Characterization of Cross-Border Heavy-Duty …docs.trb.org/prp/17-03753.pdfFarzaneh, Birt, Johnson, Gu, and Overmyer 2 1 ABSTRACT 2 The research presented in this paper characterizes

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Characterization of Cross-Border Heavy-Duty Drayage Activity 3

in the Laredo-Nuevo Laredo Airshed 4

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Reza Farzaneh, Ph.D., P.E. * 8

Texas A&M Transportation Institute 9

505 E. Huntland Dr., Suite 455, Austin, TX 78752 10

Tel 512.407.1118 | Fax 512.467.8971 | Email: [email protected] 11

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Andrew Birt 13


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Jeremy Johnson 16


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Chaoyi Gu 19


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and 22

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Sarah Overmyer 24


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Total words: 5570 + (6 figures and 2 tables) × 250 = 7,570 39 40 41

* Corresponding author

mailto:[email protected]

Farzaneh, Birt, Johnson, Gu, and Overmyer

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ABSTRACT 1

The research presented in this paper characterizes the activities and emissions of drayage 2

truck activities in the Laredo-Nuevo Laredo region. Drayage vehicle activity is a 3

significant component of total on-road vehicle activity and mobile source emissions in 4

the Laredo-Nuevo Laredo airshed. Currently the air quality impacts of drayage trucks are 5

only partially captured in regional emissions inventories through vehicle activity 6

estimates based on regional travel demand models. In this study, global positioning 7

system (GPS) units were fitted to a sample of 20 drayage trucks operating in the Laredo-8

Nuevo Laredo area. The resulting GPS data were analyzed in GIS to generate trip by trip 9

information on truck activity, with each trip defined by an origin and destination. The trip 10

data were used to determine the most visited trucking facilities, to develop maps 11

illustrating the key freight corridors in the region, and extract other relevant information 12

such as trip lengths and speed distributions and resulted emissions. The results show that 13

the Colombia bridge crossing is the most utilized port of entry in the region, and is 14

associated with relatively high emissions caused by high truck volumes and slow speeds. 15

Additionally, the specific geography of the Colombia Bridge port of entry, and truck 16

facilities on the US side of the border results in high truck volumes, low truck speeds, and 17

therefore high emissions adjacent to some urban areas of Laredo.18

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INTRODUCTION 1

Drayage vehicle activity is a significant component of total on-road vehicle activity and mobile 2

source emissions in the US-Mexico border region, specifically the Laredo-Nuevo Laredo 3

airshed. Laredo is the largest port of entry along the US-Mexico border with more than 2 million 4

of reported trucks crossing into the US in 2015. Currently the impacts of drayage trucks are only 5

partially captured through vehicle activity estimates based on regional travel demand models 6

(TDMs) and traffic counts. Vehicle activity estimates from TDMs are indirect and not detailed 7

enough to provide a full picture of the drayage activity in the area. The goal of the study 8

presented in this paper was is to provide a detailed characterization of the drayage activity in the 9

Laredo-Nuevo Laredo region using data collected directly from a sample of trucks in the region. 10

These data are important for transportation and air quality planners and policy makers to develop 11

strategies and policies to address the air quality and transportation needs at a bi-national, regional 12

level. 13

The data, methodologies, and information generated from the project provide information and 14

inputs for characterizing local drayage activities and assessing their air quality implications 15

including in regional emissions inventories and local/project-level evaluations. The information 16

and methodologies can also be used to better characterize drayage activity at other border 17

locations along the US-Mexico border; specifically the speed profiles generated will enable 18

responsible agencies to develop more accurate Motor Vehicle Emissions Simulator (MOVES) 19

drive schedules for border-crossing drayage trucks. Besides helping to evaluate air quality 20

impacts, the results of this study will also enable local stake holders to monitor the existing state 21

of the drayage activity in the region and identify opportunities to improve the efficiency and 22

impacts of this activity at a regional level. 23

STATE-OF-THE-PRACTICE 24

Due to restrictions on Mexican trucks conducting long-haul operations in the United States, 25

freight crossing the border is transported by a drayage system. The border drayage trucks that 26

transport goods between the two countries have unique fleet and operational characteristics. In 27

freight transportation, the term drayage refers to a segment of the supply chain where a good is 28

transported from one site to another, but not the entire distance of its trip. Drayage often involves 29

the transport of cargo to or from a seaport, border POE, inland port, or intermodal freight facility, 30

to another destination and is typically characterized by short trips. For cities that are freight trade 31

centers, drayage activity can be a significant component of freight transportation. 32

