Document ID: EPA-HQ-OAR-2002-0076-0141
Agency: epa
Document Type: Supporting & Related Material
Title: 
Posted Date: 2004-04-22T04:00Z

1
ENVIRONMENTAL
PROTECTION
AGENCY
40
CFR
Part
51
Regional
Haze
Regulations
and
Guidelines
for
Best
Available
Retrofit
Technology
(
BART)
Determinations
AGENCY:
Environmental
Protection
Agency
(
EPA).

Mark
Evangelista
Summary
of
Technical
Analyses
for
the
Proposed
Rule
2
I.
BACKGROUND
A.
CALPUFF
CALPUFF
was
used
for
much
of
the
modeling
described
in
this
document.
CALPUFF
is
a
Lagrangian
dispersion
modeling
system
that
simulates
pollutant
releases
as
a
continuous
series
of
puffs.
CALPUFF
simulates
the
effects
of
meteorological
conditions
on
multiple­
pollutant
transport,
transformation,

and
removal.
CALPUFF
may
be
used
on
scales
from
tens
of
meters
from
a
source
to
hundreds
of
kilometers.
In
April,
2003,
it
was
promulgated
for
regulatory
use
in
specific
circumstances
in
The
Guideline
on
Air
Quality
Models,
Appendix
W
to
40CFR
501,
[
the
Guideline].

CALPUFF
treats
explicitly
the
sulfate
and
nitrate
components
of
particulate
matter
for
regional
haze.
Gas­
phase
chemical
transformations
are
treated
using
parameterized
models
of
SO2
conversion
to
SO4
and
NO
conversion
to
NO2,
HNO3,

and
SO4.
While
organic
aerosol
formation
is
also
treated
by
CALPUFF,
this
capability
was
not
utilized
in
the
simulations
described
here.

The
CALMET
meteorological
model
provides
three­
dimensional
wind
fields
to
the
dispersion
model,
CALPUFF.
CALMET
combines
an
objective
analysis
procedure
using
wind
observations
with
parameterized
treatments
of
slope
flows,
valley
flows,
terrain
kinematic
effects,
terrain
blocking
effects,
and
sea/
lake
1
Appendix
W
to
40
CFR
Part
51,
The
Guideline
on
Air
Quality
Models
3
breeze
circulations.
CALPUFF
may
optionally
use
single­
station
(
horizontally­
constant)
wind
fields
as
well.
2
CALPUFF
includes
algorithms
for
near­
field
effects
such
as
building
downwash,
transitional
buoyant
and
momentum
plume
rise,
partial
plume
penetration,
and
sub­
grid
scale
terrain
and
coastal
effects.
It
also
includes
algorithms
for
longer
range
effects
such
as
pollutant
removal
due
to
wet
scavenging
and
dry
deposition,
chemical
transformation,
vertical
wind
shear,
overwater
transport,
and
visibility
effects
of
particulate
matter
concentrations.
3
However,
many
of
these
capabilities
were
not
employed
in
the
simulations
described
in
this
document
because
we
were
most
concerned
with
chemical
transformation.

B.
Where
to
get
CALPUFF
CALPUFF
may
be
obtained
via
the
Support
Center
for
Regulatory
Air
Models
web
site:

http://
www.
epa.
gov/
scram001/
tt22.
htm#
calpuff
Documentation
and
model
information
may
also
be
found
on
this
web
site.

C.
Use
of
CALPUFF
for
calculating
the
change
in
visibility
The
following
discussion
appears
in
the
proposal:

In
providing
an
individual
source
exemption
option,
a
metric
is
needed
to
assess
a
source's
contribution
to
visibility
degradation.
The
metric
we
are
using
in
the
regional
haze
rule
is
the
deciview,
which
is
derived
directly
2
Ibid.

3
Ibid.
4
from
light
extinction,
an
index
commonly
used
to
measure
visibility
degradation.
4
To
determine
the
change
in
visibility
due
to
the
change
in
concentration
of
modeled
air
pollutants,
we
followed
the
example
for
a
CALPUFF
simulation
in
the
Federal
Land
Managers'

Air
Quality
Related
Values
Workgroup
(
FLAG)
Phase
I
Report
(
December
2000).
5
The
change
in
visibility
due
to
impairing
pollutants
(
SO2,
NOx,
and
directly­
emitted
PM2.5,
which
we
report
as
the
change
in
deciviews
from
natural
background
conditions,
is
derived
from
the
sum
of
light
extinction
values
for
modeled
pollutants
from
the
CALPUFF
simulation.
Light
extinction
values
may
depend
upon
component
concentration,

extinction
efficiency,
and
relative
humidity.
The
complexity
with
which
these
factors
are
considered
varies
depending
upon
the
type
of
CALPUFF
simulation.
Specifics
of
each
procedure
we
used
are
discussed
in
greater
detail
in
the
sections
describing
each
CALPUFF
simulation
and
CALPOST
processing
of
the
visibility
impacts.

The
rationale
on
the
use
of
CALPUFF
to
assess
visibility
impacts
appears
in
the
proposal:

Traditionally,
EPA
has
used
transport
and
diffusion
modeling
to
predict
the
effect
of
directly
emitted
PM2.5
emissions
on
PM2.5
ambient
concentrations.
To
simulate
the
effect
of
precursor
pollutant
emissions
on
PM2.5
concentrations
requires
air
quality
modeling
that
not
only
addresses
transport
and
diffusion,
but
also
chemical
4
Regional
Haze
Regulations
and
Guidelines
for
Best
Available
Retrofit
Technology
(
BART)
Determinations:
Proposed
Rule
5
Federal
Land
Managers'
Air
Quality
Related
Values
Workgroup
(
FLAG)

Phase
I
Report,
December
2000
5
transformations.
While
we
believe
that
it
is
technically
feasible
to
model
secondary
PM
formation,
and
there
is
at
least
one
model
[
CALPUFF]
which
incorporates
algorithms
for
estimating
secondary
transformation,
we
have
not
yet
fully
tested
such
modeling
to
determine
whether
its
application
is
justified
as
a
sole
determinant
of
air
quality
impacts
involving
secondary
transformation.
However,
where
the
statutory
criteria
for
determining
regulatory
applicability
involve
relatively
low
thresholds,
or
where
regulatory
decisions
involve
considerations
of
multiple
factors
including,
but
not
limited
to,
model
results,
we
believe
transport
and
diffusion
models
such
as
CALPUFF
can
be
appropriate
regulatory
tools
for
evaluating
air
quality
impacts
involving
secondary
transformation.
Consequently,
we
believe
its
use
by
States
to
assess
whether
a
source
is
reasonably
anticipated
to
cause
or
contribute
to
impairment
of
visibility
in
Class
I
areas
is
reasonable.
6
II.
CALPUFF
ANALYSIS
The
Interagency
Workgroup
on
Air
Quality
Modeling
(
IWAQM)

studied
the
potential
regulatory
application
of
CALPUFF
in
its
Phase
1
report7
and
Phase
2
report.
8
The
Phase
2
report,

Summary
Report
and
Recommendations
for
Modeling
Long
Range
6
Regional
Haze
Regulations
and
Guidelines
for
Best
Available
Retrofit
Technology
(
BART)
Determinations:
Proposed
Rule
7
Interagency
Workgroup
on
Air
Quality
Modeling
(
IWAQM)
Phase
I
Report:

Interim
Recommendation
for
Modeling
Long
Range
Transport
and
Impacts
on
Regional
Visibility.
EPA­
454/
R­
93­
015,
April
1993
8
Interagency
Workgroup
on
Air
Quality
Modeling
(
IWAQM)
Phase
II:

Summary
Report
and
Recommendations
for
Modeling
Long
Range
Transport
Impacts,
EPA­
454/
R­
98­
019
December
1998
6
Transport
Impacts,
has
been
used
to
suggest
defaults
for
analyses
of
long­
range
transport
using
models
such
as
CALPUFF.

The
CALMET
and
CALPUFF
User
Guides9
also
contain
default
settings.
The
template
input
files
(*.
inp)
that
come
with
the
CALPUFF
system
download
have
default
settings
for
many
parameters;
these
defaults
reflect
those
suggested
in
the
IWAQM
reports
and
those
found
in
the
CALPUFF
and
CALMET
user
guides.
In
the
modeling
discussions
to
follow,
we
mention
any
instance
in
which
we
departed
from
these
default
settings.

Additionally,
some
variables
simply
point
to
a
file
location,
file
name,
or
a
platform­
specific
parameter;
these
variables
should
be
obvious
and
we
do
not
include
them
in
the
discussions
because
their
values
will
be
unique
to
each
modeling
platform.
For
any
input
variable
not
mentioned
in
this
document,
you
may
assume
we
carried
the
default
value
in
the
*.
inp
template
file
that
comes
with
the
CALPUFF
system
download,
or
that
the
variable
is
unique
to
the
platform.

The
information
contained
in
this
modeling
discussion
would
include
elements
of
a
more
detailed
modeling
protocol
for
applications
greater
than
200
km
from
a
Class
I
area,
as
discussed
in
the
proposal.
However,
this
document
describes
only
the
CALPUFF
modeling
to
support
results
shown
in
this
proposal
and
should
not
be
regarded
as
an
outline
for
a
protocol
for
other
CALPUFF
applications.
As
stated
in
the
proposal,
for
applications
involving
receptors
beyond
200
km,

a
protocol
should
be
submitted
for
approval.

9
A
User's
Guide
for
the
CALMET
Meteorological
Model
(
5th
edition),
and
A
User's
Guide
for
the
CALPUFF
Dispersion
Model,
Earthtech
Inc.,
Concord,

MA,
January
2000.
7
A.
Domain
and
Receptor
Parameters
 
Huntington
WV
This
analysis
addressed
visibility
impacts
derived
from
reducing
SO2
emissions
at
BART­
eligible
EGUs.
To
perform
this
analysis,
we
used
existing
input
data
and
parameters
from
a
CAPLUFF
analysis
conducted
by
the
National
Park
Service
(
NPS)

for
the
same
domain
and
time
period.
Since
our
analysis
was
intended
to
illustrate
the
possible
visibility
impacts
of
a
typical
source,
and
not
to
represent
any
actual
source­
Class
I
area
scenario,
we
found
the
NPS
data
and
parameter
settings
to
be
consistent
with
our
assumptions
about
the
analysis.

Due
to
computational
limitations,
we
conducted
individual
CALMET
and
CALPUFF
for
one
month
of
data
at
a
time.
The
monthly
files
were
input
and
output
sequentially
and
automatically
by
batch
processing.
Simple
scripts
assimilated
the
results
into
three
files
of
results,
one
for
the
base
and
one
for
each
of
two
control
scenarios.

We
used
the
Lambert
Conformal
Conic
map
projection.
Using
this
projection
allowed
us
to
take
advantage
of
existing
NPS
geophysical
data
files
for
CALMET
processing.

The
modeling
domain
for
this
analysis
was
roughly
a
300
km
square
containing
Huntington,
WV,
portions
of
Shenandoah
National
Park,
and
the
Dolly
Sods
and
Otter
Creek
Wilderness
Areas
in
the
Monongahela
National
Forest
(
Figure
1).
By
using
this
domain,
we
could
again
take
advantage
of
the
existing
geophysical
and
meteorological
data.

A
total
of
114
receptors
were
located
in
arcs
at
select
radial
distances
(
100,
120,
140,
160,
180,
and
200
km)
from
the
source
location.
While
area­
specific
geophysical
data
was
incorporated
into
the
CALMET
processing,
providing
CALPUFF
meteorology
input
that
was
geographically
representative
of
8
the
domain,
area­
specific
elevations
were
not
assigned
to
the
receptors
in
the
concentric
circles.
An
elevation
of
600
meters
was
assigned
to
these
receptors
as
an
average
value
for
the
area.

