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Case Studies of Truck Activity Data for Emissions Modeling (2019)

Chapter: Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts

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Suggested Citation:"Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts." National Academies of Sciences, Engineering, and Medicine. 2019. Case Studies of Truck Activity Data for Emissions Modeling. Washington, DC: The National Academies Press. doi: 10.17226/25485.
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Suggested Citation:"Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts." National Academies of Sciences, Engineering, and Medicine. 2019. Case Studies of Truck Activity Data for Emissions Modeling. Washington, DC: The National Academies Press. doi: 10.17226/25485.
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Suggested Citation:"Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts." National Academies of Sciences, Engineering, and Medicine. 2019. Case Studies of Truck Activity Data for Emissions Modeling. Washington, DC: The National Academies Press. doi: 10.17226/25485.
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Suggested Citation:"Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts." National Academies of Sciences, Engineering, and Medicine. 2019. Case Studies of Truck Activity Data for Emissions Modeling. Washington, DC: The National Academies Press. doi: 10.17226/25485.
×
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Suggested Citation:"Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts." National Academies of Sciences, Engineering, and Medicine. 2019. Case Studies of Truck Activity Data for Emissions Modeling. Washington, DC: The National Academies Press. doi: 10.17226/25485.
×
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Suggested Citation:"Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts." National Academies of Sciences, Engineering, and Medicine. 2019. Case Studies of Truck Activity Data for Emissions Modeling. Washington, DC: The National Academies Press. doi: 10.17226/25485.
×
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Suggested Citation:"Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts." National Academies of Sciences, Engineering, and Medicine. 2019. Case Studies of Truck Activity Data for Emissions Modeling. Washington, DC: The National Academies Press. doi: 10.17226/25485.
×
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Suggested Citation:"Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts." National Academies of Sciences, Engineering, and Medicine. 2019. Case Studies of Truck Activity Data for Emissions Modeling. Washington, DC: The National Academies Press. doi: 10.17226/25485.
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Suggested Citation:"Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts." National Academies of Sciences, Engineering, and Medicine. 2019. Case Studies of Truck Activity Data for Emissions Modeling. Washington, DC: The National Academies Press. doi: 10.17226/25485.
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Suggested Citation:"Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts." National Academies of Sciences, Engineering, and Medicine. 2019. Case Studies of Truck Activity Data for Emissions Modeling. Washington, DC: The National Academies Press. doi: 10.17226/25485.
×
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Suggested Citation:"Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts." National Academies of Sciences, Engineering, and Medicine. 2019. Case Studies of Truck Activity Data for Emissions Modeling. Washington, DC: The National Academies Press. doi: 10.17226/25485.
×
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Suggested Citation:"Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts." National Academies of Sciences, Engineering, and Medicine. 2019. Case Studies of Truck Activity Data for Emissions Modeling. Washington, DC: The National Academies Press. doi: 10.17226/25485.
×
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Suggested Citation:"Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts." National Academies of Sciences, Engineering, and Medicine. 2019. Case Studies of Truck Activity Data for Emissions Modeling. Washington, DC: The National Academies Press. doi: 10.17226/25485.
×
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Suggested Citation:"Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts." National Academies of Sciences, Engineering, and Medicine. 2019. Case Studies of Truck Activity Data for Emissions Modeling. Washington, DC: The National Academies Press. doi: 10.17226/25485.
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Suggested Citation:"Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts." National Academies of Sciences, Engineering, and Medicine. 2019. Case Studies of Truck Activity Data for Emissions Modeling. Washington, DC: The National Academies Press. doi: 10.17226/25485.
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Suggested Citation:"Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts." National Academies of Sciences, Engineering, and Medicine. 2019. Case Studies of Truck Activity Data for Emissions Modeling. Washington, DC: The National Academies Press. doi: 10.17226/25485.
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Suggested Citation:"Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts." National Academies of Sciences, Engineering, and Medicine. 2019. Case Studies of Truck Activity Data for Emissions Modeling. Washington, DC: The National Academies Press. doi: 10.17226/25485.
×
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Suggested Citation:"Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts." National Academies of Sciences, Engineering, and Medicine. 2019. Case Studies of Truck Activity Data for Emissions Modeling. Washington, DC: The National Academies Press. doi: 10.17226/25485.
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Suggested Citation:"Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts." National Academies of Sciences, Engineering, and Medicine. 2019. Case Studies of Truck Activity Data for Emissions Modeling. Washington, DC: The National Academies Press. doi: 10.17226/25485.
×
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Suggested Citation:"Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts." National Academies of Sciences, Engineering, and Medicine. 2019. Case Studies of Truck Activity Data for Emissions Modeling. Washington, DC: The National Academies Press. doi: 10.17226/25485.
×
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Suggested Citation:"Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts." National Academies of Sciences, Engineering, and Medicine. 2019. Case Studies of Truck Activity Data for Emissions Modeling. Washington, DC: The National Academies Press. doi: 10.17226/25485.
×
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Suggested Citation:"Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts." National Academies of Sciences, Engineering, and Medicine. 2019. Case Studies of Truck Activity Data for Emissions Modeling. Washington, DC: The National Academies Press. doi: 10.17226/25485.
×
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Suggested Citation:"Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts." National Academies of Sciences, Engineering, and Medicine. 2019. Case Studies of Truck Activity Data for Emissions Modeling. Washington, DC: The National Academies Press. doi: 10.17226/25485.
×
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Suggested Citation:"Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts." National Academies of Sciences, Engineering, and Medicine. 2019. Case Studies of Truck Activity Data for Emissions Modeling. Washington, DC: The National Academies Press. doi: 10.17226/25485.
×
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Suggested Citation:"Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts." National Academies of Sciences, Engineering, and Medicine. 2019. Case Studies of Truck Activity Data for Emissions Modeling. Washington, DC: The National Academies Press. doi: 10.17226/25485.
×
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Suggested Citation:"Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts." National Academies of Sciences, Engineering, and Medicine. 2019. Case Studies of Truck Activity Data for Emissions Modeling. Washington, DC: The National Academies Press. doi: 10.17226/25485.
×
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Suggested Citation:"Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts." National Academies of Sciences, Engineering, and Medicine. 2019. Case Studies of Truck Activity Data for Emissions Modeling. Washington, DC: The National Academies Press. doi: 10.17226/25485.
×
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Suggested Citation:"Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts." National Academies of Sciences, Engineering, and Medicine. 2019. Case Studies of Truck Activity Data for Emissions Modeling. Washington, DC: The National Academies Press. doi: 10.17226/25485.
×
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Suggested Citation:"Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts." National Academies of Sciences, Engineering, and Medicine. 2019. Case Studies of Truck Activity Data for Emissions Modeling. Washington, DC: The National Academies Press. doi: 10.17226/25485.
×
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Suggested Citation:"Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts." National Academies of Sciences, Engineering, and Medicine. 2019. Case Studies of Truck Activity Data for Emissions Modeling. Washington, DC: The National Academies Press. doi: 10.17226/25485.
×
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Suggested Citation:"Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts." National Academies of Sciences, Engineering, and Medicine. 2019. Case Studies of Truck Activity Data for Emissions Modeling. Washington, DC: The National Academies Press. doi: 10.17226/25485.
×
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Suggested Citation:"Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts." National Academies of Sciences, Engineering, and Medicine. 2019. Case Studies of Truck Activity Data for Emissions Modeling. Washington, DC: The National Academies Press. doi: 10.17226/25485.
×
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Suggested Citation:"Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts." National Academies of Sciences, Engineering, and Medicine. 2019. Case Studies of Truck Activity Data for Emissions Modeling. Washington, DC: The National Academies Press. doi: 10.17226/25485.
×
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Suggested Citation:"Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts." National Academies of Sciences, Engineering, and Medicine. 2019. Case Studies of Truck Activity Data for Emissions Modeling. Washington, DC: The National Academies Press. doi: 10.17226/25485.
×
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Suggested Citation:"Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts." National Academies of Sciences, Engineering, and Medicine. 2019. Case Studies of Truck Activity Data for Emissions Modeling. Washington, DC: The National Academies Press. doi: 10.17226/25485.
×
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Suggested Citation:"Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts." National Academies of Sciences, Engineering, and Medicine. 2019. Case Studies of Truck Activity Data for Emissions Modeling. Washington, DC: The National Academies Press. doi: 10.17226/25485.
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A-1 Appendix A. Case Study #1: Representative Operating Mode Distributions for Different Project Contexts A.1 Emissions Model Inputs Supported • Operating mode distribution (project level). A.2 Level of Effort for Local Application • Low—to apply operating mode distributions presented in this case study to local project-level analysis. • Medium—to develop new, custom operating mode distributions from an existing simulation model. • High—to develop a new simulation model and custom operating mode distributions, or to collect field data using instrumented vehicles. A.3 Overview This case study demonstrates how operating mode distributions can be developed for various types of project-specific situations. In this case study, custom operating mode distributions were gathered from existing studies for different project contexts including: • Ports—inside the gate. • Ports—outside the gate. • Border crossings. • Highway on ramps. • Traffic incidents. These operating mode distributions can be used as inputs into MOVES emissions simulations at the project scale of analysis. The case study also presents illustrative emission factors developed using these operating mode distributions, compares emission factors across project contexts and data sources, and compares emission factors and with factors developed using MOVES default distributions and with a single average speed. Operating mode distributions indicate the fraction of time each vehicle spends in a particular “bin” representing different combinations of speed and vehicle-specific power output. There are 24 bins, including braking, idling, two coasting bins, and 20 cruise/acceleration bins. Operating mode distributions are related to drive cycles (second-by-second speed and acceleration) by equations that include two parameters specific to source types: road load coefficients and mass. These parameters may change in future versions of MOVES, in which case the OMDs will not produce the same emissions results. Case Study #7 documents the development of “representative” drive cycles for selected