The North American Free Trade Agreement (NAFTA) significantly increased US-Mexico trade 33

and resulted in increased drayage activity along the border. Because of long-haul trucking 34

restrictions between Mexico and the United States and other factors such as language barriers 35

and insurance requirements, most Mexican trucks do not operating in the United States beyond a 36

certain distance from the border (i.e. the commercial zone). Instead, freight is transported across 37

the border in drayage trucks to warehouses located within the commercial zone on the US side of 38

the border. US domiciled long-haul trucks are then responsible for transporting the freight to 39

final destinations within the United States. Table 1 lists the busiest land POEs on the US-Mexico 40

border by the number of truck crossings in 2013. As shown in Table 1, Laredo has more than 41

twice as many truck crossings as the second busiest POE in Otay Mesa, California. 42


4

Table 1: Southern Border POEs by Number of Truck Crossings 2013 (Error! Bookmark not 1

defined.). 2

POE Name Truck Crossings into United

States

% of Total Mexico Border

Laredo, TX 1,846,282 35.5%

Otay Mesa, CA 769,886 14.8%

El Paso, TX 738,914 14.2%

Hidalgo, TX 510,706 9.8%

Calexico East, CA 325,690 6.3%

Nogales, AZ 311,669 6.0%

3

Border drayage vehicles operate in commercial zones varying in distance from 3–25 miles from 4

the border. These drayage trucks pick up trailers on the Mexican side of the border and deliver 5

them to broker facilities or warehouses in the US commercial zone. Trailers are then transferred 6

to a US carrier that delivers the goods to their final destination (1). Due to long and unpredictable 7

wait times at the border, drayage vehicles spend much time idling. It is common for drayage 8

trucks to be older than typical long haulers because they are not required to be as efficient and 9

reliable as trucks hauling goods for long distances from their base. 10

Figure 1 shows a basic overview of the border crossing process involving the drayage operation. 11

The process starts when a Mexican domiciled long-haul truck drops its cargo at a warehouse or 12

yard in the commercial zone on the Mexican side of the border. The office manager calls a 13

customs broker, who fills out the documents necessary to inform both Mexico and the United 14

States of the origin and destination of the goods. Once the paperwork is complete and the trailer 15

is ready to cross, a drayage truck and second driver pick up the cargo. At Mexican customs, 16

called Aduanas, documents are verified and cargo is inspected. Some cargo goes through a 17

secondary inspection before crossing the border. On the US side of the border crossing 18

compound, the US Customs and Border Protection agents conduct a primary inspection of 19

documents. Secondary inspections can be done by a Vehicle and Cargo Inspection System or x-20

ray machine. Safety inspections are carried by other inspectors such as the Federal Motor Carrier 21

Safety Administration or the state agency responsible for road safety where inspections are 22

focused on road-safety requirements (2). 23

After completing all inspections and exiting the compound, the second driver drops off the cargo 24

at a warehouse or yard in the commercial zone in the United States where a US long-haul vehicle 25

and a third driver pick up the cargo. At this point the drayage vehicle and second driver will 26

return to Mexico, either with new cargo or empty. 27


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Figure 1: Cross-Border Drayage Process. 2

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Characteristics of the Drayage Fleet 4

The emissions of commercial vehicles such as drayage trucks are strongly dependent on 5

characteristics such as model, maintenance history, and especially age. In 2013, TTI researchers 6

collected a sample of over 3,000 vehicles at the Bridge of the Americas (BOTA) and the Ysleta-7

Zaragoza Bridge in El Paso, Texas, to develop an emissions estimation tool for border crossings 8

(3). The sample represented freight trucks that crossed the border and can be assumed to 9

comprise mostly drayage vehicles. Almost every truck sampled crossing the border was 10

registered in Mexico, with only 5 trucks domiciled in the United States. Figure 2 summarizes the 11

age distribution from this study along with the age distribution of short and long-haul heavy duty 12

vehicles registered in El Paso obtained from the vehicle registration dataset for 2011. The 2013 13

TTI study has shown that almost all drayage vehicles are registered in Mexico, therefore it is 14

highly unlikely that the US-registered trucks are drayage vehicles. 15

Figure 2 shows that the most common age for drayage vehicles is between 15–19 years (37.5 16

percent), whereas the most common age for US short haul vehicles is newer, between 10–14 17

years (29.6 percent). US long-haul vehicles are even newer, with the most common age between 18

5–9 years (25.98 percent), and only a slightly smaller proportion of vehicles less than 5 years old 19

(22.28 percent). 20

21

Mexican export

documentation,

verification, and

cargo inspection

selection

Mexican

export cargo

inspection

CBP primary

inspection

(document

inspection)

Secondary

Inspection:

VACIS, X-ray,

FMCSA,

Others

Visual vehicle

safety

inspection

Detailed state

truck safety

inspection

Warehouse

/Yard

Warehouse/

Yard

Mexico U.S.A.

