Document ID: EPA-HQ-OAR-2003-0072-0047
Agency: epa
Document Type: Supporting & Related Material
Title: 
Posted Date: 2002-09-20T04:00Z

EASTERN
RESEARCH
GROUP.
INC
It
Stevenson.
EPNCombustion
Group
Jason
Huckaby.
Eastern
Research
Croup,
Inc
FROM:

DATE:
September
4,2002
SUBJECT:
\

/

Lee
County
W
C
/
Emissions
Variability
Analysis
1.0
INTRODUCTION
This
memorandum
presents
an
analysis
qf
the
variability
in
emission
that
occurs
at
a
well
operated
municipal
waste
combustor
(
MWC).
The
analysis
reviews
the
performance
of
the
Lee
County
(
FL)
MWC.
The
Lee
County
facility
is
equipped
with
the
full
battery
of
high
efficiency
and
has
operated
unmodified
since
start
up
in
1994.
Additionally
the
ards
for
high
standards
of
operation
and
performance.

MWC
includes
data
for
the
following
pollutants
mium
(
Cd),
lead
(
Pb),
mercury
(
Hg).
hydrogen
ch
oxides
(
NO,).
The
foIlowing
se
performance,
parame
annual
test
results.

2.0
FACILITY
DESCRIPTION
The
Lee
County
M
W
C
is
Iocated
in
Fort
Myers,
FL.
The
facility
has
capacity
to
combust
1,200
tons
per
day
(
tpd)
of
municipal
solid
waste
(
MSW)
in
two
600
tpd
municipal
waste
combustor
(
MWC)
units.
The
combustors
are
mass­
burn
designs
using
reverse­
reciprocating
C;
iSmaiMWCVer
County\
LeeVanabllLyrnemoi
1
793
stoker
grates.
Process
control
is
achieved
through
the
use
of
a
distributive
control
system
(
Le.,

sensors
transmit
operating
data
to
compu
make
adjustments).
The
au
pollution
control
systems
include
s
carbon
injection
(
CI),
and
selective
non­
catalytic
re
scrubbing
syste
is
used
for
NOx
nitrogen
oxide,
produdtion,
power
additional
Hg
and
dioxidfuran
ion,
continuous
emission
monitoring
syste
vated
carbon
usage,
combustion
ctrical
energy
is
produced
by
a
39.7
Mw
electric
generator
driven
by
a
condensing
steam
turbine.
Fresh
water
usage
is
minimized
through
the
use
of
secondary
treate
steam.
Fly
ash
an
ttom
ash
are
passed
t
scalper,
magnetic
separator,
and
non­
ferrous
recovery
system
IO
recover
metals
from
the
as
3.0
PLANT
OPERATIONS
began
in
1994,
the
MWC
units'
co
operators
and
maintenance
personne
monthly
written
quizzes
on
plant
operatio
and
maintenance
personnei
attend
se
operation,
the
Lee
County
facility
has
recently
been
aw
Attachment
A).
4.0
PLANT
ENVIRONMENTAL
PERFORMANCE
Since
it
began
operations,
the
Lee
County
facility
has
been
in
full
compliance
with
all
federal,
state,
and
local
regulations.
The
facility
has
not
required
any
modification
to
­
demonstrated
compliance
with
permitted
levels
for
PM,
op
Ifuric
acid
mist,
fluorides,
NO,,
carbon
monoxid
nia,
and
dioxidfimns.
As
a
result
of
their
outs
e
Lee
County
facility
was
awarded
the
Environmental
Citizen
istrict
office
of
Florida's
DEP.
The,
ASME
award
no
(
Attachment
AI
contains
detailed
information
on
environmental
performance
for
both
air
I
5.0
PARAMETRIC
DATA
I
Operating
parameter
data
were
obtained
from
the
Lee
County
facility
for
the
years
a1
compliance
test
data
(
1994­
2001
>.
This
data
includes
information
nd
the
operating
variables
associated
with
the
air
pollution
control
tains
the
parametric
data.

6.0
EMISSfO
BILITY
ANALYSIS
as
analyzed
to
determine
the
amount
of
emissions
variabili
aintained
IWC.
Statistical
tests
were
performe
th
units
couid
be
combined
for
analysis
and
what
type
of
distribution
(
is.,

t
closely
fit
the
data
for
each
polhtant.
Addition
was
necessary.
The
analysis
investi
compliance
jtevel.
The
les
I
and
2.
Additionally,
Figures
ugh
8
present
data
plots
of
the
test
1
.
The
complete
data
Table­
1.
Summary
Statistics
for
Stack
ear
1994
through
Particulate
Matter
(
rng'dscm)

ail
values
corrected
to
3%
02.
'
arithmetic
average.

Particulate
Matter
variability
of
data
arithmetic
avera
4
4
CSmallMWCUee
County\
lneVanablttymemofutdwpd
Figure
1.
Lee
County
Dioxin/
furan
(
total
mass
basis)

I996
1997
1998
1999
2000
2001
1994
1995
Year
5
Figure
2.
Lee
County
Mercury
0.05
A
E
+
0.04
m
E
Y
$
2
0.03
0.02
0.01
0
1994
1995
1996
1997
1998
Year
1999
2000
2001
0.0014
0.001
.
cI
f3
­
s
t
.
I
o*
0008
E
0.0006
0
P
0.0004
Figure
3.
Lee
County
Cadmium
­
­
­
­

0.0013
0.0013
0.0013
0.0002
0
1997
1998
1999
2000
2001
1994
1995
1996
Year
7
'
s
h
11
4.
Lee
County
Lead
­
­
~
­
­
­
­
­
­
_
­
­
~
_
0.02
i
i
0.01
9
0.01
8
0.01
6
0.01
4
,
g
0.0t2
u
u)

5
0.01
1
x
2
0.008
0.006
0.004
0.002
0
1994
1995
1996
1997
f
998
8
Year
1999
2000
2001
t
P
E
I
Figure
5.
Lee
County
Particulate
Matter
9.2
9
8
7
6
5
4
3
2
1
0
1996
1997
1998
1999
2000
2001
1994
1995
Year
CISmaMWCUae
CountyUteVanabiltymemofma1
wpd
9
18
16
34
12
A
>

e
10
8
H
6
4
2
0
1994
1995
1996
1997
1998
1999
2000
2001
Year
45
40
35
25
e
n
Y
15
70
1994
I995
7
996
1997
1993
1999
Year
2000
2001
I
1
165
160
S:
155
E
n
P
­

150
145
140
135
1994
1995
1996
1997
t
998
Year
1999
2000
2001
C.
tSmallMWCU.
ee
Cuunty\
LrrVnriabilt~~
otinal
wpd
12
r
f
d
B
Attachment
A
Waste
to
Energy
Facility
Recognition
Award
by
ASME
i
I
~

­
3
1
:>
t,.
5
INTEROFFICE
MEMO
U
M
FROM
SOLID
WASTE
DMSION
Phone:
(
941)
479­
8181
Fax:
(
941)
479­
8119
e
county
SOUTRWEST
FLORIDA
Date:
April
30,2001
TO:
Jim
Lavender,
Director
From:
Lindsey
J.
Sampson,
P.
E.

s
ste
To
Energy
Facility
Recognition
Award
by
ASME
can
Society
of
Mechanical
that
an
award
will
be
pres
Solid
Waste
Processing
County
and
Covmta
L
the
facility's
contributions
to
the
field
of
solid
waste
proc
n
ual
North
American
hc.,
at
no
cost
to
the
County.
ation
that
was
included
in
the
Cc:
BOCC
Districts
1­
5
D.
Stilwell
T.
Eriksen
4
American
Society
cal
Engineers
Solid
Waste
cility
Re
plication
ee
Solid
Waste
Resour
Facility
Facility
Recognition
Award
Nomination
Form
1.
Award
Category
Combustion
ame
Recovery
Facility
(
the
'%'
acility
'
3
10500
Ft.
My
4.
Owner
Lee
Cotinty
Solid
Waste
Division
(
the
''
County'
3
Address:
1500
Monroe
Sireet
Contact:
Telephone:
341­
479­
8
I81
Fax:
94
1­
479­
81
I9
5
.
0
r
Martin
Systems
of
Lee.
hc.
("
OMSL")

Contact:
Tom
Eriksen
Telephone:
Fa:
941­
337­
2510
1
1
?
4
6.
Throughput
Capacity
(
tons
per
day)

1,200
tons
per
day
7.
Facility
Description
Provide
a
general
description
of
the
Facility,
including
each
major
piece
of
equipment
Include
attachment
as
needed.

Dirtral
water
wall
Opaciiy,
Sulfiir
Dioxide,
total
st
used
to
condense
the
turbine
exhaust
steam.
l3k
8.
Summary
of
Facility
Operations
Provide
a
general
summary
of
Facility
opera
through
the
Facility,
materials
andor
energy
needed.

