Document ID: EPA-HQ-OAR-2007-0562-0431
Agency: epa
Document Type: Supporting & Related Material
Title: 
Posted Date: 2009-11-13T05:00Z

12/22/08						

Technical Analysis

Attachment 1

Iowa

Area Designations For the 

24-Hour Fine Particle National Ambient Air Quality Standard

The table below identifies the counties in Iowa that EPA has designated
as not attaining the 2006 24-hour fine particle (PM2.5) standard.  A
county (or part thereof) is designated as nonattainment if it has an air
quality monitor that is violating the standard or if the county is
determined to be contributing to the violation of the standard in a
nearby area. 

 

Area 	Iowa Recommended Nonattainment Counties	EPA’s Designated
Nonattainment Counties

Davenport, IA	Scott County (partial) 

A portion of the City of Davenport described as follows: 

Northern Boundary  =  West Locust Street, to: 

Western Boundary   =  North Utah Avenue / South Utah Avenue   Southern
Boundary  =  U.S. Highway 61 (locally known as West River Drive), to: 
Eastern Boundary    =  Schmidt Road to: Rockingham Road, to:  South Pine
Street, to:  North Pine Street, to:  West 3rd Street, to:  Waverly Road,
ending at West Locus Street	Scott County (partial) 

 

Entire townships:   Buffalo, Davenport, Pleasant Valley, Sheridan

Partial townships:

1)  Blue Grass 

a)  portion contained within the city limits of Blue Grass

b)  portion contained within the city limits of Davenport 

2)  Hickory Grove

a)  portion contained within the city limits of Davenport

3)  Lincoln

a)  portion contained within the city limits of Davenport

EPA has designated the remaining counties in the state as
“unclassifiable/attainment.”  

EPA Technical Analysis for Davenport, Iowa

Introduction  

Pursuant to section 107(d) of the Clean Air Act, EPA must designate as
nonattainment those areas that violate the NAAQS and those nearby areas
that contribute to the violations.  This technical analysis for
Davenport, Iowa identifies the counties with monitors that violate the
24-hour PM2.5 standard and evaluates nearby counties for contributions
to fine particle concentrations in the area.  EPA has evaluated these
counties based on the weight of evidence of the following nine factors
recommended in EPA guidance and any other relevant information:  

- pollutant emissions

- air quality data

- population density and degree of urbanization

- traffic and commuting patterns

- growth

- meteorology

- geography and topography

- jurisdictional boundaries

- level of control of emissions sources

EPA also used analytical tools and data such as pollution roses, fine
particle composition monitoring data, back trajectory analyses, and the
contributing emission score (CES) to evaluate these areas. (See
additional discussion of the CES under factor 1 below.)

 

Figure A is a map of the counties in the vicinity of the nonattainment
area and other relevant information such as the locations and design
values of air quality monitors, and the metropolitan area boundary.

Davenport-Moline-Rock Island , IA-IL 2006 24-hr PM2.5 Nonattainment
Area

Figure A 

Figure B- Nonattainment Area Designation Boundary.  Final boundary is
noted in orange.

In a letter dated November 2007, Iowa recommended that all of the
counties in Iowa be designated as attainment based on air quality data
from 2004-2006.  EPA determined that a monitor in Scott County, Iowa,
had a violation of the 2006 24-hour PM2.5 standards based on air quality
data from 2005-2007.  In response to EPA’s notification of this new
violation and the request for a designation recommendation, in a letter
dated May 30, 2008, Iowa recommended that EPA delay promulgating any
designation for Scott County for one year.  In a subsequent letter,
dated July 29, 2008, Iowa requested that, if EPA could not grant a
one-year extension of the designation, that EPA designate only a portion
of Scott County as nonattainment for the 2006 24-hour PM2.5 standard
based on air quality data from 2005-2007.  All air quality data are from
Federal Reference Method (FRM) and Federal Equivalent Method (FEM)
monitors located in the state. 

EPA found that there was sufficient information to make a designation
determination.  (Extensions of the statutory deadline for initial
designations are based on sufficiency of monitoring data, and sufficient
monitoring data exists, as described in this TSD.)  EPA took Iowa’s
recommendation to designate nonattainment a portion of the City of
Davenport in Scott County under consideration, but finds that the
information provided does not adequately support the designation as
recommended by the State, but instead supports a larger partial county
designation as shown in Figure B.  Section 107 of the Clean Air Act
defines a nonattainment area as an area that is violating the standard
or an area that is contributing to the violation. The following is a
technical analysis for the Iowa (EPA Region 7) portion of the Davenport
area. 

Factor 1:  Emissions data

For this factor, EPA evaluated county level emission data for the
following PM2.5 components and precursor pollutants:  “PM2.5 emissions
total,” “PM2.5 emissions carbon,” “PM2.5 emissions other,”
“SO2,” “NOx,” “VOCs,” and “NH3.”  “PM2.5 emissions
total” represents direct emissions of PM2.5 and includes:   “PM2.5
emissions carbon,” “PM2.5 emissions other”, primary sulfate (SO4),
and primary nitrate.  (Although primary sulfate and primary nitrate,
which are emitted directly from stacks rather than forming in
atmospheric reactions with SO2 and NOx, are part of “PM2.5 emissions
total,” they are not shown in Table 1 as separate items).  “PM2.5
emissions carbon” represents the sum of organic carbon (OC) and
elemental carbon (EC) emissions, and “PM2.5 emissions other”
represents other inorganic particles (crustal).  Emissions of SO2 and
NOx, which are precursors of the secondary PM2.5 components sulfate and
nitrate, are also considered.  VOCs (volatile organic compounds) and NH3
(ammonia) are also potential PM2.5 precursors and are included for
consideration. Emissions data were derived from the 2005 National
Emissions Inventory (NEI), version 1.  See
http://www.epa.gov/ttn/naaqs/pm/pm25_2006_techinfo.html.

 

EPA also considered the Contributing Emissions Score (CES) for each
county.  The CES is a metric that takes into consideration emissions
data, meteorological data, and air quality monitoring information to
provide a relative ranking of counties in and near an area with a
monitored violation.  Note that this metric is not the exclusive
analytical tool used for considering data for these factors.  A summary
of the CES is included in attachment 2, and a more detailed description
can be found at
http://www.epa.gov/ttn/naaqs/pm/pm25_2006_techinfo.html#C.