1. Mexican Export Lot 2. U.S. Federal

Compound

3. State Safety

Inspection FacilityMexican long-haul

truck

Drayage truck

Drayage truck

Drayage truck

U.S. long-haul truck


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Figure 2: Age Distribution of Heavy-Duty Trucks in El Paso-Juárez Region. 2

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Cross-Border Drayage Truck Activity And Emissions 4

In 2005, Zietsman et al. looked at the border crossing travel profile (Error! Bookmark not 5

defined.). Using GPS data, the authors separated the crossing process into three sections: the 6

entrance of Mexican Customs to the US customs primary inspection booth; the distance traveled 7

within the US federal compound; and the distance traveled through the state safety inspection 8

facility. The results showed that vehicles were either idling or creep idling for 63 percent of the 9

time they spent during the crossing process.1 10

Farzaneh et al. developed an emissions estimation tool for the El Paso-Ciudad Juárez border (3). 11

A total of 10 drayage trucks were equipped with global positioning system (GPS) units for two 12

weeks to collect data to develop operating mode distributions. These vehicles engaged in border 13

crossing activities at different times of the day, different days of the week, and different 14

directions of entry. The operating mode distributions of each border crossing trip were developed 15

as the inputs for emissions estimation using EPA’s MOVES model. 16

Zietsman et al. developed a border crossing emissions profile of trucks at the El Paso-Ciudad 17

Juárez border (Error! Bookmark not defined.). In this study a total of nine trucks, 1985 to 1998 18

model years, were tested. Results showed that trucks with the highest mileage had the highest 19

hydrocarbon (HC) emissions rate, but that there were no clear patterns for HC emissions across 20

modes of idling. There was also no clear correlation between the age of trucks and oxides of 21

nitrogen (NOx), carbon monoxide (CO), and particulate matter (PM) emissions. No clear 22

correlation existed between miles accumulated and NOx. CO, and PM emissions tended to 23

increase with higher engine loads. 24

Cambridge Systematics, Inc. estimated emissions rates for a variety of traffic conditions based 25

on data obtained from the BOTA and Ysleta-Zaragoza border crossings in El Paso (4). This 26

study was intended to develop an approach for estimating emissions rates for US-Mexico border 27

1 In this study, idling was defined as being at a complete stop and creep idling was defined as

traveling less than 5 mph and with acceleration or deceleration less than 0.5 mph/sec.

0-4 years 5-9 years10-14

years

15-19

years

20-24

years

25-29

yearsover 30

U.S. short-haul 8.68% 16.52% 29.60% 21.90% 12.81% 6.37% 4.13%

U.S. long-haul 22.28% 25.98% 25.40% 14.17% 7.03% 3.06% 2.09%

Drayage 5.00% 12.70% 31.30% 37.50% 10.70% 2.20% 0.20%

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00%

40.00%

Per

cen

t of

flee

t U.S. short-haul

U.S. long-haul

Drayage


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crossings. Different congestion conditions were simulated by developing MOVES operating 1

mode profiles and classifying travel as almost complete idling (less than 1 mph), creeping (less 2

than 5 mph), and uncongested operation (around 25 to 35 mph). Various traffic scenarios were 3

tested as case studies for measuring emissions. These included free flow at the border with no 4

delay, no action being taken, shifting private vehicles to faster Secure Electronic Network for 5

Travelers Rapid Inspection (SENTRI) lanes,2 and combining US and Mexican cargo inspections. 6

The NAFTA/Mexican Truck Emissions Overview looked at Mexican truck emissions profiles 7

and estimated emissions and air quality impacts of increased Mexican vehicle travel into the 8

United States, specifically California (5). It was found that 66 percent of the Mexican trucks 9

were from 1993 or before, which means that these vehicles do not use the computer controls to 10

reduce emissions that later models have. A total of 25 percent of the observed Mexican truck 11

fleet was from prior to 1980, and on average emit high levels of NOx and PM emissions. This 12

study also pointed out that Mexico did not follow US standards that require a 50 percent 13

reduction in NOx for model years 2004 to 2007 and a 90 percent reduction for model year 2007. 14

