Appendix- Chapter 3 

3a.1 Non-EGU and Area Source Controls Applied in the Baseline and
Control Scenarios

3.1.1 Non-EGU and Area Source Control Strategies for Ozone NAAQS
Proposal

In the Non-EGU and Area Sources portion of the control strategy, maximum
control scenarios were used from the existing control measure dataset
from AirControlNET 4.1 for 2020 (for Geographic Areas defined for each
level of the standard being analyzed).  This existing control measure
dataset reflects changes and updates made as a result of the reviews
performed for the final PM2.5 RIA.  Following this, an internal review
was performed by the OAQPS engineers in the Sector Policies and Programs
Division (SPPD) to examine the controls applied by AirControlNET and
decide if these controls were sufficient or could be more aggressive in
their application, given the 2020 analysis year.  This review was
performed for non-EGU NOx control measures.  The result of this review
was an increase in control efficiencies applied for many control
measures, and more aggressive control measures for over 80 SCC’s.  
For example, SPPD recommended that we apply SCR to cement kilns to
reduce NOx emissions in 2020.  Currently, there are no SCRs in operation
at cement kilns in the U.S, but there are several SCRs in operation at
cement kilns in France now.  Based on the SCR experience at cement kilns
in France, SPPD believes SCR could be applied at U.S. cement kilns by
2020.  Following this, it was recommended that supplemental controls
could be applied to 8 additional SCC’s from non-EGU NOx sources.  We
also looked into sources of controls for highly reactive VOC non-EGU
sources.  Four additional controls were applied for highly reactive VOC
non-EGU sources not in AirControlNET.   

3a.1.2 NOx Control Measures for Non-EGU Point Sources. 

Several types of NOx control technologies exist for non-EGU sources:
SCR, selective noncatalytic reduction (SNCR), natural gas reburn (NGR),
coal reburn, and low-NOx burners. In some cases, LNB accompanied by flue
gas recirculation (FGR) is applicable, such as when fuel-borne NOx
emissions are expected to be of greater importance than thermal NOx
emissions. When circumstances suggest that combustion controls do not
make sense as a control technology (e.g., sintering processes, coke oven
batteries, sulfur recovery plants), SNCR or SCR may be an appropriate
choice. Finally, SCR can be applied along with a combustion control such
as LNB with overfire air (OFA) to further reduce NOx emissions. All of
these control measures are available for application on industrial
boilers. 

Besides industrial boilers, other non-EGU source categories covered in
this RIA include petroleum refineries, kraft pulp mills, cement kilns,
stationary internal combustion engines, glass manufacturing, combustion
turbines, and incinerators. NOx control measures available for petroleum
refineries, particularly process heaters at these plants, include LNB,
SNCR, FGR, and SCR along with combinations of these technologies. NOx
control measures available for kraft pulp mills include those available
to industrial boilers, namely LNB, SCR, SNCR, along with water injection
(WI). NOx control measures available for cement kilns include those
available to industrial boilers, namely LNB, SCR, and SNCR.
Non-selective catalytic reduction (NSCR) can be used on stationary
internal combustion engines. OXY-firing, a technique to modify
combustion at glass manufacturing plants, can be used to reduce NOx at
such plants. LNB, SCR, and SCR + steam injection (SI) are available
measures for combustion turbines. Finally, SNCR is an available control
technology at incinerators. For more information on these measures,
please refer to the AirControlNET 4.1 control measures documentation
report. 

3a.1.3 VOC Control Measures for Non-EGU Point Sources.  

VOC controls were applied to a variety of non-EGU point sources as
defined in the emissions inventory in this RIA.  These controls are: 
permanent total enclosure (PTE) applied to paper and web coating
operations and fabric operations, and incinerators or thermal oxidizers
applied to wood products and marine surface coating operations.  A PTE
confines VOC emissions to a particular area where can be destroyed or
used in a way that limits emissions to the outside atmosphere, and an
incinerator or thermal oxidizer destroys VOC emissions through exposure
to high temperatures (2,000 degrees Fahrenheit or higher).  For more
information on these measures, refer to the AirControlNET 4.1 control
measures documentation report.  

3a.1.4  NOx Control Measures for Area Sources.  

There were two controls applied for NOx emissions from area sources. 
The first is RACT (reasonably available control technology) to 25 tpy
(LNB).  This control is the addition of a low NOx burner to reduce NOx
emissions.  This control is applied to industrial oil, natural gas, and
coal combustion sources.  The second control is water heaters plus LNB
space heaters.  This control is based on the installation of low-NOx
space heaters and water heaters in commercial and institutional sources
for the reduction of NOx emissions.  For additional information
regarding these controls please refer to the AirControlNET 4.1 control
measures documentation report. 

3a.1.5 VOC Control Measures for Area Sources.

The most frequently applied control to reduce VOC emissions from area
sources was CARB Long-Term Limits.  This control, which represents
controls available in VOC rules promulgated by the California Air
Resources Board, applies to commercial solvents and commercial
adhesives, and depends on future technological innovation and market
incentive methods to achieve emission reductions.  The next most
frequently applied controls was the use of low or no VOC materials for
graphic art source categories.  The South Coast Air District’s SCAQMD
Rule 1168 control applies to wood furniture and solvent source
categories sets limits for adhesive and sealant VOC content.  The OTC
solvent cleaning rule control establishes hardware and operating
requirements for specified vapor cleaning machines, as well as solvent
volatility limits and operating practices for cold cleaners.  The Low
Pressure/Vacuum Relief Valve control measure is the addition of low
pressure/vacuum (LP/V) relief valves to gasoline storage tanks at
service stations with Stage II control systems. LP/V relief valves
prevent breathing emissions from gasoline storage tank vent pipes. 
SCAQMD Limits control establishes VOC content limits for metal coatings
along with application procedures and equipment requirements. Switch to
Emulsified Asphalts control is a generic control measure replacing
VOC-containing cutback asphalt with VOC-free emulsified asphalt.   The
equipment and maintenance control measure applies to oil and natural gas
production.  The Reformulation - FIP Rule control measure intends to
reach the VOC limits by switching to and/or encouraging the use of
low-VOC pesticides and better Integrated Pest Management (IPM)
practices.  For additional information regarding these controls please
refer to the AirControlNET 4.1 control measures documentation report.

3a.1.6  Supplemental Controls

The table below summarizes the supplemental control measures added to
our control measures database by providing the pollutant it controls and
its control efficiency.  These controls were applied in the baseline
scenario to Houston and Chicago, and the Northeast as well as in the
incremental control strategy applied to the Eastern U.S.  However, these
controls are not located in AirControlNET. 

Table 3a.1 Supplemental Emission Control Measures Applied in Modeled
Attainment Strategies for the Ozone NAAQS RIA – New Control
Technologies Added to the Control Measures Database

Pollutant	SCC	SCC Description	Control Technology	Percent Reduction  (%)

NOx	20200252	Internal Comb. Engines/Industrial/Natural Gas/2-cycle Lean
Burn	LEC (Low Emission Combustion)	87

	20200254	Internal Comb. Engines/Industrial/Natural Gas/4-cycle Lean
Burn	LEC (Low Emission Combustion)	87

VOC*	3018001-

30600701 and 30600999 - 

	Fugitive Leaks

Flares	Enhanced LDAR	50

98

	3018001 -	Fugitive Leaks	LDAR	80

	30600702- 

	Cooling towers	Monitoring Program	No one general estimate

	30600503- 	Wastewater Drains and Separators	Inspection and Maintenance
Program (Separators)  Water Seals (Drains) 	65

*Note:  the cost of these measures are not included in our incremental
annualized cost estimates since these controls are found in the
Harris-Galveston-Brazoria Cos. SIP (Texas), and they will be incurred by
2020 in any event.  We do quantify the emission reductions since these
controls are not accounted for in our baseline inventory for 2020,
however.

Low Emission Combustion (LEC)

Overview:  LEC technology is defined as the modification of a natural
gas fueled, spark ignited, reciprocating internal combustion engine to
reduce emissions of NOx by utilizing ultra-lean air-fuel ratios, high
energy ignition systems and/or pre-combustion chambers, increased
turbocharging or adding a turbocharger, and increased cooling and/or
adding an intercooler or aftercooler, resulting in an engine that is
designed to achieve a consistent NOx emission rate of not more than
1.5-3.0 g/bhp-hr at full capacity (usually 100 percent speed and 100
percent load). This type of retrofit technology is fairly widely
available for stationary internal combustion engines.  

For control efficiency, EPA estimates that it ranges from 82 to 91
percent for LEC technology applications.  The EPA believes application
of LEC would achieve average NOx emission levels in the range of 1.5-3.0
g/bhp-hr.  This is an 82-91 percent reduction from the average
uncontrolled emission levels reported in the ACT document.  An EPA
memorandum summarizing 269 tests shows that 96 percent of IC engines
with installed LEC technology achieved emission rates of less than 2.0
g/bhp-hr.  The 2000 EC/R report on IC engines summarizes 476 tests and
shows that 97% of the IC engines with installed LEC technology achieve
emission rates of 2.0 g/bhp-hr or less.

Major Uncertainties:  The EPA acknowledges that specific values will
vary from engine to engine.  The amount of control desired and number of
operating hours will make a difference in terms of the impact had from a
LEC retrofit.  Also, the use of LEC may yield improved fuel economy and
power output, both of which may affect the emissions generated by the
device. 

Leak Detection and Repair (LDAR) for Fugitive Leaks

Overview:  This control measure is a program to reduce leaks of fugitive
VOC emissions from chemical plants and refineries.  The program includes
special “sniffer” equipment to detect leaks, and maintenance
schedules that affected facilities are to adhere to. This program is one
that is contained within the Houston-Galveston-Brazoria 8-hour Ozone
SIP.  

