Appendix A-1 

Air Quality System (AQS) Data 
UNITED STATES ENVIRONMENTAL PROTECTION AGENCY

QUICKLOOK CRITERIA PARAMETERS

Report Request ID: 986601 Report Code: AMP450 Apr. 27, 2012

Selection Criteria Page 1

User ID: IDA

State County Site Parameter POC City AQCR UAR CBSA CSA

EPA

Region Method Duration Begin Date End Date

39 151

GEOGRAPHIC SELECTIONS

PROTOCOL SELECTIONS

Parameter

Classification Parameter Method Duration

QUICK LOOK 88101

SELECTED OPTIONS

EVENTS PROCESSING

MERGE PDF FILES

WORKFILE DELIMITER

Option Type Option Value

EXCLUDE REGIONALLY CONCURRED EVENTS

YES

,

SORT ORDER

1

2

3

4

5

6

7

Order Column

PARAMETER_CODE

STATE_CODE

COUNTY_CODE

SITE_ID

POC

DATES

EDT_ID

GLOBAL DATES

2009

Start Date End Date

2011

Tribal

Code

APPLICABLE STANDARDS

Standard Description

PM25 24-hour 2006

PM25 Annual 2006
Apr. 27, 2012

Note: The * indicates that the mean does

not satisfy summary criteria.

UNITED STATES ENVIRONMENTAL PROTECTION AGENCY

AIR QUALITY SYSTEM

QUICK LOOK REPORT (AMP450)

Page 1 of 4

EXCEPTIONAL DATA TYPES

EDT DESCRIPTION

0

1

2

5

NO EVENTS

EVENTS EXCLUDED

EVENTS INCLUDED

EVENTS WITH CONCURRENCE EXCLUDED
Apr. 27, 2012

Note: The * indicates that the mean does

not satisfy summary criteria.

UNITED STATES ENVIRONMENTAL PROTECTION AGENCY

AIR QUALITY SYSTEM

QUICK LOOK REPORT (AMP450)

Page 2 of 4

PM2.5 - Local Conditions (88101) Ohio Micrograms/cubic meter (LC) (105)

SITE ID

P

O

C PQAO CITY COUNTY ADDRESS YEAR METH #OBS

4TH

MAX CERT EDT

39-151-0017

39-151-0017

39-151-0017

39-151-0017

39-151-0017

39-151-0017

39-151-0020

39-151-0020

39-151-0020

1

1

1

2

2

2

1

1

1

0151

0151

0151

0151

0151

0151

0151

0151

0151

Canton

Canton

Canton

Canton

Canton

Canton

Canton

Canton

Canton

Stark

Stark

Stark

Stark

Stark

Stark

Stark

Stark

Stark

1330 DUEBER

1330 DUEBER

1330 DUEBER

1330 DUEBER

1330 DUEBER

1330 DUEBER

420 MARKET

420 MARKET

420 MARKET

2009

2010

2011

2009

2010

2011

2009

2010

2011

116

142

000

116

142

142

116

142

142

45.7

43.4

33.7

31.9

44.7

26.6

28.4

42.4

26.0

0

0

0

0

0

0

0

0

0

24-HOUR 

98TH

PERCENTILE

VALUE

30.0

33.0

28.1

31.9

42.0

26.5

27.5

32.2

23.1

314

330

332

54

60

59

108

112

114

1ST

MAX

2ND

MAX

3RD

MAX

35.6

43.4

33.6

28.4

42.0

26.5

27.6

37.8

24.0

32.5

41.3

31.9

25.6

31.3

25.3

27.5

32.2

23.1

30.7

38.2

29.4

25.1

30.4

21.6

26.1

31.7

22.3

13.15*

14.38 

12.79 

12.38*

14.99 

11.76*

11.92 

13.76 

11.28 

WTD

ARITH

MEAN
Apr. 27, 2012

Note: The * indicates that the mean does

not satisfy summary criteria.

UNITED STATES ENVIRONMENTAL PROTECTION AGENCY

AIR QUALITY SYSTEM

QUICK LOOK REPORT (AMP450)

Page 3 of 4

88101

88101

88101

000

116

142

MULTIPLE METHODS

BGI Model PQ200 PM2.5 Sampler w/WINS

BGI Models PQ200-VSCC or PQ200A-VSCC

MULTIPLE METHODS

GRAVIMETRIC

Gravimetric

PARAMETER

METHOD

CODE COLLECTION METHOD ANALYSIS METHOD

METHODS USED IN THIS REPORT
Apr. 27, 2012

Note: The * indicates that the mean does

not satisfy summary criteria.

UNITED STATES ENVIRONMENTAL PROTECTION AGENCY

AIR QUALITY SYSTEM

QUICK LOOK REPORT (AMP450)

Page 4 of 4

PQAOS USED IN THIS REPORT

PQAO AGENCY DESCRIPTION

0151 Canton City Health Department Air Pollution Control
Appendix A-2 

SLAMS letter 
Environmental 

Protection Agency 

John R. Kasich, Governor 

Mary Taylor, Lt. Governor 

Scott J. Nally, Director 

CERTIFIED MAIL 

April 27, 2012 

George Czerniak, Acting Director 

Air and Radiation Division 

U.S.EPA, Region V 

77 West Jackson Boulevard 

Chicago, Illinois 60604 

RE: 2011 SLAMS Data Certification 

Dear Mr. Czerniak: 

Please find enclosed our SLAMS Report (AMP-450, AMP-450NC and AMP255) for calendar year 2011 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 Sulfur Dioxide data were previously certified in our letter of 

February 2 7'h. 

I certify that the 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, 

;{Mtet~/( 

Robert Hodanbosi 

Chief, Division of Air Pollution Control 

Enclosure 

50 West Town street, Suoe 700 

P.O. Box 1049 

Columbus, OH 43216-1049 

614!644 3020 

614 1 644 3681 (fax) 

www.epa.ohio.gov 
Appendix B-1 

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-1 

Mobile Source Emissions 

Inventory for the Canton 

PM2.5 Nonattainment Area 
PM2.5 CONFORMITY REDESIGNATION 

FOR STARK COUNTY, OHIO 

Draft Report 

April, 2012 

Prepared By: 

STARK COUNTY AREA TRANSPORTATION STUDY 

201 Third Street NE, Suite 201 

Canton, Ohio 44702 
This report is the product of a study financed in part by the US Department of Transportation, Federal Highway 

Administration, Federal Transit Administration and the Ohio Department of Transportation. The contents of this report reflect 

the views of the Stark County Area Transportation Study, which is responsible for the facts and the accuracy of the data 

presented herein. The contents do not necessarily reflect the official views or policy of the U. S. Department of Transportation. 

This report does not constitute a standard, specification, or regulation. 
PM2.5 Conformity Redesignation for Stark County, Ohio Page i 

TABLE OF CONTENTS 

Introduction..................................................................................................................................... Page 1 

On Road Mobile Emission Summary ............................................................................................. Page 2 

Latest Planning Assumptions.......................................................................................................... Page 3 

Travel Demand Modeling - Analysis Years ................................................................................... Page 3 

Socio-Economic Demographics...................................................................................................... Page 3 

Emission-Factor Generation ........................................................................................................... Page 6 

Temperature and Relative Humidity............................................................................................... Page 7 

Ramp Fraction................................................................................................................................. Page 8 

Source-Type Population.................................................................................................................. Page 9 

Vehicle-Age Distribution................................................................................................................ Page 8 

Road-Type Distribution .................................................................................................................. Page 11 

Post Processing ............................................................................................................................... Page 12 

Appendix A – Interagency Consultation Documentation 
PM2.5 Conformity Redesignation for Stark County, Ohio Page ii 

LIST OF TABLES

Table 1 SCATS Region On-Road Mobile Emissions.......................................................... Page 2 

Table 2 SCATS Region Representative Socio-Economic Demographic Variables 

By County 2005-2025............................................................................................. Page 4 

Table 3 MOVES Inputs........................................................................................................ Page 6 

Table 4 Average Temperature and Relative Humidity Data................................................ Page 8 

Table 5 Ramp Fractions ....................................................................................................... Page 8 

Table 6 Source-Type Population for Year 2005 .................................................................. Page 9 

Table 7 Vehicle-Age Distribution for Stark County............................................................ Page 10 

Table 8 Road-Type Distribution for Stark County .............................................................. Page 11 

LIST OF FIGURES

Figure 1 SCATS Geographic Area Fine Particulate Matter Non-Attainment Area Boundary 

 ................................................................................................................................. Page 1 

Figure 2 SCATS Geographic Area Covered by Travel Demand Model and Traffic Analysis Zone 

Structure.................................................................................................................. Page 5 

PM2.5 Conformity Redesignation for Stark County, Ohio Page iii 

SELECTED ABBREVIATIONS & ACRONYMS 

SCATS – Stark County Area Transportation 

Study 

CFR – Code of Federal Regulations 

FHWA – Federal Highway Administration; 

FTA – Federal Transit Administration; 

LRTP – Long Range Transportation Plan 

MOBILE6 – Mobile Source Emission Factor 

Model 

MOU – Memorandum of Understanding 

MOVES – Motor Vehicle Emission Simulator 

MPO – Metropolitan Planning Organization 

MVEB – Motor Vehicle Emissions Budget 

NAAQS – National Ambient Air Quality 

Standard 

NOX – Nitrogen Oxides 

ODOT – Ohio Department of Transportation 

OEPA – Ohio Environmental Protection 

Agency 

PM – Particulate Matter 

PM2.5 - Particulate Matter with an aerodynamic 

diameter less than 2.5 microns (often referred to 

as Fine Particulate Matter) 

PM10 – Particulate Matter with an aerodynamic 

diameter less than 10 microns 

SIP – State Implementation Plan 

SO2 – Sulfur Dioxide 

STIP – Statewide Transportation Improvement 

Program 

TAZs – Traffic Analysis Zones 

TCM – Transportation Control Measure 

TDM – Travel Demand Model 

TIP – Transportation Improvement Program in a 

Metropolitan Planning Area 

USEPA – United States Environmental 

Protection Agency 

VHT – Vehicle Hours of Travel 

VMT – Vehicle Miles of Travel 

VOC – Volatile Organic Compounds 

Transportation Air Quality Analysis and Technical Documentation 

For the Canton/Massillon Metropolitan Statistical Area 

State Implementation Plan Inventory Mobile Emission Estimates 

For the U.S. EPA 1997 Annual PM2.5 National Ambient Air Quality Standard 

INTRODUCTION

This memorandum documents the air quality analyses and underlying planning assumptions performed 

for the Annual PM2.5 on-road mobile source emission inventories for the Canton/Massillon Metropolitan 

Statistical Area State Implementation Plan (SIP). The Ohio Department of Transportation (ODOT), 

Division of Transportation System Development-Modeling and Forecasting Section and the Stark 

County Area Transportation Study (SCATS) completed these analyses in coordination with the Ohio 

Environmental Protection Agency (OEPA). 

 

The SCATS Region is comprised of Stark County, Ohio. The Canton/Massillon Metropolitan Statistical 

Area (MSA) was classified as nonattainment for PM2.5 in the Federal Register on January 5, 2005. 

