1
The
Economic
Impact
of
Proposed
Effluent
Treatment
Options
for
Production
of
Trout
Oncorhynchus
mykiss
in
Flow­
through
Tanks.

Carole
R.
Engle
and
Steve
Pomerleau
Aquaculture/
Fisheries
Center,
Mail
Slot
4912,
University
of
Arkansas
at
Pine
Bluff,
1200
North
University
Drive,
Pine
Bluff,
AR
71601.

Gary
Fornshell
University
of
Idaho
Extension,
246
3rd
Ave
E.
Twin
Falls,
ID
83301
Jeffrey
M.
Hinshaw
Department
of
Zoology,
North
Carolina
State
University,
455
Research
Drive,
Fletcher,
NC
28732.

Debra
Sloan
North
Carolina
Department
of
Agriculture
and
Consumer
Services
P.
O.
Box
1475,
Franklin,
NC
28744.

Skip
Thompson
North
Carolina
Cooperative
Extension
P.
O.
Box
308
Waynesville,
NC
28786
2
Issue
Outline
Code:
1
Legal
Authority/
Background
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
Excerpt
No:
1
INTRODUCTION
According
to
the
1998
Census
of
Aquaculture
(
NASS
2000),
the
U.
S.
trout
industry
consists
of
561
farming
operations
located
in
42
states.
Most
of
the
production
is
in
flow­
through
concrete
tanks;
however,
earthen
ponds
continue
to
be
used
by
some
farmers.
The
majority
of
the
farms
are
small,
family­
operated
businesses
with
average
sales
per
farm
of
$
129,473
nationally.
However,
the
largest
20%
of
trout
farming
operations
(
108)
account
for
over
85%
of
total
sales.
Idaho
is
the
leading
trout
producing
state
with
70­
75%
of
domestic
production.
North
Carolina
ranks
second
in
the
United
States
with
sales
that
accounted
for
8%
and
10%
of
total
U.
S
production
and
sales,
respectively
(
NASS,
2003).
Twenty­
one
(
37%)
of
the
57
commercial
trout
farms
in
production
in
North
Carolina
in
2002
were
located
in
Transylvania
County.
Approximately
816,000
kg
of
trout
were
produced
in
Transylvania
County
in
2002.

The
United
States
Environmental
Protection
Agency
(
EPA)
began
to
review
aquaculture
for
consideration
in
the
Effluent
Limitation
Guidelines
(
ELG)
program
in
1998.
The
ELG
rulemaking
effort
develops
technology­
based
standards
that
are
economically
achievable.
EPA
outlined
five
potential
regulatory
options
for
flow­
through
systems
in
the
proposal
that
was
published
in
2002
(
USEPA
2002)
(
Table
1).
Option
1
included
quiescent
zones,
sedimentation
basins,
best
management
practices
(
BMP)
plans,
and
compliance
monitoring
for
total
suspended
solids
(
TSS).
Option
2
included
a
drug
and
chemical
BMP
plan
in
addition
to
the
other
treatment
options
in
Option
1.
Option
3
included
solids
polishing
with
micro­
screen
filters
and
weekly
compliance
monitoring
for
total
phosphorus
in
addition
to
the
Option
2
treatments.
EPA
proposed
Options
1,
2
and
3
for
large
flow­
through
facilities
that
have
an
annual
production
above
215,909
kg
(
475,000
lb)
of
trout,
but
proposed
only
Option
1
for
medium
facilities
with
an
annual
production
between
45,455
kg/
yr
(
100,000
lb/
yr)
and
215,909
kg/
yr
(
475,000
lb/
yr).
No
treatment
options
were
proposed
for
facilities
producing
less
than
45,455
kg/
yr
(
100,000
lb/
yr)
because
it
was
clear
early
in
the
process
that
these
farm
sizes
could
not
afford
treatment
of
effluents.

EPA
followed
with
publication
of
a
Notice
of
Data
Availability
(
NODA)
on
December
29,
2003.
In
the
NODA,
two
additional
options
(
Options
A
and
B)
were
included.
Options
A
and
B
restructured
the
combinations
previously
divided
into
Options
1,
2,
and
3
and
added
BMP
plans
on
escape
prevention
in
addition
to
INAD
reporting
requirements.

Quiescent
zones
(
considered
in
regulatory
Options
1
and
A)
are
settling
areas
for
solids
in
the
lower
portion
of
tanks.
Cultured
fish
are
excluded
from
quiescent
zones
with
a
screen
in
the
upper
side
of
the
zone
to
prevent
disturbing
settled
solids.
Quiescent
zones
may
be
cleaned
with
a
3
vacuum
hose
attached
to
the
drain.
Vacuumed
solids
are
then
transferred
to
a
sedimentation
basin.
Suspended
solids
settle
on
the
bottom
of
the
sedimentation
basins.
Accumulated
solids
are
removed
periodically
from
the
settling
basins
with
a
vacuum
tank
or
a
front­
end
loader
and
disposed
of
through
land
application.
Solids
control
BMP
plans
(
considered
under
Options
1,
2,
3,
and
B)
would
require
the
farm
manager
to
develop
a
BMP
plan
that
presents
a
series
of
sitespecific
activities
to
control
the
release
of
solids.
These
activities
include
specification
of
feeding
methods,
description
of
proper
pollution
control
technologies
and
equipment,
proper
operation
and
maintenance
of
equipment,
a
cleaning
schedule,
training
of
personnel,
and
record
keeping.
Compliance
monitoring
for
TSS
requires
labor
and
material
for
weekly
monitoring.
An
8­
h
composite
water
sample
would
be
collected
and
delivered
to
a
laboratory
for
analysis.
A
drug
and
chemical
BMP
plan
was
proposed
for
Options
2,
3,
and
A
to
document
the
use
of
drugs
and
chemicals.
Each
farm
manager
would
be
required
to
develop
a
BMP
plan
that
presents
a
series
of
site­
specific
activities
to
control
the
inadvertent
spillage
or
release
of
drugs
and
chemicals.

Microscreen
filters
were
included
in
Options
3
and
B
to
achieve
additional
solids
removal
with
wastewater
treatment
technology.
The
microscreen
filters
would
be
used
to
reduce
solids
discharged
from
sedimentation
basin
effluents.
Filters
would
consist
of
a
fine
screen
(
60­
90
microns)
fitted
to
a
rotating
drum
and
equipped
with
an
automatic
backwash
system
that
removes
solids
collected.

Response:
Not
a
comment
on
the
rule.
Excerpt
contains
a
description
of
the
industry
based
on
the
USDA
Census
of
Aquaculture,
the
importance
of
Idaho
and
North
Carolina
operations
as
the
largest
and
second
largest
raisers
of
trout,
and
a
review
of
the
options
considered
by
EPA
at
proposal
and
Notice
of
Data
Availability.

Issue
Outline
Code:
1
Legal
Authority/
Background
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
Excerpt
No:
2
While
there
have
been
a
number
of
studies
on
effluent
treatments
in
aquaculture,
few
studies
have
focused
on
the
economic
feasibility
of
the
specific
effluent
treatment
options
proposed
by
EPA.
Engle
and
Valderrama
(
2003)
showed
that
settling
basins
were
not
economically
feasible
for
use
in
pond
aquaculture.
Wui
and
Engle
(
2004),
using
a
mixed
integer
linear
programming
model,
found
that
the
only
feasible
treatment
alternatives
for
hybrid
striped
bass
effluents
were
not
draining
and
not
flushing
ponds.
However,
the
production
risks
of
not
flushing
or
draining
hybrid
striped
bass
ponds
have
not
been
well
documented.
Engle
and
Valderrama
(
in
review)
showed,
4
with
a
mathematical
programming
model,
that
implementation
of
BMPs
on
shrimp
farms
can
result
in
changes
in
net
revenue.
The
net
revenue
changes
were
both
positive
and
negative
and
resulted
from
changes
in
production
practices,
cash
flow,
and
increased
costs
of
financing
shrimp
production.

Response:
Not
a
comment
on
the
rule
because
the
studies
concern
pond
systems
which
are
not
within
the
scope
of
the
rule.

Issue
Outline
Code:
13B
Methodological
Overview
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
Excerpt
No:
3
Analyses
of
both
the
farm­
level
and
local
economic
impacts
are
important
to
evaluate
the
overall
effect
of
imposing
additional
treatment
technologies
on
aquaculture
farms.

Response:
EPA
concurs
and
conducted
an
economic
impact
analysis
that
examined
the
effects
of
additional
pollution
control
costs
on
enterprises,
facilities,
and
companies,
direct
impacts
on
employment
and
productions,
associated
local
impacts,
such
as
the
change
in
unemployment
rate,
farm
financial
health,
and
borrowing
capacity.
See
response
to
comment
70245­
5
for
details.

Issue
Outline
Code:
1
Legal
Authority/
Background
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
Excerpt
No:
4
Kaliba
et
al.
(
2004)
developed
an
IMPLAN
analysis
of
the
economic
impact
of
the
trout
industry.
The
trout
industry
in
Transylvania
County,
North
Carolina,
generated
about
$
9
million
in
economic
output,
created
201
jobs,
generated
$
3
million
in
labor
income,
and
$
0.9
million
in
tax
revenue
in
2002.
This
economic
activity
is
particularly
important
in
a
county
like
Transylvania
County,
where
economic
prosperity
depends
upon
locally
available
jobs
and
diversification
of
economic
activities.
5
Response:
Not
a
comment
on
the
rule.
Excerpt
describes
analysis
of
the
economic
importance
of
the
trout
industry
to
Transylvania
County,
North
Carolina.
EPA
concurs
that
aquaculture
may
play
an
important
role
in
local
economics
and,
accordingly,
has
conducted
an
economic
impact
of
the
rule.
See
response
to
comment
70249­
5
for
details.

Issue
Outline
Code:
1
Legal
Authority/
Background
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
Excerpt
No:
5
The
objective
of
this
study
was
to
evaluate
the
economic
feasibility
of
the
proposed
effluent
treatment
options
for
trout
flow­
through
systems.
The
analysis
focused
on
trout
farms
in
Idaho
and
North
Carolina
that
produce
more
than
45,455
kg/
yr
(
100,000
lb/
yr).

Response:
Not
a
comment
on
the
rule.
It
is
a
statement
that
the
study
focuses
on
in­
scope
facilities
(
e.
g.,
flow­
through
systems
with
production
>
100,000
lb/
yr.

