly operated digester.
3. Issue: Wetlands Year: 1977
Prediction: No environmentally sensitive areas in planning area.
Actual Impact: 19 acres of wooded swampland purchased. 5 acres used for
construction, wooded swampland used.
4. Issue: Biota/Terr. Year: 1980
Prediction: (No prediction present)
Findings: During warm weather thick swarms of midge flies engulf area
surrounding lagoon forcing businesses to close. Town more or less
hibernates.
-------
-22-
5. Issue: Socio/Secdev Year: 1978
Prediction: Adequate wastewater treatment is not expected to have any effei
on rate, density, or type of development in service area.
Actual Impact: Adequate sewage treatment ended sewer extension ban; 168 nei
lots platted in designated residential zone. Growth rate
since the project is 4 times projected rate.
CODE C: NOT AN ISSUE
1. Issue: Water Quality/Ground Year: 1977
Prediction: (No prediction present)
Actual Impact: Groundwater concerns were not an issue.
2. Issue: Wetlands Year: 1980
Prediction: (No prediction present)
Actual Impact: Construction not located in wetlands
3. Issue: Cultural Resource Year: 1980
Prediction: (No prediction present)
Actual Impact: No impacts were predicted or occurred
4. Issue: Energy Year: 1979
Prediction: (No prediction present)
Actual Impact: Not an Issue
5. Issues: Air Quality Year: 1976
Prediction: (No prediction present)
Actual Impact: (No impacts noted by investigator)
CODE D: CONCLUSION NOW WOULD BE PREMATURE
1. Issue: Water Quality/Ground Year: 1976
Prediction: Rehabilitation of sewers will prevent exfiltration to ground-
water.
Actual Impact: No data was available after rehabilitation. No evidence of
groundwater contamination noted.
-------
-23-
?. Issue: Biota/Aquatic Year: 1980
Prediction: Improved water quality will significantly improve aquatic life
in Chippewa River.
Actual Impact: No current fish or benthic surveys conducted.
3. Issue: Socio/Population Year: 1980
Prediction: Projected growth rate of population is 1.2%. Design
population is 1,706.
Actual Impact: No growth has occurred since 1980. Population has
remained constant at about 1374 people.
4. Issue: Socio/Land Use Year: 1980
Prediction: Approximately 450 acres will he needed for residential
development by the year 2000.
Actual Impact: No impact apparent. Land use impact could not be
assessed by site investigation.
5. Issue: Other/Recreation Year: 1978
Prediction: Downstream recreational capabilities will be enhanced due
to reduced pollution in the stream.
Actual Impact: Data were not available for water quality. They are under
review by a consultant. In terms of recreational enhance-
ment, no studies have been conducted.
a. Accuracy Classification of Qualitative and Quantitative Predictions
The data generated by the accuracy analysis for quantitative and qualitative
predictions are examined from two viewpoints. The first viewpoint, as
presented in Table 6 and Figure 5, examines the distribution of quantitative
and qualitative predictions across accuracy codes. For example, the first
viewpoint could answer a question such as: "what percent of quantitative
predictions is coded 'as predicted or better than predicted1?" On the other
hand, the second viewpoint, as presented in Table 7, examines the distribution
-------
-24-
of quantitative and qualitative predictions within each accuracy code.
This viewpoint could answer a question such as: "what percent of predictions
classified as 'not an issue' are quantitative?" The results for each viewpoin
are discussed below.
3 Viewpoint 1: Table 6 and Figure 5 present a breakdown of the accuracy code
by qualitative or quantitative predictions. Overall, both the qualita-
tive and quantitative predictions were greater than 60% "as predicted or
better than predicted," showing no significant difference in improving
the accuracy of a prediction by its qualitative or quantitative state.
The likelihood of a quantitative prediction being coded B ("prediction
not sustained") or inaccurate was nearly three times that of a qualita-
tive prediction. This is based on the fact that there is typically one
discrete measureable value of a quantitative prediction upon which to
to evaluate accuracy.
Table 6: Accuracy Classification By Quantitative and Qualitative
Predictions
Accuracy Code
A B C D Total
Quantitative
Qualitative
92(66%)
320(63%)
15(11%)
21(4%)
0(0%)
106(21%)
32(23%)
63(12%)
139 (100%)
510 (100%)
A = "As predicted or better than predicted"
B = "Prediction not sustained"
C = "No impact concerns, not an issue"
D = "Conclusion now would be premature"
-------
-25-
Figure 5: Accuracy Classification By Quantitative and Qualitative Predictions
Quantitative
B-11% (15)
B-4% (21)
D-12% (63)
Qualitative
A = "As predicted or better than predicted"
B = "Prediction .not sustained"
C = "No impact concerns, not an issue"
D = "Conclusion now would be premature"
Viewpoint 2: Table 7, in contrast to Table 6, presents the breakdown
of qualitative and quantitative predictions in each accuracy code
category. Accurate predictions, or those coded "A" were 78% qualita-
tive. All predictions coded "C" were qualitative because the category
consisted primarily of implied predictions or predictions that were
considered not an issue. The percentage figure for quantitative
predictions in Category B ("prediction not sustained") was nearly the
same as the figure for qualitative.
-------
-26-
Table 7: Quantitative and Qualitative Predictions By Accuracy Classification
Accuracy Code Quantitative Qualitative Total
A
B
C
D
92(22%)
15(42%)
0(0%)
32(34%)
320(78%)
21(58%)
• 106(100%)
63(66%)
412(100%)
36(100%)
106(100%)
95(100%)
Total 139(21%) 510(79%)649(100%)
A = "As Predicted or Better Than Predicted"
B = "Prediction not sustained"
C = "No impact concerns, not an issue"
D = "Prediction now would be premature"
b. Accuracy Classification By Issue
Table 8 provides a summary of the accuracy classification of predictions
per issue. A more detailed discussion of results for each issue is contained
in Appendix A. Physical Environment and Air Quality predictions ranked
highest in Category A, "as predicted or better than predicted". The quali-
tative nature of these predictions are, perhaps in turn, least complex to
assess. Energy predictions ranked lowest in Category A. The driving factor
for this is the fact that Energy predictions were not typically predicted;
they were implied or just not a major concern of the construction activities.
