Office of Transportation EPA420-R-97-001
and Air Quality February 1997
Analysis of the Arizona
IM240 Test Program and
Comparison with the
TECHS Model
-------
EPA420-R-97-001
February 1997
of the
the TECHS
Ed Glover
Dave Brzeziniski
Assessment and Modeling Division
Office of Mobile Sources
U.S. Environmental Protection Agency
NOTICE
This Technical Report does not necessarily represent final EPA decisions or positions.
It is intended to present technical analysis of issues using data that are currently available.
The purpose in the release of such reports is to facilitate an exchange of
technical information and to inform the public of technical developments.
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Summary and Conclusions
This document describes an analysis of Arizona IM240 data collected from the state I/M
lanes during the second half of 1995 and the first half of 1996. It includes full 239 second initial test
results from more than 16,000 cars and light-trucks. Retests on failing vehicles using the full 239
second test are also available. The analysis focused on vehicles which were initially tested during
the 1995 calendar year to increase the number of failing vehicles which could finish the I/M process
in 1996. This produced a total useable sample of about 7,650 vehicles.
This document is divided into two principal sections. The first section describes and presents
the results of the analysis done on the raw data obtained from Arizona. The analysis is descriptive
in nature, but includes some calculations of I/M benefits. It presents the average emission levels
before and after I/M by model year as well as estimates of the emission reduction benefits. It also
briefly presents average test time durations, provides a failure rate distribution by pollutant type, and
touches on gas cap failure rates. The analysis also presents in a limited fashion possible seasonal
variations in average emission levels, and vehicle fuel metering technology influences on average
emission levels. However, this section only presents analysis of data that exist (i.e., first and
subsequent I/M tests). Thus, it is not possible to directly compare the data to various "what if
scenarios of No I/M or continuation of the previous I/M program.
The second section of the document compares the emission levels and I/M benefits obtained
from the data with those predicted by EPA's TECHS emission factor model. The TECHS model
is a sub-model of the overall MOBILES model, and is used to calculate the basic vehicle emission
rates and the I/M credits. Since TECHS covers only cars in full detail, only comparisons for cars are
shown. The results of the comparsion are shown by model year and for each pollutant.
This analysis produced some interesting findings. These are summarized below al'ong with
a few recommendations.
1. Based on the analysis of the Arizona IM240 data collected from July, 1995 through May,
1996, the overall VMT weighted light-duty vehicle I/M reduction for HC is: 13.7%, the CO
reduction is 15.0%, and the NOx reduction is 6.9%. In terms of mass emissions of a typical
car or truck in the fleet, the reductions are approximately 0.08 g/mile HC, 1.43 g/mile CO,
and 0.09 g/mi Nox, on average, over the entire fleet (including both passes and failures).
These are meaningful emission reductions which should improve the air quality of the
Phoenix, Arizona area.
However, part of the observed decrease in emissions of vehicles that were retested may be
natural "regression towards the mean" that would occur even if no repairs were undertaken.
This phenomenon, sometimes seen in longitudinal studies of human populations, would, of
course, only be evident in high-emitting vehicles since only those are subject to retest.
Documentation of this effect in emissions testing should be studied before attempting
to measure its importance in the current results.
-------
Because Arizona had a well regarded I/M program in previous years, these reductions
should be viewed as an incremental improvement in the program due to the implementation
of the IM240 testing rather than reductions from a No I/M baseline. Thus, they should be
smaller than the first year reductions from a new IM240 program in an area which has never
had I/M (i.e., certain cities in Ohio). Also, since the analysis uses IM240 data exclusively,
the reductions mentioned in this report should not be viewed as hypothetical reductions to
the loaded-idle type I/M program which was in force in Arizona in prior years.
2. The number of vehicles which appear to fail their final test or did not receive a final passing
I/M test appears to be substantial - about one in three. This phenonmenon is believed to be
the result of waivers and vehicles leaving the area. However, the data at hand did not
explicitly identify whether each vehicle had recently been offered a waiver.
If one assumes that all the vehicles which had failing final retest scores are repaired to the
average level of the vehicles which passed their final I/M test, then the overall I/M program
HC reduction would be 24.0%, the CO reduction would be 20.6%, and the NOx reduction
would be 9.7%. This assumption and the increased benefits may not be unrealistic, if a
sizeable number of vehicles actually left the area and no longer contribute to the VMT. To
possibly verify this assumption, the State should consider utilizing data from their remote
sensing testing to get a better estimate of the number of vehicles which have dropped out of
the testing program but still operate in the area, and the reasons why these vehicles seemingly
disappear from the program prior to a final retest.
Subsequent to this analysis, the State of Arizona investigated the issue of unresolved initial
failures using their entire database of approximately 2,000,000 vehicle tests, and information
on vehicle waivers (not available to us). They found that approximately 15 percent of the
failures could not be resolved rather than the 30 percent that we found. The difference can
be partially explained by the existence of waiver information, vehicles dropping out of the
full IM240 sample, and a longer time frame of tests (test results past May, 1996 are now
available to the State).
To possibly resolve the remaining 15 percent of the failures, the State is planning to match
the I/M records with the state license plate records from the Department of Motor Vehicles.
This should help determine whether the unresolved failures are being registered outside the
program area.
3. The I/M benefits estimated from the I/M data are quite similar in percentage terms to those
predicted by the EPA TECHS emission factor model for HC and CO. However, the
estimated benefits for NOx based on the data are smaller than those predicted by the TECHS
model. For example, for cars the data indicates a 14.3% benefit while the TECHS model
predicts a 16.9% benefit. For CO, both the data and the TECHS model predict a 16.2%
reduction. However, for NOx the data indicates a 7.6% reduction while the TECHS model
predicts a 16.7% reduction. In absolute terms for cars, the observed versus predicted
benefits are 0.08 g/mi versus 0.09 g/mi HC, 1.24 g/mi versus 1.08 g/mi CO, and 0.08 g/mi
versus 0.20 g/mi NOx.
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4. The average before and after I/M, HC and NOx fleet emission levels based on the data are
generally lower than the corresponding average emission levels predicted by the TECHS
model. For CO, the average fleet emission levels are generally slightly higher than the
TECHS model predictions.
5. A considerable portion of the failures are NOx only failures or HC only failures (this is
particularily true for late model trucks). The relatively large NOx failure percentage is
seemingly at odds with the relatively low NOx I/M benefits. Vehicles failed for NOx are not
producing sizeable NOx reductions, either because they do not actually need repair, or
because proper repairs are not being done.
6. The failure rates of light-duty trucks in model years 1981 through 1986 are considerably
lower than those of cars, although trucks are just as "dirty" on an absolute basis and relative
to their new vehicle emission standards. Consideration should be given to increasing the
stringency of the light-duty truck cutpoints to bring the failure rates of the two vehicle types
more into parity.
7. A slight seasonal variation in mean emission levels seems to exist. Average CO emission
levels tend to increase in the summer months, and decrease during the winter months.
NOx emission do just the opposite, while HC is relatively unchanged by season. The likely
cause for this phenomenon is canister loading and purging which varies on a seasonal basis
due to changing temperatures and fuels. However, this contention cannot be proved by the
available data.
1.0 Introduction
Enhanced Inspection and Maintenance (I/M) programs were implemented beginning in
January, 1995. At that time two states (Arizona and Colorado) began implementation of their
comprehensive programs. Following Arizona and Colorado, Ohio and Wisconsin also began
implemation of their Enhanced I/M programs. All four of these programs are still in operation as
of the end of 1996.
