appendix 4. travel demand model methodology and air quality

APPENDIX 4 to the REGIONAL TRANSPORTATION PLAN 1

APPENDIX 4.

TRAVEL DEMAND MODEL METHODOLOGY AND AIR QUALITY CONFORMITY ANALYSIS

Contents Section 1 - Travel Demand Forecast Model Procedures and Assumptions Section 2 - Population and Employment Forecasts Section 3 - The Air Quality Conformity Process Section 4 - Transportation Analysis Zones, Network and Travel Demand Model Section 5 - Travel Demand Model Results and Regional Travel Section 6 - Carbon Monoxide Mobile Source Emissions Forecasts Section 7 - PM10 Modeling Assumptions Section 8 - Ozone Modeling Assumptions Section 9 - Finding of Air Quality Conformity Section 10 - Transportation Control Measures Section 11 - Conformity Analysis Index Appendix 4-A - RTC 2004 Regional Travel Demand Model Package 2 –Transit Processing and Mode Choice Modeling Capabilities Appendix 4-B - NDOT’s Traffic Volume Projections for Externals.

1. Travel Demand Forecast Model Procedures and Assumptions

Background The Las Vegas Regional Travel Demand Forecast Model follows established professional practice through the implementation of the conventional “four step” travel demand forecasting process. The first step is known as Trip Generation, in which person trips produced in and attracted to each zone are calculated from the estimates of population, employment and other socio-economic variables discussed in Appendix 3.Regional Forecasts. In the second step known as trip distribution, these productions and attractions are associated with each other through algorithms that develop a pattern of zone-to-zone movements. In the third step, Mode Choice, the zone-to-zone person trip estimates are converted into auto trips based on average vehicle occupancy rate and person transit trips. In the final step, the demand for vehicle travel is assigned to the street network to give estimates of traffic flow and the demand for transit is assigned to the transit routes to give transit ridership estimates. The Regional Transportation Commission Travel Demand Model (RTC Model) calculations are performed using the TRANSCAD software package developed by the Caliper Corporation of Newton, Massachusetts. The RTC model was converted and has incorporated a series of improvements over years. Table1. below provides the current RTC 2004 Model chronology and components, and the evolutions of the main input assumptions and the model procedures.

2 REGIONAL TRANSPORTATION COMMISSION OF SOUTHERN NEVADA

Table 1. Model Chronology Name of Model Developer Release

Date Software Platform

Calibration Year

# of TAZs

Features Utilized by RTC 2004 Model

Resort Corridor MIS Interim Mode Choice

Parsons Brinkerhoff Quade & Douglas

1995 Tranplan 1995 751 Model structure and mode choice model

Las Vegas Travel Demand Model

Parsons Brinkerhoff Quade & Douglas

2000 Tranplan 1995 1140 Visitor trip generation models; visitor distribution models; other trip matrix; Use of trip rates developed from the 1996 household travel survey, Improved estimation of visitor trips using data from the 1996 visitor and airport surveys,

RTC Las Vegas Phase I Model

Caliper Corporation

2002 TransCAD 4.0

2000 1140 Time of day distribution; highway skims; feedback looping, Locating and coding of over 800 traffic count locations and 40 screen lines for use in model calibration,

RTC Las Vegas Phase I Model Update

Caliper Corporation

2003 TransCAD 4.6

2000 1218 TAZ structure; employment planning variables; highway network; highway assignment; cold start flows and VMT

RTC Phase 1A Regional Travel Model

Parsons Corporation

2003 TransCAD 4.6

2000 1218 Household planning variables; highway network classification; resident socioeconomic sub-models; resident trip generation models; resident trip distribution models; auto occupancy models

RTC 2004 Model (Update Package 1)

Parsons Corporation

2006 TransCAD 4.7

2002/2003 1219 Updated planning variables; updated highway networks; updated link capacities; added special generators; initialized travel times; updated time of day distributions; updated transit share matrix

RTC 2004 Model (Update Package

2A)

Parsons Corporation

2008 TransCAD 4.8

2002/2003 1645 Added additional and optional capabilities, including transit network and path-building processing, Mode Choice modeling, HOV procedures and transit assignment procedures. Added TAZs (1635 internal TAZs) to enlarge the modeling area, including Bounder City area; Updated planning variables; updated highway networks.

Source: Regional Transportation Commission of Southern Nevada


RTC Regional Travel Demand Model (without Mode Choice Element) Flow Chart 1.


RTC Regional Travel Demand Model (without Mode Choice Element) Flow Chart 2.


The major latest model and zone system updates include:

• Added additional and optional capabilities, including transit network and path-building processing, Mode Choice modeling, HOV procedures and transit assignment procedures.

• Enlarge and Refinement of the zone system to include Boulder City, Apex area for the City of North Las Vegas and some other areas; increase the number of zones from 1219 to 1645 (1635 internal zones plus 10 external zones),

• Addition of network links,

An important part of the model improvement process has been a regular program of inter-agency consultation among the RTC, local entities and the Nevada Department of Transportation (NDOT). This was accomplished previously through the establishment of the Travel Demand Forecasting and Modeling Subcommittee (TDFMS) and later has been accomplished through the monthly Modeling Working Group meetings. Many of the changes made have been discussed and refined through this process. The latest version of the updated RTC model is named as RTC 2004 Model (Package 2A), it is employed in this TIP and RTP development and air quality conformity determinations. For the whole RTC model structure, refer to Appendix II B Travel Demand Model Documentation, Regional Transportation Plan FY 2006-2030 October 2006, by Regional Transportation Commission. For documentation about the Mode Choice, HOV procedures and Transit Assignment procedures included in the RTC 2004 Pack 2A, see Appendix A RTC 2004 Regional Travel Demand Model Package 2 –Transit Processing and Mode Choice Modeling Capabilities at the end of this document.

2. Population and Employment Forecasts

2.1 Background The key planning assumptions made as a foundation for the air quality emissions analysis and Conformity Finding relate to the projection of future land use, population and employment. These projections are used to determine future travel demand and travel patterns and the effect these will have on mobile source emissions. Recognizing the complexity of land use forecasting, the Southern Nevada Regional Planning Coalition (SNRPC)1 formed a Land Use Working Group (LUWG) at the request of Regional Transportation Commissions of Southern Nevada (RTC). LUWG is responsible for providing forecasted land use activity for the RTC. The LUWG consists of planning staff from Clark County and the cities of Las Vegas, North Las Vegas, and Henderson. In accordance with inter-local agreement and established practice, the population and employment projections used in this analysis are based upon those

1 In its 1997 session, the Nevada State Legislature enabled the formation of the Southern Nevada Regional Planning Authority (SNRPA). There are ten members in the Coalition membership and Board. Two elected officials are appointed by the governing body of each public entity (except Boulder City and the Clark County School District with one appoint member each). The SNRPC conducts some of its business through subcommittees.


developed by Clark County and local government land use planning staff. The total projections then were matched to the total projections by the Center for Business and Economic Research at the University of Nevada, Las Vegas (CBER). For the detailed development of the Planning Variable (Land use, Population, Employment, etc.), refer to Appendix 3 of this RTP.

2.2 Clark County and Regional Population and Employment Forecasts The CBER forecasts are for Clark County as a whole. The TDF model covers the area generally known as the Las Vegas Valley, comprising the Cities of Las Vegas, North Las Vegas and Henderson as well as those parts of unincorporated Clark County lying within the Bureau of Land Management Cooperative Land Sale and Exchange Area as designated by the Southern Nevada Public Land Management Act of 2002 displayed in Figure 1-4 as the BLM Disposal Boundary (2002). The Las Vegas Non-Attainment Area is defined as Hydrographic Basin 212, which is centered on the Las Vegas Valley. It includes bordering upland and mountain areas that are mostly uninhabited and that are held as open and recreational lands by various Federal and State agencies. The few settlements within these outlying areas have a total population of less than 2,000. In developing the CO SIP, it was agreed between the local air planning agency and the US EPA that it was acceptable to use the modeled area as a basis for estimating the mobile source emissions to be used in setting the mobile source emissions budget and in subsequent conformity determinations. Most of the population in Clark County is concentrated in the Las Vegas Valley. Based upon analyses performed in the mid-1990s, it has been estimated that 95 percent of the population of the County lives within the valley. This percentage is embodied in a number of inter-local agreements by various agencies involved in planning activity, including Clark County’s Planning Department, the School District, the RTC, the Southern Nevada Regional Planning Coalition and the Southern Nevada Water Authority, and it is, therefore, used to calculate the population control total for the Las Vegas Valley in the travel demand forecasting and air quality conformity process. The future year land use forecast was created through the work of Southern Nevada Regional Planning Coalition (SNRPC) Land Use Workgroup (LUWG) with the members representing the cities of Las Vegas, North Las Vegas, Henderson, urbanized Clark County and the RTC. The Workgroup was formed to develop a consensus based process to define future land use development plans for the RTC’s transportation planning process. Based on the available vacant land of the Assessor’s 2006 closed roll parcel, the group created GIS data of planned land development using the RTC/SNRPC planned land use development definition. This future land use is in 5-year increments by jurisdiction covering the years from 2005 through 2035. Table 2 sets out the forecast developed acres for 2005 to 2030. There are two parts to the development of the land use forecast: 1) determining the current and future land use development patterns and 2) converting the land use patterns to the planning variables (PV) that are inputs to the travel demand forecast model.


Table 2. Forecast Developed Acres, 2005-2030 Forecast Growth Acres Time Period

Residential Non-Residential Total 2006-2010 15,558 16,214 31,771 2010-2015 16,212 15,092 31,304 2015-2020 16,565 15,664 32,229 2020-2025 9,900 9,900 19,800

2025-2030 4,900 4,972 9,872

Total 63,136 61,841 124,977 Non-Residential includes open space Source: Regional Transportation Commission, Planning Variable Development and Methodology, 2008. Table 3. Summary of Planning Variables 2005 -2030

FIELD Year 2005 Year 2008 Year 2013 Year 2020 Year 2030

2013 % of 2008

2020 % of 2008

2030 % of 2008

POP 1,769,532 2,022,523 2,431,048 2,877,544 3,230,493 120% 142% 160%DU 686,226 780,260 938,335 1,120,702 1,233,422 120% 144% 158%ODU 656,743 746,472 896,869 1,069,077 1,172,324 120% 143% 157%HH_SIZE 3,051 3,050 3,183 3,507 3,869 104% 115% 127%TOTEMP 829,586 965,359 1,168,664 1,418,536 1,653,399 121% 147% 171%HOTEL 249,561 285,419 338,519 384,933 406,583 119% 135% 142%OFFICE 141,134 164,552 202,971 252,978 286,311 123% 154% 174%INDUST 123,672 147,614 184,468 237,792 317,241 125% 161% 215%OTHER_NON 167,735 195,641 231,207 290,612 364,429 118% 149% 186%RETAIL 147,484 172,133 211,498 252,221 278,835 123% 147% 162%NAFB 12,000 13,200 14,600 15,000 15,000 111% 114% 114%MIA_EMP 16,569 18,250 21,222 21,117 21,117 116% 116% 116%MIA_PASS 121,423 134,295 154,626 144,247 144,247 115% 107% 107%IVPH_EMP 0 300 3,200 5,117 8,177 1067% 1706% 2726%IVPH_PASS 0 0 0 42,059 67,213 UNLV_MAIN_EMP 2,570 2,807 3,299 3,521 3,521 118% 125% 125%UNLV_MAIN_ENR 28,104 30,809 36,286 38,734 38,734 118% 126% 126%UNLV_NLV_EMP 0 0 0 1,000 3,000 UNLV_NLV_ENR 0 0 0 10,000 30,000 NEV_ST_COLL_EMP 103 161 275 450 750 171% 279% 465%NEV_ST_COLL_ENR 1,562 3,025 6,400 12,000 20,000 212% 397% 661%F18 206,888 216,320 231,938 253,308 262,608 107% 117% 121%F912 75,282 77,994 84,662 96,002 101,402 109% 123% 130%F13 29,587 31,428 33,528 35,000 35,000 107% 111% 111%

MED_INC 60,755,187 60,755,187 60,755,187 60,755,187 60,755,187 100% 100% 100%

Source: Regional Transportation Commission staff. Table 3. is the summary of the key PVs for the TDF model. The first column has the variable names to be used in the model. Refer to the RTC travel demand model document for detailed planning variable definitions. The green colored columns show the variable totals for the modeling horizon years (2013, 2020 and 2030) for the RTP


2009-2030. The graph below shows the population, occupied dawdling units (households) and total employment growths for the plan forecast horizon years.

Population, Households and Total Employment

2013 2020 20300

500,000

1,000,000

1,500,000

2,000,000

2,500,000

3,000,000

3,500,000

1

RTP Horizon Years

Est

imat

ed M

odel

Inpu

t

Year

POP

ODU

TOTEMP

Source: Regional Transportation Commission staff.

In addition to total population, households and employment, the model utilizes certain other socio-economic indicators. These include average household income, school enrollment, and various classes of employment. The number of dwellings in each zone was estimated from land use data on the extent of residential land, using density and occupancy factors derived from the 2000 Census and local entity sources. Average household income and school enrollment were also developed from local sources. A detailed description of the methodology is provided in Appendix III.

3. The Air Quality Conformity Process and Travel Demand Results

3.1. Introduction This section describes the air quality conformity analysis conducted as part of the development of the Regional Transportation Plan 2009-2030 (RTP) and the Transportation Improvement Program for Fiscal Years 2009-2012 (TIP). The Las Vegas region is in non-attainment for three pollutants: carbon monoxide (CO), particulate matter 10 microns in size or less (PM10), and Ozone (O3). Non-attainment is the term used to describe levels of these pollutants that the U.S. Environmental Protection Agency (EPA) has designated as not meeting the clean air standards for that pollutant as defined in the National Ambient Air Quality Standards (NAAQS).


Figure 1. shows Clark County Boundary, RTC TAZ and road network, and the study boundaries for each pollutant. Within Clark County, the area defined as Hydrographic Basin 212 is designated as a non-attainment area for two pollutants – CO and PM10. This area is roughly coincidental with the Las Vegas Valley. On September 15, 2004 the EPA designated about 60 percent of Clark County as non-attainment for O3. This area extends from the Las Vegas Valley south and east to the Colorado River. The Clean Air Act Amendments of 1990 (CAAA) require that each non-attainment area and pollutant be addressed by a control plan, referred to as the State Implementation Plan (SIP), developed by the state air quality planning agency. The SIP sets out policies and actions to ensure that air quality meets the NAAQS within a time frame determined under EPA regulations. In southern Nevada, responsibility for developing the SIP is delegated by the State of Nevada to Clark County. The Clark County Department of Air Quality and Environmental Management (DAQEM) is tasked with SIP development. Under the provisions of the CAAA, the RTC, as the MPO for the region, is the agency responsible for making the determination of conformity. Much of these regulated pollutants is produced by automobiles and other road transportation, so are classified as “mobile source emissions”. Any RTP/TIP must include a determination that implementation will result in reduction of these pollutants to acceptable levels in ways that conform to the SIP. The term “conformity” describes the determination of this acceptable result. Supporting the determination is a complex modeling process that is based on assumptions about what happens if existing conditions are extended into the future and about what happens if the projects and programs in the RTP/TIP are implemented. A conforming RTP/TIP model outcome projects that the regulated pollutants will be reduced to acceptable levels within time frames that meet the NAAQS.

3.2. Conformity Guidelines This Section outlines the complex technical evaluation process involved in the conformity demonstration. Descriptions of other aspects of the process are provided in the Appendices, including a list of the projects included in the Travel Demand Model and details of the Air Quality and Transportation Control Measures assumed in the Model. RTC's Vision Statement is to provide “a safe, clean, effective regional transportation system that enhances mobility and air quality for our citizens and visitors”. To that end, the Commission has adopted the following goal for the transportation planning process:

“Implement transportation systems that improve air quality”


Figure 1. Clark County and RTC Non-attainment Areas


The specific procedures for reaching this goal are those established under Federal law for ensuring conformity between transportation plans and air quality improvement plans. This process of conformity is intended to ensure that the projects and programs proposed in the RTP, TIP and TIP amendments conform to the purpose of the CAAA and the SIPs. This means “...conformity to the (implementation) plan’s purpose of eliminating or reducing the severity and number of violations of the national ambient air quality standards and achieving expeditious attainment of such standards...”. The provisions of the CAAA in relation to conformity are amplified in the US Environmental Protection Agency (EPA) Final Rule, 40 CFR Part 93, as amended September 15, 1997. The conformity determination described in this section was performed in accordance with US DOT and EPA guidance and procedures, and also in accordance with the Transportation Conformity SIP, “Transportation Conformity Plan for the Las Vegas Valley Nonattainment Area”, Clark County Board of Commissioners, 2008

A. State Implementation Plans The State Implementation Plan (SIP) is a federally required document that defines strategies to ensure the existing and future attainment of the National Ambient Air Quality Standards (NAAQS) as defined by the United States Environmental Protection Agency (EPA). For metropolitan planning organizations, like the RTC of Southern Nevada, the SIP also establishes a mobile source emissions budget that is used in the evaluation of transportation plan conformity. A transportation plan is in conformance with the objectives of the SIP when the predicted tailpipe emissions from all travel, as defined in the long-range plan, is at or below the budget thresholds for all of the horizon years that comprise the RTP. The Las Vegas area is in non-attainment for PM10, Carbon Monoxide, and ozone and has approved SIPs for PM10 and CO. On July, 9, 2004, the EPA granted approval of the PM10 SIP. In February of 2006, the Clark County Department of Air Quality and Environmental Management submitted a CO SIP Revision to the EPA approved CO SIP (November 2004) to reflect changes in the EPA modeling process for defining tailpipe emission and to revise the mobile source emission budgets accordingly. The EPA approved the 2006 CO SIP revision on August 7, 2006, with an effective date (date as which the budgets can be used for Conformity) of September 6, 2006. The DAQEM is in the process of developing an Early Progress Plan (EPP) for ozone and expects to submit the document to the EPA in the fall of 2008. In the meantime, the RTC will utilize the EPA approved "Action versus No-Build" test for defining conformity for this pollutant, as there is currently no approved mobile source emission budget or SIP.

