United States Air and Radiation EPA420-R-01-060 

Environmental Protection November 2001 

Agency M6.SPD.002 

Final Facility Specific 

Speed Correction Factors

 Printed on Recycled 

Paper 
EPA420-R-01-060 

November 2001 

Final Facility Specific Speed Correction Factors 

M6.SPD.002
 

David Brzezinski
 

Constance Hart
 

Phil Enns
 

Assessment and Standards Division
 

Office of Transportation and Air Quality
 

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 the exchange of
 

technical information and to inform the public of technical developments which
 

may form the basis for a final EPA decision, position, or regulatory action.
 
Table Of Contents 

1.0 Summary .............................................................. 2
 

2.0 BACKGROUND ........................................................ 4
 

3.0 VEHICLE TESTING ............................................... 7
 

3.1 New Driving Cycles ................................................ 7
 

3.2 Sample Selection .................................................. 8
 

3.3 Vehicle Testing ................................................... 9
 

4.0 STATISTICAL ANALYSES ......................................... 9
 

4.1 Emitter Status .................................................... 11 
 

4.2 Roadway Type ................................................... 12 
 

4.3 Vehicle Class .................................................... 13 
 

4.4 Emission Standard ................................................ 13 
 

4.5 Convergence of Freeways and Arterial/Collectors ....................... 14 
 

4.6 Summary ....................................................... 15 
 

5.0 EMISSION LEVEL CALCULATION ...................................... 16 
 

5.1 Freeway Versus Arterial/Collector Effects ............................. 16 
 

5.1.1 High Speeds ............................................... 17 
 

5.1.2 Intermediate Speed Freeways .................................. 17 
 

5.1.3 Low Speed Freeways ........................................ 17 
 

5.1.4 Arterial/Collectors .......................................... 18 
 

5.1.5 Extremely Low Speeds and Idle ................................ 18 
 

5.2 Local Roadways and Freeway Ramps ................................. 19 
 

5.3 Special Cases .................................................... 19 
 

6.0 SPEED AND OFF-CYCLE CORRECTION FACTORS ........................ 20 
 

6.1 Basic Modeling Approach .......................................... 20 
 

6.2 Off-Cycle Adjustment ............................................. 21 
 

6.2.1 CO Off-Cycle Emission Effects ................................ 23 
 

6.2.3 HC Off-Cycle Emission Effects ................................ 24 
 

6.2.3 NOx Off-Cycle Emission Effects .............................. 24 
 

6.3 Calculating Speed Correction Factors ................................. 25 
 

6.4 Test for Model Stability ...................................... 26 
 

7.0 BENEFITS OF THE SFTP REQUIREMENT ................................ 27 
 

7.1 Methodology used to calculate SFTP benefit ........................... 27 
 

7.2 Applying the SFTP Benefit in MOBILE6 .............................. 32 
 

7.3 Applicability of SCFs to SFTP-compliant vehicles ....................... 33 
 
8.0 Application in MOBILE6 ................................................ 35 
 

8.1 Light Duty Diesel Vehicles ......................................... 36 
 

8.2 Heavy Duty Vehicles .............................................. 37 
 

8.3 Motorcycles ..................................................... 37 
 

8.4 High Speeds ..................................................... 38 
 

9.0 COMPARISON TO MOBILE5 ............................................ 38 
 

References .................................................................. 40 
 

Tables ...................................................................... 42 
 

Figures ..................................................................... 72 
 

Appendices .................................................................. 95 
 

Appendix A : Statistics .................................................. 96 
 

Appendix B : Example .................................................. 108 
 

Appendix C : Response to Comments ...................................... 115 
 

Appendix D : Peer Review of Speed Corrections ............................. 135 
 

Appendix E : Peer Review of Off-Cycle Effects .............................. 146 
 
ABSTRACT
 

In MOBILE5, adjustments were made to the basic exhaust emission estimates to account 

for the effects of area wide average trip speeds using speed correction factors developed from a 

number of driving cycles with varying average speeds. For MOBILE6 EPA has adjusted for 

differences in driving behavior versus roadway (facility) type and aggressive driving effects as 

well as average speed. EPA has developed new facility-specific inventory driving cycles, based 

on “real world” representative driving studies, and tested vehicles using these cycles to address 

these purposes. This report describes the analysis of the new driving cycle data and presents the 

resulting speed correction factors used in MOBILE6 for the gasoline passenger car and light duty 

gasoline truck classes. 

Final M6.SPD.002 1 June 2001 
1.0 Summary 

Although the adjustments described in this document are called “speed” correction 

factors, the adjustments include all of the effects on emissions caused by differences in driving 

behavior, of which average speed is the most obvious and easiest to measure. The speed 

correction factors described in this document are used in MOBILE6 to replace the speed 

correction factors now used in MOBILE5 for all light duty passenger cars and light duty trucks of 

all model years and technologies for average speeds above 7.1 mph. Low speed adjustments, 

below 7.1 mph, will still use the MOBILE5 estimates. The speed correction factors for heavy 

duty vehicles, diesel fueled vehicles and motorcycles from MOBILE5 would be retained for use 

in MOBILE6. This document also describes the method for applying the new speed correction 

factors to future technology vehicles for which no data is yet available. 

The new MOBILE6 speed correction factors specifically account for aggressive driving 

behavior not represented in older driving cycles. The effect of aggressive driving behavior is 

accounted for separately using an emission offset to allow for future control strategies, such as 

the Supplemental Federal Test Procedure for vehicle certification, to be explicitly modeled. The 

new speed correction factors also allow for evaluation of vehicle emissions by roadway type 

(facility) and by roadway segments (links). There are four roadway types modeled in MOBILE6: 

� Freeways 

� Arterial/Collectors 

� Freeway Ramps 

� Local Roadways 

EPA recognizes that many factors, such as the number of lanes and other roadway 

geometry, are not explicitly accounted for in the development of the four roadway types. 

However, each driving cycle used includes a representative amount of the driving behavior on a 

variety of roadways of that roadway type. EPA is confident that these four roadway types will be 

sufficient to allow for better modeling of the wide variety of roadways found in urban areas than 

previous models. 

The speed correction factors for freeways and arterial/collectors depend on both speed 

and basic emission levels of the vehicles. The correction factors for freeway ramps and local 

roadways depend only on emission level and cannot be adjusted for average speeds different than 

the national average. All speed corrections are based on new driving cycles designed to reflect 

“real world” representative driving behavior, including the effects of aggressive driving not 

found in the standard vehicle FTP certification driving cycle (Urban Dynamometer Driving 

Cycle) and most older driving cycles used in emission testing.

 Since the data for this analysis were collected using the new, representative driving 

cycles, an emission impact of aggressive driving is included in the effect of the new speed 

correction factors on emissions. The introduction of the new Supplemental FTP (SFTP)1

 into 

Final M6.SPD.002 2 June 2001 
vehicle emission certification will require the reduction of the emission effects from aggressive 

driving for future vehicle certification. 

Table 16 contains the MOBILE6 speed correction factors for freeways. Table 17 contains 

the MOBILE6 speed correction factors for arterial/collector roadways. For MOBILE6, the 

correction factor for Local Roadways and Freeway Ramps assume a national average speed and 

will not have an adjustment for local average speeds. The speed correction factors for freeways 

and arterial/collectors converge below 7.1 mph and at higher speeds, depending on the pollutant 

and emission level. At those points the freeway and arterial/collector speed correction factors 

become identical. The speed correction factors for speeds below 7.1 mph will remain the same 

as in MOBILE5, but are adjusted to account for the difference between the old and new speed 

correction factors at 7.1 mph. 

MOBILE5 did not model average speeds above 65 miles per hour. The new driving 

cycles also do not address average speeds above 65 miles per hour. EPA will consider whether 

sufficient information is available to model average speeds above 65 miles per hour in MOBILE6 

and will present any proposals for these higher speeds in a separate document. As in MOBILE5, 

MOBILE6 will not explicitly address average speeds less than 2.5 miles per hour. Idle emissions 

will be assumed to be the same as the grams per hour emitted at an average speed of 2.5 miles 

per hour. This “idle” emission rate will be available as an output from MOBILE6. 

Table 13 shows the coefficients used to calculate the freeway ramp and local roadway 

emissions from the basic emission rate. Table 14 and 15 show the additive offsets used to 

calculate the adjusted basic emission rate which is adjusted by the speed correction factors. 

Appendix B has an example calculation of the application of speed correction factors to the base 

emissions calculated by MOBILE6. 

Figures 4a through 4c show the effect of emission level in the sample of light duty 

gasoline vehicles as a function of speed for freeways, estimated using the new MOBILE6 speed 

correction factors. Figures 5a through 5d show the MOBILE6 speed correction factors for 

freeways for the three emission levels. Figures 6a through 7i compare the new MOBILE6 speed 

correction factors with selected MOBILE5 speed correction factors. Care should be taken in 

interpreting these figures, since there are many differences in how these factors are applied in 

MOBILE6 as compared to MOBILE5. These figures are discussed in more detail in Section 9. 

This report is organized into sections which address various aspects of the analysis. 

Section 2 gives a brief background of the need for new, facility based, speed correction 

factors. 

Section 3 discusses the development of the facility cycles and the emission testing sample 

used in the development of the speed correction factors. 

Final M6.SPD.002 3 June 2001 
Section 4 discusses the statistical analysis of the data sample. 

Section 5 describes the approach developed to summarize the emissions data. 

Section 6 uses the emission levels developed in Section 5 to develop the speed correction 

factors and off-cycle effects used for MOBILE6. 

Section 7 discusses how the new Supplemental Federal Test Procedure (SFTP) will affect 

the estimate for off-cycle emissions and speed correction factors. 

Section 8 describes how the new speed correction factors will be used in MOBILE6 and 

how MOBILE6 will estimate the speed correction for other vehicle classes. 

Section 9 compares the speed correction factors developed in Section 6 to the existing 

speed correction factors in MOBILE5. 

2.0 BACKGROUND 

EPA's highway vehicle emission factor model, MOBILE, is used for inventory modeling. 

MOBILE has historically been based on emission testing using the Federal Test Procedure (FTP) 

used to certify all light duty vehicles sold in the United States. The FTP uses a driving cycle (the 

Urban Dynamometer Driving Cycle, commonly referred to as the LA42

) which simulates urban 

driving on a laboratory dynamometer. Correction factors for various conditions (e.g., average 

speed, temperature, fuels) are applied to emissions measured at the FTP "standard" conditions. 

The speed correction factors were based on test results for vehicles tested on both the LA4 

(Urban Dynamometer Driving Cycle) and several other cycles, each having a different average 

speed. MOBILE6 will address two areas not adequately addressed in previous versions of the 

model. These are “real world” representative driving behavior and the expanded use of 

transportation models in determination of area-wide inventories. 

"Real-World Driving" 

The FTP has been used for emissions certification of all light duty vehicles sold in the 

United States. The Clean Air Act Amendments of 1990 mandated a closer look at "real-world 

driving" - that is, driving modes that are not covered by the FTP (and the Urban Dynamometer 

Driving Cycle) and representative of actual observed driving behavior. EPA organized the 

Federal Test Procedure Review Project to address this mandate. A new Supplemental FTP 

(SFTP) rule was finalized in October 1996.3 This rule specifies the addition of a new 

certification cycle with more aggressive driving and associated vehicle emission standards. 

MOBILE6 must address both the emission impacts of more aggressive driving than is 

covered in the driving cycles that were used to develop MOBILE5 and the effects of the new 

Final M6.SPD.002 4 June 2001 
SFTP standards on future model year vehicles. A special EPA emission testing project was 

initiated to address these concerns. The results of that testing are the basis for the analysis in this 

document. 

Transportation Models 

The current and older versions of the MOBILE model were developed to estimate areawide emission inventories using trip-based emission estimates with trip-based adjustments for 

average speed. Vehicle trips are defined as all driving from key-on to key-off. These vehicle 

trips may include a variety of roadways and speeds. 

Local officials have begun to integrate transportation models into their regional air quality 

planning processes. Most transportation models represent the roadway system as a network of 

"nodes," which are usually intersections, connected by "links." Each link represents a particular 

type of roadway or "facility." Transportation models generate link-specific estimates of speed 

and traffic volume. Transportation planners have begun using MOBILE to generate link-specific 

emissions estimates for planning purposes. 

Recent data from instrumented vehicles and chase car studies show that some types of 

facility-specific driving contain more frequent and more extreme acceleration and deceleration 

than others.4 Different facilities may have similar average speeds, but may differ significantly in 

the amount of steady cruise. These differences suggest that there is a need to quantify the 

emission differences (if any) between facilities in order to evaluate facility-specific speed related 

traffic control measures in inventory modeling. 

For example, at an average speed of 25 mph, travel over surface streets is likely to have a 

relatively low level of traffic congestion, but will include many stops for traffic signals. Travel 

on a freeway at 25 mph may indicate a high congestion level, but may include fewer stops. 

MOBILE5's trip based emission estimates do not differentiate between roadway types. If 

MOBILE5 is used to model roadways separately, it cannot account for any differences in 

emissions at similar average speeds resulting from these differences in driving behavior. This 

particularly affects the planning process, where plans that affect different roadways cannot be 

modeled adequately. 

Other Approaches 

California is also updating it’s highway emission factor model.5 However, California has 

taken a different approach to modeling the effects of changes in vehicle speeds. Rather than 

attempt to discern what the driving behavior is for various facilities at various average speeds, 

they divide all observed driving into speed bins. Each bin contains “microtrips” with similar 

average speeds, regardless of the roadway type where the driving was observed. By weighting 

the results of the various speed bins, any area-wide average speed can be modeled. Changes in 

driving behavior can be modeled by varying the distribution of speeds. 

Final M6.SPD.002 5 June 2001 
This approach requires areas to evaluate their fleet activity as “trips”, where individual 

vehicles travel over a variety of roadway types at varying speeds to reach a destination. These 

trips are then used to develop a distribution of average trip speeds. Transportation models 

generally do not produce trip statistics and transportation planners would need to adjust their 

models to generate these distributions. Any changes in the roadway system resulting in changes 

in average speeds on specific roadways will require a change in the full area-wide distribution of 

trip speeds. Evaluation of the emission impact of changes in the specific roadways will require 

new estimates of the area-wide emission levels. 

One important advantage of California’s approach is the need for fewer driving cycles. 

Given limited testing budgets, this allows more vehicles to be tested over each cycle, thus 

increasing the statistical confidence in the emission test results. Development of the driving 

cycles themselves requires fewer assumptions such as decisions about where and under what 

conditions the observed driving occurred. The resulting trip-based California driving cycles are 

also similar in concept to the trip-based Unified Driving Cycle (or LA92),6

 which is used by 

California as the basis for the highway vehicle emission factors. The approach for MOBILE6 

requires more driving cycles with more detailed information about driving conditions and 

location. 

The most important disadvantage of California’s approach is the dependence on vehicle 

trip information. Since vehicle trips occur over a variety of roadways at a variety of average 

speeds, evaluation of trips is most relevant for only area-wide (i.e., county-wide) emission 

estimates, where all trips can be assumed to begin and end within the area. The confidence in the 

estimate of emissions will decrease as the size of the area to be modeled is decreased or if only 

specific roadways or links are to be modeled. In addition, many transportation planners do not 

currently generate trip speed distributions and other trip information from their models. This will 

mean that changes will need to be made in the transportation models in many cases in order to 

effectively use the California emission factors. In comparison, the MOBILE6 approach is more 

compatible with analysis by roadway type and link. Since most transportation models already 

estimate speeds and miles traveled by link, MOBILE6 will not normally require major changes in 

the output from existing transportation models. Using MOBILE6, the area-wide emissions are 

still able to be estimated by compiling the results from the four roadway types. 

A more detailed description of the California approach or a comparison of the two 

approaches is beyond the scope of this document. Readers are encouraged to obtain information 

directly from California7

 for comparison with the results documented in this report. 

Final M6.SPD.002 6 June 2001 
3.0 VEHICLE TESTING 

3.1 New Driving Cycles 

The basis for the analysis found in this report is a set of light-duty, gasoline fueled 

vehicles recruited and tested in 1997. The testing included new driving cycles specifically 

designed to address the effects of in-use driving behavior on emissions. Table 1 gives a brief 

description of the new cycles that were used in the testing. Collectively, these new driving 

schedules will be referred to in this document as “facility” cycles. The driving behavior in each 

driving schedule is selected from data collected from a particular roadway type during periods of 

various congestion levels. These congestion levels have been roughly grouped into “levels of 

service” (LOS) using letters A through G, similar to congestion category designations used in 

transportation models. Briefly, LOS “A” refers to “free flow” (uncongested) situations and the 

subsequent letters indicate increasing levels of congestion. The data used and the definition of 

these categories is discussed in more detail in a separate EPA report describing the development 

of the new facility driving cycles.8

 Although the new cycles are labeled using a letter system 

similar to that used by transportation agencies, there will be additional uncertainty in matching 

conditions in the field with these new cycles due to the mismatch between LOS defined by air 

agencies and transportation agencies. This can be alleviated somewhat by careful selection of the 

average speeds and roadway types used in MOBILE6 to be those that best represent the driving 

behavior observed in the field. 

Table 2 compares the new cycles’ statistics to the target population statistics for each 

cycle. The statistics for each driving cycle will differ somewhat from the observed speed and 

acceleration statistics which the cycle is designed to simulate (or “target population”). For 

example, the highest average speed of the new arterial/collector cycles is 24.8 mph. Driving on 

specific arterial/collector roadways can have average speeds higher than that. The maximum 

speed of the arterial/collector cycles is only 58.9 mph, while the maximum speed observed in the 

target population is 74.9 mph. This is a result of the cycle development process which chooses 

the best combination of microtrips to match the target population. It is likely that the particular 

microtrip which contained the maximum observed speed in the targeted population overrepresent certain aspects of driving behavior and was, therefore, not able to be used within the 

confines of a single driving cycle of limited duration. 

Each cycle was designed to result in emission levels representative of the emissions that 

are expected from the driving behavior observed in the target population. Characteristics which 

were deemed important to the match were specific power, speed, and amount of acceleration, 

deceleration and idle. The factor which most affects emissions, shown from previous experience 

in development of the Supplemental FTP, is the power distribution. The average speed or 

maximum speed of the resulting cycles may not exactly match the target population. More 

importantly, however, the cycles approximate the power distribution of the target population. 

EPA feels that the emissions generated from the new cycles are a good representation of the 

expected emissions from the driving behavior that was observed in the target population from 

Final M6.SPD.002 7 June 2001 
which the cycle was generated. The development of these cycles is discussed in much more 

detail in a separate document.9 

It must be pointed out that however well the resulting driving cycles match the targeted 

population data, the use of fixed driving cycles, by it’s nature, cannot precisely match a particular 

roadway modeling situation. Any difference between the targeted population data and the 

specific modeling scenario will add an additional uncertainty to the modeling results. This 

uncertainty will be reduced the more the specific modeling scenario resembles the targeted 

population data used in development of the driving cycles. This will be the case in larger, area 

wide analysis, where average driving behavior will likely better match the population data that 

was used. 

In addition to the new cycles described in Table 1, each vehicle was also tested using the 

following cycles: 

- Federal Test Procedure (FTP), with an additional hot running 505 seconds of the LA4 

(Urban Dynamometer Driving Cycle). 

- California Air Resources Boards (CARB) area-wide Unified Cycle (LA92). 

- New York City Cycle (NYCC), a low speed cycle which has previously been used for 

speed correction factors in the MOBILE model. 

- ST01, a cycle based on instrumented vehicle data representing the beginning of trips 

which is the first 258 seconds of the vehicle certification air conditioning cycle (SC03). 

Table 3 shows more information on these additional cycles. 

Although the New York City cycle (NYCC) was not developed specifically for 

MOBILE6, it had been developed specifically to address the effects of “real world” 

representative driving behavior at low average speeds. Although it has a low average speed (7.1 

mph), it has maximum accelerations that are twice those found in the LA4 cycle. It was included 

in the set of results used to generate the speed corrections factors to provide a data point below 

11.6 mph (Arterial/Collector LOS E-F) in the analysis and provides a data point common to 

earlier emission testing samples for comparison. 

3.2 Sample Selection 

The vehicle sample for this analysis came from EPA Emission Factor testing performed 

at both the Automotive Testing Laboratories, Inc. (ATL), in Ohio and EPA’s National Vehicle 

and Fuels Emission Laboratory (NVFEL), in Ann Arbor, Michigan, in the spring of 1997. All of 

the vehicles at ATL were recruited at Inspection and Maintenance lanes run by the State of Ohio, 

and were tested in an as-received condition (without repairs). At the time of this analysis, a total 

of 62 1983 through 1996 model year vehicles had been recruited and had completed testing in 

Ohio, and 23 1990 through 1996 model year vehicles recruited and tested in Ann Arbor. The 

sample of 85 vehicles includes 22 light-duty trucks. Most of the 85 vehicles were fuel injection, 

Final M6.SPD.002 8 June 2001 
with 3 carbureted passenger cars and 4 carbureted light duty trucks. Only 12 of the vehicles 

tested were certified to the Tier 1 exhaust emission standards.10 The rest are certified to the 

earlier Tier 0 emission standards. 

The vehicles tested at the EPA laboratory were recruited randomly. The vehicles tested at 

ATL were selected as a stratified random sample, with strata corresponding to IM240 pass or fail 

outcome determined at state run IM240 inspection stations in Ohio. ATL used the final phase-in 

cutpoints recommended by EPA for use in I/M programs using the IM240 test procedure to 

identify vehicles in need of maintenance. Twenty of the vehicles in the ATL sample failed the 

IM240 test. Proper analysis of the ATL data requires careful weighting of the passing and failing 

vehicles if emitter status is not considered as a factor in the analysis. 

Table 4 shows the mix of EPA vehicle emission certification standards and fuel delivery 

technology in the sample used in this analysis. Table 5 lists all of the vehicles individually, 

showing vehicle make and model, odometer mileage, engine size and whether the vehicle passed 

or failed an IM240 test procedure using final phase-in cutpoints. Table 6 shows the mix of 

model years and vehicle class (car or truck) in the sample. 

3.3 Vehicle Testing 

All vehicles were tested using the driving cycles described in Section 3.1 above in the asreceived condition using vehicle certification test fuel. Testing of vehicles was done on the 

cycles in random order to reduce any order bias. Vehicles were tested at FTP ambient conditions 

(i.e., temperature and humidity). Emission results were measured both as composite “bags” and 

in grams second by second. Only the bag results were used in this analysis. 

4.0 STATISTICAL ANALYSES 

The purpose of the testing using the new facility cycles was to determine the effects of 

“real world” representative driving behavior on basic (LA4) emissions. Separate cycles were 

developed for freeway and arterial/collector roadways to allow comparison of those two roadway 

types. The testing program also “over sampled” high emitting vehicles in order to provide a 

sufficient sample size to allow separate analysis of high emitting vehicles. Although vehicle 

mileage (or vehicle age) is considered important for estimating emissions, it is not thought that 

vehicle mileage is a factor in the effect of average speed on emissions. Together, the following 

testing and vehicle parameters were considered as potentially important in determining the effect 

of average speed on emissions: 

1. Emitter status. 

2. Roadway type. 

3. Vehicle class. 

4. Exhaust Emission Standard. 

Final M6.SPD.002 9 June 2001 
These parameters subsume a host of other potentially important parameters, such as 

technology differences. The statistics of each list item will reflect the variability in emissions 

from a larger set of parameters that are subsumed within the list item. 

The data from the vehicles tested using the new facility cycles were evaluated to 

determine if the effect of the average speed on emissions differed significantly by these 

parameters. The sections below (Sections 4.1 through 4.4) discuss the statistical results for each 

parameter evaluated. Section 4.5 discusses the statistical support for the convergence of the 

freeway and arterial/collector estimates. Section 4.6 summarizes the conclusions derived from 

the statistical analysis. Section 5 describes the final methodology. 

Although the vehicle pool contains a large range of model years (1983 through 1996 

model years), the total sample size (85 vehicles) was not sufficient for analysis explicitly by 

model year or age. For this analysis, any model year dependency is assumed to be captured by 

through the emission standards. 

Table 7(a-c) shows sample means and standard deviations for the combined dataset for 

each cycle, stratified into high and normal emitter levels. A vehicle may be a Normal emitter for 

one pollutant, but considered a High emitter for another. In some cases the sample sizes 

(Normal and High) do not sum to 85 vehicles. This is because some test results on some vehicles 

were voided due to errors in the testing or sampling and could not be used. No valid emission 

test results were eliminated from the analysis. 

Figure 1(a-c) graphically shows the effects of average speed on emissions. Each point is 

the ratio of the mean for the emissions of each of the 14 facility cycles versus mean emissions for 

the LA4 (Urban Dynamometer Driving Cycle) for the same vehicles. The data show that the 

high emitting vehicles do not exhibit as much sensitivity to speed, resulting in smaller ratios. 

It was expected that as the average speed increases the difference between emissions from 

cycles representing arterial/collector roadways and emissions from cycles representing freeways 

would decrease. An analysis was done to confirm the observed convergence of freeway and 

arterial/collector roadway emissions versus average speed. This analysis is discussed in Section 

4.5 below. 

The method of analysis of variance was used to judge the effect of the above parameters 

on the relation between average speed and emissions. The dependent variables in these analyses 

were chosen to be the logarithm of grams-per-hour emissions. The grams-per-hour measure is 

more stable than grams-per-mile, particularly at lower speeds, where very little distance is 

traveled over a long time. The log transformation yields values that better satisfy the ANOVA 

test requirements of normally distributed constant-variance errors. In the actual fitting of speed 

correction factor equations, described in Section 5, gram-per-hour units were used for analysis at 

average speeds less than 30 mph. However, at high speeds (average speeds above 30 mph), 

using a linear fit and grams per hour units, when converted back to grams per mile, forces a curve 

Final M6.SPD.002 10 June 2001 
shape (tailing downward) which does not match the data trends (tailing upward). For speeds 

above 30 mph, gram per mile units were used. The resulting equation has the following form: 

Emissions AverageSpe ed = Exp ( A + B * AverageSpeed ) 

Where Emissions are reported in units of grams-per-hour for segments covering speeds 

below 30 mph and Emissions are reported in units of grams-per-mile for segments at speeds 

above 30 mph. The coefficients A and B are determined from the linear regression of the log 

transformed speed cycle results and the average speed of the speed cycles. 

Table 8 reports the ANOVA results in terms of p-values associated with tests of the 

various factors described above. The p-value gives a concise way of judging statistical 

significance. The p-value of a test is the smallest level of significance at which the null 

hypothesis can be rejected. In these models, the null hypothesis states that the levels of a given 

factor, e.g., roadway type, have equal effect on emissions. The level of significance for this test is 

the probability of rejecting the null hypothesis when it is true. That is, of falsely concluding that 

a difference exists. This will be referred to as a Type I error. By convention, the level of 

significance is chosen to be arbitrarily small, typically 0.05, in order to limit the occurrence of 

Type I error. If p is smaller than the chosen level of significance, the null hypothesis is rejected in 

favor of the claim that a difference exists. 

For example, in comparing the normal and high emitter classes of total hydrocarbons, 

Table 8 reveals a p-value of 0.000 for the main effect of the emitter class. In graphical terms, the 

main effect captures the intercept of a line relating (the logarithm of the) emissions to speed. 

Thus, the small p-value provides support for the rather obvious hypothesis that high emitters 

have different average emissions than normal emitters. However, for the interaction of emitter 

class with speed, the p-value is 0.1411, implying that the difference in the slopes (the relationship 

between emissions versus average speed) of the normal and high emitter lines (regressions) is not 

statistically significant. 

Further, more detailed ANOVA results are shown in Appendix A at the end of this report. 

Below are the statistical results for the individual factors. 

4.1 Emitter Status 

The sample was separated into “emitter status groups” based on their Hot Running LA4 

exhaust emissions. Hot Running LA4 are emissions that would result from an FTP test which 

does not include any engine starts. These emissions are intended to be the basic unit of exhaust 

emissions for use in MOBILE6.11 The emitter status groups were defined by the following 

pass/fail cutpoints: 

� 0.8 g/mi Total Hydrocarbons (THC) 

� 15 g/mi Carbon Monoxide (CO) 

Final M6.SPD.002 11 June 2001 
� 2.0 g/mi Oxides of Nitrogen (NOx) 

These are the final phase-in cutpoints recommended by EPA for use in I/M programs 

using the IM240 test procedure to identify vehicles in need of maintenance. A vehicle is 

considered a Normal emitter if its emissions are less than or equal to the cutpoint level for that 

pollutant. It is considered a High emitter if its emissions exceed the cutpoint level for that 

pollutant. Once a vehicle is identified by emitter status for a pollutant using the Hot Running 

LA4 emission results, it is always categorized that way in this analysis, regardless of its emission 

results on another driving cycle. The cutpoints were not used in combination. A vehicle could 

be considered as a Normal emitter for the CO analysis even if it were designated as a High 

emitter for NOx or THC.

 Table 8 confirms that the average emissions differ statistically by emitter class. The 

speed variable also is significant, i.e., emissions vary with average speed. However, except for 

CO, the emitter class-speed interaction is statistically non-significant. 

While it is not always the case that the other factors available for analysis in the data 

sample - roadway type, vehicle type, and emissions standard - interact statistically with emitter 

class, engineering judgement warrant modeling these factors separately for normal and high 

emitters. Statistical conclusions for these factors are presented next. 

4.2 Roadway Type 

For modeling in MOBILE6, four roadway types are considered: arterial/collectors, 

freeways, freeway ramps and local roads. With arterial/collectors and freeways, the range of 

average speeds in the facility cycles overlaps at speeds below 30 mph. At higher speeds, only 

freeway cycles are available. The interaction between roadway type and vehicle type and 

between roadway type and emission standard was examined. 

Figure 2 (a-c) shows the effects of average speed on emissions in terms of the ratio of the 

means for the emissions versus emissions for the LA4 (Urban Dynamometer Driving Cycle) for 

normal emitting vehicles. The cycles representing freeway driving and arterial/collector driving 

are connected with lines to show the difference in these road types versus average speed. The 

Unified Cycle (LA92), the Area-wide Non-Freeway cycle, Local Roadway cycle and Freeway 

Ramp cycle results are also shown in the figures. The same vehicles were tested on all cycles, so 

differences between freeways and arterial/collectors are controlled for the vehicle effect. 

The emissions data were compared statistically to determine if there is reason to model 

arterial/collectors and freeways separately. The ANOVA results appear in Table 8. For all 

pollutants in the normal emitter class, the main effects are statistically significant. The speed 

interaction effects also are significant, albeit marginally so for hydrocarbons. Among high emitter 

vehicles, only NOx exhibits a significant difference between the arterial/collector and freeway 

road types. 

Final M6.SPD.002 12 June 2001 
Since only freeway cycles are represented at speeds over 30 mph, no comparisons of 

roadway type are required. Local roadways and freeway ramps are represented by only a single 

cycle each and therefore cannot be analyzed for the effect of average speed. 

4.3 Vehicle Class 

Of the 85 vehicles in the facility cycle sample, 22 are light duty trucks. The high emitters 

among the trucks number three for NOx, six for CO and 10 for THC/NMHC. In the freeway and 

arterial/collector roadway categories, for the normal emitters, the ANOVA results for passenger 

cars versus light duty trucks in Table 8 show significant main effects. However, the interaction 

with speed effects all are non-significant. For the high emitters, none of the vehicle type 

comparisons is statistically significant at the 0.05 level. 

For the local and freeway ramp driving cycles, the results are mixed for normal emitter 

vehicles. NOx emissions differ at the 0.05 level on both cycles and CO is significant for the 

ramp cycle. Among high emitters, vehicle type is not significant for any of the pollutants on 

either cycle. 

4.4 Emission Standard 

It was expected that vehicles certified to the new Tier 1 exhaust emission standards would 

exhibit a different response to average speed than the Tier 0 vehicles. Since the facility cycle 

sample contains only 12 Tier 1 vehicles, a method was developed for increasing the sample size 

by reclassifying a portion of the Tier 0 vehicles in the sample. Vehicles were defined as “Clean” 

Tier 0 vehicles if their emissions were less than 70% of both the NMHC and NOx Tier 1 

certification standard as measured on the standard FTP test. The Tier 1 standards are: 

o NMHC standard: 0.25 g/mi (< 50,000 miles), 0.31 g/mi (>50,000 miles). 

o NOx standard: 0.4 g/mi (< 50,000 miles), 0.6 g/mi (>50,000 miles). 

A total of eight clean Tier 0 vehicles were identified by this criterion. One Tier 0 vehicle 

(number 5016) had low FTP Bag 1 and Bag 3 emissions and technically qualified for 

reassignment. However, because it had large Bag 2 and IM240 emissions, it was not considered 

representative of Tier 1 emission behavior and thus retained Tier 0 status under the new 

definition. The clean Tier 0 vehicles were used both in the analysis of both Tier 0 and Tier 1 

emission levels. Table 9 shows the subset of 20 vehicles used to represent Tier 1 emission 

behavior. Tables 11 (a-d) show the average emissions for each driving cycle in the sample of 

normal emitting Tier 0 vehicles, high emitting Tier 0 vehicles and the expanded sample of 

vehicles considered normal emitting Tier 1 vehicles. Figure 3 (a-c) compares the Tier 0 and the 

expanded Tier 1 sample of vehicles for the difference in the effects of average speed on 

emissions. Emissions are shown in terms of the ratio of the means for the emissions versus 

emissions for the LA4 (Urban Dynamometer Driving Cycle). 

Final M6.SPD.002 13 June 2001 
The ANOVA results in Table 8 compare emissions of the Tier 0 and Tier 1 vehicles for 

the reallocated sample. On the arterial/collector and freeway cycles, for normal emitters the 

emissions standard main effect is highly significant for all pollutants, and the interaction with 

speed is significant for hydrocarbons. (The results are similar for the official emission standard 

classification.) For the local and freeway ramp facility cycles, all main effects are also significant. 

There were no high emitter Tier 1 vehicles for any of the pollutants, so no test of the 

standard factor can be made for that emitter class. 

4.5 Convergence of Freeways and Arterial/Collectors 

The data show a statistical difference between the freeway and arterial/collector cycles 

below 30 mph, where the data overlaps. However, there are no arterial/collector cycles above 

24.8 mph and there are no freeway cycles below 13.1 mph. If the speed correction factors for 

both of these roadway types are to cover the entire spectrum of average speeds available in the 

MOBILE6 model (0 to 65 mph), then some assumptions about the effect of average speed on 

emissions will need to be made for the speeds outside the typical range for these roadways. 

Based on the facility cycle emission testing results, it appears that as average speed 

increases there is a decrease in the difference between emission results for arterial/collector 

cycles and freeway cycles at the same average speed. This suggests, that above a certain average 

speed, the same relationship between average speed and emissions can be used for both freeways 

and arterial/collector roadways. 

Support for the hypothesis that mean gram-per-hour emissions of arterial and highway 

driving converge in the neighborhood of 30 mph can be found in the data from tests on the cycles 

that represent these two forms of driving. Consider the following model of emissions: 

Y = b0 + b1X + b2*D + b3X*D 

where Y is emissions (in grams/hour) of a given pollutant; X is average speed of the cycle tested; 

and D is a dummy variable representing road type (D = 0 for arterial, D = 1 for highway). This 

equation effectively models two lines. When D = 0, the function estimates emissions versus 

speed for arterials, with slope b1 and intercept b0. When D = 1, the line represents highway 

emissions with slope (b1 + b3 ) and intercept (b0 + b2). 

This model is useful for examining differences between arterial and freeway emissions. 

The basic question of whether the linear functions differ is answered by testing the coefficients of 

terms involving variable D. If both these coefficients ( b2 and b3) are zero, then the road types are 

judged to be the same. For the 85 car sample, tests of this hypothesis are rejected for all 

categories of emission standard and emission level. 

Given that arterial and highway speed-emissions lines are significantly different, we now 

Final M6.SPD.002 14 June 2001 
ask if they differ at a chosen speed, e.g., 30 miles per hour. This is answered by constructing an 

appropriate function of the linear model described above. When X = 30, the function becomes: 

Y = b0 + b1*30 for arterials 

Y = b0 + b1*30 + b2*1 + b3*1*30

 = (b0 + b2) + (b1 + b3)*30 for highways 

The two functions are identical when the linear combination b2 + b3*30 equals zero. This 

hypothesis can be tested using the ESTIMATE feature of the SAS GLM procedure. 

Table 10 presents results of these tests for Tier 0 normal and high emitters, and for Tier 1 

normal emitters. At the five percent level, a significant difference is found in only in one case, 

for Tier 0 normal CO emissions. This gives strong support for the claim that arterial/collector 

roadway and freeway emissions are similar at speeds around 30 mph, even though their 

relationship at average speeds below 30 mph is different. Based on this convergence, EPA has 

concluded that the relationship between average speed and emissions for arterial/collector 

roadways and freeways should be the same at average speeds above about 30 mph. 

4.6 Summary 

The statistical analysis of the important parameters resulted in the following decisions 

about how the data would be grouped for the MOBILE6 analysis: 

Roadway Type 

There will be different equations for the two roadway types (freeways and 

arterial/collectors) for CO and NOx emission at both High and Normal emitter groups. There 

will be different equations for the two roadway types for THC and NMHC emissions only for 

normal emitting vehicles. Since the equations converge, there will be only one equation for all 

roadway types and pollutants at average speeds above about 30 mph. The exact average speed 

where the equations converge varies. For high emitting Tier 0 vehicles there will be no 

difference between the two roadway types for THC and NMHC emissions at any average speed. 

Vehicle Class 

There will not be different equations for vehicle class (car versus truck). The equations 

used will depend on emission level (below), which will adequately cover any emission standard 

differences between cars and trucks. Splitting the data by both emission standard (below) and 

vehicle class would make sample sizes much too small for any meaningful results. 

Final M6.SPD.002 15 June 2001 
Emission Standard 

There will be separate equations for Tier 0 and Tier 1 emission standard vehicles for 

normal emission levels. There are no high emitting Tier 1 vehicles in the sample. 

Emission Levels 

The Tier 0 emission standard data will be further separated by emitter status (Normal and 

High) for all pollutants with separate speed equations for each. For the purpose of analysis, this 

effectively results in three samples of vehicles representing three distinct emission levels: 

� Level 1 : Tier 1 (Normal emitter) 

� Level 2 : Tier 0 (Normal emitter) 

� Level 3 : Tier 0 (High emitter) 

5.0 EMISSION LEVEL CALCULATION 

Once the appropriate aggregations for the existing data were determined as described in 

the previous section, least square linear regressions were fit to the emission results versus 

average speed. This was done in a “multi-linear” fashion (piece-wise linear function, 

continuous), rather than using a single line or using another non-linear curve shape. Attempts to 

fit non-linear curves to the total data sample resulted in unacceptably high error coefficients. A 

linear fit of smaller groupings of the data provided a closer fit to the data. A separate linear 

regression was done for different groupings of cycles based on ranges of average speeds. 

Together, these lines will define the change in emissions of the sample over the entire range of 

average speeds. 

5.1 Freeway Versus Arterial/Collector Effects 

As discussed in the previous section, the data show a statistical difference between the 

freeway and arterial/collector cycles below 30 mph, where the data overlap. However, there are 

no arterial/collector cycles above 24.8 mph and there are no freeway cycles below 13.1 mph. If 

the speed correction factors for both of these roadway types are to cover the entire spectrum of 

average speeds available in the MOBILE6 model (0 to 65 mph), then some assumptions about 

the effect of average speed on emissions will need to be made for the speeds outside the data 

range. 

Logically, both curves will converge at idle (zero mph). Idling emissions should not 

depend on roadway type. Also, it is logical to assume that driving which has a high average 

speed must consist almost entirely of cruise with little stopping or idle, regardless of roadway 

type. This suggests a model where freeways and arterial/collector roadways have different 

emissions at normal arterial/collector average speeds, but have the same emissions at extremely 

Final M6.SPD.002 16 June 2001 
low speeds (and idle) and at higher speeds. Based on this model, EPA has defined the following 

speed/facility segments: 

o 	 High Speeds (above about 30 mph) for both freeways and arterial/collectors. 

o 	 Intermediate Speed Freeways (from 13.1 to about 30 mph) for freeways. 

o 	 Low Speed Freeways (from 7.1 to 13.1 mph) for freeways. 

o 	 Arterial/Collectors (from 7.1 to about 30 mph) for arterial/collectors. 

o 	 Extremely Low Speed and Idle (less than 7.1 mph) for both freeways and 

arterial/collectors. 

MOBILE6 will use a combined emission estimate for both arterial/collector and freeway 

facilities for THC and NMHC at the highest emission level. This will mean that, at high emitting 

THC and NMHC emission levels, that there will be no emission difference between the two 

facility types. There are still separate freeway and arterial/collector estimates for CO and NOx 

emissions at high emitting levels. 

5.1.1	 High Speeds 

A regression was done of emissions versus average speed for the three emission 

standard/emitter groups described above for the four freeway cycles with an average speed above 

30 mph (Freeway at 30.5 mph, Freeway at 52.9 mph, Freeway at 59.7 mph and Freeway at 63.2 

mph) in grams per mile for each pollutant. Tables 12a, 12b, 12c and 12d show the results of 

those regressions. All of the slope coefficients of the regressions are statistically significant, 

meaning that, with high probability, the increase or decrease in emissions versus average speed is 

different than zero. These regressions will be used to estimate the emissions of vehicles on both 

freeway and arterial/collector roadways at average speeds above the point where the equations 

converge. 

5.1.2	 Intermediate Speed Freeways 

A linear regression was done of emissions versus average speed for each of the emission 

standard/emitter groups described above for the four freeway cycles representing freeway driving 

in the most congested conditions (Freeway at 13.1 mph, Freeway at 18.6 mph and Freeway at 

30.5 mph) in grams per hour for each pollutant. Tables 12a, 12b, 12c and 12d show the results of 

those regressions. These regressions will be used to estimate the emissions of vehicles on 

freeways between average speeds of 13.1 mph and about 30 mph. Note that the freeway cycle at 

30.5 mph was included in both the intermediate speed freeway and high speed estimates. It is 

expected that the two regressions should converge at about this average speed. 

5.1.3	 Low Speed Freeways 

None of the existing facility cycles for freeway driving have an average speed below 13.1 

mph. It will be assumed that at speeds lower than 7.1 mph (the average speed of the New York 

Final M6.SPD.002 17	 June 2001 
City Cycle) the effect of average speed on emissions will be the same for freeways and 

arterial/collector roadways. The emissions of freeway driving for average speeds between 13.1 

mph and 7.1 mph will be calculated by linear interpolation between these emission levels in 

grams per hour. Tables 12a, 12b, 12c and 12d show the resulting equations representing this 

interpolation. Most freeway travel will occur at average speeds well above this range. 