"
Firxt
fire"
at
this
Facility
to
Department
of
Environmental
first
followed
by
the
Turbine
Generator
on
September
2
Acceptance
testing
was
conducted
from
October
I7­
Construction
Agreement
beiween
Ogden
and
Lee
Cotrn
Stan­
up
of
the
Facility
>
vas
virtuallyfla
passing
of
acceptance
testing
I
,
1994.
The
project
was
completed
Since
going
commercial
the
FaciIiq
h
availability
of
99.6
percent.
A
prodiiced;
1,077.000
Ktyh
ofpower
generated;
tons
of
ferrous;
and
835
tons
of
Ron­
ferroous
me
environmental
permits
and
regulations­
tial
operating,
hour
ere4
staffing,
a
d
other
key
operationa1
hon,
flow
of
materials
Include
attachment
as
County,
Ogden
and
the
Florida
roblems
noted
With
the
on
effective
December
ASME
SWPD
Fa
d
Nomination
Form
9.
Key
Contributions
to
the
Field
of
Solid
Waste
Processing
The
ASME
Solid
Waste
Processing
Division
Facility
Recognition
Award
is
based
on
information
provided
in
this
section
regarding
the
Faciliq's
contributions
to
the
field
of
solid
waste
procesmg.
The
key
selection
criteria
and
weightin
are
as
follows:

I,
Success
in
Reaching
Facility
Operation
Requirements
(
20
percent)
the
established
operating
requirements
for
the
Facility,
and
the
history
of
the
Facility
with
respect
eeting
those
operating
requirements.

me,
at
a
minimum,
is
meamred
by
the
abiliiy
ofthe
Facility
to
operate
and
be
maintained
in
s
z
h
a
manner
te.
generate
steam,
and
convert
the
steam
into
electric
power
for
export,
at
a
level
consistent
nce
Guarantees
contained
in
the
Service
Agreement
between
the
County
and
The
ting
,
I
ce
Guarantees
contained
in
Schedule
2
of
the
Service
Agreement
are
used
as
the
basis
for
nce.
These
Pejormance
Guarantees
include:

erage
Energy
Guarantee
Utility
Utilization
Guarantee
hropane
gas)

~

nee
Guarantees*
petj4onnanceparameters
measured
during
the
Facility's
acceptance
test
Facility
perjomance.
These
perjormance
parameters
include:

ate&
1.8
million
tom
of
waste
in
fistfive
years
of
operation,
which
is
96.8
vailability
of
1,200
tons
per
day).
During
the
first
three
years
of
compliance
of
waste.
Waste
processed
by
the
Facility
has
increased
evey
year,
e
County's
waste
generation.
In
the
fifth
billing
year,
th
e
during
the
five­
yearperiod.
This
is
26.5
percent
by
Mwh
of
electricity
for
sale.
The
Facility
P
net
elecrric
essed,
as
more
m
t
e
has
became
availablefiom
the
1
year
averaged
601
kWh
per
ton
of
wcrste
processed,
able
the
Facility
to
recover
energy
at
th&
rate,
high
e$
ciency
boilers,
wz
pressure
and
temperature,
were
installed
to
increase
the
turbine
efficiency.

generated
per
ton
of
waste
processed
has
generally
increased
over
the
seven
years
of
operation.

­
generator
over
the
first
seven
years
was
99.6percent.

3
ASME
SWPD
Facility
Recognitio
II.
Innovative
Contributions
to
Solid
Waste
P
Describe
the
Facility's
contributions
to
equipment,
or
operations;
approaches
applications
of
equipment
or
materials.
your
goals.

The
Lee
County
project
has
several
innovative
recovery
systm,
its
ecologically
sound
reuse
elements.

In
the
early
stages
ofnegotiations
L
standards.
The
Facility
was
therefore
sulpassed
rhese
standards
since
start­
all
clean
air
retrofits
throughout
th
This
Facility
was
designed
to
pro
in
the
United
States
with
a
perm
wet
design.
one
where
acriv
into
a
mix
tankfiom
where
the
carbonfwater
s
to
comply
with
n
I50
ug/&
cm
standard.
This
consistently
rneefi­

A
post
combustion
fenous
followed
by
a
screened
tro
that
would
have
been
destined
for
the
landfill
an
in­
line
non­
ferrous
The
Faciliw
also
provides
a
long­
range
bene4t
20
area­
wide
water
resource
management.
supplied
by
the
Ciiy
of
would
have
been
discharged
into
suface
waters,
now
serves
"
reciaaim"
water
IS
us
ue
air
pollution
control
system.
its
metals
ent
since
start­
up
and
d.
Partially
due
to
the
\
i
1
0
gallons
per
day
of
the
atmosphere
in
the
~

1
i
Additionally,
the
water
transmission
lines
coILThsl~

conservation
efforts
in
the
area.

Many
exotic.
non­
native
ecies
have
been
in
Fuctlity
war
irrf2sted
with
the
problematic
exotic
were
eradicated
and
the
weltand
rstored.
A
n
clogged
with
non­
native
aquatic
wee&.
methods
to
remove
rhese
wee&
the
Fa
These
fish
have
since
condition.

4
1
E
d
MREE
SWPD
Facility
Recognition
Award
Nomination
Form
ore
important
to
the
Facdity
than
health
andsafety.
AI1
Facility
personnel
are
repued
to
attend
monthly
safe9
specific
OSHA
required
sdety
training
themes
me
presented
by
the
Facility
'
s
S
a
f
e
Coordinator.
onnel
also
attend
weekly
safety
meetings
where
plant
safity
procedures
are
discussed
e
in`
the
employee
medical
surveiilance
program
which
includes
annual
physicals.
indushial
hygiene
ring
outage
and
non­
outage
periods
to
determine
ifl
where,
when
and
what
type
of
respiratory
may
be
required­
Monthly
plant
walkdowns
are
conducted
by
the
Faciiitys
safety
committee.
d
and
quickly
resolved
\

mpiled
an
excellent
safety
record.
The
plant's
OSHA
Frequency
Index
not
surtained
any
lost
time
injuries.
in
1998.
I999
and
2000.
the
Facil
d
a
this
outstanding
performance
and
has
operated
the
Facility
for
the
last
3
years
with
excellent
relationship
with
the
local
environmental
agencies.
llzk
ilt
on
trust
and
the
howledge
that
the
Facility
has
and
will
continue
to
compi)
with
all
pennit
e
local
DEP
stag
to
attend
all
vendor
training
sessions
along
over
a
three­
month
period
and
DEPpersonnel
attended
every
one.
By
el
were
able
to
understand
the
operation
of
not
just
the
pollution
control
equip
became
acquainted
with
the
FaciliQ
stuff
and
realized
the
level
of
education,

lied
by
vendors
prior
to
start­
up,
in
fact
it
hadjust
begun.
AN
operators
are
required
to
rn
on
power
plantfitndumentals
as
well
as
Facility
speczjk
Step
Training
program
prior
continual
on
the
job
training
and
are
given
written
quizzes
each
month
on
plant
systems.
a
lunch
of
their
choice
as
recognition
and
a
competitive
incentive.

a1
management
training.
Maintenance
and
administrative
personnel
cafiold
erection,
pump
repair,
bearing
maintenance,
FaciIiq
c
i.
e.
chlorine
handling,
water
treatmznt
and
heavy
irtance.
Several
employees
are
pres
ining
relative
to
their
support
of
the
Facility­
This
training
includes
ace
entry,
quarterly
fire
drills,
elevator
rescue.
and
chemical
handling.

all
operation
and
maintenance
personnel
receive
wee
erating
Manual.
These
Amendmew
also
required
th
Extensive
training
in
Facility
operations
an
ts.
Presently
the
Facility
Ma
as
Chief
Facility
Operator
Certification,
the
ng
in
vaste
ifi
Supervirors
have
the
four
Control
Room
I
Waste
Combustor
training
course.

5
`
I
1
4
~

ET.
Technical
Contn'butions
to
Solid
Waste
The
following
nunmarizes
the
Facility`
s
Technical
"
gent
regulations
created
by
the
iremen&
the
Faciliq
proved
that
Clean
Air
Act
Amendment
Acts
of
I990.

iVon­
Ferrous
Recovery
overy
sysrem.
The
contractor
date.
The
system
was
installed
aiko
increasing
the
Inconel
Application
for
Corrosion
Control
The
Faciliy
has
obse
ally
related
to
the
pam
idenhBed.
The
entire
furnuce
area
"
R"
Stamp
recognized
the
need
to
have
an
proceeded
by
applyingfo
facility
personnel
to
pedom
required
boiler
rep
down
time.

Power
to
Newly
Constru
W%
en
a
new
recyclingfacii
The
company
perfrmed
a
the
new
faciliry.
The
res
ASME
SWPD
Facility
Recog
Facility
Preservation
O&
fSL
has
corntan
been
investigating,
experimenting
and
utilizing
erotic
materials
to
help
stem
conmion
occum­
ng
in
high
humidity,
alkaline,
and
acidic
areas.
The
use
of
these
materials
result3
in
less
maintenance
and
a
longer
service
&
e
of
systems
inrtalled
in
iner
rmance
Enhancement
on
the
demineralization
system
due
to
decreasing
potable
water
quality.
OMSL
the
water
through
a
reverse
osmosis
membrane
water
treatment
system
in
a
much­
improvedperfomance
of
the
demineralizer,
&
meased
chemical
.
acid
Wash
System
to
Ciem
Atombms
atomizers
proved
to
be
a
high­
maintenance
item.
OMSL
designed
and
installed
and
acidgwh
operating
cleaner,
reducing
maintenance.
and
provided
proper
slurry
disrnhition
in
the
scmbbm
resulting
in
less
downtime
and
decreased
emissions.

