3.2 Non-Refinery Fuel Combustion

Category ID	Description	EIC
307_ind	Other External Combustion - Natural Gas	Various
308	Other External Combustion - LPG	Various
309	Other External Combustion - Distillate Oil	Various
310	Other External Combustion - Residual Oil	Various
311	Other External Combustion - Coke, Coal	5007002200000, 5007002400000
312	Other External Combustion - Other Fuels	Various
968	Glass Melting Furnaces - Natural Gas	Various
1590	Other External Combustion - Natural Gas (area source)	5099501100000
1747	Cement Plant Combustion - Coke	5007002200000
1748	Cement Plant Combustion - Coal	Various
1749	Cement Plant Combustion - Natural Gas	5007001100000

Introduction

Greenhouse gas (GHG) emissions from non-refinery fuel combustion sources are primarily determined by the type of fuel used and the specific combustion processes involved. These sources include a wide range of industrial and institutional equipment, such as water and steam boilers, furnaces, space heaters, process heaters, pre-heaters, ovens, and afterburners.

Non-refinery fuel combustion sources are categorized below based on their industrial application and fuel type.

Category 307_ind - Non-Refinery Fuel Combustion - Natural Gas
Category 308 - Non-Refinery Fuel Combustion - LPG
Category 309 - Non-Refinery Fuel Combustion - Distillate Oil
Category 310 - Non-Refinery Fuel Combustion - Residual Oil
Category 311 - Non-Refinery Fuel Combustion - Coke, Coal
Category 312 - Non-Refinery Fuel Combustion - Other Fuels
Category 968 - Glass Melting Furnaces - Natural Gas
Category 1747 - Cement Plant Combustion - Coke
Category 1748 - Cement Plant Combustion - Coal
Category 1749 - Cement Plant Combustion - Natural Gas
Category 1590 - Industrial Fuel Combustion

Industrial boilers (covered in source categories 307_ind, 308 – 312) burn fuels such as natural gas and oil to generate heat and steam for various applications, each contributing varying levels of emissions. When fuel is combusted outside of a chamber and the resulting heat is used to heat a working fluid, such as water, it is referred to as external combustion. This fuel combustion process produces a large amount of carbon dioxide (CO₂) and minute quantities of methane (CH₄) and nitrous oxide (N₂O). In the glass manufacturing source category (category 968), natural gas-fired glass melting furnaces operate at high temperatures that is critical for glass production. Similarly, cement manufacturing source categories (1747-1749) rely on kilns that burn fuels like petroleum coke and natural gas to generate the intense heat required for clinker formation. A brief description of the source categories covered in this methodology documentation is provided below:

Category 307_ind estimates emissions from natural gas combustion sources, including industrial and institutional equipment such as water and steam boilers, furnaces, space heaters, process heaters, pre-heaters, ovens, and afterburners.
Categories 308, 309, 310, 311, and 312 account for emissions from the external combustion of various fuels, including liquefied petroleum gas (LPG), distillate oil, residual oil, coke, coal, and other fuels, at industrial facilities throughout the San Francisco Bay Area (SFBA).
Category 968 includes emissions generated by natural gas-fired glass melting furnaces, which are essential in glass manufacturing facilities. These furnaces operate at high temperatures to melt raw materials such as silica, soda ash, and limestone, producing molten glass for various applications. The combustion of natural gas in these furnaces results in GHG emissions, primarily CO₂, along with other pollutants.
Categories 1747, 1748, and 1749 account for emissions from various fuels used to generate the high temperatures required in kilns for the cement manufacturing process. Historically, these fuels have included coke (category 1747), coal (category 1748), and natural gas (category 1749). However, since year 2010, coal has been phased out as a fuel source in cement kilns. Cement manufacturing is a major contributor to GHG emissions, primarily due to both fuel combustion and the chemical reactions involved in clinker production.
Category 1590 is classified as an area source category, representing fuel combustion emissions from industrial heating sources that are not annually cataloged by the BAAQMD (the Air District) Air District. Estimating emissions for these sources requires data from the California Energy Commission (CEC) and Air District natural gas usage by county for permitted industrial and commercial sources.

