CHARACTERIZATION OF BORDER VEHICLES AN E B ......Characterization of Border Vehicles 1The survey instruments are enclosed in the appendix. 2The customs allotted a separate space for

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CHARACTERIZATION OF BORDER VEHICLES : AN

EXPANDED BORDER VEHICLE EMISSION, M AINTENANCE

AND WILLINGNESS -TO-PAY PROFILE ALONG CALEXICO ,CALIFORNIA AND M EXICALI , M EXICO

(Project No. AQ PP96I-5)

SOUMEN N. GHOSH

L. BOHREN

D. J. M OLINA

New Mexico State University/Colorado State University/University ofNorth Texas

GOALS AND OBJECTIVES OF THE PROJECT

The overall goal of the project was to develop an expanded profile of the vehicles crossingthe U.S.-Mexico border in terms of their emissions and mechanical conditions, motorists’attitudes toward air pollution and maintenance, and their willingness to pay for themaintenance needed to improve air quality. In this phase of the research the researchersfocused on collecting data from the Calexico (US) and Mexicali (Mexico) border region asproposed in their original proposal. It also provides a willingness to pay profile of themotorists crossing this border which complements the data collected earlier for the El Paso-Ciudad Juarez region.

As outlined in the proposal the specific objectives of the project were:

• to characterize the vehicle population crossing the border between Calexico (US) andMexicali (Mexico), with data obtained on up to 500 vehicles based on a properly designedsample scheme;

• to determine the vehicle emissions and mechanical condition from data obtained on up to500 vehicles;

• to interview vehicle owners and develop an owner/vehicle maintenance and willingnessto pay profile;

• to estimate average and maximum willingness to pay for rectification of the emissionproblems of their vehicles; and

• to create a light-duty vehicle database that can be used to analyze vehicle distribution,emission characteristics.

SCERP 1996 Final Report CX 824924-01-0

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The database developed, as a part of the research can be integrated with the heavy-dutytrucking data (collected by SDSU) to assist air quality planners in determining the benefit/costof repairs and their resulting potential impacts for emission reductions along the borderregions of California-Mexico.

AN OVERVIEW OF THE AIR QUALITY PROBLEM IN THE IMPERIAL VALLEY (CALEXICO -M EXICALI ) REGION

The Imperial Valley air basin is currently in the state of non-attainment with respect to Ozoneand PM10 . Studies have indicated that this non-attainment status may be largely due to theair pollution from mobile sources and from fugitive dusts that come from the farming belt ofImperial Valley and Baja Mexicali region. To the extent the air pollution is from mobilesources, previous studies have indicated that vehicular pollution is a large factor particularlyat the border crossings. Although in recent years there has been a significant improvement inthe air quality in California, as understood underscored in the following statement by JohnDunlap (chairman of the California Air Resources Board (ARB) "California -- 1997 is abanner year for air quality," said John Dunlap, chairman of the California Air ResourcesBoard (ARB). Enjoying this clean air trend along with the rest of the state, Imperial Countyshowed remarkable improvement in air quality in 1997, highlighted by a major reduction inlung-damaging ozone, according to Imperial County Air Pollution Control. As OfficerStephen Birdsall remarks, "From 1994 through 1996 we went over the state ozone standard(.09 parts per million) an average of 76 times each year," Birdsall said. "The preliminaryfigures we have so far this year shows we exceeded the state standard on 54 days, a decreaseof about 30 percent.” ARB Chairman Dunlap attributed the state-wide clean air trend to anumber of factors: "California has the world's cleanest gasoline, the cleanest diesel fuel andthe cleanest cars and we've continued requiring automakers to reduce emissions from newcars year-after-year." Dunlap also noted that local air districts, such as the Imperial CountyDistrict, have worked to reduce air emissions from business and industry. The ARB chairmanpointed out that the clean air gains come at a time when California is celebrating the 50th

anniversary of air pollution control programs. These air quality programs date back to 1947when Gov. Earl Warren signed legislation giving California counties the authority to begintheir own pollution-control programs. The pay-off from these programs can be seen in state-wide clean air progress. A review of air quality over the past 25 years shows:

- Average ozone levels down 30%.- Carbon monoxide levels down by 60%. - Sulfur dioxide down 80%. - Ambient lead levels down by 97%

Characterization of Border Vehicles

1The survey instruments are enclosed in the appendix.

2The customs allotted a separate space for this survey.

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"These clean-air gains have been made during a period when the state's population andnumber of automobiles have skyrocketed -- 20 million more cars and 21 million more peoplesince 1947," Dunlap said. However, the ARB chairman said, California still f aces the nation'sgreatest clean-air challenge. "More than 90 percent of Californians live in areas that exceedfederal standards for ozone.” Dunlap further suggested simple measures such as keeping ourcars and trucks tuned up as steps anyone can take to help the state's efforts toward cleanerair (See www.arb.ca.gov). In the following section several issues related to clean cars in theborder region of Mexicali-Calexico are addressed.

VEHICLE EMISSION AND THE M OTORIST ATTITUDE SURVEYS

The survey was conducted between October 23 to 29 of 1996. It was conducted on the USside at the only crossing between Mexicali, Mexico and Calexico, California (since thenanother border crossing has opened). The survey had two parts1 one for collection ofemission data and under-hood inspection while the car was at an idle stage. The other partdealt with motorists’ attitudes toward air pollution control, their willingness-to-pay (WTP)for emission testing, WTP for maintenance of the vehicle and WTP for correction of theemission problems in the car along with other socio-economic and demographiccharacteristics. Two separate teams conducted the survey(s) simultaneously, one teamcollecting the emission data, the other interviewing the motorists at the customs check point2.A team of expert technicians collected the emission data. The team consisted of threetechnicians from the National Center for Vehicle Emission Control and Safety (NCVECS) ofColorado State University, in Fort Collins, Colorado. The attitudes, WTP and the socio-economic portion of the survey was collected by the students from the Imperial College in ElCentro. These students were bilingual and were trained by the researchers prior to actualconducting of the survey including pilot surveys. They were all residents of this border regionand were very familiar with the area. In all there were eight students who were used to collectthese information. However, at any time, only two students were utilized.

In order to obtain the broader possible representation, each day the survey was conducted atdifferent hours. For instance, on the first day the survey began at 5:30 a.m. Each day thesurvey was conducted for no less than five hours and no more than seven hours. On somedays, the sandstorms that are frequent at that time of the year delayed the surveys. The rangeof time used to conduct the survey was from 5:30 a.m. to 7:00 p.m. The technicians used theequipment, as shown in Picture I, to test the emissions as they checked the tampering data.


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As the NCVECS staff inspected the vehicle, the researchers and students from the ImperialCollege asked the questions on attitudes, the WTP questions and other socio-economic anddemographic characteristics. As seen in pictures two through three, a variety of vehicles weresurveyed.

