APPENDIX A

Air Quality System (AQS) Data

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

DESIGN VALUE REPORT

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

Selection Criteria Page 1

User ID: GYE

State County Site Parameter POC City 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 2006
UNITED 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 4
UNITED 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 Y
UNITED 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

Y
UNITED 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 Y
Environmental

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 Sources .............................................................................................. 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 Burners 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 Factor 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 number of counties with air quality data showing nonattainment for the following PM2.5 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-attainment of the 1997 

Fine Particle (PM2.5) National Ambient Air Quality Standards (NAAQS). The Federal 

Register ( Vol. 72, No. 79/ Wednesday, April 25, 2007) provides the emissions inventory 

rules and regulations for the PM2.5 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 of non-attainment areas for PM2.5 standards, a new 

attainment demonstration SIP will be necessary. A key element in the overall SIP 

planning process is the need for an updated emissions inventory. This document 

presents the 2005 Base Year Particulate SIP Emissions Inventory for Ohio as required 

by the CAAA. It includes emissions for point, area, on-road mobile and non-road mobile 

for the State of Ohio. 

This technical report documents the procedures and the methodologies that were used 

in the development of daily emissions for all counties in Ohio. This report describes the 

following: 

1. Identification of stationary and mobile sources included in the 

inventory; 

2. Sources of data, and data collection methods used in the development 

of the inventory; 

3. Methods and procedures used to estimate emissions; and 

4. Assumptions considered in the development of the emissions 

inventories. 

The intent of this report is to describe 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 Emission Modeling System (EMS) to generate 

Summer Weekday emissions for VOC and NOx. 
4

SECTION 1

POINT SOURCES 

Emissions and source specific data for point sources are collected for the 2005 baseyear SIP inventory by the Ohio Environmental Protection Agency (Ohio EPA.) The 

primary source of data for point sources is facility reported STARShip files. STARShip 

is a software package developed by Ohio EPA, Division of Air Pollution Control (DAPC), 

to assist the regulated community in preparing 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 emissions fee/inventory process conducted by Ohio 

EPA and include emissions, process rates, operating schedules, emissions control data 

and other relevant information. 

The STARShip files are electronically transferred to the DAPC and stored into the 

Division’s Oracle database, STARS. The files 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 Emission Inventory (NEI) database format in version 3.0. 

The files are quality assured again using the United States Environmental Protection 

Agency’s (U.S.EPA) QA/QC software for format and content. The data is finally 

submitted to LADCO for emissions processing through the Emissions Modeling System. 

The State provided inventory for Electric Generating Units (EGU) is replaced with the 

Federal EGU inventory. The EGU inventory is compiled by U.S. EPA’s Acid Rain 

Program. It is based on facility reported emissions as measured 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 emissions inventories is that between point and 

area sources. In this inventory, 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, or other reliable data. A 

more detailed discussion of the area source inventory is provided in Section 2. The 

point source inventory described 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 Identification 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 facility-reported actual 2005 emissions. 

1.1.2 Non-reactive VOC Emissions Adjustments 

This section is primarily applicable for VOC pollutants. Sources are required to identify 

emissions of photochemically non-reactive Volatile Organic Compounds (VOC.) Based 

upon this information, those emissions have been specifically excluded from the 2005 

base line inventory in accordance with U.S. EPA’s “Recommended Policy on the 

Control of Volatile Organic Compounds.” A complete list of the 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 ((CF3)2CFCF2OCH3) 

• Heptafluoropropane ((CF3)CFCF2OC2H5) 

• Perchloroethylene 

• Cyclic, branched or linear completely methylated siloxanes 

• Methyl acetate 

• Volatile methyl siloxanes 

• Acetone 

1.1.3 Emissions Estimation Methodologies 

Since source reported actual annual emissions 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 spatial profiles to the annual 

emissions to calculate weekday emissions rates. The final point source inventory is 

split into two separate reports, the Electric Generating Units (EGU) which is the U.S. 

EPA inventory for electric generating units and 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 required 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 available for fugitive sources. However, since 

these emissions are now electronically reported in the State’s ORACLE database, 

STARS, these emissions can be classified as point sources. 

1.3 References 

Getting Started: Emissions Inventory Methods for PM2.5 U.S. Environmental Protection 

Agency, Research Triangle Park, NC, September, 1999. 

Emissions Inventory Guidance for Implementation of Ozone and Particulate Matter 

National Ambient Air Qaulity Standards (NAAQS) and Regional Haze Regulations, 

Office of Air Quality Planning & Standards Research, Triangle Park, NC. November 

2005. 

Compilation of Air Pollution Emission Factors, Fourth Edition and Supplements, AP-42. 

U.S. Environmental Protection 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 Electric Generating Unit National Emissions Inventory 

(NEI). Eastern research group, Inc., 1600 Perimeter 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, individual, numerous, and have not 

been inventoried as specific point, mobile, or biogenic sources. For inventory purposes, 

they are grouped with other like sources into categories that allow emissions to be 

calculated collectively using 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 largely based on Ohio’s data availability. 

Data which was not available on a county-level is estimated by assigning a percentage 

of the state’s total activity to each county based on the state’s population or employment 

information. If Ohio county specific activity data is available through Ohio EPA or other 

State Agencies, that data is used rather than allocating activity by percentage. Table 2-1 

lists the sources which emit PM2.5, NOx and SO2 along with the respective EFs used to 

calculate each pollutant. 

Table 2-1 Categories in the 2005 PM2.5 SIP Area Source inventory 

Area Source NOx PM2.5 SO2 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 sector energy consumption is obtained from the 

Energy Information Administration (EIA)’s State Energy Data System (SEDS), and 

apportioned per county based on population4

. Emissions factors are given in table 2-1. 

The area source emissions are calculated based 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 population4

. 

The area source NOX emissions are calculated and adjusted by subtracting the 

emissions due to point sources. 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 factors are given in table 2-1. 

SO2 emissions were calculated using EF 42.6 Lb/1000 Gal. PM10 and PM2.5 emissions

are calculated using 1Lb/1000 Gal and 0.25 Lb/1000 Gal respectively. All Factors are 

obtained from AP-4219 

Industrial Residual Oil Combustion (SCC 2102005000) 

Ohio’s fuel consumption is apportioned per county based on the county’s population4

. 

The area source NOX emissions are calculated and adjusted by subtracting the 

emissions due to point sources. 54,652 thousand gallons14 are consumed in 2005 and 

a heating value of 140 MMBTU/1000 Gal is used. The SO2 emissions are calculated 

using EF 157 Lb/1000 Gal. PM10 and PM2.5 emissions are calculated using 7.17 Lb/1000 

Gal and 4.67 Lb/1000 Gal respectively. All factors are obtained from AP-4219 

Industrial Natural Gas Combustion (SCC 2102006000) 

Ohio’s fuel consumption is apportioned per county based on the county’s population4

. 

The area source NOX emissions are calculated and adjusted by subtracting the 

emissions due to point sources. 293,857 MMCF14 are consumed in 2005. The SO2
10

emissions are calculated using EF 0.6 Lb/MMBTU. The PM10 and PM2.5 emissions are 

calculated using 7.6 Lb/MMBTU. All factors were obtained from AP-4219 

2.3 Residential Fuel Combustion 

Residential Coal Combustion (SCC 2104001000) 

Ohio’s household consumption of coal is apportioned per county based on county 

population4

. NOX emissions are calculated using EF of 9.1 of coal. The SO2 emissions 

are calculated using EF 31Lb/1000 Gal. The PM10 and PM2.5 emissions are calculated 

using 6.2Lb/Ton and 3.8 Lb/Ton respectively. All factors were obtained from AP-4219 

Residential Distillate Oil Combustion (SCC 2104004000) 

Ohio’s household consumption of distillate oil is apportioned per county based on 

county population4. NOX emissions are calculated using EF of 18 lb/1000 gallons 

distillate fuel respectively. A heating value of 140 MMBTU/1000 Gal is used. The SO2

emissions are calculated using EF 42.6 Lb/1000 Gal. The PM10 and PM2.5 emissions

are calculated using 1.08Lb/1000 Gal and 0.83 Lb/1000 Gal respectively. All factors are 

obtained from AP-4219 

Residential Liquid Petroleum Gas Combustion (LPG) 

(SCC 2104007000) 

Ohio’s household consumption of LPG is apportioned per county based on county 

population4. NOX emissions are calculated using EF of 13 lb/1000 gallons LPG. The 

SO2 emissions are calculated using EF 0.1 Lb/1000 Gal. The PM10 and PM2.5 emissions

are calculated using 0.17Lb/1000 Gal. All factors are obtained from AP-4219 

Residential Natural Gas Combustion (SCC 2104006010) 

Ohio’s household consumption of LPG is apportioned per county based on county 

population4

. NOX emissions are calculated using EF of 94 lb/MMSCF. MMSCF stands 

for Million Standard Cubic Feet. This source also emits SO2 emissions which are 

calculated using EF 0.6 Lb/MMBTU. The PM10 and PM2.5 emissions are calculated 

using 7.6Lb/MMBTU. All factors are obtained from AP-4219 

Residential Wood Combustion 

NOX emissions from this area source are calculated for seven types of residential 

heating units that utilize wood for fuel. They are 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 are adjusted for those that burn wood. The 

following assumptions are applied to those adjusted homes: 

92 percent of wood combusted 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 

population4

. 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 2104008003 2104008004 

SCC 2104008010 2104008050 2104008030 

SCC 2104008001 

RAPIDS Code Non-Certified Non-Catalytic Catalytic Units 

SO2 4.00E-01 4.00E-01 4.00E-01 Lb/ton 

NOX 2.80E+00 2.80E+00 2.00E+00 Lb/ton 

PM2.5 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 SO2 which is calculated using EF 0.4 Lb/Ton 

EF. The PM2.5 emissions are calculated using EF as shown in table 2-2. All factors are 

obtained from AP-4219 

2.4 Human Cremation (SCC 2810060200) 

 

Not all Ohio counties possess a crematory so only those counties with crematories are 

used to calculate the number of cremations and their resulting NOx emissions. The 

2005 cremation data is obtained from the Ohio Department of Health, Vital Statistics17. 

