Canada’s Air Pollutant Emissions Inventory Report 2020: annex 2

In-house estimation methodologies: continued

A2—8: Estimation methodologies for Paints and Solvents by sector/subsector

Dry Cleaning, General Solvent Use, Printing and Surface Coatings


Dry Cleaning includes emissions from companies that provide dry cleaning of fabric and leather items.

General Solvent Use consists of emissions from a broad range of applications occurring in residential, commercial, industrial and institutional settings. Industrial applications include uses such as degreasing, adhesives and sealants, aerosols, blowing agents and resin manufacturing. The use of consumer and commercial products, pesticides and personal care products is also included under General Solvent Use.

Printing covers emissions from the manufacturing or use of printing inks. The sector consists of flexographic, gravure, letterpress, lithographic and other printing.

Surface Coatings encompasses emissions from a broad range of applications and industries, including individuals and companies engaged in the manufacturing or use of paints and coatings.

General inventory method

Pollutant(s) estimated:

The analysis methodology used is largely a “top-down” national mass balance approach that involves gathering statistical activity data on the production, distribution, end-use patterns and disposal of VOC-containing products and then building relationships between stages. More detailed data on solvent quantities and practices are collected from a subset of solvent and formulated product users, producers and distributors in Canada.

Activity data

Solvent use quantities (1990 to 2004): Cheminfo Services, 2007

Solvent use quantities (2005 to 2018): Cheminfo Services, 2016a

Domestic consumption is determined using a national mass balance approach. Information on production, trade and inventory changes is obtained from various literature sources, Statistics Canada and interviews with a subset of solvent producers and distributors.

Projected estimates of national total solvent use for the years 2015–2018 were developed based on historical base year national total solvent use and macroeconomic growth and solvent growth ratios (Cheminfo Services, 2016b).

Macroeconomic growth data (GDP by NAICS): Statistics Canada, n.d.

Emission factors (EF)

The estimated use of emission control technologies is applied in each solvent application area. More specifically, emissions are calculated by taking the estimated quantity of solvent used in an application area multiplied by the estimated percentage of uncontrolled VOCs or:

EVOCs = Quantitysolventused  × (100%–% VOCscontrolled)

where EVOCs is the emission estimate of VOCs.

If there is no estimated use of control technologies, then 100% of the solvent VOCs is assumed to evaporate. Only a small portion of the estimated VOC emissions is reduced by the application of control technologies. Control efficiencies are applied (as percentages) in the following applications: flexographic, rotogravure and lithographic printing, aircraft coatings, automotive original equipment manufacture (OEM) coatings, metal can manufacturing, metal coil coating, metal furniture manufacturing, adhesives and sealants, and resin manufacturing (Cheminfo Services, 2016a).

A2—8 References

Cheminfo Services. (2007). Volatile organic compound (VOC) emissions from the use of solvents in Canada – Inventory improvement and trends compilation - Task #2: VOC emission trends compilation 1985-2005, Unpublished report. Markham (ON): Cheminfo. Prepared for Environment Canada.

Cheminfo Services. (2016a). Compilation of volatile organic compound (VOC) emissions from the use of solvents in Canada: Inventory update. VOC emission trends compilation: 2005 to 2017, Final report. Unpublished report. Markham (ON): Cheminfo. Prepared for Environment and Climate Change Canada.

Cheminfo Services. (2016b). User manual for the solvent VOC database model, Final report Version 3. Unpublished report. Markham (ON): Cheminfo. Prepared for Environment and Climate Change Canada.

Statistics Canada. (n.d.). Table 379-0031 Gross domestic product (GDP) at basic prices, by North American Industry Classification System (NAICS), monthly (dollars), CANSIM (database) [accessed 2017 Nov 8].

A2—9: Estimation methodologies for Dust by sector/subsector

Coal Transportation


Coal Transportation includes PM emissions resulting from the transportation of coal by open-top rail, truck or barge.

Most of the coal mined in Canada is carried to trans-shipment terminals (ports, for export) or to end use facilities by unit trains. Coal imported into Canada is predominantly shipped in lake and ocean vessels—some imported coal is landed directly at the end use facility; some is transported inland from import terminals by train or truck. Coal imported from central and western United States is generally transported by rail to end use facilities. Trucks are typically only used for coal shipment over shorter distances, whether to rail load-out (where it is shipped by rail the rest of the journey), or directly to the end-user / trans-shipment (port) terminals (Cope and Bhattacharyya, 2001).

