## APPENDIX A

Air Quality System (AQS) Data

State and Local Air Monitoring Stations (SLAMS)UNITED STATES ENVIRONMENTAL PROTECTION AGENCY

DESIGN VALUE REPORT

Mar. 3, 2011 Report Request ID: 843140 Report Code: AMP480

Selection Criteria Page 1 User ID: GYE

State County City

Site Parameter POC AQCR UAR CBSA CSA EPA Region Method Duration Begin Date End Date
21
54
39
39 019

011
087
145 0017

0006 GEOGRAPHIC SELECTIONS

PROTOCOL SELECTIONS

Parameter Classification Parameter Method Duration

DESIGN VALUE 88101

SELECTED OPTIONS

USER SITE METADATA MERGE PDF FILES QUARTERLY DATA IN WORKFILE WORKFILE DELIMITER SINGLE EVENT PROCESSING Option Type Option Value

COUNTY NAME YES NO

, EXCLUDE REGIONALLY CONCURRED EVENTS

GLOBAL DATES

2010 Start Date End Date
2010 Tribal

APPLICABLE STANDARDS
Standard Description PM25 24-hour 2006 PM25 Annual 2006UNITED STATES ENVIRONMENTAL PROTECTION AGENCY AIR QUALITY SYSTEM PRELIMINARY DESIGN VALUE REPORT Report Date: Mar. 3, 2011

Notes: 1. Warning: Computed design values are a snapshot of the data at the time the report was run (may not be all data for year). 2. Annual Values not meeting completeness criteria are marked with an asterisk ('*'). Page 1 of 4UNITED STATES ENVIRONMENTAL PROTECTION AGENCY AIR QUALITY SYSTEM PRELIMINARY DESIGN VALUE REPORT Report Date: Mar. 3, 2011

Notes: 1. Warning: Computed design values are a snapshot of the data at the time the report was run (may not be all data for year). 2. Annual Values not meeting completeness criteria are marked with an asterisk ('*'). Page 2 of 4 

### Pollutant: Standard Units: NAAQS Standard: Statistic: Statistic: Site-LevelPM2.5 - Local Conditions(88101) Micrograms/cubic meter (LC)(105) PM25 24-hour 2006 / PM25 Annual 2006 Annual Weighted Mean Annual 98th Percentile Level: Level: Design Value Year: 2010

REPORT EXCLUDES MEASUREMENTS WITH REGIONALLY CONCURRED EVENT FLAGS.

15 35 State Name: Kentucky

Site_ID / COUNTY NAME | | | Cred. Days Comp. Qrtrs Wtd.

Mean 98th Perctil Cert. | | | Cred. Days Comp. Qrtrs 98th Perctil Wtd.

Mean Cert. |

| | Cred. Days Comp. Qrtrs 98th Perctil Wtd.

Mean Cert. |

| | Design Value Valid

Ind. | | | Design Value Valid

Ind. 24-Hour Annual 2010 2009 2008

21-019-0017 Boyd 119 4 26.2 11.2 N 116 4 23.5 10.9 N 120 4 24.3 12.1 Y 25 Y 11.4 YUNITED STATES ENVIRONMENTAL PROTECTION AGENCY AIR QUALITY SYSTEM PRELIMINARY DESIGN VALUE REPORT Report Date: Mar. 3, 2011

Notes: 1. Warning: Computed design values are a snapshot of the data at the time the report was run (may not be all data for year). 2. Annual Values not meeting completeness criteria are marked with an asterisk ('*'). Page 3 of 4 

### Pollutant: Standard Units: NAAQS Standard: Statistic: Statistic: Site-LevelPM2.5 - Local Conditions(88101) Micrograms/cubic meter (LC)(105) PM25 24-hour 2006 / PM25 Annual 2006 Annual Weighted Mean Annual 98th Percentile Level: Level: Design Value Year: 2010

REPORT EXCLUDES MEASUREMENTS WITH REGIONALLY CONCURRED EVENT FLAGS.

15 35 State Name: Ohio

Site_ID / COUNTY NAME | | | Cred. Days Comp. Qrtrs Wtd.

Mean 98th Perctil Cert. | | | Cred. Days Comp. Qrtrs 98th Perctil Wtd.

Mean Cert. |

| | Cred. Days Comp. Qrtrs 98th Perctil Wtd.

Mean Cert. |

| | Design Value Valid

Ind. | | | Design Value Valid

Ind. 24-Hour Annual 2010 2009 2008

39-087-0012

39-145-0013 Lawrence

Scioto 117

116 4

4 25.1

24.4 12.1

11.8 N

N 116

117 4

4 21.4

21.8 11.3

10.9 N

N 98

348 4

4 27.6

24.4 13.1

12.1 Y

N 25

24 Y

Y 12.2

11.6 Y

YUNITED STATES ENVIRONMENTAL PROTECTION AGENCY AIR QUALITY SYSTEM PRELIMINARY DESIGN VALUE REPORT Report Date: Mar. 3, 2011

Notes: 1. Warning: Computed design values are a snapshot of the data at the time the report was run (may not be all data for year). 2. Annual Values not meeting completeness criteria are marked with an asterisk ('*'). Page 4 of 4 

### Pollutant: Standard Units: NAAQS Standard: Statistic: Statistic: Site-LevelPM2.5 - Local Conditions(88101) Micrograms/cubic meter (LC)(105) PM25 24-hour 2006 / PM25 Annual 2006 Annual Weighted Mean Annual 98th Percentile Level: Level: Design Value Year: 2010

REPORT EXCLUDES MEASUREMENTS WITH REGIONALLY CONCURRED EVENT FLAGS.

15 35 State Name: West Virginia

Site_ID / COUNTY NAME | | | Cred. Days Comp. Qrtrs Wtd.

Mean 98th Perctil Cert. | | | Cred. Days Comp. Qrtrs 98th Perctil Wtd.

Mean Cert. |

| | Cred. Days Comp. Qrtrs 98th Perctil Wtd.

Mean Cert. |

| | Design Value Valid

Ind. | | | Design Value Valid

Ind. 24-Hour Annual 2010 2009 2008

54-011-0006 Cabell 116 4 28.0 13.2 N 111 4 22.5 12.0 N 114 4 27.4 14.1 Y 26 Y 13.1 YEnvironmental protection Agency John R. Kasich, Governor Mary Taylor, Lt. Governor Scott J. Nally, Director



### CERTIFIED MAIL

March 10, 2011
Cheryl L. Newton, Director Air and Radiation Division U.S.EPA, Region V 77 West Jackson Boulevard Chicago, Illinois 60604

RE: 2010 SLAMS PM,.5 and Ozone Data Certification

Dear Ms. Newton:

Please find enclosed our SLAMS Report (AMP-450, AMP-450NC and AMP255) for calendar year 2010 as required in 40 CFR, Part 58, Section 58.15. The ambient concentration and the quality assurance data have been completely submitted to the AQS database.

The remaining criteria pollutant data will be certified within the month of April.

I certify that the Ozone and PM,., data in the report are accurate to the best of our knowledge taking into consideration the quality

assurance findings and only to the extent of the activities performed by Ohio EPA.

There were no incidents of air pollution that reached or exceeded levels as specified by Section 51.151 which could cause significant harm to the health of persons.
Sincerely,

Robert Hodanbosi Chief, Division of Air Pollution Control

Enclosure

50 West Town Street,**Su~e** 700 PO. Box 1049 Columbus,OH 43216-1049 61416443020 61416443184 (fax) www.epa.ohio.gov

## APPENDIX B

Ohio 2005 

## SIP Base Year Inventory Discussion

### 1 

## OHIO 2005 Base Year PM2.5 SIP Inventory

Ohio Environmental Protection Agency Lazarus Government Center 50 West Town Street, Suite 700 Columbus Ohio 43215

Prepared by Ohio EPA

Division of Air Pollution Control Emissions Inventory Unit February 2008

### 2 

## Table of Contents

Section Page

Introduction .................................................................................................3

1.0 Point Sources .............................................................................................4

2.0 Area S ources ..............................................................................................8

3.0 Non Road Sources........................................................................15

4.0 On Road Sources.......

.................. .................. ................ ................ .............17

5.0 MAR Sources..............................................................................43

Table 2-1 Categories included in the 2005 area source Inventory.............................8 2-2 Emission Factors used for Wood Bu rners included in area sources............11 3-1 NMIM NCD Tables for Specific Years and States ........................................... 

### 16 4-1 Federal Functional Class Categories............................................................ 

### 23 4-2 DVMT Summary by County



### .................................................................. . 24 4-3 Speed by Federal Functional Class ............................................................. 

### 28 4-4 Link Group Codes & Associated BPR Curves

.......................................... 

### 29 4-5 Mobile6 Inputs.................................................................................31 4-6 LADCO Data Output............................................. .............39 4-7 County Summary Table of MPOs by County......................................... .40 5-1 Number of operations and LTOs for 2005.............................................. 45 5-2 EDMS Aircraft Emissions ..................................................................50 5-3 Fleet Emission Fa ctor Categories ........................................................51 5-4 Pollutant by County (Sample) ............................................................. 54

. Figure

1............................... ......... Speed Comparison Graphs.....................................27

### 3 

## 2005 Base Year PM2.5 SIP Inventory for Ohio

Introduction

The State of Ohio has a nu mber of counties with air quality data showing nonattainment for the following PM 2 

### . 5 

### standard:

• 

### Annual Standard = 15.0 ug/m3 The Clean Air Act Amendments (CAAA) requires all states to revise and submit State Implementation Plans (SIP) for areas which are classified as non-atta inment of the 1997 Fine Particle (PM 2 

### . 5 

### ) National Ambient Air Quality St andards (NAAQS). The Federal Register ( Vol. 72, No. 79/ Wednesday, April 25, 2007) provides the emissions inventory rules and regulations for the PM 2 

### . 5

### Clean Air Fine Particle implementation rule. An electronic version of the document can be found at http://www.epa.gov/fedrgstr/EPAAIR/2007/April/Day-25/a6347.pdf. 

### As part of the designation ofnon-attainment areas for PM 2 

### . 5

### standards, a new attainment demonstration SIP will be necessary. A key el ement in the overall SIP planning process is the need for an updated emissions inventory. This document presents the 2005 Base Year Pa rticulate SIP Emissions Inv entory for Ohio as required by the CAAA. It includes emissions for poi nt, area, on-road mobi le and non-road mobile for the State of Ohio. This technical report document s the procedures and the me thodologies that were used in the development of daily emissions for all counties in Ohio. This report describes the following:

1. Identification of st ationary and mobile sources included in the inventory; 2. Sources of data, and data collecti on methods used in the development of the inventory; 3. Methods and procedures used to estimate emissions; and 4. Assumptions considered in t he development of the emissions inventories. The intent of this report is to descri be how the inventory was prepared, and what information was considered in the inventory development. This document is comprised of 5 sections , one section for each inventory type. The biogenic inventory is not being discussed in this document because Ohio EPA did not participate in the generation of this inventory. Lake Michigan Air Directors Consortium (LADCO) ran EPA’s BEIS model in the Em ission Modeling System (EMS) to generate Summer Weekday emissions for VOC and NOx.

### 4 

### SECTION 1

POINT SOURCES Emissions and source specificdata for point sources are collected for the 2005 baseyear SIP inventory by the Ohio Envir onmental Protection Agency (Ohio EPA.) The primary source of data for pointsources is facility reported STARShip files. STARShip is a software package developed byOhio EPA, Division of Ai r Pollution Control (DAPC), to assist the regulated community in prepar ing and submitting a variety of electronic permit applications and reports to the DAPC . These data are reported by the Title V facilities annually as part of the emission s fee/inventory process conducted by Ohio EPA and include emissions, process rates, oper ating schedules, emissions control data and other relevant information. The STARShip files are electr onically transferred to the DAPC and stored into the Division’s Oracle database, STARS. The f iles are reviewed by the local air agencies and Ohio EPA district and central office staff. After review, the data are imported into Excel and linked with an Access® database to further process the information into the federally approved National Em ission Inventory (NEI) database format in version 3.0. The files are quality assured ag ain using the United States Environmental Protection Agency’s (U.S.EPA) QA/QC so ftware for format and content. The data is finally submitted to LADCO for emissions processi ng through the Emissions Modeling System. The State provided inv entory for Electric Generating Un its (EGU) is replaced with the Federal EGU inventory. T he EGU inventory is compiled by U.S. EPA’s Acid Rain Program. It is based on facility report ed emissions as meas ured by continuous emissions monitors. In conclusion, the final point source inventory is a hybrid of the federal EGU inventory and the state provided non-EGU units. A major distinction typically made in emissi ons inventories is t hat between point and area sources. In this invent ory, point sources are sources for which individual records are maintained for that source. Such records are maintained for all Ohio Title V facilities (706 facilities statewide). The area source inventory accounts for facilities from nonTitle V facilities and calculates emissions information using surrogate emissions factors based on energy usage, population, employment records, orother reliable data. A more detailed discussion of t he area source inventory is pr ovided in Section 2. The point source inventory descr ibed herein is considered to be the most current and accurate source of emissions data available for 2005.

1.1 Point Source Process Emissions Ohio EPA defines point source process emissions as those which occur at an identifiable Title V stationary stack or vent. Point source emissions not emitted from discrete stacks or vents are termed fugitive emissions and are discussed in Section 1.2.

### 5 1.1.1 Source Identificati on and Data Collection The sources to be included in the 2005 base year inventory are identified using the Title V STARS database. Facility production and emissions data are included in this database. This information is fac ility-reported actual 2005 emissions.

1.1.2 Non-reactive VOC Emissions Adjustments This section is primarily appl icable for VOC pollutants. S ources are required to identify emissions of photochemically non-reactive Volatile Organic Compounds (VOC.) Based upon this information, those emissions have been specifically excl uded from the 2005 base line inventory in accordance with U.S. EPA’s “Recommended Policy on the Control of Volatile Organic Co mpounds.” A complete list ofthe compounds that U.S. EPA has identified as being photochemically non -reactive, and therefore not included in the inventory, are listed below:

• Methane

• Ethane

• Methylene chloride

• Methyl chloroform

• Trichlorofluoromethane (CFC-11)

• Dichlorodifluoromethane (CFC-12)

• Chlorodifluoromethane (CFC-22)

• Trifluoromethane (HFC-23)

• Chlorofluoromethance (HCFC-31)

• Difluoromethane (HFC-32)

• Decafluoropentane (HFC-43-10mee)

• Ethylfluoride (HFC-161)

• Trichlorotrifluoroethane (CFC-113)

• Dichlorotetrafluoroethane (CFC-114)

• Chloropentafluoroethane (CFC-115)

• 2,2-Dichloro-1,1,1-trifluoroethane (HCFC-123)

• 1,1,2-Trifluoroethane (HCFC-123a)

• 2-Chloro-1,1,1,2-tetrafluoroethane (HCFC-124)

• Pentafluoroethane (HFC-125)

• 1,1,2,2,-Tetrafluoroethane (HFC-134)

• 1,1,1,2-Tetrafluoroethane (HFC-134a)

• 1,1-Dichloro-1-fluoroethane (HCFC-141b)

• 1-Chloro-1,1,-difluoroethane (HCFC-142b)

• 1,1,1-Trifluoroethane (HFC-143a)

• Fluoroethane (HCFC-151a)

• 1,1-Difluoroethane (HFC-152a)

• Pentafluoropropane (HFC-225ca)

• Pentafluoropropane (HFC-225cb)

• Hexafluoropropane (HFC-236ea)

• Hexafluoropropane (HFC-236fa)

• Pentafluoropropane (HFC-245ca)

• Pentafluoropropane (HFC-245ea)

• Pentafluoropropane (HFC-245eb)

### 6 • Pentafluoropropane (HFC-245fa)

• Pentafluorobutane (HFC-365mfc)

• Parachlorobenzotrifluoride (PCBTF)

• Methoxybutane

• Nonaflourobutane

• Heptafluoropropane ((CF 3 ) 2 CFCF 2 OCH 3 )

• Heptafluoropropane ((CF 3 )CFCF 2 OC 2 H 5 )

• Perchloroethylene

• Cyclic, branched or linear completely methylated siloxanes

• Methyl acetate

• Volatile methyl siloxanes

• Acetone



### 1.1.3 Emissions Esti mation Methodologies Since source reported actual annual emi ssions are used in the 2005 base year inventory, no estimation methods are necessary . The reports are provided to LADCO in National Emissions Inventory Input Format (NIF) 3.0 format. LADCO imported and processed the NIF files in EMS and applied temporal and spat ial profiles to the annual emissions to calculate weekday emissions rate s. The final point source inventory is split into two separate reports, the ElectricGenerating Units (EGU) which is the U.S. EPA inventory for electric generating units a nd the non-EGU which is the state inventory minus the EGU units.

1.2 Point Source Fugitive Emissions Another type of emissions data which is r equired to be filed from point sources is fugitive emissions. Before 1990, fugitive emissions were categorized as area sources due to the lack of detailed information availa ble for fugitive sources. However, since these emissions are now el ectronically reported in t he State’s ORACLE database, STARS, these emissions can be classified as point sources.

1.3 References Getting Started: Emissions In ventory Methods for PM2.5 U.S. Environmental Protection Agency, Research Triangle Park, NC, September, 1999. Emissions Inventory Guidance for Implem entation of Ozone and Particulate Matter National Ambient Air Qaulity Standards (N AAQS) and Regional Haze Regulations , Office of Air Quality Planning & Standards Research, Triangle Park, NC. November 2005. Compilation of Air Pollution Emission Factors, Fourth Ed ition and Supplements, AP-42

. U.S. Environmental Protecti on Agency, Research Triangle Park, NC, September 1985.

### 7 Preparing 2002 Regional PM2.5 Emissions QAQPS PM Inventory Conference Inventory Conference San Diego, 2003.

Documentation for the 2002 El ectric Generating Unit Nati onal Emissions Inventory (NEI) . Eastern research group, Inc., 1600 Peri meter Park Drive, Morrisville, NC 27560 and E.H. Pechan and Associates, Inc., 5528–B Hempstead Way

### 8 

### SECTION 2

AREA SOURCES

Area sources are sources which are typically small, indivi dual, numerous, and have not been inventoried as specific point, mobile, orbiogenic sources. For inventory purposes, they are grouped with other like sources into categories that allow emissions to be calculated collectively usi ng one methodology. Since area sources are traditionally defined at the county level, most methods are designed to estimate area source emissions at the county level.

Ohio EPA has either used published Emission Inventory Improvement Program (EIIP) 6 

### methodologies or selected other methodologies which are shared by other states. The decision of which methodology to use was lar gely based on Ohio’s data availability. Data which was not available on a county-lev el is estimated by assigning a percentage of the state’s total activity to each county based on the state’s popul ation or employment information. If Ohio county specific activity data is available throu gh Ohio EPA or other State Agencies, that data is us ed rather than allocating acti vity by percentage. Table 2-1 lists the sources which emit PM 2.5 

### , NO x 

### and SO 2 

### along with the respective EFs used to calculate each pollutant.

Table 2-1 Categories in the 2005 PM 2 

### . 5

### SIP Area Source inventory

Area Source NO x

### PM 2.5 

### SO 2 

### Section Commercial Natural Gas Combustion 94 lb/MMSCF 7.6 lb/MMSCF 0.6 lb/MMSCF 2.1 Industrial Distillate Oil Combustion 20 lb/E3gal fuel 0.25 lb/E3gal fuel 42.6 lb/E3gal fuel 2.2 Industrial Residual Oil Combustion 55 lb/E3gal fuel 4.67 lb/E3gal fuel 157 lb/E3gal fuel 2.2 Industrial Natural Gas Combustion 94 lb/MMSCF 7.6 lb/MMSCF 0.6 lb/MMSCF 2.2 Residential Coal Combustion 9.1 Lb/Ton Coal 3.8 Lb/Ton Coal 31 Lb/Ton Coal 2.3 Residential Distillate Oil Combustion 18 lb/E3gal fuel 0.83 lb/E3gal fuel 42.6 lb/E3gal fuel 2.3 Residential Natural Gas Combustion 94 lb/MMSCF 7.6 lb/MMSCF 0.6 lb/MMSCF 2.3 Residential LPG Combustion 13 lb/E3gal fuel 0.17 lb/E3gal fuel 0.1 lb/E3gal fuel 2.3

Human Cremation 1.01E+01 lb/Ton cremated 0.0637 lb/Ton cremated NA 2.4

Structure Fires 1.4 Lb/Ton burned 10.8 Lb/Ton burned NA 2.5 Outdoor Wood Boilers 2.8 Lb/Ton 2.76E+1 Lb/Ton 4 E-1 Lb/Ton 2.6

### 9 Residential Wood Combustion

Non-Certified Non-Catalytic Catalytic 2.80E+00 lb/Ton

2.80E+00 lb/Ton

2.00E+00 lb/Ton 3.06E+01 lb/Ton

1.96E+01 lb/Ton

2.04E+01 lb/Ton 4.00E-01 lb/Ton

4.00E-01 lb/Ton

4.00E-01 lb/Ton 2.3

2.1 

### Commercial Natural Gas Combustion (SCC 2103006000)

The 2005 total state-level commercial sectorenergy consumption is obtained from the Energy Information Administration (EIA)’s State Energy Data System (SEDS), and apportioned per county based on population 4 

### . Emissions factors are given in table 2-1. The area source emissions are calculated ba sed on an adjusted value by subtracting the emissions due to point sources.

2.2 Industrial Fuel Combustion

Industrial Distillate Oil Combustion (SCC 2102004000) Ohio’s fuel consumption is apportioned per county based on the county’s population 4



### . The area source NO X

### emissions are calculated and adjusted by subtracting the emissions due to point source s. A heating value of 140 MMBTU/1000 Gal is used and 84,408 thousand gallons are consumed in 2005. [MMBTU stand for Million British Thermal Units]. Emissions fact ors are given in table 2-1.

SO 2 

### emissions were calculated us ing EF 42.6 Lb/1000 Gal. PM 10 

### and PM 2.5 

### emissions are calculated using 1Lb/1000 Ga l and 0.25 Lb/1000 Gal respecti vely. All Factors are obtained from AP-42 19


### Industrial Residual Oil Combustion (SCC 2102005000) Ohio’s fuel consumption is apportioned per county based on the county’s population 4



### . The area source NO X

### emissions are calculated and adjusted by subtracting the emissions due to point sour ces. 54,652 thousand gallons 14

### are consumed in 2005 and a heating value of 140 MMBTU/1000 Gal is used. The SO 2 

### emissions are calculated using EF 157 Lb/1000 Gal. PM 10 

### and PM 2.5 

### emissions are calculated using 7.17 Lb/1000 Gal and 4.67 Lb/1000 Gal respectively. All factors are obtained from AP-42 19



### Industrial Natural Gas Combustion (S CC 2102006000) Ohio’s fuel consumption is apportioned per county based on the county’s population 4



### . The area source NO X

### emissions are calculated and adjusted by subtracting the emissions due to point sources. 293,857 MMCF 14

### are consumed in 2005. The SO 2

### 10 emissions are calculated usi ng EF 0.6 Lb/MMBTU. The PM 10 

### and PM 2.5 

### emissions are calculated using 7.6 Lb/MMBTU. All factors were obtained from AP-42 19



### 2.3 Residential Fuel Combustion Residential Coal Combustion (SCC 2104001000) Ohio’s household consumption of coal is apportioned per county based on county population 4 

### . NO X

### emissions are calculated using EF of 9.1 of coal. The SO 2 

### emissions are calculated using EF 31Lb/1000 Gal. The PM 10 

### and PM 2.5 

### emissions are calculated using 6.2Lb/Ton and 3.8 Lb/Ton respectively . All factors were obtained from AP-42 19



### Residential Distillate Oil Combustion (SCC 2104004000) Ohio’s household consumption of distillate oil is apportioned per county based on county population 4 

### . NO X

### emissions are calculated us ing EF of 18 lb/1000 gallons distillate fuel respectively. A heating value of 140 MMBTU/1000 Gal is used. The SO 2 

### emissions are calculated using EF 42.6 Lb/1000 Gal. The PM 10 

### and PM 2.5 

### emissions are calculated using 1.08Lb/1000 Gal and 0.83 Lb/1000 Gal respectively. All factors are obtained from AP-42 19


### Residential Liquid Petroleu m Gas Combustion (LPG) (SCC 2104007000) Ohio’s household consumption of LPG is apportioned per county based on county population 4 

### . NO X

### emissions are calculated using EFof 13 lb/1000 gallons LPG. The SO 2 

### emissions are calculated usi ng EF 0.1 Lb/1000 Gal. The PM 10 

### and PM 2.5 

### emissions are calculated using 0.17Lb/1000 Gal. All factors are obtained from AP-42 19


### Residential Natural Gas Combustion (SCC 2104006010) Ohio’s household consumption of LPG is apportioned per county based on county population 4 

### . NO X

### emissions are calculated using EF of 94 lb/MMSCF. MMSCF stands for Million Standard Cubic Feet. This source also emits SO 2 

### emissions which are calculated using EF 0.6 Lb/MMBTU. The PM 10 

### and PM 2.5 

### emissions are calculated using 7.6Lb/MMBTU. All fact ors are obtained from AP-42 19



### Residential Wood Combustion NO X

### emissions from this area source are ca lculated for seven types of residential heating units that utilize wood for fuel. Theyare listed below with the appropriate SCC: Fireplaces without inserts 2104008001 Fireplaces with inserts catalytic (non-U.S. EPA cert) 2104008002 Fireplaces with inserts non -catalytic 2104008003 Fireplaces with inserts catalytic (U.S. EPA cert) 2104008004 Wood stoves – Conventional 2104008010 Woodstoves – Catalytic 2104008030 Wood stoves – Non catalytic 2104008050

### 11 The number of Ohio homes with fireplaces ar e adjusted for those t hat burn wood. The following assumptions are applie d to those adjusted homes: 92 percent of wood combust ed in non-certified units 5.7 percent of wood combusted in non-catalytic units 2.3 percent of wood combusted in catalytic units A state consumption value is applied which is apportioned to each county based on its population 4 

### . Table 2-2 shows the EF used for each of the seven types of indoor wood burners which make-up this category:

Table 2-2 Emission Factors Used for Wood Burners

SCC 2104008002 210400 8003 2104008004 SCC 2104008010 210400 8050 2104008030 SCC 2104008001 RAPIDS Code Non-Certified N on-Catalytic Catalytic Units SO 2 

### 4.00E-01 4.00E-01 4.00E-01 Lb/ton NO X 

### 2.80E+00 2.80E+00 2.00E+00 Lb/ton PM 2.5 

### 3.06E+01 1.96E+01 2.04E+01 Lb/ton To avoid double counting of wood consumption for fuel, this category is adjusted by subtracting the wood consumption from OWB to allow this category to account only for indoor wood burning emissions.

Residential Wood combustion also emits SO 2 

### which is calculated using EF 0.4 Lb/Ton EF. The PM 2.5 

### emissions are calculated using EF as shown in table 2-2. All factors are obtained from AP-42 19



### 2.4 Human Cremation (SCC 2810060200)

Not all Ohio counties possess a crematory soonly those counties with crematories are used to calculate the number of cremations and their resulting NOx emissions. The 2005 cremation data is obtained fr om the Ohio Department ofHealth, Vital Statistics 17



### . It is estimated that 3% of deaths occur outsi de the State of Ohio with no available data to account for their disposition at the time this area source is being calculated. Therefore, those deaths are not accounted for in this category. The methodology does not offer an EF for NOx for this category nor is NOx required to be calculated for this area source. Ohio f eels that it is a combustion source and NOx needs to be included in the inventory al ong with the other com bustion sources. Through its Permits-to-Install for human crem ation, Ohio has se lected a NOx EF of 10.13lb/ton cremated to calculate emi ssions from this area source.

### 12 This source also emits PM, PM 10 

### , and PM 2.5

### emissions which are calculated using EF 0.1 Lb/Ton, 0.071Lb/Ton and, 0.0637 Lb/Ton respectively. All factors are obtained from AP-42 19



### 2.5 Structur e Fires (SCC 2810030000) The Structure Fires category includes resid ential and commercial fires resulting from unintentional actions. Intentional fires, fo rest and wildfires, agricultural, and vehicle burning are not included in this area source

. The State Fire Marshall Office, Fire Prevention Bureau 15

### provided data on the number of st ructure fires per county in 2005.
This area source is consider ed a combustion source for NO X

### emissions which are calculated using EF 1.4 lb/ton burned. The residential and commercial structures fires for each county are tabul ated and a fuel load ing of 1.15 Ton/fire is applied. This source also emits PM, PM 10 

### , and PM 2.5

### emissions which are calculat ed using EF 10.8 Lb/Ton. This factor was obtained from AP-42 19



### 2.6 Outdoor W ood Boilers (SCC 2104008070) Outdoor Wood Boilers (OWB), are also known as outdoor water stoves and outdoor wood furnaces, are used as outdoor residenti al heaters. These boilers have wood burning fireboxes surrounded by a water reserv oir vented by a chimney stack. The combustion of the wood in t he firebox heats the water in the surrounding reservoir and the heated water is pumped to the residence. OWB units can also supply residential hot water. The water capacit y ranges from 60 gallons to 764 gallons. The operational design creates long periods where the fire smolders and creosote is formed 13



### . When the water circulating through the furn ace reaches an upper set point, the air supply to the fire is cut-off, cooling the fire so the water will not overheat. The furnace operates in this "idle" mode until the water te mperature hits a lower set point and the air supply is re-established. The OWB may be in idle mode far longer than in operating mode. This type of operating causes very poor combustion and heavy foul smoke. Most of the smoke emitted is fi ne condensed organic material t hat does not burn under cool, oxygen starved conditions. In addition, manyowners burn green wood full of moisture which also causes poor combustion 12



### . The smoke created from these outdoor wood burning units can contain severa l pollutants that are harmful to breathe, including fine particle pollution such as PM 2.5 11 

### in addition to NOx (research assisted by Deborah Lucas, DAPC intern, 2007) This new area source category has many unknowns and variables associated with it and Ohio does not possess accurate OWB uni t sales data available to calculate emissions on the county level. Therefore, several assu mptions are made in agreement with the Great Lake States in order toformulate a homogeneous inventory for the region.

### 13 The assumptions are as follows:

• 100% of wood combusted in non-certified units.

• OWB units to be 90% in rural counties and 10% in urban counties

• 11.68 cords of wood consumption per unit peryear (includes heating efficiency of 30-40%)

• 5 months heating season = 3650 hours (24/7)

• PM 2.5 

### emissions factor (g/kg wood) =13.82 (Average of indoor and outdoor) or 27.64 lb/ton of wood The agreed upon methodology requi res that total number ofOWB sold in Ohio be apportioned to each county based on rural or urban designation while observing the 9:1 ratio in area sales. The guesstimated factor s (see above) are applied to calculate the emissions from this outdoor wood burner. Total emissions obtained from this category are subtracted from the Residential Wood Co mbustion category to allow for accurate emissions from the indoor wood burning units.

2.7 References 1. Documentation For the 2002 Non-Point S ource National Emission Inventory For CAPS and HAPS . U.S. Environmental Protecti on Agency. Emissions Factor and inventory Group. E.H Pe chan and Associates, Inc. January 2004.

2. United States Census Bureau. Population Division. http://eire.census.gov/popest/data/c ounties/tables/CO-EST 2002/CO-EST2002-01- 39.php (Accessed 2003) 3. United States Census Bureau. County Business Patterns. http://censtats.census.gov/cbpnaic/cbpnaic.shtml (Accessed 2003) 4. Ohio Department of Development, Office of Strategic Research. Population Projects by Age and Sex: 2005-2030. http://www.odod.ohio.gov /research/files/p200.htm (Accessed August 2006) 5. Environmental Protection Agency (EPA). 1999 Base Year Non-point Source National Emission Inventory for Hazardous Air Pollutants, Research Triangle Park, NC. September 28, 2001.

6 . Environmental Protection Agency ( EPA). STAPPA-ALAP CO-EPA Emission Inventory Improvement Progr am (EIIP). Volume III - Area Sources Preferred and Alternative Methods. November 1996.

7. Documentation for the Dr aft 1999 National Emissions In ventory (Version 3.0) for Criteria Air Pollutants and Amm onia. Area Sources. E. H. Pechan & Associates, Inc. March 3, 2003

### 14 8. U.S. Environmental Pr otection Agency, STAPPA-ALAPC O-EPA Emission Inventory Improvement Program (EIIP), Volume III - Area Sources Preferred and Alternative Methods, Chapter 8. September 1997. 9. Spreadsheet formulation provided by “Buzz” David Asse lmeier, Air Quality Planning Section, Inventory Group, Springfield, Illinois. 10. Environmental Protection Agen cy (EPA). STAPPA-ALAPCO-EPA Emission Inventory Improvement Progr am (EIIP). Volume III - Area Sources Preferred and Alternative Methods. May 1997. 11. (Environmental Chemistry.com) viewed on Feb 8th, 2007. [http://environmentalchemistry.com/yogi /environmental/200602out doorwoodfurnaces.ht ml ] 12. (Washington State, Department of Ecology) viewed on Feb 8th, 2007 [http://www.ecy.wa.gov/progr ams/air/AOP_Permits/Boiler /Outdoor_Boilers_home.html] 13. U.S. Environmental Protection Agen cy. Reducing Pollution from Outdoor WoodFired Hydronic Heaters. Fact Sheet http://www.epa.gov/owhh/ pdfs/fact_sheet_1_29_07.pdf(Accessed 1/2007)

14. Industrial Sector E nergy Price and Expenditure Estimates, 1970-2001, Ohio. Energy Information Administration. U. S. Department of Energy. http://www.eia.doe.gov/emeu/st ates/sep_prices/ind/pr_ind_oh.html http://www.eia.doe.gov/em eu/aer/pdf/pages/sec1_27.pdf(Accessed 2003)

15. State Fire Marshal Office. Fire Prevention Bureau, Columbus, Ohio. http://www.com.state.oh. us/odoc/sfm/firecont.htm (Accessed 2003)

16. Documentation for the Draft 1999 National Emissions In ventory (Version 3.0) For Criteria Air Pollutants and Amm onia. Area Sources. E. H. Pechan & Associates, Inc. March 3, 2003 17. Ohio Department of Health, Vital Statistics 18. Environmental Protection Agency. STAPPA-ALAPCO-EPA Em ission Inventory Improvement Program (EIIP). Volume X – Emissions Projections. December 1999. http://www.epa.gov/ttn/chief/eiip/techreport/volume10/x01.pdf (Accessed 2/2007) 19. Environmental Protection Agency. AP-42. http://www.epa.gov/ttn/chief/ap42/

### 15 

### SECTION 3

NON-ROAD SOURCES The non-road inventory is gener ated regionally by running U. S. EPA’s Nati onal Mobile Inventory Model (NMIM) model. The Wi sconsin Department ofNatural Resources undertook the responsibility of customizing the NMIM input files and submitting the output file in NIF format to LADCO and U.S. EPA. LADCO process ed the NMIM files in their emissions model and generat ed daily emissions rates. Grant Heatherington from the Wisconsin Department of Natural Reso urces provided the following descriptions... The National Mobile Inventory Model (NMIM) developed by USEPA was used to estimate emissions for all other non-road m obile categories. NMIM consolidates nonroad mobile emissions and on-road emissions modeling into a singl e modeling system. Only the non-road emissions modeling portion ofNMIM was used in the development of this emission’s inventory. NMIM uses the USEPA’s NONROAD model to calculate nonroad mobile emissions. The basic NONROAD algorithm for calculating emissions uses base year equipment populati ons, average load factors, available engine powers, activity hours and emission factors. Before NMIM was run, modifications and additions were made to the NM IM input data.

a. Added emission factors for diesel ta mpers/rammers provided by E.H. Pechan & Associates, Inc. Diesel tampers/rammers are a type of construction equipment.

b. Revised PM 2.5 

### ratios in SCC table to correctly calculate PM 2 

### . 5

### diesel emissions. This error was introduc ed with NMIM2005 and didn’t exist in NMIM2004.

c. Revised gasoline parameter s using updates provi ded by the states and E.H. Pechan & Associates, Inc. Ga soline parameters include Reid Vapor Pressure (RVP), oxygenate c ontent and sulfur content.

The NMIM NEI NIF files are on the LADCO ftp site at: ftp://ftp.airtoxics.org/in v2005/nonroad/NMIM /Base_L_ph2/2005/



### Revised NMIM2005 Input Data

Emission Factor Data All States: Pechan revised the brake specific fuel consumption (BSFC) emission factor data to include diesel tampers/rammers (2270002006). The revised NMIM file is saved as revBSFC.EMF.

### 16 Population Data For 26000.pop, replaced default file supplied with NMIM2005 with 26000_rev_NMIM05.pop that contains revised construction data missing from 26000.pop external file provided with NMIM2005. This Michigan construction data should have been added with the other LADCO states modified construction data but was overlooked.


### SCC Data The default SCC table of NCD20060201 is replaced by a version that contains corrections to the PM25fac field that earlier NCDs contained (i.e. changed from 0.92 to 0.97 for diesel non-road equipment) in NONROAD2004.



### Fuel Data

LADCO States: Pechan revised four tables (countyyear, countyyearmonth, datasource and gasoline) in the National County Database (NCD) used by NMIM to incorporate new fuel data. AIR revised gasoline characteristics per instructions from the states. Also, gasoline characteristic revisions for 2005 provided by states were incorporated. Additional revisions were incorporated into 2002 data for non-road Stage 2 controls. Depending on the year being modeled, different versions of the revised tables are used. Also, the countynrfile, countyyear and datasource tables were revised to reference the new activity, allocation, growth, population and seasonality files described above. NCD tables with names ending in “def” are default versions of the table. See table below for the appropriate versions of the tables for the selected years. Non-LADCO States: The countynrfile, countyyear and datasource tables were revised to reference the new activity, allocation and seasonality files described above. See table below for the appropriate versions of the tables for the selected years.


### Table 3-1 NMIM National County DatabaseTables for Specific Years and States

States Years 1999 (WI only) 2002, 05, 07, 08, 09, 12 and 18 LADCO states countynrfile_NMIM05_rev, countyyear_NMIM05_rev, countyyearmonth_NMIM05_w _05_12_18_rev, datasource_NMIM05_rev, gasoline_NMIM05_def SCC_NCD20060201_rev (used when NCD20060201 is used) countynrfile_NMIM05_rev, countyyear_NMIM05_rev , countyyearmonth_NMIM05_w_05_12_18_rev, datasource_NMIM05_rev, gasoline_NMIM05_w_05_12_18_rev SCC_NCD20060201_rev (used when NCD20060201 is used)

### 17 

### SECTION 4

ON-ROAD SOURCES A mobile source of air pollution is a self-p ropelled or portable emi tter of air pollutants, and mobile source emissions are those genera ted by the engines or motors that power such sources. Most mobile sources, exce pt jet or turboprop ai rcraft, are powered by internal combustion (IC) piston engines, and nearly all use liquid fuels. Gaseous fuels, such as compressed natur al gas (CNG) or li quefied petroleum gas (LPG), had only a very small fraction of the motor fuel market in Ohio in 2005. Solid fuels have not been used by mobile sources in significant amounts since railroads retired their coal-powered steam locomotives in the 1950s. 4.1 Categories of Mobile Sources For inventory and planning pur poses, mobile sources ar e divided into two major categories. 1. On-highwaymobile sources (usually referred to as on-road ), e.g., motor vehicles such as cars, vans, trucks, buses and motorcycles used for transportation of goods and pa ssengers on roads and streets 2. Off-highway(usually referred to as non-road ) mobile sources including:

• Modes of powered transportation thatdo not use roads, such as aircraft, trains, ships and boats, and motor vehicles used off-road.

• Self-propelled or portable motoriz ed machines or equipment not used for transportation, ranging from constructi on equipment and farm tractors to lawnmowers and hand-held power weed choppers.

Mobile Sources: All on-road mobile source s are self-propelled.

Non-road Mobile Sources: Some non-road mobile source s (e.g., farm tractors), are self-propelled, but many non-road sources ar e not. A gasoline-powe red chain saw is a familiar example of a non-self-pr opelled non-road mobile source. Stationary Sources: Not all movable or portable emi ssion sources are mobile sources, however. A small truck-portable cement or hot-mix asphalt plant, for example, may be set up near a construction or road-building site . Such plants are classified as stationary sources, not mobile sources for two reasons: (1) they may operate for weeks or months at a single location, and (2) the trucks thatmove the plants do not supply power for them.

### 18 NOTE: Not all Internal Combustion engines (IC) orturbine engines are mobile sources. Fixed IC engines, such as those that pow er pipeline compressors or standby generators in electricity plants and elsewhere, are al so classified as stationary sources. 4.1.1 Categories and Componen ts of Mobile Source Emissions
There are three categories ofmobile source emissions:

• Exhaust or tailpipe emissions , which result from the combustion of fuel in the source’s engine

• Evaporative emissions , which result from evaporation of fuel from the engine or its fuel system

• Refueling emissions

Exhaust Emissions: Are the result of fuel combustion and occu r only when the engine is running. Evaporative emissions: Are Volatile Organic Compou nd (VOC) based only and are continuously emitted from an engine’s fuel syst em, whether the engine is running or not. Gasoline is a very volatile fuel, so total VOC emissions from gasoline powered vehicles have a large evaporative component. Diesel and je t fuels are of very low volatility, so evaporative emissions from diesel and turbi ne engines are a much smaller part of their total VOC emissions. Evaporative emission s for CNG or LPG powered vehicles are negligible because their fuel tanks and systems are of necessity, sealed. Evaporative and exhaust VOC emissions can be calculated separately for most mobile source categories. Evaporative emissions do not include VOC emissions that occur during refueling. Refueling Emissions: These emissions are the third category of mobile source emissions. Refueling emissi ons are entirely VOC. Alth ough they result from the evaporation of fuel, they ar e distinct from, and not dire ctly related to, evaporative emissions as defined above. Refueling emissions have two subcomponents:

• Displacement emissions . These occur when new fuel is transferred into a partly filled tank--be it a service station stor age tank, a portable fuel container (gas can), or a vehicle or engine’s fuel tank; displacing the air in the tank and forcing that vapor-rich air out the inlet pipe or other vent. There are two stages of displacement emissions:

o “ Stage I ” emissions occur when the underground storage tanks at a service station are being refilled;

### 19 o “ Stage II ” emissions occur when a motor vehicle (or gas can) is being refueled.

NOTE: These emissions are covered in , “Area Sources,” section 3.6.

• Spill emissions . These occur when drops of fuel drip or splash on the ground during or after refueling and evaporate away. 4.2 Ohio On-Road Mobile Source Inventory
The inventory of on-road mobile source emissions was developed in conjunction with the Ohio Department of Transportation (ODOT), Lake Michigan Air Director’s Consortium (LADCO), Unit ed States Environmental Protection Agency (USEPA), and the Ohio EPA (OEPA). Estimates of the amounts of NOx and VO C are reported by county in tons per day. Emissions are reported for a typical ozone season weekday in the summer of 2005.

4.2.1 Emission Inventories Developed with MOBILE6 Model

MOBILE6 Overview: MOBILE6 is a computer program that es timates hydrocarbon (HC), carbon monoxide (CO), oxides of nitrogen (NO x 

### ), exhaust particulate matter (which consists of several components), tire wear particula te matter, brake wear particu late matter, sulfur dioxide (SO 2 

### ), ammonia (NH 3 

### ), six hazardous air pollutant (HAP), and carbon dioxide (CO 2 

### ) emission factors for gasoline-f ueled and diesel highway moto r vehicles, and for certain specialized vehicles such as natural-gas-fuel ed or electric vehicles that may replace them. The program uses the calculation procedures presented in technical reports posted on EPA's MOBILE6 Web page http ://www.epa.gov/otaq/models.htm. MOBILE6 emission factor estimates depend on various conditions, such as ambient temperatures, travel speeds, operating modes, fuel volatility, and mileage accrual rates. Many of the variables affe cting vehicle emissions can be specified by the user. MOBILE6 will estimate emission factors fo r any calendar year between 1952 and 2050, inclusive. Vehicles from the 25 most re cent model years are considered to be in operation in each calendar year.

4.2.2 MOBILE6 Defaults: MOBILE6 includes default values for a wide range of conditions that affect emissions. These defaults are designed to represent “ national average” input data values. Users who desire a more precise estimate of local emissions can substitute information that more specifically reflects local conditions. Use of local input data will be particularly common when the local emission inventory is to be constructed from separate

### 20 estimates of roadways, geographic areas, or ti mes of day, in which fleet or traffic conditions vary considerably. A list of MOBILE6 input parameters is provi ded below. Most of these inputs are optional because the model will supply default values unless alternate dataare provided. 4.2.3 MOBILE6 Input Parameters

• Calendar year

• Month (January, July)

• Hourly Temperature

• Altitude (high, low)

• Weekend/weekday

• Fuel characteristics (Reid va por pressure, sulfur content, oxygenate content, etc.)

