rail yard activity study: development of truck activity

April 2017

Prepared by the

Rail Yard Activity Study:Development of Truck Activity andOn-Road Emissions Estimates for

Four Texas Intermodal Facilities

TransportationInstitute

Texas A&M

RAIL YARD ACTIVITY STUDY: DEVELOPMENT OF TRUCK ACTIVITY AND PROVISIONAL ON-ROAD EMISSIONS ESTIMATES FOR FOUR TEXAS

INTERMODAL FACILITIES

TECHNICAL REPORT

FINAL

Prepared for the Texas Commission on Environmental Quality

Air Quality Planning and Implementation Division

By

L.D. White, Associate Research Specialist, and Dennis G. Perkinson, Ph.D., Principal Investigator

Transportation Modeling Program Texas A&M Transportation Institute

TTI Study No.: 607081-0001 Study Title: Air Quality Technical Support

(PGA: 582-16-63959-05)

April 2017

TEXAS A&M TRANSPORTATION INSTITUTE The Texas A&M University System College Station, Texas 77843-3135

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EXECUTIVE SUMMARY

Emissions inventories, especially those related to State Implementation Plan (SIP) development or transportation conformity, rely on travel demand models (TDM) to estimate vehicle activity. Certain categories of intermodal facilities, such as airport cargo terminals, commercial marine ports, and rail yards, have the potential to produce a significant amount of activity not included in the TDM, but are still related to on-road mobile vehicles (i.e., trucks delivering and picking up containers, cargo, and bulk goods at these facilities). Some of the larger intermodal sites may experience a significant number of truck trips per day, resulting in a potentially significant category of activity and emissions (“off-model” on-road mobile) not included in the emissions inventories. To assess the potential magnitude of this “off-model” activity, the Texas A&M Transportation Institute (TTI) focused on two intermodal facilities in the Port of Houston area (Barbours Cut and Bayport) and two in the Dallas-Fort Worth (DFW) area (Union Pacific [UP] Dallas Intermodal Terminal and Burlington Northern Santa Fe [BNSF] Alliance Intermodal Facility). TTI used Global Positioning Satellite (GPS) data to develop truck trip profiles, which were used to develop summer weekday distance or vehicle miles of travel (VMT) and speed estimates. Using a process similar to the one used by TTI as part of TTI’s statewide virtual link method, MOVES2014a-based summer weekday emissions rates were developed and applied to the VMT and speed estimates to produce summer weekday emissions estimates. These summer weekday emissions estimates were converted to annual emissions by applying annual activity and emissions rate annualization factors. Table A shows a summary of the annual VMT and emissions estimates and Table B shows a summary of the summer weekday VMT and emissions estimates.

Table A. Annual VMT and Emissions (Tons) Estimates.

Year Data Barbours

Cut Bayport

BNSF Alliance

UP Dallas Intermodal

2011

VMT 285,203.70 499,447.75 218,266.35 454,523.55

VOC 5.40 9.07 3.73 7.81

CO 18.43 30.01 12.50 25.76

NOx 45.93 76.43 34.19 70.13

2014

VMT 321,170.80 562,340.90 245,765.45 511,792.05

VOC 4.47 7.49 2.68 6.01

CO 14.77 24.16 8.96 19.73

NOx 37.81 62.84 24.95 54.00

2017

VMT 357,134.25 625,500.50 273,337.55 569,206.55

VOC 2.72 4.57 1.65 3.76

CO 9.49 15.59 5.88 12.94

NOx 27.45 45.58 17.58 38.39

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Table B. Summer Weekday VMT and Emissions (Pounds/Day) Estimates.

Year Data Barbours

Cut Bayport BNSF Alliance UP Dallas Intermodal

2011

VMT 4,590.19 5,953.20 3,512.85 5,417.70

VOC 30.81 52.32 21.29 45.05

CO 100.99 164.41 68.52 141.15

NOx 226.72 377.33 170.99 350.73

2014

VMT 5,169.03 6,702.86 3,955.44 6,100.29

VOC 25.44 43.12 15.25 34.56

CO 80.94 132.39 49.10 108.11

NOx 186.64 310.22 124.76 270.08

2017

VMT 5,747.86 7,455.67 4,399.19 6,784.66

VOC 15.44 26.12 9.33 21.47

CO 52.01 85.41 32.20 70.90

NOx 135.52 225.01 87.90 191.97

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TABLE OF CONTENTS List of Figures ............................................................................................................................... vii List of Tables ................................................................................................................................ vii Purpose .............................................................................................................................................1 Background ......................................................................................................................................1 Rail Yard Activity Study: Development of Truck Activity and Provisional On-Road Emissions

Estimates for Four Texas Intermodal Facilities ...................................................................1 Subtask 2.1: Project Data .............................................................................................................1 Subtask 2.2: Summary of Proposed Methodology ......................................................................2 Subtask 2.3: Provisional Emissions Inventory Estimates ............................................................2 Acknowledgments .......................................................................................................................2

Summary of Results .........................................................................................................................3 Subtask 2.1: Project Data .................................................................................................................5 Subtask 2.2: Summary of Proposed Methodology ..........................................................................5 Subtask 2.3: Provisional Emissions Inventory Estimates ................................................................6

Activity Estimation ......................................................................................................................6 GPS Data Preparation ..............................................................................................................6 GPS-Based Truck Average Trip Length and Trip Time ..........................................................8 Summer Weekday Daily Facility VMT and Operation Time ..................................................9 Summer Weekday Hourly VMT, Operating Times, and Speeds ...........................................11

Emissions Rates .........................................................................................................................12 Summer Weekday Emissions Estimation ..................................................................................13 Annual Emissions Estimation ....................................................................................................14

Recommendations ..........................................................................................................................14 References ......................................................................................................................................14 Appendix A: Electronic Data Submittal Description .....................................................................17 Appendix B: Summer Weekday VMT and Emissions Summary ..................................................21 Appendix C: Rail Yard Activity Study Project Data .....................................................................29 Appendix D: Rail Yard Activity Method.......................................................................................33 Appendix E: Summer Weekday Hourly VMT, Operational Time, and Speed .............................39 Appendix F: Rail Yard Activity Study Rates Pre-Analysis Plan ...................................................47 Appendix G: Emissions Rate Annualization Factors .....................................................................55

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LIST OF FIGURES

Figure 1. Barbours Cut Facility. ......................................................................................................7 Figure 2. Bayport Facility. ...............................................................................................................8

LIST OF TABLES

Table 1. Summer Weekday VMT and Emissions (Pounds/Day). ...................................................3 Table 2. Annual VMT and Emissions (Tons/Year). ........................................................................4 Table 3. GPS-Based Average Truck Trip Length and Operation Time. .........................................9 Table 4. 2017 Port of Houston Area Daily Truck VMT and Operational Time by Facility. ..........9 Table 5. 2011 and 2014 Port of Houston Area Daily Truck VMT and Operational Time by

Facility. ....................................................................................................................................10 Table 6. DFW Areas Daily Truck VMT and Operational Time by Facility. .................................10 Table 7. Hourly VMT and Operational Time Distributions. .........................................................11 Table 8. Emissions Control Strategies and Approaches. ...............................................................13

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PURPOSE

This study obtained and analyzed information on truck activity associated with major intermodal facilities in Texas as agreed upon between the Texas Commission on Environmental Quality (TCEQ) and the Texas A&M Transportation Institute (TTI). The two major intermodal facilities in the Port of Houston area (Barbours Cut and Bayport) and two major facilities in the DFW area (Union Pacific [UP] Dallas Intermodal Terminal and Burlington Northern Santa Fe [BNSF] Alliance Intermodal Facility) were selected for the study. The trucks operating in and around these facilities are a potential source of on-road oxides of nitrogen (NOX) emissions that are not currently captured in the on-road emissions inventories. The information may be used to: determine emissions that contribute to the formation ozone, assess possible controls programs, and assess emissions for other rail yards in Texas.

BACKGROUND

Emissions inventories, especially those related to State Implementation Plan (SIP) development or transportation conformity, rely on travel demand models (TDM) to estimate vehicle activity. Certain categories of intermodal facilities, such as airport cargo terminals, commercial marine ports, and rail yards, have the potential to produce a significant amount of activity not included in the TDM, but are still related to on-road mobile vehicles (i.e., trucks delivering and picking up containers, cargo, and bulk goods at these facilities). Some of the larger intermodal sites may experience a significant number of truck trips per day, resulting in a potentially significant category of activity and emissions (“off-model” on-road mobile) not included in the emissions inventories.

RAIL YARD ACTIVITY STUDY: DEVELOPMENT OF TRUCK ACTIVITY AND PROVISIONAL ON-ROAD EMISSIONS ESTIMATES FOR FOUR TEXAS INTERMODAL FACILITIES

TTI produced 2011, 2014, and 2017 provisional emissions inventory estimates for the truck activity at the selected intermodal facilities in the Port of Houston area (Barbours Cut and Bayport) and in the DFW area (UP Dallas Intermodal Terminal and BNSF Alliance Intermodal Facility). Emissions estimates were developed for the following pollutants: volatile organic compounds (VOC), carbon monoxide (CO), NOX, sulfur dioxide (SO2), ammonia, particulate matter (PM) with an aerodynamic diameter equal to or less than 2.5 microns (PM2.5), and PM with an aerodynamic diameter equal to or less than 10 microns (PM10). Two temporal profiles were included in this analysis: summer weekday and annual. This study was divided into three subtasks: project data, summary of proposed methodology, and provisional activity and emissions estimates.

Subtask 2.1: Project Data

TTI investigated the availability of data from several data sources, including industry sources and the organizations operating the facilities themselves, as well as other organizations that had contacts or possible data related to the intermodal facilities (i.e., TTI, TCEQ, the Houston-Galveston Area Council [H-GAC], and the North Central Texas Council of Governments [NCTCOG]). Since the collection of new field data or instrumented vehicle data was not required for this study, only existing data was used in this subtask for the study.

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One of the primary data sources discovered as part of this subtask was Global Positioning Satellite (GPS) data collected as part of the H-GAC drayage loan program. This data was used to create a much clearer picture of the travel patterns near and within the specified Port of Houston facilities.

Subtask 2.2: Summary of Proposed Methodology

Based on the availability and viability of the existing data collected as part of Subtask 2.1, TTI developed and proposed methods for estimating the truck activity at these facilities and the emissions estimates resulting from this activity. TTI’s statewide virtual link method for developing emissions inventories served as the basis for this proposed methodology, with suitable adaptations to reflect the concepts of this study (i.e., only trucks included in the activity and emissions estimates, activity occurring within the facility not included in typical emissions inventory analyses).