Methodology

Permitted Sources (Categories 307_ind, 308 - 312, 968, 1747 - 1749)

Point sources are operations that emit air pollution into the atmosphere at a fixed location within a facility, and for which the Bay Area Air Quality Management District (BAAQMD or the Air District) has issued a permit to operate (PTO), e.g. refinery cooling towers. These point sources could also be a collection of similar equipment and/or sources located across multiple facilities, e.g. reciprocating engines.

During the PTO issuance process, the Air District collects site-specific information from the operating facility and/or determines from published literature, e.g. United States Environmental Protection Agency’s (USEPA) AP-42 (USEPA, 2024), characteristics of a source including maximum throughput, emission factors for emitted pollutants, and control factors associated with downstream abatement devices. This data is then compared against the Air District’s Regulations to ensure compliance. Facilities that hold a PTO are required to renew their permit periodically (this period varies based on facility and source type). Upon renewal, the facilities are requested to provide any updates to source characteristics as well as the source throughput for the past twelve months. This throughput, in combination with the emission factors and controls factors stored in the Air District’s internal database, are used to programmatically estimate annual emissions at the source level. The methodology used to calculate emissions for the reported base year(s) of a permitted point source is as follows:

Base Year(s) Emissions _{source,pollutant}=

Activity Data_source × Emission Factor_pollutant × Control Factor_pollutant × GWP_pollutant

Base Year(s) Emissions _county= ∑ ^N_i=1 Emissions_i

Where:

Base Year: is a year for which activity / throughput data is available from permit records.
Activity Data _source is the throughput or activity data for applicable base year(s) at the source/equipment level. This data is usually available from the internal permit records that are provided annually to the Air District at permit renewal by the facility operator.
Emission Factor_pollutant is a factor that allocates an amount of emissions, in mass, of a particular pollutant by unit of activity data. For example, tons CO₂ per gallons of gasoline burned or pounds of N₂O per million standard cubic feet of natural gas combusted. GHG emissions are calculated by using specific emission factors for every source/operation for which information has been supplied by the facility (and verified/validated through source tests). If no specific emission factors are available, generalized factors developed by Air District staff are used to determine emissions. These default factors typically come from published literature such as USEPA’s AP-42 (USEPA, 2024) or California Air Resource Board’s (CARB) Mandatory Reporting Requirement (CARB, 2019) for Greenhouse Gases.
Control Factor_pollutant is a fractional ratio (between 0 and 1) that captures the estimated reduction in emissions as a result of District rules and regulations.
GWP_pollutant is the Global Warming Potential. The current version of the GHG emissions inventory incorporates the global warming potential (GWP) reported in the Fifth Assessment report of the Intergovernmental Panel for Climate Change (IPCC, 2014). The GWPs for the three principal GHGs are 1 for carbon dioxide (CO₂), 34 for methane (CH₄), and 298 for nitrous oxide (N₂O), when calculated on a 100-year basis with climate-carbon feedback included.
N is the number of permitted and similar sources in a county.

If available, a facility can provide emission factors specific to the source that are verified and validated through source tests to estimate GHG emissions. If no specific emission factors are available, general factors developed by Air District staff are used to estimate emissions. These source level emissions are then sorted and aggregated by year, county, and category.

Further speciation and quality assurance of emissions, including those of GHGs, are performed as a part of the inventory refinement process. A systematic crosswalk has been developed between CARB’s California Emissions Projection Analysis Model (CEPAM) source category classification using the primary sector emission inventory codes (EICs) and the Air District’s source category classification (category identification number - cat_ids), which ensures consistency when reporting annual emissions under the California Emissions Inventory Data Analysis and Reporting Systems (CEIDARS) to CARB (CARB, 2022a). This emissions data represents the reported base years emissions for a point source category.