• Humidity and solar load

• Registration (age) distribution by vehicle class

• Annual mileage accumulation by vehicle class

• Diesel sales fractions by vehicle class and model year

• Average speed distribution by hour and roadway

• Distribution of vehicle miles traveled by roadway type

• Engine starts per day by vehi cle class and distribution by hour

• Engine start soak time distribution by hour

• Trip end distribution by hour

• Average trip length distribution

• Hot soak duration

• Distribution of vehicle miles traveled by vehicle class

• Full, partial, and multiple diurnal distribution by hour

• Inspection and maintenance ( I/M) program description

• Anti-tampering inspection program description

• Stage II refueling emissions inspection program description

• Natural gas vehicle fractions

• HC species output

• Particle size cutoff

• Emissions factors for PM and HAP

• 

### Output format specific ations and selections
4.2.4 MOBILE6 References
The following publications prov ide much of the guidance fo r the preparation of the onhighway inventory. EPA-450/4-81-026d (Revised), now EPA/450-R-92-009, Procedures for Emission Inventory Preparation , Volume IV: Mobile Sources , December 1992. Hereafter, “Procedures Vol. IV”. The 1992 vers ion is still the definitive document on

### 21 inventories. If a previous edition is referr ed to, the fact will be not ed as, for example, “the 1989 Procedures Vol. IV” or “Volume IV, 1989 edition”.
EPA420-R-03-010, User’s Guide to MOBILE6.1 and MOBILE6.2: Mobile Source Emission Factor Model , August 2003. This is the User’s Guide for the official MOBILE6.2.03 on-highway mobile source em ission factor model and will usually be referred to as the M6.2 (or simply M6) User’s Guide (UG). The M6 model in its various versions was developed and publis hed by Assessment & Modeling Division (AMD) of the National Vehicle & Fuels Em issions Laboratory (NVFEL) in Ann Arbor, Michigan. The NVFEL is part of USE PA Office of Transportation & Air Quality (OTAQ), formerly the Office ofMobile Sources (OMS).

Technical Guidance on the Use of MOBILE6 for Emission Inventory Preparation , August 2004. Hereafter, the M6 “Technical Guidance [Document]” or “TGD”. The TGD is the pr imary source of guidance on M6 inputs and an invaluable adjunct to the M6 User’s Guide. USEPA document “Frequently Asked Questions on MOBILE6” , 16 January 2002. Hereafter, [M6] “FAQ”. Thisdocument was published along with the M6 TGD. USEPA memo, “Policy Guidance on the Use of MOBILE6 for SIP Development and Transportation Conformity” , dated 18 January 2002, from John Seitz, Director of OAQPS, and Mar go Oge, Director of OTAQ, to Regional Air Division Directors.

4.3 Ohio’s Alternate Data for MOBILE6 Alternative data is state-specif ic data that is used in the M obile6 runs. Using local data is preferred to using the default data in Mobi le6. Efforts are made to collect as much local data as possible.

4.3.1 Vehicle Registra tion Distribution by Age

Overview: The vehicle age distribution determines the fr action of vehicles operating within each emissions control requirementstandard and the deterioration of the emission control technology. Emission rates vary widely between new and older vehicles. Thus, even small changes in fleet age, particularly for older vehicles , may result in large changes in emission totals.

### 22 The MOBILE6 model requires esti mates of a distribution of r egistered vehicles by age and vehicle category for current and futureyears. MOBILE6 default values were developed using national level vehicle registration data by age and class for July 1, 1996. EPA developed a methodology to convert t he July 1, 1996 registration profile into a general registration distribut ion by age and by vehicle ca tegory for some 6 composite (gasoline and diesel) vehicle types plus motorcycles. To project future changes, EPA evaluated general sales growth and vehicle scrappage trends for the total light-duty vehicle in-use fleet and the total heavy-dut y vehicle in-use fleet, and made minor adjustments, where possible, to reflect some of the differences between vehicle categories. Description: The MOBILE6 model requires estimates of a distribution of registered vehicles by age and vehicle category for curr ent and future years. OEPA chose to use local vehicle registration data provided by the Ohio Bureau of Motor Vehicles (BMV) which was sent to the Lake Michigan Air Dir ectors Consortium (LADCO) to develop these inputs. LADCO then contracted with a subcontractor to breakout the age distribution data from the Vehicle Identification Num bers (VIN).

Note: It was learned during the course of this inventory that there were some discrepancies in the age distribution data. But itwas too large of a project to reevaluate the data prior to this invent ory. This will be corrected in the next inventory (2008). Method Applicability: This approach is most applic able in areas where there are significant differences in the local vehicle fleet age distribution rela tive to the national average.
Data Sources and Procedures: This approach involves using local vehicle registration data. This is typically available at the county level, but may also be applied using statewide data from the stat e motor vehicle registration office. The fleet age should be representative of the vehicle fleet over the small urban or rural area under question. Advantages:

• Uses locally specific registration data, which is likely more representative of the local area than t he national default.

• Requires minimal additional resources, particularly if data is readily available at the county or local level fr om the State departm ent of motor vehicle registration.

• Recommended by EPA and generally is encouraged as a preferred approach over the national default approach.

### 23 4.3.2 Daily Vehicle Miles Traveled (DVMT)

Overview: In coordination with Ohio Metropolitan Pl anning Organizations (MPOs), the Ohio Department of Transportation (ODOT) provi ded Daily Vehicle Miles Traveled (DVMT) data and travel demand model (TDM) data. TDM data will be covered in another section. Because TDM results are used by t he state and MPOs to fo recast traffic for a variety of reasons, undergo rigorous calibrati on and validation checks, and are sensitive to roadway capacity/travel time improvement s, the TDMs are considered the best tool for emissions forecasting. Therefore, the DVMT data discussed in this section is not used directly for all areas of Ohio. In countie s where it is not used directly it is used for making rough emissions estimates where model s do not exist or where time prohibits the use of TDMs. DVMT is a simple mechan ism to measure how much traffic is flowing along a roadway during an average 24 hour peri od. This simple formula multiplies Average Annual Daily Traffic (AADT) by the length of the roadway. For example; if a roadway is 2 miles in length and the AADT is 4000 vehicles per day the DVMT would be computed by multiplying 2* 4,000 =8,000 or 8,000 DVMT. County-By-County DVMT is computed usin g the State of Ohio, Department of Transportation’s Roadway Information F iles and the annual Highway Performance Monitoring System (HPMS) Summary Reports . DVMT’s are computed for all of the Federal Functional Class (FC) categories within each of Ohio’s 88 counties. The AADT and Roadway length information prov ides a very accurate estimate of statewide total DVMT for The State Highway S ystem (Interstate, US and State Routes). County total DVMT are consistent and cons idered a good source of county level DVMT for countywide emissions estimates. For roadways that are notpart of the State Highway System, various representative count s were used, such as: railroad crossing counts, HPMS Sample Section Counts, etc. All traffic count data that was not collected during the current year has had statewide growth factors applied to account for systematic growth. Given the previously mentioned methodologies, the DVMT data is more accurate on roads functionally classified as collector or above.

Table 4-1 Federal Func tional Class Categories:

01 - Rural Interstate 02 - Rural Principal Arterial 06 - Rural Minor Arterial 07 - Rural Major Collector 08 - Rural Minor Collector 09 - Rural Local 11 - Urban Interstate 12 - Urban Freeway & Expressway 14 - Urban Principal Arterial 16 - Urban Minor Arterial 17 - Urban Collector 19 - Urban Local

### 24 Table 4-2 DVMT County Summary:

For PDF web based tables of 2005 DVMT by county see: http://www.dot.state.oh.us/techservsite/availpro/Road_%20Infor/KDVMT/vmt2005.pdf Disclaimer by ODOT:

The above PDF web based tables contain the State of Ohio's adjusted county DVMT's and road mileage for the years 1990 - 2005. Please be aware that the numbers are estimates only. The factoring process used annual, estimated, and statewide ADT (Average Daily Traffic) growth factors, deriv ed from the output of a limited number of traffic counting stations around the state. Although the growth factors are available by functional class, they are more reliable for major roads such as interstates or expressways, which are relatively well-sampl ed, than for local roads or collectors. The numbers also do no allow for periodic, large- scale functional reclassification actions

### 25 which reassign selected roads or road segm ents from one functional class to another. The Ohio Department of Transportation t herefore does not warr ant the accuracy, completeness, or reliability of these estimates for your research. We also do not assume responsibility for any incorrectness that may occur.

4.3.3 VMT From Travel Demand Models (TDM)

Overview: Travel demand forecast modeling is perform ed by the Ohio Metropolitan Planning Organizations (MPOs) and ODOT for a multit ude of purposes including the preparation of regional emissions estimate s. The ODOT Office of Te chnical Services’ Modeling & Forecasting Section recommends that Ohio ’s TDMs and ODOT’s conformity analysis methods be used to establish the roadway mob ile source portion of Ohio’s SIP budget to assure consistent methods are used for transportation conformity analysis and budgets. Therefore, ODOT provided both MPO regional TDM runs and statewide TDM runs with associated data to OEPA and LADC O. The ODOT provided model run data for years 2002, 2005, 2009, 2012, and 2018. Data provided included loaded networks in both CSV format and GIS shape files, trip end summaries, zone boundary GIS shape files, intra-zonal trip VMT estimates, and VMT summaries for each of the loaded networ ks. Additional post processing data was provided including but not lim ited to metadata describing the loaded networks, Hourly distribution by functional cla ss, speed profiles, day of week / weekend / monthly car and truck traffic profiles, 2009 & 2018 VMT RPO data sets, state wide VMT growth rates for local traffic, and a 2005 VMT summary comparison spreadsheet. It should be noted that among other things, the loaded TDM Netw orks contain distance and daily volumes from which VMT is computed. Network volumes are post processed to esti mate VMT by hour of day. The hourly volumes and capacity, posted speed limi t, and type of roadway for each roadway segment are then used to estimate aver age hourly speeds needed for MOBILE6 based emissions estimates. Modelin g by segment by hour of day in this way makes emissions estimates more sensitive to the effects of roadway improvements. This allows transportation planners to evaluate the relati ve emissions affect of improvements to individual roadways as well as packages ofimprovements and the entire set of planned roadway improvement projects air quality impacts of construction programs.

### 26 4.3.4 Speed Di stribution Profiles

Overview: ODOT provided speed distribution profiles toLADCO. A couple of different sets of speed distribution profiles were provided to OEPA and LADCO for their use, a table of space mean speeds by functional class for use with DVMTs and link group speed curves for post processing travel demand model traffic forecasts. Both sets of speed profiles are based on the same speed study c onducted by ODOT. The speed study is documented in “Statewide Travel Time Study, May 2001 by Greg Giaimo, Ohio Department of Transportation ”. When OEPA asked for s peeds for use with MOBILE6 for development of CERR, ODOT provided a set of speeds based on that statewide travel time study. Those speeds are doc umented in a technical memorandum titled “Estimation of Average Speed by Functional Class for MOBILE6 Runs ” dated 5/27/2004. Readers should refer to those docum ents for the details. Here the contents of the technical memo, Estimated Average Speed by Functional Class, are summarized.

Space Mean Speeds by Functional Class for U se with County Level DVMT, HPMS:

The memo states that the s peeds which the Ohio Department of Transportation (ODOT) had been using prior to that date, 2004, fo r air quality analysis estimates based on County DVMT summaries, were developed by a former ODOT employee for addressing the one (1) hour standards conformity ru les established due to 1990 emissions exceedances. No documentation was found in ODOT’s files on the origin of these average speed values or how they were esti mated. In addition, EPA has requirements for using latest planning assumptions for ai r quality conformity analyses. Therefore, ODOT believed that it was in the state’s best interest to use the mo st recent available data to provide a new set of estimated av erage speeds consistent with those used for urban area travel demand models which were under development at that time. The memo contains comparisons of 2002 speed dat a obtained from traf fic count equipment, automatic traffic recorders (ATRs) which co llect data continuously throughout the year. It also contains comparisons of the newspeeds with those used to address the one hour standard Gebhart’s. The graphs shown in figure 1, taken from the memo, illustrate the comparisons. The first graph compares time mean speeds from the ATRs with space mean speeds from ODOTs travel time study done in 2001and with the speeds used for addressing the one hour standard.

### 27 Figure 1 - Speed Comparison Graphs

Speeds Comparison

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0

FC01 FC 0

6 F C0 8 F C1 1 FC1 4 FC1 7



### Functional ClassSpeed Average Speed

1990 Analysis Speeds 2001 Speed Study



## Speeds Comparison

0 20 40 60 80 100

FC 0

1 FC 06 F C08 F C11 FC14 FC 1

7

R

AMPS



### Functional ClassSpeed 

### Average Speed
Min. Avg Speed
Max. Avg. Speed
Gebhardt's Speeds
Spd Study Est Speeds Spd Study Greg Est



### The following caution statem ent was taken from the Estimation of Average Speed by Functional Class memo.

CAUTION

### : It should be noted that speeds on facilities falling in any one of the federal functional classifications vary greatly bet ween roadways, between hour of the day, and day of the week. So these provide only very rough estimates of speed and should be used with caution. In addition, it is expec ted that these average statewide speeds are higher than the average speeds in t he non-attainment areas because the non-

### 28 attainment counties tend to be more popul ated and more congested. The document “Highway Vehicle Speed Es timation Procedures For Use in Emission Inventories”, September 1991 by Earl Ruiter of Cambridge Systematics Inc. is referenced by EPA’s documented procedures for emission inventor y preparation. This document suggests post processing travel demand model traffic assignment results to estimate average speeds.
Final space mean speeds that ODOT provi ded are summarized in the Table 1 below: Table 4-3 Speed by Federal Functional Class Functional Class 1990 Analysis 2001 Speed Study Speeds Speeds FC01 57.3 64.0 FC02 45.3 53.0 FC06 39.9 53.0 FC07 35.1 43.1 FC08 30.5 43.1 FC09 28.0 43.1 FC11 46.3 61.6 FC12 43.3 61.6 FC14 18.9 29.3 FC16 19.6 29.3 FC17 19.6 29.2 FC19 19.6 23.8

It was decided by mutual agreement among individuals within the ODOT Office of Technical Services that these new s pace mean speed based average speed estimates were reproducible and defensib le since they are well docu mented and should therefore be the speeds used with HPMS** VMT if anyyear 2002 emissions budget work is done using only the county level VMT summaries discussed in section 5.3.2 Daily Vehicle Miles Traveled (DVMT).

** Note that HPMS VMT is a statewide VMT estimate and the county level DVMT summaries are consistent with the HPMS VMT so the county level DVMT summaries are loosely referred to as HPMS VMTs even though in fact they are not. 4.3.5 Link Group Speed Curves: The ODOT Modeling & Forecasting Section recommends that Ohio’s travel demand forecasting models and ODOT’s conformity anal ysis methods be used to establish the roadway mobile source portion of Ohio’s SIP budget for reasons already mentioned in 5.3.2 and to assure consistent methods are used for transportation conformity demonstration analyses and budget s. Therefore, ODOT pr ovided travel demand model runs and the speed curves by link group that ODOT uses for the speed estimates within

### 29 the post processing of travel demand model runs for estimating regional emissions. Table 2 shows these link group curves.

Table 4-4 Link Group Cod es & Associated BPR Curves

Link Group Facility Type Free Flow Speed Areatype a b 1 Freeway 75 Any 0.39 6.3 2 Freeway 70 Any 0.32 7.0 3 Freeway 65 Any 0.25 9.0 4 Freeway 60 Any 0.18 8.5 5 Freeway 55 Any 0.10 10.0 6 Multi-Lane 60 Rural 0.09 6.0 7 Multi-Lane 55 Rural 0.08 6.0 8 Multi-Lane 50 Rural 0.07 6.0 9 Multi-Lane 45 Rural 0.07 6.0 10 2 Lane Any Rural 0.34 4.0 10 Urban Street 50 Suburban 0.34 4.0

11 Urban Street 50 Urban 0.74 5.0

12 Urban Street 50 CBD 1.16 6.0

13 Urban Street 40 Suburban 0.38 5.0

14 Urban Street 40 Urban 0.70 5.0

15 Urban Street 40 CBD 1.00 5.0

16 Urban Street 35 Suburban 0.96 5.0

17 Urban Street 35 Urban 1.00 5.0

18 Urban Street 35 CBD 1.40 5.0

19 Urban Street 30 Suburban 1.11 5.0

20 Urban Street 30 Urban 1.20 5.0

21 Urban Street 30 CBD 1.50 5.0

Note: a and b are the BPR curv e parameters for the equation

T = T 0 

### {1 + a * (V/C)^b]

### 30 More complete details about emissions mode ling process employed by ODOT may be found in ODOT documentations. The docum ent titled “Congestion Management & Air Quality Analysis (CMAQ) Program Docu mentation” dated December 2005 may be obtained from the ODOT web site at www.dot.state.oh.us/urban/data/cmaq.doc (Microsoft Word document)

4.4 Mobile6 Inputs: The following table contains the inputs s upplied to LADCO to process our mobile inventory. 4.4.1 Ohio’s 2005 MOBILE6 Inputs The following tables are the result of a joint meeting between Ohio EPA, ODOT, and MPOs from around the state. At that meeting Mobile6 inputs were discussed and efforts were made to verify the sources of data inputs for Moble6. Dialogue has continued between the parties.

For historical reference:

>>> Dave Moore <Dave.Moore1@dot.s tate.oh.us> 4/10/2006 2:13 PM >>>
All, An air quality coordination meeting has been scheduled for April 27, 2006 at 10:00 AM at ODOT Central Office conference room GA. The primary purpose of this meeting is to discuss development of 2002 mobile source inventories for use in developi ng the Ohio 2007 8-Hour Ozone SIP Attainment Demonstrations. See meeting agen da below. OEPA is working to ward a June 15, 2006 schedule for submitting the 2002 invent ories to US EPA. A key component of the meeting will be to review a nd confirm the MOBILE6.2 i nput parameters, by Ohio a/q area, for use in developing the 2002 mobile inve ntories. See draft templa te below. The Ohio MPO travel demand models will be used to generate t he 2002 VMT inputs to MOBILE. Thanks, DM DM

### 31 IMPORTANT NOTICE: The following tables are not to be used for inventory purposes as the data is subject to change. For the cu rrent input table, contact Ohio EPA, Division of Air Pollution Control.

Table 4-5 Mobile Inputs 

### Cleveland-Akron 2005 Ozone M6.2 Inputs Includes the following counties: Ashtabula, Cuyahoga, Geauga, Lake, Lorain, Medina, Portage, Summit



### State Programs Input

Stage II Refueling 93/3/86/86
Anti-tampering Programs 96/78/50/22222/21111111/1/12/098./12111112
I/M Programs Yes Exclude Ashtabula County - No I/M program Program 1 2004 2050 2 T/O OBD I/M Model Years 1 1996 2050 Vehicles 1 22222 21111111 1 Stringency 1 30.0 Compliance 1 98.0 Waiver Rates 1 1.0 1.0 Cutpoints Exemption Age 1 25 Grace Period 1 4 NO TTC Credits Effectiveness DESC file
Program 2 2004 2050 2 T/O EVAP OBD & GC Model Years 2 1996 2050 Vehicles 2 22222 11111111 1 Stringency Compliance 2 98.0 Waiver Rates 2 1.0 1.0 Cutpoints Exemption Age 2 25 Grace Period 2 4 NO TTC Credits Effectiveness DESC file
Program 3 2001 2003 2 T/O ASM 2525 PHASE-IN

### 32 Model Years 3 1996 2003 Vehicles 3 22222 21111111 1 Stringency 3 30.0 Compliance 3 98.0 Waiver Rates 3 3.0 1.0 Cutpoints Exemption Age 3 25 Grace Period 3 2 NO TTC Credits Effectiveness DESC file
Program 4 2001 2050 2 T/O ASM 2525 PHASE-IN Model Years 4 1975 1995 Vehicles 4 22222 21111111 1 Stringency 4 30.0 Compliance 4 98.0 Waiver Rates 4 3.0 1.0 Cutpoints Exemption Age 4 25 Grace Period 4 4 NO TTC Credits Effectiveness DESC file
Program 5 1998 2000 2 T/O LOADED/IDLE Model Years 5 1975 2000 Vehicles 5 22222 21111111 1 Stringency 5 30.0 Compliance 5 98.0 Waiver Rates 5 3.0 1.0 Cutpoints Exemption Age 5 25 Grace Period 5 2 NO TTC Credits Effectiveness DESC file
Program 6 1996 1997 2 T/O IM240 Model Years 6 1975 1997 Vehicles 6 22222 21111111 1 Stringency 6 30.0 Compliance 6 98.0 Waiver Rates 6 3.0 1.0 Cutpoints 6 CUTPOINT.D Exemption Age 6 25 Grace Period 6 2 NO TTC Credits Effectiveness DESC file

### 33 Program 7 1996 2050 2 T/O GC Model Years 7 1975 1995 Vehicles 7 22222 21111111 1 Stringency Compliance 7 98.0 Waiver Rates 7 3.0 1.0 Cutpoints Exemption Age 7 25 Grace Period 7 2 NO TTC Credits Effectiveness DESC file



### Fuel Commands

Fuel Program 1
Oxygenated Fuels 0.00 0.42 0.00 0.036 2

Fuel RVP 9


### Alternative Emission Regulati ons and Control Measures

Rebuild Effects 0.1



### External Conditions Commands

Calendar Year 2005

Evaluation Month 7
Min/Max Temperature National Climatic Data Center



### Vehicle Fleet Characteristic Commands

Registration Distribution Variable

### 34 

### Cincinnati-Dayton-Springfield 2005 Ozone M6.2 Inputs Includes the following counties: Ohio : Butler, Clark, Clermont, Clinton, Greene, Hamilton, Miami, Montgomery, Warren Indiana : Lawrenceburg Twp., Dearborn County Kentucky : Boone, Campbell and Kenton counties


### State Programs Input Note: Indiana and Kentucky inputs may not coincide with Ohio inputs
Stage II Refueling 93/3/86/86
Anti-tampering Programs 96/78/05/22222/21111111/1/12/098./12111112
I/M Programs Yes Excludes Clinton Co. and Miami Co., OH, Dearborn County, IN - No I/M program Note: I/M inputs for Kentucky counties are not included Program 1 2004 2050 2 T/O OBD I/M Model Years 1 1996 2050 Vehicles 1 22222 21111111 1 Stringency 1 30.0 Compliance 1 98.0 Waiver Rates 1 1.0 1.0 Cutpoints Exemption Age 1 25 Grace Period 1 2 NO TTC Credits Effectiveness DESC file
Program 2 2004 2050 2 T/O EVAP OBD & GC Model Years 2 1996 2050 Vehicles 2 22222 11111111 1 Stringency Compliance 2 98.0 Waiver Rates 2 1.0 1.0 Cutpoints Exemption Age 2 25 Grace Period 2 2 NO TTC Credits Effectiveness DESC file
Program 3 2001 2003 2 T/O ASM 2525 PHASE-IN Model Years 3 1996 2003 Vehicles 3 22222 21111111 1 Stringency 3 30.0 Compliance 3 98.0

### 35 Waiver Rates 3 3.0 1.0 Cutpoints Exemption Age 3 25 Grace Period 3 2 NO TTC Credits Effectiveness DESC file
Program 4 2001 2050 2 T/O ASM 2525 PHASE-IN Model Years 4 1975 1995 Vehicles 4 22222 21111111 1 Stringency 4 30.0 Compliance 4 98.0 Waiver Rates 4 3.0 1.0 Cutpoints Exemption Age 4 25 Grace Period 4 4 NO TTC Credits Effectiveness DESC file
Program 5 1998 2000 2 T/O LOADED/IDLE Model Years 5 1975 2000 Vehicles 5 22222 21111111 1 Stringency 5 30.0 Compliance 5 98.0 Waiver Rates 5 3.0 1.0 Cutpoints Exemption Age 5 25 Grace Period 5 2 NO TTC Credits Effectiveness DESC file
Program 6 1996 1997 2 T/O IM240 Model Years 6 1975 1997 Vehicles 6 22222 21111111 1 Stringency 6 30.0 Compliance 6 98.0 Waiver Rates 6 3.0 1.0 Cutpoints 6 CUTPOINT.D Exemption Age 6 25 Grace Period 6 2 NO TTC Credits Effectiveness DESC file
Program 7 1996 2050 2 T/O GC Model Years 7 1975 1995 Vehicles 7 22222 21111111 1

### 36 Stringency Compliance 7 98.0 Waiver Rates 7 3.0 1.0 Cutpoints Exemption Age 7 25 Grace Period 7 2 NO TTC Credits Effectiveness DESC file



### Fuel Commands

Fuel Program 1
Oxygenated Fuels 0.00 0.42 0.00 0.036 2

Fuel RVP 9


### Alternative Emission Regulati ons and Control Measures

Rebuild Effects 0.1



### External Conditions Commands

Calendar Year 2005

Evaluation Month 7
Min/Max Temperature National Climatic Data Center



### Vehicle Fleet Characteristic Commands

Registration Distribution Variable

### 37 

### Other Areas ( excluding NOACA/AMATS

### and OKI/MVRPC 

### ) Ozone M6.2 Inputs Includes the following counties: Ohio : Belmont, Columbiana, Delaware, Fairfield, Franklin, Jefferson, Knox, Licking, Lucas,Madison, Mahoning, Pickaway, Trumball, Wood



### Fuel Commands Input

Fuel Program 1
Oxygenated Fuels 0.00 0.42 0.00 0.036 2

Fuel RVP 9


### Alternative Emission Regulati ons and Control Measures

Rebuild Effects 0.1 (0.30 for 2018)



### External Conditions Commands

Calendar Year All

Evaluation Month 7
Min/Max Temperature National Climatic Data Center



### Vehicle Fleet Characteristic Commands

Registration Distribution Variable



### 4.5 Ohio’s Mobile Emission Data Processed by LADCO (Lake Michigan Air Director’s Consortium): 2005 TDM and Mobile6 input data were provided to LADCO for processing. The data was processed by LADCO with T3 to prepare itas an input into the ConCEPT model. T3 and ConCEPT are described as follows.

### 38 4.5.1 T3--Development of Link-Level Mobile Source Emission Inventories: Highly resolved emission inventories for on- road mobile sources are needed for air quality modeling to develop the necessarytechnical support for new State Implementation Plans (SIPs) fo r regional haze, fine particles , and ozone. Emissions for on-road motor vehicles are estimated using vehi cle miles traveled, tr ip starts and ends, speed, and other activity data developed byState Agencies and Metropolitan Planning Organizations (MPOs) using transportati on demand models (TDMs), and emission factors from EPA's MOBILE6 model. To s upport this modeling in the upper Midwest, ENVIRON, working with LADCO, State DOTs, and local MPOs, has developed a software tool (the TDM Transformation Tool, or "T3") that takes TDM output from approximately twenty transportation networ ks using a variety of models, applies appropriate data transformations , and outputs link- and county-le vel activity data in a uniform format for input to the CONCEPTemissions processing model (a new emissions processing model also developed wit h funding from LADCO). In a parallel effort, analyses of extensive automatic tra ffic recorder (ATR) dat a collected by State DOTs were conducted to develop temporal profiles (hour of day , day of week, and month of year) of vehicle counts and vehicl e mix by roadway type for developing the detailed on-road emissi on inventories. T3 provides a conduit from the projections of traffic demand model ers regarding vehicle types, road networks, and vehicle activity tothe activity data required by emissions modelers. The primary goals ofT3 are to provide an easy mechanism for incorporating TDM model outputs in as "raw" a format as possible, while simult aneously providing a great degree of flexibility in representing t he TDM projections in terms acceptable to most air quality models. These goal s have been achieved through the use of a dimensional transformation approach, w here the dimensions of the various transformations are user-defined - hence the name of the tool.
By Stella Shepard, Alison K. Pollack, John Haasbeek, ENVIRON International Corporation, 101 Rowland Way, Su ite 220, Novato, CA. 94945 & Mark Janssen, Lake Michigan Air Directors Consortium (LADCO ), 2250 E. Devon Avenue # 250, Des Plaines, IL 60018, janssen@ladco.org

4.5.2 ConCEPT--Consolidated CommunityEmissions Processing Tool an OpenSource Tool for the Emi ssions Modeling Community: The new CONCEPT (CONsolidated Communi ty Emissions Processing Tool) Emissions Processor is now available for use by the emissions modeling community. Developed as joint project between Alpine Geophysics, LLC and ENVIRON Corporation, with Midwest RPO and joint RPO funding, the CONCEPT model combines the best attributes of current emissions modeling syste ms into an open source model highlighting the following features: • Open Source. Writt en primarily in PostgreSQL, th e software required for running

### 39 CONCEPT is in the public dom ain. The model itself is GNU Public License (GPL) compliant and users are encouraged to make additions and enhancements to the modeling system.
• Transparent. The database structur e of the model makes the system easy to understand, and the modeling codes themselv es are extremely well documented to encourage user participation in the customizing the system for specific modeling requirements. • Quality Control. The CONCEPT model structure an d implementation allows for multiple levels of QA analysis during every step of the emissions calculation process. Using the database structures, an emissions modeler can easily trace a process or facility and review the calculat ion procedures and assumptions for any emissions value. The CONCEPT model includes modules for the major emissions source categories: area source, point source, on-ro ad motor vehicles, non-road motor vehicles and biogenic emissions, as well as a num ber of supporting modules, including spatial allocation factor development, speciation pr ofile development, growth and control for point and area sources, and CEM point sour ce emissions handling. The emissions modeling community has alr eady begun development of addi tional CONCEPT support modules including CEM preproce ssing software, graphical QA tools, and an interface to the traffic demand models for on-road mo tor vehicle emissions estimation. By Cyndi Loomis, James G. Wilkinson, Alpine Geophysics, LLC, & John Haasbeek, Alison Pollack, ENVIRON Corporation. & Mark Janssen, Lake Michigan Air Directors Consortium (LADCO), 2250 E. Devon Av enue # 250, Des Plaines, IL 60018, janssen@ladco.org

4.5.3 LADCO Ohio Data Outputs for 2005:
The following LADCO outputs and documents can be found at: www.ladco.org/tech/e mis/net05/index.html

Table 4-6 LADCO Data Output

Sta te Network T3 Descripti on DOC M6 Inpu ts VM T vs HP MS Exc el Average Day VMT (this should match conformi ty inventory ) Co unt y Em issi on s Re por t All Pollut ants After Speci ation Dropped VMT M6 Run Summ ary Pollut ant T otals (Short ) Raw Summ ary (pol,ve h, etype) Hourly Tempo ral Summ ary Hourly Veh Mix Summ ary Hourly Speed Summ ary (with volum e/ capaci ty)

OH AKRON AKRON OH OH AKRON 1 1 1 1 1 1 1 1 1

### 40 OH CANTON CANTON OH OH CANTON 1 1 1 1 1 1 1 1 1 OH CINCI CINCI OH OH CINCI 1 1 1 1 1 1 1 1 1 OH CLEVE CLEVE OH OH CLEVE 1 1 1 1 1 1 1 1 1

OH COLUMB US COLUMB US OH OH COLUMB US 1 1 1 1 1 1 1 1 1

OH SPRING FLD SPRING FLD OH OH SPRING FLD 1 1 1 1 1 1 1 1 1

OH TOLEDO TOLEDO OH OH TOLEDO 1 1 1 1 1 1 1 1 1

OH YNGSTO WN YNGSTO WN OH OH YNGSTO WN 1 1 1 1 1 1 1 1 1

OH STATEW D STATEW D OH OH STATEW D 1 1 1 1 1 1 1 1 1



### Additional Documents on LADCO Web Page: “Comparison to EPA's Default Model NMIM”

“How we Build the 2005 Vmt/Networks” “Spreadsheet/Graphics on Vehicle Mix” “Background on the T3 Tool “

4.6 MPO Contact Table Table 4-7 County Summary Ta ble of MPOs by County FIPS County Model Network MPO Contact Person 39001 Adams Statewide

39003 Allen Statewide Lima Allen County Regional Planning Commission Tom Mazur

39005 Ashland Statewide 39007 Ashtabula Statewide 39009 Athens Statewide 39011 Auglaize Statewide

39013 Belmont Statewide Bel-O-Mar Regional Council and Interstate Planning Commission Rakesh Sharma

39015 Brown Statewide

39017 Butler Cincinnat/Dayton Ohio-Kentucky-Indiana Regional Council of Governments Andy Reser

39019 Carroll Statewide 39021 Champaign Statewide

39023 Clark Springfield Coordinating Committee of the Clark County-Springfield Eric Ottoson

### 41 Transportation Study

39025 Clermont Cincinnat/Dayton Ohio-Kentucky-Indiana Regional Council of Governments Andy Reser

39027 Clinton Statewide 39029 Columbiana Statewide 39031 Coshocton Statewide 39033 Crawford Statewide

39035 Cuyahoga Cleveland Northeast Ohio Areawide Coordinating Agency Bill Davis

39037 Darke Statewide 39039 Defiance Statewide

39041 Delaware Columbus Mid-Ohio Regional Planning Commission Nick Gill

39043 Erie Statewide 39045 Fairfield Statewide 39047 Fayette Statewide

39049 Franklin Columbus Mid-Ohio Regional Planning Commission Nick Gill

39051 Fulton Statewide 39053 Gallia Statewide

39055 Geauga Cleveland Northeast Ohio Areawide Coordinating Agency Bill Davis

39057 Greene Cincinnat/Dayton Miami Valley Regional Planning Commission Ana Ramirez
39059 Guernsey Statewide

39061 Hamilton Cincinnat/Dayton Ohio-Kentucky-Indiana Regional Council of Governments Andy Reser

39063 Hancock Statewide 39065 Hardin Statewide 39067 Harrison Statewide 39069 Henry Statewide 39071 Highland Statewide 39073 Hocking Statewide 39075 Holmes Statewide 39077 Huron Statewide 39079 Jackson Statewide

39081 Jefferson Statewide Brooke-Hancock-Jefferson Transportation Study Policy Committee Mike Proprocki

39083 Knox Statewide

39085 Lake Cleveland Northeast Ohio Areawide Coordinating Agency Bill Davis

39087 Lawrence Statewide KYOVA Interstate Planning Commission

39089 Licking Columbus Licking County Area Transportation Study Matthew Hill
39091 Logan Statewide 39093 Lorain Cleveland Northeast Ohio Areawide Bill Davis

### 42 Coordinating Agency

39095 Lucas Toledo Toledo Metropolitan Area Council of Governments Sujatha Mohanakrishnan

39097 Madison Statewide

39099 Mahoning Youngstown Eastgate Regional Council of Governments R.P. Samulka

39101 Marion Statewide

39103 Medina Cleveland Northeast Ohio Areawide Coordinating Agency Bill Davis
39105 Meigs Statewide 39107 Mercer Statewide

39109 Miami Cincinnat/Dayton Miami Valley Regional Planning Commission Ana Ramirez

39111 Monroe Statewide

39113 Montgomery Cincinnat/Dayton Miami Valley Regional Planning Commission Ana Ramirez
39115 Morgan Statewide 39117 Morrow Statewide 39119 Muskingum Statewide 39121 Noble Statewide 39123 Ottawa Statewide 39125 Paulding Statewide 39127 Perry Statewide 39129 Pickaway Statewide 39131 Pike Statewide

39133 Portage Akron Akron Metropolitan Area Transportation Study Jason Segedy

39135 Preble Statewide 39137 Putnam Statewide

39139 Richland Statewide Richland County Regional Planning Commission John Adams

39141 Ross Statewide 39143 Sandusky Statewide 39145 Scioto Statewide 39147 Seneca Statewide 39149 Shelby Statewide

39151 Stark Canton Stark County Regional Planning Commission Dan Slicker

39153 Summit Akron Akron Metropolitan Area Transportation Study Jason Segedy

39155 Trumbull Youngstown (partial county model

coverage) Eastgate Regional Council of Governments R.P. Samulka

39157 Tuscarawas Statewide 39159 Union Statewide 39161 Van Wert Statewide 39163 Vinton Statewide

39165 Warren Cincinnat/Dayton Ohio-Kentucky-Indiana Regional Council of Governments Andy Reser, OKI

+

### 43 + Miami Valley Regional Planning Commission Ana Ramirez, MVRPC

39167 Washington Statewide Wood-Washington-Wirt Interstate Planning Commission 39169 Wayne Statewide 39171 Williams Statewide

39173 Wood Toledo Toledo Metropolitan Area Council of Governments Sujatha Mohanakrishnan
39175 Wyandot Statewide 

### NOTE: Complete MPO information can be found at, www.dot.state.oh.us/urban/mpomap.htm and at www.dot.state.oh.us/urban/mpolist.htm#Cleveland

.



### SECTION 5

MARINE, AIRCRAFT and RAIL (MAR) SOURCES

MAR sources are non-road sour ces which are significant enoug h in terms of emissions to be considered separately from the rest of the non-road sources. The MAR inventory consists of commercial marines, aircraft and locomotive sources. The marine and locomotive inventory is generated by Environ 1 

### under contract with LADCO and the aircraft inventory is generated by Ohio EPA.

5.1 Marine Vessel Sources The approach to commercial marine emi ssion estimates needed to be flexible because the activity data was available in many fo rmats. Emission esti mates were determined either by multiplying engine power, load factor, hours per ye ar of operation, or on the basis of the number of gall ons of fuel consumed.

Emissions were determined for ten subclasses of vessel types: Deep draft vessels (DDV) at port, DDV mid-late, push boats (rivers/lakes), tugs, ferries, other special (excursion) vessels, support vessels, dredges, commercial fishing, and military vessels (Coast Guard). These were linked to various Ohio lakes and rivers. Because of the large variety of methodologie s employed, inventory tables for the ten subcategories are detailed in the comp lete inventory prepared and published by ENVIRON Internati onal Corporation: LADCO 2005 COMMERCIAL MARINE EMISSIONS , by Christian E. Li ndhjem, March, 2007. Emission totals produced by ENVIRON were provided to LADCO to submit to EPA for Ohio’s State Implementation Plan (SIP).

### 44 5.2 Rail Sources The primary activity unit used to determine em issions is gallons of fuel consumed. Emission rates were derived from EPA doc uments provided as support documentation for the 1997 locomotive emission standards (EPA, 1997). Gallons of fuel consumed were based on rail activity. Rail activity was broken down into four Source Category Codes (SCC). Class I, linehaul rail: Large interstate railroad companies like Union Pacific and Norfolk Southern. Class I,II, III, switching rail: Yard operations. Class II, III line haul: Regional and local railroads. And Passenger rail: AMTRAK. Class I, line-haul represents 84.3% of fuel used and the larges t emission’s category. The complete emission’s inventory was prepared and published by ENVIRON International Corporation: LADCO 2005 LOCOMOTIVE EMISSIONS , by Christian E. Lindhjem, February, 2007. Emission totals produced by ENVIRON were provided to LADCO to submit to EPA for Ohio’s State Implementation Plan (SIP).

EPA. 1997: "Locomotive Emission Standards." Regulatory Support Document, United States Environmental Protection Agency, O ffice of Mobile Sources, April. And EPA 1997, Emission Factors for Locomotives," Environmental Protecti on Agency, EPA420-F-97-051, December.



### 5.3 Aircraft Sources

INTRODUCTION: The aircraft emission’s inventory is derived by taking the number of Landings and Take Offs (LTOs) per year and multiplying by an emission fact or. In the Ohio inventory when specific aircraft models and engine type emission factors are known they were used. For the rest of the inventory the emission factors came from USEPA’s fleet average emissions data. Those results are t hen compiled as tons per year per pollutant by county. The following de scribes the components, met hodology, and concludes with a description of an Access based aircraft emission calculator.

COMPONENTS: I. Ohio Airports: A list of both towered and non-towered airports in Ohio is obtained from the Ohio Department of Transportation. See: www.dot.state.oh.us/aviation/ In conversation with ODOT two individuals stated that the 16 4 airports listed covered over 90% of the airports in Ohio. See Table 1.

### 45 II. Number of Operations/LTOs by Airport/County: The ODOT list contained the number of operations a year per airport. An operation is either a landing or a take-off. A Landing and Take Off (LTO) is required for FAA EDMS calculations. LTOs were deriv ed simply by dividing the number of operations by two. These were totaled by county.

Table 5-1 Number of operations and LTOs for 2005

County Airport Name ID Total Operations LTOs/Year
Adams Alexander Salamon AMT 5210 2605 Allen Allen County AOH 32500 16250 Ashland Ashland County 3G4 49240 24620 Ashtabula Ashtabula County HZY 16886 8443
Ashtabula Germack 7D9 840 420 Athens Ohio University UNI 51600 25800 Auglaize Neil Armstrong AXV 29456 14728
Belmont Barnesville-Bradfield 6G5 10150 5075
Belmont Alderman 2P7 6150 3075 Brown Brown County GEO 5157 2578.5 Butler Butler County Regional HAO 61687 30843.5 Butler Hook Field Municipal MWO 40050 20025 Butler Miami University OXD 16708 8354 Carroll Carroll County -Tolson TSO 34950 17475
Carroll Parsons 5D6 2674 1337 Champaign Grimes Field I74 23480 11740 Champaign Weller 38I 300 150 Clark Springfield-Beckley Municipal SGH 64033 32016.5
Clark Mad River I54 15350 7675 Clermont Clermont County I69 35741 17870.5 Clinton Airborne Airpark ILN 52000 26000
Clinton Clinton Field I66 29360 14680
Clinton Hollister Field 2B6 161 80.5 Columbiana Columbiana County Ø2G 31146 15573
Columbiana Koons 8G8 2546 1273 Coshocton Richard Downing I4Ø 19550 9775 Coshocton Tri-City 8ØG 8085 4042.5 Crawford Port Bucyrus 17G 24871 12435.5 Crawford Galion Municipal GQQ 5216 2608 Cuyahoga Burke Lakefront BKL 97100 48550 Cuyahoga Cleveland-Hopkins International CLE 234356 117178 Cuyahoga Cuyahoga County CGF 79774 39887 Darke Darke County VES 9238 4619
Defiance Defiance Memorial DFI 9130 4565 Delaware Delaware Municipal DLZ 39300 19650
Delaware Packer 5E9 3181 1590.5
Erie Hinde 88D 1350 675 Erie Kelleys Island 89D 25495 12747.5 Erie Griffing-Sandusky SKY 112100 56050

### 46 Erie Wakeman I64 17324 8662
Fairfield Miller's Farm 7B4 360 180 Fairfield Fairfield County LHQ 43066 21533 Fayette Fayette County I23 29405 14702.5
Franklin Ohio State University OSU 134459 67229.5
Franklin Port Columbus International CMH 218438 109219
Franklin Rickenbacker International LCK 96200 48100
Franklin Bolton Field TZR 69149 34574.5 Franklin Columbus Southwest Ø4I 11833 5916.5 Franklin Darby Dan 6I6 11260 5630 Fulton Fulton County USE 21123 10561.5 Gallia Gallia-Meigs Regional GAS 12200 6100 Geauga Gates 7D8 4200 2100 Geauga Geauga County 7G8 5350 2675 Greene Greene County - Lewis A. Jackson I19 37400 18700
Greene Bloom 14I 100 50 Guernsey Cambridge Municipal CDI 6040 3020
Hamilton Lunken LUK 129430 64715
Hamilton Blue Ash ISZ 35000 17500
Hamilton Cincinnati West I67 30197 15098.5
Hancock Bluffton 5G7 71980 35990 Hancock Findlay FDY 19800 9900
Hancock Priebe 7D5 3850 1925 Hardin Ada ØD7 331 165.5 Hardin Hardin County I95 6562 3281 Hardin Elliott's Landing O74 1560 780 Harrison Harrison County 8G6 11900 5950 Henry Henry County 7W5 15637 7818.5 Highland Highland County HOC 18325 9162.5 Holmes Holmes County 1ØG 21400 10700 Huron Huron County 5A1 10100 5050
Huron Willard 8G1 2715 1357.5
Jackson James A. Rhodes I43 6053 3026.5 Jefferson Jefferson County Airpark 2G2 15969 7984.5
Jefferson Eddie Dew Memorial 1G8 3540 1770 Knox Knox County 4I3 20150 10075 Knox Wynkoop 6G4 4691 2345.5 Lake Concord Airpark 2G1 4510 2255 Lake Willoughby Lost Nation Municipal LNN 45085 22542.5 Lawrence Lawrence County Airpark HTW 41910 20955 Licking Newark-Heath VTA 12457 6228.5 Logan Bellefontaine Regional EDJ 8325 4162.5
Lorain Columbia 4G8 5150 2575 Lorain Elyria 1G1 14300 7150 Lorain Lagrange 92D 1155 577.5 Lorain Lorain County Regional LPR 62000 31000
Lorain Reader-Botsford Airfield 67D 18700 9350 Lucas Toledo Express TOL 94600 47300

### 47 Madison Madison County UYF 41410 20705 Mahoning Salem Airpark 38D 16920 8460 Mahoning Tri-City 3G6 10555 5277.5 Mahoning Elser Metro 4G4 49232 24616 Mahoning Lansdowne Ø4G 750 375 Marion Marion Municipal MNN 42650 21325
Medina Medina Municipal 1G5 79685 39842.5 Medina Wadsworth Municipal 3G3 41025 20512.5 Medina Weltzien Skypark 15G 79130 39565 Mercer Lakefield CQA 16212 8106
Miami Hartzell Field I17 10200 5100 Miami Troy Skypark 37I 4264 2132
Miami Waco Field 1WF 0 0 Monroe Monroe County 4G5 3324 1662 Montgomery Brookville Air-Park I62 29359 14679.5 Montgomery James M. Cox Dayton Intl DAY 134524 67262 Montgomery Dayton Wright Brothers MGY 89045 44522.5 Montgomery Moraine Airpark I73 12938 6469 Montgomery Dahio Trotwood I44 1853 926.5 Montgomery Phillipsburg 3I7 68000 34000 Morgan Morgan County I71 5725 2862.5 Morrow Morrow County 4I9 19108 9554 Muskingum Zanesville Municipal ZZV 33312 16656 Muskingum Parr 42I 16150 8075 Noble Noble County - Mike Brienza Field I1Ø 5950 2975
Ottawa Middle Bass-East Point 3W9 1300 650
Ottawa Middle Bass Island 3T7 6500 3250
Ottawa North Bass Island 3X5 1000 500
Ottawa Carl R. Keller Field PCW 20890 10445 Ottawa Put-In-Bay 3W2 15140 7570 Paulding Paulding 2H8 2100 1050 Perry Crooksville I84 400 200 Perry Perry County I86 4550 2275 Pickaway Pickaway County CYO 35450 17725 Pickaway Clarks Dream Strip Ø3I 2770 1385 Pike Pike County EOP 2012 1006 Portage Freedom Air Field 7D6 1623 811.5 Portage Farview 86D 3353 1676.5 Portage Mills 7E3 1050 525 Portage Portage County 29G 9621 4810.5
Putnam Ruhe's R47 13250 6625 Putnam Putnam County OWX 11910 5955 Putnam Ohio Dusting Co. 6C2 2995 1497.5 Richland Mansfield Lahm Regional MFD 57518 28759 Richland Shelby Community 12G 2012 1006 Ross Ross County RZT 50150 25075 Sandusky Fremont 14G 37450 18725 Sandusky Sandusky County Regional S24 6148 3074

### 48 Scioto Greater Portsmouth Regional PMH 45830 22915
Seneca Bandit Field 5D9 140 70 Seneca Fostoria Metropolitan FZI 7900 3950
Seneca Weiker 82D 320 160 Seneca Seneca County 16G 60165 30082.5 Shelby Sidney Municipal I12 20500 10250
Stark Barber 2D1 13750 6875 Stark Miller Airport 4G3 8000 4000 Stark Beach City 2D7 6112 3056
Summit Akron Fulton International AKR 26000 13000 Summit Akron-Canton Regional CAK 120441 60220.5 Summit Mayfield 1D4 450 225 Summit Kent State University 1G3 72500 36250
Trumbull Braceville 41N 425 212.5
Trumbull Warren 62D 14738 7369 Trumbull Youngstown-W arren Regional YNG 98298 49149 Tuscarawas Harry Clever Field PHD 54880 27440 Union Union County MRT 31886 15943 Van Wert Van Wert County VNW 20516 10258 Vinton Vinton County 22I 5225 2612.5 Warren Warren County I68 24951 12475.5 Warren Red Stewart Airfield 4ØI 16800 8400 Wayne Wayne County BJJ 96520 48260 Williams Williams County ØG6 10010 5005 Wood Wood County 1GØ 27405 13702.5
Wood Bordner 3D8 2200 1100 Wood Deshler Municipal 6D7 2000 1000
Wood Metcalf TDZ 90700 45350 Wyandot Wyandot County 56D 7410 3705



### III. Aircraft Models and Number of LTO/yr: Specific aircraft models by airport (generally t he larger airports) is obtained from “Table 7” provided by the United States Departm ent of Transportation, Office of Airline Information. This provided the number of LTO’s for each aircraft model per year per airport.