On­
line
Binsting
of
Baghouses
dnd
Off­
line
Cleaning
of
Eloiler
to­
energy
facilitis
to
utilize
on­
line
percussion
cIeaning
to
improve
the
operation
of
the
harges
are
set
offin
the
fly­
ash
hoppers
while
the
boilers
are
in
operation,
that
res&
in
a
a
longer
period
between
outages
increasing
availability.

aned
off­
line
with
these
*
amile
charges.
ThiY
results
in
a
cleaner
boiler
and
no
w
e
of
water
corrosion.
TiiY
jiirther
provides
a
cleaner
working
environment
for
mainten
ed
outage
lime,
and
reduces
the
amount
of
wastewater
generatedfiom
the
Fa
rmance
of
the
Facility
with
respect
to
air
quality,
water
quality,
workplace
nt
environmental
areas.
Include
attachments
as
needed
(
e.
g.
monitoring
data,
graphs).

a
summary
of
the
Facility's
Environmental
Performance:

Environmental
Performance
ent
recordsince
starnip­
The
Fucility
has
been
in
fill
compliance
with
all
an
Air
Act
of
i
995
without
performing
any
mod@
cations
to
the
plant.
i
n
uddigon,
tal
Citizen
Award
for
the
results.

Annual
Air
Emissions
Testing
dnnuai
uir
emissions
testing,
also
known
as
stack
teshg.
wusper$
ormed
at
the
Facility
in
June
2000.
During
this
stack
test.
issions
of
particulate
matter
(
P%$
l,
opacity,
arsenic,
bqliium,
lead,
mercuv,
sulfMic
,
carbon
monoxide,
volatile
organic
compounds
(
TOG),
mlfir
dioxide*
hydrogen
demonstrated
to
be
in
compliance
with
all
permitted
levelsfor
mercuy,
sulfiric
acid
mist.
fluorides,
nitrogen
oxides
(
WOd,
carbon
&
ir
dioxide.
hydrogen
chloride,
ammonia,
and
dioxinsi@
ram.

7
I
_­_
­
i
_
­
I­

I
3
a
ASME
SWPD
Facili
ard
Nomination
Form
Tale
Y
Operating
Permit
0710119­
0014
Vto
the
Facility
on
November
I
.
2000.

In
recognition
of
the
excellent
level
DEP
awarded
Ogden
Martin
Sys
me
honor
because
it
the
DEF,
the
award
tained
by
the
Facility
the
South
n
Award
''
on
September
12,19
V.
FaciIity
Economics
(
10
percent)
Discuss
comparative
costshipping
fe
management
facilities.

Long­
rem
environmentally
responsible
solutions
to
VI.
Role
in
Integrated
Waste
Managemen
Describe
the
role
of
the
Facility
in
n.
and
agricllltural
waste
collection
center
(
under
cons
progrants
that
are
10.
Supplemental
Xnformation
c3
Photographs
ASME
SWPD
Facility
Recognition
Award
Nomination
Form
Submitted
By
Samer
Malcolm
Pirnie,
Inc.

Address:
1715
E.
9"'
Avenue
Tampa,
Florida
33605
Telephone:
(
8
13)
248­
6900
Fax:
(
813)
248­
8085
Number
of
Copies
Five
complete
copies
o
the
nomination
submittal
should
be
provided
Nomination
Due
Date
ASME
Solid
Waste
Processing
Division
Selection
Process
judged
by
the
SWPD's
Facility
Recogtion
Award
subcommittee
of
the
Honors
and
Awards
Committee,
selection
criteria
described
above.
The
selection
process
will
be
completed
upon
approval
ofthe
recommended
D's
Executive
CodUee.

ted
at
the
annual
Waste
Processing
Conference
@
JAWTEC).
The
award
will
consist
of
a
plaque
2suitabie
for
mounting
at
the
Facility.

ication
of
Award
will
publicize
the
award
through
press
releases
and
various
ASME
and
waste
management
industry
publication.

D
member
in
good
standing
may
nominale
a
FaciIity
for
the
SWPD
FaciSity
Recognition
Award.
Self­
nomination
by
Facility
personnel
are
welcome.

9
PHOTOGRAPHS
An
array
of
instruments
in
the
plant's
control
room
Facility
staff
monitor
the
plant's
condition
1
A
view
of
plant
piping
le.
*

2
I
The
refuse
claw
in
action
Facility
tipping
floor.
The
refuse
pit
is
visible
to
the
left.
1
i'

ter
pumps
at
the
cool
tower.

Sid
4
The
Facility's
reverse
osmosis
plant.
&

.
t
i.

View
of
the
non­
ferrous
metal
recovery
pile
7
t
EXCERPTS
OF
FDEP
2000
SOLID
WASTE
MANAGEMENT
ANNUAL
REPORT
LOU0
Solid
Waste
Management
m
Elonda
I
Employee
Directory
I
Help
1
SiteMap
1
Search
Solid
w
ment
in
Florida
2000
This
2000
Solid
Waste
Man
nual
Report
provides
a
comprehensive
analysis
of
solid
ludes
information
about
the
activities
of
the
Department,
ai
in
Florida
primarily
based
on
information
compiled
by
ling
with
waste
issues
t
n
s
for
downloading
rh3
whole
report
for
viewing
online
­­­

rt
is
availabie
in
Adobe's
Portable
Document
Format
(
PDF).
If
you
d
f
the
reader
software,
it
is
avaifable
free­
of­
charge
from
Adobe's
s
above
to
download
the
software
now.
Once
you
have
the
Acroba
you
may
download
the
entire
report
or
specfic
chapters.

PDF
file
is
too
small
to
read,
use
the
magnifyng
glass
tool
to
zoom
in.

n
the
appendices
can
also
be
downloaded
in
an
Microsoft
Excel
Instructions
the
chapters:
AVAILABLE
NOW!

These
files
will
dated
shortly,
so
please
be
patient,
you
may
wish
to
wait
until
the
efore
downloading.
Check
back
the
beginning
of
March.

1.
Create
a
directory
an
you
can
do
it
during
many
of
2.
rd
drive
for
the
report.
If
you
forget,
you
ng
file,
cDacwszisgzc
­
is,
saving
it
in
on
your
is
3­
19
Megabytes
(
M8).
It
will
take
some
time
to
patient.
save
this
Droqram
to
disk"
oDtion
and
then
select
llowing
steps
also.

3.

http
://
www
.
dep­
state
.
fl
.
us/
dwm/
documents/
sdswn­
OO/
defauk
htm
03/
07/
200
Z
Counties
(
CY
1998)

have
recycling
rates
21
County
I
(
Jan.
1,
7998
­
Dec.
31,
7998)

4.
4
6.
6.

324
233.
133.
47.
1.450.
247.
13.
55.
892
107.
85.
106.
2.090.
210.
80.
33.
25.
13.
35.
19.

13
i
7
19
3
148
10
6
1%

109
175
54
13
321
32
147.
22
50.
14
34
21.
27
43.
21.
7.
38.

Studies
as
reported
by
eact~
c.
aUay
by
ma
end
of
19%
for
eachcancymth
apopubtia,
over
75.
W.
fa
these
materials
by
theand
of
1994
for
each
canty.
n
36
35
35
40
34
32
31
31
37
30
28
n
37
27
43
27
39
26
28
26
32
25
25
24
27
24
40
23
22
22
22
21
20
20
19
27
18
18
17
16
18
16
16
15
75
t5
15
14
13
13
13
12
12
12
11
10
10
9
9
9
8
7
5
4
3s
3
1
d
sd
11
55
56
41
84
22
39
26
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61
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53
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17
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29
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a
1
FDEP
03/
0712001
&.
XIS
Attachment
B
Lee
County
Parametric
Data
Counq4LeeVambifrymemofmai.
wpd
e
*

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t
Attachment
C
Compliance
Test
Data
Analysis
for
Lee
County
Solid
Waste
Resource
Recovery
Facility
C:\
SmaUMWC\
Lee
County\
LeeVar1abiltymemofmaLwpd
COMPLIANCE
TEST
DATA
ANALYSIS
FOR
LEE
COUNTY
SOLID
WASTE
RESOURCE
RECOVERY
FACILITY
Prepared
for:

US.
Environmental
Protection
Agency
Office
of
Air
Quality
Planning
and
Standards
Emission
Standards
DivisiodCombustion
Group
Research
Triangle
Park,
NC
27560
Prepared
by:

Eastern
Research
Group
1600
Perimeter
Park
Drive
Morrisville,
North
Carolina
27560
September
4,2002
*
ERG
­
September
2002
TABLE
OF
CONTENTS
Section
Paye
#

1
.
O
DESCRIPTION
OF
LEE
COUNTY
SOLID
WASTE
RESOURCE
RECOVERY
FACILITYDATA
.
.
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2.0
STUDYOBJECTIVES
.
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3.0
PRELIMINARY
DATA
ANALYSIS
.
.
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4
4.0
COMPREHENSIVE
DATA
ANALYSIS
.
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6
4.1
Statistical
Distribution
of
Pollutant
Emission
Measurements
.
.
e
.
.
.
.
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.
.
e
.
.
.
.
6
4.1.1
Dioxin/
Furan
.
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8
4.1.2
Particulate
Matter
(
PM)
.
.
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8
­

4.1.3
Cadmium
.
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9
.

4.1.4
Lead
.
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­

4.1.5
Mercury
.
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l
O
4.1.6
Mercury
Percent
Reduction
.
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10
4.1.7
Hydrogen
Chloride
(
HC1)
.
.
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1
1
4.1.8
Hydrogen
Chloride
(
HCl)
Percent
Reduction
.
.
.
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.
1
1
4.1.9
Sulfur
Dioxide
(
SO,)
Arithmetic
Average
.
.
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12
4.1.10
Sulfur
Dioxide
(
SO,)
Percent
Reduction
.
.
.
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.
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.
.
.
.
.
.
.
.
.
.
.
.
12
4.1.11
Nitrogen
Oxides
(
NOJ
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
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.
13
4.2
95
and
99
Percent
Threshold
(
Le.,
Exceedance)
Values
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
13
5.0
REFERENCES
.
.
.
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..
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11
ERG
­
September
2002
I
I
LIST
OF
TABLES
Page
Table
1
Raw
MWC
Compliance
Data
from
Lee
County
Solid
Waste
Resource
Recovery
Facility
Unit
1
...........................................
16
Recovery
Facility
Unit
2
............................
Table
2
Raw
MWC
Compliance
Data
from
Lee
County
Solid
Waste
Table
3
Summary
Statistics
for
MWC
Compliance
Data
from
Lee
County
Solid
Waste
Resource
Recov
1
.........................
18
Table
4
Summary
Statistics
for
M
W
a
from
Lee
County
Solid
Waste
lityUnit2
.
.
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.
.

