2.1 On-Road Mobile Sources

Category ID	Description	EIC
2666	Heavy Heavy Duty Trucks - Biodiesel	70000000000000
2667	Light Duty Passenger - Biodiesel	70000000000000
2668	Light Duty Trucks (I) - Biodiesel	70000000000000
2669	Light Duty Trucks (II) - Biodiesel	70000000000000
2670	Light Heavy Duty Trucks (I) - Biodiesel	70000000000000
2671	Light Heavy Duty Trucks (II) - Biodiesel	70000000000000
2672	Medium Duty Trucks - Biodiesel	70000000000000
2673	Motor Homes - Biodiesel	70000000000000
2674	Medium Heavy Duty Trucks - Biodiesel	70000000000000
2675	Other Buses - Biodiesel	70000000000000
2676	School Buses - Biodiesel	70000000000000
2677	Urban Buses - Biodiesel	70000000000000
2678	Heavy Heavy Duty Trucks - Distillate	72876412107076
2679	Light Duty Passenger - Distillate	71076412100000
2680	Light Duty Trucks (I) - Distillate	72276412100000
2681	Light Duty Trucks (II) - Distillate	72376412100000
2682	Light Heavy Duty Trucks (I) - Distillate	72576412100000
2683	Light Heavy Duty Trucks (II) - Distillate	72676412100000
2684	Medium Duty Trucks - Distillate	72476412100000
2685	Motor Homes - Distillate	78076412100000
2686	Medium Heavy Duty Trucks - Distillate	72776412107051
2687	Other Buses - Distillate	77576412107202
2688	School Buses - Distillate	77576412107203
2689	Urban Buses - Distillate	77576412107204
2690	Heavy Heavy Duty Trucks - Ethanol	70000000000000
2691	Light Duty Passenger - Ethanol	70000000000000
2692	Light Duty Trucks (I) - Ethanol	70000000000000
2693	Light Duty Trucks (II) - Ethanol	70000000000000
2694	Light Heavy Duty Trucks (I) - Ethanol	70000000000000
2695	Light Heavy Duty Trucks (II) - Ethanol	70000000000000
2696	Motorcycles - Ethanol	70000000000000
2697	Medium Duty Trucks - Ethanol	70000000000000
2698	Motor Homes - Ethanol	70000000000000
2699	Medium Heavy Duty Trucks - Ethanol	70000000000000
2700	Other Buses - Ethanol	70000000000000
2701	School Buses - Ethanol	70000000000000
2702	Urban Buses - Ethanol	70000000000000
2703	Heavy Heavy Duty Trucks - Gasoline	72873411007080
2704	Light Duty Passenger - Gasoline	71073411000000
2705	Light Duty Trucks (I) - Gasoline	72273411000000
2706	Light Duty Trucks (II) - Gasoline	72373411000000
2707	Light Heavy Duty Trucks (I) - Gasoline	72573411000000
2708	Light Heavy Duty Trucks (II) - Gasoline	72673411000000
2709	Motorcycles - Gasoline	75073411000000
2710	Medium Duty Trucks - Gasoline	72473411000000
2711	Motor Homes - Gasoline	78073411000000
2712	Medium Heavy Duty Trucks - Gasoline	78073411000000
2713	Other Buses - Gasoline	77573411007200
2714	School Buses - Gasoline	77573411007203
2715	Urban Buses - Gasoline	77573411007204
2716	Heavy Heavy Duty Trucks - Natural Gas	72873401107076
2717	Medium Heavy Duty Trucks - Natural Gas	72773401107051
2718	Other Buses - Natural Gas	77573401107202
2719	School Buses - Natural Gas	77573401107203
2720	Urban Buses - Natural Gas	77573401107204
2721	Heavy Heavy Duty Trucks - Renewable Diesel	70000000000000
2722	Light Duty Passenger - Renewable Diesel	70000000000000
2723	Light Duty Trucks (I) - Renewable Diesel	70000000000000
2724	Light Duty Trucks (II) - Renewable Diesel	70000000000000
2725	Light Heavy Duty Trucks (I) - Renewable Diesel	70000000000000
2726	Light Heavy Duty Trucks (II) - Renewable Diesel	70000000000000
2727	Medium Duty Trucks - Renewable Diesel	70000000000000
2728	Motor Homes - Renewable Diesel	70000000000000
2729	Medium Heavy Duty Trucks - Renewable Diesel	70000000000000
2730	Other Buses - Renewable Diesel	70000000000000
2731	School Buses - Renewable Diesel	70000000000000
2732	Urban Buses - Renewable Diesel	70000000000000

Introduction

On-road vehicles are the largest source of GHG emissions in California, accounting for 35% of the state’s emissions in 2022 (CARB, 2024a). This document outlines the methodology for estimating greenhouse gas (GHG) emissions from the operation of on-road vehicles including passenger cars, light duty trucks (pick-ups, SUVs etc.), heavy-duty trucks (semi-trucks, utility trucks etc.), buses, motor homes and motorcycles for the nine counties that make up the San Francisco Bay Area (SFBA). The exhaust from the combustion of gasoline and diesel, typically used to power these vehicles, contains gases that are toxic to human health and GHGs like carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O).