Although the MSA area also includes Carroll County, OEPA and USEPA concurred that only Stark 

County is designated as the nonattainment area within the MSA as Carroll County is rural in nature with 

a population of less than 30,000. SCATS is the MPO (Metropolitan Planning Organization) for this 

county. The SCATS MPO boundary and urban planning model cover the entire nonattainment area. 

This area is shown on the following map as prepared by the USEPA. 

Figure 1 – Location of Massillon/Canton MSA 

Map as shown at: http://www.epa.gov/pmdesignations/states/Ohio.htm 

PM2.5 Conformity Redesignation for Stark County, Ohio Page 1 

SCATS submitted the necessary Travel Demand Model networks along with all land use and socioeconomic demographics. The ODOT Modeling and Forecasting section performed the MOVES runs to 

generate travel-demand-model-based emission factors as well as the complete air quality analyses for 

the metropolitan area. 
ON-ROAD MOBILE EMISSION SUMMARY 

Table 1 below presents a summary of the pollutant emissions including Fine Particulate Matter (PM2.5), 

Nitrogen Oxides (NOx), and Sulfur Dioxide (SO2) modeled for the SCATS Region. The Model Years 

for the demonstration includes the Base Year 2005, Attainment Year 2008 (a leap year), Interim Year 

2015, and Maintenance Year 2025. 

Table 1 

SCATS REGION ON-ROAD MOBILE EMISSIONS 

Direct PM

TOTAL

Model PM 2.5

Year # Days PM 2.5 (tons/yr)

2005 365 1.19 433.47

2008 366 0.78 286.14

2015 365 0.49 177.68

2025 365 0.24 88.26

NOX Precursors

TOTAL

Model NOX

Year # Days NOX (tons/yr)

2005 365 38.37 14004.65

2008 366 29.99 10977.26

2015 365 18.54 6767.79

2025 365 11.13 4064.20

SO2

TOTAL

Model SO2

Year # Days SO2 (tons/yr)

2005 365 0.52 191.33

2008 366 0.13 46.12

2015 365 0.06 20.84

2025 365 0.05 19.24

VMT

Model TOTAL

VMT VMT

Year # Days (daily) (annual)

2005 365 7,880,843 2,876,507,695

2008 366 7,315,831 2,677,594,146

2015 365 7,675,289 2,801,480,485

2025 365 8,248,822 3,010,820,030

PM2.5 Conformity Redesignation for Stark County, Ohio Page 2 
PM2.5 Conformity Redesignation for Stark County, Ohio Page 3 
PM2.5 Conformity Redesignation for Stark County, Ohio Page 4 

LATEST PLANNING ASSUMPTIONS 

The annual PM2.5 inventory runs meet the latest planning-assumption requirements. This report will 

present the latest population and land use data available that calibrated the modeling process used to 

calculate the vehicle emissions for the mobile-emissions budgets as well as the input values for U.S. 

EPA’s most recent emissions software MOVES for this air-quality re-designation. 

This re-designation effort will require the use of U.S. EPA’s most recent emissions software MOVES 

for all mobile source-emission analyses, and the annual emissions estimates will be based a singleseason approach. Since travel demand models produce average daily conditions, the daily emissions 

estimates are multiplied by 365 days to produce annual emissions estimates expressed in tons per year. 

TRAVEL DEMAND MODELING - ANALYSIS YEARS 

A Travel Demand Model (TDM) is the traditional forecasting tool used to examine potential changes in 

future travel patterns for a specific study area, in this case the Canton/Massillon Metropolitan Statistical 

Area. The SCATS MPO, with the assistance of ODOT Modeling & Forecasting, maintains a validated 

region-wide TDM that employs a four-step modeling process consisting of trip generation, trip 

distribution, mode choice, and route assignment performed with the Cube Voyager software package. 

The model outputs generated from the TDM are link-by-link directional traffic volumes for four time 

periods, morning, mid-day, evening, and night-time. The outputs are used for simulating Base Year and 

Horizon Year travel patterns generated by the LRTP transportation network. 

The current SCATS TDM Validation Year is 2000. The model uses comparable Average Daily Traffic 

count data, updated socio-economic variables for each of the analysis years by either updating existing 

or known land use commitment for 2005 and 2008, or projecting 2015 and 2025 variables based on a 

straight-line extrapolation between the 2005 set of variables and the Horizon Year 2030 variables. These 

networks represent all planned federal-aid projects as well as any regionally significant projects found in 

the SCATS TIP and LRTP expected to be open for traffic by the end of each respective analysis year. 

The interagency consultation process, established the following model years for the analysis that 

reflected the most recent correspondence from the U.S. EPA: 

• Analysis Year 2005 – Baseline Emissions 

• Analysis Year 2008 – Attainment Year 

• Analysis Year 2015 – Interim Year 

• Analysis Year 2025 – Maintenance Year 

SOCIO-ECONOMIC DEMOGRAPHICS 

Identifying projected growth centers and understanding urban and rural population changes are essential 

to determine future transportation needs in a given study area. Critical elements include an 

understanding of the past and anticipated future shifts in the region’s economy, population, land use 

patterns, and other environmental factors over time. In turn, these factors are useful for predicting future 

transportation patterns and justifying transportation improvements over the next twenty years. 

Travel forecasting procedures require the user to delineate the TDM study area into geographic areas 

called Traffic Analysis Zones (TAZs). Typically, TAZs are based on factors such as land use, area types 

(urban, suburban or rural), or political government units such as cities, villages, or townships. TAZs 

represent centers of travel generators or attractors based on a set of demographic variables. The SCATS 
MPO collects and reviews the TDM independent variables that characterize current and future estimates 

of the metropolitan area’s social and economic activity that may influence land-use development 

patterns. In all, there are 690 TAZs in the SCATS model. Figure 2 displays the SCATS MPO 

geography covered by the travel demand model including the Traffic Analysis Zone structure. The 

computer-based TDM for the SCATS highway network employs the following land use variables: 

• [AREA_TYPE] ≡ Area Type 

• [AVG_PARK] ≡ Average parking cost 

• [ENROLL] ≡ School enrollment classified by Private [ENROLL_PRIV], Public 

[ENROLL_PUB] and Post-secondary [ENROLL_UNIV] schools 

• [HOTEL_RM] ≡ Hotel Rooms 

• [MED_HHINC] ≡ Median household income 

• [POP] ≡ Population 

• [POP_18] ≡ Population 18 years or less 

• [POP_GRP] ≡ Population residing in Group Quarters 

• [TOTEMP] ≡ Total Employment grouped by the North American Industrial Classification 

System (NAICS) 

• [TOT_HH] ≡ Occupied housing 

• [TOT_VEH] ≡ Vehicles available per household 

• [WORKERS] ≡ Workers per household 

Table 2 is a set of demographic variables developed for the most recent Long-Range Transportation Plan 

for the SCATS area compiled in May, 2009. 

Table 2 

SCATS REGION 

REPRESENTATIVE SOCIO-ECONOMIC DEMOGRAPHIC 

VARIABLES 2005-2025 

2005 2008 2015 2025

Population 385,781 386,666 388,766 391,722

Households 151,905 153,165 156,113 160,315

Employment 177,027 185,276 204,919 232,490

PM2.5 Conformity Redesignation for Stark County, Ohio Page 5 
Figure 2 

SCATS GEOGRAPHIC AREA 

COVERED BY TRAVEL DEMAND MODEL 

AND TRAFFIC ANALYSIS ZONE STRUCTURE 

PM2.5 Conformity Redesignation for Stark County, Ohio Page 6 
EMISSION-FACTOR GENERATION

The MOVES model generated the emission factors for base year-2005 and attainment year-2008 

representing the Transportation Improvement Program implemented in the SCATS Region. The model 

also generated emission factors for two future year scenarios 2015, and 2025. 

 

Table 3 summarizes the settings used in the MOVES run specification file and the MOVES CountyData Manager. The subsequent tables provide the specific inputs that are not using the MOVES default 

values. 

Table 3 

MOVES INPUTS 

MOVES Version MOVES2010a

Scale Custom Domain 

MOVES Modeling Technique Emission Factor Method 

Rates per Distance 

Rates per Vehicle 

Time Span Time Aggregation: Hour 

1 Month representing average annual temperatures 

All hours of day selected 

16 speed bins 

Weekdays only 

Geographic Bounds Stark County

Vehicles/Equipment All 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 None 

General Output Units = grams, joules and miles 

Output Emissions Time = hour, Location = custom area, on-road emission rates by road 

type and source use type

Advance Performance None 

RunSpec Parameter Settings 

PM2.5 Conformity Redesignation for Stark County, Ohio Page 7 
Table 3 (continued) 

MOVES INPUTS 

Source Type Population Combination of local and default data 

Local data from motor vehicle registration 

Default data used for source types 51, 52, 53, 61, and 62 

Future year growth rate based on MPO model Household growth rate

Vehicle Type VMT Combination of local and default data 

HPMSVTypeYear VMT = daily VMT from travel demand model 

monthVMTFraction = default 

dayVMTFraction=default 

hourVMTFraction=local 

I/M Program None

Fuel Formulation Default

Fuel Supply Default 

Metereology Data Local data obtained from NOAA National Climatic Data Center. Data 

will consist of monthly high and low temperatures and daily relative 

humidity for 2002. 

Ramp Fraction Using the base year travel demand model for VHT fractions.

Future fractions will be assumed constant

Road Type Distribution Use ODOT county summary VMT categorized by federal functional 

classes 

Age Distribution Combination of local and default data. 

Local data from motor vehicle registration 

Default data used for source types 41, 42, 43, 51, 52, 53, 61, and 62 

The same age distribution will be used for all analysis years 

Average Speed Distribution Default 

Alternative Fuel Type Default 

County Data Manager Sources 

TEMPERATURE AND RELATIVE HUMIDITY 

The single season approach for temperature and relative humidity uses weather data collected by the 

National Oceanic and Atmospheric Administration (NOAA) National Climatic Data Center (NCDC). 

Temperature data for the MOVES emission factors came from the Akron Canton Airport and are shown 

in Table 4. Data entered into a spreadsheet, provided by U.S. EPA, converted the Mobile6 data to get 

the correct data for the MOVES model. Annual PM2.5 emissions data were established using the single 

season methodology. The standard emissions modeling routines establish daily pollutant burdens. 

Annual direct PM2.5, NOx precursor, and SO2 emissions for the PM2.5 conformity tests were established 

by multiplying the daily model results by 365. 

PM2.5 Conformity Redesignation for Stark County, Ohio Page 8 
Hour Average Average

Temperature Relative Humidity

1 60.8 82

2 57.2 93

3 57.2 93

4 60.8 82

5 60.8 87

6 62.6 82

7 62.6 82

8 64.4 77

9 66.2 72

10 66.2 72

11 68.0 68

12 69.8 64

13 69.8 64

14 71.6 60

15 69.8 60

16 69.8 60

17 69.8 64

18 66.2 68

19 66.2 63

20 66.2 68

21 66.2 68

22 64.4 72

23 64.4 72

24 60.8 82

Table 4 – Temperature and Relative Humidity Data

RAMP FRACTION 

The Base-Year Travel Demand Model used the Vehicles Hour of Travel (VHT) fractions to derive the 

Ramp Fractions shown in Table 5. The future-year networks also used the base-year fractions. 

