"
Machlin,
Marc"
<
MACHLINM@
pepperlaw.
com>
Sent
by:
"
Purgason,
E.
Theresa"
<
PURGASOT@
pepperlaw.
com>
03/
07/
2005
04:
16
PM
To
Group
A­
AND­
R­
DOCKET@
EPA
cc
bcc
Subject
Petition
for
Reconsideration
of
EPA's
PM­
2.5
Non­
Attainment
Designation
Attached
for
filing
is
the
Petition
of
Oakland
County
for
Reconsideration
of
EPA's
PM­
2.5
Non­
Attainment
Designation.
Pleas
confirm
filing
of
this
Petition.
As
discussed
with
your
office,
we
were
unable
to
file
this
using
your
EDocket
system
due
to
your
system
problems.
Thank
you
for
your
assistance.

Marc
D.
Machlin
Pepper
Hamilton
LLP
600
Fourteenth
Street,
N.
W.
Washington,
DC
20005­
2004
Phone:
202.220.1439
Fax:
202.220.1665
Email:
machlinm@
pepperlaw.
com
<<#
303308
v9
­
Petition
to
EPA
by
Oakland
County,
Michigan.
doc>>
BEFORE
THE
UNITED
STATES
ENVIRONMENTAL
PROTECTION
AGENCY
)
AIR
QUALITY
DESIGNATIONS
AND
)
CLASSIFICATIONS
FOR
THE
FINE
)
PARTICLES
(
PM­
2.5)
NATIONAL
AIR
)
QUALITY
STANDARDS
)
Air
Docket
No.
OAR­
2003­
0061
)
RIN­
2060­
AM04
FINAL
RULE
)
)
40
CFR
PART
81
)
)

PETITION
OF
OAKLAND
COUNTY,
MICHIGAN
FOR
RECONSIDERATION
OF
EPA'S
PM­
2.5
NON­
ATTAINMENT
DESIGNATION
Thomas
P.
Wilczak
Kurt
A.
Kissling
PEPPER
HAMILTON
LLP
100
Renaissance
Center
 
36th
Floor
Detroit,
MI
48243­
1157
(
313)
259­
7110
wilczakt@
pepperlaw.
com
kisslingk@
pepperlaw.
com
Keith
J.
Lerminiaux
Deputy
Corporation
Counsel
OAKLAND
COUNTY
Department
of
Corporate
Counsel
1200
North
Telegraph
Road,
Department
419
Pontiac,
MI
48341­
0419
(
248)
858­
0557
lerminiauxk@
co.
Oakland.
mi.
us
John
W.
Carroll
PEPPER
HAMILTON
LLP
200
One
Keystone
Plaza
North
Front
&
Market
Streets
Harrisburg,
PA
17108­
1181
(
717)
255­
1155
carrollj@
pepperlaw.
com
Marc
D.
Machlin
PEPPER
HAMILTON
LLP
Hamilton
Square
600
Fourteenth
Street,
N.
W.
Washington,
D.
C.
20005­
2004
(
202)
220­
1200
machlinm@
pepperlaw.
com
Attorneys
for
Petitioner
Oakland
County
March
7,
2005
i
TABLE
OF
CONTENTS
PAGE
INTRODUCTIONS
AND
SUMMARY......................................................................................
2
PROCEDURAL
HISTORY........................................................................................................
4
ARGUMENT
...........................................................................................................................
13
I.
UNDER
THE
CLEAN
AIR
ACT,
AN
AREA
MAY
BE
DESIGNATED
AS
A
NON­
ATTAINMENT
AREA
ONLY
IF
THE
AREA
IS
VIOLATING
ONE
OF
EPA'S
PM­
2.5
STANDARDS
OR
IS
CONTRIBUTING
TO
VIOLATIONS
IN
A
NEARBY
AREA
.............................................................................
13
A.
The
Clean
Air
Act
Requires
EPA
To
Give
Substantial
Deference
To
State
Designations
..............................................................................................
13
B.
The
Clean
Air
Act
Requires
EPA
To
Base
All
PM­
2.5
Designations
On
Actual
Monitoring
Data
For
PM­
2.5
Levels
In
Ambient
Air..............................
14
II.
AS
MDEQ
HAS
DETERMINED,
OAKLAND
COUNTY
IS
MEETING
EPA'S
AMBIENT
AIR
STANDARDS
FOR
PM­
2.5
...................................................................
16
III.
AS
MDEQ
HAS
DETERMINED,
OAKLAND
COUNTY
MAKES
NO
"
CONTRIBUTION"
TO
NON­
ATTAINMENT
IN
ANY
NEARBY
AREAS...................
17
A.
Air
Flowing
From
Oakland
County
To
Wayne
County
Contains
PM­
2.5
At
Levels
That
Are
Lower
Than
Rural
Background
Concentrations.........................................................................................................
17
B.
In
Rejecting
MDEQ's
Recommended
Designations,
And
In
Establishing
A
Presumption
Requiring
A
Uniform
Designation
For
Metropolitan
Statistical
Areas,
EPA
Violated
The
Clean
Air
Act
And
The
Data
Quality
Act...........................................................................
19
1.
EPA's
Actions
Violated
The
Clean
Air
Act
And
The
PM­
2.5
Regulations
..............................................................................
19
2.
EPA's
Actions
Not
Only
Were
Arbitrary
And
Capricious,
But
Also
Violated
The
Data
Quality
Act...................................
21
3.
EPA's
Actions
Failed
To
Meet
Due
Process
And
APA
Requirements...............................................................................
25
C.
Even
Under
EPA's
Unlawful
Multi­
Factor
Test,
Oakland
County
Qualifies
As
An
Attainment
Area
For
PM­
2.5
.............................................
27
­
ii­
1.
Factor
One
 
Comparison
of
emissions.............................................................................
27
2.
Factor
Two
 
Comparison
of
air
quality............................................................................
28
3.
Factor
Three
 
Population
Density
and
Degree
of
Urbanization........................................
29
4.
Factor
Four
 
Traffic
and
Commuting
Patterns.................................................................
30
5.
Factor
Five
­
Extent
of
Growth
.........................................................................................
30
6.
Factor
Six
 
Meteorology..................................................................................................
31
7.
Factor
Seven
 
Geography/
topography..............................................................................
31
8.
Factor
Eight
 
Jurisdictional
boundaries
...........................................................................
31
9.
Factor
Nine
 
Level
of
Control
of
Emissions
....................................................................
32
CONCLUSION
........................................................................................................................
33
EXHIBIT
1
REPORT
OF
GRADIENT
CORPORATION................................................
TAB
1
BEFORE
THE
UNITED
STATES
ENVIRONMENTAL
PROTECTION
AGENCY
)
AIR
QUALITY
DESIGNATIONS
AND
)
CLASSIFICATIONS
FOR
THE
FINE
)
PARTICLES
(
PM­
2.5)
NATIONAL
AIR
)
QUALITY
STANDARDS
)
Air
Docket
No.
OAR­
2003­
0061
)
RIN­
2060­
AM04
FINAL
RULE
)
)
40
CFR
PART
81
)
)

PETITION
OF
OAKLAND
COUNTY,
MICHIGAN
FOR
RECONSIDERATION
OF
EPA'S
PM­
2.5
NON­
ATTAINMENT
DESIGNATION
Pursuant
to
Section
107(
d)(
6)(
A)
and
Section
307(
d)(
6)(
B)
of
the
Clean
Air
Act,

42
U.
S.
C
§
7407(
d)(
6)(
A)
and
7607(
d)(
6)(
B),
respectively,
Oakland
County,
a
Michigan
municipal
corporation,
hereby
petitions
for
reconsideration
of
the
decision
of
the
U.
S.

Environmental
Protection
Agency
("
EPA")
designating
Oakland
County
as
a
non­
attainment
area
for
fine
particulate
matter
("
PM­
2.5").
EPA's
decision
was
published
in
Air
Quality
Designations
and
Classifications
for
Fine
Particles
(
PM­
2.5)
National
Ambient
Air
Quality
Standards,
70
Fed.
Reg.
944,
980
(
January
5,
2005).
For
the
reasons
specified
below,
Oakland
County
respectfully
requests
re­
designation
as
a
PM­
2.5
attainment
area.
Re­
designation
of
Oakland
County
as
an
attainment
area
would
be
fully
consistent
with
the
recommendations
issued
by
the
State
of
Michigan,
acting
through
the
Michigan
Department
of
Environment
Quality
("
MDEQ").
INTRODUCTION
AND
SUMMARY
Oakland
County
requests
re­
designation
as
a
PM­
2.5
attainment
area
on
five
separate
and
independent
grounds.

1.
Section
107
of
the
Clean
Air
Act
requires
EPA
to
give
substantial
deference
to
the
attainment
and
non­
attainment
recommendations
issued
by
the
states.
EPA
may
override
such
recommendations
only
when
"
necessary"
based
upon
monitoring
data
for
PM­
2.5.

2.
The
quality­
assured
PM­
2.5
monitoring
data
show
that
Oakland
County
is
in
attainment.
As
of
January
5,
2005,
when
EPA
issued
its
decision,
the
agency
did
not
yet
have
the
PM­
2.5
data
for
calendar
year
2004.
MDEQ
submitted
the
new
data
on
February
22,
2005,

and
it
again
proved
that
Oakland
County
is
complying
fully
with
EPA's
PM­
2.5
standards.

MDEQ
also
established
that
only
one
county
in
the
Detroit
Metropolitan
Statistical
Area,
Wayne
County,
could
legitimately
be
classified
as
a
non­
attainment
area
for
PM­
2.5.
See
Letter
from
Steven
E.
Chester,
MDEQ
Director,
to
Bharat
Mathur,
Acting
Regional
Administrator
for
EPA
Region
5
(
February
22,
2005).

MDEQ's
submission
was
based
upon
certified
quality­
assured
monitoring
data
for
PM­
2.5.
For
calendar
year
2004,
MDEQ
reported
that
in
Oakland
County,
the
annual
average
PM­
2.5
level
was
12.76
µ
g/
m
³
.
On
a
three­
year
basis,
Oakland
County's
average
annual
PM­
2.5
level
was
14.1
µ
g/
m
³
,
which
is
well
below
the
applicable
EPA
standard.
As
explained
in
the
accompanying
report
from
the
Gradient
Corporation,
these
reported
levels
actually
overstate
the
PM­
2.5
level
in
Oakland
County
because
the
County's
monitoring
station
is
located
in
a
"

worstcase
site
near
Wayne
County,
and
near
the
confluence
of
several
large
highways.
In
any
event,

whether
measured
on
a
one
year
basis
or
a
three­
year
average,
Oakland
County
unquestionably
is
meeting
EPA's
ambient
air
quality
standards
within
its
own
boundaries.
­
3­
3.
Based
upon
the
monitoring
data,
PM­
2.5
levels
in
Oakland
County
are
not
contributing
to
non­
attainment
in
Wayne
County.
The
2004
data
confirm
that,
throughout
the
Detroit
Metropolitan
Statistical
Area,
the
PM­
2.5
levels
are
declining.
Even
in
Wayne
County
itself,
at
three
of
the
seven
monitoring
stations,
including
the
stations
closest
to
Oakland
County,

the
PM­
2.5
levels
are
now
at
or
below
EPA's
annual
standard
of
15
µ
g/
m
³
.

Moreover,
as
MDEQ
has
explained,
PM­
2.5
levels
in
Wayne
County
are
highest,

by
far,
when
the
wind
is
coming
from
the
south
and
southwest,
not
from
Oakland
County,
which
is
located
north
of
Wayne
County.
This
strongly
suggests
that
Oakland
County
is
not
contributing
in
any
way
to
PM­
2.5
levels
in
Wayne
County.
In
the
accompanying
report,

Gradient
has
now
expanded
upon
MDEQ's
analysis.
Based
upon
certified
quality­
assured
monitoring
data
for
PM­
2.5,
Gradient
has
shown
that
when
the
wind
is
blowing
southward
(
from
Oakland
County
to
Wayne
County),
the
ambient
air
from
Oakland
County
contains
PM­
2.5
levels
that
are
at
or
below
rural
background
levels.
As
a
result,
the
air
from
Oakland
County
is
actually
lowering
PM­
2.5
levels
in
Wayne
County,
thereby
improving
ambient
air
quality.

Gradient's
report
also
demonstrates
that
the
highest
levels
of
PM­
2.5
in
Oakland
County
are
associated
with
winds
moving
from
the
south
(
or
from
Wayne
County).
In
2004,
for
example,
when
the
winds
were
from
the
south,
the
average
PM­
2.5
level
in
Oakland
County
was
15.5
µ
g/
m
³
.
By
contrast,
when
the
winds
were
from
the
north,
the
average
PM­
2.5
level
was
only
8.3
µ
g/
m
³
,
which
is
below
rural
background
levels
identified
by
EPA.
Thus,
the
data
show
conclusively
that
Oakland
County
is
not
making
any
"
contribution"
to
PM­
2.5
levels
in
Wayne
County.

4.
The
analysis
used
by
EPA
to
justify
designation
of
Oakland
County
as
a
nonattainment
area
is
flawed
in
many
respects.
From
a
statutory
standpoint,
EPA
failed
to
give
the
­
4­
State's
proposed
designations
the
required
level
of
deference.
Rather
than
modifying
the
State's
proposed
designations
only
when
"
necessary,"
as
required
by
Section
107(
d)(
1)
of
the
Clean
Air
Act,
EPA
adopted
a
"
presumption"
requiring
uniform
designations
for
Metropolitan
Statistical
Areas,
including
the
Detroit
area.
Under
this
approach,
EPA
unlawfully
shifted
to
MDEQ
the
burden
of
proving
under
a
nine­
factor
test
that
individual
counties
were
entitled
to
a
different
classification.

Neither
EPA's
"
presumption"
nor
its
"
nine­
factor
test"
can
be
reconciled
with
Section
107
of
the
Clean
Air
Act.
The
Act
specifically
requires
that
attainment
decisions
be
based
upon
certified
qualified­
assured
monitoring
data
for
PM­
2.5.
The
methodology
adopted
in
the
EPA
Guidance
and
applied
in
EPA's
January
5,
2005
decision,
however,
requires
a
subjective
evaluation
of
other
factors,
including
estimated
emissions
data,
population
density,

population
growth,
and
traffic
and
commuting
patterns.
This
entire
approach
is
unlawful
and
should
be
discarded.

5.
Lastly,
in
applying
its
nine­
factor
test,
EPA
made
a
series
of
errors.
When
these
errors
are
corrected,
Oakland
County
qualifies
as
an
attainment
area
even
under
this
unlawful
and
subjective
test.

PROCEDURAL
HISTORY
In
mid­
2003,
EPA
began
to
solicit
PM­
2.5
attainment
recommendations
from
the
States
and
Indian
tribes.
Initially,
EPA
Region
5
solicited
the
State
of
Michigan's
recommendations
for
PM­
2.5
non­
attainment
areas
in
a
June
2,
2003
letter
from
then­
Regional
Administrator
Thomas
Skinner
to
Governor
Granholm
(
OAR­
2003­
0061­
0010).
The
Regional
Administrator
attached
to
his
letter
the
April
1,
2003
guidance
memo
issued
by
Jeffrey
­
5­
Holmstead,
the
Assistant
Administrator
for
Air
and
Radiation
(
OAR­
2003­
0061­
0002)
("
EPA
Guidance").

The
EPA
Guidance
outlined
EPA's
approach
to
designating
PM­
2.5
nonattainment
areas.
EPA
emphasized
that
designation
recommendations,
as
well
as
comments
on
EPA's
ultimate
determinations,
would
be
solicited
from
states
and
tribes,
but
not
from
local
governments
or
the
public.
Id.
at
Att.
2,
pp.
2­
3.
EPA
stated
that
it
would
presume
that
an
entire
Metropolitan
Statistical
Area1
was
non­
attainment
if
a
single
violation
occurred
within
the
boundaries
of
that
Metropolitan
Statistical
Area.
See
id.
at
Att.
2,
pp.
4­
5.
EPA
also
stated
its
goal
of
"
maximize[
ing]
consistency
between
designations
for
PM­
2.5
and
designations
for
the
8­

hour
ozone
standard."
Id.
at
Att.
2,
p.
6.
In
addition,
EPA
predicted,
before
receiving
a
single
state
or
tribal
recommendation,
that
only
a
"
limited
number"
of
situations
would
warrant
variation
from
the
"
presumption"
of
non­
attainment
throughout
an
entire
Metropolitan
Statistical
Area.
See
id.
at
Att.
2,
p.
6.

In
the
EPA
Guidance,
EPA
also
adopted
a
multi­
factor
approach
as
the
only
basis
for
overcoming
the
"
presumption."
This
multi­
factor
test
was
to
be
used
for
determining
when
to
exclude
an
area
or
county
in
attainment
from
a
Metropolitan
Statistical
Area
containing
a
nonattainment
area
located
elsewhere.
Id.
at
Att.
2,
p.
7.
States
and
tribes
were
given
the
burden
of
proving
to
EPA
that
an
area
should
be
carved
out
of
the
defined
Metropolitan
Statistical
Area.

Id.
Each
"
factor"
was
described
in
a
separate
bullet,
but
the
bullets
consisted
of
one
or
two
lines
1
While
the
Office
of
Management
and
Budget
("
OMB")
has
varied
its
nomenclature
for
the
different
types
of
Metropolitan
Statistical
Areas,
e.
g.,
using
CMSAs,
MSAs,
CSAs,
and
CBSAs,
the
key
concept
employed
by
OMB
and
adopted
by
EPA
is
that
a
Metropolitan
Statistical
Area
encompasses
a
mass
of
related
urban
areas
independent
of
city
or
county
boundaries.
OMB
included
Oakland
County
in
the
"
Detroit­
Ann
Arbor­
Flint"
Metropolitan
Statistical
Area,
which
also
includes
Monroe,
Wayne,
Livingston,
Macomb,
St.
Clair,
Washtenaw,
Genesee,
Lapeer,
and
Lenawee
Counties.
­
6­
of
text,
were
incomplete
sentences,
did
not
explain
how
or
why
the
factor
was
relevant;
nor
did
these
bullets
identify
the
relative
importance
of
the
factors.
Id.
Although
EPA
stated
that
"[
t]
his
guidance
is
not
binding
on
States,
Tribes,
the
public,
or
EPA,"
this
was
the
only
substantive
guidance
provided
by
EPA
for
the
purpose
of
differentiating
between
attainment
and
nonattainment
areas
within
a
Metropolitan
Statistical
Area.
2
On
February
13,
2004,
the
State
of
Michigan
submitted
its
recommendations.
3
The
State
indicated
to
EPA
Region
5
that
Wayne
and
Monroe4
Counties
should
be
designated
as
separate
non­
attainment
areas.
In
his
cover
letter
to
the
EPA
Regional
Administrator,
Steven
E.

Chester,
the
Director
of
the
Michigan
Department
of
Environmental
Quality
("
MDEQ"),
made
several
points
in
support
of
this
recommendation.
Initially,
he
explained
that
the
"
presumptive
point
of
origin
for
non­
attainment
designations 
is
arbitrary
as
it
applies
to
PM­
2.5,
which
is
clearly
evident
after
reviewing
current
PM­
2.5
monitoring
data
and
historical
monitoring
data
for
particulate
matter."
MDEQ
February
2004
Letter
at
p.
1.

In
MDEQ's
view,
the
data
from
the
monitoring
stations
in
Michigan
conclusively
established
that
PM­
2.5
non­
attainment
was
limited
to
a
discrete
area
within
Wayne
County
with
identified
boundaries.
Id.
MDEQ
also
explained
that
an
EPA
decision
to
create
a
"
widespread"

2
Although
additional
EPA
guidance
later
issued,
it
focused
on
the
OMB's
changing
nomenclature
for
dealing
with
Metropolitan
Statistical
Areas
and
did
nothing
to
materially
alter
the
EPA
Guidance.
Compare
the
EPA
Guidance
with
the
February
13,
2004
memo
by
Lydia
N.
Wegman,
Director
of
the
Air
Quality
Strategies
and
Standards
Division,
to
the
Air
Division
Directors
in
EPA
Regions
I­
X.

3
See
Steven
Chester's
February
13,
2004
letter
to
Thomas
Skinner
("
MDEQ
February
2004
Letter"),
and
attached
"
Recommended
Attainment/
Non­
Attainment
Boundaries
in
Michigan
for
the
PM­
2.5
National
Ambient
Air
Quality
Standards"
report,
by
Steve
Chester
(
February
13,
2004)
("
MDEQ
Report")
(
docketed
together
as
OAR­
2003­
0061­
0096).

4
Although
Monroe
County
was
originally
recommended
for
non­
attainment
status
based
on
the
2001­
2003
data,
the
availability
of
the
2004
data
allowed
for
consideration
of
the
2002­
2004
period,
which
indicated
that
Monroe
County
is
also
measuring
in
attainment
for
both
PM­
2.5
standards.
­
7­
non­
attainment
area
that
includes
areas
in
attainment
is
"
inappropriate
from
a
regulatory
perspective
and
misleading
from
a
public
health
perspective."
Id.
In
addition,
MDEQ
emphasized
that
several
different
legal
authorities,
independent
of
those
created
by
a
nonattainment
designation
for
PM­
2.5,
already
existed
and
provided
mechanisms
for
dealing
with
issues
related
to
PM­
2.5
in
every
part
of
Michigan.

Lastly,
MDEQ
explained
that
despite
prevailing
winds
from
the
south
and
southwest,
monitors
downwind
of
the
discrete
non­
attainment
area
still
measured
attainment,

demonstrating
that
even
with
high
PM­
2.5
contributions
from
a
different
area
(
i.
e.,
Wayne
County),
those
counties
downwind
of
Wayne
County
still
met
both
PM­
2.5
standards.
This
further
demonstrated
the
unsuitability
of
the
Metropolitan
Statistical
Area
boundary
created
by
OMB.
Id.
at
p.
2.