B.
CALMET
Parameters
We
used
CALMET
to
process
meteorology
data
for
1991­
1995.

Data
from
ten
surface
stations
was
included;
nine
of
these
stations
were
also
included
as
precipitation
stations
in
the
CALMET
input
file.
We
included
data
from
three
upper­
air
rawinsonde
stations.
(
The
meteorological
stations
and
other
CALMET
parameters
are
identified
in
Table
1.)
We
incorporated
the
geophysical
data
 
land
type,
elevation,
land
use,
and
surface
parameters
 
from
the
existing
data
provided
by
NPS.

Table
1
summarizes
the
(
non­
default)
parameter
settings
we
used
for
the
CALMET
simulations.

We
created
60
CALMET
output
files,
one
for
each
month
for
five
years.

C.
CALPUFF
Parameters
We
set
up
the
CALPUFF
input
file
to
use
the
same
domain
parameters
and
meteorology
years
as
we
used
in
the
CALMET
processing.
The
CALMET
output
files
were
directly
input
into
the
CALPUFF
simulations,
again
for
one
month
at
a
time.

We
selected
options
to
model
concentrations
of
SO2,
SO4,
NOx,

HNO3,
NO3,
and
PM2.5
while
providing
input
emissions
for
only
SO2,
NOx,
and
PM2.5.
The
CALPUFF
simulations
contain
only
one
emissions
source,
a
single
point
source.
We
applied
source
characteristics
typical
of
BART­
eligible
EGUs
(
base
elevation
=
200
m,
stack
height
=
100m,
stack
diameter
=
8.0
m,
exit
velocity
=
27.0
m/
s,
exit
temperature
=
400
deg
K)
to
all
simulations
in
the
analysis.
9
Two
base
simulations
were
conducted
to
estimate
the
emissions
of
typical
Electricity
Generating
Units
(
EGUs)
of
250
MW
and
750
MW.
We
calculated
SO2
emissions
for
these
EGUs
using
the
following
assumptions:
1
MW
=
10.5
x
106
Btu/
hr;

bituminous
coal
heat
content
13,000
Btu/
lb;
38
lb
sulfur
per
ton
of
coal.
10
We
estimated
the
following
emission
rates:

EGU
Size(
MW)
EGU
Size
Btu/
hr
SO2
TPY
Lb/
MMBtu
SO2
250
2.625
*
109
29,185
2.54
750
7.875
*
109
87,556
2.54
We
estimated
the
NOx
and
PM2.5
emissions
based
upon
SO2
emissions.
By
examining
the
ratio
of
SO2
emissions
to
NOx
emissions
for
a
set
of
BART­
eligible
EGUs
in
the
East,
11
we
determined
a
SO2/
NOx
ratio
of
1/
2.8
to
be
a
good
fit
for
the
set.
Figure
2
shows
the
frequency
of
the
ratios
in
the
set.

For
the
base
simulations
only,
we
estimated
the
NOx
emission
rate
to
be
1/
2.8
(
approx.
36%)
of
the
SO2
emission
rate.
A
similar
examination
of
the
ratio
of
SO2
emissions
to
direct
emissions
of
PM2.5
yielded
a
good
fit
at
a
1/
200
ratio.
We
therefore
estimated
the
PM2.5
emission
rate
to
be
1/
200
(
approx.
0.5%)
the
SO2
rate.

10
Compilation
of
Air
Pollution
Emission
Factors:
AP­
42,
Fifth
Edition,

Volume
1:
Stationary
Point
and
Area
Sources
EPA,
1995
11
"
Summary
of
BART
Source
Analyses,"
Memorandum
from
Bill
Balcke
and
Doran
Stegura,
Perrin
Quarles
Associates,
Inc.,
to
Chad
Whiteman,
EPA
March
24,
2003.
See
2001
emissions
data
in
BART
AR
file,
copy
included
in
the
docket
10
We
simulated
two
emission
control
scenarios
 
90%
SO2
reduction
and
95%
SO2
reduction.
In
both
these
scenarios
we
also
applied
the
NOX
emission
rate
of
.2
lb/
1MM
BTU
that
is
proposed
for
power
plants
subject
to
BART12.
Direct
emission
rates
for
PM2.5
remained
the
same
for
the
base
and
control
simulations.
Table
2
shows
the
emission
rates
we
used
for
the
base
and
control
simulations.

We
carried
some
of
the
same
CALPUFF
parameters
that
were
used
in
the
NPS
analysis
mentioned
in
Section
II­
A:
monthly
average
values
for
background
concentrations
of
ozone
(
50
ppb),
ammonia
(
0.10
ppb),
and
hydrogen
peroxide
(
1.0
ppb).

These
monthly
average
values
remained
constant
from
month
to
month.

The
other
parameters
we
set
for
the
CALPUFF
simulation
are
summarized
in
Table
3.

D.
CALPOST
Parameters
We
ran
CALPOST
to
average
and
report
the
extinction
coefficients
for
visibility­
related
impacts
from
the
concentrations
output
by
CALPUFF.
CALPOST
also
reported
visibility
impacts
in
units
of
deciviews;
it
is
the
change
in
deciviews
among
the
emission
rate
scenarios
we
modeled
that
we
sought
in
this
analysis.

The
CALPOST
settings
for
this
analysis
mainly
describe
the
format
of
the
output
report.
An
exception
was
the
computation
of
light
extinction
and
associated
deciviews;
this
computation
was
performed
by
CALPOST.
Once
again,
we
carried
some
of
the
same
CALPUFF
parameters
that
were
used
in
the
NPS
analysis
12
Regional
Haze
Regulations
and
Guidelines
for
Best
Available
Retrofit
Technology
(
BART)
Determinations:
Proposed
Rule
11
mentioned
in
Section
II­
A.
We
set
background
light
extinction
values
for
sulfate
by
providing
a
monthly
value
for
background
sulfate
concentration;
this
value
was
not
considered
in
the
CALPUFF
computation
of
total
sulfate
concentration.
The
monthly
sulfate
concentration
values
were
taken
with
the
hourly
RH
values
from
CALMET/
CALPUFF
to
compute
the
background
light
extinction
due
to
sulfate.
We
also
set
a
background
value
for
light
extinction
based
upon
soil.
Background
concentrations
for
other
pollutants
(
nitrate,
organic
carbon,

elemental
carbon,
and
coarse
particles)
were
set
to
zero,
and
their
corresponding
contribution
to
the
background
light
extinction
was
zero
as
well.
The
CALPOST
parameter
settings
are
listed
in
Table
4.

E.
Results
The
CALPOST
output
reports
were
generated
for
each
emission
scenario
(
3),
for
each
year
(
5),
and
for
each
source­
receptor
distance
(
6),
for
a
total
of
90
separate
reports.
One
sample
report
for
the
200
km
distance
in
the
base
simulation
of
the
250
MW
EGU
appears
in
Table
5.

In
Table
5,
the
receptor
that
reported
the
maximum
deciview
change
due
to
pollutants
for
each
day
is
listed.
For
example,

on
day
304
receptor
number
112
reported
a
total
deciview
value
of
16.706.
Of
that
total,
10.486
deciviews
were
due
to
background
effects.
The
remainder,
6.220
deciviews,
was
due
to
the
pollutant
concentrations
output
by
CALPUFF;
the
change
in
deciviews
due
to
the
contribution
of
pollutant
concentrations
on
light
extinction
is
commonly
referred
to
in
units
of
"
delta
deciviews"
(
DDV).
Receptor
112
had
the
highest
DDV
due
to
pollutants
(
6.220)
of
any
receptor
200
km
from
the
source
on
that
day.
Of
that
6.220
DDV,
69.0%
was
due
to
the
contribution
12
from
sulfates,
30.9%
from
nitrates,
and
0.1%
from
emitted
fine
particulates.

Maximum
values
for
DDV
were
determined
for
each
distance
in
each
year,
by
EGU
size
(
Table
6.
Note,
from
the
example
above,

the
maximum
DDV
for
a
250
MW
EGU
at
200
km
in
1992
is
6.220.)

From
this
table,
the
maximum
DDV
for
each
distance
in
any
of
the
five
modeled
years
was
identified,
along
with
the
receptor
number
and
day
(
Table
7).

Once
the
locations
and
dates
of
the
maximum
DDV
over
the
5­

year
period
were
known,
we
then
examined
those
values
at
the
same
locations
and
dates
for
the
emission
control
scenarios.

The
results
are
shown
in
Table
8.
For
the
250
MW
EGU,

visibility
impact
at
receptor
10
drops
9.029
DDV
with
90%
SO2
reduction
in
emissions,
and
drops
9.649
DDV
for
95%
reduction.

For
the
750
MW
EGU
example,
visibility
impact
at
receptor
10
drops
12.318
DDV
at
90%
SO2
reduction,
drops
13.583
DDV
with
95%
reduction.

These
results
do
not
specifically
represent
any
BARTeligible
source
or
any
particular
Class
I
area
and
its
corresponding
sources.
Rather,
the
results,
and
the
entire
analysis
illustrate
what
may
be
conducted
for
a
BART
analysis,

and
indicate
the
type
of
results
the
analysis
might
yield.

III.
CALPUFF
SCREENING
ANALYSES
We
also
conducted
analyses
for
the
proposed
alternative
of
using
CALPUFF
in
a
screening
mode.
Screening
analyses
are
generally
used
to
obtain
conservative,
yet
realistic
estimates
of
impacts.
13
The
differences
in
setup
and
execution
between
the
CALPUFF
analysis
described
in
Section
II
and
the
CALPUFF
13
Appendix
W
to
40
CFR
Part
51,
The
Guideline
on
Air
Quality
Models
13
screening
analyses
described
in
this
section
are
summarized
in
Table
9,
with
further
explanations
below.
A
CALPUFF
screening
analysis
is
easier
to
set
up
and
execute
than
the
CALPUFF
analysis
described
in
Section
II,
it
does
not
require
CALMET
processing,
and
the
receptor
alignment
is
easier
to
set
up.

These
differences
also
result
in
a
faster
execution
of
the
screening
analysis.

A.
Meteorology
As
before,
we
used
five
years
of
meteorology
data.
However,

we
did
not
process
the
data
through
CALMET.
In
the
screening
mode,
CALPUFF
incorporates
a
basic
wind
field
from
only
one
meteorology
station.
In
the
same
manner
as
in
plume
models,

the
winds
are
assumed
to
be
horizontally
homogeneous
throughout
the
modeling
domain
for
each
hour.
Only
minor
processing
of
the
meteorology
data
for
Huntington
surface
station
was
necessary,
unlike
using
the
ten
surface
stations
and
three
upper­
air
stations
in
the
previous
simulations.
The
ease
of
processing
meteorology
allowed
us
to
simulate
three
other
areas,
Oklahoma
City,
Athens,
GA,
and
Phoenix.

Further
simplification
came
about
by
assuming
flat
terrain
conditions
throughout
the
modeling
domain,
and
therefore
not
processing
the
geophysical
data.
The
assumption
of
flat
terrain
is
consistent
with
the
use
of
only
a
single
wind
for
each
hour
over
the
entire
modeling
domain.

A
meteorology
input
file
was
still
generated,
although
not
by
CALMET.
In
setting
CALPUFF
parameters,
the
new
meteorology
file
was
identified
and
the
following
parameters
are
set:

CALPUFF
Variable
Value
Explanation
14
Input
Group
Name
(
setting)

1
METFM
2
Use
an
ISC
ASCII
file,

which
is
a
file
of
singlestation
meteorology
data
prepared
by
processors
for
input
into
plume
models,

much
like
the
data
processed
by
MPRM
for
input
in
to
ISC.