Results
for
the
Two­
Sample
F­
Test
..................................
.20
Results
for
the
Two­
Sample
t­
Test
(
Equal
Variances)
.
.
.
.
.
.
.
.
.
.
.
.
.
.
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.
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.
.
.21
­

Table
5
Table
6
Table
7
Summary
Statistics
for
MW
Solid
Waste
Resource
Reco
Units
1
and
2
Combined
.
*
­
*
­
*
*
*
*
­
*
­
*
*
.
­
­
*
­
*
­
*
m.
22
pliance
Data
from
Lee
County
Table
8
Summary
Statistics
for
C
Compliance
Data
from
Lee
County
Solid
Waste
Resource
Recovery
Facility
Units
1
and
2
Combined
..........................................
.23
Table
9
The
Shapiro­
Wilk
Normality
Statistic
(
W)
for
the
Raw
and
Ln­
TransformedMWC
Compliance
Data
from
Lee
County
Solid
Waste
Resource
Recovery
Facility
Units
1
and
2
Combined
..........
.24
Table
10
95
and
99
Percent
Thresholds
and
Threshold­
Mean
Differences
for
the
Raw
and
Ln­
transformed
MWC
Compliance
Data
from
Lee
County
Solid
Waste
Resource
Recovery
Facility
Units
1
and2Combined
.
.
.
.
.
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.
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,
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2
5
...
111
K\
0154\
11\
06\
mwc­
anaIysis­
rq~
o1'
t­
September
2002.
wpd
w
'
ERG
­
September
2002
LIST
OF
FIGURES
Page
Figure
l(
a)
Frequency
Histograms
for
Dioxifluran
(
ng/
dscm)
Compliance
Data
from
Lee
County
Solid
Waste
Resource
Recovery
Facility
Units
1
and
2
Combined
..........................................
.26
Figure
1
(
b)
Normal
Probability
Plots
for
Dioxifluran
(
ng/
dscm)
Compliance
Data
from
Lee
County
Solid
Waste
Resource
Recovery
Facility
Unitsland2Combined
...........................................
27
Frequency
Histograms
for
PM
(
mg/
dscm)
Compliance
Data
from
Lee
County
Solid
Waste
Resource
Recovery
Facility
Unitsland2Combined
...........................................
28
Figure
2(
a)

Figure
2(
b)
Normal
Probability
Plots
for
PM
(
mddscm)
Compliance
­

Data
from
Lee
County
Solid
Waste
Resource
Recovery
Facility
Units
1
and
2
Combined
..........................................
.29
­

Frequency
Histograms
for
Cadmium
(
mg/
dscm)
Compliance
Data
from
Lee
County
Solid
Waste
Resource
Recovery
Facility
Units
1
and
2
Combined
..........................................
.30
Normal
Probability
Plots
for
Cadmium
(
mg/
dscm)
Compliance
Data
from
Lee
County
Solid
Waste
Resource
Recovery
Facility
Units
1
and
2
Combined
..........................................
.31
Frequency
Histograms
for
Lead
(
mg/
dscm)
Compliance
Data
from
Lee
County
Solid
Waste
Resource
Recovery
Facility
Units
1
and2
Combined
..........................................
.32
Normal
Probability
Plots
for
Lead
(
mg/
dscm)
Compliance
Data
from
Lee
County
Solid
Waste
Resource
Recovery
Facility
Units
1
and
2
Combined
..........................................
.33
Figure
3
(
a)

Figure
3(
b)

Figure
4(
a)

Figure
4(
b)

Figure
5(
a)
Frequency
Histograms
for
Mercury
(
mg/
dscm)
Compliance
Data
&
om
Lee
County
Solid
Waste
Resource
Recovery
Facility
Units
1
and
2
Combined
...........................................
34
Figure
5(
b)
Normal
Probability
Plots
for
Mercury
(
mg/
dscm)
Compliance
Data
fiom
Lee
County
Solid
Waste
Resource
Recovery
Facility
Units
1
and
2
Combined
..........................................
.
3
5
K:\
0154\
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06bnwc­
analysis­
report­
September
2002.
wpd
iv
LIST
OF
FI
S
(
Continued)

Figure
6(
a)
Frequency
Histograms
for
Data
from
Lee
County
Units
1
and
2
Combine
.
.
.
.
.
.
.
.
.
.
.
.
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.
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.
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.
.
.
.
3
6
Figure
6(
b)
Normal
Probability
PI
Figure
7(
a)
Frequency
Histograms
for
Data
from
Lee
County
Sol
Units
1
and
2
Comb
Normal
Probability
Plots
for
HC1
(
ppmv)
Compliance
Data
from
Lee
County
Figure
7(
b)

­
Units
1
and
2
Combine
.
.
.
.
.
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.
.
­

­
Figure
8(
a)
Frequency
Histograms
for
H
Reduction
Compliance
Data
from
Lee
Co
Units
1
and
2
Comb
Normal
Probability
Plots
for
HC1
Percent
Reduction
Compliance
Data
from
Lee
County
Solid
Waste
Resource
Recovery
Facility
Units
1
and
2
Combined
.
.
,
.
.
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.
.

Frequency
Histograms
for
SO,
Arithmetic
Average
(
ppmv)
Compliance
Data
from
Lee
County
Solid
Wast
Units
1
and
2
Com
e
Recovery
Facility
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
4
0
Figure
8(
b)

Figure
9(
a)
urce
Recovery
Fa
.
.
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.
.
.
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.
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.
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.
.
.
.
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.
.
.
.
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.
.
.
.
.
.
.
.
.
.
.

Figure
9(
b)
Normal
Probability
Plots
for
SO,
Arithmetic
Average
(
ppmv)
Compliance
Data
from
Lee
County
Solid
Waste
Resource
Reco
Units
1
and
2
Combined
....................
'
­
*
­
*
­
*
­
*
­
­
­
43
Figure
1O(
a)
Frequency
Histograms
ent
Reduction
Compliance
Data
from
Lee
County
Units
1
and
2
Combined
Figure
1
O(
b)
Normal
Probability
Plots
for
SO,
Percent
Reduction
Compliance
Data
from
Lee
Coun
Units
1
and
2
Comb
Frequency
Histograms
for
NO,
(
ppmv)
Compliance
Data
from
Lee
County
Solid
Waste
Resource
Recovery
Facility
Unitsland2Combined
.
.
.
.
.
.
.
.
.
.
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,
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.
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,
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.
4
6
Recovery
Facility
..........................................
.44
ery
Facility
.
.
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.
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.
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.

Figure
1
1
(
a)

V
K
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report­
September
2002.
wpd
LIST
OF
FIGURES
(
Continued)

Figure
1
1
(
b)
Normal
Probability
Plots
for
NO,
(
ppmv)
Compliance
Data
from
Lee
County
Solid
Waste
Resource
Recovery
Facility
Units
1
and
2
Combined
.
.
.
.
.
,
.
.
.
.
.
.
.
.
.
.
,
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­
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.
.47
KA0154\
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report­
September
2002.
wpd
.
.­

Y
vi
'*

ERG
­
September
2002
1.0
DESCRIPTION
OF
LEE
COUNTY
SOLID
WASTE
RESOURCE
RECOVERY
FACILITY
DATA
Upon
request
from
the
U.
S.
Environmental
Protection
Agency,
COVANTA
Lee
Inc.

submitted
annual
municipal
waste
combustor
(
MWC)
compliance
data
for
the
period
1994
to
200
1
from
its
solid
waste
resource
recovery
facility
located
in
Lee
County,
Florida.
The
facility
consists
of
two
600
tons
per
day
(
tpd)
mass
burn
waterwall
units
(
referred
to
as
Unit
1
and
Unit
2)
each
of
which
is
equipped
with
spray
dryer,
fabric
filter,
carbon
injection,
and
selective
non­

catalytic
reduction.
The
MWC
data
submitted
included
emissions
measurements
from
both
units
for
the
following
pollutants:

e
e
e
e
e
e
Dioxidfuran
(
ng/
dscm),

Particulate
matter
(
PM)
(
rng/
dscm),

Cadmium
(
mg/
dscm),

Lead
(
mg/
dscm),

Mercury
and
percent
mercury
reduction
if
available
(
mg/
dscm),

Hydrogen
Chloride
(
HCl)
and
percent
HC1
reduction
if
available
(
ppmv),

Sulfur
dioxide
(
SO,)
and
percent
SO,
reduction
if
available
(
ppmv),

Nitrogen
oxides
(
NOJ
(
ppmv).