The enhanced I/M programs differ from the traditional idle test I/M programs in several
important ways. One difference is that the enhanced programs conduct the IM240 test (or the Fast-
Pass / Fast-Fail (FPFF) or Fast-Pass (FP) tests). These tests are conducted on a dynamometer which
applies a road-load and inertia weight to the vehicle and operates it over a transient driving cycle that
includes accelerations and deceleration. This type of operation more closely simulates actual in-use
driving than previous I/M tests such as the idle test or a steady-speed test. The IM240 type tests also
have a higher correlation with the new-vehicle certification test (the Federal Test Procedure (FTP))
to which all vehicles are designed. Also, the emission measurements are made using more accurate
analytical equipment that reports the results in units of mass (grams/mile). In contrast the idle type
tests are typically performed at only one vehicle operating mode - idle. In the case of Arizona the
previous I/M program also used a lightly loaded steady-speed cruise type test for 1981 and later
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Table 1.1
Vehicle
CAR
CAR
CAR
CAR
CAR
CAR
CAR
CAR
CAR
TRUCK
TRUCK
TRUCK
TRUCK
TRUCK
TRUCK
TRUCK
TRUCK
TRUCK
TRUCK
TRUCK
TRUCK
Arizona Phase-In Outpoints
Pollutant
HC
HC
HC
CO
CO
CO
NOx
NOx
NOx
HC
HC
HC
HC
CO
CO
CO
CO
NOx
NOx
NOx
NOx
Model Year
81-82
83-90
91-95
81-82
83-90
91-95
81-82
83-90
91-95
81-83
84-87
88-90
91-95
81-83
84-87
88-90
91-95
81-83
84-87
88-90
91-95
Composite
2.00
2.00
1.20
60.00
30.00
20.00
3.00
3.00
2.50
7.50
3.20
3.20
2.40
100.00
80.00
80.00
60.00
7.00
7.00
3.50
3.00
Phase 2
1.25
1.25
0.75
48.00
24.00
16.00
-
-
-
5.00
2.00
2.00
1.50
80.00
64.00
64.00
48.00
-
-
-
-
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model years. This type of test is generally recognized as a more effective test than the idle test.
However, both tests generally correlate poorly with the FTP, and the measurements are made using
less expensive and less precise equipment that only reports the emission readings in units of
concentration (% or ppm).
Table 1.1 provides a list of the phase-in cutpoints recommended by EPA, and used by the
Arizona I/M program if the vehicle completes the entire 239 second test. All of the vehicles in this
analysis received the full IM240 test. The composite cutpoints are applied against the entire test
emission measurement. The phase 2 cupoint is essentially a second way to pass test. For example,
if a vehicle fails the composite cutpoint, but passes the phase 2 cupoint, it is an overall passing
vehicle.
Now that the programs have been operating for more than one year, it is time to take a
preliminary look at the effectiveness of the enhanced I/M concept in Arizona. This was done by
analyzing a sample of available data from the Arizona I/M program, and comparing it with the
results from the EPA model. This report presents the finding from an analysis of the Arizona I/M
program data. EPA is focusing first on Arizona because of the availability of significant quantities
of full IM240 tests on randomly selected vehicles. Also, Arizona has been long recognized by EPA
as conducting one of the best centralized I/M programs.
2.0 Arizona I/M Program and Data
2.1 Arizona I/M Program
The Phoenix and Tucson, Arizona I/M program conducts approximately 800,000 IM240
equivalent tests per year. The program is biennial in structure with half of the fleet receiving the
test in the first year, and the other half receiving it in the second year. All 1981 and later model years
are tested except for the current year model year (i.e., 1996). The three pollutants HC, CO, and NOx
are measured, and a partial functional evaporative system test (i.e., gas cap check) is performed.
Later in May, 1996 a test of the integrity of the evaporative system (i.e., pressure test at the fillpipe)
was added to the program requirements. Pass / fail standards are assessed against a vehicle based
on its emission performance, and its response to the evaporative test. The pass/fail standards which
are in-force are those recommended by EPA in its guidance to states. Currently, the phase-in
standards (less stringent) are being used to reduce the impact of the new program on the motorists.
Both cars and light-duty trucks are tested. The test which is conducted is not strictly an IM240 test,
but instead is a proprietary fast-pass / fast-fail (FPFF) algorithm which may either pass or fail the
vehicle prior to the end of the 239 second IM240 sequence. This algorithm is used to speed up the
testing process without altering the actual pass/fail outcome, and can terminate a test in as little as
30 seconds, or run for the full 239 seconds. On average, the test runs about 60 seconds; however,
most passing vehicles fast-pass through the test in 30 seconds. Failing vehicles must run at least 94
seconds, and typically run more than 150 seconds. This is to ensure that vehicles get sufficient
operation to apply a pass/fail standard during phase 2 of the IM240 test which runs from 94 seconds
to 239 seconds.
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As part of its monitoring efforts, the State of Arizona conducts full EM240 tests on a
randomly selected 2 percent of the vehicle population. It also does full IM240 tests during special
studies in which the vehicles are not necessarily randomly selected. All of the vehicles in the 2
percent sample and the special studies which fail also receive full IM240 tests until they pass or are
cost-waivered. These full IM240 test data allow the problem of inconsistent test duration of the
FPFF testing to be overcome. In addition, the data also provides information on the emissions from
the two sub-IM240 cycles called Phase 1 and Phase 2 (Phase 1 is the first 93 seconds, and Phase 2
is the remaining seconds), and on the emissions from the first 30 seconds of the IM240 test. The
two different Phases may be useful in comparing and accounting for the possible effects of uncertain
vehicle preconditioning prior to the I/M test. The first 30 seconds is of interest because every 1981
and later light-duty vehicle in Phoenix and Tucson I/M program is tested at least 30 seconds. Thus,
it may be possible to utilize the results from this sample of full IM240 tests to develop a correlation
which can be applied to the entire population of data. However, this work has not currently been
completed, and is not included in this report.
2.2 Arizona I/M Data
The Arizona I/M data were purchased by EPA from the Arizona I/M testing contractor
Gordon-Darby. The data were available on a set of 18 CD-ROMs. The set contained complete
second-by-second test records on approximately 1.2 million FPFF or Full IM240 vehicle test records.
The complete set of data obtained by EPA spanned the time range of January, 1995 through June,
1996. A subset of these data contained approximately 16,000 vehicles which were either randomly
selected or part of a special study. All of these 16,000 vehicles received the full IM240 test. Data
from the months of January, 1995 through June, 1995 are not available because the random selection
feature of the program had not yet been implemented, nor were any special studies of this type
conducted.
Only the vehicles which had full IM240 tests, and were randomly recruited were used in the
analysis of Arizona's I/M program. This reduced the number of vehicles from approximately 16,000
down to 14,422. The sample used in the analysis was further restricted by considering only those
vehicles which received their initial I/M test in 1995 (retest data collected in 1996 was used). This
reduced the number of vehicles in the analysis to 7,647 vehicles. The data restriction ensured more
complete matching of the initial test with the final retest on those vehicles which failed the initial
test by requiring that every failing vehicle have at least six months to obtain repairs and pass through
the I/M process. This may seem like an overly conservative restriction; however, Tables 2.1 and
2.2 show that in some cases it may take a motorist several months and several test iterations to get
through the I/M process. For example, the average vehicle which failed the initial test and passed
the retest took 19.4 days and 2.7 iterations. The average initial test failure and subsequent waiver/no
passing test took 38.7 days and 3.5 iterations. In some rare cases the duration between the initial test
and the final available retest was more than 300 days and/or 10 iterations. However, in many of
these extreme cases the additional tests may be the result of change of ownership, and should
actually be considered new initial tests.
