Appendix F 

Emission Inventory Description 
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May 7, 2007 Appendix F 1 

TABLE OF CONTENTS 

1. Introduction ............................................................................................................... 2

Purpose ...................................................................................................................... 2

Statutory Requirements ............................................................................................ 2

Emission Inventory Overview................................................................................... 2

Basic Elements of the Emission Inventory.......................................................... 2

Agency Responsibilities........................................................................................ 3

Pollutants and Precursors .................................................................................... 4

Geographic Considerations .................................................................................. 6

Base Year Inventory Selection for the SIP........................................................... 7

Emission Estimation Concepts............................................................................. 7

Emission Forecasting Overview........................................................................... 7

Types of Inventories (Annual Average, Seasonal, Modeling) ............................ 8

2. Emission Inventory Improvements.......................................................................... 9

Overview..................................................................................................................... 9

Improvement Process ............................................................................................... 9

Planning and Development - SIP .......................................................................... 9

Regulatory Support................................................................................................ 9

Special Studies / Research ................................................................................... 9

Stakeholder Outreach.......................................................................................... 10

Quality Assurance/Quality Control (QA/QC)...................................................... 10

Specific Category Improvements........................................................................... 11

Stationary ............................................................................................................. 11

Mobile.................................................................................................................... 13

Biogenic................................................................................................................ 18

3. Emissions Estimation Methods and Documentation........................................... 19

Major NOx/ROG Categories .................................................................................... 19

Emissions Estimation Methods.............................................................................. 19

Stationary Emissions........................................................................................... 19

Area-wide Emissions ........................................................................................... 21

CEFS Forecasting Algorithm (Used for Stationary, Area-wide, Aircraft, and 

Ships).................................................................................................................... 22

Temporal Factors (Stationary and Area Sources Only).................................... 23

Growth Factors (Stationary and Area Sources Only) ....................................... 23

Control Factors .................................................................................................... 24

Mobile Sources..................................................................................................... 25

Biogenics (Overview of the BEIGIS Model) ....................................................... 34

Emissions Inventory Systems Data (CEIDARS, CEFS)..................................... 35
May 7, 2007 Appendix F 2 

1. Introduction 

Purpose

This Emission Inventory Appendix describes the emission inventory and the role it 

plays in the State Implementation Plan (SIP) development process. An emission 

inventory is an estimate of the amount and type of pollutants emitted into the 

atmosphere over a defined period of time. Emission inventories serve three principal 

roles in the development of the SIP: 

• They provide the emissions data used for developing control strategies; 

• They are a primary input to photochemical modeling used in attainment 

demonstrations; and 

• They are used to track progress in meeting the emission reduction commitments. 

This document will discuss the requirements for SIP development as it pertains to 

emission inventories, describe the elements (or sectors) that make up an emission 

inventory, provide an overview of the methodologies used to derive emission estimates, 

summarize the recent improvements to the emission inventory, and explain how the 

emission inventory is documented through Quality Assurance (QA) and Quality Control 

(QC). 

Statutory Requirements

The federal Clean Air Act (CAA) contains the statutory requirements for attaining clean 

air (air quality standards). The U.S. Environmental Protection Agency (U.S. EPA) 

regulations list requirements pertaining to emissions information that must be included 

as part of the SIP submittal package. The regulations require that the SIP emission 

inventory contain the pollutants for which an area is nonattainment. For an 8-hour 

ozone SIP, the emission inventory must contain the two ozone precursors: oxides of 

nitrogen (NOx) and reactive organic gases (ROG). (The terms, ROG and VOC (volatile 

organic compounds), are used interchangeably in this document.) For the PM2.5 SIP, 

the emission inventory must contain directly emitted PM2.5 and PM precursors: NOx, 

ROG, sulfur oxides (SOx), and ammonia (NH3). 

Emission Inventory Overview

Basic Elements of the Emission Inventory 

An emission inventory is a critical tool in the evaluation of air pollution. Very simply, an 

emission inventory is a systematic listing of the sources of air pollution along with the 

amount of pollution emitted from each source or category over a given time period. 

Emission inventories are an estimate of the air pollution emissions that are actually 

released into the environment—they are not measurements of ambient concentrations. 

The following are examples of pollution sources by key sectors: 
May 7, 2007 Appendix F 3 

• Industrial sources—power plants and oil refineries; 

• Area-wide sources—consumer products and residential fuel combustion for 

heating homes; 

• On-road sources—passenger vehicles and heavy-duty trucks; 

• Off-road mobile sources—aircraft, trains, ships, recreational boats, construction 

equipment and farm equipment; and 

• Non-anthropogenic (natural) sources—biogenic (or vegetation), geogenic 

(petroleum seeps), and wildfires. 

The first four sectors listed are examples of anthropogenic, or human caused, emission 

sources. California’s statewide emission inventory includes over 17,000 individual 

facilities (or point sources) where business addresses are specifically identified. These 

facilities comprise approximately 14,000 process/industry types. 

The emission inventory also includes approximately 450 area-wide source categories. 

The area-wide source categories include aggregated point sources, or facilities, that are 

not inventoried individually but are estimated as a group and reported as a single 

source category, for example, gas stations and dry cleaners. Area-wide sources 

typically are associated with human activity and take place over a wide geographic 

area. Consumer products and unpaved road dust are additional examples of area-wide 

sources. The complete methodologies for these and all area-wide source categories 

can be found at: http://www.arb.ca.gov/ei/areasrc/areameth.htm. 

The mobile source emission inventory is developed by ARB’s emission factor models - 

EMFAC and OFFROAD. EMFAC estimates on-road emissions from all on-road motor 

vehicles, from passenger cars through heavy duty diesel trucks, and groups them in 

250 categories (or technology groups). Off-road categories include emissions from all 

vehicles and equipment that operate off-road which includes aircraft, locomotives, lawn 

and garden, cargo handling, construction, and ships and harbor-craft. OFFROAD 

groups these equipment into 1300 categories. For each category in EMFAC and 

OFFROAD, emissions are given by emission mode (e.g. running exhaust, starts, 

evaporative losses, and tire and brake wear). 

Non-anthropogenic sources generally include source categories with naturally occurring 

emissions such as wildfires and geogenic sources (e.g., petroleum seeps). 

Agency Responsibilities 

ARB works jointly with the thirty-five local air pollution control and air quality 

management districts (districts) to develop a comprehensive statewide emission 

inventory. Districts are responsible for developing emission estimates for major facilities 

(point sources) in their jurisdictions by working closely with facility owners. Districts are 

also responsible for developing emission estimates for approximately one-third of the 

non-point (or area-wide) sources. 
May 7, 2007 Appendix F 4 

ARB is responsible for developing the mobile source inventory (both on-road and offroad sources) and the remaining two-thirds of the area-wide sources. ARB works with 

other state agencies including the California Department of Transportation (CalTRANS), 

the Department of Motor Vehicles (DMV), and local councils of government (COGs) to 

assemble motor vehicle activity information necessary for the mobile source emission 

estimation models. To estimate emissions for the remaining two-thirds of the area-wide 

sources, ARB works jointly with State agencies, such as the Department of Pesticide 

Regulation (DPR) which develops the emission estimates for pesticides and the 

California Energy Commission which maintains power production and energy demand 

data that are critical for estimating future emissions growth from power plants.

Pollutants and Precursors 

California’s ozone attainment strategy is to reduce emissions of ozone precursors – 

NOx and VOC. The strategy for reducing PM2.5 focuses on reducing NOx. 

Oxides of Nitrogen (NOx) 

NOx from anthropogenic sources occurs primarily when fossil fuels are combusted at 

high temperatures. The table below shows that in 2006, 85 percent of NOx emissions in 

California are generated from mobile sources such as cars, trucks, buses, aircraft, and 

trains, while area-wide and stationary sources contribute the remaining 15 percent. 

2006 Statewide Emission Inventory – Nitrogen Oxides 

NOx Emissions (Annual Average) 

Source Tons/day Percent 

Stationary 419 12 percent 

Area-wide 96 3 percent 

On-road Mobile 1848 51 percent 

Gasoline vehicles 679 19 percent 

Diesel vehicles 1169 32 percent 

Other Mobile 1235 34 percent 

Gasoline vehicles 76 2 percent 

Diesel vehicles 825 23 percent 

Other 333 9 percent 

Total Statewide 3598 100 percent 
May 7, 2007 Appendix F 5 

Reactive Organic Gases (ROG) 

Reactive Organic Gases1 are any compound of carbon, excluding carbon monoxide, 

carbon dioxide, carbonic acid, metallic carbides or carbonates, and ammonium 

carbonate, which participate in atmospheric photochemical reactions to form ozone and 

particulate matter (PM10 and PM2.5) in the atmosphere. References ii and iii provide 

information on the differences between ROG and VOCs. 

The primary anthropogenic sources of ROG in California, as shown in the table below, 

are on-road mobile which includes exhaust, fuel evaporation, and incomplete fuel 

combustion, and area-wide sources which includes solvents from dry-cleaning, 

degreasing, and coating operations. 

2006 Statewide Emission Inventory – Reactive Organic Gases 

ROG Emissions (Annual Average) 

Source Tons/day Percent 

Stationary 389 17 percent 

Area-wide 654 28 percent 

On-road Mobile 743 32 percent 

Gasoline vehicles 670 29 percent 

Diesel vehicles 73 3 percent 

Other Mobile 541 23 percent 

Gasoline vehicles 389 17 percent 

Diesel vehicles 111 5 percent 

Other 41 2 percent 

Total Statewide 2327 100 percent 

Particulate Matter (PM2.5) 

Particulate matter (PM) is a complex mixture of varying sized particles and liquid 

droplets including components such as acids, organic chemicals, metal, and soil or 

dust. There are two types of PM: primary and secondary. Primary PM is emitted 

directly from a source, such as unpaved roads, fires, and demolition or construction 

sites. Secondary PM is formed by complex reactions in the atmosphere with chemicals 

such as sulfur and nitrogen dioxides. The majority of “fine particles” (PM2.5) is formed 

by these complex reactions. A subset of PM2.5 of particular concern are those that are 

emitted by diesel engines. 
May 7, 2007 Appendix F 6 

2006 Statewide Emission Inventory – PM2.5

PM Emissions (Annual Average) 

Source tons/day Percent 

Stationary 103 13 percent 

Area-wide 568 70 percent 

On-road Mobile 66 8 percent 

Gasoline vehicles 15 2 percent 

Diesel vehicles 43 5 percent 

Break & Tire wear 8 1 percent 

Other Mobile 81 10 percent 

Gasoline vehicles 10 1 percent 

Diesel vehicles 41 5 percent 

Other 29 4 percent 

Total Statewide 817 100 percent 

Geographic Considerations 

In California, the emission inventory is constructed at the district, air basin, and county 

levels. This provides the flexibility needed to meet the jurisdictional requirements of 

local and State governments while addressing the spatial aspects of air quality issues. 

