- History
- Scope of GHGenius
- GHGenius Inventory Data
- GHGenius Impact Assessment
- GHGenius Results
- Analysis Tools
- Computing Platform
The GHGenius model has been developed by (S&T)2 Consultants Inc. It was originally based on the 1999 version of Dr. Mark Delucchi's Lifecycle Emissions Model (LEM). GHGenius is capable of analyzing the emissions of many contaminants associated with the production and use of traditional and alternative transportation fuels.
Dr. Mark Delucchi developed the first version of his Lifecycle Emissions Model (LEM) during the period of 1987-1993. This resulted in the development of a spreadsheet model based on Lotus software for AppleTM computers, which contained capabilities for predicting emissions of greenhouse gases and criteria non-greenhouse gases for some alternative fuels of potential interest in the transportation sector. The model was comprehensive in scope and level of detail, and, hence, required input of extensive information on the energy usage for fuel production; distribution and related fuel cycle sources, as well as factors for emissions of non-greenhouse gases from these sources and motor vehicles.
Delucchi updated LEM in 1997, this work focused primarily on including recent data for motor fuel production, processing, distribution and use in the United States, and incorporation of improved algorithms for predicting non-greenhouse gas emissions from motor vehicles based on the U.S. EPA Mobile 5 model. A partial Canadianization of LEM was completed by Delucchi for Natural Resources Canada in late 1998 through to March 1999, drawing from information on the production and distribution of conventional and alternative fuels that was provided by NRCan, Statistics Canada, and some other Canadian government agencies.
The partially Canadianized version of the fuel cycle model prepared by Delucchi in 1999 was the basis for the development of GHGenius. It was first converted to a Windows platform and used for the preparation of the report "Alternative and Future Fuels and Energy Sources for Road Vehicles" prepared for the Transportation Issue Table, National Climate Change Process.
In 2001, Levelton and (S&T)2 worked with Delucchi to expand GHGenius to be capable of projections to the year 2050, added Mexico to the model and added the capability of regional analysis for Canada and the United States. Delucchi was also working on a second revision of his model during this period and some of the revised methodology was incorporated into GHGenius.
The models GHGenius and Delucchi's LEM share the same basic approach but they differ in a number of areas. GHGenius has many more alternative fuel pathways but these are applied to traditional light and heavy-duty vehicle whereas LEM has pathways that include mini-buses, mini-cars, motor scooters, bicycles, transit systems and industrial vehicles. GHGenius has more detailed output for all contaminants and an economic assessment of the lifecycle cost of greenhouse gas emission reductions.
The later versions of GHGenius (3.0 onwards) have been developed in Excel rather than Lotus 123. Delucchi's LEM had also been independently converted to an Excel platform. The macro's in the two excel models have different code, but achieve the same results. GHGenius also has been converted to metric units rather than imperial measure. Since 2003 all of the model development has been done by (S&T)2 Consultants Inc.
GHGenius focuses on the life cycle assessment (LCA) of current and future fuels for transportation applications. It also considers a few circumstances where the fuels could be used in stationary applications rather than for transportation.
GHGenius can predict emissions for past, present and future years through to 2050 using historical data or correlations for changes in energy and process parameters with time or government forecasts that are stored in the model.
GHGenius can perform the LCA for specific regions (east, central or west) of Canada, and the United States. The model can also be run for Mexico, India, and four regions of the European Union. For Canada, it is also possible to model many of the processes by province. It is also possible to model regions of North America.
All of the steps in the life cycle are included in the model from raw material acquisition to end-use. The fuel cycle segments considered in the model are as follows:
The model is capable of analyzing the emissions from conventional and alternative fuelled internal combustion engines or fuel cells for light duty vehicles, for class 3-6 medium-duty trucks, for class 7 and 8 heavy-duty trucks, for urban buses and for a combination of buses and trucks, and for light and heavy duty battery powered electric vehicles. There are over 200 vehicle and fuel combinations possible with the model.
For light duty internal combustion vehicles the fuels that the model is capable of analyzing include:
For light duty fuel cell vehicles the fuels that the model is capable of analyzing include:
Light duty electric vehicles with the national or regional mixes of electricity generation.
