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- For wood to natural gas there is some work underway in Europe investigating and demonstrating at the pilot level the gasification of wood and the upgrading of the gas to produce pipeline quality natural gas. Some preliminary data is available. This data has been reviewed and the model has been updated to reflect recent advances.
- There is some interest in producing pipeline quality gas from coal in Canada. There is one commercial pant in the United States (Dakota Gasification) and the literature surrounding that plant has been reviewed, along with new process developments in the field, to develop the basis for a new pathway in the model. This pathway is similar to the wood to natural gas pathway and the use of the gas will include light and heavy-duty vehicles.
Tags: Coal - Ethanol - GHGenius 3.6 - Lignocellulosic - Natural Gas - Wood
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
The primary work on the ethanol pathways in GHGenius was undertaken in 1999 and while there have been some minor updates since then, the primary data in the model has not been reviewed in the past five years. There are several important issues that have been investigated and added to the model to better reflect the emissions of modern plants. These include:
1. Reviewed and updated energy requirements for grain ethanol plants. There have been significant reductions in the energy requirements of new grain ethanol plants in the past five years. This progress has been reviewed and incorporated into the model.
2. The addition of the capture and liquefaction of carbon dioxide. Ethanol plants produce a very concentrated carbon dioxide stream, which can be captured and liquefied for use in a variety of industrial applications. Alternative sources of carbon dioxide are less concentrated and require more energy to concentrate and purify. Depending on the degree to which carbon dioxide from ethanol plants displace carbon dioxide from other sources there can be an energy and emissions credit applied to the ethanol plant. This alternative processing scheme has been added to the model with the flexibility to activate or not, either fully or partially.
3. In the development of commercial ethanol from lignocellulose plants there are new co-products being developed. Some of these include fertilizers and soil conditioners. The model has been expanded to include fertilizer co-products.
4. There is some information in the literature that suggests that some animals that consume distillers dried grains have lower levels of flatulence. The literature has been surveyed for further information on this issue and this emission credit has been incorporated into the model.
A major part of any life cycle analysis is the collection of the data on the inputs and outputs of the production cycle being analyzed. The quality of the data has a large impact on the quality of the results being calculated. Data quality must balance the available time and resources against the quality of the data required to make a decision regarding overall environmental or human health impact.
In GHGenius the data on many of the production pathways is continually being updated as new information sources emerge or as processes evolve. Recently new information on the emissions of the fertilizer sector in Canada has become available, and new information on nitrous oxide emissions in the agriculture sector are also available. These changes to the model were described in a recent report on the emissions from biodiesel production ((S&T)2, 2005). These changes also impact the ethanol fuel pathways either directly in the case of fertilizer or indirectly in the case of soybean emissions since the distillers dried grains (DDG) displaces soybean meal and the emissions credit for the DDG is a function of the emissions from the soybean lifecycle.
The input variables are another class of data input. These variables can be expected to differ in different regions of the country or in different countries in response to different practices or environmental conditions. These inputs are generally found on the input sheet in GHGenius as one expects them to be changed in different circumstances.
These input variables for the different ethanol pathways have been reviewed and where better data now exists for some variables, this information has been added to GHGenius. It is important to keep in mind that the general approach to the data in GHGenius is to model the most likely scenarios, not the best-case scenario where practices or existing equipment would have to change to produce the modelled results.
Several new co-products have been added to GHGenius that are applicable to the ethanol pathways. The ability to model the capture of carbon dioxide and have that product displace gas from alternative production sources in now available. Cellulosic ethanol production processes produce large amounts of lignin, which can be processed by different means. It is possible to burn the material and produce electricity or it may be possible to sell the material for other applications. One application may be as a source of fertilizer and this capability has been added to the model. The handling of other co-products such as acetic acid has been improved in the model.
