United States Air and Radiation EPA420-R-96-009
Environmental Protection March 1996
Agency
Methodology for
Estimating Emission
Rates from
State-Specific
IM240 Data
> Printed on Recycled Paper
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METHODOLOGY FOR ESTIMATING
BASIC EMISSION RATES
FROM STATE-SPECIFIC
IM240 DATA
FINAL REPORT
Prepared for:
Ms. Connie Radwan
Office of Mobile Sources
U.S. Environmental Protection Agency
2565 Plymouth Road
Ann Arbor, Ml 48105
Prepared by:
E.H. Pechan & Associates, inc.
5537-C Hempstead Way
Springfield, VA 22151
March 8,1996
EPA Contract No. 68-D3-0035
Work Assignment II-68
Pechan Report No. 96.03.004/1768
THIS DOCUMENT HAS NOT BEEN PEER OR ADMINISTRATIVELY REVIEWED WITHIN EPA AND IS
FOR AGENCY USE/DISTRIBUTION ONLY. DO NOT QUOTE, CITE, OR DISTRIBUTE. MENTION OF
TRADE NAMES OR COMMERCIAL PRODUCTS DOES NOT CONSTITUTE ENDORSEMENT OR
RECOMMENDATION FOR USE.
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CONTENTS
Page
ACRONYMS AND ABBREVIATIONS v
CHAPTER I
INTRODUCTION 1
CHAPTER II
IM240-TO-FTP CORRELATION 3
A. DEVELOPMENT OF IM240 LANE-TO-FTP BAG 3 CORRELATION 3
B. DEVELOPMENT OF FTP CORRELATIONS 4
CHAPTER III
METHODOLOGY FOR INCORPORATING STATE-GENERATED IM240 DATA 7
A. DIRECT INCORPORATION OF STATE DATA 7
B. METHOD FOR DEVELOPING BER EQUATIONS 8
CHAPTER IV
EVALUATION OF PROCEDURE 11
CHAPTER V
RECOMMENDATIONS FOR FURTHER ACTION 13
A. RECOMMENDATIONS OF DATA ELEMENTS TO BE COLLECTED 13
B. STRATIFICATION OF DATA SAMPLE 13
C. EFFECTS OF VEHICLE PRECONDITIONING 13
REFERENCES 15
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ACRONYMS AND ABBREVIATIONS
BERs basic emission rates
DR deterioration rate
EPA U.S. Environmental Protection Agency
FTP Federal Test Procedure
I/M inspection and maintenance
ZML . zero-mile level
VINs Vehicle Identification Numbers
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CHAPTER I
INTRODUCTION
In the development of the U.S. Environmental Protection Agency's (EPA) MOBILE5
emission factor model, emission data from the Federal Test Procedure (FTP) were
supplemented with emission data collected from the IM240 test procedure. A statistical
correlation was performed between the FTP and IM240 data sets so that the larger data
set of IM240 tests could be used in developing basic emission rates (BERs). Historically,
the BERs in the MOBILE model had been based primarily on FTP data, with correction
factors applied to the emissions measured at the standard conditions of the FTP.
The purpose of this report is to assist EPA in developing a methodology to use State-
generated IM240 test data to develop locality-specific emission factors. The emphasis of
this report is to make recommendations that apply to new efforts that are to be performed
in the future by the States that use IM240 tests in their vehicle emissions inspections.
For States with enhanced inspection and maintenance (I/M) programs, there will be
two main situations where IM240 emission test data are gathered. One is where the
IM240 test is the primary test method in the I/M program. All subject vehicles receive an
IM240 test annually or biennially. The other situation is where IM240 testing is being
performed as part of an evaluation program where a minimum of 0.1 percent of the
vehicles subject to inspection in a given year are tested. The testing shall be done on a
representative random sample of vehicles and is required in all enhanced I/M program
areas as a check on the effectiveness of the I/M program. With the recent emphasis in
many States on attempting to meet enhanced I/M requirements through test-and-repair
networks, it is uncertain whether IM240 testing will be the primary test method.
