Appendix G 

Emissions Analysis Methodology and Results 

Medium-Heavy Duty Diesel Trucks, Heavy-Heavy Duty Diesel Trucks, 

and Regulated Bus Categories 

-iTable of Contents 

List of Acronyms...........................................................................................................iii

A. Introduction ........................................................................................................... 1

B. Methodology.......................................................................................................... 2

C. Statewide Emissions Analysis Updates.............................................................. 2

1) Construction Trucks .......................................................................................... 2

2) Medium Heavy-Duty Diesel Truck Population Split........................................... 7

3) Impact of Recession and Growth by Category.................................................. 8

4) Motorcoach/Buses ............................................................................................ 8

5) Out-of-State Vehicle Miles Traveled ............................................................... 10

6) Odometer Capping.......................................................................................... 11

D. 2008 Truck Field Data Collection....................................................................... 12

1) Study Design and Data Collection Locations .................................................. 12

2) Regional Allocation Based on OD Survey Data .............................................. 18

3) OD and LP Survey Data Analysis ................................................................... 22

4) Discussion of Field Study Results................................................................... 29

E. Regional Allocation of Activity and Emissions ................................................ 30

1) Interstate Trucks ............................................................................................. 30

2) Heavy-Heavy Duty In-State Tractors .............................................................. 31

3) Heavy-Heavy Duty In-State Single-Unit Trucks .............................................. 31

4) Medium-Heavy Duty In-State Trucks .............................................................. 33

5) Drayage Trucks............................................................................................... 34

6) Construction Trucks ........................................................................................ 35

7) Agricultural Trucks .......................................................................................... 36

8) Utility Trucks ................................................................................................... 37

9) Regional Allocation Results ............................................................................ 38

F. Impact of the Recession on VMT and Vehicle Sales........................................ 38

1) Drayage Trucks............................................................................................... 39

2) Construction Trucks ........................................................................................ 40

3) MHDDT........................................................................................................... 40

4) HHDDT ........................................................................................................... 42

G. Proposed Regulatory Scenarios and Compliance Assumptions.................... 43

1) MHDDT Rule Compliance (<26,000 lbs GVWR)............................................. 43

2) Small Fleet Rule Compliance (>26,000 lbs GVWR)........................................ 44

3) Large Fleet Rule Compliance (>26,000 lbs GVWR)........................................ 46

4) Agricultural Truck Compliance Assumptions................................................... 47

5) Utility Truck Compliance Assumptions............................................................ 47

6) Drayage Truck Compliance Assumptions ....................................................... 48

7) School Bus Compliance Assumptions ............................................................ 49

8) Regulatory Credit and Other Provisions - Not Modeled in the Inventory......... 49

H. Emissions Results .............................................................................................. 50

1) Evaluation of Baseline Statewide Fuel Usage Estimates................................ 50

2) Estimating Statewide Emissions Benefits of the Proposed Regulation........... 51
-ii3) PM and NOx Emissions Benefits from both the Truck and Bus and In-Use OffRoad Rules are Preserved..................................................................................... 55

4) Meeting SIP Targets ....................................................................................... 56

I. Additional Documentation.................................................................................. 58

J. References........................................................................................................... 62

K. Attachment – CARB Origin-Destination Survey Questionnaire ...................... 65
-iiiList of Acronyms 

AADTT Annual Average Daily Truck Traffic 

ARB Air Resources Board 

BACT Best Available Control Technology 

BEA Bureau of Economic Analysis 

BLS Bureau of Labor Statistics 

BOE Board of Equalization 

BTS Bureau of Transportation Statistics 

Caltrans California Department of Transportation 

CBA California Bus Association 

CPUC California Public Utilities Commission 

CY Calendar Year 

DMV Department of Motor Vehicles 

DOF Department of Finance 

DPF Diesel Particulate Filter 

EDA Equipment Data Associates 

FHWA Federal Highway Administration 

GDP Gross Domestic Product 

GVWR Gross Vehicle Weight Rating 

HDT Heavy-Duty Truck 

HHDDT Heavy Heavy-Duty Diesel Trucks 

IFTA International Fuel Tax Agreement 

IRP International Registration Plan 

LP License plate 

MHDDT Medium Heavy-Duty Diesel Trucks 

MVSTAFF California Motor Vehicle Stock, Travel and Fuel Forecast 

MY Model Year 

NAAQS National Ambient Air Quality Standards 

NOOS Neighboring out-of-state 

NOx Nitrogen Oxides 

NNOOS Non-neighboring out-of-state 

OD Origin-Destination 

OOS Out-of-state 

PM Particulate Matter 

POAK Port of Oakland 

POLA Ports of Los Angeles and Long Beach 

PTO Power Take Off 

SCAG Southern California Association of Governments 

SIP State Implementation Plan 

TEU Twenty-foot equivalent unit 

UCC Uniform Commercial Code 

USDOE United States Department of Energy 

USEPA United States Environmental Protection Agency 

USGS United States Geological Survey 

VIUS Vehicle Inventory and Use Survey 

VMT Vehicle Miles Traveled 
-iv- 
G-1 

A. Introduction 

Commercial heavy-duty diesel trucks and buses (commercial diesel buses and trucks 

exceeding 14,000 lbs gross vehicle weight rating (GVWR)) are currently the single 

largest source of nitrogen oxide (NOx) emissions in California, accounting for 30 percent 

of statewide NOx emissions (ARB, 2008). These same trucks and buses are also the 

largest source of diesel particulate matter (diesel PM) in California, representing about 

40 percent of statewide diesel PM emissions. 

In December 2008, the Air Resources Board (ARB or Board) adopted the Statewide 

Truck and Bus Rule (regulation). That regulation was designed to achieve emissions 

reductions by requiring truck and bus fleet owners to modernize their fleets and install 

exhaust retrofits. As part of that regulatory development, staff developed a statewide 

emissions analysis that quantified emissions from different types of trucks and buses 

separated by registration type, body type and/or vocation as well as mileage thresholds. 

The assumptions used in development of that emissions analysis were published in 

Appendix G of the technical support document (TSD) for the 2008 rulemaking, and the 

results of the inventory were published in an on-line database (ARB, 2008). 

In December 2008, the National Bureau of Economic Research declared that the United 

States had entered an economic recession. That recession turned out to be the most 

severe in the United States since the Great Depression. In December 2009, staff 

reported its statewide estimate of the impact of the economic recession on truck and 

bus emissions. Results suggested that emissions in 2009 across all trucks and buses 

operating in California were approximately 20 percent lower than estimates provided in 

the 2008 Rule staff report (ARB, 2009). As a result of the recession, the Board directed 

staff to develop regulatory amendments to the Rule that provide economic relief while 

ensuring air quality goals would still be attained. 

The emissions inventory developed to support the proposed regulatory amendments 

builds upon the 2008 and 2009 work. We revised the inventory methodology to improve 

the quality and accuracy of emissions estimates. We revised growth rates and 

forecasted vehicle age distributions to reflect the impact of the economic recession both 

today and in the future. We developed a new procedure for allocating statewide 

emissions to each air basin in California so the impact of the Rule could be evaluated 

regionally. Finally, we assessed the impact of the proposed regulatory amendments on 

emissions from Trucks and Buses on a statewide and regional basis. This appendix 

provides the fundamental analysis behind updates to the emissions analysis, regional 

emissions estimates, the impact of the economy on emissions, and the emissions 

impact of new regulatory amendments. 
G-2 

B. Methodology 

Emissions are calculated as the product of a population of vehicles, the number of miles 

each vehicle travels, and emission rates per mile. Beneath this simple equation lies a 

series of data and assumptions about the population, miles traveled, and emission rates 

per vehicle model year in a given calendar year, growth and attrition estimates, 

deterioration, and other factors that affect emissions estimates, all of which were 

discussed in the 2008 Rulemaking. We applied the concept separately for each 

analysis category of trucks that shares similar travel, service, size, age or other 

characteristics. 

 

∑MY, C (POPMY, C X AC MY, C X ER MY, C) = EMSCY, Equation 1 

where: POPMY, C is the population of trucks for model year MY within each analysis 

category C for a given calendar year; 

ACMY, C is the accrual rate (miles traveled per year) per truck by model year 

MY and analysis category C in a given calendar year; 

ERMY, C is the calculated emission rate, in grams pollutant per mile driven, 

assuming statewide speed travel distributions in EMFAC2007 and fleet 

specific cumulative mileage accrual over the life of the truck, by model 

year MY and analysis category C; 

EMSCY is the emissions calculated in tons per day for a given calendar year. 

The basic calculation methodology is unchanged from that described in Appendix G of 

the Rule Initial Statement of Reasons published in ARB (2008). Emissions analysis 

updates described in this document relate to changes in inputs to the methodology. 

The emissions analysis methodology published in 2008 involved applying annual 

average growth rates that are independent of the economic cycle. In 2009 staff 

developed a scaling model that was designed to assess the impact of multiple potential 

economic forecast scenarios on emissions (ARB, 2009). For this rulemaking, staff are 

using an emissions forecast that reflects the average of a fast recovery and slow 

recovery bounding scenario. This emissions forecast scenario is input directly to the 

emissions model for the analysis described in this document. 

C. Statewide Emissions Analysis Updates 

1) Construction Trucks 

In the emissions analysis presented to the Board in December, 2008, ARB staff 

categorized the medium heavy-duty diesel trucks (MHDDT) and heavy heavy-duty 

diesel trucks (HHDDT)1

 into different fleet categories that differentiated trucks and 

buses by registration type (in-state vs. interstate), body type (tractor, single-unit, etc.), 

 

1

 Heavy-duty diesel trucks include MHDDT with a GVWR above 14,000 lbs and up to 33,000 lbs, and 

HHDDT with GVWR above 33,000 lbs. 
G-3 

and vocation (agricultural, construction, drayage, etc.). Over the past year staff listened 

to stakeholder comments and evaluated the impact of the recession on the construction 

sector. Our analysis suggested that trucks involved in construction have been impacted 

more severely by the recession than other trucking sectors. In order to reflect this 

finding, staff separated trucks owned by construction firms from other trucking 

categories in the inventory, and then developed an alternate economic forecast 

reflecting the economic downturn on construction trucking. 

Like other vocational trucking categories, trucks owned by construction firms cannot be 

easily identified through the California Department of Motor Vehicles (DMV) registration 

database. To identify a population of construction trucks, staff analyzed data in the 

Vehicle Inventory and Use Survey (VIUS), (VIUS, 2002). Construction trucks were 

identified in the survey by selecting “construction” as the industry in which the vehicle 

was most used. Based on the survey, staff estimated the fractions of trucks in the 

construction industry relative to the population in the inventory fleet category and the 

results are shown in Table 1. 

Table 1. Percentage of Construction Trucks by Inventory Category 

Percent of Construction 

Trucks in Each Category 

MHDDT instate 21 

HHDDT tractor 20 

HHDDT single-unit 40 

HHDDT CAIRP2 6 

Next, staff evaluated the age distribution of construction trucks in VIUS and compared 

that to all trucks in VIUS. Results suggested that construction trucks have roughly the 

same average age profile as other trucking categories, and as a result staff decided to 

assume that construction trucks by body type have the same age distribution as nonconstruction trucks of the same body type and registration status. Table 2 compares 

the average age of construction trucks against non-construction trucks by inventory 

category. 

Table 2. Construction vs. Non-Construction Truck Average Age (VIUS, 2002)3

Construction General 

Tractor 8.0 7.4 

Single Unit (non-tractor) 7.6 7.2 

 

2

 CAIRP: California registered International Registration Plan (IRP) trucks 

3

 VIUS grouped all age 16 and older into one category and only trucks age 15 or newer in VIUS were 

included in the analysis. 
G-4 

Staff assumed that all in-state registered tractors and single-unit construction trucks 

followed the in-state single unit accrual schedule as documented (ARB, 2008). 

The emission factors remain unchanged; as a result HHDDT single-unit emission rates 

are used for HHDDT construction single-unit trucks, HHDDT tractor emission rates for 

HHDDT construction tractors, HHDDT IRP truck emission rates for HHDDT construction 

IRP trucks, and MHDDT emission rates for MHDDT construction trucks. 

To estimate the impact of the recession on construction activity in California, staff 

reviewed a variety of economic indicators. Surrogates for construction emissions such 

as employment, gross domestic product, building permits, value of equipment financed, 

and fuel consumption indicate that construction activity decreased between 30 percent 

and 80 percent in California between 2006 and 2009, as shown in Table 3. 

Table 3. Impact of Recession on Economic Metrics 

Data Type Change Relative 

to Peak Data Source 

CA Construction Employment 

(2006-2009) -30% US Bureau of Labor Statistics 

(BLS, 2010)

CA Construction GDP 

(2005-2008) -30% US Bureau of Economic Analysis; (BEA, 2009) 

CA Construction Taxable Fuel Refunds 

(2006-2008) -40% CA Board of Equalization; (BOE, 2008) 

CA Construction Valuation 

(2005-2009) -65% CA Dept of Finance; (DOF, 2010) 

CA New Building Permits 

(2004-2009) -80% CA Dept of Finance; (DOF, 2010) 

CA New Equipment Sales Financed 

(2005-2009) -80% Equipment Data Associates; (EDA, 2010) 

Based on above reviews, staff estimated a 50 percent reduction in activity from 2006 to 

2009. Staff generated an estimation of average recovery using bounding fast and slow 

recovery scenarios to represent both vehicle miles traveled (VMT) growth assumptions, 

as shown in Figure 1, and vehicle sales in the construction sector, as shown in Figure 2. 

Construction vehicle sales trends were estimated using the relationship between vehicle 

sales and economic trends documented in the staff report for the 2008 Truck and Bus 

rulemaking (ARB, 2008). 
G-5 

Figure 1. Construction Vehicle Miles Travelled (VMT) Growth Assumption 

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

2006 2008 2010 2012 2014 2016 2018 2020 2022

Growth Relative to 2006

Historical trend Slow Fast Average
G-6 

Figure 2. Construction Truck Sales Trend and Estimated Recovery 

a) Heavy Heavy-Duty Construction Truck Sales 

0

50

100

150

200

250

300

1985 1990 1995 2000 2005 2010 2015 2020 2025

HHDDT Cosntruction Sales (thousands)

Historical Trend Fast Slow Average

Historical

b) Medium Heavy-Duty Construction Truck Sales 

0

50

100

150

200

250

300

1985 1990 1995 2000 2005 2010 2015 2020 2025

MHDDT Construction Sales (thousands)

Historical Trend Fast Slow Average

Historical
G-7 

2) Medium Heavy-Duty Diesel Truck Population Split 

Diesel fueled trucks with a GVWR between 14,000 and 33,000 lbs GVWR are 

considered to be MHDDT. The proposed amended regulation would exempt vehicles 

with a GVWR less than 26,000 lbs from meeting PM filter requirements. To estimate 

the population of vehicles that are above 26,000 lbs within the MHDDT category staff 

analyzed the GVWR code of MHDDT in the DMV registration data (DMV, 2005). 