Regarding the sample size, that is the number of cars and motorists to be surveyed, it wasdecided that 400 drawn at random would be sufficient to have enough statistical variationsand significance. Two important criteria were used to select the samples: traffic flow duringthe different times of the day and the types of motorists. Upon investigation with localcustoms officers and area residents it was decided that in order to best represent the vehiclefleet crossing the border, the survey needed at times to begin early in the morning andcontinue through late evenings. Although ideally a systematic random sampling design wouldhave been best (i.e., stop every 5th or every 4th vehicle) it was very difficult, if not impossible,for the customs officers to maintain that schedule. Consequently, the following technique wasused. We were able to maintain two vehicles being tested simultaneously. As soon one vehiclepulled away from the survey station, a vehicle coming through one of three custom checkstations was chosen at random. If the vehicle that was at that station did not have to befurther inspected by the custom agents (i.e. sent to another custom dock for more meticuloussearch) it would be asked to pull into our survey station. If that vehicle was not available thenthe next vehicle to go through that custom’s checkpoint was chosen. Thus, while this sampleof 400 vehicles may not be "truly" random, it is likely to be a fairly good representation of theactual fleet crossing this border. Although we collected information on 400 vehicles andmotorists, some data could not be used because of lack of clarity and/or incompleteinformation. The final number of observations (vehicles and motorists) used in this analysiswas 385.

THIS SECTION REPORTS, IN SEVERAL TABLES , CROSS-TABULATION OF VARIOUS KEY

VARIABLES AND PLACE OF RESIDENCY

In Table 1, characteristics of the population of those crossing the border and residing inMexicali, and Calexico/El Centro, or other places in California present at times some strongdifferences and while at the same time showing some strong similarities. For instance, thepopulation of Mexicali is shown to be more stable with nearly two thirds being originally fromthat city. Further evidence of this population stability is the fact that nearly 85% of theMexicali respondents (including those who are and are not originally from the region)indicated that had lived in the region for over a decade. These numbers are in sharp contrastto the Calexico/El Centro and other California population where about three quarters are notoriginally from their current place of residence and 80% of all these respondents indicatingthey had lived in their current location less than a decade. On the other hand, an example ofthe similarities lies on the fact that majority of the respondents on both sides of the border


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indicated they lived in households that fluctuate between 3 and 5 members. In addition, mostrespondents were under the age of 40.

The number of college graduates is larger among the individuals from Mexicali crossing theborder than it is for individuals from the US side who were also crossing. This particularvariable is a strong reminder that the results of this survey should not be used to represent theentire population of these communities. It is representative of only those who cross the borderand consequently it may provide a case of self-selection bias. For instance, it may be the casethat professionals from Mexicali were more likely to cross the border during the times wesurveyed than professionals from Calexico/ El Centro.

In Table 2, information regarding the vehicle is presented. As a rule, most of the individualscrossing (regardless of their place of residence) own the vehicle they were driving. It isinteresting to note that it is not just individuals in Mexico who are purchasing their vehicleson the other side of the border. For instance, nearly one of every five individuals who residein Calexico/El Centro purchased their vehicle on the Mexican side. It is also clear that mostdid not purchase their vehicle new, irrespective of their place of residence. The vehicles werefor the most part from the 1980's. Finally, it appears that irrespective of the place ofresidency, most of those crossing this border live in a household with two or three vehicles,most of which are in driving condition.

In Table 3, information regarding the physical attributes of the vehicle is examined. Labelswere an item that were commonly missing or malfunctioning among the border residents(whether from Mexicali or Calexico/El Centro). For instance, about a fourth of their vehicleshad either missing or malfunctioning emission labels. Dash labels were missing in over 5% ofthe vehicles driven by Mexicali residents and nearly 4% of Calexico/ El Centro residents.Tank labels were generally a missing item in vehicles driven by Mexicali residents (43%) andin many of those driven by Calexico/El Centro (29%). In at least three percent of the borderresidents the air cleaner was missing. Two items with air pollution implications that weremissing or disconnected (or modified) were the catalytic converter and the filler neckrestricter. Among the border residents, very close to one in five of the vehicles had a missingcatalytic converter. The vehicles driven by Calexico/ El Centro residents had the filler neckrestricter disconnected or modified nearly nine percent of the time as compared to the nearlyfour percent for those residing in Mexicali. This could be of concern since it could lead tomisfueling. Fortunately, all of the vehicles with California residents (whether from the borderor not) tested negative for plumbtesmo, and only slightly over one percent of vehicles drivenby Mexicali residents tested positive. Only about half of one percent of vehicles driven byMexicali residents had a malfunctioning exhaust system integrity (none were found among theCalexico/El Centro or other California).

In Table 4, it appears that regardless of the place of residence of the driver interviewed, themost common time frame to maintain the vehicle is three months. It also is the case that


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regardless of residency, the number one reason for maintaining the vehicle is concern forsecurity. The similarity in patterns is also found in the next two most common reasons formaintaining the vehicle (reliability and fuel efficiency respectively). Not surprisingly, theamounts generally spent on maintenance is lower for those drivers from Mexicali than thosefrom California (whether from the border or not). In fact, nearly half of the respondents fromMexicali (46%) indicated they did not spend money on maintenance.

In Table 5, data on the vehicle use is presented. It appears that nearly one in every ten,irrespective of residency, use different vehicles to drive to work and to cross the border.Those from Mexicali were more likely to use public transit than were those from California,but even then fewer than five percent were using public transit. It should be noted again, thatthis is no indication of the general use of public transit by individuals in Mexicali or inCalifornia. California drivers (whether from the border or not) were more likely to drivelonger to get to work than Mexicali drivers. However, the driving mileage was in general verysimilar for all drivers. Among the border residents, those who occasionally cross the border(that is who rarely cross it and those who do it only once a week) the patterns are verysimilar. There is a striking difference in border crossing patterns among the residents whocould be labeled frequent crossers (those who cross it several times a week and those whodo it daily). Individuals from Mexicali are more likely to cross daily, while those fromCalexico/ El Centro are more likely to cross several times a week. Mexicali drivers that wereinterviewed were more likely to use unpaved roads than were the California drivers.

Table 6 presents data concerning the individual’s perception of air pollution according to theirplace of residence. In an overwhelming majority, all respondents, regardless of their place ofresidence, believe that air pollution has caused health problems for at least one familymember. All respondents, regardless of their place of residency, are more likely to think thatMexicali is more responsible for air pollution in the region. On the other hand, Mexicalirespondents were more likely to think that cities on each side of the border were equallyresponsible than were the respondents from Calexico/ El Centro. The remainder of this tablepresents the respondent’s perception of the worst outcome produced by air pollution. Poorvisibility was the most common negative outcome of air pollution, irrespective of place ofresidence. In the last two rows of this table the percentage of individuals that ranked poorvisibility, dust, or bad smells were grouped in a category labeled esthetics. Those giving theother categories are grouped into a category labeled health. In all but two cases, the estheticscategory ranked higher than health. Overall, the perceptions of all respondents, regardless ofplace of residence, concerning problems caused by pollution are very similar in ranking thetwo top problems. All respondents placed esthetic issues as the top two rated problemscaused by air pollution. It is only when ranking the third problem resulting from air pollutionthat the respondents from Calexico/ El Centro were more likely to choose a health issue overan esthetic issue. The Mexicali respondents continue to choose an esthetic consequence intheir third ranking.