Subtask 2.3: Provisional Emissions Inventory Estimates

TTI developed provisional summer weekday and annual activity and emissions estimates for 2011, 2014, and 2017 based on the data used in Subtask 2.1 and the TCEQ approved methodology developed in Subtask 2.2. Since EPA does not currently have any guidance on the development of emissions estimates for on-road vehicle types at intermodal facilities (“off-model” on-road activity), these emissions estimates are considered provisional. For each analysis year, the provisional emissions were estimated using three basic steps based on an adaptation of TTI’s statewide virtual link method: activity development, emission rate development, and emissions calculations. The truck activity was developed by applying daily truck trips to hourly vehicle miles traveled (VMT) (distance) and vehicle hours traveled (VHT) (operation time) distributions developed using the GPS data. An hourly speed was also calculated (VMT divided by VHT) as part of the truck activity development. TTI’s statewide virtual link method was used as the basis for developing MOVES2014a-based emissions rates. These hourly emissions rates were then applied to the hourly VMT and speed estimates to calculate the provisional emissions.

Acknowledgments

Dennis Perkinson, Ph.D., L.D. White, Michael Martin, and Martin Boardman, all of TTI, contributed to the development of the truck activity and MOVES2014a-based emissions estimates. Dr. Perkinson contributed to each subtask in this study, primarily in the project data collection and methodology development. Mr. White also contributed in all facets of this study, including the data collection, methodology development, and provisional emissions estimates. Mr. Martin processed the large collection of geographically diverse GPS data to produce only that data related directly to the facilities of interest in this study. Mr. Boardman produced MOVES model and MOVES output post-processor set-ups, and the MOVES-based emissions factors with adjustments for Texas low-emissions diesel (TxLED) fuel. Gary Lobaugh, of TTI, was responsible for editing, design, and production of this Technical Report. Dr. Perkinson was the principle investigator for this project. This work was performed by TTI under contract to TCEQ. Mary McGarry-Barber was the TCEQ project technical manager.

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SUMMARY OF RESULTS

Table 1 and Table 2 summarize the summer weekday and annual truck activity and emissions estimates for each facility, respectively.

Table 1. Summer Weekday VMT and Emissions (Pounds/Day).

Year Data Barbours


2011

VMT 4,590.19 5,953.20 3,512.85 5,417.70

Speed 5.87 4.35 5.87 4.35

VOC 30.81 52.32 21.29 45.05

CO 100.99 164.41 68.52 141.15

NOx 226.72 377.33 170.99 350.73

PM2.5 - Total Exhuast 17.10 28.64 11.68 24.56

PM2.5 - Brakewear 2.08 3.01 1.59 2.73

PM2.5 - Tirewear 0.08 0.10 0.06 0.10

PM10 - Total Exhaust 14.72 12.34 10.06 10.58

PM10 - Brakewear 13.33 6.87 10.18 6.25

PM10 - Tirewear 0.52 0.70 0.40 0.63

2014

VMT 5,169.03 6,702.86 3,955.44 6,100.29 Speed 5.87 4.35 5.87 4.35 VOC 25.44 43.12 15.25 34.56 CO 80.94 132.39 49.10 108.11 NOx 186.64 310.22 124.76 270.08 PM2.5 - Total Exhuast 13.44 22.52 7.85 17.86 PM2.5 - Brakewear 2.33 3.36 1.78 3.06 PM2.5 - Tirewear 0.09 0.12 0.07 0.11 PM10 - Total Exhaust 11.57 9.71 6.76 7.70 PM10 - Brakewear 14.93 7.70 11.42 7.01 PM10 - Tirewear 0.58 0.78 0.45 0.71

2017

VMT 5,747.86 7,455.67 4,399.19 6,784.66

Speed 5.87 4.35 5.87 4.35

VOC 15.44 26.12 9.33 21.47

CO 52.01 85.41 32.20 70.90

NOx 135.52 225.01 87.90 191.97

PM2.5 - Total Exhuast 7.61 12.74 4.45 10.29

PM2.5 - Brakewear 2.59 3.75 1.98 3.41

PM2.5 - Tirewear 0.10 0.13 0.07 0.12

PM10 - Total Exhaust 6.55 5.49 3.83 4.44

PM10 - Brakewear 16.62 8.57 12.71 7.79

PM10 - Tirewear 0.65 0.87 0.50 0.79

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Table 2. Annual VMT and Emissions (Tons/Year).

Year Data Barbours


2011

VMT 285,203.70 499,447.75 218,266.35 454,523.55

Speed 5.40 9.07 3.73 7.81

VOC 18.43 30.01 12.50 25.76

CO 45.93 76.43 34.19 70.13

NOx 3.12 5.23 2.13 4.48

PM2.5 - Total Exhuast 0.38 0.55 0.29 0.50

PM2.5 - Brakewear 0.01 0.02 0.01 0.02

PM2.5 - Tirewear 2.69 2.25 1.84 1.93

PM10 - Total Exhaust 2.44 1.26 1.86 1.14

PM10 - Brakewear 0.10 0.13 0.07 0.12

2014

VMT 321,170.80 562,340.90 245,765.45 511,792.05 Speed 4.47 7.49 2.68 6.01 VOC 14.77 24.16 8.96 19.73 CO 37.81 62.84 24.95 54.00 NOx 2.45 4.11 1.43 3.26 PM2.5 - Total Exhuast 0.43 0.62 0.33 0.56 PM2.5 - Brakewear 0.02 0.02 0.01 0.02 PM2.5 - Tirewear 2.11 1.77 1.23 1.41 PM10 - Total Exhaust 2.73 1.41 2.09 1.28 PM10 - Brakewear 0.11 0.14 0.08 0.13

2017

VMT 357,134.25 625,500.50 273,337.55 569,206.55

Speed 2.72 4.57 1.65 3.76

VOC 9.49 15.59 5.88 12.94

CO 27.45 45.58 17.58 38.39

NOx 1.39 2.33 0.81 1.88

PM2.5 - Total Exhuast 0.48 0.69 0.36 0.62

PM2.5 - Brakewear 0.02 0.02 0.01 0.02

PM2.5 - Tirewear 1.20 1.00 0.70 0.81

PM10 - Total Exhaust 3.04 1.57 2.33 1.43

PM10 - Brakewear 0.12 0.16 0.09 0.15

More detailed emissions estimates (e.g., pollutant and emissions process) are included as part of Appendix B, as well as in the electronic data submittal as described in Appendix A.

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SUBTASK 2.1: PROJECT DATA

Vehicle activity is a key component of any emissions estimate. Since truck activity at intermodal facilities is not something that is typically modeled, the availability of data to estimate truck activity at these facilities was not directly available from one distinct source (i.e., a TDM). To estimate this truck activity, TTI explored the availability of data from several different sources, including industry sources and the organizations operating the facilities. TTI additionally included other organizations with contacts to possible data sources relating to these facilities including TCEQ, H-GAC, and NCTCOG. The main data sources used in this analysis are:

Digital mapping applications – used to assess the geography of the facilities;

Port of Houston Authority – provided recent truck activity data;

H-GAC – provided access to the GPS data collected as part of the H-GAC drayage loan program; and

TTI’s statewide virtual link methodology as last described in Production of Statewide Non-Link On-Road Emissions Inventories with MOVES2014a for 2020, 2023, and 2026, TTI, November 2016.

The primary data source used to obtain a clearer picture of the truck activity and patterns was the GPS data from a H-GAC drayage loan program. This GPS data was accessed through a website provided by H-GAC. Daily location reports were created and downloaded for the summer period (June 1, 2016 through August 31, 2016). These location reports included the record time, record mileage, record location (latitude and longitude) typically for each five-minute increment while the truck was in use. Other data was included but not explicitly necessary for this study. The full description of the project data, as detailed in the final deliverable for Subtask 2.1, is included in Appendix C (Subtask 2.1 Project Data).

SUBTASK 2.2: SUMMARY OF PROPOSED METHODOLOGY

TTI developed a methodology for estimating truck activity and emissions at intermodal facilities based on an adaptation of TTI’s hourly, statewide, Highway Performance Monitoring System (HPMS) virtual link method. The main components of the methodology include:

VMT mix - the activity isolated within or near these intermodal facilities closely matches the MOVES short-haul drive cycle; thus, the only vehicle category included will be SUT 61 (combination short-haul truck);

VMT – activity profiles (VMT and VHT per truck trip) developed using the GPS data from H-GAC’s drayage loan program, with the daily number of truck trips applied to the activity profiles to estimate the total hourly VMT and VHT;

Speeds – aggregate hourly speeds were calculated using the hourly VMT and VHT estimates;

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Off-network activity and emissions will not be included since the focus of this study is on the activity within or near the facility, which assumes the truck to always be operating in some fashion, whether it be idling or moving; and

MOVES 2014a-based emissions rates developed based on TTI’s statewide virtual link method that relies on county groupings (based on intersections of input data sets).

As outlined in the proposed method, the detailed GPS activity data was not available for the DFW facilities. Therefore, the activity profiles based on the H-GAC GPS data were applied to the DFW facilities based on the assumption that the operations are sufficiently standard across the industry; thus making the Houston patterns and operating procedures generally applicable. The full description of the proposed method, as detailed in the final deliverable for Subtask 2.2, is included in Appendix D (Subtask 2.2 Summary of Proposed Method).

SUBTASK 2.3: PROVISIONAL EMISSIONS INVENTORY ESTIMATES

TTI estimated the provisional (the U.S. Environmental Protection Agency [EPA] has yet to define any guidance on estimating the emissions for on-road vehicle while internal to intermodal facilities) 2011, 2014, and 2017 summer weekday truck activity and emissions at these four intermodal facilities based on the proposed methodology developed under Subtask 2.2 and the viable data collected under Subtask 2. Annual activity and emissions were calculated as well. As with an emissions inventory, three critical components were developed to estimate the emissions: activity development, emissions rate development, and emissions estimation.

Activity Estimation

To estimate the hourly VMT and speeds associated with the truck activity at these facilities, the truck average trip length and trip time were based on the GPS data from the H-GAC drayage loan program and multiplied by the number of truck trips per day to estimate the daily VMT and operating time for all trucks visiting the facility. Hourly VMT and operating time profiles, also based on the H-GAC GPS data, were used to distribute the daily VMT and operating time to each hour of the day and hourly speeds were calculated using the hourly VMT and operating time.

GPS Data Preparation

The initial GPS data sets downloaded from the Ituran website consisted of 194 files spanning the summer weekday period from June 1, 2016 to August 31, 2016. Each file consisted of the date, time, vehicle mileage, location (latitude and longitude) for records per trip and vehicle. Prior to calculating the average trip length, average trip time, or the hourly profiles, the GPS data from H-GAC’s drayage loan program was processed to include only those trips associated with either the Barbours Cut or Bayport facility. Since each file contained multiple vehicles and multiple trips throughout Harris County, each trip in these files was assigned a trip number based on significant changes in date and/or time and, using GIS software, only those trips within the borders of each facility were retained for use in this study. Figure 1 and Figure 2, respectively, illustrate the Barbours Cut and Bayport areas included in this study.

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Figure 1. Barbours Cut Facility.

8

Figure 2. Bayport Facility.

GPS-Based Truck Average Trip Length and Trip Time

The trip distance for each trip in the Barbours Cut and Bayport facility GPS data were calculated by taking the difference between the beginning vehicle mileage and the ending vehicle mileage and averaged to estimate the average trip distance for a truck entering the respective facility. The trip operation time for each trip was calculated using the start time of the GPS data for the trip and the time of the last GPS data record for the trip and averaged to estimate the average trip operation time for a truck entering the facility. Estimating the average trip distance and trip time separately accounts for the idle times that exist from the truck queueing that occurs entering and exiting the facility. Table 3 shows the average trip distance and trip operation time for both the Barbours Cut and Bayport facilities.