Table 5 

RAMP FRACTIONS 

roadTypeID roadDesc rampFraction

2 Rural Restricted Access 0.05

4 Urban Restricted Access 0.13

SOURCE-TYPE POPULATION 

A combination of local and MOVES default data is the Source-Type Population for vehicle 

classifications. The MOVES default values provided the data for Source-Type Population 51, 52, 53, 

61, and 62 while local data from Ohio motor vehicle registrations accounted for all other Source-Type 

PM2.5 Conformity Redesignation for Stark County, Ohio Page 9 
Population needed to run the MOVES model. Table 6 shows the Source-Type Population 

identifications, the corresponding Source-Type Name, and the number of vehicles analyzed for Stark 

County. 

Table 6 

SOURCE-TYPE POPULATION FOR YEAR 2005

11 MotorCycle 24,199

21 Passenger Car 282,913

31 Passenger Truck 129,129

32 Light Commercial Truck 2,916

41 Intercity Bus 129

42 Transit Bus 19

43 School Bus 744

51 Refuse truck 86

52 Single Unit Short-haul Truck 182

53 Single Unit Long-haul Truck 138

54 Motor Home 418

61 Combination Short-haul Truck 1,063

62 Combination Long-haul Truck 1,223

sourceTypeID sourceTypeName sourceTypePopulation

VEHICLE-AGE DISTRIBUTION 

A grouping of data from Ohio sources along with the MOVES model defaults make up the Vehicle-Age 

Distribution. MOVES default values included Vehicle-Type ID 41, 42, 51, 52, 53, 61, and 62. Local 

data from Ohio motor vehicle registrations accounted for all other Vehicle-Type ID. Table 7 shows the 

Vehicle-Age Distribution for Stark County. 

PM2.5 Conformity Redesignation for Stark County, Ohio Page 10 
Table 7 

VEHICLE-AGE DISTRIBUTION FOR STARK COUNTY, OH

Year Source Type Age Fraction Year Source Type Age Fraction

2005 11 0 0.0015 2005 21 0 0.0060

2005 11 1 0.0214 2005 21 1 0.0238

2005 11 2 0.0508 2005 21 2 0.0362

2005 11 3 0.0633 2005 21 3 0.0440

2005 11 4 0.0790 2005 21 4 0.0471

2005 11 5 0.0733 2005 21 5 0.0510

2005 11 6 0.0719 2005 21 6 0.0491

2005 11 7 0.0794 2005 21 7 0.0530

2005 11 8 0.0576 2005 21 8 0.0562

2005 11 9 0.0530 2005 21 9 0.0545

2005 11 10 0.0446 2005 21 10 0.0624

2005 11 11 0.0365 2005 21 11 0.0613

2005 11 12 0.0260 2005 21 12 0.0562

2005 11 13 0.0217 2005 21 13 0.0543

2005 11 14 0.0203 2005 21 14 0.0487

2005 11 15 0.0210 2005 21 15 0.0500

2005 11 16 0.0167 2005 21 16 0.0398

2005 11 17 0.0114 2005 21 17 0.0337

2005 11 18 0.0087 2005 21 18 0.0282

2005 11 19 0.0077 2005 21 19 0.0215

2005 11 20 0.0073 2005 21 20 0.0178

2005 11 21 0.0088 2005 21 21 0.0150

2005 11 22 0.0091 2005 21 22 0.0111

2005 11 23 0.0103 2005 21 23 0.0082

2005 11 24 0.0177 2005 21 24 0.0069

2005 11 25 0.0159 2005 21 25 0.0057

2005 11 26 0.0135 2005 21 26 0.0045

2005 11 27 0.0162 2005 21 27 0.0026

2005 11 28 0.0241 2005 21 28 0.0017

2005 11 29 0.0186 2005 21 29 0.0017

2005 11 30 0.0927 2005 21 30 0.0478

PM2.5 Conformity Redesignation for Stark County, Ohio Page 11 
ROAD-TYPE DISTRIBUTION 

 

The ODOT Division of Highways produced a summary of Vehicle Miles Traveled (VMT), categorized 

by federal functional class, for Stark County. This summary was used as the basis for the Road-TypeDistribution Fractions. Table 8 illustrates Road-Type Distribution. 

Table 8 

ROAD-TYPE DISTRIBUTION FOR STARK COUNTY 

NON-ATTAINMENT AREA

Source

Type

Road

Type

Road

Description

Road-Type

VMT Fraction

Source

Type

Road

Type

Road

Description

Road-Type

VMT Fraction

11 1 Off-Network 0 43 4 Urban Restricted Access 0.19

11 2 Rural Restricted Access 0.01 43 5 Urban Unrestricted Access 0.62

11 3 Rural Unrestricted Access 0.18 51 1 Off-Network 0

11 4 Urban Restricted Access 0.19 51 2 Rural Restricted Access 0.01

11 5 Urban Unrestricted Access 0.62 51 3 Rural Unrestricted Access 0.18

21 1 Off-Network 0 51 4 Urban Restricted Access 0.19

21 2 Rural Restricted Access 0.01 51 5 Urban Unrestricted Access 0.62

21 3 Rural Unrestricted Access 0.18 52 1 Off-Network 0

21 4 Urban Restricted Access 0.19 52 2 Rural Restricted Access 0.01

21 5 Urban Unrestricted Access 0.62 52 3 Rural Unrestricted Access 0.18

31 1 Off-Network 0 52 4 Urban Restricted Access 0.19

31 2 Rural Restricted Access 0.01 52 5 Urban Unrestricted Access 0.62

31 3 Rural Unrestricted Access 0.18 53 1 Off-Network 0

31 4 Urban Restricted Access 0.19 53 2 Rural Restricted Access 0.01

31 5 Urban Unrestricted Access 0.62 53 3 Rural Unrestricted Access 0.18

32 1 Off-Network 0 53 4 Urban Restricted Access 0.19

32 2 Rural Restricted Access 0.01 53 5 Urban Unrestricted Access 0.62

32 3 Rural Unrestricted Access 0.18 54 1 Off-Network 0

32 4 Urban Restricted Access 0.19 54 2 Rural Restricted Access 0.01

32 5 Urban Unrestricted Access 0.62 54 3 Rural Unrestricted Access 0.18

41 1 Off-Network 0 54 4 Urban Restricted Access 0.19

41 2 Rural Restricted Access 0.01 54 5 Urban Unrestricted Access 0.62

41 3 Rural Unrestricted Access 0.18 61 1 Off-Network 0

41 4 Urban Restricted Access 0.19 61 2 Rural Restricted Access 0.01

41 5 Urban Unrestricted Access 0.62 61 3 Rural Unrestricted Access 0.18

42 1 Off-Network 0 61 4 Urban Restricted Access 0.19

42 2 Rural Restricted Access 0.01 61 5 Urban Unrestricted Access 0.62

42 3 Rural Unrestricted Access 0.18 62 1 Off-Network 0

42 4 Urban Restricted Access 0.19 62 2 Rural Restricted Access 0.01

42 5 Urban Unrestricted Access 0.62 62 3 Rural Unrestricted Access 0.18

43 1 Off-Network 0 62 4 Urban Restricted Access 0.19

43 2 Rural Restricted Access 0.01 62 5 Urban Unrestricted Access 0.62

43 3 Rural Unrestricted Access 0.18

PM2.5 Conformity Redesignation for Stark County, Ohio Page 12 
PM2.5 Conformity Redesignation for Stark County, Ohio Page 13 

POST PROCESSING 

Several custom programs created by ODOT were used to compute the total emissions. The process uses 

data on daily and directional traffic distributions as well as more up-to-date volume/delay functions from 

the 2000 Highway Capacity Manual (HCM). This process, described below and illustrated in Figure 4, 

also uses rewritten code able to handle the newer model network formats and MOVES-generated 

emission factors. 

 

The first step in the process involves running postcms.exe to calculate hourly link volumes based on the 

percentage of the daily volume (travel demand model output) determined by a link’s facility and area 

type. The analysis does not use the link speeds from the travel demand model. Using a link’s volumeto-capacity ratio and link group code, a post-process to the model based on HCM methods estimates the 

link speeds. 

 

The second step (mmoves.exe) uses a combination of the MOVES emission factors and the hourly link 

volumes that are output of the postcms.exe program. The hourly volumes are multiplied by the MOVES 

emission factor for the corresponding hour of day, speed bin, and road type to calculate emissions for 

every network link for each hour. The total link on-road vehicle emissions for the area is the sum of all 

individual link-hour emissions. 

 

The third step, (vehcalm.exe), calculates vehicle-based emissions for each source type for each hour of 

the day. A combination of local and default data is the source for the vehicle source type. The final 

vehicle emissions are the sum of all individual hourly emissions for all vehicle types. 

Since the intrazonal trips are not loaded onto the network, the fourth step in the process requires a 

separate method to account for those trips that use local roads to travel within a zone. The intracalm.exe 

program uses intrazonal trips to estimate VMT using the area in square miles and intrazonal trips of each 

zone. The computer program assumes that the zone is circular and uses the radius of the circle as the 

average trip length for these intrazonal trips. By combining MOVES-generated emissions with 

estimated intrazonal VMT, the intrazonal emissions are then calculated. The emission rates are the same 

as those used to calculated link-based emissions. 

 

The final step is to summarize link, vehicle, and intrazonal emissions for each pollutant, and analyzed 

year, and to multiply annual average daily emissions by 365 to produce an annual estimate. 
APPENDIX A 

INTERAGENCY CONSULTATION DOCUMENTATION 

"Jennifer Hunter" 

<Jennifer.Hunter@epa.state.oh.us>

04/11/2011 02:02 PM 

To "Carolina Prado" <Carolina.Prado@epa.state.oh.us>, Dave.Moore1@dot.state.oh.us, Leigh.Oesterling@fhwa.dot.gov, 

morris.patricia@epamail.epa.gov, "Sarah VanderWielen" <Sarah.VanderWielen@epa.state.oh.us> cc Mark.Byram@dot.state.oh.us, Nino.Brunello@dot.state.oh.us Subject Re: Ozone Maintenance Plans - MOVES

 

Dave, Carolina forwarded this on to me. Add Sarah to this list - she is responsible for ozone where 

Carolina is PM2.5.

This is the last list Sarah generated that we worked on. I want to also add modeling the base year. In the 

last guidance we got from Pat it wasn't clear if that year would also be needed. However, b/c of the 

differences we are seeing between MOVES and MOBILE6 I'd like to have all the years in our submittals 

updated for clarity. We do compare base year and attainment year emissions to show there were real 

reductions.

I've attached the spreadsheet Sarah worked on that has your info below but the first tab also shows the 

base year used for each area and which counties were included.

One other nuance. In the next couple weeks we are going to work on some changes to RVP default 

values which will affect modeling for both Cinci and Cleve. We will be asking they be incorporated as 

the defaults in MOVES but that won't happen until after this work is done I am sure. Andy at OKI is 

already aware of this and the adjusted defaults. We still need to discuss with Cleve area. Once we work 

it up we will send it around to the IAC group for a thorough look see.

Also, we had a note in our spreadsheet that we would also need to MOVES based PM2.5 for the Canton 

area to be updated - since this is an area we haven't done for the redesignations. Carolina will work up 

dates/budgets for that and we will send around.

And on an unrelated/related note. We found out recently for the PM2.5 modeling we are doing for 

redesignation of the annual standard - that we will have to do different modeling and budgets for the 24-

hr standard. This affects Cleve and Steuby. We were going to set up a call with you all and the affected 

MPOs in those areas after we finish a seasonal analysis we are doing. So we could better discuss what 

inputs and assumptions may need to change for the 24-hr modeling.