A-2 situations for which OMDs are presented in this case study. These representative drive cycles will continue to be applicable in future versions of MOVES even if the OMD conversion parameters change. The case study includes a comparison of emissions under the various scenarios, as well as a comparison of selected operating mode distributions. Diagrams of modeled situations are provided at the end. A.4 Data Sources Source Source Agency Description Availability and Cost Advances in Project- Level Analysis FHWA Operating mode distributions developed using microsimulation models set up for different hypothetical freeway and port situations Data published in report (E. H. Pechan and Cambridge Systematics, Inc., 2010) and provided with this case study United States-Mexico Land Ports of Entry Emissions and Border Wait-Time White Paper and Analysis Template FHWA Operating mode distributions developed using a simulation model based on observed conditions at the El Paso U.S.- Mexico border crossing Published report with summary information (Kear, Wilson, and Corbett, 2012); data available upon request; analysis results provided with this case study Data Collection of Drayage Trucks in Houston-Galveston Port Area U.S. Environmental Protection Agency (EPA) Operating mode distributions developed using data collected from instrumented trucks serving the Port of Houston Available upon request; analysis results provided with this case study Collection of Activity Data from On-Road Heavy-Duty Diesel Vehicles California Air Resources Board Data collection of 100 instrumented trucks operating in California Published report (Boriboonsomsin et al., 2017). data available upon request; analysis results provided with this case study Fleet DNA National Renewable Energy Laboratory Drive cycles for different vocations compiled from data from nearly 500 trucks nationwide Publicly available at https://www.nrel.gov/transportation/fl eettest-fleet-dna.html A.5 Data Processing and Analysis Operating mode distributions can be developed from second-by-second vehicle trajectories (speed/ acceleration) by vehicle type, which may be obtained from instrumented vehicles or from simulation model output. NCHRP Web-Only Document 210, Volume 2, Section 4.6, explains how this can be done. A companion tool to that document assists MOVES users in converting vehicle trajectories to operating mode distributions.1 A tool developed by the National Renewable Energy Laboratory (NREL) can be used to convert multiple drive cycles into a single representative drive cycle.2 Table A.1 provides sample operating mode distributions. 1 http://www.trb.org/Publications/Blurbs/172041.aspx. 2 National Renewable Energy Laboratory. DRIVE: Drive-Cycle Rapid Investigation, Visualization, and Evaluation Analysis Tool, https://www.nrel.gov/transportation/drive.html.

A-3 Table A.1 Sample Operating Mode Distributions opModeID opModeName FHWA Advances; Port Gate, 10 Trucks per Hour (Gate Approach); Custom FHWA Advances; Port Gate, 10 Trucks per Hour (Gate Approach); MOVES Default Houston- Galveston Port Drayage; On Port; Custom El Paso; Border Crossing, Uncongested Links (Northbound FAST Trucks); Custom 0 Braking 0.134227753 0.09821 0.0196 0.248414801 1 Idling 0.573750496 0.139079 0.6955 0.122883056 11 Low-Speed Coasting; VSP< 0; 1<=Speed<25 0.011654556 0.162438 0.1669 0.024480295 12 Cruise/Acceleration; 0<=VSP< 3; 1<= Speed<25 0.006316226 0.228359 0.0982 0.033911229 13 Cruise/Acceleration; 3<=VSP< 6; 1<=Speed<25 0.00916975 0.105918 0.0135 0.007464484 14 Cruise/Acceleration; 6<=VSP< 9; 1<=Speed<25 0.011125535 0.0469077 0.0035 0.004454611 15 Cruise/Acceleration; 9<=VSP<12; 1<=Speed<25 0.015101232 0.0113805 0.001 0.004575006 16 Cruise/Acceleration; 12<=VSP; 1<=Speed<25 0.068516612 0.0241977 0.0005 0.007905931 21 Moderate Speed Coasting; VSP< 0; 25<=Speed<50 0.019333422 0.0451641 0.0006 0.014206598 22 Cruise/Acceleration; 0<=VSP< 3; 25<=Speed<50 0.016191334 0.0538018 0.0005 0.266273377 23 Cruise/Acceleration; 3<=VSP< 6; 25<=Speed<50 0 0.0424723 0.0001 0.222369372 24 Cruise/Acceleration; 6<=VSP< 9; 25<=Speed<50 0.003190175 0.0170291 0 0.006461193 25 Cruise/Acceleration; 9<=VSP<12; 25<=Speed<50 0.004552811 0.00958591 0 0.01697568 26 Cruise/Acceleration; 12<=VSP; 25<=Speed<50 0 0 0 0 27 Cruise/Acceleration; 12<=VSP<18; 25<=Speed<50 0.012760699 0.00327227 0 0.015972389 28 Cruise/Acceleration; 18<=VSP<24; 25<=Speed<50 0.017634138 0.00608864 0 0.001645397 29 Cruise/Acceleration; 24<=VSP<30; 25<=Speed<50 0.015053138 0.00304864 0 0.000963159 30 Cruise/Acceleration; 30<=VSP; 25<=Speed<50 0.061639309 0.00304864 0 0.001043422 33 Cruise/Acceleration; VSP< 6; 50<=Speed 0.00219625 0 0 0 35 Cruise/Acceleration; 6<=VSP<12; 50<=Speed 0.009602584 0 0 0 37 Cruise/Acceleration; 12<=VSP<18; 50<=Speed 0.000416807 0 0 0 38 Cruise/Acceleration; 18<=VSP<24; 50<=Speed 0.00030459 0 0 0 39 Cruise/Acceleration; 24<=VSP<30; 50<=Speed 0.000416807 0 0 0 40 Cruise/Acceleration; 30<=VSP; 50<=Speed 0.006845251 0 0 0 501 brakewear;stopped 0 0 0 0 Average Speed 15 15 2.45 30 Note: Operating mode fractions are colored on relative scale within each column. Red represents the higher values in a given column, and green represents the lower values in a given column.