B. Regional Emissions Analysis: Budgets for CO, PM10 and Ozone The principal step toward making a conformity determination is to demonstrate that the anticipated levels of atmospheric pollution which will result from planned and programmed transportation projects will be less than the relevant budget defined in the State Implementation Plan.


The CO SIP budgets for mobile source emissions are shown on Table 4.

Table 4. Mobile Source CO Emissions Budgets for the Las Vegas Valley Year CO Emissions Budget (tons per day) 2006 623 2010 690 2015 768 2020 817

Source: Clark County DAQEM, Carbon Monoxide Modeling and SIP Update, August 2006 For PM10, the SIP budget established for 2003 to demonstrate reasonable further progress (RFP) towards attainment of the 24-hour standard, and the budget established for the attainment year of 2006 apply to the conformity determination and are set out in Table 5.

Table 5. Mobile Source PM10 Emissions Budgets for the Las Vegas Valley

Year PM10 Emissions Budget (tons per day) 2003 155.77 (24-hour RFP) 2006 141.41 (24-hour standard)

Source: Clark County DAQEM As defined earlier in this document, the DAQEM will submit an Early Progress Plan (EPP) for O3 to the EPA. The O3 EPP will include a mobile source emission budget for conformity. Prior to approved budgets, marginal and below areas may choose between two measures of conformity:

• The “build-no-greater than no-build” test, a test shows that forecasts of the levels of O3 resulting from the planned projects and programs will be no worse than doing nothing, and

• The “no greater than 2002” test, a test shows that forecasts of the levels of O3 will not be any worse than they were in 2002.

3.3. Regional Emissions Analysis

A. Consultation on Conformity Procedures The technical procedures used to determine the SIP budgets and to demonstrate conformity are developed in conjunction with local entities through the DAQEM Technical Advisory Committee (TAC). DAQEM’s TAC reports to the Executive Advisory Committee of the Clark County Board of Commissioners. This technical committee consists of staff representatives from Clark County, the RTC, the Cities of Boulder City, Henderson, Las Vegas and North Las Vegas, and the NDOT, as well as members from industry and from the public. The DAQEM website is at http://www.co.clark.nv.us/air_quality/index.htm.


Consultation between local and Federal agencies is maintained through the inter-agency consultation procedures contained in the Transportation Conformity SIP, “Transportation Conformity Plan for the Las Vegas Valley Nonattainment Area”, Clark County Board of Commissioners, January 2008. These procedures include periodic meetings of the Air Quality Conformity Working Group. The Air Quality Conformity Working Group meets monthly and discusses a variety of topics related to air quality issues. It consists of representatives from each of RTC’s member entities, in addition to representatives of the Federal Highway Administration, Federal Transit Administration, and the EPA. The main focus of these meetings is to avoid delay in the conformity process by coordinating air quality and conformity discussions.

B. Horizon Analysis Years Under Federal Regulations, conformity has to be determined for a series of “Horizon” years. These must include the designated attainment year, if applicable, and the last year of the Transportation Plan and they must be not more than 10 years apart. For this conformity determination, the following horizon years are used: 2013, 2020 and 2030 for all three pollutants. A second component of a conformity determination is an assessment of the progress in implementing TCMs. These measures are intended to reduce emissions or concentrations of pollutants from transportation sources by reducing vehicle use or otherwise reducing vehicle emissions. As part of the conformity process, the RTC has to certify that TCMs identified in the SIPs are being implemented on schedule and that no federal funds are being diverted from these projects in such a way as to delay their timely implementation. The scope and status of TCMs is further discussed in Section 10 of this document with additional details.

C. Conformity Determination Technical Methodology The calculation of mobile source emissions for each horizon year involves several steps, and these are described in the remaining sections of this chapter, as follows:

• The underlying assumptions regarding population and employment change in the region are outlined in the previous section.

• All regionally significant transportation projects are included in the Travel Demand Forecast (TDF) model, which is then used to forecast vehicle miles of travel (VMT) and travel speeds in the region.

• The Mobile 6.2 emission model is then used to develop emission factors for CO, VOC and NOx (the later two pollutants are two major components of Ozone O3), that indicate how much pollutant are produced for each vehicle mile of travel. These factors are applied to the forecasts from the travel demand model to derive the modeled total of mobile source CO, VOC, NOx emissions.


• The emission benefits from the TCMs are then subtracted from the modeled vehicle emissions to produce a forecast of net mobile source emissions.

• The procedures for establishing PM10 concentrations are described later. The predicted net CO, PM10 and O3 emissions that result from these procedures are then compared with the mobile source emissions budgets described above. The results are set out in Sections 6, 7, 8 and 9.

4. Transportation Analysis Zones, Network and Travel Demand Model

4.1. Transportation Analysis Zones

As noted in sub-section 1.1 and 1.2., the socio-economic data used in the model is disaggregated into 1635 internal Transportation Analysis Zones (TAZs). There are 10 external zones. The total modeling area has been expanded to cover the core areas of the Bounder City, areas north and northwest to the City of North Las Vegas, industrial area northeast to the City of North Las Vegas, and areas around Ivanpah Airport. Most TAZs are bounded by highway or major streets. Railroads and natural barriers such as major washes are also used to define zone boundaries. Zones range from 0.25 to 0.5 sq. mile in most of the developed parts of the region and often 1 sq. mile in the suburbs.

4.2. Model Networks The travel demand modeling process begins with the identification of the streets and highways to be included in the network. The model network includes all roads that are federally classified as collectors or above, as well as streets that are included in the consolidated Master Plan for Streets and Highways for the Las Vegas Valley. Each link in the network is defined by a number of attributes. The main attributes are:

• Link length • Number of lanes (*) • Posted speed limits (*) • Roadway group • Area type • Free-flow speed • Capacity and • Speed-capacity equation coefficients.

The attributes denoted by an asterisk are coded using a variety of sources, including geographic files maintained by the Clark County GIS Management Office (GISMO), survey photography, local entity records and field checking. Network roads are grouped into 11 facility types and four area types. These classifications are used to enter default values for other roadway attributes such as free-flow speed and capacity and also to summarize system performance.


Figure 2. Travel Demand Analysis Zones


The roadway facility types are based on generalized descriptions of the type of facility. They include:

• Interstates • Other freeways • High-Occupancy Vehicle (HOV)lanes, • Expressways / Beltways • Two classes of arterial roads (Major and Minor) • Collectors • Local roads • Other roads used by transit • Two classes of ramps (Ramp and System Ramp) • Zone centroid connector links • External connector links

The four area types are:

• Central Business District of the City of Las Vegas • Resort Corridor • Other areas characterized by urban density and land use, and • Suburban areas.

The free-flow speeds and capacities are set to default values in look up tables for each facility type and area type. The values for free-flow speeds are set out in Table 6 and capacities in Table 7. Table 6. Free-Flow Speeds

Free-Flow Speeds by Area Type Functional Class CBD Resort Urban Suburban System Ramps 40 40 51 53 Minor Arterials 31 31 36 41 Major Arterials 31 33 39 43 Ramps 15 25 28 36 Interstates 53 53 56 60 Freeways 51 51 54 59 Expressways 50 50 50 50 Collectors 29 29 33 39 Other 25 25 25 25 HOV 55 55 60 65

Source: Regional Transportation Commission, Travel Demand Model, 2004 Pack 2A The speed-capacity equation coefficients were developed as a part of the model calibration process and reflect the observed characteristics of different types of roadway in the area. They are used in the assignment process to control the relationship between traffic flow, capacity and congested time.


Table 7. Free-Flow Capacities

Free-Flow Capacity by Area Type Functional Class CBD Resort Urban Suburban System Ramps 2,000 2,000 2,000 2,000 Minor Arterials 560 600 600 640 Major Arterials 700 750 750 800 Ramps 1,600 1,600 1,600 1,600 Interstates 2,000 2,000 2,000 2,000 Freeways 2,000 2,000 2,000 2,000 Expressways 925 925 925 925 Collectors 420 450 450 480 Other 416 416 416 416 HOV 1,950 1,950 1,950 1,950

Source: Regional Transportation Commission, Travel Demand Model, 2004 Pack 2A

4.3. Horizon Year Networks The development of the future year networks begins with the identification and selection of “regionally significant” capacity-adding transportation projects that are proposed for inclusion in the RTP and TIP. The definition of regional significance is that contained in Section 2.2 of the RTCs “Policies and Procedures”, as amplified through the inter-agency consultative procedures laid down in the “Transportation Conformity Plan for the Las Vegas Valley Nonattainment Area”, Clark County Board of Commissioners, March 2005, and in 40 CFR 93 S.93.101. All such projects are included in the future build networks, irrespective of funding source. Projects are categorized by anticipated horizon year of completion, i.e., 2013, 2020 or 2030. Alignments, design scope and attributes for new roads, and changes in the attributes of existing roads, are defined by NDOT and the local entities as part of the TIP process. Projects included in the model analysis are listed in Appendix I Capital Program Projects. Table 8 summarizes the contents of the 2013 No build year model networks and future build networks. In total, the 2013 No build coded model network covers approximately 3638 link miles of roadway within the valley, as well as links representing the minor roads that connect zone centroids to the network, and roads leading into and out of the region. The 2030 build network has 3,945 link miles and 11,922 lane miles coded in the network. Table 9 shows the link miles and lane miles changes from the previous build horizon year due to the projects included in the next build horizon year. Note that the changes to centroid connector links are set to zero, because these changes are not necessarily caused by the projects, but by the reconfiguration, for coding purposes only, of the zone connections to the future projects. Table 10 shows that all projects included in this RTP will result in 530 more link miles and 2,570 more lane miles for the Valley from year 2013 to year 2030.


Table 8. Network Link Miles and Lane Miles by Roadway Type

2013 No Build 2013 Build 2020 Build 2030 Build

DescriptionLink

MilesLane Miles

Link Miles

Lane Miles

Link Miles

Lane Miles

Link Miles

Lane Miles

External Links 43.11 93.67 43.11 93.67 43.11 93.67 43.11 102.64System to System Ramp 28.83 37.91 28.55 37.63 31.32 43.57 37.39 55.65Minor Arterial 413.62 1,737.96 421.12 1,753.08 478.42 2,091.38 565.19 2,495.08Major Arterial 465.14 2,271.36 466.56 2,285.55 512.23 2,579.74 549.59 2,775.17Ramp 141.79 181.35 143.54 183.39 145.94 186.32 157.71 204.98Interstate 205.49 623.21 205.49 622.91 205.52 643.43 205.52 779.89Freeway 124.38 377.80 124.38 377.80 126.11 403.91 138.12 447.99Expressway/Beltway 0.81 1.90 0.81 1.90 19.78 77.68 19.78 77.68Collector 690.60 1,886.56 690.60 1,886.56 676.18 1,900.94 745.77 2,097.12Centroid Connector 1,455.45 2,910.90 1,455.45 2,910.90 1,341.15 2,682.30 1,334.02 2,668.04Local 21.80 49.86 21.80 49.86 21.80 49.86 27.59 61.44HOV Lanes 20.89 20.89 20.89 20.89 28.53 28.53 95.93 106.35Transit Link 18.75 37.34 18.75 37.34 18.75 37.34 18.75 37.34Transit Access Link 5.93 11.86 5.93 11.86 6.07 12.14 6.07 12.14TOTAL 3,637 10,243 3,647 10,273 3,655 10,831 3,945 11,922Source: Regional Transportation Commission staff

Table 9. Changes in Link Miles and Lane Miles over the Previous Horizon Year

2013 No Build 2013 Build 2020 Build 2030 Build

Description Link Miles

Lane Miles

Link Miles

Lane Miles

Link Miles

Lane Miles

Link Miles

Lane Miles

External Links 0.00 2.86 0.00 0.00 0.00 0 0.00 8.97System to System Ramp 10.64 12.89 -0.28 -0.28 2.77 5.94 6.07 12.08Minor Arterial 51.37 303.61 7.50 15.12 57.30 338.3 86.77 403.70Major Arterial 14.77 158.95 1.42 14.19 45.67 294.19 37.36 195.43Ramp 10.00 17.99 1.75 2.04 2.40 2.93 11.77 18.66Interstate -0.07 71.14 0.00 -0.31 0.03 20.525 0.00 136.46Freeway 9.81 65.96 0.00 0.00 1.73 26.11 12.01 44.08Expressway/Beltway 0.00 0.00 0.00 0.00 18.97 75.78 0.00 0.00Collector -23.57 -25.48 0.00 0.00 -14.42 14.38 69.59 196.18Centroid Connector 0.00 0 0.00 0.00 0.00 0 0.00 0.00Local 0.88 1.76 0.00 0.00 0.00 0 5.79 11.58HOV Lanes 14.36 14.36 0.00 0.00 7.64 7.64 67.40 77.82Transit Link 10.01 19.98 0.00 0.00 0.00 0 0.00 0.00Transit Access Link 2.31 4.62 0.00 0.00 0.14 0.28 0.00 0.00TOTAL 101 649 10 31 122 786 297 1,105

Source: Regional Transportation Commission staff


Table 10. Total Changes in Link Miles and Lane Miles from 2008 Network to 2030 Build Total Changes from2008 to 2030

DescriptionLink Miles

Lane Miles

External Links 0.00 11.83System to System Ramp 19.20 30.63Minor Arterial 202.94 1060.73Major Arterial 99.22 662.76Ramp 25.92 41.62Interstate -0.04 227.82Freeway 23.55 136.15Expressway/Beltway 18.97 75.78Collector 31.60 185.08Centroid Connector 0.00 0.00Local 6.67 13.34HOV Lanes 89.40 99.82Transit Link 10.01 19.98Transit Access Link 2.45 4.90TOTAL 530 2,570 Sources: Regional Transportation Commission staff.

4.4. No-Build Versus Build Year Networks As stated above, currently there is no approved Ozone (O3) mobile source emission budget or SIP, therefore the RTC has to conduct "Action versus No-Build Test” ( known also as Build Versus No-Build Test) for defining conformity for Ozone pollutant. The No-Build network is determined by taking out all projects to be financed by the Federal funding from the Build network for the horizon year. Tables 11 to 13 list all Federal funded projects included in the Build networks but not in the No Build networks for the same horizon years. Figure 3.presents a map that shows the coded road network and all Federal funded projects not in the Build but in the No-Build networks. The projects are colored for different horizon years. Table 11. Federal Funded Projects in 2013 Build But Not in 2013 No-Build (No Action) ProjNo Sponsor Location From To Description

108 Clark County

Cactus Ave. @ I-15 a new interchange @ I-15

843 Henderson SR564 Lake Mead Pkwy Boulder Hwy

Lake Mead National Recreation Area

Widen to 6 lanes and a grade sepaerated intersection at Lake Las Vegas Entrance enhancements

4150 DNOT I-15 S. SR 160 (Blue Diammond) Tropicana Av. Widen from 6 to 8 lanes, include HOV and

auxiliary lanes Source: Regional Transportation Commission staff


Table 12. Federal Funded Projects in 2020 Build But Not in 2020 No-Build (No Action)

ProjNo Sponsor Location From To Description

110 Henderson I-15 @ Starr Construct Interchange

244 NDOT I-15 South Phase 4 Sloan Rd SR 160 (Blue

Diamond) I-15 South Phase 2: widen from 6 to 8 lanes and add additional auxiliary lanes

894 Las Vegas Summerlin Pkwy. Beltway US 95 Widen to 8 lanes

4021 DoA Ivanpah Expressway

Ivanpah Valley Airport I-15 New Alignment (Ivanpah Expressway)

4146 North Las Vegas

Lake Mead Blvd. Losee Rd Las Vegas

Blvd.

Realign roadway and widen to 8 lanes, including dedicated right- and left-turn lanes, auxiliary lanes, and modification of freeway ramps associated with the I-15 interchange. (PE, ROW, Construction

4149 NDOT

I-15 / US 95 (Spaghatti Bowl) Neon Phase 1

Construct a 4 lane system to system direct connect HOV ramps, including add/drop lanes at Oakey/Wyoming. Widen 1-15 to accommodate HOV ramps (PE,RW, Const.)