Once base year emissions are determined, historical backcasting and forecasting of emissions relative to the base year emissions are estimated using growth profiles as follows:

Current Year Emissions_county = Base Year(s) Emission_county x Growth Factor

Where:

Growth Factor: is a scaling factor that is used to derive historical emissions estimates for years for which activity data and/or emissions are not available, and to forecast emissions for future years, using surrogates that are assumed to be representative of activity and/or emissions trends.

For those years where no data is available, emissions data are backcast to the year 1990, as well as forecasted to year 2050 using either interpolation or another mathematical approach (see Trends section), or by applying a growth profile based on socioeconomic indicators. GHG emissions data from the years 1990 to 2050, including the projections outlined below, are analyzed for each source category and pollutant, with the trends evaluated for any observed anomalies and modified, if needed:

Historical Backcast (1990 – 2006): Association of Bay Area Governments (ABAG) Employment growth profiles (ABAG, 2024) and scaled District permitted data
Base Years (2007 – 2022): District permitted data
Future Projection (2023 – 2050)
- The fuel use forecast for non-refinery fuel combustion sources in category 307_ind is based on the California Energy Commission's (CEC) 2023 Integrated Energy Policy Report (CEC, 2023c). This report provides updated projections on energy demand and fuel consumption trends for natural gas, offering valuable insights into future energy needs for these sources.
The forecast for non-refinery fuel combustion sources involving other fuels is based on energy demand projections by fuel type, derived from CARB’s E3 Pathways model as outlined in the 2022 Scoping Plan (CARB, 2022b) for categories 308-312. This model predicts energy consumption trends in the Industrial sector, factoring in the shift toward zero-emission technologies. In addition to projecting a reduction in fuel consumption, the model also incorporates historical emissions trends. By combining both historical data and future projections, the forecast provides a comprehensive view of expected energy use and emissions reduction within the industrial sector.
In April 2020, the global COVID-19 pandemic and a decline in demand prompted facility # 17, the Lehigh Cement Plant in Santa Clara County, to halt its cement kiln operations. This initial shutdown reflected broader economic slowdowns and shifts in industrial activity during the pandemic. In November 2022, it was officially announced that the plant would permanently close and would not resume operations. The closure is expected to significantly impact future emissions trends of this subsector, particularly concerning the combustion of coke (category 1747), coal (category 1748), and natural gas (category 1749).
Owens-Brockway in Alameda County permanently ceased operations in 2015, which will also influence emissions trends from the fuel combustion in glass melting furnaces (category 968).

Emissions data is finally aggregated under sub-sectors and sectors for tracking trends and documentation purposes.

Local Controls

The Air District adopted Regulation 9, Rule 7 in 1992 (BAAQMD, 2011) to address nitrogen oxides (NO_x) and carbon monoxide (CO) emissions from industrial, institutional, and commercial boilers, steam generators, and process heaters. Regulation 9, Rule 7 applies to sources in Category 307_ind. The 2008 amendments aimed to further reduce NO_x emissions while ensuring cost-effectiveness and technological feasibility. These updates established stricter NO_x limits for heaters rated at 10 MM BTU/hr and higher and introduced new requirements for smaller heaters using natural gas, LPG, and other fuels. The amended Regulation 9, Rule 7 in 2011 (BAAQMD, 2011) established retrofit requirements for both new and existing equipment. Additionally, energy efficiency measures were implemented to reduce GHG emissions by minimizing heat loss, promoting efficient operation, and mitigating potential GHG increases associated with NO_x control measures. Regulation 9, Rule 7, has been reviewed and the effect of regulatory controls is included in the estimation of emissions forecasts (or missing historical data), where applicable. There is no impact of the above-mentioned criteria air pollutant-specific rules on GHGs emissions from the regulated equipment, that have not already been accounted for in the emission calculation method. Hence, no separate controls need to be applied to the derived/reported GHG emissions.

Historical Emissions

Historical emissions for point sources are derived from source-specific data provided by the facility on throughputs, compiled or reported emission factors, and regulation-based control factors. This information is archived in the Air District’s internal database and is queried to retrieve the data for historical and current years. Interpolation techniques to account for missing data are used when necessary.