The highest percentage of predictions not sustained occurred for the Socio-
economic issue. Most socioeconomic data are based on quantitative population
and economic data" developed by agencies other than USEPA. Unlike the other
predictions that have been examined among NEPA documents, socioeconomic data
are typically on records developed for broad applications by the U.S. Census
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-27-
Table 8: Accuracy
ISSUE
WATER QUALITY
WETLANDS
FLOODPLAINS
BIOTA
SOCIO ECONOMIC
AGRICULTURE
Classification of Predictions
A
55
26
34
39
70
28
PHYSICAL ENVIRONMENT 40
CULTURAL RESOURCES
SOLID WASTE
ENERGY
AIR QUALITY
OTHER/RECREATION
TOTAL
A = As Predicted or
B = Prediction Not
C = Not an Issue
D = Conclusion Now
34
29
13
35
9
412
(60%)
(59%)
(78%)
(74%)
(53%)
(64%)
(82%)
(77%)
(64%)
(30%)
(80%)
(64%)
B
4
3
1
2
18
1
0
0
4
2
1
0
36
(4%)
(7%)
(2%)
(4%)
(14%)
(2%)
(0%)
(0%)
(9%)
(5%)
(2%)
(0%)
Better Than Predicted
Sustained
Would Be Premature (could
C
15
15
8
6
1
11
7
9
8
18
7
1
106
not
Per Issue
(16%)
(34%)
(18%)
(11%)
(1%)
(25%)
(14%)
(21%)
(18%)
(41%)
(16%)
(7%)
D
18
0
1
6
43
4
2
1
4
11
1
4
95
(20%)
(0%)
(2%)
(11%)
(32%)
(9%)
(4%)
(2%)
(9%)
(24%)
(2%)
(29%)
TOTAL
92(14%)
44(7%)
44(7%)
53(8%)
132(20%)
44(7%)
49(8%)
44(7%)
45(7%)
44(7%)
44(7%)
14(2%)
649
be evaluated)
-------
-28-
Bureau and State Demographic Centers. Economic data such as user cost
predictions are usually based on costs developed by facilities planning
consultants. The high percentage of predictions for the Socioeconomic
issue which were classified in Category B, "prediction not sustained",
may be attributed to the recession in 1979/19SO which impacted growth in
communities and led to large increases in the costs of goods and services
(and thus construction costs). Thus, predictions made during the planning
phase of projects were not accurate due to unforeseen changes in the economy.
Due to the greater variability in forecasting socioeconomic data, a higher
rate of predictions not sustained for this data is expected. Therefore, a
reassessment may be warranted of how socioeconomic data are utilized in
studies which evaluate prediction accuracy.
Socioeconomic predictions also ranked as the highest percentage of predictions
for which a "prediction now would be premature" or could not be evaluated.
Because many socioeconomic predictions are made on a 20-year basis, such
as a projected 20-year population, it would not seem appropriate to evaluate
the accuracy of that prediction during the 20-year planning period.
Solid Waste and Wetland predictions ranked respectively, behind Socio-
economic predictions in Category B, "prediction not sustained". The
reason for these predictions not being sustained is a little different
than for socioeconomic predictions in that these predictions had a fairly
high percentage of implied predictions which were later found to have some
adverse impact.
-------
-29-
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-30-
The probability of making an inaccurate prediction (or a prediction that
could not be sustained) for each issue is illustrated in Figure 6. As
discussed previously socioeconomic predictions are the least likely to be
accurate at 14%, or a 1 in fi chance of making an inaccurate prediction.
c. Accuracy Classification By River Basin
The major focus of this study was to evaluate prediction accuracy in Region V
using three river basins which provided the geographical boundaries from
which to select a sample of projects. The three river basins that were used
include; the Maumee, the Saginaw, and the Lower Portion of the Upper Mississipp
Table 9 and Figure 7 present a breakdown of accuracy classification for each
river basin.
Table 9: Accuacy Classification of Predictions Per River Basin
Number of
River Basin' Projects
Maumee 14
Saginaw
Upper
Mississippi
Total
10
20
44
Total
Predictions
215
137
297
649
A
156 (72.6%)
67 (48.9%)
189 (63.6%)
412 (63.5%)
B
7 (3.3%)
8 (5.8%)
21 (7.1%)
36 (5.6%)
C
22 (10.2%)
48 (35.0)
36 (12.1%)
106 (16.3%)
n
30 (13,
14 (10,
51 (17,
95 (14,
-------
-31-
Figure 7: Accuracy Classification of Predictions By River Basin
B- 3.35
C-10.2%
D- 13.9%
Maumee
D- 10.2%
Saginaw
B- 7.1%
Lower Portion of the Upper Mississippi
A
B
C
D
"As predicted or better than predicted"
"Prediction not sustained"
"No impact concerns, not an issue"
"Conclusion now would be premature"
-------
-32-
The highest percentage of predictions in Category A, "as predicted or better
than predicted", was found for the Maumee River Basin, at 72.6%, while the
Saginaw River Basin had the lowest percentage of predictions in Category A,
at 48.9%. The low percentage in Category A for the Saginaw may be attributed
to the high percentage of predictions classified in Category C, "not an
issue", at 35.0%. All the projects for the study found in the Saginaw River
Basin were limited to the time period of 1975 to 1979, when negative decs were
predominant. As mentioned previously, the negative decs contained few predicti
statements due to the complete facilities plan review conducted by USEPA prior
to issuance of the NEPA document. Predictions classified in Category C, "not
an issue", were mainly implied predictions for which no impacts were expected
and no actual impacts were found during the field investigations, and thus, the
predictions can be considered accurate predictions.