The light duty pathways are summarized in the following table. There are also a few indirect pathways such as natural gas to FT Distillate to hydrogen that cannot be easily shown in the table.
Table 1: Light Duty Vehicle and Fuel Pathways
For heavy duty internal combustion vehicles the fuels that can be analyzed include:
For heavy duty fuel cell applications the fuels that are included in the model are:
The heavy-duty vehicle pathways are summarized in the following table. There are again some indirect pathways that are not shown.
Table 2: Heavy-Duty Vehicle and Fuel Pathways
A critical issue for life cycle assessment is the quality of the data used for undertaking the analysis. The type of data used is usually the single most important issue when life cycle assessments from different sources are compared. GHGenius has data for Canada, the United States, Mexico, India, and four regions of the European Union for many of the steps in the various fuel processes and it allows the user to provide data for some steps in the process to provide the highest degree of flexibility possible in the model without compromising the quality of the results.
Much of the data for the United States has been sourced from the US DOE Energy Information Administration. This includes both historical data and future projections for processes such as electric power, crude oil, refined petroleum products, natural gas and coal production. In other cases, data for US processes is derived from US Census and US EPA reports.
For Canada, reports produced by Statistics Canada, Natural Resources Canada, Environment Canada and the National Energy Board have been used as data sources for information on the production of power, crude oil, refined petroleum products, natural gas and coal production. Industry associations such as the Canadian Association of Petroleum Producers (CAPP) and the Canadian Gas Association (CGA) have also been used as sources of data.
The non-energy related process emissions in the model are calculated based mostly on the US EPA AP-42 emission factors. The emissions from vehicles for conventional fuels are derived from the Environment Canada model Mobile6.2C. For the alternative fuels, the emissions are calculated based on relative emission factors. In some cases, these relative emission factors are based on analysis performed by the US EPA and in other cases from an assessment of the available literature.
For other data needs, the hierarchy used in the model has been to use industry average values where available, then actual operating plant operating data, then engineering design data and failing the availability of any of that data then estimated data from pilot plants, engineering simulations or scientific experiments is used.
GHGenius is populated with data for all of the processes included in the model but an input sheet is provided so that the user can readily make changes to many of the steps in the lifecycle in order to customize the LCA to their particular needs. The user can also make changes in many of the specific steps in the life cycle to develop a better understanding of the sensitivity of the processes to these changes. This flexibility makes the model a powerful tool for analysis.
GHGenius focuses on estimating life cycle emissions for three impact categories; the primary greenhouse gases, the criteria pollutants from combustion sources and the energy used. The specific categories that are in the model include:
Greenhouse Gases
The GHG emissions are also calculated for the carbon dioxide equivalent emission. The user can choose to use the Intergovernmental Panel on Climate Change (IPCC) 20 or 100 year global warming potentials (GWP) or other values that the user may wish to use.
In the case of the greenhouse gases, GHGenius can assess the cost effectiveness of various strategies using the results from the lifecycle assessment and the fuel and vehicle costs that are input by the users. This tool is particularly helpful in comparing vehicle related GHG reduction strategies with fuel related strategies on a common basis.
Other Air Contaminants
The non-methane organic gases are also weighted according to their ozone forming potentials.
Energy Use
GHGenius produces a wide range of outputs designed to meet the needs of the users. The specific output data includes:
For all of this data the model can be run for specific regions within a country or regionally for the continent and thus the results can be provided for specific regions.
There are a number of internal checks on the data and calculations included in GHGenius. These include checks to ensure that power produced and consumed by processes are internally consistent. Checks are also provided for the calculation of the separate gases and the CO2 equivalent emissions. These can be calculated two ways by the model and the comparison of the results of the two methods ensures internal consistency in the model.
GHGenius has three tools to enable the user to undertake more complex scenario investigations.
There are two Sensitivity Solvers which allows the user to vary any input cell over a range and determine the impact on up to four output cells in the model. There is also a two dimensional solver that can vary two input cells at a time. The results are also automatically graphed.
The third tool is a built in Monte Carlo simulation tool. Up to eight input cells can be varied according to user selected distributions and values and the impact on up to 21 output cells can be determined. The results can also be presented graphically.
