1 

ARB Staff Assessment of the Impact of the Economy 

 on California Trucking Activity and Emissions 2006-2014 

California Air Resources Board 

December 2009

Summary 

At its December 2008 meeting, the California Air Resources Board (ARB or 

Board) adopted the Statewide Truck and Bus Rule (Rule). At that Hearing, the 

Board directed ARB staff to report back in December 2009 on the impact of the 

current recession on heavy duty diesel truck activity and emissions in California. 

This document describes the data sources and approach taken to evaluate near 

term statewide impacts of the recession on trucking activity and emissions as 

well as the results of a sensitivity analysis assessing the implications of two 

different growth scenarios for statewide truck and bus emissions through 2014. 

With the exception of drayage trucks, there was insufficient information available 

to accurately characterize how the recession is impacting truck emissions either 

regionally or by type of trucking vocation. 

In conducting this assessment, staff analyzed a wide variety of data sources 

including diesel fuel sales, roadway sensor information, shipping container 

throughput, trucking industry tonnage reports, truck sales trends, and truck 

registration data. Based on the data reviewed diesel fuel use, truck traffic, and a 

number of other statewide surrogates of truck activity in California decreased by 

approximately 20 percent between 2007 and 2009. The lower emissions 

associated with this reduced activity has been partially offset by the overall age 

of the California-registered truck fleet increasing by approximately one year 

between 2006 and 2009 due to a 60 percent reduction in new truck registrations 

in California over that time period. Combined, the reduced truck activity and 

older average fleet age results in calendar year 2009 emissions being 20 percent 

lower than was estimated in the Rule staff report. 

Looking forward, there is no single metric or forecast that is a direct indicator for 

projecting future emissions from trucks and buses in California. As a result, staff 

reviewed a large number of economic and fuel consumption forecasts for 

California and the nation. These included forecasts from national agencies such 

as the Congressional Budget Office and the Energy Information Administration; 

California state agencies including the Department of Finance, Legislative 

Analyst’s Office, and California Energy Commission; leading California 

universities including the UCLA Anderson School and the University of the 

Pacific; and independent consultants such as Beacon Economics. 

These forecasts provided a range of different rates of economic recovery. To 

encompass the variability in these forecasts staff conducted a sensitivity analysis 

of potential future emissions trends. The upper and lower bounds of this 
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sensitivity analysis were defined by two growth rates and informed by the 

economic, fuel, and other forecasts reviewed. Staff defined a faster growth 

scenario where California truck activity and sales begin to grow in 2010 and 

return to the long term trend in eight years, and a slower growth scenario in 

which California truck activity and sales are flat from 2009 to 2011 and then grow 

at historically average rates through 2014. The eight year recovery period 

assumed in the faster growth scenario is consistent with the length of time 

required for the U.S. economy to recover from the Great Depression. It is also 

supported by the Congressional Budget Office forecast coupled with an 

assumption that California’s economic recovery will lag the nation by two years. 

The rate of growth assumed in the slower growth scenario is generally consistent 

with most of the California-specific employment forecasts reviewed. 

Results show that in the near term (2010 and 2011), in both scenarios evaluated, 

lower truck activity will reduce diesel particulate matter (PM2.5) and oxide of 

nitrogen (NOx) emissions to a greater degree than was expected in the 2008 

Rule staff report. However, beginning in 2012 and continuing through 2014, the 

Rule is required to achieve needed emissions reductions for both growth 

scenarios considered. Under a faster growth scenario, the Rule in its entirety Is 

needed to meet State Implementation Plan (SIP) obligations for NOx and PM2.5. 

Under a slower growth scenario, the Rule provides slightly more emissions 

reductions than were expected in the Rule staff report. This analysis shows that 

assumptions about the rate of economic recovery and related growth in truck 

activity and sales determines whether the Rule provides any NOx emissions 

reductions above and beyond what was expected in the Rule staff report. 

Introduction 

In December 2008 the California Air Resources Board (ARB) adopted the 

Statewide Truck and Bus Rule (Rule). At that hearing, the Board directed ARB 

staff to report back to the Board in December 2009 on the impact of the current 

recession on heavy duty diesel vehicle activity and emissions in California. This 

document describes the data sources and approach taken to evaluate near term 

impacts of the recession as well as the results of a sensitivity analysis assessing 

the implications of different economic scenarios for California truck emissions 

through 2014. 

In developing the Rule in 2008, ARB staff updated assumptions about the 

population of trucks operating in California, the annual miles traveled by different 

trucking vocations, their average age, and sales. A complete description of these 

sources and how they were used to estimate emissions for the Rule is provided 

in Appendix G of the Rule staff report. This assessment uses the same 

emissions estimation methods as were used for the staff report but incorporates 

more current truck activity, population, and age data from a variety of sources. 
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Assessing Current Truck Activity 

Staff evaluated a variety of different data sources to assess the current impact of 

the recession on trucking activity. 

