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UTEC 3.1

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USER GUIDE FOR URBAN TRANSPORTATION EMISSIONS CALCULATOR (UTEC) V.3.0

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1. Quick Guide

The Urban Transportation Emissions Calculator (UTEC) is a user-friendly tool for estimating annual emissions of greenhouse gases (GHGs) and key air pollutants from personal, commercial, and public transit vehicles in an urban context.

UTEC is very easy to use and this Quick Guide will describe the basic steps on how to generate results quickly. The quality of the emission estimates will depend on the quality of the input data and ability to tailor default values to local conditions. For more detailed discussion of the inputs, underlying data, calculations, and assumptions, see the other sections of this User Guide.

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1.1 Running Scenarios

UTEC allows users to create one or two scenarios. Each scenario has its own input screens, and results are available for each scenario as well as a comparison of the two scenarios.

Running a scenario involves three main tasks: (1) Scenario Inputs, (2) Vehicle Inputs, and (3) Results. These tasks involve 12 basic steps as described below. Optional steps are indicated.

Scenario Inputs

1. Enter scenario name (optional): Meaningful scenario names (e.g., “Full Bus Rapid Transit Implementation”) will aid in keeping track of multiple scenarios.
2. Select evaluation year: Affects emission results as it is expected that vehicle fuel efficiencies and other emission factors will improve in the future.
3. Select province/territory: Allows the Tool to account for the proportion of automobiles vs. light trucks in each province/territory, as well as the differing GHG intensities associated with electricity production in each province/territory. An option for Canada-wide values is also available.
4. Continue to Vehicle Inputs screen: Click on the button “Submit and continue to Personal Vehicles”.

Vehicle Inputs

Vehicle inputs consist of three screens: Personal Vehicles, Commercial Vehicles, and Public Transit. Each screen follows approximately the same structure.

5. Enter kilometres travelled: The primary inputs to the Tool are vehicle-kilometres travelled (VKT) for road vehicles, passenger-kilometres travelled (PKT) for rail transit vehicles, and revenue tonne-kilometres (RTK) for rail freight vehicles.
6. Specify the time period over which kilometres travelled was measured: VKT or PKT can be entered as tallies for the peak weekday hour, average weekday daily, or annual. RTK can only be as an annual value.
7. Modify expansion factors (optional): Expansion factors are used to convert inputted travel data into an annual value. Users are encouraged to tailor expansion factors to local conditions. Default values are based on results from large urban areas.
8. Enter driving conditions (optional): The proportion of stop-and-go city driving versus free flow highway driving is used to estimate fuel efficiency. Default values are based on results from large urban areas.
9. Specify fleet breakdown (optional): Different vehicle technologies run on different fuels and have different fuel efficiencies. For each vehicle type, enter the percentage of the vehicle fleet by vehicle-technology. Default values are based on national fleet characteristics.
10. Go to Results or Continue to the next Vehicle Inputs screen: Click on the appropriate button to either proceed to Results or to the next Vehicle Inputs screen.

Results

Each scenario has its own Results screen, and a Scenario Comparison screen is also available to compare the results of both scenarios. Results are displayed in three tables: Annual Greenhouse Gas Emissions, Annual Criteria Air Contaminant Emissions, and Annual Travel.

Note: The units for each table vary based on the size of the numbers.

11. Review results: UTEC does not save scenarios. Results can be copied to an external application such as Microsoft Excel to save results and conduct further analysis.
12. Modify current scenario or Create new scenario: Click on the appropriate button to return to the Scenario Inputs sheet and make modifications, or clear the scenario and start over. Alternatively, use the tab-like buttons at the top of the screen to go to any input sheet and make modifications.

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2. Tool Inputs

2.1 Scenario Inputs

UTEC v.3.0 allows users to create and compare up to two different scenarios. Each scenario has its own set of vehicle input screens and results. The Scenario Comparison page provides an easy way to view the differences between two scenarios.

Users can choose to create and enter inputs for one or both scenarios. For one scenario, simply enter all input data for one set of the input screens. The other scenario will show zero emissions.

Enter Scenario Name

The scenario names can be anything of your choosing. Scenario name is displayed in the Results screen, and choosing meaningful scenario names (e.g., Full Bus Rapid Transit Implementation) will aid in keeping track of multiple scenarios. Note that UTEC cannot save results from any scenario.

Select Evaluation Year

The evaluation year will affect emission results as it is expected that vehicle fuel efficiencies and other emission factors will improve in the future. The nature of these changes is discussed later in the sections on Fuel Efficiency, GHG Emission Factors, and CAC Emission Factors. The evaluation years were set in five‑year increments from 2006 through 2031 to correspond with Census years as these are the years to which many municipalities have calibrated their travel demand forecasting models.

Select Province/Territory

Selecting the province or territory of the municipality of interest allows the Tool to account for the varied provincial breakdowns of light-duty passenger vehicles (i.e., proportion of automobiles vs. light trucks), as well as the differing GHG intensities associated with electricity production in each province. An option for Canada-wide values is also available.

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2.2 Personal Vehicles

The Personal Vehicles input screen accepts activity and fleet inputs for Light-Duty Passenger Vehicles (LDPVs). This includes cars and light trucks less than 6,000 lbs. gross vehicle weight rating (GVWR).

Enter Vehicle-kilometres Travelled by Light-Duty Passenger Vehicles

Vehicle-kilometres travelled (VKT) represents the primary input to the Tool for LDPVs and care should be taken to enter accurate values.

Based on the data available, the user can enter VKT for the peak hour, average weekday, or annual time period. Travel demand models, available in most larger municipalities, generate travel estimates for the peak hour. If modelled VKT data are not available, other methods may be used. For example, if peak hour traffic counts are available, multiplying the peak hour traffic count by the appropriate road length will yield peak hour VKT.

Modify Personal Vehicle Expansion Factors

Expansion factors are used to convert inputted travel data into an annual value. If the user specified that input VKT is daily or annual, the appropriate expansion factors will automatically set to one.

While all municipalities have unique relationships between peak hour and annual travel, default values take into account travel characteristics for the Toronto area, a large urban region, based on data from the 2001 Transportation Tomorrow Survey. Users are encouraged to tailor expansion factors to local conditions.

Enter Percentage of Kilometres in City and Highway Driving

Based on fuel efficiency ratings for new vehicles, stop-and-go city driving consumes approximately 20% to 65% more fuel per kilometre than free-flow highway driving (Fuel Consumption Guide 2008, Office of Energy Efficiency, Natural Resources Canada, 2007). The proportion of city versus highway driving is used to estimate fuel efficiency for light-duty passenger vehicles. Default values reflect that the majority of driving for personal vehicles is expected to be in stop-and-go city conditions.

Enter Breakdown of LDPV Fleet

The LDPV category includes many vehicle classes, such as small automobiles, large automobiles, sport utility vehicles, minivans, pick-up trucks, etc. To allow greater accuracy in calculation of fuel consumption and emissions, the light-duty passenger vehicle type is subdivided into automobiles (LDPV-A) and light trucks (LDPV-T). LDPV-T includes all larger personal vehicles, such as sport utility vehicles, minivans, and pick-up trucks. The default automobile and light truck proportions are province-specific and were determined from 2008 data reported by the Office of Energy Efficiency Comprehensive Energy Use Database, Transportation Sector¹.

Enter Passenger Fleet Breakdown By Fuel Technology

The Tool allows for eleven (11) different fuel vehicle technologies for LDPVs, as shown in Exhibit 5.1. Users can select up to six LDPV fuel vehicle technologies per scenario from the pull-down lists. Each vehicle is assumed to travel the same distance annually so that the value entered is equivalent to the proportion of the VKT by each vehicle technology. The sum of percentages must be 100%.

Default values for fleet breakdown are based on national VKT data by vehicle type reported in the Environment Canada MOBILE6.2C output.

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2.3 Commercial Vehicles

The Commercial Vehicles input screen accepts activity and fleet inputs for:

Light-Duty Commercial Vehicles (LDCV) – trucks less than 8,500 lbs. GVWR;
Medium-Duty Commercial Vehicles (MDCV) – trucks between 8,501 and 33,000 lbs. GVWR; and,
Heavy-Duty Commercial Vehicles (HDCV) – trucks heavier than 33,001 lbs. GVWR.

¹ http://oee.nrcan.gc.ca/corporate/statistics/neud/dpa/comprehensive_tables/index.cfm?fuseaction=Selector.showTree

Enter Vehicle-kilometres Travelled by Commercial VEhicles

Vehicle-kilometres travelled (VKT) represents the primary input to the Tool for commercial vehicles and care should be taken to enter accurate values.

Based on the data available, the user can enter VKT for the peak hour, average weekday, or annual time period. Travel demand models, available in most larger municipalities, generate travel estimates for the peak hour, although they may not consider commercial vehicles. If modelled VKT data are not available, other methods may be used, such as cordon counts or assuming that commercial travel represents a certain proportion of passenger travel. Alternatively, fleet managers may keep records or their truck travel on a daily or annual basis.

Modify Commercial Vehicle Expansion Factors

Users are encouraged to tailor expansion factors to local conditions. The default value for the peak hour to daily expansion factor takes into account travel characteristics for the Toronto area, a large urban region, based on data from the Ministry of Transportation, Ontario (MTO) 2001 Commercial Vehicle Survey and the University of Toronto Data Management Group cordon count database (also 2001 counts). It is an average of expansion factors for each commercial vehicle type. Based on these sources, the peak hour to daily expansion factor increases with increasing truck size (LCDV = 12, MDCV = 14.5, HDCV = 16). This reflects that travel for larger trucks is spread out more evenly over the day. The user can adjust the default peak hour to daily expansion factor if only one or two commercial vehicle types are being considered.