Results suggest that about 30 percent of the MHDDTs statewide are above 26,000 lbs 

and they have different age distribution than the overall medium heavy-duty diesel 

trucks as shown in Figure 3. 

Figure 3. Medium Heavy-Duty Diesel Truck Age Distributions 

0%

1%

2%

3%

4%

5%

6%

7%

8%

9%

10%

-1 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41

Age

Percent in Category

Between 26,001 and 33,000 lbs GVWR All Medium-Heavy

The average age of diesel trucks with GVWR between 26,000 and 33,000 lbs is about 

11 years old while the overall medium heavy-duty diesel is about 8 years old. To reflect 

the differences in age distribution and population fraction, staff assumed that 30 percent 

of MHDDTs between age 9 and 13, 58 percent of the older than 13 years and 20 

percent of vehicles newer than nine years old are MHDDT above 26,000 lbs. This 

assumption is applied to MHDDT instate and interstate trucks. 
G-8 

3) Impact of Recession and Growth by Category 

As described in ARB (2009), the recession has had a major impact on the trucking 

industry. In order to develop the updated emissions analysis, staff revisited fuel and 

economic truck activity indicators to estimate the impact of the recession on truck and 

bus operations in California. Using the same methodology as described in ARB (2009) 

staff developed an estimate for an average recovery forecast based on fast and slow 

bounding recovery scenarios. 

Staff’s previous analysis identified a relationship between overall economic trends and 

truck sales. The impact of this relationship is that as the economy has deteriorated as a 

result of the recession, national new truck sales have decreased and fewer new 

vehicles are registered in California (ARB, 2009). Because of this relationship, staff has 

developed both forecasts for the impact of the reduced total vehicle activity caused by 

the recession on emissions by truck category, and forecasts for the impact of reduced 

vehicle sales on emissions by truck category. Detailed assumptions by category are 

presented in Section F. 

4) Motorcoach/Buses 

In the December 2008 Board Hearing, the Board adopted specific regulatory provisions 

for motorcoaches. In order to reflect these regulatory provisions, staff consulted with 

the California Bus Association (CBA) to obtain information to assist in estimating the 

population, mileage accrual rates, and other assumptions for the motorcoach inventory 

category. The CBA provided population estimates from the California Public Utility 

Commission (CPUC, 2009), and results of a survey (CBA, 2010) that could be used to 

assess mileage accrual. The age distribution was assessed by matching registered 

motorcoach companies against the buses those firms registered in the DMV database. 

Staff subtracted the motorcoach population by age from the other bus category, and 

assumed a 1.75 percent growth rate per year in the absence of the recession. Staff 

used HHDDT emission rates because motorcoaches are rated in excess of 33,000 lbs 

GVWR, and emission rates for the other bus category from which motorcoaches were 

extracted are based on a weighted average of heavier and lighter buses. 

To estimate the impact of the recession, staff used CBA provided population estimates 

in 2000 (3376), 2008 (3589), and 2009 (3125). Age distributions were forecasted by 

assuming heavy heavy-duty vehicle sales forecasts developed using the fast and slow 

recovery bounding scenarios. Table 4 provides assumed motorcoach populations and 

VMT, while Figure 4 shows the assumed accrual schedule. 
G-9 

Table 4. Motorcoach Population and VMT 

Motor Coach Population VMT (million miles per year) 

Year No Recession With Recession No Recession With Recession 

2000 3320 3320 147 147 

2005 3670 3670 160 160 

2007 3760 3451 166 153 

2008 3914 3294 169 143 

2009 4042 3125 172 133 

2010 4113 3240 175 137 

2014 4374 3775 187 158 

2020 4834 4375 208 183 

Figure 4. Motorcoach Mileage Accrual 

0

10,000

20,000

30,000

40,000

50,000

60,000

-1

13579

1113151719212325272931333537394143

Age

Miles per year

Other Bus Motorcoach
G-10 

5) Out-of-State Vehicle Miles Traveled 

The 2008 inventory analysis assumed a set amount of VMT by out-of-state (OOS) 

trucks in California in 2005, based on information from the International Fuel Tax 

Agreement (IFTA) program provided by email from the California State Board of 

Equalization (BOE, 2010a). After the 2008 inventory was developed BOE provided 

2007 calendar year estimated out-of-state truck VMT and fuel usage in California. This 

number was substantially lower than what had been provided in 2005. In 2010, staff 

received 2008 and 2009 estimated out-of-state truck VMT and fuel usage in California. 

Overall, data representing California registered trucks in the IFTA program appears 

plausible, with a 20 percent increase between 2005 and 2007, and then a 20 percent 

decrease due to the recession from 2007 to 2009. Out-of-state VMT data shown in 

Table 6 are not consistent between 2005 and 2007-2009. For example, the 2005 data 

provided by BOE are much higher than any of the 2007-2009 data, and the 2008 data 

are higher than 2007 data. These trends are not consistent with either economic 

surrogates or overall on-road fuel trends. Because of these anomalies in the IFTA data, 

staff decided to adjust the IFTA numbers for out-of-state trucks to reflect our best 

estimate of what out-of-state truck VMT in California should be given the totality of 

available data. To adjust the data, staff calculated the average annual truck VMT 

between 2007 and 2009 for OOS and for CA registered IFTA respectively, and then 

back-casted 2005 out-of-state IFTA miles based on the ratio of the two averages and 

2005 CA registered IFTA truck miles. Staff then applied the impact of the recession as 

measured by the BOE data for on-road fuel trends. The BOE IFTA data, as well as staff 

assumptions based on the data are shown in Table 5. 

Table 5. Reported and Estimate Interstate VMT (million miles/year) in California: 

2005-2009 

Year 

CA Registered 

IFTA Truck 

Miles in CA 

Reported 

OOS Truck 

Miles in CA 

Modeled OOS 

Truck Miles in 

CA 

no recession 

Modeled OOS 

Truck Miles in 

CA with 

recession 

2005 2,189 4,398 3,144 3,144

2007 2,660 2,943 3,419 3,397

2008 2,213 3,761 3,601 3,115

2009 2,134 3,358 3,654 2,843
G-11 

0 10 20 30 40 50

Truck Age

Odometer

Current Method Revised Method

6) Odometer Capping 

Truck emission rates are a function of cumulative mileage on the vehicle through an 

emissions process called deterioration. The cumulative lifetime mileage on a vehicle 

can be measured using the vehicle’s odometer. Previous analyses, as well as the 

EMFAC2007 model, assumed that odometer is a function of the year by year mileage 

accrual. To evaluate this assumption, staff collected truck “for-sale” records from 

truckpaper.com that contained odometer readings, as well as odometer records from 

the Goods Movement Bond Program and data in VIUS (2002). Results demonstrated 

that odometer is not simply a function of the year by year mileage accrual, and instead 

odometer readings tend to level off depending on engine design life. This concept is 

shown in Figure 5. 

Figure 5. Schematic Representation of Difference between Current and Revised 

Method for Estimating Vehicle Odometer

The reason for the difference is that when a truck or vehicle is young, the average 

odometer is a function of some high accruing and some low accruing vehicles. As 

vehicles age higher mileage vehicles are scrapped more quickly than lower mileage 

vehicles. So, surviving older vehicles are more likely to have accrued fewer miles than 

average when those vehicles were younger. The net result is that odometer is a 

function of both accrual rates and vehicle survival rates, and observed odometer 

readings in practice tend to level out to a constant level for older vehicles. Staff decided 

to cap odometer readings at a specific value for each truck category and used capped 
G-12 

odometer-age relation to generate emission rates by age. The choice of the cap 

depends on the data sources evaluated; in this case staff decided to cap odometer 

levels at 800,000 for HHDDTs, and at 400,000 for MHDDTs, as shown in Table 6. 

Overall, the change in odometer led to less than a 5 percent change in the inventory for 

any calendar year. 

Table 6. Odometer Cap by Inventory Category 

Inventory Category Survival Rate Based Odometer Reading Cap Value 

MHDDT Ag 400,000 

MHDDT CAIRP 400,000 

MHDDT instate 400,000 

MHDDT OOS 400,000 

HHDDT Ag 800,000 

HHDDT CAIRP 800,000 

HHDDT NNOOS 800,000 

HHDDT NOOS 800,000 

HHDDT other port 800,000 

HHDDT POAK 800,000 

HHDDT POLA 800,000 

HHDDT single No change from ARB (2008) 

HHDDT tractor 800,000 

MHDDT utility No change from ARB (2008) 

HHDDT utility No change from ARB (2008) 

MHDDT instate construction 400,000 

HHDDT single construction No change from ARB (2008) 

HHDDT tractor construction 800,000 

HHDDT CAIRP construction 800,000 

 

D. 2008 Truck Field Data Collection 

1) Study Design and Data Collection Locations 

In 2008 ARB staff implemented a large-scale field data collection effort. The primary 

objective of this effort was to obtain information to improve regional allocation estimates 

of heavy-duty truck (HDT) activity. The data collection effort consisted of two 

components: license plate (LP) surveys and origin-destination (OD) surveys. License 

plate surveys consisted of time-stamped digital photographs at each location, and 

provided the mixture of trucks by registration type at 15 weigh stations and 15 roadside 

locations4

. OD surveys were collected by intercepting and talking with truck drivers to 

obtain information on the truck and on the current trip. OD surveys provided trip 

information which helped to allocate the trip VMT into geographic areas, and were 

 

4

 The license plate data collection effort obtained data from 16 weigh stations and 30 roadside locations. 

However, given the time required to process data, staff prioritized the list of locations to be processed so 

that most weigh stations and major representative roadside locations in the South Coast, the San Joaquin 

Valley and the San Fransisco Bay Area are included in the analysis. 
G-13 

collected at 18 weigh stations and 3 roadside locations. Attachment A provides the OD 

survey instrument. A total of 54,570 license plates and 6,215 OD surveys were 

collected and processed for the regional allocation analysis. Most of the data were 

collected during the daytime and in the middle of the week. 

The survey was designed to capture both inter-regional and local trips. Two types of 

survey sites were considered: locations on major freeways at the border of an air basin 

and locations inside a particular region or air basin. Locations near state borders were 

omitted from this study to focus on intra-state truck traffic. Interstate truck traffic data 

collected by UC Davis (Lutsey, 2008) were used to inform and supplement data 

collected through the ARB field data collection; that collection effort was focused on 

roadways near California’s border with Mexico, Nevada, Arizona, and Oregon. 

Data collection covered all major portions of the California state highway system, but a 

higher concentration of data was collected in the South Coast Air Basin and San 

Joaquin Valley Air Basin. OD surveys were conducted primarily at weigh stations for 

safety purposes, and tended to be biased towards inter-regional trips because weigh 

stations are typically located between rather than within regions. License plate 

collection sites were focused on assessing the mix of different types of vehicles 

operating within a region, and selected locations were located across a region of 

interest. Table 7 and Figure 6 show survey locations. 
G-14 

Table 7. ARB 2008 Statewide HDT LP and OD Survey Plan 

Site ID# Route County Name/Description Direction*

LP OD

1 I-80 Solano Cordelia EB/WB 24 2 3

2 I-10 Riverside Desert Hills EB/W B 24 3 3

3 CA-91 Orange Peralta EB/W B 9 2 3

4 I-5 Los Angeles Castaic NB 9 3

5 I-15 San Bernardino Cajon NB/SB 9 2 3

6 US-101 Ventura Conejo NB/SB 9 2 3

8 I-5 San Diego San Onofre NB/SB 9 2 3

9 I-680 Contra Costa Walnut Creek NB/SB 9 3

10 I-680 Alameda Mission Grade NB 9 2 3

11 I-880 Alameda Nimitz NB/SB 9 2 3

12 I-580 Alameda Livermore EB/W B 9 2 3

13 US-101 Santa Clara Gilroy NB/SB 9 2 3

14 I-15 San Diego Rainbow NB/SB 9 3

15 5 Kern Grapevine SB 9 2 3

16 5 Merced Santa Nella NB/SB 9 2 3

17 99 Merced Chowchilla River NB 9 2 3

18 58 Kern Keene EB 9 2 3

19 58 Kern Cache Creek W B 9 2 3

21 I-710 Los Angeles Near Jct 105 NB/SB 9 2

23 I-605 Los Angeles Near Jct. 5 NB/SB 9 2

25 I-105 Los Angeles Near Jct 19 EB/WB 9 2

26 CA-60 Los Angeles Near Jct 710 EB/W B 9 2

30 I-15 San Bernardino South of Jct CA 60 NB/SB 9 2

34 CA-91 Riverside Near Jct 215 EB/W B 9 1

35 CA-60 Riverside Near Jct 91 EB/W B 9 1

38 CA-237 Santa Clara Near Great America Parkway EB/W B 9 1

39 I-880 Alameda Near Oakland/Jct Rte 77 NB/SB 9 1

40 I-280 San Mateo Near Daly City/Ocean Ave NB/SB 9 1

41 US-101 Alameda Near Jct 84 NB/SB 9 1

42 I-5 Sacramento at Arena Blvd NB/SB 9 1

47 CA-99 Fresno Fowler NB/SB 9 1

49 CA-198 Kings Near Jct 41 EB/WB 9 1

50 CA-46 Kern Near Jct 43 EB/WB 9 1

51 9 1

52 9 1

53 9 1

Number of days per 

direction

Weigh Stations

Roadside/overpass Survey Sites

Hours of 

work per 

day

Etiwanda and the 60

Riverside and Agua Mansa (colton)

91 Fwy and the 15 Fwy (Corona)

 * Direction: NB-northbound; SB-southbound; EB-eastbound; WB-westbound 
G-15 

Figure 6. ARB 2008 HDT Field Study Survey Locations 

Information from OD surveys and collected license plates were annotated and 

integrated into a database. License plate data were evaluated and cross referenced to 

the DMV database to obtain state of registration from all trucks, model year and GVWR 

from California-registered trucks. 

OD surveys were generally conducted during daytime hours, with the exception of the 

Desert Hills weigh stations where additional surveys were collected through the night. 