In the case of GHGs, up until the year 2006, the Air District was not engaged in systematic information collection during permit renewal process. This changed when AB32 bill was passed into a statewide law in 2006, and a statewide Cap and Trade system was introduced to reduce GHG emissions from specific facilities. Hence, GHG emissions data for years 1990-2006 are derived from the historical emissions data reported in the base year 2011 GHG inventory (released in year 2012). The historic emissions dataset is scaled to sync with the data in the permit database (which started systematic GHG data accounting from year 2006 onwards), to generate a complete GHG emissions time series for each point source category from 1990 to 2050.

Future Projections

Forecasting of point source emissions is done based on calculations as shown in the equation below using recently updated growth profiles and a base year of 2022. The growth profiles for the current base year inventory have been verified and updated to represent the most likely surrogate for forecasting emissions for a given category up to the year 2050. Forecasting for point source emissions includes impact of in-place regulations but does not include estimation of controls that will theoretically be implemented as part of future policy emission targets or proposed regulation and legislation.

PE = Gr × C_i × E_i

PE = projected emissions of pollutant i in a future year

Gr = growth rate by economic profile of industry or population

C_i = control factor of pollutant i based on adopted rules and regulations
E_i = base year emissions of pollutant i

Forecast for industrial sector energy use associated with fuel combustion sources involving different fuels (category 308-312) are applied from CARB’s E3 Pathways model as used in their 2022 Scoping Plan (CARB, 2022b). The E3 forecasting model predicts energy consumption trends in the Industrial sector, factoring in the shift toward zero-emission technologies. This demand is forecasted to decrease as zero-emissions technologies are promoted and adopted. The forecast also accounts for historical emissions, which show an overall downward trend at the state level for the industrial sector. As noted in the introduction in the Methodology section, the permanent closure of a large glass smelting furnace and a large cement plant in the region in recent years has significantly altered and lowered the forecast for GHG emissions for categories 968 and 1747-49, respectively.

Area Sources (Category 1590)

Category 1590 is considered an area source category as it accounts for emissions from industrial heating sources that are not directly permitted by the Air District, and thus not routinely or annually reported. The data used to estimate emissions for these sources must be extracted from either CARB or CEC databases. The methodology used to calculate emissions for the reported base years for this source category is as follows:

Base Year(s) Emissions _{county,pollutant}=

Activity Data × Emission Factor_pollutant × Control Factor_pollutant × Fraction_county× Fraction_{in District}× GWP_pollutant

Where:

Base Year: is a year for which activity / throughput data is reported by CEC and/or CARB, and available.
Activity Data: is the throughput or activity data for applicable reported base years. This data may be determined in one or two ways:
- Apportioning Larger-Scale Data: Throughput data from a larger domain, such as state or national level, is scaled using the proportion of a representative metric in the regional domain relative to the larger domain. For example, the ratio of a county’s population to the state population can be used as a scaling factor to determine the county throughput from state-level throughput.
- Using Local Sources: Alternatively, data from a locally published and verifiable source may be used, such as the county-level natural gas usage data provided by the CEC.
Emission Factor_pollutant: is a factor that allocates an amount of emissions, in mass, of a particular pollutant by unit of activity data. For example, tons of CO₂ per gallon of gasoline burned or pounds of N₂O per million standard cubic feet (MMSCF) of natural gas combusted. This factor generally comes from a published literature source such as USEPA AP-42 (USEPA, 1998) or CARB’s Mandatory Reporting Requirement (MRR) for Greenhouse Gases (CARB, 2019).
Control Factor_pollutant : is a fractional ratio (between 0 and 1) that captures the estimated reduction in emissions as a result of Air District rules and regulations.
Fraction_county: is the fraction of total regional emissions (between 0 and 1) estimated to be allocated to a particular county. It is typically derived from regional socioeconomic metrics and/or actual county-level throughput data.
Fraction_{in District} : The Air District jurisdiction covers only a portion of Solano and Sonoma County. For this reason, additional allocation must be made for these counties to determine the proportion of the county’s emissions occurring within the Air District’s jurisdiction.
GWP_pollutant is the Global Warming Potential of a particular greenhouse gas (GHG) pollutant. The current version of the GHG emissions inventory incorporates the global warming potential (GWP) reported in the Fifth Assessment report of the Intergovernmental Panel for Climate Change (IPCC, 2014). The GWPs for the three principal GHGs are 1 for carbon dioxide (CO₂), 34 for methane (CH₄), and 298 for nitrous oxide (N₂O), when calculated on a 100-year basis with climate-carbon feedback included.