Issue
Outline
Code:
1
Legal
Authority/
Background
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
Excerpt
No:
6
MATERIALS
AND
METHODS
Surveys
of
trout
farms
in
Transylvania
County,
North
Carolina,
and
Idaho
were
conducted
in
2003.
Survey
data
were
collected
from
13
of
the
21
farms
(
62%)
in
Transylvania
County,
NC.
The
questionnaire
solicited
information
on
resource
inputs
and
production
levels
for
2002.
These
included
trout
marketing,
sales,
and
variable
costs.
Variable
cost
data
collected
included:
transportation
costs,
labor
costs,
chemical
and
oxygen
costs,
diseases
and
treatment
costs,
electricity,
fuel
and
lubricant
costs,
stocking
and
feeding
costs,
waste
management
and
effluent
monitoring
costs,
repair
and
maintenance
costs,
and
overhead
costs.
Items
included
in
the
6
overhead
cost
were:
telephone,
farm
insurance,
legal,
accounting,
office
supplies
and
consumables,
interest
on
capital,
land
lease
costs,
and
nets,
boots,
waders
and
other
miscellaneous
purchases.
Similar
production
and
financial
information
was
also
collected
from
eight
trout
farms
in
Idaho
by
personal
interviews
with
the
farm
owner
or
manager.

Base
farm
scenarios
were
developed
that
included:
1)
medium­
sized
farm
in
North
Carolina
producing
68,182
kg/
yr
(
150,000
lb/
yr);
2)
medium­
sized
farm
in
Idaho
(
90,909
kg/
yr;
200,000
lb/
yr);
and
3)
large­
sized
farm
in
Idaho
(
1,136,364
kg/
yr;
2,500,000
lb/
yr).
These
base
scenarios
were
selected
by
choosing
the
most
commonly
observed
farm
sizes
in
the
survey
data
within
the
production
level
categories
for
which
USEPA
proposed
treatment
options.
Different
management
practices
used
in
Idaho
as
opposed
to
North
Carolina
required
development
of
separate
base
scenarios.
No
large
farm
scenario
was
analyzed
for
North
Carolina
because
no
farms
operating
in
Transylvania
County
have
production
levels
greater
than
215,909
kg/
yr
(
475,000
lb/
yr).

Response:
This
is
the
first
point
of
divergence
between
the
Engle
et
al.
and
EPA
economic
analyses.
Engle,
et
al
develop
three
scenarios
to
represent
13
trout
farms
in
North
Carolina
and
8
trout
farms
in
Idaho
from
which
they
collected
data.
In
contrast,
the
EPA
methodology
would
have
created
21
scenarios,
one
with
facility­
specific
data
for
each
farm
in
the
study.
Where
EPA
has
the
ability
to
do
so,
the
preferred
approach,
and
the
approach
consistent
with
prior
effluent
guidelines
rules,
is
to
use
facility­
specific
costs,
revenues,
and
pollution­
control
costs
as
a
more
precise
method
of
evaluating
the
impacts
of
pollution
control
options.

Issue
Outline
Code:
13B
Methodological
Overview
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
Excerpt
No:
7
Enterprise
budgeting
techniques
(
Kay
and
Edwards
1994)
were
used
to
evaluate
the
effect
of
imposing
effluent
treatment
options
proposed
by
USEPA
on
the
trout
farm
size
scenarios
selected.
Enterprise
budgets
were
developed
first
without
the
proposed
treatment
options.
Production
characteristics,
management
practices,
and
prices
from
the
survey
results
were
used
to
develop
estimates
of
annual
costs
and
returns
using
standard
budgeting
techniques
(
Kay
and
Edwards
1994).
Costs
associated
with
the
treatment
options
proposed
by
EPA
were
added
to
the
budgets
and
changes
in
net
returns
were
then
measured.
Additional
scenarios
were
developed
to
reflect
both
farm
businesses
with
no
land
financing
costs
and
those
with
land
financing
costs.

Response:
This
is
a
second
point
of
divergence
between
the
Engle
et
al.
and
the
EPA
studies.
Engle
et
al.
7
mention
that
their
study
uses
"
standard
budgeting
techniques"
to
develop
three
model
farms
for
analysis.
The
authors
do
not
specify
whether
they
choose
a
"
representative"
farm
in
each
scenario
and
then
use
all
parameters
from
those
representative
farms,
whether
they
consistently
use
calculated
average
values
for
each
parameter
in
the
model
farm,
or
whether
the
average
values
are
modified
slightly
to
generate
a
coherent
set
of
costs
and
returns.
(
The
difference
of
the
averages
is
not
the
same
as
the
average
of
the
differences,
that
is,
the
difference
between
the
average
total
cost
and
the
average
total
revenues
need
not
match
the
average
taken
of
the
facility­
specific
earnings.)
In
contrast,
the
EPA
approach
is
to
use
facility­
specific
matched
sets
of
costs,
revenues,
and
pollution
control
costs
to
evaluate
impacts.
EPA
also
notes
that
Engle
et
al.
do
not
remove
expected
baseline
closures
prior
to
generating
any
values
and/
or
characterizing
"
representative"
facilities.
This
assumption
can
lead
to
significant
differences
in
results
between
EPA
and
Engle
et
al.

Early
in
the
rulemaking
process,
EPA
also
examined
and
decided
not
to
use
an
enterprise
budget
approach
to
evaluating
impacts,
see
DCN
20153,
ERG,
2001,
"
Lessons
Learned
from
Sensitivity
Analysis
and
Enterprise
Budgets"
and
DCN
20189,
ERG,
2001.
"
Enterprise
Budgets
and
Survey
Data:
Aquatic
Animal
Production."

Issue
Outline
Code:
10
Option
Costs
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
Excerpt
No:
8
Both
"
low"
and
"
high"
cost
scenarios
were
developed
to
account
for
the
range
of
implementation
costs
resulting
from
variation
in
site­
specific
conditions.
For
example,
compliance
monitoring
of
TSS
can
be
accomplished
either
by
hand
or
by
purchasing
an
automatic
composite
sampler.
Installation
of
quiescent
zones
may
or
may
not
result
in
reduced
production
depending
upon
tank
configuration.
Similarly,
construction
of
offline
settling
ponds
may
require
destruction
of
existing
tanks
if
no
additional
level
land
is
available.
For
Option
1,
the
low
cost
scenario
included:
solids
control
BMP
plan,
compliance
monitoring
of
TSS
done
by
automatic
composite
sampler,
quiescent
zones
without
negative
effect
on
production,
offline
settling
pond
constructed
without
having
to
destroy
tanks
and
emptied
with
a
vacuum
tank,
and
no
additional
land
purchased
for
disposal
of
solids.
The
high
cost
scenarios
for
Option
1
included:
solids
control
BMP
plan,
compliance
monitoring
of
TSS
done
by
hand,
quiescent
zones
that
proportionally
reduce
production,
replacing
existing
tanks
with
offline
settling
ponds
because
no
extra
land
was
available,
offline
settling
pond
emptied
with
a
front­
end
loader,
and
additional
land
purchased
for
disposal
of
the
solids.
No
site­
specific
variation
in
costs
was
considered
for
Option
2
because
no
evidence
for
such
variation
was
found.
Thus,
no
distinction
was
made
in
the
analysis
of
Option
2
for
low
or
high
cost
variations.
For
Option
3,
the
low
cost
scenarios
were
based
on
EPA's
cost
8
assumptions
(
EPA
2002)
while
the
high
cost
scenarios
were
based
on
comments
of
the
Trout
Subgroup
of
the
Joint
Subcommittee
on
Aquaculture's
Aquaculture
Effluents
Task
Force
related
to
cost
variations
observed
in
the
trout
industry
(
TSAETF
2003).
Option
A
included
primary
settling,
BMP
plans
for
drugs
and
chemicals,
and
escape
prevention,
and
reporting
for
INADS
and
extra
label
drug
use.
Option
B
included
those
items
in
A
in
addition
to
either
a
BMP
plan
for
solids
control
or
solids
polishing
with
a
microscreen
filter.
Both
EPA
and
AETF
estimates
of
costs
associated
with
microscreens
were
included.

Response:
[
Engineering
response
needed.]

A
third
point
of
divergence
between
the
Engle
et
al.
and
EPA
studies
is
the
consideration
of
pollution
control
features
already
in
place
at
a
facility
("
treatment
in
place").
Engle
et
al.
assumes
that
the
model
facilities
incur
costs
for
all
components
of
an
option
while
EPA
based
its
sitespecific
cost
estimates
on
the
existing
treatment
in
place
at
facilities
that
received
a
detailed
questionnaire.
EPA
characterizes
baseline
conditions
using
existing
compliance
levels
and
treatment
in
place
(
FR
68:
75068­
75105
and
FR67:
57872­
57928).
This
approach
is
consistent
with
past
effluent
guidelines
and
EPA's
Guidelines
for
Preparing
Economic
Analyses
(
USEPA,
Guidelines
for
Preparing
Economic
Analysis,
EPA
240­
R­
00­
003,
September
2000,
Section
5.3.2)
and
Office
of
Management
and
Budget
(
OMB)
guidelines.
OMB
guidelines
state
that
"...
the
baseline
should
be
the
best
assessment
of
the
way
the
world
would
look
absent
the
regulation
...
it
may
be
reasonable
to
forecast
that
the
world
absent
the
regulation
will
resemble
the
present."
(
OMB.
OMB
Circular
A­
4,
Regulatory
Analysis,
Appendix
D
in
Informing
Regulatory
Decisions:
2003
Report
to
Congress
on
the
Costs
and
Benefits
of
Federal
Regulations
and
Unfunded
Mandates
on
State,
Local,
and
Tribal
Entities.
2003.).
This
means
that
if
a
facility
already
has
option
components
in
place
by
2001
(
the
most
recent
year
in
the
detailed
questionnaire),
EPA
does
not
assign
costs
for
those
components
to
the
facility.
For
example,
if
a
facility
has
primary
settling
(
a
component
that
occurs
in
all
options
under
consideration),
it
would
not
be
expected
to
incur
the
costs
for
primary
settling.)
It
should
also
be
noted
that
the
final
rule
focuses
on
BMPs
and
provides
significant
flexibility
(
and
lower
costs)
to
facilities
in
meeting
the
requirements
of
the
final
rule.

Issue
Outline
Code:
13B
Methodological
Overview
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
Excerpt
No:
9
Since
production
characteristics,
costs,
and
prices
vary
through
time
and
from
farm
to
farm,
a
stochastic
Monte
Carlo
simulation
model
was
used
to
assess
the
effect
of
variations
in
various
1
Use
of
a
particular
brand
name
does
not
imply
endorsement.

9
budget
parameters
on
net
returns.
The
enterprise
budgets
developed
were
based
on
typical
farm
values
observed
in
the
survey
data.
Crystal
Ball
®
1
(
Decisioneering,
Inc.,
Denver,
Colorado),
an
add­
on
program
to
Microsoft
Excel,
was
used
to
substitute
probability
distributions
for
the
single
values
used
in
the
enterprise
budget
worksheets.
Triangular
distributions
characterized
by
a
most
likely,
a
minimum,
and
a
maximum
value
were
used
for
most
assumptions.
The
model
generated
stochastic
fluctuations
in
selected
variables
and
calculated
the
probability
of
achieving
positive
net
returns.
Simulations
of
1,000
iterations
per
scenario
were
run.