Major Uncertainties:  The degree of leakage from pipes and processes at
chemical plants is always difficult to quantify given the large number
of such leaks at a typical chemical manufacturing plant.  There are also
growing indications based on tests conducted by TCEQ and others in
Harris County, Texas that fugitive leaks have been underestimated from
chemical plants by a factor of 6 to 20 or greater.  

Enhanced LDAR for Fugitive Leaks

Overview:  This control measure is a more stringent program to reduce
leaks of fugitive VOC emissions from chemical plants and refineries that
presumes that an existing LDAR program already is in operation.  

Major Uncertainties:  The calculations of control efficiency and cost
presume use of LDAR at a chemical plant.  This should not be an
unreasonable assumption, however, given that most chemical plants are
under some type of requirement to have an LDAR program.  However, as
mentioned earlier, there is growing evidence that fugitive leak
emissions are underestimated from chemical plants by a factor of 6 to 20
or greater.  

Flare Gas Recovery

Overview:  This control measure is a condenser that can recover 98
percent of the VOC emitted by flares that emit 20 tons per year or more
of the pollutant.  

Major Uncertainties: Flare gas recovery is just gaining commercial
acceptance in the US and is only in use at a small number of refineries.
 

Cooling Towers

Overview:  The control measure is continuous monitoring of VOC from the
cooling water return to a level of 10 ppb.  This monitoring is
accomplished by using a continuous flow monitor at the inlet to each
cooling tower.  

There is not a general estimate of control efficiency for this measure;
one is to apply a continuous flow monitor until VOC emissions have
reached a level of 1.7 tons/year for a given cooling tower.  

Major Uncertainties:  The amount of VOC leakage from each cooling tower
can greatly affect the overall cost-effectiveness of this control
measure.

Wastewater Drains and Separators

Overview:   This control measure includes an inspection and maintenance
program to reduce VOC emissions from wastewater drains and water seals
on drains.  This measure is a more stringent version of measures that
underlie existing NESHAP requirements for such sources.

Major Uncertainties:  The reference for this control measures notes that
the VOC emissions inventories for the five San Francisco Bay Area
refineries whose data was a centerpiece of this report are incomplete. 
In addition, not all VOC species from these sources were included in the
VOC data that is a basis for these calculations.

In addition to the new supplemental controls presented above, there were
a number of changes made to existing AirControlNET controls.  These
changes were made based upon an internal review performed by EPA
engineers to examine the controls applied by AirControlNET and determine
if these controls were sufficient or could be more aggressive in their
application, given the 2020 analysis year.  This review was performed
for non-EGU NOx control measures.  The result of this review was an
increase in control efficiencies applied for many control measures, and
more aggressive control measures for over 70 SCCs.  The changes apply to
the control strategies performed for the Eastern US only.  These changes
are listed in the table below.

Table 3a.2 Supplemental Emission Control Measures Applied in Modeled
Attainment Strategies for the Ozone NAAQS RIA – Changes to Control
technologies currently in our Control Measures Database

Pollutant	SCC	AirControlNET Source

Description	AirControlNET Control

Technology	New Control Technology	New Control Efficiency (%)	Old 

Control Efficiency (%)

NOX	10200104  10200204  10200205  10300207  10300209

10200217  10300216	ICI  Boilers - Coal-Stoker	SNCR	SCR	90.0	40.0

NOX	10200901  10200902   10200903   10200907   10300902   10300903	ICI
Boilers - Wood/Bark/

Waste	SNCR	SCR	90.0	55.0

NOX	10200401   10200402   10200404   10200405   10300401	ICI Boilers -
Residual Oil	SCR	SCR	90.0	80

NOX	10200501   10200502   10200504	ICI Boilers - Distillate Oil	SCR	SCR
90.0	80

NOX	10200601   10200602   10200603   10200604   10300601   10300602  
10300603   10500106   10500206	ICI Boilers - Natural Gas	SCR	SCR	90.0	80

NOX	30500606	Cement Manufacturing - Dry	SCR	SCR	90.0	80

NOX	30500706	Cement Manufacturing - Wet	SCR	SCR	90.0	80

NOX	30300934	Iron & Steel Mills - Annealing	SCR	SCR	90.0	85

NOX	10200701   10200704   10200707   10200710   10200799   10201402  
10300701   10300799	ICI Boilers - Process Gas	SCR	SCR	90.0	80

NOX	10200802   10200804	ICI Boilers - Coke	SCR	SCR	90.0	70

NOX	10201002	ICI Boilers - LPG	SCR	SCR	90.0	80

NOX	10201301   10201302	ICI Boilers - Liquid Waste	SCR	SCR	90.0	80

NOX	30700110	Sulfate Pulping - Recovery Furnaces	SCR	SCR	90.0	80

NOX	30100306	Ammonia Production – 

Pri. Reformer, Nat. Gas	SCR	SCR	90.0	80

	30500622

30500623	Cement Kilns	Biosolid Injection	Biosolid Injection	40.0	23

NOX	30590013   30190013   30190014   39990013	Industrial  and
Manufacturing Incinerators	SNCR	SCR	90.0	45

NOX	30101301   30101302	Nitric Acid Manufacturing	SNCR	SCR	90.0	908

NOX	30600201	Fluid Cat. Cracking Units	LNB + FGR	SCR	90.0	901

NOX	30590003	Process Heaters - Process Gas	LNB + SCR	LNB + SCR	90.0	88

NOX	30600101 30600103 30600111	Process Heaters - Distillate Oil	LNB +
SCR	LNB + SCR	90.0	90

NOX	30600106 30600199	Process Heaters - Residual Oil	LNB + SCR	LNB + SCR
90.0	80

NOX	30600102 30600105	Process Heaters - Natural Gas	LNB + SCR	LNB + SCR
90.0	80

NOX	30700104	Sulfate Pulping - Recovery Furnaces	SCR	SCR	90.0	80

NOX	30790013	Pulp and Paper - Natural Gas - Incinerators	SNCR	SCR	90.0
45

NOX	39000201	In-Process; Bituminous Coal; Cement Kiln	SNCR - urea based
SCR	90.0	50

NOX	39000203	In-Process; Bituminous Coal; Lime Kiln	SNCR - urea based
SCR	90.0	50

NOX	39000289	In-Process Fuel Use;Bituminous Coal; Gen	SNCR	SCR	90.0	40

NOX	39000489	In-Process Fuel Use; Residual Oil; Gen	LNB	SCR	90.0	37

NOX	39000689	In-Process Fuel Use; Natural Gas; Gen	LNB	SCR	90.0	50

NOX	39000701	In-Proc;Process Gas;Coke Oven/Blast Furn	LNB + FGR	SCR	90.0
55

NOX	39000789	In-Process; Process Gas; Coke Oven Gas	LNB	SCR	90.0	50

NOX	50100101   50100506   50200506   50300101   50300102   50300104  
50300506   50100102	Solid Waste Disp;Gov;Other Incin;Sludge	SNCR	SCR
90.0	45



The last category of supplemental controls is control technologies
currently in our control measures database being applied to SCCs not
controlled currently in AirControlNET.  

Table 3a.3 Supplemental Emission Control Measures Applied in Modeled
Attainment Strategies for the Ozone NAAQS RIA –Control technologies
currently in our Control Measures Database Applied to New Source types

Pollutant	SCC	SCC Description	Control Technology	Control Efficiency

NOX	39000602	Cement Manufacturing - Dry	SCR	90.0

NOX	30501401	Glass Manufacturing - General	OXY-Firing	85.0

NOX	30302351 30302352 30302359	Taconite Iron Ore Processing  -
Induration - Coal or Gas	SCR	90.0

NOX	10100101	External Combustion Boilers;Electric Generation;Anthracite
Coal;Pulverized Coal	SNCR	40.0

NOX	10100202	External Combustion Boilers;Electric
Generation;Bituminous/Subbituminous Coal;Pulverized Coal: Dry Bottom
(Bituminous Coal)	SNCR	40.0

NOX	10100204	External Combustion Boilers;Electric
Generation;Bituminous/Subbituminous Coal;Spreader Stoker (Bituminous
Coal)	SNCR	40.0

NOX	10100212	External Combustion Boilers;Electric
Generation;Bituminous/Subbituminous Coal;Pulverized Coal: Dry Bottom
(Tangential) (Bituminous Coal)	SNCR	40.0

NOX	10100401	External Combustion Boilers;Electric Generation;Residual
Oil;Grade 6 Oil: Normal Firing	SNCR	50.0

NOX	10100404	External Combustion Boilers;Electric Generation;Residual
Oil;Grade 6 Oil: Tangential Firing	SNCR	50.0

NOX	10100501	External Combustion Boilers;Electric Generation;Distillate
Oil;Grades 1 and 2 Oil	SNCR	50.0

NOX	10100601	External Combustion Boilers;Electric Generation;Natural
Gas;Boilers > 100 Million Btu/hr except Tangential	NGR 	50.0

NOX	10100602	External Combustion Boilers;Electric Generation;Natural
Gas;Boilers < 100 Million Btu/hr except Tangential	NGR 	50.0

NOX	10100604	External Combustion Boilers;Electric Generation;Natural
Gas;Tangentially Fired Units	NGR 	50.0

NOX	10101202	External Combustion Boilers;Electric Generation;Solid
Waste;Refuse Derived Fuel	SNCR	50.0

NOX	20200253	Internal Comb. Engines/Industrial/Natural Gas/4-cycle Rich
Burn	NSCR 	90



3a.2Mobile Controls/Rules Used in Baseline and Control Scenarios

3a.2.1 Diesel Retrofits and Vehicle Replacement 

Retrofitting heavy-duty diesel vehicles and equipment manufactured
before stricter standards are in place – in 2007-2010 for highway
engines and in 2011-2014 for most nonroad equipment – can provide NOX
and HC benefits.  The retrofit strategies included in the RIA retrofit
measure are:

Installation of emissions after-treatment devices called selective
catalytic reduction (“SCRs”) 

Rebuilding nonroad engines (“rebuild/upgrade kit”)

We chose to focus on these strategies due to their high NOx emissions
reduction potential and widespread application.  Additional retrofit
strategies include, but are not limited to, lean NOx catalyst systems
– which are another type of after-treatment device – and alternative
fuels.  Additionally, SCRs are currently the most likely type of control
technology to be used to meet EPA’s NOx 2007-2010 requirements for HD
diesel trucks and 2008-2011 requirements for nonroad equipment. We
looked at options of applying this measure to 50% and 100% of the fleet
that do not meet EPA’s more stringent standards and are still expected
to be operating in 2020. Actual emissions reductions may vary
significantly by strategy and by the type and age of the engine and its
application.  