Table 2. Sample from “Table 7.” This is the all community total ofaircraft models for the Akron/Canton area. “All Service” departure s were used as the number of LTOs per year for that model. Listed in the original table are airc raft model by airport and number of services/LTOs.

### 49 **TOTAL DEPARTURES PERFORMD**
**Aircraft Scheduled Non-Sched All Model Service Service Service** 

A-318 1 1 A319 384 384 BOEING 717-200 3850 3850 BOEING 727-100 1 1 BOEING 727-200 5 5 BOEING 737-100/200 74 74 BOEING 737-200C 3 3 6 BOEING 737-300 2 2 BOEING 737-700/LR 212 212 BOEING 737-800 5 5 BOEING 757-200 4 4 BOEING 767-300/ER 4 4 CANADAIR RJ-100/ER 542 3 545 CANADAIR RJ-700 2881 2881 CONVAIR CV-580 3 3 DASSAULT FALCON 7 7 DHC8-100 DASH 8 2 2 DOUGLAS DC-9-15F 13 13 DOUGLAS DC-9-30 6 6 EMBRAER-145 144 144 RJ-200ER/RJ-440 5519 5519 SAAB-FAIRCHD 340/B 1804 1804 ALL TYPES 15342 130 15472

IV. Emission Factors: Where there was specific aircraft model data the emission factors were derived using the FAA’s Emission Dispersion Modeling System (EDMS). EDMS is a combined emissions and dispersion model for assessing ai r quality at civilian airports and military air bases. The model was developed by the Federal Aviation Administration (FAA) in cooperation with the Unit ed States Air Force (USAF). The model is used to produce an inventory of emissions generated by source s on and around the airport or air base, and to calculate pollutant concentrations in these environments.

### 50 Table 5-2 EDMS Aircraft Emissions Emissions provided by Michigan Department of Environmental Quality. (The few aircraft in Ohio not included in the table had emissions derived by EDMS 5.0 in-house.)

EDMS Aircraft Emissions/LTO by Aircraft Type EDMS 4.5 Emissions Inventory Report of 2005 Aircraft Inventory Emissions Factors

Year 2005 Lbs Emitted Per LTO Aircraft Type CO NOx HC VOC SO2 PM2.5 PM10 A- 318 19.8 18.7 4.0 4.4 1.5 0.0 0.0 A-300-600/R/CF/RCF 27.1 56.4 2.0 2.2 4.0 0.2 0.2 A-300B/C/F-100/200 30.2 52.5 3.5 3.7 3.3 0.2 0.2 A-310-200C/F 32.6 52.5 7.3 7.9 3.3 0.2 0.2 A-319 19.8 18.7 4.0 4.4 1.5 0.0 0.0 A320-100/200 13.7 19.8 1.3 1.3 1.8 0.2 0.2 A-321 16.8 36.8 3.1 3.3 2.2 0.0 0.0 A-330-200 29.8 61.5 0.4 0.4 4.4 0.2 0.2 AVROLINER RJ85 24.7 9.5 2.9 3.3 1.3 0.2 0.2 BAE-146-300 24.7 9.0 3.1 3.3 1.3 0.2 0.2 BEECH 1900 A/B/C 11.0 1.1 3.3 3.5 0.2 0.0 0.0BEECH KINGAIR C90 1.8 0.9 0.2 0.2 0.2 0.0 0.0 717-200 11.7 23.4 0.0 0.0 1.5 0.0 0.0 727-100 21.4 23.1 4.6 5.1 2.9 0.4 0.4 727-100C/QC 44.5 19.8 4.6 5.1 2.4 1.1 1.1 727-200 19.6 27.3 2.9 3.1 3.3 1.1 1.1 737-100/200 14.1 16.1 2.2 2.4 2.0 0.7 0.7 737-200C 13.9 17.4 6.8 7.5 2.0 0.9 0.9 737-300 28.7 15.9 1.8 2.0 1.8 0.0 0.0 737-400 26.5 18.5 1.5 1.5 1.8 0.0 0.0 737-500 24.7 21.2 1.3 1.3 2.0 0.0 0.0 737-700/LR 17.6 20.1 2.0 2.0 1.8 0.4 0.4 737-800 15.7 27.1 1.5 1.8 2.0 0.7 0.7 737-900 15.7 27.1 1.5 1.8 2.0 0.7 0.7 747-100 252.6 108.5 106.7 116.8 7.1 0.4 0.4 747-200/300 60.6 104.7 7.1 7.7 6.8 0.7 0.7 747-400 67.0 105.6 5.7 6.4 7.3 0.7 0.7 757-200 24.7 35.7 2.0 2.2 2.6 0.4 0.4 757-300 27.1 33.1 0.4 0.4 3.1 0.2 0.2 767-200/ER 32.6 52.5 7.3 7.9 3.3 0.2 0.2 767-300/ER 32.0 62.2 2.6 2.9 4.0 0.4 0.4 777 32.8 85.1 5.1 5.7 4.4 0.4 0.4CANADAIR RJ100/ER 16.3 4.9 1.5 1.8 0.7 0.0 0.0 CANADAIR RJ-700 12.6 9.3 0.0 0.0 1.1 0.0 0.0 CESSNA 208 1.1 0.4 0.0 0.0 0.0 0.0 0.0 CONVAIR CV-580 36.2 0.9 8.8 9.5 0.7 0.0 0.0 DASSAULT FALCON 13.7 2.6 2.4 2.6 0.2 0.0 0.0 DHC8-100 DASH 8 5.1 3.1 0.0 0.0 0.4 0.0 0.0 DORNIER 328 JET 1.3 6.6 11.9 12.6 0.7 0.0 0.0 DOUGLAS DC-10-10 102.5 76.7 38.6 42.1 4.2 0.0 0.0 DOUGLAS DC-10-30 45.4 78.7 5.3 5.7 5.1 0.4 0.4

### 51 DOUGLAS DC-10-40 131.8 81.8 30.2 33.1 6.0 0.7 0.7 DOUGLAS DC-8-63 263.5 25.6 219.1 239.9 4.2 5.1 5.1 DOUGLAS DC-8-71 53.6 34.6 3.1 3.3 3.7 0.0 0.0 DOUGLAS DC-8-73 53.6 34.6 3.1 3.3 3.7 0.0 0.0 DOUGLAS DC-9-10 14.1 14.6 3.7 4.0 1.8 0.2 0.2 DOUGLAS DC-9-15F 14.1 14.6 3.7 4.0 1.8 0.2 0.2 DOUGLAS DC-9-30 14.1 14.6 3.7 4.0 1.8 0.2 0.2 DOUGLAS DC-9-40 39.7 16.5 10.8 11.9 2.0 1.3 1.3 DOUGLAS DC-9-50 12.6 20.1 1.8 1.8 2.2 0.9 0.9 EMBRAER-135 12.8 5.5 1.1 1.3 0.7 0.0 0.0 EMBRAER-140 13.7 6.0 1.3 1.3 0.7 0.0 0.0 EMBRAER-145 6.4 6.8 1.1 1.1 0.7 0.0 0.0 EMBRAER-170 9.0 9.7 0.0 0.0 1.1 0.0 0.0 F28-4000/6000 76.7 10.4 77.2 84.4 1.5 0.0 0.0 JETSTREAM 41 4.6 2.0 0.4 0.7 0.2 0.0 0.0 L-101101/100/200 33.3 112.0 6.2 6.8 5.7 1.3 1.3 LEAR-25 75.2 0.7 7.9 8.4 0.2 0.0 0.0 LOCKHEED L100-30 48.7 9.9 19.6 21.4 1.8 0.0 0.0 MD-11 47.8 93.3 4.0 4.4 6.0 0.7 0.7 MD-80, 1, 2, 3, 7, 8 16.3 20.3 0.0 0.0 2.2 0.2 0.2 MD-90 12.1 23.8 0.2 0.2 2.0 0.2 0.2 RJ-200ER/RJ-440 16.3 4.9 1.5 1.8 0.7 0.0 0.0 SAAB-FAIRCHD 340/B 4.2 1.5 1.5 1.5 0.2 0.0 0.0


### NOTE: Where specific aircraft model data was not available fleet emissions were used. EPA default fleet average emissi on factors were taken from “Documentation for Aircraft, Commercial Marine Vessel, ,Locomotive, and Other Non-road Components of the National Emissions Inventory. 2005, s ee Appendix A, Aircraft Emission Estimation Methodology.” Specific model LTOs weresubtracted from county LTO totals to eliminate double counting those LTOs.

Table 5-3 Fleet Emissi on Factor Categories

Fleet emission factors were br oken down into three categories. Itinerant General, Local General, and Military.

Table 5-3aFleet Average Emission Factors for Itinerant General Aircraft.
(Taken from : Table A-5) Pollutant Emission Factors (lbs/LTO) HC 1.234 NOx 0.158 CO 28.13 SOx 0.015 PM10 0.60333

Note: Air taxi HC emissions * VOC/HC ( 0.9914) conversion factor = air taxi VOC estimate

### 52 Table 5-3b Fleet Average Emission Factors for Local General Aircraft.
(Taken From: Table A-11) Pollutant Emission Factors (lbs/LTO) HC 0.394 NOx 0.065 CO 12.014 SOx 0.01 PM10 0.2367

Note: GA HC emissions * VOC/HC( 0.9708) conversion factor = GA VOC estimate

Table 5-3c Fleet Average Emission Fa ctors for Military Aircraft.
(Taken from: Table A-17) Pollutant Emission Factors (lbs/LTO HC 1.234 NOx 0.158 CO 28.13 SOx 0.015 PM10 0.60333

Note: Military HC emissions * VOC/HC( 1.1046) conversion factor = Military VOC estimate

METHODOLOGY

Introduction The following information was considered in the development of emission estimates:

1. Commercial scheduled and non-scheduled ai rcraft air carrieractivity and commercial air freight activityby aircraft model types,

2. General aviation and air taxi annual loca l and itinerant operations for year 2005, 3. Military annual local and iti nerant operations for year 2005. Due to the need to have aircraft operations in formation expressed as landing/take off (LTO) cycles, the following assumptions were made:

1. For commercial aircraft and commercial ai r freight activity, t he number of annual aircraft annual LTO cycles was assu med to be equal to the number of

### 53 departures. The daily LTO cycle frequency was then obtained by dividing the yearly LTO cycles by 365.

2. For general aircraft annual local and iti nerant airport operations, each respective operations total was divided by 2 to obt ain the corresponding year local and itinerant LTO cycles. The expected dailylocal and itinerant LTO cycles then were obtained by dividing these annual totals by 365. 3. For military annual local and itinerant operat ions, each respective operations total was divided by 2 to obtain the correspondi ng year local and itinerant LTO cycles. The expected military daily local and iti nerant LTO cycles then were obtained by dividing these annual totals by 365. Airport LTO cycles were further categoriz ed into commercial aircraft by plane and engine type, general aviation itinerant aircraft of unknown aircraft type, general aviation local aircraft of unknown aircraft type, and military aircraft. This was necessary in order to utilize the U.S. Department of Transportation, Federal Av iation Administration EDMS Emissions and Dispersion Modeling System . Commercial and air freight aircraft emission factors per LTO cycle were det ermined using EDMS for each commercial aircraft type models where possible were used at each towered airport. Default commercial aircraft engine type, and Enviro nmental Protection Agency (EPA) default time in mode values for takeoff, approach, and landing roll times were used in the EDMS model simulations. For those aircraft types that could not be determined using the EDMS emissions model, aircraft emission factors based upon EPA alter native fleet average procedures were then used to estimate their emissions. These included general aviation and air taxi itinerant aircraft of unknown aircraft type, general aviation local aircraft of unknown aircraft type, and military aircraft. Conversion from total hydrocarbons to volatile organic compounds was performed and based upon the EPA guidance

.



### APPROACH

1. A list of more than 90% of the airports was obtained fr om the Ohio Department of Transportation. These were classed by airport, county, aircraft flightclassification, and the total number of op erations per year. 2. The number of operations (a landing ora take off) were then divided by two giving the number of LTOs per year per airport. These airports were combined by county for the total number of LTOs per year, per county. 3. In dialog with ODOT it was determined thatthe following Ohio flight groups of aircraft be combined to match the three categorie s used by the USEPA in calculating emissions.

### 54 Itinerant(General, air carrier, commuter, ai r taxi, general aviation itinerant)

Local (General aviation local) Military(Military)

4. LTOs for specific models of aircraft per airport were ta ken from the FAA Table 7. See Table 2 above. These were then combined to gi ve the number of LTOs per aircraft model per county. Specific model LTOs weresubtracted from county totals to avoid double counting those LTOs.

5. Emission factors were det ermined from the FAA’s EDMS pr ogram for specific aircraft model and engine type. See IV. Emission factors above. The aircraft emission table provided by Michigan has the emission factors for most of the aircraft fl own in Ohio. . Where specific aircraft model data was notavailable USEPA average fleet emissions were used. 6. Emission factors times LTOs by count y yielded tons per y ear per county.

Table 5-4 Pollutant by County (Sample)

County POLLUTANT ACTIVITY(LTOS/YEAR) ACTIVITY(LTOS/DAY) EMISSIONS(TON/YEAR) ADAMS CO 2605 7.136986 24.552325 ADAMS HC 2605 7.136986 0.977285 ADAMS NOX 2605 7.136986 0.136045 ADAMS PM10-PRI 2605 7.136986 0.513114825 ADAMS PM25-PRI 2605 7.136986 0 ADAMS SOX 2605 7.136986 0.0157875 ADAMS VOC 2605 7.136986 0.96314234 ALLEN CO 16250 44.52055 147.945065 ALLEN HC 16250 44.52055 5.841097 ALLEN NOX 16250 44.52055 0.827189 ALLEN PM10-PRI 16250 44.52055 3.081191265 ALLEN PM25-PRI 16250 44.52055 0 ALLEN SOX 16250 44.52055 0.0984575 ALLEN VOC 16250 44.52055 5.769568254 ASHLAND CO 24620 67.45205 173.67794 ASHLAND HC 24620 67.45205 6.19414 ASHLAND NOX 24620 67.45205 0.94895 ASHLAND PM10-PRI 24620 67.45205 3.532515 ASHLAND PM25-PRI 24620 67.45205 0 ASHLAND SOX 24620 67.45205 0.1311 ASHLAND VOC 24620 67.45205 6.07175247 ASHTABULA CO 8863 24.28219 78.115087 ASHTABULA HC 8863 24.28219 3.042551 ASHTABULA NOX 8863 24.28219 0.431593

### 55 ASHTABULA PM10-PRI 8863 24.28219 1.623493455 ASHTABULA PM25-PRI 8863 24.28219 0 ASHTABULA SOX 8863 24.28219 0.0520325 ASHTABULA VOC 8863 24.28219 2.99420213 ATHENS CO 25800 70.68493 196.874985 ATHENS HC 25800 70.68493 7.267183 ATHENS NOX 25800 70.68493 1.081521 ATHENS PM10-PRI 25800 70.68493 4.037266335 ATHENS PM25-PRI 25800 70.68493 0 ATHENS SOX 25800 70.68493 0.1420925 ATHENS VOC 25800 70.68493 7.128180006



### 7. Emissions were then summed by pollut ants in each county by SCC aircraft category type so data could be provided to LADCO in the EPA prescribed NEI – NIF format.

DATA ERROR The first aircraft emission inventory submitt ed to LADCO in April, 2007 contained an error. The inventory submitted in May, 2007has the error corrected. The error was the result of a carry-over function in Access that picked up the number of operations as instead of LTOs....which made the in ventory exactly twice as lar ge as what it really was.

ACCESS CALCULATOR

Introduction: Our database programmer set up Access applic ation to calculate Ohio’s aircraft emission inventory, and export those results to Excel. His utility allows for easy modification of the aircraft data to match futu re data scenarios. Ou tput to Excel also allows for additional datamanipulation and importation.

### 56 Interface:

Through this interface the following sets of data can be edited/updated: Airport activity, emission factors, specific airport emissi ons, state/county FIPS, detailed aircraft information, airport informati on, and aircraft SCCs. Oncethe final emissions have been calculated and summed, then the data can be expo rt via the export function on the Main Menu

.

## APPENDIX C

Mobile Source Emission Inventory (MOVES)

# Mobile Source Emissions Inventory for Huntington-Ironton-Ashland PM 2.5 

# Nonattainment Area

Includes Cabell County, Wayne County, and a portion of Mason County in West Virginia, Lawrence County, Scioto County, a portion of Adams County, and a portion of Gallia County in Ohio, and

Boyd County and a portion of Lawrence County in Kentucky Emission estimates for the Year 2005, 2008, 2015, and 2022 developed in support of the PM2.5

### State Implementation Plan

April 2011

Prepared for the West Virginia Department of Environmental Protection, the Ohio Environmental

Protection Agency, and the Kentucky Division for Air Quality by

KYOVA Interstate Planning Commission

### Acknowledgments

Title Mobile Source Emissions Inventory for Huntington-Ironton-Ashland PM2.5



### Nonattainment Area

Abstract This report was prepared for the West Virginia Department of Environmental

Protection, the Ohio Environmental Protection Agency, and the Kentucky Division for Air Quality. The nonattainment area includes Cabell County, Wayne County, and a portion of Mason County in West Virginia, Lawrence County, Scioto County, a portion of Adams County, and a portion of Gallia County in Ohio, and Boyd County and a portion of Lawrence County in Kentucky. This report includes emission estimates for the years 2005, 2008, 2015, and 2022 was generated to support the attainment SIPs for the annual PM2.5

### standard. EPA’s Motor Vehicle Emission Simulation (MOVES) 2010a was used to generate the emission rates.

Date April 2011 Agency KYOVA Interstate Planning Commission

Michele Craig, Executive Director Saleem Salameh, Technical Study Director Project Consultant

Kimley-Horn and Associates, Inc.

Allison Fluitt Jennifer Hunter

This project is receiving funding support from the following agencies: Cabell County, City of Huntington, City of Ironton, Federal Highway Administration, Federal Transit Administration, Huntington Chamber of Commerce, Lawrence County, Lawrence County Public Transit System, Ohio Department of Transportation, Tri-State Airport Authority, Tri-State Transit Authority, Wayne County, and West Virginia Department of Transportation. The contents of this document reflect the view of KYOVA Interstate Planning Commission which is responsible for the facts and accuracy of the data presented herein. The contents do not necessarily reflect the official views or policies of the affiliated agencies listed above. This document does not constitute a standard, specification, or regulation.Mobile Source Emissions Inventory for the Page 1

Huntington-Ironton-Ashland PM 2.5Nonattainment Area

# Mobile Source Emissions Inventory for the HuntingtonIronton-Ashland PM 2.5 

# Nonattainment Area

This report was prepared for the Ohio Environmental Protection Agency (Ohio EPA), the West Virginia Department of Environmental Protection (WVDEP), and the Kentucky Division for Air Quality (KDAQ) to support the attainment State Implementation Plans (SIPs) for the annual PM2.5 

### standard. The Huntington-Ironton-Ashland PM 2.5

### nonattainment area for the on-road emission estimation analysis is divided into a modeled area composed of Cabell, Wayne, and Mason (partial) Counties in West Virginia, Lawrence, Scioto, Adams (partial), and Gallia (partial) Counties in Ohio, and Boyd and Lawrence (partial) Counties in Kentucky. This document includes emissions estimates for the years 2005, 2008, 2015, and 2022. The United States Environmental Protection Agency’s (US EPA) Motor Vehicle Emissions Simulator (MOVES) 2010a model was used to generate the emission rates. The MOVES model replaced MOBILE6.2 as the official emissions modeling software of the EPA in December 2009. For the purposes of this analysis, MOVES emission rates were generated for direct PM 2.5 

### , PM 2.5

### tirewear, PM 2.5 

### brakewear, NO
x

### and SO 2 

### . The KYOVA Interstate Planning Commission is the Metropolitan Planning Organization (MPO) responsible for the long range planning and air quality conformity for the Huntington, WV and Ironton, OH region. The Ashland MPO is responsible for these activities for the Ashland, KY area. The transportation conformity process was established to ensure a region’s transportation activities and associated federal funding are consistent with the air quality goals set forth in the SIPs for the three states in this region. The SIPs include an inventory of projected emissions from vehicles. One or more of the analysis years in the projected inventory may be designated as the motor vehicle emissions budget (MVEB). This budget establishes a maximum allowable limit on future emissions from vehicles (mobile sources). The transportation plans and programs for the region (in this case, KYOVA and the Ashland MPO) must be in conformance with all the provisions in the SIP. The conformity process is a quantitative analysis which uses the MOVES software developed by the US EPA. The objective is to demonstrate that forecasted regional vehicle emissions do not exceed the established budget. Tables 1a through 1cshow the daily and annual mobile source emissions for the West Virginia, Ohio, and Kentucky portions of the Huntington-Ironton-Ashland nonattainment areas. Separate MVEB’s are typically designated for these areas. An extensive interagency consultation process was initiated to gain feedback and consensus from agencies including the KYOVA Interstate Planning Commission (KYOVA), WVDEP, Ohio EPA, KDAQ, Ohio Department of Transportation (ODOT), West Virginia Department of Transportation (WVDOT), Kentucky Transportation Cabinet (KYTC), Federal Highway Administration (FHWA), Federal Transit Administration (FTA), and US EPA. Assumptions and methodology used in this analysis are documented in the Appendix of this report. For the development of the associated SIPs, it is recommended an additional safety margin be added to the motor vehicle emissions budget (MVEB) to account for any uncertainty with assumptions used in the development of this analysis. Daily and annual mobile source emissions for each county in the nonattainment area are shown in Tables 2a through 2i

.Mobile Source Emissions Inventory for the Page 2

Huntington-Ironton-Ashland PM 2.5Nonattainment Area 

### Table 1a. Mobile Source Emissions for the Huntington-Ironton-Ashland PM2.5 

### Nonattainment Area, West Virginia Portion (tons)

West Virginia Area (Cabell, Wayne, and Mason (Partial) Counties)

2005 Vehicle Population: 100,782 Daily VMT: 3,965,990 Annual VMT: 1,356,293,075 17.55 6,013.60 0.3347 114.54 0.6677 228.60 0.0381 13.04 0.0112 3.84

2008 Vehicle Population: 103,240 Daily VMT: 4,092,426 Annual VMT: 1,403,016,167 14.45 4,964.74 0.0907 31.12 0.5768 197.97 0.0394 13.51 0.0116 3.97

2015 Vehicle Population: 108,975 Daily VMT: 4,361,792 Annual VMT: 1,491,649,487 6.98 2,394.60 0.0386 13.22 0.2749 94.16 0.0420 14.36 0.0124 4.23

2022 Vehicle Population: 114,711 Daily VMT: 4,923,274 Annual VMT: 1,683,665,856 3.62 1,243.28 0.0393 13.46 0.1251 42.87 0.0474 16.19 0.0139 4.77 Primary PM 2.5- Brakewear Particulate Primary PM 2.5- Tirewear Particulate Primary Exhaust PM 2.5- Total Oxides of Nitrogen (NO x ) Sulfur Dioxide (SO 2 ) Primary PM 2.5- Brakewear Particulate Primary PM 2.5- Tirewear Particulate Primary Exhaust PM 2.5- Total

Primary Exhaust PM 2.5- Total Oxides of Nitrogen (NO x ) Sulfur Dioxide (SO 2 ) Primary PM 2.5- Brakewear Particulate Primary PM 2.5- Tirewear Particulate

Oxides of Nitrogen (NO x ) Sulfur Dioxide (SO 2 )

Primary PM 2.5- Brakewear Particulate Primary PM 2.5- Tirewear Particulate Daily Emissions (tons) Annual Emissions (tons)

Pollutant Name

Oxides of Nitrogen (NO x ) Sulfur Dioxide (SO 2 ) Primary Exhaust PM 2.5- TotalMobile Source Emissions Inventory for the Page 3

Huntington-Ironton-Ashland PM 2.5Nonattainment Area 

### Table 1b. Mobile Source Emissions for the Huntington-Ironton-Ashland PM 2.5 

### Nonattainment Area, Ohio Portion (tons)

Ohio Area (Lawrence, Scioto, Adams (Partial), and Gallia (Partial) Counties)

2005 Vehicle Population: 164,363 Daily VMT: 3,079,755 Annual VMT: 1,053,217,320 11.52 3,955.84 0.1920 65.73 0.3575 122.67 0.0241 8.24 0.0080 2.73

2008 Vehicle Population: 168,407 Daily VMT: 3,166,879 Annual VMT: 1,085,708,635 9.64 3,319.55 0.0633 21.73 0.3037 104.44 0.0248 8.50 0.0082 2.82

2015 Vehicle Population: 177,836 Daily VMT: 3,557,112 Annual VMT: 1,216,464,596 5.30 1,824.63 0.0292 10.01 0.1651 56.65 0.0279 9.53 0.0092 3.16

2022 Vehicle Population: 187,269 Daily VMT: 4,059,935 Annual VMT: 1,388,420,261 2.68 924.08 0.0304 10.42 0.0939 32.25 0.0318 10.86 0.0105 3.61 Primary PM 2.5- Tirewear Particulate Primary PM 2.5- Brakewear Particulate Sulfur Dioxide (SO 2 ) Primary Exhaust PM 2.5- Total Primary PM 2.5- Tirewear Particulate

Oxides of Nitrogen (NO x ) Primary PM 2.5- Brakewear Particulate Sulfur Dioxide (SO 2 ) Primary Exhaust PM 2.5- Total Primary PM 2.5- Tirewear Particulate

Oxides of Nitrogen (NO x ) Primary PM 2.5- Brakewear Particulate Sulfur Dioxide (SO 2 ) Primary Exhaust PM 2.5- Total Primary PM 2.5- Tirewear Particulate

Oxides of Nitrogen (NO x ) Primary PM 2.5- Brakewear Particulate Sulfur Dioxide (SO 2 ) Primary Exhaust PM 2.5- Total

Pollutant Name Daily Emissions (tons) Annual Emissions (tons)

Oxides of Nitrogen (NO x )Mobile Source Emissions Inventory for the Page 4

Huntington-Ironton-Ashland PM 2.5Nonattainment Area 

### Table 1c. Mobile Source Emissions for the Huntington-Ironton-Ashland PM 2.5 

### Nonattainment Area, Kentucky Portion (tons)

Kentucky Area (Boyd and Lawrence (Partial) Counties)

2005 Vehicle Population: 52,269 Daily VMT: 1,520,525 Annual VMT: 519,990,431 8.30 2,843.94 0.0370 12.65 0.3338 114.31 0.0168 5.76 0.0045 1.55

2008 Vehicle Population: 53,576 Daily VMT: 1,469,006 Annual VMT: 503,622,799 6.73 2,311.75 0.0360 12.36 0.2827 97.03 0.0165 5.65 0.0044 1.51

2015 Vehicle Population: 56,625 Daily VMT: 1,585,233 Annual VMT: 542,119,590 3.57 1,225.13 0.0368 12.61 0.1359 46.54 0.0179 6.11 0.0048 1.63

2022 Vehicle Population: 59,674 Daily VMT: 1,735,819 Annual VMT: 593,617,125 1.99 685.60 0.0375 12.83 0.0647 22.18 0.0199 6.81 0.0053 1.80 Primary PM 2.5- Tirewear Particulate Primary PM 2.5- Brakewear Particulate Sulfur Dioxide (SO 2 ) Primary Exhaust PM 2.5- Total Primary PM 2.5- Tirewear Particulate

Oxides of Nitrogen (NO x ) Primary PM 2.5- Brakewear Particulate Sulfur Dioxide (SO 2 ) Primary Exhaust PM 2.5- Total Primary PM 2.5- Tirewear Particulate

Oxides of Nitrogen (NO x ) Primary PM 2.5- Brakewear Particulate Sulfur Dioxide (SO 2 ) Primary Exhaust PM 2.5- Total Primary PM 2.5- Tirewear Particulate

Oxides of Nitrogen (NO x ) Primary PM 2.5- Brakewear Particulate Annual Emissions (tons)

Oxides of Nitrogen (NO x ) Sulfur Dioxide (SO 2 ) Primary Exhaust PM 2.5- Total

Pollutant Name Daily Emissions (tons)Mobile Source Emissions Inventory for the Page 5

Huntington-Ironton-Ashland PM 2.5Nonattainment Area 

### Table 2a. Mobile Source Emissions by County for the Huntington-Ironton-Ashland PM 2.5 

### Nonattainment Area, Cabell County, WV (tons)

Cabell County, WV

2005 Vehicle Population: 73,091 Daily VMT: 2,808,750 Annual VMT: 960,538,915 12.44 4,262.48 0.2371 81.13 0.4731 161.97 0.0270 9.23 0.0079 2.72

2008 Vehicle Population: 74,874 Daily VMT: 2,885,502 Annual VMT: 989,243,546 10.20 3,504.59 0.0640 21.95 0.4069 139.66 0.0278 9.52 0.0082 2.80

2015 Vehicle Population: 79,033 Daily VMT: 3,096,762 Annual VMT: 1,059,033,672 4.96 1,702.34 0.0274 9.39 0.1953 66.88 0.0298 10.19 0.0088 3.00

2022 Vehicle Population: 83,193 Daily VMT: 3,336,065 Annual VMT: 1,140,870,563 2.46 847.76 0.0267 9.13 0.0850 29.12 0.0321 10.97 0.0094 3.23 Primary PM 2.5- Brakewear Particulate Primary PM 2.5- Tirewear Particulate Primary Exhaust PM 2.5- Total Oxides of Nitrogen (NO x ) Sulfur Dioxide (SO 2 ) Primary PM 2.5- Brakewear Particulate Primary PM 2.5- Tirewear Particulate Primary Exhaust PM 2.5- Total Oxides of Nitrogen (NO x ) Sulfur Dioxide (SO 2 ) Primary PM 2.5- Brakewear Particulate Primary PM 2.5- Tirewear Particulate Primary Exhaust PM 2.5- Total Oxides of Nitrogen (NO x ) Sulfur Dioxide (SO 2 ) Primary PM 2.5- Brakewear Particulate Primary PM 2.5- Tirewear Particulate Primary Exhaust PM 2.5- Total Oxides of Nitrogen (NO x ) Sulfur Dioxide (SO 2 ) Daily Emissions (tons) Annual Emissions (tons)

Pollutant NameMobile Source Emissions Inventory for the Page 6

Huntington-Ironton-Ashland PM 2.5Nonattainment Area 

### Table 2b. Mobile Source Emissions by County for the Huntington-Ironton-Ashland PM2.5 

### Nonattainment Area, Wayne County, WV (tons)

Wayne County, WV

2005 Vehicle Population: 25,446 Daily VMT: 1,139,180 Annual VMT: 389,577,827 5.02 1,720.01 0.0961 32.87 0.1914 65.52 0.0109 3.74 0.0032 1.10

2008 Vehicle Population: 26,067 Daily VMT: 1,187,259 Annual VMT: 407,030,689 4.17 1,432.79 0.0263 9.02 0.1670 57.30 0.0114 3.92 0.0034 1.15

2015 Vehicle Population: 27,515 Daily VMT: 1,241,619 Annual VMT: 424,609,965 1.97 676.93 0.0110 3.76 0.0781 26.74 0.0120 4.09 0.0035 1.20

2022 Vehicle Population: 28,963 Daily VMT: 1,560,054 Annual VMT: 533,508,781 1.13 386.80 0.0124 4.26 0.0394 13.49 0.0150 5.13 0.0044 1.51 Primary PM 2.5- Tirewear Particulate Primary PM 2.5- Brakewear Particulate Sulfur Dioxide (SO 2 ) Primary Exhaust PM 2.5- Total Primary PM 2.5- Tirewear Particulate

Oxides of Nitrogen (NO x ) Primary PM 2.5- Brakewear Particulate Sulfur Dioxide (SO 2 ) Primary Exhaust PM 2.5- Total Primary PM 2.5- Tirewear Particulate

Oxides of Nitrogen (NO x ) Primary PM 2.5- Brakewear Particulate Sulfur Dioxide (SO 2 ) Primary Exhaust PM 2.5- Total Primary PM 2.5- Tirewear Particulate

Oxides of Nitrogen (NO x ) Primary PM 2.5- Brakewear Particulate Sulfur Dioxide (SO 2 ) Primary Exhaust PM 2.5- Total

Pollutant Name Daily Emissions (tons) Annual Emissions (tons)

Oxides of Nitrogen (NO x )Mobile Source Emissions Inventory for the Page 7

Huntington-Ironton-Ashland PM 2.5Nonattainment Area 

### Table 2c. Mobile Source Emissions by County for the Huntington-Ironton-Ashland PM 2.5 

### Nonattainment Area, Nonattainment Portion of Mason County, WV (tons)

Mason County (Partial), WV

2005 Vehicle Population: 2,244 Daily VMT: 18,060 Annual VMT: 6,176,333 0.09 31.12 0.0016 0.54 0.0032 1.11 0.0002 0.06 0.0001 0.02

2008 Vehicle Population: 2,299 Daily VMT: 19,665 Annual VMT: 6,741,932 0.08 27.36 0.0005 0.16 0.0029 1.01 0.0002 0.06 0.0001 0.02

2015 Vehicle Population: 2,427 Daily VMT: 23,410 Annual VMT: 8,005,850 0.04 15.33 0.0002 0.07 0.0016 0.54 0.0002 0.08 0.0001 0.02

2022 Vehicle Population: 2,555 Daily VMT: 27,155 Annual VMT: 9,286,512 0.03 8.72 0.0002 0.08 0.0008 0.26 0.0003 0.09 0.0001 0.03 Primary PM 2.5- Brakewear Particulate Primary PM 2.5- Tirewear Particulate Primary Exhaust PM 2.5- Total Oxides of Nitrogen (NO x ) Sulfur Dioxide (SO 2 ) Primary PM 2.5- Brakewear Particulate Primary PM 2.5- Tirewear Particulate Primary Exhaust PM 2.5- Total Oxides of Nitrogen (NO x ) Sulfur Dioxide (SO 2 ) Primary PM 2.5- Brakewear Particulate Primary PM 2.5- Tirewear Particulate Primary Exhaust PM 2.5- Total Oxides of Nitrogen (NO x ) Sulfur Dioxide (SO 2 ) Primary PM 2.5- Brakewear Particulate Primary PM 2.5- Tirewear Particulate Primary Exhaust PM 2.5- Total Oxides of Nitrogen (NO x ) Sulfur Dioxide (SO 2 )

Pollutant Name Daily Emissions (tons) Annual Emissions (tons)Mobile Source Emissions Inventory for the Page 8

Huntington-Ironton-Ashland PM 2.5Nonattainment Area 

### Table 2d. Mobile Source Emissions by County for the Huntington-Ironton-Ashland PM2.5 

### Nonattainment Area, Lawrence County, OH (tons)

Lawrence County, OH

2005 Vehicle Population: 72,392 Daily VMT: 1,315,020 Annual VMT: 449,711,752 4.93 1,692.81 0.0820 28.08 0.1529 52.46 0.0103 3.52 0.0034 1.17

2008 Vehicle Population: 74,172 Daily VMT: 1,334,081 Annual VMT: 457,366,121 4.07 1,403.49 0.0267 9.16 0.1282 44.10 0.0104 3.58 0.0035 1.19

2015 Vehicle Population: 78,325 Daily VMT: 1,470,988 Annual VMT: 503,049,909 2.21 759.82 0.0121 4.14 0.0685 23.51 0.0115 3.94 0.0038 1.31

2022 Vehicle Population: 82,480 Daily VMT: 1,742,638 Annual VMT: 595,949,049 1.15 397.98 0.0131 4.48 0.0404 13.87 0.0136 4.66 0.0045 1.55 Primary PM 2.5- Brakewear Particulate Primary PM 2.5- Tirewear Particulate Primary Exhaust PM 2.5- Total Oxides of Nitrogen (NO x ) Sulfur Dioxide (SO 2 ) Primary PM 2.5- Brakewear Particulate Primary PM 2.5- Tirewear Particulate Primary Exhaust PM 2.5- Total Oxides of Nitrogen (NO x ) Sulfur Dioxide (SO 2 ) Primary PM 2.5- Brakewear Particulate Primary PM 2.5- Tirewear Particulate Primary Exhaust PM 2.5- Total Oxides of Nitrogen (NO x ) Sulfur Dioxide (SO 2 ) Primary PM 2.5- Brakewear Particulate Primary PM 2.5- Tirewear Particulate Primary Exhaust PM 2.5- Total Oxides of Nitrogen (NO x ) Sulfur Dioxide (SO 2 )

Pollutant Name Daily Emissions (tons) Annual Emissions (tons)Mobile Source Emissions Inventory for the Page 9

Huntington-Ironton-Ashland PM 2.5Nonattainment Area 

### Table 2e. Mobile Source Emissions by County for the Huntington-Ironton-Ashland PM 2.5 

### Nonattainment Area, Scioto County, OH (tons)

Scioto County, OH

2005 Vehicle Population: 88,852 Daily VMT: 1,616,940 Annual VMT: 552,962,632 6.06 2,081.20 0.1009 34.53 0.1880 64.50 0.0126 4.33 0.0042 1.43

2008 Vehicle Population: 91,039 Daily VMT: 1,678,238 Annual VMT: 575,354,151 5.11 1,761.97 0.0336 11.52 0.1611 55.40 0.0131 4.51 0.0044 1.49

2015 Vehicle Population: 96,136 Daily VMT: 1,915,776 Annual VMT: 655,158,989 2.86 983.09 0.0157 5.39 0.0889 30.52 0.0150 5.13 0.0050 1.70

2022 Vehicle Population: 101,235 Daily VMT: 2,131,162 Annual VMT: 728,816,580 1.41 486.95 0.0160 5.47 0.0494 16.97 0.0167 5.70 0.0055 1.89 Primary PM 2.5- Tirewear Particulate Primary PM 2.5- Brakewear Particulate Sulfur Dioxide (SO 2 ) Primary Exhaust PM 2.5- Total Primary PM 2.5- Tirewear Particulate

Oxides of Nitrogen (NO x ) Primary PM 2.5- Brakewear Particulate Sulfur Dioxide (SO 2 ) Primary Exhaust PM 2.5- Total Primary PM 2.5- Tirewear Particulate

Oxides of Nitrogen (NO x ) Primary PM 2.5- Brakewear Particulate Sulfur Dioxide (SO 2 ) Primary Exhaust PM 2.5- Total Primary PM 2.5- Tirewear Particulate

Oxides of Nitrogen (NO x ) Primary PM 2.5- Brakewear Particulate Sulfur Dioxide (SO 2 ) Primary Exhaust PM 2.5- Total

Pollutant Name Daily Emissions (tons) Annual Emissions (tons)

Oxides of Nitrogen (NO x )Mobile Source Emissions Inventory for the Page 10

Huntington-Ironton-Ashland PM 2.5Nonattainment Area 

### Table 2f. Mobile Source Emissions by County for the Huntington-Ironton-Ashland PM 2.5 

### Nonattainment Area, Nonattainment Portion of Adams County, OH (tons)

Adams County, OH (Partial)

2005 Vehicle Population: 2,098 Daily VMT: 99,565 Annual VMT: 34,049,176 0.36 122.49 0.0061 2.10 0.0112 3.84 0.0008 0.27 0.0003 0.09

2008 Vehicle Population: 2,150 Daily VMT: 103,978 Annual VMT: 35,647,156 0.30 103.66 0.0021 0.71 0.0097 3.32 0.0008 0.28 0.0003 0.09

2015 Vehicle Population: 2,270 Daily VMT: 114,277 Annual VMT: 39,080,671 0.16 54.82 0.0009 0.32 0.0051 1.76 0.0009 0.31 0.0003 0.10

2022 Vehicle Population: 2,391 Daily VMT: 124,576 Annual VMT: 42,602,717 0.08 26.21 0.0009 0.32 0.0028 0.95 0.0010 0.33 0.0003 0.11 Primary PM 2.5- Brakewear Particulate Primary PM 2.5- Tirewear Particulate Primary Exhaust PM 2.5- Total Oxides of Nitrogen (NO x ) Sulfur Dioxide (SO 2 ) Primary PM 2.5- Brakewear Particulate Primary PM 2.5- Tirewear Particulate Primary Exhaust PM 2.5- Total Oxides of Nitrogen (NO x ) Sulfur Dioxide (SO 2 ) Primary PM 2.5- Brakewear Particulate Primary PM 2.5- Tirewear Particulate Primary Exhaust PM 2.5- Total Oxides of Nitrogen (NO x ) Sulfur Dioxide (SO 2 ) Primary PM 2.5- Brakewear Particulate Primary PM 2.5- Tirewear Particulate Primary Exhaust PM 2.5- Total Oxides of Nitrogen (NO x ) Sulfur Dioxide (SO 2 )

Pollutant Name Daily Emissions (tons) Annual Emissions (tons)Mobile Source Emissions Inventory for the Page 11

Huntington-Ironton-Ashland PM 2.5Nonattainment Area 

### Table 2g. Mobile Source Emissions by County for the Huntington-Ironton-Ashland PM2.5 

### Nonattainment Area, Nonattainment Portion of Gallia County, OH (tons)

Gallia County, OH (Partial)

2005 Vehicle Population: 1,021 Daily VMT: 48,230 Annual VMT: 16,493,759 0.17 59.34 0.0030 1.02 0.0054 1.86 0.0004 0.13 0.0001 0.04

2008 Vehicle Population: 1,046 Daily VMT: 50,582 Annual VMT: 17,341,207 0.15 50.43 0.0010 0.34 0.0047 1.62 0.0004 0.14 0.0001 0.05

2015 Vehicle Population: 1,105 Daily VMT: 56,070 Annual VMT: 19,175,027 0.08 26.89 0.0005 0.16 0.0025 0.86 0.0004 0.15 0.0001 0.05

2022 Vehicle Population: 1,163 Daily VMT: 61,559 Annual VMT: 21,051,915 0.04 12.94 0.0005 0.16 0.0014 0.47 0.0005 0.16 0.0002 0.05 Primary PM 2.5- Tirewear Particulate Primary PM 2.5- Brakewear Particulate Sulfur Dioxide (SO 2 ) Primary Exhaust PM 2.5- Total Primary PM 2.5- Tirewear Particulate

Oxides of Nitrogen (NO x ) Primary PM 2.5- Brakewear Particulate Sulfur Dioxide (SO 2 ) Primary Exhaust PM 2.5- Total Primary PM 2.5- Tirewear Particulate

Oxides of Nitrogen (NO x ) Primary PM 2.5- Brakewear Particulate Sulfur Dioxide (SO 2 ) Primary Exhaust PM 2.5- Total Primary PM 2.5- Tirewear Particulate