In cases where nonattainment areas do not line up with these geographic boundaries, 

ARB further resolves the inventory to estimate the portion of emissions that occur within 

nonattainment area boundary lines. This is done by selecting only the point sources 

that fall within the nonattainment area boundaries, and estimating the emissions 

contribution of each area-wide and mobile source category to the nonattainment area. 

California recently approved the statewide Emission Reduction Plan for Ports and 

Goods Movement that extends the off-shore boundaries for estimating the emission 

impact from shipping activities, thus leading to a modification in the geographic 

accounting of the off-shore emissions in the inventory. Formerly, only marine emissions 

occurring within a 3-mile range were included as part of California’s emission inventory. 

The SIP emission inventory now includes emissions from shipping activities out to 100 

miles. In the new definition, emissions occurring within three miles of the shore line are 

assigned to the nearest air basin (e.g., emissions occurring within three miles of the Los 

Angeles County shore line are assigned to Los Angeles County in the South Coast Air 

Basin). Emissions occurring outside the 3-mile boundary are assigned to the Outer 

Continental Shelf Air Basin, but are still associated with the responsible county and 

district (e.g. the emissions occurring outside of the 3-mile boundary of Los Angeles 

County would be assigned to the Outer Continental Shelf Air Basin and would be the 

responsibility of the South Coast Air District). 
May 7, 2007 Appendix F 7 

Base Year Inventory Selection for the SIP 

The SIP is based on emission projections that are linked to a base year inventory. 

U.S. EPA identified 2002 as the emission inventory base year for the 8-hour ozone and 

PM2.5 SIPs. This selection was announced by memoranda to the States in 

November 18, 20022

. 

Emission Estimation Concepts 

The key to the emission inventory is found in what is termed the “emission process”. 

The emission process defines the fundamental level at which emissions are calculated, 

stored, and maintained in the inventory. The total emissions for each emission process 

are calculated by applying a process rate (i.e., the number of emission activity units) to 

the emission factor (i.e., the amount of emissions per activity unit). 

In principle, this simple concept holds for all emission sectors (i.e., point, area-wide, 

on-road mobile, and off-road mobile). Differences lie in the method or approach used to 

derive the process rate and emission factors. For example, the emissions from a power 

plant could be calculated by applying an emission factor (pounds of emissions per 

megawatt-hour) times the number of megawatt-hours of electrical energy generated. 

The emissions from the light-duty passenger car fleet could be calculated by applying 

an emission factor (grams of emissions per mile traveled) times the total vehicle miles 

traveled (VMT) for that mobile category. It should be noted that the examples above 

are simplified—particularly for on-road and off-road emissions. These emission factors 

are specific to model year, technology and fuel type, and are adjusted for temperature, 

humidity, and operating speed. 

Emission Forecasting Overview 

Emissions forecasting depends on two independent variables: growth and control. For 

stationary sources, socioeconomic growth profiles are developed and linked to the 

inventory via the inventory process and/or industry types. For example, power plant 

growth is estimated based on the combined effects of economic growth in the sector 

along with the projected energy utilization by the California Energy Commission (CEC). 

Growth for consumer products is estimated by population growth at the county level. 

These growth profiles are constructed for the entire timeframe addressed in the SIP. 

The California Emission Forecasting System (CEFS) includes growth data for the period 

1990–2030 for SIP forecasting exercises. Similarly, control profiles are constructed to 

reflect adopted emission control measures. A control profile is developed that describes 

the implementation of the rule and the profile is included as part of the baseline CEFS 

forecasts. CEFS projections are run for the entire State by applying the growth and 

control profiles to the 2002 base year inventory to obtain the projections needed for SIP 

analysis. 

EMFAC and OFFROAD do not use a base year projection approach. Rather, the 

emission models employ sophisticated routines that predict vehicle fleet turnover by 

vehicle model year. As with stationary sources, EMFAC and OFFROAD include control 
May 7, 2007 Appendix F 8 

algorithms that account for all adopted regulatory actions (e.g., an amended emission 

standard to be implemented by a certain year, or increased stringency on a roadside 

inspection program to be implemented in a future year) which, when combined with the 

fleet turnover algorithms, provide baseline projections. 

CEFS integrates the projected inventories for stationary and mobile sources into a 

single database to provide a comprehensive statewide forecast inventory. 

Nonattainment area inventories are extracted from this comprehensive inventory. This 

establishes the baseline projections from which the SIP inventory is constructed. The 

data are accessible to ARB and district planners via user-friendly web reporting tools. 

Types of Inventories (Annual Average, Seasonal, Modeling) 

Annual Average

Annual average emissions data by major source category in tons per day are derived 

from a simple average by taking the annual emissions reported (or estimated) in tons 

per year and dividing the emissions by 365 days. 

Seasonal Inventories

Summer and winter planning emissions take into account the temporal variation (e.g. 

activity variation) of emissions at a facility or a source category throughout the year. 

This is accomplished by collecting throughput or activity data from point source facilities 

where available, and developing temporal profiles for area sources to estimate monthly 

variation of the emissions. CEFS calculates summer and winter planning emissions 

based on these temporal data. The summer planning season for California is MayOctober, and the winter planning season is November-April. (Note: U.S. EPA assumes 

a shorter summer planning period (June-August) in its temporal data collection 

schema.) California requires planning evaluations to be based on a longer summer 

because it experiences longer periods in which temperatures are warm enough to 

contribute to ozone formation than most other states). The summer season planning 

emission inventory is used in ozone SIP planning. 

Modeling Inventories

CEFS also generates emission inputs for photochemical modeling exercises. The 

categories handled by CEFS are stationary, area-wide and off-road mobile sources. 

(Note: Modeling emissions for the on-road sector are generated with EMFAC/DTIM, 

and these modeling inputs are handled outside of CEFS.) Modeling inventories are 

month/day-specific estimates that are temporally and spatially resolved at a finer level 

than planning inventories—CEFS calculates emissions for a typical weekday or a typical 

weekend day based on weekly operation profiles identified for the emissions processes. 

Point source locations are identified in CEFS by the Universal Transverse Mercator 

(UTM--North American Datum (NAD83) version) geographic coordinate system. 

Modeling inventory projections include facility level emissions at the facility, device, and 

process level with stack locations and associated flow characteristic as applicable. 

Area source emissions are maintained at the county level and are further resolved 
May 7, 2007 Appendix F 9 

based on spatial surrogates as a post-processing step prior to modeling. The day 

specific emissions are generated for typical weekday and weekend periods. 

Planning and Modeling Inventory Differences

The temporal information used to determine seasonal planning inventories is also used 

to develop month/day-specific modeling inventories—the data are just further resolved 

for modeling inventories. It should be noted that modeling inventories generated by 

CEFS are not actual day specific emissions based on field studies—they are estimates 

of emissions for “typical” operating conditions. In some cases, “actual” day-specific 

information is available and this can be used to overwrite the results of the CEFS 

emission modeling inventory outputs. It is important to note that because modeling 

inventories are month/day-specific, the emission numbers will not match the planning 

inventory emissions. 

2. Emission Inventory Improvements 

Overview

ARB devotes substantial effort to continually improve the emission inventory. Updates 

to the inventory occur through three processes: planning and development, regulatory 

support, and special studies. The new information acquired and methodologies 

developed are folded back into the models as well as the methodologies for sources not 

previously included. This is a dynamic process and ARB will continually work to 

improve its methodologies through research and stakeholder feedback. 

Improvement Process 

Planning and Development - SIP 

The planning process is undertaken to develop strategies for meeting air quality goals. 

The SIP inventory is the centerpiece data element for determining future attainment in 

photochemical modeling exercises, and the basis for defining control strategies. 

Regulatory Support 

The regulatory process identifies potential emission reductions. This typically involves 

new surveys to gather the most up-to-date data (e.g. equipment activity and 

populations). These improved data allow for more accurate emission estimates and 

identify key areas where reductions can be achieved. The planning and regulatory 

processes are also used to solicit peer review and stakeholder input. 

Special Studies / Research 

Another mechanism through which improvements are made is special studies. These 

studies may or may not be associated with the SIP or regulatory support processes but 

are used to further the understanding of emission modeling and verification. Special 

studies include funding or participating in cutting edge research projects, developing 
May 7, 2007 Appendix F 10 

innovative emission inventory methodologies, and collaborating with industry, academia 

and the public to better understand emissions processes. Examples of special studies 

include, but are not limited to, Southern California Ozone Study and Central California 

Ozone Study related research. The results from these projects have provided data that 

allow validation checks between observed air quality and emission trends3

, and 

emissions associated with air quality exceedances4

. 

Stakeholder Outreach 

ARB works jointly with other State agencies, districts, and stakeholders to develop a 

comprehensive emission inventory on an annual basis. Comprehensive inventories are 

submitted triennially and partial inventories are submitted annually to U.S. EPA for the 

National Emission Inventory5

 (NEI). ARB also publishes the most current emission 

inventory in the annual Almanac of Emissions and Air Quality6

. 

Quality Assurance/Quality Control (QA/QC) 

QA/QC is a formal process focused specifically on ensuring the integrity and accuracy 

of the inventories for the California 2007 8-hour ozone SIP and PM2.5 SIP in California. 

ARB formally initiated this comprehensive effort in September 2004 through its 

Emission Inventory Technical Advisory Committee (EITAC). This started an iterative 

process of continual updates to the 2002 base year emission inventory for stationary 

point and area-wide sources (including growth and control data), leading up to the 

finalization of the SIP inventory. In addition, ARB emission inventory staff worked jointly 

with the ARB’s modeling staff through the Gridded Emission Coordination Group that 

includes district modeling staff and industry representatives. A principle aim of this 

group is to provide a critical feedback loop to emission inventory staff to ensure that 

inventory inputs have been reliably prepared for use in photochemical modeling. 

The statewide emissions inventories are assembled and maintained by ARB in the 

California Emission Inventory Development and Reporting System (CEIDARS) and 

California Emission Forecasting and Planning Inventory System (CEFS) databases. 

Before an emission inventory is approved, a series of checks are performed to assure 

that the correct statewide emissions estimates are reported. Upon completion of the 

models, various scenarios are run to provide emissions by county, air basin, district, EIC 

code, pollutant, calendar year, and season. Queries are then run on these scenarios to 

provide the statewide emission totals by pollutant and year. Finally, as a check to 

ensure that what CEFS estimates as state totals match what EMFAC/OFFROAD 

estimates, the CEFS queries are matched against EMFAC/OFFROAD model output. 