The requirement to use ultra-low sulfur diesel fuel was also not required in Mexico. The most 15

recent diesel engine emissions standards applied in Mexico at the time were the EPA standards 16

for the 1993–2003 model years. 17

Drayage Activity in Laredo-Nuevo Laredo 18

Harrison et al. identified the range of drayage truck movement and the types of drayage truck 19

movements in the Laredo border area through a literature review and interviews (6). The 20

boundaries of the Laredo commercial zone extended 18 kilometers into Mexico from the border 21

and were within 8 miles of the Laredo city limits on the Texas side of the border. Drayage 22

companies, which are almost all based in Mexico, move trailers across the Texas-Mexico border 23

as well as transport both truckload movement and less than truckload deliveries between 24

locations in Laredo.3 The authors used truck crossing data, studied maps, and conducted 25

interviews to collect detailed information about major industrial areas near the Laredo crossing. 26

Based on information from the Laredo Bridge Authority, the authors estimated that 77 percent of 27

trucks use the World Trade Bridge and the remaining 23 percent use the Colombia Solidarity 28

Bridge. This is likely because the World Trade Bridge is closer to industrial areas than the 29

Columbia Solidarity Bridge. 30

A TTI study provides detailed descriptions of the two international bridges (World Trade Bridge 31

and Laredo-Columbia Solidarity Bridge) in Laredo that allow commercial traffic (7). Although 32

the study does not specifically focus on drayage or emissions, location information is presented 33

as well as information regarding access and connections to major roadways to in both Texas and 34

Mexico. Operational characteristics for both bridges including hours of operation, truck crossing 35

volumes, and the process for crossing the border are included. 36

Zietsman et al. focused on the use of alternative fuels in heavy-duty diesel trucks as a means of 37

reducing emissions (Error! Bookmark not defined.). The authors used GPS data to develop 38

2 The SENTRI program is a trusted traveler program that allows private vehicles to use separate

lanes at POEs for expedited processing. For more information see:

http://www.cbp.gov/travel/trusted-traveler-programs/sentri. 3 The website www.forwarders.com/StateDirecory/TX.html provides a list of freight forwarding

companies found in Laredo.

http://www.cbp.gov/travel/trusted-traveler-programs/sentri

http://www.forwarders.com/StateDirecory/TX.html


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drayage drive cycles that capture the driving patterns (acceleration, deceleration, speed, etc.) of 1

drayage trucks from Mexico at the Laredo border. Second-by-second speed (mph) and location 2

(coordinate) data were collected and analyzed to develop a representative drayage cycle to 3

address critical driving components of drayage trips. Three movement phases are indicated from 4

drive cycles, including border to company, company to company, and border crossing. Emission 5

testing using PEMS units for various pollutants was conducted. The results were mixed 6

regarding the relationship of fuel type to emissions across drive cycle and vehicle age. 7

TTI conducted a case study to analyze the air quality impact of truck and rail freight movement 8

along the corridor from Mexico City to Montreal (Error! Bookmark not defined.). As part of 9

this study, data for trucks crossing the border into the United States were obtained from the US 10

Bureau of Transportation Statistics (BTS). Because 2008 was the last full year of data available 11

at the time, the study authors assumed that 2010 truck volumes would recover to 2007 levels; 12

therefore, 2007 border crossing truck volumes were used to estimate 2035 truck volumes. The 13

report includes BTS’s most recent full-year traffic data for POE at Laredo for analysis years 14

from 1995 to 2014. 15

The Laredo-Coahuila/Nuevo León/Tamaulipas Border Master Plan is a part of the Border Master 16

Plans along the US-Mexico border that also include the El Paso and Lower Rio Grande Valley 17

regions (8). The focus of the reports is on long range plans to inventory and prioritize 18

transportation and POE infrastructure as a means of facilitating trade. The Border Master Plans 19

were created through detailed research on infrastructure projects and many in-depth interviews 20

and meetings with stakeholders. The reports include comprehensive descriptions of the 21

infrastructure in the region, on both the US and Mexican side of the border. The authors 22

predicted that population in the Laredo/Nuevo León/Tamaulipas region would increase 23

20 percent in the following 20 years and that employment in the same region would increase by 24