The
tests
followed
the
procedures
required
by
the
large
MWC
New
Source
Performance
Standards
(
NSPS)
(
40
CFR
Subpart
Cb).
The
values
reported
for
dioxins/
furans,
PM,
cadmium,

lead,
mercury
and
HCl
are
the
arithmetic
average
control
device
outlet
levels
for
a
3­
run
stack
test
using
the
EPA
test
methods
and
sampling
times
required
by
the
NSPS.
For
mercury,
the
average
percent
reduction
for
the
3­
run
test
is
also
provided.
The
SO,
values
are
%­
hour
arithmetic
average
outlet
concentration
and
percent
reduction
values
calculated
fiom
continuous
emission
monitoring
(
GEM)
data
during
the
first
24
hours
of
the
annual
performance
test.
(
Note
that
Subpart
Cb
requires
facilities
to
demonstrate
SO,
compliance
with
either
a
geometric
mean
outlet
concentration
or
a
percent
reduction.
The
facility
is
using
percent
reduction
and
did
not
K\
0154\
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06unwc­
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report­
September
2002.
wpd
1
t
provide
the
geometric
mean.)

device
outlet
calculated
from
CEM
d
Tables
1
and
2
present
the
raw
MWC
compliance
data
provided
by
the
Lee
County
solid
waste
resource
recovery
facility
units
1
and
2
94
through
2001.
'
EQG
­
September
2002
2.0
STUDY
OBJECTIVES
The
main
objectives
of
the
study
are:

To
characterize
the
variability
in
pollutant
emission
measurements
(
due
to
variability
in
process
and
measurement)
using
basic
univariate
statistics
and
relative
frequency
histograms,

To
evaluate
the
statistical
distribution
of
pollutant
emission
measurements
(
ie.,
normal
versus
lognormal)
with
normality
tests
and
applicable
shape
statistics,
such
as
relative
frequency
histograms
and
normal
probability
plots,
and
To
compute
relevant
threshold
values
(
Le.,
exceedance
values),
based
on
computed
sample
means
and
standard
deviations,
for
which
the
probability
that
a
given
test
at
the
facility
will
be
above
the
threshold
value
is
95
and
99
percent.
*