Traditionally, GHG emissions are estimated using California Air Resources Board’s (CARB) EMission FACtor (EMFAC) model. The EMFAC model is used to prepare the criteria pollutants emissions inventories of on-road mobile sources in California to support CARB’s planning and policy development efforts and to meet the Federal Highway Administration’s (FHWA) transportation conformity requirements (CARB, 2022a). Since its initial release, CARB has improved the model through periodic releases that incorporate the latest vehicle population, activity data, and emission testing and fuel technology, as well as adopted on-road mobile source regulations. The latest version of the model, EMFAC2021 v1.0.2 (CARB, 2022b) available at the time, has been used for regional inventory development. Since then, EMFAC2025 has been released and this version or any subsequent releases will be incorporated into future inventory updates.

EMFAC2021 may be used to estimate GHG emissions by pollutant, vehicle class, fuel technology, county, and year (from 2000 and 2050). In 2006, following the adoption of Assembly Bill 1803, CARB acquired the responsibility from the California Energy Commission (CEC) to develop the statewide GHG inventory. Since 2006, CARB has developed the official annual statewide GHG emission inventory each year (per H&SC section 39607.4) to track its progress in achieving the statewide GHG targets established by California Global Warming Solutions Act (AB 32) (CARB, 2024a). The inventory, referred to as AB32 GHG Inventory, follows GHG inventory best practices consistent with the Intergovernmental Panel on Climate Change (IPCC) Guidelines for National Greenhouse Gas Inventories (“IPCC Guidelines”) (IPCC, 2006). This inventory provides the state-total GHG emissions for the On-Road Mobile Sources in its Road Transportation subsector (IPCC 1A3b) based on annual reported fuel sales from federal and state agencies, fuel consumption modeled using the latest version of EMFAC model at the time, fuel mix information collected through multiple CARB programs, and energy-based GHG emission factors. In addition, the CO₂ emissions resulting from the combustion of biofuels such as ethanol, biodiesel, renewable diesel are classified as biogenic CO₂ (CO₂_bio) (CARB, 2016; CARB, 2022c; CARB, 2022d; CARB, 2023). Biogenic CO₂ emissions from on-road mobile sources are estimated and tracked separately but not included in the regional GHG inventory totals.

Consistent with the source categorization scheme that is similar to that found in CARB’s AB32 GHG inventory, the SFBA on-road mobile source GHG emissions are reported across 67 source categories comprised of EMFAC2007 vehicle class by various fuel type, as listed in the table above.

Methodology

On-road vehicles are classified as mobile sources because they: 1) are not permanently located at a fixed site, 2) emit air pollution while in motion, 3) can travel throughout the region and outside its boundaries; and 4) are regulated by CARB, not the Air District. CARB prepares statewide inventories for mobile sources in accordance with IPCC Guidelines. However, simply proportioning the statewide inventory using county boundaries can be misleading – for example, drivers can purchase fuel in one county and consume it in another. To improve spatial accuracy, EMFAC2021 provides county-level estimates of GHG emissions by fuel blends such as gasoline (fossil gasoline and ethanol) and diesel (distillate, biodiesel, renewable diesel). While EMFAC2021 is valuable for tracking emissions by fuel blend, it does not allow the Air District to understand and track long term reductions as the state shifts to lower carbon intensity fuels.

To address these limitations, the Air District adopted a hybrid methodology for this GHG inventory update. This method aligns with the statewide AB32 GHG inventory methodology and enables estimation of county-level emissions using the following parameters:

• Fuel sales data from California Department of Tax and Fee Administration (CDTFA) and U.S. Energy Information Administration (EIA), which are used in the development of the statewide AB32 inventory, are used as the base,
• County-specific fuel consumption rates from EMFAC2021 are applied to allocate emissions spatially and to vehicle categories, and
• Compositional fraction of each fuel type in the fuel blends is used to differentiate between fossil fuels and biofuels.

Advantages of the hybrid approach include:

• Emissions are estimated based on actual fuel usage, not just modeled fuel consumption, and,
• The method provides flexibility to track emissions by fuel type, enabling better monitoring of the state’s progress in reducing carbon intensity, consistent with AB32 goals.

This approach enhances the Air District’s ability to quantify and understand GHG reductions resulting from the transition to cleaner fuels across the SFBA.

Base Year Emissions

CARB AB32 GHG inventory use two distinct methodologies depending on the pollutant. For CO₂ & CO₂-bio, emissions are estimated using the Emission Factor approach, consistent with CARB’s Mandatory Reporting of Greenhouse Gas Regulation (CARB, 2019). Because CO₂ emissions are assumed to be based on a higher heating value (HHV; described below) and complete combustion of fuel, emission factors depend solely on the fuel type. In contrast, CH₄ and N₂O emissions, which are byproducts of incomplete combustion, are estimated using the ‘Emission Scaling’ approach which scales CH₄ and N₂O emissions from EMFAC2021 model and incorporates pollutant-specific emissions factors that vary by fuel types, vehicle types, emission standards, control technologies, operation modes, weather etc. More details on the two approaches are described in the following sections.

Note that the base years cover all the years from 2000-2022, for which the actual fuel sales data from CDTFA and EIA as well as fuel consumptions data from EMFAC2021 model are available.

