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Assessing the Awareness of Florida Homeowners about the Use of Biomass for Electricity production


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ASSESSING AWARENESS OF FLORIDA HOMEOWNERS ABOUT THE USE OF BIOMASS FOR ELECTRICITY PRODUCTION By MARK D. ADAMS A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2003

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Copyright 2003 by Mark D. Adams

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To my parents, Alphonso and Jacqueline Adams; and the rest of my loving family

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ACKNOWLEDGMENTS I would like to take this opportunity to thank Dr. Donald L. Rockwood, who presided as my major professor. His support, advice, and assistance throughout this graduate program have been invaluable. I would also like to thank the rest of my committee members (Drs. Janaki Alavalapati and Tracy Irani, and Mr. Jim Stricker) for their guidance and encouragement while conducting this research. The Florida Institute of Phosphate Research, the Center for Natural Resources, and Gainesville Regional Utilities also provided invaluable support for this project; without their contributions, much of this project could not have taken place. Special thanks go to my statistics professors (Eve Brank and Larry Winner) for introducing me to the logistics of social statistics. Thanks also go to the IFAS Communications and Mail Documenting Services support staff for their diligent and timely assistance. Finally, I would like to thank my wonderful parents, Alphonso and Jacqueline Adams, and the rest of my family for their constant and loving support throughout this project and my academic career. iv

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TABLE OF CONTENTS Page ACKNOWLEDGMENTS.................................................................................................iv LIST OF TABLES............................................................................................................vii LIST OF FIGURES...........................................................................................................ix ABSTRACT.........................................................................................................................x CHAPTER 1 INTRODUCTION........................................................................................................1 2 LITERATURE REVIEW.............................................................................................3 Alternative Energy Overview.......................................................................................3 Role of Energy Producers.............................................................................................4 Media Related Response to Environmental Issues.....................................................10 Environmental Benefits Approach.............................................................................11 Overview of Survey Literature...................................................................................12 3 METHODS.................................................................................................................16 4 RESULTS AND DISCUSSIONS...............................................................................20 Overall County Responses..........................................................................................20 Respondent Demographics.........................................................................................21 Responses to Environmental Questions......................................................................24 5 CONCLUSIONS........................................................................................................41 6 FUTURE RESEARCH...............................................................................................43 APPENDIX A SURVEY: ENVIRONMENTAL VALUES AND AWARENESS OF FLORIDA RESIDENTS...............................................................................................................44 B INITIAL COVER LETTER.......................................................................................45 v

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C FOLLOW-UP COVER LETTER...............................................................................46 D RETURN ADDRESSED STAMPED ENVELOPE..................................................47 E GRU BROCHURE: DEERHAVEN GENERATING STATION NEIGHBORS WITH NATURE.........................................................................................................48 F CONTINGENCY TABLE AND CHI-SQUARE VALUES FOR GLOBAL WARMING, ALTERNATIVE ENERGY METHODS, AND WILLINGESS TO PAY MORE FOR SAFE ENERGY...........................................................................49 G OVERALL COUNTY RESULTS FOR HOME AND LIFESTYLE ACTIVITY.....55 H OVERALL COUNTY RESULTS FOR HOME COOLING AND HEATING.........58 I OVERALL COUNTY RESULTS FOR WATER HEATERS, POOLS, AND SPAS...........................................................................................................................60 J OVERALL COUNTY RESULTS FOR HOME AND KITCHEN APPLIANCES...63 K OVERALL COUNTY RESULTS FOR ENVIRONMENTAL AWARENESS........66 LIST OF REFERENCES...................................................................................................69 BIOGRAPHICAL SKETCH.............................................................................................74 vi

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LIST OF TABLES Table page 2-1 Biomass crop yields in Florida.................................................................................10 4-1 Number of responses and percentage of all responses by county............................21 4-2 Overall Response and Respondent Demographics for Alachua (A), Duval (D), Hillsborough (H), Orange, Polk (P) Counties and Alachua Group B......................22 4-3 Numbers and percentages of missing demographical information for Alachua (A), Duval (D), Hillsborough (H), Orange (O), Polk (P) and Alachua Group B.....23 4-4 Participant awareness of environmental terms for Alachua (A), Duval (D), Hillsborough (H), Orange (O), Polk (P), and Alachua Group B..............................25 4-5 Participant response to choice related topics for environmental benefits for Alachua (A), Duval (D), Hillsborough (H), Orange (O), Polk (P), and Alachua Group B....................................................................................................................27 4-6 Support and willingness to pay additional dollars for production of clean energy for Alachua (A), Duval (D), Hillsborough (H), Orange (O), Polk (P), and Alachua Group B....................................................................................................................30 4-7 Knowledge of local utility energy production, satisfaction of energy conservation efforts, and willingness to pay higher cost for environmental benefits for Alachua (A), Duval (D), Hillsborough (H), Orange (O), Polk (P), and Alachua Group B....32 4-8 Summary of nonsignificant t-tests of Independent samples for a comparison of the means of Group A and Group B Alachua County homeowners on knowledge and willingness to pay for safe energy and subscriptions to Green Energy Programs.................................................................................................................35 4-9 Logistic regression coefficients (b) and their standard errors (SE) and significance for demographic variables Education, Gender, Ethnicity, Age, and Income in predicting responses to survey questions ................................................................37 F-1 Heard of global warming..........................................................................................49 F-2 Heard of biomass......................................................................................................50 vii

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F-3 Heard of Co-firing....................................................................................................51 F-4 Aware if local utility company has green energy program......................................52 F-5 Subscribe to a Green Energy Program.....................................................................53 F-6 Willing to pay more for environmentally safe energy.............................................54 viii

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LIST OF FIGURES Figure page 2-1 A Model of Stages in the Innovation-Decision Process.............................................6 2-2 Distinguishing characteristics of interpersonal and mass media channels.................8 A-1 Environmental values and awareness of Florida residents.......................................44 B-1 Initial cover letter.....................................................................................................45 C-1 Follow-up cover letter..............................................................................................46 D-1 Return addressed stamped envelope........................................................................47 E-1 GRU Brochure: Deerhaven generating station neighbors with nature.....................48 ix

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Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science ASSESSING AWARENESS OF FLORIDA HOMEOWNERS ABOUT THE USE OF BIOMASS FOR ELECTRICITY PRODUCTION By MARK D. ADAMS December 2003 Chair: Donald L. Rockwood Major Department: Forest Resources and Conservation This research had two goals: 1) to measure a portion of Florida homeowners awareness of biomass and its potential for use in co-firing; and 2) to assess a sample of Florida homeowners awareness opinions, and preferences with respect to environmental alternatives, which ranged from energy production and conservation to willingness to pay for technologies that could produce cleaner energy. A survey was developed and mailed in March 2003 to 150 residents in five Florida counties: Alachua, Hillsborough, Duval, Orange, and Polk. Alachua was considered a treatment county because in May 2003 an additional 150 residents were mailed the survey and an energy production brochure provided by Gainesville Regional Utilities (GRU), a local utility provider for the residents of Gainesville, Florida. Individuals who may have owned property in the target counties, but were not living there were excluded. Survey participants were asked questions relating to their homes, lifestyle, environmental views, and demographical information Although 94.1% of participants had heard of x

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global warming, 55.7% had not heard of biomass, and 68.1% had not heard of co-firing. Furthermore, while the awareness of biomass and co-firing was low, more than half of the respondents indicated willingness to pay at least a $5 to $20 rate increase for technology that would produce cleaner energy, which can reduce global warming. There was a higher response rate from males than females in this research. Programs that promote and support the production of energy using yard wastes, agricultural, and forest timber-related products from various tree species are known as Green Energy Programs. These programs, which can be provided by utility companies to promote and create bioenergy for consumers, can be useful, particularly since this study indicates respondents willingness to pay higher premiums for bioenergy. However, despite this willingness, 59.7% of respondents were either not aware or unsure about subscribing to Green Energy Programs, and 52.8% were unaware if their local utility company provided Green Energy Programs. Similar to the high percentages of participants unawareness of biomass and co-firing, the high percentages of participants who are either not aware or unsure about subscribing to Green Energy Programs also suggest a need for utility companies to educate their consumers about the advantages and benefits of Green Energy Programs. Utility companies that produce electricity from Green Energy can benefit from fewer pollutants and as a result, they are less likely to pay governmental fines for environmental pollution. To promote awareness of alternative energy methods, the public must be educated about the advantages of Green Energy xi

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CHAPTER 1 INTRODUCTION The production of energy is a major global concern. Because of the population growth of many nations, the worlds crude petroleum resource will not be enough to produce energy for future generations. Furthermore, the high price of oil is linked to its growing demand and short supply, and since the global oil production is expected to decline within 5 years, alternative energy production methods will become necessary (McQueen 2000). Fossil fuels, such as oil and coal, are primarily used for energy production. For example, 56% of the United States electricity, as well as large portions of the worlds electricity, is generated by coal (Tillman 2000). Although coal has been used as a source of energy, the limited and declining supply of oil is a concern. While oil is a component used for energy production, coal is still the primary source of energy, but producing energy from coal has negative environmental effects. For instance, pollution and global warming are directly related to burning coal. Even though the accumulation of CO2 can cause global warming, biofuels can be used to balance the industrial and other CO2 emissions (Brown et al. 2000). Since fossil fuels, such as oil and coal, have long been relied on for energy production and because of a reduced supply and harmful by-products, alternative methods of energy production must be implemented. The growing demand for energy is a major concern of the United States. Currently, some United States regions are facing an energy crisis. Since energy is produced mainly from nonrenewable fossil fuels, the energy-shortage problem will 1

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2 continue to grow. In addition to this, pollutants are emitted from utility plants that use fossil fuels to produce energy. These emissions create harmful environmental effects, such as acid rain and global warming. Therefore, alternative methods of energy production must be used to reduce these negative consequences and to sustain our future. Since biomass is a renewable resource that can be co-fired to produce energy, it could be the ideal choice. For example, wood-cellulosic plants and their residues can be used to generate energy. (Keith 2000). Furthermore fast growing energy crops, known as biomass (Elliot 2000) can also be used to produce energy. Because of fragile ecosystems such as The Everglades, Floridians are concerned that pollutants that may cause acid rain can be damaging to these sensitive environments. To address these concerns, Florida agencies such as the Southwest Florida Water Management District and the Florida Department of Environmental Protection rely upon landscape models that use biogeochemical mechanisms that are site-specific and mass-balanced to control energy and material flows; these mechanisms can also predict changes in carbon and phosphorus structures of sensitive areas such as the soil, water, and plant communities of the (Sklar et al. 2001). Since the production of energy relies upon a nonrenewable source, which creates negative environmental consequences, the research objectives of this study were to assess the awareness of Florida homeowners about using biomass as a viable alternative for energy production, and to evaluate Florida homeowners awareness, opinions, and attitudes toward bioenergy and their willingness to pay for cleaner forms of energy production from biomass.

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CHAPTER 2 LITERATURE REVIEW This literature review covers social and scientific research pertinent to survey questions included in the survey design and the statistical procedures used to summarize this research. Alternative Energy Overview Energy production is a critical problem that must be solved if future generations are to be sustained. Environmentalists believe that the current method of energy production should be replaced with a method that does not add to global warming. In order to produce a clean, continued source of energy, the use of biomass is gaining support because it provides a source of fuel, which has a higher degradability rate than petroleum products (Speidel 2000). In fact, US governmental agencies are interested in the possibility of biomass being used to produce energy. For example, the US Department of Energy (DOE) and the National Renewable Energy Laboratory (NREL) support industries that are attempting to develop the economic and commercial prospects of biomass (Mielenz et al. 1996). The most promising forms of biomass are energy crops, which can be used by power plants that use wood as a primary source of (Mcllveen-Wright et al. 2001). Although wood is the desired form of biomass, which produces energy, leaves and litter fall can are also useful (Guo and Sims 1999a). Soil is also an equally significant factor since it can affect the amount of litter fall as well as the root distribution of trees and plant (Garg and Jain 1992). Various species of Eucalyptus can also be used to produce 3

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4 energy; however, since these are nonnative species, researchers believe that heat loss from trees can be related to the environment (Criddle et al. 1996). As previously mentioned, another immediate benefit from the utilization of biomass is its ability to reduce the amount of CO2 emissions into the atmosphere, as a result, reducing global warming (Classen et al. 1999). If biomass has a promising role to play in sustaining our future, it is evident that a balancing act between caring for the environment and ensuring that native forests must occur by ensuring that the resources of smaller land areas will not be exhausted by relying primarily upon them to produce high quantities of wood (Campinhos 1999). Not only does biomass have the potential to produce energy, but it can also be used to help reclaim environmentally disturbed lands. Using biomass resources has certain environmental benefits; however, unless consumers are ready to pay for higher costs of energy from renewable resources, energy produced from renewable resources will have to compete with other sources of energy production (Rahmani et al. 2003). Therefore, the technology costs must be considered for the development of agricultural equipment that can decease production costs and maximize the potential for high crop yields (Central Pennsylvania Energy Center 1990). Role of Energy Producers Utility companies are beginning to realize that the production of energy can be achieved by using a process that combines wood and coal; this process is known as co-firing. Similar to litter fall, some studies show that wood harvested from coppicing is ideal for use in the gasification plants of utility companies (Warren et al. 1995). Local farmers growing short rotation woody crops may assist utility companies in producing energy by using the wood chips harvested from coppiced trees. The chips would pass

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5 through on-site farm equipment, which have gasified engines or electric generators that are connected to the National Grid (Sells and Audsley 1991). Another useful biomass product is perhaps the most unlikely vegetables. Corn has the potential for producing many different forms of food; however, it can be used to produce energy as well. For example, corn stover can be combined with coal in coal-burning steam electric plants. Furthermore, another positive benefit of corn is that it emits low rates of sulfur, and it does not produce harmful by-products, such as CO2carbon dioxide (Hitzhusen and Abdallah 1980). An Iowa agricultural program model estimating crop emissions found that crop residues replace the current BTUs produced from electric plants (English et al. 1981). The ownership of the utility plant is significant since it determines which types of federal laws that each plant must adhere to when producing energy (Hill and Hadley 1995). Finally, as an indirect product of biomass, anaerobic materials, such as manure can produce electricity that can be sold to public utilities (Bravo-Ureta and McMahon 1983). Since bioenergy is a relatively new type of technology, it is important to understand the process by which it might become the standard method of energy production; to do this, a discussion of The Diffusion of Innovation theory is necessary. When innovations are first developed and introduced into a community or social system, the innovation goes through or is communicated through certain channels over time among members of a social system (Rogers 1995). Since communication is a happens by individuals creating and sharing information with one another in order to reach a mutual understanding (Rogers 1995), communication becomes vital for an innovation which is perceived as new by individuals or other units of adoption (Rogers 1995).

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6 Communication, however, about new ideas or technologies does not only occur between the developers of new inventions or technologies, it can also occur in stages among the intended recipients of the new innovation (Figure 2-1). Communication Channels I. Knowledge II. Persuasion III. Decision IV. Implementation V. Confirmation 1. Adoption Continued Adoption Later Adoption Characteristics of Perceived Characteristics 2. Rejection Discontinuance The decisionof the Innovation Continued Rejection Making Unit 1. Relative advantage 1. Socio-economic 2. Compatibility characteristics 3. Complexity 2. Personality 4. Trialability variables 5. Observability 3. Communication behavior Figure 2-1. A Model of Stages in the Innovation-Decision Process. (Rogers, E.M. 1995. Diffusion of Innovation 3rd Edition. The Free Press, Macmillan Publishing Company. New York, New York. p.114) The five stages that an innovation undergoes are important since they can provide bioenergy researchers and proponents with useful details about how to introduce co-firing to potential subscribes, and how to stimulate awareness and demand for this type of alternative innovation. There are five stages which an innovation undergoes before it is accepted into a social system: 1. Knowledge occurs when an individual (or other decision-making unit) is exposed to the innovations existence and gains some understanding of how it functions. 2. Persuasion occurs when an individual (or other decision-making unit) forms a favorable or unfavorable attitude toward the innovation.

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7 3. Decision occurs when an individual (or other decision-making unit) engages in activities that lead to a choice to adopt or reject the innovation. 4. Implementation occurs when an individual (or other decision-making unit) puts an innovation to use. 5. Confirmation occurs when an individual (or other decision-making unit) seeks reinforcement of an innovation-decision already made, but he or she may reverse this previous decision if exposed to conflicting messages about the innovation (Rogers 1995). Since the decision to adopt or reject a new type of technology occurs at stage three, which is the Decision stage, it is a critical stage because people must be provided with enough information about the benefits of an innovation in order for it to be adopted. Change agents are individuals responsible for providing this information to a group of people or into a social setting. Although the adoption of technology can occur when customers understand and value technologies according to their ability to reduce the cost of a solution to an existing problem or their ability to create new possibilities and solutions (Chesbrough 2003), change agents must realize the needs and problems of their clients since a change agent can selectively transmit information that is relevant (Rogers 1995); therefore, change agents may be suitable choices for educating the public about the potential benefits of biomass co-firing. Change agents also can facilitate by relying upon media related methods, such as interpersonal channels that involve a face-to-face exchange between two or more individuals. These channels have greater effectiveness in the face of resistance or apathy on the part of the communicatee. However, interpersonal channels are useful since they provide two essential functions: 1. Allow a two-way exchange of ideas. The receiver may secure clarification or additional information about the innovation from the source individual. This characteristic of interpersonal channels sometimes allows them to overcome the social and psychological barriers of selective exposure, perception, and retention.

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8 2. Persuade receiving individuals to form or change strongly held attitudes (Rogers and Shoemaker 1971). The attributes of interpersonal channels depict the flow of communication between social channels (Figure 2-2). Characteristics Interpersonal Mass Media Channels Channels Message flow Tends to be two-way Tends to be one-way Communication context Face-to-face Interposed Amount of feedback available High Low Ability to overcome selectivity High Low Speed to large audiences Relatively slow Relatively rapid Possible effect Attitude formation Knowledge change and change Figure 2-2. Distinguishing characteristics of interpersonal and mass media channels.(Rogers, E.M. and Shoemaker, F.F. 1971 Communication of innovations: a cross-cultural approach. 2nd Edition. The Free Press. New York, New York p.46) In order for biomass to become a useful and economically feasible commodity which can be relied upon for energy production, there are at least three main requirements which must be met: 1) the availability of land for energy crops to be grown, 2) the intended crops to be grown must be suitable for use in a co-firing process, 3) and there must be ideal climates that will allow different types of biomass species to grow. With its large area and year-round warm weather climate, Florida is an ideal place to grow energy crops. For example, Short Rotation Woody Crops can be grown from thousands of acres of land [which can be used as energy feedstock] and other biomass crops in Florida. Furthermore, central Florida is an ideal place that can produce Short Rotation Woody Crops since there are large areas of flatwoods, which are typically flat and poorly drained, and reclaimed phosphate mined lands. These types of terrain can yield soil types that are capable of supporting biomass production (Stricker et al. 2000).

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9 Florida utility companies, which may choose to produce energy from biomass must have an adequate number of biomass crops, which have different harvesting periods. Furthermore, these crops must be grown and harvested throughout the year and be able to provide a consistent flow of feedstock; these are key elements in a successful biomass-to-energy system (Stricker et al. 2000). If people perceive biomass as being a form of technology that will provide them with benefits that are not limited to the environment, then they may be more willing to pay for bioenergy. Therefore, if consumers of biomass-produced electricity are the final beneficiaries of bioenergy, then the first individuals to benefit from biomass production are landowners. The willingness to grow biomass was measured in a previous survey that was administered to landowners in Central Florida (Rahmani et al. 1996). Survey results indicated that, even though most of the landowners were unaware about biomass crops, they were willing to provide more than 5000ha (12000/A) to grow these crops if there was a guarantee that they could be assured net returns of $149 per ha ($60/A). These net returns are valuable since they represent the return to land and management after direct and indirect production costs (Stricker et al. 1997). Another issue that many Florida landowners who were willing to grow energy crops must examine is which crops should be grown. Because of Floridas warm and humid climate there are a variety of energy feedstock crops, which can be grown and harvested, furthermore, most of these biomass crops produce higher yields and do not contribute to environmental problems. Results from 20 year studies demonstrate that elephant grass, sugarcane, Leucaena, along with various Eucalyptus species, and slash pine, which produce higher yield potential than

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10 other biomass crops in the area (Stricker et al. 2000). Table 2-1 shows yield rates of these biomass crops. Table 2-1. Biomass crop yields in Florida Biomass crops Dry Mg/ha/yr Dry ton/A/yr Sugarcane 30-49 14-22 Elephant grass 40 18 Leucaena 35 16 Eucalyptus species 29-40 13-18 Slash pine 21 9 ____________________________________________________________________ (Stricker, J. A. Rockwood, D.L., Segrest, S.A., Alker, G.R. Prine, G.M., Carter, Douglas, R.C. 2000. Short rotation woody crops for Florida. University of Florida Polk County Extension Service and University of Florida School of Forest Resources and Conservation, The Common Purpose Institute, University of Florida Agronomy Department) The acceptance of biomass is determined by the differences in cost rates reductions for renewable energy technologies and conventional power plants which, in turn, will affect the relative cost of generated electricity (Neij 1997). Utility providers must also be responsive to a variety of different needs since they are met with a variety of challenges and expectations. In California, for example, there is an ongoing debate regarding the ability existing energy production methods and delivery infrastructures to maintain reliable day-to-day operations (Asmus 2002). Therefore, the acceptance of the technology-transfer for using biomass must be determined by effective procedures, practices, and design structures (Brown and Major 1990), particularly since being able to quickly deliver a product to meet consumer demand translates into the concept that accelerated growth is related to innovation that are rapidly produced (Michaels 2000). Media Related Response to Environmental Issues Various media can facilitate the use of biomass for producing energy. For example, the USDA Forest Service and the Northeastern Forest Experiment Station

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11 conducts telephone surveys to obtain the publics opinion for biomass energy production (Wharton 1991). A very successful component has been the Cooperative Extension Service, which recognizes the importance of educating children about energy as it relates to their future (Slack 1983). Furthermore, elementary schools are informed that there is a direct relationship between environmental education along, nutrition, and energy (State Office of Public Instruction, 1979). The National Food Review (NFR) also educates the general public on the usefulness of plants, such as euphorbia and rapeseed which improve health and can be also be used as secondary sources of fuel (Stucker and Stucker 1984). The federal government must further these efforts by developing and maintaining communication programs, which promote public research and development programs for private sectors to use biomass (Hillman and Yancey 1998). For example, the adoption of anaerobic technology as another method of energy production can be examined by analyzing an agencys budget for research and development of alternative energy technology (Anderson and Altobello 1982). Therefore, as previously mentioned, the diffusion and adoption of technologies that promote alternative methods of energy production is a fast-growing joint effort between classrooms and extension agents (Francis and Madden 1993). Environmental Benefits Approach Because of global warming and other important environmental issues, consumers must be willing to pay more for energy produced from co-firing methods. To raise consumer awareness, there must be an identification of goods and services that can be derived from forest resources and timber related products (Mulloy and Ottisch 2000).