Response:
Methodological
description,
not
a
comment
on
the
rule.
EPA
notes
that
Monte
Carlo
analysis
traditionally
is
conducted
with
consideration
of
correlations
among
random
parameters;
it
is
not
clear
that
efforts
were
made
to
reject/
accept
potential
for
correlations.
Failure
to
insert
suggested
correlations
can
lead
to
greater
ranges
of
projected
earnings.
It
is
also
not
clear
if
the
study
relied
on
standard
errors
or
standard
errors
of
the
mean
results
when
presenting
results.

Before
the
detailed
questionnaire
data
were
available,
EPA
also
examined
enterprise
budgets
and
a
sensitivity
analysis
approach
based
on
parameter
values
and
ranges
supplied
by
the
Joint
Subcommittee
on
Aquaculture,
Aquaculture
Effluent
Task
Force,
see
DCN
20153,
ERG,
2001,
"
Lessons
Learned
from
Sensitivity
Analysis
and
Enterprise
Budgets"
and
DCN
20189,
ERG,
2001.
"
Enterprise
Budgets
and
Survey
Data:
Aquatic
Animal
Production."

Issue
Outline
Code:
13B
Methodological
Overview
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
Excerpt
No:
10
The
enterprise
budgets
were
used
to
construct
mixed
integer
programming
models
for
North
Carolina
farms
with
capacity
to
produce
68,182
kg/
yr
(
150,000
lb/
yr)
and
for
Idaho
farms
with
capacities
of
both
90,909
kg/
yr
(
200,000
lb/
yr)
and
1,136,364
kg/
yr
(
2,500,000
lb/
yr).
The
objective
function
of
the
model
was
to
maximize
net
returns
above
variable
costs.
Constraints
included
supply
and
demand
balances
for
foodsize
trout
and
for
purchased
inputs.
The
North
Carolina
model
included
production
and
sales
activities
for
both
food
trout
and
recreational
trout
sales.
Resource
availability
constraints
and
non­
negativity
constraints
were
included.
Effluent
treatment
option
constraints
were
integer
variables
including
each
component
of
the
proposed
options.
The
model
was
formulated
by
aggregating
all
equations
so
that
the
model
maximizes
net
returns
above
variable
costs
after
imposing
the
various
treatment
options
subject
to
constraints
including
integer
variable
constraints.
10
Response:
Description
of
methodology,
not
a
comment
on
the
rule.

Issue
Outline
Code:
13A
Description
of
the
Industry
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
Excerpt
No:
11
RESULTS
AND
DISCUSSION
The
response
rate
of
the
structured
questionnaire
in
Transylvania
County
in
North
Carolina
was
81%.
Farms
had
a
median
production
level
of
66,000
kg/
yr,
ranging
from
1,000­
204,500
kg/
yr
(
Table
2).
Median
market
price
of
food
trout
was
$
2.42/
kg
($
1.10/
lb).
Major
expenses
on
trout
farms
were
the
variable
costs
of
fingerlings,
feed,
labor,
management,
and
the
fixed
depreciation
costs.
Fingerlings
cost
$
0.07
each,
but
ranged
from
$
0.07­$
0.17
depending
upon
the
size
purchased.
Feed
conversion
ratios
ranged
from
1.04­
1.55
with
a
median
of
1.20.
Feed
prices
ranged
from
$
0.66­$
0.79/
kg
with
a
median
price
of
$
0.70/
kg.
Depreciation
costs
ranged
from
$
6,000­$
18,000/
farm.

Farmers
interviewed
in
Idaho
had
a
median
production
of
1.2
million
kg/
yr,
ranging
from
27,000
kg/
yr
to
1.2
million
kg/
yr.
Idaho
trout
farmers
purchased
eggs
instead
of
fingerlings
at
a
median
cost
of
$
0.015
each.
Feed
conversion
ratios
were
similar,
but
Idaho
feed
costs
were
slightly
lower
than
in
North
Carolina.
Depreciation
costs
per
farm
increased
with
the
larger
farm
sizes
in
Idaho.

Table
2.
Selected
results
of
surveys
of
trout
farms
in
Transylvania
County,
North
Carolina
and
Idaho.
Item
Unit
North
Carolina
(
68,182
kg/
yr
farm)
Idaho
(
90,909
kg/
yr
farm)
Median
Range
Median
Range
Farm
size
kg/
yr
66,000
1,000­
204,500
1,200,000
27,000­
1,136,364
Market
price
food
trout
$/
kg
2.42
2.33­
3.04
1.76
1.54­
1.83
Seed
costa
$
each
0.07
0.07­
0.17
0.015
0.015­
0.02
Feed
FCRb
1.20
1.04­
1.55
1.20
1.20­
1.55
Price
$/
kg
0.70
0.66­
0.79
0.64
0.62­
0.66
Labor
h
1,680
1,470­
2,100
1,400
1,400­
2,400
Management
h
720
630­
1,800
600
600­
3,600
11
Depreciation
$
12,000
6,000­
18,000
16,000
8,000­
24,000
aNorth
Carolina
farmers
mostly
purchased
fingerlings
while
Idaho
farmers
purchased
eggs.
bAdapted
from
EPA's
detailed
survey
aggregated
values.
cLabor
costs
include
both
paid
labor
and
unpaid
(
family)
labor.

Response:
EPA
compared
the
data
sets
used
by
Engle
et
alia
to
the
EPA
in­
scope
population
(
i.
e.,
>
100,000
lb/
yr).
Based
on
the
information
presented
in
Engle
et
alia,
Table
2,
EPA
developed
Table
1
(
below)
and
made
the
following
observations.
For
North
Carolina,
the
smallest
farm
in
the
survey
produces
1,000
kg/
yr.
This
farm
is
so
small
that
it
does
not
qualify
to
be
a
CAAP
and
is
not
within
the
scope
of
the
rule.
By
the
median
value,
we
have
a
farm
that
is
large
enough
to
be
within
the
scope
of
the
rule.
At
a
minimum,
one
of
13
or
7.7
percent
of
the
NC
farms
are
out
of
scope
of
the
rule.
At
most,
six
of
13
or
nearly
half
the
sample
might
be
outside
the
scope
of
the
rule.
It
is
therefore
not
clear
how
many
facilities
are
used
in
the
analysis.

The
Idaho
data
set
has
eight
observations.
The
smallest
farm
produces
27,000
kg/
yr
so,
although
it
is
a
CAAP,
it
is
not
within
the
scope
of
the
rule.
It
is
not
clear
how
the
median
value,
reported
as
1.2
million
kg/
yr,
can
exceed
the
maximum
value
reported
as
1.1
million
kg/
yr
[
sic].
The
average
of
observation
#
4
and
observation
#
5
is
1.2
million
kg/
yr,
so
the
most
likely
situation
is
that
both
observations
are
close
to
1.2
million
kg/
yr.
So
at
least
one
and
possibly
three
observations
are
outside
the
scope
of
the
rule
(
i.
e.,
between
12.5
and
37.5
percent
of
the
population).
This
also
implies
that
the
medium­
sized
Idaho
enterprise
budget
is
based
on
at
least
one
observation
outside
the
scope
of
the
rule.
12
Table
1
Farm
Sizes
in
Engle
et
alia,
2004
Farm
Size
(
kg)

Observation
North
Carolina
Idaho
1
1,000
27,000
2
3
4
1,200,000
5
6
7
66,000
8
1,136,364
9
10
11
12
13
204,500
Source:
Engle,
et
alia,
Table
2.

EPA
met
with
the
principal
investigator
of
the
study,
Professor
Carole
Engle,
on
April
30.
At
the
meeting,
Prof.
Engle
first
clarified
that
the
study
does
not
combine
data
and
results
across
all
facilities,
but
differentiates
between
operations
with
less
than
and
greater
than
100,000
lbs/
year
of
production.
Although
the
Engle
paper's
Table
2
reports
the
survey
data
across
all
facilities
surveyed,
she
stated
that
the
models'
production
size
categories
are
analyzed
separately.

Issue
Outline
Code:
13A
Description
of
the
Industry
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
Excerpt
No:
12
Enterprise
Budget
and
Risk
Analysis
13
The
enterprise
budget
analysis
showed
that
gross
revenue
for
similar
sizes
of
production
units
is
lower
in
Idaho
than
in
North
Carolina
(
Table
3).
Differences
in
products,
target
markets,
market
channels,
and
positioning
of
trout
products
in
the
respective
states
result
in
lower
prices
received
by
farmers
in
Idaho
as
compared
to
those
received
by
trout
farmers
in
North
Carolina.

The
greatest
expense
in
trout
farming
is
feed
(
Table
4).
Feed
represented
40%
of
Total
Variable
Costs
(
TVC)
and
36%
of
Total
Costs
(
TC)
of
trout
farming
in
North
Carolina.
On
the
larger
trout
farm
sizes
modeled
for
Idaho,
feed
represented
from
52­
57%
of
TVC
and
from
44­
50%
of
TC.
Labor
was
the
next
largest
cost
on
the
smaller
farm
sizes
(
15%
of
TC
in
NC
and
11%
of
TC
on
the
medium
farm
in
Idaho).
Depreciation
was
the
second­
greatest
cost
on
the
largest
farm
size
in
Idaho.
For
the
NC
farm,
management
(
12%
of
TC),
fingerlings
(
8%
of
TC),
depreciation
(
8%
of
TC),
interest
on
operating
capital
(
7%
of
TC),
and
oxygen
(
6%
of
TC)
followed.
All
representative
farms
modeled
showed
positive
net
returns
after
accounting
for
both
cash
and
non­
cash
expenses
(
Table
3).
Overall
net
returns
were
highest
on
the
larger
farm
in
Idaho
and
were
followed
by
the
NC
farm.
The
lowest
returns
modeled
were
those
of
the
medium­
sized
Idaho
farm.

Breakeven
prices
above
total
costs
(
BEP
Total
Costs)
ranged
from
$
1.31/
kg
­
$
2.05/
kg
($
0.69­
$
1.04/
lb),
with
the
NC
farm
model
exhibiting
the
highest
BEP
Total
Cost
(
Table
3).
However,
given
the
higher
market
prices,
the
higher
BEP
Total
Cost
does
not
reflect
lower
profitability.

Response:
Most
of
the
comment
is
a
description
of
the
enterprise
budgets
developed
for
the
analysis,
rather
than
a
comment
on
the
rule.
One
methodological
difference
between
the
Engle
et
alia
study
and
the
EPA
analysis
is
that
the
former
includes
non­
cash
costs,
such
as
depreciation,
as
the
primary
method
of
calculating
earnings.
That
is,
the
analysis
is
done
on
a
net
income
basis.
In
contrast,
EPA
examines
cash
inflows
and
outflows
and
calculates
earnings
as
cash
flow.
The
EPA
analysis
also
considered
net
income
as
a
sensitivity
analysis.
For
a
more
detailed
discussion
regarding
cash
flow,
net
income,
and
depreciation,
see
EEBA,
Economic
and
Environmental
Benefits
Analysis
of
the
Final
Effluent
Limitations
Guidelines
and
Standards
for
the
Concentrated
Aquatic
Animal
Production
Industry,
EPA...,
DCN
63010,
Appendix
A.