Oxides of Nitrogen (NO x ) Primary PM 2.5- Brakewear Particulate Sulfur Dioxide (SO 2 ) Primary Exhaust PM 2.5- Total

Pollutant Name Daily Emissions (tons) Annual Emissions (tons)

Oxides of Nitrogen (NO x )Mobile Source Emissions Inventory for the Page 12

Huntington-Ironton-Ashland PM 2.5Nonattainment Area 

### Table 2h. Mobile Source Emissions by County for the Huntington-Ironton-Ashland PM2.5 

### Nonattainment Area, Boyd County, KY (tons)

Boyd County, KY

2005 Vehicle Population: 49,199 Daily VMT: 1,429,198 Annual VMT: 488,758,339 7.80 2,673.25 0.0347 11.89 0.3138 107.44 0.0158 5.41 0.0043 1.46

2008 Vehicle Population: 50,429 Daily VMT: 1,380,484 Annual VMT: 473,274,668 6.32 2,172.59 0.0339 11.62 0.2657 91.18 0.0155 5.31 0.0041 1.42

2015 Vehicle Population: 53,299 Daily VMT: 1,494,083 Annual VMT: 510,947,840 3.36 1,154.59 0.0347 11.89 0.1281 43.86 0.0168 5.76 0.0045 1.54

2022 Vehicle Population: 56,169 Daily VMT: 1,640,241 Annual VMT: 560,930,984 1.88 647.64 0.0354 12.12 0.0611 20.95 0.0188 6.43 0.0050 1.70 Primary PM 2.5- Brakewear Particulate Primary PM 2.5- Tirewear Particulate Primary Exhaust PM 2.5- Total Oxides of Nitrogen (NO x ) Sulfur Dioxide (SO 2 ) Primary PM 2.5- Brakewear Particulate Primary PM 2.5- Tirewear Particulate Primary Exhaust PM 2.5- Total Oxides of Nitrogen (NO x ) Sulfur Dioxide (SO 2 ) Primary PM 2.5- Brakewear Particulate Primary PM 2.5- Tirewear Particulate Primary Exhaust PM 2.5- Total Oxides of Nitrogen (NO x ) Sulfur Dioxide (SO 2 ) Primary PM 2.5- Brakewear Particulate Primary PM 2.5- Tirewear Particulate Primary Exhaust PM 2.5- Total Oxides of Nitrogen (NO x ) Sulfur Dioxide (SO 2 )

Pollutant Name Daily Emissions (tons) Annual Emissions (tons)Mobile Source Emissions Inventory for the Page 13

Huntington-Ironton-Ashland PM 2.5Nonattainment Area 

### Table 2i. Mobile Source Emissions by County for the Huntington-Ironton-Ashland PM2.5 

### Nonattainment Area, Nonattainment Portion of Lawrence County, KY (tons)

Lawrence County, KY (Partial)

2005 Vehicle Population: 3,070 Daily VMT: 91,327 Annual VMT: 31,232,092 0.50 170.69 0.0022 0.76 0.0200 6.86 0.0010 0.35 0.0003 0.09

2008 Vehicle Population: 3,147 Daily VMT: 88,522 Annual VMT: 30,348,132 0.40 139.16 0.0022 0.74 0.0170 5.84 0.0010 0.34 0.0003 0.09

2015 Vehicle Population: 3,326 Daily VMT: 91,151 Annual VMT: 31,171,751 0.21 70.54 0.0021 0.73 0.0078 2.68 0.0010 0.35 0.0003 0.09

2022 Vehicle Population: 3,505 Daily VMT: 95,579 Annual VMT: 32,686,140 0.11 37.96 0.0021 0.71 0.0036 1.22 0.0011 0.37 0.0003 0.10 Primary PM 2.5- Brakewear Particulate Primary PM 2.5- Tirewear Particulate Primary Exhaust PM 2.5- Total Oxides of Nitrogen (NO x ) Sulfur Dioxide (SO 2 ) Primary PM 2.5- Brakewear Particulate Primary PM 2.5- Tirewear Particulate Primary Exhaust PM 2.5- Total Oxides of Nitrogen (NO x ) Sulfur Dioxide (SO 2 ) Primary PM 2.5- Brakewear Particulate Primary PM 2.5- Tirewear Particulate Primary Exhaust PM 2.5- Total Oxides of Nitrogen (NO x ) Sulfur Dioxide (SO 2 ) Primary PM 2.5- Brakewear Particulate Primary PM 2.5- Tirewear Particulate Primary Exhaust PM 2.5- Total Oxides of Nitrogen (NO x ) Sulfur Dioxide (SO 2 )

Pollutant Name Daily Emissions (tons) Annual Emissions (tons)Mobile Source Emissions Inventory for the Page 14

Huntington-Ironton-Ashland PM 2.5Nonattainment Area 

### Background US EPA published a Federal Register notice 1 

### of availability on March 2, 2010, to approve MOVES2010 (Motor Vehicle Emissions Simulator), hereafter referred to as MOVES. Upon publication of the Federal Register notice, MOVES became U.S. EPA’s approved motor vehicle emission factor model for estimating VOCs, NO
x 

### , CO, PM 10

### and PM2.5 

### and other pollutants and precursors from cars, trucks, motorcycles, and buses by state and local agencies. MOVES is a computer program designed by the US EPA to estimate air pollution emissions from mobile sources. MOVES replaces US EPA’s previous emissions model for on-road mobile sources, MOBILE6.2. MOVES can be used to estimate exhaust and evaporative emissions as well as brake and tire wear emissions from all types of on-road vehicles. An updated version of this software, MOVES2010a, was used for the purposes of this analysis. MOVES2010a is a minor update to MOVES2010. MOVES2010a includes general performance improvements from MOVES2010, and also allows users to account for emissions under new car and light truck energy and greenhouse gas standards. The Clean Air Act (CAA) requires US EPA to regularly update its mobile source emission models. US EPA continuously collects data and measures vehicle emissions to make sure the Agency has the best possible understanding of mobile source emissions. This assessment, in turn, informs the development of US EPA’s mobile source emission models. MOVES represents the Agency’s most up-to-date assessment of on-road mobile source emissions. MOVES also incorporates several changes to the US EPA’s approach to mobile source emission modeling based upon recommendations made to the Agency by the National Academy of Sciences. US EPA believes that MOVES should be used in ozone, CO, PM, and nitrogen dioxide State Implementation Plan (SIP) development as expeditiously as possible. The CAA requires that SIP inventories and control measures be based on the most current information and applicable models that are available when a SIP is developed. On March 2, 2010, US EPA and US DOT established a two-year grace period before MOVES is required for new transportation conformity analyses. As a result, MOVES will be the required analysis platform for all conformity analyses after March 2, 2012. The more detailed MOVES approach to modeling (when compared with the previous MOBILE model) allows US EPA to easily incorporate large amounts of in-use data from a wide variety of sources, such as data from vehicle inspection and maintenance (I/M) programs, remote sensing device (RSD) testing, certification testing, portable emission measurement systems (PEMS), etc. This approach also allows users to incorporate a variety of activity data to better estimate emission differences such as those resulting from changes to vehicle speed and acceleration patterns. MOVES has a graphical user interface which allows users to more easily set up and run the model. MOVES database-centered design provides users much greater flexibility regarding output choices. Unlike earlier models which provided emission factors in grams-per-mile in fixed output formats, MOVES output can be expressed as total mass (in tons, pounds, kilograms, or grams) or as emission factors (grams-per-mile and in some cases grams-per-vehicle). Output can be easily aggregated or disaggregated to examine emissions in a range of scales, from national emissions impacts down to the emissions impacts of individual transportation projects. The database-centered design also allows

1 http://www.regulations.gov/search/Regs/home.html#documentDetail?R=0900006480ab1f98Mobile Source Emissions Inventory for the Page 15

Huntington-Ironton-Ashland PM 2.5Nonattainment Area 

### US EPA to update emissions data incorporated in MOVES more easily and will allow users to incorporate a much wider array of activity data to improve estimation of local emissions. For example, the improvements in MOVES will allow project-level PM2.5

### emissions to be estimated.

Mobile Source Emission Forecast Process The emissions inventory development and emissions projection discussion below identifies procedures used by the KYOVA Interstate Planning Commission regarding emissions of all the counties in the Huntington-Ironton-Ashland nonattainment area. All of these inventories and emissions projections were prepared using similar methodologies. Mobile emissions inventories and projections for all counties were prepared by Kimley-Horn and Associates on behalf of the KYOVA Interstate Planning Commission, with data provided by KYOVA, ODOT, Ohio EPA, WVDOT, WVDEP, KYTC, and KDAQ. Cabell County, WV, Wayne County, WV, and Lawrence County, OH are represented within the KYOVA Travel Demand Model. Boyd County, KY is represented by the KYTC’s Ashland Regional Travel Demand Model. For these areas, information from the travel demand models combined with Highway Performance Monitoring Systems (HPMS) county-level data from each respective area were used in the emissions analysis. For the full or partial counties not included within the available travel demand models, HPMS data was relied upon more heavily for the travel characteristics. The Appendixof this report provides a full description of the data sources and analysis procedures used in this analysis effort.

Table 3 summarizes the settings used in the MOVES run specification file. Table 4lists the assumptions used in the MOVES County Data Manager. Further details on the use of MOVES are found in the Appendix

. Table 3. MOVES Runspec Parameters MOVES Runspec Parameter Settings MOVES2010a, Version 2010/08/26 Scale County, Emission Rates Time Span Time aggregation = Hour 1 month representing average annual temperatures (April) All hours of the day selected Weekdays only Geographic Bounds 3 custom domai ns

– 3 West Virginia counties, 4 Ohio counties, 2 Kentucky counties Vehicles/Equipment All valid source types, gasoline and diesel Road Type All road types including off

- network Pollutants and Processes NO x , all PM2.5 categories, SO 2 , total energy consu mption Strategies Modified AVFT strategy reflecting 0% CNG buses in the transit fleet General Output Units = grams, joules, miles Output Emissions Time = hour, location = link, on

- road emission rates by road type and source use type Advanced Performanc e NoneMobile Source Emissions Inventory for the Page 16

Huntington-Ironton-Ashland PM 2.5Nonattainment Area 

### Table 4. MOVES County Data Manager Parameters County Data Manager Input Data Source Meteorology Data Local. OH and WV data from ODOT. KY data from KDAQ Source Type Population Local and default. Local data from motor vehicle registration dat a. WV data from WVDEP. Default data used for source types 51, 52, 53, 61, and 62. OH data from ODOT. Default data used for source types 41, 51, 54, 61, and 62. KY data from KYTC. No default data used. 0.8% annual growth factor applied for all areas. Age Distribution Local and default. Local data from motor vehicle registration data. WV data from WVDEP. Ohio data used for source types 41, 42, 43, 51, 52, 53, 61, and 62. OH data from ODOT (Lawrence and Scioto Counties). KY data from KYTC (Boyd County). Vehicle Type VMT

– HPMS Vehicle Type VMT Local. OH and WV data from ODOT. Lawrence County, OH, Cabell County, WV, and Wayne County, WV data from KYOVA Travel Demand Model. Scioto County, OH data from interim statewide model. Adams County, OH, Gallia County, OH, and Mason County, WV data from ODOT and WVDOT roadway inventory data. KY data from KYTC. Ashland Travel Demand Model and HPMS data used to forecast information. Vehicle Type VMT

– Monthly VMT Fraction Determined using EPA conversion tool for Annual Average Weekly VMT Vehicle Type VMT

– Daily VMT Fraction Determined using EPA conversion tool for Annual Average Weekly VMT Vehicle Type VMT

– Hourly VMT Fraction Local and default. OH and WV data from ODOT. Default used for off

network, OH data used for on- road classes. KY data from KYTC. Default used for off-network, road type 4. KY data used for road types 2, 3, and 5. Average Speed Distribution Default Road Type Distribution Local. ODOT applied HPMS data for Lawrence County, OH, Scioto County, OH, Cabell County, WV, and Wayne County, WV. Assumed to apply to all geographic areas. Ramp Fraction Local. OH and WV data from KYOVA Travel Demand Model. KY data from Ashland Travel Demand Model. Fuel Supply Local and default. Default for WV and OH. KY data from KDAQ. Fuel Formulation Default I/M Programs No data entered Zone Road Activity Default


### Travel Demand Modeling The latest planning assumptions available for the Huntington-Ironton-Ashland non-attainment area were used. Both the KYOVA Travel Demand Model and the KYTC Ashland Regional Travel Demand Model are the most recent and approved regional travel demand models for their respective areas. For each travel demand model, model validation is a joint process between the MPO and the appropriate state review agencies. The KYOVA Travel Demand Model is a three step model. Trip generation, trip distribution, and trip assignment components are included in the model. Mode choice is not an element of the current model. The Travel Demand Model covers Cabell County, WV, Wayne County, WV, and Lawrence County, OH. The current base year for the travel demand model is 2000. SocioeconomicMobile Source Emissions Inventory for the Page 17

Huntington-Ironton-Ashland PM 2.5Nonattainment Area 

### data was forecasted to the year 2035 as a part of the most recent regional metropolitan transportation plan. The QRS II modeling platform was used to develop this model. The KYOVA Interstate Planning Commission’s currently adopted transportation plan, titled Huntington-Ironton Area Transportation Study (HIATS), The Year 2035 Long-Range Transportation Planwas prepared in May 2009. Appendix A of that document contains the assumptions and methodology used to develop the Travel Demand Model. Similar to the KYOVA Travel Demand Model, the Ashland Regional Travel Demand Model is a traditional three-step model. The model includes trip generation, trip distribution, and trip assignment components. Transit operations are not included in the model; as a result, there is no mode choice component. The Travel Demand Model covers Boyd and Greenup Counties in Kentucky. Updated in 2007, this model has a base year of 2007 and a final horizon year of 2040. 2010, 2020, and 2030 forecast years were also incorporated into the model. The TransCAD modeling platform was used to develop this model. The document titled Ashland Regional Travel Demand Model, Model Update Report was developed in January 2008 for the Kentucky Transportation Cabinet. This document contains the assumptions and methodology used to develop the current Travel Demand Model. For areas of the modeling region in a county with a travel demand model, information from this model was applied for the analysis. Specifically, VMT data in the HPMS vehicle class format and ramp fractions for rural and urban restricted roadways were obtained from the travel demand models. For areas outside of the travel demand model extents, ramp fractions were assumed to mirror those seen in their respective states. HPMS vehicle class VMTs for areas outside the travel demand model limits were derived and forecasted from current HPMS traffic data in those areas. In addition to the information above, numerous additional data sources were consulted to obtain the needed information for the MOVES software. Source type population and vehicle age distribution data were obtained from ODOT, WVDEP, and KYTC for their respective states. ODOT and KYTC provided data about hourly vehicle distributions. Guidance and data for meteorological, fuel supply, and fuel formulation inputs were obtained from ODOT and KDAQ. The KYOVA Interstate Planning Commission supplied information on the transit vehicle population for the region. Information regarding these parameters is discussed in Tables 3 and 4

. Post-Processing The analysis was performed using the emission rates method. This method was chosen over the inventory method in an attempt to generate a set of MOVES runs that could later be used for other project applications without re-running the entire MOVES program. As a result, post-processing of the data was required to arrive at the overall emissions output. To do this, the rate per distance and rate per vehicle output data were matched with the appropriate geographic area, analysis year, source types, pollutant types, road types, modeling hours, and speed classes and then aggregated with the corresponding source type population and vehicle miles traveled information. The resulting information was summarized by pollutant type for each full or partial county being analyzed to generate the overall emissions in tons per year. The Appendix provides additional detail on the data sources gathered, modeling assumptions, and post-processing steps.APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-1

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area



# APPENDIX

Technical Documentation for Using MOVES2010a to Develop Mobile SourceEmissions for the Huntington-IrontonAshland PM 2.5

# Nonattainment Area

March 2011APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-2

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area 

### 1.0 MOVES2010a The MOVES2010a software was released by the Environmental Protection Agency in August 2010. This software uses a graphical user interface with a set of input categories. A Runspec can be developed that stores the input values for these categories. The values and information included in the Runspecs developed for this analysis are explained in more detail in the following sections.

1.1 Description This input window is used to distinguish the individual Runspecs. For this analysis, the description is used to introduce the purpose for the analysis, the area being studied (i.e. West Virginia, Ohio, or Kentucky), and the year of analysis (i.e. 2005, 2008, 2015, and 2022).

1.2 Scale This input window is used to detail the information needed for the domain/scale of the analysis as well as the calculation type. The county level was selected as the domain for this effort, since it is the appropriate level for use in SIP and regional conformity analysis. The emission rate method was chosen for the calculation type. This calculation type was chosen following a discussion with the involved review agencies to determine the most appropriate calculation method for this analysis.

1.3 Time Spans The Time Spans input window has a variety of different timescale inputs that are used for understanding the level of temporal aggregation being used in the analysis. The time aggregation level was specified as hours, based on guidance from EPA/FHWA for the preferred aggregation level for SIP runs. Based on the interagency consultation process, the years 2005, 2008, 2015, and 2022 were chosen for the analysis years. 2022 was chosen as the final horizon year because that year must be more than 10 years beyond the current year. Each year was done within a different Runspec. Since the pollutant analysis being conducted is for the annual PM2.5

### standard, a representative month was chosen to portray average annual temperatures. April was established as the representative month through the consultation process. Weekdays were selected as the representative day type since they are considered to be the worst-case type when compared with weekends. All hours of the day were included in the analysis to represent conditions over a full 24-hour period.

1.4 Geographic Bounds Rather than looking at each full and partial county within the non-attainment area, a custom domain method was employed. Custom domains were used to represent the areas to be modeled in each of the three states. The custom domains are as follows:

x West Virginia: Cabell, Wayne, and Mason (partial) Counties. CountyID 1.

x Ohio: Lawrence, Scioto, Adams (partial), and Gallia (partial) Counties. CountyID 2.

x Kentucky: Boyd and Lawrence (partial) Counties. CountyID 3. The component counties within each state’s analysis area were listed within this input window. Default information was used for the barometric pressure in each custom domain. This region is not a geographic phase-in area, so that value was kept as zero. Since the region does not have an I/M program, the refueling vapor program adjustment fraction and the refueling spill program adjustment factors were also left as zero.APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-3

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### This input window also asks for the name of the domain input database. A total of twelve input databases were created during this process, reflecting the appropriate Runspec and input data for the following conditions:

x West Virginia, Year 2005

x West Virginia, Year 2008

x West Virginia, Year 2015

x West Virginia, Year 2022 x Ohio, Year 2005

x Ohio, Year 2008

x Ohio, Year 2015

x Ohio, Year 2022 x Kentucky, Year 2005

x Kentucky, Year 2008

x Kentucky, Year 2015

x Kentucky, Year 2022

1.5 Vehicles/Equipment This input window allows the user to specify which fuel and vehicle types are present within the transportation network. There are thirteen vehicle classes (referred to as source use types) and five fuel types. This analysis considers diesel and gas fuel types only. This was partly to reflect the lack of compressed natural gas and liquefied petroleum gas vehicles in the population, and also to allow for default fuel formulation and fuel supply information to be used in portions of the study area. Within these constraints, all possible vehicle and fuel types were considered. Diesel motorcycles, gas combination long-haul trucks, and gas intercity buses were removed since they are not represented in the vehicle population.

1.6 Road Type The MOVES software incorporates five different roadway types: off-network, rural restricted access, rural unrestricted access, urban restricted access, and urban unrestricted access. Expressways and freeways in the region are considered as restricted access facilities. For this analysis, all five vehicle types were considered. Off-network emissions are intended to account for vehicle starts and evaporative emissions for parked vehicles. While these emissions are not captured through the information provided by the regional travel demand models, default values can be used to assess their impacts.

1.7 Pollutants and Processes This input window allows the user to specify different pollutants and processes that are desired for modeling. Since the purpose of this analysis is to assess emissions relating to the annual PM2.5 

### standard, the interagency consultation specified the inclusion of total energy consumption, all PM2.5 

### categories, NO
x 

### , and SO 2 

### .
1.8 Miscellaneous Strategies The MOVES software includes input windows where provisions can be specified for alternative vehicle fuels and technologies (AVFT), on-road retrofit strategies, and rate of progress information. If no information is entered for AVFT, MOVES assumes a default mix of alternative fuels. KYOVA provided information detailing the makeup of the bus fleet for the Tri-State Transit Authority (TTA). The TTA fleet is composed of standard gas and diesel vehicles as well as a small number of hybrid vehicles. At this time, the MOVES software is not equipped to consider hybrid vehicles in its AVFT element. This element can only be used to reflect compressed natural gas, electric, and advanced internal combustion engines. Therefore, the MOVES default file was modified to reflect only standard fuel types. Table 1 shows the modified portion of the AVFT file used in this MOVES analysis for the entire region.APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-4

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area 

### Table 1. AVFT Input for All Runspecs (Source Type 42) sourceTypeID modelYearID fuelTypeID engTechID fuelEngFraction

42 1960 2 1 1 42 1961 2 1 1 42 1962 2 1 1 42 1963 2 1 1 42 1964 2 1 1 42 1965 2 1 1 42 1966 2 1 1 42 1967 2 1 1 42 1968 2 1 1 42 1969 2 1 1 42 1970 2 1 1 42 1971 2 1 1 42 1972 2 1 1 42 1973 2 1 1 42 1974 2 1 1 42 1975 2 1 1 42 1976 2 1 1 42 1977 2 1 1 42 1978 2 1 1 42 1979 2 1 1 42 1980 2 1 1 42 1981 2 1 1 42 1982 2 1 1 42 1983 2 1 1 42 1984 2 1 1 42 1985 2 1 1 42 1986 2 1 1 42 1987 2 1 1 42 1988 2 1 1 42 1989 2 1 1 42 1990 2 1 1 42 1991 2 1 1 42 1992 2 1 1 42 1993 2 1 1 42 1994 2 1 1 42 1995 2 1 1 42 1996 2 1 1 42 1997 2 1 1 42 1998 2 1 1 42 1999 2 1 1 42 2000 2 1 1 42 2001 2 1 1 42 2002 2 1 1 42 2003 2 1 1 42 2004 2 1 1 42 2005 2 1 1APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-5

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area sourceTypeID modelYearID fuelTypeID engTechID fuelEngFraction

42 2006 2 1 1 42 2007 2 1 1 42 2008 2 1 1 42 2009 2 1 1 42 2010 2 1 1 42 2011 2 1 1 42 2012 2 1 1 42 2013 2 1 1 42 2014 2 1 1 42 2015 2 1 1 42 2016 2 1 1 42 2017 2 1 1 42 2018 2 1 1 42 2019 2 1 1 42 2020 2 1 1 42 2021 2 1 1 42 2022 2 1 1 42 2023 2 1 1 42 2024 2 1 1 42 2025 2 1 1 42 2026 2 1 1 42 2027 2 1 1 42 2028 2 1 1 42 2029 2 1 1 42 2030 2 1 1 42 2031 2 1 1 42 2032 2 1 1 42 2033 2 1 1 42 2034 2 1 1 42 2035 2 1 1 42 2036 2 1 1 42 2037 2 1 1 42 2038 2 1 1 42 2039 2 1 1 42 2040 2 1 1 42 2041 2 1 1 42 2042 2 1 1 42 2043 2 1 1 42 2044 2 1 1 42 2045 2 1 1 42 2046 2 1 1 42 2047 2 1 1 42 2048 2 1 1 42 2049 2 1 1 42 2050 2 1 1APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-6

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area 

### 1.9 Output Output for the MOVES program is stored in a user-created database. Output databases were created for each of the 12 different Runspec conditions. As specified in the interagency consultation process, grams, joules, and miles were used as the units of measure in the output database. Based on the parameters already established in these Runspecs, the time measurement for this analysis was set as hourly, and the location was automatically set for the link level. To assist with post-processing aggregation, it was further requested that the source use type information be included with the output.

2.0 County Data Manager Once all of the base parameters have been established for a given MOVES Runspec, the County Data Manager can be used to enter locally-specific data. Input provided in Excel spreadsheet format can be referenced using this tool, which converts the data to MySQL format and incorporates it into the MOVES analysis. For the Huntington-Ironton-Ashland non-attainment area, locally-specific data could consist of data used for the entire region, for one or more state portions, or for a particular county. The following sections detail these input criteria, and the methodology and assumptions used to arrive at the information entered for each.

2.1 Meteorology Data Importer This importer requires the average temperature and relative humidity information for each hour of the day. As detailed in the MOVES Runspec information, the month of April was assumed to represent average annual conditions. The Protocol Report developed for this analysis indicated all meteorological information would be derived from NOAA information obtained at the Tri-State Airport. However, the presence of specific data in the Kentucky area led to the airport data being used only for the Ohio and West Virginia portions of this analysis. Due to the detail of this data as well as the location of the airport, this data is assumed to appropriately represent the Ohio and West Virginia areas of the analysis. ODOT supplied the information for Ohio and West Virginia, obtained originally from NOAA. The Ohio and West Virginia data represents the meteorological conditions at the Tri-State Airport. 2002 was chosen for the meteorological base year due to the guidance provided in Federal Register 40 CFR 93.122, which states temperatures should be consistent with those used to establish the budget in the current State Implementation Plan. Table 2 shows the April portion of the meteorology data used in Ohio and West Virginia. Meteorological data for the Kentucky portion of the analysis area was obtained from KDAQ. This data provided temperature and humidity information for Boyd County, KY. Data for this county is also anticipated to be applicable for the modeled portion of Lawrence County, KY. The temperature and relative humidity data was obtained from historical data obtained through NOAA. Table 3 shows the April portion of the meteorology data used in Kentucky.APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-7

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area monthID zoneID HourID temperature relHumidity 4 990010 1 46.8 75.0 4 990010 2 45.5 77.0 4 990010 3 44.6 78.0 4 990010 4 43.9 80.0 4 990010 5 43.3 82.0 4 990010 6 42.7 83.0 4 990010 7 42.2 80.0 4 990010 8 42.6 78.0 4 990010 9 45.3 74.0 4 990010 10 49.5 68.0 4 990010 11 53.8 66.0 4 990010 12 57.4 63.0 4 990010 13 60.7 61.0 4 990010 14 62.4 58.0 4 990010 15 63.0 56.0 4 990010 16 63.2 54.0 4 990010 17 62.8 53.0 4 990010 18 61.5 55.0 4 990010 19 59.4 59.0 4 990010 20 56.7 62.0 4 990010 21 54.0 66.0 4 990010 22 51.7 68.0 4 990010 23 50.0 73.0 4 990010 24 48.3 73.0 monthID zoneID hourID temperature relHumidity 4 990030 1 48.8 61.5 4 990030 2 47.4 63.8 4 990030 3 46.4 66.4 4 990030 4 45.6 68.4 4 990030 5 45.0 70.5 4 990030 6 44.4 72.2 4 990030 7 43.8 73.5 4 990030 8 44.3 73.6 4 990030 9 47.2 68.7 4 990030 10 51.8 62.3 4 990030 11 56.5 56.4 4 990030 12 60.5 51.5 4 990030 13 64.0 48.0 4 990030 14 65.9 45.3 4 990030 15 66.6 43.2 4 990030 16 66.8 42.2 4 990030 17 66.3 41.6 4 990030 18 65.0 41.7 4 990030 19 62.7 42.7 4 990030 20 59.7 45.3 4 990030 21 56.7 48.2 4 990030 22 54.2 51.7 4 990030 23 52.3 55.3 4 990030 24 50.5 58.6 

### Table 2. West Virginia and Ohio Meteorology Data Table 3. Kentucky Meteorology Data

2.2 Source Type Population Importer This importer provides the user with the opportunity to enter vehicle population data for the local area, sorted by the 13 MOVES vehicle source types. Data for this importer was obtained from West Virginia, Ohio, and Kentucky for their respective areas. The Protocol Report prepared for this analysis indicated that each state’s area would use a combination of default data and local information. While this was the case, the source types using default and local data varied by each state. The 0.8% annual growth factor established in the Protocol Report was used to determine future year source type population numbers for all three states. A definition of all source type IDs can be found in the excerpt of the MOVES2010 User Guide found at the back of the Protocol Report. WVDEP supplied the data for Cabell, Wayne, and Mason Counties. This data was originally obtained from the WVDMV and then cleaned to fit within the MOVES source types. An inventory of the bus population in the three-county area was obtained and used to modify the supplied DMV data. Due to questions about the validity or completeness of some of the data, default values were used for the following source types: 51 (Refuse Truck), 52 (Single Unit Short-Haul Truck), 53 (Single Unit Long-Haul Truck), 61 (Combination Short-Haul Truck), and 62 (Combination Long Haul Truck). Actual data has been used for Motorcycles, Passenger Cars, Passenger Trucks, Light Commercial Trucks, Transit Buses, School Buses, and Motor Homes. For source type 41 (Intercity Bus), the data was obtained by looking atAPPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-8

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area 

### the actual transit bus number, and then applying the ratio found in the MOVES default data between intercity and transit buses. Mason County data was obtained for the entire county, and then reduced by WVDEP to reflect the township in the partial county nonattainment area. Data obtained was from the year 2007. Table 4shows the West Virginia source type population data for the year 2008.

Ohio data was obtained from ODOT. This data was cleaned to fit within the MOVES source type classifications. Due to questions about the accuracy or validity of certain source types, default values were employed in some instances. Default values were used for source type 41 (Intercity Bus), 51 (Refuse Truck), 54 (Motor Home), 61 (Combination Short-Haul Truck), and 62 (Combination Long-Haul Truck). This data was provided for the year 2008. Table 5 shows the Ohio source type population data for the year 2008. Kentucky data was obtained from the Kentucky Transportation Cabinet. KYTC used the converter tool available from EPA/FHWA to adjust the data currently available in Mobile6 format into MOVES source types. There were no default values used for any of the source types in the Kentucky data set. Kentucky provided data for Boyd County during the year 2010. A factor of 0.0624 was used to estimate Lawrence County data based on Boyd County data. This factor was based on 2009 VMT of 85,757 for the Lawrence nonattainment area and 1,375,095 for Boyd. Table 6shows the Kentucky source type population data for the year 2008. Table 4. 2008 West Virginia Source Type Population yearID sourceTypeID sourceTypePopulation 2008 11 2847 2008 21 44548 2008 31 43905 2008 32 7146 2008 41 63 2008 42 34 2008 43 240 2008 51 43 2008 52 2597 2008 53 296 2008 54 128 2008 61 660 2008 62 732APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-9

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area 

### Table 5. 2008 Ohio Source Type Population yearID sourceTypeID sourceTypePopulation 2008 11 10899 2008 21 105584 2008 31 47800 2008 32 1168 2008 41 33 2008 42 3 2008 43 486 2008 51 20 2008 52 371 2008 53 123 2008 54 5005 2008 61 254 2008 62 291 

### Table 6. 2008 Kentucky Source Type Population yearID sourceTypeID sourceTypePopulation 2008 11 2278 2008 21 25773 2008 31 19154 2008 32 5781 2008 41 9 2008 42 27 2008 43 46 2008 51 7 2008 52 234 2008 53 16 2008 54 25 2008 61 124 2008 62 100



### 2.3 Age Distribution Importer The Age Distribution Importer allows the user to provide vehicle age distribution data sorted by the MOVES vehicle source types. Vehicle age distribution is divided into 30 years based on vehicle model years. For each vehicle type, the sum of all age distributions will equal one. Age distribution information was obtained from each state for their respective area. The Protocol Report indicates a combination of local and default data would be used to determine the overall distribution. Since the type and quality of data available by state varies, these local and default data combinations were established unique to each state. As stated in the Protocol Report, the age distribution determined for each state was used for all analysis years.APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-10

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area source TypeID yearID ageID ageFraction 11 2008 0 0.0267 11 2008 1 0.0620 11 2008 2 0.0904 11 2008 3 0.1036 11 2008 4 0.0895 11 2008 5 0.0806 11 2008 6 0.0581 11 2008 7 0.0797 11 2008 8 0.0620 11 2008 9 0.0482 11 2008 10 0.0383 11 2008 11 0.0326 11 2008 12 0.0210 11 2008 13 0.0201 11 2008 14 0.0186 11 2008 15 0.0156 11 2008 16 0.0132 11 2008 17 0.0099 11 2008 18 0.0063 11 2008 19 0.0048 11 2008 20 0.0048 source TypeID yearID ageID ageFraction 11 2008 21 0.0051 11 2008 22 0.0078 11 2008 23 0.0096 11 2008 24 0.0099 11 2008 25 0.0117 11 2008 26 0.0087 11 2008 27 0.0096 11 2008 28 0.0084 11 2008 29 0.0057 11 2008 30 0.0377 21 2008 0 0.0313 21 2008 1 0.0391 21 2008 2 0.0532 21 2008 3 0.0643 21 2008 4 0.0578 21 2008 5 0.0609 21 2008 6 0.0586 21 2008 7 0.0608 21 2008 8 0.0628 21 2008 9 0.0608 21 2008 10 0.0664 

### West Virginia data was provided by WVDEP, based on information from motor vehicle registration data. 2010 data was used to assess the age distribution of certain vehicle types. Based on the availability and confidence level about some of the vehicle class data, only certain types were distributed using local data. Cabell, Mason, and Wayne age distribution data was used for the following source types: source type 11 (Motorcycle), source type 21 (Passenger Car), source type 31 (Passenger Truck), source type 32 (Light Commercial Truck), and source type 54 (Motor Home). The age distribution data provided from Ohio was used for the remaining source types. Table 7 shows the age distributions used for the West Virginia area (shown for the year 2008). Ohio data was obtained from ODOT, based on information from motor vehicle registration data. The data was cleaned and prepared by ODOT to fit within the MOVES format. Data provided was for Scioto and Lawrence Counties, but is expected to be representative of the entire area. This data was provided for 2008. Table 8shows the age distributions used for the Ohio area (shown for the year 2008). Kentucky data was provided by the Kentucky Transportation Cabinet, based on information from motor vehicle registration data. While this data is for Boyd County, it is assumed to also be representative of the Lawrence County area. This data was provided for the year 2010. Table 9shows the age distributions used for the Kentucky area (shown for the year 2008). Table 7. West Virginia Non-Attainment Area Age DistributionsAPPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-11

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area source TypeID yearID ageID ageFraction 21 2008 11 0.0600 21 2008 12 0.0510 21 2008 13 0.0446 21 2008 14 0.0360 21 2008 15 0.0351 21 2008 16 0.0260 21 2008 17 0.0214 21 2008 18 0.0171 21 2008 19 0.0142 21 2008 20 0.0110 21 2008 21 0.0084 21 2008 22 0.0065 21 2008 23 0.0052 21 2008 24 0.0040 21 2008 25 0.0028 21 2008 26 0.0027 21 2008 27 0.0012 21 2008 28 0.0007 21 2008 29 0.0011 21 2008 30 0.0348 31 2008 0 0.0309 31 2008 1 0.0326 31 2008 2 0.0514 31 2008 3 0.0555 31 2008 4 0.0599 31 2008 5 0.0670 31 2008 6 0.0698 31 2008 7 0.0644 31 2008 8 0.0646 31 2008 9 0.0565 31 2008 10 0.0617 31 2008 11 0.0541 31 2008 12 0.0498 31 2008 13 0.0457 31 2008 14 0.0363 31 2008 15 0.0345 31 2008 16 0.0301 31 2008 17 0.0209 31 2008 18 0.0170 31 2008 19 0.0144 31 2008 20 0.0113 31 2008 21 0.0125 31 2008 22 0.0110 31 2008 23 0.0077 31 2008 24 0.0069 31 2008 25 0.0064 source TypeID yearID ageID ageFraction 31 2008 26 0.0043 31 2008 27 0.0026 31 2008 28 0.0017 31 2008 29 0.0013 31 2008 30 0.0173 32 2008 0 0.0414 32 2008 1 0.0419 32 2008 2 0.0740 32 2008 3 0.0810 32 2008 4 0.0903 32 2008 5 0.0810 32 2008 6 0.0671 32 2008 7 0.0708 32 2008 8 0.0557 32 2008 9 0.0550 32 2008 10 0.0441 32 2008 11 0.0418 32 2008 12 0.0253 32 2008 13 0.0318 32 2008 14 0.0255 32 2008 15 0.0307 32 2008 16 0.0301 32 2008 17 0.0193 32 2008 18 0.0155 32 2008 19 0.0108 32 2008 20 0.0118 32 2008 21 0.0095 32 2008 22 0.0087 32 2008 23 0.0073 32 2008 24 0.0101 32 2008 25 0.0064 32 2008 26 0.0046 32 2008 27 0.0038 32 2008 28 0.0014 32 2008 29 0.0013 32 2008 30 0.0020 41 2008 0 0.0000 41 2008 1 0.0147 41 2008 2 0.0000 41 2008 3 0.0000 41 2008 4 0.0882 41 2008 5 0.0441 41 2008 6 0.0294 41 2008 7 0.0588 41 2008 8 0.0000 41 2008 9 0.0294APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-12

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area source TypeID yearID ageID ageFraction 41 2008 10 0.0441 41 2008 11 0.1471 41 2008 12 0.1324 41 2008 13 0.0588 41 2008 14 0.0000 41 2008 15 0.0441 41 2008 16 0.0588 41 2008 17 0.0147 41 2008 18 0.0000 41 2008 19 0.0000 41 2008 20 0.0294 41 2008 21 0.0000 41 2008 22 0.1471 41 2008 23 0.0147 41 2008 24 0.0000 41 2008 25 0.0000 41 2008 26 0.0147 41 2008 27 0.0000 41 2008 28 0.0000 41 2008 29 0.0000 41 2008 30 0.0295 42 2008 0 0.0000 42 2008 1 0.0000 42 2008 2 0.0000 42 2008 3 0.0000 42 2008 4 0.0000 42 2008 5 0.0000 42 2008 6 0.0000 42 2008 7 0.0000 42 2008 8 0.0000 42 2008 9 0.3333 42 2008 10 0.0000 42 2008 11 0.0000 42 2008 12 0.3333 42 2008 13 0.0000 42 2008 14 0.0000 42 2008 15 0.0000 42 2008 16 0.0000 42 2008 17 0.0000 42 2008 18 0.0000 42 2008 19 0.0000 42 2008 20 0.0000 42 2008 21 0.0000 42 2008 22 0.0000 42 2008 23 0.0000 42 2008 24 0.0000 source TypeID yearID ageID ageFraction 42 2008 25 0.0000 42 2008 26 0.3333 42 2008 27 0.0000 42 2008 28 0.0000 42 2008 29 0.0001 42 2008 30 0.0000 43 2008 0 0.0168 43 2008 1 0.0189 43 2008 2 0.0671 43 2008 3 0.0461 43 2008 4 0.0335 43 2008 5 0.0335 43 2008 6 0.0461 43 2008 7 0.0629 43 2008 8 0.0629 43 2008 9 0.0839 43 2008 10 0.0650 43 2008 11 0.0650 43 2008 12 0.0629 43 2008 13 0.0440 43 2008 14 0.0294 43 2008 15 0.0252 43 2008 16 0.0314 43 2008 17 0.0231 43 2008 18 0.0231 43 2008 19 0.0105 43 2008 20 0.0273 43 2008 21 0.0126 43 2008 22 0.0105 43 2008 23 0.0168 43 2008 24 0.0105 43 2008 25 0.0126 43 2008 26 0.0231 43 2008 27 0.0042 43 2008 28 0.0105 43 2008 29 0.0063 43 2008 30 0.0143 51 2008 0 0.0000 51 2008 1 0.0714 51 2008 2 0.2005 51 2008 3 0.1071 51 2008 4 0.0934 51 2008 5 0.0055 51 2008 6 0.0192 51 2008 7 0.0357 51 2008 8 0.0302APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-13

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area source TypeID yearID ageID ageFraction 51 2008 9 0.0302 51 2008 10 0.0440 51 2008 11 0.0659 51 2008 12 0.0330 51 2008 13 0.0385 51 2008 14 0.0385 51 2008 15 0.0467 51 2008 16 0.0330 51 2008 17 0.0357 51 2008 18 0.0330 51 2008 19 0.0082 51 2008 20 0.0110 51 2008 21 0.0000 51 2008 22 0.0027 51 2008 23 0.0055 51 2008 24 0.0000 51 2008 25 0.0082 51 2008 26 0.0000 51 2008 27 0.0000 51 2008 28 0.0000 51 2008 29 0.0000 51 2008 30 0.0029 52 2008 0 0.0000 52 2008 1 0.0714 52 2008 2 0.2005 52 2008 3 0.1071 52 2008 4 0.0934 52 2008 5 0.0055 52 2008 6 0.0192 52 2008 7 0.0357 52 2008 8 0.0302 52 2008 9 0.0302 52 2008 10 0.0440 52 2008 11 0.0659 52 2008 12 0.0330 52 2008 13 0.0385 52 2008 14 0.0385 52 2008 15 0.0467 52 2008 16 0.0330 52 2008 17 0.0357 52 2008 18 0.0330 52 2008 19 0.0082 52 2008 20 0.0110 52 2008 21 0.0000 52 2008 22 0.0027 52 2008 23 0.0055 source TypeID yearID ageID ageFraction 52 2008 24 0.0000 52 2008 25 0.0082 52 2008 26 0.0000 52 2008 27 0.0000 52 2008 28 0.0000 52 2008 29 0.0000 52 2008 30 0.0029 53 2008 0 0.0000 53 2008 1 0.0714 53 2008 2 0.2005 53 2008 3 0.1071 53 2008 4 0.0934 53 2008 5 0.0055 53 2008 6 0.0192 53 2008 7 0.0357 53 2008 8 0.0302 53 2008 9 0.0302 53 2008 10 0.0440 53 2008 11 0.0659 53 2008 12 0.0330 53 2008 13 0.0385 53 2008 14 0.0385 53 2008 15 0.0467 53 2008 16 0.0330 53 2008 17 0.0357 53 2008 18 0.0330 53 2008 19 0.0082 53 2008 20 0.0110 53 2008 21 0.0000 53 2008 22 0.0027 53 2008 23 0.0055 53 2008 24 0.0000 53 2008 25 0.0082 53 2008 26 0.0000 53 2008 27 0.0000 53 2008 28 0.0000 53 2008 29 0.0000 53 2008 30 0.0029 54 2008 0 0.0128 54 2008 1 0.0128 54 2008 2 0.0256 54 2008 3 0.0321 54 2008 4 0.0577 54 2008 5 0.0449 54 2008 6 0.0256 54 2008 7 0.0449APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-14

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area source TypeID yearID ageID ageFraction 54 2008 8 0.0256 54 2008 9 0.0321 54 2008 10 0.0256 54 2008 11 0.0321 54 2008 12 0.0192 54 2008 13 0.0064 54 2008 14 0.0064 54 2008 15 0.0192 54 2008 16 0.0449 54 2008 17 0.0385 54 2008 18 0.0064 54 2008 19 0.0192 54 2008 20 0.0641 54 2008 21 0.0577 54 2008 22 0.0321 54 2008 23 0.0385 54 2008 24 0.0321 54 2008 25 0.0641 54 2008 26 0.0256 54 2008 27 0.0064 54 2008 28 0.0192 54 2008 29 0.0064 54 2008 30 0.1218 61 2008 0 0.0017 61 2008 1 0.0096 61 2008 2 0.0198 61 2008 3 0.0224 61 2008 4 0.0285 61 2008 5 0.0350 61 2008 6 0.0401 61 2008 7 0.0410 61 2008 8 0.0429 61 2008 9 0.0462 61 2008 10 0.0551 61 2008 11 0.0549 61 2008 12 0.0492 61 2008 13 0.0534 61 2008 14 0.0425 61 2008 15 0.0490 61 2008 16 0.0521 61 2008 17 0.0367 61 2008 18 0.0358 61 2008 19 0.0343 61 2008 20 0.0302 61 2008 21 0.0367 61 2008 22 0.0356 source TypeID yearID ageID ageFraction 61 2008 23 0.0234 61 2008 24 0.0232 61 2008 25 0.0192 61 2008 26 0.0143 61 2008 27 0.0079 61 2008 28 0.0075 61 2008 29 0.0058 61 2008 30 0.0460 62 2008 0 0.0010 62 2008 1 0.0370 62 2008 2 0.0120 62 2008 3 0.0761 62 2008 4 0.0601 62 2008 5 0.0571 62 2008 6 0.0410 62 2008 7 0.0931 62 2008 8 0.0370 62 2008 9 0.0581 62 2008 10 0.0671 62 2008 11 0.0871 62 2008 12 0.0801 62 2008 13 0.0400 62 2008 14 0.0501 62 2008 15 0.0430 62 2008 16 0.0370 62 2008 17 0.0210 62 2008 18 0.0120 62 2008 19 0.0080 62 2008 20 0.0170 62 2008 21 0.0150 62 2008 22 0.0110 62 2008 23 0.0080 62 2008 24 0.0030 62 2008 25 0.0100 62 2008 26 0.0020 62 2008 27 0.0040 62 2008 28 0.0000 62 2008 29 0.0000 62 2008 30 0.0121APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-15