4242 Las Vegas Elkhorn @US 95 Construct HOV direct connect

4249 Las Vegas Oakey / Wyoming I-15 Mains Street Construct a grade separation at

Oakey/Wyoming Source: Regional Transportation Commission staff


Table 13. Federal Funded Projects in 2030 Build But Not in 2030 No-Build (No Action) ProjNo Sponsor Location From To Description

115 Henderson I-15 @Bermuda Rd Construct an interchange (PE, ROW, Const)

243 NDOT I-15 South CA State Line Sloan Rd Widen from 6 to 8 lanes (PE, ROW, Const)

245 NDOT I-15 (Phase 4) Sloan Rd SR 160 Blue Diamond Rd

I-15 South Phase 4: Widen to 10 lanes and add additional auxiliary lanes

247 NDOT I-15 (Phase 3) SR 160 (Blue Diammond Rd) Tropicana Ave

I-15 South Phase 3: Widen to 10 lanes and additional auxiliary lanes and operational improvements (PE, ROW, Const)

249 NDOT I-515 (Phase 2) Foothills Grade Separation

Charlestion Blvd

Widen to 10 lanes; to include HOV lanes and add new interchange @ Sahara Ave. (PE, ROW, Const)

250 NDOT I-515/US 95 (Phase 1)

Charleston Blvd

I-15/US 95 Interchange (Spaghetti Bowl)

Widen to 10 lanes; to include HOV lanes and add new interchange @ Pecos Rd, F St, (PE, ROW, Const)

758 Henderson I-15 @Sloan Construct an interchange (PE, ROW, Const)

823 North Las Vegas I-15 @Washburn

Rd

Widen from 2 to 4 lanes and construct grade separation over I-15 on Washburn Rd. from Pecos Rd to Lamb Blvd

889 Las Vegas Sheep Mountain Pkwy

@US95 & CC215 Western Beltway

Construct system to system interchange

4144 NDOT I-15 I-215I-15/US 95 (Spaghetti Bowl)

Widen from 10 to 14 lanes to include HOV lanes (PE, ROW, Const)

4147 NDOT

Martin L King Blvd/Industrial Rd Connector Neo

Palomino Ln WyomingConstruct a 6-lane overpass with grade separation at Oakey/Wyoming (PE, ROW, Const)

4148 NDOT US 95 North (Package 2) Ann Rd Kyle Canyon

Rd

Ann to Centennial: widen from 6 to 8 lanes. Add auxiliary lanes.Centennial to Durango: widen from 4 to 8 lanes.Durango to Kyle Canyon: widen from 4 to 6 lanes. (PE, ROW, Const)

4153 NDOT I-15

@I-215 Southern Beltway (Interchange)

System to system direct connector HOV ramps (PE, ROW, Const)

4161 NDOTI-15 Southbound NEON Phase 3

US 95 Sahara AveConstruct SB collector distributor roads with new bridges over Alta, Charleston, and Oakey/Wyoming (PE, ROW, Const)

4162 NDOTI-15 Northbound NEON Phase 4

US 95 Sahara Ave

Construct SB collector distributor roads with new bridges over Sahara Ave., Oakey/Wyoming. Charleston and northbound off ramps to Alta Dr. (PE, ROW, Const)

4167 NDOTSR 160 (Blue Diamond Rd) @ I-15

Construct a flyover ramp from EB SR 160 to NB I-15 (PE, ROW, Const)

4247 Clark County Tropicana Ave Decatur Blvd Polaris Construct a grade seperation over Dean

Martin Drive (PE, ROW, Const)

4248 Clark County Tropicana Ave Polaris I-15

Construct a fourth westbound lane (including replacement of the UPRR Bridge over Tropicana



Figure 3. Federal Funded Projects Included in the Build But Not In NO-Build Horizon Years

Sources: Regional Transportation Commission, Planning

4.5. Transit Network, HOV and Park-and-Ride For the first time, and from this RTP, transit network skims, mode choice and transit assignments are modeled for the Las Vegas Valley. In addition, High Occupancy Vehicle (HOV) and Park –and Ride (PnR) facilities are also coded in the network, and the HOV and PnR trips can be modeled too. Figure 4. presents a map showing the 2030 Build transit network routes and the proposed future Park and Ride facilities.


Figure 4. 2030 Build Transit Routes and Future Park and Ride Facilities (All transit routes = Green; All future Park and Ride Facilities = Red Dots)


5. Travel Demand Model Result and Regional Travel The RTC Travel Demand Model Package 2A, a full four step travel demand model with visitor model elements is used to develop the following model results. A full description of the each step of the RTC Travel Demand Model is contained in Appendix II B Travel Demand Model Documentation, Regional Transportation Plan FY 2006-2030 October 2006, by Regional Transportation Commission. The model’s new capabilities included in Pack 2A, such as Transit Processing, Mode Choice Modeling, HOV and Transit Assignment Capabilities are described at the end of this document. This section summarizes the modeling results from the each step of the RTC Travel Demand Model Pack 2A.

5.1. Trip generation

Trip Generation is the process of generating estimates of the person trips produced in, or attracted to, each zone. Table 14 summarizes the total number of person trips generated by the trip generation step of the travel demand model.

Table 14. Person-Trips in the Las Vegas Valley, 2013-2030

2013 2020 2030Home-Based Work 1,341,000 1,631,301 1,901,401Home-Based School 624,633 738,044 860,949Home-Based Shopping 747,698 880,765 1,019,160Other Home-Based 3,152,269 3,696,292 4,246,291Non-Home-Based 2,397,000 2,837,200 3,278,900Residence Air 18,066 21,577 18,066Total Resident Trips 8,280,666 9,805,179 11,324,767Multi-Day Visitor Trips 645,982 758,839 809,912Visitor Airport Based Trips 142,011 170,180 193,164Total Visitor Trips 787,993 929,019 1,003,076Total Person Trips 9,068,659 10,734,198 12,327,843

Trip PurposeAverage Weekday Person Trips



Figure 5. Average Weekday Person Trips by Purpose (Series 1=2013, Series 2=2020, Series 3=2030)

Average Weekday Person Trips by Purpose

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

Home-B

ased W

ork

Home-B

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Home-B

ased S

hopp

ing

Other H

ome-B

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Non-H

ome-B

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ir

Total R

eside

nt Trip

s

Multi-D

ay Visit

or Trip

s

Visitor

Airport

Based T

rips

Total V

isitor

Trips

Total P

erson

Trips

Trip Purpose

Trip

s in

Tho

usan

d

Series1Series2Series3


5.2. Trip Distribution The RTC model distributes trips using a conventional gravity distribution algorithm. In this, zonal trip productions for each purpose are matched with trip attractions based on a computed probability function employing the travel time between zones. One of the key elements in this process are the estimation of travel times using the model network. Tables 15A through 15C below present the summaries of the average travel distance and average travel time by trip purpose and the total trips in the trip distribution model runs. Table 15D shows that from 2013 to 2030, with more trips and more congestions in the future, both the average travel distance and average travel time for most trip type increase. The average distance and average time for airport trips, including visitor airport and residence airport trips, increase due to the opening of Ivanpah Airport in 2017, resulting in an increasing share of aviation demand being met by the Ivanpah Airport.


Table 15A. 2013 Trip Distribution Summary Average Total Trips within the TAZ

Trip Purpose Distance Time Trips Trips PercentHome-Based Work Income Group 1 10.5 22.1 112,983 396 0.4%Home-Based Work Income Group 2 10.1 21.8 126,699 211 0.2%Home-Based Work Income Group 3 11.0 23.1 326,583 621 0.2%Home-Based Work Income Group 4 12.1 24.5 774,735 882 0.1%Home-Based School 4.5 11.8 624,633 34,010 5.4%Home-Based Shopping 5.1 13.1 747,698 19,770 2.6%Home-Based Other 7.3 17.1 3,152,269 34,856 1.1%Non-Home-Based 7.0 16.4 2,397,000 82,073 3.4%Hotel-Based Convention 3.8 13.4 56,493 973 1.7%Hotel-Based Business 6.7 17.9 17,174 80 0.5%Hotel-Based Gaming 4.2 14.0 175,199 2,747 1.6%Visitor Hotel-Based Other 4.4 14.2 184,476 2,786 1.5%Visitor Non-Hotel-Based Other 3.8 13.1 76,359 2,128 2.8%Non-Hotel Gaming 3.8 13.3 133,747 3,520 2.6%Visitor Airport 6.9 27.1 136,560 67 0.0%Resident Airport 13.3 32.8 18,066 0 0.0%Airport-Based Business 4.4 24.3 4,368 0 0.0%Airport-Based Other 6.9 27.1 1,083 1 0.0%Non-Airport-Based Business 6.3 16.2 1,661 28 1.7%Non-Airport-Based Other 4.2 13.8 873 20 2.3%Total Trips 9,068,659 185,167 Source: Regional Transportation Commission staff

Table 15B. 2020 Trip Distribution Summary Average Total Trips within the TAZ

Trip Purpose Distance Time Trips Trips PercentHome-Based Work Income Group 1 12.8 25.9 150,061 450 0.3%Home-Based Work Income Group 2 10.3 23.1 154,663 263 0.2%Home-Based Work Income Group 3 11.4 24.7 391,332 693 0.2%Home-Based Work Income Group 4 12.4 26.0 935,245 1,095 0.1%Home-Based School 4.8 12.6 738,044 31,102 4.2%Home-Based Shopping 5.0 13.4 880,765 19,045 2.2%Home-Based Other 7.3 17.7 3,696,292 45,380 1.2%Non-Home-Based 7.8 18.3 2,837,200 74,535 2.6%Hotel-Based Convention 3.7 13.7 65,893 1,202 1.8%Hotel-Based Business 6.9 19.1 20,028 79 0.4%Hotel-Based Gaming 4.0 14.4 206,167 3,853 1.9%Visitor Hotel-Based Other 4.2 14.6 216,688 3,853 1.8%Visitor Non-Hotel-Based Other 3.6 13.4 89,312 3,147 3.5%Non-Hotel Gaming 3.7 13.6 158,219 4,801 3.0%Visitor Airport 14.5 54.1 164,729 69 0.0%Resident Airport 21.7 61.3 21,577 0 0.0%Airport-Based Business 13.7 53.8 4,368 0 0.0%Airport-Based Other 14.7 54.3 1,083 0 0.0%Non-Airport-Based Business 6.2 16.5 1,661 33 2.0%Non-Airport-Based Other 4.0 14.0 873 24 2.7%Total Trips 10,734,198 189,624 Source: Regional Transportation Commission staff


Table 15C. 2030 Trip Distribution Summary Average Total Trips within the TAZ

Trip Purpose Distance Time Trips Trips PercentHome-Based Work Income Group 1 15.3 29.6 203,847 388 0.2%Home-Based Work Income Group 2 10.7 24.1 175,748 285 0.2%Home-Based Work Income Group 3 11.9 25.7 447,293 773 0.2%Home-Based Work Income Group 4 13.0 26.9 1,074,513 1,232 0.1%Home-Based School 4.7 12.3 860,949 32,937 3.8%Home-Based Shopping 5.2 13.5 1,019,160 20,924 2.1%Home-Based Other 7.7 18.2 4,246,291 51,434 1.2%Non-Home-Based 8.3 19.9 3,278,900 90,111 2.7%Hotel-Based Convention 3.6 13.7 69,863 1,324 1.9%Hotel-Based Business 7.1 19.5 21,227 70 0.3%Hotel-Based Gaming 4.0 14.4 220,346 4,000 1.8%Visitor Hotel-Based Other 4.2 14.7 231,161 4,000 1.7%Visitor Non-Hotel-Based Other 3.6 13.5 94,936 3,555 3.7%Non-Hotel Gaming 3.7 13.8 169,845 5,525 3.3%Visitor Airport 15.9 79.0 187,712 72 0.0%Resident Airport 23.1 86.8 23,747 0 0.0%Airport-Based Business 14.8 78.2 4,368 0 0.0%Airport-Based Other 15.9 79.0 1,083 0 0.0%Non-Airport-Based Business 6.4 16.7 1,661 32 1.9%Non-Airport-Based Other 4.0 14.2 873 26 3.0%Total Trips 12,333,524 216,687 Source: Regional Transportation Commission staff

Table 15D. Difference Trip Distribution Summaries Between 2013 and 2030 Average Total Trips within the TAZ

Trip Purpose Distance Time Trips Trips PercentHome-Based Work Income Group 1 4.8 7.4 90,864 -8 -0.2%Home-Based Work Income Group 2 0.7 2.3 49,049 74 0.0%Home-Based Work Income Group 3 0.9 2.6 120,710 152 0.0%Home-Based Work Income Group 4 0.9 2.5 299,778 350 0.0%Home-Based School 0.2 0.5 236,316 -1,073 -1.6%Home-Based Shopping 0.1 0.4 271,462 1,154 -0.6%Home-Based Other 0.4 1.0 1,094,022 16,578 0.1%Non-Home-Based 1.3 3.5 881,900 8,038 -0.7%Hotel-Based Convention -0.2 0.3 13,370 350 0.2%Hotel-Based Business 0.4 1.6 4,053 -10 -0.1%Hotel-Based Gaming -0.2 0.4 45,147 1,252 0.2%Visitor Hotel-Based Other -0.2 0.5 46,685 1,213 0.2%Visitor Non-Hotel-Based Other -0.2 0.4 18,577 1,428 1.0%Non-Hotel Gaming -0.1 0.5 36,098 2,004 0.6%Visitor Airport 9.0 51.9 51,152 5 0.0%Resident Airport 9.8 54.1 5,681 0 0.0%Airport-Based Business 10.4 53.8 0 0 0.0%Airport-Based Other 9.0 51.9 0 0 0.0%Non-Airport-Based Business 0.1 0.5 0 5 0.3%Non-Airport-Based Other -0.2 0.4 0 7 0.7%Total Trips 3,264,865 31,520 Source: Regional Transportation Commission staff

Regional Transportation Plan FY 2005-2030 Appendix 4

5.3. Mode Choice The RTC 2004 Model Pack 2 includes additional and optional transit processing and mode Choice modeling capabilities. The basic procedures include in the RTC 2004 Model Pack 2 are Transit network coding procedures; Transit path-building and skimming procedures; Mode choice procedures; Transit assignment procedures; and HOV modeling procedures. These added procedures greatly enhance the transit forecast and analysis capabilities of the RTC model. It is the first time that the RTC model is able to forecast the transit ridership and HOV volumes for the future horizon years. The model choice uses a nested logit model to estimate the zone-to-zone person trips that travel in autos and that use transit services. Table 16 shows a summary of total person trips by model as the results of the mode choice model. Table 16. DAILY - TOTAL PERSON TRIPS BY MODE (including visitor trips) Description 2013 2020 2030 % Change

2013-2030TOTAL DAILY PERSON - DRIVE-ALONE 3,979,728 4,705,216 5,418,704 36.2%TOTAL DAILY PERSON - SHARED RIDE 4,363,426 5,182,533 6,025,382 38.1%TOTAL DAILY PERSON - DRIVE - TRANSIT 2,698 9,003 15,120 460.4%TOTAL DAILY PERSON - LOCAL - TRANSIT 180,833 196,565 198,073 9.5%TOTAL DAILY PERSON - PREMIUM - TRANSIT 38,641 62,139 64,081 65.8%TOTAL DAILY PERSON - TAXI 183,640 199,141 206,364 12.4%TOTAL DAILY PERSON - TOUR_SHUTTLEBUS 45,070 45,923 47,021 4.3%TOTAL DAILY PERSON - OTHER - WALK 274,623 333,680 358,779 30.6%DAILY_TOTAL PERSON - VEHCILE 6,235,281 7,355,511 8,464,294 35.7%DAILY_TOTAL PERSON - TRANSIT 222,172 267,706 277,274 24.8%Source: Regional Transportation Commission staff

A. Auto Trips The person trips traveling in autos are then turned into an estimate of auto trips through the application of vehicle occupancy rates derived from an earlier household survey. The rates set out in Table 17 are held constant for all forecast horizon years. Note that the term “auto” in this context includes light trucks and vans used for personal travel as well as passenger cars. Table 17. Vehicle Occupancy Rates

Travel Purpose Average Vehicle Occupancy

(Persons per Vehicle) Home-Based Work 1.06 Home-Based School 1.23 Home-Based Shopping 1.43 Other Home-Based 1.70 Non-Home-Based 1.53 Overall Average 1.39

Source: Regional Transportation Commission, Travel Demand Model, 2004 Pack 2A.


The Vehicle Occupancy Rates are used to convert person travel trips made entirely inside the region into vehicle trips. Vehicle trips not included are ones into and out of the region and through trips that cross the region. Projections of total vehicle travel include these and commercial trips made by trucks, buses. The model network includes ten cordon stations on roads crossing the regional boundary which are connected to the rest of the network by external connector links. Projections of external trips and the distribution of the local end of those trips have been developed jointly with NDOT through the inter-agency consultative process. Commercial vehicle trips, including light delivery and service trips as well as truck trips, are separately forecasted and distributed. These projections are added to the number of auto trips to give total vehicle trips summarized in Table 13. Figure 4.5 shows the percentage changes in trips by vehicle type from 2013 to 2030. The higher percentage changes in external trips reflect all fast growths surrounding the modeling area, including areas outside Clark County, and adjacent states.

Table 18. Vehicle Trips in the Las Vegas Valley, 2013-2030

Average Weekday Vehicle Trips % Changes 2013 2020 2030 2013- 2030

Drive Alone 4,334,553 5,126,732 5,908,730 36.3%Shared Drive 1,900,728 2,228,779 2,555,564 34.5%

Auto Trips 6,235,281 7,355,511 8,464,294 35.7%External Trips 133,689 159,334 195,685 46.4%Truck Trips 221,136 262,182 294,340 33.1%Taxi Trips 177,153 187,399 191,742 8.2%

Total Vehicle Trips 6,767,259 7,964,427 9,146,062 35.2%

Trip Purpose

Source: Regional Transportation Commission, Travel Demand Model, 2004 Pack 2A. Figure 6. Percent Changes in Vehicle Trips by Type from 2013 to 2030

Percent Changes in Vehicle Trips from 2013 to 2030

0%5%

10%15%20%25%30%35%40%45%50%

DriveAlone

SharedDrive

AutoTrips

ExternalTrips

TruckTrips

Taxi Trips TotalVehicleTrips

Vehicle Trip Type

Perc

ent I

ncre

ase

% Changes 2013- 2030



5.4. Assignments A. Time-of-Day Auto Trip Analysis Before the estimates of average daily vehicle trips for each trip purpose are assigned to the road links of the networks, these vehicle trips are grouped into seven time periods. These periods were defined through the inter-agency consultative process and are based on the observed distribution of traffic flow as shown by continuous traffic counts. The periods are:

• From midnight to 7 a.m. (7 hours), • From 7 to 9 a.m. (2 hours), • From 9 a.m. to 2 p.m. (5 hours), • From 2 to 4 p.m. (2 hours), • From 4 to 6 p.m. (2 hours), • From 6 to 8 p.m. (2 hours) and • From 8 p.m. to midnight (4 hours).