Table 1 shows emissions of PM2.5 and precursor pollutant components
(given in tons per year) and the CES for violating and potentially
contributing counties in the Davenport area.  Counties are listed in
descending order by CES.

County	State Recommended Nonattainment?	CES	PM2.5

emissions 

total

(tpy)	PM2.5

emissions 

carbon

(tpy)	PM2.5

emissions 

other

(tpy)	SO2

(tpy)	NOx

(tpy)	NH3

(tpy)	VOCs

(tpy)

Scott, IA	Yes, Partial	100	2,034	395	1,639	9,173	11,317	1,986	9,323

Muscatine, IA	Yes, Partial	80	1,702	283	1,419	27,020	10,717	1,083	4,910

Clinton, IA	No	52	2,711	354	2,357	11,506	13,217	4,870	11,503

Rock Island, IL	No	27	932	269	663	2,169	6,140	664	7,359

Henry, IL	No	7	1,273	252	1,021	268	6,648	2,805	3,431

Mercer, IL 	No	4	793	149	644	133	1,120	1,026	1,469

Table 1- PM2.5 Related Emissions and Contributing Emissions Score

Table 1 shows emissions of PM2.5 and precursor pollutants’ components
(given in tons per year (tpy)) and the CES for violating and potentially
contributing counties in the Davenport area. A review of this data shows
that Iowa counties contribute 68% of the total PM2.5 emissions, 97% of
the total SO2 emissions, 71% of the total NOx emissions and 68% of the
total VOC emissions in the areas EPA evaluated for this designation.
Although emissions from Clinton County, IA (especially for SO2 and NOx)
are greater than those of Scott County, IA, the EPA eliminated Clinton
County, IA from consideration for inclusion into the Davenport
nonattainment area boundary based on a more detailed assessment of
meteorology data, which is explained in greater detail under Factor 6,
and information about significant reductions in emissions from sources
in that areas, which is described under Factor 9 of this document.   

In an August 2008 letter (the “120-day letter”) EPA notified the
State of its intent to designate separate nonattainment areas for Scott
County, IA and Muscatine County, IA.  EPA determined that these two
counties are in separate Core Based Statistical Areas (CBSA) and should
be separate nonattainment areas.   A portion of Muscatine County, IA is
being designated as a separate nonattainment area.  

In addition to reviewing emissions data from a county-level, an
evaluation of the emissions from local point and area sources near the
violating monitor were also conducted.  Because of the form of the
standard (24-hour average) and the rural nature of the area surrounding
Davenport, local sources are critical in terms of contributions to
ambient PM2.5 concentrations on exceedance days.  

A)  Point Source Emissions

Direct PM2.5 emissions from the major sources located in Scott County
and nearby areas are categorized in Table 1.1.  The emissions from Iowa
sources plotted in Table 1.1 was obtained from the 2002 NEI.  Table 1.1
provides Scott County total emissions of direct PM2.5 from major point
sources, with emission totals in tons per year.  Table 1.1 shows a value
of 978.6 tpy of PM2.5 emissions for all of Scott County.  Figure 1 shows
that all major point sources of direct PM2.5 in Scott County are located
within the nonattainment boundary identified above.  The nonattainment
area accounts for 100% of the total point sources of direct PM2.5
emissions in Scott county compared to just 6% of the total direct PM2.5
emissions for this area that would have been contained in the State’s
recommended boundary (point sources included in the State’s
recommended boundary are noted by an asterisk(*)).

Scott County Point Sources NEI 2002 (tons per year)

FACILITY NAME	CITY	NOx	PM2.5 	SO2

ARCH MIRROR NORTH	BETTENDORF	0	0.14	 

LAFARGE NORTH AMERICA INC	BUFFALO	1766	76	4963

JOHN DEERE - DAVENPORT WORKS	DAVENPORT	6.206	9.29	0.175

ALCOA INC	BETTENDORF	240.5	346	1.78

NICHOLS ALUMINUM CASTING	DAVENPORT	54.08	53.8	0.26

KRAFT FOODS  INC  - DAVENPORT	DAVENPORT	117.6	54.1	336.2

MIDAMERICAN ENERGY CO  - RIVERSIDE STATION	BETTENDORF	2102	230	2329

LINWOOD MINING & MINERAL CORPORATION	DAVENPORT	280.6	31.9	 

SCOTT AREA SANITARY LANDFILL	DAVENPORT	0.005	22.9	 

SIVYER STEEL	BETTENDORF	23.2	87.8	3.458

BLACKHAWK FOUNDRY & MACHINE (*)	DAVENPORT	3.064	65.9	 

QUAD CITY DRUM RECYCLING COMPANY	DAVENPORT	0	0.13	 

NICHOLS ALUMINUM - DAVENPORT	DAVENPORT	12.67	0.76	0.06

 	TOTAL	4606	979	7634

Table 1.1- Emissions from Major Point Sources in Scott County.  

The State asserted that several Scott County point sources could be
eliminated from further study by examining their contribution of direct
PM2.5 to the 300 Wellman monitor (the violating monitor located near the
Blackhawk Foundry) based on a commonly used screening method that
divides distance by total emissions (Q/d).  This method was used by the
State to support its conclusion that a single point source nearest the
violating monitor, Blackhawk Foundry, is the primary contributor to
violations at this monitor.  The State also conducted air dispersion
modeling using AERMOD to demonstrate the potential of local point
sources to contribute direct PM2.5 emissions to the violating monitor
which will be described in detail below.  Generally, the State asserted
that the contribution from point sources other then the Blackhawk
Foundry is insignificant.  The EPA can not support this position.  The
violating monitor location did not have speciated data available for
study; therefore the State could not provide conclusive data from a
filter analysis to demonstrate overwhelming contribution from the
Foundry, or to confirm insignificant contributions from other nearby
sources.   Even if it is correct that the Blackhawk Foundry is a
“primary” contributor to ambient PM2.5 levels at the violating
monitor, it is not the exclusive source of contribution to the total
mass of ambient PM2.5 at that monitor.  EPA concludes that additional
sources in this area are also contributing to the aggregate amount of
ambient PM2.5 at the violating area, as section 107(d) contemplates that
term.  

 Figure 1- Point sources in Scott County, IA.