5.1.4 Arterial/Collectors 

The freeway cycle at 30.5 mph (already included in the freeway estimate) was included in 

the arterial/collector roadway estimates as well. It was shown that the two regressions should 

converge at about this average speed. The New York City Cycle was also included in the 

arterial/collector roadway estimates. The New York City Cycle was not derived from the same 

chase car or instrumented data used to develop the other facility cycles. However, the New York 

City Cycle was originally developed as a speed correction cycle and, as shown in Table 3, does 

contain acceleration rates higher than those contained in the LA4 (Urban Dynamometer Driving 

Schedule). It was deemed that the New York City Cycle was representative of “real world” 

representative driving and could be included in the analysis as another facility cycle. 

A linear regression was done of emissions versus average speed for each of the emission 

standard/emitter groups described above for the arterial/collector cycles (Arterial/Collector at 

11.6 mph, Arterial/Collector at 19.2 mph, Arterial/Collector at 24.8 mph) in grams per hour for 

each pollutant. Included in that regression was data from the New York City Cycle (with and 

average speed of 7.1 mph) and the Freeway at 30.5 mph cycle for the same vehicles. 

Tables 12a, 12b, 12c and 12d show the results of those regressions. These regressions 

will be used to estimate the emissions of vehicles on arterial/collector roadways in this range of 

average speeds. 

5.1.5 Extremely Low Speeds and Idle 

No data was collected for the vehicles in the sample at speeds lower than 7.1 mph (the 

average speed of the New York City Cycle). In this range the model will assume that the effect 

of average speed on emissions will be the same for freeways and arterial/collector roadways. 

Since the MOBILE5 model already has estimates for the effect of average speed on vehicles at 

speeds from 2.5 to 7.1 mph, and since there is no need to differentiate this effect by facility type, 

the existing speed correction factors in MOBILE5 will be used for this range of average speeds 

for both freeways and arterial/collectors. 

The MOBILE5 speed correction factors do not match the new speed correction factors at 

7.1 mph. This discontinuity will be resolved by adding the difference in the two estimates to 

values calculated using the old MOBILE5 speed correction factors. As in MOBILE5, emissions 

at idle will be assumed to be the same (in grams per hour) as the emissions at 2.5 mph (the 

lowest average speed modeled). 

Final M6.SPD.002 18 June 2001 
5.2	 Local Roadways and Freeway Ramps 

There is only one cycle each to represent driving on local roadways and freeway ramps. 

As a result, these cycles are not included in the analysis of emissions versus average speed. 

However, the data from these cycles were separated using the same sample splits by emission 

standard (Tier 0 versus Tier 1) and emitter status (Normal versus High) as are used for the 

freeway and arterial/collectors. The average emission levels were analyzed as a quadratic 

function of the base emission rate (hot running LA4 emissions). The local roadway regressions 

do not include a constant (gram per hour) value, since it is assumed that driving on these 

roadways does not include offcycle driving behavior. These regressions will be used to estimate 

the emission levels for these roadway types as a function of the base emission rate calculated in 

MOBILE6. The coefficients for these regressions are shown in Table 13. 

5.3	 Special Cases 

Ideally, the equations above would define a rational, smooth relationship for emissions 

versus average speed for the range of 0 to 65 mph for each pollutant based on the available data. 

However due to vagaries of using observed driver behavior data and the use of a multi-linear 

modeling approach, some of the equations resulting from the general approach will cause small 

discontinuities in the overall relationship. For example, the intermediate speed freeway emission 

level for NOx (computed in gram per hour) does not intersect with the high speed freeway 

emission level estimate (computed in grams per mile) at any speed. These discontinuities will 

require special handling to be coded mathematically. For MOBILE6, some basic “rules” will be 

used to assure that there are no abrupt or counter-intuitive changes in emissions versus average 

speed. 

1)	 If at 30.5 mph, the emission estimate for the intermediate speed freeway equation is still 

higher than the emissions for freeways calculated using the high speed equation, then the 

emission value calculated for 30.5 mph using the intermediate speed freeway equation 

will be used for speeds greater than 30.5 mph until the value for the high speed equation 

for that speed exceeds the intermediate speed freeway value. This rule keeps the 

intermediate speed freeway value from increasing beyond the emission level calculated at 

30.5 mph, which is the highest average speed data point used in the regression (no 

extrapolations). 

2)	 When calculating the emissions of an arterial/collector roadway, the arterial/collector 

estimate for emissions will be used unless the estimate for freeways at that same speed 

are higher than the arterial/collector estimate. This rule defines at what average speed the 

arterial/collector and freeway emission estimates will converge. Above that speed the 

arterial/collector and freeway emission estimates will be assumed to be the same. All of 

the MOBILE6 arterial/collector equations intersect with the freeway estimate between 24 

and 34 mph. 

Final M6.SPD.002 19	 June 2001 
6.0 SPEED AND OFF-CYCLE CORRECTION FACTORS
 

Using the methods in the previous section, the emission data can be described as a series 

of continuous, smooth functions for the two roadway types (freeways and arterial/collectors) by 

emission levels for all pollutants over the entire range of average speeds in MOBILE6 (2.5 to 65 

mph). This generalized relationship between emissions and average speed for any emission level 

is referred to in the model as speed correction factors. For the freeway and arterial facility types, 

these speed correction factors are the values which will be stored and used in MOBILE6 to adjust 

exhaust emission estimates to account for average speed. As discussed in the following section, 

an additional correction factor is applied for the freeway and arterial facility types to account for 

“off-cycle” emissions, separately from average speed. 

6.1 Basic Modeling Approach 

The basic exhaust emission rate generated by MOBILE6 will be based on a hot running 

LA4 emission estimate with an average speed of 19.6 mph. In MOBILE6, freeway ramp and 

local roadway emissions do not depend on speed and can be determined directly from the basic 

exhaust emission rate. For freeways and arterial/collector roadways, the adjustment to account 

for the average speed and facility type is supplemented by an additional adjustment to account for 

“off-cycle” emissions. The off-cycle adjustment is meant to capture the change in emissions 

resulting from higher power operation not reflected in changes in average speed. The speed 

correction factor (SCF) represents the change in emissions which results from a redistribution of 

vehicle operating modes which occurs an different levels of roadway congestion. The 

segregation of off-cycle and average speed effects was made in MOBILE6 primarily to assess the 

benefit of the Supplemental Federal Test Procedure (SFTP) requirement, as discussed later in 

Section 7. 

In MOBILE6, the running basic emission rate is adjusted using the following general 

method to account for off-cycle and average speed effects: 

Local Roadways and Freeway Ramps: 

Adjusted BER = BER * CF 

Where:
 

BER = Basic Emission Rate (running emissions for the LA4 cycle).
 

CF = Multiplicative correction factor 


Freeways and Arterials: 

Adjusted BER = (BER + OC) * SCF 

Final M6.SPD.002 20 June 2001 
Where:
 

BER = Basic Emission Rate (running emissions for the LA4 cycle).
 

OC = Off-Cycle Emissions Offset (a function of BER emissions)
 

SCF = Multiplicative Speed Correction Factor (a function of speed and emissions)
 

The calculation of the correction factor for freeway ramps and local roadways in 

discussed in Section 5. The remainder of this section addressed the development of off-cycle 

emissions adjustment and freeway/arterial speed correction factors.

 Using the above equation, with a BER identical to the average hot running LA4 

emissions of each sample of vehicles in each of the three emission level groupings described in 

Section 4.6, the estimate of emissions at any speed for each facility will match the average 

emission level predicted by the regression equations from the facility cycle data from that vehicle 

sample. For cases where the BER is not identical to the average hot running LA4 emissions of 

any of the facility cycle sample emission level groupings, the off-cycle adjustment OC will still 

be calculated as a function of the BER, however the SCF will be interpolated using the three 

emission level sample estimates. The interpolation would be determined by the emission level of 

the sum of the BER and the OC. There are three cases, which cover the generation of SCFs for 

any base emission level: 

o	 If the emissions were equal to one the three predetermined emission level 

thresholds, the SCF from that level would be used. 

o	 If the emissions are between levels, the SCF would be interpolated between the 

values for those levels. 

o 	 If the emissions were below the Level 1 level or the above the Level 3 level, Level 

1 and Level 3 SCF would be used, respectively. 

It is important to note that the latter case results in the Level 1 SCFs being applied for 

most vehicles and trucks under the NLEV and Tier 2 emission standards. As discussed in 

Section 7, the effects of the SFTP rule will reduce the overall adjusted emissions for vehicles 

under these programs, but the relative magnitude of the SCF (i.e. the shape of the SCF curve) 

will remain unchanged from Level 1. 

6.2	 Off-Cycle Adjustment 

It has been long recognized that the FTP does not reflect vehicle operation at higher 

speeds and accelerations, which contribute significantly to overall emissions. The maximum 

speed of the FTP is 57 miles per hour (mph), and the maximum acceleration (determined by 

limitations in chassis dynamometer technology in early 1970's) is 3.3 mph per second. A more 

direct measure of cycle stringency is power, a combined measure of speed and acceleration 

Final M6.SPD.002 21	 June 2001 
which has been found to correlate well with emissions. One metric for power is “specific 

power”, calculated according to the following equation: 

specific power = Vf

2

 - Vi

2

, Vf > Vi 

Where Vi and Vf are the initial and final velocity, respective to a one-second interval.12 Using this 

metric, the average and maximum specific power for the FTP is 192 mph2

/sec. In contrast, data 

from Baltimore gathered in the early 1990's as part of the FTP review project’s in-use driving 

surveys found a maximum specific power level of 558 mph2/sec. More importantly, the distribution 

of specific power for Baltimore showed a higher proportion of higher specific power events than the 

FTP; for example, 2.6 percent of operation on the FTP is at specific power over 100 mph2/sec, while 

6.4 percent of Baltimore events were above this threshold.13 This emissions implications of this are 

significant given the contribution of these events to overall emissions. 

 In MOBILE6, an off-cycle correction factor was developed separately from the speed 

correction factor in an attempt to isolate the effects of high power operation. An alternate 

approach would have been to create a single correction factor which accounted for both “offcycle” and speed effects; this approach was suggested by Guensler in an independent peer review 

of the off-cycle methodology, contained in Appendix E. We are maintaining these effects as 

separate adjustments, however, because emissions resulting from aggressive driving behavior and 

emissions resulting from changes in average cycle speed reflect two different processes which 

should be accounted for separately in assessing the benefit of the off-cycle provision of the 

SFTP requirement. 

The off-cycle adjustment reflects the emissions change resulting from average power 

levels higher than those on the FTP, independent of average cycle speed. In order to isolate the 

high power effects separate from changes in average cycle speed, the off-cycle adjustment was 

derived by comparing running LA4 emissions to an emission test cycle of comparable average 

speed used in the development of the freeway speed correction factor, the Freeway Level Of 

Service (LOS) F cycle. The average speed of this cycle is 18.6 mph, but the maximum 

acceleration rate is 6.9 mph/s, as opposed to 3.3 mph/s over the LA4. The average specific 

power of the Freeway F cycle is 44 mph2

/s, 15 percent higher than the 38 mph2/s of the LA4. It 

was thus assumed that significant emissions differences between this cycle could be attributed to 

the difference in cycle stringency, or off-cycle emissions. The off-cycle correction factor is a 

function of base running emissions, relating the difference in emissions between the freeway 

LOS F cycle and the LA4 to base running (LA4) emissions, as shown in the following equation: 

Off-Cycle (g/mi) = Freeway F(g/mi) - LA4(g/mi) 

The data underlying the off-cycle emission effects is from EPA testing of 85 cars and trucks 

with model years 1983 through 1996 (the same sample used for generating the SCFs). The sample 

consisted of 63 cars and 22 light trucks that received emissions tests on both the LA4 and Freeway 

F cycles. The additive approach of the equation above was used for all three pollutants. The overall 

Final M6.SPD.002 22 June 2001 
 

 

model hypothesis was that ultimately only a vehicle’s base LA4 emissions was significant in 

determining the off-cycle emissions. Other variables potentially significant to emissions generation 

such as vehicle type, model year, and fuel delivery system were accounted for in the base emission 

rates, and were eliminated from the model through stepwise regression because of insufficient 

statistical significance. 

6.2.1 CO Off-Cycle Emission Effects 

Prior to the analysis of the CO emission off-cycle effects, the data was examined in a 

graphical form, and found to contain considerable scatter for vehicles with high CO emissions. 

12 data points were between 10 and 100 grams/mile, in general an order of magnitude higher 

than the remaining 73 data points. As a result of the scatter and the potential for these high 

emission vehicles to have an unrepresentatively large influence on the final model, it was decided 

to separate the sample into high and normal emitters based on a given vehicle’s overall FTP 

emission level. The threshold emission level dividing the ‘normal’ and ‘high’ emitters that was 

chosen was 10.2 g/mi over the FTP, or three times certification standard. This level was chosen 

to maintain consistency in the definition of ‘high’ emitter throughout MOBILE6. 

Least squares regression was performed separately on both the normal and high emitter 

samples. The CO Off-Cycle emissions as defined in Equation 4 were least squares regressed 

versus LA4 CO emissions, LA4 CO emissions squared, fuel delivery type, vehicle type (car or 

truck), and model year. For the ‘normal’ emitters, stepwise regression with a 5 percent 

significance requirement (p-value < 0.05) eliminated all of the variables except the LA4 CO 

emissions and LA4 CO emission squared terms. For the ‘high’ emitters, stepwise regression 

eliminated all of the variables. A subsequent regular regression showed that none of the 

variables were close to being statistically significant. All of the statistical results are shown in 

Appendix A. 

The fit which was chosen to represent the CO off-cycle emissions in normal emitters in 

MOBILE6 was a quadratic linear fit of the CO off-cycle offset versus running LA4 CO emissions. 

This regression fit was force through zero because it is believed that off-cycle emissions will be zero 

on zero emitting LA4 vehicles. The regression equation proposed for use in MOBILE6 for normal 

emitters is shown the the following equation 

OCCO = 0.984 * LA4CO - 0.07638 * (LA4CO)2 

Where: 

OCCO is the CO emission increase due to off-cycle operation in g/mi. 

LA4CO is the base CO emission level over the LA4. 

A regression analysis of the high emitting vehicles resulted in no significant predictors of the 

off-cycle offset, including LA4 CO emissions. The average results was also not significantly 

Final M6.SPD.002 23 June 2001 
 

 

 

 

 

 

 

different from zero. Thus, we are establishing the off-cycle offset for CO high emitters at zero. A 

likely explanation for this is that high emitting CO vehicles are likely already experiencing excess 

enrichment over the LA4, which the increase in cycle stringency is not exacerbating. 

The CO Off-Cycle effect as a function of LA4 CO emissions is shown in Figure 8a. The line 

annotated with circles is CO off-cycle effect for the ‘Normal’ emitters. The zero line is the CO offcycle effect for ‘High’ emitters. 

6.2.3 HC Off-Cycle Emission Effects 

In the case of hydrocarbon emissions, the base LA4HC emission level and the squared value 

of the LA4HC were found to be the only statistically significant variable using as stepwise 

regression process. Segregation of the data into low and high emitters was not found to be necessary 

in the case of HC offset. The full regression statistics are shown in Appendix A. 

The equation predicting the NMHC off-cycle offset in units of g/mi is shown in the following 

equation. The equation and the underlying data are also shown in graphical form in Figure 8b. 

OCHC = 0.305 * LA4HC - 0.02492 * (LA4HC)2 

Where: 

OCHC is the HC emission increase due to off-cycle operation in g/mi. 

LA4HC is the base HC emission level over the LA4. 

Since the THC off-cycle emission fit is a quadratic in form, it produces a peak offset which 

declines and eventually goes negative. The maximum THC off-cycle offset is 0.933 g/mi and occurs 

when the base LA4 THC emission level equals 6.12 g/mi (See Figure 2). It was decided that the 

value of the THC offset would be fixed at 0.933 g/mi for all LA4 emission levels exceeding 6.12 

g/mi rather than let it decline. The rationale for this assumption is that it is counter-intuitive to 

expect that the lightly loaded LA4 cycle would produce HC emission levels which are less than or 

even declining relative to the Freeway F emission cycle. The HC offset function’s maximum occurs 

at a LA4 emission level which is virtually out of the range of the running LA4 HC emission levels 

in the model. Only very high emitting older model year light vehicles will approach a value of 6.12 

g/mi running LA4. Thus, the assumption of a maximum offset value of 0.933 g/mi THC will rarely 

be invoked. 

6.2.3 NOx Off-Cycle Emission Effects 

Similar to HC, for NOx only the base LA4 emission level, its squared value, and an intercept 

forced through zero were found to be statistically significant. Segregation of the data into low and 

high emitters was also not found to be necessary in the case of NOx offset. The full regression 

statistics are shown in Appendix A. The equation predicting the NOx off-cycle offset in units of 

g/mi is shown in Equation 8. 

Final M6.SPD.002 24 June 2001 
Since the NOx off-cycle emission fit is a quadratic form, it produces a peak offset which 

declines and eventually goes negative. The maximum NOx off-cycle offset is 0.58 g/mi and occurs 

when the base LA4 NOx emission level equals 3.50 g/mi (See Figure 3). At higher NOx levels, 

the downward trend is dictated by limited data, and as a result we have decided to impose an 

artificial cap of 0.58 g/mi for all LA4 NOx emission levels exceeding 3.50 g/mi rather than let it 

decline. On late model light vehicles, only the very high emitter levels will approach a value of 3.50 

g/mi running LA4 (for comparison the current FTP certification standard is 0.40 g/mi NOx). Thus, 

the assumption of a maximum NOx off-cycle offset value of 0.581 g/mi will rarely be invoked. 

OCNOX = 0.332 * LA4NOx - 0.04745 * (LA4NOx)2 

Constraint: LA4NOx <= 3.50 g/mi 

OCNOX = 0.58 g/mi 

Constraint: LA4NOx > 3.50 g/mi 

Where: 

OCNOX is the NOx emission increase due to off-cycle operation in g/mi. 

LA4NOx is the NOx emission level over the LA4. 

6.3 Calculating Speed Correction Factors 

As discussed in Section 6.2, MOBILE6 adjusts the basic exhaust emission rates (BER) by 

first adding an emission value which accounts for off-cycle emissions (OC). From this point, 

SCFs are generated to account for changes in facility type and average speed. For freeway and 

arterial roadways, the SCF is applied as a multiplicative adjustment directly to the sum of the 

BER and the off-cycle adjustment. 

The SCF is defined as the ratio of the predicted emissions at any average speed to the 

predicted emissions at 19.6 mph for freeways for the same vehicle. Using the emission level 

equations described in Section 5, a set of SCFs will be determined for each speed in increments 

of 5 mph beginning at 5 mph through 65 mph and at 2.5 mph for each of the three emission 

levels within MOBILE6. These increments correspond to the increments of average speed for 

the VMT average speed distribution for freeways and arterial/collector roadways in MOBILE6. 

MOBILE6 calculates these speed correction factors directly from the emission levels, rather than 

store the resultant speed correction factors themselves. Table 16 shows the freeway SCF sets for 

the three emission levels. These SCF sets are shown graphically in Figures 5a, 5b, 5c and 5d. 

Table 16 shows the freeway emissions at 19.6 mph for each emission level. Table 17 shows the 

arterial/collector SCF sets for the three emission levels. 

The vehicle miles traveled (VMT) average speed distribution for freeways and 

arterial/collector roadways in MOBILE6 represent the distribution of speeds for the area to be 

Final M6.SPD.002 25 June 2001 
modeled. Each average speed bin is the fraction of all miles traveled which occurs within a 

given speed range. For example, the 30 mph bin will include the miles traveled on links where 

the average speed is between 27.5 mph and 32.5 mph. The sum of the distribution fractions must 

always be one. If only a single roadway is to be modeled, the average speed can be entered as 

two adjacent bin values whose average speed matches the average speed for the roadway. In this 

case, all other speed bin values would be zero. MOBILE6 is intended to model average roadway 

speeds and cannot model the emissions of vehicles at an instantaneous (cruising) speed. 

6.4 Test for Model Stability 

Guensler’s peer review comments (Appendix E) suggested a method to test for the 

stability of the overall off-cycle and speed modeling methodology. This method was to develop 

an alternative model in which the off-cycle adjustment was generated using a facility cycle other 

than FWYF (LOS B or C was specifically suggested), and comparing the results of this alternate 

model to that used in MOBILE6 on other LOS cycles, or an independent data set. Guensler 

suggested that if the alternate model was shown to predict the same results as the MOBILE6 

approach over the range of LOS cycles, the model estimation approach would be shown to be 

stable. 

Overall, we expect that the suggested approach would yield similar results no matter what 

cycle was used as the basis for the off-cycle adjustment and SCFs. This is because the off-cycle 

adjustment is simply the expression of the emission increase between the LA4 and a single cycle 

(FWYF in this analysis), and the SCFs are in turn the expression of the emission increase from 

any average speed relative to that same cycle. Changing the base cycle will not change this 

overall relationship; if the relationship between the LA4 and base cycle were changed, the SCFs 

would change accordingly, resulting in similar predictions of overall emissions. 

In demonstrate this, we formulated an alternate model for off-cycle adjustments and SCFs 

which relied on emission results from the Freeway AC cycle, one of the highest average speed 

cycles tested for this analysis (average speed of 59.7 mph). We focused on the 22 vehicles used 

to derive the “Level 1" SCFs discussed in Section 5. We then used this alternate model to predict 

arterial emissions at 11.6 mph (average speed of the Arterial E cycle), representing the lowest 

end of the speed range and relatively high SCFs. The hypothesis was that if stability were shown 

at the low end of the speed range where SCFs are the highest, it could be inferred on the 

remainder of the speed curve. 

The base and alternative models are shown in Table 6-1, along with the prediction of 

mean emissions for arterials at 11.6 MPH. The means show less than 3 percent difference 

between the two models, and 95 percent confidence intervals confirm this difference is not 

significant. This analysis suggests that the modeling approach used to estimate off-cycle 

emissions and SCFs would result in stable emissions predictions regardless of which cycle is 

used as the base cycle. 

Final M6.SPD.002 26 June 2001 
Table 6-1: Test For Model Stability for Arterial at 11.6 mph 

Pollutant Model 

Approach 

Model Formulation 

(LA4 + Off-Cycle Adjustment)*SCF 

Predicted Level 1 

emissions (g/mi) ± 

95% CI 

NOx MOBILE6 [LA4NOx+(0.332*LA4NOx-0.04745*LA4NOx2)]*(1.71) 0.43 ± 0.13 

Alternate [LA4NOx+(2.05*LA4NOx-4.42*LA4NOx2

)]*(1.71/1.42) 0.42 ± 0.09 

HC MOBILE6 [LA4HC+(0.305*LA4HC-0.02492*LA4HC2

)]*(1.86) 0.093 ± 0.023 

Alternate [LA4HC+(0.775*LA4HC)]*(1.86/1.24) 0.095 ± 0.023 

CO MOBILE6 [LA4CO+(0.984*LA4CO-0.07638*LA4CO2

)]*(1.34) 2.23 ± 0.91 

Alternate [LA4CO+(3.417*LA4CO-0.823*LA4CO2

)]*(1.34/1.59) 2.26 ± 0.7 

7.0 BENEFITS OF THE SFTP REQUIREMENT 

7.1 Methodology used to calculate SFTP benefit 

Increasing attention to the importance of off-cycle emissions led to the development of a 

new compliance procedure, known as the Supplemental Federal Test Procedure (SFTP). In 

addition to “off-cycle” emissions, the SFTP addresses emissions which are generated with the air 

conditioning on, which were also inadequately represented by the FTP. The SFTP requirements 

grew out of the 1990 Clean Air Act Amendments, which instructed EPA to review the existing 

procedures and revise them in whatever ways were necessary to make them more representative 

of actual in-use conditions. Developed in conjunction with the California Air Resources Board 

(ARB) and auto manufacturers, the SFTP requirement adds two additional certification cycles, 

and tailpipe standards associated with those cycles, to impose control of off-cycle (US06 cycle) 

and air conditioning emissions (SC03 cycle). The US06 is run with the vehicle in the hot 

stabilized condition; that is, with the vehicle fully warmed up to insure that the engine and 

catalytic converter have reached typical operating temperatures. The SC03 follows a 10-minute 

soak and is run with vehicle air conditioning (A/C) in operation or with an appropriate simulation 

of air-conditioning operation. 

The assigned benefits of the SFTP rule will depend on whether a vehicle is a Tier 1 

vehicle or a LEV. EPA and ARB promulgated separate requirements applying to these standard 

levels, and hence the benefits resulting from the rule must take into account the relative 

stringency of the EPA and ARB rules. Under NLEV, the Tier 1 rule will only apply to LDTs 

above 6000 pounds (LDT3s and LDT4s), which phase in to the SFTP requirement at 40 percent 

in 2002, 80 percent in 2003, and 100 percent in 2004.14 These trucks will be allowed to certify 

to the Tier 1 SFTP standards until they begin phasing into the Tier 2 final standards in 2008, at 

which point they will be required to comply with the SFTP provisions under the Tier 2 rule 

discussed below. 

Final M6.SPD.002 27 June 2001 
 

For Tier 1 and interim Tier 2 LDT3s and LDT4s, the benefits derived in EPA’s SFTP 

final rulemaking shown in Table 7-1 will be used directly in MOBILE6 (Post-SFTP CO air 

conditioning emissions are a special case, as discussed below). The percent reductions shown for 

the SFTP rule will be applied directly to the off-cycle adjustment to generate final off-cycle 

adjustments for SFTP-compliant vehicles. 

TABLE 7-1 

TIER 1 SFTP BENEFITS FROM 

OFF-CYCLE OPERATION and AIR CONDITIONING 

POLLUTANT OFF-CYCLE AIR CONDITIONING 

HC 88% 100% 

CO 72% Fuel Consumption Increase 

NOx 78% 50% 

*EPA rule estimated benefits of Tier 1 SFTP standards, in terms of percent reduction of uncontrolled “excess” 

emissions. 

A detailed derivation of these benefits are contained in the SFTP final rulemaking.15 

They were derived by comparing the emission results over off-cycle driving from a sample of 

light-duty vehicles and trucks tested in an uncontrolled condition (pre-SFTP), and with emission 

control software modifications made by vehicle manufacturers to reduce off-cycle emissions (e.g. 

eliminating commanded enrichment). This approach is consistent with that suggested by the 

Guensler comments, which suggests “comparing the percentage reduction in emissions that will 

occur for current vehicles as they move from their current emissions levels on the composite 

SFTP to the compliance emission rates...”. Because vehicles complying with the SFTP are just 

starting to enter the market, an assessment of SFTP benefit on the in-use fleet is not yet possible. 

We therefore consider the approach used in the EPA SFTP rule to be the best available. 

Under NLEV, the ARB rule will apply to LEV LDVs and LDTs under 6,000 pounds 

(LDT1/2). The ARB rule contains NOx and HC certification standards which differ from EPA’s 

both in terms of the relative stringency over the US06 and SC03 cycles, and the mileage at which 

a vehicle is required to show compliance. The percent reductions derived for EPA’s Tier 1 

ruletherefore cannot be applied directly to vehicles complying with the ARB standards. 

A sample of vehicles with emissions below the Tier 1 SFTP standards, based on 

compliance strategies developed by the auto manufacturers, were available to develop the 

benefits of EPA’s Tier 1 rule. A comparable sample was not available in which to derive 

benefits from the ARB standards under NLEV. For the purpose of MOBILE6, we therefore 

developed a methodology which estimated the percent reductions for the ARB standards on 

LEVs based on the EPA Tier 1 benefits presented in Table 1. This methodology required an 

assessment of the relative stringency of the EPA and ARB SFTP standards compared to their 

Final M6.SPD.002 28 June 2001 
respective FTP standard. Several factors added complication to this analysis: first, the ARB 

standards are applicable at 4,000 miles whereas the EPA standards are applicable at 50,000 miles 

and full useful life (100/120K miles); second, the SFTP standards are expressed at NMHC+NOx, 

while MOBILE treats these pollutants separately. Third, the SFTP standards are based on 

operation when the vehicle is warmed-up, necessitating that the warmed-up component of the 

FTP be extracted in order to performing comparisons with the SFTP standards. An analytical 

step was required to address each of these factors. 

Reductions in off-cycle emissions due to ARB’s LEV SFTP standards for NOx and HC 

were estimated through a determination of the stringency of the ARB and EPA US06 standards. 

The stringency of the ARB and EPA standards is characterized by how well they control offcycle emissions for LEVs and Tier 1 vehicles, respectively; this stringency is thus best 

determined through a comparison. A direct comparison between these standards This 

comparison was made in relation to emissions over the FTP The basis for this determination 

was a comparison between the US06/SC03 standards and an estimation of “running certification 

levels” (i.e. the running component of FTP certification levels) calculated for Tier 1 vehicles and 

LEVs, according to the following steps, shown in Tables 7-2 and 7-3: 

1) Average certification emissions for model year 1999 LDVs and LDTs were generated 

from EPA’s CFEIS database at 4,000 miles for LEVs and 50,000 miles for Tier 1 (Row 

1). The certification database used to generate these averages are provided with this 

report. 

2) “Running certification levels” were estimated for Tier 1 and LEV by multiplying the 

certification levels from Step 2 by the appropriate running BER fractions discussed in 

Draft Final MOBILE6 Report M6.EXH.007 (December 1999); 0.90 for NOx and 0.23 for 

HC. The FTP certification levels and the derived “running certification levels” are shown 

in Row 2. 

3) NMHC+NOx US06 and SC03 standards were split into separate NMHC and NOx 

standards by applying a split of 0.14/0.86 for NMHC/NOx, derived from the development 

of EPA’s Tier 1 standards, and discussed in EPA’s final SFTP rule (Rows 3 and 4). 

4) A ratio of the resulting 50,000 mile SFTP NMHC and NOx “standards” from Step 3 

and the running certification levels from Step 2 were calculated for both the Tier 1 (EPA) 

and LEV(ARB) requirements for US06 (Row 5). The ratio (R) represents the magnitude 

of increase allowed between the FTP and US06 cycles, and hence represents the 

stringency of the SFTP standard relative to the FTP standards. 

Final M6.SPD.002 29 June 2001 
 

5) The stringency of the ARB standards relative to the EPA standards were estimated by 

comparing the value of R calculated in Step 4, according to the following equation (Row 

6): 

Additional Stringency of ARB Standards (%) = [(REPA - 1) - (RARB-1)] / (REPA - 1) 

The additional stringency represents the additional off-cycle emissions which would be 

eliminated above and beyond the reductions under the Tier 1 standards. 

6) Benefits under the ARB rule were then derived by adjusting the Tier 1 benefits (Row 7) 

from Table 7-1 according to the additional stringency contained in Step 5, according to the 

following equation (Row 8): 

ARB Benefit (%) = EPA Benefit + (Step 5) * (1 - EPA Benefit) 

These steps are illustrated in Tables 7-2 and 7-3. 

Final M6.SPD.002 30 June 2001 
Table 7-2: Worksheet for Developing LEV NOx Benefits
 

Tier 1 (50K Miles) LEV (4K Miles) 

LDV/ 

T1 LDT2 LDT3 LDT4 LDV/ T1 LDT2 LDT3 LDT 4 

(1) Average FTP Certification Level 0.17 0.19 0.24 0.30 0.07 0.11 0.13 0.16 

(2) Estimated “Running” Certification Level 0.15 0.17 0.21 0.27 0.06 0.10 0.11 0.14 

(3) Estimated NOx 4K Standard (ARB) 0.12 0.22 0.34 0.52 

(4) Estimated NOx 50K Standard (EPA) 0.50 0.78 0.78 1.15

 (5) US06 Standard / Running Certification Level 3.26 4.57 3.69 4.19 1.87 2.15 3.03 3.68 

(6) Additional Stringency of ARB Standard 62% 68% 25% 16% 

(7) EPA SFTP Benefit (%) 78 78 78 78 

(8) ARB Benefit (%) 92% 93% 83% 81% 

Table 7-3: Worksheet for Developing LEV HC Benefits
 

Tier 1 (50K Miles) LEV (4K Miles) 

LDV/ 

T1 LDT2 LDT3 LDT4 LDV/ T1 LDT2 LDT3 LDT4 

(1) Average FTP Certification Level 0.10 0.10 0.10 0.13 0.03 0.05 0.05 0.07 

(2) Estimated “Running” Certification Level 0.02 0.02 0.02 0.03 0.01 0.01 0.01 0.02 

(3) Estimated NOx 4K Standard (ARB) 0.02 0.04 0.06 0.08 

(4) Estimated NOx 50K Standard (EPA) 0.08 0.13 0.13 0.19 

(5) US06 Standard / Running Certification Level 3.62 5.34 5.50 6.40 2.44 3.17 4.69 5.40 

(6) Additional Stringency of ARB Standard: 45% 50% 18% 19% 

(7) EPA SFTP Benefit (%) 88 88 88 88 

(8) ARB Benefit (%) 93% 94% 90% 90% 

Final M6.SPD.002 31 June 2001 
We consider the ARB CO standards over the US06 to be functionally equivalent to the 

EPA standards. We expect that these standards (9.0 g/mi for Tier 1, 8.0 g/mi for LEV) will serve 

as more of a cap on excess CO emissions, unlike the NOx and HC standards. As such, we are 

proposing to apply the Tier 1 benefit (78 percent) to LEVs as well. 

The resulting SFTP benefits for LEVs are presented in Tables 7-4. 

TABLE 7-4 

LEV SFTP BENEFITS OVER OFF-CYCLE OPERATION 

LDV/T1 LDT2 LDT3 LDT4 

HC 93% 94% 90% 90% 

CO 78% 78% 78% 78% 

NOx 92% 93% 83% 81% 

7.2 Applying the SFTP Benefit in MOBILE6 

The effect of the SFTP rule will be modeled in MOBILE6 by applying the percent 

reductions derived in Section 7.1 to the off-cycle adjustment (OC) for freeways and arterial 

roadways, and to the correction factor (CF) for freeway ramps. In equation form, this is 

represented as follows: 

Freeway Ramps: Adjusted BER w/ SFTP = BER * CF * (1-SFTP)_ 

Where:
 

BER = Basic Emission Rate (running emissions for the LA4 cycle).
 

CF = Multiplicative correction factor 


SFTP = SFTP benefit from Section 7.1
 

Freeways and Arterials: Adjusted BER w/ SFTP = (BER + (OC*(1-SFTP)) * SCF 

Where:
 

BER = Basic Emission Rate (running emissions for the LA4 cycle).
 

OC = Off-Cycle Emissions Offset (a function of BER emissions)
 

SCF = Multiplicative Speed Correction Factor (a function of speed and emissions)
 

SFTP = SFTP benefit from Section 7.1
 

This approach was generated based on the following assumptions about how “excess” 

emissions are generated, defined as emissions higher than the running LA4 in terms of 

grams/mile: 

Final M6.SPD.002 32 June 2001 
�	 “excess” emissions over the local roadway cycle are due solely to reduced travel 

efficiency (e.g. less distance traveled per unit of engine work), rather than off-cycle 

driving, and hence emissions will not be reduced from the SFTP. 

�	 “excess” emissions over the freeway ramp cycle are due solely to off-cycle driving, and 

hence “excess” emissions will be reduced in direct proportion to the SFTP benefits; 

�	 “excess” emissions over the freeway and arterial cycles are due to both off-cycle 

emissions and reduced driving efficiency, and hence emissions will be reduced only over 

the off-cycle driving events on these cycles, in proportion to the SFTP benefits. 

This latter situation for freeways and arterial is the primary reason why two separate 

adjustments (Off-Cycle and SCFs) have been developed to address the overall issue of driving 

behavior. Peer review comments from Guensler suggested that two separate adjustments were 

unneccessary, instead recommending that a single adjustment be developed which encompassed 

both corrections. However, the specific contribution of off-cycle emissions must be estimated in 

order to account for the benefit of the SFTP. A single adjustment factor would combine “excess” 

emissions due to both off-cycle emissions and reduced travel efficiency, making it difficult to 

estimate the benefits of off-cycle control from SFTP. 

Guensler’s peer review comments infer that applying SFTP reductions only to the offcycle adjustment translates to emission reductions not being applied on all freeway and arterial 

driving due to the SFTP. This is not the case; as indicated in the Freeway and Arterial equation 

above, reductions in the off-cycle adjustment will result in reductions over the entire speed range 

for freeway and arterial roadways. What will vary, however, is the relative magnitude of these 

reductions. The SFTP benefits reported in Section 7.1 will only be realized in full over the 

FWYF cycle, because the “excess” emissions over this cycle are assumed to be due exclusively 

to off-cycle emissions. For cycles with average speeds lower than 19.6 mph, it is not appropriate 

to treat all of the “excess” emissions as off-cycle emissions, since reduced travel efficiency 

contributes to these emissions as well. For cycles with average speeds higher than 20 mph, it is 

more reasonable to assume that excess emissions are caused predominately by off-cycle 

emissions, and hence the assumption that the SFTP rule will reduce the calculated off-cycle 

increment is likely conservative. 

7.3	 Applicability of SCFs to SFTP-compliant vehicles 

The SCFs were developed on a sample of vehicles which were not certified to comply 

with the SFTP. Given the advent of the SFTP rule, we felt it important to assess whether the 

SCFs could reasonably be applied for vehicles which would comply with the off-cycle 

requirements. We analyzed emissions results across EPA facility-specific test cycles for a subset 

of test vehicles with low off-cycle emissions; our criteria for choosing these vehicles was 

emission performance on the “Freeway Ramp” cycle, a short cycle which is meant to mimic 

driving performance while entering a freeway. As such, this cycle as high acceleration rates, 

comparable to those found on the US06 cycle. If a vehicle performs well on the Ramp cycle, we 

Final M6.SPD.002 33	 June 2001 
presume it would likewise perform well on the US06; in particular, it is likely that such a vehicle 

would have adequate catalyst volume so as to not experience severe catalyst “breakthrough”, an 

important contributor to high off-cycle emissions. 

Our criteria for choosing “clean” SFTP vehicles was whether the vehicle’s emissions over 

the ramp cycle were at or below EPA’s implied NMHC+NOx US06 standard at 50,000 miles 

(0.58 grams/mile). 20 vehicles met this criteria, and are listed in Table 7-5 along with g/mi 

emissions over the Ramp cycle. CO emissions are also listed; the US06 standard for CO is 9 

g/mi, which all of the vehicles meet, most by over 50 percent. 

Table 7-5: “Clean SFTP” Vehicles 

Vehicle Ramp 

NMHC+NOx/CO 

(g/mi) 

Vehicle Ramp 

NMHC+NOx/CO 

(g/mi) 

5021 0.13/4.6 5213 0.33/0.47 

5217 0.13/2.17 5013 0.36/2.91 

5240 0.14/0.28 5062 0.37/0.86 

5007 0.16/1.11 5060 0.38/2.52 

5229 0.20/6.5 5038 0.38/0.08 

5061 0.22/0.69 5234 0.43/1.35 

5063 0.23/0.86 5231 0.47/5.2 

5017 0.26/3.4 5059 0.53/7.8 

5018 0.30/3.4 5223 0.55/0.03 

5010 0.31/0.7 5221 0.58/2.53 

It is likely that most of these vehicles were included in the sample used to develop the 

“Level 1" (low emission) MOBILE6 speed correction factors. Hence, the comparison is not of 

two completely independent data sources. The main purpose of this exercise is to assess whether 

the SCFs which were developed with pre-SFTP vehicles in mind can reasonably be applied to the 

subset of vehicles we project would comply with the SFTP requirement. It is important to note 

that, because of the SFTP benefits discussed in Section 4, speed-corrected emissions will be 

lower for SFTP-compliance vehicles than for pre-SFTP vehicles, even if the same SCFs are 

applied. At issue is whether the relative increase in emissions observed for pre-SFTP vehicles 

across the speed range applies to post-SFTP vehicles as well. 

Final M6.SPD.002 34 June 2001 
We computed average emissions from this sample for the freeway, arterial, and local 

facility-specific test cycles used to develop the SCFs presented earlier in this paper. We then 

divided these emissions by that of the Freeway F cycle, which is approximately the basis for 

generating the MOBILE6 SCFs. In this way, we could develop SCFs specifically for the clean 

SFTP vehicles, and compare them to the “Level 1" SCFs proposed for MOBILE6. 

The results of this comparison are shown in Figures 9a-9c for NOx, HC and CO. As 

shown by these charts, the SCFs for vehicles with low off-cycle emissions are consistent with 

the MOBILE6 SCFs. From this we conclude that it is reasonable to apply the MOBILE6 SCFs to 

vehicles which comply with the SFTP. 

8.0 Application in MOBILE6 

The speed corrections described in this document are applied to gasoline fueled, lightduty vehicles (cars and light trucks) of all model years and technologies. The speed correction 

factor would be applied to the basic exhaust hot running emission rates, adjusted to freeway 

emission levels at 19.6 mph. Additional adjustment would be made to the freeway emission 

estimate between 7.1 and about 30 mph to account for arterial/collector roadways. MOBILE6 

would continue to use the existing speed correction factors and methodology found in MOBILE5 

for diesel vehicles, gasoline fueled heavy-duty vehicles and motorcycles. Heavy-duty diesel 

vehicles will also be adjusted for NOx excess emissions separately from the MOBILE6 speed 

correction factors. 

In MOBILE6, the daily average emission rate will be calculated by VMT weighting an 

emission estimate for each hour of the day. Within each hour of the day, there will be a 

distribution of speeds (either a default national average or a user supplied distribution) for 

freeways and arterial/collectors. The speed correction would be applied to the estimate of 

Normal and High emitters within each model year separately. Older (pre-1981) model year 

gasoline fueled, light-duty vehicles will have only composite (combined Normal and High) basic 

exhaust emission rates. In these cases the speed correction will be applied to the composite basic 

exhaust emission rates (including both Normal and High emitters). Speed correction factors will 

not be applied to the effects of engine start on emissions estimated by MOBILE6. 

The speed distribution in MOBILE6 will consist of average speed “bins” from 5 to 65 

mph in 5 mph increments and for 2.5 mph (14 speed bins) representing the distribution of 

average speeds within each hour.16 Each hour of the day will have an estimate of the distribution 

of vehicle miles traveled (VMT) on freeways, ramps, local and arterial/collector roadways. 