GHGenius now runs in Excel 2000 or later. The user must also accept the license terms and conditions prior to using the model.
History
Dr. Mark Delucchi developed the first version of his Lifecycle Emissions Model (LEM) during the period of 1987-1993. This resulted in the development of a spreadsheet model based on Lotus software for AppleTM computers, which contained capabilities for predicting emissions of greenhouse gases and criteria non-greenhouse gases for some alternative fuels of potential interest in the transportation sector. The model was comprehensive in scope and level of detail, and, hence, required input of extensive information on the energy usage for fuel production; distribution and related fuel cycle sources, as well as factors for emissions of non-greenhouse gases from these sources and motor vehicles.
Delucchi updated LEM in 1997, this work focused primarily on including recent data for motor fuel production, processing, distribution and use in the United States, and incorporation of improved algorithms for predicting non-greenhouse gas emissions from motor vehicles based on the U.S. EPA Mobile 5 model. A partial Canadianization of LEM was completed by Delucchi for Natural Resources Canada in late 1998 through to March 1999, drawing from information on the production and distribution of conventional and alternative fuels that was provided by NRCan, Statistics Canada, and some other Canadian government agencies.
The partially Canadianized version of the fuel cycle model prepared by Delucchi in 1999 was the basis for the development of GHGenius. It was first converted to a Windows platform and used for the preparation of the report "Alternative and Future Fuels and Energy Sources for Road Vehicles" prepared for the Transportation Issue Table, National Climate Change Process.
In 2001, Levelton and (S&T)2 worked with Delucchi to expand GHGenius to be capable of projections to the year 2050, added Mexico to the model and added the capability of regional analysis for Canada and the United States. Delucchi was also working on a second revision of his model during this period and some of the revised methodology was incorporated into GHGenius.
The models GHGenius and Delucchi's LEM share the same basic approach but they differ in a number of areas. GHGenius has many more alternative fuel pathways but these are applied to traditional light and heavy-duty vehicle whereas LEM has pathways that include mini-buses, mini-cars, motor scooters, bicycles, transit systems and industrial vehicles. GHGenius has more detailed output for all contaminants and an economic assessment of the lifecycle cost of greenhouse gas emission reductions.
The later versions of GHGenius (3.0 onwards) have been developed in Excel rather than Lotus 123. Delucchi's LEM had also been independently converted to an Excel platform. The macro's in the two excel models have different code, but achieve the same results. GHGenius also has been converted to metric units rather than imperial measure. Since 2003 all of the model development has been done by (S&T)2 Consultants Inc.
Scope of GHGenius
GHGenius focuses on the life cycle assessment (LCA) of current and future fuels for transportation applications. It also considers a few circumstances where the fuels could be used in stationary applications rather than for transportation.
GHGenius can predict emissions for past, present and future years through to 2050 using historical data or correlations for changes in energy and process parameters with time or government forecasts that are stored in the model.
GHGenius can perform the LCA for specific regions (east, central or west) of Canada, and the United States. The model can also be run for Mexico, India, and four regions of the European Union. For Canada, it is also possible to model many of the processes by province. It is also possible to model regions of North America.