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Table 3. GPS-Based Average Truck Trip Length and Operation Time.

Facility Number of

Trips Average Trip

Distance (miles) Average Trip Time

(minutes) Barbours Cut

1,367 4.048 41.343

Bayport 964 3.150 43.440

Summer Weekday Daily Facility VMT and Operation Time

The GPS-based average truck trip length and operation time, which was assumed to be representative of the typical truck patterns at these facilities, was used to estimate the daily VMT and operation time of trucks within the designated borders of the facilities. The Port of Houston Authority provided recent truck activity data (visits, transactions, and turn times for February 2017 and the first week of March 2017) and based on the information provided, there was no basis for changes due to seasonal patterns. Thus, the February 2017 monthly truck visits were used to expand the average truck trip length and average trip operation time to represent the 2017 daily activity for the entire facility. Table 4 shows the daily truck VMT and operational time for the Barbours Cut and Bayport facilities.

Table 4. 2017 Port of Houston Area Daily Truck VMT and Operational Time by Facility.

Facility Feb. 2017

Truck Visits

2017 Truck

Visits/Day

Average Trip

Distance

Average Trip Time

(mins) Daily VMT

Daily Operational

Time (minutes) Barbours Cut

39,760 1,420 4.048 41.343 5,747.862 58,707.202

Bayport 66,280 2,367 3.150 43.440 7,455.671 102,822.007

For the historical analysis years, direct historical truck activity is not available. Historical cargo volumes were also not available within the scope of this study. On-going substantial improvements to the facilities during the analysis period make the usual methods of estimating historical activity inapplicable. Therefore, the Port of Houston Authority expected growth rate of 3.36 percent per year (taken from Port of Houston Authority published reports) was used to back-cast the number of truck visits per day and calculate the historical analysis year daily VMT and operational time. Table 5 shows the 2011 and 2014 Port of Houston area daily truck VMT and operational time by facility.

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Table 5. 2011 and 2014 Port of Houston Area Daily Truck VMT and Operational Time by

Facility.

Year Facility Truck

Visits/Day

Average Trip

Distance

Average Trip Time

(mins) Daily VMT

Total Operational

Time (minutes)

2011 Barbours Cut 1,134 4.048 41.343 4,590.194 46,883.075

Bayport 1,890 3.150 43.440 5,953.198 82,101.222

2014 Barbours Cut 1,277 4.048 41.343 5,169.028 52,795.139

Bayport 2,128 3.150 43.440 6,702.860 92,439.894

For the DFW area facilities, the operations were assumed to be sufficiently standard across the industry; thus, making the Houston area patterns and operations applicable to the DFW facilities. Similarly, the rail yard physical design was considered standard across the industry for facilities of comparable size; thus, making the 230-acre Barbours Cut facility equivalent to the approximately 200-acre BNSF Alliance and the 376-acre Bayport facility equivalent to the approximately 360-acre UP Dallas Intermodal Terminal (both DFW facilities were estimated from published sources and digital maps). This is especially key in terms of truck operations (visits, average trip length, average trip operational time) per acre. For the DFW facilities, the truck visits per day, average trip distance, and average trip time (shown previously in Table 4) were scaled based on the number of acres in the facility compared to the equivalent facility in the Port of Houston area, and the daily VMT and operational time were calculated based on these adjusted truck visits/day, average trip distance, and average trip time. Table 6 shows the daily truck VMT and operational time for the BNSF Alliance and UP Dallas Intermodal facilities.

Table 6. DFW Areas Daily Truck VMT and Operational Time by Facility.

Year Facility Truck

Visits/Day

Average Trip

Distance

Average Trip Time (mins)

Daily VMT

Total Operational Time (mins)

2011 BNSF Alliance 998 3.520 35.950 3,512.847 35,879.246 UP Dallas Intermodal

1,796 3.016 41.591 5,417.698 74,716.434

2014 BNSF Alliance 1,124 3.520 35.950 3,955.438 40,399.746 UP Dallas Intermodal

2,023 3.016 41.591 6,100.285 84,130.112

2017 BNSF Alliance 1,250 3.520 35.950 4,399.191 44,932.111 UP Dallas Intermodal

2,250 3.016 41.591 6,784.664 93,568.497

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Summer Weekday Hourly VMT, Operating Times, and Speeds

Along with the average trip distance and trip time, the GPS data were also used to calculate hourly distance and operating time profiles. Instead of aggregating the distance traveled and time operating by trip, these data were aggregated by hour and converted to an hourly distribution. One set of hourly distributions (one for distance and one for operational time) were developed for use with both facilities covered by the GPS data. As was the case with the average trip distance and average trip time, these hourly distributions were assumed representative of the typical truck patterns. While developing these distributions, it was noted that there were hours where operational time did exist when the vehicle did not move. This is a direct indication of vehicle idling and was maintained in the hourly distributions. Table 7 shows the hourly VMT and operational time distributions.

Table 7. Hourly VMT and Operational Time Distributions.

Time Hourly VMT Distribution

Hourly Operational

Time Distribution

12 a.m. to 1 a.m. 0.000000 0.000000

1 a.m. to 2 a.m. 0.000000 0.000134 2 a.m. to 3 a.m. 0.000229 0.000103 3 a.m. to 4 a.m. 0.000000 0.000072 4 a.m. to 5 a.m. 0.000000 0.000000 5 a.m. to 6 a.m. 0.000190 0.000144 6 a.m. to 7 a.m. 0.005582 0.014315 7 a.m. to 8 a.m. 0.070871 0.077052 8 a.m. to 9 a.m. 0.107505 0.108507 9 a.m. to 10 a.m. 0.107910 0.098468 10 a.m. to 11 a.m. 0.117671 0.118990 11 a.m. to 12 p.m. 0.100545 0.105188 12 p.m. to 1 p.m. 0.116416 0.122504 1 p.m. to 2 p.m. 0.100107 0.108477 2 p.m. to 3 p.m. 0.094713 0.096598 3 p.m. to 4 p.m. 0.091690 0.079282 4 p.m. to 5 p.m. 0.054568 0.045000 5 p.m. to 6 p.m. 0.027274 0.021108 6 p.m. to 7 p.m. 0.004378 0.003884 7 p.m. to 8 p.m. 0.000351 0.000174 8 p.m. to 9 p.m. 0.000000 0.000000 9 p.m. to 10 p.m. 0.000000 0.000000 10 p.m. to 11 p.m. 0.000000 0.000000 11 p.m. to 12 p.m. 0.000000 0.000000

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These distributions were applied to the daily VMT and operational times for each analysis year to distribute these values to each hour of the day. An hourly speed was also calculated for those hours where the VMT was greater than 0 by dividing the hourly VMT by the hourly operational time. These hourly distributions were applied to all analysis years and assumed applicable to the DFW facilities based on the same assumptions applied during the daily VMT and operational time calculation process. Appendix E includes summaries of the summer weekday hourly VMT, operational times, and speeds by facility and analysis year.

Emissions Rates

TTI developed summer and winter (for use in estimating annual emissions) weekday emissions rates for combination short-haul trucks (source type ID 61) using MOVES2014a. The emissions rates were developed based on TTI’s hourly, statewide virtual link, MOVES rates-per-activity method used in developing on-road mobile emissions inventories. The following MOVES pollutants were included in the emission rates:

Gaseous: VOC, CO, nitrogen oxide (NO), nitrogen dioxide (NO2), Nitrous Acid (HONO), NOx (NOx = NO + NO2 + HONO), carbon dioxide (CO2), SO2, and ammonia (NH3);

Primary PM2.5: sulfate (SO4), organic carbon (OC), elemental carbon (EC), total exhaust, non-EC PM (nonECPM), the aerosols Nitrate (NO3) and Ammonium (NH4), and brake wear (Brakewear) and tire wear (Tirewear); and,

Primary PM10: total exhaust, Brakewear, and Tirewear.

As part of the control strategies modeled in the emissions rates (and consequently in the emissions), TTI post-processed the emissions rates to incorporate the TxLED effects on diesel NOx emissions. Table 8 shows a summary of the emissions controls modeled in this analysis.

13

Table 8. Emissions Control Strategies and Approaches.

Strategy Approach

Federal Motor Vehicle Control Program Standards

MOVES defaults.

Federal Heavy-Duty Diesel Engines Rebuild and 2004 Pull-Ahead Programs (to Mitigate NOx Off-Cycle Effects)

MOVES defaults.

Reformulated Gasoline (RFG) Properties

Local inputs to MOVES – TTI will use RFG fuel formulations developed using summer and winter EPA RFG compliance surveys (Dallas and Houston) sample data from 2011, 2014, and 2015 (latest readily available for both seasons), and MOVES default winter RVP (not available in sample data) and MOVES default sulfur level for 2017 (consistent with Tier 3 gasoline sulfur standard).

Diesel Sulfur

Local input to MOVES – TTI will use 2011 and 2014 conventional diesel formulations (average sulfur level) estimated using east Texas counties diesel sample data from TCEQ 2011 and 2014 surveys, and will use expected future year value reflecting consistency with federal ultra low sulfur diesel standard for the 2017 future year.

TxLED

MOVES output post-processing – TTI will adjust diesel vehicle NOx (and NO, NO2, and HONO) rates for TxLED counties using evaluation-year-specific NOx reduction factors to be provided by TCEQ (using 4.8% reductions for 2002 and later, and 6.2% reductions for 2001 and earlier model years).

I/M Program Not applicable for the vehicle weight category.

The emissions rates were also post-processed to estimate annual emission rates from the summer and winter weekday emissions rates. For this study, the summer and winter weekday emissions rates were weighted equally (50-50 split) to calculate annual emissions rates that will be used to calculate annualization factors in the summer weekday emissions annualization process. Appendix F presents a more detailed description of the emissions rates.

Summer Weekday Emissions Estimation

Summer weekday emissions were calculated based on the hourly VMT, hourly operational time, and hourly speed for each facility and analysis year. The process for calculating the VMT-based emissions (i.e., those hours where the VMT was greater than zero) was identical to the process used for developing emissions inventories. For hourly speeds falling between MOVES speed bin average speeds, emissions factors were interpolated from bounding speeds. For link speeds falling outside of the MOVES speed range (less than 2.5 mph and greater than 75 mph), the emissions factors for the associated bounding speeds were used. The interpolated (or assigned) rates were multiplied by the hourly VMT to produce the hourly emissions estimates. For those

14

hours where the VMT was zero but operational time (idle) did exist, emissions were calculated by converting the 2.5 mph emission rates to mass/hour and multiplying by the operational (idle) time. This was performed for each hour of the day.

Annual Emissions Estimation

The annual emissions were calculated by converting the summer weekday activity and emissions to annual using an activity annualization factor and emissions rate annualization factors. For the purpose of this study, an activity annualization factor of 365 (no basis was found for seasonality and these facilities typically operate seven days a week) was multiplied by the activity and emissions to annualize the activity. Emissions rate annualization factors (calculated as the annual emissions rates divided by the summer weekday emissions rates) were also applied to the summer weekday emissions to convert the summer weekday emissions to annual. Appendix G contains the emissions rate annualization factors.

