Canada’s Black Carbon Inventory Report 2022: 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], 2022). This chapter gives an overview of the development of the black carbon inventory. For more details on the air pollutant emissions inventory development, refer to Chapter 3 of the APEI.
3.1 Methodology - black carbon as a fraction of particulate matter less than or equal to 2.5 microns in diameter
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 (PM2.5), and only PM2.5 emissions resulting from combustion contain significant amounts of black carbon. Therefore, for most sources, the basis for the black carbon inventory is the PM2.5 emitted from combustion processes, multiplied by the BC/PM2.5 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 PM2.5, they are not considered sources of black carbon in this inventory.
For example, diesel engines have relatively high emission rates of PM2.5 per unit energy, and the fraction of black carbon in these PM2.5 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 PM2.5 emissions include solid fuel combustion units, such as coal- and wood-fired boilers and wood fireplaces. Industrial sources are generally equipped with highly effective PM2.5 controls on boiler emissions, with PM-control efficiencies often in the 90% range. This is reflected in the lower PM2.5 emissions compared with other sources. In contrast, the smaller and markedly different equipment used for residential wood combustion (fireplaces, wood stoves or furnaces) have poorer PM2.5 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 PM2.5 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/PM2.5 fraction for wood devices than for diesel engines.
The dataset that breaks down the PM2.5 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, 2014a) to calculate black carbon emissions from compiled combustion PM2.5 emissions. Several PM2.5 speciation profiles are specific to the combustion processes or technologies (e.g. appliance types for residential wood combustion), 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 PM2.5 emissions data from combustion were used directly with BC/PM2.5 fractions to estimate black carbon emissions. Annex 2 lists all BC/PM2.5 fractions used in this inventory. Separating combustion from non-combustion sources of PM2.5 remains a challenge in some cases because of a lack of data on activities (i.e. quantity of fuel burned) and on non-combustion sources (e.g. rock dust at a mine). In those cases, separating combustion PM2.5 from non-combustion PM2.5 is done on the basis of expert knowledge of the relevant activities prior to applying BC/PM2.5 fractions.
To estimate emissions from mobile sources, bottom-up approaches were 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, PM2.5 was estimated first, and BC/PM2.5 fractions were subsequently applied. The methods for estimating PM2.5 emissions from mobile sources are described in the APEI Report (ECCC, 2022).
3.2 Use of facility reported emissions
Only PM2.5 emissions resulting from combustion contain significant amounts of black carbon. In the APEI, PM2.5 emission estimates are calculated using a variety of data sources, notably emission estimates reported by Canadian facilities to the National Pollutant Release Inventory (NPRI). For sources that are incompletely covered by PM2.5 estimates reported to the NPRI, PM2.5 emissions are calculated in-house using activity data, statistics 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, 2019). Emissions due to agricultural, construction and residential (wood and other) fuel combustion are estimated from data on fuel consumption and combustion technologies. Commercial Fuel Combustion is estimated using a combination of facility-reported and other data sources.
Stack emissions of PM2.5 reported by facilities form the basis of black carbon estimates from facility-reported data. For each individual stack, the appropriate black carbon speciation factor (or factors) was applied to the combustion-related PM2.5 (Annex 2). The emissions are then summed at the facility level and aggregated to form the sectoral emission estimate.
As new data and methodologies become available, emission estimates from previous inventory editions are recalculated. Table 3–1 presents the main improvements to the estimation methodologies for this year’s inventory.
|Description||Impact on emissions|
|Ore and Mineral Industries|
Recalculations occurred in the Aluminium Industry sectors for years 2013 to 2019 as a result of revised facility reporting of PM2.5 emissions in the Aluminium Industry sector and a better understanding of processes in these sectors, allowing for more accurate assignment of speciation factors.