All of the steps in the life cycle are included in the model from raw material acquisition to end-use. The fuel cycle segments considered in the model are as follows:
- Vehicle Operation
Emissions associated with the use of the fuel in the vehicle. Includes all greenhouse gases. - Fuel Dispensing at the Retail Level
Emissions associated with the transfer of the fuel at a service station from storage into the vehicles. Includes electricity for pumping, fugitive emissions and spills. - Fuel Storage and Distribution at all Stages
Emissions associated with storage and handling of fuel products at terminals, bulk plants and service stations. Includes storage emissions, electricity for pumping, space heating and lighting. - Fuel Production (as in production from raw materials)
Direct and indirect emissions associated with conversion of the feedstock into a saleable fuel product. Includes process emissions, combustion emissions for process heat/steam, electricity generation, fugitive emissions and emissions from the life cycle of chemicals used for fuel production cycles. - Feedstock Transport
Direct and indirect emissions from transport of feedstock, including pumping, compression, leaks, fugitive emissions, and transportation from point of origin to the fuel refining plant. Import/export, transport distances and the modes of transport are considered. - Feedstock Production and Recovery
Direct and indirect emissions from recovery and processing of the raw feedstock, including fugitive emissions from storage, handling, upstream processing prior to transmission, and mining. - Feedstock Upgrading
The direct and indirect emissions from the upgrading of bitumen to synthetic crude oil, including fugitive emissions from processing. This stage is also utilized for two step processes such as biodiesel and renewable diesel where an oil is produced first and then the fuel is produced from the oil. - Fertilizer Manufacture
Direct and indirect life cycle emissions from fertilizers, and pesticides used for feedstock production, including raw material recovery, transport and manufacturing of chemicals. This is not included if there is no fertilizer associated with the fuel pathway. - Land use changes and cultivation associated with biomass derived fuels
Emissions associated with the change in the land use in cultivation of crops, including N2O from application of fertilizer, changes in soil carbon and biomass, methane emissions from soil and energy used for land cultivation. - Carbon in Fuel from Air
Carbon dioxide emissions credit arising from use of a renewable carbon source that obtains carbon from the air. - Leaks and flaring of greenhouse gases associated with production of oil and gas
Fugitive hydrocarbon emissions and flaring emissions associated with oil and gas production. - Emissions displaced by co-products of alternative fuels
Emissions displaced by co-products of various pathways. System expansion is used to determine displacement ratios for co-products from biomass pathways. - Vehicle assembly and transport
Emissions associated with the manufacture and transport of the vehicle to the point of sale, amortized over the life of the vehicle. - Materials used in the vehicles
Emissions from the manufacture of the materials used to manufacture the vehicle, amortized over the life of the vehicle. Includes lube oil production and losses from air conditioning systems.
The model is capable of analyzing the emissions from conventional and alternative fuelled internal combustion engines or fuel cells for light duty vehicles, for class 3-6 medium-duty trucks, for class 7 and 8 heavy-duty trucks, for urban buses and for a combination of buses and trucks, and for light and heavy duty battery powered electric vehicles. There are over 200 vehicle and fuel combinations possible with the model.
For light duty internal combustion vehicles the fuels that the model is capable of analyzing include:
- Conventional gasoline (including hybrids),
- Low sulphur or reformulated gasoline (light duty or hybrid vehicles),
- Gasoline from biomass or natural gas,
- Diesel fuel (regular or low sulphur) including hybrids,
- Natural gas (compressed or liquefied),
- Methanol from natural gas, coal, wood, or landfill gas in 0 - 100 % blends in conventional or reformulated gasoline,
- Mixed Alcohols from natural gas, refuse derived fuel or wood,
- Liquefied petroleum gases (LPG) from refineries and natural gas plants (propane and butane mixture),
- Hythane™ (a mixture of natural gas and hydrogen),
- Hydrogen from electrolysis or reforming natural gas (compressed or liquefied),
- Ethanol from corn, whole corn plants, sugar beets, sugar cane, wheat, barley, peas, sorghum, or a mix of 0-100 % wood or agricultural cellulosic material (four different ag feedstocks) in 0 - 100 % blends in conventional or reformulated gasoline,
- Synthetic natural gas from coal or wood,
- Butanol from corn,
- Fischer Tropsch Distillate from natural gas, wood, RDF, LFG, or coal (including hybrids),
- Refined Bio-Oil from wood or ag residues,
- Upgraded pyrolysis oil,
- Biodiesel blends with biodiesel produced from canola, soybeans, camelina, tallow, yellow grease, palm, fish oil, algae, jatropha, palm sludge, or spent bleaching earth (including hybrids),
- Renewable gasoline from any oil that can make biodiesel,
- Biomethane from landfill gas or anaerobic digestion of manure and/or ag residues.
For light duty fuel cell vehicles the fuels that the model is capable of analyzing include:
- Methanol from natural gas or coal reformed onboard the vehicle,
- Any ethanol reformed onboard the vehicle,
- Gasoline, or FTD reformed onboard the vehicle,
- Hydrogen from electrolysis (compressed or liquefied),
- Hydrogen from reforming natural gas, methanol, any ethanol, liquid petroleum gases, gasoline, or FTD,
- Hydrogen from coal or biomass,
- Hydrogen from nuclear thermo cracking of water.
