Biomass Crop Assistance Program, Project Area Number 1 Implemented for Western Missouri and Eastern Kansas County Biomass Producers PDF Download
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Author:
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ISBN:
Category : Agriculture and state
Languages : en
Pages : 3
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Author:
Publisher:
ISBN:
Category : Agriculture and state
Languages : en
Pages : 3
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Author:
Publisher:
ISBN:
Category : Agricultural administration
Languages : en
Pages : 1134
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Author: Evan K. Drury
Publisher:
ISBN: 9781607414209
Category : Aigua
Languages : en
Pages : 0
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Environmental quality is a general term which can refer to varied characteristics that relate to the natural environment as well as the built environment, such as air and water purity, pollution, noise and the potential effects that they may have on physical and mental health. The natural environment is contrasted with the built environment, which comprises the areas and components that are strongly influenced by humans. A geographical area is regarded as a natural environment if the human impact on it is kept under a certain limited level. This book presents research on a wide variety of environmental concerns in today's world. Included are chapters on renewable energy technology, water quality, recycling of electronic equipment, and corporate environmental commitment. The attitudes of university students toward environmental concerns are also discussed as well as a study that empirically examines local land use planning capacity for mitigating environmental hazards.
Author:
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Category : Agricultural subsidies
Languages : en
Pages : 2
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Category : Aeronautics
Languages : en
Pages : 1368
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Author: California Energy Commission. Agricultural Biomass to Energy Program
Publisher:
ISBN:
Category : Agricultural wastes as fuel
Languages : en
Pages : 40
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Author:
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ISBN:
Category :
Languages : en
Pages : 167
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The Driftless Area Initiative Biomass Energy Project evaluated the potential for biomass energy production and utilization throughout the Driftless Region of Illinois, Iowa, Minnesota and Wisconsin. The research and demonstration aspect of the project specifically focused on biomass energy feedstock availability and production potential in the region, as well as utilization potential of biomass feedstocks for heat, electrical energy production, or combined heat and power operations. The Driftless Region was evaluated because the topography of the area offers more acres of marginal soils on steep slopes, wooded areas, and riparian corridors than the surrounding "Corn Belt". These regional land characteristics were identified as potentially providing opportunity for biomass feedstock production that could compete with traditional agriculture commodity crops economically. The project researched establishment methods and costs for growing switchgrass on marginal agricultural lands to determine the economic and quantitative feasibility of switchgrass production for biomass energy purposes. The project was successful in identifying the best management and establishment practices for switchgrass in the Driftless Area, but also demonstrated that simple economic payback versus commodity crops could not be achieved at the time of the research. The project also analyzed the availability of woody biomass and production potential for growing woody biomass for large scale biomass energy production in the Driftless Area. Analysis determined that significant resources exist, but costs to harvest and deliver to the site were roughly 60% greater than that of natural gas at the time of the study. The project contributed significantly to identifying both production potential of biomass energy crops and existing feedstock availability in the Driftless Area. The project also analyzed the economic feasibility of dedicated energy crops in the Driftless Area. High commodity crop prices and land values coupled with low fossil fuel prices, particularly natural gas, hampered the likelihood of widespread production and/or utilization of for large scale heating or electrical generation at the time of the study.
Author: Andy Clark
Publisher: DIANE Publishing
ISBN: 1437903797
Category : Technology & Engineering
Languages : en
Pages : 248
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Cover crops slow erosion, improve soil, smother weeds, enhance nutrient and moisture availability, help control many pests and bring a host of other benefits to your farm. At the same time, they can reduce costs, increase profits and even create new sources of income. You¿ll reap dividends on your cover crop investments for years, since their benefits accumulate over the long term. This book will help you find which ones are right for you. Captures farmer and other research results from the past ten years. The authors verified the info. from the 2nd ed., added new results and updated farmer profiles and research data, and added 2 chap. Includes maps and charts, detailed narratives about individual cover crop species, and chap. about aspects of cover cropping.