The daily to annual expansion factor is based on typical commercial travel patterns.

Enter Percentage of Kilometres in City and Highway Driving

The proportion of city versus highway driving is used to estimate fuel efficiency for commercial vehicles. Default values reflect that, with increasing vehicle size, average trip distance increases and a greater proportion of driving tends to occur in free-flow, highway conditions.

Enter Commercial Fleet Breakdown By Fuel Technology

The Tool allows for eleven (11) different vehicle-technologies for light-duty commercial vehicles and seven (7) different vehicle-technologies for medium- and heavy-duty commercial vehicles, as shown in Exhibit 5.1. Users can select up to four (4) fuel vehicle technologies per vehicle type from the pull-down lists. Each vehicle is assumed to travel the same distance annually so that value entered is equivalent to the proportion of the VKT by each vehicle technology. The sum of percentages must be 100%.

Default values for fleet breakdown are based on national VKT data by vehicle type reported in the Environment Canada MOBILE6.2C output. Assumptions regarding alternative fuel technologies are described in the discussion of Emission Factors.

Enter Annual Revenue Tonne-kilometres by Freight Rail

Annual revenue tonne-kilometres (RTK) represent the primary input to the Tool for freight rail and care should be taken to enter accurate values.

Unlike other input data for commercial vehicles which can be entered for peak hour, average weekend or annual time periods, there are no expansion factors available. Users should convert travel data to annual values outside of the Tool.

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2.4 Public Transit Vehicles

Public Transit vehicles include:

Buses refer to standard, 40-foot public transit buses.
Trolley Buses refer to grid-connected public transit buses (e.g., electrically powered from an overhead wire), such as those in service in Vancouver.
Light Rail is usually driven by electric power taken from overhead lines, such as Toronto streetcars, although it can be diesel-powered (e.g. Ottawa O-train).
Subway/Metro is electrically powered heavy rail and normally operates underground.
Heavy Rail refers to diesel-fuelled commuter rail in this application.

Enter Vehicle-kilometres Travelled by Buses

Vehicle-kilometres travelled (VKT) represents the primary input to the Tool for buses and care should be taken to enter accurate values.

Enter Percentage of Bus Kilometres in City and Highway Driving

The proportion of city versus highway driving is used to estimate fuel efficiency for buses with internal combustion engines (i.e. not Trolley Buses). Default values reflect that all driving for buses is expected to be in stop-and-go city conditions.

Enter Passenger-kilometres Travelled by Rail Vehicles

Passenger-kilometres travelled (PKT) represents the primary input to the Tool for rail vehicles, since this measure is a better indicator of rail energy consumption due the variability of rail vehicle size (i.e. the number of cars). Care should be taken to enter accurate values.

Specify Time period for Entered Activity Data

Based on the data available, the user can enter VKT and PKT for the peak hour, average weekday, or annual time period. Travel demand models, available in most larger municipalities, generate travel estimates for the peak hour. If modelled VKT or PKT data are not available, other methods may be used. For example, a transit agency may collect data on daily or annual basis.

Modify Public Transit Expansion Factors

Expansion factors are used to convert inputted travel data into an annual value. If the user specified that inputted VKT and PKT are daily or annual, the appropriate expansion factors will automatically set to one. Users are encouraged to tailor expansion factors to local conditions. Compared with personal and commercial vehicles, public transit travel has the greatest proportion of daily VKT during the peak hour, when transit demand is highest.

The default value for the peak hour to daily expansion factor takes into account travel characteristics for the Toronto area, a large urban region, based on data from the 2001 Transportation Tomorrow Survey. The default value represents an appropriate expansion factor for buses, light rail, and subways that are used regularly over the course of the day.

A lower peak hour to daily expansion factor would be appropriate for commuter rail given that ridership is highly peaked and commute-trip oriented. For commuter rail in the Toronto area (i.e. GO Transit), the peak hour to daily expansion factor is estimated as 4.5 based on 2001 TTS data.

The daily to annual expansion factor is based on typical transit ridership patterns.

Enter Bus Fleet Breakdown By Fuel Technology

The Tool allows for nine (9) different vehicle-technologies for buses (not including trolley buses), as shown in Exhibit 5.1. Users can select up to four (4) fuel vehicle technologies per scenario from the pull-down lists. Each vehicle is assumed to travel the same distance annually so that value entered is equivalent to the proportion of the VKT by each vehicle technology. The sum of percentages must be 100%.

Assumptions regarding alternative fuel technologies are described in the discussion of Vehicle and Fuel Technologies and of Emission Factors.

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3. Results

UTEC v.3.0 allows users to create one or two scenarios. The Tool has an output screen for each scenario which summarizes the annual travel and related GHG and CAC emissions. The Tool also has a “Scenario comparison” output screen to view the differences in outputs between the two scenarios.

The three tables cover GHG emissions, CAC emissions and annual travel. Note that units for each table vary based on the size of the numbers.

The Tool cannot save scenarios and results. The output screen for each scenario is structured so that it can be easily copied and pasted into a spreadsheet program, such as Microsoft Excel. This allows the user to store results from different scenarios and compare and analyze the results as they see fit.

Users are also able to modify current scenario inputs or start over. Buttons allow users to clear the current scenario/scenarios and start over, or return to the Scenario Inputs sheet and make modifications. Alternatively, use the tab-like buttons at the top of the screen to go to any input sheet and make modifications.

GHG and CAC Emissions

The output summarizes annual vehicle operation and upstream GHG emissions in unit of mass of CO₂e. The output also summarizes annual CAC emissions by contaminant.

Annual Travel

The output summarizes annual vehicle-kilometres travelled for road vehicles, annual passenger-kilometres travelled for rail passenger vehicles, and annual revenue tonne-kilometres for rail freight.

Scenario Comparison

The Scenario Comparison page shows the difference between Scenario 1 and Scenario 2, using Scenario 1 as the base case (i.e. negative values indicate Scenario 2 emissions data is lower than Scenario 1).

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4. Expansion Factors

UTEC estimates GHG and CAC emissions based on annual kilometres of travel. The Tool includes some flexibility in the required inputs recognising that different users may have travel data available for different time periods. Based on their data available, users are allowed to enter vehicle-kilometres travelled (VKT) or passenger-kilometres travelled (PKT) as tallies for: weekday peak hour, average weekday (daily), or annual.

Expansion factors are used to convert input travel data (vehicle-kilometres or passenger-kilometres) into an annual value:

annual kms = χ_vkt/pkt × (α_peak>daily) × (α_daily>annual)

Where:

χ_vkt/pkt = veh-kms or pass-kms entered as input data
α_peak>daily = Peak-hour to Daily Expansion Factor
α_daily>annual = Daily to Annual Expansion Factor

Expansion factors are automatically defaulted to 1 based on the entered time period. For example, if the user enters and specifies Daily VKTs, the Tool will automatically set α_peak>daily = 1, which the user will not be allowed to modify. The Daily-to-Annual expansion factor may still be modified and should be tailored by the user to reflect travel characteristics in the area of interest.

The peak-to-daily expansion factor accounts for the fact that travel in the off-peak or non-rush hour periods is lower and, therefore, the factor is less than 24. An area with a high proportion of “commuter traffic” would have a lower peak to daily factor than an area with traffic patterns that are spread throughout the day. Similarly, an area with significant seasonal travel patterns will have a different daily-to-annual expansion factors than an area with only typical commuting patterns.

Users are encouraged to tailor expansion factors to local conditions. Tailoring expansion factors to local conditions will have a very significant impact on the results.

Default expansion factors take into account travel characteristics for a large urban area, and are based on the travel characteristics of the Toronto area (see Exhibit 4.1).

**Exhibit 4.1 : Default Expansion Factors**
Input	Default Expansion Factor (Value)	Source / Data based on
Personal Vehicles	peak-to-daily (10.5) daily-to-annual (320)	2001 Transportation Tomorrow Survey
Commercial Vehicles	peak-to-daily (14)	Ministry of Transportation, Ontario (MTO) 2001 Commercial Vehicle Survey and the University of Toronto Data Management Group cordon count database (also 2001 counts)
Commercial Vehicles	daily-to-annual (280)	Typical commercial travel patterns
Public Transit	peak-to-daily (6.5)	2001 Transportation Tomorrow Survey The default value represents an appropriate expansion factor for buses, light rail, and subways that are used regularly over the course of the day. A lower peak hour to daily expansion factor would be appropriate for commuter rail given that ridership is highly peaked and commute-trip oriented. For commuter rail in the Toronto area (i.e. GO Transit), the peak hour to daily expansion factor is estimated as 4.5 based on 2001 TTS data.
Public Transit	daily-to-annual (300)	Typical transit ridership patterns

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5. Vehicle and Fuel Technologies

5.1 Vehicle Types

Vehicles considered in the Tool can be categorized by the type of vehicle (e.g., cars vs. buses) and fuel technology (e.g., gasoline vs. biodiesel). UTEC v.3.0 now includes ten (10) vehicle types and fifteen (15) fuel technologies. Vehicle types considered include:

Light-duty passenger vehicles (LDPV) – Automobiles and light trucks for passenger use less than 6,000 lbs. gross vehicle weight rating (GVWR);
Light-duty commercial vehicles (LDCV) – Trucks for commercial use less than 8,500 lbs. GVWR (e.g., pick-up truck);
Medium-duty commercial vehicles (MDCV) – Trucks for commercial use between 8,501 and 33,000 lbs. GVWR (e.g., box truck);
Heavy-duty commercial vehicles (HDCV) – Trucks for commercial use greater than 33,001 lbs. GVWR (e.g., semi-trailer);
Public transit buses (BUS) – Bus used for public transit, except trolley buses;
Public transit trolley buses (TB) – Grid-connected public transit bus (e.g., electrically powered from an overhead wire);
Light rail (LR) – Light transit rail powered by electricity or diesel fuel, such as a streetcar or the Ottawa O-train, respectively;
Subway/Metro (SM) – Electrically powered subway or metro system;
Heavy rail (HR) – Diesel-fuelled commuter rail; and,
Freight rail (FR) – Diesel-fuelled freight rail.