A-4 In this case study, custom operating mode distributions were gathered from existing studies for different scenarios, including port traffic, border crossings, on ramps, and traffic incidents. The Excel file that accompanies this guidebook catalogues these custom operating mode distributions. Some of the studies developed operating mode distributions using observed data, and others developed them using traffic microsimulation models. A number of these custom operating mode distributions were tested in MOVES for the combination short-haul truck source type. Comparison runs using MOVES default operating mode distributions and average speeds were also conducted for many of the scenarios. MOVES2014a runs were conducted in project-level mode using the operating mode distributions from each study. Other than operating mode distributions, inputs were generally held constant between runs for different scenarios. The main inputs and parameters included: • Scale: Project level. • Location: Wayne County, Michigan was used for operating mode distributions that were not tied to a particular location. When operating mode distributions were tied to a particular location (e.g., El Paso or Houston), that location was used. • Timeframe: Weekday; April; 2016. • Age distribution: MOVES defaults.3 • Fuel: MOVES defaults. • Operating mode distribution: Custom inputs from different studies. • Links: Provided with custom operating mode distributions. • Meteorology: MOVES defaults. • Link source type: Combination short-haul truck (id 61). • Fuel types, pollutants, processes: Diesel and gasoline; all applicable pollutants and pollutant processes. For MOVES default comparisons, inputs and parameters were held constant, except for operating mode distributions. Run specs were modified so that MOVES saved the default operating mode distributions to the output databases. 3 It may not be appropriate to use a regional, population-based age distribution for project-scale analysis, since vehicles operating on the road will be more heavily skewed towards newer vehicles which travel more miles per vehicle. Ideally an age distribution representative of the fleet operating on the project facility being evaluated should be used. If a regional, population-based age distribution is used, it should be adjusted for annual mileage accumulation rates by vehicle age. See Section 3.0 of the guidebook for further information on making this adjustment. This case study illustrates relative differences in emission rates by project context but should not be used to apply actual emission rates locally; instead the project sponsor should use a representative operating mode distribution in combination with other locally-appropriate MOVES inputs.

A-5 A.6 Findings from Sample Data A.6.1 Overview The custom scenarios tested, organized by source, were: • FHWA Advances in Project-Level Analysis study: – Actuated signalized arterial; Volume/Capacity (V/C) ratio 0.70.* – Actuated signalized arterial; V/C 1.20.4 – Pretimed signalized arterial; V/C 0.70.* – Freeway to freeway; V/C 1.20.*5 – Incident, 1 lane, 45 minutes; V/C 1.40. – Incident, 2 lanes, 45 minutes; V/C 0.90.* – Incident, 2 lanes, 45 minutes; V/C 1.40.* – Incident, 2 lanes, 90 minutes; V/C 1.40. – Incident, 3 lanes, 45 minutes; V/C 1.40. – On-ramp; V/C 1.20.* – On-ramp with metering; V/C 1.20.* – Port gate, 10 trucks per hour.* – Port gate, 60 trucks per hour.* – On-port property.* • Data Collection of Drayage Trucks in Houston-Galveston Port Area study: – In-port activity.* 4 Results excluded; operating mode distribution and resulting emission rates were unreasonable. 5 A custom operating mode distribution was missing for one of the five links in this scenario, so the emissions produced by the link in the custom and default runs were identical. * MOVES default comparison run also conducted.

A-6 • United States-Mexico Land Ports of Entry Emissions and Border Wait-Time White Paper and Analysis Template study (i.e., El Paso Border Crossing study): – Border crossing, uncongested links.* – Border crossing, creeping queue.* – Border crossing, stop-and-go queue.* • California Air Resources Board instrumented trucks: – On-port operations, Ports of Los Angeles and Long Beach (POLA-POLB). – Operations in the vicinity of warehouses in Southern California. • NREL, Fleet DNA: – POLA-POLB drayage composite. – POLA-POLB drayage metro highway. – POLA-POLB drayage port near dock. – POLA-POLB drayage creep queue. – POLA-POLB drayage local. This case study compares operating mode distributions and also presents sample emissions results using the operating mode distributions from the two FHWA studies and the Houston-Galveston study. [The California Air Resources Board (CARB) and NREL data were added to the library subsequent to conducting the emissions analysis.] For simplification purposes, the emissions results focus predominantly on PM2.5 emissions in grams/mile and grams/hour. Some charts show NOx and CO2 equivalent emissions rates. The Excel data file that accompanies this guidebook presents the complete results of these runs. A.6.2 Summary of Findings Key takeaways from the analysis included: • There were substantial discrepancies between custom and MOVES default operating mode distributions in many cases, suggesting that it can be worthwhile to use custom operating mode distributions for specific situations rather than average speeds. • For the microsimulation-based FHWA Advances study, most custom operating mode distributions produced higher emissions rates than their default counterparts. In particular, custom rates were much higher than the defaults for incidents, signalized arterials, on ramps, and freeway-to-freeway interchanges. Note, however, that simulation model outputs have not been fully validated against real- world driving conditions.

A-7 • For the field data collection and simulation-based El Paso Border crossing study, custom operating mode distributions produced considerably lower emissions rates than the defaults for all scenarios and links. • For the data collection-based Houston-Galveston Port Drayage study, the custom operating mode distribution produced somewhat lower emissions rates than its default counterparts. • On-port operating mode distributions were relatively consistent across multiple sources, although the NREL cycles showed somewhat more activity in higher-speed, higher-power modes. Similarly, on-port emissions rates were relatively consistent between the FHWA Advances (microsimulation) and Houston- Galveston Port Drayage (field data) studies. Custom rates were somewhat lower than default rates for both studies. • The California instrumented truck study includes a small number of vehicles. However, OMDs are generally similar across individual vehicles, and also comparing two port contexts—the Port of Los Angeles and the Port of Long Beach. This suggests there may be transferability to other situations. • While the results presented here focus on PM2.5, the differences in emission rates by scenario tended to be proportional between pollutants. The percentage differences between custom operating mode distribution emission rates and their default counterparts also tended to be proportional between pollutants. A.6.3 Emissions Results in Detail The following tables and charts show select results from the MOVES runs using the custom operating mode distributions and, in cases where default comparisons were done, their default operating mode counterparts. The average speed corresponding to the custom OMD profile is also shown as a black dot. Emission results are shown in both grams per mile and grams per hour. • Figure A.1 and Figure A.2 show emissions of PM2.5 for various port situations. • Figure A.3 through Figure A.8 show PM2.5, NOx, and CO2 emissions for selected port and border crossing situations. • Figure A.9 through Figure A.14 show PM2.5, NOx, and CO2 emissions for various highway scenarios from the FHWA Advances study. • Figure A.15 and Figure A.16 show PM2.5 emissions for incident-specific scenarios from the FHWA Advances study. • Figure A.17 and Figure A.18 show PM2.5 emissions for specific scenarios from the FHWA border crossing study. • Table A.2 shows PM2.5 emission rates (per mile and per hour) for all scenarios modeled. Values are highlighted with colors ranging from green (lower rates) to red (higher rates). For MOVES default values, other inputs and parameters were held constant with the scenarios and run specs were modified so that MOVES saved the default operating mode distributions to the output databases.