The vehicle trips for each travel purpose are grouped according to the proportion of daily trips that start or return in each time period. Then an equilibrium highway assignment process is used to load the time of day zone-to-zone vehicle trips onto the road network. The trips are assigned to road links based on computed travel times that take into account the relationships among traffic flow, free-flow speed, roadway capacity and congested (or “loaded”) speed and travel time. The formula used is a modification of the Bureau of Public Roads (BPR) formula for computing the decrease in speed as roads approach congested volumes. The coefficients in the formula have been developed from the Highway Capacity Manual and modified through the model calibration process to reflect local conditions. The assignment is performed for each of the seven time periods. Results are then aggregated to produce daily traffic flows on each link in the network. The following tables present summaries of the unadjusted modeled forecasts for the Valley. It should be noted that the road types changes for some links in the future over years due to the projects to be built. The vehicle miles traveled (VMT) are calculated by the trips assigned to the model network links and the link lengths of the network.


Table 19A. 2013 Trip Assignment Summary Road Type Daily VMT Daily Flow Average Daily Speed

External Links 267,023 151,688 25.0System to System Ramps 429,929 2,051,297 43.2Minor Roads 5,789,031 31,420,075 31.9Major Roads 16,091,321 92,805,264 32.7Ramps 1,289,615 7,785,191 26.5Interstates 11,103,747 28,240,866 48.1Freeways 5,072,947 18,441,884 50.7Expressways 442 3,482 50.0Collectors 3,279,469 15,261,459 30.4Centroid Connectors 3,536,622 12,022,323 25.0Local Roads 52,935 343,230 28.4High Occupancy Vehicle (HOV) 270,241 1,342,648 51.4Total 46,913,082 208,526,762 Source: Regional Transportation Commission

Table 19B. 2020Trip Assignment Summary

Road Type Daily VMT Daily Flow Average Daily SpeedExternal Links 316,079 180,649 25.0System to System Ramps 490,081 2,298,662 41.9Minor Roads 7,941,243 41,314,145 31.4Major Roads 18,789,717 106,121,042 31.6Ramps 1,543,606 9,492,261 26.7Interstates 14,566,624 38,071,585 45.5Freeways 6,857,699 23,022,393 49.7Expressways 1,062 8,979 49.7Collectors 3,735,466 17,050,606 29.8Centroid Connectors 4,355,423 14,232,600 25.0Local Roads 60,318 382,196 27.7High Occupancy Vehicle (HOV) 358,128 1,723,573 49.8Total 58,657,318 252,175,117 Source: Regional Transportation Commission Table 19C. 2030 Trip Assignment Summary

Road Type Daily VMT Daily Flow Average Daily SpeedExternal Links 392,087 221,999 25.0System to System Ramps 665,298 4,069,275 40.6Minor Roads 9,415,217 47,709,671 31.8Major Roads 20,600,457 114,260,574 31.3Ramps 1,726,555 10,842,809 26.8Interstates 18,047,187 48,133,295 45.8Freeways 8,128,180 26,901,345 49.0Expressways 863,808 230,357 21.6Collectors 4,465,254 18,847,960 30.0Centroid Connectors 4,844,743 16,367,002 25.0Local Roads 89,631 455,483 27.0High Occupancy Vehicle (HOV) 1,667,233 4,620,960 44.5Total 69,238,417 288,039,769 Source: Regional Transportation Commission


Table 19D. Changes in Trips Assignments from 2013 to 2030

Road Type% Changes

in Daily VMT% Changes

in Daily FlowChanges in Average

Daily SpeedExternal Links 46.8% 46.4% 0.0System to System Ramps 54.7% 98.4% -2.6Minor Roads 62.6% 51.8% -0.1Major Roads 28.0% 23.1% -1.4Ramps 33.9% 39.3% 0.3Interstates 62.5% 70.4% -2.4Freeways 60.2% 45.9% -1.7Expressways 195428.8% 6515.3% -28.4Collectors 36.2% 23.5% -0.4Centroid Connectors 37.0% 36.1% 0.0Local Roads 69.3% 32.7% -1.4High Occupancy Vehicle (HOV) 516.9% 244.2% -6.9Total 47.6% 38.1% Source: Regional Transportation Commission One element of travel not included in the network assignment. These are intra-zonal trips. The intra-zonal trips are computed by applying an intra-zonal trip length to the intra-zonal trips tabulated in the trip table but not assigned to the network. Since TRANSCAD does not have a procedure for calculating this length, a default length of one mile has been used, based on the fact that nearly all zones in the model are no more than one square mile in area.

B. Transit Assignment Results

The other element is transit vehicle trips that is included in the network modeling for this RTP and is summarized in Table 20. In the table, total modeled daily transit trips, total daily boarding, total Transit Person Miles Traveled (PMT) and Transit Person Hours Traveled (PHT) are summarized. Transit trips increase by over 20% in the year of 2020 from the year of 2013, this changes are mainly caused by the proposed increase and the improvement in transit services for year 2020. The transit service supplies for year 2030 basically remain the same for the year of 2020, and the slight 4% increase in the transit trips will be due to the net increase from the regional growth. Table 20. Modeled Daily Transit Trips, Person Miles Traveled and Person Time Traveled.

Year % Increase from Descriptions 2013 2020 2030 2013-2030Total Transit Trips 222,172 267,706 277,274 24.8%Person Miles Traveled (PMT) 1,199,032 1,554,870 1,680,600 40.2%Person Hours Traveled (PHT) 139,271 167,737 175,920 26.3%Total Daily Boarding 359,748 435,413 449,588 25.0%% change in Transit Trips 20% 4%% change in PMT 30% 8%% change in PHT 20% 5%% change in Daily Boarding 21% 3% Source: Regional Transportation Commission


Figure 7A. Modeled 2013 Horizon Year Auto Time From All TAZs to TAZ 528 (County Building is located in TAZ 528)

Figure 7B. Modeled 2030 Horizon Year Auto Time From All TAZs to TAZ 528 (County Building is located in TAZ 528)


Figure 8A. Modeled 2013 Horizon Year Auto Time From All TAZs to TAZ 687 (Las Vegas @ Flammingo)

Figure 8B. Modeled 2030 Horizon Year Auto Time From All TAZs to TAZ 687 (Las Vegas @ Flammingo)


Figure 9. 2008 (Top) and 2030 (Bottom) Modeled Daily Volumes


Figure 10. 2008 (Top) and 2030 (Bottom) Modeled PM PK Congestions (V/C Ratio)


5.5. Model Travel Forecast Corrections A series of corrections and adjustments are made to the modeled VMT before they are used as a basis for estimating mobile source emissions. The first set of adjustments involves comparing modeled volumes with traffic counts and correcting errors in assigned traffic volumes. NDOT and the local entities have an extensive program of traffic counts and over 1,000 count locations are coded into the Master Highway network. These counts are aggregated by roadway group. When this RTP analysis was performed, the updated NDOT traffic counts available were NDOT 2007 traffic counts. In order to compare apples to apples, the model was run with 2007 roadway network and the 2007 model input file, then assigned traffic volumes were compared with the NDOT 2007 traffic counts. The aggregate modeled volume at count locations in each facility type is compared with the corresponding counts to produce an overall percentage error for count locations in that facility type. This error is expressed as a correction factor that is then applied to the VMT for all links in that group. Table 21 lists these comparisons and correction factors. Table 21. Correction to 2007 Year Ground Counts

Facility Type

Number of

Count Stations

Aggregate Model Flow

Aggregate Count Flow

Conversion Factor

External Links 6 71,122 70,345 0.98908 System Ramps 30 458,561 470,005 1.02496 Minor Arterials 261 3,799,773 4,127,135 1.08615 Major Arterials 425 14,441,395 13,190,104 0.91335 Ramps 251 2,153,535 2,125,360 0.98692 Interstates 122 8,899,227 8,090,475 0.90912 Freeways 39 2,426,553 2,033,770 1.05241 Expressways/Beltways 3 48,761 76,203 1.56279 Collectors 247 1,438,071 1,589,457 1.10527

Source: Regional Transportation Commission. Note that in Table 21, the direct initial correction factor for Freeways was 0.83813, which was recalculated to 1.05241. Because some existing Expressways/Beltways are re-classified as Freeways in the future horizon years (see Figure 11 that shows a roadway functional class for different horizon years), the initial and directly calculated conversion factor needs to be adjusted, such as follows: Freeway factor = (freeway counts + expressway counts)/(model freeway flows + model expressway flows)+ 0.2. See the map showing the functional class of the highways. This step results in link volumes and VMT that are corrected to observed volumes.


Figure 11. Current and Future Roadway Functional Class

In accordance with Federal guidance, this corrected model VMT is then benchmarked against the base year VMT from the Highway Performance Monitoring System (HPMS). At the time when this document is prepared, the most resent HPMS data is the total VMT by county in 2006 Annual Traffic Report published by Nevada Department of Transportation. The system-wide correction factor used to control the corrected model VMT to the HPMS total is calculated in the following steps. First, the NDOT HPMS (2006 Annual VMT (AVMT)) for the Clark County Urbanized Area is converted into Annual Average Weekday VMT (AAWDVMT); Second, the 2006 AAWDVMT was factored up to 2007 AAWDVMT by an average growth rate in the HPMS from years of 2004 to 2006. The third step is to match the RTC modeling area to the NDOT defined Urbanized Area. See Figure 12 for the NDOT defined Urbanized Area. The RTC modeling area is basically the same as the 2004 NDOT defined Urbanized Area, except for the newly expanded modeling areas for Boulder City, Ivanpah Airport, and Apex Industrial areas. See Figure 13. The VMT on these roads was subtracted from the total modeled WDVMT. Then, for the same specified Urbanized Area, the 2007 AAWDVMT was compared with the corrected model WDVMT to develop an adjustment factor. This factor is applied to the entire system in the model to derive corrected and benchmarked base year VMT.


Figure 12. NDOT Defined Urbanized Area


Figure 13. The Links (in Red) for which the VMT Was Subtracted From the Total Modeled VMT.

The process is summarized as follows.

• Year 2006 HPMS Annual VMT for the Urbanized Area: 12,701,427,381 • Year 2006 HPMS Annual Average Weekday VMT for the Urbanized Area:

34,798,431 • Year 2007 HPMS Annual Average Weekday VMT for the Urbanized Area:

37,024,418. • Year 2007 Model AAWDVMT for the Las Vegas Valley: 36,969,095 • Year 2007 Model AAWDVMT link corrected to: 35,960,657 • After Subtracted Model AAWDVMT outside Urban Area: 33,675,538. • Year 2007 HPMS correction factor: 1.099

The correction and HPMS factor are applied to all future horizon years, so that the emissions for each year are calculated using the modeled growth in VMT based upon a corrected and HPMS adjusted 2007 base.


5.6. Travel Forecast Seasonal Adjustments The corrected and HPMS adjusted AAWDVMT is then adjusted to reflect the winter and summer conditions that are characteristic of peak CO emissions and O3 emissions respectively. This involves two factors. The first is a seasonal adjustment from AAWDVMT to December average weekday VMT. 2004 NDOT continuous traffic counts are employed to calculate this factor (0.969). The summer seasonal adjustment factors are calculated using the average of June, July and August ADT. Table 22 shows the factors. There are no significant differences in seasonal traffic patterns across the various roadway functional classes, so the same factor is applied equally to all modeled VMT. The 2004 seasonal adjustment factor is also held constant for all future horizon years.

Table 22. Seasonal Adjustment Factors Summer adjustment factor 1.021711371 Winter adjustment factor 0.969123638

Source: NDOT, Hourly Counts, 2004 RTP 2006-2030

5.7. Vehicle Miles Traveled Outside Modeling Area But Inside Ozone Non-attainment Area

A. Introduction The 8-hour Ozone Non-attainment Area is larger than Las Vegas Regional Travel Demand modeling domain. This section describes how the VMT is developed for the traffic outside the modeling boundary but within the Ozone Non-attainment Area. Two elements are involved in this development, one is the traffic on the corridors such as State Route or Interstate outside the modeling network but within the Ozone Non-attainment Area; the other element is traffics generated in small communities outside the modeling area but within the Ozone Non-attainment Area. The following will describe each of these separately.

B. The VMT on the roadway corridors The VMT outside the modeling area are calculated using available NDOT traffic counts. First, the corridors inside the Ozone Non-attainment boundary but outside of the RTC TDF model boundary are identified. Table 23A presents a list of roadway corridors identified. This table includes corridor endpoints, length, total lanes, and posted speed. Note that due to the TAZ expansion in this RTP, the number of corridors or the lengths of some of the corridors have been updated (reduced) from the RTP 2006-2030. In Table 23A, the average speeds are listed, where the average speeds equals the posted speed if it is constant for the corridor, where the posted speed varies for a corridor, the speed monitoring data is not available, the average travel speeds have been estimated by the information from the NDOT’s Annual Speed Monitoring Report. This dataset assumes that the average travel speed will not change on a segment during the 2013 to 2030 period.


Table 23A. List of Roadway Corridors Outside Modeling Network

Corridor Endpoints Length

(mi)

Lanes (both dir.)

Posted Speed

Average Speed

I-15 North TDF Model Boundary and Moapa/Glendale 24 4 75 75

US 95 South CA Stateline and US 93 Interchange 60 2 to 4 70 70 US 93 North I-15 Interchange and Ozone Boundary 11 2 70 70 US 93 South AZ Stateline and Boulder Beach 5 2 Varies 50

US 93/95 US 95/93 Interchange and TDF Model Boundary 2.5 4 65 65

SR 160 TDF Model Boundary and Ozone Boundary 12 2 70 70

SR 159 SR 160 and TDF Model Boundary 14 2 Varies 55

SR 157 US 95 and end of road at Mt. Charleston 19 2 Varies 55

SR 158 SR 157 and SR 156 7 2 Varies 45

SR 156 US 95 and end of road at Mt. Charleston 18 2 Varies 55

SR 163 US 95 and AZ Stateline 26 2 to 4 Varies 55 Casino Drive Needles Highway and SR 163 13 2 to 4 Varies 35 Bruce Woodbury Drive Needles Highway and Casino Drive 8 2 Varies 40 Davis Dam Road SR 163 and Davis Dam 7 2 Varies 45 Needles Highway CA Stateline and SR 163 13 2 to 4 Varies 60

SR 147 TDF Model Boundary and Ozone Boundary 2 2 65 65

SR 168 Ozone Boundary near Glendale 6 2 Varies 45 Valley of Fire Road I-15 Interchange and Ozone Boundary 15 2 65 65 SR 161 I-15 Interchange and Ozone Boundary 12 2 70 70 SR 164 I-15 Interchange and Searchlight 20 2 70 70

Source: Regional Transportation Commission staff Next, the future traffic volumes are projected for these corridors. Forecast for future AADTs are based on the data from two sources. The NDOT has projected the traffic volumes for the RTC modeling network external connectors (see Appendix B at the end of this document), Therefore the NDOT’s projections are used where the data is available. In Table 16B, the NDOT’s estimates are highlighted with yellow color. The traffic volume projects for the remaining corridors are developed by applying average annual growth from the historical NDOT’s traffic counts AADT at stations on these corridors. Table 23B also provides the estimated VMT that is calculated by multiplying the volume estimates and the corridor length.