B.
Source/
Receptor
Relationship
As
we
described
in
the
analysis
in
Section
II,
we
created
numerous
individual
reports
running
CALMET,
CALPUFF,
and
CALPOST.
Even
though
the
screening
analysis
is
more
generalized,
there
are
still
several
files
to
deal
with.
One
reason
is
the
simplified
relationship
between
the
source
and
the
receptors.
As
in
our
previous
analysis,
we
created
a
matrix
of
receptors
that
surrounded
the
source
in
concentric
circles.
This
orientation
best
served
our
purposes
of
analyzing
discrete
distances
from
the
source
rather
than
actual
locations
of
Class
I
areas.
This
orientation
was
also
used
in
the
screening
analysis,
and
each
circle
was
processed
separately
by
CALPOST.

Our
desired
result
of
the
screening
analysis
was
a
maximum
DDV
for
each
distance
from
a
receptor
temporally
and
spatially
independent
of
any
other
value.
In
other
words,
we
wanted
to
know
the
maximum
DDV
at
a
distance
from
the
source
for
all
directions
and
times
in
the
simulation.
We
would
have
one
15
maximum
DDV
at
20
km,
at
40,
km,
and
so
on
for
each
meteorology
station
for
each
emission
scenario.

The
application
of
this
result
might
be
considered
worst
case,
and
if
such
a
worst
case
result
still
did
not
cross
some
threshold,
then
perhaps
no
further
modeling
would
be
necessary
in
a
BART
analysis.
That
application,
though,
would
be
built
on
the
assumption
that
the
screening
analysis
produced
results
more
conservative
than
the
more
involved
CALPUFF
simulation,

which
may
not
always
be
the
case.
14
However,
our
intent
was
to
generate
an
array
of
reasonably
worst
case
values
with
the
hope
that
any
loss
of
conservatism
would
be
small
enough
to
be
absorbed
in
the
calculations
and
assumptions.

C.
Emission
Scenarios
We
applied
the
same
assumptions
and
settings
concerning
background
concentrations,
species
emitted
and
modeled,
and
emissions
as
we
did
in
the
analysis
described
in
Section
II­
C.

We
also
held
the
same
ratios
of
NOx
and
PM2.5
emissions
to
SO2
emissions.
As
before
for
uncontrolled
modeling
scenarios,
when
we
varied
the
SO2
emissions,
the
emissions
of
NOx
and
PM2.5
also
varied
proportionally.
We
chose
500,
100,
200,
10000,

15000,
and
20000
tons
per
year
for
SO2
emissions.

D.
Computing
Extinction
and
Deciviews
A
departure
from
the
previous
CALPUFF
analysis
involved
setting
the
parameters
for
use
of
relative
humidity
in
computing
the
light
extinction
and
the
associated
deciviews.

Since
we
did
not
process
meteorology
through
CALMET,
we
did
not
have
hourly
RH
values
to
use
in
the
computation.
By
14
Analysis
of
the
CALMET/
CALPUFF
Modeling
System
in
a
Screening
Mode,

EPA­
454/
R­
98­
010,
November,
1998
16
setting
a
parameter
in
CALPOST,
we
use
monthly
values
for
the
F(
RH)
factor
used
in
computing
extinction.
These
values
came
from
the
FLAG
report15,
and
a
choice
to
use
the
FLAG
values
is
available
in
the
CALPOST
template
input
file.

CALPOST
Input
Group
Variable
Name
Value
(
setting)
Explanation
2
MVISBK
6
Use
the
monthly
factors
from
the
FLAG
report.

2
RHFAC
2.98,2.79,2.81,2.56
3.12,3.39,3.54,3.87
3.85,3.27,2.97,3.10
Set
the
FLAG
values
for
F(
RH)

E.
Results
The
results
of
this
modeling
were
also
used
to
produce
the
look­
up
tables,
another
proposed
alternative
for
assessing
visibility
impacts.
We
discuss
those
results
in
the
following
section.

15
Federal
Land
Managers'
Air
Quality
Related
Values
Workgroup
(
FLAG)

Phase
I
Report,
December
2000
17
III.
LOOK­
UP
TABLE
This
option
would
allow
a
State
or
source
to
look
up
the
maximum
allowable
annual
emission
rate
of
visibility
impairing
pollutants
(
SO2,
NOx,
and
direct
PM2.5)
at
a
given
distance
that
would
yield
a
CALPUFF­
modeled
net
visibility
impact
at
a
particular
threshold
value
(
in
this
example
0.5
DDV).
To
create
this
look­
up
table,
we
conducted
several
screening
analyses
with
varying
SO2
emission
rates
and,
by
the
ratios,

varying
NOx
and
PM2.5
emission
rates
as
well.
We
applied
the
results
of
these
screening
analyses
to
build
linear
regression
equations,
which
we
used
to
generate
a
table.

Step
1
was
to
generate
tables
of
the
maximum
DDV
for
each
distance
for
each
SO2
emission
scenario,
and
for
each
of
the
four
meteorology
stations.
We
grouped
and
sorted
the
data
so
that
for
each
downwind
distance
the
DDV
were
ranked
from
highest
to
lowest
for
each
level
of
SO2
emissions.
This
data
appears
in
Tables
10­
13.

We
combined
data
for
Huntington
and
Athens
into
an
"
East"

category,
and
Oklahoma
City
and
Phoenix
into
a
"
West"

category,
providing
ten
DDV
values
for
each
SO2
emission
rate,

for
each
downwind
distance
for
the
East
and
for
the
West.
From
those
ten
values,
we
extracted
the
maximum
values
and
generated
linear
regression
equations
to
compute
DDV
from
SO2
emission
rate.
From
there,
we
set
the
DDV
to
0.5
(
the
threshold
value
in
the
proposal),
and
calculated
what
SO2
emissions
rate
would
be
required
at
each
distance
to
result
in
0.5
DDV.
Those
emission
rate/
distance
combinations
were
used
to
again
generate
another
linear
regression
equation
to
compute
the
SO2
emission
rate
as
a
function
of
distance.
The
look­
up
table
prototype
was
generated
from
that
equation.

Table
14
is
an
example
of
the
look­
up
table.
18
Of
course,
this
is
again
an
illustrative
example.
If
a
table
were
to
be
generated
for
States
and
sources
to
use,
more
screening
analyses
would
have
to
be
done
to
provide
more
data
points.
Non­
linear
relationships
would
be
examined
to
better
characterize
the
data.
Several
threshold
values
could
be
used
to
create
tables
for
bracketing.
It
is
unclear
whether
one
table
would
be
applicable
for
a
region
or
a
State,
as
we
found
significant
differences
in
the
values
for
tables
in
the
East
and
West.

The
advantages
of
the
look­
up
tables
are
that
they
are
easy
to
use
and
no
modeling
would
be
required.
However,
they
may
be
too
general
to
represent
all
source
categories.
For
instance,
the
source
category
in
the
example
in
Table
14
is
EGUs.
Another
source
category
may
have
different
source
and
emissions
characteristics
which
may
require
development
of
a
separate
look­
up
table.
Also,
the
meteorological
stations
used
may
not
be
appropriate
for
all
geographic
areas
in
the
East
and
West,
and
the
ratios
used
for
emission
estimates
would
likely
be
different
for
each
source
category.
Several
sets
of
look­
up
tables
requiring
several
sets
of
assumptions
may
be
cumbersome
and
complex
in
development
and
still
may
not
be
meaningful
for
the
desired
purpose.

IV.
SUMMARY
In
support
of
this
proposal,
we
illustrated
three
possible
methods
to
assess
the
visibility
impacts
for
the
BART
analysis:
1)
A
comprehensive
CALPUFF
simulation
performed
for
a
domain
in
the
East
for
five
years
of
meteorology
data;

