# APPENDIX A Air Quality System Data

## This page left inte ntionally blankAppendix A-1 (DRAFT)Air Quality System (AQS) Data Report2006 Through September 2011 (current as of October 3, 2012)AirQualitySystem(AQS)DataReportEXCEPTIONALDATATYPESEDTDESCRIPTION0NOEVENTS1EVENTSEXCLUDED2EVENTSINCLUDED3EXCEPTIONALEVENTSEXCLUDED4NATURALEVENTSEXCLUDED5EVENTSWITHCONCURRENCEEXCLUDED6EXCEPTIONALEVENTSWITHCONCURRENCEEXCLUDED7NATURALEVENTSWITHCONCURRENCEEXCLUDEDIndianaPartsperMillionStateCountySiteIDParameterCode(Ozone)POCYearADDRESS%ofOBS1stMax8‐HR2ndMax8‐HR3rdMax8‐HR4thMax8‐HR1889224420112006MISSISSIPPIST.,IITRIBUNKER980.0780.0740.0730.0731889224420112007MISSISSIPPIST.,IITRIBUNKER790.0890.0890.0850.0851889224420112008MISSISSIPPIST.,IITRIBUNKER930.0770.0660.0630.0621889224420112009MISSISSIPPIST.,IITRIBUNKER960.0610.0590.0580.0581889224420112010MISSISSIPPIST.,IITRIBUNKER800.080.0670.0640.0641889224420112011MISSISSIPPIST.,IITRIBUNKER980.0830.0670.0660.06618893044201120061OLIVERST/WHITINGHIGHSCHO1000.0860.0850.0830.081Appendix A-2 (DRAFT)18893044201120071OLIVERST/WHITINGHIGHSCHO990.0940.0910.090.08818893044201120081OLIVERST/WHITINGHIGHSCHO790.0660.0650.0650.06218893044201120091OLIVERST/WHITINGHIGHSCHO1000.0710.0690.0670.06218893044201120101OLIVERST/WHITINGHIGHSCHO1000.0720.0720.0710.06918893044201120111OLIVERST/WHITINGHIGHSCHO1000.0750.0690.0690.0691889200844201120060141STSTREET1000.0820.0770.0760.0751889200844201120070141STSTREET960.0870.0820.0790.0771889200844201120080141STSTREET970.0720.0720.070.0681889200844201120090141STSTREET990.0760.0690.0670.0651889200844201120100141STSTREET920.0730.0710.0710.0691889200844201120110141STSTREET910.0740.0730.0730.07218127244420112006DIANARD/WATERTREATMENTPLAN1000.0760.0750.0740.0718127244420112007DIANARD/WATERTREATMENTPLAN970.0910.0890.0890.08418127244420112008DIANARD/WATERTREATMENTPLAN1000.0820.0720.070.06918127244420112009DIANARD/WATERTREATMENTPLAN1000.0730.070.070.06718127244420112010DIANARD/WATERTREATMENTPLAN990.080.0760.0680.06718127244420112011DIANARD/WATERTREATMENTPLAN900.0820.0750.0740.068181272644201120060WESLEY/VALPARAISOWATERDEP990.0780.0740.0720.071181272644201120070WESLEY/VALPARAISOWATERDEP930.0840.0830.0810.08181272644201120080WESLEY/VALPARAISOWATERDEP960.0660.0620.0620.061181272644201120090WESLEY/VALPARAISOWATERDEP1000.0760.0690.0660.064181272644201120100WESLEY/VALPARAISOWATERDEP1000.0630.0620.0620.061181272644201120110WESLEY/VALPARAISOWATERDEP970.0770.0640.0630.063

# 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 Whitingparts 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 09-11parts 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

NO x 

## and VOC Point Source Trends Lake and Porter Counties, Indiana (Tons per Summer Day) Year NO x 

## VOC 2001 209 29 2003 154 23 2005 123 21 2007 120 23 2009 94 23


## Graph 4.1 Lake and Porter Counties, Indiana NO x 

## Point Source Emissions 2001-2009



## 209
154 123 120 94

0 50 100 150 200 250

2001 2003 2005 2007 2009Tons 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 2009Tons per Summer Day