Issue
Outline
Code:
13B
Methodological
Overview
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
Excerpt
No:
13
The
enterprise
budgets
included
all
unpaid
family
labor
and
management.
The
majority
of
medium­
sized
farms
are
family­
operated
businesses
in
which
the
majority
of
labor
and
14
management
is
from
unpaid
family
members.
The
value
of
this
resource
is
especially
large
in
proportion
to
overall
costs
and
revenue
on
smaller
farm
sizes.
Therefore,
when
a
dollar
value
is
assigned
to
the
number
of
hours
worked
by
the
family
members,
net
returns
from
the
enterprise
are
near
the
breakeven
point.

Response:

A
fourth
point
of
divergence
between
the
Engle
et
alia
and
EPA
analyses
is
the
treatment
of
unpaid
labor
and
management.
First,
the
comment
that
"
The
majority
of
medium­
sized
farms
are
family­
operated
businesses
in
which
the
majority
of
labor
and
management
is
from
unpaid
family
members"
is
not
reflective
of
the
facilities
that
received
detailed
questionnaires
and
are
within
the
scope
of
the
rule
(
i.
e.,
production
>
100,000
lb/
yr).
Of
the
110
commercial
facilities
estimated
to
be
within
the
scope
of
the
rule
(
generated
from
EPA's
detailed
questionnaire
data),
only
3
reported
unpaid
labor
and
management.
The
use
of
unpaid
labor
and
management
is
more
common
at
facilities
that
produce
between
20,000
to
100,000
lb/
yr.
The
statement
is
consistent,
however,
if
the
population
studied
in
the
Engle
et
alia
analysis
contains
a
substantial
proportion
of
facilities
that
produce
less
than
100,000
lb/
yr
and
are
not
within
the
scope
of
the
rule,
see
response
to
comment
AAPNODA­
847­
11.

EPA
examined
the
effect
of
imputing
a
range
of
costs
for
labor
and
management
to
the
three
facilities
reporting
unpaid
labor
in
the
EPA
questionnaire
and
found
that
it
did
not
have
an
effect
on
the
impacts
estimated
as
a
result
of
the
rule.
That
is,
either
the
facility
was
viable
in
the
baseline
and
remained
viable
after
the
imposition
of
incremental
pollution
control
costs
or
the
facility
was
not
viable
in
the
baseline.
The
analysis
is
in
the
rulemaking
record.
When
estimating
the
costs
of
pollution
control,
EPA
includes
labor
costs
for
each
facility
in
the
analysis
even
if
it
reported
unpaid
labor
and
management.

Unpaid
family
labor
and
management
is
"
unpaid"
only
with
respect
to
the
income
statement.
Distributions
from
the
business
to
cover
family
living
and
other
personal
expenses
are
generally
referred
to
as
"
family
living
withdrawals"
or
"
owner
withdrawals."
These
withdrawals
are
shown
in
the
statement
of
owner
equity
in
the
balance
sheet
and
not
the
income
statement.
EPA
examines
potential
changes
in
balance
sheet
ratios
as
a
result
of
additional
pollution
control
costs
(
see
"
financial
health"
analysis
in
the
EEBA,
Economic
and
Environmental
Benefits
Analysis
of
the
Final
Effluent
Limitations
Guidelines
and
Standards
for
the
Concentrated
Aquatic
Animal
Production
Industry,
EPA...,
DCN
63010).

EPA
is
following
the
recommendation
of
the
Farm
Financial
Standards
Council
(
FFSC)
in
its
analysis.
FFSC
specifically
recommends
that
a
"
charge
for
unpaid
family
labor
and
management
should
not
be
included
on
the
income
statement..."
(
DCN
20095).

Finally,
how
the
different
analyses
address
unpaid
labor
and
management
is
related
to
the
difference
in
facility­
specific
and
model
facility
approaches.
As
mentioned
in
responses
to
AAPNODA­
847­
6,
EPA
uses
a
facility­
specific
approach
and,
following
FFSC
guidance,
does
not
15
impute
a
labor
cost
in
the
rare
case
the
unpaid
labor
and
management
is
reported.
The
Engle
et
alia
study
does
not
describe
how
many
data
points
were
adjusted
for
unpaid
labor
and
management
or
how
the
representative
labor
rate
was
chosen.
The
only
statement
provided
is
that
after
the
adjustment
"
net
returns
from
the
enterprise
are
near
the
breakeven
point."
That
is,
in
the
Engle
et
alia
analysis,
the
model
enterprises
are
very
marginal
prior
to
any
additional
costs.
This
marginality
is,
as
noted
in
response
to
comment
AAPNODA­
847­
7,
is
potentially
due
to
the
inclusion
of
baseline
closure
facilities.
If
baseline
closures
are
excluded,
marginality
is
reduced,
and
results
show
greater
capacity
to
incur
compliance
costs.

Issue
Outline
Code:
10
Compliance
Costs
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
Excerpt
No:
14
The
treatment
options
proposed
by
EPA
require
a
combination
of
labor,
management,
capital
(
charged
as
annual
depreciation),
and
operating
and
maintenance
(
O
and
M)
costs
(
Table
5).
Quiescent
zones
require
land
and
capital
costs
associated
with
the
structure
and
vacuum
components
for
removal
of
sediments.
Likewise,
an
offline
settling
pond
requires
capital
for
the
structure,
land
for
field
application
and
O
and
M
costs.
The
offline
settling
pond
will
require
either
a
front­
end
loader
or
a
vacuum
tank
for
proper
operation.
The
drug
and
chemical
BMP
requires
only
labor
and
management
time
with
a
much
higher
time
requirement
the
first
year.
The
solids
control
BMP
plan
requires
only
labor
and
management
time
with
a
greater
quantity
of
time
required
the
first
year.
Compliance
monitoring
also
requires
labor
and
management
if
the
monitoring
is
done
by
hand.
However,
if
a
composite
sampler
is
purchased,
additional
capital
cost
is
incurred.
Solids
polishing
with
a
microscreen
entails
a
capital
cost.
Estimates
of
the
capital
cost
vary
between
EPA
and
the
AETF
Trout
Subgroup,
but
both
estimates
are
presented.

Response:
[
Engineering
response
needed.]

Issue
Outline
Code:
15
Model
Facility
Impacts
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
Excerpt
No:
15
16
All
effluent
treatment
options
resulted
in
negative
net
returns
for
the
medium­
sized
farms
in
both
NC
and
ID
(
Table
6).
These
results
showed
that
none
of
the
treatment
options
proposed
is
economically
feasible
for
this
farm
size.

Table
6.
Net
returns
and
probability
of
achieving
positive
net
returns
after
imposing
various
effluent
treatment
options,
Monte
Carlo
simulation
risk
analysis.

Treatment
strategies
Net
returns
from
North
Carolina
farm
scenario
Net
returns
from
Idaho
farm
scenarios
Medium
(
150,000
lb/
yr)
Medium
(
200,000
lb/
yr)
Large
(
2,500,000
lb/
yr)

Most
likely
Probability
of
positive
returns
Most
likely
Probability
of
positive
returns
Most
likely
Probability
of
positive
returns
$
%
$
%
$
%
Low
cost
scenarios
Baselinea
8,644
46
5,647
2
284,281
84
Option
1b
­
25,509
0
­
33,810
0
43,087
11
Option
2c
­
27,180
0
­
35,469
0
41,427
10
Option
3d
­
32,320
0
­
39,879
0
35,573
10
Option
Ae
­
25954
0
­
31066
0
45832
11
Option
Bf,
w/
solids
control
BMP
­
28848
0
­
33924
0
42974
11
Option
Bf,
microscreens,
EPA
­
29020
0
­
33402
0
42232
11
Option
Bf,
microscreens,
AETF
­
43776
0
­
48888
0
­
43278
0
High
cost
scenarios
Baselineg
6,125
40
3,128
1
271,688
82
Option
1h
­
55,908
0
­
65,142
0
­
259,844
0
Option
2c
­
57,579
0
­
66,801
0
­
21,503
0
Option
3i
­
77,474
0
­
86,697
0
­
352,686
0
Option
Ae
­
56,352
0
­
62,398
0
­
257,098
0
Option
Bf,

w/
solids
control
BMP
­
59,246
0
­
65,256
0
­
259,958
0
Option
Bf,
­
59,418
0
­
64,734
0
­
260,700
0
17
microscreens,
EPA
Option
Bf,
microscreens,
AETF
­
74,174
0
­
80,220
0
­
346,208
0
aExcluding
land
financing
costs.
bIncludes:
solids
control
BMP
plan,
compliance
monitoring
done
by
automatic
composite
sampler,
quiescent
zones
without
negative
effect
on
production,
offline
settling
pond
constructed
without
having
to
destroy
tanks
and
emptied
with
a
vacuum
tank,
and
no
additional
land
purchased
for
disposal
of
the
solids.
cIncludes
Option
1
plus
a
drug
and
chemicals
BMP
plan.
dIncludes
Options
1
and
2
plus
solid
polishing
with
microscreen
filters
(
estimates
adapted
from
USEPA
2002).
ePrimary
settling,
BMP
plans
for
drugs
and
chemicals,
escape
prevention,
and
reporting
INAD
and
extra
label
drug
use.
fIncludes
Option
A
plus
either
a
BMP
plan
for
solids
control
or
solids
polishing
with
microscreen
filter.
gIncluding
land
financing
costs.
hIncludes:
solids
control
BMP
plan,
compliance
monitoring
done
by
hand,
quiescent
zones
which
proportionately
reduce
production,
offline
settling
pond
constructed
by
having
to
destroy
tanks
and
emptied
with
a
front­
end
loader,
and
additional
land
purchased
for
disposal
of
the
solids.
iSolids
polishing
with
microscreen
filters
(
TSAETF
2003).

Response:
Table
6
indicates
the
marginality
of
the
two
medium
model
projects.
Normal
variation
in
the
parameters
is
sufficient
to
push
98
percent
of
the
medium
ID
farms
and
64
percent
of
the
NC
farms
into
unprofitability
before
the
addition
of
incremental
pollution
control
costs.
Engle
et
alia
note
the
percentage
of
unprofitable
enterprises
(
see
AAPNODA­
847­
16)
but
do
not
discuss
the
observation
as
indicating
the
baseline
enterprises
are
on
the
knife
edge
of
profitability.
This,
combined
with
the
high
cost
estimates
and
Monte
Carlo
analysis
assumptions
(
see
response
to
comment
AAPNODA­
847­
8)
leads
to
the
inferred
high
level
of
impacts.