2)
Several
screening
analyses
using
CALPUFF
were
also
performed
for
the
same
time
period;
and
3)
A
look­
up
table
was
created
based
upon
the
results
of
the
screening
analyses.
Procedures
19
for
applying
each
method,
as
well
as
output
from
the
three
methods
were
discussed.
20
Figure
1
The
Huntington,
WV
CALPUFF
Modeling
Domain
21
Figure
2
Number
of
BART
Eligible
EGUs
by
SO2/
Nox
Ratio
Eastern
Region
0
10
20
30
40
50
<
0.2
0.2­
0.4
0.4­
0.6
0.6­
0.8
0.8­
1.0
1
­
2
2
­
3
3
­
4
4
­
5
5
­
6
>
6
SO2/
NOx
Ratio
Number
of
EGUs
22
TABLE
1
CALMET
Parameter
Variables
and
Settings
Input
Group
Variable
Name
Value
(
setting)
Explanation
0
LCLFILES
F
Sets
the
file
names
to
all
UPPERCASE
0
NUSTA
3
Number
of
upper­
air
stations
0
NOWSTA
0
Number
of
overwater
stations
2
PMAP
LCC
Set
Lambert
Conformal
map
projection
2
RLAT0
37N
Set
reference
latitude
2
RLON0
83W
Set
projection
central
meridian
2
XLAT1
30N
projection
cone
slice
point
2
XLAT2
60N
projection
cone
slice
point
2
NX
101
number
of
grid
cells
in
X
direction
2
NY
93
number
of
grid
cells
in
Y
direction
2
DGRIDKM
3
grid
spacing
in
km
2
XORIGKM
160
[
southwest
corner
of
grid
xcoordinate
2
YORIGKM
60
[
southwest
corner
of
grid
ycoordinate
2
NZ
10
number
of
vertical
layers
2
ZFACE
0,20,50,75,100,250,500,
750,1000,2000,3000
heights
of
vertical
layers
4
NSSTA
10
number
of
surface
stations
4
NPSTA
9
number
of
precipitation
stations
4
IFORMC
1
sets
output
format
to
be
CALPUFF
input
5
BIAS
­
1,
9*
1
gives
100%
weight
to
surface
obs
for
layer
1
winds,
and
100%
weight
to
upper­
air
obs
for
other
layers
5
LVARY
T
use
varying
radius
of
influence
to
find
valid
data
5
RMAX1
30
max
radius
of
influence
at
the
sfc
5
RMAX2
30
[
max
radius
of
influence
aloft
5
RMAX3
50
max
radius
of
influence
over
water
5
TERRAD
10
radius
of
influence
of
terrain
5
R1
1
[
sfc
obs
and
first­
guess
data
equally
weighted
if
they're
within
1
km
of
each
other
5
R2
1
same
as
R1,
only
for
data
aloft
5
NITER
50
use
the
max
number
of
iterations(
50)
in
minimizing
divergence
5
NSMTH
2,8,8,12,12,12,0,0,0,0
number
of
passes
in
the
smoothing
procedure
for
each
vertical
layer
23
TABLE
1
(
cont.)
CALMET
Parameter
Variables
and
Settings
Input
Group
Variable
Name
Value
(
setting)
Explanation
5
NINTR2
5,5,5,5,5,5,5,0,0,0
max
number
of
stations
to
use
to
interpolate
data
to
a
grid
point,
for
each
vertcal
layer
5
ISURFT
2
Use
surface
station
#
2
(
BECK)
to
get
sfc
temp
for
diagnostic
wind
module
5
IUPT
1
Use
upper­
air
station
#
1
(
STIR)
to
calculate
lapse
rate
for
the
domain.
6
MNMDAV
10
Search
no
more
than
10
grid
cells
in
X,
Y
direction
for
spatial
averaging
of
mixing
heights.
6
ZIMAX
2500
Set
max
mixing
height
over
land.
6
ZIMAXW
2500
Set
max
mixing
height
over
water.
6
TRADKM
20
Set
radius
of
influence
in
km
for
temperature
interpolation.
6
JWAT1
55
Disable
temperature
interpolation
over
water.
6
JWAT2
55
Disable
temperature
interpolation
over
water.
6
SIGMAP
50
Set
radius
of
influence
for
precipitation
interpolation.
7
SS1
HUNT
Identify
surface
met
station.
7
SS2
BECK
Identify
surface
met
station.
7
SS3
ELKI
Identify
surface
met
station.
7
SS4
RICH
Identify
surface
met
station.
7
SS5
ROAN
Identify
surface
met
station.
7
SS6
CHAR
Identify
surface
met
station.
7
SS7
HARR
Identify
surface
met
station.
7
SS8
BALT
Identify
surface
met
station.
7
SS9
PITT
Identify
surface
met
station.
7
SS10
MTST
Identify
surface
met
station.
8
US1
STIR
Identify
upper­
air
station.
8
US2
PITT
Identify
upper­
air
station.
8
US3
HUNT
Identify
upper­
air
station.
9
PS1
HUNT
Identify
precipitation
station
9
PS2
BECK
Identify
precipitation
station
9
PS3
ELKI
Identify
precipitation
station
9
PS4
RICH
Identify
precipitation
station
9
PS5
ROAN
Identify
precipitation
station
9
PS6
CHAR
Identify
precipitation
station
9
PS7
HARR
Identify
precipitation
station
9
PS8
BALT
Identify
precipitation
station
9
PS9
PITT
Identify
precipitation
station
24
Table
2
Emission
rates
for
the
Huntington
simulations
Sim
MW
EGU
SO2
tpy
NOx
tpy
PM2.5
tpy
Base
250
29185
10423
146
90%
reduction
250
2919
2300
146
95%
red.
250
1459
2300
146
Base
750
87556
31271
438
90%
red.
750
8756
6899
438
95%
red.
750
4378
6899
438
25
TABLE
3
CALPUFF
Parameter
Variables
and
Settings
Input
Group
Variable
Name
Value
(
setting)
Explanation
0
NMETDAT
12
Incorporate
12
CALMET
files
(
1
per
month).
1
NSPEC
6
Set
the
number
of
chemical
species
to
model.
1
NSE
3
Set
number
of
chemical
species
emitted.
2
MSPLIT
1
Allow
puff
splitting.
3a
CSPEC
SO2
Identify
chemical
species
to
be
modeled.
3a
CSPEC
SO4
Identify
chemical
species
to
be
modeled.
3a
CSPEC
NOX
Identify
chemical
species
to
be
modeled.
3a
CSPEC
HNO3
Identify
chemical
species
to
be
modeled.
3a
CSPEC
NO3
Identify
chemical
species
to
be
modeled.
3a
CSPEC
PM25
Identify
chemical
species
to
be
modeled.
3a
SO2
1,1,1,0
Set
as
modeled,
emitted,
gas
deposited.
3a
SO4
1,0,2,0
Set
as
modeled,
not
emitted,
particle
deposited.
3a
NOX
1,1,1,0
Set
as
modeled,
emitted,
gas
deposited.
3a
HNO3
1,0,1,0
Set
as
modeled,
not
emitted,
gas
deposited.
3a
NO3
1,0,2,0
Set
as
modeled,
not
emitted,
particle
deposited
3a
PM25
1,1,2,0
Set
as
modeled,
emitted,
particle
deposited.
4
RLAT0
37N
Setting
consistent
with
CALMET.
4
RLON0
83W
Setting
consistent
with
CALMET.
4
XLAT1
30N
Setting
consistent
with
CALMET.
4
XLAT2
60N
Setting
consistent
with
CALMET.
4
NX
101
Setting
consistent
with
CALMET.
4
NY
93
Setting
consistent
with
CALMET.
4
NZ
10
Setting
consistent
with
CALMET.
4
DGRIDKM
3
Setting
consistent
with
CALMET.
4
ZFACE
0,20,50,75,100,250,500,
750,1000,2000,3000
Setting
consistent
with
CALMET.

4
XORIGKM
160
Setting
consistent
with
CALMET.
4
YORIGKM
60
Setting
consistent
with
CALMET.
26
TABLE
3
(
cont.)
CALPUFF
Parameter
Variables
and
Settings
Input
Group
Variable
Name
Value
(
setting)
Explanation
4
IBCOMP
5
Set
computational
grid
to
5
grid
cells
inside
CALMET
grid
in
X
dir.
4
JBCOMP
5
Set
computational
grid
to
5
grid
cells
inside
CALMET
grid
in
Y
dir.
4
IECOMP
96
Set
number
of
computational
grid
cells
in
X
dir.
4
JECOMP
88
Set
number
of
computational
grid
cells
in
Y
dir.
4
LSAMP
F
Set
no
gridded
receptors;
all
receptors
are
discrete.
5
IPRTU
3
Set
units
to
print
as
ug/
m**
3
6
NHILL
0
Set
no
CTDM
processing.
6
MHILL
2
Set
no
CTDM
processing.
6
XCTDMKM
0
Set
no
CTDM
processing.
6
YCTDMKM
0
Set
no
CTDM
processing.
7
HNO3
0.1628,1,18,0,
0.00000008
Set
chemical
parameters
for
HNO3,
which
had
no
default
values
stated.
8
SO4
0.48,2
Set
dry
deposition
parameters.
8
NO3
0.48,2
Set
dry
deposition
parameters.
8
PM25
0.48,2
Set
dry
deposition
parameters.
10
SO4
1.0E­
04,
3.0E­
05
Set
wet
deposition
parameters.
10
HNO3
6.0E­
05,
0.0E00
Set
wet
deposition
parameters.
10
NO3
1.0E­
04,
3.0E­
05
Set
wet
deposition
parameters.
11
MOZ
0
Use
monthly
background
ozone.
11
BCKO3
12*
50
Set
monthly
background
ozone
for
each
month
to
50
ppb.
11
BCKNH3
12*
0.10
Set
monthly
background
ammonia
concentration
for
each
month
to
0.1
ppb
11
MH2O2
0
Use
monthly
background
hydrogen
peroxide.
11
BCKH2O2
120*
01.00
Set
monthly
background
hydrogen
peroxide
concentration
for
each
month
to
1.0
ppb
13a
NPT1
1
Set
number
of
point
sources
to
1.
13a
IPTU
4
Set
units
to
tons/
yr.
13a
NPT2
0
The
point
source
does
not
use
variable
emissions.
13b
SRCNAM
EGU_
250_
00
Identify
source
scenario
for
250
MW
EGU
base
simulation.
13b
X
205,105,100,200,8.0,
27.0,400,0,29185,0.0,
10423,0.0
Set
source
location,
parameters
and
emissions
data
(
for
species
in
CSPEC
above)
for
250
MW
EGU
base
simulation.
14
NAR1
0
No
area
sources
are
included.
27
TABLE
3
(
cont.)
CALPUFF
Parameter
Variables
and
Settings
Input
Group
Variable
Name
Value
(
setting)
Explanation
14
NAR2
0
No
area
sources
are
included.
15
NLN2
0
No
line
sources
are
included.
16
NVL1
0
No
volume
sources
are
included.
16
NVL2
0
No
volume
sources
are
included.
17a
NREC
144
Set
144
non­
gridded
receptors.
17b
X
Identify
receptors.
28
TABLE
4
CALPOST
Parameter
Variables
and
Settings
Input
Group
Variable
Name
Value
(
setting)
Explanation
1
ASPEC
VISIB
Process
visibility.
1
LD
1
Process
discrete
receptors.
1
NDRECP
Select
which
receptors
to
process
in
this
simulation.
2
LVSO4
T
Include
modeled
sulfate
in
visibility
calculation.
2
LVNO3
T
Include
modeled
nitrate
in
visibility
calculation
2
LVOC
F
Do
not
include
modeled
organic
carbon
in
visibility
calculation.
2
LVPMC
F
Do
not
include
modeled
coarse
particles
in
visibility
calculation.
2
LVPMF
T
Include
modeled
fine
particulates
in
visibility
calculation.
2
LVEC
F
Do
not
include
modeled
elemental
carbon
in
visibility
calculation.
2
LVBK
F
Do
not
include
background
in
TOP(
n)
visibility
calculations.
2
MVISBK
2
Compute
background
extinction
by
applying
hourly
RH
adjustment
to
modeled
sulfate
and
nitrate.
2
SPECPMC
PMC
Assign
species
name
from
CALPUFF
file
for
coarse
particles.
2
SPECPMF
PM25
Assign
species
name
from
CALPUFF
file
for
fine
particles.
2
BKSO4
0.3,0.3,0.3,0.3,
0.3,0.3,0.3,0.3,
0.3,0.3,0.3,0.3
Set
the
background
concentration
of
sulfate,
in
ug/
m3,
for
each
month.

2
BKNO3
0.0,0.0,0.0,0.0,
0.0,0.0,0.0,0.0,
0.0,0.0,0.0,0.0
Set
the
background
concentration
of
nitrate,
in
ug/
m3,
for
each
month.

2
BKPMC
0.0,0.0,0.0,0.0,
0.0,0.0,0.0,0.0,
0.0,0.0,0.0,0.0
Set
the
background
concentration
of
coarse
particulates,
in
ug/
m3,
for
each
month.
2
BKOC
0.0,0.0,0.0,0.0,
0.0,0.0,0.0,0.0,
0.0,0.0,0.0,0.0
Set
the
background
concentration
of
organic
carbon,
in
ug/
m3,
for
each
month.

2
BKSOIL
8.5,8.5,8.5,8.5,
8.5,8.5,8.5,8.5,
8.5,8.5,8.5,8.5
Set
the
background
concentration
of
soil
(
dust),
in
ug/
m3,
for
each
month.

2
BKEC
0.0,0.0,0.0,0.0,
0.0,0.0,0.0,0.0,
0.0,0.0,0.0,0.0
Set
the
background
concentration
of
elemental
carbon,
in
ug/
m3,
for
each
month.
29
TABLE
4
(
cont.)
CALPOST
Parameter
Variables
and
Settings
Input
Group
Variable
Name
Value
(
setting)
Explanation
3
IPRTU
3
Set
concentration
units
to
ug/
m3.