Load-in and load-out losses, including transportation within the mine-site and to mine-mouth facilities, are estimated and reported by mine facilities to the NPRI as part of fugitive emissions. Emissions from fuel combustion during coal transport (diesel, gasoline or oil) are inventoried separately as part of the Transportation and Mobile Equipment source category.

General inventory method

Pollutant(s) estimated:
TPM, PM10, PM2.5

Emissions are estimated for each source-destination rail, truck or barge transportation route and summed by province.

Emission factors for TPM for each rail or truck transportation route (source-destination) are derived from the distance travelled, the emission control/dust-mitigation effectiveness, and moisture (precipitation) along the route. For each province that a route crosses, the route emissions attributed to that province are determined from the proportion of the province-segment of the route to total route length. The PM10 and PM2.5 emissions are calculated from the total particulate matter emissions based on a scaling factor.

The mass of coal transported along each route is determined on the basis of either mine production of marketable coal (for mine to port or mine to end-user) or coal demand by end-user (for imported coal to end users). Coal mine production sent to multiple destinations is proportioned on the basis of documented coal shipping volumes to each destination, reported coal demand for coal-users, or estimates from (Cope & Bhattacharyya, 2001). Where no information was available, the coal production was proportioned to the various destinations on the basis of the distance between the mine and the destination.

Activity data

Coal mine production and coal-user demand: (Statistics Canada, Table 135-0002, n.d.; Statistics Canada, Table 25-10-0048-01, n.d.; Statistics Canada, RESD, n.d.; Cope & Bhattacharyya, 2001) and company websites (accessed 2017).
Monthly climate summaries: ECCC, 2017)
Rail Transportation Network: (NRCan, n.d.)(1:1M scale used)
Mine Locations: (BC MINEFILE, 2017; AER, 2015), environmental assessment reports, and in-house remote-sensing.

Emission factors (EF)

Cope & Bhattacharyya (2001)

Construction Operations


Construction Operations include PM emissions primarily resulting from soil disturbance on construction sites. The amount of soil disturbance is related to the surface area and duration of a construction project. The geographic region, type of construction (residential, industrial-commercial-institutional [ICI], engineering) and soil characteristics are all considered.

General inventory method

Pollutant(s) estimated:
TPM, PM10, PM2.5

Residential construction

Emission factors (SNC-Lavalin Environment, 2005) are applied to the number of housing starts, the average lengths of construction (duration) and buildings-to-hectares conversion factors, by province/territory and dwelling type. The number of houses with basements, average basement area and depth (volume of earth moved) are also considered. Emission factors are corrected for soil texture using average provincial soil silt contents weighted by the areas of highest residential construction or average territorial level soil silt contents. Thornthwaite’s precipitation-evaporation (PE) index by province/territory is used to correct the emission factors for soil moisture.

ICI and engineering construction

Methodology under review

The in-house estimates for ICI were last calculated for 2012 and were carried forward to 2018.

Activity data
Residential construction

Dwelling starts: (Statistics Canada, Table 027-0009, n.d.; CMHC, 2017)

Average lengths of construction: (CMHC, 2017)

Buildings to hectares conversion factors: (SNC-Lavalin Environment, 2005)

Average basement area and depth: (SNC-Lavalin Environment, 2005)

Number of homes with basements: (SNC-Lavalin Environment, 2005)

ICI and engineering construction

Methodology under review

Emission factors (EF)
Residential construction:

TPM, PM10, PM2.5: (SNC-Lavalin Environment, 2005).

Correction factors:
% silt contentFootnote 1

Precipitation-Evaporation (PE) Index: (SNC-Lavalin Environment, 2005).

ICI and engineering construction

Methodology under review.

Mine Tailings


Mine Tailings covers emissions of particulates resulting primarily from wind erosion at mine tailings ponds located on active and inactive mine sites.

Concentrators used for mining produce both a finely-milled concentrate rich in the desired metal(s) and a solids-laden mine tailings stream. This slurry is sent to a tailings pond where the solids settle out of suspension and the supernatant solution is either recycled back in the process or discharged as effluent. It is common, though not universal practice to keep the solids in the tailings pond submerged, even when the mine is inactive or closed. If the solids are no longer submerged, fugitive particulate emissions occur through wind dispersion.