Thanks, Jen 

>>> <Dave.Moore1@dot.state.oh.us> 4/11/2011 2:18 PM >>> 

Jennifer, 

One more question. 

Canton Annual PM2.5 - analysis years: Attainment 2008 - Interim Budget 2015 - Maintenance Budget 2022? 
Thanks 

DM 

-----"Jennifer Hunter" <Jennifer.Hunter@epa.state.oh.us> wrote: ----- 

To: Dave.Moore1@dot.state.oh.us, Patricia Morris/R5/USEPA/US@EPA 

From: "Jennifer Hunter" <Jennifer.Hunter@epa.state.oh.us> 

Date: 04/11/2011 01:29PM 

cc: "Carolina Prado" <Carolina.Prado@epa.state.oh.us> 

Subject: Re: Ozone Maintenance Plans - MOVES 

I'm not sure how we tackle Canton. We aren't doing a redesignation at this time and the only budget established previously 

was under the attainment demonstration and was for 2009 for PM2.5 and NOx. Pat do we have to go back and update that 

budget or since it is in the past does it just go away? I feel like I have asked this question before. Dave/Pat - did we ever 

establish any other PM2.5 budgets for other conformity reasons? 

Thanks, Jen 

----- Forwarded by Dave Moore/SysPlanProgMgmt/CEN/ODOT on 04/11/2011 02:49 PM ----- Morris.Patricia@epamail.epa.gov

04/11/2011 02:43 PM 

To "Jennifer Hunter" <Jennifer.Hunter@epa.state.oh.us> cc Dave.Moore1@dot.state.oh.us, "Carolina Prado" <Carolina.Prado@epa.state.oh.us> Subject Re: Ozone Maintenance Plans - MOVES

Jen, 

For Canton, yes, the 2009 budget will continue to apply to future years so it will need to be updated. I have heard that 

USEPA may extend the grace period for MOVES but of course nothing is for certain. Have you heard about an extension of 

the grace period? If the grace period is extended it will allow more time to update the Canton budgets. 

The PM2.5 attainment plan budget can be updated by running MOVES for the base year of modeling and again for the 2009 

year. As long as the percent emissions decrease is as big as the submitted attainment demonstration then the new MOVES 

budget can be justified. The ozone maintenance plan budgets would also need to be updated. 

Pat 

Patricia Morris 

Environmental Scientist 

USEPA Region 5 

(312) 353-8656

morris.patricia@epa.gov

From: Hunter, Jennifer [mailto:Jennifer.hunter@epa.state.oh.us] 

Sent: Tuesday, June 14, 2011 10:09 AM

To: CBaker@akronohio.gov; PJividen@akronohio.gov; jrdutton@co.stark.oh.us; areser@oki.org; B Davis; 

ngill@morpc.org; aramirez@mvrpc.org; ssalameh@ntelos.net; tmazur@lacrpc.com; smapel@lcounty.com; 

mhilll@lcounty.com; randy.durst@movrc.org; sschmid@clarkcountyohio.gov; daniel@clarkcountyohio.gov; 

mikepap@bhjmpc.org; gedeon@tmacog.org; rsharma@belomar.org; krodi@eastgatecog.org; 

pompeo@eastgatecog.org; morris.patricia@epamail.epa.gov; frank.burkett@fhwa.dot.gov; 

Mark.byram@dot.state.oh.us; NINO.BRUNELLO@DOT.STATE.OH.US; Dave.moore1@dot.state.oh.us
Cc: Velalis, Tom; Kim, Myoungwoo; VanderWielen, Sarah; Prado, Carolina; Braun, Paul

Subject: MOVES Information/Updates 

IAC Group,   

A couple questions came up a few months back (courtesy of Andy at OKI) that lead OEPA to do a little

research.  There are two issues this email will address and provide additional information regarding

inputs for MOVES related SIP/Conformity modeling.  If you have any comments or concerns on the

content and guidance within, please let me know by COB 6/24/11 

1- There was a request for updated meteorology and question of what data should be used.  First,

recent NOAA data, or other SIP approvable data, should be used, the same as you have historically.  A

question was also raised in regards to the ozone SIP and the need to use temperatures from the 10

worst ozone days.  If you are doing modeling that necessitates using the 10 worst ozone days, we have

provided the attached list for all ozone monitors in Ohio with ozone data showing which days are the

10 worst between 2006 and 2010.  If you would need any additional data or help on how to read this

document just let me know. 

2 – It has been brought to our attention that some of the default profile data  for fuel characteristics is

not what we believe to be appropriate. Specifically for the Cinci/Dayton area (low RVP requirements).   

Attached is a spreadsheet that identifies what the fuel characteristic defaults are and what should be

used in their place.  This only affects the Cinci‐Dayton area.  Defaults for the remainder of the state are

still good.  We will work with USEPA to get these defaults adjusted in the future. 

 

Thanks, Jen

From: B Davis [mailto:BDavis@mpo.noaca.org] 

Sent: Tuesday, June 14, 2011 10:24 AM

To: Hunter, Jennifer; CBaker@akronohio.gov; PJividen@akronohio.gov; jrdutton@co.stark.oh.us; Andy Reser; 

ngill@morpc.org; aramirez@mvrpc.org; ssalameh@ntelos.net; tmazur@lacrpc.com; smapel@lcounty.com; 

mhilll@lcounty.com; randy.durst@movrc.org; sschmid@clarkcountyohio.gov; daniel@clarkcountyohio.gov; 

mikepap@bhjmpc.org; gedeon@tmacog.org; rsharma@belomar.org; krodi@eastgatecog.org; 

pompeo@eastgatecog.org; morris.patricia@epamail.epa.gov; frank.burkett@fhwa.dot.gov; 

Mark.byram@dot.state.oh.us; NINO.BRUNELLO@DOT.STATE.OH.US; Dave.moore1@dot.state.oh.us

Cc: Velalis, Tom; Kim, Myoungwoo; VanderWielen, Sarah; Prado, Carolina; Braun, Paul; 

Leigh.Oesterling@dot.gov; V Nemalapuri; E Kang

Subject: RE: MOVES Information/Updates 

Hi Jennifer et al., 

 

Your e-mail prompts me to ask a question related to a similar but perhaps separate issue. Existing 

Mobile6 based budgets must be updated to MOVES so that conformity determinations can continue post 

March 2012. I’m hoping that we (meaning NOACA) can complete the technical aspects of this effort by 

September of this year. 

 

I’m guessing that the MOVES runs for the budget update efforts should mirror as closely as possible the 

inputs for the Mobile6 efforts. My question is how closely? For example should a 2020 network from 

the prior effort be used, or a current 2020 network? If we use a current network set, we will in effect not 

only be updating to MOVES but also revising the budgets at the same time. 

 

Just thought I’d start the conversation, 

 

Regards, 
 

Bill Davis 

NOACA 

(216)-241-2414, Ext. 251 

Andy Reser <ARESER@oki.org>

06/14/2011 10:38 AM 

To B Davis <BDavis@mpo.noaca.org>, "Hunter, Jennifer" 

<Jennifer.hunter@epa.state.oh.us>, "CBaker@akronohio.gov" 

<CBaker@akronohio.gov>, "PJividen@akronohio.gov" <PJividen@akronohio.gov>, 

"jrdutton@co.stark.oh.us" <jrdutton@co.stark.oh.us>, "ngill@morpc.org" 

<ngill@morpc.org>, "aramirez@mvrpc.org" <aramirez@mvrpc.org>, 

"ssalameh@ntelos.net" <ssalameh@ntelos.net>, "tmazur@lacrpc.com" 

<tmazur@lacrpc.com>, "smapel@lcounty.com" <smapel@lcounty.com>, 

"mhilll@lcounty.com" <mhilll@lcounty.com>, "randy.durst@movrc.org" 

<randy.durst@movrc.org>, "sschmid@clarkcountyohio.gov" 

<sschmid@clarkcountyohio.gov>, "daniel@clarkcountyohio.gov" 

<daniel@clarkcountyohio.gov>, "mikepap@bhjmpc.org" <mikepap@bhjmpc.org>, 

"gedeon@tmacog.org" <gedeon@tmacog.org>, "rsharma@belomar.org" 

<rsharma@belomar.org>, "krodi@eastgatecog.org" <krodi@eastgatecog.org>, 

"pompeo@eastgatecog.org" <pompeo@eastgatecog.org>, 

"morris.patricia@epamail.epa.gov" <morris.patricia@epamail.epa.gov>, 

"frank.burkett@fhwa.dot.gov" <frank.burkett@fhwa.dot.gov>, 

"Mark.byram@dot.state.oh.us" <Mark.byram@dot.state.oh.us>, 

"NINO.BRUNELLO@DOT.STATE.OH.US" <NINO.BRUNELLO@dot.state.oh.us>, 

"Dave.moore1@dot.state.oh.us" <Dave.moore1@dot.state.oh.us> cc "Velalis, Tom" <Tom.Velalis@epa.state.oh.us>, "Kim, Myoungwoo" 

<Myoungwoo.Kim@epa.state.oh.us>, "VanderWielen, Sarah" 

<Sarah.VanderWielen@epa.state.oh.us>, "Prado, Carolina" 

<Carolina.Prado@epa.state.oh.us>, "Braun, Paul" <Paul.Braun@epa.state.oh.us>, 

"Leigh.Oesterling@dot.gov" <Leigh.Oesterling@dot.gov>, V Nemalapuri 

<VNemalapuri@mpo.noaca.org>, E Kang <EKang@mpo.noaca.org> Subject RE: MOVES Information/Updates

My opinion is that we should be using the most recent data/networks for the budget revision. 

 

‐          Andy 

 

Andrew J. Reser 

Model Applications Coordinator 

OKI Regional Council of Governments 

720 East Pete Rose Way, Suite 420 

Cincinnati, OH  45202 

(513) 621‐6300 ext. 146 

>>> <Dave.Moore1@dot.state.oh.us> 6/14/2011 10:47 AM >>> 

Per latest planning assumptions regs, ODOT concurs. 

Additionally, ODOT Statewide Planning staff will assist in maintaining a thorough record of MOVES SIP update inputs, by 

area. 

Thanks DM 

>>> <Leigh.Oesterling@dot.gov> 10/5/2011 2:26 PM >>> 
Regional Conformity grace period extended by 12 months to March 2, 2013. 

See message below. . . 

Leigh A. Oesterling, Planning & Environmental Team Leader 

Federal Highway Administration – Ohio Division 

200 N. High Street, Room 328 

Columbus, OH 43215 

(614) 280-6837 

leigh.oesterling@dot.gov 

Please consider the environment before printing this email.

Sent: Wednesday, October 05, 2011 2:19 PM 

Subject: INFORMATION: EPA finalizes MOVES regional grace period extension 

TO THE ATTENTION OF DIVISION AIR QUALITY AND PLANNING STAFF:

The purpose of this email is to inform you that EPA finalizes a conformity rule to extend the grace 

period that provides an additional 12 months before the MOVES model is required for regional 

emissions for transportation conformity determinations. 

On March 2, 2010, EPA approved the MOVES model for regional conformity analysis and established a 

two-year grace period. As a result of the grace period extension, MOVES2010a is not required for new 

regional conformity analysis until March 2, 2013. 

