8.3 Accidental Fires

    Category ID Description EIC
    750 Accidental Fires - Structural 66065602000000
    753 Accidental Fires - Automobiles 66065802000000
    1580 Accidental Fires - All Vegetation 93093402000000

    Introduction

    This document describes the methodology for estimating greenhouse gas (GHG) emissions from accidental fire activities in the San Francisco Bay Area (SFBA). Accidental fire activities include structural fires, automobile fires, and vegetation fires. These activities are classified under the Industrial, Transportation, and Agriculture sectors, respectively, and produce carbon dioxide (CO2), biogenic carbon dioxide (CO2_bio), methane (CH4), and nitrous oxide (N2O) emissions. Emissions are reported under specific categories based on the types of materials burned and are covered in different sectors:

    • Category 750 (Structural Fires) includes emissions generated from residential and commercial structure fires, mobile home fires, and also fires at industrial facilities. Most of the fires that occur in this category are a result of cooking accidents, gas leaks, heating equipment overload, and faulty electrical wiring in building structures. This source category is classified under the Industrial sector.
    • Category 753 (Automobile Fires) encompasses emissions resulting from fires in automobiles. These types of fires primarily arise from igniting due to a spark, an overheated engine, or a hot exhaust coming in contact with flammable liquids such as gasoline and oil within an automobile. Since this category has to do with transportation-related sources, it is classified under the Transportation sector.
    • Category 1580 (All Vegetation Fires) accounts for emissions from the combustion of living and dead vegetation in wildfires. Some of the sources include the burning of woodland, timber, brush, and grass. These fire incidents are typically unplanned and accidental, although wildfires attributed to vandalism are also included in this category. This category is part of the Agricultural sector as the vegetation fire sources are often related to agriculture and forestry. Note that CO2 emissions from this category are classified as biogenic, and consistent with California Air resources Board’s (CARB) GHG inventory reporting approach (CARB, 2016), these emissions are not included in the regional CO2 total.

    GHG emissions from planned agricultural activity and forest management fires (also known as Agricultural Burn) are covered under a separate write-up.

    Methodology

    Structural fire (category 750), automobile fire (category 753), and all vegetation fire (category 1580) emissions data are directly obtained by the Bay Area Air Quality Management District (BAAQMD or Air District) from the California Air Resources Board (CARB) database models. These categories are considered area source categories. Unlike point sources which can be identified by location (e.g., oil refineries and power plants) and are often permitted by local air districts, area source categories do not have specific locations and are spread over large areas (e.g., road dust). The methodology used to derive emissions for these categories are discussed below.

    For the base year(s) emissions of structural fire (category 750) and automobile fire (category 753), the methodology used to calculate emissions is provided in CARB’s area source documentation on Structure and Automobile Fires, Section 7.14 (CARB, 1999). In this area source report, specific methods and calculations used by CARB to measure and assess emissions from these two categories are outlined and discussed in detail.

    Since the emission calculations of all vegetation fires (category 1580) are more complex and detailed than the above two categories, the methodology used to calculate emissions for the base year(s) requires a computer application model from the United States Forest Service (USFS), called First Order Fire Effects Model (FOFEM) (CARB, 2023; Lutes, 2020). The model considers parameters such as the type of vegetation and whether it is alive or dead, heat output, soil heating, and geospatial extent of the fire as part of the activity data and for selecting the appropriate emissions factors in the emission estimates. The details of this model are discussed in the methodology document report prepared by CARB (CARB, 2020).

    The general equation used by CARB, and subsequently modified by the Air District, to calculate GHG emissions for the base year of these area source accidental fire categories is as follows:

    Base Year(s) Emissions county,pollutant =

    Activity Data × Emission Factorpollutant × Control Factorpollutant × Fractioncounty × GWP pollutant

    Where:

    • Base Year: is a year for which emissions data is directly reported by CARB and available.
    • Activity Data: is the total regional throughput or activity data for applicable base year(s).
    • Emission Factorpollutant: is a factor that allocates an amount of emissions, in mass, of a particular pollutant by unit of activity data.
    • Control Factorpollutant : is a fractional ratio (between 0 and 1) that captures the estimated reduction in emissions as a result of Air District rules and regulations.
    • Fractioncounty : is the fraction of total regional emissions (between 0 and 1) estimated to be allocated to a particular county.
    • GWPpollutant is the Global Warming Potential of a particular 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 Emissionscounty = Base Year(s) Emissioncounty 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.