 

 On-Road Diesel Fuel Sales – the California State Board of Equalization 

(BOE) collects and makes publically available California-specific on-road 

diesel fuel sales estimates on a monthly basis. There is a 4 month lag in the 

release of the BOE fuel sales data such that the most recent fuel sales data 

used in this analysis was August 2009; data were evaluated back to 2000. 

Fuel sales vary seasonally; the magnitude of the calculated reduction in fuel 

sales can vary depending upon the time period selected for analysis. 

 Highway Performance Monitoring System (PeMS) – Thousands of roadway 

sensors are embedded on freeways and state highways throughout 

California. This system was developed by the California Department of 

Transportation (Caltrans) to assist traffic management efforts and summary 

reports are published through Caltrans and UC Berkeley. Truck volume data 

are estimated on an hourly basis at each site, allowing trends in truck activity 

to be developed, but this is complicated by the fact that sensors are added, 

removed, and repaired every year. 

PeMS data are most useful when high quality data are available for several 

consecutive years at the same site or set of sites. Staff reviewed data for eight 

PeMS stations as shown in Table 1 that were selected based on their location 

on major truck thoroughfares and their data quality over the period 2004 - 2009. 

Staff also evaluated California and regional summary data provided by UC 

Berkeley through their PeMS web site. These data are available in near-real 

time; the most recent PeMS data used in this analysis were from October 2009. 

Table 1. Selected PeMS Locations 

Location Freeway Station No. County 

Norwalk I5 Northbound 715915 Los Angeles 

Oakland I580 Westbound 400549 Alameda 

Ontario I10 Eastbound 801269 San Bernardino 

Los Angeles SR101 764781 Los Angeles 

San Joaquin Valley and 

French Camp Road 

SR99 Northbound 1004910 San Joaquin 

Irvine I405 Northbound 1201333 Orange 

East of Pleasant Valley I80 Westbound 401877 Solano 

San Jose I880 Southbound 400514 Santa Clara 

 Weigh-in Motion (WIM) Stations – More than one hundred weigh-in motion 

sensors are embedded on freeways and state highways in California. These 

sensors provide very detailed and accurate information on truck volumes, 
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weights, axle configuration, and speeds throughout the State. Staff obtained 

multi-year historical data from Caltrans for nine selected sites and analyzed 

the results. These sites were chosen based on their location and data 

completeness between 2004 and 2009. Selected locations are shown in 

Table 2. The WIM data require significant processing such that the most 

recent data used in this analysis were from March 2009. 

Table 2. Selected WIM Stations 

Location Freeway Station 

No. 

County 

Fresno SR-99 SB 10 Fresno 

Antelope I80 (East of Sacramento) 3 Sacramento 

Hayward I880 NB 18 Alameda 

Fontana I15 NB 70 San Bernardino 

Balboa I15 NB 88 San Diego 

Chico SR-99 SB 107 Butte 

Ports of LA / Long Beach I710 Near I405 Interchange 116 Los Angeles 

Carbona 580 WB in San Joaquin County 113 San Joaquin 

Willows I5 NB 108 Glenn 

 Port Container Throughput – The Ports of Los Angeles, Long Beach, and 

Oakland publish historical and current port-specific container throughput 

statistics in a monthly database. The most recent container throughput data 

analyzed for this assessment was from October 2009; data were evaluated 

back to 1995. 

 American Trucking Association (ATA) Truck Tonnage Index – Each month the 

ATA asks its national membership the amount of tonnage each carrier 

hauled, including all types of freight. These data are summarized, normalized 

to the 2000 calendar year, and published. The index represents the relative 

activity of ATA members, and is not specific to California. The most recent 

ATA truck tonnage data analyzed for this assessment was from September 

2009; data were analyzed back to 2005.

 Bureau of Transportation Statistics (BTS) Transportation Services Index – 

The TSI is a seasonally adjusted, weighted measure of the movement of 

freight which is published monthly. The index is national and not specific to 

California. The most recent BTS transportation services data analyzed for 

this assessment was from September 2009; data were evaluated back to 

1990. 
 5 

A complete listing of each source and the estimated decrease in activity relative 

to calendar year 2007 is provided in Table 3. 