A-8 Figure A.1 PM2.5 g/mile Emissions by Scenario Custom versus Default Op Mode Distributions—Ports Figure A.2 PM2.5 g/hour Emissions by Scenario Custom versus Default Op Mode Distributions—Ports 0 5 10 15 20 25 30 35 40 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 Gate approach Intersection approach Gate approach Intersection approach On port Port gate, 10 trucks/hr Port gate, 60 trucks/hr On port FHWA Advances Houston- Galveston Port Drayage Average Speed (mph) Emissions (g/mile) grams/mile - Custom grams/mile - MOVES Default avg speed - Custom 0 5 10 15 20 25 30 35 40 0 10 20 30 40 50 60 Gate approach Intersection approach Gate approach Intersection approach On port Port gate, 10 trucks/hr Port gate, 60 trucks/hr On port FHWA Advances Houston- Galveston Port Drayage Average Speed (mph) Emission Rate (g/hour operating) grams/hour operating - Custom grams/hour operating - MOVES Default avg speed - Custom

G uide to Truck A ctivity D ata for E m issions M odeling A -9 Figure A.3 PM2.5 g/mile Emissions by Scenario, Custom versus Default Op Mode Distributions Select Links for Ports, Border Crossings 0 5 10 15 20 25 30 35 40 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 Southbound Trucks (all) Southbound Trucks (all) Southbound Trucks (all) Gate approach Intersection approach Gate approach Intersection approach Border crossing, Creeping queue Border crossing, Stop & go queue Border crossing, Uncongested links On port Port gate, 10 trucks/hr Port gate, 60 trucks/hr On port El Paso FHWA Advances Houston- Galveston Port Drayage Average Speed (mph)Emissions (g/mile) grams/mile - Custom grams/mile - MOVES Default avg speed - Custom

G uide to Truck A ctivity D ata for E m issions M odeling A -10 Figure A.4 PM2.5 g/hour Emissions by Scenario, Custom versus Default Op Mode Distributions Select Links for Ports, Border Crossings 0 5 10 15 20 25 30 35 40 0 10 20 30 40 50 60 Southbound Trucks (all) Southbound Trucks (all) Southbound Trucks (all) Gate approach Intersection approach Gate approach Intersection approach Border crossing, Creeping queue Border crossing, Stop & go queue Border crossing, Uncongested links On port Port gate, 10 trucks/hr Port gate, 60 trucks/hr On port El Paso FHWA Advances Houston- Galveston Port Drayage Average Speed (mph)Emission Rate (g/hour operating) grams/hour operating - Custom grams/hour operating - MOVES Default avg speed - Custom

G uide to Truck A ctivity D ata for E m issions M odeling A -11 Figure A.5 NOx g/mile Emissions by Scenario, Custom versus Default Op Mode Distributions Select Links for Ports, Border Crossings 0 5 10 15 20 25 30 35 40 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 Southbound Trucks (all) Southbound Trucks (all) Southbound Trucks (all) Gate approach Intersection approach Gate approach Intersection approach Border crossing, Creeping queue Border crossing, Stop & go queue Border crossing, Uncongested links On port Port gate, 10 trucks/hr Port gate, 60 trucks/hr On port El Paso FHWA Advances Houston- Galveston Port Drayage Average Speed (mph)Emissions (g/mile) grams/mile - Custom grams/mile - MOVES Default avg speed - Custom

G uide to Truck A ctivity D ata for E m issions M odeling A -12 Figure A.6 NOx g/hour Emissions by Scenario, Custom versus Default Op Mode Distributions Select Links for Ports, Border Crossings 0 5 10 15 20 25 30 35 40 0 100 200 300 400 500 600 700 800 900 Southbound Trucks (all) Southbound Trucks (all) Southbound Trucks (all) Gate approach Intersection approach Gate approach Intersection approach Border crossing, Creeping queue Border crossing, Stop & go queue Border crossing, Uncongested links On port Port gate, 10 trucks/hr Port gate, 60 trucks/hr On port El Paso FHWA Advances Houston- Galveston Port Drayage Average Speed (mph)Emission Rate (g/hour operating) grams/hour operating - Custom grams/hour operating - MOVES Default avg speed - Custom

G uide to Truck A ctivity D ata for E m issions M odeling A -13 Figure A.7 CO2 g/mile Emissions by Scenario, Custom versus Default Op Mode Distributions Select Links for Ports, Border Crossings 0 5 10 15 20 25 30 35 40 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 9,000 Southbound Trucks (all) Southbound Trucks (all) Southbound Trucks (all) Gate approach Intersection approach Gate approach Intersection approach Border crossing, Creeping queue Border crossing, Stop & go queue Border crossing, Uncongested links On port Port gate, 10 trucks/hr Port gate, 60 trucks/hr On port El Paso FHWA Advances Houston- Galveston Port Drayage Average Speed (mph)Emissions (g/mile) grams/mile - Custom grams/mile - MOVES Default avg speed - Custom

G uide to Truck A ctivity D ata for E m issions M odeling A -14 Figure A.8 CO2 g/hour Emissions by Scenario, Custom versus Default Op Mode Distributions Select Links for Ports, Border Crossings 0 5 10 15 20 25 30 35 40 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000 100,000 Southbound Trucks (all) Southbound Trucks (all) Southbound Trucks (all) Gate approach Intersection approach Gate approach Intersection approach Border crossing, Creeping queue Border crossing, Stop & go queue Border crossing, Uncongested links On port Port gate, 10 trucks/hr Port gate, 60 trucks/hr On port El Paso FHWA Advances Houston- Galveston Port Drayage Average Speed (mph)Emission Rate (g/hour operating) grams/hour operating - Custom grams/hour operating - MOVES Default avg speed - Custom

G uide to Truck A ctivity D ata for E m issions M odeling A -15 Figure A.9 PM2.5 g/mile Emissions by Scenario, Custom versus Default Op Mode Distributions Select Scenarios from FHWA Advances Study 0 10 20 30 40 50 60 70 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 En tir e se gm en t In te rs ec tio n ap pr oa ch o nl y D ow ns tre am fr om m er ge a re a D ow ns tre am fr om m er ge a re a #2 M er ge a re a O n- R am p U ps tre am fr om m er ge a re a D ow ns tre am fr om m er ge a re a M er ge a re a O n- R am p U ps tre am fr om m er ge a re a D ow ns tre am fr om m er ge a re a M er ge a re a O n- R am p U ps tre am fr om m er ge a re a D ow ns tre am fr om m er ge a re a M er ge a re a O n- R am p U ps tre am fr om m er ge a re a Actuated signalized arterial; 0.70 V/C Freeway to Freeway; 1.2 V/C Incident, 2 lanes, 45 minutes; 1.40 V/C On port On ramp with metering; 1.20 V/C On ramp; 1.20 V/C FHWA Advances Average Speed (mph)Emissions (g/mile) grams/mile - Custom grams/mile - MOVES Default avg speed - Custom