The
information
in
Table
6
highlights
a
fifth
difference
in
the
economic
methodologies
between
the
Engle
et
alia
and
EPA
studies.
EPA
follows
Agency
and
OMB
guidance
in
that
facilities
which
are
not
profitable
in
the
baseline
(
i.
e.,
prior
to
any
additional
costs)
cannot
be
considered
as
impacts
of
the
rule.
EPA
found
35
or
49
of
the
estimated
110
commercial
facilities
to
be
unprofitable
in
the
baseline
depending
on
whether
cash
flow
or
net
income
was
used
as
the
measure
for
earnings.
The
projected
closures
of
these
facilities
cannot
be
attributed
to
the
rule.
For
discussion
of
implications
of
this
rule,
see
response
to
comment
APNODA­
847­
7
and
13.

Issue
Outline
Code:
13B
Methodological
Overview
18
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
Excerpt
No:
16
Net
returns
for
the
largest
farm
size
considered
were
still
positive
after
imposing
the
lowest­
cost
scenarios
for
each
treatment
option.
However,
while
positive,
net
returns
were
only
$
31­
38/
MT
of
production.
This
low
level
of
profitability
would
generate
a
return
on
average
investment
of
less
than
4%.
Such
a
low
rate
of
return
is
unlikely
to
be
sufficiently
attractive
for
investors.
The
opportunity
costs
of
using
this
capital
in
trout
farming
are
likely
to
be
too
great
to
continue
to
operate
over
time.
Net
returns
became
negative
for
all
treatment
options
considered
for
the
large
farm
under
the
high
cost
scenarios.

Response:
EPA's
decision
criterion
is
the
clear
breakpoint
of
"
profitable
before
regulation
and
unprofitable
after
regulation"
to
identify
impacts.
EPA
calculates
the
present
value
of
future
earnings
with
a
7
percent
real
discount
rate
to
address
the
opportunity
costs
of
capital.
EPA
did
not
identify
what
constituted
an
"
acceptable"
rate
of
return
because
USDA
data
indicate
that,
on
average,
limited
resource,
retirement,
residential/
lifestyle,
and
low­
sales
(<$
100,000)
farms
show
losses
from
farming
activities;
high­
sales
farms
and
large
family
farms
(<$
500,000)
obtain
about
half
their
income
from
off­
farm
sources;
and,
overall,
91
percent
of
farm
operator's
household
income
came
from
off­
farm
sources
in
2001
(
USDA,
Agricultural
Income
and
Finance:
Annual
Lender
Issue,
AIS­
80,
March
11,
2003).

See
response
to
comment
AAPNODA­
847­
8
regarding
the
overestimation
of
compliance
costs.
The
overestimated
costs
result
in
the
impacts
seen
for
the
large
enterprise.

Issue
Outline
Code:
15
Model
Facility
Impacts
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
Excerpt
No:
17
The
risk
analyses
resulted
in
estimates
of
the
probability
of
each
scenario
generating
positive
net
returns
(
Table
6).
The
estimated
probabilities
of
achieving
positive
net
returns
for
the
North
Carolina
baseline
scenario
were
46%
for
the
low
cost
scenario
and
40%
for
the
high
cost
scenario.
These
probabilities
dropped
to
2%
and
1%,
respectively
for
the
medium­
sized
farm
in
Idaho.
These
relatively
low
probabilities
reflect
the
low
profitability
of
trout
farming
on
this
scale
if
all
family
labor
and
management
are
charged
at
full
rates.
The
probability
of
obtaining
positive
19
net
returns
was
highest
for
the
largest
farm
size
in
Idaho,
84%
for
the
low
cost
base
scenario
and
82%
for
the
high
cost
base
scenario.
These
high
probabilities
of
positive
net
returns
likely
reflect
economies
of
scale
associated
with
trout
farming.

Response:
See
response
to
comment
AAPNODA­
847­
7,
13,
and
15
regarding
baseline
closures.
See
response
to
comment
AAPNODA­
847­
11
regarding
the
possible
misalignment
of
populations
examined
in
the
Engle
et
alia
and
EPA
studies.

Issue
Outline
Code:
15
Model
Facility
Impacts
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
Excerpt
No:
18
Imposing
the
various
effluent
treatment
options
decreased
the
probability
of
generating
positive
net
returns
to
0%
for
the
medium­
sized
farms
in
North
Carolina
and
Idaho
as
well
as
for
the
highcost
scenario
on
the
large
Idaho
farm.
Thus,
not
only
are
mean
expected
net
returns
estimated
to
be
negative
but
there
is
an
extremely
low
probability
of
these
farms
surviving
the
additional
costs
associated
with
the
proposed
treatment
alternatives.
For
the
low­
cost
scenario
on
the
large
Idaho
farm,
the
probability
of
obtaining
positive
net
returns
decreased
to
11%
for
Option
1
and
to
10­
11%
for
the
other
options.
Thus,
even
though
net
returns
were
still
positive
after
imposing
the
proposed
treatment
options,
the
financial
risk
increases
substantially.

Response:
See
response
to
comment
AAPNODA­
847­
7,
13,
and
15
regarding
baseline
closures.
See
response
to
comment
AAPNODA­
847­
11
regarding
the
possible
misalignment
of
populations
examined
in
the
Engle
et
alia
and
EPA
studies.

Issue
Outline
Code:
13B
Methodological
Overview
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
Excerpt
No:
19
20
The
cost
analyses
presented
in
this
study
include
all
labor
and
management
costs
even
if
these
represent
unpaid
family
labor.
However,
opportunity
costs
are
real
costs
when
a
farm
operator
is
making
long­
term
decisions
related
to
their
business.
If
the
increased
time
burdens
on
labor
and
management
from
effluent
treatment
options
become
so
great
that
the
operator
and
family
have
more
attractive
alternatives,
that
farmer
will
choose
to
do
something
else
with
his/
her
time
and
the
farm
may
close.
Consideration
of
the
effects
on
unpaid
family
labor
and
management
is
critical
to
this
type
of
analysis.
Inclusion
of
costs
of
family
labor
is
the
most
appropriate
way
to
include
this
resource
in
economic
analyses
(
Kay
and
Edwards
1994).

Response:
See
response
to
comment
AAPNODA­
847­
13
regarding
unpaid
labor
and
management.

Issue
Outline
Code:
15
Model
Facility
Impacts
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
Excerpt
No:
20
Results
of
Mixed
Integer
Programming
Analysis
Base
Scenario
Net
returns
above
variable
costs
in
the
base
solution
of
the
model
for
the
medium­
sized
farm
in
North
Carolina
were
$
59,877
(
Table
7).
Note
that
these
returns
do
not
represent
profits
because
annual
fixed
costs
are
not
included.
Fixed
costs
are
complex
to
account
for
in
mathematical
programming
models
and
objective
functions
are
frequently
specified
as
net
returns
above
variable
costs
for
this
reason.
However,
annual
net
returns
for
these
treatment
options
were
negative,
as
shown
in
Table
6.
These
models
were
developed
to
explore
additional
constraints
and
limitations
imposed
by
the
proposed
treatments.

Response:
Engle
et
alia
is
inconsistent
in
that
the
mixed
integer
programming
analysis
does
not
include
annual
fixed
costs,
sunk
costs,
or
capital
replacement
costs
as
recommended
in
AAPNODA­
847­
34.

The
positive
returns
shown
in
the
baseline
and
the
negative
returns
seen
in
the
regulatory
scenario
result
from
the
high
compliance
costs
used
in
Engle
et
alia.
One
factor
in
the
high
costs
is
the
assumption
that
all
facilities
include
all
costs
for
each
component
in
the
option.
That
is,
treatment
in
place
in
the
baseline
scenario
is
not
considered.
Following
OMB
guidance,
EPA
considers
treatment
in
place
when
estimating
facility­
specific
costs
of
compliance.
See
also
response
to
comment
APPNODA­
847­
8
regarding
overestimated
compliance
costs.
21
Issue
Outline
Code:
15
Model
Facility
Impacts
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
Excerpt
No:
21
In
the
base
scenario,
all
tanks
on
the
NC
farm
were
in
production
with
26
used
for
foodfish
trout
production
and
4
used
to
produce
trout
for
the
recreational
market.
Of
the
total
operating
capital
required
($
140,000),
$
75,000
was
equity
capital
(
retained
earnings)
and
the
remaining
$
65,000
was
borrowed
at
an
interest
rate
of
8%.
The
investment
capital
level
used
in
the
model
was
$
90,000.
The
additional
$
90,000
of
borrowing
capacity
specified
was
not
used
in
the
base
scenario.
Part­
time
labor
was
hired
in
the
model
because
family
labor
alone
was
not
sufficient
to
meet
all
labor
and
management
requirements
on
the
farm.
Baseline
farms
were
economically
feasible
even
with
no
owner
equity
in
operating
capital.
Without
owner
equity,
net
returns
would
be
reduced
by
the
amount
of
the
interest
charged
on
all
operating
capital,
or
$
6,000,
for
total
net
returns
of
$
53,877.
Varying
levels
of
interest
on
operating
capital
affected
the
overall
level
of
net
returns
but
did
not
result
in
changes
in
the
basic
farm
production
plan.

The
base
scenario
model
was
particularly
sensitive
to
the
level
of
credit
reserves
both
for
operating
and
investment
capital.
Reductions
in
total
available
operating
capital
(
equity
capital
plus
borrowing
capacity)
resulted
in
reducing
the
number
of
tanks
in
production
and
a
consequent
reduction
in
net
returns
above
variable
costs
of
$
5,455
from
the
scenario
in
which
100%
of
the
operating
capital
was
borrowed
(
Table
7).
This
sensitivity
to
availability
of
operating
capital
(
regardless
of
whether
equity
or
borrowed)
is
important
because
the
maximum
amount
of
operating
capital
(
for
either
a
line
of
credit
or
a
standard
loan)
is
frequently
set
as
a
percentage
of
the
value
of
the
crop.