It is estimated that 3% of deaths occur outside 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 feels that it is a combustion source and NOx 

needs to be included in the inventory along with the other combustion sources. 

Through its Permits-to-Install for human cremation, Ohio has selected a NOx EF of 

10.13lb/ton cremated to calculate emissions from this area source. 
12

This source also emits PM, PM10, and PM2.5 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-4219

2.5 Structure Fires (SCC 2810030000) 

The Structure Fires category includes residential and commercial fires resulting from 

unintentional actions. Intentional fires, forest and wildfires, agricultural, and vehicle 

burning are not included in this area source. The State Fire Marshall Office, Fire 

Prevention Bureau15 provided data on the number of structure fires per county in 2005. 

This area source is considered a combustion source for NOX emissions which are 

calculated using EF 1.4 lb/ton burned. The residential and commercial structures fires 

for each county are tabulated and a fuel loading of 1.15 Ton/fire is applied. This source 

also emits PM, PM10, and PM2.5 emissions which are calculated using EF 10.8 Lb/Ton. 

This factor was obtained from AP-4219 

2.6 Outdoor Wood Boilers (SCC 2104008070) 

Outdoor Wood Boilers (OWB), are also known as outdoor water stoves and outdoor 

wood furnaces, are used as outdoor residential heaters. These boilers have wood 

burning fireboxes surrounded by a water reservoir vented by a chimney stack. The 

combustion of the wood in the 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 capacity ranges from 60 gallons to 764 gallons. The operational 

design creates long periods where the fire smolders and creosote is formed13. 

When the water circulating through the furnace 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 temperature 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 fine condensed organic material that does not burn under cool, 

oxygen starved conditions. In addition, many owners burn green wood full of moisture 

which also causes poor combustion12. The smoke created from these outdoor wood 

burning units can contain several 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 unit sales data available to calculate 

emissions on the county level. Therefore, several assumptions are made in agreement 

with the Great Lake States in order to formulate 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 per year (includes heating efficiency of 

30-40%) 

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

• PM2.5 emissions factor (g/kg wood) =13.82 (Average of indoor and outdoor) or 

27.64 lb/ton of wood 

The agreed upon methodology requires that total number of OWB 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 factors (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 Combustion category to allow for accurate 

emissions from the indoor wood burning units. 

 

2.7 References 

1. Documentation For the 2002 Non-Point Source National Emission Inventory For 

CAPS and HAPS. U.S. Environmental Protection Agency. Emissions Factor and 

inventory Group. E.H Pechan and Associates, Inc. January 2004. 

2. United States Census Bureau. Population Division.

http://eire.census.gov/popest/data/counties/tables/CO-EST2002/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-ALAPCO-EPA Emission 

Inventory Improvement Program (EIIP). Volume III - Area Sources Preferred and 

Alternative Methods. November 1996. 

7. Documentation for the Draft 1999 National Emissions Inventory (Version 3.0) for 

Criteria Air Pollutants and Ammonia. Area Sources. E. H. Pechan & Associates, Inc. 

March 3, 2003 
14

8. U.S. Environmental Protection Agency, STAPPA-ALAPCO-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 Asselmeier, Air Quality Planning 

Section, Inventory Group, Springfield, Illinois. 

10. Environmental Protection Agency (EPA). STAPPA-ALAPCO-EPA Emission 

Inventory Improvement Program (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/200602outdoorwoodfurnaces.ht

ml] 

12. (Washington State, Department of Ecology) viewed on Feb 8th, 2007 

[http://www.ecy.wa.gov/programs/air/AOP_Permits/Boiler/Outdoor_Boilers_home.html]

13. U.S. Environmental Protection Agency. 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 Energy Price and Expenditure Estimates, 1970-2001, Ohio. 

Energy Information Administration. U. S. Department of Energy. 

http://www.eia.doe.gov/emeu/states/sep_prices/ind/pr_ind_oh.html

http://www.eia.doe.gov/emeu/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 Inventory (Version 3.0) For 

Criteria Air Pollutants and Ammonia. Area Sources. E. H. Pechan & Associates, Inc. 

March 3, 2003 

17. Ohio Department of Health, Vital Statistics 

18. Environmental Protection Agency. STAPPA-ALAPCO-EPA Emission 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 generated regionally by running U.S. EPA’s National Mobile 

Inventory Model (NMIM) model. The Wisconsin Department of Natural 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 processed the NMIM files in 

their emissions model and generated daily emissions rates. Grant Heatherington from 

the Wisconsin Department of Natural Resources provided the following descriptions... 

The National Mobile Inventory Model (NMIM) developed by USEPA was used to 

estimate emissions for all other non-road mobile categories. NMIM consolidates nonroad mobile emissions and on-road emissions modeling into a single modeling system. 

Only the non-road emissions modeling portion of NMIM 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 populations, average load factors, available engine powers, 

activity hours and emission factors. Before NMIM was run, modifications and additions 

were made to the NMIM input data. 

a. Added emission factors for diesel tampers/rammers provided by E.H. 

Pechan & Associates, Inc. Diesel tampers/rammers are a type of 

construction equipment. 

b. Revised PM2.5 ratios in SCC table to correctly calculate PM2.5 diesel 

emissions. This error was introduced with NMIM2005 and didn’t exist in 

NMIM2004. 

c. Revised gasoline parameters using updates provided by the states and 

E.H. Pechan & Associates, Inc. Gasoline parameters include Reid Vapor 

Pressure (RVP), oxygenate content and sulfur content. 

The NMIM NEI NIF files are on the LADCO ftp site at: 

ftp://ftp.airtoxics.org/inv2005/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 Database Tables 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-propelled or portable emitter of air pollutants, 

and mobile source emissions are those generated by the engines or motors that power 

such sources. Most mobile sources, except jet or turboprop aircraft, are powered by 

internal combustion (IC) piston engines, and nearly all use liquid fuels. 

Gaseous fuels, such as compressed natural gas (CNG) or liquefied 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 purposes, mobile sources are divided into two major 

categories. 

1. On-highway mobile 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 passengers on roads and streets 

2. Off-highway (usually referred to as non-road) mobile sources including: 

• Modes of powered transportation that do not use roads, such as aircraft, 

trains, ships and boats, and motor vehicles used off-road. 

• Self-propelled or portable motorized machines or equipment not used for 

transportation, ranging from construction equipment and farm tractors to 

lawnmowers and hand-held power weed choppers. 

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

Non-road Mobile Sources: Some non-road mobile sources (e.g., farm tractors), are 

self-propelled, but many non-road sources are not. A gasoline-powered chain saw is a 

familiar example of a non-self-propelled non-road mobile source. 

Stationary Sources: Not all movable or portable emission 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 that move the plants do not supply power for 

them. 
18

NOTE: Not all Internal Combustion engines (IC) or turbine engines are mobile sources. 

Fixed IC engines, such as those that power pipeline compressors or standby generators 

in electricity plants and elsewhere, are also classified as stationary sources. 

4.1.1 Categories and Components of Mobile Source Emissions 

There are three categories of mobile 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 occur only when the engine 

is running. 

Evaporative emissions: Are Volatile Organic Compound (VOC) based only and are 

continuously emitted from an engine’s fuel system, 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 jet fuels are of very low volatility, so 

evaporative emissions from diesel and turbine engines are a much smaller part of their 

total VOC emissions. Evaporative emissions 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 emissions are entirely VOC. Although they result from the 

evaporation of fuel, they are distinct from, and not directly 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 storage 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), United States Environmental Protection Agency (USEPA), and 

the Ohio EPA (OEPA). Estimates of the amounts of NOx and VOC 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 estimates hydrocarbon (HC), carbon monoxide 

(CO), oxides of nitrogen (NOx), exhaust particulate matter (which consists of several 

components), tire wear particulate matter, brake wear particulate matter, sulfur dioxide 

(SO2), ammonia (NH3), six hazardous air pollutant (HAP), and carbon dioxide (CO2) 

emission factors for gasoline-fueled and diesel highway motor vehicles, and for certain 

specialized vehicles such as natural-gas-fueled 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 affecting vehicle emissions can be specified by the user. 

