# Appendix A-1 Air Quality System (AQS) DataUNITED STATES ENVIRONMENTAL PROTECTION AGENCY

QUICKLOOK CRITERIA PARAMETERS

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

Selection Criteria Page 1 User ID: IDA

State County City

Site Parameter POC 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 2006Apr. 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 EXCLUDEDApr. 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

MEANApr. 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 REPORTApr. 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 letterEnvironmental 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 Discussion1 

## 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 20082 

## Table of Contents

Section Page

Introduc tion ................................................................................................. 3

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

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

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

4.0 On Road Sources.......

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

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

Table
2-1 Categories included in the 2005 area source Inventory.............................8 2-2 Emission Factors used for Wood Bu rners included in area sources............11 3-1 NMIM NCD Tables for Specific Years and States ........................................... 16 4-1 Federal Functional Class Categories............................................................ 23 4-2 DVMT Summary by County

.................................................................. . 24 4-3 Speed by Federal Functional Class ............................................................. 28 4-4 Link Group Codes & Associated BPR Curves

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

. Figure

1............................... ......... Speed Comparison Graphs.....................................273 

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

Introduction

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

• Annual Standard = 15.0 ug/m3
The Clean Air Act Amendments (CAA A) requires all states to revise and submit State Implementation Plans (SIP) for areas which are classified as non-atta inment of the 1997 Fine Particle (PM 2
. 5 ) National Ambient Air Quality St andards (NAAQS). The Federal Register ( Vol. 72, No. 79/ Wednesday, April 25, 2007) provides the emissions inventory rules and regulations for the PM 2
. 5 Clean Air Fine Particle implementation rule. An electronic version of the document can be found at http://www.epa.gov/fedrgstr/EPAAIR/2007/April/Day-25/a6347.pdf.
As part of the designation of non-attainment areas for PM 2
. 5 standards, a new attainment demonstration SIP will be necessary. A key el ement in the overall SIP planning process is the need for an updated emissions inventory. This document presents the 2005 Base Year Pa rticulate SIP Emissions Inv entory for Ohio as required by the CAAA. It includes emissions for poi nt, area, on-road mobi le and non-road mobile for the State of Ohio.

This technical report document s the procedures and the me thodologies that were used in the development of daily emissions for all counties in Ohio. This report describes the following:

1. Identification of st ationary and mobile sources included in the inventory; 2. Sources of data, and data collecti on methods used in the development of the inventory; 3. Methods and procedures used to estimate emissions; and 4. Assumptions considered in t he development of the emissions inventories.
The intent of this report is to descri be how the inventory was prepared, and what information was considered in the inventory development.

This document is comprised of 5 sections , one section for each inventory type. The biogenic inventory is not being discussed in this document because Ohio EPA did not participate in the generation of this inventory. Lake Michigan Air Directors Consortium (LADCO) ran EPA’s BEIS model in the Em ission Modeling System (EMS) to generate Summer Weekday emissions for VOC and NOx.4 

### SECTION 1

POINT SOURCES

Emissions and source specific data for point sources are collected for the 2005 baseyear SIP inventory by the Ohio Envir onmental Protection Agency (Ohio EPA.) The primary source of data for point sources is facility reported STARShip files. STARShip is a software package developed by Ohio EPA, Division of Ai r Pollution Control (DAPC), to assist the regulated community in prepar ing and submitting a variety of electronic permit applications and reports to the DAPC . These data are reported by the Title V facilities annually as part of the emission s fee/inventory process conducted by Ohio EPA and include emissions, process rates, oper ating schedules, emissions control data and other relevant information.
The STARShip files are electr onically transferred to the DAPC and stored into the Division’s Oracle database, STARS. The f iles are reviewed by the local air agencies and Ohio EPA district and central office staff. After review, the data are imported into Excel and linked with an Access® database to further process the information into the federally approved National Em ission Inventory (NEI) database format in version 3.0. The files are quality assured ag ain using the United States Environmental Protection Agency’s (U.S.EPA) QA/QC so ftware for format and content. The data is finally submitted to LADCO for emissions processi ng through the Emissions Modeling System. The State provided inv entory for Electric Generating Un its (EGU) is replaced with the Federal EGU inventory. T he EGU inventory is compiled by U.S. EPA’s Acid Rain Program. It is based on facility report ed emissions as meas ured by continuous emissions monitors. In conclusion, the final point source inventory is a hybrid of the federal EGU inventory and the state provided non-EGU units.

A major distinction typically made in emissi ons inventories is t hat between point and area sources. In this invent ory, point sources are sources for which individual records are maintained for that source. Such records are maintained for all Ohio Title V facilities (706 facilities statewide). The area source inventory accounts for facilities from nonTitle V facilities and calculates emissions information using surrogate emissions factors based on energy usage, population, employment records, or other reliable data. A more detailed discussion of t he area source inventory is pr ovided in Section 2. The point source inventory descr ibed herein is considered to be the most current and accurate source of emissions data available for 2005.

1.1 Point Source Process Emissions Ohio EPA defines point source process emissions as those which occur at an identifiable Title V stationary stack or vent. Point source emissions not emitted from discrete stacks or vents are termed fugitive emissions and are discussed in Section 1.2.5 1.1.1 Source Identificati on and Data Collection The sources to be included in the 2005 base year inventory are identified using the Title V STARS database. Facility production and emissions data are included in this database. This information is fac ility-reported actual 2005 emissions.

1.1.2 Non-reactive VOC Emissions Adjustments This section is primarily appl icable for VOC pollutants. S ources are required to identify emissions of photochemically non-reactive Volatile Organic Compounds (VOC.) Based upon this information, those emissions have been specifically excl uded from the 2005 base line inventory in accordance with U.S. EPA’s “Recommended Policy on the Control of Volatile Organic Co mpounds.” A complete list 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 ((CF 3 ) 2 CFCF 2 OCH 3 )

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

• Perchloroethylene

• Cyclic, branched or linear completely methylated siloxanes

• Methyl acetate

• Volatile methyl siloxanes

• Acetone

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

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

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

. U.S. Environmental Protecti on Agency, Research Triangle Park, NC, September 1985.7 Preparing 2002 Regional PM2.5 Emissions QAQPS PM Inventory Conference Inventory Conference San Diego, 2003.

Documentation for the 2002 El ectric Generating Unit Nati onal Emissions Inventory (NEI) . Eastern research group, Inc., 1600 Peri meter Park Drive, Morrisville, NC 27560 and E.H. Pechan and Associates, Inc., 5528–B Hempstead Way8 

### SECTION 2

AREA SOURCES

Area sources are sources which are typically small, indivi dual, 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 usi ng one methodology. Since area sources are traditionally defined at the county level, most methods are designed to estimate area source emissions at the county level.

Ohio EPA has either used published Emission Inventory Improvement Program (EIIP) 6 methodologies or selected other methodologies which are shared by other states. The decision of which methodology to use was lar gely based on Ohio’s data availability. Data which was not available on a county-lev el is estimated by assigning a percentage of the state’s total activity to each county based on the state’s popul ation or employment information. If Ohio county specific activity data is available throu gh Ohio EPA or other State Agencies, that data is us ed rather than allocating acti vity by percentage. Table 2-1 lists the sources which emit PM 2.5 , NO x and SO 2 along with the respective EFs used to calculate each pollutant.

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

Area Source NO x PM 2.5 SO 2 Section Commercial Natural Gas Combustion 94 lb/MMSCF 7.6 lb/MMSCF 0.6 lb/MMSCF 2.1
Industrial Distillate Oil Combustion 20 lb/E3gal fuel 0.25 lb/E3gal fuel 42.6 lb/E3gal fuel 2.2
Industrial Residual Oil Combustion 55 lb/E3gal fuel 4.67 lb/E3gal fuel 157 lb/E3gal fuel 2.2
Industrial Natural Gas Combustion 94 lb/MMSCF 7.6 lb/MMSCF 0.6 lb/MMSCF 2.2
Residential Coal Combustion 9.1 Lb/Ton Coal 3.8 Lb/Ton Coal 31 Lb/Ton Coal 2.3
Residential Distillate Oil Combustion 18 lb/E3gal fuel 0.83 lb/E3gal fuel 42.6 lb/E3gal fuel 2.3
Residential Natural Gas Combustion 94 lb/MMSCF 7.6 lb/MMSCF 0.6 lb/MMSCF 2.3
Residential LPG Combustion 13 lb/E3gal fuel 0.17 lb/E3gal fuel 0.1 lb/E3gal fuel 2.3

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

Structure Fires 1.4 Lb/Ton burned 10.8 Lb/Ton burned NA 2.5
Outdoor Wood Boilers 2.8 Lb/Ton 2.76E+1 Lb/Ton 4 E-1 Lb/Ton 2.69 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 population 4 . Emissions factors are given in table 2-1. The area source emissions are calculated ba sed on an adjusted value by subtracting the emissions due to point sources.

2.2 Industrial Fuel Combustion

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

. The area source NO X emissions are calculated and adjusted by subtracting the emissions due to point source s. A heating value of 140 MMBTU/1000 Gal is used and 84,408 thousand gallons are consumed in 2005. [MMBTU stand for Million British Thermal Units]. Emissions fact ors are given in table 2-1.

SO 2 emissions were calculated us ing EF 42.6 Lb/1000 Gal. PM 10 and PM 2.5 emissions are calculated using 1Lb/1000 Ga l and 0.25 Lb/1000 Gal respecti vely. All Factors are obtained from AP-42 19

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

. The area source NO X emissions are calculated and adjusted by subtracting the emissions due to point sour ces. 54,652 thousand gallons 14 are consumed in 2005 and a heating value of 140 MMBTU/1000 Gal is used. The SO 2 emissions are calculated using EF 157 Lb/1000 Gal. PM 10 and PM 2.5 emissions are calculated using 7.17 Lb/1000 Gal and 4.67 Lb/1000 Gal respectively. All factors are obtained from AP-42 19

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

. The area source NO X emissions are calculated and adjusted by subtracting the emissions due to point sources. 293,857 MMCF 14 are consumed in 2005. The SO 210 emissions are calculated usi ng EF 0.6 Lb/MMBTU. The PM 10 and PM 2.5 emissions are calculated using 7.6 Lb/MMBTU. All factors were obtained from AP-42 19

2.3 Residential Fuel Combustion
Residential Coal Combustion (SCC 2104001000) Ohio’s household consumption of coal is apportioned per county based on county population 4 . NO X emissions are calculated using EF of 9.1 of coal. The SO 2 emissions are calculated using EF 31Lb/1000 Gal. The PM 10 and PM 2.5 emissions are calculated using 6.2Lb/Ton and 3.8 Lb/Ton respectively . All factors were obtained from AP-42 19

Residential Distillate Oil Combustion (SCC 2104004000) Ohio’s household consumption of distillate oil is apportioned per county based on county population 4 . NO X emissions are calculated us ing EF of 18 lb/1000 gallons distillate fuel respectively. A heating value of 140 MMBTU/1000 Gal is used. The SO 2 emissions are calculated using EF 42.6 Lb/1000 Gal. The PM 10 and PM 2.5 emissions are calculated using 1.08Lb/1000 Gal and 0.83 Lb/1000 Gal respec tively. All factors are obtained from AP-42 19

