Life Cycle Assessment and
GHGENIUS
Don O’Connor
(S&T)2 Consultants Inc.
www.ghgenius.ca
Agenda
¾ Life Cycle Assessment
¾ What is it and why do it?
¾ How do you do it?
¾ Why GHGENIUS?
¾ What can GHGENIUS do?
¾ Model capabilities
¾ How it works
¾ Fuel and Vehicle Pathways
¾ Some results.
Life Cycle Assessment
¾ Life Cycle Assessment (LCA) is a technique for
assessing the potential environmental aspects
associated with a product (or service), by:
¾ compiling an inventory of relevant inputs and
outputs,
¾ evaluating the potential environmental impacts
associated with those inputs and outputs, and
¾ interpreting the results of the inventory and impact
phases in relation to the objectives of the study.
¾ Source: US EPA
What is LCA?
¾ LCA is a cradle to-grave approach for assessing
industrial systems
¾ Begins with gathering the raw materials from the
the earth and ends when the materials are
returned to the earth
¾ Evaluates all of the stages as if they are
interdependent
¾ Provides a comprehensive view of all
environmental impacts and allows a more accurate
assessment of environmental trade-offs
Life Cycle Stages
Product Life Cycle
Benefits Of LCA
¾ Helps decision makers select options that provide
the lowest environmental impact
¾ This is used with other information such as cost and
performance to select a product or process
¾ Companies can claim one product is better than
another on the basis of LCA
¾ LCA inventory process helps to narrow in on the
area where the biggest reductions in
environmental emissions can be made
¾ Can be used to reduce production costs
Limitations of LCA
¾ Can be time and resource intensive
¾ Availability and accuracy of data can influence the
results
¾ Most LCA’s won’t determine which product works
the best or is the most cost effective
¾ LCA’s need to be used as one component of the
decision making process assessing the trade-offs
with cost and performance
Phases of LCA
¾ Goal Definition and Scoping - Define and describe the product,
process or activity. Establish the context in which the assessment is to
be made and identify the boundaries and environmental effects to be
reviewed for the assessment
¾ Inventory Analysis - Identify and quantify energy, water and materials
usage and environmental releases (e.g., air emissions, solid waste
disposal, wastewater discharge)
¾ Impact Assessment - Assess the human and ecological effects of
energy, water, and material usage and the environmental releases
identified in the inventory analysis
¾ Interpretation - Evaluate the results of the inventory analysis and
impact assessment to select the preferred product, process or service
with a clear understanding of the uncertainty and the assumptions used
to generate the results
Phases of LCA
Life Cycle Assessment Framework
Goal and Scope
Definition
Inventory
Analysis
Impact
Assessment
Interpretation
Identification of
Significant
Issues
Evaluation by:
•Completeness check
•Sensitivity Check
•Consistency Check
Conclusions, Recommendations and
Reporting
Life Cycle Assessment Principles
¾ The ISO 14040 standard for Life Cycle
Assessment has seven principles:
1.
2.
3.
4.
5.
6.
7.
Life Cycle Perspective
Environmental Focus
Relative Approach and Functional Unit
Iterative Approach
Transparency
Comprehensiveness
Priority of Scientific Approach
LCA 101
¾ The US EPA has a program to expand the use of
LCA in the United States.
¾ http://www.epa.gov/ORD/NRMRL/lcaccess/
¾ LCA 101 document is available at
¾ http://www.epa.gov/ORD/NRMRL/lcaccess/lca101.h
tml
How Do You Do an LCA?
¾ The systematic approach and the large volumes of
data required favour the use of software tools for
undertaking an LCA.
¾ You can develop your own software and assemble
your own data set, or
¾ Use a software tool specifically designed for the
task.
LCA Software and Databases
¾ The US EPA lists 30 tools on their website and
warns that the list is not complete.
¾ http://www.epa.gov/ORD/NRMRL/lcaccess/resource
s.html#Software
¾ 23 are European models.
¾ Five are American.
¾ One is Canadian (Athena, for building products).
¾ Many have a specific focus, e.g. building products,
transportation.
LCA Software and Databases
¾
¾
¾
¾
¾
¾
¾
¾
¾
¾
¾
¾
¾
¾
Boustead Model 5.0
ECO-it 1.3: Eco-Indicator Tool for environmentally friendly design - PRé Consultants
EcoPro - sinum Corporate Environmental Management
EDIP - Environmental design of industrial products - Danish EPA
EIOLCA - Economic Input-Output LCA at Carnegie Mellon University
GaBi 4 - (Ganzheitliche Bilanzierung) - University of Stuttgart (IKP)/PE Product
Engineering
IDEMAT - Delft University Clean Technology Institute Interduct Environmental Product
Development
KCL-ECO 4.0 - KCL LCA software
LCAiT 4- CIT EkoLogik (Chalmers Industriteknik)
LCNetBase - Life cycle assessment using traceable US data - Sylvatica
SimaPro 7 for Windows - PRé Consultants
SPOLD - Society for the Promotion of Life-cycle Assessment Development
TEAM(TM) (Tools for Environmental Analysis and Management) - Ecobalance, Inc.
Umberto - An advanced software tool for Life Cycle Assessment - Institut für
Umweltinformatik
Transportation LCA Tools
¾ GHGENIUS (NRCan)
¾ GREET (Argonne National Laboratory)
¾ LEM (Mark Delucchi, UC Davis)
¾ GEMIS (European)
¾ Gabi (European)
¾ SimaPro (European)
Issues to Consider
¾ Why are the results from different studies So
Different?
¾ Who is right?
¾ What is being done differently?
¾ When were they done?
¾ Where were they done?
¾ How were they done?
Canadian Energy Flows
Canadian Energy Flows
44% Useful
Energy
US Energy Flows
US Energy Flows
36% Useful
Energy
When Was the Data Collected?
Useful Energy
60.0%
Usefule Energy %
50.0%
40.0%
30.0%
20.0%
10.0%
0.0%
1950
1960
1970
1980
Year
1990
2000
2010
When Was the Data Collected?
¾ US Crude Oil Production
¾ Net Energy Ratio (energy produced per unit of energy
consumed)
Farming Efficiency
When Was the Data Collected?
3
Energy requirements [GJ/m ]
32
1983
16
Energy use in ethanol processing
PR = 0.84 + 0.01 (R2 = 0.89)
8
0.5
1
2
4
2005
8
16
32
Cumulative dry grind ethanol production [106 m3]
64
Differences at the Plant Level
Differences at the Plant Level
Differences at the Plant Level
Forecasts Change
Average Power Emissions,
g CO 2eq/GJ
140,000
120,000
100,000
80,000
60,000
40,000
20,000
0
1990
2000
2010
2020
2030
Ye ar
2007 Forecast
2003 Forecast
2040
2050
2060
Questions?
GHGENIUS
Model Background
¾ Based on a Lotus 123 spreadsheet model
developed by Dr. Mark Delucchi, University of
California, Davis in the late 1980’s for estimating
transportation emissions
¾ In 1998 Delucchi added some specific Canada
information for a US DOE, NRCan project
¾ In 1999, Levelton Engineering was asked by
NRCan to use the model for the Transportation
Table of the National Climate Change Process
Model Background
¾ Levelton moved the model from an Apple to a
Windows environment, but still using Lotus 123.
¾ Verified and updated the Canadian specific data,
¾ Separated results for Trucks from Buses,
¾ Added separate gases output tables,
¾ Added cost effectiveness, and
¾ Added the first new fuelcycle (NG to DME)
Model Background
¾ Since 1999 the model, now called GHGENIUS, has been
used for studies for Agriculture and Agri-Food Canada,
Natural Resources Canada, a number of the Provinces and
some industries
¾ Many new pathways have been added so that there are
now over 200 transportation fuel pathways in the model.
Much more Canadian specific data in the model
¾ An Excel version is now available with an updated guide.
¾ Documentation includes an over 500 page GHGENIUS guide
and numerous reports. Some Delucchi documentation is still
relevant
Why GHGENIUS?
¾ Follows an accepted LCA process
¾ Transportation specific but covers most energy sources and
many materials manufacturing processes and land use
changes
¾ Best Canadian database available
¾ Good American database
¾ Allows comparison of Canadian and US applications of the
same process
¾ There are some significant differences in the industrial
infrastructure between the countries
¾ Has some economic tools incorporated
Model Scope
¾ Covers raw materials production to end use.
¾ Lifecycle Stages
¾ Raw Materials Acquisition
¾
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¾
¾
¾
Feedstock production and recovery
Feedstock transmission
Fertilizer manufacture
Land use changes
Leaks and flaring associated with fossil fuels
¾ Manufacturing
¾
¾
¾
¾
Fuel production
Fuel storage and distribution
Fuel dispensing
Emissions displaced by co-products
¾ Vehicle operation
¾ Vehicle materials, assembly and transport.
