RADIAN 

CORPORATION 

DCN: 87-245-019-04 

HEAVY-DUTY DIESEL VEHICLE 

INSPECTION AND MAINTENANCE STUDY 

FINAL REPORT 

VOLUME I 

SUMMARY REPORT 

Submitted to: 

California Air Resources Board 

1800 15th Street 

P. 0. Box 2815 

Sacramento, CA 95812 

ARB Contract No. A4-151-32 

Submitted by: 

Christopher S. Weaver. P.E. 

Project Director 

Robert F. Klausmeier 

Program Manager 

Radian Corporation 

10395 Old Placerville Road 

Sacramento, CA 95827 

May 16, 1988 

The statements and conclusions in this report are those of the Contractor and 

are not necessarily those of the State Air Resources Board. The mention of 

commercial products. their source or their use in connection with material 

reported herein is not to be considered as an actual or implied endorsement of 

such products. 

10395 Old Placerville Rd./Sacramento, California 95827/(916)362-5332 
RADIAN 

COO .. OOAYIO• 

LIST OF TABLES 

Table Title 

2-1 Common Types of Emissions-Related Defects in Heavy-Duty 

Diesel Trucks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-2 

2-2 Survey of Diesel Mechanics and Maintenance Managers: 

Questionnaire Results..................................... 2-9 

2-3 Comparison of Radian Fleet-Average Emission Factor 

Estimates with EMFAC7C ............................•.•..... 

2-4 Contributions of Each Heavy-Duty Vehicle Class to Total 

State'W'ide Emissions ...•............•.•.••....•••..••.•.... 

2-5 Contributions of Total Excess Emissions by Each Heavy-Duty 

Vehicle Class ............................................ . 

3-1 Proposed Periodic I/M T.est Procedures ••••••..•••••••..••.• 

3-2 Effectiveness of Smoke Opacity Tests in Identifying High 

'Ein.itters .......................••..........•.•.•..•....... 

3-3 Pass/Fail Analysis for Two Sets of I/M Failure Criteria: 

New York Bus Database •••• •...••••••..•.•••••••...•.......• 

4-1 I/M. Scenarios Considered •..•.•••••••••••••••••••••••.•••.• 

4-2 Estimated Costs and Cost-Effectiveness of I/M Programs, 

199 0 • •......................•......•...................... 

4-3 Estimated Costs and Cost-Effectiveness of I/M Programs, 

1995 . .................................••........ . ......... 

4-4 Estimated Costs and Cost-Effectiveness of I/M Programs, 

2000 . .............................•............. . •...•.... 

iii 

2-15 

2-16 

2-18 

3-4 

3-16 

3-24 

4-3 

4-14 

4-15 

4-16 
RADIAN 

ce•P•••'~'••• 

LIST OF FIGURES 

Figure Title 

ES-1a Projected NOx Emissions from Heavy-Duty Diesels: 

19 85-200 0 ••••••••••••••••••••••••••••••••••••••••••••••••• viii 

ES-1b Projected HC Emissions from Heavy-Duty Diesels: 

1985-2000 •••••••••••••••••••.••••••.•••••....•.••. • • • • • · • • ix 

ES-1c Projected PM Emissions from Heavy-Duty Diesels: 

1985-2000. • ... • • • • • • • •. •. • •. • • • • • • • • • • • • • • • .. • • • • • • • • • • • • • X 

ES-2 Breakdown of PM Emissions by vehicle class: 1990 .......••• xii 

ES-3 Acceleration Peak Smoke Opacities from the Screening 

Tests..................................................... xiv 

ES-4 Visual Opacity Estimates vs. Opacimeter: 

Acceleration Peak.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . "XV 

ES-5 Acceleration Smoke Opacity vs. PM: New York Bus 2 Cycle ••• xvii 

ES-6 Emissions Reductions Projected for Alternative I&M 

Programs : 1990........................................... xxi 

ES-7 Emissions Reductions Projected for Alternative I&M 

Programs: 2000............................................ XX:L 

ES-8 Percent Reduction in Excess Emissions for Alternative I&M 

Programs: 1990............................................ xxii 

ES-9 Percent Reduction in Excess Emissions for Alternative I&M 

ES-10 

ES-11 

ES-12 

Programs: 2000 . .......................................... . 

Estimated Costs of Alternative I&M Programs: 1990 •••••.•.• 

Estimated Costs of Alternative I&M Programs: 2000 ••.•.•••. 

Estimated Cost-Effectiveness of Alternative I&M Programs 

for Particulate Emissions Control. ...................... .. 

2-1 Distribution of Truck Smoke Opacity in Road-Load 

xxii 

xxiii 

xxiv 

xxvi 

O~ration ............................................... ·. 2-4 

2-2 Distribution of Truck Smoke Opacity in Full-Power. 

Steady-State Operation.................................... 2-5 

2-3 Distribution of Truck Smoke Opacity Under Transient 

Acceleration.............................................. 2-6 

iv 
RADIAN co•.,.o•a'I'IOII 

2-4 Projected Statewide NOx Emissions from Heavy-Duty Diesel 

Vehicles.................................................. 2-11 

2-5 Projected Statewide HC Emissions from Heavy-Duty Diesel 

Vehicles.................................................. 2-12 

2-6 Projected Statewide PM Emissions from Heavy-Duty Diesel 

Vehicles.................................................. 2-13 

3-1 Bar Chart of Peak Acceleration Smoke Opacities from the 

Field Screening.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-6 

3-2 

3-3 

3-4 

3-5 

3-6 

3-7 

3-8 

Visual vs. Measured Smoke Opacity (Acceleration Peak) ••••• 

Measured vs. Visual Smoke Opacity (Snap Idle Peak Reading) 

Particulate Emissions vs. Lug-Down Opacity ••••••••.••••••• 

Particulate Emissions vs. Acceleration Peak Smoke Opacity. 

NOx Emissions vs. Mode 4 Concentrations ••••••••••••••••••• 

Predicted vs. Actual HC (Based on Modes 6 & 14) ••••••••••. 

Acceleration Smoke Opacity vs. Particulate Emiasions (New 

3-10 

3-11 

3-13 

3-14 

3-18 

3-19 

York Bus 2 Cycle)......................................... 3-21 

3-9 Actual Particulate Emissions vs. Emissions Predicted from 

Acceleration and Cruise Mode Opacities: New York Bus 

3-10 

Composite .. ...................................•........... 

Actual Particulate Emissions vs. Emissions Predicted from 

Acceleration and Cruise Mode Opacities: New York Truck 

3-22 

Cycle..................................................... 3-23 

4-10 

4-5 Comparison of I/M Scenarios: Percent Reduction i n Excess 

Emissions Due to I/M •••••••••••••••••••••••••••• • • II • II II •••• 4-11 

4-6 Comparison of I/M Scenarios: Reduction of Offensive 

Smoke Due to I/M ••••••••••••••.••••••••••••••••••••••••••• 4-13 

4-7 Comparison of I/M Scenari os: Program Costs and CostEffectiveness ............................................ . 4-18 

v 

-- ~ 
....... 

IUUIUUI ,. ... 

HEAVY DUTY DIESEL VEHICLE 

INSPECTION AND MAINTENANCE STUDY 

EXECUTIVE SUMMARY 

Heavy-duty diesel vehicles are responsible for significant emissions 

of oxides of nitrogen (NOx). unburned hydrocarbons (HC). and particulate 

matter (PM) in urban areas in California. As with other types of vehicles, 

poor maintenance and/or tampering with emissions controls can greatly increase 

these emissions. Up to now. however, diesel vehicles in most states have been 

exempt from any type of inspection and maintenance (I/M). such as California's 

Smog Check Program. This is due to the lack of a well-documented emissions 

test procedure for diesels. and to uncertainty as to the cost-effectiveness of 

such a program. 

In order to address these issues. the California Air Resources Board 

(ARB) issued contract no. A4-151-32 to Radian Corporation, for a study which 

would: 

• Quantify the extent of excess emissions from heavy-duty diesel 

vehicles due to malmaintenance and/ or tampering; 

• Develop and validate suitable I/M procedures for heavy-duty 

diesel trucks and buses; and 

• Estimate the costs and emissions benefits of implementing a 

heavy-duty diesel I/M program. 

The s.tudy results indicate: that excess emissions from heavy-duty diesels are 

significant: that suitable procedures for ·detecting high-emitting vehicles 

exist; and that a suitability designed I/M program could be very costeffective compared to other diesel emissions control measures that have been 

adopted. 

vi 
QUANTIFYING THE PROBLEM 

To quantify the problem of excess emissions. a computer model of 

total and excess emissions from heavy-duty diesel vehicles was developed. 

Excess emissions are calculated from estimates of the emissi ons levels of 

properly functioning vehicles and estimates of the effects and frequency of 

occurrence of 18 types of emissions-related defects. Defect frequency 

estimates were based on a visual survey of truck smoke opacity on California 

freeways and a questionnaire survey of diesel fleet maintenance managers and 

mechanics. The impact of each type of defect on emissions was estimated using 

data from several sources. Key data sources were an EPA/Engine Manufacturers' 

Association cooperative test program: laboratory studies by EPA and pouthwest 

Research Institute: and a database compiled by the New York City Department of 

Environmental Protection covering more than 400 emissions tests on trucks and 

buses. This last was computerized and analyzed for the first time as part of 

this study. 

The computer model of diesel emissions and tampering/malmaintenance 

effects constructed for this study deals with four general classes of heavyduty diesel vehicles: heavy-heavy. medium-heavy. light-heavy, and transit bus. 

The model further differentiates between out-of-state and California-registered 

vehicles. and between California-registered vehicles with California and 

Federal engines. The model can also be used to estimate the impact of a given 

I/M program on emissions. 

The emissions model results for the case with no I/M program are 

plotted in Figure 1. This figure displays the annual average statewide tons 

per day of NOx• HC. and PM emitted by heavy-duty diesel vehicles. broken down 

into baseline and excess emissions. The baseline emissions level is the 

amount that would be emitted even if all the engines in use were in good 

mechanical condition and with their emission· controls performing properly. 

Excess emissions are defined as the increase over and above the baseline due 

to tampering. malmaintenance. and excessive engine wear. As Figure 1 shows. 

excess emissions account for a rather small fraction of heavy-duty diesel NO X 

emissions. but a large and increasing fraction of HC and PM emi ssions. 

vii 
)( 

0 

z 

EXCESS EMISSIONS MODEL PROJECTIONS 

Statewide NOx Emissions 

600 ,-------------------------------------------------------~ 

1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 

Year 

Figure ES-la: Projected NOx Emissions from Heavy-Duty Diesels: 1985-2000. 

viii 

•.,, ·~ 
0 

:I 

EXCESS EMISSIONS MODEL PROJECTIONS 

Statewide HC Emissions 

140 

130 

120 

110 

100 

90 

80 

70 

60 

20 

10 

0 

198~ 1986 1987 1988 1989 1990 1991 1992 1Q93 1994 199~ 1996 1997 1998 1999 2000 

Year 

Figure ES-lb: Projected HC Emissions from Heavy-Duty Diesels: 1985- 2000. 

i x 
~ 

RIHMI!· 

EXCESS EMISSIONS MODEL PROJECTIONS 

Statewide Pt.4 Emissions 

140 

lJO 

120 

110 

100 

90 

80 

70 

60 

40 

20 

10 

0 

1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 

Year 

Figure ES-lc: Projected PM Emissions from Heavy-Duty Diesels: 1985-2000. 

• 

X 
RADIAN 

···~······· 

Figure 2 shows the projected breakdown of total PM emissions between 

the different classes of heavy-duty vehicles for the year 1990 (breakdowns for 

HC and NOx• and for other years. show a similar pattern). As the figure 

indicates. nearly all of these emissions are due to heavy-heavy and 

medium-heavy trucks, with heavy-heavy vehicles alone accounting for about two 

thirds. Light-heavy duty vehicles and transit buses are responsible for a 

relatively minor share. Out-of-state vehicles are fairly significant contributors to the overall emissions levels. but California-registered vehicles 

with Federal engines are even more significant. Together. these two groups 

account for about one-half of the total heavy-duty diesel emissions in 

California. 

Because of the lack of applicable statistical data to base them on. 

these projections include considerable uncertainty. The range of uncertainty 

in the excess emissions estimates is estimated at -30 percent to +70 percent 

of the value shown. while the uncertainty in the total emissions is estimated 

at approximately -20 to +50 percent. 

DEVELOPMENI' AND VALIDATION OF I/M TEST EROCEDURES 

Two types of inspection test procedures for heavy-duty diesel 

vehicles were developed and validated: a Periodic Inspection and Maintenance 

Test (PIMT) procedure and a Roadside Smoke Opacity Check (ROC). The purpose 

of each of these procedures is to identify heavy-duty diesel vehicles which 

are producing excessive pollutant emissions. The ROC is intended to be used 

for random enforcement testing. For this reason. it was required that it be 

performable within the physical confines of a California Highway Patrol (CHP) 

weigh station. The PIMT. as its name implies. is intended to be used in a 

periodic (e. g. annual or biennial) inspection program. analogous to 

California's existing Smog Check Program. 

A number of candidate ROC and PIMT procedures were developed and 

subjected to validation testing. The ROC was applied to 52 heavy-duty diesel 

trucks belonging to various government agencies and private fleets. The 

results of the ROC screening were used to select eleven trucks for PIMT 

xi 
....... 

CO·~••aTIO• 

PM EMISSIONS BREAKDOWN BY CLASS: 1990 

MEDIUM-HEAVY (31 . 1%) 

" 

0 Ca. Reg ./Ca . Engine 

rZJ Ca. Reg ./Fed. Engine 

D Out-of-state 

Figure ES-2: Breakdown of PM Emissions by Vehicle Class: 1990. 

xii 
........ ............. 

testing at ARB's Haagen-Smit Laboratory facility. Mass emissions measurements 

were also taken on these trucks. using a chassis-dynamometer version of the 

old 13-mode emissions test. Six of these vehicles were then repaired in an 

attempt to reduce their emissions. and then retested. In addition. smoke test 

data from the NYCDEP database were analyzed to determine their correlation 

with mass PM and HC emissions. 

The most effective ROC test procedure was found to be measuring peak 

smoke opacity during a full-power vehicle acceleration from a stop. Figure 3 

displays the validation test results using this procedure. The trucks 

selected for dynamometer testing are indicated by the arrows underneath the 

figure. Another test procedure--measuring smoke opacity as the engine accelerates from idle to the torque-converter stall speed--was found to give similar 

results. This procedure is safer and requires less space than the vehicle 

acceleration. but applies only to vehicles with automatic transmissions. Two 

other test procedures gave poor results. These were: quick acceleration to 

the engine's governor speed; and lugging-down the engine against the brakes. 

Smoke opacity measurements in the ROC testing were made with an 

end-of-stack opacity meter mounted on the truck. Opacity was also estimated 

visually by an ARB employee. Figure 4 is a cross plot comparing these two 

measurements for the acceleration peak data. Cross-hairs indicating our 

proposed failure criterion for that mode are also shown on the plot. These 

data indicate a fair degree of correspondence between the visual opacity 

estimates and the opacimeter data in the moderate-to-high opacity range. This 

suggests that a visual screening approach could be feasible with the ROC. 

greatly simplifying its implementation in the field. An officer could distinguish passing from failing levels by eye in most cases. Marginal or 

protested cases could then be confirmed using an opacimeter. 

Statistical analysis of the PIMT data showed poor correlation 

between acceleration smoke opacity and 13-mode particulate emissions. This 

was due to the presence of two vehicles with high transient acceleration 

smoke. but low emissions on the 13-mode test (which is conducted under steadystate conditions). This test is incapable of measuring emissions which occur 

xiii 
:< 

1-'• 

< 

ACCELERATION PEAK 

100 

Failure Criterion: 35'- Opacity 

90 -

80 -

Pass 39. 754Wt 

Fail 13 25'-

Total 52 mv 

70-

60 -

50 -

..... t 

t t 

..... 