    Depending on the source categorization, criteria air pollutants emissions are available from CARB in three databases: On-Road Model, Off-Road Model, and California Emissions Projection Analysis Model (CEPAM). From these models, the Air District either collects emissions data from these categories and when not available, derives missing GHG data or obtains them directly from CARB. For structural fires (category 750) and automobile fires (category 753), GHG emissions are derived from the statewide CEPAM inventory (CARB, 2024). For all vegetation fires (category 1580), the Air District obtains the GHG emissions data by directly contacting CARB as the latest base year emissions are not publicly available by county.

    Because CEPAM inventory only includes county-level criteria air pollutant (CAP) emissions for structural fires (category 750) and automobile fires (category 753), including those of particulate matter (PM), nitrogen oxides (NOx), carbon monoxide (CO), total and reactive organics (TOG and ROG, respectively), the Air District applies surrogate methods to estimate county-level GHG emissions by using specific CAP emission factors as surrogate for ratioing the emissions.

    A detailed description of how surrogate methods are used to populate CH4 and N2O emissions for accidental fire categories is described in the next section.

    Emissions Factors and Apportionment

    Structural Fires (category 750) & Automobile Fires (category 753)

    For structure fires (category 750) and automobile fires (category 753), the emission factors (EFs) for CO, NOx, CO2, CH4, and N2O are based on averages, weighted based on relative proportion of fuel material burned where more weight (significance) is assigned to the larger contributors. Category specific composite EFs are derived from the United States Environmental Protection Agency (USEPA)’s AP-42 document (USEPA, 2024) and are listed in the table below.

    Fire Type

    CO

    NOx

    CO2

    CH4

    N2O

    Structural Fire

    215.04

    5.12

    3133.4

    7.25

    0.115

    Automobile Fire

    31.25

    1

    783.5

    2.5

    0.169

    Since the CEPAM inventory only provides emissions for CAPs, CO2, CH4 and N2O emissions are estimated by first deriving category specific emission ratios (ER) by dividing two known pollutants’ EFs and then multiplying that ER with known emissions of one pollutant to produce unknown emissions of another pollutant as shown below:

    • CO2 = CO, CEPAM × (CO2 / CO)
    • CH₄ = CO, CEPAM × (CH₄ / CO)
    • N₂O = NOx, CEPAM × (N₂O / NOx)

    For example, ERs (CO2/CO and CH4/CO) are applied to the surrogate CO emissions from CEPAM to derive county-level CO2 and CH4 emissions, respectively. Similarly, an ER of N2O/NOx is applied to NOx base year emissions from CEPAM to derive county-level N2O emissions. Also, an example of an emission calculation is provided in the Sample Calculation subsection of this document.

    Vegetation Fires (category 1580)

    For all vegetation fires (category 1580), CARB calculates emissions using FOFEM. The composite emission factors for different types of fuel materials burned (deadwood, surface fuels, tree-specific types, shrubs, and herbaceous plants) as well as other inputs needed to complete the emission calculation are embedded in the model.

    Unlike structural and automobile fires, for all vegetation fires (category 750), the CO2, CH4 and N2O emissions are more complex to generate and require predictive modeling to accurately estimate the base year county-specific emissions. The Air District uses updated county specific GHG emissions from CARB (CARB, 2025) instead of applying surrogates to outdated information from CEPAM.

    County Fractions

    County fractions are presented in the following table and are based on CO (for CO2 and CH4) and NOx (for N2O) emissions distribution across SFBA based on CEPAM.