38 percent in the same time period. They also predicted that congestion at the border and 25

approaching roadways would increase. 26

STUDY APPROACH AND RESULTS 27

A series of field data collections and an activity and emissions estimation approach in a GIS 28

environment were developed and executed to characterize the regional cross-border trucks 29

activity and tailpipe emissions from a sample of drayage trucks. The field data collections 30

included an activity data collection using GPS loggers. The first step in the data collection 31

process was to locate participants willing to participate in the study. The TTI research team was 32

able to locate two fleets in Laredo who were willing to participate in the study 33

Researchers traveled to Laredo in June 2015 to perform the following tasks: 34

Obtain consent from signatures from each participant. 35

Install three GPS data loggers in each participating vehicle. Typically, the devices were 36

set in the driver-side storage compartment to ensure that the vibration detector starts 37

recording whenever the vehicle door is opened, usually at the beginning of a trip. If the 38

vehicle did not have a driver-side storage compartment, the loggers were placed in the 39

vehicle’s glove box or another secure location inside the cabin. 40

Details about the participant and vehicle were logged. 41


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The GPS battery capacity and memory size are the main factors influencing the number of days 1

they can be used to collect data. Based on previous research projects, the research team has 2

determined that the data loggers can be used to collect a week of truck activity data. One week 3

after the GPS loggers were installed in participating vehicles, TTI researchers returned to Laredo 4

to retrieve the devices. Data from each GPS unit were downloaded into an electronic spreadsheet 5

and saved onto a central server and given a unique identifier. Under IRB guidance, this unique 6

identifier cannot be traced back to the participating driver or vehicle. After completing the data 7

transfer to the server, the data points from each of the three devices installed on each truck were 8

merged into a single file labeled with unit number, date of initial activation, and type of vehicle 9

observed. Only researchers assigned to the project were provided access to the secure files on the 10

server, and data encryption was used to protect all data files. 11

Data Analysis 12

The goal of the data analysis was to translate the second-by-second coordinate and speed data 13

from the GPS units into more easily interpretable information that describes the activity of 14

drayage trucks in the region. The specific informational products produced by the data analysis 15

are: 16

1. Tables and graphs summarizing the length, speed, duration, and emissions associated 17

with each trip undertaken by each truck during the study period. 18

2. Maps that illustrate the activity and emissions of trucks along the major freight corridors 19

in the region. 20

Summarizing Truck Activities 21

TTI researchers imported the individual GPS points from each data logger into ESRI ArcMap 22

GIS software. The points were plotted using their unique ID and date to separate the points into 23

more manageable activity segments. Then, unique trips for each truck and each day were 24

identified using plots of the GPS data overlaid onto a map of the region. Trips were defined as 25

periods of activity that had continuous truck activity and that had a distinct origin and 26

destination. Each truck trip was given a unique ID and the data points converted to a single 27

polyline shapefile containing the detailed path of each truck trip during the study. The locations 28

of origins and destinations were also tagged with unique identifications, and stored in a data 29

table. Each truck trip was then further split into line segments representing portions of the trip 30

occurring in the United States and Mexico. Finally, the length and average speed of the total US 31

and Mexican portions of each trip were calculated using ArcMap’s Calculate Geometry tool. 32

Data for each unique truck trip (including US and Mexican portions of the trip) and Origin and 33

destination locations were then exported to a spreadsheet to calculate summary statistics and for 34

to create graphs for visualization. 35

The trip by trip data were also used to create maps illustrating the movement of trucks along 36

freight corridors in the region. The average speed and volume of trucks operating on each link 37

during each hour of the day (i.e., 12.00 a.m. to 1:00 a.m., 1:00 a.m. to 2:00 a.m., 2:00 a.m. to 38

3:00 a.m.) were derived from this process. This process was repeated for different temporal 39

periods within the 6-day study period. The temporal aggregations were: weekdays only (4 days), 40

weekends only (2 days), weekday mornings, and weekday afternoons. ArcMap was used to 41

create maps that plot the width of the corridor segments as a function of the number of discrete 42

truck trips that occurred on that corridor segment (corridor activity maps). These maps were also 43


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used to simultaneously display the average speed and estimated NOx and PM associated with the 1

truck activity on each corridor link. NOx and PM emissions were estimated using the 2

methodology outlined next. 3

Emission Estimation 4

The analyses described above provide summarized truck activity data in two distinct formats: 5