3
L1HR
F
Do
not
report
out
1­
hour
averages.
3
L3HR
F
Do
not
report
out
3­
hour
averages.
3
L24HR
T
Report
out
24­
hour
averages.
3
LRUNL
F
Do
not
report
length­
of­
run
averages.
3
LT50
F
Do
not
produce
"
Top
50"
tables.
3
LTOPN
F
Do
not
produce
"
Top(
N)"
tables.
Table
5
Deciviews
for
Receptors
200
km
from
a
250
MW
EGU
(
Base)

30
Bkgnd.
Conc.
Total
Year
Day
Recp
.
%_
SO4
%_
NO3
%_
PMF
DV
DV
DV
1992
2
97
63.4%
36.4%
0.3%
7.330
0.251
7.581
1992
3
99
55.6%
44.3%
0.1%
7.607
1.587
9.195
1992
4
96
67.1%
31.5%
1.4%
7.221
0.000
7.221
1992
5
96
0.0%
0.0%
0.0%
7.485
0.000
7.485
1992
6
96
0.0%
0.0%
0.0%
8.426
0.000
8.426
1992
7
96
0.0%
0.0%
0.0%
7.290
0.000
7.290
1992
8
96
0.0%
0.0%
0.0%
7.297
0.000
7.297
1992
9
99
70.0%
29.8%
0.3%
7.888
1.088
8.976
1992
10
113
41.6%
58.3%
0.1%
9.172
1.031
10.203
1992
11
114
30.8%
69.1%
0.1%
9.617
0.583
10.200
1992
12
96
0.0%
0.0%
0.0%
7.200
0.000
7.200
1992
13
111
37.1%
62.8%
0.1%
7.844
1.213
9.057
1992
14
101
65.1%
34.9%
0.1%
7.835
2.771
10.606
1992
15
101
36.5%
63.1%
0.5%
7.716
0.434
8.150
1992
16
108
30.8%
68.9%
0.3%
7.220
0.214
7.433
1992
17
114
37.9%
60.9%
1.3%
6.657
0.119
6.776
1992
18
109
30.3%
68.1%
1.7%
6.878
0.156
7.034
1992
19
96
0.0%
0.0%
0.0%
7.090
0.000
7.090
1992
20
111
44.6%
54.9%
0.5%
6.989
0.170
7.159
1992
21
107
28.8%
70.7%
0.6%
7.391
0.349
7.740
1992
22
112
34.4%
64.6%
1.1%
6.852
0.277
7.130
1992
23
114
32.5%
67.2%
0.4%
7.427
0.932
8.360
1992
24
98
40.1%
59.0%
0.9%
8.421
0.257
8.678
1992
25
114
71.2%
26.6%
2.3%
6.702
0.048
6.749
Table
5
Deciviews
for
Receptors
200
km
from
a
250
MW
EGU
(
Base)

31
1992
26
108
63.7%
36.3%
0.1%
8.304
2.307
10.610
1992
27
111
36.5%
63.0%
0.5%
7.634
0.064
7.698
1992
28
99
42.2%
57.5%
0.3%
7.611
2.375
9.986
1992
29
111
46.7%
53.2%
0.1%
8.240
0.799
9.040
1992
30
113
71.2%
28.6%
0.2%
7.711
2.110
9.821
1992
31
110
47.1%
52.8%
0.2%
7.542
3.551
11.094
1992
32
113
40.9%
58.5%
0.5%
7.162
0.338
7.500
1992
33
96
0.0%
0.0%
0.0%
7.169
0.000
7.169
1992
34
96
0.0%
0.0%
0.0%
7.347
0.000
7.347
1992
35
96
0.0%
0.0%
0.0%
7.653
0.000
7.653
1992
36
109
35.3%
64.4%
0.3%
7.965
1.522
9.487
1992
37
96
0.0%
0.0%
0.0%
7.058
0.000
7.058
1992
38
96
0.0%
0.0%
0.0%
7.161
0.000
7.161
1992
39
114
49.8%
50.1%
0.1%
7.649
0.692
8.341
1992
40
114
38.5%
61.1%
0.3%
7.346
0.006
7.351
1992
41
96
0.0%
0.0%
0.0%
7.020
0.000
7.020
1992
42
96
0.0%
0.0%
0.0%
6.913
0.000
6.913
1992
43
114
83.9%
14.4%
1.7%
6.840
0.111
6.951
1992
44
96
0.0%
0.0%
0.0%
6.774
0.000
6.774
1992
45
105
58.3%
41.4%
0.3%
8.129
0.740
8.868
1992
46
114
36.8%
62.9%
0.3%
7.592
0.271
7.863
1992
47
98
52.1%
47.5%
0.3%
9.627
0.988
10.615
1992
48
110
54.2%
45.6%
0.2%
7.812
1.056
8.867
1992
49
110
42.0%
57.8%
0.2%
8.126
0.191
8.317
1992
50
96
86.5%
13.2%
0.3%
8.192
0.703
8.895
1992
51
106
30.7%
69.0%
0.3%
7.604
0.398
8.001
1992
52
112
55.5%
44.1%
0.4%
6.959
0.193
7.152
1992
53
110
39.1%
59.7%
1.2%
6.959
0.438
7.397
Table
5
Deciviews
for
Receptors
200
km
from
a
250
MW
EGU
(
Base)

32
1992
54
106
56.1%
43.5%
0.4%
7.341
1.510
8.851
1992
55
110
49.6%
50.2%
0.2%
8.083
2.195
10.278
1992
56
101
69.9%
29.9%
0.2%
9.861
0.097
9.958
1992
57
102
77.3%
22.6%
0.1%
10.331
1.519
11.850
1992
58
114
62.8%
30.7%
6.6%
10.164
0.003
10.167
1992
59
114
34.5%
65.2%
0.3%
7.825
1.033
8.858
1992
60
110
33.8%
65.2%
1.0%
7.051
0.293
7.344
1992
61
109
13.1%
84.6%
2.4%
7.049
0.012
7.060
1992
62
114
32.0%
66.9%
1.1%
6.720
0.292
7.013
1992
63
112
78.9%
19.3%
1.9%
6.746
0.381
7.127
1992
64
111
75.9%
23.6%
0.6%
7.033
0.231
7.264
1992
65
112
91.0%
9.0%
0.0%
10.021
0.582
10.603
1992
66
106
83.4%
16.5%
0.1%
7.566
2.364
9.930
1992
67
100
45.5%
54.2%
0.3%
7.738
1.831
9.569
1992
68
107
70.1%
29.7%
0.2%
7.987
0.721
8.708
1992
69
114
30.6%
69.3%
0.1%
8.900
0.624
9.524
1992
70
100
85.0%
14.3%
0.7%
7.662
0.151
7.813
1992
71
105
62.0%
37.6%
0.4%
7.777
0.151
7.928
1992
72
112
39.8%
58.3%
2.0%
7.263
0.028
7.291
1992
73
114
54.5%
44.1%
1.5%
6.710
0.056
6.766
1992
74
114
31.9%
66.4%
1.6%
6.712
0.000
6.712
1992
75
114
38.8%
60.3%
1.0%
6.806
0.748
7.553
1992
76
114
59.8%
39.3%
0.9%
6.903
0.002
6.905
1992
77
114
43.8%
55.4%
0.8%
6.703
0.050
6.754
1992
78
108
33.3%
65.4%
1.2%
7.559
0.376
7.935
1992
79
96
0.0%
0.0%
0.0%
9.255
0.000
9.255
1992
80
111
70.3%
29.4%
0.3%
9.246
0.171
9.417
1992
81
96
0.0%
0.0%
0.0%
7.761
0.000
7.761
Table
5
Deciviews
for
Receptors
200
km
from
a
250
MW
EGU
(
Base)

33
1992
82
114
39.1%
60.2%
0.7%
6.837
0.000
6.837
1992
83
103
36.5%
63.2%
0.2%
8.183
1.224
9.407
1992
84
96
0.0%
0.0%
0.0%
7.582
0.000
7.582
1992
85
114
75.0%
24.6%
0.4%
6.840
0.022
6.862
1992
86
101
48.9%
50.7%
0.4%
7.427
1.342
8.768
1992
87
113
75.9%
24.1%
0.0%
11.126
1.344
12.470
1992
88
114
66.4%
33.5%
0.1%
7.547
1.351
8.898
1992
89
96
0.0%
0.0%
0.0%
7.042
0.000
7.042
1992
90
110
66.2%
33.0%
0.8%
7.083
0.007
7.091
1992
91
101
69.7%
30.2%
0.1%
9.079
2.591
11.670
1992
92
114
74.9%
24.2%
0.8%
7.420
0.074
7.494
1992
93
110
56.4%
43.3%
0.3%
7.856
0.897
8.753
1992
94
96
0.0%
0.0%
0.0%
8.020
0.000
8.020
1992
95
114
54.0%
44.5%
1.6%
6.678
0.018
6.696
1992
96
106
63.4%
36.5%
0.1%
8.081
2.215
10.296
1992
97
114
75.9%
24.0%
0.1%
7.150
0.204
7.354
1992
98
96
0.0%
0.0%
0.0%
6.960
0.000
6.960
1992
99
107
80.2%
18.6%
1.2%
6.812
0.650
7.462
1992
100
111
56.6%
43.3%
0.1%
7.337
0.419
7.756
1992
101
105
83.6%
15.8%
0.5%
7.291
0.795
8.086
1992
102
106
54.4%
45.5%
0.1%
8.467
0.719
9.186
1992
103
109
50.3%
49.6%
0.1%
8.362
3.776
12.138
1992
104
111
85.7%
14.1%
0.2%
8.823
0.308
9.131
1992
105
96
0.0%
0.0%
0.0%
6.760
0.000
6.760
1992
106
111
88.7%
11.0%
0.4%
6.924
0.146
7.071
1992
107
114
91.2%
8.4%
0.4%
6.834
0.098
6.932
1992
108
103
79.7%
19.9%
0.5%
7.607
0.939
8.546
1992
109
106
48.1%
51.6%
0.3%
7.848
0.345
8.193
Table
5
Deciviews
for
Receptors
200
km
from
a
250
MW
EGU
(
Base)

34
1992
110
110
43.0%
56.9%
0.1%
8.446
0.837
9.283
1992
111
105
62.6%
37.4%
0.1%
8.648
1.811
10.459
1992
112
96
95.2%
3.7%
1.2%
7.155
0.382
7.537
1992
113
97
80.2%
19.2%
0.6%
8.822
0.878
9.700
1992
114
99
44.7%
55.1%
0.3%
7.639
0.858
8.497
1992
115
113
84.9%
13.7%
1.5%
6.863
0.410
7.273
1992
116
108
81.2%
16.3%
2.5%
6.995
0.236
7.231
1992
117
96
0.0%
0.0%
0.0%
8.348
0.000
8.348
1992
118
96
0.0%
0.0%
0.0%
7.750
0.000
7.750
1992
119
96
0.0%
0.0%
0.0%
7.150
0.000
7.150
1992
120
96
0.0%
0.0%
0.0%
6.915
0.000
6.915
1992
121
113
89.4%
10.4%
0.2%
8.525
0.259
8.784
1992
122
109
70.9%
28.9%
0.2%
8.080
1.227
9.308
1992
123
112
95.0%
4.7%
0.4%
8.847
0.045
8.892
1992
124
107
88.8%
7.3%
3.9%
6.993
0.214
7.208
1992
125
114
86.5%
8.5%
5.0%
6.824
0.008
6.832
1992
126
96
0.0%
0.0%
0.0%
7.017
0.000
7.017
1992
127
96
0.0%
0.0%
0.0%
8.133
0.000
8.133
1992
128
96
0.0%
0.0%
0.0%
7.558
0.000
7.558
1992
129
96
0.0%
0.0%
0.0%
6.933
0.000
6.933
1992
130
96
0.0%
0.0%
0.0%
7.638
0.000
7.638
1992
131
104
82.0%
17.7%
0.4%
8.192
0.970
9.162
1992
132
112
73.5%
26.4%
0.1%
8.089
0.482
8.571
1992
133
96
0.0%
0.0%
0.0%
7.606
0.000
7.606
1992
134
101
95.4%
4.3%
0.3%
7.638
0.663
8.301
1992
135
99
89.1%
10.9%
0.1%
7.803
1.177
8.980
1992
136
113
83.0%
16.9%
0.1%
8.749
0.018
8.766
1992
137
96
0.0%
0.0%
0.0%
6.871
0.000
6.871
Table
5
Deciviews
for
Receptors
200
km
from
a
250
MW
EGU
(
Base)

