The rapid growth of the maquiladora industry
in Mexico and the decrease in trade barriers brought about by the passage
of the North American Free Trade Agreement (NAFTA), has significantly increased
trade between the US and Mexico in recent years. Much of this trade is carried
by heavy-duty trucks (gross vehicle weight greater than 8,500 pounds) and
has resulted in a dramatic growth in the number of trucks crossing the border
between the US and Mexico. Very little information is available concerning
emissions from these trucks, the majority of which burn diesel fuel, either
while idling waiting to cross the border or while circulating in the border
region. This information is needed in order to develop a complete emissions
inventory from mobile sources, which in turn is important for developing
appropriate mitigation strategies to improve air quality along the US-Mexico
border. Although there exists some data on emissions from cars and light-duty
vehicles in a few Mexican cites located near the border, there is virtually
no data available on emissions from heavy-duty trucks in the Mexican border
area. This paper presents emission estimates from idling heavy-duty trucks
waiting to cross the border into San Diego, California from Tijuana, Baja
Between 1991 and 1995 the number of truck border
crossings between Mexico and California increased by 37%, to almost 700,000
a year. On average, over 1,600 northbound trucks cross each day at just
one border crossing, Otay Mesa-Mesa de Otay, between Tijuana and San Diego.
In Fiscal Year 1997, 28, 326, 595 passenger vehicles, 127, 965 buses and
793,403 commercial trucks utilized Southern Californias ports of entry.
Over 15,000,000 of the passenger vehicles entered at the San Ysidro port
of entry while 558, 383 trucks utilized the Otay Mesa commercial crossing.
The majority of heavy-duty vehicles use diesel
fuel and are major emitters of NOx and particulate matter (PM). In San Diego
County, for example, diesel burning trucks accounted for 80% of PM10 (particulate
matter with a diameter less than 10 microns) and 25% of NOx emitted from
all vehicles, even though diesel trucks accounted for only 4% of the total
vehicle miles traveled in 1996. Although significant advances have been
made to reduce emissions from passenger cars and light trucks, which by
and large use gasoline, the same is not the case for the major portion of
heavy-duty trucks currently in use. Current estimates for the U.S. are that
emissions from heavy-duty highway vehicles are projected to represent a
significant fraction of mobile source NOx emissions by the middle of the
next decade. While diesel engines have advantages in terms of fuel efficiency
and durability, control of NOx and PM emissions is much more difficult than
for gasoline engines.
In this study we have, first, characterized
the fleet of trucks crossing at the Otay Mesa port of entry between Tijuana
and San Diego. Second, we have determined the delay patterns on the Mexican
side of the border including a description of how delays vary by time-of-day
and day-of-week. Finally, we have used the fleet characteristics and delay
patterns to calculate an emissions inventory for northbound trucks passing
through the Otay Mesa port.
2. Overview of Data Collection
For the California-Mexico border as a whole,
total vehicle crossings and truck crossings are shown in Table
1 and Table2, respectively. Between 1991 and
1995, the number of passenger vehicles crossing from Baja California to
California increased by only 8%, whereas the number of trucks increased
by 37%. One also sees from Table 2,
that by 1993, all commercial truck traffic has shifted from the San Ysidro
crossing to Otay Mesa, which was built specifically for handling commercial
For this reason, we have chosen the Otay Mesa
port of entry to conduct surveys of trucks waiting to cross the border.
By focusing our data collection at the Otay Mesa crossing, located 5 miles
east of the main port of entry at San Ysidro, we were able to capture a
representative sample of all the heavy-duty truck traffic between San Diego
We concentrated on northbound traffic (from
Mexico into the United States) based on our observation that southbound
congestion is minimal. Because it was not possible to utilize our Mexican
student data collectors on the US side of the border, we only collected
data on trucks waiting to clear Mexican customs. After clearing Mexican
customs they cross to the US side of the border where they must wait once
again to clear US customs. Thus, waiting times derived from our samples
only refer to the Mexican side of the border. We take into account, however,
waiting times on the US side of the border in the discussion of our results.
Trucks enter a queue waiting to pass through
one of five Mexican customs booths. The queue often extends southward, past
the curved section of road into the 2-lane straight roadway. Once the paperwork
at the Mexican customs is complete, most trucks immediately cross into the
United States and wait for passage through American customs. Approximately
7% of the trucks were randomly chosen for additional inspection before crossing
into the United States. These trucks were routed to an eastern parking area.
In the current study, data ware collected at
3 points: 1) at the beginning of the queue, 2) at the custom booths, and
3) at the inspection area. Data collection at the beginning of the queue
was the most difficult as the queue length was constantly changing. For
that reason, students only handed identification tags to the drivers, and
recorded the truck's license plate and time of entry into the queue. At
the custom booth, students retrieved the identification tags and collected
additional information, such as the time of arrival at the booth, mileage,
and truck type. Since customs are computerized, trucks typically wait less
than a minute, which limits the number of questions at the customs booth.