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area source TypeID yearID ageID ageFraction 11 2022 0 0.0017 11 2022 1 0.0240 11 2022 2 0.0578 11 2022 3 0.0786 11 2022 4 0.0896 11 2022 5 0.0908 11 2022 6 0.0739 11 2022 7 0.0782 11 2022 8 0.0631 11 2022 9 0.0530 11 2022 10 0.0472 11 2022 11 0.0341 11 2022 12 0.0257 11 2022 13 0.0210 11 2022 14 0.0224 11 2022 15 0.0193 11 2022 16 0.0156 11 2022 17 0.0105 11 2022 18 0.0083 11 2022 19 0.0043 11 2022 20 0.0072 11 2022 21 0.0072 11 2022 22 0.0076 11 2022 23 0.0104 11 2022 24 0.0182 11 2022 25 0.0129 11 2022 26 0.0149 11 2022 27 0.0140 11 2022 28 0.0227 11 2022 29 0.0122 11 2022 30 0.0536 21 2022 0 0.0062 21 2022 1 0.0199 21 2022 2 0.0331 21 2022 3 0.0389 21 2022 4 0.0404 21 2022 5 0.0420 21 2022 6 0.0411 21 2022 7 0.0434 21 2022 8 0.0475 21 2022 9 0.0525 21 2022 10 0.0646 21 2022 11 0.0630 21 2022 12 0.0599 source TypeID yearID ageID ageFraction 21 2022 13 0.0613 21 2022 14 0.0542 21 2022 15 0.0581 21 2022 16 0.0470 21 2022 17 0.0411 21 2022 18 0.0345 21 2022 19 0.0264 21 2022 20 0.0213 21 2022 21 0.0195 21 2022 22 0.0144 21 2022 23 0.0097 21 2022 24 0.0092 21 2022 25 0.0058 21 2022 26 0.0044 21 2022 27 0.0025 21 2022 28 0.0017 21 2022 29 0.0019 21 2022 30 0.0345 31 2022 0 0.0067 31 2022 1 0.0208 31 2022 2 0.0445 31 2022 3 0.0494 31 2022 4 0.0543 31 2022 5 0.0632 31 2022 6 0.0627 31 2022 7 0.0608 31 2022 8 0.0631 31 2022 9 0.0553 31 2022 10 0.0629 31 2022 11 0.0589 31 2022 12 0.0584 31 2022 13 0.0487 31 2022 14 0.0473 31 2022 15 0.0481 31 2022 16 0.0407 31 2022 17 0.0335 31 2022 18 0.0245 31 2022 19 0.0190 31 2022 20 0.0137 31 2022 21 0.0150 31 2022 22 0.0119 31 2022 23 0.0093 31 2022 24 0.0066 31 2022 25 0.0059 

### Table 8. Ohio Non-Attainment Area Age DistributionsAPPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-16

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area source TypeID yearID ageID ageFraction 31 2022 26 0.0038 31 2022 27 0.0021 31 2022 28 0.0011 31 2022 29 0.0010 31 2022 30 0.0068 32 2022 0 0.0070 32 2022 1 0.0209 32 2022 2 0.0689 32 2022 3 0.0489 32 2022 4 0.0445 32 2022 5 0.0262 32 2022 6 0.0218 32 2022 7 0.0271 32 2022 8 0.0349 32 2022 9 0.0297 32 2022 10 0.0558 32 2022 11 0.0620 32 2022 12 0.0541 32 2022 13 0.0550 32 2022 14 0.0384 32 2022 15 0.0742 32 2022 16 0.0567 32 2022 17 0.0349 32 2022 18 0.0462 32 2022 19 0.0305 32 2022 20 0.0323 32 2022 21 0.0366 32 2022 22 0.0166 32 2022 23 0.0122 32 2022 24 0.0218 32 2022 25 0.0131 32 2022 26 0.0087 32 2022 27 0.0052 32 2022 28 0.0026 32 2022 29 0.0009 32 2022 30 0.0123 41 2022 0 0.0000 41 2022 1 0.0147 41 2022 2 0.0000 41 2022 3 0.0000 41 2022 4 0.0882 41 2022 5 0.0441 41 2022 6 0.0294 41 2022 7 0.0588 41 2022 8 0.0000 41 2022 9 0.0294 source TypeID yearID ageID ageFraction 41 2022 10 0.0441 41 2022 11 0.1471 41 2022 12 0.1324 41 2022 13 0.0588 41 2022 14 0.0000 41 2022 15 0.0441 41 2022 16 0.0588 41 2022 17 0.0147 41 2022 18 0.0000 41 2022 19 0.0000 41 2022 20 0.0294 41 2022 21 0.0000 41 2022 22 0.1471 41 2022 23 0.0147 41 2022 24 0.0000 41 2022 25 0.0000 41 2022 26 0.0147 41 2022 27 0.0000 41 2022 28 0.0000 41 2022 29 0.0000 41 2022 30 0.0295 42 2022 0 0.0000 42 2022 1 0.0000 42 2022 2 0.0000 42 2022 3 0.0000 42 2022 4 0.0000 42 2022 5 0.0000 42 2022 6 0.0000 42 2022 7 0.0000 42 2022 8 0.0000 42 2022 9 0.3333 42 2022 10 0.0000 42 2022 11 0.0000 42 2022 12 0.3333 42 2022 13 0.0000 42 2022 14 0.0000 42 2022 15 0.0000 42 2022 16 0.0000 42 2022 17 0.0000 42 2022 18 0.0000 42 2022 19 0.0000 42 2022 20 0.0000 42 2022 21 0.0000 42 2022 22 0.0000 42 2022 23 0.0000 42 2022 24 0.0000APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-17

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area source TypeID yearID ageID ageFraction 42 2022 25 0.0000 42 2022 26 0.3333 42 2022 27 0.0000 42 2022 28 0.0000 42 2022 29 0.0001 42 2022 30 0.0000 43 2022 0 0.0168 43 2022 1 0.0189 43 2022 2 0.0671 43 2022 3 0.0461 43 2022 4 0.0335 43 2022 5 0.0335 43 2022 6 0.0461 43 2022 7 0.0629 43 2022 8 0.0629 43 2022 9 0.0839 43 2022 10 0.0650 43 2022 11 0.0650 43 2022 12 0.0629 43 2022 13 0.0440 43 2022 14 0.0294 43 2022 15 0.0252 43 2022 16 0.0314 43 2022 17 0.0231 43 2022 18 0.0231 43 2022 19 0.0105 43 2022 20 0.0273 43 2022 21 0.0126 43 2022 22 0.0105 43 2022 23 0.0168 43 2022 24 0.0105 43 2022 25 0.0126 43 2022 26 0.0231 43 2022 27 0.0042 43 2022 28 0.0105 43 2022 29 0.0063 43 2022 30 0.0143 51 2022 0 0.0000 51 2022 1 0.0714 51 2022 2 0.2005 51 2022 3 0.1071 51 2022 4 0.0934 51 2022 5 0.0055 51 2022 6 0.0192 51 2022 7 0.0357 51 2022 8 0.0302 source TypeID yearID ageID ageFraction 51 2022 9 0.0302 51 2022 10 0.0440 51 2022 11 0.0659 51 2022 12 0.0330 51 2022 13 0.0385 51 2022 14 0.0385 51 2022 15 0.0467 51 2022 16 0.0330 51 2022 17 0.0357 51 2022 18 0.0330 51 2022 19 0.0082 51 2022 20 0.0110 51 2022 21 0.0000 51 2022 22 0.0027 51 2022 23 0.0055 51 2022 24 0.0000 51 2022 25 0.0082 51 2022 26 0.0000 51 2022 27 0.0000 51 2022 28 0.0000 51 2022 29 0.0000 51 2022 30 0.0029 52 2022 0 0.0000 52 2022 1 0.0714 52 2022 2 0.2005 52 2022 3 0.1071 52 2022 4 0.0934 52 2022 5 0.0055 52 2022 6 0.0192 52 2022 7 0.0357 52 2022 8 0.0302 52 2022 9 0.0302 52 2022 10 0.0440 52 2022 11 0.0659 52 2022 12 0.0330 52 2022 13 0.0385 52 2022 14 0.0385 52 2022 15 0.0467 52 2022 16 0.0330 52 2022 17 0.0357 52 2022 18 0.0330 52 2022 19 0.0082 52 2022 20 0.0110 52 2022 21 0.0000 52 2022 22 0.0027 52 2022 23 0.0055APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-18

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area source TypeID yearID ageID ageFraction 52 2022 24 0.0000 52 2022 25 0.0082 52 2022 26 0.0000 52 2022 27 0.0000 52 2022 28 0.0000 52 2022 29 0.0000 52 2022 30 0.0029 53 2022 0 0.0000 53 2022 1 0.0714 53 2022 2 0.2005 53 2022 3 0.1071 53 2022 4 0.0934 53 2022 5 0.0055 53 2022 6 0.0192 53 2022 7 0.0357 53 2022 8 0.0302 53 2022 9 0.0302 53 2022 10 0.0440 53 2022 11 0.0659 53 2022 12 0.0330 53 2022 13 0.0385 53 2022 14 0.0385 53 2022 15 0.0467 53 2022 16 0.0330 53 2022 17 0.0357 53 2022 18 0.0330 53 2022 19 0.0082 53 2022 20 0.0110 53 2022 21 0.0000 53 2022 22 0.0027 53 2022 23 0.0055 53 2022 24 0.0000 53 2022 25 0.0082 53 2022 26 0.0000 53 2022 27 0.0000 53 2022 28 0.0000 53 2022 29 0.0000 53 2022 30 0.0029 54 2022 0 0.0073 54 2022 1 0.0151 54 2022 2 0.0320 54 2022 3 0.0368 54 2022 4 0.0450 54 2022 5 0.0413 54 2022 6 0.0450 54 2022 7 0.0472 source TypeID yearID ageID ageFraction 54 2022 8 0.0415 54 2022 9 0.0377 54 2022 10 0.0495 54 2022 11 0.0405 54 2022 12 0.0336 54 2022 13 0.0340 54 2022 14 0.0293 54 2022 15 0.0320 54 2022 16 0.0254 54 2022 17 0.0275 54 2022 18 0.0175 54 2022 19 0.0130 54 2022 20 0.0197 54 2022 21 0.0202 54 2022 22 0.0191 54 2022 23 0.0218 54 2022 24 0.0173 54 2022 25 0.0200 54 2022 26 0.0228 54 2022 27 0.0175 54 2022 28 0.0128 54 2022 29 0.0079 54 2022 30 0.1697 61 2022 0 0.0017 61 2022 1 0.0096 61 2022 2 0.0198 61 2022 3 0.0224 61 2022 4 0.0285 61 2022 5 0.0350 61 2022 6 0.0401 61 2022 7 0.0410 61 2022 8 0.0429 61 2022 9 0.0462 61 2022 10 0.0551 61 2022 11 0.0549 61 2022 12 0.0492 61 2022 13 0.0534 61 2022 14 0.0425 61 2022 15 0.0490 61 2022 16 0.0521 61 2022 17 0.0367 61 2022 18 0.0358 61 2022 19 0.0343 61 2022 20 0.0302 61 2022 21 0.0367 61 2022 22 0.0356APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-19

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area source TypeID yearID ageID ageFraction 61 2022 23 0.0234 61 2022 24 0.0232 61 2022 25 0.0192 61 2022 26 0.0143 61 2022 27 0.0079 61 2022 28 0.0075 61 2022 29 0.0058 61 2022 30 0.0460 62 2022 0 0.0010 62 2022 1 0.0370 62 2022 2 0.0120 62 2022 3 0.0761 62 2022 4 0.0601 62 2022 5 0.0571 62 2022 6 0.0410 62 2022 7 0.0931 62 2022 8 0.0370 62 2022 9 0.0581 62 2022 10 0.0671 62 2022 11 0.0871 62 2022 12 0.0801 62 2022 13 0.0400 62 2022 14 0.0501 62 2022 15 0.0430 62 2022 16 0.0370 62 2022 17 0.0210 62 2022 18 0.0120 62 2022 19 0.0080 62 2022 20 0.0170 62 2022 21 0.0150 62 2022 22 0.0110 62 2022 23 0.0080 62 2022 24 0.0030 62 2022 25 0.0100 62 2022 26 0.0020 62 2022 27 0.0040 62 2022 28 0.0000 62 2022 29 0.0000 62 2022 30 0.0121APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-20

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area source TypeID yearID ageID ageFraction 11 2022 0 0.0092 11 2022 1 0.0303 11 2022 2 0.0537 11 2022 3 0.0968 11 2022 4 0.0982 11 2022 5 0.0932 11 2022 6 0.0877 11 2022 7 0.0569 11 2022 8 0.0629 11 2022 9 0.0464 11 2022 10 0.0408 11 2022 11 0.0395 11 2022 12 0.0390 11 2022 13 0.0207 11 2022 14 0.0147 11 2022 15 0.0289 11 2022 16 0.0142 11 2022 17 0.0179 11 2022 18 0.0069 11 2022 19 0.0055 11 2022 20 0.0069 11 2022 21 0.0050 11 2022 22 0.0046 11 2022 23 0.0028 11 2022 24 0.0017 11 2022 25 0.0010 11 2022 26 0.0006 11 2022 27 0.0004 11 2022 28 0.0002 11 2022 29 0.0001 11 2022 30 0.1135 21 2022 0 0.0045 21 2022 1 0.0385 21 2022 2 0.0339 21 2022 3 0.0523 21 2022 4 0.0593 21 2022 5 0.0580 21 2022 6 0.0604 21 2022 7 0.0543 21 2022 8 0.0532 21 2022 9 0.0634 21 2022 10 0.0657 21 2022 11 0.0672 21 2022 12 0.0590 source TypeID yearID ageID ageFraction 21 2022 13 0.0522 21 2022 14 0.0446 21 2022 15 0.0393 21 2022 16 0.0383 21 2022 17 0.0279 21 2022 18 0.0240 21 2022 19 0.0174 21 2022 20 0.0124 21 2022 21 0.0090 21 2022 22 0.0112 21 2022 23 0.0077 21 2022 24 0.0053 21 2022 25 0.0037 21 2022 26 0.0025 21 2022 27 0.0018 21 2022 28 0.0012 21 2022 29 0.0008 21 2022 30 0.0308 31 2022 0 0.0039 31 2022 1 0.0315 31 2022 2 0.0280 31 2022 3 0.0520 31 2022 4 0.0592 31 2022 5 0.0592 31 2022 6 0.0657 31 2022 7 0.0644 31 2022 8 0.0626 31 2022 9 0.0582 31 2022 10 0.0576 31 2022 11 0.0575 31 2022 12 0.0483 31 2022 13 0.0457 31 2022 14 0.0417 31 2022 15 0.0313 31 2022 16 0.0332 31 2022 17 0.0319 31 2022 18 0.0206 31 2022 19 0.0172 31 2022 20 0.0162 31 2022 21 0.0137 31 2022 22 0.0143 31 2022 23 0.0119 31 2022 24 0.0108 31 2022 25 0.0126 

### Table 9. Kentucky Non-Attainment Area Age DistributionsAPPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-21

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area source TypeID yearID ageID ageFraction 31 2022 26 0.0066 31 2022 27 0.0049 31 2022 28 0.0039 31 2022 29 0.0032 31 2022 30 0.0319 32 2022 0 0.0041 32 2022 1 0.0305 32 2022 2 0.0277 32 2022 3 0.0520 32 2022 4 0.0594 32 2022 5 0.0592 32 2022 6 0.0639 32 2022 7 0.0635 32 2022 8 0.0611 32 2022 9 0.0573 32 2022 10 0.0566 32 2022 11 0.0574 32 2022 12 0.0481 32 2022 13 0.0441 32 2022 14 0.0417 32 2022 15 0.0314 32 2022 16 0.0331 32 2022 17 0.0319 32 2022 18 0.0217 32 2022 19 0.0176 32 2022 20 0.0157 32 2022 21 0.0137 32 2022 22 0.0149 32 2022 23 0.0124 32 2022 24 0.0118 32 2022 25 0.0136 32 2022 26 0.0070 32 2022 27 0.0054 32 2022 28 0.0047 32 2022 29 0.0038 32 2022 30 0.0345 41 2022 0 0.0000 41 2022 1 0.0000 41 2022 2 0.0000 41 2022 3 0.0000 41 2022 4 0.0286 41 2022 5 0.0000 41 2022 6 0.0000 41 2022 7 0.0000 41 2022 8 0.0000 41 2022 9 0.0000 source TypeID yearID ageID ageFraction 41 2022 10 0.0000 41 2022 11 0.0000 41 2022 12 0.0000 41 2022 13 0.0000 41 2022 14 0.0000 41 2022 15 0.0000 41 2022 16 0.0000 41 2022 17 0.0000 41 2022 18 0.0000 41 2022 19 0.0000 41 2022 20 0.0000 41 2022 21 0.0000 41 2022 22 0.0000 41 2022 23 0.0000 41 2022 24 0.0000 41 2022 25 0.0000 41 2022 26 0.0000 41 2022 27 0.0000 41 2022 28 0.0000 41 2022 29 0.0000 41 2022 30 0.9714 42 2022 0 0.0000 42 2022 1 0.0000 42 2022 2 0.0000 42 2022 3 0.0000 42 2022 4 0.0286 42 2022 5 0.0000 42 2022 6 0.0000 42 2022 7 0.0000 42 2022 8 0.0000 42 2022 9 0.0000 42 2022 10 0.0000 42 2022 11 0.0000 42 2022 12 0.0000 42 2022 13 0.0000 42 2022 14 0.0000 42 2022 15 0.0000 42 2022 16 0.0000 42 2022 17 0.0000 42 2022 18 0.0000 42 2022 19 0.0000 42 2022 20 0.0000 42 2022 21 0.0000 42 2022 22 0.0000 42 2022 23 0.0000 42 2022 24 0.0000APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-22

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area source TypeID yearID ageID ageFraction 42 2022 25 0.0000 42 2022 26 0.0000 42 2022 27 0.0000 42 2022 28 0.0000 42 2022 29 0.0000 42 2022 30 0.9714 43 2022 0 0.0242 43 2022 1 0.0239 43 2022 2 0.0009 43 2022 3 0.0934 43 2022 4 0.0010 43 2022 5 0.0941 43 2022 6 0.0704 43 2022 7 0.0024 43 2022 8 0.0701 43 2022 9 0.0248 43 2022 10 0.1183 43 2022 11 0.0250 43 2022 12 0.0944 43 2022 13 0.0034 43 2022 14 0.0265 43 2022 15 0.0010 43 2022 16 0.0479 43 2022 17 0.0934 43 2022 18 0.0017 43 2022 19 0.0009 43 2022 20 0.0021 43 2022 21 0.0246 43 2022 22 0.0029 43 2022 23 0.0021 43 2022 24 0.0020 43 2022 25 0.0020 43 2022 26 0.0021 43 2022 27 0.0024 43 2022 28 0.0012 43 2022 29 0.0000 43 2022 30 0.1409 51 2022 0 0.0119 51 2022 1 0.0138 51 2022 2 0.0237 51 2022 3 0.0278 51 2022 4 0.0667 51 2022 5 0.0615 51 2022 6 0.0892 51 2022 7 0.0367 51 2022 8 0.0549 source TypeID yearID ageID ageFraction 51 2022 9 0.0291 51 2022 10 0.0693 51 2022 11 0.0343 51 2022 12 0.0555 51 2022 13 0.0492 51 2022 14 0.0446 51 2022 15 0.0263 51 2022 16 0.0330 51 2022 17 0.0179 51 2022 18 0.0378 51 2022 19 0.0083 51 2022 20 0.0149 51 2022 21 0.0085 51 2022 22 0.0220 51 2022 23 0.0371 51 2022 24 0.0308 51 2022 25 0.0138 51 2022 26 0.0136 51 2022 27 0.0131 51 2022 28 0.0122 51 2022 29 0.0111 51 2022 30 0.0312 52 2022 0 0.0167 52 2022 1 0.0148 52 2022 2 0.0221 52 2022 3 0.0348 52 2022 4 0.0403 52 2022 5 0.0539 52 2022 6 0.0591 52 2022 7 0.0419 52 2022 8 0.0399 52 2022 9 0.0329 52 2022 10 0.0711 52 2022 11 0.0355 52 2022 12 0.0563 52 2022 13 0.0586 52 2022 14 0.0541 52 2022 15 0.0234 52 2022 16 0.0324 52 2022 17 0.0225 52 2022 18 0.0319 52 2022 19 0.0122 52 2022 20 0.0262 52 2022 21 0.0153 52 2022 22 0.0301 52 2022 23 0.0318APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-23

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area source TypeID yearID ageID ageFraction 52 2022 24 0.0270 52 2022 25 0.0183 52 2022 26 0.0180 52 2022 27 0.0179 52 2022 28 0.0116 52 2022 29 0.0054 52 2022 30 0.0439 53 2022 0 0.0167 53 2022 1 0.0148 53 2022 2 0.0228 53 2022 3 0.0364 53 2022 4 0.0396 53 2022 5 0.0544 53 2022 6 0.0588 53 2022 7 0.0431 53 2022 8 0.0399 53 2022 9 0.0337 53 2022 10 0.0726 53 2022 11 0.0358 53 2022 12 0.0578 53 2022 13 0.0607 53 2022 14 0.0549 53 2022 15 0.0240 53 2022 16 0.0321 53 2022 17 0.0220 53 2022 18 0.0317 53 2022 19 0.0124 53 2022 20 0.0268 53 2022 21 0.0146 53 2022 22 0.0291 53 2022 23 0.0307 53 2022 24 0.0257 53 2022 25 0.0170 53 2022 26 0.0166 53 2022 27 0.0159 53 2022 28 0.0106 53 2022 29 0.0053 53 2022 30 0.0436 54 2022 0 0.0213 54 2022 1 0.0160 54 2022 2 0.0184 54 2022 3 0.0367 54 2022 4 0.0160 54 2022 5 0.0450 54 2022 6 0.0305 54 2022 7 0.0435 source TypeID yearID ageID ageFraction 54 2022 8 0.0252 54 2022 9 0.0344 54 2022 10 0.0687 54 2022 11 0.0359 54 2022 12 0.0527 54 2022 13 0.0619 54 2022 14 0.0610 54 2022 15 0.0188 54 2022 16 0.0326 54 2022 17 0.0284 54 2022 18 0.0265 54 2022 19 0.0154 54 2022 20 0.0354 54 2022 21 0.0241 54 2022 22 0.0411 54 2022 23 0.0300 54 2022 24 0.0271 54 2022 25 0.0265 54 2022 26 0.0268 54 2022 27 0.0286 54 2022 28 0.0141 54 2022 29 0.0000 54 2022 30 0.0574 61 2022 0 0.0113 61 2022 1 0.0137 61 2022 2 0.0236 61 2022 3 0.0264 61 2022 4 0.0699 61 2022 5 0.0621 61 2022 6 0.0926 61 2022 7 0.0357 61 2022 8 0.0565 61 2022 9 0.0284 61 2022 10 0.0686 61 2022 11 0.0341 61 2022 12 0.0549 61 2022 13 0.0474 61 2022 14 0.0433 61 2022 15 0.0264 61 2022 16 0.0332 61 2022 17 0.0176 61 2022 18 0.0386 61 2022 19 0.0078 61 2022 20 0.0134 61 2022 21 0.0080 61 2022 22 0.0216APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-24

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area source TypeID yearID ageID ageFraction 61 2022 23 0.0381 61 2022 24 0.0317 61 2022 25 0.0138 61 2022 26 0.0136 61 2022 27 0.0134 61 2022 28 0.0126 61 2022 29 0.0118 61 2022 30 0.0299 62 2022 0 0.0105 62 2022 1 0.0135 62 2022 2 0.0235 62 2022 3 0.0245 62 2022 4 0.0749 62 2022 5 0.0633 62 2022 6 0.0981 62 2022 7 0.0343 62 2022 8 0.0592 62 2022 9 0.0274 62 2022 10 0.0676 62 2022 11 0.0337 62 2022 12 0.0541 62 2022 13 0.0449 62 2022 14 0.0413 62 2022 15 0.0267 62 2022 16 0.0334 62 2022 17 0.0170 62 2022 18 0.0397 62 2022 19 0.0071 62 2022 20 0.0111 62 2022 21 0.0071 62 2022 22 0.0205 62 2022 23 0.0396 62 2022 24 0.0329 62 2022 25 0.0135 62 2022 26 0.0134 62 2022 27 0.0133 62 2022 28 0.0131 62 2022 29 0.0129 62 2022 30 0.0278APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-25

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area 

### 2.4 Vehicle Type VMT and VMT Fractions This data importer asks the user for the VMT in the study area by HPMS vehicle class type, hourly VMT distributions, daily VMT distributions, and monthly VMT distributions. The HPMS vehicle class VMT is asked for an annual basis. To determine this information, data can be pulled from available travel demand models or from regional HPMS data.

HPMS Vehicle Class VMT To determine the HPMS vehicle type VMTs, additional analysis was necessary. Overall VMTs for West Virginia and Ohio were obtained from ODOT. VMTs for Lawrence County, OH, Cabell County, WV, and Wayne County, WV were obtained from the currently approved KYOVA Regional Travel Demand Model (currently operating on the QRSII platform). Scioto County, OH VMT information was obtained using the interim statewide model. The Portsmouth Bypass was assumed to be in place as of the 2015 analysis year, which increased the total VMT in the county. For the partial counties in Ohio, current mileage figures were obtained from ODOT OTS Roadway Inventory staff. VMTs for these areas were estimated using road lengths and other data fields in the statewide model network. The VMT for the portion of Mason County, WV included in this analysis was based on VMT and growth rates supplied by WVDOT. The projected VMTs for the four analysis years were totaled over all the complete and partial counties within the Ohio and West Virginia areas. Once these tallies were obtained, the next step was to separate out the total VMT into the six HPMS vehicle classes. ODOT provided a percentage for each analysis year for these vehicle classes. These percentages were obtained by looking at Ohio statewide data obtained through the Automatic Traffic Recorders program, and were then applied to the total Ohio VMT to obtain the needed input data. For West Virginia, VMT splits into the HPMS vehicle classes were obtained from 2003 HPMS data for the portion of the region being analyzed. These percentages were then applied to the total West Virginia VMT to arrive at the needed input data. The EPA conversion tool was used to convert these daily VMT numbers to annual values. Table 10 shows the annual VMT for the West Virginia area over all analysis years. Table 11 provides this information for the Ohio area. For Kentucky, data was supplied by the Kentucky Transportation Cabinet. HPMS VMT data was obtained for the years 2005 and 2008. Travel demand model data was used to forecast the VMT data for 2015 and 2022. Once VMTs were determined for each model year (divided by roadway functional class), a set of HPMS VMT fractions were applied to determine the VMT for each HPMS vehicle class type. The VMTs were summed over each HPMS vehicle class to determine the daily HPMS VMTs. The EPA conversion tool was then used to convert these daily VMT numbers to annual values. Table 12 shows the annual VMT for the Kentucky area over all analysis years.APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-26

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area 

### Table 10. West Virginia Area Annual VMT by HPMS Vehicle Class HPMSVtypeID yearID HPMSBaseYearVMT baseYearOffNetVMT

10 2005 7528013 0 20 2005 966958093 0 30 2005 230138467 0 40 2005 9176503 0 50 2005 49781926 0 60 2005 92710073 0 10 2008 7787346 0 20 2008 1000268940 0 30 2008 238066533 0 40 2008 9492625 0 50 2008 51496869 0 60 2008 95903853 0 10 2015 8279299 0 20 2015 1063459344 0 30 2015 253106008 0 40 2015 10092307 0 50 2015 54750102 0 60 2015 101962427 0 10 2022 9345073 0 20 2022 1200355849 0 30 2022 285687722 0 40 2022 11391464 0 50 2022 61797948 0 60 2022 115087799 0APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-27

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area 

### Table 11. Ohio Area Annual VMT by HPMS Vehicle Class HPMSVtypeID yearID HPMSBaseYearVMT baseYearOffNetVMT

10 2005 4230446 0 20 2005 754466644 0 30 2005 232789023 0 40 2005 2379414 0 50 2005 17589971 0 60 2005 41761823 0 10 2008 4360953 0 20 2008 777741625 0 30 2008 239970467 0 40 2008 2452818 0 50 2008 18132614 0 60 2008 43050158 0 10 2015 4886159 0 20 2015 871407965 0 30 2015 268871010 0 40 2015 2748220 0 50 2015 20316393 0 60 2015 48234849 0 10 2022 5576852 0 20 2022 994587493 0 30 2022 306877783 0 40 2022 3136699 0 50 2022 23188256 0 60 2022 55053178 0APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-28

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area 

### Table 12. Kentucky Area Annual VMT by HPMS Vehicle Class HPMSVtypeID yearID HPMSBaseYearVMT baseYearOffNetVMT

10 2005 4089356 0 20 2005 341756317 0 30 2005 99443539 0 40 2005 4446556 0 50 2005 23236805 0 60 2005 47017859 0 10 2008 3883519 0 20 2008 330674222 0 30 2008 94738580 0 40 2008 4340952 0 50 2008 22324145 0 60 2008 47661382 0 10 2015 4175112 0 20 2015 355212826 0 30 2015 102229743 0 40 2015 4717645 0 50 2015 24149076 0 60 2015 51635189 0 10 2022 4477945 0 20 2022 387223488 0 30 2022 111097489 0 40 2022 5265797 0 50 2022 26351915 0 60 2022 59200492 0 

### Daily VMT Fraction The EPA conversion tool for Annual Average Weekday Vehicles Miles Traveled was used to determine the daily VMT fraction for each analysis year. The daily VMT fractions were the same over all analysis years and areas, months of the year, and vehicle source types. DayIDs are included, indicating either weekday (dayID = 5) or weekend (dayID = 2) analysis. An excerpt of the table developed for the daily VMT fraction is shown as Table 13

. Table 13. Daily VMT Fractions, All Scenarios sourcetypeID monthID roadtypeID dayID dayVMTFraction

11 4 1 2.0 0.237635 11 4 1 5.0 0.762365 11 4 2 2.0 0.237635 11 4 2 5.0 0.762365 11 4 3 2.0 0.237635 11 4 3 5.0 0.762365 11 4 4 2.0 0.237635 11 4 4 5.0 0.762365 11 4 5 2.0 0.237635 11 4 5 5.0 0.762365APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-29

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area 

### Monthly VMT Fraction The EPA conversion tool for Annual Average Weekday Vehicles Miles Traveled was used to determine the monthly VMT fraction for each analysis year. The monthly VMT fractions are the same over each geographic area and vehicle source type. Monthly VMT fractions for 2005, 2015, and 2022 are all the same. Since 2008 is a leap year, the monthly VMT fractions are slightly different. For the month of April, the monthly VMT fraction is approximately 0.082098 for 2008, and 0.082302 for 2005, 2015, and 2022. Hourly VMT Fraction For Ohio and West Virginia, ODOT provided information for the hourly VMT fraction. This information consisted of hour of the day fractions for four roadway types (rural restricted, rural unrestricted, urban restricted, and urban unrestricted). This information was divided further for cars and trucks. To translate this information into the format needed for MOVES, a few assumptions were made. First, the default mix of off-network hourly distribution percentages was used for all vehicle classes. Second, the hourly distribution percentages for cars and trucks were separated into appropriate MOVES vehicle classes. The data for cars was used for vehicle types 11 (motorcycle), 21 (passenger car), 31 (passenger truck), and 32 (light commercial truck). The data for trucks was used for vehicle types 41 (intercity bus), 42 (transit bus), 43 (school bus), 51 (refuse truck), 52 (single unitshort-haul truck), 53 (single unit long-haul truck), 54 (motor home), 61 (combination shorthaul truck), and 62 (combination long-haul truck). Data was obtained for hourly VMT fractions in the Kentucky portion of the study area from the Kentucky Transportation Cabinet. Classification count data for District 9 was obtained that included 24-hour count data over a wide spectrum of roadway functional classes. This data was available by the FHWA Vehicle Class categorizations. To translate this information into the format needed for MOVES, a few assumptions were made. First, the default mix of off-network hourly distribution percentages was used for all vehicle classes. Second, the hourly distribution percentages for the FHWA Vehicle Classes were separated into their appropriate MOVES vehicle classes. Since the Boyd and Lawrence County areas being modeled do not contain any roadway facilities that would be designated as Urban Restricted, default data was also used for this class. Due to the large file size for these hourly distributions, the full input data sets are not shown here. Table 14shows an excerpt of the hourly distribution data from the West Virginia area in 2005.APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-30

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area 

### Table 14. Excerpt of Hourly VMT Fractions, West Virginia Area, 2005 sourceTypeID roadTypeID dayID hourID hourVMTFraction

11 1 5 1 0.009862 11 1 5 2 0.006272 11 1 5 3 0.005058 11 1 5 4 0.004667 11 1 5 5 0.006995 11 1 5 6 0.018494 11 1 5 7 0.045957 11 1 5 8 0.069644 11 1 5 9 0.060828 11 1 5 10 0.050286 11 1 5 11 0.049935 11 1 5 12 0.054365 11 1 5 13 0.057646 11 1 5 14 0.058032 11 1 5 15 0.062255 11 1 5 16 0.071005 11 1 5 17 0.076973 11 1 5 18 0.077432 11 1 5 19 0.059783 11 1 5 20 0.044392 11 1 5 21 0.035446 11 1 5 22 0.031824 11 1 5 23 0.024942 11 1 5 24 0.017907



### 2.5 Average Speed Distribution Importer This importer gives the user the opportunity to enter locally specific average speed data, disaggregated by vehicle source type, road type, weekday/weekend, and hour of the day. The MOVES model uses 16 speed bins, dividing speed distributions into a fraction of driving within each speed bin for each of the criteria listed previously. The Protocol Report indicated local data would be used for this analysis. Based on consultation with ODOT, default data was used instead.

2.6 Road Type Distribution Importer The road type distribution importer can be used to incorporate locally-specific roadway distribution information. Road type distribution information for this analysis was obtained from ODOT. This information was collected using 2009 HPMS data for Lawrence and Scioto Counties in Ohio and Cabell and Wayne Counties in West Virginia. This information was then cleaned and organized for conversion into the five MOVES roadway types. It is assumed that the data gathered for the four counties is representative not only of the partial county areas within West Virginia and Ohio, but also of Boyd and Lawrence Counties in Kentucky. Road type distributions were assumed to be the same for all analysis areas, analysis years, and vehicle source types. An excerpt of the road type distribution information is provided in Table 15

.APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-31

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area source TypeID road

TypeID roadType

VMTFraction 11 1 0 11 2 0.18 11 3 0.42 11 4 0.12 11 5 0.28 21 1 0 21 2 0.18 21 3 0.42 21 4 0.12 21 5 0.28 31 1 0 31 2 0.18 31 3 0.42 31 4 0.12 31 5 0.28 32 1 0 32 2 0.18 32 3 0.42 32 4 0.12 32 5 0.28 41 1 0 41 2 0.18 41 3 0.42 41 4 0.12 41 5 0.28 42 1 0 42 2 0.18 42 3 0.42 42 4 0.12 42 5 0.28 43 1 0 43 2 0.18 43 3 0.42 43 4 0.12 43 5 0.28 source TypeID road

TypeID roadType

VMTFraction 51 1 0 51 2 0.18 51 3 0.42 51 4 0.12 51 5 0.28 52 1 0 52 2 0.18 52 3 0.42 52 4 0.12 52 5 0.28 53 1 0 53 2 0.18 53 3 0.42 53 4 0.12 53 5 0.28 54 1 0 54 2 0.18 54 3 0.42 54 4 0.12 54 5 0.28 61 1 0 61 2 0.18 61 3 0.42 61 4 0.12 61 5 0.28 62 1 0 62 2 0.18 62 3 0.42 62 4 0.12 62 5 0.28 

### Table 15. Excerpt of Road Type Distribution DataAPPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-32

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area Year roadTypeID rampFraction 2005 2 0.085 2005 4 0.085 2008 2 0.087 2008 4 0.087 2015 2 0.092 2015 4 0.092 2022 2 0.097 2022 4 0.097 Year roadTypeID rampFraction 2005 2 0.085 2005 4 0.085 2008 2 0.081 2008 4 0.081 2015 2 0.085 2015 4 0.085 2022 2 0.093 2022 4 0.093

Year roadTypeID rampFraction 2005 2 0.056 2005 4 0.056 2008 2 0.056 2008 4 0.056 2015 2 0.056 2015 4 0.056 2022 2 0.056 2022 4 0.056 

### 2.7 Ramp Fraction Importer This importer allows the user to input the percentage of traffic on urban restricted and rural restricted roadways that is traveling on ramp facilities. The Protocol Report indicated that ramp fractions would need to be considered outside of MOVES due to model limitations. However, the MOVES2010a platform addresses these limitations, thereby allowing ramps to be considered within the model. To determine this factor, data was obtained from both the KYOVA Regional Travel Demand Model as well as the Ashland Regional Travel Demand Model for their respective parts of the study area. Lawrence County, OH data from the travel demand model was used to represent all of the Ohio area. Information from Cabell and Wayne Counties, WV was summed to determine the overall percentage for the West Virginia area. These numbers were determined using VHT information forecasted in each of the analysis years. Tables 16 and 17 show the ramp fractions for West Virginia and Ohio, respectively. Information obtained from Boyd County was used to represent all of the Kentucky area. Since the portion of Lawrence County, KY being modeled does not contain any restricted access facilities, the information from Boyd accurately represents the entire area. A ramp fraction of 5.6% was applied for this area, pulled from the data gathered for previous Mobile6 runs in the area. This fraction was applied to all study years. Table 18shows the ramp fractions for Kentucky. Table 16. West Virginia Ramp Fractions Table 17. Ohio Ramp Fractions

Table 18. Kentucky Ramp FractionsAPPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-33

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area countyID fuelYearID monthGroupID fuelFormulationID marketShare marketShareCV 99001 2005 4 5661 0.03 0.5 99001 2005 4 6099 0.1658 0.5 99001 2005 4 4950 0.8042 0.5 99001 2005 4 20311 1 0.5 99001 2008 4 2451 0.428571 0.5 99001 2008 4 7852 0.571429 0.5 99001 2008 4 20043 1 0.5 99001 2012 4 3930 1 0.5 99001 2012 4 20011 1 0.5 

### 2.8 Fuel Formulation and Fuel Supply Importer The fuel formulation and fuel supply importers are used to input locally-specific fuel properties into the model. The Protocol Report stated that default information would be used for this category. Default files were used for fuel supply for WV and OH, while default files were used for fuel formulation in all three states. The availability of locally-specific fuel supply data for Kentucky resulted in a customized file for that area. Since default files are created specific to county, separate default files were used to obtain the needed information for Kentucky, Ohio, and West Virginia. The West Virginia default file was from Cabell County, assumed for this analysis as representative of the entire WV analysis area. The Ohio default file was from Lawrence County, assumed for this analysis as representative of the entire OH analysis area. One modification was made to the 2005 fuel supply, changing the fuel formulation ID from 20317 to 20311. This provided the proper sulfur content reference for 2005. The other years had accurate sulfur content information in their default file. Direction for this modification came from ODOT. The Kentucky default file for fuel formulation was from Boyd County. The Kentucky Division for Air Quality supplied fuel supply information for the Kentucky portion of the analysis area. Data provided was for 2008, but is also expected to appropriately represent the fuel supply conditions in 2005, 2015, and 2022. As referenced above, the Kentucky default file developed using Boyd County information was used to develop fuel supply data for all model years. Tables 19-21 provide the fuel supply information used for West Virginia, Ohio, and Kentucky, respectively. Since default fuel formulation data was used for all areas, that information is not displayed within this report. Table 19. West Virginia Fuel Supply Data (same beginning in 2012)APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-34

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area countyID fuelYearID monthGroupID fuelFormulationID marketShare marketShareCV 99002 2005 4 6146 0.102668 0.5 99002 2005 4 1060 0.247235 0.5 99002 2005 4 5010 0.650096 0.5 99002 2005 4 20311 1 0.5 99002 2008 4 7775 0.432171 0.5 99002 2008 4 2380 0.567829 0.5 99002 2008 4 20043 1 0.5 99002 2012 4 3883 1 0.5 99002 2012 4 20011 1 0.5 

### Table 20. Ohio Fuel Supply Data (same beginning in 2012)

Table 21. Kentucky Fuel Supply Data (same for all years) countyID fuelYearID monthGroupID fuelFormulationID marketShare marketShareCV 99003 2005 4 20043 1 0.5 99003 2005 4 2337 0.428571 0.5 99003 2005 4 7736 0.571429 0.5



### 2.9 Inspection and Maintenance (I/M) Importer This importer would allow local inspection and maintenance data to be entered for the study area. The Huntington-Ironton-Ashland non-attainment area has no I/M program in place. When default data is exported for this, the file indicates there are no I/M programs in place for the area. Since this is an accurate representation of the I/M program in the area, no further data was entered.

2.10 Zone Road Activity Importer This importer is required for use if the geographic area has been generated using the Custom Domain option. The default file for zone road activity was exported for use in this category, and was then modified to reflect the custom domain numbers established earlier in the MOVES run. Tables 22-24show the zone road activity data entered for West Virginia, Ohio, and Kentucky, respectively. Values for zone road activity data are the same for all analysis years. Table 22. West Virginia Zone Road Activity Data zoneID roadTypeID SHOAllocFactor 990010 1 1 990010 2 1 990010 3 1 990010 4 1 990010 5 1APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-35

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area 

### Table 23. Ohio Zone Road Activity Data zoneID roadTypeID SHOAllocFactor 990020 1 1 990020 2 1 990020 3 1 990020 4 1 990020 5 1 

### Table 24. Kentucky Zone Road Activity Data zoneID roadTypeID SHOAllocFactor 990030 1 1 990030 2 1 990030 3 1 990030 4 1 990030 5 1



### 3.0 Post-Processing of MOVES Output Once the appropriate data was input into the MOVES Runspecs and the County Data Manager, the 12 scenarios were run using the MOVES program. The following MOVES output databases were produced:

x westvirginia_2005_out2

x westvirginia_2008_out2

x westvirginia_2015_out2

x westvirginia_2022_out2 x ohio_2005_out2

x ohio_2008_out2

x ohio_2015_out2

x ohio_2022_out2 x kentucky_2005_out2

x kentucky_2008_out2

x kentucky_2015_out2

x kentucky_2022_out2 Since the emission rates method was used for this analysis, only two tables within each output database are used. The tables are called rateperdistance and ratepervehicle. Ultimately, information from both tables will be used to determine overall emissions, aggregating the information for the running emissions (rateperdistance) and idling emissions (ratepervehicle). The rateperdistance table for each output database contains 299,520 records, while the ratepervehicle table for each output database contains 4,056 records. The rateperdistance and ratepervehicle tables all represent scenarios for one geographic area (West Virginia, Ohio, or Kentucky), one analysis year (2005, 2008, 2015, or 2022), one month (April), and one day type (weekdays). Results within the rateperdistance tables are disaggregated by hour of the day, pollutant type, process type, vehicle source type, roadway type, and speed category. Temperature and relative humidity data vary by the hour of the day. Results within the ratepervehicle tables are disaggregated by hour of the day, pollutant type, process type, and vehicle source type. Temperature data within these tables varies by the hour of the day. The final output desired for this analysis summarizes the total emissions by pollutant type for each analysis year and geographic area. As a result, the information contained in each scenario’s rateperdistance and ratepervehicle has to be matched with corresponding vehicle miles traveled (VMT) and source population data. To do this, a set of supporting tables were created that match these criteria with information contained in the rateperdistance andAPPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-36

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area 

### ratepervehicle tables such as vehicle source types, road types, speed categories, and hour of the day. The creation of those tables and the process used to calculate total emissions are detailed in the subsequent sections.

3.1 VMT and Source Type by County This table displays the daily and annual VMTs and the source type population for all of the counties and analysis years in this effort. The daily VMTs were pulled for each area from the spreadsheets used to develop the HPMS vehicle type VMTs. Annual VMTs for each county were determined using the EPA converter spreadsheet. Source types for each state’s area were broken out by county, and then forecasted for each analysis year using the 0.8% growth rate established in the Protocol Report. Table 25 shows the VMT and source type population information for each county and analysis year.

3.2 Source Type Population Fraction and VMT Fraction This table separates the vehicle population into the different source types, and then determines the fraction of the population represented in each type as well as the fraction of total VMT represented in each type. The source type populations were pulled from the local data used for the MOVES runs. Within the MOVES format, VMTs were gathered by the six HPMS vehicle classes rather than the 13 MOVES source types. As a result, a translation was needed to match up the appropriate HPMS vehicle classes with the MOVES source types. One the two classification types were matched to one another, the source type fractions established based on the vehicle populations were used to factor VMTs of different source type classifications that fell within the same HPMS vehicle class. Table 26shows the source type population fractions and VMT fractions for each state’s area and the four analysis years.

3.3 Hourly Distribution Fractions This table provides the hourly VMT fractions, separated out by source type, road type, hour of the day, and state. Hourly distribution fractions were pulled from the table created for use in the MOVES program. Distribution fractions remain consistent for all analysis years. Due to the size of the input table, only an excerpt of this information is shown in the body of this report. Table 27 shows the hourly distribution fractions for each of the three states for vehicle source type 21 (passenger cars) and roadway type 2 (rural restricted access).

3.4 Road Type Distribution Fractions This table provides the road type VMT fractions separated by vehicle source types. Road type fractions were pulled directly from the MOVES input file developed earlier. It should be noted that road type distribution fractions have been assumed to be equal for all geographic areas of this study. Table 28 shows the road type distribution fractions.