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In Table 7, a closer scrutiny regarding the individual’s perception of air pollution is presented.Nearly all respondents were aware that vehicle emissions are a cause of air pollution. In thenext two items, individuals were asked to state how much they would be willing to pay foreither an emission test or for correcting an emission problem with their vehicle. The answerof all individuals was converted to dollars using the exchange rate for 1996 published byBANAMEX. The groupings for both of these variables need some description prior to thediscussion of the table. The no answer category and the zero are assumed to have twodifferent interpretations. Those choosing not to answer are assumed to be doing so for avariety of reasons such as they don’t know, the rather not tell, or they don’t want to indicatethat they were not willing to pay for either the emission test or for correcting the emissionproblem. Those given zero as an answer are assumed to be giving a "protest vote" againsteither the emission test or for correcting the emission problem. The remaining five ranges (1-5, 6-10, 11-20, 21-40, 41 or more) were used since they provided less skewed distributions.The "protest vote" for both the emission test and the emission correction problem was greaterin Mexicali followed by Calexico/El Centro and lowest for the non-border Californians.Interestingly, border respondents were in general as likely to pay for an emission test as non-border residents, however, Calexico/ El Centro respondents were more likely to pay largeramounts for correcting the emission problem.

The next two items in Table 7 relate first to the perception regarding the ability of thegovernment in general and second to the specific task of improving the air quality. While itis true that majority of the respondents irrespective of their place of residence expressed trustin government, Mexicali respondents were in all cases less trusting of government than theCalifornia respondents. All respondents were more likely to trust the government for thespecific task of cleaning the air than in the overall activities of the government. Hence, ingeneral there appears to be a strong sense that the government is well suited to tackle theissue of air quality.

In the last portion of Table 7, respondents were asked to determine which public programswould be best to withdraw funds from and to use those moneys to fund improvement in airquality. Respondents, regardless of place of residence, chose crime prevention as the topchoice for withdrawing funds to improve air quality. The second item that was ranked firstmore often, was education in all three groups. Money from other pollution related costs(residual water drainage and drinking water) were the lowest ranked category from which therespondents felt money should be diverted to help control air pollution.

In Table 8, income and occupation characteristics according to place of residence arepresented. Nearly nine of ten of the border crossers we interviewed from Mexicali wereworking as compared to nearly three out of every four from Calexico/ El Centro. On the otherhand, nearly one of ten of those interviewed from Mexicali were students or housewives ascompared to nearly one in five from those interviewed from Calexico/ El Centro. Mexicalirespondents were also more likely to work in Calexico/El Centro than vice-versa. However,


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one in five of those residing in Calexico/ El Centro received all their income in Mexican pesos.One in four of those from Mexicali earned all their income in dollars. The income of thosefrom Mexicali was more evenly distributed than were those from Calexico/ El Centro.

In Table 9, data on idle emissions readings for CO and HC are presented. The data use thecut points of 1.2% CO and 220ppm HC (these cuts points were used in previous studies, i.e.the El Paso/Cd. Juarez study). In addition, a proxy for the California standard is alsocalculated (labeled here California Idle Standard). The reason it is a proxy and not the actualCalifornia standard is that it requires an idle and a raised reading. In this survey, only idlereadings were taken. Consequently, measuring the California idle standard was based only onthe idle cut off points of the actual California standard (found in the following URL:http://www.smogcheck.ca.gov/_private/0059t3.htm). It should be pointed out that theCalifornia idle standard is based on both the age and the weight of the vehicle. Furthermore,it should be pointed out that at the time of the survey the Calexico/ El Centro region did nothave a California emission test program.

Vehicles driven by residents from Mexicali were more likely to exceed any of the threemeasures than were those from California. In fact, these vehicles exceeded the HC readingmore than half the time and exceeded the California proxy standard nearly 70% of the time.Vehicles driven by residents from Calexico/El Centro were more likely to exceed the COreading than the HC reading. It is interesting to point out that vehicles from Calexico/ElCentro residents exceeded the California idle standard nearly fifty seven percent of the time.The vehicles from Mexicali residents exceed the California idle standard nearly seventypercent of the time. The measurements were then compared according to the license plate onthe vehicle. The vehicles with California license plates were more likely to exceed the HC andthe California idle standard readings than did the vehicles from Calexico/ El Centro residents.

CROSS TABULATION

In this section we give closer scrutiny critically to the motorists’ willingness-to-pay (WTP)for emission test and willingness-to-pay for emission correction. The way Tables 10-14 arepresented are known as the cross-tabulations where the ranges found in Table 7 for bothWTPs are cross-tabulated against several key factors. The purpose of the cross-tabulationsis to determine if a pattern appears between two factors (in this case one of the WTPs andsome other key variable). In table 10, the WTPs are cross-tabulated against the reasons formaintenance the interviewee gave for maintaining their vehicle As mentioned earlier thesurvey instrument sought the reasons for maintaining the vehicle by the owner. Five suchreasons for maintaining the vehicle were provided: (a) security, (b) reliability, (c) fuelefficiency, (d) lowering pollution, and (e) pass emission inspection. While there is no one clearreason for maintaining the vehicle the data on WTP was cross referenced with each of thesereasons. The interpretation of the data in the table is as follows: For example, 16 percent of


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the motorists who reported security is one reason they maintain their vehicles were notwilling-to-pay any amount for emission test (or a "protest vote" as explained in the discussionof Table 7). In reviewing the other "protest votes" concerning the emission test, we found that12 percent of the motorists who maintain their vehicle for reliability would also not pay foremission test. In addition, 14% of those individuals who maintain for fuel efficiency and 18%of those who stated passing the emission test as the reason for maintaining their vehicle hada "protest vote." As a more peculiar result, 13% of those individuals who stated loweringpollution level as a reason maintain for maintaining their vehicle also had a "protest vote."This last result indicates that even among those who are concerned about the pollution levelthere was a rejection of government intervention.

We note here some further findings for those who were WTP for an emission test. Thosereporting security as a reason for maintaining the vehicle, their more common WTP range wasbetween $6-10 (18.41%) and the lowest were for those WTP between $21-$41 (9.75%). Inall, if security is considered as one of the main reasons for maintaining the vehicle(s) about68% would pay for an emission testing. However, more than 50% of this 68% would pay $11or more for emission testing. Similar results are reported in this table for other reasons suchas reliability, fuel efficiency, lowering pollution and to pass emission inspection. It isinteresting to note, however, that only about 16% (61 out of 385) reported passing theemission inspection as a reason for maintaining their vehicle and about 75% of these wereWTP for an emission test.

The second part of Table 10 examines the other WTP variable, willingness-to-pay forcorrecting emission problem and cross-tabulates it with the same reasons the intervieweesstated as their reason for maintaining their vehicle. The picture is very similar to thatpresented above for the WTP for an emission test. However, of those motorists whoreported lowering pollution as one of the reasons for maintaining their vehicles, (109 out of385, or about 28%) about 74% are WTP for emission correction. Furthermore, about 31%would pay $21 or more for fixing emission problems with their cars. More curiously,however, is the fact that nearly fifteen percent (14.68%) of those claiming that they maintaintheir vehicle to lower pollution have a "protest vote" against paying for only correcting anemission problem. This appears very contradictory at first glance. Upon further reflection,it may indicate that while these individuals are willing to maintain their car in good shape(realizing this implies a reduction in pollution levels) they are not completely devoted to thereduction of air pollution if that implies an abnormal expense beyond the average maintenancecost. Another interesting "protest vote" is the nearly twenty percent (19.67) who maintaintheir vehicle in order to pass emission inspection. This implies that nearly one in five of thosewho are maintaining their vehicle with the purpose of passing an emission inspection aretotally opposed to the concept of being forced to pass vehicle inspections.