35
1992
138
104
93.5%
6.2%
0.3%
7.865
0.355
8.220
1992
139
102
88.1%
11.6%
0.2%
7.655
1.805
9.460
1992
140
112
50.1%
49.9%
0.1%
10.562
1.074
11.636
1992
141
96
0.0%
0.0%
0.0%
6.888
0.000
6.888
1992
142
96
0.0%
0.0%
0.0%
6.902
0.000
6.902
1992
143
96
98.9%
0.1%
1.0%
6.693
0.019
6.711
1992
144
96
85.1%
14.5%
0.4%
6.850
0.104
6.954
1992
145
111
90.1%
9.8%
0.1%
7.595
0.779
8.374
1992
146
114
92.4%
7.2%
0.4%
8.254
0.009
8.263
1992
147
96
0.0%
0.0%
0.0%
6.969
0.000
6.969
1992
148
114
94.6%
5.3%
0.1%
10.506
0.283
10.789
1992
149
96
0.0%
0.0%
0.0%
6.927
0.000
6.927
1992
150
96
0.0%
0.0%
0.0%
7.014
0.000
7.014
1992
151
96
0.0%
0.0%
0.0%
6.908
0.000
6.908
1992
152
98
74.6%
25.4%
0.1%
9.090
0.545
9.636
1992
153
114
74.2%
25.7%
0.1%
9.363
0.757
10.121
1992
154
96
0.0%
0.0%
0.0%
7.439
0.000
7.439
1992
155
96
0.0%
0.0%
0.0%
7.319
0.000
7.319
1992
156
97
99.5%
0.1%
0.3%
7.269
0.192
7.461
1992
157
96
0.0%
0.0%
0.0%
8.079
0.000
8.079
1992
158
104
97.9%
2.0%
0.1%
8.607
0.033
8.641
1992
159
112
76.8%
23.0%
0.2%
9.055
1.785
10.839
1992
160
104
83.7%
16.1%
0.2%
9.047
2.554
11.601
1992
161
109
63.8%
36.0%
0.2%
8.236
0.477
8.713
1992
162
114
98.4%
1.2%
0.4%
10.192
0.034
10.226
1992
163
96
0.0%
0.0%
0.0%
6.803
0.000
6.803
1992
164
96
0.0%
0.0%
0.0%
6.712
0.000
6.712
1992
165
96
0.0%
0.0%
0.0%
6.849
0.000
6.849
Table
5
Deciviews
for
Receptors
200
km
from
a
250
MW
EGU
(
Base)

36
1992
166
103
98.7%
1.0%
0.4%
8.121
0.446
8.568
1992
167
101
92.5%
7.4%
0.1%
8.294
1.130
9.424
1992
168
107
93.3%
6.6%
0.1%
8.124
0.363
8.487
1992
169
114
97.1%
2.9%
0.1%
8.107
0.021
8.129
1992
170
97
97.7%
1.5%
0.8%
7.069
0.457
7.526
1992
171
100
92.7%
6.8%
0.5%
7.715
0.971
8.686
1992
172
104
92.4%
6.9%
0.7%
7.482
0.467
7.948
1992
173
96
0.0%
0.0%
0.0%
7.410
0.000
7.410
1992
174
96
0.0%
0.0%
0.0%
7.270
0.000
7.270
1992
175
96
0.0%
0.0%
0.0%
7.382
0.000
7.382
1992
176
106
96.9%
2.4%
0.7%
7.631
0.363
7.994
1992
177
112
83.0%
16.7%
0.3%
8.518
0.414
8.932
1992
178
114
75.5%
24.5%
0.1%
9.971
3.653
13.624
1992
179
114
54.3%
45.7%
0.1%
10.455
0.945
11.400
1992
180
113
49.7%
50.2%
0.1%
8.743
0.504
9.247
1992
181
96
0.0%
0.0%
0.0%
7.147
0.000
7.147
1992
182
104
98.4%
1.3%
0.3%
7.889
0.713
8.602
1992
183
106
78.0%
21.7%
0.3%
8.127
1.358
9.484
1992
184
109
70.4%
29.5%
0.1%
9.004
1.567
10.570
1992
185
105
98.5%
1.3%
0.1%
8.462
0.589
9.051
1992
186
103
95.0%
4.6%
0.4%
8.030
1.355
9.384
1992
187
113
62.4%
37.5%
0.1%
9.789
1.147
10.936
1992
188
112
54.1%
45.8%
0.1%
8.814
1.581
10.395
1992
189
114
22.5%
77.3%
0.2%
9.835
0.245
10.080
1992
190
96
0.0%
0.0%
0.0%
7.230
0.000
7.230
1992
191
112
82.1%
17.8%
0.1%
8.218
0.537
8.755
1992
192
112
96.9%
2.4%
0.7%
7.791
0.125
7.917
1992
193
113
98.5%
0.3%
1.2%
7.136
0.374
7.510
Table
5
Deciviews
for
Receptors
200
km
from
a
250
MW
EGU
(
Base)

37
1992
194
114
89.6%
9.8%
0.6%
7.498
0.626
8.124
1992
195
109
91.2%
8.3%
0.5%
7.676
0.922
8.598
1992
196
110
91.3%
8.2%
0.5%
7.614
0.254
7.869
1992
197
111
83.7%
15.4%
0.8%
7.585
0.809
8.395
1992
198
107
83.1%
15.4%
1.5%
7.909
0.200
8.109
1992
199
114
64.4%
35.4%
0.2%
9.542
0.973
10.515
1992
200
101
76.2%
23.3%
0.5%
8.432
0.850
9.281
1992
201
114
71.4%
28.4%
0.2%
9.009
1.283
10.292
1992
202
114
79.2%
20.7%
0.1%
9.485
2.040
11.525
1992
203
114
72.2%
27.7%
0.1%
8.585
2.382
10.967
1992
204
111
74.4%
25.5%
0.1%
8.803
0.940
9.743
1992
205
114
74.4%
25.5%
0.1%
10.703
0.599
11.302
1992
206
111
97.0%
2.9%
0.1%
8.720
0.763
9.483
1992
207
113
91.4%
8.5%
0.1%
9.870
1.565
11.436
1992
208
114
98.7%
1.1%
0.2%
9.816
0.154
9.970
1992
209
114
65.9%
34.0%
0.1%
10.441
1.733
12.174
1992
210
114
47.4%
52.5%
0.1%
9.344
0.169
9.513
1992
211
96
0.0%
0.0%
0.0%
7.787
0.000
7.787
1992
212
113
98.7%
0.9%
0.4%
8.602
0.391
8.993
1992
213
113
68.3%
31.5%
0.3%
8.374
0.659
9.033
1992
214
101
37.5%
62.4%
0.1%
8.228
0.350
8.578
1992
215
96
0.0%
0.0%
0.0%
7.720
0.000
7.720
1992
216
105
90.6%
9.2%
0.2%
8.742
1.131
9.873
1992
217
108
55.0%
44.9%
0.1%
8.683
3.621
12.304
1992
218
109
66.0%
33.9%
0.2%
8.508
0.683
9.191
1992
219
96
0.0%
0.0%
0.0%
7.374
0.000
7.374
1992
220
96
0.0%
0.0%
0.0%
7.228
0.000
7.228
1992
221
96
99.0%
0.4%
0.5%
7.131
0.506
7.637
Table
5
Deciviews
for
Receptors
200
km
from
a
250
MW
EGU
(
Base)

38
1992
222
102
94.8%
4.2%
1.1%
7.471
0.294
7.765
1992
223
106
62.7%
36.9%
0.4%
8.058
0.397
8.455
1992
224
114
98.4%
1.4%
0.2%
8.609
0.076
8.686
1992
225
111
82.8%
16.9%
0.3%
8.557
0.536
9.092
1992
226
96
0.0%
0.0%
0.0%
7.259
0.000
7.259
1992
227
96
0.0%
0.0%
0.0%
7.596
0.000
7.596
1992
228
96
0.0%
0.0%
0.0%
8.777
0.000
8.777
1992
229
96
0.0%
0.0%
0.0%
9.328
0.000
9.328
1992
230
96
0.0%
0.0%
0.0%
8.147
0.000
8.147
1992
231
96
0.0%
0.0%
0.0%
8.376
0.000
8.376
1992
232
112
96.9%
3.1%
0.1%
9.331
0.735
10.066
1992
233
112
72.6%
27.2%
0.2%
8.444
1.677
10.121
1992
234
96
0.0%
0.0%
0.0%
7.494
0.000
7.494
1992
235
96
0.0%
0.0%
0.0%
7.061
0.000
7.061
1992
236
96
86.2%
13.6%
0.2%
7.178
0.373
7.551
1992
237
96
86.6%
13.1%
0.3%
7.373
0.358
7.731
1992
238
102
98.3%
1.4%
0.4%
8.553
0.998
9.551
1992
239
105
69.2%
30.8%
0.1%
9.059
2.739
11.798
1992
240
114
98.5%
1.4%
0.1%
7.706
0.000
7.706
1992
241
102
97.3%
2.6%
0.1%
8.834
1.794
10.627
1992
242
99
78.6%
21.3%
0.1%
8.727
1.969
10.695
1992
243
96
0.0%
0.0%
0.0%
7.357
0.000
7.357
1992
244
109
42.7%
57.2%
0.2%
7.920
2.410
10.329
1992
245
112
86.3%
12.6%
1.1%
7.313
0.113
7.426
1992
246
96
0.0%
0.0%
0.0%
7.400
0.000
7.400
1992
247
98
99.5%
0.2%
0.4%
7.974
0.405
8.379
1992
248
108
74.3%
25.6%
0.1%
8.291
0.743
9.034
1992
249
111
71.1%
28.8%
0.1%
8.914
0.972
9.886
Table
5
Deciviews
for
Receptors
200
km
from
a
250
MW
EGU
(
Base)

39
1992
250
96
99.0%
0.6%
0.4%
7.928
0.105
8.033
1992
251
97
92.6%
7.1%
0.3%
7.685
1.027
8.713
1992
252
102
90.8%
9.0%
0.2%
9.290
1.031
10.321
1992
253
104
66.7%
33.2%
0.1%
8.999
2.120
11.118
1992
254
110
49.3%
50.6%
0.1%
9.305
0.848
10.153
1992
255
103
32.3%
67.5%
0.1%
9.070
1.571
10.640
1992
256
114
61.2%
38.5%
0.2%
8.867
0.372
9.240
1992
257
96
0.0%
0.0%
0.0%
8.017
0.000
8.017
1992
258
99
96.4%
3.4%
0.1%
9.012
1.359
10.371
1992
259
102
79.5%
20.5%
0.1%
9.429
4.292
13.721
1992
260
104
81.1%
18.9%
0.0%
9.567
3.119
12.686
1992
261
104
90.7%
9.2%
0.1%
9.329
4.734
14.063
1992
262
108
58.1%
41.8%
0.1%
8.446
2.225
10.671
1992
263
105
61.1%
38.8%
0.1%
9.621
5.411
15.032
1992
264
111
17.5%
81.6%
0.9%
8.906
0.021
8.927
1992
265
97
96.4%
3.2%
0.4%
7.827
0.162
7.989
1992
266
101
88.6%
10.8%
0.7%
7.808
0.605
8.413
1992
267
104
94.2%
5.1%
0.7%
8.692
0.300
8.992
1992
268
114
95.5%
4.0%
0.5%
7.134
0.020
7.154
1992
269
96
0.0%
0.0%
0.0%
7.013
0.000
7.013
1992
270
96
0.0%
0.0%
0.0%
7.539
0.000
7.539
1992
271
103
92.9%
7.0%
0.1%
9.967
2.160
12.127
1992
272
108
87.6%
12.2%
0.1%
8.772
1.187
9.959
1992
273
110
80.4%
19.6%
0.0%
9.261
2.417
11.678
1992
274
96
0.0%
0.0%
0.0%
6.928
0.000
6.928
1992
275
96
0.0%
0.0%
0.0%
7.536
0.000
7.536
1992
276
96
0.0%
0.0%
0.0%
7.401
0.000
7.401
1992
277
111
88.6%
11.3%
0.1%
8.236
1.281
9.516
Table
5
Deciviews
for
Receptors
200
km
from
a
250
MW
EGU
(
Base)