Model Scope – Fuel Cycle
Model Scope – Fuel Cycle
Inventory Data
¾ A variety of data sources used for inventory data
¾ For existing processes,
¾Statistics Canada
¾Industry reports
¾GHG Registries (formerly VCR)
¾ For new to Canada processes
¾Foreign operating data
¾Engineering studies
¾Basic scientific assessment
Inventory Data
¾ Where possible relies on public data. US data
relies heavily on US Census and DOE EIA data
¾ Generally uses industry averages rather than plant
specific data
¾ The model is dynamic in that changes in one fuel
cycle can effect many other cycles. Iterates to
solve circular references
¾ Unlike some other models it allows the inputs to be
in common units and the model calculates the
energy impacts
Model Impact Assessment
¾ Capable of estimating life cycle emissions of the
primary greenhouse gases, the criteria air
contaminants (CAC), and the energy balance
¾ Greenhouse Gases (GHG)
¾ Uses IPCC weighting factors as default values
¾ Carbon dioxide
¾ Methane
¾ Nitrous Oxide
¾ Chlorofluorocarbons and Hydrofluorocarbons
Model Impact Assessment
¾ Criteria Air Contaminants
¾ Carbon monoxide,
¾ Nitrogen oxides,
¾ Non-methane organic compounds,
¾ Sulphur dioxide,
¾ Total Particulate Matter.
¾ Energy required per unit of energy produced
¾ Calculates cost effectiveness ($/tonne CO2 eq
displaced) versus gasoline and diesel engines
Interpretation Capabilities
¾ GHGENIUS can calculate emissions for any year between
1996 and 2050
¾ Correlations for changes in energy and process parameters
with time are stored in the model. Based on historical trends or
in some cases forecasts, e.g. NEB for power and oil
production
¾ Results are calculated for each stage of the lifecycle and for
each contaminant
¾ Capable of estimating emissions in Canada, the United
States, Mexico as well as regionally, east, central, or west in
North America, and India
¾ Some pathways can be analyzed provincially
Model Overview
¾ The model has grown to be quite large
¾ 49 sheets
¾ Over 265,000 cells with data or results
¾ 11.7 MB
¾ Compared to GREET, LEM and GEMIS
¾ It has many more pathways
¾ It has Canadian data
¾ Easier to make changes to pathways
¾ Much more detailed output
How it Works
¾ Calculations are done on a per unit of energy basis
- automatically corrects for volumetric fuel
differences
¾ Calculates emissions associated with fuel
production and with fuel use and then merges the
two data sets
¾ For each step in the lifecycle, the energy
consumption by fuel type and the emissions
associated with the step are specified
How it Works
¾ Generally follows ISO 14000 guidelines
¾ Does calculate emissions associated with vehicle
manufacture
¾ Does calculate energy consumption and emissions
for the manufacture and maintenance of trucks,
tractors, trains, ships, and pipelines used to make
and transport the fuels
¾ Does not include production plant
¾ Co-products calculated based on system
expansion if possible, and the displacement
method
How it Works
¾ One of the outputs is the emissions (GHG and
criteria) per GJoule (HHV or LHV basis) of fuel
delivered to the nozzle
¾ Well to Tank portion
¾ Uses fuel consumption inputs for a conventional
gasoline or diesel vehicle and then relative
efficiency for alternative fuel powertrains
¾ Automatically calculates the impact of different
powertrain and fuel weights
How it Works
¾ Criteria emissions for gasoline and diesel powered
vehicles uses algorithm to mimic Mobile6.2C
results
¾ Tank to Wheel portion
¾ Mobile6.2C provides fleet average emissions for a
year and GHGENIUS produces average emissions
over vehicle life
¾ Alternative fuel criteria emissions are also
calculated on a relative basis to gasoline and
diesel fuel
Model Capabilities
¾ Capable of modelling many vehicle types
¾ Light duty vehicles
¾Internal combustion engines
¾Fuel Cells
¾Battery powered vehicles
¾ Heavy duty vehicles
¾Trucks and buses (separately and combined)
¾Internal combustion engines and fuel cells
Fuel Pathways
¾ There are many fuel pathways in the model
¾ Some are indirect
¾ Natural gas to methanol, and then methanol to
hydrogen
¾ There are also many fuel blends
¾ Gasoline and ethanol
¾ Diesel and one of eight biodiesels
¾ Also has a few fuel pathways for power generation
and space heating
Fuel Pathways
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Crude Oil
Natural Gas
Uranium
Electricity
Wood
Corn Stover
Wheat Straw
Switchgrass
Hay
Manure
Corn
Wheat
Barley
Peas
Sugarcane
Sugar beets
Canola
Soybeans
Palm
Tallow
Yellow Grease
Fish Oil
Algae
Jatropha
RDF
LFG
Used Oil
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Fuel Pathways
¾ Gasoline and diesel fuel are the baseline fuels
¾ Four types of crude oil
¾Conventional (onshore or offshore), conventional
heavy, bitumen, synthetic
¾Some international oil data since more than half
of crude oil refined in Canada is imported
¾Proportions of each modelled for three regions of
Canada or user set
¾ Sulphur content of fuel can be set by the model or
user
¾ Refinery energy use based on regional differences
Pathways
¾ Light Duty
¾ Internal combustion engine
¾ Gasoline (conventional and low sulphur)
¾ Diesel (low sulphur and ultra low sulphur)
¾ LPG (refinery or field source)
¾ NG (CNG or LNG) (fossil or biomass)
¾ Hydrogen (SMR or electrolysis)
¾ Hybrids (gasoline and diesel) and Plug in Hybrids
¾ Battery powered vehicles (national and regional power mix).
Electricity is modelled provincially
¾ Fuel cell engine (13 hydrogen pathways or methanol (3),
ethanol (7), LPG, gasoline or FT distillate reformed onboard)
Fuel Pathways
¾ Light Duty Fuel Blends
¾ Gasoline blends
¾ Ethanol gasoline (low level and high level)
¾ Eight feedstock families (twelve feedstocks)
¾ Butanol gasoline (low level and high level)
¾ Methanol gasoline (low level and high level)
¾ Four feedstocks
¾ Mixed Alcohols (low level and high level)
¾ Three feedstocks
¾ Biodiesel blends
¾ Eight feedstocks
¾ Hythane (Hydrogen – Natural Gas)
¾ Two hydrogen sources
Fuel Pathways
¾ Heavy Duty ICE Vehicles
¾ Buses and Trucks, combined or separate
¾ Diesel
¾ FT Distillate (3 feedstocks)
¾ LPG (2 sources)
¾ NG (CNG, LNG, fossil and biomass)
¾ DME (NG and Wood)
¾ Hydrogen (2 sources)
¾ Ethanol (8 feedstock families)
¾ Butanol
¾ Methanol (4 feedstocks)
¾ Mixed alcohol (2 feedstocks)
¾ Hydrogenated Renewable Diesel (HRD)(8 feedstocks)
¾ Diesel hybrid
Fuel Pathways
¾ Diesel blends (0 to 100% blends)
¾FT Distillate (4 feedstocks)
¾Biodiesel, (8 feedstocks)
¾E-Diesel, (8 feedstock families)
¾Mixed alcohols (3 feedstocks)
¾Hydrogenated Renewable Diesel (8 feedstocks)
Fuel Pathways
¾ HD Fuel Cell Vehicles
¾ Methanol reformed on board (3 feedstocks)
¾ All 13 of the hydrogen pathways
Using GHGENIUS
System Requirements
¾ GHGENIUS is currently an Excel spreadsheet
application
¾ It requires Microsoft Excel 2000 or later to operate
¾Except Excel 2008 for Macs
¾ Each “run program” completes 300 cycles of the
model
¾ The speed with which it operates will be a function
of the computer speed and the amount of RAM
¾ 1GB RAM is visibly faster than 512MB
Running The Model
¾ There are several ways to run the model.
¾ F9
¾ Does not run the macros but does run the iterations.
¾ Table 54 on Upstream Results is OK but not the rest
of the tables with the separate gases.
¾ On Lifecycle Results, the LDV is OK but not the
electric vehicles or the separate trucks and buses.
¾ Fast.
GHGenius Macros
¾ A macro is a series of commands and
functions that are stored in a Microsoft Visual
Basic module and can be run whenever you need
to perform the task. They are used to automate
both simple and complex routines.
¾ There are more than 125 Macros in GHGenius.
Most are used to navigate through the model and
restore defaults.
¾ Excel must have macros enabled for the model to
function.
GHGenius Macros
¾ The macros have the advantage of automating
repetitive tasks but have the disadvantage of
reducing transparency.
