APPENDIX A 

Air Quality System Data 
This page left intentionally blank 
Appendix A-1 (DRAFT) 

Air Quality System (AQS) Data Report 

2006 Through September 2011 (current as of October 3, 2012) 

Air Quality System (AQS) Data Report

EXCEPTIONAL DATA TYPES

EDT DESCRIPTION

0 NO EVENTS

1 EVENTS EXCLUDED

2 EVENTS INCLUDED

3 EXCEPTIONAL EVENTS EXCLUDED

4 NATURAL EVENTS

EXCLUDED

5 EVENTS WITH CONCURRENCE EXC

6 EXCEPTIONAL EVENTS WITH CONC

7 NATURAL EVENTS WITH CONCURR

Indiana Par

State

County

SiteID

Paramete

r Code

(Ozone)

POC Year ADDRESS

% ofOBS

1st

Max 8‐

HR

2

Ma

H

18 89 22 44201 1 2006 MISSISSIPPI ST., IITRI BUNKER 98 0.078 0

18 89 22 44201 1 2007 MISSISSIPPI ST., IITRI BUNKER 79 0.089 0

18 89 22 44201 1 2008 MISSISSIPPI ST., IITRI BUNKER 93 0.077 0

18 89 22 44201 1 2009 MISSISSIPPI ST., IITRI BUNKER 96 0.061 0

18 89 22 44201 1 2010 MISSISSIPPI ST., IITRI BUNKER 80 0.08 018 89 22 44201 1 2011 MISSISSIPPI ST., IITRI BUNKER 98 0.083 0

18 89 30 44201 1 2006 1 OLIVER ST/ WHITING HIGH SCHO 100 0.086 0
Appendix A-2 (DRAFT) 

18 89 30 44201 1 2007 1 OLIVER ST/ WHITING HIGH SCHO 99 0.094 0

18 89 30 44201 1 2008 1 OLIVER ST/ WHITING HIGH SCHO 79 0.066 0

18 89 30 44201 1 2009 1 OLIVER ST/ WHITING HIGH SCHO 100 0.071 018 89 30 44201 1 2010 1 OLIVER ST/ WHITING HIGH SCHO 100 0.072 0

18 89 30 44201 1 2011 1 OLIVER ST/ WHITING HIGH SCHO 100 0.075 018 89 2008 44201 1 2006 0 141 ST STREET 100 0.082 018 89 2008 44201 1 2007 0 141 ST STREET 96 0.087 0

18 89 2008 44201 1 2008 0 141 ST STREET 97 0.072 0

18 89 2008 44201 1 2009 0 141 ST STREET 99 0.076 0

18 89 2008 44201 1 2010 0 141 ST STREET 92 0.073 0

18 89 2008 44201 1 2011 0 141 ST STREET 91 0.074 0

18 127 24 44201 1 2006 DIANA RD/ WATER TREATMENT PLAN 100 0.076 0

18 127 24 44201 1 2007 DIANA RD/ WATER TREATMENT PLAN 97 0.091 0

18 127 24 44201 1 2008 DIANA RD/ WATER TREATMENT PLAN 100 0.082 0

18 127 24 44201 1 2009 DIANA RD/ WATER TREATMENT PLAN 100 0.073 

18 127 24 44201 1 2010 DIANA RD/ WATER TREATMENT PLAN 99 0.08 0

18 127 24 44201 1 2011 DIANA RD/ WATER TREATMENT PLAN 90 0.082 0

18 127 26 44201 1 2006 0 WESLEY/ VALPARAISO WATER DEP 99 0.078 0

18 127 26 44201 1 2007 0 WESLEY/ VALPARAISO WATER DEP 93 0.084 0

18 127 26 44201 1 2008 0 WESLEY/ VALPARAISO WATER DEP 96 0.066 0

18 127 26 44201 1 2009 0 WESLEY/ VALPARAISO WATER DEP 100 0.076 0

18 127 26 44201 1 2010 0 WESLEY/ VALPARAISO WATER DEP 100 0.063 0

18 127 26 44201 1 2011 0 WESLEY/ VALPARAISO WATER DEP 97 0.077 0
APPENDIX B 

Historic and Projected Emission Inventories 

Lake and Porter Counties, Indiana 
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Appendix B-1 (DRAFT) 

Fourth Highest Daily Values 

Site 2006 2007 2008 2009 2010 2011 06-08 

avg 

07-09 

avg 

08-10 

avg 

09-11 

avg 

Gary 0.073 0.085 0.062 0.058 0.064 0.066 0.073 0.068 0.061 0.062 

Hammond 0.075 0.077 0.068 0.065 0.069 0.072 0.073 0.070 0.067 0.068 

Ogden Dunes 0.070 0.084 0.069 0.067 0.067 0.068 0.074 0.073 0.067 0.067 

Valparaiso 0.071 0.080 0.061 0.064 0.061 0.063 0.070 0.068 0.062 0.062 

Whiting 0.081 0.088 0.062 0.062 0.069 0.069 0.077 0.070 0.064 0.066 

Graph 3.1 Design Values for Lake and Porter Counties, Indiana, 2009-2011

0.062

0.068

0.067

0.062

0.066

0.06

0.065

0.07

0.075

0.08

Gary Hammond Ogden 

Dunes

Valparaiso Whiting

parts per million

Design Value 8-Hour Standard
Appendix B-2 (DRAFT) 

Historic Ozone Design Values 

 Gary Hammond Ogden Dunes Valparaiso Whiting 

98-00 0.084 0.088 0.091 0.086 n/a 

99-01 0.084 0.090 0.09 0.083 n/a 

00-02 0.084 0.092 0.09 0.086 n/a 

01-03 0.084 0.090 0.087 0.086 n/a 

02-04 0.078 0.083 0.082 0.084 n/a 

03-05 0.076 0.078 0.078 0.077 n/a 

04-06 0.075 0.076 0.076 0.073 0.077 

05-07 0.082 0.079 0.081 0.076 0.085 

06-08 0.073 0.073 0.074 0.070 0.077 

Graph 3.2 Design Values for Lake and Porter Counties, Indiana 2000-2011 

0.065

0.070

0.075

0.080

0.085

0.090

0.095

00-02 01-03 02-04 03-05 04-06 05-07 06-08 07-09 08-10 09-11

parts per million

Design Value 1997 8-Hour Ozone Standard (0.085 ppm) 2008 8-Hour Ozone Standard (0.075 ppm)
Appendix B-3 (DRAFT) 

Emission Inventories for Lake and Porter Counties, Indiana 

NOx and VOC Point Source Trends 

Lake and Porter Counties, Indiana 

(Tons per Summer Day)

Year NOx VOC 

2001 209 29 

2003 154 23 

2005 123 21 

2007 120 23 

2009 94 23 

Graph 4.1 Lake and Porter Counties, Indiana NOx Point Source Emissions 2001-2009 

209

154 123

120

94

0

50

100

150

200

250

2001 2003 2005 2007 2009

Tons per Summer Day

Year

Graph 4.2 Lake and Porter Counties, Indiana VOC Point Source Emissions 2001-2009 

29

23

21

23 23

0

5

10

15

20

25

30

35

2001 2003 2005 2007 2009

Tons per Summer Day

Year
Appendix B-4 (DRAFT) 

NOx Emissions – NW Indiana Electric Generating Units 

1999-2011 (Tons per Ozone Season) 

NOx Emissions – Indiana Electric Generating Units 

1999-2011 (Tons per Ozone Season) 

1999 31,815 1999 149,660 

2000 25,028 2000 133,880 

2001 27,394 2001 136,121 

2002 19,260 2002 114,083 

2003 17,966 2003 98,482 

2004 11,419 2004 66,568 

2005 10,537 2005 55,390 

2006 9,567 2006 53,768 

2007 11,230 2007 54,816 

2008 10,833 2008 59,967 

2009 7,305 2009 39,457 

2010 7,030 2010 45,687 

2011 5,300 2011 37,068 

Graph 4.3 NOx Emissions - Northwest Indiana Electric Generating Units. 1999-2011 

Graph 4.4 Statewide NOx Emissions from Electric Generating Units, 1999-2011 
Appendix B-5 (DRAFT) 

NOx Emission Trends – Lake and Porter Counties, Indiana (Tons per Summer Day) 

Year Area Non-Road Mobile Point Total 

2001 6.99 50.21 77.28 208.95 343.43 

2003 5.50 32.14 65.22 154.35 257.21 

2005 4.62 30.93 57.17 122.73 215.45 

2007 5.28 24.75 53.15 119.57 202.75 

2009 5.6 21.66 45.11 93.6 165.97 

Graph 4.7 NOx Emission Trends by Category and Year, Lake and Porter Counties, 

Indiana, All Sources, 2001-2009 

0

50

100

150

200

250

300

350

400

Area Non-Road Mobile Point Total

Tons per Summer Day

2001 2003 2005 2007 2009

Graph 4.5 NOx Emissions Trends - Lake and Porter Counties, Indiana 

All Sources, 2001-2009 

343.43

257.21

215.45 202.75

165.97

0.00

50.00

100.00

150.00

200.00

250.00

300.00

350.00

400.00

2001 2003 2005 2007 2009

Tons per Summer Day

Year
Appendix B-6 (DRAFT) 