Table 23B. Traffic Volume and VMT Estimates for the Outside Corridors

Corridor 2013

Volume 2020

Volume 2030

Volume2013 VMT

2020 VMT

2030 VMT

I-15 North 28,160 34,000 42,000 675,840 816,000 1,008,000 US 95 South 14,800 19,000 24,000 888,000 1,140,000 1,440,000 US 93 North 1,710 1,850 2,200 18,810 20,350 24,200 US 93 South 19,200 22,000 25,000 96,000 110,000 125,000 US 93/95 19,200 22,000 25,000 48,000 55,000 62,500

SR 160 13,800 17,000 21,000 165,600 204,000 252,000 SR 159 7,360 9,800 13,000 103,040 137,200 182,000 SR 157 3,920 4,700 6,500 74,480 89,300 123,500 SR 158 750 802 1,125 5,250 5,614 7,875 SR 156 680 762 915 12,240 13,716 16,470 SR 163 8,000 8,000 10,600 208,000 208,000 275,600 Casino Drive 8,000 9,860 11,700 104,000 128,180 152,100 Bruce Woodbury Drive 11,000 11,900 13,500 88,000 95,200 108,000 Davis Dam Road 400 400 400 2,800 2,800 2,800 Needles Highway 13,000 15,800 17,015 169,000 205,400 221,195 SR 147 3,920 4,700 6,500 7,840 9,400 13,000 SR 168 1,400 1,600 1,820 8,400 9,600 10,920 Valley of Fire Road 760 870 1,060 11,400 13,050 15,900 SR 161 3,200 3,640 4,470 38,400 43,680 53,640 SR 164 1,100 1,300 1,560 22,000 26,000 31,200

Source: Regional Transportation Commission C. The VMT on Minor Arterials, Collectors and Locals In addition to the VMT and speed estimates for the roadways listed in the above two tables, estimates of VMT and speed were made for travel on minor arterials, collectors and local streets in the cities of Laughlin, Searchlight, Blue Diamond, Cal-Nev-Ari, and Goodsprings. Estimates were based on VMT per person. Using the same approach from the 2004 Urban Mobility Report (http://mobility.tamu.edu/ums) to assist in the development of VMT per person for the cities listed above. It was assumed that all travel on interstates, freeways, expressways, and major arterials was captured in the itemized estimates summarized in Table 16B. Therefore, the estimates summarized following only cover travel on roadways classified as minor arterials, collectors, and locals. Table 24A and 24B summarize the population forecasts and the VMT per capita estimates. According to Flexibility in Highway Design, Chapter 3, Functional Classification (http://fhwa.dot.gov/environment/flex/ch03.htm), travel on minor arterials, collectors, and


local roads account for 46.7 percent of average daily travel on US roadways. These VMTs were then disaggregated to minor arterials, collectors, and locals using factors listed in Table 24C which were derived from Flexibility in Highway Design and the RTC TDF Model. The data in Table 24C was then used to develop the VMT by average speed values in Table 24D. Table 24A: Population Forecasts

City 2006 2010 2015 2020 2025 2030 Laughlin 8629 15084 25807 34295 50276 54773 Searchlight 780 1459 1707 1987 1987 1987 Blue Diamond 439 524 2129 3802 4070 5918 Cal-Nev-Ari 248 316 316 350 350 350 Goodsprings 257 257 296 476 476 476

Source: Clark County Department of Comprehensive Planning and Regional Transportation Commission. (Year 2006 data came from CCDCP.) Table 24B: Estimate of VMT Per Capita

VMT City Per capita 2013 2020 2030

Laughlin 5 100,234 160,660 252,750Searchlight 2 2,740 3,288 3,324 Blue Diamond 2 1,249 1,380 1,390 Cal-Nev-Ari 2 597 648 650 Goodsprings 2 561 956 966

VMP Per Capita Index Source: Texas Transportation Institute, Urban Mobility Study

Table 24C: Summary of Percent VMT and Average Speed for Minor Arterials, Collectors, and Local Roadways

Roadway Type Percent VMT Speed (mph)

Minor Arterial 39 35 Collector 33 30

Local 28 36


Table 24D: Summary of Forecast VMT by Average Speed on Minor Arterials, Collectors, and Local Roadways

VMT Place/Roadway Type 2013 2020 2030

Laughlin Minor Arterials (35 mph) 39,091 62,657 98,573Collectors (30 mph) 33,077 53,018 83,408Locals (25 mph) 28,066 44,985 70,770Searchlight Minor Arterials (35 mph) 1,068 1,282 1,296Collectors (30 mph) 904 1,085 1,097Locals (25 mph) 767 921 931Blue Diamond Minor Arterials (35 mph) 487 538 542Collectors (30 mph) 412 455 459Locals (25 mph) 350 386 389Cal-Nev-Ari Minor Arterials (35 mph) 233 253 254Collectors (30 mph) 197 214 215Locals (25 mph) 167 181 182Goodsprings Minor Arterials (35 mph) 219 373 377Collectors (30 mph) 185 315 319Locals (25 mph) 157 268 270Total Minor Arterials (35 mph) 41,098 65,103 101,041Collectors (30 mph) 34,776 55,088 85,496Locals (25 mph) 29,507 46,741 72,542

Source: Regional Transportation Commission

6. Carbon Monoxide Mobile Source Emissions Forecasts

6.1. Introduction Mobile source emissions for CO are calculated by using emission factors developed through the Mobile6.2 emissions model. These emission factors are the average emissions per vehicle-mile for a particular speed of travel, as determined by the EPA. The settings used in the Mobile6.2 model were developed in cooperation with the Clark County Department of Air Quality Management, and are similar to those used in the development of the CO SIP. The Mobile6.2 model takes into consideration the effects of the different emissions from various vehicle types, such as passenger vehicle, light truck, heavy truck and motorcycle, as well as the effect of the mix of gasoline-powered and diesel-powered vehicles.


Specific input settings define the following factors for each forecast horizon year: • Fleet mix composition, • Mileage accumulation rates by vehicle type and age, • Vehicle registration rates by vehicle type and age, • Impact of inspection/maintenance programs, • Impact of anti-tampering programs, • Impact of refueling controls, • Reid vapor pressure of fuel, • Daily minimum, maximum and ambient temperatures, • Oxygen content of fuel and • Vehicle speed.

The basic calculation steps are: The link-specific emissions calculation is performed based on the procedure outlined in the 2005 CO SIP; Adjust the daily volumes to hourly volumes; Adjust the link speeds using the hourly volume to capacity ratio in the BPR curve; Calculate the hourly link VMT as the hourly volume times the link length; Calculate the link emissions as the link VMT times the MOBILE6.2 composite emission factor for the link roadway type, hour, and adjusted link speed; Adjust the emissions to average December day, by HPMS factor, count-to-model volume factor, growth factor and transit factor. The emissions for each facility type are then summed to give the modeled mobile source emissions for each year, as shown in Table 25.

Table 25: 2010-2030 CO Emissions Summary Total CO Emissions (tons/day) Facility Type 2007 2010 2013 2015 2020 2030 External 2.15 2.08 2.01 2.01 2.01 2.35 System-to-system Ramp 4.77 4.64 4.51 4.45 4.41 5.56 Minor Arterial 45.03 47.25 49.47 52.78 57.75 65.02 Major Arterial 122.77 118.89 115.00 114.15 113.59 118.28 Ramp 14.34 13.68 13.02 13.17 13.40 13.89 Interstate 92.26 88.96 85.65 89.77 95.96 114.16 Freeway 37.72 41.35 44.99 47.85 52.14 59.51 Expressway 5.62 2.81 0.01 0.01 0.01 9.76 Collector 27.90 27.93 27.96 27.33 26.91 30.95 Centroid 29.20 29.43 29.67 30.44 31.59 33.72 Local 0.53 0.49 0.44 0.44 0.44 0.63 HOV 0.00 0.95 1.90 2.00 2.16 9.30

TOTAL 382 378 375 384 400 463 Budgets 623 690 690 768 817 817

Source: The budgets were from Clark County Carbon Monoxide Modeling and SIP, October, 2005, DAQEM, Emission Calculations are from the Regional Transportation Commission staff. The horizon analysis years for this RTP are 2013, 2020 and 2030. However, to meet the Transportation Conformity Rule, in addition to including the attainment year and the last year of the transportation plan, the analysis must include any years which the SIP


establishes MVEB that are within the timeframe of the transportation plan. For CO, that means that the analysis years 2010 and 2015 must be included. Note that the emissions analysis, for comparison to the years when MVEBs are established, may be determined by interpolating between the years for which the full regional emissions analysis is performed. Therefore, if regional emissions were established by a full network run for 2013 and 2020, emissions for 2015 could be interpolated for comparison to the MVEB. In Table 25, the emissions for year 2010 were interpolated from the emissions between years 2007 and 2013, and the emissions for year 2015 were interpolated from the emissions between years 2013 and 2020. Modeled mobile source CO emissions can be reduced through the application of credits for the various Transportation Control Measures as defined in the State Implementation Plan. The first of these measures - technician training - is related to the Vehicle Inspection and Maintenance Program, and the effect of this program is included in the emissions modeling process through the application of the relevant Mobile 6.2 input settings. The other TCM’s have the effect of reducing emissions below the level predicted through the modeling process. Based on the information supplied by the DAQEM, reduction factors are included in the CO input setup file for the Mobile 6.2 modeling of the travel output from the RTC’ travel demand model. Table 26.shows that the net CO Emissions are the same as the Total emissions listed in Table 25. As the future CO Emissions are below the budgets with big margins, this analysis will not extend to extensive and detailed discussions about the control measures. Table 26. Net CO Emissions

Emissions in Tons Per Day 2007 2010 2013* 2015 2020 2030

Modeled CO Emissions 382 378 375 384 400 463 TCM’s Credited in Model n/a n/a n/a n/a n/a n/a Net CO Emissions 382 378 375 384 400 463


7. PM10 Modeling Assumptions

7.1. Transportation Activities Contribution to PM10 Emissions According to the 2001 PM10 SIP, over 37 percent of the Las Vegas Valley’s dust emissions are related to transportation activities; 26 percent of the PM10 emissions are linked to travel on paved roads and 9 percent can be attributed to travel on unpaved roads. While the inventory process has correctly characterized the problem, it is beneficial to review the primary sources of PM10 to understand how control regulations for construction will reduce future emissions and help to demonstrate positive air quality conformity. The paved roadway network itself is not directly responsible for emissions. Rather, fugitive dust originating from construction activities and disturbed vacant land are the primary contributors. Wind and construction “track out” deposit dust on roads and the


movement of vehicles traveling over the pavement re-entrains the dust into the air, which contributes to the regional PM10 emission problem. Paved road emissions also include a category of streets where the paved surface does not exceed 28 feet in width and are classified as streets with “unpaved shoulders”. The idea is that, due to the narrow paved width, vehicles often travel onto the shoulders and track dust back onto the paved surface, contributing to the regional PM10 emissions. On the other hand, when vehicles travel over unpaved roads they directly disturb the surface and create PM10 emissions, which also contribute to the regional PM10 problem at a rate of about 9 percent of the total. By the end of June 2003, Clark County and other local governments had paved all unpaved roads in the PM10 nonattainment area with an ADT of 150 or more. By March 2004, the local governments had paved all unpaved roads with an ADT of 100 or more. This fully implements the road paving contingency measure set forth in Section 4.6.3 of the PM10 SIP. These actions were documented in the Clark County PM10 State Implementation Plan Milestone Achievement Report dated June 2007 and submitted to EPA Region 9 by the Nevada Division of Environmental Protection on October 3, 2007. In addition to PM10 emissions linked to travel on paved and unpaved roads, there are several other PM10 emission sources that must be accounted for within the transportation conformity process. These include:

• Vehicular exhaust, • Vehicular brake wear, • Vehicular tire wear and • Road construction.2

Table 27. Roadway Silt Loading Factors

Paved Roads Roadway Category 2006 Ext. Connector 0.470 Freeway Ramps 0.620 Minor Arterial 0.470 Major Arterial 0.490 Ramps 0.620 Interstate 0.020 Freeway 0.020 Expressway 0.020 Collector 0.620 Local 1.720 Inter-Zonal Trips 1.720 Public Transit 0.014

2 Note that road construction is treated the same way that general construction is treated - all applicable dust control regulations are applied to the site during construction activity to ensure emission reductions.


7.2. PM10 Emission Budgets for the Annual and the 24 Hour NAAQS and PM10 Emissions For Paved Roads

The SIP budgets provide a stepped approach to achieving the NAAQS for PM10, with a 2006 budget for the 24-hour standard. The reduction in the mobile source emission budget between the years 2003 and 2006 reflects the effectiveness of the control strategies for both construction activities and the stabilization of disturbed lands as defined within the 2001 PM10 SIP; see pages 5.33 - 5.36 of the 2001 PM10 SIP. Table 27. identifies the PM10 roadway silt loading rates developed from the most recent silt sampling data.

7.2.1. VMT and Silt Loading The silt loading factors in Table 27 are based on silt sampling that occurred in 2003, 2004 and 2005 as part of Clark County’s 2001 SIP commitments. A number of silt sampling sites were kept constant during the 2000 through 2005 sampling periods. As a result, several of the sampling sites were impacted by construction activity track-out during the 2003 through 2005 sampling period. This data reflects current actual silt loadings on Las Vegas Valley roadways, including roads impacted by construction activity track-out. As shown in Table 27, there is a big difference between the dust emissions from the various roadway facility types, from 0.1 grams per vehicle-mile on Interstates to over 1 gram per vehicle-mile on local roads. However, there is no differentiation between the factors that apply in different parts of the valley.

7.2.2. Unimproved Shoulder Calculation: SIP Control Implementation Schedule

Calculations for roadways with unimproved shoulders come directly from data developed by Clark County in support of the PM10 SIP. Based on the programming of CMAQ funds to reduce/eliminate roadways with less than 28' of paving, the SIP roadway remediation schedule is as follows:

• 50 percent in 2004 • 25 percent in 2005 • 25 percent in 2006

It is assumed there will be no significant area of unpaved shoulders remaining after 2006.

7.3. PM10 Roadway Emissions Calculation Table 28 shows the calculation of PM10 emissions from paved roadways based on these current silt loading factors and average vehicle fleet weight. Clark County DAQEM conducted an assessment of average fleet vehicle weight using Nevada Department of Motor Vehicles data through 2005. Based on this assessment, it was determined that the 2006 average vehicle fleet weight for Clark County was 2.29 tons. The results were published in a report titled Average Vehicle Fleet Weight in Clark County, Nevada, dated January, 2006. The findings were presented to the Clark County Technical Advisory Committee for comment and reviewed by EPA Region 9 staff.


7.4. PM10 Emissions from Vehicles The SIP emission rates for on-road mobile sources, including actual vehicle emission calculations for Vehicular Sulfate Particulate Matter, Tire Wear, Brake Wear and Exhaust Particles are set out in Table 29.

For this conformity analysis, the DAQEM advises that, in view of the minimal difference between the rates for the various facility types, it is acceptable to use a single rate for all VMT in each horizon year analysis. The rate for 2006 is 0.072 grams per vehicle-mile. The rate for 2006 is used for all subsequent years, as shown in Table 30.

7.5. Roadway Construction PM10 Emissions A series of PM10 inventories were conducted during the 1999-2000 period in support of the SIP development. The following identifies the assumptions for the purpose of estimating PM10 from highway construction.

7.6. Roadway Construction PM10 Emissions A series of PM10 inventories were conducted during the 1999-2000 period in support of the SIP development. The following identifies the assumptions for the purpose of estimating PM10 from highway construction. CONSTRUCTION: Highway Construction PM10 Emission Rates

• Calculate total number of months for analysis period • Convert the Lane Miles of Project to Acres

5280 x 12 (average lane width) = 63,360 square feet in a lane mile 63,360/43,560 (number of square feet in an acre) = 1.45 acres per lane mile Factor: 1.45 x total project lane mile = number of acres under construction

• Apply SIP emission factor = .42 tons/month = 840 pounds/acre/month • Apply Best Management Practice reduction factor to total acres under

construction = Product - (product x .68) • Convert to Average Day Emissions: divide by 30.5 (annual average days in

month) and divided by total number of month for analysis period WIND EROSION: Highway Construction Emission Calculations for PM10

• Define Project Acres Obtain acre calculation for analysis period from Step 1 of Highway Construction.

• Apply PM10 Wind Erosion Rates Per Day to Acre Calculation 35% of Acres x 7.60 x 10-4 tons 65% of acres x 1.98 x 10-2 tons

• Define Total Daily Wind Erosion Add products from Step 2

• Apply Sections 90 through 94 Regulations Reduce by 71%

These rates are applied to the estimated acreage covered by highway construction projects, and the results are set out in Table 30. For the years 2003 through 2005, acreages have been calculated based on projects identified in the TIP. The average of these three years is used as a basis for 2006 and subsequent years


Table 28. PM10 Roadway Analysis for Horizon Years 2006 2013 2020 2030

Facility Type

Adjusted 2013 AAWDVMT



PM10 Emission Factors (g/v-m)

Paved Road Emissions (kg/day)



External connectors 290,372 343,717 426,371 1.85 537 636 789System Ramps 484,480 552,264 749,713 2.215 1,073 1,223 1,661Minor Arterials 6,913,064 9,483,163 11,243,333 1.85 12,789 17,544 20,800Major Arterials 16,158,628 18,868,310 20,686,624 1.901 30,718 35,869 39,325Ramps 1,399,312 1,674,907 1,873,418 2.215 3,099 3,710 4,150Interstates 11,098,518 14,559,764 18,038,688 0.238 2,641 3,465 4,293Freeways 5,869,720 7,934,791 9,404,817 0.238 1,397 1,888 2,238Beltway 759 1,824 1,484,200 0.238 0 0 353Collectors 3,985,159 4,539,278 5,426,105 2.215 8,827 10,055 12,019Centroid connectors 3,888,323 4,788,550 5,326,531 1.901 7,392 9,103 10,126Other Local Roads 58,200 66,316 98,544 4.299 250 285 424HOV Lanes 297,116 393,743 1,833,031 0.238 71 94 436Public Transit Bus 56,686 68,023 68,023 4.299 244 292 292Intra-zonal 185,167 189,624 216,687 4.299 796 815 932DAILY TOTALS 50,685,502 63,464,276 76,876,086 69,835 84,980 97,838

Convert to US tons per day 0.001102 0.001102 0.001102PM10 Emissions (Tons per day) 77.0 93.6 107.8

2006 Mobile Source PM10 Emissions Budgets for the Las Vegas Valley 141.41 141.41 141.41AAWDVMT=Average Annual Week Day Vehicle Miles Traveled. Transit Daily Miles was provided by the RTC Transit Department 8-13-2008. Source: Regional Transportation Commission staff

Table 29. Mobile Source PM10 Emission Factors (Grams per Vehicle-Mile)

Roadway Category 2013 2020 2030 Ext. Connector 0.0275 0.026 0.0257 Freeway Ramps 0.0275 0.026 0.0257 Minor Arterial 0.0275 0.026 0.0257 Major Arterial 0.0275 0.026 0.0257 Ramps 0.0275 0.026 0.0257 Interstate 0.0275 0.026 0.0257 Freeway 0.0275 0.026 0.0257 Expressway 0.0275 0.026 0.0257 Collector 0.0275 0.026 0.0257 Local 0.0275 0.026 0.0257 Inter-Zonal Trips 0.0275 0.026 0.0257 Public Transit 0.0275 0.026 0.0257

Source: DAQEM

Table 30. PM10 Vehicle Emissions 2013 2020 2030 AAWDVMT 44,793,987 56,020,120 67,921,978 Vehicle Emissions Factor (gm/v-m) 0.0275 0.026 0.0257 PM10 Vehicle Emissions (kg/day) 1,232 1,457 1,746 PM10 Vehicle Emissions (tons/day) 1.36 1.61 1.92

Source: DAQEM


Table 30. PM10 Emissions from Highway Construction and Wind Erosion

2013 2020 2030SOURCE Link Lane Link Lane Link Lane CONSTRUCTIONConstruction Miles 110.9 679.4 122.2 786.1 296.8 1105.0Horizon Year Total Projects 144 104 58Number of months in Horizon Year 60 84 24Estimated Acreage 985 1140 1602Emissions Factors (tons/acre/mon) 0.42 0.42 0.42PM10 Vehicle Emission (tons/day) 0.2261 0.1869 0.9193Best Practices Reduction (%) 68% 68% 68%Net PM 10 Emissions (tons/day) 0.07235 0.0598 0.2942WIND EROSIONEstimated Acreage 985 1140 1602Erosion Rate (tons/acre/day) 35% of site 0.00076 0.0008 0.000865% of site 0.0198 0.0198 0.0198PM10 Emissions (tons/day) 0.27 0.31 0.4544Sections 90-94 Reduction (%) 71% 71% 71%Net PM 10 Emissions (tons/day) 0.19097 0.2193 0.3226


7.6.1. More about Particulate Matter (PM10) Analysis Methodology Year 2007 serves as the “base” and form the basis for each later scenario, The horizon years 2013 and 2020, serve as intermediate analysis points. The long-range horizon year of the transportation plan's forecast period, the year 2030, shall be the final emissions analysis year.