¾ Cells with values written in by the macro only have
a number in them and not a formula, so the
precedents and dependents can’t be traced.
¾ We have considered the possibility of removing
some of the macros, replacing them with formulas,
to increase the transparency.
Main Macros
¾ Main GHGenius macros
¾ Separate Gases
¾ Separate Buses and Trucks
¾ EV Regions
¾ Model Run
¾ All can be accessed through the GHGenius drop
down menu in the tool bar.
¾ A macro installs this when the file is opened.
Separate Gases
¾ Determines the value of each individual gas for each stage of the
fuel cycle and enters the result in the appropriate cell on Upstream
Results HHV in rows 89 to 396.
¾ The macro utilizes the matrix on sheet B in rows 15 to 24.
¾ It sets all GWPs to one and calculates the results, pastes this as
the unweighted emissions in Table 54a.
¾ For CO2 it sets all values to zero in the matrix and the difference is
pasted in the corresponding section on the Upstream Results
HHV sheet.
¾ It then selects a gas, setting it to zero and calculating the results.
The difference between the two calculations is the value for the
gas that was set to zero and it is pasted in the corresponding
section on the Upstream Results HHV sheet.The macro
sequentially steps through each separate gas repeating the
process.
Separate Buses and Trucks
¾ Buses and Trucks have very different driving cycles and fuel
economies.
¾ During the initial GHGenius development it was important to
look at each of these sectors separately so a macro was
written to run the model three times, once for buses (using
the fuel economy and driving cycle found on the input sheet
in cells E10:E18), once for trucks (Cells G10:G18), and
once for a combined fleet (Cells F10:F18).
¾ The results are found on Lifecycle Results in rows 84 to
289. The macro also calculates the exhaust emissions for
HD vehicles in rows 116 to 265 on the Exhaust Emissions
sheet.
Separate Buses and Trucks
¾ The combined fleet is the default case run by the
model using F9 to do the calculations.
¾ You can see that these cells have formulas in them,
e.g. B76 on Lifecycle Results.
¾ The macro writes in the values for the other two
cases by substituting the fuel economies and
driving cycles.
EV Regions
¾ The EV Regions are set by the model for each
country.
¾ On the Lifecycle Results sheet cells B55 to B68
have formulas in them.
¾ The macro changes the electric power mix for the
preset regions, reruns the model and pastes the
results into the appropriate column.
¾ The User set power mix (column J) is calculated
based on lookup tables for the selected power
type.
Model Run
¾ The Model Run macro now runs the Separate
Gases and Separate Buses and Trucks in
sequence.
¾ It no longer runs the EV Region macro as it was
getting too complicated to run the regionalization
scenarios and the EV Region at the same time.
¾ There is now more flexibility in running the model
generally than there is in running the EV Regions.
Macros
¾ Two of the other important macros are:
¾ The Sensitivity Solver (RunSolver2)
¾Runs Separate Gases 11 times.
¾User sets the high and low value and the model
divides the range into 10 equal increments.
¾Some values need to be integers.
¾ Monte Carlo Simulator (simulate)
¾Varies up to five input variables with user
selected distributions.
¾Monitors up to 18 different output cells.
Macros
¾ None of the macros are hidden or locked. All of
them can be modified by the user.
¾ There are only a few cases where one might want
to modify a macro.
¾ Speeding up the Sensitivity Solver might be one.
¾ Could remove the Model Run step and just use F9 if
the range that was being analyzed didn’t include the
separate gases of Buses and Trucks.
Running The Model
¾ “Run Program” button on Input sheet
¾ Separate Gases and Separate Buses and Trucks
macros are run but not the EV macro.
¾ All results, except EV are correct.
¾ Slow
¾ “GHGenius” drop down menu.
¾ Run Model (Same as Run Program)
¾ Separate gases macro
¾ Separate trucks and buses
¾ EV Regions
Running The Model
¾ If you get results with many cells with “ERR”,
“#VALUE”, or “#DIV/0!” you probably have divided
by a zero in one of the circular references.
¾ Close the file.
¾ DO NOT SAVE.
¾ Reopen the file.
¾ Look for the problem.
¾ If you save it will be very difficult to find and correct
the error because of the circular references and the
way that the ERR propagates through the model.
Saving Results
¾ Sheets Lifecycle Results, CostLDV, CostHDV,
LDV Summ and HDV Summ can be saved to your
hard drive after each run.
¾ Use “Export Data” button at the top of the Input
Sheet.
¾ Prompts for a file name and location to save. Be
sure to change the file name for multiple runs.
Results
¾ The results for GHGenius are displayed on a
number of different sheets
¾ Energy consumption
¾ Energy Balance
¾Total primary energy used by stage
¾Primary fossil energy used by stage
¾Energy used per kilometre of travel by stage
¾Fossil energy used per kilometre of travel by
stage
¾Energy used per input type
Results
¾ GHG Emissions
¾ Upstream Results HHV, Upstream Results LHV,
Lifecycle Results and Lifecycle Results (2), all by
stage
¾ J (power), AD (Summary of percent changes)
¾ CAC emissions
¾ Upstream Results, LDV Summ, HDV Summ
¾All by stage
¾ Cost Effectiveness
¾ LDV Cost, HDV Cost
Data Inputs
¾ Cells with a yellow background are cells that have
data that could be changed by a user
¾ Cells with a red outline and white background have
input data transferred to them from an input
elsewhere in the model
¾ Most of the typical data inputs have been
assembled on the Input Sheet
¾ There are still cells (identified by yellow) on the
other sheets that more advanced users may wish
to consider changing for some analyses
Questions?
Data Inputs
Model Set Up
¾ On the “Input Sheet” section
¾ Enter the year (B3)
¾ Enter the Country (G3)
¾Only used for table headings does not set the
model for the country.
¾ Select the “country weight” factors
¾Cells B5 to M5
¾Used for regionalization
¾Must add to 1.0
Model Set Up
¾ For “average” Canada
¾ Canada East - 0.22
¾ Canada Central – 0.48
¾ Canada West – 0.30
¾ This is close to the regional production of refined petroleum
products and slightly under weighted to central Canada for
power generation (overweight east)
¾ Select GWP factor B6
¾ 0 = IPCC 1995; 1 = IPCC 2001; 2 = IPCC 2007;
¾ 3 = Delucchi's CEF
GWP Selection B6
Carbon Dioxide (CO2)
Methane (CH4)
Nitrous Oxide (N2O)
1995
2001
2007
1
1
1
21
23.5
25
310
296
298
Model Set Up –Provincial Versions
¾ Version 3.15 introduced some provincial default
values. These override the other default buttons.
¾ Selects
¾ Electric Power
¾ Transportation distances for petroleum fuels
¾ Types of LPG
¾ Corn, wheat, and sugar cane ethanol transportation
distances and producing regions
¾ Canola, soybean, tallow, and yellow grease
transportation distances and producing regions
The BC GHGenius Model
¾ For the Low Carbon Fuel Standard, BC uses
model version 3.16c, not the current version.
¾ To convert the GHGenius model to the “BC”
model, two changes are require:
¾ Click the “BC” button at the top of the Input sheet.
¾ Set B6 to 0.
The Alberta GHGenius Model
¾ For the Alberta Renewable Fuel Standard, Alberta
uses model version 3.19.
¾ To convert the GHGenius model to the “Alberta”
model, two changes are require:
¾ Click the “Alberta” button at the top of the Input
sheet.
¾ Set B6 to 0.
Model Set Up – Vehicle Energy Use
¾ Sheet C area, vehicle energy use.
¾ Three different default fuel economy values for Canada, US or
Mexico
¾ Built in improvement factors
¾ Rates of improvement set in rows 12 & 13 and 16 & 17.
These are percentages. Defaults are 0.05% to 2025 and
0.08% past 2025.
¾ To set a different fuel economy
¾ Enter the values in rows 11 and 15 and set improvement
factors to 0.
¾ Or enter the values in rows 11 and 15 for year 2000 and
the appropriate improvement factors to give the desired
results
Vehicle Energy Use
¾ Three additional switches.
¾ C19. Pulls truck values based upon class standards.
¾ C20. Sets the HD case(s) to be run.
¾ 0 - combined trucks and urban buses
¾ 1- buses only
¾ 2 - trucks only
¾ Overridden by the “Run Program” button. Use the
“Separate Gases” macro.
¾ C21. Fraction of energy used by buses.
¾ Note: LDDV vehicle energy comes from the Input Sheet and
is not calculated independently like the other alternative
fuels. Be careful how the results are interpreted.
