Canada’s Black Carbon Inventory Report 2024: chapter 3

Black carbon inventory development

As mentioned in the introduction, the Black Carbon (BC) Inventory is based on the Air Pollutant Emissions Inventory (APEI) (Environment and Climate Change Canada [ECCC], 2024). This chapter gives an overview of the development of the Black Carbon Inventory. For more details on the APEI development, refer to Chapter 3 of the APEI Report (ECCC, 2024).

3.1 Overview of Methodology to Calculate Black Carbon Emissions

Two important assumptions underlie the present inventory: black carbon is predominantly emitted in particulate matter less than or equal to 2.5 microns in diameter (PM_2.5), and only PM_2.5 emissions resulting from combustion contain significant amounts of black carbon. Therefore, for sources where BC emissions are not directly calculated, emissions are based on the PM_2.5 emitted from combustion processes and multiplied by the BC/PM_2.5 fractions specific to each type of source. Although non-combustion sources, such as dust raised by traffic on paved and unpaved roads or by wind, and machinery on open fields or mine sites, can be significant sources of PM_2.5, they are not considered sources of black carbon in this inventory.

For example, diesel engines have relatively high emission rates of PM_2.5 per unit energy, and the fraction of black carbon in these PM_2.5 emissions is also relatively high. The majority of diesel fuel in Canada is used for mobile sources, including off-road applications. Other combustion sources with high PM_2.5 emissions include solid fuel combustion units, such as coal- and wood-fired boilers and wood fireplaces. Industrial sources are generally equipped with PM_2.5 controls on boiler emissions, with PM-control efficiencies often in the 90% range. This is reflected in their lower PM_2.5 emissions compared to other sources. In contrast, the smaller and markedly different equipment used for residential wood combustion (fireplaces, wood stoves or furnaces) have poorer PM_2.5 control efficiencies than larger units, notwithstanding the different types of fuel and firing practices used for burning firewood. Given their lower efficiency, combined with the lack of treatment of stack gases for many existing residential wood-burning devices, such devices are by far the largest source of combustion-related PM_2.5 emissions in Canada. Nonetheless, black carbon emissions from residential wood burning are only slightly more than one third that of mobile sources due to a lower BC/PM_2.5 fraction for wood devices than for diesel engines.

The dataset that breaks down the PM_2.5 emitted from a particular source (e.g., diesel engine emissions) into its different components, including black carbon and organic carbon, is known as a speciation profile. Most speciation profiles contain a fraction for elemental carbon; these fractions are commonly used as a surrogate to quantify black carbon emissions. The current inventory relies primarily on the United States Environmental Protection Agency’s (U.S. EPA) SPECIATE database (U.S. EPA, 2022) to calculate black carbon emissions from compiled combustion PM_2.5 emissions. Several PM_2.5 speciation profiles are specific to the combustion processes or technologies (e.g., appliance types for residential wood combustion), to the subsector classification (e.g., concrete batching and products), to the fuel type (e.g., diesel, gasoline, natural gas) or to the application (e.g., natural gas use for electrical power generation).

Where readily available, the PM_2.5 emissions data from combustion are used directly with BC/PM_2.5 fractions to estimate black carbon emissions. Annex 2 lists all BC/PM_2.5 fractions used in this inventory. For example, estimates for Agricultural Fuel Combustion sources are based on the fuel type and quantity consumed in Canada and the corresponding BC/PM_2.5 fraction.

Some activity data does not specify whether PM_2.5 is derived from combustion or non-combustion sources. In these cases, separating combustion from non-combustion sources of PM_2.5 remains a challenge because of a lack of data on activities (i.e., quantity of fuel burned) or on contributions from non-combustion sources (e.g., rock dust at a mine). In those cases, separating combustion PM_2.5 from non-combustion PM_2.5 is done on the basis of expert knowledge of the relevant activities prior to applying BC/PM_2.5 fractions. For example, National Pollutant Release Inventory (NPRI) facility-reported data of PM_2.5 releases from stacks form the basis of black carbon estimates. For each individual stack, the appropriate black carbon speciation factor (or factors) is applied to the combustion-related PM_2.5 (Annex 2). The emissions are then summed at the facility level and aggregated to form the sectoral emission estimate.

For sources of PM_2.5 that are not covered by NPRI reporting requirements, their PM_2.5 emissions are calculated using activity data (i.e., statistics datasets) and emission factors. For this inventory, emissions from Manufacturing, Electric Power Generation as well as Ore and Mineral Industries are estimated using facility data. Oil and Gas Industry estimates are based on facility-reported data used in combination with the results of independent studies (EC, 2014; ECCC, 2017; Quadram Engineering Ltd, 2019). Emissions due to agricultural, construction and residential (wood and others) fuel combustion are estimated from fuel consumption data and combustion technology information. Commercial Fuel Combustion is estimated using a combination of facility-reported and other data sources. Other notable methodologies that are used to estimate black carbon emissions at the sector level include:

• In some upstream oil and gas subsectors, black carbon emissions from flaring are directly calculated using the volume of flared gas, the higher heating value (HHV) of the gas, and an empirical equation relating the HHV to black carbon emissions (Quadram Engineering Ltd, 2019).
• To estimate emissions from mobile sources, bottom-up approaches are adopted, i.e., applying fuel-specific emission factors to disaggregated activity data, such as vehicle or equipment data sorted by class, age or model year.
  • In most cases, PM_2.5 is estimated first, and BC/PM_2.5 fractions are subsequently applied. For Road Transportation, elemental carbon (as a proxy for BC) is taken directly from the MOVES model output.
  • The methods for estimating PM_2.5 emissions from mobile sources are described in the APEI Report (ECCC, 2024).