It is important to note that this extension does not affect EPA’s previously established two year grace 

period for the use of MOVES2010a for carbon monoxide and particulate matter hot-spot analyses for 

project level conformity determinations. New hot-spot analyses will be required to use MOVES2010a 

after the end of the grace period on December 20, 2012. 

A copy of the direct final rule and related material is available on EPA’s website: 

http://www.epa.gov/otaq/stateresources/transconf/conf-regs.htm

If you have questions related to this final rule, please contact Cecilia Ho at Cecilia.ho@dot.gov or at 202-

366-9862. 

"Dines, Jennifer" <Jennifer.Dines@epa.state.oh.us> 4/17/2012 9:04 AM >>> 

Hello group, I want to start work on the redesignation of Stark County (Canton‐Massilion nonattainment area)

for the annual and 24‐hour PM2.5 standard. We have not done the MOVES modeling for this area.  It would

essentially be the same process for all the other areas we’ve done recently.  We need the following pollutants

and years with documentation:

PM2.5, SO2, NOx

2005, 2008, 2015, 2025

Who would perform the modeling and who would do the documentation?  And what sort of time would be

needed to complete it? I’m about a week out of having all my documentation, other than mobile numbers,

ready.

This would wrap up all PM2.5 redesignations for the State of Ohio (WOOO HOOO) and it would also eliminate

the need for us to do a special update for the Stark area just for PM2.5.
Thanks, Jen

Jennifer Dines

Manager, State Implementation Plan and Rulemaking Section

Division of Air Pollution Control

Ohio Environmental Protection Agency

Wk (614) 644‐3696

Fax (614) 644‐3681

>>> "Byram, Mark" <Mark.Byram@dot.state.oh.us> 4/17/2012 12:59 PM >>> 

Hi Jennifer:

ODOT Statewide Planning – Modeling & Forecasting Section will be providing the analysis for this.  Nino Brunello

will coordinate with Jeff Dutton and his staff to provide the documentation.  Nino will provide you and the group

with a timeline for completing the work by COB Thursday 4‐17.

Respectfully,

Mark Byram, P.E.

Modeling & Forecasting Section

Office of Statewide Planning

Ohio Department of Transportation

(614)466‐7825

>>> "Brunello, Nino" <Nino.Brunello@dot.state.oh.us> 4/19/2012 11:17 AM >>> 

Jeff,

I completed all of the MOVES modeling, travel demand modeling, and air quality post‐processing for your

region.  The attached spreadsheet has the final pollutant totals.

I also attached the documentation BHJ did for their report that can be used as a template for the SCATS

documentation.  The attached tables, and the tables I sent earlier that were for the Ozone document, should be

enough to do replacement.  All you need to do is revise the narrative parts.  {Make sure to remove the ‘revision

history’ page.}

If you have any questions or if I have left out some information, please let me know.

I am going to respond to Jennifer Dines (and the rest of the group) what I’ve done.  Can you give her an expected

completion time?

Thanks,

Nino

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

Nino Brunello, P.E. 

Modeling & Forecasting Section 

Division of Planning 

Ohio Department of Transportation 

(614) 752-5742
"Brunello, Nino" Nino.Brunello@dot.state.oh.us

Jeff, 

Sorry, but I just noticed that I forgot to add the SO2 totals in the spreadsheet. I’ll update it and resend. It won’t 

take long. 

Nino 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

Nino Brunello, P.E. 

Modeling & Forecasting Section 

Division of Planning 

Ohio Department of Transportation 

(614) 752-5742 

"Brunello, Nino" Nino.Brunello@dot.state.oh.us

The SO2 totals are now in the table, and I also added the annual VMTs since they were reported in the BHJ

document.

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

Nino Brunello, P.E. 

Modeling & Forecasting Section 

Division of Planning 

Ohio Department of Transportation 

(614) 752-5742

From: Dan Slicker 

To: Dave Moore 

Dave, 

 

I can't stand air-quality stuff, whenever I see anything having to do with it, my brain partially shuts down. Until 

today, I didn't realize that we were dealing with two separate air-quality issues. Whenever I see "ozone", 

"PM2.5", "conformity", or "redesignation" my brain files it under "air quality", and I make I note that I'll have to 

send some networks down to Nino and plagiarize an air-quality document in the near future. 

 

So, I have a few questions that need answers, so I can set my priorities. 

 

1. When is the 8-Hour Ozone SIP document due? 

2. When is the PM2.5 Redesignations for Stark County document due? 

3. Do we need to do an interagency consultation for either of these? 

4. Besides the TIP and T-Plan air-quality analyses, are there any other air-quality issues we need to deal with in 

the next 2 years? 

 

Dan Slicker 

Dan,

Responses below.

Thanks
DM

1. When is the 8-Hour Ozone SIP document due? We’ve missed a number of due dates for submitting this 

documentation to OEPA. The most recent date was April 1st. OEPA is ready to move (pun intended) 

on the MOVES based budget SIP revisions. As you know, SCATS’ T-Plan conformity lapse date is 

6/15/13. Conformity for the Plan Update will need to be coordinated with the new 2014-2017 TIP. 

Considering standard review/approval schedules the T-Plan Update and Conformity Determination 

documentation will need to be submitted to US DOT/EPA by 5/1/13. This conformity work needs to be 

MOVES based. So, the SIP revision must be fully approved or have budget adequacy finding in time 

for SCATS’ T-Plan/TIP approval/conformity findings. So backing up some more, OEPA needs a 

minimum 45 days to incorporated SCATS’ results in the SIP revision for submission to US EPA. US EPA 

needs a minimum 90 days to process the revision through the Federal Register process. The 

schedules/dates identified above put us somewhere in the Winter 2012/2013 timeframe. Accordingly, 

there’s still time to accomplish the work, but schedules have a way of slipping. 

Should we even discuss the matter of the new .075 Ozone standard, potential revocation of the

exiting 8‐Hour standard, the matter of Stark attaining the new standard and whether any of the above

matters if the new standard is implemented?

2. When is the PM2.5 Redesignations for Stark County document due? Similar schedules as above. Note, Stark 

County is a PM2.5 nonattainment area for both the 1997 annual and 2006 daily standards. Based on recent 

OEPA streams it appears the intent is for the 1997 and 2006 standard budgets to be exactly the same.

3. Do we need to do an interagency consultation for either of these? Interagency consultation on the current 

Stark County aq SIP efforts is warranted just to make sure everyone is on the same page.

4. Besides the TIP and T-Plan air-quality analyses, are there any other air-quality issues we need to deal with in 

the next 2 years? Once the SIPs are updated, likely just Plan/TIP conformity.

There are two other matters:

• OEPA is updating the “Conformity SIP”.  SCATS may want to review the conformity SIP MOU that was

prepared circa 2008‐2009 to re‐familiarize themselves with this topic.

• Not really air quality SIP/Conformity related, but SCATS should review its current suballcated funds

CMAQ projects to assure they all have affirmative CMAQ eligibility findings.   

"Dines, Jennifer" Jennifer.Dines@epa.state.oh.us

I will offer that the PM2.5 redesignations is listed as one of the top priorities by our director and this is the last 

area to be done. I will also add that if we do not do the redesignation and update mobiles numbers via that 

mechanism we will have to do the same work to update old mobile6 to MOVES numbers for Stark county for 

PM2.5 via the previous attainment SIP. So it has to be done either way. 

I believe Nino completed all the modeling in accordance with all procedures used across the state for all other 

redesignations and all that needs done is the write-up, which he provided a template for. So I don't think it will 

take much effort to complete that piece of the puzzle so the redesignation can move forward quickly. But if this is 

a problem please let me know as I am being asked routinely on the status and will need to be able to provide my 

management with an update. 

Until I crunch the numbers from Nino's modeling I won't be able to have much of a meaningful consultation 

process on that issue. Typically we consult after I incorporate mobile numbers in with all the other pollutant 

sectors to determine our possible safety margin options if budgets are necessary. Then we typically discuss if 

that is agreeable. 

Thanks, 

Jennifer Dines 

Manager, State Implementation Plan and Rulemaking Section 

Division of Air Pollution Control 

Ohio Environmental Protection Agency 

Wk (614) 644-3696 
Fax (614) 644-3681 

>>> Jeffrey Dutton 4/24/2012 9:24 AM >>> 

Good Morning Jennifer, 

 

We plan to have the PM 2.5 analysis report to you by weeks end. 

 

Jef 

 

Jeff Dutton 

SCATS Technical Director 

Stark County Regional Planning Commission 

201 3rd Street NE, Suite 201 

Canton, Ohio 44702 

From: Dan Slicker [mailto:dkslicker@co.stark.oh.us] 

Sent: Friday, April 20, 2012 1:59 PM 

To: Brunello, Nino 

Cc: Jeffrey Dutton 

Subject: Re: FW: FW: PM2.5 Redesignations for Stark County 

Nino, 

 

The BHJ document contains tables for Source Type Population, Vehicle Age Distribution, and Road Type 

Distribution. Do we need to produce similar tables? If so, do you have the necessary data? I can get the roadtype data, but I'll need help with the source types and vehicle ages. 

 

Dan

>>> "Brunello, Nino" <Nino.Brunello@dot.state.oh.us> 4/20/2012 2:32 PM >>> 

The Vehicle Age Distribution and Road Type Distribution tables will be the same as the ones that are in 

the spreadsheet I sent you on the April 2nd for the ozone documentation. Those values are assumed to be 

constant. You just need to change the year on the Age Distribution table. I’ll give you the Source Type 

Pop. What year are you using for your example?

From: Dan Slicker [mailto:dkslicker@co.stark.oh.us] 

Sent: Friday, April 20, 2012 2:40 PM 

To: Brunello, Nino 

Subject: RE: FW: FW: PM2.5 Redesignations for Stark County 

Thanks, 

 

2005 would work. 

 

Dan

"Brunello, Nino" Nino.Brunello@dot.state.oh.us

The 2005 MOVES vehicle population file is attached.
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

Nino Brunello, P.E. 

Modeling & Forecasting Section 

Division of Planning 

Ohio Department of Transportation 

(614) 752-5742

>>> "Dines, Jennifer" <Jennifer.Dines@epa.state.oh.us> 4/26/2012 8:25 AM >>> 

Jeff or Nino, could one of you also take a quick look at the attached summary of how mobile emissions were

derived and provide me with any edits.  It will probably need to be Jeff....I used the OKI write‐up as an example

and SCATS may do a few things differently.  I’ve got my document all ready to go except this last section and the

analysis report.

Thanks again for all your help!

Jennifer Dines

Manager, State Implementation Plan and Rulemaking Section

Division of Air Pollution Control

Ohio Environmental Protection Agency

Wk (614) 644‐3696

Fax (614) 644‐3681

>>> "Brunello, Nino" <Nino.Brunello@dot.state.oh.us> 4/26/2012 8:39 AM >>> 

After a quick scan, there are a lot of changes needed. OKI’s methodology for using MOVES was done 

independent of what was used for the rest of the state. Jeff, let me take a crack at it first, and then I will pass it 

along to you. Okay? 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

Nino Brunello, P.E. 