Electric Power
¾ Select Country consistent with “country weights”
(row 5) and Country selected in row 3
¾ For Canada only, the individual province/region
can also be selected for generic power
¾ Use Canada if “country weights” is not 1.0 in a
single cell
¾ Select the provinces for ethanol production
¾ Sheet D has the data on electric power in the
model. There are some yellow cells for EV for
regions other than Canada. Canada can be set on
sheet J
Conventional Fuels
¾ Rows 32 to 54 on the Input Sheet set various
parameters of the fuels and feedstocks for
modelling
¾ Row 35 sets the fuel blend on a volumetric basis
¾ The model will automatically calculate the energy
portions of each component of the blend
¾ Only one component needs to be added, the other
is calculated by difference
Alternative Fuels
¾ In row 39, the gasoline that is used for blending
with alcohol is selected
¾ This can be different for farm tractors and for the
end use vehicle
¾ The cost effectiveness sheet only has the option of
using the low sulphur gasoline
Gaseous Fuels
¾ The user selects either compressed or liquefied
versions of natural gas or hydrogen in cells B42
and B43 by entering either CNG or LNG, and CH2
or LH2 using the drop down menus.
¾ The liquefied fuels can be produced in large or
small plants and the choice is made in C42 and
C43.
¾ The characteristics of the two types of plants are
found on Sheet AB. Changes can be made there.
Feedstock Selection
¾ The mix of feedstocks for some fuels is chosen in
B46 to 50. The input is from 0 to 1. Fractions are
allowed.
¾ B46. Methanol from NG (0 to 1) or Coal (remainder)
¾ B47. Hydrogen for ICE from NG (0 to 1) or electricity
(remainder)
¾ B48. Ethanol from wood (0 to 1) or “grass”
(remainder)
¾ B50. HRD from any of the eight feedstocks
Fuel Properties
¾ In cell B52, the sulphur content of low sulphur can
be selected as 30 ppm (enter a 1) or 1 ppm (enter
a 0)
¾ In cell F52 the sulphur content of diesel fuel can be
selected (range is 500 to 10 ppm)
¾ In cells I44 to I48 the composition of the mixed
alcohol fuel is specified
Feedstock Selection
¾ For the type of “grass” in row 54 we select from
switchgrass, corn stover, wheat straw or hay.
¾ Put a 1 in the appropriate box. Can do a blend,
insert values for three and hay is calculated by
difference.
¾ E46, select the renewable fraction of RDF (refuse
derived fuel).
¾ E44, select the efficiency of the Thermocracking
process being modelled.
Crude Oil Selection
¾ Five types of crude oil can be modelled,
conventional (light and medium), offshore
conventional, conventional heavy, bitumen and
synthetic
¾ The model has programmed refinery crude slates
for each region and for all of Canada (based on
StatsCan data and NEB forecasts)
¾ The user can also select his own slate by choosing
“Input” from the button menu and then inputting the
desired values in cells B65 to E65. The amount of
synthetic is calculated by difference.
Crude Oil Selection
¾ The values selected on the Input Sheet determine
the types of Canadian crude oil processed.
¾ The sources and fractions of foreign crude oil
processed are determined from data on Sheet Z,
rows 50 to 71 and columns AP to AR for Canada.
¾ The types of foreign crude oil are found on Sheet
S.
Typical Crude Oil Trends
0.700
0.500
0.400
0.300
0.200
0.100
C onventional Light
Bitum en
Synthetic
Expon. (C onventional Light)
Expon. (Bitum en)
0
20
3
8
20
2
6
20
2
4
20
2
2
20
2
0
20
2
8
20
1
6
20
1
4
20
1
2
20
1
20
1
0
8
20
0
6
20
0
4
20
0
2
20
0
0
0.000
20
0
Fraction of Oil Refined
0.600
Feedstock and Fuel Transportation
¾ Rows 67 to 99 are used to describe the modes of
transportation and the distances for each mode for
feedstocks and fuels.
¾ A few distances are calculated automatically by
the model but most can be set by the user on the
Input Sheet.
¾ Rows 74 to 79 are used for feedstock transmission
distances.
¾ Rows 81 to 85 are for modes used. The total for all
modes must be at least one but it can be as high
as five.
Feedstock and Fuel Transportation
¾ Rows 89 to 93 are for transportation distances for
products and rows 95 to 99 are for modes of
transportation.
¾ Four buttons are used to restore default distances
for Canada, US, Mexico and India.
¾ Natural gas transmission distances are set as a
fraction of total transmission distance for methanol
and FT plants in cell B70. It is assumed that these
plants are located close to the source.
Biomass Production
¾ Fertilizer and Pesticide input data (other than
nitrogen) is entered in rows 105 to 122.
¾ Six inputs
¾ Potassium, potash, lime, sulphur, herbicides, seeds
¾ Eighteen different feedstocks
¾ Corn, wheat, barley, peas, sugarcane, sugar beet,
whole corn,soybeans, canola, palm, algae, jatropha,
wood, corn stover, wheat straw, hay, switchgrass,
and fish.
Biomass Production
¾ Input energy requirements for crop production in
rows 126 to 143.
¾ Do not include transportation of feedstock from
farm to plant (included previously).
¾ Inputs available for many types of fuel but not all
will be used.
¾ Switch available for wood residues (B145). Zeros
out land use changes as these are assumed to be
applicable to the production of the primary product
and not the residue.
Biomass Yields and Nitrogen Fertilizer
¾ Biomass yields and nitrogen fertilizer rates are regionalized.
Input data is in rows 149 to 219.
¾ For each crop, yield in a base year and annual rates of
change can be specified.
¾ Producing region must be specified.
¾ Nitrogen application rates are input. Be careful that the
nitrogen rates and the yield are consistent.
¾ P and K rates for wood are also regionalized.
¾ Nitrogen applied as animal manure can also be specified for
each crop.
¾ Defaults can be restored by the button.
Alternative Fuel Production
¾ Rows 229 to 234 are for the input data for the
alternative fuel production processes.
¾ Input energy/feedstock required for each process.
¾ Be careful of the units.
¾ Default restores data.
¾ Corn ethanol energy is regionalized.
¾ Input in rows 239 to 242.
¾ Default restores data.
Co-products
¾ A246 to A254 are for co-products from ethanol and
biodiesel processes.
¾ Rows 259 to 269 deal with additional co-products
from cellulose ethanol processes.
¾ There are other more detailed inputs that can be
changed on Sheet Y.
¾ Rows 259 and 271 to 279 deal with electricity
produced as a co-product and the type of power
displaced by the power.
Service Station Energy
¾ Liquid fuel requirements are calculated
automatically.
¾ Compressed gases the user specifies the inlet
pressure and the outlet pressure. The model
calculates the energy required.
¾ This is difficult to calculate and real world data could
be substituted if available.
¾ Inlet pressure is more significant than the outlet
pressure in the energy calculation.
Cost Effectiveness
¾ Basically the change in lifetime ownership costs
divided by the reduction in GHG emissions.
¾ Fuel and vehicle cost data is entered on Input Cost
Sheet.
¾ If GHG emissions increase it is not calculated.
¾ If costs decrease, then calculates a negative cost
effectiveness.
¾ Be careful with the magnitude of negatives. Large
negative numbers are created from large savings or
small GHG benefits.
Cost Effectiveness
¾ For the fuel, the plant gate cost and the distribution
and retail costs are input. Traditional fuels are
calculated from the price of crude oil.
¾ For the vehicles, the additional vehicle capital cost,
incremental operating and maintenance costs, and
other differential costs are input.
¾ Some fuel blends are calculated automatically.
¾ The default results are calculated without tax.
¾ Consumer cost effectiveness should be calculated
with tax (and tax incentives) included.
Conventional Fuels
General fuel
Fuel specification
Feedstock
Vehicle operation
LD Gasoline
RFG30ppm S
Crude oil
HD Petrol Diesel
0.0015% S
Crude Oil
Grams/km CO2
Grams/km CO2
211.4
1,078.3
Fuel dispensing
0.4
1.8
Fuel storage and distribution
1.5
7.3
40.8
129.5
Feedstock transport
2.9
13.9
Feedstock Recovery
28.5
134.9
Land-use changes, cultivation
0.7
3.3
CH4 and CO2 leaks and flares
6.0
27.7
-0.8
-3.5
291.6
1,393.1
2.9
5.5
27.9
31.3
322.3
1,429.9
Fuel production
Emissions displaced by co-products
Sub total (fuelcycle)
Vehicle assembly and transport
Materials in vehicles (incl. storage)& lube oil
Grand total
Regional Differences
Canada
Region
Fuel dispensing
Fuel distribution and storage
Fuel production
Feedstock transmission
Feedstock recovery
Land-use changes, cultivation
Fertilizer manufacture
Gas leaks and flares
CO2, H2S removed from NG
Emissions displaced
Total
Combustion
Grand Total
112
466
12,317
886
8,606
215
0
1,808
0
-231
24,180
63,778
87,958
Gasoline
Eastern
Central
Canada
Canada
g CO2eq/GJ (HHV)
127
48
885
372
12,606
12,610
1,744
873
5,788
7,529
8
176
0
0
1,444
1,494
0
0
0
-189
22,603
22,913
63,778
63,778
86,381
86,691
Western
Canada
204
646
11,799
234
12,477
431
0
2,582
0
-461
27,912
63,778
91,690
Questions?