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12 Most Midwestern states have taken progressive steps to reduce harmful pollutants by passing environmental laws or regulations. However, this measure is difficult for some state legislatures to achieve. For example, difficulty in creating and enforcing regulatory policies may be due to a lack of the full value of these goods and the decision itself of how best to utilize them, particularly since lawmakers have difficulty in incorporating the value of forest products into policy decisions (Buttond 2000). Lawmakers must further weigh the costs incurred by government when determining if the policies that are passed will benefit the public (Stoneman 2002). Even if most people are aware of the immediate benefits of forests, such as recreation, wildlife areas, and timber, they may think that opportunity costs associated with biomass are astronomically high because they have little knowledge of the benefits which can be gained from biomass. In fact, individuals may believe that since the potential gain of biomass is high, the use of biomass may not be economically feasible. However, this mindset can be overcome by exploring the relationship of biomass with other familiar agricultural products and services, such as grazing and hunting (Gluck 2000). If these apprehensions cannot be overcome in such a manner, then people must understand the risks and benefits of biomass to better choose among it potential success or failure (Rogers 1998). But even making minimum cost choices can be beneficial particularly when there are no environmental constraints. In fact, many renewable technologies are able to become profitable demand devices (Cosmi et al. 2002) since energy can be produced from biomass by a variety of methods (McKendry 2002). Overview of Survey Literature As with any type of data collection survey procedure, the size of any survey research must be considered and well planned before any research can begin. This advice

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13 is important since it makes prospective researchers consider key items such as the availability of resources, such as time, money, and available expert assistance (Newman and McNeil 1998). This warning becomes particularly crucial for assessing the fast growing global social topic of consumer demand in relation to environmental issues and considerations. To assess consumer demand and awareness of biomass and co-firing, surveys have been conducted throughout parts of the US and various other countries. For example, Norwegian officials determined that the type of energy production is linked to socioeconomic information. In Norway, choice probability is impacted by income. For instance, families with higher income generally use electric heating instead of coal and wood (Vaage 2000). Although income may have an impact on energy production in Norway, there may be other determinant factors of how energy is produced within the other developed countries. In the US, for instance, fossil fuel dependency is from environmental concern rather than economic status (Bourdaire and Ellis 2000). Furthermore, The willingness to pay higher premiums for bioenergy is gaining support on a global scale. In Finland, for example, where bioenergy is the primary source of fuel, if consumers willingness to pay can be attributed to the annual growth of biomass, then an adequate amount of biomass quantities can be produced according to the scale and size of power plants in Finland (Markku et al. 2003). Since consumer perception and awareness greatly influence whether or not a product or a production method will be accepted, it is useful to conduct studies that measure perception and awareness. One such study was performed using a quasi-experimental design to assess the perception of environmental risks associated with some

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14 environmental company sites. The study determined that stimuli and personality variables are related to risk perception, and certain objects or stimuli affect risk perception (Weber 2001). Given that bioenergy remains a relatively new method of energy production, researchers caution that the designs and field experiments must be reliable not only to test the effectiveness of the innovation, but to also maintain internal and external validity. Researchers further state it is not adequate to test for the effects of the presence or absence of the experimental treatment on the dependent variable; instead, the evaluation design must also test the effectiveness of the intervention on the dependent variable (Caro and Gottlieb 2001). An important dependent variable that is most frequently measured in surveys is willingness to pay. While survey research can be used in conjunction with experimental and aggregate data to predict a specific outcome, some researchers may feel that this collection approach for survey research can be impractical. To combat this problem, researchers typically rely upon secondary analysis, which is typically previously collected survey data by someone else (Weisberg et al. 1989). This distinction provides the researcher with a clearer choice to a cost-benefit analysis. As a result, researchers are made aware that benefit-cost analysis can be used not only to provide specific answers to difficult questions, but also for stimulating and organizing thinking questions, such as: 1) How much money should be spent on a particular study and 2) How to use the results (Pearson and Boruch 1980)? When conducting survey research, researchers must select respondents who are likely to remain within the sample area. To accomplish this, researchers must be aware

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15 of respondents choice of living preferences. For example, Audirac and Smith noted a previous study, which surveyed 630 Florida residents, indicated that the location and home type were reasons why people decided to move; this decision to relocate ultimately may affect survey response results since people who lived in single-family homes were less likely to relocate. Furthermore, individuals who considered moving preferred less centralized & dense locations (Audirac and Smith 1992).

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CHAPTER 3 METHODS Participant responses were compiled from a 55-question questionnaire (Appendix A). The 55 substantive variables measured in this research were categorized into six subsets: 1) Home and Lifestyle Activity, 2) Home Cooling and Heating, 3) Water Heaters, Pools, and Spas, 4) Home and Kitchen Appliances, 5) Environmental Awareness, and 6) Demographics. The questions developed were designed to yield several types of responses measured by different response scales. For example, survey responses included 5-point Likert scales, such as not at all to always, not satisfied to extremely satisfied, not concerned to extremely concerned, and not willing to extremely willing. Demographics for all survey counties included information such as gender, income, ethnicity, age, and educational levels. To ensure that the sample was representative of Florida homeowners, county selection was based upon population size, demographics, urban and rural differences, accessibility, coverage area of utility service providers, and projected growth rates. A randomizer program randomly selected 150 residents from CD listings provided by county property appraisers. The selected participants were current residents of the county. No pilot tests were performed because of limitations relating to expense and length of survey period. Participants were surveyed over a period of five months beginning in March 2003. The survey was mailed to five Florida counties: Alachua, Hillsborough, Duval, Orange, and Polk. County selections were based upon projected growth rates, 16

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17 geographical access, and a potentially high survey response rate. Participants from each county received a packet, which included a survey, cover letter(s) (Appendices B & C), and a return addressed stamped envelope (Appendix D). The cover letter explained participants rights as mandated by the University of Floridas Institutional Review Board. The letter also informed participants that their identity would remain anonymous, that there would be no compensation, and also explained the general purpose of the survey. On the last page of the survey, participants were encouraged to write additional responses about the survey, or survey questions. A quasi-experimental design was used. The 55 question survey did not include pictures, diagrams, or information that might have affected participant response; however, the GRU brochure Deerhaven Generating Station Neighbors with Nature (Appendix E) included in a follow-up survey mailing in May 2003 did have pictures and facts relating to GRUs current method of energy production. The GRU brochure was mailed, along with a survey, to 150 additional residents in Alachua County known as Test Alachua, or Group B. The purpose of this brochure was to compare the difference in responses between Group A and Group B about questions, such as willingness to pay more for safe energy production, awareness of GRUs conservation programs, and knowledge of GRUs energy production methods. The brochure was only distributed in Alachua County because residents of the other target counties were not GRU customers. Because participants were asked to select answers to questions and to provide any written responses, the data were both objective and subjective. As a label was attached to each survey for county identification purposes, returned survey responses were coded and entered using Statistical Package For The Social Sciences (SPSS). Since SPSS generates

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18 data output primarily from numerical responses, the survey was designed to satisfy this requirement. County identification was achieved by assigning numbers to each county. County: Alachua (1), Test Alachua (11), Hillsborough (2), Duval (3), Orange (4), and Polk (5). Records of survey return dates were also recorded. A master file for each county location included information about participants name, address, city, and county. The pre-assigned identification labels were circled using a black marker if the survey contained any type of participant written response. The responses were generally found on the last page of the survey since there was a section provided for comments; however, some participants wrote comments next to survey questions. Although participants were informed that their anonymity would be maintained, some surveys were returned with no identification label. As a result, there were five surveys that could not be identified by one of the five counties. Unidentified surveys were not used for individual county data reporting purposes; however, they were used to provide information for other survey categories, such as demographical information. While planning and preparation of the survey questions were essential to capture the desired response, there were several instances where participants provided alternative answers to the survey response choices. For example, on some yes / no questions, participants wrote out not sure as their answer. To avoid conducting biased research, separate response categories for these answers were added to the data output analysis function(s), and data analyses were performed with the alternative response represented. Questions that were not answered generated missing totals for that variable, which SPSS identified as missing system(s). There were a variety of survey results generated from the data. A key focus of this research relied upon descriptive data, which is demonstrated

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19 primarily through various frequency distributions. In addition to this, t-tests, logistic regressions, and cross tabulations that produced contingency tables were also conducted. All variances were assumed to be equal and not equal, and 95% confidence intervals were used to report F values, and significance levels were determined using an alpha level of 0.05. Comparisons between Group A and Group B of Alachua County were conducted for seven questions (Table 4-9). Each group was drawn from 150 randomly selected individuals who were assumed to share similar demographical characteristics since they were all selected from Alachua County. As a treatment or control group, Group B was given the GRU brochure Deerhaven Generating Station Neighbors with Nature to compare their response to individuals from Group A. A determination for Chi-Square values was also conducted to measure the observed and expected frequencies of variables. The test for Chi-Square significance and the measure of association between variables is based on an Alpha-Level of 0.05 with degrees of freedom calculated as: df = (r-1)(c-1)

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CHAPTER 4 RESULTS AND DISCUSSIONS For the counties surveyed, responses were received from the following individual cities and locales: Alachua County Gainesville, High Springs, Newberry, Archer, Alachua, Hawthorne, and Micanopy, Hillsborough County Tampa, Odessa, and Lutz, Duval County Jacksonville, Baldwin, Maxville, and Orange Park, Orange County Tangerine, Zellwood, Orlando, Apopka, and Plymouth, Polk County Lakeland, Bartow, Haines City, Frostproof, Fort Meade, and Lake Wales. Demographic information was a key subset because the collected results provided statistical information relating to frequency distribution, t-test comparisons, and logistic regressions. Overall County Responses Selected questions analyzed participants response, awareness levels, and overall support of bioenergy. The items in Appendix N present the overall county results for the remaining survey questions that addressed consumer usage of energy and electricity as it relates to the home environment, and general questions relating to home and lifestyle activity. A total of 278 respondents contributed to this survey, for an overall percentage response rate of 30.9% (Table 4-1). Alachua County had the highest overall number of responses at 109, or 39.2% of all responses, while Orange County had the lowest number of responses with 27 participants contributing 9.7% of survey returns. The 30.9% response rate reflects the predicted percentages of completed and returned surveys that were mailed from a total of 900 surveys to all of the five surveyed 20

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21 counties. There was no danger of participant fatigue as sampled participants were only sent the survey twice, and other survey participants could have been selected from the same sample. Alachua Countys 36.3% response rate may be attributed to Alachua County residents being used to receiving previous surveys conducted by the University of Florida. As a result, future surveys conducted on Alachua County residents by University of Florida researchers may continue to report higher response rates than the same type of research conducted on residents from other counties and by other researchers. Table 4-1. Number of responses and percentage of all responses by county (150 surveyed individuals per county). County Number of Responses Percentage of all Responses Alachua 66 23.7 Duval 43 15.5 Hillsborough 50 18.0 Orange 27 9.7 Polk 44 15.8 Test Alachua 43 15.5 Unknown 5 1.8 Total 278 100.0 Respondent Demographics The overall demographic data (Table 4-2) indicated that 81.7 % of the respondents were Caucasians, and that 49.3 % of the respondents were male, 47.1% female and .7% couples. Participants earning incomes of $50,000 or more had the highest response rate of 47.5%, and 51-65 was the largest age group. Some participants chose not to provide some personal information. These particular instances were categorized as missing (Table 4-3). Alachua County had the highest missing percentage, 61.3%, of participants who chose not to answer

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22 demographical questions, and Duval County had the lowest missing percentage, 11.6% of participant nonresponse for demographical questions. Table 4-2. Overall Response and Respondent Demographics for Alachua (A), Duval (D), Hillsborough (H), Orange, Polk (P) Counties and Alachua Group B Demographic County A D H O P No. % No. % No. % No. % No % Overall No % Gender Male Female Couple (Female / Male) (A) 32 48.5 (B) 18 41.9 (A) 28 42.4 (B) 24 55.8 (A) 2 3.1 23 53.5 20 46.5 24 48.0 24 48.0 10 37.0 17 63.0 29 65.9 14 31.8 136 51.3 127 47.9 2 0.7 Income Less than $19k $20k $30k $30k $40k $40k $50k $50k or more (A) 4 6.1 (B) 3 7.0 (A) 2 3.0 (B) 5 11.6 (A) 5 7.6 (B) 6 14.0 (A) 4 6.1 (B) 4 9.3 (A) 41 62.1 (B) 19 44.2 4 9.3 5 11.6 7 16.3 9 20.9 13 30.2 0 0.0 5 10.0 1 2.0 9 18.0 33 66.0 3 11.1 9 33.3 4 14.8 1 3.7 6 22.2 3 8.3 6 6.7 6 16.7 3 8.3 18 50.0 17 7.1 32 13.4 29 12.2 30 12.6 130 54.6 Ethnicity Caucasian African American Hispanic Native American Pacific Islander Asian American Other (A) 52 78.8 (B) 36 83.7 (A) 2 3.1 (B) 3 7.0 (A) 1 1.5 (B) 0 0.0 (A) 2 3.1 (B) 0 0.0 (A) 0 0.0 (B) 0 0.0 (A) 1 1.5 (B) 1 2.3 (A) 1 1.5 (B) 1 2.3 34 79.1 3 7.0 0 0.0 3 7.0 0 0.0 0 0.0 3 7.0 43 86.2 1 2.0 3 6.0 0 0.0 0 0.0 1 2.0 1 2.0 17 63.0 1 3.7 1 3.7 5 18.5 0 0.0 1 3.7 0 0.0 41 93.2 1 2.3 1 2.3 1 2.3 0 0.0 0 0.0 0 0.0 223 85.4 11 4.2 6 2.3 11 4.2 0 0.0 4 1.5 6 2.3

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23 Table 4-2 Continued. Demographic County A D H O P No. % No. % No. % No. % No % Overall No % Age 26-34 35-50 51-65 66 older (A) 1 1.5 (B) 1 2.3 (A) 18 27.3 (B) 17 39.5 (A) 22 33.3 (B) 14 32.6 (A) 21 31.8 (B) 10 23.3 1 2.3 8 18.6 22 51.2 12 27.9 8 16.0 22 44.0 14 28.0 5 10.0 1 3.7 7 25.9 5 18.5 13 48.1 0 0.0 12 27.3 13 29.5 19 43.2 12 4.5 84 31.6 90 33.8 80 30.1 Table 4-3. Numbers and percentages of missing demographical information for Alachua (A), Duval (D), Hillsborough (H), Orange (O), Polk (P) and Alachua Group B Demographic County A D H O P No. % No. % No. % No. % No % Overall No % Gender Missing Total (A) 4 6.1 (B) 1 2.3 5 8.4 0 0.0 0 0.0 2 4.0 2 4.0 0 0.0 0 0.0 1 2.3 1 2.3 8 14.7 Income Missing Total (A) 10 15.2 (B) 6 14.0 16 29.2 5 11.6 5 11.6 2 4.0 2 4.0 4 14.8 4 14.8 8 18.2 8 18.2 35 77.8 Ethnicity Missing Total (A) 7 10.6 (B) 2 4.7 9 15.3 0 0.0 0 0.0 1 2.0 1 2.0 2 7.4 2 7.4 0 0.0 0 0.0 12 24.7 Age Missing Total (A) 4 6.1 (B) 1 2.3 5 8.4 0 0.0 0 0.0 1 2.0 1 2.0 1 3.7 1 3.7 0 0.0 0 0.0 7 14.1

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24 While there may be a need for bioenergy researchers to educate and stimulate the awareness of respondents who represented the demographics with low response rates, researchers must also be aware that since participants can be randomly selected, there may be no specific demographical group targeted in some research studies. As a result, the response rate of individuals from different demographics can vary. Responses to Environmental Questions There were several environmental questions asked of participants: 1) Have you ever heard of the term Global Warming, 2) Have you ever heard of the term Biomass, and 3) Have you ever heard of the term Co-firing (Table 4-4). While these three questions served as introductions to other surveyed variables, they indicated participants awareness level of terminology that relates to negative environmental impacts caused by pollution and the participants awareness of remedies to reduce the causes of these harmful impacts. Although 94.1 % of respondents had heard of global warming, more than half had not heard of biomass or co-firing, 55.7% and 68.1%, respectively. These low awareness rates may indicate that most Floridians are unaware of the causes of negative environmental impacts, or the potential solutions to this particular problem. For example, Duval and Orange Counties had the highest level of participant unawareness of biomass and co-firing; 65.1% of Duval County respondents had not heard of biomass or co firing, and 81.5% of Orange County respondents had not heard of co-firing. Furthermore, the percentages for the unawareness level for biomass and co-firing for Alachua, Hillsborough, and Polk Counties were also more than 50%; however, residents of Alachua County were more familiar with biomass than co-firing.

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25 Table 4-4. Participant awareness of environmental terms for Alachua (A), Duval (D), Hillsborough (H), Orange (O), Polk (P), and Alachua Group B Question-Response County A D H O P No. % No. % No. % No. % No % Overall No % Heard of Global Warming Yes No Not Sure Missing Total (A) 64 97.0 (B) 42 97.7 (A) 0 0.0 (B) 1 2.3 (A) 0 0.0 (B) 0 0.0 (A) 2 3.0 (B) 0 0.0 (A) 66 100.0 (B) 43 100.0 41 95.3 1 2.3 0 0.0 1 2.3 43 99.9 47 94.0 2 4.0 0 0.0 1 2.0 50 100.0 23 85.2 1 3.7 1 3.7 2 7.4 27 100.0 40 90.9 2 4.5 0 0.0 2 4.5 44 99.9 257 94.1 7 2.6 1 .4 8 2.9 273 100.0 Heard of Biomass Yes No Missing Total (A) 35 3.0 (B) 23 53.5 (A) 30 45.5 (B) 19 44.2 (A) 1 1.5 (B) 1 2.3 (A) 66 100.0 (B) 43 100.0 14 32.6 28 65.1 1 2.3 43 100.0 18 36.0 31 62.0 1 2.0 50 100.0 8 29.6 16 59.3 3 11.1 27 100.0 13 29.5 28 63.6 3 6.8 44 99.9 111 40.7 152 55.7 10 3.7 273 100.1 Heard of Co-firing Yes No Not Sure Missing Total (A) 11 16.7 (B) 10 23.3 (A) 43 65.2 (B) 29 67.4 (A) 8 12.1 (B) 4 9.3 (A) 4 6.1 (B) 0 0.0 (A) 66 100.1 (B) 43 100.0 9 20.9 28 65.1 6 14.0 0 0.0 43 100.0 8 16.0 35 70.0 5 10.0 2 4.0 50 100.0 2 7.4 22 81.5 1 3.7 2 7.4 27 100.0 10 22.7 29 65.9 2 4.5 3 6.8 44 99.9 50 18.3 186 68.1 26 9.5 11 4.0 273 99.9

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26 Proponents and researchers of bioenergy may derive most of their support for the passage of environmental laws from individuals between the ages of 35-50, 30.2% of the sampled population, and between the ages of 51-65 or 33.5%. These age groups are significant since people within these age groups are more likely to vote, attend community public meetings, and work within legislatures for the passage of laws. Since the type of energy production can be linked to income, as suggested by Norway officials, people with higher incomes are more in favor of bioenergy than those with lower incomes. As a result, the probability of bioenergy being the preferred method of energy production increases with income. Other environmental questions relating to Green Energy Programs were different from those that measured participant awareness of environmental terms because these questions addressed consumer choice and behavior for the potential gain of environmental benefits (Table 4-5). Green Energy Programs are vital services that can be offered to consumers of electricity by their local utility company. Utility companies may be more willing to provide Green Energy Programs if there is high consumer demand, and if consumers are willing to pay higher premiums for bioenergy. Green Energy Programs benefit the environment because they rely upon alternative methods of energy production rather than on current conventional methods, which emit harmful levels of pollutants into the Earths atmosphere, thereby causing global warming. The results of Green Energy Programs are similar to those of biomass and co-firing because a significant amount, 52.8%, of participants, who are either unaware if their local utility company has a Green Energy

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27 Program. Furthermore, 59.7% of participants are unsure if they would subscribe to Green Energy Programs if their local utility company provided one. Table 4-5. Participant response to choice related topics for environmental benefits for Alachua (A), Duval (D), Hillsborough (H), Orange (O), Polk (P), and Alachua Group B Question-Response County A D H O P No. % No. % No. % No. % No % Overall No % Aware if Utility has Green Energy Program Yes No Not Sure Yes / Not Sure Missing Total (A) 18 27.3 (B) 13 30.2 (A) 18 27.3 (B) 7 16.3 (A) 29 43.9 (B) 22 51.2 (A) 0 0.0 (B) 1 2.3 (A) 1 1.5 (B) 0 0.0 (A) 66 100.0 (B) 43 100.0 2 4.7 10 23.3 29 67.4 1 2.3 1 2.3 43 100.0 8 16.0 12 24.0 29 58.0 0 0.0 1 2.0 50 100.0 3 11.1 8 29.6 14 51.9 0 0.0 2 7.4 27 100.0 12 27.3 9 20.5 21 47.7 0 0.0 2 4.5 44 100.0 56 20.5 64 23.4 144 52.8 2 .7 7 2.6 273 100.0 Subscribes to Green Energy Program Yes No Not Sure Missing Total (A) 2 3.0 (B) 2 4.7 (A) 37 56.1 (B) 17 39.5 (A) 13 19.7 (B) 13 30.2 (A) 14 21.2 (B) 11 25.6 (A) 66 100.0 (B) 43 100.0 2 4.7 13 30.2 9 20.9 19 44.2 43 100.0 3 6.0 17 34.0 18 36.0 12 24.0 50 100.0 2 7.4 6 22.2 10 37.0 9 33.3 27 99.9 5 11.4 18 40.9 6 13.6 15 34.1 44 100.0 16 5.9 108 39.6 69 25.2 80 29.3 273 100.0

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28 Table 4-5 Continued Would subscribe to Green Energy Program Yes No Not Sure Missing Total (A) 16 24.2 (B) 13 30.2 (A) 3 4.5 (B) 1 2.3 (A) 41 62.1 (B) 27 62.8 (A) 6 9.1 (B) 2 4.7 (A) 66 100.0 (B) 43 100.0 11 25.6 2 4.7 24 55.8 6 14.0 43 100.1 12 24.0 1 2.0 30 60.0 7 14.0 50 100.0 6 22.2 1 3.7 17 63.0 3 11.1 27 100.0 6 13.6 6 13.6 24 54.5 8 18.2 44 99.9 64 23.4 14 5.1 163 59.7 32 11.7 273 99.9 The large amount of skepticism surrounding these types of programs, which may not entirely indicate a high level of unawareness of Green Energy (as later survey results will show), but rather a need for the general public to be educated about what Green Energy Programs are, how Green Energy can be provided, and the benefits of Green Energy. An equally challenging question though is who shall educate bioenergy researchers, or utility companies. Public service messages presenting the benefits of bioenergy can also be useful to educate people of the potential for this kind of technology. Only 5.9% of participants indicated that they currently subscribe to a Green Energy Program. Polk County had the highest overall subscription rate with 11.4%, while Duval County had the lowest, 4.7%. One potential reason why Polk County had the highest percentage of subscribers to Green Energy Programs is because some of its residents may subscribe to utility companies that offer Green Energy and because of Polk Countys geographic characteristics. Compared to the other surveyed counties, Polk

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29 County is a relatively large, rural area with locations where energy crops can be grown for co-firing. Furthermore, because of its size, Polk County has more utility providers than most Florida counties. As a result, utility customers can be provided with more options and opportunities for energy source selections. Although there were high percentages of participants that answered No or Not sure to the questions about the awareness of environmental terminology (Table 4-6), participant support and willingness to pay for bioenergy was relatively high. For example, 39.6% of respondents were somewhat supportive of bioenergy, and 54.9% were willing to pay more for energy production methods that were environmentally safe, and 39.6 % were willing to pay at least an additional $20 for clean energy. Participants were later asked to provide responses relating to their local utility companies. In response to Do you know how your local utility company produces electricity, 60.4% were aware of how their local utility company produced energy, and 21.2% were unsure and 15.8% did not know how energy is produced in their communities (Table 4-7). Local utility providers can raise consumer awareness levels about energy by actively increasing public awareness, establishing the support of the business sector, and verifying the controls over utilities' power trading, and governmental regulation (Gan 2002). Utility companies can increase public awareness of how their energy is produced locally by providing guided tours, public service broadcasts, utilization of county extension agents, and other means of community involvement. Utility companies can benefit from knowing consumers awareness level of energy since consumers who are more aware of energy may be more likely to practice energy

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30 conservation methods, which can reduce the instances of blackouts caused by overloaded power grids While consumer satisfaction with local utility companies efforts to promote energy conservation appears high, there was some differences in level of satisfaction; 39.9% were somewhat satisfied, and 35.9% were satisfied. Participants responses may have been influenced by their current utility bills, or by their own conservation behaviors to reduce their monthly electric bill. Utility companies were not surveyed in their efforts to promote energy conservation, or their energy conservation methods. Table 4-6. Support and willingness to pay additional dollars for production of clean energy for Alachua (A), Duval (D), Hillsborough (H), Orange (O), Polk (P), and Alachua Group B Question-Response County A D H O P No. % No. % No. % No. % No % Overall No % Support for paying a higher cost for cleaner energy Not Supportive Somewhat Supportive Supportive Very Supportive Extremely Supportive Not Sure Missing Total (A) 10 15.2 (B) 5 11.6 (A) 23 34.8 (B) 18 41.9 (A) 16 24.2 (B) 12 27.9 (A) 8 12.1 (B) 4 9.3 (A) 1 1.5 (B) 2 4.7 (A) 1 1.5 (B) 1 2.3 (A) 7 10.6 (B) 1 2.3 (A) 66 99.9 (B) 43 100.0 10 23.3 15 4.9 12 27.9 2 4.7 3 7.0 0 0.0 1 2.3 43 100.1 3 6.0 20 40.0 16 32.0 8 16.0 1 2.0 0 0.0 2 4.0 50 100.0 4 14.8 9 33.3 9 33.3 3 11.1 0 0.0 0 0.0 2 7.4 27 99.9 2 4.5 23 52.3 10 22.7 4 9.1 0 0.0 0 0.0 5 11.4 4 100.0 34 12.4 108 39.6 75 27.5 29 10.6 7 2.6 2 .7 18 6.6 273 100.0