To estimate the potential emissions reductions from this measure, we
applied a mix of two retrofit strategies (SCRs and rebuild/upgrade kits)
for the 2020 inventory of:

Heavy-duty highway trucks class 6 & above, Model Year 1995-2009

All diesel nonroad engines, Model Year 1991-2007, except for locomotive,
marine, pleasure craft, & aircraft engines

Class 6 and above trucks comprise the bulk of the NOx emissions
inventory from heavy-duty highway vehicles, so we did not include trucks
below class 6. We chose not to include locomotive and marine engines in
our analysis since EPA has proposed regulations to address these
engines, which will significantly impact the emissions inventory and
emission reduction potential from retrofits in 2020.  There was also not
enough data available to assess retrofit strategies for existing
aircraft and pleasure craft engines, so we did not include them in this
analysis.  In addition, EPA is in the process of negotiating standards
for new aircraft engines.

The lower bound in the model year range – 1995 for highway vehicles
and 1991 for nonroad engines – reflects the first model year in which
emissions after-treatment devices can be reliably applied to the
engines.  Due to a variety of factors, devices are at a higher risk of
failure for earlier model years.  We expect the engines manufactured
before the lower bound year that are still in existence in 2020 to be
retired quickly due to natural turnover, therefore, we have not included
strategies for pre-1995/1991 engines because of the strategies’
relatively small impact on emissions. The upper bound in the model year
range reflects the last year before more stringent emissions standards
will be fully phased-in.

We chose the type of strategy to apply to each model year of highway
vehicles and nonroad equipment based on our technical assessment of
which strategies would achieve reliable results at the lowest cost. 
After-treatment devices can be more cost-effective than rebuild and vice
versa depending on the emissions rate, application, usage rates, and
expected life of the engine.  The performance of after-treatment
devices, for example, depends heavily upon the model year of the engine;
some older engines may not be suitable for after-treatment devices and
would be better candidates for rebuild/upgrade kit.  In certain cases,
nonroad engines may not be suitable for either after-treatment devices
or rebuild, which is why we estimate that retrofits are not suitable for
5% of the nonroad fleet.  The mix of strategies employed in this RIA for
highway vehicles and nonroad engines are presented in Table 3a.4 and
Table 3a.5, respectively.  The groupings of model years for highway
vehicles reflect changes in EPA’s published emissions standards for
new engines.  

Table 3a.4 Application of Retrofit Strategy for Highway Vehicles by
Percentage of Fleet

Model Year 	       SCR 

<1995	0%

1995-2006	100%

2007-2009	50%

>2009	0%



Table 3a.5 Application of Retrofit Strategy for Nonroad Equipment by
Percentage of Fleet

Model Year	Rebuild/Upgrade kit	SCR

1991-2007	50%	50%



The expected emissions reductions from SCR’s are based on data derived
from EPA regulations (Control of Emissions of Air Pollution from 2004
and Later Model Year Heavy-duty Highway Engines and Vehicles published
October 2000), interviews with component manufacturers, and EPA’s
Summary of Potential Retrofit Technologies.  This information is
available at   HYPERLINK
"http://www.epa.gov/otaq/retrofit/retropotentialtech.htm" 
www.epa.gov/otaq/retrofit/retropotentialtech.htm .  The estimates for
highway vehicles and nonroad engines are presented in Table 3a.6 and
Table 3a.7, respectively.  

Table 3a.6: Percentage Emissions Reduction by Highway Vehicle Retrofit
Strategy

 	PM	CO	HC	NOx

SCR (+DPF)	90%	90%	90%	70%



Table 3a.7: Percentage Emissions Reduction by Nonroad Equipment Retrofit
Strategy

Strategy	PM	CO	HC	NOx

SCR (+DPF)	90%	90%	90%	70%

Rebuild/Upgrade Kit	30%	15%	70%	40%



It is important to note that there is a great deal of variability among
types of engines (especially nonroad), the applicability of retrofit
strategies, and the associated emissions reductions.  We applied the
retrofit emissions reduction estimates to engines across the board (e.g.
retrofits for bulldozers are estimated to produce the same percentage
reduction in emissions as for agricultural mowers).  We did this in
order to simplify model runs, and, in some cases, where we did not have
enough data to differentiate emissions reductions for different types of
highway vehicles and nonroad equipment.  We believe the estimates used
in the RIA, however, reflect the best available estimates of emissions
reductions that can be expected from retrofitting the heavy-duty diesel
fleet.

Using the retrofit module in EPA’s National Mobile Inventory Model
(NMIM) available at http://www.epa.gov/otaq/nmim.htm, we calculated the
total percentage reduction in emissions (PM, NOx, HC, and CO) from the
retrofit measure for each relevant engine category (source category
code, or SCC) for each  county in 2020. To evaluate this change in the
emissions inventory, we conducted both a baseline and control analysis. 
Both analyses were based on NMIM 2005 (version NMIM20060310),
NONROAD2005 (February 2006), and MOBILE6.2.03 which included the updated
diesel PM file PMDZML.csv dated March 17, 2006.

For the control analysis, we applied the retrofit measure corresponding
to the percent reductions of the specified pollutants in Tables 3a.6 and
3a.7 to the specified model years in Tables 1 and 2 of the relevant
SCCs.  Fleet turnover rates are modeled in the NMIM, so we applied the
retrofit measure to the 2007 fleet inventory, and then evaluated the
resulting emissions inventory in 2020. The timing of the application of
the retrofit measure is not a factor; retrofits only need to take place
prior to the attainment date target (2020 for this RIA).  For example,
if retrofit devices are installed on 1995 model year bulldozers in 2007,
the only impact on emissions in 2020 will be from the expected inventory
of 1995 model year bulldozer emissions in 2020. 

We then compared the baseline and control analyses to determine the
percent reduction in emissions we estimate from this measure for the
relevant SCC codes in the targeted nonattainment areas. 

Pollutants and Source Categories Affected by Measure (SCC) 

NOx, and HC 

3a.2.2 Implement Continuous Inspection and Maintenance Using Remote
Onboard Diagnostics (OBD)

Continuous Inspection and Maintenance (I/M) is a new way to check the
status of OBD systems on light-duty OBD-equipped vehicles.  It involves
equipping subject vehicles with some type of transmitter that attaches
to the OBD port.  The device transmits the status of the OBD system to
receivers distributed around the I/M area.  Transmission may be through
radio-frequency, cellular or wi-fi means.  Radio frequency and cellular
technologies are currently being used in the states of Oregon,
California and Maryland. 

Current I/M programs test light-duty vehicles on a periodic basis –
either annually or biennially.  Emission reduction credit is assigned
based on test frequency.  Using Continuous I/M, vehicles are
continuously monitored as they are operated throughout the
non-attainment area.  When a vehicle experiences an OBD failure, the
motorist is notified and is required to get repairs within the normal
grace period – typically about a month.  Thus, Continuous I/M will
result in repairs happening essentially whenever a malfunction occurs
that would cause the check engine light to illuminate. The continuous
I/M program is applied to the same fleet of vehicles as the current
periodic I/M programs.   Currently, MOBILE6 provides an increment of
benefit when going from a biennial program to an annual program.  The
same increment of credit applies going from an annual program to a
continuous program.

 

Pollutants and Source Categories Affected by Measure (SCC):

All 1996 and newer light-duty gasoline vehicles and trucks: 

All 1996 and newer 2201001000 Light Duty Gasoline Vehicles (LDGV),
Total: All Road Types

All 1996 and newer 2201020000 Light Duty Gasoline Trucks 1 (LDGT1),
Total: All Road Types

All 1996 and newer 2201040000 Light Duty Gasoline Trucks 2 (LDGT2),
Total: All Road Types

OBD systems on light duty vehicles are required to illuminate the
malfunction indicator lamp whenever emissions of HC, CO or NOx would
exceed 1.5 times the vehicle’s certification standard.  Thus, the
benefits of this measure will affect all three criteria pollutants. 
MOBILE6 was used to estimate the emission reduction benefits of
Continuous I/M, using the methodology discussed above.  

3a.2.3 Eliminating Long Duration Truck Idling

Virtually all long duration truck idling – idling that lasts for
longer than 15 minutes – from heavy-duty diesel class 8a and 8b trucks
can be eliminated with two strategies: 

truck stop & terminal electrification (TSE) 

mobile idle reduction technologies (MIRTs) such as auxiliary power
units, generator sets, and direct-fired heaters 

TSE can eliminate idling when trucks are resting at truck stops or
public rest areas and while trucks are waiting to perform a task at
private distribution terminals.  When truck spaces are electrified,
truck drivers can shut down their engines and use electricity to power
equipment which supplies air conditioning, heat, and electrical power
for on-board appliances.  

MIRTs can eliminate long duration idling from trucks that are stopped
away from these central sites.  For a more complete list of MIRTs see
EPA’s Idle Reduction Technology page at   HYPERLINK
"http://www.epa.gov/otaq/smartway/idlingtechnologies.htm" \t "_blank" 
http://www.epa.gov/otaq/smartway/idlingtechnologies.htm . 