General inventory method

Pollutant(s) estimated:
TPM, PM10, PM2.5

The particulate matter dust emissions are estimated by applying an emission factor to the area of exposed mine tailings. The emission factor is from Evans and Cooper (1980), which is loosely based on wind soil-loss equations. A term to account for snow cover was added to the original equation.

EFTPM = 1.33C x A x S

where C is a weather correction factor,

A is the area of mine tailings in acres, and

S is (365 — n_days_with_snow_cover) / 365

The emission factor is for total particulate matter (TPM), with the smaller particulate matter size fractions determined as ratios of total particulate matter:

PM10 = 0.8 x TPM,

PM2.5 = 0.2 x TPM.

The weather correction factor C, is calculated from the equation:

C = 0.345(V30)3 / PE2

where, V30 is the average annual wind speed at 30 ft elevation (miles per hour)

PE is the Thornthwaite Precipitation-Evaporation index, calculated as

PE = 115 ∑ [ P / (T-10) ](10/9)   (sum of monthly)

where P is precipitation in inches, T is the temperature in Fahrenheit or 28.4 °F, whichever is greater.

The weather correction factor, C, is determined for each province, by year using monthly surface wind speed (CCMP, n.d), precipitation (CRU 4.03, 2019) and temperature (CRU 4.03, 2019). All data sources ranged from spatial resolution of 0.25x0.25 to 1x1 degree latitude/longitude resolution.

The snow cover correction is applied as a single provincial value (full time-series data was not available). Days with snow cover taken as the mean number of days with snow cover greater than 5cm. Snow cover data was obtained from Canadian Meteorological Centre (CMC, 2019) Daily Snow Depth Analysis, using 2000 to 2018 data, except years with missing data (2003-5, and 2008).

The mine tailings areas were measured via a remote sensing classification of mine-disturbance areas throughout the country. Mine disturbance areas were classified from Landsat-5 and Sentinel 1, and Sentinel 2 imagery for the years 1990, 2000, 2010, and 2018, using supervised random forest classification, processed using Google Earth Engine (Fuentes et al., 2020). Tailings areas are taken as one third of total mine disturbance areas, with further ‘within-mine’ classification and mapping planned as a future improvement.

The classification of mine disturbance areas was restricted to a search area consisting of a 3km buffer around known mine sites (existing or abandoned) identified in various ancillary data sources at any time between 1977 and 2016. Ancillary data sources used were: Murray et al. (1977), Natural Resources Canada, Map 900A, Producing Mines, 48th ed. (1996) to 66th ed. (2016), Parsons et al. (2012), Natural Resources Canada (NRCan), CanVec ManMade vector data (NRcan, n.d.), filtered for “Industrial Waste”, which includes tailings.

The mine-disturbance areas were manually refined and corrected in "challenging" regions for the automated classification, such as mountainous areas, badlands and high-arctic regions.

Activity data

Fuentes et al. (2019).

Emission factors (EF)

Evans and Cooper (1980) with addition of term to account for snow cover.

Paved and Unpaved Roads


Emissions from the Paved Roads sector originate from primary (road abrasion) and secondary (re-suspended) PM emissions. Emissions from unpaved roads originate from suspended or re-suspended silt from the road surface.

General inventory method

Pollutant(s) estimated:
TPM, PM10, PM2.5

Road abrasion, or primary paved road emissions, are produced by multiplying the total vehicle kilometres travelled for each province/territory by pollutant-specific emission factors.

The methodology for secondary (re-suspended) emissions is based on the US EPA AP-42 methods. Paved road emissions follow the AP-42 Section 13.2.1, 2011 update (U.S. EPA, 2011). Unpaved roads estimation methods follows the AP-42 Section 13.2.2, 2006 update methods for publicly accessible roads (U.S. EPA, 2006). In both cases, Canadian-specific traffic distribution model was used to determine traffic volume by road class, and regional distribution of traffic for application of weather correction parameters. Unpaved roads also includes facility reported emissions occurring on private roads and parking lots.

The road dust emissions are nominally the application of an emission factor to the vehicle kilometers travelled (VKT). The emission factor calculation differs for paved an unpaved roads. For paved roads, the emission factor is a function of the silt load—which in turn is a function of annual average daily traffic volume (AADT), the average vehicle fleet weight, and weather corrections for wet-days, winter silt load adjustments (to account for grit application) and snow cover. For unpaved roads, the emission factor is a function of road surface silt content, mean vehicle speeds, and surface material moisture content, a correction to remove 1980’s vehicle tailpipe, tire-wear and break wear emissions (which were included in the original model parameterization), and weather corrections for snow and frozen road surfaces.