The PM10 emissions predicted by the horizon year scenarios, defined in above, shall be less than the mobile source emission budget established in the 2001 PM10 SIP. The approved PM10 mobile source emissions budget is 141.41 tons per day for 2006 and successive planning horizon years. The Table 31 summarizes the calculation of total PM10 mobile source emissions for each of the horizon analysis years. Table 31. Total PM10 Mobile Source Emissions Per Day for Horizon Years SOURCE 2013 2020 2030 Paved Road Dust 76.96 93.65 107.82Vehicle Emissions 1.53 1.81 2.17Highway Construction 0.07 0.06 0.29Windblown Construction Dust 0.19 0.22 0.32

PM10 Mobile Source Emissions 78.75 95.74 110.60

BUDGET 141.4 141.4 141.4Source: Regional Transportation Commission staff.


8. Ozone Modeling Assumptions Currently, there is no Ozone O3 budget for the RTC modeling area. The EPA gave non-attainment areas until 2008 to develop a new SIP and mobile source budget for O3. In the absence of an emission budget, the RTC will compare the “Action” scenario versus the “No Build” scenario as defined in 40 CFR Part 93. The regulatory prescribed comparison is structured as follows. Travel demand (VMT) and the associated emission estimates are generated for future travel under two scenarios. For the “Action” scenario all travel is loaded onto the “anticipated” built network as defined in the project listing that comprises the 2013-2030 project list in the RTP. The emission estimates are calculated for the “Action” scenario by required horizon years, i.e., 2013, 2020 and 2030. The emission output for the “Action” scenario is compared against the “No Build” scenario for each of the horizon years. If the “Action” scenario emission estimates are less than the “No Build” for each of the horizon years, the region is determined to be in positive transportation conformity for O3. The “No Build” scenario is defined as: 1) the in-place roadway network as of RTP’s start year of 2009, 2) assumption of the continuation of all ongoing travel demand management and/or transportation system management activities, 3) the continued application of any SIP mandated control measures, and 4) inclusion and assumption of completion for all “ongoing” roadway construction projects. Except for the model networks are coded as No Build or Action scenarios, the same travel demand input files based on the same land use information were applied into the model for the “Action” scenario and the “No Build” scenario for each of the horizon years.

8.1. Estimating Regional Travel for Ozone Conformity The RTC estimates travel by horizon years for CO and PM10 utilizing the regional travel demand model, which encompasses the Las Vegas urban area. The non-attainment area for O3 is larger than the extent of the travel model domain the RTC maintains. Therefore, the RTC estimates regional travel for the roadway network outside of the urban area. Working with NDOT, RTC estimated VMT and travel speeds for the roadway network outside of the urban area. This included segments of I-15, US 93, US 95, State Route (SR) 157, SR 158, SR 159, SR 160, SR 161, SR 163, SR 164, SR 167, SR 168 and roadways in Laughlin. VMT estimates were based on regression analysis data provided by NDOT. Travel speed estimates were based on data published in NDOT’s Annual Speed Monitoring Report Details.

8.2. Ozone Roadway Emissions Calculation Tables 32A through 32C display the results of air quality modeling for O3. The modeling process uses levels of nitrous oxides (NOx) and volatile organic compounds (VOC), precursors of O3, to forecast the effectiveness of the RTP/TIP on levels of O3. Mobile


6.2 was run to obtain the NOx and VOC emission factors for urbanized areas and these factors were applied to the corrected, adjusted and modeled VMT. Mobile 6.2 was run separately to obtain the emission parameters for Rural Areas and these emission factors were applied to the VMT outside the modeling areas. As Tables 33 – 34 show that emissions from outside modeling areas are constant for the same horizon years regardless of Build or No Build. The Total NOx and VOC emissions should include all emissions outside the modeling area but within the Ozone Non – attainment boundary, but this inclusion does not change the results of the Build versus No-Build tests for the analysis on Ozone pollutants. Table 35 shows the total NOx and VOC emissions including the emissions within the modeling area, and the areas outside modeling area but within the boundaries of the Ozone Nonattainment Areas for all horizon years. Table 32A. 2013 Horizon Year VOC and NOx Emissions for TDF Modeling Area

NOx (tons/day) VOC (tons/day) Build vs. No Build

ROAD TYPE Build No

BuildBuild No

BuildNOx VOC

External 0.14 0.14 0.17 0.17 0.00 0.00 System-to-system Ramp 0.24 0.25 0.27 0.28 -0.01 -0.01 Minor Arterial 3.47 3.47 4.75 4.80 -0.01 -0.06 Major Arterial 8.68 8.69 13.51 13.61 -0.01 -0.10 Ramp 0.69 0.69 0.78 0.79 0.00 -0.01 Interstate 5.91 6.01 8.52 9.33 -0.10 -0.81 Freeway 2.90 2.91 3.40 3.48 0.00 -0.08 Expressway 0.00 0.00 0.00 0.00 0.00 0.00 Collector 2.01 2.01 2.87 2.90 0.00 -0.03 Centroid 2.13 2.13 3.59 3.59 0.00 0.00 Local 0.03 0.03 0.05 0.05 0.00 0.00 HOV 0.12 0.12 0.12 0.12 0.00 0.00 TOTAL EMISSIONS 26.30 26.44 38.04 39.13 -0.14 -1.09

Source: Regional Transportation Commission staff. Same for Tables 32B and 32C. Table 32B. 2020 Horizon Year VOC and NOx Emissions for TDF Modeling Area

NOx (tons/day) VOC (tons/day) Build vs. No Build

ROAD TYPE Build No

BuildBuild No

BuildNOx VOC

External 0.08 0.08 0.13 0.13 0.00 0.00 System-to-system Ramp 0.14 0.14 0.19 0.19 0.00 0.00 Minor Arterial 2.49 2.49 4.52 4.50 0.00 0.02 Major Arterial 5.39 5.39 10.74 10.69 0.00 0.05 Ramp 0.42 0.42 0.57 0.57 0.00 0.00 Interstate 4.12 4.13 8.36 8.46 -0.01 -0.10 Freeway 2.02 2.05 3.11 3.26 -0.03 -0.15 Expressway 0.00 0.00 0.00 0.00 0.00 0.00 Collector 1.17 1.18 2.08 2.11 -0.01 -0.03 Centroid 1.35 1.35 2.88 2.88 0.00 0.00 Local 0.02 0.02 0.04 0.04 0.00 0.00 HOV 0.08 0.07 0.11 0.10 0.01 0.01 TOTAL EMISSIONS 17.27 17.31 32.73 32.92 -0.04 -0.18


Table 32C. 2030 Horizon Year VOC and NOx Emissions for TDF Modeling Area NOx (tons/day) VOC (tons/day) Build vs. No Build

ROAD TYPE Build No

BuildBuild No

BuildNOx VOC

External 0.07 0.07 0.13 0.13 0.00 0.00 System-to-system Ramp 0.13 0.11 0.20 0.17 0.02 0.03 Minor Arterial 2.14 2.33 4.52 5.13 -0.19 -0.61 Major Arterial 4.43 4.72 10.75 11.91 -0.29 -1.16 Ramp 0.34 0.33 0.50 0.49 0.01 0.01 Interstate 3.76 3.73 10.43 11.69 0.03 -1.25 Freeway 1.74 1.68 3.37 3.14 0.06 0.23 Expressway 0.59 0.58 3.72 3.65 0.01 0.06 Collector 1.01 1.11 2.18 2.33 -0.10 -0.15 Centroid 1.07 1.08 2.72 2.73 0.00 -0.01 Local 0.02 0.02 0.05 0.05 0.00 0.00 HOV 0.27 0.08 0.48 0.12 0.19 0.35 TOTAL EMISSIONS 15.57 15.84 39.05 41.55 -0.26 -2.49

Table 33A. Interstate and Major Road NOx Emissions Outside TDF Modeling Area VMT and Emission Factors Outside Corridor Horizon Year VMT Emission Factors VMT Ave 2013 2020 2030

2013 2020 2030 Speed NOX VOC NOX VOC NOX VOC 104,000 128,180 152,100 35 0.849 0.538 0.42 0.38 0.292 0.318 88,000 95,200 108,000 40 0.864 0.517 0.43 0.36 0.296 0.303

5,250 5,614 7,875 45 0.897 0.5 0.44 0.35 0.304 0.29 2,800 2,800 2,800 45 0.897 0.5 0.44 0.35 0.304 0.29 8,400 9,600 10,920 45 0.897 0.5 0.44 0.35 0.304 0.29

96,000 110,000 125,000 50 0.951 0.486 0.46 0.34 0.316 0.28 103,040 137,200 182,000 55 1.031 0.474 0.49 0.33 0.334 0.273 74,480 89,300 123,500 55 1.031 0.474 0.49 0.33 0.334 0.273 12,240 13,716 16,470 55 1.031 0.474 0.49 0.33 0.334 0.273

208,000 208,000 275,600 55 1.031 0.474 0.49 0.33 0.334 0.273 169,000 205,400 221,195 60 2.055 0.432 0.83 0.31 0.488 0.263 48,000 55,000 62,500 65 2.102 0.432 0.851 0.309 0.497 0.263

7,840 9,400 13,000 65 2.102 0.432 0.851 0.309 0.497 0.263 11,400 13,050 15,900 65 2.102 0.432 0.851 0.309 0.497 0.263

888,000 1,140,000 1,440,000 70 2.102 0.432 0.851 0.309 0.497 0.263 18,810 20,350 24,200 70 2.102 0.432 0.851 0.309 0.497 0.263

165,600 204,000 252,000 70 2.102 0.432 0.851 0.309 0.497 0.263 38,400 43,680 53,640 70 2.102 0.432 0.851 0.309 0.497 0.263 22,000 26,000 31,200 70 2.102 0.432 0.851 0.309 0.497 0.263

675,840 816,000 1,008,000 75 2.102 0.432 0.851 0.309 0.497 0.263 Source: Emission factors from Mobile 6 Rural Run results. VMT from Regional Transportation Commission staff. See tables in previous section.


Table 33B. NOX and VOC Emissions From Interstate, Highways and Major Arterials Outside Modeling Area Outside Corridor VMT 2013 Emissions 2020 Emissions 2030 Emissions

2013 VMT 2020 VMT 2030 VMT NOX VOC NOX VOC NOX VOC104,000 128,180 152,100 88,296 55,952 53,707 48,068 44,413 48,368

88,000 95,200 108,000 76,032 45,496 40,460 34,177 31,968 32,7245,250 5,614 7,875 4,709 2,625 2,465 1,942 2,394 2,2842,800 2,800 2,800 2,512 1,400 1,229 969 851 8128,400 9,600 10,920 7,535 4,200 4,214 3,322 3,320 3,167

96,000 110,000 125,000 91,296 46,656 50,710 36,850 39,500 35,000103,040 137,200 182,000 106,234 48,841 67,640 45,002 60,788 49,686

74,480 89,300 123,500 76,789 35,304 44,025 29,290 41,249 33,71612,240 13,716 16,470 12,619 5,802 6,762 4,499 5,501 4,496

208,000 208,000 275,600 214,448 98,592 102,544 68,224 92,050 75,239169,000 205,400 221,195 347,295 73,008 171,304 63,469 107,943 58,174

48,000 55,000 62,500 100,896 20,736 46,805 16,995 31,063 16,4387,840 9,400 13,000 16,480 3,387 7,999 2,905 6,461 3,419

11,400 13,050 15,900 23,963 4,925 11,106 4,032 7,902 4,182888,000 1,140,000 1,440,000 1,866,576 383,616 970,140 352,260 715,680 378,720

18,810 20,350 24,200 39,539 8,126 17,318 6,288 12,027 6,365165,600 204,000 252,000 348,091 71,539 173,604 63,036 125,244 66,276

38,400 43,680 53,640 80,717 16,589 37,172 13,497 26,659 14,10722,000 26,000 31,200 46,244 9,504 22,126 8,034 15,506 8,206

675,840 816,000 1,008,000 1,420,616 291,963 694,416 252,144 500,976 265,104Convert to US Tons Per Day (Kg/day by /1000, tons by * 0.001102) 0.00000110TOTAL

2,747,100 3,332,490 4,125,900 5.48 1.35 2.78 1.16 2.06 1.22 Source: Regional Transportation Commission staff.

Table 34A. 2013 Minor VOC Emissions Outside TDF Modeling Area

Speed

VOC emission factor

NOX emission factor Total VMT

VOC emissions

NOX emissions

Minor Arterials 35 0.538 0.849 41,098 22,111 34,893Collectors 30 0.57 0.862 34,776 19,822 29,977Other Local Roads 25 0.898 0.61 29,507 26,497 17,999Convert to US Tons Per Day (Kg/day by /1000, tons by * 0.001102) 0.00000110

TOTAL 105,380 0.08 0.09 Source: Regional Transportation Commission staff.

Table 34B. 2020 Minor Year NOx Emissions Outside TDF Modeling Area

Speed

VOC emission factor


VOC emissions

NOX emissions


TOTAL 166,932 0.07 0.08 Source: Regional Transportation Commission staff.


Table 34C. 2030 Minor VOC Emissions Outside TDF Modeling Area

Speed

VOC emission factor


VOC emissions

NOX emissions


TOTAL 259,080 0.10 0.09 Source: Regional Transportation Commission staff. Table 35. TOTAL NOx and VOC Emissions for Horizon Years

2013 2020 2030

TYPEBuild No

BuildBuild No

BuildBuild No

BuildBuild No

BuildBuild No

BuildBuild No

BuildModeled Emission 26.30 26.44 38.04 39.13 17.27 17.31 32.73 32.92 15.57 15.84 39.05 41.55Highway EmissionOutside Model Area 5.48 5.48 1.35 1.35 2.78 2.78 1.16 1.16 2.06 2.06 1.22 1.22Local EmissionOutside Model Area 0.08 0.08 0.09 0.09 0.07 0.07 0.08 0.08 0.10 0.10 0.09 0.09TOTAL 31.85 31.99 39.49 40.58 20.13 20.17 33.97 34.16 17.73 18.00 40.36 42.85

NOx

(tons/day)VOC

(tons/day)NOx

(tons/day)VOC

(tons/day)NOx

(tons/day)VOC

(tons/day)


9. Finding of Conformity It is a requirement of Federal and State Conformity Regulations that the projected mobile source emissions for the Non-attainment Area for the pollutants should be lower than the Budgets contained in the State Implementation Plans. For CO, the projected net mobile source emissions are compared with the Mobile Source Emissions Budgets set out in the September 6, 2006 amendment to the “Carbon Monoxide State Implementation Plan for the Las Vegas Valley Nonattainment Area” Clark County Board of Commissioners, August 2000. For PM10, the projected emissions resulting from the process described in Section 5.6 are compared with the Mobile Source Emissions Budgets set out the “PM10 State Implementation Plan for Clark County, Nevada”. For O3, the projected emissions resulting from the process described in Section 8 are compared with the “No Build” scenario as defined in 40 CFR Part 93. As shown in Table 36, these tests of conformity are satisfied for all pollutants.


Table 36. Conformity Test Summary

CO (tons/day) PM10 (tons/day)

Year Emissions Emissions

Budget Conformity

Requirement EmissionsEmissions

Budget Conformity

Requirement

2010 378 690 Satisfied 2013 375 690 Satisfied 78.75 141.44 Satisfied 2015 384 768 Satisfied 2020 400 817 Satisfied 95.74 141.44 Satisfied 2030 463 817 Satisfied 110.60 141.44 Satisfied

NOx (tons/day) VOC (tons/day) Year Build No Build

Conformity Requirement Build No Build

Conformity Requirement

2013 31.85 31.99 Satisfied 39.49 40.58 Satisfied 2020 20.13 20.17 Satisfied 33.97 34.16 Satisfied 2030 17.73 18.00 Satisfied 40.36 42.85 Satisfied

Based on the foregoing analysis, the projects and programs contained in the Regional Transportation Plan FY 2009-2030 found to be in conformity with the requirements of the Clean Air Act Amendments of 1990, the relevant sections of the Final Conformity Rule 40 CFR Part 93 and the procedures set forth in the Clark County Transportation Conformity Plan.