Inventory verification7

 is another important step to ensure the accuracy of the emission 

inventory. Since 1987 there have been a number of studies that have contributed to 

model development. In these tests, emissions from vehicle fleets are compared to 

output for similar fleets calculated from the EMFAC model. Comparisons have been 

made between EMFAC fuel consumption estimates and actual fuel sales for that fleet 

reported by the State Board of Equalization, and emissions derived from fuel sales and 

remote sensing data. 
May 7, 2007 Appendix F 11 

Specific Category Improvements

Stationary 

Methods for estimating emissions from industrial point sources have continually 

improved as district staff work with facility owners to ensure that reported emissions are 

real as opposed to permitted (or potential) values. The California Clean Air Act Fee 

Regulation imposes fees on large permitted point sources thus encouraging facility 

owners to report the most accurate emissions possible. ARB audits the district 

emission inventory programs on a planned cycle to further ensure that emission 

inventory program requirements are met. 

Area-wide 

New survey data for consumer products and architectural coatings improve the 

aggregated inventory estimates as well as a better characterization of emissions at the 

product type. Currently there are 152 consumer product categories and 56 architectural 

coatings categories - the 1994 SIP inventory only had three categories each. The same 

is true for degreasing categories - the 1994 SIP had only five categories and the current 

inventory now has 32 categories. Improvements have also been made to the 

agricultural industry categories as a result of a partnership between ARB and the 

agricultural community. ARB participates in an ad-hoc agricultural advisory committee 

to approve methods used for estimating base year emissions and future year growth 

and control assumptions for forecasting. The methodologies for the following categories 

have also been updated: auto refinishing, industrial coatings and solvents, livestock 

husbandry, pesticides, waste burning, wildland fire use, ammonia, and wineries. The 

most recent improvements to the area-wide emission inventory sectors are described 

below: 

 Ammonia 

A comprehensive 2002 ammonia inventory was developed for all area-wide sources (in 

addition to on-road, off-road, and natural sources). The emissions were calculated 

using data provided in reports by ENVIRON and the NASA Ames Research Center. 

 Architectural Coatings 

In response to the California Clean Air Act Fee Regulation, several architectural coating 

manufacturers submitted revisions to their 2001 survey data (calendar year 2000 sales). 

The changes in sales volume and emissions were applied uniformly across all 

categories. 

 Auto Refinishing 

This category was updated using data from a 2001 ARB survey and the emissions were 

grown to 2002. 

 Consumer Products 

Two sets of changes have been incorporated into the consumer products inventory. 

First, manufacturers submitted revisions to their 1997 survey data in response to the 

California Clean Air Act Fee Regulation and resulted in updates for 13 categories. Next, 
May 7, 2007 Appendix F 12 

results of the 2001 Consumer Products Survey have been incorporated. Some 

categories have been expanded and several new categories have been added. 

 Industrial Coatings and Solvents 

The emissions for several of these categories have been updated using the 

U.S. Census Bureau’s 2002 Industrial Report for Paint and Allied Products. The 

nationwide consumption data were apportioned to California using manufacturing 

employment data for the industry sectors likely to use the specific types of industrial 

coatings. 

 Livestock Husbandry 

ARB published a new methodology in 2004 for estimating ROG emissions from 

livestock facilities including dairies, feedlots, poultry operations, and other confined 

animal facilities. The methodology also includes PM estimates for dairies and feedlots. 

The emission estimates are based on animal population data from the year 2000. ARB 

uses district-specific data where available and employs a generalized methodology 

where data are lacking. For permitting purposes and to more fully reflect the processspecific livestock emissions, the San Joaquin Valley Air District has adopted livestock 

emission factors that differ from the ARB default values. 

 Pesticides 

The pesticide inventory includes the emissions from agricultural and structural 

applications. Updated emissions for 2003 are calculated using information from the 

annual Pesticide Use Report (PUR) database and pesticide product emission potential 

(EP) data maintained by the California Department of Pesticide Regulation (DPR). The 

EPs that are assigned to the products are either measured by thermogravimetric 

analysis (TGA), calculated by DPR chemists, or assigned a default value equal to the 

median TGA-based EP in each formulation category. Prior to 2002, DPR assigned EP 

values to products with no measured values as the maximum TGA in that category. The 

use of median rather than maximum TGA values has resulted in a significant lowering of 

ROG emissions for pesticides with default emission values. The average 2003 TOG and 

ROG emissions from all agricultural and structural pesticides were 55 percent lower in 

2003 than in 1995. The most significant reduction was in the structural methyl bromide 

category, likely due the Montreal Protocol, which mandates the phase-out of methyl 

bromide. 

 Waste Burning 

Emissions result from the waste burning of agricultural residues, weed abatement, 

range improvement, and other materials. Although this is a district-reported category, 

ARB has developed default 2002 emission estimates for several districts that have not 

provided updates in recent years. Updated emissions data have been developed for 

the following areas: South Coast Air Basin, Mojave Desert Air Basin, San Diego Air 

Basin, Salton Sea Air Basin, Amador County, and Western Nevada County. There 

have been no changes to the underlying methodology for calculating emissions. The 

emissions are based on district-reported burning activity. Emission factors and fuel 

loading values have been expanded to include more specific crop types. 
May 7, 2007 Appendix F 13 

 Wildland Fire Use (WFU) 

A WFU is a naturally ignited lightning fire that is managed for resources benefit. The 

WFU emission inventory category was created in 2004, and inventory back-populated to 

1994 where data were available. WFU emissions are calculated using the Geographic 

Information System (GIS) based Emission Estimating System model developed for ARB 

by UC Berkeley’s Center for the Assessment and Monitoring of Forest and 

Environmental Resources laboratory. 

 Wineries 

This is a newly updated methodology for wine fermentation emissions. The emission 

factors for wine fermentation have not been updated from the older methodology, but 

the source of wine fermentation activity has been updated. The Tax and Trade Bureau 

(TTB) is now the source of estimates for amounts of wine fermented in the state. 

Temporal data gained from the TTB records allow us to give detailed monthly breakouts 

of wine fermentation in the state. 

Mobile 

ARB is continually improving EMFAC and OFFROAD, and emission inventory elements 

as represented in each model. The following discussion includes evolution of EMFAC 

and OFFROAD, inventory verification, and improvements made for EMFAC2007 and 

the SIP. 

On-road 

The following are modifications to the model and the inventory since the last SP. For a 

more thorough technical explanation please refer to the tech memos at 

http://www.arb.ca.gov/msei/msei.htm, and 

http://www.arb.ca.gov/msei/onroad/previous_version.htm. The changes below are 

those changes reflected in EMFAC2007 that have occurred since EMFAC2002. 

 Revisions to the Methodology used to Characterize the On-road Vehicle Fleet 

Vehicle population data by class, age and geographic area used in EMFAC are based 

on the Vehicle Registration Database maintained by the California Department of Motor 

Vehicles (DMV). EMFAC back-casts historic changes in vehicle population using the 

oldest DMV data available, and forecasts from the most recent. As new data are 

received, projections are replaced with actual data. EMFAC2007 population estimates 

were updated based on 2000-2005 data. 

 Modification of Mileage Accrual Rates 

Previous mileage accrual rates were based on Smog Check data acquired from 1991-

1995. To more accurately model vehicle miles traveled, the new model incorporates 

data from Bureau of Automotive Repair (BAR) 2001-2003 for the following gasoline 

powered vehicle classes: passenger cars, light-duty trucks (Tiers 1 and 2), mediumduty trucks, light heavy-duty trucks (Tier 4 and 5), and motor homes. 
May 7, 2007 Appendix F 14 

 Updating Vehicle Miles Traveled and Speed Distributions 

Vehicle miles traveled and speed distributions were submitted by transportation 

planning agencies for the South Coast, the San Francisco Bay Area, and San Diego 

and Santa Barbara Counties and used to update EMFAC. 

 Modifications to the Inspection Maintenance Programs 

Modifications were made to reflect the changes in inspection and maintenance (I&M) 

programs for areas that upgraded to the enhanced Accelerated Simulation Mode 

program and change-of-ownership exemptions. 

 Ethanol Permeation 

In the prior EMFAC, evaporative emissions were correlated to oxygen content. 

Evaporative emissions from methyl-tert-butyl ether (MTBE) and ethanol (EtOH) were 

assumed to be similar since both contained two percent oxygen. Because recently 

completed studies indicate that EtOH has much higher permeation rates through fuel 

tank walls, hoses and fittings, EMFAC was modified to reflect these findings. 

 Revision of Heavy Heavy-Duty Diesel Truck Emission Factors and Speed 

Correction Factors 

New chassis dynamometer testing data developed through the CRC E55-59 program 

were analyzed and integrated into EMFAC. Emission factors for this category reflect all 

available data from CRC as well as other data sets. These data were used to develop 

new emission factors and speed correction factors. New tampering, mal-maintenance 

and malfunction survey data were used to update deterioration rates, demonstrating 

that heavy heavy-duty diesel truck emissions are greater than previously estimated. 

Trucks were for the first time tested over an ARB-developed heavy-heavy-duty test 

cycle, generating idle emissions data covering a wide span of model years as well as 

emission data at several different speeds and idle. These new data have been adopted 

by ARB and used to generate new emission factors and new speed correction factors. 

 Redistribution of Heavy Heavy-Duty Diesel Truck Vehicle Miles Traveled in 

California 

Vehicle miles traveled estimates are provided by the transportation planning agencies, 

but ARB is responsible for the distribution of that VMT by vehicle class and region. 

Heavy duty diesel truck VMT in EMFAC2002 was allocated based on truck registration. 

This method is appropriate for light duty vehicles and heavy duty gasoline trucks, but 

heavy heavy-duty diesel trucks travel extensively outside their registration counties. 

VMT was redistributed in EMFAC2007 using survey information from the California 

Department of Transportation (CalTrans) and modeled from MVSTAFF, an annual 

report by CalTrans. The new distribution more accurately reflects actual truck travel 

patterns in California. 

 Revised Break Wear PM Emission Factors 

EMFAC has been modified to account for true brake counts. Previously a single 

emission factor for brake wear, based on a 1983 study,8

 was used to calculate the 

amount of airborne dust attributable to break wear (12.8 mg/mile). This emission factor 
May 7, 2007 Appendix F 15 

assumed that all vehicles were equipped with four brakes, even if the vehicle had more 

than four brakes. 