Emission Factor Approach (CO₂ & CO₂-bio)

Emissions _{yr, cnty, pol, cat} =

Activity Data _{yr, cnty, FT, VC} × Heat Content _FT × Emission Factor _pol × Control Factor _pol × GWP _pol

Where:

• Emissions _{yr, cnty, pol, cat}: is the annual total CO₂ equivalent (CO₂eq) emissions in a given year by county, GHG pollutant, and source category (i.e., unique combination of fuel type (FT) and vehicle class (VC)).
• Activity Data _{yr, cnty, FT, VC}: is quantity of fuel consumed in a given year by county, FT and VC.
• Heat Content _FT: is the higher heating value (HHV) of a given fuel type (Btu/unit), based on the methodology from CARB’s AB 32 GHG Inventory (2023 Edition) (CARB, 2023). HHV is used to convert fuel consumption (gallons of gasoline) to energy (Btu) which can then be multiplied against the energy-based emission factors to estimate emissions.
• Emission Factor _pol: relates to the quantity of emissions, in mass of pollutant emitted per unit of energy produced. For CO₂ and CO₂_bio, the energy-based emission factors are adopted from the methodology index of CARB’s AB 32 GHG Inventory (2023 Edition) (CARB, 2023).
• Control Factor _pol: is a fraction between 0 and 1 that estimates the reduction in emissions based on Air District rules and regulations.
• GWP_pol is the Global Warming Potential (GWP) of a particular GHG pollutant. The current version of the GHG emissions inventory incorporates the GWP values reported in the Fifth Assessment report of the Intergovernmental Panel for Climate Change (IPCC, 2014). The GWPs for the principal GHGs are 1 for CO₂ & CO₂_bio, 34 for CH₄, and 298 for N₂O, when calculated on a 100-year basis with climate-carbon feedback included.

With:

• yr: year for which the actual activity is available; 2000 – 2022 in this case.
• cnty: San Francisco Bay Area county including partial counties (Sonoma and Solano Counties) in the Air District’s jurisdiction.
• pol: GHG pollutant (CO₂ or CO₂_bio).
• cat: source category defined as the unique combination of FT and VC shown in the table in the Introduction section.
• FB: fuel blend as defined in the table below.
• FT: fuel type as defined in the table below.
• VC: EMFAC2007 vehicle classes consistent with the statewide GHG inventory categorization.

Fuel Blend (FB)	Fuel Type (FT)
Gasoline	Gasoline
	Ethanol
Diesel	Distillate
	Biodiesel
	Renewable Diesel
Natural Gas	Natural Gas

CH₄ and N₂O emissions estimates at the county-scale are directly derived from EMFAC 2021 database. The methodology is based on an emissions-apportionment technique rather than activity-based (like that of CO₂ and CO₂_bio) derivation as shown in the ‘Emissions Scaling’ subsection below.

Activity Data / Throughput

The activity data used to estimate CO₂ and CO₂_bio emissions by source category (i.e., a combination of vehicle class and fuel type) is estimated with the formula below.

Activity Data _{yr, cnty, FT, VC} = Fuel Consumption _{yr, cnty, FB, VC} × Fuel Sales Adjustment Factor_{yr, FB} × Fraction of Fuel Mix _{yr, FT}

Where:

• Fuel Consumption _{yr, cnty, FB, VC}: is the fuel consumption modeled by EMFAC2021 for a particular fuel blend and vehicle class each year by county, available from CARB’s EMFAC Web Portal (CARB, 2024c).

Fuel Sales Adjustment Factor

The fuel sale adjustment factor scales the statewide fuel consumption modeled by EMFAC2021 to the actual fuel sales. It is calculated using the formula below.

Fuel Sales Adjustment Factor_{yr, FB} = Fuel Sales _{state, yr, FB} ÷ Fuel Consumption _{state, yr, FB}

Where:

• Fuel Sales _{state, yr, FB}: is the annual statewide fuel sales of a particular fuel blend for a given year between 2000 and 2022 published by federal or state agencies. For gasoline blend and diesel blend, the taxable fuel sales data are collected from the California Department of Tax and Fee Administration (CDTFA) and/or, previously, the California Board of Equalization (BOE). For vehicles utilizing compressed natural gas or liquefied natural gas as fuel, the annual Natural Gas Consumption by End Use (NGCEU) data of California are retrieved from U.S. Energy Information Administration (EIA) (EIA, 2024).
• Fuel Consumption _{state, yr, FB}: is the annual statewide fuel consumption of a particular fuel blend for a given year between 2000 and 2022 modeled by EMFAC2021, downloaded from CARB’s EMFAC Web Portal (CARB, 2024c).

Fraction of Fuel Mix

Both the reported fuel sales and the fuel consumption modeled in EMFAC represent total quantities of blended fossil and non-fossil fuels. These totals reflect blended fuels, such as gasoline mixed with ethanol or diesel blended with biodiesel. To estimate emissions by specific fuel type, a fuel mix fraction is applied. This fraction—based on the methodology used in CARB’s AB 32 GHG Inventory—represents the proportion of each component (e.g., pure gasoline, ethanol, biodiesel) within the blended fuel. These proportions are calculated at the state level and vary by year. CARB compiles this information using activity data reported by fuel suppliers through the Mandatory Greenhouse Gas Reporting Program (MRR) and the Low Carbon Fuel Standard (LCFS) (CARB, 2016; CARB, 2022c; CARB, 2022d; CARB, 2023).