-------
Data on three vehicle classes (cars (LDV), light-duty trucks 1 (LDT1), and light-duty trucks
2 (LDT2)) were available. The LDT1 vehicles are typically the smaller pickup trucks and vans (i.e.,
less than 6,000 Ibs GVW), and the LDT2 vehicles are the larger delivery trucks and vans (i.e., 6,000
to 8,500 Ibs GVW). The breakdown in the 7,647 sample is as follows: LDV - 5,031 or 66%; LDT1
- 2,102 or 27%; LDT2 - 514 or 7%. The overall failure rate for the sample of 7,647 vehicles is 12.7
percent or 973 vehicles. Tables 2.3 through 2.7 provide a complete breakdown of the sample size
by test year, vehicle type, and initial test pass / fail status, (explained below) failure rate, and model
year distribution.
The initial test results on the 973 vehicles which failed their initial I/M test were matched (or
attempted to be matched) by VIN (vehicle identification number) with their final retest record. For
this analysis all intermediate test results were ignored. This matching process created three
categories plus the first category that includes the vehicles which initially passed. Table 2.6 gives
a breakdown of these categories by vehicle type.
1. Pass Initial Test - No Retest
2. Fail Initial Test - Pass Retest
3. Fail Initial Test - Fail Retest
4. Fail Initial Test - No Retest Available
These four categories represent the typical I/M outcome for most vehicles. The first category
includes the majority of the vehicles whose emissions are low and pass the test on the first try. The
second category are the I/M successes. These are vehicles which initially fail, but are sufficiently
repaired to pass a retest. The majority of the I/M benefits result from these vehicles. The third and
fourth categories are those vehicles which did not appear to have a final emission result which passed
the I/M standards. In an ideal I/M program in which no waivers were allowed, and every motorist
could be tracked down and made to participate, these outcomes would not exist. However, in a real
program these factors do exist, and have a tendency to dilute the benefits of I/M.
This analysis cannot offer a complete explanation for why many vehicles in the sample (32
percent of the failures) do not complete the I/M process with emission scores that are below the
standards. However, for the case of the #3 category, the data does show that 65 percent (see Figure
2.1 and the individual bar "Waiv-Fail") of these vehicles received their final IM240 test at the state
waiver lane, and presumably received a compliance waiver. The remaining 35 percent of these
vehicles received their final test at a non-waiver station. These two statistics are shown on the right
half of the figure under "Fail Last Known Retest". Because the test database does not contain a flag
that provides waiver status, it is not possible to definitively conclude that any of these vehicles
received waivers. The left half of Figure 2.1 provides similar statistics on vehicles which passed
their retest. For comparison, in this group only about 10 percent of the retests were done at the
waiver lane, and 65 percent were performed at the same station as the initial test.
The vehicles in category #4 have a final test status which is completely unknown. Several
possibilities exist for why the final test is missing. One possibility is that the retest result is outside
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Table 2.1
Distribution of Vehicle Test Duration
Percentile Status *
5 2
10
25
2
2
50 2
75
90
95
Mean
Max
5
10
25
50
75
90
95
Mean
Max
5
10
25
50
75
90
95
Mean
Max
2
2
2
2
2
3
3
3
3
3
3
3
3
3
All
All
All
All
All
All
All
All
All
Duration (days)
0.0
1.0
2.0
8.0
23.0
51.1
81.1
19.4
185.0
0.1
2.0
5.3
18.5
50.0
113.3
144.5
38.7
328.0
0.0
1.0
3.0
10.0
28.3
63.0
102.0
23.5
328.0
- See Section 2.2 of the text for an explanation of the
"Status" Code
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Table 2.2
Distribution of Vehicle Test Iterations
Percentile
5
10
25
50
75
90
95
Mean
Max
5
10
25
50
75
90
95
Mean
Max
5
10
25
50
75
90
95
Mean
Max
Slalua
2
2
2
2
2
2
2
2
2
3
3
3
3
3
3
3
3
3
All
All
All
All
All
All
All
All
All
Number of Tests
2
2
2
2
3
4
5
2.7
13
2
2
3
3
4
6
6
3.5
11
2
2
2
2
3
4
6
2.9
13
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Table 2.3
Testing Volume by Calendar Year (Initial Tests)
Year
1995
1996
Total
Number
7647
6775
14422
Table 2.4
Percentage
53.0%
47.0%
Model Year Distribution
Initial Tests in Calendar Year 1995
Model Year
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
Total
Number
170
186
241
424
536
669
630
559
617
574
614
591
747
750
334
5
7647
Percentage
2.2%
2.4%
3.2%
5.5%
7.0%
8.7%
8.2%
7.3%
8.1%
7.5%
8.0%
7.7%
9.8%
9.8%
4.4%
0.1%
10
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Model Year
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
Total
STATUS
1
2
3
4
ALL
Table 2.5
Model Year Distribution
Initial Tests in Calendar Year 1995
CAR
119
130
167
289
377
434
434
378
438
381
435
377
462
408
200
2
5031
LDT1
39
41
57
102
128
182
166
156
150
162
153
172
229
271
91
3
2102
Table 2.6
LDT2
12
15
17
33
31
53
30
25
29
31
26
42
56
71
43
0
514
Distribution of the Sample by
Test Status and Vehicle Type
CAR
4321
460
145
105
5031
LDT1
1905
143
30
24
2102
LPT2
448
55
5
6
514
ALL
170
186
241
424
536
669
630
559
617
574
614
591
747
750
334
5
7647
ALL
6674
658
180
135
7647
11
-------
MYR
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
ALL
Table 2.7
I/M Failure Rate by Vehicle Type
CAR
54.6%
41.5%
49.7%
43.6%
28.4%
22.8%
15.2%
8.7%
4.1%
4.2%
5.3%
3.4%
1.1%
0.2%
0.5%
14.1%
and Model Year
TRUCKS
5.9%
12.5%
23.0%
28.9%
23.3%
15.7%
13.3%
19.3%
10.1%
4.7%
3.9%
8.4%
2.8%
0.3%
0.7%
10.1%
ALL
40.0%
32.8%
41 .5%
38.9%
26.9%
20.3%
14.6%
12.2%
5.8%
4.4%
4.9%
5.2%
1.7%
0.3%
0.6%
12.7%
12
-------
of the 2% sample. In other words, the vehicle did receive a final state I/M test, but it was not a full
IM240 test. The existence of this outcome was checked by searching the entire program database
for the existence of these vehicles. In very few cases were they found with a passing FPFF test to
indicate that they had somehow dropped out of the 2% sample. Another possibility is that upon
failure of the I/M test, the vehicle owner decided to sell or register the vehicle outside of the program
boundaries. If this were the case, the I/M record would not exist. However, the overall State
registration records should reflect this outcome. Another possibility, although somewhat remote,
is that the vehicle is still in the I/M process, and has not yet received its first retest or its retest was
receded as an initial test. This outcome would require at least a six month time frame between the
first I/M test and the retest.
3.0 Analysis of the Arizona I/M Data
3.1 Calculation of I/M Reductions
The percent reduction (Benefit) in emissions due to I/M was determined for each model year
and pollutant. It was done by summing the before and after I/M HC, CO, and NOx emissions from
each vehicle and then taking the difference, and the percent difference. The calculations were done
separately for each model year, and vehicle type (LDV, LDT1, LDT2).
Mathematically, the equation is:
Benefit = [SUM(ip) + SUM(if)] - [SUM(ip) + SUM(rp) + SUM(rf) + SUM(irm)] (eq 1)
The benefit can be expressed as a percentage by:
Benefit% = Benefit / [SUM(ip) + SUM(if)] (eq2)
where:
SUM(ip) - Sum of the initial test emission from vehicles which pass the initial test.