Speeds on unpaved roads were estimated to be 70 km/hr for highway, 60 km/hr for collectors, 50 km/hr for arterial roads and resource and recreation roads, and 40 km/hr for local roads. The average fleet weight for Canada was estimated to be 2.676 tonnes. The silt content of unpaved roads was taken as 3.9% (AP-42 section 13.2.2, 2006 update default value).

Silt loads were taken from the AP-42 table 13.2.1-2. Silt Load (sL) is a function of Average Annual Daily Traffic Volume (AADT), with adjustments for winter grit application (winter baseline multiplier).

AP-42 table 13.2.1-2
AADT sL Baseline sL Winter Multiplier Units
<500 0.6 4 g/m2
500—5000 0.2 3 g/m2
5000—10000 0.06 2 g/m2
>10000 0.03 1 g/m2

In order to determine the number of roads having traffic volumes (AADT) within the various silt load ranges and to apply regional weather correction parameters the regional distribution of VKT is also required. The Natural Resources Canada road network was used, with roads reclassified into a subset of classes (paved/unpaved resources and recreation, local, collector, arterial, highway, freeway, and winter roads. Winter roads being neither paved nor unpaved and assumed to be a non-source of dust. Freeways are only paved). Traffic counts from provinces and municipalities from across Canada were gathered by ECCC and spatially matched to the road network (approximately 500,000 data-points). Roads and census population (1991-2016 census years) were summarized by census subdivision using census geography vintages/versions from the 1996, 2006, and 2016 census’ (Statistics Canada 1996, 1996b, 2006, 2006b, 2016, 2016b). The ratios of mean traffic volume by road class modelled against regional population density to a baseline of paved local roads was used to distribute the estimated total VKT in Canada to each road class in each census subdivision, by year (geography and population varying by census year). See Table A2—4: Estimation Methodologies for Transportation and Mobile Equipment for VKT estimation methods).

Weather parameters (soil moisture) and corrections (precipitation, winter multipliers) were applied on a monthly time-scale at the census subdivision level. The frost days and wet days were obtained from Climate Research Unit (CRU 4.03, 2019), 0.5x0.5 degree spatial resolution, monthly. Soil moisture was from NOAA Climate Prediction Center (NOAA n.d.), 0.5x0.5 degree spatial resolution, monthly. Winter silt load multipliers were applied, by census subdivision, for any month that the subdivision had more than 15 days with mean temperature below zero.

It is assumed that no dust is (re)suspended from paved or unpaved roads on days with precipitation. The emission factor was adjusted using the factor:

Precip_Cor = (n_Days_per_Month – Precipitation_Days) / n_Days_per_Month

For unpaved roads, soil moisture was taken as the mean surface soil moisture content of the census subdivision, or 6.515% (the AP-42 2006 update, section 13.2.2 default value), if weather data was not available.

Activity data

See General Inventory Method. The same method used to calculate VKT for Transportation and Mobile Equipment sources was used to estimate VKT for the primary and secondary emissions.

Emission factors (EF)

Primary—(EEA, EMEP/EEA, 2013)
Secondary—Methodology under review.

A2—9 References

[AER] Alberta Energy Regulator. (2015). Coal Mine Locator, online database. Serial Publication: ST45-[updated 2015 May 15; accessed 2017 Sep].

BC MINEFILE. (2017). Coal producer database search results, British Columbia Ministry of Energy and Mines, MINFILE digital data [posted 2017 Sep; accessed 2017 Sep].

[CCMP] Cross-Calibrated Multi-Platform. (n.d.). Gridded surface vector winds, Level 3.5 – Monthly Mean. Accessed via Remote Sensing Systems ( Spatial resolution: 0.25x0.25 degree. Accessed July 2019.

[CMC] Canadian Meteorological Centre. (n.d). Daily Snow Depth Analysis Data, accessed via National Snow & Ice Data Center (US). Spatial resolution 24x24 km. Accessed July 2019.

[CMHC] Canadian Mortgage and Housing Corporation. (2017). Housing Market Information Portal, [database on the Internet]. Ottawa (ON) [accessed 2017 Sep 20].

Cope DL, Bhattacharyya KK. (2001). A study of fugitive coal dust emissions in Canada. Prepared for the Canadian Council of Ministers of the Environment. 2001. Unpublished report.