Control Factors / Emission Controls

A default control factor of 1.0 is applied to all on-road categories, as no local controls have been incorporated. This is due to the following reasons:

• The Air District does not have regulatory authority over on-road motor vehicles, which are governed at the federal and state level.
• Reductions in CO₂, CH₄ and N₂O emissions resulting from CARB regulations such as improved fuel economy standards, increased vehicle electrification, and the transition to renewable fuels are already reflected in annual fuel sales data and EMFAC2021 modeled fuel consumption.
• N₂O emission reductions associated with vehicles meeting more stringent NO_x standards are also captured in EMFAC2021 county-level estimates.

Emissions Scaling Approach (CH₄ & N₂O)

For CH₄ and N₂O, emissions directly estimated from EMFAC2021 are scaled using fuel sales adjustment factors based on statewide fuel consumptions and sales by fuel types as shown in the formula below.

Emissions _{yr, cnty, pol, cat} =

EMFAC Emissions _{yr, cnty, pol, VC, FB} × Fuel Sales Adjustment Factor_{yr, FB} × Fraction of Fuel Mix _{yr, FT} × Control Factor _pol× GWP _pol

Where:

• EMFAC Emissions _{yr, cnty, pol, VC, FB}: is the CH₄ or N₂O emissions modeled by EMFAC2021 in a given year by county, vehicle class and fuel blend as available from CARB’s EMFAC web portal (CARB, 2024c).

The fuel sales adjustment factor, fraction of fuel mix, and control factor are described above in the previous section.

Historical and Future Emissions

Once emissions of the years 2000-2022 are determined, historical backcasting and forecasting of emissions, relative to the base year emissions are performed using growth profiles as follows:

Emissions _FY = Emission ₂₀₂₂ × Growth Factor_FY

Emissions _HY = Emission ₂₀₀₀ × Growth Factor_HY

Where:

• Emissions _FY: is the annual county-total CO₂ equivalent (CO₂eq) emissions of a particular future year (FY) between 2023 and 2050.
• Growth Factor_FY: is the growth factor that equals the ratio of EMFAC fuel consumption of a given future year normalized to the year 2022.
• Emissions _HY: is the annual county-total CO₂ equivalent (CO₂eq) emissions of a particular historical year (HY) between 1990 and 1999.
• Growth Factor_FY: is the growth factor that equals the ratio of EMFAC fuel consumption of a given historical year normalized to the year 2000.

Historical Emissions / Backcast

As EMFAC2021 only includes fuel consumption data starting in 2000, an archived version of EMFAC2011 is used to estimate fuel consumption for prior years starting in 1990. The archived EMFAC2011 includes annual county total fuel consumptions by EMFAC2007 vehicle class and gasoline/diesel blends. For a given county, vehicle class, and fuel blend, the backcast growth factor is then derived using the formula below, normalized to the year 2000.

Growth Factor _HY = Fuel Consumption _HY ÷ Fuel Consumption ₂₀₀₀

Where:

• Growth Factor _HY: is the backcast growth factor of a particular historical year (HY between 1990-1999).
• Fuel Consumption _HY: is the EMFAC2011-based fuel consumption of a particular historical year.
• Fuel Consumption ₂₀₀₀: is the EMFAC2021-based fuel consumption for 2000.

Future Projections / Growth Factor

The latest fuel sales data is available up to the base year 2022. Beyond 2022, growth factors by county, vehicle class, and fuel blend are developed using projected fuel consumptions from EMFAC2021 and normalized to year 2022.

Growth Factor _FY = Fuel Consumption _FY ÷ Fuel Consumption ₂₀₂₂

Where:

• Growth Factor _FY: is the forecast growth factor for a particular future year (FY between 2023-2050).
• Fuel Consumption _FY: is the EMFAC2021-based fuel consumption of a particular future year.
• Fuel Consumption ₂₀₂₂: is the EMFAC2021-based fuel consumption of the year 2022.

Sample Calculations

CO₂

The table below shows a sample calculation for estimating base year 2022 CO₂ emissions from Heavy Heavy-Duty Trucks (HHDT) vehicle-type – Distillate fuel-type (category 2678) in Alameda County in units of million metric tons of CO₂ equivalents per year (MMTCO₂eq/yr).

Step 1	Obtain statewide fuel sales of diesel blend	3,067,876,790 gallons
Step 2	Obtain statewide fuel consumption of diesel blend from EMFAC2021 model	3,173,524,000 gallons
Step 3	Derive fuel sales adjustment factor for diesel blend	= 3,067,876,790 gallons ÷ 3,173,524,000 gallons = 0.96671
Step 4	Obtain fraction of distillate in diesel Blend from CARB	0.7108
Step 5	Obtain diesel blend consumed by heavy-heavy-duty-trucks (HHDT) from EMFAC Model for Alameda county	4,599,292 gallons
Step 6	Derive Activity: distillate consumed by HHDT in Alameda county by multiplying diesel blend consumed by the fraction of distillate in diesel blend and the fuel sales adjustment factor	= 94,599,292 gallons × 0.96671 × 0.7108 = 65,002,713 gallons
Step 7	Obtain heat content of distillate	138,000 btu/gallon
Step 8	Obtain CO2 emission factor of distillate	0.0741 g/btu
Step 9	Obtain control factor for CO2 based on Air District regulations	1.0
Step 10	Derive CO2 emissions (ton/yr) converted from grams to tons	= 65,002,713 gallons × 138,000 btu/gallon × 1.0 × 0.0741 g/btu ÷ 907,185 g/tons = 732,711.3 ton/yr
Step 11	Obtain GWP of CO2 from IPCC	= 1.0
Step 12	Convert CO2 emissions to MMTCO2eq/yr	= 732,711.3 ton/yr × 1 × 0.907185 metric tonne/ton ÷ 1,000,000 = 0.6647 MMTCO2eq/yr

N₂O

The table below shows a sample calculation for estimating base year 2000 N₂O emissions from passenger cars, also referred to as Light Duty Auto (LDA) vehicle-type – Gasoline fuel-type (category 2704) in Contra Costa county.