### Year

### Appendix B-4 (DRAFT) NO x 

### Emissions – NW Indiana Electric Generating Units 1999-2011 (Tons per Ozone Season) NO x 

### 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 NO x 

## Emissions - Northwest Indiana El ectric Generating Units. 1999-2011

Graph 4.4 Statewide NO x 

## Emissions from Electric Generating Units, 1999-2011

### Appendix B-5 (DRAFT) NO x 

### Emission Trends – Lake and Porter Counties, Indiana (T ons 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 Categor y 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 TotalTons per Summer Day



### 2001 2003 2005 2007 2009



## Graph 4.5 NO x 

## 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 2009Tons per Summer Day

Year

### Appendix B-6 (DRAFT) VOC Emission Trends – Lake and Porter Counties, Indiana (T ons 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 Categor y and Year, Lake and Porter Counties, Indiana, 2001-2009

0 20 40 60 80 100 120 140

Area Non-Road Mobile Point TotalTons 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 2009Tons 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) NO x 

## Emissions for Lake and Porter Counties, Indiana

0 50 100 150 200 250

Area Non-Road Mobile Point TotalTons 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 TotalTons per Summer Day

2001 2003 2005 2007 2009 

## NO x 

## 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 25.8NonRoad 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

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# 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

- Statew id e Def a ult 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 Schoo l Bus 

## 51 Refuse Truck 

## 52 Single Unit Short- h au l Truck 

## 53 Sing le Unit Long-haul Truck 

## 54 Motor Home 

## 61 Combination Short-hau l Truck 

## 62 Combination Lon g -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 type s 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 identi fication 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 c ritical enough to ca ll 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 th e 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 vehi cles. 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 IND OT con t ained 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 di s tribution 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 corr e l a tio n between MOVES source t ypes 3 1 (passenger tru cks) 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 li ght duty trucks were counted in the vehicle populations. Th e light duty trucks were distributed between MOVES source typ es 31 and 32 as per the Environmental Protection Agency's (EPA) guidance docum e nted in Table A.1 of the appendix of the Technical Guidance on th e Use of MOVES2010 for Emission Invent ory Preparation in State Implementation Plans and Transportat ion Conformity. The guidance provides two sets of factors for distributing MOBILE6

. 2 li ght trucks between MOVES source types 31 a nd 32. These are based on fuel type and are shown in Table 3.

2

## 8 6.2 19 t Duty Trucks in Table 3: Distribution of MO ILE L ' h 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 so urc e 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 typ es (motorcycles and heavy vehicles) were derived by applying the Mileage Accumulation Rate (MAR) method documented in EPA's Te c hnical Guidance on th e 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 MOVE S for a single pollutant and a single year for all vehicles, fuels , months, days , and hour s

. 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 typ e.
The Northwestern Indiana Regional Planning Commission (NIRPC), which i s the metropolitan planning organization (MPO) for Lak e 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 mod e l '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 u s ing s tatewide default VMT distribution facto rs 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 socioeconom ic growth rates fo r 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 rat es were then used to grow the light vehicle popu lation s (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 temperatu res 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 Transpo rtation Improvement Program. and the Indiana State Im plementation Plan for Air Qual i ty , A ppendi x E, deve l oped by NIRPC in June, 2011

. Meteorological data reflect average annual conditions fo r 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 th i s report

. Default VMT Distributions: 

## As part of this effort, INDOT developed a default set of VMT distribution factors by High way Performance Monitoring System (HPMS) vehicle t y pe 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 locat io ns corresponding to each of the four MOVES road types

. Furthermor e, 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 vehic l e 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 4 1315 I 70 MARION 170 MM 83.5



## 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 f ac tors. 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 w e re 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 wa s 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 f a ctors determine what percentage of annual VMT is occur r ing in each month of the year. The statewide default daily distribution fa c tor s are shown in Appendix G. The st a tewide default monthly distribution factor s ar e shown in Appendix H.
Ramp Fractions: 

## The ramp fraction s repr ese nt th e percentage of vehicle

- hours

- traveled (VHT) for road typ es 2 (rur a l restri c ted acc e ss) and 4 (urban restricted access) occurring on the ramps a s sociat e d with tho se 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 Appendi x 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) , NO x, 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/S c ale 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, NO x , and PM 2

. 5 with all Processes Processes supporting subspecies; NO x General Database Name LakePorter LakePorter PM Output Ozone Unit s Select "Grams" and "Miles" and

" Million BTU"

Activity Distance, Population
Output On Road Select "Source Use Type" and "Road Emissions Type" Detail

* Repr ese nt s both L a ke and P o rter Countie s

.