B)  Other Source Emissions

EPA also examined other sources of emissions utilizing 2002 NEI.  The
other emissions are grouped into three source categories:  onroad,
offroad, nonpoint sources (also known as area sources).  In the charts
and discussion below, these three categories are compared to the point
source emissions already discussed.  The onroad source generally
characterizes the tailpipe emissions associated with typical interstate,
highway, and secondary roadway traffic.  Typical offroad sources include
construction, mining, and agricultural vehicular emissions.  The
nonpoint source category is largely derived using population density to
determine emissions, but also includes dust from paved and unpaved
roads, agricultural tilling, and construction projects (roads, buildings
sites etc.).

Figure 1.1-Area Source (also known as Nonpoint Source) Emissions, Scott
County

Figure 1.2-Total PM2.5 Emissions, Scott County.

In Scott County, nonpoint source direct PM2.5 emissions are almost half
of the total county emissions, as shown in Figure 1.2, and are roughly
equivalent to point source emissions.  Outside of rural-based
agricultural activities, such as tilling and road dust, much of this
direct PM2.5 is attributed to area sources that are based on population
activities.  EPA’s promulgated nonattainment area boundary captures
89% of the population in Scott County, so a majority of the
population-based area sources are captured in the nonattainment area
boundary.

Figure 1.3-SO2 Emissions from Various Source Categories, Compiled from
EPA’s 2002 NEI.

A review of the emission inventories reveals that SO2 emissions are
predominantly produced by electrical generating units and other
industrial (major point source) coal-fired boilers (see Figure 1.3). 
All of the large Scott County point sources are contained within the
boundary designated as nonattainment by the EPA, in order to encompass
the sources that may be contributing to violations in the area to ensure
an adequate boundary for evaluation of potential control strategies for
the area.

Figure 1.4- NOx Emissions from Various Source Categories, Compiled from
EPA’s 2002 NEI. 

The distribution of NOx emissions among source categories is shown in
Figure 1.4.  Onroad and offroad NOx emissions from vehicles contribute a
significant percentage of the county emission inventory totals in the
more urbanized area.  In Scott County, approximately 54% of the NOx
emissions and VOC emissions are attributable to mobile sources.  Mobile
source NOx and VOC emissions are also discussed under Factor 4 of this
document.  The remainder of the NOx is attributable to the point and
nonpoint source categories.  EPA’s promulgated nonattainment area
boundary for this area encompasses the urbanized area in and around
Davenport, IA and therefore captures a majority of the mobile source NOx
and PM2.5 emissions in Scott County.  For example, approximately 64% of
the total highway miles in the county are within the nonattainment area
boundary.  

C)  Modeling

As discussed below modeling analysis is not required as part of the
designation process.  However,  the State did conduct such analysis and
did provide its analysis to the EPA for review in response to EPA’s
120-day letter.  To demonstrate the impact of a local emissions’
contribution to the violating monitor in Scott and Muscatine counties,
the State conducted dispersion modeling using AERMOD and photochemical
modeling using CAMx.  This detailed information was submitted to the EPA
in October of 2008 for review.  AERMOD was used to demonstrate the
importance of nearby sources in contributing to monitored exceedances.
The State ran separate AERMOD simulations to compare predicted
concentrations with monitored data for the years 2005-2007.  For each of
the three years, a simulation was run for each of the three monitors in
the Davenport area (Jefferson, Adams and 300 Wellman) totaling nine
simulations.  Each simulation included a 60 degree arc of receptors (the
Blackhawk receptor arc), equidistant from Blackhawk Foundry’s Cupola
stack, centered on the 300 Wellman monitor.  The State utilized
emissions inputs based on the actual PM2.5 emission rate estimates for
sources at the Foundry only.

  

Table 1.2- Quantification of Blackhawk Foundry’s contribution to total
monitored PM2.5 concentrations on exceedance days at the 300 Wellman
monitor.  Predicted concentrations from using AERMOD.

The State also conducted additional AERMOD runs to examine the impact
from other local sources in the Davenport Area.  The State noted that
the highest-eighth-highest (H8H) AERMOD predicted value for all
facilities combined is 16.26 µg/m3, of which 95% is attributable to
Blackhawk Foundry.  If Blackhawk Foundry is removed from the analysis,
the H8H occurs on a different day, and is reduced to 5.51 µg/m3.  If
several other point sources located nearer the violating monitor (Rich
Metals and Nestle Purina) are removed from the analysis, the H8H occurs
on a different day, and is reduced to 1.60 µg/m3. From these data the
State asserts that the point sources in the Davenport area, other than
the Blackhawk Foundry, have little contribution to the violating
monitor.  

EPA disagrees with the State’s assertion for several reasons.  The
State’s emissions inputs to the model are based on actual emissions
estimates representing a single year, and thus do not represent
potential impacts from a range of emissions activity at all of the
sources that have occurred in the past and that are likely to continue
in the future.  Additionally, for the base elevation and downwash
parameters used for all sources other than Blackhawk Foundry, the State
used AERMAP and DEM files to determine the base elevations, excluding
downwash, resulting in less conclusive results of impacts to the
monitor.  For these reasons, EPA concluded that due to these
uncertainties it could not support the State’s assertion that the
contributions from sources other than Blackhawk Foundry are minimal. 
Therefore, EPA cannot support the State’s proposed nonattainment area
boundary and believes the appropriate boundary should include a much
broader set of sources of PM2.5, NOx, and SO2 emissions in the local
area.

In addition to AERMOD, the State conducted a CAMX modeling technique
known as zero out to eliminate all anthropogenic emissions from sources
from grid cells which correspond to geographic areas of interest such as
Scott County, IA.  This type of modeling was used to provide data
regarding the impacts of longer-range transport, the importance of
precursor gases, and the aggregate role of sources in the area. These
models are not yet capable of reliably assessing the impacts of a single
source at the source receptor distances encountered in Scott County
(approximately 150 – 500 meters).  

Round	Area	Source Sectors	Pollutants

Rock Island 	Rock Island County	All Anthropogenic	NOx,SO2,Fine Primary

Scott County 1	Rural Scott County	All Anthropogenic	NOx,SO2,Fine Primary

Scott County 2	Quad Cities Metro	Onroad	All

Muscatine County	Rural Muscatine County	All Anthropogenic	NOx,SO2,Fine
Primary

Table 1.3 -Description of Zero-out Modeling Sensitivity Runs.