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31 Table 4-6 Continued Question-Response County A D H O P No. % No. % No. % No. % No % Overall No % Willingness to pay more for cleaner energy Yes No Not Sure Missing Total (A) 35 53.0 (B) 26 60.5 (A) 22 33.3 (B) 14 32.6 (A) 0 0.0 (B) 0 0.0 (A) 9 13.6 (B) 3 7.0 (A) 66 99.9 (B) 43 100.1 21 48.8 19 44.2 1 2.3 2 4.7 43 100.0 32 64.0 14 28.0 0 0.0 4 8.0 50 100.0 14 51.9 10 37.0 0 0.0 3 11.1 27 100.0 22 50.0 14 31.8 0 0.0 8 18.2 44 100.0 150 54.9 93 34.0 1 .4 29 10.6 273 99.9 Additional dollars willing to pay for cleaner energy $5 $20 $20 $25 $25 $30 $35 or more Missing Total (A) 26 39.4 (B) 18 41.9 (A) 5 7.6 (B) 6 14.0 (A) 4 6.1 (B) 1 2.3 (A) 1 1.5 (B) 1 2.3 (A) 30 45.5 (B) 17 39.5 (A) 66 100.1 (B) 43 100.0 11 25.6 8 18.6 1 2.3 1 2.3 22 51.2 43 100.0 26 52.0 4 8.0 3 6.0 1 2.0 16 32.0 50 100.0 10 37.0 2 7.4 1 3.7 1 3.7 13 48.1 27 99.9 17 38.6 5 11.4 2 4.5 1 2.3 19 43.2 44 100.0 108 39.6 30 11.0 12 4.4 6 2.2 117 42.9 273 100.1

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32 Table 4-7. Knowledge of local utility energy production, satisfaction of energy conservation efforts, and willingness to pay higher cost for environmental benefits for Alachua (A), Duval (D), Hillsborough (H), Orange (O), Polk (P), and Alachua Group B Question-Response County A D H O P No. % No % No. % No. % No % Overall No % Knows how local utility company produces electricity Yes No Not Sure Missing Total (A) 41 62.1 (B) 30 69.8 (A) 8 12.1 (B) 4 9.3 (A) 16 24.2 (B) 8 18.6 (A) 1 1.5 (B) 1 2.3 (A) 66 99.9 (B) 43 100.0 25 58.1 9 20.9 8 18.6 1 2.3 43 99.9 29 58.0 11 22.0 9 18.0 1 2.0 50 100.0 9 33.3 8 29.6 9 33.3 1 3.7 27 99.9 31 70.5 3 6.8 8 18.2 2 4.5 44 100.0 165 60.4 43 15.8 58 21.2 7 2.6 273 100.0 Satisfaction rate of utility companys effort of energy conservation Not Satisfied Somewhat Satisfied Satisfied Very Satisfied Extremely Satisfied Missing Total (A) 9 13.6 (B) 5 11.6 (A) 27 40.9 (B) 15 34.9 (A) 20 30.3 (B) 16 37.2 (A) 2 3.0 (B) 4 9.3 (A) 0 0.0 (B) 0 0.0 (A) 8 12.1 (B) 3 7.0 (A) 66 99.1 (B) 43 100.0 0 0.0 15 34.9 21 48.8 5 11.6 1 2.3 1 2.3 43 99.9 6 12.0 24 48.0 15 30.0 3 6.0 0 0.0 2 4.0 50 100.0 2 7.4 13 48.1 10 37.0 0 0.0 0 0.0 2 7.4 27 99.9 3 6.8 15 34.1 16 36.4 4 9.1 0 0.0 6 13.6 44 100.0 25 9.1 109 39.9 98 35.9 18 6.6 1 .4 22 8.1 273 100.0

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33 Table 4-7. Continued Question-Response County A D H O P No. % No % No. % No. % No % Overall No % Higher cost for benefits Not Willing Somewhat Willing Willing Very Willing Extremely Willing Missing Total (A) 11 16.7 (B) 4 9.3 (A) 19 28.8 (B) 12 27.9 (A) 20 30.3 (B) 15 34.9 (A) 4 6.1 (B) 5 11.6 (A) 3 4.5 (B) 1 2.3 (A) 9 13.6 (B) 6 14.0 (A) 66 100 (B) 43 100 9 20.9 17 39.5 13 30.2 1 2.3 0 0.0 3 7.0 43 99.9 3 6.0 24 48.0 15 30.0 6 12.0 0 0.0 2 4.0 50 100 5 18.5 11 40.7 6 22.2 2 7.4 1 3.7 2 7.4 27 99.9 3 6.8 21 47.7 13 29.5 2 4.5 0 0.0 5 1.4 44 99.9 35 12.8 104 38.1 82 30.0 20 7.3 5 1.8 27 9.9 273 99.9 If however, the utility companies within the target counties are indeed actively promoting energy conservation practices, the low awareness of environmental terms in this study suggests that their efforts of promoting alternative forms of energy production is low or ambiguous. Even though the traditional method of generating electricity caused environmental destruction, the environmental benefits of using renewable energy technologies are still well-known (Morgenstern 2002), at least 30% of the participants were willing to pay higher costs to have the benefit of a cleaner environment, and 38.1% were somewhat willing even though the knowledge of environmental remedies, such as biomass or co

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34 firing which can be used to reduce levels of harmful pollutants, is low (Table 4-4). If people are educated about the benefits of biomass and co-firing, the awareness levels of potential alternative energy production methods will grow, as will peoples willingness to pay for environmental benefits. Table 4-8 indicates the results of T-test of Independent samples, which was used to compare the means of Group A and Group B. There were no significant differences at a 0.05 Alpha Significance Level between residents who received the GRU brochure Deerhaven Generating Station Neighbors with Nature, Group B, and those who did not Group A. A reason for this may be related to the fact that GRU is the primary electricity provider for Alachua County. Although smaller utility companies, such as Clay Electric, may provide electricity to Alachua residents, some residents may be aware that small utility companies frequently purchase power from larger utility providers. As a result, residents may feel that there is no difference in energy production between two electric companies within the same county. An additional reason why there may be no significance between Group A and Group B may be because brochures may not be ideal forms of media which can generate significant responses between members within the same sampled population. Responses can also be provided in the form of behavior, which can be controlled or determined by advertising through various types of media. For instance, in the earlier 70s, to educate people about the dangers of forest fires, the USDA Forest Service used Smokey The Bear as a national spokesperson to remind and educate people that only you can prevent forest firesonly you.

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35 Table 4-8. Summary of nonsignificant t-tests of Independent samples for a comparison of the means of Group A and Group B Alachua County homeowners on knowledge and willingness to pay for safe energy and subscriptions to Green Energy Programs. Question County Alachua Test Alachua N X N X ________________________________________________________________________ Willing to pay more for safe 57 1.39 40 1.35 environmentally safe energy production. Aware if local utility has 65 2.16 43 2.26 Green Energy Program. Would subscribe to Green 60 2.44 41 2.34 Energy Program if local utility provided one. Knows how local utility 65 1.63 42 1.48 company produces energy. Support of paying higher 59 2.48 42 2.60 premiums for cleaner energy. Satisfaction of local utility 58 2.28 40 2.48 companys efforts to promote energy conservation. Willingness to pay higher 57 2.45 37 2.65 costs for environmental benefits. ________________________________________________________________________ Survey Remarks Internal validity was an important concern throughout this research. Since the goal was to survey 150 residents from each county (excluding the 150 additional Alachua County residents in Group B), the mortality rates (nonrespondents and exclusions) for each county was represented as mail-related occurrences, such as bad addresses, no such person at this address, commercial businesses which were inadvertently selected during

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36 the randomized selection process, and people who owned property in the target county, but did not physically live in that county. Situations such as these warranted methods of double-dipping, or reselecting participants from the sample population. Demographic information made available to researchers or proponents of biomass is necessary because efforts can not only be directed towards those who support biomass and co-firing, but also to individuals who may have little or no knowledge of alternative energy production methods. Since there was a low response rate among minority groups, and no response from people between the ages of 18-25, educational efforts of alternative energy production should begin within these segments of the general population. Table 4-9 presents demographic results for environmental questions, which were analyzed using a Logistic Regression method. Although each independent variable demonstrated a level of significance for each question, not all dependent variables were significant. The variation in significance for dependent variables is due to some independent variables being far less significant than others. Significance was determined at a .05 Alpha-Level. The independent variable that was significant more times than any other independent variables was the education level of participants. This is important since educational levels may have larger influences on the choices regarding bioenergy and other choice-related topics. Furthermore, when a person has ample information about a particular topic or even new types of technology, such as co-firing, that person may perceive the benefit of this new type of technology and become more likely to adopt it. The age and gender independent variables both demonstrated significance at least three times, while ethnicity was significant in only one case scenario.

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37 Table 4-9. Logistic regression coefficients (b) and their standard errors (SE) and significance (*, at the 0.05 level by the Wald test) for demographic variables Education, Gender, Ethnicity, Age, and Income in predicting responses to survey questions (in bold). Statistic Constant Education Gender Ethnicity Age Income Heard of Global Warming B -6.752 .054 .588 .457 .464 -1.029* SE 4.275 .064 1.185 .295 .711 .501 Heard of Biomass B 5.995 -.084* -.788* .165 -.112 -.173 SE 1.305 .023 .305 .125 .181 .132 Heard of Co-firing B 3.274 .011 -1.260* -.107 .044 -.080 SE 1.393 .024 .387 .126 .211 .161 Aware if local utility company has a Green Energy Program B 4.309 -.091* -.151 -.173 .226 .181 SE 1.422 .027 .354 .120 .209 .151 Subscribes to local utilitys Green Energy Program B -2.731 -.020 -.884 5.556 .175 .357 SE 24.069 .043 .716 23.919 .389 .252 Would subscribe Green Energy Program if local utility provided one B 1.794 -.037 -.170 -.123 .245 .080 SE 1.267 .023 .329 .124 .193 .140 Knows how local utility produces energy B 5.376* -.053* -.830 .059 -.304 -.308 SE 1.323 .022 .307 .120 .184 .126 Support of paying higher premiums for cleaner energy B 1.747 .069* -.044 -.116 -.371 -.228 SE 1.802 .031 .457 .151 .279 .199 Satisfaction of local utility companys effort to promote energy conservation B -2.010 .021 .137 .090 .694* .088 SE 1.874 .033 .469 .229 .274 .190 Willing to pay more for environmentally safe energy production B .038 -.071* -.006 .182 .336 .185 SE 1.251 .024 .315 .115 .191 1.251 Willingness to pay higher costs for environmental benefits B 1.014 .091* -.237 -.157 -.378 -.231 SE 1.702 .030 .431 .139 .263 .187

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38 Appendices F-K presents the results of contingency tables for the following six dependent variables: 1) Have you heard of Global Warming? 2) Have you heard of Biomass? 3) Have you heard of Co-firing? 4) Do you know if your local utility company has a Green Energy Program? 5) Would you subscribe to a Green Energy Program if your local utility company provided one? 6) Are you willing to pay more money towards your electric bill for energy production methods that are environmentally safe? The Chi-Square values included within the Contingency Tables are useful because they indicate a measure of how close the observed frequencies are to the frequencies of independent variables (Agresti 1986). Furthermore, the size of the Chi-Square value can also be used to determine how strong the association is between variables in the reported data. The large Chi-Square values for the independent variables, income and ethnicity, were significant factors for participants knowledge or awareness of global warming. Furthermore, the Chi-Square values of income and gender were also significant participants were asked if they had heard of biomass. Gender was the only variable to demonstrate significance for determining if a participant heard of co-firing; in fact, 14.4% of males indicated they had heard of co-firing and 40.9% of females indicated they had not heard of co-firing.

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39 Almost all of the participants within each surveyed demographic (income, gender, age, and ethnicity) indicated that they had heard of global warming. Participants earning salaries between $30K-$40K and $50K or more had the highest the highest overall awareness level of global warming. Females had a lower awareness level than males, and participants who identified themselves as couples had the highest rate of awareness. Participants who were between the ages of 26-34 and 51-65 had a higher awareness level than the other age categories, while respondents who were 66 or older had the lowest awareness level of global warming. African Americans had the highest awareness level of global warming, while Caucasians had the lowest awareness level. The awareness level of biomass was highest among participants earning $50k or more and the lowest among those earning between $20K-$30K. Females had a lower awareness level about biomass than males. Individuals between the ages of 51-65 had the lowest awareness level compared to participants who were 26-34 years of old. All ethnic groups had a high rate of unawareness of biomass. A high rate of unawareness about co-firing existed among all income levels. Females were less aware of co-firing than males. Respondents between the ages of 51-65 had the lowest awareness rate, and Hispanics represented the lowest awareness level of co-firing. All income levels had a high rate of unawareness of knowing if their local utility companies had Green Energy Programs. Males were more aware about Green Energy Programs. Ages 51-65 represented the largest group, which did of Green Energy Programs. Caucasians had the highest awareness level about Green Energy Programs, while the other ethnic groups unawareness rates were similar.

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40 When asked if participants would subscribe to a Green Energy Program if was provided by their local utility company, there was a high rate of uncertainty among all income levels. Respondents between the ages of 35-50 were most likely to subscribe to Green Energy Programs than any other age category. Caucasians represented the larges ethnic group that would subscribe to Green Energy Programs. Participants earning $50K or more are willing to pay more for environmentally safe energy production than people in the other income levels. Females are also willing to pay more than males for safer energy production. Individuals between ages 26-34 were indicated that they were also willing to pay more for safer energy production. In fact, only one individual between the ages of 26-34 reported they were not willing to pay more. African Americans were least willing to pay more for safe energy production, while Caucasians were the ethnic group that was most willing to pay more. Appendices L-M present the overall county results of questions from the sections of the survey that addressed home type, energy consumption, home and community lifestyle, and other environmental awareness type questions; these survey sections were: 1) Home and Lifestyle Activity, 2) Home Cooling and Heating, 3) Water Heaters, Pools, and Spas, 4) Home and Kitchen Appliances, and 5) Environmental Awareness.

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CHAPTER 5 CONCLUSIONS Since 55.7% of participants were unaware of biomass and 68.1% were unaware of co-firing, there is a need to educate the public about alternative methods that can be used to promote a healthy environment. Effective ways of educating the public include utilizing educational and community service programs that rely upon mass communication medium, such as television, newspapers, Internet, and radio for the dissemination of energy conservation and alternative production programs to the general public. Counties that exhibit a greater awareness and a willingness to pay for alternative forms of energy should also be viewed as potential locations where proponents of bioenergy can gain support. A total of 23.5% of the participants had not heard of Green Energy Programs, and 52.8% were also unsure if they heard these programs. Therefore, an emphasis to educate the public must also be placed on such programs since they are instrumental for educating the public about alternative forms of energy. While the sustainability of natural resources may continue to be a concern for most individuals, a gap remains between achieving sustainability and the desire for sustainability. To close this gap, researchers of biomass, its proponents, utility companies, and perhaps legislatures must work together to make niche market technologies, such as co-firing not only an environmentally safe alternative method to 41

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42 produce energy, but a financially sound measure as well. Therefore, education of the public is critical if public support and demand for the potential of biomass is to be realized. Because Florida is an ideal place for growing tree species that are suitable for co-firing, Florida utility companies should seek locations where energy crops can be grown. Large rural regions such as Polk County can be ideal for this purpose. The concept of willingness to pay should continue to be explored particularly in its relation to the causes or reasons why respondents may indicate willingness for or against paying higher premiums for safer energy.

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CHAPTER 6 FUTURE RESEARCH This study can benefit from post surveys or longitudinal type studies that measure the difference in participant response after a period of time. While this survey included six sections, other sections could be added to the survey that could analyze consumer choice, or incentives for home-type selection, allocation for additional bioenergy revenues contributed from consumers, and preference(s) for alternative energy production methods analysis. Researchers who wish to continue this study may also conduct short telephone surveys to allow participants to feel as if they are more a part of the research because they are talking directly to an individual. To include the missing demographics of this research in future studies, such as missing minority groups and people between the ages of 18-25, surveys similar to this research can benefit from larger sample sizes, or conducting cross sectional surveys to capture respondents from every county within a particular state. 43

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APPENDIX A SURVEY: ENVIRONMENTAL VALUES AND AWARENESS OF FLORIDA RESIDENTS Figure A-1. Environmental values and awareness of Florida residents 44

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APPENDIX B INITIAL COVER LETTER Figure B-1. Initial cover letter 45

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APPENDIX C FOLLOW-UP COVER LETTER Figure C-1. Follow-up cover letter 46

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APPENDIX D RETURN ADDRESSED STAMPED ENVELOPE Figure D-1. Return addressed stamped envelope 47

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APPENDIX E GRU BROCHURE: DEERHAVEN GENERATING STATION NEIGHBORS WITH NATURE Figure E-1. GRU Brochure: Deerhaven generating station neighbors with nature 48

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APPENDIX F CONTINGENCY TABLE AND CHI-SQUARE VALUES FOR GLOBAL WARMING, ALTERNATIVE ENERGY METHODS, AND WILLINGESS TO PAY MORE FOR SAFE ENERGY Table F-1. Heard of global warming Demographic Response Yes % No % Not Sure % Total % Chi-Square Gender Male Female Couple (Female / Male) Total 132 50.2 121 46.0 2 .7 255 97.0 1 .38 5 1.9 0 0.0 6 2.3 1 .38 1 .38 0 0.0 2 .7 134 51.0 127 48.3 2 .8 263 100.0 3.045 Income Less than $19k $20k $30k $30k $40k $40k $50k $50k or more Total 15 6.4 28 11.9 28 11.9 27 1.4 131 55.5 229 97.0 2 .8 2 .8 0 0.0 2 .8 0 0.0 6 2.3 0 0.0 1 .4 0 0.0 0 0.0 0 0.0 1 .4 17 7.2 31 3.1 28 11.9 29 12.3 131 55.5 236 99.9 20.838* Ethnicity Caucasian African American Hispanic Native American Asian American Other Total 221 85.0 10 3.8 4 1.5 8 3.1 3 1.2 6 2.3 252 96.9 3 1.2 0 0.0 2 .8 0 0.0 1 .4 0 0.0 6 2.3 1 .4 0 0.0 0 0.0 1 .4 0 0.0 0 0.0 2 .8 225 86.5 10 3.8 6 2.3 9 3.5 4 1.5 6 2.3 260 100.0 49.358* Age 26-34 35-50 51-65 66 older Total 12 4.6 81 30.8 90 34.2 71 27.0 254 96.6 0 0.0 2 .8 0 0.0 5 1.9 7 2.7 0 0.0 0 0.0 0 0.0 2 .8 2 .8 12 4.6 83 31.6 90 34.2 78 29.7 263 100.0 11.978 *Significance at 0.05 Alpha-Level 49

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50 Table F-2. Heard of biomass Demographic Response Yes % No % Total % Chi-Square Gender Male Female Couple (Female / Male) Total 72 27.7 36 13.8 1 .4 109 41.9 61 23.5 89 34.2 1 .4 151 58.1 133 51.2 125 48.1 2 .8 260 100.0 17.042* Income Less than $19k $20k $30k $30k $40k $40k $50k $50k or more Total 3 1.3 8 3.4 10 4.3 11 4.7 71 30.3 103 44.0 13 5.6 23 9.8 17 7.3 18 7.7 60 25.6 131 56.0 16 6.8 31 13.2 27 11.5 29 12.4 131 56.0 234 100.0 14.798* Ethnicity Caucasian African American Hispanic Native American Asian American Other Total 97 37.7 2 .8 1 .4 1 .4 1 .4 4 1.6 106 41.2 125 48.6 8 3.1 4 1.6 9 3.5 3 1.2 2 .8 151 58.8 222 86.4 10 3.9 5 1.9 10 3.9 4 1.6 6 2.3 257 100.0 10.095 Age 26-34 35-50 51-65 66 older Total 4 1.5 35 13.4 40 15.3 29 11.1 108 41.4 8 3.1 49 18.8 50 19.2 46 17.6 153 58.6 12 4.6 84 32.2 90 34.5 75 28.7 261 100.0 .899 Significant at 0.05 Alpha-Level

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51 Table F-3. Heard of Co-firing Demographic Response Yes % No % Not Sure % Total % Chi-Square Gender Male Female Couple (Female / Male) Total 38 14.4 11 4.2 1 .4 50 18.9 78 29.5 108 40.9 1 .4 187 70.8 18 6.8 9 3.4 0 0.0 27 10.2 134 50.8 128 48.5 2 .8 264 100.0 23.810* Income Less than $19k $20k $30k $30k $40k $40k $50k $50k or more Total 2 .8 5 2.1 4 1.7 3 1.3 32 13.3 46 19.2 12 5.0 25 10.4 24 10.0 21 8.8 88 36.7 170 70.8 3 1.3 2 .8 1 .4 6 2.5 12 5.0 24 10.0 17 7.1 32 13.3 29 12.1 30 12.5 132 55.0 240 100.0 11.169 Ethnicity Caucasian African American Hispanic Native American Asian American Other Total 44 16.9 1 .4 0 0.0 1 1.4 0 0.0 3 1.2 252 18.8 156 60.0 10 3.8 6 2.3 7 2.7 3 1.2 3 1.2 185 71.1 22 8.5 1 .4 0 0.0 2 .8 1 .4 0 0.0 26 10.0 222 85.4 12 4.6 6 2.3 10 3.8 4 1.5 6 2.3 260 100.0 12.941 Age 26-34 35-50 51-65 66 older Total 1 .4 21 8.0 12 4.5 15 5.7 49 18.6 10 3.8 54 20.5 73 27.7 51 19.3 188 71.2 1 .4 9 3.4 8 3.0 9 3.4 27 10.2 12 4.5 84 31.8 93 35.2 75 28.4 264 100.0 6.387 Significance at 0.05 Alpha-Level

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52 Table F-4. Aware if local utility company has green energy program Demographic Response Yes % No % Not Sure % Total % Chi-Square Gender Male Female Couple (Female / Male) Total 30 11.5 25 9.6 0 0.0 55 21.1 28 10.7 35 13.4 0 0.0 63 24.1 74 28.3 67 25.7 2 .8 143 54.8 132 50.6 127 48.7 2 .8 261 100.0 5.111 Income Less than $19k $20k $30k $30k $40k $40k $50k $50k or more Total 2 .8 8 3.4 6 2.5 7 3.0 26 11.0 49 20.7 8 3.4 7 3.0 6 2.5 5 2.1 27 11.4 53 22.4 8 3.4 17 7.2 15 6.3 17 7.2 78 32.9 135 57.0 18 7.6 32 13.5 27 11.4 29 12.2 131 55.3 237 100.0 14.089 Ethnicity Caucasian African American Hispanic Native American Asian American Other Total 45 17.4 2 .8 1 .4 2 .2 2 .2 2 .2 54 20.9 51 19.8 2 .8 1 .4 3 1.2 1 .4 3 1.2 61 23.6 125 48.4 6 2.3 4 1.6 6 2.3 1 .4 1 .4 143 55.4 221 85.7 10 3.9 6 2.3 11 4.3 4 1.6 6 2.3 258 100.0 12.367 Age 26-34 35-50 51-65 66 older Total 4 1.5 18 6.9 19 7.3 14 5.3 55 21.0 1 .4 20 7.6 17 6.5 25 9.5 63 24.0 7 2.7 45 17.2 53 20.2 39 14.9 144 55.0 12 4.6 83 31.7 89 34.0 78 29.8 262 100.0 7.258

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53 Table F-5. Subscribe to a Green Energy Program Demographic Response Yes % No % Not Sure % Total % Chi-Square Gender Male Female Couple (Female / Male) Total 31 13.2 30 12.8 2 .9 63 26.8 10 4.3 3 1.3 0 0.0 13 5.5 79 33.6 80 34.0 0 0.0 159 67.7 120 51.1 113 48.1 2 .9 235 100.0 9.122 Income Less than $19k $20k $30k $30k $40k $40k $50k $50k or more Total 2 .9 9 4.2 6 2.8 8 3.7 34 15.8 59 27.4 1 .5 4 1.9 0 0.0 0 0.0 9 4.2 14 6.5 11 5.1 14 6.5 19 8.8 19 8.8 79 36.7 142 66.0 14 6.5 27 12.6 25 11.6 27 12.6 122 56.7 215 99.9 9.420 Ethnicity Caucasian African American Hispanic Native American Asian American Other Total 52 22.3 3 1.3 1 .4 2 .9 1 .4 3 1.3 62 26.6 9 3.9 1 .4 1 .4 1 .4 0 0.0 1 .4 13 5.6 139 59.7 5 2.1 4 1.7 6 2.6 3 1.3 1 .4 158 67.8 200 85.8 9 3.9 6 2.5 9 3.9 4 1.7 5 2.1 233 100.0 13.974 Age 26-34 35-50 51-65 66 older Total 5 2.1 25 10.6 17 7.2 16 6.8 63 26.7 0 0.0 3 1.3 7 3.0 4 11.7 14 5.9 6 2.5 51 21.6 58 24.6 44 18.6 159 67.4 11 4.7 79 33.5 82 34.7 64 27.1 236 100.0 6.061