Table 3. Estimated Decrease in Current Activity Relative to 2007 

Data Source Region Change 2007-2009 Latest Data Used 

California Fuel Sales Statewide -13% to -18% August 2009 

California PeMS Counts Statewide -4% or more October 2009 

California WIM Counts Statewide -10% or more March 2009 

Port of LA / Long Beach 

Container Traffic 

Los Angeles -26% October 2009 

Port of Oakland 

Container Traffic 

Bay Area -17% October 2009 

ATA Tonnage Index Nationwide -10% September 2009 

BTS Transportation 

Services Index 

Nationwide -14% September 2009 

Results show that truck activity in California is down between 4% and 26% since 

2007, depending on the data source. Staff believes statewide fuel sales is the 

most appropriate measure of the impact of the recession on non-drayage trucks, 

which is consistent with national trends. Preliminary analysis of PeMS and WIM 

data show significant variability in truck activity reductions depending upon the 

location and staff are continuing to assess regional differences. 

Staff believes there are significant differences in the impact of the recession on 

different types of trucking operations. For example, as shown in Table 1, 

container movements through California’s ports and associated drayage truck 

activity have been impacted more significantly than trucking operations in 

general. Also, according to the California Department of Finance, construction 

employment has decreased significantly more than transportation employment as 

a whole. However, with the exception of drayage trucks, staff was not able to 

identify trucking activity-specific statistics for individual trucking sectors in 

California. 

Assessing Current Truck Age in California

In developing the emissions analysis documented in the Rule staff report, staff 

evaluated the impact that trucking sales have on the age distribution of vehicles, 

and found that national sales statistics are correlated with truck age distributions 

in California. This is important because newly manufactured trucks are cleaner 

than older trucks. This correlation was used as an input to the emissions 

analysis, so that historical and future forecasted truck sales have an impact on 

the modeled age distribution of vehicles in each calendar year. When more 

vehicles are sold nationally, more appear in California fleets; and when fewer 

vehicles are sold nationally, fewer appear in California fleets. To validate this 

assumption, staff analyzed trends in national new truck sales reported by 

WardsAuto and changes in the fraction of new truck registrations reported by the 

California Department of Motor Vehicles (DMV). 
 6 

WardsAuto is a company that monitors and publishes national truck sales data 

that are available through a subscription service. Figure 1 shows historical new 

truck sales, and indicates that current sales volumes are at their lowest level in 

25 years. The table also shows significant year to year variability and sensitivity 

to economic conditions. 

Figure 1. National Heavy Duty Diesel New Truck Sales 1985-2009 

0

50

100

150

200

250

300

1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009

Thousands of Trucks

Calendar Year

14,001- 33,000 lbs 33,001 lbs. & over

2006 1999

2003

1995

1991

Because national truck sales are so low, staff expects that the average age of 

vehicles operating in California is getting older. Staff assumes the relationship 

between vehicle sales and registered truck population applies to all trucks 

regardless of registered location, body type, or vocation. This assumption has 

been confirmed for California registered trucks by analysis of California DMV 

registration data, as described below. 

Every six months ARB staff obtains a snapshot copy of the DMV registration 

database. The database contains roughly 50 million records that staff process to 

count the number of cars and trucks by weight class, technology, age, and other 

factors. Staff processed the database to count California-registered non-drayage 

heavy-heavy duty diesel trucks by model year. Drayage trucks were removed in 

order to focus this analysis on vehicle sales caused by normal business vehicle 

replacement decisions, and not by replacement decisions driven by compliance 

requirements. Staff identified roughly 3000 new vehicle registrations in 2009 that 

were also registered in the ARB drayage truck registry. These new vehicle 

registrations in the drayage fleet were higher than normal new vehicle 
 7 

registration rates for drayage trucks, suggesting that these additional 

registrations were completed to comply with Drayage Truck Rule requirements 

effective January 2010, and were not caused by natural turnover. The emissions 

reductions generated by compliance with the Drayage Truck Rule are attributed 

to that Rule and not to the Statewide Truck and Bus Rule. 

Table 4 shows that between 2005 and 2007, approximately 6% of all registered 

in-state non-drayage heavy-heavy duty diesel trucks were new model year 

vehicles. The associated 10% increase in truck population over that same time 

period suggests that in those years the number of new trucks entering the 

California fleet exceeded the number of trucks being retired. However, starting in 

2008, new truck registrations dropped dramatically, consistent with the decline in 

national truck sales, such that less than 3% in-state non-drayage trucks 

registered in 2009 were new model year vehicles. This drop in new vehicle 

registrations resulted in the truck population leveling off and the average fleet 

age increasing by almost a year as fewer new vehicles were purchased and 

existing vehicles stayed on the road longer. 