VOC Emission Trends – Lake and Porter Counties, Indiana (Tons per Summer Day) 

Year Area Non-Road Mobile Point Total 

2001 50.38 19.55 23.48 29.21 122.62 

2003 27.31 21.02 20.96 23.28 92.57 

2005 27.1 19.55 17.19 20.57 84.41 

2007 27.02 10.69 15.93 22.62 76.26 

2009 26.97 6.26 13.42 23.14 69.79 

Graph 4.8 VOC Emission Trends by Category and Year, Lake and Porter Counties, 

Indiana, 2001-2009 

0

20

40

60

80

100

120

140

Area Non-Road Mobile Point Total

Tons per Summer Day

2001 2003 2005 2007 2009

Graph 4.6 VOC Emissions Trends - Lake and Porter Counties, Indiana, 2001-2009 

122.62

92.57

84.41

76.26

69.79

0

20

40

60

80

100

120

140

2001 2003 2005 2007 2009

Tons per Summer Day

Year
Appendix B-7 (DRAFT) 

Projected Emissions Inventory 

Graph 4.9 Comparisons of 2005 and 2010 (Estimated) and 2020 and 2030 (Projected) NOx

Emissions for Lake and Porter Counties, Indiana 

0

50

100

150

200

250

Area Non-Road Mobile Point Total

Tons per Summer Day

2005 2010 2020 2030

Graph 4.10 Comparisons of 2005 and 2010 (Estimated) and 2020 and 2030 (Projected) 

VOC Emissions for Lake and Porter Counties, Indiana 

0

20

40

60

80

100

120

140

Area Non-Road Mobile Point Total

Tons per Summer Day

2001 2003 2005 2007 2009

NOx Emission Inventory, Lake and Porter Counties, 

Indiana (Tons per Summer Day) 

VOC Emission Inventory, Lake and Porter 

Counties, Indiana (Tons per Summer Day) 

Sector 2005 2010 2020 2030 2005 2010 2020 2030 

Area 4.62 4.67 4.69 4.74 27.1 29.17 27.93 25.8 

NonRoad 30.93 20.92 14.22 9.76 19.55 17.76 13.82 10.47 

Mobile 57.17 41.09 14.52 11.56 17.19 12.16 5.21 4.66 

Point 122.73 107.00 84.56 76.89 20.57 18.69 22.94 27.88 

TOTAL 215.45 173.68 117.99 102.95 84.41 77.78 69.9 68.81 
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APPENDIXC 

MOVES20 1 Oa Input Data and Parameters, Lake and Porter Counties, 

Indiana 
This page intentionally left blank 
Lake and Porter Counties 

MOVES2010a Input Data and 

Parameters 

INDOT Planning Contract 

Final Report 

October 2, 2012 

CDMth sm• 
Table of Contents 

Overview .................. .. ................................... ....................................................................... 1 

Vehicle Age Distribution .......................................................................... ............................. 1 

Vehicle Population ........................................................... .. ............... .................................... 2 

Meteorological Data .............................................................................................................. 4 

Default VMT Distributions ........................................................ ............................................. 4 

Default Hourly Distributions .................................................................................................. 5 

Default Daily and Monthly Distributions ................................................................................ 6 

Ramp Fractions ..... ............................................................................................................... 6 

LIST OF TABLES 

Table 1: MOVES201 Oa Source Type Codes ............................................................................. 1 

Table 2: MOVES201 Oa Road Type Codes ....................................... ... ...................................... 1 

Table 3: Distribution of MOBILE 6.2 Light Duty Trucks into MOVES Source Types ................... 3 

Table 4: Inventory of Permanent Count Stations ....................................................................... 5 

LIST OF APPENDICES 

Appendix A- MOVES201 Oa Input Settings and Assumptions 

Appendix 8- Vehicle Age Distributions for Lake and Porter Counties 

Appendix C- Vehicle Populations for Lake and Porter Counties 

Appendix D- Meteorological Data for Lake and Porter Counties 

Appendix E- Default Statewide Factors 

Appendix F- Statewide Default Hourly Distribution Factors 

Appendix G - Statewide Default Daily Distribution Factors 

Appendix H- Statewide Default Monthly Distribution Factors 

Appendix I - Ramp Fractions 
Overview: 

This report is being written to document the input parameters for a set of MOVES201 Oa 

runs for the Lake and Porter Counties 8-hour Ozone Maintenance Area and the Lake 

and Porter Counties PM 2.5 non-attainment area. This report contains a discussion on 

the intended input settings used in MOVES2010a and the development of the input 

data sets. These MOVES201 Oa runs are intended to develop a default set of emission 

rates that can be used for conformity determination and is part of a statewide effort being 

conducted by the Indiana Department of Transportation (INDOT). 

Throughout this report references are made to MOVES 201 Oa codes for two types of 

data. The values for the source type codes are shown in Table 1. The values for the 

road type codes are shown in Table 2. MOVES2010a input settings and assumptions for 

this effort are shown in Appendix A. 

Table 1: MOVES201 Oa Source Type Codes 

sourcetypeid Description 

11 Motorcycles 

21 Passenger Car 

31 Passenger Truck 

32 Light Commercial Truck 

41 Intercity Bus 

42 Transit Bus 

43 School Bus 

51 Refuse Truck 

52 Single Unit Short-haul Truck 

53 Single Unit Long-haul Truck 

54 Motor Home 

61 Combination Short-haul Truck 

62 Combination Long-haul Truck 

Table 2: MOVES201 Oa Road Type Codes 

roadtypeid 

Vehicle Age Distribution: 

1 

2 

3 

4 

5 

Description 

Off Network 

Rural Restricted Access 

Rural Unrestricted Access 

Urban Restricted Access 

Urban Unrestricted Access 

The vehicle age distributions for MOVES source types 21, 31 , and 32 (cars, passenger 

trucks, and light commercial vehicles respectively) were developed through an analysis 

of Indiana's 2009 vehicle registration data. The analysis was performed by Eastern 

Research Group (ERG) under contract to the Lake Michigan Air Directors Consortium 

(LADCO). ERG was provided with vehicle identification numbers (VIN) for vehicles in 

Indiana. 
There were approximately 6.37 million VINs in the statewide data set. Out of these, 

approximately 1.3 million returned errors. Of these, approximately 200,000 errors were 

deemed non-critical. This means that the model year and vehicle type assigned to the 

records were most likely correct despite there being an error in the VIN decoding. These 

records were included in ERG's analysis. The remaining errors were considered critical 

enough to call into question the accuracy of the model year and vehicle types. These 

critical errors were excluded from ERG's analysis. 

In all, approximately 5.2 million VINs from around the state were used in the analysis. 

Each VIN was associated to a specific county. ERG then developed age distributions for 

each county in the state along with seven combination areas comprised of two or more 

counties each. Additional information on the methodology used to develop the vehicle 

age distributions can be found in a May 28, 2010 report written by ERG for LADCO titled 

MOBILE6 and MOVES Registration Distribution Calculations for Indiana Registration 

Data. Each set of age distributions was provided in both MOBILE6 and MOVES formats. 

The MOVES formatted data will be used for these MOVES201 Oa runs. 

Due to limitations in ERG's VIN decoder, it was not possible to develop vehicle age 

distributions for any source types other than 21, 31, and 32 from the vehicle registration 

data. For all other source types, MOVES201 Oa default vehicle age distributions specific 

to each source types were used. This includes motorcycles and all heavy vehicles. 

Vehicle age distributions for all source types were kept constant for all future years. The 

vehicle age distributions for Lake and Porter Counties as a combined area are shown in 

Appendix B of this report. 

Vehicle Population: 

The vehicle populations for source types 21, 31, and 32 were developed directly from 

the vehicle registration data. All valid records that were identified from the vehicle 

registration data set were used to determine the number of vehicles for each of these 

three source types. The VIN decoded data provided to INDOT contained vehicle types 

according to MOBILE6.2 vehicle categories. There is a direct correlation between 

MOVES source type 21 (cars) and the MOBILE6.2 vehicle type LDV. All valid LDV 

records (those records not excluded from the vehicle age distribution analysis due to 

errors as was described in the section on Vehicle Age Distribution in this report) were 

counted in the vehicle population. 

There is not a direct correlation between MOVES source types 31 (passenger trucks) 

and 32 (light commercial vehicles) and the MOBILE6.2 light truck vehicle types (LDT1, 

LDT2, LDT3, and LDT4). All valid records from the vehicle registration data set for 

MOBILE6.2 light duty trucks were counted in the vehicle populations. The light duty 

trucks were distributed between MOVES source types 31 and 32 as per the 

Environmental Protection Agency's (EPA) guidance documented in Table A.1 of the 

appendix of the Technical Guidance on the Use of MOVES2010 for Emission Inventory 

Preparation in State Implementation Plans and Transportation Conformity. The guidance 

provides two sets of factors for distributing MOBILE6.2 light trucks between MOVES 

source types 31 and 32. These are based on fuel type and are shown in Table 3. 