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54 Table F-6. Willing to pay more for environmentally safe energy Demographic Response Yes % No % Not Sure % Total % Chi-Square Gender Male Female Couple (Female / Male) Total 77 31.3 73 29.7 2 .8 152 61.8 53 21.5 40 16.2 0 0.0 93 37.8 0 0.0 1 .4 0 0.0 1 .4 130 52.8 114 46.3 2 .8 246 100.0 3.142 Income Less than $19k $20k $30k $30k $40k $40k $50k $50k or more Total 9 4.0 16 7.1 20 8.9 17 7.6 83 37.0 145 64.7 6 2.7 13 5.8 6 2.7 10 4.5 43 19.2 78 34.8 0 0.0 0 0.0 0 0.0 1 .4 0 0.0 1 .4 15 6.7 29 12.9 26 11.6 28 12.5 126 56.3 224 99.9 10.157 Ethnicity Caucasian African American Hispanic Native American Asian American Other Total 134 55.1 5 2.1 3 1.2 4 1.6 2 .8 3 1.2 151 62.1 74 30.5 6 2.5 2 .8 4 1.6 2 .8 3 1.2 91 37.4 1 .4 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 1 .4 209 86.0 11 4.5 5 2.1 8 3.3 4 1.6 6 2.5 243 100.0 4.501 Age 26-34 35-50 51-65 66 older Total 11 4.5 53 21.5 50 20.3 37 15.0 151 61.4 1 .4 26 10.6 36 14.6 31 12.6 94 38.2 0 0.0 1 .4 0 0.0 0 0.0 1 .4 12 4.9 80 32.5 86 35.0 68 27.6 246 100.0 9.617

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APPENDIX G OVERALL COUNTY RESULTS FOR HOME AND LIFESTYLE ACTIVITY On a scale of 1 to 5, rate your likelihood to conserve energy within your home. Response Frequency Percent Not at all 2 .7 Sometimes 44 15.8 Often 75 27.0 Regularly 102 36.7 Always 52 18.7 Sub Total 275 98.9 Missing 3 1.1 Total 278 100.0 Do you recycle yard wastes, plastics, glass, or any other recyclable item? Response Frequency Percent Yes 227 81.7 No 50 18.0 Sub Total 277 99.7 Missing 1 .3 Total 278 100.0 On a scale of 1 to 5, how satisfied were you with the dollar amount and kilowatt usage of your last electric bill? Response Frequency Percent Not satisfied 62 22.3 Somewhat satisfied 93 33.5 Satisfied 91 32.7 Very satisfied 23 8.3 Extremely satisfied 3 1.1 Sub Total 272 97.8 Missing 6 2.2 Total 278 100.0 55

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56 Do you have a computer in your home? Response Frequency Percent Yes 222 79.9 No 54 19.4 Sub Total 276 99.3 Missing 2 .7 Total 278 100.0 Which is your preferred choice for receiving news related information? Response Frequency Percent Internet 16 5.8 Newspaper 74 6.6 Radio 17 6.1 Television 125 45.0 Combination 42 15.1 Sub Total 274 98.6 Missing 4 1.4 Total 278 100.0 Do you have access to the Internet? Response Frequency Percent Yes 218 78.5 No 52 18.7 Sub Total 270 97.2 Missing 8 2.8 Total 278 100.0

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57 Please describe the type of home you currently live in. Response Frequency Percent One-story, single family home 190 68.3 Two-story, single family home 37 13.3 Mobile home, single-wide 7 2.5 Mobile home, double or triple wide 28 10.1 Condo 5 1.8 Town home 4 1.4 Other 6 2.2 Sub Total 277 99.6 Missing 1 .4 Total 278 100.0 On a scale of 1 to 5, how energy efficient is your home? Response Frequency Percent Not energy efficient 22 7.9 Somewhat energy efficient 114 41.0 Energy efficient 96 34.5 Very energy efficient 36 12.9 Extremely energy efficient 4 1.4 Sub Total 272 97.8 Missing 6 2.2 Total 278 100.0 How many appliances within your home use natural gas? Response Frequency Percent 1 37 13.3 2 33 11.9 3 or more 21 7.6 None 76 27.3 Sub total 167 60.1 Missing 111 39.9 Total 278 100.0

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APPENDIX H OVERALL COUNTY RESULTS FOR HOME COOLING AND HEATING Which method do you use to cool your home? (Please circle w for with, or o for without ceiling fan). Response Frequency Percent Air conditioning (Window unit with ceiling fan) 15 5.4 Central air conditioner (With ceiling fan) 191 68.7 Ceiling fans 9 3.2 Air conditioner (Window unit without ceiling fan) 5 1.8 Central air conditioner (Without ceiling fan) 35 12.6 Combination 17 6.1 Other 3 1.1 Sub Total 275 98.9 Missing 3 1.1 Total 278 100.0 During summer months, how often do you use any of the items in question 1 to cool your home? Response Frequency Percent Never 2 .7 Sometimes 21 7.6 Often 114 41.0 Continuously 139 50.0 Sub Total 276 99.3 Missing 2 .7 Total 278 100.0 58

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59 During the winter months, how do you heat your home? Response Frequency Percent Electrical Central Heating 99 35.6 Wood (Fireplace) 16 5.8 Heat Pump 57 20.5 Natural Gas Central Heating 36 12.9 Kerosene / Oil 5 1.8 Electric Portable Heaters 1 .4 Other 11 4.0 None 2 .7 Combination 44 15.8 Sub Total 271 97.5 Missing 7 2.5 Total 278 100.0

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APPENDIX I OVERALL COUNTY RESULTS FOR WATER HEATERS, POOLS, AND SPAS How many water heaters do you use in your home? Response Frequency Percent 1 231 83.1 2 34 12.2 3 3 1.1 4 or more 2 .7 Sub total 270 97.1 Missing 8 2.9 Total 278 100.0 Which type of the following describes your main water heater? (Choose one) Response Frequency Percent Standard separate tank (Electric) 167 60.1 Standard tank with heat recovery (Electric) 34 12.2 Heat pump water heater (Electric) 7 2.5 Other electric system 2 .7 Natural gas 32 11.5 Propane 13 4.7 Combination 7 2.5 Sub total 262 94.2 Missing 16 5.8 Total 278 100.0 60

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61 Is your water heater insulated? Response Frequency Percent Yes 165 59.4 No 63 22.7 Not sure 41 14.7 Sub total 269 96.8 Missing 9 3.2 Total 278 100.0 Do you have a swimming pool at your home? Response Frequency Percent Yes 69 24.8 No 199 71.6 Sub total 268 96.4 Missing 10 3.6 Total 278 100.0 How is your swimming pool heated? Response Frequency Percent Electric heat pump (Dedicated) 4 1.4 Natural gas 4 1.4 Propane 3 1.1 Solar 7 2.5 Not heated 50 18.0 Combination 1 .4 Sub total 69 24.8 Missing 209 75.2 Total 278 100.0 Do you have a spa, whirlpool tub, or hot tub in your home? Response Frequency Percent Yes 43 15.5 No 215 77.3 Sub total 258 92.8 Missing 20 7.2 Total 278 100.0

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62 How do you heat your spa, whirlpool tub, or hot tub? Response Frequency Percent Electric heat pump (Dedicated) 8 2.9 Natural gas 8 2.9 Other electric heat 12 4.3 Propane 6 2.2 Not heated 10 3.6 Combination 1 .4 Sub total 45 16.2 Missing 233 83.8 Total 278 100.0

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APPENDIX J OVERALL COUNTY RESULTS FOR HOME AND KITCHEN APPLIANCES How many refrigerators do you use in your home? Response Frequency Percent 1 190 68.3 2 74 26.6 3 or more 8 2.9 Sub total 272 97.8 Missing 6 2.2 Total 278 100.0 How old is / are your refrigerator(s)? Response Frequency Percent New 25 9.0 2-5 years 68 24.5 5-10 years 113 40.6 15 years or more 40 14.4 2 combined 20-25 years 3 1.1 2 combined 7-15 years 6 2.2 10-15 years 1 .4 2 combined new and 5-10 years 6 2.2 13 years 1 .4 2 combined 2-5 years and 15 years or more 1 .4 2 combined new and 2-5 years 3 1.1 2 combined 5-10 years and 15 + years 1 .4 2 combined new and over 30 years 1 .4 3 or more combined 20-25 years or more 1 .4 2 combined new and 15 years or more 1 .4 2 combined 25-30 years or more 1 .4 Sub total 272 97.8 Missing 6 2.2 Total 278 100.0 63

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64 Which type of range / oven do you use in your home? Response Frequency Percent Electric 232 83.5 Natural gas 19 6.8 Propane 21 7.6 Combination 2 .7 Sub total 274 98.6 Missing 4 1.4 Total 278 100.0 Do you use a microwave oven in your home? Response Frequency Percent Yes 269 96.8 No 6 2.2 Sub total 275 98.9 Missing 3 1.1 Total 278 100.0 Do you use a dishwasher in your home? Response Frequency Percent Yes 207 74.5 No 66 23.7 Sub total 273 98.2 Missing 5 1.8 Total 278 100.0 Which type of clothes dryer do you use in your home? Response Frequency Percent Electric 251 90.3 Natural gas 7 2.5 Propane 6 2.2 Combination 1 .4 Other 3 1.1 None 5 1.8 Sub total 273 98.2 Missing 5 1.8 Total 278 100.0

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65 Do you have a washing machine in your home? Response Frequency Percent Yes 271 97.5 No 4 1.4 Sub total 275 98.9 Missing 3 1.1 Total 278 100.0 Other than the refrigerator, which of the following appliances do you use most on a daily basis in your home? Response Frequency Percent Range / Oven 68 24.5 Microwave 97 34.9 Dishwasher 6 2.2 Clothes Dryer 5 1.8 Washing Machine 9 3.2 Other 2 .7 Combination 85 30.6 Sub total 272 97.8 Missing 6 2.2 Total 278 100.0

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APPENDIX K OVERALL COUNTY RESULTS FOR ENVIRONMENTAL AWARENESS Do you belong to any type of natural resource, conservation, or environmental organizations? Response Frequency Percent Yes 40 14.4 No 233 83.8 Sub total 273 98.2 Missing 5 1.8 Total 278 100.0 How concerned are you with global warming? Response Frequency Percent Not concerned 43 15.5 Moderately concerned 107 38.5 Concerned 54 19.4 Very concerned 42 15.1 Extremely concerned 16 5.8 Sub total 262 94.2 Missing 16 5.8 Total 278 100.0 Do you believe that there are enough natural resources for future generations? Examples of natural resources are air, water, plant material, etc? Response Frequency Percent Yes 106 38.1 No 89 32.0 Not sure 73 26.3 Sub total 268 96.4 Missing 10 3.6 Total 278 100.0 66

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67 How concerned are you with global issues, such as conservation, pollution, and environmental issues? Response Frequency Percent Not concerned 13 4.7 Moderately concerned 85 30.6 Concerned 83 29.9 Very concerned 62 22.3 Extremely concerned 28 10.1 Sub total 271 97.5 Missing 7 2.5 Total 278 100.0 Do you believe there will be enough energy to support future generations? Response Frequency Percent Yes 117 42.1 No 62 22.3 Not sure 91 32.7 Sub total 270 97.1 Missing 8 2.9 Total 278 100.0 How often have you attended community and county meetings or public forums since living in your current home? Response Frequency Percent Never 186 66.9 Once a month 50 18.0 Twice a month 5 1.8 More than 3 times a month 2 .7 3 times a month 1 .4 Occasionally 2 .8 Sub total 246 88.5 Missing 32 11.5 Total 278 100.0

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68 How often do you encourage others to conserve energy? Response Frequency Percent Never 44 15.8 Sometimes 125 45.0 Often 86 30.9 Continuously 13 4.7 Sub total 268 96.4 Missing 10 3.6 Total 278 100.0

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LIST OF REFERENCES Agresti, A. and Finlay, B. 1985. 1985. Statistical methods for the social sciences 2nd Edition. Dellen Publishing Company. San Francisco. Anderson, J.L. Jr. and Altobello, M.A. 1982. Energy recovery from agricultural wastes. 82-29 in Staff Paper. Univ. Conn. Dep. Agric. Econ. Rural Soc. Audirac, I., and Smith, M.T. 1992. Urban form and residential choice: preference for urban density in Florida. J. Arch. & Plan. Res. Spring, 9:1, 19-32. Asmus, P. 2002. Capturing markets and delivering value in the electric utility industry. Coop. Environ. Strategy. 9:2, 122-128. Bourdaire, J. and Ellis, J. 2000. Energy-related services and global environmental concerns what possible strategies for forestry? Eco Engineering. 16:1,51-61. Bravo-Ureta, B.E. and McMahon, G.V. 1983. The economic feasibility of electricity generation on cage layer operations, (net present value). 8311 in Staff Paper Univ. Conn. Dep Agric. Econ. Rural Soc. Brown, M.A. and Major, C.H. 1990. Technology-transfer strategies of DOEs conversion programs. J. Tech. Trans. 15: 33-40. Brown, R.A., Rosenberg, N.J., Hays, C.J. Easterling, W.E. and Means, L.O. 2000 Potential production and environmental effects of switch grass and traditional crops under current and greenhouse-altered climate in the central United States: a simulation study. Agrci. Ecosys. and Environ. 78: 31-47. Buttel, F.H. and Flinn, W.L. 1976. Economic growth versus the environment: survey evidence. Soc. Sci. Quart. 57: 2, September, 410-420. Buttond, G. 2000. How can policy take into consideration the full value of forest? Land Use Policy. 17: 169-175. Campinhos, E. Jr. 1999. Sustainable plantations of high-yield eucalyptus trees for production of fiber: the Aracruz case. New Forests. 17-18: 129-143. Caro, F. and Gottlieb, A. 2001. A field experiment in aging services: opportunities and obstacles in the pursuit of internal and external validity. Evaluation and Program Planning 24:3, 249-246. 69

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70 Central Pennsylvania Energy Center (CPEC). 1990. Energy in alternative agriculture. Center: Pennsylvania Energy Office. Lewisburg, PA. Chesbrough, H. 2003. Open innovation: the new imperative for creating and profiting from technology. Harvard Business School Press. Boston, MA. Classen, P.A.M., Sijtsma, L., Stams, A.J.M., Vries de, S.S., Weusthuis, R. A., Van Lier, J.B., Lopez Contreras, A.M., and Van Niel, E.W.J. 1999. Utilization of biomass for the supply of energy carriers. Appl. Microbiology and Biotech. 52: 741-755. Cosmi, C., Macchiato, M., Mangiamele, L., Marmo, G., Pietrapertosa, F., and Salvia, M. 2002. Environmental and economic effects of renewable energy on a local case study. Energy Policy. Article in press: 1-15. Criddle, R.S., Anekonda, T.S., Sachs, R.M., Breidenbach, R.W., and Hansen, L.D., 1996. Selection of biomass production based on respiration parameters in eucalyptus: acclimation of growth and respiration to changing growth temperature. Canadian J. Forest Res. 26: 1569-1576. Elliot, D. 2000. Renewable energy and sustainable futures. Futures. 32: 261-274. English, B.C., Short, C. and Heady, E.O. 1981. The economic feasibility of crop residues as auxiliary fuel in coal-fired power plants. Am. J. Agric. Econ. 63: 636-644. Francis, C.A. and Madden, J.P. 1993. Designing the future: sustainable agriculture in the U.S. Agric. Ecosystems & Environ. 46: 123-134. Gan, L. 2002. Promoting green electricity development from industrial to developing countries: what needs to be done. Environ Politics. 11, 1, spring, 184-191. Garg, V.K. and Jain, R.K. 1992. Influence of fuelwood trees on sodic soils. Canadian J. Forest Res. 22: 729-735. Gluck, P. 2000. Policy means for ensuring the full value of forest to society. Land Use Policy. 17: 177-185. Guo, L.B. and Sims, R.E.H. 1999a. Litter production and nutrient return in New Zealand eucalypt short-rotation forests: implication for land management. Agric. Ecosystems & Environ. 73: 93-100. Guo, L.B. and Sims, R.E.H. 1999b. Litter decomposition and nutrient release via litter decomposition in New Zealand eucalypt short rotation forests. Agric. Ecosystems & Environ. 75: 133-140.

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71 Hill L and Hadely J. 1995. Federal tax incentives and disincentives for the adoption of woodfuel electric generating technologies. Bioresource Tech. 53: 173-178. Hilman, N.D. and Yancey, M.A. 1998. Use of net present value analysis to evaluate a publicly funded biomass-to ethanol research, development, and demonstration program and valuate expected private sector fund. Appl. Biochemistry and Tech. 70-72: 807-819. Hitzhusen, F. J. and Abdallah, M. 1980. Economics of electrical energy from crop residue combustion with high sulfur coal. Am. J. Agric. Econ. 62: 416-425. Marrku, O.R., Gronfors, T.H.A., and Haukka, P. 2003. Development and optimization of power plant concepts for local wet fuels. Biomass and Bioenergy. 24:1, 27-37. McIlveen-Wright, D.R., Williams, B.C., and McMullan, J.T. 2001. A re-appraisal of wood-fired combustion. Bioresource Tech. 76: 183-190. McKendry, P. 2002. Energy production from biomass (part 2): conversion technologies. Bioresource Tech. 83: 47-54. McQueen, R.E. 2000. World population growth, distribution and demographics and their implications on food production. Canadian J. Of Anim. Sci. 80:229-234. Michaels, M.Z. 2000. Speed: linking innovation, process, and time to market. The Conference Board. New York. Mielenz, J.R. 1996. Commercialization of biomass ethanol technology: feasibility studies biomass-to-ethanol production facilities. Appl. Biochemistry and Biotech. 57-58: 763-775. Morgenstern, J. 2002. Renewable energy for rural electrification in developing countries. Dissertation Abstracts International, A: The Humanities and Soc. Sci; 63, 2, August. 781-A. Mulloy, F. and Ottisch, A. 2000. The full value of forests. Land Use Policy 17: 167-168. Neij, L. 1997. Use of experience curves to analyze the prospects of diffusion and adoption of renewable energy technology. Energy Policy. 23: 1099-1107. Newman, I. and McNeil, K. 1998. Conducting survey research in the social sciences. University Press of America. Pearson, R.W. and Boruch, R.F. 1980. Survey Research Designs: Towards a Better Understanding of Their Costs and Benefits. Springer-Verlag

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72 Rahmani, M., A.W. Hodges, and Stricker, J.A. 1996. Potential producers and their attitudes toward adoption of biomass crops in Central Florida. Proc. Seventh National Bioenergy Conference, BIOENERGY 96, 671-678, Ibid. Rahmani, M., Hodges, A., Stricker, J.A., and Kiker, C.F. 2003. Will investing in Renewable energy pays off?: A case study in Florida. Food and Resource Economics Department, Polk County Extension Service, Institute of Food and Agricultural Sciences, University of Florida. Rahmani, M., Stricker, J.A., and Kiker, C.F. A comparison of renewable energy options for Florida. Food and Resource Economics Department, Institute of Food and Agricultural Sciences, University of Florida, Polk County Extension Service. Rogers, E.M. 1995. Diffusion of Innovation. 3rd Edition. The Free Press. Macmillan Publishing Company. New York. Rogers, E.M. and Shoemaker, F.F. 1971 Communication of innovations: a crosscultural approach. 2nd Edition. The Free Press. New York. Rogers, G.O. 1998. The dynamics of risk perception: how do perceived risks respond to risk events? Insurance: Mathematics and Econ. 22:3, 292-292. Seattle: State Office of Public Instruction. 1979. Energy, food, and you: an interdisciplinary curriculum guide for secondary schools. State Report. Sells, J.E. and Audsley, E. 1991. The profitability of an arable wood crop for electricity. J. Agric. Engineering Res. 48: 273-285. Sklar, F.H., Fritz, H.C., Wu, Y., Van Zee, R. and McVoy, C. 2001. South Florida: the reality of change and the prospects of sustainability. Eco Econ. 37:3, 379-401. Slack, W. 1983. Getting it together: pencils, plans and plants. Athens: Cooperative Extension Service. University of Georgia. College of Agriculture. Spiedel, H.K. 2000. Biodegradability of new-engineered fuels compared to conventional petroleum fuels and alternative fuels in current use. Appl. Biochemistry and Biotech. 84-86: 879-897. 76 Stoneman, P. 2002. The economics of technological diffusion. Blackwell Publishers. Stricker, J.A., Rahmani, M., Hodges, A., and Kiker, C.F. Economic analysis of biomass crop production in Florida. University of Florida, Institute of Food and Agricultural Sciences, Food and Resource Economics Department, Polk County Extension Services.

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73 Stricker, J.A., Rockwood, D.L., Segrest, S.A., Alker, G.R. Prine, G.M., Carter, Douglas, R.C. 2000. Short rotation woody crops for Florida. University of Florida Polk County Extension Service and University of Florida School of Forest Resources and Conservation, The Common Purpose Institute, University of Florida Agronomy Department. Stucker, B.C. and Stucker, T.A. 1984. Planting for the future. 8-10, in National Food Review NFR. United States Dep. Econ. Research Service state offices. Wash. D.C. Tillman, D. 2000. Co-firing benefits for coal and biomass. Biomass and Bioenergy. 363-364. Vaage, K. 2000. Heating technology and energy use: a discrete/continuous choice approach to Norwegian household energy demand. Energy Econ. 22:6 649-666. Warren, T.J.B., Poulter, R., Parfitt, R.I. 1995. Converting biomass to electricity on a farm-sized scale using downdraft gasification and a spark-ignition engine. Bioresource Tech. 52: 95-98. Weber, O. 2001. Perception of environmental risks of company sites. J. Environ Psych. 21:2. 165-178. Weisberg, H.F., Krosnick, J.A, and Bowen, B.D. 1989. Survey research and data analysis. 2nd edition. Library of Congress. Wharton, E.H. 1991. Fuelwood telephone surveys: how accurate are they? Northern J. Appl. For. 8:119-122.

PAGE 85

BIOGRAPHICAL SKETCH He was born August 13, 1968 in Tampa, Florida. He graduated from Hillsborough High School in 1986 and later graduated from Hillsborough Community College in 1990 with an Associate of Arts degree in liberal arts. He then came to the University of Florida in 1990 and received a Bachelor of Arts degree in criminal justice (with a minor in sociology) in 1994. Later, he began pursuing a Master of Arts degree in English in the fall semester of 1997 and graduated August 2000. He then began a teaching career as an Adjunct English Professor and later returned to the University of Florida for a Master of Science degree in environmental science 74


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ASSESSING AWARENESS OF FLORIDA HOMEOWNERS ABOUT THE USE OF
BIOMASS FOR ELECTRICITY PRODUCTION


















By

MARK D. ADAMS


A THESIS PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE

UNIVERSITY OF FLORIDA


2003

































Copyright 2003

by

Mark D. Adams




























To my parents, Alphonso and Jacqueline Adams; and the rest of my loving family















ACKNOWLEDGMENTS

I would like to take this opportunity to thank Dr. Donald L. Rockwood, who

presided as my major professor. His support, advice, and assistance throughout this

graduate program have been invaluable. I would also like to thank the rest of my

committee members (Drs. Janaki Alavalapati and Tracy Irani, and Mr. Jim Stricker) for

their guidance and encouragement while conducting this research.

The Florida Institute of Phosphate Research, the Center for Natural Resources, and

Gainesville Regional Utilities also provided invaluable support for this project; without

their contributions, much of this project could not have taken place.

Special thanks go to my statistics professors (Eve Brank and Larry Winner) for

introducing me to the logistics of social statistics. Thanks also go to the IFAS

Communications and Mail Documenting Services support staff for their diligent and

timely assistance.

Finally, I would like to thank my wonderful parents, Alphonso and Jacqueline

Adams, and the rest of my family for their constant and loving support throughout this

project and my academic career.
