In this analysis all anthropogenic SO2, NOx, and primary fine particle
emissions outside the metro area in Scott County were zeroed out. 
Pollutant emissions from elevated point sources outside the city limits,
namely Linwood Mining and Mineral Corp., John Deere-Davenport Works,
Scott County Sanitary Landfill, and Lafarge North America, were also
zeroed out.  Using data from this analysis the State asserted that rural
Scott County contributed on average 1-3% of the total PM2.5 on modeled
violating days.

A second photochemical modeling analysis provided by the State was based
upon the use of the Particulate Source Apportionment Technique (PSAT)
capability of the CAMx modeling system.  This is a method for
investigating how defined regions and selected sources contribute to
particulate matter formation at any given receptor.  EPA Region 7, with
assistance from the Kansas Department of Health and Environment (KDHE),
implemented a PSAT simulation to augment the zero-out modeling runs
conducted by the State of Iowa. In this instance, the PSAT analysis is
only intended to provide examination of the local contribution to
secondary formation.   The State analyzed the data provided by this
simulation to develop its response to EPA’s 120-day letter.  

Figure 1.5 and Figure 1.6, show that PSAT estimates approximately 83% of
particulate sulfate and 76% of particulate nitrate originate from
emissions in the continental U.S. for concentrations at or above the
98th percentile at the 300 Wellman monitor receptor location. On these
same days, less than 1% of the sulfates and less than 1% of the nitrates
are attributable to Scott County. These results demonstrate that
long-range transport is the dominant contributor to the high sulfate and
nitrate concentrations. Based on this analysis, the State asserts that
the contribution from Scott County to secondary formation is relatively
low, on the order of 1 to 3 % for secondary sulfate and nitrate
components of total PM2.5 contributed by the Scott County point sources
of PM2.5 precursors.   

The presence of long range transport to the Davenport area does not
negate the fact that there is a violating monitor in the area, nor
EPA’s obligation under section 107(d) is to designate as nonattainment
to the area that is violating, and the nearby areas that are
contributing to that violation.  Therefore, EPA must evaluate what
nearby emissions and emissions activities in the Davenport area are
contributing to violations based upon the facts and circumstances in
this specific area.  EPA concludes that the modeling results submitted
by the State lend support to focusing primarily on the sources of direct
PM2.5 emissions that may contribute to the violations at the 300 Wellman
site, and to a lesser extent on sources of NOx and SO2 in the
surrounding area that may be contributing in addition to the amount from
long-range transport.  EPA concludes that the modeling provided by the
State for the purpose of informing designations adds to the
understanding of the potential local contribution to secondarily formed
PM2.5, and to the weight of evidence used by EPA to establish final
boundaries. However, the results cannot be interpreted alone as being
highly determinative because the databases and methods used in the
State-submitted photochemical simulations (e.g. grid cell resolution and
lack of performance evaluation) introduce significant uncertainties. 
EPA expects that these uncertainties can be addressed by more thorough
modeling in a future PM2.5 State Implementation Plan. 

Figure 1.5 -Average sulfate contributions by source region at the
Blackhawk Foundry (300 Wellman) monitor for 98th percentile and above
sulfate concentrations estimated by CAMx PSAT.

Figure 1.6-Average nitrate contributions by source region at the
Blackhawk Foundry (300 Wellman) monitor for 98th percentile and above
nitrate concentrations estimated by CAMx PSAT.

Figure 1.7- Modeled Average Contributions to the Blackhawk Foundry (300
Wellman) monitor.

Summary of Factor 1, Emissions Data

In summary, after review of emissions data, modeling data, and
consideration of the dominant wind direction associated with the local
exceedance events at the 300 Wellman monitor (see Factor 6), EPA has
determined that nearby emissions of direct PM2.5 and sources of SO2
(sulfate) and NOx (nitrate), primarily from long-range transport, have a
large impact on the violating monitor during exceedance events, and that
the contribution from rural Scott County is low.  EPA determined that
inclusion of the local PM2.5 emissions, including point sources in the
local area, is a highly significant consideration in establishing the
nonattainment boundaries.  For Scott County, the boundary includes all
of the local point sources of direct PM2.5 and SO2.

Factor 2:  Air quality data 

This factor considers the 24-hour PM2.5 design values (in µg/m3) for
air quality monitors in counties in the Davenport Area based on data for
the 2005-2007 period.  A monitor’s design value indicates whether that
monitor attains a specified air quality standard. The 24-hour PM2.5
standard is met when the 3-year average of a monitor’s 98th percentile
values are 35 µg/m3 or less.  A design value is only valid if minimum
data completeness criteria are met. The 24-hour PM2.5 design values for
counties in the Davenport Area are shown in Table 2.

County	State

Recommended

Nonattainment?	Design Values

2004-06(µg/m3)

	Design Values

2005-07(µg/m3)

Scott, IA*	Partial	32	37

Rock Island, IL	No	30	31

Henry, IL	No	**	**

Mercer, IL	No	**	**

Muscatine, IA	Partial	34	36

Clinton, IA	No	34	32

*There are a total of three (3) PM2.5 monitors in Scott County, IA. The
only monitor reflected in this table is the violating monitor.

** There are no PM2.5 monitoring stations in this county; therefore
there are no monitoring values. 

Table 2.-Air Quality Data 

The 300 Wellman Street monitor in Scott County exceeds the 24-hour PM2.5
standard with a design value of 37 (g/m3.  PM2.5 monitoring at this site
began in 2005, thus no trends in design values are available at this
time.  The design values at the 10th and Vine and Adams School monitors
in Scott County are below the current level of the NAAQS. Although there
is only one violating monitor in Scott County, IA, the absence of a
violating monitor, alone, is not a sufficient reason to eliminate other
areas, which may be contributing to the violation.  Other areas are
evaluated based on the weight of evidence of all nine factors and other
relevant information.