Table 11 reports a bivariate distribution of the WTPs with respect to whether their vehiclesexceed or fail to exceed a set emission levels in terms of hydrocarbon, carbon monoxide, and


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the California idle standard (describe in Table 9). A majority, 73% or 258 out of 383, of themotorists regardless of whether their vehicles exceeded the level of hydrocarbon emissions(HC>220) or not, are WTP for an emission test. Of the motorists whose vehicles exceededthe HC level, 50% are willing to pay between $11-20, 35% are WTP between $21-40, and40% are WTP $41 or more for emission test. Similar results transpired for those vehicles thatexceeded the carbon monoxide (CO>1.2) level. As far as failing to exceed the California idlestandard is concerned, the distribution of the WTPs for emission testing is somewhat differentfrom that of the HC and the CO cut of points. Larger percentage of motorists whose vehiclesexceed the California idle standard report higher WTP for emission testing. For example, 65%of motorists whose vehicles exceed the California idle standard are WTP between $11-20.Similarly, 57% and 62% of the motorists who’s vehicles exceed the California idle standardreport they are willing to pay between $21-40 or $41 or more respectively for emissiontesting.

In reviewing the WTP for correcting the emission problems several points are worth noting.For instance, a significant percentage of the motorists whose cars exceeded the stipulated HCor the CO levels reported WTP $11 or more. For example, out of 66 (about 18%) motoristswho reported their WTP to be $41 or more, 45% exceed the HC levels and 41% exceededthe CO levels. Similarly, a larger percentage of motorists reported higher WTP when theircars exceeded the California idle standard (e.g., 65% are WTP $41 or more, 53% are WTPbetween $21-40, and 55% are WTP $11-20 and so on).

Motorists’ perceptions of the effects of air pollution on their health or aesthetics and how thatis related to the WTPs for emission testing and emission correction are presented in Table 12.Six items were identified as affected by air pollution: (a) poor visibility, (b) dust, (c) badsmell, (d) dry or watery eyes, (e) dry or runny nose, and (f) irritated throat. (a) through (c)of these six items were grouped into a category called aesthetics. The other three, (d) through(f), were grouped into a category labeled health. Consequently, in this table we review howmuch motorists along the Calexico/El Centro-Mexicali border are WTP for either emissiontest or emission correction according to whether they rank the adverse pollution effects asprimarily one aesthetics or of health. Although there were a large number of individuals whodid not answer how much they are willing to pay for emission test, or they answered inprotest, (i.e., zero payment), there were many who would be WTP for an emission test. It isinteresting to note that a larger percentage of individuals who perceived pollution effects onaesthetics as more important than the effect on health are WTP more for emission tests. Forexample of those individuals who are WTP between $41 or more, 71% ranked aesthetics asnumber one, while 83% ranking aesthetics as their number one concern are WTP between$21-40, and 79% ranking it number one are WTP between $11-20 for correcting emissionproblems. This result is very consistent with our previous study along the US-Mexico borderbetween El Paso-Juarez (see Ghosh, et al., 1996).


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A controversial issue regarding willingness to pay for public goods, such as air pollutioncontrol, is the level of trust individuals have on government programs. In Table 13 the WTPsare cross-tabulated against two important variables, trust, and the place of residence. As itwas shown in Table 7 that there is in general trust in government by the border residents,however, it is interesting to note that border residents who are from Mexicali have in generalless trust in government (64.38% or 141 of 219) and are willing to pay proportionately morefor emission test (e.g., 32% would pay $11 or more for emission test) than those whoexpressed trust in government. Residents who are from Calexico/El Centro would do thesame (e.g., 60% would be willing to pay $11 or more). However, residents from otherCalifornia areas who have trust in government would pay proportionately more than thosewho did not have trust in government, (e.g., 53% would pay $11 or more as opposed to43%). Similarly, comparing residents from Mexicali with the residents from Calexico/ElCentro and from other California areas who have trust in government our data show thatMexicali residents are willing to pay less (e.g., 30% from Mexicali as opposed to 32% fromCalexico/El Centro, and 53% from other California residents are willing to pay $11 or more)for emission test. Same conclusion can be drawn for their WTP for emission correction. Thepicture is slightly different when one considers trust in government for improving air quality.In the case of Mexicali residents about 30% who have trust in government’s commitment toimprove air quality would be willing to pay $11 or more for emission test, and about 35%would pay the same amount to fix the emission problem in their cars. On the other hand 39%of the Calexico/El Centro residents with similar trust characteristics would be willing to pay$11 or more for emission test while 47% would be WTP the same amount for emissioncorrection.

The final Cross-tabulation presented in Table 14 deals with the WTPs and the motoristsperception of who is to be blamed more for air pollution: Mexicali, Calexico/El Centro orthey are both equally responsible. The three way cross tabulation is as follows: how muchmotorists are WTP given that they are residents of Mexicali, or Calexico/El Centro, or OtherCalifornia and whether they were the perceive as the most to be blamed for the air pollution:Mexicali, or Calexico/El Centro or both are equally to be blamed. About 34% of the residentswho reside in Mexicali and believe that Mexicali is to be blamed for air pollution in this borderregion are WTP $11 or more for an emission test. On the other hand, 28% of those residingin Mexicali who believe that Calexico/El Centro is more responsible are WTP about the sameamount of money for emission test compared to about 27% who believe that both areresponsible. Motorists who reside in Calexio/El Centro and believe that Calexico/El Centroare more responsible are willing to pay more. More specifically, about 71% are WTP $21 ormore for an emission tests. About 55% of the residents living in Calexico/El Centro whobelieve that both Calexico and Mexicali are responsible are WTP $11 or more. Similar WTPsfor emission correction are reported by the border residents depending on their beliefs aboutwho is responsible for air pollution. One word of caution in interpreting these numbers isnoteworthy. While the sample is not weighted to reflect the true population distribution ofMexicali, Calexico/El Centro, and other California residents crossing the border, hence it is


3 The TOBIT technique was developed by James Tobin for observed values that may haveone or two or many limit points. In our case the WTP has a lower limit, zero, however,there was no upper limit placed. Hence it was chosen to be the appropriate regressionmodel.

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not wise to generalize the relative importance of one city versus the other (i..e., Mexicali, orCalexico). However, one common observation that transpires from these cross tabulationsthat there are significant number of individuals crossing border are willing to pay for eitheremission test, or emission correction.