Modeling & Forecasting Section 

Division of Planning 

Ohio Department of Transportation 

(614) 752-5742 

>>> "Brunello, Nino" <Nino.Brunello@dot.state.oh.us> 4/26/2012 10:44 AM >>> 

Jeff/Dan: 

My updated summary is attached. 

- I corrected all sections where the SCATS model if different from the OKI/MVRPC models. 

- I removed all of the Massillon references; ”Dayton-Springfield” was used because the MPOs have two separate 

models. 

- Please check my usage of SCATS vs. Stark County; I tried to vary it to avoid too much repetition, but I may 

have used them when they may not be interchangeable. 

Dan, please review and update the paragraph that lists the years for which you created complete variable data 

sets. Then you should also replace the parts that describe the variable trends. 

Please let me know if you have any questions about my edits. 

Thanks, 
Nino 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

Nino Brunello, P.E. 

Modeling & Forecasting Section 

Division of Planning 

Ohio Department of Transportation 

(614) 752-5742
Appendix D-1 

LADCO Technical Support 

Document (Supplement, 

Without CAIR Modeling, 

September 12, 2008, FINAL) 

(available at 

http://www.ladco.org/reports/general/) 
Appendix E-1 

Incomplete· Monitoring Data 

Substitution Analysis 
Canton-Massillon PM2.5 Nonattainment Area 

Monitor Missing Data Analysis 

The current Canton-Massillon nonattainment area is located in northeast Ohio and 

includes Stark County. 

The area has two monitors measuring PM2.5 concentrations, which are operated by the 

Air Pollution Control Division of the Canton City Health Department. 

Annual Standard 

A listing of the design values based on the three-year average of the annual mean 

concentrations from 2009 through 2011 is shown in Table 1. The design values 

calculated for the Canton-Massillon area show that the annual PM2.5 NAAQS has been 

attained. 

Table 1 - Monitoring Data for the Canton-Massillon area for 2009 – 2011 

Source: U.S. EPA Air Quality System (AQS); http://www.epa.gov/ttn/airs/airsaqs/index.htm

However, based on Section 107(d)(3)(E)(i) of the Clean Air Act (CAA), the PM2.5

monitoring data has to show that the three-year average of the annual mean values, 

based on data from all monitoring sites in the area or its affected downwind environs, 

are below 15.0 μg/m3

. Moreover, in accordance with the CAA Amendments, three 

complete years of monitoring data are required to demonstrate attainment at a 

monitoring site. In addition, U.S. EPA regulations require at least 75% data capture in 

each quarter of a consecutive 3-year period in order for a design value to be valid. 

Table 1 shows that monitor site 39-151-0017, located at 1330 Dueber Avenue, did not 

comply with the 75% data capture requirement in 2009. Specifically, the first quarter 

(January, February, and March) of 2009 has only 67% capture. 

In order to comply with U.S.EPA 75% capture requirements, Ohio EPA prepared a 

statistical analysis using imputation and subsequent Bootstrap analysis. Missing 

values for site 39-151-0017 were generated and subjected to ordinary analysis as if the 

imputed values were real measurements (this approach is usually better than excluding 

subjects with incomplete data). Most methods for the accounting of incomplete data 

can be complex; the imputation/Bootstrap method prepared by Ohio EPA, however, is a 

relatively simple method to implement, even though the computations can be slow. This 

Average

2009 2010 2011 2009-2011

39‐151‐0017 Stark 13.1 14.4 12.8 13.4

39‐151‐0020 Stark 11.9 13.8 11.3 12.3

Less than 75% capture in at least one quarter

Annual Standard

Site County

Year
is a prod

resampl

Briefly, t

from a r

used to 

monitor 

generate

random 

a pseud

was per

regressi

missing 

set of 1

performe

Imputin

Choice 

monitor(

approxim

having 7

proximity

the sam

monitor.

interest 

Figure 1:

For simp

duct of the 

ing iteration

the imputat

reference m

establish a

and value

e concentra

resampling

do-confiden

rformed by

on analysi

data, follow

1000 slope

ed. 

ng missing 

of referen

(s) in quest

mately 30 

75% or be

y of these m

me or simila

 The locat

located in S

Monitor Loc

plification, w

need to pe

ns were co

tion of miss

monitor with

a mathemat

es in the in

ation values

g of the res

ce interval 

y randomly 

s, then ad

wed by the 

 and interc

data for C

nce monito

tion. Neare

km to the 

etter captur

monitors to

ar air masse

tion of thes

Stark Coun

cations 

we will refer

erform the 

nducted. 

sing values

h a more co

tical relation

ncomplete 

s for missin

siduals from

for the cho

resamplin

dding these

re-calculat

cepts pairs

Canton-Mas

r was initi

est monitors

north, in A

e in all qu

o the Canto

es, and are

se potential

ty, is show

r to site 39-

Bootstrap 

 was perfo

omplete da

nship betwe

data set. 

ng data. Th

m the regres

osen regres

g, with rep

e residuals

tion of the r

s, on which

ssillon PM

ially based

s (39-153-0

Akron, Ohi

arters from

n-Massillon

e thus likely

l reference 

n in Figure 

-151-0017 a

resampling

rmed using

ata record. 

een values

This relati

he Bootstra

ssion analy

ssion mode

placement, 

s to the “b

regression 

h further s

2.5 nonatt

d on the p

0017 and 3

io (Summit

m 2003 to 

n monitors s

y candidate

monitors, 

1. 

as Site A, 3

g many time

g PM2.5 con

 Regressio

s recorded a

onship wa

ap technique

ysis, was us

el. The Boo

the real r

best guess”

constants. 

statistical a

ainment ar

physical p

39-153-002

t County). 

2011, the 

suggests th

es to serve 

as well as 

39-151-002

es. Here, 

ncentration 

on analysis

at the refer

s then use

e, based on

sed to calc

otstrap ana

residuals of

” values of

 The result

analysis ca

rea 

roximity of

3) were loc

 In additio

relatively c

hat they sa

 as a refer

the monito

20 as Site B

1000 

data 

 was 

rence 

ed to 

n the 

ulate 

alysis 

f the 

f the 

t is a 

n be 

f the 

cated 

on to 

close 

mple 

rence 

ors of 

B, 
39-153-0017 as Site C, and 39-153-0023 as Site D. It should be noted here that the 

second monitor in Canton, 39-151-0020, was not considered as a reference due to a 

lack of sufficient data in certain quarters of earlier years used in this analysis (Table 3). 

1. Canton-Massillon Annual Design Value History 

Table 2 – Historic Design Values for Stark and Summit Counties, 2003 to 2010 

From Table 2, both monitors in Stark County have design values that meet the PM2.5

annual standard since the 2006-2008 period. However, Site A has not proven clean 

data in 2009, and therefore it makes the entire nonattainment area ineligible for redesignation based on the 2009-2011 period. As mentioned previously, the lack of clean 

data in 2009 is due to the low percentage (67%) of data capture in the first quarter of 

2009. 

The imputation and Bootstrapping procedures will generate the necessary missing data 

to provide a re-calculated 2009-2011 design value for Site A. 

2. Correlation, Quarterly Data Capture, and Data Site Pairing 

Although location is a critical factor in determining the suitability of a monitor to serve as 

a reference for missing data imputation, a more rigorous statistical analysis was 

necessary to differentiate between Site C and Site D. To this end, three analyses were 

performed. Firstly, a linear regression of the reference monitor to Site A was performed. 

In a linear regression, the relationship between a dependent variable (Site A data), Y, 

and an independent variable, X (Site C or D data), is assessed. The familiar straight 

line regression model, Y = mX + b was used here. Under this model, linear regression 

finds the straight line that minimizes the sum-of-squares differences between the line 

and the Y data. The purpose of the regression analysis was to determine the degree of 

correlation between Site A and Site C and D. The statistic of interest, R2

, describes the 

degree of relationship between two variables1

 (variables or site concentrations in Site A 

and C and D). R2 is only a descriptive statistics. Roughly speaking, we associate a 

high value of R2

 with a good fit of the regression line and associate a low value of R2

with a poor fit. 

Secondly, the mean of the quarterly data captured (the mean of the percentage 

captured) allowed the central tendency of each site to be verified, providing a second 

 

1 An R2 value of 0.0 means that knowing X does not help to predict Y, there is no linear relationship 

between X and Y. When R2 equals 1.0, all points lie exactly on a straight line with no scatter; knowing X 

predicts Y perfectly. 

1999‐2001 2000‐2002 2001‐2003 2002‐2004 2003‐2005 2004‐2006 2005‐2007 2006‐2008 2007‐2009 2008‐2010 2009‐2011

39‐151‐0017 A Stark 18.3 18.0 17.3 16.6 16.7 16.0 16.1 14.8 14.3 13.8 13.4

39‐151‐0020 B Stark 16.9 16.4 15.8 15.0 15.2 14.2 14.3 12.9 12.9 12.7 12.3

39‐153‐0017 C Summit 17.4 17.0 16.6 15.7 15.6 15.0 14.9 14.0 13.7 13.3 12.6

39‐153‐0023 D Summit 16.2 16.3 15.6 15.0 14.6 14.1 14.1 13.1 12.7 12.3 11.7

Less than 75% capture in at least one quarter

Violating Design Value

Site ID County Site

Annual Design Value
means of determining what site (C or D) has a more complete data record from which to 

impute data for Site A. 

Finally, although not as statistically significant as the correlation or mean of the 

percentage captured, pairing the site data seeks to reduce variability between data sets. 

Particular focus was placed on 2009-2011, the period for which the redesignation 

request is based upon and the period in which Site A demonstrated less than 75% 

capture in the first quarter of 2009. 

Below are the results for Site A vs. C and for Site A vs. D. 

Figure 2: Linear Regression: Site A vs. Site C: 

y = 0.9721x + 1.2388

R2 = 0.8753

0

10

20

30

40

50

60

0 10 20 30 40 50 60

Site A Concentration (

μg m-3)

Site C Concentration (μg m-3)

Site A vs. Site C

Linear Regression

ANOVA

df SS MS F Significance F

Regression 1 62478.3728 62478.37 9180.234 0

Residual 1308 8901.920173 6.805749

Total 1309 71380.29298

CoefficientsStandard Error t Stat P‐value Lower 95% Upper 95% Lower 95.0% Upper 95.0%

Intercept 1.23884 0.155837522 7.949532 4.02E‐15 0.933116533 1.54455418 0.933116533 1.544554181

X Variable 1 0.97209 0.01014561 95.81354 0 0.95218335 0.99199025 0.95218335 0.991990246

Regression Statistics

Multiple R 0.935568718

R Square 0.875288826

Adjusted R

Square 0.875193481

Standard Error 2.60878312

Observations 1310
Figure 3: Linear Regression: Site A vs. Site D: 

y = 0.9941x + 1.8143

R2 = 0.8807

0

10

20

30

40

50

60

0 10 20 30 40 50 60

Site A Concentration (

μg m-3)

Site D Concentration (μg m-3)

Site A vs Site D

Linear Regression

ANOVA

df SS MS F Significance F

Regression 1 42723.00423 42723 5981.858 0

Residual 810 5785.097836 7.1421

Total 811 48508.10207

Coefficients Standard Error t Stat P‐value Lower 95% Upper 95% Lower 95.0% Upper 95.0%

Intercept 1.8142945 0.193758463 9.3637 7.42E‐20 1.43396659 2.19462241 1.43396659 2.19462241