2 
Table 3: Distribution of MO 8 ILE 6.2 L19 ' h t Duty Trucks in to MOVES Source Types 

Source Types 

Fuel 31 32 

Gas 78% 22% 

Diesel 42% 58% 

As per ERG's assumption documented in MOBILE6 and MOVES Registration 

Distribution Calculations for Indiana Registration Data, all light duty trucks that did not 

have a fuel type identified were counted as diesel trucks. This was to prevent an 

underestimation of diesel trucks and their related emissions. 

Since only valid records from the vehicle registration data were used to calculate vehicle 

populations for source types 21, 31, and 32, it is reasonable to assume that some of the 

erroneous records that were discarded from the analysis actually belonged to these 

source types. The nature of these errors is not that the vehicle does not exist. Rather, it 

is that the vehicle could not be properly identified with any sense of certainty. It was 

therefore necessary to adjust the vehicle populations calculated from vehicle registration 

data to compensate for these discarded records. Based on an analysis of the error rate 

reported by ERG, vehicle populations for source types 21, 31, and 32 were increased by 

5.8 percent. 

Vehicle populations were not able to be developed directly from the vehicle registration 

data for some source types. This was due to the limitations in the VIN decoder used by 

ERG to process the vehicle registration data. Vehicle populations for all other source 

types (motorcycles and heavy vehicles) were derived by applying the Mileage 

Accumulation Rate (MAR) method documented in EPA's Technical Guidance on the Use 

of MOVES201 0 for Emission Inventory Preparation in State Implementation Plans and 

Transportation Conformity, Section 3.3 Source Type Population. 

The default MARs were extracted from MOVES by running MOVES for a single pollutant 

and a single year for all vehicles, fuels, months, days, and hours. The activity output was 

set to report both distance and population. A ratio of population to vehicle-miles-traveled 

(VMT) was calculated from these outputs. The ratios were calculated for each source 

type. 

The Northwestern Indiana Regional Planning Commission (NIRPC), which is the 

metropolitan planning organization (MPO) for Lake and Porter Counties, provided VMT 

by MOVES road types extracted from their travel demand model's base year. Since the 

default MARs in MOVES vary by year (but not by location), the MOVES run that was 

executed to extract the MARs was run for a year consistent with the travel demand 

model's base year. This resulted in MARs that could be applied directly to the validated 

VMTs reported by the travel demand model. The travel demand model VMTs were 

converted into annual VMT and distributed by vehicle types using statewide default VMT 

distribution factors documented in this report in the section on Default VMT Distributions. 

The MARs were then applied to the annual vehicle type VMTs. The result was an 

estimated vehicle population for each source type for the travel demand model's base 

year. Since the vehicle populations for source types 21, 31, and 32 were developed 

directly from the vehicle registration data, the population estimates derived for those 

3 
source types using the MAR method were discarded and the observed data were used 

instead. 

Future year vehicle populations were developed base on socioeconomic growth rates for 

the maintenance area. The MPO provided base year and horizon year population and 

employment data for the area. Annual growth rates were calculated for population 

growth and employment growth individually. Population growth rates were then used to 

grow the light vehicle populations (source types 11, 21, 31, and 32). Employment growth 

rates were used to grow the heavy vehicle populations (source types 41, 42, 43, 51, 52, 

53, 54, 61, and 62). Vehicle populations were calculated for every year from 2008 to 

2040. These vehicle populations for Lake and Porter Counties as a combined area are 

shown in Appendix C. 

Meteorological Data: 

The default set of hourly temperatures and hourly relative humidity was developed using 

EPA's data converters for changing MOBILE6.2 minimum I maximum temperatures and 

absolute humidity to the MOVES equivalent formats. The values for the MOBILE6.2 

inputs were taken from the Air Quality Conformity Determination Between the 2040 

Regional Transportation Plan. the Fiscal Year 2012 to 2015 Transportation Improvement 

Program. and the Indiana State Implementation Plan for Air Quality, Appendix E, 

developed by NIRPC in June, 2011 . 

Meteorological data reflect average annual conditions for the PM 2.5 runs. The 

MOBILE6.2 meteorological input data for each of the twelve months of the years were 

averaged together to create average annual temperatures and humidity. These were 

then passed through the data converters. The data reflect summer conditions for ozone 

using MOBILE6.2 inputs for July. The MOVES formatted meteorological data for Lake 

and Porter Counties as a combined area are presented in Appendix D of this report. 

Default VMT Distributions: 

As part of this effort, INDOT developed a default set of VMT distribution factors by 

Highway Performance Monitoring System (HPMS) vehicle type and by MOVES road 

type. These distribution factors were developed by analyzing four consecutive years of 

continuous traffic count data ending in 2010 for twenty permanent traffic count stations 

throughout Indiana. The stations were selected to provide a spread of locations 

corresponding to each of the four MOVES road types. Furthermore, these stations were 

selected from among sites that were concentrated in nonattainment and maintenance 

areas. In some cases, data from the requested site were either partially or completely 

unavailable. An inventory of the sites used to develop the distributions is shown in Table 

4. 

The vehicle counts reported at each station were provided by vehicle class. These were 

aggregated into the six basic HPMS vehicle types: motorcycle, passenger car, light 

truck, bus, single-unit heavy truck, and combination heavy truck. The distribution of VMT 

by vehicle type was calculated for each road type by taking each vehicle type's 

percentage of total traffic. These default statewide factors are shown in Appendix E. 

4 
Table 4 Inventory of Permanent Count Stations 

SiteiD City County Location Road Type Data Quality 

3000 MUNCIE DELAWARE 

HAMILTON 

MARION 

LAKE 

LAPORTE 

SR 332 RM 0.5 3 Closed since 9/26/2006. No 

data. 

3200 CARMEL US 31 RM 125.7 5 Good 

3300 INDY WEST 1465 MM 10.0 4 Closed since 9/1/1 0 

4000 GARY 

4500 LAPORTE 

I 80 I I 94 M M 6. 0 4 

SR 2 RM 65.2 3 

Only 2010 data passed QC 

Good 

5600 

6100 

SELLERSBURG CLARK 

EVANSVILLE GIBSON 

165 MM 8.0 

164 MM 27.9 

4 

2 

Bad sensors. Not usable. 

Good 

0105 TERRE HAUTE VI GO Good-closed 

5/13/09 

11/13/08-

0201 MIDDLEBURY ELKHART 

US41 RM 104.2 

SR 120 RM 13.9 

3 

3 Good- closed 8/3/10-12/6/10 

0210 FORT WAYNE ALLEN 

0303 MUNCIE DELAWARE 

0327 DALEVILLE DELAWARE 

0403 SOUTH BEND ST. JOSEPH 

0501 INDY SOUTH MARION 

0502 MARTINSVILLE MORGAN 

0507 SEYMOUR JACKSON 

0602 HAZLETON GIBSON 

0603 DUBOIS DUBOIS 

1-69 0.53 mi N of 4 SR 3 

US 35 RM 44.5 5 

169MM31.4 2 

US 20 RM 77.1 

SR 37 RM 143.5 

SR 67 RM 80.6 

165 MM 47.0 

SR 56 RM 0.6 

SR 56 RM 53.3 

4 

5 

3 

2 

3 

0608 EVANSVILLE VANDERBURGH SR 66 RM 23.5 

3 

5 

1315 I 70 MARION 170 MM 83.5 4 

Default Hourly Distributions: 

Good 

Good 

Good-built in 12/10/2007 

Good 

Good-closed 5/22/09-6/1/09 

Good 

Good 

Good 

Good- closed 1 0/16/08-

3/20/09 

Good 

Closed 5/17/06-3/24/08 

The same set of twenty permanent traffic count locations discussed in the section on 

Default VMT Distributions was analyzed to develop a set of hourly distribution factors. 

These factors were calculated by road type, by HPMS vehicle type. Hourly factors were 

only calculated for the average weekday. The hourly distribution pattern for each traffic 

count location was reviewed. Any data that appeared to reflect either an error in the data 

or an outlier of behavior were removed to prevent bias in the data. The following data 

were excluded from the analysis: 

• Bus data from count stations 0105 and 0603 were excluded due to abnormal 

midnight peaks in the data; 

• An abnormal relationship between passenger cars and light duty trucks at count 

station 4500 prompted the exclusion of all data from this location due to 

questions of reliability; 

• Peak spreading behavior observed at count station 4000 from traffic related to 

Chicago was considered to be too unique to be included in a default statewide 

data set; and, 

• Combination truck traffic from station 3200 was excluded due to too much 

overnight traffic when compared to other vehicles and other stations. 