SUM(if) - Sum of the initial test emission from vehicles which fail the initial test.
SUM(rp) - Sum of the retest emissions from vehicles which pass the retest.
SUM(rf) - Sum of the retest emissions from vehicles which fail the retest.
SUM(irm) - Sum of the initial test emissions from vehicles with no retest
When these equations are applied to the database of 7,647 vehicles, the results shown in
Figures 3.1 through 3.6 are obtained for each model year and vehicle type. In each of these figures,
the individual model year benefits are shown as percentage of the initial test levels. For example in
Figure 3.1, the HC I/M reduction is approximately 25 percent for the 1981 model year. The
composite reduction for all of the model years of a given vehicle type and pollutant are also shown
as an insert in Figures 3.1 through 3.6. These results are weighted by both Arizona model year
vehicle miles travelled (VMT) and registration distributions. The VMTs which are used for each
of the 1981 and later model years are average values from the MOBILES model. Only the 1981 and
13
-------
Figure 2.1
I/M Station Switching Versus Test Outcome
100.0%
90.0%
80.0%
70.0%
„ 60,0%
0)
O)
CO
jjj 50.0%
u
40.0%
30.0%
20.0%
10.0%
0.0%
Fail Last Known Retest]
Same-Pass Diff-Pass Waiv-Pass Same-Fail
Station Type
Diff-Fail
Waiv-Fail
-------
later model years are included, thus ignoring the pre-1981 vehicles in this analysis. The effect of
the model year weighting factors is to give the newer model years more contribution to the composite
reduction for each vehicle type. This is necessary because newer vehicles on average accumulate
more mileage in a given period than older ones.
The overall I/M reduction for each pollutant is calculated by weighting the composite
reductions for each of the three vehicle types together. Other vehicle types such as motorcycles and
heavy-duty gas trucks are excluded from this calculation since they are not part of the IM240
program. Thus, this analysis does not consider the impacts of the I/M program on the overall mobile
source inventory in Arizona, but only on the three vehicle classes which are covered by I/M, and
where IM240 data are available. However, these three classes (LDV, LDT1, and LDT2) make up
the majority of the VMT and emissions contribution. For this analysis, the LDT1 and LDT2
categories were combined into one group called LDT. The overall weighed reduction from the I/M
program is shown in Table 3.1 for each pollutant. The overall VMT weighted program HC
reduction is 13.7%, the CO reduction is 15.0%, and the NOx reduction is 6.9%.
3.2 Average Vehicle Emissions
The average vehicle emissions before and after I/M are shown in Figures 3.7 through 3.9 for
HC, CO, and NOx as function of model year for the LDVs. These figures compare the average test
emissions from vehicles which initially pass the I/M test with retest emissions from vehicles which
initial fail but pass the retest (category 1 vs category 2) and those which do not pass the final retest
(category 3). The emissions shown as category #1 in the figures are initial test results. Those labeled
as category #2 or #3 are retest emissions.
The chart shows that the repair technicians in Arizona are on average not returning the failing
LDVs upon repair to the level of the initial passing vehicles. This is mostly because of the
considerable amount of likely waiver vehicles which continue to fail (category #3). However, even
the category #2 vehicles (pass the retest) are not being returned on average to the levels of the
passing vehicles. However, the difference is fairly small between the emission levels of vehicles
which pass the initial test, and the emission levels of vehicles which pass their retest. An analogous
analysis of the LDT's was also performed, but the results are not shown in graphical form. The truck
curves exhibited the same general relationship as a function of test status as the car curves (i.e., the
failing trucks are not returned to the average levels of the initial passes). However, the average
emission levels from all of the trucks curves were higher than the car curves.
Figures 3.10 through 3.12 compare the average emissions before and after I/M for the
vehicles which pass the retest with those which fail the retest. Two observations can be made
regarding these figures: (1) The retest emissions from the vehicles which continue to fail are lower
than their initial emission levels. This suggests that waiver vehicles do receive some useful repairs,
and do account for some small part of the I/M benefits; although, the possibility exists that some
of this reduction is the result of the phenonmenon known as regression to the mean. (2) The initial
emission levels of vehicles which fail their retest and are likely waivered (category 3), are generally
higher than the initial emission levels of vehicles which pass their retest (category 2). This suggests
15
-------
Figure 3.1
I/M Exhaust HC Benefits from LDV Vehicles
50.0%
45.0%
40.0%
35.0%
0.0%
[Overall Reduction = 14.3%
[•HC Benefits]
1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995
Model Year
-------
Figure 3.2
I/M CO Benefits from LDV Vehicles
O
TJ
0>
OC
50.0%
45.0%
40.0%
35.0%
30.0%
25.0%
£ 20.0%
O
15.0%
10.0%
5.0%
0.0%
Overall Reduction = 16.2%|
[•CO Benefits I
1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995
Model Year
-------
Figure 3.3
I/M NOx Benefits from LDV Vehicles
00
C
o
50.0%
45.0%
40.0%
35.0%
0.0%
Overall Reduction = 7.6%
[•NOx Benefit j
1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995
Model Year
-------
Figure 3.4
I/M Exhaust HC Benefits from LDT1 and LDT2 Vehicles
50.0%
45.0%
Overall Reduction = 12.4%
0.0%
1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995
Model Year
-------
Figure 3.5
I/M CO Benefits from LDT1 and LDT2 Vehicles
50.0%
45.0%
40.0%
35.0%
NJ
O
0.0%
Overall Reduction = 12.2%
ICO
1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995
Model Year
-------
Figure 3.6
I/M NOx Benefits from LDT1 and LDT2 Vehicles
50.0%
45.0%
40.0%
35.0%
3 30.0%
25.0%
20.0%
15.0%
10.0%
5.0%
0.0%
Overall Reduction = 5.4%
I NOx
1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995
Model Year
-------
that the vehicles which are waivered or missing their retest are higher emitting and likely to be more
difficult to repair. It also tends to invalidate the assumption that the lost emission reduction from
a waivered failure is equivalent to the achieved emission reduction from a non-waivered failure. The
results from a similar analysis of the truck data (not shown) produced results which were analogous
to the cars.
Table 3.4 shows the average emission levels for all of the vehicles before and after I/M.
These average emission levels are weighted by the four levels of test status and by model year. The
test status weighting are based on the actual percentage of each of the four test status conditions in
the sample. The model year weighting factors are the MOBILES travel fractions. The VMT
fractions between cars and trucks shown in the table are used to calculate the overall average before
and after emission levels in units of grams per mile. The results show the average reduction in HC
emissions is about 0.08 grams/mile, the CO reduction is about 1.43 grams/mile, and the Nox
reduction is about 0.09 grams/mile. Also, the results show a sizeable difference between the
average emissions of cars and trucks both before and after I/M. For comparison, the analogous
average emission levels based on the TECHS model are shown for cars at the bottom of Table 3.4.
Except for Nox emissions, the average emission levels and reductions are reasonably close or higher
than those predicted by the TECHS model. For example, the average TECHS HC reduction is 0.09
g/mi, and the average CO reduction is 1.08 g/mi.
3.3 Alternative Calculation of I/M Reductions
Equations 1 and 2 produce a somewhat conservative estimate of the I/M benefits because
they assume that all of the category #3 vehicles do not receive any further additional repair, and that
category #4 vehicles do not receive any repair. This may be an unjustified assumption if the final
retests were actually performed, but are not present in the database. This could potentially be the
case since subsequent to the analysis, a few additional passing retests (six vehicles were identified)
were located in the overall Arizona database which contains all of the vehicles which were tested
instead of a sample which received only the full IM240 test. These retests were not part of the
analysis dataset which received the full IM240 because they were coded as initial tests. The benefits
of the program could also be understated slightly if some of the category #4 vehicles were sold
outside of the program area, and thus no longer contribute to the VMT and emission inventory of
the program area.