G uide to Truck A ctivity D ata for E m issions M odeling A -16 Figure A.10 PM2.5 g/hour Emissions by Scenario, Custom versus Default Op Mode Distributions Select Scenarios from FHWA Advances Study 0 10 20 30 40 50 60 70 0 20 40 60 80 100 120 140 160 En tir e se gm en t In te rs ec tio n ap pr oa ch o nl y D ow ns tre am fr om m er ge a re a D ow ns tre am fr om m er ge a re a #2 M er ge a re a O n- R am p U ps tre am fr om m er ge a re a D ow ns tre am fr om m er ge a re a M er ge a re a O n- R am p U ps tre am fr om m er ge a re a D ow ns tre am fr om m er ge a re a M er ge a re a O n- R am p U ps tre am fr om m er ge a re a D ow ns tre am fr om m er ge a re a M er ge a re a O n- R am p U ps tre am fr om m er ge a re a Actuated signalized arterial; 0.70 V/C Freeway to Freeway; 1.2 V/C Incident, 2 lanes, 45 minutes; 1.40 V/C On port On ramp with metering; 1.20 V/C On ramp; 1.20 V/C FHWA Advances Average Speed (mph)Emission Rate (g/hour operating) grams/hour operating - Custom grams/hour operating - MOVES Default avg speed - Custom

G uide to Truck A ctivity D ata for E m issions M odeling A -17 Figure A.11 NOx g/mile Emissions by Scenario, Custom versus Default Op Mode Distributions Select Scenarios from FHWA Advances Study 0 10 20 30 40 50 60 70 0 10 20 30 40 50 60 70 80 En tir e se gm en t In te rs ec tio n ap pr oa ch o nl y D ow ns tre am fr om m er ge a re a D ow ns tre am fr om m er ge a re a #2 M er ge a re a O n- R am p U ps tre am fr om m er ge a re a D ow ns tre am fr om m er ge a re a M er ge a re a O n- R am p U ps tre am fr om m er ge a re a D ow ns tre am fr om m er ge a re a M er ge a re a O n- R am p U ps tre am fr om m er ge a re a D ow ns tre am fr om m er ge a re a M er ge a re a O n- R am p U ps tre am fr om m er ge a re a Actuated signalized arterial; 0.70 V/C Freeway to Freeway; 1.2 V/C Incident, 2 lanes, 45 minutes; 1.40 V/C On port On ramp with metering; 1.20 V/C On ramp; 1.20 V/C FHWA Advances Average Speed (mph)Emissions (g/mile) grams/mile - Custom grams/mile - MOVES Default avg speed - Custom

G uide to Truck A ctivity D ata for E m issions M odeling A -18 Figure A.12 NOx g/hour Emissions by Scenario, Custom versus Default Op Mode Distributions Select Scenarios from FHWA Advances Study 0 10 20 30 40 50 60 70 0 500 1,000 1,500 2,000 2,500 En tir e se gm en t In te rs ec tio n ap pr oa ch o nl y D ow ns tre am fr om m er ge a re a D ow ns tre am fr om m er ge a re a #2 M er ge a re a O n- R am p U ps tre am fr om m er ge a re a D ow ns tre am fr om m er ge a re a M er ge a re a O n- R am p U ps tre am fr om m er ge a re a D ow ns tre am fr om m er ge a re a M er ge a re a O n- R am p U ps tre am fr om m er ge a re a D ow ns tre am fr om m er ge a re a M er ge a re a O n- R am p U ps tre am fr om m er ge a re a Actuated signalized arterial; 0.70 V/C Freeway to Freeway; 1.2 V/C Incident, 2 lanes, 45 minutes; 1.40 V/C On port On ramp with metering; 1.20 V/C On ramp; 1.20 V/C FHWA Advances Average Speed (mph)Emission Rate (g/hour operating) grams/hour operating - Custom grams/hour operating - MOVES Default avg speed - Custom

G uide to Truck A ctivity D ata for E m issions M odeling A -19 Figure A.13 CO2 Equivalent g/mile Emissions by Scenario, Custom versus Default Op Mode Distributions Select Scenarios from FHWA Advances Study 0 10 20 30 40 50 60 70 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 En tir e se gm en t In te rs ec tio n ap pr oa ch o nl y D ow ns tre am fr om m er ge a re a D ow ns tre am fr om m er ge a re a #2 M er ge a re a O n- R am p U ps tre am fr om m er ge a re a D ow ns tre am fr om m er ge a re a M er ge a re a O n- R am p U ps tre am fr om m er ge a re a D ow ns tre am fr om m er ge a re a M er ge a re a O n- R am p U ps tre am fr om m er ge a re a D ow ns tre am fr om m er ge a re a M er ge a re a O n- R am p U ps tre am fr om m er ge a re a Actuated signalized arterial; 0.70 V/C Freeway to Freeway; 1.2 V/C Incident, 2 lanes, 45 minutes; 1.40 V/C On port On ramp with metering; 1.20 V/C On ramp; 1.20 V/C FHWA Advances Average Speed (mph)Emissions (g/mile) grams/mile - Custom grams/mile - MOVES Default avg speed - Custom

G uide to Truck A ctivity D ata for E m issions M odeling A -20 Figure A.14 CO2 Equivalent g/hour Emissions by Scenario, Custom versus Default Op Mode Distributions Select Scenarios from FHWA Advances Study 0 10 20 30 40 50 60 70 0 50,000 100,000 150,000 200,000 250,000 300,000 En tir e se gm en t In te rs ec tio n ap pr oa ch o nl y D ow ns tre am fr om m er ge a re a D ow ns tre am fr om m er ge a re a #2 M er ge a re a O n- R am p U ps tre am fr om m er ge a re a D ow ns tre am fr om m er ge a re a M er ge a re a O n- R am p U ps tre am fr om m er ge a re a D ow ns tre am fr om m er ge a re a M er ge a re a O n- R am p U ps tre am fr om m er ge a re a D ow ns tre am fr om m er ge a re a M er ge a re a O n- R am p U ps tre am fr om m er ge a re a Actuated signalized arterial; 0.70 V/C Freeway to Freeway; 1.2 V/C Incident, 2 lanes, 45 minutes; 1.40 V/C On port On ramp with metering; 1.20 V/C On ramp; 1.20 V/C FHWA Advances Average Speed (mph)Emission Rate (g/hour operating) grams/hour operating - Custom grams/hour operating - MOVES Default avg speed - Custom