MOBILE6 will estimate emission factors for any calendar year between 1952 and 2050, 

inclusive. Vehicles from the 25 most recent 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 times of day, in which fleet or traffic 

conditions vary considerably. 

A list of MOBILE6 input parameters is provided below. Most of these inputs are optional 

because the model will supply default values unless alternate data are provided. 

4.2.3 MOBILE6 Input Parameters 

• Calendar year

• Month (January, July) 

• Hourly Temperature 

• Altitude (high, low) 

• Weekend/weekday 

• Fuel characteristics (Reid vapor 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 vehicle 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 specifications and selections

4.2.4 MOBILE6 References 

The following publications provide much of the guidance for 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 version is still the definitive document on 
21

inventories. If a previous edition is referred to, the fact will be noted 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 emission 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 published by Assessment & Modeling Division 

(AMD) of the National Vehicle & Fuels Emissions Laboratory (NVFEL) in Ann Arbor, 

Michigan. The NVFEL is part of USEPA Office of Transportation & Air Quality 

(OTAQ), formerly the Office of Mobile 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 primary 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”. This document 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 Margo Oge, Director of OTAQ, to Regional Air Division 

Directors. 

4.3 Ohio’s Alternate Data for MOBILE6 

Alternative data is state-specific data that is used in the Mobile6 runs. Using local data 

is preferred to using the default data in Mobile6. Efforts are made to collect as much 

local data as possible. 

4.3.1 Vehicle Registration Distribution by Age 

Overview: 

The vehicle age distribution determines the fraction of vehicles operating within each 

emissions control requirement standard 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 estimates of a distribution of registered vehicles by age 

and vehicle category for current and future years. 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 the July 1, 1996 registration profile into 

a general registration distribution by age and by vehicle category 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-duty 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 current 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 Directors Consortium (LADCO) to develop 

these inputs. LADCO then contracted with a subcontractor to breakout the age 

distribution data from the Vehicle Identification Numbers (VIN). 

Note: It was learned during the course of this inventory that there were some 

discrepancies in the age distribution data. But it was too large of a project to reevaluate 

the data prior to this inventory. This will be corrected in the next inventory (2008). 

Method Applicability: This approach is most applicable in areas where there are 

significant differences in the local vehicle fleet age distribution relative 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 state 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 the national default. 

• Requires minimal additional resources, particularly if data is readily available at 

the county or local level from the State department 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 Planning Organizations (MPOs), the Ohio 

Department of Transportation (ODOT) provided 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 the state and MPOs to forecast traffic for a 

variety of reasons, undergo rigorous calibration and validation checks, and are sensitive 

to roadway capacity/travel time improvements, 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 counties where it is not used directly it is used for 

making rough emissions estimates where models do not exist or where time prohibits 

the use of TDMs. DVMT is a simple mechanism to measure how much traffic is flowing 

along a roadway during an average 24 hour period. 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 using the State of Ohio, Department of 

Transportation’s Roadway Information Files 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 provides a very accurate estimate of 

statewide total DVMT for The State Highway System (Interstate, US and State Routes). 

County total DVMT are consistent and considered a good source of county level DVMT 

for countywide emissions estimates. For roadways that are not part of the State 

Highway System, various representative counts 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 Functional 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, derived 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-sampled, 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 segments from one functional class to another. 

The Ohio Department of Transportation therefore does not warrant 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 performed by the Ohio Metropolitan Planning 

Organizations (MPOs) and ODOT for a multitude of purposes including the preparation 

of regional emissions estimates. The ODOT Office of Technical Services’ Modeling & 

Forecasting Section recommends that Ohio’s TDMs and ODOT’s conformity analysis 

methods be used to establish the roadway mobile 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 LADCO. 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 networks. Additional post processing data was 

provided including but not limited to metadata describing the loaded networks, Hourly 

distribution by functional class, speed profiles, day of week / weekend / monthly car and 

truck traffic profiles, 2009 & 2018 VMT RPO data sets, statewide VMT growth rates for 

local traffic, and a 2005 VMT summary comparison spreadsheet. It should be noted 

that among other things, the loaded TDM Networks contain distance and daily volumes 

from which VMT is computed. 

Network volumes are post processed to estimate VMT by hour of day. The hourly 

volumes and capacity, posted speed limit, and type of roadway for each roadway 

segment are then used to estimate average hourly speeds needed for MOBILE6 based 

emissions estimates. Modeling 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 relative emissions affect of improvements to 

individual roadways as well as packages of improvements and the entire set of planned 

roadway improvement projects air quality impacts of construction programs. 
26

4.3.4 Speed Distribution Profiles 

Overview: 

ODOT provided speed distribution profiles to LADCO. 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 conducted 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 speeds for use with MOBILE6 

for development of CERR, ODOT provided a set of speeds based on that statewide 

travel time study. Those speeds are documented in a technical memorandum titled 

“Estimation of Average Speed by Functional Class for MOBILE6 Runs” dated 

5/27/2004. Readers should refer to those documents 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 Use with County Level DVMT, HPMS: 

The memo states that the speeds which the Ohio Department of Transportation (ODOT) 

had been using prior to that date, 2004, for air quality analysis estimates based on 

County DVMT summaries, were developed by a former ODOT employee for addressing 

the one (1) hour standards conformity rules 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 estimated. In addition, EPA has requirements 

for using latest planning assumptions for air quality conformity analyses. Therefore, 

ODOT believed that it was in the state’s best interest to use the most recent available 

data to provide a new set of estimated average 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 data obtained from traffic count equipment, 

automatic traffic recorders (ATRs) which collect data continuously throughout the year. 

It also contains comparisons of the new speeds 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

FC06

FC08

FC11

FC14

FC17

Functional Class

Speed

Average Speed

1990 Analysis

Speeds

2001 Speed Study

Speeds Comparison

0

20

40

60

80

100

FC01FC06FC08

FC11

FC14FC17

RAMPS

Functional Class

Speed

Average Speed

Min. Avg Speed

Max. Avg. Speed

Gebhardt's Speeds

Spd Study Est

Speeds

Spd Study Greg Est

The following caution statement 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 between 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 expected that these average statewide speeds are 

higher than the average speeds in the non-attainment areas because the non-
28

attainment counties tend to be more populated and more congested. The document 

“Highway Vehicle Speed Estimation Procedures For Use in Emission Inventories”, 

September 1991 by Earl Ruiter of Cambridge Systematics Inc. is referenced by EPA’s 

documented procedures for emission inventory preparation. This document suggests 

post processing travel demand model traffic assignment results to estimate average 

speeds. 

Final space mean speeds that ODOT provided 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 space mean speed based average speed estimates 

were reproducible and defensible since they are well documented and should therefore 

be the speeds used with HPMS** VMT if any year 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 analysis 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 budgets. Therefore, ODOT provided 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 Codes & 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 curve parameters for the equation 

T = T0 {1 + a * (V/C)^b] 
30

More complete details about emissions modeling process employed by ODOT may be 

found in ODOT documentations. The document titled “Congestion Management & Air 

Quality Analysis (CMAQ) Program Documentation” 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 supplied 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.state.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 developing the Ohio 2007 8-Hour Ozone SIP Attainment 

Demonstrations. See meeting agenda below. OEPA is working toward a June 15, 2006 schedule for 

submitting the 2002 inventories to US EPA. 

A key component of the meeting will be to review and confirm the MOBILE6.2 input parameters, by Ohio 

a/q area, for use in developing the 2002 mobile inventories. See draft template below. The Ohio MPO 

travel demand models will be used to generate the 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 current 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 Regulations 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 Regulations 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 Regulations 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 it as 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 necessary technical support for new State 

Implementation Plans (SIPs) for regional haze, fine particles, and ozone. Emissions for 

on-road motor vehicles are estimated using vehicle miles traveled, trip starts and ends, 

speed, and other activity data developed by State Agencies and Metropolitan Planning 

Organizations (MPOs) using transportation demand models (TDMs), and emission 

factors from EPA's MOBILE6 model. To support 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 networks using a variety of models, applies 

appropriate data transformations, and outputs link- and county-level activity data in a 

uniform format for input to the CONCEPT emissions processing model (a new 

emissions processing model also developed with funding from LADCO). In a parallel 

effort, analyses of extensive automatic traffic recorder (ATR) data collected by State 

DOTs were conducted to develop temporal profiles (hour of day, day of week, and 

month of year) of vehicle counts and vehicle mix by roadway type for developing the 

detailed on-road emission inventories. 