[ 

I! 

t I! u : 

r ur I! M UUUvu11v 

V/llr II II/ / llll / /l/11./:/ 

20 - Ill/// Ill 1111 1111 VI / /VV;I 

V Ill/VII Ill /1.1 // I II VII/IV/(

a 

10--i // /v/1 r:l/ll 11 VI/IV ' 

I / l/ / I V / I v / /if / / / / / / / / llln / II / / II / I I 1

H/ V/IIA/VIVjV/V/1 //I/ 

It I I I I It I I I It I I I I I I I I I I I I l I I I I f rl 'l It I I I I I It I I I It 

Figure ES-3: Acceleration Peak Smoke Opacities from the Screening Tests. 
RADIAN co•••••Y•o• 

ACCELERATION PEAK 

100 

90 

80 

.... 70 

# 

..... 

"' ~ 60 0 

< z 

(I) 

~ ~ 0 0 

"' _, 

< 40 :;:) 0 [] 

Ct) 

s: 

30 

0 0 

20 

0 R'-0.90 

10 DO RMS Errora10 2~ Opacity 

0 

0 20 40 60 80 100 

OPACIMETER MEASUREMENT(~) 

Figure ES-4: Visual Opacity Estimates vs. Opacimeter: Acceleration Peak . 

XV 
RAR¥,-11 •••• 911.;.-e. 

only under transient conditions. A similar statistical analysis was conducted 

on the NYCDEP database, which included both acceleration smoke measurements 

and mass emissions measured under transient conditions. This analysis showed 

good correlation between acceleration smoke and total PM. 

shown in Figure 5. 

These data are 

We examined the effectiveness of the acceleration smoke opacity 

test in detecting high-emitting vehicles. For the PIMT validation tests, a 

failure criterion of 35 percent opacity resulted in seven failures, accounting 

for 71 percent of the excess PM emissions. Two of these failures were "errors 

of commission"--vehicles with high acceleration smoke opacity but low 13-mode 

emissions (these were the same vehicles that caused the poor correlation 

discussed above). As discussed above, however, these vehicles would likely 

have shown higher emissions on a transient emissions test. 

A similar analysis was conducted on the bus portion of the NYCDEP 

database. Of this fleet, 69.3 percent were law emitters, and all of these 

passed the I/M test (there were no errors of commission). The remaining 30.7 

percent of the buses were classed as high emitters. Of these, more than 

two-thirds (20.8 percent of the total) also passed the I/M test. causing them 

to be classed as errors of omission). Only 9.9 percent of the buses failed 

the I/M test. However, this small group accounted for more than 68 percent of 

the total excess particulate emissions and 80 percent of excess hydrocarbon 

emissions for the entire fleet. Mean emissions from the failing group were 

26.7 g/mi of particulate, which is nearly nine times the mean for the lowemitting group, and three times the mean for the false negative group. Thus, 

while these tests did not detect all high emitters, they did detect the 

highest emitters, which account for most of the excess emissions. 

Cl)STS AND EMISSION BENEFITS OF HEAVY-DUTY DIESEL I/M 

After analyzing the resul~s of the preceding phases, a number of 

alternative I/M scenarios were defined. These were input into the heavy-duty 

xvi 
. ·-··· . -- _ .. , ~~ 

··-t 

RADUUI 

c ........... . 

NEW YORK BUS 2 CYCLE 

40 

0 

c 0 

0 ..... 

·e c .... 

Cl 

.... 

a: 

w 

~ < 2 

w c ~ 

< 0 

...1 

~ 

0 

t= 0 a: 

< 0.. 

0 PM (g/mi)•1.78.o.417 Oacc 

R2•0.8& 

0 

0 20 40 60 80 

ACCELERATION SMOKE OPACITY(~) 

Figure ES-5: Acceleration Smoke Opacity vs. PM: New York Bus 2 Cycle. 

xvii 
.. 

........ 

c ............ . 

diesel emissions model developed in Task One. This model was used to calculate the change in emissions as a result of each I/M scenario. as well as 

repair costs and related data. 

Alternative I/M Program Designs 

Because of the differences in technology. ownership. and operating 

patterns. existing I/M programs for light-duty vehicles may not be a good 

model for heavy-duty diesel I/M. Other existing enforcement programs aimed at 

heavy-duty trucks (such as Highway Patrol weigh stations and safety inspection 

programs) should be considered as well. To reduce emissions. while minimizing 

the burden on vehicle owners. the primary goals of a heavy-duty diesel I/M 

program should be the following: 

• Deter tampering with emission controls; 

• Detect tampering which is not deterred. and require that it be 

corrected; 

• Identify gross-emitting vehicles. and require that they be 

repaired: and 

• Encourage proper maintenance and awareness of the importance of 

emission controls in the bulk of the heavy-duty diesel fleet. 

The I/M program scenarios investigated in this study were chosen 

with these gpals in mind. They consist of a number of variations on two basic 

approaches: a dynamometer-based periodic I/M program. and a program of in-use 

smoke opacity enforcement and random anti-tampering inspections. 

Case 1. the basic periodic I/M scenario. consists of periodic, 

annual inspections enforced through the registration process. It assumes a 

decentralized. garage-based inspection program. using chassis dynamometer test 

procedures for smoke opacity and gaseous pollutant concentration in specific 

xviii 
operating modes. In addition. an anti-tampering inspection and functional 

check of emission controls such as EGR valves. trap-oxidizers. timing advance 

units. etc. is included. The basic scenario includes a $1.000 cost limit for 

repairs. with no cost limit for correcting tampering. Cost waivers require 

approval by a referee station. 

Cases la through lf consist of variations on this basic s cenario. In 

Case la. inspection is performed in central. state-operated inspection 

stations. rather than in truck garages. In Case lb. the repair cost limit is 

reduced to $500. In Case lc. the repair cost limit is eliminsted--i. e. "fix 

it or park it". In Case ld. the gaseous pollutant concentration measurements 

are eliminated. Case le is a biennial inspection program. Case lf. the final 

variation. reflects the legal constraints of the current Smog Check legislation in California. These include: biennial inspection. $100 cost limit. and 

a limit on the charge for a Smog Certificate of $6. 

Case 2 describes a very different I/M program. based on i n-use smoke 

opacity enforcement and anti-tampering inspections. This would include 

stationing ARB Smoke Inspectors at CHP truck scales and inspection stations to 

maintain continuous visual screening for excessive smoke. and with the 

authori:ty to pull a truck over for a smoke test and/or anti-tampering inspection. Trucks cited for excessive smoke would be required to be repaired and 

test below the standards within two weeks. unless they receive a cost waiver. 

The cost limit for repairs in the basic scenario is $1.000 (a variant. 

Case 2a. eliminates the cost limit). Smoke tests after repairs may be 

performed by authorized garages. Trucks cited for excessive smoke more than 

once in 6 months are subject to a $250 fine (except where the first citation 

resulted in a waiver). Tampering with emission controls. or knCMingly 

operating a truck with tampered controls. is subject to a $1.000 fine for the 

first offense. and $2.500 fine for each subsequent occurrence. Tampering must 

be corrected within two weeks. with no cost limit. 

In addition. ARB Inspectors would accompany CHP depot truck inspection teams to conduct anti-tampering inspections at the same time the CHP 

xix 

. . ~· .. 

.. :-:.:.: ·· ' · _ .. 

' .. 
IUlDUUI 

···~··· ... ··· 

conducts safety inspections. At the same time, the existing truck smoke law 

would be tightened. and local police forces trained in enforcing it. Dedicated 

roving smoke patrol officers would be assigned in critical air pollution areas 

such as the South Coast Air Basin. 

Results 

Emissions--Figures 6 and 7 show the projected reduction in NOx• HC, 

and PM emissions in California due to each alternative I/M program. Figure 6 

shows the results projected for 1990. and Figure 7 those for 2000. Figures 8 

and 9 show the percentage reduction in excess emissions due to each program. 

As these figures indicate, all of the annual inspection programs are 

reasonably effective in reducing excess NOx• but they are less effective in 

reducing HC and PM emissions. The centralized program in Case la is 

marginally more effective in this regard, reflecting the greater probability 

of deterring or detecting tampering with the central inspection. All of these 

programs are hampered, however, by their relatively infrequent and predictable 

inspections, which limit the deterrence of "reversible" tampering, and which 

do relatively little to reduce the overall incidence of non-tampered 

high-emitting vehicles. 

The in-use inspection programs, on the other hand, are highly 

effective in reducing particulate and HC emissions--resulting in more than a 

50 percent reduction in excess PM. These programs are less effective in 

reducing NO , however, due to the inability to perform gaseous emissions 

X 

measurements in the field. 

Costs and Cost-Effectiveness--Overall costs for each alternative 

program are shown in Figures 10 and 11. Figure 10 shows the annual costs for 

1990, while Figure 11 shows the costs for 2000. The breakdown of costs into 

administration and enforcement, inspection, repairs, indirect costs, and fines 

is also shown. Indirect costs include lost driver and vehicle time due to 

inspections. and the costs (or benefits) of changes in fuel economy. 

XX 
RADIAN· co•~••••••• 

1990 

2000 

40 

J!> 

30 

~ 2.5 'i 

J 

0 

Ul 

8 20 

~ c: 1.5 

~ 

10 

.5 

0 

NO 1/W CASE 1 c.-sE 1 o c.-sE 1 b CASE 1 c CAS[ 1 d ~ 1e CAS[ H CASE 2 CASE 2a 

Figure ES-6: Emissions Reductions Projected for Alternative 

I&M Programs: 1990. 

~ 

i 

! 

0 

Ui 

NO 1/W CASE 1 CASE 1 a CASE 1 b CASE 1 c CASE 1 d CASE 1 e CAS£ 1 r CASE 2 CASE 2a 

C2:Z) NOX ~ Particulate 

Figure ES-7: Emissions Reductions Projected for Alternative I&M 

Programs: 2000. 

xxi 
·- -~~ .-.:.--: .::~ 

RADUUI co•••••Y••• 

1990 

2000 

1()(K 

~ 

~ 

7CK 

c 8CK 0 

~ 

g ~ l 

at 4al 

30111 

2<K 

1CK 

~ 

NO 1/W CASE 1 CASE 1 a CASE 1 b CAS£ 1 c CASE 1 d CASE 1e CASE 1r CASE 2 CASE 2o 

Figure ES-8: Percent Reduction in Excess Emissions for Alternative 

I&M Programs: 1990. 

NO 1/W CASE 1 CASE 1 a CASE 1 b CASE 1 c CASE 1 d CASE 1 1 CASE 1 f CASE 2 CASE 2o 

IZ2J NOx ~ Particulate 

Figure ES-9: Percent Reduction in Excess Emissions for Alternative 

I&M Programs: 2000. 

xxii 
RADUUI 

co•••••w-••• 

Program Costs: 1990 

$220 

$200 

$180 

... $160 

CIS 

~ 

>- $140 ........ ... 

... 

CIS 

0 $120 

Cl 

... 

0 $100 >~ 

% ., 

.: 

0 $80 

:< 0/ : // $60 V// v: // $40 

$20 ~-

CASE 1 CASE 1 a CASE 1 b CASE 1 c CASE 1 d CASE 1 e CASE lf CASE 2 C\SE " 

00 Inspections !2:Z] Repairs 

- Admin/Enforcement ~Fines 

Figure ES-10: Estimated Costs of Alternative I&M Programs: 1990. 

xxiii 
RADUUI: c .......... . 

.... 

0 

"' c 

.:: 

Program Costs: 2000 

8210 ~------------------------------------------------------------. 

8200 

8190 

8180 

8170 

$160 

8150 

81 40 

8130 +-.:-...--.. 

8120 

8110 

ttoo 

890 

$80 ~-r-,~ 

870 

860 

$50 

840 h"-"-v'' 

830 

820 

810 ... _ $0 __. 

CASE 1 CASE la CASE 1b CASE lc CASE 1d CASE 1e CASE 1! CASE 2 CASE 2a 

~ Inspections r:z::;;j Repairs LS:SJ Indire ct Costs 

- Admin/Enforcement CJ3 Fines 

Figure ES-11: Estimated Costs of Alternative I&M Programs: 2000. 

xxiv 

·· -----~~~ 
RADIAN 

co•••••'~'••• 

Cost-effectiveness estimates for each alternative are summarized in 

Figure 12. To calculate the cost-effectiveness of an emissions control 

strategy (such as I/M) which affects more than one pollutant requires that 

some decisions be made as to the proper allocation of costs between the 

different pollutants. For our calculations. we assigned each program a credit 

of $4.000 per ton of NO or HC reduced. and assigned the remaining costs of 

X 

the program to PM control. Making these assumptions. we were able to calculate the cost-effectiveness of each program as a particulate control measure. 

treating the HC and NO reductions as side benefits. The value of $4.000 per X 

ton of HC and NO eliminated is fairly typical of other ongoing emission 

X 

control initiatives in California. 

As Figure 12 shows. the most cost-effective I/M program scenario by 

our calculations is Case 2. followed by Case 1e. Cost-effectiveness estimates 

for Case 2 ranged from $1.489/ton in 1990 to $2.942/ton in 2000; those for 

Case 1e from $2.836 to $7.805. For comparison. the cost-effectiveness of the 

1994 PM standard of 0.1 g/BHP-hr for heavy-duty vehicles has been estimated at 

around $7.000-$11.000 per ton of PM eliminated. Case 2 also results in the 

second .largest reduction in emissions (after Case 2a). and thus appears 

clearly preferable overall. 

By far the highest costs-per-ton of emissions control are calculated 

for the two scenarios with no repair cost limits. due to the very high costs 

of engine overhaul included in these cases. These calculations overestimate 

the actual economic costs somewhat. since overhauling an engine i ncreases its 

value and useful life. Nonetheless. it appears that some reasonable limit on 

repair costs is needed in a heavy-duty diesel I/M program in order to keep 

overall program costs and cost-effectiveness reasonable . 

CONCLUSIONS AND RECOMMENDATIONS 

1. Malmaintenance and tampering with emissions controls are 

estimated to result in substantial excess em i ssions from 

heavy-duty diesel vehicles. Excess emissions will become ev en 

XXV 
u 

u 

> 

0 E,...... 

u " o::u c: ~ c 

0.. ~ ~ 0 

0~ 

r::" 

0 

1-

' .. 

RADIAN 

CO ... O.AYIOM 

Cost-Effectiveness for Particulate Control 

$24 

$22 

$20 

$18 

$16 

$14 

$12 

$10 

$8 

$6 

$4 

$2 

$0 

NO 1/M CASE 1 CASE 1 o CASE 1 b CASE 1 c CASE 1 d CASE 1 e CASE 1f CASE 2 CASE 2o 

[Z2] 1990 IS:SJ 1995 tzZl 2000 

Figure ES-12: Estimated Cost-Effectiveness of Alternative I&M Programs 

For Particulate Emissions Control. 

xxvi 

---- ~ 
RADIAN 

co•~••••••• 

more significant in the future. as stringent new emissions 

controls introduce new motivations and opportunities for 

tampering. 

2. A set of effective I/M test procedures for heavy-duty diesel 

trucks and buses has been developed and validated. These tests 

are able to identify about 65 to 80 percent of excess diesel PM 

and HC emissions. 

3. Visual smoke monitoring at weigh stations (with confirmatory 

opacimeter testing) and random anti-tampering inspections in 

conjunction with existing safety checks would be .the most 

effective and cost-effective I/M program for heavy-duty 

diesels. Periodic I/M programs such as the Smog Check are 

projected to be more expensive and less effective than an 

in-use program. 

4. Due to the lack of an adequate statistical database. the 

estimates of excess emissions. I/M test effectiveness. and I/M 

program bene£ its developed in this study contain much uncertainty. It is recommended that ARB undertake a program for 

heavy-duty diesel vehicles which would be comparable to its 

periodic emissions surveillance programs for light-duty vehicles. This program should include recruitment of a representative sample of trucks and buses. and testin g both for 

smoke opacity and for emissions using a heavy-dut y transient 

test procedure. 

x xvii 
RADIAN 

CO.PO.A'I'IOII 

1.0 INTRODUCTION 

In order to protect and improve the quality of its air, the State of 

California is interested in minimizing pollutant emissions from heavy-duty 

diesel trucks and buses. Diesel-engined vehicles are major contributors to 

ambient levels of particulate matter and oxides of nitrogen (NO ) in urban X 

air. Diesels also emit lesser (but still significant) amounts of unburned 

hydrocarbons (HC), and a small amount of carbon monoxide (CO). Diesel HC 

emissions are of special concern, since the hydrocarbon species emitted 

include polynuclear aromatic compounds, nitro-aromatics, and other toxic, 

carcinogenic, or mutagenic species. Diesel HC and aldehyde emissions are also 

responsible for the characteristic diesel odor. 