5.2 Fuel Technologies

Fuel technologies considered include gasoline, diesel, propane, compressed natural gas, liquefied natural gas, ethanol (E10 and E85), methanol (M85), ethanol-diesel (ED10), Biodiesel (B100), hybrid-electric, plug-in hybrid electric vehicle, electric vehicle, and fuel cell.

Gasoline (G) – conventional gasoline from crude oil;
Diesel (D) – conventional diesel fuel from crude oil;
Propane (P) – liquefied petroleum gases;
Compressed natural gas (CNG) – natural gas in compressed state;
Liquefied natural gas (LNG) – natural gas in liquefied state;
E10 ethanol-gasoline blend – 10% ethanol blended with 90% gasoline, where the ethanol is assumed to be derived from corn feedstock;
E85 ethanol-gasoline blend – 85% ethanol blended with 15% gasoline, where the ethanol is assumed to be derived from corn feedstock;
M85 methanol-gasoline blend – 85% methanol blended with 15% gasoline, where the methanol is assumed to be derived from natural gas;
E10 ethanol-diesel blend – 10% ethanol blended with diesel, where the ethanol is assumed to be derived from corn feedstock;
B100 Biodiesel – 100% biodiesel fuel derived from soybeans;
Hybrid electric vehicle, Gasoline (HYB-G) – A vehicle which combines a gasoline-fuelled internal combustion engine and electric batteries to power electric motors;
Hybrid electric vehicle, Diesel (HYB-D) – A vehicle which combines a diesel-fuelled internal combustion engine and electric batteries to power electric motors;
Plug-in hybrid electric (PHEV) – A plug-in hybrid electric vehicle (PHEV) is a hybrid vehicle with batteries that can be recharged by connecting a plug to an electric power source. It shares the characteristics of both conventional hybrid electric vehicles and battery electric vehicles. The Tool assumes PHEV50/50 (i.e. battery can provide energy for 50km of driving and vehicle operates in battery mode 50% of driving);
Electric Vehicle (EV) – Electric vehicle is used to refer to a variety of grid-powered vehicles including light-duty vehicles with batteries that can be recharged by connecting a plug to an electric power source, and grid-connected light rail vehicles and subways; and
Fuel cell (FC) – Compressed (gaseous) hydrogen derived from natural gas is assumed to be the fuel cell reactant for light-duty vehicles and buses, in line with prevailing practice.

The Tool estimates annual GHG and CAC emissions for 51 vehicle-technology categories, displayed in Exhibit 5.1.

**Exhibit 5.1 : Vehicle-Fuel Technology Combinations Considered**
Technology	Vehicle
Technology	LDPV	LDCV	MDCV	HDCV	BUS	TB	LR-E	LR-D	SM	HR	FR
Gasoline (G)	yes	yes	yes	yes	yes
Diesel (D)	yes	yes	yes	yes	yes			yes		yes	yes
Propane (P)	yes	yes	yes	yes	yes
Compressed Natural Gas (CNG)	yes	yes	yes	yes	yes
Liquefied Natural Gas (LNG)			yes	yes	yes
Ethanol (E10)	yes	yes
Ethanol (E85)	yes	yes
Methanol (M85)	yes	yes
Ethanol-Diesel (ED10)			yes	yes	yes
Biodiesel (B100)			yes	yes	yes
Hybrid Gasoline (HYB-G)	yes	yes
Hybrid Diesel (HYB-D)					yes
Plug-in Hybrid (PHEV)	yes	yes
Electric Vehicle (EV)	yes	yes				yes	yes		yes
Fuel Cell (FC)	yes	yes			yes

(1) Plug in Hybrid Electric Vehicle assumes PHEV50/50 (i.e. battery can provide energy for 50km of driving and vehicle operates in battery mode 50% of driving).

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5.3 Vehicle Classification

One topic, which affects the calculation of all factors, is vehicle classification. Different sources use different vehicle classification systems. GHGenius uses the most aggregate vehicle classifications, while MOBILE6.2C uses the most refined vehicle classification system. Exhibit 5.2 shows how the vehicle classifications from GHGenius, the Environment Canada GHG Emissions Inventory, and MOBILE6.2C relate and how they were used to determine emission factors for the Tool vehicle types.

**Exhibit 5.2 : Vehicle Classification by Data Source**
UTEC	MOBILE 6.2C	Environment Canada GHG Inventory	GHGenius
LDPV-A	LDGV	LDGA	Light-Duty Vehicle (LDV)
LDPV-A	LDDV	LDDA
LDPV-T	LDGT1	LDGT
	LDGT2	LDGT
	LDDT12	LDDT
LDCV	LDGT3	LDGT
	LDGT4	LDGT
	LDDT34	LDDT
MDCV	HDGV2B	HDGV	Heavy-Duty Vehicle (HDV)/Bus
	HDGV3
	HDGV4
	HDGV5
	HDGV6
	HDGV7
	HDDV2B	HDDV
	HDDV3
	HDDV4
	HDDV5
	HDDV6
	HDDV7
HDCV	HDGV8A	HDGV
	HDGV8B	HDGV
	HDDV8A	HDDV
	HDDV8B	HDDV
Bus	GAS BUS	HDGV
Bus	URB BUS	HDDV
TB	N/A	N/A	N/A
LR-E	N/A	N/A	N/A
SM	N/A	N/A	N/A
LR-D	N/A	Diesel Rail Transportation	N/A
HR	N/A		N/A
FR	N/A		N/A

Note: See Glossary for definition of acronyms.

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6. Emission Factors

Factors are used to calculate fuel consumption, GHG emissions, and CAC emissions from annual vehicle travel data, as discussed in the following sections. Fuel efficiencies and GHG and CAC emission factors were drawn from three primary sources:

Canada’s Greenhouse Gas Emissions Inventory, Environment Canada – Vehicle operation GHG emission factors for conventional vehicles (i.e. gasoline and diesel powered) are based on the 1990-2008 National Inventory Report (NIR) by Environment Canada (see http://www.ec.gc.ca/ges-ghg/default.asp?lang=En&n=83A34A7A-1).
MOBILE6.2C outputs from the National Inventory of CAC Emissions, Environment Canada – Environment Canada prepared runs of MOBILE6.2C² for the years 1980 to 2030 using national level fleet data. The results from these runs provided CAC emission factors and fuel efficiencies for conventional road vehicles used in UTEC. These data were used in previous versions of the Tool and communication with Environment Canada indicated that these results, prepared in 2002 still represent valid data regarding expected fleet composition and CAC emission factors.
GHGenius, Natural Resources Canada – GHGenius is an Excel-based tool developed for Natural Resources Canada, capable of estimating lifecycle emissions of the primary greenhouse gases and criteria pollutants from combustion sources. GHGenius summarizes some of the best data available on emissions factors associated with conventional and alternative fuels. Upstream fuel cycle GHG emission factors for all fuels were derived from GHGenius using default Canada inputs, which represent national industry average values. In addition, fuel efficiencies and vehicle operation GHG and CAC emission factors for alternative fuel vehicles are derived from GHGenius. See http://www.ghgenius.ca/ to access the Tool and all supporting documentation.

6.1 Fuel Efficiency

Fuel efficiency factors are used to determine fuel consumption rates based on annual vehicle-kilometres travelled (VKT), passenger-kilometres travelled (PKT) and revenue tonne-kilometres (RTK) values. These fuel consumption rates are used to calculated direct and indirect GHG emissions. CAC emissions are estimated directly from VKT, PKT and RTK.

Fuel efficiency is expressed in Litres per 100-km (L/100 km) for most technology types with some variations as shown in Exhibit 6.1.

² MOBILE is a model developed by the U.S. Environmental Protection Agency for estimating pollution from highway vehicles. MOBILE calculates gram per mile emissions of hydrocarbons (HC), carbon monoxide (CO), oxides of nitrogen (NOx), carbon dioxide (CO₂), particulate matter (PM) and air toxics from Gas, diesel, and natural-gas-fuelled cars, trucks, buses, and motorcycles for the calendar years between 1952 and 2050. MOBILE is the most recognized model for estimating CAC emission from road sources. MOBILE includes over 25 vehicle classifications. The most recent version is MOBILE6.2, which has been adapted by Environment Canada to Canadian conditions as MOBILE6.2C.

**Exhibit 6.1 : Units for Baseline Fuel Efficiency by Vehicle Technology**
Vehicle Technology	Fuel Efficiency Units
Compressed Natural Gas	m³/100 km
Electric-Vehicle	MJ/100 km
Plug in Hybrid Electric Vehicle	MJ/100 km
Trolley Bus	MJ/100 km
Light Rail (electric)	MJ/100 p-km
Light Rail (diesel)	L/100 p-km
Subway/Metro (electric)	MJ/100 p-km
Heavy Rail (diesel)	L/100 p-km
Freight Rail (diesel)	L/100 tonne-km
All others	L/100 km

For passenger vehicles, commercial vehicles, and buses, fuel efficiency is calculated as a weighted average of city and highway fuel efficiency factors based on the inputted proportion of kilometres in city and highway conditions.