5 
Furthermore, traffic patterns reported by those count stations corresponding to road type 

3 (3000, 4500, 0105, 0201, 0502, 0602, and 0603) had a tendency to over represent 

long distance travel. This was most likely the result of statewide permanent count 

stations focusing primarily on higher order facilities. Rural collectors and local streets are 

less likely to reflect long distance travel. The hourly distributions for road type 3 (rural 

unrestricted access) were adjusted to better account for traffic behavior on lower order 

facilities in rural areas. A sample of traffic count data from Morgan County, IN was used 

to introduce more local traffic behavior in the road type 3 hourly distributions. An analysis 

of the Morgan County data showed a pattern more consistent with AM and PM peaking 

characteristics reflecting local commuting traffic on collectors and local streets for 

passenger cars and light duty trucks. The Morgan County data for passenger cars and 

light duty trucks on collectors and local streets were weighted and added to the road 

type 3 data set. This analysis assumed that rural collectors and local streets accounted 

for 20 percent of all VMT for road type 3. 

The statewide default hourly distribution factors are presented in Appendix F. 

Default Daily and Monthly Distributions: 

Default daily and monthly distribution factors were calculated from INDOT's official count 

adjustment factors which are more commonly used to develop AADT from raw traffic 

counts. These factors are based on the set of daily traffic counts collected from all 

permanent count stations throughout the state. The daily distribution factors determine 

what percentage of VMT is occurring on weekdays and what percentage is occurring on 

weekends. The monthly distribution factors determine what percentage of annual VMT is 

occurring in each month of the year. The statewide default daily distribution factors are 

shown in Appendix G. The statewide default monthly distribution factors are shown in 

Appendix H. 

Ramp Fractions: 

The ramp fractions represent the percentage of vehicle-hours-traveled (VHT) for road 

types 2 (rural restricted access) and 4 (urban restricted access) occurring on the ramps 

associated with those road types. These fractions were calculated based on the 

percentage of VHT occurring on ramps reported by the base year travel demand model. 

These ramp fractions are reported in Appendix I. 

6 
Appendix A 

Number of Runs: 

Input Item Ozone PM 2.5 

Years 2006, 2010, 2008, 2010, 

2015,2020, 2015, 2020, 

2025, 2030, 2025,2030, 

2035, 2040 2035,2040 

Pollutants/ Volatile PM 2.5 with all 

Processes Organic subspecies; 

Compound NOx 

(VOC), NOx, 

and supporting 

Meteorology Summer Average 

Annual 

#of MOVES 8 8 

runs 
General Parameters: 

MOVES Input Item 

Screen Ozone PM 2.5 

Description Description User Choice 

Scale Domain/Scale County 

Calculation Type Emission Rate 

Time Spans Time Hour Hour 

Aggregation 

Level 

Year 2004, 2010, 2008, 2010, 

2015, 2020, 2015, 2020, 

2025, 2030, 2025,2030, 

2035, 2040 2035, 2040 

Months July April 

Days Weekday Weekday 

Hours Select All Select All 

Geographic Geographic Lake County* Lake County* 

Bounds Bounds 

Vehicles Vehicles All Gas and Diesel Combinations 

Road Type Road Type Select All 

Pollutants/ Pollutants/ VOC, NOx, and PM 2.5 with all 

Processes Processes supporting subspecies; NOx 

General Database Name LakePorter LakePorter PM 

Output Ozone 

Units Select "Grams" and "Miles" and 

"Million BTU" 

Activity Distance, Population 

Output On Road Select "Source Use Type" and "Road 

Emissions Type" 

Detail 

*Represents both Lake and Porter Counties. 
C t D t M • 

County Data Excel Sheet Tab 

Manager Input Name 

Source (Vehicle) sourceTypeYear 

Type Population 

Vehicle Type HPMSVTypeYear 

VMT (by 13 

MOVES Vehicle 

Types) 

Ozone PM 2.5 

Local Registration for Source Types 21, 31, and 32; 

Estimated population using default MOVES mileage 

accumulation rates and local VMT for all other source types. 

Future year vehicle populations based on population growth 

rates for source types 11, 21, 31, and 32. Employment 

growth used for all other source types. 

Statewide default vehicle distributions across road types 

developed by INDOT using an analysis of permanent count 

station data from a statewide data set. 

MonthVMTFraction Statewide default monthly fractions developed by IN DOT 

using an analysis of permanent count station data from a 

statewide data set. 

DayVMTFraction Statewide default daily fractions developed by IN DOT using 

an analysis of permanent count station data from a 

statewide data set. 

HourVMTFraction Statewide default hourly fractions developed by INDOT 

Average Speed avgSpeed 

Distribution (% Distribution 

of VHT in each 5 

mph speed bin) 

Road Type roadType 

Distribution Distribution 

(VMT by 5 

MOVES Road 

Types) 

Age Distribution sourceTypeAge 

(Vehicle Distribution 

Population by 

Age of Vehicle) 

Ramp Fraction RoadType 

Meteorology ZoneMonthHour 

Data 

Fuel (% of FueiFormulation 

Market Share by 

Fuel Type) FueiSupply 

1/M Program IMCoverage 

using an analysis of permanent count station data from a 

statewide data set. 

National defaults. 

Calculated from local VMT data. Use travel demand model 

base year distributions for all years. 

Local age distributions developed from vehicle registration 

data for source types 21, 31 , and 32. Default MOVES age 

distributions for all other source types. 

Based on local travel demand model. 

MOBILES Summer Met Data MOBILE612 month Met 

Converted to MOVES format Data Converted to MOVES 

format and averaged to 

annual meteorology 

MOVES Defaults 

Lake County MOVES Lake County MOVES 

Defaults for Summer (check Defaults for annual {check if 

if varies among counties) varies among counties) 

Consistent with current local 1/M Program 
AppendixB 

e 1ceAge o· 'b . ISifl UfiOfiS for L k a eand p orter Co unt1es: 

Source Types 

ageid 11 21 31 32 41 42 43 51 52 53 54 61 62 

0 0.21 09690540 0.0267370941 0.0145061143 0.0355122377 0.0643023355 0.0545743076 0.0622220643 0.0494240790 0.0588526168 0.0787544027 0.0615095870 0.0535634660 0.0670845256 

1 0.1921154969 0.0530181832 0.0500664299 0.0734065149 0.0626728412 0.0531913309 0.0606452875 0.0481716155 0.0573612230 0.0767586735 0.0599508636 0.0535634660 0.0670845256 

2 0.1573471585 0.0665539321 0.0582074781 0.0786470016 0.0624853859 0.0530322328 0.0604638952 0.0480275345 0.0571896519 0.0765290827 0.0597715492 0.0541045093 0.0677621447 

3 0.1359771581 0.0610324714 0.0519847618 0.0656848868 0.0624229593 0.0529792497 0.0604034894 0.0479795509 0.0571325186 0.0764526251 0.0597118340 0.0575579884 0.0720873878 

4 0.1058454735 0.0659801258 0.0780550961 . 0.0793616134 0.0617369906 0.0523970560 0.0597397140 0.0474523026 0.0565046834 0.0756124785 0.0590556596 0.0564182312 0.0706599203 

5 0.0750909142 0.06456271 02 0.0733914482 0.0732874129 0.0559170498 0.0474575929 0.0541080614 0.0429789769 0.0511779950 0.0684845018 0.0534884926 0.0489290859 0.0612802835 

6 0.0476805323 0.0608386692 0.0747132670 0.0647716220 0.0468365056 0.0397508123 0.0453212873 0.0359994879 0.0428670388 0.0573630896 0.0448023279 0.0366034411 0.0458432683 

7 0.0331026886 0.0649389143 0.080664841 0 0.0721559442 0.0425786431 0.0361370941 0.0412011709 0.0327268079 0.0389700355 0.0521482660 0.0407293873 0.03407 42206 0.0426755959 

8 0.0197278356 0.06499971 so 0.0643827445 0.0597693392 0.0488268516 0.0397426124 0.0453119367 0.0359920640 0.0428582007 0.0573512681 0.0447930981 0.0358093100 0.0448486759 

9 0.0118473747 0.0677129448 0.0689108213 0.0689004903 0.0534377006 0.0453533365 0.0517089150 0.0410733035 0.0489087688 0.0654479137 0.0511 168252 0.0526288382 0.0659139597 

10 0.0053251777 0.0607512683 0.0648030151 0.0568165234 0.0532712252 0.0452120443 0.0515478328 0.0409453420 0.0487564067 0.0652440247 0.0509575859 0.0624520143 0.0782168041 

11 0.0025378610 0.0524367768 0.0558146471 0.0510748953 0.0407951886 0.0536203440 0.041 1075833 0.0313560350 0.0391491717 0.0523881239 0.0302729398 0.0478258601 0.0598985955 

12 0.001301 1470 0.0529801828 0.0501138798 0.0424003017 0.0331924560 0.0489936472 0.0382933197 0.0255124310 0.0294483131 0.0394065607 0.0468101868 0.0389128550 0.0487354179 

13 0.0006124019 0.0425262678 0.0366377810 0.0326140898 0.0277347637 0.0456089741 0.0333751020 0.0545980574 0.0316399801 0.0194774783 0.0291673253 0.0325145854 0.0462990441 

14 0.0002476898 0.0448138930 0.0390038231 0.0330507970 0.0364294706 o.03m46681 0.0430863640 0.0632656498 0.0364439725 0.0194691525 0.0347804437 0.0427077419 0.0462072388 