Assuming that widespread use of IM240 test equipment is unlikely, more stringent
requirements might be placed on the IM240-based evaluation program testing to ensure
that this data set is representative of the vehicle fleet emissions in any given
State/nonattainment area.
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CHAPTER II
IM240-TO-FTP CORRELATION
This chapter discusses the proposed methodology for developing the correlation
coefficients to be used in converting the IM240 emissions data to FTP-equivalent emissions
data. These correlation coefficients were derived from a data base consisting of IM240 and
FTP tests performed on a subset of the Hammond, Indiana Lane Data Base vehicles at an
EPA contractor's lab in South Bend, Indiana.
Our proposed methodology for correlating the IM240 data to FTP data consists of the
following basic steps: (1) developing a correlation between the IM240 lane data base and
Bag 3 of the FTP; and (2) developing a correlation between Bag 3 of the FTP and each of
the other Bags as well as the total FTP.
A. DEVELOPMENT OF IM240 LANE-TO-FTP BAG 3 CORRELATION
Based on comments in both the Sierra (Sierra, 1994) and SAI (SAI, 1994) reports
evaluating the methodology used to derive the BERs used in MOBILESa, Pechan
recommends eliminating the fuel and temperature adjustments used previously to
correlate IM240 lane scores to IM240 lab scores. Although EPA's intent in applying fuel
and temperature adjustments was to make the IM240-to-FTP correlations more generic
(i.e., less region-specific), the resultant effects of the fuel and temperature corrections
appear to be minimal. Instead, Pechan recommends developing a direct correlation
between IM240 lane test data and the corresponding FTP Bag 3 data, since the IM240
driving cycle was developed from the Bag 3 FTP driving cycle. As such, a good correlation
should be observed between IM240 and FTP Bag 3 emissions.
Although variations in fuel RVP and temperature can affect emissions, in this
instance, the temperature and fuel corrections appeared to make little difference when
compared with the unadjusted lane data. A number of other factors may also influence
differences between lane and lab IM240 scores such as (1) differences in preconditioning
between the two tests; (2) inconsistent dynamometer settings; (3) vehicle changes between
tests; and (4) operator effects. As illustrated in the Sierra report (Sierra, 1994), several
different approaches to the lane versus lab temperature and fuel adjustments yielded
almost no difference from the approach used for MOBILESa. With no clear trends in the
data by month or season, the small sample sizes available for some months, in combination
with the variability added by applying the seasonal adjustments, Pechan recommends that
no lane to lab adjustments be applied to the IM240 data.
Equation (1) illustrates the regression equation.
Bag 3 = a + b * FTP (1)
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B. DEVELOPMENT OF FTP CORRELATIONS
The next step of the proposed methodology is to regress the FTP Bag 3 data against the
FTP Bag 2 data, developing a relationship that will then be applied to the IM240 data that
has been correlated to the FTP Bag 3. Preliminary analysis using EPA's FTP data base as
a whole (i.e., not stratified) indicated a relatively good correlation between Bag 3 and Bag
2. Using linear regression, an R2 value of 0.86 was obtained for HC, 0.88 for CO, and 0.91
for NOX. Presumably, these correlation coefficients would improve even more if the data
base is first stratified to obtain separate correlation equations for each technology group,
model year group, and emitter class combination. A log fit of the data should also be
investigated to determine whether a better fit of the data is obtained with a log regression.
Finally, the Bag 3 FTP data needs to be related to Bag 1, the cold start Bag. Since
both Bag 1 and Bag 3 follow the same cycle, differences between these two Bags should be
attributable to the cold start. For MOBILESa, the cold start offset was calculated as the
mean value of the difference between the FTP and the IM240 for the set of normal emitters
with an FTP value greater than the IM240 value. For the vehicle-specific correlations, a
cold start offset equation was developed where the cold start offset was calculated as a
function of mileage, assuming that as a vehicle ages, cold start emissions will increase
because the catalyst takes longer to reach light-off.
