Doctor of Philosophy / Department of Grain Science & Industry / Dirk E. Maier / The feasibility of utilizing cellulosic biomass as an energy feedstock is dominated by factors such as facility location, feedstock availability, and transportation cost. The main goal of this research was to develop a GIS-based method that will generate more accurate biomass residue availability data as input data to biomass supply chain logistics models. This research was carried out in four objectives to ensure that, as improvement parameters were implemented, the methodology remained valid and became more accurate. The first objective compared an existing method to a proposed method to quantify feedstock availability given a facility’s location using a geographical information system. The proposed method proved to be more robust (by a factor of 1.45) than the existing method because it calculates the distance from the facility to farm fields using a real road network, and the acreage of crop-specific fields in a given service area based on crop season specific satellite images. The second objective implemented two improvement parameters to the previously proposed constant removal rate (CRR) method. It examined the effect of field-level yield variance and variable removal rates (VRR) on quantification of the feedstock availability supply for a biorefinery. The new VRR method predicted on average 113,384 ± 38,770 dry tons (DT) of additional residue per service area compared to the CRR method. The third objective further improved the VRR method by utilizing multiple crops as biomass sources and estimating VRR based on crop rotation. On average a 3,793 ± 5,733 DT per service area difference resulted when increasing the number of crop-specific VRR rates used to estimate feedstock quantification. The supplementary use of crop-specific VRR rates affected residue availability given a crop’s residue removal rate is influenced by crop yield, crop rotation, soil characteristics, as well as field location and management. The fourth objective assessed the suitability of potential feedstock storage locations (FSL) to store multi-crop biomass remotely based on a spatial and location-allocation analysis. The sensitivity analysis showed that scenario 2 (16-km; 10-mile service area) appeared to be the more cost-effective option given fewer FSLs (35) were needed and more demand points could be serviced (98.1%) compared to scenario 1 (8-km; 5-mile service area; 62.1% demand points; 50 FSLs), despite presumably higher transportation costs.
| Identifer | oai:union.ndltd.org:KSU/oai:krex.k-state.edu:2097/16304 |
| Date | January 1900 |
| Creators | Martinez-Kawas, Adrian |
| Publisher | Kansas State University |
| Source Sets | K-State Research Exchange |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
Page generated in 0.0017 seconds