­

K
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4
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September
2002.
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3
I­­
~~~
­

­

1­

­­"?
3.0
PRELIMINARY
DATA
ANALYSIS
Tables
3
and
4
present
the
routine
swnmary
statistics
for
the
annual
MWC
compliance
data
fiom
the
Lee
County
solid
waste
resource
recovery
facility
units
1
and
2,
respectively,
for
the
period
1994
to
200
1
pollutant,
ERG
first
evaluated
precision.
For
this,
ERG
empl
any
evidence
to
indic
the
two
units
are
substantial1
sts
that
assess
whether
there
is
First,
ERG
conducted
a
hypothesis
t
r
there
is
sufficie
­
indicate
a
significant
difference
in
the
variability
and
2.
Table
5
presents
the
results
of
the
hypothesis
test
(
two­
sample
F­
test)
conducted
for
each
pollutant.
Because
the
computed
value
of
the
F­
statistic
was
less
than
the
critical
value,
Fa,
for
all
pollutants
at
the
95
and
99
percent
confidence
levels,
ERG
faiIed
to
reject
the
null
hypothesis
that
the
variability
of
pollutant
emission
measurements
from
the
two
units
are
statistically
equivalent.
­

Having
established
that
there
is
insufficient
evidence
to
support
that
the
observed
variability
of
pollutant
emission
measurements
for
Unit
1
is
different
than
that
of
Unit
2,
ERG
conducted
an
additional
hypothesis
test
to
evaluate
whether
there
is
sufficient
evidence
to
indicate
a
difference
in
the
mean
value
of
pollutant
emission
measurements
between
the
two
units.
Table
6
presents
the
results
of
the
hypothesis
test
(
two­
sample
t­
test)
conducted
for
each
pollutant.
From
the
table,
the
absolute
value
of
the
computed
t­
statistic
is
less
than
the
critical
value,
t,,
for
all
pollutants
at
the
95
and
99
percent
confidence
levels.
This
indicates
that
there
is
insufficient
evidence
to
reject
the
null
hypothesis
that
the
mean
pollutant
emission
measurements
fiom
the
two
units
are
statistically
equivalent.

Because
both
hypothesis
tests
suggest
that
there
is
no
statistically
significant
difference
in
the
mean
pollutant
emission
measurement
and
its
variability
between
Units
1
and
2
for
each
4
K\
0154\
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September
2002.
wpd
1
c
ERG
­
September
2002
pollutant,
ERG
combined
the
data
for
the
two
units
for
all
pollutants.*
It
is
expected
that
the
data
from
the
two
units
would
be
similar
because
the
designs
of
the
combustors
and
control
equipment
are
identical,
they
were
installed
at
the
same
time,
they
receive
MSW
from
the
same
sources,
and
they
are
operated
and
maintained
similarly
at
the
same
MWC
facility.
Table
7
.

presents
the
routine
summary
statistics
for
MWC
compliance
data
from
the
Lee
County
solid
waste
resource
recovery
facility
units
1
and
2
combined.
Table
8
provides
the
same
summary
statistics
for
the
In­
transformed
MWC
compliance
data.

*
It
should
be
noted
that
the
parametric
distributional
tests
conducted
are
relatively
low
power,
especially
for
small
sample
sizes.
Hence,
conclusions
obtained
fiom
these
tests
have
to
be
weighted
appropriately
in
light
of
other
relevant
considerations,
such
as
the
similarity
of
control
technologies
in
each
unit.

K:\
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wc­
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September
2002.
wpd
5
*
I
ERG
­
September
2002
(
1'
I
4.0
COMPREHENSIVE
DAT
ERG
utilized
several
statistical
an
data
for
both
units
combined.
These
techniques
1
0
ical
distribution
llutant
data
(
normal
ver
probability
plots,
s
and
normality
tests,
and
0
Computation
of
threshold
values
(
i.
e.,
exceedance
values)
for
each
pollutant
based
on
sample
means
and
standard
deviations.

The
following
sections
discuss
the
techniques
and
results
obtained
in
further
detail.

.
­

4.1
Statistical
Distribution
of
Pollutant
Emission
Measurements
There
are
numerous
methods
for
evaluating
the
statistical
distribution
of
a
given
data
set.

For
the
Lee
County
MWC
data,
ERG
employed
the
following
techniques
to
assess
whether
the
compliance
data
submitted
for
a
given
pollutant
is
normally
or
lognormally
distributed:

0
Frequency
histograms,

Normal
probability
plots,

0
Sample
moments
(
skewness
and
kurtosis),
and
0
Shapiro­
Wilk
(
W)
test.

AJFequency
histogram
divides
the
data
range
into
units,
counting
the
number
of
points
within
the
units,
and
displaying
the
data
as
the
height
or
area
within
a
bar
graph.
The
frequency
histogram
provides
a
means
for
assessing
the
symmetry
and
variability
of
the
data.
If
the
data
afe
symmetric,
the
frequency
histogram
will
also
display
symmetry
around
a
central
point,
such
as
a
mean.
Typically,
the
frequency
histog
ibuted
data
will
be
bell­
shaped.

6
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­
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2002
A
normalprobabilityplot
shows
the
observations
of
a
sample
plotted
against
a
cumulative
frequency
distribution
(
or
quantiles
of
a
data
set
against
the
quantiles
of
the
normal
distribution).
Comparing
against
the
standard
S­
shaped
cumulative
frequency
distribution
is
difficult,
so
the
chart
transforms
the
observations
so
they
can
be
compared
against
a
straight­
line.

Observations
for
a
normally
distributed
sample
should
closely
follow
a
straight­
line.
For
non­

normally
distributed
data,
there
will
be
large
deviations
in
the
tails
or
middle
of
a
normal
probability
plot.
The
normal
probability
plot
is
also
another
way
to
assess
the
degree
of
symmetry
(
or
asymmetry)
displayed
by
the
data.
For
example,
if
the
data
in
the
upper
tail
fall
above
and
the
data
in
the
lower
tail
fall
below
the
quartile
line,
the
data
are
too
slender
to
be
well
modeled
by
a
normal
distribution.
Similarly,
if
the
data
in
the
upper
tail
fall
below
and
the
data
in
the
lower
tail
fall
above
the
quartile
line,
then
the
tails
of
the
data
are
too
heavy
to
be
well
modeled
using
a
normal
distribution.

The
skewness
coeficient
measures
the
degree
of
symmetry
(
or
asymmetry)
displayed
by
a
data
set.
The
kurtosis
coefJicient,
on
the
other
hand,
measures
the
degree
of
flatness
of
a
distribution
near
its
center.
For
an
ideal
normal
distribution,
the
skewness
and
kurtosis
coefficients
are
equal
to
0.
Substantial
variations
from
the
0
value
indicate
that
the
data
may
not
be
modeled
using
a
normal
distribution.

The
Shapiro­
Wilk
(
w)
test
is
one
of
most
commonly
employed
tests
of
normality.
The
test
involves
computing
a
correlation
between
the
quantiles
of
the
standard
normal
distribution
and
the
ordered
values
of
a
data
set
and
is
only
recommended
for
sample
sizes
less
than
or
equal
to
50.
The
statistical
power
of
the
test,
however,
declines
for
very
small
sample
sizes.
The
value
of
the
W
statistic
computed
for
a
given
set
of
data
can
range
from
0
to
1,
with
low
values
typically
leading
to
the
rejection
of
the
null
hypothesis
of
normality.

In
evaluating
the
most
appropriate
statistical
distribution
(
normal
versus
lognormal)
for
a
given
set
of
data,
the
results
obtained
from
the
application
of
the
above
statistical
techniques
have
to
be
considered
jointly.
Especially
for
small
sample
sizes,
no
single
technique
is
likely
to
yield
definitive
conclusions
on
the
type
of
distribution
displayed
by
the
data.
The
following
sections
present
the
results
of
the
statistical
analyses
performed
on
MWC
compliance
data
for
K:\
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­,
each
pollutant.
The
sections
also
provide
an
assessment
the
data
based
on
the
analyses
performed
tatistical
distribution
displayed
by
4.1.1
Dioxin/
F'uran
The
frequency
histograms
dioxidfuran
data
are
depicted
in
Figures
1
(
a)
and
1
(
b
transformed
data
is
more
symmetric
aro
the
raw
data.
Further,
the
In­
transforme
normal
probability
plot
depicted
in
Figure
1
data
(
0.0487)
is
much
statistics
for
the
raw
and
In­
transformed
dioxidfuran
data
are
0.8568
and
0.9572,
respectively
(
see
Table
9).
The
W­
statistic
indicates
a
normal
data
distribution
for
the
In­
transformed
data
at
the
95
percent
level
of
confidence.
­

­

Overall,
the
analyses
performed
suggests
al
dioxidfbran
compliance
data
submitted
by
the
Lee
County
solid
wa
distribution.

4.1.2
Particulate
Matter
(
PM)

The
frequency
histograms
and
n
and
ln­
tmnsformed
PM
data
are
depicted
in
Figures
2(
a)
and
2
is
more
symmetric
around
its
mean
with
so
the
In­
transformed
data
is
more
evenly
spread
out
and
hence
more
close
straight
line
in
the
normal
probability
plot
depicted
in
Figure
2(
b).
The
skewness
coefficient
of
approximate
the
ed
data
(
0.0835)
is
7).
Similar
to
the
­

dioxin/
fbran
data,
ho
indicates
normality
at
the
95
percent
level
of
confidence.
r
the
In­
transformed
PM
data
(
0.8688)

8
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Overall,
the
analyses
performed
suggests
that
the
annual
PM
compliance
data
submitted
by
the
Lee
County
solid
waste
resource
recovery
facility
display
a
lognormal
distribution.

4.1.3
Cadmium
I
The
fiequency
histograms
and
normal
probability
plots
of
the
raw
and
In­
transformed
cadmium
data
are
depicted
in
Figures
3(
a)
and
3(
b),
respectively.
From
Figure
3(
a),
the
raw
data
appears
more
symmetric
around
its
mean
with
some
extreme
values
in
the
highest
bin
(
0.001
125
scm).
The
normal
probability
plot
of
the
raw
data
more
closely
approximates
the
straight
line
in
the
normal
probability
