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 Sugar Cane TagsBarley
Biodiesel
Canola
Corn
Ethanol
GHGenius 3.2
GHGenius 4.01
HRD
Jatropha
Lignocellulosic
Materials
PHEV
Palm Oil
Soybeans
Sugar Cane
SuperCetane
Tallow
Used Cooking Oil
Wheat
Wheat Straw
Yellow Grease
 Sugar Cane Ethanol Update
 Prepared May 2012
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This pathway in GHGenius was added to the model in 2006. Sugarcane production systems in Brazil have undergone significant change since that time with the introduction of mechanical cane harvesting, the continued evolution of the sugar and ethanol mills, and the development of a more significant co-generation capacity in the industry as a result of changing government policies.

There is also much more data available on the industry as a result of a significant effort by the Brazilian industry to document their activities and the inclusion of this pathway in the US RFS2 program and in the California Low Carbon Fuel Standard program. There is information available for both manual and mechanical harvesting. This update includes the option to allow the user to choose which harvesting approach to use for modelling. The user can specify how much of the feedstock is harvested manually and how much is done mechanically and the button installs the appropriate defaults throughout the model.

Where possible, the data in the model has been converted to the time series approach that has been used in recent updates to the model. This provides greater certainty for the input data as it effectively deals with year to year variations due to weather.

Particular attention has been paid to soil emissions and fugitive emissions from the vinasse disposal systems. These two issues were identified as areas of uncertainty and ongoing research in Brazil.

The version of the model that accompanies this report is GHGenius 4.01. Several other changes to the model were carried out at the same time but these have their own reports. The sugarcane ethanol system is shown in the following figure.

Tags: Ethanol - GHGenius 4.01 - Sugar Cane
 2010 Biofuel Analysis
 Prepared December 2010
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In 2006, GHGenius was used to analyze the GHG emissions from the biodiesel and fuel ethanol pathways of interest in Canada. That project also investigated the sensitivity of the emissions to some of the parameters than could vary from project to project. That report has been used by a number of government departments, as they study the development of the industry in Canada. It is also one of the more popular reports on the GHGenius website.

Our knowledge of the performance of the biofuels industry in Canada has improved significantly in the four years since that work was done. In addition, GHGenius has been updated with better data on the biofuel production process and feedstock production systems. An updated report is therefore warranted, given the continued interest in the subject and the updated modelling data. The report will also serve as an updated documentation resource for these pathways in the model.

The biofuel pathways that have been analyzed in this report include five ethanol pathways, corn, wheat, barley and sugar cane based systems and a cellulosic ethanol system based on wheat straw feedstock. Six biodiesel feedstocks have been considered, canola, soybeans, tallow, used cooking oil, palm oil and jatropha. Four feedstocks have been considered for hydrotreated oils, palm, canola, tallow, and soybean oil.

For the sensitivity analysis, the focus has been on the issues that can vary from plant to plant, such as co-product drying, the use of combined heat and power, and the energy source for the thermal energy. In addition, issues that still have some uncertainty, such as changes in soil carbon are evaluated.

Tags: Barley - Biodiesel - Canola - Corn - Ethanol - HRD - Jatropha - Palm Oil - Soybeans - Sugar Cane - Tallow - Used Cooking Oil - Wheat - Wheat Straw
 Biofuel Sensitivity Analysis
 Prepared August 2006
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The purpose of this work was to identify key factors that influence the life-cycle greenhouse gas (GHG) emissions of current ethanol and biodiesel production pathways. This information can then be used by policy makers, fuel producers, distributors, retailers and consumers to assist them in making decisions that positively impact the lifecycle GHG performance of the renewable fuels sector.

For the transportation sector there are generally three ways that GHG emissions can be reduced; improve energy efficiency at all stages of the life cycle, use lower carbon intensity fuel sources, or change transportation modes. Combinations of the three approaches are of course also possible.

Renewable fuel producers have some control over the first two categories but they will be looking to maximize the return on investment when they design and build biofuel facilities and not necessarily minimizing GHG emissions. This may lead to the facilities being energy efficient but the types of energy that are used in the facilities may not be optimized.

For this work we are interested in, among other possibilities, the emissions impact that could arise from different farming practices. These practices could result in soil carbon changes and perhaps in changes in above ground biomass. The default values for modelling have therefore been set so that in the base case there is no change in soil carbon, no change in above ground biomass arising from increased crop yields, and no biomass growth resulting from nitrogen run-off lost offsite.

Tags: Biodiesel - Canola - Corn - Ethanol - Lignocellulosic - Palm - Soybeans - Sugar Cane - SuperCetane - Tallow - Wheat - Yellow Grease
 Sugar Cane Ethanol and Other Updates
 Prepared January 2006
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The report covers work on new pathways and updating data. This work involved the following tasks and deliverables.

1. A new table has been added to sheet I that shows the fossil energy consumption per kilometre driven. This augments the existing Table 51c that shows the total energy consumed per kilometre driven.

2. New information on the energy requirements to remove sulphur from gasoline and diesel fuel in Canada has recently become available. This information has been reviewed, and the formulas on sheet G have been changed to be consistent with this new data.

3. There is increased interest in the concept of plug in hybrid vehicles. These vehicles have a larger battery pack than existing hybrid vehicles and must be plugged in to maximize the battery charge. The vehicles operate with some fraction of the energy consumed provided by the power from the grid rather than having all of the power provided by the gasoline engine. These vehicles can operate as a combination of a battery powered electric vehicle and a gasoline vehicle. This pathway has been added to the results sheets using a user specified fraction of distance provided by the grid power and battery size.

4. There has also been interest in modelling gasoline powered heavy-duty vehicles and gasoline hybrid heavy-duty vehicles. These vehicles may also be medium duty vehicles so the classes of vehicles modelled have been expanded by including vehicle weight as part of the user inputs. This will allow the different weight classes to exhibit different efficiencies. The US EPA guidance on this issue has been followed.

5. The production of ethanol from sugar cane has been added to the model. While the production of ethanol from sugar cane is not likely possible in Canada, there has been some sugar cane ethanol imported into Canada and interest in this pathway remains high in Canada. Some information on the production process is available from Brazilian sources and this information has been reviewed to extract the data required for adding this pathway to GHGenius.

6. The energy consumed in the manufacture of materials that are used in the manufacture of vehicles is found on sheet L in the model. This information was briefly reviewed in the 2004 model update but there were still significant gaps in terms of good quality Canadian data availability. This issue has been reviewed again to search for new information that has become available in the past several years on the subject. Updated data has been incorporated into the model.

The version of the model that accompanies this report is version 3.2.

Tags: Ethanol - GHGenius 3.2 - Materials - PHEV - Sugar Cane
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