Survey teams invited truck drivers to complete a survey while the trucks were weighed 
G-16 

and inspected. The surveyor inspected the truck and engine to obtain basic truck 

information and asked truck drivers questions verbally to help fill out the OD survey 

questionnaire. The questionnaire was prepared in both English and Spanish. Staff 

manually input OD survey data from each paper survey into a database. Using Arc GIS 

tools, each OD trip, including its origin, destination and route, was mapped onto the 

roadway system. Trips were parsed into segment by county boundary. Therefore, total 

trip distance and miles traveled in each air basin were generated for each trip. VMT 

were summarized by each truck category, survey location, trip type, and air basin. 

License plate images were collected from trucks pulling through a weigh station or 

traveling on the roadway network at normal speeds using high performance digital 

cameras between February and May 2008. At each direction-specific survey location, 

license plate images were collected during daylight hours on weekdays for one to two 

days, except for the Desert Hills weigh station. At the Desert Hills weigh station, 

additional license plate images were also collected during night hours and on Saturday 

in both directions. LP pictures were manually input from each digital photograph into a 

database, and cross-referenced against the DMV registration database to obtain model 

year, body type, and other characteristics. Table 8 shows the data collection period, the 

number of OD records and the number of LP records collected and analyzed at each 

site. 
G-17 

Table 8. ARB 2008 Statewide HDT LP and OD Data Summary 

Date

Start End

Weigh Stations

1 I-80 Cordelia WB 12/17/2007 14 23 519

WB 12/18/2007 0 9 746

4/15/2008 6 15 132

4/16/2008 6 16 137

4/17/2008 x x 133

2 I-10 Desert Hills EB/WB 3/4/2008 2 16 71 691

3/5/2008 1 23 82 62

3/6/2008 0 12 85 513

3/8/2008 6 13 51

3/19/2008 8 15 128 562

3/20/2008 7 12 130 361

3 CA-91 Peralta EB/WB 4/21/2008 6 14 59

4/22/2008 6 14 64

4/23/2008 6 14 56

4/24/2008 6 13 69

4/28/2008 6 15 62

4/29/2008 6 14 76

5/12/2008 8 11 284

5/13/2008 7 15 1570

4 I-5 Castaic NB 4/2/2008 8 12 46

4/3/2008 7 12 70

4/7/2008 7 17 70

4/9/2008 7 12 42

4/10/2008 8 13 70

5 I-15 Cajon NB/SB 3/17/2008 7 14 28 163

3/18/2008 7 14 26 207

4/2/2008 7 14 33 249

4/3/2008 8 12 14

4/7/2008 9 13 60

4/28/2008 8 15 127

4/29/2008 7 15 124

4/30/2008 7 10 34

6 US-101 Conejo NB x 7 17 212

4/15/2008 8 15 83

4/16/2008 6 15 20 333

4/17/2008 7 14 52

4/30/2008 6 10 54

8 I-5 San Onofre NB/SB 4/21/2008 7 15 141 1206

4/22/2008 7 15 141

4/23/2008 7 15 143 1004

9 I-680 W alnut Creek NB/SB 4/28/2008 7 13 80

4/30/2008 7 9 36

5/15/2008 6 15 53

10 I-680 Mission Grade NB 4/28/2008 6 13 64 576

4/29/2008 7 14 112 557

4/30/2008 x x 25

11 I-880 Nimitz NB 5/19/2008 6 16 70 903

5/20/2008 6 16 136 431

5/21/2008 6 15 55

12 I-580 Livermore EB/WB 5/12/2008 6 16 132 584

5/13/2008 6 16 134 134

5/14/2008 6 16 135

5/22/2008 7 7 1

13 US-101 Gilroy SB 5/7/2008 7 15 201 544

5/8/2008 9 13 200 411

14 I-15 Rainbow NB/SB 4/28/2008 7 16 144

4/29/2008 7 15 138

4/30/2008 7 15 133

15 5 Grapevine SB 4/8/2008 7 15 50 695

4/9/2008 7 15 71 384

4/10/2008 7 14 75 1014

16 5 Santa Nella NB / SB 5/4/2008 7 9 168

5/5/2008 7 7 201 199

5/6/2008 6 7 161 199

Number of 

LP Survey

Hour

Number 

of OD 

Site ID # Route Name/Description Direction Survey
G-18 

 (continued) 

Date

Start End

17 99 Chowchilla River NB 4/15/2008 7 14 34 444

4/16/2008 7 14 43 521

4/17/2008 7 14 46 454

18 58 Keene EB 4/21/2008 12 13 80

4/22/2008 9 9 18

4/23/2008 10 12 46

5/19/2008 9 16 71 263

5/20/2008 6 15 85 524

5/21/2008 7 12 74

19 58 Cache Creek WB 4/21/2008 9 16 67 349

4/22/2008 7 15 90 482

4/23/2008 7 14 70

Roadside/overpass Survey Sites

21 I-710 Near Jct 105 NB/SB 2/26/2008 8 12 1543

2/27/2008 6 11 3163

2/28/2008 5 10 2044

23 I-605 Near Jct. 5 NB/SB 3/4/2008 6 13 1972

3/5/2008 5 13 4823

3/6/2008 8 14 3848

25 I-105 Near Jct 19 EB/W B 3/12/2008 8 13 1269

3/13/2008 8 13 1854

26 CA-60 Near Jct 710 EB/WB 3/17/2008 8 13 1153

30 I-15 South of Jct CA 60 NB/SB 4/1/2008 9 15 863

34 CA-91 Near Jct 215 EB/WB 4/7/2008 9 9 87

4/9/2008 8 13 459

35 CA-60 Near Jct 91 EB/WB 4/8/2008 8 14 1293

4/9/2008 14 14 1

38 CA-237 Near Great America Parkway EB/WB 4/13/2008 9 15 241

4/14/2008 9 15 133

39 I-880 Near Oakland/Jct Rte 77 NB/SB 4/15/2008 8 14 2892

40 I-280 Near Daly City/Ocean Ave NB/SB 4/16/2008 8 15 679

41 US-101 Near Jct 84 NB/SB 4/17/2008 8 15 1521

42 I-5 At Arena Bl (95834) NB/SB 4/21/2008 8 16 2644

47 CA-99 Fowler NB/SB 4/29/2008 8 23 2814

49 CA-198 Near Jct 41 EB/WB 4/30/2008 13 24 419

50 CA-46 Near Jct 43 EB/WB 5/8/2008 8 14 405

51 4/15/2008 6 13 162

52 4/16/2008 6 12 106

53 4/17/2008 6 9 35

Total 6215 54570

Etiwanda and the 60

Riverside and Agua Mansa (colton)

91 Fwy and the 15 Fwy (Corona)

Number of 

LP Survey

Hour

Number 

of OD 

Site ID # Route Name/Description Direction Survey

2) Regional Allocation Based on OD Survey Data 

To analyze OD data staff used the NORTAD (BTS, 1998) roadway network, which is 

comprised of the North American Transportation Atlas, as well as highway networks 

representing Mexico and Canada. This roadway network included an estimate of the 

congested speed and length of each roadway link. The United States Geological 

Survey Geographic Names Information System (USGS, 2009) and other internet 

sources were used to assign GIS coordinates for each origin and destination in the OD 

database. Using ArcGIS Network Analyst and congested speeds for each link staff 

estimated the route traveled for each origin-destination pair in the OD database using 

both a fastest path and a shortest path algorithm. Results were assessed visually using 

GIS, and quantitatively by calculating VMT by truck category and air basin. Because 

the number of samples collected at each survey location is not proportional to the 

number of trips passing the specific location, staff scaled up the trip-VMT based on the 

Average Annual Daily Truck Traffic (AADTT) at the locations where the trips were 
G-19 

observed. Staff used Caltrans reported AADTT for location on state highways5

(Caltrans, 2009) and FAF2 AADTT for off-highway locations (FHWA, 2008). 

Results showed that many trucks traveling in California are also participating in trucking 

activities across the United States. More importantly, results suggested interstate 

trucks have a different travel pattern from trucks that do not travel outside of California, 

and that California registered single-unit trucks have a different travel pattern from 

California-registered tractors. While this finding is relatively intuitive, the field study data 

represent the first attempt at a quantitative study to assess differences in travel patterns 

across different types of trucking. Figure 7 compares the OD results visually across 

four inventory categories. 

 

5

 Caltrans Truck Traffic report only provides AADTT on California State Highways. 
G-20 

Figure 7. Estimated Travel Pattern by Inventory Category 

HHDDT Tractor MHDDT

HHDDT Out-of-State HHDDT CAIRP
G-21 

Figure 8 compares results from all trucking categories in the OD data to results 

generated through the US Freight Analysis Framework (FAF2), (FHWA, 2008). Results 

are generally similar, and reflect differences between the various approaches and mix of 

vehicles contained in each study. Table 9 presents the percentage of travel by air basin 

estimated using the OD data by inventory category. 

Figure 8. Heavy Duty Truck Travel Patterns: ARB OD Survey Results vs. FAF2 

ARB OD Survey FAF2 Truck Flow
G-22 

Table 9. Truck VMT Regional Allocation Factors by Fleet Based on OD Analysis 

Air Basin 

HHDDT 

OOS 

HHDDT 

CA IRP 

HHDDT 

Tractor

HHDDT 

Single 

HHDDT 

All 

MHDDT 

All 

Great Basins Valley 0.3% 0.6% 0.2% 0.2% 0.3% 0.4%

Lake County 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%

Lake Tahoe 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%

Mountain Counties 2.6% 0.9% 0.6% 0.6% 1.6% 0.9%

Mojave Desert 27.7% 19.3% 5.8% 10.4% 19.1% 11.7%

North Coast 0.4% 0.3% 0.4% 0.7% 0.4% 0.8%

North Central Coast 0.4% 0.5% 0.8% 0.9% 0.6% 0.9%

Northeast Plateau 3.2% 2.6% 0.4% 0.0% 2.2% 0.1%

South Coast 14.3% 21.1% 28.6% 24.9% 20.2% 26.2%

South Central Coast 0.5% 0.6% 1.0% 2.2% 0.7% 1.8%

San Diego County 1.3% 2.9% 6.7% 3.9% 3.2% 5.0%

San Francisco Bay 4.5% 4.0% 10.8% 15.1% 6.4% 12.3%

San Joaquain Valley 29.2% 33.1% 37.9% 36.9% 32.8% 30.7%

Salton Sea 2.8% 3.8% 3.1% 2.6% 3.1% 4.8%

Sacramento Valley 12.8% 10.4% 3.7% 1.6% 9.3% 4.4%

Total 100% 100% 100% 100% 100% 100%

3) OD and LP Survey Data Analysis 

In addition to evaluating the OD analysis results, staff developed an alternative analysis 

using both the LP and OD data. The general approach was to estimate the number of 

inter air basin trips and intra air basin trips by inventory category and air basin, and to 

multiply those trip estimates by an assumed trip length within each air basin to estimate 

VMT by air basin for each inventory truck category. These results could then be used to 

develop a percent VMT allocation by inventory truck category. 

The first step in this process was to separate LP data collection sites into two types: 

inter-regional sites and intra-regional sites. Inter-regional sites are located near the 

border of one air basin and were likely to capture inter-regional truck trips, while intraregional sites were located in the middle of air basins and were likely to capture trips 

within a single air basin. Interregional site are marked with circles and intra-regional 

sites are marked with stars as shown in Figure 9. 
G-23 

Figure 9. License Plate Survey Locations by Trip Type 

License plates surveyed were then cross-referenced to the California DMV registration 

database to obtain vehicle registration information. Based on the location of vehicle 

registration, staff separated data at each site into trucks traveling inside or outside of the 

air basin in which they were registered. Since the survey was conducted in selected 

urban areas (South Coast and Bay area) and rural areas (Mojave Desert and San 

Joaquin Valley) in California, we also grouped the LPs into urban and rural groups. The 

average fractions of trips by trucks registered inside vs. outside of an air basin observed 

at inter-air basin locations and intra-air basin locations, respectively, are shown in Table 

10, where “inAB” refers to trucks traveling within their air basin of registration and 

“outAB” refers to trucks traveling outside their air basin of registration. 
G-24 

Table 10. Average Percentages of Truck License Plates by Registered Air Basin 

for Intra and Inter Air Basin Survey Location Groups 

Air Basin Survey T7CAIRP T7Tractor T7Single T6 

Group Location inAB outAB inAB outAB inAB outAB inAB outAB 

SC Inter 0.34 0.66 0.37 0.63 0.43 0.57 0.39 0.61 

SC Intra 0.76 0.24 0.89 0.11 0.92 0.08 0.90 0.10 

SF Inter 0.20 0.80 0.40 0.60 0.48 0.52 0.46 0.54 

SF Intra 0.27 0.73 0.56 0.44 0.70 0.30 0.76 0.24 

MD Inter 0.15 0.85 0.09 0.91 0.06 0.94 0.10 0.90 

SJV Inter 0.25 0.75 0.32 0.68 0.40 0.70 0.22 0.81 

SJV Intra 0.52 0.48 0.71 0.29 0.82 0.18 0.66 0.34 

URBAN Inter 0.28 0.72 0.38 0.62 0.45 0.55 0.41 0.59

URBAN Intra 0.63 0.37 0.80 0.20 0.86 0.14 0.86 0.14

RURAL Inter 0.22 0.78 0.25 0.75 0.26 0.74 0.17 0.83

RURAL Intra 0.52 0.48 0.71 0.29 0.82 0.18 0.66 0.34

Staff categorized three types of trips for each area basin and inventory category: trips 

within an air basin by local trucks (trucks registered in that air basin), inter-air basin trips 

by local trucks, and inter-air basin trips by non-local trucks (trucks registered outside of 

the air basin of travel). Staff assumed that the distribution of the number of trips is 

consistent with the distribution of the overall truck population, and that at intra-regional 

sites the observed ratio of trips between local trucks and non-local trucks represented 

the real ratio of population of trucks registered in vs. out of the specific air basin. The 

population of trucks registered in each air basin was obtained from analyzing DMV truck 

registration data. 

The non-local truck population was estimated using the local truck population and the 

ratio of non-local to local trips observed at intra-regional sites (Equation 2). Next, staff 

assumed that at inter-regional sites, the observed ratio of trips by local trucks vs. nonlocal trucks represented the ratio of population between local trucks making interregional trips and non-local trucks making inter-regional trips. Thus the population of 

local trucks making inter-regional trips was derived using the population of non-local 

trucks and the ratio of trips observed at inter-regional sites (Equation 3). Finally, the 

population of local-trucks that make inter-regional trips is estimated as the difference 

between total registered population in the air basin and the population of local trucks 

making inter-regional trips (Equation 4). Staff also assumed that the existence of nonlocal trucks traveling completely within an air basin is insignificant and distributed evenly 

statewide, and therefore will not affect the analysis. 