Students asked a more complete list of questions at the inspection area
where truck drivers typically can wait for up to two hours. Since trucks
are randomly chosen for inspection, the responses are representative of
the entire fleet of trucks crossing the border. Table
3 summarizes the specific information collected.
By combining the times of arrival at the queue
and at the customs booth, we determined the wait time on the Mexican side
of the border. Unfortunately, as noted above, we did not receive authorization
to collect data on the U.S. side of the border. Once trucks cross into the
U.S., they wait in additional queues to be processed by the American customs
agents. We do not determine the total waiting time to cross border,
only the amount of time spent waiting on the Mexican side.
Data were collected on 8 days during the month
of February 1997 during the hours of 9 a.m. to 5 p.m. In order to match
data at the start and end of the queue, a unique id had to be correctly
recorded at both locations. We used the combination of identification tag
number and license plate for the unique id. (License plate number alone
was not sufficient as some trucks crossed several times during the day.)
Complete data observations by day are shown in Table
4. We observed approximately 30% of the truck crossings assuming that
daily northbound traffic is 1,600 per day.
Based on weekday traffic, 17.4% of all trucks
crossing between 9 a.m. and 5 p.m. do so on Mondays; 20.3% cross on Tuesdays;
21.3% cross on Wednesdays; 21.2% cross on Thursdays; and 19.5% cross on
Fridays. Since traffic levels are highest mid-week (Tuesday through Thursday),
we would expect delays to also be highest mid-week.
3. Characterizing the Fleet, Trip Patterns, and Trucks Counts by Time-of-day
The fleet of trucks crossing the border can
be characterized based on the larger sample of trucks waiting in the queue
(e.g., vintage, mileage, and basic truck type) or the more detailed questions
asked of truck drivers in the inspection area (e.g., loaded weight, place
of manufacture, etc.). Since so little data are collected of the larger
sample at the customs booth, most of the fleet characterization is based
on the smaller sample of 351 trucks from the inspection area. This smaller
sample is randomly chosen from the larger population so we assume that the
characterization of the sample also represents the larger population.
3.1 Origin of manufacture, manufacturer, and trucking company
Based on the survey response, the vast majority
of trucks (95%) were manufactured in the United States, with the remaining
5% from Mexico. The most common truck manufacturers were International (22%
of all trucks), Freightliner (17%), Kenworth (16%), Ford (14%), GMC (13%),
and Peterbilt (12%). The remaining 6% were spread among many other manufacturers
including KenMex (1%) and Mack (1%).
The majority of trucks in our sample are operated
by Mexican trucking companies. The specific breakdown for operators of trucks
was as follows: 70% Mexican-based trucking companies, 16% U.S.-based companies,
14% based in other countries including Canada or in both the United States
3.2 Distribution of trucks by weight, fuel, and vintage
Since emission factors in the two main emission
models (Environmental Protection Agency's MOBILE model and California Air
Resources Board's EMFAC model) vary by the loaded vehicle weight, fuel type,
and vintage, it is important that we classify trucks based on these parameters.
The vast majority (97%) of trucks passing through
Otay Mesa are heavy-duty trucks with loaded vehicle weight over 8,500 pounds.
Of these trucks, 76.7% are fueled by diesel and the remaining 23.3% are
fueled by gasoline. The distribution of heavy-duty trucks by vintage and
fuel type is represented in Figure 1. The remaining
3% of trucks weigh between 6,000 and 8,500 pounds, falling under the classification
of light-duty trucks. Half of these trucks are fueled by diesel, half by
gasoline. Since we had such a limited number of light-duty trucks, we were
unable to characterize them by vintage.
We also queried drivers as to where they purchased
their fuel. Diesel fuel sold in the United States has lower sulfur content
by weight than diesel fuel in Mexico. According the drivers' responses,
85% of the trucks using diesel fuel purchased that fuel in Mexico (15% was
purchased in the United States). 56% of trucks using gasoline purchased
their fuel in Mexico (44% was purchased in the United States).
3.3 Frequency of daily border crossings, departure, and destination
Truckers who were scheduled to cross the border
into the United States several times in a day made nearly half of the truck
crossings. More specifically, daily northbound crossings for the observed
trucks were as follows: 50.4% cross northbound only once during the day,
25.0% cross twice, 12.0% cross three times, 7.6% cross four times, and 5.0%
cross five or more times.