 On-road Fuel Correction Factors 

Fuel correction factors are used to reflect the impact on emissions of commercial fuels 

compared to the fuel used during the certification process. Modifications to the fuel 

correction factors (FCFs) were incorporated into EMFAC2007 for both diesel and 

gasoline. For example, the FCFs for Phase II reformulated gasoline (RFG) were 

modified for the 1996-2003 calendar years to be cumulative to the Phase I (1992-1995 

calendar years) values. Additionally, the impacts of ethanol on evaporative processes, 

changes in sulfur and aromatics composition in fuel, exhaust hydrocarbon benefits for 

clean diesel, and an out-of-state diesel fueling rate of 10 percent were incorporated. 

 Revised Planning Humidity Profiles 

Meteorological conditions impact the emissions process in vehicles, therefore, 

EMFAC2007 incorporates ambient relative humidity profiles to determine NOx

conversion in exhaust as well as air conditioner usage by automobile drivers. 

Previously, EMFAC used annual average daily relative humidity profiles for each county 

or geographical area in the State. EMFAC2007 now incorporates hour-by-hour 

temperature, relative humidity, and ozone concentration data from 700 stations for the 

years 1996-2004. 

 Revised Planning Temperature Profiles 

EMFAC2007 contains daily ambient temperature profiles for use in evaluating 

evaporative emissions and other heating/cooling related processes. In the previous 

EMFAC, hourly temperature observations collected on high ozone days were spatially 

distributed by zip code and weighted by population. The resulting weighted profiles 

seemed rather cool. Weighting in EMFAC2007 is done by vehicle miles traveled (VMT) 

and provides more representative temperature profiles. 

 Corrections to Heavy-duty Gas Cap Benefits 

In reviewing the gas cap benefits staff noticed reductions on hydrocarbon emissions 

were negligible for heavy duty gasoline vehicles. Further review revealed the gas cap 

benefits were not fully implemented in EMFAC. In EMFAC2007, the gas cap algorithm 

has been implemented for heavy duty vehicles. 

 Coding Corrections 

Several coding errors have been corrected which results in a minor change to 

emissions estimates. 

Other Mobile

The following measures are reflected in OFFROAD2007 or the external modules. For a 

more thorough discussion on improvements to the other mobile inventory, please refer 

to the tech memos at http://www.arb.ca.gov/msei/msei.htm. 
May 7, 2007 Appendix F 16 

 Addition of Tier 4 Emission Factors to Off-Road Large Compression Ignition 

Engines (>25 hp) 

The previous OFFROAD model only provided emission factors based on Tier 0, 1, 2 

and 3 emission standards for compression-ignited engines greater than 25 horsepower 

(hp). In 2003, Tier 4 emission standards were adopted by ARB and the OFFROAD 

model has been updated to incorporate these new standards. 

 Off-road exhaust emissions inventory fuel correction factors 

Fuel correction factors have been modified to be consistent with EMFAC and to take 

into account current reformulated gasoline impacts. Carbon monoxide fuel correction 

factors for summertime and wintertime fuel which vary geographically, and the benefits 

of ultra low sulfur diesel (requirement commencing in 2007) were applied. 

 Addendum to Evaporative Emissions 

The current version of the OFFROAD model includes an updated estimate of the 

evaporative emissions from large spark-ignited engines, including those used in 

recreational marine applications. 

 Revisions to the Diesel Transport Refrigeration Units (TRU) Off-road Inventory 

TRU emissions are calculated in the OFFROAD model as a function of emission rate, 

population, activity, average horsepower, and load factor. With the exception of the 

emission rates, all other factors were based on the 1997 Power Systems Research 

(PSR) report. Since late 2002, ARB has obtained more up-to-date population and 

activity estimates from surveys of TRU manufacturers. These results have revised the 

input factors of population, activity, load factor, average horsepower, growth factors, 

survival rates, and useful lifetime estimates to the OFFROAD model. 

 Estimation of the Impact of Ethanol on Off-Road Evaporative Emissions 

Since the phase out of methyl-tert-butyl ether (MTBE) as a gasoline additive in 2004 

ethanol (EtOH) has been used as an additive to meet the required two percent oxygen 

content in commercially dispensed gasoline. Because MTBE and EtOH both contained 

two percent oxygen, their evaporative emissions were assumed to be similar. However, 

recently completed studies indicate this is not a correct assumption. These tests 

indicate that EtOH has much higher permeation rates through fuel tank walls, hoses and 

fittings. OFFROAD2007 reflects these findings. 

 Recreational Marine 

Growth factors and engine-to-boat ratios were updated with more recent DMV and 

National Marine Manufacturers Association (NMMA) data. Additionally, evaporative 

emissions are separated into operating and storage emissions. 

 Agricultural 

Based on findings from the Agricultural Advisory Committee, growth factors for the 

San Joaquin Valley were updated. 
May 7, 2007 Appendix F 17 

 Recreational Vehicles 

The OFFROAD model has been modified to account for updated population for MC, All 

Terrain Vehicles (ATVs) and snowmobiles using Department of Motor Vehicles (DMV) 

calendar year 1991-2005 totals. Human population data from Census 2000, personal 

income, and median household income data from Department of Finance were also 

applied to develop the growth rate for recreational vehicles. DMV 2005 registration data 

has been used to update county allocation factors. In addition, DMV registration also 

shows the inactive population for MC, ATV and snowmobile. Thus, the diurnal and 

resting emissions for inactive population for these three equipments are included in the 

OFFROAD2007. Also, the activity and load factor for snowmobile were updated to be 

the same as U.S. EPA’s NONROAD model. Activity results from U.S. EPA’s 

NONROAD model for specialty vehicles, benefits of golf carts and specialty vehicles 

subject to small off-road engine and large spark ignition (LSI) controls, benefits of 

snowmobiles subject to the U.S. EPA’s capping standard, and the addition of OFMC 

and ATV evaporative emission factors as grams per mile were calculated in 

OFFROAD2007. 

Although the overall statewide emissions from recreational vehicle are the same, the 

distribution of emissions to the specific county/air basin/air district has been changed 

relative the location where the equipment is stored or operated. The storage allocation 

is relevant to the diurnal and resting emissions from active and inactive recreational 

vehicles and is based on the county of DMV registration. The operational allocation 

applies to exhaust, hot soak and running loss emissions and represents where the 

off-road trails are located. 

 Construction and Ground Service Equipment (D> 25 horsepower) 

The OFFROAD model was updated with population, useful life, age distribution, annual 

activity, growth data and a deterioration rate cap introduced based on the 2003 McKay 

& Co. Study, ARB’s 2005 Off-Road Diesel In-Use Equipment Survey, ARB’s 2006 OffRoad Diesel In-Use Mini Survey, 2003 TIAX Survey of Public Fleets, and input from 

industry and stakeholders in public workgroup meetings and workshops. 

 Small Off-Road Equipment (SORE) 

The OFFROAD model was updated with: new exhaust and evaporative standards; new 

population and activity estimates for residential lawn and garden equipment obtained 

from the Lawn and Garden Survey; new population estimates for commercial lawn and 

garden equipment from an ERG survey; and modified small off-road engine survival rate 

curves using information from the Outdoor Power Equipment Institute. 

The following changes were made to external modules: 

 Changes to the Locomotive Inventory 

Locomotive growth factors were revised in the OFFROAD model based on new data 

that better reflected locomotive operations, including projected growth in intermodal 

freight traffic, both domestic and international, U.S. industrial production, and various 

railroad statistics available from the Association of American Railroads (AAR). Other 
May 7, 2007 Appendix F 18 

measures such as the 1998 South Coast and 2005 State memorandum of 

understanding were also reflected. 

 Cargo Handling Equipment 

A separate methodology for cargo handling equipment at the ports and inter-modal rail 

yards per the Cargo Handling Equipment Air Toxic Control Measure (December 2005) 

was incorporated. 

 Ocean Going Vessels 

The OGV inventory reflects updated population and activity data for ocean-going 

vessels statewide. The emission estimates were developed for main and auxiliary 

engines in eight vessel types (auto carrier, bulk cargo, container, general cargo, 

passenger, reefer, roll-on roll-off and tankers). In addition, methodology was developed 

to allocate statewide emissions to individual ports and districts. The ARB regulation 

requiring vessels with auxiliary engines to switch from heavy fuel oil to marine distillate 

within 24 nautical miles of California was incorporated into the inventory. 

 Commercial Harbor Craft 

The commercial harbor craft inventory was revised with a single statewide approach. 

OFFROAD emission factors were used to calculate emissions and adjusted to better 

reflect the “E3” test cycle which is more representative of marine engines. 

 Portable Fuel Containers/Gas Cans

Emission estimates were developed from data such as percentage of 

household/businesses with cans, average cans per household/business, average 

volume of cans, and refill frequencies collected during two surveys in 1998 and 2004. 

Allocation factors and growth rates for residential gas cans are based on the 

Department of Finance's Census 2000 data and landscaping employment growth 

projected by EDD (California Employment Development Department). 

Biogenic 

After its original application to the Southern California Ozone Study domain, the 

biogenic emission inventory GIS (BEIGIS) model was expanded to the Central 

California Ozone Study/California Regional Particulate Air Quality Study domain. In 

order to represent central and northern California conditions during summer and winter 

seasons, the BEIGIS model has incorporated further inputs, such as crop Geographic 

Information System (GIS) data for central and northern California developed by the 

California Department of Water Resources (DWR). Because it is a statewide land 

use/land cover database, the Gap Analysis Program (GAP) is still used to represent 

natural areas in the model. Urban vegetation survey data for Fresno, Oakland, and 

Sacramento were compiled from several studies and used to develop urban land use 

biogenic volatile organic compounds (BVOC) inputs for other urban areas in the central 

and northern California portion of the model. Crop BVOC and leaf mass factors for 

additional crops listed in DWR crop GIS databases were compiled from literature. Crop 

calendars developed by the University of California-Davis Department of Agricultural 
May 7, 2007 Appendix F 19 

and Resource Economics were consulted in order to develop growing season and 

dormant season crop BVOC inputs. In-leaf and off-leaf season BVOC profiles were 

also developed for natural and urban areas, in order to account for the presence of 

deciduous and evergreen species in landscapes. A 1 km2

 resolution winter Leaf Area 

Index (LAI) raster derived from Advanced Very High Resolution Radiometer (AVHRR) 

satellite data9

 was used in order to account for winter dormancy in natural areas and 

croplands. 

3. Emissions Estimation Methods and Documentation 

Major NOx/ROG Categories

Mobile sources account for about 75 percent of ozone precursor emissions (ROG and 

NOx) in the State in 2006 and will continue to dominate the inventory in 2020, however 

total emissions from all sources will drop 28 percent from 5,924 tons/day to 4,237 

tons/day. 