These distributions will be used to weight together the emission estimates in each speed bin to 

give an hourly emission estimate. Freeway Ramps and Local Roadways will have hourly 

emission estimates and VMT estimates, but will not have speed distributions. The hourly 

emission estimates will be weighted by the hourly VMT distribution separately for each facility. 

Finally, the VMT distribution between facilities will be used to combine the results into an areawide running exhaust emission estimate. Emissions due to engine start within each hour will be 

calculated separately. 

Final M6.SPD.002 35 June 2001 
In summary, MOBILE6 will: 

o 	 Determine the basic running exhaust emission rate (BER). 

o 	 For each hour, correct the BER for temperature and fuel effects. 

o 	 Using the corrected BER, calculate the emissions for Freeway Ramps, Local 

Roadways and for the 14 speed bins for freeways and arterial/collectors using the 

appropriate emission offsets and speed correction factors described in this 

document. 

o 	 Using the speed distributions, weight the freeways, ramps, local and 

arterial/collector speed bin results to get hourly emissions. 

o 	 Using the hourly VMT distributions, weight together the hourly facility results to 

get daily emissions by facility. 

o 	 Using the facility VMT distribution, weight the daily facility emissions to get the 

area-wide running exhaust emission estimate. 

o 	 Combine the running exhaust emission estimate with the engine start emissions to 

get the composite exhaust emission rate. 

Appendix B shows an example speed correction calculation. 

The national average default factors used in MOBILE6 for VMT weighting the speedcorrected, facility-type emissions into a single area-wide running emissions rate is described in a 

report prepared for EPA by Systems Applications International.17 This report also contains the 

default distributions of average speeds on each facility over the day. All of these default values 

can be overridden by the user with local information using methods described in a separate 

guidance document.18 

The operating mode inputs used in MOBILE5 will not be needed for MOBILE6. Instead, 

MOBILE6 uses values for the number of engine starts, the distribution of soak times between 

engine starts, the mileage accumulation rates and the distribution of these factors over the day.19 

These values are used to determine the weighting of the running exhaust emissions with the 

effects of engine starts to calculate a composite exhaust emission factor. Although MOBILE6 

contains default values, these default values will normally be overridden by user supplied local 

information. 

Similarly, once the composite running and engine start emissions are calculated, the 

composite exhaust HC emissions can be combined with the calculated non-exhaust HC 

emissions. The reader should refer to the reports regarding the non-exhaust emission estimates 

and their associated activity for more details on how these values are calculated.20 

8.1	 Light Duty Diesel Vehicles 

The speed correction factors (SCFs) for LDDV and LDDT in MOBILE5 were derived 

from the SCFs calculated for HDDV. However, in MOBILE5, an adjustment was added for 

LDDV and LDDT to account for user supplied changes to the operating modes, which are cold 

Final M6.SPD.002 36	 June 2001 
start versus hot start VMT fractions applied to FTP bag emission rates, to account for the 

different average speeds between the FTP bags. These fractions did not affect HDDV, since the 

emissions from HDDV are not calculated from individual FTP bag emission results. 

In MOBILE6, there will not be user inputs for operating modes. The emission estimates 

for LDDV and LDDT in MOBILE6 have been split into the portion that occurs as a result of 

engine starts separately from the hot running emissions. The intention of the operating mode 

adjustment to the SCFs for LDDV and LDDT in MOBILE5 was to account for user supplied 

changes in the mix of FTP bag results in the basic exhaust emission rates. However, the basic 

exhaust emission rate for LDDV and LDDT in MOBILE6 is not affected by user inputs and is 

based solely on the LA4 driving cycle, which is the basis for the full FTP. As a result, the 

operating mode adjustment to the SCFs for LDDV and LDDT in MOBILE6 will be set to a 

constant based on the standard FTP operating mode mix. The adjustment to account for changes 

in speed that were caused by the operating mode will no longer be necessary in MOBILE6. 

The MOBILE5 speed correction factor coefficients for LDDV and LDDT from 

MOBILE521 are shown in Table 18. These factors will be used in MOBILE6 as well, but with 

the SADJ value fixed at 19.6 mph, which is the speed of the basic emission rate cycle, the LA4. 

8.2 Heavy Duty Vehicles 

The speed correction factors for heavy duty vehicles are not changed from those used in 

MOBILE5.22 The coefficients used in MOBILE6 are shown in Table 19 and Table 20. 

8.3 Motorcycles 

The speed correction factors for motorcycles are not changed from those used in 

MOBILE5.23 However, the SADJ factor discussed in the light duty diesel vehicle section were 

also applied to motorcycle speed correction factors in MOBILE5. In MOBILE6, the SADJ factor 

will be set to 19.6 mph. The coefficients used in MOBILE6 are shown in Table 21. 

The speed correction factors for motorcycles were developed in earlier versions of the 

model only for speeds up to 55 mph. In MOBILE5, for average speeds above 55 mph for THC 

and CO and 48 mph for NOx, the speed correction factor used for motorcycles was derived from 

the speed correction factor used for light duty gasoline vehicles for 65 mph. The speed 

correction factor (SCF) calculated for motorcycles is adjusted using the ratio of the difference 

between the light duty vehicle SCF at 65 mph and the motorcycle SCF at the target speed divided 

by the difference between 65 mph and the target speed. 

RATIO = ( LDGVSCF(65) - MCSCF(s) ) / (65 - SPD ) 

MCSCF(s) = MCSCF(s) * (1.0 + ( RATIO*(s - SPD) ) ) 

Where : s = average speed (mph) target speed 

Final M6.SPD.002 37 June 2001 
LDGVSCF(65) = light duty gasoline vehicle SCF at 65 mph 

MCSCF(s) = motorcycle SCF at the target speed (s) 

SPD = average speed where adjustment begins in mph 

- 55 mph for THC and CO emissions 

- 48 mph for NOx emissions 

This adjustment was retained for the calculation of motorcycle speed correction factors in 

MOBILE6. 

8.4	 High Speeds 

The driving cycles developed for MOBILE6 were derived from data collected before 

national speed limits were increased from 55 mph to 70 mph. The average speed of driving for 

uncongested freeways in the data sample was 59.7 mph (73.1 mph maximum). Another driving 

cycle, developed using a subset of vehicles driving over 55 mph, has an average speed of 63.2 

mph. It is clear that using the existing driving behavior information collected before the increase 

in the national speed limit cannot provide a credible estimate of the driving behavior at average 

speeds above about 65 mph. Existing research24 has shown that even minor variations in driving 

at high speeds can have a significant effect on driving emissions at those speeds. For this reason, 

until new information about driving behavior at high speeds and their effect on emissions is 

available, MOBILE6 will not directly predict emission impacts of average speeds over 65 mph. 

9.0	 COMPARISON TO MOBILE5 

Figures 6a, 6b, and 6c show the MOBILE6 speed correction factors (SCFs) for freeways 

compared to selected speed correction factors used in MOBILE5. This comparison cannot be 

made clearly, since the two versions of the model use very different approaches. 

�	 The MOBILE6 SCFs depend on emission level and the MOBILE5 SCFs do not. 

�	 The MOBILE5 SCFs are applied to a composite exhaust emission rate, including 

engine start emissions. The MOBILE6 SCFs will only be applied to the hot 

running exhaust emissions, before the effects of engine start are added. 

�	 The MOBILE6 SCFs are intended to estimate the effects on freeways excluding 

ramp activity, but the MOBILE5 SCFs are a composite of all roadway types. 

�	 The MOBILE6 SCFs include the effect of additional aggressive driving effects on 

emissions missing from the MOBILE5 SCFs. 

The overall shape of the MOBILE5 and MOBILE6 SCFs is similar. The MOBILE6 

SCFs are flatter at speeds greater than 55 mph than in MOBILE5, especially for CO and NOx. 

This may be due largely to the fact that the old speed cycles above 48 mph all started from idle 

(zero mph) and accelerated to a speed higher than the average speed of the cycle. This extra 

acceleration, which is not generally found on cruising vehicles on limited access freeways, adds 

to the power demand, therefore likely increasing emissions in the old high speed cycles relative 

Final M6.SPD.002 38	 June 2001 
to lower speed cycles. The acceleration to reach freeway speeds is now contained in the separate 

ramp cycle. This additional ramp cycle will allow this effect to be weighted appropriately with 

freeway driving. The effect from starting and ending at idle is less pronounced in the lower 

speed cycles since they inherently have a higher percentage of driving at idle. 

In Figure 6a (THC), the MOBILE6 SCF for the lowest emission level (based Tier 1 

vehicles) has a positive slope beyond about 30 mph, indicating increasing THC emissions with 

increasing average speed. However, as shown in Figure 4a, Tier 1 vehicles are much cleaner at 

all speeds than the normal emitting Tier 0 vehicles. The shape of the THC MOBILE6 SCFs for 

the higher emission levels (based on Tier 0 vehicles, Normal and High) is very close to the shape 

of MOBILE5 SCFs.

 For higher average speeds (above 19.6 mph) the MOBILE6 SCFs for CO emissions 

(Figure 6b) have a strongly positive slope at lower emission levels (based on Tier 0 Normals and 

Tier 1 vehicles). This is very different from the SCFs used in MOBILE5. The MOBILE6 SCFs 

for THC/NMHC emissions for Tier 0 Normal vehicles have a negative slope. However CO 

emissions are more sensitive to aggressive driving than THC/NMHC emissions, which may 

explain the difference in the trends. 

The MOBILE6 SCFs for NOx emissions (Figure 6c) for the higher emission levels (based 

on Tier 0 vehicles) have a slight upward trend at higher speeds, similar to the MOBILE5 trends. 

The lowest emission level SCFs (based on Tier 1 vehicles) has a steep slope, similar to the oldest 

MOBILE5 SCF. All of the MOBILE6 SCFs tend to rise as average speeds decrease, which is 

expected with more accelerations and decelerations (stop and go driving) present in the driving 

patterns. However, the MOBILE6 SCFs rise much more steeply and to higher levels than the 

MOBILE5 SCFs. 

Similar graphs comparing MOBILE6 speed correction factors for arterial/collector 

roadways and freeways with MOBILE5 speed correction estimates are shown in Figures 7a 

through 7i. Speed correction factors for arterial/collector roadways and freeways are the same 

below 7.1 mph and above about 30 mph. In general, speed correction factors for arterial/collector 

roadways are higher between those speeds. 

Since the Freeway Ramp and Local Roadway emissions are estimated directly from the 

basic exhaust emission rate (based on the hot running LA4 emissions), they cannot be compared 

to the speed correction factor used in MOBILE5. 

Final M6.SPD.002 39 June 2001 
 

References 

1

 See the EPA web site http://www.epa.gov/otaq/sftp.htm for more information. 

2

 Federal Test Procedure, or FTP means the test procedure as described in the Combined Federal 

Register § 86.130-00(a) through (d) and (f) which is designed to measure urban driving tail pipe 

exhaust emissions and evaporative emissions over the Urban Dynamometer Driving Schedule as 

described in Appendix I to this part. (See also http://www.epa.gov/otaq/labmthod.htm.) 

3

 See the EPA web site http://www.epa.gov/otaq/sftp.htm for more information. 

4

 Carlson, T.R., et al., “Development of Speed Correction Cycles,” MOBILE6 Stakeholder 

Review Document (M6.SPD.001). Prepared for EPA by Sierra Research, Inc., 1997. 

(http://www.epa.gov/otaq/m6.htm) 

5

 See the California Air Resources Board web site, http://www.arb.ca.gov/msei/msei.htm. 

6

 Gammariello, R.T. and Long, J.R., “Development of Unified Correction Cycles,” California Air 

Resources Board, Sixth CRC On-Road Vehicle Emissions Workshop, March 1996. This report 

is available at the CARB web site (http://www.arb.ca.gov/msei/pubs/ucc_crc5.pdf). 

7 ibid 

8 ibid 

9 ibid 

10 See the EPA web site, http://www.epa.gov/otaq/regs/ld-hwy/tier-1/ for more information. 

11 Brzezinski, D.J., et al., “Coefficients for the Determination of Engine Start and Running 

Emissions From FTP Bag Emissions,” MOBILE6 Stakeholder Review Document (M6.STE.002), 

1997. (http://www.epa.gov/otaq/m6.htm) 

12 “Federal Test Procedure Review Project: Preliminary Technical Report,” EPA Office of 

Mobile Sources Certification Division, (EPA420-R-93-007), May 1993. This report is available 

at the EPA web site (http://www.epa.gov/otaq/sftp.htm). 

13 ibid 

14 “Final Regulations for Revisions to the Federal Test Procedure for Emissions From Motor 

Vehicles,” Federal Register, 40 CFR Part 86 Volume 61, Number 205, Oct 22, 1996, Page 54869 

(http://www.epa.gov/otaq/ld-hwy.htm). 

15 “Regulatory Impact Analysis (Final Rule) : Federal Test Procedure Revisions,” 

EPA Office of Mobile Sources, August 15, 1996 (http://www.epa.gov/otaq/ld-hwy.htm). 

16 M6.SPD.003, op cit 

Final M6.SPD.002 40 June 2001 
 

 

17 “Development of Methodology for Estimating VMT Weighting by Facility Type,” MOBILE6 

Stakeholder Review Document (M6.SPD.003) EPA420-P-99-006. Prepared for EPA by Systems 

Applications International, Inc., 1998. (http://www.epa.gov/otaq/m6.htm) 

18 “Guidance for the Development of Facility Type VMT and Speed Distributions,” MOBILE6 

Stakeholder Review Document (M6.SPD.004) EPA420-P-99-004. Prepared for EPA by Systems 

Applications International, Inc., 1998. (http://www.epa.gov/otaq/m6.htm) 

19 Glover, E.L., et al., “Soak Length Activity Factors for Start Emissions,” MOBILE6 

Stakeholder Review Document (M6.FLT.003). (http://www.epa.gov/otaq/m6.htm) 

20 See the EPA web site for MOBILE6 reports, http://www.epa.gov/otaq/m6.htm 

21 “AP-42 Volume II, Compilation of Air Pollution Emission Factors, Mobile Sources,” 

Appendix H, June 30, 1995. (http://www.epa.gov/otaq/models.htm) 

22 ibid 

23 ibid 

24 Barth, M., et al., “Estimating Emissions and Fuel Consumption for Different Levels of 

Freeway Congestion,” University of California, Riverside. 78th Annual Transportation Research 

Board Meeting, Washington, D.C., January 1999. This report is available from TRB 

(http://nationalacademies.org/trb/bookstore). 

Final M6.SPD.002 41 June 2001 
Tables 

Final M6.SPD.002 42 June 2001 
Table 1 

New Facility-Specific/Area-Wide Speed Correction Cycle 

Statistics 

Cycle* 

Average 

Speed 

(mph) 

Maximum 

Speed 

(mph) 

Maximum 

Accel Rate 

(mph/s) 

Length 

(seconds) 

Length 

(miles) 

Freeway, High Speed 63.2 74.7 2.7 610 10.72 

Freeway, LOS A-C 59.7 73.1 3.4 516 8.55 

Freeway, LOS D 52.9 70.6 2.3 406 5.96 

Freeway, LOS E 30.5 63.0 5.3 456 3.86 

Freeway, LOS F 18.6 49.9 6.9 442 2.29 

Freeway, LOS “G” 13.1 35.7 3.8 390 1.42 

Freeway Ramps 34.6 60.2 5.7 266 2.56 

Arterial/Collectors 

LOS A-B 

24.8 58.9 5.0 737 5.07 

Arterial/Collectors 

LOS C-D 

19.2 49.5 5.7 629 3.36 

Arterial/Collectors 

LOS E-F 

11.6 39.9 5.8 504 1.62 

Local Roadways 12.9 38.3 3.7 525 1.87 

Non-Freeway AreaWide Urban Travel 19.4 52.3 6.4 1,348 7.25 

* LOS (level of service) refers to roadway congestion categories. See Section 4.6. 

Final M6.SPD.002 43 June 2001 
Table 2 

Comparison of Key Statistics 

For Facility-Specific Cycle Schedules 

Versus Total Vehicle Observations 

Driving Cycle 

Mean 

Speed 

(mph) 

Maximum 

Speed 

(mph) 

Maximum 

Accel Rate 

(mph/sec) 

Total 

SAFD 

Difference 

* (%) 

High-Power 

Difference** 

(%) Cyc. Obs. Cyc. Obs. Cyc. Obs. 

Freeway High-Speed 63.2 62.7 74.7 80.9 2.7 5.8 9.41 0.16 

Freeway LOS A-C 59.7 59.2 73.1 83.2 3.4 6.8 12.12 0.39 

Freeway LOS D 52.9 52.0 70.6 75.8 2.3 6.1 15.10 0.35 

Freeway LOS E 30.5 32.1 63.0 71.3 5.3 8.5 25.17 0.18 

Freeway LOS F 18.6 19.9 49.9 69.5 6.9 9.6 23.83 0.06 

Freeway LOS G 13.1 14.4 35.7 49.1 3.8 5.7 18.80 0.10 

Freeway Ramp 34.6 35.4 60.2 79.1 5.7 9.3 42.74 0.99 

Arterial LOS A-B 24.8 25.2 58.9 74.9 5.0 14.9 17.04 0.40 

Arterial LOS C-D 19.2 18.9 49.5 71.3 5.7 10.4 16.86 0.21 

Arterial LOS E-F 11.6 12.0 39.9 56.8 5.8 10.2 17.86 0.24 

Local Roadways 12.8 14.6 38.3 62.7 3.7 12.5 21.80 0.11 

Unified Cycle 24.6 26.3 67.2 80.3 6.9 10.4 30.27 0.19 

* The SAFD is the speed/acceleration frequency distribution based on time at each speed. Total SAFD Difference 

is the sum of the differences between the final cycle distribution and the target population distribution from which 

the cycle micro trips are chosen. (See M6.SPD.001) 

** Specific power was calculated from the following equation: 

Pt = St

2

 - St-1

2 , if St

 > St-1 0 , if St �St-1 

where St and St-1 are the vehicle speeds at times t and t-1, respectively. High power is the seconds in which the 

specific power is greater than or equal to 200 mph2

/sec. The High-Power Difference is the difference between the 

fraction of high power in the final cycle and the target population from which the cycle micro trips are chosen. 

Final M6.SPD.002 44 June 2001 
Table 3 

Statistics for Additional Tested Cycles 

Cycle 

Average 

Speed 

(mph) 

Maximum 

Speed 

(mph) 

Maximum 

Accel Rate 

(mph/s) 

Length 

(seconds) 

Length 

(miles) 

LA4 

(Urban Dynamometer 

Driving Cycle) 

19.6 56.7 3.3 1368 7.45 

Running 505 

(First 505 seconds of the 

Urban Dynamometer 

Driving Cycle) 

25.6 56.7 3.3 505 3.59 

Unified Cycle (LA92) 24.6 67.2 6.9 1435 9.81 

ST01 

(Engine Start Cycle) 

20.2 41.0 5.1 248 1.39 

New York City Cycle 

(NYCC) 

7.1 27.7 6.0 600 1.18 

Table 4 

Distribution of the Vehicle Sample 

By Emission Standard and Technology 

Fuel Delivery 

TIER 0 Emission 

Standard 

TIER 1 Emission 

Standard 

Total 

Sample 

Carburetor 7 -­ 7 

Throttle Body FI 27 1 28 

Multi-Port FI 39 11 50 

Total Sample 73 12 85 

Final M6.SPD.002 45 June 2001 
Table 5 

Vehicle Sample Description 

Site 

Veh. 

No. 

Veh. 

Class VIN 

Mod. 

Yr. Make Mod. Std. Miles 

Eng. 

Size 

Fuel 

Inj. IM240 

E.LIB 5001 LDV 1G4AH51R7J6401871 88 BUICK CENT Tier 0 129,698 2.5 TBI PASS 

E.LIB 5002 LDV 1G3NL54UXKM283722 89 OLDSMOBILE CUTL Tier 0 61,956 2.5 TBI FAIL 

E.LIB 5003 LDV 2FACP74F3MX162914 91 FORD CROW Tier 0 53,003 5.0 PFI PASS 

E.LIB 5005 LDV 1G1JC14GOM7126454 91 CHEVROLET CAVA Tier 0 54,658 2.2 TBI PASS 

E.LIB 5006 LDV 1G1JC111XK7150483 89 CHEVROLET CAVA Tier 0 107,611 2.0 TBI PASS 

E.LIB 5007 LDV 1G3HY54C9JW312653 88 OLDSMOBILE DELT Tier 0 101,534 3.8 PFI PASS 

E.LIB 5008 LDV 1FACP57U5NG145893 92 FORD TAUR Tier 0 74,078 3.0 PFI PASS 

E.LIB 5009 LDV 1G2WP14T6KF307905 89 PONTIAC GRAN Tier 0 155,181 3.1 PFI FAIL 

E.LIB 5010 LDV 4T1SK12E9PU184046 93 TOYOTA CAMR Tier 0 29,392 2.2 TBI PASS 

E.LIB 5011 LDV 2C1MS2468P6704533 93 GEO METR Tier 0 105,445 1.0 TBI PASS 

E.LIB 5012 LDV 1G2NV54D9JC821314 88 PONTIAC GRAN Tier 0 89,764 2.3 TBI PASS 

E.LIB 5013 LDV 1G2NE5434PC795009 93 PONTIAC GRAN Tier 0 72,348 2.3 PFI PASS 

E.LIB 5014 LDV 1G6CD53B7M4272204 91 CADILLAC SEDA Tier 0 51,707 4.9 TBI FAIL 

E.LIB 5015 LDV 1G2NE5438PC758996 93 PONTIAC GRAN Tier 0 58,538 2.3 PFI PASS 

E.LIB 5016 LDV 1G4HR54C5KH488839 89 BUICK LESA Tier 0 65,212 3.8 TBI FAIL 

E.LIB 5017 LDV WVWEB5159MK012875 91 VW CABR Tier 0 67,496 1.8 TBI PASS 

E.LIB 5018 LDV 1B3ES27C9SD221573 95 DODGE NEON Tier 1 20,855 2.0 TBI PASS 

E.LIB 5019 LDV 1G1FP23TXLL111092 90 CHEVROLET CAMA Tier 0 71,258 3.1 PFI FAIL 

E.LIB 5020 LDV 1FACP5245NG196687 92 FORD TAUR Tier 0 84,148 3.8 TBI PASS 

E.LIB 5021 LDV 1B3ES67C2SD188892 95 DODGE NEON Tier 1 28,525 2.0 PFI PASS 

E.LIB 5022 LDV 1G1JC1112KJ207455 89 CHEVROLET CAVA Tier 0 110,929 2.0 TBI PASS 

E.LIB 5023 LDV 1FAPP36X6JK249611 88 FORD TEMP Tier 0 107,979 2.3 PFI PASS 

E.LIB 5024 LDV 2FAPP36X8MB116542 91 FORD TEMP Tier 0 97,522 2.3 PFI FAIL 

E.LIB 5025 LDT1 1N6SD16S6MC351945 91 NISSAN HARD Tier 0 103,346 2.4 PFI PASS 

E.LIB 5026 LDV 1MEBM50U3KG663746 89 MERCURY SABL Tier 0 107,075 3.0 PFI FAIL 

E.LIB 5027 LDV JE3CU14A1NU003588 92 EAGLE SUMM Tier 0 129,457 1.5 PFI FAIL 

E.LIB 5028 LDV 1YVGE22A8P5138202 93 MAZDA 626 Tier 0 103,171 12 PFI FAIL 

E.LIB 5029 LDT1 1P4FH4430KX568849 89 PLYMOUTH VOYA Tier 0 118,586 3.0 PFI PASS 

E.LIB 5030 LDV 1FABP29D9GA165884 86 FORD TAUR Tier 0 50,755 2.5 TBI FAIL 

E.LIB 5031 LDV JT2SV24E8J3189405 88 TOYOTA CAMR Tier 0 197,090 2.0 PFI FAIL 

E.LIB 5032 LDV 1MEBP923XFA603099 85 MERCURY COUG Tier 0 113,584 14 TBI FAIL 

E.LIB 5033 LDT1 1GCBS14E3H2170996 87 CHEVROLET S10 Tier 0 128,681 2.5 TBI PASS 

E.LIB 5034 LDT1 1GCBS14A3F2156946 85 CHEVROLET S10 Tier 0 89,435 1.9 NO PASS 

E.LIB 5035 LDV 1FABP37X6HK239681 87 FORD TEMP Tier 0 118,148 2.5 TBI FAIL 

E.LIB 5036 LDV JN1HM05S8HX081093 87 NISSAN STAN Tier 0 58,173 2.0 PFI PASS 

E.LIB 5037 LDV 1P3BP49CXDF305484 83 PLYMOUTH RELI Tier 0 94,399 2.2 NO FAIL 

E.LIB 5038 LDV 2G1WL52M2T9212643 96 CHEVROLET LUMI Tier 1 16,557 3.1 PFI PASS 

E.LIB 5039 LDV 1HGED3554JA017137 88 HONDA CIVI Tier 0 184,457 1.5 TBI FAIL 

E.LIB 5040 LDV 2HGED6359KH534893 89 HONDA CIVI Tier 0 161,598 12 TBI PASS 

E.LIB 5041 LDV JT2EL32G3H0076681 87 TOYOTA TERC Tier 0 136,654 1.5 NO PASS 

E.LIB 5042 LDT1 1GCDM15NXFB180388 85 CHEVROLET ASTR Tier 0 179,855 4.3 NO FAIL 

E.LIB 5043 LDV 2HGED6349KH537915 89 HONDA CIVI Tier 0 122,821 1.5 TBI PASS 

E.LIB 5044 LDT1 1GTBS14E5J2520442 88 CHEVROLET S15 Tier 0 115,693 2.5 TBI FAIL 

Final M6.SPD.002 46 June 2001 
Table 5 

Vehicle Sample Description 

E.LIB 5045 LDV 1G2WH54T6PF250844 93 PONTIAC GRAN Tier 0 85,789 3.4 PFI FAIL 

E.LIB 5046 LDT1 1FTCR1056FUD20466 85 FORD RANG Tier 0 56,488 2.8 NO FAIL 

E.LIB 5047 LDT1 1FTDE14N8MHB05052 91 FORD ECON Tier 0 79,573 5.8 PFI FAIL 

E.LIB 5048 LDT1 1FTCR10A2KUB93426 89 FORD RANG Tier 0 123,419 2.3 TBI PASS 

E.LIB 5049 LDV 2G1AW19X5G1258479 86 CHEVROLET CELE Tier 0 131,601 2.8 NO PASS 

E.LIB 5050 LDT1 1FDDE14F9FHA59240 85 FORD ECON Tier 0 86,203 5.8 NO PASS 

E.LIB 5051 LDV 1G1JF11W1K7156403 89 CHEVROLET CAVA Tier 0 123,581 3.1 PFI PASS 

E.LIB 5052 LDV 1G1JC14GXM7146551 91 CHEVROLET CAVA Tier 0 90,945 2.2 TBI PASS 

E.LIB 5053 LDT2 1FDEE14N0MHB15171 91 FORD E150 Tier 0 97,531 5.8 PFI FAIL 

E.LIB 5054 LDV 1FAPP1282MW314230 91 FORD ESCO Tier 0 105,861 1.8 PFI FAIL 

E.LIB 5055 LDT1 2P4GH25K6MR240965 91 PLYMOUTH VOYA Tier 0 72,032 2.5 TBI PASS 

E.LIB 5056 LDT1 1GNDM15Z4MB190115 91 CHEVROLET ASTR Tier 0 90,880 4.3 TBI PASS 

E.LIB 5057 LDV 1G1LT53T9PY237873 93 CHEVROLET CORS Tier 0 41,766 3.4 PFI PASS 

E.LIB 5058 LDT1 1GCCS19Z5P0178401 93 CHEVROLET S10 Tier 0 48,578 4.3 TBI PASS 

E.LIB 5059 LDV 4T1SK11E4PU252562 93 TOYOTA CAMR Tier 0 67,344 2.2 PFI PASS 

E.LIB 5060 LDV 1HGCB7658PA075439 93 HONDA ACCO Tier 0 61,163 2.2 PFI PASS 

E.LIB 5061 LDV JN1HJ01P0LT397615 90 NISSAN MAXI Tier 0 120,786 3.0 PFI PASS 

E.LIB 5062 LDV JE3CA11A7PU098450 93 EAGLE SUMM Tier 0 52,447 1.5 PFI PASS 

E.LIB 5063 LDV 1G2WJ52M7TF204255 96 PONTIAC GRAN Tier 1 20,451 3.1 PFI PASS 

AA 5213 LDV JT2AE94A5N0273089 92 TOYOTA CORO Tier 0 77,310 1.6 PFI NULL 

AA 5217 LDV 1HGCD5632TA260884 96 HONDA ACCO Tier 1 7,573 2.2 PFI NULL 

AA 5218 LDV 1G8ZF5498NZ175489 92 SATURN SL Tier 0 89,995 1.9 TBI NULL 

AA 5219 LDV 1G1LW13T4NY109988 92 CHEVROLET BERR Tier 0 94,316 3.1 PFI NULL 

AA 5220 LDT2 1FTEF14N3RLB27661 94 FORD F150 Tier 0 97,629 5.8 PFI NULL 

AA 5221 LDT2 1FTEF1549TLB25543 96 FORD F150 Tier 1 12,877 4.9 PFI NULL 

AA 5222 LDV JM1BG2263N0464490 92 MAZDA PROT Tier 0 10,727 1.8 PFI NULL 

AA 5223 LDV 2G1WL52M2T9212643 96 CHEVROLET LUMI Tier 1 17,233 3.1 PFI NULL 

AA 5224 LDV 1G1JC5447N7116728 92 CHEVROLET CAVA Tier 0 90,196 2.2 PFI NULL 

AA 5225 LDT1 1FTCR10A9TPB08548 96 FORD RANG Tier 1 10,064 2.3 PFI NULL 

AA 5227 LDT2 1GNEV16K9LF116974 90 CHEVROLET SURB Tier 0 97,658 5.7 TBI NULL 

AA 5228 LDV 2C3ED56F7RH211101 94 CHRYSLER LHS Tier 0 59,937 3.5 PFI NULL 

AA 5229 LDV 1HGEJ8142TL073569 96 HONDA CIVI Tier 1 9,433 1.6 PFI NULL 

AA 5230 LDT1 1GNDM19WXRB229457 94 CHEVROLET ASTR Tier 0 77,178 4.3 PFI NULL 

AA 5231 LDV 1G8ZK5570RZ145840 94 SATURN SL Tier 0 25,930 1.9 PFI NULL 

AA 5232 LDV KMHJF22M5RU669848 94 HYUNDAI ELAN Tier 0 57,960 1.8 PFI NULL 

AA 5233 LDT1 1GNDU06D3NT126706 92 CHEVROLET LUMI Tier 0 33,872 3.1 PFI NULL 

AA 5234 LDV 1FARP15J9RW262996 94 FORD ESCO Tier 1 51,168 1.9 PFI NULL 

AA 5235 LDT1 2P4FH5532LR534285 90 PLYMOUTH VOYA Tier 0 98,530 3.0 PFI NULL 

AA 5237 LDV 2G1WN54X7N9117726 92 CHEVROLET LUMI Tier 0 16,133 3.4 PFI NULL 

AA 5239 LDT1 1GMDU06LXRT234029 94 PONTIAC TRAN Tier 1 68,305 3.8 PFI NULL 

AA 5240 LDV 4T1BF12K3TU871236 96 TOYOTA CAMR Tier 1 18,992 3.0 PFI NULL 

AA 5241 LDV 1B3XC56R3LD749334 90 DODGE DYNA Tier 0 6,813 3.3 PFI NULL 

Final M6.SPD.002 47 June 2001 
Table 6 

Distribution of Vehicle Sample 

By Vehicle Class and Model Year 

Model Year 

Passenger 

Car 

Light-Duty Truck 

(0-6000 GVW) 

Light-Duty Truck 

(6000-8500 GVW) Total 

1983 1 -­ -­ 1 

1985 1 4 -­ 5 

1986 2 -­ -­ 2 

1987 3 1 -­ 4 

1988 6 1 -­ 7 

1989 9 2 -­ 11 

1990 3 1 1 5 

1991 7 4 1 12 

1992 9 1 -­ 10 

1993 10 1 -­ 11 

1994 4 2 1 7 

1995 2 -­ -­ 2 

1996 6 1 1 8 

TOTAL 63 18 4 85 

Final M6.SPD.002 48 June 2001 
Table 7a 

Facility-Specific/Area-Wide Speed Correction Cycles Test Results 

Total Hydrocarbons (THC) 

Cycle 

Normal Emitters High Emitters 

# of 

veh. 

Mean 

(g/mile) 

Std. 

Dev. 

# of 

veh. 

Mean 

(g/mile) 

Std. 

Dev. 

Freeway at 63.2 mph 61 0.15 0.19 24 1.80 1.66 

Freeway at 59.7 mph 61 0.16 0.17 24 1.77 1.69 

Freeway at 52.9 mph 61 0.14 0.17 24 1.70 1.38 

Freeway at 30.5 mph 61 0.21 0.26 24 2.52 2.12 

Freeway at 18.6 mph 61 0.25 0.30 24 3.67 3.75 

Freeway at 13.1 mph 61 0.27 0.33 24 4.13 4.06 

Freeway Ramps (34.6 mph) 61 0.34 0.46 24 3.04 2.21 

Arterial/Collectors 

at 24.8 mph 

61 0.22 0.26 24 3.03 3.07 

Arterial/Collectors 

at 19.2 mph 

61 0.26 0.32 24 3.97 4.79 

Arterial/Collectors 

at 11.6 mph 

61 0.45 0.84 24 5.15 5.63 

Local Roadways (12.9 mph) 61 0.28 0.34 24 4.48 5.07 

Non-Freeway Area-Wide 

Urban Travel (19.4 mph) 

60* 0.26 0.31 24 3.57 3.06 

FTP (19.6 mph) 61 0.38 0.27 24 3.49 2.77 

Running 505 (25.6 mph) 61 0.17 0.23 24 2.57 2.51 

Unified Cycle (24.6 mph) 60* 0.24 0.27 24 3.16 3.33 

ST01(20.2 mph) 61 2.32 2.29 23* 6.88 5.36 

NYCC (7.1 mph) 61 0.62 1.09 24 7.31 7.82 

* Test not done 

Final M6.SPD.002 49 June 2001 
Table 7b 

Facility-Specific/Area-Wide Speed Correction Cycles Test Results 

Carbon Monoxide (CO) 

Cycle 

Normal Emitters High Emitters 

# of 

veh. 

Mean 

(g/mile) 

Std. 

Dev. 

# of 

veh. 

Mean 

(g/mile) 

Std. 

Dev. 

Freeway at 63.2 mph 70 6.96 7.71 15 66.76 52.09 

Freeway at 59.7 mph 70 6.96 6.12 15 65.63 54.63 

Freeway at 52.9 mph 70 5.53 5.33 15 54.45 41.82 

Freeway at 30.5 mph 70 4.48 4.01 15 66.38 43.18 

Freeway at 18.6 mph 70 5.19 4.90 15 74.39 63.48 

Freeway at 13.1 mph 70 4.79 4.45 15 82.09 77.01 

Freeway Ramps (34.6 mph) 70 10.06 10.79 15 84.02 57.32 

Arterial/Collectors 

at 24.8 mph 

70 4.28 3.87 15 75.24 59.12 

Arterial/Collectors 

at 19.2 mph 

70 5.22 5.01 15 80.79 62.65 

Arterial/Collectors 

at 11.6 mph 

70 5.94 5.65 15 116.57 94.9 

Local Roadways (12.9 mph) 70 4.23 4.14 15 92.41 87.81 

Non-Freeway Area-Wide 

Urban Travel (19.4 mph) 

69* 4.80 4.62 15 86.63 62.32 

FTP (19.6 mph) 70 5.05 3.70 15 79.92 56.89 

Running 505 (25.6 mph) 70 3.04 2.75 15 74.04 57.5 

Unified Cycle (24.6 mph) 69* 5.93 5.34 15 77.94 58.19 

ST01 (20.2 mph) 70 24.55 16.54 14* 111.2 70.30 

NYCC (7.1 mph) 70 7.88 8.12 15 158.04 136.34 

* Test not done 

Final M6.SPD.002 50 June 2001 
Table 7c 

Facility-Specific/Area-Wide Speed Correction Cycles Test Results 

Nitrogen Oxides (NOx) 

Cycle 

Normal Emitters High Emitters 

# of 

veh. 

Mean 

(g/mile) 

Std. 

Dev. 

# of 

veh. 

Mean 

(g/mile) 

Std. 

Dev. 

Freeway at 63.2 mph 72 0.77 0.71 13 3.35 1.07 

Freeway at 59.7 mph 72 0.74 0.65 13 3.27 1.02 

Freeway at 52.9 mph 72 0.70 0.60 13 3.20 0.97 

Freeway at 30.5 mph 72 0.63 0.54 13 3.15 1.00 

Freeway at 18.6 mph 72 0.72 0.59 13 3.73 1.34 

Freeway at 13.1 mph 72 0.51 0.39 13 2.81 0.99 

Freeway Ramps (34.6 mph) 72 0.98 0.81 13 4.00 1.43 

Arterial/Collectors 

at 24.8 mph 

72 0.68 0.55 13 3.47 1.07 

Arterial/Collectors 

at 19.2 mph 

72 0.79 0.66 13 3.77 1.46 

Arterial/Collectors 

at 11.6 mph 

72 0.96 0.78 13 4.44 1.84 

Local Roadways (12.9 mph) 72 0.73 0.63 13 3.74 1.46 

Non-Freeway Area-Wide 

Urban Travel (19.4 mph) 

71* 0.71 0.57 13 3.56 1.18 

FTP (19.6 mph) 72 0.70 0.53 13 3.25 1.04 

Running 505 (25.6 mph) 72 0.59 0.50 13 3.67 1.13 

Unified Cycle (24.6 mph) 71* 0.84 0.66 13 3.83 1.23 

ST01 (20.2 mph) 72 1.85 1.11 12* 3.78 1.34 

NYCC (7.1 mph) 72 0.95 0.69 13 4.07 1.45 

* Test not done 

Final M6.SPD.002 51 June 2001 
Table 8 

Analysis of Variance Results (ANOVA P-Values) 

Factor* THC CO NOx NMHC 

All Roadways Speed 0.0000 0.0000 0.0000 0.0001 

Emitter Class 0.0000 0.0000 0.0000 0.0000 

Speed*Emitter Class 0.1411 0.0152 0.9894 0.1271 

========================= Normal Emitters ========================= 

Factor* THC CO NOx NMHC 

Arterial/Collector 

and Freeway 

Roadway Type** 0.0046 0.0006 0.0000 0.0050 

Speed*Roadway Type** 0.0354 0.0020 0.0000 0.0440 

Vehicle Class 0.0016 0.0031 0.0012 0.0404 

Speed*Vehicle Class 0.1754 0.8680 0.5723 0.1802 

Standard*** 0.0000 0.0000 0.0000 0.0000 

Speed*Standard*** 0.0002 0.0576 0.6491 0.0001 

Local Roadway Vehicle Class 0.0830 0.4038 0.0124 0.5008 

Standard*** 0.0000 0.0000 0.0028 0.0000 

Freeway Ramp Vehicle Class 0.2922 0.0443 0.0018 0.7707 

Standard*** 0.0003 0.0002 0.0000 0.0007 

========================= High Emitters ========================= 

Factor* THC CO NOx NMHC 

Arterial/Collector 

and Freeway 

Roadway Type** 0.1236 0.3307 0.0000 0.1307 

Speed*Roadway Type** 0.1176 0.6233 0.0000 0.1203 

Vehicle Class 0.5942 0.8984 0.3961 0.5693 

Speed*Vehicle Class 0.0641 0.0241 0.9560 0.0699 

Local Roadway Vehicle Class 0.8787 0.5511 0.6093 0.8821 

Freeway Ramp Vehicle Class 0.3701 0.1471 0.6942 0.4075

 * All emissions in Log (gram/hour) scale.


 ** Freeways versus Arterial/Collectors limited to speeds < 30 mph, including a
 

vehicle term.


 ***	 There are no Tier 1 High emitters in sample. Some low emitting Tier 0 vehicles 

are considered both as Tier 0 and as Tier 1 vehicles (see text). 

Final M6.SPD.002 52	 June 2001 
Table 8 

Analyses of Variance Results (ANOVA p values) 

Factor* THC NMHC CO NOx 

Emitter Level .0000 .0000 .0000 .0000 

Normal Emitters Only 

Roadway type** .0006 .0003 .0206 .0000 

Vehicle Class .0001 .0004 .0001 .0001 

Standard*** .0001 .0001 .0001 .0001 

Local/Vehicle Class .0476 .1490 .0325 .2753 

Local/Standard .0001 .0001 .0001 .0001 

Ramp/Vehicle Class .0396 .0983 .0107 .0871 

Ramp/Standard .0001 .0001 .0001 .0001 

High Emitters Only 

Roadway type** .3094 .3281 .0318 .0000 

Vehicle Class .067 .067 .0004 .144 

Standard*** NA NA NA NA

 * All emissions in Log (gram/hour) scale.

 **	 Freeways versus Arterial/Collectors limited to speeds < 30 mph, including a
 

vehicle term.


 ***	 There were no Tier 1 High emitters in sample. Some low emitting Tier 0 vehicles 

were considered both as Tier 0 and as Tier 1 vehicles (see text). 

Final M6.SPD.002 53	 June 2001 
Table 9 

Description of Sample Vehicles Used for Tier 1 Analysis 

Veh 

No. 

Test 

Site 

Tier 

Std. Mileage 

FTP 

NMHC 

FTP 

NOx 

Veh 

Class 

Model 

Yr. 

Eng. 

Size 

Fuel 

Inj. 