Residential Liquid Petroleu m Gas Combustion (LPG) (SCC 2104007000) Ohio’s household consumption of LPG is apportioned per county based on county population 4 . NO X emissions are calculated using EF of 13 lb/1000 gallons LPG. The SO 2 emissions are calculated usi ng EF 0.1 Lb/1000 Gal. The PM 10 and PM 2.5 emissions are calculated using 0.17Lb/1000 Gal. All factors are obtained from AP-42 19

Residential Natural Gas Combustion (SCC 2104006010) Ohio’s household consumption of LPG is apportioned per county based on county population 4 . NO X emissions are calculated using EF of 94 lb/MMSCF. MMSCF stands for Million Standard Cubic Feet. This source also emits SO 2 emissions which are calculated using EF 0.6 Lb/MMBTU. The PM 10 and PM 2.5 emissions are calculated using 7.6Lb/MMBTU. All fact ors are obtained from AP-42 19

Residential Wood Combustion
NO X emissions from this area source are ca lculated for seven types of residential heating units that utilize wood for fuel. They are listed below with the appropriate SCC:

Fireplaces without inserts 2104008001 Fireplaces with inserts cataly tic (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 210400805011 The number of Ohio homes with fireplaces ar e adjusted for those t hat burn wood. The following assumptions are applie d to those adjusted homes:
92 percent of wood combust ed in non-certified units 5.7 percent of wood combusted in non-catalytic units 2.3 percent of wood combusted in catalytic units

A state consumption value is applied which is apportioned to each county based on its population 4 . Table 2-2 shows the EF used for each of the seven types of indoor wood burners which make-up this category:

Table 2-2 Emission Factors Used for Wood Burners

SCC 2104008002 210400 8003 2104008004 SCC 2104008010 210400 8050 2104008030 SCC 2104008001 RAPIDS Code Non-Certified N on-Catalytic Catalytic Units SO 2 4.00E-01 4.00E-01 4.00E-01 Lb/ton NO X 2.80E+00 2.80E+00 2.00E+00 Lb/ton PM 2.5 3.06E+01 1.96E+01 2.04E+01 Lb/ton

To avoid double counting of wood consumption for fuel, this category is adjusted by subtracting the wood consumption from OWB to allow this category to account only for indoor wood burning emissions.

Residential Wood combustion also emits SO 2 which is calculated using EF 0.4 Lb/Ton EF. The PM 2.5 emissions are calculated using EF as shown in table 2-2. All factors are obtained from AP-42 19

2.4 Human Cremation (SCC 2810060200)

Not all Ohio counties possess a crematory 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 fr om the Ohio Department of Health, Vital Statistics 17

. It is estimated that 3% of deaths occur outsi de the State of Ohio with no available data to account for their disposition at the time this area source is being calculated. Therefore, those deaths are not accounted for in this category. The methodology does not offer an EF for NOx for this category nor is NOx required to be calculated for this area source. Ohio f eels that it is a combustion source and NOx needs to be included in the inventory al ong with the other com bustion sources. Through its Permits-to-Install for human crem ation, Ohio has se lected a NOx EF of 10.13lb/ton cremated to calculate emi ssions from this area source.12 This source also emits PM, PM 10 , and PM 2.5 emissions which are calculated using EF 0.1 Lb/Ton, 0.071Lb/Ton and, 0.0637 Lb/Ton respec tively. All factors are obtained from AP-42 19

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

. The State Fire Marshall Office, Fire Prevention Bureau 15 provided data on the number of st ructure fires per county in 2005.

This area source is consider ed a combustion source for NO X emissions which are calculated using EF 1.4 lb/ton burned. The residential and commercial structures fires for each county are tabul ated and a fuel load ing of 1.15 Ton/fire is applied. This source also emits PM, PM 10 , and PM 2.5 emissions which are calculat ed using EF 10.8 Lb/Ton. This factor was obtained from AP-42 19

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

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

. The smoke created from these outdoor wood burning units can contain severa l pollutants that are harmful to breathe, including fine particle pollution such as PM 2.5 11 in addition to NOx (research assisted by Deborah Lucas, DAPC intern, 2007)

This new area source category has many unknowns and variables associated with it and Ohio does not possess accurate OWB uni t sales data available to calculate emissions on the county level. Therefore, several assu mptions are made in agreement with the Great Lake States in order 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)

• PM 2.5 emissions factor (g/kg wood) =13.82 (Average of indoor and outdoor) or 27.64 lb/ton of wood

The agreed upon methodology requi res that total number 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 factor s (see above) are applied to calculate the emissions from this outdoor wood burner. Total emissions obtained from this category are subtracted from the Residential Wood Co mbustion category to allow for accurate emissions from the indoor wood burning units.

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

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

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

7. Documentation for the Dr aft 1999 National Emissions In ventory (Version 3.0) for Criteria Air Pollutants and Amm onia. Area Sources. E. H. Pechan & Associates, Inc. March 3, 200314 8. U.S. Environmental Pr otection Agency, STAPPA-ALAPC O-EPA Emission Inventory Improvement Program (EIIP), Volume III - Area Sources Preferred and Alternative Methods, Chapter 8. September 1997.
9. Spreadsheet formulation provided by “Buzz” David Asse lmeier, Air Quality Planning Section, Inventory Group, Springfield, Illinois.

10. Environmental Protection Agen cy (EPA). STAPPA-ALAPCO-EPA Emission Inventory Improvement Progr am (EIIP). Volume III - Area Sources Preferred and Alternative Methods. May 1997.
11. (Environmental Chemistr y.com) viewed on Feb 8th, 2007. [http://environmentalchemistry.com/yogi /environmental/200602out doorwoodfurnaces.ht ml ] 12. (Washington State, Department of Ecology) viewed on Feb 8th, 2007 [http://www.ecy.wa.gov/progr ams/air/AOP_Permits/Boiler /Outdoor_Boilers_home.html]
13. U.S. Environmental Protection Agen cy. Reducing Pollution from Outdoor WoodFired Hydronic Heaters. Fact Sheet http://www.epa.gov/owhh/ pdfs/fact_sheet_1_29_07.pdf (Accessed 1/2007)

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

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

16. Documentation for the Draft 1999 National Emissions In ventory (Version 3.0) For Criteria Air Pollutants and Amm onia. Area Sources. E. H. Pechan & Associates, Inc. March 3, 2003
17. Ohio Department of Health, Vital Statistics

18. Environmental Protection Agency. STAPPA-ALAPCO-EPA Em ission Inventory Improvement Program (EIIP). Volume X – Emissions Projections. December 1999. http://www.epa.gov/ttn/chief/eiip/techreport/volume10/x01.pdf (Accessed 2/2007)

19. Environmental Protection Agency. AP-42. http://www.epa.gov/ttn/chief/ap42/15 

### SECTION 3

NON-ROAD SOURCES

The non-road inventory is gener ated regionally by running U. S. EPA’s Nati onal Mobile Inventory Model (NMIM) model. The Wi sconsin Department 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 process ed the NMIM files in their emissions model and generat ed daily emissions rates. Grant Heatherington from the Wisconsin Department of Natural Reso urces provided the following descriptions...

The National Mobile Inventory Model (NMIM) developed by USEPA was used to estimate emissions for all other non-road m obile categories. NMIM consolidates nonroad mobile emissions and on-road emissions modeling into a singl e modeling system. Only the non-road emissions modeling portion 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 populati ons, average load factors, available engine powers, activity hours and emission factors. Before NMIM was run, modifications and additions were made to the NM IM input data.

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

b. Revised PM 2.5 ratios in SCC table to correctly calculate PM 2
. 5 diesel emissions. This error was introduc ed with NMIM2005 and didn’t exist in NMIM2004.

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

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



### Revised NMIM2005 Input Data

Emission Factor Data

All States: Pechan revised the brake specific fuel consumption (BSFC) emission factor data to include diesel tampers/rammers (2270002006). The revised NMIM file is saved as revBSFC.EMF.16 Population Data

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

SCC Data

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

Fuel Data

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

Table 3-1 NMIM National County 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-p ropelled or portable emi tter of air pollutants, and mobile source emissions are those genera ted by the engines or motors that power such sources. Most mobile sources, exce pt jet or turboprop ai rcraft, are powered by internal combustion (IC) piston engines, and nearly all use liquid fuels.
Gaseous fuels, such as compressed natur al gas (CNG) or li quefied petroleum gas (LPG), had only a very small fraction of the motor fuel market in Ohio in 2005. Solid fuels have not been used by mobile sources in significant amounts since railroads retired their coal-powered steam locomotives in the 1950s.
4.1 Categories of Mobile Sources For inventory and planning pur poses, mobile sources ar e divided into two major categories.
1. On-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 pa ssengers 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 motoriz ed machines or equipment not used for transportation, ranging from constructi on equipment and farm tractors to lawnmowers and hand-held power weed choppers.

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

Non-road Mobile Sources: Some non-road mobile source s (e.g., farm tractors), are self-propelled, but many non-road sources ar e not. A gasoline-powe red chain saw is a familiar example of a non-self-pr opelled non-road mobile source.
Stationary Sources: Not all movable or portable emi ssion sources are mobile sources, however. A small truck-portable cement or hot-mix asphalt plant, for example, may be set up near a construction or road-building site . Such plants are classified as stationary sources, not mobile sources for two reasons: (1) they may operate for weeks or months at a single location, and (2) the trucks 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 pow er pipeline compressors or standby generators in electricity plants and elsewhere, are al so classified as stationary sources.
4.1.1 Categories and Componen ts of Mobile Source Emissions

There are three categories 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 occu r only when the engine is running.

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

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

o “ Stage I ” emissions occur when the underground storage tanks at a service station are being refilled;19 o “ Stage II ” emissions occur when a motor vehicle (or gas can) is being refueled.

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

• Spill emissions . These occur when drops of fuel drip or splash on the ground during or after refueling and evaporate away.
4.2 Ohio On-Road Mobile Source Inventory

The inventory of on-road mobile source emissions was developed in conjunction with the Ohio Department of Transportation (ODOT), Lake Michigan Air Director’s Consortium (LADCO), Unit ed States Environmental Protection Agency (USEPA), and the Ohio EPA (OEPA). Estimates of the amounts of NOx and VO C are reported by county in tons per day. Emissions are repor ted for a typical ozone season weekday in the summer of 2005.

4.2.1 Emission Inventories Developed with MOBILE6 Model

MOBILE6 Overview:
MOBILE6 is a computer program that es timates hydrocarbon (HC), carbon monoxide (CO), oxides of nitrogen (NO x ), exhaust particulate matter (which consists of several components), tire wear particula te matter, brake wear particu late matter, sulfur dioxide (SO 2 ), ammonia (NH 3 ), six hazardous air pollutant (HAP), and carbon dioxide (CO 2 ) emission factors for gasoline-f ueled and diesel highway moto r vehicles, and for certain specialized vehicles such as natural-gas-fuel ed or electric vehicles that may replace them. The program uses the calculation procedures presented in technical reports posted on EPA's MOBILE6 Web page http ://www.epa.gov/otaq/models.htm.
MOBILE6 emission factor estimates depend on various conditions, such as ambient temperatures, travel speeds, operating modes, fuel volatility, and mileage accrual rates. Many of the variables affe cting vehicle emissions can be specified by the user. MOBILE6 will estimate emission factors fo r any calendar year between 1952 and 2050, inclusive. Vehicles from the 25 most re cent model years are considered to be in operation in each calendar year.