Stationary

14%

Area-Wide

13%

Mobile

73%

2006 Stationary

21%

Area-Wide

19%

Mobile

60%

2020

Emissions Inventory for ROG and NOx by Category Statewide 2005 and 2020 

Emissions Estimation Methods 

Stationary Emissions 

Stationary emission sources identified on an individual basis or a single source are 

called point sources. Emissions from point sources are estimated from facilities that 

emit more than ten tons per year of any criteria pollutant. They are identified by name 

and location. A facility may have many individual, identifiable sources of emissions or 

(points) of emissions. For example, a coffee processing facility may have a boiler, 

roaster, grinder, and packing station as emission points. In addition, a point source may 

have one or more processes or operation. For example, a boiler burning natural gas 

part-time and oil part-time is considered to have two processes because emission rates 

are different for the two fuels. 
May 7, 2007 Appendix F 20 

The emissions for each point are computed as the product of use factor (an indicator of 

the extent of the activity per unit time) and an emission factor (the quantity of pollutant 

emitted per unit of the use factor). Point source use factors usually relate to a process 

rate, such as the amount of fuel oil consumed in a boiler or the amount of asphalt 

concrete produced at a batch plant. The general equation used to calculate the 

emissions is shown below: 

EMS =PR x EF x CONV 

Where: EMS = Emissions (tons/year) 

 PR = Process Rate or activity data in (SCC unit/year) 

 EF = Emission factor (mass/SCC unit) 

 CONV = Unit conversion factor 

Emission factors are derived from tests that relate emissions to the process causing the 

emissions. When adequate source test data are available for a source, these data are 

used to derive emission factors for the emission calculations. When adequate source 

test data for a source are not available, an alternative is to use average emission factors 

for similar emitting sources. These factors are usually derived by averaging the results 

of many tests of similar sources. Such factors are published by federal U.S. EPA in 

Compilation of Air Pollutant Emission Factors. The published emission factors in AP-42 

are usually calculated for devices without control equipment. Because controls may 

very among different facilities, it is therefore necessary to adjust the emissions factors to 

account for the specific control equipment being used. 

In the base year emission inventory, controlled emissions are estimated by applying 

control efficiency factors to the “uncontrolled” emissions. These base year control 

factors take into account operational upsets and equipment malfunctions that lead to 

excess emissions. The resulting “controlled” inventory represents the actual emissions 

that have occurred over the 365 day calendar year. Due to the wide variation in how 

districts account for these operational fluctuations, rule effectiveness is not accounted 

for as an explicit reporting variable in CEIDARS, rather, rule effectiveness is treated as 

an implied variable maintained by the districts as part of the actual “controlled” emission 

estimates that are submitted to ARB. 

In some cases, it is possible to determine emissions using a materials balance which 

reconciles the amounts of materials that enter and leave a process. This method is 

used for many sources, such as painting processes, where it is assumed that all the 

solvent used in the coating eventually evaporates. 

The source information along with activity data and emission factors used to calculate 

emissions for all point sources are kept in district’s files and are reported to ARB on a 

regular basis (generally once a year). 
May 7, 2007 Appendix F 21 

Data Acquisition

Information on emissions from stationary sources is obtained primarily from the districts 

which have primary responsibility under state law (Health and Safety Code section 

40000) for regulation of stationary sources of air pollution. 

In developing the emission inventory, there is considerable interaction between ARB 

and the districts. The planning process for an inventory development starts with the 

assessment of needs and requirements. Following the initial inventory planning, ARB 

collaborates with districts to prepare inventory development schedules and updates to 

the inventory. 

Area-wide Emissions 

Area source methodologies are used to calculate emissions from aggregated point 

sources and area-wide sources. Aggregated point sources are many small point 

sources, or facilities, that are not inventoried individually but are estimated as a group 

and reported as a single source category. Examples include gas stations and dry 

cleaners. Because many of these sources are already accounted for as facilities or 

point sources (see the previous section on Stationary Emissions), the area source 

emissions are reconciled with point emissions before being added to the emission 

inventory. For example, the area source methodology for dry cleaners is used to 

calculate the total emissions for a particular county. These area source emissions are 

then reconciled by subtracting the emissions for dry cleaners already accounted for in 

the point source inventory. 

Area-wide sources include source categories associated with human activity and 

emissions take place over a wide geographic area. Consumer products and unpaved 

road dust are examples of area-wide sources. 

Both ARB and districts share responsibility in updating the various area-wide source 

categories. Some categories are the responsibility of the district while other categories 

are ARB’s responsibility. ARB methodologies and many of the districts methodologies 

can be accessed at http://www.arb.ca.gov/ei/areasrc/index0.htm. 

Data Acquisition

When ARB develops an area-wide source methodology, many possible sources of 

activity data and emission factors are considered. Often data are obtained during the 

development of regulations. For example, in developing consumer product regulations, 

ARB routinely conducts statewide surveys. Research studies, some of which are 

sponsored by ARB, are another source of emissions data. Finally, various state and 

federal agencies may have relevant data needed to estimate emissions. 

If activity data are not available at the county level, then statewide emissions are 

apportioned to counties using a surrogate. In the case of consumer products, statewide 

emissions are apportioned to counties using population. 
May 7, 2007 Appendix F 22 

Once ARB has developed a draft methodology, it is submitted to Emission Inventory 

Technical Advisory Committee (EITAC) for review. EITAC is composed of emission 

inventory staff from the districts, ARB, and U.S. EPA. Following EITAC review and 

incorporation of recommended changes, the methodology becomes final and, where 

appropriate, emissions are reconciled with the point source inventory. Finally, process 

rate and emissions transaction format files are prepared and the CEIDARS database is 

updated. 

The districts also provide updated emissions data to ARB. Process rate and emissions 

transaction format files provided by the districts are used to update the CEIDARS 

database. When they are provided, the methodologies developed by districts are 

reviewed by ARB. 

CEFS Forecasting Algorithm (Used for Stationary, Area-wide, Aircraft, and Ships) 

The general forecasting equation for stationary sources is shown below. The CEFS 

processor calculates seasonal projections for planning and month/day specific 

projections for photochemical modeling inputs. CEFS employs a region and emission 

category selection hierarchy when selecting and applying growth and control factors. 

Consider, for example, a rule which applies to the entire universe of a particular process 

type (identified by source classification code (SCC)). If that rule is more stringent for a 

particular industry (identified by SIC), then a control profile specific to the SCC/SIC 

combination can be assigned. CEFS will cycle through the control data records 

applying the highest level of the selection hierarchy to that category (i.e. the growth and 

control data can be “layered” to target the source categories exactly as the rule calls for 

without double-counting (or overlaps). The same type of logic is used for the growth 

data. 

E _ fy E _by TF FRAC GF [CF CF ... CF ] ( r,s,p,y ) ( r,s,p,o ) ( r,s ) ( r,s,p,y ) ( r,s ) ( r,m ,s,p ) ( r,m ,s,p ) ( r,m ,s,p ) i = ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ 1 2

where 

 Primary Variables: 

 E_fy = Emissions in the future year (tons/day; annual average or seasonal) 

 E_by = Emissions in the base year (tons/year) 

 TF = Temporal Factor (or “Seasonal Adjustment Factor”) 

 FRAC = ROG, VOC, PM10 , or PM2.5 fraction (if applicable) 

 GF = Growth Factor (is the ratio of two activity levels at the end-point years) 

 CF = Control Factor (is the ratio of two control levels at the end-point years) 

 

Subscript Variables: 

 r = region (district, air basin, county) 

s = the source category (SCC/SIC or EIC for the TREND algorithm; The GIS 

 algorithm performs the projections at the facility level.) 

 p = the pollutant 

 m = the control measure (i = the ith control measure) 

 y = the year to be projected 

 o = the base year 
May 7, 2007 Appendix F 23 

Temporal Factors (Stationary and Area Sources Only) 

To better characterize emissions affected by seasons, seasonal adjustment factors (or 

“temporal factors”) are used to apportion emissions into the periods under 

consideration. The temporal algorithm used for calculating seasonal emission 

inventories was rewritten to better approximate the seasonal variation of emissions. In 

the prior algorithm used in the 1994 SIP, emission estimates for point sources

represented an “average annual operating day”. The assessment of this algorithm 

showed that it did not accurately estimate seasonal emissions because the algorithm 

was driven by the number of operating days a point source process operates. For 

processes that operated intermittently, this resulted in exaggerated seasonal emission 

estimates because the algorithm assumed that all intermittent processes operated 

simultaneously. For area sources, the prior algorithm estimated emissions based on an 

“average seasonal operating day”. 

ROG, VOC, PM10 and PM2.5 Fractions 

The reactive portion of the total organic gas (TOG) emissions (expressed as ROG) are 

calculated by applying reactive fractions which are maintained in CEIDARS. Districts 

may supply fractions at the facility/device/process level for point source processes. If 

these data are not provided at this level, default fractions maintained by ARB at the 

SCC level are invoked. In like manner, the portion of PM falling within the 10 micron 

and 2.5 micron size ranges (i.e. PM10 and PM2.5 respectively) are estimated from 

district-supplied fractions or by applying size fractions maintained by ARB in CEIDARS. 

As with the temporal factor, an emission-weighted fraction is developed for each 

SCC/SIC pair. 

Growth Factors (Stationary and Area Sources Only) 

Growth factors are derived from county-specific economic activity profiles, population 

forecasts, and other socio/demographic activity. Growth profiles are typically 

associated with the type of industry and secondarily to the type of emission process. 

For point sources, economic output profiles by industrial sector are typically linked to the 

emission sources via SIC. For area sources, other growth parameters such as 

population, dwelling units, fuel usage etc. may be used. The growth factor is the ratio of 

the growth level in the future year to the growth level in the base year. These growth 

levels are also region and source category dependent. 

Data Acquisition

Growth factor data for use in CEFS are acquired from the districts, and where no data 

are available, growth activity projections are constructed from ARB contracts10 with 

experts in the economic and demographic growth. ARB may also develop growth 

estimates in consultation with stakeholders. For example, ARB led an effort to revise 

growth assumptions in agricultural categories, under guidance of the State’s Agricultural 

Advisory Committee. Geographically speaking, much of the State relies on these 

constructed growth projections while other high emission regions, such as the South 

Coast and Bay Area, submit their own growth estimates based on data provided by 
May 7, 2007 Appendix F 24 

local councils of government (COGs). The varied sources of growth data are 

assembled into a comprehensive statewide growth data set that can be used for 

statewide emission projections. 