X Variable 1 0.99412681 0.012853569 77.342 0 0.968896579 1.01935704 0.968896579 1.019357044

Regression Statistics

Multiple R 0.938477

R Square 0.88074

Adjusted R

Square 0.880592

Standard Error 2.67247

Observations 812
Table 3: Quarterly Data Capture 

A B CD

2003Q1 93% 87% 86% 90%

2003Q2 97% 97% 89% 88%

2003Q3 90% 90% 91% 91%

2003Q4 87% 97% 90% 97%

2004Q1 87% 87% 98% 84%

2004Q2 93% 90% 92% 92%

2004Q3 97% 90% 96% 99%

2004Q4 70% 73% 98% 97%

2005Q1 80% 83% 92% 80%

2005Q2 84% 90% 94% 100%

2005Q3 93% 90% 100% 100%

2005Q4 87% 77% 90% 94%

2006Q1 93% 97% 100% 100%

2006Q2 90% 83% 100% 93%

2006Q3 97% 23% 100% 90%

2006Q4 90% 100% 97% 97%

2007Q1 97% 93% 97% 100%

2007Q2 93% 93% 100% 100%

2007Q3 74% 58% 100% 97%

2007Q4 30% 30% 87% 93%

2008Q1 0% 0% 87% 97%

2008Q2 40% 53% 100% 90%

2008Q3 84% 71% 100% 94%

2008Q4 97% 90% 100% 93%

2009Q1 67% 87% 77% 93%

2009Q2 91% 84% 97% 90%

2009Q3 99% 90% 91% 97%

2009Q4 93% 90% 100% 94%

2010Q1 84% 97% 99% 90%

2010Q2 88% 77% 100% 90%

2010Q3 96% 97% 100% 97%

2010Q4 96% 97% 100% 84%

2011Q1 97% 97% 91% 100%

2011Q2 96% 97% 93% 93%

2011Q3 84% 87% 100% 90%

2011Q4 92% 97% 100% 100%

MEAN 84% 82% 95% 94%

MEAN: 2009‐2011 90% 91% 96% 93%

Quarterly Data Capture 2003‐2011

Monitoring Sites
Table 4: Paired Data by Site and Quarter 

The R2

 value of the linear regression for Site A and Site C is 0.8753, and the R2 value 

for Site A and Site D is 0.8807. Thus, the linear relationship between Site A and Site D 

is stronger than that of Site A and C, although this difference is marginal. By 

examination of the mean quarterly data capture (Table 3), in particular between 2009 

and 2011, Site C demonstrates 96% data capture, and Site D 93% data capture. Lastly, 

Table 4 shows that significantly more data pairings occurred between Site A and Site C 

(1319 pairings) than the number of pairings between Sites A and D (809). 

Based on the three statistical categories used to determine the reference monitor, Site 

C provided more data pairings, as well as a more complete data record, in particular 

over the 2009 to 2011 period. Although the R2

 value of Site A vs Site C was somewhat 

smaller than that of Site A and Site D, this difference was considered negligible, and 

Site C was used as the reference monitor in the data imputation procedure. However, 

due to the greater R2 value between Site A and Site D, the data imputation procedure 

and Bootstrap was also performed using Site D as a reference, for the purposes of 

comparison and completeness. 

3. Data Imputation and Bootstrap Analysis 

Data imputation was conducted using the mathematical relationship established by the 

linear regression procedure between Site A and Site C, which takes the form: 

Y = mX + b 

where m is the slope, X the value recorded at the reference monitor, and b the intercept. 

For the imputation of missing values at Site A, m = 0.9721 and b = 1.2388. After 

applying the above equation to all missing data in Site A, we recalculated the design 

values based on the three-year average of the annual mean concentrations for all 

existing years in Site A (Site 39-151-0017). Table 5 shows Site 39-151-0017 before and 

after the imputation of missing data. It should be noted that both before and after 

inclusion of the imputed data, Site A demonstrated a passing design value for the 2009-

2011 period (13.4 and 13.5, respectively). 

Table 5: Annual Design Values Before and After Imputation 

SITE Pairs Q1 Pairs Q2 Pairs Q3 Pairs Q4 Total

A vs C 308 324 355 332 1319

A vs D 178 215 211 205 809

All Quarters, 2003‐2011

Site ID County 2003 2004 2005 2006 2007 2008 2009 2010 2011 '03-'05 '04-'06 '05-'07 '06-'08 07-'09 '08-'10 '09-'11

OLD 39-151-0017 Stark 16.8 15.5 17.8 14.6 15.9 13.9 13.1 14.4 12.8 16.7 16.0 16.1 14.8 14.3 13.8 13.4

NEW 39-151-0017 Stark 16.8 15.2 17.8 14.6 15.4 14.2 13.2 14.4 12.8 16.6 15.9 15.9 14.7 14.3 13.9 13.5

Incomple data (quarter with <75% data capture)

Year Annual Design Value
As state

referenc

annual a

15.3, 14

Site C (1

To prov

average

mean, s

(b) used

Bootstra

adds th

calculate

Bootstra

pseudointercep

respectiv

Figure 4:

Fig

are

ed previous

ce monitor 

averages u

4.3, and 13

15.2, 15.4, 

vide a mea

e design va

standard de

d to genera

ap analysis 

hose resam

es a new

apped slope

-confidence

t from the B

vely. 

Distribution

gure 4: Histog

ea represents

ly, the impu

for the sak

using imput

.0, respecti

14.2, and 1

asure of co

lues, a Boo

eviation, an

ate the rep

randomly 

mpled resi

w slope an

e and interc

e interval c

Bootstrap a

n of Slope Va

gram of the slo

s the 95% con

utation proc

ke of comp

ted data w

ively. Thes

13.2) as the

onfidence i

otstrap ana

nd 95% con

placement d

resamples 

duals to t

nd intercep

cept values

can be de

analysis of 

alues 

ope values fro

nfidence inter

cedure was

parison. Fo

ith Site D a

se values a

e reference

n the impu

alysis was c

nfidence int

data values

the real re

the impute

pt at each

s were calc

termined. 

Site A vs S

om a 1000 ite

rval.

s also cond

or 2004, 20

as the refe

are very sim

, as shown 

uted data a

conducted. 

terval for th

s at Site A

siduals from

ed data v

h iteration

culated, from

 The distr

Site C are s

eration Bootst

ducted usin

007, 2008,

erence mon

milar to thos

 in Table 5

as well as 

 This anal

he slope (m

A. As deta

m the regre

alues, and

. Thus, 

m which a 

ribution of 

shown in Fi

trap analysis.

ng Site D as

 and 2009

nitor were 

se imputed

. 

the threelysis provid

m) and inter

ailed above

ession anal

d subsequ

1000 pair

mean and 

the slope 

igures 4 an

. The shaded

s the 

9, the 

15.1, 

 with 

-year 

ded a 

rcept 

, the 

lysis, 

ently 

rs of 

95% 

and 

nd 5, 

d
Figure 5:

The res

Bootstra

imputati

the accu

using th

design v

This ana

Table 6: I

Lower

Imputed

Upper

From Ta

replace 

Fig

sha

Distribution

ultant mea

ap analysis

on perform

uracy of th

e upper an

values for a

alysis is sum

Imputed Qua

20

Q

r 95% 13

d Value 13

r 95% 13

able 6, it ca

missing va

gure 5: Histog

aded area rep

n of Intercept

n of the slo

s compare 

med at Site 

e regressio

d lower bou

all quarters 

mmarized in

arter Average

Qua

004

Q4

2007

Q3

3.26 18.20

3.4 18.4

3.56 18.55

an be shown

lues at Site

gram of the in

presents the 9

t Values 

ope, mboot

favorably 

A, m = 0.9

on model u

unds of the

in which Si

n Table 6.

es with Uppe

rter with <75

2007

Q4

13.43

13.8

14.08

n that in ea

e A, the qua

tercept value

95% confiden

= 0.9722, a

to those 

9721 and b

used to imp

e 95% confi

ite A demo

er and Lower

5% Data Captu

2008

Q1

20

Q

15.68 12

16.3 12

16.91 12

ach quarter 

arterly avera

s from a 1000

nce interval.

and interce

values ac

b = 1.2388.

pute missin

dence inter

nstrated les

r 95% Confid

ure

008

Q2

2009

Q1

2.08 15.27

2.4 15.4

2.70 15.49

for which i

age was we

0 iteration Bo

ept, bboot = 

ctually used

. Additiona

ng data can

rval to calcu

ss than 75%

dence Values

9

7

4

9

mputed da

ell within th

ootstrap analy

1.240 from

d for the 

al confidenc

n be gaine

ulate a rang

% data cap

s

ta were use

he 95% pse

ysis. The 

m the 

data 

ce in 

ed by 

ge of 

pture. 

ed to 

eudo-
confidence interval resulting from the 1000 iteration Bootstrap analysis. This suggests 

that the slope and intercept used to generate the imputed values are representative of 

the relationship between Site A and Site C, and therefore suitable for generating 

replacements for missing data values. It should be stated that, even when using the 

calculated upper boundary for all quarters in the 2009-2011 period, the three year 

design value for this period is 13.9, and therefore still passing the annual PM2.5 NAAQS 

of 15.0 μg m-3. 

In summary, the PM2.5 three-year average design value from 2009-2011 for monitor 39-

151-0017 prior to the inclusion of imputed data was 13.4. Although this value was 

below the annual standard, the lack of clean data in the first quarter of 2009 made this 

value invalid. Therefore, an imputation and Bootstrap analysis was performed to 

replace missing values with valid numbers to achieve the 75% capture criteria. 

Incorporating these imputed values, a new design value of 13.5 for the 2009-2011 

period was calculated. New design values for both Stark County monitors are 

summarized in Table 7. 

Table 7: Historic Design Values and Imputed Design Values, 1999-2011 

 

24-hour Standard 

The 24-hour PM2.5 standard is calculated as the three-year average of annual 98th

percentile 24-hour average values, recorded at each monitor. As with the annual 

standard, U.S. EPA regulations require at least 75% data capture in each quarter of a 

consecutive 3-year period in order for the 24-hour standard to be valid, and, as with the 

annual standard, monitor 39-151-0017(Site A) did not meet this criteria due to a quarter 

of less than 75% capture in 2009. Using the same method described above to generate 

imputed values for the missing data at Site A, a new 24-hour design value was 

calculated. Table 8 shows the historic record of 24-hour design values for both PM2.5

monitors located in Stark County. 

1999-2001 2000-2002 2001-2003 2002-2004 2003-2005 2004-2006 2005-2007 2006-2008 2007-2009 2008-2010 2009-2011

39-151-0017 Stark 18.3 18.0 17.3 16.6 16.7 16.0 16.1 14.8 14.3 13.8 13.4

39-151-0020 16.9 16.4 15.8 15.0 15.2 14.2 14.3 12.9 12.9 12.7 12.3

incomplete data (quarter with <75% capture)

violating DV

1999-2001 2000-2002 2001-2003 2002-2004 2003-2005 2004-2006 2005-2007 2006-2008 2007-2009 2008-2010 2009-2011

39-151-0017 Stark 18.3 18.0 17.3 16.5 16.6 15.9 15.9 14.7 14.3 13.9 13.5

39-151-0020 16.9 16.4 15.8 14.9 15.2 14.5 14.6 13.5 13.2 13.0 12.3

Imputed data substituted to compensate for <75% capture

violating DV

Site County Annual Design Values

Site County New Annual Design Values Using Imputed Data
Table 8: Stark County 24-hour Design Values 

For the 2009-2011 period, monitor 39-151-0020 demonstrates 75% or better data 

capture, and a valid, passing design value of 28. Monitor 39-151-0017, however, 

demonstrates an in-valid, passing design value of 30 for this same period of record. 