Finally, two charts are used to show the status of the vehicle’s neck restricter compared withmaintenance behavior and the WTP for an emission test. Recall from Table 3 thatdisconnected or modified or missing neck restricters can lead to misfueling. In Figure 1, it isinteresting to note that the majority of those who have vehicles with disconnected, modified,or missing neck restricters are also likely to give regular maintenance to their vehicle. InFigure 2, it is clear that individuals whose vehicles have their neck restricter disconnected,modified, or missing are not willing to pay for an emission test. This is not surprising sincethe vehicle would fail an emission inspection if the individual conducting the test was tobecome aware that there was an irregularly with the neck restricter.

THE STATISTICAL ANALYSES OF WILLINGNESS -TO-PAY FOR VEHICLE M AINTENANCE ,EMISSION TEST AND AIR POLLUTION CONTROL

The cross-tabulations in the previous section about the willingness-to-pay for maintenance,emission test, and correcting of the emission problems in motorists’ cars provide insightfulinformation. However, in order to further test whether there is any statistical significance ofthe variations in the WTP across respondents and to inquire which variable(s) may explainsuch variations in the WTP a behavioral model of WTP is tested using TOBIT3 technique.

1. WTPj = f(D, V, W, T, M, I, HC, CO);

WTPj is the willingness to pay for the jth activity (e.g., maintenance of the vehicle, emissiontest, and emission correction). D is a vector of demographic variables, V is a vector ofvariables that reflect the vehicle characteristics, and the vector W represent work relatedinformation. T and M represent the time of driving and the number of miles individuals drivein a week. Since the WTP is typically dependent on a person’s income, income is included inthis model. I represents individual’s household income. Last but not the least the emissioncharacteristics are included — HC is the level of hydrocarbon and CO is the amount ofCarbon monoxide that the vehicle was emitting at the time of interviews. The detaileddescription of the direction of the impact of these variables on the WTP is given in Table 15.


13

For example, for the border variable (constructed as 0 if interviewee was from Mexicali, 1 iffrom Calexico/El Centro, and 2 otherwise) a "+" that individuals who lived further away fromthe border are more likely to understand the cost of reducing pollution than those who livein the border. This may be the case since at the time this region did not have an emissioncontrol program. Similarly the variable, originally from the area they are currently living, isexpected to influence WTP in a positive manner.

A "-" sign, on the other hand implies that an increase in that variable would likely to affect theWTPs in the opposite direction. For example, if the vehicle is bought new then there is lesslikelihood for emission correction, emission testing, and maintenance except for scheduledmaintenance. In some cases there is no clear-cut a priori notion about how the variable mightaffect the WTPs, hence a " +/-" sign.

The model in equation 1 was estimated using Limdep 7.0, an econometric package designedto handle this kind of models. As mentioned above we selected the Tobit specification forestimation of the parameters of the model. Tables 16-18 reports, what is known as themarginal effects of the estimated model. The marginal effects show how amarginal/incremental change in the independent variables of the model, as described inequation 1, effect the dependent variable, in this case the WTP values.

As is evident from the reported marginal effects that not all variables have statisticallysignificant effects. This result may be attributed to several reasons: lack of a larger sample,possible multicollinearity among variables, possible heteroskedasticity since it is a cross-section data. In spite of these limitations, there are a significant number of variables that helpexplain the variations in WTPs. Some of the important ones are: border, originally from thearea, number of years lived in the area, number of individuals in the household who can drive,age, education level, where vehicle was purchased, whether the vehicle was purchased new,if the vehicle is maintained to lower air pollution, other maintenance, income, does theinterviewer drive to work, average miles driven. Interestingly enough, in all three models, theborder variable is positive and statistically significant. This result is further strengthened bythe positive sign of the variable, originally from the area. These results support our hypothesisthat those individuals who reside in the border are willing to pay more for either emission test,vehicle maintenance, or correction of the emission problems. This result tells us that borderresidents between Calexico/El Centro and Mexicali strongly feel that they have aresponsibility for the air quality in their air shed and are willing to pay to fix it. So far as theeffect of the variable age is concerned the results show that there is an inverse relationbetween age and the WTPs. In the cases of WTP for vehicle maintenance, and the WTP foremission correction it has a negative and statistically significant sign implying that as peoplegrow older they may not be willing to pay for either maintenance or correction of emissionproblems. This may be the case for two reasons: they may maintain themselves, and/or theymay buy newer vehicles that may require less maintenance, or emit less pollution. If thevehicle was purchased in the US it is more likely to be in a better shape in terms of pollution


14

control devices and better maintained, hence it is expected that this variable will have anegative impact on the WTPs. The results confirm our hypothesis. In one instance, the WTPfor maintenance, the variable, is this vehicle maintained to lower air pollution, has a negativeand statistically significant effect. This is consistent with our hypothesis. Why othermaintenance is positive and statistically significant is not quite understood. Perhaps what thisvariable does is capturing all other repair/maintenance work that are not included in the listand may outweigh the importance of regular maintenance in some cases. The effect of incomeon the WTP is counter intuitive. One reason this may, however, be the case that with higherincome individuals buy better cars and hence don't need much maintenance, testing, orcorrection of the emission problems, and thus are not willing to pay higher amounts.However, further analysis is needed to confirm such counter intuitive result. The moreindividuals drive their vehicle to work more they would be willing to pay for emissioncorrection, test, and maintenance; such are our hypotheses. In two of the three cases ourhypotheses are correct, and in the third case, WTP for maintenance, the variable is notstatistically significant. Hence, it is safe to conclude that people who depend on the vehiclefor commuting to their work place would be willing to pay more for keeping the car in abetter shape in terms of emission problems. However, our hypothesis regarding average milesdriven was not confirmed since the variable did not turn out to be positive and statisticallysignificant. However, it is negative and marginally statistically significant in only one case.Other variables such as the level of HC and CO did not turn out to be statistically significant.One reason this may be the case is that interviewees may not be aware of the fact that theirvehicles may have exceeded the HC and the CO levels hence are not WTP more. Had we toldthem after we conducted the tests they may have revised their WTPs, however, there is nostrong a priori reason to believe that such would be the case.

Although the statistical results presented in Table 16-18 are mixed in terms of corroboratingour hypotheses, one important lesson is learned in the process of estimating these models. In order to understand what motivate individuals to either put their vehicles to emissiontesting, maintenance, or correcting emission problems voluntarily, their attitudes,demographic characteristics, income and education, vehicular profiles, driving conditions mustbe thoroughly examined.

CONCLUSION AND RECOMMENDATIONS

In conclusion, our study reveals several things: (a) the border between the US and Mexicoposes interesting and challenging issues regarding non-point (vehicular) source air pollution.While a common perception is that vehicles that are registered in Mexico, in this caseMexicali, are typically more polluting (i.e., exceed California Idle Standard), our survey ofa randomly selected cross-section of motorists crossing the Calexico/El Centro-Mexicaliborder show a different result. There is only a marginal difference, 33% of the motorists’vehicles, whose residence is in Mexicali, did not exceed the California idle standard whereas


15

37% who live in Calexico/El Centro, did not exceed the same standard. However, in eithercase over 60% of the vehicles exceed the California idle standard; (b) if vehicle maintenanceon time is deemed to be a way to reduce air pollution, our survey results show that thedistribution of such maintenance across border is very similar. In other words, our study findsthat maintenance of vehicles is equally important to the residents from either side of theborder. The primary reason for vehicle maintenance, irrespective of residency is security,however, Mexicali residents are relatively more concerned about passing emission inspectionthan their counterparts from California. (c) if government is to take measures for improvingair quality in this border region, both Mexicali residents and Calexico/El Centro residents arewilling to pay about the same for either emission testing or emission correction problems intheir vehicles. However, residents from Calexico/El Centro are likely to pay slightly more thantheir counterparts from Mexicali.