IM240 

Status VIN 

5007 E.LIB 0 101536 0.13 0.23 LDV 88 3.80 PFI PASS 1G3HY5C9JW312653 

5010 E.LIB 0 29392 0.12 0.21 LDV 93 2.20 TBI PASS 4T1SK12E9PU18406 

5013 E.LIB 0 72348 0.08 0.18 LDV 93 2.30 PFI PASS 1G2NE5438PC758996 

5015 E.LIB 0 58538 0.07 0.41 LDV 93 2.30 PFI PASS 1G2NE5438PC758996 

5017 E.LIB 0 67496 0.15 0.13 LDV 91 1.80 TBI PASS WVWEB5159MK012875 

5018 E.LIB 1 20855 0.12 0.10 LDV 95 2.00 TBI PASS 1B3ES27C9SD221573 

5021 E.LIB 1 28525 0.12 0.10 LDV 95 2.00 PFI PASS 1B3ES67C2SD188892 

5038 E.LIB 1 16557 0.12 0.34 LDV 96 3.10 PFI PASS 2GIWL52M2T9212643 

5059 E.LIB 0 6734 0.13 0.28 LDV 93 2.20 PFI PASS 4T1SK11E4PU252562 

5060 E.LIB 0 61163 0.11 0.27 LDV 93 2.20 PFI PASS 1HGCB7658PA075439 

5063 E.LIB 1 20451 0.16 0.26 LDV 96 3.10 PFI PASS 1G2WJ52M7TF204255 

5217 AA 1 7573 0.09 0.20 LDV 96 2.20 PFI NULL 1HGCD5632TA260884 

5218 AA 0 89995 0.19 0.39 LDV 92 1.90 PFI NULL 1G8ZF5498NZI75489 

5221 AA 1 12877 0.10 0.53 LDT2 96 4.90 PFI NULL 1TEF1549TLB25543 

5223 AA 1 17233 0.21 0.49 LDV 96 3.10 PFI NULL 2G1WL52M2T9212643 

5225 AA 1 10064 0.12 0.40 LDT1 96 2.20 PFI NULL 1FTCR10A9TPB08548 

5229 AA 1 9433 0.17 0.10 LDV 96 1.60 PFI NULL 1HGEJ8142TL073569 

5234 AA 1 51168 0.15 0.26 LDV 94 1.90 PFI NULL 1FARP15J9RW262996 

5239 AA 1 68305 0.19 0.71 LDT1 94 3.80 PFI NULL 1GMDU06LXRT234029 

5240 AA 1 18992 0.21 0.31 LDV 96 3.00 PFI NULL 4T1BF12K3TU871236 

Final M6.SPD.002 54 June 2001 
Table 10 

Tests of Convergence in Arterial and Freeway Estimates at 30 mph 

Tier 0 Normal Emitter Sample 

Parameter Estimate 

T for H0: 

Parameter = 0 

p value 

Pr > | T | 

Standard Error 

of the Estimate 

THC 0.18089092 1.84 0.0670 0.09840365 

NMHC 0.15532642 1.83 0.0688 0.08503405 

CO 1.63652794 2.96 0.0033 0.55229111 

NOx 0.05946957 1.24 0.2160 0.04797825 

Tier 0 High Emitter Sample 

Parameter Estimate 

T for H0: 

Parameter = 0 

p value 

Pr > | T | 

Standard Error 

of the Estimate 

THC 0.95357931 1.52 0.1304 0.62676490 

NMHC 0.84766279 1.58 0.1161 0.53612496 

CO 24.7784634 1.48 0.1430 16.7645083 

NOx -0.00945343 -0.04 0.9705 0.25464544 

Tier 1 Normal Emitter Sample 

Parameter Estimate 

T for H0: 

Parameter = 0 

p value 

Pr > | T | 

Standard Error 

of the Estimate 

THC 0.01509669 1.15 0.2534 0.01310665 

NMHC 0.00615421 0.71 0.4813 0.00869272 

CO 0.25453921 0.83 0.4114 0.30796933 

NOx 0.04101364 1.20 0.2350 0.03423678 

Final M6.SPD.002 55 June 2001 
Table 11a 

Average Emissions by Emission Standard and Emission Level 

Total Hydrocarbons (THC) 

Cycle 

Tier 1* Tier 0 Normal Tier 0 High 

# of 

veh. 

Mean 

(g/mi) 

Std. 

Dev. 

# of 

veh. 

Mean 

(g/mi) 

Std. 

Dev. 

# of 

veh. 

Mean 

(g/mi) 

Std. 

Dev. 

Freeway at 63.2 mph 20 0.050 0.032 49 0.183 0.200 24 1.798 1.656 

Freeway at 59.7 mph 20 0.066 0.038 49 0.187 0.180 24 1.771 1.688 

Freeway at 52.9 mph 20 0.035 0.019 49 0.171 0.178 24 1.702 1.384 

Freeway at 30.5 mph 20 0.038 0.031 49 0.253 0.272 24 2.523 2.124 

Freeway at 18.6 mph 20 0.044 0.036 49 0.305 0.318 24 3.672 3.745 

Freeway at 13.1 mph 20 0.046 0.040 49 0.330 0.341 24 4.127 4.063 

Freeway Ramps 

(34.6 mph) 

20 0.083 0.080 49 0.408 0.488 24 3.036 2.205 

Arterial/Collectors 

at 24.8 mph 

20 0.044 0.035 49 0.262 0.278 24 3.028 3.072 

Arterial/Collectors 

at 19.2 mph 

20 0.060 0.054 49 0.318 0.341 24 3.970 4.794 

Arterial/Collectors 

at 11.6 mph 

20 0.063 0.045 49 0.551 0.917 24 5.155 5.630 

NYCC (7.1 mph) 20 0.122 0.111 49 0.744 1.183 24 7.306 7.824 

Local Roadways 

(12.9 mph) 

20 0.053 0.056 49 0.336 0.360 24 4.478 5.075 

Non-Freeway Areawide Urban Travel 

(19.4 mph) 

19 0.057 0.047 49 0.311 0.325 24 3.571 3.060 

Hot Running LA4 

(19.6 mph) 

20 0.036 0.019 49 0.199 0.201 24 3.175 2.945 

Unified Cycle 

(24.6 mph) 

19 0.060 0.049 48 0.282 0.287 24 3.158 3.328 

Final M6.SPD.002 56 June 2001 
Table 11b 

Average Emissions by Emission Standard and Emission Level 

Carbon Monoxide (CO) 

Cycle 

Tier 1 Tier 0 Normal Tier 0 High 

# of 

veh. 

Mean 

(g/mi) 

Std. 

Dev. 

# of 

veh. 

Mean 

(g/mi) 

Std. 

Dev. 

# of 

veh. 

Mean 

(g/mi) 

Std. 

Dev. 

Freeway at 63.2 mph 20 1.862 1.765 58 8.157 7.945 15 66.763 52.094 

Freeway at 59.7 mph 20 3.045 1.446 58 7.755 6.410 15 65.632 54.628 

Freeway at 52.9 mph 20 1.381 1.179 58 6.449 5.403 15 54.448 41.822 

Freeway at 30.5 mph 20 1.305 1.636 58 5.218 3.998 15 66.377 43.185 

Freeway at 18.6 mph 20 1.513 1.570 58 5.978 4.997 15 74.390 63.484 

Freeway at 13.1 mph 20 1.264 1.564 58 5.596 4.464 15 82.087 77.005 

Freeway Ramps 

(34.6 mph) 

20 2.803 2.651 58 11.665 11.170 15 84.016 57.322 

Arterial/Collectors 

at 24.8 mph 

20 1.271 1.215 58 4.934 3.921 15 75.235 59.118 

Arterial/Collectors 

at 19.2 mph 

20 1.562 1.638 58 6.052 5.103 15 80.793 62.646 

Arterial/Collectors 

at 11.6 mph 

20 1.538 1.699 58 6.902 5.727 15 116.56 

9 

94.897 

NYCC (7.1 mph) 20 2.652 3.068 58 9.061 8.384 15 158.04 

1 

136.341 

Local Roadways 

(12.9 mph) 

20 1.249 1.727 58 4.924 4.212 15 92.412 87.806 

Non-Freeway Areawide Urban Travel 

(19.4 mph) 

19 1.357 1.580 58 5.497 4.696 15 86.628 62.322 

Hot Running LA4 

(19.6 mph) 

20 0.892 0.846 58 3.569 2.997 15 82.194 64.114 

Unified Cycle 

(24.6 mph) 

19 1.892 2.104 57 6.855 5.394 15 77.941 58.194 

Final M6.SPD.002 57 June 2001 
Table 11c 

Average Emissions by Emission Standard and Emission Level 

Oxides of Nitrogen (NOx) 

Cycle 

Tier 1 Tier 0 Normal Tier 0 High 

# of 

veh. 

Mean 

(g/mi) 

Std. 

Dev. 

# of 

veh. 

Mean 

(g/mi) 

Std. 

Dev. 

# of 

veh. 

Mean 

(g/mi) 

Std. 

Dev. 

Freeway at 63.2 mph 20 0.331 0.353 60 0.840 0.736 13 3.354 1.069 

Freeway at 59.7 mph 20 0.340 0.287 60 0.806 0.674 13 3.270 1.021 

Freeway at 52.9 mph 20 0.241 0.164 60 0.789 0.619 13 3.200 0.970 

Freeway at 30.5 mph 20 0.234 0.158 60 0.709 0.558 13 3.155 0.996 

Freeway at 18.6 mph 20 0.231 0.168 60 0.817 0.591 13 3.727 1.339 

Freeway at 13.1 mph 20 0.187 0.143 60 0.585 0.386 13 2.805 0.995 

Freeway Ramps 

(34.6 mph) 

20 0.324 0.222 60 1.106 0.823 13 3.998 1.435 

Arterial/Collectors 

at 24.8 mph 

20 0.233 0.163 60 0.769 0.559 13 3.473 1.068 

Arterial/Collectors 

at 19.2 mph 

20 0.376 0.476 60 0.905 0.660 13 3.774 1.461 

Arterial/Collectors 

at 11.6 mph 

20 0.416 0.605 60 1.093 0.777 13 4.435 1.841 

NYCC (7.1 mph) 20 0.353 0.292 60 1.093 0.672 13 4.072 1.455 

Local Roadways 

(12.9 mph) 

20 0.311 0.426 60 0.830 0.637 13 3.735 1.463 

Non-Freeway Areawide Urban Travel 

(19.4 mph) 

19 0.253 0.159 60 0.796 0.583 13 3.561 1.179 

Hot Running LA4 

(19.6 mph) 

20 0.191 0.123 60 0.591 0.457 13 3.245 1.045 

Unified Cycle 

(24.6 mph) 

19 0.357 0.255 59 0.943 0.678 13 3.830 1.230 

Final M6.SPD.002 58 June 2001 
Table 11d 

Average Emissions by Emission Standard and Emission Level 

Non-Methane Hydrocarbons (NMHC) 

Cycle 

Tier 1 Tier 0 Normal Tier 0 High 

# of 

veh. 

Mean 

(g/mi) 

Std. 

Dev. 

# of 

veh. 

Mean 

(g/mi) 

Std. 

Dev. 

# of 

veh. 

Mean 

(g/mi) 

Std. 

Dev. 

Freeway at 63.2 mph 19 0.038 0.023 49 0.148 0.177 24 1.633 1.524 

Freeway at 59.7 mph 20 0.052 0.035 49 0.154 0.162 24 1.601 1.518 

Freeway at 52.9 mph 19 0.026 0.015 48 0.140 0.159 24 1.537 1.231 

Freeway at 30.5 mph 19 0.025 0.020 49 0.207 0.246 24 2.290 1.847 

Freeway at 18.6 mph 16 0.031 0.031 48 0.250 0.288 24 3.347 3.295 

Freeway at 13.1 mph 17 0.027 0.022 49 0.259 0.310 24 3.740 3.463 

Freeway Ramps 

(34.6 mph) 

18 0.068 0.069 47 0.357 0.444 24 2.767 1.957 

Arterial/Collectors 

at 24.8 mph 

20 0.029 0.028 49 0.214 0.252 24 2.737 2.672 

Arterial/Collectors 

at 19.2 mph 

18 0.042 0.041 48 0.264 0.304 24 3.616 4.291 

Arterial/Collectors 

at 11.6 mph 

20 0.034 0.022 49 0.458 0.805 24 4.665 4.888 

NYCC (7.1 mph) 19 0.082 0.089 49 0.622 1.024 24 6.571 6.609 

Local Roadways 

(12.9 mph) 

17 0.038 0.045 48 0.280 0.334 24 4.059 4.426 

Non-Freeway Areawide Urban Travel 

(19.4 mph) 

18 0.038 0.033 49 0.257 0.301 24 3.245 2.635 

Hot Running LA4 

(19.6 mph) 

20 0.020 0.009 49 0.157 0.176 24 2.945 2.770 

Unified Cycle 

(24.6 mph) 

19 0.041 0.039 48 0.232 0.265 24 2.860 2.930 

Final M6.SPD.002 59 June 2001 
Table 12a 

Regressions of Emissions Versus Average Speed 

Total Hydrocarbons (THC) 

Emissions = Constant + a*(Average Speed) 

Roadway Type Emission Level Speed Data 

Range (mph) 

Constant 

(p value) 

a 

(p value) 

Emission 

Units 

Freeway 1 

(Tier 1) 

7.1 - 13.1 1.034* -0.032* grams 

per hour 

Freeway 1 

(Tier 1) 

13.1 - 30.5 0.202 

(.4780) 

0.032 

(.0175) 

grams 

per hour 

Freeway 1 

(Tier 1) 

30.5 - 63.2 0.019 

(.2157) 

0.001 

(.0533) 

grams 

per mile 

Freeway 2 

(Tier 0 Normal) 

7.1 - 13.1 6.672* -0.170* grams 

per hour 

Freeway 2 

(Tier 0 Normal) 

13.1 - 30.5 1.933 

(.2284) 

0.192 

(.0094) 

grams 

per hour 

Freeway 2 

(Tier 0 Normal) 

30.5 - 63.2 0.315 

(.0000) 

-0.00226 

(.0570) 

grams 

per mile 

Freeway 3 

(Tier 0 High) 

7.1 - 13.1 44.558** 

(.0013) 

1.202** 

(.0908) 

grams 

per hour 

Freeway 3 

(Tier 0 High) 

13.1 - 30.5 44.558** 

(.0013) 

1.202** 

(.0908) 

grams 

per hour 

Freeway 3 

(Tier 0 High) 

30.5 - 63.2 3.193 

(.0000) 

-0.024 

(.0836) 

grams 

per mile 

Arterial/ 

Collector 

1 

(Tier 1) 

7.1 - 24.8 0.690 

(.0009) 

0.017 

(.0958) 

grams 

per hour 

Arterial/ 

Collector 

2 

(Tier 0 Normal) 

7.1 - 24.8 4.891 

(.0001) 

0.081 

(.1930) 

grams 

per hour 

Arterial/ 

Collector 

3 

(Tier 0 High) 

7.1 - 24.8 44.558** 

(.0013) 

1.202** 

(.0908) 

grams 

per hour

 * The values are calculated based on the NYCC at 7.1 mph and Freeway at 13.1 mph cycles. 

** Freeway and Arterial/Collector cycles were combined. 

Final M6.SPD.002 60 June 2001 
Table 12b 

Regressions of Emissions Versus Average Speed 

Carbon Monoxide (CO) 

Emissions = Constant + a*(Average Speed) 

Roadway Type Emission Level Speed Data 

Range (mph) 

Constant 

(p value) 

a 

(p value) 

Emission 

Units 

Freeway 1 

(Tier 1) 

7.1 - 13.1 14.730* 0.280* grams 

per hour 

Freeway 1 

(Tier 1) 

13.1 - 30.5 1.655 

(.9045) 

1.278 

(.0454) 

grams 

per hour 

Freeway 1 

(Tier 1) 

30.5 - 63.2 0.246 

(.7436) 

0.032 

(.0263) 

grams 

per mile 

Freeway 2 

(Tier 0 Normal) 

7.1 - 13.1 46.679* 2.390* grams 

per hour 

Freeway 2 

(Tier 0 Normal) 

13.1 - 30.5 15.273 

(.4824) 

4.788 

(.0000) 

grams 

per hour 

Freeway 2 

(Tier 0 Normal) 

30.5 - 63.2 2.398 

(.1526) 

0.0872 

(.0060) 

grams 

per mile 

Freeway 3 

(Tier 0 High) 

7.1 - 13.1 1206.641* -9.747* grams 

per hour 

Freeway 3 

(Tier 0 High) 

13.1 - 30.5 365.822 

(.4888) 

54.438 

(.0275) 

grams 

per hour 

Freeway 3 

(Tier 0 High) 

30.5 - 63.2 64.691 

(.0147) 

-0.0269 

(.9559) 

grams 

per mile 

Arterial/ 

Collector 

1 

(Tier 1) 

7.1 - 24.8 10.036 

(.1950) 

0.941 

(.0138) 

grams 

per hour 

Arterial/ 

Collector 

2 

(Tier 0 Normal) 

7.1 - 24.8 36.128 

(.0054) 

3.877 

(.0000) 

grams 

per hour 

Arterial/ 

Collector 

3 

(Tier 0 High) 

7.1 - 24.8 863.64 

(.0114) 

38.563 

(.0202) 

grams 

per hour

 * The values are calculated based on the NYCC at 7.1 mph and Freeway at 13.1 mph cycles. 

Final M6.SPD.002 61 June 2001 
Table 12c 

Regressions of Emissions Versus Average Speed 

Oxides of Nitrogen (NOx) 

Emissions = Constant + a*(Average Speed) 

Roadway Type Emission Level Speed Data 

Range (mph) 

Constant 

(p value) 

a 

(p value) 

Emission 

Units 

Freeway 1 

(Tier 1) 

7.1 - 13.1 4.625* -0.154* grams 

per hour 

Freeway 1 

(Tier 1) 

13.1 - 30.5 -0.855 

(.5289) 

0.264 

(.0001) 

grams 

per hour 

Freeway 1 

(Tier 1) 

30.5 - 63.2 0.126 

(.2886) 

0.0031 

(.1667) 

grams 

per mile 

Freeway 2 

(Tier 0 Normal) 

7.1 - 13.1 8.291* 0.121* grams 

per hour 

Freeway 2 

(Tier 0 Normal) 

13.1 - 30.5 -0.957 

(.7262) 

0.761 

(.0000) 

grams 

per hour 

Freeway 2 

(Tier 0 Normal) 

30.5 - 63.2 0.594 

(.0008) 

0.00373 

(.2575) 

grams 

per mile 

Freeway 3 

(Tier 0 High) 

7.1 - 13.1 24.889* 1.364* grams 

per hour 

Freeway 3 

(Tier 0 High) 

13.1 - 30.5 0.423 

(.9717) 

3.232 

(.0000) 

grams 

per hour 

Freeway 3 

(Tier 0 High) 

30.5 - 63.2 2.980 

(.0000) 

0.00512 

(.6389) 

grams 

per mile 

Arterial/ 

Collector 

1 

(Tier 1) 

7.1 - 24.8 2.325 

(.1066) 

0.170 

(.0167) 

grams 

per hour 

Arterial/ 

Collector 

2 

(Tier 0 Normal) 

7.1 - 24.8 5.123 

(.0027) 

0.567 

(.0000) 

grams 

per hour 

Arterial/ 

Collector 

3 

(Tier 0 High) 

7.1 - 24.8 14.609 

(.0471) 

2.812 

(.0000) 

grams 

per hour

 * The values are calculated based on the NYCC at 7.1 mph and Freeway at 13.1 mph cycles. 

Final M6.SPD.002 62 June 2001 
Table 12d 

Regressions of Emissions Versus Average Speed 

Non-Methane Hydrocarbons (NMHC) 

Emissions = Constant + a*(Average Speed) 

Roadway Type Emission Level Speed Data 

Range (mph) 

Constant 

(p value) 

a 

(p value) 

Emission 

Units 

Freeway 1 

(Tier 1) 

7.1 - 13.1 0.685* -0.028* grams 

per hour 

Freeway 1 

(Tier 1) 

13.1 - 30.5 0.00266 

(.9892) 

0.0236 

(.0105) 

grams 

per hour 

Freeway 1 

(Tier 1) 

30.5 - 63.2 0.00475 

(.6971) 

0.000592 

(.0115) 

grams 

per mile 

Freeway 2 

(Tier 0 Normal) 

7.1 - 13.1 5.796* -0.176* grams 

per hour 

Freeway 2 

(Tier 0 Normal) 

13.1 - 30.5 1.328 

(.3602) 

0.165 

(.0131) 

grams 

per hour 

Freeway 2 

(Tier 0 Normal) 

30.5 - 63.2 0.259 

(.0000) 

-0.00189 

(.0773) 

grams 

per mile 

Freeway 3 

(Tier 0 High) 

7.1 - 13.1 40.178* 1.103* grams 

per hour 

Freeway 3 

(Tier 0 High) 

13.1 - 30.5 37.404 

(.0580) 

1.107 

(.2142) 

grams 

per hour 

Freeway 3 

(Tier 0 High) 

30.5 - 63.2 2.899 

(.0000) 

-0.022 

(.0773) 

grams 

per mile 

Arterial/ 

Collector 

1 

(Tier 1) 

7.1 - 24.8 0.399 

(.0082) 

0.0118 

(.1048) 

grams 

per hour 

Arterial/ 

Collector 

2 

(Tier 0 Normal) 

7.1 - 24.8 4.111 

(.0003) 

0.0617 

(.2612) 

grams 

per hour 

Arterial/ 

Collector 

3 

(Tier 0 High) 

7.1 - 24.8 42.589 

(.0023) 

1.017 

(.1299) 

grams 

per hour

 * The values are calculated based on the NYCC at 7.1 mph and Freeway at 13.1 mph cycles. 

Final M6.SPD.002 63 June 2001 
Table 13 

Freeway Ramp and Local Roadway Emissions 

As a Function of Hot Running LA4 Emissions 

In Grams/Hour 

Emissions (g/hr) = Constant + a*(LA4) + b*(LA42) 

where LA4 is the hot running LA4 emissions in g/hr 

Roadway Type Pollutant Constant 

(p value) 

a 

(p value) 

b 

(p value) 

R2 

Freeway Ramp 

(34.6 mph) 

THC 4.560 

(.0302) 

2.046 

(.0000) 

-0.00356 

(.0000) 

0.934 

Freeway Ramp 

(34.6 mph) 

CO 224.333 

(.0010) 

2.040 

(.0000) 

-0.000145 

(.0074) 

0.848 

Freeway Ramp 

(34.6 mph) 

NOx 5.353 

(.1103) 

2.863 

(.0000) 

-.0101 

(.0019) 

0.866 

Freeway Ramp 

(34.6 mph) 

NMHC 4.368 

(.0193) 

2.014 

(.0000) 

-0.00387 

(.0000) 

0.934 

Local Roadways 

(12.9 mph) 

THC 0.00 1.0319 

(.0000) 

-0.0007 

(.2960) 

0.804 

Local Roadways 

(12.9 mph) 

CO 0.00 0.7405 

(.0000) 

0.000 

(.9242) 

0.831 

Local Roadways 

(12.9 mph) 

NOx 0.00 0.8156 

(.0000) 

-0.0005 

(.4656) 

0.952 

Local Roadways 

(12.9 mph) 

NMHC 0.00 1.1097 

(.0000) 

-0.0015 

(.0172) 

0.804 

Final M6.SPD.002 64 June 2001 
Table 14 

Emission Offset 

(Predicted Freeway Emissions - Average Hot Running LA4 Emissions) 

Level 1 (Tier 1) 

(grams per mile) 

Level 2 (Tier 0) 

(grams per mile) 

Level 3 (High Emitters) 

(grams per mile) 

Fwy LA4 Offset Fwy LA4 Offset Fwy LA4 Offset 

THC 0.042 0.036 0.006 0.290 0.199 0.091 3.476 3.175 0.301 

CO 1.363 0.892 0.471 5.567 3.569 1.998 73.102 82.194 -9.092 

NOx 0.220 0.191 0.029 0.712 0.591 0.121 3.253 3.245 0.008 

NMHC 0.024 0.020 0.004 0.233 0.157 0.076 3.153 2.945 0.208 

Final M6.SPD.002 65 June 2001 
Table 15 

Arterial/Collector Emission Offsets (AEO) 

(Predicted Arterial/Collector Emissions - Predicted Freeway Emissions) 

Pollutant 

Average Speed* 

(miles per hour) 

Level 1 

(grams per mile) 

Level 2 

(grams per mile) 

Level 3 

(grams per mile) 

THC 10 0.014 0.073 0 

15 0.018 0.086 0 

20 0.009 0.037 0 

25 0.005 0.007 0 

30 0.001 0 0 

CO 10 0.192 0.431 14.010 

15 0.222 0.479 17.313 

20 0.082 0.131 9.016 

25 0 0 4.038 

30 0 0 0.719 

NOx 10 0.094 0.171 0.420 

15 0.118 0.211 0.526 

20 0.065 0.110 0.290 

25 0.033 0.049 0.148 

30 0.012 0.009 0.053 

NMHC 10 0.012 0.069 0 

15 0.015 0.082 0 

20 0.008 0.035 0 

25 0.004 0.008 0 

30 0.001 0 0 

* Arterial/Collector Emission Offsets below 10 mph and over 30 mph are zero. 

Final M6.SPD.002 66 June 2001 
Table 16 

Speed Correction Factors 

For Freeways 

By Emission Level* 

Avg. 

Speed 

(mph) 

Total Hydrocarbons 

(THC) 

Carbon Monoxide 

(CO) 

Oxides of Nitrogen 

(NOx) 

Non-Methane HC 

(NMHC) 

Level 1 Level 2 Level 3 Level 1 Level 2 Level 3 Level 1 Level 2 Level 3 Level 1 Level 2 Level 3 

7.1 2.71 2.65 2.15 1.73 1.61 2.19 2.26 1.81 1.50 2.87 2.75 2.14 

10 1.71 1.71 1.63 1.29 1.27 1.52 1.40 1.28 1.18 1.69 1.73 1.62 

15 1.08 1.10 1.20 1.02 1.04 1.08 0.94 0.98 1.00 1.00 1.09 1.20 

19.6 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 

20 1.00 0.99 0.99 1.00 1.00 0.99 1.00 1.00 1.00 1.00 0.99 0.99 

25 0.95 0.93 0.86 0.99 0.97 0.94 1.04 1.01 1.00 1.00 0.94 0.86 

30 0.91 0.88 0.77 0.98 0.95 0.91 1.07 1.02 1.00 1.00 0.90 0.77 

35 0.91 0.81 0.68 1.00 0.98 0.87 1.07 1.02 1.00 1.07 0.83 0.68 

40 0.97 0.77 0.64 1.12 1.06 0.87 1.14 1.04 1.00 1.20 0.79 0.64 

45 1.04 0.73 0.61 1.24 1.14 0.87 1.21 1.07 1.00 1.32 0.74 0.61 

50 1.10 0.69 0.57 1.36 1.21 0.87 1.28 1.09 1.00 1.45 0.70 0.57 

55 1.17 0.65 0.54 1.47 1.29 0.86 1.35 1.12 1.00 1.57 0.66 0.54 

60 1.24 0.61 0.50 1.59 1.37 0.86 1.42 1.15 1.01 1.70 0.62 0.50 

65 1.30 0.57 0.47 1.71 1.45 0.86 1.49 1.17 1.02 1.82 0.58 0.47 

* Emission levels shown as Fwy emissions in Table 14. See Section 4.6. 

Final M6.SPD.002 67 June 2001 
Table 17 

Speed Correction Factors 

For Arterial/Collector Roadways 

By Emission Level* 

Avg. 

Speed 

(mph) 

Total Hydrocarbons 

(THC) 

Carbon Monoxide 

(CO) 

Oxides of Nitrogen 

(NOx) 

Non-Methane HC 

(NMHC) 

Level 1 Level 2 Level 3 Level 1 Level 2 Level 3 Level 1 Level 2 Level 3 Level 1 Level 2 Level 3 

7.1 2.71 2.65 2.15 1.73 1.61 2.19 2.26 1.81 1.50 2.87 2.75 2.14 

10 2.04 1.96 1.63 1.43 1.35 1.71 1.82 1.52 1.31 2.18 2.03 1.62 

15 1.49 1.40 1.20 1.18 1.13 1.32 1.47 1.28 1.16 1.62 1.44 1.20 

20 1.22 1.12 0.99 1.06 1.02 1.12 1.30 1.16 1.09 1.34 1.15 0.99 

25 1.05 0.95 0.86 0.99 0.97 1.00 1.19 1.08 1.04 1.17 0.97 0.86 

30 0.95 0.88 0.77 0.98 0.95 0.92 1.12 1.04 1.01 1.06 0.90 0.77 

35 0.91 0.81 0.68 1.00 0.98 0.87 1.07 1.02 1.00 1.07 0.83 0.68 

40 0.97 0.77 0.64 1.12 1.06 0.87 1.14 1.04 1.00 1.20 0.79 0.64 

45 1.04 0.73 0.61 1.24 1.14 0.87 1.21 1.07 1.00 1.32 0.74 0.61 

50 1.10 0.69 0.57 1.36 1.21 0.87 1.28 1.09 1.00 1.45 0.70 0.57 

55 1.17 0.65 0.54 1.47 1.29 0.86 1.35 1.12 1.00 1.57 0.66 0.54 

60 1.24 0.61 0.50 1.59 1.37 0.86 1.42 1.15 1.01 1.70 0.62 0.50 

65 1.30 0.57 0.47 1.71 1.45 0.86 1.49 1.17 1.02 1.82 0.58 0.47 

* Emission levels shown as Fwy emissions in Table 14. See Section 4.6. 

Final M6.SPD.002 68 June 2001 
 

Table 18 

Speed Correction Factors for Light Duty Diesel Vehicles 

SCF(s) = EXP(B*(s-sadj) + C*(s**2-sadj**2)) 

s = average speed (mph) 

sadj = basic test procedure speed; adjusted for VMT fraction of cold start operation x (0.206) 

and VMT fraction of hot start operation w (0.273), assuming FTP weighting. 

1/sadj = (w+x)/26 + (1-w-x)/16 

sadj = 19.6 mph 

Pollutant Model Years 

Coefficient Values 

(B) (C) 

THC All -0.055 0.00044 

CO All -0.088 0.00091 

NOx All -0.048 0.00071 

From “AP-42 Volume II, Compilation of Air Pollution Emission Factors, Mobile Sources,” 

Appendix H, Table 5.6 and Table 6.6 (June 30, 1995) 

Final M6.SPD.002 69 June 2001 
Table 19 

Speed Correction Factors for Heavy Duty Gasoline Vehicles 

SCF(s) = EXP(A + B*s + C*s**2), for THC & CO 

SCF(s) = A + B*s + C*s**2, for NOx 

s = average speed (mph) 

Pollutant Model Years 

Coefficient Values 

(A) (B) (C) 

THC All 1.608 -0.097 0.00083 

CO All 1.520 -0.098 0.0011 

NOx All 0.824 0.0088 0.00 

From “AP-42 Volume II, Compilation of Air Pollution Emission Factors, Mobile Sources,” 

Appendix H, Table 4.6 (June 30, 1995) 

Table 20 

Speed Correction Factors for Heavy Duty Diesel Vehicles 

SCF(s) = EXP(A + B*s + C*s**2) 

s = average speed (mph) 

Pollutant Model Years 

Coefficient Values 

(A) (B) (C) 

THC All 0.924 -0.055 0.00044 

CO All 1.396 -0.088 0.00091 

NOx All 0.676 -0.048 0.00071 

From “AP-42 Volume II, Compilation of Air Pollution Emission Factors, Mobile Sources,” 

Appendix H, Table 7.6 (June 30, 1995) 

Final M6.SPD.002 70 June 2001 
Table 21 

Speed Correction Factors for Motorcycles 

SCF( s) = SF( s)/ SF( sadj) 

SF(s) = EXP( A + B* s + C* s** 2+ D* s** 3+ E* s** 4+ F* s** 5), for THC & CO 

SF(s) = A + B* s + C* s** 2+ D* s** 3+ E* s** 4 + F* s** 5, for NOx 

s = average speed (mph) 

sadj = 19.6 mph 

Pollutant Model Years 

Coefficient Values 

(A) (B) (C) (D) (E) (F) 

Low Altitude 

THC Pre-1978 2.31E+00 -2.90E-01 1.53E-02 -4.47E-04 6.48E-06 -3.63E-08 

1978-1979 2.41E+00 -3.08E-01 1.68E-02 -5.07E-04 7.54E-06 -4.32E-08 

1980+ 2.25E+00 -2.88E-01 1.57E-02 -4.73E-04 7.08E-06 -4.08E-08 

CO Pre-1978 2.34E+00 -2.97E-01 1.60E-02 -4.77E-04 7.07E-06 -4.04E-08 

1978-1979 2.78E+00 -3.19E-01 1.53E-02 -4.22E-04 5.85E-06 -3.15E-08 

1980+ 2.71E+00 -3.31E-01 1.76E-02 -5.39E-04 8.17E-06 -4.78E-08 

NOx Pre-1978 1.69E+00 -1.18E-01 6.55E-03 -1.37E-04 1.01E-06 0.00E+00 

1978+ 1.28E+00 -8.05E-02 5.36E-03 -1.19E-04 9.01E-07 0.00E+00 

High Altitudes 

THC Pre-1978 2.25E+00 -2.91E-01 1.59E-02 -4.72E-04 6.94E-06 -3.93E-08 

1978-1979 2.15E+00 -2.84E-01 1.54E-02 -4.42E-04 6.29E-06 -3.46E-08 

1980+ 2.12E+00 -2.91E-01 1.69E-02 -5.26E-04 8.03E-06 -4.70E-08 

CO Pre-1978 1.82E+00 -2.55E-01 1.52E-02 -4.87E-04 7.58E-06 -4.50E-08 

1978-1979 1.82E+00 -2.72E-01 1.70E-02 -5.52E-04 8.63E-06 -5.11E-08 

1980+ 2.05E+00 -3.11E-01 2.05E-02 -7.09E-04 1.16E-05 -7.16E-08 

NOx Pre-1978 2.44E+00 -2.50E-01 1.38E-02 -2.87E-04 2.08E-06 0.00E+00 

1978+ 1.45E+00 -1.22E-01 7.95E-03 -1.71E-04 1.26E-06 0.00E+00 

From “AP-42 Volume II, Compilation of Air Pollution Emission Factors, Mobile Sources,” 

Appendix H, Table 8.6.1 and Table 8.6.2 (June 30, 1995) 

Final M6.SPD.002 71 June 2001 
Figures 

Final M6.SPD.002 72 June 2001 
Figure 1a. 

Facility Cycles Ratio of M eans, HC by 

Emitter Level Groups 

0.000 

0.500 

1.000 

1.500 

2.000 

2.500 

3.000 

3.500 

4.000 

0 20 40 60 80 

Average Speed (mph) 

Ratio of Means

(HC/Running LA4)

Low Emitters 

H igh Emitters 

Figure 1b. 

Facility Cycles Ratio of Means, CO by 

Emitter Level Groups 

0.000 

0.500 

1.000 

1.500 

2.000 

2.500 

3.000 

3.500 

0 20 40 60 80 

Average Speed (mph) 

Ratio of Means

(CO/Running LA4) 

Low Emitters 

High Emitters 

Final M6.SPD.002 73 June 2001 
F ig ure 1c. 

Facility Cycles Ratio of M eans, NOx 

by Emitter Level Groups 

0.000 

0.200 

0.400 

0.600 

0.800 

1.000 

1.200 

1.400 

1.600 

1.800 

2.000 

0 20 40 60 80 

Average Speed (m ph) 

Ratio of Means

(NOx/Running LA4) 

L ow E m itters 

H ig h E m itters 

Final M6.SPD.002 74 June 2001 
Figure 2a. 

Facility Cycle Data, HC 

0.000 

0.500 

1.000 

1.500 

2.000 

2.500 

3.000 

3.500 

4.000 

0 20 40 60 80 

Average Speed 

Ra tio o f M e a n s

(HC/Running LA4 ) 

Legend for Figures 2a, b and c 

Arte ria l/Colle ctors 

F re e w a ys 

LA92 

Are a -w ide , non-fre e w a y 

Local 

Ra m p 

Final M6.SPD.002 75 June 2001 
F ig u re 2b . 

Facility Cycle Data, CO 

0.000 

0.500 

1.000 

1.500 

2.000 

2.500 

3.000 

3.500 

0 20 40 60 80 

Average Speed 

R a tio o f M e a n s

(C O /Ru n nin g L A 4 

F ig u re 2c. 

Facility Cycle Data, NOx 

0.000 

0.200 

0.400 

0.600 

0.800 

1.000 

1.200 

1.400 

1.600 

1.800 

2.000 

0 20 40 60 80 

Average Speed 

R a tio o f M e a n s

(NO x/Ru n ning L A 4 

Final M6.SPD.002 76 June 2001 
0.000

2.000

4.000

0 100

Figure 3a. 

Facility Cycle Data, THC 

Tier 0 vs. Tier 1 

0.000 

0.500 

1.000 

1.500 

2.000 

2.500 

3.000 

3.500 

4.000 

0 20 40 60 80 

Average Speed 

Ratio of Means

(THC/Running LA4) 

Legend for Figures 3a, 3b and 3c 

Arterial/Collectors, Tier 0
 

Freeways, Tier 0
 

Local, Tier 0
 

Ramp, Tier 0
 

LA92, Tier 0
 

Area-wide, non-freeway, Tier 0
 

Arterial/Collectors, Tier 1
 

Freeways, Tier 1
 

Local, Tier 1
 

Ramp, Tier 1
 

LA92, Tier 1
 

Area-wide, non-freeway, Tier 1
 

Final M6.SPD.002 77 June 2001 
Figure 3b. 

Facility Cycle Data, CO 

Tier 0 vs. Tier 1 

0.000 

1.000 

2.000 

3.000 

4.000 

5.000 

6.000 

0 20 40 60 80 

Average Speed 

Ratio of Mean

s

(CO/Running

LA4) 

Figure 3c. 