Step 1	Obtain statewide fuel sales of gasoline blend	= 14,765,008,708 gallons
Step 2	Obtain statewide fuel consumption of gasoline blend from EMFAC2021 model	= 14,200,413,000 gallons
Step 3	Derive fuel sales adjustment factor for gasoline blend	= 14,765,008,708 gallons ÷ 14,200,413,000 gallons = 1.039759
Step 4	Obtain the fraction of pure gasoline in gasoline Blend from CARB	= 0.996118
Step 5	Obtain N2O Emissions of Light Duty Auto (LDA) - Gasoline Blend from EMFAC Model for Contra Costa county (ton/yr)	= 263.6456 ton/yr
Step 6	Control Factor for N2O based on Air District regulations	= 1.0
Step 7	Obtain N2O emissions of pure gasoline consumed by LDA for Contra Costa county by multiplying total N2O emissions with the fuel sales adjustment factor and control factor	= 263.6456 ton/yr × 1.039759 × 0.996118 x 1.0 = 273.0637 ton/yr
Step 8	Obtain GWP of N2O from IPCC	298
Step 9	Convert N2O emissions to MMTCO2eq/yr	= 273.0637 ton/yr × 298 × 0.907185 metric ton/ton ÷ 1000,000 = 0.07382 MMTCO2eq/yr

Assessment of Methodology

On-Road Mobile Source GHG emissions inventory are routinely updated to incorporate methodology improvement and underlying data updates from federal or state annual reports.

Base Year	Revision	Reference
2022	Adopted CARB’s AB 32 GHG Inventory methodology which uses energy-based emission factors, EMFAC2021-based fuel consumption and emissions (CH4 & N2O) adjusted by real-world fuel sales, statewide fuel mix distinguishing fossil fuel and biofuel. Created new source categories to align with CARB’s AB32 GHG inventory based on fuel type and vehicle type instead of fuel blend in EMFAC2021 to facilitate the CO2_bio emissions estimates. Updated activity data and emissions of all years during 2000-2022 via incorporating data from EMFAC2021, CDTFA, EIA, CARB MRR & LCFS programs. Updated forecast profiles based on fuel consumptions from EMFAC2021. Used GWP from IPCC’s 5th Assessment Report (AR5).	CARB, 2016; CARB, 2022c; CARB, 2022d; CARB, 2023 CARB, 2016; CARB, 2022b; CARB, 2022c; CARB, 2022d; CARB, 2023; CARB, 2024c; CDTFA, 2024; EIA, 2024; CEC, 2024 CARB, 2022b IPCC, 2014
2015	Used CARB’s Vision 2.1 Passenger Vehicle Module and Heavy-Duty Truck Module for forecasting the two subsectors:1) Passenger Cars & Trucks and Buses; 2) Heavy Duty Trucks, respectively. Used Bay Area specific EMFAC2014 modeling results for forecasting the Motorhomes & Motorcycles subsector. Updated GWP to that from IPCC’s 5th Assessment Report (AR5).	BAAQMD, 2017; CARB, 2017 BAAQMD internal procedure IPCC, 2013
2011	Updated base year 2011 CO2 emissions with estimates from EMFAC2011 (SG, v1.1) using vehicle miles travelled (VMT) and other activity data by county from the Metropolitan Transportation Commission’s (MTC) Regional Transportation Plan (RTP2030). Updated backcast and forecast profiles using the EMFAC2011 outputs from the same model run described in bullet 1 above. Used GWP from IPCC’s 4th Assessment Report (AR4).	BAAQMD, 2015; CARB, 2011 BAAQMD, 2015; CARB, 2011 IPCC, 2007

Emissions

The table below shows the total GHG emissions by pollutant in metric tons of CO₂ equivalents (MTCO₂eq) for on-road mobile categories.