City and highway fuel efficiency for gasoline and diesel vehicles are based on values from Environment Canada MOBILE6.2C forecasts. These fuel efficiencies take into account the age profile of the fleet by vehicle class at the national scale, and were modified to reflect a 0.5% annual improvement factor and varying city and highway driving conditions and fuel efficiencies.

Fuel efficiencies for alternative technology vehicles (i.e. CNG, biodiesel, etc.) were determined using relative emission factors developed based on the approach adopted in the GHGenius Tool. UTEC v.3.0 relative fuel efficiency factors are based on outputs of GHGenius v.3.19.

Efficiencies for rail vehicles and trolley buses were derived from a variety of sources: the American Public Transportation Association (APTA) Public Transportation Fact Book, the Transportation Energy Data Book (by Oak Ridges National Laboratory), and the Locomotive Emissions Monitoring Program by the Railway Association of Canada.

Additional data sources and estimation of fuel efficiency factors used by the Tool are detailed in Appendix A.

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6.2 Greenhouse Gas Emission Factors

GHG emissions are estimated based on fuel and electricity consumption from travel. The Tool calculates the GHG emissions from fuel combustion and the upstream fuel cycle effects:

Vehicle operation GHG emissions are released directly from the tailpipe of a vehicle.
Upstream GHG emissions are created and released from production of electricity used by electric vehicles (i.e. trolleys and light rail) as well as from the production, refining and transportation of transportation fuels (i.e. from wells to pump).

It is important to note that the Tool does not consider life-cycle emissions associated with the manufacture and end‑of‑life recycling of vehicles.

Additional data sources and estimation of GHG emission factors used by the Tool are detailed in Appendix A.

Global Warming Potential

GHG emissions are calculated for carbon dioxide (CO₂), nitrous oxide (N₂O), and methane (CH₄) and then reported in CO₂ equivalents (CO₂e) based on their respective global warming potentials. In order to measure the impact of the various gases involved in global warming using a single unit of measurements, the scientific community has adopted a standard based on the impact of one tonne of CO₂ over a 100-year time frame. The impacts of other gas types are compared to CO₂ over the same time frame to produce standard global warming potentials (GWP), expressed in tonnes CO₂ equivalent (CO₂e). GWP values for nitrous oxide and methane are taken from the United Nations Framework Convention on Climate Change (UNFCC, http://unfccc.int/ghg_data/items/3825.php).

Vehicle Operation GHG Emission Factors

Vehicle operation GHG emission factors for conventional vehicles (i.e. gasoline and diesel powered) are based on the National Inventory Report on greenhouse gas emissions prepared by Environment Canada.

Since emissions control technology (such as the type of catalytic converter) affects the emission rates of N₂O and CH₄, the fleet penetration of each technology (measured by the age of the fleet) will affect the fleet’s overall emission factors. For 2011 road vehicles, emission factors were calculated as a weighted average of Tier 1 / Tier 0 and Advanced Control / Moderate Control based on the proportion of the national vehicle fleet built since 1996 based on information from the 2009 Canadian Vehicle Survey: Annual published by Statistics Canada. Emission factors for later model years were set to the Tier 1 and Advanced Control values.

GHG emission factors for alternative technology vehicles were determined using relative emission factors derived from GHGenius. UTEC v.3.0 relative fuel efficiency factors are based on outputs of GHGenius v.3.19.

Emission factors for diesel rail transportation – light rail, heavy rail and freight rail – are based on the GHG inventory emission factors for Diesel Train Railways from the National Inventory Report prepared by Environment Canada.

Upstream Fuel Cycle GHG Emission Factors

Upstream fuel cycle GHG emission factors are used to estimate the associated ‘upstream’ fuel cycle GHG emissions, including fuel refining and transportation. They are fuel specific and were determined from GHGenius. The feedstock for the ethanol in E10, E85, and ED10 is assumed to be corn. The feedstock for biodiesel is assumed to be soybeans. The fuel cells are assumed to run on methanol.

UTEC v.3.0 upstream fuel cycle GHG emission factors are based on outputs of GHGenius v.3.19.

Indirect Electricity Production GHG Emission Factors

Indirect electricity production GHG emission factors are used to determine the GHG emissions associated with electric vehicles. They are specified in kg CO₂e per megajoule of electricity consumed. The factors are province- and territory-specific based on the mix of electricity generation methods in each region. These factors were determined from the electricity GHG emission factors by province and territory reported in the 1990-2008 National Inventory Report prepared by Environment Canada. Forecasts of electrical emission factors are not available so the factors do not change over the model years.

UTEC v.3.0 includes a Canada-wide emission factor, which was not available in previous versions of the Tool.

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6.3 Criteria Air Contaminant Emission Factors

CAC emission factors are used to determine the emissions of carbon monoxide (CO), nitrogen oxides (NO_x), sulphur dioxide (SO₂), volatile organic compounds (VOCs), total particulate matter (TPM), particulate matter less than 10 microns in diameter (PM₁₀), and particulate matter less than 2.5 microns in diameter (PM_2.5) from vehicle operation. Direct CAC emission factors have the units of g/km as they are better estimated by distance travelled than by amount of fuel consumed.

Additional data sources and estimation of GHG emission factors used by the Tool are detailed in Appendix A.

Direct CAC emission factors for gasoline and diesel road vehicles were developed from forecasts of CAC emission factors from MOBILE6.2C developed by Environment Canada. These emission factors were further reduced by 0.5% per year, corresponding to the annual improvement factor applied to MOBILE6.2C fuel efficiencies.

CAC emission factors for alternative technology vehicles were determined using relative CAC emission factors derived from GHGenius. The particulate matter multiplication factor was assumed to apply to all particulate emission factors (TPM, PM₁₀, and PM_2.5). UTEC v.3.0 relative fuel efficiency factors are based on outputs of GHGenius v.3.19.

CAC emission factors for diesel-powered rail (light-rail, heavy rail and freight rail) are based on the railway operations CAC emissions reported in the Locomotive Emissions Monitoring (LEM) Program (Railway Association of Canada).

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7. Glossary

B100 - 100% biodiesel (100% soybean feedstock assumed)

Bus - Urban public transit bus

CAC - Criteria air contaminant (CO, NOx, SO_x, VOC, TPM, PM₁₀, PM_2.5)

CH₄ - Methane

CNG - Compressed natural gas

CO - Carbon monoxide

CO₂ - Carbon dioxide

CO₂e - Carbon dioxide equivalents – Single unit describing the global warming potential of all GHG emissions.

D - Diesel

E10 - 10% ethanol / 90% gasoline blend (ethanol is assumed to be derived from corn feedstock)

E85 - 85% ethanol / 15% gasoline blend (ethanol is assumed to be derived from corn feedstock)

EV - Electric vehicle

ED10 - 10% ethanol / 90% diesel blend (ethanol is assumed to be derived from corn feedstock)

FC - Fuel cell (assumes the reactant is compressed gaseous hydrogen derived from natural gas)

G - Gasoline

GHG - Greenhouse gas

GWP - Global warming potential – Global warming impact of a gas compared to CO₂ over a 100-year time frame.

HDCV - Heavy-duty commercial vehicle

HR - Heavy rail (diesel powered)

HYB - Hybrid-electric vehicle (gasoline fuel is assumed for LDPV and LDCV hybrids and diesel fuel is assumed for Bus hybrids)

LDCV - Light-duty commercial vehicle

LDPV - Light-duty passenger vehicle

LDPV-A - Light-duty passenger automobile

LDPV-T - Light-duty passenger truck (minivan, SUV, light truck)

LNG - Liquefied natural gas

LR-D - Light rail (diesel powered)

LR-E - Light rail / Metro (electrically powered)

M85 - 85% methanol / 15% gasoline blend (methanol is assumed to be derived from natural gas)

MDCV - Medium-duty commercial vehicle

N₂O - Nitrous oxide

NG - Natural gas

NOx - Nitrogen oxides

P - Propane

PHEV - Plug-in hybrid electric vehicle (PHEV50/50 assumed meaning that the battery can provide energy for 50km of driving and vehicle operates in battery mode for 50% of driving)

PKT - Passenger-kilometres travelled

PM₁₀ - Particulate matter less than 10 microns in diameter

PM_2.5 - Particulate matter less than 2.5 microns in diameter

RTK - Revenue tonne-kilometres

SM - Subway/Metro

SO₂ - Sulphur dioxide

TB - Trolley bus (electrically powered from an overhead wire)

TPM - Total particulate matter

VKT - Vehicle-kilometres travelled

VOCs - Volatile organic compounds

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APPENDIX A: Tool Overview / Frequently Asked Questions

What is UTEC?

The Urban Transportation Emissions Calculator (UTEC) is a user-friendly tool for estimating annual emissions from personal, commercial, and public transit vehicles. UTEC estimates:

annual greenhouse gas (GHG) emissions from the operation of vehicles;
annual criteria air contaminant (CAC) emissions from the operation of vehicles; and
annual upstream GHG emissions from the production, refining and transportation of transportation fuels, as well as from production of electricity used by electric vehicles.

The target audience for this tool includes those with responsibility for transportation and land-use planning, academics and other transportation experts, urban transportation providers, and private and public vehicle fleet managers.

How can you use UTEC?