Once base year emissions are determined, historical backcasting and forecasting of emissions relative to the base year emissions are estimated using growth profiles as follows:

Current Year Emissions_county = Base Year(s) Emission_county x Growth Factor

Where:

Growth Factor: is a scaling factor that is used to derive historical emissions estimates for years for which activity data and/or emissions are not available, and to forecast emissions for future years, using surrogates that are assumed to be representative of activity and/or emissions trends.

More details on the inputs and variables used above are provided in the following subsections:

Activity Data

The reported base years for source category 1590 are the years 2011 – 2019. The datasets used to determine throughputs for the reported base years for the Industrial sector are listed below:

CEC Natural Gas Usage in Therms by County and by Residential and Non-Residential sectors, years 1990 – 2022 (CEC, 2023a),
CEC Natural Gas Usage in Therms by County and by Economic sector, years 1990 – 2022 (CEC, 2023b), and,
Reported natural gas throughputs by permitted industrial and commercial facilities to the Air District for years 2011-2019.

For this category, facilities subject to the registration requirements in Regulation 9, Rule 7 (BAAQMD, 2011) reported their annual throughput to the Air District from 2011 to 2019. In 2011, the Air District’s registration program for industrial process boilers and heaters came into full effect, but prior to 2011 the throughput for these devices was not reported to the Air District. Therefore, the year 2011 is considered to be a representative year for historical backcasting, as it is the first year where throughput from these registered boiler/heaters were recorded.

In a similar manner, the year 2019 is chosen to be a representative year for estimating future trends as it is the last year where natural gas throughput data was collected from these registered sources.

Prior to collecting direct natural gas usage from registered facilities (in the 1990s and 2000s), the CEC Natural Gas Usage by Residential and Non-Residential sectors was used to estimate emissions. To remain consistent with historical calculations, the same data set is used but the Air District now uses a refined approach for proportioning natural gas usage to the non-permitted area source in the Industrial and Commercial sectors using an additional CEC Natural Gas Usage by Economic sector data set. After determining the amount of natural gas used for the Industrial sector and natural gas usage from Hydrogen (H₂) production for the SFBA using the two datasets, the natural gas usage of industrial point sources, based on the Air District’s registered dataset (category 307_ind), are subtracted from CEC’s natural gas usage for the Industrial sector to avoid double counting. Not all of the natural gas that is delivered across the region is combusted, some is lost due to post-meter leakage. Therefore, an additional natural gas loss based on the leakage rate of 0.28% for industrial sources (CEC, 2020) is applied.

To summarize the calculation explained above, below is a simplified example calculation of throughput for a county for a single year:

Industrial Natural Gas Usage for Category 1590 =

(CEC Natural Gas Usage × % Industrial Usage – Industrial Natural Gas Usage for Permitted Sources including that consumed for H₂ production) × (1-Post-Meter Leakage Rate)

County Distribution / Fractions

County distribution is determined by using base year data for 2022 for Industrial sector natural gas usage from the CEC. No additional county distribution needs to be applied.