The
February
13,
2004
letter
from
MDEQ's
Director
was
supported
by
a
detailed
Report.
The
Report
provided
data
and
analysis
supporting
MDEQ's
recommendations.
MDEQ
opined
that
the
multi­
factor
approach
proposed
by
EPA
for
PM­
2.5
purposes
used
in
recent
ozone
recommendations
was
ill­
suited
for
PM­
2.5.
Unlike
ozone,
the
scientific
understanding
of
PM­
2.5,
including
the
body
of
information
regarding
its
formation
and
migration,
was
far
less
developed
and
detailed.
See
MDEQ
Report
at
p.
10.
For
example,
speciation
data
reflecting
the
make­
up
of
PM­
2.5
existed
for
only
a
fraction
of
monitoring
stations.
See
id.

MDEQ
also
highlighted
the
wind
trajectories
within
the
State
of
Michigan.
"
The
prevailing
wind
direction
demonstrates
that
sources
in
adjacent
counties
do
not
contribute
to
PM­

2.5
non­
attainment;
rather,
it
is
a
localized
problem.
The
other
adjacent
counties
[
in
the
SE
Michigan
Metropolitan
Statistical
Area],
while
in
attainment,
are
receiving
pollution
from
Wayne
County
rather
than
contributi[
ng]
to
non­
attainment
in
Wayne
County."
Id.
­
8­
Next,
MDEQ
explained
that
EPA's
1999
National
Emissions
Inventory
("
NEI"),

based
its
PM­
2.5
estimates
"
on
a
limited
number
of
EPA
PM­
2.5
emission
factors.
Also,
many
factors
were
of
poor
quality."
Id.
MDEQ
argued
that
PM­
2.5
monitoring
data,
not
the
more
theoretical
and
subjective
emissions
data
for
1999,
should
drive
the
designations
for
nonattainment
See
id.
at
pp.
10­
11;
see
also
p.
12.

In
MDEQ's
view,
using
an
OMB­
defined
Metropolitan
Statistical
Area
boundary
as
a
surrogate
for
monitoring
data
would
entail
an
"
unsupported
and
premature"
assumption
that
area
counties
were
contributing
to
Wayne
County's
non­
attainment.
Id.
at
10.
The
geographic
extent
of
Wayne
County's
zone
of
PM­
2.5
non­
attainment,
which
was
identified
by
MDEQ
and
based
on
the
quality­
assured
PM­
2.5
monitoring
data,
coincided
with
a
corridor
of
industrialized
neighborhoods
in
urban
Detroit
that
differed
considerably
in
character
from
the
rest
of
the
counties
in
the
Metropolitan
Statistical
Area.
No
other
part
of
the
Metropolitan
Statistical
Area
had
a
similar
"
population
density
and
degree
of
urbanization."
Id.
at
11.

Lastly,
data
from
the
air
monitoring
stations
in
the
Metropolitan
Statistical
Area
"
clearly
show
that
the
highest
PM­
2.5
days
in
the
Detroit
area
are
when
winds
are
from
the
south
and
southwest.
This
reinforces
[
MDEQ's]
conclusions
that
the
counties
to
the
north
of
Wayne
County
are
not
contributing
to 
PM­
2.5
violations."
Id.
at
13.
In
addition,
the
data
established
a
pattern
suggesting
that
"
the
sources
that
are
pushing
the
monitors
in
Wayne
County
over
the
standard
are
located
in
Wayne
County,"
and
providing
further
evidence
that
a
non­
attainment
designation
should
only
apply
to
Wayne
County.
See
id.
­
9­
Under
a
June
29,
2004
cover
letter
from
Bharat
Mathur,
the
Acting
Administrator
for
Region
5,
EPA
responded
to
MDEQ's
recommended
designations.
5
EPA
stated
that
it
disagreed
with
Michigan's
analysis,
and
instead
decided
to
designate
7
of
the
10
counties
in
the
Metropolitan
Statistical
Area
as
non­
attainment,
5
of
which
were
designated
solely
on
the
basis
of
"
contributing"
to
non­
attainment
elsewhere.
See
EPA
Response
at
p.
2.
EPA
"
reviewed
the
nine
factors
for
the
counties
within
the
Metropolitan
Statistical
Area
as
well
as"
adjacent
counties.
For
Factor
No.
1,
EPA
stated
that
the
methodology
it
adopted
for
estimating
emissions
in
the
respective
counties,
was
based
in
large
part
on
the
1999
NEI.
Id.
at
pp.
4­
5.
Although
EPA
stated
that
emissions
information
was
often
"
the
most
important
factor
in
assessing
boundaries
of
non­
attainment
areas,"
EPA's
source
data
and
assumptions
were
described
in
less
than
two
pages
and
were
often
unidentified.
Id.

For
Factor
No.
1,
EPA
used
speciation
data
for
the
Allen
Park
monitor
in
Wayne
County,
and
compared
it
to
the
M.
K.
Goddard
monitor
in
Pennsylvania,
which
was
selected
as
a
"
representative"
rural
background
site
with
which
to
calculate
urban
excess
values.
Id.
This
approach
used
monitoring
data
to
extrapolate
from
emission
data,
and
without
explanation,
EPA
selected
two
monitoring
sites
as
the
sources
of
the
speciation
data.
Id.

For
Factor
No.
5,
EPA
cited
the
population
change
between
1990
and
2000
for
evaluating
the
"
expected
growth"
in
those
counties
and
failed
to
consider
future
population
growth
projections
available
from
the
U.
S.
Census.
Id.
at
7.
EPA
did
not
explain
why
it
considered
growth
in
past
decades
rather
than
recent
growth
rates
or
projected
growth
rates.

5
The
attached
report,
titled
"
Review
of
Designations
in
Michigan
for
the
Particulate
Matter
Air
Quality
Standard"
("
EPA
Response"),
is
docketed
together
with
the
cover
letter
at
OAR
2003­
0061­
0278.
­
10­
For
Factor
No.
6,
EPA
listed
wind
directions
for
each
county,
by
percentage,
and
noted
a
relationship
between
wind
direction
and
PM­
2.5
concentrations.
EPA
did
not
provide
any
additional
explanation
for
the
effect
of
the
prevailing
meteorological
conditions
on
PM­
2.5
measurements.

On
September
1,
2004,
MDEQ
submitted
comments
on
the
EPA
Response
document.
6
MDEQ
reiterated
its
original
recommendations,
while
supplementing
its
analysis
rationale
with
a
series
of
responses
to
EPA's
multifactor
analysis.
While
EPA
had
expressed
a
preference
for
expanding
non­
attainment
areas
to
include
major
emission
sources,
including
area
sources,
MDEQ
pointed
out
that
downwind
emissions
sources
that
are
in
an
attainment
area
should
not
be
included
because
they
do
not
contribute
to
non­
attainment.
Imposing
additional
controls
on
those
sources
would
have
no
or
little
effect
on
the
conditions
in
the
non­
attainment
area.
See
MDEQ
Response
at
pp.
2­
3
&
5.

For
Factor
No.
2,
MDEQ
questioned
EPA's
suggestion
that
Oakland
County
should
be
designated
as
non­
attainment
because
its
design
value
was
14.8
µ
g/
m
³
.
In
MDEQ's
view,
this
was
mistaken
because
that
number,
while
still
below
the
relevant
threshold,

exaggerated
the
PM­
2.5
levels
in
Oakland
County
due
to
its
location.
See
id.
at
p.
4.
The
Oak
Park
monitoring
station
yielded
worst­
case
data
for
Oakland
County,
because
it
was
positioned
near
several
freeways
and
immediately
north
of
Wayne
County,
in
a
somewhat
industrialized
area
unlike
the
vast
majority
of
Oakland
County.
See
id.
Furthermore,
the
14.8
µ
g/
m
³
figure
6
MDEQ's
September
1,
2004
submission
consisted
of
Director
Chester's
cover
letter
to
Bharat
Mathur
(
OAR­
2003­
0061­
0397)
and
the
attached
"
Comments
on
the
U.
S.
Environmental
Protection
Agency's
Proposed
Designations
in
Michigan
for
the
Particulate
Matter
Air
Quality
Standards"
(
OAR­
2003­
0061­
0398)
("
MDEQ
Response").
­
11­
was
still
less
than
the
applicable
standard,
and
PM­
2.5
levels
at
that
location
(
and
in
general)
had
been
decreasing.
Id.

MDEQ
also
explained
that:
"
EPA
did
not
adequately
respond
to
MDEQ's
trajectory
analyses
showing
a
bias
towards
a
southwest
wind
when
daily
PM­
2.5
are
in
the
higher
categories
of
the
air
quality
index."
Id.
at
p.
4.
MDEQ
maintained
that
its
prior
Report
sufficiently
documented
the
localized
conditions
surrounding
Wayne
County's
non­
attainment,

as
well
as
the
fact
that
the
outlying
counties
were
not
contributing
to
that
non­
attainment.
See
id.

Next,
MDEQ
noted
that
the
costs
of
addressing
a
non­
attainment
designation
would
be
significant.
For
counties
measuring
in
attainment,
such
as
Oakland
County,
incurring
these
costs
would
be
pointless
because
any
additional
controls
would
have
little
or
no
effect
on
the
non­
attainment
area
needing
action.
See
id.
at
pp.
6­
7.

MDEQ
explained
that
the
scientific
data
providing
the
basis
for
its
argument
was
quality­
assured
monitoring
data,
while
the
weighted
emissions
score
used
by
EPA
is
"
arbitrary
and
by
design
can
lead
to
differing
interpretations
by
everyone."
Id.
at
7.
In
other
words,
EPA
was
not
relying
on
monitoring
data
meeting
the
requirements
of
40
CFR
Part
58,
and
EPA's
methodology
was
not
replicable
due
to
its
subjectivity.
In
addition,
MDEQ
pointed
out
that
population
"
is
not
an
accurate
indicator
of
high
PM­
2.5."
Id.
at
8.

MDEQ
further
supplemented
its
argument
with
a
November
30,
2004
letter
from
Director
Chester
to
EPA's
Acting
Regional
Administrator,
Bharat
Mathur.
This
letter
reiterated
many
of
MDEQ's
main
arguments
and
transmitted
preliminary
data
for
2004
indicating
that
PM­

2.5
levels
decreased
at
virtually
every
monitoring
station
previously
in
non­
attainment.
See
OAR­
2003­
0061­
0498.
­
12­
In
December
2004,
EPA
released
its
report
named
"
Technical
Support
for
State
and
Tribal
Air
Quality
Fine
Particle
(
PM­
2.5)
Designations."
See
OAR­
2003­
0061­
0606
et
seq.

For
Michigan,
this
Report
repeated
the
analysis
presentation
from
the
June
29,
2004
EPA
Response.
The
final
rule
containing
EPA's
PM­
2.5
designations
was
then
published
in
the
Federal
Register
on
January
5,
2005
(
70
Fed.
Reg.
944).
Notably,
the
final
rule
provided
states
and
tribes
with
the
opportunity
to
incorporate
2004
data
into
the
determinations
if
such
data
were
provided
to
EPA
by
February
22,
2005.

The
State
of
Michigan
did
provide
the
2004
data,
by
letter
dated
February
22,

2005
("
MDEQ
2005
Letter").
MDEQ
indicated
that
based
upon
the
2004
data,
Oakland
County
and
all
areas
other
than
Wayne
County
were
meeting
EPA's
standards
and
should
be
designated
as
attainment
areas.
The
2004
data
demonstrated
that
even
Monroe
County
was
meeting
both
PM­
2.5
standards,
and
therefore
deserved
an
attainment
designation.
7
See
2004
Supplement
at
p.
1.
The
data
further
demonstrated
a
decline
in
PM­
2.5
levels
across
the
board,
with
a
number
of
previously
non­
attainment
monitors
now
showing
attainment.
Id.
at
pp.
1­
2.
Furthermore,

using
EPA's
methodology,
only
four
monitoring
stations
in
the
State
of
Michigan
(
all
in
Wayne
County)
exhibited
a
design
value
greater
than
15
µ
g/
m
³
.
Id.
MDEQ
also
questioned
EPA's
prior
approach,
including
the
lack
of
support
for
EPA's
suggestion
that
"
winds
from
all
directions
have
impacts"
on
the
high
PM­
2.5.
Lastly,
MDEQ
highlighted
the
fact
that
the
"
majority
of
VMT
[
i.
e.,
vehicle
miles
traveled]
within
Wayne
County
come[
s]
from
Wayne
County
residents."
In
fact,
the
total
VMT
contribution
for
all
of
the
surrounding
counties
combined
was
less
than
35
percent.
Id.
at
p.
2.

7
This
change
coincided
with
PM­
2.5
monitors
in
the
Toledo
area
also
showing
attainment
based
on
the
2004
data.
­
13­
EPA
has
yet
to
respond
to
the
MDEQ's
2005
letter.

ARGUMENT
EPA
should
reconsider
and
rescind
its
January
5,
2005
decision
designating
Oakland
County
as
a
non­
attainment
area.
The
2004
monitoring
data
confirm
MDEQ's
finding
that,
within
the
Detroit
Metropolitan
Statistical
Area,
only
Wayne
County
may
legitimately
be
classified
as
a
non­
attainment
area
for
PM­
2.5.

As
should
be
obvious,
Oakland
County
did
not
raise
its
objections
to
EPA's
actions
until
now
because
there
was
no
opportunity
to
do
so.
EPA
never
solicited
public
comment
on
its
proposed
PM­
2.5
designations
nor
on
its
2003
EPA
Guidance,
and
EPA
never
gave
interested
parties
other
than
the
states
an
opportunity
to
participate
in
this
process.

Accordingly,
Oakland
County
is
presenting
its
objections
in
this
petition
for
reconsideration.

I.
UNDER
THE
CLEAN
AIR
ACT,
AN
AREA
MAY
BE
DESIGNATED
AS
A
NONATTAINMENT
AREA
ONLY
IF
THE
AREA
IS
VIOLATING
ONE
OF
EPA'S
PM­
2.5
STANDARDS
OR
IS
CONTRIBUTING
TO
VIOLATIONS
IN
A
NEARBY
AREA
A.
The
Clean
Air
Act
Requires
EPA
To
Give
Substantial
Deference
To
State
Designations
The
Clean
Air
Act
establishes
specific
standards
with
respect
to
designation
of
attainment
and
non­
attainment
areas.
An
"
area"
or
county
may
be
designated
as
a
nonattainment
area
only
if
it
does
not
meet
the
applicable
ambient
air
quality
standard
or
if
it
"
contributes"
to
violations
of
the
standard
in
a
"
nearby
area."
42
U.
S.
C.
§
7407(
d)(
1)(
A).
8
8
Under
the
Clean
Air
Act,
a
miniscule
"
contribution"
cannot
possibly
be
sufficient
to
warrant
a
non­
attainment
designation.
Otherwise,
virtually
every
area
in
the
United
States,
including
nearly
all
counties
located
south
or
southwest
of
Wayne
County,
would
be
designated
as
non­
attainment
areas.
­
14­
The
Clean
Air
Act
also
delegates
substantial
responsibility
to
the
States.
Each
State
has
"
primary
responsibility"
for
"
assuring
air
quality"
within
the
State
and
for
"
specify[
ing]

the
manner
in
which
national
primary
and
secondary
ambient
air
quality
standards
will
be
achieved
and
maintained.
.
.
."
Id.
§
7407(
a).
Likewise,
each
State
is
responsible
for
making
"
initial
designations"
of
all
areas
within
its
borders.
Such
areas
may
be
designated
as
"

nonattainment
"
attainment,"
or
"
unclassifiable."
Id.
§
7407(
d)(
1)(
A).
EPA
only
has
authority
to
"
make
such
modifications"
found
to
be
"
necessary"
to
a
State's
"
initial
designations."
Id.
§
7407(
d)(
1)(
B)(
ii).
Before
making
any
such
modifications,
however,
EPA
"
shall
notify
the
State
and
provide
such
State
with
an
opportunity
to
demonstrate
why
any
proposed
modification
is
inappropriate."
Id.
Thus,
procedurally
and
substantively,
the
Act
gives
the
States
"
primary
responsibility"
and
allows
EPA
to
override
State
designations
only
when
"
necessary."

B.
The
Clean
Air
Act
Requires
EPA
To
Base
All
PM­
2.5
Designations
On
Actual
Monitoring
Data
For
PM­
2.5
Levels
In
Ambient
Air
In
1998
and
again
in
2004,
Congress
amended
Section
107
of
the
Clean
Air
Act
and
added
provisions
relating
specifically
to
PM­
2.5
designations.
Notably,
as
detailed
below,

Congress
required
that
PM­
2.5
designations
be
based
upon
three
years
of
actual
"
monitoring
data"
for
fine
particles.
42
U.
S.
C.
§
7407
(
Historical
Note)

Congress
established
a
specific
time
frame
and
a
specific
data
source
for
PM­
2.5
designations.
Section
107(
d)(
6)(
A),
which
was
added
by
the
Consolidated
Appropriations
Act
for
2004,
provides
that:
"
Notwithstanding
any
other
provision
of
law,
not
later
than
February
15,

2004,
each
State
shall
submit
designations
referred
to
in
paragraph
(
1)
for
the
July
1997
PM­
2.5
national
ambient
air
quality
standards
for
each
area
within
the
State,
based
on
air
quality
monitoring
data
collected
in
accordance
with
any
applicable
Federal
reference
methods
for
the
relevant
areas."
42
U.
S.
C.
§
7407(
d)(
6)(
A)
(
emphasis
added).
Section
107,
as
amended,
then
­
15­
provides
that
EPA
"
shall,
consistent
with
paragraph
(
1),
promulgate
the
designations"
submitted
by
the
States.
Id.
§
7407(
d)(
6)(
B).

Congress
not
only
required
that
EPA's
designations
be
based
upon
"
monitoring
data,"
but
also
provided
the
funding
necessary
for
the
development
of
a
national
air
monitoring
network
for
fine
particles.
Id.
§
7407
at
Historical
Note
(
referring
to
Pub.
L.
105­
178,
Title
VI,

June
9,
1998,
112
Stat.
463).
Specifically,
in
1998,
in
the
Transportation
Equity
Act
For
The
21st
Century,
Congress
found
that
there
was
a
"
lack"
of
air
quality
monitoring
data
for
PM­
2.5;

Congress
therefore
sought
to
ensure
that
States
would
receive
"
full
funding"
for
installation
of
the
monitoring
stations
required
for
accurate
sampling.
In
the
Transportation
Equity
Act,

Congress
declared
that
"
such
data
could
provide
a
basis
for
designating
areas
as
attainment
or
non­
attainment.
.
.
."
(
Id.
at
Historical
Note.)
Indeed,
Congress
was
even
more
specific
and
directed
EPA
to
award
grants
to
ensure
that
the
States
collect
"
3
years
of
air
quality
monitoring
data."
(
Id.)
While
indicating
that
the
States
needed
time
to
consider
"
implementation
guidance
from
EPA
on
drawing
area
boundaries,"
Congress
declared
repeatedly
that
PM­
2.5
designations
had
to
be
based
upon
sampling
data
obtained
"
from
the
monitoring
network"
established
with
EPA
grants.
Id.

Ultimately,
Section
107
of
the
Clean
Air
Act,
as
amended,
is
very
explicit.
PM­

2.5
designations
must
be
based
upon
"
air
quality
monitoring
data
for
fine
particle
levels,"
as
measured
over
a
three­
year
period
in
accordance
with
"
Federal
reference
methods."
42
U.
S.
C.
§
7407
(
Historical
Note)
(
quoting
from
§
6101(
a)(
1),
(
a)(
2),
(
a)(
4)).
Such
data
must
be
obtained
from
the
national
air
monitoring
network
funded
by
EPA.
(
Id.
at
Historical
Note
(
quoting
from
§
6102).)
Only
data
from
the
monitoring
network
for
PM­
2.5
"
shall
be
considered"
by
the
States
­
16­
in
issuing
such
designations
and
by
EPA
in
making
any
"
necessary"
modifications
to
State
designations.
(
Id.
at
Historical
Note
(
quoting
from
§
6102(
c)(
1),
§
7407(
d)(
1)(
B)(
ii).)

II.
AS
MDEQ
HAS
DETERMINED,
OAKLAND
COUNTY
IS
MEETING
EPA'S
AMBIENT
AIR
STANDARDS
FOR
PM­
2.5
As
MDEQ
has
determined,
and
as
EPA
appears
to
have
conceded,
Oakland
County
is
meeting
EPA's
ambient
air
standards
for
PM­
2.5.
As
explained
in
Gradient's
report,

the
monitoring
station
in
Oakland
County
is
located
in
Oak
Park,
which
is
a
"
worst­
case"

location
in
this
County.
This
monitoring
station
is
located
in
the
southeast
corner
of
the
County,

only
a
few
miles
from
the
border
with
Wayne
County
(
which
contains
the
most
industrialized
areas
in
the
region).
This
station
also
is
located
in
the
most
urbanized
portion
of
Oakland
County.

In
addition,
the
Oak
Park
monitoring
station
is
near
the
confluence
of
several
major
highways.
These
include
Michigan
Highway
102
(
Eight­
Mile
Road),
Michigan
Highway
10
(
The
Lodge
Expressway),
Michigan
Highway
39
(
Southfield
Freeway),
Interstate
75
("
I­
75")

and
Interstate
Highway
696
("
I­
696").
See
Gradient
Report
at
1­
3.

Despite
the
location
of
this
monitoring
station,
the
data
show
conclusively
that
Oakland
County
is
meeting
the
applicable
ambient
air
quality
standards.
PM­
2.5
levels
in
the
County
are
substantially
below
EPA's
65
microgram
per
cubic
meter
24­
hour
average
concentration.
Furthermore,
the
PM­
2.5
levels
in
Oakland
County
are
well
below
the
15.0
microgram
per
cubic
meter
annual
arithmetic
mean
concentration.
See
generally
Gradient
Report
and
Letter
From
Steven
E.
Chester,
MDEQ
Director,
To
Bharat
Mathur,
Acting
Regional
Administrator
at
Attachment
2
(
February
22,
2005).
Even
before
the
2004
data
had
been
obtained,
the
air
quality
within
Oakland
County's
borders
was
meeting
this
EPA
standard.
As
of
2003,
the
one
year
average
in
the
County
was
14.58
µ
g/
m
³
,
and
the
three­
year
average
was
14.8.
­
17­
Id.
at
Attachment
2.
With
the
2004
data
included,
these
figures
continue
to
decline.
As
explained
above,
the
2004
average
in
Oakland
County
was
12.76
µ
g/
m
³
,
producing
a
three­
year
average
of
14.1.
Id.
Accordingly,
the
County
is
now
meeting
both
of
EPA's
PM­
2.5
standards
by
a
substantial
margin.