3.5 Average Speed Distribution Fractions This table provides the average speed fraction sorted by source type, road type, hour of the day, and speed class. This file is the same as the MOVES input file used earlier in this analysis. As stated previously, the same average speed distribution is used for each geographic area. Due to the size of the input table, only an excerpt of this information is shown in the body of the report. Table 29 shows the average speed distribution fractions for vehicle source type 21 (passenger cars), road type 3 (rural unrestricted access), and hour 1 (hour beginning at midnight).APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-37

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area 

### Table 25. VMT and Source Type Population by County and Year County State Full/Partial Year Daily VMT Annual VMT Source Type Pop Cabell WV Full 2005 2,808,750 960,538,915 73,091 Cabell WV Full 2008 2,885,502 989,243,546 74,874 Cabell WV Full 2015 3,096,762 1,059,033,672 79,033 Cabell WV Full 2022 3,336,065 1,140,870,563 83,193 Wayne WV Full 2005 1,139,180 389,577,827 25,446 Wayne WV Full 2008 1,187,259 407,030,689 26,067 Wayne WV Full 2015 1,241,619 424,609,965 27,515 Wayne WV Full 2022 1,560,054 533,508,781 28,963 Mason WV Partial 2005 18,060 6,176,333 2,244 Mason WV Partial 2008 19,665 6,741,932 2,299 Mason WV Partial 2015 23,410 8,005,850 2,427 Mason WV Partial 2022 27,155 9,286,512 2,555 Lawrence OH Full 2005 1,315,020 449,711,752 72,392 Lawrence OH Full 2008 1,334,081 457,366,121 74,172 Lawrence OH Full 2015 1,470,988 503,049,909 78,325 Lawrence OH Full 2022 1,742,638 595,949,049 82,480 Scioto OH Full 2005 1,616,940 552,962,632 88,852 Scioto OH Full 2008 1,678,238 575,354,151 91,039 Scioto OH Full 2015 1,915,776 655,158,989 96,136 Scioto OH Full 2022 2,131,162 728,816,580 101,235 Adams OH Partial 2005 99,565 34,049,176 2,098 Adams OH Partial 2008 103,978 35,647,156 2,150 Adams OH Partial 2015 114,277 39,080,671 2,270 Adams OH Partial 2022 124,576 42,602,717 2,391 Gallia OH Partial 2005 48,230 16,493,759 1,021 Gallia OH Partial 2008 50,582 17,341,207 1,046 Gallia OH Partial 2015 56,070 19,175,027 1,105 Gallia OH Partial 2022 61,559 21,051,915 1,163 Boyd KY Full 2005 1,429,198 488,758,339 49,199 Boyd KY Full 2008 1,380,484 473,274,668 50,429 Boyd KY Full 2015 1,494,083 510,947,840 53,299 Boyd KY Full 2022 1,640,241 560,930,984 56,169 Lawrence KY Partial 2005 91,327 31,232,092 3,070 Lawrence KY Partial 2008 88,522 30,348,132 3,147 Lawrence KY Partial 2015 91,151 31,171,751 3,326 Lawrence KY Partial 2022 95,579 32,686,140 3,505APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-38

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area 

### Table 26. Source Type Population Fractions and VMT Fractions by State and Year

State Source Type Source Type ID Source Type

Population Source Type

Fraction Source Type

VMT Fraction WV Motorcycle 11 2779 0.02757 0.00555 WV Passenger Car 21 43487 0.43150 0.71294 WV Passenger Truck 31 42860 0.42528 0.14593 WV Light Commercial Truck 32 6975 0.06921 0.02375 WV Intercity Bus 41 61 0.00061 0.00126 WV Transit Bus 42 33 0.00033 0.00069 WV School Bus 43 234 0.00232 0.00481 WV Refuse Truck 51 42 0.00042 0.00052 WV Single Unit Short-haul Truck 52 2535 0.02515 0.03110 WV Single Unit Long-haul Truck 53 289 0.00287 0.00355 WV Motor Home 54 125 0.00124 0.00154 WV Combination Short-haul Truck 61 644 0.00639 0.03240 WV Combination Long-haul Truck 62 715 0.00709 0.03596 OH Motorcycle 11 10638 0.06336 0.00402 OH Passenger Car 21 103050 0.61373 0.71634 OH Passenger Truck 31 46653 0.27785 0.21575 OH Light Commercial Truck 32 1140 0.00679 0.00527 OH Intercity Bus 41 32 0.00019 0.00014 OH Transit Bus 42 3 0.00002 0.00001 OH School Bus 43 474 0.00282 0.00210 OH Refuse Truck 51 20 0.00012 0.00006 OH Single Unit Short-haul Truck 52 362 0.00216 0.00112 OH Single Unit Long-haul Truck 53 120 0.00071 0.00037 OH Motor Home 54 4885 0.02909 0.01514 OH Combination Short-haul Truck 61 248 0.00148 0.01848 OH Combination Long-haul Truck 62 284 0.00169 0.02117 KY Motorcycle 11 2222 0.04252 0.00786 KY Passenger Car 21 25145 0.48106 0.65724 KY Passenger Truck 31 18687 0.35751 0.14690 KY Light Commercial Truck 32 5640 0.10790 0.04434 KY Intercity Bus 41 9 0.00017 0.00095 KY Transit Bus 42 27 0.00051 0.00285 KY School Bus 43 45 0.00085 0.00475 KY Refuse Truck 51 7 0.00014 0.00118 KY Single Unit Short-haul Truck 52 229 0.00438 0.03698 KY Single Unit Long-haul Truck 53 16 0.00030 0.00253 KY Motor Home 54 25 0.00047 0.00399 KY Combination Short-haul Truck 61 121 0.00231 0.04992 KY Combination Long-haul Truck 62 98 0.00187 0.04050 2005APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-39

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area State Source Type Source Type ID Source Type

Population Source Type

Fraction Source Type

VMT Fraction WV Motorcycle 11 2847 0.02757 0.00555 WV Passenger Car 21 44548 0.43150 0.71294 WV Passenger Truck 31 43905 0.42528 0.14593 WV Light Commercial Truck 32 7146 0.06921 0.02375 WV Intercity Bus 41 63 0.00061 0.00126 WV Transit Bus 42 34 0.00033 0.00069 WV School Bus 43 240 0.00232 0.00481 WV Refuse Truck 51 43 0.00042 0.00052 WV Single Unit Short-haul Truck 52 2597 0.02515 0.03110 WV Single Unit Long-haul Truck 53 296 0.00287 0.00355 WV Motor Home 54 128 0.00124 0.00154 WV Combination Short-haul Truck 61 660 0.00639 0.03240 WV Combination Long-haul Truck 62 732 0.00709 0.03596 OH Motorcycle 11 10899 0.06335 0.00402 OH Passenger Car 21 105584 0.61373 0.71634 OH Passenger Truck 31 47800 0.27785 0.21575 OH Light Commercial Truck 32 1168 0.00679 0.00527 OH Intercity Bus 41 33 0.00019 0.00014 OH Transit Bus 42 3 0.00002 0.00001 OH School Bus 43 486 0.00282 0.00210 OH Refuse Truck 51 20 0.00012 0.00006 OH Single Unit Short-haul Truck 52 371 0.00216 0.00112 OH Single Unit Long-haul Truck 53 123 0.00071 0.00037 OH Motor Home 54 5005 0.02909 0.01515 OH Combination Short-haul Truck 61 254 0.00148 0.01848 OH Combination Long-haul Truck 62 291 0.00169 0.02117 KY Motorcycle 11 2278 0.04252 0.00771 KY Passenger Car 21 25773 0.48106 0.65659 KY Passenger Truck 31 19154 0.35751 0.14450 KY Light Commercial Truck 32 5781 0.10790 0.04361 KY Intercity Bus 41 9 0.00017 0.00096 KY Transit Bus 42 27 0.00051 0.00287 KY School Bus 43 46 0.00085 0.00479 KY Refuse Truck 51 7 0.00014 0.00117 KY Single Unit Short-haul Truck 52 234 0.00438 0.03669 KY Single Unit Long-haul Truck 53 16 0.00030 0.00251 KY Motor Home 54 25 0.00047 0.00396 KY Combination Short-haul Truck 61 124 0.00231 0.05225 KY Combination Long-haul Truck 62 100 0.00187 0.04239 2008APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-40

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area State Source Type Source Type ID Source Type

Population Source Type

Fraction Source Type

VMT Fraction WV Motorcycle 11 3005 0.02757 0.00555 WV Passenger Car 21 47023 0.43150 0.71294 WV Passenger Truck 31 46345 0.42528 0.14593 WV Light Commercial Truck 32 7543 0.06921 0.02375 WV Intercity Bus 41 66 0.00061 0.00126 WV Transit Bus 42 36 0.00033 0.00069 WV School Bus 43 253 0.00232 0.00481 WV Refuse Truck 51 46 0.00042 0.00052 WV Single Unit Short-haul Truck 52 2741 0.02515 0.03110 WV Single Unit Long-haul Truck 53 313 0.00287 0.00355 WV Motor Home 54 136 0.00124 0.00154 WV Combination Short-haul Truck 61 697 0.00639 0.03240 WV Combination Long-haul Truck 62 773 0.00709 0.03596 OH Motorcycle 11 11510 0.06336 0.00402 OH Passenger Car 21 111497 0.61373 0.71634 OH Passenger Truck 31 50477 0.27785 0.21576 OH Light Commercial Truck 32 1233 0.00679 0.00527 OH Intercity Bus 41 34 0.00019 0.00014 OH Transit Bus 42 3 0.00002 0.00001 OH School Bus 43 513 0.00282 0.00211 OH Refuse Truck 51 22 0.00012 0.00006 OH Single Unit Short-haul Truck 52 392 0.00216 0.00112 OH Single Unit Long-haul Truck 53 130 0.00072 0.00037 OH Motor Home 54 5285 0.02909 0.01514 OH Combination Short-haul Truck 61 268 0.00148 0.01845 OH Combination Long-haul Truck 62 308 0.00170 0.02120 KY Motorcycle 11 2408 0.04252 0.00770 KY Passenger Car 21 27240 0.48106 0.65523 KY Passenger Truck 31 20244 0.35751 0.14485 KY Light Commercial Truck 32 6110 0.10790 0.04372 KY Intercity Bus 41 10 0.00017 0.00097 KY Transit Bus 42 29 0.00051 0.00290 KY School Bus 43 48 0.00085 0.00483 KY Refuse Truck 51 8 0.00014 0.00118 KY Single Unit Short-haul Truck 52 248 0.00438 0.03687 KY Single Unit Long-haul Truck 53 17 0.00030 0.00252 KY Motor Home 54 27 0.00047 0.00398 KY Combination Short-haul Truck 61 131 0.00231 0.05259 KY Combination Long-haul Truck 62 106 0.00187 0.04266 2015APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-41

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area State Source Type Source Type ID Source Type

Population Source Type

Fraction Source Type

VMT Fraction WV Motorcycle 11 3163 0.02757 0.00555 WV Passenger Car 21 49497 0.43150 0.71294 WV Passenger Truck 31 48784 0.42528 0.14593 WV Light Commercial Truck 32 7940 0.06921 0.02375 WV Intercity Bus 41 70 0.00061 0.00126 WV Transit Bus 42 38 0.00033 0.00069 WV School Bus 43 266 0.00232 0.00481 WV Refuse Truck 51 48 0.00042 0.00052 WV Single Unit Short-haul Truck 52 2885 0.02515 0.03110 WV Single Unit Long-haul Truck 53 329 0.00287 0.00355 WV Motor Home 54 143 0.00124 0.00154 WV Combination Short-haul Truck 61 733 0.00639 0.03240 WV Combination Long-haul Truck 62 814 0.00709 0.03596 OH Motorcycle 11 12120 0.06335 0.00402 OH Passenger Car 21 117410 0.61373 0.71634 OH Passenger Truck 31 53154 0.27785 0.21576 OH Light Commercial Truck 32 1298 0.00678 0.00527 OH Intercity Bus 41 36 0.00019 0.00014 OH Transit Bus 42 3 0.00002 0.00001 OH School Bus 43 540 0.00282 0.00211 OH Refuse Truck 51 23 0.00012 0.00006 OH Single Unit Short-haul Truck 52 412 0.00215 0.00112 OH Single Unit Long-haul Truck 53 137 0.00072 0.00037 OH Motor Home 54 5566 0.02909 0.01514 OH Combination Short-haul Truck 61 282 0.00147 0.01845 OH Combination Long-haul Truck 62 324 0.00169 0.02120 KY Motorcycle 11 2537 0.04252 0.00754 KY Passenger Car 21 28707 0.48106 0.65231 KY Passenger Truck 31 21334 0.35751 0.14376 KY Light Commercial Truck 32 6439 0.10790 0.04339 KY Intercity Bus 41 10 0.00017 0.00099 KY Transit Bus 42 31 0.00051 0.00296 KY School Bus 43 51 0.00085 0.00493 KY Refuse Truck 51 8 0.00014 0.00118 KY Single Unit Short-haul Truck 52 261 0.00438 0.03674 KY Single Unit Long-haul Truck 53 18 0.00030 0.00251 KY Motor Home 54 28 0.00047 0.00397 KY Combination Short-haul Truck 61 138 0.00231 0.05506 KY Combination Long-haul Truck 62 112 0.00187 0.04467 2022APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-42

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area 

### Table 27. Excerpt of Hourly Distribution Fractions by State WV OH KY Source Type ID Road

Type ID Hour ID Hour VMT

Fraction Hour VMT

Fraction Hour VMT

Fraction 21 2 1 0.00890 0.00890 0.00942 21 2 2 0.00564 0.00564 0.00760 21 2 3 0.00424 0.00424 0.00600 21 2 4 0.00427 0.00427 0.00691 21 2 5 0.00695 0.00695 0.01320 21 2 6 0.01798 0.01798 0.02545 21 2 7 0.03806 0.03806 0.04436 21 2 8 0.05700 0.05700 0.05558 21 2 9 0.05773 0.05773 0.05484 21 2 10 0.05538 0.05538 0.05294 21 2 11 0.05554 0.05554 0.05365 21 2 12 0.05558 0.05558 0.05484 21 2 13 0.05584 0.05584 0.05766 21 2 14 0.06051 0.06051 0.06160 21 2 15 0.06765 0.06765 0.07013 21 2 16 0.07755 0.07755 0.07870 21 2 17 0.08428 0.08428 0.08010 21 2 18 0.07970 0.07970 0.07385 21 2 19 0.06012 0.06012 0.05386 21 2 20 0.04522 0.04522 0.04211 21 2 21 0.03646 0.03646 0.03548 21 2 22 0.02912 0.02912 0.02902 21 2 23 0.02142 0.02142 0.01944 21 2 24 0.01486 0.01486 0.01325APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-43

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area Source Type ID Road

Type ID Road Type

VMT Fraction 11 1 0 11 2 0.18 11 3 0.42 11 4 0.12 11 5 0.28 21 1 0 21 2 0.18 21 3 0.42 21 4 0.12 21 5 0.28 31 1 0 31 2 0.18 31 3 0.42 31 4 0.12 31 5 0.28 32 1 0 32 2 0.18 32 3 0.42 32 4 0.12 32 5 0.28 41 1 0 41 2 0.18 41 3 0.42 41 4 0.12 41 5 0.28 42 1 0 42 2 0.18 42 3 0.42 42 4 0.12 42 5 0.28 43 1 0 43 2 0.18 43 3 0.42 43 4 0.12 43 5 0.28 Source Type ID Road

Type ID Road Type

VMT Fraction 51 1 0 51 2 0.18 51 3 0.42 51 4 0.12 51 5 0.28 52 1 0 52 2 0.18 52 3 0.42 52 4 0.12 52 5 0.28 53 1 0 53 2 0.18 53 3 0.42 53 4 0.12 53 5 0.28 54 1 0 54 2 0.18 54 3 0.42 54 4 0.12 54 5 0.28 61 1 0 61 2 0.18 61 3 0.42 61 4 0.12 61 5 0.28 62 1 0 62 2 0.18 62 3 0.42 62 4 0.12 62 5 0.28 

### Table 28. Road Type Distribution FractionsAPPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-44

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area 

### Table 29. Excerpt of Average Speed Distribution Fractions Source Type ID Road

Type ID Hour ID Average

Speed Bin ID Average Speed

Fraction 21 3 1 1 0.00226828 21 3 1 2 0.0105519 21 3 1 3 0.0170857 21 3 1 4 0.0381731 21 3 1 5 0.0460688 21 3 1 6 0.0245757 21 3 1 7 0.0420755 21 3 1 8 0.0564427 21 3 1 9 0.164311 21 3 1 10 0.157075 21 3 1 11 0.171162 21 3 1 12 0.10283 21 3 1 13 0.0851272 21 3 1 14 0.0441349 21 3 1 15 0.0286281 21 3 1 16 0.00948987



### 3.6 Aggregation Tables Once the supporting tables were created, the information within them needed to be combined in a way that matched the independent variables shown in the rateperdistance and ratepervehicle tables. Due to the large number of records and computations required to perform this exercise, some sort of advanced database and/or scripting tool was necessary. Since the KYOVA Regional Travel Demand Model is in the process of being converted to the TransCAD platform, it was determined that a programming script developed and run in TransCAD would be an effective way to summarize this information. In an effort to create a step within this scripting process that could later be referenced and checked, two intermediate tables were developed. The tables developed were designated as the VMT Summary Table and the Source Type Population Summary Table. Each table’s intent and composition is described below, along with an example of the information produced within the tables. VMT Summary Table The VMT Summary Table contains many of the same independent variables found in the rateperdistance output tables; namely, state, analysis year, source type, road type, hour of the day, and average speed bin. This table further divides the information by the individual counties in the analysis. The intent of this table is to determine the proportion of daily and annual VMT for a given county and analysis year that is represented within each combination of vehicle source type, road type, hour of the day, and speed category. This table references the source type VMT fraction generated in the Source Type Population Fraction and VMT Fraction table, the road type VMT fraction generated in the Road Type Distribution table, the hour VMT fraction generated in the Hourly Distribution FractionsAPPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-45

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area 

### table, and the average speed fraction from the Average Speed Distribution Fraction table. These four values are multiplied together to determine an overall fraction, which is then multiplied by the corresponding daily and annual VMT established in the VMT and Source Type table. When the daily VMT proportions and annual VMT proportions are summed for a particular county and analysis year combination, they will equal the corresponding VMT values shown in the VMT and Source Type table. Source Type Population Summary Table The Source Type Population Summary Table contains many of the same independent variables found in the ratepervehicle output tables; namely, state, analysis year, source type, road type, and hour of the day. This table further divides the information by the individual counties in the analysis. The intent of this table is to determine the proportion of the source type population for a given county and analysis year that is represented within each combination of vehicle source type, road type, and hour of the day. This table references the source type population fraction generated in the Source Type Population and VMT Fraction table and the hour VMT fraction generated in the Hourly Distribution Fractions table. These two values are multiplied together to get an overall fraction, which is then multiplied by the corresponding source type population information found in the VMT and Source Type table. The population proportion, when summed for a particular county and analysis year combination, should be equal to the corresponding source type population value shown in the VMT and Source Type table.

3.7 Summarizing Results As mentioned in the previous section, a TransCAD script was developed to quickly match the information in the rateperdistance and ratepervehicle tables with corresponding VMT and source type population information. This script also summed the matched information by county, analysis year, and pollutant type to create the final output format needed for this process. The script created for this process is included as Figure 1below. Results from this script are produced in a form that is easily formatted to show the overall emissions information contained in the main body of this report. Figure 1. TransCAD Script for Post-Processing MOVES Output

macro "KYOVA MOVES PP" runmacro("G30 File Close All")

//constants States = {"WV", "OH", "KY"} Counties = {"Cabell_WV", "Wayne_WV", "Mason_WV", "Lawrence_OH", "Scioto_OH", "Adams_OH", "Gallia_OH","Boyd_KY", "Lawrence_KY"} Years = {2005, 2008, 2015, 2022} SourceTypes = {11,21,31,32,41,42,43,51,52,53,54,61,62} RoadTypes = {1,2,3,4,5} Hours = {1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24} Speeds = {1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16} Pollutants = {3,31,110,111,112,115,116,117} Pollutant_Names = {"Oxides of Nitrogen (NOx)",

"Sulfur Dioxide (SO2)", "Primary Exhaust PM2.5 - Total",APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-46

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area "Primary PM2.5 - Organic Carbon", "Primary PM2.5 - Elemental Carbon", "Primary PM2.5 - Sulfate Particulate", "Primary PM2.5 - Brakewear Particulate", "Primary PM2.5 - Tirewear Particulate"} path = SplitPath(GetInterface()) in_vmt_bin = path[1]+path[2]+"VMT Source Type By County.bin" in_source_type_bin = path[1]+path[2]+"Source Type Pop VMT Fraction.bin" in_hourly_bin = path[1]+path[2]+"Hourly Distribution Fractions.bin" in_road_type_bin = path[1]+path[2]+"Road Type Distribution.bin" in_speed_bin = path[1]+path[2]+"Average Speed Distribution.bin" out_vmt_summary = path[1]+path[2]+"Summary_VMT.bin" out_veh_summary = path[1]+path[2]+"Summary_VEHICLE.bin" out_em_vmt_summary = path[1]+path[2]+"Summary_VMT_County.bin" out_em_veh_summary = path[1]+path[2]+"Summary_VEH_County.bin" out_em_total_summary = path[1]+path[2]+"Summary_Total_Emissions.bin" CreateProgressBar("MOVES Post Processor.......", "TRUE") UpdateProgressBar("Computing fractions.......", 10) ///--------------------------------Summarize VMT, write results to summary table--------------------------------- vw_vmt =OpenTable("VMT", "FFB", {in_vmt_bin,}) vw_st =OpenTable("ST", "FFB", {in_source_type_bin,}) vw_hr =OpenTable("HR", "FFB", {in_hourly_bin,}) vw_rt =OpenTable("RT", "FFB", {in_road_type_bin,}) vw_spd =OpenTable("SPD", "FFB", {in_speed_bin,}) // ----------------primary keys //vw_vmt Year County State //vw_st Year State Source Type ID //vw_hr State Source Type ID Road Type ID Hour ID //vw_rt Source Type ID Road Type ID //vw_spd Source Type ID Road Type ID Hour ID Speed Bin ID //---------------- jv1 = JoinViewsMulti("JV1", {vw_vmt+".Year", vw_vmt+".State"}, {vw_st+".Year", vw_st+".State"}, {{"O", }}) jv2 = JoinViewsMulti("JV2", {jv1+"."+vw_vmt+".State", jv1+".[Source Type ID]"}, {vw_hr+".State", vw_hr+".[Source Type ID]"}, {{"O", }}) jv3 = JoinViewsMulti("JV3", {jv2+"."+vw_hr+".[Source Type ID]", jv2+".[Road Type ID]"}, {vw_rt+".[Source Type ID]", vw_rt+".[Road Type ID]"}, {{"O", }}) jv4 = JoinViewsMulti("JV4", {jv3+"."+vw_hr+".[Source Type ID]", jv3+"."+vw_hr+".[Road Type ID]", jv3+".[Hour ID]"}, {vw_spd+".[Source Type ID]", vw_spd+".[Road Type ID]", vw_spd+".[Hour ID]"}, {{"O", }})

//-------------------VMT Table kept_fields = {jv4+"."+vw_vmt+".Year", jv4+".County", jv4+"."+vw_vmt+".State", jv4+".[Daily VMT]", jv4+".[Annual VMT]", jv4+"."+vw_st+".[Source Type ID]", jv4+".[Source Type VMT Fraction]",APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-47

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area jv4+"."+vw_hr+".[Road Type ID]", jv4+"."+vw_hr+".[Hour ID]", jv4+".[Hour VMT Fraction]", jv4+".[Road Type VMT Fraction]", jv4+".[Average Speed Bin ID]", jv4+".[Average Speed Fraction]" } idx_fields = {jv4+"."+vw_vmt+".Year", jv4+".County", jv4+"."+vw_vmt+".State", jv4+"."+vw_st+".[Source Type ID]", jv4+"."+vw_hr+".[Road Type ID]", jv4+"."+vw_hr+".[Hour ID]", jv4+".[Average Speed Bin ID]" } add_fields = {{"Combined Factor", "Real", 24,4,}, {"Daily VMT Proportion", "Real", 24,4,}, {"Annual VMT Proportion", "Real", 24,4,}, {"Aggregation_Key", "String", 32,0,}, {"Aggregation_Key_CTY", "String", 32,0,} } for p = 1 to Pollutants.length do add_fields = add_fields + {{"RatePerDist_"+i2s(Pollutants[p]), "Real", 24,4,}, {"Daily_Emission_RatePerDist_"+i2s(Pollutants[p]), "Real", 24,4,}, {"Annual_Emission_RatePerDist_"+i2s(Pollutants[p]), "Real", 24,4,}} end // SetView(jv4) // SelectByQuery("No_RT_1", "Several", "Select * where [Road Type ID] <> 1",) ExportView(jv4+"|", "FFB", out_vmt_summary, kept_fields,{{"Additional Fields", add_fields},{"Indexed Fields",idx_fields}}) //-------------------Vehicle Pop Table kept_fields = {jv3+"."+vw_vmt+".Year", jv3+".County", jv3+"."+vw_vmt+".State", jv3+".[Source Type Pop]", jv3+"."+vw_st+".[Source Type ID]", jv3+".[Source Type Fraction]", jv3+"."+vw_hr+".[Road Type ID]", jv3+"."+vw_hr+".[Hour ID]", jv3+".[Hour VMT Fraction]" } idx_fields = {jv3+"."+vw_vmt+".Year", jv3+".County", jv3+"."+vw_vmt+".State", jv3+"."+vw_st+".[Source Type ID]", jv3+"."+vw_hr+".[Road Type ID]", jv3+"."+vw_hr+".[Hour ID]" } add_fields = {{"Combined Factor", "Real", 24,4,}, {"Population Proportion", "Real", 24,4,}, {"Aggregation_Key", "String", 32,0,}, {"Aggregation_Key_CTY", "String", 32,0,}APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-48

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area } for p = 1 to Pollutants.length do add_fields = add_fields + {{"RatePerVeh_"+i2s(Pollutants[p]), "Real", 24,4,}, {"Daily_Emission_RatePerVeh_"+i2s(Pollutants[p]), "Real", 24,4,}, {"Annual_Emission_RatePerVeh_"+i2s(Pollutants[p]), "Real", 24,4,}} end ExportView(jv3+"|", "FFB", out_veh_summary, kept_fields,{{"Additional Fields", add_fields}, {"Indexed Fields",idx_fields}}) CloseView(jv4) CloseView(jv3) CloseView(jv2) CloseView(jv1) CloseView(vw_vmt) CloseView(vw_st) CloseView(vw_hr) CloseView(vw_rt) CloseView(vw_spd)

//---------------------------VMT calculation UpdateProgressBar("Computing VMT.......", 20) order = {"Sort Order", {{"Year", "Ascending"},{"County", "Ascending"},{"State", "Ascending"},{"[Source Type ID]", "Ascending"},{"[Road Type ID]", "Ascending"},{"[Hour ID]", "Ascending"},{"[Average Speed Bin ID]", "Ascending"}}} vw_vmt =OpenTable("VMT", "FFB", {out_vmt_summary,}) st_frac = GetDataVector(vw_vmt+"|", "[Source Type VMT Fraction]",{order}) hr_frac = GetDataVector(vw_vmt+"|", "[Hour VMT Fraction]",{order}) rt_frac = GetDataVector(vw_vmt+"|", "[Road Type VMT Fraction]",{order}) spd_frac = GetDataVector(vw_vmt+"|", "[Average Speed Fraction]",{order}) combo_frac = st_frac * rt_frac * hr_frac * spd_frac SetDataVector(vw_vmt+"|", "[Combined Factor]", combo_frac,{order}) daily_vmt = GetDataVector(vw_vmt+"|", "[Daily VMT]",{order}) annual_vmt = GetDataVector(vw_vmt+"|", "[Annual VMT]",{order}) daily_vmt_prop = daily_vmt * combo_frac annual_vmt_prop = annual_vmt * combo_frac SetDataVector(vw_vmt+"|", "[Daily VMT Proportion]", daily_vmt_prop,{order}) SetDataVector(vw_vmt+"|", "[Annual VMT Proportion]", annual_vmt_prop,{order}) vy = GetDataVector(vw_vmt+"|", "Year",) vs = GetDataVector(vw_vmt+"|", "State",) id1 = GetDataVector(vw_vmt+"|", "[Source type ID]",) id2 = GetDataVector(vw_vmt+"|", "[Road Type ID]",) id3 = GetDataVector(vw_vmt+"|", "Hour ID",) id4 = GetDataVector(vw_vmt+"|", "Average Speed Bin ID",) id_string = i2s(vy) +"_" + vs + "_" + i2s(id1) + "_" + i2s(id2)+ "_" + i2s(id3)+ "_" + i2s(id4) SetDataVector(vw_vmt+"|", "Aggregation_Key", id_string,) vc = GetDataVector(vw_vmt+"|", "County",) id_string = i2s(vy) +"_" + vs +"_" + vc SetDataVector(vw_vmt+"|", "Aggregation_Key_CTY", id_string,) //-----------------------Veh pop calculation UpdateProgressBar("Computing Veh Population .......", 25)APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-49

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area order1 = {"Sort Order", {{"Year", "Ascending"},{"County", "Ascending"},{"State", "Ascending"},{"[Source Type ID]", "Ascending"},{"[Road Type ID]", "Ascending"},{"[Hour ID]", "Ascending"}}} vw_veh =OpenTable("VMT", "FFB", {out_veh_summary,}) st_frac = GetDataVector(vw_veh+"|", "[Source Type Fraction]",{order1}) hr_frac = GetDataVector(vw_veh+"|", "[Hour VMT Fraction]",{order1})
combo_frac = st_frac * hr_frac SetDataVector(vw_veh+"|", "[Combined Factor]", combo_frac,{order1}) st_pop = GetDataVector(vw_veh+"|", "[Source Type Pop]",{order1}) pop_prop = st_pop * combo_frac SetDataVector(vw_veh+"|", "[Population Proportion]", pop_prop,{order1}) vy = GetDataVector(vw_veh+"|", "Year",) vs = GetDataVector(vw_veh+"|", "State",) id1 = GetDataVector(vw_veh+"|", "[Source type ID]",) id2 = GetDataVector(vw_veh+"|", "Hour ID",) id_string = i2s(vy) +"_" + vs + "_" + i2s(id1) + "_" + i2s(id2) SetDataVector(vw_veh+"|", "Aggregation_Key", id_string,) vc = GetDataVector(vw_veh+"|", "County",) id_string = i2s(vy) +"_" + vs +"_" + vc SetDataVector(vw_veh+"|", "Aggregation_Key_CTY", id_string,) CloseView(vw_vmt) CloseView(vw_veh)

//-------------------------Read MOVES Rates Tables UpdateProgressBar("Reading Rates from MOVES.......", 30) add_fields = {{"Aggregation_Key", "String", 32,0,}} for s = 1 to States.length do for y = 1 to Years.length do ds = States[s]+"_"+i2s(Years[y]) vw = OpenTable("RD", "ODBC", {ds, "rateperdistance"},{{"Read Only", True}}) bin_name = path[1]+path[2]+"MOVES_RatePerDist_"+ds+".bin" ExportView(vw+"|", "FFB", bin_name, ,{{"Additional Fields", add_fields}}) CloseView(vw) //add aggregation field values //aggregate by - {sourceTypeID, roadTypeID, hourID,avgSpeedBinID,pollutantID} vw = OpenTable("RD", "FFB", {bin_name,}) id1 = GetDataVector(vw+"|", "sourceTypeID",) id2 = GetDataVector(vw+"|", "roadTypeID",) id3 = GetDataVector(vw+"|", "hourID",) id4 = GetDataVector(vw+"|", "avgSpeedBinID",) id5 = GetDataVector(vw+"|", "pollutantID",) id_string = i2s(id1) + "_" + i2s(id2)+ "_" + i2s(id3)+ "_" + i2s(id4)+ "_" + i2s(id5) SetDataVector(vw+"|", "Aggregation_Key", id_string,) CloseView(vw) vw = OpenTable("RD", "ODBC", {ds, "ratepervehicle"},{{"Read Only", True}}) bin_name = path[1]+path[2]+"MOVES_RatePerVeh_"+ds+".bin" ExportView(vw+"|", "FFB", bin_name, ,{{"Additional Fields", add_fields}}) CloseView(vw) //add aggregation field valuesAPPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-50

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area //aggregate by - {sourceTypeID, hourID,pollutantID} vw = OpenTable("RD", "FFB", {bin_name,}) id1 = GetDataVector(vw+"|", "sourceTypeID",) id2 = GetDataVector(vw+"|", "hourID",) id3 = GetDataVector(vw+"|", "pollutantID",) id_string = i2s(id1) + "_" + i2s(id2)+ "_" + i2s(id3) SetDataVector(vw+"|", "Aggregation_Key", id_string,) CloseView(vw) end end //-------------------------Aggregate MOVES Rates Per Distance Tables //aggregate by - {sourceTypeID, roadTypeID, hourID,avgSpeedBinID,pollutantID} UpdateProgressBar("Aggregate Distance Rates .......", 40) vw_vmt =OpenTable("VMT", "FFB", {out_vmt_summary,}) field_names = { {"sourceTypeID","MIN",}, {"roadTypeID","MIN",}, {"hourID","MIN",}, {"avgSpeedBinID","MIN",}, {"pollutantID","MIN",}, {"ratePerDistance","SUM",} } add_fields = {{"Aggregation_Key_VMT", "String", 32,0,}} for s = 1 to States.length do for y = 1 to Years.length do ds = States[s]+"_"+i2s(Years[y]) bin_name = path[1]+path[2]+"MOVES_RatePerDist_"+ds+".bin" vw = OpenTable("RD", "FFB", {bin_name,}) temp_name = path[1]+path[2]+"Agg_RateVmt_"+ds+".bin" avw = AggregateTable("AGG", vw+"|", "FFB", temp_name, "Aggregation_Key", field_names,{"Missing as zero", "Yes"}) CloseView(vw) temp_name = path[1]+path[2]+"temp1.bin" for p = 1 to Pollutants.length do SetView(avw) query = "Select * where [Low pollutantID] = " + i2s(Pollutants[p]) svw = "Pneeded" n1 = SelectByQuery(svw, "Several", query,) if n1> 0 then do temp_name = path[1]+path[2]+"temp1.bin" ExportView(avw+"|"+svw, "FFB", temp_name, ,{{"Additional Fields", add_fields}}) tvw = OpenTable("RD", "FFB", {temp_name,}) id1 = GetDataVector(tvw+"|", "Low sourceTypeID",) id2 = GetDataVector(tvw+"|", "Low roadTypeID",) id3 = GetDataVector(tvw+"|", "Low hourID",) id4 = GetDataVector(tvw+"|", "Low avgSpeedBinID",) vsy = Vector(id1.length, "String",{{"Constant", i2s(Years[y]) + "_" + States[s]}}) id_string = vsy+ "_" + i2s(id1) + "_" + i2s(id2)+ "_" + i2s(id3)+ "_" + i2s(id4) SetDataVector(vw+"|", "Aggregation_Key_VMT", id_string,)APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-51

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area jv1 = JoinViews("JV1", vw_vmt + ".Aggregation_Key", tvw + ".Aggregation_Key_VMT", {{"O", }}) //set rates in vmt table SetView(jv1) svw2 = "Subset" query = "Select * where ratePerDistance <> null" n1 = SelectByQuery(svw2, "Several", query,) if (n1 > 0) then do vr = GetDataVector(jv1+"|"+svw2, "ratePerDistance",) SetDataVector(jv1+"|"+svw2, "RatePerDist_"+i2s(Pollutants[p]), vr,) end CloseView(jv1) CloseView(tvw) end end CloseView(avw) end end CloseView(vw_vmt) //-------------------------Aggregate MOVES Rates Per Vehicle Tables //aggregate by - {sourceTypeID, hourID,pollutantID} UpdateProgressBar("Aggregate Vehicle Rates .......", 60) vw_veh = OpenTable("VMT", "FFB", {out_veh_summary,}) field_names = { {"sourceTypeID","MIN",}, {"hourID","MIN",}, {"pollutantID","MIN",}, {"ratePerVehicle","SUM",} } add_fields = {{"Aggregation_Key_VEH", "String", 32,0,}} for s = 1 to States.length do for y = 1 to Years.length do ds = States[s]+"_"+i2s(Years[y]) bin_name = path[1]+path[2]+"MOVES_RatePerVeh_"+ds+".bin" vw = OpenTable("RD", "FFB", {bin_name,}) temp_name = path[1]+path[2]+"Agg_RateVeh_"+ds+".bin" avw = AggregateTable("AGG", vw+"|", "FFB", temp_name, "Aggregation_Key", field_names,{"Missing as zero", "Yes"}) CloseView(vw) temp_name = path[1]+path[2]+"temp1.bin" for p = 1 to Pollutants.length do SetView(avw) query = "Select * where [Low pollutantID] = " + i2s(Pollutants[p]) svw = "Pneeded" n1 = SelectByQuery(svw, "Several", query,) if n1> 0 then do temp_name = path[1]+path[2]+"temp1.bin" ExportView(avw+"|"+svw, "FFB", temp_name, ,{{"Additional Fields", add_fields}}) tvw = OpenTable("RD", "FFB", {temp_name,}) id1 = GetDataVector(tvw+"|", "Low sourceTypeID",)APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-52

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area id2 = GetDataVector(tvw+"|", "Low hourID",) vsy = Vector(id1.length, "String",{{"Constant", i2s(Years[y]) + "_" + States[s]}}) id_string = vsy+ "_" + i2s(id1) + "_" + i2s(id2) SetDataVector(vw+"|", "Aggregation_Key_VEH", id_string,) jv1 = JoinViews("JV1", vw_veh + ".Aggregation_Key", tvw + ".Aggregation_Key_VEH", {{"O", }}) //set rates in vmt table SetView(jv1) svw2 = "Subset" query = "Select * where ratePerVehicle <> null" n1 = SelectByQuery(svw2, "Several", query,) if (n1 > 0) then do vr = GetDataVector(jv1+"|"+svw2, "ratePerVehicle",) SetDataVector(jv1+"|"+svw2, "RatePerVeh_"+i2s(Pollutants[p]), vr,) end CloseView(jv1) CloseView(tvw) end end CloseView(avw) end end CloseView(vw_veh) temp_name = path[1]+path[2]+"temp1.bin" if GetFileInfo(temp_name) <> null then DeleteFile(temp_name) temp_name = path[1]+path[2]+"temp1.dcb" if GetFileInfo(temp_name) <> null then DeleteFile(temp_name)

///--------------------------------Calculate Emissions--------------------------------- UpdateProgressBar("Calculate Emissions .......", 70) vw_vmt =OpenTable("VMT", "FFB", {out_vmt_summary,}) daily_vmt = nz(GetDataVector(vw_vmt+"|", "[Daily VMT Proportion]",)) annual_vmt = nz(GetDataVector(vw_vmt+"|", "[Annual VMT Proportion]",)) for p = 1 to Pollutants.length do rate = nz(GetDataVector(vw_vmt+"|", "RatePerDist_"+i2s(Pollutants[p]),)) daily_em = rate * daily_vmt annual_em = rate * annual_vmt SetDataVector(vw_vmt+"|", "Daily_Emission_RatePerDist_"+i2s(Pollutants[p]), daily_em,) SetDataVector(vw_vmt+"|", "Annual_Emission_RatePerDist_"+i2s(Pollutants[p]), annual_em,) end CloseView(vw_vmt) vw_veh =OpenTable("VEH", "FFB", {out_veh_summary,}) pop = nz(GetDataVector(vw_veh+"|", "[Population Proportion]",)) for p = 1 to Pollutants.length do rate = nz(GetDataVector(vw_veh+"|", "RatePerVeh_"+i2s(Pollutants[p]),)) daily_em = rate * pop annual_em = rate * pop * 365 SetDataVector(vw_veh+"|", "Daily_Emission_RatePerVeh_"+i2s(Pollutants[p]), daily_em,) SetDataVector(vw_veh+"|", "Annual_Emission_RatePerVeh_"+i2s(Pollutants[p]), annual_em,) end CloseView(vw_veh)APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-53

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area ///--------------------------------Aggregate results to county--------------------------------- UpdateProgressBar("Calculate Emissions .......", 90) vw_vmt =OpenTable("VMT", "FFB", {out_vmt_summary,}) field_names = { {"Year","MIN",}} for p = 1 to Pollutants.length do field_names = field_names + {{"Daily_Emission_RatePerDist_"+i2s(Pollutants[p]), "SUM"}, {"Annual_Emission_RatePerDist_"+i2s(Pollutants[p]), "SUM"}} end vw_vmt_cty = AggregateTable("VMT_CTY", vw_vmt+"|", "FFB", out_em_vmt_summary, "Aggregation_Key_CTY", field_names,{"Missing as zero", "Yes"}) CloseView(vw_vmt) xls_name = path[1]+path[2]+"Summary_VMT_County.xls" ExportView(vw_vmt_cty+"|", "EXCEL", xls_name,,) vw_veh =OpenTable("VEH", "FFB", {out_veh_summary,}) field_names = { {"Year","MIN",}} for p = 1 to Pollutants.length do field_names = field_names + {{"Daily_Emission_RatePerVeh_"+i2s(Pollutants[p]), "SUM"}, {"Annual_Emission_RatePerVeh_"+i2s(Pollutants[p]), "SUM"}} end vw_veh_cty = AggregateTable("VEH_CTY", vw_veh+"|", "FFB", out_em_veh_summary, "Aggregation_Key_CTY", field_names,{"Missing as zero", "Yes"}) CloseView(vw_veh) xls_name = path[1]+path[2]+"Summary_VEH_County.xls" ExportView(vw_veh_cty+"|", "EXCEL", xls_name,,) //----------------------add together bin_fields = {{"Year", "Integer", 12,0,}, {"State", "String", 2,0,}, {"County", "String", 12,0,}, {"Pollutant", "String", 32,0,}, {"Daily Emission (grams/day)","Real", 24,4,}, {"Annual Emission (grams/year)","Real", 24,4,} } vw_sum = CreateTable("Emission Summary", out_em_total_summary, "FFB", bin_fields) order = {"Sort Order", {{"Aggregation_Key_CTY", "Ascending"}}} dim daily[Years.length, Counties.length, Pollutans.length] dim annual[Years.length, Counties.length, Pollutans.length] key = GetDataVector(vw_vmt_cty+"|", "Aggregation_Key_CTY",{order}) dim em_daily[Pollutants.length] dim em_annual[Pollutants.length] for p = 1 to Pollutants.length do vd1 = GetDataVector(vw_vmt_cty+"|", "Daily_Emission_RatePerDist_"+i2s(Pollutants[p]),{order}) vd2 = GetDataVector(vw_veh_cty+"|", "Daily_Emission_RatePerVeh_"+i2s(Pollutants[p]),{order}) em_daily[p] = vd1 + vd2 vd1 = GetDataVector(vw_vmt_cty+"|", "Annual_Emission_RatePerDist_"+i2s(Pollutants[p]),{order}) vd2 = GetDataVector(vw_veh_cty+"|", "Annual_Emission_RatePerVeh_"+i2s(Pollutants[p]),{order}) em_annual[p] = vd1 + vd2 end for i = 1 to key.length do subs = ParseString(key[i], "_")APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-54

Source Emissions for the Huntington-Ironton-Ashland PM 2.5 Nonattainment Area my_year = s2i(subs[1]) my_state = subs[2] my_county = subs[3] for p = 1 to Pollutants.length do my_pollutant = Pollutant_Names[p] my_day_em = em_daily[p][i] my_anu_em = em_annual[p][i]

r= null r.Year = my_year r.County= my_county r.State = my_state r.Pollutant = my_pollutant r.[Daily Emission (grams/day)]= my_day_em r.[Annual Emission (grams/year)] = my_anu_em AddRecord(vw_sum, r) end end xls_name = path[1]+path[2]+"Summary_Total_Emissions.xls" ExportView(vw_sum+"|", "EXCEL", xls_name,,) CloseView(vw_sum) CloseView(vw_veh_cty) CloseView(vw_vmt_cty) DestroyProgressBar()

endMacro

## APPENDIX D

LADCO Technical Support Document

LADCO Technical Support Document (supplemental)

# Regional Quality Analyses for Ozone, PM 2

. 5 

# and Regional Haze:

Final Technical Support Document

April 25, 2008 States of Illinois, Indiana, Michigan, Ohio, and Wisconsin

The document can be found at: hll.P:llwww.epa.ohio.9.QYLportals/27/SIP/Appendix 

# 0 -

TSD Version IV April 25 2008 FINAL.QQf

# Regional Quality Analyses for Ozone, 

# PM 2

. 5 

# and Regional Haze:

Technical Support Document Supplement



# September 12, 2008 States of Illinois, Indiana, Michigan, Ohio and Wisconsin

The document can be found at: b!!P:I Iwww.epa.ohio.g.QY{portals/27/SIP/AQPendix % 

# 20 

# 0- 2 TSO Sugplement without CAIR modeling FINAL.gQf

## APPENDIX E

Analysis of Insignificance of Mobile Emissions

### 1 Analysis of Insignificance of Mobile Emissions

In Ohio’s July 16, 2008 PM 2.5 

### Attainment Demonstration SIP 1 

### , Ohio found that the regional highway emissions of PM 2.5 

### , NO x 

### , and SO 2 

### were insignificant contributors to the nonattainment problems and, t herefore, none of the thr ee pollutants necessitated emissions inventory analysis or required the establishment ofmobile emission budgets. As documented in Ohio EPA’s attainment demonstration SIP, Ohio EPA in consultation with U.S. EPA determined thatthe Huntington-Ashland nonattainment area is not significantly impacted by on-road mobile emissions as compared to other source emissions; in addition, mobile source emissions in the area were expected to decrease. Based on the results of mobile source emission projections prepared as a part of this redesignation and maintenance plan, Ohio EPAis again making a finding that the regional highway emissions of PM 2.5 

### , NO x 

### , and SO 2 

### continue to be insignificant contributors to the nonattainment problems in this area, as discussed below. U.S. EPA’s redesignation guidance requires the submittal of a comprehensive inventory of PM 2.5

### precursor emissions (primary particles (organic carbon, crustal matter, and elemental carbon), SO 2 

### and NO x 2 

### ) representative of the y ear when the area achieves attainment of the annual PM 2.5

### air quality standard. Ohio al so must demonstrate that the improvement in air quality between the y ear that violations occurred and the year that attainment was achieved is based on permanent and enf orceable emission reductions. Other emission inventory related requirements include a projection of the emission inventory to a year at least 10 years following redesignation; a demonstration that the projected level ofemissions is sufficient to maintain the annual PM 2.5

### standard; and a commitment to provide future updates ofthe inventory to enable tracking of emission levels during the 10- year maintenance period. The emissions inventory development proce ss addresses emissions from several types of sources or sectors: point (EGU or non-EG U); non-point or area; marine, air, rail (MAR); non-road, and on-road or mobile. The inventories, with the exception of the mobile (on-road) , used in this submitta l are developed by the Lake Michigan Area Directors Consortium (LADCO) as discuss ed in greater detail elsewhere in the documents associated with this submittal.. Al l LADCO’s emission inventories utilized in the redesignation and mainte nance plan for the Hunt ington-Ashland annual PM 2.5 

### nonattainment area were prepared for county level emission.

Mobile emissions inve ntories and projections for all co unties were prepared by KimleyHorn and Associates Inc., with data provi ded by the Kentucky-Ohio-West Virginia Interstate Planning Commission (KYOVA), Ohio Department of Tr ansportation (ODOT), Ohio EPA, West Virginia Department ofTransportation (WVDOT), West Virginia Department of Environmental Protection (WVDEP), Kent ucky Transportation Cabinet (KYTC), and Kentucky Div ision of Air Quality (KDAQ). T he mobile emissi on inventories

1 http://www.epa.ohio.gov/portals/27/SIP/Attain/PM2_5/PM25Doc.pdf 2 VOC and NH 3are not addressed.