15 0.0001527705 0.0327297600 0.0357704509 0.0282867181 0.0283511969 0.0332950401 0.0210164622 0.0395649332 0.0357887614 0.0311848083 0.0335202065 0.0332372597 0.0300444032 

16 0.0000668536 0.0270600977 0.0244095876 0.0196716756 0.0235884296 0.0279132162 0.0253671498 0.0341566540 0.0259987277 0.0230196849 0.0233151 075 0.0276536739 0.0230524492 

17 0.0000299603 0.0197450172 0.0162482037 0.0135180737 0.0175637044 0.0244970846 0.0206833627 0.0146346390 0.0197956396 0.0052258132 0.0206748599 0.0205906442 0.0138452217 

18 0.0000127409 0.0157207729 0.0129944958 0.01 06794767 0.0201192241 0.0250480695 0.0266888558 0.0401958334 0.0193740288 0.0037212159 0.0155464816 0.0235865809 0.01 00066460 

19 0.0000055369 O.Q1 09327203 0.0097340094 0.0083371380 0.0225790392 0.0366610768 0.0301447753 0.0342277190 0.0227335396 0.0175775477 0.0203628520 0.0264703224 0.0098603738 

20 0.0000022027 0.0097167069 0.0096594452 0.0078607301 0.0226407923 0.0281971934 0.0173882093 0.0270081845 0.0289395633 0.0183674556 0.0265944575 0.0265427135 0.009575511 2 

21 0.0000010015 0.0060838669 0.0075445351 0.0053595887 0.0212965445 0.0224413685 0.0209032932 0.0367 430589 0.0255089927 0.0121624816 0.0238465850 0.0249667984 0.0083402541 

22 0.0000005320 0.0047196519 0.0043586128 0.0031760526 0.0221366577 0.0207614938 0.0211741003 0.0294241579 0.0211707159 0.0029207200 0.0232916866 0.0259516972 0.0021970287 

23 0.0000002372 0.0034656381 0.0032604864 0.0028187467 0.0187753208 0.0176845935 0.0186862600 0.0367365508 0.02557 42899 0.0006595597 0.0173635700 0.0220110680 0.0022815392 ·- 24 0.0000001 072 0.0034048375 0.0028063230 0.0021239852 0.0165801584 0.0153441343 0.0162223474 0.0195371739 0.0181341022 0.0013228019 0.0186391363 0.0194375881 0.0028947085 

25 0.0000000515 0.0020672227 0.0018979963 0.0014292237 0.0130464803 0.0119613578 0.0125269842 0.0202862884 0.01 01534224 0.0013255722 0.0189070434 0.0152949162 0.0014963357 

26 0.0000000201 0.0015238168 0.0010100052 0.0009131151 0.0052066606 0.0114707358 0.0046276161 0 .0058785937 0.0158244798 0.0000000000 0.0123859355 0.0061039775 0.0003051544 

27 0.0000000084 0.0007410082 0.0008269841 0.0008535641 0.0044375500 0.0062552616 0.0034269422 0.0066192300 0.0082431519 0.0005853113 0.0073123264 0.0052023202 0.0002365920 

28 0.0000000046 0.0008208090 0.0006507416 0.0006550608 0.0038534093 0.0027153367 0.0040227141 0.0058648852 0.0078447522 0.0004224309 0.0040199156 0.0045175071 0.0007539156 

29 0.0000000027 0.0007486082 0.0002846994 0.0002382039 0.0050202650 0.0073813428 0.0039557847 0.0014702211 0.0082910352 0.0000000000 0.0005297244 0.0058854602 0.0002483418 

30 0.0000000060 0.0106363170 0.0052872753 0.0046449769 0.0041641999 0.0025473919 0.0046291194 0.0021486392 0.0093642209 0.0005969550 0.0069720059 0.0048818593 0.0002641374 

Source: Quafily assured vehicle registration data for the combined Lake County and Porter County area for source types 21. 32, and 32, MOVES201 Oa default distributions for all other source types. 
AppendixC 

L a k eand orter c ounties e icle Pooulations: 

Vehicle 

Populations Source Types 

11 21 31 32 41 42 43 51 52 53 54 61 62 

Annual Populations 

2006 12,164 276,531 159,214 46,746 293 157 2,005 56 3,634 434 631 6,485 7,399 

2009 12,247 278,418 160,301 49,078 296 159 2.021 58 3,664 437 836 6,539 7,461 -- 2010 12,330 280,31 8 161,395 49,413 298 160 2,038 59 3,694 441 845 6,593 7,523 

2011 12,414 282,231 162.496 49,751 301 161 2.055 59 3,725 445 852 6.848 7,586 

2012 12.499 284,156 163,605 50,090 303 163 2,072 60 3,756 448 859 6,703 7,849 

2013 12.584 286,095 184,721 50,432 306 164 2,089 60 3,788 452 867 6,759 7,713 

2014 12,670 288,048 165,845 50,n6 308 166 2,107 61 3,819 456 874 6,816 7,n7 

2015 12,757 290,013 166,977 51,122 311 167 2.124 61 3,851 460 881 6,872 7,842 

2016 12,844 291,992 168,116 51,471 314 168 2,142 62 3,883 463 888 6,930 7,907 

2017 12,931 293,984 169,263 51 ,822 316 170 - 2,160 62 3,915 467 896 6,987 7,973 

2018 13,020 295,990 170,418 52,176 319 171 2,178 63 3,948 471 903 7,046 8,039 

2019 13,108 298,010 171,581 52,532 322 173 2,196 63 3,981 475 911 7,104 8,106 

2020 13,198 300,044 172,752 52,891 324 174 2 ,214 64 4.014 479 918 7,163 8,174 

2021 13,288 302,091 173,931 53,251 327 175 2,233 64 4.048 483 926 7,223 8,242 - 2022 13.379 304,152 175,117 53,615 330 1n 2,251 65 4,081 487 934 7,283 8,311 

2023 13,470 306,228 176,312 53,981 332 178 2,270 66 4.115 491 942 7,344 8,380 

2024 13,562 308,317 1n,516 54.349 335 180 2,289 66 4,150 495 949 7,405 8,450 

2025 13,654 310,421 178,727 54,720 338 181 2,308 67 4.184 499 957 7,467 8.520 

2026 13,748 312,539 179,946 55,093 341 183 2,327 67 4,219 504 965 7,529 8,591 

2027 13,841 314,672 181,174 55,469 344 184 2,347 68 4,254 508 973 7,592 8,663 

2028 13,936 316,819 182,410 55,848 346 186 2,366 68 4,290 512 982 7,655 8,735 

2029 14,031 318.981 183,655 56,229 349 187 2,386 69 4,325 516 990 7,719 8.808 - 2030 14,127 321,158 184,908 56,612 352 189 2,406 69 4,361 521 998 7,783 8,881 

2031 14,223 323.349 186,170 56,999 355 191 2.426 70 4,398 525 1,006 7,848 8,955 

2032 14 ,320 325,556 187,440 57,388 358 192 2,446 71 4,434 529 1,015 7,913 9,030 

2033 14.418 327,m 188,71 9 57,779 361 194 2,467 71 4,471 534 1,023 7,979 9,105 

2034 14,516 330,014 190,007 58,174 364 195 2,487 72 4,509 538 1,032 8,046 9,181 

2035 14.615 332,265 191,304 58,571 367 197 2,508 72 4,546 543 1,040 8,113 9,257 

2036 14,715 334,533 192,609 58,970 370 199 2,529 73 4.584 547 1,049 8,181 9,334 

2037 14,815 336,815 193,923 59,373 373 200 2,550 74 4,622 552 1,058 8,249 9,412 

2038 14,916 339,114 195,247 59,n8 376 202 2,571 74 4,661 556 1,066 8,317 9.490 

2039 15,018 341 ,428 196,579 60,186 380 204 2,593 75 4,700 561 1,075 8,387 9,570 

2040 15.121 343,757 197,920 60.596 383 205 2,61 4 75 4,739 566 1,084 8.457 9,649 

Source. Quahty assured veh1cle regiStraOon data for the combined Lake County and Porter County area for source types 21, 32, and 32, MOVES2010a default m1leage accumulation rates for all other source types. PopulatiOn growth factors are taken from local 

socioeconomic data forecasts. 
Appendix D 

L k a ean dPrt o er C oun1es t" Mt e eoro og1ca . I D a t a: 

Ozone PM2.5 

monthiD zoneiD HouriD temperature reiHumidity monthiD zoneiD HouriD temperature reiHumidity 