1. Trip by trip summaries of routes traveled during the study, including sections of each trip 6

that occurs in the United States versus Mexico. These trip by trip summaries include 7

average speed and the date and times of the trips. 8

2. Link by link summaries of truck activity along the freight corridors identified during the 9

study. 10

These truck activity data were used to estimate emissions associated with each trip and with each 11

link of the freight corridor. Emissions were estimated using EPA’s MOVES. MOVES 2014 was 12

used to create a database of NOx and PM emission rates specific to diesel short-haul combination 13

truck types operating in the Laredo. These inputs were obtained for Laredo from the Texas 14

Statewide Emission Inventory. Emission rates were calculated for a rural arterial highway using 15

worst case environmental conditions for the two pollutants. In the case of NOx, worst case 16

emission rates occur under summer temperature and humidity conditions (89.5°F and 50.9 17

percent relative humidity). For PM, the worst case emissions occur during winter temperature 18

and humidity conditions (59.3°F and 59.6 percent relative humidity). These MOVES emission 19

rates, expressed in grams per mile per vehicle (g/mi) were generated for 16 speed bins from <2.5 20

mph, 5 mph, 10 mph, and every 5 mph to 75 mph. Emissions were estimated for both trip by trip 21

and link by link. 22

Results 23

Table 2 shows a summary of activities during the study period, aggregated by trip origin (United 24

States or Mexico) and by the time of day (mornings or afternoon). In total, 189 distinct trips were 25

made during the 6-day study period. A similar number of trips were made from US and Mexican 26

destinations, but the data suggest that trips from Mexican destinations were more common 27

during the morning hours, while trips originating from the United States tended to occur in the 28

afternoon. This is probably explained by the fact that drayage trucks are predominately Mexican 29

domiciled and permanently reside at warehouses or residences on the Mexican side of the border. 30

Table 2: Summary of Trips throughout Study Period. 31

AM PM Entire Day

USA Mexico USA Mexico USA Mexico

USA

and

Mexico

Number of trips by

origin 22 54 71 42 93 96 189

Number of portions of

trips occurring in each

country

44 65 88 69 132 134 266

Total driven miles in

each country 417 898 585 992 1002 1890 2892


11

Miles driven per

vehicle 9.49 13.82 6.65 14.37 7.59 14.11 15.30

Average speed per

vehicle (mph) 11.99 16.44 16.79 18.42 12.87 17.42 15.52

NOx (grams/vehicle) 455.89 578.39 296.96 575.40 349.94 576.85 653.38

PM (grams/vehicle) 11.30 14.39 7.38 14.36 8.69 14.38 16.26

* based on the origin of the trip

Table 2 also shows the average distance per vehicle, average speed, and emissions generated 1

during travel within Mexican versus the United States. Error! Reference source not found. 2

shows a histogram of the distances traveled during each trip recorded during the study. The 3

average daily distance per vehicle traveled in Mexico is 1.8 times that of the distance traveled in 4

the United States (14.1 miles compared to 7.6 miles equating to 1.8 times the average travel 5

distance). As a result more NOx and PM emissions are generated in Mexico compared to the 6

United States. However, because trucks generally traveled at a higher speed in Mexico than in 7

the United States, (17.4 mph compared to 12.87 mph, respectively), Mexican NOx emissions are 8

only 1.65 greater than those generated in the United States, while Mexican PM emissions are 9

only 1.13 times those of emissions generated in the United States. 10


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Figure 3: Distribution of Trip Lengths for A) Cross-Border and B) Non-Cross-Border 2

Trips. 3

4

A) Cross-border trips. Total = 80

B) Non- Cross-border trips. Total = 112


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The researchers also calculated summary statistics for cross-border and non-cross-border trips 1

undertaken during the study. In total 77 (41percent) of the 184 total trips were cross-border trips 2

(three cross-border trips involved a circular trip across the border). Over the duration of the 3

study, there were 112 non-cross-border trips (59 percent of the total). However, 71 percent of the 4

total miles driven during the study were during cross-border trips compared to only 29 percent of 5

the total miles driven during non-cross-border trips, reflecting the generally smaller average trip 6

length of non-cross-border trips (Figure 3). In total, cross-border trips generated approximately 7