TABLE OF CONTENTS
Page

A C K N O W L E D G M E N T S ................................................................................................. iv

LIST OF TABLES ......... ... ........... ... ............. ......... .............. .. vii

LIST OF FIGURES ......... ......................... ...... ........ ............ ix

A B ST R A C T .......... ..... ...................................................................................... x

CHAPTER

1 IN TRODU CTION ................................................. ...... .................

2 LITER A TU R E REV IEW ............................................................. ....................... 3

A alternative Energy Overview ......................................................... ..................... 3
R ole of Energy Producers ............................................................. .............4
Media Related Response to Environmental Issues................. ............................10
Environm mental B benefits A approach ................................. ................... ..................11
Overview of Survey Literature ........................................................ ............. 12

3 M E T H O D S .......................................................................................................1 6

4 RESULTS AND DISCU SSION S......................................... .......................... 20

O overall C county R esponses............................................................... .....................20
R espondent D em graphics ................................................. ............................ 21
Responses to Environmental Questions ............................................. ...............24

5 CON CLU SION S .................................. .. .......... .. .............41

6 FU TU R E R E SEA R CH ......................................................................... .............43

APPENDIX

A SURVEY: ENVIRONMENTAL VALUES AND AWARENESS OF FLORIDA
R E S ID E N T S ...................................................................................................4 4

B INITIAL COVER LETTER ................................................................... ................ 45




v









C FOLLOW -UP COVER LETTER .................................................................... 46

D RETURN ADDRESSED STAMPED ENVELOPE .................................................47

E GRU BROCHURE: DEERHAVEN GENERATING STATION NEIGHBORS
W ITH N A TURE ....................................................... .......... .. .............48

F CONTINGENCY TABLE AND CHI-SQUARE VALUES FOR GLOBAL
WARMING, ALTERNATIVE ENERGY METHODS, AND WILLINGNESS TO
PAY M ORE FOR SAFE ENERGY ................................. ....................49

G OVERALL COUNTY RESULTS FOR HOME AND LIFESTYLE ACTIVITY.....55

H OVERALL COUNTY RESULTS FOR HOME COOLING AND HEATING......... 58

I OVERALL COUNTY RESULTS FOR WATER HEATERS, POOLS, AND
S P A S ...................................... ..................................................... 6 0

J OVERALL COUNTY RESULTS FOR HOME AND KITCHEN APPLIANCES...63

K OVERALL COUNTY RESULTS FOR ENVIRONMENTAL AWARENESS........66

L IST O F R E F E R E N C E S ........................................................................ .....................69

B IO G R A PH IC A L SK E TCH ..................................................................... ..................74















LIST OF TABLES


Table page

2-1 Biom ass crop yields in Florida................... ..... ............................... ............ 10

4-1 Number of responses and percentage of all responses by county ............................21

4-2 Overall Response and Respondent Demographics for Alachua (A), Duval (D),
Hillsborough (H), Orange, Polk (P) Counties and Alachua Group B ....................22

4-3 Numbers and percentages of "missing" demographical information for Alachua
(A), Duval (D), Hillsborough (H), Orange (0), Polk (P) and Alachua Group B.....23

4-4 Participant awareness of environmental terms for Alachua (A), Duval (D),
Hillsborough (H), Orange (0), Polk (P), and Alachua Group B............................25

4-5 Participant response to choice related topics for environmental benefits for
Alachua (A), Duval (D), Hillsborough (H), Orange (0), Polk (P), and Alachua
G rou p B .............................................................................2 7

4-6 Support and willingness to pay additional dollars for production of clean energy
for Alachua (A), Duval (D), Hillsborough (H), Orange (0), Polk (P), and Alachua
G ro u p B .......................................................................... 3 0

4-7 Knowledge of local utility energy production, satisfaction of energy conservation
efforts, and willingness to pay higher cost for environmental benefits for Alachua
(A), Duval (D), Hillsborough (H), Orange (0), Polk (P), and Alachua Group B....32

4-8 Summary of nonsignificant t-tests of Independent samples for a comparison of the
means of Group A and Group B Alachua County homeowners on knowledge and
willingness to pay for safe energy and subscriptions to "Green Energy
Program s." ............ ........ .............. ............. 35

4-9 Logistic regression coefficients (b) and their standard errors (SE) and significance
for demographic variables Education, Gender, Ethnicity, Age, and Income in
predicting responses to survey questions ............ .......................... ...............37

F-l H eard of global w arm ing...................... .... ......... ........... .................. .......... ..... 49

F -2 H eard ofbiom ass........ .................................................................. .......... ..... .. 50









F -3 H heard of C o-fi ring .................................................................... ..........................5 1

F-4 Aware if local utility company has green energy program ....................................52

F-5 Subscribe to a Green Energy Program .......................................... ............... 53

F-6 Willing to pay more for environmentally safe energy ..........................................54
















LIST OF FIGURES


Figure p

2-1 A Model of Stages in the Innovation-Decision Process ........................... .........

2-2 Distinguishing characteristics of interpersonal and mass media channels .............8

A-1 Environmental values and awareness of Florida residents................. .......... 44

B -l Initial cover letter .......................... ......... .. .. ...... .. ............45

C F follow -up cov er letter ......... ............................................................... .................... 46

D-l Return addressed stamped envelope ............................................. ............... 47

E-l GRU Brochure: Deerhaven generating station neighbors with nature...................48















Abstract of Thesis Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Master of Science

ASSESSING AWARENESS OF FLORIDA HOMEOWNERS ABOUT THE USE OF
BIOMASS FOR ELECTRICITY PRODUCTION

By

MARK D. ADAMS


December 2003

Chair: Donald L. Rockwood
Major Department: Forest Resources and Conservation

This research had two goals: 1) to measure a portion of Florida homeowner's

awareness ofbiomass and its potential for use in co-firing; and 2) to assess a sample of

Florida homeowner's awareness opinions, and preferences with respect to environmental

alternatives, which ranged from energy production and conservation to willingness to pay

for technologies that could produce cleaner energy.

A survey was developed and mailed in March 2003 to 150 residents in five Florida

counties: Alachua, Hillsborough, Duval, Orange, and Polk. Alachua was considered a

"treatment" county because in May 2003 an additional 150 residents were mailed the

survey and an energy production brochure provided by Gainesville Regional Utilities

(GRU), a local utility provider for the residents of Gainesville, Florida. Individuals who

may have owned property in the target counties, but were not living there were excluded.

Survey participants were asked questions relating to their homes, lifestyle, environmental

views, and demographical information Although 94.1% of participants had heard of









global warming, 55.7% had not heard of biomass, and 68.1% had not heard of co-firing.

Furthermore, while the awareness of biomass and co-firing was low, more than half of

the respondents indicated willingness to pay at least a $5 to $20 rate increase for

technology that would produce cleaner energy, which can reduce global warming. There

was a higher response rate from males than females in this research.

Programs that promote and support the production of energy using yard wastes,

agricultural, and forest timber-related products from various tree species are known as

Green Energy Programs. These programs, which can be provided by utility companies to

promote and create bioenergy for consumers, can be useful, particularly since this study

indicates respondents' willingness to pay higher premiums for bioenergy. However,

despite this willingness, 59.7% of respondents were either not aware or unsure about

subscribing to Green Energy Programs, and 52.8% were unaware if their local utility

company provided Green Energy Programs. Similar to the high percentages of

participants' unawareness of biomass and co-firing, the high percentages of participants

who are either not aware or unsure about subscribing to Green Energy Programs also

suggest a need for utility companies to educate their consumers about the advantages and

benefits of Green Energy Programs. Utility companies that produce electricity from

Green Energy can benefit from fewer pollutants and as a result, they are less likely to pay

governmental fines for environmental pollution. To promote awareness of alternative

energy methods, the public must be educated about the advantages of Green Energy














CHAPTER 1
INTRODUCTION

The production of energy is a major global concern. Because of the population

growth of many nations, the world's crude petroleum resource will not be enough to

produce energy for future generations. Furthermore, the high price of oil is linked to its

growing demand and short supply, and since the global oil production is expected to

decline within 5 years, alternative energy production methods will become necessary

(McQueen 2000).

Fossil fuels, such as oil and coal, are primarily used for energy production. For

example, 56% of the United States' electricity, as well as large portions of the world's

electricity, is generated by coal (Tillman 2000). Although coal has been used as a source

of energy, the limited and declining supply of oil is a concern. While oil is a component

used for energy production, coal is still the primary source of energy, but producing

energy from coal has negative environmental effects. For instance, pollution and global

warming are directly related to burning coal. Even though the accumulation of CO2 can

cause global warming, biofuels can be used to balance the industrial and other CO2

emissions (Brown et al. 2000). Since fossil fuels, such as oil and coal, have long been

relied on for energy production and because of a reduced supply and harmful by-

products, alternative methods of energy production must be implemented.

The growing demand for energy is a major concern of the United States.

Currently, some United States regions are facing an energy crisis. Since energy is

produced mainly from nonrenewable fossil fuels, the energy-shortage problem will









continue to grow. In addition to this, pollutants are emitted from utility plants that use

fossil fuels to produce energy. These emissions create harmful environmental effects,

such as acid rain and global warming. Therefore, alternative methods of energy

production must be used to reduce these negative consequences and to sustain our future.

Since biomass is a renewable resource that can be co-fired to produce energy, it could be

the ideal choice. For example, wood-cellulosic plants and their residues can be used to

generate energy. (Keith 2000). Furthermore fast growing energy crops, known as

biomass (Elliot 2000) can also be used to produce energy.

Because of fragile ecosystems such as The Everglades, Floridians are concerned

that pollutants that may cause acid rain can be damaging to these sensitive environments.

To address these concerns, Florida agencies such as the Southwest Florida Water

Management District and the Florida Department of Environmental Protection rely upon

landscape models that use biogeochemical mechanisms that are site-specific and mass-

balanced to control energy and material flows; these mechanisms can also predict

changes in carbon and phosphorus structures of sensitive areas such as the soil, water,

and plant communities of the (Sklar et al. 2001).

Since the production of energy relies upon a nonrenewable source, which creates

negative environmental consequences, the research objectives of this study were to assess

the awareness of Florida homeowners about using biomass as a viable alternative for

energy production, and to evaluate Florida homeowners' awareness, opinions, and

attitudes toward bioenergy and their willingness to pay for cleaner forms of energy

production from biomass.














CHAPTER 2
LITERATURE REVIEW

This literature review covers social and scientific research pertinent to survey

questions included in the survey design and the statistical procedures used to summarize

this research.

Alternative Energy Overview

Energy production is a critical problem that must be solved if future generations are

to be sustained. Environmentalists believe that the current method of energy production

should be replaced with a method that does not add to global warming. In order to

produce a clean, continued source of energy, the use of biomass is gaining support

because it provides a source of fuel, which has a higher degradability rate than petroleum

products (Speidel 2000). In fact, US governmental agencies are interested in the

possibility of biomass being used to produce energy. For example, the US Department of

Energy (DOE) and the National Renewable Energy Laboratory (NREL) support

industries that are attempting to develop the economic and commercial prospects of

biomass (Mielenz et al. 1996).

The most promising forms of biomass are energy crops, which can be used by

power plants that use wood as a primary source of (Mcllveen-Wright et al. 2001).

Although wood is the desired form of biomass, which produces energy, leaves and litter

fall can are also useful (Guo and Sims 1999a). Soil is also an equally significant factor

since it can affect the amount of litter fall as well as the root distribution of trees and

plant (Garg and Jain 1992). Various species of Eucalyptus can also be used to produce









energy; however, since these are nonnative species, researchers believe that heat loss

from trees can be related to the environment (Criddle et al. 1996).

As previously mentioned, another immediate benefit from the utilization of

biomass is its ability to reduce the amount of CO2 emissions into the atmosphere, as a

result, reducing global warming (Classen et al. 1999). If biomass has a promising role to

play in sustaining our future, it is evident that a balancing act between caring for the

environment and ensuring that native forests must occur by ensuring that the resources of

smaller land areas will not be exhausted by relying primarily upon them to produce high

quantities of wood (Campinhos 1999). Not only does biomass have the potential to

produce energy, but it can also be used to help reclaim environmentally disturbed lands.

Using biomass resources has certain environmental benefits; however, unless consumers

are ready to pay for higher costs of energy from renewable resources, energy produced

from renewable resources will have to compete with other sources of energy production

(Rahmani et al. 2003). Therefore, the technology costs must be considered for the

development of agricultural equipment that can decease production costs and maximize

the potential for high crop yields (Central Pennsylvania Energy Center 1990).

Role of Energy Producers

Utility companies are beginning to realize that the production of energy can be

achieved by using a process that combines wood and coal; this process is known as co-

firing. Similar to litter fall, some studies show that wood harvested from coppicing is

ideal for use in the gasification plants of utility companies (Warren et al. 1995). Local

farmers growing short rotation woody crops may assist utility companies in producing

energy by using the wood chips harvested from coppiced trees. The chips would pass









through on-site farm equipment, which have gasified engines or electric generators that

are connected to the National Grid (Sells and Audsley 1991).

Another useful biomass product is perhaps the most unlikely vegetables. Corn

has the potential for producing many different forms of food; however, it can be used to

produce energy as well. For example, corn stover can be combined with coal in

coal-burning steam electric plants. Furthermore, another positive benefit of corn is

that it emits low rates of sulfur, and it does not produce harmful by-products, such as

CO2carbon dioxide (Hitzhusen and Abdallah 1980).

An Iowa agricultural program model estimating crop emissions found that crop

residues replace the current BTUs produced from electric plants (English et al. 1981).

The ownership of the utility plant is significant since it determines which types of federal

laws that each plant must adhere to when producing energy (Hill and Hadley 1995).

Finally, as an indirect product of biomass, anaerobic materials, such as manure can

produce electricity that can be sold to public utilities (Bravo-Ureta and McMahon 1983).

Since bioenergy is a relatively new type of technology, it is important to understand

the process by which it might become the standard method of energy production; to do

this, a discussion of "The Diffusion of Innovation" theory is necessary. When

innovations are first developed and introduced into a community or social system, the

innovation goes through or is communicated through certain channels over time among

members of a social system (Rogers 1995). Since communication is a happens by

individuals creating and sharing information with one another in order to reach a mutual

understanding (Rogers 1995), communication becomes vital for an innovation which is

perceived as new by individuals or other units of adoption (Rogers 1995).










Communication, however, about new ideas or technologies does not only occur between

the developers of new inventions or technologies, it can also occur in stages among the

intended recipients of the new innovation (Figure 2-1).


Communication Channels




I. Knowledge II. Persuasion III. Decision IV. Implementation V. Confirmation

S\ -- 1. Adoption Continued Adoption
Later Adoption


Characteristics of Perceived Characteristics 2. Rejection Discontinuance
The decision- of the Innovation Continued Rejection
Making Unit
1. Relative advantage
1. Socio-economic 2. Compatibility
characteristics 3. Complexity
2. Personality 4. Trialability
variables 5. Observability
3. Communication
behavior

Figure 2-1. A Model of Stages in the Innovation-Decision Process. (Rogers, E.M. 1995.
Diffusion of Innovation 3rd Edition. The Free Press, Macmillan Publishing
Company. New York, New York. p. 114)

The five stages that an innovation undergoes are important since they can provide

bioenergy researchers and proponents with useful details about how to introduce co-firing

to potential subscribes, and how to stimulate awareness and demand for this type of

alternative innovation. There are five stages which an innovation undergoes before it is

accepted into a social system:

1. Knowledge occurs when an individual (or other decision-making unit) is exposed to
the innovation's existence and gains some understanding of how it functions.

2. Persuasion occurs when an individual (or other decision-making unit) forms a
favorable or unfavorable attitude toward the innovation.









3. Decision occurs when an individual (or other decision-making unit) engages in
activities that lead to a choice to adopt or reject the innovation.

4. Implementation occurs when an individual (or other decision-making unit) puts an
innovation to use.

5. Confirmation occurs when an individual (or other decision-making unit) seeks
reinforcement of an innovation-decision already made, but he or she may reverse
this previous decision if exposed to conflicting messages about the innovation
(Rogers 1995).

Since the decision to adopt or reject a new type of technology occurs at stage three,

which is the Decision stage, it is a critical stage because people must be provided with

enough information about the benefits of an innovation in order for it to be adopted.

Change agents are individuals responsible for providing this information to a group of

people or into a social setting. Although the adoption of technology can occur when

customers understand and value technologies according to their ability to reduce the cost

of a solution to an existing problem or their ability to create new possibilities and

solutions (Chesbrough 2003), change agents must realize the needs and problems of their

clients since a change agent can selectively transmit information that is relevant (Rogers

1995); therefore, change agents may be suitable choices for educating the public about

the potential benefits of biomass co-firing. Change agents also can facilitate by relying

upon media related methods, such as interpersonal channels that involve a face-to-face

exchange between two or more individuals. These channels have greater effectiveness in

the face of resistance or apathy on the part of the communicate. However, interpersonal

channels are useful since they provide two essential functions:

1. Allow a two-way exchange of ideas. The receiver may secure clarification or
additional information about the innovation from the source individual. This
characteristic of interpersonal channels sometimes allows them to overcome the
social and psychological barriers of selective exposure, perception, and retention.









2. Persuade receiving individuals to form or change strongly held attitudes (Rogers
and Shoemaker 1971).

The attributes of interpersonal channels depict the flow of communication between social

channels (Figure 2-2).

Characteristics Interpersonal Mass Media
Channels Channels

Message flow Tends to be two-way Tends to be one-way
Communication context Face-to-face Interposed
Amount of feedback available High Low
Ability to overcome selectivity High Low
Speed to large audiences Relatively slow Relatively rapid
Possible effect Attitude formation Knowledge change
and change
Figure 2-2. Distinguishing characteristics of interpersonal and mass media
channels.(Rogers, E.M. and Shoemaker, F.F. 1971 Communication of
innovations: a cross-cultural approach. 2nd Edition. The Free Press. New York,
New York p.46)

In order for biomass to become a useful and economically feasible commodity

which can be relied upon for energy production, there are at least three main

requirements which must be met: 1) the availability of land for energy crops to be grown,

2) the intended crops to be grown must be suitable for use in a co-firing process, 3) and

there must be ideal climates that will allow different types of biomass species to grow.

With its large area and year-round warm weather climate, Florida is an ideal place to

grow energy crops. For example, Short Rotation Woody Crops can be grown from

thousands of acres of land [which can be used as energy feedstock] and other biomass

crops in Florida. Furthermore, central Florida is an ideal place that can produce Short

Rotation Woody Crops since there are large areas of flatwoods, which are typically flat

and poorly drained, and reclaimed phosphate mined lands. These types of terrain can

yield soil types that are capable of supporting biomass production (Stricker et al. 2000).









Florida utility companies, which may choose to produce energy from biomass must

have an adequate number of biomass crops, which have different harvesting periods.

Furthermore, these crops must be grown and harvested throughout the year and be able to

provide a consistent flow of feedstock; these are key elements in a successful biomass-to-

energy system (Stricker et al. 2000). If people perceive biomass as being a form of

technology that will provide them with benefits that are not limited to the environment,

then they may be more willing to pay for bioenergy. Therefore, if consumers of biomass-

produced electricity are the final beneficiaries of bioenergy, then the first individuals to

benefit from biomass production are landowners.

The willingness to grow biomass was measured in a previous survey that was

administered to landowners in Central Florida (Rahmani et al. 1996). Survey results

indicated that, even though most of the landowners were unaware about biomass crops,

they were willing to provide more than 5000ha (12000/A) to grow these crops if there

was a guarantee that they could be assured net returns of $149 per ha ($60/A). These net

returns are valuable since they represent the return to land and management after direct

and indirect production costs (Stricker et al. 1997). Another issue that many Florida

landowners who were willing to grow energy crops must examine is which crops should

be grown.

Because of Florida's warm and humid climate there are a variety of energy

feedstock crops, which can be grown and harvested, furthermore, most of these biomass

crops produce higher yields and do not contribute to environmental problems. Results

from 20 year studies demonstrate that elephant grass, sugarcane, Leucaena, along with

various Eucalyptus species, and slash pine, which produce higher yield potential than









other biomass crops in the area (Stricker et al. 2000). Table 2-1 shows yield rates of

these biomass crops.

Table 2-1. Biomass crop yields in Florida
Biomass crops Dry Mg/ha/yr Dry ton/A/yr
Sugarcane 30-49 14-22
Elephant grass 40 18
Leucaena 35 16
Eucalyptus species 29-40 13-18
Slash pine 21 9

(Stricker, J. A. Rockwood, D.L., Segrest, S.A., Alker, G.R. Prine, G.M., Carter,
Douglas, R.C. 2000. Short rotation woody crops for Florida. University of Florida
Polk County Extension Service and University of Florida School of Forest
Resources and Conservation, The Common Purpose Institute, University of
Florida Agronomy Department)


The acceptance of biomass is determined by the differences in cost rates reductions

for renewable energy technologies and conventional power plants which, in turn, will

affect the relative cost of generated electricity (Neij 1997). Utility providers must also be

responsive to a variety of different needs since they are met with a variety of challenges

and expectations. In California, for example, there is an ongoing debate regarding the

ability existing energy production methods and delivery infrastructures to maintain

reliable day-to-day operations (Asmus 2002). Therefore, the acceptance of the

technology-transfer for using biomass must be determined by effective procedures,

practices, and design structures (Brown and Major 1990), particularly since being able to

quickly deliver a product to meet consumer demand translates into the concept that

accelerated growth is related to innovation that are rapidly produced (Michaels 2000).

Media Related Response to Environmental Issues

Various media can facilitate the use of biomass for producing energy. For

example, the USDA Forest Service and the Northeastern Forest Experiment Station









conducts telephone surveys to obtain the public's opinion for biomass energy production

(Wharton 1991). A very successful component has been the Cooperative Extension

Service, which recognizes the importance of educating children about energy as it relates

to their future (Slack 1983). Furthermore, elementary schools are informed that there is a

direct relationship between environmental education along, nutrition, and energy (State

Office of Public Instruction, 1979).

The National Food Review (NFR) also educates the general public on the

usefulness of plants, such as euphorbia and rapeseed which improve health and can be

also be used as secondary sources of fuel (Stucker and Stucker 1984). The federal

government must further these efforts by developing and maintaining communication

programs, which promote public research and development programs for private sectors

to use biomass (Hillman and Yancey 1998). For example, the adoption of anaerobic

technology as another method of energy production can be examined by analyzing an

agency's budget for research and development of alternative energy technology

(Anderson and Altobello 1982). Therefore, as previously mentioned, the diffusion and

adoption of technologies that promote alternative methods of energy production is a fast-

growing joint effort between classrooms and extension agents (Francis and Madden

1993).

Environmental Benefits Approach

Because of global warming and other important environmental issues, consumers

must be willing to pay more for energy produced from co-firing methods. To raise

consumer awareness, there must be an identification of goods and services that can be

derived from forest resources and timber related products (Mulloy and Ottisch 2000).









Most Midwestern states have taken progressive steps to reduce harmful pollutants

by passing environmental laws or regulations. However, this measure is difficult for

some state legislatures to achieve. For example, difficulty in creating and enforcing

regulatory policies may be due to a lack of the full value of these goods and the decision

itself of how best to utilize them, particularly since lawmakers have difficulty in

incorporating the value of forest products into policy decisions (Buttond 2000).

Lawmakers must further weigh the costs incurred by government when determining if the

policies that are passed will benefit the public (Stoneman 2002).

Even if most people are aware of the immediate benefits of forests, such as

recreation, wildlife areas, and timber, they may think that opportunity costs associated

with biomass are astronomically high because they have little knowledge of the benefits

which can be gained from biomass. In fact, individuals may believe that since the

potential gain of biomass is high, the use of biomass may not be economically feasible.

However, this mindset can be overcome by exploring the relationship of biomass with

other familiar agricultural products and services, such as grazing and hunting (Gluck

2000). If these apprehensions cannot be overcome in such a manner, then people must

understand the risks and benefits of biomass to better choose among it potential success

or failure (Rogers 1998). But even making minimum cost choices can be beneficial

particularly when there are no environmental constraints. In fact, many renewable

technologies are able to become profitable demand devices (Cosmi et al. 2002) since

energy can be produced from biomass by a variety of methods (McKendry 2002).

Overview of Survey Literature

As with any type of data collection survey procedure, the size of any survey

research must be considered and well planned before any research can begin. This advice









is important since it makes prospective researchers consider key items such as the

availability of resources, such as time, money, and available expert assistance (Newman

and McNeil 1998). This warning becomes particularly crucial for assessing the fast

growing global social topic of consumer demand in relation to environmental issues and

considerations.

To assess consumer demand and awareness of biomass and co-firing, surveys have

been conducted throughout parts of the US and various other countries. For example,

Norwegian officials determined that the type of energy production is linked to

socioeconomic information. In Norway, choice probability is impacted by income. For

instance, families with higher income generally use electric heating instead of coal and

wood (Vaage 2000). Although income may have an impact on energy production in

Norway, there may be other determinant factors of how energy is produced within the

other developed countries. In the US, for instance, fossil fuel dependency is from

environmental concern rather than economic status (Bourdaire and Ellis 2000).

Furthermore, The willingness to pay higher premiums for bioenergy is gaining support on

a global scale. In Finland, for example, where bioenergy is the primary source of fuel, if

consumers' willingness to pay can be attributed to the annual growth of biomass, then an

adequate amount of biomass quantities can be produced according to the scale and size of

power plants in Finland (Markku et al. 2003).

Since consumer perception and awareness greatly influence whether or not a

product or a production method will be accepted, it is useful to conduct studies that

measure perception and awareness. One such study was performed using a quasi-

experimental design to assess the perception of environmental risks associated with some









environmental company sites. The study determined that stimuli and personality

variables are related to risk perception, and certain objects or stimuli affect risk

perception (Weber 2001). Given that bioenergy remains a relatively new method of

energy production, researchers caution that the designs and field experiments must be

reliable not only to test the effectiveness of the innovation, but to also maintain internal

and external validity.

Researchers further state it is not adequate to test for the effects of the presence or

absence of the experimental treatment on the dependent variable; instead, the evaluation

design must also test the effectiveness of the intervention on the dependent variable (Caro

and Gottlieb 2001). An important dependent variable that is most frequently measured in

surveys is "willingness to pay."

While survey research can be used in conjunction with experimental and aggregate

data to predict a specific outcome, some researchers may feel that this collection

approach for survey research can be impractical. To combat this problem, researchers

typically rely upon secondary analysis, which is typically previously collected survey

data by someone else (Weisberg et al. 1989). This distinction provides the researcher

with a clearer choice to a cost-benefit analysis. As a result, researchers are made aware

that benefit-cost analysis can be used not only to provide specific answers to difficult

questions, but also for stimulating and organizing thinking questions, such as: 1) How

much money should be spent on a particular study and 2) How to use the results (Pearson

and Boruch 1980)?