Agenda
¾ Working with the model
¾ Fuel economy changes
¾ Crude oil, gasoline and diesel fuel
¾ Ethanol
¾ Biodiesel
¾ Natural Gas
Data
¾ From this morning we know that the data that is
used in an LCA strongly influences the results.
¾ For the established fuel production pathways
GHGENIUS uses published industry average data.
¾ Some data is based on individual plant data.
¾ The area of greatest uncertainty is for the
emerging production pathways. The data for these
pathways can be improved as some real world
experience is gained.
Examples
¾ Going to look at some examples and run through
the key inputs and their impact on results:
¾ Crude oil, gasoline and diesel fuel
¾ Ethanol
¾ Biodiesel
¾ Natural Gas
Fuel Economy
¾ The defaults in the model are for a mid sized
vehicle. How do you model a compact or a pick-up
truck?
¾ To set a different fuel economy
¾ Enter the values in rows 11 and 15 and set
improvement factors to 0.
¾ Or enter the values in rows 11 and 15 for year 2000
and the appropriate improvement factors to give the
desired results
Fuel Economy
¾ Compact
¾ Cell B11 = 8
¾ Cell B12 = 0
¾ Cell B13 = 0
¾ Cell B15 = 6
¾ Cell B16 = 0
¾ Cell B17 = 0
¾ Push F9
¾ Go to Lifecycle Results Sheet
Fuel Economy
Inputs
Default
Compact
Pick-up
10.67/8.2
8.0/6.0
17.0/13.0
g CO2eq/km
211.4
153.4
344.6
Fuel dispensing
0.4
0.3
0.6
Fuel storage and distribution
1.5
1.1
2.5
40.8
30.3
64.9
Feedstock transport
2.9
2.2
4.7
Feedstock recovery
28.5
21.2
45.4
Land-use changes, cultivation
0.7
0.5
1.1
CH4 and CO2 leaks and flares
6.0
4.5
9.5
-0.8
-0.6
-1.2
291.6
213.0
472.1
Vehicle operation
Fuel production
Emissions displaced by co-products
Sub total (fuelcycle)
Additional Output
¾ What if you know the quantity of fuel consumed by
a fleet but not the mileage of all of the vehicles.
¾ How can you estimate the fleet GHG emissions?
¾ Go to the Upstream Results 2 sheet.
¾ These are the lifecycle results presented not the
basis of g/km but rather on the basis of g/litre of fuel
consumed.
¾ Gaseous fuels are on the basis of g/kilogram of fuel.
Questions?
Gasoline / Diesel
¾ Input
¾ Country / Regions
¾ Fuel Consumption
¾ Crude Slate
¾ Distance Shipped
¾ Sheet S
¾ Changing Canada
¾ Changing Foreign Countries
Oil Sand Production Options
Gasoline / Diesel
¾ Find outputs for upstream low sulphur gasoline on
Upstream Results.
¾ Find outputs for a light duty vehicle using low
sulphur gasoline on Lifecycle Results.
¾ Using GHGenius default values we get Canadian
average results.
Canada Average
Upstream Results
Lifecycle Results
g CO2E/GJ
g CO2E/km
24,180
322.3
Gasoline / Diesel
¾ Go to the Input sheet to change the region to
Canada West with the default button. It will change
the region and crude slate.
¾ Check the crude flow on sheet Z to see where the
crude is coming from now.
¾ Run the model to check the same outputs.
Upstream Results
Lifecycle Results
g CO2E/GJ
g CO2E/km
Canada Average
24,180
322.3
Canada West
27,912
336.0
Gasoline / Diesel
¾ Go to the Input sheet to change to 100% synthetic
crude on row 65.
¾ First change the region to “Input” then zero out all
non-synthetic.
¾ Run the model again to check the outputs.
Upstream Results
Lifecycle Results
g CO2E/GJ
g CO2E/km
Canada Average
24,180
322.3
Canada West
27,912
336.0
Synthetic Crude
34,301
358.1
Gasoline / Diesel
¾ Go to Sheet S to check what the energy inputs for
producing synthetic crude are.
¾ Synthetic is found in the range X2 to AK25.
¾ The latest version of the model has a lot of
flexibility. Bitumen can be produced from mining,
SAGD, or CSS. All with separate inputs and we
can blend the production systems. (Z6 to AB6)
¾ Synthetic can be modelled as an integrated
system or as bitumen processed in an upgrader.
Bitumen feedstock for upgrading can be a different
blend than bitumen for refining.(Z4 to AB4)
Gasoline / Diesel
¾ Run 100% SAGD and Upgrader.
¾ Set Z4 to 1 and AA and AB4 to zero.
¾ Set AH 6 to one and AI 6 to zero.
¾ Run the model and check out outputs.
Upstream Results
Lifecycle Results
g CO2E/GJ
g CO2E/km
Canada Average
24,180
322.3
Canada West
27,912
336.0
Synthetic Crude
34,301
358.1
Upgraded SAGD
39,763
377.0
Gasoline / Diesel
¾ Gasify coke at the upgrader instead of using NG.
¾ Set AG 10 to 0 and AG 14 to 3,100,000.
¾ Run the model and check out outputs.
Upstream Results
Lifecycle Results
g CO2E/GJ
g CO2E/km
Canada Average
24,180
322.3
Canada West
27,912
336.0
Synthetic Crude
34,301
358.1
Upgraded SAGD
39,763
377.0
Coke instead of NG
41,633
383.5
Impact of Crude Oil
¾ What impact does the type of crude oil have?
¾ Light, Heavy, Bitumen, Synthetic
Impact of Crude Oil
General fuel
Fuel specification
Feedstock
Gasoline
Gasoline
Gasoline
Gasoline
RFG30ppm S
RFG30ppm S
RFG30ppm S
RFG30ppm S
Conv Crude oil
Heavy Crude Oil
Bitumen
Synthetic
Grams/km CO2
Grams/km CO2
Grams/km CO2
Grams/km CO2
211.4
211.4
211.4
211.4
Fuel dispensing
0.7
0.7
0.7
0.7
Fuel storage and distribution
2.1
2.2
2.2
2.2
37.1
54.4
81.7
41.2
Feedstock transport
0.8
0.8
0.8
0.8
Feedstock recovery
27.2
14.1
33.2
64.7
Land-use changes, cultivation
0.0
0.0
1.1
3.3
CH4 and CO2 leaks and flares
5.7
32.5
2.4
4.6
Emissions displaced by co-products
0.0
0.0
0.0
-3.8
284.9
316.0
333.3
325.1
Vehicle assembly and transport
2.9
2.9
3.0
3.1
Materials in vehicles & lube oil
28.3
29.0
29.0
29.9
316.2
348.1
365.3
358.1
Vehicle operation
Fuel production
Sub total (fuelcycle)
Grand total
Summary
¾ We have used the model to evaluate the impact of
fuel consumption of vehicles and we have
evaluated the impact of different types of crude oil
and different ways of producing crude oil.
¾ Lets reset the defaults
¾ Sheet S. Default button ~Y24
¾ Input sheet. Canada button ~B2
¾ Push F9.
¾ Check Upstream Results for 24,180 in cell D19.
Questions?
Model Scope – Fuel Cycle
Ethanol
¾ The model has pathways for corn, wheat, sugar
beet, and sugar cane with data from actual
operations and industry averages. The information
on barley, peas, and cellulosic ethanol is based on
demonstration facilities and lab data.
¾ GHG benefits arise from the renewable nature of
the fuel (don’t count the CO2 emissions from
combustion) offset by the increased emissions
from feedstock production and fuel production.
Ethanol Factors to Consider
¾ The feedstock production inputs can be important.