ID	Description	ALA	CC	MAR	NAP	SF	SM	SNC	SOL	SON
1590	Other External Combustion - Natural Gas (area source)	0.02	0.87	0.00	0.00	0.00	0.00	0.02	0.07	0.01
307_ind	Other External Combustion - Natural Gas	0.14	0.54	0.00	0.01	0.04	0.04	0.15	0.05	0.02
308	Other External Combustion - LPG	0.00	0.01	0.00	0.59	0.00	0.00	0.00	0.20	0.20
309	Other External Combustion - Distillate Oil	0.01	0.06	0.00	0.03	0.10	0.67	0.08	0.01	0.03
312	Other External Combustion - Other Fuels	0.06	0.76	0.01	0.00	0.07	0.03	0.01	0.05	0.00

BAAQMD Jurisdiction Fraction

The BAAQMD jurisdiction only accounts for a part of Solano and Sonoma counties. The remaining area is covered by other Air Districts. For category 1590, the percentage of Solano and Sonoma County populations within the Air District boundary (or jurisdiction) are estimated using the Association of Bay Area Government’s (ABAG) Plan Bay Area 2050 dataset (ABAG, 2021). The dataset summarizes population by Travel Analysis Zones (TAZs). The population for each TAZ within Air District’s jurisdictional boundaries is summed and divided by the total county-wide population to estimate the percentage of population within the SFBA for Solano and Sonoma counties. These proportions are shown below:

County	% of Population within the District’s jurisdiction
Solano	0.70
Sonoma	0.86

Emission Factors and Local Controls

As mentioned above, the emission factors for this category are dependent on the control factors. The combination of these two factors produces the Effective Emission Factor used in the emissions calculations. The Effective Emission Factor represents average emissions emitted from a natural gas combustion boiler/heater with add-on pollutant controls included. These controls may come in the form of a physical control device or as an emissions limit stipulated by Air District regulation or permit conditions. For example, the Effective Emission Factor in 1990 for N₂O was 2.2 lb/MMSCF, however, this same factor in 2022 is around 1.22 lb/MMSCF due to requirements in Regulation 9-6 (BAAQMD, 2023) that progressively lower the nitrogen oxides allowed to be emitted from small-to-medium natural gas commercial heaters sold in the Bay Area.

To compile the effective emission factor for each year, either the emission factor or control factor is adjusted to account for fleet turnover and/or compliance with the Air District regulation. In this case, the emission factor determined to be applicable in the year 1990 is held constant from 1990 onwards, and the evolving control factor is used to adjust the Effective Emission Factor.

The 1990 emission factors used for these calculations are presented in the table below:

Pollutant	Emission Factor (lb/MMSCF)	Reference
CH₄	2.26	EPA 40 CFR Part 98 Subpart C, 2016
N₂O	2.2	EPA AP-42, Chapter 1.4, 1998 (N₂O Uncontrolled)
CO₂	120,019	EPA 40 CFR Part 98 Subpart C, 2016

The GHG emissions calculated for the Industrial Fuel Combustion area source category 1590 are not currently regulated under District Regulation 9, Rule 7 (BAAQMD, 2011) or Regulation 9, Rule 6 (BAAQMD. 2021). These rules are designed to control air pollution by setting limits on emissions of NO_xand CO. It specifically applies to regulated and permitted industrial, institutional, steam generators, and process heaters. However, sources in category 1590 are not subject to the same emission limits or compliance requirements, and thus there are no co-impacts on GHG emissions to account for.

Historical Emissions

For historical backast of natural gas throughput, the CEC natural gas usage by county for the Industrial sector for 1990 to 2011 is used to produce a backcast profile. This profile is normalized to the year 2011 and applied to the year 2011 throughput obtained from the latest CEC publication (CEC, 2023a; CEC, 2023b) to determine throughput for years 1990-2011. As explained above, an effective emission factor was then applied from 1990-2011 to estimate emissions for N₂O, CO₂, and CH₄.

Future Projections

The CEC publishes an Integrated Energy Policy Report (IERP) every 2 years in which they forecast natural gas usage by an energy provider that accounts for achievable fuel substitution (AAFS) and achievable energy efficiency (AAEE). For all forecasting, a scenario based on a combination of AAFS and AAEE factors that best represents business-as-usual scenario is chosen. Business-as-usual is defined as existing conditions that include impacts from state and federal regulation adopted as of year 2022. To portray business-as-usual forecasting of emissions, the CEC recommends the use of Scenario 3 Programmatic AAFS and AAEE for the Pacific Gas & Electricity (PG&E) regional service area (CEC, 2023c).