4.2.2 MOBILE6 Defaults:
MOBILE6 includes default values for a wide range of conditions that affect emissions. These defaults are designed to represent “ national average” input data values. Users who desire a more precise estimate of local emissions can substitute information that more specifically reflects local conditions. Use of local input data will be particularly common when the local emission inventor y is to be constructed from separate20 estimates of roadways, geographic areas, or ti mes of day, in which fleet or traffic conditions vary considerably.
A list of MOBILE6 input parameters is provi ded below. Most of these inputs are optional because the model will supply default values unless alternate data are provided.

4.2.3 MOBILE6 Input Parameters

• Calendar year

• Month (January, July)

• Hourly Temperature

• Altitude (high, low)

• Weekend/weekday

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

• Humidity and solar load

• Registration (age) distribution by vehicle class

• Annual mileage accumulation by vehicle class

• Diesel sales fractions by vehicle class and model year

• Average speed distribution by hour and roadway

• Distribution of vehicle miles traveled by roadway type

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

• Engine start soak time distribution by hour

• Trip end distribution by hour

• Average trip length distribution

• Hot soak duration

• Distribution of vehicle miles traveled by vehicle class

• Full, partial, and multiple diurnal distribution by hour

• Inspection and maintenance ( I/M) program description

• Anti-tampering inspection program description

• Stage II refueling emissions inspection program description

• Natural gas vehicle fractions

• HC species output

• Particle size cutoff

• Emissions factors for PM and HAP

• Output format specific ations and selections

4.2.4 MOBILE6 References

The following publications prov ide much of the guidance fo r the preparation of the onhighway inventory.
EPA-450/4-81-026d (Revised), now EPA/450-R-92-009, Procedures for Emission Inventory Preparation , Volume IV: Mobile Sources , December 1992. Hereafter, “Procedures Vol. IV”. The 1992 vers ion is still the definitive document on21 inventories. If a previous edition is referr ed to, the fact will be not ed as, for example, “the 1989 Procedures Vol. IV” or “Volume IV, 1989 edition”.

EPA420-R-03-010, User’s Guide to MOBILE6.1 and MOBILE6.2: Mobile Source Emission Factor Model , August 2003. This is the User’s Guide for the official MOBILE6.2.03 on-highway mobile source em ission factor model and will usually be referred to as the M6.2 (or simply M6) User’s Guide (UG). The M6 model in its various versions was developed and publis hed by Assessment & Modeling Division (AMD) of the National Vehicle & Fuels Em issions Laboratory (NVFEL) in Ann Arbor, Michigan. The NVFEL is part of USE PA Office of Transportation & Air Quality (OTAQ), formerly the Office 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 pr imary source of guidance on M6 inputs and an invaluable adjunct to the M6 User’s Guide.
USEPA document “Frequently Asked Questions on MOBILE6” , 16 January 2002. Hereafter, [M6] “FAQ”. 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 Mar go Oge, Director of OTAQ, to Regional Air Division Directors.

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

4.3.1 Vehicle Registra tion Distribution by Age

Overview:
The vehicle age distribution determines the fr action of vehicles operating within each emissions control 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 esti mates of a distribution of r egistered 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 t he July 1, 1996 registration profile into a general registration distribut ion by age and by vehicle ca tegory for some 6 composite (gasoline and diesel) vehicle types plus motorcycles. To project future changes, EPA evaluated general sales growth and vehicle scrappage trends for the total light-duty vehicle in-use fleet and the total heavy-dut y vehicle in-use fleet, and made minor adjustments, where possible, to reflect some of the differences between vehicle categories.

Description: The MOBILE6 model requires estima tes of a distribution of registered vehicles by age and vehicle category for curr ent and future years. OEPA chose to use local vehicle registration data provided by the Ohio Bureau of Motor Vehicles (BMV) which was sent to the Lake Michigan Air Dir ectors Consortium (LADCO) to develop these inputs. LADCO then contracted with a subcontractor to breakout the age distribution data from the Vehicle Identification Num bers (VIN).

Note: It was learned during the course of this inventory that there were some discrepancies in the age distribution data. But it was too large of a project to reevaluate the data prior to this invent ory. This will be corrected in the next inventory (2008).
Method Applicability: This approach is most applic able in areas where there are significant differences in the local vehicle fleet age distribution rela tive to the national average.

Data Sources and Procedures: This approach involves using local vehicle registration data. This is typically available at the county level, but may also be applied using statewide data from the stat e motor vehicle registration office. The fleet age should be representative of the vehicle fleet over the small urban or rural area under question.

Advantages:

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

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

• Recommended by EPA and generally is encouraged as a preferred approach over the national default approach.23 4.3.2 Daily Vehicle Miles Traveled (DVMT)

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

Table 4-1 Federal Func tional Class Categories:

01 - Rural Interstate 02 - Rural Principal Arterial 06 - Rural Minor Arterial 07 - Rural Major Collector 08 - Rural Minor Collector 09 - Rural Local 11 - Urban Interstate 12 - Urban Freeway & Expressway 14 - Urban Principal Arterial 16 - Urban Minor Arterial 17 - Urban Collector 19 - Urban Local24 Table 4-2 DVMT County Summary:

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

Disclaimer by ODOT:

The above PDF web based tables contain the State of Ohio's adjusted county DVMT's and road mileage for the years 1990 - 2005. Please be aware that the numbers are estimates only. The factoring process used annual, estimated, and statewide ADT (Average Daily Traffic) growth factors, deriv ed from the output of a limited number of traffic counting stations around the state. Although the growth factors are available by functional class, they are more reliable for major roads such as interstates or expressways, which are relatively well-sampl ed, than for local roads or collectors. The numbers also do no allow for periodic, large- scale functional reclassification actions25 which reassign selected roads or road segm ents from one functional class to another.
The Ohio Department of Transportation t herefore does not warr ant the accuracy, completeness, or reliability of these estimates for your research. We also do not assume responsibility for any incorrectness that may occur.

4.3.3 VMT From Travel Demand Models (TDM)

Overview:
Travel demand forecast modeling is perform ed by the Ohio Metropolitan Planning Organizations (MPOs) and ODOT for a multit ude of purposes including the preparation of regional emissions estimate s. The ODOT Office of Te chnical Services’ Modeling & Forecasting Section recommends that Ohio ’s TDMs and ODOT’s conformity analysis methods be used to establish the roadway mob ile source portion of Ohio’s SIP budget to assure consistent methods are used for transportation conformity analysis and budgets. Therefore, ODOT provided both MPO regional TDM runs and statewide TDM runs with associated data to OEPA and LADC O. The ODOT provided model run data for years 2002, 2005, 2009, 2012, and 2018.

Data provided included loaded networks in both CSV format and GIS shape files, trip end summaries, zone boundary GIS shape files, intra-zonal trip VMT estimates, and VMT summaries for each of the loaded networ ks. Additional post processing data was provided including but not lim ited to metadata describing the loaded networks, Hourly distribution by functional cla ss, speed profiles, day of week / weekend / monthly car and truck traffic profiles, 2009 & 2018 VMT RPO data sets, state wide VMT growth rates for local traffic, and a 2005 VMT summary comparison spreadsheet. It should be noted that among other things, the loaded TDM Netw orks contain distance and daily volumes from which VMT is computed.

Network volumes are post processed to esti mate VMT by hour of day. The hourly volumes and capacity, posted speed limi t, and type of roadway for each roadway segment are then used to estimate aver age hourly speeds needed for MOBILE6 based emissions estimates. Modelin g by segment by hour of day in this way makes emissions estimates more sensitive to the effects of roadway improvements. This allows transportation planners to evaluate the relati ve emissions affect of improvements to individual roadways as well as packages of improvements and the entire set of planned roadway improvement projec ts air quality impacts of construction programs.26 4.3.4 Speed Di stribution 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 c onducted by ODOT. The speed study is documented in “Statewide Travel Time Study, May 2001 by Greg Giaimo, Ohio Department of Transportation ”. When OEPA asked for s peeds for use with MOBILE6 for development of CERR, ODOT provided a set of speeds based on that statewide travel time study. Those speeds are doc umented in a technical memorandum titled “Estimation of Average Speed by Functional Class for MOBILE6 Runs ” dated 5/27/2004. Readers should refer to those docum ents for the details. Here the contents of the technical memo, Estimated Average Speed by Functional Class, are summarized.

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

The memo states that the s peeds which the Ohio Department of Transportation (ODOT) had been using prior to that date, 2004, fo r air quality analysis estimates based on County DVMT summaries, were developed by a former ODOT employee for addressing the one (1) hour standards conformity ru les established due to 1990 emissions exceedances. No documentation was found in ODOT’s files on the origin of these average speed values or how they were esti mated. In addition, EPA has requirements for using latest planning assumptions for ai r quality conformity analyses. Therefore, ODOT believed that it was in the state’s best interest to use the mo st recent available data to provide a new set of estimated av erage speeds consistent with those used for urban area travel demand models which were under development at that time. The memo contains comparisons of 2002 speed dat a obtained from traf fic count equipment, automatic traffic recorders (ATRs) which co llect data continuously throughout the year. It also contains comparisons of the 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 FC 0

6 F C0 8 F C1 1 FC1 4 FC1 7

Functional ClassSpeed Average Speed

1990 Analysis Speeds 2001 Speed Study



### Speeds Comparison

0 20 40 60 80 100

FC 0

1 FC 06 F C08 F C11 FC14 FC 1

7

R

AMPS

Functional ClassSpeed Average Speed

Min. Avg Speed

Max. Avg. Speed

Gebhardt's Speeds

Spd Study Est Speeds Spd Study Greg Est

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

CAUTION 

### : It should be noted that speeds on facilities falling in any one of the federal functional classifications vary greatly bet ween roadways, between hour of the day, and day of the week. So these provide only very rough estimates of speed and should be used with caution. In addition, it is expec ted that these average statewide speeds are higher than the average speeds in t he non-attainment areas because the non-28 attainment counties tend to be more popul ated and more congested. The document “Highway Vehicle Speed Es timation Procedures For Use in Emission Inventories”, September 1991 by Earl Ruiter of Cambridge Systematics Inc. is referenced by EPA’s documented procedures for emission inventor y preparation. This document suggests post processing travel demand model traffic assignment results to estimate average speeds.

Final space mean speeds that ODOT provi ded are summarized in the Table 1 below:
Table 4-3 Speed by Federal Functional Class
Functional Class 1990 Analysis 2001 Speed Study Speeds Speeds FC01 57.3 64.0 FC02 45.3 53.0 FC06 39.9 53.0 FC07 35.1 43.1 FC08 30.5 43.1 FC09 28.0 43.1 FC11 46.3 61.6 FC12 43.3 61.6 FC14 18.9 29.3 FC16 19.6 29.3 FC17 19.6 29.2 FC19 19.6 23.8

It was decided by mutual agreement among individuals within the ODOT Office of Technical Services that these new s pace mean speed based average speed estimates were reproducible and defensib le since they are well docu mented and should therefore be the speeds used with HPMS** VMT if 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 anal ysis methods be used to establish the roadway mobile source portion of Ohio’s SIP budget for reasons already mentioned in 5.3.2 and to assure consistent methods are used for transportation conformity demonstration analyses and budget s. Therefore, ODOT pr ovided travel demand model runs and the speed curves by link group that ODOT uses for the speed estimates within29 the post processing of travel demand model runs for estimating regional emissions. Table 2 shows these link group curves.