 
G-25 

(* )

,

,

, ,

ab fl

ab fl

ab fl ab fl RAI

RAO PIO = P Equation 2

(* )

,

.

, ,

ab fl

ab fl

ab fl ab fl RIO

RII PII = PIO Equation 3 

PIRab, fl = Pab, fl − PIIab, fl Equation 4 

where, 

PIO = the population of trucks traveling in and out of an air basin other than the 

air basin in which they are registered.

ab = air basin 

fl = inventory category 

P = truck population registered in an air basin by inventory category 

RAO = the average fraction of trucks traveling in an air basin other than their 

registration air basin, seen at an intra-air basin survey location 

RAI = the average fraction of trucks traveling in their registration air basin, seen 

at an intra-air basin survey location.

PII = the population of trucks traveling in and out of their registration air basin, 

seen at an inter-air basin survey location 

RII = the average fraction of trucks traveling in an air basin where they are 

registered, seen at an inter-air basin survey location 

RIO = the average fraction of trucks traveling in an air basin other than their 

registration air basin, seen at an inter-air basin survey location 

PIR = the population of trucks traveling completely in their registration air basin 

The relative ratio between the above populations reflected the relative ratio of trips by 

corresponding population. It should be noted that it is the relative ratio, not the absolute 

value that impacts the regional allocation. Table 11, Table 12, and Table 13 display 

estimated truck population (surrogate for trips) by trip type and inventory category. 
G-26 

Table 11. Intra Air Basin Truck Population by Trucks Registered in the Air Basin 

Air Basin 

HHDDT CA 

IRP 

HHDDT InState 

Tractor 

HHDDT InState Single MHDDT 

All 

South Coast 168,447 240,514 112,619 2,471,067 

San Francisco 6,829 34,336 30,360 828,013 

Mojave Desert 16,845 10,110 8,409 106,131 

San Joaquin Valley 51,421 102,215 45,940 667,300 

Great Basins Valley 255 316 462 3,894 

Lake County 44 462 673 6,368 

Lake Tahoe 444 21 131 3,468 

Mountain Counties 2,585 4,281 7,811 69,687 

North Coast 1,548 4,057 6,914 38,309 

North Central Coast 6,047 7,450 7,051 90,369 

Northeast Plateau 1,535 1,069 1,357 9,917 

Sacramento Valley 25,513 33,221 28,210 354,499 

South Central Coast 3,963 13,572 14,200 243,396 

San Diego County 12,124 34,952 21,444 419,807 

Salton Sea 4,613 10,455 5,494 76,899 

Table 12. Inter Air Basin Truck Population by Trucks Registered in the Air Basin 

Air Basin 

HHDDT CA 

IRP 

HHDDT InState Tractor HHDDT InState Single MHDDT All 

South Coast 32,887 20,005 8,320 193,157 

San Francisco 15,872 37,841 20,264 307,155 

Mojave Desert 3,406 411 124 6,541 

San Joaquin Valley 22,772 24,695 6,798 110,492 

Great Basins Valley 151 111 105 2,250 

Lake County 26 161 153 3,680 

Lake Tahoe 263 7 30 2,004 

Mountain Counties 439 598 1,002 7,753 

North Coast 916 1,417 1,577 22,139 

North Central Coast 3,578 2,602 1,608 52,223 

Northeast Plateau 908 373 309 5,731 

Sacramento Valley 15,094 11,600 6,433 204,861 

South Central Coast 1,371 2,185 1,214 30,172 

San Diego County 2,282 3,107 1,271 15,297 

Salton Sea 1,596 1,683 470 9,533 
G-27 

Table 13. Inter Air Basin Truck Population by Trucks Registered 

out of the Air Basin 

Air Basin 

HHDDT 

OOS 

HHDDT 

CA IRP 

HHDDT 

Tractor 

HHDDT 

Single MHDDT All

South Coast 1,319,639 64,380 33,720 10,997 299,380 

San Francisco 257,693 62,613 56,087 21,777 367,524 

Mojave Desert 153,728 19,005 4,358 1,927 58,710 

San Joaquin Valley 728,206 69,627 52,563 11,909 405,282 

Great Basins Valley 3,341 381 177 128 3,201 

Lake County 3,625 66 258 187 5,236 

Lake Tahoe 2,139 663 12 36 2,851 

Mountain Counties 39,897 1,108 956 1,218 11,031 

North Coast 39,212 2,312 2,267 1,917 31,498 

North Central Coast 67,631 9,033 4,163 1,955 74,300

Northeast Plateau 13,249 2,293 597 376 8,154 

Sacramento Valley 286,578 38,108 18,564 7,823 291,464 

South Central Coast 87,128 5,006 6,526 3,481 142,547 

San Diego County 167,315 8,329 9,280 3,643 72,270 

Salton Sea 58,024 5,827 5,027 1,347 45,037 

Next staff converted the estimated population of trucks by trip type, air basin and fleet 

category to VMT by trip type, air basin and fleet category. This required estimation of 

average travel distance within each air basin for each trip type. Average travel 

distances per trip were estimated using the OD data. Each OD record was crossreferenced to the DMV database to identify the air basin in which each truck was 

registered. Using these data, staff calculated the average travel miles by travel air 

basin, trip type and inventory category. In evaluating the OD data, staff found that intraair basin trips were under-represented. This was a consequence of conducting surveys 

at weigh stations which tend to be located in between air basins and capture interregional travel. As a result, staff estimated an average intra-air basin trip distance 

based on travel demand model output developed by SCAG and the San Joaquin Valley 

transportation agencies in their heavy-duty truck models. Average travel miles of intraair basin trips by HHDDT and MHDDT were estimated to be 25 and 20 miles, 

respectively, in San Joaquin Valley air basin (Cambridge Systematics, 2008), and 15 

and 13 miles, respectively, in South Coast air basin (SCAG, 1999). For inter-air basin 

trips, that is, trips traversing multiple air basins, staff divided trips into segments in each 

air basin and compiled the average travel miles in each air basin by trip type. For 

interstate trips, only travel miles accrued within California were used. Table 14 and 

Table 15 show average travel miles within a specific air basin for inter air basin truck 

trips by local trucks and those by non-local trucks, respectively. 
G-28 

Table 14. Average Travel Miles for Inter Air Basin Truck Trips by Trucks 

Registered in the Air Basin

Air Basin 

HHDDT 

CA IRP 

HHDDT InState Tractor HHDDT InState Single MHDDT All 

South Coast 97 85 59 67 

San Francisco 62 53 61 61 

Mojave Desert 104 56 28 40 

San Joaquin Valley 182 138 70 77 

Great Basins Valley 115 74 39 54 

Lake County 99 74 39 54 

Lake Tahoe 99 74 39 54 

Mountain Counties 99 74 39 33 

North Coast 99 74 39 54 

North Central Coast 55 52 28 39 

Northeast Plateau 82 74 39 54 

Sacramento Valley 100 58 44 46 

South Central Coast 48 40 46 33 

San Diego County 75 77 65 47 

Salton Sea 107 102 17 107 

Table 15. Average Travel Miles for Inter Air Basin Truck Trips by Trucks Not 

Registered in the Air Basin 

Air Basin 

HHDDT 

OOS 

HHDDT 

CA IRP 

HHDDT InState 

Tractor 

HHDDT InState 

Single 

MHDDT 

All 

South Coast 88 108 97 70 75 

San Francisco 66 56 56 56 56 

Mojave Desert 169 135 91 68 80 

San Joaquin Valley 207 190 149 189 163 

Great Basins Valley 160 127 68 131 118 

Lake County 97 100 66 76 77 

Lake Tahoe 13 100 2 76 77 

Mountain Counties 65 47 36 61 38 

North Coast 72 114 65 65 82 

North Central Coast 53 57 45 33 38 

Northeast Plateau 83 81 83 76 82 

Sacramento Valley 136 129 75 52 66 

South Central Coast 45 48 40 48 41 

San Diego County 55 64 61 59 53 

Salton Sea 66 73 69 40 61 
G-29 

To calculate regional allocation factors by inventory category using the LP and OD 

study data, staff multiplied the estimated trips per air basin by inventory category by the 

assumed average travel miles per trip by air basin by inventory category. Results are 

shown in Table 16. 

Table 16. Truck VMT Regional Allocation Factors by Fleet Based on OD/LP 

Analysis 

Air Basin 

HHDDT 

OOS 

HHDDT 

CAIRP 

HHDDT InState 

Tractor 

HHDDT InState 

Single 

HHDDT 

All 

MHDDT 

All 

South Coast 30.4% 24.9% 24.1% 21.1% 26.9% 23.2% 

San Francisco 4.3% 10.5% 15.9% 20.7% 9.9% 17.2% 

Mojave Desert 7.2% 6.6% 1.9% 2.5% 5.3% 2.4% 

San Joaquin Valley 40.4% 36.6% 38.7% 27.8% 38.0% 30.1% 

Great Basins Valley 0.1% 0.1% 0.1% 0.2% 0.1% 0.2% 

Lake County 0.1% 0.0% 0.1% 0.3% 0.1% 0.2% 

Lake Tahoe 0.0% 0.2% 0.0% 0.1% 0.0% 0.1% 

Mountain Counties 0.7% 0.3% 0.5% 2.2% 0.7% 0.7% 

North Coast 0.7% 0.8% 1.0% 2.6% 1.0% 1.6% 

North Central Coast 1.0% 1.7% 1.4% 2.1% 1.3% 2.3% 

Northeast Plateau 0.3% 0.6% 0.3% 0.5% 0.4% 0.4% 

Sacramento Valley 10.3% 13.9% 8.1% 10.0% 10.5% 12.3% 

South Central Coast 1.0% 0.8% 1.9% 4.1% 1.5% 4.0% 

San Diego County 2.4% 1.7% 3.7% 4.4% 2.8% 3.4% 

Salton Sea 1.0% 1.4% 2.2% 1.4% 1.4% 1.8% 

Total 100% 100% 100% 100% 100% 100% 

4) Discussion of Field Study Results 

The ARB field study is the most comprehensive study of its kind that has been 

conducted to date on truck travel in California. Results show significant differences in 

truck travel between broad types of trucking operations in California that are important 

to consider when developing an emissions inventory representing heavy duty trucks. 

Despite the large amount of data collected there are still some limitations to consider. 

For example, it was necessary to obtain OD data primarily at weigh stations. This was 

done for practical purposes as conducting OD surveys at most roadside locations is 

disruptive to traffic and places survey staff unacceptably close to traffic. However most 

weigh stations are located on roadways on the outskirts of urban areas and as a result 

will see more inter-regional than intra-regional trips. As was observed in the LP data, 

most trips at roadside locations were intra-air basin trips traveled by trucks that are also 

registered in the air basin – local trips for which OD data were limited. In another 

example, while many sites were sampled, some regions, especially rural areas such as 

the northern portion of the state were not well covered by the field study due to staffing 

limitations on data collection. Regional allocation factors developed to represent these 

areas may be more uncertain as a result. 
G-30 

In light of these limitations, staff evaluated field study results along with other 

corroborative data on an inventory category specific basis to decide on regional 

allocation factors for each category. 

E. Regional Allocation of Activity and Emissions 

Staff derived a regional allocation for each truck category by analyzing relevant field 

study results and corroborative data sources specific to the trucking type or vocation. 

1) Interstate Trucks 

Table 17 compares the regional distribution factors developed using the OD and OD/LP 

approaches to regional distribution assumptions in EMFAC2002 and EMFAC2007. 

Table 17. Comparison of CA Interstate Truck VMT Regional Allocations 

Air Basin OD LP/OD EMFAC2002 EMFAC2007 Assumed 

Great Basins Valley 0.6% 0.1% 0.2% 0.6% 0.6%

Lake County 0.0% 0.0% 0.1% 0.0% 0.0%

Lake Tahoe 0.0% 0.2% 0.1% 0.1% 0.1%

Mountain Counties 0.9% 0.3% 1.1% 1.8% 1.8%

Mojave Desert 19.3% 6.7% 1.5% 15.1% 15.1%

North Coast 0.3% 0.8% 1.3% 1.4% 1.4%

North Central Coast 0.5% 1.7% 2.5% 1.8% 1.8%

Northeast Plateau 2.6% 0.6% 0.3% 1.5% 1.5%

South Coast 21.1% 25.2% 36.9% 20.0% 20.0%

South Central Coast 0.6% 0.8% 2.6% 1.3% 1.3%

San Diego County 2.9% 1.8% 7.5% 3.8% 3.8%

San Francisco Bay 4.0% 9.1% 17.3% 7.8% 7.8%

San Joaquin Valley 33.1% 37.2% 17.6% 28.9% 28.9%

Salton Sea 3.8% 1.4% 1.8% 6.5% 6.5%

Sacramento Valley 10.4% 14.1% 9.3% 9.6% 9.6%

Total 100% 100% 100% 100% 100%

ARB staff revised the VMT distribution for HHDDT in EMFAC2007, as documented in 

ARB (2006a). The document described the redistribution of HHDDT VMT from a 

registration to a travel basis. The travel based VMT distribution was estimated using a 

combination of data from a survey conducted by California Department of 

Transportation (Caltrans) in 1999, and modeled information from MVSTAFF, an annual 

report developed by Caltrans. Detailed descriptions of the methodologies in developing 

the VMT redistribution can be found in the Technical Memo. Although the distribution 

was applied to the entire HHDDT fleet in EMFAC2007, the underlying Caltrans survey 

was geared toward long-haul trucks since the survey data were collected at weigh 

stations, agricultural inspection stations and rest areas. 

The ARB 2008 field study was designed to focus on intra-California trips. Compared to 

the Caltrans 1999 study, the ARB field study captured more intra-state trips and local 

trips in both origin-destination and license plate data. In particular, two thirds of the 

license plate data were collected at roadside locations where intra-state trips were more 
G-31 

likely to be captured. As a result, regional allocations based on the OD and LP analysis 

is not appropriate for distributing inter-state trip VMT. Staff chose to use the regional 

allocation developed for HHDDT VMT redistribution in EMFAC2007 for all interstate 

trucks, including out-of-state registered trucks and California registered inter-state 

trucks. The “assumed” allocations in the table were used for interstate fleets. 