New motor vehicles must meet strict pollutant emission standards 

before they can be sold. In order to improve the level of emissions control 

in custcmer use, however, California and many other states have found it 

necessary to implement programs of periodic inspection and maintenance (I/M) 

to check emissions levels and/ or the functioning of emissions controls, and 

require corrective repairs where necessary. California presently has a strong 

I/M program for light-duty and some heavy-duty gasoline vehicles, and has 

considered a similar program for light-duty diesels. Heavy-duty vehicles--

those over 8,500 pounds gross vehicle weight- -have traditionally been exempted 

from I/M requirements, however. This is especially true for diesels. 

Implementation of I/M programs for diesels has been impeded by the 

technical difficulty of developing a suitable emissions test, and by uncertainty as to the magnitude of the problem and of the cost-effectiveness of an 

I/M program for these vehicles. In response to the need for improved control 

of heavy-duty diesel emissions, the California Air Resources Board (ARB) 

contracted with Radian Corporation to quantify the problem of excess emissions 

from heavy-duty diesel trucks and buses, to develop preliminary I/M procedures 

for these vehicles. and to estimate the costs and cost-effectiveness of 

implementing an I/M program for heavy-duty diesels. 

1-1 
RADIAN coaPoaa'I'ION 

1.1 Outline of the Study 

The project was divided into five major tasks. as listed below. 

(1) Quantify the problem of excess emissions from heavy-duty 

diesels due to poor maintenance and/or tampering with emission 

controls. This task included defining common emissions-related 

defects. estimating the frequency of defects in the truck 

population. estimating the emissions consequences of each 

defect, and combining these estimates with data on truck 

populations and travel patterns to estimate the impact of 

excess emissions from heavy-duty diesels on air quality and 

public offense due to excessive smoke. 

(2) Develop and document a periodic inspection procedure and a 

quick roadside smoke opacity check to identify heavy-duty 

diesel vehicles having excessive emissions. The periodic 

inspection procedure was intended to be conceptually similar to 

the procedures for the present Smog Check Program for lightduty gasoline vehicles. The roadside opacity check procedure 

was intended as a quick and simple check for excessive emissions which could be applied at a truck weigh station or 

similar environment. 

(3) Estimate the costs and emissions benefits of implementing the 

procedures developed in Task Two, assuming that the emissions 

defects identified by the procedure are properly repaired. 

(4) Validate the procedures developed in Task Two by applying them 

to a representative sample of trucks in a blind test. 

(5) Prepare a final report documenting the work. 

1-2 
RADIAN 

co•~•••'~'• Oil 

1.2 Outline of the Report 

The final report for this project is contained in four volumes, of 

which this is Volume I. The volume numbers and their titles are as follows: 

I. SUMMARY REPORT 

II. QUANTIFYING THE PROBLEM 

III. DEVELOPMENT AND VALIDATION OF I/M TEST PROCEDURES 

IV, I/M PROGRAM DESIGN AND COST-EFFECTIVENESS ANALYSIS 

Volume I, this volume, presents an overview of the other three volumes, and 

summarizes the major conclusions and recommendations. Volume II describes a 

computer model of heavy-duty diesel emissions developed for this project, and 

presents the model results for the case with no I/M program. Volume III 

describes the development and validation of test procedures to identify 

heavy-duty diesel vehicles which are excess emitters. Volume IV outlines 

several possible designs for I/M programs using these procedures, and estimates the emissions reductions and cost-effectiveness for each. 

1.3 Limitations and Caveats 

This report presents our estimates of the current and future pollutant emissions from heavy-duty diesel vehicles in California; and the effectiveness, costs, and cost-effectiveness of each of several possible heavy-duty 

diesel I/M programs. These estimates are heavily based on the model of excess 

heavy-duty diesel emissions described in Volume II, and the I/M effects model 

described in Volume IV. Neither these models nor any other can produce 

"Truth"; at best, they can only reflect the consequences of the data and 

assumptions that go into them. The limitations on the data and assumptions 

going into these models are discussed in Volumes II and IV. 

1-3 
RADIAN 

CORPORA'I'IOII 

The results presented here reflect our estimates of the effects of 

alternative heavy-duty diesel I/M programs . These estimates are necessarily 

very rough: estimates of the effectiveness even of operating I/M programs are 

notoriously difficult. and no programs comparable to those described here are 

now in operation. In the absence of hard data to serve as a benchmark. even 

t he most careful estimates contain a great deal of uncertainty. and the ones 

presented here should be understood in this light . Our estimates are based on 

experienced judgement. and we consider them to be somewhat conservative (in 

the sense of under-estimating the effects of an I/M program). but they cannot 

be shown to be either "right" or "wrong" based on the data available today. 

Our estimates also assume that the programs described are competentl y designed, effectively executed. and vigorously enforced. This has not 

always been the case in light-duty I/M programs in the U. S. A poorly designed. mismanaged. or badly enforced I/M program would sacrifice a large 

portion of the benefits estimated in this report. while costing as much or 

more. These limitations should also be borne in mind in interpreting and 

applying our results. 

1-4 
RADIAN ca•Pa•a'f i O M 

2. 0 QUANTIFYING THE PROBLEM OF EXCESS EMISSIONS FROM HEAVY-DUTY DIESEL 

VEHICLES 

In Task 1 of this study. Radian developed a computer model of total 

and excess emissions from heavy-duty diesel vehicles. This model. its input 

data. and the model results are described in detail in Volume II. and briefly 

summarized below. 

2.1 Frequency of Occurrence of Emissions-Related Defects 

Table 2-1 is a list of common types of tampering and malmaintenancerelated defects which can affect emissions from heavy-duty diesel vehicles. 

Virtually no reliable published information on the frequency of occurrence of 

these defects in heavy-duty vehicles exists. In order to fill this gap in the 

available data. we undertook two surveys as part of this program. The first 

was a field survey of truck smoke emissions. using visual observation. The 

second was a questionnaire survey of truck mechanics, engine rebuilders. and 

fleet maintenance managers. undertaken as part of a larger study of engine 

rebuilding practices by another ARB contractor. 

Visual smoke survey--Most of the more common types of emissionsrelated defects show a characteristic smoke emissions "signature". Smoke 

emissions in different operating modes are different for different types of 

defects. For example. tampering with the smoke limiter on a turbocharged 

engine results in excess smoke during acceleration, but has no effect on 

steady-state smoke. It is thus possible to estimate the frequency of occurrence of many types of emissions-related defects by comparing the frequency 

and severity of smoke emissions data from different operating modes. 

To obtain first-hand information on diesel truck smoke emissions 

patterns. a visual survey of truck smoke emissions in California was undertaken. Truck smoke emissions were observed visually by a Radian staff member 

who had been ARB-certified as a smoke reader. Trucks were observed in three 

operating modes: acceleration from low speed or stop. steady-state full-power 

2-1 
RADIAN 

CORPORA'I'ION 

TABLE 2-1. COMMON TYPES OF EMISSIONS-RELATED DEFECTS 

IN HEAVY-DUTY DIESEL TRUCKS 

Defect Likely Cause 

Injection Timing Changes 

Timing Retarded 

Timing Advanced 

Fuel Injection Problems 

Minor Injector Problem 

Moderate Injector Problem 

Severe Injector Problem 

Fuel Air Ratio Problems 

Puff Limiter Misset 

Puff Limiter Disabled 

Maximum Fuel Too High 

Clogged Air Filter 

Turbocharger Worn 

Turbocharger Wrong Type 

Intercooler Clogged 

Other Air-Supply Problems 

Other Engine Problems 

Improper Rebuilding 

Excessive Oil Consumption 

Engine Mechanical Failure 

Future Technologies 

Electronic Controls Failed 

Electronic Controls Tampered 

Catalytic Converter Removed 

Trap Bypassed 

Trap Failed/Removed 

EGR System Disabled 

2-2 

Wear/Malmaintenance 

Tampering/Malmaintenance 

Wear 

Wear 

Wear/Bad Fuel 

Tampering/Malmaintenance 

Tampering 

Tampering 

Mal maintenance 

Wear 

Tampering 

Malmaintenance 

Mal maintenance 

Tampering/Malmaintenance 

Wear 

Malmaintenance 

Malmaintenance 

Tampering 

Tampering 

Tampering 

Tampering 

Tampering 
RADIAN oa~oaa'fiOM 

operation (up a steep hill). and steady-state road-load operation on a level 

section of freeway. 

Observations were made at a number of sites in the Los Angeles and 

Oakland/Sacramento areas; in all, 1,243 observations at 13 locations were 

recorded. An attempt was made to observe a representative cross-section of 

the trucking activity in the State (e.g. long-distance and interstate trucking 

on I-80, short-distance trucking on L.A.'s Harbor Freeway and the L.A. Harbor 

area). 

survey. 

Figures 2-1 through 2-3 summarize the results of the truck smoke 

Figure 2-1 shows the distribution of smoke opacities observed for 

trucks in steady-state, road-load operation, Figure 2-2 shows the opacity 

distribution for steady-state, full-load operation, and Figure 2-3 shows the 

distribution for transient smoke during acceleration. 

As these figures indicate, both the greatest range in values and the 

highest absolute values for opacity are found in the acceleration mode. 

Roughly half of the trucks observed had peak acceleration smoke opacities less 

than 30 percent (slight to moderate smoke). Most of the rest (44 percent of 

the total) had opacities in the 40 to 60 percent range. Most people would 

consider this smoke level to be visually offensive. The remaining 6 percent 

had opacities over 60 percent, indicating very heavy (and highly offensive) 

smoke. As expected. smoke emissions in steady-state, full-power operation 

were much lower, and those in road-load operation lower still. 

The significance of these smoke data can be understood by comparing 

them to the results for well-maintained engines. Federal smoke regulations 

limit smoke opacity in peak, acceleration average, and lug-down modes to 50 

percent, 20 percent, and 15 percent, respectively. Our observations of 

acceleration smoke are most comparable to the peak value, although we would 

expect them to be somewhat lower due to the eye's tendency to "average" rapid 

changes in opacity. Our full-power observations are comparable to the 

2-3 
10 

20 

:;..,30 

4-l 

•r-i 

c.J 

~40 

0 

50 

60 

RADIAN 

COR~ORA91011 

0 5 10 15 20 

Percent 

tt•4mm 

I 73 • 93 

25 30 70 

Sample size = 468 

Figure 2-1. Distribution of Truck Smoke Opacity 

in Road-Load Operation 

2-4 

75 

73.93 

.... 93.38 ~ 

c.J 

~ 

~ 

98.72 p.., 

~ 

> 

99.15 :1 

<C 

....-! 

;:l 

99.79 3 

u 

100.00 
0 

10 

20 

>-

4.1 

-M 

u 

111 30 

p. 

0 

40 

so 

RADIAN 

co ......... .. 

5 10 15 20 25 30 50 

Percent 

Sample size = 243 

Figure 2-2. Distribution of Truck Smoke Opacity in 

Full-Power, Steady-State Operation 

2-5 

52.26 52.26 

75.72 <.J 

~ 

Q) 

u 

92.18 

p.., 

~ 

Q) 

96.30 ~ .... 

C1l ,..., 

99.18 § 

:l 

u 

00.00 

55 
RADIAN co•.,o••••o• 

0 

10 

20 

30 

;:.., 40 19.69 4.J 

~ 

u 

co so A. 

0 

60 

70 

80 

90 

5 10 15 20 25 30 

Percent 

Sample size = 523 

Figure 2-3. Distribution of Truck Smoke Opacity 

Under Transient Acceleration 

2-6 

8.22 

20.27 

35.18 

49.71 4.J 

c 

Q) 

u 

69.41 ..... 

Q) 

p.. 

Q) 

83.75 > 

~ 

4.J 

co 

~ 

93.69 ~ :l 

u 

97.51 

98.66 

100.00 
RADIAN 

CO RI"O R A'I'IO II 

"lug-down" value, although again, we would expect them to be somewhat lower. 

The lug-down value measures smoke opacity at near the peak torque point, while 

most of the engines we observed would have been operating at higher engine 

speeds where smoke emissions are lower. 

Based on Federal smoke certification data, peak smoke levels of 

about 20 to 30 percent opacity should be typical of well-maintained and 

properly adjusted engines, while a typical lug-down smoke level would be about 

10 percent. Only 10 of 153 heavy-duty diesel engines certified in 1987 had 

peak smoke opacities greater than 35 percent, and most of these were smaller, 

naturally aspirated engines used in light and medium-heavy duty trucks, not 

the heavy-heavy trucks in our survey. Only two engine families in 1987 ~ 

certified with peak opacities of 40 percent or more; in 1986, only one did. 'y. 

In our visual survey, however, slightly more than half the trucks were estimated to have peak smoke opacities of 40 percent or more. 

The cruise mode in our observations has no counterpart in the 

Federal smoke tests, since this operating mode should not normally produce 

visible smoke. Smoke opacity in this part-load, steady-state cruise mode 

is normally 2 percent or less in a properly functioning engine. Our visual 

survey showed more than 25 percent of the trucks observed with opacities of 10 

percent or more, however. Clearly, a large fraction of trucks on the road in 

California are emitting excessive smoke. 

Maintenance questionna ire--Expe rie need professional mechanics and 

other engine professionals would be expected to have reasonably good knowledge 

of the state of maintenance of the "average truck". Where hard statistical 

' 

data are lacking, the consensus of those directly involved in the field may be 

a useful guide; this is the foundation of the so-called ''Delphi" method. In 

order to obtain these professionals' estimates of the frequency of various 

emissions-related defects, Radian prepared a set of questions to be included 

in a survey of diesel engine mechanics and rebuilders that was being conducted 

by another ARB contractor. A total of 103 responses were received to this 

2-7 
RADIAN 

C O a PORA 'I' IO II 

survey. The respondents were asked to estimate (or give their best guess at) 

the fraction of all trucks on the road which exhibit each of a number of 

common types of problems. 

This wording represented a compromise. From the standpoint of 

survey response and reliability. it would have been preferable to ask about 

the incidence of problems in the particular group of trucks that each respondent was responsible for, since respondents could then have answered from 

their own knowledge rather than from their (possibly less reliable) impressions of the industry as a whole. On the other hand. the survey was planned 

to target fleet maintenance managers and heavy-duty truck mechanics. Asking 

about only the vehicles each was responsible for would have biased the estimates downward. since the very existence of a fleet maintenance manager 

implies a significant commitment to proper maintenance. and the worst-maintained vehicles probably seldom see the inside of a truck repair shop. In 

addition, many of the practices asked about are illegal. and it was considered 

likely that respondents would be unwilling to admit to engaging in illegal 

acts. 

A statistical summary of the survey results is given in Table 2-2. 

The minimum. maximum. and median responses, the sample mean. and the upper and 

lower confidence limits (at the 68 percent significance level) for the mean 

are shown for each question. These data tend to confirm the impressions 

developed from the visual smoke survey and from anecdotal evidence. Resetting 

and disabling smoke limiters. increasing maximum fuel settings. and advancing 

the injection timing are considered to be quite common, especially on linehaul trucks. The most common maintenance problems are worn or clogged injectors and clogged air filters. followed by worn turbochargers and pressure 

leaks. Clogged intercoolers and excessive backpressure are considered less 

common. but by no means rare. 