Our proposed procedure includes incorporating mileage in the calculation of the cold
start offset. For the proposed procedure, the difference between the FTP Bag 1 and FTP
Bag 3 would be calculated for all vehicles in the FTP data set. This cold start offset would
then be regressed against mileage for each technology group, model year group, and
emitter category. Emissions computed using the resulting regression equation would then
be added to the calculated Bag 3 results to provide an estimated Bag 1 for each of the
vehicles in the IM240 data base. These steps are illustrated in equations (2) through (4):
Bag 2 = c + d * Bag 3 (2)
CS = Bag 1 - Bag 3 = e + f * ODOM (3)
Bag 1 =Bag 3 + e + / * ODOM (4)
where:
CS = cold start offset, and
ODOM = odometer reading (miles)
Once the regression coefficients a through /have been calculated, FTP emissions by Bag
can be estimated for each of the IM240 lane test data points. It should be noted that the
above equations do not imply that only linear regressions are appropriate. The actual data
should be examined using logarithmic or log-linear regressions, as well, and the regression
type yielding the best fit to the data should be selected.
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For States that are only performing IM240 tests for their evaluation program (i.e., with
a sample size of 0.1 percent of the set of vehicles subject to an I/M test), the sample size of
data collected in the evaluation program will likely be too small to perform the described
stratification of data. In such cases, it may be advantageous for States to sample a greater
share of vehicles. Alternatively, a smaller number of data stratifications might be used,
depending on where gaps are found in the data. For example, if the sample size of the
1981-1982 model year group is very small relative to the 1983 and later model year group,
then the model year group stratification might be eliminated.
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CHAPTER III
METHODOLOGY FOR INCORPORATING STATE-
GENERATED IM240 DATA
A. DIRECT INCORPORATION OF STATE DATA
Before the State-collected IM240 data are converted to FTP-equivalent data, the
State's data base of IM240 emissions needs to be quality assured. In other words, any data
records which might be missing certain pieces of data (such as mileage, model year,
technology type, etc.) should be eliminated, so that the resulting BER equations are not
inappropriately skewed. Vehicles with mileage listed as "0" or above a certain level should
be removed from the data base. The upper bounds of acceptable mileage should be
determined by plotting a histogram to determine an obvious point after which the data
obviously drops off. Any data that are entered into the State's data base using codes, such
as a code indicating which of the four technology types applies to a given vehicle, should be
checked to make sure that all codes are valid.
The correlations developed in the previous chapter would then be applied to each
vehicle in the State's IM240 data base. The procedure for adjusting each IM240 record is
summarized below.
• Calculate the FTP Bag 3 equivalent for each record using the technology group,
model year group, and emitter category regression coefficients developed above in
equation (1).
• Estimate FTP Bag 2 emissions by applying the FTP Bag 3-to-FTP Bag 2
correlation to the FTP Bag 3 emissions that were calculated in the previous step,
again according to technology type, model year group, and emitter category (i.e.,
calculate Bag 2 emissions using equation (2)).
• Estimate Bag 1 emissions by adding the appropriate cold start offset to the
calculated Bag 3 emissions as a function of the vehicle mileage, with different
equations applying to each technology group, model year group, and emitter
category combination (equation (4)).
• Calculate the total FTP-equivalent emissions using the following equation (i.e.,
weight each of the Bags according to the fraction of total FTP mileage
accumulated in each mode):
FTP = 0.206 * Bag 1 + 0.521 * Bag 2 + 0.273 * Bag 3 (5)
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These IM240-to-FTP correlations using the Hammond data are needed because the
States will not be performing FTP tests, and, therefore, would not be able to develop State-
specific IM240-to-FTP correlations.
B. METHOD FOR DEVELOPING BER EQUATIONS
Once FTP-equivalent emissions have been calculated for each vehicle in the State
IM240 data base, BER equations would need to be developed for each model year group,
technology type, and emitter category combination to be input to the TECH model. This is
accomplished by performing a regression of the FTP-equivalent emissions against mileage
for each of the subcategories of data. The y-intercept of the regression would represent the
zero-mile level (ZML) for the BER equation, while the slope would represent the
deterioration rate (DR).