2) Heavy-Heavy Duty In-State Tractors 

Table 18 compares regional distribution factors developed using the OD and OD/LP 

approaches to assumptions in EMFAC2002 and EMFAC2007. 

Table 18. Comparison of CA In-State Tractor HHDT VMT Regional Allocations 

Air Basin OD LP/OD EMFAC2002 EMFAC2007 Assumed 

Great Basins Valley 0.2% 0.1% 0.2% 0.6% 0.16%

Lake County 0.0% 0.1% 0.1% 0.0% 0.06%

Lake Tahoe 0.0% 0.0% 0.1% 0.1% 0.00%

Mountain Counties 0.6% 0.5% 1.1% 1.8% 0.56%

Mojave Desert 5.8% 1.9% 1.5% 15.1% 3.83%

North Coast 0.4% 1.0% 1.3% 1.4% 0.71%

North Central Coast 0.8% 1.4% 2.5% 1.8% 1.13%

Northeast Plateau 0.4% 0.3% 0.3% 1.5% 0.32%

South Coast 28.6% 24.1% 36.9% 20.0% 26.34%

South Central Coast 1.0% 1.9% 2.6% 1.3% 1.49%

San Diego County 6.7% 3.7% 7.5% 3.8% 5.20%

San Francisco Bay 10.8% 15.9% 17.3% 7.8% 13.34%

San Joaquin Valley 37.9% 38.7% 17.6% 28.9% 38.32%

Salton Sea 3.1% 2.2% 1.8% 6.5% 2.61%

Sacramento Valley 3.7% 8.1% 9.3% 9.6% 5.93%

Total 100% 100% 100% 100% 100%

The HHDDT in-state tractor fleet category is a mix of vocational trucks that are 

dedicated to specific industries/services and travel mostly in California close to their 

base of operations, and trucking companies that regularly travel across California. 

Therefore neither a travel based nor a registration based allocation would fully describe 

the HHDDT tractor travel. ARB field study results are particularly relevant to this 

category. 

Although the scale of OD survey conducted by ARB in 2008 was smaller than Caltrans 

survey in 1999, it was designed to capture both inter-regional and local trips by different 

inventory categories, and was supplemented by the large-scale LP survey. Staff used 

the average of the results from OD survey, and OD/LP survey for the regional allocation 

as shown in Table 18. 

3) Heavy-Heavy Duty In-State Single-Unit Trucks 

Staff believes the vast majority of single-unit trucks make short haul trips because the 

trucks are generally used for local delivery or vocational applications such as street 
G-32 

sweeping, liquids transport, drilling and other uses. These types of trips were underrepresented in both the Caltrans 1999 study and the ARB field study. The degree to 

which local trips were under-estimated is highly uncertain and depends on the selection 

of survey locations. Therefore, regional allocations developed based on these survey 

data are not appropriate for allocating single-unit truck VMT. Staff assumed that singleunit trucks travel mostly in their registered air basin and applied a registration-based 

regional allocation method. This assumption was supported by our observations in the 

ARB field study. Staff developed registration populations by air basin from DMV data 

after excluding specific fleets including agricultural trucks and construction trucks, and 

multiplied populations with age-specific accrual rates to derive VMT by registration area 

basin. Table 19 presents regional distribution factors developed using the OD and 

OD/LP approaches, regional distribution assumptions in EMFAC2002 and EMFAC2007 

and the one developed in this analysis. 

Table 19. Comparison of CA In-state Single-Unit HHDT VMT Regional Allocations 

Air Basin OD LP/OD EMFAC2002 EMFAC2007 Assumed 

Great Basins Valley 0.2% 0.2% 0.2% 0.6% 0.1%

Lake County 0.0% 0.3% 0.1% 0.0% 0.1%

Lake Tahoe 0.0% 0.1% 0.1% 0.1% 0.1%

Mountain Counties 0.6% 2.2% 1.1% 1.8% 2.5%

Mojave Desert 10.4% 2.5% 1.5% 15.1% 1.6%

North Coast 0.7% 2.6% 1.3% 1.4% 2.4%

North Central Coast 0.9% 2.1% 2.5% 1.8% 2.3%

Northeast Plateau 0.0% 0.5% 0.3% 1.5% 0.0%

South Coast 24.9% 21.1% 36.9% 20.0% 40.7%

South Central Coast 2.2% 4.1% 2.6% 1.3% 4.3%

San Diego County 3.9% 4.4% 7.5% 3.8% 7.7%

San Francisco Bay 15.1% 20.7% 17.3% 7.8% 18.0%

San Joaquin Valley 36.9% 27.8% 17.6% 28.9% 10.1%

Salton Sea 2.6% 1.4% 1.8% 6.5% 1.1%

Sacramento Valley 1.6% 10.0% 9.3% 9.6% 9.0%

Total 100% 100% 100% 100% 100%
G-33 

4) Medium-Heavy Duty In-State Trucks 

Like HHDDT single-unit trucks, MHDDT instate trucks mostly make local delivery or 

vocational trips that were under-represented in both the Caltrans 1999 and ARB 2008 

OD surveys. Staff applied the registration-based regional allocation method to mediumheavy duty in-state trucks, including both GVWR above and below 26,000 lbs. Table 20 

compares regional distribution factors developed using the OD and OD/LP approaches, 

regional distribution assumptions in EMFAC2002 and EMFAC2007 and the one 

developed in this analysis. 

Table 20. Comparison of CA In-State MHDDT VMT Regional Allocations 

Air Basin OD LP/OD EMFAC2002 EMFAC2007 Assumed 

Great Basins Valley 0.4% 0.2% 0.2% 0.1% 0.1%

Lake County 0.0% 0.2% 0.1% 0.1% 0.1%

Lake Tahoe 0.0% 0.1% 0.1% 0.1% 0.1%

Mountain Counties 0.9% 0.7% 1.1% 0.9% 1.1%

Mojave Desert 11.7% 2.4% 1.5% 2.2% 1.4%

North Coast 0.8% 1.6% 1.3% 0.7% 0.8%

North Central Coast 0.9% 2.3% 2.5% 2.6% 2.0%

Northeast Plateau 0.1% 0.4% 0.3% 0.2% 0.0%

South Coast 26.2% 23.2% 36.9% 42.5% 44.5%

South Central Coast 1.8% 4.0% 2.6% 3.5% 4.1%

San Diego County 5.0% 3.4% 7.5% 7.9% 7.3%

San Francisco Bay 12.3% 17.2% 17.3% 17.1% 19.0%

San Joaquin Valley 30.7% 30.1% 17.6% 12.1% 9.9%

Salton Sea 4.8% 1.8% 1.8% 1.3% 1.0%

Sacramento Valley 4.4% 12.3% 9.3% 8.7% 8.6%

Total 100% 100% 100% 100% 100%
G-34 

5) Drayage Trucks 

Drayage trucks were not identified during the 2008 field study and as a result were not 

specifically analyzed as part of that study. The regional allocation of drayage truck 

emissions is based upon the emissions analysis developed for ARB’s Drayage Truck 

Regulation (ARB, 2007a). As described in Appendix B of the Technical Support 

Document for the Drayage Truck Regulation, the regional allocations were based on OD 

surveys conducted by Ports of Los Angles and Long Beach and a study done by the 

Metropolitan Transportation Commission in the Bay Area. Using the study results, staff 

estimated VMT in each air basin by the drayage trucks serving the ports and developed 

the regional allocations. These are shown in Table 21. 

Table 21. Comparison of CA Drayage Truck Regional Allocations 

Air Basin 

Los Angeles 

Ports/Railyards 

Bay Are 

Ports/Railyards 

Other Drayage 

Trucks 

Great Basins Valley 0.0% 0.0% 0.0% 

Lake County 0.0% 0.0% 0.0% 

Lake Tahoe 0.0% 0.0% 0.0% 

Mountain Counties 0.0% 2.0% 0.0% 

Mojave Desert 4.3% 0.0% 0.0% 

North Coast 0.0% 0.0% 3.5% 

North Central Coast 0.0% 1.7% 0.0% 

Northeast Plateau 0.0% 0.0% 0.0% 

South Coast 81.7% 0.0% 0.0% 

South Central Coast 0.1% 0.0% 11.6% 

San Diego County 1.4% 0.0% 34.0% 

San Francisco Bay 0.0% 63.6% 28.8% 

San Joaquin Valley 8.8% 28.2% 18.3% 

Salton Sea 3.7% 0.0% 0.0% 

Sacramento Valley 0.0% 4.5% 3.9% 

Total 100% 100% 100% 
G-35 

6) Construction Trucks 

For construction fleets, staff assumed that the regional allocation is proportional to the 

regional rate of population growth. This surrogate is designed to reflect where 

populations are growing and therefore where construction is more likely to be focused. 

The Demographic Research Unit of California Department of Finance (DOF, 2009) 

provides population estimates and projections by county. The populations within 

counties were then distributed into air basins based on census data. Staff calculated 

the year to year increase in population within each air basin and used the fraction of the 

population growth in air basin versus statewide growth as a surrogate for construction 

fleets regional allocation. The resulting allocations are shown in Table 22 for calendar 

year 2008, and projected for 2020 and 2030 where DOF provided a population forecast. 

Staff interpolated regional allocation factors linearly between forecast years. 

Table 22. Regional Allocation for Construction Fleets 

Calendar Year Air Basin 

2008 2020 2030 

Great Basin Valleys 0.0% 0.1% 0.1% 

Lake County 0.1% 0.2% 0.2% 

Lake Tahoe 0.2% 0.2% 0.2% 

Mountain Counties 0.3% 1.5% 1.2% 

Mohave Desert 2.4% 3.4% 3.2% 

North Coast 0.3% 0.7% 0.6% 

North Central Coast 1.7% 1.6% 1.7% 

Northeast Plateau 0.0% 0.3% 0.2% 

South Coast 35.4% 37.7% 31.9% 

South Central Coast 3.0% 3.0% 2.8% 

San Diego 10.7% 6.5% 7.8% 

San Francisco Bay 22.0% 10.1% 13.7% 

San Joaquin Valley 13.1% 21.7% 23.3% 

Salton Sea 3.0% 3.8% 3.3% 

Sacramento Valley 7.7% 9.3% 9.7% 

Total 100% 100% 100% 
G-36 

7) Agricultural Trucks 

ARB staff, in conjunction with agricultural trade associations, administered a survey to 

farmers, ranchers, and other agricultural businesses designed to identify and 

characterize trucks serving the agricultural sector. The results were used to develop 

population, age distribution and accrual rates as described in the Appendix G of the 

Technical Support Document (ARB, 2008). In addition to the characteristics in 

Appendix G, the survey also collected information regarding where the trucks had 

traveled. The results indicated that although most of the agricultural trucks traveled 

within one air basin boundary, about 30 percent of them did travel across air basins. 

The results, shown in Table 23 are generally consistent with the distribution of irrigated 

acreage given the 30 percent of agricultural trucks that travel across multiple regions. 

In this analysis, staff used the agricultural survey-based regional allocation factors. 

Table 23. Regional Allocation for Agricultural Activities 

Air Basin 

Irrigated 

Acreage 

Agricultural 

Truck Survey Assumed 

Great Basins Valley 0.3% 0.3% 0.3% 

Lake County 0.8% 1.6% 1.6% 

Lake Tahoe 0.0% 0.0% 0.0% 

Mountain Counties 1.1% 2.1% 2.1% 

Mojave Desert 5.3% 0.7% 0.7% 

North Coast 0.6% 5.3% 5.3% 

North Central Coast 4.2% 3.9% 3.9% 

Northeast Plateau 5.0% 2.3% 2.3% 

South Coast 0.5% 2.4% 2.4% 

South Central Coast 4.1% 4.6% 4.6% 

San Diego County 1.1% 2.1% 2.1% 

San Francisco Bay 2.1% 6.5% 6.5% 

San Joaquin Valley 49.3% 45.1% 45.1% 

Salton Sea 5.5% 3.7% 3.7% 

Sacramento Valley 20.0% 19.3% 19.3% 

Total 100% 100% 100% 
G-37 

8) Utility Trucks 

A utility company is defined in the fleet rule for public agencies and utilities as a 

privately-owned company that provides water, natural gas, and electricity (ARB, 2006b). 

Some of the large utility companies that operate throughout California register all their 

trucks at their corporate office making it infeasible to use the actual registration data to 

allocate utility fleet VMT. However, staff believes most utility trucks are used to service 

the general population and would have similar allocation as MHDDTs. As a result, staff 

assumed the same MHDDT spatial allocation in EMFAC 2007 for utility trucks, as 

shown in Table 24. 

Table 24. Regional Allocation for Utility Trucks 

Air Basin 

MHDDT 

Utility 

HHDDT 

Utility 

MHDDT 

EMFAC 2007

HHDDT 

EMFAC 2007

Great Basins Valley 0.1% 0.1% 0.1% 0.6% 

Lake County 0.1% 0.1% 0.1% 0.0% 

Lake Tahoe 0.1% 0.1% 0.1% 0.1% 

Mountain Counties 0.9% 0.9% 0.9% 1.8% 

Mojave Desert 2.2% 2.2% 2.2% 15.1% 

North Coast 0.7% 0.7% 0.7% 1.4% 

North Central Coast 2.6% 2.6% 2.6% 1.8% 

Northeast Plateau 0.2% 0.2% 0.2% 1.5% 

South Coast 42.5% 42.5% 42.5% 20.0% 

South Central Coast 3.5% 3.5% 3.5% 1.3% 

San Diego County 7.9% 7.9% 7.9% 3.8% 

San Francisco Bay 17.1% 17.1% 17.1% 7.8% 

San Joaquin Valley 12.1% 12.1% 12.1% 28.9% 

Salton Sea 1.3% 1.3% 1.3% 6.5% 

Sacramento Valley 8.7% 8.7% 8.7% 9.6% 

Total 100% 100% 100% 100% 
G-38 

9) Regional Allocation Results 

Using the regional allocation described in the previous section, staff estimated the 

MHDDT and HHDDT VMT for each air basin and calendar year. Table 25 shows the 

VMT results for selected air basin by fleet category in 2008. 