T3 provides a conduit from the projections of traffic demand modelers regarding vehicle 

types, road networks, and vehicle activity to the activity data required by emissions 

modelers. The primary goals of T3 are to provide an easy mechanism for incorporating 

TDM model outputs in as "raw" a format as possible, while simultaneously providing a 

great degree of flexibility in representing the TDM projections in terms acceptable to 

most air quality models. These goals have been achieved through the use of a 

dimensional transformation approach, where 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, Suite 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 Community Emissions Processing Tool an OpenSource Tool for the Emissions Modeling Community: 

The new CONCEPT (CONsolidated Community 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 systems into an open source model highlighting 

the following features: 

• Open Source. Written primarily in PostgreSQL, the software required for running 
39

CONCEPT is in the public domain. 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 structure of the model makes the system easy to 

understand, and the modeling codes themselves are extremely well documented to 

encourage user participation in the customizing the system for specific modeling 

requirements. 

• Quality Control. The CONCEPT model structure and 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 calculation procedures and assumptions for any emissions value. 

The CONCEPT model includes modules for the major emissions source 

categories: area source, point source, on-road motor vehicles, non-road motor vehicles 

and biogenic emissions, as well as a number of supporting modules, including spatial 

allocation factor development, speciation profile development, growth and control for 

point and area sources, and CEM point source emissions handling. The emissions 

modeling community has already begun development of additional CONCEPT support 

modules including CEM preprocessing software, graphical QA tools, and an interface to 

the traffic demand models for on-road motor 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 Avenue # 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/emis/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 

Totals 

(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 COLUMBUS 1 1 1 1 1 1 1 1 1

OH SPRING

FLD

SPRING

FLD OH OH SPRINGFLD 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 YNGSTOWN 1 1 1 1 1 1 1 1 1

OH STATEW

D

STATEW

D OH OH STATEWD 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 Table 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 sources which are significant enough 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 Environ1

 under contract with LADCO and the 

aircraft inventory is generated by Ohio EPA. 

5.1 Marine Vessel Sources 

The approach to commercial marine emission estimates needed to be flexible because 

the activity data was available in many formats. Emission estimates were determined 

either by multiplying engine power, load factor, hours per year of operation, or on the 

basis of the number of gallons 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 methodologies employed, inventory tables for the ten 

subcategories are detailed in the complete inventory prepared and published by 

ENVIRON International Corporation: LADCO 2005 COMMERCIAL MARINE 

EMISSIONS, by Christian E. Lindhjem, 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 emissions is gallons of fuel consumed. 

Emission rates were derived from EPA documents 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 largest 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, Office of Mobile Sources, April. And EPA 1997, Emission Factors for 

Locomotives," Environmental Protection 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 factor. 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 then compiled as tons per year per pollutant 

by county. The following describes the components, methodology, 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 164 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 derived 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-Warren 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 the larger airports) is obtained from “Table 

7” provided by the United States Department 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 of aircraft models for 

the Akron/Canton area. “All Service” departures were used as the number of LTOs per 

year for that model. Listed in the original table are aircraft 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 air quality at civilian airports and military 

air bases. The model was developed by the Federal Aviation Administration (FAA) in 

cooperation with the United States Air Force (USAF). The model is used to produce an 

inventory of emissions generated by sources 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 0.0 

BEECH 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 0.4 

CANADAIR 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 emission factors were taken from “Documentation for Aircraft, 

Commercial Marine Vessel, ,Locomotive, and Other Non-road Components of the 

National Emissions Inventory. 2005, see Appendix A, Aircraft Emission Estimation 

Methodology.” Specific model LTOs were subtracted from county LTO totals to 

eliminate double counting those LTOs. 

Table 5-3 Fleet Emission Factor Categories 

Fleet emission factors were broken down into three categories. Itinerant General, Local 

General, and Military. 

Table 5-3a Fleet 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 Factors 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 aircraft air carrier activity and 

commercial air freight activity by aircraft model types, 

2. General aviation and air taxi annual local and itinerant operations for year 2005, 

3. Military annual local and itinerant operations for year 2005. 

Due to the need to have aircraft operations information expressed as landing/take off 

(LTO) cycles, the following assumptions were made: 

1. For commercial aircraft and commercial air freight activity, the number of annual 

aircraft annual LTO cycles was assumed 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 itinerant airport operations, each respective 

operations total was divided by 2 to obtain the corresponding year local and 

itinerant LTO cycles. The expected daily local and itinerant LTO cycles then 

were obtained by dividing these annual totals by 365. 

3. For military annual local and itinerant operations, each respective operations total 

was divided by 2 to obtain the corresponding year local and itinerant LTO cycles. 

The expected military daily local and itinerant LTO cycles then were obtained by 

dividing these annual totals by 365. 

Airport LTO cycles were further categorized 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 Aviation Administration EDMS 

Emissions and Dispersion Modeling System. Commercial and air freight aircraft 

emission factors per LTO cycle were determined using EDMS for each commercial 

aircraft type models where possible were used at each towered airport. Default 

commercial aircraft engine type, and Environmental 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 alternative 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 from the Ohio Department of 

Transportation. These were classed by airport, county, aircraft flight classification, and 

the total number of operations per year. 

2. The number of operations (a landing or a 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 that the following Ohio flight groups of aircraft 

be combined to match the three categories used by the USEPA in calculating 

emissions. 
54

Itinerant (General, air carrier, commuter, air taxi, general aviation itinerant) 

Local (General aviation local) 

Military (Military) 

4. LTOs for specific models of aircraft per airport were taken from the FAA Table 7. 

See Table 2 above. These were then combined to give the number of LTOs per aircraft 

model per county. Specific model LTOs were subtracted from county totals to avoid 

double counting those LTOs. 

5. Emission factors were determined from the FAA’s EDMS program 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 flown in Ohio. . 

Where specific aircraft model data was not available USEPA average fleet emissions 

were used. 

6. Emission factors times LTOs by county yielded tons per year 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 pollutants 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 submitted to LADCO in April, 2007 contained an 

error. The inventory submitted in May, 2007 has 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 inventory exactly twice as large as what it really was. 

ACCESS CALCULATOR 

Introduction: 

Our database programmer set up Access application 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 future data scenarios. Output to Excel also 

allows for additional data manipulation and importation. 
56

Interface: 

Through this interface the following sets of data can be edited/updated: Airport activity, 

emission factors, specific airport emissions, state/county FIPS, detailed aircraft 

information, airport information, and aircraft SCCs. Once the final emissions have been 

calculated and summed, then the data can be export via the export function on the Main 

Menu. 
APPENDIX C

Mobile Source Emission Inventory (MOVES)
Mobile Source Emissions Inventory

for Huntington-Ironton-Ashland PM2.5

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 PM2.5 Nonattainment Area

Mobile Source Emissions Inventory for the HuntingtonIronton-Ashland PM2.5 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 PM2.5 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 PM2.5, PM2.5 tirewear, PM2.5 brakewear, NOx and SO2.

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 1c show 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 PM2.5 Nonattainment 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 PM2.5 - Brakewear Particulate

Primary PM2.5 - Tirewear Particulate

Primary Exhaust PM2.5 - Total

Oxides of Nitrogen (NOx)

Sulfur Dioxide (SO2)

Primary PM2.5 - Brakewear Particulate

Primary PM2.5 - Tirewear Particulate

Primary Exhaust PM2.5 - Total

Primary Exhaust PM2.5 - Total

Oxides of Nitrogen (NOx)

Sulfur Dioxide (SO2)

Primary PM2.5 - Brakewear Particulate

Primary PM2.5 - Tirewear Particulate

Oxides of Nitrogen (NOx)

Sulfur Dioxide (SO2)

Primary PM2.5 - Brakewear Particulate

Primary PM2.5 - Tirewear Particulate

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

Oxides of Nitrogen (NOx)

Sulfur Dioxide (SO2)

Primary Exhaust PM2.5 - Total
Mobile Source Emissions Inventory for the Page 3

Huntington-Ironton-Ashland PM2.5 Nonattainment Area

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

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

Primary PM2.5 - Tirewear Particulate 0.0105 3.61

Primary PM2.5 - Brakewear Particulate

Sulfur Dioxide (SO2)

Primary Exhaust PM2.5 - Total

Primary PM2.5 - Tirewear Particulate

Oxides of Nitrogen (NOx)

Primary PM2.5 - Brakewear Particulate

Sulfur Dioxide (SO2)

Primary Exhaust PM2.5 - Total

Primary PM2.5 - Tirewear Particulate

Oxides of Nitrogen (NOx)

Primary PM2.5 - Brakewear Particulate

Sulfur Dioxide (SO2)

Primary Exhaust PM2.5 - Total

Primary PM2.5 - Tirewear Particulate

Oxides of Nitrogen (NOx)

Primary PM2.5 - Brakewear Particulate

Sulfur Dioxide (SO2)

Primary Exhaust PM2.5 - Total

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

Oxides of Nitrogen (NOx)
Mobile Source Emissions Inventory for the Page 4

Huntington-Ironton-Ashland PM2.5 Nonattainment Area

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

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

Primary PM2.5 - Tirewear Particulate 0.0053 1.80

Primary PM2.5 - Brakewear Particulate

Sulfur Dioxide (SO2)

Primary Exhaust PM2.5 - Total

Primary PM2.5 - Tirewear Particulate

Oxides of Nitrogen (NOx)

Primary PM2.5 - Brakewear Particulate

Sulfur Dioxide (SO2)