2-8 
RADIAN 

COaii'OaA'I'IOM 

TABLE. 2-2. SURVEY OF DIESEL MECHANICS AND MAINTENANCE MANAGERS: 

QUESTIONNAIRE RESULTS 

Lover S&.ll.ple Upper 

Question Minimum Con. Limit Mean Con. Limit MuimWII Median 

1. Injection Tiaing Advanced 

Line Haul 0 11.1 12.4 13.8 50 10 

Other Turbocharged 0 7.3 8.6 9.9 50 5 

Nat. Aspirated 0 9.8 11.7 13.5 75 10 

2. Injection Timing R.tarded 

Line Haul 0 6.5 7.6 8.6 30 5 

Other Turbocharged 0 5.6 5.8 8.1 40 2 

Nat. A& pirated 0 5.1 6.2 7.3 45 3 

3. Iojectora-Woru or Clogged 

Lioa Haul 0 17.8 20.0 22.1 75 15 

Other Turbocharged 0 18.9 21.1 23.2 75 15 

Nat. Aapiratecl 0 20.1 22.4 24.6 75 20 

4. Saoke-Liaiter a.eet 

Line Haul 0 25.8 28.8 31.9 100 20 

Other Turbocharged 0 15.2 17.7 20.3 80 10 

5. Saoke-Liaiter Diaablad 

Line Haul 0 26.8 29.8 32.9 100 25 

Other Turbocharged 0 15.0 17.4 19.8 80 10 

6. H.u:iaua P'uel •turned op• 

Line Haul 0 21.8 23.7 25.7 80 20 

Other Turbocharged 0 12.3 14.1 15.9 80 10 

Nat. Aapirated 0 15.1 17.2 19.3 90 10 

7. Air Filter Closaad 

Line Haul 0 20.0 21.9 23.9 80 20 

Other Turbocharged 0 21.1 23.2 25.3 65 20 

Nat. Aapirared 0 19.0 21.0 23.1 60 18 

e. Iotercoolar Clogged 

Line Haul 0 5.9 7.0 8.0 60 

Other Turbocharged 0 3.4 4.1 4.9 20 

9. Turbocharger Woru 

Line Haul 0 12.3 13.7 15.2 80 10 

Other Turbocharged 0 11.6 13.2 14.8 80 10 

10. Nonstandard Turbocharger 

tine Haul 0 7.5 8.7 9.9 50 

Other Turbocharged 0 5.0 5.8 6.6 25 

11. Presaura L•ak• 

Line Haul 0 11.6 12.8 14.0 50 10 

Other Turbocharged 0 10.5 11.9 13.3 60 10 

12. Excessive Baekpraaaure 

tina Haul 0 5.3 6.5 7.7 15 

Other Turbocharged 0 5.6 6.9 8.2 15 10 

Nat. Aapirated 0 6 . 2 8.4 10.7 25 10 

Total Responses: 103 

2-9 
RADIAN 

CORPORAYIOII 

2.2 Emissions Impacts of Tampering and Malmaintenance 

To estimate the overall emissions impacts of tampering and mal -

maintenance in diesel engines. a computer model of diesel emissions and 

tampering/malmaintenance effects was constructed. This model deals with four 

general classes of heavy-duty diesel vehicles: heavy-heavy. medium-heavy. 

light-heavy. and transit bus. The model further differentiates between 

out-of-state and California-registered vehicles. and between Californiaregistered vehicles with California and Federal engines. Input data to this 

model included estimates of the baseline emissions for each heavy-duty vehicle 

class and model year. and the frequencies of occurrence and the emissions 

impacts of individual defects. This model is described extensively in Volume 

II. 

The emissions model results for the case with no I/M program are 

plotted in Figures 2-4 through 2-6. These figures display the total annual 

average statewide emissions of NO • unburned hydrocarbons. and diesel particu- x 

late matter from heavy-duty diesel vehicles. expressed in tons of pollution 

per day. These projections are broken down into baseline emissions and excess 

emissions. The baseline emissions level is the amount of pollution that would 

be emitted even if all the engines in use were in good mechanical condition 

with their emission controls performing properly. Excess emissions are 

defined as the increase over and above the baseline emissions level due to 

tampering. malmaintenance. and excessive engine wear. 

As Figures 2-4 through 2-6 show. excess emissions are estimated to 

account for a large and increasing fraction of HC and PM emissi ons. Excess 

NO emissions are estimated to be a smaller fraction of the total. Because X 

heavy-duty diesel NO emissions are so large. however. this excess is still X 

significant for air quality. 

The emissions estimates developed in this study are considerably 

higher than current ARB estimates and projections. This is due to the higher 

2-10 
r"\ 

6 

"'0 

~ c 

0 

..... 

......, 

X 

0 

2 

RADIAN 

CORPORA'I'ION 

EXCESS EMISSIONS MODEL PROJECTIONS 

Statewide NOx Emissions 

500 

400 

300 

200 

100 

0 

1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 

Figure 2-4. 

Year 

Projected Statewide NO Emissions from Heavy-Duty Vehicles X 

2-11 
(.) 

I 

RADIAN 

CO.PO.A'I'IOII 

EXCESS t:MISSIONS MODEL PROJECTIONS 

Statewide HC Emissions 

140 

130 

120 

110 

100 

90 

80 

70 

60 

40 

30 

20 

10 

0 

1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 i995 1996 1997 1998 1999 2000 

Year 

Figure 2-5. Projected Statewide HC Emissions from Heavy-Duty Diesel Vehicles 

2-12 
RADIAN 

COR .. ORAYION 

EXCESS EMISSIONS MODEL PROJECTIONS 

Statewide PM Emissions 

140 

130 

120 

110 

100 

90 

80 

70 

60 

50 

40 

30 

20 

10 

0 

1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 199~ 1996 1997 1998 1999 2000 

Year 

Figure 2-6. Projected Statewide PM Emissions from Heavy-Duty Diesel Vehicles 

2-13 
RADIAN oa~oaaor•o • 

emission factors (grams of pollutant per vehicle-mile travelled) estimated in 

this study. Table 2-3 compares Radian 1 s estimates of fleet-average emission 

factors in several years with those projected by EMFAC7C. The higher Radian 

values for PM are due primarily to the greater in- use deteriora t ion projected 

in this study . The higher NO values are also partly due to the large number X 

of Federally-certified trucks and buses projected to be used in California. 

Tables 2-4 and 2-5 show the breakdown of total and excess pollutant 

emissions between the different classes of heavy-duty vehicles treated in the 

model. As these tables indicate. the lion 1 s share of both total and excess 

emissions are due to heavy-heavy and medium-heavy trucks; light-heavy duty 

vehicles and transit buses are responsible for a relatively minor share. 

Out-of- state vehicles (which are assumed to have Federal engines) are fairly 

significant contributors to the overall emissions levels. but Californiaregistered vehicles with Federal engines are even more significant. Together. 

these groups account for about half of the total heavy-duty diesel emissions 

in California. 

Because of the lack of applicable statistical data to base them on. 

the model projections presented in here contain considerable uncertainty. The 

range of uncertainty in the excess emissions estimates is estimated at -30 

percent to +70 percent of the value shown. while the uncertainty in the total 

emissions is estimated at approximately -20 to +50 percent. 

2-14 
RADIAN 

co•Po•a'I'IDII 

TABLE 2-3. COMPARISON OF RADIAN FLEET-AVERAGE EMISSION 

FACTOR ESTIMATES WITH EMFAC7C 

Radian 

Calendar 

EMFAC7C1 Average of Year All Classes 

1985 

NOx 19.52 22.6 

HC 3.02 4.2 

PM 2.63 5.2 

1990 

NOx 16.90 19.3 

HC 2.72 3.4 

PM 2.35 4.2 

1995 

NOx 15.82 16.3 

HC 2.61 2.4 

PM 1. 66 2.6 

2000 

NOx 13.46 15.0 

HC 2.51 1.8 

PM 1.29 1.7 

1 Source: EMFAC7C pred. for California. April 6. 1986. 

2-15 
RADIAN 

co•~o••,.•o• 

TABLE 2-4. CONTRIBUTIONS OF EACH HEAVY-DUTY CLASS 

TO TOTAL STATEWIDE EMISSIONS 

CONI'RIBUTIONS TO TOTAL STATEWIDE EMISSIONS: 1987 

California Registered Out-OfCalif. Federal State 

Engine Engine Total Vehicles Total 

Oxides of Nitrogen (TPD) 

Heavy 111.7 133.7 245.4 92.5 337.9 

Medium 87.2 30.8 118.0 41.6 159.6 

Light 4.9 0.6 5.4 0.2 5.6 

Bus 16.9 22.7 39.6 o.o 39.6 

Total 220.7 187.7 408.4 134.3 542.7 

Percent 40.7% 34.6% 75.3% 24.7% 100.0% 

Unbu:rned Hydrocarbons (TPD) 

Heavy 23.0 21.4 44.4 12.9 57.3 

Medium 24.3 6.4 30.8 8.6 39.4 

Light 1.6 0.2 1.8 0.1 1.8 

Bus 4.1 1.9 5.9 0.0 5.9 

Total· 53.0 29.9 82.9 21.6 104.5 

Percent 50.7% 28.7% 79.4% 20.6% 100.0% 

Particulate Matter (TPD) 

Heavy 36.0 29.3 65.3 17.4 82.7 

Medium 27.3 6.5 33.9 8.8 42.6 

Light 1.3 0.2 1.4 0.0 1.5 

Bus 2.8 1.2 4.0 o.o 4.0 

Total 67.4 37.2 104.6 26.2 130.8 

Percent 51.5% 28.4% 80.0% 20.0% 100.0% 

~-16 

Percent 

62.3% 

29.4% 

1.0% 

7.3% 

100.0% 

54.9% 

37.7% 

1. 7% 

5.7% 

100.0% 

63.2% 

32.6% 

1.1% 

3.0% 

100.0% 

(Continued) 
TABLE 2-4. (Continued) 

CONI'RIBUTIONS TO TOTAL STATEWIDE EMISSIONS: 2000 

California Resistered Out-OfCalif. Federal State 

Enaine Enaine Total Vehicles Total Percent 

Oxides of Nitroaen (TPD) 

Heavy 128.6 137.1 265.8 87.6 353.4 63.6% 

Medium 97.1 26.7 123.8 33.4 157.2 28.3% 

Light 14.2 1.8 16.0 0.5 16.5 3.0% 

Bus 12.8 15.4 28.2 0.0 28.2 5.1% 

Total 252.8 181.0 433.7 121.5 555.3 100.0% 

Percent 45.5% 32.6% 78.1% 21.9% 100.0% 

Unburned Hydrocarbons (TPD) 

Heavy 14.9 13.8 28.7 7.3 36.1 52.6% 

Medium 16.5 4.4 20.8 5.4 26.3 38.3% 

Light 2.6 0.3 2.9 0.1 3.0 4.4% 

Bus 2.2 1.0 3.3 0.0 3.3 4.8% 

Total 36.2 19.5 55.8 12.8 68.6 100.0% 

Percent 52.8% 28.5% 81.3% 18.7% 100.0% 

Particulate Matter (TPD) 

Heavy 16.8 15.2 32.0 7.8 39.9 63.5% 

Medium 12.1 3.1 15.3 3.9 19.2 30.6% 

Light 1.9 0.2 2.1 0.1 2.1 3.4% 

Bus 1.1 0.5 1.6 0.0 1.6 2.5% 

Total 31.9 19.1 50.9 11.8 62.8 100.0% 

Percent 50.8% 30.4% 81.2% 18.8% 100.0% 

2-17 
TABLE 2-5. CONI'RIBUTIONS OF TOTAL EXCESS EMISSIONS BY 

EACH HEAVY-DUTY VEHICLE CLASS 

CONTRIBUTIONS TO STATEWIDE EXCESS EMISSIONS: 1987 

California Registered Out-OfCalif. Federal State 

Engine Engine Total Vehicles Total 

Oxides of Nitrogen (TPD) 

Heavy 10.7 3.5 14.3 2.8 17.1 

Medium 7.6 1.1 8.7 1.6 10.3 

Light o.o o.o o.o 0.0 o.o 

Bus 1.1 0.1 1.2 0.0 1.2 

Total 19.4 4.7 24.2 4.4 28.5 

Percent 68.0% 16.6% 84.6% 15.4% 100.0% 

Unburned Hzdrocarbons (TPD) 

Heavy 8.8 7.3 16.1 3.1 19.2 

Medium 10.5 2.8 13.2 3.6 16.9 

Light 0.7 0.1 0.8 0.0 0.8 

Bus 1.3 0.6 1.9 o.o 1.9 

Total 21.3 10.7 32.0 6.8 38.8 

Percent 55.0% 27.5% 82.5% 17.5% 100.0% 

Particulate Matter (TPD) 

Heavy 21.8 16.9 38.7 8.8 47.5 

Medium 15.5 3.8 19.3 5.1 24.4 

Light 0.6 0.1 0.7 0.0 0.7 

Bus 1.2 0.5 1.6 0.0 1.6 

Total 39.1 21.3 60.4 13.9 74.4 

Percent 52.6% 28.7% 81.2% 18.8% 100.0% 

Percent 

59.8% 

36.1% 

0.0% 

4.1% 

100.0% 

49.6% 

43.5% 

2.1% 

4. 8% 

100.0% 

63.9% 

32.9% 

1.0% 

2.2% 

100.0% 

(Continued) 

2-18 
RADIAN co••o•aY•o• 

TABLE 2-5. (Continued) 

CONI'RIBUTIONS TO STATEWIDE EXCESS EMISSIONS: 2000 

California Registered Out-OfCalif. Federal State 

Engine Engine Total Vehicles Total Percent 

Oxides of Nitrogen (TPD) 

Heavy 16.2 19.2 35.3 12.5 47.9 72.8% 

Medium 10.0 2.6 12.5 3.3 15.8 24.0% 

Light 1.3 0.2 1.4 0.0 1.5 2.3% 

Bus 0.4 0.2 0.6 0.0 0.6 o. 9% 

Total 27.8 22.1 50.0 15.8 65.8 100.0% 

Percent 42.3% 33.6% 75.9% 24.1% 100.0% 

Unburned Hydrocarbons (TPD) 

Heavy 8.0 6.8 14.8 2.9 17.7 49.3% 

Medium 9.7 2.6 12.2 3.1 15.4 42.8% 

Light 1.5 0.2 1.7 0.1 1.8 4.9% 

Bus 0.7 0.3 1.0 0.0 1.0 2. 9% 

Total 19.9 9.9 29.8 6.1 35.9 100.0% 

Percent 55.4% 27.7% 83.0% 17.0% 100.0% 

Particulate Matter (TPD) 

Heavy 12.0 10.8 22.8 5.0 27.9 63.0% 

Medium 8.9 2.3 11.2 2.9 14.1 32.0% 

Light 1.3 0.2 1.5 o.o 1.5 3.5% 

Bus 0.5 0.2 0.7 0.0 0.7 1.5% 

Total 22.7 13.5 36.3 8.0 44.2 100.0% 

Percent 51.4% 30.5% 82.0% 18.0% 100.0% 

2-19 
RADIAN 

CORPORA910N 

3.0 DEVELOPMENT AND VALIDATION OF I/M TEST PROCEDURES 

Our objective in Tasks Two and Four of the project was to develop 

and validate two inspection test procedures for heavy-duty diesel vehicles: a 

Periodic Inspection and Maintenance Test (PIMT) procedure and a Roadside Smoke 

Opacity Check (ROC). The purpose of each of these procedures is to identify 

heavy-duty diesel vehicles which are producing excessive pollutant emissions. 

The ROC is intended to be used for random enforcement testing. For this 

reason, it was required that it be performable within the physical confines of 

a California Highway Patrol weigh station. The PIMT. as its name implies. is 

intended to be used in a periodic (e.g. annual or biennial) inspection program, analogous to California's existing Smog Check Program for light-duty 

vehicles. The results of these efforts are described in detail in Volume III. 

and are briefly summarized below. 

3.1 Test Procedures 

Many candidate test procedures were considered. Most of these 

procedures appeared to be suitable for detecting one or more types of emissions-related defects. but no single procedure appeared capable of detecting 

all common defects in diesel engines. As a result. the test procedures 

proposed for validation testing included a number of candidate procedures--

more than were considered desirable for the final product. The results of the 

validation testing were used to identify those specific tests among those 

proposed which were most effective in identifying high-emitting vehicles. 