Response:
The
authors
do
not
state
the
basis
for
the
$
90,000
in
borrowing
capacity
except
to
say
that
it
is
frequently
set
as
a
percentage
of
the
value
of
the
crop.
EPA
examined
agricultural
lending
practices
when
developing
its
methodology.
USDA
notes
that
"
Farm
lenders
also
learned
the
risks
of
lending
on
the
basis
of
collateral
in
the
1980s
and
have
instituted
better
loan
analysis
tools
based
on
cash
flow
and
other
criteria."
(
USDA,
Agricultural
Income
and
Finance:
Annual
Lender
Issue,
AIS­
80,
March
11,
2003,
p.
12).
Most
agricultural
loan
programs
have
requirements
for
adequate
cash
flow
and/
or
debt/
asset
ratios
(
see
ERG,
2004,
"
CAAP
Facilities:
Access
to
Credit
and
Limits
on
Borrowing
Capacity,"
memorandum
to
EPA,
in
the
rulemaking
record).
EPA
developed
two
tests
based
on
USDA
methodology
("
credit
test"
and
"
financial
health,"
see
EEBA,
Economic
and
Environmental
Benefits
Analysis
of
the
Final
Effluent
Limitations
Guidelines
and
Standards
for
the
Concentrated
Aquatic
Animal
Production
Industry,
EPA...,
DCN
63010,
Section
3.2.2).
EPA
received
no
comments
on
these
tests.
22
EPA
checks
to
see
whether
the
debt/
asset
ratio
and
ability
to
repay
loans
are
impaired
by
the
additional
costs
of
the
rule.
EPA
performs
a
credit
test
(
borrowing
capacity)
that
calculates
the
ratio
of
the
pre­
tax
annualized
cost
of
an
option
and
the
after­
tax
Maximum
Feasible
Loan
Payment
(
MFLP)
(
i.
e.,
80
percent
of
after­
tax
cash
flow).
EPA
identified
any
company
with
a
ratio
exceeding
80
percent
of
MFLP
as
affected
under
this
test
(
i.
e.,
the
test
threshold
is
actually
64
percent
of
the
after­
tax
cash
flow).
USDA
notes
that
"
Lenders
generally
require
that
no
more
than
80
percent
of
a
loan
applicant's
available
income
be
used
for
repayment
of
principal
and
interest
on
loans."
(
USDA,
2000a,
p.
19).
It
is
felt
that
the
assumption
of
using
an
'
actual'
threshold
of
64%
of
after­
tax
cash
flow
lends
conservatism
to
the
credit
test.
the
credit
test
is
performed
at
the
company
level
only
because
this
is
the
level
at
which
financial
institutions
make
their
determination.
EPA
notes
that
similar
issues
(
i.
e.,
increased
difficulty
obtaining
credit)
were
raised
on
an
Agency
rulemaking
on
the
final
CAFO
regulation.
For
that
rule
EPA
received
no
recommendations
on
possible
approaches
to
deal
with
these
issues
as
part
of
its
analysis.
Similarly
for
this
final
regulation,
EPA
did
not
receive
any
recommendations
on
how
to
address
high
debt
levels
and
access
to
capital
constraints
among
regulated
facilities.
EPA
received
no
comments
about
its
tests
of
borrowing
capacity
or
financial
health
used
in
the
analysis.

The
assumption
that
borrowing
capacity
is
set
as
a
percentage
of
crop
value
results
in
the
mixed
integer
programing
model
is
sensitive
to
reductions
in
credit
reserves.
That
is,
if
the
capacity
is
lowered
the
value
of
the
crop
is
implicitly
lowered.
Lower
crop
values
imply
smaller
crops
and
smaller
crops
need
fewer
tanks
into
production.
Thus
the
model
is
structured
such
that
any
additional
costs
will
send
the
enterprise
into
a
downward
spiral.

Issue
Outline
Code:
13B
Methodological
Overview
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
Excerpt
No:
22
If
a
farmer
would
be
required
to
take
tanks
out
of
production
for
a
quiescent
zone,
total
production
is
reduced,
and
the
operating
capital
borrowing
capacity
is
also
reduced.
This
factor
may
not
be
critical
if
land
adjacent
to
the
farm
is
available
for
purchase
at
prices
that
are
economically
feasible.
For
each
$
20,000
reduction
in
total
operating
capital,
four
tanks
were
dropped
out
of
production
(
Table
7).
Net
returns
would
decrease
by
ca
$
6,000
for
each
$
20,000
decrease
in
operating
capital,
depending
upon
the
ratio
of
equity
to
borrowed
operating
capital.
The
decrease
in
net
returns
resulted
from
increased
interest
costs.

Response:
Engle
et
alia
examine
a
hypothetical
situation.
EPA
did
not
identify
a
situation
where
a
site
would
have
to
take
tanks
out
of
production
for
a
quiescent
zone
based
on
the
data
collected
at
actual
23
aquaculture
facilities
in
the
detailed
questionnaire.

In
addition,
for
the
barrier
to
entry
analysis
EPA
estimated
that
about
10
percent
of
the
facilities
incur
no
costs
(
because
existing
treatment
in
place
meet
the
requirements)
and
nearly
two­
thirds
of
the
facilities
incur
no
land
or
capital
costs.
Where
incremental
land
and
capital
costs
were
incurred,
they
formed
about
1.5
percent
of
the
total
assets
of
the
facility.
EPA
assumed
the
facility
would
attempt
to
maintain
production
levels,
incur
the
additional
costs,
and
experience
lower
earnings
as
a
result.
EPA
then
examined
the
change
in
earnings
for
the
closure
analysis,
credit
test,
and
financial
health
analysis.

Issue
Outline
Code:
13B
Methodological
Overview
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
Excerpt
No:
23
Investment
capital
constraints
in
the
model
included
both
equity
capital
that
could
be
used
for
investment
and
borrowed
investment
capital.
Sensitivity
analyses
were
developed
in
which:
1)
additional
land
was
assumed
to
be
available;
2)
investment
capital
borrowing
capacity
was
assumed
to
be
$
90,000;
and
3)
operating
capital
borrowing
capacity
was
assumed
to
increase
with
the
addition
of
any
new
tanks.
The
assumed
$
90,000
of
borrowing
capacity
in
investment
capital
was
based
on
the
assumption
that
the
land
and
tanks
were
owned
and
served
as
collateral.
Thus,
the
borrowing
capacity
would
be
equal
to
the
value
of
the
land
and
tanks.
Under
these
assumptions,
the
model
constructed
12
new
tanks
that
would
be
financed
through
borrowed
capital.
Net
returns
would
increase
to
$
63,794
from
the
additional
production
generated.
Labor
needs
were
met
in
the
model
by
hiring
additional
part­
time
labor.

Both
land
prices
and
tank
construction
costs
affected
the
farm's
ability
to
add
to
the
physical
plant
of
the
business.
If
the
farm
did
not
have
land
available
for
construction
of
new
tanks,
no
new
tanks
would
be
constructed
even
with
adequate
levels
of
borrowing
capacity.
The
average
land
purchase
price
specified
in
the
model
of
$
25,000
was
too
high
for
expansion
to
be
feasible.
Land
prices
had
to
drop
to
less
than
$
13,000/
acre
for
expansion
to
be
feasible
(
Table
8).
At
a
land
price
of
$
12,500,
16
new
tanks
would
be
constructed
that,
after
debt­
servicing
charges,
would
increase
net
returns
above
variable
costs
to
$
67,179.
Land
prices
of
$
6,000
or
less
would
allow
construction
of
20
new
tanks
for
net
returns
above
variable
costs
of
$
70,204.
A
40%
decrease
in
tank
construction
costs
resulted
in
further
increases
in
farm
capacity
through
additional
construction
of
new
tanks
and
net
returns
above
variable
costs
of
$
76,401­$
77,841,
depending
upon
land
price.
However,
increasing
tank
construction
costs
to
$
2,917
had
no
effect
on
construction
of
new
tanks.
24
Response:

This
is
an
interesting
sensitivity
analysis
that
examines
the
amount
of
expansion
possible
given
a
mix
of
land
and
tank
construction
costs.
It
is
not
a
comment
on
the
rule.

Issue
Outline
Code:
13B
Methodological
Overview
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
Excerpt
No:
24
With
Effluent
Treatment
Options
The
mixed
integer
programming
models
were
not
feasible
under
any
proposed
effluent
treatment
options
when
full
costs
of
quiescent
zones
and
offline
settling
basins
were
used
in
the
model
(
Table
9).
Construction
of
off­
line
settling
basins
required
higher
levels
of
capital
investment
than
is
likely
to
be
available
for
trout
farms
in
NC.
Lenders
often
impose
a
cap
that
limits
the
total
amount
of
lending
to
a
particular
farm;
some
lenders
base
this
cap
on
a
percentage
of
the
value
of
the
crop
inventory.
The
model
could
not
find
a
feasible
solution
when
credit
reserves
were
specified
in
the
model
at
levels
commonly
used
by
rural
banks
for
aquaculture
loans.

Response:
With
a
starting
credit
limit
of
$
90,000
and
land
costs
for
field
application
for
the
NC
farm
of
$
150,000
(
see
Engle
et
alia,
Table
5),
it
is
expected
that
the
model
could
not
find
a
feasible
solution.
See
also
response
to
comment
AAPNODA­
847­
8
regarding
overestimated
compliance
costs.

Issue
Outline
Code:
13B
Methodological
Overview
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
Excerpt
No:
25
Since
aquaculture
is
viewed
as
a
high­
risk
activity
in
areas
that
are
primarily
row­
crop
areas,
the
standards
used
for
evaluating
aquaculture
loans
may
differ
from
those
used
in
other
forms
of
agriculture.
Moreover,
banks
in
some
states
will
not
use
swimming
fish
inventory
as
collateral
for
loans.
25
Response:
See
response
to
AAPNODA­
847­
21
regarding
the
use
of
cash
flow
and
debt/
asset
ratios
as
bases
for
evaluating
agricultural
loans,
rather
than
inventory
or
production.

Issue
Outline
Code:
13B
Methodological
Overview
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
Excerpt
No:
26
For
the
model
to
produce
a
feasible
solution,
either
the
costs
of
designing
and
installing
quiescent
zones
and
offline
settling
basins
had
to
be
reduced
to
less
than
75%
of
the
estimated
cost
or
the
level
of
borrowing
capacity
would
have
to
exceed
the
value
of
existing
facilities.
This
would
require
farms
to
use
personal
collateral
other
than
the
land
and
tanks
themselves.
At
75%
of
estimated
costs
of
constructing
quiescent
zones
and
offline
settling
basins,
only
8
tanks
were
in
production
and
net
returns
above
variable
costs
were
only
$
12,295
(
Table
9).
Farms
that
do
not
account
for
all
unpaid
family
labor
or
sunk
costs
in
equipment
and
facilities
may
be
able
to
construct
facilities
at
lower
cash
costs.
Subsequent
runs
of
the
model
were
developed
using
quiescent
zone
and
offline
settling
basin
investment
capital
requirements
of
50%
of
the
estimated
cost.

Table
10
presents
results
of
the
mixed
integer
programming
models
for
the
medium­
sized
farm
scenario
in
North
Carolina
when
the
various
effluent
treatment
options
were
forced
into
the
models
using
the
50%
level
of
estimated
construction
costs
of
quiescent
zones
and
offline
settling
basins.
Net
returns
above
variable
costs
decreased
dramatically
(
43%­
56%)
for
Options
1,
2,
A,
and
B
with
a
solids
control
BMP.
The
model
could
not
identify
a
mathematically
feasible
way
to
comply
with
either
Options
3
or
B
with
microscreen
filters.

Response:
See
response
to
comment
AAPNODA­
847­
24
regarding
the
relative
position
of
the
credit
limit
and
one
component
of
a
compliance
cost.
Lowering
the
compliance
costs
to
a
point
below
the
credit
limit
would
permit
the
model
to
identify
returns
above
variable
costs.
See
also
response
to
comment
AAPNODA­
847­
8
regarding
overestimated
compliance
costs.

Issue
Outline
Code:
15
Model
Facility
Impacts
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
26
Document
Number:
AAPNODA­
847
Excerpt
No:
27
Forcing
treatment
Option
1
into
the
model
resulted
in
dropping
four
tanks
out
of
production.
Less
operating
capital
was
borrowed
because
fewer
tanks
were
in
production,
but
an
additional
$
85,549
of
investment
capital
was
borrowed.
The
additional
investment
capital
was
required
primarily
for
primary
settling
units.