Two options are available at this point: (1) use the BERs as calculated for input to the
TECH model; or (2) adjust the FTP-equivalent emissions data to remove the effects of the
I/M program.
If option (1) is selected, the BERs input to MOBILE and the emission factors output by
MOBILE would represent in-use emissions resulting from the State's current I/M program
averaged over the time that the testing was performed. For vehicles that have failed their
initial test, only the data from the final test should be included (whether the vehicle passed
the test at this point or was given a waiver). Any records containing test data prior to the
final pass/waiver determination should be removed from the data base before computing
the BER equations.
If option (2) is selected, Vehicle Identification Numbers (VTNs) should be used to track
vehicles that have failed the IM240 test over successive test cycles. In this case, test data
from vehicles that have failed the IM240 test in the first test cycle should be identified.
Emissions from the initial test in the first cycle should be compared with the emissions
from the final retest for that vehicle in the first cycle (i.e., after the vehicle passes the
IM240 test or is given a waiver). The reduction (or increase) in emissions between these
two tests should be calculated. Next, the vehicle's initial test data from the next test cycle
should be located. Assuming that the effect of any repairs made to the vehicle would
deteriorate at the same rate as the vehicle's initial deterioration rate, the difference in
emissions between the initial and final tests in the first cycle should be added to the
emissions from the second cycle. This process would be repeated in successive test cycles.
These adjustments should be performed using the FTP-equivalent emissions data. Finally,
using the adjusted data from all test cycles (excluding data other than each vehicle's initial
test in a given cycle), BER equations could be developed by technology type/model year
group/emitter category using linear regressions of the FTP-equivalent emissions versus
mileage. The resulting equations would be used as input to the TECH model.
By using the results from both option (1) and option (2), a State could estimate the
overall effects of its I/M program on vehicle emissions. The output from both options (1)
and (2) would be input (separately) to the TECH model. The resulting output BER
equations could be used as input to the MOBILE model, with each of the two BER equation
sets (i.e., with and without I/M) in a separate MOBILE input file. The data would be
accessed by appropriately setting the control flag "NEWFLG" within the MOBILE input
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file. By keeping all other inputs within the two MOBILE input files identical, the
difference in the emission factors output by MOBILE for these two files will represent the
effect of the I/M program in place at the time the data were collected.
This methodology could only be used by States using IM240 as their primary motor
vehicle emission test method. States that are only performing testing on a sample of
vehicles would not have the ability to trace a vehicle's pre- and post-repair emissions.
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CHAPTER IV
EVALUATION OF PROCEDURE
The approach discussed in this report is analyzed here. First, the methodology for
calculating FTP-adjusted emissions is examined. This is followed by an evaluation of the
two options for developing BERs from the FTP-equivalent emissions data.
The primary strength of applying the proposed procedure to calculate FTP-adjusted
emissions is that the method would be compatible with the current structure of
MOBILESa. All correction factors within the MOBILE model that are based on the FTP
test cycle would still be valid (such as the speed adjustments). In addition, the fact that
the data are State-specific, rather than the MOBILE default BERs developed from the
vehicle fleet in another State, adds a degree of reality to the emission factors that are
calculated with these State-specific BERs.
One weakness of this approach stems from the lack of FTP testing at the State level.
IM240 emissions from a State-specific data base are being adjusted to FTP-equivalents
using FTP correlations that were based on the vehicle fleet from a different region. This
will likely bias the FTP-equivalent emissions in that they will not be truly representative
of the State in which the data were collected, but will be somewhat influenced by the
vehicle fleet in other regions (e.g., Hammond, Indiana). As indicated earlier in the report,
temperature and fuel effects are not expected to cause significant differences in the
resultant data adjusted to FTP equivalents. However, differences in the vehicle mix
between the FTP test site and the State of interest may be a more important consideration.