G uide to Truck A ctivity D ata for E m issions M odeling A -21 Figure A.15 PM2.5 g/mile Emissions by Scenario, Custom versus Default Op Mode Distributions Incident Scenarios from FHWA Advances Study 0 5 10 15 20 25 30 35 40 45 50 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 D ow ns tre am fr om m er ge a re a M er ge a re a O n- R am p U ps tre am fr om m er ge a re a D ow ns tre am fr om m er ge a re a M er ge a re a O n- R am p U ps tre am fr om m er ge a re a D ow ns tre am fr om m er ge a re a M er ge a re a O n- R am p U ps tre am fr om m er ge a re a D ow ns tre am fr om m er ge a re a M er ge a re a O n- R am p U ps tre am fr om m er ge a re a D ow ns tre am fr om m er ge a re a M er ge a re a O n- R am p U ps tre am fr om m er ge a re a Incident, 1 lanes, 45 minutes; 1.40 V/C Incident, 2 lanes, 45 minutes; 0.90 V/C Incident, 2 lanes, 45 minutes; 1.40 V/C Incident, 2 lanes, 90 minutes; 1.40 V/C Incident, 3 lanes, 45 minutes; 1.40 V/C FHWA Advances Average Speed (mph)Emissions (g/mile) grams/mile - Custom grams/mile - MOVES Default avg speed - Custom

G uide to Truck A ctivity D ata for E m issions M odeling A -22 Figure A.16 PM2.5 g/hour Emissions by Scenario, Custom versus Default Op Mode Distributions Incident Scenarios from FHWA Advances Study 0 5 10 15 20 25 30 35 40 45 50 0 20 40 60 80 100 120 140 160 D ow ns tre am fr om m er ge a re a M er ge a re a O n- R am p U ps tre am fr om m er ge a re a D ow ns tre am fr om m er ge a re a M er ge a re a O n- R am p U ps tre am fr om m er ge a re a D ow ns tre am fr om m er ge a re a M er ge a re a O n- R am p U ps tre am fr om m er ge a re a D ow ns tre am fr om m er ge a re a M er ge a re a O n- R am p U ps tre am fr om m er ge a re a D ow ns tre am fr om m er ge a re a M er ge a re a O n- R am p U ps tre am fr om m er ge a re a Incident, 1 lanes, 45 minutes; 1.40 V/C Incident, 2 lanes, 45 minutes; 0.90 V/C Incident, 2 lanes, 45 minutes; 1.40 V/C Incident, 2 lanes, 90 minutes; 1.40 V/C Incident, 3 lanes, 45 minutes; 1.40 V/C FHWA Advances Average Speed (mph)Emission Rate (g/hour operating) grams/hour operating - Custom grams/hour operating - MOVES Default avg speed - Custom

G uide to Truck A ctivity D ata for E m issions M odeling A -23 Figure A.17 PM2.5 g/mile Emissions by Scenario, Custom versus Default Op Mode Distributions El Paso Border Crossing Study 0 5 10 15 20 25 30 35 0.0 0.5 1.0 1.5 2.0 2.5 3.0 N or th bo un d FA ST T ru ck s N or th bo un d La de n Tr uc ks N or th bo un d U nl ad en T ru ck s So ut hb ou nd T ru ck s (a ll) N or th bo un d FA ST T ru ck s N or th bo un d La de n Tr uc ks N or th bo un d U nl ad en T ru ck s So ut hb ou nd T ru ck s (a ll) N or th bo un d FA ST T ru ck s N or th bo un d La de n Tr uc ks N or th bo un d U nl ad en T ru ck s So ut hb ou nd T ru ck s (a ll) Border crossing, Creeping queue Border crossing, Stop & go queue Border crossing, Uncongested links El Paso Average Speed (mph)Emissions (g/mile) grams/mile - Custom grams/mile - MOVES Default avg speed - Custom

G uide to Truck A ctivity D ata for E m issions M odeling A -24 Figure A.18 PM2.5 g/hour Emissions by Scenario, Custom versus Default Op Mode Distributions El Paso Border Crossing Study 0 5 10 15 20 25 30 35 0 5 10 15 20 25 30 35 N or th bo un d FA ST T ru ck s N or th bo un d La de n Tr uc ks N or th bo un d U nl ad en T ru ck s So ut hb ou nd T ru ck s (a ll) N or th bo un d FA ST T ru ck s N or th bo un d La de n Tr uc ks N or th bo un d U nl ad en T ru ck s So ut hb ou nd T ru ck s (a ll) N or th bo un d FA ST T ru ck s N or th bo un d La de n Tr uc ks N or th bo un d U nl ad en T ru ck s So ut hb ou nd T ru ck s (a ll) Border crossing, Creeping queue Border crossing, Stop & go queue Border crossing, Uncongested links El Paso Average Speed (mph)Emission Rate (g/hour operating) grams/hour operating - Custom grams/hour operating - MOVES Default avg speed - Custom

Guide to Truck Activity Data for Emissions Modeling A-25 Table A.2 PM2.5 Emissions by Scenario Study, Scenario, and Link Name PM2.5 Emissions, g/mile PM2.5 Emissions, g/hour % Δ from Default Average Speed Custom MOVES Default Custom MOVES Default El Paso; Border crossing, Creeping queue (Northbound FAST Trucks) 1.52 2.42 8.96 14.30 -60% 5.9 El Paso; Border crossing, Creeping queue (Northbound Laden Trucks) 1.54 2.42 9.08 14.30 -57% 5.9 El Paso; Border crossing, Creeping queue (Northbound Unladen Trucks) 1.56 2.42 9.18 14.30 -56% 5.9 El Paso; Border crossing, Creeping queue (Southbound Trucks (all)) 1.50 2.42 8.85 14.30 -62% 5.9 El Paso; Border crossing, Stop-and-go queue (Northbound FAST Trucks) 1.40 2.42 8.27 14.30 -73% 5.9 El Paso; Border crossing, Stop-and-go queue (Northbound Laden Trucks) 1.39 2.42 8.20 14.30 -74% 5.9 El Paso; Border crossing, Stop-and-go queue (Northbound Unladen Trucks) 1.41 2.42 8.31 14.30 -72% 5.9 El Paso; Border crossing, Stop-and-go queue (Southbound Trucks (all)) 1.42 2.42 8.37 14.30 -71% 5.9 El Paso; Border crossing, Uncongested links (Northbound FAST Trucks) 0.73 1.03 7.34 10.27 -40% 30.0 El Paso; Border crossing, Uncongested links (Northbound Laden Trucks) 0.71 1.03 7.12 10.27 -44% 30.0 El Paso; Border crossing, Uncongested links (Northbound Unladen Trucks) 0.79 1.03 7.90 10.27 -30% 30.0 El Paso; Border crossing, Uncongested links (Southbound Trucks (all)) 0.78 1.10 7.75 11.00 -42% 25.0 FHWA Advances; Actuated signalized arterial; 0.70 V/C (Entire segment) 2.59 1.13 0.70 0.30 56% 23.0 FHWA Advances; Actuated signalized arterial; 0.70 V/C (Intersection approach only) 2.11 1.25 0.26 0.15 41% 18.0 FHWA Advances; Freeway to Freeway; 1.2 V/C (Downstream from merge area #2) 1.54 1.13 0.79 0.58 27% 23.0 FHWA Advances; Freeway to Freeway; 1.2 V/C (Downstream from merge area) 2.04 0.50 0.70 0.17 76% 58.0 FHWA Advances; Freeway to Freeway; 1.2 V/C (Merge area) 1.20 1.07 0.04 0.04 11% 27.0 FHWA Advances; Freeway to Freeway; 1.2 V/C (On-Ramp) 2.74 1.92 1.82 1.28 30% 8.0 FHWA Advances; Incident, 1 lanes, 45 minutes; 1.40 V/C (Downstream from merge area) 0.76 0.34 39.0 FHWA Advances; Incident, 1 lanes, 45 minutes; 1.40 V/C (Merge area) 1.35 0.06 16.0 FHWA Advances; Incident, 1 lanes, 45 minutes; 1.40 V/C (On-Ramp) 1.77 0.55 9.0 FHWA Advances; Incident, 1 lanes, 45 minutes; 1.40 V/C (Upstream from merge area) 1.21 0.69 19.0 FHWA Advances; Incident, 2 lanes, 45 minutes; 0.90 V/C (Downstream from merge area) 3.38 0.71 1.54 0.32 79% 44.0 FHWA Advances; Incident, 2 lanes, 45 minutes; 0.90 V/C (Merge area) 1.70 1.09 0.08 0.05 36% 26.0 FHWA Advances; Incident, 2 lanes, 45 minutes; 0.90 V/C (On-Ramp) 1.52 0.78 0.48 0.24 49% 37.0 FHWA Advances; Incident, 2 lanes, 45 minutes; 0.90 V/C (Upstream from merge area) 1.29 1.10 0.73 0.63 15% 25.0 FHWA Advances; Incident, 2 lanes, 45 minutes; 1.40 V/C (Downstream from merge area) 3.01 0.76 1.37 0.34 75% 39.0