III.
AS
MDEQ
HAS
DETERMINED,
OAKLAND
COUNTY
MAKES
NO
"
CONTRIBUTION"
TO
NON­
ATTAINMENT
IN
ANY
NEARBY
AREAS
A.
Air
Flowing
From
Oakland
County
To
Wayne
County
Contains
PM­
2.5
At
Levels
That
Are
Lower
Than
Rural
Background
Concentrations
MDEQ
has
correctly
determined
that
Oakland
County
is
not
making
any
"
contribution"
to
non­
attainment
in
Wayne
County.
As
explained
in
the
Gradient
report,
within
Oakland
County,
the
highest
levels
of
PM­
2.5
are
measured
when
the
winds
are
from
the
south.

In
calendar
year
2004,
for
example,
when
the
wind
direction
was
from
the
south,
the
average
PM­
2.5
level
in
Oakland
County
was
15.5
µ
g/
m
³
.
By
contrast,
when
the
wind
direction
is
from
the
north
(
toward
Wayne
County),
the
average
2004
concentration
in
Oakland
County
was
only
8.3
µ
g/
m
³
.

Furthermore,
when
the
wind
is
blowing
to
the
south
(
toward
Wayne
County),
the
PM­
2.5
levels
at
Oak
Park
are
consistently
at
or
below
the
rural
background
levels
identified
by
EPA.
At
the
M.
K.
Goddard
Station
in
rural
Pennsylvania,
EPA
reported
that
during
the
April
2002
 
March
2003
time
period,
the
PM­
2.5
level
averaged
11.9
µ
g/
m
³
.
This
actually
exceeds
the
levels
measured
in
Oakland
County
when
the
wind
is
blowing
to
the
south
(
toward
Wayne
County).
Gradient
has
calculated
these
annual
PM­
2.5
concentrations
in
Oakland
County
as
9.4
µ
g/
m
³
(
2000),
9.3
µ
g/
m
³
(
2001),
8.2
µ
g/
m
³
(
2002),
9.7
µ
g/
m
³
(
2003),
and
8.3
µ
g/
m
³
(
2004).

These
numbers
show
conclusively
that
air
from
Oakland
County
is
not
causing
any
harm
whatsoever
in
Wayne
County.
­
18­
Moreover,
even
in
Wayne
County,
the
air
monitoring
stations
on
the
northern
end
of
the
County
(
closest
to
Oakland
County)
are
measuring
PM­
2.5
levels
at
or
below
the
federal
standard.
In
Wayne
County,
the
three­
year
average
for
the
Livonia
Station
is
13.7
µ
g/
m
³
,
and
the
three­
year
average
for
the
East
Seven­
Mile
Station
is
14.5
µ
g/
m
³
.
These
two
monitoring
stations
are
located
between
Oakland
County
and
the
industrial
corridor
of
Wayne
County
where
exceedances
have
occurred.
As
MDEQ
has
stated,
PM­
2.5
exceedances
exist
only
in
the
"
highly
industrialized
area
of
Wayne
County."
See
Letter
from
Steven
E.
Chester,
MDEQ
Director,
to
Acting
Regional
Administrator
Bharat
Mathur
at
2
(
February
22,
2005).

If
anything,
as
Gradient's
report
explains,
the
impacts
run
in
the
opposite
direction;
Wayne
County
and
other
areas
to
the
south
are
generating
PM­
2.5
that
is
reducing
air
quality
in
Oakland
County.
Despite
that
adverse
impact,
however,
the
monitoring
data
show
that
Oakland
County
is
meeting
the
federal
standards,
both
for
the
three­
year
annual
average
and
for
the
24­
hour
period.

In
addition,
the
2004
monitoring
data
further
support
the
State
of
Michigan's
argument
that
PM­
2.5
levels
are
declining.
Oakland
County's
PM­
2.5
levels
fell
to
historic
lows
in
2004.
In
Oakland
County,
the
annual
average
levels
have
declined
from
15.00
(
2002),
to
14.58
(
2003),
to
12.76
(
2004).
This
is
consistent
with
the
national
and
"
Industrial
Midwest"

trends
identified
in
a
December
2004
report
issued
by
EPA.
See
EPA,
The
Particle
Pollution
Report
(
December
2004).
Indeed,
EPA
has
reported
that
since
1999,
PM­
2.5
levels
have
decreased
by
nine
percent
in
the
"
Industrial
Midwest,"
a
region
that
includes
Michigan.
Id.
at
14.
As
EPA
has
stated:
"
National
programs
that
affect
regional
emissions
 
including
EPA's
Acid
Rain
Program
 
have
contributed
to
lower
sulfate
concentrations
and
consequently,
to
lower
PM­
2.5
concentrations,
particularly
in
the
Industrial
Midwest
and
Southeast."
Id.
In
­
19­
making
attainment
and
non­
attainment
designations,
it
would
be
irrational
for
EPA
to
disregard
this
downward
trend
in
PM­
2.5
levels.
After
all,
these
designations
will
be
used
in
the
future
to
decide
whether
additional
emissions
controls
are
necessary.

B.
In
Rejecting
MDEQ's
Recommended
Designations,
And
In
Establishing
A
Presumption
Requiring
A
Uniform
Designation
For
Metropolitan
Statistical
Areas,
EPA
Violated
The
Clean
Air
Act
And
The
Data
Quality
Act
1.
EPA's
Actions
Violated
The
Clean
Air
Act
And
The
PM­
2.5
Regulations
EPA's
PM­
2.5
designations
in
the
State
of
Michigan
have
violated
two
statutory
requirements.
First,
EPA
failed
to
give
the
State
of
Michigan
"
primary
responsibility"
for
the
PM­
2.5
designations
within
the
State.
Rather
than
adopting
the
State's
initial
designations
or
making
only
those
modifications
that
are
truly
"
necessary,"
EPA
has
imposed
a
presumption
that
treats
the
entire
Metropolitan
Statistical
Area
as
a
non­
attainment
area.
By
imposing
this
"
presumption"
on
a
national
basis,
and
by
requiring
use
of
the
Metropolitan
Statistical
Area
unless
a
State
is
able
to
justify
a
deviation
under
EPA's
multi­
factor
test,
EPA
has
effectively
denied
to
the
State
of
Michigan
and
to
all
States
the
primacy
intended
by
Congress.
Within
the
State
of
Michigan,
this
has
resulted
in
non­
attainment
designations
for
a
multitude
of
counties
in
the
Detroit
Metropolitan
Statistical
Area,
despite
the
fact
that
only
one
of
the
seven
counties
has
PM­
2.5
levels
above
the
15
microgram
per
cubic
meter
annual
standard
for
PM­
2.5.

Second,
EPA's
PM­
2.5
designations
have
not
been
based
upon
the
monitoring
data
for
PM­
2.5,
as
required
by
the
Clean
Air
Act.
Instead,
EPA
applied
the
EPA
Guidance,

which
establishes
the
presumption
in
favor
of
a
single
designation
for
an
entire
Metropolitan
Statistical
Area.
The
EPA
Guidance
then
requires
consideration
of
a
multitude
of
factors,

including
estimated
emissions
data,
population
density,
degree
of
urbanization,
traffic
and
commuting
patterns,
expected
growth
rates,
weather,
jurisdictional
boundaries,
and
geographic
­
20­
or
topographic
features.
See
EPA
Guidance.
Under
the
first
factor
(
emissions
data),
EPA
has
evaluated
the
estimated
emissions
of
PM­
2.5
and
for
certain
precursors
to
PM­
2.5,
such
as
nitrous
oxides
(
NOx)
and
sulfur
oxides
(
SOx).
Yet
the
emissions
data
for
these
precursor
compounds
are
based
partly
on
estimates,
as
are
most
of
the
data
for
PM­
2.5
emissions.

Ultimately,
instead
of
focusing
on
reliable,
measured
emission
concentrations
of
PM­
2.5
from
monitoring
stations,
EPA
has
focused
on
a
multitude
of
surrogates,
each
of
which
has
some
indirect
and
possibly
unknown
relationship
to
the
actual
level
of
fine
particles
in
the
air.
EPA
has
then
compounded
the
inherent
inaccuracies
of
the
emissions
data
by
using
speciated
monitoring
data
from
non­
certified
air
monitoring
devices
to
estimate
the
proportion
of
emissions
which
might
be
contributing
to
non­
attainment.
Thus,
the
first
factor
(
emissions
data)

is
actually
a
combination
of
emission
estimates
filtered
through
comparison
with
monitoring
data
of
questionable
reliability.

In
the
end,
neither
the
"
presumption"
in
favor
of
Metropolitan
Statistical
Areas
nor
the
"
multi­
factor"
approach
devised
by
EPA
can
be
reconciled
with
Section
107
of
the
Clean
Air
Act,
which
focuses
on
the
measurement
and
evaluation
of
actual
PM­
2.5
levels.
EPA's
"
multi­
factor"
approach
is
designed
to
give
the
agency
broad
discretion
to
evaluate
and
weigh
on
a
highly
subjective
basis
surrogates
for
PM­
2.5.
This
approach
deviates
impermissibly
from
the
monitoring
data­
driven
approach
embodied
in
the
statute.

To
some
extent,
EPA
has
attempted
to
justify
its
Metropolitan
Statistical
Area
presumption
by
invoking
its
past
practice
in
making
attainment
and
non­
attainment
designations
for
ozone.
See
EPG
Guidance.
This
completely
disregards
the
fact
that
ozone
and
PM­
2.5
designations
are
governed
by
very
different
statutory
provisions.
While
the
PM­
2.5
provisions
require
the
agency
to
rely
upon
"
air
quality
monitoring
data"
for
fine
particles,
the
ozone
­
21­
provisions
specifically
authorize
designations
based
upon
"
a
metropolitan
statistical
area
or
consolidated
metropolitan
statistical
area."
Compare
42
U.
S.
C.
§
7407(
d)(
6)(
A)
and
Historical
Note
(
governing
PM­
2.5
designations)
to
42
U.
S.
C.
§
7407(
d)(
4)(
A)
(
governing
ozone
and
carbon
monoxide).

Furthermore,
EPA's
non­
attainment
designations
in
Michigan
are
inconsistent
with
EPA's
own
regulations
establishing
air
quality
standards
for
PM­
2.5.
EPA's
regulations
do
not
authorize
the
subjective
application
of
a
multi­
factor
test.
The
regulations
require
the
use
of
designated
air
monitors
and
provide
for
use
of
a
specified
reference
method.
See
40
C.
F.
R.

§
50.7,
Appendix
N
to
Part
50,
and
40
C.
F.
R.
Part
58.
As
pertinent
here,
the
regulations
then
provide
that:
"
The
national
primary
and
secondary
ambient
air
quality
standards
for
particulate
matter
are:
(
1)
15.0
micrograms
per
cubic
meter
(
µ
g/
m3)
annual
arithmetic
mean
concentration,

and
65
µ
g/
m3
24­
hour
average
concentration
measured
in
the
ambient
air
as
PM2.5
.
.
.
."
40
C.
F.
R.
§
50.7(
a)(
1).
Essentially,
the
regulations
now
in
place
establish
air
quality
standards
based
upon
measured
concentrations
of
PM­
2.5,
not
based
upon
a
subjective
review
of
estimated
emissions
data
or
other
factors.

2.
EPA's
Actions
Not
Only
Were
Arbitrary
And
Capricious,
But
Also
Violated
The
Data
Quality
Act
EPA's
approach
has
not
only
been
inconsistent
with
the
Clean
Air
Act,
but
also
has
been
arbitrary
and
capricious.
To
start
with,
the
use
of
an
Metropolitan
Statistical
Area
as
a
presumptive
non­
attainment
area
corrupts
the
purpose
for
which
Metropolitan
Statistical
Areas
are
established.
As
the
Office
of
Management
and
Budget
("
OMB")
cautioned
when
promulgating
the
standards
for
establishing
Metropolitan
Statistical
Areas,
they
are
statistical
areas
only
and
should
not
form
the
basis
for
policy
decisions,
such
as
establishment
of
non­
­
22­
attainment
areas.
9
There
is
no
evidence
or
data
supporting
a
"
presumption"
that
Oakland
County
is
contributing
to
non­
attainment
in
nearby
Wayne
County
based
solely
on
inclusion
in
a
statistically
based
urban
area.
In
order
to
bridge
this
technical
chasm,
EPA
published
its
guidance
document
setting
forth
nine
criteria
under
which
a
state
could
seek
to
exclude
from
a
Metropolitan
Statistical
Area­
based
non­
attainment
area
certain
geographic
regions
which
met
the
exclusionary
criteria.
That
guidance,
however,
inadequately
defines
the
criteria
and
provides
no
system
for
weighting
of
the
individual
criteria.
Additionally,
as
applied
by
EPA
in
its
December
2004
Comment
and
Response
Document,
the
criteria
are
unevenly
applied
by
EPA
in
making
decisions
about
which
areas
should
be
included
or
excluded
from
non­
attainment
areas.

Since
EPA
has
chosen
to
make
decisions
on
area
inclusion/
exclusion
on
the
basis
of
the
nine
factors,
each
of
which
has
some
data
component,
it
is
critical
that
the
data
used
to
make
these
critical
decisions
be
carefully
reviewed,
consistent
with
the
agency's
obligations
under
the
Data
Quality
Objectives
Act
(
DQOA),
44
U.
S.
C
§
3516
(
Note).
10
A
cursory
9
"
The
Metropolitan
Area
concept
has
been
successful
as
a
statistical
representation
of
the
social
and
economic
linkages
between
urban
cores
and
outlying,
integrated
areas.
This
success
is
evident
in
the
continued
use
and
application
of
Metropolitan
Area
definitions
across
broad
areas
of
data
collection,
presentation,
and
analysis.
This
success
also
is
evident
in
the
use
of
statistics
for
Metropolitan
Areas
to
inform
the
debate
and
development
of
public
policies
and
in
the
use
of
Metropolitan
Area
definitions
to
implement
and
administer
a
variety
of
nonstatistical
Federal
programs.
These
last
uses,
however,
raise
concerns
about
the
distinction
between
appropriate
uses
 
collecting,
tabulating,
and
publishing
statistics
as
well
as
informing
policy
 
and
inappropriate
uses
 
implementing
nonstatistical
programs
and
determining
program
eligibility.
OMB
establishes
and
maintains
these
areas
solely
for
statistical
purposes."
65
Fed.
Reg.
82,228,
December
22,
2000.

10
On
December
21,
2000,
Congress
passed
PL
106­
554.
Section
515
Title
V
of
that
law,
114
Stat.
2763,
2763A­
453,
has
been
named
the
Data
Quality
Objectives
Act
("
DQOA").
The
DQOA
required
the
OMB
to
issue
guidelines
to
ensure
that
information
disseminated
by
federal
agencies
is
supported
by
valid
data.
In
compliance
with
the
DQOA,
OMB
issued
guidelines
effective
January
3,
2002.
67
Fed.
Reg.
8452.

Each
federal
agency
responsible
for
disseminating
influential
scientific,
financial
or
statistical
information
shall
include
a
high
degree
of
"
transparency"
about
the
data
and
methods
to
facilitate
the
reproducibility
of
such
information
by
qualified
third
parties.
67
Fed.
Reg.
8452
(
January
3,
2002).
"
Reproducibility"
of
data
is
an
indication
of
transparency,
according
to
OMB's
guidelines.
Id.
at
8460.
(
continued...)
­
23­
examination
of
the
data
employed
by
EPA
in
evaluating
the
request
by
MDEQ
to
exclude
Oakland
County
reveals
the
dearth
of
support
for
the
data
relied
upon
in
EPA's
December
Report.
For
example,
in
applying
the
first
factor,
which
calls
for
a
comparison
of
emission
data,

the
Report
ignores
available
emission
inventory
data
in
favor
of
emissions
estimates
derived
from
air
quality
monitoring
data.
Then,
artificially
starting
with
the
assumption
that
all
areas
included
in
an
Metropolitan
Statistical
Area
contribute
to
the
overall
air
emissions
for
the
area,

the
agency
merely
determines
what
percent
of
the
total
emissions
for
the
area
are
derived
from
the
various
counties
which
comprise
the
Metropolitan
Statistical
Area.
After
putting
the
rabbit
in
the
hat,
EPA
then
concludes
that
the
counties
comprising
the
Metropolitan
Statistical
Area
contribute
to
non­
attainment
in
the
county
monitoring
non­
attainment.
Rather
than
looking
at
actual
ambient
air
levels
for
PM­
2.5,
as
is
required
by
the
Clean
Air
Act,
however,
EPA
uses
emissions
data
for
other
criteria
pollutants
and
ascribes
an
urban
excess
matrix
to
derive
a
weighted
PM­
2.5
emissions
factor
for
each
county.
This
hypothetical
calculation
methodology
________________________

(
continued...)

With
regard
to
analytical
results,
OMB
guidelines
state
that
guidelines
"
shall
generally
require
sufficient
transparency
about
data
and
methods
that
an
independent
reanalysis
could
be
undertaken
by
a
qualified
member
of
the
public."
Id.

EPA's
data
quality
standards
were
adopted
in
October
2002
under
the
title,
"
Guidelines
For
Ensuring
and
Maximizing
the
Quality,
Objectivity,
Utility
and
Integrity
of
Information
Disseminated
by
the
Environmental
Protection
Agency,"
EPA/
260R­
02­
008
(
the
"
Guidelines").
EPA
later
directed
the
Science
Policy
Council
to
develop
assessment
factors
as
a
"
complement"
to
the
Guidelines.
The
Council's
factors
are
published
in
EPA
100/
B­
03/
001
(
June
2003)("
Assessment
Factors").

The
Assessment
Factors
are:
Soundness,
Applicability
and
Utility,
Clarity
and
Completeness,
Uncertainty
and
Variability,
Evaluation
and
Review.
All
data
reviewed
must
meet
the
highest
standards
possible
under
each
factor.
EPA
must
also
review
the
scientific
and
technical
basis
for
the
designations
because
this
process
of
review
and
approval
involves
the
"
dissemination
of
information"
to
the
public
that
falls
under
the
scrutiny
of
EPA's
Data
Quality
Guidelines.

Many
of
the
methodologies
employed
by
EPA
in
the
designation
of
Oakland
County
are
based
on
emission
assumptions
rather
than
real
data.
The
only
qualified
data
is
the
monitoring
data,
which
conclusively
demonstrate
that
Oakland
County
is
an
attainment
area
and
is
not
contributing
to
nonattainment
in
a
nearby
area.
­
24­
naturally
shows
that
each
county
has
emissions
which
"
contribute"
to
the
total
Metropolitan
Statistical
Area
emissions
total,
since
the
formula
demands
that
each
county
be
ascribed
a
percentage
of
the
whole.
What
the
methodology
fails
to
do,
however,
is
to
compare
the
"
urban"

excess
with
actual
background
emissions
from
non­
urban
settings
during
actual
monitored
nonattainment
events.
Accordingly,
the
data
are
not
replicable
and
fail
to
satisfy
the
DQOA
criteria.

The
DQOA
was
enacted
by
Congress
specifically
to
prevent
such
specious
analyses.

The
data
quality
review
is
especially
important
in
the
process
of
promulgating
a
federal
non­
attainment
designation
over
the
objection
of
the
Governor,
as
in
this
case.
No
other
agency
action
demands
higher
scrutiny
than
adopting
a
non­
attainment
designation,
which
can
have
significant
negative
economic
impact
on
a
County,
discouraging
the
siting
and
expansion
of
business
and
industry,
and
unfairly
affecting
quality
of
life
issues
by
suggesting
that
the
air
quality
of
the
County
fails
to
meet
minimum
health­
based
standards.
11
Oakland
County
adopts
many
of
the
comments
filed
by
MDEQ
in
its
letters
of
February
13,
2004,
September
1,
2004,
November
30,
2004,
and
February
22,
2005
with
respect
to
designating
Oakland
County
as
attainment
for
PM­
2.5.
In
addition
to
the
comments,
data,
and
analysis
provided
by
MDEQ,
Oakland
County
presents
the
attached
report
from
Gradient
Corporation
evaluating
the
potential
contribution
of
Oakland
County
source
area
emissions
to
the
measured
non­
attainment
in
Wayne
County.
Oakland
County
also
takes
exception
to
the
utilization
of
the
nine­
factor
analysis
set
forth
initially
in
the
EPA
Guidance
from
Assistant
Administrator
Jeffrey
Holmstead
to
Regional
Administrators
dated
April
1,
2003.
Tellingly,

11
In
adopting
a
presumption
that
all
counties
within
an
Metropolitan
Statistical
Area
should
be
considered
non­
attainment
if
even
one
monitor
demonstrates
non­
attainment,
and
in
applying
the
ninefactor
analysis,
EPA
has
offered
at
best
only
superficial
explanations.
The
Data
Quality
Objectives
Act
(
DQOA)
and
the
EPA
data
quality
Guidelines
demand
more
substantive
analyses.
­
25­
before
introducing
those
nine
factors
in
the
EPA
Guidance,
the
Assistant
Administrator
made
this
statement
about
the
factors:
"
These
factors
resemble
the
factors
identified
in
previous
EPA
guidance
on
8­
hour
ozone
non­
attainment
boundaries,
though
EPA
will
make
its
decisions
based
on
the
distribution
of
sources
contributing
to
PM­
2.5
concentrations."
(
emphasis
supplied).

Despite
compelling
evidence
that
Oakland
County
is
not
contributing
to
monitored
PM­
2.5
noncompliance
in
the
area
of
Wayne
County
in
which
non­
attainment
has
been
monitored
(
Dearborn
16.5;
Allen
Park
15.1;
SWHS
16.5;
Wyandotte
15.4),
and
despite
the
fact
that
the
monitors
in
Wayne
County
closest
to
Oakland
County
are
measuring
attainment
(
Livonia
13.7;
East
7
Mile
14.5;
Linwood
15.0),
EPA
classified
Oakland
County
as
non­
attainment
and
ignored
this
geographic
pattern.