The co-product credits for DDG have been reviewed. The displacement factors for DDG have been reduced as more feed trials suggest lower displacement ratios that are used in other models and have been used in previous versions of GHGenius. The value of DDG as animal feed is a very complicated subject as there are many components in a typical ration and it is almost impossible to design a reasonably sized experiment to isolate the impact of one of the components. There is a significant amount of information on the impact of diets on methane production from cattle. It is clear that introducing dietary supplements, particularly ones with by-pass protein will reduce the methane production rate in dairy and beef cattle. Estimates of the impact of DDG on methane emission rates have been made and incorporated into the model.
Tags: Corn - Ethanol - GHGenius 2.6 - Lignocellulosic - Wheat
Prepared November 2004
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They have also established a $100 million Ethanol Expansion Program to assist with the construction of new ethanol plants in Canada. The funding under the Ethanol Expansion Program is part of a larger bio-fuels strategy that also includes the extension of the National Biomass Ethanol Program, research and development under the biotechnology component of the Technology and Innovation Strategy and an investment in bio-diesel.
There has been little economic and financial analysis of ethanol within a Canadian context. The few published and unpublished studies carried-out so far for the public sectors have dealt mostly with potential socio-economic impacts and have attracted little interest from the investment community due to their lack of focus on profitability, both short and long term. Policy and decision makers, financial institutions, and other economic players need the more detailed, formal analysis framework in order to make investment decisions regarding the development of these fuels.
The primary objective of this study is to assess the current and future economics of ethanol plants in Canada and to develop estimates of demand, supply, and prices (costs and selling) of this fuel. The results are then used to develop a template-like analytical tool for various models of ownership structure, to help assess the financial performance of various types of fuel ethanol (regional and feedstock specific) plants across Canada.
The work was carried out in Phases and stages. This report covers Phase 1, for fuel ethanol. A similar report has been prepared for biodiesel.
The specific objectives of Phase 1, Stage 1 were to:
· Review literature on economic and financial performance of ethanol plants.
· Identify successful plants and reasons for success.
· Quantify feedstock resources and production costs.
· Develop a comprehensive financial model.
· Develop a supply curve.
The objectives of Phase 1, Stage 2 were to:
· Identification of market barriers.
· Evaluate policy tools including.
o Government capital investment
o Favourable tax treatment
o Infrastructure investment
o R&D funding
o Renewable content mandates
o Emission taxes
· Examine the potential for regionalization of tools.
· Quantification of levels of support required.
· Investigate other approaches to market development.
Phase 1, Stage 3 of the work focuses on the international aspects of a developing ethanol industry and considers the threats and opportunities that international trade in biofuels presents. The specific tasks of this stage include:
· Identification of the level of international trade.
· Production cost comparison with the potential exporters of fuel ethanol.
· Analysis of the import alternatives that ethanol users in Canada would face.
· Evaluate the impacts that ethanol imports might face and identify measures that might mitigate the impacts.
· Evaluate the impact of trade agreements on enabling or disabling Canadian industry competitiveness.
The next phase of the work will include some GHG analyses.
Tags: Corn - Economic - Ethanol - Lignocellulosic - Wheat
Prepared for Natural Resources Canada in March 2004
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- Allow selection of ethanol cellulosic feedstock from the input sheet. Ethanol from lignocellulosic feedstocks could be produced from a variety of feedstocks including wheat straw, corn stover, switchgrass, and hay.
- Improve the quality and functionality of the emissions from crude oil production and refining in Canada. The model has been modified to use four different crude oil types, conventional, heavy, bitumen and synthetic.
- Harmonize the methodology for the production of hydrogen from electrolysis with other methods.
- Review and update the Canadian electricity mix.
- Update the emissions of criteria air contaminants from heavy-duty diesel engines on Sheet H in light of the new emission standards being phased in this decade.
- The latest LEM model by Dr. Mark Delucchi made many changes to sheet L that calculates emissions associated with materials. The documentation that describes the changes to determine the best data to use for GHGenius with particular attention to the data for Canada has been reviewed and the appropriate changes have been made to GHGenius.
Tags: Crude Oil - Electricity - Ethanol - Exhaust Emissions - GHGenius 2.5 - Lignocellulosic - Refining
Prepared for Agriculture and Agri-Food Canada in December 1999
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Tags: Ethanol - Lignocellulosic