3.2 Recalculations

As new data and methodologies become available, emission estimates from previous inventory editions are recalculated to provide a consistent and comparable trend in emissions. Recalculations occur annually for numerous reasons, including the following:

• correction of errors detected by quality control procedures
• incorporation of updates to activity data including changes to data sources
• reallocation of activities to different categories (which will affect subtotals)
• refinements of methodologies and emission factors
• inclusion of categories previously not estimated (which improves inventory completeness)

New stack information was reported by facilities because of updated NPRI reporting requirements, as specified in the 2022–2024 Canada Gazette notice^{Footnote 1} . Some sector emissions for 2013–2021 were recalculated based on this new stack information; this is the case mainly for sectors under Ore and Mineral Industries and Manufacturing categories.

Table 3–1 presents the main improvements and updates to the estimation methodologies for this year’s inventory.

Total emissions for black carbon and PM_2.5 were revised for all years as presented in Figure 3–1 and Figure 3–2. Overall, recalculations of previously reported 2013–2021 estimates did not result in a significant change in emissions. The trends between 2013 and 2021 remained constant for the previous and current submission (-30% for black carbon emissions and around -20% for PM_2.5 emissions). The difference between the black carbon and PM_2.5 emission trends is, as mentioned above, due to some sectors not using PM_2.5 to estimate emissions.

Table 3.1: Summary of Methodological Changes, Refinement or Improvements

Figure 3.1 Comparison of Black Carbon Emission Trends (2024 vs 2023 Inventory Edition)

Figure 3.2 Comparison of PM_2.5 from Combustion Emission Trends (2024 vs 2023 Inventory Edition)

3.3 Sources of Uncertainty

A key source of uncertainty associated with black carbon inventories is inconsistency between definitions and measurements of black carbon (Bond et al., 2013). Scientists use different methods to measure black carbon particle emissions at the source and in the atmosphere, and therefore measured quantities are not strictly comparable.

Although not quantified, uncertainty in the black carbon estimates in this inventory stems partly from the uncertainty around the BC/PM_2.5 fractions. There is large variability in the size of measurement samples used to derive these fractions; the same fractions can by default be applied to several different technologies. An example of the limitation of available BC/PM_2.5 fractions can be seen with the application of the diesel BC/PM_2.5 fraction for aviation turbo fuel in jet aircraft, as there is no available fraction specific to aviation turbo fuel. Similarly, a single BC/PM_2.5 fraction is applied to all residential wood combustion appliances except wood furnaces (Annex 3, Table A3–1). The refinement of BC/PM_2.5 fractions is dependent on new measurements. Assignment of fractions to sector or equipment type is made using engineering knowledge and judgment based on limited available information (such as facility stack information), with varying degrees of accuracy.

There is considerable uncertainty in determining the proportion of combustion PM_2.5 emissions from industrial sources. The primary data source for estimating PM_2.5 emissions from many industrial sources is the NPRI, in which emissions are reported by facilities by stack or as one aggregate value for the facility as a whole and are mostly not broken down between combustion and non-combustion emissions.

3.4 Considerations for Future Editions of this Inventory

Future improvements will focus on expanding current coverage, as well as improving the accuracy of emission estimates. Examples include the following:

• Explore incorporating emissions from diesel engines used for electricity generation in remote locations that are not currently reporting emissions to the NPRI.
• Review and update the BC/PM_2.5 fractions for off-road transportation.
• Review and update the BC emission factors for marine transportation.
• Update BC emissions from residential wood combustion.
• Include emissions from prescribed burning, which is the controlled and intentional burning of biomass as a land management practice.
• Explore incorporating emissions from missing industrial sectors, such as the Chemicals Industry.
• Incorporate BC emissions from waste incineration sources.
• Review and integrate new stack data, collected by the NPRI as per the updated reporting requirements in the 2022–2024 Canada Gazette notice, for other sectors in the Ore and Mineral Industries and Manufacturing source categories.

References, Chapter 3, Black Carbon Inventory Development

Bond TC, Doherty SJ, Fahey DW, Forster PM, Berntsen T, DeAngelo BJ, Flanner MG, Ghan S, Kärcher B, Koch D, et al. 2013. Bounding the role of black carbon in the climate system: a scientific assessment. Journal of Geophysical Research. 118(11): 5380–5552.

[EC] Environment Canada. 2014. Technical Report on Canada’s Upstream Oil and Gas Industry. Vols. 1–4. Calgary (AB): Prepared by Clearstone Engineering Ltd.

[ECCC] Environment and Climate Change Canada. 2017. An Inventory of GHG, CAC and Other Priority Emissions by the Canadian Oil Sands Industry: 2003 to 2015. Vols 1–3. Calgary (AB): Prepared by Clearstone Engineering Ltd.

[ECCC] Environment and Climate Change Canada. 2024. Canada’s Air Pollutant Emissions Inventory Report 1990–2022: The Canadian Government’s Submission under the Convention on Long-Range Transboundary Air Pollution to the United Nations Economic Commission for Europe (March 2024).

Quadram Engineering Ltd. 2019. A Black Carbon Inventory for Gas Flaring in Alberta’s Upstream Oil and Gas Sector. Unpublished report. Prepared for Environment and Climate Change Canada.

[U.S. EPA] United States Environmental Protection Agency. 2022. SPECIATE 5.2. [accessed 2023 Dec 8].