40
1992
278
111
53.6%
46.3%
0.1%
8.918
4.091
13.009
1992
279
112
80.4%
19.6%
0.1%
10.272
0.696
10.968
1992
280
96
0.0%
0.0%
0.0%
6.938
0.000
6.938
1992
281
96
0.0%
0.0%
0.0%
7.187
0.000
7.187
1992
282
96
93.8%
5.9%
0.4%
7.576
1.068
8.643
1992
283
100
41.9%
58.0%
0.1%
8.707
3.931
12.639
1992
284
98
73.5%
26.2%
0.3%
8.585
0.590
9.175
1992
285
110
41.0%
58.8%
0.1%
8.231
1.673
9.904
1992
286
104
40.7%
58.8%
0.5%
8.254
0.341
8.596
1992
287
112
83.1%
16.2%
0.8%
7.702
0.086
7.787
1992
288
114
79.6%
19.6%
0.8%
7.531
0.271
7.802
1992
289
109
44.0%
55.7%
0.3%
7.526
2.030
9.556
1992
290
108
41.3%
58.4%
0.3%
8.201
1.239
9.440
1992
291
105
56.0%
43.4%
0.6%
8.073
0.774
8.847
1992
292
114
91.9%
4.8%
3.3%
6.850
0.012
6.862
1992
293
114
75.0%
24.2%
0.8%
7.103
0.069
7.172
1992
294
114
79.8%
19.5%
0.7%
6.871
0.039
6.910
1992
295
102
54.7%
44.0%
1.3%
7.710
0.324
8.034
1992
296
109
67.4%
30.8%
1.8%
7.094
0.067
7.160
1992
297
96
0.0%
0.0%
0.0%
7.833
0.000
7.833
1992
298
112
77.7%
22.2%
0.1%
8.585
0.999
9.584
1992
299
112
78.9%
21.0%
0.2%
7.928
1.561
9.489
1992
300
96
0.0%
0.0%
0.0%
7.036
0.000
7.036
1992
301
114
84.3%
14.0%
1.7%
7.405
0.136
7.541
1992
302
114
50.5%
48.9%
0.7%
7.127
0.094
7.221
1992
303
106
74.5%
25.4%
0.1%
7.761
3.521
11.282
1992
304
112
69.0%
30.9%
0.1%
10.486
6.220
16.706
1992
305
114
58.9%
41.1%
0.0%
11.784
4.357
16.141
Table
5
Deciviews
for
Receptors
200
km
from
a
250
MW
EGU
(
Base)

41
1992
306
114
76.3%
22.2%
1.4%
10.469
0.004
10.473
1992
307
96
0.0%
0.0%
0.0%
8.370
0.000
8.370
1992
308
96
31.7%
65.2%
3.1%
8.617
0.013
8.630
1992
309
109
53.9%
45.8%
0.3%
7.803
0.706
8.509
1992
310
107
63.7%
36.0%
0.3%
7.122
0.274
7.396
1992
311
114
58.1%
41.6%
0.3%
10.321
0.104
10.424
1992
312
96
0.0%
0.0%
0.0%
7.399
0.000
7.399
1992
313
96
0.0%
0.0%
0.0%
7.815
0.000
7.815
1992
314
96
0.0%
0.0%
0.0%
7.790
0.000
7.790
1992
315
96
88.8%
10.7%
0.5%
7.098
0.382
7.480
1992
316
99
48.6%
51.0%
0.4%
7.051
0.965
8.016
1992
317
105
59.4%
40.1%
0.4%
9.319
1.299
10.618
1992
318
100
26.7%
73.1%
0.1%
8.790
1.784
10.574
1992
319
114
68.7%
28.6%
2.7%
6.824
0.083
6.907
1992
320
114
73.0%
26.3%
0.7%
6.833
0.363
7.197
1992
321
114
43.7%
55.9%
0.4%
6.937
0.400
7.337
1992
322
106
58.3%
41.4%
0.4%
7.339
0.380
7.719
1992
323
108
56.2%
42.4%
1.4%
6.933
0.248
7.182
1992
324
109
39.9%
59.7%
0.4%
8.035
0.331
8.367
1992
325
114
62.0%
38.0%
0.1%
9.713
0.278
9.991
1992
326
99
52.0%
47.9%
0.1%
8.507
0.022
8.529
1992
327
98
78.1%
21.8%
0.1%
9.944
1.093
11.037
1992
328
99
43.7%
56.2%
0.1%
10.076
4.297
14.373
1992
329
110
77.4%
22.0%
0.6%
7.158
0.146
7.304
1992
330
97
48.7%
51.1%
0.2%
8.346
0.078
8.424
1992
331
100
56.4%
43.5%
0.1%
9.316
4.028
13.344
1992
332
100
32.4%
67.5%
0.1%
8.012
1.374
9.386
1992
333
114
70.3%
29.1%
0.7%
7.558
0.126
7.685
Table
5
Deciviews
for
Receptors
200
km
from
a
250
MW
EGU
(
Base)

42
1992
334
96
0.0%
0.0%
0.0%
8.663
0.000
8.663
1992
335
114
59.7%
39.6%
0.8%
7.127
0.094
7.221
1992
336
114
43.6%
55.9%
0.6%
7.491
0.619
8.110
1992
337
111
47.5%
52.3%
0.2%
8.294
1.281
9.575
1992
338
103
35.4%
64.3%
0.3%
8.253
1.972
10.225
1992
339
114
50.4%
48.9%
0.7%
6.785
0.003
6.788
1992
340
105
43.4%
56.2%
0.4%
7.536
0.965
8.501
1992
341
111
30.9%
67.6%
1.5%
7.333
0.030
7.363
1992
342
107
48.0%
51.5%
0.5%
7.309
0.472
7.782
1992
343
110
31.3%
68.3%
0.4%
7.544
0.161
7.704
1992
344
96
0.0%
0.0%
0.0%
6.914
0.000
6.914
1992
345
96
43.4%
55.8%
0.9%
6.889
0.000
6.889
1992
346
96
0.0%
0.0%
0.0%
10.422
0.000
10.422
1992
347
96
0.0%
0.0%
0.0%
9.383
0.000
9.383
1992
348
96
0.0%
0.0%
0.0%
8.060
0.000
8.060
1992
349
96
0.0%
0.0%
0.0%
7.247
0.000
7.247
1992
350
96
58.0%
41.8%
0.2%
7.791
0.004
7.796
1992
351
97
45.9%
53.9%
0.3%
7.538
3.009
10.548
1992
352
105
67.5%
32.5%
0.0%
10.278
5.880
16.158
1992
353
112
72.7%
27.2%
0.0%
10.948
1.161
12.109
1992
354
96
47.0%
52.7%
0.3%
7.427
0.042
7.468
1992
355
103
50.6%
48.0%
1.4%
7.021
0.474
7.495
1992
356
114
58.4%
41.5%
0.1%
10.023
1.475
11.498
1992
357
102
56.5%
42.6%
1.0%
7.606
0.428
8.034
1992
358
112
64.1%
35.9%
0.1%
8.618
1.862
10.480
1992
359
113
86.4%
13.5%
0.1%
10.548
1.154
11.702
1992
360
114
71.9%
25.8%
2.3%
6.862
0.000
6.862
1992
361
106
42.2%
57.3%
0.5%
7.202
0.433
7.635
Table
5
Deciviews
for
Receptors
200
km
from
a
250
MW
EGU
(
Base)

43
1992
362
114
54.6%
42.4%
3.0%
6.720
0.017
6.737
1992
363
96
51.3%
48.0%
0.7%
6.969
0.235
7.203
1992
364
99
59.0%
40.7%
0.4%
7.799
0.582
8.381
1992
365
96
73.8%
26.2%
0.1%
8.827
2.792
11.620
44
TABLE
6
Maximim
DDV
for
Receptor
Distances
for
Each
Year
250
MW
and
750
MW
EGUs
250
MW
Dist
(
km)
1991
1992
1993
1994
1995
100
8.767
11.857
10.038
9.525
9.179
120
7.989
10.063
9.146
8.195
8.198
140
7.330
8.713
8.422
7.750
6.703
160
6.952
7.590
6.964
6.808
6.060
180
6.870
6.696
6.296
5.980
7.411
200
7.351
6.220
7.398
5.581
7.029
750
MW
Dist
(
km)
1991
1992
1993
1994
1995
100
14.124
19.120
18.055
15.894
15.479
120
13.698
17.734
15.844
15.341
15.010
140
13.399
16.087
14.827
14.909
12.515
160
14.061
14.537
13.273
13.568
12.584
180
13.954
13.484
12.589
12.282
14.702
200
14.563
12.813
14.266
11.564
14.107
45
TABLE
7
Maximim
DDV
for
Receptor
Distances
for
All
Years
250
MW
and
750
MW
EGUs
MW
Dist
(
km)
DDV
Year
Day
Recp.

250
100
11.857
1992
261
10
250
120
10.063
1992
304
35
250
140
8.713
1992
263
48
250
160
7.590
1992
263
67
250
180
7.411
1995
284
85
250
200
7.398
1993
13
98
750
100
19.120
1992
261
10
750
120
17.734
1992
304
35
750
140
16.087
1992
304
54
750
160
14.537
1992
304
73
750
180
14.702
1995
284
85
750
200
14.563
1991
38
96
46
TABLE
8
Comparison
of
Base
and
Control
Scenarios
on
DDV
for
5
Years
for
250
MW
and
750
MW
EGUs
250
MW
EGU
90%
Control
95%
Control
Year
Day
Recp.
Base
DDV
Difference
DDV
Difference
1992
261
10
11.857
2.828
9.029
2.208
9.649
1992
304
35
10.063
2.607
7.456
2.318
7.745
1992
263
48
8.713
1.981
6.732
1.652
7.061
1992
263
67
7.590
1.610
5.980
1.320
6.270
1995
284
85
7.411
1.317
6.094
0.963
6.448
1993
13
98
7.398
1.342
6.056
0.978
6.420
750
MW
EGU
90%
Control
95%
Control
Year
Day
Recp.
Base
DDV
Difference
DDV
Difference
1992
261
10
19.120
6.802
12.318
5.537
13.583
1992
304
35
17.734
6.368
11.366
5.768
11.966
1992
304
54
16.087
5.258
10.829
4.722
11.365
1992
304
73
14.537
4.389
10.148
3.882
10.655
1995
284
85
14.702
3.618
11.084
2.753
11.949
1991
38
96
14.563
3.616
10.947
2.770
11.793
47
TABLE
9
Comparison
of
CALPUFF
and
CALPUFF
Screen
Analysis
CALPUFF
Analysis
CALPUFF
Screening
Model
used
CALPUFF
CALPUFF
Input
meteorology
Process
5
years
of
location­
specific,
meteorology
data
Representative
met
location
(
data
already
processed)
Terrain
included
Site­
specific
terrain
included
None
(
assumed
flat)
Source­
Receptor
distances
Source
to
Class
I
area
receptor
Source
to
Class
I
area
receptor
Location
of
Visibility
impact
Maximum
impact
at
specific
receptors
at
appropriate
distance/
direction
from
source
Maximum
impact
in
any
direction
at
a
particular
sourcereceptor
distance
Purpose(
s)
of
results
Demonstrate
a
specific
source's
contribution
to
visibility
impairment
in
Class
I
area(
s).
Demonstrate
a
specific
source's
contribution
to
visibility
impairment
in
Class
I
area(
s).