Fertilizer requirements, manure vs. synthetic
fertilizer
¾ Feedstock transportation distances
¾ Energy requirements for ethanol manufacturing
¾ Co-products produced, CO2 capture or venting, coproduct use
¾ Ethanol transportation distances
¾ All of these are on the Input sheet
Ethanol Pathways
Corn
Wheat
Barley
Peas
Sugar
beets
175
175
175
175
175
1,146
1,778
1,133
1,133
1,133
25,283
36,844
40,003
42,707
41,913
Feedstock transmission
2,069
1,515
1,702
1,915
5,650
Feedstock recovery
5,649
4,153
4,948
7,888
6,883
20,414
6,901
8,504
-228
17,806
5,055
10,126
13,401
12,950
8,959
Gas leaks and flares
0
0
0
0
0
CO2, H2S removed from NG
0
0
0
0
0
-16,569
-23,662
-27,963
-42,309
-9,438
43,223
37,830
41,903
24,231
73,081
Fuel dispensing
Fuel distribution and storage
Fuel production
Land-use changes, cultivation
Fertilizer manufacture
Emissions displaced
Total
Impact of Production Location
¾ Corn Ethanol produced in Ontario vs. US Central
production.
¾ The Ontario corn ethanol is the default case for
“Canada”.
¾ To model US ethanol we need to make some
changes to the model.
¾Row 5 Country weight. US Central 1.0 (F5)
¾Transportation Distances (~A78) to US
¾Corn producing region, 0 in C152 and 1 in F152
¾Manure B221 to 0
¾NG fuel (F241 to 1, F242 to 0)
Corn Ethanol Location
Corn
Corn
Corn
Central Canada
Central US NG
Central US Coal
175
665
665
1,146
1,648
1,648
25,283
36,381
49,125
Feedstock transmission
2,069
2,284
2,284
Feedstock recovery
5,649
5,495
5,495
20,414
19,944
19,944
5,055
7,719
7,719
Gas leaks and flares
0
0
0
CO2, H2S removed from NG
0
0
0
-16,569
-16,618
-16,618
43,223
57,519
70,264
Fuel dispensing
Fuel distribution and storage
Fuel production
Land-use changes, cultivation
Fertilizer manufacture
Emissions displaced
Total
Corn Ethanol Location
¾ What are the differences?
¾ Electric power CI accounts for the delta in fuel dispensing.
¾ Fuel distribution and storage, slightly shorter distances for
Canada, 43% moves 701 km by rail in Canada vs. all moving
600 km in US. Trucking distance 183 km vs. 225 km.
¾ Fuel Production. Electric power CI and NG CI higher in US.
Assumed electricity requirement in US slightly higher. NG
requirements the same. Coal CI is much higher.
¾ Fertilizer manufacture. Impact of manure and a less efficient
US fertilizer production sector.
What Drives Corn Ethanol Results?
¾ Feedstock Recovery
¾ The energy required for produce the crop is an area
where data quality is very poor.
¾ USDA used to publish results from surveys done
every 4 years but due to cost constraints they
stopped doing this a few years ago.
¾ Fuel use is a function mostly of area and not yield,
except if grain drying is required. So there will be
regional differences.
¾ GHGenius now adjust rate of change to be
compatible with projected yield changes.
2004
2002
2000
1998
1996
1994
1992
1990
1988
1986
1984
1982
1980
1978
1976
1974
1972
1970
1968
1966
1964
1962
Index Energy Efficiency, Energy/Farm Output
Farm Energy Index
2.50
2.00
1.50
1.00
0.50
0.00
What Drives Corn Ethanol Results?
¾ Fertilizer Manufacture
¾ Canadian N fertilizer industry is more efficient than
the US industry.
¾ Manure as a fraction of N fertilizer in the US varies
widely state to state and good quality data is difficult
to obtain.
¾ Intermediate results on sheet V, column J.
¾ Europe uses mostly ammonium nitrate fertilizers
which have about twice the GHG emissions as
ammonia solutions or urea. This strongly
influences some of the European biofuel results.
Nitrogen Fertilizer Production Efficiency
What Drives Corn Ethanol Results?
¾ Fuel Production
¾ Mostly thermal and electrical energy requirements
¾ Type of fuel used, biomass, NG, or coal
¾ Co-generation
¾ Quantity of co-product dried
¾ Plant design
¾ Industry has exhibited significant improvement over
time and some continued improvement is expected.
Fuel Production Energy
Type of Process Energy
¾ We saw earlier the difference between NG and
Coal.
¾ To look at biomass, enter the mass of biomass
required in cell P233 on input sheet.
¾ 10 MJ requires 0.556 kg of stover. Enter this in
P233 and zero F240.
Corn Ethanol Process Fuel
Corn
Corn
Corn
Central US NG
Central US
Coal
Central US
Stover
665
665
665
1,648
1,648
1,648
36,381
49,125
17,139
Feedstock transmission
2,284
2,284
2,874
Feedstock recovery
5,495
5,495
9,281
19,944
19,944
19,944
7,719
7,719
7,719
Gas leaks and flares
0
0
0
CO2, H2S removed from NG
0
0
0
-16,618
-16,618
-16,618
57,519
70,264
42,654
Fuel dispensing
Fuel distribution and storage
Fuel production
Land-use changes, cultivation
Fertilizer manufacture
Emissions displaced
Total
Calculating a Plant CI
¾ For BC LCFS, biofuel plants need to determine the
CI for their operation.
¾ We run the model for those activities that the plant
has control over.
¾ Feedstock transportation modes and distances.
¾ Plant operations
¾Power, fuel, yield
¾ Co-products or special characteristics
¾ Ethanol Transportation distances
Midwest US Corn Ethanol Plant
¾ We are going to go through the steps to determine
the CI for a typical US corn plant.
¾ Set the model to BC with the BC button.
¾ Change the region to US central in row 5, cell F5.
¾ Change GWPs to 1996 values, B6 is 0.
¾ This plant has no control over feedstock
production so the first plant specific input is the
feedstock transportation information.
Feedstock Transportation
¾ Plants receive corn either by truck, rail or a
combination of the two.
¾ We need to know the distance and fraction of
each.
¾ Assume 100% truck and an average distance of
50 km.
¾ Cell F79 set to 50. (F75 to F78 should be zero)
¾ Cell F85 to 1.0.
Plant Operations
¾ For basic plant operations we need to know the
feedstock consumption (kg/litre produced), and the
energy requirements.
¾ Enter the yield in cell P234
¾ Enter misc. fuel consumed in P230
¾ Enter electric power and fuel use in rows 239 to
242.
¾ Check base year in row 227.
Plant Operations
¾ P234 is set to 2.45
¾ P230 is set to 0.0005
¾ F239 is set to 0.20
¾ F240 is set to 8.2
¾ F241 is set to 1.0
¾ F242 is set to 0.0
¾ P 227 is set to 2010.
Ethanol Transportation
¾ The ethanol is moved from the plant to a blending point by
truck and/or rail and then to the final point of use by truck.
¾ Assume that the product is moved by rail 3,000 km and then
the default 80 km to the dispensing by truck.
¾ O89 is set to 3,000
¾ O93 is set to 80
¾ O95 is set to 1.0
¾ O99 is set to 1.0
¾ Push F9
Corn Ethanol CI
Corn
Central US to BC
Fuel dispensing
Fuel distribution and storage
Fuel production
Feedstock transmission
Feedstock recovery
Land-use changes, cultivation
Fertilizer manufacture
661
2,605
36,106
699
5,295
20,564
7,540
Gas leaks and flares
0
CO2, H2S removed from NG
0
Emissions displaced
Total
-16,685
56,784
Combining Regions
¾ How do we deal with corn ethanol produced in the
US and used in BC?
¾ We need to run the model twice for this and
combine the results of the two runs.
¾ The fuel distribution needs to have the distance
changed by removing BC distance but run in the US
model since almost all of the transportation would
be in the US.
¾ The rest of the lines would use the US results.
¾ Set O93 to 0.
¾ Push F9
Corn Ethanol Combined Results
Corn
Corn
Corn
Corn
US Run
US run less
BC Ops
BC ops
Combined
661
0
2,605
2,245
36,106
36,106
699
699
5,295
5,295
20,564
20,564
7,540
7,540
Gas leaks and flares
0
0
CO2, H2S removed from NG
0
0
-16,685
-16,685
56,784
55,764
Fuel dispensing
Fuel distribution and storage
Fuel production
Feedstock transmission
Feedstock recovery
Land-use changes, cultivation
Fertilizer manufacture
Emissions displaced
Total
Combining Regions – BC Run
¾ Click on BC in row 2.
¾ Now need to reset to US Central and install BC
transportation distances.
¾ O89 is set to 0.
¾ O93 to 80
¾ Push F9
¾ Copy results from Upstream Emissions cells K23
and K24.