This measure demonstrates the potential emissions reductions if every
class 8a and 8b truck is equipped with a MIRT or has dependable access
to sites with TSE in 2020.

 

To estimate the potential emissions reduction from this measure, we
applied a reduction equal to the full amount of the emissions attributed
to long duration idling in the MOBILE model, which is estimated to be
3.4% of the total NOx emissions from class 8a and 8b heavy duty diesel
trucks.  Since the MOBILE model does not distinguish between idling and
operating emissions, EPA estimates idling emissions in the inventory
based on fuel conversion factors.  The inventory in the MOBILE model,
however, does not fully capture long duration idling emissions.  There
is evidence that idling may represent a much greater share than 3.4% of
the real world inventory, based on engine control module data from long
haul trucking companies.  As such, we believe the emissions reductions
demonstrated from this measure in the RIA represent ambitious but
realistic targets. For more information on determining baseline idling
activity see EPA’s "Guidance for Quantifying and Using Long-Duration
Truck Idling Emission Reductions in State Implementation Plans and
Transportation Conformity” available at
http://www.epa.gov/smartway/idle-guid.htm. 

 

Pollutants and Source Categories Affected by Measure (SCC): NOx

Table 3a.8 Class 8a and 8b heavy duty diesel trucks (decrease NOx for
all SCCs)

SCC	Note: All SCC Descriptions below begin with "Mobile Sources; Highway
Vehicles - Diesel;"

2230074110	Heavy Duty Diesel Vehicles (HDDV) Class 8A & 8B;Rural
Interstate: Total

2230074130	Heavy Duty Diesel Vehicles (HDDV) Class 8A & 8B;Rural Other
Principal Arterial: Total

2230074150	Heavy Duty Diesel Vehicles (HDDV) Class 8A & 8B;Rural Minor
Arterial: Total

2230074170	Heavy Duty Diesel Vehicles (HDDV) Class 8A & 8B;Rural Major
Collector: Total

2230074190	Heavy Duty Diesel Vehicles (HDDV) Class 8A & 8B;Rural Minor
Collector: Total

2230074210	Heavy Duty Diesel Vehicles (HDDV) Class 8A & 8B;Rural Local:
Total

2230074230	Heavy Duty Diesel Vehicles (HDDV) Class 8A & 8B;Urban
Interstate: Total

2230074250	Heavy Duty Diesel Vehicles (HDDV) Class 8A & 8B;Urban Other
Freeways and Expressways: Total

2230074270	Heavy Duty Diesel Vehicles (HDDV) Class 8A & 8B;Urban Other
Principal Arterial: Total

2230074290	Heavy Duty Diesel Vehicles (HDDV) Class 8A & 8B;Urban Minor
Arterial: Total

2230074310	Heavy Duty Diesel Vehicles (HDDV) Class 8A & 8B;Urban
Collector: Total

2230074330	Heavy Duty Diesel Vehicles (HDDV) Class 8A & 8B;Urban Local:
Total



Estimated Emissions Reduction from Measure (%): 3.4 % decrease in NOx
for all SCCs affected by measure 

3a.2.4 Commuter Programs

Commuter programs recognize and support employers who provide incentives
to employees to reduce light-duty vehicle emissions.  Employers
implement a wide range of incentives to affect change in employee
commuting habits including transit subsidies, bike-friendly facilities,
telecommuting policies, and preferred parking for vanpools and carpools.
 The commuter measure in this RIA reflects a mixed package of
incentives.

This measure demonstrates the potential emissions reductions from
providing commuter incentives to 10% and 25% of the commuter population
in 2020.

We used the findings from a recent Best Workplaces for Commuters survey,
which was an EPA sponsored employee trip reduction program, to estimate
the potential emissions reductions from this measure.  The BWC survey
found that, on average, employees at workplaces with comprehensive
commuter programs emit 15% fewer emissions than employees at workplaces
that do not offer a comprehensive commuter program.  

We believe that getting 10-25% of the workforce involved in commuter
programs is realistic. For modeling purposes, we divided the commuter
programs measure into two program penetration rates: 10% and 25%.  This
was meant to provide flexibility to model a lower penetration rate for
areas that need only low levels of emissions reductions to achieve
attainment. 

According to the 2001 National Household Transportation Survey (NHTS)
published by DOT, commute VMT represents 27% of total VMT.  Based on
this information, we calculated that BWC would reduce light-duty
gasoline emissions by 0.4% and 1% with a 10% and 25% program penetration
rate, respectively.

Pollutants and Source Categories Affected by Measure (SCC): NOx, and VOC

Table 3a.9 All light-duty gasoline vehicles and trucks

SCC	Note: All SCC Descriptions below begin with "Mobile Sources; Highway
Vehicles - Gasoline;"

2201001110	Light Duty Gasoline Vehicles (LDGV);Rural Interstate: Total

2201001130	Light Duty Gasoline Vehicles (LDGV);Rural Other Principal
Arterial: Total

2201001150	Light Duty Gasoline Vehicles (LDGV);Rural Minor Arterial:
Total

2201001170	Light Duty Gasoline Vehicles (LDGV);Rural Major Collector:
Total

2201001190	Light Duty Gasoline Vehicles (LDGV);Rural Minor Collector:
Total

2201001210	Light Duty Gasoline Vehicles (LDGV);Rural Local: Total

2201001230	Light Duty Gasoline Vehicles (LDGV);Urban Interstate: Total

2201001250	Light Duty Gasoline Vehicles (LDGV);Urban Other Freeways and
Expressways: Total

2201001270	Light Duty Gasoline Vehicles (LDGV);Urban Other Principal
Arterial: Total

2201001290	Light Duty Gasoline Vehicles (LDGV);Urban Minor Arterial:
Total

2201001310	Light Duty Gasoline Vehicles (LDGV);Urban Collector: Total

2201001330	Light Duty Gasoline Vehicles (LDGV);Urban Local: Total

2201020110	Light Duty Gasoline Trucks 1 & 2 (M6) = LDGT1 (M5);Rural
Interstate: Total

2201020130	Light Duty Gasoline Trucks 1 & 2 (M6) = LDGT1 (M5);Rural
Other Principal Arterial: Total

2201020150	Light Duty Gasoline Trucks 1 & 2 (M6) = LDGT1 (M5);Rural
Minor Arterial: Total

2201020170	Light Duty Gasoline Trucks 1 & 2 (M6) = LDGT1 (M5);Rural
Major Collector: Total

2201020190	Light Duty Gasoline Trucks 1 & 2 (M6) = LDGT1 (M5);Rural
Minor Collector: Total

2201020210	Light Duty Gasoline Trucks 1 & 2 (M6) = LDGT1 (M5);Rural
Local: Total

2201020230	Light Duty Gasoline Trucks 1 & 2 (M6) = LDGT1 (M5);Urban
Interstate: Total

2201020250	Light Duty Gasoline Trucks 1 & 2 (M6) = LDGT1 (M5);Urban
Other Freeways and Expressways: Total

2201020270	Light Duty Gasoline Trucks 1 & 2 (M6) = LDGT1 (M5);Urban
Other Principal Arterial: Total

2201020290	Light Duty Gasoline Trucks 1 & 2 (M6) = LDGT1 (M5);Urban
Minor Arterial: Total

2201020310	Light Duty Gasoline Trucks 1 & 2 (M6) = LDGT1 (M5);Urban
Collector: Total

2201020330	Light Duty Gasoline Trucks 1 & 2 (M6) = LDGT1 (M5);Urban
Local: Total

2201040110	Light Duty Gasoline Trucks 3 & 4 (M6) = LDGT2 (M5);Rural
Interstate: Total

2201040130	Light Duty Gasoline Trucks 3 & 4 (M6) = LDGT2 (M5);Rural
Other Principal Arterial: Total

2201040150	Light Duty Gasoline Trucks 3 & 4 (M6) = LDGT2 (M5);Rural
Minor Arterial: Total

2201040170	Light Duty Gasoline Trucks 3 & 4 (M6) = LDGT2 (M5);Rural
Major Collector: Total

2201040190	Light Duty Gasoline Trucks 3 & 4 (M6) = LDGT2 (M5);Rural
Minor Collector: Total

2201040210	Light Duty Gasoline Trucks 3 & 4 (M6) = LDGT2 (M5);Rural
Local: Total

2201040230	Light Duty Gasoline Trucks 3 & 4 (M6) = LDGT2 (M5);Urban
Interstate: Total

2201040250	Light Duty Gasoline Trucks 3 & 4 (M6) = LDGT2 (M5);Urban
Other Freeways and Expressways: Total

2201040270	Light Duty Gasoline Trucks 3 & 4 (M6) = LDGT2 (M5);Urban
Other Principal Arterial: Total

2201040290	Light Duty Gasoline Trucks 3 & 4 (M6) = LDGT2 (M5);Urban
Minor Arterial: Total

2201040310	Light Duty Gasoline Trucks 3 & 4 (M6) = LDGT2 (M5);Urban
Collector: Total

2201040330	Light Duty Gasoline Trucks 3 & 4 (M6) = LDGT2 (M5);Urban
Local: Total



Estimated Emissions Reduction from Measure (%):

With a 10% program penetration rate:	0.4% 

With a 25% program penetration rate:	1% 

3a.2.5 Reduce Gasoline RVP from 7.8 to 7.0 in Remaining Nonattainment
Areas

Volatility is the property of a liquid fuel that defines its evaporation
characteristics.  RVP is an abbreviation for "Reid vapor pressure," a
common measure of gasoline volatility, as well as a generic term for
gasoline volatility.  EPA regulates the vapor pressure of all gasoline
during the summer months (June 1 to September 15 at retail stations). 
Lower RVP helps to reduce VOCs, which are a precursor to ozone
formation. This control measure represents the use of gasoline with a
RVP limit of 7.0 psi from May through September in counties with an
ozone season RVP value greater than 7.0 psi.