Table 4. Estimated DMV Registration Database Heavy-Heavy Duty Registered 

Non-Drayage Truck Population in California: 2005-2009 

Year Percent of 

New 

Vehicles in 

Fleet 

Population 

(thousands) 

(nondrayage) 

Average Age 

2005 6.4% 181 9.1 

2006 6.8% 198 9.1 

2007 6.1% 199 9.2 

2008 3.4% 198 9.6 

2009 2.7% 197 9.9 

Table 5 compares the reduction in national new truck sales (as measured 

through national sales data) to the reduction in the number of new non-drayage 

registered vehicles as measured through the California DMV database. Results 

show comparable reductions between 2005 and 2009 in new truck sales on a 

nationwide basis and registration of new model year non-drayage trucks in 

California. 
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Table 5. Trend in National New Truck Sales and New Registered Non-Drayage 

Trucks in California: 2006-2009 

 % Change Relative to 2005 

Year National1 California2

2006 +12% +6% 

2007 -40% -5% 

2008 -46% -47% 

2009 -64% -58%* 

1

 WardsAuto national sales database 

2

 Analysis of California DMV new truck registration data 

* Excludes drayage trucks

The Emissions Analysis 

The Rule emissions analysis reflects annual average long term growth and did 

not evaluate emissions under the cyclical conditions of periodic economic 

expansion and contraction. However, the Rule emissions analysis has two 

important inputs that can be used to reflect the economic cycle: activity growth 

rates, and sales forecasts. 

During a recession the economy contracts due to less economic activity. In the 

trucking sector this translates into fewer overall miles driven and fewer average 

miles driven per truck. Some trucking firms may operate fewer vehicles during a 

recession than during stable economic periods. The net effect is that during a 

recession (assuming no changes in average vehicle age), fewer miles are driven, 

and emissions are reduced as a result. 

During stable economic periods trucking firms will operate their vehicles and as 

mileage accumulates, vehicles will eventually reach the end of their economic or 

useful life. When this occurs firms will replace older trucks with new or newer 

used vehicles. This turnover of vehicles is a standard practice in the industry 

during stable economic periods and varies by type of business. However, during 

a recession this turnover is affected in two ways. First, because fewer miles are 

being driven per truck per year, older vehicles will last longer than they otherwise 

would have, reducing the demand for new or newer used vehicles. Second, 

because businesses are more financially stressed during a recession they are 

less likely or able to purchase new or newer used vehicles. The combined 

impact of these two factors is that over time the fleet gets older. Because older 

vehicles have fewer and less effective emissions controls than newer vehicles, 

fleet average emission rates will increase over time. 

During this recession, the decreased demand for newer vehicles has resulted in 

lower vehicle sales. As shown in Figure 1 and Table 5, 2008 and 2009 model 

year sales and registrations have been very low relative to historical values. In 
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the absence of regulatory requirements, 2008 and 2009 model year vehicles will 

enter the California fleet both now and in the future in numbers significantly lower 

than previously assumed. Because 2007 standard engines are 70% cleaner for 

NOx and 85% cleaner for PM2.5 than engines manufactured prior to 2007, fleet 

average emission rates will be higher both now and in the future relative to what 

was anticipated in the Rule inventory. 

Revised 2009 calendar year emissions estimates were developed using the most 

recent diesel fuel sales, truck activity, and truck sales data available. A listing of 

the fuel sales and activity data sources used are shown in Table 3 and the truck 

sales estimates used are provided in Tables 4 and 5. Figures 2 and 3 show that 

these revised PM2.5 and NOx emissions estimates for calendar year 2009 are 

approximately 20% lower than the estimates provided in the Rule staff report. 

Figure 2. 2009 PM2.5 Emissions: 2008 Staff Report vs. Revised Estimate 

0

5

10

15

20

25

30

35

Staff Report Revised Analysis

PM2.5 (Tons per Day)
 10 

Figure 3. 2009 NOx Emissions: 2008 Staff Report vs. Revised Estimate 

0

100

200

300

400

500

600

700

800

900

Staff Report Revised Analysis

NOx (Tons per Day)

The Statewide Truck and Bus Rule phases-in compliance requirements for NOx 

and PM2.5 over a thirteen year period starting in 2011. The first round of 

requirements take effect over three years beginning in 2011, and requires nearly 

all vehicles to be equipped with a diesel particulate filter by 2014. These 

relatively near-term requirements are focused on reducing near-source risk in the 

vicinity of ports, heavily traveled roadways, and environmental justice 

communities; and on providing emissions reductions in 2014 to meet SIP targets. 

The second round of requirements in the Rule focuses on reducing NOx 

emissions to meet both particulate matter and ozone air quality standards. 