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

Link Group Facility Type Free Flow Speed Areatype a b

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

11 Urban Street 50 Urban 0.74 5.0

12 Urban Street 50 CBD 1.16 6.0

13 Urban Street 40 Suburban 0.38 5.0

14 Urban Street 40 Urban 0.70 5.0

15 Urban Street 40 CBD 1.00 5.0

16 Urban Street 35 Suburban 0.96 5.0

17 Urban Street 35 Urban 1.00 5.0

18 Urban Street 35 CBD 1.40 5.0

19 Urban Street 30 Suburban 1.11 5.0

20 Urban Street 30 Urban 1.20 5.0

21 Urban Street 30 CBD 1.50 5.0

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

T = T 0 {1 + a * (V/C)^b]30 More complete details about emissions mode ling process employed by ODOT may be found in ODOT documentations. The docum ent titled “Congestion Management & Air Quality Analysis (CMAQ) Program Docu mentation” dated December 2005 may be obtained from the ODOT web site at www.dot.state.oh.us/urban/data/cmaq.doc (Microsoft Word document)

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

For historical reference:

>>> Dave Moore <Dave.Moore1@dot.s tate.oh.us> 4/10/2006 2:13 PM >>>

All,
An air quality coordination meeting has been scheduled for April 27, 2006 at 10:00 AM at ODOT Central Office conference room GA. The primary purpose of this meeting is to discuss development of 2002 mobile source inventories for use in developi ng the Ohio 2007 8-Hour Ozone SIP Attainment Demonstrations. See meeting agen da below. OEPA is working to ward a June 15, 2006 schedule for submitting the 2002 invent ories to US EPA.
A key component of the meeting will be to review a nd confirm the MOBILE6.2 i nput parameters, by Ohio a/q area, for use in developing the 2002 mobile inve ntories. See draft templa te below. The Ohio MPO travel demand models will be used to generate t he 2002 VMT inputs to MOBILE. Thanks, DM DM31 IMPORTANT NOTICE: The following tables are not to be used for inventory purposes as the data is subject to change. For the cu rrent input table, contact Ohio EPA, Division of Air Pollution Control.

Table 4-5 Mobile Inputs



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

State Programs Input

Stage II Refueling 93/3/86/86

Anti-tampering Programs 96/78/50/22222/21111111/1/12/098./12111112

I/M Programs Yes Exclude Ashtabula County - No I/M program Program 1 2004 2050 2 T/O OBD I/M Model Years 1 1996 2050 Vehicles 1 22222 21111111 1 Stringency 1 30.0 Compliance 1 98.0 Waiver Rates 1 1.0 1.0 Cutpoints Exemption Age 1 25 Grace Period 1 4 NO TTC Credits Effectiveness DESC file

Program 2 2004 2050 2 T/O EVAP OBD & GC Model Years 2 1996 2050 Vehicles 2 22222 11111111 1 Stringency Compliance 2 98.0 Waiver Rates 2 1.0 1.0 Cutpoints Exemption Age 2 25 Grace Period 2 4 NO TTC Credits Effectiveness DESC file

Program 3 2001 2003 2 T/O ASM 2525 PHASE-IN32 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 file33 Program 7 1996 2050 2 T/O GC Model Years 7 1975 1995 Vehicles 7 22222 21111111 1 Stringency Compliance 7 98.0 Waiver Rates 7 3.0 1.0 Cutpoints Exemption Age 7 25 Grace Period 7 2 NO TTC Credits Effectiveness DESC file

Fuel Commands

Fuel Program 1

Oxygenated Fuels 0.00 0.42 0.00 0.036 2

Fuel RVP 9

Alternative Emission Regulati ons and Control Measures

Rebuild Effects 0.1

External Conditions Commands

Calendar Year 2005

Evaluation Month 7

Min/Max Temperature National Climatic Data Center

Vehicle Fleet Characteristic Commands

Registration Distribution Variable34 

### 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 98.035 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 136 Stringency Compliance 7 98.0 Waiver Rates 7 3.0 1.0 Cutpoints Exemption Age 7 25 Grace Period 7 2 NO TTC Credits Effectiveness DESC file

Fuel Commands

Fuel Program 1

Oxygenated Fuels 0.00 0.42 0.00 0.036 2

Fuel RVP 9

Alternative Emission Regulati ons and Control Measures

Rebuild Effects 0.1

External Conditions Commands

Calendar Year 2005

Evaluation Month 7

Min/Max Temperature National Climatic Data Center

Vehicle Fleet Characteristic Commands

Registration Distribution Variable37 

### Other Areas ( excluding NOACA/AMATS 

### and OKI/MVRPC 

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

Fuel Commands Input

Fuel Program 1

Oxygenated Fuels 0.00 0.42 0.00 0.036 2

Fuel RVP 9

Alternative Emission Regulati ons and Control Measures

Rebuild Effects 0.1 (0.30 for 2018)

External Conditions Commands

Calendar Year All

Evaluation Month 7

Min/Max Temperature National Climatic Data Center

Vehicle Fleet Characteristic Commands

Registration Distribution Variable

4.5 Ohio’s Mobile Emission Data Processed by LADCO (Lake Michigan Air Director’s Consortium):

2005 TDM and Mobile6 input data were provided to LADCO for processing. The data was processed by LADCO with T3 to prepare 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) fo r regional haze, fine particles , and ozone. Emissions for on-road motor vehicles are estimated using vehi cle miles traveled, tr ip starts and ends, speed, and other activity data developed by State Agencies and Metropolitan Planning Organizations (MPOs) using transportati on demand models (TDMs), and emission factors from EPA's MOBILE6 model. To s upport this modeling in the upper Midwest, ENVIRON, working with LADCO, State DOTs, and local MPOs, has developed a software tool (the TDM Transformation Tool, or "T3") that takes TDM output from approximately twenty transportation networ ks using a variety of models, applies appropriate data transformations , and outputs link- and county-le vel activity data in a uniform format for input to the CONCEPT emissions processing model (a new emissions processing model also developed wit h funding from LADCO). In a parallel effort, analyses of extensive automatic tra ffic recorder (ATR) dat a collected by State DOTs were conducted to develop temporal profiles (hour of day , day of week, and month of year) of vehicle counts and vehicl e mix by roadway type for developing the detailed on-road emissi on inventories.
T3 provides a conduit from the projections of traffic demand model ers regarding vehicle types, road networks, and vehicle activity 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 simult aneously providing a great degree of flexibility in representing t he TDM projections in terms acceptable to most air quality models. These goal s have been achieved through the use of a dimensional transformation approach, w here the dimensions of the various transformations are user-defined - hence the name of the tool.

By Stella Shepard, Alison K. Pollack, John Haasbeek, ENVIRON International Corporation, 101 Rowland Way, Su ite 220, Novato, CA. 94945 & Mark Janssen, Lake Michigan Air Directors Consortium (LADCO ), 2250 E. Devon Avenue # 250, Des Plaines, IL 60018, janssen@ladco.org

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

• Open Source. Writt en primarily in PostgreSQL, th e software required for running39 CONCEPT is in the public dom ain. The model itself is GNU Public License (GPL) compliant and users are encouraged to make additions and enhancements to the modeling system.

• Transparent. The database structur e of the model makes the system easy to understand, and the modeling codes themselv es are extremely well documented to encourage user participation in the customizing the system for specific modeling requirements.

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

4.5.3 LADCO Ohio Data Outputs for 2005:

The following LADCO outputs and documents can be found at: www.ladco.org/tech/e mis/net05/index.html

Table 4-6 LADCO Data Output

Sta te Network T3 Descripti on DOC M6 Inpu ts VM T vs HP MS Exc el Average Day VMT (this should match conformi ty inventory ) Co unt y Em issi

on
s Re por t All Pollut ants After Speci ation Dropped VMT M6 Run Summ ary Pollut ant T otals (Short ) Raw Summ ary (pol,ve h, etype) Hourly Tempo ral Summ ary Hourly Veh Mix Summ ary Hourly Speed Summ ary (with volum e/ capaci ty)

OH AKRON AKRON OH OH AKRON 1 1 1 1 1 1 1 1 140 OH CANTON CANTON OH OH CANTON 1 1 1 1 1 1 1 1 1
OH CINCI CINCI OH OH CINCI 1 1 1 1 1 1 1 1 1
OH CLEVE CLEVE OH OH CLEVE 1 1 1 1 1 1 1 1 1

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

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

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

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

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

Additional Documents on LADCO Web Page:

“Comparison to EPA's Default Model NMIM”

“How we Build the 2005 Vmt/Networks”

“Spreadsheet/Graphics on Vehicle Mix”

“Background on the T3 Tool “

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

39003 Allen Statewide Lima Allen County Regional Planning Commission Tom Mazur

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

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

39015 Brown Statewide

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

39019 Carroll Statewide 39021 Champaign Statewide

39023 Clark Springfield Coordinating Committee of the Clark County-Springfield Eric Ottoson41 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 Davis42 Coordinating Agency

39095 Lucas Toledo Toledo Metropolitan Area Council of Governments Sujatha Mohanakrishnan

39097 Madison Statewide

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

39101 Marion Statewide

39103 Medina Cleveland Northeast Ohio Areawide Coordinating Agency Bill Davis

39105 Meigs Statewide 39107 Mercer Statewide

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

39111 Monroe Statewide

39113 Montgomery Cincinnat/Dayton Miami Valley Regional Planning Commission Ana Ramirez

39115 Morgan Statewide 39117 Morrow Statewide 39119 Muskingum Statewide 39121 Noble Statewide 39123 Ottawa Statewide 39125 Paulding Statewide 39127 Perry Statewide 39129 Pickaway Statewide 39131 Pike Statewide

39133 Portage Akron Akron Metropolitan Area Transportation Study Jason Segedy

39135 Preble Statewide 39137 Putnam Statewide

39139 Richland Statewide Richland County Regional Planning Commission John Adams

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

39151 Stark Canton Stark County Regional Planning Commission Dan Slicker

39153 Summit Akron Akron Metropolitan Area Transportation Study Jason Segedy

39155 Trumbull Youngstown (partial county model

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

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

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

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

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

39173 Wood Toledo Toledo Metropolitan Area Council of Governments Sujatha Mohanakrishnan

39175 Wyandot Statewide NOTE: Complete MPO information can be found at, www.dot.state.oh.us/urban/mpomap.htm and at www.dot.state.oh.us/urban/mpolist.htm#Cleveland

.