Using the same data set with imputed values for missing data at Site A derived from 

reference monitor 39-153-0017 (Site C) from which the annual design values were 

calculated, new annual 98th percentile values and three-year averages were also 

calculated from 2003 to 2011. These data are summarized in Table 9. 

Table 9: Monitor 39-151-0017 24-hour Design Values with Imputed Data 

 

Inclusion of imputed data significantly increased the number of creditable samples for 

each year in which monitor 39-151-0017 did not have sufficient data to meet the 75% 

data capture criteria, but this did not have a significant impact on the annual 98th

percentile values or the three-year averages. With imputed data, monitor 39-151-0017 

demonstrates a passing value of 30 for the 2009-2011 period, with sufficient data to 

meet the 75% capture criteria. 

39‐151‐17 2003 2004 2005 2006 2007 2008 2009 2010 2011

Creditable Samples 111 106 111 111 89 67 320 111 336 2003‐2005 2004‐2006 2005‐2007 2006‐2008 2007‐2009 2008‐2010 2009‐2011

98th Percentile 34.2 36.3 47.6 32.2 33.4 37.9 30 33 28.1 39 39 38 35 34 34 30

39‐151‐20 2003 2004 2005 2006 2007 2008 2009 2010 2011

Creditable Samples 112 104 104 92 83 65 107 112 114 2003‐2005 2004‐2006 2005‐2007 2006‐2008 2007‐2009 2008‐2010 2009‐2011

98th Percentile 34.5 32.8 39.3 26.1 32.8 29.8 27.5 32.2 23.1 36 33 33 30 30 30 28

<75% data capture in a least one quarter

Year

24‐hour Design Value

24‐hour Design Value

39‐151‐17OLD 2003 2004 2005 2006 2007 2008 2009 2010 2011

Creditable Samples 111 106 111 111 89 67 320 111 336 2003‐2005 2004‐2006 2005‐2007 2006‐2008 2007‐2009 2008‐2010 2009‐2011

98th Percentile 34.2 36.3 47.6 32.2 33.4 37.9 30 33 28.1 39 39 38 35 34 34 30

39‐151‐17NEW 2003 2004 2005 2006 2007 2008 2009 2010 2011

Creditable Samples 111 122 111 111 113 119 334 111 336 2003‐2005 2004‐2006 2005‐2007 2006‐2008 2007‐2009 2008‐2010 2009‐2011

98th Percentile 34.2 36.3 47.6 32.2 33.4 38.1 30.3 33 28.1 39 39 38 35 34 34 30

<75% data capture in a least one quarter

Year includes one or more quarters with imputed values

Year

24‐hour Design Value

24‐hour Design Value
Appendix F-1 

Public Notice 
Public Notice 

Ohio Environmental Protection Agency 

Redesignation and Maintenance Plan for the Canton-Massillon, OH Annual and 

24-Hour PM 2.5 Standards 

Stark County, Ohio 

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 Canton-Massillon area (Stark 

County), to attainment with respect to the 1997 annual and the 2006 24-Hour PM2.5 

national ambient air quality standards (NAAQS). Air quality monitoring data collected 

between 2009 and 2011 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 

and 2006 24-Hour PM2.5 standards 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 Canton-Massillon 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 Canton-Massillon area in the future. 

The Canton-Massillon area is currently designated as nonattainment for the 1997 

annual and 2006 24-Hour PM2.5 standard. As part of an acceptable maintenance plan, 

Ohio EPA has developed, as required, a contingency plan to provide for additional 

emission reductions if a violation of the NAAQS is monitored after the area has been 

redesignated. 

The State of Ohio proposes to: 

1. Request the U.S. EPA redesignate the Canton-Massillon area to attainment with 

respect to the 1997 annual and 24-Hour 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 June 6, 2012 at the following address: 

E-mail: erica.fetty@epa.state.oh.us

Mailing address: Erica Fetty 

Ohio Environmental Protection Agency, DAPC 

Lazarus Government Center 

P.O. Box 1049 

Columbus, Ohio 43216-1049 

Phone: (614) 644-2310 

Pursuant to Section 119.03 of the Ohio Revised Code, a public hearing on this 

redesignation request will be conducted as follows: Wednesday June 6, 2012 at 

2:30PM, at Stark Co Library, Sandy Valley Branch, 9754 Cleveland Avenue SE 

Magnolia, OH 44643. 

All interested persons are entitled to attend or be represented at the hearing 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 June 6,2012 will be considered by Ohio EPA prior to final 

action on this redesignation. Written statements submitted after June 6, 2012 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 or at 

http://www.epa.ohio.gov/dapc/SIP/2006.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 Erica Fetty at (614) 644-2310, 

Erica.Fetty@epa.state.oh.us or mailed to Erica Fetty at the above address. 
(216) 696-2272

FINCUN-MANCINI -- THE COURT REPORTERS

Page 1

1 OHIO ENVIRONMENTAL PROTECTION AGENCY

 PUBLIC HEARING

2 

3 

4 - - - - - - - - - - - - - - -:

 :

5 In Re: :

 :

6 Ohio EPA Requests : 

Recognition of Improved Air : 

7 Quality in Northeast Ohio :

 :

8 - - - - - - - - - - - - - - -:

9

10

11 Transcript of proceedings 

12 held before the Ohio Environmental Protection 

13 Agency, at the Stark County Library, Sandy Valley 

14 Branch, 9734 Cleveland Avenue., S.E., Magnolia, Ohio 

15 44643, on June 6, 2012, commencing at 2:30 p.m.

16

17

18 APPEARANCES:

19 Mary McCarron, Ohio EPA Public Interest Center 

20 Paul Braun, Ohio EPA, Division of Air Quality

21 Heidi Griesmer, Ohio EPA, Division of Air 

 Quality

22 

23

24

25
(216) 696-2272

FINCUN-MANCINI -- THE COURT REPORTERS

Page 2

1 PROCEEDINGS

2 MS. McCARRON: My name is Mary 

3 McCarron. Thank you for taking the time to 

4 come to the hearing today. I'm a public 

5 information officer at Ohio EPA. 

6 The State of Ohio plans to ask the 

7 U.S. EPA to officially recognize that air 

8 quality in the Canton-Massillon area meets the 

9 1997 annual and the 2006 24-hour federal fine 

10 particulates standards.

11 The proposed redesignation request 

12 affects Stark County.

13 Comments can be submitted until the 

14 close of business today, June 6, 2012. You 

15 may email comments to Erika Fetty. 

16 fetty@epa.ohio.gov. 

17 All interested persons are entitled to 

18 attend or be represented, and to present oral 

19 and/or written comments concerning the 

20 proposed action. All written and oral 

21 comments received as part of the official 

22 record will be considered by the Director of 

23 Ohio EPA before a final decision is made.

24 If you wish to present testimony at 

25 this hearing, I will call you up in the order 
(216) 696-2272

FINCUN-MANCINI -- THE COURT REPORTERS

Page 3

1 that you signed in and if you do not want to 

2 provide testimony go ahead and say, "pass".

3 There is no cross-examination of 

4 speakers or representative of Ohio EPA in 

5 public hearings such as this. Ohio EPA 

6 hearings provide citizens the opportunity to 

7 submit comments on the official record. 

8 Therefore, we will not be able to answer any 

9 questions during the hearing. However, Ohio 

10 EPA staff may ask clarifying questions of the 

11 person testifying to ensure the record is as 

12 complete as possible.

13 I will go ahead and read the names of 

14 those who have registered. Bob -- 

15 MR. NAU: Nau.

16 MS. McCARRON: What is it?

17 MR. NAU: Nau. 

18 MS. McCARRON: Can you state your 

19 name, spell it for the court reporter and then 

20 proceed with your testimony?

21 MR. NAU: My name is Bob Nau, 

22 N-a-u. I'm the Executive Director of the 

23 Stark County Regional Planning Commission and 

24 the Stark County Area Transportation Study, 

25 which is the local metropolitan planning 
(216) 696-2272

FINCUN-MANCINI -- THE COURT REPORTERS

Page 4

1 organization for purposes of transportation 

2 planning. I'm here to support the Ohio EPA's 

3 request to ask the U.S. EPA to recognize that 

4 air quality in the Canton-Massillon area meets 

5 the 1997 annual and the 2006 24-hour federal 

6 fine particulates standards and to support 

7 that request that is important to Stark 

8 County, not only from a transportation 

9 planning standpoint, but also to promote 

10 economic development and the health, safety 

11 and welfare of our residence.

12 MS. McCARRON: Thank you.

13 Karl Lucas.

14 MR. LUCAS: I can pass. 

15 MS. McCARRON: Okay. At this time, 

16 there is nobody else present to provide 

17 testimony so we will go off the record until 

18 3:00 p.m.

19 (Recess taken.)

20 MS. McCARRON: We are back on the 

21 record.

22 The time is now 3:00 p.m. And we will 

23 close the hearing.

24 (Hearing concluded at 3:00 p.m.)

25 - - -
(216) 696-2272

FINCUN-MANCINI -- THE COURT REPORTERS

Page 5

1 State of Ohio, )

 ) SS:

2 County of Cuyahoga. ) 

3

4 C E R T I F I C A T E

5 This certifies that the foregoing is a true

6 and correct transcript of the proceedings had 

7 before the State of Ohio, Environmental 

8 Protection Agency, at the Stark County

9 Library, Sandy Valley Branch, 9734 Cleveland 

10 Avenue, S.E., Magnolia, Ohio 44643, on 

11 Wednesday, May 6, 2012, commencing at

12 2:30 p.m. 

13 In Re:

14 Ohio EPA Requests 

 Recognition of Improved Air 

15 Quality in Northeast Ohio. 

16

17

18

19 ___________________________

 COURT REPORTER

20

 FINCUN-MANCINI COURT REPORTERS

21 1801 East Ninth Street

 Suite 1720

22 Cleveland, Ohio 44114

 (216) 696-2272

23 (216) 696-2275 FAX 

24

25
Division of Air Pollution Control 

Response to Comments 

Redesignation Request and Maintenance Plan for the 1997 Annual and 2006 

24-Hour Standards for the Canton-Massillon Area 

Agency Contact for this Package

Division Contact: (Erica Fetty, Division of Air Pollution Control, 614-644-2310, 

Erica.Fetty@epa.state.oh.us) 

Ohio EPA held a public hearing in Magnolia, OH on June 6, 2012, regarding the 

Redesignation Request and Maintenance Plan for the Canton-Massillon Annual and 24-

Hour 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 June 6, 2012. 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 oral testimony from the Stark County Regional Planning 

Commission and the Stark County Area Transportation Study in support of the 

redesignation request. In addition, Ohio EPA received written comments from 

Shumaker, Loop & Kendrick, LLP in support of the redesignation for the CantonMassillon Annual and 24-Hour PM2.5 Nonattainment Area. These testimonies can be 

found in this submittal.