 
and
Develop
a
look­
up
table
to
determine
SO2
emission
rates
for
given
sourcereceptor
distances
48
Table
10
Results
from
the
Athens,
GA
Screening
Analysis
SO2
Emissions
50
km
100
km
150
km
200
km
250
km
300
km
1989
500
0.144
0.151
0.137
0.114
0.100
0.091
1990
500
0.109
0.111
0.091
0.101
0.104
0.096
1986
500
0.140
0.101
0.098
0.096
0.090
0.086
1988
500
0.090
0.081
0.080
0.075
0.066
0.057
1987
500
0.119
0.081
0.087
0.070
0.069
0.085
1989
1000
0.285
0.301
0.274
0.227
0.201
0.182
1990
1000
0.212
0.221
0.181
0.201
0.206
0.193
1986
1000
0.279
0.201
0.196
0.192
0.180
0.172
1988
1000
0.179
0.163
0.160
0.150
0.133
0.115
1987
1000
0.237
0.162
0.175
0.140
0.139
0.169
1989
2000
0.557
0.596
0.545
0.452
0.400
0.364
1990
2000
0.411
0.438
0.360
0.397
0.410
0.383
1986
2000
0.553
0.398
0.389
0.382
0.359
0.343
1988
2000
0.354
0.322
0.318
0.298
0.264
0.229
1987
2000
0.468
0.324
0.348
0.279
0.278
0.338
1989
5000
1.306
1.431
1.324
1.105
0.979
0.896
1990
5000
0.967
1.054
0.880
0.967
0.996
0.936
1986
5000
1.335
0.957
0.948
0.932
0.880
0.841
1988
5000
0.863
0.780
0.777
0.731
0.650
0.564
1987
5000
1.133
0.795
0.855
0.684
0.686
0.831
1989
10000
2.058
2.324
2.176
1.842
1.634
1.520
1986
10000
2.273
1.611
1.623
1.609
1.526
1.455
1990
10000
1.606
1.757
1.433
1.590
1.647
1.555
1988
10000
1.650
1.371
1.399
1.334
1.192
1.045
1987
10000
2.146
1.274
1.475
1.201
1.205
1.397
1989
15000
3.262
3.709
3.553
3.042
2.706
2.501
1990
15000
2.236
2.744
2.451
2.674
2.744
2.594
1986
15000
3.570
2.550
2.586
2.568
2.444
2.347
1988
15000
2.393
2.102
2.155
2.050
1.840
1.614
1987
15000
3.073
2.202
2.398
1.928
1.942
2.331
1989
20000
3.952
4.578
4.484
3.885
3.465
3.214
1990
20000
2.874
3.273
3.154
3.431
3.519
3.332
1986
20000
4.514
3.221
3.296
3.287
3.138
3.020
1988
20000
3.077
2.664
2.765
2.645
2.385
2.101
1987
20000
3.918
2.830
3.091
2.494
2.508
3.003
49
Table
11
Results
from
the
Oklahoma
City
Screening
Analysis
SO2
Emissions
50
km
100
km
150
km
200
km
250
km
300
km
1986
500
0.126
0.115
0.116
0.113
0.108
0.076
1989
500
0.117
0.112
0.098
0.104
0.092
0.074
1990
500
0.086
0.103
0.101
0.090
0.082
0.077
1987
500
0.111
0.088
0.082
0.079
0.081
0.081
1988
500
0.078
0.091
0.073
0.062
0.057
0.046
1986
1000
0.247
0.229
0.231
0.225
0.216
0.152
1989
1000
0.234
0.224
0.015
0.208
0.183
0.147
1990
1000
0.167
0.205
0.202
0.180
0.164
0.155
1987
1000
0.220
0.175
0.165
0.157
0.163
0.163
1988
1000
0.159
0.181
0.146
0.124
0.115
0.093
1986
2000
0.482
0.450
0.458
0.448
0.431
0.304
1989
2000
0.462
0.446
0.387
0.414
0.364
0.293
1990
2000
0.323
0.406
0.402
0.359
0.328
0.309
1987
2000
0.434
0.347
0.327
0.315
0.325
0.324
1988
2000
0.320
0.359
0.292
0.247
0.231
0.185
1986
5000
1.147
1.077
1.104
1.090
1.053
0.750
1989
5000
1.116
1.089
0.950
1.010
0.982
0.718
1990
5000
0.764
0.972
0.979
0.881
0.801
0.759
1987
5000
1.043
0.841
0.798
0.774
0.801
0.799
1988
5000
0.795
0.873
0.717
0.609
0.572
0.459
1986
10000
1.943
1.797
1.746
1.742
1.703
1.234
1989
10000
2.115
1.866
1.602
1.740
1.561
1.343
1990
10000
1.245
1.564
1.601
1.460
1.310
1.265
1987
10000
1.933
1.432
1.383
1.289
1.340
1.338
1988
10000
1.251
1.538
1.255
1.019
0.881
0.808
1986
15000
2.601
2.637
2.907
2.937
2.881
2.115
1989
15000
3.029
2.978
2.638
2.770
2.483
2.016
1990
15000
1.864
2.558
2.651
2.442
2.195
2.102
1987
15000
2.804
2.254
2.173
2.139
2.238
2.245
1988
15000
2.227
2.395
1.978
1.726
1.635
1.329
1986
20000
3.243
3.147
3.639
3.715
3.667
2.727
1989
20000
3.862
3.773
3.387
3.535
3.190
2.605
1990
20000
2.103
3.084
3.348
3.122
2.827
2.681
1987
20000
3.571
2.836
2.755
2.725
2.870
2.889
1988
20000
2.948
3.060
2.528
2.227
2.126
1.739
50
Table
12
Results
from
the
Huntington,
WV
Screening
Analysis
SO2
Emissions
50
km
100
km
150
km
200
km
250
km
300
km
1989
500
0.147
0.121
0.158
0.177
0.146
0.089
1987
500
0.159
0.158
0.147
0.151
0.134
0.095
1986
500
0.175
0.140
0.151
0.145
0.123
0.097
1990
500
0.159
0.121
0.110
0.103
0.093
0.077
1988
500
0.138
0.127
0.109
0.087
0.064
0.058
1989
1000
0.293
0.241
0.315
0.352
0.292
0.178
1987
1000
0.316
0.315
0.293
0.302
0.266
0.190
1986
1000
0.347
0.280
0.301
0.290
0.245
0.193
1990
1000
0.316
0.243
0.219
0.206
0.186
0.153
1988
1000
0.275
0.253
0.218
0.174
0.128
0.115
1989
2000
0.578
0.477
0.624
0.697
0.579
0.355
1987
2000
0.622
0.624
0.580
0.597
0.527
0.377
1986
2000
0.683
0.554
0.597
0.575
0.486
0.384
1990
2000
0.623
0.484
0.435
0.411
0.370
0.303
1988
2000
0.545
0.501
0.432
0.345
0.256
0.230
1989
5000
1.386
1.155
1.503
1.673
1.403
0.874
1987
5000
1.490
1.501
1.401
1.440
1.277
0.922
1986
5000
1.617
1.339
1.443
1.390
1.179
0.938
1990
5000
1.492
1.183
1.058
1.009
0.907
0.742
1988
5000
1.318
1.216
1.049
0.843
0.634
0.566
1989
10000
2.497
2.068
2.392
2.671
2.280
1.472
1987
10000
2.685
2.458
2.363
2.445
2.191
1.608
1986
10000
2.701
2.283
2.354
2.296
2.011
1.610
1990
10000
2.650
2.077
1.888
1.703
1.646
1.419
1988
10000
2.380
2.157
1.946
1.582
1.161
1.068
1989
15000
3.683
3.112
4.007
4.413
3.781
2.461
1987
15000
3.931
3.952
3.752
3.850
3.457
2.567
1986
15000
4.080
3.569
3.860
3.741
3.220
2.607
1990
15000
3.932
3.217
2.903
2.812
2.532
2.083
1988
15000
3.548
3.297
2.878
2.352
1.815
1.616
1989
20000
4.655
3.952
5.066
5.557
4.800
3.179
1987
20000
4.958
4.961
4.747
4.872
4.398
3.303
1986
20000
5.145
4.503
4.881
4.745
4.109
3.357
1990
20000
4.953
4.090
3.713
3.614
3.262
2.693
1988
20000
4.503
4.196
3.684
3.030
2.361
2.104
51
Table
13
Results
from
the
Phoenix
Screening
Analysis
SO2
Emissions
50
km
100
km
150
km
200
km
250
km
300
km
1990
500
0.084
0.059
0.052
0.053
0.049
0.035
1989
500
0.066
0.066
0.058
0.039
0.025
0.017
1986
500
0.051
0.039
0.037
0.037
0.034
0.024
1987
500
0.058
0.049
0.048
0.037
0.030
0.029
1988
500
0.053
0.039
0.034
0.029
0.032
0.017
1990
1000
0.169
0.119
0.103
0.106
0.097
0.070
1989
1000
0.131
0.131
0.116
0.079
0.050
0.034
1986
1000
0.102
0.078
0.074
0.075
0.068
0.048
1987
1000
0.115
0.098
0.097
0.073
0.061
0.057
1988
1000
0.106
0.078
0.068
0.058
0.065
0.034
1990
2000
0.335
0.236
0.205
0.212
0.194
0.139
1989
2000
0.256
0.260
0.232
0.158
0.100
0.069
1986
2000
0.203
0.156
0.149
0.149
0.136
0.096
1987
2000
0.226
0.195
0.192
0.146
0.121
0.114
1988
2000
0.212
0.155
0.136
0.115
0.129
0.068
1990
5000
0.809
0.579
0.506
0.521
0.477
0.344
1989
5000
0.595
0.639
0.572
0.392
0.249
0.171
1986
5000
0.500
0.386
0.370
0.371
0.337
0.240
1987
5000
0.543
0.481
0.475
0.360
0.299
0.283
1988
5000
0.522
0.383
0.337
0.287
0.321
0.169
1990
10000
1.303
1.126
0.986
1.015
0.932
0.676
1987
10000
0.911
0.931
0.863
0.708
0.589
0.555
1989
10000
1.051
1.091
0.971
0.675
0.455
0.340
1986
10000
0.971
0.716
0.654
0.656
0.595
0.463
1988
10000
0.966
0.751
0.324
0.519
0.521
0.296
1990
15000
2.162
1.646
1.446
1.488
1.369
0.998
1989
15000
0.160
1.795
1.634
1.143
0.731
0.505
1986
15000
1.431
1.115
1.072
1.078
0.986
0.708
1987
15000
1.474
1.366
1.358
1.044
0.872
0.826
1988
15000
1.490
1.108
0.969
0.835
0.935
0.502
1990
20000
2.735
2.140
1.885
1.938
1.786
1.309
1989
20000
2.018
2.320
2.126
1.499
0.963
0.668
1986
20000
1.865
1.460
1.405
1.413
1.297
0.934
1987
20000
1.876
1.783
1.770
1.369
1.146
1.087
1988
20000
1.938
1.451
1.268
1.097
1.229
0.664
52
TABLE
14
Example
of
a
Look­
Up
Table
Distance
East
West
50
2606
3330
60
2631
3497
80
2683
3831
100
2734
4166
120
2785
4500
140
2837
4835
160
2888
5169
180
2939
5503
200
2991
5838
220
3042
6172
240
3093
6507
260
3145
6841
280
3196
7175
300
3248
7510
320
3299
7844
340
3350
8179
360
3402
8513
380
3453
8848
400
3504
9182
420
3556
9516
440
3607
9851
460
3658
10185
480
3710
10520
500
3761
10854