Under section 211(c)(4)(C) of the CAA, EPA may approve a non-identical
state fuel control as a SIP provision, if the state demonstrates that
the measure is necessary to achieve the national primary or secondary
ambient air quality standard (NAAQS) that the plan implements. EPA can
approve a state fuel requirement as necessary only if no other measures
would bring about timely attainment, or if other measures exist but are
unreasonable or impracticable.

Pollutants and Source Categories Affected by Measure (SCC):

All light-duty gasoline vehicles and trucks: Affected SCC:

2201001000 Light Duty Gasoline Vehicles (LDGV), Total: All Road Types

2201020000 Light Duty Gasoline Trucks 1 (LDGT1), Total: All Road Types

2201040000 Light Duty Gasoline Trucks 2 (LDGT2), Total: All Road Types

2201070000 Heavy Duty Gasoline Vehicles (HDGV), Total: All Road Types

2201080000 Motorcycles (MC), Total: All Road Types

3a.2.6 Application order for Onroad and Nonroad Mobile Controls

Application order- 0.084 Mobile

Eliminate Long Duration Idling

ONRetrofit

LOWRVP

Best Workplaces for Commuters

Application order- 0.084 Nonroad

Diesel C1&C2 Marine/Diesel C3 Marine - 90% Rule (adding controls for
SCCs for residual fuel)

ICAO Engine NOx Standards for Commercial Aircraft

NRRetrofit

LOWRVP

Application order- 0.070 Mobile

Eliminate Long Duration Idling

Inspection and Maintenance

ONRetrofit

LOWRVP

Best Workplaces for Commuters

Application order – 0.070  Nonroad

Diesel C1&C2 Marine/Diesel C3 Marine - 90% Rule (adding controls for
SCCs for residual fuel)

ICAO Engine NOx Standards for Commercial Aircraft

NRRetrofit

LOWRVP

3a.3  EGU Controls Used in the Control Strategy 

CAIR

The data and projections presented in Section 3.2.2 cover the electric
power sector, an industry that will achieve significant emission
reductions under the Clean Air Interstate Rule (CAIR) over the next 10
to 15 years. Based on an assessment of the emissions contributing to
interstate transport of air pollution and available control measures,
EPA determined that achieving required reductions in the identified
States by controlling emissions from power plants is highly cost
effective. CAIR will permanently cap emissions of sulfur dioxide (SO2)
and nitrogen oxides (NOx) in the eastern United States. CAIR achieves
large reductions of SO2 and/or NOx emissions across 28 eastern states
and the District of Columbia. 

Figure 3a.1 CAIR Affected Region

When fully implemented, CAIR will reduce SO2 emissions in these states
by over 70% and NOx emissions by over 60% from 2003 levels (some of
which are due to NOx SIP Call). This will result in significant
environmental and health benefits and will substantially reduce
premature mortality in the eastern United States. The benefits will
continue to grow each year with further implementation. CAIR was
designed with current air quality standard in mind, and requires
significant emission reductions in the East, where they are needed most
and where transport of pollution is a major concern. CAIR will bring
most areas in the Eastern US into attainment with the current ozone and
current PM2.5 standards. Some areas will need to adopt additional local
control measures beyond CAIR. CAIR is a regional solution to address
transport, not a solution to all local nonattainment issues. The large
reductions anticipated with CAIR, in conjunction with reasonable
additional local control measures for SO2, NOx, and direct PM, will move
States towards attainment in a deliberate and logical manner. 

Based on the final State rules that have been submitted and the proposed
State rules that EPA has reviewed, EPA believes that all States intend
to use the CAIR trading programs as their mechanism for meeting the
emission reduction requirements of CAIR.

The analysis in this section reflects these realities and attempts to
show, in an illustrative fashion, the costs and impacts of meeting a
proposed 8-hr ozone standard of 0.070 for the power sector.

Integrated Planning Model and Background

CAIR was designed to achieve significant emissions reductions in a
highly cost-effective manner to reduce the transport of fine particles
that have been found to contribute to nonattainment. EPA analysis has
found that the most efficient method to achieve the emissions reduction
targets is through a cap-and-trade system on the power sector that
States have the option of adopting. The modeling done with IPM assumes a
region-wide cap and trade system on the power sector for the States
covered. 

It is important to note that the analysis herein uses the Integrated
Planning Model (IPM) v2.1.9 to ensure consistency with the analysis
presented in 2006 PM NAAQS RIA and report incremental results.  EPA’s
IPM v2.1.9 incorporates Federal and State rules and regulations adopted
before March 2004 and various NSR settlements.  A detailed discussion of
uncertainties associated with the EGU sector can be found in 2006 PM
NAAQS RIA (pg. 3-50).  A newer version of the model (IPM v3.0) is
available which includes input and model assumption updates in modeling
power sector.  IPM v3.0 will be used in the Final Ozone NAAQS RIA as
part of the updated modeling platform.  Additionally, other control
strategies are being considered that may be applicable to the EGU
sector, which would be presented in the final Ozone RIA. 

The economic modeling using IPM presented in this and other chapters has
been developed for specific analyses of the power sector. EPA’s
modeling is based on its best judgment for various input assumptions
that are uncertain, particularly assumptions for future fuel prices and
electricity demand growth. To some degree, EPA addresses the uncertainty
surrounding these two assumptions through sensitivity analyses. More
detail on IPM can be found in the model documentation, which provides
additional information on the assumptions discussed here as well as all
other assumptions and inputs to the model (  HYPERLINK
"http://www.epa.gov/airmarkets/progsregs/epa-ipm/past-modeling.html" 
http://www.epa.gov/airmarkets/progsregs/epa-ipm/past-modeling.html ).

EGU NOx Emission Control Technologies

The Integrated Planning Model v2.1.9 (IPM) includes SO2, NOx, and
mercury (Hg) emission control technology options for meeting existing
and future federal, regional, and state, SO2, NOx and Hg emission
limits. The NOx control technology options include Selective Catalytic
Reduction (SCR) system and Selective Non-Catalytic Reduction (SNCR)
systems.  It is important to note that beyond these emission control
options, IPM offers other compliance options for meeting emission
limits.  These include fuel switching, re-powering, and adjustments in
the dispatching of electric generating units.    

Table 3a.10 summarizes retrofit NOx emission control performance
assumptions.

Table 3a.10.  Summary of Retrofit NOx Emission Control Performance
Assumptions

	Selective Catalytic Reduction 

(SCR)	Selective Non-Catalytic Reduction

 (SNCR)

Unit Type	Coal	Oil/Gas*	Coal	Oil/Gas*

Percent Removal	90% 

down to 0.06 lb/mmBtu	80%	35%	50%

Size Applicability	Units  100 MW	Units  25 MW	Units  25 MW

and

Units < 200 MW	Units  25 MW

* Controls to oil- or gas-fired EGUs are not applied as part of the EGU
control strategy included in this RIA.

Existing coal-fired units that are retrofit with SCR have a NOx removal
efficiency of 90%, with a minimum controlled NOx emission rate of 0.06
lb/mmBtu in IPM v2.1.9..  Potential (new) coal-fired, combined cycle,
and IGCC units are modeled to be constructed with SCR systems and
designed to have emission rates ranging between 0.02 and 0.06 lb
NOx/mmBtu.  

Detailed cost and performance derivations for NOx controls are discussed
in detail in the EPA’s documentation of IPM
(http://www.epa.gov/airmarkets/progsregs/epa-ipm/past-modeling.html).

3a.4 Emissions Reductions by Sector

Figures 3a.2- 3a.6 show the NOx reductions for each sector under the
0.070 ppm control stategy.  

Figure 3a.2 Tons of Nitrogen Oxide (NOx) Emissions Reduced from
Electrical Generating Unit (EGU) Sources*

*Reductions are negative and increases are positive

**The -99 - +100 range is not shown because these are small county-level
NOx reductions or increases that likely had little to no impact on ozone
estimates.  Most counties in this range had NOx differences of under 1
ton.

                 

Figure 3a.3 Tons of Nitrogen Oxide (NOx) Emissions Reduced from Non-EGU
Point Sources*

*Reductions are negative and increases are positive

**The -99 - 0 range is not shown because these are small county-level
NOx reductions or increases that likely had little to no impact on ozone
estimates.  Most counties in this range had NOx differences of under 1
ton.

Figure 3a.4 Tons of Nitrogen Oxide (NOx) Emissions Reduced from Area
Sources*

*Reductions are negative and increases are positive

**The -99 – 0 range is not shown because these are small county-level
NOx reductions or increases that likely had little to no impact on ozone
estimates.  Most counties in this range had NOx differences of under 1
ton.

Figure 3a.5 Tons of Nitrogen Oxide (NOx) Emissions Reduced from Nonroad
Sources*

*Reductions are negative and increases are positive

**The -99 - 0 range is not shown because these are small county-level
NOx reductions or increases that likely had little to no impact on ozone
estimates.  Most counties in this range had NOx differences of under 1
ton.

Figure 3a.6 Tons of Nitrogen Oxide (NOx) Emissions Reduced from Onroad
Sources*

*Reductions are negative and increases are positive

**The -99 - 0 range is not shown because these are small county-level
NOx reductions or increases that likely had little to no impact on ozone
estimates.  Most counties in this range had NOx differences of under 1
ton.