The percentage of predictions classified in Categories C and A could represent
the total percentage of accurate predictions for a river basin. Therefore, the
total percentage of accurate predictions for each river basin can be shown as:
Maumee River Basin: 82.8%
Saginaw River Basin: 83.9%
Upper Mississippi River Basin: 75.8%
Comparing these results indicates that the prediction accuracy was relatively
equal for the three river basins in this study.
-------
-33-
B. Effectiveness in Making Accurate Predictions
This section discusses the overall effectiveness of USEPA-Region V in
making predictions, based on the results of this study. Figure 8 presents
the classification of accuracy for all 649 predictions.
Figure 8: Overall Accuracy of Predictions
A = "As predicted or better than predicted"
B = "Prediction not sustained"
C = "No impact concerns, not an issue"
D = "Conclusion now would be premature"
-------
-34-
Th e greatest frequency of prediction impacts are found in Category A -
"as predicted or better than predicted" which comprises 63.5* or 412 of 649
predictions.
From the accuracy coding results it becomes necessary to discuss the effect-
iveness in making accurate predictions. Since the effectiveness should not
be expressed simply as the percentage of predictions in Category A (accurate)
or in Category B (inaccurate), this study takes into account predictions in
Category C ("not an issue") and Category D ("could not be evaluated") needed
to be taken into account.
Those issues with implied predictions in NEPA documents and no actual impacts
observed in the field investigations are considered to be accurate predictions
when evaluating effectiveness. Therefore, the percentage of predictions
classified as "not an issue" (Category C) together with the percentage of
predictions considered "as predicted or better than predicted" (Category A)
would represent a valid value for total percentage of "accurate" predictions.
Predictions coded "D", or "conclusion now would be premature," should be tenta-
tively considered in the evaluation of NEPA prediction effectiveness. Because
the accuracy of these predictions cannot be evaluated at this time, it is
not known whether each prediction at some point in the near future will be
accurate or inaccurate. The predictions that could not be evaluated are
part of the sample and can alter the effectiveness of prediction results.
-------
-35-
Therefore, the overall effectiveness of Region V in predicting impacts
accurately may be given as a range which incorporates those predictions
classified in Categories A, C, and D. On the lower end of the range is
the percentage of predictions coded A ("as predicted or better than predicted")
plus the percentage of predictions coded C ("not an issue"). On the upper end
of the range is the percentage of predictions coder! A ,the percentage of
predictions coded C, and the percentage of predictions coded D ("conclusion
now would be premature"). The total percentage of accuracy, or the effect-
iveness in making an accurate prediction would be somewhere between these
lower and upper bounds. The following mathematical relationship was developed
to present the range of making an accurate prediction:
A + C <_ Accuracy (%) _< A + C + D
where:
A= % of predictions "as predicted or better than predicted"
C= % of predictions "not an issue"
0= % of predictions "conclusion now would be premature"
This relationship can be expressed as: "The percentage of accuracy is greater
than or equal to A + C and less than or equal to A + C + D."
This range of accuracy is based on the fact that we are at least as accurate
as A + C (the lower bound of the range), but it could be better. The
theoretical highest percentage of accuracy that could be achieved occurs
if all Category D predictions were to become accurate.
-------
-36-
Using the data results from this study, the effectiveness range of
USEPA-Region V in making an accurate prediction can he shown as:
A + C _< % Accuracy £ A + C + 0 [using the relationship developed above"
63.5% + 16.3% <_ % Accuracy _< 63.5% + 16.3% + 14.6% [inserting data from Figure
79.8% <_% Accuracy <_ 94.4%
Therefore, the effectiveness of USEPA-Region V in making accurate predictions
is in the range of 80% to 94%.
V. CONCLUSIONS
This section summarizes the key findings of the study.
- This study categorized 649 predictions present or implied from 44 study
projects into four accuracy codes: A) as predicted or better than
predicted;-B) prediction not sustained; C) not an issue; and D) conclusion
now would be premature.
- A general trend was evident that NEPA documents, over time, contained more
predictions rather than relying on implied predictions.
- During the study's time span (1975-1982) 21% of all predictions were
quantitative.
- The environmental issues that lent themselves more to quantitative
predictions were: cultural resources (55%), socioeconomic (50%), other/
recreation (29%), and agriculture (20%).
- The greatest frequency of prediction impacts are "as predicted or
better than predicted" with 412 of 649 or 63.5%.
- No significant difference was observed with regard to the accuracy of
quantitative or qualitative predictions. Both qualitative and quant-
itative predictions were greater than 60% "as predicted or better than
predicted."
-------
-37-
- No significant difference was observed with regard to the accuracy of
predictions between the three river basins.
- Region V effectiveness in making accurate predictions for this study is
found to be in the range of 80% to 94%.
- This study of the Region V NEPA process for non-EIS projects indicates
that an effective NEPA program is in place.
VI. RECOMMENDATIONS
This section makes recommendations for future environmental predictions in
NEPA documents.
Because the responsibility for Facilities Plan review and preliminary
environmental review has been delegated to the States, it is important
that IJSEPA's oversight in reviewing the preliminary Environmental Assessments
(EA) ensure adequate coverage of important issues. The USEPA reviewers
should ensure that the EA makes predictions for all twelve issues outlined
in 40 CFR Part 6. Baseline data on the environmental conditions prior to
construction should be provided so that specific predictions can be made
about the expected impacts to the existing environment. When possible, a
prediction should be presented as a quantitative expression of the predicted
environmental impact which would allow for a more measureable assessment
of USEPA's effectiveness in predicting impacts. The nature of the data used
for making predictions for socioeconomic issues in NEPA documents may
warrant a reassessment of how they are used in studies which evaluate
prediction accuracy, since socioeconomic data represent the Region's most
frequent sources of inaccurate predictions.