A
BMP
plan
for
drugs
and
chemicals
was
added
to
the
model
to
evaluate
the
impact
of
imposing
Option
2
on
medium­
sized
trout
farms
in
North
Carolina
(
Table
10).
The
solution
was
similar
to
that
for
Option
1
with
slightly
lower
net
returns
above
variable
costs
($
26,358),
a
reduction
of
$
7,613
that
accounted
for
the
increased
variable
costs,
interest
on
operating
capital,
and
increased
hours
of
part­
time
labor
hired.

The
use
of
microscreens
for
solids
polishing
and
weekly
compliance
monitoring
requirements
were
added
to
the
Option
2
model
to
evaluate
farm­
level
effects
of
Option
3.
The
model
could
not
produce
a
mathematically
feasible
solution
when
Option
3
was
imposed
for
either
the
EPA
or
the
AETF
cost
estimates.

Net
returns
above
variable
costs
of
$
32,859
(
45%
decrease
from
the
base
scenario)
were
obtained
when
Option
A
was
imposed
on
the
model.
Total
operating
capital
borrowed
was
$
51,088.
Total
investment
capital
borrowed
was
$
85,549.
Part­
time
labor
was
hired
for
577
hours.
Since
the
driving
factor
in
the
model
results
was
the
amount
of
investment
capital
required
for
the
quiescent
and
settling
basins,
results
of
the
sensitivity
analyses
were
similar
to
those
discussed
earlier.

Option
B
with
a
solids
control
BMP
plan
resulted
in
net
returns
above
variable
costs
of
$
26,145.
Option
B
with
microscreen
filters
was
not
mathematically
feasible.
Negative
net
returns
above
variable
costs
were
obtained
even
with
the
EPA
estimates
of
microscreen
costs.

Response:
See
response
to
comment
AAPNODA­
847­
21
regarding
the
relative
position
of
the
credit
limit
and
compliance
cost.
See
response
to
comment
AAPNODA­
847­
8
regarding
the
absence
of
consideration
of
treatment
in
place
in
the
baseline
scenario.
See
also
response
to
comment
AAPNODA­
847­
8
regarding
overestimated
compliance
costs.

Issue
Outline
Code:
15
Model
Facility
Impacts
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
27
Excerpt
No:
28
Figure
1
presents
net
returns
above
variable
costs
for
the
proposed
treatment
options
for
the
two
Idaho
farm
scenarios.
Overall,
trends
were
similar
to
those
found
for
the
NC
farm
scenarios.
For
the
medium­
sized
farm,
net
returns
above
variable
costs
decreased
to
very
low
levels
for
proposed
treatment
Option
1.
Option
2
was
similar.
Option
3
generated
negative
net
returns
above
variable
costs
(
for
both
EPA
and
AETF
cost
estimates)
for
the
medium­
sized
farm.
Option
A
resulted
in
net
returns
above
variable
costs
of
a
similar
magnitude
to
those
of
Options
1
and
2.
None
of
the
Option
B
treatment
options
were
feasible.

Response:
See
response
to
comment
AAPNODA­
847­
21
regarding
the
relative
position
of
the
credit
limit
and
compliance
cost.
See
response
to
comment
AAPNODA­
847­
8
regarding
the
absence
of
consideration
of
treatment
in
place
in
the
baseline
scenario.
See
also
response
to
comment
AAPNODA­
847­
8
regarding
overestimated
compliance
costs.

Issue
Outline
Code:
15
Model
Facility
Impacts
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
Excerpt
No:
29
On
the
large
Idaho
farm,
net
returns
above
variable
costs
were
positive,
but
at
levels
74­
84%
lower
than
pre­
treatment
levels
for
Options
1,
2,
and
A.
Options
3
and
B
(
with
EPA
estimates)
were
still
positive,
but
at
a
lower
level.
Options
3
(
with
AETF
estimates),
B
(
with
BMP
for
solids
control),
and
B
(
with
AETF
estimates)
were
all
negative.

Response:
EPA
acknowledges
that
the
returns
for
the
large
Idaho
facility
remained
positive
under
costs
for
all
options.
See
also
response
to
comment
AAPNODA­
847­
8
regarding
overestimated
compliance
costs.

Issue
Outline
Code:
13B
Methodological
Overview
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
Excerpt
No:
30
28
Investment
capital
limited
the
farm's
ability
to
implement
the
proposed
treatment
options.
Limits
on
investment
capital
borrowing
resulted
in
reducing
the
number
of
tanks
in
production.
Imposing
effluent
treatment
technologies
forces
farms
to
operate
at
less
efficient
levels.

Response:
By
setting
an
apriori
credit
limit
and
not
taking
treatment
in
place
into
account
when
estimating
incremental
costs
to
comply
with
the
rule,
the
Engle
et
alia
analysis
developed
scenarios
that
have
high
probability
of
showing
impacts
under
most
modeling
assumptions
(
see
response
to
comments
AAPNODA­
847­
7,
AAPNODA­
847­
13,
and
AAPNODA­
847­
15
for
discussion
of
other
modeling
assumptions).

By
tying
the
credit
limit
to
production
or
sales
rather
than
using
cash
flow
and
debt/
asset
ratios
to
qualify
for
an
agricultural
loan,
the
methodology
sets
up
a
downward
spiral
in
that
the
costs
of
compliance
cause
the
facility
to
start
cannibalizing
itself,
see
response
to
comment
AAPNODA­
847­
21.

Issue
Outline
Code:
13B
Methodological
Overview
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
Excerpt
No:
31
CONCLUSIONS
Trout
farming
has
been
a
profitable
aquaculture
business
in
the
U.
S.,
particularly
in
Idaho
and
North
Carolina.
Results
of
the
enterprise
budget
analysis
showed
that
proposed
effluent
treatment
options
result
in
negative
net
returns
for
medium­
sized
farms
in
both
North
Carolina
and
Idaho.
Under
higher­
cost
scenarios,
even
the
largest
farm
size
considered
became
unprofitable
after
imposing
treatment
options.

Response:
EPA
disagrees
with
this
conclusion
because
it
is
based
on
overstated
costs,
costs
that
do
not
take
into
account
treatment
in
place,
and
not
removing
models
that
are
not
profitable
in
the
baseline
before
evaluating
the
effects
of
the
rule.

EPA
disagrees
with
these
conclusions
as
they
apply
to
this
rule­
making
in
that
EPA
applies
methods
and
assumptions
that
are
consistent
with
its
efforts
to
assess
economic
achievability.
There
are
two
main
issues
to
address
when
considering
why
the
approach
taken
by
Engle
et
al.
is
less
applicable
to
assessing
economic
achievability:
(
1)
compliance
cost
assumptions,
and
(
2)
economic
analysis
methods.
For
cost
assumptions,
the
Engle
et
al.
analysis
assumes
no
abatement
in
place
for
all
facilities
and
substantially
higher
costs
for
offline
settling
and
other
cost
categories
(
see
response
to
comment
AAPNODA­
847­
8).
EPA
uses
facility
specific
detailed
survey
29
responses
to
determine
what
technology
facilities
have
in
place,
and
then
estimates
incremental
cost
needed
to
meet
requirements.
This
is
the
traditional
approach
for
assessing
economic
achievability.
For
economic
analysis
methods,
Engle
et
al.
relies
on
methods
that
(
a)
do
not
account
for
baseline
closures,
(
b)
examines
"
representative
facilities",
and
(
c)
relies
on
limited
survey
information
of
trout
flow­
through
facilities
in
ID
and
one
county
in
NC
(
see
response
to
comments
AAPNODA­
847­
7,
AAPNODA­
847­
13,
and
AAPNODA­
847­
15).
EPA
conducts
traditional
facility­
specific
analysis
(
implying
no
need
to
create
representative
facilities
­
note
that
EPA
was
criticized
for
relying
on
representative
facilities
for
the
proposed
rule)
using
facility­
specific
data
from
a
national
survey
of
all
CAAP
system
operations
(
not
just
trout
flow­
through).
EPA
also
identifies
baseline
closures
and
is
therefore
able
to
differentiate
between
closures
due
to
the
rule
and
other
closures
likely
to
occur,
even
in
the
absence
of
the
rule
(
in
accordance
with
EPA
economic
guidance).
EPA's
methods
are
similar
to
methods
used
for
majority
of
past
ELGs.

Issue
Outline
Code:
13B
Methodological
Overview
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
Excerpt
No:
32
The
risk
analysis
showed
very
low
probabilities
of
generating
positive
net
returns
after
imposing
treatment
options
for
all
farm
sizes
and
cost
levels.

Response:
The
authors
do
not
note
that
Table
6
in
the
report
indicates
a
very
low
probability
of
generating
positive
net
returns
before
imposing
treatment
options.
Keeping
the
unprofitable
facilities
in
the
analysis
obscures
the
potential
impacts
of
the
rule.
See
response
to
comments
AAPNODA­
847­
7,
AAPNODA­
847­
13,
and
AAPNODA­
847­
15.

Issue
Outline
Code:
15
Model
Facility
Impacts
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
Excerpt
No:
33
The
mixed
integer
programming
models
further
demonstrated
that
proposed
treatment
options
will
not
be
economically
feasible
for
trout
farms
in
North
Carolina
and
Idaho.
Limits
to
the
30
borrowing
capacity
of
both
operating
and
investment
capital
were
the
primary
factors.
The
models
showed
that
the
high
land
prices
in
areas
adjacent
to
trout
farms
prevent
their
expansion.
If
additional
production
area
is
taken
out
of
production
in
order
to
treat
effluents,
then
the
operating
capital
borrowing
capacity
is
reduced;
yet,
investment
capital
borrowing
would
need
to
increase.

Response:
Limits
to
borrowing
capacity
are
based
on
the
assumption
that
the
amount
of
credit
available
is
based
on
production.
In
contrast,
EPA
examines
impacts
on
borrowing
capacity
and
financial
health
through
cash
flow
and
debt/
asset
ratios,
i.
e.,
following
USDA
methodology
and
requirements
from
several
agricultural
loan
programs
(
see
response
to
comments
#
21).

EPA
does
not
assume
facilities
will
expand
in
order
to
respond
to
the
requirements
of
the
regulation,
see
EEBA,
Economic
and
Environmental
Benefits
Analysis
of
the
Final
Effluent
Limitations
Guidelines
and
Standards
for
the
Concentrated
Aquatic
Animal
Production
Industry,
EPA...,
DCN
63010,
Section
3.2.1.
EPA
does
not
assume
a
facility
can
"
grow"
its
way
out
of
potential
economic
impacts.
EPA
assumed
the
facility
would
attempt
to
maintain
production
levels,
incur
the
additional
costs,
and
experience
lower
earnings
as
a
result.
EPA
then
examined
the
change
in
earnings
for
the
closure
analysis,
credit
test,
and
financial
health
analysis.