When conducting survey research, researchers must select respondents who are

likely to remain within the sample area. To accomplish this, researchers must be aware






15


of respondents' choice of living preferences. For example, Audirac and Smith noted a

previous study, which surveyed 630 Florida residents, indicated that the location and

home type were reasons why people decided to move; this decision to relocate ultimately

may affect survey response results since people who lived in single-family homes were

less likely to relocate. Furthermore, individuals who considered moving preferred less

centralized & dense locations (Audirac and Smith 1992).














CHAPTER 3
METHODS

Participant responses were compiled from a 55-question questionnaire (Appendix

A). The 55 substantive variables measured in this research were categorized into six

subsets: 1) Home and Lifestyle Activity, 2) Home Cooling and Heating, 3) Water

Heaters, Pools, and Spas, 4) Home and Kitchen Appliances, 5) Environmental

Awareness, and 6) Demographics. The questions developed were designed to yield

several types of responses measured by different response scales. For example, survey

responses included 5-point Likert scales, such as "not at all" to "always," "not satisfied"

to "extremely satisfied," "not concerned" to "extremely concerned," and "not willing" to

"extremely willing." Demographics for all survey counties included information such as

gender, income, ethnicity, age, and educational levels.

To ensure that the sample was representative of Florida homeowners, county

selection was based upon population size, demographics, urban and rural differences,

accessibility, coverage area of utility service providers, and projected growth rates. A

randomizer program randomly selected 150 residents from CD listings provided by

county property appraisers. The selected participants were current residents of the

county. No pilot tests were performed because of limitations relating to expense and

length of survey period. Participants were surveyed over a period of five months

beginning in March 2003.

The survey was mailed to five Florida counties: Alachua, Hillsborough, Duval,

Orange, and Polk. County selections were based upon projected growth rates,









geographical access, and a potentially high survey response rate. Participants from each

county received a packet, which included a survey, cover letters) (Appendices B & C),

and a return addressed stamped envelope (Appendix D). The cover letter explained

participants' rights as mandated by the University of Florida's Institutional Review

Board. The letter also informed participants that their identity would remain anonymous,

that there would be no compensation, and also explained the general purpose of the

survey. On the last page of the survey, participants were encouraged to write additional

responses about the survey, or survey questions.

A quasi-experimental design was used. The 55 question survey did not include

pictures, diagrams, or information that might have affected participant response;

however, the GRU brochure "Deerhaven Generating Station Neighbors with Nature"

(Appendix E) included in a follow-up survey mailing in May 2003 did have pictures and

facts relating to GRU's current method of energy production. The GRU brochure was

mailed, along with a survey, to 150 additional residents in Alachua County known as Test

Alachua, or Group B. The purpose of this brochure was to compare the difference in

responses between Group A and Group B about questions, such as willingness to pay

more for safe energy production, awareness of GRU's conservation programs, and

knowledge of GRU's energy production methods. The brochure was only distributed in

Alachua County because residents of the other target counties were not GRU customers.

Because participants were asked to select answers to questions and to provide any

written responses, the data were both objective and subjective. As a label was attached to

each survey for county identification purposes, returned survey responses were coded and

entered using Statistical Package For The Social Sciences (SPSS). Since SPSS generates









data output primarily from numerical responses, the survey was designed to satisfy this

requirement. County identification was achieved by assigning numbers to each county.

County: Alachua (1), Test Alachua (11), Hillsborough (2), Duval (3), Orange (4), and

Polk (5). Records of survey return dates were also recorded. A master file for each

county location included information about participants' name, address, city, and county.

The pre-assigned identification labels were circled using a black marker if the

survey contained any type of participant written response. The responses were generally

found on the last page of the survey since there was a section provided for comments;

however, some participants wrote comments next to survey questions.

Although participants were informed that their anonymity would be maintained,

some surveys were returned with no identification label. As a result, there were five

surveys that could not be identified by one of the five counties. Unidentified surveys

were not used for individual county data reporting purposes; however, they were used to

provide information for other survey categories, such as demographical information.

While planning and preparation of the survey questions were essential to capture

the desired response, there were several instances where participants provided alternative

answers to the survey response choices. For example, on some "yes / no" questions,

participants wrote out "not sure" as their answer. To avoid conducting biased research,

separate response categories for these answers were added to the data output analysis

functionss, and data analyses were performed with the alternative response represented.

Questions that were not answered generated missing totals for that variable, which SPSS

identified as missing systemss. There were a variety of survey results generated from

the data. A key focus of this research relied upon descriptive data, which is demonstrated









primarily through various frequency distributions. In addition to this, t-tests, logistic

regressions, and cross tabulations that produced contingency tables were also conducted.

All variances were assumed to be equal and not equal, and 95% confidence intervals

were used to report F values, and significance levels were determined using an alpha

level of 0.05.

Comparisons between Group A and Group B of Alachua County were conducted

for seven questions (Table 4-9). Each group was drawn from 150 randomly selected

individuals who were assumed to share similar demographical characteristics since they

were all selected from Alachua County. As a treatment or control group, Group B was

given the GRU brochure "Deerhaven Generating Station Neighbors with Nature" to

compare their response to individuals from Group A. A determination for Chi-Square

values was also conducted to measure the observed and expected frequencies of

variables. The test for Chi-Square significance and the measure of association between

variables is based on an Alpha-Level of 0.05 with degrees of freedom calculated as:

df= (r-1)(c-1)














CHAPTER 4
RESULTS AND DISCUSSIONS

For the counties surveyed, responses were received from the following individual

cities and locales: Alachua County Gainesville, High Springs, Newberry, Archer,

Alachua, Hawthorne, and Micanopy, Hillsborough County Tampa, Odessa, and Lutz,

Duval County Jacksonville, Baldwin, Maxville, and Orange Park, Orange County -

Tangerine, Zellwood, Orlando, Apopka, and Plymouth, Polk County Lakeland, Bartow,

Haines City, Frostproof, Fort Meade, and Lake Wales.

Demographic information was a key subset because the collected results provided

statistical information relating to frequency distribution, t-test comparisons, and logistic

regressions.

Overall County Responses

Selected questions analyzed participants' response, awareness levels, and overall

support ofbioenergy. The items in Appendix N present the overall county results for the

remaining survey questions that addressed consumer usage of energy and electricity as it

relates to the home environment, and general questions relating to home and lifestyle

activity. A total of 278 respondents contributed to this survey, for an overall percentage

response rate of 30.9% (Table 4-1). Alachua County had the highest overall number of

responses at 109, or 39.2% of all responses, while Orange County had the lowest number

of responses with 27 participants contributing 9.7% of survey returns.

The 30.9% response rate reflects the predicted percentages of completed and

returned surveys that were mailed from a total of 900 surveys to all of the five surveyed









counties. There was no danger of "participant fatigue" as sampled participants were only

sent the survey twice, and other survey participants could have been selected from the

same sample. Alachua County's 36.3% response rate may be attributed to Alachua

County residents being used to receiving previous surveys conducted by the University of

Florida. As a result, future surveys conducted on Alachua County residents by

University of Florida researchers may continue to report higher response rates than the

same type of research conducted on residents from other counties and by other

researchers.

Table 4-1. Number of responses and percentage of all responses by county (150
surveyed individuals per county).
County Number of Percentage of all
Responses Responses
Alachua 66 23.7
Duval 43 15.5
Hillsborough 50 18.0
Orange 27 9.7
Polk 44 15.8
Test Alachua 43 15.5
Unknown 5 1.8
Total 278 100.0

Respondent Demographics

The overall demographic data (Table 4-2) indicated that 81.7 % of the respondents

were Caucasians, and that 49.3 % of the respondents were male, 47.1% female and .7%

"couples." Participants earning incomes of $50,000 or more had the highest response

rate of 47.5%, and 51-65 was the largest age group.

Some participants chose not to provide some personal information. These

particular instances were categorized as "missing" (Table 4-3). Alachua County had the

highest "missing" percentage, 61.3%, of participants who chose not to answer









demographical questions, and Duval County had the lowest "missing" percentage, 11.6%

of participant nonresponse for demographical questions.

Table 4-2. Overall Response and Respondent Demographics for Alachua (A), Duval (D),
Hillsborough (H), Orange, Polk (P) Counties and Alachua Group B
Demographic County Overall
A D H O P
No. % No. % No. % No. % No % No %
Gender
Male (A) 32 48.5 23 53.5 24 48.0 10 37.0 29 65.9 136 51.3
(B) 18 41.9
Female (A) 28 42.4 20 46.5 24 48.0 17 63.0 14 31.8 127 47.9
(B) 24 55.8
Couple (A) 2 3.1 2 0.7
(Female /
Male)
Income
Less than
$19k (A) 4 6.1 4 9.3 0 0.0 3 11.1 3 8.3 17 7.1
(B) 3 7.0
$20k- $30k (A) 2 3.0 5 11.6 5 10.0 9 33.3 6 6.7 32 13.4
(B) 5 11.6
$30k- $40k (A) 5 7.6 7 16.3 1 2.0 4 14.8 6 16.7 29 12.2
(B) 6 14.0
$40k- $50k (A) 4 6.1 9 20.9 9 18.0 1 3.7 3 8.3 30 12.6
(B) 4 9.3
$50kormore (A) 41 62.1 13 30.2 33 66.0 6 22.2 18 50.0 130 54.6
(B) 19 44.2
Ethnicity
Caucasian (A) 52 78.8 34 79.1 43 86.2 17 63.0 41 93.2 223 85.4
(B) 36 83.7
African (A) 2 3.1 3 7.0 1 2.0 1 3.7 1 2.3 11 4.2
American (B) 3 7.0

Hispanic (A) 1 1.5 0 0.0 3 6.0 1 3.7 1 2.3 6 2.3
(B) 0 0.0
Native (A) 2 3.1 3 7.0 0 0.0 5 18.5 1 2.3 11 4.2
American (B) 0 0.0

Pacific (A) 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0 0 0.0
Islander (B) 0 0.0

Asian (A) 1 1.5 0 0.0 1 2.0 1 3.7 0 0.0 4 1.5
American (B) 1 2.3

Other (A) 1 1.5 3 7.0 1 2.0 0 0.0 0 0.0 6 2.3
(B) 1 2.3









Table 4-2 Continued.
Demographic County Overall
A D H O P
No. % No. % No. % No. % No % No %
Age
26-34 (A) 1 1.5 1 2.3 8 16.0 1 3.7 0 0.0 12 4.5
(B) 1 2.3
35-50 (A) 18 27.3 8 18.6 22 44.0 7 25.9 12 27.3 84 31.6
(B) 17 39.5
51-65 (A)22 33.3 22 51.2 14 28.0 5 18.5 13 29.5 90 33.8
(B) 14 32.6
66 older (A)21 31.8 12 27.9 5 10.0 13 48.1 19 43.2 80 30.1
(B) 10 23.3


Table 4-3. Numbers and percentages of "missing" demographical information for
Alachua (A), Duval (D), Hillsborough (H), Orange (0), Polk (P) and Alachua
Group B
Demographic County Overall
A D H O P No %
No. % No. % No. % No. % No %
Gender
Missing (A) 4 6.1 0 0.0 2 4.0 0 0.0 1 2.3
(B) 1 2.3

Total 5 8.4 0 0.0 2 4.0 0 0.0 1 2.3 8 14.7

Income
Missing (A) 10 15.2 5 11.6 2 4.0 4 14.8 8 18.2
(B) 6 14.0

Total 16 29.2 5 11.6 2 4.0 4 14.8 8 18.2 35 77.8
Ethnicity
Missing (A) 7 10.6 0 0.0 1 2.0 2 7.4 0 0.0
(B)2 4.7

Total 9 15.3 0 0.0 1 2.0 2 7.4 0 0.0 12 24.7
Age
Missing (A) 4 6.1 0 0.0 1 2.0 1 3.7 0 0.0
(B) 1 2.3

Total 5 8.4 0 0.0 1 2.0 1 3.7 0 0.0 7 14.1









While there may be a need for bioenergy researchers to educate and stimulate the

awareness of respondents who represented the demographics with low response rates,

researchers must also be aware that since participants can be randomly selected, there

may be no specific demographical group targeted in some research studies. As a result,

the response rate of individuals from different demographics can vary.

Responses to Environmental Questions

There were several environmental questions asked of participants: 1) Have you

ever heard of the term "Global Warming," 2) Have you ever heard of the term

"Biomass," and 3) Have you ever heard of the term "Co-firing" (Table 4-4).

While these three questions served as introductions to other surveyed variables,

they indicated participants' awareness level of terminology that relates to negative

environmental impacts caused by pollution and the participants' awareness of remedies to

reduce the causes of these harmful impacts.

Although 94.1 % of respondents had heard of global warming, more than half had

not heard ofbiomass or co-firing, 55.7% and 68.1%, respectively. These low awareness

rates may indicate that most Floridians are unaware of the causes of negative

environmental impacts, or the potential solutions to this particular problem. For example,

Duval and Orange Counties had the highest level of participant unawareness of biomass

and co-firing; 65.1% of Duval County respondents had not heard of biomass or co firing,

and 81.5% of Orange County respondents had not heard of co-firing. Furthermore, the

percentages for the unawareness level for biomass and co-firing for Alachua,

Hillsborough, and Polk Counties were also more than 50%; however, residents of

Alachua County were more familiar with biomass than co-firing.









Table 4-4. Participant awareness of environmental terms for Alachua (A), Duval (D),
Hillsborough (H), Orange (0), Polk (P), and Alachua Group B
Question- County Overall
Response A D H O P
No. % No. % No. % No. % No % No %
Heard of
Global
Warming
Yes (A) 64 97.0 41 95.3 47 94.0 23 85.2 40 90.9 257 94.1
(B) 42 97.7
No (A) 0 0.0 1 2.3 2 4.0 1 3.7 2 4.5 7 2.6
(B) 1 2.3
Not Sure (A) 0 0.0 0 0.0 0 0.0 1 3.7 0 0.0 1 .4
(B) 0 0.0
Missing (A) 2 3.0 1 2.3 1 2.0 2 7.4 2 4.5 8 2.9
(B) 0 0.0

Total (A) 66 100.0 43 99.9 50 100.0 27 100.0 44 99.9 273 100.0
(B) 43 100.0

Heard of
Biomass
Yes (A) 35 3.0 14 32.6 18 36.0 8 29.6 13 29.5 111 40.7
(B) 23 53.5
No (A) 30 45.5 28 65.1 31 62.0 16 59.3 28 63.6 152 55.7
(B) 19 44.2
Missing (A) 1 1.5 1 2.3 1 2.0 3 11.1 3 6.8 10 3.7
(B) 1 2.3

Total (A) 66 100.0 43 100.0 50 100.0 27 100.0 44 99.9 273 100.1
(B) 43 100.0
Heard of Co-
firing
Yes (A) 11 16.7 9 20.9 8 16.0 2 7.4 10 22.7 50 18.3
(B) 10 23.3
No (A) 43 65.2 28 65.1 35 70.0 22 81.5 29 65.9 186 68.1
(B) 29 67.4
Not Sure (A) 8 12.1 6 14.0 5 10.0 1 3.7 2 4.5 26 9.5
(B) 4 9.3
Missing (A) 4 6.1 0 0.0 2 4.0 2 7.4 3 6.8 11 4.0
(B) 0 0.0

Total (A) 66 100.1 43 100.0 50 100.0 27 100.0 44 99.9 273 99.9
(B) 43 100.0









Proponents and researchers of bioenergy may derive most of their support for the

passage of environmental laws from individuals between the ages of 35-50, 30.2% of the

sampled population, and between the ages of 51-65 or 33.5%. These age groups are

significant since people within these age groups are more likely to vote, attend

community public meetings, and work within legislatures for the passage of laws. Since

the type of energy production can be linked to income, as suggested by Norway officials,

people with higher incomes are more in favor of bioenergy than those with lower

incomes. As a result, the probability of bioenergy being the preferred method of energy

production increases with income.

Other environmental questions relating to "Green Energy Programs" were different

from those that measured participant awareness of environmental terms because these

questions addressed consumer choice and behavior for the potential gain of

environmental benefits (Table 4-5).

Green Energy Programs" are vital services that can be offered to consumers of

electricity by their local utility company. Utility companies may be more willing to

provide "Green Energy Programs" if there is high consumer demand, and if consumers

are willing to pay higher premiums for bioenergy. "Green Energy Programs" benefit the

environment because they rely upon alternative methods of energy production rather than

on current conventional methods, which emit harmful levels of pollutants into the Earth's

atmosphere, thereby causing global warming. The results of "Green Energy Programs"

are similar to those of biomass and co-firing because a significant amount, 52.8%, of

participants, who are either unaware if their local utility company has a "Green Energy









Program." Furthermore, 59.7% of participants are unsure if they would subscribe to

"Green Energy Programs" if their local utility company provided one.

Table 4-5. Participant response to choice related topics for environmental benefits for
Alachua (A), Duval (D), Hillsborough (H), Orange (0), Polk (P), and Alachua
Group B
Question- County Overall
Response A D H O P
No. % No. % No. % No. % No % No %
Aware if
Utility has
"Green Energy
Program"

Yes (A) 18 27.3 2 4.7 8 16.0 3 11.1 12 27.3 56 20.5
(B) 13 30.2
No (A) 18 27.3 10 23.3 12 24.0 8 29.6 9 20.5 64 23.4
(B) 7 16.3
Not Sure (A) 29 43.9 29 67.4 29 58.0 14 51.9 21 47.7 144 52.8
(B) 22 51.2
Yes /Not Sure (A) 0 0.0 1 2.3 0 0.0 0 0.0 0 0.0 2 .7
(B) 1 2.3

Missing (A) 1 1.5 1 2.3 1 2.0 2 7.4 2 4.5 7 2.6
(B) 0 0.0

Total (A) 66 100.0 43 100.0 50 100.0 27 100.0 44 100.0 273 100.0
(B)43 100.0

Subscribes to
"Green Energy
Program"

Yes (A) 2 3.0 2 4.7 3 6.0 2 7.4 5 11.4 16 5.9
(B) 2 4.7
No (A) 37 56.1 13 30.2 17 34.0 6 22.2 18 40.9 108 39.6
(B) 17 39.5
Not Sure (A) 13 19.7 9 20.9 18 36.0 10 37.0 6 13.6 69 25.2
(B) 13 30.2
Missing (A) 14 21.2 19 44.2 12 24.0 9 33.3 15 34.1 80 29.3
(B) 11 25.6

Total (A) 66 100.0 43 100.0 50 100.0 27 99.9 44 100.0 273 100.0
(B) 43 100.0









Table 4-5 Continued
Would
subscribe to
"Green Energy
Program"

Yes (A) 16 24.2 11 25.6 12 24.0 6 22.2 6 13.6 64 23.4
(B) 13 30.2
No (A) 3 4.5 2 4.7 1 2.0 1 3.7 6 13.6 14 5.1
(B) 1 2.3
Not Sure (A) 41 62.1 24 55.8 30 60.0 17 63.0 24 54.5 163 59.7
(B) 27 62.8
Missing (A) 6 9.1 6 14.0 7 14.0 3 11.1 8 18.2 32 11.7
(B) 2 4.7

Total (A) 66 100.0 43 100.1 50 100.0 27 100.0 44 99.9 273 99.9
(B)43 100.0


The large amount of skepticism surrounding these types of programs, which may

not entirely indicate a high level of unawareness of Green Energy (as later survey results

will show), but rather a need for the general public to be educated about what "Green

Energy Programs" are, how "Green Energy" can be provided, and the benefits of "Green

Energy." An equally challenging question though is who shall educate bioenergy

researchers, or utility companies. Public service messages presenting the benefits of

bioenergy can also be useful to educate people of the potential for this kind of

technology.

Only 5.9% of participants indicated that they currently subscribe to a "Green

Energy Program." Polk County had the highest overall subscription rate with 11.4%,

while Duval County had the lowest, 4.7%. One potential reason why Polk County had

the highest percentage of subscribers to "Green Energy Programs" is because some of its

residents may subscribe to utility companies that offer "Green Energy" and because of

Polk County's geographic characteristics. Compared to the other surveyed counties, Polk









County is a relatively large, rural area with locations where energy crops can be grown

for co-firing. Furthermore, because of its size, Polk County has more utility providers

than most Florida counties. As a result, utility customers can be provided with more

options and opportunities for energy source selections.

Although there were high percentages of participants that answered "No" or "Not

sure" to the questions about the awareness of environmental terminology (Table 4-6),

participant support and willingness to pay for bioenergy was relatively high. For

example, 39.6% of respondents were somewhat supportive of bioenergy, and 54.9% were

willing to pay more for energy production methods that were environmentally safe, and

39.6 % were willing to pay at least an additional $20 for clean energy.

Participants were later asked to provide responses relating to their local utility

companies. In response to Do you know how your local utility company produces

electricity, 60.4% were aware of how their local utility company produced energy, and

21.2% were unsure and 15.8% did not know how energy is produced in their

communities (Table 4-7). Local utility providers can raise consumer awareness levels

about energy by actively increasing public awareness, establishing the support of the

business sector, and verifying the controls over utilities' power trading, and governmental

regulation (Gan 2002). Utility companies can increase public awareness of how their

energy is produced locally by providing guided tours, public service broadcasts,

utilization of county extension agents, and other means of community involvement.

Utility companies can benefit from knowing consumers' awareness level of energy since

consumers who are more aware of energy may be more likely to practice energy









conservation methods, which can reduce the instances of "blackouts" caused by

overloaded power grids

While consumer satisfaction with local utility companies efforts to promote energy

conservation appears high, there was some differences in level of satisfaction; 39.9%

were somewhat satisfied, and 35.9% were satisfied. Participants' responses may have

been influenced by their current utility bills, or by their own conservation behaviors to

reduce their monthly electric bill. Utility companies were not surveyed in their efforts to

promote energy conservation, or their energy conservation methods.

Table 4-6. Support and willingness to pay additional dollars for production of clean
energy for Alachua (A), Duval (D), Hillsborough (H), Orange (0), Polk (P),
and Alachua Group B
Question- County Overall
Response A D H O P
No. % No. % No. % No. % No % No %
Support for
paying a
higher cost for
cleaner energy

Not Supportive (A) 10 15.2 10 23.3 3 6.0 4 14.8 2 4.5 34 12.4
(B) 5 11.6
Somewhat (A) 23 34.8 15 4.9 20 40.0 9 33.3 23 52.3 108 39.6
Supportive (B) 18 41.9

Supportive (A) 16 24.2 12 27.9 16 32.0 9 33.3 10 22.7 75 27.5
(B) 12 27.9
Very (A) 8 12.1 2 4.7 8 16.0 3 11.1 4 9.1 29 10.6
Supportive (B) 4 9.3

Extremely (A) 1 1.5 3 7.0 1 2.0 0 0.0 0 0.0 7 2.6
Supportive (B) 2 4.7

Not Sure (A) 1 1.5 0 0.0 0 0.0 0 0.0 0 0.0 2 .7
(B) 1 2.3
Missing (A) 7 10.6 1 2.3 2 4.0 2 7.4 5 11.4 18 6.6
(B) 1 2.3
Total (A) 66 99.9 43 100.1 50 100.0 27 99.9 4 100.0 273 100.0
(B) 43 100.0










Table 4-6 Continued
Question- County Overall
Response A D H O P
No. % No. % No. % No. % No % No %
Willingness
to pay more
for cleaner
energy

Yes (A) 35 53.0 21 48.8 32 64.0 14 51.9 22 50.0 150 54.9
(B) 26 60.5
No (A) 22 33.3 19 44.2 14 28.0 10 37.0 14 31.8 93 34.0
(B) 14 32.6
Not Sure (A) 0 0.0 1 2.3 0 0.0 0 0.0 0 0.0 1 .4
(B) 0 0.0
Missing (A) 9 13.6 2 4.7 4 8.0 3 11.1 8 18.2 29 10.6
(B) 3 7.0

Total (A) 66 99.9 43 100.0 50 100.0 27 100.0 44 100.0 273 99.9
(B) 43 100.1
Additional
dollars
willing to
pay for
cleaner
energy

$5-$20 (A) 26 39.4 11 25.6 26 52.0 10 37.0 17 38.6 108 39.6
(B) 18 41.9
$20-$25 (A) 5 7.6 8 18.6 4 8.0 2 7.4 5 11.4 30 11.0
(B) 6 14.0
$25-$30 (A) 4 6.1 1 2.3 3 6.0 1 3.7 2 4.5 12 4.4
(B) 1 2.3
$35 or more (A) 1 1.5 1 2.3 1 2.0 1 3.7 1 2.3 6 2.2
(B) 1 2.3
Missing (A) 30 45.5 22 51.2 16 32.0 13 48.1 19 43.2 117 42.9
(B) 17 39.5
Total (A) 66 100.1 43 100.0 50 100.0 27 99.9 44 100.0 273 100.1
(B) 43 100.0










Table 4-7. Knowledge of local utility energy production, satisfaction of energy
conservation efforts, and willingness to pay higher cost for environmental
benefits for Alachua (A), Duval (D), Hillsborough (H), Orange (0), Polk (P),
and Alachua Group B
Question- County Overall
Response A D H O P
No. % No % No. % No. % No % No %
Knows how
local utility
company
produces
electricity

Yes (A) 41 62.1 25 58.1 29 58.0 9 33.3 31 70.5 165 60.4
(B) 30 69.8
No (A) 8 12.1 9 20.9 11 22.0 8 29.6 3 6.8 43 15.8
(B) 4 9.3
Not Sure (A) 16 24.2 8 18.6 9 18.0 9 33.3 8 18.2 58 21.2
(B) 8 18.6
Missing (A) 1 1.5 1 2.3 1 2.0 1 3.7 2 4.5 7 2.6
(B) 1 2.3

Total (A) 66 99.9 43 99.9 50 100.0 27 99.9 44 100.0 273 100.0
(B) 43 100.0
Satisfaction
rate of utility
company s
effort of
energy
conservation

Not Satisfied (A) 9 13.6 0 0.0 6 12.0 2 7.4 3 6.8 25 9.1
(B) 5 11.6 15 34.9 24 48.0 15 34.1
Somewhat (A) 27 40.9 21 48.8 15 30.0 13 48.1 16 36.4 109 39.9
Satisfied (B) 15 34.9 10 37.0 98 35.9

Satisfied (A) 20 30.3 5 11.6 3 6.0 0 0.0 4 9.1 18 6.6
(B) 16 37.2
Very Satisfied (A) 2 3.0 1 2.3 0 0.0 0 0.0 0 0.0 1 .4
(B) 4 9.3
Extremely (A) 0 0.0 1 2.3 2 4.0 2 7.4 6 13.6 22 8.1
Satisfied (B) 0 0.0
(A) 8 12.1
Missing (B) 3 7.0

Total (A) 66 99.1 43 99.9 50 100.0 27 99.9 44100.0 273 100.0
(B) 43 100.0










Table 4-7. Continued
Question- County Overall
Response A D H O P
No. % No % No. % No. % No % No %
Higher cost
for benefits

Not (A) 11 16.7 9 20.9 3 6.0 5 18.5 3 6.8 35 12.8
Willing (B) 4 9.3 17 39.5 24 48.0 11 40.7 21 47.7 104 38.1

Somewhat (A) 19 28.8 13 30.2 15 30.0 6 22.2 13 29.5 82 30.0
Willing (B) 12 27.9 1 2.3 6 12.0 2 7.4 2 4.5 20 7.3

Willing (A) 20 30.3 0 0.0 0 0.0 1 3.7 0 0.0 5 1.8
(B) 15 34.9
Very (A) 4 6.1 3 7.0 2 4.0 2 7.4 5 1.4 27 9.9
Willing (B) 5 11.6

Extremely (A) 3 4.5
Willing (B) 1 2.3

Missing (A) 9 13.6
(B) 6 14.0
Total (A) 66 100 43 99.9 50 100 27 99.9 44 99.9 273 99.9
(B) 43 100


If however, the utility companies within the target counties are indeed actively promoting

energy conservation practices, the low awareness of environmental terms in this study

suggests that their efforts of promoting alternative forms of energy production is low or

ambiguous.