plot
depicted
in
Figure
3(
b).
Further,
the
skewness
coefficient
of
the
raw
data
(­
0.544)
is
higher
(
closer
to
0,
the
value
for
an
ideal
normal
distribution)
than
that
of
the
In­
transformed
data
(­
0.9395).
The
W­
tests
for
the
raw
and
ln­
­

transformed
data
both
reject
the
null
hypothesis
of
normality
at
the
95
percent
level
of
­

confidence.

Overall,
the
analyses
performed
suggests
that
the
annual
cadmium
compliance
data
submitted
by
the
Lee
County
solid
waste
resource
recovery
facility
display
a
relatively
normal
distribution.
I
4.1.4
Lead
The
frequency
histograms
and
normal
probability
plots
of
the
raw
and
In­
transformed
lead
data
are
depicted
in
Figures
4(
a)
and
4(
b),
respectively.
From
Figure
4(
a),
the
In­
transformed
data
appears
more
symmetric
around
its
mean
with
some
extreme
values
in
the
­
5.25
to
­
4.75
range.
The
In­
transformed
data
is
more
evenly
spread
and
hence
more
closely
approximates
the
straight
line
in
the
normal
probability
plot
depicted
in
Figure
4(
b).
Further,
the
skewness
coefficient
of
the
In­
transformed
data
(­
0.473
1)
is
lower
(
closer
to
0,
the
value
for
an
ideal
normal
distribution)
than
that
of
the
raw
data
(
0.876).
The
W­
tests
conducted
for
the
raw
and
ln­

transformed
data,
however,
both
fail
to
reject
the
null
hypothesis
of
normality
at
the
95
percent
level
of
confidence.

c
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2002.
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I
Overall,
the
analyses
performed
suggests
that
the
annual
lead
compliance
data
suimitted
by
the
Lee
County
solid
waste
resource
recovery
display
a
lognormal
distribution.
,

4.1.5
Mercury
The
frequency
histograms
and
normal
probability
plots
of
the
raw
and
In­
tr
mercury
data
are
depicted
in
Figures
5(

appears
more
symmetric
around
its
mean
with
fewer
extreme
v
evenly
spread
and
hence,
more
closely
appr
plot
depicted
in
Figure
5(
b)
as
well.
T
observations
clustered
along
higher,
hence
closer
t
(­
2.6078).
The
computed
W­
statistic
for
a
normal
data
distribution
at
the
95
percent
level
of
confidence.
the
value
for
an
Overall,
the
analyses
performed
sug
mercury
compliance
data
submitted
by
the
Lee
County
solid
waste
resource
recovery
facility
display
a
relatively
normal
distribution.

4.1.6
Mercury
Percent
Reduction
The
frequency
histograms
and
normal
probability
plots
of
the
raw
and
In­
transformed
mercury
percent
reduction
data
are
depicted
in
Figures
6(
a)
and
6(
b),
respectively.
From
Figure
,
6(
a),
both
the
raw
and
the
ln­
transformed
data
appear
to
be
positively
skewed.
There
also
is
no
substantial
difference
between
how
the
raw
and
In­
transformed
data
are
spread
along
the
straight
line
in
the
normal
probability
data
(­
1.3233)
is
higher,
henc
transformed
data
(­
1
3549).
Fu
reduction
compliance
data
(
0
confidence.
efficient
of
the
raw
e
for
an
ideal
normal
distribution,
than
the
ln­

raw
mercury
percent
95
percent
level
of
10
K.\
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report­
September
2002.
wpd
P
ERG
­
September
2002
Overall,
the
analyses
performed
suggests
that
the
annual
mercury
percent
reduction
compliance
data
submitted
by
the
Lee
County
solid
waste
resource
recovery
facility
display
a
relatively
normal
distribution.

4.1.7
Hydrogen
Chloride
(
HCI)

The
frequency
histograms
and
normal
probability
plots
of
the
raw
and
In­
transformed
HCl
data
are
depicted
in
Figures
7(
a)
and
7(
b),
respectively.
From
Figure
7(
a),
the
In­
transformed
data
appears
less
skewed
than
the
raw
data.
Further,
the
In­
transformed
data
is
more
evenly
spread
out
and
hence
more
closely
approximates
the
straight
line
in
the
normal
probability
plot
depicted
in
Figure
7(
b).
The
skewness
coefficient
of
the
In­
transformed
data
(
0.591
8)
is
lower
than
that
for
the
raw
data
(
1.3
140).
Finally,
the
W­
test
for
the
In­
transformed
data
fails
to
reject
­

the
null
hypothesis
of
normality
at
the
95
percent
level
of
confidence.
­

Overall,
the
analyses
performed
suggests
that
the
annual
HC1
compliance
data
submitted
by
the
Lee
County
solid
waste
resource
recovery
facility
display
a
lognormal
distribution.

4.1.8
HCI
Percent
Reduction
The
frequency
histograms
and
normal
probability
plots
of
the
raw
and
In­
transformed
HCl
percent
reduction
data
are
depicted
in
Figures
8(
a)
and
8(
b),
respectively.
From
Figure
8(
a),

both
the
raw
and
the
In­
transformed
data
appear
to
be
positively
skewed.
There
also
is
no
substantial
difference
between
how
the
raw
and
In­
transformed
data
are
spread
along
the
straight
line
in
the
normal
probability
plot
depicted
in
Figure
S(
b).
The
skewness
coefficients
of
the
raw
and
In­
transformed
data
are
nearly
identical
indicating
no
substantial
difference
between
using
the
two
distributional
assumptions.
Finally,
the
computed
W­
statistics
for
the
raw
and
ln­

transformed
data
both
fail
to
reject
the
assumption
of
normality
at
the
95
percent
level
of
confidence.

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2002.
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4.1.9
Sulfur
Dioxide
(
SO,)
Arithmetic
Average
The
frequency
histograms
the
raw
and
ln­
transformed
so,

ectively.
From
Figure
9(
a),
the
arithmetic
average
data
are
depicted
in
Figure
raw
data
is
negatively
skewed
wi
In­
transformed
data
is
positively
ske
The
raw
data
is,
ho
plot
depicted
in
Figure
9(
b).
The
the
quartile
line
in
the
upper
tail.

hence
closer
to
0,
the
value
for
1.0151).
Additionally,
the
data
(
0.9030)
also
support
e
upper
tail
of
the
distribution.

0,
arithmetic
average
compliance
nt
level
of
confidence.

Overall,
the
analyses
performed
suggests
that
the
annual
SO,
ar
compliance
data
submitted
by
the
Lee
County
s
relatively
normal
distribution.

4.1.10
SO,
Percent
Reduction
1
The
frequency
histograms
an
probability
plots
of
the
percent
reduction
data
are
depicted
both
the
raw
and
the
In­
transfo
percent
reduction
data,
there
is
no
s
data
are
spread
along
the
straight
li
skewness
coeffkients
of
the
raw
and
In­
transformed
data
are
fairly
close
with
the
skewness
n
how
the
raw
and
In­
transformed
coefficient
of
the
raw
data
slightly
better
than
that
of
the
In­
transformed
one.
Finally,
the
'
ERG
­
September
2002
computed
W­
statistics
for
the
raw
and
ln­
transformed
data
both
fail
to
reject
the
assumption
of
normality
at
the
95
percent
level
of
confidence.

Overall,
the
analyses
performed
suggests
that
the
annual
SO,
percent
reduction
compliance
data
submitted
by
the
Lee
County
solid
waste
resource
recovery
facility
display
a
relatively
normal
distribution.

4.1.11
Nitrogen
Oxides
(
NO,)

The
frequency
histograms
anb
normal
probability
plots
of
the
raw
anc
In­
transformed
NO,
data
are
depicted
in
Figures
1
1
(
a)
and
1
l(
b),
respectively.
From
Figure
1
1
(
a),
both
the
raw
and
In­
transformed
data
are
positively
skewed
with
extreme
values
in
upper
tail
of
the
distribution.
Moreover,
there
are
no
substantial
differences
in
the
spread
of
observations
along
the
quartile
line
between
the
raw
and
In­
transformed
data
in
the
normal
probability
plots
depicted
in
Figure
1
1
(
b).
The
skewness
coefficient
of
the
raw
data
(­
1.5242),
however,
offers
a
slight
­

­

improvement
over
that
of
the
In­
transformed
one
(­
1.5905).
The
conducted
W­
tests
for
the
raw
and
In­
transformed
data
both
reject
the
normality
assumption
at
the
95
percent
level
of
confidence.

Overall,
the
analyses
performed
suggests
that
the
annual
NO,
compliance
data
submitted
by
the
Lee
County
solid
waste
resource
recovery
facility
display
a
relatively
normal
distribution.

4.2
95
and
99
Percent
Threshold
(
i.
e.
Exceedance)
Values
In
the
second
stage
of
the
comprehensive
data
analysis,
ERG
computed
compliance
thresholds
(
i.
e.,
exceedance
values)
at
95
and
99
percent
significance
levels
for
each
pollutant.

The
95
and
99
percent
exceedance
values
reflect
the
emission
levels
that
the
Lee
County
facility
can
meet
during
an
annual
test
with
95
and
99
percent
probability,
respectively,
and
are
computed
as:
­

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where:
tandard
Deviation
Mean
Standard
deviation
=
Sarnpl
ta
P
Table
10
presents
the
95
and
mean
by
pollutant
(
c
applicable
threshold
v
­

Section
4.1
for
each
p
.

I
Deviation
and
is
spec
threshold
and
the
mean
is
t,
'
Standard
­

j
14
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analysis­
report­
Septmber
2002.
wpd
'
c
'
ERG
­
September
2002
5.0
REFERENCES
Epperson,
David
and
David
White.
1995.
"
Supplemental
Analysis
of
NO,
Emissions
Data
from
the
Stanislaus
County
MWC."
Memorandum
from
Radian
Corporation
to
Walt
Stevenson,
EPA/
ESD.
August
30.

Lanier,
Steven
W.
and
Charles
D.
Hendrix.
2001.
Reference
Method
Accuracy
and
Precision
(
ReMAP):
Phase
I
:
Precision
of
Manual
Stack
Emission
Measurements.
American
Society
of
Mechanical
Engineers
(
ASME)
Research
Committee
on
Industrial
and
Municipal
Waste.
February.

Mendenhall,
William,
Dennis
D.
Wackerly,
and
Richard
L.
Scheaffer.
1990.
Mathematical
Statistics
with
Applications.
4&
Edition.
P
WS­
Kent
Publishing
Company.
Boston,
MA.

U.
S.
Environmental
Protection
Agency
(
EPA).
2000.
Guidance
for
Data
Quality
Assessment:
Practical
Methods
for
Data
Analysis.
EAP
QNG­
9
QAOO
Update.
Office
of
Environmental
Information.
Washington,
D.
C.
July.
­

­

K.\
O
154U
l\