Primary Exhaust PM2.5 - Total

Primary PM2.5 - Tirewear Particulate

Oxides of Nitrogen (NOx)

Primary PM2.5 - Brakewear Particulate

Sulfur Dioxide (SO2)

Primary Exhaust PM2.5 - Total

Primary PM2.5 - Tirewear Particulate

Oxides of Nitrogen (NOx)

Primary PM2.5 - Brakewear Particulate

Annual Emissions (tons)

Oxides of Nitrogen (NOx)

Sulfur Dioxide (SO2)

Primary Exhaust PM2.5 - Total

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

Huntington-Ironton-Ashland PM2.5 Nonattainment Area

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

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 PM2.5 - Brakewear Particulate

Primary PM2.5 - Tirewear Particulate

Primary Exhaust PM2.5 - Total

Oxides of Nitrogen (NOx)

Sulfur Dioxide (SO2)

Primary PM2.5 - Brakewear Particulate

Primary PM2.5 - Tirewear Particulate

Primary Exhaust PM2.5 - Total

Oxides of Nitrogen (NOx)

Sulfur Dioxide (SO2)

Primary PM2.5 - Brakewear Particulate

Primary PM2.5 - Tirewear Particulate

Primary Exhaust PM2.5 - Total

Oxides of Nitrogen (NOx)

Sulfur Dioxide (SO2)

Primary PM2.5 - Brakewear Particulate

Primary PM2.5 - Tirewear Particulate

Primary Exhaust PM2.5 - Total

Oxides of Nitrogen (NOx)

Sulfur Dioxide (SO2)

Pollutant Name Daily Emissions (tons) Annual Emissions (tons)
Mobile Source Emissions Inventory for the Page 6

Huntington-Ironton-Ashland PM2.5 Nonattainment 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

Primary PM2.5 - Tirewear Particulate 0.0044 1.51

Primary PM2.5 - Brakewear Particulate

Sulfur Dioxide (SO2)

Primary Exhaust PM2.5 - Total

Primary PM2.5 - Tirewear Particulate

Oxides of Nitrogen (NOx)

Primary PM2.5 - Brakewear Particulate

Sulfur Dioxide (SO2)

Primary Exhaust PM2.5 - Total

Primary PM2.5 - Tirewear Particulate

Oxides of Nitrogen (NOx)

Primary PM2.5 - Brakewear Particulate

Sulfur Dioxide (SO2)

Primary Exhaust PM2.5 - Total

Primary PM2.5 - Tirewear Particulate

Oxides of Nitrogen (NOx)

Primary PM2.5 - Brakewear Particulate

Sulfur Dioxide (SO2)

Primary Exhaust PM2.5 - Total

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

Oxides of Nitrogen (NOx)
Mobile Source Emissions Inventory for the Page 7

Huntington-Ironton-Ashland PM2.5 Nonattainment Area

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

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 PM2.5 - Brakewear Particulate

Primary PM2.5 - Tirewear Particulate

Primary Exhaust PM2.5 - Total

Oxides of Nitrogen (NOx)

Sulfur Dioxide (SO2)

Primary PM2.5 - Brakewear Particulate

Primary PM2.5 - Tirewear Particulate

Primary Exhaust PM2.5 - Total

Oxides of Nitrogen (NOx)

Sulfur Dioxide (SO2)

Primary PM2.5 - Brakewear Particulate

Primary PM2.5 - Tirewear Particulate

Primary Exhaust PM2.5 - Total

Oxides of Nitrogen (NOx)

Sulfur Dioxide (SO2)

Primary PM2.5 - Brakewear Particulate

Primary PM2.5 - Tirewear Particulate

Primary Exhaust PM2.5 - Total

Oxides of Nitrogen (NOx)

Sulfur Dioxide (SO2)

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

Huntington-Ironton-Ashland PM2.5 Nonattainment 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 PM2.5 - Brakewear Particulate

Primary PM2.5 - Tirewear Particulate

Primary Exhaust PM2.5 - Total

Oxides of Nitrogen (NOx)

Sulfur Dioxide (SO2)

Primary PM2.5 - Brakewear Particulate

Primary PM2.5 - Tirewear Particulate

Primary Exhaust PM2.5 - Total

Oxides of Nitrogen (NOx)

Sulfur Dioxide (SO2)

Primary PM2.5 - Brakewear Particulate

Primary PM2.5 - Tirewear Particulate

Primary Exhaust PM2.5 - Total

Oxides of Nitrogen (NOx)

Sulfur Dioxide (SO2)

Primary PM2.5 - Brakewear Particulate

Primary PM2.5 - Tirewear Particulate

Primary Exhaust PM2.5 - Total

Oxides of Nitrogen (NOx)

Sulfur Dioxide (SO2)

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

Huntington-Ironton-Ashland PM2.5 Nonattainment Area

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

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

Primary PM2.5 - Tirewear Particulate 0.0055 1.89

Primary PM2.5 - Brakewear Particulate

Sulfur Dioxide (SO2)

Primary Exhaust PM2.5 - Total

Primary PM2.5 - Tirewear Particulate

Oxides of Nitrogen (NOx)

Primary PM2.5 - Brakewear Particulate

Sulfur Dioxide (SO2)

Primary Exhaust PM2.5 - Total

Primary PM2.5 - Tirewear Particulate

Oxides of Nitrogen (NOx)

Primary PM2.5 - Brakewear Particulate

Sulfur Dioxide (SO2)

Primary Exhaust PM2.5 - Total

Primary PM2.5 - Tirewear Particulate

Oxides of Nitrogen (NOx)

Primary PM2.5 - Brakewear Particulate

Sulfur Dioxide (SO2)

Primary Exhaust PM2.5 - Total

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

Oxides of Nitrogen (NOx)
Mobile Source Emissions Inventory for the Page 10

Huntington-Ironton-Ashland PM2.5 Nonattainment Area

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

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 PM2.5 - Brakewear Particulate

Primary PM2.5 - Tirewear Particulate

Primary Exhaust PM2.5 - Total

Oxides of Nitrogen (NOx)

Sulfur Dioxide (SO2)

Primary PM2.5 - Brakewear Particulate

Primary PM2.5 - Tirewear Particulate

Primary Exhaust PM2.5 - Total

Oxides of Nitrogen (NOx)

Sulfur Dioxide (SO2)

Primary PM2.5 - Brakewear Particulate

Primary PM2.5 - Tirewear Particulate

Primary Exhaust PM2.5 - Total

Oxides of Nitrogen (NOx)

Sulfur Dioxide (SO2)

Primary PM2.5 - Brakewear Particulate

Primary PM2.5 - Tirewear Particulate

Primary Exhaust PM2.5 - Total

Oxides of Nitrogen (NOx)

Sulfur Dioxide (SO2)

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

Huntington-Ironton-Ashland PM2.5 Nonattainment 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

Primary PM2.5 - Tirewear Particulate 0.0002 0.05

Primary PM2.5 - Brakewear Particulate

Sulfur Dioxide (SO2)

Primary Exhaust PM2.5 - Total

Primary PM2.5 - Tirewear Particulate

Oxides of Nitrogen (NOx)

Primary PM2.5 - Brakewear Particulate

Sulfur Dioxide (SO2)

Primary Exhaust PM2.5 - Total

Primary PM2.5 - Tirewear Particulate

Oxides of Nitrogen (NOx)

Primary PM2.5 - Brakewear Particulate

Sulfur Dioxide (SO2)

Primary Exhaust PM2.5 - Total

Primary PM2.5 - Tirewear Particulate

Oxides of Nitrogen (NOx)

Primary PM2.5 - Brakewear Particulate

Sulfur Dioxide (SO2)

Primary Exhaust PM2.5 - Total

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

Oxides of Nitrogen (NOx)
Mobile Source Emissions Inventory for the Page 12

Huntington-Ironton-Ashland PM2.5 Nonattainment 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 PM2.5 - Brakewear Particulate

Primary PM2.5 - Tirewear Particulate

Primary Exhaust PM2.5 - Total

Oxides of Nitrogen (NOx)

Sulfur Dioxide (SO2)

Primary PM2.5 - Brakewear Particulate

Primary PM2.5 - Tirewear Particulate

Primary Exhaust PM2.5 - Total

Oxides of Nitrogen (NOx)

Sulfur Dioxide (SO2)

Primary PM2.5 - Brakewear Particulate

Primary PM2.5 - Tirewear Particulate

Primary Exhaust PM2.5 - Total

Oxides of Nitrogen (NOx)

Sulfur Dioxide (SO2)

Primary PM2.5 - Brakewear Particulate

Primary PM2.5 - Tirewear Particulate

Primary Exhaust PM2.5 - Total

Oxides of Nitrogen (NOx)

Sulfur Dioxide (SO2)

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

Huntington-Ironton-Ashland PM2.5 Nonattainment 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 PM2.5 - Brakewear Particulate

Primary PM2.5 - Tirewear Particulate

Primary Exhaust PM2.5 - Total

Oxides of Nitrogen (NOx)

Sulfur Dioxide (SO2)