RECOMMENDATIONS

Confirm assumption that Houston GPS trucks are representative of typical truck patterns.

As noted in the body of this report, the data available for the Houston facilities was extremely detailed. Consequently, the activity estimates for the Dallas area sites was extrapolated from patterns observed in Houston. Any follow-on study should attempt to gather comparable data for the Dallas facilities, if only to confirm the validity of the “typical circulation pattern” assumption used in this study.

Limitations of H-GAC GPS truck activity data.

While the GPS data available for the Houston area was extremely detailed and valuable, there were limitations in the data for the purposes of this study. Specifically, the GPS data was collected at five-minute intervals (or greater). While adequate for flow patterns through the facility, this interval cannot capture all the nuances of movements in confined areas such as intermodal facilities, where very brief periods of idling and small maneuvers are of interest.

Follow-on studies that use existing truck movement data originally collected for another purpose may not be able to specify the collection interval. In those cases, the limitations inherent in longitudinally sparse data should be noted, and to the extent possible, compensated for by complementary means (e.g., supplemental data or confirmation of interpretation).

In the case of a follow-on study that includes site specific truck movement data collection, smaller intervals should be used (ideally sub-minute, but certainly no greater than one minute). Similarly, the locations should be passively collected (i.e., not triggered by truck movement).

REFERENCES

U.S. Environmental Protection Agency (EPA). Procedures for Emission Inventory Preparation, Volume IV: Mobile Sources. EPA420-R-92-009, Emission Planning and

15

Strategies Division, Office of Mobile Sources and Technical Support Division, Office of Air Quality Planning and Standards, December 1992.

EPA. Memorandum: Texas Low Emission Diesel (LED) Fuel Benefits. To Karl Edlund, EPA, Region VI, from Robert Larson, EPA, Office of Transportation and Air Quality (OTAQ), National Vehicle and Fuel Emissions Laboratory at Ann Arbor, Michigan, September 27, 2001.

EPA. Guidance for Quality Assurance Project Plans for Modeling. EPA QA/G-5M, EPA/240/R-02/007, Office of Environmental Information, December 2002.

EPA. Emissions Inventory Guidance for Implementation of Ozone and Particulate Matter National Ambient Air Quality Standards (NAAQS) and Regional Haze Regulations. EPA-454/R-05-001, issued by the Emissions Inventory Group, Emissions, Monitoring and Analysis Division, Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, August 2005.

EPA. Motor Vehicle Emission Simulator (MOVES) 2009, Software Design and Reference Manual. Draft, EPA420-B-09-007, Assessment and Standards Division Office of Transportation and Air Quality, March 2009.

EPA. Emissions Inventory Guidance for Implementation of Ozone [and Particulate Matter] National Ambient Air Quality Standards (NAAQS) and Regional Haze Regulations, Draft, April, 11, 2014.

EPA. Motor Vehicle Emission Simulator (MOVES), User Guide for MOVES2014. EPA420-B-14-055, Assessment and Standards Division, Office of Transportation and Air Quality, July 2014.

EPA. Policy Guidance on the Use of MOVES2014 for State Implementation Plan Development, Transportation Conformity, and Other Purposes. EPA420-B-14-008, Transportation and Climate Division, Office of Transportation and Air Quality, July 2014.

EPA. MOVES2014 Technical Guidance: Using MOVES to Prepare Emission Inventories for State Implementation Plans and Transportation Conformity. EPA420-B-15-007, Transportation and Climate Division, Office of Transportation and Air Quality, January 2015.

Federal Register, Friday, April 30, 2004, Part II, Environmental Protection Agency, 40 CFR Parts 50, 51 and 81, [OAR 2003-0079, FRL-7651-7], RIN 2060-AJ99, Final Rule To Implement the 8-Hour Ozone National Ambient Air, Quality Standard – Phase 1.

Federal Register, Tuesday, October 7, 2014, Environmental Protection Agency, 40 CFR Parts 51, 52, and 80 Final Rule To Implement the 8-Hour Ozone National Ambient Air Quality Standard; Final Rule.

Federal Register, Tuesday, November 29, 2005, Part II, Environmental Protection Agency, Official Release of the MOVES2014 Motor Vehicle Emissions Model for SIPs and Transportation Conformity.

TTI. TTI Emissions Inventory Estimation Utilities Using MOVES: MOVES2014UTL User’s Guide. Texas Transportation Institute, The Texas A&M University System, College Station, TX, November 2014.

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APPENDIX A: ELECTRONIC DATA SUBMITTAL DESCRIPTION

19

Rail Yard Activity Study – Electronic Data Submittal Description (TTI, April 2017)

This appendix describes the rail yard activity study data files TTI submitted to TCEQ, per Grant Activities No. 582-16-63959-05. TTI analyzed available information on truck activity associated with four intermodal facilities — two intermodal facilities in the Port of Houston area (Barbours Cut and Bayport) and two facilities in the DFW area (Union Pacific [UP] Dallas Intermodal Terminal and Burlington Northern Santa Fe [BNSF] Alliance Intermodal Facility. Based on the available information, TTI also produced summer weekday and annual emissions. The following data from this study is included as part of the electronic data submittal:

Tab-delimited summer weekday and annual activity and emissions for diesel combination short-haul trucks (MOVES source type ID 61);

Activity and Emissions summary spreadsheet;

The GPS data used to develop the activity profiles (both the raw and processed data sets);

MOVES2014a inputs and outputs; and

MOVES2014a-based fully adjusted emissions rate databases.

Naming Conventions Where applicable, all of the files included in the electronic data submittal follow the same base name convention with:

FFFF – facility name (“BarboursCut” for Barbours Cut, “Bayport,” “BNSFAlliance” for BNSF Alliance, and “UPDallasIntermodal” for UP Dallas Intermodal);

YYYY – analysis year (2011, 2014, and 2017);

SSSS – season (“SummerWkd” for summer weekday activity and emissions, “Annual” for annual activity and emissions, “s” for summer emissions rates, and “w” for winter emission rates); and

CCCC – for emissions rate county code (48201 for Barbours Cut and Bayport facilities, 48439 for BNSF Alliance, and 48113 for UP Dallas Intermodal).

Activity and Emissions Data Files The tab-delimited summer weekday and annual emissions data files were included in the “Rail Yard Activity Emissions Tab Files” zip file. This zip file contains a total of 24 files (12 for summer weekday and 12 for annual) named using the following naming convention: “FFFF_YYYYSSSS_ActEms.tab.” In addition to the tab-delimited activity and emissions files, a summary of the summer weekday and annual emissions was also included in the spreadsheet “Rail Yard Activity and Emissions Summaries 5April2017.xlsx.”

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GPS Data The raw GPS data from the H-GAC drayage loan program (as downloaded from the Ituran website) were included in the “Rail Yard Raw HGAC GPS Data” zip file. The processed GPS data used to develop the activity profiles for the two Port of Houston area facilities were included in the “Rail Yard Processed HGAC GPS Data” zip file. Emissions Rates – MOVES Input Files The MOVES inputs used (in conjunction with the MOVES default database: movesdb20161117), in the form of the MOVES MRSs and MOVES CDBs used, were provided:

“MVS14A_RYARD_YYYYSSSSWKD_CCCC_ER.MRS” (18 MRS files, i.e., two seasons per county per year) – provided in “railyard_mvs14a_18MRSs.zip;” and

“mvs14a_ryard_YYYYSSS_CCCC_er_cdb_in” (18 MySQL database folders, nine per season) – provided in “railyard_mvs14a_18CDBs.zip”).

Emissions Rates – MOVES Output, Fully Adjusted Rates The following were provided from the MOVES output (“railyard_mvs14a_18MOVESoutput.zip”):

“mvs14a_ryard_YYYYSSSSwkd_CCCC_er_log.txt” (18 log files generated from the MOVES execution, nine per season); and

“mvs14a_ryard_YYYYSSSSwkd_CCCC_er_out” (18 MySQL database folders, nine per season).

The following files/databases were provided from the fully adjusted emission rates used in the emissions analysis and build the annual emission rates (railyard_mvs14a_sumwin_RatesAdjDBs.zip):

“mvs14a_ryard_YYYYSSSSwkd_CCCC_er_outratesadj” (18 MySQL database folders, nine per season) – provided in “railyard_mvs14a_sumwin_RatesAdjDBs.zip;” and

“mvs14a_ryard_YYYYawkd_CCCC_er_outratesadj” (nine MySQL database folders, and three annual databases for each year) – provided in “railyard_mvs14a_ann_RatesAdjDBs.zip.”

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APPENDIX B: SUMMER WEEKDAY VMT AND EMISSIONS SUMMARY

23

2011 Summer Weekday VMT and Emissions (Pounds) Summary

Data Barbours

Cut Bayport

BNSF Alliance


VMT 4,590.19 5,953.20 3,512.85 5,417.70

VOC 5.87 4.35 5.87 4.35

CO 30.81 52.32 21.29 45.05

NOx 100.99 164.41 68.52 141.15

SO2 226.72 377.33 170.99 350.73

NH3 0.16 0.26 0.12 0.23

PM2.5 – Total Exhaust 0.68 1.17 0.52 1.07

Sulfate Particulate (SO4) 17.10 28.64 11.68 24.56

Organic Carbon 0.32 0.55 0.25 0.51

Elemental Carbon 8.45 14.92 5.76 12.78

Composite Non-EC PM 5.13 7.54 3.49 6.46

NO3 11.97 21.10 8.19 18.10

NH4 0.10 0.18 0.07 0.16

PM2.5 – Brakewear 0.21 0.37 0.14 0.31

PM2.5 – Tirewear 2.08 3.01 1.59 2.73

PM10 – Total Exhaust 0.08 0.10 0.06 0.10

PM10 – Brakewear 14.72 12.34 10.06 10.58

PM10 – Tirewear 13.33 6.87 10.18 6.25

VMT 0.52 0.70 0.40 0.63

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Data Barbours

Cut Bayport

BNSF Alliance


VMT 5,169.03 6,702.86 3,955.44 6,100.29

VOC 5.87 4.35 5.87 4.35

CO 25.44 43.12 15.25 34.56

NOx 80.94 132.39 49.10 108.11

SO2 186.64 310.22 124.76 270.08

NH3 0.18 0.30 0.14 0.26

PM2.5 – Total Exhaust 0.77 1.32 0.59 1.20


Organic Carbon 0.38 0.65 0.29 0.59



NO3 9.46 16.65 5.54 13.23

NH4 0.08 0.14 0.05 0.11

PM2.5 – Brakewear 0.16 0.28 0.09 0.22

PM2.5 – Tirewear 2.33 3.36 1.78 3.06

PM10 – Total Exhaust 0.09 0.12 0.07 0.11

PM10 – Brakewear 11.57 9.71 6.76 7.70

PM10 – Tirewear 14.93 7.70 11.42 7.01

VMT 0.58 0.78 0.45 0.71

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Data Barbours

Cut Bayport

BNSF Alliance


VMT 5,747.86 7,455.67 4,399.19 6,784.66

VOC 5.87 4.35 5.87 4.35

CO 15.44 26.12 9.33 21.47

NOx 52.01 85.41 32.20 70.90

SO2 135.52 225.01 87.90 191.97

NH3 0.35 0.57 0.26 0.51

PM2.5 – Total Exhaust 0.86 1.47 0.66 1.34

Sulfate Particulate (SO4)