### SECTION 5

MARINE, AIRCRAFT and RAIL (MAR) SOURCES

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

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

Emissions were determined for ten subclasses of vessel types: Deep draft vessels (DDV) at port, DDV mid-late, push boats (rivers /lakes), tugs, ferries, other special (excursion) vessels, support vessels, dredges, commercial fishing, and military vessels (Coast Guard). These were linked to various Ohio lakes and rivers.
Because of the large variety of methodologie s employed, inventory tables for the ten subcategories are detailed in the comp lete inventory prepared and published by ENVIRON Internati onal Corporation: LADCO 2005 COMMERCIAL MARINE EMISSIONS , by Christian E. Li ndhjem, March, 2007.
Emission totals produced by ENVIRON were provided to LADCO to submit to EPA for Ohio’s State Implementation Plan (SIP).44 5.2 Rail Sources

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

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

5.3 Aircraft Sources

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

COMPONENTS:

I. Ohio Airports: A list of both towered and non-towered airpor ts in Ohio is obtained from the Ohio Department of Transportation. See: www.dot.state.oh.us/aviation/ In conversation with ODOT two individuals stated that the 16 4 airports listed covered over 90% of the airports in Ohio. See Table 1.45 II. Number of Operations/LTOs by Airport/County: The ODOT list contained the number of operations a year per airport. An operation is either a landing or a take-off. A Landing and Take Off (LTO) is required for FAA EDMS calculations. LTOs were deriv ed simply by dividing the number of operations by two. These were totaled by county.

Table 5-1 Number of operations and LTOs for 2005

County Airport Name ID Total Operations LTOs/Year

Adams Alexander Salamon AMT 5210 2605 Allen Allen County AOH 32500 16250 Ashland Ashland County 3G4 49240 24620 Ashtabula Ashtabula County HZY 16886 8443

Ashtabula Germack 7D9 840 420 Athens Ohio University UNI 51600 25800 Auglaize Neil Armstrong AXV 29456 14728

Belmont Barnesville-Bradfield 6G5 10150 5075

Belmont Alderman 2P7 6150 3075
Brown Brown County GEO 5157 2578.5 Butler Butler County Regional HAO 61687 30843.5 Butler Hook Field Municipal MWO 40050 20025 Butler Miami University OXD 16708 8354 Carroll Carroll County -Tolson TSO 34950 17475

Carroll Parsons 5D6 2674 1337 Champaign Grimes Field I74 23480 11740 Champaign Weller 38I 300 150 Clark Springfield-Beckley Municipal SGH 64033 32016.5

Clark Mad River I54 15350 7675 Clermont Clermont County I69 35741 17870.5 Clinton Airborne Airpark ILN 52000 26000

Clinton Clinton Field I66 29360 14680

Clinton Hollister Field 2B6 161 80.5 Columbiana Columbiana County Ø2G 31146 15573

Columbiana Koons 8G8 2546 1273 Coshocton Richard Downing I4Ø 19550 9775 Coshocton Tri-City 8ØG 8085 4042.5 Crawford Port Bucyrus 17G 24871 12435.5 Crawford Galion Municipal GQQ 5216 2608 Cuyahoga Burke Lakefront BKL 97100 48550 Cuyahoga Cleveland-Hopkins International CLE 234356 117178 Cuyahoga Cuyahoga County CGF 79774 39887 Darke Darke County VES 9238 4619

Defiance Defiance Memorial DFI 9130 4565 Delaware Delaware Municipal DLZ 39300 19650

Delaware Packer 5E9 3181 1590.5

Erie Hinde 88D 1350 675 Erie Kelleys Island 89D 25495 12747.5 Erie Griffing-Sandusky SKY 112100 5605046 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 Stat e 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 4730047 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 307448 Scioto Greater Portsmouth Regional PMH 45830 22915

Seneca Bandit Field 5D9 140 70 Seneca Fostoria Metropolitan FZI 7900 3950

Seneca Weiker 82D 320 160
Seneca Seneca County 16G 60165 30082.5 Shelby Sidney Municipal I12 20500 10250

Stark Barber 2D1 13750 6875 Stark Miller Airport 4G3 8000 4000 Stark Beach City 2D7 6112 3056

Summit Akron Fulton International AKR 26000 13000 Summit Akron-Canton Regional CAK 120441 60220.5 Summit Mayfield 1D4 450 225 Summit Kent State University 1G3 72500 36250

Trumbull Braceville 41N 425 212.5

Trumbull Warren 62D 14738 7369 Trumbull Youngstown-W arren Regional YNG 98298 49149 Tuscarawas Harry Clever Field PHD 54880 27440 Union Union County MRT 31886 15943
Van Wert Van Wert County VNW 20516 10258 Vinton Vinton County 22I 5225 2612.5
Warren Warren County I68 24951 12475.5
Warren Red Stewart Airfield 4ØI 16800 8400
Wayne Wayne County BJJ 96520 48260 Williams Williams County ØG6 10010 5005 Wood Wood County 1GØ 27405 13702.5

Wood Bordner 3D8 2200 1100 Wood Deshler Municipal 6D7 2000 1000

Wood Metcalf TDZ 90700 45350 Wyandot Wyandot County 56D 7410 3705

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

Table 2. Sample from “Table 7.” This is the all community total of aircraft models for the Akron/Canton area. “All Service” departure s were used as the number of LTOs per year for that model. Listed in the original table are airc raft model by airport and number of services/LTOs.49 **TOTAL DEPARTURES PERFORMD**

**Aircraft Scheduled Non-Sched All Model Service Service Service** 

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

IV. Emission Factors: Where there was specific aircraft model data the emission factors were derived using the FAA’s Emission Dispersion Modeling System (EDMS). EDMS is a combined emissions and dispersion model for assessing ai r quality at civilian airports and military air bases. The model was developed by the Federal Aviation Administration (FAA) in cooperation with the Unit ed States Air Force (USAF). The model is used to produce an inventory of emissions generated by source s on and around the airport or air base, and to calculate pollutant concentrations in these environments.50 Table 5-2 EDMS Aircraft Emissions Emissions provided by Michigan Department of Environmental Quality. (The few aircraft in Ohio not included in the table had emissions derived by EDMS 5.0 in-house.)

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

Year 2005 Lbs Emitted Per LTO Aircraft Type CO NOx HC VOC SO2 PM2.5 PM10
A- 318 19.8 18.7 4.0 4.4 1.5 0.0 0.0
A-300-600/R/CF/RCF 27.1 56.4 2.0 2.2 4.0 0.2 0.2
A-300B/C/F-100/200 30.2 52.5 3.5 3.7 3.3 0.2 0.2
A-310-200C/F 32.6 52.5 7.3 7.9 3.3 0.2 0.2
A-319 19.8 18.7 4.0 4.4 1.5 0.0 0.0
A320-100/200 13.7 19.8 1.3 1.3 1.8 0.2 0.2
A-321 16.8 36.8 3.1 3.3 2.2 0.0 0.0
A-330-200 29.8 61.5 0.4 0.4 4.4 0.2 0.2
AVROLINER RJ85 24.7 9.5 2.9 3.3 1.3 0.2 0.2
BAE-146-300 24.7 9.0 3.1 3.3 1.3 0.2 0.2
BEECH 1900 A/B/C 11.0 1.1 3.3 3.5 0.2 0.0 0.0BEECH KINGAIR C90 1.8 0.9 0.2 0.2 0.2 0.0 0.0
717-200 11.7 23.4 0.0 0.0 1.5 0.0 0.0
727-100 21.4 23.1 4.6 5.1 2.9 0.4 0.4 727-100C/QC 44.5 19.8 4.6 5.1 2.4 1.1 1.1
727-200 19.6 27.3 2.9 3.1 3.3 1.1 1.1
737-100/200 14.1 16.1 2.2 2.4 2.0 0.7 0.7
737-200C 13.9 17.4 6.8 7.5 2.0 0.9 0.9
737-300 28.7 15.9 1.8 2.0 1.8 0.0 0.0
737-400 26.5 18.5 1.5 1.5 1.8 0.0 0.0
737-500 24.7 21.2 1.3 1.3 2.0 0.0 0.0
737-700/LR 17.6 20.1 2.0 2.0 1.8 0.4 0.4
737-800 15.7 27.1 1.5 1.8 2.0 0.7 0.7
737-900 15.7 27.1 1.5 1.8 2.0 0.7 0.7
747-100 252.6 108.5 106.7 116.8 7.1 0.4 0.4
747-200/300 60.6 104.7 7.1 7.7 6.8 0.7 0.7
747-400 67.0 105.6 5.7 6.4 7.3 0.7 0.7
757-200 24.7 35.7 2.0 2.2 2.6 0.4 0.4
757-300 27.1 33.1 0.4 0.4 3.1 0.2 0.2
767-200/ER 32.6 52.5 7.3 7.9 3.3 0.2 0.2
767-300/ER 32.0 62.2 2.6 2.9 4.0 0.4 0.4

777 32.8 85.1 5.1 5.7 4.4 0.4 0.4CANADAIR RJ100/ER 16.3 4.9 1.5 1.8 0.7 0.0 0.0
CANADAIR RJ-700 12.6 9.3 0.0 0.0 1.1 0.0 0.0
CESSNA 208 1.1 0.4 0.0 0.0 0.0 0.0 0.0
CONVAIR CV-580 36.2 0.9 8.8 9.5 0.7 0.0 0.0
DASSAULT FALCON 13.7 2.6 2.4 2.6 0.2 0.0 0.0
DHC8-100 DASH 8 5.1 3.1 0.0 0.0 0.4 0.0 0.0
DORNIER 328 JET 1.3 6.6 11.9 12.6 0.7 0.0 0.0
DOUGLAS DC-10-10 102.5 76.7 38.6 42.1 4.2 0.0 0.0
DOUGLAS DC-10-30 45.4 78.7 5.3 5.7 5.1 0.4 0.451 DOUGLAS DC-10-40 131.8 81.8 30.2 33.1 6.0 0.7 0.7
DOUGLAS DC-8-63 263.5 25.6 219.1 239.9 4.2 5.1 5.1
DOUGLAS DC-8-71 53.6 34.6 3.1 3.3 3.7 0.0 0.0
DOUGLAS DC-8-73 53.6 34.6 3.1 3.3 3.7 0.0 0.0
DOUGLAS DC-9-10 14.1 14.6 3.7 4.0 1.8 0.2 0.2
DOUGLAS DC-9-15F 14.1 14.6 3.7 4.0 1.8 0.2 0.2
DOUGLAS DC-9-30 14.1 14.6 3.7 4.0 1.8 0.2 0.2
DOUGLAS DC-9-40 39.7 16.5 10.8 11.9 2.0 1.3 1.3
DOUGLAS DC-9-50 12.6 20.1 1.8 1.8 2.2 0.9 0.9
EMBRAER-135 12.8 5.5 1.1 1.3 0.7 0.0 0.0
EMBRAER-140 13.7 6.0 1.3 1.3 0.7 0.0 0.0
EMBRAER-145 6.4 6.8 1.1 1.1 0.7 0.0 0.0
EMBRAER-170 9.0 9.7 0.0 0.0 1.1 0.0 0.0
F28-4000/6000 76.7 10.4 77.2 84.4 1.5 0.0 0.0
JETSTREAM 41 4.6 2.0 0.4 0.7 0.2 0.0 0.0
L-101101/100/200 33.3 112.0 6.2 6.8 5.7 1.3 1.3
LEAR-25 75.2 0.7 7.9 8.4 0.2 0.0 0.0
LOCKHEED L100-30 48.7 9.9 19.6 21.4 1.8 0.0 0.0
MD-11 47.8 93.3 4.0 4.4 6.0 0.7 0.7 MD-80, 1, 2, 3, 7, 8 16.3 20.3 0.0 0.0 2.2 0.2 0.2
MD-90 12.1 23.8 0.2 0.2 2.0 0.2 0.2
RJ-200ER/RJ-440 16.3 4.9 1.5 1.8 0.7 0.0 0.0
SAAB-FAIRCHD 340/B 4.2 1.5 1.5 1.5 0.2 0.0 0.0

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

Table 5-3 Fleet Emissi on Factor Categories

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

Table 5-3a Fleet Average Emission Factor s 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 estimate52 Table 5-3b Fleet Average Emission Factor s for Local General Aircraft.