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nwc­
analysis­
report­
September
2002.
wpd
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0
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Y
Y
3
3
k
d0"
w
l
w
l
n
a
a
5
W
ERG
­
September
2002
Frequency
Histograms
for
Dio
Data
from
Lee
County
Frequency
Hi
Frequency
Histogram:
in­
transformed
Data
4.5
0.5
1
1.5
2
2.5
3
Ln(
dioxin/
furan
(
ngldscm))
Bins*

26
*
b
e
4
ERG
­
September
2002
Normal
Probability
Plots
for
DioxinB'uran
(
ng/
dscm)
Compliance
Data
from
Lee
County
Solid
Waste
Resource
Recovery
Facility
Units
1
and
2
Combined
Normal
Probability
Plot:
Raw
Data
0
5
10
15
20
25
30
DioxinlFuran
(
ngldscm
)

Normal
Probability
Plot:
Ln­
transformed
Data
0.5
1
1.5
2
2.5
3
3.5
Ln(
Dioxin/
furan
(
nglds
crn
))

K\
0154\
11\
06\
mwc­
analysis­
report­
September
2002.
wpd
27
Frequency
Histograms
for
PM
(
mgldsc
ounty
Solid
Waste
Resource
Recove
9,
I
1
l
0
2
4
6
8
Particulate
Matter
(

*
The
x­
axis
labels
denote
the
midpoint
of
the
bin
range,
Le.,
+/­
1
mg/
dscm
about
the
midpoint.

6
5
4
s
E
s
3
ET
$
2
1
0
*
The
x­
axis
labels
denote
the
midpoint
of
the
bin
range,
Le.,
+
I­
0.25
In
(
mg/
dscm)
about
the
midpoint.

28
K:\
0154\
11\
06hwc­
analysis­
report­
September
2002.
wpd
/
'
i
Figure
2(
b)
Normal
Probability
Plots
for
PM
(
mgdscm)
Compliance
Data
from
Lee
County
Solid
Waste
Resource
Recovery
Facility
Units
1
and
2
Combined
Normal
Probability
Plot:
Raw
Data
0
2
4
6
8
10
Particulate
Matter
(
mg/
dscm)

Normal
Probability
Plot:
Ln­
transformed
Data
2
.­
2
1
.
Id
E
m
s
o
­
E
­
1
m
z
­
2
­
1
­
0.5
0
0.5
1
1.5
2
2.5
Ln(
Particu1ate
Matter
(
m
gldscm))

K\
0154\
11\
06\
mwc­
analysis­
report­
September
2002.
wpd
29
a
Figure
3(
a)
Frequency
Histograms
for
Cadmium
(
m
ce
Data
from
Lee
Waste
Resource
Re
J
3.5
3
2.5
6
E
2
1.5
2
"
1
0.5
0
0
Cadmium
(
mgldscm)
Bins*

*
The
x­
axis
labels
denote
the
midpoint
of
F
Frequency
Histogram:
Ln­
transformed
ta
4.5
,
1
1
1
1
1
4
3.5
3
5
2.5
2
1.5
1
0.5
0
6
s
2
u.

­
8.25
­
8
­
7.75
­
7.5
­
7.25
­
7
­
6.75
Ln(
Cadmium
(
mg/
dscm))
Bins*

*
The
x­
axis
labels
denote
the
midpoint
of
the
bin
range,
Le.,
+/­
0.125,
In
(
mddscm)
about
the
midpoint.

K\
0154\
11\
06\
mwc­
analysis­
report­
September
2002.
wpd
30
'
E8G
­
September
2002
Figure
3(
b)
Normal
Probability
Plots
for
Cadmium
(
mg/
dscm)
Compliance
Data
from
Lee
County
Solid
Waste
Resource
Recovery
Facility
Units
1
and
2
Combined
Normal
Probability
Plot:
Raw
Data
0.00025
0.0005
0.00075
0.001
0.00125
0.0015
Cadm
ium
(
mgldscm)

*
The
x­
axis
labels
denote
the
midpoint
of
the
bin
range,
Le.,
+
I­
1
mg/
dscm
about
the
midpoint.

Normal
Probability
Plot:
Ln­
transformed
Data
­
8.25
­
8
­
7.75
­
7.5
­
7.25
­
7
­
6.75
­
6.5
Ln(
Cadm
ium
(
ngldscm))

E.\
O154\
11\
06\
mwc­
analysis­
report­
September
2002.
wpd
31
Frequency
Histograms
for
Lead
(
mg/
dscm)
Co
om
Lee
County
Solid
Waste
nd
2
Combined
Lead
(
mgldscm)
Bins*
­

*
The
x­
axis
labels
denote
the
midpoint
of
the
b
rmed
Data
4.5
4
3.5
3
2.5
1.5
1
0.5
0
5
2
*
The
x­
axis
labels
denote
the
midpoint
of
the
bin
range,
i.
e.,
+/­
0.25
In
(
mg/
dscm)
about
the
midpoint.

32
K:\
0154\
11\
06\
mwc­
analysis­
report­
September
2002.
wpd
r­

=­­­­

­
4
.
:
­
September
2002
I
Figure
4(
b)
Normal
Probability
Plots
for
Lead
(
mg/
dscm)
Compliance
Data
from
Lee
County
Solid
Waste
Resource
Recovery
Facility
Units
1
and
2
Combined
Normal
Probability
Plot:
Raw
Data
0
0.003
0.005
0.008
0.01
0.013
0.015
0.018
0.02
Lead
(
mgldscm)

Normal
Probability
Plot:
Ln­
transformed
Data
2
I
I
I
I
b
I
i
­
7
­
6.5
­
6
­
5.5
­
5
­
4.5
­
4
­
3.5
Ln
(
Lead
(
m
g/
ds
cm
))

K\
0154\
11\
06hwc­
analysis­
report­
September
2002.
wpd
33
Figure
5(
a)
1
Frequency
Histograms
for
Mercu
Waste
Resource
R
from
Lee
County
Solid
*
The
x­
axis
labels
denote
the
midpoint
of
the
bin
range,
Le.,
+/­
0.005
mg/
dscm
about
the
midpoint.

ency
Histogram
med
Data
7
6
5
1
0
*
The
x­
axis
labels
denote
the
midpoint
of
the
bin
range,
Le.,
+/­
0.25
In
(
mg/
dscm)
about
the
midpoint.

34
K\
0154\
11\
06\
mwc­
analysis­
repo~­
September
2002.
wpd
Figure
5(
b)
Normal
Probability
Plots
for
Mercury
(
mg/
dscm)
Compliance
Data
from
Lee
County
Solid
Waste
Resource
Recovery
Facility
Units
1
and
2
Combined
Normal
Probability
Plot:
Raw
Data
n
0
0.01
0.02
0.03
0.04
0.05
0.06
Mercury
(
m
glds
cm
)

Normal
Probability
Plot:
Ln­
transformed
Data
2
1
0
­
.­
E
O
m
3
m
0
u
­
1
­
2
­
3
­
4
­

­
7
­
6.5
­
6
­
5.5
­
5
­
4.5
­
4
­
3.5
­
3
­
2.5
Ln
(
M
e
rcury
(
m
glds
cm
))

K\
0154\
11\
06\
mwc­
analysis­
report­
September
2002.
hpd
35
Frequency
Histograms
for
Merc
ata
from
Lee
County
ed
a
7
6
3
5
f
4
L
e
3
Q
i
2
1
I
0
*
The
x­
axis
labels
denote
the
midpoint
of
the
bin
range,
Le.,
+/­
5%
about
the
midpoint.

Frequency
Histogram
Data
3
e
C
a,
3
Q
U.
I
O
,
I
I
I
I
9
7
6
5
4
3
2
1
0
a
3.6
4.4
*
The
x­
axis
labels
denote
the
midpoint
of
the
bin
range,
Le.,
+/­
0.1
In
(%)
about
the
midpoint.

36
K\
0154\
11\
06\
mwc­
analysis­
report­
September
2002.
wpd
Figure
6@)
Normal
Probability
Plots
for
Mercury
Percent
Reduction
Compliance
Data
from
Lee
County
Solid
Waste
Resource
Recovery
Facility
Units
1
and
2
Combined
Normal
Probability
Plot:
Raw
Data
2
1
Q)
­
.­
I
+
I
5
0
I
5
­
2
­
I
I
ti
z
­
2
­
3
40
50
60
70
80
90
100
Mercury
%
Reduction
Normal
Probability
Plot:
Ln­
transformed
Data
Q)

E
m
­
.­
+
I
5
­
m
E
z
I
3.8
4
4.2
4.4
4.6
3.6
Ln(
Mercury
%
Reduction)

K
\
O
154\
11\
06\
mwc­
analysis­
report­
September
2002.
wpd
37
~
~
~­
­
­

LJ­­

­~
~
­­
­~
­
­
­~
~
­
­
a
I
.
.
>

Frequency
Histograms
for
HCl
(
ppm
Resource
Recovery
Lee
County
Solid
Waste
8
7
6
E
5
L
2
?
3
5
4
m
2
1
0
_
i
*
The
x­
axis
labels
denote
the
midpoint
of
the
b
midpoint.

Frequency
Histogram;
Ln­
transformed
Data
I
I
I
7
6
5
$
4
W
s3
2
L
2
1
0
2.25
2.5
Ln(
HCI
(
ppmv))
Bins*

38
K
\
O
154\
11\
06\
mwc­
analysis­
report­
September
2002.
wpd
%

4
Figure
7(
b)
Normal
Probability
Plots
for
HCl
(
ppmv)
Compliance
Data
from
Lee
County
Solid
Waste
Resource
Recovery
Facility
Units
1
and
2
Combined
Normal
Probability
Plot:
Raw
Data
­
2
0
I
10
.
15
20
25
30
35
40
HCI
(
PPmv)

Normal
Probability
Plot:
Ln­
transformed
Data
K.\
0154\
11\
06\
mwc­
analysis­
report­
Septernber
2002.
wpd
39
Frequency
Histograms
for
H
ta
from
Lee
County
ine
Solid
Waste
Reso
6
5
4
5
2
3
C
r
E
2
1
0
*
The
x­
axis
labels
denote
the
midpoint
of
the
bin
range,
Le.,
%
about
the
midpoint.

7
6
5
>,
E
4
Q)

5
3
2
L
2
1
0
K\
0154\
11\
06\
mwc­
analysis­
report­
September
2002.
wpd
40
c
4'
T&
ERG
­
September
2002
Normal
Figure
8(
b)

Solid
Waste
Resource
Recovery
Facility
Units
1
and
2
Combined
Probability
Plots
for
HCI
Percent
Reduction
Compliance
Data
from
Lee
County
Q)

E
m
­
.­
c
a
Normal
Probability
Plot:
Raw
Data
95.5
96
96.5
97
97.5
98
98.5
HCI
%
Reduction
Normal
Probability
Plot:
Ln­
transformed
Data
4.56
4.565
4.57
4.575
4.58
4.585
4.59
Ln(
HCI
%
Reduction)

41
K
\
O
154\
11\
06\
mwc­
analysis­
repon­
September
2002.
wpd
­­­­
r­
7
­_
D_/
>

Frequency
Histogra
0
2.5
5
7.5
10
12.5
15
17.5
S
*
The
x­
axis
labels
denote
the
midpoint
of
the
bin
range,
i.
e.,
+/­
1.25
ppmv
about
the
midpoint.

Frequency
Histogra
Da
7
6
5
g
4
Q)
J
c
r
3
2
u
2
1
0
Ln(
S02
Arithmetic
Mean
(
ppmv))
Bins*

*
The
x­
axis
labels
denote
the
midpoint
of
the
bin
range,
i.
e.,
+/­
0.5
In(
ppmv)
about
the
midpoint.

42
KAO
154\
11\
06\
mwc­
analysis­
report­
September
2002.
wpd
Figure
9(
b)
ormal
Probability
Plots
for
SO,
Arithmetic
Average
(
ppmv)
Compliance
Data
from
Lee
County
Solid
Waste
Resource
Recovery
Facility
Units
1
and
2
Combined
Normal
Probability
Plot:
Raw
Data
0
2.5
5
7.5
10
12.5
15
17.5
20
SO2
Arithmetic
Average
(
ppmv)
.
­

Normal
Probability
Plot:
Ln­
transformed
Data
­
1
0
1
2
3
­
3
­
2
Ln(
S02
Arithmetic
Mean
(
ppmv))

K:\
0154\
11\
06hwc­
analysis­
report­
September
2002.
wpd
43
Frequency
Histograms
fo
Solid
8
*
The
x­
axis
labels
denote
the
midpoint
of
the
bin
range,
Le.,
+/­
2­
5
%
about
the
midpoint.

sformed
I
i
6
5
4
6
f
3
;
2
U
1
0
Ln(
S02
%
Reductio
*
The
x­
axis
labels
denote
the
midpoint
of
the
bin
range,
i.
e.,
+/­
0.025
In(%)
about
the
midpoint.

44
E
\
O
154\
11\
06\
mwc­
analysis­
report­
September
2002.
wpd
Figure
1O(
b)
Normal
Probability
Plots
for
SO,
Percent
Reduction
Compliance
Data
from
Lee
County
Solid
Waste
Resource
Recovery
Facility
Units
1
and
2
Combined
Normal
Probability
Plot:
Raw
Data
2
85
90
95
100
80
SO2
%
Reduction
Normal
Probability
Plot:
Ln­
transformed
Data
2
I
­
2
0,

­
3
,
4.35
4.4
4.45
4.5
4.55
4.6
4.65
ln(
S02
%
Reduction)

K:\
O
154U
1\
06\
mwc­
analysis­
report­
September
2002.
wpd
45
.­

I
Frequency
Histograms
Lee
County
So
ta
9
.
,
I
I
I
8
7
6
$
5
0
5
4
E
3
2
1
0
NOX
(
ppmv)
Bins*
­

*
The
x­
axis
labels
denote
the
midpoint
of
the
bin
range,
Le.,
+/­
2.5
ppmv
about
the
midpoint.

9
8
7
6
3
f
5
$
4
E
3
2
1
0
*
The
x­
axis
labels
denote
the
midpoint
of
the
bin
range,
Le.,
+
I­
0.0125
ln(
ppmv)
about
the
midpoint.

46
K:\
0154\
11\
06\
mwc­
analysis­
qo~­
September
2002.
wpd
­
%,

G
­
September
2002
­
3
Figure
ll(
b)
Normal
Probability
Plots
for
NO,
(
ppmv)
Compliance
Data
from
Lee
County
Solid
Waste
Resource
Recovery
Facility
Units
1
and
2
Combined
Normal
Probability
Plot:
Raw
Data
I
I
I
NOX
(
PPm
VI
I
155
160
165
170
145
150
Normal
Probability
Plot:
Ln­
transformed
Data
K
\
O
154\
1
1\
06\
mwc­
analysis­
report­
September
2002.
wpd
1
47
i