Even though the traditional method of generating electricity caused environmental

destruction, the environmental benefits of using renewable energy technologies are still

well-known (Morgenstern 2002), at least 30% of the participants were willing to pay

higher costs to have the benefit of a cleaner environment, and 38.1% were somewhat

willing even though the knowledge of environmental remedies, such as biomass or co-









firing which can be used to reduce levels of harmful pollutants, is low (Table 4-4). If

people are educated about the benefits of biomass and co-firing, the awareness levels of

potential alternative energy production methods will grow, as will people's willingness to

pay for environmental benefits.

Table 4-8 indicates the results of T-test of Independent samples, which was used

to compare the means of Group A and Group B. There were no significant differences at

a 0.05 Alpha Significance Level between residents who received the GRU brochure

"Deerhaven Generating Station Neighbors with Nature", Group B, and those who did not

Group A. A reason for this may be related to the fact that GRU is the primary electricity

provider for Alachua County. Although smaller utility companies, such as Clay Electric,

may provide electricity to Alachua residents, some residents may be aware that small

utility companies frequently purchase power from larger utility providers. As a result,

residents may feel that there is no difference in energy production between two electric

companies within the same county. An additional reason why there may be no

significance between Group A and Group B may be because brochures may not be ideal

forms of media which can generate significant responses between members within the

same sampled population. Responses can also be provided in the form of behavior,

which can be controlled or determined by advertising through various types of media.

For instance, in the earlier 70's, to educate people about the dangers of forest fires, the

USDA Forest Service used "Smokey The Bear" as a national spokesperson to remind and

educate people that "only you can prevent forest fires... only you."









Table 4-8. Summary of nonsignificant t-tests of Independent samples for a comparison
of the means of Group A and Group B Alachua County homeowners on
knowledge and willingness to pay for safe energy and subscriptions to "Green
Energy Programs."


County
Alachua
N X


Willing to pay more for safe
environmentally safe energy
production.

Aware if local utility has
"Green Energy Program".

Would subscribe to "Green
Energy Program" if local
utility provided one.

Knows how local utility
company produces energy.

Support of paying higher
premiums for cleaner energy.

Satisfaction of local utility
company's efforts to promote
energy conservation.

Willingness to pay higher
costs for environmental benefits.


57 1.39



65 2.16


60 2.44



65 1.63


59 2.48


58 2.28



57 2.45


Test Alachua


40 1.35



43 2.26


41 2.34



42 1.48


42 2.60


40 2.48



37 2.65


Survey Remarks

Internal validity was an important concern throughout this research. Since the

goal was to survey 150 residents from each county (excluding the 150 additional Alachua

County residents in Group B), the mortality rates (nonrespondents and exclusions) for

each county was represented as mail-related occurrences, such as bad addresses, no such

person at this address, commercial businesses which were inadvertently selected during


Question









the randomized selection process, and people who owned property in the target county,

but did not physically live in that county. Situations such as these warranted methods of

"double-dipping," or reselecting participants from the sample population.

Demographic information made available to researchers or proponents of biomass

is necessary because efforts can not only be directed towards those who support biomass

and co-firing, but also to individuals who may have little or no knowledge of alternative

energy production methods. Since there was a low response rate among minority groups,

and no response from people between the ages of 18-25, educational efforts of alternative

energy production should begin within these segments of the general population.

Table 4-9 presents demographic results for environmental questions, which were

analyzed using a Logistic Regression method. Although each independent variable

demonstrated a level of significance for each question, not all dependent variables were

significant. The variation in significance for dependent variables is due to some

independent variables being far less significant than others. Significance was determined

at a .05 Alpha-Level.

The independent variable that was significant more times than any other

independent variables was the education level of participants. This is important since

educational levels may have larger influences on the choices regarding bioenergy and

other choice-related topics. Furthermore, when a person has ample information about a

particular topic or even new types of technology, such as co-firing, that person may

perceive the benefit of this new type of technology and become more likely to adopt it.

The age and gender independent variables both demonstrated significance at least three

times, while ethnicity was significant in only one case scenario.











Table 4-9. Logistic regression coefficients (b) and their standard errors (SE) and
significance (*, at the 0.05 level by the Wald test) for demographic variables
Education, Gender, Ethnicity, Age, and Income in predicting responses to
survey questions (in bold).
Statistic Constant Education Gender Ethnicity Age Income
Heard of Global Warming
B -6.752 .054 .588 .457 .464 -1.029*
SE 4.275 .064 1.185 .295 .711 .501
Heard of Biomass
B 5.995 -.084* -.788* .165 -.112 -.173
SE 1.305 .023 .305 .125 .181 .132
Heard of Co-firing
B 3.274 .011 -1.260* -.107 .044 -.080
SE 1.393 .024 .387 .126 .211 .161
Aware if local utility company has a "Green Energy Program"
B 4.309 -.091* -.151 -.173 .226 .181
SE 1.422 .027 .354 .120 .209 .151
Subscribes to local utility's "Green Energy Program"
B -2.731 -.020 -.884 5.556 .175 .357
SE 24.069 .043 .716 23.919 .389 .252
Would subscribe "Green Energy Program" if local utility provided one
B 1.794 -.037 -.170 -.123 .245 .080
SE 1.267 .023 .329 .124 .193 .140
Knows how local utility produces energy
B 5.376* -.053* -.830 .059 -.304 -.308
SE 1.323 .022 .307 .120 .184 .126
Support of paying higher premiums for cleaner energy
B 1.747 .069* -.044 -.116 -.371 -.228
SE 1.802 .031 .457 .151 .279 .199
Satisfaction of local utility company's effort to promote energy conservation
B -2.010 .021 .137 .090 .694* .088
SE 1.874 .033 .469 .229 .274 .190
Willing to pay more for environmentally safe energy production
B .038 -.071* -.006 .182 .336 .185
SE 1.251 .024 .315 .115 .191 1.251
Willingness to pay higher costs for environmental benefits
B 1.014 .091* -.237 -.157 -.378 -.231
SE 1.702 .030 .431 .139 .263 .187









Appendices F-K presents the results of contingency tables for the following six

dependent variables:

1) Have you heard of "Global Warming"?

2) Have you heard of"Biomass"?

3) Have you heard of "Co-firing"?

4) Do you know if your local utility company has a "Green Energy Program"?

5) Would you subscribe to a "Green Energy Program" if your local utility company

provided one?

6) Are you willing to pay more money towards your electric bill for energy production

methods that are environmentally safe?

The Chi-Square values included within the Contingency Tables are useful because

they indicate a measure of how close the observed frequencies are to the frequencies of

independent variables (Agresti 1986). Furthermore, the size of the Chi-Square value can

also be used to determine how strong the association is between variables in the reported

data.

The large Chi-Square values for the independent variables, income and ethnicity,

were significant factors for participant's knowledge or awareness of global warming.

Furthermore, the Chi-Square values of income and gender were also significant

participants were asked if they had heard of biomass. Gender was the only variable to

demonstrate significance for determining if a participant heard of co-firing; in fact, 14.4%

of males indicated they had heard of co-firing and 40.9% of females indicated they had

not heard of co-firing.









Almost all of the participants within each surveyed demographic (income, gender,

age, and ethnicity) indicated that they had heard of global warming. Participants earning

salaries between $30K-$40K and $50K or more had the highest the highest overall

awareness level of global warming. Females had a lower awareness level than males, and

participants who identified themselves as "couples" had the highest rate of awareness.

Participants who were between the ages of 26-34 and 51-65 had a higher awareness level

than the other age categories, while respondents who were 66 or older had the lowest

awareness level of global warming. African Americans had the highest awareness level

of global warming, while Caucasians had the lowest awareness level.

The awareness level of biomass was highest among participants earning $50k or

more and the lowest among those earning between $20K-$30K. Females had a lower

awareness level about biomass than males. Individuals between the ages of 51-65 had

the lowest awareness level compared to participants who were 26-34 years of old. All

ethnic groups had a high rate of unawareness of biomass.

A high rate of unawareness about co-firing existed among all income levels.

Females were less aware of co-firing than males. Respondents between the ages of 51-65

had the lowest awareness rate, and Hispanics represented the lowest awareness level of

co-firing.

All income levels had a high rate of unawareness of knowing if their local utility

companies had "Green Energy Programs." Males were more aware about "Green Energy

Programs." Ages 51-65 represented the largest group, which did of "Green Energy

Programs." Caucasians had the highest awareness level about "Green Energy Programs,"

while the other ethnic groups' unawareness rates were similar.









When asked if participants would subscribe to a "Green Energy Program" if was

provided by their local utility company, there was a high rate of uncertainty among all

income levels. Respondents between the ages of 35-50 were most likely to subscribe to

"Green Energy Programs" than any other age category. Caucasians represented the

large ethnic group that would subscribe to "Green Energy Programs."

Participants earning $50K or more are willing to pay more for environmentally

safe energy production than people in the other income levels. Females are also willing

to pay more than males for safer energy production. Individuals between ages 26-34

were indicated that they were also willing to pay more for safer energy production. In

fact, only one individual between the ages of 26-34 reported they were not willing to pay

more. African Americans were least willing to pay more for safe energy production,

while Caucasians were the ethnic group that was most willing to pay more.

Appendices L-M present the overall county results of questions from the sections

of the survey that addressed home type, energy consumption, home and community

lifestyle, and other environmental awareness type questions; these survey sections were:

1) Home and Lifestyle Activity, 2) Home Cooling and Heating, 3) Water Heaters, Pools,

and Spas, 4) Home and Kitchen Appliances, and 5) Environmental Awareness.














CHAPTER 5
CONCLUSIONS

Since 55.7% of participants were unaware of biomass and 68.1% were unaware of

co-firing, there is a need to educate the public about alternative methods that can be used

to promote a healthy environment. Effective ways of educating the public include

utilizing educational and community service programs that rely upon mass

communication medium, such as television, newspapers, Internet, and radio for the

dissemination of energy conservation and alternative production programs to the general

public. Counties that exhibit a greater awareness and a willingness to pay for alternative

forms of energy should also be viewed as potential locations where proponents of

bioenergy can gain support.

A total of 23.5% of the participants had not heard of "Green Energy Programs,"

and 52.8% were also unsure if they heard these programs. Therefore, an emphasis to

educate the public must also be placed on such programs since they are instrumental for

educating the public about alternative forms of energy.

While the sustainability of natural resources may continue to be a concern for most

individuals, a gap remains between achieving sustainability and the desire for

sustainability. To close this gap, researchers of biomass, its proponents, utility

companies, and perhaps legislatures must work together to make niche market

technologies, such as co-firing not only an environmentally safe alternative method to









produce energy, but a financially sound measure as well. Therefore, education of the

public is critical if public support and demand for the potential of biomass is to be

realized.

Because Florida is an ideal place for growing tree species that are suitable for co-

firing, Florida utility companies should seek locations where energy crops can be grown.

Large rural regions such as Polk County can be ideal for this purpose. The concept of

"willingness to pay" should continue to be explored particularly in its relation to the

causes or reasons why respondents may indicate willingness for or against paying higher

premiums for safer energy.














CHAPTER 6
FUTURE RESEARCH

This study can benefit from post surveys or longitudinal type studies that measure

the difference in participant response after a period of time. While this survey included

six sections, other sections could be added to the survey that could analyze consumer

choice, or incentives for home-type selection, allocation for additional bioenergy

revenues contributed from consumers, and preferences) for alternative energy production

methods analysis. Researchers who wish to continue this study may also conduct short

telephone surveys to allow participants to feel as if they are more a part of the research

because they are talking directly to an individual.

To include the missing demographics of this research in future studies, such as

missing minority groups and people between the ages of 18-25, surveys similar to this

research can benefit from larger sample sizes, or conducting cross sectional surveys to

capture respondents from every county within a particular state.













APPENDIX A
SURVEY: ENVIRONMENTAL VALUES AND AWARENESS OF FLORIDA
RESIDENTS


IF AS


Environmental Values and Awareness of
Florida Residents


Figure A-1. Environmental values and awareness of Florida residents



















APPENDIX B
INITIAL COVER LETTER




UNIVERSITY OF
FLORIDA

IFA S 118 NewinsZielger Hal
PO Box 110410
School of Forest Resources and Conservation Gainesville, PL 32611-0410
Phone: (352) 46-3054
Fax: (352) 846-1277
http://www.sfr.ufLedu

Dear Survey Participant:

Hello. I am a graduate student in the School of Forest Resources and Conservation at the
University of Florida, and I am conducting research that relates to energy production,
environmental issues, and natural resource conservation. The purpose of this study is to assess
Florida residents' attitudes and awareness about each of those topics. As a Florida resident, you
have been selected to participate within this study.

The results of this study will provide researchers with valuable information about public response
for reducing negative environmental effects, producing energy from methods that are ecologically
safe, and for conserving vital natural resources for future generations. Each participant will
remain anonymous, and you will not be contacted by anyone about participating in the survey.
The estimated time to complete the survey takes about 15 minutes, and a pre-paid postage return
envelope has been included to provide an easy return of the survey.

Although you do not have to complete any or all of this survey, it would be helpful if you could
complete as many questions as possible. Again, you do not have to answer any question you do
not wish to answer. While you will not be compensated, your participation in this survey is
greatly appreciated.

Thank you in advance for your participation. If you have any questions about this research,
please contact me at (352) 846-3054, or my graduate chair, Dr. Donald Rockwood, at (352) 846-
0897. Any questions or concerns about participants' rights may be directed to the UF IRB Office,
University of Florida, PO. Box 112250, Gainesville, FL. 32611-2250, (352) 392-0433.

Thank you,



Mark Adams
Graduate Research Assistant






EqualOpporFtmity/Affirve Ati.on J.sbttfion



Figure B-l. Initial cover letter



















APPENDIX C
FOLLOW-UP COVER LETTER





UNIVERSITY OF

FLORIDA

IFA S 118 Newins-Zielger Hall
PO Box 110410
School of Forest Resources and Conservation Gainesville, FL 32611-0410
Phone: (352) 846-3054
Fax: (352) 846-1277
http://www.sfc.ufl.edu


Dear Survey Participant:

Hello. I am a graduate student in the School of Forest Resources and Conservation at the
University of Florida, and I am conducting research that relates to energy production,
environmental issues, and natural resource conservation. The purpose of this study is to assess
Florida residents' attitudes and awareness about each of those topics. As a Florida resident, you
have been selected to participate within this study.

We are writing to you again because we have not received your response regarding the
Environmental Values and Awareness of Florida Residents survey. While you may feel that
your survey response does not make a difference, as a Florida resident, your opinions on
environmental issues is extremely important because they provide researchers with valuable
information about public response for reducing negative environmental effects, producing energy
from methods that are ecologically safe, and for conserving vital natural resources for future
generations.

Again, each participant will remain anonymous, and you will not be contacted by anyone about
participating in the survey. The estimated time to complete the survey takes about 15 minutes,
and a pre-paid postage return envelope has been included to provide an easy return of the survey.

Although you do not have to complete any or all of this survey or answer any question you do not
wish to answer, it would be helpful if you could complete as many questions as possible. While
you will not be compensated, your participation in this survey is greatly appreciated.

Thank you in advance for your participation. If you have any questions about this research,
please contact me at (352) 846-3054, or my graduate chair, Dr. Donald Rockwood, at (352) 846-
0897. Any questions or concerns about participants' rights may be directed to the UF IRB Office,
University of Florida, P.O. Box 112250, Gainesville, FL. 32611-2250, (352) 392-0433.

Thank you,



Mark Adams
Graduate Research Assistant


Eqal Opporunity/Affirmahve ActionA hution



Figure C-1. Follow-up cover letter

















APPENDIX D
RETURN ADDRESSED STAMPED ENVELOPE



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APPENDIX E
GRU BROCHURE: DEERHAVEN GENERATING STATION NEIGHBORS WITH
NATURE


Figure E-1. GRU Brochure: Deerhaven generating station neighbors with nature















APPENDIX F
CONTINGENCY TABLE AND CHI-SQUARE VALUES FOR GLOBAL WARMING,
ALTERNATIVE ENERGY METHODS, AND WILLINGESS TO PAY MORE FOR
SAFE ENERGY

Table F-1. Heard of global warming
Response
Demographic Yes % No % Not Sure % Total % Chi-Square
Gender
Male 132 50.2 1 .38 1 .38 134 51.0

Female 121 46.0 5 1.9 1 .38 127 48.3

Couple (Female / Male) 2 .7 0 0.0 0 0.0 2 .8

Total 255 97.0 6 2.3 2 .7 263 100.0 3.045
Income
Less than $19k 15 6.4 2 .8 0 0.0 17 7.2

$20k- $30k 28 11.9 2 .8 1 .4 31 3.1

$30k- $40k 28 11.9 0 0.0 0 0.0 28 11.9

$40k $50k 27 1.4 2 .8 0 0.0 29 12.3

$50k or more 131 55.5 0 0.0 0 0.0 131 55.5

Total 229 97.0 6 2.3 1 .4 236 99.9 20.838*
Ethnicity
Caucasian 221 85.0 3 1.2 1 .4 225 86.5
African American 10 3.8 0 0.0 0 0.0 10 3.8
Hispanic 4 1.5 2 .8 0 0.0 6 2.3
Native American 8 3.1 0 0.0 1 .4 9 3.5
Asian American 3 1.2 1 .4 0 0.0 4 1.5
Other 6 2.3 0 0.0 0 0.0 6 2.3
Total 252 96.9 6 2.3 2 .8 260 100.0 49.358*
Age
26-34 12 4.6 0 0.0 0 0.0 12 4.6
35-50 81 30.8 2 .8 0 0.0 83 31.6
51-65 90 34.2 0 0.0 0 0.0 90 34.2
66 older 71 27.0 5 1.9 2 .8 78 29.7
Total 254 96.6 7 2.7 2 .8 263 100.0 11.978
*Significance at 0.05 Alpha-Level










Table F-2. Heard of biomass
Demographic Response
Yes % No % Total % Chi-Square
Gender
Male 72 27.7 61 23.5 133 51.2

Female 36 13.8 89 34.2 125 48.1

Couple (Female / Male) 1 .4 1 .4 2 .8

Total 109 41.9 151 58.1 260 100.0 17.042*
Income
Less than $19k 3 1.3 13 5.6 16 6.8

$20k- $30k 8 3.4 23 9.8 31 13.2

$30k- $40k 10 4.3 17 7.3 27 11.5

$40k- $50k 11 4.7 18 7.7 29 12.4

$50k or more 71 30.3 60 25.6 131 56.0

Total 103 44.0 131 56.0 234 100.0 14.798*
Ethnicity
Caucasian 97 37.7 125 48.6 222 86.4
African American 2 .8 8 3.1 10 3.9
Hispanic 1 .4 4 1.6 5 1.9
Native American 1 .4 9 3.5 10 3.9
Asian American 1 .4 3 1.2 4 1.6
Other 4 1.6 2 .8 6 2.3
Total 106 41.2 151 58.8 257 100.0 10.095
Age
26-34 4 1.5 8 3.1 12 4.6
35-50 35 13.4 49 18.8 84 32.2
51-65 40 15.3 50 19.2 90 34.5
66 older 29 11.1 46 17.6 75 28.7
Total 108 41.4 153 58.6 261 100.0 .899
Significant at 0.05 Alpha-Level










Table F-3. Heard of Co-firing
Demographic Response
Yes % No % Not Sure % Total % Chi-Square
Gender
Male 38 14.4 78 29.5 18 6.8 134 50.8

Female 11 4.2 108 40.9 9 3.4 128 48.5

Couple (Female / Male) 1 .4 1 .4 0 0.0 2 .8

Total
50 18.9 187 70.8 27 10.2 264 100.0 23.810*

Income
Less than $19k 2 .8 12 5.0 3 1.3 17 7.1

$20k- $30k 5 2.1 25 10.4 2 .8 32 13.3

$30k- $40k 4 1.7 24 10.0 1 .4 29 12.1

$40k- $50k 3 1.3 21 8.8 6 2.5 30 12.5

$50kormore 32 13.3 88 36.7 12 5.0 132 55.0

Total 46 19.2 170 70.8 24 10.0 240 100.0 11.169
Ethnicity
Caucasian 44 16.9 156 60.0 22 8.5 222 85.4
African American 1 .4 10 3.8 1 .4 12 4.6
Hispanic 0 0.0 6 2.3 0 0.0 6 2.3
Native American 1 1.4 7 2.7 2 .8 10 3.8
Asian American 0 0.0 3 1.2 1 .4 4 1.5
Other 3 1.2 3 1.2 0 0.0 6 2.3
Total 252 18.8 185 71.1 26 10.0 260 100.0 12.941
Age
26-34 1 .4 10 3.8 1 .4 12 4.5
35-50 21 8.0 54 20.5 9 3.4 84 31.8
51-65 12 4.5 73 27.7 8 3.0 93 35.2
66 older 15 5.7 51 19.3 9 3.4 75 28.4
Total 49 18.6 188 71.2 27 10.2 264 100.0 6.387
* Significance at 0.05 Alpha-Level










Table F-4. Aware if local utility company has green energy program
Demographic Response
Yes % No % Not Sure % Total % Chi-Square
Gender
Male 30 11.5 28 10.7 74 28.3 132 50.6

Female 25 9.6 35 13.4 67 25.7 127 48.7

Couple (Female / Male) 0 0.0 0 0.0
2 .8 2 .8
Total
55 21.1 63 24.1 143 54.8 261 100.0 5.111