Control Factors 

Control factors are derived from “adopted” ARB regulations, district rules, and 

“proposed” measures which impose emission reductions or a technological change on a 

particular emission process. Control factors comprise three components: Control 

Efficiency, Rule Effectiveness, and Rule Penetration. Control factors are closely linked 

to the type of emission process and secondarily to the type of industry. Control levels 

are assigned to emission categories which are targeted by the rules via emission 

inventory codes (SCC/SIC, EIC etc.) used in CEIDARS. The control factor is the ratio of 

the control level in the future year to the control level in the base year. These control 

levels are also region, control measure, source category, and pollutant dependent. 

Data Acquisition 

The baseline emission projections require a full complement of control factor data that 

account for the “adopted” rules that are on the books by a predetermined cutoff date. A 

major component of the CEFS program is its ability to link rules to targeted emission 

categories and quantify the emission reductions associated with the rules. 

Implementation of CEFS requires districts to submit local control rule profiles (for all 

rules leading to emission reductions) that link the rules to the appropriate emission 

categories. The profiles must describe the behavior of the rule (i.e. whether the rule is 

phased in a linear fashion or abrupt implementation in the form of a step function). The 

rule profiles must be designed to be pollutant specific and must carry enough data 

points to adequately characterize the rule over the implementation period. The CEFS 

program interpolates the profile for intermediate years in either a step or linear mode 

depending on what the district has flagged for the rule. The construction of a 

comprehensive control rule data set for a large district is a sizeable undertaking. Some 

districts develop the control profiles in house, while others have opted to contract the 

work out. In either case, ARB staff work closely with the district staff and/or contractors 

to educate staff on the proper construction of the control profiles. In gearing up for the 

8-Hour Ozone SIP, in Fall 2004, ARB conducted a special forecasting workshop to 

provide guidance to districts on all aspects of the emission forecasting program 

including presentations on forecasting logic and input data requirements. In most 

cases, districts responded by submitting rule-specific control profiles for their adopted 

rules as required. 

ARB also develops control profiles for state rules and International Maritime 

Organizations (IMOs) such as for consumer products, pesticides, architectural coatings, 

and ships. For state rules, ARB deploys interdivisional teams to develop, refine, and 

finalize the control profiles to be used in SIP projections. Similar data requirements 

exist for the development of these control profiles as described above for district rules. 
May 7, 2007 Appendix F 25 

Mobile Sources 

Mobile sources include all non-stationary sources of 

air pollution such as cars, trucks, motorcycles, buses, 

airplanes, and locomotives. In general, emissions are 

calculated as the product of the number of sources 

 population/volume), activity and emission factor. 

E = Pop * A * EF 

where, 

E = pollutant specific emissions [mass emitted per unit 

time] 

Pop = population of on-road mobile sources [-] 

A = activity (travel data) [e.g. miles traveled per day, or hours operational] 

EF = source specific emission factor [mass per unit activity] 

In California, most mobile source inventories are estimated by two mathematical 

modeling tools: EMFAC for on-road sources and OFFROAD for off-road sources. 

Because many different types of data are necessary to develop an inventory, ARB must 

rely on other organizations to provide that data. The inventory has involved the efforts 

of the California Air Pollution Control Officers Association, CalTrans, the Southern 

California Council of Governments (SCAG), and the DMV. CalTrans provides SCAG 

with information regarding highway projects so that they can estimate and project 

vehicle miles traveled (VMT) from their Travel Demand Model (TDM). This activity data 

are then coupled with the emission factors generated from ARB’s Emission Factor 

Model (EMFAC2007) and population data provided by the DMV to calculate the 

emission inventory. Finally, all statewide emission inventories are assembled and 

maintained by ARB in the CEIDARS and CEFS databases. 

On-Road Emission Inventory 

EMFAC contains several different modules that account for different portions of the onroad inventory calculation process. EMFAC covers on-road mobile sources including 

gas and diesel cars, trucks, buses, and motorcycles. The subsequent sections illustrate 

the methods by which the on-road emission inventory is developed. For more detailed 

information please refer to the ARB website at http://www.arb.ca.gov/msei/onroad/onroad.htm. A guide to online documentation is also provided at the end of this section. 

Source Categories 

On-road mobile sources are categorized into thirteen vehicle classes, two fuel types 

(gas and diesel), and three technology categories (catalyst, noncatalyst and diesel) as 

indicated in the table below. 
May 7, 2007 Appendix F 26 

EMFAC Vehicle Categories 

Class Description Weight (GVW) Abbreviation Technology Group 

PC Light Duty Autos (Passenger Cars) All LDA NCAT, CAT, DSL 

T1 Light-Duty Trucks (LDT1) 0-3,750 LDT1 NCAT, CAT, DSL 

T2 Light-Duty Trucks (LDT2) 3,751-5,750 LDT2 NCAT, CAT, DSL 

T3 Medium-Duty Trucks 5,751-8,500 MDV NCAT, CAT, DSL 

T4 Light-Heavy Duty Trucks (LHDV1) 8,501-10,000 LHDT1 NCAT, CAT, DSL 

T5 Light-Heavy Duty Trucks (LHDV2) 10,001-14,000 LHDT2 NCAT, CAT, DSL 

T6 Medium-Heavy Duty Trucks (MHDV) 14,001-33,000 MHDT NCAT, CAT, DSL 

T7 Heavy-Heavy Duty Trucks (HHDV) 33,001+ HHDT NCAT, CAT, DSL 

UB Urban Bus (UB) All UB CAT, DSL 

OB Other Bus OBUS CAT, DSL 

SB School Buses All SBUS CAT, DSL 

MH Motor Homes All MH CAT, DSL 

MC Motorcycles All MCY NCAT, CAT 

Population and Activity

In general, population data are obtained from vehicle registration data compiled by DMV 

and classified according to fuel, class, technology group, age (model year) and 

geographic area. Further calculations require data on population growth rates by 

calendar year, vehicle class, fuel type and geographic area. These estimates are 

coupled with activity data and emission factors, as indicated previously, to estimate total 

emissions. 

On-road activity refers most commonly to vehicle miles traveled, speed, and number of 

trips for each vehicle type and model year. 

Vehicle Miles Traveled 

Vehicle miles traveled (VMT) are the number of 

miles traveled by a given vehicle in a specified 

time period and is estimated from the inspection 

and maintenance program (I&M) where the model 

year and odometer reading is taken. The COG’s 

provide VMT as estimated by their transportation 

demand models. EMFAC then matches VMT 

estimated in the model to those values provided by 

the COGs. 
May 7, 2007 Appendix F 27 

This analysis is completed for each county and helps to elucidate regional differences in 

travel. VMT is calculated based on the vehicle population and accrual rates by age, 

vehicle class, fuel type, by geographic and inspection and maintenance option. The 

model also contains hourly distributions of VMT by class. 

Vehicle Starts or Trips 

Vehicle starts are obtained for gasoline-powered vehicles except heavy-duty trucks and 

included as an input to the inventory. Starts are used to calculate trip emissions and 

calculated as the product of a per-vehicle start rate (starts per vehicle per day) and the 

fleet population. The estimates of trips per day are based on travel surveys and vehicle 

instrumented data for passenger cars, and light and medium duty trucks. 

Ambient Temperatures 

Because motor vehicle emissions are dependent on temperature and humidity profiles, 

historical meteorological data are compiled. The emission inventory process includes 

data on averaged monthly, summer and winter episodic diurnal temperatures for each 

geographic area as well as averaged monthly relative humidity for each geographic 

area. The following table indicates the primary data sources for activity and population: 

Emission Factors

Emission factor used in EMFAC are based on emission tests with dynamometers 

coupled with certification data yield base emission rates (BERs) that are adjusted with 

correction factors, and vehicle inspection and maintenance (I&M) programs (e.g. smog 

check scenarios). Correction factors are applied for non-standard operating conditions 

such as what mode the vehicle is in (e.g. hot/cold/start/running), trip speed, 

environmental conditions, and inspection and maintenance programs within that 

geographic area. These correction factors include, but are not limited to, speed 

correction factors, temperature correction factors, fuel correction factors and driving 

cycle correction factors. Emission factors are 

provided for different temperatures, operating 

speeds, emission modes, model types, model 

years, technology types, fuel, and relative 

humidity. These emission factors can be 

expressed as grams per vehicle, grams per 

mile, grams/hour and grams per start. Activity 

data are matched to the corresponding 

emission factor to estimate total emissions. 

EMFAC includes tailpipe exhaust and 

evaporative emissions as part of the on-road 

inventory. Tailpipe exhaust emissions include 

running, idle and start exhausts. Running 

exhaust represents emissions released from the tailpipe under hot stabilized conditions, 

while idle and start exhaust, the other tailpipe emissions, include any emissions 

associated with idling and starting the vehicle. Evaporative emissions consist of hot 
May 7, 2007 Appendix F 28 

soaks, diurnals, resting losses and running losses all of which are generated by the 

evaporation of fuel from an engine. The inventory accounts for particulate matter (PM) 

associated with tire and break wear. 

Guide to Online Documentation 

“Understanding the On-Road Emissions Inventory Program” - 

http://www.arb.ca.gov/msei/onroad/on-road.htm

Mobile Source Emission Estimates - 

http://www.arb.ca.gov/msei/onroad/emfac2002_output_table.htm

Previous Model Versions and Revisions - 

http://www.arb.ca.gov/msei/onroad/previous_version.htm, 

http://www.arb.ca.gov/msei/onroad/latest_revisions.htm

EMFAC Technical Support Documentation - 

http://www.arb.ca.gov/msei/onroad/doctable_test.htm

Tech Memos - http://www.arb.ca.gov/msei/msei.htm

Other Mobile Emission Inventory 

Off-road mobile sources include off-road vehicles such as boats, outdoor recreational 

vehicles (ORV’s), industrial and construction equipment, farm equipment, lawn and 

garden equipment, ships, aircraft, and trains. OFFROAD is used to estimate emissions 

for most of these categories. Other sources such as ocean going vessels and 

commercial harbor craft are based on calculations in modules external to OFFROAD. 

Off-road emissions are calculated much in the same way as on-road emissions – the 

product of emission factor, activity, and population. The model also incorporates 

elements such as technology types, population, activity, horsepower, load factors, and 

control factors. For more detailed information please refer to the ARB website at 

http://www.arb.ca.gov/msei/offroad/off-road.htm. In addition, a guide to online 

documentation is provided at the end of this section. 

Source Categories

Off-road sources are divided up into eight major categories: aircraft, trains, ships and 

commercial boats, recreational boats, off-road recreational vehicles, off-road equipment, 

farm equipment, and fuel storage and handling. The categories are then subdivided by 

fuel type, engine type, horsepower group and preempted or non-preempted status to 

better characterize emissions, adopted and proposed control strategies, and use. 