3a.5 Change in Ozone Concentrations Between Baseline and Post-0.070 ppm
Control Strategy Modeling

Table 3a.11 Changes in Ozone Concentrations Between Baseline and
Post-0.070 ppm Control Strategy Modeling

State	County	Baseline 

8-hour ozone DV (ppm)	Control Scenario 

8-hour ozone 

DV (ppm)	Change (ppm)

Alabama	Baldwin	0.067	0.066	0.001

Alabama	Clay	0.060	0.056	0.004

Alabama	Elmore	0.062	0.060	0.002

Alabama	Jefferson	0.064	0.063	0.001

Alabama	Madison	0.063	0.061	0.002

Alabama	Mobile	0.068	0.068	0.000

Alabama	Montgomery	0.061	0.060	0.001

Alabama	Morgan	0.066	0.065	0.001

Alabama	Shelby	0.066	0.065	0.001

Alabama	Tuscaloosa	0.057	0.056	0.001

Arizona	Maricopa	0.078	0.077	0.001

Arizona	Pinal	0.072	0.071	0.001

Arkansas	Crittenden	0.075	0.072	0.003

Arkansas	Pulaski	0.069	0.068	0.001

California	Alameda	0.067	0.067	0.000

California	Amador	0.068	0.068	0.000

California	Butte	0.069	0.069	0.000

California	Calaveras	0.073	0.073	0.000

California	Colusa	0.059	0.059	0.000

California	Contra Costa	0.070	0.070	0.000

California	El Dorado	0.080	0.080	0.000

California	Fresno	0.092	0.092	0.000

California	Glenn	0.060	0.060	0.000

California	Imperial	0.072	0.072	0.000

California	Kern	0.096	0.096	0.000

California	Kings	0.079	0.079	0.000

California	Lake	0.053	0.053	0.000

California	Los Angeles	0.105	0.105	0.000

California	Madera	0.075	0.075	0.000

California	Mariposa	0.073	0.073	0.000

California	Merced	0.080	0.080	0.000

California	Monterey	0.054	0.054	0.000

California	Napa	0.051	0.051	0.000

California	Nevada	0.076	0.076	0.000

California	Orange	0.066	0.065	0.001

California	Placer	0.076	0.076	0.000

California	Riverside	0.102	0.102	0.000

California	Sacramento	0.076	0.076	0.000

California	San Benito	0.067	0.067	0.000

California	San Bernardino	0.129	0.129	0.000

California	San Diego	0.077	0.077	0.000

California	San Joaquin	0.067	0.067	0.000

California	San Luis Obispo	0.053	0.053	0.000

California	Santa Barbara	0.065	0.065	0.000

California	Santa Clara	0.065	0.065	0.000

California	Santa Cruz	0.054	0.055	-0.001

California	Shasta	0.058	0.058	0.000

California	Solano	0.057	0.057	0.000

California	Sonoma	0.049	0.049	0.000

California	Stanislaus	0.076	0.076	0.000

California	Sutter	0.065	0.065	0.000

California	Tehama	0.066	0.066	0.000

California	Tulare	0.088	0.088	0.000

California	Tuolumne	0.073	0.073	0.000

California	Ventura	0.079	0.080	-0.001

California	Yolo	0.064	0.064	0.000

Colorado	Adams	0.061	0.060	0.001

Colorado	Arapahoe	0.073	0.072	0.001

Colorado	Boulder	0.066	0.064	0.002

Colorado	Denver	0.068	0.067	0.001

Colorado	Douglas	0.076	0.076	0.000

Colorado	El Paso	0.064	0.063	0.001

Colorado	Jefferson	0.078	0.076	0.002

Colorado	Larimer	0.069	0.067	0.002

Colorado	Weld	0.067	0.065	0.002

Connecticut	Fairfield	0.088	0.087	0.001

Connecticut	Hartford	0.069	0.067	0.002

Connecticut	Litchfield	0.063	0.061	0.002

Connecticut	Middlesex	0.081	0.080	0.001

Connecticut	New Haven	0.084	0.083	0.001

Connecticut	New London	0.072	0.070	0.002

Connecticut	Tolland	0.071	0.069	0.002

D.C.	Washington	0.076	0.073	0.003

Delaware	Kent	0.072	0.070	0.002

Delaware	New Castle	0.075	0.073	0.002

Delaware	Sussex	0.070	0.068	0.002

Florida	Bay	0.067	0.066	0.001

Florida	Brevard	0.055	0.053	0.002

Florida	Duval	0.058	0.057	0.001

Florida	Escambia	0.069	0.069	0.000

Florida	Hillsborough	0.072	0.071	0.001

Florida	Manatee	0.067	0.065	0.002

Florida	Pasco	0.061	0.060	0.001

Florida	Pinellas	0.064	0.063	0.001

Florida	Santa Rosa	0.065	0.064	0.001

Florida	Sarasota	0.063	0.061	0.002

Georgia	Bibb	0.073	0.069	0.004

Georgia	Chatham	0.057	0.056	0.001

Georgia	Cherokee	0.055	0.052	0.003

Georgia	Cobb	0.072	0.068	0.004

Georgia	Coweta	0.072	0.064	0.008

Georgia	Dawson	0.058	0.055	0.003

Georgia	De Kalb	0.076	0.072	0.004

Georgia	Douglas	0.071	0.067	0.004

Georgia	Fayette	0.069	0.066	0.003

Georgia	Fulton	0.080	0.076	0.004

Georgia	Glynn	0.058	0.057	0.001

Georgia	Gwinnett	0.067	0.064	0.003

Georgia	Henry	0.072	0.068	0.004

Georgia	Murray	0.062	0.059	0.003

Georgia	Muscogee	0.065	0.061	0.004

Georgia	Paulding	0.068	0.065	0.003

Georgia	Richmond	0.067	0.063	0.004

Georgia	Rockdale	0.071	0.067	0.004

Illinois	Adams	0.062	0.057	0.005

Illinois	Champaign	0.064	0.062	0.002

Illinois	Clark	0.057	0.056	0.001

Illinois	Cook	0.083	0.083	0.000

Illinois	Du Page	0.065	0.064	0.001

Illinois	Effingham	0.062	0.061	0.001

Illinois	Hamilton	0.066	0.064	0.002

Illinois	Jersey	0.074	0.069	0.005

Illinois	Kane	0.067	0.066	0.001

Illinois	Lake	0.074	0.073	0.001

Illinois	Macon	0.060	0.059	0.001

Illinois	Macoupin	0.064	0.060	0.004

Illinois	Madison	0.071	0.066	0.005

Illinois	McHenry	0.070	0.068	0.002

Illinois	McLean	0.063	0.061	0.002

Illinois	Peoria	0.066	0.064	0.002

Illinois	Randolph	0.065	0.062	0.003

Illinois	Rock Island	0.058	0.057	0.001

Illinois	Sangamon	0.060	0.058	0.002

Illinois	St Clair	0.072	0.069	0.003

Illinois	Will	0.068	0.067	0.001

Illinois	Winnebago	0.061	0.060	0.001

Indiana	Allen	0.070	0.068	0.002

Indiana	Boone	0.072	0.069	0.003

Indiana	Carroll	0.066	0.064	0.002

Indiana	Clark	0.076	0.074	0.002

Indiana	Delaware	0.069	0.067	0.002

Indiana	Floyd	0.071	0.070	0.001

Indiana	Gibson	0.056	0.054	0.002

Indiana	Greene	0.069	0.067	0.002

Indiana	Hamilton	0.076	0.073	0.003

Indiana	Hancock	0.074	0.071	0.003

Indiana	Hendricks	0.071	0.069	0.002

Indiana	Huntington	0.067	0.065	0.002

Indiana	Jackson	0.068	0.065	0.003

Indiana	Johnson	0.070	0.068	0.002

Indiana	La Porte	0.075	0.073	0.002

Indiana	Lake	0.084	0.083	0.001

Indiana	Madison	0.071	0.068	0.003

Indiana	Marion	0.075	0.072	0.003

Indiana	Morgan	0.070	0.066	0.004

Indiana	Perry	0.071	0.071	0.000

Indiana	Porter	0.078	0.077	0.001

Indiana	Posey	0.071	0.070	0.001

Indiana	Shelby	0.077	0.074	0.003

Indiana	St Joseph	0.069	0.067	0.002

Indiana	Vanderburgh	0.068	0.066	0.002

Indiana	Vigo	0.070	0.065	0.005

Indiana	Warrick	0.068	0.067	0.001

Iowa	Clinton	0.063	0.062	0.001

Iowa	Scott	0.066	0.065	0.001

Kansas	Wyandotte	0.070	0.069	0.001

Kentucky	Bell	0.063	0.062	0.001

Kentucky	Boone	0.067	0.066	0.001

Kentucky	Boyd	0.072	0.067	0.005

Kentucky	Bullitt	0.067	0.064	0.003

Kentucky	Campbell	0.077	0.073	0.004

Kentucky	Carter	0.064	0.061	0.003

Kentucky	Christian	0.066	0.065	0.001

Kentucky	Daviess	0.062	0.062	0.000

Kentucky	Edmonson	0.067	0.066	0.001

Kentucky	Fayette	0.063	0.061	0.002

Kentucky	Graves	0.068	0.066	0.002

Kentucky	Greenup	0.068	0.064	0.004

Kentucky	Hancock	0.067	0.067	0.000

Kentucky	Hardin	0.068	0.065	0.003

Kentucky	Henderson	0.066	0.065	0.001

Kentucky	Jefferson	0.072	0.070	0.002

Kentucky	Jessamine	0.062	0.063	-0.001

Kentucky	Kenton	0.073	0.069	0.004

Kentucky	Livingston	0.071	0.069	0.002

Kentucky	McCracken	0.069	0.067	0.002

Kentucky	McLean	0.065	0.064	0.001

Kentucky	Oldham	0.072	0.070	0.002

Kentucky	Pulaski	0.065	0.064	0.001