3.
EPA's
Actions
Failed
To
Meet
Due
Process
And
APA
Requirements
The
EPA
Guidance
has
been
used
by
the
agency
as
a
legislative
rule
with
the
force
and
effect
of
law.
As
explained
below,
however,
this
rule
was
issued
by
EPA
unlawfully,

and
without
soliciting
public
comment.

While
EPA
asserts
that
it's
the
EPA
Guidance
is
a
non­
binding
policy
statement,

EPA
has
used
this
memorandum
as
a
legislative
rule.
The
April
2003
"
guidance"
created
an
entirely
new
methodology
for
determining
whether
an
area
is
in
attainment
for
PM­
2.5.
This
"
guidance"
was
sent
to
all
Regional
Administrators
and
was
obviously
intended
to
be
binding
on
all
EPA
personnel
and
on
the
States
and
other
interested
parties.
This
was
confirmed
in
the
February
13,
2004
memorandum
supplementing
this
guidance
and
in
EPA's
January
5,
2005
decision
published
in
the
Federal
Register.
Nowhere
in
the
February
2004
supplement
or
in
the
January
5,
2005
decision
did
EPA
indicate
that
States
or
EPA
regional
offices
were
free
to
disregard
the
EPA
Guidance
or
to
deviate
from
the
agency's
"
nine­
factor"
test.
­
26­
In
distinguishing
between
legislative
rules
and
non­
binding
guidance
or
nonbinding
statements
of
policy,
the
courts
have
focused
on
whether
the
agency
action
"(
1)

impose[
s]
any
rights
and
obligations'
or
(
2)
`
genuinely
leaves
the
agency
and
its
decision
makers
free
to
exercise
discretion.'"
General
Electric
Co.
v
EPA,
290
F.
3d
377,
382
(
D.
C.
Cir.
2002)

(
citations
omitted);
Appalachian
Power
Co.
v
EPA,
208
F.
3d
1015
(
D.
C.
Cir.
2000)
In
this
proceeding,
after
issuance
of
the
2003
guidance,
the
agency
did
not
act
as
if
it
were
"
free"
to
exercise
its
discretion.
Indeed,
in
the
January
5,
2005
decision
published
in
the
Federal
Register,

EPA
treated
the
"
guidance"
document
as
having
the
force
and
effect
of
law.

Under
the
Clean
Air
Act
and/
or
the
Administrative
Procedures
Act,
EPA
generally
must
go
through
notice
and
comment
rulemaking
prior
to
issuing
legislative
rules.
See
generally
42
U.
S.
C.
§
7607(
d);
5
U.
S.
C.
§
553.
Since
the
agency
failed
to
do
this,
the
EPA
Guidance
should
be
rescinded
and
declared
null
and
void.

In
addition,
EPA
issued
its
non­
attainment
designations
improperly
without
giving
interested
parties,
such
as
Oakland
County,
an
opportunity
to
be
heard.
Even
if
the
designation
process
were
exempt
from
the
statutory
provisions
on
notice
and
comment
rulemaking,
EPA
would
still
be
required
to
ensure
that
its
procedures
meet
due
process
requirements.
The
essential
requirements
of
due
process
are
notice
and
an
opportunity
to
be
heard.
See,
e.
g.,
General
Electric
Co.
v.
EPA,
53
F.
3d
1324,
1329
(
D.
C.
Cir.
1995);
Amoco
Products
Co.
v
Fry,
118
F.
3d
812,
819
(
D.
C.
Cir.
1997)
("[
n]
otice
and
a
meaningful
opportunity
to
challenge
the
agency's
decision
are
the
essential
elements
of
due
process").

In
this
proceeding,
EPA
solicited
comment
from
the
State
of
Michigan,
as
required
by
statute.
Yet
EPA
failed
to
give
other
interested
parties,
such
as
Oakland
County,
any
­
27­
opportunity
to
submit
comments.
The
agency
therefore
failed
to
meet
basic
due
process
requirements.

C.
Even
Under
EPA's
Unlawful
Multi­
Factor
Test,
Oakland
County
Qualifies
As
An
Attainment
Area
For
PM­
2.5
Notwithstanding
the
irrationality
of
the
"
nine­
factor"
analysis,
the
County
has
attempted
to
re­
examine
the
key
factors
and
the
data
used
by
EPA.
This
re­
examination
confirms
that
the
agency
erred
in
designating
Oakland
County
as
a
non­
attainment
area.

1.
Factor
One
 
Comparison
of
Emissions
The
Gradient
report
discusses
EPA's
"
factor
one"
analysis
in
some
detail.

Gradient
shows
that
when
a
more
appropriate
rural
background
site
in
Illinois
is
used,
Oakland
County's
"
composite
emissions
score"
drops
from
13.6
to
12.6.
(
See
Gradient
Report
at
pp.
11­

12.)
12
Gradient
also
shows
that
EPA's
factor
one
analysis
is
biased
against
counties
that
are
large
in
size.
When
EPA's
composite
score
for
Oakland
County
is
normalized
on
a
square
mile
basis
to
remove
this
bias,
the
County's
score
falls
from
13.6
to
11.5.
(
Id.)

In
addition,
EPA's
selection
of
a
rural
background
location
in
Pennsylvania
appears
to
have
inflated
the
"
urban
increment"
for
the
Detroit
area.
Even
without
the
2004
data,

12
EPA
chose
to
use
speciation
data
from
two
monitors
that
created
an
unbalanced
and
unrealistic
data
set
for
consideration.
EPA
first
chose
speciation
data
from
the
Allen
Park
monitor
in
the
heavily
industrialized
Detroit
non­
attainment
corridor.
Then,
EPA
chose
a
rural
monitor
in
a
non­
attainment
county
in
western
Pennsylvania,
downwind
of
Ohio's
power
plants
as
a
background
monitor
for
comparison
to
the
urban
data
from
the
Allen
Park
speciation
monitor.
Not
surprisingly,
the
Pennsylvania
monitor
showed
a
higher
percentage
of
sulfate
as
compared
to
nitrate.
The
ratio
at
the
Pennsylvania
site
(
50%
vs.
16%)
reflects
emissions
from
upwind
coal­
fired
power
plants
and
is
not
believed
to
be
indicative
of
the
mix
of
PM­
2.5
emissions
monitored
as
true
background
for
Wayne
County.
The
use
of
the
Illinois
monitor
used
for
the
Chicago
comparison,
at
which
the
sulfate
to
nitrate
ratio
was
43%
vs.
30%,
is
a
better
measure
of
background
air
quality
from
which
to
calculate
the
so­
called
"
urban
excess"
for
the
Detroit
area.
Because
the
ratio
of
"
emissions"
for
the
Detroit
Metropolitan
Statistical
Area
was
37%
vs.
26%
for
sulfate
vs.
nitrate,
the
Illinois
rural
monitor
gives
a
more
realistic
value
for
background.
­
28­
which
show
a
lower
urban
increment,
using
the
Illinois
monitor
as
the
background
drops
the
"
urban
increment"
for
the
Detroit
Metropolitan
Statistical
Area
from
4.3
µ
g/
m3
to
3.9
µ
g/
m3;

these
numbers
were
generated
at
a
time
when
the
Detroit
monitor
was
reporting
16.1
µ
g/
m3.

Since
the
date
of
EPA's
analysis,
the
average
monitored
value
at
the
monitor
location
used
to
represent
the
Detroit
Metropolitan
Statistical
Area
has
dropped
to
15.1
µ
g/
m3,
thus
potentially
reducing
the
"
urban
increment"
to
2.9
µ
g/
m3.

More
importantly,
as
Gradient
explains,
EPA's
weighted
emissions
score
"
is
an
uncertain
and
imperfect
metric"
for
making
PM­
2.5
attainment
decisions.
Among
other
things,

this
"
score"
wrongly
assumes
that
there
is
a
direct
relationship
between
estimated
SO2
and
NOx
emission
rates
and
actual
levels
of
sulfate
and
nitrate
particles
in
the
air.
(
Gradient
Report
at
12­

13.)
Furthermore,
EPA's
"
emissions
score"
relies
upon
speciation
data
from
a
single
monitoring
station
in
Wayne
County.
These
data
are
unlikely
to
be
representative
of
conditions
throughout
the
Detroit
Metropolitan
Statistical
Area.
(
Id.
at
13.)

2.
Factor
Two
 
Comparison
of
Air
Quality
As
explained
in
the
various
reports
filed
by
MDEQ
and
the
appended
expert
report
of
Gradient,
the
air
quality
in
Oakland
County
meets
EPA's
annual
attainment
standard
by
a
large
margin
on
days
when
air
contaminants
from
neighboring
Wayne
County
are
not
affecting
the
Oakland
County
monitor,
which
is
located
near
the
boundary
of
the
two
counties.
The
average
concentration
in
Oakland
County
is
less
than
10
µ
g/
m3
for
every
year
when
winds
are
from
the
north.
By
contrast,
virtually
all
of
the
Oak
Park
monitor's
PM­
2.5
measurements
over
15
µ
g/
m3
over
the
past
five
years
occurred
when
winds
came
from
the
south,
which
indicates
transport
from
Wayne
County
and
its
industrialized
non­
attainment
area.
Despite
this
occasional
contribution
from
Wayne
County,
the
average
long­
term
concentration
at
the
Oakland
County
­
29­
monitor
is
only
14.1
µ
g/
m3.
The
values
measured
at
the
Oakland
County
monitoring
station
for
days
when
the
wind
is
not
carrying
contaminants
into
Oakland
County
from
Wayne
County
are
far
less
than
the
measured
values
in
other
attainment
counties
in
Michigan
which
have
monitoring
stations,
such
as
Allegan,
Bay,
Berrien,
Genesee,
Ingham,
Kalamazoo,
Kent,

Muskegon,
Ottawa,
and
Saginaw
Counties.
Since
the
non­
affected
background
air
quality
in
Oakland
County
is
cleaner
than
surrounding
counties,
Oakland
County
cannot
be
contributing
to
non­
attainment
in
Wayne
County
on
those
days
when
the
wind
is
from
the
north.
To
the
contrary,
on
such
days,
the
cleaner
air
in
Oakland
County
would
be
diluting
the
more
contaminated
air
from
sources
within
Wayne
County.

When
comparing
Oakland
County
to
its
neighboring
downwind
counties,
it
is
important
to
note
that
EPA
is
proposing
to
designate
the
downwind
counties
(
Lapeer
and
Genesee)
as
attainment.
Other
counties
adjacent
to
Oakland
County
(
other
than
Wayne
which
is
discussed
above),
include
Macomb
to
the
east,
Livingston
to
the
west
and
Washtenaw
to
the
southwest.
While
these
counties
are
currently
proposed
for
inclusion
in
the
Detroit
Metropolitan
Statistical
Area
non­
attainment
area,
none
of
them
has
recorded
monitored
non­
attainment.

Consequently,
Oakland
County
cannot
be
designated
as
non­
attainment
with
respect
to
ambient
air
quality
in
these
counties,
since
these
counties
also
have
ambient
air
quality
which
meets
the
NAAQS.

3.
Factor
Three
 
Population
Density
and
Degree
of
Urbanization
EPA's
data
shows
that
Wayne
County
has
a
population
density
240%
higher
than
that
of
Oakland
County.
Oakland
County
has
a
mix
of
urban,
suburban,
and
rural
areas,
and
while
it
has
a
significant
population
of
over
1.2
million,
that
factor
is
irrelevant
for
the
purposes
of
designation
of
air
quality;
this
is
demonstrated
by
the
monitor
demonstrating
attainment
being
­
30­
located
in
the
most
populous
portion
of
the
County
(
Oak
Park).
The
overall
housing
density
in
Oakland
County
is
less
than
one
housing
unit
per
acre,
a
value
consistent
with
the
overall
suburban
character
of
the
County.
13
4.
Factor
Four
 
Traffic
and
Commuting
Patterns
Fewer
than
18%
of
Oakland
County
workers
commute
into
Wayne
County.

Seventy­
one
percent
of
Oakland
County
workers
live
and
commute
to
work
within
Oakland
County.
The
County's
many
small
livable
communities
allow
most
workers
to
live
and
work
in
the
same
area,
with
short
commutes
from
home
to
work.
Thus,
generalized
calculations
of
VMT
based
solely
upon
miles
of
roads
or
population
misrepresent
the
true
commuting
pattern
within
this
County.
14
5.
Factor
Five
­
Extent
of
Growth
U.
S.
Census
data
indicate
that
from
2002
to
2003,
Oakland
County's
population
increased
by
a
very
modest
0.4
percent.
The
County
itself
has
estimated
that
from
2000
to
2030,

population
growth
will
be
in
the
range
of
14
percent.
Again,
over
a
30
year
period,
this
is
a
modest
growth
rate.

13
U.
S.
Census
information
is
available
at
its
web
site,
http://
www.
census.
gov,
and
information
specific
to
Oakland
County
is
available
at
http://
www.
census.
gov/
acs/
www/
Products/
Profiles/
Single/
2003/
ACS/
MI.
htm.
Housing
density
information
is
available
at
http://
factfinder.
census.
gov/
servlet/
GCTTable?_
bm=
y&­
context=
gct&
ds_
name=
DEC_
2000_
SF1_
U&­
CONTEXT=
gct&­
mt_
name=
DEC_
2000_
SF1_
U_
GCTPH1R_
US13S&­
tree_
id=
4001&­
redoLog=
true&­_
caller=
geoselect&­
geo_
id=
04000US26&­
format=
ST­
2|
ST­
2S&­_
lang=
en.

14
U.
S.
Census
information
regarding
commuting
patters
of
Oakland
County
residents
can
be
found
at
http://
www.
census.
gov/
acs/
www/
Products/
Profiles/
Single/
2003/
ACS/
Tabular/
050/
05000
US261253.
htm.
­
31­
6.
Factor
Six
 
Meteorology
Gradient's
report
establishes
the
direct
and
incontrovertible
correlation
between
ambient
air
quality
data
and
wind
direction.
This
report
proves
conclusively
that
Oakland
County
air
emission
sources
are
not
contributing
to
monitored
non­
attainment
in
Wayne
County.

7.
Factor
Seven
 
Geography/
topography
In
addition
to
the
known
localized
air
quality
conditions
in
Wayne
County,
as
demonstrated
by
Michigan's
array
of
monitoring
stations,
one
must
also
consider
that
pollutants
from
Canada,
which
lies
south
and
east
of
Wayne
County,
also
may
be
affecting
the
air
quality
within
Wayne
County.
These
industrial
sources
are
not
adequately
accounted
for
in
EPA's
evaluation
of
contributing
source
areas.
Lying
north
and
west
of
the
major
point
source
emitters
of
PM­
2.5,
Oakland
County
enjoys
cleaner
air
than
its
upwind
neighboring
communities
in
Wayne
and
Monroe
Counties.

8.
Factor
Eight
 
Jurisdictional
Boundaries
Oakland
County
is
comprised
of
30
small
cities,
21
townships,
and
10
villages.

The
County's
Planning
and
Economic
Development
Department
administers
the
County's
Environmental
Stewardship
Program
to
assist
its
communities
in
achieving
sustainable
environmental
quality.
Oakland
County
is
a
discrete
jurisdiction
and
designating
the
whole
county
as
attainment
would
certainly
allow
for
efficient
administration
of
the
program.
­
32­
As
MDEQ
repeatedly
stated,
from
an
administrative
perspective,
having
Wayne
County
designated
as
non­
attainment
while
having
Oakland
County
designated
attainment
would
be
simple
to
administer
from
an
air
quality
program
perspective.
15
9.
Factor
Nine
 
Level
of
Control
of
Emissions
Oakland
County's
point
source
emissions
are
among
the
lowest
per
capita
emissions
in
the
region.
Although
an
imprecise
method
of
measurement
of
level
of
control
of
emissions,
this
comparison
is
useful
in
demonstrating
the
relative
level
of
point
source
emissions
and
their
presumed
control
by
geographic
area.
The
1999
emissions
inventory
lists
the
point
source
emissions
for
PM­
2.5
at
230
tpy
or
0.4
lb/
per
capita/
year
(
lb/
p/
yr)
for
Oakland
County.

Similar
per
capita
figures
for
surrounding
counties
are:
Monroe
County
 
81.3
lb/
p/
yr;
St.
Clair
County
 
41.6
lb/
p/
yr;
Lenawee
County
 
4.8
lb/
p/
yr;
Wayne
County
 
3.5
lb/
p/
yr;
Livingston
County
 
1.8
lb/
p/
yr;
Genesee
County
 
1.2
lb/
p/
yr;
Macomb
County
 
0.9
lb/
p/
yr;
Washtenaw
County
 
0.7
lb/
p/
yr;
and
Lapeer
County
 
0.1
lb/
p/
yr.
As
can
be
seen
from
this
comparison,

Oakland
County's
point
source
emissions
on
a
per
capita
basis
are
less
than
each
of
the
counties
included
in
the
non­
attainment
area
and
lower
than
two
of
the
three
attainment
counties
that
were
excluded
from
the
Metropolitan
Statistical
Area
(
Lenawee
and
Genesee).

A
comparison
of
PM­
2.5
area
source
emissions
is
even
more
dramatic.
Oakland
County's
per
capita
area
source
PM­
2.5
emissions
were
only
13.6
lb/
p/
yr
in
1999,
as
compared
to
Lapeer
(
52.1
lb/
p/
yr),
Lenawee
(
49.2
lb/
p/
yr),
Livingston
(
39.2
lb/
p/
yr),
Monroe
(
38.4
lb/
p/
yr),

St.
Clair
(
35.5
lb/
p/
yr),
Washtenaw
(
21.5
lb/
p/
yr),
Genesee
(
20.2
lb/
p/
yr),
Macomb
(
12.3
lb/
p/
yr),
and
Wayne
(
6.4
lb/
p/
yr)
Counties.
Thus,
Oakland
County's
area
source
PM­
2.5
15
See
MDEQ's
submissions
on
February
13,
2004,
September
1,
2004,
November
30,
2004,
and
February
22,
2005.
­
33­
emissions
on
a
per
capita
basis
are
less
than
all
of
the
attainment
counties
that
were
excluded
from
the
Metropolitan
Statistical
Area.
On
a
per
capita
basis,
Oakland
County's
emissions
are
lower
than
emissions
in
four
out
of
the
other
six
counties
included
in
EPA's
non­
attainment
designation.
This
indicates
that
the
existing
"
level
of
control"
is
more
than
adequate.

CONCLUSION
EPA
should
rescind
its
non­
attainment
designation
for
Oakland
County.
As
recommended
by
MDEQ,
Oakland
County
should
be
designated
as
being
in
attainment
with
all
PM­
2.5
standards.

Respectfully
Submitted,

Thomas
P.
Wilczak
Kurt
A.
Kissling
PEPPER
HAMILTON
LLP
100
Renaissance
Center
 
36th
Floor
Detroit,
MI
48243­
1157
(
313)
259­
7110
wilczakt@
pepperlaw.
com
kisslingk@
pepperlaw.
com
Keith
J.
Lerminiaux
Deputy
Corporation
Counsel
OAKLAND
COUNTY
Department
of
Corporate
Counsel
1200
North
Telegraph
Road,
Department
419
Pontiac,
MI
48341­
0419
(
248)
858­
0557
lerminiauxk@
co.
Oakland.
mi.
us
John
W.
Carroll
PEPPER
HAMILTON
LLP
200
One
Keystone
Plaza
North
Front
&
Market
Streets
Harrisburg,
PA
17108­
1181
(
717)
255­
1155
carrollj@
pepperlaw.
com
Marc
D.
Machlin
PEPPER
HAMILTON
LLP
Hamilton
Square
600
Fourteenth
Street,
N.
W.
Washington,
D.
C.
20005­
2004
(
202)
220­
1200
machlinm@
pepperlaw.
com
Attorneys
for
Petitioner
Oakland
County
March
7,
2005
BEFORE
THE
UNITED
STATES
ENVIRONMENTAL
PROTECTION
AGENCY
)
AIR
QUALITY
DESIGNATIONS
AND
)
CLASSIFICATIONS
FOR
THE
FINE
)
PARTICLES
(
PM­
2.5)
NATIONAL
AIR
)
QUALITY
STANDARDS
)
Air
Docket
No.
OAR­
2003­
0061
)
RIN­
2060­
AM04
FINAL
RULE
)
)
40
CFR
PART
81
)
)

CERTIFICATE
OF
SERVICE
I
hereby
certify
that
on
March
7,
2005,
a
copy
of
the
foregoing
Petition
for
Reconsideration
was
served
by
electronic
mail
and
by
either
hand
or
overnight
mail,
on
the
following
persons:

Stephen
L.
Johnson,
Acting
Administrator
U.
S.
Environmental
Protection
Agency
Ariel
Rios
Building,
1102A
1200
Pennsylvania
Avenue,
N.
W.
Washington,
DC
20460
(
202)
564­
7411
johnson.
stephen@
epa.
gov
Bharat
Mathur,
Acting
Regional
Administrator
U.
S.
Environmental
Protection
Agency­
Region
5
77
West
Jackson
Boulevard,
R­
19J
Chicago,
IL
60604­
3507
(
312)
886­
3000
mathur.
bharat@
epa.
gov
Ann
R.
Klee,
Esq.,
General
Counsel
U.
S.
Environmental
Protection
Agency
Ariel
Rios
Building,
2310A
1200
Pennsylvania
Avenue,
N.
W.
Washington,
DC.
20460
(
202)
564­
8040
klee.
ann@
epa.
gov
Jeffrey
R.
Holmstead
Assistant
Administrator
For
Air
and
Radiation
U.
S.
Environmental
Protective
Agency
Ariel
Rios
Building,
6101A
1200
Pennsylvania
Avenue,
N.
W.
Washington,
DC.
20460
(
202)
564­
7400
Marc
D.
Machlin
Exhibit
1
REPORT
OF
GRADIENT
CORPORATION/
DR.
PETER
DRIVAS
AND
DR.
CHRISTOPHER
M.
LONG
Gradient
CORPORATION
Oakland
County
PM2.5
Attainment
Analysis
Prepared
for
Pepper
Hamilton
LLP
600
Fourteenth
Street,
N.
W.
Washington,
DC
20005­
2004
Prepared
by
Gradient
Corporation
20
University
Road
Cambridge,
MA
02138
March
7,
2005
Gradient
CORPORATION
Table
of
Contents
Page
Executive
Summary
...................................................................................................
ES­
1
1
Introduction.........................................................................................................................
1
2
Oakland
County
PM2.5
Data
Analysis
..................................................................................
3
2.1
Monitor
Location.....................................................................................................
3
2.2
Attainment
Status....................................................................................................
4
2.3
Impact
on
Wayne
County........................................................................................
5
2.4
Impact
on
Downwind
Counties.............................................................................
17
3
Weighted
Emissions
Analysis
...........................................................................................
20
4
Conclusions.......................................................................................................................
25
5
References
........................................................................................................................
26
Appendix
A
Vector­
Averaged
Wind
Speed
and
Direction
Appendix
B
Qualifications
of
Authors
ES­
1
Gradient
CORPORATION
Executive
Summary
We
have
been
retained
by
Pepper
Hamilton,
LLP,
on
behalf
of
Oakland
County,

Michigan
to
assess
the
attainment
status
of
Oakland
County
with
regard
to
the
National
Ambient
Air
Quality
Standards
for
PM2.5.
The
Michigan
Department
of
Environmental
Quality
(
DEQ)

and
EPA
Region
V
have
reached
very
different
conclusions
on
the
PM2.5
attainment
status
of
Oakland
County.
The
DEQ's
position
is
that
only
Wayne
County
in
the
Detroit
metropolitan
area
should
be
designated
as
a
PM2.5
nonattainment
area,
and
that
Oakland
County,
as
well
as
other
counties
near
Detroit,
should
be
designated
as
attainment
areas
for
PM2.5.
The
DEQ's
position
is
based
primarily
on
air
monitoring
data,
which
show
attainment
for
PM2.5
for
all
counties
except
for
Wayne.