Requirements are phased in between 2012 and 2023 and are designed to meet 

two objectives. The first objective is to meet regional SIP targets in the South 

Coast, San Joaquin, and other regions of the state. The second is to ensure that 

by 2023 all trucks operating in California will be equipped with the lowest NOx 

and PM2.5 emissions control technology available. 

Because the Rule is designed to phase-in compliance over time, understanding 

how the recession will impact future year emissions is important. The Rule 

emissions analysis documented in the staff report assumed long-term annual 

average growth in activity and an estimate of future new vehicle sales. In order 

to assess the impact of the recession, staff evaluated economic and fuel 

consumption projections from a wide variety of sources in order to estimate how 

activity and new vehicle sales will change during and after the recession. 
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Forecasts Used 

Staff evaluated a number of economic, fuel, and other forecasts at the local, 

state, and national level including: 

Economic Forecasts 

 UCLA Anderson School 

Since March 2006 the UCLA Anderson Forecast has provided quarterly 

economic forecasts for California and the U.S. The most recent forecast, 

published in September 2009, provides forecasts for employment, gross 

domestic product (GDP) and housing permits out to 2011. Previous 

publications (e.g. 2007 and 2008) have provided extended forecasts out to 

2020, but the 2009 forecast did not do so. 

 University of the Pacific 

The California and Metro Forecast is a quarterly forecast of the economies of 

California and 11 metropolitan areas in northern California (Modesto, Merced, 

Napa, Fresno, Oakland, Sacramento, San Francisco, San Jose, StocktonLodi, and Vallejo-Fairfield). Published in September of this year the report 

provides forecasts for gross state product, employment, housing permits, and 

population out to 2014. 

 Beacon Economics 

Beaconomics is a quarterly economic forecast for the U.S. and California. 

Published in September of this year the report provides forecasts for personal 

income, employment, housing permits, and imports/exports out to 2013. 

 California Department of Finance 

The forecasts were prepared by the Economic Research Unit of the California 

Department of Finance in April 2009. The reports provide annual and 

quarterly economic forecasts employment, income, and housing permits for 

California and the U.S. out to 2011. 

 California Legislative Analyst’s Office 

The LAO’s “2010-11 Budget: California’s Fiscal Outlook” published in 

November 2009 provides economic projections on California’s budget as well 

as California and U.S. employment, GDP and housing permits out to 2015. 

 United States Congressional Budget Office 

In the CBO’s “The Budget and Economic Outlook: An Update” published in 

August 2009 they provide a forecast of U.S. real and potential gross domestic 
 12 

product out to 2019. The projections suggest that real GDP will converge 

with potential GDP no later than 2015. 

Fuel Consumption and Other Forecasts 

 California Energy Commission 

CEC staff for the 2009 Integrated Energy Policy Report, developed long-term 

forecasts of transportation fuel demand. The Fuel Demand Forecast provides 

diesel fuel consumption for four primary areas: truck and rail freight goods 

movement, residential and commercial light-duty vehicle transportation, urban 

and intercity public transit, and off-road vehicles. The report was published in 

August 2009 and forecasts fuel demand out to 2030. 

 United States Energy Information Administration 

The Annual Energy Outlook 2009 published in March 2009 provides 

projections of US energy supply, demand, and prices through 2030. The 

projections are based on results from the Energy Information Administration's 

National Energy Modeling System. The reference case was updated in April 

2009 to reflect the American Recovery and Reinvestment Act adopted in 

February 2009. The Annual Energy Outlook forecasts national fuel use, truck 

sales and truck vehicle miles traveled through 2030 but does not include any 

information specific to California. 

Table 6 compares each of the forecasts in terms of the information provided, 

when the forecast is last published, and when the next release is anticipated. 

Projecting heavy duty truck emissions into the future requires developing growth 

rates that represent California-specific estimated vehicle activity (vehicle miles 

traveled or VMT) and new vehicle sales in each future year. These growth rates 

can then be input to the emissions analysis to calculate future year emissions. 

Staff evaluated each forecast, and found that none provided California-specific 

growth estimates for truck VMT or truck sales in future years. Staff then 

evaluated each forecast to compare information provided across forecasts. Both 

the Annual Energy Outlook (AEO) from the United States Energy Information 

Administration and the Integrated Energy Policy Report from the California 

Energy Commission provided future year fuel consumption forecasts. The AEO 

also provided truck VMT and truck sales forecasts, but these were nationwide 

projections and did not provide any estimates for California specifically. 
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Table 6. Comparison of Economic and Fuel Consumption Forecasts Economic Forecasts 

Region Data Source Information Provided Forecast to Date Last Published FutuCalifornia UCLA Anderson 

School 

CA non-farm employment by sector; California and national GDP; housing permits. 