Roadside Smoke Opacity Check 

Candidate procedures for the roadside smoke opacity check were 

limited to those which can reasonably be performed at a truck weigh station or 

other roadside environment. and were thus limited to off-dynamometer. noninvasive procedures. Four candidate procedures were proposed: a quick acceleration in gear; lug-down in gear (manual transmission vehicles only); stall 

3-1 
RADIAN 

CO ... O . AYIOII 

idle (automatic transmission vehicles only); and snap idle. The acceleration 

test procedure for the ROC consists of a full-power (accelerator to the floor) 

acceleration to governor speed in a suitably low gear. Two opacity values are 

recorded: the transient peak opacity, and the stabilized value after reaching 

governor speed. This procedure can be performed on either manual or 

automatic-transmission trucks. 

The snap idle procedure consists of flooring the accelerator with 

the engine idling in neutral, causing it to accelerate to governor speed. 

Since there is no load on the engine except its own friction and inertia. this 

occurs very rapidly. 

recorded. 

Again, both the peak and the stabilized opacity are 

The stall idle procedure is applicable only to vehicles with hydraulie torque converters. It is identical to the snap idle, except that it is 

performed with the gear selector of the automatic transmission set to "Drive" 

rather than neutral, and with the brakes set to prevent the vehicle from 

accelerating. The stalled torque converter absorbs considerable engine power. 

putting a significant load on the engine. Operation in this mode for more 

than a few seconds will overheat and damage the transmission, so caution is 

required. 

The final test procedure proposed was a lug down using the vehicle's 

service brake. This test applies only to vehicles without hydraulic torque 

converters. In it, the driver holds the accelerator down with one foot, while 

pushing on the brakes with the other in order to load the engine. Since full 

engine power is absorbed in the brakes, this test must not be prolonged beyond 

a few seconds. Even so, it places great stress on the brakes, driveline, and 

transmission. 

Smoke opacity in any of these tests could be judged either with an 

opacimeter on the stack or by a trained observer. For mass testing, the most 

3-2 
RADIAN 

CORPORA'I'IO N 

efficient approach would be to make a "first cut 11 by visual observation. with 

subsequent opacimeter testing for confirmation in marginal or disputed cases. 

Periodic Inspection Procedure 

The candidate inspection procedures proposed for the periodic I/M 

test are listed in Table 3-1. These procedures were intended to be performed 

in a diesel repair shop or similar facility. The proposed PIMT consists of 

visual and functional checks of emissions control equipment. together with 

smoke opacity measurements under acceleration. lugdown. and road-load conditions. HC and NO concentration measurements in specific modes were also X 

included in the candidate procedures. in order to evaluate their usefulness. 

In developing these tests. we had to decide whether or not to base 

them on a chassis dynamometer or some other loading technique. Chassis 

dynamometers capable of loading a heavy-duty truck in steady-state operation 

typically cost $100.000 to $200.000 installed. and not all truck repair 

stations have them. Heavy-duty truck dynamometers with transient capabilities 

are even more expensive. and are found only in a few resea r eb organizations. 

A decision to rely on dynamometer tests would exclude many diesel repair shops 

from performing I/M tests. On the other hand. the need to t est for excessive 

smoke emissions under load. and the greater controllability and repeatability 

of dynamometer loading compared to alternative means argued for a dynamometerbased procedure. 

Contacts with dynamometer manufacturers revealed t hat enough chassis 

dynamometers were already in use in California to handle the anticipated test 

load. Obviously. many of these facilities are presently used for other 

activities and thus would not be available full time for I/M testing. but this 

large number of facilities now in use suggested that any others that might be 

needed could be built fairly readily . Thus. it was decided to develop test 

procedures based on the use of a chassis dynamometer. 

In addition to a chassis dynamometer. we assumed that something 

analogous to the automatic Test Analyzer Systems (TAS) used in light-duty I/M 

3-3 
RADIAN 

CORPORATIO• 

TABLE 3-1. PROPOSED PERIODIC I/M TEST PROCEDURES 

VISUAL/FUNCTIONAL INSPECTION 

Air filter "pop-out" indicator 

for excessive restriction 

Air supply and exhaust system for 

restrictions and leaks 

EGR valve (if fitted) 

Fuel injection pump adjustment seals 

Fuel supply system, pump, lines, and 

injectors for leaks 

Electronic control trouble lights 

Electronic control system computer, 

sensors, and actuators 

Trap-oxidizer system (if fitted) 

Oxidation catalyst (if fitted) 

DYNAMOMETER TEST PROCEDURES 

Full-power acceleration 

Lug-down--maximum torque at 

100% rated speed 

90% rated speed 

80% rated speed 

70% rated speed 

60% rated speed/max torque speed 

Road-load--75% torque at 

100% rated speed 

90% rated speed 

80% rated speed 

70% rated speed 

60% rated speed/max torque speed 

NOx concentration 

HC concentration 

3-4 
RADIAN 

C O R PORA Y IO N 

programs would be available for an I/M program. In addition to . logic and 

recording capabilities, this system was assumed to be capable of measuring 

exhaust smoke opacity, and (optionally) HC and NO concentrati ons. Prelimi- x 

nary inquiries with several instrumentation suppliers indicated that such a 

system would be well within the present state of the art, and that it could 

probably be sold at a price comparable to the more expensive of the TAS 

analyzers now used in California's Smog Check Program for light-duty vehicles. 

Detailed specification or development of such a system was not attempted in 

this project, however. 

3.2 Validation Testing 

Validation testing of the Roadside Opacity Check (ROC) and Periodic 

I/M Test (PIMT) procedures was accomplished · in two stages. In the first 

stage, Radian and ARB staff applied the proposed ROC to 52 heavy-duty diesel 

trucks belonging to various government agencies, one private utility. and a 

commer~ial used-truck dealership. Based on the screening results, eleven of 

tp.ese ,trucks were brought into ARB 1 s Haagen-Smit laboratory for additional 

. testing, including both the PIMT procedure and gaseous and particulate emis-

. easurements. 

about 25 percent. The failure rates for the other procedures were quite 

variable--ranging from 14 percent for the stall idle peak to nearly 50 percent 

f9x the lugdown test. The latter value is probably unrepresentative, due to 

3-5 
.... 

jl 

>-

1-

u 

4( 

(l. 

0 

UJ 

~ 

0 

:E 

(/') 

RADIAN 

CORPORATIO• 

ACCELERATION PEAK 

100 , 

Failure Criterion: 354!1. Opacity 

90 - Pass 39 754!1. p 

Fail 13 25 .. v 

80 - Total 52 100, ' 

70 -

v 

60 v -

50 - v 

40 v - 1/ 

-------·· ···-- 30 - ~ 

v v v 

v v 

20 - I/ 1/V v 

vv v 

10 

a 

vv~~ - P' 

I~ IR~P1 · IRv ~v v ' I-' vv v v I~ 1.-1 k ' vv vv IP V1v v v v[rJ k 

., I I I I I I I I I I I I I 

*Vehicle selected for testing at Haagen-Smit Laboratory. 

Figure 3-1. Bar Chart of Peak Acceleration Smoke 

Opacities from the Field Screening 

3-6 

1/ 

v v 

v 

VV ' 

~ / 

' 

.. · ,. . ' 

' ' ' 

I I I I I 
RADIAN 

CORPORA'I'ION 

the significant problems encountered in performing this test. and the fact 

that many of the high opacities measured were not confirmed in subsequent 

dynamometer testing. 

Testing problems--Aside from the usual problems of field measurement 

on vehicles. no significant problems or concerns were experienced in conducting the stall idle or snap idle tests. These two tests could be conducted 

with the vehicle standing still. With the full-power acceleration test. it 

was necessary to have sufficient room to accelerate--and to slow down afterwards--without undue risk. A1 though no incidents were experienced in our 

screening tests. safety and the provision of an appropriate test area would be 

a concern in any widespread application of this proce~ure. 

The acceleration/lug-down test used with manual- transmission vehicles required even more space than the acceleration alone. since the engine 

must run at near rated speed for several seconds during the lug-down. The 

effects of this operation on safety (especially in a congested area such as a 

truck depot) would be a significant concern. Shortage of space often resulted in the drivers having to apply the brakes too quickly to give a smooth 

reduction in engine speed. This led to "overshooting" the target of 60 

percent of rated speed. and often caused stumbling and considerable excess 

black smoke as the engine was lugged down below its peak torque point. resulting in poor repeatability. This test also places considerable strain on the 

engine. brakes. and transmission. and could cause the drive tires to spin in 

some high-powered trucks. 

PIMT and dynamometer emissions testing 

On the basis of the screening tests described above. eleven trucks 

were selected for more extensive testing at ARB's Haagen-Smit Laboratory. The 

screening test results for thes·e trucks are indicated by the asterisks in 

Figure 3-1. These trucks were delivered to the laboratory one at a time to be 

tested using the smoke opacity tests from the Periodic I/M Test (PIMT) 

3-7 
RADIAN 

C0-~0-A'I'IOII 

procedure. and a modified chassis-dynamometer ve r s i on of the Federal 13-mo'de 

emissions test procedure. The latter test included measurements of HC, CO, 

NO • and particulate emissions, fuel economy. and road horsepower (power X 

delivered to the dynamometer rolls). Concentrations of HC. CO, co2• and NOx 

in the raw exhaust were also measured and recorded, 

The emissions testing at Haagen-Smit Laboratory used a chassis 

version of the old Federal 13-mode test. which is a steady-state test procedure. Since transient effects on HC and PM emissions are important, the 

current Federal test procedure involves operation over a transient test cycle. 

The heavy-duty dynamometer at the Laboratory was incapable of generating 

reproducible transient conditions, howeve-r, so that transient emissions 

testing couid not be performed in- this study. This undoubtedly affected the 

results. ARB and the Southern California Rapid Transit District are currently 

cooperating on the development of a heavy- duty chassis dynamometer with 

transient emissions testing capability, and it is recommended that this or a 

similar facility be used in any further studies in this area. 

Based on the results of these tests, six of the higher- emitti ng 

trucks in the sample were sent out for diagnosis and repair of emissionsrelated mal functions. These trucks were then returned to the laboratory for 

another round of testing. 

Analysis of Test Results 

The statistical analysis of the data generated by the validation 

testing program addressed four main issues. 

• How do visual smoke opacity estimates compare to opacity values 

measured with an opacimeter? 

• How well do smoke opacity values correlate with particulate 

emissions? 

3-8 
RADIAN 

ca••a •A'I'IO II 

• Which smoke opacity tests are most effective in identifying 

high particulate and HC emitters, and how effective are they? 

• How we l l can composite NO and HC emissions over the entire X 

test cycle be, predicted from concentration data for individual 

modes? Are these relationships strong enough to identify 

excess emitters reliably? 

Visual vs. Measured Smoke Opacity--Figures 3-2 and 3-3 contain cross 

plots comparing the smoke opacity measured with the opacimeter with the visual 

opacity estimate for two test modes: acceleration peak and snap idle peak. 

Each of the visual and opacimeter values plotted is the average of two test 

for two test runs. For each figure, the opacimeter measurement is plotted on 

the horizontal axis, and the visual estimate on the vertical axis. Crosshairs indicating the failure criterion for that mode are also shown on each 

plot. As these figures indicate, the correlation between the estimated and 

measured value is fairly strong, and the RMS error in the estima t es was of the 

order of 10 percent opacity for bot~. 

These data indicate a · fair degree of correspondence between the 

visual opacity estimates and the opacimeter data in the moderate-to-high 

opacity range. This range is the one of greatest interest for smoke observation. It was much harder to estimate smoke opacities accurately in the lower 

opacity range, and a greater number of significant errors occurred. Relatively few of these errors would have changed the outcome of an I/M test, however, 

as the small populations in the upper left and lower right quadrants of the 

plots indicate. These data indicate that a visual screening approach could 

be feasible with the ROC, which would greatly simplify its implementation in 

the field. An officer could distinguish passing from failing levels by eye in 

most cases. Marginal or protested cases could then be confirmed using an 

opacimeter. 

3-9 
RADIAN 

CORPORATION 

ACCELERATION PEAK 

100 

90 

80 

...... 70 ~ ...... 

w 

t- 60 0 

.: 

~ 

(/) 

t= ~ 0 0 

w 

~ 

.: -40 :;:) 0 Q I 

~ 

> 

,)() 

a a 

20 

D Ra.0.90 

10 RMS Errora10.2., Opacity 

0 

0 20 40 60 80 100 

OPACIMETER MEASUREMENT(") 

Figure 3-2. Visual vs. Measured Smoke Opacity (Acceleration Peak) 

3-10 
RADIAN 

CORPORATIOR 

100 

ga 

eo 

...... 7a ~ ..... 

z 

Q 80 ... 

oo( 

~ !50 i= 

en 

w 

~ 4a 

< 

:::> 

en 

> .30 

2a 

la 

a 

a 

SNAP IDLE PEAK 

0 

0 

0 0 

0 

0 

0 c c 

R••0.95 

RMS Error•8 .6% Opacity 

2a 4a sa 

OPACIMETER MEASUREMENT(%) 

Figure 3-3. Measured vs. Visual Smoke Opacity 

(Snap ldl·e Peak Readirtg) 

3-11 

80 100 
RADIAN co••o ••••o• 

Correlation of Smoke Opacity With Particulate Emissions--Correlation 

and multiple linear regression analyses were performed, comparing the smoke 

opacity data from the PIMT with cycle-composite particulate emissions from the 

chassis 13-mode cycle. Perfect correlation was not anticipated, as it was 

known that some problems (e.g. misset smoke limiters) can lead to very high 

peak smoke opacities. while having only a moderate effect on cycle-composite 

emissions (indeed, the acceleration smoke limiter should have had no effect on 

PM emissions in these steady-state tests). 

Correlation analyses indicated that the best predictors of 13-mode 

PM emissions were the smoke opacity at the maximum torque point (lug-down 

smoke). 75 percent power at rated speed (road load smoke). and 100 percent 

power at rated speed (maximum power smoke). Surprisingly (given the steadystate test cycle) acceleration peak smoke also turned out to correlate reasonably well with PM emissions. Subsequently. regression analyses were carried 

out using lug-down. road-load. and acceleration peak smoke opacities. The 

results for the lug-down and acceleration peak regressions are plotted in 

Figures 3-4 and 3-5. 

The best one-variable model for PM emissions was the one having 

lug-down smoke opacity (Old) as the independent variable. R2 for this model 

was calculated as 0.60. indicating only fair correlation. The results of this 

model are plotted as the dashed line in Figure 3-4. 

Examination of Figure 3-4 shows that the visual fit of the data 

could be substantially improved if the two points marked PASADENA-02 were 

excluded. These points represent before and after-repairs measurements on one 

truck. This truck had the only automatic transmission in the group. and was 

later found to be suffering from overheating. due to the installation of an 

incorrect cylinder head gasket. Either or both of these could have affected 

the correlation between smoke and PM emissions. However. repeating the 

regression without these two data points did not improve the statistical fit. 

The results of this calculation are plotted as the solid line in the figure. 

3-12 
RADIAN 

CORPORA910M 

0.9 

0.8 

...... ... 

.c. 0 .7 I 

~ 

l: 

a: 0 .6 -

Q 

~ 

~ 0 .5 

UJ 

... 

Ci) 0.4 

0 

ll. 

~ 

0 0 .3 

u 

0.2 

0 .1 

0 

0 

0 

0 

10 

0 

0 

- PASADENA-02 - ------ ----- - ....a 

//" 

~·· ./" ... ........... ./". ...... __ , .. .-.... --· ... 

20 

Dashed line: 

PM-<>.326.0.0 144 0 ld 

R 2 =0.61 

Solid Line: (excluding P~2) 

Pt-1•0.319.0.0124 Old +0.303 Dt 

R2 • 0.53 

30 

LUGOOWN SMOKE OPACITY (%) 

Figure 3-4. Particulate Emissions vs. Lug-Down Opacity 

3-13 

40 
RADIAN 

caaPaaA't'ION 

_-a 

0 .9 _....PASAOENA-02- -- ...-

0.8 o¥ 

....... 0 ... 

.s::. 0 .7 I 

c.. 

J: 

a: 

- 0 .6 Cll 

...... 