Facility Cycle Data, NOx 

Tier 0 vs. Tier 1 

0.000 

0.500 

1.000 

1.500 

2.000 

2.500 

0 20 40 60 80 

Average Speed 

Ratio of Means

(NOx/Running LA4) 

Final M6.SPD.002 78 June 2001 
Figure 4b 

Carbon Monoxide (CO) 

Freeway Emission Levels 

0 

20 

40 

60 

80 

100 

120 

140 

160 

180 

5 10 15 20 25 30 35 40 

Average Speed (mph) 

Emissions in Grams Per Mile 

Level 1 (Tier 1 Normal) 

Level 2 (Tier 0 Normal) 

Level 3 (Tier 0 High) 

Figure 4a 

Total Hydrocarbon (THC) 

Freeway Emission Levels 

0.0 

1.0 

2.0 

3.0 

4.0 

5.0 

6.0 

7.0 

8.0 

5 10 15 20 25 30 35 40 

Average Speed (mph) 

Emissions in Grams Per Mile 

Level 1 (Tier 1 Normal) 

Level 2 (Tier 0 Normal) 

Level 3 (Tier 0 High) 

Final M6.SPD.002 79 June 2001 
Figure 4d 

Non-Methane Hydrocarbons (NMHC) 

Freeway Emission Levels 

0.0 

1.0 

2.0 

3.0 

4.0 

5.0 

6.0 

7.0 

5 10 15 20 25 30 35 40 

Average Speed (mph) 

Emissions in Grams Per Mile 

Level 1 (Tier 1 Normal) 

Level 2 (Tier 0 Normal) 

Level 3 (Tier 0 High) 

Figure 4c 

Oxides of Nitrogen (NOx) 

Freeway Emission Levels 

0.0 

0.5 

1.0 

1.5 

2.0 

2.5 

3.0 

3.5 

4.0 

4.5 

5.0 

5 10 15 20 25 30 35 40 

Average Speed (mph) 

Emissions in Grams Per Mile 

Level 1 (Tier 1 Normal) 

Level 2 (Tier 0 Normal) 

Level 3 (Tier 0 High) 

Final M6.SPD.002 80 June 2001 
Figure 5a 

Freeway Speed Correction Factors for 

Total Hydrocarbons (THC) 

0.0 

0.5 

1.0 

1.5 

2.0 

2.5 

3.0 

0 10 20 30 40 50 60 70 

Average Speed (mph) 

Speed Correction Factor 

Emission Level 1 

(0.04 g/mi) 

Emission Level 2 

(0.29 g/mi) 

Emission Level 3 

(3.48 g/mi) 

Figure 5b 

Freeway Speed Correction Factors for 

Carbon Monoxide (CO) 

0.0 

0.5 

1.0 

1.5 

2.0 

2.5 

0 10 20 30 40 50 60 70 

Average Speed (mph) 

Speed Correction Factor 

Emission Level 1 

(1.4 g/mi) 

Emission Level 2 

(5.6 g/mi) 

Emission Level 3 

(73.1 g/mi) 

Final M6.SPD.002 81 June 2001 
Figure 5d 

Freeway Speed Correction Factors for 

Non-Methane Hydrocarbons (NMHC) 

0.0 

0.5 

1.0 

1.5 

2.0 

2.5 

3.0 

3.5 

0 10 20 30 40 50 60 70 

Average Speed (mph) 

Speed Correction Factor 

Emission Level 1 

(0.02 g/mi) 

Emission Level 2 

(0.23 g/mi) 

Emission Level 3 

(3.15 g/mi) 

Figure 5c 

Freeway Speed Correction Factors for 

Oxides of Nitrogen (NOx) 

0.0 

0.5 

1.0 

1.5 

2.0 

2.5 

0 10 20 30 40 50 60 70 

Average Speed (mph) 

Speed Correction Factor 

Emission Level 1 

(0.22 g/mi) 

Emission Level 2 

(0.71 g/mi) 

Emission Level 3 

(3.25 g/mi) 

Final M6.SPD.002 82 June 2001 
Figure 6a 

Comparison to MOBILE5 

Speed Correction Factors for 

Total Hydrocarbons (THC) 

0.00 

0.50 

1.00 

1.50 

2.00 

2.50 

3.00 

0 10 20 30 40 50 60 70 

Average Speed (mph) 

Speed Correction Factor 

Emission Level 1 (0.04 g/mi) 

Emission Level 2 (0.29 g/mi) 

Emission Level 3 (3.48 g/mi) 

M5 1975 MYR 

M5 1981 MYR 

M5 1991+ MYR 

Figure 6b 

Comparison to MOBILE5 

Speed Correction Factors for 

Carbon Monoxide (CO) 

0.00 

0.50 

1.00 

1.50 

2.00 

2.50 

0 10 20 30 40 50 60 70 

Average Speed (mph) 

Speed Correction Factor 

Emission Level 1 (1.4 g/mi) 

Emission Level 2 (5.6 g/mi) 

Emission Level 3 (73.1 g/mi) 

M5 1975 MYR 

M5 1981 MYR 

M5 1993+ MYR 

Final M6.SPD.002 83 June 2001 
Figure 7a 

Arterial/Collector Speed Correction Factors 

Total Hydrocarbons (THC) 

Level 1 Emissions (0.04 g/mi) 

0.0 

0.5 

1.0 

1.5 

2.0 

2.5 

3.0 

5 10 15 20 25 30 35 40 

Average Speed (mph) 

Speed Correction Factor 

M5 1975 MYR 

M5 1981 MYR 

M5 1993+ MYR 

Freeway Level 1 

Arterial/Collector Level 1 

Figure 6c 

Comparison to MOBILE5 

Speed Correction Factors for 

Oxides of Nitrogen (NOx) 

0.00 

0.50 

1.00 

1.50 

2.00 

2.50 

0 10 20 30 40 50 60 70 

Average Speed (mph) 

Speed Correction Factor 

Emission Level 1 (0.22 g/mi) 

Emission Level 2 (0.71 g/mi) 

Emission Level 3 (3.25 g/mi) 

M5 1975 MYR 

M5 1981 MYR 

M5 1993+ MYR 

Final M6.SPD.002 84 June 2001 
Figure 7b 

Arterial/Collector Speed Correction Factors 

Total Hydrocarbons (THC) 

Level 2 Emissions (0.29 g/mi) 

0.0 

0.5 

1.0 

1.5 

2.0 

2.5 

3.0 

5 10 15 20 25 30 35 40 

Average Speed (mph) 

Speed Correction Factor 

M5 1975 MYR 

M5 1981 MYR 

M5 1993+ MYR 

Freeway Level 1 

Arterial/Collector Level 1 

Figure 7c 

Arterial/Collector Speed Correction Factors 

Total Hydrocarbons (THC) 

Level 3 Emissions (3.48 g/mi) 

0.0 

0.5 

1.0 

1.5 

2.0 

2.5 

5 10 15 20 25 30 35 40 

Average Speed (mph) 

Speed Correction Factor 

M5 1975 MYR 

M5 1981 MYR 

M5 1993+ MYR 

Freeway Level 3 

Arterial/Collector Level 3 

Final M6.SPD.002 85 June 2001 
Figure 7d 

Arterial/Collector Speed Correction Factors 

Carbon Monoxide (CO) 

Level 1 Emissions (1.36 g/mi) 

0.0 

0.5 

1.0 

1.5 

2.0 

2.5 

5 10 15 20 25 30 35 40 

Average Speed (mph) 

Speed Correction Factor 

M5 1975 MYR 

M5 1981 MYR 

M5 1993+ MYR 

Freeway Level 1 

Arterial/Collector Level 1 

Figure 7e 

Arterial/Collector Speed Correction Factors 

Carbon Monoxide (CO) 

Level 2 Emissions (5.57 g/mi) 

0.0 

0.5 

1.0 

1.5 

2.0 

2.5 

5 10 15 20 25 30 35 40 

Average Speed (mph) 

Speed Correction Factor 

M5 1975 MYR 

M5 1981 MYR 

M5 1993+ MYR 

Freeway Level 2 

Arterial/Collector Level 2 

Final M6.SPD.002 86 June 2001 
Figure 7f 

Arterial/Collector Speed Correction Factors 

Carbon Monoxide (CO) 

Level 3 Emissions (73.1 g/mi) 

0.0 

0.5 

1.0 

1.5 

2.0 

2.5 

5 10 15 20 25 30 35 40 

Average Speed (mph) 

Speed Correction Factor 

M5 1975 MYR 

M5 1981 MYR 

M5 1993+ MYR 

Freeway Level 3 

Arterial/Collector Level 3 

Figure 7g 

Arterial/Collector Speed Correction Factors 

Oxides of Nitrogen (NOx) 

Level 1 Emissions (0.22 g/mi) 

0.0 

0.5 

1.0 

1.5 

2.0 

2.5 

5 10 15 20 25 30 35 40 

Average Speed (mph) 

Speed Correction Factor 

M5 1975 MYR 

M5 1981 MYR 

M5 1993+ MYR 

Freeway Level 1 

Arterial/Collector Level 1 

Final M6.SPD.002 87 June 2001 
Figure 7h 

Arterial/Collector Speed Correction Factors 

Oxides of Nitrogen (NOx) 

Level 2 Emissions (0.71 g/mi) 

0.0 

0.5 

1.0 

1.5 

2.0 

2.5 

5 10 15 20 25 30 35 40 

Average Speed (mph) 

Speed Correction Factor 

M5 1975 MYR 

M5 1981 MYR 

M5 1993+ MYR 

Freeway Level 2 

Arterial/Collector Level 2 

Figure 7i 

Arterial/Collector Speed Correction Factors 

Oxides of Nitrogen (NOx) 

Level 3 Emissions (3.25 g/mi) 

0.0 

0.5 

1.0 

1.5 

2.0 

2.5 

5 10 15 20 25 30 35 40 

Average Speed (mph) 

Speed Correction Factor 

M5 1975 MYR 

M5 1981 MYR 

M5 1993+ MYR 

Freeway Level 3 

Arterial/Collector Level 3 

Final M6.SPD.002 88 June 2001 
Figure 8a
 

CO Off-Cycle Emissions
 

-50 

-40 

-30 

-20 

-10 

0 

10 

20 

30 

40 

50 

60 

Off-Cycle CO Offset (g/mi) 

Normal 

High 

Data 

0 10 20 30 40 50 60 70 80 90 

Basic Exhaust Running Emissions (LA4 g/mi) 

Final M6.SPD.002 89 June 2001 

100 
Figure 8b
 

THC Off-Cycle Emissions
 

-0.50 

-0.40 

-0.30 

-0.20 

-0.10 

0.00 

0.10 

0.20 

0.30 

0.40 

0.50 

0.60 

0.70 

0.80 

0.90 

1.00 

Off-Cycle THC Offset (g/mi) 

0 1 2 3 4 5 

Basic Exhaust Running Emissions (LA4 g/mi) 

Final M6.SPD.002 90 June 2001 

6 
2.5 

Off-Cycle NOx Offset (g/mi) 

Figure 8c
 

NOx Off-Cycle Emissions
 

2 

1.5 

1 

0.5 

0 

-0.5 

-1 

0 1 2 3 4 5 6 7 8 9 

< 3.50 g/mi 

> 3.50 g/mi 

NOX_DELT 

Basic Exhaust Running Emissions (LA4 g/mi) 

Final M6.SPD.002 91 June 2001 
Speed Correction Factor 

Figure 9a 

Comparison of MOBILE6 Level 1 NOx SCFs with Clean SFTP SCFs 

2.4 

2.2 

2.0 

1.8 

1.6 

1.4 

1.2 

Case 

1.0 

M6 Level 1 SCF 

.8 Clean SFTP 

0 10 20 30 40 50 60 70 

Average Speed 

Final M6.SPD.002 92 June 2001 
Figure 9b 

Comparison of MOBILE6 Level 1 HC SCFs with Clean SFTP SCFs 

Speed Correction Factor 

3.0 

2.5 

2.0 

1.5 

1.0 

.5 

0 10 20 30 40 50 60 70 

Average Speed 

Case 

M6 Level 1 SCF 

Clean SFTP 

Final M6.SPD.002 93 June 2001 
Figure 9c 

Comparison of MOBILE6 Level 1 CO SCFs with Clean SFTP CO SCFs 

Final M6.SPD.002 94 June 2001 
Appendices 

Final M6.SPD.002 95 June 2001 
 

 

 

 

 

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Appendix A : Statistics 

MAIN EFFECTS & INTERACTIONS WITH SPEED
 

All Vehicles
 

| | THC | NMHC | CO | NOX |
 

|----------------------------+-------+-------+-------+-------|
 

|FACTOR | | | | |
 

|----------------------------| | | | |
 

|S | 0.0000| 0.0001| 0.0000| 0.0000|
 

|----------------------------+-------+-------+-------+-------|
 

|EMIT_CLASS | 0.0000| 0.0000| 0.0000| 0.0000|
 

|----------------------------+-------+-------+-------+-------|
 

|S*EMIT_CLASS | 0.1411| 0.1271| 0.0152| 0.9894|
 

Final M6.SPD.002 96 June 2001 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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EMIT NORMAL - ACTUAL TIER CLASS
 

| | THC | NMHC | CO | NOX |
 

|----------------------------+-------+-------+-------+-------|
 

|ROAD |FACTOR | | | | |
 

|-------------+--------------| | | | |
 

|ART/FWY |ROADTYPE | 0.0046| 0.0050| 0.0006| 0.0000|
 

| |--------------+-------+-------+-------+-------|
 

| |S*ROADTYPE | 0.0354| 0.0440| 0.0020| 0.0000|
 

| |--------------+-------+-------+-------+-------|
 

| |VEH_TYPE | 0.0016| 0.0404| 0.0031| 0.0012|
 

| |--------------+-------+-------+-------+-------|
 

| |S*VEH_TYPE | 0.1754| 0.1802| 0.8680| 0.5723|
 

| |--------------+-------+-------+-------+-------|
 

| |STANDARD | 0.0000| 0.0000| 0.0000| 0.0000|
 

| |--------------+-------+-------+-------+-------|
 

| |S*STANDARD | 0.0002| 0.0001| 0.0576| 0.6491|
 

|LOCAL |VEH_TYPE | 0.0830| 0.5008| 0.4038| 0.0124|
 

| |--------------+-------+-------+-------+-------|
 

| |STANDARD | 0.0000| 0.0000| 0.0000| 0.0028|
 

|-------------+--------------+-------+-------+-------+-------|
 

|RAMP |VEH_TYPE | 0.2922| 0.7707| 0.0443| 0.0018|
 

| |--------------+-------+-------+-------+-------|
 

| |STANDARD | 0.0003| 0.0007| 0.0002| 0.0000|
 

EMIT HIGH - ACTUAL TIER CLASS
 

| | THC | NMHC | CO | NOX |
 

|----------------------------+-------+-------+-------+-------|
 

|ROAD |FACTOR | | | | |
 

|-------------+--------------| | | | |
 

|ART/FWY |ROADTYPE | 0.1236| 0.1307| 0.3307| 0.0000|
 

| |--------------+-------+-------+-------+-------|
 

| |S*ROADTYPE | 0.1176| 0.1203| 0.6233| 0.0000|
 

| |--------------+-------+-------+-------+-------|
 

| |VEH_TYPE | 0.5942| 0.5693| 0.8984| 0.3961|
 

| |--------------+-------+-------+-------+-------|
 

| |S*VEH_TYPE | 0.0641| 0.0699| 0.0241| 0.9560|
 

| |--------------+-------+-------+-------+-------|
 

| |STANDARD | N/A| N/A| N/A| N/A|
 

| |--------------+-------+-------+-------+-------|
 

| |S*STANDARD | N/A| N/A| N/A| N/A|
 

|LOCAL |VEH_TYPE | 0.8787| 0.8821| 0.5511| 0.6093|
 

| |--------------+-------+-------+-------+-------|
 

| |STANDARD | N/A| N/A| N/A| N/A|
 

|-------------+--------------+-------+-------+-------+-------|
 

|RAMP |VEH_TYPE | 0.3701| 0.4075| 0.1471| 0.6942|
 

| |--------------+-------+-------+-------+-------|
 

| |STANDARD | N/A| N/A| N/A| N/A|
 

Final M6.SPD.002 97 June 2001 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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EMIT NORMAL - CLEAN TIER 0 CLASS
 

| | THC | NMHC | CO | NOX |
 

|----------------------------+-------+-------+-------+-------|
 

|ROAD |FACTOR | | | | |
 

|-------------+--------------| | | | |
 

|ART/FWY |ROADTYPE | 0.0046| 0.0050| 0.0006| 0.0000|
 

| |--------------+-------+-------+-------+-------|
 

| |S*ROADTYPE | 0.0354| 0.0440| 0.0020| 0.0000|
 

| |--------------+-------+-------+-------+-------|
 

| |VEH_TYPE | 0.0004| 0.0243| 0.0062| 0.0026|
 

| |--------------+-------+-------+-------+-------|
 

| |S*VEH_TYPE | 0.1322| 0.1476| 0.8361| 0.5608|
 

| |--------------+-------+-------+-------+-------|
 

| |CLEANT0 | 0.0000| 0.0000| 0.0000| 0.0000|
 

| |--------------+-------+-------+-------+-------|
 

| |S*CLEANT0 | 0.0002| 0.0001| 0.0576| 0.6491|
 

|LOCAL |VEH_TYPE | 0.0572| 0.4049| 0.1660| 0.0184|
 

| |--------------+-------+-------+-------+-------|
 

| |CLEANT0 | 0.0000| 0.0000| 0.0000| 0.0028|
 

|-------------+--------------+-------+-------+-------+-------|
 

|RAMP |VEH_TYPE | 0.1570| 0.5501| 0.0201| 0.0009|
 

| |--------------+-------+-------+-------+-------|
 

| |CLEANT0 | 0.0003| 0.0007| 0.0002| 0.0000|
 

EMIT HIGH - CLEAN TIER 0 CLASS
 

| | THC | NMHC | CO | NOX |
 

|----------------------------+-------+-------+-------+-------|
 

|ROAD |FACTOR | | | | |
 

|-------------+--------------| | | | |
 

|ART/FWY |ROADTYPE | 0.1236| 0.1307| 0.3307| 0.0000|
 

| |--------------+-------+-------+-------+-------|
 

| |S*ROADTYPE | 0.1176| 0.1203| 0.6233| 0.0000|
 

| |--------------+-------+-------+-------+-------|
 

| |VEH_TYPE | 0.5942| 0.5693| 0.8984| 0.3961|
 

| |--------------+-------+-------+-------+-------|
 

| |S*VEH_TYPE | 0.0641| 0.0699| 0.0241| 0.9560|
 

| |--------------+-------+-------+-------+-------|
 

| |CLEANT0 | .| .| .| .|
 

| |--------------+-------+-------+-------+-------|
 

| |S*CLEANT0 | .| .| .| .|
 

|LOCAL |VEH_TYPE | 0.8787| 0.8821| 0.5511| 0.6093|
 

| |--------------+-------+-------+-------+-------|
 

| |CLEANT0 | .| .| .| .|
 

|-------------+--------------+-------+-------+-------+-------|
 

|RAMP |VEH_TYPE | 0.3701| 0.4075| 0.1471| 0.6942|
 

| |--------------+-------+-------+-------+-------|
 

| |CLEANT0 | .| .| .| .|
 

Final M6.SPD.002 98 June 2001 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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EMIT NORMAL
 

| | P |
 

| |-------------------------------|
 

| | THC | NMHC | CO | NOX |
 

| |-------+-------+-------+-------|
 

| | PROB | PROB | PROB | PROB |
 

|----------------------------+-------+-------+-------+-------|
 

|ROAD |FACTOR | | | | |
 

|-------------+--------------| | | | |
 

|ART/FWY |ROADWAY TYPE | 0.0001| 0.0000| 0.0405| 0.0000|
 

| |--------------+-------+-------+-------+-------|
 

| |VEHICLE CLASS | 0.0000| 0.0640| 0.0000| 0.0000|
 

| |--------------+-------+-------+-------+-------|
 

| |STANDARD | 0.0000| 0.0000| 0.0000| 0.0000|
 

|-------------+--------------+-------+-------+-------+-------|
 

|LOCAL |VEHICLE CLASS | 0.1017| 0.5022| 0.1380| 0.0408|
 

| |--------------+-------+-------+-------+-------|
 

| |STANDARD | 0.0000| 0.0000| 0.0000| 0.0000|
 

|-------------+--------------+-------+-------+-------+-------|
 

|RAMP |VEHICLE CLASS | 0.2047| 0.6109| 0.0213| 0.0035|
 

| |--------------+-------+-------+-------+-------|
 

| |STANDARD | 0.0000| 0.0000| 0.0000| 0.0000|
 

EMIT HIGH
 

| | P |
 

| |-------------------------------|
 

| | THC | NMHC | CO | NOX |
 

| |-------+-------+-------+-------|
 

| | PROB | PROB | PROB | PROB |
 

|----------------------------+-------+-------+-------+-------|
 

|ROAD |FACTOR | | | | |
 

|-------------+--------------| | | | |
 

|ART/FWY |ROADWAY TYPE | 0.9736| 0.9570| 0.0151| 0.0201|
 

| |--------------+-------+-------+-------+-------|
 

| |VEHICLE CLASS | 0.0667| 0.0873| 0.0004| 0.1444|
 

| |--------------+-------+-------+-------+-------|
 

| |STANDARD | .| .| .| .|
 

Note: these probabilities are for tests of factor main effects, not
 

interactions with speed.
 

Final M6.SPD.002 99 June 2001 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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 EMIT NORMAL - CLEAN TIER 0 CLASS
 

| | THC | NMHC | CO | NOX |
 

|----------------------------+-------+-------+-------+-------|
 

|ROAD |FACTOR | | | | |
 

|-------------+--------------| | | | |
 

|ART/FWY |ROADTYPE | 0.0001| 0.0000| 0.0405| 0.0000|
 

| |--------------+-------+-------+-------+-------|
 

| |VEH_TYPE | 0.0000| 0.0186| 0.0000| 0.0000|
 

| |--------------+-------+-------+-------+-------|
 

| |STANDARD | 0.0000| 0.0000| 0.0000| 0.0000|
 

|-------------+--------------+-------+-------+-------+-------|
 

|LOCAL |VEH_TYPE | 0.0572| 0.4049| 0.1660| 0.0184|
 

| |--------------+-------+-------+-------+-------|
 

| |STANDARD | 0.0000| 0.0000| 0.0000| 0.0028|
 

|-------------+--------------+-------+-------+-------+-------|
 

|RAMP |VEH_TYPE | 0.1570| 0.5501| 0.0201| 0.0009|
 

| |--------------+-------+-------+-------+-------|
 

| |STANDARD | 0.0003| 0.0007| 0.0002| 0.0000|
 

EMIT NORMAL - ACTUAL TIER CLASS
 

| | THC | NMHC | CO | NOX |
 

|----------------------------+-------+-------+-------+-------|
 

|ROAD |FACTOR | | | | |
 

|-------------+--------------| | | | |
 

|ART/FWY |ROADTYPE | 0.0001| 0.0000| 0.0405| 0.0000|
 

| |--------------+-------+-------+-------+-------|
 

| |VEH_TYPE | 0.0000| 0.0686| 0.0001| 0.0000|
 

| |--------------+-------+-------+-------+-------|
 

| |STANDARD | 0.0000| 0.0000| 0.0000| 0.0000|
 

|-------------+--------------+-------+-------+-------+-------|
 

|LOCAL |VEH_TYPE | 0.0830| 0.5008| 0.4038| 0.0124|
 

| |--------------+-------+-------+-------+-------|
 

| |STANDARD | 0.0002| 0.0001| 0.0000| 0.0024|
 

|-------------+--------------+-------+-------+-------+-------|
 

|RAMP |VEH_TYPE | 0.2922| 0.7707| 0.0443| 0.0018|
 

| |--------------+-------+-------+-------+-------|
 

| |STANDARD | 0.0013| 0.0002| 0.0001| 0.0010|
 

EMIT HIGH
 

| | THC | NMHC | CO | NOX |
 

|----------------------------+-------+-------+-------+-------|
 

|ROAD |FACTOR | | | | |
 

|-------------+--------------| | | | |
 

|ART/FWY |ROADTYPE | 0.9736| 0.9570| 0.0151| 0.0201|
 

| |--------------+-------+-------+-------+-------|
 

| |VEH_TYPE | 0.0667| 0.0873| 0.0004| 0.1444|
 

| |--------------+-------+-------+-------+-------|
 

| |STANDARD | .| .| .| .|
 

|-------------+--------------+-------+-------+-------+-------|
 

|LOCAL |VEH_TYPE | 0.8787| 0.8821| 0.5511| 0.6093|
 

| |--------------+-------+-------+-------+-------|
 

| |STANDARD | .| .| .| .|
 

|-------------+--------------+-------+-------+-------+-------|
 

|RAMP |VEH_TYPE | 0.3701| 0.4075| 0.1471| 0.6942|
 

| |--------------+-------+-------+-------+-------|
 

| |STANDARD | .| .| .| .|
 

GLM P-VALUES FOR MODELS WITH NO SPEED INTERACTIONS (FROM FACVEHA.SAS)
 

Final M6.SPD.002 100 June 2001
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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EMIT NORMAL - CLEAN TIER 0 CLASS
 

| | P |
 

| |-------------------------------|
 

| | THC | NMHC | CO | NOX |
 

| |-------+-------+-------+-------|
 

| | PROB | PROB | PROB | PROB |
 

|----------------------------+-------+-------+-------+-------|
 

|ROAD |FACTOR | | | | |
 

|-------------+--------------| | | | |
 

|ART/FWY |S*ROADTYPE | 0.0354| 0.0440| 0.0020| 0.0000|
 

| |--------------+-------+-------+-------+-------|
 

| |S*VEH_TYPE | 0.1322| 0.1476| 0.8361| 0.5608|
 

| |--------------+-------+-------+-------+-------|
 

| |S*STANDARD | 0.0002| 0.0001| 0.0576| 0.6491|
 

EMIT HIGH - CLEAN TIER 0 CLASS
 

| | P |
 

| |-------------------------------|
 

| | THC | NMHC | CO | NOX |
 

| |-------+-------+-------+-------|
 

| | PROB | PROB | PROB | PROB |
 

|----------------------------+-------+-------+-------+-------|
 

|ROAD |FACTOR | | | | |
 

|-------------+--------------| | | | |
 

|ART/FWY |S*ROADTYPE | 0.1176| 0.1203| 0.6233| 0.0000|
 

| |--------------+-------+-------+-------+-------|
 

| |S*VEH_TYPE | 0.0641| 0.0699| 0.0241| 0.9560|
 

| |--------------+-------+-------+-------+-------|
 

| |S*STANDARD | .| .| .| .|
 

EMIT NORMAL - CLEAN ACTUAL TIER CLASS
 

| | P |
 

| |-------------------------------|
 

| | THC | NMHC | CO | NOX |
 

| |-------+-------+-------+-------|
 

| | PROB | PROB | PROB | PROB |
 

|----------------------------+-------+-------+-------+-------|
 

|ROAD |FACTOR | | | | |
 

|-------------+--------------| | | | |
 

|ART/FWY |S*ROADTYPE | 0.0354| 0.0440| 0.0020| 0.0000|
 

| |--------------+-------+-------+-------+-------|
 

| |S*VEH_TYPE | 0.1754| 0.1802| 0.8680| 0.5723|
 

| |--------------+-------+-------+-------+-------|
 

| |S*STANDARD | 0.0024| 0.0020| 0.0560| 0.0151|
 

EMIT HIGH - CLEAN ACTUAL TIER CLASS
 

| | P |
 

| |-------------------------------|
 

| | THC | NMHC | CO | NOX |
 

| |-------+-------+-------+-------|
 

| | PROB | PROB | PROB | PROB |
 

|----------------------------+-------+-------+-------+-------|
 

|ROAD |FACTOR | | | | |
 

|-------------+--------------| | | | |
 

|ART/FWY |S*ROADTYPE | 0.1176| 0.1203| 0.6233| 0.0000|
 

| |--------------+-------+-------+-------+-------|
 

| |S*VEH_TYPE | 0.0641| 0.0699| 0.0241| 0.9560|
 

| |--------------+-------+-------+-------+-------|
 

| |S*STANDARD | .| .| .| .|
 

GLM P-VALUES FOR MODELS WITH NO SPEED INTERACTIONS (FROM FACVEHA.SAS)
 

Final M6.SPD.002 101 June 2001 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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EMIT NORMAL - CLEAN TIER 0 CLASS
 

| | P |
 

| |-------------------------------|
 

| | THC | NMHC | CO | NOX |
 

| |-------+-------+-------+-------|
 

| | PROB | PROB | PROB | PROB |
 

|----------------------------+-------+-------+-------+-------|
 

|ROAD |FACTOR | | | | |
 

|-------------+--------------| | | | |
 

|ART/FWY |ROADTYPE | 0.0046| 0.0050| 0.0006| 0.0000|
 

| |--------------+-------+-------+-------+-------|
 

| |VEH_TYPE | 0.0004| 0.0243| 0.0062| 0.0026|
 

| |--------------+-------+-------+-------+-------|
 

| |STANDARD | 0.0000| 0.0000| 0.0000| 0.0000|
 

EMIT HIGH - CLEAN TIER 0 CLASS
 

| | P |
 

| |-------------------------------|
 

| | THC | NMHC | CO | NOX |
 

| |-------+-------+-------+-------|
 

| | PROB | PROB | PROB | PROB |
 

|----------------------------+-------+-------+-------+-------|
 

|ROAD |FACTOR | | | | |
 

|-------------+--------------| | | | |
 

|ART/FWY |ROADTYPE | 0.1236| 0.1307| 0.3307| 0.0000|
 

| |--------------+-------+-------+-------+-------|
 

| |VEH_TYPE | 0.5942| 0.5693| 0.8984| 0.3961|
 

| |--------------+-------+-------+-------+-------|
 

| |STANDARD | .| .| .| .|
 

EMIT NORMAL - CLEAN ACTUAL TIER CLASS
 

| | P |
 

| |-------------------------------|
 

| | THC | NMHC | CO | NOX |
 

| |-------+-------+-------+-------|
 

| | PROB | PROB | PROB | PROB |
 

|----------------------------+-------+-------+-------+-------|
 

|ROAD |FACTOR | | | | |
 

|-------------+--------------| | | | |
 

|ART/FWY |ROADTYPE | 0.0046| 0.0050| 0.0006| 0.0000|
 

| |--------------+-------+-------+-------+-------|
 

| |VEH_TYPE | 0.0016| 0.0404| 0.0031| 0.0012|
 

| |--------------+-------+-------+-------+-------|
 

| |STANDARD | 0.0000| 0.0000| 0.0000| 0.0000|
 

EMIT HIGH - CLEAN ACTUAL TIER CLASS
 

| | P |
 

| |-------------------------------|
 

| | THC | NMHC | CO | NOX |
 

| |-------+-------+-------+-------|
 

| | PROB | PROB | PROB | PROB |
 

|----------------------------+-------+-------+-------+-------|
 

|ROAD |FACTOR | | | | |
 

|-------------+--------------| | | | |
 

|ART/FWY |ROADTYPE | 0.1236| 0.1307| 0.3307| 0.0000|
 

| |--------------+-------+-------+-------+-------|
 

| |VEH_TYPE | 0.5942| 0.5693| 0.8984| 0.3961|
 

| |--------------+-------+-------+-------+-------|
 

| |STANDARD | .| .| .| .|
 

GLM P-VALUES FOR MODELS WITH NO SPEED INTERACTIONS (FROM FACVEHA.SAS)
 

Final M6.SPD.002 102 June 2001 
Regression statistics for CO Off-Cycle Emissions Analysis (Normal emitters) 

Variables Entered/Removed(a,b) 

Model Variables 

Entered 

Variables 

Removed 

Method 

1 LA4COSQR . Stepwise (Criteria: Probability-of-F-to-enter <= .050, Probability-of-F-to-remove >= .100). 

2 LA4CO . Stepwise (Criteria: Probability-of-F-to-enter <= .050, Probability-of-F-to-remove >= .100). 

a Dependent Variable: CO_DELT 

b Linear Regression through the Origin 

Model Summary 

Model R R Square(a) Adjusted R Square Std. Error of the 

Estimate 

1 .678(b) .459 .450 3.0755 

2 .889(c) .791 .784 1.9279 

a For regression through the origin (the no-intercept model), R Square measures the proportion of the variability in the dependent variable 

about the origin explained by regression. This CANNOT be compared to R Square for models which include an intercept. 

b Predictors: LA4COSQR 

c Predictors: LA4COSQR, LA4CO 

ANOVA(d,e) 

Model Sum of Squares df Mean Square F Sig. 

1 Regression 497.694 1 497.694 52.618 .000(a) 

Residual 586.440 62 9.459 

Total 1084.134(b) 63 

2 Regression 857.399 2 428.700 115.336 .000(c) 

Residual 226.735 61 3.717 

Total 1084.134(b) 63 

a Predictors: LA4COSQR 

b This total sum of squares is not corrected for the constant because the constant is zero for regression through the origin. 

c Predictors: LA4COSQR, LA4CO 

d Dependent Variable: CO_DELT 

e Linear Regression through the Origin 

Coefficients(a,b) 

Unstandardized Coefficients Standardized Coefficients t Sig. 95% Confidence Interval for B 

Model B Std. Error Beta Lower Bound Upper Bound 

1 LA4COSQR -3.277E-02 .005 -.678 -7.254 .000 -.042 -.024 

2 LA4COSQR -7.638E-02 .005 -1.579 -14.520 .000 -.087 -.066 

LA4CO .984 .100 1.070 9.837 .000 .784 1.184 

a Dependent Variable: CO_DELT 

b Linear Regression through the Origin 

Final M6.SPD.002 103 June 2001 
Regression statistics for CO Off-Cycle Emissions Analysis (Normal emitters) 

Excluded Variables(c,d) 

Beta In t Sig. Partial Correlation Collinearity Statistics 

Model Tolerance 

1 LA4CO 1.070(a) 9.837 .000 .783 .290 

FINJ .500(a) 6.731 .000 .653 .923 

VTYP .416(a) 5.120 .000 .548 .939 

MODEL_YR .470(a) 6.206 .000 .622 .946 

2 FINJ .064(b) .638 .526 .082 .341 

VTYP -.035(b) -.397 .693 -.051 .442 

MODEL_YR .037(b) .395 .694 .051 .388 

a Predictors in the Model: LA4COSQR 

b Predictors in the Model: LA4COSQR, LA4CO 

c Dependent Variable: CO_DELT 

d Linear Regression through the Origin 

Regression statistics for CO Off-Cycle Emissions Analysis (High Emitters) 

Case Processing Summary 

Cases 

Valid Missing Total 

HIGHCO N Percent N Percent N Percent 

CO_DELT Normal 63 100.0% 0 .0% 63 100.0% 

High 22 100.0% 0 .0% 22 100.0% 

LA4CO Normal 63 100.0% 0 .0% 63 100.0% 

High 22 100.0% 0 .0% 22 100.0% 

Final M6.SPD.002 104 June 2001 
Regression statistics for CO Off-Cycle Emissions Analysis (High Emitters) 

Descriptives 

HIGHCO Statistic Std. Error 

CO_DELT Normal Mean 1.1968 .5044 

95% Confidence Interval for Mean Lower Bound .1884 

Upper Bound 2.2051 

5% Trimmed Mean 1.3587 

Median 1.0782 

Variance 16.031 

Std. Deviation 4.0038 

Minimum -25.29 

Maximum 12.42 

Range 37.71 

Interquartile Range 2.1735 

Skewness -4.346 .302 

Kurtosis 32.170 .595 

High Mean -1.9790 7.2988 

95% Confidence Interval for Mean Lower Bound -17.1576 

Upper Bound 13.1996 

5% Trimmed Mean 1.7699 

Median 5.0273 

Variance 1171.982 

Std. Deviation 34.2342 

Minimum -128.76 

Maximum 51.06 

Range 179.82 

Interquartile Range 24.5018 

Skewness -2.481 .491 

Kurtosis 9.106 .953 

LA4CO Normal Mean 2.73210603 .45566035 

95% Confidence Interval for Mean Lower Bound 1.82125397 

Upper Bound 3.64295809 

5% Trimmed Mean 2.25774861 

Median 1.98924000 

Variance 13.080 

Std. Deviation 3.61669191 

Minimum .019160 

Maximum 25.774990 

Range 25.755830 

Interquartile Range 2.76831000 

Skewness 4.438 .302 

Kurtosis 26.534 .595 

High Mean 57.94719000 13.56327504 

95% Confidence Interval for Mean Lower Bound 29.74081545 

Upper Bound 86.15356455 

5% Trimmed Mean 51.19508025 

Median 38.69987500 

Variance 4047.173 

Std. Deviation 63.61739899 

Minimum 1.729990 

Maximum 239.809000 

Range 238.079010 

Interquartile Range 73.66766000 

Skewness 1.631 .491 

Kurtosis 2.391 .953 

Final M6.SPD.002 105 June 2001 
Regression statistics for HC Off-Cycle Emissions Analysis 

Variables Entered/Removed(b,c) 

Model Variables Entered Variables Removed Method 

1 LA4HCSQR, LA4HC(a) . Enter 

a All requested variables entered. 

b Dependent Variable: THC_DELT 

c Linear Regression through the Origin 

Model Summary 

Model R R Square(a) Adjusted R Square Std. Error of the 

Estimate 

1 .255(b) .065 .043 1.1960 

a For regression through the origin (the no-intercept model), R Square measures the proportion of the variability in the dependent variable 

about the origin explained by regression. This CANNOT be compared to R Square for models which include an intercept. 

b Predictors: LA4HCSQR, LA4HC 

ANOVA(c,d) 

Model Sum of Squares df Mean Square F Sig. 

1 Regression 8.268 2 4.134 2.890 .061(a) 

Residual 118.715 83 1.430 

Total 126.982(b) 85 

a Predictors: LA4HCSQR, LA4HC 

b This total sum of squares is not corrected for the constant because the constant is zero for regression through the origin. 

c Dependent Variable: THC_DELT 

d Linear Regression through the Origin 

Coefficients(a,b) 

Unstandardized Coefficients Standardized Coefficients t Sig. 95% Confidence Interval for B 

Model B Std. Error Beta Lower Bound Upper Bound 

1 LA4HC .305 .134 .571 2.283 .025 .039 .570 

LA4HCSQR -2.492E-02 .014 -.437 -1.748 .084 -.053 .003 

a Dependent Variable: THC_DELT 

b Linear Regression through the Origin 

Final M6.SPD.002 106 June 2001 
Regression statistics for NOx Off-Cycle Emissions Analysis 

Variables Entered/Removed(b,c) 

Model Variables Entered Variables Removed Method 

1 LA4NOSQR, LA4NOX(a) . Enter 

a All requested variables entered. 

b Dependent Variable: NOX_DELT 

c Linear Regression through the Origin 

Model Summary 

Model R R Square(a) Adjusted R Square Std. Error of the Estimate 

1 .615(b) .378 .363 .3521 

a For regression through the origin (the no-intercept model), R Square measures the proportion of the variability in the dependent variable 

about the origin explained by regression. This CANNOT be compared to R Square for models which include an intercept. 

b Predictors: LA4NOSQR, LA4NOX 

ANOVA(c,d) 

Model Sum of Squares df Mean Square F Sig. 

1 Regression 6.253 2 3.126 25.219 .000(a) 

Residual 10.289 83 .124 

Total 16.542(b) 85 

a Predictors: LA4NOSQR, LA4NOX 

b This total sum of squares is not corrected for the constant because the constant is zero for regression through the origin. 

c Dependent Variable: NOX_DELT 

d Linear Regression through the Origin 

Coefficients(a,b) 

Unstandardized Coefficients Standardized 

Coefficients 

t Sig. 95% Confidence Interval for B 

Model B Std. Error Beta Lower Bound Upper Bound 

1 LA4NOX .332 .066 1.107 4.998 .000 .200 .464 

LA4NOSQR -4.745E-02 .018 -.582 -2.627 .010 -.083 -.012 

a Dependent Variable: NOX_DELT 

b Linear Regression through the Origin 

Final M6.SPD.002 107 June 2001 
Appendix B : Example 

Example Application of Speed Adjustment to Exhaust Emissions 

The following description is meant as an example of how the basic exhaust emission rates 

estimated by MOBILE6 will be adjusted for the effects of average speed and roadway type. The 

example will show how the various parts of the overall emission estimate are weighted together. 

It is beyond the scope of this document to explain fully the derivation of the basic exhaust 

emission estimates or the weighting factors. The derivation of these distributions are described 

in other documents. It is also not the intent of this example to reveal the values for emissions or 

weighting factors that are used in MOBILE6. All of the values shown in this example should, 

therefore, be considered as draft and may not match values shown in other documents. This 

should not detract from the value of this example in showing the process of how the basic 

emission rates are adjusted for speed. 

Basic Emission Rates 

For each scenario, MOBILE6 will calculate a basic exhaust emission rate (BER) for two 

emission levels (high and normal) for each pollutant for each model year for each vehicle class. 

The basic unit for the BER is the hot running LA4 (with an average speed of 19.6 mph) at 

standard operating conditions (i.e., temperature, humidity, etc.). The effect of engine starts on 

emissions is calculated separately and is not adjusted for the effects of average speed. 

MOBILE6 calculates the emissions for each hour of the day, so the first step is to adjust 

the BER for the conditions that affect exhaust emissions. For example, the temperature at 6 a.m. 

will be different than the temperature at 1 p.m., so the BER at 6 a.m. will not be the same as the 

BER at 1 p.m. after adjustment for temperature. Some adjustments (such as the effects of fuel 

sulfur content) will not vary by time of day. Ultimately, there will be 24 values, one for each 

hour of the day calculated from the same BER, adjusted for hourly conditions. There will be two 

sets of adjusted BER values, one for normal emissions and one for high emitters. 

Example Basic Emission Rates

 For this example, we will follow the calculation of NOx emissions from a 1990 model 

year passenger car. The calculation would be similar for the other pollutants and other vehicle 

classes. This example will not fabricate values for all hours. The calculations will be similar in 

all hours, so a single hour example is all that should be required. So, for a given hour, the NOx 

emissions (BERs) for our vehicles will be assumed to be: 

� 0.65 g/mi for normal emitters 

� 2.10 g/mi for high emitters 

Final M6.SPD.002 108 June 2001 
After adjustment, these values must be weighted together by their occurrence in the fleet. 

The number of high emitters will depend on many things (i.e., age, I/M programs, OBD, etc.), 

but for our example, we will assume that high emitters are 10% of 1990 model year passenger 

cars in this scenario. 

Freeway Ramps and Local Roadways 

There are four basic roadway types; freeways, arterial/collectors, freeway ramps and local 

roadways. The freeway ramps and local roadways can be determined directly from the BER, 

since they do not vary with average speed. The freeway ramp and local roadway emissions are a 

function of the BER (see Table 13). The NOx BERs we will use (described above) are in grams 

per mile units and must be converted to grams per hour. The average speed of the hot running 

LA4 is 19.6 miles per hour. For normal emitters, 0.65 grams per mile times 19.6 miles per hour 

is 12.74 grams per hour. For high emitters, 2.10 grams per mile times 19.6 miles per hour is 

41.16 grams per hour. Using the equation shown in Table 13, the freeway ramp and local 

roadway emissions in grams per hour are: 

Normal Ramp = 5.353 + 2.863*(12.74) - 0.0101*(12.74)2 = 40.19 g/hr 

Normal Local = 1.870 + 0.701*(12.74) + 0.000609*(12.74)2 = 10.90 g/hr 

High Ramp = 5.353 + 2.863*(41.16) - 0.0101*(41.16)2 = 106.08 g/hr 

High Local = 1.870 + 0.701*(41.16) + 0.000609*(41.16)2 = 31.75 g/hr 

The results will be weighted using VMT and must be converted to grams per mile units. 

The freeway ramp cycle has an average speed of 34.6 miles per hour and the local roadway cycle 

has an average speed of 12.9 miles per hour. 

Normal Ramp = (40.19 g/hr) / 34.6 mph = 1.16 g/mi
 

Normal Local = (10.90 g/hr) / 12.9 mph = 0.84 g/mi
 

High Ramp = (106.08 g/hr) / 34.6 mph = 3.07 g/mi
 

High Local = (31.75 g/hr) / 12.9 mph = 2.46 g/mi
 

Since we have assumed that 10% of the vehicles are high emitters, we can now weight the 

normal and high emitter results to give a complete freeway ramp and local roadway estimate for 

the 1990 model year in this hour. 

Freeway Ramp = 1.16* 0.90 + 3.07 * 0.10 = 1.35 g/mi
 

Local Roadway = 0.84 * 0.90 + 2.46 * 0.10 = 1.01 g/mi
 

Each hour will have its own basic exhaust emission rate. Since the Freeway Ramp and 

Local Roadway emission levels depend on the basic exhaust emission rate, a separate calculation 

will be done for each hour of the day. 

Final M6.SPD.002 109 June 2001 
Emission Offset 

The emission offset (EO) represents the difference between the LA4-based BER and 

freeway emissions at 19.6 miles per hour. The values for the EO are shown in Table 14. Since 

the BER values lie between the LA4 values (0.591 and 3.245 g/mi) shown in Table 14, the EO 

must be calculated using interpolation. 

Normal EO = 0.121 + ((0.008-0.121)/(3.245-0.591))*(0.65-0.591) = 0.12 g/mi 

High EO = 0.121 + ((0.008-0.121)/(3.245-0.591))*(2.10-0.591) = 0.06 g/mi 

An additional emission offset is used for arterial/collector roadways, however this offset 

depends on average speed and emissions. These are shown in Table 15. The ratio of the freeway 

emission level at each speed plus the arterial/collector offset for that speed, divided by the 

freeway emission level at 19.6 miles per hour is the arterial/collector speed correction factor. 

These are shown in Table 17. 

Freeway Emissions 

Freeway emissions depend on average speed. For each hour of the day, MOBILE6 has a 

default distribution of average speeds for freeways. Users will be able to enter local distributions 

of freeway average speeds. This is not the same as a distribution of speeds on a particular 

freeway. 

The MOBILE6 default distribution of average speeds for freeways assumes that there are 

many freeways in the area and the distribution represents the average speeds observed from the 

different freeways at that hour. The cycles used to develop the speed correction factors each 

contain the entire range of vehicle speeds on freeways grouped by ranges of observed congestion. 

So, changing speed in the MOBILE6 model is changing the average speed of the combination of 

all vehicles on freeways. MOBILE6 does not effectively model the effect of average speed on 

individual vehicles or small groups of vehicles within a single freeway section. If you wish to 

model a specific freeway, you would want to reduce the default distribution down to a single, 

average speed for the freeway of interest. 

In each hour, MOBILE6 will calculate values for each average speed “bin” from 5 to 65 

mph in 5 mph increments and for 2.5 mph (14 speed bins) by applying the speed correction 

factors from Table 16 to the base freeway emission level at 19.6 mph. The base freeway 

emission level is simply the sum of the BER and the adjusted emission offset (EO). 