## 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 V ehic l e 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 ana ly s i s of permanent count station data from a statew i de data set.
National defaults

.

Ca l culated from l ocal VMT data. Use travel demand model base year distributions for all years

.

Lo cal 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 l oca l 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 annua l {check if if varies among counties) varies among counties) Consistent with current lo ca l 1/M ProgramAppendixB

e 1ceAge 

### o· 'b

. ISifl UfiOfiS for L k a eand p orter Co unt1es: Source Types age id 11 21 31 32 4 1 42 43 51 52 53 54 61 62 0 0.21 09690540 0.0267370941 0.01 4 5061143 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 .0 58207478 1 0.0786470016 0.0624853859 0.0530322328 0

. 0604638952 0.0480275345 0.05718965 1 9 0.0765290827 0.0597715492 0

. 0541045093 0.06776214 4 7 3 0.1359771581 0.06103247 14 0. 05 19847618 0.0656848868 0.0624229593 0.0529792 4 97 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 0.0 474575929 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 0.03613709 41 0

. 0412011709 0.0327268079 0

. 0389700355 0.0521482660 0.0407293873 0.03407 42206 0.0426755959 8 0.0197278356 0.06499971 so 0.064382 7445 0.0597693392 0 .0 488268516 0.0397 426124 0.0453119367 0.0359920640 0.0428582007 0.0573512681 0.0447930981 0

. 0358093100 0.0448486759 9 0.0118473747 0.0677129448 0.0689108213 0.068900 4903 0.0534377006 0.0453533365 0.0517089150 0.0410733035 0.0489087688 0.0654479 137 0.05 11 168252 0.0526288382 0.0659139597 10 0.005325 1 777 0.0607512683 0.0648030151 0.0568165234 0.0532712252 0.0452 12 0443 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 1 075833 0.03 1 3560350 0.039 1 491717 0.0523881239 0.0302729398 0.0478258601 0.0598985955 12 0

. 001301 1 470 0.052980 1 828 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 0.04560897 4 1 0.0333751020 0

. 0545980574 0.0316399801 0.0194774783 0.029 1 673253 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 0.028351 1 969 0.0332950401 0.0210 1 64622 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 0.0096 5 94452 0.007860730 1 0.0226407923 0.0281971934 0.0173882093 0.027008 1 845 0.0289395633 0.0183674556 0.0265944575 0.0265427135 0.0095755 11 2 21 0.0000010015 0.0060838669 0.00 75445 351 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 0.0043586 12 8 0.0031760526 0.0221366577 0.0207614938 0.0211741003 0.0294241579 0.0211707159 0.0029207200 0

. 0 232916866 0.0259516972 0.002 1 970287 23 0.0000002372 0.0034656381 0.0032604864 0.0028187467 0.0 1 87753208 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 0.0 1 65801584 0

. 015344 1 343 0.0162223474 0.0195371739 0.0 1 81341022 0.0013228019 0.0186391363 0.0 1 94375881 0.0028947085 25 0.0000000515 0.002067222 7 0.00 18 979963 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 .00 152 38168 0

. 0010100052 0.0009131 1 51 0

. 0052066606 0

. 0114707358 0.0046276161 0

. 0058785937 0

. 0158244798 0.0000000000 0.0 12 3859355 0.0061039775 0.0003051544 27 0.0000000084 0.0007410082 0.0008269841 0.0008535641 0

. 0044375500 0

. 0062552616 0.0034269422 0

. 0066192300 0

. 0082431519 0.0005853 113 0

. 00 7 3123264 0.0052023202 0.0002365920 28 0.0000000046 0

. 0008208090 0

. 0006507416 0.0006550608 0

. 0038534093 0

. 0027 1 53367 0.0040227141 0

. 0058648852 0.0078447522 0.000 4224309 0.0040 1991 56 0.0045175071 0.0007539156 29 0.0000000027 0.0007486082 0.0002846994 0.0002382039 0