Table 25. VMT by Fleet Category in Selected Air Basins, 2008 

2008 Air Basin VMT, Thousand Miles/Day Fleet Category 

SCAB SFBAB SJVAB SVAB 

MHDDT Ag 7 20 139 59 

MHDDT CAIRP 13 5 19 6 

MHDDT instate 3,577 1,878 959 832 

MHDDT instate construction 530 329 196 115 

MHDDT OOS 8 3 11 4 

MHDDT utility 19 9 7 5 

HHDDT Ag 18 49 343 146 

HHDDT CAIRP 1,341 524 1,936 641 

HHDDT CAIRP construction 102 63 38 22 

HHDDT NNOOS 1,508 590 2,178 721 

HHDDT NOOS 488 191 705 233 

HHDDT other port - 59 37 8 

HHDDT POAK - 205 91 14 

HHDDT POLA 1,514 - 163 - 

HHDDT single 721 318 178 160 

HHDDT single construction 264 164 98 57 

HHDDT tractor 1,891 958 2,752 426 

HHDDT tractor construction 197 122 73 43 

HHDDT utility 11 5 4 3 

F. Impact of the Recession on VMT and Vehicle Sales 

The recession impacts the emissions inventory both in terms of reduced activity and in 

terms of aging fleets due to reduced new truck sales. Staff developed assumptions for 

the impact of the recession and future year forecasts for both VMT and vehicle sales by 

inventory category. These assumptions were fundamentally based on the approach 

described in previous documentation (ARB, 2008 and ARB, 2009), where staff defined a 

fast recovery scenario and a slow recovery scenario. The chosen forecast is the 

average of the two bounding scenarios. This section provides assumptions on activity 

and new truck sales for each inventory category in graphical format. 

To forecast VMT by model year staff followed a multi-step process. To forecast future 

year VMT, staff multiplied base year VMT by the revised growth factor reflecting the 

recession for each calendar year for each inventory category. Staff used the 

methodology described (ARB, 2008 and ARB, 2009) to forecast a model year 

distribution in each future year based on the assumed sales fraction for each category. 
G-39 

Next, staff multiplied the age-accrual rate schedule by the assumed age distribution in 

each calendar year for each category to estimate the population-weighted mileage 

accrual rates for each calendar year and category. To estimate population by model 

year, staff divided total calendar year VMT by weighted accrual rates in each calendar 

year. 

This approach is a simplification because it assumes the total population in each 

category will fluctuate with the recession. In reality, to respond to the recession some 

fleets will downsize or park vehicles, and some fleets will continue to operate most if not 

all of their vehicles with less mileage accrual per year. 

1) Drayage Trucks 

Drayage truck activity is developed based on Twenty-foot equivalent unit (TEU) 

throughput at ports of Los Angeles, Long Beach, and Oakland. Staff estimates that 

drayage truck VMT in southern California decreased 25 percent between 2006 and 

2009 as shown in Figure 10; and in northern California decreased by 14 percent based 

on container throughput, as shown in Figure 11. The Drayage Truck category was not 

adjusted for sales during the recession because of the impacts of the Drayage Truck 

Rule. 

Figure 10. Drayage Truck VMT Projection for Ports of Los Angeles and Long 

Beach and Intermodal Railyards 

0.00

0.50

1.00

1.50

2.00

2.50

2006 2008 2010 2012 2014 2016 2018 2020 2022

Ratio to 2006 VMT

No Recession Fast Recovery Slow Recovery Average
G-40 

Figure 11. Drayage Truck VMT Projection for the Port of Oakland and Intermodal 

Railyards 

0.00

0.50

1.00

1.50

2.00

2.50

3.00

2006 2008 2010 2012 2014 2016 2018 2020 2022

Ratio to 2006 VMT

No Recession Fast Recovery Slow Recovery Average

2) Construction Trucks 

Assumptions for this category are described in Section C-1. 

3) MHDDT 

To estimate the impact of recession on MHDDTs, staff reviewed BOE diesel fuel sales 

data (BOE, 2010b) and estimated VMT growth using bounding scenarios as shown in 

Figure 12. To forecast MHDDT truck sales, staff used the same method documented 

(ARB, 2008 and ARB, 2009). 
G-41 

Figure 12. MHDDT VMT Growth Assumption 

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

2006 2008 2010 2012 2014 2016 2018 2020 2022

Ratio to 2006 VMT

No Recession Fast Recovery Slow Recovery Average

Figure 13. MHDDT Sales Forecast 

0

50

100

150

200

250

300

1985 1990 1995 2000 2005 2010 2015 2020 2025

Thousands of Units Sold Nationally

Fast average Slow Historical Trend

Historical
G-42 

4) HHDDT 

To estimate the impact of recession on HHDDTs, staff reviewed BOE diesel fuel sales 

data (BOE, 2010b) and estimated VMT growth using bounding scenarios as shown in 

Figure 14. To forecast HHDDT truck sales, staff used the same method documented 

(ARB, 2008; ARB, 2009). VMT and sales assumptions apply to all HHDDT categories 

unless otherwise noted including interstate trucks.

Figure 14. HHDDT VMT Growth Assumption 

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2006 2008 2010 2012 2014 2016 2018 2020 2022

Ratio to 2006 VMT

No Recession Fast Recovery Slow Recovery Average

Figure 15. HHDDT Sales Forecast 

0

50

100

150

200

250

300

1985 1990 1995 2000 2005 2010 2015 2020 2025

Thousands of Units Sold Nationally

Fast average Slow Historical Trend

Historical
G-43 

G. Proposed Regulatory Scenarios and Compliance Assumptions 

The proposed regulatory amendments provide substantial economic relief through the 

focusing of early PM requirements on vehicles that are most cost-effective to control, 

and on slowing the penetration of NOx targets over time. To reflect these amendments, 

staff has made assumptions about how trucks in each category will respond to 

proposed regulatory requirements. Because of the impact of the recession and the 

increased life of retrofits before turnover is required in the Rule amendments, staff 

assumes that all vehicles subject to early PM requirements (2014 and prior) will install a 

Diesel Particulate Filter (DPF), and that turnover to comply with the regulation will 

generally occur only when explicitly required. 

This section provides the assumptions used to calculate the emissions benefits of the 

proposed amended regulation for each inventory category for which regulatory 

requirements changed between the 2008 regulation and the proposed regulation. If the 

requirements did not change, the assumptions documented in ARB (2008) are still valid. 

The proposed rule provides specific compliance requirements for MHDDT fleets of truck 

GVWR of 26,000 lbs or less, regardless of their fleet size. Medium-heavy duty trucks 

with GVWR above 26,000 lbs are assumed to use the same compliance schedules as 

heavy-heavy duty trucks depending on their fleet size. 

1) MHDDT Rule Compliance (<26,000 lbs GVWR) 

This compliance schedule applies to all MHDDT with a GVWR less than 26,000 lbs. It 

also applies to MHDDT non-specialty agricultural trucks with a GVWR of 26,000 lbs or 

less and above first mileage threshold as described in ARB (2008). 

Table 26. Turnover Assumptions for Medium Heavy Duty Truck Fleets 

GVWR<26,000 lbs 

By Jan. 1 Model Year Turn over to 

2015 pre-1996 2010 

2016 1996 2011 

2017 1997 2012 

2018 1998 2013 

2019 1999 2014 

2020 2000-2002 2015 

2021 2003-2006 2016 

2023 2007-2009 2017 
G-44 

2) Small Fleet Rule Compliance (>26,000 lbs GVWR) 

The proposed amendments to the Regulation continue to provide flexibility for small 

fleets subject to early PM requirements. A small fleet is defined as a fleet that has three 

trucks or fewer. Staff assumes that small fleets will take advantage of these provisions. 

Amendments require the first truck in a small fleet to be DPF equipped by 2014, the 

second truck to be DPF equipped by 2015, and the third truck to by DPF equipped by 

2016. Small fleets must then meet Best Available Control Technology (BACT) 

requirements starting in 2020. 

Table 27 presents the revised assumptions for interstate trucks in small fleets, Table 28 

presents the revised assumptions for single-unit trucks in small fleets, and 

Table 29 presents the revised assumptions for tractors in small fleets. 

Table 27. Retrofit/Turnover Assumptions for >26,000 lbs GVWR Interstate Trucks 

in Small Fleets 

Due Date 

January 1st of 

Calendar Year 

Model Year 

Group 1st truck 2nd truck 3rd truck 

2014 2003-2006 DPF 

2014 1998-2002 DPF -- -- 

2015 2003-2006 DPF DPF 

2015 1998-2002 DPF 1/3 DPF, 1/3 2008, 1/3 2010 -- 

2015 Pre-1994 2010 2010 -- 

2016 2003-2006 DPF DPF DPF 

2016 1998-2002 DPF 1/3 DPF, 1/3 2008, 1/3 2010 2011

2016 Pre-1996 2010 2010 2010 

2017 1996-1997 2010 2010 2010 

2020 1998-2000 2013 2013 -- 

2021 2001-2004 2014 2014 2014 

2022 2005-2006 2015 2015 2015 

2023 all remaining 2015 2015 2015 
G-45 

Table 28. Retrofit/Turnover Assumptions for >26,000 lbs GVWR Single-Unit 

Trucks in Small Fleets 

Due Date 

January 1st of 

Calendar Year 

Model Year 

Group 1st truck 2nd truck 3rd truck 

2014 1998-2006 DPF -- -- 

2015 1998-2006 DPF DPF -- 

2015 Pre-1994 2010 2010 -- 

2016 1998-2006 DPF DPF DPF 

2016 Pre-1996 2010 2010 2010 

2017 1996-1997 2010 2010 2010 

2020 1998-2000 2013 2013 2013 

2021 2001-2004 2014 2014 2014 

2022 2005-2006 2015 2015 2015 

2023 all remaining 2015 2015 2015 

Table 29. Retrofit/Turnover Assumptions for >26,000 lbs GVWR Tractor Trucks in 

Small Fleets 

Due Date 

January 1st of 

Calendar Year 

Model Year 

Group 1st truck 2nd truck 3rd truck 

2014 2003-2006 DPF 

2014 1998-2002 DPF -- -- 

2015 2003-2006 DPF DPF 

2015 1998-2002 DPF 20% DPF, 60% 2008, 20% 2010 -- 

2015 Pre-1994 2010 2010 -- 

2016 2003-2006 DPF DPF DPF 

2016 1998-2002 DPF 20% DPF, 60% 2008, 20% 2010 2011

2016 Pre-1996 2010 2010 2010 

2017 1996-1997 2010 2010 2010 

2020 1998-2000 2013 2013 -- 

2021 2001-2004 2014 2014 2014 

2022 2005-2006 2015 2015 2015 

2023 all remaining 2015 2015 2015 
G-46 

3) Large Fleet Rule Compliance (>26,000 lbs GVWR) 

The proposed regulatory amendments provide relief to large fleet HHDDTs, because 

pre-1998 trucks would no longer be subject to early PM requirements. To reflect this 

change, staff updated compliance assumptions for large fleets. These assumptions are 

specific to each vehicle category because of differences in average miles traveled and 

vehicle dollar values between different categories. Table 30 presents compliance 

assumptions for >26,000 lbs GVWR tractors in large fleets; Table 31 presents 

compliance assumptions for >26,000 lbs GVWR single-unit trucks in large fleets. The 

proposed regulatory amendments contain a large fleet provision that allows fleets to 

install DPFs on 90% instead of 100% of their fleet. To reflect this provision, emissions 

benefits calculated using Tables 30 and 31 are multiplied by 0.9 to estimate the final 

benefit from large fleets. This assumption is also discussed in G8 below. 

Table 30. Retrofit/Turnover Assumptions for >26,000 lbs GVWR Tractor Trucks in 

Large Fleets 

Due Date January 

1st of Calendar Year 

Model Year 

Group Assumed Compliance 

2012 1998-2000 DPF 

2013 2001-2002 DPF 

2013 2003-2004 DPF 

2014 2005-2006 DPF 

2015 Pre-1994 2010 

2016 1994-1995 2011 

2017 1996-1997 2012 

2020 1998-2000 2015 

2021 2001-2002 2016 

2021 2003-2004 2016 

2022 2005-2006 2017 

2023 all remaining 2017 

Table 31. Retrofit/Turnover Assumptions for >26,000 lbs GVWR Single-Unit 

Trucks in Large Fleets 

Due Date January 

1st of Calendar Year 

Model Year 

Group Assumed Compliance 

2012 1998-2000 DPF 

2013 2001-2004 DPF 

2014 2005-2006 DPF 

2015 Pre-1994 2010 

2016 1994-1995 2010 

2017 1996-1997 2010 

2020 1998-2000 2013 

2021 2001-2004 2014 

2022 2005-2006 2015 

2023 all remaining 2015 
G-47 

4) Agricultural Truck Compliance Assumptions 

The proposed regulatory amendments do not alter the fundamental compliance 

structure for agricultural trucks. However, because of changes to BACT requirements, 

compliance assumptions for specialty vehicles and some model year groups have been 

altered slightly, as shown in Table 32. 

Table 32. Retrofit/Turnover Assumptions for Agriculture Trucks 

 Below 10,000 miles/yr and specialty agricultural trucks

Due Date January 

1st of Calendar Year Model Year Turnover to 

2023 pre-2010 2012 

 Above 10,000 miles/yr but below first mileage threshold 

Due Date January 

1st of Calendar Year Model Year Retrofit /Turnover to

2017 pre-1998 2010 

2017 1998-2006 50% 2010 and 50% 2008 

2023 2007-2009 2012 

5) Utility Truck Compliance Assumptions 

As a result of proposed regulatory amendments, the following assumptions in Table 33 

are made for compliance for trucks owned by Utilities. 

Table 33. Retrofit/Turnover Assumptions for Utility Trucks 

 T6 Utility T7 Utility 

Due Date January 

1st of Calendar Year Model Year 

Retrofit 

/Turnover to Model Year 

Retrofit 

/Turnover to 

2014 Pre-1998 2010 Pre-1998 2010 

2014 1998-2006 DPF 1998-2006 DPF 

2021 1998-2006 2013 1998-2004 2013 

2022 2005-2006 2014 

2023 2007-2009 2015 2007-2009 2015 
G-48 

6) Drayage Truck Compliance Assumptions 

Proposed regulatory amendments would harmonize drayage truck and truck and bus 

regulatory requirements by removing the Phase II drayage truck requirement to turnover 

to a 2007 truck by 2014, while keeping Phase I retrofit requirements. Due to 

requirements imposed by the Ports of Los Angeles and Long Beach, all drayage trucks 

will meet 2007 standards in 2014; as a result regulatory amendments will have little 

effect in southern California. Drayage trucks in the Bay Area are not subject to this local 

requirement, and so benefits of the Drayage Truck Rule will be reduced by these 

amendments in that area. By 2017, drayage trucks will be required to follow truck and 

bus requirements, as shown in Table 34. 