70 percent of total NOx and PM emissions. Southbound cross-border trips tended to occur at 8

higher average speeds in both United States and Mexico than northbound trips possibly because 9

southbound trips occurred more frequently in the afternoon, possibly coinciding with lighter 10

traffic (both at the border and on the broader network). Trucks traveled at approximately half the 11

speed during non-cross-border trips than during cross-border trips. 12

Northbound cross-border trips (i.e., trips originating from Mexico) were more frequently 13

undertaken in the mornings (65 out of 109 morning trips) while southbound trips were more 14

frequently undertaken during the afternoon (88 out 157 afternoon trips). A similar trend occurs 15

for non-cross-border trips. The majority of morning trips occur from Mexico, while most 16

afternoon non-cross-border trips occur from the United States. An approximately equal number 17

of north- and southbound cross-border trips occurred through the study. This reflects the 18

intrinsic, reciprocal nature of drayage activities (i.e., trucks crossing the border one way will 19

return across the border in a relatively short period of time [within a single day]). However, the 20

high proportion of non-cross-border trips observed during this study suggest that for every cross-21

border trip, between one and two shorter, non-cross-border trips are undertaken in preparation 22

for the cross-border trip. It is likely that delays at the border represent a significant portion of the 23

time taken to complete a cross-border trip. Therefore, it is possible that the frequency of non-24

cross-border trips is caused by trucks consolidating goods from a number of locations on one 25

side of the border before they are delivered to one, or a number of facilities across the border. 26

The differences in miles traveled, speed, and emissions on each side of the border can be largely 27

explained by differences in the location of facilities in the United States versus Mexico (Figure 28

4). Here, two factors are important. First, the average distance between facilities most likely has 29

a large impact on the distances traveled in the United States and Mexico for all trips (cross-30

border and non-cross-border). In general, Mexican facilities tend to be more widely distributed 31

than US facilities. Second, the distance traveled during cross-border trucks specifically is also 32

likely related to the distance between border crossings and each facility. Again, Figure 4 33

illustrates that the most frequently visited US facilities tend to be located much closer to the 34

principal border crossing (World Trade Bridge) compared to facilities in Mexico. 35

The complex relationship among travel distance, travel speeds, and emissions highlights the 36

importance of developing a thorough understanding of the truck activity on the network. 37

Researchers developed maps illustrating the volume, speed, and emissions (NOx and PM) of 38

trucks using the network according to different aggregations of trip type and time period. In all 39

cases, the width of the bands represents truck volume and the color of the lines represent either 40

speed, or the emissions per mile calculated using truck volumes and average speeds. In the first 41

set of figures representing activities across the entire study period (Figure 5 and Figure 6), maps 42

showing all data (i.e., volume, speed, and PM) are provided to illustrate the connections between 43

them. 44


14

1

Figure 4: Location of Facilities Visited by Trucks during the Study and the Number of 2

Visits Made to Each Facility. 3

4

Figure 5 provides a comprehensive map of truck volume and speed during the entire study 5

period, with the width of the bands representing truck volume and the color of the lines 6

representing the speed of the trucks. For the same time period, Figure 6 shows the PM emissions 7

associated with the speed illustrated in Figure 5. The maps illustrate that the most important 8

crossing location throughout the study was the World Trade Bridge, and as might be expected, 9

there is an approximately mile stretch of network on either side of the crossing associated with 10

high truck volumes, low speeds, and therefore high and concentrated emissions (both NOx and 11

PM). Figure 5 and Figure 6 also illustrate the generally longer travel distances and higher travel 12

speeds in Mexico compared to the United States. 13

14


15

1

2

Figure 5: Corridor Activity Map Showing the Truck Activity (Number of Truck Trips) 3

along Different Sections of the Corridor for the Entire Study Period and the Average Speed 4

of Trucks along the Freight Corridors. 5

6

7


16

1

Figure 6: Corridor Activity Map Showing the Truck Activity (Number of Truck Trips) 2

along Different Sections of the Corridor for the Entire Study Period and the PM Emissions 3

Associated with This Truck Activity. 4

5

6


17

Of particular interest is the close proximity of the World Trade Bridge crossing to an urbanized 1

areas of Laredo and to a number of facilities in this area. Emissions close to the US border tend 2

to be highly concentrated because of relatively slow speeds associated with the border crossing 3

and the urban roads close to the border. The most heavily visited US facility also occurs in a 4

relatively urbanized area close to the border. In contrast, the most heavily urbanized areas of 5

Nuevo Laredo are located farther away from the border crossing, and in general (except for the 6

congested urbanized areas) average speeds on the Mexican network tend to be higher. 7

Another significant feature of Figure 5 is the relatively low volumes of trucks using the 8

Colombia Solidarity Bridge to the north of Laredo relative to the World Trade Bridge POE. 9