Kentucky	Scott	0.056	0.055	0.001

Kentucky	Simpson	0.066	0.065	0.001

Kentucky	Trigg	0.060	0.058	0.002

Kentucky	Warren	0.066	0.065	0.001

Louisiana	Ascension	0.071	0.066	0.005

Louisiana	Bossier	0.073	0.070	0.003

Louisiana	Caddo	0.068	0.065	0.003

Louisiana	Calcasieu	0.072	0.067	0.005

Louisiana	East Baton Rouge	0.077	0.074	0.003

Louisiana	Grant	0.063	0.059	0.004

Louisiana	Iberville	0.076	0.072	0.004

Louisiana	Jefferson	0.072	0.069	0.003

Louisiana	Lafayette	0.070	0.064	0.006

Louisiana	Lafourche	0.072	0.068	0.004

Louisiana	Livingston	0.072	0.068	0.004

Louisiana	Orleans	0.060	0.058	0.002

Louisiana	Ouachita	0.068	0.064	0.004

Louisiana	Pointe Coupee	0.064	0.060	0.004

Louisiana	St Bernard	0.067	0.065	0.002

Louisiana	St Charles	0.068	0.066	0.002

Louisiana	St James	0.069	0.065	0.004

Louisiana	St John The Baptist	0.072	0.069	0.003

Louisiana	St Mary	0.068	0.062	0.006

Louisiana	West Baton Rouge	0.074	0.071	0.003

Maine	Cumberland	0.065	0.063	0.002

Maine	Hancock	0.070	0.067	0.003

Maine	Kennebec	0.060	0.057	0.003

Maine	Knox	0.063	0.060	0.003

Maine	Penobscot	0.062	0.059	0.003

Maine	York	0.069	0.066	0.003

Maryland	Anne Arundel	0.076	0.074	0.002

Maryland	Baltimore	0.077	0.075	0.002

Maryland	Calvert	0.065	0.063	0.002

Maryland	Carroll	0.068	0.066	0.002

Maryland	Cecil	0.078	0.075	0.003

Maryland	Charles	0.070	0.068	0.002

Maryland	Frederick	0.067	0.065	0.002

Maryland	Harford	0.084	0.082	0.002

Maryland	Kent	0.075	0.072	0.003

Maryland	Montgomery	0.072	0.070	0.002

Maryland	Prince Georges	0.075	0.072	0.003

Maryland	Washington	0.067	0.063	0.004

Massachusetts	Barnstable	0.072	0.070	0.002

Massachusetts	Berkshire	0.067	0.066	0.001

Massachusetts	Bristol	0.072	0.069	0.003

Massachusetts	Essex	0.071	0.070	0.001

Massachusetts	Hampden	0.070	0.068	0.002

Massachusetts	Hampshire	0.068	0.066	0.002

Massachusetts	Middlesex	0.067	0.064	0.003

Massachusetts	Suffolk	0.067	0.065	0.002

Massachusetts	Worcester	0.064	0.062	0.002

Michigan	Allegan	0.075	0.072	0.003

Michigan	Benzie	0.070	0.068	0.002

Michigan	Berrien	0.072	0.070	0.002

Michigan	Cass	0.069	0.067	0.002

Michigan	Clinton	0.066	0.062	0.004

Michigan	Genesee	0.067	0.064	0.003

Michigan	Huron	0.070	0.067	0.003

Michigan	Ingham	0.066	0.062	0.004

Michigan	Kalamazoo	0.065	0.062	0.003

Michigan	Kent	0.067	0.064	0.003

Michigan	Lenawee	0.069	0.063	0.006

Michigan	Macomb	0.080	0.078	0.002

Michigan	Mason	0.072	0.070	0.002

Michigan	Missaukee	0.064	0.061	0.003

Michigan	Muskegon	0.074	0.071	0.003

Michigan	Oakland	0.077	0.075	0.002

Michigan	Ottawa	0.070	0.067	0.003

Michigan	St Clair	0.073	0.071	0.002

Michigan	Washtenaw	0.076	0.072	0.004

Michigan	Wayne	0.076	0.073	0.003

Minnesota	Anoka	0.058	0.057	0.001

Minnesota	Washington	0.059	0.059	0.000

Mississippi	De Soto	0.069	0.067	0.002

Mississippi	Hancock	0.070	0.068	0.002

Mississippi	Harrison	0.064	0.067	-0.003

Mississippi	Hinds	0.055	0.053	0.002

Mississippi	Jackson	0.069	0.070	-0.001

Mississippi	Warren	0.054	0.051	0.003

Missouri	Clay	0.070	0.068	0.002

Missouri	Jefferson	0.076	0.072	0.004

Missouri	Platte	0.069	0.068	0.001

Missouri	St Charles	0.076	0.072	0.004

Missouri	St Louis	0.079	0.075	0.004

Missouri	St Louis City	0.078	0.075	0.003

Missouri	Ste Genevieve	0.068	0.064	0.004

Nevada	Clark	0.072	0.072	0.000

Nevada	Washoe	0.063	0.063	0.000

New Hampshire	Hillsborough	0.063	0.060	0.003

New Hampshire	Rockingham	0.063	0.061	0.002

New Jersey	Atlantic	0.071	0.069	0.002

New Jersey	Bergen	0.077	0.075	0.002

New Jersey	Camden	0.082	0.080	0.002

New Jersey	Cumberland	0.073	0.071	0.002

New Jersey	Essex	0.056	0.055	0.001

New Jersey	Gloucester	0.080	0.078	0.002

New Jersey	Hudson	0.074	0.073	0.001

New Jersey	Hunterdon	0.078	0.077	0.001

New Jersey	Mercer	0.083	0.081	0.002

New Jersey	Middlesex	0.081	0.079	0.002

New Jersey	Monmouth	0.078	0.077	0.001

New Jersey	Morris	0.077	0.075	0.002

New Jersey	Ocean	0.084	0.081	0.003

New Jersey	Passaic	0.071	0.069	0.002

New Mexico	Dona Ana	0.071	0.070	0.001

New Mexico	San Juan	0.071	0.068	0.003

New York	Albany	0.064	0.063	0.001

New York	Bronx	0.069	0.068	0.001

New York	Chautauqua	0.074	0.070	0.004

New York	Dutchess	0.067	0.066	0.001

New York	Erie	0.079	0.075	0.004

New York	Jefferson	0.075	0.072	0.003

New York	Monroe	0.073	0.072	0.001

New York	Niagara	0.076	0.075	0.001

New York	Orange	0.063	0.061	0.002

New York	Putnam	0.070	0.068	0.002

New York	Queens	0.068	0.067	0.001

New York	Richmond	0.074	0.072	0.002

New York	Saratoga	0.066	0.065	0.001

New York	Suffolk	0.086	0.084	0.002

New York	Ulster	0.065	0.063	0.002

New York	Wayne	0.070	0.068	0.002

New York	Westchester	0.075	0.074	0.001

North Carolina	Alexander	0.066	0.064	0.002

North Carolina	Buncombe	0.065	0.065	0.000

North Carolina	Camden	0.063	0.062	0.001

North Carolina	Caswell	0.063	0.059	0.004

North Carolina	Chatham	0.063	0.061	0.002

North Carolina	Cumberland	0.065	0.063	0.002

North Carolina	Davie	0.067	0.065	0.002

North Carolina	Durham	0.063	0.060	0.003

North Carolina	Edgecombe	0.066	0.064	0.002

North Carolina	Forsyth	0.068	0.065	0.003

North Carolina	Franklin	0.063	0.060	0.003

North Carolina	Granville	0.067	0.065	0.002

North Carolina	Guilford	0.064	0.061	0.003

North Carolina	Johnston	0.062	0.059	0.003

North Carolina	Lincoln	0.069	0.067	0.002

North Carolina	Mecklenburg	0.074	0.072	0.002

North Carolina	New Hanover	0.062	0.061	0.001

North Carolina	Northampton	0.067	0.064	0.003

North Carolina	Person	0.071	0.068	0.003

North Carolina	Randolph	0.063	0.060	0.003

North Carolina	Rockingham	0.064	0.061	0.003

North Carolina	Rowan	0.073	0.071	0.002

North Carolina	Union	0.065	0.063	0.002

North Carolina	Wake	0.066	0.064	0.002

Ohio	Allen	0.071	0.067	0.004

Ohio	Ashtabula	0.077	0.073	0.004

Ohio	Butler	0.073	0.070	0.003

Ohio	Clark	0.068	0.063	0.005

Ohio	Clermont	0.071	0.068	0.003

Ohio	Clinton	0.074	0.070	0.004

Ohio	Cuyahoga	0.071	0.068	0.003

Ohio	Delaware	0.071	0.068	0.003

Ohio	Franklin	0.076	0.073	0.003

Ohio	Geauga	0.080	0.076	0.004

Ohio	Greene	0.068	0.062	0.006

Ohio	Hamilton	0.074	0.070	0.004

Ohio	Jefferson	0.067	0.064	0.003

Ohio	Knox	0.069	0.065	0.004

Ohio	Lake	0.076	0.073	0.003

Ohio	Lawrence	0.069	0.065	0.004

Ohio	Licking	0.069	0.066	0.003

Ohio	Lorain	0.071	0.068	0.003

Ohio	Lucas	0.072	0.069	0.003

Ohio	Madison	0.068	0.063	0.005

Ohio	Mahoning	0.071	0.068	0.003

Ohio	Medina	0.069	0.066	0.003

Ohio	Miami	0.065	0.061	0.004

Ohio	Montgomery	0.068	0.062	0.006

Ohio	Portage	0.074	0.070	0.004

Ohio	Preble	0.061	0.058	0.003

Ohio	Stark	0.071	0.068	0.003

Ohio	Summit	0.075	0.071	0.004

Ohio	Trumbull	0.073	0.070	0.003

Ohio	Warren	0.071	0.068	0.003

Ohio	Washington	0.064	0.061	0.003

Ohio	Wood	0.070	0.067	0.003

Oklahoma	Cleveland	0.065	0.064	0.001

Oklahoma	Marshall	0.069	0.067	0.002

Oklahoma	Mc Clain	0.067	0.065	0.002

Oklahoma	Oklahoma	0.067	0.065	0.002