. 0050202650 0 .007 38 1 3428 0.003955 7 847 0

. 00147022 1 1 0.00829 1 0352 0.0000000000 0.000529 7 244 0

. 0058854602 0.0002483418 30 0.0000000060 0.0106363170 0.0052872753 0 .00 46449769 0

. 004164 1 999 0.0025473919 0.0046291194 0

. 0021486392 0 .0093642209 0.0005969550 0.00697 2 0059 0

. 0048818593 0.0002641374

Source: Quafi ly assured veh i cle registration data for the combined Lake County and P orter C ounty area f or source types 2 1. 32, and 32 , MOVES201 Oa default d is trib utions for a ll othe r source types

.AppendixC

L k

a eand orter 

## c o un ties e icle Pooulations: Ve hi cl e Popul ations Source Type s 11 21 3 1 32 41 42 43 51 52 53 54 61 62 Annual Popul ations 2006 12,164 276 , 531 159 , 214 46,74 6 293 15 7 2 ,005 56 3,634 434 631 6,485 7 ,399 2009 12 ,247 278,4 18 160,301 49,078 296 159 2.021 58 3,664 437 836 6,539 7,46 1



### -- 2010 12,330 280 ,31 8 161,395 4 9, 413 2 98 16 0 2,038 59 3,694 441 845 6 , 593 7, 523 2011 12,41 4 282 ,23 1 162.496 49,7 51 30 1 161 2.055 59 3,725 445 852 6.848 7 , 586 20 12 12.499 284,156 163,605 50,090 303 163 2,072 60 3,756 448 859 6,703 7,849 20 1 3 12.584 286,095 184,721 50,432 306 164 2 ,089 60 3,788 452 867 6,759 7,7 1 3 2014 12,670 288,048 16 5 , 845 50,n6 308 166 2 , 107 61 3,819 456 874 6,816 7,n7 2015 12,7 57 290 , 013 166,977 51,122 311 167 2.124 61 3,851 460 881 6,872 7,842 20 1 6 12,844 291,992 168,116 5 1, 47 1 3 14 168 2 , 142 62 3,883 463 888 6,930 7,907 20 1 7 12, 931 293 ,984 169,263 51 ,8 22 3 1 6 1 70



## - 2 , 1 60 62 3,915 467 896 6,987 7,973 20 1 8 13,020 295 , 990 170 , 418 52 , 1 76 3 1 9 17 1 2,178 63 3,948 471 903 7,046 8,039 20 1 9 13,108 298,010 171,581 52 , 532 322 173 2 , 1 96 63 3,981 475 911 7, 1 04 8,106 2020 13,198 300,044 172,752 52,891 32 4 174 2 , 214 64 4 .01 4 479 918 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



### - 2 0 22 13.379 304 , 1 52 175,117 53,615 330 1n 2,25 1 65 4 ,08 1 487 934 7 , 283 8,3 11 2023 13,470 306,2 28 176,312 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 ,40 5 8,450 2025 13,654 310, 4 21 178,727 54 ,720 338 181 2,308 67 4 .18 4 499 957 7,4 67 8.520 2026 1 3,748 312,539 179,946 55,093 3 41 183 2,327 67 4 ,219 504 965 7 , 529 8,591 2027 13 ,8 4 1 314,672 18 1 ,174 55,469 3 44 1 84 2,347 68 4 ,25 4 508 973 7 , 592 8,663 2028 1 3,936 316,819 182,410 55 , 84 8 3 4 6 186 2 , 366 68 4 ,290 5 1 2 982 7 ,65 5 8,735 2029 14 ,031 318.981 183,655 56,229 3 4 9 18 7 2,386 69 4 ,325 5 1 6 990 7 ,719 8.808



