Summary of Key Findings
The study area includes five counties which mainly surround the northern extent of Guelph. The service area distance of 100km captured the entire study area's extent. In order to get a better estimate of total available resources within 50 and 100 kilometer distances of Guelph, biomass yield estimations of counties south of Guelph including Halton, Hamilton, Brant and Oxford would be needed. These counties could theoretically supply more biomass due to their more southern extent and thus longer growing season.
Results from the analysis suggest that forestry and fallow land devoted to switchgrass production only provide a marginal 2.3% increase in biomass yields. Therefore, current agricultural practices could provide sufficient biomass resources for a potential biofuel refinery. If the study area included all the potential resources within a 50km and 100km service distance of the City of Guelph, the total yield of biomass could provide the City of Guelph with approximately 24.6% and 56% of annual electricity demand.
Strengths and Limitations
Using GIS modeling allows for the inclusion of sustainability thresholds and criterias. Because of this, biomass yield data is produced and can represent a fairly accurate yearly supply of biomass within the study area. These results, determined from the model, will allow for further investigation into the construction of a biorefinery. It provides the City of Guelph with an in-depth spatial analysis of potential biomass resources and enables for further planning and investing decisions regarding the implementation of bioenergy production. The results from this model will assist in making Guelph’s energy plan initiatives a successful reality of the future. This can be achieved by having access to information on where high density areas of potential biomass resources are located as well as accessible routes and distances to these resources via road networks.
The economics associated with a biorefinery location, including infrastructure and transportation methods for biomass resources is the next step in terms of determining realistic costs. This is necessary in determining whether or not a biofuel refinery is possible and where, specifically, that biofuel refinery would be most economically viable. An in-depth cost analysis would be required to determine the limitations of transporting low density resources over long distances.
We would like to thank Adam Bonnycastle, Kirby Calvert, Melanie Chabot, and Nabil Allataifeh for their instruction and guidance throughout this project.