Outlined below are a few categorical descriptions. 
May 7, 2007 Appendix F 29 

Commercial Marine Vessels 

Commercial marine vessels include ocean-going ships and harbor craft, but exclude 

recreational vessels. Ocean-going ships include international trade vessels such as 

container ships, bulk carriers, general cargo ships, tankers, and auto carriers. 

Passenger cruise ships, and some military and Coast Guard vessels, are also included 

in this category. 

The diesel engines powering the majority of oceangoing ships are referred to by U.S. 

EPA as “Category 3” engines, meaning they have a displacement greater than 30 liters 

per cylinder. These engines are available in configurations with 4 to 14 cylinders, and 

power outputs ranging from roughly 5 to 100 megawatts. 

Ocean-going ships generally run boilers and diesel generators in addition to propulsion 

engines, particularly while “hotelling” in port. Diesel generators provide electrical power 

for lights and equipment, and boilers provide steam for hot water and fuel heating. 

Most ocean-going ships run their main propulsion engines (and many newer ships also 

run their auxiliary engines) on intermediate fuel oil (IFO 180 or IFO 380). This fuel is 

also referred to as “bunker fuel,” and requires heating to reduce its viscosity to a point 

where it can be properly atomized and combusted. Bunker fuel typically contains much 

higher levels of sulfur, nitrogen, ash, and other compounds which increase exhaust 

emissions. Diesel-powered gas turbine engines and auxiliary engines on many oceangoing ships use lighter “distillate” diesel fuel (also referred to as marine gas oil), which is 

much lower in sulfur and other contaminants. 

Harbor craft (or the “captive fleet”) include tugboats, commercial fishing vessels, 

commercial passenger fishing vessels, work boats, crew boats, ferries, and some Coast 

Guard and military vessels. These vessels generally stay within California coastal 

waters and often leave and return to the same port. Most harbor craft use dieselpowered propulsion and auxiliary engines that generally run on distillate diesel fuel. 

Locomotives and Rail-yards 

Railroads operate national locomotive fleets that travel between states daily, currently 

moving more than 40 percent of the total intercity revenue ton-miles of freight in the 

United States. 

Compression-Ignition (diesel) Engines 

Off-road compression-ignition (CI) engines are diesel engines primarily used in farm, 

construction, and industrial equipment. Examples include tractors, excavators, dozers, 

scrapers, portable generators, transport refrigeration units (TRUs), irrigation pumps, 

welders, compressors, scrubbers, and sweepers. Locomotives, commercial marine 

vessels, marine engines over 37 kilowatts (kW), or recreational vehicles are excluded 

from this category. 
May 7, 2007 Appendix F 30 

Large Spark-Ignition Engines 

The large spark-ignition engine (LSI) category consists of off-road spark-ignition 

engines greater than 25 horsepower and typically fueled by gasoline or liquefied 

petroleum gas (LPG). A small number are fueled by compressed natural gas (CNG), 

and some have dual fuel capability. LSI engines are most commonly found in forklifts, 

specialty vehicles, portable generators, pumps, compressors, farm equipment, and 

construction equipment. This category excludes marine propulsion engines, engines 

used in equipment that operate on rails, recreational vehicles, snowmobiles, and gas 

turbines. 

Recreational Vehicles 

This category consists of off-road motorcycles and all terrain vehicles (ATVs), both of 

which are designed for operation over rough terrain. U.S. EPA standards for exhaust 

and evaporative for off-road motorcycles and ATVs were established in 2006. Although 

the federal exhaust standards are not as stringent as California’s, California will benefit 

from the evaporative standards which control fuel tank and fuel line permeability. 

In 1994, ARB approved off-highway recreational vehicle regulations (including off-road 

motorcycles). These regulations established exhaust emission standards and test 

procedures that included off-road motorcycles and ATVs. The regulations also provided 

specific coding requirements of the vehicle identification number to distinguish an 

emission-compliant vehicle. In 1998, the regulations were amended to link vehicle 

registration and usage to compliance with California’s exhaust emission standards. 

Those in compliance are eligible for off-highway vehicle (OHV) green sticker registration 

that allows year-round operation in designated off-road areas. Those not in compliance 

are eligible for OHV red sticker registration that allows operation only during designated 

months when ozone levels are low. These revisions affect engines built in 1997 greater 

than 90 cc. The same standards also apply to engines built in 1999 of 90 cc or less. 

Engines built pre-1997 and pre-1999, respectively, are not subject to this regulation. 

Small Off-Road Engine (SORE) 

The small off-road engine (SORE or "small engine") category consists of off-road sparkignition engines fueled typically by gasoline, liquid petroleum gas (LPG) or other 

alternative fuels and below 25 horsepower. The SORE category includes lawn, garden 

and other maintenance utility equipment. Within this category, engines are typically 

grouped by engine displacement measured in cubic centimeters (cc). Engines under 

65 cc displacement are traditionally associated with handheld equipment such as weed 

trimmers, leaf blowers and chain saws. Engines greater than 65 cc displacement are 

collectively referred to as non-handheld small off-road engines. Non-handheld 

equipment is primarily lawn mowers, but also includes other equipment such as riding 

mowers and generator sets. 

The sources of evaporative emissions from this category are from gasoline vapors 

vented from the carburetor and fuel cap and occur from diurnal (emissions due to daily 

temperature changes), hot soak (occur after shutdown of equipment), and running loss 

(occur during equipment operation) processes. Permeation (liquid gasoline migrating 

through the walls of plastic fuel tanks) is also another source of emissions. 
May 7, 2007 Appendix F 31 

Activity and Population

As with the on-road inventory, emission factors must be coupled with population and 

activity data to estimate total emissions. The statewide equipment population of offroad mobile sources was collected from a variety of sources including industry and 

government agencies. Then growth factors based on socioeconomic indicators and 

scrappage factors were applied to determine future populations. Scrappage, or attrition, 

functions describe the relationship between equipment age and the proportion of 

equipment that has been removed from service. It is expressed as a fraction of the 

average lifetime of the equipment and is a function of the expected life of the engine, 

the annual hours of operation, and the 

average load factor. 

Activity includes information such as 

annual average usage hours, load factor, 

brake-specific fuel consumption, and 

starts per year for each equipment type 

by fuel, engine type, and horsepower 

group. 

Data Acquisition

The statewide equipment populations were obtained through various industry and 

government agency sources. Power Systems Research (PSR) is the source for many 

of the state population estimates for off-road categories. PSR’s Power Systems 

Research/Compass International’s 1996 Database contained engine data compiled over 

the last 7 years, and included engine sales records for every engine installed in North 

America, as well as imported engine-driven products. Engine data includes 

horsepower, model number and engine description (number of cylinders, turbocharged 

versus naturally-aspirated, displacement, etc). Some of the principal data sources, by 

category, are listed in the table below: 

The Portable Equipment Database is maintained by ARB. Data are obtained through a 

voluntary registration program with the State as an alternate method of obtaining an 

operational permit for off-road non-propulsion engines. Equipment populations for 

dredging, oil drilling, lawn and garden, military tactical support and other portable 

equipment categories were obtained directly from the Portable Equipment Database. In 

order to avoid double counting, the population of generators, pumps and compressors 

found in the drilling, dredging, tactical support and other portable equipment, were 

subtracted from the industrial and light-commercial categories. 
May 7, 2007 Appendix F 32 

Category Data Source

Agricultural United States Department of 

Agriculture(USDA), Power Systems 

Research (PSR) 

Construction and Mining MacKay & Company, PSR, Portable 

Equipment Database, Energy & 

Environmental Analysis (EEA) 

Light Commercial PSR, Portable Equipment Database 

Industrial PSR, Booz Allen-Hamilton (BAH) 

Logging Power Systems Research 

Lawn and Garden Portable Equipment Database, BAH 

Airport Ground Support Air Transport Association (ATA), EEA 

Transport Refrigeration Units PSR, Department of Motor Vehicles (DMV) 

Dredging Portable Equipment Database 

Oil Drilling Portable Equipment Database 

Military Tactical Support Equipment Portable Equipment Database 

Recreational Equipment Department of Motor Vehicles (DMV) 

Pleasure Craft U.S. Coast Guard, DMV 

Commercial and Government Vessels BAH, US Coast Guard, CA Department of 

Fish and Game, ARB Survey 

Locomotive and Rail Operations Booz Allen-Hamilton 

Aircraft (Commercial, Military and General) Booz Allen-Hamilton 

Agricultural Aircraft Booz Allen-Hamilton 

Ocean-Going Vessels CA State Lands Commission, Port of 

Los Angeles EI, Survey, US Army Corp of 

Engineers, Entec 

Agricultural Engines District Permit Data, Carl Moyer Program, 

Sonoma Technology, CA Department of 

Water Resources Farmland Monitoring and 

Mapping Program 

MacKay & Company conducted surveys in 1991, 1995, and 1999 to estimate 

nationwide construction equipment population and usage. This work was sponsored by 

Construction Equipment Magazine. MacKay & Company’s 1999 Construction 

Equipment population analysis was used to obtain populations for those construction 

equipment contained in the analysis. Since data in MacKay’s analysis are nationwide, 

staff used a factor of 10 percent in order to estimate California’s statewide population. 

U.S. EPA staff estimated that 10 percent of the total nationwide dollar amount spent on 

construction-related activities occurs in California. For specific pieces of construction 

equipment not found in MacKay’s analysis, 10 percent of PSR’s nationwide data were 

used. 

Finally, all statewide emission inventories are assembled and maintained by ARB in 

CEIDARS and CEFS databases. 
May 7, 2007 Appendix F 33 

Emission Factors

ARB estimates all off-road mobile emissions with OFFROAD. OFFROAD integrates 

emission factors by model year for hydrocarbons (HC), carbon monoxide (CO), carbon 

dioxide (CO2), oxides of nitrogen (NOx), particulate matter (PM), and oxides of sulfur 

(SOx). Hydrocarbon emissions are modeled for three types of engine processes: 

exhaust, evaporative and start emissions. 

The emission factors for each engine are a 

function of new engine emissions expressed 

in grams per brake horsepower hour and 

deterioration rates. Deterioration is due 

primarily to tampering and mal-maintenance 

and wear on engine parts with use, and 

occurs at different rates for each pollutant. 

The OFFROAD methodology for estimating 

deterioration is based on the zero-hour 

emission rate (g/bhp-hr), the deterioration 

rate (increase in emissions per unit of 

activity, g/bhp-hr2), and the number of hours 

accumulated on the equipment. Equipmentspecific emission factors are obtained by 

adjusting the appropriate engine emission rate by how the equipment is used (duty 

cycle). Finally, control factors can be applied to emissions or population to account for 

regulatory control scenarios. 