Guide to Truck Activity Data for Emissions Modeling A-26 Study, Scenario, and Link Name PM2.5 Emissions, g/mile PM2.5 Emissions, g/hour % Δ from Default Average Speed Custom MOVES Default Custom MOVES Default FHWA Advances; Incident, 2 lanes, 45 minutes; 1.40 V/C (Merge area) 3.58 1.30 0.17 0.06 64% 17.0 FHWA Advances; Incident, 2 lanes, 45 minutes; 1.40 V/C (On-Ramp) 1.62 1.45 0.51 0.45 10% 13.0 FHWA Advances; Incident, 2 lanes, 45 minutes; 1.40 V/C (Upstream from merge area) 2.11 1.25 1.20 0.71 41% 18.0 FHWA Advances; Incident, 2 lanes, 90 minutes; 1.40 V/C (Downstream from merge area) 2.96 1.34 39.0 FHWA Advances; Incident, 2 lanes, 90 minutes; 1.40 V/C (Merge area) 3.45 0.16 17.0 FHWA Advances; Incident, 2 lanes, 90 minutes; 1.40 V/C (On-Ramp) 1.70 0.53 13.0 FHWA Advances; Incident, 2 lanes, 90 minutes; 1.40 V/C (Upstream from merge area) 2.30 1.31 18.0 FHWA Advances; Incident, 3 lanes, 45 minutes; 1.40 V/C (Downstream from merge area) 2.49 1.13 37.0 FHWA Advances; Incident, 3 lanes, 45 minutes; 1.40 V/C (Merge area) 3.69 0.17 19.0 FHWA Advances; Incident, 3 lanes, 45 minutes; 1.40 V/C (On-Ramp) 2.10 0.66 15.0 FHWA Advances; Incident, 3 lanes, 45 minutes; 1.40 V/C (Upstream from merge area) 1.84 1.05 15.0 FHWA Advances; On port 3.55 4.01 6.01 6.80 -13% 3.0 FHWA Advances; On-ramp with metering; 1.20 V/C (Downstream from merge area) 3.22 0.72 1.46 0.33 78% 43.0 FHWA Advances; On-ramp with metering; 1.20 V/C (Merge area) 2.86 1.35 0.13 0.06 53% 16.0 FHWA Advances; On-ramp with metering; 1.20 V/C (On-Ramp) 3.38 1.92 1.06 0.60 43% 8.0 FHWA Advances; On-ramp with metering; 1.20 V/C (Upstream from merge area) 1.91 1.25 1.08 0.71 34% 18.0 FHWA Advances; On-ramp; 1.20 V/C (Downstream from merge area) 2.24 0.81 1.02 0.37 64% 35.0 FHWA Advances; On-ramp; 1.20 V/C (Merge area) 3.48 1.38 0.16 0.07 60% 15.0 FHWA Advances; On-ramp; 1.20 V/C (On-Ramp) 2.84 1.92 0.89 0.60 32% 8.0 FHWA Advances; On-ramp; 1.20 V/C (Upstream from merge area) 1.86 1.21 1.06 0.69 35% 19.0 FHWA Advances; Port gate, 10 trucks/hr (Gate approach) 1.38 0.78 0.64 0.36 44% 15.0 FHWA Advances; Port gate, 10 trucks/hr (Intersection approach) 2.41 1.38 0.36 0.21 43% 37.0 FHWA Advances; Port gate, 60 trucks/hr (Gate approach) 2.60 2.72 1.21 1.27 -5% 13.0 FHWA Advances; Port gate, 60 trucks/hr (Intersection approach) 2.57 1.45 0.39 0.22 44% 5.0 FHWA Advances; Pretimed signalized arterial; 0.70 V/C (Entire segment) 2.76 1.19 0.74 0.32 57% 20.0 FHWA Advances; Pretimed signalized arterial; 0.70 V/C (Intersection approach only) 3.00 1.41 0.37 0.17 53% 14.0 Houston-Galveston Port Drayage; On port 3.57 4.73 8.76 11.59 -32% 2.5 Note: Emission rates are colored on relative scale within each column. Red represents the higher values in a given column, and green represents the lower values in a given column.

Guide to Truck Activity Data for Emissions Modeling A-27 A.6.4 Comparison of Operating Mode Distributions Figure A.19 to Figure A.22 compare operating mode distributions for on-port drayage from various sources. Figure A.19 shows data collected from trucks operating at the ports of Los Angeles, Long Beach, and Houston-Galveston, as well as warehouse operations in southern California. The distributions are generally similar across the locations and show trucks spending most of their time (around 70 percent at ports) in idle mode (1), with most of the rest in low-speed coasting (11) or low speed/low power acceleration (12). The idling fraction is slightly lower in warehouse operation but still over 60 percent. While the sample of trucks in the California dataset is small (four), port OMDs are similar across individual trucks (Figure A.20). The modeled OMDs from the FHWA Advances study show even more time in idle mode (over 80 percent) but do not show any time in low-speed coasting. Drayage cycles from the NREL Fleet DNA database are also presented for comparison (Figure A.21). The NREL cycles for the “port near dock” and “creep queue” situations show somewhat more activity in low- speed, higher VSP bins (12 – 16), although most activity is still in the idle mode (70 percent for port near dock). Figure A.23 to Figure A.25 compare OMDs simulated at port gates and in queues at border crossings. Figure A.23 shows port gate OMDs modeled in the FHWA Advances study, for 10 trucks per hour and 60 trucks per hour at the gate approach. The OMDs are generally similar, with about 60 percent of time spent idling, 12 – 13 percent braking, and the rest distributed across low to moderate speed operation at varying degrees of VSP. Figure A.24 includes the same situations from the FHWA Advances study, but shows the default OMDs assumed by MOVES for the average speed in each situation. The difference in OMDs between the two sources is substantial. Figure A.25 compares creeping queue OMDs for the El Paso border crossing study (simulated, based on observed data) and as observed in the NREL Fleet DNA database. Most of the activity is in idling, braking, or other low-speed, low VSP conditions, although the NREL database shows a small fraction in higher-VSP low-speed bins. Other specific situations modeled in the El Paso study show some variation from these examples. The port, warehousing, and border crossings show significantly different OMDs than typical on-highway conditions, which include much more time in higher speed and higher VSP bins. A few examples of on- highway OMDs, from the many situations modeled in the FHWA Advances study, are shown in Figure A.26.