Most trucks began their trip from Tijuana's
maquiladoras, and completed the trip in San Diego County. The breakdown
of departures and destinations are listed in Table
3.4 Number of trucks crossing northbound by time-of-day
We did not count every single truck crossing
the border throughout the day. Our survey was only conducted during the
hours of 9 a.m. to 5 p.m., with a break during the lunch hour. Even during
the hours for which surveys were administered, we were unable to collect
information for every single truck. Therefore, we rely on detailed truck
counts from the California Department of Transportation (Caltrans) summarized
in Table 6.
4. Characterizing Delays
Trucks waiting to reach the custom booths (between
data collection points 1 and 2) remain idling. Those trucks chosen for inspection
move to the side, and are shut off during the inspection period. Since emission
patterns depend upon whether the truck is running, delay times are separated
based on whether the truck is idling or shut down for inspection.
4.1 Delay While Idling
Based on the full sample of 3,946 truck crossings,
the average northbound truck waits 12.0 minutes before reaching the Mexican
custom booth. Such an average masks a great deal of variation, both by day-of-week
and time-of-day. Focusing first on daily variation, the average delay is
longest during the middle of the week (Tuesday and Wednesday) with much
less delay on Monday and Friday. This result is not surprising since the
number of trucks crossing in the middle of the week was higher than on Mondays
or Fridays (see Table 7). Average delays by
day-of-week are: 1.97 minutes on Monday, 13.07 on Tuesday, 23.35 on Wednesday,
7.44 on Thursday, and 4.18 on Friday.
Even greater variation occurs within any given
day. Congestion is typically worse during the afternoon hours (1-4 p.m.)
with a marked drop off just before 5 p.m.
The majority of trucks (95%)crossing at the
border were manufactured in the United States, and most of these trucks
are registered in both the United States and Mexico. We therefore assume
that trucks at the border are similar to trucks of the same vintage and
model throughout the rest of the United States, and determine emissions
of HC, CO and NOx using the Environmental Protection Agency's MOBILE model
(MOBILE5b). Within MOBILE, emission factors vary by several factors including
speed, fuel type, vehicle age, and temperature. We use the characteristics
of the border trucks (specifically vintage and fuel type) to determine composite
emission factors appropriate for idle emissions at the border. We calculate
idle emissions using the lowest allowable speed in MOBILE5b (or 2.5 miles
per hour) and for two different temperature scenarios (60-75 degrees Fahrenheit
for the morning hours and 70-90 degrees Fahrenheit for the afternoon hours).
Diesel emissions from MOBILE are the same for both temperature scenarios,
while gasoline emissions vary depending upon the pollutant.
The USEPA's PART5 model was used to estimate
PM10 emissions. In the PART5 model, particulates do not vary with ambient
temperature, so there's no need to separate morning and afternoon calculations.
PM10 does vary with altitude (set to 500 feet), whether reformulated or
gasoline is used (flag set to no) and the number of rainy days, which was
set to 44 based on yearly averages for San Diego. I/M programs are primarily
for light duty vehicles, so this shouldn't make a difference for trucks.
Any other assumptions were set at the default values used in PART5.
For LDGT and LDDT, composite emission factors
were used because we did not have enough observations for these vehicles
types to classify the fleet crossing the border, e.g., we assume the fleet
is the same as the rest of the US.
4.1 Composite emission factors
Our sample contained so few light-duty trucks
that we were unable to describe the population of these vehicles by vintage
(see Section 3.2). Therefore, we make the simplifying assumption that light-duty
trucks at the border are similar to light-duty trucks in the United States
in terms of their age distribution. We simply use the composite idle emission
factors for light-duty gasoline trucks (LDGT) and light-duty diesel trucks
Our sample is large enough to characterize
the population distribution of heavy-duty trucks by both fuel type and vintage.
We determine emission factors for all vintages of heavy-duty gasoline trucks
(HDGT), and heavy-duty diesel trucks (HDDT). We then combine the emission
factors with the proportion of the fleet represented by that vintage to
determine a composite emission factor for HDGT and HDDT.
Appendix A lists the detailed emission factors
for each vintage and fuel type of heavy-duty trucks. Table
8 lists the composite emission factors. For light-duty trucks, the composite
factors are based on the fleet distribution in the United States. For heavy-duty
trucks, they are based upon the fleet distribution at the border (shown
in Figure 1).
4.2 Truck emissions by time-of-day
In section 3.2, we characterized the fleet
by weight and fuel type. We combine that characterization with the total
number of trucks crossing in a time period (based on Caltrans data in Table 6) to determine the number of trucks crossing
in a time period for each weight/fuel-type category. These totals are combined
with the composite idle emission factors and the average delay for the time
period to determine total emissions by time-of-day. The total emission calculations
are only for northbound trucks on the Mexican side of the border. Additional
pollutants are emitted as the trucks wait on the U.S. side of the border,
but these are not included in our calculations.