Corn Ethanol Combined Results
Corn
Corn
Corn
US Run
US run less
BC Ops
BC ops
661
0
30
30
2,605
2,245
469
2,714
36,106
36,106
0
36,106
699
699
0
699
5,295
5,295
0
5,295
20,564
20,564
0
20,564
7,540
7,540
0
7,540
Gas leaks and flares
0
0
0
0
CO2, H2S removed from NG
0
0
0
0
-16,685
-16,685
0
-16,685
56,784
55,764
499
56,263
Fuel dispensing
Fuel distribution and storage
Fuel production
Feedstock transmission
Feedstock recovery
Land-use changes, cultivation
Fertilizer manufacture
Emissions displaced
Total
Corn
BC LCFS CI
¾ The BC LCFS CI also includes the non CO2
exhaust emissions.
¾ Go to the Exhaust Emissions sheet.
¾ Cell I97
¾ Value is 2,110 g/GJ
¾ Add this to 56,263
¾ 58,373 g/GJ or
¾ 58.37 g/MJ
Questions?
Corn vs. Wheat Ethanol
¾ Differences are driven not by process conditions
but by where the wheat is produced.
¾ N2O emissions increase when the soil is saturated.
¾ This condition rarely occurs in western Canada.
¾ On sheet W we have, for information only, the N2O
emission factors for each province as well as for the
region. Users could input these more specific values
into the appropriate cells in range AF105 to AY145.
Ethanol
Upstream Emissions for Ethanol from Wheat
EtOH from
Wheat Straw
Feedstock
Wheat
EtOH with
NG
Wheat EtOH
with Straw
Fuel
175
175
175
175
1,146
1,778
1,778
1,341
25,283
36,844
9,836
49,247
Feedstock transmission
2,069
1,515
1,994
1,809
Feedstock recovery
5,649
4,153
8,438
778
20,414
6,901
6,901
0
5,055
10,126
10,126
2,716
Gas leaks and flares
0
0
0
0
CO2, H2S removed from NG
0
0
0
0
-16,569
-23,662
-23,662
-19,391
43,223
37,830
15,586
36,674
Corn
Fuel dispensing
Fuel distribution and storage
Fuel production
Land-use changes, cultivation
Fertilizer manufacture
Emissions displaced
Total
Sugar Cane Ethanol
¾ There is a sugar cane ethanol pathway in GHGenius
based on data from Brazil but there is no country data
in the model for Brazil for power generation and
fertilizer manufacture.
¾ This has a relatively small impact on model results.
¾ Most mills are at least self sufficient in power generation, new
mills are power producers.
¾ Fertilizer requirements are low.
¾ Pathway was added several years ago and does not
reflect the increase in mechanization or the higher
efficiency of power generation in the new mills.
Ethanol Pathways
Corn
Wheat
Sugar Cane
175
175
175
1,146
1,778
5,185
25,283
36,844
6,436
Feedstock transmission
2,069
1,515
1,074
Feedstock recovery
5,649
4,153
1,400
20,414
6,901
3,792
5,055
10,126
2,885
Gas leaks and flares
0
0
0
CO2, H2S removed from NG
0
0
0
-16,569
-23,662
-145
43,223
37,830
20,802
Fuel dispensing
Fuel distribution and storage
Fuel production
Land-use changes, cultivation
Fertilizer manufacture
Emissions displaced
Total
Sensitivity Solver
¾ This tool allows us to change any input variable in
the model and determine the impact on any output
cell in the model.
¾ A range is chosen for the input variable and the
model divides the range by ten and runs the model
for each of the increments.
¾ The results are plotted.
Sensitivity Solver
¾ Lets look at how the model projects changes in GHG
emissions for corn ethanol over time.
¾ Go to Sensitivity Solver Sheet.
¾ Set B7 to 2 (Input Sheet)
¾ C7 to 2 (Column B)
¾ D7 to 3 (Row 3)
¾ E7 to 2000 (Start value)
¾ F7 to 2020 (End value)
¾ B8 to 6 (Upstream Results sheet)
¾ C8 to 11 (Column K)
¾ D8 to 33 (Row 33)
¾ Push Run Solver
Corn Ethanol vs. Time
60,000
GHG Emissions
g CO2eq/GJ
50,000
40,000
30,000
20,000
10,000
0
2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020
Year
Modelling a Specific Plant
¾ Feedstock Production
¾ Are the default values for fertilizer and fuel OK or do
you want to enter specific values in rows 105 to 143,
and 149 to 212?
¾ Do you want to use Provincial or regional N2O
emission factors?
¾If Provincial we need to go to sheet W and
manually transfer the provincial value found in
BE106 to BE116 to AF105 to AH122.
¾Is no tillage % and summerfallow correct? Rows
110 and 111, column B to O.
Modelling a Specific Plant
¾ For the plant we could model biomass as the heat
source.
¾ Some US plants are demonstrating Carbon
Capture and Storage of the CO2 from
fermentation.
¾ Both can be modelled with GHGenius.
¾ Input sheet B57 set to 1.
¾ Push “Go to Sequestration”
¾ Column V, row 15 to 43
¾ Push F9, go back to Upstream Emissions sheet
Low Carbon Ethanol Systems
Fuel
F e e d s to c k
Year
F u e l d is p e n s in g
F u e l d is trib u tio n a n d s to ra g e
F u e l p ro d u c tio n
F e e d s to c k tra n s m is s io n
F e e d s to c k re c o ve ry
L a n d -u s e c h a n g e s ,
c u ltiva tio n
F e rtilize r m a n u fa c tu re
G a s le a k s a n d fla re s
C O 2 , H 2 S re m o ve d fro m N G
E m is s io n s d is p la c e d
T o ta l
C o m b u s tio n e m is s io n s
G ra n d T o ta l
G H G e n iu s
3 .1 9
E th a n o l
C o rn
2010
75
1 ,1 6 1
2 3 ,7 7 6
2 ,6 0 4
5 ,6 3 9
2 0 ,4 1 4
5 ,0 3 3
0
0
-1 6 ,5 3 8
4 2 ,1 6 5
2 ,1 1 0
4 4 ,2 7 5
G H G e n iu s
G H G e n iu s
3 .1 9
3 .1 9
E th a n o l
E th a n o l
C o rn
W heat
2020
2010
S to ve r fu e l +
CSS
g C O 2 e q /G J
64
321
1 ,1 6 1
1 ,4 6 3
-2 1 ,0 1 2
4 3 ,9 9 1
3 ,2 8 5
1 ,5 8 4
8 ,7 9 0
4 ,3 5 1
1 9 ,6 2 2
6 ,9 0 1
4 ,3 3 8
0
0
-1 5 ,7 6 6
483
2 ,1 1 0
2 ,5 8 3
1 0 ,2 6 9
0
0
-2 3 ,5 9 1
4 5 ,2 8 9
2 ,1 1 0
4 7 ,3 9 9
G H G e n iu s
3 .1 9
E th a n o l
W heat
2020
S tra w fu e l +
CSS
266
1 ,4 3 6
-1 0 ,0 0 6
2 ,0 4 7
7 ,7 9 4
7 ,0 5 7
9 ,1 5 8
0
0
-2 2 ,7 0 2
-4 ,9 4 9
2 ,1 1 0
-2 ,8 3 9
Ethanol Limitations
¾ Ethanol is probably one of the most studied systems from
an LCA perspective.
¾ GHGenius doesn’t have wet mill co-products built into the
model at this time. It hasn’t been an issue for Canada, but
when imports are considered it is a possibility.
¾ US information on N2O emission factors is not as available as
it is for Canada.
¾ Soil carbon change data on a regional basis (and crop basis)
is not readily available.
¾ Direct farm energy data for most crops could be better.
¾ Ideally the model would handle tillage systems in a more
automated manner but this gets back to field energy
availability.
Questions?
Biodiesel
¾ Eight feedstocks in the model, soybeans, canola,
palm, algae, jatropha, waste cooking oils, animal
fats, and fish oil.
¾ In all cases we look at the “crop” production, the
extraction of the fats and oils, and the
transesterification of the fats and oils to make
biodiesel
¾ Feedstock production is generally more significant
than the biodiesel production process, as a result
the pathways look quite different.
Soybean Biodiesel
Canola Biodiesel
Tallow Biodiesel
Biodiesel
¾ GHGenius is the only model that uses a dynamic
system expansion process to allocate emissions
between the oil and meal.
¾ Other models use mass, energy, or economic
value to do this allocation.
¾ There are issues with all of these alternative
processes.
¾ Interestingly the EPA RFS2 work that was done
using FASOM, which is essentially an extremely
complex system expansion, had negative
emissions for soybean oil.
Biodiesel
¾ How can we have have negative emissions for oil
and therefore more than 100% of the emissions
allocated to the meal?
¾ If there was no soybean meal what would be used
to feed animals and meet their protein
requirements?
¾ If the emissions associated with the production of
this alternative animal feed is higher than those
associated with soybean meal production then
producing soybean meal avoids more emissions
than it creates and we have negative emissions for
soybean oil.