(Taken From: Table A-11) Pollutant Emission Factors (lbs/LTO) HC 0.394 NOx 0.065 CO 12.014 SOx 0.01 PM10 0.2367

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

Table 5-3c Fleet Average Emission Fa ctors for Military Aircraft.

(Taken from: Table A-17) Pollutant Emission Factors (lbs/LTO HC 1.234 NOx 0.158 CO 28.13 SOx 0.015 PM10 0.60333

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

METHODOLOGY

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

1. Commercial scheduled and non-scheduled ai rcraft air carrier activity and commercial air freight activity by aircraft model types,

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

3. Military annual local and iti nerant operations for year 2005.

Due to the need to have aircraft operations in formation expressed as landing/take off (LTO) cycles, the following assumptions were made:

1. For commercial aircraft and commercial ai r freight activity, t he number of annual aircraft annual LTO cycles was assu med to be equal to the number of53 departures. The daily LTO cycle frequency was then obtained by dividing the yearly LTO cycles by 365.

2. For general aircraft annual local and iti nerant airport operations, each respective operations total was divided by 2 to obt ain the corresponding year local and itinerant LTO cycles. The expected daily local and itinerant LTO cycles then were obtained by dividing these annual totals by 365.

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

.

APPROACH

1. A list of more than 90% of the airports was obtained fr om the Ohio Department of Transportation. These were classed by airport, county, aircraft flight classification, and the total number of op erations per year.
2. The number of oper ations (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 categorie s used by the USEPA in calculating emissions.54 Itinerant (General, air carrier, commuter, ai r taxi, general aviation itinerant)

Local (General aviation local)

Military (Military)

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

5. Emission factors were det ermined from the FAA’s EDMS pr ogram for specific aircraft model and engine type. See IV. Emission factors above. The aircraft emission table provided by Michigan has the emission factors for most of the aircraft fl own in Ohio. . Where specific aircraft model data was not available USEPA average fleet emissions were used.
6. Emission factors times LTOs by count y yielded tons per y ear per county.

Table 5-4 Pollutant by County (Sample)

County POLLUTANT ACTIVITY(LTOS/YEAR) ACTIVITY(LTOS/DAY) EMISSIONS(TON/YEAR) ADAMS CO 2605 7.136986 24.552325 ADAMS HC 2605 7.136986 0.977285 ADAMS NOX 2605 7.136986 0.136045 ADAMS PM10-PRI 2605 7.136986 0.513114825 ADAMS PM25-PRI 2605 7.136986 0 ADAMS SOX 2605 7.136986 0.0157875 ADAMS VOC 2605 7.136986 0.96314234 ALLEN CO 16250 44.52055 147.945065 ALLEN HC 16250 44.52055 5.841097 ALLEN NOX 16250 44.52055 0.827189 ALLEN PM10-PRI 16250 44.52055 3.081191265 ALLEN PM25-PRI 16250 44.52055 0 ALLEN SOX 16250 44.52055 0.0984575 ALLEN VOC 16250 44.52055 5.769568254 ASHLAND CO 24620 67.45205 173.67794 ASHLAND HC 24620 67.45205 6.19414 ASHLAND NOX 24620 67.45205 0.94895 ASHLAND PM10-PRI 24620 67.45205 3.532515 ASHLAND PM25-PRI 24620 67.45205 0 ASHLAND SOX 24620 67.45205 0.1311 ASHLAND VOC 24620 67.45205 6.07175247 ASHTABULA CO 8863 24.28219 78.115087 ASHTABULA HC 8863 24.28219 3.042551 ASHTABULA NOX 8863 24.28219 0.43159355 ASHTABULA PM10-PRI 8863 24.28219 1.623493455 ASHTABULA PM25-PRI 8863 24.28219 0 ASHTABULA SOX 8863 24.28219 0.0520325 ASHTABULA VOC 8863 24.28219 2.99420213 ATHENS CO 25800 70.68493 196.874985 ATHENS HC 25800 70.68493 7.267183 ATHENS NOX 25800 70.68493 1.081521 ATHENS PM10-PRI 25800 70.68493 4.037266335 ATHENS PM25-PRI 25800 70.68493 0 ATHENS SOX 25800 70.68493 0.1420925 ATHENS VOC 25800 70.68493 7.128180006

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

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

ACCESS CALCULATOR

Introduction:
Our database programmer set up Access applic ation to calculate Ohio’s aircraft emission inventory, and export those results to Excel. His utility allows for easy modification of the aircraft data to match futu re data scenarios. Ou tput to Excel also allows for additional data manipulation and importation.56 Interface:

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

.

# Appendix C-1 Mobile Source Emissions Inventory for the Canton PM2.5 Nonattainment Area

# PM 2.5 

# 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 44702This 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, whic h 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 Transportati on. This report does not constitute a standard, specification, or regulation.PM 2.5 Conformity Redesignation for Stark County, Ohio Page i TABLE OF CONTENTS

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

On Road Mobile Emission Summary ............................................................................................. Pag e 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 DocumentationPM 2.5 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 Repres entative Socio-Economic Demographic Variables By County 2005-2025............................................................................................. Page 4

Table 3 MOVES Inputs........................................................................................................ Pag e 6

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

Table 5 Ramp Fractions ....................................................................................................... Pa ge 8

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

Table 7 Vehicle-Age Distributio n for Stark County............................................................ Page 10

Table 8 Road-Type Distributi on for Stark County .............................................................. Page 11

LIST OF FIGURES

Figure 1 SCATS Geographic Area Fine Partic ulate Matter Non-Atta inment Area Boundary

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

Figure 2 SCATS Geographic Area Covered by Travel Demand Model and Traffic Analysis Zone Structure.................................................................................................................. Page 5PM 2.5 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

NO X – Nitrogen Oxides

ODOT – Ohio Department of Transportation

OEPA – Ohio Environmental Protection Agency

PM – Particulate Matter PM 2.5 - Particulate Matter with an aerodynamic diameter less than 2.5 mi crons (often referred to as Fine Particulate Matter)

PM 10 – Particulate Matter with an aerodynamic diameter less than 10 microns

SIP – State Implementation Plan

SO 2 – 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 Analys is and Technical Documentation For the Canton/Massillon Metrop olitan Statistical Area State Implementation Plan Inventory Mobile Emission Estimates For the U.S. EPA 1997 Annual PM 2.5 

### National Ambient Air Quality Standard

INTRODUCTION

This memorandum documents the air quality analys es and underlying planning assumptions performed for the Annual PM 2.5 on-road mobile source emission inventor ies for the Canton/Massillon Metropolitan Statistical Area State Implementation Plan (SIP). The Ohio Department of Transportation (ODOT), Division of Transportation Syst em Development-Modeling and Fo recasting Section and the Stark County Area Transportation Study (SCA TS) completed these analyses in coordination with the Ohio Environmental Protection Agency (OEPA).

The SCATS Region is comprised of Stark County, Oh io. The Canton/Massillon Metropolitan Statistical Area (MSA) was classified as nonattainment for PM 2.5 in the Federal Register on January 5, 2005. Although the MSA area also include s Carroll County, OEPA and USEPA concurred that only Stark County is designated as the nonattainment area within th e 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 followi ng 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

PM 2.5 Conformity Redesignation for Stark County, Ohio Page 1 SCATS submitted the necessary Travel Demand Mode l 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 (PM 2.5 ), Nitrogen Oxides (NO x ), and Sulfur Dioxide (SO 2 ) modeled for the SCATS Region. The Model Years for the demonstration includes the Ba se Year 2005, Attainment Year 2008 (a leap year), Interim Year 2015, and Maintenance Year 2025.

Table 1 SCATS REGION ON-RO AD MOBILE EMISSIONS

Direct PM TOTAL Model PM 2.5 Yea r # 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 Yea r # Days NO X (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 Yea r # 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

V MT Model TOTAL VMT V MT Yea r # 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

PM 2.5 Conformity Redesignation for Stark County, Ohio Page 2PM 2.5 Conformity Redesignation for Stark County, Ohio Page 3PM 2.5 Conformity Redesignation for Stark County, Ohio Page 4 LATEST PLANNING ASSUMPTIONS

The annual PM 2.5 inventory runs meet the latest planning -assumption requirements. This report will present the latest population and land use data available that calibra ted the modeling process used to calculate the vehicle emissions for the mobile-emissi ons budgets as well as the input values for U.S. EPA’s most recent emissions software MOVE S for this air-quali ty 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 a nnual emissions estimates will be based a singleseason approach. Since travel demand models pr oduce average daily conditions, the daily emissions estimates are multiplied by 365 days to produce annual em issions estimates expressed in tons per year.

TRAVEL DEMAND MODELI NG - ANALYSIS YEARS

A Travel Demand Model (TDM) is the traditional forecasting tool used to examine potential changes in future travel patterns for a specifi c study area, in this case the Cant on/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 modeli ng process consisting of trip generation, trip distribution, mode choice, and route assignment perf ormed with the Cube Voya ger 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 generate d by the LRTP transportation network.

The current SCATS TDM Validation Y ear 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 extrapolatio n between the 2005 set of variables and the Horizon Year 2030 variables. These networks represent all planned federa l-aid projects as well as any re gionally significan t projects found in the SCATS TIP and LRTP expected to be open for tra ffic 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 cente rs and understanding urban and rura l population changes are essential to determine future transporta tion 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 fact ors over time. In turn, these factors are usef ul for predicting future transportation patterns and justifying transportati on improvements over the next twenty years.

Travel forecasting procedures require the user to delineate the TDM study ar ea into geographic areas called Traffic Analysis Zones (TAZs) . Typically, TAZs are based on fact ors such as land use, area types (urban, suburban or rural), or polit ical government units such as cities, villages, or townships. TAZs represent centers of travel generators or attractors based on a se t of demographic variables. The SCATSMPO collects and reviews the TDM i ndependent variables that character ize 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 includi ng 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-seconda ry [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 develope d 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

PM 2.5 Conformity Redesignation for Stark County, Ohio Page 5Figure 2 SCATS GEOGRAPHIC AREA COVERED BY TRAVEL DEMAND MODEL AND TRAFFIC ANALYSIS ZONE STRUCTURE

PM 2.5 Conformity Redesignation for Stark County, Ohio Page 6EMISSION-FACTOR GENERATION

The MOVES model generated the emission factors for base year-2005 and attainment year-2008 representing the Transportation Improvement Progr am implemented in the SCATS Region. The model also generated emission factors for tw o future year scenarios 2015, and 2025.