7.61 12.74 4.45 10.29

Organic Carbon 0.57 0.95 0.43 0.84


Composite Non-EC PM

2.15 3.17 1.23 2.54

NO3 5.47 9.57 3.22 7.75

NH4 0.04 0.08 0.02 0.06

PM2.5 – Brakewear 0.08 0.15 0.05 0.12

PM2.5 – Tirewear 2.59 3.75 1.98 3.41

PM10 – Total Exhaust 0.10 0.13 0.07 0.12

PM10 – Brakewear 6.55 5.49 3.83 4.44

PM10 – Tirewear 16.62 8.57 12.71 7.79

VMT 0.65 0.87 0.50 0.79

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2011 Annual VMT and Emissions (Tons) Summary

Data Barbours

Cut Bayport

BNSF Alliance


VMT 285,203.70 499,447.75 218,266.35 454,523.55

VOC 5.40 9.07 3.73 7.81

CO 18.43 30.01 12.50 25.76

NOx 45.93 76.43 34.19 70.13

SO2 0.05 0.08 0.03 0.07

NH3 0.17 0.29 0.13 0.26

PM2.5 – Total Exhaust 3.12 5.23 2.13 4.48


Organic Carbon 1.54 2.72 1.05 2.33



NO3 0.02 0.03 0.01 0.03

NH4 0.04 0.07 0.03 0.06

PM2.5 – Brakewear 0.38 0.55 0.29 0.50

PM2.5 – Tirewear 0.01 0.02 0.01 0.02

PM10 – Total Exhaust 2.69 2.25 1.84 1.93

PM10 – Brakewear 2.44 1.26 1.86 1.14

PM10 – Tirewear 0.10 0.13 0.07 0.12

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Data Barbours

Cut Bayport

BNSF Alliance


VMT 321,170.80 562,340.90 245,765.45 511,792.05

VOC 4.47 7.49 2.68 6.01

CO 14.77 24.16 8.96 19.73

NOx 37.81 62.84 24.95 54.00

SO2 0.05 0.08 0.03 0.07

NH3 0.19 0.32 0.14 0.29

PM2.5 - Total Exhaust 2.45 4.11 1.43 3.26


Organic Carbon 1.20 2.12 0.70 1.68



NO3 0.02 0.03 0.01 0.02

NH4 0.03 0.05 0.02 0.04

PM2.5 - Brakewear 0.43 0.62 0.33 0.56

PM2.5 - Tirewear 0.02 0.02 0.01 0.02

PM10 - Total Exhaust 2.11 1.77 1.23 1.41

PM10 - Brakewear 2.73 1.41 2.09 1.28

PM10 - Tirewear 0.11 0.14 0.08 0.13

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Data Barbours

Cut Bayport

BNSF Alliance


VMT 357,134.25 625,500.50 273,337.55 569,206.55

VOC 2.72 4.57 1.65 3.76

CO 9.49 15.59 5.88 12.94

NOx 27.45 45.58 17.58 38.39

SO2 0.07 0.11 0.05 0.10

NH3 0.22 0.38 0.17 0.34

PM2.5 – Total Exhaust 1.39 2.33 0.81 1.88

Sulfate Particulate (SO4)

0.10 0.17 0.08 0.15

Organic Carbon 0.65 1.14 0.37 0.92


Composite Non-EC PM

1.00 1.75 0.59 1.41

NO3 0.01 0.01 0.00 0.01

NH4 0.02 0.03 0.01 0.02

PM2.5 – Brakewear 0.48 0.69 0.36 0.62

PM2.5 – Tirewear 0.02 0.02 0.01 0.02

PM10 – Total Exhaust 1.20 1.00 0.70 0.81

PM10 – Brakewear 3.04 1.57 2.33 1.43

PM10 – Tirewear 0.12 0.16 0.09 0.15

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APPENDIX C: RAIL YARD ACTIVITY STUDY PROJECT DATA

31

GRANT ACTIVITIES UNDER THE GRANT UMBRELLA CONTRACT BETWEEN THE TEXAS COMMISSION ON ENVIRONMENTAL QUALITY (TCEQ) AND

THE TEXAS A&M TRANSPORTATION INSTITUTE (TTI)

Grant Activities No. 582-16-63959-05 Rail Yard Activity Study

Under this contract, the Texas A&M Transportation Institute (TTI) will obtain and analyze information regarding truck activity associated with two rail yards in the Port of Houston area. The trucks in these two rail yards are a potential source of on-road oxides of nitrogen (NOx) that are not currently included in on-road emissions inventories. The information collected during this study and resulting from this study may assist in determining the significance of the emissions that contribute to the formation of ozone in rail yards, assist in assessing possible control programs, and aid in the assessment of emissions for other rail yards in Texas. TASK 2 – DEVELOP PROVISIONAL ON-ROAD EMISSIONS INVENTORIES FOR TWO TEXAS RAIL YARDS Under this Task, TTI will produce 2011, 2014, and 2017 provisional on-road mobile emissions inventory estimates for the trucks at two rail yards in the Port of Houston area, Barbours Cut and Bayport. As part of Task 2, TTI will determine available data sources, obtain existing data from these sources (where available), and determine the viability of the data for use in on-road emissions assessments. TTI has explored available data sources and determined that the primary data source for this project will be the Global Positioning Satellite (GPS) data collected as part of the Houston-Galveston Area Council (H-GAC) drayage loan program. The data was accessed through the Ituran website using a password and username provided by H-GAC. From this website, location reports for the period of June 1, 2016 through August 31, 2016 (summer) were created for each truck driven in Harris County. Each record in the location report includes the location date and time, vehicle name, heading, distance in miles, the vehicle mileage, location address, latitude, longitude, and a location (other data is included but will not be used in this study). Since not all of the trucks included in the drayage loan program will be operating in these two rail yards, this data will be condensed to include only those trucks operating near or within the two rail yards; thus providing a much clearer picture of the travel patterns near and within these rail yards.

33

APPENDIX D: RAIL YARD ACTIVITY METHOD

35

GRANT ACTIVITIES UNDER THE GRANT UMBRELLA CONTRACT BETWEEN THE TEXAS COMMISSION ON ENVIRONMENTAL QUALITY (TCEQ) AND THE

TEXAS A&M TRANSPORTATION INSTITUTE (TTI)

Grant Activities No. 582-16-63959-05 Rail Yard Activity Study

Travel demand models, which estimate the vehicle activity that occurs on the roadway network links in the modeled area, are used to calculate the on-road activity for developing most emissions inventories. Certain types of intermodal facilities, such as airport cargo terminals, commercial marine ports, and rail yards, may produce significant on-road activity that occurs off the travel model network. Trucks deliver and pick up containers, cargo, and bulk goods at these facilities. The on-road emissions produced during the off-network activity at the terminals and ports are not currently captured in the network-based, on-road emissions inventories used for reporting and state implementation plan development. Some larger intermodal sites may experience hundreds to thousands of truck trips per day. This study will assess the magnitude of the off-network, on-road activity and emissions at two intermodal rail yards in the Port of Houston area and the Dallas-Fort Worth (DFW) area. TASK 2.2 - SUMMARY OF PROPOSED INVENTORY DEVELOPMENT METHODOLOGY Under Task 2, the Texas A&M Transportation Institute (TTI) will produce 2011, 2014, and 2017 provisional emissions inventory estimates for the truck activity at the selected rail yards in the Port of Houston area (Barbours Cut and Bayport) and in the DFW area (Union Pacific [UP] Dallas Intermodal Terminal and Burlington Northern Santa Fe [BNSF] Alliance Intermodal Facility). TTI has explored available data sources and determined that the primary data source for this project will be the Global Positioning Satellite (GPS) data collected as part of the Houston-Galveston Area Council (H-GAC) drayage loan program. The data was accessed through the Ituran website using a password and username provided by H-GAC. From this website, location reports for the period of June 1, 2016 through August 31, 2016 (summer) were created for each truck driven in Harris County. Each record in the report includes the location date and time, vehicle name, heading, distance in miles, the vehicle mileage, location address, latitude, longitude, and a location (other data is included but will not be used in this study). This data provides a much clearer picture of the travel patterns near and within the specified Port of Houston rail yards. As part of Task 2, TTI has developed methods for producing these provisional emissions inventories using currently available data, not limited to the HGAC drayage loan program. A summary of the proposed inventory development methodology is included in the following sections. EMISSIONS INVENTORY DESCRIPTION 1. Methodology: Adaptation of TTI’s hourly statewide, Highway Performance Monitoring System (HPMS) virtual link, MOVES rates-per-activity method.

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2. Facilities:

Port of Houston Area – Barbours Cut, Bayport DFW Area – UP Dallas Intermodal Terminal, BNSF Alliance Intermodal Facility

3. Analysis Years: 2011, 2014, 2017 4. Periods/Day Types:

Summer Weekday

Annual

5. Sources: MOVES Source Use Type (SUT) 61 (Combination Short-Haul Truck) 6. MOVES2014a Pollutants:

Gaseous: Volatile organic compounds (VOC), carbon monoxide (CO), oxides of nitrogen (NOx = NO + NO2 + HONO), sulfur dioxide (SO2), and ammonia (NH3);

Primary PM2.5: sulfate (SO4), organic carbon (OC), elemental carbon (EC), total exhaust, non-EC PM (nonECPM), the aerosols Nitrate (NO3) and Ammonium (NH4), and brake wear (Brakewear) and tire wear (Tirewear); and

Primary PM10: total exhaust, Brakewear, and Tirewear.

7. Emissions Processes: Running Exhaust, Crankcase Running Exhaust, Start Exhaust, Crankcase Start Exhaust, Extended Idle Exhaust, Crankcase Extended Idle Exhaust, Auxiliary Power Exhaust, Evaporative Permeation, Evaporative Fuel Vapor Venting, Evaporative Fuel Leaks, Brakewear, and Tirewear. 8. Emissions Estimation Process Components: Basic components of the inventories are outlined separately.

Vehicle miles traveled (VMT) and average speeds;

VMT mix;

Vehicle population and parked vehicle activity estimates;

Hourly vehicle category pollutant and process mass emissions rates.

9. Emissions Inventory Electronic Data Forms to be Provided:

Tab-delimited, county, year, and day type on-road inventory data files (text files) containing hourly and 24-hour activity and emissions summaries: for roadway-based processes by roadway and vehicle type – VMT, vehicle hours traveled (VHT), average speed (VMT/VHT), and pollutant/process emissions totals; and for parked vehicle-based

37

processes by vehicle type – source hours parked (SHP), source hours idling (SHI), auxiliary power unit (APU) hours, starts, and pollutant/process emissions totals.