Except for the need to service facilities to the north of the region, the figures suggest that there is 10

little advantage for trucks to make border crossings at this POE. As Figure 4 illustrates, the extra 11

travel distance required to reach most of the facilities via the Colombia Solidarity Bridge is 12

approximately 35 miles, which at the average speeds recorded through the study, is likely to 13

equate to a detour of approximately 1 to 2 hours. 14

CONCLUSIONS 15

The goal of this study was to characterize the activities and emissions of drayage truck activities 16

in the Laredo-Nuevo Laredo airshed. This research is part of a larger goal of improving cross-17

border freight transportation in the Laredo region. Additionally, there is increasing societal 18

awareness of the impact of air quality on human health. 19

Laredo POE is the busiest POE for trucks in the United States. In line with increased trade 20

between United States and Mexico, it is also one of the fastest growing. Although the Laredo 21

airshed currently attains the air quality standards set by EPA, there is considerable motivation to 22

ensure that economic development in the region is planned such that, over the long term, the 23

region maintains or improves current air quality conditions. 24

This study has resulted in the development of data collection methods and analyses to effectively 25

communicate drayage activities and their air quality impacts to a broad range of border 26

transportation stakeholders. The identification and communication of current drayage activities is 27

an important first step in developing an informed plan to improve the efficiency of cross-border 28

trade in the region. Some of the most important findings from the study and their implications to 29

air quality and cross-border freight in the region are: 30

Morning drayage activities generally occur on the Mexican side of the border. 31

Presumably this is because most drayage trucks and drivers are Mexican domiciled. 32

Similarly, afternoon activities tend to involve return trips from the United States to 33

Mexico. The requirement for reciprocal trips (preferably fully loaded) is probably an 34

important factor that drives the timing of trips. 35

According to the trucks sampled in this study, most drayage activities occur during 36

weekdays. Weekend activities are considerably more limited. To develop a full and 37

consistent picture of drayage activities, it is important to understand current drayage 38

activities, but also to identify why these activities occur when they do. 39


18

For every cross-border trip observed through the study, between one and two non-cross-1

border trips took place. Although non-cross-border trips tended to be of shorter duration, 2

they are an important component of the whole drayage industry. As such, it is important 3

to understand why these trips take place. For example, non-cross-border trips may occur 4

as drivers commute to work in their trucks, or may be undertaken to consolidate loads to 5

ensure fully loaded trucks are taken across the border. 6

Most border crossings from trucks sampled during this study took place at the World 7

Trade Bridge. Although there are a number of facilities located north of Laredo and 8

Nuevo Laredo, and therefore close to the Colombia Solidarity Bridge, relatively few 9

crossings take place at this POE. Based on the current data, it appears that in most cases, 10

detours through this POE are not beneficial. However, it is possible that under some 11

circumstances this crossing could be advantageous (e.g., heavy traffic near the urban 12

areas of Laredo-Nuevo Laredo, increased border wait times at the World Trade Bridge 13

crossing, or during periods of construction). 14

The World Trade Bridge crossing is associated with high concentrations of NOx and PM 15

pollutants associated with slow moving trucks. The proximity of this crossing to the city 16

of Laredo is particularly relevant for PM pollutants that have been shown to cause 17

localized health problems. 18

The spatial distribution of facilities serviced by the drayage trucks is different on each 19

side of the border. Note the close proximity of US facilities to the World Trade Bridge 20

POE and to urban Laredo. The slow speeds associated with border crossing, in 21

combination with lower speeds near within urban areas, lead to high emission 22

concentrations in this area. 23

The results of this study provide insights into current drayage activities in the Laredo-Nuevo 24

Laredo airshed. They also provide information that can be used toward a long-term goal of 25

identifying planning and policy strategies capable of improving border freight transportation 26

efficiency. Based on the findings presented in this study, researchers suggest a number of ways 27

in which the methods presented could be expanded and improved. 28

ACKNOWLEDGEMENTS 29

The study reported in this paper was funded by the Border Environment Cooperation 30

Commission (BECC) as part of a research study titled Characterizing Drayage Activities and 31

Emissions in the Laredo-Nuevo-Laredo Airshed (9). 32

33


19

REFERENCES 1

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Documents

Characterization of Cross-Border Heavy-Duty …docs.trb.org/prp/17-03753.pdfFarzaneh, Birt, Johnson, Gu, and Overmyer 2 1 ABSTRACT 2 The research presented in this paper characterizes