2011 September 2009 Dece

 Univ. of the Pacific CA non-farm employment by 

sector; California GDP; housing starts. Forecasts statewide and regional. 

2014 September 2009 Dece

 Beacon Economics CA non-farm employment by 

sector; California and national GDP; housing permits; and imports/exports. 

2013 September 2009 Dece

 CA Dept of Finance CA non-farm employment by 

sector; California and national GDP; housing permits. 

2011 April 2009 2010 

 CA Office of the 

Legislative Analyst 

CA non-farm employment by sector; California and national GDP; housing permits. 

2015 November 2009 2010 

United States Congressional 

Budget Office (CBO) 

National Real GDP 2019 August 2009 Early 

Fuel Consumption Forecasts 

Region Data Source Information Provided Forecast to Date Last Published FutuCalifornia CEC Fuel Demand 

Forecast 

CA diesel fuel demand 2030 August 2009 Augu

United States Energy Information 

Administration (EIA) 

National truck VMT and new truck sales 

2030 April 2009 2011 
 14 

Most California-specific economic forecasts evaluated by staff provided a 

statewide assessment of projected economic measures such as gross state 

domestic product and employment. Those economic measures are not direct 

indicators of trucking activity or vehicle sales but are useful for assessing the 

potential timing and rate of a future economic recovery. Most of the available 

California forecasts focused on the near-term (the next three to five years) and 

did not forecast longer term trends. Finally, each economic forecast projected 

different recovery rates for economic indicators such as gross domestic product 

and employment. 

Bounding Potential Emissions Forecast Scenarios 

As part of this assessment, staff developed a bounding exercise to bracket the 

range of potential economic recovery conditions and their impact on heavy duty 

vehicle emissions in California. Based on the range of economic and other 

forecasts discussed previously, staff developed a faster growth scenario and a 

slower growth scenario for the years 2010 through 2014. These faster and 

slower growth scenarios bracket the range of available forecasts that were 

reviewed. Both scenarios provide emissions projections for several broad 

trucking categories: non-drayage heavy-heavy duty trucks and buses (>33,000 

lbs gross vehicle weight rating); non-drayage medium-heavy duty trucks and 

buses (14,000-33,000 lbs gross vehicle weight rating), drayage trucks at the Port 

of Los Angeles and Long Beach, and drayage trucks at the Port of Oakland. 

The faster growth scenario assumes that by 2017 trucking activity and vehicle 

sales in California will return to levels anticipated in the Rule staff report. The 

return to anticipated activity and vehicle sales levels by 2017 is based on historic 

recovery rates from previous recessions and also accounts for the idea that 

California is likely to recover more slowly from this recession than the country as 

a whole. Specifically, the Congressional Budget Office historical national gross 

domestic product data indicates that no national recession or depression since 

1929, including the Great Depression, has taken more than eight years to 

recover back to previously anticipated growth levels. In addition, the 

Congressional Budget Office forecast suggests that real gross domestic product 

at a nationwide level will converge with potential gross domestic product trends 

no later than 2015. Coupling this national forecast with the assumption that 

California’s recovery will lag the nation by several years yields the 2017 recovery 

date assumed for the faster growth scenario. 

For this analysis, the vehicle activity recovery rate was assumed to be linear 

between current 2009 levels and anticipated 2017 levels, which results in a 

recovery rate of approximately 6.3% per year in heavy heavy-duty diesel truck 

activity. Because vehicle sales are much more sensitive to changes in economic 

conditions than is truck activity, the growth in heavy heavy-duty diesel vehicle 
 15 

sales was assumed to be 36% per year for 2010 and 2011, and 4.8% per year 

from 2012 to 2017. 

The slower growth scenario is based on the assumption that trucking activity and 

new vehicle sales will not return to previously anticipated levels in the 

foreseeable future. Staff assumed that truck activity will remain flat in 2010 at 

2009 levels, and then grow at annual average growth rates reflected in long term 

trends and published in the staff report (which as documented in the staff report 

is 2.6% per year for heavy heavy-duty diesel trucks). This scenario is generally 

consistent with the economic outlook defined by the California Legislative 

Analyst’s Office (November 2009), national trends in the AEO, and recovery 

rates in most California-specific employment forecasts. Vehicle sales are 

assumed to be flat in 2010 and 2011, with 11% per year growth occurring 

between 2011 and 2017. 