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-38-
VII. FURTHER STUDIES
This methodology could be used for further studies involving EIS's. Such
a study could focus on the accuracy of predictions made for a certain issue
in EIS's or on the overall accuracy of predictions for all issues. The
relatively large data base for existing conditions and the depth of data and
predictions in an EIS could prove to be very useful for the evaluation
methodology used for this study. A study of prediction accuracy in EIS's
could provide further data in evaluating the Region's and/or Nation's
effectiveness in NEPA review.
-------
Appendix A
Results and Discussion for Each Issue
-------
A-l
1. WATER QUALITY
Water quality impacts concern both surface water and groundwater.
Approximately 96 percent of the predictions made for water quality issues
are qualitative. Most water quality impact predictions referred to
relative improvements or impacts to surface and groundwater quality.
Of the total 92 predictions made for water quality issues, 48 were pre-
dictions made for surface water quality issues (44 present, 4 implied) and
44 predictions made for groundwater quality issues (20 present, 24 implied.
Impacts on surface water due to improved effluent quality and elimination
of plant bypasses to a stream and on stream quality are common predictions
in NEPA documents. The most common predictions concerning groundwater
quality impacts addressed the removal of failing septic tank systems.
Figure A-l illustrates the accuracy classification of water quality issues.
Figure A-l: Accuracy Classification of Water Quality Issues
B-4% (4)
A» "As predicted or better then predicted"
B* "Prediction not sustained"
O "No impact concerns, not an issue"
D* "Conclusion now would be premature"
-------
A-2
Table A-l below, presents a comparison of surface water and groundwater
quality sub-issues.
Table A-l: Accuracy Classification of Water Quality Sub-issues
A BCD Total
Surface water
Groundwater
Total
37
18
5T
(77%)
.(41%)
3
1
T
(6%)
.(2%)
2 (4%)
13 (30%)
T5~
6
12
T8~
(13%)
(27%)
48
44
A = "As predicted or better than predicted"
B = "Prediction not sustained"
C = "No impact concerns, not an issue"
D = " Conclusion now would be premature"
Whereas 60 percent of all water quality predictions are accurate, or as
predicted, the above table shows that while the coun.t of predictions are
almost evenly split between surface and groundwater predictions, there are
twice as many accurate surface water quality predictions as groundwater
quality predictions. Variability exists in the accuracy classification
of groundwater impacts. In more than half the NEPA documents for this
study (24 of 44), there was no prediction present for the groundwater sub-
issue. Nearly 30 percent of groundwater predictions were considered not
an issue and could not be evaluated due, for the most part, to the lack
of data or study of groundwater impacts. Where surface water quality pre-
dictions could not be evaluated, water sampling had yet to be completed
for the receiving stream.
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A-3
2. WETLANDS
Typically, predictions relating to impacts on wetlands have forecast whether
new facilities would be built in or adjacent to wetlands or whether dis-
charged effluent would affect wetlands. A total of 44 predictions (12 pre-
sent, 32 implied) were made for wetland issues. Though the breakdown of
quantitative/qualitative predictions for this issue shows that only 14
percent of wetland predictions were quantitative, six of twelve (50%) pre-
dictions actually recorded in the NEPA documents contained numeric values.
The remaining six were phrased as "no wetlands will be impacted," thus zero
acres of wetlands would be impacted (see Appendix B for specific predictions
and actual impacts). Figure A-2 presents the classification of accuracy
for the wetland issues.
Figure A-2: Accuracy Classification of Wetlands Predictions
B-7% (3)
A= "As predicted or better then predicted"
B' "Prediction not sustained"
O "No impact concerns, not an issue"
0* "Conclusion now would be premature"
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A-4
The percentage of wetland predictions considered "not an issue" was the
second highest for the twelve issues (energy was highest). This is due
to the fact that, in most cases, there were no wetlands in the area to be
impacted by a facility. Consistently, a large number (32 of 44) of implied
predictions indicate no impact to wetlands. None of the wetland predictions
could be classified as "could not be evaluated".
3. FLOODPLAINS
Predictions about floodplain impacts were very similar to those for wetland
impacts in that they concerned whether new facilities would be built in or
adjacent to floodplains. Concern for floodplain impacts is whether the
facilities created obstructions in the floodplain or increased flood eleva-
tions expanding the 100 year flood area. A total of 44 predictions (19
present, 25 implied) were tabulated for floodplain issues. Forty-three
(43) percent of the NEPA documents addressed floodplains. Of the 19 predic-
i
tions present, 5 (26%) were quantitative. Most floodplain impact predictions
are phrased as expected relative impacts rather than as specific quantities
to be impacted (see Appendix B for specific predictions and actual impacts).
Figure A-3 presents the classification of accuracy for floodplain issues.
Of the twelve environmental concerns, floodplain predictions had the third
highest percentage classified "as predicted of better than predicted"
behind Physical Environment and Air Quality. Here the percentage of predic-
tions that were "not an issue" may be indicative of the fact that, since a
major facilities plan includes siting alternatives which avoid and/or mitigate
impacts to floodplains, most projects evaluated did not involve impacts to
floodplains.
-------
A-5
Figure A-3: Accuracy Classification of Floodplain Predictions
B-4% (2)
D-2% (1)
A* "As predicted or better then predicted"
B* "Prediction not sustained"
C» "No impact concerns, not an issue"
D* "Conclusion now would be premature"
4. BIOTA
Predictions for the biota issue were concerned with potential impacts to
plants and animals due to construction and/or operation of a facility. This
environmental concern has three sub-issu»s: 1) terrestrial biota, 2) aquatic
biota, and 3) rare, endangered, or threatened species. Of the total 53
predictions for biota issues there were: 6 for the terrestrial sub-issue (4
present, 2 implied); 8 for the aquatic sub-issue (7 present, 1 implied); 4
for the rare, endangered, threatened species sub-issue (2 present, 2 implied);
and 35 for the generic issue of biota (25 present, 10 implied). Thus, the
majority of biota issue predictions were not defined to a sub-issue.