Inventory summary compatible with the National Emissions Inventory (NEI) Emissions Inventory System (EIS) Consolidated Emissions Reporting Schema (CERS) Extensible Markup Language (XML) format, and the Texas Air Emissions Repository (TexAER) will not be provided at this time.

DEVELOPMENT OF VMT MIX 10. The VMT mix designates the vehicle categories included in the analysis and specifies the fraction of VMT attributable to each vehicle category. Since these provisional inventories are isolated to the rail yards only and drayage/internal rail yard activity closely matches the MOVES short-haul drive cycle, the only vehicle category included will be SUT 61 (combination short-haul truck). DEVELOPMENT OF VMT AND SPEEDS 11. Background: The basis for TTI’s virtual link method is the HPMS functional class/area type combinations used in the Texas Department of Transportation’s (TxDOT) Roadway Inventory Functional Classification Record [RIFCREC] reports. This virtual link method adjusts annual average daily traffic (AADT) VMT estimates (either historical data from TxDOT’s RIFCREC reports or forecast AADT VMT) to reflect a specific seasonal day type, distributes the VMT to hour of the day, disaggregates the VMT to the virtual link level, and splits the VMT by direction. A speed model is also applied to estimate the hourly virtual link-level operational speeds by estimating delay (as a function of volume-to-capacity) and applying this delay to free-flow speeds. A modified version of this virtual link method will be used to estimate the VMT and speeds within the limits of the rail yards. 12. VMT: Activity profiles will be developed using the data from the H-GAC drayage loan program for activity within the rail yard. Since these profiles will be based on a limited number of trucks, the profiles will be expanded to include the total number of truck trips when estimating VMT. This detailed level of activity data is not readily available for the DFW rail yards included in this analysis. Therefore, the activity profiles will be used for both the Port of Houston area and DFW area rail yards. 13. Speeds: Given that speeds at this type of facility are a function of the type of vehicle and distance of the trip, not the roadway type where any significant form of delay can occur, speeds will be estimated as part of the activity profiles and applied across all truck trips. VEHICLE POPULATION AND PARKED VEHICLE ACTIVITY ESTIMATES 14. These provisional emissions inventories are isolated to the rail yards only; thus all parked vehicle activity (SHP, hoteling activity, and starts) are assumed to occur outside of the area of interest and will not be calculated.

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DEVELOPMENT OF MOVES EMISSIONS FACTORS 15. Using TTI’s statewide virtual link method, TTI will develop emissions rates using MOVES2014a1 and the TTI post-processing utilities for preparing MOVES2014a-based emissions rates. This method develops emissions rates by county groups that are based on the intersections of input data sets aggregated by (or covering) various geographic areas, including TxDOT districts, fuel regions (consistent with MOVES), and vehicle inspection and maintenance (I/M) program areas.

1 EPA’s latest official release of MOVES, downloadable from http://www.epa.gov/otaq/models/moves/index.htm.

39

APPENDIX E: SUMMER WEEKDAY HOURLY VMT, OPERATIONAL TIME, AND SPEED

41

2011 Summer Weekday Hourly VMT, Operational Time, and Speed

Hour

Barbours Cut Bayport

VMT Operational

Time (mins)

Speed (mph)

VMT Operational

Time (mins)

Speed (mph)

1 0.000 0.000 0.000 0.000 0.000 0.000

2 0.000 6.273 0.000 0.000 10.985 0.000

3 1.053 4.827 13.092 1.366 8.454 9.696

4 0.000 3.382 0.000 0.000 5.923 0.000

5 0.000 0.000 0.000 0.000 0.000 0.000

6 0.872 6.735 7.768 1.131 11.795 5.753

7 25.620 671.137 2.290 33.228 1,175.289 1.696

8 325.312 3,612.436 5.403 421.910 6,326.066 4.002

9 493.467 5,087.162 5.820 639.996 8,908.593 4.310

10 495.328 4,616.468 6.438 642.409 8,084.317 4.768

11 540.131 5,578.612 5.809 700.517 9,769.216 4.302

12 461.520 4,931.555 5.615 598.563 8,636.095 4.159

13 534.373 5,743.354 5.583 693.048 10,057.710 4.134

14 459.513 5,085.717 5.421 595.960 8,906.062 4.015

15 434.752 4,528.792 5.760 563.847 7,930.780 4.266

16 420.877 3,716.994 6.794 545.852 6,509.166 5.032

17 250.476 2,109.729 7.123 324.852 3,694.538 5.276

18 125.194 989.606 7.591 162.369 1,732.990 5.622

19 20.096 182.115 6.621 26.063 318.918 4.903

20 1.609 8.181 11.803 2.087 14.326 8.742

21 0.000 0.000 0.000 0.000 0.000 0.000

22 0.000 0.000 0.000 0.000 0.000 0.000

23 0.000 0.000 0.000 0.000 0.000 0.000

24 0.000 0.000 0.000 0.000 0.000 0.000

Total 4,590.194 46,883.075 5.874 5,953.198 82,101.222 4.351

42

2011 Summer Weekday Hourly VMT, Operational Time, and Speed (Continued)

Hour

BNSF Alliance UP Dallas Intermodal

VMT Operational

Time (mins)

Speed (mph)

VMT Operational

Time (mins)

Speed (mph)

1 0.000 0.000 0.000 0.000 0.000 0.000

2 0.000 4.801 0.000 0.000 9.997 0.000

3 0.806 3.694 13.092 1.243 7.693 9.696

4 0.000 2.588 0.000 0.000 5.390 0.000

5 0.000 0.000 0.000 0.000 0.000 0.000

6 0.667 5.155 7.768 1.029 10.734 5.753

7 19.607 513.616 2.290 30.239 1,069.574 1.696

8 248.960 2,764.569 5.403 383.959 5,757.053 4.002

9 377.647 3,893.165 5.820 582.427 8,107.289 4.310

10 379.071 3,532.946 6.438 584.624 7,357.154 4.768

11 413.359 4,269.268 5.809 637.504 8,890.501 4.302

12 353.198 3,774.080 5.615 544.721 7,859.301 4.159

13 408.952 4,395.343 5.583 630.708 9,153.046 4.134

14 351.662 3,892.059 5.421 542.352 8,104.985 4.015

15 332.713 3,465.849 5.760 513.128 7,217.428 4.266

16 322.095 2,844.586 6.794 496.751 5,923.684 5.032

17 191.688 1,614.559 7.123 295.631 3,362.224 5.276

18 95.810 757.338 7.591 147.764 1,577.112 5.622

19 15.379 139.371 6.621 23.719 290.232 4.903

20 1.232 6.261 11.803 1.899 13.037 8.742

21 0.000 0.000 0.000 0.000 0.000 0.000

22 0.000 0.000 0.000 0.000 0.000 0.000

23 0.000 0.000 0.000 0.000 0.000 0.000

24 0.000 0.000 0.000 0.000 0.000 0.000

Total 3,512.847 35,879.246 5.874 5,417.698 74,716.434 4.351

43


Hour


VMT Operational

Time (mins)

Speed (mph)

VMT Operational

Time (mins)

Speed (mph)

1 0.000 0.000 0.000 0.000 0.000 0.000

2 0.000 7.064 0.000 0.000 12.368 0.000

3 1.186 5.436 13.092 1.538 9.518 9.696

4 0.000 3.809 0.000 0.000 6.669 0.000

5 0.000 0.000 0.000 0.000 0.000 0.000

6 0.982 7.585 7.768 1.273 13.280 5.753

7 28.851 755.769 2.290 37.412 1,323.288 1.696

8 366.335 4,067.973 5.403 475.039 7,122.682 4.002

9 555.694 5,728.665 5.820 720.588 10,030.416 4.310

10 557.790 5,198.615 6.438 723.305 9,102.342 4.768

11 608.243 6,282.088 5.809 788.730 10,999.413 4.302

12 519.719 5,553.436 5.615 673.937 9,723.604 4.159

13 601.758 6,467.604 5.583 780.321 11,324.236 4.134

14 517.458 5,727.037 5.421 671.006 10,027.566 4.015

15 489.576 5,099.883 5.760 634.850 8,929.471 4.266

16 473.951 4,185.715 6.794 614.589 7,328.839 5.032

17 282.061 2,375.770 7.123 365.759 4,159.776 5.276

18 140.981 1,114.398 7.591 182.815 1,951.218 5.622

19 22.630 205.080 6.621 29.345 359.078 4.903

20 1.812 9.212 11.803 2.350 16.130 8.742

21 0.000 0.000 0.000 0.000 0.000 0.000

22 0.000 0.000 0.000 0.000 0.000 0.000

23 0.000 0.000 0.000 0.000 0.000 0.000

24 0.000 0.000 0.000 0.000 0.000 0.000

Total 5,169.028 52,795.139 5.874 6,702.860 92,439.894 4.351

44

2014 Summer Weekday Hourly VMT, Operational Time, and Speed (Continued)

Hour


VMT Operational

Time (mins)

Speed (mph)

VMT Operational

Time (mins)

Speed (mph)

1 0.000 0.000 0.000 0.000 0.000 0.000

2 0.000 5.405 0.000 0.000 11.256 0.000

3 0.908 4.160 13.092 1.400 8.663 9.696

4 0.000 2.914 0.000 0.000 6.069 0.000

5 0.000 0.000 0.000 0.000 0.000 0.000

6 0.751 5.804 7.768 1.159 12.086 5.753

7 22.078 578.327 2.290 34.049 1,204.332 1.696

8 280.327 3,112.883 5.403 432.334 6,482.396 4.002

9 425.228 4,383.673 5.820 655.808 9,128.743 4.310

10 426.831 3,978.069 6.438 658.281 8,284.097 4.768

11 465.439 4,807.162 5.809 717.825 10,010.633 4.302

12 397.699 4,249.584 5.615 613.352 8,849.511 4.159

13 460.477 4,949.122 5.583 710.172 10,306.257 4.134

14 395.969 4,382.427 5.421 610.684 9,126.149 4.015

15 374.633 3,902.518 5.760 577.778 8,126.766 4.266

16 362.676 3,202.981 6.794 559.338 6,670.021 5.032

17 215.839 1,817.980 7.123 332.878 3,785.837 5.276

18 107.882 852.757 7.591 166.381 1,775.816 5.622

19 17.317 156.931 6.621 26.707 326.799 4.903

20 1.387 7.049 11.803 2.139 14.680 8.742

21 0.000 0.000 0.000 0.000 0.000 0.000

22 0.000 0.000 0.000 0.000 0.000 0.000

23 0.000 0.000 0.000 0.000 0.000 0.000

24 0.000 0.000 0.000 0.000 0.000 0.000

Total 3,955.438 40,399.746 5.874 6,100.285 84,130.112 4.351

45


Hour


VMT Operational

Time (mins)

Speed (mph)

VMT Operational

Time (mins)

Speed (mph)