UTEC can be used for urban transportation emissions estimation in a wide variety of contexts involving different vehicle types (i.e. personal, commercial, and public transit vehicles), fuel technologies (e.g., gasoline, diesel, hybrid, ethanol, biodiesel, etc.), and planning horizons (2006-2031). Sample uses include:

determining a baseline level of annual GHG and CAC emissions from passenger transportation for an urban area;
forecasting annual GHG and CAC emissions from passenger transportation for an urban area for future years (i.e. 2011, 2016, 2021, 2026, 2031);
assessing the emissions implications of a particular transit project (e.g., a new rapid transit line);
assessing the emissions implications of converting a portion of a commercial or transit fleet to an alternative fuel (e.g., hybrid-diesel or natural gas buses, biodiesel trucks, etc.)

As discussed below, UTEC estimates emissions from transportation activity data (e.g., vehicle-kilometres travelled). It cannot predict the emission implications of different land uses or other transportation demand strategies (e.g., ridematching) directly if activity data is not available.

What vehicle types and fuel technologies are considered?

The Tool estimates GHG and CAC emissions for the following vehicles:

Light-duty passenger vehicles (LDPV) – Automobiles and light trucks for passenger use less than 6,000 lbs. gross vehicle weight rating (GVWR);
Light-duty commercial vehicles (LDCV) – Trucks for commercial use less than 8,500 lbs. GVWR (e.g., pick-up truck);
Medium-duty commercial vehicles (MDCV) – Trucks for commercial use between 8,501 and 33,000 lbs. GVWR (e.g., box truck);
Heavy-duty commercial vehicles (HDCV) – Trucks for commercial use greater than 33,001 lbs. GVWR (e.g., semi-trailer);
Public transit buses (BUS) – Bus used for public transit;
Public transit trolley buses (TB) – Grid-connected public transit bus (e.g., electrically powered from an overhead wire);
Light rail (LR) – Light transit rail powered by electricity or diesel-fuelled, such as an electric streetcar or the Ottawa O-train, respectively;
Subway/Metro (SM) – Electrically powered subway or metro system;
Heavy rail (HR) (diesel) – Diesel-fuelled commuter rail;
Freight rail (FR) – Diesel-fuelled freight rail (i.e. goods movement).

The Tool also considers the impacts of new technologies and alternative fuels for road vehicles. The vehicle-technology combinations considered for road-vehicles are displayed in Exhibit A.1.

**Exhibit A.1: Vehicle-Technology Combinations Considered**
Technology	Vehicle
Technology	LDPV	LDCV	MDCV	HDCV	BUS	TB	LR-E	LR-D	SM	HR	FR
Gasoline (G)	yes	yes	yes	yes	yes
Diesel (D)	yes	yes	yes	yes	yes			yes		yes	yes
Propane (P)	yes	yes	yes	yes	yes
Compressed Natural Gas (CNG)	yes	yes	yes	yes	yes
Liquefied Natural Gas (LNG)			yes	yes	yes
Ethanol (E10)	yes	yes
Ethanol (E85)	yes	yes
Methanol (M85)	yes	yes
Ethanol-Diesel (ED10)			yes	yes	yes
Biodiesel (B100)			yes	yes	yes
Hybrid Gasoline (HYB-G)	yes	yes
Hybrid Diesel (HYB-D)					yes
Plug-in Hybrid (PHEV)	yes	yes
Electric Vehicle (EV)	yes	yes				yes	yes		yes
Fuel Cell (FC)	yes	yes			yes

(1) Plug in Hybrid Electric Vehicle assumes PHEV50/50 (i.e. battery can provide energy for 50km of driving and vehicle operates in battery mode 50% of driving).

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What are the key inputs?

The primary input to the Tool is vehicle-kilometres travelled (VKT) for road vehicles and passenger-kilometres travelled (PKT) for rail vehicles. These numbers can be entered as tallies for the peak weekday hour, average weekday daily, or annual time period. To improve the accuracy of results, it is strongly recommended that the user modify default values for other inputs, such as expansion factors and fleet composition, to local conditions, but this is not required to run the Tool.

The key inputs are summarized below and described individually in the Inputs Section.

Activity data – As discussed, the primary input to the Tool is VKT for road vehicles and PKT for rail vehicles, which can be entered as tallies for the peak weekday hour, average weekday daily, or annual time period.
Evaluation year – The user can select from an evaluation year between 2006 and 2031 in five-year increments, corresponding to Census years. Fuel efficiency and emission factors are expected to improve in future years as discussed in the Emission Factors section of the User Guide.
Province/territory – The study province or territory sets the default light-duty vehicle fleet composition and the GHG emission factor for electricity generation.
Expansion factors – Expansion factors convert inputted activity data to annual values and have a large influence on final results. Default values are provided based on data from a large urban region, however, tailoring these values to local conditions is recommended, if data is available. Unique expansion factors are provided for personal vehicles, commercial vehicles, and public transit reflecting different travel patterns among these vehicle types.
Driving conditions – For road vehicles, users can modify default values for the proportion of driving in city (i.e. stop-and-go driving with low average speed) and Highway (i.e. free flow driving with high average speed) conditions. UTEC modifies fuel efficiency based on driving conditions.
Fleet composition – Default fleet composition by road vehicle type and fuel is based on national averages. Users can change this breakdown and specify the proportion of vehicles using alternative fuel technologies.

What are the main sources of data?

While the data used in UTEC are collected from a variety of sources, the underlying fleet composition, fuel efficiency, and GHG and CAC emission factors were drawn from three primary sources:

Canada’s Greenhouse Gas Emissions Inventory, Environment Canada – Vehicle operation GHG emission factors for conventional vehicles (i.e. gasoline and diesel powered) are taken from the 1990-2008 National Inventory Report 1990-2008: Greenhouse Gas Sources and Sinks in Canada (see http://www.ec.gc.ca/ges-ghg/default.asp?lang=En&n=83A34A7A-1).
MOBILE6.2C outputs from the National Inventory of CAC Emissions, Environment Canada – Environment Canada prepared runs of MOBILE6.2C³ for the years 1980 to 2030 using their own projections of technology and fleet changes at the national level. The results from these runs provided CAC emission factors and fuel efficiencies for conventional road vehicles used in UTEC.
GHGenius, Natural Resources Canada – GHGenius is an Excel-based tool developed for Natural Resources Canada, capable of estimating life-cycle emissions of the primary greenhouse gases and criteria pollutants from combustion sources. GHGenius summarizes some of the best data available on emissions factors associated with conventional and alternative fuels. Upstream fuel cycle GHG emission factors for all fuels were derived from GHGenius based on average national values. In addition, fuel efficiencies and vehicle operation GHG and CAC emission factors for alternative fuel vehicles were derived from GHGenius (see www.ghgenius.ca to access the Tool and all supporting documentation).

How do I tailor UTEC to my local conditions?

Other than ensuring you have good estimates of travel activity by vehicle class, there are a number of ways that UTEC can be tailored to local conditions.

Modify expansion factors – Expansion factors are used to convert inputted travel data into an annual value. Tailoring expansion factors to local conditions will have a very significant impact on the accuracy of results. The default expansion factors take into account travel characteristics for a large urban area (e.g., metropolitan Toronto area). Travel patterns in the area of interest may be significantly different, so that care should be taken in determining appropriate factors (e.g., if the vast majority of transit travel occurs during the peak periods, then the peak-daily expansion factor will be lower than default values in the Tool).
Modify driving conditions – The level of congestion and amount of highway travel in the area of interest will influence the proportion of stop-and-go city driving versus free flow highway driving. This has a significant influence on fuel efficiency (it was assumed that city driving consumes 30% more fuel per kilometre than highway driving).
Modify proportion of automobiles and light trucks in light-duty passenger fleet – The light-duty passenger vehicle type includes many vehicle classes, such as small automobiles, large automobiles, sport utility vehicles, minivans, pick-up trucks, etc. To allow greater accuracy in calculation of fuel consumption and emissions, the light-duty passenger vehicle type is subdivided into automobiles and light trucks. The default proportion of LDPVs in automobile and light trucks is province-specific, but can be further refined to local conditions.
Modify breakdown of vehicle fleet by fuel technology – For each vehicle type, the user can specify the proportion of the fleet by fuel technology (e.g., gasoline, diesel, hybrid, propane, etc.) Default values represent national fleet characteristics.

³ MOBILE is a model developed by the U.S. Environmental Protection Agency for estimating pollution from highway vehicles. MOBILE calculates gram per mile emissions of hydrocarbons (HC), carbon monoxide (CO), oxides of nitrogen (NOx), carbon dioxide (CO₂), particulate matter (PM) and air toxics from Gas, diesel, and natural gas-fuelled cars, trucks, buses, and motorcycles for the calendar years between 1952 and 2050. MOBILE is the most recognized model for estimating CAC emission from road sources. MOBILE includes over 25 vehicle classifications. The most recent version is MOBILE6.2, which has been adapted by Environment Canada to Canadian conditions as MOBILE6.2C.

Certain aspects of UTEC cannot be modified, which puts limits on how far the Tool can be tailored to local conditions. For example, emission factors and fuel efficiencies by vehicle type cannot be modified and are based on national level fleet data, primarily due to data limitations. This may result in underestimates of fuel consumption and emissions in provinces that do not have emission standards for vehicles in operation (e.g., Drive Clean in Ontario) or in provinces with older vehicle fleets (e.g., British Columbia, since many areas do not use road salt). In addition, upstream fuel cycle GHG emission factors for all fuels were derived from GHGenius based on average national values.

Overall, it is expected that UTEC provides good estimates of annual emissions for an urban area, provided that the user can reasonably tailor the aforementioned inputs to local conditions. Emission estimates will be less accurate, however, if the fleet under consideration is significantly different from the national average (e.g., a truck fleet with all vehicles purchased in one year) or if it has a less representative speed profile (e.g., only modelling low-speed local traffic). This is particularly the case for CAC emission estimates, which are very sensitive to driving conditions.