Method for Forecasting Emissions 

Staff developed a scaling approach for estimating the impacts of projected 

reduced activity and projected reduced vehicle sales on emissions for each 

calendar year between 2010 and 2014. The scaling approach starts with the 

emissions estimated by the Rule analysis, and ratios those emissions to reflect 

the change in activity, sales, and the reductions resulting from the Rule. The 

scaling approach is conducted in a Microsoft Access database. The following 

equation was used to calculate emissions for NOx and PM2.5 without the 

application of reductions generated by the Rule: 

ΣEsypc = Ebypc x Asyc x Ssyc (1) 

 

where 

Esypc = Emissions after rule is applied for scenario “s,” year “y,” pollutant “p,” and 

category “c”

Ebypc = Baseline emissions from rule inventory analysis for year “y” and pollutant 

“p,” and category “c” 

Asyc = Activity ratio reduction factor for scenario “s,” year “y,” and category “c” 

Ssyc = Sales ratio reduction factor for scenario “s,” year “y,” and category “c” 

The following equation was used to calculate emissions for NOx and PM2.5 (prior 

to 2014) after the Rule is applied: 

ΣEsypc = Ebypc x Asyc x Ssyc x Rypc (2) 

where, 

Rypc = Rule ratio reduction factor for scenario year “y,” pollutant “p,” and 

category “c”

A similar scaling equation was used for calculating PM2.5 emissions after 

application of the Rule in 2014 except that the sales reduction ratio is not used 
 16 

because after the implementation of the Rule for PM2.5 in 2014, all vehicles are 

required to be equipped with a diesel particulate filter. As a result, the increase 

in age does not materially affect remaining emissions after the Rule is applied. 

The equation for PM2.5 emissions in 2014 is as follows: 

ΣEsypc = Ebypc x Asyc x Rypc (3) 

 

In these equations, the activity ratio reduction is calculated as the projected 

activity level (vehicle miles traveled) divided by the anticipated activity level in the 

Rule inventory analysis (vehicle miles traveled) in each calendar year for each 

scenario. 

The rule reduction factor is calculated as the ratio of the Rule emissions analysis 

with the rule applied in each calendar year divided by the Rule emissions 

analysis baseline inventory without the rule applied. This ratio is calculated for 

each calendar year, pollutant and inventory category in the Rule inventory, and is 

applied independent of economic scenario. The fact that the ratio is applied 

independent of economic scenario is a simplification because the model year 

distribution of vehicles will vary from the baseline in each economic scenario due 

to different forecasts of vehicle sales and their impact on projected age 

distributions in each category and fleet size group. 

The sales reduction ratio is calculated using a two step process that adjusts the 

fraction of a model year in an age distribution by the ratio of projected sales 

under a bounding scenario to annual average projected sales. This ratio reflects 

the fact that a recession reduces the originally estimated new vehicle sales and 

vehicle turnover, and as a result the vehicle fleet becomes older. In the Rule 

inventory analysis vehicle turnover is a function of national new vehicle sales, the 

methodology for which is described on pages 46-53 of Appendix G of the Staff 

Report for the Statewide Truck and Bus Rule. In the methodology, the fraction of 

each model year in the inventory category age distribution is a function of an 

average age distribution and a sales forecast, as shown in equation 4. This 

fraction for each model year and calendar year is normalized to one, as shown in 

equation 5. 

FMY,CY,c = AMY,CY,c x (Ss / Sa) (4) 

 where, 

FMY, CY, c = Fraction of a given model year in a calendar year and 

inventory category. 

AMY, CY, c = Average fraction of a given model year in a calendar year and 

inventory category, calculated using 2000-2005 historical 

DMV data. 

Ss = Projected sales in a forecast scenario “s.” 

Sa = Projected average annual sales, calculated with by regression 

line through historical truck sales 1985-2009 and projected 

into the future. 
 17 

Fcc = (FMY,CY,c x 100) / Σ FMY,CY,c (5) 

where, 

Fcc = Corrected fraction of a given model year in a calendar year 

and inventory category. 

Using this methodology, the fraction of a model year in a calendar year and 

inventory category can be adjusted using different sales forecast scenarios. To 

assess the impact of this assumption, the VMT-weighed average emission rate 

can be compared across economic scenarios. As an example, Table 7 

compares the heavy-heavy duty diesel California registered in-state tractor fleet 

average PM2.5 and NOx emission rate for the 2008 Rule emissions analysis 

published in the staff report, the faster growth scenario, and the slower growth 

scenario in calendar year 2014. The table shows that the expected fleet average 

emission rate in 2014 is significantly higher than assumed in the staff report due 

to sharply lower truck sales. Depending upon the rate of truck activity growth, 

fleet average emission rates in 2014 will be 6% to 16% higher for NOx and 8% to 

21% higher for PM2.5 than was assumed in the 2008 Rule analysis. 

Table 7. Heavy-Heavy Duty Diesel Tractor VMT Weighted Emission Rates 

(grams per mile) in 2014 by Growth Scenario. 