Several recommendations follow from our study: to improve air quality further in thisnonattainment region, (1) a mandatory emission inspection program needs to be instituted forthe border vehicles; (2) following the inspection program, vehicles which fail to pass theCalifornia Idle standard, must seek avenues to fix emission problems; (3) individuals whocannot afford to pay for an emission correction or emission test may receive a one-time grant;(4) the border governments must allocate grant monies for qualified individuals to participatein the emission inspection and correction programs; (5) a detailed Benefit-Cost analysis mustbe conducted before actual implementation of the grant program.


16

Picture I: NECVECS Testing Equipment at the Border Crossing

Picture II: Testing for Emissions and Interviewing the Driver


17

Picture III: Interviewing the Drivers

Picture IV: Interviewing the Drivers


18

Figure I

Figure II


16

Picture I: NECVECS Testing Equipment at the Border Crossing

Picture II: Testing for Emissions and Interviewing the Driver


17

Picture III: Interviewing the Drivers

Picture IV: Interviewing the Drivers


18

Figure I

Figure II


19

Table 1Distribution of Demographic Information by Place of Residence

Item Distribution

Percentages (except for number of observations)

MexicaliCalexico/El Centro

OtherCalifornia

Are they Yes 67.05 25.30 22.78

Numbers of Yearsresiding in currentlocations

4 years or less 5 to 10 years 11 to 20 years 21 to 30 years over 30 years Observations

7.848.33

16.1823.5344.12 204

30.2636.8410.5314.477.89

76

38.3627.4015.079.599.59

73Number of peopleliving inhousehold

12345678Observations

2.2414.3516.5929.1523.328.524.041.79

223

4.8210.8421.6926.5119.288.437.231.20

79

6.4114.1017.9516.6719.2312.827.695.13

79Gender ofinterviewee

Male Female Observations

71.1728.83222

59.0440.96 83

77.2222.7879

Age ofinterviewee

Under 20 years 20 to 29 years 30 to 39 years40 to 49 years 50 to 59 years60 and over Observations

2.3422.4335.5122.439.817.48

214

3.8016.4632.9122.7813.9210.1379

4.0514.8628.3820.2713.5118.9274

What is theinterviewee’seducation level?

LessElementaryElementaryLess HighSchool High

5.3614.7310.7121.4315.63

7.2328.9212.0524.1012.05

5.0640.5111.3924.058.86


20

Table 2Distribution of Vehicle Ownership and Types by Place of Residence

Item Distribution



OtherCalifornia

Did intervieweeown the vehicle

Yes No

75.025.0

79.5220.48

81.0118.99

Where was thevehicle Purchased

Mexico California Other U.S.state Observation

70.028.641.36

220

18.7577.503.75

80

11.8484.213.95

76Was the vehiclepurchased new?

Yes No Observation

11.9888.02

217

13.7586.25

80

20.0080.52

77Vehicle Make Audi

BuickCadillacChevroletChryslerDatsunDodgeFordGEOGMCHondaHyundaiJeepLincolnMazdaMercuryMitsubishi

0.462.760.00

21.661.372.767.37

26.730.460.920.000.000.460.920.925.530.46

0.006.330.00

22.782.533.807.59

24.050.000.006.331.270.000.000.002.530.00

1.352.701.35

22.972.700.006.76

16.220.002.700.001.350.261.351.35

10.811.35


21

Table 2 (Continuation)Distribution of Vehicle Ownership and Types by Place of Residence

Item Distribution



OtherCalifornia

Vehicle Make NissanOldsmobilePlymouthPontiacToyotaVolkswagen Observations

10.603.231.843.234.5613.69

217

6.333.802.530.006.332.53

79

6.762.700.001.35

12.62.70

74Make Prior to 1970

1970-19791980-19841985-19891990-19941995-1996 Observations

2.7619.8223.5037.7911.065.07

217

3.8022.7824.0532.9113.922.53

79

5.4116.2222.9736.4913.515.41

74Number ofadditionalvehicles in thehousehold

01234 or more Observations

14.5541.3630.009.095.00

218

13.5840.7430.869.884.94

80

16.4640.5124.0515.192.53

78Number of theadditionalvehicles that arein drivingcondition

01234 or more Observations

14.1637.9032.889.135.93

217

9.8841.9830.8612.354.93

79

16.4635.4427.8516.463.79

74


22

Table 3Distribution of Vehicle Physical Attributes by Place of Residence

Item Distribution



OtherCalifornia

Emission Label FunctioningProperlyMissing ItemMalfunctioning Observations

71.8923.691.38

217

77.3316.006.67

75

83.1015.491.41

71

OriginalEquipmentCatalytic Converter

YesNoCan’t Tell Observations

87.109.683.23

217

86.0813.920.00

79

87.848.114.05

74Original Engine Yes

No Observations

94.915.09

218

92.417.59

79

91.898.11

74Exhaust Manifold Functioning

ProperlyNon-Stock Observations

97.70 2.30

217

100.0 0.00

79

100.0

0.00

74Air Cleaner Functioning

ProperlyNon-StockMissing Item Observations

94.47 2.303.23

217

91.14 5.063.80

79

98.65 1.350.0

74CarburetorType

CarburatedNon-StockFuel Injection Observations

52.531.84

45.62

219

54.435.06

40.51

79

54.050.00

45.95

74


23

Table 3 (Continuation)Distribution of Vehicle Physical Attributes by Place of residence

Item

Distribution


MexicaliCalexico/ El

CentroOther

CaliforniaDash Label Not Original

EquippedFunctioningProperlyMissing Item Observations

11.57

83.335.09

218

14.10

82.053.85

78

9.46

85.145.41

74Tank Label

Not OriginalEquippedFunctioningProperlyMissing Item Observations

10.65

46.30

43.06

216

14.10

56.41

29.49

78

9.46

74.32

16.22

74Catalytic Converter Not Original

EquippedFunctioningProperlyMissing Item Observations

10.60

70.51

18.89

217

13.92

68.35

17.72

79

9.46

74.32

16.22

74Filler Neck Resr. Not Original

EquippedFunctioningProperlyDisconnected/ModifiedMissing Item Observations

10.60

84.79 3.69 0.92

217

13.92

77.22 8.86 0.00

79

9.46

85.14 5.41 0.00

74


24

Table 3 (continuation)Distribution of Vehicle Physical Attributes by Place of Residence

Item Distribution


MexicaliCalexico/ El

CentroOther

CaliforniaExhaustSystem

StockNon-Stock Observations

95.854.15

217

98.721.28

79

97.302.70

74ExhaustSystemIntegrity

FunctioningProperlyNon-stockMalfunctioning Observations

98.461.020.51

195

98.671.330.0

75

100.00

0.000.00

74Plumbtesmo Positive

Negative Observations

98.971.03

195

0.0100.00

79

0.0100.0

74


25

Table 4 Distribution of Vehicle Physical Attributes by Place of Residence

Item Distribution

Percentages(except for number of observations)


OtherCalifornia

How often is thevehiclemaintained

weekly monthly every 3 months every 6 months yearly rarely Observations

5.6620.7552.3616.513.301.42

212

8.9719.2351.2815.385.130.00

78

13.5114.8650.0013.514.054.05

74For the following question the percentage is those who answered yes to each of thereasons. Consequently, the percentages do not add to a 100Why do youhave this vehiclemaintained?