7 180890 1 67.0 88.0 4 180890 1 43.7 100.0 

7 180890 2 65.8 91.8 4 180890 2 42.5 100.0 

7 180890 3 64.9 94.9 4 180890 3 41.6 100.0 

7 180890 4 64.2 97.2 4 180890 4 41.0 100.0 

7 180890 5 63.6 99.0 4 180890 5 40.5 100.0 

7 180890 6 63.0 100.0 4 180890 6 39.9 100.0 

7 180890 7 62.5 100.0 4 180890 7 39.4 100.0 

7 180890 8 62.9 100.0 4 180890 8 39.8 100.0 

7 180890 9 65.5 92.6 4 180890 9 42.3 100.0 

7 180890 10 69.7 80.2 4 180890 10 46.2 97.2 

7 180890 11 74.0 69.4 4 180890 11 50.3 83.5 

7 180890 12 77.7 61.4 4 180890 12 53.8 73.5 

7 180890 13 80.9 55.3 4 180890 13 56.8 65.8 

7 180890 14 82.6 52.2 4 180890 14 58.5 62.0 

7 180890 15 83.2 51.2 4 180890 15 59.0 60.7 

7 180890 16 83.4 50.9 4 180890 16 59.2 60.3 

7 180890 17 83.0 51.6 4 180890 17 58.8 61.2 

7 180890 18 81.7 53.7 4 180890 18 57.6 63.8 

7 180890 19 79.7 57.5 4 180890 19 55.7 68.6 

7 180890 20 77.0 62.9 4 180890 20 53.1 75.3 

7 180890 21 74.3 68.8 4 180890 21 50.5 82.7 

7 180890 22 71.9 74.5 4 180890 22 48.3 89.9 

7 180890 23 70.3 78.8 4 180890 23 46.7 95.4 

7 180890 24 68.6 83.4 4 180890 24 45.2 100.0 

Source: Mobile 6.2 reported meteorological data from Air Quality Conformity Determination Between the 2040 Regional Transportation Plan, the Fiscal Year 2012 

to 2015 Transportation Improvement Program, and the Indiana State Implementation Plan for Air Quality, Appendix E, developed by NIRPC in June, 2011 

converted using EPA data converter. 
Appendix E 

Indiana Default VMT Distributions by Vehicle Type and Road Type: 

Road Light Duty Single Unit Combination 

Type Motorcycle Passenger Car Truck Bus Truck Truck 

2 0.007033832 0.506408086 0.163786651 0.004174166 0.007773053 0.310824213 

3 0.001733929 0.659751199 0.225767175 0.000793168 0.010963315 0.100991214 

4 0.004429643 0.424581084 0.299243052 0.005271096 0.008735204 0.257739921 

5 0.002785022 0.702754695 0.245240087 0.001402085 0.009764356 0.038053756 

Source: Statewide averages developed from Indiana Department of Transportation traffic count data for all road types except for Road Type 4. Distributions for 

Road Type 4 taken specifically from 1-80 in Gary (count station 4000) as per ICG consensus to represent higher than average truck traffic in Gary. 
Appendix F 

Indiana Default Hourly Distribution Factors for Road Type 2 - Rural Restricted Access: 

Source Types 

Hour 11 21 31 32 41 42 43 51 52 53 54 61 62 

1 0.0125903247 0.0101219844 0.0084967341 0.0084967341 0.0254913340 0.0254913340 0.0254913340 0.0126607789 0.0126607789 0.0126607789 0.0126607789 0.0197906895 0.0197906895 

2 0.0104070951 0.0069241973 0.0066421955 0.0066421955 0.0269500431 0.0269500431 0.0269500431 0.011 4617645 0.0114617645 0.01 14617645 0.01 14617645 0.0212124099 0.0212124099 

3 0.0098043179 0.0056567534 0.0061275627 0.0061275627 0.0231103443 0.0231103443 0.0231103443 0.0107741941 0.0107741941 0.0107741941 0.0107741941 0.0201622890 0.0201622890 

4 0.0140329469 0.0069658232 0.0084286563 0.0084286563 0.0234460042 0.0234460042 0.0234460042 0.0128724692 0.0128724692 0.0128724692 0.0128724692 0.0213065902 0.0213065902 

5 0.0165212405 0.0100941552 0.0134026652 0.0134026652 0.0244090660 0.0244090660 0.0244090660 0.017 4195788 0.0174195788 0.0174195788 0.0174195788 0.0250478552 0.02504 78552 

6 0.0312047458 0.0241732202 0.0316551315 0.0316551315 0.0322923692 0.0322923692 0.0322923692 0.0261005783 0.0261005783 0.0261005783 0.0261005783 0.0304976568 0.0304976568 

7 0.0399082603 0.0390974746 0.0481531313 0.0481531313 0.0302344914 0.0302344914 0.0302344914 0.0420450985 0.0420450985 0.0420450985 0.0420450985 0.0339947725 0.0339947725 

8 0.0482864956 0.0528758381 0.0535145983 0.0535145983 0.0386071681 0.0386071681 0.0386071681 0.0556119122 0.0556119122 0.0556119122 0.0556119122 0.0383435322 0.0383435322 

9 0.0472316355 0.0493101459 0.0541442978 0.0541442978 0.0454144773 0.0454144773 0.0454144773 0.0647383083 0.0647383083 0.0647383083 0.0647383083 0.0447350945 0.0447350945 

10 0.0521292001 0.0488627065 0.0570682751 0.0570682751 0.0533197396 0.0533197396 0.0533197396 0.0711110358 0.0711110358 0.0711110358 0.0711110358 0.0517738130 0.0517738130 

11 0.0559204481 0.0513700269 0.0575854739 0.0575854739 0.0576707709 0.0576707709 0.0576707709 0.0730230234 0.0730230234 0.0730230234 0.0730230234 0.0557712464 0.0557712484 

12 0.05728221 00 0.0533048469 0.0582753930 0.0582753930 0.0549541212 0.0549541212 0.0549541212 0.0731872952 0.0731872952 0.0731872952 0.0731872952 0.0571435296 0.0571435296 

13 0.0592008057 0.05515861 41 0.0599414146 0.059941414 6 0.0541541840 0.0541541840 0.0541541840 0.0739324454 0.0739324454 0.0739324454 0.0739324454 0.0567014536 0.0567014536 

14 0.0615145144 0.0595500442 0.0635019874 0.0635019874 0.0570747392 0.05707 47392 0.0570747392 0.07 46488056 0.07 46488056 0.07 46488056 0.07 46488056 0.0567500887 0.0567500887 

15 0.0647783324 0.0662712693 0.0683897966 0.0683897966 0.0551925339 0.0551925339 0.0551925339 0.0704234655 0.0704234655 0.0704234655 0.0704234655 0.0578234055 0.0578234055 

16 0.0713500739 0.0764876319 0.077211 0428 0.077211 0428 0.0551956709 0.0551956709 0.0551956709 0.0628801912 0.0628801912 0.0628601912 0.0628601912 0.0577540296 0.0577540296 

17 0.0754978425 0.0847160034 0.0792545794 0.0792545794 0.0557979766 0.0557979766 0.0557979766 0.0534712990 0.0534712990 0.0534712990 0.0534712990 0.0562910814 0.0562910814 

18 0.0693763461 0.0821220539 0.0693254052 0.0693254052 0.0501011685 0.0501011685 0.0501011685 0.0436895095 0.0436895095 0.0436895095 0.0436895095 0.0527021980 0.0527021980 

19 0.0542187052 0.0620082513 0.0521045300 0.0521045300 0.0459685909 0.0459665909 0.0459665909 0.0363413126 0.0363413126 0.0363413126 0.0363413126 0.05022151 00 0.0502215100 

20 0.0432143461 0.0459015588 0.0390794599 0.0390794599 0.0462959768 0.0462959768 0.0462959768 0.0312048570 0.0312048570 0.0312048570 0.0312048570 0.04671 16534 0.0467116534 

21 0.0358137860 0.0372595462 0.0311015284 0.031 1015284 0.0418602463 0.0418602463 0.0418602463 0.0261242877 0.0261242877 0.0261242877 0.0261242877 0.0421311043 0.042131 1043 

22 0.0294294934 0.0312744978 0.0249803003 0.0249803003 0.03664967 45 0.0366496745 0.0366496745 0.0215822587 0.0215822587 0.0215822587 0.0215822587 0.0381387483 0.0381387483 

23 0.0223450238 0.0235734666 0.0182964081 0.0182964081 0.0347517842 0.0347517842 0.0347517842 0.0189759266 0.0189759266 0.0189759266 0.0189759266 0.0342326572 0.0342326572 

24 0.0179418099 0.0169198902 0.0133194323 0.0133194323 0.0310595247 0.0310595247 0.0310595247 0.0157396039 0.0157396039 0.0157396039 0.0157396039 0.0307625891 0.0307625891 

Source: Statewide averages developed from Indiana Department of Transportation traffic count data. 
Indiana Default Hourlv Distribution Factors for Road Tvoe 3- Rural Unrestricted Access: 

Source Types 

Hour 11 21 31 32 41 42 43 51 52 53 54 61 62 

1 0.0040299464 0.0073183989 0.0054636028 0.0054636028 0.0036998387 0.0036998387 0.0036998387 0.0043986387 0.0043986387 0.0043988387 0.0043986387 0.0164160879 0.0164160879 

2 0.0040299464 0.0041131835 0.0034619242 0.0034619242 0.0045536477 0.0045536477 0.0045536477 0.0041872686 0.0041872686 0.0041872686 0.0041872686 0.0167510731 0.0167510731 

3 0.0041817017 0.0032797517 0.0030691885 0.0030691885 0.0046485153 0.0046485153 0.0046485153 0.0073497934 0.0073497934 0.0073497934 0.0073497934 0.0165479051 0.0165479051 