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How has UTEC been upgraded?

The first version of UTEC was made available in mid-2006. Given the continually growing body of knowledge with regards to emission estimation, comments received to date, and the desire to enhance the value of the Tool to the target audience, UTEC has been upgraded in 2008 (v.2.0.) and in 2011 (v.3.0).

Key upgrades for UTEC v.3.0 include:

New rail freight emissions – The Tool has been upgraded to estimate emissions from diesel freight rail based on user inputs of revenue tonne-kilometres. Fuel efficiencies and emission factors have been updated to include this new vehicle mode.
Updated fuel efficiencies – Fuel efficiencies have been updated to reflect the most recent data from GHGenius v.3.19, the American Public Transportation Association (APTA) 2010 Public Transportation Fact Book, the Transportation Energy Data Book, Edition 29 by the Oak Ridge National Laboratory and U.S. Department of Energy, and the 2008 Locomotive Emissions Monitoring Program by the Railway Association of Canada.
Updated GHG and CAC emission factors – Vehicle operation GHG emission factors have been updated to reflect the most recent work from Environment Canada’s 1990-2008 National Inventory Report. Upstream fuel cycle GHG emission factors have been updated based on the most current data summarized in GHGenius v3.19. CAC emission factors for alternative fuel technologies have been updated based on the most current data summarized in GHGenius v.3.19. Diesel rail CAC emission factors have been updated based on the 2008 Locomotive Emissions Monitoring Program by the Railway Association of Canada.
New “Canada” values – Breakdown of light-duty passenger vehicles (i.e. proportion of automobiles and light trucks) and GHG intensities associated with electricity production vary by province or territory. The Tool has been upgraded to include a default breakdown of light-duty passenger vehicles and GHG intensity factor for all of Canada when selecting a province/territory in the scenario input screen.
New two-scenario comparison – The Tool has been upgraded to allow users to enter inputs for up to two scenarios and includes results comparing both scenario inputs.
Improved navigation – The Tool’s navigation menu has been updated to be more intuitive and user friendly. This update includes the addition of new pages: Glossary, User Guide in text-friendly format, and Related Links.
Improved mouse-over help feature – This update of the Tool includes the addition of dashed underline marks to indicate where “mouse-over” comments are available and updated text to help users with definitions and data inputs.

APPENDIX B: Emission Factor Estimation

Factors are used to calculate fuel consumption, GHG emissions, and CAC emissions from annual vehicle travel data, as discussed in the following sections.

One topic, which affects the calculation of all factors, is vehicle classification. Classification of vehicles typically varies between different sources. GHGenius uses the most aggregate vehicle classifications, while MOBILE6.2C uses the most refined vehicle classification system. Exhibit B.1 shows how the GHG Inventory and Mobile 6.2C vehicle classifications relate and how they were used to determine emission factors for the Tool vehicle types.

**Exhibit B.1 : Vehicle Classification by Data Source**
UTEC	MOBILE 6.2C	Environment Canada GHG Inventory	GHGenius
LDPV-A	LDGV	LDGA	Light-Duty Vehicle (LDV)
LDPV-A	LDDV	LDDA
LDPV-T	LDGT1	LDGT
	LDGT2	LDGT
	LDDT12	LDDT
LDCV	LDGT3	LDGT
	LDGT4	LDGT
	LDDT34	LDDT
MDCV	HDGV2B	HDGV	Heavy-Duty Vehicle (HDV)/Bus
	HDGV3
	HDGV4
	HDGV5
	HDGV6
	HDGV7
	HDDV2B	HDDV
	HDDV3
	HDDV4
	HDDV5
	HDDV6
	HDDV7
HDCV	HDGV8A	HDGV
	HDGV8B	HDGV
	HDDV8A	HDDV
	HDDV8B	HDDV
Bus	GAS BUS	HDGV
Bus	URB BUS	HDDV
TB	N/A	N/A	N/A
LR-E	N/A	N/A	N/A
SM	N/A	N/A	N/A
LR-D	N/A	Diesel Rail Transportation	N/A
HR	N/A		N/A
FR	N/A		N/A

Note: See Glossary for definition of acronyms.

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Fuel Efficiency

Fuel efficiency is expressed in Litres per 100-km (L/100 km) for most technology types with some variations as shown in Exhibit B.2.

**Exhibit B.2 : Units for Baseline Fuel Efficiency by Vehicle Technology**
Vehicle Technology	Fuel Efficiency Units
Compressed Natural Gas	m³/100 km
Electric-Vehicle	MJ/100 km
Plug in Hybrid Electric Vehicle	MJ/100 km
Trolley Bus	MJ/100 km
Light Rail (electric)	MJ/100 p-km
Light Rail (diesel)	L/100 p-km
Subway/Metro (electric)	MJ/100 p-km
Heavy Rail (diesel)	L/100 p-km
Freight Rail (diesel)	L/100 tonne-km
All others	L/100 km

Conventional Road Vehicle Fuel Efficiency

Baseline fuel efficiencies for gasoline and diesel vehicles for each forecast year were determined based on values from Environment Canada MOBILE6.2C forecasts. These fuel efficiencies take into account the age profile of the fleet by vehicle class at the national scale. Since VKT values were provided for each of the 27 MOBILE6.2C vehicle classes considered, fuel efficiencies for each Tool vehicle type could be calculated as a weighted average of the related MOBILE6.2C vehicle classes as shown in Exhibit B.1.

Runs of MOBILE6.2C were prepared by Environment Canada for the years 1980 to 2030 using national level fleet data. The results from these runs provided CAC emission factors and fuel efficiencies for conventional road vehicles used in UTEC.

Environment Canada MOBILE6.2C forecasts predict only marginal improvements in fuel efficiency over time. Since larger improvements are expected, MOBILE6.2C fuel efficiencies for LDPV, LDCV, MDCV, HDCV, and BUS were scaled by a 0.5% annual improvement factor. This annual improvement rate is on the conservative end of fuel efficiency improvements predicted by NRCan’s Emissions Outlook document, which predicts fuel efficiency improvements in the order of 0.5% to 1% per year for most vehicle types.

The MOBILE6.2C fuel efficiency results were also modified to estimate city and highway fuel efficiencies for each vehicle class. This was a two-step process:

Determine the driving conditions assumed in the MOBILE6.2C results: In developing the Canadian version of the MOBILE6.2 model, MOBILE6.2C, Environment Canada commissioned a study to develop speed profiles as input to the model (Average Speed Estimates for MOBILE6C Emissions Forecasting, 2003). This study developed a national speed profile based on speed profiles of urban and inter-urban travel for various areas across the country. In analyzing the data used in this study, it was determined that the national speed profile included approximately 31% of VKT under highway conditions. This included inter-urban travel and approximately 10% of urban travel.
Determine the relationship between city and highway fuel efficiency: Based on fuel efficiency ratings for new vehicles, stop-and-go city driving consumes approximately 20% to 65% more fuel per kilometre than free flow highway driving, varying by vehicle model (Fuel Consumption Guide 2008, Office of Energy Efficiency, Natural Resources Canada, 2007). Based on these results and default city and highway fuel efficiencies reported in GHGenius, it was assumed that city driving consumes 30% more fuel per kilometre than highway driving.

Using these values, city and highway fuel efficiency for gasoline and diesel vehicles were generated from MOBILE6.2C results by horizon year and vehicle class.

UTEC v.3.0 fuel efficiency factors for gasoline and diesel vehicles remain unchanged from UTEC v.2.0.

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Alternative Technology Road Vehicle Fuel Efficiency

City and highway fuel efficiencies for alternative technology vehicles were determined using relative fuel efficiency factors developed based on the approach adopted in the GHGenius Tool. GHGenius uses separate relative efficiency factors for city and highway conditions, which provide a basis to determine the fuel efficiency of alternative technology vehicles from known gasoline and diesel-powered vehicle fuel efficiencies of the same vehicle type. GHGenius provides relative efficiency factors for light-duty vehicles and heavy-duty vehicles / transit buses. Relative efficiency factors for light-duty vehicles were assumed to apply to light-duty passenger and light-duty commercial vehicles. Relative efficiency factors for heavy-duty vehicles were assumed to apply to medium-duty commercial vehicles.

The relative efficiency factor is determined based on the relative efficiency of the alternative fuel / engine combination and the impact on vehicle weight changes on the relative vehicle efficiency. The relative efficiency of the alternative fuel / engine combination is the most important factor. For each alternative technology, relative efficiency is projected to improve with time at a different rate. See Chapter 39 of Documentation for Natural Resources Canada’s GHGenius Model 3.0 (S&T² Consultants, 2005), available at www.ghgenius.ca, for a more detailed description of the derivation of relative efficiency factors. Relative fuel efficiency factors for alternative technology vehicles are shown in the tables below for light-duty and heavy-duty vehicles, respectively. The factors presented are designed to modify gasoline and diesel fuel efficiency expressed in MJ/km.

UTEC v.3.0 relative fuel efficiency factors are based on outputs of GHGenius v.3.19, and are summarized in Exhibit B.3 for Light-Duty Passenger and Light-Duty Commercial Vehicles, and in Exhibit B.4 for Medium-Duty and Heavy-Duty Commercial Vehicles and Transit Buses.