To account for the possible scenario that many of the category #3 and #4's were actually
repaired or sold outside of the program, Equation 1 was modified by assuming that the category #4
vehicles and the category #3 vehicles which did not receive their final IM240 test at the waiver lane
were repaired to the average level of the category #2 vehicles. The same assumptions for model year
distributions and VMT that were used in the previous scenario were used again. If these
assumptions are made, the the overall I/M benefits are 24.0 percent for HC, 20.6 percent for CO,
and 9.7 percent for NOx. The overall results for this scenario and the results for the individual
vehicle types are shown in Table 3.2.
22
-------
Table 3.1
I/M Reductions - Actual Results
Vehicle Type
CAR
LOT
ALL
VMT
0.703
0.297
100.0%
If All Vehicles Were Re
Vehicle Type
CAR
LOT
ALL
VMT
0.703
0.297
100.0%
H£
14.3%
12.4%
13.7%
Table 3.2
I/M Reductions
GO.
16.2%
12.2%
15.0%
NOx
7.6%
5.4%
6.9%
paired to the Average After Repair Level
MC
26.3%
18.5%
24.0%
Table 3.3
I/M Reductions
£0.
22.0%
17.2%
20.6%
NOx
11.1%
6.5%
9.7%
If All Vehicles Were Renal red to the Averaae Initial Passlno Level
Vehicle Type
CAR
LOT
ALL
YMT
0.703
0.297
100.0%
H£
30.4%
22.8%
28.1%
GO.
27.4%
20.6%
25.4%
Ufix
12.8%
8.7%
11.6%
23
-------
Type VMT
CAR 0.703
LOT 0.297
ALL 100.0%
I Table 3.4
i
I
Average Emissions Before and After I/M I
I
H£
Before I/M
0.52
0.90
0.63
H£
After I/M
0.44
0.80
0.55
00.
Before I/M
8.21
13.80
9.87
GO.
After I/M
6.97
12.30
8.44
NOx
Before I/M
1.05
1.72
1.25
NOx
After I/M
0.97
1.62
1.16
24
-------
Figure 3.7
Average LDV HC Emissions - Retest vs Initial Test Results
4.00
3.50
NJ
Ol
RETEST: Fail Initial / Fail Retest
RETEST: Fail Initial / Pass Retest
•Init Status 1
- Final Status 2
- Final Status 3
1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996
Model Year
-------
Figure 3.8
Average LDV CO Emissions - Retest vs Initial Test Results
80.00
70.00
RETEST: Fail Initial / Fail Retest
RETEST: Fail Initial / Pass Retest
•Init Status 1
• Final Status 2
• Final Status 3
10.00
0.00
1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996
Model Year
-------
Figure 3.9
Average LDV NOx Emissions - Retest vs Initial Results
7.00
RETEST: Fail Initial / Fail Retest
RETEST: Fail Initial / Pass Retest
•Init Status 1
• Final Status 2
• Final Status 3
0.00
1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996
Model Year
-------
Figure 3.10
Average LDV HC Emissions Before and After I/M
4.50
4.00
' Init Status 2
• Final Status 2
- -A - Init Status 3
- *- Final Status 3
1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996
Model Year
-------
Figure 3.11
Average LDV CO Emissions Before and After I/M
N)
VO
80.00
70.00
"^—Init Status 2
•*~ Final Status 2
*--Init Status 3
* - - Final Status 3
0.00
1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996
Model Year
-------
Figure 3.12
Average LDV NOx Emissions Before and After I/M
7.00
0.00
• Init Status 2
• Final Status 2
- - * - - Init Status 3
-•*-- Final Status 3
1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996
Model Year
-------
The likely maximum I/M benefit given these outpoints, and vehicle fleet can also be
calculated by assuming that all of the initial failing vehicleMre repaired to the average level of the
vehicles which passed their initial test. This is a reasonabtaissumption of maximum benefits at [he
current pass/fail standards since it is unlikely that repair te«fmicians will be able to reduce vehicles
emissions on average below those of initial passing vehicles. If this assumption is made, the
maximum benefits for the Arizona I/M program for HC, CO, and NOx are 28.1 percent, 25.4
percent, and 11.6 percent, respectively. Table 3.3 summarizes the overall benefits for this scenario
for each of the three vehicle types.
3.4 IM24Q Failure Rates
Figure 3.13 shows the failure rate by model year and pollutant for the LDV's. Figure 3.14
shows the failure rates for the combined sample of LDT1 and LDT2 vehicles (LDT). The figures
are stacked bar types with the failure rates for each individual pollutant stacked on top of each other.
The sum of the individual pollutants is the overall failure rate for a given model year. Several points
are evident from Figures 3.13 and 3.14. The first is a dramatic decrease in LDV failure rate after the
1988 model year, and LDT failure rate after 1989. For example, for LDVs, between the 1988 and
1989 model years, the failure rates fall from about 8 percent to about 4 percent, and stay fairly low
from 1989 onward. This is contrasted with an ever rising failure rate from 1988 back to 1981. The
lower failure rate on the newer cars is even more apparent when the lower cutpoints (more stringent)
for the 1989 and later vehicles are factored into the situation. The reason for the lower failure rates
on the 1989 and later cars versus the/newer cars may be the widespread introduction of ported fuel
injection starting in the 1988 to 1989 model year. For LDT vehicles heavy penetration of ported fuel
injection may have occurred a little* later. In other limited, but detailed studies, ported fuel injection
has generally been shown to have lower emissions and more durability than previous technology.
Another possibility is that it simply takes about 7 years of operation before vehicles deteriorate
sufficiently to begin failing at higher rates, and that after that point is reached the failure rates climb
steadily each year. Finally, it may be that under the previous Arizona I/M program, vehicles five
years and younger were better repaired when needed than were older vehicles.
Another point which is evident from the two figures is the considerable difference in failure
rates between light-duty trucks and cars on all of the older model years (1986 and older model years).
For example, the failure rate on the 1981 through 1983 model year cars is around 50 percent,
whereas for trucks it is less than 20 percent. In addition, the 1981 through 1982 truck failure rates
are lower than the rates for several succeeding model years, whereas the average emission levels for
these two model years are generally higher. The average emission levels of cars and trucks are
shown in Figures 3.23 through 3.27 for all three pollutants. These corresponding lower failure rates
translate into smaller I/M benefits, and occur in model years which generally should produce fairly
substantial I/M benefits. This sizeable difference in failure rates and benefits is likely the result of
the differences in cutpoints between the two vehicle types. For example, the phase-in HC cutpomt
for 1981 and 1982 model year cars is 2.00 g/mi, whereas the corresponding truck cutpoint is 7.50
g/mi. The other pollutant cutpoints also have similar differences.