Scenario PM2.5 Percent NOx Percent 

2008 Rule Emissions Analysis 0.49 100% 10.2 100% 

Faster Growth Scenario 0.52 108% 10.8 106% 

Slower Growth Scenario 0.58 121% 11.9 117% 

Results 

Figure 4 compares estimated PM2.5 emissions resulting from implementation of 

the Rule as described in the 2008 staff report to what would happen under the 

two growth scenarios assumed. Because the Rule is phased-in over a number of 

years, most of the Rule reductions are expected to occur between 2012 and 

2014. The figure shows in 2011 the recession provides more emissions 

reductions than the Rule was projected to provide in the Rule staff report. After 

2011 the Rule is projected to provide more emissions reductions than the 

recession alone would provide. After 2012 the Rule provides significantly more 

emissions reductions than under either the faster or the slower growth scenarios. 

 
 18 

Figure 4. Statewide PM2.5 Emissions 2011-2014 

0

5

10

15

20

25

30

2011 2012 2013 2014

Calendar Year

PM2.5 Tons per Day

Faster Growth Without Regulation

Slower Growth Without Regulation

Staff Report Projection With Regulation

Due to the phase-in of requirements in the Rule, NOx emissions reductions are 

not expected until 2013. Figure 5 compares NOx emissions reductions projected 

to be achieved by the Rule in the 2008 staff report to the faster and slower 

growth scenarios. Results show that in 2013 and 2014 the Rule is anticipated to 

provide more emissions reductions than would be achieved by the recession 

alone. 

Figure 5. Statewide NOx Emissions 2011-2014 

0

100

200

300

400

500

600

2013 2014

Calendar Year

NOx Tons per Day

Faster Growth Without Regulation

Slower Growth Without Regulation

Staff Report Projection With Regulation
 19 

The Statewide Truck and Bus Rule was designed to provide sufficient NOx and 

PM2.5 emissions reductions to meet SIP targets in the South Coast region in 

2014. The next step in the analysis was to estimate calendar year 2014 

emissions under the faster and slower growth scenarios and compare the results 

to the SIP target. Figure 6 compares 2014 PM2.5 emissions in the faster and 

slower growth scenarios after the Rule is applied to anticipated emissions levels 

in the staff report and SIP target. Results suggest that in the faster growth 

scenario, the Rule is not projected to provide significantly more PM2.5 emissions 

reductions than anticipated in the staff report. In the slower growth scenario, 

emissions are slightly lower than anticipated in the staff report. 

Figure 6. Projected 2014 Statewide PM2.5 Emissions (tons per day) 

0

5

10

15

20

25

Staff Report Faster Growth Slower Growth

PM2.5 Tons per Day

Without Rule With Rule

Reduction level to 

meet SIP target

Figure 7 compares 2014 NOx emissions in the faster and slower growth 

scenarios after the Rule is applied to anticipated emissions levels in the staff 

report. Under the faster growth scenario the drop in truck activity that reduces 

emissions is offset by the increased emissions caused by decreased vehicle 

sales and fleet turnover. Under the slower growth scenario the impact of the 

drop in activity due to the recession reduces emissions more than the impact of 

reduced sales increases emissions. After the Rule is applied to the slower 

growth scenario, the Rule might provide slightly more emissions reductions than 

were anticipated in the Rule staff report. This analysis shows that assumptions 

about the rate of economic recovery and related growth in truck activity and sales 

determines whether the Rule provides any NOx emissions reductions above and 

beyond what was expected in the Rule staff report. 

 
 20 

Figure 7. Projected 2014 Statewide NOx Emissions (tons per day) 

0

100

200

300

400

500

600

Staff Report Faster Growth Slower Growth

NOx Tons per Day

Without Rule With Rule

Reduction level to 

meet SIP target

Conclusions 

The economy has had a significant impact on emissions from trucks and buses in 

California. Staff estimates emissions in 2009 have been reduced by more than 

20% relative to estimates published in the 2008 staff report. Projected future 

emissions are dependent upon how California truck activity and truck sales 

recovers from the recession over the next five years. Staff developed two 

scenarios that were designed to bound the range of economic and fuel forecasts 

that were reviewed. Results suggest the recession will reduce emissions in 2011 

more than was anticipated by the Rule in the staff report because the Rule is 

phased-in and relatively few reductions were anticipated in 2011. After 2012 the 

Rule is expected to generate much lower emissions than would be generated by 

the recession alone. In 2014, the analysis demonstrates the Rule is necessary to 

achieve the SIP target, and the extent to which the economy recovers will dictate 

whether or not the Rule will generate any emissions reductions above and 

beyond what was expected in the staff report. 
 21 

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