ID	Description	CH4	CO2	CO2_bio	N2O	Total
2704	Light Duty Passenger - Gasoline	11026.4	7249586.9	0.0	70894.8	7331508.1
2706	Light Duty Trucks (II) - Gasoline	5767.8	4228898.4	0.0	39617.9	4274284.1
2710	Medium Duty Trucks - Gasoline	4328.8	2827674.9	0.0	27921.9	2859925.6
2678	Heavy Heavy Duty Trucks - Distillate	106.0	1612409.8	0.0	75182.0	1687697.8
2707	Light Heavy Duty Trucks (I) - Gasoline	808.7	794838.5	0.0	8519.4	804166.6
2705	Light Duty Trucks (I) - Gasoline	1806.6	774988.2	0.0	10802.9	787597.7
2691	Light Duty Passenger - Ethanol	1238.7	0.0	534050.6	7965.0	543254.3
2686	Medium Heavy Duty Trucks - Distillate	37.6	511667.7	0.0	23857.7	535563.0
2721	Heavy Heavy Duty Trucks - Renewable Diesel	33.0	0.0	501326.1	23375.5	524734.6
2693	Light Duty Trucks (II) - Ethanol	647.9	0.0	311527.4	4451.0	316626.3
2682	Light Heavy Duty Trucks (I) - Distillate	133.9	258109.0	0.0	12034.8	270277.7
2697	Medium Duty Trucks - Ethanol	486.3	0.0	208304.5	3136.9	211927.7
2712	Medium Heavy Duty Trucks - Gasoline	151.1	179108.8	0.0	1225.6	180485.5
2729	Medium Heavy Duty Trucks - Renewable Diesel	11.7	0.0	159086.5	7417.7	166515.9
2666	Heavy Heavy Duty Trucks - Biodiesel	10.3	0.0	142916.2	7213.6	150140.1
2683	Light Heavy Duty Trucks (II) - Distillate	48.2	131707.1	0.0	6141.1	137896.4
2716	Heavy Heavy Duty Trucks - Natural Gas	74.6	116347.7	0.0	65.3	116487.6
2708	Light Heavy Duty Trucks (II) - Gasoline	95.4	115260.6	0.0	1091.4	116447.4
2725	Light Heavy Duty Trucks (I) - Renewable Diesel	41.7	0.0	80250.5	3741.8	84034.0
2689	Urban Buses - Distillate	8.2	75775.7	0.0	3533.2	79317.1
2687	Other Buses - Distillate	5.3	65490.0	0.0	3053.7	68549.0
2713	Other Buses - Gasoline	38.2	63322.7	0.0	378.6	63739.5
2694	Light Heavy Duty Trucks (I) - Ethanol	90.8	0.0	58552.8	957.1	59600.7
2692	Light Duty Trucks (I) - Ethanol	202.9	0.0	57090.4	1213.7	58507.0
2711	Motor Homes - Gasoline	17.6	49647.9	0.0	229.6	49895.1
2674	Medium Heavy Duty Trucks - Biodiesel	3.6	0.0	45351.8	2289.0	47644.4
2709	Motorcycles - Gasoline	1728.6	42438.3	0.0	2690.5	46857.4
2726	Light Heavy Duty Trucks (II) - Renewable Diesel	15.0	0.0	40949.9	1909.5	42874.4
2684	Medium Duty Trucks - Distillate	1.7	38266.7	0.0	1784.3	40052.7
2732	Urban Buses - Renewable Diesel	2.5	0.0	23560.0	1098.5	24661.0
2670	Light Heavy Duty Trucks (I) - Biodiesel	12.7	0.0	22877.6	1154.7	24045.0
2730	Other Buses - Renewable Diesel	1.7	0.0	20362.0	949.4	21313.1
2688	School Buses - Distillate	1.4	17676.8	0.0	824.4	18502.6
2679	Light Duty Passenger - Distillate	3.6	16906.9	0.0	788.3	17698.8
2715	Urban Buses - Gasoline	3.2	17293.1	0.0	54.8	17351.1
2720	Urban Buses - Natural Gas	9.7	15117.9	0.0	8.5	15136.1
2699	Medium Heavy Duty Trucks - Ethanol	17.0	0.0	13194.4	137.6	13349.0
2681	Light Duty Trucks (II) - Distillate	0.9	12305.9	0.0	573.8	12880.6
2727	Medium Duty Trucks - Renewable Diesel	0.4	0.0	11897.8	554.7	12452.9
2671	Light Heavy Duty Trucks (II) - Biodiesel	4.5	0.0	11673.9	589.3	12267.7
2685	Motor Homes - Distillate	1.6	9388.2	0.0	437.7	9827.5
2695	Light Heavy Duty Trucks (II) - Ethanol	10.8	0.0	8490.9	122.5	8624.2
2717	Medium Heavy Duty Trucks - Natural Gas	5.4	8575.5	0.0	4.9	8585.8
2714	School Buses - Gasoline	19.0	7526.4	0.0	88.2	7633.6
2677	Urban Buses - Biodiesel	0.8	0.0	6716.5	338.9	7056.2
2675	Other Buses - Biodiesel	0.4	0.0	5804.7	292.9	6098.0
2731	School Buses - Renewable Diesel	0.4	0.0	5496.0	256.2	5752.6
2722	Light Duty Passenger - Renewable Diesel	1.2	0.0	5256.6	245.0	5502.8
2700	Other Buses - Ethanol	4.3	0.0	4664.8	42.5	4711.6
2724	Light Duty Trucks (II) - Renewable Diesel	0.2	0.0	3826.1	178.4	4004.7
2698	Motor Homes - Ethanol	1.9	0.0	3657.4	25.8	3685.1
2696	Motorcycles - Ethanol	194.2	0.0	3126.4	302.3	3622.9
2672	Medium Duty Trucks - Biodiesel	0.0	0.0	3391.8	171.3	3563.1
2728	Motor Homes - Renewable Diesel	0.4	0.0	2918.9	136.1	3055.4
2719	School Buses - Natural Gas	1.3	1913.0	0.0	1.0	1915.3
2676	School Buses - Biodiesel	0.0	0.0	1566.7	79.1	1645.8
2667	Light Duty Passenger - Biodiesel	0.2	0.0	1498.5	75.6	1574.3
2703	Heavy Heavy Duty Trucks - Gasoline	3.3	1359.8	0.0	29.9	1393.0
2702	Urban Buses - Ethanol	0.2	0.0	1273.8	6.1	1280.1
2669	Light Duty Trucks (II) - Biodiesel	0.0	0.0	1090.9	55.2	1146.1
2673	Motor Homes - Biodiesel	0.0	0.0	832.2	42.0	874.2
2718	Other Buses - Natural Gas	0.4	752.6	0.0	0.3	753.3
2701	School Buses - Ethanol	2.1	0.0	554.4	9.9	566.4
2680	Light Duty Trucks (I) - Distillate	0.2	183.0	0.0	8.5	191.7
2690	Heavy Heavy Duty Trucks - Ethanol	0.3	0.0	100.3	3.4	104.0
2723	Light Duty Trucks (I) - Renewable Diesel	0.0	0.0	56.9	2.7	59.6
2668	Light Duty Trucks (I) - Biodiesel	0.0	0.0	16.2	0.8	17.0