Sample Calculations

An example calculation for Contra Costa County GHG emissions for year 2022 in units of metric tons of CO₂ equivalents (MTCO₂eq) for category 1590 is shown below:

Step 1	Convert 2019 natural gas usage for Non-Residential sector, obtained from the CEC for Contra Costa County, from MMTherms (million therms) to MMSCF (million standard cubic feet)	1028.69 MMTherms × 100,000 MMBtu/MMTherms ÷ 0.001026 MMBtu/scf × 1E-06 MMSCF/scf = 100,262.6 MMSCF
Step 2	Estimate the amount of non-residential natural gas used in the Industrial sector for Contra Costa using industrial usage percentage	100,262.6 MMSCF x 95.0% = 95,249 MMSCF
Step 3	Gather 2019 natural gas usage data from permitted/registered sources located in Contra Costa County in the Industrial sector in MMSCF (category 307_ind)	31,756 MMSCF
Step 4	Derive 2019 natural gas usage for area sources in the Industrial sector by subtracting 2019 natural gas usage activity data for category 307_ind	95,249 MMSCF – 31,756 MMSCF = 63,493 MMSCF
Step 5	Account for loss of natural gas through leakage	63,493 MMSCF x (1-0.0045) = 63,207 MSCF
Step 6	Grow the natural gas emissions from 2019 to 2022 using growth projections from ABAG Plan Bay Area 2050 datasets	63,207 MMSCF x 0.711 = 44,955 MMSCF
		CO₂	CH₄	N₂O
Step 7	GHG emission factors (lbs/ MMSCF)	120,019	2.26	0.23
Step 8	IPCC AR5 GWP values	1	34	298
Step 9	Calculate GHG emissions, convert to metric tons and apply GWP (MTCO₂eq/year)	= 44,955 MCF x 120,019 lbs/MCF x 1 ton/2000 lbs x 0.907185 MT/ton x 1 =2.45×10⁶ MTCO2eq	= 44,955 MCF x 2.26 lbs/MCF x 1 ton/2000 lbs x 0.907185 MT/ton x 34 GWP = 1,567 MTCO2eq	= 44,955 MCF x 0.23 lbs/MCF x 1 ton/2000 lbs x 0.907185 MT/ton x 298 GWP = 1,398 MTCO2eq

Assessment of Methodology

The general methodology for determining emissions in category 1590 has not changed. However, the determination of natural gas throughput allocated to the category has been significantly improved upon by the inclusion of post-meter leakage and a refined sector split of industrial area and point source contributions that significantly improves the accuracy of the resulting emissions.

Base Year	Revision	Reference
2022	Used reported base years throughputs for 2011 to 2019. Updated base year, backcast and forecast natural gas usage based on CEC data normalized to 2011 and 2019, respectively . Use CEC data based on the business-as-usual model forecast. Updated Sonoma/Solano County proportions in the SFBA using ABAG’s Plan Bay Area 2050 projections for 2022. Reduced potential double counting errors by subtracting the point source contributions (Category 307_ind) from the industrial sector for area sources. Updated emission factors based on USEPA AP-42 and Title 40 values Updated control factors to reflect latest applicable local regulatory requirements Used the latest GWP from the Fifth Assessment report of the IPCC.	BAAQMD permitted inventory for base years CEC, 2023c ABAG, 2021 BAAQMD, internal USEPA,1998; USEPA, 2016 BAAQMD, 2023 IPCC, 2014
2015	Used single base year of 2010, 1990-2010 data is same as Air District’s BY 2011 estimates The forecast includes projected reductions based on nonmandated policies and goals. No controls accounted for in the emissions from adopted Air District regulations	BAAQMD, 2015 Greenblatt, 2013 Greenblatt, 2013

Emissions

The detailed breakdown of non-refinery fuel combustion GHG emissions for the base year 2022 in units of MTCO₂eq is provided in the table below.