:E 

c.. 0 .5 0 

w 

t: 

(/) 

0 0 .4 

c.. 0 

:E Dashed Line: 0 0 . .3 0 

(.) PM•0.375+0.00284 Oacc 

R2s 0.19 

0 .2 

Solid Line: (excluding P~) 

0 .1 PMa0.3544oQ.00209 Oacc •0.415 Dt 

R2•0.20 

0 

0 20 40 60 80 100 

ACCEL SMOKE OPACITY {%) 

Figure 3-5. Particulate Emissions vs. Acceleration Peak Smoke Opacity 

3-14 
RADIAN 

CO R PORA'I'ION 

Part of the reason for the poor fit is undoubtedly the limited range of PM 

emissions data in the remaining sample. 

Figure 3-5 is a plot of acceleration peak smoke opacity (0 ace) vs. 

part ic ula te emissions. As this figure shows. the correlation is rather 

poor--the best fit model has an R 2 value of only 0.19. This model is plotted 

as the dashed line in Figure 3-5. Again , the exclusion of data for truck 

PASADENA-02 had little effect on the quality of the fit (plotted as the solid 

line in the figure). This poor correlation is not surprising, since several 

of the trucks exhibiting high transient smoke emissions during acceleration 

had rather low steady-state emissions, and these are what would have been 

measured in the steady-state emissions tests performed. 

Effectiveness in Identifying Excess Emitters--Table 3-2 shows the 

results of a pass/fail analysis of the 14 data points from the validation 

testing for which both particulate and smoke ~asureinents were available. 

This table shows the number of "true positive", "false positive", "true 

negative" and "false negative" results generated by each test mode. A "true 

positive" is a high-emitting vehicle which fails the smoke opacity test; a 

"false positive" is a low-emitting vehicle which fails. Similarly, a "true 

negative" is a low-emitting vehicle which passes the test; and a "false 

negative" is a high-emitting vehicle which passes . False positives and false 

negatives cor·respond to errors of commission and errors of omission, respectively. For this analysis, "high-emitting" vehicles were defined as those 

having either PM or HC emissions in excess of 0. 6 g/RHP-hr in the 13-mode 

emissions test. 

Table 3-2 also shows the percentage of the total excess HC and PM 

emissions identified by each of the tests. Consistent with the definition of 

a "high emitter", "excess" emissions were defined as those exceeding 0.6 

g/RHP-hr for either HC or PM. As the table shows. several of the smoke 

opacity tests were equally effective in identifying high particulate emissions, but the acceleration peak and snap idle peak were the most effective in 

3-15 
RADIAN 

C ORPORA'I',ON 

TABLE 3-2. EFFECTIVENESS 

HIGH EMITTERS 

ilitpoint 

Test (<1>acity) 

Accel Peak 35% 

Accel Stabilized 6% 

&lap Idle Peak 35% 

Snap Idle leY% 

Stabilized 

Lug--J::b.m 2fJ%, 

Road Load 5% 

* Error of omission 

** Error of commission 

True 

Neg 

4 

6 

3 

6 

6 

6 

OF SMOKE OPACITY TESTS IN IDENTIFYING 

Percentage of Excess 

False* False'<* True Fmi.ssions Detected 

Neg Pos Poo Total R1 HC 

3 2 5 14 71% 67% 

7 0 1 14 1~ 251Z 

4 3 4 14 71.% 5~ 

6 0 2 14 71.% 351Z 

6 0 2 14 71.% 351Z 

8 0 0 14 (J% 0% 

3-16 
RADIAN 

CORPORAYIOII 

identifying high HC emissions. The acceleration peak test also had the fewest 

false negatives of any of the tests. In addition, two false positives (errors 

of commission) with the acceleration test should not really be considered as 

such. Each of the trucks in question exhibited transient smoke levels high 

enough to be offensive, and would likely have exhibited higher-than-normal 

transient particulate emissions, even though its steady-state particulate 

emissions were low. 

Modal NO and HC Concentrations vs. Emissions--In developing our 

recommended test procedures, we speculated that measurement of exhaust gas NO X 

and HC concentrations in specific operating modes might be useable for identifying vehicles emitting excessive amounts of these pollutants. This approach 

is used in nearly all I/M programs for spark-ignition vehicles. In order to 

evaluate the effectiveness of this type of test for heavy-duty diesel vehicles, we performed a linear regression analysis to compare the modal emissions 

concentrations to the cycle composite values. The results of this analysis 

showed that the NO concentration in mode 4, alone, gave the best correlation X 

with the cycle composite NO • This relationship is shown in Figure 3-6. For X 

HC emissions, the linear regression analysis indicated that a combination of 

HC concentrations in modes 6 and 14 gave the best prediction of 

cycle-composite HC emissions. A cross plot of actual HC emissions vs. emissions predicted by this model is given in Figure 3-7. 

3.3 Analysis of the NYCDEP Database 

The validation test results showed a statistically significant 

relationship between smoke opacity measurements and particulate emissions 

measured under steady-state conditions. A larger database was considered 

desirable, however, in order to increase our confidence in the statistical 

validity of the procedures. In addition, it was considered very desirable to 

assess the correlation between smoke opacity and transient HC and particulate 

emissions, since actual vehicle operation is characterized by mostly transient 

conditions. 

3-17 
RADIAN 

co ... o ...... o .. 

H 

13 

12 

11 

,.. 

.... 10 .c 

I 

0.. 9 ~ 

a: 

-

01 8 

-

X 

0 7 

z 

w 

..... 6 

(i) 

0 5 

0.. 

::::E 4 0 

0 

3 

2 

0 

0 

Figure 3-6; 

0 

0 

0 

0 

0 

0 

0 

NOx•0.636+0.0178ppm,. 

R2•0.76 

200 400 

MODE 4 NOx CONC. (PPM) 

NO · Emissions vs. Mode 4 Concentrations X 

3-18 

600 
RADIAN 

CORPORATIO• 

BASED ON MODES 6 AND 14 

1 2 ~--------------------------------------------------------------~ 

1 1 

0 .9 

--.c 

I 0 .8 ll. 

~ 

a: 

..... 

Cl 0 .7 

D 

0 

0 

00 

0 

-(.) 

~ 06 0 0 

0 

w 

a: O.!i 

0 

::I 

C/) 

~ 0 .4 

W · 

~ 

0 .3 

0 .2 

HC-o. 150.0.028ppm1•0.00066ppm. 

0 .1 R2.0.73 

0 

0 02 0.4 0 .6 0 .8 1 2 

PREDICTED HC. {g/RHP-hr) 

Figure 3-7. Predicted vs. Actual HC (Based on Modes 6 & 14) 

3-19 
RADIAN 

CORPORA'I',OII 

A suitable database was made available by the Frost Street emissions 

laboratory of the New York City Department of Environmental Protection 

(NYCDEP). This database consists of more than 315 emissions tests on 133 

diesel buses, and another 118 tests on 20 heavy-duty diesel trucks. To our 

knowledge. this is by far the largest collection of in-use diesel emissions 

data ever collected. 

Our statistical analysis of the NYCDEP database followed the same 

pattern as the validation test analysis. Single and multiple linear regression were used to establish the relationship between smoke and particulate 

emissions. The results of these regressions are shown in Figures 3-8 through 

3-10. showing the relationship between smoke opacity and particulate emissions 

in three different emissions test cycles. A strong positive correlation 

between smoke opacity and particulate emissions is clearly visible in all 

three figures. 

In addition to the linear regression analyses, a pass/fail analysis 

was performed using the same failure criteria as for the validation testing. 

The effects of two I/M tests were simulated: acceleration opacity and roadload cruise opacity. Buses were classed as passing or failing an I/M test 

based on their opacity measurements; and as low or high emitters based on 

their emissions on the NYB-2 cycle. Our analysis compared the numbers of high 

and low emitters which passed or failed the simulated I/M test, using two 

different levels of stringency. Table 3-3 shows the results of this analysis. 

For the bus fleet tested. using the less stringent failure criteria, 

69.3 percent of the buses were low emitters. and all of these passed the I/M 

test (there were no false positives). The remaining 30.7 percent of the buses 

were classed as high emitters. Of these, more than two-thirds (20.8 percent 

of the total) also passed the I/M test, causing them to be classed as false 

negatives. Only 9.9 percent of the buses failed the I/M test. However, this 

small group accounted for more than 68 percent of the total excess particulate 

emissions and 80 percent of excess hydrocarbon emissions for the entire fleet. 

3-20 
RADIAN 

CORPORA'I'IOII 

40 

35 

..... 

·e 30 ...... 

Cl ..., 

a: 

LIJ 

~ 

25 

~ 

< 

~ 

LIJ 20 ~ 

< ..J 

::I 

u 15 

i= 

a: 

< 

ll. 10 

5 

0 

0 20 

NEW YORK BUS 2 CYCLE 

0 

D 

0 PM (g/mi)•1 .78.0.417 Oacc 

R2•0.89 

40 60 80 

ACCELERATION SMOKE OPACITY (%) 

Figure 3-8. Acceleration Smoke Opacity vs. Particulate Emissions 

(New York Bus 2 Cycle) 

3-21 
8 

7 

6 

-

.E 

5 ....... 01 

-

a.. 0 4 w I 

N w 

N a: 

:::> (J) 

3 c( w 

2 

1 

a 

I I DO 

I 

...... 

a 

Fi gure 3-9. 

NEW YORK BUS COMPOSITE CYCLE 

07 

2 

0 

0 0 

4 

PM•0.64+0.137 Oacc•0.134 O

R2 •0.71 

6 

PREDICTED PM (g/mi} 

Actual particulate emissions v s . emissions pred1ctea 

acceleration and cruise mode opacities: New York Bus Com

Cycl e . 
-

E 

....... 

Ol 

-

a. 

VJ 0 I 

N w 

VJ a: 

::> 

fJ) 

c( 

w 

8 

7 

6 

5 

4 I 

I n 

3 

2 

0 

1 

NEW YORK TRUCK CYCLE 

0 

/ 0 

0 

0 

D 

PM•1.63+0.0036 Oacc•0.231 O

0 

0 2 4 6 

PREDICTED PM (g/mi) 

Figure 3-10. Actual particulate emissions vs. emissions predicted fr

acceleration and cruise mode opacities: New York Truck Cycle. 
RADIAN 

CORPORA'I'IOII 

TABLE 3-3. PASS/FAIL ANALYSIS FOR TWO SETS OF I/M FAILURE 

CRITERIA: NEW YORK BUS DATABASE 

True Negative 

False Negative 

False Positive 

True Positive 

Total 

Original Failure Criteria 

0 > 35% or 0 6% 

ace crs 

No. of Percent 

Veh. of Veh. 

147 69.3 

44 20.8 

0 0.0 

21 9.9 

212 100.0 

Percent Excess Emissions Detected 

Revised Failure Criteria 

0 > 15% or 0 > 3% 

ace crs 

No. of Percent 

Veh. of Veh. 

True Negative 139 65.6 

False Negative 34 16.0 

False Positive 8 3.8 

True Positive 31 14.6 

Total 212 100.0 

Percent Excess Emissions Detected 

3-24 

Mean Emissions 

(NYC Bus 2) 

PM HC 

3.08 

8.21 

26.67 

68.5% 

7.90 

10.98 

37.53 

80.8% 

Mean Emissions 

(NYC Bus 2) 

PM HC 

3.04 7.89 

7. 17 10.71 

4.28 7.96 

20.71 29.26 

80.9% 83.4% 
RADIAN 

CO II!It OII! A WIO II 

Mean emissions from the failing group were 26.7 g/mi of particulate, which is 

nearly nine t i mes the mean for the low-emitting group, and three times the 

mean for the false negative group. Thus, while these tests did not detect all 

high emitters, they did detect the highest emitters, which account for most of 

the excess emissions. 

Examination of the bus data, as well as the results of work for ARB 

indicated that, for buses the failure criteria for smoke opacity could be made 

considerably more stringent than our initial proposals. Accordingly, the 

above analysis was redone using failure criteria of 15 percent opacity in 

acceleration mode and 3 percent opacity in cruise. This reduced the percentage of false negatives from 20.8 to 16 percent, increasing the number of true 

positives by the same amount. At the same time, however, eight false positive 

tests (low-emitting vehicles which failed the I/M test) were also created. 

All of these failed only in the acceleration mode--none failed the cruise mode 

test. The term "false positive" is thus somewhat of a misnomer, as each of 

these buses was emitting mildly offensive levels of visible smoke on acceleration, even though their overall particulate levels were not excessive by our 

definition. 

3.4 Conclusions and Recommendations 

Based on the test data and analysis presented here, the following 

conclusions and recommendations can be made. 

Roadside Opacity Check 

• The acceleration smoke opacity test appears to be the most 

effective of the four candidate procedures proposed for the 

ROC. However, a change in instrumentation to measure the 

"average" rather than the peak opacity might improve the 

correlation with emissions and should be investigated further. 

This test also has the advantage of being applicable to either 

3-25 
RADIAN 

CORPORA'I'IOII 

manual or automatic transmissions. The stall idle test invalves very similar operating conditions and produces similar 

results. It appears to be an acceptable alternate test for 

vehicles with automatic transmissions. 

• The proposed failure criterion for peak opacity in the acceleration and stall idle tests was 35 percent (or 5 percent over 

the Federal Peak certification, if that is higher). Based on 

our limited data, this appears to be appropriate for trucks, 

and we recommend that it be retained. Alternatively, an 

opacity cutoff of 50 percent (equivalent to the Federal Smoke 

Test criterion) could be used. This would result in a much 

lo~r failure rate, and some trucks with visually offensive 

smoke levels would pass. However, the higher cutoff should 

still suffice to identify gross emitters. Buses appear to be 

capable of meeting a more stringent failure criterion of 15 

percent peak smoke opacity. 

• Some trucks may exhibit high transient peak smoke opacity, even 

though their overall PM emissions are moderate. Thus, the 

acceleration test could be expected to generate a significant 

number of "errors of canmission" if only PM emissions (and not 

visible smoke) vrere the issues of concern. However, all 

vehicles subject to such "errors of commission" would still be 

exhibiting visually offensive smoke. In a program concerned 

with both smoke and PM emissions, these could not ·be considered 

errors of commission. 

• Separate failure criteria were proposed for stabilized smoke 

opacity in the acceleration and stall idle tests. Based on the 

New York City database. these modes can identify some additional high emitters, but they also create a disproportionate 

number of errors of commission. We recommend omitting these 

test criteria from the final procedure. 

3-26 
RADIAN 

CDRPDRA'I'IOII 

• The snap idle test procedure is easier and requires less space 

to perform than the acceleration test. but the results correlate poorly with em is sions--resul ting in a greater number of 

errors of commission. It appears that some engine designs are 

more sensitive than others to the unrealistic operating conditions involved. We recommend against general use of this test, 

although it may be useful for specific classes of vehicles such 

as buses. 

• The lug-down test procedure using the vehicle's service brakes 

is difficult to perform, shows poor repeatability. and is less 

effective than other procedures in identifying high emitters. 

We recommend that this test be dropped. 

• Visual estimates of smoke opacity--even when performed by 

persons without formal training in opacity estimation--were 

found to correlate well with the values measured with the 

opacimeter. Since no equipment or contact with the vehicle is 

required, visual estimation is much faster than opacimeter 

measurements. We recommend that this approach be used for 

initial screening in ROC, with doubtful or protested cases 

being resolved by retesting with an opacimeter. Using this 

approach, it would be possible to screen essentially every 

truck passing through a truck weigh station or similar 

facility. 

Periodic I/M Test 

• Peak smoke opacity during acceleration correlates fairly well 

with particulate emissions under transient operating conditions. The acceleration peak opacity is also a good measure of 

offensive in-use smoke. The acceleration test showed good 

repeatability, and was the most effective test for identifying 

3-27 
RADIAN 

COaPOaA~IOII 

high hydrocarbon and particulate emitters. both in the Task 

Four tests and the NYCDEP data. We recommend that this test be 

included in the PIMT. 