Summary of Base Year 2022 Emissions

In 2022, the On-Road Mobile Source subsector was the dominant source of emissions within the Transportation sector, accounting for approximately 87% of transportation-related emissions and contributing around 30% to the overall regional GHG inventory in the SFBA. Gasoline-powered passenger cars (LDA), light-duty trucks (LDT), and medium-duty vehicles (MDV) are the top three emitting categories, followed by distillate-powered heavy heavy-duty trucks (HHDT). Collectively, these four source categories are responsible for over 80% of on-road mobile source GHG emissions in 2022. CO₂ is the primary GHG pollutant emitted due to its high volume, despite having a relatively low GWP.

The tables below show the contribution of On-Road Mobile Source subsector GHG emissions to the overall regional total and to the Transportation sector. Please note that CO₂_bio emissions are excluded in the following tables and tracked separately.

Contribution of On-Road Mobile Sources Emissions by Sector

Subsector	Sector	Subsector GHG Emissions (MMTCO2eq)	Sector GHG Emissions (MMTCO2eq)	% of Sector
On-Road Mobile Sources	Transportation	19.64	22.60	86.89%

Contribution of On-Road Mobile Sources Emissions to Regional Total

Subsector	Subsector GHG Emissions (MMTCO2eq)	Regional Total GHG Emissions (MMTCO2eq)	% of Regional Total
On-Road Mobile Sources	19.64	65.68	29.90%

Trends

The time series chart below shows the emission trends for On-Road Mobile Source subsector categories.

Summary of Trends

Overall, on-road mobile source GHG emissions have declined significantly over the past few decades despite a growing vehicle population and long-term increase in vehicle miles travelled (VMT) in the SFBA. This is largely due to the improved fuel economy and reduced fossil fuel use due to CARB’s adoption of progressive rules requiring cleaner fleets and use of low carbon intensity fuels.

Uncertainties

The uncertainties of this GHG inventory are introduced by underlying data and modeling tools, as well as methodological changes.

• The fuel mix data and fuel sales adjustment factors are compiled at the state-level which may not accurately reflect the actual fuel mix and fuel sales in the SFBA counties. CEC has county-level fuel sales data by fuel-type that is based on the California Retail Fuel Outlet Annual Reporting (CEC-A15), received from all retail transportation fueling stations in California (CEC, 2024). This dataset has its limitations in data completeness due to survey response rates (A15 sales data represents nearly 86 percent of total gasoline consumed in California) and due to confidentiality agreements about details that can be disclosed at the county-level. For example, CEC is not able to disclose the number of stations nor fuel sales for counties with three or fewer fueling stations of a particular fuel type. They can only share them as a lumpsum in their report. Plus, the survey-based fuel sales data indicates where the fuel is loaded. Considering the mobility of on-road vehicles, it may not be representative of where the fuel is consumed, and pollutants are emitted. Despite all these constraints, it is worth exploring the possibility of using CEC county-level fuel sales data to determine if it can be a good alternative to statewide fuel mix.
• EMFAC2021 does not include the impact of CARB regulations adopted after its release in 2021, including Advanced Clean Car II (ACC II) and Advanced Clean Fleet (ACF) which aims to accelerate the transition to zero emissions vehicle fleet, which further reduce the fossil fuel usage, especially for years beyond 2035. Portions of these rules are incorporated in EMFAC2025 but uncertainty at the federal levels makes it difficult to assert which regulations will be implemented in the near future.
• Following the completion of the SFBA On-Road Mobile Source subsector GHG inventory, the AB32 GHG Emissions Inventory has recently been updated to include the year 2022. This version implements updated emission factors and HHVs for all years (CARB, 2024b). The updates and fuel consumption data modeled by EMFAC2025 will be used in the next cycle of GHG inventory development for all years (1990-2050) which may result in slightly different emissions estimates from the current version even for the same category, year and county.