Table 3 summarizes the settings used in the MO VES run specification file and the MOVES CountyData Manager. The subsequent ta bles provide the specifi c inputs that are not us ing the MOVES default values.

Table 3 MOVES INPUTS

MOVES Version MOVES2010a Scale Custom Domain MOVES Modeling Technique Emission Factor Method Rates p er Distance Rates p er 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 NO X , All PM 2.5 categories, SO 2 , 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
t yp e and source use t yp e Advance Performance None RunSpec Parameter Settings

PM 2.5 Conformity Redesignation for Stark County, Ohio Page 7Table 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 rela tive 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, provid ed by U.S. EPA, converted the Mobile6 data to get the correct data for the MOVES model. Annual PM 2.5 emissions data were established using the single season methodology. The standard emissions modeling routines establish daily pollutant burdens. Annual direct PM 2.5 , NO x precursor, and SO 2 emissions for the PM 2.5 conformity tests were established by multiplying the daily model results by 365.

PM 2.5 Conformity Redesignation for Stark County, Ohio Page 8Hour 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 prov ided the data for Source-Type Population 51, 52, 53, 61, and 62 while local data from Ohio motor vehicl e registrations accounted for all other Source-Type

PM 2.5 Conformity Redesignation for Stark County, Ohio Page 9Population needed to run the MOVES model. Table 6 shows the Source-Type Population identifications, the corresponding Source-Type Name, a nd 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 Truc k 1,063 62 Combination Long-haul Truc k 1,223 sourceTypeID sourceTypeName sourceTypePopulation

VEHICLE-AGE DISTRIBUTION

A grouping of data from Ohio sources along with th e 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.

PM 2.5 Conformity Redesignation for Stark County, Ohio Page 10Table 7 VEHICLE-AGE DISTRIBUTION FOR STARK COUNTY, OH

Year Source T y pe A g e Fraction Yea r Source T y pe A g e 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

PM 2.5 Conformity Redesignation for Stark County, Ohio Page 11ROAD-TYPE DISTRIBUTION

The ODOT Division of Highways produced a summary of Vehicle Miles Traveled (VMT), categorized by federal functional class, for St ark County. This summary was used as the basis for the Road-TypeDistribution Fractions. Table 8 i llustrates 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

PM 2.5 Conformity Redesignation for Stark County, Ohio Page 12PM 2.5 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 traffi c distributions as well as more up- to-date volume/delay functions from the 2000 Highway Capacity Manual (HCM). This pro cess, 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 invol ves running postcms.exe to calculate hourly link volumes based on the percentage of the daily volume (t ravel demand model output) determin ed by a link’s facility and area type. The analysis does not use the link speeds fro m 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 progra m. 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. Th e total link on-road vehicle emission s for the area is the sum of all individual link-hour emissions.

The third step, (vehcalm.e xe), calculates vehicle-based emissions for each source type for each hour of the day. A combination of local a nd default data is the source for the vehicle source type. The final vehicle emissions are the sum of all individua l 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 tr ips that use local roads to travel within a zone. The intracalm.exe program uses intrazonal trips to esti mate 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 radi us 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 in trazonal emissions for each pollutant, and analyzed year, and to multiply annual average daily em issions 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 re sponsible 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 atta inment 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 a nd 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 Cl eve. We will be asking they be incorporated as the defaults in MOVES but that won't happen until afte r 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 th e IAC group for a thorough look see.
Also, we had a note in our spreadsheet that we w ould also need to MOVES based PM2.5 for the Canton area to be updated - since this is an area we have n'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 anal ysis we are doing. So we c ould 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" <Caro lina.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 maintenan ce 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; jr dutton@co.stark.oh.us; areser@oki.org; B Davis; ngill@morpc.org; aramirez@mvrpc.org; ssalameh@ntelo s.net; tmazur@lacrpc.com; smapel@lcounty.com; mhilll@lcounty.com; randy.durst@movrc.org; sschmid@c larkcountyohio.gov; daniel@clarkcountyohio.gov; mikepap@bhjmpc.org; gedeon@tma cog.org; rsharma@belomar.or g; krodi@eastgatecog.org; pompeo@eastgatecog.org; morris.patricia@epa mail.epa.gov; frank.burkett@fhwa.dot.gov; Mark.byram@dot.state.oh.us; NINO.BRUNELLO@DOT.STATE.OH.US; Dave.moore1@dot.state.oh.usCc: 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@akr onohio.gov; jrdutton@co.stark.oh.us; Andy Reser; ngill@morpc.org; aramirez@mvrpc.org; ssalameh@ntelo s.net; tmazur@lacrpc.com; smapel@lcounty.com; mhilll@lcounty.com; randy.durst@movrc.org; sschmid@c larkcountyohio.gov; daniel@clarkcountyohio.gov; mikepap@bhjmpc.org; gedeon@tma cog.org; rsharma@belomar.or g; krodi@eastgatecog.org; pompeo@eastgatecog.org; morris.patricia@epa mail.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; VanderWiel en, 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 se parate issue. Existing Mobile6 based budgets must be update d to MOVES so that conformity determinations can continue post March 2012. I’m hoping that we (meaning NOACA) can co mplete 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 ho w closely? For example should a 2020 network from the prior effort be used, or a curren t 2020 network? If we us e 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 star t 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 sta ff 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

T O THE ATTENTION OF D IVISION A IR QUALITY AND PLANNING STAFF :
The purpose of this email is to inform you that EP A finalizes a conformity rule to extend the grace period that provides an additional 12 months be fore the MOVES model is required for regional emissions for transportation conformity determinations.

On March 2, 2010, EPA approved the MOVES model for regional conform ity analysis and established a two-year grace period. As a result of the grace pe riod 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 prev iously 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.s tate.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@d ot.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 ha ving 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 interagenc y 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.

ThanksDM

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 1 st . 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 th e T-Plan Update and Conformity Determination documentation will need to be submitted to US DOT/EP A by 5/1/13. This conformity work needs to be MOVES based. So, the SIP revision must be fully a pproved or have budget adequacy finding in time for SCATS’ T-Plan/TIP approval/conformity finding s. So backing up some more, OEPA needs a minimum 45 days to incorporated SCATS’ results in th e 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 Redesignatio ns 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 interagenc y 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 upda te 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 wi th 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 routine ly 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 inco rporate mobile numbers in with all the other pollutant sectors to determine our possible safety margin option s 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) 644-3696Fax (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 Dist ribution, and Road Type Distribution. Do we need to produce similar tables? Ifso, 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 2 nd for the ozone documentation. Those values are assumed to be constant. You just need to change the year on the Age Dist ribution 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@e pa.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 need ed. OKI’s methodology for using MOVES was done independent of what was used for the rest of the state. Je ff, 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 mo del if different from the OKI/MVRPC models. - I removed all of the Massillon refere nces; ”Dayton-Springfield” was used because the MPOs have two separate models. - Please check my usage of SCATS vs. Stark County; I trie d 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 ar ea is located in northeast Ohio and includes Stark County.

The area has two monitors measuring PM 2.5 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 s hown in Table 1. The design values calculated for the Canton-Massill on area show that the annual PM 2.5 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/a irs/airsaqs/index.htm
However, based on Section 107(d)(3)(E)( i) of the Clean Air Act (CAA), the PM 2.5 monitoring data has to show that the thr ee-year average of the annual mean values, based on data from all monitoring sites in t he area or its affected downwind environs, are below 15.0 μ g/m 3 . Moreover, in accordance with the CAA Amendments, three complete years of monitoring data are required to demonstrat e attainment at a monitoring site. In addition, U.S. EPA regulati ons 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 captur e 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% c apture requirements, Ohio EPA prepared a statistical analysis using im putation and subsequent Bootst rap analysis. Missing values for site 39-151-0017 were generated and subjected to or dinary analysis as if the imputed values were real m easurements (this approach is us ually better than excluding subjects with incomplete data). Most met hods for the accounting of incomplete data can be complex; the im putation/Bootstrap met hod 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 Yearis a pro d resampl
Briefly, t from a r used to monitor generat e random a pseu d was pe r regressi missing set of 1 perform e
Imputi n

Choice monitor ( approxi m having 7 proximit y the sa m monitor

. interest

Figure 1:

For sim p d uct of the ing iteratio n

t he imputa t
r eference m establish a and valu e e concentr a

resamplin g d o-confiden

r formed b y on analysi data, follo w 1 000 slope
e d.

n g missing

of refere n ( s) in ques t
m ately 30 7 5% or b e y of these m
m e or simil a

The loca t located in S

Monitor Lo c

p lification, w need to p e
n s were co

t ion of mis s
m onitor wit h
a mathema t
e s in the i n a tion value s g of the re s ce interval y randomly

s, then a d

w ed by the and inter c

data for C

n ce monito t ion. Near e km to the
e tter captu r

m onitors t o a r air mass e

t ion of the s S tark Coun

c ations

w e will refe r e rform the

n ducted.

s ing values h a more c o t ical relatio n
n complete
s for missi n s iduals fro m

for the ch o resamplin d ding thes e

re-calcula t
c epts pair s

C anton-Ma s

r was init i
e st monitor s

north, in A e in all qu
o the Canto
e s, and ar e s e potentia l

ty, is show

r to site 39

- Bootstrap

was perfo
o mplete d a
n ship betw e data set.

n g data. T h

m the regre s o sen regre s g, with re p e residual s t ion of the r s , on whic h

s sillon PM

i ally base d
s (39-153- 0 A kron, Oh i arters fro m n-Massillo n e thus likel y l reference n in Figure

- 151-0017 a resamplin g

rmed usin g a ta record.
e en values This relati h e Bootstr a s sion anal y s sion mod e p lacement,
s to the “ b

r egression h further s

2.5 nonatt

d on the p 0 017 and 3 i o (Summi t
m 2003 to
n monitors s y candidat e

monitors, 1.

a s Site A, 3 g many tim e

g PM 2.5 co n

Regressi o s recorded a

onship wa
a p techniqu e y sis, was u s e l. The Bo o

the real r b est guess ”

constants.
s tatistical a

ainment a r

p hysical p 3 9-153-002 t County). 2011, the suggests t h
e s to serve as well as

3 9-151-00 2 e s. Here,

n centration
o n analysis
a t the refer s then us e e, based o n s ed to calc
o tstrap an a
r esiduals o f

” values o f The resul t
a nalysis ca

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roximity o f 3) were lo c In additi o relatively c h at they sa as a refe r the monit o

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f the
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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 desi gn values that meet the PM 2.5 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 capt ure in the first quarter of 2009.