Previous year design values for the Scott County monitors are shown in
Table 2 and Figure 2.  Design values at the 10th and Vine and Adams
School monitors are, and have been, below the current level of the
NAAQS.  Design values between the 10th and Vine and Adams School
monitors have differed by at most 2 µg/m3 over the 2001–2007 period. 
The importance of direct PM2.5 emissions from sources near the 300
Wellman monitor are easily discernable, given the proximity of the
monitors and the range in the 2005-2007 design values (Figure 2.1).  
However, the ambient PM2.5 at that monitor is not exclusively the result
of such emissions, and is the result of cumulative impacts from
emissions elsewhere, including emissions of PM2.5 and PM2.5 precursors
from other sources in the Davenport area as well as from more distant
sources.  

 Figure 2-Comparison of Recent Design Values for the Scott County
Monitors.   

 Figure 2.1 -Spatial distance of Davenport monitoring locations

A closer view of the three PM2.5 monitor locations in Scott County,
along with their respective design values, is provided in Figure 2.1. 
Figure 2.1 includes the location of Scott County’s major point source
facilities, shown by red dots, near the three monitor sites.  A 5 (g/m3
difference in design value is observed between the 300 Wellman and the
10th & Vine monitor.  The 10th and Vine monitor is situated
approximately 1.8 miles to the northeast of the 300 Wellman monitor. 
Such differences in design values over a relatively small distance are
usually indicative of localized contributions from sources near a
monitor.  As shown in Figure 2.1, the nearest major source to the 300
Wellman monitor is Blackhawk Foundry.  It has been shown through
modeling (under Factor 1) that the Foundry’s emissions affect the 300
Wellman monitor, however contributions from other local sources cannot
be excluded from consideration due to their proximity to the violating
monitor and uncertainties in the modeling previously discussed.  That
emissions from the Blackhawk Foundry impact the monitor is not really in
dispute; the question for purposes of designations is what other nearby
areas are also contributing to the violation at that monitor. The
potential for multiple sources to impact the violating monitor is part
of EPA’s basis for including a broader area partial county boundary. 
Inclusion of contributing sources will assure proper consideration of
all such sources during the development of the nonattainment area SIP
for this area.

Air quality monitoring data on the composition of fine particle mass are
available from the EPA Chemical Speciation Network and the IMPROVE
monitoring network.  Analysis of these data indicates that the total
concentrations of the chemical composition at the speciation monitor in
Davenport located at 10th and Vine Streets, for the cold season, are as
follows: 26% sulfate, 17% carbonaceous PM2.5, 55% nitrate and 2%
crustal.  For the warm season, the total concentrations of the chemical
composition at the speciation monitor in Davenport located at 10th and
Vine Streets, are as follows: 77% sulfate, 20% carbonaceous PM2.5, 0%
nitrate and 2% crustal.  The speciation data from this monitoring
location indicate a strong precursor influence on the monitor, as
discussed under Factor 1, which is primarily attributed to long range
transport.  

EPA also conducted positive matrix factorization (PMF) analysis from
speciation data available the 10th and Vine monitor located
approximately 1.8 miles to the northeast of the violating 300 Wellman
monitor. The 10th and Vine monitor is also located near a significant
point source.  EPA conducted this analysis in an effort to evaluate the
PSAT modeling analysis from the State (indicating large secondary
formation component to the violating monitor) and to establish if source
signatures were present at a monitor some distance from the violating
monitor.  The PMF data was analyzed for days when the 24-hour average at
the violating monitor exceeded 35 ug/m3.  As shown in Figure 2.2, on
exceedance days secondary particulate matter (sulfate and nitrate)
accounted for 74% of the filter mass, with totals potentially greater if
one considers the contribution of secondarily formed organic carbon. 
Two unique sources, a calcium source and an iron/manganese source,
contributed 2% and 3% respectively to the apportioned mass at the 10th
and Vine monitor.  It is also likely that a portion of the organic
carbon profile obtained from the PMF analysis is attributable to
operations at the Blackhawk Foundry due to the presence of coking
operations at the facility.  From this analysis EPA concluded that the
same calcium source(s) were likely to influence the nearby violating
monitor, indicating that point sources other than Blackhawk Foundry
potentially influence the violating monitor.  

Figure 2.2 -PMF Predicted Source Apportionment at 10th and Vine.

In order to further understand the trends at the monitors in the area,
the State and EPA evaluated information for individual days when an
exceedance of the standard was monitored.  Sorting the monitoring data
in this manner can assist in discerning trends and is useful in further
understanding of the nature of the monitored exceedances.  The following
table assists in the review of the individual days when a monitor
recorded an exceedance.  This information, in combination with the
meteorological information, discussed in Factor 6, assists in the
understanding of the trends in exceedances in the Davenport Area. 

The daily averaged PM2.5 concentrations in Table 2.1 are colored coded
according to concentrations.  Exceedances are highlighted in red, and
indicate a daily average concentration greater than 35 (g/m3.  Cells
shown in yellow represent concentrations greater than 30(g/m3 and less
than or equal to 35 g/m3.  Green indicates daily averaged PM2.5
concentrations less than or equal to 30  (g/m3.  Blank cells indicate no
measurements were made at a particular monitor on that day.

From Table 2.1, it is observed that there are days when multiple
monitors record exceedances on the same day, and there are days when
only a single monitor exceeds the standard.  Out of the 21 exceedance
days listed in Table 2.1, eight out of the 21 days are days in which
only the monitor at 300 Wellman (a.k.a. Blackhawk Foundry monitor)
recorded exceedances of the standard.  In contrast, out of the 21 days
listed in Table 2.1, 4 out of the 21 days are days when only the 10th
and Vine (a.k.a. Jefferson) monitor recorded exceedances of the
standard.  As such, there are 9 days when more than one monitor in the
Davenport Area exceeds the standard.  

Table 2.1- Air Quality Data for Individual PM2.5 Monitors in
Davenport-Moline-Rock Island, IA-IL, Muscatine, IA and Select
Surrounding Counties Compared to Individual Days when Exceedances were
monitored. 

Of the 17 exceedance days recorded at the 300 Wellman monitor between
2005 and 2007, 7 events are classified as local events and the remaining
10 exceedance days are described as regional by the State.  Additional
review of the local events shown in Table 2.1 reveals that these events
predominantly occur during the summer and early fall seasons.  The local
events are also tightly correlated to a southwesterly wind direction.  