Guide to Online Documentation 

“Understanding the Off-Road Emissions Inventory Program” - 

http://www.arb.ca.gov/msei/offroad/off-road.htm

Mobile Source Emission Estimates - 

http://www.arb.ca.gov/msei/onroad/emfac2002_output_table.htm

Model Revisions - http://www.arb.ca.gov/msei/offroad/updates.htm

OFFROAD Technical Support Documentation - http://www.arb.ca.gov/msei/offroad/pubs.htm

http://www.arb.ca.gov/research/resnotes/notes/97-8.htm 

Tech Memos - http://www.arb.ca.gov/msei/msei.htm
May 7, 2007 Appendix F 34 

Biogenics (Overview of the BEIGIS Model) 

Development of effective ozone and PM2.5 control strategies in California requires 

accurate emission inventories of their precursor emissions, including biogenic volatile 

organic compounds (BVOCs) such as isoprene and monoterpenes. Due to the 

heterogeneity of vegetation land cover, species composition and leaf mass distribution 

in California, quantifying BVOC emissions in this domain requires an emission inventory 

model with region-specific input databases and a high degree of spatial and temporal 

resolution. In response to this need, ARB developed a GIS-based model for estimating 

BVOC emissions, called BEIGIS, which uses California-specific input databases with a 

minimum spatial resolution of 1 km2 and an hourly temporal resolution. 

The BEIGIS isoprene emission algorithm11 is of the form I = IS × CL × CT , where I is 

the isoprene emission rate (grams isoprene per gram dry leaf mass per hour) at 

temperature T and photosynthetically active radiation flux PAR. IS is a reference 

emission factor (grams isoprene per gram dry leaf mass per hour) at a standard 

temperature of 30 °C and PAR flux of 1000 μmol m-2 s-1. CL and CT are environmental 

adjustment functions for PAR and temperature, respectively. The monoterpene 

emission algorithm adjusts a reference monoterpene emission factor by a temperature 

function11. Methylbutenol (MBO) emissions are modeled with an algorithm12 similar to 

that for isoprene. Dry leaf mass/ leaf area ratios, and reference emission factors for 

isoprene, monoterpenes and MBO, are plant species-specific and assembled from the 

scientific literature. Modeled BVOC emissions for a given spatial domain therefore 

represent the contribution by various plant species (through their leaf mass and 

emission rates) to the total BVOC emissions. 

The main inputs to BEIGIS are land use land cover (LULC) GIS databases, gridded leaf 

area index (LAI) derived from AVHRR satellite data13, leaf area/dry leaf mass factors, 

reference emission factors, and gridded hourly ambient temperature and sunlight data 

(generated by the CALMET and/or MM5 models). For urban areas, LULC databases 

were developed from regional planning agency data and botanical surveys14. Natural 

areas are represented using GAP, a statewide LULC database developed by the 

University of California-Santa Barbara for the U.S.G.S. Biological Resources Division 

and the California Department of Fish and Game15. Agricultural areas are represented 

using crop GIS databases developed by the California Department of Water Resources 

(http://www.landwateruse.water.ca.gov). Ground surveys have been funded by ARB to 

validate vegetation land cover and LAI input databases used in BEIGIS16. Model 

validation using micrometeorological flux measurements is on-going. BEIGIS 

assimilates spatial and temporal inputs and executes BVOC emission algorithms within 

a GIS. Outputs from BEIGIS are gridded 1 km2

 hourly emissions of isoprene, 

monoterpenes and MBO, aggregated to 16 km2 or 25 km2 resolution, depending on 

photochemical modeling requirements. A fourth BVOC category called “other” biogenic 

VOC (OVOC) is comprised of compounds such as acetone, methanol, and other 

oxygenated BVOCs. OVOC is not modeled directly. Gridded hourly OVOC emissions 

are estimated as an added fraction, scaled to 30 percent of the sum of isoprene, 

monoterpene, and MBO within each grid cell. A speciation profile is applied to the 
May 7, 2007 Appendix F 35 

OVOC fraction based on OVOCs measured at Blodgett Experimental Forest17. The 

BEIGIS model was first applied in the Southern California Ozone Study18 (SCOS97). 

Emissions Inventory Systems Data (CEIDARS, CEFS) 

ARB redesigned its base year emission inventory system (known as the California 

Emissions Inventory Development and Reporting System (CEIDARS)) in 1995 and 

emission forecasting system (known as the California Emission Forecasting System 

(CEFS)). Technical papers describing these systems are available on request. 
May 7, 2007 Appendix F 36 

 

References 

1

 “FACT SHEET #1: Development of Organic Emission Estimates California's Emission 

Inventory and Air Quality Models” (2000) [Online] Air Resources Board. Available from 

http://www.arb.ca.gov/ei/speciate/factsheets_model_ei_speciation_tog_8_00.pdf

[Accessed March 2007] 

2 2002 Base Year Emission Inventory SIP Planning: 8-hr Ozone, PM2.5 and Regional 

Haze Programs (2002) [Online] Environmental Protection Agency. Available from 

http://www.epa.gov/ttnchie1/eidocs/2002baseinven_102502new.pdf [Accessed 

February 2007] 

3

 ARB Project 05-6CCOS with Dr. Charles L. Blanchard. Understanding Relationships 

Between Changes in Ambient Ozone and Precursor Concentrations and Changes in 

VOC and NOx Emissions from 1990 to 2004 in Central California 

4

 STI - 05-3CCOS - Comparison of Ambient Measurements to Emissions 

Representations for Modeling 

5 National Emissions Inventories for the U.S. (2007) [Online] Environmental Protection 

Agency. Available from http://www.epa.gov/ttn/chief/net/index.html [Accessed February 

2007] 

6 The California Almanac of Emissions and Air Quality (2006) [Online] California Air 

Resources Board. Available from http://arb.ca.gov/aqd/almanac/almanac.htm

[Accessed February 2007] 

7 Triennial Review of the Emission Inventory SB 2174 Public Workshop November 2000 

(2000) [Online] California Air Resources Board. Available from 

http://www.arb.ca.gov/ei/sb2174slides/ [Accessed February 2007] 8

 Cha, S.; Carter, P.; Bradow, R. Simulation of Automobile Brake Wear Dynamics and 

Estimation of Emissions, Society of Automotive Engineers, SAE Paper 831036, 

Warrendale, PA, 1983. 

9

 Nikolov, N; Zeller, K. Efficient retrieval of vegetation leaf area index and canopy 

clumping factor from satellite data to support pollutant deposition assessments. 

Environmental Pollution vol 141 (3) 539-549 (2006). 

10 E. H. Pechan & Associates, Development of Emission Growth Surrogates and Activity 

Projections Used in Forecasting Point and Area Source Emissions, Final Report, 

February 26, 2001. 

11 Guenther, A. B., P. R. Zimmerman, P. C. Harley, R. K. Monson and R. Fall. 1993. 

Isoprene and monoterpene emission rate variability – model evaluations and sensitivity 

analyses. Journal of Geophysical Research. 98(D7): 12609-12617. 

Guenther, A. B. R. K. Monson and R. Fall. 1991. Isoprene and monoterpene emission 

rate variability: observations with eucalyptus and emission rate algorithm development. 

Journal of Geophysical Research. 96: 10799-10808. 

12 Harley, P., V. Fridd-Stroud, J. Greenberg, A. Guenther and P. Vasconcellos. 1996. 

Emission of 2-methyl-3-buten-2-ol by pines: A potentially large natural source of 

reactive carbon to the atmosphere. Journal of Geophysical Research. 103: 25479-

25486. 
May 7, 2007 Appendix F 37 

 13 Nikolov, N. and K. Zeller. 2006. Efficient retrieval of vegetation leaf area index and 

canopy clumping factor from satellite data to support pollutant deposition assessments. 

Environmental Pollution. Vol. 141 Issue 3: 539-549. DOI:10.1016/j.envpol.2005.08.059 

14 Benjamin, M., Sudol, M., Bloch, L. and A. Winer. 1996. Low-emitting urban forests: 

ataxonomic methodology for assigning isoprene and monoterpene emission rates. 

Atmospheric Environment. 30 (9): 1437-1452. 

Horie, Y., Sidawi, S. and R. Ellefsen. 1990. Inventory of leaf biomass and emission 

factors for vegetation in California’s south coast air basin. Final Technical Report III-C. 

South Coast Air Quality Management District. Diamond Bar, CA. 

Nowak, D. J. 1991. Urban forest development and structure: Analysis of 

Oakland,California. PhD dissertation. University of California, Berkeley, CA. 

Sidawi, S. and Y. Horie. 1992. Leaf biomass density for urban, agricultural and 

naturalvegetation in California’s San Joaquin Valley. Final Report. San Joaquin Valley 

Air Pollution Study Agency. 

15 Davis, F. W., D. M. Stoms, A. D. Hollander, K. A. Thomas, P. A. Stine, D. Odion, M. I. 

Borchert, J. H. Thorne, M. V. Gray, R. E. Walker, K. Warner, and J. Graae. 1995. The 

California GAP Analysis Project—Final Report. University of California, Santa Barbara, 

CA. [http://www.biogeog.ucsb.edu/projects/gap/gap_rep.html]

16 Karlik, J. and A. McKay. 1999. Development of methodology and databases for 

estimating leaf masses in California airsheds. Final Report. Contract No. 97-719. State 

of California Air Resources Board. Sacramento, CA. 

Karlik, J. 2002. Validation of databases for modeling biogenic volatile organic compound 

emissions in central California. Final Report. Contract No. 00-16CCOS. San 

Joaquin Valleywide Air Pollution Study Agency and California Environmental Protection 

Agency – Air Resources Board. 

Winer, A., Karlik, J. and J. Arey. 1998. Biogenic hydrocarbon inventories for California: 

generation of essential databases. Final Report. Contract No. 95-309. State of 

California Air Resources Board. Sacramento, CA. 

Winer, A. and Karlik, J. 2001. Development and validation of databases for modeling 

biogenic hydrocarbon emissions in California’s airsheds. Final Report. Contract No. 97- 

320. California Environmental Protection Agency – Air Resources Board. Sacramento, 

CA. 

17 Lamanna, M. and A. Goldstein. 1999. In situ measurements of C2-C10 volatile 

organic compounds above a Sierra Nevada ponderosa pine plantation. Journal of 

Geophysical Research. Vol. 104, No. D17: 21247-21262. 

18 Scott, K. and M. Benjamin. 2003. Development of a biogenic volatile organic 

compounds emission inventory for the SCOS97-NARSTO domain. Atmospheric 

Environment 37, Supplement No. 2: S39-S49.