1 0.000 0.000 0.000 0.000 0.000 0.000

2 0.000 7.855 0.000 0.000 13.757 0.000

3 1.319 6.045 13.092 1.711 10.587 9.696

4 0.000 4.235 0.000 0.000 7.418 0.000

5 0.000 0.000 0.000 0.000 0.000 0.000

6 1.092 8.434 7.768 1.416 14.772 5.753

7 32.082 840.400 2.290 41.614 1,471.909 1.696

8 407.358 4,523.509 5.403 528.392 7,922.645 4.002

9 617.921 6,370.168 5.820 801.518 11,156.952 4.310

10 620.251 5,780.762 6.438 804.541 10,124.644 4.768

11 676.355 6,985.564 5.809 877.314 12,234.780 4.302

12 577.917 6,175.316 5.615 749.629 10,815.681 4.159

13 669.144 7,191.854 5.583 867.961 12,596.084 4.134

14 575.404 6,368.358 5.421 746.368 11,153.782 4.015

15 544.399 5,670.974 5.760 706.151 9,932.358 4.266

16 527.024 4,654.436 6.794 683.614 8,151.955 5.032

17 313.647 2,641.812 7.123 406.838 4,626.969 5.276

18 156.768 1,239.190 7.591 203.348 2,170.364 5.622

19 25.164 228.045 6.621 32.641 399.407 4.903

20 2.015 10.244 11.803 2.614 17.942 8.742

21 0.000 0.000 0.000 0.000 0.000 0.000

22 0.000 0.000 0.000 0.000 0.000 0.000

23 0.000 0.000 0.000 0.000 0.000 0.000

24 0.000 0.000 0.000 0.000 0.000 0.000

Total 5,747.862 58,707.202 5.874 7,455.671 102,822.007 4.351

46


Hour


VMT Operational

Time (mins)

Speed (mph)

VMT Operational

Time (mins)

Speed (mph)

1 0.000 0.000 0.000 0.000 0.000 0.000

2 0.000 6.012 0.000 0.000 12.519 0.000

3 1.010 4.627 13.092 1.557 9.635 9.696

4 0.000 3.241 0.000 0.000 6.750 0.000

5 0.000 0.000 0.000 0.000 0.000 0.000

6 0.836 6.455 7.768 1.289 13.442 5.753

7 24.554 643.208 2.290 37.869 1,339.444 1.696

8 311.776 3,462.111 5.403 480.837 7,209.643 4.002

9 472.933 4,875.468 5.820 729.382 10,152.878 4.310

10 474.716 4,424.361 6.438 732.133 9,213.473 4.768

11 517.656 5,346.467 5.809 798.356 11,133.706 4.302

12 442.316 4,726.336 5.615 682.162 9,842.320 4.159

13 512.137 5,504.353 5.583 789.845 11,462.495 4.134

14 440.392 4,874.083 5.421 679.196 10,149.993 4.015

15 416.662 4,340.334 5.760 642.598 9,038.492 4.266

16 403.364 3,562.317 6.794 622.089 7,418.317 5.032

17 240.053 2,021.936 7.123 370.223 4,210.563 5.276

18 119.985 948.426 7.591 185.046 1,975.041 5.622

19 19.260 174.536 6.621 29.704 363.462 4.903

20 1.542 7.840 11.803 2.379 16.327 8.742

21 0.000 0.000 0.000 0.000 0.000 0.000

22 0.000 0.000 0.000 0.000 0.000 0.000

23 0.000 0.000 0.000 0.000 0.000 0.000

24 0.000 0.000 0.000 0.000 0.000 0.000

Total 4,399.191 44,932.111 5.874 6,784.664 93,568.497 4.351

47

APPENDIX F: RAIL YARD ACTIVITY STUDY RATES PRE-ANALYSIS PLAN

49

GRANT ACTIVITIES UNDER THE GRANT UMBRELLA CONTRACT BETWEEN THE TEXAS COMMISSION ON ENVIRONMENTAL QUALITY (TCEQ) AND THE

TEXAS A&M TRANSPORTATION INSTITUTE (TTI)

Grant Activities No. 582-16-63959-05

Pre-Analysis Plan Rail Yard Activity Study — 2011, 2014, and 2017 Rates

EMISSIONS ANALYSIS SCOPE 1. Methodology: Hourly, statewide, HPMS virtual link, MOVES rates-per-activity method. 2. Counties: Dallas, Tarrant, Harris. 3. Analysis Years: 2011, 2014, 2017. 4. Periods and Day Types:

Summer weekday.

Annual.

5. Sources: Gasoline- and diesel-powered combination short-haul trucks (MOVES source type ID 61). 6. MOVES Pollutants:

Gaseous: Volatile organic compounds (VOC), carbon monoxide (CO), nitrogen oxide (NO), nitrogen dioxide (NO2), Nitrous Acid (HONO), oxides of nitrogen (NOx = NO + NO2 + HONO), carbon dioxide (CO2), sulfur dioxide (SO2), and ammonia (NH3);

Primary PM2.5: sulfate (SO4), organic carbon (OC), elemental carbon (EC), total exhaust, non-EC PM (nonECPM), the aerosols Nitrate (NO3) and Ammonium (NH4), and brake wear (Brakewear) and tire wear (Tirewear);

Primary PM10: total exhaust, Brakewear, and Tirewear; and

7. MOVES Processes: Running Exhaust, Crankcase Running Exhaust, Start Exhaust, Crankcase Start Exhaust, Extended Idle Exhaust, Crankcase Extended Idle Exhaust, Auxiliary Power Exhaust, Evaporative Permeation, Evaporative Fuel Vapor Venting, Evaporative Fuel Leaks, Brakewear, and Tirewear. 8. TTI Utilities: The TTI utilities to be used are: RatesCalc – produces and/or compiles emissions rate tables from MOVES output; RatesADJ – makes adjustments to MOVES or RatesCalc emissions rates output; and MOVESfleetInputBuild – produces

50

sourcetypeagedistribution and avft (alternative vehicle fuels and technologies, i.e., fuel engine fractions) MOVES table inputs, based on vehicle registration data and MOVES default data. DEVELOPMENT OF MOVES EMISSIONS FACTORS 21. Background: TTI will develop summer weekday emission rates (and winter weekday – for use in combination with summer weekday in estimating annual emissions) only for combination short-haul trucks (source type ID 61) using MOVES2014a2 and the TTI post-processing utilities for preparing MOVES2014a-based emissions rates for inventory calculations.3 TTI will run MOVES in rates mode for each county. TTI will use the miles- and starts-based rates directly output by MOVES (with adjustments as appropriate), and will calculate the SHP-based evaporative rates that are not directly available from MOVES (using a combination of MOVES default data and county database input and output from MOVES). (Since hotelling only applies to MOVES source type ID 62, SHI- or APU hours-based rates will not be modeled.) Rates will be adjusted for NOx effects from Texas low-emissions diesel (TxLED) fuel. Table 1 lists the emissions processes with associated activity basis and emissions rate units.

Table 1. On-Road Fleet Emissions Rates by Process and Activity Factor.

Emissions Process Activity1 Emissions Factor Units1

Running Exhaust Crankcase Running Exhaust

VMT mass/mile (mass/mi)

Brake Wear VMT mass/mi

Tire Wear VMT mass/mi

Start Exhaust Crankcase Start Exhaust

starts mass/start

Extended Idle Exhaust Crankcase Extended Idle Exhaust

SHI mass/shi

Auxiliary Power Exhaust APU Hours mass/APU hour

Evaporative Permeation Evaporative Fuel Vapor Venting

Evaporative Fuel Leaks VMT, SHP mass/mi, mass/shp

1 The amount of travel on roads (VMT), SHP, vehicle starts, SHI, and APU hours are the basic activity factors. SHI and APU hours are for combination long-haul trucks only. Evaporative permeation, fuel vapor venting, and fuel leaks occur both during operation and while parked.

22. MOVES Model Inputs: TTI will develop look-up tables of emissions factors by pollutant, speed (where applicable), process, hour, road type (where applicable), and average vehicle category (i.e., gasoline and diesel combination short-haul trucks) for input to the emissions

2 EPA’s latest official release of MOVES, downloadable from http://www.epa.gov/otaq/models/moves/index.htm. 3 TTI Emissions Inventory Estimation Utilities Using MOVES: MOVES2014aUtl User’s Guide, TTI, August 2016.

51

calculations. Aside from the MOVES database, all inputs for each run will be in a MOVES RunSpec and a CDB. TTI will develop summer and winter emissions factors for the MOVES weekday day type. See Attachment 1 for more information on inputs. 23. Emissions Factor Post-Processing: TTI’s RatesAdj utility will be used to incorporate TxLED effects on diesel vehicle NOx emissions, and to combine summer and winter rates into annual average weekday rates. Since the study areas are located in counties within the TxLED region, TTI will adjust on-road mobile source emissions factors for TxLED effects. TTI will apply diesel vehicle-class-specific and analysis year-specific TxLED NOx reduction factors to both summer and winter rates, and will adjust the emissions factors for NOx and its subcomponents of NO, NO2, and HONO. RatesAdj will be run subsequently to calculate annual average weekday rates using an equal split of summer and winter emission rates. 24. Emissions Controls Modeling:

Table 2. Emissions Modeling Strategies and Approaches.

Strategy Approach

Federal Motor Vehicle Control Program Standards

MOVES defaults.

Federal Heavy-Duty Diesel Engines Rebuild and 2004 Pull-Ahead Programs (to Mitigate NOx Off-Cycle Effects)

MOVES defaults.

Reformulated Gasoline (RFG) Properties

Local inputs to MOVES – TTI will use RFG fuel formulations developed using summer and winter EPA RFG compliance surveys (Dallas and Houston) sample data from 2011, 2014, and 2015 (latest readily available for both seasons), and MOVES default winter RVP (not available in sample data) and MOVES default sulfur level for 2017 (consistent with Tier 3 gasoline sulfur standard).

Diesel Sulfur

Local input to MOVES – TTI will use 2011 and 2014 conventional diesel formulations (average sulfur level) estimated using east Texas counties diesel sample data from TCEQ 2011 and 2014 surveys, and will use expected future year value reflecting consistency with federal ultra low sulfur diesel standard for the 2017 future year.

TxLED

MOVES output post-processing – TTI will adjust diesel vehicle NOx (and NO, NO2, and HONO) rates for TxLED counties using evaluation-year-specific NOx reduction factors to be provided by TCEQ (using 4.8% reductions for 2002 and later, and 6.2% reductions for 2001 and earlier model years).

I/M Program Not applicable for the vehicle weight category.

52

Attachment 1 — MOVES2014a-Based Emissions Rates

MOVES RunSpecs (MRS), County Input Databases (CDB), Outputs and Post-Processing Following are the inputs, outputs, and post-processing activities TTI will conduct. MOVES Inputs (MRSs and CDBs) and Output:

18 MRS files – one for each of three counties, three analysis years, and two seasons.

18 CDBs – one for each of three counties, three analysis years, and two seasons.

18 MOVES output databases – one per MRS file.

Post-Processing – RatesCalc and RatesAdj Utility Runs:

Interim Rate Databases (one per MRS): Using the RatesCalc utility, the mass/SHP off-network evaporative process rates will be calculated (using data from the CDB, MOVES default database, and the MOVES rateperprofile and ratepervehicle emissions rate output). Rates directly from the MOVES run, and the calculated SHP-based rates, will be tabulated and placed in a RatesCalc-created output database. Pre-requisite pollutants (that are required to estimate other pollutants needed) will be dropped (i.e., total gaseous hydrocarbons, non-methane hydrocarbons, total energy consumption, water vapor). Three rate tables will be included: ttirateperdistance, ttirateperstart, and ttiratepershp; and will contain, respectively, copies of the MOVES rateperdistance and rateperstart rates, and the SHP-based rates calculated by RatesCalc. A column specifying units (i.e., grams) will be added to each rates table.