## - 2030 14 , 127 321,158 184,908 56,612 352 189 2,406 69 4 ,361 521 998 7 , 78 3 8,88 1 203 1 14 ,223 323.349 186,170 5 6,999 355 191 2.426 70 4 ,39 8 525 1, 006 7,848 8,955 2032 1 4 ,32 0 325, 55 6 18 7 ,440 57 ,388 358 192 2,446 71 4,434 529 1,015 7,9 1 3 9,030 2033 1 4.4 1 8 327,m 188, 71 9 57,779 36 1 194 2,467 71 4,471 534 1 ,023 7,979 9, 1 05 2034 1 4,5 1 6 330,014 190,007 58,174 364 195 2,487 72 4 , 509 538 1 ,032 8 , 046 9 , 1 81 2035 1 4.6 1 5 332,265 19 1 ,304 58,571 367 197 2,508 72 4,546 543 1 , 040 8 , 11 3 9,257 2036 1 4,7 1 5 334,533 192 ,609 58,970 370 199 2,529 73 4.584 547 1 ,049 8 , 18 1 9,334 2037 1 4 , 8 1 5 336,815 1 93,923 59,373 373 200 2,550 7 4 4 ,622 552 1 ,058 8 ,2 49 9 ,4 12 2038 14 ,9 1 6 339,1 14 195,247 59 , n8 376 202 2 , 571 74 4 ,66 1 556 1 ,066 8,317 9. 4 90 2039 1 5,0 1 8 341 , 4 28 196,579 60,186 380 204 2,593 75 4 ,700 56 1 1 ,075 8,387 9,570 2040 1 5. 1 21 343 ,7 57 197,920 60.596 383 205 2,61 4 75 4 ,739 566 1 ,084 8.457 9,649 Source. Q u ahty assured veh 1 cle reg iStraOon da ta for th e 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 loca l socioeconomic data f orecasts.

### Appendix D



## L k

a ean 

## dPrt 

## C t" Mt

. I D 

## t o er oun1es e eoro og1ca a a: Ozone 

### PM2.5 monthiD zoneiD HouriD temperature reiHumidit y monthiD zoneiD HouriD temperature r e iH umidity 

### 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 1808 90 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 7 4.5 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

Sou rc e: Mobile 6.2 reported meteorological data from Air Quality Conformity Determina t ion Between the 2040 Regional Transportation Plan, the Fiscal Year 2012 to 2015 Transportation Improvement Program , and th e Indiana State Implementat i on Plan for Air Quality, Append i x E , developed b y NIRPC i n 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 6 1 62 1 0.01259032 47 0.0101219844 0.0084967341 0.00849673 4 1 0.02549 1 3340 0.0254913340 0.0254913340 0.0126607789 0.0126607789 0

. 0126607789 0.0126607789 0.0 1 97906895 0.0 1 97906895 2 0.0104070951 0.0069241973 0.0066421955 0.0066421955 0.0269500431 0.026950043 1 0.0269500431 0.011 4 617645 0.0114617645 0

. 01 14617 645 0.01 1 4617645 0

. 02 12124 099 0.0212 1 24099 3 0.0098043179 0.0056567534 0.0061275627 0.0061275627 0.0231103443 0.0231103443 0.0231103443 0.0107741941 0.0 1 07741941 0.01077 4 194 1 0.01077 4 1941 0.0201622890 0.020 1 622890 4 0.0 1 40329469 0.0069658232 0

. 0084286563 0.0084286563 0.0234460042 0.0234460042 0.0234460042 0.0128724692 0.0 1 28724692 0.0128724692 0.0128724692 0

. 02 1 3065902 0.0213065902 5 0.0165212 4 05 0.0 10094 1552 0.0134026652 0.0134026652 0.0244090660 0.0244090660 0.0244090660 0.017 4195788 0.0174195 788 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 0.026 1 005783 0.026 1 005783 0

. 0304976568 0.0304976568 7 0.0399082603 0.0390974746 0.0481531313 0.048153 13 13 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

. 038607 16 81 0.038607 1681 0.0556119122 0.0556119122 0.0556119122 0.0556119122 0.0383435322 0.0383435322 9 0.0472316355 0.0493101459 0.0541442978 0.0541442978 0.0454 144773 0.0454144773 0.0454144773 0.0647383083 0.0647383083 0.0647383083 0.0647383083 0.0447350945 0 .044 7350945 10 0.0521292001 0.0488627065 0.0570682751 0.0570682751 0.0533 1 97396 0.0533 1 97396 0.0533 1 97396 0.07 11110 358 0.0711110358 0.0711110358 0.0 7 1 1 110358 0.05 17738 130 0.0517738130 11 0.055920 44 81 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 0.05495412 12 0.054954 1212 0.073 1 872952 0.0731872952 0.073 1 872952 0.0 73 1 872952 0.057 1 435296 0