System Expansion
System Expansion
System Expansion
System Expansion
Biodiesel
General fuel -->
Fuel specification -->
Petrol diesel Biodiesel
0.001% S
CanD100
g CO2 /km g CO2 /km
Vehicle operation
Biodiesel
Biodiesel
SoyD100
PalmD100 TallowD100
g CO2 /km g CO2 /km
Biodiesel
Biodiesel
Biodiesel
YG100
FishD100
g CO2 /km g CO2 /km
g CO2 /km
1,078.3
1,108.3
1,108.3
1,108.3
1,108.3
1,108.3
1,108.3
0.0
-1,081.7
-1,081.7
-1,081.7
-1,081.7
-1,081.7
-1,081.7
1,078.3
26.7
26.7
26.7
26.7
26.7
26.7
Fuel dispensing
1.8
2.0
2.0
2.0
2.0
2.0
2.0
Fuel storage and distribution
7.3
18.2
14.1
14.7
8.2
8.2
14.7
129.5
111.6
213.6
400.0
640.4
151.2
1,050.2
Feedstock transport
13.9
15.0
30.2
37.7
58.0
12.2
0.0
Feedstock recovery
134.9
106.7
142.1
23.1
0.0
0.0
820.7
Land use changes and cultivation
3.3
100.4
622.1
220.4
0.0
0.0
0.0
Fertilizer manufacture
0.0
155.3
89.5
67.2
0.0
0.0
0.0
CH4 and CO2 leaks and flares
27.7
0.0
0.0
0.0
0.0
0.0
0.0
Emissions displaced by co-products
-3.5
-412.9
-919.3
-261.1
-641.5
-252.8
-898.5
1,393.1
123.0
220.8
530.7
37.9
-52.5
1,015.8
5.5
5.5
5.5
5.5
5.5
5.5
5.5
31.3
31.3
31.3
31.3
31.3
31.3
31.3
1,429.9
159.8
257.6
567.5
57.1
-15.7
1,052.6
C in end-use fuel from CO2 in air
Net Vehicle operation
Fuel production
Sub total (fuelcycle)
Vehicle assembly and transport
Materials in vehicles (incl. storage)&
lube oil
Grand total
Modelling a Specific Plant
¾ What do we have to do to model a specific plant?
¾ Where is the plant located?
¾Use one of the buttons in row 2 or set the region
in row 5.
¾ Feedstock transportation distances
¾Are defaults OK or do you want to input specific
parameters in rows 75 to 85?
¾ Product transportation distances
¾Are defaults OK or do you want to input specific
parameters in rows 89 to 99?
Modelling a Specific Plant
¾ For the biodiesel plant we need the same kind of
information as the ethanol plant.
¾ Feedstock requirements, AH 234
¾ Electric Power, AH 229
¾ Natural Gas, AH 231
¾ Misc. Fuel, AH 230
¾ Year of Data, AH 227
¾ We may also want to change some of the chemical
inputs on sheet X. Rows 29 to 41.
Biodiesel Production
¾ Oil production and biodiesel production are
separate stages and there can be transportation in
between.
¾ Two sets of biodiesel production parameters
¾ Vegetable oil esterification and animal fat
esterification.
¾ Yield is different as is input energy.
Canola Biodiesel vs. Time
10,000
9,000
GHG Emissions
g CO2eq/GJ
8,000
7,000
6,000
5,000
4,000
3,000
2,000
1,000
0
2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020
Year
Biodiesel Limitations
¾ There is a wide range in biodiesel GHG emission results in
the literature.
¾ This is driven by the use of old data for oilseed crushing and
the issue of nitrogen fixing crops and N2O emissions.
¾ The impact of energy consumption in the biodiesel plant is not
that great and so plant to plant variances due to this are not
large.
¾ The utilization of glycerine, what it is displacing is a significant
variable and there is a lack of public data on this issue.
¾ Farm field energy issues are similar to the other biomass
feedstocks.
Questions?
Renewable Diesel - HRD
Renewable Diesel
¾ Select Feedstock on the Input sheet in cell B50.
¾ All of the feedstock transportation distances are
the same as for biodiesel. One set of inputs feed
both pathways.
¾ HRD distribution distances are different from
biodiesel. AE89 to AE99 on Input sheet.
¾ HRD Processing parameters
¾ BC227 to BC 234.
HRD Biodiesel Comparison
General fuel -->
Fuel spec (feedstock) -->
Production process energy -->
Vehicle operation
C in end-use fuel from CO2 in air
Net Vehicle Operation
Fuel dispensing
Fuel storage and distribution
Fuel production
Feedstock transport
Feedstock recovery
Land-use changes, cultivation
Fertilizer manufacture
Gas leaks and flares
CO2, H2S removed from NG
Emissions displaced by co-products
Sub total (fuelcycle)
% changes (fuelcycle)
Vehicle assembly and transport
Materials in vehicles
Grand total
% changes (grand total)
Petrol diesel
0.0015% S
crude oil
1,078.6
0.0
1,078.6
7.2
10.2
123.4
5.9
194.9
6.6
0.0
33.5
0.0
-7.5
1,453.0
-5.7
37.5
1,496.1
--
HRD
Biodiesel
HRD100
PalmD100
Palm Oil
C0/NG26/B69/EL3
1,032.4
1,108.6
-1,005.6
-1,081.7
26.8
27.0
7.0
8.3
13.9
16.5
351.1
361.9
41.2
39.7
25.7
24.8
238.2
229.2
70.6
67.9
0.0
0.0
0.0
0.0
-26.3
-261.8
748.3
513.3
-48.5
-64.7
5.7
5.7
37.5
37.5
791.5
556.5
-47.1
-62.8
Questions?
Natural Gas for Vehicles
¾ GHG emissions from the combustion of natural
gas are 20-30% less per GJ than gasoline or
diesel fuel
¾ This is partially offset by lower engine efficiency.
This relative engine efficiency is thus a key driver
in the GHG performance of NGV
¾ Other factors that are important are compression
or liquefaction energy, leaks of methane at all
stages of the lifecycle
LD NGV GHG Performance
0.0000
1995
2000
2005
2010
-5.0000
Percent Change
-10.0000
-15.0000
-20.0000
-25.0000
-30.0000
Year
2015
2020
2025
HD NGV GHG Performance
5
% Reduction in GHG Emissions
0
1995
2000
2005
2010
-5
-10
-15
-20
-25
Ye ar
2015
2020
2025
Natural Gas for Vehicles
¾ Input sheet
¾ Compression inlet and outlet pressures
¾ Sheet AB
¾ Fuel compression issues
¾ Sheet R
¾ Natural gas distribution and dispensing
¾ Sheet C
¾ Vehicle relative efficiency
Natural Gas
¾ Sheet C
¾ Powertrain Efficiency
¾ Fuel Storage / Extra Weight
¾ For technologies under development there is
uncertainty about the relative efficiency of the new
technology compared to gasoline or diesel.
¾ On sheet C we have our best estimates of a value
and how they change over time
¾ Manufacturers don’t release much information and
what they do may not be 100% accurate.
EV Performance Evolution
Alternative Run Types
¾ Monte Carlo
¾ Runs with either full macros or the “F9” style
¾ Up to five inputs, and eighteen outputs
simultaneously
¾ Will not give individual inputs, but parameters of
distributions
¾ Graphs of distributions are optional
¾ More iterations will give more accuracy but will add
significant time to the run
Natural Gas
¾ Monte Carlo
¾ C!I36 and C!I37:
¾Set cell 36 equal to cell 37
¾Vary cell 37 around 0.85 by 0.04
¾ C!Z105:
¾Vary the range
¾This will automatically change the weight of the
vehicle
¾ Set to run Buses, do not check “Full Run”
-4
-5
-6
-7
-8
.1
.3
.4
.5
.6
.8
0.
9
2.
0
3.
1
4.
3
5.
4
6.
5
7.
6
8.
7
9.
9
1.
0
2.
1
3.
2
4.
4
5.
5
6.
6
7.
7
8.
8
0.
0
1.
1
-9
-1
-1
-1
-1
-1
-1
-1
-1
-1
-2
-2
-2
-2
-2
-2
-2
-2
-3
-3
Natural Gas
Improvement over diesel by frequency
350
300
250
200
150
100
50
0
Questions?
Website
¾ www.ghgenius.ca
¾ Public area for
¾ Information on the model.
¾ Links to other sites of interest.
¾ Area for registered users
¾ Reports that have been prepared using GHGenius.
¾ Model for download.
¾ User forum.
Questions
and
Discussion
Thank You
Index
¾ Fuel Economy
¾ Crude Oil
¾ Ethanol
¾ Biodiesel
¾ Natural Gas