Summer and Winter Weekday Rates Databases (one per year, county, and season): Using the RatesAdj utility, emissions rates will be copied from the RatesCalc rate tables. RatesAdj will apply TxLED adjustments to diesel vehicle NOx, NO, NO2, and HONO rates. No unit conversions will be made (mass unit is grams). The set of copied and adjusted rates will be placed in RatesAdj output database tables (ttirateperdistance, ttirateperstart, and ttiratepershp) for use in seasonal weekday emissions calculations. This will be performed for both summer (*swkd*RatesAdj) and winter (*wwkd*RatesAdj) weekday rates.

Annual Average Weekday Rates Databases (one per year and county): RatesAdj will be run to combine the summer and winter weekday rates (equal portions) to produce the annual average weekday rates estimates.

Table 3 describes the MRSs TTI will use to produce the MOVES2014a-based rates for on-road emissions calculations for each county, year, and seasonal day-type scenario. Table 4 describes the CDBs to be built and used for the rates analysis. Unless otherwise stated, the information applies to all counties, years, and seasonal day types.

53

Table 3. MOVES2014a RunSpec Selections by GUI Panel.

Navigation Panel Detail Panel1 Selection

Scale1 Model; Domain/Scale;

Calculation Type On-Road; County; Emissions Rates

Time Spans1 Time Aggregation Level;

Years – Months – Days – Hours Hour;

<Year> - <Month> - Weekday - All

Geographic Bounds1

Region; Selections;

Domain Input Database

Zone and Link; <County>;1

mvs14a_ryard_<Year><Season>_<County>_er_CDB_in 1

On-Road Vehicle

Equipment SUT/Fuel Combinations

SUT Gasoline Diesel Motorcycle - - Passenger Car - - Passenger Truck - - Light Commercial Truck - - Intercity Bus - - Transit Bus - - School Bus - - Refuse Truck - - Single Unit Short-Haul Truck - - Single Unit Long-Haul Truck - - Motor Home - - Combination Short-Haul Truck √ √ Combination Long-Haul Truck - -

Road Type Selected Road Types Off-Network –

Rural Restricted Access – Rural Unrestricted Access – Urban Restricted Access – Urban Unrestricted Access

Pollutants and Processes2

VOC; CO; NOx; NO; NO2; HONO; Atmospheric CO2; SO2; NH3;

PM2.5: OC, EC, SO4, NonECPM, NO3, NH4, Total Exhaust, Brakewear, and Tirewear;

PM10: Total Exhaust, Brakewear, and Tirewear

Running Exhaust, Start Exhaust, Crankcase Running Exhaust, Crankcase Start Exhaust, Evap Permeation,

Fuel Vapor Venting, Fuel Leaks

Manage Input Data Sets

Additional Input Database Selections

None

Strategies Rate Of Progress Not Applicable

General Output Output Database;

Units; Activity

mvs14a_ryard_<Year><Season>_<County>_er_out;1 Pounds, KiloJoules, Miles;

Hotelling Hours, Population, Starts (not adjustable, pre-selected)Output

Emissions Detail

Always; For All Vehicles/Equipment;

On Road

Time: Hour – Location: Link – Pollutant; Fuel Type, Emissions Process;

Source Use Type Advanced

Performance Measures

Aggregation and Data Handling Only the “clear BaseRateOutput after rate calculations” box will

be checked

1 Separate runs will be performed by year (2011, 2014, 2017), season (summer “s,” winter “w”), and county (Dallas “48113,” Harris “48201,” Tarrant “48439”). There will be 18 MRS files “mvs14a_ryard_<Year><Season>_<County>_er.mrs” (named similar to the associated 18 CDBs and 18 output databases).

2 Chained pollutants require other pollutants (not listed in the table) to be selected (e.g., VOC requires Total Gaseous Hydrocarbons and Non-Methane Hydrocarbons).

54

Table 4. MOVES CDB Input Tables.

Input Table Category Notes

year Time Designates analysis year as a base year (base year means that activity inputs will be supplied rather than forecast by the model).

state Geography Identifies the state (Texas) for the analysis.

County1 Geography/ Meteorology

Identifies county of analysis with local altitude and barometric pressure. TTI will use 2014 meteorological data (consistent with data previously provided by TCEQ for the 2014 AERR inventories).

Zonemonthhour1 Meteorology Local, hourly temperature, and relative humidity for the county. TTI will use data provided by TCEQ (as described above for “county”).

roadtype Activity Lists the MOVES road types and associated ramp activity fractions. Road type ramp fractions will be set to 0.

Hpmsvtypeyear2

Activity (Defaults)

TTI will use MOVES default national calendar year annual VMT by HPMS vehicle category.

roadtypedistribution2 TTI will use MOVES default road type VMT fractions.

monthvmtfraction2 TTI will use MOVES default month VMT fractions.

dayvmtfraction2 TTI will use MOVES default day VMT fractions.

hourvmtfraction2 TTI will use MOVES default hour VMT fractions.

avgspeeddistribution2 TTI will use MOVES default average speed distributions.

sourcetypeyear2 Fleet

(Defaults) TTI will use MOVES default national analysis year SUT populations.

sourcetypeage-distribution

Fleet

TTI will estimate SUT age fractions using TxDOT/TxDMV mid-year vehicle registration data and MOVES defaults, as needed — historical data for historical years (2011, 2014), latest available data (2014) for a future year (2017), aggregated to the TxDOT district level associated with each county (i.e., statewide inventory method aggregation).

avft Fleet TTI will estimate SUT fuel fractions using statewide aggregate TxDOT/TxDMV vehicle registration data and defaults, where needed, using data sets consistent with sourcetypeagedistribution tables.

zone Activity Start, hoteling, and SHP zone allocation factors. County = zone, and all factors will be set to 1.0 (required for county scale analyses).

zoneroadtype Activity SHO zone/roadtype allocation factors. County = zone, and all factors are set to 1.0 (required for county scale analyses).

fuelsupply Fuel There will be a single RFG and a single conventional diesel fuel formation (i.e., marketshares = 1.0) for each county modeling scenario.

fuelformulation Fuel

RFG and diesel formulations will be based on local survey data (EPA RFG compliance survey samples and TCEQ diesel survey samples) using latest available formulations for a future year (2017), except for sulfur levels to be set for consistency with pertinent federal standards.

countyyear Stage II Not applicable.

imcoverage I/M Not applicable to the weight class modeled. 1 Meteorological inputs for the summer and winter county level rates will be period hourly average temperatures and relative

humidity, and period average barometric pressure (estimated using aggregate 2014 seasonal period data from weather stations within each county) — June through August for summer and December-January-February for winter.

2 Use of default activity and population inputs for the MOVES rates mode runs is a basic aspect of the rates-per-activity emissions estimation method, which calculates the emissions inventory estimates via post-processing. The actual, local vehicle activity estimates are used externally in the emissions calculations post-processing procedures.

3 For historical years: diesel sulfur will be based on 2011 and 2014 TCEQ diesel fuel surveys (aggregate sample data for east Texas), RFG formulations will be based on 2011 and 2014 local (Houston and Dallas) EPA RFG surveys sample data. Future year (2017) RFG formulation will be based on latest (2015) local EPA RFG surveys. 2017 sulfur levels will be set to expected future year values (i.e., consistent with federal Tier 3 sulfur gasoline and ultra low sulfur diesel standards).

55

APPENDIX G: EMISSIONS RATE ANNUALIZATION FACTORS

57

Barbours Cut and Bayport Emissions Rate Annualization Factors

pollutantID processID 2011 2014 2017

2 1 1.000000002 0.99999996 1

2 15 0.999999957 0.99999998 1

3 1 1.109958644 1.10995842 1.109959

3 15 1.109958813 1.10995871 1.109959

30 1 1 1 1

31 1 0.939635648 0.93957252 0.93941

35 1 1.000000035 0.99999998 1

35 15 0.999999989 0.99999995 1

36 1 0.999999991 0.99999998 1

36 15 1.000000007 0.99999998 1

87 1 1.000000008 0.99999992 1

87 15 1 0.99999997 1

100 1 1.000000015 0.99999998 1

100 15 0.999999974 0.99999999 1

106 9 1 1 1

107 10 1 1 1

110 1 0.999999999 0.99999997 1

110 15 0.99999997 0.99999994 1

111 1 1.000000016 0.99999995 1

111 15 0.999999961 0.99999996 1

112 1 0.999999977 0.99999994 1

112 15 1 1 1

115 1 0.999999974 1 1

115 15 0.999999997 1 1

116 9 1 1 1

117 10 1 1 1

118 1 0.999999987 0.99999999 1

118 15 1 0.99999997 1

58

BNSF Alliance Emissions Rate Annualization Factors


2 1 1 1 1

2 15 1 1 1

3 1 1.095591 1.095592 1.095591

3 15 1.095591 1.095591 1.095591

30 1 1 1 1

31 1 0.944241 0.944084 0.943958

35 1 1 1 1

35 15 1 1 1

36 1 1 1 1

36 15 1 1 1

87 1 1 1 1

87 15 1 1 1

100 1 1 1 1

100 15 1 1 1

106 9 1 1 1

107 10 1 1 1

110 1 1 1 1

110 15 1 1 1

111 1 1 1 1

111 15 1 1 1

112 1 1 1 1

112 15 1 1 1

115 1 1 1 1

115 15 1 1 1

116 9 1 1 1

117 10 1 1 1

118 1 1 1 1

118 15 1 1 1

59

UP Dallas Intermodal Emissions Rate Annualization Factors


2 1 1.000000014 1.00000001 1

2 15 0.999999999 1.00000001 1

3 1 1.095637967 1.09563788 1.095638

3 15 1.095637949 1.09563791 1.095638

30 1 1 1 1

31 1 0.946894162 0.94677028 0.946644

35 1 1 1.00000004 1

35 15 0.999999942 1.00000001 1

36 1 1 0.99999997 1

36 15 1.00000005 1.00000002 1

87 1 0.999999978 1 1

87 15 1.00000001 0.99999995 1

100 1 0.999999976 1.00000003 1

100 15 0.999999906 1.00000004 1

106 9 1 1 1

107 10 1 1 1

110 1 1 1 1

110 15 1.000000023 1.00000005 1

111 1 0.999999994 1.00000001 1

111 15 0.999999977 1.00000001 1

112 1 0.99999999 1.00000003 1

112 15 1 1.00000002 1

115 1 1.000000013 1 1

115 15 1 1 1

116 9 1 1 1

117 10 1 1 1

118 1 1.000000008 1.00000001 1

118 15 0.999999991 1.00000004 1

rail yard activity study: development of truck activity

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