Table 34. Retrofit/Turnover Assumptions for Drayage Trucks 

Assumptions for Southern California Drayage Trucks

Calendar year 

Population distribution 2010 2011 2012 2013 2014 2014-2016

MY 1994-2003, DPF 4% 4% 4% 4% 4%

MY 2004 10% 10% 0% 0% 0%

MY 2004 DPF 0% 0% 6% 6% 6%

MY 2005-2006 21% 21% 11% 0% 0%

MY 2005-2006, DPF 0% 0% 0% 9% 9%

MY 2007-2009 58% 58% 70% 72% 72%

MY 2010 and newer 7% 7% 9% 9% 9%

Trucks new 

to the 

drayage 

service 

would meet 

2007 

engine 

standard 

Approach for Drayage Trucks Outside of Southern California 

Due Date January 

1st of Calendar Year Model Year Retrofit / Turnover to 

2010 Pre -1994 1994 

2010 1994 - 2003 DPF 

2012 2004 DPF 

2013 2005-2006 DPF 

Truck and Bus Regulation Assumptions starting in 2017 

Due Date January 

1st of Calendar Year Model Year Turnover to 

2020 pre-1998 2010 

2020 1998-2000 2012 

2021 2001-2004 2012 

2022 2005-2006 2012 

2023 2007-2009 2012 
G-49 

7) School Bus Compliance Assumptions 

Under the proposed regulation, school bus compliance requirements would be deferred 

for two years, as shown in Table 35. 

Table 35. Retrofit/Turnover Assumptions for School Buses 

Due Date January 

1st of Calendar Year

Model 

Year Turnover to Percent with DPF 

2012 1987-2006 33% 

2013 1987-2006 66% 

2014 1987-2006 100% 

2014 pre-1987 2007 

8) Regulatory Credit and Other Provisions - Not Modeled in the Inventory 

The proposed regulatory amendments contain several provisions that are not modeled 

within the inventory, including reduced activity credits, early retrofit credits, alternative 

fuel credits, and large fleet phase-in. These provisions cannot be explicitly modeled 

because they are not mandatory, and the choice to exercise these provisions depends 

on many factors that are difficult to predict. Their impact on the margin is estimated, but 

other inventory charts shown in Section H do not include the impact of these provisions. 

The reduced activity credits and alternative large fleet phase-in relief provisions in the 

regulation will likely reduce the number of filter equipped trucks, especially in the 2014 

timeframe, from what is modeled directly in the inventory. Whether a fleet will choose to 

exercise reduced activity credits depends on how it has been impacted, and how it has 

responded to the recession. Some fleets will choose to take advantage of alternative 

fuel vehicle credits or early retrofits and others will not. 

The reduced activity credits are designed to be self-correcting in that if the economy 

recovers more slowly more credits would be generated, and if the economy recovers 

more quickly fewer credits would be generated. For example, if the economy recovers 

more slowly than anticipated, more fleets would use reduced activity credits. This would 

reduce the benefits the Rule would achieve, but those disbenefits would be offset by 

reduced activity and emissions caused by the recession. 
G-50 

H. Emissions Results 

1) Evaluation of Baseline Statewide Fuel Usage Estimates 

The Truck and Bus Rule is not expected to have a significant impact on reducing 

statewide emissions of CO2. However, comparing modeled fuel-use in the emissions 

analysis to the total amount of diesel fuel taxed in California annually is a valuable tool 

to ensure the emissions analysis is reasonably accurate. To develop this analysis, staff 

added annual CO2 emissions estimates for diesel trucks and buses in this inventory to 

estimates of CO2 emissions representing light-duty and light heavy-duty diesel vehicles. 

The combined total represents all on-road use of taxable diesel in California. Staff 

assumed 10,159 grams of CO2 emissions per gallon diesel fuel to convert CO2

emissions to gallons of diesel fuel. Figure 16 compares estimated fuel usage in the 

inventory analysis (including lighter duty vehicles from EMFAC2007) with on-road 

taxable diesel fuel provided by the BOE in their 10 year report (BOE, 2010b). Results 

show very good agreement, within 5 percent or less, between the inventory analysis 

and reported fuel data. 

Figure 16. ARB Modeled Estimates of On-Road Diesel Fuel Use Based on the 

Emissions Analysis vs. BOE On-Road Taxable Fuel by Calendar Year 

0

0.5

1

1.5

2

2.5

3

3.5

2005 2006 2007 2008 2009

Billion Gallons Diesel Fuel per Year

BOE On-Road Taxable Fuel ARB Estimates - All On-Road Diesel
G-51 

2) Estimating Statewide Emissions Benefits of the Proposed Regulation 

When the Board adopted the regulation in 2008, the Rule was designed to achieve 

maximum reduction of diesel particulate matter emissions by 2014, and to ensure 

maximum NOx emissions reductions by 2023. The rule was also designed to achieve 

sufficient NOx reductions to achieve reductions in nitrate particulate to meet the 

particulate matter ambient air quality standard in both the South Coast Air Basin and the 

San Joaquin Valley. 

The proposed amendments to the regulation are designed to ensure these overall 

benefits are achieved at a much lower cost. This is possible because the recession is 

projected to continue to reduce anticipated emissions levels well into the future. 

Overall, staff anticipates the amended regulation will reduce diesel PM emissions by 50 

percent from currently anticipated levels in 2014, and that the regulation will ensure that 

by 2020 practically all trucks operating in California will be equipped with a diesel 

particulate filter. Figure 17 and Figure 18 compare anticipated baseline emissions 

(without the Rule) to emissions with the amended Rule if it is adopted. Staff anticipates 

the amended Rule will achieve a 15 percent reduction in NOx emissions and a 50 

percent reduction in PM2.5 emissions from anticipated levels without the Rule in place 

between 2015 and 2023. 

The emissions benefits shown in this section cover only BACT requirements and other 

major portions of the regulation that are modeled in the inventory. Credit provisions 

discussed in Section G8 of this document are covered quantitatively below in 

Section H4. 
G-52 

Figure 17. Statewide NOX Emissions Estimates Baseline and with Regulation 

0

100

200

300

400

500

600

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023

NOx (tons per day)

Baseline

With Regulation

Figure 18. Statewide PM2.5 Emissions Estimates Baseline and with Regulation 

0

5

10

15

20

25

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023

PM2.5 (tons per day)

Baseline

With Regulation
G-53 

Figure 19 and Figure 20 compare anticipated emissions without the Rule to emissions 

with the amended Rule in the South Coast. 

Figure 19. South Coast NOX Emissions Estimates Baseline and with Regulation 

0

20

40

60

80

100

120

140

160

180

200

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023

NOx (tons per day)

Baseline

With Regulation

Figure 20. South Coast PM2.5 Emissions Estimates Baseline and with Regulation 

0

1

2

3

4

5

6

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023

PM2.5 (tons per day)

Baseline

With Regulation
G-54 

Figure 21 and Figure 22 compare anticipated emissions without the Rule to emissions 

with the amended Rule in the San Joaquin Valley. 

Figure 21. San Joaquin Valley NOX Emission Estimates Baseline and with 

Regulation 

0

20

40

60

80

100

120

140

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023

NOx (tons per day)

Baseline

With Regulation

Figure 22. San Joaquin Valley PM2.5 Emissions Estimates Baseline and with 

Regulation 

0

1

2

3

4

5

6

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023

PM2.5 (tons per day)

Baseline

With Regulation
G-55 

3) PM and NOx Emissions Benefits from both the Truck and Bus and In-Use Off-Road 

Rules are Preserved 

Staff designed proposed regulatory amendments across both the Statewide Truck and 

Bus and In-Use Off-Road Rules to provide the maximum amount of economic relief 

possible while still preserving as much of the originally envisioned benefits as possible. 

Our estimates suggest that statewide the combined impact of the recession with 

amended regulations on both on-road and off-road inventories will provide essentially 

the same cumulative remaining emissions levels between 2011 and 2023 to what the 

adopted Rules would have achieved without the recession. This concept is shown in 

Figure 23 for PM2.5 and Figure 24 for NOx below. 

Figure 23. Year by Year Comparison of PM2.5 Emissions after On-Road and OffRoad Regulations are Applied: Adopted Rules without Recession vs. 

Amended Rules with Recession 

0

5

10

15

20

25

30

2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023

Statewide PM2.5 Emissions (tons/day)

Adopted Without Recession With Proposed Amendments

 
G-56 

Figure 24. Year by Year Comparison of NOX Emissions after On-Road and OffRoad Regulations are Applied: Adopted Rules without Recession vs. 

Amended Rules with Recession 

0

100

200

300

400

500

600

700

800

2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023

Statewide NOx Emissions (tons/day)

Adopted Without Recession With Proposed Amendments

4) Meeting SIP Targets 

In September 2007, ARB adopted a State Implementation Plan (SIP) committing the 

State to develop measures to achieve emission reductions from sources under State 

regulatory authority. The reductions are needed to attain the Clean Air Act National 

Ambient Air Quality Standards (NAAQS) for PM2.5 in 2014 and for ozone longer term. 

While multiple areas throughout the State exceed federal air quality standards, the air 

quality in the South Coast and the San Joaquin Valley poses the greatest challenge and 

defines the amount of reductions needed. Reductions are needed by 2014 to meet the 

PM2.5 attainment deadline and by 2023 to meet the ozone attainment deadline for 

compliance with the NAAQS. 

 

Staff decided to consider the impact of the recession and inventory changes on fleets 

affected by the truck and off-road regulations together in deciding how to provide 

regulatory relief so that emissions reductions could be targeted more cost effectively, 

and staff could ensure the combined emissions benefits achieved by the two rules 

would meet SIP legal requirements for the combined SIP categories. 
G-57 

To develop this comparison, remaining emissions anticipated after the application of the 

heavy-duty truck and in-use off-road regulatory concepts in the 2007 SIP were 

compared to anticipated remaining emissions from heavy-duty trucks and in-use offroad equipment in the updated rule inventories. The difference between the remaining 

emissions in the SIP and in the revised inventory is referred to as the margin. The 

margin defines how much relief can be provided under the truck and off-road rules while 

still meeting SIP legal requirements. The margin is compared in NOx equivalent 

emissions which is a weighted combination of NOx and PM2.5. The PM2.5 to NOx ratio is 

10:1 in South Coast and 9:1 in the San Joaquin Valley; these numbers were based on 

photochemical modeling in the 2007 SIP (ARB, 2007b). 

Reduced activity credit provisions of the proposed regulatory amendments could not be 

accurately modeled within the inventory, but are expected to have a significant impact in 

reducing emissions benefits from strictly what BACT compliance would provide in 2014. 

This is because under the proposed credit provisions fleets that have downsized as a 

result of the recession can treat a retired vehicle as compliant, which reduced early PM 

compliance requirements for other vehicles in the fleet. This effect will be most 

significant in 2014 when SIP compliance is measured. The large-fleet phase-in 

requirements could lead to many large fleets meeting early PM requirements for 90 

percent instead of 100 percent for vehicles subject to regulatory requirements. 

Table 36 compares the 2014 margin in the San Joaquin Valley air basin for several 

inventory scenarios. The rules as currently adopted would provide a margin of 40 tons 

NOx equivalent emissions. After modeling the major portions of the proposed Rule 

amendments without credit provisions, the remaining margin is estimated at 2.4 tons. 

Table 36. Comparison of 2014 Remaining Emissions in the San Joaquin Valley 

Air Basin After Truck and Off-Road Rules Are Applied: SIP, Adopted 

Rule, With Rule Inventory (Not Including Credit Provisions) 

San Joaquin Valley 2014 NOX Eq. Emissions (tons/day) 

SIP Adopted* Proposed 

Off-Road NOX 29.1 12.1 13.4 

 PM2.5 0.7 0.4 0.6 

Trucks NOX 88.6 75.2 101.8 

 PM2.5 1.9 1.1 2.0 

NOX Eq (pm*9) 141.1 101 138.7 

Margin without Credit 

Provisions 

 40 2.4 

Margin with Credit 

Provisions 

 n/a 0 

 * From August 2010 Workshop 

Staff estimates that a maximum of 15 percent of the total NOx equivalent benefits could 

be lost as a result of the reduced activity credit and large-fleet phase-in requirements of 

the proposed amended regulation. Staff believes that if the reduced activity credit and 

large-fleet phase-in requirements of the proposed regulation are considered, the 

remaining margin would be eliminated. This would represent a reduction in overall 

benefits of about 14 percent. 
G-58 

Table 37 compares the 2014 margin in the South Coast air basin for several inventory 

scenarios. The rules as currently adopted would provide a margin of 62 tons NOx

equivalent emissions. After modeling the major portions of the proposed Rule 

amendments, the remaining margin is estimated to be 7.4 tons. Staff estimates a 

maximum of 15 percent of the total NOx equivalent benefits could be lost as a result of 

the reduced activity credit and large-fleet phase-in requirements of the proposed 

amended regulation. The total NOx equivalent benefit in the South Coast in 2014 is 18 

tons/day. A 15% benefit loss would be equal to 2.7 tons; a 2.7 ton reduction from the 

7.4 margin would leave a margin of 4.6 tons NOx equivalent emissions after all 

provisions of the Rule are considered. 

Table 37. Comparison of 2014 Remaining Emissions in the South Coast Basin 

After Truck and Off-Road Rules Are Applied: SIP, Adopted Rule, 

Provisions Modeled in the Inventory, and All Regulatory Provisions 

 SIP Adopted* Proposed 

Off-Road NOX 85.6 24.9 27.6 

 PM2.5 2.3 0.9 1.3 

Trucks NOX 55.1 81.5 117.6 

 PM2.5 2.3 0.9 2.1 

NOX Eq (pm*10) 186.7 124.4 179.3 

Margin without Credit 

Provisions 

 62 7.4 

Margin with Credit 

Provisions 

 n/a 4.6 

* From August 2010 Workshop 

With the proposed amendments the truck rules will continue to provide major diesel PM 

emissions reductions to protect public health and to ensure all trucks operating in 2023 

are equipped with the cleanest engines available. The combined margin for 

trucks/buses and off-road equipment is minimized, providing maximum relief while still 

meeting SIP legal obligations. 

I. Additional Documentation 

As part of the Rulemaking package staff is providing the emissions inventory model and 

associated documentation. The following is a guide to the model files and 

documentation. 