4 0.0053114356 0.0057247729 0.0048082254 0.0048082254 0.0039844417 0.0039844417 0.0039844417 0.0084039684 0.0084039684 0.0084039684 0.0084039684 O.D195836328 0.0195836328 

5 0.0140963815 0.0151258840 0.0143177758 0.0143177758 0.0082534864 0.0082534864 0.0082534864 0.0153176438 0.0153176438 0.0153176438 0.0153176438 0.0258467673 0.0258467673 

6 0.0292719118 0.0316782840 0.0354335195 0.0354335195 0.0293141068 0.0293141068 0.0293141068 0.0299744215 0.02997 44215 0.0299744215 0.02997 44215 0.0344245647 0.0344245647 

7 0.0397598894 0.0468485516 0.0516314034 0.0516314034 0.0496157860 0.0496157860 0.0496157860 0.0557776279 0.0557776279 0.0557776279 0.0557776279 0.0440469233 0.0440469233 

8 0.0448183995 0.0633910409 0.0636260878 0.0636260878 0.0768428043 0.0768428043 0.0768428043 0.0778885464 0.0778885464 0.0778885464 0.0778885464 0.0512793380 0.0512793380 

9 0.0370114322 0.04603577 46 0.0558633273 0.0558633273 0.1049236315 0.1049236315 0.1049236315 0.0853025536 0.0853025536 0.0853025536 0.0853025536 0.0568238265 0.0568238265 

10 0.0416989849 0.0427840868 0.0547852386 0.0547852386 0.1065363817 0.1065363817 0.1065363817 0.0879727734 0.0679727734 0.0879727734 0.0879727734 0.0599756501 0.0599756501 

11 0.0509391967 0.0444183487 0.0568454275 0.0568454275 0.1186794422 0.1186794422 0.1186794422 0.0886336394 0.0686336394 0.0886336394 0.0886336394 0.0633505956 0.0633505956 

12 0.0563855259 0.0512966366 0.0618918527 0.0618918527 0.1154539418 0.1154539418 0.1154539418 0.0859045570 0.0859045570 0.0859045570 0.0859045570 0.0635864154 0.0635864154 

13 0.0638721209 0.0537246907 0.061081821 1 0.0610818211 0.0999905132 0.0999905132 0.0999905132 0.0858537212 0.0858537212 0.0858537212 0.0858537212 0.0644099711 0.0644099711 

14 0.0708697265 0.0545001954 0.0632013074 0.0632013074 0.0864244379 0.0864244379 0.0864244379 0.0852196109 0.0852196109 0.0852196109 0.0852196109 0.0637040231 0.0637040231 

15 0.0774626513 0.0656899700 0.0681384267 0.0681384267 0.0592922873 0.0592922873 0.0592922873 0.077 4551039 0.077 4551039 0.0774551039 0.0774551039 0.0609657913 0.0609657913 

16 0.0849155229 0.0775959037 0.0785115831 0.0765115831 0.0295038421 0.0295038421 0.0295038421 0.0663381066 0.0663381066 0.0663381068 0.0663381066 0.057005831 1 0.0570058311 

17 0.0916096179 0.0871890696 0.0796014405 0.0796014405 0.0317806660 0.0317806660 0.0317806660 0.0433522764 0.0433522764 0.0433522764 0.0433522764 0.0517440242 0.0517440242 

18 0.0855899909 0.0856725476 0.0737419189 0.0737419189 0.0184043260 0.0184043260 0.0184043260 0.0290727541 0.0290727541 0.0290727541 0.0290727541 0.0467760851 0.0467760851 

19 0.0685259502 0.0656330958 0.0545272751 0.0545272751 0.0120481928 0.0120481928 0.0120481928 0.0187744815 0.01877 44815 0.0187744815 0.0187744815 0.0413186686 0.0413186686 

20 0.0503658989 0.0457301992 0.0390975413 0.0390975413 0.0118584575 0.0118584575 0.0118584575 0.0129711680 0.0129711680 0.0129711680 0.0129711680 0.0364127078 0.0364127078 

21 0.0353421239 0.0400621944 0.0294058171 0.0294058171 0.0096765013 0.0096765013 0.0096765013 0.01 06166656 0.01 06166656 0.0106166656 0.0106166656 0.0318882915 0.0318882915 

22 0.0217853168 0.0289018238 0.0218457686 0.0218457686 0.0061663979 0.0061663979 0.0061663979 0.0079972816 0.0079972816 0.0079972816 0.0079972816 0.0290264055 0.0290264055 

23 0.0119380838 0.0205028665 0.0136731866 0.0136731866 0.0048382506 0.0048382506 0.0048382506 0.0061564888 0.0061564888 0.0061564888 0.0061564888 0.0255574344 0.025557 4344 

24 0.0061882440 0.0127827290 0.0079763402 0.0079763402 0.0035101034 0.00351 01 034 0.00351 01034 0.0050809093 0.0050809093 0.0050809093 0.0050809093 0.0225579868 0.0225579868 

Source: Statewide averages developed from Indiana Department of Transportation traffic count data. 
Indiana Default Hourty Distribution Factors for Road Type 4 -Urban Restricted Access: 

Source Types 

Hour 11 21 31 32 41 42 43 51 52 53 54 61 62 

1 0.0114838630 0.01 04500369 0.0090397680 0.0090397680 0.0186488577 0.0186488577 0.0186488577 0.0090968023 0.0090968023 0.0090968023 0.0090968023 0.0194173119 0.0194173119 

2 0.0071800855 0.0062500477 0.0056304309 0.0056304309 0.0163411464 0.0163411464 0.0163411464 0.0080102618 0.0080102618 0.0080102618 0.0080102618 0.0198708197 0.0198708197 

3 0.0063691205 0.0049689741 0.0046493622 0.0046493622 0.0157775876 0.0157775876 0.0157775876 0.0078361983 0.0078361983 0.0078361983 0.0078361983 0.0186489893 0.0186489893 

4 0.0073777516 0.0058427101 0.0058801326 0.0058801326 0.0161766037 0.0161766037 0.0161766037 0.0086827231 0.0086827231 0.0086827231 0.0086827231 0.0198231326 0.0198231326 

5 0.0108139353 0.0098545059 0.01 08999000 0.01 08999000 0.0221330492 0.0221330492 0.0221330492 0.0117 453229 0.0117 453229 0.0117453229 0.0117 453229 0.0232515449 0.0232515449 

6 0.0235457656 0.0231603609 0 .0263517526 0.0263517526 0.0299755654 0.0299755654 0.0299755654 0.0204013312 0.0204013312 0.0204013312 0.0204013312 0.0294638153 0.0294638153 

7 0.0461747881 0.0495085217 0.0542414568 0.0542414568 0.0393812372 0.0393812372 0.0393812372 0.0435263184 0.0435263184 0.0435263184 0.0435263184 0.0375553768 0.0375553768 

8 0.0567226756 0.0788353145 0.0674512195 0.0674512195 0.0503870867 0.0503870867 0.0503870867 0.0659533819 0.0659533819 0.0659533819 0.0659533819 0.0446175773 0.0446175773 

9 0.0493171440 0.0638279223 0.0614111771 0.0614111771 0.0589556475 0.0589556475 0.0589556475 0.0756333178 0 .0756333178 0.0756333178 0.0756333178 0.0515843704 0.0515843704 

10 0.0406144957 0.0466481655 0.0536303211 0.0536303211 0.0581555587 0.0581555587 0.0581555587 0.0790728466 0.0790728466 0.0790728466 0.0790728466 0.0553194565 0.0553194565 

11 0.0415130748 0.04281 02606 0.0512594850 0.0512594850 0.0616027281 0.0616027281 0.0616027281 0.0824723032 0.0824723032 0.0824723032 0.0824723032 0.0583081277 0.0583081277 

12 0.0465166969 0.0452333632 0.0529793024 0.0529793024 0.0644246353 0.0644246353 0.0644246353 0.0820640679 0.0820640679 0.0820640679 0.0820640679 0.0589378233 0.0589378233 

13 0.0517959830 0.0478487216 0.0547982766 0.0547982766 0.0637644078 0.0637644078 0.0637644078 0.0808088903 0.0808088903 0.0808088903 0.0808088903 0.0575925555 0.0575925555 

14 0.0566713893 0.0502151226 0.0576660799 0.0576660799 0.0625591325 0.0625591325 0.0625591325 0.0811795580 0.0811795580 0.0811795580 0.0811795580 0.0571667797 0.0571667797 

15 0.0671882913 0.0580384620 0.0656779676 0.0656779676 0.0619482678 0.0619482678 0.0619482678 0.0795090490 0.0795090490 0.0795090490 0.0795090490 0.0573429674 0.0573429674 

16 0.0810035452 0.0715596945 0.0786905659 0.0786905659 0.0609466141 0.0609466141 0.0609466141 0.0727723312 0.0727723312 0.0727723312 0.0727723312 0.0567213465 0.0567213465 

17 0.0863864724 0.0838541 123 0.0821371575 0.0821371575 0.0577256909 0.0577256909 0.0577256909 0.0563364761 0.0563364761 0.0563364761 0.0563364761 0.0551911545 0.0551911545 