Author: Larry E. Biles
Publisher:
ISBN:
Category : Computer software
Languages : en
Pages : 260
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"The goal of this research project was to assess the geospatial economic availability of cellulosic feedstocks (woody and ag-residue) for demand sites in Kansas with supply zones coming from within the state and in some instances from the five-state surrounding region. The study will improve the overall understanding of the economic costs for cellulosic feedstocks for potential manufacturers wishing to locate in the state of Kansas. The study provides business decision-makers in the cellulosic feedstock-using industries with a geospatial economic tool that will allow them to assess the economic comparative advantages of cellulosic supply in the state, and at the sub-regional/interstate levels. A key outcome of the study was the development of the website http://www.biosat.net/Kansas/index.html, which will allow business decision makers to use the web-based tool for demand sites and supply regions for all possible locations in KS that are not possible to illustrate in this final report. Key cost inputs (e.g., diesel costs, etc.) for the cost models of the KS BioSAT model are updated periodically for users of the website. The KS BioSAT project is an outcome of the "BioSAT" project by Perdue et al. (2011), http://www.biosat.net/. Users of the BioSAT model on http://www.biosat.net/ will have an access link to the KS BioSAT model. Assessing the economic capability and stability of the bioenergy supply chain infrastructure is essential for market organization of this emerging industry, and is the key question addressed by this study. Elbehri (2007) noted that lack of biomass production capacity, high relative costs of production, logistics, and transportation of feedstocks, are all potential constraints that need to be better understood. A plethora of literature exists on the economic availability of biomass (Young and Ostermeier 1989, Young et al. 1991a 1991b, Lunnan 1997, Walsh 1998, 2000, DiPardo 2000, Ugarte et al. 2000, 2006, 2007, Biomass Research and Development Board 2008, Western Governors Association 2008, Perez et al. 2009, Galik et al. 2009, U.S. Dept. of Energy 2011). A recent report by the U.S. Department of Agriculture and Department of Energy concluded that 1.3 billion tons of biomass are available annually for energy production (Perlack et al. 2005, U.S. Dept. of Energy 2011). Geo-referenced producer supply curves were estimated in this study for woody and agricultural residue feedstocks. The resolution of the study was the 5-digit zip code tabulation areas (ZCTA) in Kansas and five of its surrounding states. The aggregate producer supply curves are geo-referenced and estimate of resources costs (e.g., stumpage), logging or harvesting costs, and transportation costs to the mill-gate. Sourcing (or feedstock supply) areas are often non-concentric aggregations of ZCTAs which we believe accurately portray supply zones as a function of the corresponding available road network. Resource cost data (e.g., mill residue prices, pulpwood prices, etc.) were obtained from Timber Mart South (TMS), Timber Mart North, and the Missouri price reporting service. The transportation cost model of the KS BioSAT model estimates trucking costs based on the shortest travel time (influences variable costs) between the potential demand ZCTA and its associated supply ZCTAs . Microsoft© MapPoint® 2011 was used to estimate the shortest travel time routes and distances between ZCTAs. Road networks in MapPoint® are a combination of the Geographic Data Technology, Inc. (GDT) and Navteq data. The Subregional Timber Supply (SRTS) model was used to estimate logging residue supply and recovery rates (Abt et al. 2000, Abt 2008). The Fuel Reduction Cost Simulator (FRCS), as modified for the Billion Ton Study, was used to estimate the costs of harvesting "in-woods" logging residues (Dykstra 2008). The Auburn Harvest Analyzer (AHA) was used to estimate harvesting costs for 'roundwood' (Greene and Lanford 1987, Tufts et al. 1985, Tufts et al. 1988, Lanford and Stokes 1996, Holtzscher and Lanford 1997). The AHA model was adapted for the six-state study region givens its ecoregions, forest stand types, and two available harvesting systems. Agricultural residues costs were estimated from the literature (Gallagher et al. 2003, U.S. Bureau of Labor Statistics, 2009). Forest volume estimates were obtained from the Forest Inventory and Analysis Database (FIADB) (U.S. Department of Agriculture, Forest Service 2012). Mill residue estimates were obtained from the U.S. Forest Service Forest Inventory and Analysis Database Timber Product Output Reports (U.S. Department of Agriculture, Forest Service 2014). Agricultural residue estimates were obtained using USDA National Agricultural Statistics Service survey data and residue derivatives were estimated using the equations and conversion factors of the literature (Proctor 1994, Nelson et al. 2004, USDA National Agricultural Statistics Service 2012). Softwood and hardwood logging residue marginal cost curves were estimated for "chipping tops and limbs at the landing" (referred to as logging residue costs "at-landing") and for ""in-woods" harvesting of sub-merchantable material" (referred to as "in-woods" logging residue costs). Marginal cost curves for procuring mill residues were estimated for "clean softwood," "clean hardwood," "unclean softwood," "unclean hardwood". Marginal cost curves for 'roundwood' were estimated for "lowland hardwood," "mixed natural softwood and hardwood," "natural softwood," "pine plantation," and "upland hardwood" for both pulpwood and sawtimber. Given that there were cost estimates for 44 possible combinations of feedstocks types available from the KS BioSAT model; cost data for only a select set of feedstocks are presented in this report. More detail is given in the results section of the report and cost data for all feedstock types are available at www.biosat.net/Kansas/index.html/."
Author:
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ISBN:
Category : Government publications
Languages : en
Pages : 1250
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