Light duty electric vehicles with the national or regional mixes of electricity generation.
The light duty pathways are summarized in the following table. There are also a few indirect pathways such as natural gas to FT Distillate to hydrogen that cannot be easily shown in the table.
Table 1: Light Duty Vehicle and Fuel Pathways
| Gasoline | Diesel | Biodiesel | FTD | Methanol | Ethanol | Butanol | Mixed Alcohols | NG | LPG | Hydrogen | Hythane | Elec | |
| Crude Oil | ICE FC | ICE | ICE | FC | EV | ||||||||
| Coal | ICE | ICE FC | ICE | FC | EV | ||||||||
| Natural Gas | ICE FC | ICE FC | ICE | ICE | ICE | ICE FC | ICE | EV | |||||
| Landfill Gas | ICE | ICE FC | ICE | FC | |||||||||
| Manure | ICE | ||||||||||||
| Wood or Grass | ICE | ICE | ICE | ICE FC | ICE FC | ICE | ICE | FC | EV | ||||
| Corn | ICE FC | ICE | FC | ||||||||||
| Sugar Cane | ICE FC | ||||||||||||
| Sugar Beets | ICE FC | ||||||||||||
| Wheat | ICE FC | FC | |||||||||||
| Barley | ICE FC | ||||||||||||
| Peas | ICE FC | ||||||||||||
| Sorghum | ICE FC | ||||||||||||
| Wheatstover | ICE FC | ||||||||||||
| Soybeans | ICE | ICE | ICE | ||||||||||
| Canola | ICE | ICE | ICE | ||||||||||
| Palm | ICE | ICE | ICE | ||||||||||
| Camelina | ICE | ICE | ICE | ||||||||||
| Tallow | ICE | ICE | ICE | ||||||||||
| Yellow Grease | ICE | ICE | ICE | ||||||||||
| Jatropha | ICE | ICE | ICE | ||||||||||
| Algae | ICE | ICE | ICE | ||||||||||
| Marine Oils | ICE | ICE | ICE | ||||||||||
| Palm Sludge | ICE | ICE | ICE | ||||||||||
| SBE | ICE | ICE | ICE | ||||||||||
| RDF | ICE | ICE | |||||||||||
| Electricity | ICE FC | ICE |
For heavy duty internal combustion vehicles the fuels that can be analyzed include:
- Diesel fuel,
- Low sulphur diesel fuel,
- Gasoline,
- Hybrid vehicles,
- Battery powered vehicles,
- DME (dimethyl ether),
- Liquefied petroleum gases (LPG) from refineries and natural gas plants (propane and butane mixture),
- Hythane™ (a mixture of natural gas and hydrogen from reforming natural gas),
- Diesel fuel from Fischer-Tropsch (FTD) synthesis of natural gas, coal, wood or RDF and mixes of diesel and FTD,
- Ethanol from wet stover, corn, sugar cane, sugar beets, wheat, barley, peas, sorghum, or a mix of 0-100 % wood or four agricultural cellulosic materials in 0 - 100 % blends in diesel fuel,
- Ethanol as above but in gasoline blends,
- Biodiesel from soybeans, canola, palm, camelina, tallow, yellow grease, algae, jatropha, palm sludge, spent bleaching earth or marine oils in 0-100% blends in diesel fuel in heavy duty applications,
- Methanol made from natural gas, coal, wood or landfill gas,
- Mixed alcohols from wood, RDF or natural gas,
- HRD from all biodiesel feedstocks,
- Synthetic natural gas from coal or wood,
- Biomethane from manure or agricultural residues
For heavy duty fuel cell applications the fuels that are included in the model are:
- Methanol from natural gas, coal, or landfill gas reformed onboard the vehicle,
- Hydrogen from electrolysis (compressed or liquefied),
- Hydrogen from reforming natural gas, methanol, any ethanol, liquid petroleum gases, gasoline, FTD, coal or wood,
- Hydrogen from nuclear thermo cracking of water.
The heavy-duty vehicle pathways are summarized in the following table. There are again some indirect pathways that are not shown.