ID	Description	CFC-11	CH4	CO2	CO2_bio	N2O	Total
1590	Other External Combustion - Natural Gas (area source)	0.0	1795.5	2804543.4	0.0	1601.5	2807940.4
307_ind	Other External Combustion - Natural Gas	0.0	731.7	1990084.9	0.0	1662.4	1992479.0
312	Other External Combustion - Other Fuels	2.9	8468.9	343014.3	120343.7	873.1	472702.9
309	Other External Combustion - Distillate Oil	0.0	41.5	30429.0	0.0	69.0	30539.5
308	Other External Combustion - LPG	0.0	5.9	11099.2	0.0	192.1	11297.2

Summary of Base Year 2022 Emissions

The table below outlines the relative contribution of non-refinery fuel combustion GHG emissions to overall emissions at both the regional and sector levels. Categories 307_ind and 1590 are the two largest contributors to GHG emissions in this subsector and account for 5.90 MMTCO₂eq/year.

Contribution of Non-Refinery Fuel Combustion Emissions by Sector

Subsector	Sector	Subsector GHG Emissions (MMTCO2eq)	Sector GHG Emissions (MMTCO2eq)	% of Sector
Non-Refinery Fuel Combustion	Industrial	5.22	17.90	29.16%

Contribution of Non-Refinery Fuel Combustion Emissions to Regional Total

Subsector	Subsector GHG Emissions (MMTCO2eq)	Regional Total GHG Emissions (MMTCO2eq)	% of Regional Total
Non-Refinery Fuel Combustion	5.22	65.68	7.95%

Trends

The time series chart below shows the emission trends for all categories in this subsector.

Summary of Trends

The GHG emissions associated with category 307_ind, which include non-refinery fuel combustion boilers, heaters, and furnaces using natural gas, are expected to remain stable or unchanged. This is primarily due to the regulatory controls implemented by the Air District, which effectively manage and limit emissions from these sources.

The closure of the Lehigh Cement Plant in Santa Clara County represents a significant change in the regional emissions inventory. Previously, the plant was a major source of GHG emissions due to the combustion of coke (category 1747), coal (category 1748), and natural gas (category 1749) as part of the cement production process. With its closure, current and future emissions from these sources have been eliminated. Similarly, the permanent shutdown of Owens-Brockway in Alameda County in 2015 has notably impacted emissions trends for category 968. Owens-Brockway was associated with emissions from glass melting furnaces, and its closure has effectively removed emissions from these sources.

Uncertainties

As noted above, point source emissions are calculated at an individual source level. The accuracy of these calculations is limited by the accuracy of the specific emission factors applied and estimated throughput. As these emissions are aggregated to create category level summaries, it is difficult to define a quantitative error associated with the total.

There are potentially some non-refinery fuel combustion sources permitted as part of natural gas combustion in the industrial sector, that may slightly overlap with the commercial sector. While this overlap is not expected to be significant, it could be further refined by obtaining the exact methodology used by the CEC to allocate emissions across economic sectors and comparing it to the Air District’s distribution approach. Additionally, natural gas usage data for boilers registered with the Air District is not updated annually and may represent maximum usage rates rather than actual consumption. As a result, emissions for category 307_ind could be marginally overestimated.

As the definition of the term ‘Industrial’ may vary slightly depending on the base data set used to derive emissions, there is the possibility that emissions accounted for in these categories and those estimated as a part of natural gas combustion in the Commercial sector have a slight overlap. This overlap is not estimated to be significant but can be refined in the future by obtaining the exact method by which the CEC has distributed emissions into the various economic sectors and by comparing this how the Air District distributes emissions. In addition, the natural gas usage for those boilers registered with the Air District is not reported by the facility operator annually and therefore, may be outdated or represent maximum usage rates rather than actual consumption. This may result in emissions from category 307_ind being marginally overestimated.

Contact

Author: Michael Nguyen

Reviewer: Abhinav Guha

Last Update: 08/19/2025

References

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