### 2 are only generated for the annual PM 2.5

### nonattainment areas, meaning that if an area was designated partial nonattainment, that was the only area that was modeled for inventory development (as oppos ed to the entire county thatthe partial nonattainment area is included within).

Since the mobile emissions inventories only address nonatta inment areas (county level or only partial areas determi ned as nonattainment) and t he remainder of the source sector inventories (non-elect ric generating unit (EGU), EG U, area, non-road, and MAR) address complete counties (which are notnecessarily entirely classified as nonattainment), Ohio EPA and U.S. EPA agr eed that an apportioning analysis approach would most accurately provide for a determi nation of mobile emissions insignificance. The analysis incorporates apportioning no n-road, MAR, and area emission sources from the entire county le vel inventory to the partial nona ttainment portion of the county based on the percentages of populat ion in the county versus th e partial area (based on the 2000 Census. This type of apportioning ma y not be as appropriate for the EGU and non-EGU sectors. However, for all partial nonattainm ent counties within this nonattainment area all EGU emissions within the county level inv entory reside solely within the partial area. As such, Ohio EPA has apportioned all EGU emissions into the partial area. Apportioning county level non- EGU emissions into the partial area for all the years of interest would be more challe nging. Because of these challenges and also due to time/recourse constraint s, Ohio EPA has elected to remove non-EGUs from this insignificance analysis ONLY in the partial nonattainment count ies. This is justified as omitting non-EGUs will provide for more cons ervative results (i.e., the percentage of mobile emissions will be lar ger). Therefore, if the in significance analysis with the omission of non-EGUs determines mobile em issions are insignificant, performing the analysis with non-EGU’s apportioned will sh ow even greater insignificance. Table 1 shows the total population in each c ounty that contains one or more partial nonattainment areas, the total population in each partial nonattainment area, and the population percentage in each partial nonattain ment area relative to the county population. This data is based on the 2000 Census data . The population percentages will be used to apportion all existing county level emissions (except mobile, EGU and non-EGU emissions) to the partial nonattainment area.

### 3 Table 1. Total County Population, Part ial Nonattainment Area Population, and Percentage of County Population with in the Partial Nonattainment Area.

Total % of County Adams County, OH 27,330 Sprigg Township 1,639 6.00% Monroe Township 735 2.69% Gallia County, OH 31,069 Cheshire Township 1,259 4.05% Mason County, WV 25,957 Graham Tax District 2,774 10.69% Lawrence County, KY 15,569 The area described by US Census 2000 block group identifier 21

‐ 127

‐ 9901

‐ 6 Sources: 2000 Census: http://censtats.census.gov/pub/Profiles.shtml West Virginia 2000 partial information:

http://www.epa.gov/oaqps001/greenbk/qnay.html Kentucky 2000 partial information:

http://www.census.gov/geo/www/cenpop/blkgrp/bg_21_ky.txt 1,050 6.74% Population



### The designation of a partial area as nonatta inment for the annual PM2.5 standard, is primarily attributed to the existence of EGUs (power plants) within the area encompassing the partial nonattainment area. As mentioned previously, all EGU emissions within each partial area presented in this redesignation and maintenance plan, reside only within the partial nonatta inment area. Hence, all county level EGU emission sources are apportioned to the parti al area since these emissions are only present in the partial area.

Non-EGU and EGU sources include those sources that are ident ified by point locations, typically because they are regulated and t heir locations are available in regulatory reports. As mentioned above EG U sources will be included in th e insignificance analysis apportioned to the partial area.

Because non-EGU sources include an infinite amount of facilities and processes, and because the recourses that would be needed to estimate non-EGU emissions within a partial area, based on county level emission s (for the apportionmentanalysis), it was agreed that Ohio EPA would omit these em issions in the partial areas from the insignificance analysis for the partial nonatta inment counties. Moreover, omitting these emissions will provide a more conservative fi nding of mobile emissi ons insignificance as discussed above.

Table 2 to Table 13 3

### show partial nonattainment areas apportioning results and entire county level emissions. The emission reductions from the apportioning approach compared to the entire county level emissi ons, show further reductions across all

3 Table 2 to Table 13 are similar to Table 18 to Table 47 of the Redesignation and Maintenance document, without Non-EGU sources

### 4 emission sources (except EGUs and mobile sources since they are already only representing partial nonattain ment areas). Please note t he Table 2 to Table 13 below only reflects emissions as a part of th e apportioning analysis for the partial nonattainment areas. The remaining emissi ons for full nonattainment counties included in the determination of insi gnificance can be found in redesignation and maintenance document from Table 18 to Table 47.

PM 2.5 

### Table 2 - Adams County, Ohio PM 2.5

### Partial Nonattainment Areas Apportioning Results and Entire County Level Emissions: Emission Totals for Projected 2015 and 2022 (tpy) – Without CAIR Sector 2015 Interim 2015 Partial Only 2022 Maintenance 2022 Partial Only EGU Point 3569.95 3569.95 3544.65 3544.65 Non-road 8.70 0.76 4.04 0.35 Area 285.55 24.80 282.69 24.56 MAR 4.21 0.37 1.74 0.15 On-road 2.17 2.17 1.39 1.39 TOTAL 3870.58 3598.05 3834.51 3571.10



### Table 3 - Gallia County, Ohio PM 2.5

### Partial Nonattainment Areas Apportioning Results and Entire County Level Emissions: Emission Totals for Projected 2015 and 2022 (tpy) – Without CAIR Sector 2015 Interim 2015 Partial Only 2022 Maintenance 2022 Partial Only EGU Point 1,073.20 1,073.20 1,100.12 1,100.12 Non-road 7.22 0.29 4.07 0.16 Area 181.29 7.35 182.52 7.40 MAR 4.32 0.18 1.84 0.07 On-road 1.06 1.06 0.68 0.68 TOTAL 1,267.09 1,082.08 1,289.23 1,108.43



### Table 4 - Lawrence County, Kentucky PM 2.5

### Partial Nonattainment Areas Apportioning Results and Entire County Level Emissions: Emission Totals for Projected 2015 and 2022 (tpy) – Without CAIR Sector 2015 Interim 2015 Partial Only 2022 Maintenance 2022 Partial Only EGU Point 422.88 422.88 433.23 433.23 Non-road 7.21 0.49 4.91 0.33 Area 91.70 6.18 92.09 6.21 MAR 13.33 0.90 9.05 0.61 On-road 3.12 3.12 1.69 1.69 TOTAL 538.24 433.57 540.97 442.07

### 5 Table 5 - Mason County, West Virginia PM 2.5

### Partial Nonattainment Areas Apportioning Results and Entire County Level Emissions: Emission Totals for Projected 2015 and 2022 (tpy) – Without CAIR Sector 2015 Interim 2015 Partial Only 2022 Maintenance 2022 Partial Only
EGU Point 259.80 259.80 266.33 266.33 Non-road 9.38 1.00 4.70 0.50 Area 139.42 14.90 141.99 15.17 MAR 35.53 3.80 25.66 2.74 On-road 0.64 0.64 0.38 0.38 TOTAL 444.77 280.14 439.06 285.12



### NO X 

### Table 6 - Adams County, Ohio NO x

### Partial Nonattainment Areas Apportioning Results and Entire County Level Emissions: Emission Totals for Projected 2015 and 2022 (tpy) – With CAIR
Sector 2015 Interim 2015 Partial Only 2022 Maintenance 2022 Partial Only
EGU Point 25,671.39 25,671.39 23,276.73 23,276.73 Non-road 92.82 8.06 57.47 4.99 Area 134.84 11.71 137.93 11.98 MAR 199.67 17.34 97.77 8.49 On-road 54.82 54.82 26.21 26.21 TOTAL 26,153.54 25,763.32 23,596.11 23,328.40



### Table 7 - Gallia County, Ohio NO x

### Partial Nonattainment Areas Apportioning Results and Entire County Level Emissions: Emission Totals for Projected 2015 and 2022 (tpy) – With CAIR
Sector 2015 Interim 2015 Partial Only 2022 Maintenance 2022 Partial Only EGU Point 24,476.65 24476.65 9,385.96 9385.96 Non-road 67.88 2.75 38.85 1.57 Area 131.45 5.33 135.53 5.49 MAR 194.41 7.88 95.18 3.86 On-road 26.89 26.89 12.94 12.94 TOTAL 24,897.28 24,519.50 9,668.46 9,409.82

### 6 Table 8 - Lawrence County, Kentucky NO x

### Partial Nonattainment Areas Apportioning Results and Entire C ounty Level Emissions: Emission Totals for Projected 2015 a nd 2022 (tpy) – With CAIR
Sector 2015 Interim 2015 Partial Only 2022 Maintenance 2022 Partial Only
EGU Point 2,997.63 2997.63 2,252.78 2252.78 Non-road 41.05 2.77 28.16 1.90 Area 92.45 6.23 96.64 6.52 MAR 444.15 29.95 286.03 19.29 On-road 70.54 70.54 37.96 37.96 TOTAL 3,645.82 3,107.12 2,701.57 2,318.45



### Table 9 - Mason County, West Virginia NO x

### Partial Nonattainment Areas Apportioning Results and Entire County Level Emissions: Emission Totals for Projected 2015 a nd 2022 (tpy) – With CAIR
Sector 2015 Interim 2015 Partial Only 2022 Maintenance 2022 Partial Only
EGU Point 11,957.32 11957.32 11,300.37 11300.37 Non-road 124.24 13.28 96.26 10.29 Area 391.32 41.82 414.58 44.31 MAR 971.05 103.78 663.19 70.87 On-road 15.33 15.33 8.72 8.72 TOTAL 13,459.26 12,131.53 12,483.12 11,434.56



### SO 2 

### Table 10 - Adams County, Ohio SO 2

### Partial Nonattainment Areas Apportioning Results and Entire County Level Emissions: Emission Totals for Projected 2015 and 2022 (tpy) – With CAIR Sector 2015 Interim 2015 Partial Only 2022 Maintenance 2022 Partial Only
EGU Point 27,077.57 27,077.57 23,276.73 23,276.73 Non-road 0.91 0.08 0.14 0.01 Area 31.73 2.76 30.08 2.61 MAR 6.61 0.57 1.79 0.16 On-road 0.32 0.32 0.32 0.32 TOTAL 27,117.14 27,081.30 23,309.06 23,279.83

### 7 Table 11 - Gallia County, Ohio SO 2

### Partial Nonattainment Areas Apportioning Results and Entire County Level Emissions: Emission Totals for Projected 2015 and 2022 (tpy) – With CAIR
Sector 2015 Interim 2015 Partial Only 2022 Maintenance 2022 Partial Only
EGU Point 41,924.16 41924.16 20,510.45 20510.45 Non-road 0.67 0.03 0.15 0.01 Area 15.91 0.65 15.35 0.62 MAR 6.9 0.28 2.26 0.09 On-road 0.16 0.16 0.16 0.16 TOTAL 41,947.80 41,925.28 20,528.37 20,511.33



### Table 12 - Lawrence County, Kentucky SO 2

### Partial Nonattainment Areas Apportioning Results and Entire County Level Emissions: Emission Totals for Projected 2015 a nd 2022 (tpy) – With CAIR Sector 2015 Interim 2015 Partial Only 2022 Maintenance 2022 Partial Only EGU Point 20,475.34 20475.34 11,800.13 11800.13 Non-road 0.41 0.03 0.12 0.01 Area 98.36 6.63 98.02 6.61 MAR 38.28 2.58 21.04 1.42 On-road 0.73 0.73 0.71 0.71 TOTAL 20,613.12 20,485.31 11,920.02 11,808.88



### Table 13 - Mason County, West Virginia SO 2

### Partial Nonattainment Areas Apportioning Results and Entire County Level Emissions: Emission Totals for Projected 2015 a nd 2022 (tpy) – With CAIR
Sector 2015 Interim 2015 Partial Only 2022 Maintenance 2022 Partial Only
EGU Point 44,094.05 44094.05 41,340.89 41340.89 Non-road 1.03 0.11 0.25 0.03 Area 123.14 13.16 125.6 13.42 MAR 4.38 0.47 1.06 0.11 On-road 0.07 0.07 0.08 0.08 TOTAL 44,222.67 44,107.86 41,467.88 41,354.53



### Table 14 to Table 16 show a summary comparison between entir e counties (without apportionment and with non-EGU emissions, see columns D and F) and only nonattainment areas (with appo rtionment and excluding N on-EGU emissions in the partial areas, see columns E and G). T he comparison shows the apportionment results in a decrease of at least 7.23% for 201 5 emissions and 7.05% for 2022 of PM2.5 emissions, 2.81% for 2015 emissions and 2.84% for 2022 emissions of NO x

### emissions

### 8 and 0.20% for 2015 emissions and 0.24% for 2022 emissions of SO 2 

### emission. Recall, as mentioned above, det ailed emissions by each sector for full nonattainment counties included in the determination ofinsignificance and identifie d below can be found in the full document.

Table 14 - Huntington-Ashland Area PM2.5 Partial Nonattainment Areas Apportioning Results and Entire County Level Emissions: Emission Totals for Projected 2015 a nd 2022 (tpy) – With CAIR

A D E F G

PM 2.5 2015 Interim 2015 Interim with Apportionment and Non

‐ EGU in Partial Areas Only 2022 Maintenance 2022 Interim with Apportionment and Non

‐ EGU in Partial Areas Only Adams, OH 3870.58 3598.05 3834.51 3571.10 Gallia, OH 1,267.09 1,082.08 1,289.23 1,108.43 Lawrence, OH 181.56 181.56 158.79 158.79

Scioto, OH 517.46 517.46 475.21 475.21 Boyd, KY 1,977.20 1,977.20 1,941.71 1,941.71 Lawrence, KY 538.24 433.57 540.97 442.07

Cabell, WV 900.25 900.25 881.53 881.53 Mason, WV 444.77 280.14 439.06 285.12 Wayne, WV 358.66 358.66 319.69 319.69 COMBINED PM 2.5 TOTAL 10,055.81 9,328.97 9,880.70 9,183.65



### Table 15 - Huntington-Ashland Area NO x

### Partial Nonattainment Areas Apportioning Results and Entire County Level Emissions: Emission Totals for Projected 2015 a nd 2022 (tpy) – With CAIR

A D E F G

NOx 2015 Interim 2015 Interim with Apportionment and Non

‐ EGU in Partial Areas Only 2022 Maintenance 2022 Interim with Apportionment and Non

‐ EGU in Partial Areas Only Adams, OH 26,153.54 25,763.32 23,596.11 23,328.40 Gallia, OH 24,897.28 24,519.50 9,668.46 9,409.82 Lawrence, OH 1,771.48 1,771.48 1,179.13 1,179.13 Scioto, OH 2,750.01 2,750.01 1,643.98 1,643.98 Boyd, KY 10,974.99 10,974.99 10,073.03 10,073.03 Lawrence, KY 3,645.82 3,107.12 2,701.57 2,318.45 Cabell, WV 4,146.09 4,146.09 2,980.41 2,971.41 Mason, WV 13,459.26 12,131.53 12,483.12 11,434.56 Wayne, WV 5,979.24 5,979.24 4,900.76 4,900.76 COMBINED NOx TOTAL 93,777.71 91,143.28 69,226.57 67,259.54

### 9 Table 16 - Huntington-Ashland Area SO2 Partial Nonattainment Areas Apportioning Results and Entire County Level Emissions: Emission Totals for Projected 2015 a nd 2022 (tpy) – With CAIR

A D E F G

SO 2 2015 Interim 2015 Interim with Apportionment and Non

‐ EGU in Partial Areas Only 2022 Maintenance 2022 Interim with Apportionment and Non

‐ EGU in Partial Areas Only Adams, OH 27,117.14 27,081.30 23,309.06 23,279.83 Gallia, OH 41,947.80 41,925.28 20,528.37 20,511.33 Lawrence, OH 64.67 64.67 38.19 38.19 Scioto, OH 1,103.30 1,103.30 796.00 796.00 Boyd, KY 11,964.29 11,964.29 12,840.55 12,840.55 Lawrence, KY 20,613.12 20,485.31 11,920.02 11,808.88 Cabell, WV 1,756.37 1,756.37 1,865.27 1,865.27 Mason, WV 44,222.67 44,107.86 41,467.88 41,354.53 Wayne, WV 846.29 846.29 874.07 874.07 COMBINED SO 2 TOTAL 149,635.65 149,334.67 113,639.41 113,368.65



### The following table shows the percentage of the mobile po rtion of all emissions, for each pollutant in the entir e nonattainment area, apporti oned per the above, for 2015 and 2022.

Table 17 – Percent of Mobile Emissions fo r the Huntington-Ashland Area in 2015 and 2022 – With Apportionment Anal ysis for partial nonattainment areas
NO x SO 2 PM 2.5 2015 2022 2015 2022 2015 2022

Huntington

‐ Ashland Area Total (tpy) 91,143.28 67,259.54 149,334.67 113,368.65 9,328.97 9,183.65 Mobile (tpy) 5,444.35 2,852.96 35.85 36.73 236.36 141.31

% Mobile 5.97% 4.24% 0.02% 0.03% 2.53% 1.54%

Ohio Portion Total (tpy) 54,804.31 35,561.33 70,174.55 44,625.35 5,379.15 5,313.53 Mobile (tpy) 1,824.62 924.08 10.01 10.43 69.34 46.71

% Mobile 3.33% 2.60% 0.01% 0.02% 1.29% 0.88%



### NO x

### constitutes less than six percent(<6%) of the area’s total NO x

### emissions in the 2015 and 2022 horizon years. PM 2.5 

### constitutes less than three percent (<3%) of the area’s total PM 2.5 

### emissions in the 2015 a nd 2022 horizon years. SO 2 

### constitutes less than one percent (<1%) of the area’s total SO 2 

### emissions in the 2015 and 2022 horizon years.

### 10 Therefore, the Ohio EPA is herein making a finding that the area’s highway emissions for PM 2.5 

### , NO x 

### , and SO 2 

### continue to be insignificant c ontributors to the nonattainment problem of the Huntington- Ashland area, as agreed upon as a part of the interagency consultation process. Moreover, the result s from Table 17 show emissions adjusted for partial nonattainment areas and does not include Non-EGU emission so urces in partial areas, providing higher percentages of mobile emissions (for all three pollutants) and showing a conservative (overestimated) per centage of mobile emissions. Because of this finding it is not necessaryto establish mobile emission budgets for this area in the 2015 and 2022 horizon years.

## APPENDIX F

Public Participation

Public Notice

Public Comments Hearing Transcript Responsive Summary to Comments

### Public Notice Ohio Environmental Protection AgencyRedesignation and Maintenance Plan for the Ohio Portion of the HuntingtonAshland, OH-KY-WV Annual PM 2.5

### Nonattainment Area
Adams, Gallia, Lawrence and Scioto Counties Notice is hereby given that the Director of the Ohio Environmental Protection Agency, (Ohio EPA) is requesting that the United States Environment al Protection Agency (U.S. EPA) revise the current air qua lity designation for the Ohio portion of the HuntingtonAshland nonattainment area, including Adams, Gallia, Lawrence and Scioto counties to attainment with respect to the 1997 annual PM 2.5

### national ambient air quality standard (NAAQS). Fine particle pollution or PM 2.5

### is a mixture of microscopic solids and liquid droplets suspended in air that is 2.5 micr ometers in diameter and smaller – 1/30 th 

### the diameter of a human hair. PM 2.5

### can be emitted directly orformed secondarily in the atmosphere. Air quality monitoring data collected between 2008 and 2010 in the region demonstrate attainment of the NAAQS and t here is evidence thatthe improved air quality is due to permanent, enforceable emi ssion reductions. In addition, existing requirements are sufficient to maintain the 1997 annual PM 2.5

### standard in this area at least ten years into the future. Computer models show that existing stat e and federal emission reduction requirements are sufficient to attain and maintain t he NAAQS in the Huntington-Ashland area. Therefore, Ohio EPA proposes to utilize ex isting emission inventory information and projections of future emissions as the dem onstration of the ability to maintain the NAAQS in the Huntington-Ashland area in the future. The Huntington-Ashland area is currently designated as nonattainment for the 1997 annual PM 2.5

### standard. As part of an acceptable maintenance plan, Ohio EPA is required to develop a contingency plan to prov ide for additional emission reductions if a violation of the NAAQS is monitored afte r the area has been redes ignated. The plan which Ohio EPA is proposing to USEPA as part of this redesignation contains reductions which will help alleviate the ambi ent problem until a re vised SIP can be developed. The State of Ohio proposes to: 1. Request the U.S. EPA r edesignate the Huntington-Ashland area to attainment with respect to the 1997 annual PM 2.5

### NAAQS and revise the maintenance plan. This request will document t hat existing enforceable control measures are responsible for the observed improvement in air quality. 2. Designate existing controls as sufficient to maintain the NAAQS into the future. 3. Commit to the proposed contingency plan.

### These actions must be noticed to allo w public comment and to satisfy USEPA requirements for public involvement in SIP re lated activities. This notice addresses Ohio EPA’s reliance on the emission projections as evidence of attainment and maintenance and the commitment to instit ute contingency measures ifambient exceedances or violations trigger the contingency plan r equirements. Written comments will be received on or before April 21, 2011 at the following address:

E-mail: Carolina.Prado@epa.state.oh.us Mailing address: Carolina Prado Ohio Environmental Protection Agency, DAPC Lazarus Government Center P.O. Box 1049 Columbus, Ohio 43216-1049 Phone: (614)- 728-1743

Pursuant to Section 119.03 of the Ohio Revised Code, a public hearing on this redesignation request will be conducted as follows April 21, 2011 1:30 PM, at Portsmouth City Health Department, Firs t Floor Conference Room, 605 Washington Street, Portsmouth, Ohio. All interested persons are entitled to att end or be represented at the hearings and give written or oral comments on these changes. All oral comments presented at the hearing, and all written statements submitted atthe hearing or to the above address by the close of business on Ap ril 21, 2011 will be considered by Ohio EPA prior to final action on this redesignation. Written statements submitted after April 21, 2011 may be considered as time and circumstances permit, but will not be part of the official record of the hearing. This redesignation and maintenance request is available on Ohio EPA DAPC’s Web page for electronic downloading at: http://www.epa.ohio.gov/dapc/SIP/annual.aspx

. Questions regarding accessing the web site should be directed to Arunee Niamlarb at 614-728-1342; other questions or comments about this documentshould be directed to either Carolina Prado, (614)-644-2310, Carolina.Prado@epa.state.oh.us or Jennifer Hunter at (614) 644-3696, Jennifer.Hunter@epa.state.oh.us or mailed to Carolina Prado or Jennifer Hunter at the above address.Committees: Veterans Affairs, Vice-Chairman Health Tran.sportation Contact Information: Office: 614-466-2124 Toll-Free: 1-800-282-0253 FAX; 614·719·6989 El1'Jai1: disidct89@ohr.state.oh.lls www,houst.state,oh.ltS 

# State Representative Terry A. Johnson 89 th 

## Ohio House District

April 15, 2011

Director Scott J, Nally Ohio Environmental Protection Agency, 30 W. Town Street Columbus,OU 43215

Dear Director NaLly,

I am writing in SUPPOlt of the proposal to re-designate the Portsmouth, Ohio area air quality as meeting the 1997 federal fine particulate standard. Portsmouth is part of the Huntington, W.Va.- Ashland, Ky., metropditan area, and air quality data from2008-2010 shows that the area has suceessfully met the 1997 national fine particulate matter standard for OVer three years.

This area has been below the national standard over this cntire three-year period by a substantial margin. As a result, I wholehea;tedly support your ini.tiative to ask the U.S. Environmental Protection Agency to re-designnte the area to reflect full compliance with the standard.

This re"designation is vital for our local economy 'md would anow industry to locate in southern Ohio without tbe n.eed to obtain air quality offsets. It would have an enOl1TIOUS positive impact for the entire region. Scioto, Adams, Gatlia and Lawrence counties in Ohio would be much more competitive when recruiting prospective employers. If Ohio does not get this re-designation, tben Kentucky and West Virginia likely will. Tbat would have basieany the same impact on our air quality with little or no economic benefit for Ohio.

As a practicing physician, I know the adverse effects can that result fl'Om exeessive particulate matter in the air we breathe. However, I am convinced that current national, state and loeal air potluti.o!1 controls which limit particulate matter-causing emissions will enable the area to maintain tbe required air quality and advance the economic development we so desperately need.

Tbank you for considering tbis request. Please contact me if you require additional information.
Sincerely,

Terry A. Johnson State Representative

77 South High Street • Columbus, Ohio 43215-6111

## GREATER lAWRENCE COUNTY 

# W AREA

" ;;A 

### LAWRENCE ECONOMIC DEVELOPMENT CORP.**~~** P,O, Box 488 South Point, Ohio 45680-0488 740-377-4550 800-408-1334 FAX 740-377-2091

April 21. 2011

Ohio EPA-Division of Air Pollution Control P.O. Box 1049 Columbus. Ohio 43216-1049

Re: Air Quality Public Hearing- Fine Particulate Re-designatlon

Dear: Ms. Carolina Prado

In regards to the Air Quality Re-designation within our region, the Lawrence Economic Development Corporation would like to express its support of re-classifying Lawrence County, Ohio to be In compliance with the national standards for 2.5 particulate emissions. Our main concerns have always been drifting emissions from the Kentucky side of the Ohio River and therefore have expected a higher compliance level, although not preViously required, from our power plants along the Ohio River.

Our responsibility as an Ohio Community Improvement Corporation is to encourage business growth as well as to promote the quality of life In our region. It is our firm belief that Lawrence County companies emits far below the national emissions standard. We have been in compliance and will continue to maintain compliance of regulatory controls to limit and lower 2.5 particulate emissions in the Huntington-Ashland area past the 10 year requirement for designation.

We ask you to consider this request on behalf of Lawrence County for the betterment of our community. Should you have any concerns, please feel free to contact me at: 740-377-4550.

# LAWRENCE COUNTY PORT AUTHORITY

P.O. Box 488 South Point, Ohio 45680-0488 740-377-4550 800408-1334 FAX 740-377-2091 www.lawrencecountyohio.org



### Date: April 2], 2011

# {~(");r To: Ohio Envirolli11ental Protection Agency

# ,~y**V~** From: Lawrence County Port Authority, Bill Dingus, Executive Director 

# .r:.

Subject: Comments for April 21, 20 

### I] Public Hearing for Redesignation.

The Lawrence County Port Authority hereby goes on record endorsing the changing of compliance status for Adams, Gallia, Lawrence, and Scioto Counties in Ohio. The air quality data shows that the region is now meeting the fine particulate standards, and it is requested by our agency that appropriate redesignation occur to allow the strides made in the region in improving air quality. Currently, economic development efforts being made to recruit family wage jobs
are hindered by the incorrect designation. Numerous industries have closed which were contributing to the emission levels, and great strides have been made in applying efforts through available ODOT funds to further eliminate air emissions. This barrier discourages consideration of these relatively poor counties to be considered for private manufacturing economic growth, thus contributing to older vehicles that have greater emissions as well as a lower standard of living for the region.

Please recognize the effOlis and accomplishments that have been made in this four county region by providing a redesignation of meeting standards, and thereby, open new opportunities to ow' region. Please do not hesitate if information is needed to quantify the importance of this change.140610 th St., PO Box 60, Portsmouth, OH 45662 740.355.0141 Phone 740.355.3513 Fax

March 21, 2011

Governor John Kasich 77 South High St. Columbus, OH 43215

Dear Governor Kasich:

I am writing to you today from the prospective of an owner of a local construction business, a developer of industrial parks in Southeast Ohio and as a life-long resident of Scioto County. I am asking your assistance in having Scioto and lawrence Counties re-designated as Attainment with the U.s. EPA.

As you know, successful economic development is a public/private partnership that many times requires the public sector to help provide the necessary infrastructure and environment for private industry to then make an investment of capital. For years, my company, Hadsell Development has worked with the Southern Ohio Port Authority in Scioto County and LEDC in Lawrence County to redevelop the former steel mill property in New Boston and ethanol plant property in South Point. This was made possible through Federal, State and local grants that were used for such purposes as brownfieid restoration and infrastructure development. I have worked with the Ohio EPA on many projects over the years. Few are as important as what is and could be coming to eastern Scioto County this year.

What we know for sure is that a local company, SunCoke, prOVides many good paying jobs and contributes significantly to the local and state tax base. They are going to construct an over $500,000,000 plant expansion in either Scioto County or across the river and state-line in Greenup, KY. Why are they considering an off-site plant extension? It's simple. Right now, they can do it for less in Kentucky. Not because the materials, land or labor will be any cheaper. It's because, even though we breathe the same air as they do in Greenup, Scioto County is classified by the U.S. EPA as a nonattainment county. As long as that continues, we will be at a significant disadvantage in bringing any new manufacturing to the area and Ohio could iose a half-biilion dollar expansion project to our neighbors who are, literally, a stone's throwaway.

Because we have been testing in attainment for several years now, our area deserves to quickly receive
an Attainment designation, so that we can move forward in creating a more business and worker friendiy environment that will positively impact our local, state and regional economy. Thank you for your assistance.
Sincerely,

# Qa~tLt Hadsell Development, J&H Erectors and McGovney Ready Mix and River Terminal 

### VJ ,j- C.<>,.., "" a..u"-) t-.L c,.

### Ohio EPA Bearing, April 21, 2011 portsmouth, Ohio

Thank you, Ohio EPi\, for holding this hearing and allowing me to

comment on the request to US 

### EPA to change the current: nonattainm,mt designat ion for this region to one of at tainment for particul at e mat tel", spec iricall y for the 1997 annu al PM 2.5
national ambient air qUalitystan,dard (NlIAQS).



### Now, I know that this hearing is just a formality. None-the-less, ( 

### I appreciate the opportunity to speak on the record, to be
accorded due process.

Let me start by saying that less bad is no good. That's a concept.
Less bad is no good.

Ohio EPl\ is claiming that the dirty air of this region is cleaner,
is clean enough.!t was at one time so dirty that it 

### was dirtier
tha.n the national allowable standards and thus the region was considered to be in nonattainment with respect to those standards,
the national ambient air qUal ity standards for annual PM 2.5. Ohio

EPA 

### says that now its tests and monitoring show that the air is less dirty than the US 

### standard,that the air is clean enough to be designated in attainment of the standards for clean. But, while
the ,air is cleaner, it is still dirty. It is less bad but it's

st ill not good.

The March 2010 draft of the Redesignat ion and Maint enanee pI an

says nothing about why particulate matter is regulated or what the
benefits aI'S of lowering the amounts of part iculate matter.

1

### The state Implementat ion Plan for PM 2.5, revised June 7, 2010,
does say the following: quote "The NiliAQS are air qUality standards
for pollut ant s t hat pose publ ic heal t h risks. High 1 evel s of

PM 2.5 can contribute to a number of health impacts, including
premature mortality, aggravation of respiratory and cardiovascular disease, lung disease, decreased lung' function, asthma attacks, and
other cardiovascular impacts." unquote.

No data is presented to correlate cleaner air with better beal tho
Tbat is simply assumed. I cballenge that assumption with the concept that less bad is no good. Yes, tbe air is cleaner and tbere

are probably fewer bad health effects. But althcughcleaner, the
air is st ill dirt y and is st ill probabl y having adverse heal th
effect s not onl y on humans but on allot ber animal sand 13.1 so on plants. That's not good.

Some migbt argue that one can't have zero particulate matter and to
that I say, wby not? Jlt least why not zero particulate matter
emissions from human industrial activity. Tbese emissions are

waste products called pollution.

Let me quote from a bock called Cradle to Cradle by William McDonough and Micbael Braungart, quote "To el iminate the concept
of waste means to design things

- products, packaging, and systems

- from the very beginning on the understanding that waste does not
exist." end quote. Nature doesn't have waste. Humans shoUld
ernul at e nat ure.

Tbe world is now in a crisis situation from tbe many human industrial wastes and pollutants.

2

### Another quote, this by Albert Einstein: quote "The world will not
evolve past its ourrent state of oris is by using the same thinking
that .created the situation." end quote. Thinking that less bad
is good is not good enough. Less bad is no good. Thinking needs

to be about onl y good.

People have known, probablY forever, that human activities have
harmful effeots. The oreation of EPA and the Clean Air Act were legislative attempts to do something about waste pOllution and
its harmful effeots. Industries like energy. transportation and agrioul ture are the bigger air polluters. They are largely responsible for the world air crisis. Here in the US, the EPA
has been complicit in that air pollution.

EPIl is a regulatory agency. Here's what Cradle to Cradle says about regulation: quote "But Ultimately a regulation is a signal of design failure. In fact, it is what we call a license to harm; a permit issued by a government to an industry so that it may dispense siCkness, destruction and death at an "acceptable" rate." end quote.

Ohio EPA is no doubt trying to follow the letter of the law, working with industry and giving permits to allow the maximum

waste pollution up to the limits of the law. Supposedly that lets industry avoid as much pollution control cost .as possible.

As a citizen who has to breathe**wh~tever** 

### air is around me, whereever I am, I want Ohio EPA to follow the intent of the law, to
work with industry to el iminate all waste and all pollution such
that regUlation would not be necessary.



### 3

### Ohio EPA follows national laws. I'm fairly sure there is nothiner
in those laws that says that states cannot do better than the
federal erovernrnent. Here's an exampl e. In adapt at ion to cl imat e. chane e, t he federal erovernment is do ing muc h too 1 it tl 

### e. Several
cities like C:hicaeo and New York and a county in Washington are making their own plans for the future and implementing them. Ohio**EP~** 

### similarly could be making :its own clean air laws better than

nat ional ones.

One specific thing that bothers me about the redesignation proposal is that it is for the Ohio portion of the**Huntinerton-~sh** 

### land, Obio, Kentucky, Ifest Virginia nonattainment area for annual

PM 2.5

- tbe counties of 4\d!jms, Gallia, Lawrence and Scioto.**T'~o** 

### of Barry Commoner's ecoloerical laws say tbat, quote "Everything is connected to everything else and Everything has to go/ somewhere." end quote. The air in this geographic region is not fixed

to this reEion. It's a part of and intimately connected to the
world atmosphere. Air circulates in the atmosphere throuerhout the
world. This has been vividly demonstrated recently by**radioa~tive** 

### material produced in Japan being detected in countries around the
worl d.

Not all the air pollution measured in this reerion was produced in
this region. Much came from upwind.**B~** 

### the same token, not all
the air pollution produced in this region stays hsre; it moves downwind to other areas.

In my opinion, these geographical boundaries, which are conceptual,

4

### have no real meaning for air which has no boundaries and which is always in motion, always changing, much as a river flo,.s cont inu**OQs:;:X.~lth** 

### different water at anyone place at any given moment
in time.

This relates closely with another concern I have. 

# In the conclusion
of the draft Redesignation Request is says that: quote "

... the air quality improvements are due t() permanent and enforceable mea:sures."
end quote. The text says that Ohio commits to maintaining control

measures after redesignaticn. It 

### also says, quote, "Ohio, through
Ohio EPA'S 

### Legal section, has the legal authority and necessary

resources to actively enforce any violet ions of its rules or permit provisions." end quote. The authority**.~s** 

### there, but will it be
used? And, will there be the resources?

I wish that I could totally bel ieve and trust my government,
believe and trust Ohio EPA. 

### But based on personal experience and knm'l1edge, I cannot.

For years Ohio EPA 

### .cited violat ions at the stuart power plant in
Adams County and did nothing further with enforcement. It took a legal suit by an individual and the Sierra Club to get some posit i 

### ve act ion. I bel ieve t hat any fines are probabl y so small
that a large industry like DP&L would consider them just part of the

cost of doing business and maybe take them out of the petty cash fund.

In my dealings with Ohio EPA 

### and open burn permits for prescribed
forest fires, I have not seen a commitment to public health and well-being ora will ingness to follo,. all rules and laws and
enforc e them.



### 5

### I'm concerned that the current Ohio administration strongly favors private economic activity over pUblic wellfare, that it 

### has a strong
bias for deregulation, that it 

### has little if any understanding of ecology, and that it will help balance the bUdget by inappropriately cLlttingfunding to Ohio EPA. 

### There are likely to be far too few
Ohio EPA 

### employees to do all the necessary monitoring and enforcement of cl ean air laws. Despite t heir best intent ions to do a
proper job, Ohio EPA employees may not have proper administrative
support.

I hc,pe I'm wrong, but I believe that Ohio EPA 

### \1ill have trouble maintaining pollution controls and providing enforcement to stay
in attainment. There are contingency plans in Case of failure. perhaps they will suffice.

In conclusion, I cannot support a redesignat ion from nonattainment

to attainment for this region. But, neither do I formally oppose it.



### In my opinion, the whol e world needs to be decl ared in nonatt ainment
for industrial pollutants to the earth's atmosphere. Everyone
needs to be working, not for attainment of some arbitrary acceptable
level of pollution but for total elimination 

### 0:1' industrial pollution
with no need for any regulation.

We need to strive for oomplete good because less bad is no good.

Barbara A. 

### Lund 

### 2635 Hamilton Road Lynx, OR 

### 45650
937 -544-71 04

6 · "ENVIRONMENTAL PROTECTION AGENCY HEARING April 21, 2011
My name is William J. Tipton. I lived at 508 Tipton lane Nile Township Scioto County Ohio.

The State of Ohio's requirements for burning of bio-mass fuels in our power plants and the burning of Shawnee State Forest could have a negative effect on the industrial development of Scioto County.

Due to the regulations of the Environmental Protection Agency for clean air and the loss of our old dirty industries here in Scioto and adjoining counties the air quality has improved. This is good news for our physical health and the industrial development of Scioto County.

Let me interject here that I feel the Environmental Protection Agency should never be abbreviated EPA. The term EPA is used by those who want us to forget who you really are and what you stand for. In all your statements and communications you should insist that Environmental Protection Agency be spelled out.

I assume that you monitor the air quality every day and therefore extremely high days of pollution would bring the over -all average up.

The State of Ohio is requiring the burning of bio-mass fuels in our power plants that were never designed to burn anything but coal. Just the burning of bio-mass in one of our power plants, we have three very close to us, will increase carbon-monoxide ·in our air by one thousand two hundred and

. fourteen tons. All the power plants will probably be doing this in the future. Another effect is that biomass is 90% wood. This means the loss of thousands of acres of trees. What effect will that have on our air quality? Next the unnecessary burning of our sixty three thousand acre forest will add untoid thousands of tons of air pollution and the loss of more trees. Therefore the State of Ohio that proclaims to want to help make jobs here in our area is one of our biggest enemies. i know that making jobs is not your primary concern but making sure we have clean air is your major concern. The Environmental Protection Agency should recommend that these unnecessary sources of air

# :::::";:'''~''v~#~ William J. Tipton 508 Tipton Lane Stout, Ohio 45684 740-858-2197 email wtipton3@columbus.rr.com· Dec 07 10 05:14a p.1



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### o 97875 HEARING. PUBLIC 042111.txt

BEFORE THE OHIO ENVIRONMENTAL PROTECTION AGENCY

In re: Redesignation and Maintenance Plan for the ohio Portion of the Huntington-Ashland, OH-KY-WV Annual PM 2.5 Non-Attainment Area

Before Mary McCarron, public Involvement Manager Taken at portsmouth city Health Department 605 washington street 1st Floor Conference Room

portsmouth, ohio 45662 April 21, 2011, 1:35 p.m.

DepoNet 101 Marietta Street 2700 Centennial Tower Atlanta, Georgia 30303 (800) 337-6638

1 ATTENDEES 2 carolina M. prado, ohio EPA Environmental specialist 3 

### cindy charles, page 1 1

2

### o 97875 HEARING. PUBLIC 042111.txt 4 USEPA and OEPA Representative
5 

### Robert walton 6 

### Barbara A. Lund 7 John Essman 8 

### william J. Tipton 9 

### Frank Lewis 10 Bob walton, Jr. 11 Scott Evans 12 Don Hadsell 13 Robert Klouman 14 David Malone 15 16
17 

### 18 19 

### 20 21 22 23 24

3

1 

### 2 3 

### 4 

### PRO C E E DIN G S

MS. MCCARRON: All right. we're going 5 to go ahead and get started. My name is Mary 6 Mccarron. I'm public information officer for ohio 7 EPA, and I'll be presiding over the hearing today.
page 2

### o 97875 HEARING. PUBLIC 042111.txt 8 I want to thank you for taking the time to attend 9 the hearing. 10 The purpose of this hearing is to 11 obtain any comments from any interested person 12 regarding ohio EPA's proposed action. The state 13 of ohio is proposing to ask U.s. EPA to officially 14 recognize that the air quality in the portsmouth 15 area meets the 1997 federal fine particulate 16 standards. portsmouth is part of the Huntington, 17 West virginia and Ashland, Kentucky metropolitan 18 area. 19 The proposed redesignation request 20 affects Adams, Gallia, Lawrence, and Scioto 21 counties in ohio. The states of West virginia and 22 Kentucky would need to submit separate requests to 23 u.s. EPA to redesignate counties in their states 24 associated with this area.

4

1 

### Comments can be submitted until the 2 close of business today, April 21st, 2011. You 3 may email comments to Carolina, c-a-r-o-l-i-n-a, 4 dot, Prado, p-r-a-d-o, at epa.ohio.gov. That 5 email address is also included in the handout that 6 was at the registration table. 7 All interested persons are entitled to 8 attend or be represented and to present oral 9 and/or written comments concerning the proposed 10 action. All written and oral comments received as 11 part of the official record will be considered by Page 3

### o 97875 HEARING. PUBLIC 042111.txt 12 the director of the ohio EPA before a final 13 decision is made. Written statements submitted 14 after the comment period closes may be considered, 15 as time and circumstances permit, but won't be 16 part of the official record. 17 If you wi sh to present oral testimony 18 and haven't signed in, I'm going to call folks up 19 in the order they signed in. If you don't want to 20 speak or provide testimony, just go ahead and say, 21 "Pass." If you do want to provide testimony, I 22 just ask that you state your name and spell it for 23 our court reporter and then proceed with your 24 testimony.