18 0.0843264717 0.0874512166 0.0756929494 0.0756929494 0.0510164625 0.0510164625 0.051 0164825 0.0371719560 0.0371719560 0.0371719560 0.0371719560 0.0531125437 0.0531125437 - 19 0.0645951265 0.0604364374 0.0543673700 0.0543873700 0.0450990958 0.0450990958 0.0450990958 0.0249336618 0.0249336618 0.0249338618 0.0249336618 0.0487199307 0.0487199307 

20 0.0469536991 0.04247 49554 0.0373951308 0.0373951308 0.0364927066 0.0364927066 0.0364927066 0.0188134711 0.0188134711 0.0188134711 0.0188134711 0.0432101938 0.0432101938 

21 0.0373781148 0.0353280630 0.0293181427 0.0293181427 0.0322318571 0.0322318571 0.0322318571 0.0162446774 0.0162446774 0.0162446774 0.0162446774 0.0390319248 0.0390319248 

22 0.0316564842 0.0313403787 0.0249971308 0.0249971308 0.02820467 47 0.02820467 47 0.02820467 47 0.0142456600 0.0142456600 0.0142456600 0.0142456600 0.0355118446 0.0355118446 

23 0.0245992722 0.0251562568 0.0203505544 0.0203505544 0.0242700475 0.0242700475 0.0242700475 0.0124474209 0.0124474209 0.0124474209 0.0124474209 0.0317711657 0.0317711657 

24 0.0198157539 0.0189063955 0.0154623663 0.0154623663 0.0217813392 0.0217813392 0.0217813392 0.0110419727 0.0110419727 0.0110419727 0.0110419727 0.0278292477 0.0278292477 

Source: Statewide averages developed from Indiana Department of Transportation traffic count data. 
Indiana Default Hourly Distribution Factors for Road Type 5 -Urban Unrestricted Access: 

Source Types 

Hour 11 21 31 32 41 42 43 51 52 53 54 61 62 

1 0.0092279794 0.0085268711 0.0060669694 0.0060669694 0.0126828270 0.0126828270 0.0126828270 0.0037158531 0.0037158531 0.0037158531 0.0037158531 0.0106396358 0.0106396358 

2 0.0055316691 0.0048527626 0.0037675180 0.0037675180 0.0099485186 0.0099485186 0.0099485186 0.0038117041 0.0038117041 0.0038117041 0.0038117041 0.0124309233 0.0124309233 

3 0.0047273286 0.0037895145 0.0033129405 0.0033129405 0.0069482800 0.0069482800 0.0069482800 0.0044165887 0.0044165887 0.0044165887 0.0044165887 0.0121505035 0.0121 505035 

4 0.0047017359 0.0044201 159 0.0042394230 0.0042394230 0.0113599945 0.0113599945 0.0113599945 0.0056282193 0.0056282193 0.0056282193 0.0056282193 0.0144699998 0.0144699998 

5 0.0081859928 0.0079416389 0.0087215410 0.0087215410 0.0153898606 0.0153898606 0.0153898606 0.0086545038 0.0086545038 0.0086545038 0.0086545038 0.021 0508569 0.0210508569 

6 0.0225361588 0.0203863353 0.0238668712 0.0238668712 0.0256929528 0.0256929528 0.0256929528 0.0191822890 0.0191822890 0.0191822890 0.0191822890 0.0299165403 0.0299165403 

7 0.0435184779 0.0478282898 0.0541952158 0.0541952158 0.0448331117 0.0448331 117 0.0448331117 0.0418068371 0.0418068371 0.0418068371 0.0418068371 0.0436775030 0.0436775030 

8 0.0602121997 0.0721456866 0.0675347974 0.0675347974 0.0691895946 0.0691895946 0.0691895946 0.0731482386 0.0731482386 0.0731482386 0.0731482386 0.0588646976 0.0588646976 

9 0.0556311148 0.0567013667 0.0643660182 0.0643660182 0.0747059425 0.0747059425 0.0747059425 0.0880926125 0.0860926125 0.0880926125 0.0880926125 0.0640862836 0.0640862836 

10 0.0485821670 0.0466493163 0.0603283916 0.0603283916 0.0803995772 0.0803995772 0.0803995772 0.0921313810 0.0921313810 0.092131381 0 0.0921313810 0.0680944168 0.0680944168 

11 0.0495985610 0.0468148434 0.0590657789 0.0590657789 0.0774061573 0.0774061573 0.0774061573 0.0943973720 0.0943973720 0.0943973720 0.0943973720 0.0703404942 0.0703404942 

12 0.0573056055 0.0516032787 0.0615645883 0.0615645883 0.0753332651 0.07 53332651 0.0753332651 0.0911430924 0.0911430924 0.0911430924 0.0911430924 0.0698309800 0.0698309800 

13 0.0607752380 0.0555323143 0.0626732860 0.0626732860 0.0739763390 0.0739763390 0.0739763390 0.0895629476 0.0895629476 0.0895629476 0.0895629476 0.0685413889 0.0685413869 

14 0.0609214817 0.0562211 160 0.0629887267 0.0629887267 0.0779993863 0.0779993863 0.0779993863 0.0912650000 0.0912650000 0.0912650000 0.0912650000 0.0671175363 0.0671175363 

15 0.0649907135 0.0607579027 0.0667909366 0.0667909366 0.0761037810 0.0761037810 0.0761037810 0.0905726397 0.0905726397 0.0905726397 0.0905726397 0.0651260461 0.0651260461 

16 0.0724418316 0.0715477952 0.0751790074 0.0751790074 0.0728035185 0.0728035185 0.0728035185 0.0775387708 0.0775387708 0.0775387708 0.0775387708 0.0605241028 0.0605241028 

17 0.0773519648 0.0803647101 0.0757034489 0.0757034489 0.0526405510 0.0526405510 0.0526405510 0.0464337395 0.0464337395 0.0464337395 0.0464337395 0.0557685235 0.0557685235 

18 0.0770777578 0.0832250581 0.0684911688 0.0684911688 0.0347686748 0.0347686748 0.0347686748 0.0260342365 0.0260342365 0.0260342365 0.0260342365 0.0506461891 0.0506461891 

19 0.0635977420 0.0637849687 0.0526386278 0.0526386278 0.0285090860 0.0285090860 0.0285090860 0.0173341336 0.0173341336 0.0173341336 0.0173341336 0.0402747366 0.04027 47366 

20 0.0483079600 0.0462284324 0.0372839274 0.037283927 4 0.0220585728 0.0220585728 0.0220585728 0.0112536468 0.0112536468 0.0112536468 0.0112536468 0.0310667712 0.0310667712 

21 0.0383158572 0.0386568197 0.0292289942 0.0292289942 0.0174082029 0.0174082029 0.0174082029 0.0076615624 0.0076615624 0.0076615624 0.0076615624 0.0268533367 0.0268533367 

22 0.0305027859 0.03251 07827 0.0236169348 0.0236169348 0.0137124544 0.0137124544 0.0137124544 0.0062358957 0.0062358957 0.0062358957 0.0062358957 0.0231915644 0.0231915644 

23 0.0214502991 0.0236017051 0.0170601049 0.0170601049 0.0139442910 0.0139442910 0.0139442910 0.0053276381 0.0053276381 0.0053276381 0.0053276381 0.0193751364 0.0193751364 

24 0.0145073780 0.0159083752 0.0113147831 0.0113147831 0.0121850602 0.0121850602 0.0121850602 0.0046510979 0.004651 0979 0.0046510979 0.0046510979 0.0159618330 0.0159618330 

Source: Statewide averages developed !rom Indiana Department of Transportation traffic count data. 
Appendix G 

Indiana Default Daily Distribution Factors: 

dayiD 

monthiD 2 5 

1 0.2325411725 0.7674588275 

2 0.2380547378 0. 7619452622 

3 0.2393402049 0.7606597951 

4 0.2396052454 0.7603947546 

5 0.2484757701 0. 7515242299 

6 0.2489743665 0.7510256335 

7 0.2481153021 0. 7518846979 

8 0.2527028648 0.7472971352 

9 0.2496078420 0.7503921580 

10 0.2462808693 0.7537191307 

11 0.2439742406 0.7560257594 

12 0.2258784720 0.7741215280 

Source: Statewide averages developed from Indiana Department of Transportation traffic count data. 
Appendix H 

Indiana Default Monthly Distribution Factors: 

monthiD monthVMTFraction 

1 0.0733424010 

2 0.0693661929 

3 0.0827036024 

4 0.0831789580 

5 0.0891346903 

6 0.0888150873 

7 0.0907968617 

8 0.0918542094 

9 0.0854175366 

10 0.0875162272 

11 0.0812354405 

12 0.0766387926 

Source: Statewide averages developed from Indiana Department of Transportation traffic count data. 
Appendix I 

Lake and Porter Counties Ramp Fractions: 

Road Type 

2 

4 

Ramp 

Fraction 

0.79% 

6.66% 

Source: Analysis of VHT from the CMAP travel demand model.