Primary PM2.5 - Brakewear Particulate

Primary PM2.5 - Tirewear Particulate

Primary Exhaust PM2.5 - Total

Oxides of Nitrogen (NOx)

Sulfur Dioxide (SO2)

Primary PM2.5 - Brakewear Particulate

Primary PM2.5 - Tirewear Particulate

Primary Exhaust PM2.5 - Total

Oxides of Nitrogen (NOx)

Sulfur Dioxide (SO2)

Primary PM2.5 - Brakewear Particulate

Primary PM2.5 - Tirewear Particulate

Primary Exhaust PM2.5 - Total

Oxides of Nitrogen (NOx)

Sulfur Dioxide (SO2)

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

Huntington-Ironton-Ashland PM2.5 Nonattainment Area

Background

US EPA published a Federal Register notice1 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, NOx, CO, PM10 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=0900006480ab1f98
Mobile Source Emissions Inventory for the Page 15

Huntington-Ironton-Ashland PM2.5 Nonattainment 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 Appendix of 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 4 lists 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 domains – 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 NOx, all PM2.5 categories, SO2, total energy consumption

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 Performance None
Mobile Source Emissions Inventory for the Page 16

Huntington-Ironton-Ashland PM2.5 Nonattainment 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 data. 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 offnetwork, 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. Socioeconomic
Mobile Source Emissions Inventory for the Page 17

Huntington-Ironton-Ashland PM2.5 Nonattainment 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 Plan was 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 PM2.5 Nonattainment Area

APPENDIX

Technical Documentation for Using

MOVES2010a to Develop Mobile Source

Emissions for the Huntington-IrontonAshland PM2.5 Nonattainment Area

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

Source Emissions for the Huntington-Ironton-Ashland PM2.5 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.
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Source Emissions for the Huntington-Ironton-Ashland PM2.5 Nonattainment Area

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, NOx, and SO2.

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.
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Source Emissions for the Huntington-Ironton-Ashland PM2.5 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 1
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Source Emissions for the Huntington-Ironton-Ashland PM2.5 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 1
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Source Emissions for the Huntington-Ironton-Ashland PM2.5 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.
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Source Emissions for the Huntington-Ironton-Ashland PM2.5 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 at
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Source Emissions for the Huntington-Ironton-Ashland PM2.5 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 4 shows 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 6 shows 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 62 732
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Source Emissions for the Huntington-Ironton-Ashland PM2.5 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 PM2.5 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 8 shows 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 9 shows the age distributions used for the Kentucky area (shown for the year

2008).

Table 7. West Virginia Non-Attainment Area Age Distributions
APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-11

Source Emissions for the Huntington-Ironton-Ashland PM2.5 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 0.0294
APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-12

Source Emissions for the Huntington-Ironton-Ashland PM2.5 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 0.0302
APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-13

Source Emissions for the Huntington-Ironton-Ashland PM2.5 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 0.0449
APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-14

Source Emissions for the Huntington-Ironton-Ashland PM2.5 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 0.0121
APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-15

Source Emissions for the Huntington-Ironton-Ashland PM2.5 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 Distributions
APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-16

Source Emissions for the Huntington-Ironton-Ashland PM2.5 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 0.0000
APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-17

Source Emissions for the Huntington-Ironton-Ashland PM2.5 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 0.0055
APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-18

Source Emissions for the Huntington-Ironton-Ashland PM2.5 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 0.0356
APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-19

Source Emissions for the Huntington-Ironton-Ashland PM2.5 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 0.0121
APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-20

Source Emissions for the Huntington-Ironton-Ashland PM2.5 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 Distributions
APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-21

Source Emissions for the Huntington-Ironton-Ashland PM2.5 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 0.0000
APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-22

Source Emissions for the Huntington-Ironton-Ashland PM2.5 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 0.0318
APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-23

Source Emissions for the Huntington-Ironton-Ashland PM2.5 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 0.0216
APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-24

Source Emissions for the Huntington-Ironton-Ashland PM2.5 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 0.0278
APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-25

Source Emissions for the Huntington-Ironton-Ashland PM2.5 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 PM2.5 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 0
APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-27

Source Emissions for the Huntington-Ironton-Ashland PM2.5 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 0
APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-28

Source Emissions for the Huntington-Ironton-Ashland PM2.5 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 0.762365
APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-29

Source Emissions for the Huntington-Ironton-Ashland PM2.5 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 unit

short-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 14 shows 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 PM2.5 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 PM2.5 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 Data
APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-32

Source Emissions for the Huntington-Ironton-Ashland PM2.5 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 18 shows the

ramp fractions for Kentucky.

Table 16. West Virginia Ramp Fractions Table 17. Ohio Ramp Fractions

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

Source Emissions for the Huntington-Ironton-Ashland PM2.5 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 PM2.5 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 22-24 show 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 1
APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-35

Source Emissions for the Huntington-Ironton-Ashland PM2.5 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 and
APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-36

Source Emissions for the Huntington-Ironton-Ashland PM2.5 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 26 shows 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 PM2.5 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 3,505
APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-38

Source Emissions for the Huntington-Ironton-Ashland PM2.5 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

2005
APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-39

Source Emissions for the Huntington-Ironton-Ashland PM2.5 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

2008
APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-40

Source Emissions for the Huntington-Ironton-Ashland PM2.5 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

2015
APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-41

Source Emissions for the Huntington-Ironton-Ashland PM2.5 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

2022
APPENDIX – Technical Documentation for Using MOVES2010a to Develop Mobile Page A-42

Source Emissions for the Huntington-Ironton-Ashland PM2.5 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 0.01325
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Source Emissions for the Huntington-Ironton-Ashland PM2.5 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 Fractions
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Source Emissions for the Huntington-Ironton-Ashland PM2.5 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 Fractions
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Source Emissions for the Huntington-Ironton-Ashland PM2.5 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 1 below. 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",
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"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]",
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Source Emissions for the Huntington-Ironton-Ashland PM2.5 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,}
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Source Emissions for the Huntington-Ironton-Ashland PM2.5 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)
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 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 values
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Source Emissions for the Huntington-Ironton-Ashland PM2.5 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,)
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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",)
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 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 PM2.5 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 PM2.5 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, PM2.5 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, PM2.5 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:IIwww.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 PM2.5 Attainment Demonstration SIP1

, Ohio found that the 

regional highway emissions of PM2.5, NOx, and SO2 were insignificant contributors to the 

nonattainment problems and, therefore, none of the three pollutants necessitated 

emissions inventory analysis or required the establishment of mobile emission budgets. 

As documented in Ohio EPA’s attainment demonstration SIP, Ohio EPA in consultation 

with U.S. EPA determined that the 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 EPA is again making a finding that the 

regional highway emissions of PM2.5, NOx, and SO2 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 PM2.5 precursor emissions (primary particles (organic carbon, crustal matter, and 

elemental carbon), SO2 and NOx

2

) representative of the year when the area achieves 

attainment of the annual PM2.5 air quality standard. Ohio also must demonstrate that 

the improvement in air quality between the year that violations occurred and the year 

that attainment was achieved is based on permanent and enforceable 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 of emissions is sufficient to maintain the annual PM2.5 standard; 

and a commitment to provide future updates of the inventory to enable tracking of 

emission levels during the 10-year maintenance period. 

The emissions inventory development process addresses emissions from several types 

of sources or sectors: point (EGU or non-EGU); 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 submittal are developed by the Lake Michigan Area 

Directors Consortium (LADCO) as discussed in greater detail elsewhere in the 

documents associated with this submittal.. All LADCO’s emission inventories utilized in 

the redesignation and maintenance plan for the Huntington-Ashland annual PM2.5

nonattainment area were prepared for county level emission. 

Mobile emissions inventories and projections for all counties were prepared by KimleyHorn and Associates Inc., with data provided by the Kentucky-Ohio-West Virginia 

Interstate Planning Commission (KYOVA), Ohio Department of Transportation (ODOT), 

Ohio EPA, West Virginia Department of Transportation (WVDOT), West Virginia 

Department of Environmental Protection (WVDEP), Kentucky Transportation Cabinet 

(KYTC), and Kentucky Division of Air Quality (KDAQ). The mobile emission inventories 

 

1 http://www.epa.ohio.gov/portals/27/SIP/Attain/PM2_5/PM25Doc.pdf 

2 VOC and NH3 are not addressed. 
2 

are only generated for the annual PM2.5 nonattainment areas, meaning that if an area 

was designated partial nonattainment, that was the only area that was modeled for 

inventory development (as opposed to the entire county that the partial nonattainment 

area is included within). 

Since the mobile emissions inventories only address nonattainment areas (county level 

or only partial areas determined as nonattainment) and the remainder of the source 

sector inventories (non-electric generating unit (EGU), EGU, area, non-road, and MAR) 

address complete counties (which are not necessarily entirely classified as 

nonattainment), Ohio EPA and U.S. EPA agreed that an apportioning analysis approach 

would most accurately provide for a determination of mobile emissions insignificance. 