Although
the
monitor
in
Oakland
County
shows
attainment
for
PM2.5,
EPA
Region
V
disagrees
with
the
DEQ,
and
holds
a
position
that
seven
counties
in
the
Detroit
metropolitan
area,
including
Oakland
County,
should
be
designated
as
nonattainment
for
PM2.5.
The
EPA
Region
V
position
is
based
on
a
number
of
factors
that
are
subjectively
applied,
especially
in
light
of
actual
attainment
data,
including
location
in
the
same
metropolitan
area,
a
comparison
of
county
emissions
of
PM2.5
precursors,
and
the
possibility
that
transport
of
PM2.5
emissions
from
Oakland
County
may
contribute
to
the
PM2.5
violations
in
Wayne
County.

We
have
analyzed
the
PM2.5
data
taken
at
the
Oakland
County
monitor
in
Oak
Park,

Michigan,
over
the
last
five
years,
from
2000
to
2004,
and
have
compared
the
PM2.5
data
with
meteorological
data
from
Detroit
City
Airport.
Based
upon
our
analysis
of
the
available
PM2.5
and
meteorological
data,
Oakland
County
should
be
designated
as
in
PM2.5
attainment,
for
the
following
main
reasons:

1.
The
one
PM2.5
monitor
in
Oakland
County
is
located
in
Oak
Park,
which
is
in
the
southeast
corner
of
Oakland
County
and
only
about
one
mile
north
of
the
Wayne
County
border.
The
site
is
also
located
near
the
intersection
of
two
major
highways
and
is
in
the
most
heavily
industrialized
portion
of
the
county.
This
monitoring
location
likely
will
record
the
highest
PM2.5
values
in
Oakland
County,
due
to
nearby
local
sources
and
its
proximity
to
Wayne
County
emissions.
ES­
2
Gradient
CORPORATION
2.
Even
with
this
"
worst­
case"
location
in
Oakland
County,
the
PM2.5
monitor
at
Oak
Park
is
currently
in
attainment
for
PM2.5,
with
a
3­
year
average
PM2.5
concentration
less
than
15
µ
g/
m3
for
the
years
2001­
2003
and
2002­
2004.
The
DEQ
has
previously
demonstrated
that
the
Oak
Park
monitor
is
in
attainment
for
the
PM2.5
standard.

3.
When
the
Oak
Park
PM2.5
data
are
compared
with
local
meteorological
data,
almost
all
the
high
PM2.5
values
above
15
µ
g/
m3
over
the
last
five
years
have
occurred
with
winds
blowing
from
the
south
(
i.
e.,
indicative
of
transport
from
Wayne
County
and
other
potential
emission
sources
to
the
south).
This
trend
is
very
consistent
from
year
to
year.

4.
When
winds
are
blowing
from
the
north
towards
Wayne
County,
the
annual­
average
PM2.5
values
at
the
Oak
Park
monitor
were
very
low,
less
than
10
µ
g/
m3
for
every
year.
These
PM2.5
values
are
less
than
those
at
rural
regional
background
locations.
Thus,
the
transport
of
emissions
from
Oakland
County
is
not
contributing
to
PM2.5
violations
in
Wayne
County.
Note
that
because
the
Oak
Park
monitor
is
located
near
the
southern
border
of
Oakland
County,
it
is
well
positioned
to
detect
emissions
from
Oakland
County
sources
prior
to
transport
to
Wayne
County.
A
similarly
positioned
monitor
at
Livonia,
which
is
just
across
the
Wayne
County
border
near
the
southwestern
corner
of
Oakland
County,
has
recorded
a
3­
year
average
of
13.7
µ
g/
m3.

EPA
Region
V's
nonattainment
position
for
Oakland
County
is
also
based
on
other
factors
that
are
subjectively
applied,
such
as
projected
population
growth
and
the
emission
levels
of
PM2.5
precursors
in
Oakland
County
compared
with
other
counties.
These
factors
can
vary
widely
depending
on
the
data
sources,
and
techniques
such
as
"
weighted
emissions
score"
are
highly
uncertain
and
depend
strongly
on
the
choice
of
a
regional
background
monitoring
location.
The
use
of
actual
PM2.5
monitoring
data
and
meteorological
data
should
take
precedence
over
any
subjective
factors,
and
the
actual
PM2.5
data
and
meteorological
factors
strongly
support
a
designation
of
PM2.5
attainment
for
Oakland
County.
1
Gradient
CORPORATION
IV.
1
Introduction
On
February
13,
2004,
the
Michigan
Department
of
Environmental
Quality
(
DEQ)

submitted
an
analysis
of
PM2.5
attainment
status
(
Chester,
2004a)
for
a
number
of
counties
in
the
Detroit
Consolidated
Metropolitan
Statistical
Area
(
CMSA).
The
Michigan
DEQ's
position
was
that
only
Wayne
and
Monroe
Counties
in
the
Detroit
CMSA
should
be
designated
as
PM2.5
nonattainment
areas,
and
that
Oakland
County,
as
well
as
all
other
counties
in
the
Detroit
CSMA,

should
be
designated
as
attainment
areas
for
PM2.5.16
The
DEQ's
position
was
based
primarily
on
air
monitoring
data
through
2003,
which
showed
attainment
for
PM2.5
for
all
counties
except
for
Wayne
and
Monroe.
Also,
the
PM2.5
data
in
Wayne
County
were
compared
with
meteorological
data,
and
the
analysis
showed
that
the
high
PM2.5
values
at
two
monitors
in
Wayne
County
were
primarily
related
to
southerly
winds
(
i.
e.,
from
the
south),
indicating
that
high
PM2.5
values
at
Wayne
County
monitors
were
caused
primarily
by
transport
of
emissions
from
the
south.

On
July
29,
2004,
EPA
Region
V
presented
an
analysis
on
PM2.5
attainment
status
(
Mathur,
2004)
for
the
Detroit
CMSA
that
disagreed
with
the
DEQ
position.
Although
PM2.5
monitors
in
Oakland
County
and
other
nearby
counties
have
demonstrated
attainment
of
the
PM2.5
standard
of
15
µ
g/
m3
over
the
last
three
years,
EPA
Region
V's
position
was
that,
in
addition
to
Wayne
and
Monroe
Counties,
five
other
counties
in
the
Detroit
CMSA
(
Oakland,

Livingston,
Macomb,
St.
Clair,
and
Washtenaw
Counties)
should
be
designated
as
nonattainment
for
PM2.5.
This
position
was
based
on
a
number
of
factors
which
were
subjectively
applied,

including
location
in
the
same
CSMA,
projected
population
growth,
a
comparison
of
county
emissions
of
PM2.5
precursors,
and
the
possibility
that
transport
of
PM2.5
emissions
from
other
counties
may
contribute
to
the
PM2.5
violations
in
Wayne
and
Monroe
Counties.

We
have
been
retained
by
Pepper
Hamilton,
LLP,
on
behalf
of
Oakland
County
to
assess
the
attainment
status
of
Oakland
County
with
regard
to
the
National
Ambient
Air
Quality
16
On
February
22,
2005,
DEQ
submitted
2004
monitoring
data
and
amended
its
recommended
designations
to
redesignate
Monroe
County
as
attainment.
2
Gradient
CORPORATION
Standards
for
PM2.5.
For
this
purpose,
we
have
examined
relevant
documents
and
analyses
prepared
by
both
the
DEQ
and
EPA
Region
V,
and
have
compared
detailed
PM2.5
data
from
Oakland
County
with
meteorological
data
from
Detroit
City
Airport.

Our
analysis
is
focused
on
three
of
the
nine
factors
used
by
USEPA
to
designate
nonattainment
areas.
Section
2,
which
presents
our
analysis
of
the
Oakland
County
PM2.5
data
and
meteorological
data,
addresses
both
Factor
2:
Air
Quality
in
Potentially
Included
Versus
Excluded
Areas
and
Factor
6:
Meteorology.
Section
3
of
our
report
addresses
Factor
1:

Emissions
in
Areas
Potentially
Included
Versus
Excluded
from
the
Nonattainment
Area
and
highlights
the
highly
uncertain
nature
of
this
factor.
DEQ
has
previously
addressed
these
three
factors,
as
well
as
the
six
remaining
factors,
and
shown
major
flaws
in
the
USEPA
methodology.

We
summarize
our
conclusions
in
Section
4
of
this
report
and
provide
references
in
Section
5.

This
document
was
prepared
by
Dr.
Peter
Drivas
and
Dr.
Chris
Long
of
Gradient
Corporation.
The
qualifications
of
the
authors
are
presented
in
Appendix
B.
3
Gradient
CORPORATION
V.
2
Oakland
County
PM2.5
Data
Analysis
A.
2.1
Monitor
Location
The
one
PM2.5
monitor
in
Oakland
County
is
located
in
Oak
Park,
which
is
in
the
southeast
corner
of
Oakland
County
and
only
about
one
mile
north
of
the
Wayne
County
border.

The
site
is
also
located
near
the
intersection
of
two
major
highways
in
the
most
heavily
industrialized
portion
of
the
county,
as
shown
in
Figure
1.
Because
of
its
location,
the
Oak
Park
monitor
will
likely
record
the
highest
PM2.5
values
in
Oakland
County,
due
to
nearby
local
sources
and
its
proximity
to
Wayne
County
(
i.
e.,
the
strong
possibility
of
transport
of
Wayne
County
emissions
during
the
prevailing
winds
from
the
south).

Because
of
its
location,
the
Oak
Park
monitor
is
essentially
a
"
worst­
case"
monitor
for
Oakland
County
to
determine
attainment
for
PM2.5.
Oakland
County
extends
approximately
30
miles
in
the
north­
south
direction,
and
if
the
monitor
were
placed
near
the
center
of
Oakland
County,
it
would
be
about
15
miles
from
the
Wayne
County
border
instead
of
only
one
mile,
and
likely
would
record
lower
PM2.5
concentrations.

Oak
Park
Figure
1.
Counties
in
Detroit
Metropolitan
Area
4
Gradient
CORPORATION
B.
2.2
Attainment
Status
USEPA
established
National
Ambient
Air
Quality
Standards
(
NAAQS)
for
fine
particles
in
1997
that
included
both
an
annual
average
PM2.5
standard
of
15
µ
g/
m3
and
a
24­
hour
PM2.5
standard
of
65
µ
g/
m3.
In
order
to
determine
compliance
with
these
standards
and
to
designate
nonattainment
areas,
USEPA
required
that
three
consecutive
years
of
clean
data
be
collected
and
used
to
calculate
the
3­
year
average
of
annual
arithmetic
mean
PM2.5
concentrations
and
the
3­

year
average
of
the
98th
percentile
of
24­
hour
PM2.5
concentrations
for
comparison
with
the
annual
average
and
24­
hour
PM2.5
standards,
respectively.

Table
1
below
demonstrates
that,
despite
the
"
worst­
case"
location
of
the
county's
PM2.5
monitor,
the
Oakland
County
PM2.5
monitoring
data
meet
the
PM2.5
NAAQS
and
thus
meet
the
definition
of
an
attainment
area.
As
shown
in
this
table,
both
the
3­
year
average
PM2.5
concentrations
for
the
years
2001­
2003
and
2002­
2004
(
14.8
and
14.1
µ
g/
m3,
respectively)
are
less
than
the
15
µ
g/
m3
standard.
In
addition,
the
3­
year
average
of
the
98th
percentiles
of
both
2001­
2003
and
2002­
2004
24­
hour
PM2.5
concentrations
(
38.1
and
36.0
µ
g/
m3,
respectively)
are
well
below
the
24­
hour
PM2.5
standard
of
65
µ
g/
m3.
The
DEQ
has
previously
demonstrated
that
the
Oak
Park
monitor
is
in
attainment
for
the
PM2.5
standard.

Table
1
Summary
of
2001­
2004
PM2.5
Monitoring
Data
for
Oak
Park,
MI
Year
Annual
Ave.
3­
year
Annual
Ave.
98th
Percentile
3­
year
Ave.
of
98th
Percentiles
2001
14.70
­­
39.4
­­
2002
15.00
­­
38.4
­­
2003
14.58
14.8
36.6
38.1
2004
12.76
14.1
33
36.0
Notably,
as
recently
highlighted
in
documents
submitted
by
the
DEQ
(
Chester,
2005),

PM2.5
levels
in
Southeast
Michigan
show
a
downward
trend
in
recent
years.
Table
1
confirms
the
presence
of
a
strong
downward
trend
for
the
Oakland
County
PM2.5
monitoring
data.
In
5
Gradient
CORPORATION
particular,
the
2004
PM2.5
annual
average
was
the
lowest
on
record
for
Oak
Park,
and
the
2004
data
dropped
the
2002­
2004
three­
year
average
PM2.5
concentration
to
14.1
µ
g/
m3.

Additionally,
just
across
the
Wayne
County
border
near
the
southwestern
corner
of
Oakland
County,
the
Livonia
monitor
has
recorded
three
year
averages
of
14.4
µ
g/
m3
and
13.7
µ
g/
m3
for
2001­
2003
and
2002­
2004,
respectively,
thus
providing
additional
evidence
that
no
portion
of
Oakland
County
is
contributing
to
nonattainment
in
Wayne
County.

The
Oakland
County
PM2.5
monitoring
data
are
thus
conclusive
that
the
county
is
in
attainment
with
the
PM2.5
standard,
and
since
the
monitoring
data
represent
a
worst­
case
location
in
the
county,
it
is
clear
that
Oakland
County
should
be
designated
as
an
attainment
area.

C.
2.3
Impact
on
Wayne
County
Based
on
analyses
of
meteorological
data
and
PM2.5
measurement
data,
Michigan
DEQ
has
previously
concluded
that
Wayne
and
Monroe
Counties
are
receiving
pollution
from
emission
sources
to
the
south.
In
particular,
in
the
February
13,
2004
PM2.5
Designation
Recommendations
Technical
Support
Document
(
Chester,
2004a),
DEQ
presented
three
sets
of
back
trajectory
paths
corresponding
to
the
2002
Dearborn
PM2.5
sampling
days
with
daily
PM2.5
concentrations
of
less
than
15
µ
g/
m3,
daily
PM2.5
concentrations
between
28
µ
g/
m3
and
40
µ
g/
m3,
and
daily
PM2.5
concentrations
greater
than
or
equal
to
40
µ
g/
m3.
Back
trajectory
paths
show
the
origin
and
path
of
transport
of
air
parcels
to
a
particular
destination
area.
The
Michigan
DEQ
trajectories
clearly
showed
that
the
highest
PM2.5
days
in
the
Detroit
CMSA
occurred
when
winds
were
from
the
south
and
southwest,
indicating
that
counties
to
the
north
of
Detroit
such
as
Oakland
County
are
not
associated
with
high
PM
levels
in
Wayne
County.
Only
for
cleaner
days
(
i.
e.,
PM2.5<
15
µ
g/
m3)
in
Wayne
County
were
trajectories
consistently
from
the
north,
indicating
that
the
northern
counties
were
associated
with
improved
air
quality
in
Wayne
County.

In
a
September
1,
2004
document
presenting
comments
on
USEPA's
proposed
PM2.5
designations
for
Michigan
(
Chester,
2004b),
DEQ
included
pollution
roses
that
depicted
wind
directions
on
days
with
higher
( 
15
µ
g/
m3)
and
lower
(<
15
µ
g/
m3)
PM2.5
levels
as
measured
at
6
Gradient
CORPORATION
the
Allen
Park
and
Dearborn
monitors
in
Wayne
County.
As
summarized
by
DEQ,
these
pollution
roses
show
that
PM2.5
concentrations
at
the
Wayne
County
monitors
are
highest
when
winds
are
from
the
south
and
southwest.

To
complement
the
DEQ
analyses
and
to
specifically
address
PM2.5
levels
in
Oakland
County,
we
analyzed
meteorological
data
on
days
with
higher
and
lower
PM2.5
levels
as
measured
at
the
Oak
Park
PM2.5
monitor
in
Oakland
County.
For
these
analyses,
we
obtained
the
last
five
years
(
2000­
2004)
of
24­
hour
PM2.5
data
for
the
Oak
Park
PM2.5
monitor
from
USEPA's
Air
Quality
System
(
AQS).
17
With
the
exception
of
2004
where
individual
24­
hour
data
were
available
only
up
through
July
200418,
daily
PM2.5
data
at
the
Oak
Park
monitor
were
typically
available
for
every
three
days
between
2000­
2004.

We
obtained
hourly
meteorological
data
for
the
years
2000­
2004
for
the
National
Weather
Service
(
NWS)
station
at
the
Detroit
City
Airport
from
the
National
Climatic
Data
Center
(
NCDC).
This
is
the
closest
NWS
meteorological
station
to
the
monitors
in
Oakland
and
Wayne
Counties.
Figure
2
shows
a
five­
year
average
wind
rose
summarizing
2000­
2004
wind
speed
and
wind
direction
measurements
at
the
Detroit
City
Airport.
As
shown
in
this
wind
rose,

the
most
frequent
winds
are
from
the
southwest
quadrant,
with
the
least
frequent
winds
from
the
northeast
quadrant.

17
http://
www.
epa.
gov/
ttn/
airs/
airsaqs/
detaildata/
downloadaqsdata.
htm
18
The
USEPA
AQS
website
notes
that
complete
2004
data
will
be
available
by
July
1,
2005.
7
Gradient
CORPORATION
Figure
2.
2000­
2004
Wind
Rose
for
Detroit
City
Airport
For
comparison
with
the
daily
PM2.5
data,
we
calculated
daily
vector­
averaged
wind
speed
and
directions
from
the
hourly
Detroit
City
Airport
meteorological
data.
These
vectoraveraged
calculations
are
described
in
greater
detail
in
Appendix
A.
We
eliminated
all
days
without
PM2.5
data,
and
any
days
where
PM2.5
data
were
available
but
there
were
fewer
than
12
hours
of
valid
meteorological
observations.
With
the
exception
of
2003
where
eight
days
were
eliminated
due
to
periods
of
missing
meteorological
data,
we
typically
only
eliminated
one
or
two
days
per
year
due
to
missing
meteorological
data.

Figure
3
presents
five­
year
average
wind
roses
for
days
at
the
Oak
Park
monitor
with
PM2.5
levels
of
less
than
15
µ
g/
m3
(
Figure
3a),
and
days
with
PM2.5
levels
greater
than
or
equal
to
15
µ
g/
m3
(
Figure
3b).
These
plots
clearly
show
that
almost
all
the
high
PM2.5
values
above
15
µ
g/
m3
over
the
last
five
years
have
occurred
with
winds
blowing
from
the
south
(
i.
e.,
indicative
of
transport
from
Wayne
County
and
other
potential
non­
Oakland
County
emission
sources
to
the
south).
For
winds
blowing
from
the
north,
which
represent
transport
across
the
majority
of
8
Gradient
CORPORATION
the
Oakland
County
area
(
given
that
the
Oak
Park
monitor
is
on
the
southern
border
of
the
county),
PM2.5
levels
are
consistently
less
than
15
µ
g/
m3.

The
data
are
very
consistent
from
year
to
year.
Figures
4
through
8
show
all
individual
24­
hour
PM2.5
data
points
over
the
last
five
years,
with
one
graph
per
year.
In
Figures
4
through
8,
the
data
have
been
segregated
by
general
wind
direction
into
"
north"
(
blowing
from
the
northwest
and
northeast
quadrants)
and
"
south"
(
blowing
from
the
southwest
and
southeast
quadrants).
These
figures
dramatically
show
that
significantly
higher
PM2.5
measurements
at
the
Oak
Park
monitor
occur
when
winds
are
from
the
south
(
i.
e.,
from
the
direction
of
Wayne
County).
The
trend
is
very
consistent
from
year
to
year
from
2000
through
2004.