**Exhibit B.3 : Relative Fuel Efficiency Factors for Alternative Technology Vehicles (MJ/km / MJ/km), Light-Duty Passenger and Light-Duty Commercial Vehicles (relative to Gasoline)**
Driving Conditions	Year	P	CNG	E10	E85	M85	HYB-G	PHEV	EV	FC
City	2006	0.98	1.06	0.99	0.94	0.95	0.59	0.44	0.29	0.40
	2011	0.96	1.05	0.99	0.93	0.94	0.57	0.43	0.29	0.39
	2016	0.94	1.02	0.99	0.92	0.93	0.55	0.42	0.28	0.39
	2021	0.92	1.00	0.99	0.91	0.92	0.54	0.41	0.29	0.38
	2026	0.91	0.98	0.99	0.90	0.91	0.53	0.41	0.29	0.38
	2031	0.90	0.97	0.99	0.90	0.90	0.53	0.41	0.29	0.37
Highway	2006	0.98	1.06	0.99	0.94	0.95	0.81	0.60	0.39	0.57
	2011	0.96	1.05	0.99	0.93	0.94	0.78	0.58	0.39	0.54
	2016	0.94	1.02	0.99	0.92	0.93	0.75	0.57	0.38	0.52
	2021	0.92	1.00	0.99	0.91	0.92	0.73	0.56	0.39	0.51
	2026	0.91	0.98	0.99	0.90	0.91	0.72	0.56	0.40	0.50
	2031	0.90	0.97	0.99	0.90	0.90	0.71	0.56	0.40	0.49

**Exhibit B.4 : Relative Fuel Efficiency Factors for Alternative Technology Vehicles (MJ/km / MJ/km), Medium-Duty and Heavy-Duty Commercial Vehicles and Transit Buses (relative to Diesel)**
Driving Conditions	Year	P	CNG	LNG	E10	E85	M85	ED10	B100	HYB-G	HYB-D	PHEV	EV	FC
City	2006	1.25	1.26	0.99	-	-	-	1.00	1.00	-	0.61	-	-	0.50
	2011	1.24	1.17	1.00	-	-	-	1.00	1.00	-	0.57	-	-	0.48
	2016	1.22	1.17	0.99	-	-	-	1.00	1.00	-	0.55	-	-	0.47
	2021	1.21	1.17	0.99	-	-	-	1.00	1.00	-	0.54	-	-	0.47
	2026	1.20	1.17	0.99	-	-	-	1.00	1.00	-	0.54	-	-	0.46
	2031	1.19	1.17	0.98	-	-	-	1.00	1.00	-	0.53	-	-	0.46
Highway	2006	1.25	1.26	0.99	-	-	-	1.00	1.00	-	0.84	-	-	0.71
	2011	1.24	1.17	1.00	-	-	-	1.00	1.00	-	0.78	-	-	0.67
	2016	1.22	1.16	0.99	-	-	-	1.00	1.00	-	0.75	-	-	0.65
	2021	1.21	1.15	0.99	-	-	-	1.00	1.00	-	0.74	-	-	0.63
	2026	1.20	1.14	0.99	-	-	-	1.00	1.00	-	0.72	-	-	0.62
	2031	1.19	1.13	0.98	-	-	-	1.00	1.00	-	0.71	-	-	0.61

Trolley Bus and Rail Vehicle Fuel Efficiency

Efficiencies for rail vehicles and trolley buses were derived from a variety of sources as outlined:

Trolley buses: 86.64 MJ/100 pass-km based on the 2010 APTA Public Transportation Fact Book (average passenger load factor of approximately 13.9);
Light Rail (electric): 77.05 MJ/100 pass-km based on the 2010 APTA Public Transportation Fact Book (average light-rail car occupancy of 23.6 passengers);
Light Rail (diesel): Fuel efficiency of 5.58 L/100 pass-km based on O-train efficiency and average light-rail car occupancy. A project summary from the Urban Transportation Showcase Program reports O-train efficiency as 1.32 L/veh-km (http://www.tc.gc.ca/eng/programs/environment-utsp-otrainlightrailproject-973.htm). The average light rail car occupancy of 23.6 passengers reported in the 2010 APTA Public Transportation Fact Book is used.
Subway/Metro (electric): 51.76 MJ/100 pass-km based on the 2010 APTA Public Transportation Fact Book (average subway/metro car occupancy of 25.0 passengers per car);
Heavy Rail (diesel): 4.49 L/100 pass-km based on the 2008 results for commuter rail from the Transportation Energy Data Book, Edition 29, Table 9.11, Oak Ridges National Laboratory (average commuter rail car occupancy of 35.6 passengers per car).
Freight Rail (diesel): 0.60 L/100 tonne-km based on the 2008 results for freight operations from the Locomotive Emissions Monitoring Program 2008, Railway Association of Canada.

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Greenhouse Gas Emission Factors

GHG emissions are estimated based on fuel and electricity consumption from travel. The Tool calculates the GHG emissions from fuel combustion and the upstream fuel cycle effects:

Vehicle operation GHG emissions are released directly from the tailpipe of a vehicle.
Upstream GHG emissions are created and released from production of electricity used by electric vehicles (i.e. trolleys and light rail) as well as from the production, refining and transportation of transportation fuels (i.e. from wells to pump).

It is important to note that the Tool does not consider life-cycle emissions associated with the manufacture and end‑of‑life recycling of vehicles.

Global Warming Potential

In order to measure the impact of the various gases involved in global warming using a single unit of measurements, the scientific community has adopted a standard based on the impact of one tonne of CO₂ over a 100-year time frame. The impacts of other gas types are compared to CO₂ over the same time frame to produce standard global warming potentials (GWP), expressed in tonnes CO₂ equivalent (CO₂e). GWP values for nitrous oxide and methane are taken from the United Nations Framework Convention on Climate Change (UNFCC, http://unfccc.int/ghg_data/items/3825.php).

Vehicle Operation GHG Emission Factors for Conventional Vehicles

Direct GHG Emission Factors are used to determine the tailpipe GHG emissions of CO₂, N₂O, and CH₄ from urban transportation fuel use. Direct GHG emission factors are measured in g/L except for compressed natural gas, which is measured in g/m³. Vehicle operation GHG emission factors for conventional vehicles (i.e. gasoline and diesel powered) are based on the National Inventory Report on greenhouse gas emissions prepared by Environment Canada.

UTEC v.3.0 GHG emission factors for gasoline and diesel road vehicles are based on the 1990-2008 National Inventory Report by Environment Canada.

Gasoline and diesel emission factors were taken from the GHG Inventory for each vehicle type as shown in Exhibit B.1. Since emissions control technology (such as the type of catalytic converter) affects the emission rates of N₂O and CH₄, the fleet penetration of each technology (measured by the age of the fleet) will affect the fleet’s overall emission factors. The terminology used by Environment Canada to refer to the most recent and preceding emission control technologies are Tier 1 and Tier 0 for gas-powered vehicles and Advanced Control and Moderate Control for diesel-powered vehicles.

For 2011 road vehicles, emission factors were calculated as a weighted average of Tier 1 / Tier 0 and Advanced Control / Moderate Control based on the proportion of the national vehicle fleet built since 1996. Information of the vehicle fleet composition for light- and heavy-duty vehicles has been updated and was obtained from the 2009 Canadian Vehicle Survey: Annual published by Statistics Canada (http://www.statcan.gc.ca/bsolc/olc-cel/olc-cel?catno=53-223-X&CHROPG=1&lang=eng). Emission factors for later model years were set to the Tier 1 and Advanced Control values.

Vehicle Operation GHG Emission Factors for Alternative Technology Vehicles

Similar to relative efficiency factors discussed earlier, GHG emission factors for alternative technology vehicles were determined using relative emission factors derived from GHGenius. GHGenius uses relative GHG emission factors, which provide a basis to determine CO₂, N₂O, and CH₄ emission factors for alternative technology vehicles from known gasoline and diesel-powered emission factors of the same vehicle type. GHGenius provides relative emission factors for light-duty vehicles and heavy-duty vehicles / transit buses. Relative emission factors for light-duty vehicles were assumed to apply to light-duty passenger and light-duty commercial vehicles. Relative efficiency factors for heavy-duty vehicles were assumed to apply to medium-duty and heavy-duty commercial vehicles as well as buses. The approach and sources used in determining these relative emission factors are described in Chapter 40 of Documentation for Natural Resources Canada’s GHGenius Model 3.0 (NRCan, 2005), available at www.ghgenius.ca.

UTEC v.3.0 relative GHG emission factors for alternative technology vehicles are based on outputs of GHGenius v.3.19 and are shown in Exhibit B.5.

**Exhibit B.5 : Relative GHG Emission Factors for Alternative Technology Vehicles**
Vehicle Type	GHG	P	CNG	LNG	E10	E85	M85	ED10	B100	HYB-G	HYB-D	PHEV	EV	FC
LDPV, LDCV	CO₂	0.67	0.85	-	0.96	0.16	0.56	-	-	1	-	1	-	-
	CH₄	0.77	22.7	-	1.01	1.16	0.39	-	-	1	-	1	-	-
	N₂O	0.77	0.31	-	0.39	0.62	0.25	-	-	1	-	1	-	-
MDCV, HDCV, BUS	CO₂	0.57	0.71	0.49	-	-	-	0.9	0.01	-	1	-	-	-
	CH₄	0.53	12.74	8.77	-	-	-	0.96	0.96	-	1	-	-	-
	N₂O	0.53	0.85	0.58	-	-	-	0.96	0.96	-	1	-	-	-

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Note: Factors for LDPV/LDCV are relative to gasoline emission factors of the same vehicle type, factors for MDCV/HDCV/BUS are relative to dieses emission factors of the same vehicle type.

All electric vehicles have no direct GHG emissions. Hybrid vehicle emission factors are assumed to be the same per litre as the primary fuel (e.g., gas for LDPV, diesel for BUS) for the vehicle type under consideration.