[CRU] University of East Anglia Climatic Research Unit, Harris I C, Jones, P.D. (2019), Climatic Research Unit (CRU) Time-Series (TS) version 4.03 of high-resolution gridded data of month-by-month variation in climate. Accessed via Centre for Environmental Data Analysis (CEDS) Web Processing Service ( Spatial resolution: 0.5 degree. Accessed July 2019.

[ECCC] Environment and Climate Change Canada. (2017). Monthly climate summaries, [database on the Internet]. Environment Canada, National Inquiry Response Team [accessed 2007 Sep].

[EEA] European Environment Agency. (2013). EMEP/EEA Air pollutant emission inventory guidebook 2013, Technical guidance to prepare national emission inventories. Luxembourg: Publications Office of the European Union. Technical Report No. 12/2013.

Evans and Cooper. (1980). An Inventory of Particulate Emissions from Open Sources, Journal of the Air Pollution Control Association. 30:12, 1298-1303, DOI: 10.1080/00022470.1980.10465188

Fuentes M, Millard K, Laurin E. (2019). Big geospatial data analysis for Canada’s Air Pollutant Emissions Inventory (APEI): using google earth engine to estimate particulate matter from exposed mine disturbance areas, GIScience & Remote Sensing, DOI:

Murray et al. (1977). PIT SLOPE MANUAL, Supplement 10-1, Reclamation by Vegetation, Vol 2 – Mine Waste Inventory by Satellite Imagery. Mining Research Laboratories, Energy Mines and Resources Canada

[NRCan] Natural Resources Canada. (1996-2016). Map 900A, Producing Mines, 48th ed. (1996) to 66th ed. (2016). 21 versions/editions used.

[NRCan] Natural Resources Canada (n.d.). CanVec spatial vector data. (Geodatabase). ManMade vector data, filtered for “Industrial Waste”, which includes tailings.

[NRCan] National Resources Canada. (n.d.). CanVec spatial vector data. (Geodatabase). Transport networks in Canada, Road Segments. Retrieved 2017 Jul.

[NOAA] National Oceanic and Atmospheric Administration. (n.d.). NOAA Climate Prediction Center (CPC) Soil Moisture, provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA,. Accessed July 2019.

Parsons et al. (2012) Environmental geochemistry of tailings, sediments and surface waters collected from 14 historical gold mining districts in Nova Scotia

SNC-Lavalin Environment. (2005). CAC fugitive emissions from the Canadian construction and demolition sector, Final Report, Unpublished report. Longueuil (QC). Prepared for the Canadian Council of Ministers of the Environment and Environment Canada.

Statistics Canada. (n.d.). Report on energy supply and demand in Canada (Annual), Catalogue No. 57 003 X.

Statistics Canada. (n.d.). Table 25-10-0048-01 (formerly CANSIM  303-0016) Coal and coke statistics, monthly (tonnes) (1946-2007), (database) [accessed 2017 Jul 13].

Statistics Canada. (n.d.). Table 027-0009 Canada Mortgage and Housing Corporation, housing starts, under construction and completions, all areas, annual (units), CANSIM (database) [accessed 2017 Aug 1].

Statistics Canada. (n.d.). Table 135-0002 Production and exports of coal, monthly (tonnes) (2008-2017), CANSIM (database) [accessed July 13, 2017].

Statistics Canada. (1996a). Population and Dwelling Counts, for Canada, Provinces and Territories, 1991 and 1996 Censuses, Data (table). "Population and dwelling count highlight tables, 1996 Census." Catalogue no. 95F0181XDB96001. Ottawa, Ontario.

Statistics Canada.  (1996b). 1996 Census (Geography Products: Geographic Data Products). Statistics Canada Catalogue No. 92F0029XDE, 92F0030XDE, 92F0032XDE - 92F0040XDE.

Statistics Canada. (2006a). Population and Dwelling Counts, for Canada, Provinces and Territories, 2001 and 2006 Censuses, Data (table). "Population and dwelling count highlight tables, 2006 Census." Catalogue no. 94-581-XCB2006001. Ottawa, Ontario.

Statistics Canada.  (2006b). 2006 Census (Geography Products: Geographic Data Products). Statistics Canada

Statistics Canada. (2016a). Population and Dwelling Counts, for Canada, Provinces and Territories, 2011 and 2016 Censuses, Data (table). "Population and dwelling count highlight tables, 2016 Census." Catalogue no. 98-401-X2016055. Ottawa, Ontario.