When EPA issued its 120-day letter, an analysis of speciation data was
not available at the 300 Wellman monitor.  Between August 2008 and
October 2008 the State attempted to perform an exploratory analysis on
archived FRM filters from several sites in Eastern Iowa in an attempt to
more conclusively demonstrate ambient impacts of local sources on the
violating monitor. The analysis included filters from the two violating
FRM monitors (Muscatine-Garfield and 300 Wellman), FRM samplers
collocated with speciation samplers at Davenport (10th and Vine) and
Lake Sugema (EPA’s IMPROVE network), and a fifth site in the vicinity
of the violating monitors chosen by the State.  However, comparison of
ion data measured on the archived FRM filters with ion data measured
from speciation samplers did not demonstrate comparability and therefore
were deemed unreliable for statistical analysis.  

EPA reviewed the data submitted from this analysis and found that the
data derived is not of sufficient quality for use.  Furthermore, given
the relatively short distance of 1.8 miles between the 300 Wellman
monitor and the 10th & Vine monitor, it can be assumed that PMF
speciation data for direct PM2.5 at 10th & Vine could be considered
representative of direct PM2.5 conditions at the violating monitor. 
Because the PMF analysis showed a signature of multiple sources at a
monitor that is downwind of the violating monitor, EPA can not support
the State’s recommended very small partial boundary that focuses on a
single point source. Although there speciation data available at the
nearby 10th and Vine monitor, there is no speciation data from the
violating monitoring site, nor is there data demonstrating that just one
local point source has overwhelming contribution to the violating
monitor.  In addition, as discussed under Factor 1, the point source
modeling, although not sufficient to show precisely the degree of
contribution, does show that other point sources have some contribution
to the violating monitor.  Therefore all local point sources must be
considered in establishing the boundary.  

Summary of Factor 2, Air Quality Data

In summary, the other monitors in Scott County (10th and Vine monitor
and Adams School monitor) have 24-hour average readings above the level
of the standard, but these do not result in a 3-year design value that
exceeds the NAAQS.   The design values at these monitors are 5–6
µg/m3 below the design value of the violating 300 Wellman monitor. 
Regional events do impact the area and the effects are seen on the two
non-violating monitors as well as the 300 Wellman monitor, however the
marked difference in monitor design values across the area suggests that
local influences remain a critical component of the exceedance events at
the 300 Wellman monitor.  The available speciation data from a nearby
location indicate that the local contribution to exceedance days
originates from a collection of sources.  Determining the area that is
contributing to a violation is part of the designation process and
supports a broader boundary than the very small boundary recommended by
the State.   

Note:  Eligible monitors for providing design value data generally
include State and Local Air Monitoring Stations (SLAMS) at
population-oriented locations with an FRM monitor.  All data from
Special Purpose Monitors (SPM) are eligible for comparison to the
relevant NAAQS, subject to the requirements given in the October 17,
2006 Revision to Ambient Air Monitoring Regulations (71 FR 61236).  All
monitors used to provide data must meet the monitor siting and
eligibility requirements given in 71 FR 61236 to 61328 in order to be
acceptable for comparison to the 24-hr PM2.5 NAAQS for designation
purposes.

Factor 3: Population density and degree of urbanization (including
commercial development)

Table 3 shows the 2005 population for each county in the area being
evaluated, as well as the population density for each county in that
area.  Population data may give an indication of whether it is likely
that population-based emissions contribute to violations of the 24-hour
PM2.5 standards.

County	State Recommended Nonattainment?	2005 Population	2005 Population
Density (pop/sq mi)

Scott, IA	Partial	161,170	345

Rock Island, IL	No	147,454	327

Henry, IL	No	50,508	61

Mercer, IL	No	16,840	30

Muscatine, IA	Partial	42,567	95

Clinton, IA	No	49,744	70

Table 3- Population

Figure 3- Land Use Map for the Counties in the Davenport-Moline-Rock
Island IA-IL Area  and Surrounding Counties

	

The urbanized portions of Scott and Rock Island counties are
geographically located close to each other, i.e. the area is commonly
known as the Quad Cities area.  The Quad Cities area of Iowa includes
the cities of Davenport and Bettendorf on the Iowa side, and Moline and
Rock Island on the Illinois side.  As illustrated in Table 3 and Figure
3, the populations in the counties evaluated are predominantly
concentrated in the urbanized portions of the counties in near proximity
to the 300 Wellman monitor.  Davenport City, which is approximately 8
miles wide and 13 miles long, comprises 23% of Scott County’s total
land area of 457 sq miles.  The remaining 77% of the land area in Scott
County is generally rural.  The EPA designated nonattainment area is
focused primarily on the urbanized area of Scott County, and captures
approximately 89% of the county population.

Summary of Factor 3, Population Density 

Figure 3 demonstrates the near proximity of the urbanized population in
Scott County to the violating 300 Wellman monitor.  Rural Scott County,
which comprises a relatively small portion of the county’s population,
is associated with relatively low population-based area source emissions
and potential contribution to the violating monitor.  Similarly, Figure
3 demonstrates the near proximity of the urbanized population in Rock
Island County to the violating monitor.  This supports a boundary that
is focused on the urbanized portions of Scott County and Rock Island
County. 

Factor 4: Traffic and commuting patterns 

This factor considers the number of commuters in each county who drive
to another county within the Davenport Area, total commuters in each
county who commute to other counties within the Davenport Area, as well
as the total Vehicle Miles Traveled (VMT) for each county in millions of
miles (see Table 5).  A county with numerous commuters indicates the
potential for mobile-source related emissions to contribute to fine
particle concentrations in the area analyzed, and may indicate the
degree of economic integration of an area.  As shown in Table 4, Scott
County, IA and Rock Island County, IL have the greatest number commuting
within the statistical area.  