Nearly 91 percent of the biota predictions were qualitative. Most impact
predictions for biota issues concerned relative impacts to vegetation or
animal species. Most quantitative predictions were phrased as "no vegata-
-------
A-6
tion will be impacted" (Appendix B lists the specific predictions and actual
impacts). Predictions for the biota issue resulted in the fourth highest
percentage of accuracy("as predicted or better") of the twelve issues.
Figure A-4 illustrates the classification of accuracy for the biota issue.
Figure A-4: Accuracy Classification of Biota Predictions
B-4% (2)
A» "As predicted or better then predicted"
B» "Prediction not sustained"
Ca "No impact concerns, not an issue"
D* "Conclusion now would be premature"
5. SOCIOECONOMIC
Twenty (20) percent of environmental impact predictions contained in this
study referred to socioeconomic issues. Largely responsible for the abund-
ance of socioeconomic predictions is the number of indicators included in
the issue, such as population, growth, user charges, and employment for
which predictions were made. A total of 132 predictions (117 present, 15
implied) were made for socioeconomic issues. Fifty (50) percent were
quantitative.
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A-7
Figure A-5 illustrates the accuracy classification distribution for the
socioeconomic issue.
Figure A-5: Accuracy Classification of Socioeconomic Predictions
C-1% (1)
A» "As predicted or better then predicted"
B* "Prediction not sustained"
C= "No impact concerns, not an issue"
D» "Conclusion now would be premature"
Socioeconomic issues had the second lowest percentage of accurate predic-
tions and the highest percentage of inaccurate predictions. Because of
the number of socioeconomic sub-issues a table of the results is provided
to clarify the results. Table A-2 shows the accuracy classification for
the various sub-issues. Following the table, further findings of each socio-
economic sub-issue are provided.
-------
A-8
Table A-2: Accuracy of Socioeconomic Sub-Issue Predictions
Sub-issue
Employment
User Charge
Land-Use
Population
Property Values
Secondary Growth
Total
Quant.
1
12
10
2
1
3
29
A = "As predicted or
B = "Prediction not
Accuracy
A
Qua! .Total
7 8
4 16
17 27
3 5
2 3
8 11
Quant.
0
5
0
4
0
0
41 70 9
Code
B
Qual.
0
4
0
2
0
3
9
Total
0
9
0
6
0
3
Quant
0
0
0
0
0
0
18 0
C
.Qual
0
0
0
1
0
0
1
.Total
0
0
0
1
0
0
Quant
1
1
1
23
0
2
1 28
0
.Qua!
5
3
3
1
0
3
15
.Tot
2
4
better than predicted"
sustained"
C = "No impact concerns, not an issue"
D = "Conclusion now
would be premature
II
0 Employment
Employment predictions in this study primarily relate to needs for additional
staff to operate a wastewater treatment facility. This sub-issue was addressed
in 14 of 44 projects Of the 14 predictions, 2 (14%) were quantitative predic-
tions. Six predictions classified "could not be evaluated," relate to future
employment projections, within a municipality for the 20-year planning period,
for which assessments at this time would be premature.
0 User Charges
Before 1979, less emphasis was placed on highlighting projected user fees--
and the like—in NEPA documents. Consequently, the results show that user
fees were highlighted in 29 of 44 study documents (25 present, 4 implied).
Sixty-two (62) percent of the predictions were quantitative and forecasted
average household dollar costs, while the remaining qualitative predictions
stated costs as an expected increase or decrease. Construction costs may
-------
A-9
change due to weather, time expected, site problems, labor, and industrial
market trends. This fact may account for the finding that fifty (50) per-
cent of all innaccurate predictions ("prediction not sustained") for socio-
economic issues were for user charges.
0 Land-use
Predictions concerning the land-use primary addressed changes in land-use of
facility sites or zoning changes prompted by the wastewater treatment project.
Approximately 87 percent of land-use predictions for facility sites were
accurate.
0 Population
Facilities planning takes into account 20-year population projections for the
area. These figures, prepared by the responsible State agency, are often
reported in NEPA documents. Eighty-one (81) percent of population predictions
were quantitative, which indicates that in some cases only a general pre-
diction about the expected change in population was made.
Population predictions represented the largest percentage (18%) of all sub-
issues that "could not be evaluated". This is due to the fact that, i-n most
cases, it is premature to evaluate a 20-year projection when the projections
were made less than 20 years ago.
0 Property Values
Predictions concerning the potential impact of a project on property values
were only addressed for 3 projects in the study. All predictions made were
accurate.
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A-10
0 Secondary Growth
A concern for some projects was the potential for a facility to induce develop-
ment in the planning area. Predictions for this sub-issue were addressed in
19 projects. The majority of the predictions were qualitative, and a majority
were found to be accurate.
0 Summary of Socioeconomic Sub-issues
As presented in Figure A-5, the low percentage of accurate ("as predicted or
better than predicted") predictions can be attributed to the large percentage
of predictions that could not be evaluated. Many predictions concerned a
20-year planning period yielding predictions that would be better examined
at the conclusion of the planning period. The high percentage of inaccurate
("prediction not sustained) predictions is probably due to a significant
reliance on quantitative measures and the fact that cost estimate figures
presented in facilities planning are susceptible to changes in the economy
between the planning, environmental review, and construction phases.