Contact

Author: Yuan Du

Reviewer: Abhinav Guha

Last Update: 07/16/2025

References

BAAQMD. 2015. Bay Area Emissions Inventory Summary Report: Greenhouse Gases. Base Year 2011 http://www.baaqmd.gov/~/media/Files/Planning%20and%20Research/Emission%20Inventory/BY2011_GHGSummary.ashx?la=en

BAAQMD. 2017. Greenhouse Gas Emission Estimates and Draft Forecasts. https://www.baaqmd.gov/~/media/files/planning-and-research/plans/2017-clean-air-plan/ghg_emissions_and_forecasts_draft.pdf?rev=03f881a814054a93a8f1d29b9dec09fa&sc_lang=en

CARB. 2011. EMFAC2011 model archived at: https://ww2.arb.ca.gov/our-work/programs/msei/emfac2014-model-and-previous-versions

CARB. 2016. California’s 2000-2014 Greenhouse Gas Emission Inventory Technical Support Document (2016 Edition). https://ww2.arb.ca.gov/sites/default/files/classic/cc/inventory/ghg_inventory_tsd_00-14.pdf

CARB. 2017. Vision 2.1 Passenger Vehicle Module. ARB 2017 Vision 2.1 Heavy-Duty Vehicle Module. See also: Vision Model Update Memo Major Changes between Vision 2.1 and 2.0, May 27, 2016. https://www.arb.ca.gov/planning/vision/downloads.htm

CARB. 2019. California Air Resources Board. Mandatory Greenhouse Gas Reporting Regulation. https://ww2.arb.ca.gov/mrr-regulation

CARB. 2022a. MSEI - Modeling Tools - EMFAC Software and Technical Support Documentation. https://ww2.arb.ca.gov/msei-modeling-tools-emfac-software-and-technical-support-documentation. Last updated on 5/2/2022.

CARB. 2022b. EMFAC2021 (v1.0.2) Model Technical Documentation. https://ww2.arb.ca.gov/sites/default/files/2021-08/emfac2021_technical_documentation_april2021.pdf

CARB. 2022c. California’s Greenhouse Gas Emissions Inventory: A Compilation of Inventory Updates Since the 2016 Edition of the Inventory Supplement to the Technical Support Document (2017-2021 Edition). https://ww2.arb.ca.gov/sites/default/files/classic/cc/inventory/method_updates_compilation.pdf

CARB. 2022d. California’s 2000-2020 Greenhouse Gas Emissions Inventory 2022 Edition Inventory Updates Since the 2021 Edition of the Inventory - Supplement to the Technical Support Document. https://ww2.arb.ca.gov/sites/default/files/2023-12/ghg_inventory_00-20_method_update_document.pdf

CARB. 2023. GHG Inventory Documentation Index. https://ww2.arb.ca.gov/applications/california-ghg-inventory-documentation. Last updated in 2023 and accessed in 2024.

CARB. 2024a. Current California GHG Emission Inventory Data. https://ww2.arb.ca.gov/ghg-inventory-data

CARB. 2024b. California’s 2000-2022 AB 32 Greenhouse Gas Emissions Inventory (2024 Edition) Updates Documentation. https://ww2.arb.ca.gov/sites/default/files/2024-09/nc-ghg_inventory_00-22_method_update_document.pdf

CARB. 2024c. EMFAC Web Portal. https://arb.ca.gov/emfac/emissions-inventory/586dad5367a4e28c9acd1d3f3868e30d7775da34. Accessed in 2024.

CDTFA. 2024. Datasets Catalog - Fuel Taxes for Diesel and Motor Vehicle Fuel. https://www.cdtfa.ca.gov/dataportal/catalog.htm?category=Fuel%20Taxes

CEC. 2024. California Retail Fuel Outlet Annual Reporting (CEC-A15) Results https://www.energy.ca.gov/data-reports/energy-almanac/transportation-energy/california-retail-fuel-outlet-annual-reporting#notes

EIA. 2024. Natural Gas Consumption by End Use. http://www.eia.gov/dnav/ng/ng_cons_sum_dcu_sca_a.htm. Release on 5/31/2024.

IPCC. 2006. Intergovernmental Panel on Climate Change, “IPCC Guidelines for National Greenhouse Gas Inventories, Volume 1 – General Guidance and Reporting”. https://www.ipcc-nggip.iges.or.jp/public/2006gl/vol1.html

IPCC. 2007. Forster, P., V. Ramaswamy, P. Artaxo, T. Berntsen, R. Betts, D.W. Fahey, J. Haywood, J. Lean, D.C. Lowe, G. Myhre, J. Nganga, R. Prinn, G. Raga, M. Schulz and R. Van Dorland, 2007: Changes in Atmospheric Constituents and in Radiative Forcing. In: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M.Tignor and H.L. Miller (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. https://www.ipcc.ch/site/assets/uploads/2018/02/ar4-wg1-chapter2-1.pdf

IPCC. 2013. G. D. Myhre, et al., 2013: Anthropogenic and Natural Radiative Forcing. In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [T. F. Stocker, et al. (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. https://www.ipcc.ch/pdf/assessmentreport/ar5/wg1/WG1AR5_Chapter08_FINAL.pdf

IPCC. 2014: Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II, and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, R.K. Pachauri and L.A. Meyers (eds.)]. IPCC, Geneva, Switzerland, 151 pp. Available here: https://www.ipcc.ch/site/assets/uploads/2018/02/SYR_AR5_FINAL_full.pdf