    ID Description ALA CC MAR NAP SF SM SNC SOL SON
    1580 Accidental Fires - All Vegetation 0.38 0.19 0.03 0.28 0.00 0.05 0.02 0.00 0.06
    750 Accidental Fires - Structural 0.21 0.15 0.04 0.02 0.13 0.10 0.23 0.06 0.07
    753 Accidental Fires - Automobiles 0.21 0.15 0.03 0.02 0.11 0.10 0.25 0.06 0.07

    Control Factors / Emission Controls

    Accidental fires are typically unexpected and unintentional events and therefore difficult to predict and control. As such, there are no current Air District rules that affect activity or emissions for accidental fire categories. However, for all vegetation fires (category 1580), although there are no controls, California adopted the Wildfire and Forest Resilience Action Plan in 2021 (CFMTF, 2021). This plan sets guidelines and practices on forest management in California to mitigate wildfires by actively diminishing fuel accumulation through prescribed burns, thinning dense woodlands, and establishing fuel breaks. The objective is to cultivate healthier, more resilient forests that are less susceptible to catastrophic wildfires. Although the plan does not add controls, it potentially reduces the intensity, scope, and frequency of vegetation wildfires thereby reducing emissions.

    Historical Emissions / Backcast

    Historical GHG emissions are derived from the same source and methodology as base year emissions for each category. For base year 2022, structural fires (category 750) and automobile fires (category 753) emissions are obtained from the CEPAM inventory. As the CEPAM inventory does not extend back beyond the year 2000, structural fires (category 750) emissions are adjusted using normalized household population data from 1990 to 1999 (BAAQMD, 2015), while automobile fires (category 750) are adjusted with normalized human population data from the same period. These SFBA-specific growth profiles are originally derived from previous versions of the forecasting database generated by the Association of Bay Area Governments (ABAG, 2021). For all vegetation fires (category 1580), the historical emissions are estimated by CARB (CARB, 2025) back up to the year 2000. To backcast the vegetative fires emissions for the year 1990-1999 time period, the Air District applies the five-years average for years 2000 to 2004 to all years before 2000.

    Future Projections / Growth Factor

    Similar to historical emissions, future projections are also obtained from the same source and methodology as base year emissions for each category. For structural fires (category 750) and automobile fires (category 753), projected emissions from the years 2023-2050 are from CEPAM. For all vegetation fires (category 1580), CARB provide annual emissions up to the year 2023. Projected emissions beyond 2023 are based on a five-year average of emissions from years 2018 to 2023 (excluding 2020), similar to the approach used to backcast emissions. The year 2020 is an abnormally high wildfire year with emissions exponentially higher than previous years and therefore is considered an outlier. The average emission value is used to populate emissions for all years from 2024 to 2050.

    Sample Calculations

    The table below shows an example calculation to estimate base year 2022 GHG emissions in units of metric tons of CO2 equivalents (MTCO2eq) from structural fires (category 750) in Sonoma County.

    Step 1

    Obtain CO and NOx emissions for Sonoma County from CEPAM
    (tons/day)

    CO = 0.248

    NOx = 0.006

    Step 2

    Gather structural fires composite emission factors for CO, CO2, CH4, NOx, and N2O from USEPA AP-42 (lbs/fire)

    COef = 215.04

    NOxef = 5.12

    CO2ef = 3133.4

    CH4ef = 7.25

    N2Oef = 0.115

    Step 3

    Derive Emission Ratios (ERs)

    CO2ef/COef = 14.57

    CH4ef/COef = 0.0337

    N2Oef/NOxef = 0.0225

    CO2

    CH4

    N2O

    Step 4

    Calculate emissions for CO2, CH4, and N2O. Then convert the emissions units to metric tons/year:

    CO2 = CO x CO2ef/COef

    CH4 = CO x CH4ef/COef

    N2O = NOx x N2Oef / NOxef

    (MT)/year)

    0.248 tons/day

    × 14.57

    × 365 day/year

    × 0.9072 MT/ton

    = 1196.48

    0.248 tons/day

    × 0.0337

    × 365 day/year

    × 0.9072 MT/ton

    = 2.77

    0.006 tons/day

    × 0.0225

    × 365 day/year

    × 0.9072 MT/ton

    = 0.045

    Step 5

    Global Warming Potential from IPCC

    1

    34

    298

    Step 6

    Calculate the total CO2 equivalent emissions using the GWP (MTCO2eq/year)

    1196.48

    × 1

    = 1196.48

    2.77

    × 34

    = 94.18

    0.045

    × 298

    = 13.41

    1196.48

    + 94.18

    + 13.41

    = 1304.07 MTCO2eq/year

    Assessment of Methodology

    The general methodology for determining emissions for these categories has not changed, although all of the data inputs have been updated.