Socioeconomic data were based on population and economic data developed by
agencies other than USEPA. Unlike the other predictions that have been
examined among NEPA documents, Socioeconomic data are typically based on
records for broad applications by the U.S. Census Bureau and State Demographic
Centers. Socioeconomic data were also used from 208 Planning Agencies but
when closely examined could not be readily distinguished from that of any
other Socioeconomic data source.
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A-ll
6. AGRICULTURE
Predictions about the impacts of Construction Grants projects on agricultural
land appeared in many early NEPA documents and virtually all of the more
recent ones. The issue is related to both direct impacts of site selection
and facility construction in terms of lost agricultural land as well as in-
direct or induced effects brought about by land development or sludge land
application. A total of 44 predictions (21 present, 23 implied) were made
for agricultural issues. Only 20 percent of the predictions were quantita-
tive, stating the number of acres expected to be impacted. The remaining
predictions were qualitative and reflected a statement of whether agricultural
lands would be impacted. Figure A-6 presents the classification of accuracy
for agriculture predictions.
Figure A-6: Accuracy Classification of Agriculture Predictions
B-2% (1)
A= "As predicted or better then predicted'
B= "Prediction not sustained"
C= "No impact concerns, not an issue"
D= "Conclusion now would be premature"
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A-12
The percentage of accuracy ("as predicted or better") for agriculture is
consistent with the general trend of accuracy for all issues (63%, as dis-
cussed later). The percentage of predictions considered "not an issue" was
third highest. This is reflected by the large number of projects (23) for
which a prediction was implied. That is, in more than half of the projects,
impacts to agriculture were not considered an issue that needed to be tran-
scribed to a NEPA document for public notice. •
7. PHYSICAL ENVIRONMENT
Predictions of impacts to the physical environment from Construction Grants
projects were related to effects on topography, soils and aesthetic values.
In many cases, impacts on the physical environment were predicted to be
short-term impacts from construction practices that should be mitigated as
much as possible. Impacts due to erosion are of particular concern since
construction activities may cause these water pollution abatement projects
themselves to become non-point sources of water pollution. A total of 49
predictions (32 present, 17 implied) were made for this issue. Eight (8)
percent of the predictions were quantitative. Most predictions concerning
the physical environment deal with qualitative impacts, most of which include
mitigative measures to reduce the potential impacts. Figure A-7 presents
the classification of accuracy for physical environment predictions.
Physical'Environment issues had the highest percentage of accuracy("as
predicted or better"). None of the issues could be classified as worse
than predicted.
-------
A-13
Figure A-7: Accuracy Classification of Physical Environment Predictions
D-4% (2)
A» "As predicted or better then predicted"
B* "Prediction not sustained"
Ca "No impact concerns, not an issue"
D» "Conclusion now would be premature"
8. CULTURAL RESOURCES
Cultural resource predictions concerned on the potential of facility con-
struction impacts on historical buildings and/or archaeological sites in
an area. The prediction is based on an evaluation provided by USEPA in
consultation with the State Historic Preservation Officer (SHPO). A
prediction concerning cultural resource impacts was present in 30 NEPA
documents for this study.
Fifty-five (55) percent of the predictions were quantitative predictions,
most of which were phrased as "no impacts to cultural resources will occur."
Figure A-8 presents the classification of accuracy for cultural resource
issues.
-------
A-14
Figure A-8: Accuracy Classification of Cultural Resource Predictions
D-2% (1)
A- "As predicted or better then predicted"
B» "Prediction not sustained"
C* "No impact concerns, not an issue"
0* "Conclusion now would be premature"
This issue was one of three for which none of the predictions were innaccu-
rate("prediction not sustained"). The percentage of accuracyC'as predicted
or better") is the third highest of all issues which is probably due to
the quality of the SHPO data base or field surveys done in advance.
9. SOLID WASTE
Solid waste predictions addressed in NEPA documents usually concerned sludge
management and referred to both land application and landfilling of sludge.
Many of the early NEPA documents made no predictions relating to solid
waste issues, but virtually all later documents contained some reference to
solid waste. Of the total of 45 predictions (25 present, 20 implied), only
11 percent were quantitative. Figure A-9 presents the accuracy classifica-
tion for solid waste predictions.
-------
A-15
Figure A-9: Accuracy Classification of Solid Waste Predictions
A» "As predicted or better then predicted"
B» "Prediction not sustained"
O "No impact concerns, not an issue"
0* "Conclusion now would be premature"
The relatively high percentage of predictions that were "not an issue"
indicates that for several projects no sludge was generated by the
selected process or the issue was not a concern of the NEPA public
notice documents.
10. ENERGY
Most predictions on energy issues relate to energy use for the operation
of facilities built with Federal Construction Grants. Predictions and find-
ings of energy use focused on expected and actual energy use in new faci-
lities. NEPA document predictions are stated in terms of fuel use,
energy consumption, electricity use, or all of these. This issue was
addressed in 14 projects. Figure A-10 presents the classification of
accuracy for the energy issue.
Energy predictions resulted in the lowest accuracy percentage for "as pre-
dicted or better". The percent of predictions classified "not an issue,"
was highest of all environmental concerns. This clearly shows that energy
-------
A-16
Figure A-10: Accuracy Classification of Energy Predictions
B-5% (2)
A» "As predicted or better then predicted"
B* "Prediction not sustained"
O "No impact concerns, not an issue"
D= "Conclusion now would be premature"
predictions were rarely extracted from the operational calculations of
wastewater treatment plans.
11. AIR QUALITY
Predictions relating to the impact of Construction Grant projects on air
quality are usually stated in terms of impacts due to dust or odors. Short
term impacts such as dust problems, were often expected to be mitigated
during construction. Either an increase or decrease in odors was a topic
of concern for treatment plant operations. Long term air quality impacts
were usually addressed by stating that the project conformed to the State
Implementation Plan for air quality.