County	State Recommended Nonattainment?	2005 VMT

(106 mi)	Number Commuting to any violating counties

	Percent

Commuting to any violating counties 

	Number Commuting within (and into) the  statistical area 	Percent

Commuting within (and into) the statistical area 

Scott, IA	Partial	    1,614 	61,500 	79 	      74,020 	          95 

Rock Island, IL	No	    1,313 	14,240 	20 	      67,530 	          97 

Henry, IL	No	       695 	1,870 	8 	      22,340 	          91 

Mercer, IL	No	       135 	1,200 	15 	        6,570 	          85 

Clinton, IA	No	       423 	2,610 	11 	        3,600 	          15 

Muscatine, IA	Partial	       372 	17,330 	85 	        1,060 	           
5 

Table 4-Traffic and Commuting Patterns

The 2005 VMT data used for table 4 and 5 of the 9-factor analysis have
been derived using methodology such as that described in "Documentation
for the  2005 Mobile National Emissions Inventory, Version 2," December
2008, prepared for the Emission Inventory Group, U.S. EPA.  This
document may be found at:
ftp://ftp.epa.gov/EmisInventory/2005_nei/mobile_sector/documentation/200
5_mobile_nei_version_2_report.pdf 

CAMX modeling (discussed under Factor 1) submitted by the State suggests
a 1-3% contribution on exceedance days from mobile sources.  The State
also asserts that the zero-out modeling shows that NOx precursor
emissions from mobile sources are not significant to local PM2.5
formation or toward the violation at the 300 Wellman monitor.   Figures
4 and 4.1, (from the 2002 NEI) show that 56% of the total NOx emissions
in Scott County are attributable to mobile sources, and 49% of the total
VOC emissions in Scott County are attributable to mobile sources. 
Direct PM2.5 emissions from mobile sources are not a significant portion
of local direct PM2.5 emissions as shown previously in Figure 1.2.  The
NEI numbers suggest that a local secondary contribution to the violating
monitor from mobile sources is probable

Summary Factor 4-Traffic and commuting patterns

As the metropolitan area is the most heavily vehicle-traversed part of
the county, it is reasonable to include the contiguous metropolitan area
in the nonattainment boundary. The partial county nonattainment area
boundary promulgated by EPA is inclusive of the major metropolitan area.

Figure 4-Total NOx sources for all of Scott County

Figure 4.1-Total VOC sources for all of Scott County

 

Factor 5:  Growth rates and patterns  

This factor considers population growth for 2000-2005 and growth in VMT
for 1996-2005 for counties in Davenport-Moline-Rock Island area, as well
as patterns of population and VMT growth.  Areas with rapid population
or VMT growth indicate the potential for proportionate emissions growth
from mobile sources and other emitting activities, such as construction
of infrastructure, including roads, homes, and businesses.  Table 5
below shows population, population growth, VMT and VMT growth for
counties that are included in the Davenport-Rock Island Area.  Counties
are listed in descending order based on VMT growth between 1996 and
2005.

County	Population (2005)	Population % change (2000 - 2005)	2005 VMT

(1000s mi)	VMT

% change

(1996 to 2005)

Muscatine, IA	42,567	2	372	43

Clinton, IA	49,744	-1	423	39

Scott, IA	161,170	2	1,614	25

Henry, IL	50,508	-1	695	7

Rock Island, IL	147,454	-1	1,313	3

Mercer, IL	16,840	-1	135	-12

Table 5- Population and VMT Values and Percent Change.

The State provided to EPA the population growth projections shown in
Figure 5 as part of its technical support for the State’s designation
recommendation.  This information was assembled from several data
sources, such as U.S. Census Bureau, Iowa and Illinois Department of
Commerce, Bi-State Regional Commission and nonpoint sources.   This
chart compliments Table 5 in that it illustrates, graphically, the
growth that occurred in Scott County from 2000-2005 and displays trends
from various counties in and surrounding the Davenport-Moline-Rock
Island area.  Scott County is the only county in EPA’s evaluation area
that is projected to have a growth in population in the coming years. 

Summary of Factor 5- Growth rates and patterns  

The area has not seen a very large increase in population in the recent
past, and only Scott County is projected to have any future growth. 
This factor continues to point to Scott County as a primary area of
interest for designations. 

Figure 5-Population Projections Chart 

Factor 6:  Meteorology (weather/transport patterns)

For this factor, EPA considered the most representative National Weather
Service wind direction and speed data throughout the year, with an
emphasis on “high PM2.5 days.”  These high days are defined as days
where any FRM or FEM air-quality monitors had 24-hour PM2.5
concentrations above 95% on a frequency distribution curve of PM2.5
24-hour values.  For this factor, EPA also considered each County’s
CES, which includes an analysis of trajectories of air masses for high
PM2.5 days.    

EPA also relied upon information provided the State as part of its
technical support for the State’s designation recommendation.  The
purpose of this analysis is to determine contributing emissions in any
particular direction relative to the violating monitor.  The purpose of
the analysis conducted by the State and EPA is to determine contributing
emissions in any particular direction relative to the violating monitor.

The State provided wind rose plots generated using WRPLOT VIEW,
developed by Lakes Environmental (http://www.lakes-environmental.com). 
The State asserted that wind speed and direction measured by the
Davenport Municipal Airport (KDVN) is representative of the wind field
at the violating monitor in Scott County, Iowa and is not unduly
influenced by differences in surrounding terrain.  The KDVN ASOS
anemometer had a 94% data capture for hourly wind speed and direction
measurements collected near the top of the hour; its data was used in
this analysis.  

Figure 6 shows the wind rose for 383 hourly observations on at the KDVN
ASOS location on exceedance days in 2005-2007.  Each petal represents a
measured surface-level wind direction (direction the wind is blowing
from), which were archived in 10 degree intervals ranging from 10 to
360.  The azimuth of each petal indicates the measured wind direction,
and the length from the center of the plot measures the relative
frequency each wind direction was observed.  For a particular wind
direction the length of the colored segments indicates the relative
frequency of six wind speeds bins, which is shown in the lower right
corner

Examining wind data in this manner only for days when the 300 Wellman
violating monitor measures a 24-hour average PM2.5 concentration greater
than or equal to 35.5 μg/m3 provides evidence that sources in a
particular direction from the violating monitor may have contributed to
the violation of the NAAQS.  The wind rose in Figure 6 indicates that
the prevailing winds can come from many different directions on
exceedance days.  The prevailing wind directions with the seven greatest
frequencies are in an 80 degree arc from the southwest to the southeast,
indicating the greatest potential for nearby sources in those directions
to contribute to monitored violations.  As shown by the length of the
black petals, relatively light winds were not often associated with
exceedance days.  Most exceedance days occur when prevailing winds are
greater than 7 knots (shown as red, blue or green). 