. 057 1 435296 13 0.0592008057 0.05515861 41 0.0599414146 0.05994 1 41 4 6 0.054 15418 40 0 .05415418 4 0 0.054154 1 840 0.073932445 4 0.0739324454 0.0739324454 0.0739324454 0.0567 01 453 6 0.0567014536 14 0.0615145144 0.0595500442 0

. 0635019874 0.0635019874 0.0570747392 0.05707 47392 0.05 70 747392 0.07 4648 8 056 0.07 46488056 0.07 46488056 0.07 46 4 88056 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 0.055 19 56709 0

. 0551956709 0.0551956709 0.0628801912 0.0628801912 0.0628601912 0.0628601912 0.0577540296 0.0577540296 17 0.07 54978425 0.0847160034 0.0792545794 0.0792545794 0.0557979766 0.0557979766 0.0557979766 0.0534712990 0.0534712990 0.0534712990 0.0534712990 0.05629108 14 0.0562910814 18 0.0693763461 0.0821220539 0.0693254052 0.0693254052 0.05010 1 1685 0.0501011685 0.050 1 011685 0.0436895095 0.0436895095 0.0436895095 0.0436895095 0.0527021980 0.0527021980 19 0.0542 1 87052 0.0620082513 0 .052104 5300 0.052 1 045300 0.0459685909 0.0459665 909 0.0459665909 0.0363413 12 6 0.03634 1 3126 0.03634 1 3126 0.03634 1 3126 0.0502215 1 00 0.0502215100 20 0.0432 1 43461 0

. 0459015588 0.0390794599 0.0390794599 0.0462959768 0

. 0462959768 0.0462959768 0.0312048570 0.03 1 2048570 0.0312048570 0 .0 3 1 2048570 0.04671 1 6534 0.0467116534 21 0.0358137860 0.0372595462 0.03110 15284 0.031 1 015284 0.0418602463 0.04 18602463 0.0418602463 0.0261242877 0.0261242877 0.0261242877 0.026 1242 877 0.0421311043 0.042131 1 043 22 0.0294294934 0.0312744978 0

. 0 24 9803003 0.0249803003 0.03664967 45 0.0366496745 0

. 03664967 4 5 0.02 15822587 0.02 15 822587 0.0215822587 0.0215822587 0.0381387483 0.0381387483 23 0.0223450238 0.0235734666 0.0182964081 0.018296408 1 0.0347517842 0.0347517842 0.0347517842 0

. 0189759266 0.0 189759 266 0.0189759266 0.0189759266 0.03 4 2326572 0

. 0342326572 24 0.0 1 79418099 0.0169198902 0.0133 1 94323 0.0133194323 0.0310595247 0.0310595247 0

. 0310595247 0 .0157396039 0 .0157 396039 0.0157396039 0.015739603 9 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 T ypes 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. 1 186794422 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. 1 154539418 0. 1154539418 0.1154539418 0.0859045570 0.0859045570 0.0859045570 0.08590 455 70 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 0.068 1 384267 0.068 1 384267 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 0.078511583 1 0.076511583 1 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 0.05 17440242 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 0.04 13 186686 0.04 131 86686 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 .006166397 9 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 T ransportation traffi c co u nt data.Indiana Default Hourty Distribution Factors for Road Type 4 -Urban Restricted Access : Sou r ce T ypes 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 0.005880 1 326 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 0.0221330 4 92 0.0221330492 0.0117 453229 0.0117 453229 0.0 1 17 4 53229 0.0 1 17 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 0.02040133 12 0.0294638153 0.0294638153 7 0.0461747881 0.0495085217 0.0542 4 14568 0.0542414568 0.0393812372 0.0393812372 0.0393812372 0.0435263184 0.0435263184 0.0435263 1 84 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 1 2 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 1 3 0.0517959830 0