The analysis incorporates apportioning non-road, MAR, and area emission sources 

from the entire county level inventory to the partial nonattainment portion of the county 

based on the percentages of population in the county versus the partial area (based on 

the 2000 Census. This type of apportioning may not be as appropriate for the EGU and 

non-EGU sectors. However, for all partial nonattainment counties within this 

nonattainment area all EGU emissions within the county level inventory 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 challenging. Because of these challenges and also 

due to time/recourse constraints, Ohio EPA has elected to remove non-EGUs from this 

insignificance analysis ONLY in the partial nonattainment counties. This is justified as 

omitting non-EGUs will provide for more conservative results (i.e., the percentage of 

mobile emissions will be larger). Therefore, if the insignificance analysis with the 

omission of non-EGUs determines mobile emissions are insignificant, performing the 

analysis with non-EGU’s apportioned will show even greater insignificance. 

Table 1 shows the total population in each county that contains one or more partial 

nonattainment areas, the total population in each partial nonattainment area, and the 

population percentage in each partial nonattainment 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, Partial Nonattainment Area Population, and 

Percentage of County Population within 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 nonattainment 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 nonattainment area. Hence, all county level EGU 

emission sources are apportioned to the partial area since these emissions are only 

present in the partial area. 

Non-EGU and EGU sources include those sources that are identified by point locations, 

typically because they are regulated and their locations are available in regulatory 

reports. As mentioned above EGU sources will be included in the 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 emissions (for the apportionment analysis), it was 

agreed that Ohio EPA would omit these emissions in the partial areas from the 

insignificance analysis for the partial nonattainment counties. Moreover, omitting these 

emissions will provide a more conservative finding of mobile emissions insignificance as 

discussed above. 

Table 2 to Table 133

 show partial nonattainment areas apportioning results and entire 

county level emissions. The emission reductions from the apportioning approach 

compared to the entire county level emissions, 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 nonattainment areas). Please note the Table 2 to Table 13 below 

only reflects emissions as a part of the apportioning analysis for the partial 

nonattainment areas. The remaining emissions for full nonattainment counties included 

in the determination of insignificance can be found in redesignation and maintenance 

document from Table 18 to Table 47.

PM2.5 

Table 2 - Adams County, Ohio PM2.5 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 PM2.5 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 PM2.5 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 PM2.5 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

NOX 

Table 6 - Adams County, Ohio NOx 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 NOx 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 NOx 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 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 NOx 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 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

SO2 

Table 10 - Adams County, Ohio SO2 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 SO2 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 SO2 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 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 SO2 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 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 entire counties (without 

apportionment and with non-EGU emissions, see columns D and F) and only 

nonattainment areas (with apportionment and excluding Non-EGU emissions in the 

partial areas, see columns E and G). The comparison shows the apportionment results 

in a decrease of at least 7.23% for 2015 emissions and 7.05% for 2022 of PM2.5 

emissions, 2.81% for 2015 emissions and 2.84% for 2022 emissions of NOx emissions 
8 

and 0.20% for 2015 emissions and 0.24% for 2022 emissions of SO2 emission. Recall, 

as mentioned above, detailed emissions by each sector for full nonattainment counties 

included in the determination of insignificance and identified 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 and 2022 (tpy) – With CAIR 

A D E F G

PM2.5 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 PM2.5

TOTAL 10,055.81 9,328.97 9,880.70 9,183.65

Table 15 - Huntington-Ashland Area NOx Partial Nonattainment Areas 

Apportioning Results and Entire County Level Emissions: Emission 

Totals for Projected 2015 and 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 and 2022 (tpy) – With CAIR 

A D E F G

SO2 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 SO2

TOTAL 149,635.65 149,334.67 113,639.41 113,368.65

The following table shows the percentage of the mobile portion of all emissions, for 

each pollutant in the entire nonattainment area, apportioned per the above, for 2015 

and 2022. 

Table 17 – Percent of Mobile Emissions for the Huntington-Ashland Area in 2015 

and 2022 – With Apportionment Analysis for partial nonattainment 

areas 

NOx SO2 PM2.5

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%

NOx constitutes less than six percent (<6%) of the area’s total NOx emissions in the 

2015 and 2022 horizon years. PM2.5 constitutes less than three percent (<3%) of the 

area’s total PM2.5 emissions in the 2015 and 2022 horizon years. SO2 constitutes less 

than one percent (<1%) of the area’s total SO2 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 PM2.5, NOx, and SO2 continue to be insignificant contributors to the nonattainment 

problem of the Huntington-Ashland area, as agreed upon as a part of the interagency 

consultation process. Moreover, the results from Table 17 show emissions adjusted for 

partial nonattainment areas and does not include Non-EGU emission sources in partial 

areas, providing higher percentages of mobile emissions (for all three pollutants) and 

showing a conservative (overestimated) percentage of mobile emissions. Because of 

this finding it is not necessary to 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 Agency 

Redesignation and Maintenance Plan for the Ohio Portion of the HuntingtonAshland, OH-KY-WV Annual PM2.5 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 Environmental Protection Agency (U.S. 

EPA) revise the current air quality 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 PM2.5 national ambient air quality standard 

(NAAQS). Fine particle pollution or PM2.5 is a mixture of microscopic solids and liquid 

droplets suspended in air that is 2.5 micrometers in diameter and smaller – 1/30th the 

diameter of a human hair. PM2.5 can be emitted directly or formed secondarily in the 

atmosphere. Air quality monitoring data collected between 2008 and 2010 in the region 

demonstrate attainment of the NAAQS and there is evidence that the improved air 

quality is due to permanent, enforceable emission reductions. In addition, existing 

requirements are sufficient to maintain the 1997 annual PM2.5 standard in this area at 

least ten years into the future. 

Computer models show that existing state and federal emission reduction requirements 

are sufficient to attain and maintain the NAAQS in the Huntington-Ashland area. 

Therefore, Ohio EPA proposes to utilize existing emission inventory information and 

projections of future emissions as the demonstration 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 PM2.5 standard. As part of an acceptable maintenance plan, Ohio EPA is 

required to develop a contingency plan to provide for additional emission reductions if a 

violation of the NAAQS is monitored after the area has been redesignated. The plan 

which Ohio EPA is proposing to USEPA as part of this redesignation contains 

reductions which will help alleviate the ambient problem until a revised SIP can be 

developed. 

The State of Ohio proposes to: 

1. Request the U.S. EPA redesignate the Huntington-Ashland area to attainment 

with respect to the 1997 annual PM2.5 NAAQS and revise the maintenance plan. 

This request will document that 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 allow public comment and to satisfy USEPA 

requirements for public involvement in SIP related activities. This notice addresses Ohio 

EPA’s reliance on the emission projections as evidence of attainment and maintenance 

and the commitment to institute contingency measures if ambient exceedances or 

violations trigger the contingency plan requirements. 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, First Floor Conference Room, 605 Washington 

Street, Portsmouth, Ohio. 

All interested persons are entitled to attend 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 at the hearing or to the above address by 

the close of business on April 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 document should 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

89th 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 ,~yV~

From: Lawrence County Port Authority, Bill Dingus, Executive Director .r:.

Subject: Comments for April 21, 20I] 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 ofthese 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 ofmeeting standards, and thereby,

open new opportunities to ow' region. Please do not hesitate if information is

needed to quantify the importance ofthis change.
140610th 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 orisis 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-~shland, 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 inuOQs:;: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 shouldnever 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
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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,

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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

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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.

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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.

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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

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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.

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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

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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.

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MR. WALTON: Thank you.

MS. McCARRON: If you could spell your

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24 name for the court reporter, and then go ahead and

1 start.

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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.

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MS. McCARRON: NO problem.

MR. WALTON: I have another question

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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.

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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

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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.

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MS. MCCARRON: Okay.

MR. WALTON: But I am very, very

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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

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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.

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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,

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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

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5 no good. That's a concept. Less bad is no good.

6 ohio EPA is claiming that the dirty air

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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.

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7 one might argue that one cannot have

8 zero particulate matter. And to that I say: why Page 9
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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 exist," end quote.

19 Nature doesn't have waste. Humans

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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 gna1 of

10 design failure. In fact, it is what we call a

11 license to harm; a permit issued by a government

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13 dispense sickness, destruction, and death at an

14 ' acceptab1e' 1eve1 ," 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

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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
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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.

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24 MS. McCARRON: You've got about one

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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

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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

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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

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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

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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.

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16 reporter.

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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

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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

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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

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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.

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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.

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And that's it. Thank you.

MS. McCARRON: All right. Thank you.

Scott Evans.

MR. EVANS: Yes. I am scott Evans,

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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.

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7 MS. McCARRON: Okay. Are you going to

8 designate which --

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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.

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17 "Dear Di rector Na11 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 "This area has been be1ow the na ti ona1

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.

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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.

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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

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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

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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."

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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.

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15

16

MS. MCCARRON: Thank you.

Don Hadsell.