Table 2: Heavy-Duty Vehicle and Fuel Pathways
| Diesel or Blends | FTD | DME | Methanol | Ethanol | Butanol | Mixed Alcohols | Biodiesel | HRD | HRJ | NG | LPG | Hydrogen | Hythane | |
| Crude Oil | ICE | ICE | FC | |||||||||||
| Coal | ICE | ICE FC | ICE | |||||||||||
| Natural Gas | ICE | ICE | ICE FC | ICE | ICE | ICE | ICE FC | ICE | ||||||
| Landfill Gas | ICE FC | ICE | FC | |||||||||||
| Manure | ICE | |||||||||||||
| Wood or Grass | ICE | ICE | ICE | ICE | ICE | FC | ||||||||
| Corn | ICE | ICE | FC | |||||||||||
| Sugar Cane | ICE | |||||||||||||
| Sugar Beets | ICE | |||||||||||||
| Wheat | ICE | FC | ||||||||||||
| Barley | ICE | |||||||||||||
| Peas | ICE | |||||||||||||
| Sorghum | ICE | |||||||||||||
| Wet stover | ICE | |||||||||||||
| Soybeans | ICE | ICE | ICE | |||||||||||
| Canola | ICE | ICE | ICE | |||||||||||
| Palm Oil | ICE | ICE | ICE | |||||||||||
| Camelina | ICE | ICE | ICE | |||||||||||
| Tallow | ICE | ICE | ICE | |||||||||||
| Jatropha | ICE | ICE | ICE | |||||||||||
| Algae | ICE | ICE | ICE | |||||||||||
| Yellow Grease | ICE | ICE | ICE | |||||||||||
| Marine Oils | ICE | ICE | ICE | |||||||||||
| Palm Sludge | ICE | ICE | ICE | |||||||||||
| SBE | ICE | ICE | ICE | |||||||||||
| RDF | ICE | ICE | ||||||||||||
| Electricity | ICE FC | ICE | ||||||||||||
| Nuclear | FC |
GHGenius Inventory Data
A critical issue for life cycle assessment is the quality of the data used for undertaking the analysis. The type of data used is usually the single most important issue when life cycle assessments from different sources are compared. GHGenius has data for Canada, the United States, Mexico, India, and four regions of the European Union for many of the steps in the various fuel processes and it allows the user to provide data for some steps in the process to provide the highest degree of flexibility possible in the model without compromising the quality of the results.
Much of the data for the United States has been sourced from the US DOE Energy Information Administration. This includes both historical data and future projections for processes such as electric power, crude oil, refined petroleum products, natural gas and coal production. In other cases, data for US processes is derived from US Census and US EPA reports.
For Canada, reports produced by Statistics Canada, Natural Resources Canada, Environment Canada and the National Energy Board have been used as data sources for information on the production of power, crude oil, refined petroleum products, natural gas and coal production. Industry associations such as the Canadian Association of Petroleum Producers (CAPP) and the Canadian Gas Association (CGA) have also been used as sources of data.
The non-energy related process emissions in the model are calculated based mostly on the US EPA AP-42 emission factors. The emissions from vehicles for conventional fuels are derived from the Environment Canada model Mobile6.2C. For the alternative fuels, the emissions are calculated based on relative emission factors. In some cases, these relative emission factors are based on analysis performed by the US EPA and in other cases from an assessment of the available literature.
For other data needs, the hierarchy used in the model has been to use industry average values where available, then actual operating plant operating data, then engineering design data and failing the availability of any of that data then estimated data from pilot plants, engineering simulations or scientific experiments is used.
GHGenius is populated with data for all of the processes included in the model but an input sheet is provided so that the user can readily make changes to many of the steps in the lifecycle in order to customize the LCA to their particular needs. The user can also make changes in many of the specific steps in the life cycle to develop a better understanding of the sensitivity of the processes to these changes. This flexibility makes the model a powerful tool for analysis.
GHGenius Impact Assessment
GHGenius focuses on estimating life cycle emissions for three impact categories; the primary greenhouse gases, the criteria pollutants from combustion sources and the energy used. The specific categories that are in the model include:
Greenhouse Gases
- Carbon dioxide (CO2),
- Methane (CH4),
- Nitrous oxide (N2O),
- Chlorofluorocarbons (CFC-12),
- Hydrofluorocarbons (HFC-134a).