9.1. Transportation Control Measures A second component of conformity determination is an assessment of the progress in implementing TCMs. These measures are intended to reduce emissions or concentrations of pollutants from transportation sources by reducing vehicle use or otherwise reducing vehicle emissions. As part of the conformity process, the RTC must certify that TCMs identified in the SIPs are either programmed or are being implemented on schedule and that no Federal funds are being diverted from these projects in such a way as to delay their timely implementation. Due to the length of the text and the level of detail associated with the control measures discussion for both CO and PM10, this analysis will not extend further discussion here.

9.1.1. Statement of TCM Progress As required by 23 CFR, Part 450.324, n(3), in non-attainment areas, the TIP must describe the progress in implementing any required TCMs, including any reasons for significant delays in the planned implementation and strategies for ensuring their advancement at the earliest possible time. The following table provides the existing status of TCMs from both the CO and PM10 SIPs.


9.1.2. Transportation Control Measure Certification The RTC of Southern Nevada certifies that TCMs identified in the both the 2000 CO SIP and the 2001 PM10 SIP are being implemented on schedule and that no Federal funds are being diverted from these projects in such a way as to delay their timely implementation. Table 37 lists some of the adopted mobile source TCMs.

Table 37. Status of Adopted Mobile Source Transportation Control Measures Carbon Monoxide

Control Measures from 2000 CO SIP

Emission Reduction Status

Voluntary Transportation Control Measure/TDM 0.08% Ongoing; the RTC's TDM program is

described in detail in Section 4 Alternative Fuels Program for Government Fleets 0.12% Ongoing; local government committed to

alternative fuels program Previously Adopted Enforceable Control

Measure Adoption

Date Status

Motor Vehicle Inspection & Maintenance Program 1978 Ongoing

Fleet Over 1967 Ongoing Particulate Matter 10 Microns or Less (PM10)

Control Measures from 2001 PM10 SIP Status

Paving of Unpaved Roads Ongoing contracts with member entities for paving; funds programmed into the TIP.

Stabilize Narrow Roadway Shoulders Approved and programmed into the TIP.

Transportation Construction - Rules 90-94

Ongoing; all transportation construction projects must conform. All transportation construction contracts, regardless of funds source, include the requirement to conform to Rules 90-94.


APPENDIX 4-A:

RTC 2004 Regional Travel Demand Model Package 2 for 2009-2030 RTP

Travel Demand Model

Transit Processing and Mode Choice Modeling Capabilities

Prepared for:

Regional Transportation Commission of Southern Nevada


2009-2030 RTP Travel Demand Model - RTC 2004 Regional Travel Demand Model Package 2

Transit Processing and Mode Choice Modeling Capabilities - Basic Procedures Introduction The RTC 2004 Regional Travel Demand Model Package 2 A (hereafter short for The RTC 2004 Model Pack 2) will be used for the 2009-2030 RTP. The RTC 2004 Model Pack 2 adds transit processing and mode choice modeling capabilities to the RTC 2004 Regional Travel Demand Model (hereafter short for The RTC 2004 Model) that was used in the 2006-2030 RTP. The RTC 2004 Model represents an evolution of travel forecasting models and model components specifically developed for the Las Vegas Valley portion of Clark County. Model components for trip generation, trip distribution, and auto occupancy models were re-estimated based on the 1996 regional travel survey. In addition, 2000 Census data were used to update socioeconomic sub-models for trip generation and to re-expand the 1996 travel survey data. (for model details, refer to RTC 2004 Regional Travel Demand Model). The RTC 2004 Model has been updated to the RTC 2004 Model Pack 2 by including additional and optional transit processing and mode Choice modeling capabilities. This document provides a description of the basic procedures included in the RTC 2004 Model Pack 2: • Transit network coding procedures • Transit path-building and skimming procedures • Mode choice procedures • Transit assignment procedures The simplified mode split procedure in the RTC 2004 Model continues to be used for forecasts not requiring detailed mode choice processing. Results from the detailed procedures described in this document can be aggregated and summarized at the district level to provide input for the simplified mode split procedures. If the proposed changes are sufficiently large (e.g. the widening of an interstate freeway), it might be reasonable to use the simplified mode split for initial planning forecasts and then use the detailed transit modeling and mode choice procedures described in this chapter for final alternative testing. Transit Network Description For the base year or currently, the Citizens Area Transit (CAT) provided public transportation services for the Las Vegas Valley. Fixed-route local bus service provide


the bulk of the existing transit system with limited stop service and express service being. Most bus routes provided 30 minute headways throughout the day; several routes offered 24-hour service but with 45 minute or 60 minute headways during the “owl” service. In 2004, the monorail serving the Las Vegas Strip and the MAX bus rapid transit (BRT) demonstration project on North Las Vegas Boulevard were opened. The transit routes, including local bus, limited bus, express bus and premium services for the base year and future years were coded into the TransCAD network for the model. The following Figure1 shows the transit system that existed in 2002-2003 as an example.

YEAR 2000 - TRANSIT ROUTES

Figure 1: 2002-2003 CAT Bus Routes Para-transit services are also provided in the region. CAT provides a several fixed routes that serve retirement communities, shopping areas, and establishments which provide services to seniors. The routes offer limited services two days each week. These routes are not considered part of the modeled transportation system. While all current transit services provide relatively balanced services throughout the day, both peak and off-peak transit networks are coded for the modeling process. This


approach provides the capability to analyze future alternatives that vary service by time-of-day. Transit speeds have been coded to reflect the schedule nature of transit service but also taking into consideration prevailing roadway speeds for mixed flow operations. Scheduled time points for the transit service were recorded on the coded transit network for the morning peak, afternoon peak, and off-peak periods. The travel times on links between time points were estimated by prorating the scheduled travel times over those links on a route-by-route basis. The resulting average speeds on links were summarized by facility type, area type, and time-of-day for each route. Modeled congested speeds are updated within the modeling process by running several iterations of the entire modeling process until final assigned roadway speeds reasonably match the roadway network speeds used for trip distribution and mode choice. Transit speeds for premium transit services will be estimated for each alternative based on the operating characteristics of the alternative, station spacing, and station dwell times. In general, transit speeds for premium transit services will be unaffected by changes in modeled congested speeds on roadways. Transit Access Coding Walk Access Substantial effort was expended to determine appropriate walk access coding conventions for the RTC 2004 Pack 2. Since walk access distance data were not recorded for the 2002 on-board survey, the “best” walk access coding distance was determined through multiple assignments of the observed trip tables derived from the 2002 survey data to the 2002 network. The resulting modeled boardings by line were compared to observed boardings by line. This effort was part of the determination of transit path-building parameters. The best results were obtained when walk access was coded to all transit within 1.25 miles of a TAZ. Walk access distances were varied by trip purpose and income group being modeled. The variation in walk access distances reflect the fact that lower income groups are more likely to be captive and, thus, more likely to walk longer distances to access transit than higher income groups. About 80 percent of the linked transit trips summarized from the 2002 CAT on-board survey were made by travelers reporting low or lower-middle incomes. The walk access distances also reflect that residents do not walk long distances to transit for non-home-based trips and, likewise, that visitors do not walk long distances to transit. Two different transit networks (peak and off-peak) are each used for path-building. Value-of-time is also varied for the path-building process. Two different value-of-time assumptions are used for the visitor paths. In total, five different sets of walk access to transit skims are built. Table 1 shows the walk distances for transit path-building for different trip purposes and different income groups.


Table 1: Walk Distances for Transit Path-Building

Trip Purpose Income Group Network Used

Maximum Walk

Access Distance (Miles)

Maximum Walk

Transfer Distance (Miles)

Walk Speed (MPH)

Home-Based Work Low & Lower Middle Peak 1.25 0.25 3 Home-Based Work Upper-Middle & High Peak 0.5 0.25 3 Home-Based Non-Work All Off-Peak 0.5 0.25 3 Non-Home-Based All Off-Peak 0.5 0.25 3 All Visitor All Off-Peak 0.5 0.25 3 Walk access is allowed to occur over the coded roadway network provided the network link is not part of a limited access facility (interstate, freeway, expressway, system ramp or ramp). In all cases, transfer walk times are limited to one-quarter mile (five minutes). All walk access and walk transfer are assumed to occur at a three mile per hour average walking speed. Drive Access While there is very little formal park-and-ride facilities and existing auto access to transit in the Valley, park-and-ride might be a very important component of future alternatives. The recently opened (2003/2004) South Strip Transit Terminal provides parking along with facilitating transfers between CAT fixed routes and bus lines. For future alternatives, drive access will be allowed to premium transit stations with proposed formal park-and-ride lots. Bicycle, drop off and other access will also be considered as “walk” access. Transit Path-Building Impedances for path-building consider fares and weighted travel times. Since relationships between fares, in-vehicle time, wait-time, and walk time vary by trip purpose (and income group for home-based work trips), maintaining complete consistency between path-building and mode choice parameters would require runs of transit path-builder for trip purpose and income group for which the mode choice model has been calibrated. This would imply building 13 different sets of transit paths for walk access to bus, alone. For the RTC 2004 Pack 2, some simplification has been assumed so that only five sets of walk access to bus transit paths need to be built. Since transit path-building considers transit fares paid, the current CAT system fare policy must be understood. That fare policy (as obtained from the RTC web-site) is as follows:

Full Fare, Reduced Fare, Full and Reduced Passes, and Transfers. Based on an analysis of 2003 revenue and boarding information, the average fare for local bus service taking into account of discounts and passes was calculated; the


average fare paid for express buses were calculated too. The modeled fares are probably more consistent with the auto operating costs represented to the model. The “full fare” method has been used for path-building and modeling purposes. For the mode choice model application, fares are expressed in 1995 dollars. Value-of-time can be determined from the mode choice model. Again, for simplification, values-of-time have been combined for a number of trip purposes. All weighted time values were converted to monetary terms and combined with fares for path-building purposes. Improved model results were obtained if the added transfer penalties were also included in the mode choice models. Through calibrations, an added transfer penalty of seven minutes per transfer was found to produce reasonable results. The path-building weights will be used for transit path-building and transit assignment along with the trip purposes that will be modeled using each set of transit impedances. The transit assignments show that there is a high correlation between the modeled boardings by line and the observed boardings by line. See Table 2 as an example. Table 2: 2002 Transit Assignment Summary Measure Observed (Summarized from

2002 CAT On-Board Survey) Assigned Observed

Trip Tables Number of Linked Trips 109,282 109,282 Total Boardings 142,744 150,360 Boardings per Linked Trip 1.31 1.38 Boardings by Type of Service Local Bus 139,836 147,412 Limited Bus 2,320 2,642 Express Bus 588 306 Coefficient of Determination (R2) 0.96 Root Mean Squared Error on Boardings 837 Percent Root Mean Squared Error 26%


0

5,000

10,000

15,000

20,000

25,000

0 5,000 10,000 15,000 20,000 25,000Observed Boardings

Mod

eled

Boa

rdin

gs

Local

Limited

Express

Figure 2: Assignment of Observed 2002 Linked Trips vs.

Observed Boardings by Route Mode Choice Resident Trip Purposes Resources were not available for the full development of mode choice models for the Las Vegas Valley. Thus, the decision was made to transfer a model to the region and update the model constants to reproduce observed transit ridership for the region. Several donor models were considered. The Las Vegas Travel Demand Model was prepared by PBQ&D in 2001. This mode choice model was estimated based on the spring 1996 household survey supplemented with data from an on-board transit passenger travel survey performed in October and November 1995. Since the PBQ&D model offers the benefit of being estimated using local data, the use of the PBQ&D mode choice model as the donor model was reasonable. Figure 3 shows the structure of the PBQ&D model. The following changes were made to the PBQ&D model structure shown in Figure 3: • The 2004 RTC Model is a trip-based model that models all trips made in motorized

vehicles. Trips made using non-motorized modes are not modeled. • Premium transit services such as the monorail and MAX BRT system are being

planned and implemented in the Las Vegas region. Some of the service will offer multiple transit options within a corridor. For example, both the monorail and buses provide transit service on the Strip. Thus, a local / premium nest under the walk to transit access mode has been added to the mode choice model. Since park-and-


ride lots are normally associated with premium transit services offered to outlying areas, there is little need to provide a local / premium nest under the drive access mode.

Choice

Motorized

Auto Transit

Drive Alone Shared Ride

2 Person 3+ Person

Walk Access Drive Access

Local Bus Park-and-Ride

Kiss-and-Ride

Walk/Bike

Figure 3: PBQ&D Mode Choice Model Structure

The analysis of toll roads is an increasing requirement in many regions, especially in fast growing areas like Las Vegas. A nesting structure for the testing of toll road alternatives could be added to the model under the drive alone, shared ride 2, and share ride 3+ nests. The toll road nest would need to be adapted from work performed elsewhere (e.g. Southern California). Since the average wage rates for each income group were known, the coefficients of cost for the home-based work mode choice model could be varied by income group to be more consistent with FTA guidelines. It’s interesting to note that the $6.12 per hour rate is within the FTA guidelines. Several changes were made to the original PBQ&D mode choice models for consistency with FTA guidelines or to enhance consistency with transit path-building procedures. Figure 4 shows the general mode choice model structure used for the 2004 RTC Park 2. The structure shown in Figure 4 is used for all resident trip purposes.


Choice

Auto Transit

Drive Alone Shared Ride Walk Access Drive Access

2 Persons 3+ Persons LocalService

PremiumServiceDrive Alone Drive Access

Figure 4 : 2004 RTC Mode Choice Model Structure Visitor Trip Purposes The PBQ&D visitor models were adapted for use with the 2004 RTC Pack 2 with Mode Choice Analysis. The mode choice model structures and parameters for the three general types of visitor models were transferred for the 2004 RTC Pack 2. The generic multinomial mode choice structures for the three types of visitor models (multi-day visitors, single day visitors, and airport related trips) are shown in Figure 5 and Figure 6. Unlike, the models for residents of the region, the visitor models forecast all person trips, not just person trips made in motorized vehicles. Thus, walk skims are required for the mode choice model implementation. The walk skims are built over the coded roadway network links except freeway or ramp links. Several other “exotic” modes are included in the visitor mode choice models: taxi, shuttle bus, and tour bus. And, private auto must consider both autos privately owned by visitors and those rented by visitors.

Choice

Walk Taxi Public Bus Shuttle Bus Premium Transit Private Auto

Figure 5: 2004 RTC Pack 2 Mode Choice Model Structure – Multi-day & Single

Day Visitor Trips


Choice

Private Auto Taxi Public Bus Shuttle Bus Tour Bus Premium Transit

Figure 6: 2004 RTC Pack 2 Mode Choice Model Structure – Airport Trips

The originally transferred visitor models included 12 trip purposes. Several of the trip purposes were combined for mode choice modeling purposes. However, efforts were made to combine only those purposes that were relatively similar both in terms of the type of trip being modeled and in terms of model coefficients. Table 3 shows the original trip purposes and the combined purposes. As with the resident-based mode choice models, a coefficient on the number of transfers was added to the visitor and airport models. The coefficient for each transfer was set to be equivalent to seven minutes of in-vehicle travel time. Mode choice model parameters and mode specific constants for the visitor and airport models are shown in Table 4. Note that the taxi base fare is fixed and could effectively be incorporated into the taxi mode constant. However, incorporating the fixed values as input constants allows for the consideration of policy changes such as a cutting the frequency of shuttle service if fixed guideway transit to the airport is provided or changing the “drop fare” for taxi service. Table 3: Combination of Visitor Trip Purposes for Mode Choice Original Trip Purpose Combined Trip Purpose Hotel-Based Convention Hotel-Based Business Hotel-Based Convention / Business

Hotel-Based Gaming Hotel-Based Gaming Hotel-Based Other Hotel-Based Other Non-Hotel-Based Gaming Non-Hotel-Based Other Single-Day Non-Airport-Based Business Single-Day Non-Airport-Based Other

Non-Hotel-Based

Resident Airport Resident Airport Visitor Airport Airport-Based Business Airport-Based Other

Vistor Airport

Two distinct types of visitor travel or travelers can be identified based on the values-of-time: travelers with very high values-of-time and travelers with “normal” values-of-time. The low value-of-time suggests that the trips are made at a more leisurely pace with travelers being less willing to substitute higher cost and fast modes for lower cost and slower mode. The airport trips are also associated with low values-of-time for several


reasons, such as the value-of-time for airport trips is in the range for noted for resident-based trips. Mode Choice and Transit Assignment Validation Results Table 4 summarizes the observed and modeled linked transit trips and transit mode shares by trip purpose. The observed linked transit trips by purpose were estimated from the expanded 2001/2002 on-board transit travel survey data. Table 4 simply shows that the calibration process was successful in reproducing the observed targets. Table 5 summarizes the observed and modeled boardings by the path-building techniques defined previously. The modeled boardings per linked trip are higher than the observed boardings per linked trip. As discussed in the section describing path-building parameters, the boardings per linked trip could be reduced by increasing the maximum walk access distances. When new on-board survey data are collected for the Las Vegas region, a concerted effort should be made to obtain good data on walk access and egress distances since reliable observed data could lead to improvements to the modeling process. Table 4: 2002 Observed and Modeled Transit Trips by Purpose

Trips Mode Shares Trip Purpose Observed Modeled Observed Modeled

Home-Based Work Low Income 17,920 17,896 29.8% 29.8% Lower Middle Income 12,377 12,376 16.9% 16.9% Upper Middle Income 5,303 5,303 2.9% 2.9% High Income 3,599 3,599 0.8% 0.8% Total Home-Based Work 39,199 39,174 5.2% 5.2% Home-Based School 2,471 2,464 0.7% 0.7% Home-Based Shop 9,304 9,275 2.1% 2.1% Home-Based Other 33,820 33,810 1.8% 1.8% Non-Home-Based 11,558 11,486 0.9% 0.9% Total Resident Trips 96,352 96,209 2.1% 2.1% Hotel-Based Convention / Business 257 257 0.4% 0.4% Hotel-Based Gaming 5,994 5,948 4.1% 4.1% Hotel-Based Other 3,343 3,338 2.2% 2.2% Non-Hotel-Based 3,308 3,302 1.9% 1.9% Airport-Based Resident 0 51 0% 0.4% Airport-Based Visitor 85 85 0.1% 0.1% Total Visitor Trips1 12,987 12,981 2.1% 2.1% Total Trips 109,339 109,190 2.1% 2.1% 1 Includes resident-based airport trips.