Recalculations in the Aluminium Industry sector occurred for all years of the time series, ranging from a maximum decrease of 0.95 tonnes (2.1%) in 2014 to a maximum increase of 0.28 tonnes (0.55%) in 2013.
|Oil and Gas Industry|
Recalculations occurred due to updates to the methodology used to estimate flaring emissions from oil and gas operations in Saskatchewan. The updated methodology uses operator reported volumes of flared gas (SK MER, 2013-2020) and gas composition data by production class provided by the Saskatchewan Ministry of Energy and Resources (SK MER, 2021) allowing the updated methodology to reflect regional variability within the province. Using the gas composition data, the higher heating value (HHV) is calculated for each production class, enabling the direct estimation of black carbon emissions using the empirical relationship between HHV and black carbon emissions established by the Quadram study (2019). This methodology is used to estimate black carbon emissions from flaring in Saskatchewan for the following oil and gas sectors: Natural Gas Production and Processing, Light/Medium Crude Oil Production, Heavy Crude Oil Cold Production and In-situ Oil Sands Production.
These recalculations resulted in upward revisions to emissions for the oil and gas sector in all years (from 2013 to 2019), with the changes ranging from 330 tonnes (14.5%) in 2019 to 649 tonnes (26.4%) in 2014.
Recalculations occurred in the Pulp and Paper Industry sector and Wood Products sector for years 2016 to 2019 as a result of revised facility reporting of PM2.5 emissions.
Recalculations in the Pulp and Paper Industry sector and Wood Products sector ranged from a maximum decrease of 1.3 tonnes (0.72%) in 2016 to a maximum increase of 23 tonnes (15%) in 2019.
|Transportation and Mobile Equipment – Rail|
Recalculations occured in the rail transportation sector. Provincial activity data was updated to reflect the amount of fuel consumed within a geographical region whereas the previous model was based on fuel supplied to a geographical region.
The recalculations to the rail model did not significantly affect the national number but reallocated fuel between provinces resulting in significant provincial recalculations.
|Commercial/Residential/Institutional – Home Firewood Burning|
Recalculations occured in the commercial/institutional and residential sector in all years back to 2013. Recalculations occured due to updated fuel consumption data in the Report on Energy Supply and Demand in Canada, and the Households and the Environment Survey.
The recalculations resulted in changes ranging from -7 kt in 2015 to 166 kt in 2018. The recalculations for 2019 resulted in an increase of 62 kt.
3.4 Sources of uncertainty
A key source of uncertainty associated with black carbon inventories is the inconsistencies 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/PM2.5 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/PM2.5 fractions can be seen with the application of the diesel BC/PM2.5 fraction for aviation turbo fuel in jet aircraft, as there is no available fraction specific to aviation turbo fuel. Similarly, a single BC/PM2.5 fraction is applied to all residential wood combustion appliances except wood furnaces (Annex 3, Table A3–1). The refinement of BC/PM2.5 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 stack names), with varying degrees of accuracy.
There is considerable uncertainty in determining the proportion of combustion PM2.5 emissions from industrial sources. The primary data source for estimating PM2.5 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 not broken down between combustion and non-combustion emissions. For some sectors (such as Aluminium, Pulp and Paper, and Cement and Concrete industries), it is assumed that the PM2.5 emissions are combustion-related when emissions of both CO and NOx are reported from the same stack; this assumption contributes to the overall uncertainty.
3.5 Considerations for future editions of this inventory
Future improvements will focus on expanding current coverage, as well as improving the accuracy of emission estimates, including 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/PM2.5 fractions for the off-road transportation
- review and update the BC emission factors for marine transportation
- 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 Non-Ferrous Refining and Smelting and the Chemicals Industry
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. 2021. Canada’s air pollutant emissions inventory report 1990–2019: The Canadian government’s submission under the Convention on Long-Range Transboundary Air Pollution to the United Nations Economic Commission for Europe (March 2020).
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.
[SK MER] Saskatchewan Ministry of Energy and Resources. 2013−2020. Saskatchewan fuel, flare and vent [accessed 2021 Jul 16].
[SK MER] Saskatchewan Ministry of Energy and Resources. 2021. Gas composition by production class. Unpublished. Provided to Environment and Climate Change Canada [2021 Jul 13].
Statistics Canada. 2017. Household and the environment survey, 2017. [accessed 2019 Sep 13].
[U.S. EPA] United States Environmental Protection Agency. 2014a. SPECIATE 4.4. [accessed 2021 Feb 12].
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