A total of 44 predictions (29 present, 15 implied) were made for this
issue. Only 7 percent of the predictions were quantitative, mainly those
phrased as "no impacts to air quality." Figure A-ll presents the classifica-
tion of accuracy for air quality.
-------
A-17
Figure A-ll: Accuracy Classification of Air Quality Predictions
B-2% (1)
D-2% (1)
A» "As predicted or better then predicted"
B» "Prediction not sustained"
O "No impact concerns, not an issue"
D* "Conclusion now would be premature"
The second highest percent of accurate predictions ("as predicted or
better") was for air quality issues. The relatively high percentage of
"not an issue" indicates that the air quality issues are often not a
concern or are easily and effectively mitigated.
12. OTHER/RECREATION
Recreational impacts were addressed in 9 projects for this study. Figure
A-12 presents the classification of accuracy for recreation.
The percentage of predictions that were classified in Category D, "could
not be evaluated", is the second highest of all predictions. This is
due to data that was not readily available, as explained earlier, and
thus no comparison could be made during or following the field visit.
-------
A-18
Figure A-12: Accuracy Classification of Other/Recreation Predictions
C-7% (1)
A» "As predicted or better then predicted1
B» "Prediction not sustained"
C* "No impact concerns, not an issue"
D» "Conclusion now would be premature"
-------
APPENDIX B
FEDERAL STATUTES PERTINENT TO ENVIRONMENTAL
REVIEW OF CONSTRUCTION GRANTS PROJECTS
-------
B.I Federal Regulations
Table B-l lists major Federal statutes, regulations, and executive orders
that aay be expected to have influenced facility planning for construction
grant projects and the review of plans through the NEPA process during the
period of this study (1975 to 1982). This is a general list, and many of
these regulations vould not have affected the need to state potential
environmental impact predictions for each project.
The nev regulations listed in Table B-2 were especially relevant to the
assessment of impacts of construction grant projects. Most of these vere
cited, in some manner, in guidance documents distributed to Federal and many
State Construction Grants program staff for use in reviewing plans and other
documents submitted to program staff by grantees and grant applicants. This
list is excerpted from a more general one relating to all aspects of con-
struction grant review contained in EPA'a Office of Water Program Operations,
Regulation and Policy Matrix; A Guide to the Rules Governing Grants Awarded
Under the Construction Grants Program (December 1983). This list includes
Federal regulations relating specifically to the implementation of NEPA as it
relates to the Construction Grants program, in addition to closely related
regulated costs (including cost effectiveness analyses and industrial cost
recovery provisions).
NEPA documents rarely state which legal considerations formed the basis
of decisions to include or exclude certain types of environmental impact
issues, or decisions on methods of formulating predictions. Because of this,
there is no way of knowing exactly which statutes or regulations were actually
taken into account in preparing NEPA documents.
B.2 Program Guidance
The actual developments in the Federal regulatory climate that would most
directly affect the preparation of NEPA documents would have been guidance
documents, reflecting new Federal policies. These would be further affected
B-l
-------
TABLE B-l FEDERAL REGULATIONS IN EFFECT
WATER QUALITY
Surface Water
Groundvater
WETLANDS
FLOODPLAINS
BIOTA
SOCIOECONOMIC
Und Use
AGRICULTURAL
Clean Water Act of 1977, as amended (PL 95-523, 42 U.S.C. 300)
Federal Water Pollution Control Act of 1972
(PL 92-500, 33 USC 466 et. seq.)
USEPA. Regulations for the discharge of vastevater into the
waters of the U.S. (40 CFR Parts 122-125, 129, 133)
USEPA. Guidelines on discharge of dredged or fill materials
to navigable waters (40 CFR 230)
Rivers and Harbors Act of 1899 (33 U.S.C. 401 «8. seq.)
Clean Water Act, as amended (PL 95-523, 42 U.S.C. 300)
Resource Conservation and Recovery Act of 1976, as amended
(PL 94-580, 42 USC 6901)
Safe Water Drinking Act of 1974 (PL 93-523, 42 USC 300)
USEPA. "Statement of Procedures on Flood Management and
Wetlands Protection" (44 FR 1455, January 5, 1979)
Executive order 11990, Protection of Wetlands (42 FR 26961,
May 25, 1977)
Clean Water Act, Section 404 (33 U.S.C. 1251)
Rivers and Harbors Act, Section 10 (33 U.S.C. 401)
USEPA* "Statement of Procedures on Flood Management and
Wetlands Protection" (44 FR 1455, January 5, 1979)
US Water Resources Council. Floodplaln Management Guidelines for
Implementing Executive Order 11988 (43 FR 6030, Febuary 10, 1978)
Executive Order 11988, Floodplaln Management (42 FR 26951,
May 25, 1977)
Clean Water Act, Section 404 (33 U.S.C. 1251) ;
Flood Disaster Protection Act of 1973; National Flood Insurance
Act (42 USC 400 et. seq.)
Rivers and Harbors and Flood Control Act (33 USC 569 et. seq.) '
Rivers and Harbors Act of 1899 (33 U.S.C. 401 et. seq.)
Endangered Species Act Amendments of 1982 (16 U.S.C. 153 et. seq.)
Executive Order 11911, Preservation of Endangered Species
(41 FR 15683 April 13, 1976)
U.S. Dept. of Interior, Fish and Wildlife Service. Interagency
Cooperation Endangered Species Act of 1973 (50 CFR Pert 402)
Endangered Species Act of 1973, as amended
Marine Mammal Protection Act 1972 (16 U.S.C. 1361 et. seq.)