Vehicle Operation GHG Emission Factors for Diesel Rail Vehicles

Emission factors for diesel rail transportation – light rail, heavy rail and freight rail – are based on the GHG inventory emission factors for Diesel Train Railways from the 1990-2008 National Inventory Report prepared by Environment Canada.

Upstream Fuel Cycle GHG Emission Factors

Upstream fuel cycle GHG emission factors are used to estimate the ‘upstream’ fuel cycle GHG emissions associated including fuel refining and transportation. They are fuel specific and were determined from GHGenius. GHGenius estimates the GHG emissions in CO₂ equivalents from fuel dispensing, fuel distribution and storage, fuel production, feedstock transmission, feedstock recovery, land use changes, fertilizer manufacture, gas leaks and flares, and emissions displaced. Default results that are used represent average industry conditions in Canada. There are many assumptions involved in these calculations, such as the distance the fuel is transported and the fuel feedstock. The user should refer to GHGenius (www.ghgenius.ca) if detailed analysis of upstream GHG emissions is required.

The feedstock for the ethanol in E10, E85, and ED10 is assumed to be corn. The feedstock for biodiesel is assumed to be soybeans. The fuel cells are assumed to run on methanol.

UTEC v.3.0 upstream fuel cycle GHG emission factors are based on outputs of GHGenius v.3.19.

Indirect Electricity Production GHG Emission Factors

Indirect electricity production GHG emission factors are used to determine the GHG emissions associated with electric vehicles. They are specified in kg CO₂e/MJ of electricity consumed. The factors are province- and territory-specific based on the mix of electricity generation methods in each region. These factors were determined from the electricity GHG emission factors reported in the 1990-2008 National Inventory Report (Table A-13) by province and territory. Forecasts of electrical emission factors are not available so the factors do not change over the model years.

UTEC v.3.0 includes a Canada-wide emission factor, which was not available in previous versions of the Tool.

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Criteria Air Contaminant Emission Factors

Vehicle Operation CAC Emission Factors for Conventional Vehicles

Direct CAC emission factors for conventional vehicles were developed from forecasts of CAC emission factors from MOBILE6.2C developed by Environment Canada. These factors were estimated based on national speed profiles developed from urban and inter-urban travel (Average Speed Estimates for MOBILE6C Forecasting, Environment Canada, 2003). CAC emission factors are very sensitive to driving conditions and driving speed, in particular. As such, if the speed profile of the fleet under consideration is substantially different from the national average, CAC emission estimations will be less accurate.

For conventional vehicles, MOBILE6.2C estimates emission factors for CO, NO_x, SO₂, VOC, as well as particulate matter (TPM, PM₁₀, and PM_2.5) from fuel combustion and brake and tire wear. Emission factors were provided by Environment Canada for all the model years for the 27 vehicle classifications shown in Exhibit B.1. Substantial improvements in CAC emission factors are forecast over time. CAC emission factors were further reduced by 0.5% per year, corresponding to the annual improvement factor applied to MOBILE6.2C fuel efficiencies.

Since VKT values were provided for each of the 27 MOBILE6.2C vehicle classes considered, emission factors for each vehicle type could be calculated as a weighted average of the related MOBILE6.2C vehicle classes.

Vehicle Operation CAC Emission Factors for Alternative Technology Vehicles

CAC emission factors for alternative technology vehicles were determined using relative emission factors derived from GHGenius. GHGenius uses relative CAC emission factors, which provide a basis to determine CO, NO_x, SO₂, VOCs, and TPM emission factors for alternative technology vehicles from known gasoline- and diesel-powered emission factors of the same vehicle type. GHGenius provides relative emission factors for light-duty vehicles and heavy-duty vehicles / transit buses. Relative emission factors for light-duty vehicles were assumed to apply to light-duty passenger and light-duty commercial vehicles. Relative emission factors for light-duty vehicles were assumed to apply to light-duty passenger and light-duty commercial vehicles. Relative efficiency factors for heavy-duty vehicles were assumed to apply to medium-duty and heavy-duty commercial vehicles as well as buses.

The approach and sources used in determining these relative emission factors are described in Chapter 40 of Documentation for Natural Resources Canada’s GHGenius Model 3.0 (NRCan, 2005), available at www.ghgenius.ca.

The particulate matter multiplication factor was assumed to apply to all particulate emission factors (TPM, PM₁₀, and PM_2.5).

For electric road vehicles, the CO, NO_x, SO₂, and VOC emissions were assumed to be zero; however, even though these vehicles have no exhaust, they do generate particulate matter emissions from brake and tire wear. Based on MOBILE6.2C factors for gas and diesel vehicles, the average proportion of TPM, PM₁₀, and PM_2.5 emissions from brake and tire wear was determined for each vehicle type. These values were used as multiplication factors to determine particulate matter emissions from road-based electric vehicles.

UTEC v.3.0 relative CAC emission factors for alternative technology vehicles are based on outputs of GHGenius v.3.19 and are shown in Exhibit B.6.

**Exhibit B.6 : Relative CAC Emission Factors for Alternative Technology Vehicles**
Vehicle Type	CAC	Vehicle Technology
Vehicle Type	CAC	P	CNG	LNG	E10	E85	M85	ED10	B100	HYB-G	HYB-D	PHEV	EV	FC
LDPV	CO	0.60	0.27	-	0.97	0.68	0.70	-	-	0.56	-	0.28	-	-
	NO_x	0.90	1.53	-	0.99	0.92	0.93	-	-	0.56	-	0.28	-	-
	SO₂	0.28	0.13	-	0.97	0.67	0.51	-	-	0.62	-	0.31	-	-
	VOC	0.16	0.11	-	0.25	0.02	0.23	-	-	0.14	-	0.07	-	-
	TPM	0.25	1.61	-	0.96	0.52	0.55	-	-	0.56	-	0.28	0.60	0.60
	PM₁₀	0.25	1.61	-	0.96	0.52	0.55	-	-	0.56	-	0.28	0.60	0.60
	PM_2.5	0.25	1.61	-	0.96	0.52	0.55	-	-	0.56	-	0.28	0.42	0.42
LDCV	CO	0.60	0.27	-	0.97	0.68	0.70	-	-	0.56	-	0.28	-	-
	NO_x	0.90	1.53	-	0.99	0.92	0.93	-	-	0.56	-	0.28	-	-
	SO₂	0.28	0.13	-	0.97	0.67	0.51	-	-	0.62	-	0.31	-	-
	VOC	0.16	0.11	-	0.25	0.02	0.23	-	-	0.14	-	0.07	-	-
	TPM	0.25	1.61	-	0.96	0.52	0.55	-	-	0.56	-	0.28	0.40	0.40
	PM₁₀	0.25	1.61	-	0.96	0.52	0.55	-	-	0.56	-	0.28	0.40	0.40
	PM_2.5	0.25	1.61	-	0.96	0.52	0.55	-	-	0.56	-	0.28	0.28	0.28
MDCV/ HDCV	CO	0.10	0.10	0.10	-	-	-	0.85	0.50	-	-	-	-	-
	NO_x	1.00	0.30	0.30	-	-	-	1.00	1.10	-	-	-	-	-
	SO₂	3.09	0.99	0.99	-	-	-	1.13	0.31	-	-	-	-	-
	VOC	0.72	0.50	0.50	-	-	-	0.90	0.85	-	-	-	-	-
	TPM	1.00	0.45	0.45	-	-	-	0.80	0.50	-	-	-	-	0.29
	PM₁₀	1.00	0.45	0.45	-	-	-	0.80	0.50	-	-	-	-	0.29
	PM_2.5	1.00	0.45	0.45	-	-	-	0.80	0.50	-	-	-	-	0.14
BUS	CO	0.10	0.10	0.10	-	-	-	0.85	0.50	-	0.67	-	-	-
	NO_x	1.00	0.30	0.30	-	-	-	1.00	1.10	-	0.67	-	-	-
	SO₂	3.09	0.99	0.99	-	-	-	1.13	0.31	-	0.67	-	-	-
	VOC	0.72	0.50	0.50	-	-	-	0.90	0.85	-	0.66	-	-	-
	TPM	1.00	0.45	0.45	-	-	-	0.80	0.50	-	0.67	-	-	0.29
	PM₁₀	1.00	0.45	0.45	-	-	-	0.80	0.50	-	0.67	-	-	0.29
	PM_2.5	1.00	0.45	0.45	-	-	-	0.80	0.50	-	0.67	-	-	0.14

Note: Factors for LDPV/LDCV are relative to gasoline emission factors of the same vehicle type, factors for MDCV/HDCV/BUS are relative to diesel emission factors of the same vehicle type.

Vehicle Operation CAC Emission Factors for Diesel Rail Vehicles

CAC emission factors for diesel-powered rail (light rail, heavy rail and freight rail) are based on the railway operations CAC emissions reported in the Locomotive Emissions Monitoring (LEM) Program (Railway Association of Canada). Emission factors reported in LEM Program are provided for CO, NO_x, SO₂, VOC, and TPM in grams per litre. Fuel efficiencies for each rail mode are used to convert the estimate emissions to grams per passenger-kilometre.

For UTEC v.3.0, diesel light rail and heavy rail factors are based on 2005 data while freight rail factors are based on 2008 data reported in the LEM Program 2008 report.

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UTEC 3.1

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What is UTEC?

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What vehicle types and fuel technologies are considered?

What are the key inputs?

What are the main sources of data?

How do I tailor UTEC to my local conditions?

How has UTEC been upgraded?

Fuel Efficiency

Greenhouse Gas Emission Factors

Criteria Air Contaminant Emission Factors