MR. HADSELL: Yeah, Don Hadsell,

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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

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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 1oca1 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

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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

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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

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o

22

23

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97875 HEARING. PUBLIC 042111.txt

page 27
1 

Response to Comments 

PM2.5 redesignation request for the 1997 PM2.5 Annual Standard 

for the Huntington-Ashland Area 

Agency Contact for this Package

Division Contact: (Carolina Prado, Division of Air Pollution Control, 614-644-2310, 

Carolina.Prado@epa.state.oh.us) 

Ohio EPA held a public hearing in Portsmouth, OH on April 21, 2011, regarding the 

Redesignation Request and Maintenance Plan for the Huntington-Ashland PM2.5

Nonattainment Area. This document summarizes the comments and questions received 

at the public hearing and during the associated comment period, which ended on April 

21, 2011. Ohio EPA reviewed and considered 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 document, the questions are grouped by topic and 

organized in a consistent format. The name of the commenter follows the comment in 

parentheses. 

Ohio EPA received four letters in support of the redesignation request for the 

1997 PM2.5 Annual Standard for the Huntington-Ashland Area (State 

Representative Terry A. Johnson, 89th Ohio House District; Bill Dingus, Executive 

Director for the Lawrence Economic Development Corporation; Bill Dingus, 

Executive Director for the Lawrence County Port Authority 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 countries 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 changing, much as a river flows 

continuously with different water at any one place at any 

given moment in time (Barbara Lund). 

Response 1: The Huntington-Ashland metropolitan statistical area (MSA) 

includes five counties in West Virginia (Cabell and Wayne), 

Kentucky (Boyd and Greenup) and Ohio (Lawrence). 

Nonattainment areas are not only selected based upon an MSA. 

Rather, selection is based on several factors including, but not 

limited to, air monitoring data and emissions sources that can 

influence monitored violations. This 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 with Lawrence County, contained 

a violating monitor at that time. The partial areas of Adams and 

Gallia counties, even though they are not part of the HuntingtonAshland MSA, were included as part of the nonattainment area 

primarily because of the existence of an electric generating unit 

(EGU - power plant) in the townships designated nonattainment 

(Monroe and Sprigg Townships in Adams County and Cheshire 

Township in Gallia County). Emissions from these sources may 

contribute to violations at those monitors in the 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 of air quality and being an 

attainment or non-attainment county, I was under the 
3 

impression that the entire area 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. But for many years, or several 

years, I think Scioto County met attainment standards, but 

the other counties in the metropolitan area did not. The 

County Commissioners, the Port Authority, and others 

locally, had made a request three 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 attainment standards (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. Therefore, in 2010, 

Ohio EPA began working with the environmental agencies in 

Kentucky and West Virginia, in a joint effort to prepare information 

necessary for the redesignations. However, each state agency is 

responsible for preparing and submitting their own redesignation 

request. USEPA Region 5 will act on Ohio's request individually 

and redesignate only the four counties 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 any time period where Ohio's 

counties are designated attainment and another state’s counties 

are designated nonattainment, Ohio would follow its approved 

maintenance plan while the other state would continue to follow 

the requirements for nonattainment areas (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, Kentucky, that is an attainment 

county. Being in economic development, I'm very much 

involved in competition with the State of Kentucky and West 

Virginia, and we have a situation right now where SunCoke, if 

we were attainment, probably 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 and -- if air emissions is a 

concern of theirs, they look at a map, they'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. So also 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 maintenance of the HuntingtonAshland PM2.5 Nonattainment Area. 

Comment 4: Let me start by saying that less bad is no good. That's a 

concept. Less bad is no good. Ohio 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 PM2.5. 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 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 maintenance of the HuntingtonAshland PM2.5 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 PM2.5 annual standard) Ohio 

EPA has been working together with the regulated community to 

reduce atmospheric emissions and achieve or go beyond 

USEPA’s mandates.

Comment 5: The March 2010 draft of the Redesignation and maintenance 

plan says nothing about why particulate matter is regulated 

or what the benefits are of lowering the amounts of 

particulate matter. The State Implementation Plan for PM2.5, 

revised June 7, 2010, 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 premature mortality, aggravation 

of respiratory and cardiovascular disease, lung disease, 
5 

decreased lung function, asthma 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 cleaner ant 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 animals and also on plants. That 

is not good. (Barbara Lund). 

Response 5: Particulate matter is one of the six 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 pollutant challenge facing our state and 

region. Achieving significant reductions in particulate matter is 

one of Ohio EPA’s priorities. Over the past 14 years Ohio EPA 

has made significant progress in reducing 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 PM2.5 monitoring data in the area. For the 

monitors located in Ohio’s two counties, monitoring data has 

shown a decrease from a high of 22.03 ug/m3 (1999 to 2001) to a 

low of 11.6 ug/m3

 (2008 to 2010). Lowering PM2.5 emissions and 

meeting the federal air quality standard was achieved by 

controlling and modernizing facilities and/or sources in the area; 

USEPA studies show that PM2.5 emission reductions results in 

better health protections for the people living near these facilities. 

 A state is not required to prepare a risk analysis or health benefits 

analysis as part of a redesignation request and maintenance plan. 

USEPA prepares these analyses as part of the review of national 

ambient air quality standards. USEPA's mandate is to protect 

public health and welfare with an adequate margin of safety. This 

means that USEPA does not consider costs or other economic 

factors in setting air quality standards, rather its decision is purely 

a public health decision. USEPA did perform such analyses when 

it established the 1997 annual PM2.5 standard at 15.0 ug/m3. At 

that time, USEPA determined that 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 analyses to determine an acceptable 

level for the standard based upon the most recent scientific 

evidence. USEPA has been conducting such a review and 

intends to announce its recommendation on any necessary 

changes to the PM2.5 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 emulate nature. The world is 

now in a crisis situation from the many human industrial 

wastes and pollutants. Another quote and this one by Albert 

Einstein, "The world will not evolve 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 PM2.5 Redesignation 

Request for the Huntington-Ashland nonattainment area. Ohio 

EPA will continue to work with the regulated community to reduce 

waste and pollution. 

Comment 7: People have known, probably 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 effects. 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 complicit 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 government to an industry so that 

it, the industry, may dispense sickness, 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 intent of the law, to work with 
7 

industry to eliminate all waste and all pollution such that 

regulation would not be necessary. Ohio EPA follows 

national laws. I’m fairly 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 own plans for the future and 

implementing them. Ohio EPA similarly 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 area. In part this is due to important 

regulatory requirements established 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 waste 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 after redesignations. It also 

says, “Ohio, through Ohio EPA’s legal section, has the legal 

authority and necessary resources to actively enforce any 

violations of its rule or permit 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 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 positive 

action. I believe that any fines are probably 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 (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 applying 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 businesses. Ultimately, it is Ohio 

EPA’s preference to assist companies in complying with 

regulations so that any enforcement is not necessary. 

Comment 9: I’m concerned that the current Ohio administration strongly 

favors private economic activity over public welfare, 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 cutting funding to Ohio EPA. There 

are likely far too few Ohio EPA employees to do all the 

necessary monitoring and enforcement of clean air laws. 

Despite their best intentions to do a proper job, Ohio EPA 

employees may not have proper 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 concerns. Undoubtedly, Ohio and 

the nation as a whole, is facing many economic hurdles. Ohio 

EPA, as does many other government agencies, strives to do 

more with fewer resources. However, the mission of Ohio EPA’s 

Division of Air Pollution Control remains unchanged; “to attain and 

maintain the air quality at a level 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 redesignation from nonattainment to 

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

it. In my opinion, the whole world 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 industrial 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 industrial development of Scioto 

County. (William Tipton). 

Response 11: Thank you for your comment on Ohio's PM2.5 Redesignation 

Request for the Huntington-Ashland nonattainment area. 

Comment 12: The State of Ohio is requiring burning of biomass fuels in our 

power plants that were never designed to burn anything but 

coal. Just the burning of biomass 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 loss of thousands of acres of 

trees. And what effect would that have on the quality of our 

air? 63,000 acre forest, and that will 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 pollution be stopped. (William 

Tipton). 

Response 12: Ohio EPA is not aware of any regulatory requirement for the 

burning of biomass by power 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 energy sources, such as clean coal, 

nuclear energy, fuel cells, hydro, wind, solar, biomass and 

cogeneration. Half of this standard (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; rather, it is one option to fulfill the 

alternative energy source requirement. 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 Environmental Protection Agency should never 

be abbreviated EPA. The term EPA is used by those who 

want us to forget who you are and what you really stand for. 
10 

In all of your statements and communications, you should 

insist that Environmental Protection 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 document providing reference to the 

acronym, EPA. Thereafter, the 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 at SunCoke and Sunoco. From 

the standpoint as a former township trustee, 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 resident 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 stay 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 proposed expansion of theirs, many 

more would have the opportunity to do so. It only makes 

sense that the same air that we basically 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 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. And then 

for someone who could be looking 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. Walton 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 should not raise emissions or 

prevent those opportunities from manifesting themselves in 

the community. They need only be solicited. 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 PM2.5

Redesignation Request for the Huntington-Ashland nonattainment 

area. 

Comment 15: The commentor pointed out in 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 outdated or unenforced regulation. 

The fact that people (corporations) can and do commit 

wrongs indicates that regulations 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