Normal Base Freeway Emission at 19.6 mph = 0.65 + 0.12 = 0.77 g/mi
 

High Base Freeway Emission at 19.6 mph = 2.10 + 0.06 = 2.16 g/mi
 

There are three sets of speed correction factors in Table 16, one for each of three emission 

levels. Both the Normal and High base freeway emission levels we have calculated lie between 

Final M6.SPD.002 110 June 2001 
the Level 2 and Level 3 emission levels, shown in Table 16. So the speed correction factor will 

be interpolated between the values for Level 2 and Level 3 in Table 16. However, these speed 

correction factors do not apply below 7.1 mph. MOBILE6 will use the MOBILE5 speed 

correction factors (See Table 1.6B in AP-42) for speeds below 7.1 mph. For our example, the 

NOx speed correction factors for the 1990 model year have A and B coefficients of 1.456 and 

0.926 respectively, where the form of the equation is A/speed + B, resulting in the following 

speed correction factors: 

SCF for 2.5 mph = (1.456/2.5) + 0.926 = 1.51
 

SCF for 5.0 mph = (1.456/5.0) + 0.926 = 1.22
 

SCF for 7.1 mph = (1.456/7.1) + 0.926 = 1.13
 

The MOBILE5 speed correction factor at 7.1 mph (1.13) was applied to all emission 

levels in MOBILE5. The MOBILE5 speed correction factors will be adjusted to match the speed 

correction factors in Table 16 for NOx at 7.1 mph of 2.26, 1.81 and 1.50 for emission levels 1, 2 

and 3 respectively by adding the difference to each value. 

Level 1 SCF for 2.5 mph = 1.51 + (2.26 - 1.13) = 2.63 


Level 1 SCF for 5.0 mph = 1.22 + (2.26 - 1.13) = 2.34
 

Level 2 SCF for 2.5 mph = 1.51 + (1.81 - 1.13) = 2.19 


Level 2 SCF for 5.0 mph = 1.22 + (1.81 - 1.13) = 1.90
 

Level 3 SCF for 2.5 mph = 1.51 + (1.50 - 1.13) = 1.87 


Level 3 SCF for 5.0 mph = 1.22 + (1.50 - 1.13) = 1.58
 

Using the average emissions for each speed correction factor emission level (from Table 

14) of 0.712 and 3.253 g/mi NOx for Level 2 and Level 3 respectively and the predicted base 

freeway emission rates of 0.77 and 2.16 g/mi for Normals and High categories, weighting factors 

can be derived for interpolating between the speed correction factors. The sum of the two 

weighting factors will equal 1. 

Normal Level 2 Weighting = (3.253 - 0.77)/(3.253 - 0.712) = 0.978
 

Normal Level 3 Weighting = (1.0 - 0.978) = 0.022
 

High Level 2 Weighting = (3.253 - 2.16)/(3.253 - 0.712) = 0.431
 

High Level 3 Weighting = (1.0 - 0.431) = 0.569
 

These weighting factors are used to combine the Level 2 and Level 3 speed correction 

factors for the calculated base freeway emission case. A new weighted speed correction factor is 

calculated for each of the fourteen speed bins for Normals and Highs. For example, the 10 mph 

speed bin speed correction factors (using values from Table 16) would be: 

Final M6.SPD.002 111 June 2001 
Normal SCF for 10 mph = 0.978 * 1.28 + 0.022 * 1.18 = 1.28
 

High SCF for 10 mph = 0.431 * 1.28 + 0.569 * 1.18 = 1.22
 

These speed correction factors are applied to the predicted base freeway emission rates to 

determine speed corrected emission rates for each speed bin. For example the speed corrected 

emission rates for the 10 mph speed bin would be: 

Normal emission level for 10 mph = 1.28 * 0.77 = 0.99 g/mi
 

High emission level for 10 mph = 1.22 * 2.16 = 2.64 g/mi
 

Each hour has a default VMT distribution of average freeway speeds that correspond to 

these speed bins. The emission rates for each of the bins can be weighted, using this VMT 

distribution, to give a composite freeway emission rate. This weighting is repeated for normal 

and high emitters, and the two emitter groups can be combined to give an overall freeway NOx 

emission rate for 1990 model year vehicles for that hour of the day. 

Arterial/Collector Emissions 

The arterial/collector speed correction factors shown in Table 17 are applied to the base 

freeway emission rate calculated for the freeway emission levels. Since the three emission level 

groups are identical for arterial/collector roadways and freeways, the same weighting factors are 

used to interpolate between the speed correction factors. For example, the 10 mph speed bin 

speed correction factors (using values from Table 17) would be: 

Normal SCF for 10 mph = 0.978 * 1.52 + 0.022 * 1.31 = 1.52
 

High SCF for 10 mph = 0.431 * 1.52 + 0.569 * 1.31 = 1.40
 

These speed correction factors are applied to the base freeway emission levels to 

determine emission levels for each speed bin. For example the emission levels for the 10 mph 

speed bin would be: 

Normal emission level for 10 mph = 1.52 * 0.77 = 1.17 g/mi
 

High emission level for 10 mph = 1.40 * 2.16 = 3.02 g/mi
 

Since the speed correction factors for arterial/collectors (shown in Table 17) converge 

with freeway speed correction factors (shown in Table 16) at higher speeds and below 7.1 mph, 

the emission rate for arterial/collectors and freeways will be the same for some speed bins. All of 

the speed bins are combined, weighted by the fraction of VMT in that speed bin for that hour. 

The composite arterial/collector emissions for Normals and Highs are combined weighted by 

their proportions in the fleet for that model year. 

Final M6.SPD.002 112 June 2001 
Area-wide Emissions 

Once a fleetwide (combined Normal and High), hourly (combined speed bins) estimate is 

available for each roadway type (freeway, arterial/collector, freeway ramp and local roadway), 

these estimates can be combined in a variety of ways, depending on the needs of the user. If an 

area-wide, hourly result is needed, the results for the four roadway types can be combined, 

weighted by the fraction of VMT for each roadway for that hour. An area-wide daily result can 

be obtained by combining the hourly results weighted by the VMT fraction for each hour. 

Although there are default values for the fraction of VMT for each roadway and the VMT 

fraction for each hour, users may substitute their own values. 

Composite Engine Start and Running Emissions 

The emission rates addressed in this document do not contain the effects of engine starts. 

The effect of engine start on emissions is calculated separately and is calculated in units of grams 

per engine start. These emission effects resulting from engine starts are not determined by 

roadway type and do not depend on average trip speed. They can, however, be combined with 

the running emissions to give an overall exhaust emission estimate. 

Since the MOBILE6 model does not include a distribution of the effects of engine start on 

emissions by roadway type, the combination of the effects of engine start and running emissions 

is best done on area-wide (combined roadway) emission results. This can be done on an hourly 

or daily basis. 

MOBILE6 has an estimate of the average daily vehicle miles traveled (VMT) for each 

model year in a given calendar year and a distribution of that average VMT over the day by hour. 

MOBILE6 also has an estimate for the number of engine starts per day and the distribution of 

those starts over the day by hour. For a given hour, the grams due to engine starts in that hour are 

calculated as: 

Grams / Engine Start * Fraction of Starts in the Hour * Number of Starts / Day 

This value can be converted to grams per mile by determination of the average number of 

miles traveled by vehicles in that hour: 

Hourly VMT = Daily VMT * Fraction of VMT in the Hour 

Once the effect of engine start on emissions is converted to grams per mile, it can be 

added directly to the area-wide emission estimate for that hour. 

Total Exhaust = Engine Start / Hourly VMT + Area-wide Emissions for the Hour 

Final M6.SPD.002 113 June 2001 
Similarly, a daily total exhaust emission rate can be calculated. Although there are 

default values for the number of daily engine starts, the fraction of engine start in each hour, the 

daily VMT and the fraction of VMT in each hour, users may substitute their own values. 

A calculation is done for each model year of each vehicle class. These values are 

weighted using travel fractions (as is done in MOBILE5) to calculate area-wide, daily emission 

rates for highway mobile sources. 

FTP Emissions 

The Federal Test Procedure (FTP) is a special case of vehicle driving. It can be simulated 

in MOBILE6 by careful choice of weighting factors for engine start soak time, vehicle miles 

traveled and roadway types. Since this case will be of special interest for comparison of 

MOBILE6 emission rates to Federal certification standards, we plan to build in the appropriate 

weighting factors so that calculation of FTP emission estimates using MOBILE6 can be done 

simply and consistently. 

Final M6.SPD.002 114 June 2001 
Appendix C : Response to Comments 

Comment numbers refer to EPA indexing of comments received for easy reference. All 

EPA responses are shown in italics. 

Lance Freeman, October 12, 1999: 

I think there may be a fallacy, started by misinterpreting previous speed curves, that lower 

speeds are correlated to higher emissions. But I'm guessing that those speed curves were heavily 

weighted with emissions from the start mode. 

All of the speed correction driving cycles were done *without* engine starts, so engine 

starts are not a factor in the effect of low average speeds on emissions. However, since 

the speed correction factors are applied to emission levels in grams per mile, the 

corrections are very large for low speeds. This makes sense, since at low speeds you get 

very few miles (the denominator) for each gram of emissions generated. For example, at 

idle (average speed=0) the speed correction factor is infinite. So, at low speeds it often 

makes more sense to examine the emissions in terms of grams per unit of time (usually 

grams per hour). In those units, the effect of lower speeds on emissions is much different. 

EPA uses units of grams per mile for travel in MOBILE6, since we consider the miles 

traveled as the appropriate unit of work (i.e., purpose of travel) as opposed to travel as a 

way to spend your time. Mathematically, however, they should be equivalent. 

Sam Long, IL EPA (Comment #9) March 13, 1997: 

Under “Transportation Models" section, the paragraph is not clear. It should be made 

clearer that 35 mph on a local street or collector (or even some arterials) would be a good speed, 

but would be slow and represent very congested conditions on a freeway. (I presume this is what 

was meant.) 

Some additional text was added to clarify this issue. 

HPMS facility types do not include specifically include on-and off-ramps, but quite often 

metropolitan planning organizations (MPOs) list [some] on-and off-ramps on their network. 

Data of this sort may or may not be readily available. 

Guidance will be available to help areas determine appropriate inputs for MOBILE6. 

Default values will be available for issues such as the fraction of freeway VMT that 

occurs on freeway ramps. 

What is a "micro trip"? (One one thousandth of a mile is 5ft!) 

Final M6.SPD.002 115 June 2001 
A “micro trip” is any portion of a trip between the time the engine is started and the 

engine is shut down which begins and ends with a period of idling. One example would 

be the driving from one signal to the next. Separating driving into micro trips allows an 

unambiguous dividing of long trips into smaller parts that can be used in cycle 

development. More information about micro trips are in the report M6.SPD.001 listed in 

the references. 

What is meant by “Average Speed per %VMT” or indeed %VMT? In as much as areawide estimates (of emissions) are what emissions inventories and emission reduction strategies 

are all about, I suggest that much effort go into [non-attainment] area-wide estimates. Similarly 

for statewide inventories, which are needed for some circumstances. 

Each roadway link has a distance (in miles) and an average speed (in miles per hour). 

Average speed is the length of the link (distance) divided by the time (in hours) it takes for 

vehicles to drive from one end of the link to the other. If a set of average speed bins are 

created (i.e., every 5 mph) and the link distances are put into the bins depending on the 

average speed, this will create a distribution of miles traveled (VMT) by average speed. 

“Signal density"? What's that? The number of traffic signals in a given area? If that's the 

case, I imagine each transportation model zone would have a different signal density. What about 

stop signs? Are they traffic signals within the meaning of the act, or are we just talking about 

traffic lights? Four-way stops are different from one- or two-way stops. How and where are 

users to obtain such data? The MPOs presumably; but not all NAAs are completely covered by a 

transportation network. Even where a comprehensive network exists, why, there are thousands 

of zones in the Chicago area, for example. 

EPA had originally discussed ways to account for the number of traffic signals on 

roadways, but such plans were dropped from the final version of the model. Signal 

density would allow users to better account for roadways with similar average speeds, 

but with different driving behavior. 

William Benjey, HPCC EPA (Comment #10) March 19, 1997: 

Moving to facility-type output with short-term (hourly instead of daily?) mobile emission 

factor outputs for specific road types would in a sense be more consistent with hourly time scale 

of most episodic air quality modeling. However, because the VMT data needed to use the 

emission factors for specific road segments usually does not exist outside of a few urban areas, it 

will be difficult to apply the Mobile 6 emission factors on a regional basis. Consequently think 

that your efforts to provide a weighted running emission factor for all roadway types in addition 

to the hourly facility-based factor information is crucial. 

Users who do not have specific vehicle activity data will still be able to run MOBILE6 

using the national average default values. Guidance will be needed to specify the local 

Final M6.SPD.002 116 June 2001 
 

data that must be provided for specific modeling situations. 

Given that the input and output file formats are likely to change appreciably, it would a 

very significant help to regional modelers if the input and output data could be tagged with 

geographic identifier information. In other words, since the input options affecting the emission 

factors vary geographically, the output files vary geographically. Ideally, the mobile model could 

be set to generate a set of geographically-specific emission factors for a region defined by the 

user. Currently ,it is tedious and resource-intensive to sequentially run the mobile model 

separately for all the different areas included in a regional air quality model run and then in turn 

perform sequential air quality model runs or manually tag many mobile output files for different 

geographic areas before a air quality model run. If the Mobile 6 input and output files were 

tagged (or at least had the option of allowing the user to easily tag them) with geographic 

identifiers, we could combine the output files and read them by identifier. Areas with only 

county-level VMT data available would be identified with state and county-level FIPS codes and 

would use the weighted average running emission factors. Areas with road link specific VMT 

data would be identified by state and county FIPS codes plus latitude and longitude data for the 

road link nodes (end points) and could use the facility-type emission factors. 

MOBILE6 has an option for “database” output, where the emission values are written to 

an ASCII file formatted for importing to database software. Since the output includes run 

and scenario numbers, the database software can be used to easily “tag” the emission 

results for linking with geographic information. 

Harold Brazil, SEMCOG, MI (Comment #16) April 4, 1997: 

Is this "short time period emission factors" for a one hour period or peak 

hour period? Would this be used for Photochemical Modeling purposes? 

MOBILE6 will only provide information as hourly or daily, with all hours aggregated. 

The hourly results can be aggregated by the user into other useful time periods, such as 

peak hours, for use in photochemical modeling. 

Celia Shih, NY DEP (Comment #17) April 7, 1997: 

Were there any new data collected under various speed cycles since MOBILE5? Will 

there be any update on the “regular” speed correction factors in MOBILE6? 

This report represents the only new data collection since MOBILE5 specifically to 

address speed correction factors. New driving cycles were developed from the new data 

and these new driving cycles were used to develop the speed correction factors used in 

MOBILE6. 

John Walsh, EPA #2, NY (Comment #18) April 3, 1997: 

Final M6.SPD.002 117 June 2001 
How many facility types are there? Should there be a switch between facility-specific 

emissions and more general area-specific emissions? 

MOBILE6 will always calculate emissions for four facility types, but will automatically 

aggregate the results for the descriptive output. These results are also available in the 

database output using the AGGREGATED OUTPUT command. Facility specific 

emission rates are only available using the database output. 

Sam Long, Illinois EPA (Comment #21) April 10, 1997: 

The necessary [non-default] inputs may not be available to all users. Also, daily emission 

rates will still be needed, and by no means everyone has link-based or hourly information. Linkbased information is not very adaptable to forecasting ROP or conformity. If you come up with 

typical speeds for various facility types (at various levels of service), will these speeds be 

published and be acceptable as MOBILE inputs for inventory and other purposes? 

Although MOBILE6 will have national average speed distribution estimates, this is likely 

one area where EPA guidance may require that local information be used, since driving 

behavior has a significant effect on emissions and overall driving behavior (speed) 

distributions will vary from area to area because of different roadway types available. 

If link-based speeds (free-flow or congested) are available, it is possible to estimate an 

average or representative speed for each functional class on the network. I did so in the ‘90 

inventory, rounding off to the nearest 5 mph, and used the results in off-network areas. However, 

the arithmetic average speed will differ from the average speed weighted by link-length, and both 

will differ from the median and modes of the speeds. You should specify which of these speeds 

is to be used as representative, and how they are to be calculated, if you want users to derive 

them from link-based data. 

Guidance on how to calculate average speed VMT distributions for MOBILE6 will be 

needed. Briefly, each roadway link has a distance (in miles) and an average speed (in 

miles per hour). Average speed is the length of the link (distance) divided by the time (in 

hours) it takes for vehicles to drive from one end of the link to the other. If a set of 

average speed bins are created (i.e., every 5 mph) and the link distances are put into the 

bins depending on the average speed, this will create a distribution of miles traveled 

(VMT) by average speed. 

What facility types do you have in mind? The HPMS facility types loom large in USEPA 

and FHWA planning, but those twelve types do not include such things as ramps and bridges. 

On the other hand, some transportation model networks do have ramps and bridges as facility 

types, but those and the other facility types in such networks may not—often do not—match the 

HPMS facility types. Do you have suggestions for equating various non-HPMS functional 

classes to HPMS classes, apart from the methods appearing in Sections 2 and 3 of publication 

Final M6.SPD.002 118 June 2001 
MD? 

The need to distinguish between roadway types will be a new feature of MOBILE6. 

However, there are only four categories of roadway types in MOBILE6. Guidance will 

be needed to assist users in determining which of these four roadway types should be 

used to model each particular roadway. 

Congestion-level weighting factors: In-use level-of-service data are not, in my 

experience, easy to come by. “Congested” and “free” speeds in transportation model outputs 

from CATS represent two different levels of service, of course, but offhand I don’t remember 

just which ones they are; I don’t think they were specified to me. I looked at some 1990 trafficby-hour data from IDOT for several continuous-traffic-count stations in Illinois, and estimated 

that about 75% of VMT in the Chicago area occurs under more or less congested conditions, and 

25% under free-flow conditions, and weighted total emissions accordingly, using the modeled 

“congested” and “free” speeds as MOBILE inputs. My proportion above may be somewhat of an 

overestimate; it may be closer to 60% congested/40% free, or even down to 50/50; but the 

congested-free proportion, as long as it’s within reasonable limits, doesn’t affect the final 

emission estimates all that much, as I noted in our ‘90 inventory document. 

MOBILE6 will use average speed as a surrogate for roadway congestion. The driving 

cycles were developed by grouping trips by level of congestion, but the emission results 

are grouped by average speed. Lower speeds will correlate to higher congestion and 

higher speeds to more free flow. There will be no need to specify the congestion levels 

for roadways in MOBILE6. 

The numbers in the speed-correction table (Table 1) in the Workshop handout, especially 

average and maximum speeds, look reasonable and plausible. 

Marion R. Poole, DOT, NC (Comment #25) April 16, 1997: 

Facility specific drive cycles are perhaps the most significant of the proposed 

improvements to the MOBILE Model. North Carolina approves of the move in this direction. 

The current model uses an average drive cycle to represent all possible driving conditions. This 

leads to counterintuitive results in some cases. However, we have some concerns based on the 

amount of aggregation and disaggregation in the supporting materials. 

Is the variability of stop/delay time implicit in the drive cycle that will be used to develop 

the basic emissions rates for each facility type? Our experience is that stop/delay time varies 

across facility types. We believe that any future version of the MOBILE model should account 

for this variation. An alternative method would be to allow the user to specify stop/delay time 

for each facility type. 

Final M6.SPD.002 119 June 2001 
In MOBILE6, the amount of stop/delay is implicit in the average speed. Average speed is 

defined as the distance traveled (in miles) divided by the time (in hours). Stop/delay 

would increase the amount of time, without changing the distance traveled, and decrease 

the average speed. The stop/delay involved in each driving cycle is fixed, but when a 

specific average speed is input to MOBILE6, an implicit amount of stop/delay will be 

assumed based on the driving cycle at that speed. More detailed analysis of specific 

roadways will likely require new emission modeling approaches that do not depend on 

fixed driving cycles. 

We also note that arterials and collectors will share a driving trace. As noted above our 

experience indicates the existence of significant differences in stop/delay time and start mode 

between facility types. Collectors resemble locals streets more than arterial streets. 

It was not possible, using the available data, to make a finer distinction between roadway 

types for MOBILE6. As discussed above, differences in stop/delay time are accounted for 

in the average speed input. Although collectors may resemble local streets in terms of 

stop/delay, there are important differences in the maximum speed and congestion levels 

that, for purposes of emission modeling, make them more like arterials. 

The proposed freeway drive cycles also provided some surprises. The proposed drive 

cycles include: High Speed, LOS A-C, LOS D, LOS F, and LOS G. We recommend that the 

High speed drive cycle and the LOS A drive cycle be combined, and that the drive cycle for LOS 

B-C be kept together. Our understanding of the Highway Capacity Manual indicates that high 

speed driving occurs under LOS A. We also propose that LOS F and LOS G be combined. To 

the best of our knowledge, the Highway Capacity Manual does not recognize a LOS G. From the 

associated driving trace, this drive cycle represents breakdown conditions and might best be 

consolidated into the drive cycle for LOS F. 

MOBILE6 will not use congestion levels as the method to associate driving with emission 

levels. Instead, average speed will be used. The driving cycles were designed to give the 

widest range of average speeds, adding a high speed cycle and a LOS G category. 

Average speed will be used as a surrogate for congestion levels. 

Gary Flispart, Jefferson Cty, KY (Comment #26) April 25, 1997: 

Many of the proposed changes suggest a movement away from the coarse focus of SIP 

inventory modeling and toward the fine focus of transportation simulation. Accurately 

approximating real-world behavior and associated emissions has clearly been the long-term goal 

of both transportation evaluators and air quality regulators. The key difference, of course, has 

been in the relative time focus: short-term (hour by hour) versus long-term (daily or annual 

average). Traffic planners deal in peaks and valleys throughout a day, while the SIP focuses on 

an annual inventory based on a typical summer day (for VOC). Both in the sharing of traffic-­

related data and in mutual needs to comply with mandated SIP conformity, the relationship 

Final M6.SPD.002 120 June 2001 
between transportation users and SIP users of MOBILE models is critical. MOBILE6 

developments impact both the traffic-related data which must be gathered to prepare a SIP and 

the eventual build-no-build evaluation of highway projects. It is essential that MOBILE6 not 

support one type of user at the expense of the other, because the two are interdependent. 

Since SIP inventories are currently based on daily average emissions, any change which 

disfavors such daily estimates has profound effect on inventories and targets. 

The new subclasses of facility type could either be ignored, force-fitted to existing 

categories, or adopted by APCDJC. Because KDOT does not currently measure traffic for all the 

proposed categories, if they were adopted the HPMS data gathering process would need to be 

altered or supplemented, which could involve anywhere from a week's analysis of data from 

other sources to a complete restructuring of transportation measurement in the area. 

Coordination with KIPDA and KDOT would be essential. 

Comment: SIP inventories are currently performed using daily averages and are 

reasonably calculable when handled that way. In the District's experience, the people who used 

MOBILE to compile SIP inventories and evaluate SIP strategies were not the same people who 

compiled the link or trip models. The District is concerned that by shifting the emphasis toward 

detailed transportation modeling, the primary efforts of SIP modeling may be undercut. Trying 

to produce an annual inventory by summation of all trips or links in a simulation would add 

tremendous complexity which APCDJC sees as unwarranted. The District strongly suggests the 

need for MOBILE6 and other future models to continue to produce daily average emission 

factors in a manner similar to that in MOBILE5, to support SIPs and tracking. 

The need for daily average emissions was recognized by the MOBILE6 team. MOBILE6 

will continue to support daily average emission results in both the descriptive and 

database output options. This will not completely eliminate the need for areas to produce 

more detailed vehicle activity data, disaggregated by time of day, vehicle type and 

roadway. Guidance will be needed to assist areas to determine what new data is needed 

and generate the needed information. 

Harold Nudelman, NYCDEP, NY (Comment #27) April 28, 1997: 

Have the new facility-specific cycles been reviewed by DOT/FHWA personnel? We are 

especially concerned about in-City roadways (arterials/collectors and local) where there are speed 

limits that may only allow 30-35mph. The maximum and average speeds for the bottom 3 cycles 

on Table 1, for congested in-City arterials and local roads, may be too high for many congested 

New York City streets during peak hours. New York City is likely to have a traffic control sign 

and signal density which is at the extreme end of the range in the nation. Frequency of starts and 

stops, and therefore of acceleration/deceleration, will not only affect average speeds but also the 

emissions associated with a given speed. We support any efforts by EPA to develop operating 

mode data that would allow us to project the impact on emissions of a high density of traffic 

Final M6.SPD.002 121 June 2001 
 

signals on local streets as well as on arterials. Will speed corrections for arterials/collectors also 

utilize data from the NYCC and FTP cycles? Will the speeds on local streets be adjusted? If 

yes, what cycles will be used other than the NYCC? 

The data available for MOBILE6 development did not allow for creation of new driving 

cycles and data for extreme low speeds. However, each vehicle was tested using the New 

York City Cycle to allow modeling of average speeds to that level (7.1 mph) and to allow 

connection to the existing data from driving cycles below 7.1 mph. The speed correction 

factors from these older driving cycles will be used in MOBILE6 for speeds below 7.1 

mph. 

Extreme conditions will always be difficult to model without data gathered to specifically 

address those conditions. The driving cycle for local roadways has only a single average 

speed, so changes in average speed on local roadways cannot be modeled. Guidance 

will be needed to indicate the best methods to deal with specific situations where using 

the default values would not be appropriate. 

How will idle CO emissions be calculated? Will they be calculated from the 2.5 mph 

emissions estimates? If yes, will the 2.5 mph emissions for local streets be the same as the 2.5 

mph emissions for arterial/collectors? If they are not the same, how will they be calculated? 

How different can we expect the low speed correction factors to be in the new model compared 

to those used in MOBILE 5? Is there any reason why idle emissions data is not directly collected 

to use in the model instead of adjusting the 2.5 mph emissions? 

No new analysis of idling emissions has been performed since the release of MOBILE5b. 

In MOBILE5b, idling emissions are calculated from the emission estimates for 2.5 mph, 

as described in the MOBILE5 User Information Sheet #2. MOBILE6 will not explicitly 

estimate idling emissions at all. However, idling emissions will still be calculated using 

the method described in the MOBILE5 User Information Sheet #2. The speed correction 

factor (and thus the emission estimate) for emissions at 2.5 mph will be the same for both 

roadway types in MOBILE6 (freeway and arterial/collectors), since the speed correction 

factor curves converge at extreme low (and high) speeds. 

Collecting data for and analysis of idling emission data has not been a high priority for 

EPA. Programs to develop idling emission factors have been proposed repeatedly, but 

pushed aside by higher priority issues. An independently funded research project 

specifically targeted at developing idling emission factors may be needed. 

Dale Aspy, EPA #4, GA (Comment #30) April 30, 1997: 

A number of Region 4 states have requested the ability to model idle emissions for 

project level analyses. Many of these same states have also requested the ability to conduct 

facility specific modeling on an hourly basis to allow for peak use times. The Region supports 

Final M6.SPD.002 122 June 2001 
the inclusion of non-FTP emission factors and the option of user supplied information regarding 

non-FTP speed and acceleration activity factors. 

Idling emissions were also discussed in the previous comment (#27). MOBILE6 will not 

explicitly generate idling emission rates. However, idling emissions may still be 

calculated using the method described in the MOBILE5 User Information Sheet #2. 

Idling emissions were left out of MOBILE6 since idling is a specific mode. Modal 

emission rates (i.e., acceleration, deceleration, cruise and idling) were considered 

outside the scope of the MOBILE6 project. Existing guidance (i.e., MOBILE5 User 

Information Sheet #2) was considered sufficient for estimating idling emissions. 

MOBILE6 does model emissions by hour and allows for user supplied speed VMT 

distributions. MOBILE6 does not allow for adjustment of the amount of off-cycle driving 

behavior, which is implicit in the driving cycles used to develop the speed correction 

factors. 

Michael Keenan, NYSDEC (Comment #31) April 30, 1997: 

Refocusing the Mobile model to the premise that most driving is non-FTP should prove 

to be a most worthwhile development. 

The attached tables contain the minimum and maximum average roadway type speeds 

presently available for SIP modeling in New York State. The values shown are the estimates for 

calendar year 1999. Comparison with EPA’s New Facility-Specific Speed Correction Cycles 

(i.e., Table 1 at March 1997 Workshop) indicates that the proposed Freeway Average Speeds of 

13.1 to 63.2 mph would encompass New York’s input range of 19.7 to 59.6 for Interstates, 

Freeways and Expressways. However, for the various roadway types encompassing Arterials and 

Collectors, New York’s speed range of 7.2 to 55.9 mph is much broader than EPA’s average 

speed range of 11.6 to 24.8 mph. A large variance also exists within New York’s Local average 

speed range of 3.0 to 39.2 mph. Using a single local cycle with an average value of 12.9 mph 

would appear to be most inappropriate for modeling such a variable speed range. Because the 

range of possible average speeds for any given roadway type varies significantly, speed should 

continue to be an input variable to the Mobile model. 

However, by modifying the nomenclatures, the new facility specific cycles would prove 

useful in better defining which speed correction factors should be applied. For instance, although 

Freeways are limited access highways, the driving cycle traces may be applicable to certain rural 

roadways as well. For example, the High Speed, Level of Service (LOS) A-C and LOS D 

Freeway cycles appear to be suitable for any road that has unimpeded, nonstop free flow. 

Freeway LOS E and perhaps even LOS F could be of use for modeling speed corrections on 

roads which have a quick stop at a stop sign or slowing down to make a turn. Perhaps 

differentiating roadways among nonstop, brief stops and many stops would be a more useful 

approach for identifying which speed correction algorithm to use. This is perhaps what was 

Final M6.SPD.002 123 June 2001 
meant by “signal density” in Issue #3. 

The speed correction factors for freeways and arterial/collector roadways in MOBILE6 

converge at low and high speeds. In this way, any speed from 2.5 mph to 65 mph can be 

modeled on both freeways and arterial/collector roadways. Guidance will be needed to 

assist users in choosing the appropriate roadway type in MOBILE6 for the specific road 

to be modeled.

 Issue #1 points out that the “disaggregation . . . by facility-type” is most appropriate for 

short time periods. Shorter time periods generally have less variability of speed, temperature, 

vehicle mix, etc. Further, four-step transportation models are now being developed for short 

time frames (i.e., peak travel times). In addition, from the modeling perspective, combining 

variables complicates input development. Thus, the Mobile model input at the scenario level 

should reflect input appropriate to a discrete roadway type for a time period short enough to 

minimize large differences in any input variable over that time period. 

MOBILE6 allows for different VMT by facility type and vehicle type for each hour of the 

day. However, guidance will be needed to choose the appropriate level of aggregation 

for development of MOBILE6 inputs for specific emission inventory analysis. 

“Weighted running emission factors” and inputting %VMT by roadway type (ala Issue 

#2's methodology) would complicate using the Mobile model and jeopardize input integrity. 

While this concept may sound attractive and efficient, the model already suffers enough 

uncertainty without introducing more. With today’s desktop computers, multiple scenario runs 

can be performed quite rapidly. Ample software and/or software packages are available for 

preprocessing and postprocessing (e.g., G/mi times VMT). Therefore, the Mobile model does 

not have to become its own postprocessor! 

As was noted in other comments, daily average emissions continues to be a highly desired 

output of the MOBILE model. As a result, MOBILE6 must be capable of producing 

emission results for a given day that aggregates all hours, roadways and vehicle types. 

However, it will be possible, with appropriate input commands, to get results specific to a 

less aggregate scenario, such as for an individual roadway. 

Shengxin Jin, NY DOT (Comment #36) May 6,1997: 

Average vehicle speed is another important issue in CO intersection dispersion modeling. 

Vehicle speeds differ from intersection to intersection. Even at the same intersection, vehicle 

speeds can vary depending on the directions of traveling vehicles. Without a vehicle speed 

option as a model input, the differences in vehicle emissions due to speeds can not be 

determined. This will significantly affect CO dispersion modeling results. 

Average speed will still be a user input for the MOBILE6 model. However, the 

Final M6.SPD.002 124 June 2001 
complexity of the input will be increased due to the need for speed VMT distributions. 

Marcel Halberstadt, AAMA, MI (Comment #37) June 5,1997: 

The EPA approach is somewhat different than the ARB's approach, in which a single, 

self-weighted inventory cycle was developed (the LA92, or Unified Cycle (UC)) and a significant 

number of cars and trucks were tested on this cycle. Also, ARB developed Unified Correction 

Cycles for developing speed correction factors for the UC. AAMA is unsure if EPA can devote 

enough resources to make their approach more accurate than ARB. Concern stems from EPA's 

desire to make one model fit all modeling purposes. The Unified Cycle approach is certainly 

more simple, and has the advantage that only a single, self-weighted cycle needs to be run for 

area-wide modeling. EPA's approach requires significantly more testing per vehicle, 

consequently, fewer vehicles can be tested. There is also an issue with respect to whether 

vehicles can be maintained at proper temperatures throughout the duration of the EPA cycle 

testing. AAMA recommends that EPA also have all of the vehicles tested on ARB's Unified 

Cycle as well as the other cycles, so the Unified Cycle can be compared to a weighted average of 

EPA's cycles. AAMA will reserve further comments on both ARB's approach and EPA's 

approach until it evaluates the data from EPA's test program, and particularly how EPA compares 

the data on the Unified Cycle to the data from the EPA's test cycles. If EPA's approach of many 

factor-specific correction cycles remains unchanged for MOBILE6, it is essential that the model 

contain default (nationwide) statistics to develop average emission rates for a nationwide 

inventory. 

EPA understands and accepts the advantages of the California approach to emission 

modeling. However, the EPA approach meets the important requirement that emission 

estimates on smaller scales (i.e., individual roadways) be as accurate as possible. 

California knows that transportation planners will use their model to estimate emissions 

for individual roadways, despite the fact that this is not appropriate, because there is no 

reasonable alternative. The EPA approach is more appropriate for modeling individual 

roadways, which can then be aggregated to create area wide daily emission estimates. 

EPA agrees that the current EPA approach will require significantly more testing per 

vehicle and will result in fewer vehicle tests. However, EPA is confident that 

improvements in instrumented vehicle technology will allow for the use of emission 

testing results from in-use vehicles on roadways to create emission estimates for future 

models. In this way, MOBILE6 is a transition model which can be used to improve our 

understanding of how emission inventories can be improved using a better designed 

emission model. 

EPA must also allow users to output emissions based solely on current FTP certification 

test results, for ready comparison with the current and historical emission standards. 

MOBILE6 is designed to estimate “real world” driving emissions and cannot easily 

Final M6.SPD.002 125 June 2001 
replicate the exhaust emission certification procedure (FTP). Doing so would require 

elimination of “real world” driving behavior effects on emissions and altering the default 

vehicle activity distributions. This will be possible using diagnostic commands, but is not 

an expected typical use of the model. 

Marcel Halberstadt, AAMA (Comment #53) December 4, 1997: 

EPA is proposing to use data currently being developed from the testing of in-use 

vehicles over a variety of driving cycles. This testing has been performed at ATL and EPA. Data 

collected at the two different sites shows remarkably different sensitivity of emissions to average 

speed. The ATL data generally showed lower emissions, and a lower emissions sensitivity to the 

different test cycles. EPA indicated that because of the differences, it would run a correlation 

program to try to determine the reason for the differences, but also indicated that EPA may base 

the speed effects for current vehicles in MOBILE6 on the EPA data alone because the ATL data 

“may be underloaded.” 

AAMA supports EPA’s efforts to conduct a correlation program. AAMA believes the 

differences between the ATL and EPA data must be thoroughly understood before EPA makes 

significant decisions about which data to base the speed effects on. EPA did not indicate why it 

thought the ATL data may be “underloaded”. Another possible explanation, which was not 

addressed at the workshop, is that the EPA data may be in error (or “overloaded”). If the reasons 

for the differences are not thoroughly understood, EPA should combine the data, but not omit the 

ATL data without very good reason. 

EPA thoroughly investigated the differences between the results at the two testing sites 

(including testing the same vehicle at both sites) and resolved that the differences are not 

due to errors or differences in the testing procedures at the two sites. EPA has concluded 

that the differences observed are vehicle to vehicle variance and all test results at both 

sites have been used in the analysis. 

Another issue relates to how EPA plans to use the freeway ramp driving cycle. AAMA 

understands that EPA intends to develop national weighting factors for different types of 

roadway operation, and allow users to input these fractions as well. The model would then 

weight the emissions from the different cycles together. It is not clear, however, whether EPA 

will also have speed correction factors, which will adjust emissions between the speeds of the 

different cycles. If EPA plans to do this, then it should develop such speed correction factors 

from the new data, but omit the data from the freeway ramp cycle. This cycle appears to result in 

emissions that do not lie on the typical emissions/speed curve (see Figures 1a-1c of the above 

report). 

MOBILE6 separates driving into four roadways types, with freeway ramps as it’s own 

roadway, separate from other freeway driving. However, since there is only one ramp 

driving cycle, ramp emissions will not be a function of average speed. 

Final M6.SPD.002 126 June 2001 
 

 

Facility-type Speed Correction Factors – It is still not clear to AAMA how the facilitytype speed correction factors (SCFs) are being developed. Is EPA developing separate SCFs by 

facility types, or a single SCF curve across the entire speed range? If SCFs are being developed 

for different facility types, then how will EPA divide the facility types and levels of service? 

How will high emitters be handled? Will the SCFs for low and high emitters be estimated 

separately, and then combined by the estimated fraction of low and high emitters? 

As this final report should make clear, MOBILE6 divides driving into different facility 

types with a speed correction curve for freeways and arterial collectors. Levels of 

service are not used directly. Instead, average speed is used as a surrogate for the 

congestion level on roadways. Speed correction factors for high emitting vehicles were 

determined separately from normal emitting vehicles. 

Effect of SFTP Standards for Tier 1s and LEV-Type Vehicles – EPA is proposing to 

include the effects of off-cycle aggressive driving through the use of the facility-specific speed 

correction factors. Thus, the SCFs will include the effect of speed as well as off-cycle effects. 

How does EPA plan to incorporate the effects of the SFTP rules on Tier 1 and LEV vehicles, 

using the facility cycle data on Tier 0 vehicles? 

The development of the speed correction factors included an emissions offset which 

attempts to capture the difference between the base exhaust emission factor, based on the 

FTP driving cycle (LA4), and truly representative driving, which includes aggressive 

driving behavior. A full discussion of the emission offset is in Section 6.0. This emission 

offset is the portion of the overall adjustment to the base emission rate that will be 

affected by the SFTP. The effects of the SFTP on emissions are discussed in the report, 

“Determination of Off-Cycle Emissions and Supplemental FTP Control Modeling in 

MOBILE6,” (M6.SPD.005). 

EPA estimated the benefits of SFTP rules in its support document to its supplemental 

FTP final rule. However, in that analysis, EPA estimated emissions over ST01, REM01 and 

REP05 from testing over the FTP and US06, along with some Tier 0 vehicle data. This 

methodology contains a number of assumptions which have not been confirmed with data. 

Therefore, AAMA does not recommend that EPA use this methodology in MOBILE6 without a 

thorough review of it appropriateness. 

Likewise, how does EPA plan to estimate these factors for LEVs with and without nonFTP controls? ARB assumed that the impact of non-FTP driving on LEV emissions was the 

same in relative terms as for Tier 1 vehicles in EMFAC7G. In its supporting analyses for its 

proposed non-FTP standards, ARB also estimated the impact of non-FTP driving on LEV 

emissions both with and without SFTP controls. However, as was the case above, this 

methodology involves many unconfirmed assumptions. Also, the technology assumed by ARB to 

enable compliance with the non-FTP standards (i.e., rich-bias) is not likely to be the technology 

of choice for most manufacturers. Therefore, AAMA again recommends that EPA publish the 

Final M6.SPD.002 127 June 2001 
details of any methodology which it plans to use to estimate LEV emission impacts for public 

comment prior to its incorporation into MOBILE6. 

The report, “Determination of Off-Cycle Emissions and Supplemental FTP Control 

Modeling in MOBILE6,” (M6.SPD.005) describes how MOBILE6 handles off-cycle 

emissions and the effects of the SFTP. It should be of some comfort to know that off-cycle 

emissions and the effects of the SFTP are added to the base exhaust emission rates. This 

means that only the small increment of remaining off-cycle effects left after the 

effectiveness of the SFTP has been applied is added to the base emissions of vehicles 

affected by the SFTP. This should mitigate the effects of uncertainty in the estimate of 

what off-cycle emissions might be for LEVs. The true effectiveness of the SFTP cannot be 

known until vehicles certified under the new certification procedures can be tested. 

Gary McVoy, Ph.D., Director, Environmental Analysis Bureau, New York State 

Department of Transportation (Comment #86) August 2, 1999: 

Vehicle speeds on local roads are much different from project to project and from area to 

area. For example, the local speed and driving pattern in New York City are much different from 

those in the NY upstate cities. No speed adjustment for the local roadways affects our ability to 

perform accurate and publicly defensible air quality analysis. 

The limited data available on the driving behavior and their emission impacts on local 

roadways make it impossible to accurately determine the effects of average speeds on 

local roadways. However, it may be possible, with proper guidance, to account for the 

differences in the average speeds on local roadways, using MOBILE6, in a manner 

consistent with EPA policy. This issue will be addressed in guidance from EPA. 

Gerry Kelpin, New York City Department of Environmental Protection (Comment 

#93) October 5, 1999: 

We would like to raise a number of concerns with some of the assumptions proposed for 

the model. The areas of our concern are as follows: 

1)	 The use of the Mobile5 low speed relation to estimate CO emissions for speeds below 7.1 

mph, and the subsequent use of the estimated 2.5 mph emissions for estimating CO idle 

emissions. 

OMS views the Mobile Model as essentially a tool for developing emissions inventories. 

However, the use of the model for providing link by link carbon monoxide emissions to be used 

as input for intersection air quality modeling to determine compliance with the NAAQS has also 

been an important function of the model. We believe that the proposed assumptions for adjusting 

the extremely low speed emissions and using the resultant 2.5 mph emissions to estimate the idle 

emissions overestimates CO emissions for these conditions and will result in overestimated 

Final M6.SPD.002 128	 June 2001 
modeled intersection impacts. If the Mobile6 CO emissions are not sufficiently lower than the 

Mobile5 emissions then this could even result in erroneous determinations of non-compliance. 

In order to explain our concern about the Mobile Model assumptions for low speeds and 

idle, and their potential for generating incorrect results, we have to discuss how the emissions 

input for the CAL3QHC(R) air quality model, that EPA designated as the reference model for 

modeling CO at intersections in 1992, is generated. The CAL3QHC(R) model does not utilize 

average speed emissions. The CAL3QHC(R) model utilizes free flow, or running speed 

emissions, and idle emissions for each link. (In the air quality model, a link is usually the 

distance on a roadway between traffic signals, or other types of intersection controls.) The 

emissions on a given link are divided into idle emissions over the length of the queue for the 

vehicles stopped in the queue, and the moving emissions from all the vehicles passing through 

the link over the entire length of the link. The moving emissions for the CAL3QHC(R) model, 

therefore, should reflect the running speed (speed when vehicles are in motion) and not the 

average speed. 