    Base Year

    Revision

    Reference

    2022

    1. GHG emissions (structural and automobile fire categories) derived from CARB’s CEPAM Inventory
    2. GHG emissions (all vegetation fires) obtained from CARB
    3. Review and updated emission factors
    4. Average household and human population to backcast emissions using ABAG historical growth profile
    5. Used Global Warming Potential (GWP) from IPCC
    1. CARB, 2024
    2. CARB, 2025
    3. USEPA, 1973
    4. BAAQMD, 2015; ABAG, 2021
    5. IPCC, 2014

    2015

    1. Emissions are derived by the Air District using projection of emissions from the BY2011 GHG inventory
    2. Used Global Warming Potential (GWP) from IPCC
    3. Updated household and human population growth profile using ABAG population growth profile
    1. BAAQMD, 2015
    2. IPCC, 2014
    3. BAAQMD, 2015
    4. BAAQMD, 2015; ABAG, 2021

    Emissions

    The table below shows the total GHG emissions by pollutant in MTCO2eq for accidental fire categories.

    ID Description CH4 CO2 CO2_bio N2O Total
    1580 Accidental Fires - All Vegetation 1404.4 0.0 17836.9 740.9 19982.2
    750 Accidental Fires - Structural 1330.1 16908.8 0.0 186.2 18425.1
    753 Accidental Fires - Automobiles 26.1 239.2 0.0 16.6 281.9

    Summary of Base Year 2022 Emissions

    Structural fires (category 750) and automobile fires (category 753), and all vegetation fires (category 1580) produce minor quantities of CO2, CH4, and N2O emissions. In comparison to other emissions in their respective sectors, all three accidental fires categories contribute negligibly, accounting for significantly less than 1% of their sector’s GHG emissions.

    Contribution of Accidental Fires Emissions by Sector
    Subsector Sector Subsector GHG Emissions (MMTCO2eq) Sector GHG Emissions (MMTCO2eq) % of Sector
    Accidental Fires Agriculture 0.002 1.26 0.17%
    Accidental Fires Industrial 0.02 17.90 0.10%
    Accidental Fires Transportation 0.000 22.60 0.001%

    Contribution of Accidental Fires Emissions to Regional Total
    Subsector Subsector GHG Emissions (MMTCO2eq) Regional Total GHG Emissions (MMTCO2eq) % of Regional Total
    Accidental Fires 0.02 65.68 0.03%

    Trends

    The time series chart below shows the GHG emission trends for structural fires (category 750), automobile fires (category 753), and all vegetation fires (category 1580) categories.

    Summary of Trends

    Activity associated with structural fires (category 750) and automobile fires (category 753) are household and population dependent and therefore, have generally increased year after year due to the steady increase in SFBA’s household and population data. The only notable decrease in the trend for these two categories is in 2000-2002 where there is a slight dip in the emissions, likely due to a decrease in households and SFBA population resulting from the 2000 recession where many dot-com companies collapsed. For all the other years, the emission trend is observed to be slightly upward.

    For all vegetation fires (category 1580), the emissions trend fluctuates year to year as per the occurrence and magnitude of vegetation fires for any given year. The size may be minimal in years with few or no vegetation fires and very extensive in years with severe vegetation fires. The years 2017 and 2020 witnessed unprecedented wildfires in the SFBA, specifically the Tubbs, Nun, and Atlas fires in 2017, and the Glass, Complex, and Hennessey fires in 2020. Wildfires are anticipated to markedly escalate due to future climate change, predominantly defined by elevated temperatures and diminished precipitation, resulting in arid conditions that render vegetation more vulnerable to ignition and swift fire propagation. Because vegetation fires are extremely variable and their occurrences are unpredictable, the forecasted emissions are based upon an average of data from recent past and are held constant for future years.