The GHG emissions are also calculated for the carbon dioxide equivalent emission. The user can choose to use the Intergovernmental Panel on Climate Change (IPCC) 20 or 100 year global warming potentials (GWP) or other values that the user may wish to use.
In the case of the greenhouse gases, GHGenius can assess the cost effectiveness of various strategies using the results from the lifecycle assessment and the fuel and vehicle costs that are input by the users. This tool is particularly helpful in comparing vehicle related GHG reduction strategies with fuel related strategies on a common basis.
Other Air Contaminants
- Carbon monoxide (CO),
- Nitrogen oxides (NOx),
- Non-methane organic compounds (NMOCs),
- Sulphur dioxide (SO2),
- Total particulate matter.
The non-methane organic gases are also weighted according to their ozone forming potentials.
Energy Use
- Total energy used per unit of energy produced for each stage of the fuel production steps,
- Total fossil energy used per unit of energy produced for each stage of the fuel production steps,
- Energy used per kilometre driven for the fuel used in light duty internal combustion engines, light duty fuel cell vehicles, heavy duty internal combustion engines, and heavy duty fuel cell vehicles,
- The proportions of types of energy used for each stage of the fuel production cycle.
GHGenius Results
GHGenius produces a wide range of outputs designed to meet the needs of the users. The specific output data includes:
- CO2-equivalent emissions (in g/km or g/unit fuel) by stage of fuelcycle and for vehicle manufacture, for the feedstock/fuel/vehicle combinations identified above,
- Summary of % change in lifecycle g/km emissions from alternative-fuel vehicles, relative to conventional gasoline LDV or diesel HDV,
- Emissions (in g/km) by individual pollutant for each stage of the fuelcycle for each feedstock/fuel,
- Emissions from EV, by region,
- CO2-equivalent emissions (in g/unit of fuel) by stage of fuelcycle and for vehicle manufacture, for the feedstock/fuel/vehicle combinations identified above,
- CO2-equivalent emissions (in g/GJ) (HHV or LHV) for each stage of the upstream fuelcycle for each feedstock/fuel,
- Emissions (in g/GJ) (HHV or LHV) by individual pollutant for each stage of the upstream fuelcycle for each feedstock/fuel,
- kJ of process and end-use energy per kilometre of travel by stage of lifecycle, for different feedstock/fuel/vehicle combinations,
- kJ of fossil process and end-use energy per kilometre of travel by stage of lifecycle, for different feedstock/fuel/vehicle combinations,
- Breakdown of energy use by type of energy (e.g., diesel fuel, natural gas, propane), stage of lifecycle, and feedstock/fuel combination,
- Emissions from electricity use: CO2-equivalent emissions (in g/GJ and g/kWh delivered) for different sources of electricity generation,
- Emissions from use of heating fuels: CO2-equivalent emissions (in g/GJ-heat-delivered) for natural gas, LPG, electricity, biodiesel and fuel oil;
- The cost effectiveness of GHG reduced for each of the vehicle/fuel combinations in the model.
For all of this data the model can be run for specific regions within a country or regionally for the continent and thus the results can be provided for specific regions.
There are a number of internal checks on the data and calculations included in GHGenius. These include checks to ensure that power produced and consumed by processes are internally consistent. Checks are also provided for the calculation of the separate gases and the CO2 equivalent emissions. These can be calculated two ways by the model and the comparison of the results of the two methods ensures internal consistency in the model.
Analysis Tools
GHGenius has three tools to enable the user to undertake more complex scenario investigations.
There are two Sensitivity Solvers which allows the user to vary any input cell over a range and determine the impact on up to four output cells in the model. There is also a two dimensional solver that can vary two input cells at a time. The results are also automatically graphed.
The third tool is a built in Monte Carlo simulation tool. Up to eight input cells can be varied according to user selected distributions and values and the impact on up to 21 output cells can be determined. The results can also be presented graphically.
Computing Platform
GHGenius now runs in Excel 2000 or later. The user must also accept the license terms and conditions prior to using the model.