Statistics Canada.  (2016b). 2016 Census (Geography Products: Geographic Data Products). Statistics Canada Catalogue No. Catalogue no. 92-160-G

[U.S. EPA] United States Environmental Protection Agency. (1995). Compilation of Air Pollutant Emission Factors, Volume I: Stationary Point and Area Sources, 5th Edition. Research Triangle Park (NC): Office of Air Quality Planning and Standards.

[U.S. EPA] United States Environmental Protection Agency. (2006). Office of Air Quality Planning and Standards. Compilation of Air Pollutant Emission Factors, AP-42, Fifth Edition, Volume I: Stationary Point and Area Sources, Section 13.2.2, Unpaved Roads. Research Triangle Park, NC. January 2006.

[U.S. EPA] United States Environmental Protection Agency. (2011). Office of Air Quality Planning and Standards. Compilation of Air Pollutant Emission Factors, AP-42, Fifth Edition, Volume I: Stationary Point and Area Sources, Section 13.2.1, Paved Roads. Research Triangle Park, NC. January 2011.

A2—10: Estimation methodologies for Fires by sector/subsector

Prescribed Burning


Prescribed Burning includes emissions from controlled fires used for land management treatments. Prescribed burning is used to reduce logging residues, manage forest production, control insects and minimize potential for destructive wildfires. The practice of prescribed burning is carried out by the logging industry and forestry officials to manage Crown lands. This sector excludes the burning of agricultural residues.

General inventory method

Pollutant(s) estimated:
TPM, PM10, PM2.5, SOx, NOx, VOCs, CO, NH3, dioxins/furans, B(a)p, B(b)f, B(k)f, I(cd)p

Total annual mass of forest debris burned by fire and by province/territory is multiplied by pollutant-specific emission factors.

Activity data

The total number of hectares burned in each province/territory per year (CIFFC, 2019; PCA, 2019; NFD, 2016) is multiplied by a conversion factor for each province/territory (EC, 1992) to convert the area burned into the mass of forest debris burned. Pollutant and province-specific emission factors are then applied to the mass of forest debris to determine the release of pollutants from the burn.

Emission factors (EF)

TPM, PM10, PM2.5, SOx, NOx, VOCs, CO, NH3:

All provinces/territories (except British Columbia): (U.S. EPA, 1995).

British Columbia: (GVRD & FVRD, 2003; BCMWLAP, 2004)

Dioxins/furans, B(b)f, B(k)f: (Lemieux et al., 2004), B(a)p, I(cd)p:  (Johnson et al., 1992)

Structural Fires


Structural Fires cover emissions from vehicle fires (such as fires from cars, trains and airplanes) and buildings fires. Structural fires emit large quantities of pollutants due to rapid but incomplete combustion. This sector includes only emissions estimated in-house.

General inventory method

Pollutant(s) estimated:
TPM, PM10, PM2.5, NOx, VOCs, CO, NH3

Tonnes of structures burned per year, by province/territory, are multiplied by pollutant-specific emission factors.

Activity data

The Secretary/Treasurer of the Council of Canadian Fire Marshals and Fire CommissionersFootnote 2 (CCMFC) and the following members of the CCMFC are contacted to obtain the number of annual structural fires in their jurisdictions:

Number of structure fires in each province/territory is multiplied by a loading factor to convert the number of fires into tonnes of structure burned (EIIP, 2001).

Loading factor = 1.04 t of structure burned/fire

Given the unavailability of activity data, emission estimates for 2001, 2002 and 2004 are calculated using linear interpolation.

Emission factors (EF)

TPM, PM10, PM2.5, NOx, VOCs, CO: GVRD and FVRD (2003)
NH3: Battye et al. (1994)

A2—10 references

Battye R, Battye W, Overcash C, Fudge S. (1994). Development and selection of ammonia emission factors. Durham (NC), Report No. EPA/600/R-94/190.

[BCMWLAP] British Columbia Ministry of Water, Land and Air Protection. (2004). 2000 British Columbia emissions inventory of criteria air contaminants: Methods and calculations, Victoria (BC). [PDF]

[CIFFC] Canadian Interagency Forest Fires Centre. (2019). Canada Report 2018. [PDF]

[EC] Environment Canada. (1992). Canada’s greenhouse gas emissions: Estimates for 1990, Ottawa (ON): Environment Canada. Report No. EPS 5/AP/4.