    Uncertainties

    The main uncertainty in the updated methodology arises from the use of composite emission factors in automobile and structure fires. Depending on the manufacturer and the year of construction, a wide range of materials are used to construct cars and other structures. The burning of materials from these sources might have a wide range of emission factors, leading to a large uncertainty. Additionally, the EFs themselves are seldom verified and validated against measurements, in part due to the difficulty in measuring process emissions from area sources. The EFs represented herein this inventory are from global literature and not validated against local conditions and/or practices.

    Additionally, wildfire events are unpredictable, large on a spatial scale, and could last for days and even months. The accuracy and resolution of the underlying wildfire perimeters and vegetation fuel beds data, the assumption to use fuel moisture value of the ignition start date and the centroid of the wildfire polygon while computing fuel consumption, and the assumption that all areas within the wildfire perimeter experienced the fire, all contribute to a high magnitude of uncertainties in emissions estimates for the category.

    Contact

    Author: Tan Dinh

    Reviewer: Abhinav Guha

    Last Update: 07/21/2025

    References

    ABAG. 2021. Plan Bay Area 2050, Association of Bay Area Governments. https://planbayarea.org/finalplan2050

    BAAQMD. 2015. Base Year 2015 Criteria Air Pollutant Emission Inventory Methodology, Accidental Structural and Automobile Fires Category, Bay Area Air Quality Management District. https://baaqmd.github.io/BY2015-methodology/10-misc.html. Accessed February 2025.

    CARB. 1999. Section 7.14 Methodology on Structure and Automobile Fires, California Air Resources Board. https://arb.ca.gov/ei/areasrc/fullpdf/full7-14.pdf

    CARB. 2016. California’s 2000-2014 GHG Inventory - Technical Support Document, California Air Resources Board. https://ww2.arb.ca.gov/sites/default/files/classic/cc/inventory/ghg_inventory_tsd_00-14.pdf

    CARB. 2020. Public Comment Draft on Greenhouse Gas Emissions of Contemporary Wildfire, Prescribed Fire, and Forest Management Activities, California Air Resources Board. https://ww2.arb.ca.gov/sites/default/files/classic/cc/inventory/pubs/ca_ghg_wildfire_forestmanagement.pdf

    CARB. 2023. Wildfire Emission Estimate for 2022 Errata. California Air Resources Board. Wildfire Emission Estimates for 2022 ERRATA FINAL.pdf

    CARB. 2024. California Emissions Projection Analysis Model 2024, CEPAM2019v1.04, California Air Resources Board. https://ww2.arb.ca.gov/applications/cepam2019v1-04-standard-emission-tool. Accessed 2024.

    CARB. 2025. All vegetation category emissions data request and fulfillment by CARB, California Air Resources Board. February 2025. Data available on request.

    CFMTF. 2021. California’s Wildfire and Forest Resilience Action Plan, California Forest Management Task Force. January 2021. https://wildfiretaskforce.org/wp-content/uploads/2022/04/californiawildfireandforestresilienceactionplan.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.)]. Intergovernmental Panel for Climate Change, Geneva, Switzerland. 151 pp. https://www.ipcc.ch/site/assets/uploads/2018/02/SYR_AR5_FINAL_full.pdf

    Lutes, D. 2020. First Order Fire Effects Model: FOFEM 6.7 User’s Guide. USDA Forest Service, Rocky Mountain Research Station. Fire, Fuel, Smoke Science Program. https://www.firelab.org/project/fofem

    USEPA. 2024. Compilation of Air Pollutant Emission Factors, AP-42, Section 2.5 and 2.6, United States Environmental Protection Agency. https://www.epa.gov/air-emissions-factors-and-quantification/ap-42-compilation-air-emissions-factors-stationary-sources