Figure
9
summarizes
data
from
Figures
4
through
8,
and
presents
calculated
annualaverage
PM2.5
values
at
the
Oak
Park
monitor
by
wind
direction.
Figure
9
clearly
shows
that
when
winds
were
blowing
from
the
north
towards
Wayne
County,
the
annual­
average
PM2.5
values
were
less
than
10
µ
g/
m3
for
every
year.
Further,
this
plot
shows
that
PM2.5
levels
measured
at
the
Oak
Park
monitor,
for
winds
from
the
north,
are
on
average
less
than
those
from
sites
such
as
Bondville,
Illinois
(
12.3
µ
g/
m3)
that
USEPA
has
selected
as
representative
of
regional
background
PM2.5
levels.
Thus,
this
analysis
conclusively
shows
that
the
transport
of
emissions
from
Oakland
County
is
not
contributing
to
high
PM2.5
levels
in
Wayne
County.
9
Gradient
CORPORATION
(
a)
Less
than
15
µ
g/
m3
(
b)
Greater
Than
or
Equal
to
15
µ
g/
m3
10
Gradient
CORPORATION
Figure
3.
Wind
Roses
for
High
and
Low
PM2.5
Days
at
Oak
Park,
MI:
2000­
2004
Data
11
Gradient
CORPORATION
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Jan
PM
2.5
Conc.
(
µ
g/
m
3)

0
5
10
15
20
25
30
35
40
45
50
55
60
Winds
from
the
North,
PM
2.5
Ave=
9.4
Winds
from
the
South,
PM
2.5
Ave=
19.3
Figure
4.
Daily
PM2.5
Levels
at
Oak
Park
vs.
Daily
Average
Wind
Direction:
2000
Data
12
Gradient
CORPORATION
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Jan
PM
2.5
Conc.
(
µ
g/
m
3)

0
5
10
15
20
25
30
35
40
45
50
55
60
Winds
from
the
North,
PM
2.5
Ave=
9.3
Winds
from
the
South,
PM
2.5
Ave=
19.6
Figure
5.
Daily
PM2.5
Levels
at
Oak
Park
vs.
Daily
Average
Wind
Direction:
2001
Data
13
Gradient
CORPORATION
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Jan
PM
2.5
Conc.
(
µ
g/
m3)

0
5
10
15
20
25
30
35
40
45
50
55
60
Winds
from
the
North,
PM
2.5
Ave=
8.2
Winds
from
the
South,
PM
2.5
Ave=
19.9
Figure
6.
Daily
PM2.5
Levels
at
Oak
Park
vs.
Daily
Average
Wind
Direction:
2002
Data
14
Gradient
CORPORATION
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Jan
PM
2.5
Conc.
(
µ
g/
m3)

0
5
10
15
20
25
30
35
40
45
50
55
60
Winds
from
the
North,
PM
2.5
Ave=
9.7
Winds
from
the
South,
PM
2.5
Ave=
18.2
Figure
7.
Daily
PM2.5
Levels
at
Oak
Park
vs.
Daily
Average
Wind
Direction:
2003
Data
15
Gradient
CORPORATION
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Jan
PM
2.5
Conc.
(
µ
g/
m
3)

0
5
10
15
20
25
30
35
40
45
50
55
60
Winds
from
the
North,
PM
2.5
Ave=
8.3
Winds
from
the
South,
PM
2.5
Ave=
15.5
Figure
8.
Daily
PM2.5
Levels
at
Oak
Park
vs.
Daily
Average
Wind
Direction:
2004
Data
16
Gradient
CORPORATION
2000
2001
2002
2003
2004
2000
2001
2002
2003
2004
Annual
Average
PM
2.5
Conc.
(
µ
g/
m
3)

0
5
10
15
20
25
Annual
Ave.
PM
2.5
Conc.
with
Winds
from
North
Annual
Ave.
PM
2.5
Conc.
with
Winds
from
South
Bondville,
IL
Regional
Background
Figure
9.
Summary
of
PM2.5
Concentrations
at
Oak
Park
by
Wind
Direction
17
Gradient
CORPORATION
D.
2.4
Impact
on
Downwind
Counties
To
investigate
whether
Oakland
County
influences
PM
levels
in
neighboring
downwind
counties,
particularly
Macomb
County
directly
to
the
east,
we
conducted
an
analogous
analysis
to
that
discussed
in
Section
2.3
by
pairing
2000­
2004
daily
PM2.5
data
from
the
New
Haven,
MI
monitor
in
Macomb
County
with
daily
averaged
Detroit
City
Airport
meteorological
data.
Figure
10
shows
that
high
PM2.5
levels
in
Macomb
County
are
also
associated
with
winds
from
the
south
and
southwest,
indicating
that
Wayne
County
contributes
to
high
PM2.5
levels
in
Macomb
County.
Winds
from
the
direction
of
Oakland
County
(
i.
e.,
winds
from
the
west
and
northwest)
are
dominant
on
low
PM2.5
days,
demonstrating
that
Oakland
County
does
not
contribute
to
high
PM2.5
values
in
neighboring
Macomb
County.
It
should
be
noted
the
New
Haven
monitor
at
Macomb
County
is
in
attainment
with
the
PM2.5
standard,
with
a
3­
year
average
PM2.5
value
of
13.1
µ
g/
m3
from
2001­
2003
and
12.7
µ
g/
m3
from
2002­
2004.

The
other
two
counties
bordering
Oakland
County
to
the
north
(
Lapeer
and
Genesee
Counties)
have
been
designated
by
EPA
as
attainment
and
thus
it
is
presumed
that
Oakland
County
is
not
contributing
to
nonattainment
in
those
counties.
18
Gradient
CORPORATION
(
a)
Less
than
15
µ
g/
m3
(
b)
Greater
Than
or
Equal
to
15
µ
g/
m3
Figure
10.
Wind
Roses
for
High
and
Low
PM2.5
Days
at
New
Haven,
MI:
2000­
2004
Data
19
Gradient
CORPORATION
20
Gradient
CORPORATION
VI.
3
Weighted
Emissions
Analysis
Despite
the
availability
of
monitoring
data
that
statutorily
demonstrate
attainment,
EPA
Region
V
has
elected
to
calculate
what
is
called
a
"
weighted
emissions
score"
as
part
of
the
process
for
designating
nonattainment
areas
for
the
PM2.5
NAAQS.
This
is
the
first
of
nine
factors
(
Factor
1)
that
EPA
Region
V
used
subjectively
to
determine
Oakland
County's
nonattainment
status.
USEPA
(
2004)
itself
has
acknowledged
that
the
weighted
emissions
score
metric
has
"
particular
uncertainties."
As
stated
in
the
December
2004
Technical
Support
for
State
and
Tribal
Air
Quality
Fine
Particle
(
PM2.5)
Designation,
USEPA
(
2004)
states
that
this
metric
"
should
be
regarded
simply
as
one
way
to
assess
multiple
emissions
all
contributing
to
the
'
emissions'
factor
identified
in
EPA
guidance."

The
weighted
emissions
score
is
determined
from
two
primary
data
sources,
(
1)
estimates
of
county­
wide
emissions
of
SO2,
NOx,
carbon
particles,
and
crustal
particles
and
(
2)
a
measure
of
urban
excess
that
reflects
excess
local
contributions
of
the
major
PM2.5
chemical
components
(
sulfates,
nitrates,
carbon,
and
crustal
matter)
from
speciation
monitoring
data.
As
defined
by
USEPA
(
2004),
the
weighted
emissions
score
thus
uses
measured
concentration
data
in
combination
with
estimated
county­
wide
emissions
inventories
in
this
calculation.
This
mixing
and
matching
of
measured
concentration
data
with
estimated
emissions
inventories
contributes
to
the
high
level
of
uncertainty
associated
with
this
calculation.

The
uncertainty
associated
with
the
pairing
of
measured
concentration
data
with
emissions
estimates
is
illustrated
by
focusing
on
the
use
of
county
emissions
of
SO2
and
NOx
as
surrogates
for
PM2.5
sulfate
and
nitrate
air
concentrations.
The
conversion
of
SO2
and
NOx
emissions
from
point
sources
or
area
sources
to
sulfates
and
nitrates
is
extremely
complex,
and
depends
on
the
air
concentrations
of
other
pollutants,
meteorology,
and
the
travel
time
of
the
emissions
from
the
sources
to
a
given
monitoring
location.
The
conversion
to
sulfates
and
nitrates
is
primarily
photochemical,
and
depends
significantly
on
solar
radiation
and
the
ozone
concentrations
that
are
entrained
into
the
air
parcel
containing
the
SO2
and
NOx
emissions.

Because
of
the
complexity
of
sulfate
and
nitrate
formation,
there
is
not
a
simple
linear
relationship
between
SO2
and
NOx
emission
rates
and
the
resulting
sulfate
and
nitrate
particles.
21
Gradient
CORPORATION
Thus,
using
SO2
and
NOx
emissions
as
surrogates
for
PM2.5
concentrations
introduces
substantial
uncertainty
into
the
Factor
1
analysis.

There
are
also
uncertainties
associated
with
the
emissions
inventories
themselves,
as
they
are
estimated
values
and
not
actual
measurement
data.
However,
it
was
not
possible
to
address
emission
inventory
uncertainties
in
this
report
since
EPA
Region
V
does
not
fully
document
the
source
of
the
emissions
estimates
for
carbon
and
crustal
particles.
19
It
is
very
unclear
how
the
emissions
inventory
estimates
for
carbon
and
crustal
particles
were
obtained,
and
as
discussed
later,
the
emission
estimates
for
carbon
particles
are
a
key
determinant
of
the
weighted
emissions
score
for
Oakland
County.

To
calculate
"
urban
excess",
EPA
Region
V
applied
a
methodology
where
concentrations
of
four
PM2.5
speciated
components
representative
of
the
counties
in
the
metropolitan
area
were
compared
to
the
corresponding
concentrations
representative
of
regional
background
levels.
The
difference
in
concentrations
between
the
county
speciation
data
and
the
regional
background
levels
was
assumed
to
be
representative
of
local
contributions
of
PM2.5
components.
Because
speciation
data
are
not
available
for
the
Oakland
County
PM2.5
monitor
in
Oak
Park,
speciation
data
from
the
Allen
Park
monitor
in
Wayne
County
were
used
by
EPA
for
assessing
emissions
in
all
counties
in
the
Detroit
CMSA,
including
Oakland
County.
Importantly,
this
use
of
speciation
data
from
the
Allen
Park
monitor
in
Wayne
County
to
represent
the
speciation
profile
in
all
Detroit­
CMSA
counties
is
a
potentially
large
source
of
uncertainty,
especially
given
differences
in
emissions
sources
between
the
different
counties.

EPA
Region
V
chose
the
M.
K.
Goddard
site
in
Pennsylvania
as
representative
of
regional
background
PM2.5
levels
in
each
of
the
counties
in
the
Detroit
metropolitan
area.
Little
information
is
provided
regarding
the
rationale
for
the
selection
of
this
site
as
representative
of
regional
background.
However,
back
trajectory
analyses
conducted
by
DEQ
(
Chester,
2004a)

19
USEPA
(
2004)
states
that
the
county
emissions
estimates
used
in
the
Factor
1
analysis
were
taken
from
the
2001
National
Emission
Inventory,
version
3.
However,
this
emissions
inventory
could
not
be
found
on
the
USEPA
website,
nor
are
estimates
of
carbon
and
crustal
particles
typical
components
of
USEPA
emissions
inventory
data.
22
Gradient
CORPORATION
have
demonstrated
that
air
parcels
in
the
Detroit
metropolitan
area
rarely
originate
in
western
Pennsylvania.
DEQ
has
previously
concluded
that
the
M.
K.
Goddard
site
was
inappropriate
for
use
in
this
urban
excess
methodology.

Based
on
the
DEQ
back
trajectory
analyses,
Bondville,
IL
(
southwest
of
Detroit)
is
a
more
appropriate
site
than
the
M.
K.
Goddard
site
in
Pennsylvania
to
represent
regional
background
PM2.5
levels
in
the
Detroit
metropolitan
area.
The
DEQ
analyses
of
back
trajectories
indicate
that
air
parcels
in
the
Detroit
CMSA
frequently
originate
from
the
Bondville,
IL
vicinity
on
days
of
high
PM2.5
levels
in
Wayne
County.

Table
2
compares
the
urban
excess
percentages
by
PM2.5
component
for
the
Detroit
CMSA.
Note
that
this
comparison
is
based
on
2002­
2003
speciation
data
as
provided
in
USEPA
(
2004).
As
shown
in
this
comparison,
the
selection
of
a
site
representative
of
regional
background
has
a
significant
impact
on
the
speciated
urban
excess
percentages.
With
the
M.
K.

Goddard
site
as
the
regional
background
site,
there
is
no
urban
excess
of
sulfates,
and
the
majority
of
the
urban
excess
is
attributed
to
nitrates.
With
the
Bondville
site
as
the
regional
background
site,
the
majority
of
the
urban
excess
is
attributed
to
carbon
particles,
with
smaller
percentages
of
nitrates
and
sulfates.
Note
that
with
the
majority
of
the
urban
excess
being
attributed
to
carbon
particles,
the
EPA
emissions
estimates
for
carbon
particles
thus
play
a
key
role
in
the
determination
of
the
composite
emissions
scores
for
each
county.
However,
as
discussed
above,
EPA
did
not
fully
document
the
source
of
the
carbon
particle
emissions
estimates.

Table
2
Urban
Excess
Results:
M.
K.
Goddard,
PA
Site
vs.
Bondville,
IL
Site
With
M.
K.
Goddard,
PA
Site
With
Bondville,
IL
Site
Total
Mass
Urban
Excess
(
µ
g/
m3)
4.3
3.9
%
Sulfates
0
17.9
%
Nitrates
53.6
12.8
%
Carbon
Mass
42.2
69.2
%
Crustal
Mass
4.0
0
23
Gradient
CORPORATION
Notwithstanding
the
major
flaws
in
the
weighted
emissions
score
methodology
identified
above,
Table
3
demonstrates
the
resulting
impact
on
the
composite
emissions
scores
for
the
Detroit
metropolitan
area
counties
when
the
Bondville,
IL
site
is
used
to
represent
regional
background.
Both
Table
2
and
Table
3
thus
illustrate
the
sensitivity
in
this
metric
for
a
change
in
just
one
of
the
parameters
(
the
regional
background
site)
employed
in
the
calculation.

Furthermore,
the
composite
emissions
score
clearly
is
biased
by
county
area,
since
area
source
emissions
are
dependent
on
total
county
area,
and
area
sources
dominate
emissions
in
many
of
the
Detroit
area
counties
(
Oakland
County
is
the
largest
of
the
Detroit­
CMSA
counties).

It
would
be
more
appropriate
to
normalize
emissions
by
county
area
for
use
in
calculation
of
composite
emissions
scores,
and
Table
4
shows
county
areas
and
composite
emissions
scores
when
emission
are
normalized
by
area.
This
table
again
shows
significant
changes
in
composite
emissions
scores
with
a
slight
change
in
the
calculation
methodology.

Table
3
Composite
Emission
Scores:
MK
Goddard,
PA
Site
vs.
Bondville,
IL
Site
Composite
Emission
Scores
County
EPA
(
With
MK
Goddard,
PA
Site)
With
Bondville,
IL
Site
Wayne
29.8
28.3
Monroe
15.1
17.7
Oakland
13.6
12.6
St.
Clair
10.4
11.9
Macomb
9.5
8.1
Genesee
7.5
7.3
Washtenaw
5.3
5.0
Livingston
4.0
4.3
Lenawee
2.5
2.8
Lapeer
2.1
2.0
Table
4
Composite
Emission
Scores:
USEPA
Methodology
vs.
County
Area
Normalization
24
Gradient
CORPORATION
Composite
Emission
Scores1
County
County
Area
(
sq.
miles)
USEPA
With
Normalization
by
County
Area
Wayne
614.2
29.8
23.7
Monroe
551.1
15.1
18.7
St.
Clair
724.4
10.4
11.6
Oakland
872.5
13.6
11.5
Macomb
480.4
9.5
8.2
Genesee
639.6
7.5
7.8
Washtenaw
709.9
5.3
5.8
Livingston
568.4
4.0
5.3
Lenawee
750.5
2.5
4.1
Lapeer
654.2
2.1
3.2
1Both
sets
of
composite
emission
scores
use
the
MK
Goddard,
PA
site
as
the
regional
background
site.

In
conclusion,
the
weighted
emissions
score
clearly
is
an
uncertain
and
imperfect
metric
for
assessing
PM2.5
attainment
status.
It
is
based
on
a
number
of
highly
uncertain
assumptions,

including
the
relationship
between
measured
speciation
data
and
emissions
estimates.

Uncertainties
are
introduced
by
assuming
that
there
is
a
simple
linear
relationship
between
SO2
and
NOx
emission
rates
and
the
resulting
sulfate
and
nitrate
particles.
In
addition,
the
EPA
calculation
for
the
Detroit­
area
CMSA
also
relies
upon
speciation
data
from
a
single
monitor
in
Wayne
County
(
i.
e.,
the
Allen
Park
monitor)
to
represent
the
speciation
profiles
in
all
other
Detroit­
CMSA
counties
despite
large
differences
in
emission
sources
between
the
different
counties.

The
overall
lack
of
credibility
of
this
metric
has
been
demonstrated
by
showing
significant
impacts
on
the
composite
emissions
scores
with
slight
changes
in
the
calculation
methodology.
Importantly,
this
metric
does
not
provide
any
information
on
whether
local
PM2.5
contributions
in
counties
such
as
Oakland
County
have
any
impacts
on
concentrations
in
the
portions
of
Wayne
County
where
monitor
violations
have
been
observed.
Our
analyses
presented
in
Section
2
specifically
addressed
the
transport
and
impacts
of
local
emissions
in
Oakland
County,
and
they
conclusively
demonstrated
that
the
transport
of
emissions
from
Oakland
County
is
not
contributing
significantly
to
the
exceedances
of
the
PM2.5
standard
or
nonattainment
in
the
neighboring
counties
that
include
Wayne
County
and
Macomb
County.
25
Gradient
CORPORATION
VII.
4
Conclusions
Our
analysis
of
the
available
evaluations
of
PM2.5
attainment
status
and
detailed
PM2.5
and
meteorological
data
strongly
supports
a
designation
of
PM2.5
attainment
for
Oakland
County,

for
the
following
main
reasons:

1.
The
one
PM2.5
monitor
in
Oakland
County
is
located
in
Oak
Park,
which
is
in
the
southeast
corner
of
Oakland
County
and
only
about
one
mile
north
of
the
Wayne
County
border.
The
site
is
also
near
the
intersection
of
two
major
highways
and
is
in
the
most
heavily
industrialized
portion
of
the
county.
This
monitoring
location
will
likely
record
the
highest
PM2.5
values
in
Oakland
County,
due
to
nearby
local
sources
and
its
proximity
to
Wayne
County
emissions.

2.
Even
with
this
"
worst­
case"
location
in
Oakland
County,
the
PM2.5
monitor
at
Oak
Park
is
currently
in
attainment
for
PM2.5,
with
a
3­
year
average
PM2.5
concentration
less
than
15
µ
g/
m3
for
the
years
2001­
2003
and
2002­
2004.
EPA
Region
V
concurs
with
the
Michigan
DEQ
that
the
Oak
Park
monitor
is
in
attainment
for
the
PM2.5
standard.

3.
Oakland
County
does
not
contribute
to
Wayne
County
nonattainment
based
on
an
analysis
of
PM2.5
and
meteorological
data.
Specifically,
when
the
Oak
Park
PM2.5
data
are
compared
with
local
meteorological
data,
almost
all
the
high
PM2.5
values
above
15
µ
g/
m3
over
the
last
five
years
have
occurred
with
winds
blowing
from
the
south
(
i.
e.,
indicative
of
transport
from
Wayne
County
and
other
potential
emission
sources
to
the
south).
This
trend
is
very
consistent
from
year
to
year.

4.
When
winds
are
blowing
from
the
north
towards
Wayne
County,
the
annual­
average
PM2.5
values
at
the
Oak
Park
monitor
were
very
low,
less
than
10
µ
g/
m3
for
every
year.
These
PM2.5
values
are
less
than
those
at
rural
regional
background
locations.
Thus,
the
transport
of
emissions
from
Oakland
County
is
not
contributing
to
PM2.5
violations
in
Wayne
County.
Our
analysis
also
demonstrated
that
winds
from
the
direction
of
Oakland
County
are
dominant
on
low
PM2.5
days
in
neighboring
Macomb
County,
demonstrating
that
Oakland
County
also
does
not
contribute
to
high
PM2.5
values
in
this
county.

5.
EPA
Region
V's
nonattainment
position
for
Oakland
County
is
based
primarily
on
subjective
factors,
such
as
the
county
emissions
of
PM2.5
precursors.
These
factors
can
vary
widely
depending
on
the
data
sources,
and
techniques
such
as
"
weighted
emissions
score"
are
highly
uncertain
and
depend
strongly
on
the
choice
of
a
regional
background
monitoring
location,
and
can
not
be
reasonably
used
in
making
a
determination
of
attainment
status.

The
use
of
actual
PM2.5
monitoring
data
and
meteorological
data
should
take
precedence
over
any
subjective
factors
that
contain
high
uncertainty.
The
actual
PM2.5
data
and
meteorological
factors
strongly
support
a
designation
of
PM2.5
attainment
for
Oakland
County.
26
Gradient
CORPORATION
5
References
Chester,
S.
E.
2004a.
Letter
from
Steven
E.
Chester,
Michigan
DEQ
to
Thomas
V.
Skinner,
EPA
Region
V,
dated
February
13,
2004.

Chester,
S.
E.
2004b.
Letter
from
Steven
E.
Chester,
Michigan
DEQ
to
Bharat
Mathur,
EPA
Region
V,
dated
September
1,
2004.

Chester,
S.
E.
2004c.
Letter
from
Steven
E.
Chester,
Michigan
DEQ
to
Bharat
Mathur,
EPA
Region
V,
dated
November
30,
2004.

Chester,
S.
E.
2005.
Letter
from
Steven
E.
Chester,
Michigan
DEQ
to
Bharat
Mathur,
EPA
Region
V,
dated
February
22,
2005.