Oklahoma	Tulsa	0.073	0.070	0.003

Pennsylvania	Allegheny	0.079	0.076	0.003

Pennsylvania	Armstrong	0.072	0.069	0.003

Pennsylvania	Beaver	0.076	0.073	0.003

Pennsylvania	Berks	0.071	0.068	0.003

Pennsylvania	Blair	0.065	0.063	0.002

Pennsylvania	Bucks	0.084	0.082	0.002

Pennsylvania	Cambria	0.071	0.068	0.003

Pennsylvania	Centre	0.066	0.064	0.002

Pennsylvania	Chester	0.075	0.073	0.002

Pennsylvania	Clearfield	0.068	0.065	0.003

Pennsylvania	Dauphin	0.070	0.068	0.002

Pennsylvania	Delaware	0.074	0.073	0.001

Pennsylvania	Erie	0.069	0.067	0.002

Pennsylvania	Franklin	0.070	0.068	0.002

Pennsylvania	Greene	0.069	0.066	0.003

Pennsylvania	Lackawanna	0.064	0.062	0.002

Pennsylvania	Lancaster	0.071	0.068	0.003

Pennsylvania	Lawrence	0.063	0.059	0.004

Pennsylvania	Lehigh	0.071	0.069	0.002

Pennsylvania	Luzerne	0.064	0.063	0.001

Pennsylvania	Lycoming	0.059	0.057	0.002

Pennsylvania	Mercer	0.073	0.069	0.004

Pennsylvania	Montgomery	0.078	0.076	0.002

Pennsylvania	Northampton	0.072	0.070	0.002

Pennsylvania	Perry	0.063	0.061	0.002

Pennsylvania	Philadelphia	0.080	0.078	0.002

Pennsylvania	Washington	0.070	0.067	0.003

Pennsylvania	Westmoreland	0.070	0.067	0.003

Pennsylvania	York	0.071	0.067	0.004

Rhode Island	Kent	0.074	0.072	0.002

Rhode Island	Providence	0.071	0.068	0.003

Rhode Island	Washington	0.075	0.072	0.003

South Carolina	Anderson	0.067	0.065	0.002

South Carolina	Berkeley	0.058	0.057	0.001

South Carolina	Charleston	0.057	0.055	0.002

South Carolina	Cherokee	0.063	0.061	0.002

South Carolina	Chester	0.064	0.061	0.003

South Carolina	Edgefield	0.063	0.058	0.005

South Carolina	Pickens	0.065	0.063	0.002

South Carolina	Richland	0.069	0.066	0.003

South Carolina	Spartanburg	0.066	0.063	0.003

South Carolina	Union	0.062	0.059	0.003

South Carolina	York	0.063	0.061	0.002

Tennessee	Anderson	0.064	0.061	0.003

Tennessee	Blount	0.071	0.067	0.004

Tennessee	Davidson	0.064	0.063	0.001

Tennessee	Hamilton	0.066	0.063	0.003

Tennessee	Haywood	0.067	0.063	0.004

Tennessee	Jefferson	0.068	0.065	0.003

Tennessee	Knox	0.071	0.066	0.005

Tennessee	Meigs	0.066	0.063	0.003

Tennessee	Rutherford	0.065	0.063	0.002

Tennessee	Shelby	0.072	0.069	0.003

Tennessee	Sullivan	0.072	0.062	0.010

Tennessee	Sumner	0.068	0.067	0.001

Tennessee	Williamson	0.068	0.066	0.002

Tennessee	Wilson	0.066	0.065	0.001

Texas	Brazoria	0.078	0.076	0.002

Texas	Collin	0.075	0.072	0.003

Texas	Dallas	0.079	0.077	0.002

Texas	Denton	0.078	0.075	0.003

Texas	El Paso	0.070	0.069	0.001

Texas	Ellis	0.074	0.069	0.005

Texas	Galveston	0.078	0.075	0.003

Texas	Gregg	0.079	0.073	0.006

Texas	Harris	0.092	0.090	0.002

Texas	Harrison	0.065	0.062	0.003

Texas	Hood	0.068	0.066	0.002

Texas	Jefferson	0.079	0.072	0.007

Texas	Johnson	0.073	0.069	0.004

Texas	Marion	0.069	0.065	0.004

Texas	Montgomery	0.072	0.070	0.002

Texas	Orange	0.068	0.064	0.004

Texas	Parker	0.068	0.066	0.002

Texas	Rockwall	0.067	0.063	0.004

Texas	Smith	0.071	0.068	0.003

Texas	Tarrant	0.079	0.076	0.003

Utah	Box Elder	0.066	0.065	0.001

Utah	Cache	0.055	0.054	0.001

Utah	Davis	0.071	0.070	0.001

Utah	Salt Lake	0.073	0.072	0.001

Utah	Utah	0.070	0.069	0.001

Utah	Weber	0.067	0.066	0.001

Vermont	Bennington	0.060	0.059	0.001

Virginia	Alexandria City	0.072	0.069	0.003

Virginia	Arlington	0.078	0.075	0.003

Virginia	Caroline	0.063	0.062	0.001

Virginia	Charles City	0.074	0.073	0.001

Virginia	Chesterfield	0.071	0.070	0.001

Virginia	Fairfax	0.077	0.074	0.003

Virginia	Fauquier	0.062	0.061	0.001

Virginia	Frederick	0.067	0.064	0.003

Virginia	Hampton City	0.077	0.076	0.001

Virginia	Hanover	0.074	0.072	0.002

Virginia	Henrico	0.074	0.073	0.001

Virginia	Loudoun	0.070	0.068	0.002

Virginia	Madison	0.067	0.065	0.002

Virginia	Prince William	0.066	0.064	0.002

Virginia	Roanoke	0.069	0.067	0.002

Virginia	Stafford	0.064	0.062	0.002

Virginia	Suffolk City	0.080	0.080	0.000

West Virginia	Berkeley	0.068	0.063	0.005

West Virginia	Cabell	0.073	0.069	0.004

West Virginia	Hancock	0.068	0.065	0.003

West Virginia	Kanawha	0.069	0.064	0.005

West Virginia	Monongalia	0.064	0.063	0.001

West Virginia	Ohio	0.067	0.064	0.003

West Virginia	Wood	0.065	0.062	0.003

Wisconsin	Brown	0.065	0.063	0.002

Wisconsin	Columbia	0.062	0.061	0.001

Wisconsin	Dane	0.062	0.060	0.002

Wisconsin	Dodge	0.063	0.062	0.001

Wisconsin	Door	0.074	0.072	0.002

Wisconsin	Fond Du Lac	0.061	0.060	0.001

Wisconsin	Jefferson	0.066	0.065	0.001

Wisconsin	Kenosha	0.086	0.085	0.001

Wisconsin	Kewaunee	0.074	0.072	0.002

Wisconsin	Manitowoc	0.074	0.072	0.002

Wisconsin	Milwaukee	0.075	0.073	0.002

Wisconsin	Outagamie	0.059	0.057	0.002

Wisconsin	Ozaukee	0.079	0.077	0.002

Wisconsin	Racine	0.079	0.077	0.002

Wisconsin	Rock	0.069	0.068	0.001

Wisconsin	Sheboygan	0.082	0.080	0.002

Wisconsin	Walworth	0.066	0.065	0.001

Wisconsin	Washington	0.065	0.063	0.002

Wisconsin	Waukesha	0.067	0.065	0.002

Wisconsin	Winnebago	0.063	0.062	0.001



 “Stationary Reciprocating Internal Combustion Engines Technical
Support Document for NOx SIP Call Proposal,” U.S. Environmental
Protection Agency.  September 5, 2000.  Available on the Internet at  
HYPERLINK "http://www.epa.gov/ttn/naaqs/ozone/rto/sip/data/tsd9-00.pdf" 
http://www.epa.gov/ttn/naaqs/ozone/rto/sip/data/tsd9-00.pdf .  

“Stationary Internal Combustion Engines:  Updated Information on NOx
Emissions and Control Techniques,” Ec/R Incorporated, Chapel Hill, NC.
 September 1, 2000.  Available on the Internet at   HYPERLINK
"http://www.epa.gov/ttn/naaqs/ozone/ozonetech/ic_engine_nox_update_09012
000.pdf" 
http://www.epa.gov/ttn/naaqs/ozone/ozonetech/ic_engine_nox_update_090120
00.pdf .

 VOC Fugitive Losses:  New Monitors, Emissions Losses, and Potential
Policy Gaps.  2006 International Workshop.  U.S. Environmental
Protection Agency, Office of Air Quality Planning and Standards and
Office of Solid Waste and Emergency Response.  October 25-27, 2006.    

 VOC Fugitive Losses:  New Monitors, Emissions Losses, and Potential
Policy Gaps.  2006 International Workshop.  U.S. Environmental
Protection Agency, Office of Air Quality Planning and Standards and
Office of Solid Waste and Emergency Response.  October 25-27, 2006.    

 Bay Area Air Quality Management District (BAAQMD).  Proposed Revision
of Regulation 8, Rule 8: Wastewater Collection Systems.  Staff Report,
March 17, 2004. 

 Bay Area Air Quality Management District (BAAQMD).  Proposed Revision
of Regulation 8, Rule 8: Wastewater Collection Systems.  Staff Report,
March 17, 2004.

 Herzog, E., Bricka, S., Audette, L., and Rockwell, J., 2005. Do
Employee Commuter Benefits Reduce Vehicle Emissions and Fuel
Consumption?  Results of the Fall 2004 Best Workplaces for Commuters
Survey, Transportation Research Record, Journal of the Transportation
Research Board: Forthcoming.

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