31
-------
Figure 3.13
Arizona LDV I/M Failure Distribution by Pollutant
60.0%
50.0%
40.0%
QC 30.0%
3
20.0%
10.0%
0.0%
• Fail All
BFail CO & NOx
BFailHC&NOx
HFailHC&CO
• Fail NOx Only
BFail CO Only
B Fail HC Only
81 82 83 84 85 86 87 88 89 90
Model Year
91
92
93
94
95 ALL
-------
Figure 3.14
Arizona LDT1 and LDT2 I/M Failure Distribution by Pollutant
60.0%
Based on 2,616 Trucks
0.0%
81
82
83 84
85
86
87 88 89 90
Model Year
91
92 93
94
ALL
• Fail All
HFailCO&NOx
BFailHC&NOx
BFail HC & CO
• Fail NOx Only
BFail CO Only
G Fail HC Only
-------
Figures 3.13 and 3.14 also show the breakdown of the sample by pollutant failure mode. The
largest pollutant failure categories are the NOx only failures and the HC only failures. Combined
NOx and HC failures are also somewhat common. Also, for late model trucks, the NOx only failures
make up a very large percentage of the overall failures. The high NOx failure rates (NOx only and
NOx and HC) are surprising given that the likely overall NOx reduction benefit is only in the 5 to
10 percent range.
3.5 Gas Cap Failure Rates
Figures 3.15 and 3.16 show the results of Arizona's I/M gas cap test in terms of failure rates,
and the percentage of failures which are apparently not retested or repaired. Because FPFF was not
a factor in the gas cap test, the entire sample of over 400,000 vehicle tests performed from June,
1995 through December, 1995 were analyzed. The results in Figure 3.15 show the failure rates by
model year to be fairly small. They typically range from about 0.5 percent for new cars and trucks
up to about 6 percent for 1981 trucks. These results seem reasonable given the fairly simple and
durable nature of a gas cap, and the lack of real incentives to tamper by the motorist. The results also
show that the truck failure rates are consistently higher than the car failure rates.
Despite the low failure rates, substantial HC emission benefits from repair are possible due
to the relatively large emission contribution that a vehicle with a bad or missing gas cap can make.
Unfortunately, the current tests are functional type tests and do not produce emission level type
information. Thus, the size of the HC emission reductions cannot be determined from the data in
a manner analogous to the exhaust emission tests.
Figure 3.16 shows the percent of gas cap failures which are not retested or repaired. The
percentages are quite high considering that the repair is quite simple, obvious, and inexpensive. The
likely reason for the high rates is that many of these vehicles also failed the exhaust test, and the
owner is not retesting the vehicle because of exhaust emission component problems and perhaps sold
the vehicle outside the program, put it up on blocks, scrapped it, etc. Some evidence for this can be
seen in the 1981 through 1984 truck non-repaired rates in Figure 3.16. These seem to follow the
same shape as the exhaust failure rates rather than the gas cap only failure rates as one would expect.
3.6 Seasonal Differences in Emission Levels
Figures 3.17 through 3.19 show the mean monthly HC, CO, and NOx initial test emission
levels for cars. Each figure has four curves. The one labelled HC240 (or CO240 or NOx240)
represents the results from the full 239 second test. The figure labelled HC30 are the results from
the first 30 seconds of the IM240 test. The Phase 1 and Phase 2 curves represent the first 93 seconds,
and the remaining 146 seconds, respectively. The individual Phase 1 and 30 second results are
shown because they are generally more or less suseptible to cold start or other preconditioning
problems than the full IM240 test. Thus, they may exhibit more or less variation due to seasonal
ambient temperature changes than the full EM240 test.
34
-------
Figure 3.15
Gas Cap Failure Rate in the Arizona I/M Program
10.0%
9.0%
8.0%
7.0%
- 6.0%
-------
Figure 3.16
Percent of Gas Cap Failures NOT Repaired / Retested
25.0%
22.5%
20.0%
17.5%
15.0%
CO
DC
12.5%
10.0%
7.5%
5.0%
2.5%
0.0%
Illlll I
• Cars
S Trucks
81 82 83 84 85 86 87 88 89 90 91 92 93 94 95
Model Year
All
-------
Examination of the three figures shows that the average HC emissions show the least amount
of variation by month or season of the year. In fact, for HC emissions there appears to be no definite
pattern of increasing or decreasing emission levels versus month of test. On the other hand, the CO
emissions show a more definite trend of higher CO emissions during the summer and lower
emissions during the winter. The brief 30 second test results are particularily dramatic. The opposite
results are obtained from the NOx curves which shows slight increases during the winter months and
decreases during the summer months.
The exact reasons for the seasonal emission patterns cannot be conclusively determined from
these data. However, the most likely explanation includes higher canister vapor loading and purge
during the hot summer months which can lead to: richer air/fuel ratios, CO emission spikes, and
potentially lower NOx emissions. The seasonal emission trends may exist despite a seemingly
opposite seasonal pattern in gasoline volatility. While winter RVP is higher than summer RVP, the
temperature effect may be stronger than the RVP effect. The level of oxygen in the fuel OF the RVP
(volatility) of the fuel maybe changing on a monthly or seasonal basis, and should have an impact
on emission levels. Another contributing factor may be that oxygenated fuel use in the winter
lowers fleetwide CO emissions. The limitations of the NOx correction factor may also have a
seasonal effect on the NOx emissions. The correction factor is only applicable to temperatures at
or under 86F. However, many summer months in Arizona have temperatures which exceed 86F, and
in these cases the correction for 86F is used. Thus, this may have an effect on the reported NOx
emissions and failure rates.
One explanation which does not seem consistent with the data is that the vehicles are poorly
preconditioned for their emission test in the wintertime because of colder ambient temperatures and
more vehicles in cold start mode immediately prior to their emission test. For example, at some busy
stations during the end or beginning of the month testing rush, some vehicles may idle longer in line
prior to their test. If the ambient temperatures are lower, then catalysts and engines may also be at
slightly lower temperatures, and produce higher emission levels at the beginning of the test. If this
were the case, and if its emission effect were substantial, the CO emission levels (particularily the
30 second test) should rise during the winter and fall during the summer. The opposite actually
occurs.
3.7 Comparison of Emission Levels of Carbureted Versus Fuel Iniected Vehicles
A propertiary VIN decoder purchased from Radian Corporation was used to decode the
individual vehicle VINs and segregate them into either fuel injected or carbureted classifications.
The vehicles were also segregated into car and truck groups. This process permitted an investigation
of whether fuel metering type has a significant effect on average emission levels.
Figures 3.20 and 3.21 show the distribution of fuel metering type for cars and trucks. The
results show the clear and overwhelming penetration of fuel injection technology into the fleet
between 1981 and 1990. For cars, fuel injection technology had completely penetrated by 1990 and
for trucks it was 1991. The crossover points occurred during the 1984 through 1985 time frame with
cars penetrating slightly earlier, but trucks penetrating slighly faster once they had begun.
