1. Introduction

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 California.

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 truck traffic.

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 and Tijuana.

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 and Mexico.

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 5.

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.

4. Emissions

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

Light-Duty Trucks

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 (LDDT).

Heavy-Duty 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 as follows:

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.

  1. Total dollar volume of trade between the United States and Mexico increased by 11.6% between 1992 and 1996. However, the dollar value of Mexican exports to the US increased 107% over the same period. (U.S. Department of Commerce Statistics.
  2. The border region is defined by the US and Mexican governments as a 60 mile wide zone on both sides of the US-Mexico border (La Paz Agreement, 1983, 1983 United States-Mexico Agreement on Cooperation for the Protection and Improvement of the Environment in the Border Area)
  3. Development of Mobile Emissions Factor Model for Cuidad Juárez, Chihuahua, Prepared for the Air Quality Planning Division, Texas Natural Resource Conservation Commission, by Sandeep Kishan, Rick Baker, Meredith Fast and Chris Weyn, Radian International, August 30, 1996; Emisiones a la Atmosfera por Quema de Combustibles a lo largo de la Frontera Mexico-Texas, Gerado M. Mijía Velázquez, Emma I. Cortés Soriana and Alberto Mendoza Domínguez, Reporte:CCAM-LMA-2/95, Diciembre de 1995.
  4. US Customs, private communication, 1996
  5. Border Area Transportation: The Local, State, National, and International Connection, San Diego Association of Governments (SANDAG) INFO Publication, 1996.
  6. Statement of Mr. Rudy M. Camacho, Director, Southern California Customs Management Center before the Committee on Commerce, Subcommittee on Health and Environment, United States House of Representatives, San Diego, California, November 18, 1997
  7. San Diego Air Pollution Control District, Carl Selnik, private communication, September 10, 1997
  8. Tighter Controls Evaluated for NOx, HC and PM Emissions from Heavy-duty Engines, Environmental Fact Sheet, EPA 420-F-008a, September 1995.
  9. Based on conversations with Mexican custom officials.
  10. Observed 3,946 trucks in 8 days, or 493 trucks per day. 493 / 1600 = 30.3%.
  11. (need reference here regarding sulfur content of Mexican diesel)
  12. Northbound truck volumes were provided by Mark Baza, Transportation Planning Branch, Caltrans District 11. The volumes are for one day in 1995.
  13. A 1993 study by Caltrans District 11 estimated an average northbound delay of 17.0 minutes including both the delay on the Mexican and U.S. sides of the border. The Caltrans' estimate was based on observations from 6:00 a.m. to 6:00 p.m. during one day.
  14. February 17 (Monday) was a holiday in Mexico. Since customs are closed on holidays, some congestion on Tuesday February 18 may simply be from trucks that would have crossed on Monday.
  15. MOBILE calculates emission factors in grams per mile, but we are interested in idle emission factors in grams per hour (or minute). We make the simplifying assumption that the 2.5 mph emission factors can be applied to the entire delay time. In effect, a truck would travel 2.5 miles in an hour so idle emissions are simply the grams-per-mile emission factors multiplied by 2.5.
  16. They can easily be calculated if estimates for average delay on the U.S. side are available.
  17. San Diego Air Pollution Control District, Carl Selnick, private communication, September 1997
  18. INE web site: at http://www.ine.gob.mx/INE/documentos/indicadores/ca2_31.htm
  19. Ambient air monitoring data from the CICA web page maintained by the USEPA: http://www.epa.gov/docs/airprogm/oar/oaqps/cica/index.html