If the average age and/or accumulated mileage in each of the technology type/model year
group/emitter category groupings in the State data differ significantly from the
corresponding data used to calculate the IM240-to-FTP conversions, the effects may be
more severe than any fuel/temperature effects. It might be possible to evaluate whether
this is an important issue by weighting the data from the IM240-to-FTP data base such
that the average age or mileage of each subgrouping is significantly higher or lower than
the current data base, and then recalculating the correlation coefficients.
The strength of using the first option for developing BERs, in which the effects of the
State's I/M program are included, is that the actual emissions resulting from the I/M
program will be seen. This would show whether an I/M program is achieving the emissions
benefits needed in the area projected for meeting attainment and rate of progress
demonstrations.
The primary advantage of the second option for developing BERs, in which the effects
of the State's I/M program are excluded from the BER equations, is that it makes it
possible within the current structure of the MOBILE model to calculate no-I/M emission
factors. It also enables an area to model emission factors that represent a change to the
I/M program from the program characteristics included in the program at the time the
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IM240 test data were collected. Regional influences, other than the effects of I/M, can be
seen by comparing these emission factors with MOBILE emission factors calculated with
default BER equations. This also provides a consistent baseline for developing an emission
inventory for the State, using the State-specific BERs for areas with an I/M program from
option 1, and option 2 BERs for areas without an I/M program. Also, if a State has
different I/M program characteristics in different areas of the State, the State-specific
BERs would represent a combination of the two. One way to alleviate these problems
would be to develop separate sets of BERs for each area. However, this would significantly
decrease sample sizes, and in some instances, a valid analysis may not be possible if the
sample size is too small.
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CHAPTER V
RECOMMENDATIONS FOR FURTHER ACTION
A. RECOMMENDATIONS OF DATA ELEMENTS TO BE COLLECTED
Section 51.365 of the I/M Final Rule (57 FR 52950, 1992) provides a list of the
minimum data elements. Data items of interest for this project are listed below:
Date of the test;
Emission test start time and the time final emission scores are determined;
VIN;
Gross vehicle weight rating;
Vehicle model year, make, and type;
Odometer reading;
Category of test performed;
Fuel type;
Type of vehicle preconditioning (if any); and
Emission scores.
The information on test times and dates could be used with information from the
National Climatic Center to determine hourly (or every 3rd hour) temperatures from a
nearby meteorological site. Temperature data could also be collected at the test site.
The work scope also mentions fuel samples as a potentially required item. For
reformulated gasoline areas, it may be possible to use the data collected by EPA to enforce
the reformulated gasoline program.
B. STRATIFICATION OF DATA SAMPLE
Stratification of the data are always desirable, but if there are too few records to
analyze in each strata, other problems are introduced. Stratifying data allows for
differences that might be masked if the data were considered as a whole, much in the way
that extreme values are muted when considering a mean value. However, if there are
insufficient numbers of records in the strata, the benefits of stratification can be lost.
The vehicles in a specified region may have certain characteristics that are more
prevalent (fleet age, cars versus trucks, 4-wheel drives, etc.) in that State. If so, it should
be worthwhile and possible (numberwise) to stratify the data by that factor to assure that
the effects are not overlooked.
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C. EFFECTS OF VEHICLE PRECONDITIONING
There seems to be an implicit assumption in the EEA and Sierra studies that all
IM240 tests are performed with the vehicle in a fully warmed-up (hot stabilized) condition.
This assumption may be invalid.
A presentation made by a Toyota representative pointed out (Babcock, 1994) that if
there is no vehicle preconditioning before running an IM240 test, there may be many false
failures. It has been suggested that each vehicle undergo a set amount of preconditioning
before being given an IM240 test. EPA staff suggest that this is an unnecessary step that
would add time to every test, and that the two ways to pass test procedure is going to allow
vehicles to pass based on Bag 2 cutpoints, even in instances where a vehicle begins the
IM240 procedure with a highly loaded evaporative canister. Canister purging will occur in
the first 93 seconds of the test. The concern about the need for preconditioning was raised
by test results based on testing performed in Toyota's lab. (This testing was performed for
a small number of vehicles, though.) EPA feels that it has a much more extensive data set
of IM240 results from test lanes that match what the State programs will experience, EPA
finds that more than 50 percent of vehicles tested pass the composite test without
preconditioning.