37
-------
Figure 3.17
2.50
Comparison of Mean HC Emissions versus Test Date
Cars Only
•HC240
•HC30
•HC BAG1
•HC BAG2
Test Date
-------
Figure 3.18
Comparison of Mean CO Emissions versus Test Date
Cars Only
40.00
"CO240
•CO30
•CO BAG1
•CO BAG2
Test Date
-------
Figure 3.19
Comparison of Mean NOx Emissions versus Test Date
Cars Only
•NOx240
•NOx30
•NOx BAG1
•NOx bAG2
Test Date
-------
Figure 3.20
100.0%
0.0%
Distribution of Fuel Injected vs Carbureted Cars
Initial Arizona IM240 Tests
1981 1982 1983 1984 1985 1986 198/ 1988 1989 1990 1991 1992 1993 1994 1995
Model Year
•%Cart>
•% Fl
ALL
-------
Figure 3.21
100.0% O
0.0%
Distribution of Fuel Injected vs Carbureted Trucks
Initial Arizona IM240 Tests
-%Carb
•% Fl
1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995
Model Year
ALL
-------
Figure 3.22
3.50
Comparison of HC Emissions of Fuel Injected vs Carbureted Cars
Initial Arizona IM240 Tests
•HCCarb
•HCFI
0.00
1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995
Model Year
-------
Figure 3.23
3.50
3.00
0.50
0.00
Comparison of HC Emissions of Fuel Injected vs Carbureted Trucks
Initial Arizona IM240 Tests
-HCCarb
•HCFI
1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995
Model Year
-------
Figure 3.24
Comparison of CO Emissions of Fuel Injected vs Carbureted Cars
Initial Arizona IM240 Tests
50.00
45.00
-
01 (J
5.00
0.00
•CO Garb
•COFI
1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995
Model Year
-------
Figure 3.25
Comparison of CO Emissions of Fuel Injected vs Carbureted Trucks
Initial Arizona IM240 Tests
50.00
45.00
£ 2 25.00
0.00
-COCarb
•CO Fl
1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995
Model Year
-------
Figure 3.26
4.00
3.50
"a)
0.00
Comparison of NOx Emissions of Fuel Injected vs Carbureted Cars
Initial Arizona IM240 Tests
-NOxCarb
•NOx Fi
1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995
Model Year
-------
Figure 3.27
4.00
0.50
0.00
Comparison of NOx Emissions of Fuel Injected vs Carbureted Trucks
Initial Arizona IM240 Tests
-NOxCarb
•NOx Fi
1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995
Model Year
-------
Unfortunately, the Radian VIN decoder does not reliably decode the vehicles into finer fuel injection
category such as ported fuel injection and throttle body fuel injection. However, it is believed that
the vast majority of the late model vehicles are ported fuel injection types while many of the early
1980's fuel injection cars were throttle body technology. It should also be noted that the first fuel
injected models to be introduced and the last carbureted model to be produced may have been
peculiar cases. Thus, the comparison between fuel injected and carbureted is best for the model
years with a reasonable percentage of each. Sample sizes are also better for these middle model
years.
Figures 3.22 and 3.23 show surprizingly similar HC emission results between fuel injection
and carbureted vehicle technology during the years in which overlap of the two technologies existed.
For cars the agreement between fuel injection and carbureted average emission levels is nearly
identical. The difference is larger for trucks; however, even this difference is typically only about
0.5 g/mi HC with carbureted trucks being higher. The results are somewhat surprising because it
has long been assumed that fuel injection technology was clearly superior to carbureted technology
in terms of HC emission control.
Figures 3.24 and 3.25 show the comparison between fuel injected vehicles and carbureted
vehicles in terms of CO emissions. The results for both cars and trucks show sizeable differences
between the two types with the fuel injected vehicles having lower emissions. The differences are
particularly striking for trucks except for the 1990 model year which had a comparatively small
sample of trucks. The sizeable differences in average CO emissions between fuel injected and
carbureted technologies are expected, and are likely due to the more precise fuel control offered by
the ported fuel injected vehicles versus the carbureted.
The NOx emission results shown in Figure 3.26 and 3.27 are also generally similar for both
fuel injected and carbureted cars and trucks for the model years with good numbers of both types.
4.0 Comparsion of Arizona I/M Results with MOBILES/TECHS Projections
The previous section presented the calculated emission reductions from the Arizona I/M
program. This section compares the results from the Arizona IM240 data with those projected by
the EPA emission models. This comparison is not intended be a formal, and rigorous evaluation of
the Arizona 1/M program as part of the SIP process. Instead, it should be viewed more as a
qualitative comparison of the program versus the EPA models. It is as much an investigation of the
realism of the EPA models as of the Arizona I/M program.
The most appropriate EPA emission models in which to compare the data against are the
MOBILES and TECHS series of models (i.e., MOBILESa, MOBILESb). MOBILES is a computer
model which projects vehicle emission rates for a given broad location based on a set of input
parameters. These inputs include registration and VMT distributions, types of fuel, average
temperatures, average speeds, types of control programs, and many others. The output is an overall
49
-------
Figure 4.1
I/M Concept Schematic
1995 NO I/M
2.276 g/mi HC
1996 NO I/M
2.574 g/mi HC
1995
After Loaded/ Idle I/M
1.655 g/mi HC
1996
IM240 Baseline
1.953 g/mi HC
1996
After IM240
1.542 g/mi HC
50
-------
emission factor (projection) for a given area. The TECHS model is a sub program of the MOBILES
model. It is used to generate the individual model year emission rates and the I/M credits which are
used in the MOBILES model. The TECHS model is a flexible program that can more precisely
model emission rates and I/M reductions than the overall MOBILES model. Its flexibility includes
the ability to project individual model year emission factors for a range of different vehicle ages.
This flexibility permited a more precise comparison to be made between the data collected over a
fairly narrow time frame, and an EPA emission model. This is a flexibility which the MOBILES
model does not currently allow. However, if real data is found to match TECHS predictions, the
match also will apply to MOBILES.
Arizona's I/M program was modeled using the TECHS model and the concept shown in
Figure 4.1. The vertical axis/direction in Figure 4.1 is the average emission level in grams per mile,
and the horizontial axis is time. This figure is a conceptual schematic depicting the change in an
individual model year's average emissi ^ level as the result of an I/M cycle. The points which are
shown as an illustrative example are for the HC pollutant, the 1985 model year, and two vehicle age
inputs (10 and 11 years old in 1995). The 1985 model year was chosen because it shows a larger I/M
benefit than some of the more recent model years.
Separate TECHS model runs for two ages (i.e., 10 and 11 years) were done because the
typical new car model year begins in October, and cars are sold throughout the year. Thus, some
vehicles in the sample may be almost one year older than others. For simplicity it was assumed that
all of the cars in Arizona sample were originally sold in the month that they were tested, and that the
ones tested in June through September had age (n) and those tested between October and December
were age (n+1). The average result of the two ages is a weighted average based on number of
vehicles in the two groups in the Arizona database.
Point A in Figure 4.1 represents a particular model year (in this case the 1985 model year)
as it would have existed on January 1,1995, if no I/M program existed. The higher emission levels
from point A to point C reflect the deterioration of the particular model year over the one year
period. Point B in the figure represents the model year as it exists as the result of its I/M program
that was in effect at that time. The particular I/M program which was in operation was a loaded /
idle test on 1981 and later vehicles. Point C in the figure represents the particular model years
hypothetical emission level one year later as it would have existed if no I/M program existed. Point
D is the predicted before IM240 emission level for the particular model year. It cannot be obtained
directly from the TECHS model; however, it was calculated by projecting a line from Point B, and
assuming that the slope is the same as the slope of the line from Point A to Point C (this consistency
in deterioration rates between I/M and Non I/M is a fundamental assumption of the TECHS model
in calculating I/M program benefits). Point E was computed by performing a TECHS run using
IM240 assumptions. It is the final IM240 emission level for a particular model year after inspection
and repairs.
Creating this conceptual schematic is necessary because the actual Arizona IM240 program
results are available only at Point D and Point E, and the comparison can only be made between
these points. Clearly no actual data will ever be available at Points A and C (No I/M cases) since
the Arizona I/M program has run continuously since 1977. Point D represents the initial test results
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of the vehicles as they come into the IM240 process. Point E represents the results afterwards (after
failing vehicles are repaired to pass the IM240 test). The actual I/M reductions obtained from the
data for a given model year should therefore be similar to the difference between Point D and Point
E in the TECHS output.