We illustrate with the example of hydrocarbon
emissions during the 9-10 a.m. time period. During this time period 132
trucks cross the border (97% weigh over 8,500 pounds). We also know that
76.7% of the heavy-duty trucks are fueled by diesel (HDDT) and 23.3% are
fueled by gasoline (HDGT). For light-duty trucks, half are fueled by gasoline
(LDGT) and half by diesel (LDDT). The breakdown of trucks by weight/fuel-type
is as follows: 1.9 trucks LDGT, 1.9 trucks LDDT, 28.6 trucks HDGT, and 94.0
trucks HDDT. On average, a truck waits 5.48 minutes from 9-10 a.m. (last
column of Table 5). Total HC emissions are
HCLDGT = (2.0 trucks)(5.48 min./truck)(32.10 grams/hr.)(1 hr./60 min.) = 5.86 grams
HCLDDT = (2.0 trucks)(5.48 min./truck)(5.58 grams/hr.)(1 hr./60 min.) = 1.02 grams
HCHDGT = (29.7 trucks)(5.48 min./truck)(62.10 grams/hr.)(1 hr./60 min.) = 168.45 grams
HCHDDT = (98.2 trucks)(5.48 min./truck)(21.88
grams/hr.)(1 hr./60 min.) = 196.24 grams
Total HC = HCLDGT + HCLDDT + HCHDGT + HCHDDT
= 371.55 grams.
Similar calculations are performed for all
other pollutants and hourly time periods. The results are summarized in
Table 9, where the total daily emissions are given in grams and tons.
5. Discussion and Conclusions
The values shown in Table 9 underestimate
the daily emissions for two reasons. First, we could not collect information
on waiting times at the US Customs booth. If we assume that waiting times
at the US Customs booth is about the same as at the Mexican booth, then
we would double the values given in Table 9. Casual observation of trucks
passing through the Otay Mesa crossing suggest this is not an unreasonable
assumption. Second, we were unable to collect information on trucks that
arrive at the customs gate before 09:00. Even doubling the values in Table
9, still underestimates emissions because of this factor. Caltrans data
(see table 6) that 21% of daily truck traffic sometimes arrives before 09:00.
This then could add another 21% to the values in Table 9.
It is useful to put our results into the broader
context of truck emissions in the whole San Diego-Tijuana region. Emissions
estimates for heavy-duty trucks are not available for Tijuana, but do exist
for San Diego County. Table 10 gives estimated
emissions, vehicle miles traveled per day, and numbers of trucks in San
Diego County for 1996. These data were obtained from the MVEI models used
to estimate mobile emissions in California and were provided by the San
Diego Air Pollution Control District. From these data one sees that although
diesel burning trucks account for only 4% of the total VMT and 0.8% of the
total vehicles in San Diego County, they account for 80% of the PM10 and
25% of the NOx emissions.
Some data do exist for estimates of mobile
emissions in Tijuana, although they are not broken down by vehicle class.
The Instituto Mexicano de Ecologia estimates that mobile emissions from
a vehicle fleet of 241,040 in Tijuana, are (in tons/day): total suspended
particulates, 2.7; SO2, 1.7; NOx, 20.1; HC, 53.5; CO, 533 and lead, 0.1.
The figures for CO emissions appear rather high when compared to San Diego
County. Tijuana's vehicle fleet, which is only 11% the size of San Diego's,
produces emissions of CO equivalent to 71% of the value for all of San Diego
county. NOx emissions, however, scale roughly with comparative vehicle size
between San Diego and Tijuana.
We also see that the emissions from trucks
idling on the Mexican side of the border, when compared to the whole
of San Diego County, are negligible. However, as a portion of the emissions
inventory for regions adjacent to the border itself, such as Otay Mesa and
Mesa de Otay, they may be a significant contributor to particulate emissions
and NOx. It is relevant to note that recent ambient air quality monitoring
of PM10 near Otay Mesa shows higher than average reading, compared to other
sites in San Diego.
The uncertainties discussed earlier, point
out the need for further studies which would address waiting times at both
US and Mexican Customs stops and cover a greater portion of the day. Most
important, however, is the need for actual emissions testing of heavy-duty
trucks in order to obtain measured emission factors, instead of relying
on estimates based on model calculations. Without these data it will not
be possible to obtain reliable information on the contribution that Mexican
trucks make to the emissions inventory of the region.
As trade continues to grow between the US and Mexico, more trucks will cross the border and circulate on US and Mexican roads and highways. Clearly, more comprehensive and reliable information will be needed to address ways to reduce and control emissions from these trucks in the binational region.