The Toyota presentation, on the other hand, suggested that based on Toyota's data,
without preconditioning, there will be many false failures. In general, Toyota thinks that
without preconditioning, the average test result will be biased high. This would be a
concern if States are going to be using IM240 results as an indicator of overall emission
levels. The upshot of the above is that in a situation where IM240 test results for a small
sample of vehicles is being used to represent a State's emission rates, consistent
preconditioning could be important in ensuring that emission test results are not biased.
Another consideration is that the data collected by States that choose to implement a
fast-pass criteria will differ from those that perform testing for the entire 240 seconds of
the test. The emissions data in such situations will likely be skewed high.
The effects of both issues (preconditioning and fast-pass tests) could be mitigated by
using full IM240 tests with preconditioning, at least on a sample of the vehicles. It is
highly recommended that both preconditioning and full IM240 tests be used by States that
are only testing the required sample of vehicles.
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REFERENCES
Babcock, 1994: Robert Babcock, Toyota USA, Presentation at Tenth Annual Mobile
Sources/Clean Air Conference, Estes Park, CO, September 27-29, 1994.
57 FR 52950, 1992: Federal Register, Vol. 57, No. 215, p. 52950, "Inspection/Maintenance
Program Requirements," Final Rule, November 5, 1992.
SAI, 1994: Systems Applications International, "Investigation of MOBILESa Emission
Factors - Assessment of Exhaust and Nonexhaust Factor Methodologies and
Oxygenate Effects," prepared for American Petroleum Institute, February 7, 1994.
Sierra, 1994: Sierra Research, Inc., "Investigation of MOBILESa Emission Factors --
Evaluation of IM240-to-FTP Correlation and Base Emission Rate Equations," prepared
for American Petroleum Institute, June 1994.
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TECHNICAL REPORT ABSTRACT
REPORT TITLE: Methodology for Estimating Basic Emission Rates from State-Specific
IM240 Data
REPORT DATE: March 8, 1996
CONTRACT NO.: 68-D3-0035
PRIME CONTRACTOR: E.H. Pechan & Associates, Inc.
WORK ASSIGNMENT NO./DELIVERY ORDER NO. (if applicable): 11-68
PROJECT OFFICER: Mary Wilkins
PROJECT OFFICER ADDRESS: U.S. EPA, MD-12, RTP, NC 27711 TEL.: (919) 541-5229
PROGRAM OFFICE: Office of Mobile Sources
NO. OF PAGES IN REPORT: 16
DOES THIS REPORT CONTAIN CONFIDENTIAL BUSINESS INFORMATION
YES NO X
REPORT ABSTRACT - Include a brief (200 words or less) factual summary of the scope
and nature of the work performed and referenced in the report.
In the development of EPA's MOBILES emission factor model, emission data from the
Federal Test Procedure (FTP) were supplemented with emission data collected from the
IM240 test procedure. A statistical correlation was performed between the FTP and IM240
data sets so that the larger data set of IM240 tests could be used in developing basic
emission rates (BERs).
Two reports were provided that detail shortcomings in the approach and statistical
analyses used to develop the MOBILES exhaust BERs. The objective of this work
assignment is to assist EPA in improving the use of IM240 data used in developing the
MOBILE model exhaust BERs (for LDGVs only). Since the time that the MOBILES BERs
were developed, additional FTP and IM240 emission test data have been collected, which
EPA plans to incorporate into the development of exhaust BERs for MOBILE6. This report
documents a proposed methodology for developing exhaust BER equations from State-
collected IM240 data that can be used as input to EPA's TECH model.
KEY WORDS/DESCRIPTORS - Select the scientific or engineering terms that identify the
major concept of the research and are sufficiently specific and precise to be used as index
entries for cataloging.
MOBILES; MOBILE6; TECHS; FTP; IM240; I/M programs
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