The imputation and Bootstrappi ng procedures will generate the necessary missing data to provide a re-calculated 2009-2011 design value for Site A.
2. Correlation, Quarterly Data Ca pture, and Data Site Pairing

Although location is a cr itical factor in determining the su itability 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 r egression of the reference monito r to Site A was performed. In a linear regression, the relationship between a dependent variabl e (Site A data), Y, and an independent variabl e, X (Site C or D data), is asse ssed. The familiar straight line regression model, Y = mX + b was used her e. Under this model, linear regression finds the straight line that minimizes t he 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, R 2 , describes the degree of relationship between two variables 1 (variables or site c oncentrations in Site A and C and D). R 2 is only a descriptive statistics. Roughly spea king, we associate a high value of R 2 with a good fit of the regression li ne and associate a low value of R 2 with a poor fit.
Secondly, the mean of the quarterly dat a captured (the mean of the percentage captured) allowed the central tendency of each site to be ve rified, providing a second

1 An R 2 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 exac tly 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

‐ 201 0 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 Valuemeans 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 signifi cant as the correlation or mean of the percentage captured, pairing the site data seeks to reduce vari ability between data sets. Particular focus was placed on 2009-2011, the period for which the redesignation request is based upon and the period in wh ich Site A demonst rated 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 60Site A Concentration (μg m-3)

Site C Concentration ( μ g 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

Coefficient s Standard Erro r 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 1310Figure 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 60Site A Concentration (μg m-3)

Site D Concentration ( μ g m -3 ) 

### Site A vs Site D Linear Regression

ANOVA df SS MS F S ignificance 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 812Table 3: Quarterly Data Capture

A B CD 2003 Q1 93% 87% 86% 90% 2003 Q2 97% 97% 89% 88% 2003 Q3 90% 90% 91% 91% 2003 Q 4 87% 97% 90% 97% 2004 Q1 87% 87% 98% 84% 2004 Q2 93% 90% 92% 92% 2004 Q3 97% 90% 96% 99% 2004 Q 4 70% 73% 98% 97% 2005 Q1 80% 83% 92% 80% 2005 Q2 84% 90% 94% 100% 2005 Q3 93% 90% 100% 100% 2005 Q 4 87% 77% 90% 94% 2006 Q1 93% 97% 100% 100% 2006 Q2 90% 83% 100% 93% 2006 Q3 97% 23% 100% 90% 2006 Q 4 90% 100% 97% 97% 2007 Q1 97% 93% 97% 100% 2007 Q2 93% 93% 100% 100% 2007 Q3 74% 58% 100% 97% 2007 Q 4 30% 30% 87% 93% 2008 Q1 0% 0% 87% 97% 2008 Q2 40% 53% 100% 90% 2008 Q3 84% 71% 100% 94% 2008 Q 4 97% 90% 100% 93% 2009 Q1 67% 87% 77% 93% 2009 Q2 91% 84% 97% 90% 2009 Q3 99% 90% 91% 97% 2009 Q 4 93% 90% 100% 94% 2010 Q1 84% 97% 99% 90% 2010 Q2 88% 77% 100% 90% 2010 Q3 96% 97% 100% 97% 2010 Q 4 96% 97% 100% 84% 2011 Q1 97% 97% 91% 100%
2011 Q2 96% 97% 93% 93%
2011 Q3 84% 87% 100% 90%
2011 Q4 92% 97% 100% 100%
MEAN 84% 82% 95% 94%
MEAN: 2009

‐ 2011 90% 91% 96% 93%QuarterlyDataCapture2003‐2011 Monitoring SitesTable 4: Paired Data by Site and Quarter

The R 2 value of the linear regression for Site A and Site C is 0.8753, and the R 2 value for Site A and Site D is 0.8807. Thus, the linear relationship betw een Site A and Site D is stronger than that of Si te A and C, although this difference is marginal. By examination of the m ean quarterly data capture (Table 3) , in particular between 2009 and 2011, Site C demonstrates 96% data captur e, 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 pairi ngs 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 per iod. Although the R 2 value of Site A vs Site C was somewhat smaller than that of Site A and Site D, th is difference was consi dered negligible, and Site C was used as the reference monitor in the data imputation pr ocedure. However, due to the greater R 2 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 a nd Bootstrap Analysis
Data imputation was conducted using the mat hematical 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 an d b = 1.2388. After applying the above equation to al l 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 missi ng data. It should be noted that both before and after inclusion of the imputed dat a, Site A demonstrated a passi ng 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) Annual Design Value YearA s stat e referen c annual a 15.3, 1 4 Site C ( 1

To pro v averag e mean, s (b) use d Bootstr a adds t h calculat e Bootstr a pseudo

intercep respecti v

Figure 4:

Fi

g ar

e e d previous
c e monitor
a verages u 4 .3, and 13 1 5.2, 15.4,

v ide a me a e design va
s tandard d e d to gener a a p analysis h ose resa m e s a ne w a pped slop e

- confidenc e t from the B

v ely.

Distributio n

g ure 4: Histo g e a re p resent s

ly, the imp u for the sa k

u sing impu t

. 0, respect i 14.2, and 1

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w slope a n

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n of Slope V a

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the 95% co n u tation pro c k e of com p t ed data w i vely. The s 1 3.2) as th e

o nfidence i
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n d 95% co n p lacement d

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n d interce p c ept value s c an be de
a nalysis of

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o

pe va l ues f ro
n fidence inte r c edure wa s p arison. F o ith Site D a s e values a e reference

n the imp u a lysis was c
n fidence in t d ata value s the real re t he imput e p t at eac h
s were cal c termined. Site A vs S

o m a 1000 it e
r val. s also con d
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c ulated, fro m

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e ration Boots t d ucted usi n 007, 2008,
e rence mo n
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in Table 5

a s well as This ana l h e slope ( m A

. A s det a

m the regr e alues, an d . Thus,

m which a

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s hown in F i

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n itor were
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.

the three

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15.1, with

- year d ed a

r cept , the l ysis, ently

r s of

95% and

n d 5,

dFigure 5:

The res Bootstr a imputati the acc u using th design v This an a

Table 6: I

Lowe r Impute d

Uppe r

From T a replace Fi

g sh a Distributio n

ultant mea
a p analysi s on perfor m
u racy of th e upper an
v alues for a a lysis is su m

I mputed Qu a

2 0

Q

r 95% 1 3 d Value 1 3

r 95% 1 3

a ble 6, it c a

missing va g ure 5: Histo g a ded area re p n of Intercep t

n of the sl o s compare
m ed at Site

e regressi o d lower bo u a ll quarters

m marized i n

a rter Averag e Qua 0 04 Q 4 2007 Q3
3 .26 18.20
3 .4 18.4
3 .56 18.55

a n be show n

lues at Sit e g ram of the in p resents the 9 t Values

o pe, m boot

favorably A, m = 0. 9
o n model u
u nds of th e in which S i

n Table 6.

e s with Upp e
rter with <7 5 2007

Q4
13.43
13.8
14.08

n that in e a e A, the qu a

tercept value 9 5% confide n

= 0.9722, a

to those 9 721 and b

u sed to im p e 95% confi

i te A demo

e r and Lowe r 5 % Data Capt u

2008

Q1 2 0 Q
15.68 1 2
16.3 1 2
16.91 1 2

a ch quarter
a rterly aver a s from a 100 0
n ce interval.

a nd interc e values a c b = 1.2388

. p ute missi n dence inte r nstrated le s

r 95% Confi d

u re 0 08 Q 2 200 9 Q1
2 .08 15.2 7
2 .4 15. 4
2 .70 15.4 9

for which i age was w e 0

iteration B o

e pt, b boot = c tually use d

. Addition a
n g data ca n
r val to calc u s s than 75 %

d ence Value s

9

7
4
9

mputed da ell within t h o otstrap anal y

1.240 fro m

d for the
a l confiden c
n be gain e
u late a ran g % data ca p

s

ta were us e h e 95% ps e y

sis. The

m the data
c e in
e d by

g e of p ture.

e d to
e udo-confidence interval resulting from the 1000 iteration Bootstrap anal ysis. This suggests that the slope and intercept used to generate the imputed va lues are representative of the relationship between Site A and Site C, and therefore su itable for generating replacements for missing data values. It s hould 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 PM 2.5 NAAQS of 15.0 μ g m -3

. In summary, the PM 2.5 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 va lid 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 val ues 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 PM 2.5 standard is calculated as the three-year average of annual 98 th percentile 24-hour average valu es, recorded at each monitor. As with the annual standard, U.S. EPA regul ations require at least 75% da ta capture in each quarter of a consecutive 3-year period in order for the 24-hour standard to be va lid, 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 re cord of 24-hour design values for both PM 2.5 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 DataTable 8: Stark County 24-hour Design Values

For the 2009-2011 period, mo nitor 39-151-0020 demonstrat es 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 Si te A derived from reference monitor 39-153-0017 (Site C) from which the annual design values were calculated, new annual 98 th percentile values and thr ee-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 incr eased the number of cr editable 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 98 th percentile values or the thr ee-year averages. With im puted data, monitor 39-151-0017 demonstrates a passing value of 30 for th e 2009-2011 period, with sufficient data to meet the 75% c apture 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

‐ 17 OLD 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

‐ 17 NEW 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 NoticePublic 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 Environment al Protection Agency (Ohio EPA) is requesting that the United States Environment al Protection Agency (U.S. EPA) revise the current ai r quality designation for the Canton-Massillon area (Stark County), to attainment with respect to the 1997 annual and the 2006 24-Hour PM 2.5 national ambient air quality standards (NAAQS). Air qualit y monitoring data collected between 2009 and 2011 in the region demonstrate attainment of t he 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 PM 2.5 standards in this area at least ten years into the future.
Computer models show that existing stat e and federal emission reduction requirements are sufficient to attain and maintain the NAAQS in the Canton-Massillon area. Therefore, Ohio EPA proposes to utilize ex isting emission inventory information and projections of future emissions as the dem onstration of the abilit y to maintain the NAAQS in the Canton-Massillon area in the future.

The Canton-Massillon area is currently des ignated as nonattainment for the 1997 annual and 2006 24-Hour PM 2.5 standard. As part of an a cceptable maintenance plan, Ohio EPA has developed, as r equired, a contingency plan to provide for additional emission reductions if a viol ation of the NAAQS is moni tored after the area has been redesignated.
The State of Ohio proposes to:
1. Request the U.S. EPA redes ignate the Canton-Massillon area to attainment with respect to the 1997 annual and 24-Hour PM 2.5 NAAQS and revise the maintenance plan. This request will document that existing enforceable control measures are responsible for the obs erved improvement in air quality.
2. Designate existing controls as sufficient to maintain the NAAQS into the future.
3. Commit to the proposed contingency plan.

These actions must be noticed to allo w public comment and to satisfy USEPA requirements for public involvement in SIP-re lated activities. This notice addresses Ohio EPA’s reliance on the emission projections as evidence of attainment and maintenance and the commitment to instit ute contingency measures if ambient exceedances orviolations trigger the contingency plan r equirements. 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 att end 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 stat ements 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 Niamlar b at 614-728-1342; other questions or comments about this document should be dire cted 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

25Division of Air Pollution Control
Response to Comments
Redesignation Request and Maintenanc e 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 Magnol ia, OH on June 6, 2012, regarding the Redesignation Request and Maintenance Plan for the Canton-Massillon Annual and 24- Hour PM 2.5 Nonattainment Area. This document summarizes the comments and questions received at the pu blic 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 doc ument, the questions are grouped by topic and organized in a consistent format. The name of the commenter follo ws the comment in parentheses.

Ohio EPA received oral testimony from the Stark County Regional Planning Commission and the Stark County Area Tr ansportation 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 Nonattain ment Area. These testimonies can be found in this submittal.