• The addition of smoke opacity in road-load cruise to the peak 

smoke opacity significantly improved the correlation between 

smoke measurements and particulate emissions in the NYCDEP 

databases. This test also identified some high-emitting 

vehicles in the NYCDEP data base which passed the acceleration 

test. and it generated no errors of canmission. We recommend 

that this test be included in the PIMT as well. 

• The failure criterion proposed for the dynamometer acceleration 

test in the PIMT was 35 percent peak opacity. or 5 percent over 

the Federal certification value if that is higher. This 

criterion appears to be appropriate. For the road load cruise 

test. the proposed failure criterion was 5 percent opacity. 

This appears slightly lax--a cutoff of 4 percent opacity at 75 

percent power and rated speed appears more appropriate. 

• Peak lug-down smoke opacity also correlates well with steadystate emissions. but we have no data ·to assess its correlation 

with transient results. This test identified fewer high emitters in the Task Four testing than did the acceleration test. 

and did not identify any high emitters that the acceleration 

test missed. In a larger sample. however. this might not have 

been true. This test is also clearly related to on-road smoke 

emissions in full-power operation. We recommend that this test 

be included in the PIMT. 

• As discussed above for the ROC. the snap idle test correlates 

poorly with emissions. and generates more errors of canmission 

than the acceleration test. This is apparently due to design 

3-28 
RADIAN 

C DRPORA 'I' ID II 

features which make sane engines more sensitive to this test 

than others. We recommend that this test be dropped from 

consideration for general use. although it may still prove 

useful with specific makes of engines. 

• NO concentrations in modes 4 and 5 (50 percent and 75 percent X 

power at rated speed) of the chassis dynamometer test correlate 

well with cycle composite NO emissions. This measurement X 

could be used to identify vehicles with excessi ve NO emissions X 

due to tampering or improper replacement of fuel injection 

pumps. We recommend that this measurement be included in the 

PIMT. 

• The combination of HC emissions in modes 6 (full power/rated 

speed) and 14 (no load/governor speed) correlat es well with 

cycle-composite HC emissions measured in the 13-mode cycle. 

Further research will be needed to determine whether this 

correlation will hold for HC emissions in transient operation. 

but we consider it likely that this will be the case. We 

recommend that this measurement also be included in the PIMT. 

General 

• The data and analysis presented here demonstrate the technical 

feasibility of identifying heavy-duty diesel vehicles which are 

excessive emitters. by means of simple tests based on smoke 

opacity and (possibly) NO and HC concentrations. X 

• Further work with a larger truck sample is needed to refine the 

failure criteria. to improve estimates of the failure rates and 

emissions reductions from repaired vehicles. and to better 

define the 

particulate 

relationships between 

and HC emissions. To 

3-29 

smoke opacity and in-use 

reflect actual operating 
RADIAN 

c oaPoa A 'I'ION 

conditions, this work should be conducted using a transient 

test cycle on a suitably-equipped chassis dynamom=ter. As a 

possible alternative, techniques for mass emission measurements 

on vehicles in normal use might be developed . 

In this further testing, steps should be taken to obtain a 

random sample of trucks in use, rather than relying on volunteer fleets. The volunteer (primarily publicly-owned) fleets 

in our test program exhibited much lower smoke than observed in 

the visual smoke survey. This probably reflects significantly 

better maintenance than the average. A realistic assessment of 

in-use emissions must include the occasional "gross" emitter, 

which is unlikely to be found in a well-maintained fleet. 

3-30 
RADIAN coa•oa A 'I'IO N 

4. 0 COSTS. EMISSION REDUCTIONS. AND COST-EFFECTIVENESS OF ALTERNATIVE 

HEAVY-DUTY DIESEL I/M PROGRAMS 

In Task Three of the project. Radian estimated the costs and emission reductions due to various alternative approaches to heavy-duty diesel 

I/M. and evaluated the cost-effectiveness of each. This task was the last one 

completed. The results of this Task are presented in Volume IV. and briefly 

summarized below. 

4.1 Procedure 

After analysis of the results of Tasks One and Four. Radian defined 

a number of alternative I/M scenarios for further investigation. A simple 

model of I/M program effects on the frequency of occurrence of each type of 

emissions defect was developed. and used to prepare revised estimates of 

defect frequency for input to the heavy-duty diesel emissions model described 

in Volume II. The I/M effects model also calculated the average repair costs. 

probability of requiring repairs. and the probability of being fined for 

tampering for each vehicle class under each I/M scenario. These were used to 

estimate the costs of each type of program. 

Design of an inspection and maintenance program for heavy-duty 

diesel vehicles presents many difficult issues. Because of the differences in 

technology. ownership. and operating patterns. existing I/M programs for 

light-duty vehicles may not be a good model for heavy-duty diesel I/M. Other 

existing enforcement programs aimed at heavy-duty trucks (such as CHP weigh 

stations and safety inspection programs) should be considered as models as 

well. 

In order to effectively reduce emissions. while minimizing the 

burden on vehicle owners. the primary goals of a heavy-duty diesel I/M program 

should be the following: 

4-1 
RADIAN 

CORPOR.YIOII 

• deter tampering with emission controls; 

• detect tampering which is not deterred, and require that it be 

corrected; 

• identify gross-emitting vehicles, and require that they be 

repaired; and 

• encourage proper maintenance and awareness of the importance of 

emission controls in the bulk of the heavy-duty diesel fleet. 

The I/M program scenarios investigated in this study were chosen 

with these goals in mind. They consist of a number of variations on two basic 

approaches: a dynamometer-based periodic I/M program, and a program of in-use 

smoke opacity enforcement and random anti-tampering inspections. 

scenarios are summarized in Table 4-1. 

These 

elements. 

Case 1, the basic periodic I/M scenario, consists of the following 

• Periodic, annual inspections enforced through the registration 

process. 

• Decentralized, garage-based inspection program. using chassis 

dynamometer test procedures for smoke opacity and gaseous 

pollutant concentration in specific operating modes. 

• Visual or functional check of emission control such as EGR 

valves, trap bypass valves, timing advance units, etc. 

• Anti-tampering inspection of trap-oxidizer, catalytic converter, fuel injection system seals, etc. 

4-2 
RADIAN 

CORPORA'I'IOII 

TABLE 4-1. I/M SCENARIOS CONSIDERED 

Gaseous 

Case Inspection Frequency Cost Limit Emissions ? 

1 Decentralized Annual $1.000 Yes 

la Centralized Annual 1.000 Yes 

lb Decentralized Annual 500 Yes 

lc Decentralized Annual None Yes 

1d Decentralized Annual 1.000 No 

le Decentralized Biennial 1.000 Yes 

1£ Decentralized Biennial 100 Yes 

2 In-use Variable 1.000 No 

2a In-use Variable None No 

4-3 
RADIAN 

CORPO.A'I'IOII 

• Regulations requiring fuel injection system adjustments to be 

sealed by an authorized shop, and making breaking the seal 

prima facie evidence of tampering. 

• $1,000 cost limit for repairs, no cost limit for correcting 

tampering. Cost waivers require approval by a referee station. 

• Overall program administrative and enforcement structure 

similar to the existing Smog Check, but with aggressive undercover enforcement and expanded mechanic training. 

Cases 1a through lf consist of variations on this basic scenario. 

In Case la, inspection is performed in central, state-operated inspection 

stations, rather than in truck garages. In Case lb, the repair cost limit is 

reduced to $500. In Case 1C, the repair cost limit is eliminated--i.e. "fix 

it or park it". In Case 1d, the gaseous pollutant concentration measurements 

are eliminated, reducing the cost of the program, but also reducing its 

effectiveness for NO and HC control. Case le is a biennial inspection X 

program. Case lf, the final variation, reflects the legal constraints of the 

current Smog Check legislation. These include: biennial inspection, $100 cost 

limit, and a limit on the charge for a Smog Certificate of $6.00. 

Case 2 describes a very different I/M program based on in-use smoke 

opacity enforcement and anti-tampering inspections. 

program are the following. 

Key features of this 

• ARB Smoke Inspectors stationed at CHP truck scales and inspection stations. maintaining continuous visual screening for 

excessive smoke, and with the authority to pull a truck over 

for a smoke test and/or anti-tampering inspection. 

• Trucks cited for excessive smoke must be repaired and test 

below the standards within two weeks, or receive a cost waiver. 

4-4 
RADIAN 

CORP OR A 'I'I 0 II 

limit. 

The cost limit for repairs is $1,000. Smoke tests after 

repairs may be performed by BAR-authorized garages. 

• Trucks cited for excessive smoke more than once in 6 months are 

subject to a $250 fine (except where the first citation resulted in a waiver). 

• Tampering with emission controls, or knowingly operating a 

truck with tampered controls, is subject to a $1.000 fine for 

the first offense. and $2.500 fine for each subsequent occurrenee. Tampering must be corrected immediately. with no cost 

limit. 

• ARB Inspectors accompanying CHP depot truck inspection teams to 

conduct anti-tampering inspections at the same time the CHP 

conducts safety inspections. 

• Regulations requiring fuel injection system adjustments to be 

sealed by an authorized shop. Breaking the seal is prima facie 

evidence of tampering. 

• $1,000 cost limit for repairs, no cost limit for correcting 

tampering. Cost waivers require approval by a referee station. 

• Tightening the existing truck smoke law. training State and 

local police in smoke enforcement. and issuing traffic police 

with opacimeters. 

• Dedicated roving smoke patrol officers in critical air pollution areas such as the South Coast. 

A variant, Case 2a. consists of the same program with no repair cost 

4-5 
RADIAN 

COR.O R A'I'ION 

4.2 Results and Conclusions 

4.2.1 Pollutant Emissions and Offensive Smoke 

Pollutant emissions--Figures 4-1 through 4-3 show the total emission projected under each I/M scenario for the years 1990. 1995, and 2000. 

Figures 4-4 and 4-5 provide more detail on the reductions in excess emissions 

under each scenario. Figure 4-4 shows the emissions reduction for each 

pollutant (in tons/day. statewide) in 1990. 1995, and 2000. while Figure 4-5 

shows the percentage reduction in excess emissions of each pollutant for the 

same years. 

Several features of the data presented in these figures are worthy 

of note. First. excess NO emissions (while large in absolute terms) are only X 

a small fraction of the total diesel NO . Thus, although some programs can X 

reduce excess NO significantly. this effect is small relative to total NO 

X X 

emissions. This is not the case with HC or PM emissions. Since excess 

emissions of these pollutants account for a large fraction of the total. an 

I/M program which significantly reduces these excess emissions can have a 

large effect relative to the total. 

As Figure 4-4 indicates. all of the annual inspection programs are 

reasonably effective in reducing excess NO • but they are less effective in X 

reducing HC and PM emissions. The centralized program in Case la is marginally more effective in this regard. reflecting the greater probability of 

deterring or detecting tampering with the central inspection. All of these 

programs are hampered. however. by their relatively infrequent and predictable 

inspections. which limit the deterrence of "reversible" tampering. and which 

do relatively little to reduce the overall incidence of non-tampered highemitting vehicles. The in-use inspection programs. on the other hand. are 

highly effective in reducing particulate and HC emissions--resulting in more 

than a 50 percent reduction in excess PM. These programs are less effective 

in reducing NO • however. especially in the earlier years of the program. X 

4-6 
RADIAN 

CORII'ORA'I'I~N I I &00_-:r----------

NO f)LJ" X 

·-.., I I' • ,' ,_.) ;· >') / 

I 

l f'y 

X 

0 

z 

Hydrocarbons 

NO 1/W CASE 1 CloSE 1 a CloSE 1 b CASE 1 c CASE 1 d CloSE 1 o CASE If CASE 2 CASE 2a 

20 

10 

NO 1/W CASE 1 CloSE 1a CloSE 1b CASE 1c CASE 1d CASE to CASE 1t CASE 2 CASE 2a 

1~~-----------------------------------------------------, 

·~ .. 

Particulate ~ 

~0 

~I I 

~110 

100 

110 

110 

70 

80 

20 

10 

Figure 4-1. 

NO t/W CASE 1 CloSE 1 a CASE 1 b CASE 1 c CASE 1 d CASE 1 o CASE 1t CASE 2 CASE 2o 

IZZJ Baoollno 

Comparison of I/M Scenarios: Total Emissions - 1990 

4-7 
RADIAN 

co••o•a'l'tOII 

NO X 

Hydrocarbons 

Particulate 

~------------------------------------------------, 

NO 1/W V'S£ 1 CASE 1 a CI.SE 1 b CASE 1 c CASE 1 d CASE 1t CA3: 11 V'S£ 2 CASE 2a 

110,----------------------------------------------------------, 

100 

90 

NO 1/W CASE 1 CASE 1 a CASE 1 b CASE 1 c CASE 1 d CASE 1t CASE 11 CASE 2 CASE ~ 

1~,----------------------------------------------------, 

120 

110 

100 

NO 1/W o.s£ 1 CASE Ia CASE 1b CASE 1c CASE 1d CASE 1o CASE 11 CASE 2 CASE 2a 

IZZJ Baao .... !SSJ l:xc•• 

Figure 4-2. Comparison of 1/M Scenarios: Total Emissions - 1995 

4-8 
RADIAN 

co • 11o•aTIO II 

500 

NO X !lOO 

j 400 

) 

c 

~ 

X 

0 300 z 

~ 

' 200 

~ 

100 

0 

NO 1/W CASE 1 CASE 10 CASE 1 b CASe 1 c CASe 1d CASe 1o Ct.SE H CASe 2 CASE 2a 

110 

Hydrocarbons 100 

90 

80 

i 70 ) 

c 

~ 60 

u 

I: 

~ 50 

' 40 1; 

w; JO 

20 

10 

0 

NO 1/W CASE 1 CASE 1a CASE 1 b CASE 1 c CASe 1 d CASe 1o Ct.SE 1f CASE 2 CASE 2a 

130 

Particulate 120 

110 

100 

>: 90 

~ 80 c • 

~ 70 

JE 

.. 60 

-3 

i 50 .a 

0 

Oi 40 

JO 

20 

10 

0 

NO 1/W Cl.SE 1 CASe 1a CASE 1b CASe 1c CASE 1d CASe 1o Ct.SE H CASE 2 CASE 2a 

IZZJ s .. ollnol ~ Exc• o 

Figure 4-3. Comparison of I/M Scenarios: Total Emissions - 2000 

4-9 
RADIAN 

CO.II'O.A'I'IOII 

40 

1990 

~ 

30 

~ 25 "i 

! 

0 

cii 

8 20 

} 

c 15 

~ 

10 

5 

0 

i 

I 

I ; 

I I ' I 17 

j I 

r7 ~ ~ / / v' I 

I / / v v 

\ 1/ v 

/ 1/ 

1/ ' ·. 

1/ [/ 1/ IT \ 

1/ [/ 1/ II 1.1 [/ ~ 

1.1 [/ 1.1 1.1 [/ (/ v 

1.1 ll [/ ll ll ll v II l/1\ v 1.1 [I 

v 1.1 1.1 [I I' 

ll II v II II II ~~~ Ill\ tf 1/~ t:+: tt ~ VI'- ~ ~-'t-, VI'-

"' ...., NO 1/lol CASE 1 CASE 1 o CAS£ 1 b CAS£ 1 c CAS£ 1 d CASE 1e CASE 11 CASE 2 CASE 2G 

4() 

1995 35 

30 

~ 

~ ~ 25 j 

! 

2 

.. 20 8 

} 

c 15 

~ 

10 

5 

0 

1.1 ~ v 1.1 v 1.1 ll 17 ~ v 

1.1 1.1 v v 1.1 

v II v II II 

v 1.1 [/ 17 II [I 

v 1.1 [/ II [I v v [I [I v [I [I 1/ [I 

1/ [I v [I 

~ ll I' v 1/ v 1/ 1/ ll I' v v ~ ll 1/ v 1/ II ~ ~~ V'\ 1/ 1/ 1/'- II vk V'- ll 

~~ ll!'- 1/'- II 1/t'-- ll 1/ ll '/I' ll'\ 

t'-- vi'. II " v "' vi'-

NO 1/1.1 CAS~: 1 CASE 1o CASE 1 b CASE 1c CASE 1• CASE 1e CAS£ 11 Q.SE 2 CASE 2o 

4() 

2000 ~ 35 v 

ll 7 

30 

v v / 

v 1.1 [/ 1.1 

II ll v :/ 1/ 

~ . 25 

! 