For securityFor reliabilityFuel efficiencyTo lowerpollutionTo pass emissioninspections

72.1552.7836.67

31.3417.97

70.5152.5624.36

21.7910.26

68.3562.3438.96

27.2716.88

Who generallymaintains thisvehicle?

Self Relative Friend Dealer Mechanic IndependentGarage Observation

25.116.391.378.68

51.606.85

219

36.718.860.007.59

40.516.33

79

47.441.280.007.69

37.186.41

78Amountgenerally spenton Maintenance(dollars)

MissingNone1-56-2011-2021-4041 and more Observations

11.645.980.001.79

12.5011.6116.96

224

8.438.431.206.02

13.2533.7328.92 83

3.803.800.001.27

12.6632.9145.5779


26

Table 5Distribution of Vehicle Use by Place of Residence

Item Distribution



OtherCalifornia

How do you getto work?

This vehicleAnother vehicleBusWalkOther Observations

84.349.601.013.541.52

198

77.9410.294.411.474.41

68

76.8110.141.452.908.70

69Do you car poolto work?

YesNo Observations

40.7659.24

211

38.3661.64

73

29.8770.13

77

Do you use thisvehicle in yourwork?

YesNo Observations

51.4448.56

208

36.9463.51

74

47.2252.78

72

How much timedoes it normallytake you to driveto work? (only if they usethis or anothervehicle)

5 minutes or less6 to 10 minutes11 to 20 minutes21 to 30 minutes31 minutes or more Observations

17.4418.0235.4717.4411.63

172

18.879.43

24.5333.9613.21

53

12.9620.3729.6322.2214.81

54

What is theaverage amountof time you drivethis vehicle eachday during theweek?

30 minutes or less31 – 60 minutes61-120 minutes121-240 minutes241 minutes or over Observations

20.7727.5422.2213.5315.94

207

35.2123.9414.0812.6814.08

70

22.2226.3926.3911.1113.89

72

How many milesdo you usuallydrive per week?

0 - 50 miles51 – 95 miles96 – 155 milesover 155 miles Observations

46.3324.3115.1414.22

218

47.3721.056.5825.00

76

43.5933.333.8519.23

78


27

Table 5 (Continuation)Distribution of Vehicle Use by Place of Residence

Item Distribution



OtherCalifornia

How long haveyou been waitingto cross theborder?

None to 10 minutes11 to 20 minutes21 to 30 minutes31 to 45 minutes46 to 60 minutes61 minutes or more Observations

18.8327.8026.4615.709.421.79

223

20.0018.7530.006.25

17.507.50

80

15.1918.9921.5210.1320.2513.92

79

How often doyou drive acrossthe border?

RarelyOnce a weekSeveral times aweekDaily Observations

27.9331.9814.8625.23

222

23.0832.0525.6419.23

78

61.0416.889.09

12.99

77

How often doyou use unpavedroads or dirtroads?

RarelyOnce a weekSeveral times aweekDaily Observations

56.769.46

11.2622.52

222

75.616.109.768.54

82

67.955.136.41

20.51

78

What percentageof your drivingdo you do onunpaved streetsor roads

None1 to 10 percent11 to 30 percent31 to 99 percentAll the time Observations

23.3126.9917.1825.756.75

163

34.4321.3124.5918.041.64

61

33.9626.4111.3222.645.66

53

Tab

le 6

Dis

trib

utio

n of

Per

cept

ion

of A

ir P

ollu

tion

by P

lace

of R

esid

ence

Item

Dis

trib

utio

nP

erc

enta

ges

(exc

ept

for

num

ber

of

obse

rvatio

ns)

Mexi

cali

Cale

xico

/ E

l Centr

oO

ther

Calif

orn

ia

Do

yo

u be

lieve

tha

t ai

rpo

llutio

n ha

s ca

used

hea

lthpr

obl

ems

in a

ny m

embe

r o

fyo

ur h

ous

eho

ld?

Yes

No

Obs

erva

tions

90.9

59.

95

221

92.5

97.

41

81

87.1

812

.82

78

Who

do

yo

u th

ink

is m

ore

resp

ons

ible

for

air

pollu

tion

inth

is a

rea?

Cal

exic

o/

El C

entr

oM

exic

ali

Bo

th e

qual

ly g

uilty

Obs

erva

tions

6.33

49.7

743

.89

221

9.09

55.8

435

.06

77

9.46

50.0

040

.54

74

In t

he

fo

llow

ing

qu

est

ion

s, t

he

inte

rvie

we

e w

as

ask

ed

to

de

scrib

e w

hic

h o

f th

e f

ollo

win

g b

est

de

scrib

ed

wh

at

po

llutio

n m

ea

nt

to h

er

(him

), a

nd

to

ra

nk

the

to

p t

hre

e

Item

Mexi

cali

Cale

xico

/El C

entr

oO

ther

Calif

orn

ia1st

2nd

3rd1st

2nd

3rd1st

2nd

3rd

Po

or

Vis

ibilit

y33

.97

11.0

610

.50

25.6

47.

0412

.86

45.9

59.

096.

90D

ust

24.4

023

.12

24.3

123

.08

30.9

912

.86

12.1

628

.79

32.7

6B

ad S

mel

l12

.92

25.1

322

.10

24.3

618

.31

21.4

318

.92

28.7

910

.34

Dry

or

Wat

ery

Eye

s14

.83

19.1

08.

8417

.95

18.3

18.

5712

.16

19.7

06.

90D

ry o

r R

unny

No

se5.

2610

.05

12.1

53.

8512

.68

12.8

62.

709.

0918

.97

Irrit

ated

Thr

oat

8.13

11.5

618

.78

5.13

12.6

825

.71

6.76

4.55

20.6

9O

ther

0.48

0.00

3.31

0.00

0.00

5.71

1.35

0.00

3.45

Gro

up

ing

into

Est

he

tics

(po

or

visi

bili

ty,

du

st,

ba

d s

me

ll) a

nd

He

alth

(d

ry o

r w

ate

ry e

yes,

dry

or

run

ny

no

se,

irrita

ted

th

roa

t, o

ther)

Est

hetic

s71

.29

59.3

156

.91

73.0

856

.34

47.1

577

.03

66.6

750

.00

Hea

lth28

.740

.71

43.0

826

.93

43.6

752

.85

22.9

733

.34

50.0

1 O

bser

vatio

ns22

219

918

178

7170

7766

58

Tab

le 7

Dis

trib

utio

n of

Will

ingn

ess

to P

ay fo

r A

ir P

ollu

tion

Con

trol

and

Oth

er P

ollu

tion

Rel

ated

Per

cept

ions

Acc

ordi

ng to

Pla

ce o

f Res

iden

ce

Ite

mD

istr

ibu

tion

Pe

rce

nta

ge

s (e

xce

pt fo

r n

um

be

r o

f o

bse

rva

tion

s)

Me

xica

liC

ale

xico

/ E

l Ce

ntr

oO

the

r C

alif

orn

ia

As

you

kno

w,

the

maj

orit

y o

f the

air

pollu

tion

isca

used

by

auto

em

issi

ons

. A

re y

ou

willi

ng t

opu

t yo

ur v

ehic

le t

o a

n em

issi

on

test

if it

wer

efr

ee?