For the comparisons shown in Figure 4.2 through 4.4, the output from the TECHS model was
adjusted to in-use conditions present at the I/M lanes by applying a multiplicative factor. The
adjustments included a speed factor to correct the FTP based TECHS model speed from 19.6 MPH
to 30 mph (the average speed of the IM240 cycle). The FTP ambient temperature range of 60 to 86
F with an average of 75 F was also corrected to an average of 90 F to account for the higher ambient
temperatures in Phoenix, Arizona. Also, the vehicle start operating modes of the FTP were also
adjusted to account for the non-start mode conditions under which the IM240 test in Arizona is
conducted. Finally, the FTP indolene fuel based emissions were adjusted to account for the natural
in-use fuel properties. The adjustments factors were created from the ratios of successive MOBILES
outputs which included and excluded the above parameters .
Figures 4.2 through 4.4 show the comparison of Arizona emission levels with TECHS
emission levels at Points D and E for cars only. For example, in Figure 4.2 the curve labeled TechS
Base represents Point D, TechS I/M represents Point E, AZ Base represents the Arizona data results
at Point D, and AZ I/M represents the Arizona data results at Point E. The difference between a
Base curve and its corresponding I/M curve is the I/M benefit of the first cycle of the IM240
program.
The HC and CO results in Figure 4.2 and 4.3 suggest fairly good agreement between the
adjusted TECHS model output and the Arizona data results. For HC, the benefits are similar in
magnitude, and gradually increase with earlier model years. For example, they range from virtually
zero in the late model years to about 20 - 25 percent for the early 1980's vehicles. Some differences
are apparent in a few model years during the mid-1980s with the TECHS model predicting larger I/M
benefits than the data suggests. The average before and after I/M HC emission levels based on the
data and predicted by the TECHS model are also generally similar. Most of the differences occur
during the mid to late 1980s model years with the TECHS model generally over- predicting HC
emission levels. The overall I/M reductions weighted by TECHS travel fractions (same weighting
were used on the predictions based on the data and TECHS projections) based on the data and the
TECHS model are also quite similar. For example, for cars, the data indicates an overall 14.3%
benefit while the TECHS model predicts a 16.9% overall benefit. In absolute terms, the reductions
are 0.08 g/mi HC from the data, and 0.09 g/mi HC from the TECHS model
The agreement between the TECHS model and the Arizona data is even better for CO than
for HC. In this case, both the TECHS model and the data analysis estimate the I/M benefits at 16.2
% for cars. The difference in emission levels and benefits is very similar for all model years except
the ones in the early 1980's. For these model years, the CO emission levels based on the Arizona
data are actually higher than the model predictions. Also, for some model years, the I/M CO benefits
calculated from the data are also slightly larger than the benefits predicted by the TECHS model.
In absolute terms, the differences between the data and the TECHS are more substantial with the
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Figure 4.2
Comparison of Arizona HC Emission Levels with TECHS HC Emission Levels
Cars Only; CY1995 Only
2.00
1.80
0.20 -
0.00
•AZ Base
•AZI/M
-TechS Base
•Tech 5 I/M
1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995
Model Year
-------
Figure 4.3
Comparison of Arizona CO Emission Levels with TECHS CO Emission Levels
Cars Only; CY 1995 Only
35.00
01 .W
0.00
•AZ Base
•AZI/M
-TechS Base
-Tech 5 I/M
1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995
Model Year
-------
Figure 4.4
Comparison of Arizona NOx Emission Levels with TECHS NOx Emission Levels
Cars Only; CY 1995 Only
4.00
3.50
•AZ Base
•AZ I/M
-TechS Base
-Tech 5 I/M
0.00
1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995
Model Year
-------
reduction based on the data at 1.24 g/mi CO, and the TECHS reduction at 1.08 g/mi CO.
More sizeable differences are apparent for NOx emissions. These differences are most
apparent in the older pre-1990 cars. In this case, the emission levels from the Arizona database are
considerably lower than the predicted results from the model. It is only with the late model (1990
and later vehicles does the agreement seem good. The overall I/M NOx benefits for cars are also
smaller than those predicted by the TECHS model. For example, the data analysis indicates a 7.6%
reduction while the TECHS model predicts a 16.7% reduction. Much of this difference occurs in
the early and mid 1980s model years. For the 1990 and later model years, the NOx benefits from
both methods (TECHS and the Arizona data) seem to be very small. In absolute terms, the
reductions are also substantial with the data producing a 0.08 g/mi Nox reduction, and the TECHS
model predicting a 0.20 g/mi Nox reduction.
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5.0 Comments from Peer Review
Prior to the final release of this report, a substantially final Draft version was released for
review to various individuals and organizations. This section summarizes substantial written
comments by the reviewers. To the extent possible these comments and suggestions were
incorporated into the final version of this report.
Written comments were provided by only one reviewer - Dr. Robert Slott. They are
provided below:
Per your request, here are some possible reasons why the use of I/M data
to evaluate an I/M program may lead to an overestimation. (re: The
1/14/97 Draft Arizona I/M Emission Reduction Benefit Estimate)
I. The sample is only from the population of gasoline vehicles taking
the test. Vehicles that are driving in the non-attainment area but are
not part of the I/M program will not be included in the sample.
Non-program vehicles could be transients (e.g., tourists) or vehicles
that regularly drive in the area (e.g., vehicles registered out of the
control area).
n. The sample may not be representative for the fleet being estimated.
A sample of 7,647 vehicles may not be sufficiently large to be a random
sample of highly skewed distributions. The random nature of the sample
should be checked against a variety of fleet characteristics that could
influence I/M performance (pass/fail, model year, vehicle type, engine
and emission system technology type, zip code (a surrogate of vehicle
owner wealth)). Initial emissions from the 7,647 sample could be
checked against the initial emissions of the (14,422 - 7,647) randomly
selected vehicles tested too late to see the response for failed
vehicles. A non-representative sample could lead either to over- or
underestimation of the emissions from the fleet required to take the I/M
test.
EQ. High emitting vehicles show test-to-test variability. If vehicles
that fail have test scores that are not test-to-test reproducible, then
re-testing a failed vehicle without repair (or with ineffective repair)
leads to an overestimation of the benefit of the I/M program.
Test-to-test variability for a dynamometer test may be due to operator
variability.
IV. The I/M program benefit will be overestimated when a winter fuel is
used during one part of the year in order to reduce CO (e.g., in
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Colorado and Arizona). Vehicles that fail on the summer fuel, and
subsequently pass on the winter fuel, will have an enhanced benefit.
They may pass without an effective repair. The amount of overestimation
should be subject to estimation if the emissions' levels and times of
failure and passing, and an estimated grams/mile emissions benefit of
the winter fuel are available.
V. Any analysis that does not compare an "in-program" fleet with an
equivalent "out-of-program" fleet, credits ongoing maintenance for the
"in-program" fleet as arising from the "program." This will
overestimate the benefit of the program.
VI. The benefits of the program are apparently based on a two year time
between inspection and maintenance. If the average time to repair is
significant (longer than say two weeks), then the benefit of the program
should be reduced accordingly.
VII. Most owners primary wish is to "pass the test" rather than to
"maintain their vehicle" or "clean the air." Owners may attempt to
influence the test result in a way that is not characteristic of vehicle
performance during normal driving (e.g., special gasoline additives just
prior to taking the test). Owner behavior to attempt to pass the test
would result in a greater number of vehicles passing compared than
deserve to pass.
VDI. The Arizona analysis properly monitored each failed vehicle. Not
all analyses do. The number and emissions for each category should be
recorded: (1) repaired and later passed the test (with the length of
time between first failure and ultimate passing), (2) repaired but still
not passing the test and then waived, (3) known to be scrapped, (4)
known to be sold or registered outside the control area, (5) disappeared
off the radar screen. Extrapolating data only from vehicles that were
known to have been failed and repaired to pass, will overestimate the
benefit of a program. This analysis calculated that number separately
as an upper limit to the benefits of the program.
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