Wilderness Act of 1964, as amended (16 U.S.C. 1131)
Fish and Wildlife Coordination Act of 1934, 'as amended
(16 U.S.C. 661, 742; 43 CFR Part 17)
Federal Coastal Zone Management Act of 1972, as amended
(16 U.S.C. 1451)
U.S. Dept. of Agriculture. Land Use Policy (Reg. 9500-3,
March 22, 1983)
Agriculture and Food Act of 1981, Farmland Protection Policy
(PL 97-98, Dec. 22, 1981)
USEPA. Policy to Protect Environmentally Significant Agricultural
Lands (September 8, 1978)
-------
TABLE B-l FEDERAL REGULATIONS IN EFFECT (Continued)
PHYSICAL ENVIRONMENT
CULTURAL RESOURCES
SOLID WASTE
AIR QUALITY
NOISE
Wild tod Scenic River* Act of 1968 (16 U.S.C. 1274)
National Natural Landmark.* Program (36 C7R Part 1212; 45 FR 81184,
December 9, 1980)
Adviiory Council on Historic Preservation* Protection of Historic
and Cultural Properties (36 CFR Part 800)
Advisory Council on Historic Preservation. National Registration
Criteria (36 CFR Parts 63, 64, 66)
Executive Order 11593, Protection and Enhancement* of the Cultural
Environment (May 13, 1979)
Archaeological and Historic Preservation Act of 1974
(16 U.S.C. 469 et. seq.)
National Historic Preservation Act of 1966, as amended
(16 U.S.C. 470 et. seq.)
Historic Sites, Building and Antiquities Act of 1935
1984 Hazardous and Solid Waste Amendments (PL 98-616,
98 Stat. 3221, November 8, 1984)
Comprehensive Environmental Response, Compensation, and Liability
Act of 1980, as amended (PL 96-510)
Solid Waste Disposal Act of 1980 (PL 96-482)
Used Oil Recycling Act of 1980 (PL 96-463)
Quiet Communities Act of 1978 (PL 95-609)
Resource Conservation and Recovery Act (PL 94-580, October 21, 1976)
Solid Waste Disposal Act (42 U.S.C. 3251)
Clean Air Act Amendments of 1983 (PL 98-45, July 12, 1983)
Clean Air Act Amendments of 1981 (PL 97-23, July 17, 1981)
Clean Air Act Amendments of 1977 (PL 95-95, August 7, 1977)
Clean Air Act Amendments of 1970 (PL 91-604, December 31, 1970)
Clean Air Act (42 U.S.C. 1957 et. seq.)
Quiet Communities Act (PL 95-609 Section 2, November 8, 1978)
Noise Control Act of 1972 (PL 92-842)
1970 Noise Pollution and Abatement Act (PL 91-604)
B-3
-------
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by the administrative procedures through which nev policies and guidance vere
applied to individual projects at both the State and Federal levels, and would
be further Modified by each State's policies, laws, and regulations.
It is important to note that two very different kinds of "NEPA documents"
were examined together in this study, based on guidance in the Manual for
Evaluating Predicted and Actual Impacts of Construction Grants^Projects. The
purposes of the facilities plans and environmental reviews of the proposed
projects are very different from each other.
Initial reviews of plans were usually conducted by the States in EPA
Region V during the period of the study, and Environmental Assessments
reviewed by States apparently formed the basis for many of EPA's Negative
Declarations or Findings of No Significant Impact. The following analysis
takes into account Federal guidance and policy documents, which were also used
by the States.
Table B-3 presents a list of relevant Federal guidance documents issued
from 1973 to 1982 on environmental impact predictions and review for
Construction Grants projects. This list is also excerpted from a more general
compilation contained in EPA's Regulation and Policy Matrix (December 1983).
These guidance documents were written and distributed to ensure that
changes in Federal regulations would be implemented in a timely and uniform
manner by Federal (and State) Construction Grants Program operations. All of
these types of guidance contained instructions reflecting developments in the
application of NEPA procedures for evaluating specific kinds of environmental
impacts of construction grant projects.
B-10
-------
TABLE B-3 RELEVANT GUIDANCE DOCUMENTS ON ENVIRONMENTAL
IMPACT PREDICTIONS AND REVIEW FOR CONSTRUCTION GRANT PROJECTS, 1975-1982
May 1973 - Hay 1976
"Program Guidance Memoranda" (68 sent out over entire 3-year period)
February 1976
Handbook of Procedures - Construction Grants Program for Municipal Vastewater
Treatment Works (MCD-03).Revised 1967 handbook! to establisluuniform
national operating standards which can be readily adopted. Handbook was to be
applicable to grants processed as of July 1, 1975, and was to assist project
officers in reviewing grantee documents by explaining existing policies and
requirements.
July 1976 - December 1980
"Program Requirements Memoranda," (PRM) "Program Operation Memoranda," (POM)
and "Transmittal Memoranda" (TM)
- Program Requirements Memoranda conveyed program policies specifically
applicable to the Construction Grants Program (within and outside EPA)
- Program Operation Memoranda were internal communications explaining
"housekeeping" items
- Transmittal Memoranda were actually changes (insert replacement pages)
to the Handbook of Procedures (MCD-03)
Pall 1979 (Effective 1980)
Handbook of Procedures, Second edition, replaced the 1976 Handbook, reflecting
laws, regulations, and policies as of October 1979. The second edition was
needed to incorporate large changes in the Construction .Grants Program
resulting from the passage of the Clean Vater Act of 1977. (Became obsolete
with Clean Vater Act Amendments of 1981)
1981
Program Requirements Memoranda issued only on a fiscal-year basis to eliminate
confusion as to retroactive applicability of changes in requirements
March 1981
Facilities Planning 1981 (FRD-20)
Explained facilities planning requirements overall
July 1982
Construction Grants 1982 (CG-82) - Interim Final
Simplified construction grant requirements and ending the formal field
communication system; increased reliance on regulation for Federal
requirements, with more flexibility for States and EPA Regions for daily
operations. Revisions were based on the 1981 amendments to the Clean Vater
Act, and completely revised implementing regulations. Provided step-by-step
guidance for preparing and reviewing construction grant project documents.
B-ll
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