Yes

No

Obs

erva

tions

98.1

81.

8222

0

97.5

62.

4482

96.1

53.

8578

Ho

w m

uch

wo

uld

you

be w

illing

to

pay

for

anem

issi

on

test

?(d

olla

rs)

No

ans

wer

Zer

o1-

56-

1011

-20

21-4

041

or

mo

reO

bser

vatio

ns

20.9

812

.95

16.0

719

.64

13.8

48.

937.

5922

4

21.6

910

.84

3.61

24.1

018

.07

12.0

59.

64 8

3

20.2

57.

5911

.39

11.3

912

.66

16.4

620

.25

79

Wha

t is

the

max

imum

tha

t yo

u w

oul

d be

willi

ngto

spe

nd t

o c

orr

ect

onl

y th

e em

issi

on

pro

blem

?No

ans

wer

Zer

o1-

56-

1011

-20

21-4

041

or

mo

reO

bser

vatio

ns

28.5

713

.84

11.1

612

.05

9.82

12.5

012

.05

224

24.1

010

.84

2.41

10.8

422

.89

12.0

516

.87

83

20.2

58.

867.

5912

.66

6.33

12.6

631

.65

79

Tab

le 7

(C

ontin

uatio

n)D

istr

ibut

ion

of W

illin

gnes

s to

Pay

For

Air

Pol

lutio

n C

ontr

ol A

nd O

ther

Pol

lutio

n R

elat

ed P

erce

ptio

ns A

ccor

ding

to P

lace

of R

esid

ence

Ite

mD

istr

ibu

tion

Pe

rce

nta

ge

s (e

xce

pt fo

r n

um

be

r o

f o

bse

rva

tion

s)

Me

xica

liC

ale

xico

/ E

l Ce

ntr

oO

the

r C

alif

orn

ia

In g

ener

al d

o y

ou

have

tru

st in

the

wo

rk t

hat

the

gove

rnm

ent

does

?Y

esN

oO

bser

vatio

ns

64.3

835

.62

219

75.0

025

.00

80

89.7

410

.26

78

Do

yo

u ha

ve c

onf

iden

ce t

hat

the

gove

rnm

ent

can

impr

ove

the

air

qual

ity?

Yes

No

Obs

erva

tions

77.7

322

.27

220

86.0

813

.92

79

89.7

410

.26

78

In t

he f

ollo

win

g q

uest

ions,

the in

terv

iew

ee w

as

ask

ed t

o d

esc

ribe f

rom

wh

ich o

f th

e f

ollo

win

g w

ould

they

pre

fer

money

wa

s ta

ken

inord

er

to r

educe

air

pollu

tion T

he r

anki

ng r

epre

sents

the t

op t

hre

e a

reas

the in

terv

iew

ee w

ould

want

to s

ee m

oney

div

ert

ed f

rom

to

he

lp r

ed

uce

an

d p

reve

nt

air

po

llutio

n.

Ite

m fro

m w

hic

h fu

nd

s w

ou

ld b

e ta

ken

to

re

du

ce a

ir p

ollu

tion

Me

xica

liC

ale

xico

/ E

l Ce

ntr

oO

the

r C

alif

orn

ia

1st2n

d3rd

1st2n

d3rd

1st2n

d3rd

Crim

e P

reve

ntio

n38

.27

22.6

710

.20

43.0

820

.97

9.26

46.8

825

.93

10.6

4

Edu

catio

n30

.61

22.6

715

.65

29.2

330

.65

9.26

23.4

416

.67

23.4

0

Hea

lth13

.27

22.6

721

.77

12.3

122

.58

27.7

812

.50

29.6

38.

51

Res

idua

l Wat

er D

rain

age

13.2

722

.09

23.8

112

.31

14.5

225

.93

12.5

022

.22

34.0

4

Drin

king

Wat

er4.

599.

8828

.57

3.08

11.2

927

.78

4.69

5.56

23.4

0


31

Table 8Distribution of Income and Occupation by Place of Residence

Item Distribution



OtherCalifornia

What is youroccupation?

WorkStudentHousewifeOther

Observations

87.262.838.021.89

212

75.316.17

14.813.70

81

90.280.008.331.39

72Where do you

do your occupation?

Calexico / El CentroMexicaliOther Observations

21.18

73.894.93

203

66.21

13.5120.27

74

20.84 5.56

73.61

72What

percentage ofyour

Income do youearn in dollars?

Zero1-5051-99100 Observations

67.595.540.92

25.93

216

21.052.642.64

73.68

76

5.564.172.78

87.50

72Monthly

Income (pesos)0000 - 10001001 - 15001501- 20002001- 30003001- 40004001- 50005001- 60006001- 70007001- 80008000 and above Observations

19.8514.719.569.56

10.294.415.155.882.94

17.65

136

50.006.256.25

25.000.000.006.250.000.006.25

16

23.0834.6223.0811.543.850.000.000.000.003.85

26


32

Table 8 (Continuation)Distribution of Income and Occupation by Place of Residence

Item Distribution



OtherCalifornia

Monthly Income(dollars)

0000 - 10001001 - 15001501 - 20002001 - 30003001 - 40004001 - 50005001 - 60006001 - 70007001 - 80008000 and above Observations

42.1730.129.644.821.203.610.001.200.007.23

83

32.3124.6216.9213.853.081.540.004.620.003.08

65

19.7037.8816.6712.129.090.001.520.001.521.52

66


33

Table 9Distr ibution of Emissions by Place of residence and License Plate

Item Distribution



OtherCalifornia

Hydrocarbon Did notexceedExceededObservation

45.6254.38

217

62.0337.97

79

56.7643.24

74

CO Did notExceedExceededObservation

56.2243.78

217

56.9643.04

79

70.2729.73

74

Calif ornia IdleStandard

Did notExceedExceededObservation

30.2369.77

215

43.0456.96

79

39.4460.56

71

Item

Distribution


BajaCalifornia

California Arizona

Hydrocarbon Did notexceedExceeded Observation

50.2649.74

193

53.8046.20

184

33.3366.67

3

CO Did notExceedExceededObservation

55.4444.56

193

63.5936.41

184

33.3366.67

3

Calif ornia IdleStandard

Did notExceedExceeded Observation

33.3366.67

192

37.2262.78

180

33.3366.67

3

34

38

40

41

42

44

45

Documents

CHARACTERIZATION OF BORDER VEHICLES AN E B ......Characterization of Border Vehicles 1The survey instruments are enclosed in the appendix. 2The customs allotted a separate space for