EPA
examined
facility­
specific
data
collected
in
the
detailed
questionnaire
and
did
not
identify
cases
where
a
facility
needed
to
take
tanks
out
of
production
to
treat
effluents.
Therefore,
EPA
did
not
start
the
downward
spiral
of
few
tanks
and
lower
production
leading
to
lower
credit
limits
triggered
by
the
Engle
et
alia
methodology.

Issue
Outline
Code:
15
Model
Facility
Impacts
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
Excerpt
No:
34
Some
farms
have
adopted
some
of
the
treatment
options
proposed
by
EPA.
It
is
likely
that
these
farms
were
able
to
do
so
because
additional
land
at
affordable
prices
was
available
or
because
sunk
costs
on
older
farms
were
not
generating
cash
expenses.
This
would
allow
these
farms
to
expand
production
to
offset
the
increased
fixed
costs
associated
with
treatment.
However,
sunk
costs
in
capital
goods
will
eventually
need
to
be
replaced
and
economic
analyses
must
consider
long­
run
effects.

Response:
31
This
comment
is
internally
inconsistent.
First
it
notes
that
sunk
costs
might
not
have
been
generating
cash
expenses
and
then
says
that
economic
analyses
must
consider
the
costs
to
replace
capital
goods.
The
mixed
integer
programming
model
explicitly
does
not
consider
fixed
costs
including
sunk
costs.
The
enterprise
budget
approach
includes
depreciation
as
a
cost;
EPA
provided
a
detailed
explanation
why
depreciation
is
a
poor
measure
of
sunk
costs
or
capital
cost
replacement
in
EEBA,
Economic
and
Environmental
Benefits
Analysis
of
the
Final
Effluent
Limitations
Guidelines
and
Standards
for
the
Concentrated
Aquatic
Animal
Production
Industry,
EPA...,
DCN
63010,
Appendix
A.

EPA
does
not
assume
facilities
will
expand
in
order
to
respond
to
the
requirements
of
the
regulation,
see
EEBA,
Economic
and
Environmental
Benefits
Analysis
of
the
Final
Effluent
Limitations
Guidelines
and
Standards
for
the
Concentrated
Aquatic
Animal
Production
Industry,
EPA...,
DCN
63010,
Section
3.2.1.
EPA
does
not
assume
a
facility
can
"
grow"
its
way
out
of
potential
economic
impacts.
EPA
assumed
the
facility
would
attempt
to
maintain
production
levels,
incur
the
additional
costs,
and
experience
lower
earnings
as
a
result.
EPA
then
examined
the
change
in
earnings
for
the
closure
analysis,
credit
test,
and
financial
health
analysis.

Issue
Outline
Code:
13B
Methodological
Overview
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
Excerpt
No:
35
This
study
further
documented
the
relatively
high
levels
of
financial
risk
on
trout
farms.
The
proposed
regulations
considered
in
this
analysis
required
additional
investment
capital
that
further
increased
financial
risk.
While
some
fish
farmers
successfully
manage
around
relatively
high
levels
of
financial
risk,
at
some
point
the
risk
becomes
greater
than
the
operator's
ability
or
willingness
to
accept.
The
farm
then
shuts
down.

Response:
It
is
not
clear
what
the
commenter
means
by
documenting
the
relatively
high
financial
risk
on
trout
farms
unless
they
mean
the
likelihood
of
unprofitability
in
the
baseline.
By
not
removing
"
baseline
failures"
from
the
analysis,
the
study
obscures
the
potential
impacts
of
the
rule
within
impacts
from
normal
variation
within
the
population.
See
response
to
comment
AAPNODA­
847­
7,
AAPNODA­
847­
13,
and
AAPNODA­
847­
15.
EPA
does
not
disagree
that
some
farms
might
close;
the
question
is
whether
those
closures
are
a
result
of
the
rule.

Issue
Outline
Code:
15
32
Model
Facility
Impacts
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
Excerpt
No:
36
Limits
to
borrowing
capacity
forced
farms
to
take
tanks
out
of
production.

Response:
EPA
did
not
identify
a
facility
that
would
need
to
take
tanks
out
of
production
AAPNODA­
847­
21
for
discussion
of
borrowing
capacity.

Issue
Outline
Code:
13B
Methodological
Overview
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
Excerpt
No:
37
The
budget
analysis
showed
that
larger
farms
can
manage
the
expense
of
treating
effluents
better
than
smaller
farms,
but
imposing
these
regulations
forces
farms
to
reduce
production
due
to
limited
capacity
to
borrow
additional
funds.
Thus,
these
proposed
regulations
create
a
paradox
for
farmers
in
that
the
increased
investment
capital
required
for
compliance
increases
economies
of
scale
and
incentives
to
expand
farm
size.
However,
since
the
additional
investment
is
not
generating
additional
production,
it
uses
up
borrowing
capacity
and
causes
farmers
to
reduce
production
potential.
Thus,
farms
are
forced
to
operate
at
less
efficient
levels.

Response:
EPA
does
not
assume
facilities
will
expand
in
order
to
respond
to
the
requirements
of
the
regulation,
see
EEBA,
Economic
and
Environmental
Benefits
Analysis
of
the
Final
Effluent
Limitations
Guidelines
and
Standards
for
the
Concentrated
Aquatic
Animal
Production
Industry,
EPA...,
DCN
63010,
Section
3.2.1.
EPA
does
not
assume
a
facility
can
or
will
"
grow"
its
way
out
of
potential
economic
impacts.
EPA
assumed
the
facility
would
attempt
to
maintain
production
levels,
incur
the
additional
costs,
and
experience
lower
earnings
as
a
result.
EPA
then
examined
the
change
in
earnings
for
the
closure
analysis,
credit
test,
and
financial
health
analysis.

In
its
Regulatory
Flexibility
Analysis,
EPA
examines
the
need
for
the
rule.
One
reason
for
the
need
for
a
Federal
regulation
is
a
market
failure
from
externalities.
A
rule
causes
a
discharger
to
internalize
the
costs
of
environmental
damage
caused
by
the
discharge.
EPA
does
not
dispute
that
causing
a
discharger
to
internalize
costs
of
pollution
control
might
result
in
less
profitable,
but
33
that
does
not
automatically
render
a
rule
economically
unachievable.

Issue
Outline
Code:
15
Model
Facility
Impacts
Organization
Name:
Engle,
et
al.
Organization
Type:
State
government/
Academia
Document
Number:
AAPNODA­
847
Excerpt
No:
38
Overall,
the
proposed
regulations
pose
serious
economic
challenges
to
trout
farms,
increase
financial
risk
on
farms,
and
increase
economies
of
scale
and
barriers
to
entry.
Limitations
on
borrowing
capacity
may
force
existing
farms
to
substitute
treatment
facilities
for
production
units
and,
thus,
operate
at
less
efficient
levels.

Reponse:
EPA
disagrees.
The
two
studies
differ
markedly
in
methodological
approach
to
estimating
the
impacts
of
the
rule.
These
differences
lead
to
different
conclusions
in
each
study.

First,
EPA
uses
facility­
specific
data
collected
in
the
detailed
questionnaire.
That
is,
a
separate
analysis
is
made
for
each
observation.
The
Engle
et
alia
study
uses
a
"
representative
model"
approach.

Second,
through
its
facility­
specific
approach,
EPA
uses
matched
sets
of
costs,
revenues,
and
treatment
in
place
for
each
facility
analyzed.
The
Engle
et
alia
study
collected
financial
data
from
its
survey
of
trout
operators
in
North
Carolina
and
Idaho
and
compiled
representative
farm
enterprise
budgets.
The
"
representative"
budgets
are
based
on
data
that
include
facilities
which
show
negative
returns
before
any
incremental
pollution
control
costs
are
incurred.
EPA
believes
its
facility­
level
approach
using
actual
financial
data
as
reported
in
its
detailed
survey
of
regulated
facilities
provides
a
more
realistic
picture
of
the
baseline
financial
conditions
at
these
facilities.

Third,
the
Engle
study
does
not
remove
from
its
analysis
operations
that
show
negative
returns
pre­
regulation.
It
is
established
EPA
practice
as
well
as
OMB
guidance
to
develop
a
baseline
scenario
of
how
the
world
would
look
absent
the
regulation.
This
leads
to
EPA
removing
"
baseline
closures"
from
its
regulatory
analyses.
EPA
believes
that
the
approach
used
in
the
Engle
study
shows
artificially
low
financial
conditions
since
it
includes
financial
data
from
nonviable
firms
using
its
average
representative
farm
model
approach.
That
is,
the
findings
do
not
distinguish
between
the
effects
of
the
rule
from
the
normal
variation
in
operational
effects.

Fourth,
another
way
the
Engle
study's
approach
differs
markedly
from
EPA's
is
in
its
accounting
of
expected
compliance
costs
and
its
evaluation
of
regulatory
impacts.
Specifically,
the
Engle
study
does
not
account
for
operations
that
are
already
complying
with
the
expected
regulatory
34
options;
nor
does
it
account
for
"
treatment­
in­
place"
of
various
technologies
at
these
facilities
(
i.
e.,
accounts
for
total
economic
costs
regardless
of
what's
already
at
the
operation).
EPA's
facility­
level
approach
utilize
the
Agency's
detailed
survey
information
to
determine
facilities
that
either
do
not
discharge
wastewater
to
waters
of
the
U.
S.
(
and
so
would
not
incur
any
costs
under
the
final
regulation)
or
have
some
"
treatment­
in­
place."
Therefore,
EPA's
analysis
reflects
the
expected
"
incremental"
costs
of
complying
with
the
final
regulation,
not
accounting
for
what
the
regulated
facility
already
has
in­
place.
EPA
believes
this
facility­
level
approach
provides
a
more
realistic
picture
of
the
regulatory
impacts
a
facility
will
incur
as
a
result
of
complying
with
the
final
regulation.

Finally,
the
Engle
study's
estimates
financial
conditions
at
regulated
operations
that
includes
cost
estimates
for
"
unpaid"
labor.
EPA's
analysis
does
not
account
for
unpaid
labor
because
the
Agency's
detailed
survey
indicates
that
few
(
2
surveyed
facilities)
report
unpaid
labor
costs;
however,
EPA
conducts
additional
sensitivity
analyses
of
its
results
to
account
for
potential
unpaid
labor
costs
among
facilities
that
report
such
costs.
Because
the
Engle
study
accounts
for
unpaid
labor
costs
using
an
average
representative
farm
model
approach,
EPA
believes
that
the
resultant
baseline
financial
conditions
are
artificially
low.

See
also
response
to
comment
AAPNODA­
847­
31
ACKNOWLEDGMENTS
The
authors
thank
the
trout
farmers
in
Idaho
and
North
Carolina
who
participated
in
the
survey
interviews.
This
material
is
based
upon
work
supported
by
the
Cooperative
State
Research
Education
and
Extension
Services,
U.
S.
Department
of
Agriculture,
under
Agreement
No.
00­
38859­
9235.