Mathur,
B.
2004.
Letter
from
Bharat
Mathur,
EPA
Region
V
to
Honorable
Governor
Jennifer
M.
Granholm,
Governor
of
Michigan,
dated
July
29,
2004.

U.
S.
Environmental
Protection
Agency
(
USEPA).
2004.
Technical
Support
for
State
and
Tribal
Air
Quality
Fine
Particle
(
PM2.5)
Designation.
Office
of
Air
Quality
Planning
and
Standards,
Integrated
Policy
and
Strategies
Group,
Research
Triangle
Park,
NC.
December.
Gradient
CORPORATION
APPENDIX
A
VECTOR­
AVERAGED
WIND
SPEED
AND
DIRECTION
A­
1
Gradient
CORPORATION
To
compare
with
the
24­
hour
average
individual
PM2.5
data,
a
vector­
average
wind
direction
and
wind
speed
must
be
calculated
over
the
same
24­
hour
period.
This
is
a
standard
meteorological
procedure
that
calculates
a
resultant
wind
direction
from
hourly
wind
direction
data,
weighted
by
the
wind
speed
for
each
hour.

From
a
sequence
of
N
observations
of
wind
direction
(
 i)
and
wind
speed
(
Ui),
the
mean
east­
west
(
Ve)
and
north­
south
(
Vn)
vector
components
of
the
wind
are:

(
)
i
N
i
i
e
U
N
V
 
sin
1
1

=
 
=

(
)
i
N
i
i
n
U
N
V
 
cos
1
1

=
 
=

The
resultant
vector­
average
wind
direction
(
 ave)
and
wind
speed
(
Uave)
are:









=

n
e
ave
V
V
arctan
 
2
2
n
e
ave
V
V
U
+
=
Gradient
CORPORATION
APPENDIX
B
QUALIFICATIONS
OF
AUTHORS
B­
1
Gradient
CORPORATION
Peter
J.
Drivas,
Ph.
D.
Principal
Consultant
Dr.
Drivas
has
over
20
years
experience
in
the
fields
of
air
quality
modeling,
pesticide
drift,
reactive
chemical
modeling,
hazardous
spill
assessments,
and
indoor
air
pollution.
He
has
managed
numerous
air
quality
and
multimedia
modeling
programs;
has
been
an
expert
witness
on
air
quality
modeling;
and
has
developed
many
innovative
environmental
models,
which
can
predict
ozone
and
photochemical
smog
formation,
soil
gas
infiltration
from
buried
liquid
chemicals
into
houses,
evaporation
from
oil
spills,
and
the
consequences
of
hazardous
spills
of
toxic
materials.
He
is
an
expert
on
numerous
Agency­
approved
and
industry
standard
models
including
ISC,
CALPUFF,
AERMOD,
RPM­
IV,
PLUVUE­
II,
and
others.
He
has
published
two
books
and
over
30
technical
articles
in
the
environmental
field.
Practice
Areas
&

Expertise:

Air
Quality
Modeling
Emission
Source
Characterization
Soil­
Gas
Modeling
Chemical
Engineering
Processes
Accidental
Releases
Education:

Ph.
D.,
Chemical
Engineering,
California
Institute
of
Technology
M.
S.,
Chemical
Engineering,
Massachusetts
Institute
of
Technology
B.
S.,
Chemical
Engineering,
Massachusetts
Institute
of
Technology
Christopher
M.
Long,
Sc.
D.
Senior
Project
Manager
Dr.
Long
is
an
environmental
health
scientist
with
experience
in
the
areas
of
exposure
assessment,
indoor
air
pollution,
human
health
risk
assessment,
and
statistical
data
analysis.
Dr.
Long
has
several
years
consulting
experience
in
the
risk
assessment
field.
At
Gradient,
Dr.
Long
has
been
involved
in
fate
and
transport
analyses,
litigation
support,
and
exposure
modeling.
Prior
to
joining
Gradient,
Dr.
Long
completed
his
doctorate
in
environmental
science
and
engineering
at
the
Harvard
School
of
Public
Health.
While
at
Harvard,
Dr.
Long
conducted
a
comprehensive
study
investigating
the
sources
and
toxicity
of
indoor
particulate
matter
in
residential
homes.
He
received
a
U.
S.
EPA
graduate
fellowship
for
this
work,
and
he
is
first
author
on
several
recent
papers
on
indoor
and
outdoor
particulate
matter.
Practice
Areas
&

Expertise:

Indoor/
Outdoor
Air
Quality
Airborne
Toxicants
Exposure
Assessment/
Modeling
Human
Health
Risk
Assessment
Epidemiology
Education:

Sc.
D.,
Environmental
Science
&
Engineering,
Harvard
School
of
Public
Health
M.
S.,
Environmental
Engineering,
MIT
A.
B.,
Chemistry
and
Environmental
Studies,
Bowdoin
College
20
University
Road
Cambridge,
MA
02138
617­
395­
5000
Peter
J.
Drivas,
Ph.
D.
Principal
Consultant
Areas
of
Expertise
Air
quality
modeling,
chemically
reactive
pollutants,
accidental
releases,
multi­
media
modeling,
chemical
process
analysis,
visibility,
indoor
air
pollution,
program
management.

Education
Ph.
D.,
Chemical
Engineering,
California
Institute
of
Technology,
1974.

S.
M.
and
S.
B.,
Chemical
Engineering,
Massachusetts
Institute
of
Technology,
1970.

Professional
Experience
1996
 
present
GRADIENT
CORPORATION,
Cambridge,
MA
Principal
Consultant.
Chief
scientist
for
air
quality
modeling,
multi­
media
modeling,
indoor
air
modeling,
hazardous
spill
assessments,
modeling
of
reactive
pollutants,
emissions
characterization,
and
chemical
process
analysis.

1989
 
1996
GRADIENT
CORPORATION,
Cambridge,
MA
Principal.
Chief
scientist
for
air
quality
modeling
practice,
hazardous
spill
assessments,
modeling
of
reactive
pollutants,
and
chemical
process
analysis.
Director
of
multi­
media
modeling,
emissions
characterization,
and
indoor
air
pollution
studies.

1983
 
1989
THERMO
ELECTRON
CORPORATION,
Waltham,
MA
Environmental
Director.
Consultant
to
all
Thermo
Electron
divisions
on
air
quality
monitoring
and
modeling,
including
the
use
of
EPA
dispersion
models,
photochemical
models,
and
hazardous
spill
models.

1982
 
1983
ENERGY
RESOURCES
COMPANY,
La
Jolla,
CA
Principal
Scientist.
Directed
development
of
accidental
release
models
and
managed
air
quality
modeling
activities
related
to
permitting.
Designed
fluidized
bed
reactors
to
minimize
emissions.

1979
 
1981
ENVIRONMENTAL
RESEARCH
&
TECHNOLOGY,
Concord,
MA
Senior
Consultant.
Directed
air
quality
modeling
studies,
including
the
use
of
EPA
UNAMAP
and
photochemical
models
for
permitting
of
new
sources.
Developed
visibility
degradation
models
for
compliance
with
PSD
regulations.

1975
 
1978
PACIFIC
ENVIRONMENTAL
SERVICES,
Santa
Monica,
CA
Manager,
Atmospheric
Modeling
Division.
Responsible
for
model
development,
group
management,
and
business
development.
Project
manager
for
environmental
permitting
and
research
studies,
including
ozone
and
mobile
source
modeling.

1974
 
1975
CALIFORNIA
INSTITUTE
OF
TECHNOLOGY,
Pasadena,
CA
Research
Fellow.
Studied
indoor
air
pollution
and
infiltration
rates
in
buildings
by
means
of
a
tracer
gas
technique.
Peter
J.
Drivas,
page
2
Professional
Activities
 
Chairman
of
AWMA
national
technical
committee
on
accidental
releases.
 
Expert
witness
testimony
experience
for
air
quality
modeling
topics.
 
Author
of
approximately
30
journal
articles,
books,
and
conference
presentations.

Professional
Affiliations
American
Institute
of
Chemical
Engineers,
Consultant
to
Environmental
Division
 
Air
and
Waste
Management
Association,
Chairman
of
AT­
4
Accidental
Release
Committee
 
American
Chemical
Society
 
American
Meteorological
Association
Projects
Martin
Marietta
Energy
Systems:
Technical
consultant
on
reactive
chemistry
modifications
to
the
HGSYSTEM
model
to
account
for
UF6
chemistry
and
thermodynamics.
The
chemistry
involved
UF6
flashing
to
a
mixture
of
vapor
and
solid
particles
if
accidentally
released,
reacting
with
water
vapor
to
form
HF
and
UO2F2,
and
the
HF
continuing
to
react
with
water
vapor.
UF6
chemistry
and
thermodynamic
algorithms
were
combined
with
the
HF
chemistry
and
algorithms
in
HGSYSTEM.
The
solutions
were
obtained
by
solving
a
set
of
14
simultaneous
differential
equations
involving
chemistry,
dispersion,
and
thermodynamics.

American
Institute
of
Chemical
Engineers,
Center
for
Chemical
Process
Safety:
Co­
authored
a
guideline
book
describing
the
latest
techniques
to
calculate
the
source
emissions,
transport,
and
dispersion
of
hazardous
vapor
clouds.
Source
emission
techniques
that
were
described
included
gas
and
liquid
jet
releases,
pool
evaporation,
pipeline
breaks,
and
cryogenic
releases.
Topics
included
two­
phase
flow,
reactive
components,
and
calculation
of
multi­
component
releases.

State
of
Alaska,
Department
of
Environmental
Conservation:
Managed
study
to
evaluate
health
and
environmental
impacts
on
animals
and
plants
in
Prince
William
Sound,
Alaska,
caused
by
hydrocarbon
evaporative
emissions
from
the
Exxon
Valdez
oil
spill.
Developed
evaporative
emission
model
for
individual
air
toxics
such
as
benzene,
toluene,
and
xylene
from
oil
spills.
Air
concentrations
resulting
from
the
evaporative
emissions
were
used
to
assess
the
risk
of
adverse
environmental
impacts
in
the
vicinity
of
Prince
William
Sound.

Amoco
Corporation:
Managed
study
to
determine
impacts
of
a
proposed
chemical
plant
expansion
on
ozone
concentrations
and
visibility
in
a
nearby
national
park,
in
support
of
a
Prevention
of
Significant
Deterioration
(
PSD)
operating
permit.
A
reactive
plume
model
was
used
to
evaluate
ozone
concentrations,
and
a
visibility
screening
technique
was
used
to
determine
the
worst­
case
visibility
impairment
caused
by
the
plant
emissions.

Browning­
Ferris
Industries:
Developed
a
health
risk
exposure
assessment
of
stack
emissions
from
a
proposed
medical
waste
incinerator.
Estimated
emission
rates
of
possible
hazardous
substances
released
into
the
air
from
the
incinerator
stack,
including
metals,
dioxins,
furans,
acid
gases,
pathogens,
hydrocarbons,
and
radioisotopes.
Conducted
air
dispersion
modeling
using
the
ISCST
model
for
five
years
of
meteorological
data
to
predict
short­
term
and
long­
term
concentrations
and
resulting
health
risks
at
nearby
resident
receptor
sites.

State
of
California,
Air
Resources
Board:
Managed
an
improved
emission
inventory
for
oil
production
and
refining
emission
sources
in
the
San
Joaquin
Valley
in
California,
for
use
as
input
to
a
photochemical
grid
model.
All
available
emission
factor
models
and
equations
applicable
to
oil
production
facilities
and
refineries
were
reviewed
and
compared,
and
an
estimate
was
made
of
the
statistical
accuracy
of
the
most
appropriate
emission
factor.
Hydrocarbon
emissions
were
apportioned
into
individual
chemical
species
for
use
in
photochemical
modeling.
Peter
J.
Drivas,
page
3
Major
Oil
Company:
Developed
a
mathematical
model
for
the
prediction
of
air
quality
concentrations
resulting
from
the
accidental
releases
of
hazardous
components.
A
new
algorithm
was
developed
for
multicomponent
evaporation
from
a
liquid
spill
mixture.
Also,
techniques
for
calculating
the
evaporation
heat
balance
were
evaluated,
and
a
method
was
developed
to
determine
the
phase
partitioning
of
boiling
compounds.

Insurance
Company:
Directed
scientific
investigation
into
historical
chemical
manufacturing
and
waste
disposal
processes.
Relevant
patents
and
process
flow
sheets
were
reviewed
to
determine
the
basic
process
chemistry
and
the
amount
and
type
of
waste
material
created.
Based
on
the
process
chemistry,
chemical
reaction
calculations
were
performed
to
determine
the
composition
of
the
waste
stream
by­
products.

Thermo
Electron:
Developed
a
mathematical
model
to
predict
evaporation
and
transport
of
pollutants
at
high
temperatures
through
porous
media.
The
model
included
the
effects
of
cylindrical
as
well
as
rectangular
geometry,
considered
the
addition
of
a
layer
that
inhibits
diffusion,
and
included
the
effects
of
variable
pore
size
and
geometry
in
the
porous
medium.

EPA
Region
II:
Evaluated
potential
human
risks
due
to
implementation
of
recommended
remedial
actions
at
a
hazardous
waste
site.
Calculated
emissions
and
air
concentrations
resulting
from
five
different
remedial
activities,
including
soil
excavation,
incineration,
site
capping,
and
sediment
dredging.
Exposure
and
resulting
health
risks
due
to
emission
of
PCB
vapors
and
dust
were
examined
using
EPA­
recommended
air
quality
dispersion
and
deposition
models.

Major
Chemical
Company:
Developed
an
innovative
model
for
evaluating
the
air
emissions
from
buried
hazardous
waste
material,
resulting
in
a
presentation
at
the
1990
Air
and
Waste
Management
Association
meeting.
The
new
model
showed
that
typical
techniques
used
to
calculate
buried
waste
emissions
may
overpredict
air
concentrations
by
an
order
of
magnitude.
Conducted
air
quality
dispersion
modeling
to
estimate
downwind
exposures
and
concentrations.

Browning
Ferris
Industries:
Investigated
air
quality
issues
associated
with
the
expansion
of
a
landfill
in
Minnesota.
Calculated
the
air
exposures
of
nearby
populations
to
potential
releases
of
air
toxics
emissions
from
the
site
by
using
EPA­
recommended
air
quality
models.
Investigated
the
effects
on
the
air
quality
modeling
results
of
variability
in
terrain,
year­
to­
year
changes
in
site
meteorology,
and
the
use
of
rural
vs.
urban
dispersion
coefficients.

Law
Firm:
Developed
a
general
indoor
air
pollution
model
that
can
predict
indoor
concentrations,
as
a
function
of
time,
of
gases,
particulates,
or
fibers
such
as
asbestos.
A
Gaussian
puff
dispersion
model
was
combined
with
a
flow
field
and
general
building
decay
parameters
for
a
comprehensive
model
of
indoor
air
transport
and
dispersion
of
a
point
source
of
emissions.

General
Electric:
Provided
chemical
process
analysis
development
for
the
manufacture
of
a
solid­
state
energy
conversion
device.
Developed
time
and
temperature
process
parameters
for
manufacturing,
both
theoretically
and
experimentally,
and
calculated
chemical
formation
and
degradation
rates
as
a
function
of
temperature.

Government
of
China:
Trained
representatives
from
Beijing
and
Lanzhou,
China,
on
the
theory,
operation,
and
practical
application
of
Gaussian
and
photochemical
air
quality
models.
Developed
a
microcomputer
version
of
the
OZIPM­
2
photochemical
model
to
determine
ozone
control
strategies
in
China.

Consortium
of
Oil
Companies:
Developed
numerical
modeling
techniques
for
predicting
the
air
quality
impact
of
spills
of
cryogenic
materials
from
storage
tanks
and
pipelines,
and
two­
phase
(
gas
and
liquid)
flow
from
high­
pressure
liquid
pipelines.
A
comprehensive
modeling
system
was
developed
for
handling
any
type
of
hazardous
spill.
Peter
J.
Drivas,
page
4
U.
S.
Department
of
Energy:
Designed
a
fluidized
bed
combustion
reactor
to
minimize
air
pollutant
emissions
of
SO2
and
NOx.
A
numerical
model
was
developed
to
calculate
fluid
flow,
mixing,
and
chemical
reactions
inside
a
fluidized
bed
reactor,
and
the
results
of
the
calculations
were
used
to
guide
pilot
plant
experimental
development.

Texaco:
Managed
the
successful
air
quality
permitting
of
an
expansion
of
oil
production
operations
in
California.
Met
with
state
and
local
representatives
and
conducted
emissions
and
air
dispersion
modeling
to
demonstrate
compliance
with
current
regulations.

Consolidated
Edison
of
New
York:
Directed
the
successful
air
quality
permitting
of
a
change
in
power
plant
fuel
from
oil
to
coal,
involving
very
detailed
air
dispersion
modeling
that
considered
"
street
canyon"
effects
in
New
York
City.
Also,
developed
environmental
and
economic
analyses
of
currently
available
and
possible
future
types
of
burners
and
control
equipment
for
reducing
pollutants
from
coal­
fired
power
plants.

State
of
Maine,
Department
of
Environmental
Protection:
Developed
a
liquid
spill
evaporation
model
to
predict
time­
dependent
multicomponent
air
pollution
concentrations
resulting
from
oil
spills.
Results
of
the
model
were
used
to
analyze
the
health
risks
to
residents
near
a
liquid
spill
waste
facility.

Northern
Tier
Pipeline
Company:
Developed
an
improved
visibility
degradation
model,
and
used
this
model
to
predict
the
impact
of
a
proposed
marine
terminal
on
visibility
impacts
in
Washington's
Olympia
National
Park.
Ten
scenic
views,
selected
by
the
National
Park
Service,
were
modeled
to
determine
the
amount
of
visibility
impairment
due
to
emissions
from
the
proposed
marine
terminal.

EPA,
Office
of
Air
Quality
Planning
and
Standards:
Directed
a
major
atmospheric
tracer
study
to
develop
basic
experimental
data
on
dispersion
in
complex
terrain.
Dual
atmospheric
tracers
(
SF6
and
Freon­
11)
were
released
from
different
heights
over
a
small
hill
with
over
50
sampling
locations.
Responsible
for
the
experimental
analysis
and
database
development
for
thousands
of
air
samples.
Results
from
this
study
were
used
to
develop
EPA's
Complex
II
air
quality
model.

Aluminum
Association:
Managed
a
comprehensive
SF6
tracer
study
at
an
aluminum
plant
to
develop
basic
experimental
data
for
the
line­
source
type
of
releases
characteristic
of
aluminum
plants.
Results
from
this
study
were
used
to
develop
EPA's
Buoyant
Line
and
Plume
(
BLP)
model.

EPA,
Region
I:
Used
the
city­
specific
version
of
the
OZIPP
photochemical
model
to
estimate
hydrocarbon
emission
reductions
necessary
to
attain
the
ozone
air
quality
standard
in
Massachusetts,
Connecticut,
and
Rhode
Island.
The
city­
specific
ozone
model
was
run
with
the
specific
UV
intensity,
transported
ozone,
dilution
rate,
and
emission
parameters
for
each
of
five
major
urban
areas
to
determine
the
emission
reductions
necessary
in
each
area
to
attain
the
ozone
standard.

EPA,
Office
of
Air
Quality
Planning
and
Standards:
Developed
procedures
for
the
acquisition
and
compilation
of
emission
information
into
the
form
required
for
input
into
photochemical
air
quality
simulation
models.
Emission
methods
were
applicable
to
both
grid
and
trajectory
photochemical
models.
Techniques
were
developed
for
obtaining
the
necessary
spatial
and
temporal
resolution,
and
for
segregating
hydrocarbon
emissions
into
the
reactive
species
required
by
the
photochemical
model.

State
of
Arizona,
Highway
Department:
Used
a
photochemical
trajectory
model
to
analyze
the
impact
on
ambient
ozone
levels
of
a
proposed
new
highway
in
Phoenix.
Nine
worst­
case
air
trajectories
were
modeled
that
would
maximize
the
ozone
impact
of
the
new
highway
in
major
residential
communities
in
and
near
Phoenix.
The
highway
was
built
after
our
study
concluded
that
there
would
be
only
minor
ozone
impacts.
Peter
J.
Drivas,
page
5
Zinc
Galvanizing
Company:
Directed
an
emissions
monitoring
and
air
quality
dispersion
modeling
study
for
a
zinc
galvanizing
facility
in
Los
Angeles.
The
basic
galvanizing
process
was
studied
to
determine
emission
parameters,
stack
testing
was
conducted,
and
the
emission
results
were
used
as
input
to
an
air
quality
model.
Provided
expert
witness
testimony
on
emissions
and
air
modeling.

United
Airlines:
Performed
an
air
quality
dispersion
modeling
study
for
a
proposed
United
Airlines
food
waste
incinerator
at
Los
Angeles
International
Airport.
Provided
expert
witness
testimony
on
air
quality
modeling
and
the
impact
of
the
incinerator
on
nearby
residents.
The
incinerator
was
successfully
permitted
and
is
currently
operating.

ASARCO:
Monte
Carlo
air
modeling
and
risk
assessment
at
operating
smelter.

Publications
&
Presentations
Brody,
J.
G.,
D.
J.
Vorhees,
S.
J.
Melly,
S.
R.
Swedis,
P.
J.
Drivas,
and
R.
A.
Rudel.
2002.
"
Using
GIS
and
Historical
Records
to
Reconstruct
Residential
Exposure
to
Large­
Scale
Pesticide
Application."
Journal
of
Exposure
Analysis
and
Environmental
Epidemiology,
12:
64­
80.

Drivas,
P.
J.,
P.
A.
Valberg,
B.
L.
Murphy,
and
R.
Wilson.
1996.
"
Modeling
Indoor
Air
Exposure
from
Short­
term
Point
Source
Releases."
Indoor
Air
6:
271­
277.

Valberg,
P.
A.,
P.
J.
Drivas,
S.
M.
McCarthy,
and
A.
Y.
Watson.
1996.
"
Evaluating
the
Health
Impacts
of
Incinerator
Emissions."
J.
Hazardous
Material,
47:
205­
227.