Table 5: 2002 Observed and Modeled Transit Boardings by Path Set Boardings Boardings / Trip Trip Purposes Path-Set

Observed Modeled Observed Modeled Home-Based Work Low & Lower Middle Income 1 41,833 51,300 1.39 1.69 Upper Middle & High Income 2 11,673 16,521 1.32 1.86 Home-Based Non-Work1 3 59,331 71,336 1.31 1.57 Non-Home-Based & Visitor – Low Value-of-Time2 4 18,608 23,344 1.25 1.56

Visitor – High Value-of-Time3 5 11,299 13,692 1.19 1.43 Total Boardings 142,744 176,194 1.31 1.61 1 Includes home-based school, home-based shop, and home-based, other trips. 2 Includes hotel-based other, airport-based resident and airport-based visitor trips. 3 Includes hotel-based convention/business, hotel-based gaming, and non-hotel-based

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Figure 8: Assignment of Modeled 2002 Linked Trips vs. Assignment of Observed 2002 Linked Trips by Route Figures 7 and 8 compare the modeled and observed boardings on a route-by-route basis. Figure 7 compares the assignment of the modeled trip tables with the observed boarding counts from 2002. Figure 8 compares the assignments of the modeled trip tables to the assigned observed trip tables summarized from the 2002 on-board survey. The information in the above tables and the following figures suggest that the modeling process is reasonably reproducing observed travel Table 6 summarizes assignment statistics comparing the observed boardings with the assignment of the observed trip tables summarized from the 2002 on-board survey and the assignment of the modeled trip tables. Table 6: Transit Assignment Summary

Trip Tables Assigned Measure Observed

Boardings Observed Modeled Number of Linked Trips 109,339 109,339 109,190 Total Boardings 142,744 150,360 176,194 Boardings per Linked Trip 1.31 1.38 1.61 Boardings by Type of Service Local Bus 139,836 147,412 170,743 Limited Bus 2,320 2,642 3,878 Express Bus 588 306 1,572


MODELING PREMIUM TRANSIT AND DRIVE ACCESS TO TRANSIT Premium Service Descriptions Two new transit services were initiated in the Las Vegas region in 2004: The MAX service connecting the Downtown Transit Center with Nellis Air Force Base via North Las Vegas Boulevard was opened on June 30, 2004. The Strip Monorail service was opened between the MGM Grand Hotel and Casino on Tropicana and the Sahara Hotel and Casino on July 15, 2004. These two new services provided a unique opportunity to test the ability of the transit processing procedures and calibrated mode choice models to properly model new transit services. Premium Service Calibration Process Since detailed transit trip purpose or origin-destination data were not available for the services, the specification of the correct nesting structure and alternative specific constant was developed by running the following tests and comparing the resulting boardings to observed boardings for the late-2004 through early-2005 time period: • Both services were coded and modeled as local transit services with no special

treatment other than correctly specifying speeds, headways, and fares. • Both services were coded as above but were modeled as premium transit services,

including separate transit path-building and mode choice; the “local service” alternative specific constants were used.

• Both services were coded as above but were modeled as premium transit services, including separate transit path-building and mode choice; “premium service” alternative specific constants were specified via trial and error to best match boardings.

Premium Service Path-Building and Modeling Procedures The same basic path-building parameters for local transit paths were used. Fare weights for local bus use were used when premium paths were built. Fares for local buses were set as $5.00 boarding fares with additional $5.00 transfer fares between local buses. In contrast, boarding fares for premium transit modes were set to the proper values (i.e. $0.99 in 1995 dollars for the MAX and $2.39 in 1995 dollars for the monorail). Transfers to or from premium transit routes were free. Premium transit fares were also adjusted after the premium path-building to remove the artificially high local bus boarding and transfer fees. Also, the skims from the premium-only paths are compared to the skims using premium and local service and the “best” impedances are used for mode choice.


Premium Service Calibration Results The modeling of MAX and monorail as premium transit services was determined to be the desirable approach. A number of iterations of the calibration process were made with different values for the premium alternative specific constants and with the path-building procedures. A reasonable calibration was obtained for the MAX boardings with no difference between the values of the constants used for local and premium service. The alternative specific constants for walk to local and walk to premium transit show that there is no difference between the local and premium constants for each trip purpose. Figure 9 and Table 7 compare the modeled and observed boardings on a route-by-route basis for 2004/2005. The validation to the 2004/2005 provides two benefits: • Validation of the premium transit modeling • Validation for a year other than the year used for model calibration Figure 9 can be compared to Figure 7 for a qualitative comparison of the match between modeled and observed transit boardings by route for the original 2002 and the 2004/2005 validations. With the exception of the underestimation of the Monorail, the two figures show similar patterns for the modeled versus observed trips.

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Figure 9: Assignment of Modeled 2004/2005 Transit Trips vs. Observed Boardings by Route


The match between the modeled and observed ridership in two corridors is important in the determination of the validity of the models. Specifically, the reproduction of the transit ridership in the North Las Vegas Boulevard corridor demonstrates the ability of the model to estimate ridership on premium services while the reproduction of transit ridership in the Strip Corridor is crucial in showing the reproduction of ridership resulting from the visitor market. In total, observed transit ridership in the corridor is quite reasonably reproduced. In December 2005, ridership on the Deuce was just under 50,000 boardings per day and stabilized around 35,000 to 40,000 per day in early 2006. The ridership on the Deuce demonstrates the volatility of transit ridership in the Strip corridor. The model results suggest the need for a premium transit alternative specific constant representing substantial travel time savings. The results obtained for the MAX, the Strip Corridor, and the Monorail were all considered in making decisions regarding the final “validated” model for the region. While the MAX ridership was overestimated with no equivalent travel time savings for premium transit, ridership on the Monorail was substantially underestimated. It is very unlikely that Monorail will be considered in any of the alternatives to be considered for New Starts so the estimation of Monorail ridership becomes less important. Table 7 summarizes assignment statistics comparing the observed and modeled boardings. Results from the 2002 validation are also shown for a direct comparison of the model validation results for the two years. Table 8 summarizes the modeled transit trips and transit mode shares for 2002 and 2004/2005. The results shown in Table 8 coupled with the validation results summarized in Table 7 suggest that the model is reasonably sensitive to changes in socioeconomic characteristics and transportation supply.


Table 7: 2004/2005 Transit Assignment Summary 2004/5 Results 2002 Results3

Measure Observed Modeled Observed Modeled

Number of Linked Trips1,2 112,791 112,791 109,339 109,190 Total Boardings1,2 154,902 183,309 142,744 176,194 Boardings per Linked Trip1,2 1.37 1.62 1.31 1.61 Boardings by Type of Service Local Bus 142,503 170,676 139,836 170,743 Limited Bus 6,139 5,443 2,320 3,878 Express Bus 600 1,597 588 1,572 MAX 5,660 5,593 – – Strip Monorail 22,000 2,285 – – Coefficient of Determination (R2) 2 0.89 0.96 Root Mean Squared Error on Boardings2 2,170 1,671

Percent Root Mean Squared Error2 62% 50% 1 Actual number of linked transit trips for 2004/2005 is unknown. The modeled number of

transit trips was assumed to be correct. 2 The value excludes 2,285 assumed monorail trips (one trip per Monorail boarding)

since Monorail ridership was estimated from information included in a press release rather than being based on actual passenger counts. The Monorail Company does not publish actual ridership data.

3 Source: Table 10-18. Table 8: 2002 and 2004/2005 Modeled Transit Trips by Purpose

Modeled Trips Mode Shares Trip Purpose 2002 2004/2005 2002 2004/2005

Home-Based Work Low Income 17,896 18,519 29.8% 28.6% Lower Middle Income 12,376 12,448 16.9% 15.8% Upper Middle Income 5,303 5,026 2.9% 2.5% High Income 3,599 3,271 0.8% 0.7% Total Home-Based Work 39,174 39,264 5.2% 4.9% Home-Based School 2,464 2,477 0.7% 0.6% Home-Based Shop 9,275 9,631 2.1% 1.9% Home-Based Other 33,810 35,886 1.8% 1.7% Non-Home-Based 11,486 11,993 0.9% 0.8% Total Resident Trips 96,209 99,250 2.1% 1.9% Hotel-Based Convention / Business 257 461 0.4% 0.7% Hotel-Based Gaming 5,948 6,925 4.1% 4.2% Hotel-Based Other 3,338 4,116 2.2% 2.4% Non-Hotel-Based 3,302 4,054 1.9% 2.1% Airport-Based Resident 51 108 0.4% 0.8% Airport-Based Visitor 85 163 0.1% 0.2% Total Visitor Trips1 12,981 15,826 2.1% 2.3% Total Trips 109,190 115,076 2.1% 1.9% 1 Includes resident-based airport trips. Drive Access to Transit Since there has been very little use of the facility for park-and-ride access to transit, as for the 2002 calibration year, drive access to transit could not be calibrated based on 2004-2005 model results. Nevertheless, since future transit alternatives might make


use of park-and-ride access to attract choice riders, modeling procedures must be specified. The following summarizes modeling assumptions regarding the coding and modeling of drive access to transit: • Drive access will be coded only to formal park-and-ride lots. • Maximum drive access distances will be five miles to all park-and-ride lots except for

end-of-line stations; at end-of-line stations, drive access of up to fifteen miles will be allowed.

• Drive access distances and times will be determined from the coded roadway network.

• For mode choice, drive access cost will be determined using the same cost per mile as for the auto mode.

• Drive access will be modeled for all home-based trip purposes using the nesting structure shown in Figure 10-5; drive access will not be forecast for non-home-based trips.

• Drive access to transit will not be forecast for non-resident trip purposes. • Drive access time will be considered as out-of-vehicle travel time for mode choice;

for the home-based work purposes, the out-of-vehicle time coefficient is 2.0 times the in-vehicle time coefficient and for the home-based non-work trip purposes, the out-of-vehicle time coefficient is 3.0 times the in-vehicle time coefficient.

The drive access to transit alternative specific constants have been estimated. The proposed regional fixed guideway system, including park-and-ride lots, was coded for the 2005 network. Two sets of forecasts were made: • A forecast allowing only walk access to transit was performed to provide estimates

of transit ridership without park-and-ride. • A second set of forecasts allowing park-and-ride was performed. Park-and-ride

constants were varied so that approximately 15 to 30 percent of the total premium transit ridership for each purpose was by auto access.

Table 9 shows the target percentages of auto access by trip purpose along with the “calibrated” constants to achieve those percentages in the 2005 sensitivity test. The percentages shown in Table 9 should result in about 25 percent of all premium transit home-based work trips and about 15 percent of all premium transit home-based non-work trips being made by auto access. In comparison, in the Denver region which has a very well developed park-and-ride system, approximately 45 percent of the total systemwide home-based work trips are made using auto access and about 30 percent of the home-based non-work trips are made by auto access.


Table 9: Target Drive Access Percentages by Trip Purpose

Trip Purpose Target Drive

Access Percent

“Calibrated” Constant

Equivalent Minutes of In-Vehicle Travel Time (Compared to Walk

Access to Transit) Home-Based Work Low Income 15% -0.65066 -104.4 Lower Middle Income 20% -1.15773 -97.7 Upper Middle Income 25% -2.55443 -89.6 High Income 30% -3.38720 -85.1 Home-Based School 10% -4.05754 -153.1 Home-Based Shop 15% -2.40336 -140.1 Home-Based Other 15% -2.17282 -127.0 MODELING HIGH-OCCUPANCY VEHICLE LANES Modeling Issues By design, the mode choice model includes the capability to estimate shared ride auto use by group size. Model constants were calibrated to reproduce observed two-person and three or more person shared ride auto use by trip purpose for 2002. The estimates of the observed two-person and three or more person shared ride auto use were based on the 1996 household survey data. Future highway alternatives might include the provision of high-occupancy vehicle (HOV) lanes. Experience elsewhere has shown that HOV lane users value the travel time saved through the use of HOV lanes more highly than the simple difference between travel time on the HOV lanes and on general purpose lanes. If HOV lane traffic volumes increase to the point where HOV lanes are experiencing congestion, modification of the minimum carpool size allowed to use the HOV lanes can be made to reduce the HOV lane delay caused by congestion. The original mode choice model included coefficients for HOV travel time savings. The HOV time savings variable, as specified, is applied to any HOV time savings in excess of five minutes. But the coefficients could not be rigorously calibrated since HOV lanes were non-existent in the region in 1996 (when the data were collected). As a result, the model coefficients were specified based on models developed in other regions. The problem with forecasting HOV lane use is similar to that encountered with forecasting drive access to transit. The FTA suggested that sensitivity testing of results is important whenever drive access to transit is modeled. The same advice is applicable to the forecasting of HOV lane use. Table 10 summarizes the results of such testing for the region. The travel model was used to forecast HOV shares and HOV lane use for 2030 for the following scenarios: • A no-build scenario where no HOV lanes were assumed to exist in the region. • The build scenario where an extensive HOV lane system was implemented for the

region.


• The build scenario was modeled as above with the exception that the HOV time savings coefficient was applied to all increments of time saved, not just the increment in excess of five minutes. This was the most generous modeling approach for forecasting HOV travel.

• The build scenario was modeled as above with the exception that the HOV time savings coefficient not used. This was the most restrictive modeling approach for forecasting HOV travel.

The results summarized in Table 10 provide an idea of the sensitivity of the travel model to the HOV time savings coefficient. Since the coefficient cannot be rigorously calibrated, the sensitivity analysis as outlined above should be considered whenever planning and analysis of HOV lane alternatives is performed. In cases where HOV lanes are assumed to be in existence and an unrelated transit or roadway alternative is being analyzed, the model coefficient can be used as specified in Table 10. Table 10: HOV Time Savings Coefficient Sensitivity Testing TRIPS BY MODE NOBUILD BUILD DIFFERENCE % CHANGE drive alone 5,197,452 5,197,383 (69) 0.0% shared ride 2 3,140,653 3,142,550 1,897 0.1% shared ride 3+ 2,754,531 2,755,983 1,452 0.1% walk to local transit 211,198 208,097 (3,100) -1.5% walk to premium transit 31,348 31,490 142 0.5% drive to transit 4,704 4,382 (322) -6.8% Total 11,339,885 11,339,885 (0) 0% T:\BETH\RTP 09-30\DOC\Model Methodology-Mode Choice Sections 2006-05-05 Pk2_v1.doc


APPENDIX 4- B

NDOT TRAFFIC PROJECTIONS FOR THE RTC MODEL EXTERNAL TAZS

Clark County External AADT's 2000-2030 Source: NDOT Staff

TAZ # Description

2000 AADT (total)

2005 AADT (total)

2006 AADT (total)

2010 AADT (total)

2015 AADT (total)

2020 AADT (total)

2025 AADT (total)

2030 AADT (total)

1 US95, 5.9 mi N of SR-156 (0030374) 5,200 5,450 5,550 6,250 7,000 7,700 8,500 9,300

2 US93, at MP LN-25 S of Alamo (0170001) 1,600 1,500 1,550 1,650 1,750 1,850 2,000 2,200

3 IR15, 2 mi S of Valley of Fire Intch (0030730) 17,000 21,700 22,100 25,400 30,000 34,000 38,000 42,000

4 SR157, .2 mi W of US95 (0030368) 2,750 2,700 2,750 3,500 4,200 4,700 5,800 6,500

5 SR147, .4 mi E of Los Feliz St (0030734) 3,000 2,600 2,750 3,500 4,200 4,700 5,800 6,500

6 SR159, .1 mi E of rd to Red Rock Canyon (0030358) 2,850 4,550 5,300 6,400 8,000 9,800 11,500 13,000

7 SR564, 1.7 mi E of Las Vegas Pkwy (0033200) 3,200 2,900 2,900 3,700 4,400 4,900 6,000 6,500

8 SR160, E of SR159 (0030361) 8,750 9,550 9,750 12,000 15,000 17,000 19,000 21,000

9 US93, .3 mi E of Boulder Beach Hwy (0035220) 12,900 13,000 13,000 18,000 20,000 22,000 23,500 25,000

10 US95, .1 mi S of RxR Pass Intch (0031014) 7,600 12,300 12,700 13,000 16,000 19,000 21,000 24,000

11 IR15, at the NV/CA line (0031110) 35,000 39,500 40,500 45,000 50,000 55,000 60,000 66,000


Source: Regional Transportation Commission Staff

appendix 4. travel demand model methodology and air quality

Documents