Another analysis technique, provided by the State and used by EPA in
determining the intended nonattainment boundary, is the pollution rose. 
A pollution rose assists in assessing the pollutant transport
characteristics at the monitor location.  This graphical plot is similar
in interpretation to a wind rose, except binned wind speed is replaced
by PM2.5 concentrations measured by the Filter Dynamics Measurement
System - Tapered Element Oscillating Microbalance (FDMS-TEOM) sampler
located at the violating monitor.  Hourly PM2.5 concentrations are
paired with hourly wind directions measured by the KDVN ASOS.  This
analysis shows the relative frequency of PM2.5 concentrations measured
while winds were observed from each direction.  Note that the FDMS-TEOM
instrumentation is used for continuous PM2.5 measurements, but it is not
the Federal Reference Method (FRM) for monitoring and calculating the
PM2.5 design value for the Blackhawk Foundry monitor.  The hourly
FDMS-TEOM measurements, when averaged daily, correlate well with the
daily sampled FRM data (r2of 0.9166), however, EPA has not defined a
standard particle conditioning protocol for continuous monitors and
therefore hourly values between different sampling methods may vary. 
For these reasons, this analysis is used only as a qualitative
assessment of air quality at the monitor.

Figure 6 - Wind Rose for Davenport Municipal Airport for Exceedance Days
in 2005-2007.

Figure 6.1 shows the pollution rose for the time period of 2005-2007. 
During this period the pollution rose shows that relatively high hourly
PM2.5 readings (above 30 ug/m3) occurred when winds came from nearly any
direction, but were most frequent in nearly the same 80 degree arc from
southwest to southeast shown in previous Figure 6.  The cleanest air
tended to be associated with a westerly to northwesterly direction, and
also with the same southwest to southeast direction previously
indicated.

Summary Factory 6- Meteorology

The wind rose indicates that winds most frequently occur from a
generally southerly direction, from the southwest to the southeast, on
high PM2.5 days.  This suggests relatively low contributions from areas
located to the west, north, and east of the monitor, including Clinton
County, northern portions of Rock Island County, and the most northerly
portions of Muscatine County.  EPA’s nonattainment boundary includes
potential emissions sources located upwind to the southwest, south, and
southeast of the violating monitor.

 Figure 6.1- Pollution Rose for the Violating Monitor for 2005-2007

Note:  The meteorology factor is also considered in each county’s
Contributing Emissions Score because the method for deriving this metric
included an analysis of trajectories of air masses for high PM2.5 days.

Factor 7:  Geography/topography (mountain ranges or other air basin
boundaries)

The geography/topography analysis looks at physical features of the land
that might have an effect on the air shed and, therefore, on the
distribution of PM2.5 over the Davenport-Rock Island Area.

The Davenport Area does not have any geographical or topographical
barriers significantly limiting air-pollution transport within its air
shed.  Therefore, this factor did not play a significant role in the
decision-making process.

Factor 8:  Jurisdictional boundaries (e.g., existing PM2.5 areas) 

In evaluating the jurisdictional boundary factor, consideration was
given to existing boundaries and organizations that may facilitate air
quality planning and the implementation of control measures to attain
the standard.  Areas designated as nonattainment (e.g. for PM2.5 or
8-hour ozone standard) represent important boundaries for state air
quality planning.  In the case of the areas evaluated, none of the areas
are designated as nonattainment for any of the National Ambient Air
Quality Standards.  There was a review of the information regarding the
Bi-State Regional Commission which represents the Metropolitan Planning
Organization (MPO) for urbanized area transportation planning in the
Quad Cities area.  The MPO serves Henry, Mercer, and Rock Island
Counties in Illinois, and Scott and Muscatine Counties in Iowa.  Its web
site is:   HYPERLINK "http://www.bistateonline.org" 
www.bistateonline.org .  However, the Bi-State planning area itself was
not a key factor in determining the intended nonattainment boundary;
other factors pointed to a more localized nonattainment area boundary.

Factor 9:  Level of control of emission sources 

The emission estimates on Table 1 (under Factor 1) include any control
strategies implemented by the States in the Davenport-Moline-Rock Island
area before 2005 that may influence emissions of any component of PM2.5
emissions (i.e., total carbon, SO2, NOx, and crustal PM2.5).  This is
also the case for Clinton County, Iowa.   As presented on Table 1,
emissions in Clinton County were evaluated because of Clinton County’s
proximity to Scott County, the county with the violating monitor. 
Clinton County ranked as one of the highest counties with precursor
emissions.  However, upon closer evaluation and in working in the State,
there was evidence that emissions reductions have occurred in Clinton
County since 2005.  In reviewing the emissions from Title V facilities
in Clinton County, EPA noted that Archer Daniels Midland had a high
percentage of the county’s emissions especially for SO2, NOx, and VOC
emissions.  This facility was part of a national global settlement with
ADM.  As a result, the company has made, and will be making, substantial
air pollution control upgrades at the plant, including installation of
RTOs, scrubber enhancements, replacement of obsolete coal-fired boilers
with state of the art FBC boilers, and fuel switches to natural gas. 
The control strategy is described in more detail in the “Control
Technology Plan for Clinton, IA, Wet Corn Mill” attachment to the
Consent Decree.  Based on this more recent information, EPA has
determined that the ADM reductions are an important factor to consider
in determining nonattainment boundaries. 

Conclusion

EPA is designating the partial county nonattainment area boundary
described in the table located in the introduction, for the 2006 24-hour
PM2.5 standard after considering each of the nine factors, detailed in
the body of this document.  For this decision the EPA relied most
heavily on emissions, air quality, meteorology, and population.  The
additional modeling data provided evidence that was used to determine
that a majority of emissions from nearby sources that cause or
contribute to the violation should be included in the nonattainment
area.  EPA determined that inclusion of the local source PM2.5 emissions
is a highly significant consideration in establishing the nonattainment
boundaries.  For Scott County, the boundary includes all of the local
point sources of PM2.5, and a substantial fraction of the county-wide
area source sources. The EPA defined nonattainment includes the area
violating the standard and the area that is contributing significantly
to the violation.

 EPA designated nonattainment areas for the 1997 fine particle standards
in 2005.  In 2006, the 24-hour PM2.5 standard was revised from 65
micrograms per cubic meter (average of 98th percentile values for 3
consecutive years) to 35 micrograms per cubic meter; the level of the
annual standard for PM2.5 remained unchanged at 15 micrograms per cubic
meter (average of annual averages for 3 consecutive years).  

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