. 04784872 1 6 0.0547982766 0.0547982766 0

. 0637644078 0.0637644078 0.0637644078 0.0808088903 0.0808088903 0.0808088903 0.0808088903 0.0575925555 0 .0575925555 1 4 0.0566713893 0.0502151226 0.0576660799 0.0576660799 0.0625591325 0.0625591325 0.0625591325 0.0811795580 0.0811795580 0.08 1 1795580 0.0811795580 0.0571667797 0.0571667797 1 5 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 1 6 0.0810035452 0.0715596945 0.0786905659 0

. 0786905659 0

. 0609466141 0.0609466141 0.0609466141 0.0727723312 0.0727723312 0.0727723312 0.0727723312 0 .0 567213465 0.0567213465 17 0.0863864724 0.0838541 1 23 0.0821371575 0.0821371575 0.0577256909 0.0577256909 0.0577256909 0 .05633647 61 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 .02 49336618 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 0.01881347 1 1 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 0.0198 1 57539 0.0 1 89063955 0.0154623663 0.0154623663 0.0217813392 0.0217813392 0

. 0217813392 0.0110419727 0.0110419727 0.0110419 7 27 0.0110419727 0 .02 78292477 0.0278292477
Source : Statewide averages developed from Indiana Departmen t of Transportation traffic count data.Indiana Default Hourly Distribution Factors for Road Type 5 -Urban Unrestricted Access : Source Types Hour 11 2 1 31 32 4 1 42 43 51 52 53 54 6 1 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 0.012 1 505035 4 0.0047017359 0.0044201 1 59 0.0042394230 0.0042394230 0.0113599945 0.0113599945 0.0113599945 0.0056282193 0.0056282193 0 .00 56 2 82193 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 .0 086545038 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 0.019 1822 890 0.019 1 822890 0.0299165403 0.0299165403 7 0.0435184779 0.0478282898 0.0541952158 0.0541952158 0.0448331117 0.0448331 11 7 0.0448331117 0.0418068371 0.0418068371 0

. 041806837 1 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 0.0860926 1 25 0.0880926125 0.0880926125 0.0640862836 0.0640862836 1 0 0.0485821670 0.0466493 1 63 0.06032839 1 6 0.0603283916 0 .0 803995772 0.0803995772 0.0803995772 0.0921313810 0.0921313810 0.092131381 0 0.0921313810 0

. 0680944168 0.0680944 1 68 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 1 2 0.0573056055 0.0516032787 0.06 1 5645883 0.06 1 5645883 0.0753332651 0.07 53332651 0.0753332651 0.0911430924 0.0911430924 0.0911430924 0.09 1 1430924 0.0698309800 0.0698309800 13 0.0607752380 0.0555323 1 43 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 .0 562211 1 60 0.0629887267 0.0629887267 0.0779993863 0.0779993863 0.0779993863 0.0912650000 0.09 1 2650000 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

. 065126046 1 16 0.0724418316 0.0715477952 0.0751790074 0.0751790074 0

. 0728035185 0.0728035185 0.0728035185 0.0775387708 0.0775387708 0.0775387708 0.0775387708 0.060524 1 028 0.0605241028 17 0.0773519648 0.0803647101 0.0757034489 0.0757034489 0.05264055 1 0 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 0.017334 1 336 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 0.03106677 1 2 21 0.0383158572 0.0386568197 0.0292289942 0.0292289942 0.0174082029 0.0 1 74082029 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 0.01371245 44 0

. 0137124544 0.0062358957 0.0062358957 0.0062358957 0.0062358957 0.0231915644 0.02319 1 5644 23 0.0214502991 0.0236017051 0.0170601049 0.0 1 70601049 0.0139442910 0.01394 4 2910 0.0139442910 0.0053276381 0.0053276381 0.0053276381 0.0053276381 0.0193751364 0.0193751364 24 0.0145073780 0.0 1 5908375 2 0.0 11 3 14 7831 0.0 1 13147831 0.0121850602 0.0121850602 0.0121850602 0.0046510979 0.004651 0979 0.0046510979 0.0046510979 0.0 1 59618330 0.0 1 596 1 8330

Source: Statewide averages deve l oped !rom Indiana Department of Transportation traffi c 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 de v eloped 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.