Hanna,
S.
R.,
P.
J.
Drivas,
and
J.
C.
Chang.
1996.
Guidelines
for
Use
of
Source
Emissions
and
Atmospheric
Dispersion
Models
for
Accidental
Releases.
Center
for
Chemical
Process
Safety,
American
Institute
of
Chemical
Engineers,
New
York.

Drivas,
P.
J.
1995.
"
A
Review
of
Source
Emission
Models
for
Accidental
Releases."
Paper
No.
95­
TP54A.
03.
Proceedings:
The
88th
Annual
Meeting
of
the
Air
and
Waste
Management
Association,
San
Antonio,
TX,
June
19­
23.

McCarthy,
S.
M.,
P.
J.
Drivas,
and
R.
J.
Yamartino.
1994.
"
The
Design
and
Evaluation
of
Oil
Production
Emission
Database
Files
for
Input
to
the
SARMAP
Modeling
System."
Proceedings:
Regional
Photochemical
Measurement
and
Modeling
Studies
Conference,
San
Diego,
CA,
November
8­
12.

Murphy,
B.
L.
and
P.
J.
Drivas.
1993.
"
Migration
of
Volatile
Contaminants
into
Buildings."
Proceedings:
Eighth
Annual
Conference
on
Contaminated
Soils,
Amherst,
MA.

Drivas,
P.
J.,
K.
Raabe,
L.
C.
Daly,
and
L.
K.
Zuke.
1993.
"
Air
Toxics
Modeling
of
Excavation
and
Landfilling
Activities."
Paper
93­
RA­
114A.
03,
86th
Annual
Air
and
Waste
Management
Association
Meeting,
Denver,
Co.

Hanna,
S.
R.
and
P.
J.
Drivas.
1993.
"
Modeling
VOC
Emissions
and
Air
Concentrations
from
the
Exxon
Valdez
Oil
Spill."
Journal
of
the
Air
and
Waste
Management
Association,
43:
298­
309.

Drivas,
P.
J.,
B.
L.
Murphy,
and
P.
A.
Valberg.
1992.
"
Exposure
Modeling
of
Indoor
Sources
of
Particulates
or
Fibers."
Proceedings:
Society
for
Risk
Analysis
­
1992
Annual
Meeting,
San
Diego,
CA.

Drivas,
P.
J.,
P.
A.
Valberg,
and
T.
D.
Gauthier.
1991.
"
Health
Assessment
of
Air
Toxics
Emissions
from
Alternative
Fuels."
Paper
91­
107.6,
84th
Annual
Air
and
Waste
Management
Association
Meeting,
Vancouver,
BC.
Peter
J.
Drivas,
page
6
Drivas,
P.
J.
and
L.
C.
Daly.
1991.
"
Calculation
of
Evaporative
Emission
Rates
of
Air
Toxics
from
a
Multicomponent
Liquid
Spill."
Paper
91­
84.7,
84th
Annual
Air
and
Waste
Management
Association
Meeting,
Vancouver,
BC.

Drivas,
P.
J.
1991.
"
Validation
of
Hazardous
Spill
Emission
Models."
Invited
Paper,
International
Conference
and
Workshop
on
Mitigating
the
Consequences
of
Accidental
Releases
of
Hazardous
Materials,
New
Orleans.

Drivas,
P.
J.,
A.
P.
Toole,
and
S.
C.
Gnewuch.
1990.
"
The
Effects
of
Global
Warming
and
Increased
UV
Radiation
on
Urban
Ozone
Concentrations."
Paper
40C,
American
Institute
of
Chemical
Engineers,
Summer
National
Meeting,
San
Diego,
CA.

Drivas,
P.
J.,
D.
H.
Bass,
and
B.
L.
Murphy.
1990.
"
Atmospheric
Emissions
from
Buried
Hazardous
Waste."
Paper
90­
74.4,
83rd
Annual
Air
and
Waste
Management
Association
Meeting,
Pittsburgh,
PA.

Hanna,
S.
R.,
and
P.
J.
Drivas.
1987.
Guidelines
for
Use
of
Vapor
Cloud
Dispersion
Models.
Center
for
Chemical
Process
Safety,
American
Institute
of
Chemical
Engineers.

Drivas,
P.
J.
1986.
"
Two­
dimensional
Resistance
Analysis
in
a
Thermoelectric
Multicouple."
Proceedings:
21st
Intersociety
Energy
Conversion
Engineering
Conference,
San
Diego,
CA,
pp.
1353­
1356.

Drivas,
P.
J.
1985.
"
Prediction
of
Multicouple
Performance."
Proceedings:
Fifth
Working
Group
Meeting
on
Thermoelectrics,
Pasadena,
CA.

Drivas,
P.
J.,
J.
S.
Sabnis,
and
L.
H.
Teuscher.
1983.
"
Simulation
of
Pipeline
and
Tank
Storage
Failures."
Oil
and
Gas
Journal:
162­
169
(
September).

Drivas,
P.
J.
1982.
"
Calculation
of
Evaporative
Emissions
from
Multicomponent
Liquid
Spills."
Environmental
Science
and
Technology,
16:
726­
728.

Heinold,
D.
W.,
P.
J.
Drivas,
D.
A.
Hansen,
and
T.
F.
Lavery.
1982.
"
Acid
Rain
Impact
Assessment:
From
Stack
to
Stream."
Proceedings:
AMS/
APCA
Third
Joint
Conference
on
Applications
of
Air
Pollution
Meteorology,
San
Antonio,
TX.

Drivas,
P.
J.
and
D.
W.
Heinold.
1981.
"
Visibility
Impact
Analysis
of
a
Marine
Oil
Terminal."
Proceedings:
Fifth
Symposium
on
Turbulence,
Diffusion,
and
Air
Pollution.
Atlanta,
GA.

Drivas,
P.
J.,
A.
Bass,
and
D.
W.
Heinold.
1981.
"
A
Plume
Blight
Visibility
Model
for
Regulatory
Use."
Atmospheric
Environment
15:
2179­
2184.

Drivas,
P.
J.,
K.
H.
Wilson,
and
L.
W.
Wayne.
1979.
"
A
Case
Study:
Use
of
City­
Specific
EKMA
in
Massachusetts,
Connecticut,
and
Rhode
Island."
Proceedings:
Specialty
Conference
on
Ozone/
Oxidants,
Houston,
TX.

Drivas,
P.
J.
1978.
"
Emission
Inventory
Requirements
for
Photochemical
Air
Quality
Simulation
Models."
Proceedings:
Specialty
Conference
on
Emission
Factors
and
Inventories,
Anaheim,
CA.

Wayne,
L.
W.
and
P.
J.
Drivas.
1978.
"
Sensitivity
of
the
Empirical
Kinetic
Modeling
Approach
to
Input
Data
and
Local
Conditions."
Paper
78­
72.2,
71st
Annual
APCA
Conference,
Houston,
TX.

Drivas,
P.
J.
and
L.
W.
Wayne.
1977.
"
Sensitivity
Tests
of
a
Lagrangian
Photochemical
Air
Quality
Simulation
Model."
Paper
78­
10.3,
71st
Annual
APCA
Conference,
Houston,
TX.
Peter
J.
Drivas,
page
7
Drivas,
P.
J.,
M.
Chan,
and
L.
W.
Wayne.
1977.
"
Validation
of
an
Improved
Photochemical
Air
Quality
Simulation
Model."
Proceedings:
AMS/
APCA
Joint
Conference
on
Applications
of
Air
Pollution
Meteorology,
Salt
Lake
City,
UT.

Drivas,
P.
J.
1976.
Emissions
from
Hot­
Dip
Galvanizing
Processes.
EPA
Report
No.
EPA­
905/
4­
76­
002,
USEPA,
Region
V,
Chicago,
IL.
Available
as
Document
PB251910,
U.
S.
Dept.
of
Commerce,
National
Technical
Information
Service,
Springfield,
VA.
March.

Drivas,
P.
J.
1975.
"
On
the
Measurement
of
Ambient
Halogenated
Hydrocarbons."
Proceedings:
Caltech
Air
Quality
Symposium,
Pasadena,
CA.

Drivas,
P.
J.
and
F.
H.
Shair.
1974.
"
Probing
the
Air
Flow
Within
the
Wake
Downwind
of
a
Building
by
Means
of
a
Tracer
Technique."
Atmospheric
Environment
8:
1165­
1175.

Drivas,
P.
J.
and
F.
H.
Shair.
1974.
"
A
Tracer
Study
of
Pollutant
Transport
and
Dispersion
in
the
Los
Angeles
Area."
Atmospheric
Environment
8:
1155­
1163.

Griffith,
G.
A.,
P.
J.
Drivas,
and
F.
H.
Shair.
1974.
"
An
Inexpensive
Remote
Sequential
Air
Sampler."
Journal
of
the
Air
Pollution
Control
Association
24:
776­
777.

Drivas,
P.
J.
and
F.
H.
Shair.
1974.
"
Dispersion
of
an
Instantaneous
Crosswind
Line
Source
of
Tracer
Released
from
an
Urban
Highway."
Atmospheric
Environment
8:
475­
484.

Drivas,
P.
J.,
P.
G.
Simmonds,
and
F.
H.
Shair.
1972.
"
Experimental
Characterization
of
Ventilation
Systems
in
Buildings."
Environmental
Science
and
Technology
6:
609­
614.

Patent
Shair,
F.
H.,
P.
G.
Simmonds,
R.
B.
Leighton,
and
P.
J.
Drivas.
1975.
"
Technique
and
System
for
Coding
and
Identifying
Materials."
20
University
Road
Cambridge,
MA
02138
617­
395­
5000
Christopher
M.
Long,
Sc.
D.
Environmental
Scientist
clong@
gradientcorp.
com
Areas
of
Expertise
Public
health
and
exposure
assessment,
with
expertise
in
indoor/
outdoor
air
pollution
and
particulate
matter;
air
dispersion
modeling;
epidemiology;
human
health
risk
assessment;
risk
communication;
statistical
data
analysis.

Education
Sc.
D.,
Environmental
Science
&
Engineering,
Harvard
School
of
Public
Health,
2000.

M.
S.,
Environmental
Engineering,
Massachusetts
Institute
of
Technology,
1995.

A.
B.,
Chemistry
and
Environmental
Studies,
summa
cum
laude,
Bowdoin
College,
1993.

Professional
Experience
2000
 
Present
GRADIENT
CORPORATION,
Cambridge,
MA
Senior
Project
Manager.
Evaluate
human
exposure
and
health
effects
of
environmental
pollutants,
specializing
in
airborne
gases
and
particles.
Investigate
indoor
and
outdoor
air
quality
problems,
and
perform
air
dispersion
and
exposure
modeling.
Conduct
human
health
risk
assessments
and
worker
safety
evaluations,
and
review
and
interpret
epidemiological
and
toxicological
studies.
Prepare
technical
analyses,
expert
reports,
and
risk
communication
materials.

1997
 
2000
HARVARD
SCHOOL
OF
PUBLIC
HEALTH,
Boston,
MA
Research/
Teaching
Assistant.
Designed
and
conducted
indoor
air
particle
characterization
study
of
nine
Boston­
area
homes.
Also
served
as
teaching
assistant
for
two
graduate
courses:
Seminar
in
Risk
Analysis,
Management,
and
Communication
and
Air
Pollution:
Particles
and
Gases.

1995
 
1997
MENZIE­
CURA
&
ASSOCIATES,
INC.,
Chelmsford,
MA
Environmental
Scientist/
Risk
Assessor.
Conducted
human
health
and
ecological
risk
assessments
for
state
and
federal
hazardous
waste
sites.
Modeled
fate
and
transport
of
organic
and
inorganic
contaminants
in
all
environmental
media.
Responsibilities
also
included
project
management,
proposal
writing,
and
litigation
support.
Participated
in
environmental
site
assessments
and
field
sampling
activities
of
aquatic
and
terrestrial
habitats.
OSHA­
certified
40­
hour
training.

1993
 
1995
MASSACHUSETTS
INSTITUTE
OF
TECHNOLOGY,
Cambridge,
MA
Research
Assistant.
Conducted
research
in
trace
organic
pollutant
laboratory.
Modeled
the
fate
and
transport
of
sewage­
derived
linear
alkylbenzenes
(
LABs)
in
the
Gulf
of
Maine.

1992
NASA
GODDARD
SPACE
FLIGHT
CENTER,
Greenbelt,
MD
Research
Assistant.
Selected
as
summer
intern
in
Summer
Institute
on
Atmospheric
and
Hydrospheric
Sciences;
worked
with
atmospheric
scientists
in
GSFC's
Atmospheric
Chemistry
and
Radiation
Branch.
Used
a
photochemical
box
model
to
explore
the
potential
for
ozone
depletion
in
the
Northern
Hemisphere
stratosphere
at
middle
and
low
latitudes.
Christopher
M.
Long,
page
2
Professional
Activities
 
Invited
technical
peer
reviewer
for
the
Journal
of
the
Air
&
Waste
Management
Association,
Environmental
Science
&
Technology,
Environmental
Health
Perspectives,
and
Journal
of
Exposure
Analysis
and
Environmental
Epidemiology.

Awards/
Honors
 
U.
S.
EPA
STAR
Graduate
Fellow,
1998­
2000
 
Phi
Beta
Kappa
 
Student
abstract/
presentation
award
at
1999
ISEA/
ISEE
Annual
Conference
in
Athens,
Greece
Professional
Associations
American
Chemical
Society
(
ACS)
 
International
Society
of
Exposure
Analysis
(
ISEA)
 
Air
&
Waste
Management
Association
(
AWMA)
 
Boston
Risk
Analysis
Group
Projects
State
of
Maine:
Assisted
in
the
development
of
a
trial
guideline
for
protecting
residents
from
inhalation
exposure
to
indoor
petroleum
vapors
released
from
home
fuel
oil
spills.
Wrote
indoor
sampling
guidance.

Metropolitan
District
Commission
(
MDC):
Performed
mass
balance
calculations
for
mercury
in
Wachusett
and
Quabbin
Reservoirs.
Conducted
extensive
literature
review
on
environmental
Hg
cycling.
Wrote
technical
report.

Private
Client:
Provided
technical
analysis
of
fate
and
transport
of
zinc
and
fluoride
emissions
in
subsurface
environment
for
an
aluminum
manufacturing
facility.
Evaluated
fluoride
toxicity
to
aquatic
organisms
and
livestock
and
developed
ambient
water
quality
criteria
based
on
U.
S.
EPA
guidelines.

Law
Firm:
Reviewed
extensive
body
of
epidemiological
studies
of
ozone
health
effects
and
helped
develop
technical
document
for
litigation
support.

Private
Client:
Managed
and
conducted
MCP
Method
3
risk
characterizations
for
a
chain
of
Massachusetts
gas
stations.
Contaminants
of
interest
included
BTEX
and
MTBE.
Modeled
indoor
air
concentrations
and
collected
indoor
VOC
samples
using
Summa
canisters
to
validate
model
findings.
Conducted
wetland
sampling
and
performed
screening­
level
ecological
risk
assessments
Private
Client:
Wrote
scope
of
work,
managed,
and
performed
MCP
Method
3
human
health
risk
assessment
for
a
former
electronics
manufacturer
with
subsurface
dissolved­
phase
chlorinated
hydrocarbon
contamination.
Indoor
air
modeling
performed
using
vapor
intrusion
model.
Risk
to
town
drinking
water
wells
assessed.

Private
Client:
Developed
risk­
based
soil
cleanup
levels
for
BTEX
and
PAH
compounds
at
a
site
with
pervasive
asphalt
contamination.
Provided
technical
support
during
site
remedial
actions.

Massachusetts
Bays
Program:
Assisted
in
a
project
designed
to
quantify
point
and
nonpoint
sources
of
nitrogen
to
Massachusetts
harbors
and
coastal
embayments
and
to
evaluate
the
potential
for
eutrophication.
Delineated
watersheds
and
subwatersheds
using
topographic
maps.

ASTM
Committee
E­
50:
Authored
sections
on
chemical
properties
and
contaminant
behavior
in
ASTM
Standard
Provisional
Guide
for
Risk­
Based
Corrective
Action
(
PS
104­
98).
Christopher
M.
Long,
page
3
Private
Client:
Performed
U.
S.
EPA
screening­
level
ecological
risk
assessments
for
two
former
submarine
manufacturing
facilities.
Extensive
list
of
contaminants
of
concern
including
metals,
PAHs,
and
PCBs.

Publications
Long,
C.
M.
and
J.
A.
Sarnat.
2003.
Assessing
Indoor­
Outdoor
Relationships
and
Infiltration
Behavior
of
Elemental
Components
of
Ambient
PM2.5.
Manuscript
submitted
to
Aerosol
Science
&
Technology.

Sarnat,
J.
A.,
C.
M.
Long,
P.
Koutrakis,
B.
A.
Coull,
J.
Schwartz,
and
H.
H.
Suh.
2002.
Using
Sulfur
as
a
Tracer
of
Outdoor
Fine
Particulate
Matter.
Environ.
Sci.
Technol.
36:
5305­
5314.

Long,
C.
M.,
H.
H.
Suh,
L
Kobzik,
P.
J.
Catalano,
Y.
Ning,
and
P.
Koutrakis.
2001.
A
Pilot
Investigation
of
the
Relative
Toxicity
of
Indoor
and
Outdoor
Fine
Particles:
In­
vitro
Effects
of
Endotoxin
and
Other
Particulate
Properties.
Environ.
Health
Perspect.
109:
1019­
1026.

Long,
C.
M.,
H.
H.
Suh,
and
P.
Koutrakis.
2001.
Using
Time­
and
Size­
Resolved
Particulate
Data
to
Quantify
Penetration
and
Deposition
Behavior.
Environ.
Sci.
Technol.
25:
2089­
2099.

Gustafsson,
Ö,
C.
M.
Long,
J.
MacFarlane,
and
P.
M.
Gschwend.
2001.
Fate
of
Linear
Alkylbenzenes
(
LABs)
Released
to
the
Coastal
Environment
near
Boston
Harbor.
Environ.
Sci.
Technol.
25:
2040­
2048.

Long,
C.
M.,
H.
H.
Suh,
and
P.
Koutrakis.
2000.
Characterization
of
indoor
particle
sources
using
continuous
mass
and
size
monitors.
J.
Air
&
Waste
Manage.
Assoc.
50:
1236­
1250.

Menzie,
C.
A.,
J.
S.
Freshman,
and
C.
M.
Long.
1997.
Developing
Environmentally
Acceptable
Endpoints
for
Soil
Based
on
Ecological
Considerations.
In
Proceedings
for
the
Air
&
Waste
Management
Association's
90th
Annual
Meeting
&
Exhibition,
Toronto,
Ontario,
June
8­
13.

Presentations
Long,
C.
M.
and
B.
D.
Beck.
2002.
An
Evaluation
of
Potential
Human
Exposures
to
Trace
Metals
and
Radionuclides
in
Construction
and
Building
Materials
Containing
Coal
Combustion
Products.
Poster
presentation
at
2002
International
Society
of
Exposure
Assessment
(
ISEA)/
International
Society
of
Environmental
Epidemiology
(
ISEE)
Annual
Conference,
Vancouver,
August
11­
15,
2002.

Long,
C.
M.,
H.
H.
Suh,
and
P.
Koutrakis.
2001.
Understanding
Indoor
Exposures
to
Ambient
Particulate
Matter:
Estimates
of
Penetration
Efficiencies
and
Deposition
Rates
for
Residential
Homes.
Poster
Platform
Presentation
at
the
2001
Society
for
Risk
Analysis
Annual
Meeting,
Seattle,
WA,
December
2­
5,
2001.

Sarnat,
J.
A.,
C.
M.
Long,
P.
Koutrakis,
and
H.
H.
Suh.
2001.
Evaluating
Tracers
of
Ambient
PM2.5.
Platform
Presentation
at
the
ISEA
2001
Conference,
Charleston,
SC,
November
4­
8,
2001.

Long,
C.
M.,
H.
H.
Suh,
and
P.
Koutrakis.
2000.
Using
Time­
and
Size­
resolved
Particulate
Data
to
Investigate
Infiltration
and
Deposition
Behavior.
Platform
presentation
at
the
ISEA
2000
Conference,
Monterey
Peninsula,
CA,
October
24­
27.

Long,
C.
M.,
H.
H.
Suh,
and
P.
Koutrakis.
2000.
Using
Time­
and
Size­
resolved
Particulate
Data
to
Investigate
Infiltration
and
Deposition
Behavior.
Platform
presentation
at
the
AWMA
PM2000
Specialty
Conference,
Charleston,
SC,
January
24­
28.

Long,
C.
M.,
H.
H.
Suh,
and
P.
Koutrakis.
2000.
Characterization
of
Indoor
Particle
Sources
Using
Continuous
Mass
and
Size
Monitors.
Poster
presentation
at
the
AWMA
PM2000
Specialty
Conference,
Charleston,
SC,
January
24­
28.
Christopher
M.
Long,
page
4
Long,
C.
M.,
H.
H.
Suh,
and
P.
Koutrakis.
1999.
Characterization
of
Indoor
Particulate
Source
Strengths
Using
Continuous
Mass
and
Size
Monitors.
Platform
presentation
at
1999
Annual
ISEE/
ISEA
Conference,
Athens,
Greece,
September
5­
8.

Bernays,
W.
H.,
D.
J.
Vorhees,
C.
M.
Long,
and
P.
Eremita.
1997.
Trial
Guideline
for
Protecting
Residents
from
Inhalation
Exposure
to
Petroleum
Vapors.
Poster
presentation
at
1997
Annual
Meeting
of
the
Society
for
Risk
Analysis,
Washington,
DC,
December
7­
10.

Invited
Talks
Long,
C.
M.
and
J.
A.
Sarnat.
2003.
Infiltration
Behavior
of
PM2.5
Chemical
Components:
Implications
for
Exposure
Assessment
and
Epidemiological
Associations.
Platform
Presentation
at
the
Particulate
Matter:
Atmospheric
Sciences,
Exposure
and
the
Fourth
Colloquium
on
PM
and
Human
Health,
Pittsburgh,
PA,
March
31­
April
4,
2003.