[EIIP] Emission Inventory Improvement Program. (2001). EIIP Technical Report Series Volume 3: Area sources, Report No. EPA 454/R-97-004.

[GVRD] Greater Vancouver Regional District, [FVRD] Fraser Valley Regional District. (2003). 2000 emission inventory for the Canadian portion of the Lower Fraser Valley airshed – detailed listing of results and methodology, Burnaby (BC): Greater Vancouver Regional District.

Johnson ND, Scholtz MT, Cassidy V, Davidson K, Ord D. (1992). MOE toxic chemical emission inventory for Ontario and Eastern North America, Mississauga (ON): Ortech International. Report No. P92-T61- 5429/OG. [PDF]

Lemieux PM, Lutes CC, Santoianni DA. (2004). Emissions of organic air toxics from open burning: a comprehensive review, Prog Energy Combust Sci 30(1):1-32.

[NFD] National Forestry Database. (2019). Table 6.1. Area of site preparation by jurisdiction, tenure and treatment, 1990-2015.

[PCA] Parks Canada Agency. (2019). Prescribed fires 1990 to 2018, Parks Canada Agency.

[U.S. EPA] United States Environmental Protection Agency. (1995). Compilation of Air Pollutant Emission Factors, Volume I: Stationary Point and Area Sources, 5th Edition. Research Triangle Park (NC): Office of Air Quality Planning and Standards.

A2—11: Estimation methodology for Mercury in Products by sector/subsector

Mercury in Products


Mercury in Products covers emissions from Hg contained in products throughout their life cycle from manufacture to final disposition. The following products are included:

Emissions from the above devices impact the following sectors/subsectors:

General inventory method

Pollutant(s) estimated:

Mercury emissions from 1990 to 2008 are estimated based on the model Substance Flow Analysis of Mercury in Products originally developed by the Minnesota Pollution Control Agency, modified by ToxEcology Environmental. In 2018, the methodology was updated by ChemInfo Services with specific interest in 2009 forward. However, at that time work was also done for time series consistency which impacted emissions from 1990 to 2008 at the national level. (Barr Engineering, 2001; ToxEcology, 2007; ToxEcology, 2009; Cheminfo Services, 2018). The current update focuses on provincial distribution from 1990 forward and modifying aspects of the fluorescent and non-fluorescent lamp models from 2009 forward.

The Mercury in Products models use a lifecycle approach which considers releases from manufacturing, in-service breakage, recycling, transportation and storage of items sent to disposal as well as the ultimate disposal point for each product. The update completed by ChemInfo Services in 2018 allocated emissions to provinces and territories based on product type from 2009 forward. Prior to this update, emissions were not allocated based on product type. This year emissions from 1990 to 2008 were re-distributed based on product type for time series consistency. In addition, emissions were re-allocated for the open burning, sewage sludge incineration and municipal incineration sectors from 1990 forward to better reflect the provinces in which these practises take place. Lastly, activity data inputs for both fluorescent and non-fluorescent lamps were updated based on newly available data that was not provided at the time of the last update.

Activity data

(ToxEcology, 2007; ToxEcology, 2009; Cheminfo Services, 2018).

Emission factors (EF)

A modified version of the model, entitled Substance Flow Analysis of Mercury in Products by (Barr Engineering, 2001) used with updates from (ToxEcology, 2007; Cheminfo Services, 2018). The model includes partitioning factors to the various streams from manufacture through final disposal, including emission factors at every point along the way.

A2—11 References

Barr Engineering. (2001). Substance flow analysis of mercury in products, Minneapolis (MN): Barr Engineering. Prepared for the Minnesota Pollution Control Agency.

Cheminfo Services. (2018). Updating Environment and Climate Change Canada’s mercury-in-products flow model for the purpose of improving Canada's air pollution emission inventory, Unpublished report. Markham (ON): Cheminfo. Prepared for Environment and Climate Change Canada. (C. Services, Producer)

ToxEcology. (2007). Mass balance study for mercury-containing products model, Unpublished report. Vancouver (BC): ToxEcology. Prepared for EC.

ToxEcology. (2009). Mercury mass balance model_2008. xls [Excel spreadsheet], Unpublished report. Vancouver (BC): ToxEcology. Prepared for Environment and Climate Change Canada.

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