There are three folders in the inventory documentation package: 

• EI models recession proposed – this folder contains the actual calculations of the 

emissions inventory for the proposed regulation and with the average of faster 

and slower growth scenarios 

o Baseline by fleet 10210.mdb – is the starting point of the inventory 

calculation. Population and VMT by fleet category, model year and air 

basin are calculated and forecasted. The impacts of Drayage Truck 
G-59 

regulation and Public and Utility Fleets regulation on drayage trucks and 

utility fleets are also estimated. 

o Base by sub cat 100810.mdb – is where the fleet categories in “Baseline 

by fleet 100810.mdb” were further divided into sub categories based on 

fleet size, annual mileage, etc. 

o Modeling assumptions.xls – documents the assumptions for fleet turnover 

and retrofit under the regulation. 

o XXXAB 102010.mdb – based on the population and VMT in “Base by sub 

cat 100810.mdb” and the assumptions in “modeling assumptions.xls”, 

estimates the population and VMT results of fleet turnover and retrofit for 

each air basin. 

o Combined scenario 102010.mdb – combines the air basin results into one 

table and calculates the emissions under the proposed rule 

• EI models no recession adopted rule – this folder contains the emissions 

inventory calculations for the adopted regulation without the recession. 

o Baseline by fleet no recession.mdb – is the starting point of the inventory 

calculation. Population and VMT by fleet category, model year and air 

basin are calculated and forecasted. The impacts of Drayage Truck 

regulation and Public and Utility Fleets regulation on drayage trucks and 

utility fleets are also estimated. 

o Base by sub cat no recession.mdb – is where the fleet categories in 

“Baseline by fleet no recession.mdb” were further divided into sub 

categories based on fleet size, annual mileage, etc. 

o XXXAB no recession adopted.mdb – based on the population and VMT in 

“Base by sub cat no recession.mdb” and the assumptions for the adopted 

rule, estimates the population and VMT results of fleet turnover and retrofit 

for each air basin. 

o Combined no recession adopted.mdb– combines the air basin results into 

one table and calculates emissions estimates with adopted rule and 

without recession. 

• EI models with recession adopted rule – this folder contains the emissions 

inventory calculations for the adopted regulation with recession. 

o Baseline by fleet with recession.mdb – is the starting point of the inventory 

calculation. Population and VMT by fleet category, model year and air 

basin are calculated and forecasted. The impacts of Drayage Truck 

regulation and Public and Utility Fleets regulation on drayage trucks and 

utility fleets are also estimated. 

o Base by sub cat with recession.mdb – is where the fleet categories in 

“Baseline by fleet with recession.mdb” were further divided into sub 

categories based on fleet size, annual mileage, etc. 

o XXXAB with recession adopted.mdb – based on the population and VMT 

in “Base by sub cat with recession.mdb” and the assumptions for the 

adopted rule, estimates the population and VMT results of fleet turnover 

and retrofit for each air basin. 
G-60 

o Combined with recession adopted.mdb– combines the air basin results 

into one table and calculates emissions estimates with adopted rule and 

without recession. 

• Supporting files – this folder contains supporting data/analysis for the inventory 

o Buses – Buses and motorcoach related files 

 Buses population accrual.xls – analysis of DMV data and data 

provided by CBA to estimate the population and accrual rates for all 

other buses and motorcoaches. 

 California Public Utilities Commissions.xls - provides the 

motorcoach population. 

 CBA survey.xls – provide mileage accrual by model year for 

motorcoaches. 

 EF for bus_PTO.xls – emission factors for buses and PTO. 

o Construction – construction fleets related files 

 BOE Construction Taxable Fuel Refunds.xls 

 Construction allocation pop growth by AB.xls – spatial allocation for 

construction fleet VMT based on DOF population forecast. 

 Construction Avg age&accrual in VIUS.xls – analysis of age and 

accrual rate of construction vehicles in VIUS 2002. 

 EDA UCC data analysis.xls – new construction equipment sales 

financed. 

 Percentage of Construction Trucks.xls – VIUS based analysis on 

construction population as percentages of HHDDT and MHDDT 

populations. 

o Emission Factor – emission factor related files 

 NOx adjustment details.xls – calculation to reflect engine 

manufacturer’s compliance approaches for NOx standard. 

 HHDDT EF NOx adj cap 400_800K.xls – emission factors that 

reflect both the NOx adjustment and odometer capping for HHDDT. 

 MHDDT EF NOx adj cap 400_800K.xls – emission factors that 

reflect both the NOx adjustment and odometer capping for MHDDT. 

 EF cap 400_800K w NOx rev.xls – combines HH and MHDDT EF 

files for input to the Access models. 

o Field Study – field study related files 

 Cambridge 2008 trip length.pdf – for estimating the trip length in 

San Joaquin Valley Air Basin 

 SCAG 1999 trip length.pdf – for estimating the trip length in SCAG 

 Field study folder – documents released in 2010 regarding field 

study as part of California Public Records Act. Folder contains 

“Readme.xls” describing the content. 

o Growth & Sales – growth and sales forecasts 

 EIA sales VMT forecast.xls – the 2009 EIA forecast of VMT and 

new truck sales used for sales forecast 

 Growth w recession.xls – VMT growth trends that reflect recession 

recovery assumptions 
G-61 

 Sales w recession.xls – Sales forecast reflecting the VMT growth 

trend with recession 

o Misc 

 2005 T6 GVW split.xls – analysis based on 2005 DMV to estimate 

the percent of MHDDTs that are above 26,000 lbs GVWR 

 Fuel comparion.xls – based on estimated CO2 emissions, compare 

the estimated on-road fuel consumptions to the reported diesel 

taxable fuel from BOE 

 IFTA 2005~2009.xls - IFTA fuel/VMT from corresponding with BOE 

 Truck NOx_PM contribution to 2010_2020 STWD.xls – contains the 

analysis of the truck contribution to 2010 statewide mobile source 

emissions. 

o Jan2010 folder – contains files released in 2010 as part of California 

Public Records Act. README.doc describes the content in the folder. 
G-62 

J. References 

ARB, 2006a. California Air Resources Board. EMFAC Modeling Change Technical 

Memo: Redistribution of Heavy-Heavy Duty Diesel Truck Vehicle Miles Traveled in 

California. September 2006. Available at: 

http://www.arb.ca.gov/msei/onroad/techmemo/on-2006-05.pdf

ARB, 2006b. California Air Resources Board. Final Statement of Reasons – Proposed 

Diesel Particulate Matter Control Measure for On-Road Heavy-Duty Diesel Fueled 

Vehicles Owned or Operated by Public Agencies and Utilities. October 2006. Available 

at: http://www.arb.ca.gov/regact/dpmcm05/revfsor.pdf

ARB, 2007a. California Air Resources Board, Drayage Truck Regulation Available at: 

http://arb.ca.gov/regact/2007/drayage07/drayage07.htm and 

http://www.arb.ca.gov/msprog/onroad/porttruck/drayagetruckbenefit100507.xls 

ARB, 2007b. California Air Resources Board, Proposed State Strategy for California's 

State Implementation Plan (SIP) for the New Federal PM2.5 and 8-Hour Ozone 

Standards. Available at: http://www.arb.ca.gov/planning/sip/2007sip/2007sip.htm

ARB, 2008. California Air Resources Board. Staff Report: Initial Statement of Reasons 

(ISOR), Technical Support Document. October 2008. Available at: 

http://www.arb.ca.gov/regact/2008/truckbus08/truckbus08.htm

ARB, 2009. California Air Resources Board, ARB Staff Assessment of the Impact of the 

Economy on California Trucking Activity and Emissions 2006-2014. Available at: 

http://www.arb.ca.gov/msprog/onrdiesel/documents/truck_economic_documentation_v0

15.pdf 

BEA, 2009. Industry and State Level GDP, 1997-2008. Last updated: Tuesday, June 

02, 2009. Available at: http://bea.gov/regional/gsp/ 

BLS, 2010. U.S. 1939-current, CA 1990-current. Statewide and National Employment 

(Variety Sectors). Last assessed June 2010. Available at: 

http://www.bls.gov/data/#employment 

BOE, 2008. BOE Construction Taxable Fuel Refunds.xls. Available at Air Resources 

Board, Diesel Activities - AB1085 Compliance. Available at: 

http://www.arb.ca.gov/dieseltruck

BOE, 2010a. IFTA 2005~2009.xls. Available at Air Resources Board, Diesel Activities - 

AB1085 Compliance. Available at: http://www.arb.ca.gov/dieseltruck

BOE, 2010b. Taxable Diesel Gallons 10 Year Report. Available at: 

http://www.boe.ca.gov/sptaxprog/reports/Diesel_10_Year_Report.pdf. Last assessed 

June 2010. 
G-63 

BTS, 1998. Research and Innovative Technology Administration, NORTAD Roadway 

Network. Available at: 

http://www.bts.gov/publications/north_american_transportation_atlas_data/

Caltrans, 2009. Truck Traffic (Annual Average Daily Truck Traffic) on California State 

Highways. 2007Truck.xls. Available at: http://traffic-counts.dot.ca.gov/2007truck.xls. 

Last accessed February 2009. 

Cambridge Systematics, Inc., 2008. Cambridge 2008 trip length.pdf. Available at Air 

Resources Board, Diesel Activities - AB1085 Compliance. 

http://www.arb.ca.gov/dieseltruck

CBA, 2010. CBA survey.xls. Available at Air Resources Board, Diesel Activities - 

AB1085 Compliance. http://www.arb.ca.gov/dieseltruck

CPUC, 2009. California Public Utilities Commission.xls. Available at Air Resources 

Board, Diesel Activities - AB1085 Compliance. http://www.arb.ca.gov/dieseltruck

DMV, 2005. California Vehicles Registration Data. Confidential. 

DOF, 2009. California County Population Estimates and Components of Change 2000 

2008, December 2008 and Population Projections by Race/Ethnicity for California and 

Its Counties 2000–2050, July 2007. Last accessed February 2009. Available 

at:http://www.dof.ca.gov/research/demographic/reports/estimates/e-6/2000-08/ and 

http://www.dof.ca.gov/HTML/DEMOGRAP/ReportsPapers/Projections/P1/P1.asp

DOF, 2010. Residential Unit and Valuation, 1975-2009 (annual), 1995-current 

(monthly). Last assessed February 2010. Available at: 

http://www.dof.ca.gov/html/fs_data/latestecondata/fs_construction.htm 

EDA, 2010. California Equipment Financed, 2005-current. Available at: 

www.EDAData.com 

FHWA, 2008. Federal Highway Administration (FHWA), Freight Management and 

Operations, FAF2, 2002-2035. Available at: 

http://ops.fhwa.dot.gov/freight/freight_analysis/faf/faf2_high.htm (last accessed Dec 2, 

2008). 

Lutsey, Nicholas, 2008. Assessment of Out-of-State Heavy-Duty Truck Activity Trends 

in California – Final Report. Institute of Transportation Studies, University of California 

at Davis, March 14, 2008. Available at: http://www.arb.ca.gov/research/apr/past/04-

328.pdf

SCAG, 1999. SCAG 1999 trip length.pdf. Heavy Duty Truck Model and VMT 

Estimation, Figures 3B &3C. Available at Air Resources Board, Diesel Activities - 

AB1085 Compliance. http://www.arb.ca.gov/dieseltruck
G-64 

USGS, 2009. Geographic Names Information System. Available at: 

http://geonames.usgs.gov/index.html (last accessed March 30, 2009). 

VIUS, 2002. US Census Bureau, Service Sector Statistics Division, Transportation 

Characteristics Branch. Vehicle Inventory and Use Survey – Discontinued Products. 

Available at: http://www.census.gov/svsd/www/vius/products.html
G-65 

K. Attachment – CARB Origin-Destination Survey Questionnaire 

CARB HDT Origin-Destination Survey Questionnaire 

Survey Location: _____________________ Direction_______ Date: _________ Time:________ 

Surveyor ___________________ 

Selection Reason: X_ Random ___ Excess Smoke ( ____ %) ___ Other: ___________ 

Truck Information

 1. Vehicle Type (circle one): Single Unit w/ trailer Tractor-Trailer (Trailer is 53’ or longer? Y / N) 

 Multiple-Trailer Tractor Dump truck Concrete mixer 

 If a tractor-trailer, does the owner of the tractor also own the trailer? Yes___ No__ Don't Know_ 

 2. Number of axles: Tractor _____, Trailer ______, Total: _____ 

 3. Where is the home base of this vehicle? City ____________________ State ________ 

 6. License Plates: US State _________ Number _______________ 

 Mexico _____________ Canada ______________ 

 7. Make and Model Year of truck: __________ __________ 

 8. Make and Model Year of engine: __________ __________ 

 10. Has the engine been rebuilt or replaced?(circle one) Yes No Unknown 

 13. Odometer: _________________________ 

 14. What is the current loaded weight of this truck? _______________ lb 

 15. What is the Gross Vehicle Weight Rating (GVWR or GCWR) of this truck? _______________ lb 

Fueling Information

 16. Total Fuel capacity of this truck: __________ gallons 

 17. Where did you last fuel up this truck? City ____________________ State ________ 

 18. Where will you next fuel up this truck? City ____________________ State ________ 

 19. Where do you usually buy fuel? CA Mexico Canada Other US State (specify): __________ 

Activity Information

20a. Where did your current trip begin? City______________________ State_______ Country_______ 

 Address_________________________________________________________ 

 21. What is the destination of your current trip? 

 City_________________________________________________State________ Country______ 

 Address_________________________________________________________ 

 21a. How many tractors/trailers are there in your company? (OK if estimate) Tractors_____/Trailers_____ 

Maintenance Information

 34. In the past 12 months, has your truck had any downtime for repairs due to problems with the truck 

engine? Yes__ No__ Unknown__ 

 35. During the past 12 months, which of the following malfunctions have you had on your truck? 

 (Check all that apply): 

 Fuel Injection Problems: Mild _____ Medium _____ Severe _____ 

 Engine Failure _____ 

 Electronic Failure _____ 

 Turbocharger Problems _____ 

 Intercooler Problems _____ 

 EGR Problems _____ 

 Air/Fuel Ratio Control _____ 

 Clogged Air Filter _____ 

 Other Air Induction Problems _____ 

 Excessive Engine Oil Consumption _____ 

 PM Filter (DPF) Problems (if equipped) _____ 

 Other ________________________________________________________ 

PrePass Program (skip this if survey conducted at weigh stations) 

 36. Is this truck currently enrolled in the Caltrans PrePassTM program? Yes___ No___ Unknown__ 

Comments: ______________________________________________________________________________ 

Contact: Zhen Dai, CARB PTSD Mobile Source Analysis Branch (916) 322-7455 or zdai@arb.ca.gov