2 

.. 20 ! 

v 

1/ [/ v II 1/ ll 

1/ 1.1 1/ 1.1 

1/ ~ 1.1 

II II I/ v ll II 

} 

c 15 

~ 

10 

5 

0 

v v [/ / 1/ 

v [/ 1/ 

II v v / [/ /~ 1.1 

1.1 v 1.1 / [/ 1/f', 1.1 

1.1 v 1/ [/ 1/f', v 

II v [/ / 1/f', ll'\ v I' v 1/f', 1.1 

~~ l/K 

r~ 1/f', 1.11'-. 

" I' 1/t\ I" [;!', l/1\ vf'. I' 1.11\ 1/f', I/ f'. 1/ 

NO 1/lol CAS~: 1 CAS£ 1o CASE 1 b CASE 1 c CASE 1 d CASE h CAS£ 11 CASE 2 CASE 2G 

~ Portkulat• 

Figure 4-4. Comparison of I/M Scenarios: Reduction in Emissions Due to I/M 

4-10 
RADIAN 

co•.,.o•aYION 

1990 

c 

0 

... 

g 

" It • 

It 

1995 

c 

0 

... 

g 

i 

1: 

It 

2000 

c 

0 

... 

g 

i 

It 

K 

·~ 

9~ 

ea>l: 

7~ 

60)1; 

!IO't 

V' ~ 7 [7 

ll ~ v 

v ~ v 

v v 

v 1/ v v 

/ v v 7 

~ ·v / 

v v / 17 

~ 

v / v / / 7r; v / v / / / 

2~ 

/ v / 

~r- / 

I v ll / I v /I\ 

v v VI' ['\ 

v I"< v v v ['\ 

·~ 

Oil 

/ II ll v ~ ~ ll'\ VI\ 

['\ " vt"- v VI' ll 

~ 

1om!: 

SOil 

-

7Cl'l: 

1ICl'l: 

~ 

17 t7 p 

v v 

v v 4<211: v v 

~ 

v 

v 

v 

v v Vl" v v v [7 VI' 

2~ 

1Cl'l: 

Cl'l: 

v v v v VT' 

v v ~I'; v v v ~~ VI" 

I"< [<; v v VT' 

~"' v v liT' 1\ Vl" v liT' v 

vw 

VI' VI" Vf' v VT' VI' ~~ v~ Vl" " VI' 

NO 1/W CASE 1 CASE 1 a CASE 1 b CASE 1 c CASE 1 d CASE 1o CASE 1 I CASE 2 CASE 2o 

·~ 

90X 

-

7Cl'l: 

11001: V" 

~ ll 17 / I 

40X v / v " v v v / 

~ " 7 7 

/ " v v v 

2Clll: 

1C%11: 

ox 

v v v / 

ll VI' ll v Ill\ ll 

" VI' " l/" v / V'\ I' ~~ ~I\ 

~ / 

['\ ll'\ l/1\ VI' l/1\ v 

" " 1\ l/1' v VI' vi' NO 1/W CASE 1 CASE 1o CASE 1 b CASE 1 c CASE 1 d CASE 1a CASE 11 CASE 2 CASE 2a 

IZZJ NOx ~ Particulate 

Figure 4-5. Comparison of I/M Scenarios: Percent · 

Reduction in Excess Emissions Due to I/M 

4-11 
RADIAN 

C OIIPOII A 'I'IO • 

Offensive smoke--Figure 4-6 shows the offensive smoke index calculated for each of the I/M scenarios and the baseline case with no I/M. Also 

shown is the percentage reduction in the offensive smoke index under each I/M 

scenario. This index is an artificial value based on the frequency of occurrenee of emissions defects which result in high smoke emissions. It is 

intended to represent the rough fraction of trucks on the road exhibiting 

offensive smoke levels in any operating mode. 

As Figure 4-6 shows, the two in-use I/M scenarios produced large 

reductions in the offensive smoke index, while the periodic I/M scenarios had 

a smaller, but still significant. effect. Regardless of the scenario, the 

overall incidence of offensive smoke is projected to decline markedly between 

1990 and 2000, as trucks built to the 1991 and 1994 particulate standards come 

to dominate the fleet. 

4.2.2 Costs and Cost-Effectiveness 

Tables 4-2 through 4-4 display the estimated costs to truck owners. 

the government, and society as a whole due to each I/M scenario. In each 

scenario except Case 1e, government revenues from Smog Certificate fees or 

fines for tampering were projected to approximate or exceed the government's 

costs--thus, the net cost to the government is small or negative. Tables 4-2 

through 4-4 also show the net reduction in emissions due to each program, and 

the cost-effectiveness of each program for particulate emissions control. 

Overall cost-effectiveness estimates for each scenario are summarized in 

Figure 4-7. 

To calculate the cost-effectiveness of an emissions control 

strategy-such as I/M--which affects more than one pollutant requires that some 

assumptions be made as to the proper allocation of costs between the different 

pollutants. For our calculations. we assigned each program a credit of $4,000 

per ton of NO or HC reduced, and assigned the remaining costs of the program X 

to particulate control. Making these assumptions, we were able to calculate 

4-12 
__,..,_ 

RADIAN 

Offensive Smoke Index 

NO 1/W CASE 1 CASE 1 a CASE 1 b CASE 1 c CASE 1 d CASE 1• CASE 1t CASE 2 CASE 2a 

% Reduction in Offensive Smoke Index 

NO 1/W CASE 1 CASE 1 a CASE 1 b CASE 1 c CASE 1 d CASE 1 e CASE 1 f CASE 2 CASE 2a 

Figure 4-6. 

IZ2l 1990 ~ 2000 

Comparison of I/M Scenarios: Reduction of Offensive 

Smoke Due to I/M 

4-13 
TABLE 4-2. COSTS AND COST EFFECTIVENESS OF ALTERNATIVE I/H PROGRAM DESIGNS: 19 90 

Case 1 Case 1a Case 1b Case 1c Case 1d Cess 1e 

Case 1f Case 2 

Program Cost [millions of dollars) 

Coate to Iruck Owners 

Smog Certificates 4.44 26.09 4.44 4.44 4.44 4.44 0.76 o.oo 

Privata Inspections 23.76 o.oo 23.31 24.32 19.42 11.88 11.19 4.06 

Non-Tampering Repairs 15.89 16.29 12.13 49.22 11.26 7.94 o.88 23.88 

Tampering Repairs 8.98 B.OB 8.9o s.s8 8.79 4.49 5.68 5.73 

lost TilliS 29.81 38.63 28.99 30.81 26.06 14.90 13.70 21.71 

Fines o.oo o.oo O.OD o.oo o.oo o.oo o.oo 13.34 

Fuel Consumption -6.2 -6.8 -7.6 -6.9 -6.8 -5.2 -2.4 -16.2 

Total Cost to Owners 74.7 80.3 70.2 108.9 63.1 36.4 29.6 52.5 

Costa to Government 

Program Costa 4.4 26.7 4.4 4.4 4.4 4.4 4.4 6.8 

Fees and Fi nee -4.4 -26.1 -4.4 -4.4 -4.4 -4.4 -<l.8 -13.3 

.p. 

I Total Cost to Government o.o o.6 o.o o.o o.o D.O 3.7 -6.5 

I-' 

.p. 

Total Social Coat 74.7 80.9 70.2 108.9 83.1 38.4 33.3 46.0 

Emission Reductions 

Oxides of Nitrogen 23.3 26.4 23.1 23.5 12.7 16.3 13.6 11.3 

Unburned Hydrocarbons 3.3 3.2 2.5 5.4 1.9 2.0 -{].3 8.7 

Particulate Matter 16.7 17.9 15.5 18.1 15.7 11.4 6.7 31.1 

Coat-Effectiveness ($/Ton) 

NOx $4,000 $4,000 $4,000 $4,000 $4,000 $4,000 $4,000 $4,000 

HC $4,000 $4,000 $4,000 $4,000 $4,000 e4,ooo .4,000 u,ooo PM $5,869 $5,764 $5,779 $10,087 $7,273 $2,836 $5,861 $1,469 

• $2,330 $1,210 $2,000 $6,770 $3,930 e5o2 $1,066 (Neg) .. Cost-Effectiveness (elton PH) 

WID Indirect costa and savings 

• Indirect coste are lost time and fuel consumption. 

•• Negative cost after taking NO and HC credi ta. 

X 
TABLE 4-3, COSTS AND COST EFFECTIVENESS OF ALTERNATIVE I/H PROGRAM DESIGNS: 199

Case 1 Case 1a Case 1b Case 1c Case 1d Case 1a Cess 1f Case 2 

Program Coat (millions of dollere] 

Costs to Truck OWners 

Smog Certificates 5,89 34,6D 5,98 5.99 5,99 5,88 1.D4 o.oo 

Private Inspections 30,04 o.oo 29.44 30,90 24.46 14.41 14.25 4.78 

Non-Tampering Repairs 20,09 20,69 14.94 64,84 14.50 8,16 0.71 29.04 

Tempering Repairs 11,43 10.14 11,32 11.43 10.60 4.42 7,65 8,31 

Lost Time 37,33 47.54 36.24 39.73 35.05 17.57 17.29 25.35 

Fines 0,00 0,00 o.oo 0,00 o.oo o.oo 0,00 15,95 Fuel Consumption -1.1 - 0.4 -0.6 -1.5 -1.9 -0.5 1.2 -4.3 

Total Cost to Owners 103,7 112.5 97.1 150.1 98,6 50,0 42.1 79.1 

Coste to Government 

Program Costs 5.9 34.6 5.9 5.9 5.9 5,9 5.9 9,0 

..,... Fees end Ffnes -5,9 -34.6 -5,9 -5,9 -5,9 -5,9 -1.0 -18,0 

I 

f-1 

\..11 Total Cost to Government o.o o.o o.o o.o o.o o.o 4.8 -7.0 

Total Social Coat 103.7 112.5 97,1 150.1 86.6 50,0 47 .o 72.1 

Emission Reductions 

Oxides of Nitrogen 26.5 34.0 28.4 28.7 18.5 19.5 16.6 25,0 

Unburned Hydrocarbons 5.1 5,3 4.4 8.7 4,0 3,4 1,2 11.5 

Partfculete Matter 13.1 14.2 12.2 14.3 12,2 9,0 5,3 24.6 

Cost-Effectiveness [eLton] 

NOx $4,000 $4,000 $4,000 $4,000 $4,000 $4,000 $4,000 $4,000 

HC $4,000 $4,000 $4,000 $4,000 $4,000 $4,000 $4,000 $4.000 PM $11,396 $10,626 $11,042 $18,865 $12,588 $5,038 $10,868 $2,101 

• •• • • ($/ton PH) $3,825 $1,546 $3,049 $11,731 $5,102 (Neg) $1,342 (Nag) 

Indirect costs end savings 

-

• Indirect costs a re Lost time and fuel consumption. 

•• Negative cost after taking NO end HC credits. X 
TABLE 4-4. COSTS AND COST EFFECTIVENESS OF ALTERNATIVE I/H PROGRAM DESIGNS: 2000 

Case 1 Case 1a Case 1b Cess 1c Case 1d Case 1a Case 1f Case 2 C

Program Cost (millions of dollars) 

Coats to Truck Owners 

Smog Certificates 7.02 41.31 7.02 7.02 7.02 7.02 1.24 o.oo 

Privata Inspections 35.18 o.oo 34.43 38.11 28.62 18.90 18.75 5.47 

Non-Tampsring Repairs 24.34 25.23 17.88 78.16 18.22 10.10 0.72 34.45 

Tampering Repairs 14.33 12.81 14.23 14.33 13.17 5.40 9.99 11.66 

Lost TiiiiB 43.54 55.06 42.20 45.26 40.94 20.53 20.25 28.81 

Fines o.oo o.oo o.oo o.oo o.oo o.oo o.oo 19.31 

Fuel Consumption 4.8 6.5 5.1 4.5 4.0 3.5 4.2 5.8 

/ 

Total Cost to Owners 129.2 140.9 120.7 185.4 111.9 63.4 53.1 105.5 

Coste to 

Program Costs 7.0 41.3 7.0 7.0 7.0 7.0 7.0 10.7 

Fees and Fines -7.0 -41.3 -7.0 -7.0 -7.0 -7.0 -1.2 -19.3 

.,.. Total Cost to Governlll8nt o.o o.o o.o o.o o.o o.o 5.8 -8.6 

I 

I-' 

Q'\ 

Total Social Cost 129.2 140.9 120.7 185.4 111.9 83.4 58.9 96.9 

Emission Reductions 

Oxides of Nitrogen 33.2 40.4 33.1 33.4 23.0 22.8 19.3 34.8 

Unburned Hydrocarbons 7.1 7.8 8.4 8.5 6.2 4.8 2.4 14.9 

Particulate Hatter 12.0 13.1 11.2 13.0 11.2 8.2 5.0 22.8 

Cost-Effectivaness ($lton) 

NOx $4,000 $4,000 $4,000 $4,000 $4,000 $4,000 $4,000 $4,000 

HC $4,000 $4,000 $4,000 $4,000 $4,000 $4,000 $4,000 $4,000 PH $16,102 $14,734 $15,408 $28,145 $16,983 $7,805 $15,087 $2,942 $

• •• • • Cost-Effectiveness ($/ton PH) $5,033 $1 ,908 $3,836 $15,666 $5,983 (Neg) t1 ,608 (Nag] 

WVO Indirect costs and savings 

• Indirect coats ere lost tima and fuel consumption. 

•• Negative cost after taking NO and HC credits. X 
RADIAN CORitOR A 'riON 

the cost-effectiveness of each program as a particulate control measure. 

treating the HC and NO reduction benefits as side-effects. The value of X 

$4,000 per ton of HC and NO eliminated is fairly typical of other ongoing X 

emission control initiatives in California. although many approaches with 

higher and lower cost-effectiveness values have also been recommended. 

As Figure 4-7 shows. the most cost-effective I/M program scenario by 

our calculations is Case 2. Case 2 also results in the second largest reduction in emissions (after Case 2a). and thus appears clearly preferable overall. Case 2 is followed in cost-effectiveness by the other cost-limited 

periodic inspection programs. These are grouped fairly closely in cost-effectiveness and overall results. although Case la (centralized inspection) has 

somewhat of an advantage. This shows that centralized inspection is superior 

to even an effectively administered and enforced decentralized program. The 

advantage of centralized inspection over a less vigorously enforced decentralized program would be much greater. 

Some of the highest costs-per-ton of emissions control are calculated for the two scenarios with no repair cost limits, due to the very high 

costs of engine overhaul included in these cases. These calculations 

overestimate the actual economic costs somewhat. since overhauling an engine 

increases its value and useful life. Nonetheless. it appears that some 

reasonable limit on repair costs is needed in a heavy-duty diesel I/M program 

in order to keep overall program costs and cost-effectiveness reasonable. 

The cost-effectiveness calculations shown in the tables include an 

explicit accounting for "indirect" costs and benefits to the truck owners. 

such as lost driver and truck time, and fuel consumption effects. These are a 

large fraction of the total costs of the program. For compatibility, with 

some other cost-effectiveness estimates for I/M programs. we also calculated 

the cost-effectiveness omitting these cost elements. Omitting these elements 

reduces the calculated cost of the program considerably--to t he point that 

this cost is less than the credit: for HC and NO reductions. in some cases. X 

4-17 
RADIAN 

CORPORATION 

Cost-Effectiveness for Particulate Control 

$24 

$22 

$20 

$18 

1J 

u $16 > 

0 

E'"' 

u n $14 O::lJ c ::E 0 

ll. ~ $12 

~ 0 

0~ $10 c'-" 

0 

f-

" $8 .. $6 

$4 

$2 

$0 

NO 1/M CASE 1 CASE 1o CASE 1b CASE 1c CASE 1d CASE 1e CASE 1f CASE 2 CASE 2o 

[ZZ] 1990 !S:::sJ 1 995 ~ 2000 

Figure 4-7. Comparison of I/M Scenarios: Cost Effectiveness 

4-18