The running speed for a link is calculated by subtracting the stopped delay time from the 

total travel time, and dividing that time into the link distance. The average speed includes the 

stopped delay time in the total travel time. Running speeds will therefore always be higher than 

the average speed on any link with a stopped delay. The running speed should contain no stopped 

delay, and therefore no idle emissions. When we use the Mobile Model emissions for a given 

speed that is equal to the running speed, we are using emissions for an average speed that 

includes some percentage of idle emissions. In general the amount of time that is spent in idle 

decreases with increasing average speed. If idle emissions are higher than the moving emissions, 

the greater the percentage of idle time in the average speed, the more the running or moving 

emissions will be overestimated. 

It must be noted that although CAL3QHC(R) may request that running emissions 

estimated from a free flow speed be used, this has never been the case. None of the 

versions of the MOBILE model has ever been able to produce free flow emission 

estimates. This is true no matter how the speed is calculated. EPA has allowed the use 

of the MOBILE model as an input to the CAL3QHC(R) model only because there is no 

credible alternative. In this respect, the MOBILE6 model in general will be no better, but 

no worse, than current practice. 

The truly appropriate model for use with CAL3QHC(R) is a modal model, which 

estimates emissions base on modes instead of trips. A properly developed modal model 

would be able to estimate free flow emission rates appropriate for input into models such 

as CAL3QHC(R). EPA is currently working with researchers in California and Georgia 

to develop such modeling tools. 

The impact from the potential overestimation of moving CO emissions, however, is not 

believed to be as significant as the impact from overestimating the idle emissions. The impact of 

Final M6.SPD.002 129 June 2001 
idle emissions has generally been responsible for the major portion of the modeled local impact 

at intersections that have been near the standard. This is related to the CAL3QHC model 

assumption that all the cars in a queue on a link will idle for the entire red phase of the light 

cycle. This means idle emissions from the entire queue on a link is modeled for a percentage of 

the hour that is proportional to the red time divided by the total cycle time. 

Given the major contribution of idle emissions to local CO predicted impacts, we do not 

agree with the proposal to use the relationships between the 2.5 mph emissions and those at 7.1 

mph from Mobile5 in Mobile6, and then use the 2.5 mph emissions to calculate idle emissions. 

When this methodology for calculating idle emissions was adopted for Mobile5, it was 

recognized that it should be replaced. This is indicated by the statement on page 1-8 of the May 

1994 User's Guide to Mobile5 - "EPA will continue to collect data and to work to develop a more 

satisfactory approach to estimating idle emission factors." We believe that a more satisfactory 

method is needed because as we understand it, the speed relationship for the low speeds is based 

primarily on data from older technology, primarily carburetor, vehicles, and has not been 

demonstrated to be appropriate for the current and future fuel injected vehicles. The relationships 

that were included in Mobile5 for that speed range go back to Mobile4.1. The current and future 

fuel injected vehicles, with air/fuel ratios controlled by computer chips, should be much more 

efficient than the carburetor vehicles at controlling emissions at idle. Therefore, the relationship 

of emissions at these low speeds, and the idle emissions themselves for the newer vehicles 

should be different from what would be estimated utilizing the relationships developed for the 

early technology vehicles. 

Given the importance of the idle emissions to local CO impact prediction, we would 

recommend that CO idle emissions for current and future conditions be estimated based on actual 

measurements of idle. Is it possible to extract measured idle emissions data from the data 

generated in "grams second by second" for the vehicle cycles that were tested and described in 

the report ? If this is possible, we would recommend using relatively continuous periods of idle 

conditions (over 10 seconds) rather than shorter periods to measure the idle emissions so that 

they will be based on conditions that are similar to how they are modeled in the CAL3QHC 

model. Other sources of idle emissions may also be available (I/M programs, certification tests, 

etc.). 

No new analysis of idling emissions has been performed since the release of MOBILE5b. 

In MOBILE5b, idling emissions are calculated from the emission estimates for 2.5 mph, 

as described in the MOBILE5 User Information Sheet #2. MOBILE6 will not explicitly 

estimate idling emissions at all. However, idling emissions will still be calculated using 

the method described in the MOBILE5 User Information Sheet #2. The speed correction 

factor (and thus the emission estimate) for emissions at 2.5 mph will be the same for both 

roadway types in MOBILE6 (freeway and arterial/collectors), since the speed correction 

factor curves converge at extreme low (and high) speeds. 

Collecting data for and analysis of idling emission data has not been a high priority for 

Final M6.SPD.002 130 June 2001 
EPA. Programs to develop idling emission factors have been proposed repeatedly, but 

pushed aside by higher priority issues. An independently funded research project 

specifically targeted at developing idling emission factors may be needed to properly 

resolve these issues. 

However, all investigations on the existing data to date have supported the assumption 

that emissions at 2.5 mph are similar to those during idle. There is no reason, based on 

data, to be overly concerned about the idle emission estimates. One clear advantage of 

basing idling emission on the emissions at 2.5 mph is that is allows the idling emissions 

to be affected by all of the correction factors that are applied to running emissions, such 

as fuels and temperature. It will be very difficult to replicate these corrections 

specifically for idling emissions, even once base idle emission data becomes available. 

The issue of estimating running CO emissions between 7.1 mph and 2.5 mph, without 

using the old speed relationship from Mobile5, for intersection modeling must also be addressed. 

We do not believe that these running speeds will occur very often. For example the running 

speed for the low speed NYCC, whose average speed is 7.1 mph, is about 12 mph, after 

subtracting out the 40 % of the time in the cycle that the vehicle is in idle. We have not evaluated 

alternative solutions. However, one possible method that could be examined is to extrapolate 

the curves down to 2.5 mph from the 7.1 mph emissions measured in the new cycles. In addition, 

if new idle emissions data are available, it should be reasonable to use the idle emissions as an 

approximation of the emissions at an average speed of 2.5 mph. This should not introduce much 

error since an average speed of 2.5 mph will have a very high percentage of idle time. (The 7.1 

mph average speed cycle has 40 % of its time in idle.) A best fit curve utilizing this additional 

point, with the other points, could then be developed. 

In the future, having an idle test done as part of the certification process or as part of a 

mandated I/M program would seem to be a simple and inexpensive way of providing updated 

information for future revisions to the models' idle emissions. 

Although we have made our comments about the low speed adjustments with respect to 

CO, there should probably be an examination of whether the low speed relationships for the old 

technology vehicles is appropriate for estimating the emissions of HC and NOx from the new 

technology vehicles. Unless the applicability of the adjustments can be demonstrated, an 

approach similar to that mentioned above for CO might be worth evaluating. 

There is no particular advantage to using the New York City Cycle (NYCC) results from 

the new data set to estimate idling emissions in place of using the low speed (2.5 mph) 

cycle. Extrapolating low speed emission corrections from higher speed results is very 

difficult, since the low speed portion of the curve is quite steep. A very small error can 

produce large differences. Basing the low speed portion of the curve on data (whatever 

it’s minor flaws) is a better choice than extrapolation. 

Final M6.SPD.002 131 June 2001 
It is obvious that the only way to know what is happening with emissions at low speeds 

and idle will be to properly analyze the existing data and collect new data specifically to 

address these issues. There are new tools, such as the University of California modal 

model (NCHRP Project 25-11) which can directly address the effects of driving behavior 

on emissions at low speeds and idle and there is new data imbedded in any driving cycle 

containing idling and low speeds which has been collected on a second by second basis. 

However, much effort will be needed to review this information and propose a new set of 

low speed and idling emission rates. This effort is beyond the scope of the MOBILE6 

project and will have to be addressed as an update to the model. 

2) The adjustment of low speed emissions for aggressive driving. 

Since we do not think that the old speed adjustment factors should be utilized below 7.1 

mph for CO, the issue of adjusting the old adjustments for the aggressive driving in the new 

cycles becomes moot. We have reservations about correcting emissions for very low speeds, 

characteristic of severely congested conditions, for aggressive driving. One would think that 

under these type of conditions there would not be very much opportunity for this type of 

behavior. This would be even more true for idle emissions, if they were estimated from a 2.5 

mph emission. 

The proposed adjustment for CO at 7.1 mph and lower speeds for level 1 and level 2 

vehicles would result in a reduction of the old speed factors. This is because the new speed factor 

for 7.1 mph is lower than the old factor. Could this reflect the reduced contribution of the idle 

component to the total emissions in the NYCC for the vehicles recently tested as compared to the 

tests of earlier technology vehicles? 

The New York City Cycle (NYCC) is based on “real world” driving and includes 

aggressive driving behavior not found in the FTP. Since the FTP, which was the base 

emission rate in MOBILE5, did not include enough aggressive driving behavior, the 

speed adjustment in MOBILE5 from the base (FTP) to low speeds (NYCC) was large and 

the speed adjustment included some effects from aggressive driving. In MOBILE6, the 

speed correction factor is applied to a base emission rate after the effects of aggressive 

driving have been added as an emission offset. This may be the reason the speed 

correction is less moving from the base emission rate to the low speeds, since both now 

contain the effects of aggressive driving. 

Not much is really known about driving behavior at low speeds. The current 

instrumented vehicle data does not allow us to easily separate roadway types, so that a 

more thorough analysis of low speeds cannot be done. The chase car data, on which the 

MOBILE6 freeway and arterial/collector roadway cycles were based, did not follow 

vehicles onto local roadways, where most low speed driving occurs. New instrumented 

vehicle data will include global positioning sensing (GPS) technology, which will allow 

precise locating of the vehicle on the roadway system. 

Final M6.SPD.002 132 June 2001 
3)	 The assumption that freeway and arterial emissions converge and have the same 

emissions at, and below 7.1 mph. 

We agree that the emissions for all types of roadways will converge as the average speed 

approaches zero and the emissions become essentially idle. Given the different way arterials and 

freeways function, however, we are not certain that the assumption that their emissions converge 

at 7.1 mph and are the same below 7.1 mph is an accurate description of their behavior. 

Generally freeways, because of the lack of traffic signals that create stopped delay, should have 

the same running speeds and average speeds, while this is not the case at signalized arterials or 

collectors. Would a low average speed of 7.1 mph on a freeway be characterized by the same or a 

similar amount of idle time as the same speed on an arterial? It might be useful to compare how 

the percentage of idle time changes for freeways and arterials as their average speed cycles 

approach 7.1 mph (Freeways, LOS F to LOS G and arterials/collectors, LOS C-D to LOS E-F) . 

In addition, is the percentage of idle time in the lowest speed cycle (which had relatively close 

average speeds) for each type of roadway consistent with their both converging to the 40 % idle 

at 7.1 mph in the NYCC? If the above does not support the assumption that the emissions from 

both roadway types converge at 7.1 mph, then it may be necessary to modify this assumption. 

The lowest speed arterial/collector cycle has an average speed of 11.6 mph and 31.3% of 

the cycle time is at idle. The lowest speed freeway cycle has an average speed of 13.1 

mph and 3.3% of the cycle time is at idle. The New York City Cycle (NYCC) has an 

average speed of 7.1 mph and 32.4% of the cycle time is at idle. Table 11b shows the 

average CO emissions from vehicles on these cycles. The NYCC has higher CO 

emissions than the other two cycles in all cases. The arterial/collector cycle is higher 

than the freeway cycle in all cases. Based on this information, CO emissions will 

increase as average speed decreases and as the fraction of cycle time spent idling 

increases. 

Logically, EPA concluded that the speed correction factors for freeways and 

arterial/collector roadways must be identical when 100% of cycle time was spent at idle. 

However, based on the available information, it is not possible to determine precisely 

where the two speed curves statistically converge. The odd cycle of the three is clearly 

the freeway cycle, where very little of the driving time is at idle (3.3%). However, 

freeway driving at these very low speeds is not typical, in terms of the daily VMT on 

freeways. EPA concluded that it would be best to converge the speed correction curves 

at the NYCC where an actual data point existed. This assumption should only affect the 

limited amount of VMT that occurs on freeways at very low speeds. 

Why isn't the estimation of local roadway emissions variation with speed based on the 

relationships derived for arterials and collectors, since they would appear to be very similar to 

these roads in the way they operate? 

A detailed analysis of the emissions from the local driving cycle and the arterial/collector 

Final M6.SPD.002 133	 June 2001 
driving cycles has not been done. As you suggest, it is likely that use of the 

arterial/collector speed corrections may be appropriate for modeling local roadways as 

well. However, since local roads are not usually included in traffic demand models, 

MOBILE6 includes an overall local roadway emission estimate. The issue of whether 

local roadways can be modeled as arterial/collectors will be addressed in EPA guidance. 

Final M6.SPD.002 134 June 2001 
Appendix D : Peer Review of Speed Corrections 

Review of: Facility-Specific Speed Correction Factors, Draft 

US EPA Report Number M6.SPD.002 

By David J. Brzezinski, Phil Enns, and Constance J. Hart 

Assessment and Modeling Division 

Office of Mobile Sources, U.S. Environmental Protection Agency 

Reviewed by: Simon Washington, Transportation Systems Group, School of Civil & 

Environmental Engineering, Georgia Institute of Technology 

October 20, 1999 

NOTE: 

Most of the following comments have been addressed by making changes in the text of the 

report to clarify or add information. However, some comments are addressed below the 

comments. All EPA responses are shown in italics. 

General Review Comments: 

The comments below reflect three different types of comments. First are editorial comments that 

I believe would improve the read of the document, or would make for more precise interpretation 

of some of the statements made in the document. Second are short-term improvements, which I 

believe could be addressed in the immediate future to improve the development of driving cycles 

as proposed in MOBILE 6. The last section lists longer-term improvements, which could be 

considered after MOBILE 6 has been released. 

Overall the document is very thorough, well written, and concise. The authors have done an 

excellent job documenting a difficult project, and should be commended for their professional 

work. I would like to caveat all my comments by saying that they are intended merely to improve 

the document, and not in any way to offend any of the highly qualified and experienced authors 

who have prepared the document. The comments are my opinion only, and certainly can be over 

ridden by consensus of the authors or other reviewers. 

I have attached three asterisks (***) to those comments which I believe are the most 

pressing—that is those areas of concern that I believe raise some serious questions as to the 

validity of the currently proposed approach, and whose impact might be significant on the results 

and conclusions of this work. 

Editorial Comments: 

Page 1, 4th paragraph: The first sentence should probably read, “The proposed......basic 

emissions levels of the vehicles.” 

Page 1, 4th paragraph: The fact that ramps and local roadways cannot be adjusted for average 

Final M6.SPD.002 135 June 2001 
speeds other than the national average is a bit confusing. It suggests that the same average speed 

be assumed for all local roads, regardless of the city that is being modeled. If this is the case, then 

this is a problem when modelers may want to assess the effect of peak spreading (some TCM’s) 

or shrinking (some advanced ITS technologies), which would have an affect on local road traffic 

volumes and therefore speeds as well. This statement should be clarified. 

Page 2, 1st paragraph: The first line should read, “Since the data for this analysis were 

collected....”. The document should be searched for occurrences of the plural data to check verb 

agreement, as this occurs elsewhere as well (e.g. see page 16, paragraph 4). 

Page 2, 1st paragraph. The first sentence uses the word “realistic”, which I think should not be 

used. Any conceivable driving cycle obtained from real driving is realistic. The appropriate word 

to use might be “representative”, since what EPA is trying to do is bring into the fold a greater 

number of driving cycles that represent collectively a greater number of driving conditions. Even 

the “old” driving cycles are representative in and of themselves; however, there are fewer of 

them, so driving cycle heterogeneity is not being captured. I think it is worth keeping in mind 

(and perhaps in the text also) that there is a continuum of representation of real driving, ranging 

from one assumed driving cycle (and its assumed emissions profile) to simulation, which derives 

any speed-time profile of a fleet of vehicles given, roadway, traffic, and environmental 

conditions. Of course the latter begs for an emissions model that can handle any feasible driving 

cycle, which in fact can be accomplished by either UC Riverside’s or Georgia Tech’s Measure 

model. The point is that the continuum of driving activity is getting further disaggregated, and 

this is what MOBILE 6 is doing. 

Page 3, Background: Last sentence refers again to real world driving behavior, which implies an 

alternative to non-real world driving behavior (see previous comment). 

Page 4, 5th paragraph: Last sentence refers to the difficulty of differentiating vehicle activity 

across facilities. It might be worth emphasizing that this has particular consequences in the 

planning process, whereby plans or program that might impact modal activity cannot be modeled 

adequately. 

Page 5, paragraph 4: The second sentence should read, “Readers are encouraged to obtain 

information directly from California for comparison with the results documented in this report”. 

Page 6, paragraph 2: The last sentence is unclear, please clarify. 

Page 6, paragraph 3: EPA’s objective to match the power distribution is right on track, it is a 

strong point of the current driving cycle project update. 

Page 6, paragraph 3: I’m not sure that the authors want to use the word “We”, and instead might 

use “the US EPA”. See also page 20, third paragraph. The authors should probably search and 

replace entire document to be safe. 

Final M6.SPD.002 136 June 2001 
Page 7, paragraph 4: The second sentence should begin, “Testing of vehicles was done.....” 

Page 8, 5th full paragraph: The word “special” should be removed from the second sentence. 

Page 9, 3rd paragraph: I suggest changing the phrase in the third sentence “agrees with” to 

“provides support for”. 

Page 15, paragraph 2: The authors state, “All of the slope coefficients are statistically significant, 

meaning that the increase or decrease in emissions versus average speed is different than zero.” 

This is not technically correct. The correct interpretation of a hypothesis test is as follows: If 

repeated many times (i.e. many samples drawn from the population), the outcome (data) 

observed by the analyst/engineer and reflected in a computed test statistic (e.g. t-statistic, F-ratio, 

chi-square, etc.) would occur x percent of the time if the null hypothesis were true. In other 

words, the probability of occurrence is conditional upon the null hypothesis being true. If x is less 

then alpha, then the null hypothesis is rejected. When the null hypothesis is rejected, the 

statistical evidence suggests that the null hypothesis is not true, and that some alternative 

hypothesis provides a better account of the data. What is important to understand (and which is 

commonly misinterpreted), is that the result does not provide the probability of the null 

hypothesis being true, nor does it provide evidence that the particular alternative hypothesis is 

true. In contrast, however, it provides the probability of observing the data if the null hypothesis 

were true. 

Page 38, Table 8: The first asterisk footnote should probably read “All emissions in Log 

(gram/hour) scale”, thus replace space with scale for this table and all similar tables. 

Potential Short Term Improvements: 

Page 1, bullets: Where do 2-lane highways fit into the picture? It is known from operational 

aspects of traffic that 2-lane highways have very different emergent traffic than do interstates 

with more than two lanes, due to a number of factors including limited access, truck activity and 

restrictions, passing maneuvers, and weaving. The entire paper has not mentioned 2-lane 

highways, and perhaps should address somewhere how this is being handled. In the longer term 

perhaps some empirical data on two-lane highways could be collected to determine whether they 

should server as a “separate facility type”. 

Page 5, paragraph 2: The second sentence states, “Given limited testing budgets,...., thus 

increasing the statistical confidence in the emission test results”. It puzzles this reviewer that this 

is even a consideration, given that statistical confidence has never been considered in any of the 

modeling in MOBILE or CARB to date, particularly with regard to confidence in model outputs. 

So what if the confidence is better if it is not used in the modeling process? My point is that the 

US EPA and CARB need to do a better job of carrying through the uncertainty in forecasted 

outputs, not just in the internal decisions being made as to “how many” cycles should be 

generated. It is actually a good point being made in the text, but is largely irrelevant because of 

Final M6.SPD.002 137 June 2001 
its limited use in policy and practice. 

Page 6, paragraph 3: Although the authors feel that the emissions generated from the new cycles 

are representative of driving behavior “under specific conditions”, it is not clear that the 

forecasting of the particular “specific conditions” can be done accurately. The authors might 

want to suggest that there is additional uncertainty in matching the specific conditions in the lab 

with the same conditions in the field, due to the mismatch between LOS defined by air agencies 

and DOT’s. 

*** Page 7: 1st paragraph: It seems an awful lot to ask from 85 vehicles to infer emissions for a 

fleet of millions. It would be nice to add a table to show how representative (or not) these 

vehicles are of the national fleet. Perhaps a cross-classification of model-year by technology 

classes. Of course all the estimated means are dependent on a random sample of vehicles, and it 

is not clear whether this is the case. More documentation needs to be provided here, with perhaps 

some clues as to how the final estimates might be biased as a result of the biased sample. Also, 

much more needs to be added about recruitment and acceptance, since these are two separate 

issues. Specifically, what was the proportion of rejections, and how was recruitment performed. 

Again, random sampling is fundamental to probabilistic methods, and without it properties of 

probability can not be expected to hold. More information would inform the reader here. 

It is understandable that the typical reader will not be aware of the EPA standard vehicle 

recruitment practices. However, it is not reasonable to attempt to fully describe and 

defend these practices in this report. It should be sufficient to understand the analysis to 

know that EPA was attempting to recruit vehicles in either a random or stratified random 

fashion. Certainly, it will be hard to evaluate the total uncertainty in the overall result 

without some sense of the bias in the recruitment. However, there are plenty of 

opportunities in a sample this small to be concerned about uncertainty without the 

addition of recruitment bias. 

Page 7, 4th paragraph: It would be helpful to add a table comparing the sum of second-by-second 

emissions to bag emissions, or at least to discuss it in the text. There has been some concern 

about the difference in some of these testing discrepancies, and it would be a nice addition to the 

text. 

The second by second emissions were not analyzed at all for purposes of this report, 

since their results were not used. The issues related to second by second measurements 

are important, but beyond the scope of this report. The data from this testing, including 

the second by second results, are publically available in our Mobile Source Observation 

Database. 

Page 7, 5th paragraph: I suggest removing the words (throughout) “real world” with another 

phrase, such as “additional” or “additional representative”, or “further disaggregated”, for 

reasons explained previously. 

Final M6.SPD.002 138 June 2001 
“Real world” is a term used in the National Research Council report on the MOBILE 

model. It is used in this report to refer to data that addresses the concerns of the NRC. I 

have changed all occurrences of “real world” to “real world” representative to address 

this concern. 

Page 8, 1st paragraph: The list of parameters thought to be important really includes of host of 

parameters, especially list item 3, which includes catalytic converter type, fuel delivery system, 

engine size, etc. The text should be amended to explain that list items reflect the variability in 

emissions from a larger set of parameters that are subsumed in the list item. 

Page 9, paragraph 1: Please show the plot of grams per mile versus speed that the authors claim 

does not fit the data. It is always helpful for the reviewer to be able to concur with the authors 

assessment of lack of fit, and this cannot be done here. 

The real issue is not a true lack of fit, but an engineering judgement of the expected 

trends. Linear fits in grams per hour units lead to curves, when converted to gram per 

mile units, which “tail” downward as average speed increases. This is not what is 

expected and is not suggested by the few data points at the higher speeds. Using gram 

per mile units removes this artifact of the modeling approach (the tailing off of emissions 

using grams per hour) from the model, without introducing more complex curve fits into 

the model. 

*** Page 9, paragraph 3: It is not clear that the homogeneity of variance assumption in ANOVA 

was checked for reasonableness. This should be done and reported in the documentation. Also, 

there are many ANOVA tests being conducted, thus, the expected number of type I and type II 

errors is increased. For instance, with alpha = 0.05, and 20 rejections of the null hypothesis, one 

would expect on average (20)(0.05)=1 error The authors should keep in mind the number of tests 

they are conducting in concert with their selected alpha and beta levels. The authors might 

consider giving the beta level associated with some of the tests conducted. 

*** The authors have seemed to ignore (or simply not report) the type II error rate. Type II errors 

often are ignored in the development of statistical models—which of course is embedded with 

statistical tests of hypotheses. Analysts might set an alpha level associated with a t-statistic to 

0.05, only to find that several variables in their models, which were thought to be important on 

theoretical grounds, had p-values associated with t-statistics greater than 0.05—and so they 

subsequently removed them from consideration. In some cases these variables have suffered 

from type II errors, and should still be included in the model, especially when there is theoretical 

support for such variables. Systematically removing ‘non-significant’ variables from a model, 

therefore, ignores the possibility of important variables and related t-tests that have suffered from 

type II errors. 

The determination of which statistical error is less desirable depends on the research question and 

consequences of the errors. Because these errors are related—smaller alpha equals larger beta, all 

else being equal—careful decisions need to be with regard to selection of alpha and beta, and 

Final M6.SPD.002 139 June 2001 
attempts need to be made to quantify beta when appropriate. There are various software packages 

available for calculating type II error rates, and many textbooks also provide the necessary tools. 

The number of parameters examined were carefully selected on a theoretical basis to 

reduce their number. Non-significant variables were removed from this pre-selected list 

based on the type I error statistics and consideration of the theoretical implications. 

EPA has not investigated the additional statistical parameters, but it is not likely that the 

additional work would result in a different choice for the model. 

*** Page 11, paragraph 3: The authors state “....a method was developed for increasing sample 

size by.....”. It seems a bit unorthodox to increase sample size using this technique (or any other 

technique that does not simply collect additional appropriate data). I understand the motivation 

for this action; however, it is not clear that this will lead to satisfactory results. My concern is 

that vehicles ‘substituted’ for the Tier 1 vehicles (Tier 0 vehicles) will not perform similarly on 

the range of driving cycles used to estimate the MOBILE 6 emission factors. Theoretically, it is 

presumed that for a given vehicle manufacturer and model, a vehicle that meets Tier 0 standards 

will be fundamentally different than the same vehicle meeting Tier 1 standards—either through 

computer control of the engine, technology enhancements, or engine tuning. My skepticism also 

stems from the fact that the FTP, which is a fairly ‘tame’ driving cycle, was used to ‘classify’ 

Tier 0 vehicles as Tier 1. The ultimate manifestation of this action could be mild to fairly 

extreme bias in the mean emission response over non-FTP driving cycles of the “Tier 1” group of 

enhanced vehicles, most likely biased high. My recommendation is to not enhance the sample, or 

provide a much stronger justification and demonstrate that the Tier 0 vehicles used also were 

“clean” on non FTP cycles compared to their Tier 1 counterparts. 

EPA shares the authors concerns in this area. However, when it became clear that 

MOBILE6 would need a set of speed correction factors for emission levels below the 

average for Tier 0 vehicles, a reasonable approach to estimate the factors was needed. 

In the absence of more actual data from Tier 1 vehicles, some approach would need to be 

used. The low emitting Tier 0 vehicles did have low emission rates on the more extreme 

facility cycles as well as on the FTP. The actual technical differences between Tier 0 and 

Tier 1 vehicles is not large and can be largely arbitrary based on the model year in which 

the vehicle is certified for sale. It should be noted that because the speed correction 

factors are applied by emission level, not emission standard, that low emitting Tier 0 

vehicles will be using the factors as well. 

Page 17, 2nd paragraph: I agree with the statement, “the equations above would define a rational, 

smooth relationship for emissions versus average speed for...”. The statement deserves some 

further caveats, however; we might expect a piece-wise linear relation to occur when changing 

roadway functional classes, vehicle classes, etc. In other words, a smooth line might not be 

expected when comparing discretely different groups or traffic cases. However, we would (as the 

authors assert) expect this to be the case for a homogenous vehicle class on a facility. The authors 

then point out that this does not in fact happen in the case of freeways. It is problematic that the 

Final M6.SPD.002 140 June 2001 
models predict two different values for the same average speed on the same facility. I 

recommend truncating the portion of the curve where the relationship is in doubt, which is 

essentially using the stated rule 1 to omit the portion of the curve that is not used. 

This is in fact what was done for the final version of the model. 

Page 17, 1st list item: An accompanying figure would be nice to show here, as the text is a bit 

difficult to follow. The idea seems acceptable, however. 

Page 19, Emission Offsets: The concept of emission offsets seems to be reasonable, however; 

I’m not sure why the US EPA has replaced the use of the FTP as the BER with the FTP + EO. 

This should be explained better in the text. 

*** My bigger concern, however, is that Table 14 shows emission offsets computed by 

differencing the means of Fwy and LA4 driving cycles without taking into account the variability 

in the means of these tests. How many of the offsets are statistically significant, and how many 

are spurious? The offsets for level 1 THC and NOx, and level 3 NOx seem to be rather small, but 

one cannot tell ‘how small’ without knowing the variability in means. It is troubling to employ 

emissions offsets when in fact the offset could be in fact could be in the reverse direction. The 

authors should compute 95% confidence intervals on the offsets and only employ offsets whose 

values are convincingly significant and that can be theoretically justified. 

Whether the emission offsets are statistically significant or not will not affect the 

calculations of the speed correction factors themselves, since they assume a base 

emission level on the freeway speed correction curve. This fact is taken advantage of in 

MOBILE6 by allowing the emission offset to change, due to factors such as the SFTP, 

without significantly affecting the speed correction factors. The emission offsets should 

be considered as part of the basic emission rate and any uncertainty included in the 

uncertainty of the basic emission rate. The SFTP report mentioned above discusses the 

emission offset in more detail. 

Page 22, NLEV standards: The authors seem to be approaching the NLEV issue intelligently, and 

I have no comments about the proposed method other than keep updating the method as new 

information about the performance of the NLEV’s is forthcoming. An average approach seems 

reasonable at this point in time. I would suggest that what will become more critical in the future 

(I believe) is the ability to predict and detect failures of the cleaner vehicles and subsequent 

remediation of them. As vehicles become cleaner, the difference between ‘failed’ vehicles and 

clean vehicles will become larger, and thus failed vehicles will provide even more bang for the 

buck (in relative terms) then they do now. How failures are modeled will also become important, 

and how various I & M strategies can be modeled by adjusting failure rates will also become 

important. 

Page 30, Table 2: Need to define the terms SAFD Difference and High-Power Difference. It is 

Final M6.SPD.002 141 June 2001 
presumed that these are statistics of the difference between the cycle and the FTP. 

Page 31, Table 4: As stated previously, a companion table showing the distribution of vehicles 

for the national fleet would be helpful for determining whether the sample data is representative 

nationally. 

National average technology distributions used in MOBILE6 are described in the report, 

“Emission Control Technology Distributions,” (M6.FLT.008). These statistics can be 

summarized numerous ways, depending on the concerns of the reader. Readers should 

refer to the complete description of the technology distributions. 

Page 32-33, Table 5: Again, it seems that a comparison by manufacturer would be useful. For 

instance, I only see one German vehicle in the sample; does the German proportion of vehicles 

really represent about 1/85th of the national fleet? Again, a companion or enhanced table could 

show whether the sample of vehicles used for testing was representative. 

Manufacturer designation is almost never used in generating emission estimates for the 

MOBILE model. Comparison by manufacturer is only an indirect way to compare 

technologies, which are the real parameters that most affect emissions. It is nearly 

always better in emission modeling to project technology trends rather than to predict 

trends in sales by particular manufacturers. 

Page 35-37, Table 7: It appears that the standard deviation is larger than the mean for some 

cycles and emitter classes, see for instance FTP for normal emitters, or Running 505. This 

suggests a non-normal distribution of emissions, since negative emissions cannot result. This 

supports the notion that the ANOVA test assumption of normality and homogeneity of variance 

needs to be tested and shown (a comment detailed previously). 

EPA concedes, without additional statistical testing, that emission distributions are not 

normal. As noted, this makes sense, since emission measurements cannot be less than 

zero on any sample vehicle. 

*** Page 38-39, Table 8: The results in the table may be very deceiving and/or misleading. Of 

course one of the objectives here is to identify which factors are “important” for classifying 

fundamentally different emission conditions, whether they be vehicle, roadway, or environmental 

factors. But since all the ANOVA results are done individually, and the results were not obtained 

from controlled experiments, there are many factors that are correlated, and will subsume all of 

the variability in emissions simply because they are correlated with the “real” culprit. As a vivid 

(and perhaps overly simplistic example), if one were to compare emissions up a grade for a 

vehicle with a driver only and with three passengers, one might correctly conclude in an ANOVA 

that the presence of additional load would result in significantly increased emissions. If one also 

collected information on the number of seatbelts buckled, say 1 in one case and 4 in the other, the 

ANOVA would give identical results—it would suggest that buckling seatbelts increases 

Final M6.SPD.002 142 June 2001 
emissions. Of course it is known that the load caused the excess emissions. My concern is that 

the whole gamut of potential factors has been ‘thrown’ into the ANOVA without regard for 

potentially overlapping or confounding effects. My suggestion is to provide a table with a 

correlation matrix of the factors used in the table (using the correctly computed correlation 

coefficients for nominal and ordinal data), and provide some discussion in the text to justify 

theoretically the factors thought to be important in the emissions process. 

EPA carefully selected the parameters to be tested based on engineering judgement of 

which parameters were expected to be most important. This choice was based on the 

extensive experience of the staff involved and, hopefully, did not include spurious factors 

such as those in the above example. Admittedly, a more thorough investigation would 

include many other potentially important factors. However, the sample size suggested 

that a more rigorous search for significant factors would be fruitless. 

*** Page 58-61: Figures 2 and 3: I am very concerned about these figures, and what they 

potentially represent (analytically), and consider this to be a potentially fatal flaw in the proposed 

methodology. The following discussion assumes that the figures are regressions through the ratio 

of means. There are several deep concerns I have about these graphs: 1) incorrectly specified 

random variables; 2) data aggregation bias; and 2) biased estimators of emission ratios. Each of 

these is now discussed in detail. 

1. The random variable of interest is the ratio of emissions, such that: 

emissions cyclex SCF = θi = emissions FTP

where e is the ratio of two random variables. To find the average of the random variable 

e, one would compute: 

n  emissions cyclex  ∑ 

  i 

i =1 emissions θ = FTP 

= mean of th e ratios 

n 

which is the mean of the ratios not the ratio of the means: 

∑ 

n 

(emissions cycle x )i 

i =1 ratio of m eans = n
 

∑(emissions FTP )i
 

i =1 

To illustrate, suppose there are three thetas observed, 3/2, 1/5, and 5/3. The mean of the 

Final M6.SPD.002 143 June 2001 
ratios is (3/2+1/5+5/3)/3 = 1.12, whereas the ratio of the means is [(3+1+5)/3]/[(2+5+3)/3] = 0.9. 

Thus, the use of the ratio of the means (as opposed to the means of the ratios) will not produce a 

good estimate of the desired quantity, theta, the ratio of cycle emissions to FTP emissions. 

2. In addition to the problem specified above, the data have been aggregated (incorrectly as 

ratio of means) prior to regression. The data should be regressed using the original ratios from 

the 85 vehicles (or appropriate subsets thereof). Aggregation problems have been identified in 

previous research, and have been shown to result in incorrect relationships in the regression (the 

classic example is aggregation of trip generation by traffic analysis zone, which results in an 

incorrect sign of the relationship between trip generation and household auto ownership), and in 

inflation of R-Square and regression model statistics. Aggregation of the data prior to regression 

“throws away” the variability inherent in the data, and presents false confidence in the output. 

3. Finally, the variable theta(hat), which represents the ratio of two random variables 

(emission test results), is in fact a biased estimator of the true population parameter . An unbiased 

estimator, obtained through the method of statistical differentials, is obtained as follows: 

i ecycle   1   [ ] =   E θ 1 +  2 VAR e[] FTP 

e FTP   e FTP   

For additional information on the method of statistical differentials consult Hauer, 1997, 

“Before-After Studies in Road Safety, Pergamon. 

Given these three important considerations, I recommend re-doing all regression equations that 

have used Ratio of Means with regression on original ratio units using all data points. I would 

omit the correction for bias (item 3), which should be neglible for large variance conditions, but 

would comment on it in the text of the bias of the parameter theta. Again, I find this to be a 

potentially large error in analysis, which could significantly alter the results of the analysis. 

EPA agrees that regressions through the ratio of the means would present problems. 

However, careful reading of the report should show that regressions used for the speed 

correction factors were run on the emission levels of the individual vehicles themselves 

and not on the ratios or the ratios of the means. These figures were included only as a 

visual demonstration of the apparent effect of average speed (as defined by the driving 

cycles) on emissions based on the hot running LA4 cycle as a first step in understanding 

the analysis methodology. These figures are not a demonstration of the actual regression 

results, which are shown in Figure 4. 

Potential Long-Term Improvements: 

Page 1, bullets: Where do 2-lane highways fit into the picture? It is known from operational 

aspects of traffic that 2-lane highways have very different emergent traffic than do interstates 

Final M6.SPD.002 144 June 2001 
with more than two lanes, due to a number of factors including limited access, truck activity and 

restrictions, passing maneuvers, and weaving. The entire paper has not mentioned 2-lane 

highways, and perhaps should address somewhere how this is being handled. In the longer term 

perhaps some empirical data on two-lane highways could be collected to determine whether they 

should server as a “separate facility type”. 

Page 6, paragraph 1: The paper states, “These congestion levels have been roughly grouped into 

“levels of service” LOS using letters A through G, similar to congestion category designations 

used in transportation models. 

The definition of level-of-service (LOS) used to ‘bin’ vehicular activity used by EPA and CARB 

is different than LOS used by traffic engineers and transportation planners. LOS has been 

assumed (by air agencies) to be an attribute of an entire facility (as viewed from a platoon of 

vehicles), not segments of a facility as defined by traffic engineers and planners. Traditional LOS 

categories A through F have been used to bin vehicular activity, despite the fact that these 

categories may not optimally separate characteristically different emissions-producing vehicular 

behavior. Only density has been used to ‘bin’ vehicular activity, and it has been determined 

through windshield observation. There are many factors that engineers used to compute level of 

service such as number of lanes, speed, flow, percent truck volume, type of freeway section, 

percent of weaving volume, etc. Future work should focus on improving the “gap” between the 

two working definitions of level of service. A recent paper by Debbie Neimeyer at UC Davis has 

quantified the vast difference between LOS as approximated by the CARB and EPA methods of 

car-following cycle development, and has shown that the imprecision of this measure of LOS is 

significant. 

Page 7: 1st paragraph: It seems an awful lot to ask from 85 vehicles to infer emissions for a fleet 

of millions. Perhaps future testing programs could incorporate a larger number of vehicles in the 

testing programs. 

The data available and the methods for collecting and analyzing new data have been 

changing rapidly. EPA is seriously investigating methods that will not require fixed, 

laboratory driving cycles to estimate the emissions from highway vehicles at a variety of 

operating conditions, such as speed, load and acceleration. These new methods will be 

able to better address the above issues in future versions of EPA models. We look 

forward to working with everyone in the stakeholder community in developing these 

methodologies. 

Final M6.SPD.002 145 June 2001 
Appendix E : Peer Review of Off-Cycle Effects 

MEMORANDUM 

To:	 US Environmental Protection Agency 

Office of Mobile Sources 

From:	 Randall Guensler 

Trans/AQ, Inc. 

Date:	 June 10, 2000 

Review of Off-Cycle Correction Factors for MOBILE6 

This report constitutes a review of the EPA report entitled: Determination of Off-Cycle and 

Supplemental FTP Control Modeling in MOBILE6 (Draft Report M6.SPD.005)." Hereinafter, 

this EPA report is identified as the "Off Cycle Report." Randall Guensler of Trans/AQ, Inc. 

conducted this review under contract with the USEPA. The Off-Cycles report content as well as 

the data and statistical methods used to develop the documented relationships were the primary 

components reviewed. However, the methods and assumptions employed in developing offcycle corrections inherently tie to the methods employed in developing EPA's new cycles-based 

correction factors and engine start emissions rates. In performing a review of the Off-Cycle 

Report, it was also necessary to review the methodologies outlined in the EPA report entitled: 

Facility-Specific Correction Factors (EPA-420-P-99-002). Hereinafter, the second EPA report is 

identified as the "Cycle Correction Factor Report." 

Off-Cycle Emissions 

Instrumented vehicle studies have indicated that the grams/second emissions of CO and HC from 

well-maintained vehicles remain low and stable under conditions of nominal engine load. 

Exhaust emissions under nominal engine load conditions do scale with engine rpm (exhaust gas 

throughput) but remain at low levels. Given the inherent variability in second-by-second 

emissions at these low levels, an average emission rate can represent the emission rates under 

nominal load conditions very well. Once engine loads increase past certain threshold levels 

(where engine load is a function of speed, acceleration, vehicle weight, grade, wind resistance, 

tire rolling resistance, and accessory loads), engine computers respond by enriching the air:fuel 

mixture.1

 The enriched mixture can increase emissions by orders of magnitude for short periods 

of operation. Under enrichment conditions, engine power output increases, and peak combustion 

temperatures and peak combustion and exhaust manifold gas temperatures drop. Hence, 

manufacturers program engine computers to undergo enrichment to improve on-demand vehicle 

1

 Further, when engine loads begin to cycle rapidly from loaded to unloaded conditions (such as under conditions of 

throttle dither) emissions also increase significantly. 

Final M6.SPD.002 146	 June 2001 
 

performance and to protecting valves, rings, and catalysts under high load conditions. Engine 

computer programs may also use other input variables, such as rate of change of throttle position, 

as an indicator that increased power output is requested and therefore send a signal to undergo 

enrichment. Enrichment can also occur as the result of faulty sensor input. Under extreme 

enrichment conditions, NOx emissions can drop significantly as a function of the drop in peak 

combustion temperature. However, under most operating conditions, NOx emissions in 

grams/second tend to scale well with engine load (NOx emission rates are a function of 

temperature and pressure of combustion). Computer-programmed enleanment (and increased 

NOx emissions) can occur for some vehicles under conditions of extended cruise when 

manufacturers have programmed the vehicle to run lean to improve fuel economy. In addition, 

the demands of air conditioning increase engine load and cause vehicles to experience increased 

CO, HC, and NOx emissions.2 

Modeling Paradigm 

The key with any in-use vehicle emissions modeling approach is simultaneously accomplish two 

goals: 1) adequately represent the stable baseline emission rates in the model, and 2) represent 

the cause-effect relationships that result in significantly higher or lower emission rates under 

environmental and onroad operating conditions that differ from those experienced during 

collection of baseline emission rate data. These two components must be prepared 

simultaneously so that the baseline emission rates and the emissions modifiers are appropriate for 

the group of vehicles modeled. That is, if there is little variability baseline emission rates within 

the group "fuel injected vehicles" and if all fuel-injected vehicles respond similarly to changes in 

external operative variables (such as changes in acceleration rates), the baseline emission rates 

and correction factors are likely to be appropriate. However, if there are subgroups of fuelinjected vehicles that exhibit statistically significant differences in baseline emission rates or 

responses to changes in environmental/operating parameters, then the subgroups need to be 

modeled separately. Identifying these mutually exclusive technology groups requires a great deal 

of up-front statistical analysis. In reviewing the EPA documents, the methodologies employed 

are compared to this modeling paradigm. Deviations from the methods described above are 

reviewed and the potential impact of each deviation is qualitatively assessed. 