5

1 

### We are going to do a five minute limit 2 on testimony today. So if you can't get through 3 everything you wanted to say and you do have a 4 written document, please submit that as part of 5 the record as well. 6 And just as we say at every heari ng, 7 there's no cross-examination of speakers or 8 representatives of ohio EPA in public hearings 9 such as this. our hearings provide citizens the 10 opportunity to submit comments to us. ohio EPA 11 staff might ask clarifying questions of folks 12 providing testimony so that the record is as 13 accurate as possible. 14 I'm going to go ahead and read the 15 names of the folks who have registered. Again, if
page 4

### 97875 HEARING. PUBLIC 042111.txt 16 you would like to provide testimony, go ahead and 17 state your name, spell it for the court reporter, 18 and then proceed with your testimony, with a five 19 minute limit. 20 The person who first signed is Robert 21 walton. 22 23 MR. WALTON: Thank you. MS. McCARRON: If you could spell your

o 24 name for the court reporter, and then go ahead and

1 start. 6

2 

### MR. WALTON: Robert, R-o-b-e-r-t, 3 w-a-l-t-o-n. 4 

### Question: First, this is

-- you've got 5 here 1/30th particulate matter, so what
6 

### MS. McCARRON: During the public 7 hearing, we're not

-- we won't be answering 8 questions, but if you want to submit that question 9 as part of the official record, please do so. 10 MR. WALTON: well, I was just wondering 11 how that related to 2.5 and 10, which is what 12 we-- 13 MS. McCARRON: This is a 2.5. The 14 particulate matter is 2.5. 15 MR. WALTON: This is a 2.5. Thank you 16 for answering a question when you weren't supposed 17 to. 18 19 MS. McCARRON: NO problem. MR. WALTON: I have another question
page 5

### o 97875 HEARING. PUBLIC 042111.txt 20 that I would like answered. You don't have to do 21 it today. Adams and Gallia, how long have they 22 been in the metropolitan area? I didn't think 23 that they were. I thought the only two ohio 24 counties were Lawrence and scioto.

7

1 

### MS. McCARRON: I don't have that 2 information, so I'm not sure how long they have 3 been in. 4 

### MR. WALTON: And if west virginia and 5 Kentucky does not make this similar request, how 6 will that impact our request with the U.S. EPA? 7 You know, I was

-- in looking at this 8 matter of air quality and being an attainment or 9 non-attainment county, I was under the impression 10 that the entire area was classified either as 11 attainment or non-attainment. 12 Even though we in scioto county have 13 been attainment for several years before now, and 14 Lawrence County, there was not proof that

-- you 15 know, evidence that they were, and I don't think 16 Ashland or Huntington were. But for many years, 17 or several years, I think scioto county met 18 attainment standards, but the other counties in 19 the metropolitan area did not. 20 And we had made a request, the County 21 commissioners, the port Authority, and others 22 locally, had made a request three years ago

-- two 23 years ago, two and a half years ago, that ohio EPA Page 6

### o 97875 HEARING. PUBLIC 042111.txt 24 request U.S. EPA to redesignate us, because we did

1 have, I think three year data that we did meet 2 attainment standards. 3 so I'm just wondering how that

-- I 4 would like the answer to these questions. 8

5


### 6 

### MS. MCCARRON: Okay. MR. WALTON: But I am very, very



### o 7 pleased and very happy to be sitting here today, 8 seeing that presumably the entire metropolitan 9 area has now met the standards. 10 And it's been very difficult being 11 right across the river from Greenup, Kentucky, 12 that is an attainment county. And being in 13 economic development, I'm very much involved in 14 competition with the state of Kentucky, West 15 virginia, and primarily those two states. 16 And we have a situation right now where 17 suncoke, if we were attainment, probably would 18 make a decision to expand in scioto County, rather 19 than doing what they are at this time. And that 20 is applying for a permit to install in Kentucky 21 for Greenup county. 22 So I'm very pleased that all this could 23 change before suncoke is required

-- would be 24 required, if they choose ohio, to buy air credits

Page 7 9

### 97875 HEARING. PUBLIC 042111.txt 1 and put forth a very large expenditure. 2 I also want to comment that there are 3 economic developers who sit in New York City and 4 Los Angeles and look at a map and

-- if air 5 emissions is a concern of theirs, they look at a 6 map, they're going to make a recommendation for 7 expansion of the plant, and they see that scioto 8 County is non-attainment, "x" us out and move on. 9 Don't look any further. 10 So also I'm very happy to know that I'm 11 breathing fresher air, cleaner air. 12 Thank you.
13 

### 14 MS. MCCARRON: Thank you. The next person who has signed is, is 15 Barbara Lund. If you can state your name and 16 spell it for the court reporter, and then proceed 17 with your testimony. 18 MS. LUND: My name is Barbara Lund,

o 19 B-a-r-b-a-r-a. L-u-n-d is my last name. 20 Thank you, ohio EPA, for holding this 21 hearing and allowing me to comment on the request 22 to U.S. EPA to change the current non-attainment 23 designation for this region to one of attainment. 24 Now, I know that this hearing is just a

1 formality. Nonetheless, I appreciate the 2 opportunity to speak on the record and to be 3 accorded due process. 4 Let me start by saying that less bad is Page 8 10

### 97875 HEARING. PUBLIC 042111.txt 5 no good. That's a concept. Less bad is no good.
6 

### ohio EPA is claiming that the dirty air



### o 7 of this region is cleaner, is clean enough. It 8 was at one time so dirty that it was dirtier than 9 the national allowable standards; thus, the region 10 was considered to be non-attainment with respect 11 to those standards. 12 ohio EPA says that now its tests and 13 monitoring show that the air is less dirty than 14 the u.s. standard, that the air is clean enough to 15 be designated an attainment of the standards for 16 clean. The quality of air is cleaner. It is 17 still dirty. It is less bad, but it's still not 18 good. 19 No data is presented to correlate 20 cleaner air with better health. I skipped over a 21 little bit of this. Why do we even have 22 regulations? That simply assumed that cleaner air 23 is correlated with better health. 24 I challenge that assumption with the

1 concept that less bad is no good. Yes, the air is 2 cleaner and there are probably fewer bad health 3 effects. But although cleaner, the air is still 4 dirty and is still probably having adverse health 5 affects not only on humans, but on all other 6 animals and also on plants. That is not good. 11

7 

### one might argue that one cannot have 8 zero particulate matter. And to that I say: why Page 9

### 97875 HEARING. PUBLIC 042111.txt 9 not? At least why not zero particulate matter 10 emissions from human industrial activity. These 11 emissions are waste products called pollution. 12 Let me quote from a book called cradle 13 to Cradle by william McDonough and Michael 14 Braungart. And that's B-r-a-u-n-g-a-r-t. Quote, 15 "TO eliminate the concept of waste means to design 16 things (products, packaging, and systems) from the 17 very beginning on the understanding that waste 18 does not exi st," end quote. 19 Nature doesn't have waste. Humans



### o 20 should emulate nature. 21 Skip part of this testimony. 22 The world is now in a crisis situation 23 from the many human industrial wastes and 24 pollutants. Another quote, and this one by Albert

1 Ei nstei n, "The wor1 d wi 11 not evolve past its 2 current state of crisis by using the same thinking 3 that created the situation," end quote. 4 Thinking that less bad is good, is not 5 good enough. Less bad is no good. Thinking needs 6 to be about only good. 7 EPA is a regulatory agency, and here's 8 what cradle to cradle says about regulation, 9 quote, "But ulti matel y a regu1 ati on is a si gna 1 of 10 design failure. In fact, it is what we call a 11 license to harm; a permit issued by a government 12 to an industry so that it, the industry, may Page 10 12

### o 97875 HEARING. PUBLIC 042111.txt 13 dispense sickness, destruction, and death at an 14 ' acceptab 1 

### e' 1 

### eve 1 ," 

### unquote. 15 EPA is no doubt trying to follow the 16 letter of the law, working in industry and giving 17 permits to allow the maximum waste pollution up to 18 the limits of the law. supposedly, this let's 19 industry 

### avoid as much pollution control costs as 20 possible. 21 AS a citizen who has to breathe 22 whatever air is around me wherever I am, I want 23 EPA to follow the intent of the law, to work with 24 industry to eliminate all waste and all pollution

1 such that regulation would not be necessary. 2 I have a paragraph about how I feel 3 that EPA, in following national laws, ought to do 4 better than the national laws. There's no law 13

5
6

7
8
9 

### against doing better. One specific thing that bothers me about the redesignation proposal is that it is for the ohio portion of the non-attainment area. TWO of Barry commoner's ecological laws 10 say that, quote, "Everything is connected to 11 everything else. Everything has to go somewhere." 12 The air in this geographic region is 13 not fixed to this region. It's a part of and 14 intimately connected to the world atmosphere. Air 15 circulates in the atmosphere throughout the world, 16 and this has been vividly demonstrated recently by Page 11

### 97875 HEARING. PUBLIC 042111.txt 17 radioactive material produced in Japan being 18 detected in countries around the world. 19 Not all the air pollution measured in 20 this region was produced in this region. Much 21 came from upwind. By the same token, not all the 22 air pollution produced in this region stays here. 23 It moves downwind to other areas.



### o 24 MS. McCARRON: You've got about one

14

1 more minute.

2 

### MS. LUND: I was down on Highway 52 3 this morning and the wind was blowing from the 4 north and blowing the plant emissions into 5 Kentucky, a different region. 6 These geographi cal boundari es are 7 conceptual and have no real meaning for air, which 8 has no boundaries. 9 This is related closely to another 10 concern I have. In the conclusion of the draft 11 Redesignation Request it says, "The air quality 12 improvements are due to permanent and enforceable 13 measures." And it also says, and I won't use this 14 whole quote, but that EPA has the legal authority 15 and necessary resources to enforce. The authority 16 is there. But will it be used, and will there be 17 the resources? I have had too much knowledge and 18 experience with EPA to think that they will not 19 use their authority. 20 skipping some of this. It will be in Page 12

### o 97875 HEARING. PUBLIC 042111.txt 21 the written. 22 I'm concerned that the current 23 administration strongly favors private economic 24 activity over public welfare, that it has a strong

1 bias for deregulation, that it has little if any 2 understanding of ecology, and that it will help 3 balance the budget by inappropriately cutting 4 funding to ohio EPA. They are likely to be far 5 too few ohio EPA employees to do all the necessary 6 monitoring and enforcement of the clean air laws. 7 Despite their best intentions to do a proper job, 8 ohio EPA may not have the proper administrative 9 support. 10 I hope I'm wrong, but I believe that 11 ohio EPA will have trouble maintaining pollution 12 controls and providing enforcement to stay in 13 attainment. There are contingency plans in case 14 of failure, and perhaps they will suffice. 15 In conclusion, I cannot support a 16 redesignation from non-attainment to attainment 17 for this region, but neither do I formally oppose 18 it. 19 In my opinion, the whole world needs to 20 be declared a non-attainment for industrial 21 pollutants to the earth's atmosphere. Everyone 22 needs to be working, not for attainment for some 23 arbitrary acceptable level of pollution, but for 24 total elimination of industrial pollution with no page 13 15

### o



### o 97875 HEARING. PUBLIC 042111.txt

1 need for regulation. 2 We need to strive for complete good, 3 because less bad is no good. 4 MS. MCCARRON: Thank you. 5 John Essman. 6 MR. ESSMAN: I will pass. 7 MS. McCARRON: okay. And william 8 Tipton. 9 MR. TIPTON: Yes. My name is william 10 Tipton, W-i-l-l-i-a-m, T-i-p-t-o-n. I live at 508 11 Tipton Lane, Nile Township, Scioto County. 12 The State of ohio's requirements for 13 burning of biomass fuels in our power plants and 14 the burning of Shawnee State Forest could have a 15 negative effect on industrial development of 16 Scioto County. 17 Due to the regulations of the 18 Environmental protection Agency for clean air and 19 the loss of our old dirty industries here in 20 scioto and adjoining counties, the air quality has 21 improved. This is good news for our physical 22 health and the industrial development of scioto 23 County. 24 Let me interject here that I feel that

Page 14 16

17

### o 97875 HEARING. PUBLIC 042111.txt 1 the Environmental Protection Agency should never 2 be abbreviated EPA. The term EPA is used by those 3 who want us to forget who you are and what you 4 really stand for. In all of your statements and 5 communications, you should insist that 6 Environmental protection Agency be spelled out. 7 I assume that you monitor the air 8 quality every day; therefore, extremely high days 9 of pollution would bring the overall average up. 10 The state of ohio is requiring burning 11 of biomass fuels in our power plants that were 12 never designed to burn anything but coal. Just 13 the burning of biomass in one of our power 14 plants

-- and we have three here very close 15 will increase carbon monoxide in our air by 1,214 16 tons. All the power plants will probably be 17 forced, if this rule isn't changed, to burn 18 biomass in the future. 19 Another effect is that biomass is 90 20 percent wood. This means the loss of thousands of 21 acres of trees. And what effect would that have 22 on the quality of our air? 23 Next is the unnecessary burning of our 24 63,000 acre forest, and that will add untold

1 thousands of tons of air pollution and the loss of 2 more trees. 3 Therefore, the State of ohio, that 4 proclaims to want to help make jobs here in our Page 15 18

### 97875 HEARING. PUBLIC 042111.txt 5 

### area, is one of our biggest enemies. I know that 6 making jobs is not your primary concern, but 7 making sure we have clean air is your major
8 

### concern. 9 

### The Environmental protection Agency 10 should recommend that these unnecessary sources of 11 air pollution be stopped. 12 Thank you. 13 14 15 

### 16 reporter. 17 18 19 

### 20 MS. McCARRON: Thank you. Frank Lewis. MR. LEWIS: No. I'm just here as a

MS. McCARRON: Sorry. MR. LEWIS: That's okay. MS. McCARRON: Bob walton, Jr. MR. WALTON: Yes. My name is Bob

o 21 Walton, w-a-l-t-o-n, Jr. I live at 2244 Simon 22 Miller Road in wheelersburg, ohio. 23 I'm here today really as a resident and 24 as someone who has served as a local public

1 official, a township trustee in Porter Township, 2 where many folks who work in the eastern end of 3 the county live, specifically at sunCoke and 4 Sunoco. 5 From the standpoint as a former 6 township trustee, my job primarily was one of 7 safety, providing safe roads, providing a fire· 8 department, an EMS department, providing
page 16 19

### o 

### 97875 HEARING. PUBLIC 042111.txt 9 recreation and parks that were safe. 10 AS a resident and a father of two young 11 children, safety is always on my mind. My wife 12 and I try to provide them with a safe place to 13 grow up, to go to school, to live and have fun, 14 and hopefully graduate and be able to come back to 15 this area or to stay in this area and raise their 16 children in a safe environment. 17 The air has gotten a lot cleaner here 18 since we moved back here about 10 years ago when 19 the coke plant was still in operation. What I 20 would ask is for the EPA to push as hard as they 21 can, the u.s. EPA, for the redesignation. 22 I'd like for my kids to be able to have 23 an opportunity to come back and work for a company 24 like suncoke or Sunoco, for a company that puts a

1 lot of people in employment with good jobs, with 2 safe jobs. And with this proposed expansion of 3 theirs, many more would have the opportunity to do 4 so. 5 It only makes sense that the same air
6 

### that we basically breathe with our friends across 7 the river in Greenup would have the same 8 designation of attainment. And so I would ask for 20

9 

### 10 11 12 the ohio EPA to do what they can to make sure that

we become an attainment area so that a company like Suncoke, who has done a lot for the community, can do even more. page 17

### 97875 HEARING. PUBLIC 042111.txt 13 And then for someone who could be 14 looking at coming to Eastern Scioto county to 15 employ many people will be able to do so, instead 16 of going down the river to somewhere in Kentucky 17 with the same air with an attainment designation. 18 19 20 21 And that's it. Thank you. MS. McCARRON: All right. Thank you. Scott Evans. MR. EVANS: Yes. I am scott Evans,



### o 22 S-c-o-t-t, 

### E-v-a-n-s. I am a scioto County 23 native, currently residing at 5990 pinto Pass 24 Drive, Hilliard, ohio, due to my position as a

1 legislative aide for state Representative Terry 2 Johnson of the 89th District. 3 I would ask for a bit of leniency on 4 the five minute limit, because I'm representing 5 two different individuals and three different 6 entities. 21

7 

### MS. McCARRON: Okay. Are you going to 8 designate which

-- 9 

### 10 11 MR. EVANS: I shall. MS. MCCARRON: okay. That works. MR. EVANS: First off, on behalf of 12 State Representative Terry Johnson, I would like 13 to read into the record a letter that 14 Representative Johnson sent to Director scott J. 15 Nally of the ohio Environmental protection Agency 16 on April 15th of this year. page 18

### o 97875 HEARING. PUBLIC 042111.txt 17 "Dear Di rector Na 11 

### y, 18 "I am writing in support of the 19 proposal to redesignate the portsmouth, ohio air 20 quality as meeting the 1997 federal fine 21 particulate standard. portsmouth is part of the 22 Huntington, West virginia-Ashland, Kentucky 23 metropolitan area, and the air quality data from 24 2008 through 2010 shows that the area has

1 successfully met the 1997 national fine 2 particulate standards for over three years. 3 "Thi s area has been be 1 

### ow the na ti ona 1 

### 4 standard over this entire three year period by a 5 substantial margin. As a result, I wholeheartedly 6 support your initiative to ask the u.s. 7 Environmental Protection Agency to redesignate the 8 area to reflect full compliance with the standard. 9 "This redesignation is vital for our 10 local economy and would allow industry to locate 11 in Southern ohio without the need to obtain air 12 quality offsets. It would have an enormous 13 positive impact for the entire region. scioto, 14 Adams, Gallia, and Lawrence counties in ohio would 15 be much more competitive when recruiting 16 respective employers. If ohio does not get this 17 redesignation, then Kentucky and West virginia 18 likely will. That would have basically the same 19 impact on our air quality with little or no 20 economic benefit for ohio.
page 19 22

### o 97875 HEARING. PUBLIC 042111.txt 21 "AS a practicing physician, I know the 22 adverse affects that can result from excessive 23 particulate matter in the air we breathe. 24 However, I am convinced that current national

1 state and local air pollution controls which limit 2 particulate matter-causing emissions will enable 3 the area to maintain the required air quality and 4 advance the economic development we so desperately 5 need. 6 "Thank you for considering this 7 request." 8 signed Terry Johnson, State 9 Representative. 23

10 11 MS. MCCARRON: Thank you. MR. EVANS: Then on behalf of 12 Dr. william Dingus, who is writing in two 13 capacities, first as executive director of the 14 Greater Lawrence county Area Lawrence Economic 15 Development corporation, and then also as the 16 executive director of the Lawrence County port 17 Authority. I offer first his correspondence from 18 the Lawrence Economic Development corporation. 19 "In regards to the air quality 20 redesignation within our region, the Lawrence 21 Economic Development corporation would like to 22 express its support of reclassifying Lawrence 23 County, ohio to be in compliance with the national 24 standards for 2.5 particulate emissions. our main
page 20

### o

o 97875 HEARING. PUBLIC 042111.txt

1 concerns have always been drifting emissions from 2 the Kentucky side of the ohio River and therefore 3 have expected a higher compliance level, although 4 not previously reqUired, from our power plants 5 along the ohio River. 6 "Our responsibility as an ohio 7 community improvement corporation is to encourage 8 business growth, as well as to promote the quality 9 of life in our region. It is our firm belief that 10 Lawrence county companies emit far below the 11 national emission standards. we have been in 12 compliance and will continue to maintain 13 compliance of regulatory controls to limit and 14 lower 2.5 particulate emissions in the 15 Huntington-Ashland area past the 10 year 16 requirement for designation. 17 "We ask you to consi der thi s request on 18 behalf of Lawrence county for the betterment of 19 our community. 20 "sincerely, Bill Dingus, PhD, Executive 21 Di rector. " 22 And then in his capacity as executive 23 director of the Lawrence county Port Authority, 24 Dr. Dingus offers the following: 24

25

1 

### "The Lawrence county Port Authority page 21

### o 97875 HEARING. PUBLIC 042111.txt
2 

### hereby goes on record endorsing the changing of 3 

### compliance status for Adams, Gallia, Lawrence, and
4 

### scioto counties in ohio. The air quality data
5 

### shows that the region is now meeting the fine
6 

### particulate standards, and it is requested by our 7 agency that appropriate redesignation occur to
8 

### allow the strides made in the region in improving 9 

### air quality. 10 "currently, economic development 11 efforts being made to recruit family wage jobs are 12 hindered by the incorrect designation. Numerous 13 

### industries have closed which were contributing to 14 the emissions levels, and great strides have been 15 made in applying efforts through available ODOT
16 

### funds to further eliminate air emissions. This 17 

### barrier discourages consideration of these 18 

### relatively poor counties to be considered for 19 

### private manufacturing economic growth, thus 20 contributing to older vehicles that have greater 21 emissions, as well as a lower standard of living 22 for the region.
23 

### "please recognize the efforts and 24 accomplishments that have been made in this four

1 

### county region by providing a redesignation of
2 

### meeting standards and, thereby, open new 3 

### opportunities for our region. please do not 4 

### hesitate if information is needed to quantify the
5 

### importance of thi s change." page 22 26

### 97875 HEARING. PUBLIC 042111.txt 6 And for the record, I would say that we 7 have also honored Dr. Dingus' request to read his 8 correspondence into the record, as he and the 9 entities that he represents are constituents in 10 the 89th ohio House District. 11 I thank you for this opportunity to 12 speak on the record, and will gladly give you 13 copies of the correspondence that I just read. 14 15 16 

### MS. MCCARRON: Thank you. Don Hadsell. MR. HADSELL: Yeah, Don Hadsell,



### o 17 H-a-d-s-e-l-l. 18 I've got a letter I'm going to put on 19 the record I'll .read. 20 "I am writi ng to you today from the 21 prospective of an owner of a local construction 22 business, a developer of industrial parks in 23 Southeast Ohio, and as a lifelong resident of 24 Scioto county. I am asking your assistance in

1 having scioto and Lawrence county redesignated as 2 an attainment with the u.S. EPA. 3 "As you know, successful economi c 4 development is a public/private partnership that 5 many times requires the public sector to help 6 provide the necessary infrastructure and 7 environment for private industry to then make an 8 investment of capital. 9 For many years my company, Hadsell Page 23 27

### o 97875 HEARING. PUBLIC 042111.txt 10 Development, has worked with the Southern ohio 11 port Authority in scioto county and the LEDC in 12 Lawrence county to redevelop former steel mill 13 property in New Boston and ethanol plant property 14 in South point. This was made possible through 15 federal, state, and local grants that were used 16 for such purposes as brownfield restoration and 17 infrastructure development. I have worked with 18 the ohio EPA on many projects over the years. Few 19 are as important as what is and could be coming to 20 Eastern Scioto county this year. 21 "what we know for sure is that a local 22 company, suncoke, provides many good-paying jobs 23 and contri butes si gni fi cantl y to the 1 

### oca 1 

### and 24 state tax base. They are going to construct an

lover $500 million plant expansion in either scioto 2 county or across the river and state-line in 3 Greenup county. 4 "why are they considering off-site 5 plant extension? It's simple. Right now they can 6 do it for less in Kentucky. Not because the 7 materials, land, and labor will be any cheaper. 8 It's because even though we breathe the same air 9 as they do in Greenup County, scioto county is 10 classified by the U.S. EPA as a non-attainment 11 County. 12 "As long as that conti nues, we'll be at 13 a significant disadvantage of bringing any new Page 24 28

### 97875 HEARING. PUBLIC 042111.txt 14 manufacturing through our area, and ohio could 15 lose a half-billion dollar expansion to our 16 neighbors who are literally a stone's throwaway. 17 "Because we have been testi ng in 18 attainment for several years, our area deserves to 19 quickly receive an attainment designation so that 20 we can move forward in creating a more business 21 and worker-friendly environment that will 22 positively impact our local, state, and regional 23 economy. 24 "Thank you for your assistance."

o 29

1 And my companies that I represent are 2 called

-- all of our companies are Hadsell 3 Development, J&H Erectors, McGoVney Ready Mix and 4 River Terminal and Point Commerce, LLC.

Robert Klouman. MR. KLOUMAN: pass. MS. McCarron: okay. Thank you.

MS. McCARRON: oh, you're passing? 5
6
7
8 

### 9 okay. 10 And I believe David Malone has left. 11 At this time there's nobody else who 12 has signed in, so we're going to go ahead and end 13 the hearing. I just wanted to remind everybody 14 that if you want to submit written comments, they 15 are due by the end of business today, 5 p.m. 16 today. 17 And the time is now 2:05, and I want to Page 25

### o 97875 HEARING. PUBLIC 042111.txt 18 thank everybody for attending. This hearing is 19 now adjourned. 20

- - - - - 21 Thereupon, the foregoing proceedings 22 concluded at 2:05 p.m. 23 24

1
2 

### 3 state of ohio : C E R T I F I CAT E County of Franklin: SS 4 

### I, crystal simpson, a Notary Public in and 5 for the state of ohio, do hereby certify that I reported the aforementioned proceedings; that the 6 foregoing is a true record of the proceedings. 7 I do further certify I am not a relative, employee or attorney of any of the parties hereto, 8 and further I am not a relative or employee of any attorney or counsel employed by the parties 9 hereto, or financially interested in the action. 10 IN WITNESS WHEREOF, I have hereunto set my hand and affixed my seal of office at columbus, 11 ohio, on April 22, 2011. 12 13 14 15 16 17 18 19 20 crystal simpson, Notary Public

- state of ohio My commission expires April 27, 2013. 21 page 26 30

### o 22
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### 24 97875 HEARING. PUBLIC 042111.txt

page 27

### 1 Response to Comments PM 2.5

### redesignation request for the 1997 PM 2.5

### Annual Standard for the Huntington-Ashland Area Agency Contact for this Package Division Contact: (Carolina Prado, Division of Air Po llution Control, 614-644-2310, Carolina.Prado@epa.state.oh.us) Ohio EPA held a public hearing in Portsmout h, OH on April 21, 2011, regarding the Redesignation Request and Maintenance Plan for the Huntington-Ashland PM 2.5 

### Nonattainment Area. This document summarizes the comments and questions received at the public hearing and during the associ ated comment period, which ended on April 21, 2011. Ohio EPA reviewed and consider ed all comments received during the public comment period. By law, Ohio EPA has authority to consider specific issues related to protection of the environment and public health. In an effort to help you review this doc ument, the questions are grouped by topic and organized in a consistent format. The name ofthe commenter follo ws the comment in parentheses.
Ohio EPA received four letters in supportof the redesignation request for the 1997 PM 2.5

### Annual Standard for the H untington-Ashland Area (State Representative Terry A. Johnson, 89 th 

### Ohio House District; Bill Dingus, Executive Director for the Lawrence Economic D evelopment Corporation; Bill Dingus, Executive Director for th e Lawrence County Port Aut hority and; Don Hadsell, President for The Hadsell Companies).

General Comments/Overall Concerns Comment 1: Adams and Gallia, how long have they been in the metropolitan area? I didn't think that they were. I thought the only two Ohio counties were Lawrence and Scioto. (Robert Walton). One specific thing that bothers me about the redesignation proposal is that it is for the Ohio portion for the Huntington-

### 2 Ashland, Ohio, Kentucky, West Virginia nonattainment area for annual PM2.5 – the counties of Adams, Gallia, Lawrence and Scioto. Two of Barry Commoner’s ecological laws say that, “Everything is connected to everything else and Everything has to go somewhere.” The air in this geographic region is not fixed to this region. It’s a part of and intimately connected to the world atmosphere. Air circulates in the atmosphere throughout the world. This has been vividly demonstrated recently by radioactive material produce in Japan being detected in count ries around the world. Not all the air pollution measured in this region was produced in this region. Much came from upwind. By the same token, not all the air pollution produced in this region stays here; it moves downwind to other areas. In my opinion, these geographical boundaries, which are conceptual, have no real meaning for air which has no boundaries and which is always in motion, always ch anging, much as a river flows continuously with different wa ter at any one place at any given moment in time (Barbara Lund). Response 1: The Huntington-Ashland metropo litan statistical area (MSA) includes five counties in WestVirginia (Cabell and Wayne), Kentucky (Boyd and Greenup) and Ohio (Lawrence). Nonattainment areas are not onlyselected based upon an MSA. Rather, selection is based on seve ral factors including, but not limited to, air monitoring data a nd emissions sources that can influence monitored violations. Th is ensures that not only the immediate area that contains a monitor showing a violation is designated as nonattainment but those adjacent areas that contribute to the violation are also designated as nonattainment. Within Ohio, Scioto County is included as part of nonattainment area because the county, along wit h Lawrence County, contained a violating monitor at that time. The partial areas of Adams and Gallia counties, even though they are not part ofthe HuntingtonAshland MSA, were included as part of the nonattainment area primarily because of the existenc e of an electric generating unit (EGU - power plant) in the to wnships designated nonattainment (Monroe and Sprigg Townships in Adams County and Cheshire Township in Gallia County). Em issions from these sources may contribute to violations at those monitors in t he adjacent counties. Comment 2: And if West Virginia and Kentucky does not make this similar request, how will that impact our request with the U.S. EPA? In looking at this matter ofair quality and being an attainment or non-attainme nt county, I was under the

### 3 impression that the entire ar ea was classified either as attainment or non-attainment. Even though in Scioto County we have been attainment for several years before now, and Lawrence County, there was no proof that –evidence that they were, and I don't think Ashland or Huntington were. Bu t for many years, or several years, I think Scioto County me t attainment standards, but the other counties in the metropolitan area did not. The County Commissioners, the PortAuthority, and others locally, had made a request thr ee years ago – two years ago, two and a half years ago, that Ohio EPA request U.S. EPA to redesignate us, because we did have, I think three year data that we did meet attainmentstandards (Robert Walton). Response 2: In order for any single county(or partial county) designated nonattainment to be redesignated to attainment all monitors located within the entire area (all counties) must show attainment for a 3-year period. All monitors in this area showed attainment for the first time for the 2007 to 2009 period. Theref ore, in 2010, Ohio EPA began working with the environmental agencies in Kentucky and West Virginia, in a jo int effort to prepare information necessary for the redesignations. However, each state agency is responsible for preparing and submi tting their own redesignation request. USEPA Region 5 will act on Ohio's request individually and redesignate only the four count ies in Ohio (Adams, Gallia, Lawrence and Scioto counties). Counties in West Virginia and Kentucky will remain nonattainment until such time they make a request and their USEPA regions (which differ from Ohio’s) act upon their submittal. During anytime period where Ohio's counties are designated attainmentand another state’s counties are designated nonattainment, Oh io would follow its approved maintenance plan while the other state would continue to follow the requirements for nonattainmentareas (e.g., applying offset ratios during major source permitting). Comment 3: I am very pleased and very happy to be sitting here today, seeing that presumably the entire metropolitan area has now met the standards. It's been very difficult being right across the river from Greenup, Kentuc ky, that is an attainment county. Being in economic development, I'm very much involved in competition with th e State of Kentucky and West Virginia, and we have a situati on right now where SunCoke, if we were attainment, probabl y would make a decision to expand in Scioto County, rather than doing what they are at this time, which is applying for a permit to install in Kentucky

### 4 for Greenup County. So I'm very pleased that all this could require, if they choose Ohio, to buy air credits and put forth a very large expenditure. I also want to comment that there are economic developers who sit in New York City and Los Angeles and look at a map a nd -- if air emissions is a concern of theirs, theylook at a map, th ey're going to make a recommendation for expansion of the plant, and they see that Scioto County is non-attainment, "X" us out and move on. Don't look any further. Soalso I'm very happy to know that I'm breathing fresher air, cleaner air. (Robert Walton). Response 3: Thank you for your support and concern for the Ohio EPA proposed redesignation and maint enance of the HuntingtonAshland PM 2.5

### Nonattainment Area. Comment 4: Let me start by saying that less bad is no good. That's a concept. Less bad is no good. Oh io EPA is claiming that the dirty air of this region is cleaner, is clean enough. It was at one time so dirty that it was dirtier than the national allowable standards; thus, the region was considered to be non-attainment with respect to those standards, the national ambient air quality standards for annual PM 2.5 

### . Ohio EPA says that now its tests and m onitoring show that the air is less dirty than the US standard, that the air is clean enough to be designated an attainment of the standards for clean. The quality of air is cleaner. It is still dirty. It is less bad, but it's still not good. (Barbara Lund). Response 4: Thank you for your comments and concern for the Ohio EPA proposed redesignation and maint enance of the HuntingtonAshland PM 2.5

### Nonattainment Area. The Ohio EPA strives to constantly improve air quality for all Ohio and during the last 14 years (since the establishment of the PM 2.5 

### annual standard) Ohio EPA has been working together wit h the regulated community to reduce atmospheric emission s and achieve or go beyond USEPA’s mandates. Comment 5: The March 2010 draft of the Redesignation and maintenance plan says nothing about why pa rticulate matter is regulated or what the benefits are of lowering the amounts of particulate matter. The State Im plementation Plan for PM2.5, revised June 7, 20 10, does say the following: ‘The NAAQS area air quality standards for pollutants that pose public health risks. High levels of PM2.5 can contribute to a number of health impacts, including pr emature mortality, aggravation of respiratory and cardiovas cular disease, lung disease,

### 5 decreased lung function, ast hma attacks, and other cardiovascular impacts.” No data is presented to correlate cleaner air with better health . That is simply assumed, I challenge that assumption with the concept that less bad is no good. Yes, the air is cleanerant there are probably fewer bad health effects. But although cleaner, the air is still dirty and is still probably having adverse health, affects not only on humans, but on all other anim als and also on plants. That is not good. (Barbara Lund). Response 5: Particulate matter is one of the si x criteria pollutants monitored and regulated by Ohio EPA. Easily inhaled into lungs, particulate matter poses a host of health effects, and represents one of the most important criteria air polluta nt challenge facing our state and region. Achieving significant reduc tions in particulate matter is one of Ohio EPA’s priorities. Overthe past 14 years Ohio EPA has made significant progress in r educing particle pollution in the Huntington-Ashland area and has now attained the federal quality standard (which is shown in this redesignation request). This is evidenced in the actual PM 2.5 

### monitoring data in the area. For the monitors located in Ohio’s tw o counties, monitoring data has shown a decrease from a high of 22.03 ug/m 3

### (1999 to 2001) to a low of 11.6 ug/m 3

### (2008 to 2010). Lowering PM 2.5

### emissions and meeting the federal air qual ity standard was achieved by controlling and modernizing faciliti es and/or sources in the area; USEPA studies show that PM 2.5

### emission reductions results in better health protections for the peopl e living near these facilities. A state is not required to pr epare a risk analysis or health benefits analysis as part of a redesignatio n request and maintenance plan. USEPA prepares these analyses as part of the review of national ambient air quality standards. US EPA's mandate is to protect public health and welfare with an adequate margin of safety. This means that USEPA does not cons ider costs or other economic factors in setting air quality standar ds, rather its decision is purely a public health decision. USEPA did perform such analyses when it established the 1997 annual PM 2.5

### standard at 15.0 ug/m 3 

### . At that time, USEPA determined t hat meeting this level would provide for the necessary health benefits with an adequate margin of safety. USEPA reviews each standard every five years and again prepares appropriate analyse s to determine an acceptable level for the standard based upon the most recent scientific evidence. USEPA has been c onducting such a review and intends to announce its recommendation on any necessary changes to the PM 2.5

### standards this year. For the current level of the standard, Ohio EPA has fulfilled all statutory requirements, as

### 6 evidenced in the document, necessary to request this redesignation. Comment 6: One might argue that one cannot have zero particulate matter. And to that I say: Why not? At least why not zero particulate matter emissions from human industrial activity. These emissions are waste products called pollution. Let me quote from a book called Cradle to Cradle by William McDonough and Michael Braungart, "To eliminate the concept of waste means to design things (products, packaging, and systems) from the very beginning on the understanding that waste does not exist." Nature doesn't have waste. Humans should em ulate nature. The world is now in a crisis situation fr om the many human industrial wastes and pollutants. Another quote and this one by Albert Einstein, "The world will not evo lve past its current state of crisis by using the same thinking that created the situation." Thinking that less bad is good, is not good enough. Less bad is no good. Thinking needs to be about only good (Barbara Lund). Response 6: Thank you for your comment on Ohio's PM 2.5

### Redesignation Request for the Huntington-Ashland nonattainment area. Ohio EPA will continue to wo rk with the regulated community to reduce waste and pollution. Comment 7: People have known, probabl y forever, that human activities have harmful effects. The creation of EPA and the Clean Air Act were legislative attempts to do something about waste pollution and its harmful eff ects. Industries like energy, transportation and agriculture are the biggest air polluters, they are largely responsible for the world air crisis, here in the US the EPA has been complic it in that air pollution. EPA is a regulatory agency, and here's what Cradle to Cradle says about regulation, quote, "But ultimately a regulation is a signal of design failure. In fact, it is what we call a license to harm; a permit issued by a gover nment to an industry so that it, the industry, may dispensesickness, destruction, and death at an “acceptable” rate”. Ohio EPA is no doubt trying to follow the letter of the law, working with industry and giving permits to allow the maximum waste pollution up to the limits of the law. Supposedly , that let's industry avoid as much pollution control costs as possible. As a citizen who has to breathe whatever air is around me wherever I am, I want EPA to follow the intentof the law, to work with

### 7 industry to eliminate all wast e and all pollution such that regulation would not be n ecessary. Ohio EPA follows national laws. I’m fair ly sure there is nothing in those laws that says that states cannot do better than the federal government. Here’s an example, in adaptation to climate change, the federal government is doing much too little. Several cities like Chicago and New York and a county in Washington are making their ow n plans for the future and implementing them. Ohio EPA si milarly could be making its own clean air laws better than national ones (Barbara Lund). Response 7: As discussed above, over the past 14 years Ohio EPA has made significant progress in reducing particle pollution in the Huntington-Ashland ar ea. In part this is due to important regulatory requirements establis hed by USEPA, such as the Clean Air Interstate Rule. In addition, Ohio EPA also goes beyond federal mandates. For example, Ohio EPA requires “best available technology” be applied to all new and modified minor sources of air pollution. Ohio EPA will continue to work with the regulated community to reduce wast e and pollution in this area, and all of Ohio. Comment 8: In the conclusion to the draft Redesignation Request is says that: “the air quality improvements are due to permanent and enforceable measures.” The text says that Ohio commits to maintaining control measures a fter redesignations. It also says, “Ohio, through Ohio EPA’s legal section, has the legal authority and necessary resour ces to actively enforce any violations of its rule or permi t provisions.” The authority is there, but will it be used? And, will there be the resources? I wish that I could totally believe and trust my government, believe and trust Ohio EPA. But based on personal experience and knowledge, I cannot. For years Ohio EPA cited violations at the Stuartpower plant in Adams County and did nothing further with enfo rcement. It took a legal suit by an individual and the Sier ra Club to get some positive action. I believe that any fines are probably so small that a large industry like DP&L would cons ider them just part of the cost of doing business and maybe take them out of the petty cash fund (Barbara Lund). Response 8: Ohio EPA understands your concerns. It is this agency’s intent to implement its maintenance plan, including any necessary contingency measures and applyi ng appropriate and necessary enforcement of air pollution regulations. Ohio EPA’s air enforcement section continues to work with companies to assess

### 8 appropriate penalties for violations , but more importantly, correct the violations. Ohio EPA also has other programs, such as compliance assistance for small busine sses. Ultimately, it is Ohio EPA’s preference to assist companies in complying with regulations so that any enfor cement is not necessary.

Comment 9: I’m concerned that the cu rrent Ohio administration strongly favors private economic activity o ver public welfare, that it has a strong bias for deregulation, that it has little if any understanding of ecology, and th at it will help balance the budget by inappropriately cutti ng funding to Ohio EPA. There are likely far too few Ohio EPA employees to do all the necessary monitoring and enforc ement of clean air laws. Despite their best intentions to do a proper job, Ohio EPA employees may not have prope r administrative support. I hope I’m wrong, but I believe that Ohio EPA will have trouble maintaining pollution controls and providing enforcement to stay in attainment, there are contingency plans in case of failure. Perhaps they will suffice. (Barbara Lund). Response 9: Ohio EPA understands your conc erns. Undoubtedly, Ohio and the nation as a whole, is facing many economic hurdles. Ohio EPA, as does many other gover nment agencies, strives to do more with fewer resources. Howe ver, the mission of Ohio EPA’s Division of Air Pollution Control re mains unchanged; “to attain and maintain the air quality at a leve l that will protect the environment for the benefit of all. ” As the commentor has noted, Ohio EPA’s request does contain contingency measures in the event air quality begins to decline. Ohio EPA is committed to the measures incorporated into this request. Comment 10: I cannot support a red esignation from nonattainment to attainment for this region. But, neither do I formally oppose it. In my opinion, the whole wo rld needs to be declared in nonattainment for industrial pollutants to the earth’s atmosphere. Everyone needs to be working, not for attainment of some arbitrary acceptable level of pollution but for total elimination of industr ial pollution with no need for any regulation (Barbara Lund). Response 10: Thank you for your comment.

Comment 11: The State of Ohio's requirements for burning of biomass fuels in our power plants and the burning of Shawnee State Forest could have a negative effect on industrial development of Scioto County. Due to the regulations of the

### 9 Environmental Protection Agency for clean air and the loss of our old dirty industries here in Scioto and adjoining counties, the air quality has improved. This is good news for our physical health and the i ndustrial development of Scioto County. (William Tipton). Response 11: Thank you for your comment on Ohio's PM 2.5

### Redesignation Request for the Huntington-As hland nonattainment area.

Comment 12: The State of Ohio is re quiring burning of biomass fuels in our power plants that were neve r designed to burn anything but coal. Just the burning of biom ass in one of our power plants -- and we have three here very close -- will increase carbon monoxide in our air by 1,214 tons . All the power plants will probably be forced, if this rule isn't changed, to burn biomass in the future. Another effect is that biomass is 90 percent wood. This means the lo ss of thousands of acres of trees. And what effect would that have on the quality of our air? 63,000 acre forest, and thatwill add untold thousands of tons of air pollution and the loss of more trees. Therefore, the State of Ohio, that proclaims to want to help make jobs here in our area, is one of our biggest enemies. I know that making jobs is not your primary concern, but making sure we have clean air is your major concern. The Environmental Protection Agency should recommend that these unnecessary sources of air po llution be stopped. (William Tipton). Response 12: Ohio EPA is not aware of any regulatory requirement for the burning of biomass bypower plants. We believe the commentor is referring to Ohio’s Senate Bill 221 enacted in 2008. This bill requires that by 2025, 25 percent of electricity sold in Ohio must be generated from alternative energysources, such as clean coal, nuclear energy, fuel cells, hydr o, wind, solar, biomass and cogeneration. Half of this stand ard (12.5 percent) must be met with renewable sources, including a 0.5 percent solar set aside. Also, half of the advanced energy and renewable energy must be located in Ohio. However, this bill does not mandate the burning of biomass by all utilities; rat her, it is one option to fulfill the alternative energy source requirem ent. Ohio EPA will continue to work with utilities as they implement changes to meet Senate Bill 221 to ensure Ohio’s environmental regulations are met.

Comment 13: I feel that the Environm ental Protection Agency should never be abbreviated EPA. The term EPA is used by those who want us to forget who you are a nd what you really stand for.

### 10 In all of your statements and communications, you should insist that Environmental Prot ection Agency be spelled out. (William Tipton). Response 13: Thank you for your suggestion. Ohio EPA always spells out its name at the beginning of the docu ment providing reference to the acronym, EPA. Thereafter, t he acronym is used out of convenience and to reduce resource consumption with no intent of disguising who we are. Ohio EPA prepares many documents and the resulting savings by using the acronym is of benefit in both time and material. Comment 14: I'm here today really as a resident and as someone who has served as a local public official, a township trustee in Porter Township, where many folks who work in the eastern end of the county live, specifically atSunCoke and Sunoco. From the standpoint as a former townshiptrustee, my job primarily was one of safety, providing safe roads, providing a fire department, an EMS department, providing recreation and parks that were safe. As a resi dent and a father of two young children, safety is always on my mind. My wife and I try to provide them with a safe place to grow up, to go to school, to live and have fun, and hopefully graduate and be able to come back to this area or to st ay in this area and raise their children in a safe environment. The air has gotten a lot cleaner here since we moved back here about 10 years ago when the Coke plant was still in operation. What I would ask is for the EPA to push as hard as they can, the U.S. EPA, for the redesignation. I'd like for my kids to be able to have an opportunity to come back and work for a company like SunCoke or Sunoco, for a company that puts a lot of people in employment with good jobs, with safe jobs. And with this propo sed expansion of theirs, many more would have the opportunity to do so. It only makes sense that the same air that webasically breathe with our friends across the river in Greenup would have the same designation of attainment. And so I would ask for the Ohio EPA to do what they can to m ake sure that we become an attainment area so that a company like SunCoke, who has done a lot for the community, can do even more. And then for someone who could be l ooking at coming to Eastern Scioto County to employ many people will be able to do so, instead of going down the river to somewhere in Kentucky with the same air with an attainment designation (Bob Walton, Jr).

### 11 State Representative Johnson’s proxy Mr. Evans, the Hansell Company representative Mr. Hansell and the concerned Wheelersburg resident Mr. Walt on all appear to support an air quality attainment for Scioto County. Their support for this seems to be solely based on jobs and economic development at any lost. I believe there are economic opportunities available that shoul d not raise emissions or prevent those opportunities from manifesting themselves in the community. They need only besolicited. I further believe that standards which promote mediocrity then become the “acceptable” norm. I don’t believe I would want to accept or become accustomed to mediocrity (Robert Klouman). Response 14: Thank you for your comment and support on Ohio's PM 2.5 

### Redesignation Request for the Hunt ington-Ashland nonattainment area. Comment 15: The commentor pointed outin a note form one of her recent readings “let’s bad is not good”, all too often it seems, emissions of natural systems (including people) takes place as a direct result of greed. Much of this is made possible because of ineffective outdate d or unenforced regulation. The fact that people (cor porations) can and do commit wrongs indicates that regulati ons are needed. Not a single law or regulation was added after the nation’s latest oil spill one year ago today. If that is the example to use as a precedent, then by any means base all regulations on corporate needs instead of natures’ and citizens rights (Robert Klouman). Response 15: Thank you for your comment.

End of comments