Guide to Truck Activity Data for Emissions Modeling A-28 Figure A.19 Operating Mode Distributions Observed at Ports and Warehouses Source: Analysis of CARB data by University of California at Riverside; analysis of U.S. EPA data by ERG. Figure A.20 Operating Mode Distributions—Individual Trucks at California Ports Source: Analysis of CARB data by University of California at Riverside. 0 10 20 30 40 50 60 70 80 0 1 11 12 13 14 15 16 21 22 23 24 25 27 28 29 30 33 35 37 38 39 40 % Frequency OpMode Bin Port of Los Angeles Port of Long Beach Houston-Galveston drayage, on-port Warehouses, southern California 0 10 20 30 40 50 60 70 80 90 0 1 11 12 13 14 15 16 21 22 23 24 25 27 28 29 30 33 35 37 38 39 40 % Frequency OpMode Bin Vehicle 73 Vehicle 75 Vehicle 76 Vehicle 78

Guide to Truck Activity Data for Emissions Modeling A-29 Figure A.21 On-Port Operating Mode Distributions Modeled in FHWA Advances Study Source: E. H. Pechan and Cambridge Systematics, 2010. Figure A.22 NREL Drayage Cycles Source: Analysis of NREL data by Cambridge Systematics. 0 10 20 30 40 50 60 70 80 90 0 1 11 12 13 14 15 16 21 22 23 24 25 26 27 28 29 30 33 35 37 38 39 % Frequency OpMode Bin FHWA Advances, on-port 0 10 20 30 40 50 60 70 80 90 0 1 11 12 13 14 15 16 21 22 23 24 25 27 28 29 30 33 35 37 38 39 40 % Frequency OpMode Bin Port Near Dock Creep Queue Local

Guide to Truck Activity Data for Emissions Modeling A-30 Figure A.23 Operating Mode Distributions at Port Gates Modeled Source: E. H. Pechan and Cambridge Systematics, 2010. Figure A.24 Operating Mode Distributions at Port Gates MOVES Default Based on Average Speed Source: Cambridge Systematics analysis using MOVES2014a, speeds of 15 and 13 mph. 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0 1 11 12 13 14 15 16 21 22 23 24 25 26 27 28 29 30 33 35 37 38 39 40 % Frequency OpMode Bin FHWA Advances Port Gate, 10 trucks/hr (Gate approach) FHWA Advances Port Gate, 60 trucks/hr (Gate approach) 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0 1 11 12 13 14 15 16 21 22 23 24 25 26 27 28 29 30 33 35 37 38 39 40 % Frequency OpMode Bin FHWA Advances Port Gate, 10 trucks/hr (Gate approach) FHWA Advances Port Gate, 60 trucks/hr (Gate approach)

Guide to Truck Activity Data for Emissions Modeling A-31 Figure A.25 Operating Mode Distributions in Creeping Queues Source: Analysis of data from Kear, Wilson, and Corbett (2012) and NREL. Figure A.26 Examples of On-Highway Operating Mode Distributions (Modeled) Source: E. H. Pechan and Cambridge Systematics, 2010. 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 0 1 11 12 13 14 15 16 21 22 23 24 25 26 27 28 29 30 33 35 37 38 39 40 % Frequency OpMode Bin FHWA El Paso Border Crossing creeping queue (Northbound Unladen Trucks) FHWA El Paso Border Crossing creeping queue (Northbound Laden Trucks) FHWA El Paso Border Crossing creeping queue (Southbound Trucks (all)) NREL Fleet DNA Drayage Creep Queue 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0 1 11 12 13 14 15 16 21 22 23 24 25 26 27 28 29 30 33 35 37 38 39 40 % Frequency OpMode Bin Actuated signalized arterial; 0.70 V/C (Entire segment) Incident, 2 lanes, 45 minutes; 0.90 V/C (Merge area) On ramp; 1.20 V/C (On-ramp) Freeway to Freeway; 1.2 V/C (Downstream from merge area)

Guide to Truck Activity Data for Emissions Modeling A-32 A.6.5 Description of Project Situations Figure A.27 shows the locations of the terminals at which data was collected in the Port of Houston study. Figure A.27 Port of Houston Study: Terminals Analyzed Source: Kishan et al., 2012; map courtesy Google maps. The FHWA border crossing study conducted simulation modeling for two crossings in the El Paso-Juarez region: Ysleta-Zaragoza and the Bridge of the Americas (BOTA). Figure A.28 shows the Ysleta-Zaragoza area and Figure A.29 shows the BOTA area. These are sample figures showing northbound commercial processes; southbound processes operate in the reverse. Additional figures and explanations of the labels are provided in the source report (Kear, Wilson, and Corbett, 2012). Figure A.30 and Figure A.31 show simulation model configurations from the port approach and other selected situations for the FHWA Advances study.

Guide to Truck Activity Data for Emissions Modeling A-33 Figure A.28 FHWA Border Crossing Study Northbound Commercial, Ysleta-Zaragoza Source: Kear, Wilson, and Corbett, 2012; image courtesy Google Earth. Figure A.29 FHWA Border Crossing Study Northbound Commercial, BOTA Source: Kear, Wilson, and Corbett, 2012; image courtesy Google Earth.

Guide to Truck Activity Data for Emissions Modeling A-34 Figure A.30 FHWA Advances Study: Simulation of Port Approach Source: E. H. Pechan and Cambridge Systematics (2010). Figure A.31 FHWA Advances Study: Sub-network Configuration for On-Ramp, Ramp Metering, and Incident Scenarios Source: E. H. Pechan and Cambridge Systematics (2010).

Guide to Truck Activity Data for Emissions Modeling A-35 A.7 Transferability This case study illustrates relative differences in emission rates by project context, but the illustrative emission factors should not be used to apply actual emission rates locally. Instead the project sponsor should use a representative operating mode distribution in combination with other locally appropriate MOVES inputs. The similarity in OMDs and emission rates across the port settings suggest that results for one port setting may be transferable to another setting. Similar patterns were also observed in the vicinity of warehouses. Operations in queues at port gates and border crossings also showed similarities. OMDs in all these situations can differ substantially from highway conditions, which also show wide variability across situations.

Next: Appendix B. Case Study #2: Age Distributions from Inspection Station Data »
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NCHRP Web-Only Document 261: Case Studies of Truck Activity Data for Emissions Modeling consists of seven case studies that are appendices A to G of NCHRP Report 909: Guide to Truck Activity Data for Emissions Modeling.

NCHRP Research Report 909 explores methods, procedures, and data sets needed to capture commercial vehicle activity, vehicle characteristics, and operations to assist in estimating and forecasting criteria pollutants, air toxics, and greenhouse gas emissions from goods and services movement.

NCHRP Research Report 909 is also supplemented by three MS Excel files that contain data from the case studies:

Case Studies #1 and #7

Case Study #2

Case Studies #3, #4, and #6

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