Baseline Emission Rates 

The LA4 cycle is composed of the 505-second and 866-second dynamometer cycles employed in 

the FTP. The full FTP test consists of an LA4 test (with the 505-second cycle being conducted in 

cold start mode and the 866-second cycle conducted in hot stabilized mode), followed by a repeat 

of the 505-second component of the LA4 cycle under hot start conditions. The report sometimes 

uses LA4 and FTP composite emissions interchangeably. EPA staff should clarify the definitions 

2

 Some impact may result from cycling of the compressor and engagement/disengagement of the a/c clutch, and 

transient changes in EGR or other parameters potentially affected by the cycling. More studies are needed in this 

area to fully understand the cause-effect relationships at work.. 

Final M6.SPD.002 147 June 2001 
of the LA4, FTP, and the relationship between the two, throughout the Off-Cycle Report. 

In testing the 85 vehicles in the Cycle Correction Factor study, EPA and EPA contractors also 

tested all 85 hot-stabilized vehicles on the 505-second component of the LA4 (the FTP Bag1 and 

Bag3 cycle). Normally, certification laboratories would only test these vehicles on the 505­

second cycle under cold transient (FTP Bag1) and hot transient (FTP Bag3 conditions). EPA 

performed the hot-stabilized test so that incremental engine start emission rates (grams/start) 

could be developed for the 85 vehicles (see EPA's documentation associated with MOBILE6 

engine start emission rate development). Because hot stabilized FTP Bag1 and FTP Bag2 were 

available for these 85 vehicles, EPA staff computed a Hot Running LA4 test result for each 

vehicle by adding these two test results together (in grams) and dividing by the miles traveled on 

the LA4 cycle. The exact methodology used to develop the hot stabilized LA4 base emissions 

rates in MOBILE6 should be stated in both the Off-Cycle and Cycle Correction Factor reports as 

they impact the application of the algorithms discussed in these reports. The report should 

contain language similar to that provided by EPA staff below: 

"When we refer to a hot running LA4, we mean the LA4 cycle run without any starts 

at all. This should be equivalent to running all three bags of the FTP without a start, 

but the results of Bag1 and Bag3 should be the same. So, instead you can just add 

a hot running 505 to Bag2 of the FTP to give a hot running LA4. The "trip" in each 

case (FTP and HRLA4) would be the LA4 cycle (7.5 miles), but the FTP would 

contain engine start effects (43% cold and 57% hot) and the HRLA4 would contain 

no starts at all. So you could use the FTP weightings and substitute the HR505 for 

Bag1 and Bag3, but this should be the same as just adding the grams in the HR505 

and Bag2 (Brzezinski, 2000)." 

To develop hot stabilized LA4 MOBILE6 baseline emission rates, the EPA developed a model to 

predict hot stabilized 505 emission rates from FTP test results (using the data collected from the 

85 vehicles in the cycle correction factor database). The EPA engine starts report indicates that a 

linear model was developed to predict hot stabilized Bag1 emissions as a function of FTP Bag1 

transient, Bag2 hot stabilized, and Bag3 transient test results. This way, EPA staff could 

generate an artificial hot stabilized LA4 emission rate using the FTP Bag2 emissions and the 

artificial Hot Stabilized Bag1 for all vehicles in the comprehensive emissions testing database. 

Again, the methods employed need to be clearly defined in the Off-Cycle and Cycle Correction 

Factor reports. 

There are two distinct advantages of using FTP emission rate data for developing baseline 

emission rates. First, the EPA has maintained a continuous testing program (although spotty at 

times) that has resulted in a database of more than 23,000 in-use vehicle tests for which FTP 

emission rates are available. Second, the FTP test cycle is gentle enough to keep most vehicles 

from undergoing enrichment or enleanment. Because the FTP cycle does not usually induce 

enrichment, due to moderate speeds and low acceleration rates, researchers can more readily 

identify and quantify differences in emissions behavior for vehicles across the FTP test and 

Final M6.SPD.002 148 June 2001 
alternative test cycles. Of further importance, the FTP Bag2 cycle is even less likely to induce 

enrichment than the LA4 cycle because the 505-second sub-cycle contains a significant initial hill 

of acceleration that is more likely to induce enrichment. Hence, I believe that using Bag2 as an 

emissions baseline is a sound modeling approach and better for noting systematic changes in 

emissions behavior than the LA4 cycle. In fact, the MEASURE model even predicts higher 

emissions on the FTP 505-second hot stabilized Bag1 activity profile relative to the FTP Bag2 

activity profile. 

It is important to note at the outset that the FTP composite emission rate is composed of 

contributions from a cold transient test, a hot stabilized test, and a hot transient test. Hence, the 

engine and catalyst behavior during warm up stages of operation affect Bag1 and Bag3 values 

and therefore the composite emissions rate. In MOBILE6, start emissions are being modeled as 

an increment (grams/start) and separated from the hot stabilized emissions component. Because 

EPA was developing incremental engine start emission rates in MOBILE6, EPA staff made the 

sound decision to avoid using the FTP composite emission rate as an emissions baseline. EPA 

selected the hot stabilized LA4 as the emissions baseline because it would better reflect onroad 

activity than other cycles. The LA4 emission rate can serve as an adequate baseline in modeling. 

With LA4 as the baseline, the model needs to be able to predict vehicle emissions response when 

vehicles experience nominal engine load conditions (such as those resulting on FTP Bag2 cycle). 

Such nominal engine loads and lower emissions rates would be expected to occur when traffic 

calming TCMs are implemented. The important consequence of using the LA4 as the emissions 

baseline is that there is no comprehensive database of hot stabilized 505 emission rates. These 

emission rates must be predicted for the comprehensive emission testing database as a function 

of the composite emission test results. The basic problems with doing this are: 1) there is a 

question as to whether the 85-vehicle data set used to develop these relationships is 

representative, and 2) there is a large variability in vehicle-to-vehicle emissions response across 

transient versus stabilized test conditions. 

1. Representativeness of Sample Fleet - Based upon the statistical analyses associated 

with MEASURE model development, it is apparent that the 85 vehicles employed in 

MOBILE6 model development are not representative of the vehicle fleet. There is a good 

distribution of model years and fuel-delivery technologies. However, the data set does 

not control for other technology variables that Georgia Tech has found to be statistically 

significant in terms of establishing baseline emission rates and emission responses. 

Given the resource constraints that EPA has faced in collecting in-use emissions data for 

use in MOBILE6 model development, the 85-vehicle is probably the best that could be 

expected. However, when a vehicle sample set does not adequately control for the 

variables suspected of being involved in cause-effect relationships, the real-world 

statistical prediction intervals of the model cannot be determined. All of the statistical 

tests associated with confidence bounds assume that a representative sample has been 

analyzed. The impact of a non-representative sample fleet cannot be determined 

statistically. Hence, the uncertainty associated with using the 85-vehicle data set cannot 

be ascertained. It is impossible to determine whether the use of the 85-vehicle data will 

Final M6.SPD.002 149 June 2001 
overestimate or underestimate baseline LA4 emission rates, or whether the emissions 

response equations (i.e. cycle correction factors) will overestimate or underestimate the 

real-world emissions response. 

2. Large Variability in Vehicle-to-Vehicle Emissions Response Under Transient 

Conditions - In conducting engine start emissions analyses for the MEASURE model, 

Georgia Tech staff analyzed the contributions of Bag1, Bag2, and Bag3 emissions to the 

composite emissions for normal and high emitting vehicles. GT analysts noted that the 

major contribution to high emitter status often came from the cold and/or hot transient 

tests, but for many vehicles, the contribution came from all three bags. There was a large 

variability associated whether the transient tests or the hot stabilized portions of the tests 

contributed to high composite emission rates and pushed the vehicle into high-emitter 

status. Unfortunately, many of the suspected causal links could not be assessed because 

second-by-second emissions were required to determine when these vehicles achieved 

catalyst light-off. The issue that arises here is that the derived statistical relationship that 

EPA is using to predict Hot 505 emissions from FTP Bag1, Bag2, and Bag3 is suspect. 

All of the MOBILE6 modeling methods that follow the development of the LA4 emission 

rates (cycle correction factors, off-cycle corrections, engine start algorithms, etc.) are 

contingent upon the viability of the relationship between the FTP tests and LA4 tests. 

It would have been more appropriate to use the FTP Bag2 (hot stabilized) emission rate as the 

baseline emissions rate for all modeling work. True, emissions are lower on FTP Bag2 than they 

would be under a Hot Stabilized 505 test, but this is not critical. As discussed earlier, statistical 

analyses are designed to develop corrections from a baseline. It is advantageous to select a cycle 

with driving conditions that do not induce enrichment/enleanment so analysts can identify the 

factors that induce such enrichment/enleanment. The LA4 cycle contains higher load conditions 

than FTP Bag2 and therefore provides less stable test results from which to determine correction 

factors. Plus, hot-stabilized emission rates on the LA4 are simply not available for the vehicle 

fleet and have to be derived from FTP Bag1, Bag2, and Bag3 data. Given the methodologies and 

limited data employed, it is not possible to forecast whether the FTP baseline emissions are likely 

to be biased high or biased low. 

Off-Cycle Corrections 

The Freeway Level of Service (LOS) F test cycle represents the activity likely to be experienced 

by vehicles under congested freeway conditions (Off-Cycle Report, page 3). Both the LA4 test 

and the LOS F cycle have approximately the same average speed of 19 mph. However, the 

measured emission rates for almost every vehicle in the 85-vehicle data set under Freeway LOS F 

conditions were significantly greater than their corresponding LA4 emission rates. In effect, the 

off-cycle report indicates that the increase in emissions results from the fact that the congested 

freeway test cycle conditions are more strenuous than the FTP or LA4 test conditions. That is, 

the emissions increase results from the testing activity that is outside of the boundary of FTP or 

Final M6.SPD.002 150 June 2001 
LA4 test cycles.3

 The Off-Cycles Report states that a correction factor should be applied to the 

baseline LA4 data to account for the higher level of emissions noted for the freeway test cycle 

with the same average speed as the LA4 cycle. Hence, EPA staff developed an off-cycle 

correction factor to elevate the FTP emissions to the levels noted at the desired baseline testing 

condition. This way, cycle correction factor statistical analyses would generate a correction 

passing through an emissions ratio of 1:1 for the Freeway LOS F cycle (average speed of 

19mph). 

In reviewing both the Off-Cycle Report and the Cycle Correction Factor Report, it was not 

possible to determine the point in model development at which EPA staff determined an offcycle correction factor was required for developing MOBILE6. The Off-Cycle Report indicates 

that there is a need to account for emissions that occur under operating conditions that differ 

from those experienced in the LA4 test. The Off-Cycle Report also argues that there is a need to 

correct the LA4 emissions to the emissions level observed on under the Freeway Level of Service 

(LOS) F testing cycle. The Off-Cycle Report then states that the Cycle Correction Factor must 

equal 1.0 at these testing conditions. In contrast, the Cycle Correction Factor report simply starts 

with the premise that an off-cycle correction was to be applied to all FTP data for the 85 vehicles 

before model development was to proceed (Cycles Report, page 18 and 19). 

Although both reports argue that an off-cycle correction factor would be required, neither report 

justifies the creation of such a correction. Given the nature of correction factor development, 

there really is no compelling need to create such an off-cycle correction factor. Correction 

factors are applied to a baseline emission rate, irrespective of whether the baseline emission rate 

is an FTP Bag2 or a Hot Stabilized LA4. Introduction of an off-cycle correction factor to the test 

results that are subsequently used in development of cycle correction factors is unnecessary. In 

fact, such a correction is detrimental to the development of the cycle correction factors. This is 

because the first correction factor algorithm yields a predicted value that must by its nature 

reduce the variability in emissions response for a variable that is employed in the next algorithm 

development process. It would have been more appropriate to model the net effect of the two 

correction factors within a single cycle correction factor (statistical reasons are described in the 

next section). True, the new cycles correction factor would not equal 1.0 at 19mph on a freeway, 

but this is not a necessary condition for correction factor algorithms. 

Assessment and Validation of Off-Cycle Analytical Methods 

It was not possible to reproduce the analytical results presented in the Off-Cycle Report using the 

emission rate data provided by EPA staff. Presumably, this is because the database provided 

only contained test results for 84 of the 85 vehicles indicated in the report. The fact that the beta 

coefficients were significantly different between the modeling runs for the 84 and 85 vehicle data 

sets is a reflection of the inter-correlation of the LA4 and LA4-squared variables employed in the 

3

 The emissions increase may also result from other factors such as increased throttle dithering that affect computercontrolled enrichment. 

Final M6.SPD.002 151 June 2001 
model. The standard errors of the model beta coefficients are extremely high under conditions of 

independent variable correlation. Hence, there can be large fluctuations in the beta coefficients 

developed from model run to model run, as a function of the actual vehicle data employed in 

model development. However, the predictions from two different models that use a 95% subset 

of the original data can still be similar, even though the beta coefficients are wildly different. 

This makes interpreting the meaning of the beta coefficients difficult. It is best to think of the 

EPA off-cycle correction factor modeling approach as a curve fit rather than an explanatory 

model. 

The fact that the statistical analyses did not indicate statistically significant differences in vehicle 

emissions as a function of model year, fuel delivery system, trucks vs. cars, etc. is a reflection of 

the small sample size. Emissions variability within same-vehicle tests, let alone across vehicle 

tests, is very large. The report should reflect that there are likely significant differences in 

emission response across the various vehicle technology groups, but the database is of 

insufficient size to distinguish and separate any systematic effects across these variables from the 

highly variable emissions response. 

EPA staff used engineering judgement to prevent the algorithms from predicting negative offset 

increments. EPA staff clipped the quadratic form for high LA4 emissions levels. This way the 

equation retains a maximum offset level, rather than predicting a decline in the offset for higher 

baseline LA4 emissions levels. The report provides no scientific theory (i.e. cause-effect 

relationships related to emissions production) to support the functional form of the model (hot 

stabilized LA4 and LA4 squared) or to support the decision to truncate the model for highemitting vehicles. It is not clear that "off-cycle" emissions increments would not decline or even 

go negative for certain high-emitting vehicles when onroad operations move from LA4 driving to 

freeway LOS F driving (especially for NOx). Despite the mention in the report that there are few 

onroad vehicles with sufficient emissions levels to invoke the clipped portion of the algorithm, 

the validity concern that should be addressed through additional analyses. 

Assessment of Corresponding Cycle Correction Factors 

In developing the MOBILE6 mobile source emission rate model, the USEPA has attempted to 

significantly improve the general modeling approach for predicting emissions as a function of 

on-road vehicle operating conditions. Previous versions of MOBILE modeled emission rates as a 

direct function of average speed, irrespective of actual on-road operating conditions. Hence, 

previous model versions predicted the same emissions rates for vehicles at 25 mph, regardless of 

whether the vehicles were operating under congested freeway conditions or free-flow arterial 

conditions. Researchers have identified numerous theoretical and technical flaws with the 

previous average speed modeling approach (see Guensler, 1993 and the CRC review of EMFAC 

conducted by Environ). MOBILE6 attempts to dis-aggregate on-road emission rates by 

integrating two new explanatory variables into the existing speed-related modeling framework: 

facility type and level of service condition (reflective of congestion conditions). To develop the 

new corrections, EPA staff contracted with Sierra Research to develop new testing cycles 

Final M6.SPD.002 152 June 2001 
designed to be representative of the operating conditions on various facility classes (e.g. 

freeways, ramps, arterial) under different level of service conditions. EPA and EPA contractors 

used these new cycles to collect laboratory emissions data from 85 vehicles. Then, EPA 

contractors derived cycle correction factors, or new relationships between emission rates and 

operating conditions specifically associated with a facility class and the congestion conditions 

noted to occur at various levels of service on these facility types. The cycle correction factor 

approach disaggregates the MOBILE5a relationship between emissions and average speed, 

providing a significant theoretical improvement over the previous speed correction factor 

modeling approach. 

Cycle-based correction factors are multipliers to baseline emission rates. That is, MOBILE6 

predicts emissions under onroad driving conditions as a multiple of the emissions occurring 

under baseline testing conditions. To develop cycles-based correction factors, EPA developed 

statistical relationships between measured emission rates on test cycles designed to represent 

operating conditions on different facility types and level of service conditions and the calculated 

(and then off-cycle-adjusted) LA4 baseline emission rates. If laboratory tests yielded significant 

increases in emissions when vehicles changed from baseline-like operations to alternative 

operating conditions, the model algorithms reflected the effect in the cycles-based correction 

factors (by roadway class).4 

In MOBILE6, the cycle correction factors were determined as a ratio of predicted average 

emissions (average predicted emissions on a freeway test cycle divided by the average predicted 

emissions on the Freeway level of service cycles). These predicted emissions are based upon the 

results of a regression analysis for the 85 vehicles that simply predicted grams/second emissions 

(by emitter class) as a function of average speed for the test cycles used to collect the data. 

Before running these regressions, the emissions data were corrected by the off-cycle emissions 

offset. The basic methodology employed in developing the cycle correction factors is a problem 

unto itself. The prediction of gram/second emissions, calculation of the ratio of predicted 

emissions for each cycle, and then the subsequent prediction of the relationships of the emissions 

ratios to average speed is a fundamental flaw in the modeling approach. Such estimations toss 

away all vehicle-to-vehicle emissions response variability. The best fit curve is forced through 

the mean of the ratio of the average predictions for each cycle test result set, rather than being 

allowed to provide a best overall fit to the entire range of vehicle emissions responses expressed 

4

 Strictly speaking, MOBILE6 models emissions as a function of the level of service conditions reflected in the test 

cycles used to collect the laboratory data for cycles correction factors. MOBILE6 does not predict emissions as a 

function of average speed. Instead, average speed plays a role in a best-fit interpolation between these test cycle 

conditions. EPA staff simply plotted the average emissions from each testing cycle by average speed of testing 

cycle. Then, staff derived a best-fit interpolation between averaged values of the test cycle results as a function of 

average speed. Although the modeling approach provides significant improvement over the average speed regime 

in MOBILE5a, EPA should caution MOBILE6 users that the average speed relationships in MOBILE6 are still 

highly uncertain. If bootstrap regression and Monte Carlo analysis were performed on the derived relationships, 

both the average emissions response value for each LOS test cycle and the curve fits between the test cycle results 

would exhibit wide confidence bounds (see Guensler, 1993 for more information on this modeling technique). 

Final M6.SPD.002 153 June 2001 
 

across all of the cycles. Given the methodology employed, it is impossible to perform a standard 

statistical assessment to determine if the modeling approach is more likely to be biased high or 

biased low. The algorithms could be assessed using a combination bootstrap and Monte Carlo 

assessment approach, but the task would be very time consuming. 

With respect to the role of the off-cycle correction, one is to assume that if a cycle other than 

freeway LOS F had been selected as the off-cycle offset baseline, the same cycle-correction 

factor curves would have resulted. That is, the predicted incremental increase in baseline 

emissions to account for off-cycle effects will not affect the derivation of cycle correction factors. 

If appropriate statistical techniques were employed that retained response variability, this would 

be highly unlikely, given the nature of the small data set and highly variable emissions responses 

across these vehicles and test cycles. However, EPA staff can readily check this hypothesis. The 

question is how significant the differences will be. EPA staff should replicate the model 

estimation approach used to develop the off-cycle correction and the cycle correction factors 

using a different assumed off-cycle correction baseline. The alternative model would use the 

emission test results from freeway LOS B or LOS C cycle (instead of the LOS F cycle) as the 

basis for developing the LA4 off-cycle increment. The same multi-step procedure would be used 

to generate the alternative off-cycle correction (as a function of LA4 and LA4 squared) and the 

subsequent cycle correction factors. If the model estimation approach is stable, this procedure 

will yield the same net predictive algorithm for the range of LOS conditions. That is, when EPA 

staff apply the original and alternative model to the 85-vehicle data set (or any validation data 

set) both models will predict approximately the same emission rates for any specified operating 

condition. The issue of whether the 85-vehicle fleet provides representative responses will still 

be a major concern. However, even though standard statistical methods cannot be applied to 

assess the adequacy of the current MPOBILE6 algorithms, at least the modeling approach taken 

will be more defensible if the original and alternative modeling achieves the same correction 

factors. 

Correction of Correction Factors 

One issue that is a major concern with the modeling methods outlined in MOBILE6 is the 

interrelationships between the various algorithms and correction factors employed. The 

presumption is that all of the relationships developed in a stepwise fashion from the 85-vehicle 

test are applicable to the fleet. 

o	 MOBILE6 hot stabilized baseline LA4 emission rates are predicted from FTP 

transient data. 

o	 Off-cycle correction factors (as a function of LA4 and LA4 squared) are applied to 

the predicted LA4 test result to generate a corrected LA4 baseline. 

o	 The various correction factors do not always account for high-emitter status, Tier 

1 vs. Tier 0, and their interactions, meaning that the "technology groups" 

Final M6.SPD.002 154	 June 2001 
employed in the offset development are different than those used in the cyclecorrection factor development. 

o	 The predicted corrected LA4 baseline emission rate is multiplied by an emission 

ratio that is derived from predicted and adjusted gram/second emissions as a 

function of average speed. 

Every time a predicted variable is used as an explanatory variable in a subsequent algorithm, data 

variability is reduced. That is, the error terms associated with the first algorithm, representing 

random error and problems with model specification, do not carry forward into the development 

of the subsequent algorithm. As such, each modeling step appears to provide a more systematic 

response and better statistical fit. Using predicted variables as independent variables is not a 

significant problem, provided that no important explanatory variables are omitted in the primary 

steps. However, when a model has a large error element relative to the model output signal, such 

as the case in emissions testing, it is difficult to argue that all of the important variables have 

been included. This issue provides a compelling reason to derive all of the correction factor 

relationships simultaneously.5 

The complex step-wise modeling approach used in developing MOBILE6 results in a final model 

structure that cannot be falsified by field experiments. Given the number of general assumptions, 

and corrections to corrections employed in the modeling routines, it will not be possible to 

pinpoint the source of error when the model is determined to over-estimate or under-estimate 

emission rates under certain operating conditions. Simultaneous development of the modeled 

relationships (which would have admittedly required a larger testing data set than EPA had 

available) could have avoided the problems noted above. With simultaneous development of 

baseline emissions rates and correction factors, the emissions from various subgroups of the fleet 

under different operating conditions could be examined through ongoing roadway and laboratory 

experiments. 

There is an important bottom-line conclusion that arises from review of the various modeling 

methodologies employed in developing MOBILE6. EPA management needs to be aware that 

emission rate models cannot improve significantly until EPA has acquired the necessary 

resources to test many more vehicles under testing conditions that differ from the FTP. As a side 

note, it is not nearly as important that these laboratory tests be representative of real-world 

driving as it is that these tests reflect the range of operating conditions that vehicles experience in 

the real world. Statistical modeling approaches can generate appropriate baseline emission rates 

and correction factors once second-by-second data under alternative testing conditions are 

available. 

Supplemental FTP Emissions Effects 

5

 Simultaneous development of baseline emission rates and modal correction algorithms was the basis of 

MEASURE model development. 

Final M6.SPD.002 155	 June 2001 
By integrating two new emissions testing cycles into the FTP certification process, EPA is 

effectively raising the bar for new vehicle certification. The first supplemental test, the US06 

cycle, contains significantly higher speeds and acceleration conditions than the existing FTP. 

The second supplemental test, the AC03 cycle, contains harder acceleration rates and must be 

conducted while the vehicle's air conditioning is operating. The higher load test conditions and 

the operation of air conditioning put significantly greater engine loads on the tested vehicles. 

Consequently, the SFTP provides more opportunity for vehicles to undergo sustained high load 

conditions (leading to higher NOx) and power-demand enrichment (greatly increasing CO and 

HC emissions). The change in the test method, designed to capture more emissions from in-use 

vehicles, results in a defacto change in emissions standards (even though the actual gram/mile 

compliance limits remain unchanged. If manufacturers do not implement additional control 

strategies, many of their vehicles will fail the SFTP certification test. The question that arises in 

the Off-Cycle Report is what emission benefits will result from implementing the new SFTP 

test? 

In principle, the emissions benefit of the SFTP is the difference between in-use emissions before 

implementation of the new test method and in-use emissions after the implementation of the new 

test method and composite SFTP standard.6 If one assumes that manufacturers will comply with 

the regulations, but will not provide significant reductions beyond compliance, the net reduction 

of in-use emissions is represented by change in vehicle activity reflected in the new testing cycle. 

There is a subset of onroad vehicle activity included in the SFTP and not included in the FTP that 

leads to elevated in-use emissions with the current fleet. Under the SFTP, these activities will 

likely yield normal stabilized operating emissions. Hence, the SFTP emission rate benefits are 

associated with the change in capture of emissions by the new cycles, multiplied by the overall 

fraction of onroad vehicle activity that is included within the operating boundaries of the new test 

conditions. 

Quantifying the emissions benefits of the SFTP requires comparative testing of vehicles on the 

facility cycles as well as the US06 and AC03 cycles. Reduction in off-cycle emissions could be 

estimated by comparing the percentage reduction in emissions that will occur for current vehicles 

as they move from their current emissions levels on the composite SFTP to the compliance 

emission rates for the 5year/50,000 mile US06 standard of 0.65 grams/mile HC+NOx and 

(perhaps lower than this level to account for the benefit of compliance headroom). One could 

then make the argument that if the US06 and AC03 cycles contain the conditions in the facility 

cycles that currently lead to enrichment, the onroad emissions will be reduced by a similar 

percentage (or by a percentage weighted by the 65% contribution of these cycles to the composite 

SFTP). In plotting the cycle characteristics of the various freeway level of service cycles, the 

US06, and the AC03, it is clear that then new cycles contains a significant fraction of high-speed 

activity that appears in the Freeway LOS cycles. The acceleration rates associated with the highspeed ranges in US06 are also on par with the acceleration ranges found in the Freeway LOS 

Cycles and the US06 contains harder decelerations at higher speeds and harder accelerations at 

6

 Composite FTP is determined as a weighting of 35% FTP composite, 37% AC03, and 28% US06 contributions. 

Final M6.SPD.002 156 June 2001 
higher speeds. Three-dimensional Watson plots of fraction of operation under given speed and 

acceleration ranges could be used to determine whether the US06 and AC03 cycles cycle contain 

a wider range of load-inducing activity than the various level of service cycles. EPA could then 

effectively argue that because the SFTP cycles (which contribute 65% to the SFTP composite 

emission rate calculation) are more likely to induce off-cycle emissions than the LOS cycles, and 

because manufacturers will comply with the SFTP, off-cycle emissions under all LOS cycles will 

decline. However, EPA SFTP benefit estimation methods did not take such an approach. As 

discussed below, it is difficult to follow the logical progression of the benefit calculation and it is 

not possible to verify many of the assumptions employed in the methods reported in the OffCycle Report. 

For Tier 1 vehicles, the Off-Cycle Report indicates that the off-cycle increment7 will be adjusted 

downward by 88%, 72%, and 78% for HC, CO, and NOx respectively. The argument put 

forward is that the implementation of the SFTP will reduce the emissions difference noted across 

the LA4 test and the freeway LOS F test by these percentages. The Off-Cycle Report cites to 

"rule-estimated benefits," presumably contained in the Tier 1 rule development report as the 

source for the reduction claims. However, the basis for these claims is unverifiable in the OffCycle Report. No scientific theory or empirical data are provided to justify the values.8

 It would 

be beneficial to test these hypotheses using new modal emissions models applied to the cycle 

tests and weighted by fraction of onroad activity expected to occur under each operating 

condition. New modal models could also be employed to assess the likelihood that these 

estimates are reasonable. 

The implementation of the SFTP stands to flatten the future cycle correction factor curves in 

MOBILE6 for the future vehicle fleet. As discussed earlier, there was no compelling reason to 

prepare a linear bump-up in emissions and deem it to be an off-cycle correction factor. Similarly, 

there is no compelling reason to create a linear bump-down to adjust this off-cycle increment for 

SFTP implementation. This is because the effects of operations that differ in engine load from 

LA4 (or any other baseline) will be reflected in the final curve that result from the statistical 

method (or combination of statistical methods) employed. To the extent that operating 

conditions in the cycle correction factor test cycles are now reflected in the SFTP, there is reason 

to believe that future vehicles will behave differently on the new facility cycles used to generate 

the cycle correction factors. The Off-Cycle Report's discussion and re-derivation of cycle 

correction factors using the test results from 10 vehicles that behaved well on the ramp cycle 

does not provide adequate evidence to assess the validity of keeping the proposed cycle 

correction factors when the SFTP is implemented. This seems especially true considering the 

highly aggregated modeling approaches (and averaging of predicted values) employed in 

7

 Calculated as the difference between the hot stabilized LA4 test results and the freeway LOS F test results and 

then predicted as a function of LA4 and LA4 squared. 

8

 There also appears to be no basis for the 50% decrease in off-cycle emission reduction effectiveness for SFTP 

controls that are coded into the MOBILE6 model (noted in Appendix A, Table 3, and Table 4). This aspect needs 

to be discussed and justified in the report. 

Final M6.SPD.002 157 June 2001 
developing the cycle correction factors. Had the baseline emission rates and cycle correction 

factors been modeled in a single statistical operation, as suggested earlier, significantly different 

relationships would likely have resulted and the cycle correction factors may have taken on 

different shapes both pre- and post-SFTP implementation. Unfortunately, it does not appear that 

a scientific and statistical method that can be used to test the relationships presented in the report. 

As such, EPA should propose a comprehensive testing program designed to collect data from 

new SFTP certified vehicles when they become available. The goal of the testing program 

should verify the onroad emissions response behavior reflected in MOBILE6 both pre-and postimplementation of the SFTP. 

The methodology used to develop the LEV benefits from implementation of the SFTP is not 

clear and concise. Although the calculation methods have been conveyed in the text and tables, 

it is impossible to follow the logical flow of the multi-step procedure outlined in the report. The 

first step splits the effective SFTP standards (identified as US06 in Table 2) NHHC+NOx 

compliance levels into separate components cannot be evaluated (theory, logical reasoning, 

empirical evidence, and appropriate references should be provided to support the splits). The 

second step of estimating average 1999 certification emissions levels from the Certification and 

Fuel Economy Information System (CFEIS) should be clarified and additional detail on the 

number of vehicles tested should be provided. Presumably, the CFEIS tests reported are test 

results on the SFTP (indicated by the provision of 4K and 50K mileage accrual values 

corresponding to SFTP standards) and not the FTP.9 The third step of estimating running 

emissions levels is not clear and requires separate evaluation of the referenced MOBILE6 

exhaust emissions report to ascertain why the adjustment was made (0.9 for NOx and 0.23 for 

HC). The fourth step consists of calculating the ratio of the SFTP effective emissions standard 

(Step 1 result) and the running certification level for 1999 model year vehicles (Step 3 result). A 

discussion as to why the ratio of SFTP standard to current new vehicle certification emissions is 

lacking. In using this value in emissions benefit assessment, it seems that EPA is asserting that 

the certification standard is somehow responsible for the compliance headroom noted in the 

CFEIS and that such headroom is systematic and will remain consistent over time. 

The logical reasoning behind the next set of steps in the benefit assessment process is completely 

lost in the text. The goal appears to be to determine the increased stringency of the ARB LEV 

standards relative to the EPA standards and then to adjust the SFTP benefits accordingly. 

Presumably, the calculation is designed to represent how much cleaner in use LEVs will be under 

the California LEV standard (at 4,000 miles) relative to the 49-state standard (at 50,000 miles). 

That is, the certification of LEVs under the California program is expected to garner additional 

emissions reductions. Tables 2 and 3 illustrate the calculation method employed to represent the 

increased stringency of the ARB standard relative to the EPA standard. However, the text does 

9

 The Tables indicate that "FTP Certification Levels" are reported. If this is the case, another major issue arises. 

The use of a ratio of future SFTP certification limits to current FTP running certification emission rates would be 

meaningless in the calculations employed. There is no reason to believe that current FTP certification emission 

rates will correspond to future SFTP test results. 

Final M6.SPD.002 158 June 2001 
not explain the logic behind the calculation. While a more stringent ARB requirement is likely 

to capture emissions that the EPA requirement leaves in the in-use fleet, no compelling argument 

is provided that indicates why the calculation methodology makes sense. 

As mentioned above, it seems that the calculation methods are based upon the assertion that 

compliance headroom (represented in the ratio surrogate) in the certification database is 

systematic and the result of the differences in certification standards. The method also inherently 

assumes that such headroom will remain consistent over time. Even if EPA staff provided the 

logical flow of the equation derivation, it is unclear whether the logic behind the calculation 

methodology would hold into the future. As manufacturers produce more reliable and durable 

vehicles in response to the SFTP mandate, the compliance headroom or safety margin currently 

experienced in the certification database may drop significantly. Plus, it is unclear how these 

ratios will change for LEVs versus the 49-state fleet. Furthermore, there is no way of knowing 

whether these respective vehicle fleets will age similarly and whether the effect predicted from 

SFTP calculations based upon 1999 vehicle data will still be appropriate for these vehicles in 5 or 

6 years. Changes in these factors would be evidenced as significant changes to the ratios 

calculated in Step 4, significantly influencing the predicted CARB-related LEV benefit. Without 

additional information and explanation, it is simply not possible to evaluate the algorithms 

provided in the Tables. Since it is unlikely that EPA will be able to answer the question of 

benefit estimation stability over time, it imperative that a comprehensive testing program be 

implemented to check these significant MOBILE6 assumptions over time and make corrections 

based upon observation. 

Similar to the methods used to develop benefit estimates for the US06 cycle, the text discussion 

of AC03 benefits also lack sufficient documentation to perform an assessment of the 

methodologies employed. The first problem is failure to support the determination of the EPA 

SFTP AC03 benefit of 50% for NOx. As mentioned earlier, the justification for using the ratio 

of AC Standard to Running Certification Level (or even certification level in the CFEIS 

database) as a measure of relative effectiveness across the EPA and ARB certification programs 

is lacking. The fact that CARB has required the elimination of "commanded enrichment" is 

unclear. Presumably, CARB has prescribed that vehicles cannot be pushed into commanded 

enrichment simply whenever the air conditioning is turned on (i.e. the issue that apparently arose 

in the Cadillac dispute). However, the text is unclear as to the extent to which CARB has 

prescribed the elimination of A/C induced commended enrichment. When the air conditioning is 

in operation, a vehicle will undergo enrichment more readily unless an A/C clutch causes the air 

conditioning to disengage under these conditions (is thus what CARB actually prescribed?). If 

so, the assumption of HC eradication does not seem unreasonable. Scaling CO emissions with 

vehicle load also seems reasonable (this probably could have been done for HC as well) where 

vehicle load is predicted as a function of predicted fuel consumption increases. However, 

equations used to derive the increase in fuel consumption as a function of speed and speed 

squared are not supported in the text of the report. A multitude of alternative fuel consumption 

equations could have been employed. The concern here, given the discussions earlier regarding 

the representativeness of vehicles tested, representativeness of test conditions, and treatment of 

Final M6.SPD.002 159 June 2001 
data in developing regression models, is that these relationships may or may not be justified. The 

report should provide more detail on how the equations were developed and how the predicted 

changes in fuel consumption are used to estimate changes in CO. The derivation of the actual 

values in Tables 4 and 5 must be supported with additional text material so that the reader can 

follow the logical flow from calculation method to calculation method. As it stands, reasonable 

readers could not be expected to understand the reasoning behind the development of the benefits 

estimates. 

Conclusions: 

The methods used to develop the off-cycle corrections, cycle correction factors, and SFTP 

benefits employ multiple assumptions that cannot be verified. Modeled relationships are derived 

from a small fleet that is not representative of the on-road fleet. Data treatment is such that 

averaged values and predicted values are often used as independent variables in the statistical 

techniques from which MOBILE6 algorithms are based. A number of relationships are modeled 

as independent effects when they are actually co-dependent (e.g. off-cycle correction and cyclecorrection factors). Given these problems, it is not possible to apply standard statistical 

techniques to the model derivation process to determine confidence bounds around the 

algorithms employed in MOBILE6. Further, given the model development discussed above, it is 

not even possible to assess whether the predicted mean responses are likely to be biased high or 

low. 

Because confidence bounds around the MOBILE6 algorithms cannot be generated, a combined 

bootstrap and Monte Carlo assessment could be undertaken to determine inherent model 

uncertainty. In such an analysis, each algorithm discussed in this report would be derived 1000+ 

times using subsets of the original data set (with replacement). The modeled relationships would 

then be represented as probability distributions in MOBILE. Then, MOBILE would be run in a 

Monte Carlo fashion to develop a distribution of model output results. Guensler and Leonard did 

this for the MOBILE5a speed correction factors; however, a similar assessment for MOBILE6 

would be extremely labor-intensive. One is left to conclude that there is little for EPA to do to 

assess the adequacy of the algorithms in MOBILE6 than to assess the mean squared error and 

bias of the model in its application to validation data sets. When the algorithms are fully 

integrated in MOBILE6, EPA should use the model to predict the emissions of a validation data 

set and examine the prediction errors of the model, comparing them to the prediction errors of 

MOBILE5a and other alternative modeling approaches. 

Recommendations: 

o	 The actual definitions of the LA4, FTP, and the relationship between the two should be 

clarified in the report whenever the terms are employed. 

o	 The exact methodology used to develop the hot stabilized LA4 base emissions rates in 

MOBILE6 should be stated in both the Off-Cycle and the Cycle Correction Factor reports 

Final M6.SPD.002 160	 June 2001 
as they impact the application of the algorithms discussed in these reports. 

o	 The relationships between the methods used to develop off-cycle corrections and other 

correction factors should be delineated in a text and graphic (flowchart) format. 

o	 All methods need to be better documented so that the reader can follow both the logical 

reasoning behind the proposed analytical method and the estimation techniques 

themselves. 

o	 EPA would be better off to use FTP Bag 2 as the baseline standard (rather than LA4) 

from which to determine the emissions effects that result from changes in vehicle 

operating conditions represented in the various emissions testing cycles employed in 

developing cycle correction factors and SFTP effects. At the very least, MOBILE6 LA4 

baseline rates would not need to be predicted as a function of individual FTP Bag test 

results. 

o	 EPA presumably pursued the development of an independent "off-cycle" emissions offset 

to provide an estimate of the benefits that the new emissions testing cycles were likely to 

achieve. Alternative analytical methods could have, and should have, been applied to 

estimate the SFTP effect. The process employed in developing the estimates for 

MOBILE6 contains too many inter-correlated effects from testing on the FTP, SFTP, and 

cycle correction factor test cycles. Hence, the "off-cycle" offset cannot be reliably 

predicted from the analyses undertaken. 

o	 Cycle correction factors should have been developed directly from the laboratory test 

cycle data, rather than after artificially bumping up baseline emissions levels. The cycle 

correction factor would be more appropriate if derived from a single statistical analysis, 

rather than a staged analysis. Even if EPA retains the current method to estimate SFTP 

effects (for use in policy analyses), a single-step cycle correction factor approach would 

provide better estimates of the effect of changes in traffic conditions on emission rates. 

Final M6.SPD.002 161	 June 2001 
Response to “Review of Off-Cycle Correction Factors for MOBILE6" 

The response to specific comments made in “Review of Off-Cycle Correction Factors for 

MOBILE6" are contained throughout Section 6 of this report. A summary of the primary 

comments and responses follows: 

•	 Comment: The comments suggested a lack of clarity in discussing the relationship between 

the off-cycle adjustment and speed correction adjustments, originally documented in separate 

reports. 

Response: In response to this comment, the discussion of off-cycle effects has been 

incorporated into M6.EXH.002 for improved cohesiveness. 

•	 Comment: The comments criticized the application of two correction factors to address offcycle and speed corrections, saying it artificially reduced statistical variability of the overall 

emission effects. The comments suggested that one correction be developed to address both 

issues. 

Response: A separate correction factor is necessary to isolate the effects of increased 

emissions due to “off-cycle” driving, for the purpose of applying benefit from the SFTP rule. 

Another source of increased emissions (on a grams per distance basis) is due to the “reduced 

travel efficiency” which results at lower speeds (i.e., less distance traveled). Emission 

increases due to the latter are reflected in the speed correction factors, but will not be reduced 

by the off-cycle provisions of the SFTP. 

•	 Comment: The comments suggested that alternate facility cycles be used to derive an offcycle correction, in order to demonstrate the stability of the modeling approach used in 

MOBILE6. 

Response: In response to this comment, an alternate model formulation was developed by 

deriving off-cycle corrections and speed correction factors from the Arterial E cycle rather 

than the Freeway F cycle, and the results compared to the MOBILE6 approach. The end 

results were less than 3 percent different, and were not statistically significant. 

•	 Comment: The comments suggested that the derivation of SFTP benefits a) were not 

presented in a clear manner, b) were not based on an analysis of US06 data with and without 

SFTP control, and c) were based on reductions not clearly justified 

Response: In response to this comment, the source and derivation methodology of the SFTP 

reductions have been clarified. The Tier 1 reductions were in fact based on an analysis of 

vehicles with and without control measures intended to allow compliance with the SFTP. 

The dataset used for this analysis (performed as part of the SFTP rulemaking) is the only 

database containing vehicles which have been modified by manufacturers to demonstrate 

Final M6.SPD.002 162	 June 2001 
compliance with the SFTP. No such data exists for obtaining LEV benefits, hence an 

analytical approach was required. The derivation of LEV benefits have been clarified. 

•	 Comment: The comments suggest that speed correction curves will change for vehicles 

complying with the SFTP requirement, and questions the EPA analysis provided to 

demonstrate the adequacy of the speed correction curves for SFTP vehicles. 

Response: Speed correction curves cannot be directly estimated for vehicles complying with 

the SFTP, since these vehicles have not begun to penetrate the market in substantial numbers. 

The analysis presented in M6.EXH.002 was intended to show that the magnitude of SCFs is 

not inappropriate for vehicles which would likely comply with the SFTP. This issue cannot 

be fully researched until a robust set of SFTP-compliant vehicles are exercised over the speed 

correction cycles; until this point, the analysis presented does provide an initial support for 

the assumption that Level 1 SCFs are applicable to vehicles with low off-cycle emissions. 

Final M6.SPD.002 163	 June 2001