Income
Less than $19k 2 .8 8 3.4 8 3.4 18 7.6

$20k- $30k 8 3.4 7 3.0 17 7.2 32 13.5

$30k $40k 6 2.5 6 2.5 15 6.3 27 11.4

$40k- $50k 7 3.0 5 2.1 17 7.2 29 12.2

$50k ormore 26 11.0 27 11.4 78 32.9 131 55.3

Total 49 20.7 53 22.4 135 57.0 237 100.0 14.089
Ethnicity
Caucasian 45 17.4 51 19.8 125 48.4 221 85.7
African American 2 .8 2 .8 6 2.3 10 3.9
Hispanic 1 .4 1 .4 4 1.6 6 2.3
Native American 2 .2 3 1.2 6 2.3 11 4.3
Asian American 2 .2 1 .4 1 .4 4 1.6
Other 2 .2 3 1.2 1 .4 6 2.3
Total 54 20.9 61 23.6 143 55.4 258 100.0 12.367
Age
26-34 4 1.5 1 .4 7 2.7 12 4.6
35-50 18 6.9 20 7.6 45 17.2 83 31.7
51-65 19 7.3 17 6.5 53 20.2 89 34.0
66 older 14 5.3 25 9.5 39 14.9 78 29.8
Total 55 21.0 63 24.0 144 55.0 262 100.0 7.258










Table F-5. Subscribe to a Green Energy Program
Demographic Response
Yes % No % Not Sure % Total % Chi-Square
Gender
Male 31 13.2 10 4.3 79 33.6 120 51.1

Female 30 12.8 3 1.3 80 34.0 113 48.1

Couple (Female / Male) 2 .9 0 0.0 0 0.0 2 .9

Total 63 26.8 13 5.5 159 67.7 235 100.0 9.122

Income
Less than $19k 2 .9 1 .5 11 5.1 14 6.5

$20k- $30k 9 4.2 4 1.9 14 6.5 27 12.6

$30k- $40k 6 2.8 0 0.0 19 8.8 25 11.6

$40k- $50k 8 3.7 0 0.0 19 8.8 27 12.6

$50k or more 34 15.8 9 4.2 79 36.7 122 56.7

Total 59 27.4 14 6.5 142 66.0 215 99.9 9.420
Ethnicity
Caucasian 52 22.3 9 3.9 139 59.7 200 85.8
African American 3 1.3 1 .4 5 2.1 9 3.9
Hispanic 1 .4 1 .4 4 1.7 6 2.5
Native American 2 .9 1 .4 6 2.6 9 3.9
Asian American 1 .4 0 0.0 3 1.3 4 1.7
Other 3 1.3 1 .4 1 .4 5 2.1
Total 62 26.6 13 5.6 158 67.8 233 100.0 13.974
Age
26-34 5 2.1 0 0.0 6 2.5 11 4.7
35-50 25 10.6 3 1.3 51 21.6 79 33.5
51-65 17 7.2 7 3.0 58 24.6 82 34.7
66 older 16 6.8 4 11.7 44 18.6 64 27.1
Total 63 26.7 14 5.9 159 67.4 236 100.0 6.061










Table F-6. Willing to pay more for environmentally safe energy
Demographic Response
Yes % No % Not Sure % Total % Chi-Square
Gender
Male 77 31.3 53 21.5 0 0.0 130 52.8

Female 73 29.7 40 16.2 1 .4 114 46.3

Couple (Female/ Male) 2 .8 0 0.0 0 0.0 2 .8

Total
152 61.8 93 37.8 1 .4 246 100.0 3.142

Income
Less than $19k 9 4.0 6 2.7 0 0.0 15 6.7

$20k- $30k 16 7.1 13 5.8 0 0.0 29 12.9

$30k- $40k 20 8.9 6 2.7 0 0.0 26 11.6

$40k- $50k 17 7.6 10 4.5 1 .4 28 12.5

$50k ormore 83 37.0 43 19.2 0 0.0 126 56.3

Total 145 64.7 78 34.8 1 .4 224 99.9 10.157
Ethnicity
Caucasian 134 55.1 74 30.5 1 .4 209 86.0
African American 5 2.1 6 2.5 0 0.0 11 4.5
Hispanic 3 1.2 2 .8 0 0.0 5 2.1
Native American 4 1.6 4 1.6 0 0.0 8 3.3
Asian American 2 .8 2 .8 0 0.0 4 1.6
Other 3 1.2 3 1.2 0 0.0 6 2.5
Total 151 62.1 91 37.4 1 .4 243 100.0 4.501
Age
26-34 11 4.5 1 .4 0 0.0 12 4.9
35-50 53 21.5 26 10.6 1 .4 80 32.5
51-65 50 20.3 36 14.6 0 0.0 86 35.0
66 older 37 15.0 31 12.6 0 0.0 68 27.6
Total 151 61.4 94 38.2 1 .4 246 100.0 9.617















APPENDIX G
OVERALL COUNTY RESULTS FOR HOME AND LIFESTYLE ACTIVITY


On a scale of 1 to 5, rate your likelihood to conserve energy within your home.

Response Frequency Percent

Not at all 2 .7
Sometimes 44 15.8
Often 75 27.0
Regularly 102 36.7
Always 52 18.7
Sub Total 275 98.9
Missing 3 1.1
Total 278 100.0


Do you recycle yard wastes, plastics, glass, or any other recyclable item?

Response Frequency Percent

Yes 227 81.7
No 50 18.0
Sub Total 277 99.7
Missing 1 .3
Total 278 100.0

On a scale of 1 to 5, how satisfied were you with the dollar amount and kilowatt usage of
your last electric bill?

Response Frequency Percent

Not satisfied 62 22.3
Somewhat satisfied 93 33.5
Satisfied 91 32.7
Very satisfied 23 8.3
Extremely satisfied 3 1.1
Sub Total 272 97.8
Missing 6 2.2
Total 278 100.0









Do you have a computer in your home?


Response Frequency


Yes
No
Sub Total
Missing
Total


222
54
276
2
278


Percent

79.9
19.4
99.3
.7
100.0


Which is your preferred choice for receiving news related information?


Response

Internet
Newspaper
Radio
Television
Combination
Sub Total
Missing
Total


Frequency

16
74
17
125
42
274
4
278


Do you have access to the Internet?


Response Frequency


Yes
No
Sub Total
Missing
Total


218
52
270
8
278


Percent

78.5
18.7
97.2
2.8
100.0


Percent

5.8
6.6
6.1
45.0
15.1
98.6
1.4
100.0









Please describe the type of home you currently live in.

Response Frequency Percent

One-story, single family home 190 68.3
Two-story, single family home 37 13.3
Mobile home, single-wide 7 2.5
Mobile home, double or triple wide 28 10.1
Condo 5 1.8
Town home 4 1.4
Other 6 2.2
Sub Total 277 99.6
Missing 1 .4
Total 278 100.0


On a scale of 1 to 5, how energy efficient is your home?

Response Frequency Percent

Not energy efficient 22 7.9
Somewhat energy efficient 114 41.0
Energy efficient 96 34.5
Very energy efficient 36 12.9
Extremely energy efficient 4 1.4
Sub Total 272 97.8
Missing 6 2.2
Total 278 100.0


How many appliances within your home use natural gas?

Response Frequency Percent

1 37 13.3
2 33 11.9
3 or more 21 7.6
None 76 27.3
Sub total 167 60.1
Missing 111 39.9
Total 278 100.0















APPENDIX H
OVERALL COUNTY RESULTS FOR HOME COOLING AND HEATING


Which method do you use to cool your home? (Please circle "w" for with, or "o" for
without ceiling fan).

Response Frequency Percent

Air conditioning (Window unit with ceiling fan) 15 5.4
Central air conditioner (With ceiling fan) 191 68.7
Ceiling fans 9 3.2
Air conditioner (Window unit without ceiling fan) 5 1.8
Central air conditioner (Without ceiling fan) 35 12.6
Combination 17 6.1
Other 3 1.1
Sub Total 275 98.9
Missing 3 1.1
Total 278 100.0


During summer months, how often do you use any of the items in question 1 to cool your
home?

Response Frequency Percent

Never 2 .7
Sometimes 21 7.6
Often 114 41.0
Continuously 139 50.0
Sub Total 276 99.3
Missing 2 .7
Total 278 100.0









During the winter months, how do you heat your home?

Response Frequency Percent

Electrical Central Heating 99 35.6
Wood (Fireplace) 16 5.8
Heat Pump 57 20.5
Natural Gas Central Heating 36 12.9
Kerosene/ Oil 5 1.8
Electric Portable Heaters 1 .4
Other 11 4.0
None 2 .7
Combination 44 15.8
Sub Total 271 97.5
Missing 7 2.5
Total 278 100.0















APPENDIX I
OVERALL COUNTY RESULTS FOR WATER HEATERS, POOLS, AND SPAS


How many water heaters do you use in your home?


Frequency


231
34
3
2
270
8
278


Percent

83.1
12.2
1.1
.7
97.1
2.9
100.0


Which type of the following describes your main water heater? (Choose one)


Response

Standard separate tank (Electric)
Standard tank with heat recovery (Electric)
Heat pump water heater (Electric)
Other electric system
Natural gas
Propane
Combination
Sub total
Missing
Total


Frequency


167
34
7
2
32
13
7
262
16
278


Response

1
2
3
4 or more
Sub total
Missing
Total


Percent


60.1
12.2
2.5
.7
11.5
4.7
2.5
94.2
5.8
100.0









Is your water heater insulated?


Response Frequency


Yes
No
Not sure
Sub total
Missing
Total


165
63
41
269
9
278


Percent

59.4
22.7
14.7
96.8
3.2
100.0


Do you have a swimming pool at your home?


Response Frequency


Yes
No
Sub total
Missing
Total


69
199
268
10
278


Percent

24.8
71.6
96.4
3.6
100.0


How is your swimming pool heated?


Response


Frequency


Electric heat pump (Dedicated)
Natural gas
Propane
Solar
Not heated
Combination
Sub total
Missing
Total


50
1
69
209
278


Do you have a spa, whirlpool tub, or hot tub in your home?
Response Frequency Percent


Yes
No
Sub total
Missing
Total


43
215
258
20
278


15.5
77.3
92.8
7.2
100.0


Percent


1.4
1.4
1.1
2.5
18.0
.4
24.8
75.2
100.0






62


How do you heat your spa, whirlpool tub, or hot tub?

Response Frequency Percent

Electric heat pump (Dedicated) 8 2.9
Natural gas 8 2.9
Other electric heat 12 4.3
Propane 6 2.2
Not heated 10 3.6
Combination 1 .4
Sub total 45 16.2
Missing 233 83.8
Total 278 100.0















APPENDIX J
OVERALL COUNTY RESULTS FOR HOME AND KITCHEN APPLIANCES

How many refrigerators do you use in your home?

Response Frequency Percent

1 190 68.3
2 74 26.6
3 or more 8 2.9
Sub total 272 97.8
Missing 6 2.2
Total 278 100.0

How old is / are your refrigeratorss?

Response Frequency Percent

New 25 9.0
2-5 years 68 24.5
5-10 years 113 40.6
15 years or more 40 14.4
2 combined 20-25 years 3 1.1
2 combined 7-15 years 6 2.2
10-15 years 1 .4
2 combined new and 5-10 years 6 2.2
13 years 1 .4
2 combined 2-5 years and 15 years or more 1 .4
2 combined new and 2-5 years 3 1.1
2 combined 5-10 years and 15 + years 1 .4
2 combined new and over 30 years 1 .4
3 or more combined 20-25 years or more 1 .4
2 combined new and 15 years or more 1 .4
2 combined 25-30 years or more 1 .4
Sub total 272 97.8
Missing 6 2.2
Total 278 100.0









Which type of range / oven do you use in your home?

Response Frequency Percent

Electric 232 83.5
Natural gas 19 6.8
Propane 21 7.6
Combination 2 .7
Sub total 274 98.6
Missing 4 1.4
Total 278 100.0

Do you use a microwave oven in your home?

Response Frequency Percent

Yes 269 96.8
No 6 2.2
Sub total 275 98.9
Missing 3 1.1
Total 278 100.0

Do you use a dishwasher in your home?

Response Frequency Percent

Yes 207 74.5
No 66 23.7
Sub total 273 98.2
Missing 5 1.8
Total 278 100.0

Which type of clothes dryer do you use in your home?

Response Frequency Percent

Electric 251 90.3
Natural gas 7 2.5
Propane 6 2.2
Combination 1 .4
Other 3 1.1
None 5 1.8
Sub total 273 98.2
Missing 5 1.8
Total 278 100.0









Do you have a washing machine in your home?

Response Frequency Percent

Yes 271 97.5
No 4 1.4
Sub total 275 98.9
Missing 3 1.1
Total 278 100.0


Other than the refrigerator, which of the following appliances do you use most on a daily
basis in your home?

Response Frequency Percent

Range/ Oven 68 24.5
Microwave 97 34.9
Dishwasher 6 2.2
Clothes Dryer 5 1.8
Washing Machine 9 3.2
Other 2 .7
Combination 85 30.6
Sub total 272 97.8
Missing 6 2.2
Total 278 100.0















APPENDIX K
OVERALL COUNTY RESULTS FOR ENVIRONMENTAL AWARENESS


Do you belong to any type of natural resource, conservation, or environmental
organizations?

Response Frequency Percent

Yes 40 14.4
No 233 83.8
Sub total 273 98.2
Missing 5 1.8
Total 278 100.0


How concerned are you with global warming?

Response Frequency Percent

Not concerned 43 15.5
Moderately concerned 107 38.5
Concerned 54 19.4
Very concerned 42 15.1
Extremely concerned 16 5.8
Sub total 262 94.2
Missing 16 5.8
Total 278 100.0

Do you believe that there are enough natural resources for future generations? Examples
of natural resources are air, water, plant material, etc?

Response Frequency Percent

Yes 106 38.1
No 89 32.0
Not sure 73 26.3
Sub total 268 96.4
Missing 10 3.6
Total 278 100.0









How concerned are you with global issues, such as conservation, pollution, and
environmental issues?

Response Frequency Percent

Not concerned 13 4.7
Moderately concerned 85 30.6
Concerned 83 29.9
Very concerned 62 22.3
Extremely concerned 28 10.1
Sub total 271 97.5
Missing 7 2.5
Total 278 100.0


Do you believe there will be enough energy to support future generations?

Response Frequency Percent

Yes 117 42.1
No 62 22.3
Not sure 91 32.7
Sub total 270 97.1
Missing 8 2.9
Total 278 100.0


How often have you attended community and county meetings or public forums since
living in your current home?

Response Frequency Percent

Never 186 66.9
Once a month 50 18.0
Twice a month 5 1.8
More than 3 times a month 2 .7
3 times a month 1 .4
Occasionally 2 .8
Sub total 246 88.5
Missing 32 11.5
Total 278 100.0






68


How often do you encourage others to conserve energy?

Response Frequency Percent

Never 44 15.8
Sometimes 125 45.0
Often 86 30.9
Continuously 13 4.7
Sub total 268 96.4
Missing 10 3.6
Total 278 100.0
















LIST OF REFERENCES


Agresti, A. and Finlay, B. 1985. 1985. Statistical methods for the social sciences
2nd Edition. Dellen Publishing Company. San Francisco.

Anderson, J.L. Jr. and Altobello, M.A. 1982. Energy recovery from agricultural
wastes. 82-29 in StaffPaper. Univ. Conn. Dep. Agric. Econ. Rural Soc.

Audirac, I., and Smith, M.T. 1992. Urban form and residential choice: preference for
urban density in Florida. J. Arch. & Plan. Res. Spring, 9:1, 19-32.

Asmus, P. 2002. Capturing markets and delivering value in the electric utility industry.
Coop. Environ. Strategy. 9:2, 122-128.

Bourdaire, J. and Ellis, J. 2000. Energy-related services and global environmental
concerns what possible strategies for forestry? Eco Engineering. 16:1,51-61.

Bravo-Ureta, B.E. and McMahon, G.V. 1983. The economic feasibility of electricity
generation on cage layer operations, (net present value). 83- 11 in StaffPaper
Univ. Conn. Dep Agric. Econ. Rural Soc.

Brown, M.A. and Major, C.H. 1990. Technology-transfer strategies of DOE's
conversion programs. J. Tech. Trans. 15: 33-40.

Brown, R.A., Rosenberg, N.J., Hays, C.J. Easterling, W.E. and Means, L.O. 2000
Potential production and environmental effects of switch grass and traditional
crops under current and greenhouse-altered climate in the central United States: a
simulation study. Agrci. Ecosys. and Environ. 78: 31-47.

Buttel, F.H. and Flinn, W.L. 1976. Economic growth versus the environment: survey
evidence. Soc. Sci. Quart. 57: 2, September, 410-420.

Buttond, G. 2000. How can policy take into consideration the "full value" of forest?
Land Use Policy. 17: 169-175.

Campinhos, E. Jr. 1999. Sustainable plantations of high-yield eucalyptus trees for
production of fiber: the Aracruz case. New Forests. 17-18: 129-143.

Caro, F. and Gottlieb, A. 2001. A field experiment in aging services: opportunities and
obstacles in the pursuit of internal and external validity. Evaluation andProgram
Planning 24:3, 249-246.










Central Pennsylvania Energy Center (CPEC). 1990. Energy in alternative agriculture.
Center: Pennsylvania Energy Office. Lewisburg, PA.

Chesbrough, H. 2003. Open innovation: the new imperative for creating and profiting
from technology. Harvard Business School Press. Boston, MA.

Classen, P.A.M., Sijtsma, L., Stams, A.J.M., Vries de, S.S., Weusthuis, R. A., Van Lier,
J.B., Lopez Contreras, A.M., and Van Niel, E.W.J. 1999. Utilization ofbiomass
for the supply of energy carriers. Appl. Microbiology andBiotech. 52: 741-755.

Cosmi, C., Macchiato, M., Mangiamele, L., Marmo, G., Pietrapertosa, F., and
Salvia, M. 2002. Environmental and economic effects of renewable energy on a
local case study. Energy Policy. Article in press: 1-15.

Criddle, R.S., Anekonda, T.S., Sachs, R.M., Breidenbach, R.W., and Hansen, L.D., 1996.
Selection of biomass production based on respiration parameters in eucalyptus:
acclimation of growth and respiration to changing growth temperature. Canadian
J. ForestRes. 26: 1569-1576.

Elliot, D. 2000. Renewable energy and sustainable futures. Futures. 32: 261-274.

English, B.C., Short, C. and Heady, E.O. 1981. The economic feasibility of crop residues
as auxiliary fuel in coal-fired power plants. Am. J. Agric. Econ. 63: 636-644.

Francis, C.A. and Madden, J.P. 1993. Designing the future: sustainable agriculture in
the U.S. Agric. Ecosystems & Environ. 46: 123-134.

Gan, L. 2002. Promoting green electricity development from industrial to developing
countries: what needs to be done. Environ Politics. 11, 1, spring, 184-191.

Garg, V.K. and Jain, R.K. 1992. Influence of fuelwood trees on sodic soils.
Canadian J. Forest Res. 22: 729-735.

Gluck, P. 2000. Policy means for ensuring the full value of forest to society.
Land Use Policy. 17: 177-185.

Guo, L.B. and Sims, R.E.H. 1999a. Litter production and nutrient return in New
Zealand eucalypt short-rotation forests: implication for land management.
Agric. Ecosystems & Environ. 73: 93-100.

Guo, L.B. and Sims, R.E.H. 1999b. Litter decomposition and nutrient release via
litter decomposition in New Zealand eucalypt short rotation forests.
Agric. Ecosystems & Environ. 75: 133-140.









Hill L and Hadely J. 1995. Federal tax incentives and disincentives for the adoption of
wood- fuel electric generating technologies. Bioresource Tech. 53:173-178.

Hilman, N.D. and Yancey, M.A. 1998. Use of net present value analysis to evaluate
a publicly funded biomass-to ethanol research, development, and
demonstration program and evaluate expected private sector fund.
Appl. Biochemistry and Tech. 70-72: 807-819.

Hitzhusen, F. J. and Abdallah, M. 1980. Economics of electrical energy from crop
residue combustion with high sulfur coal. Am. J. Agric. Econ. 62: 416-425.

Marrku, O.R., Gronfors, T.H.A., and Haukka, P. 2003. Development and optimization of
power plant concepts for local wet fuels. Biomass andBioenergy. 24:1, 27-37.

McIlveen-Wright, D.R., Williams, B.C., and McMullan, J.T. 2001. A re-appraisal of
wood-fired combustion. Bioresource Tech. 76: 183-190.

McKendry, P. 2002. Energy production from biomass (part 2): conversion technologies.
Bioresource Tech. 83: 47-54.

McQueen, R.E. 2000. World population growth, distribution and demographics and their
implications on food production. Canadian J. OfAnim. Sci. 80:229-234.

Michaels, M.Z. 2000. Speed: linking innovation, process, and time to market. The
Conference Board. New York.

Mielenz, J.R. 1996. Commercialization of biomass ethanol technology: feasibility studies
biomass-to-ethanol production facilities. Appl. Biochemistry andBiotech. 57-58:
763-775.

Morgenstern, J. 2002. Renewable energy for rural electrification in developing countries.
Dissertation Abstracts International, A: The Humanities and Soc. Sci; 63, 2,
August. 781-A.

Mulloy, F. and Ottisch, A. 2000. The full value of forests. Land Use Policy
17: 167-168.

Neij, L. 1997. Use of experience curves to analyze the prospects of diffusion and
adoption of renewable energy technology. Energy Policy. 23: 1099-1107.

Newman, I. and McNeil, K. 1998. Conducting survey research in the social sciences.
University Press of America.

Pearson, R.W. and Boruch, R.F. 1980. Survey Research Designs: Towards a Better
Understanding of Their Costs and Benefits. Springer-Verlag









Rahmani, M., A.W. Hodges, and Stricker, J.A. 1996. Potential producers and their
attitudes toward adoption of biomass crops in Central Florida. Proc. Seventh
National Bioenergy Conference, BIOENERGY' 96, 671-678, Ibid.

Rahmani, M., Hodges, A., Stricker, J.A., and Kiker, C.F. 2003. Will investing in
Renewable energy pays off?: A case study in Florida. Food and Resource
Economics Department, Polk County Extension Service, Institute of Food and
Agricultural Sciences, University of Florida.

Rahmani, M., Stricker, J.A., and Kiker, C.F. A comparison of renewable energy options
for Florida. Food and Resource Economics Department, Institute of Food and
Agricultural Sciences, University of Florida, Polk County Extension Service.

Rogers, E.M. 1995. Diffusion of Innovation. 3rd Edition. The Free Press. Macmillan
Publishing Company. New York.

Rogers, E.M. and Shoemaker, F.F. 1971 Communication of innovations: a cross-
cultural approach. 2nd Edition. The Free Press. New York.

Rogers, G.O. 1998. The dynamics of risk perception: how do perceived risks respond
to risk events? Insurance: 3 A lh'eitii and Econ. 22:3, 292-292.

Seattle: State Office of Public Instruction. 1979. Energy, food, and you: an
interdisciplinary curriculum guide for secondary schools. State Report.

Sells, J.E. and Audsley, E. 1991. The profitability of an arable wood crop for
electricity. J. Agric. EngineeringRes. 48: 273-285.

Sklar, F.H., Fritz, H.C., Wu, Y., Van Zee, R. and McVoy, C. 2001. South Florida: the
reality of change and the prospects of sustainability. Eco Econ. 37:3, 379-401.

Slack, W. 1983. Getting it together: pencils, plans and plants. Aithen
Cooperative Extension Service. University of Georgia. College of
Agriculture.

Spiedel, H.K. 2000. Biodegradability of new-engineered fuels compared
to conventional petroleum fuels and alternative fuels in current use.
Appl. Biochemistry and Biotech. 84-86: 879-897.
76
Stoneman, P. 2002. The economics of technological diffusion. Blackwell Publishers.

Stricker, J.A., Rahmani, M., Hodges, A., and Kiker, C.F. Economic analysis ofbiomass
crop production in Florida. University of Florida, Institute of Food and
Agricultural Sciences, Food and Resource Economics Department, Polk County
Extension Services.









Stricker, J.A., Rockwood, D.L., Segrest, S.A., Alker, G.R. Prine, G.M., Carter,
Douglas, R.C. 2000. Short rotation woody crops for Florida. University of Florida
Polk County Extension Service and University of Florida School of Forest
Resources and Conservation, The Common Purpose Institute, University of
Florida Agronomy Department.

Stucker, B.C. and Stucker, T.A. 1984. Planting for the future. 8-10, in NationalFood
Review NFR. United States Dep. Econ. Research Service state offices. Wash. D.C.

Tillman, D. 2000. Co-firing benefits for coal and biomass. Biomass and
Bioenergy. 363-364.

Vaage, K. 2000. Heating technology and energy use: a discrete/continuous choice
approach to Norwegian household energy demand. Energy Econ. 22:6 649-666.

Warren, T.J.B., Poulter, R., Parfitt, R.I. 1995. Converting biomass to electricity on a
farm-sized scale using downdraft gasification and a spark-ignition engine.
Bioresource Tech. 52: 95-98.

Weber, 0. 2001. Perception of environmental risks of company sites. J. Environ
Psych. 21:2. 165-178.

Weisberg, H.F., Krosnick, J.A, and Bowen, B.D. 1989. Survey research and data
analysis. 2nd edition. Library of Congress.

Wharton, E.H. 1991. Fuelwood telephone surveys: how accurate are they?
Northern J. Appl. For. 8:119-122.















BIOGRAPHICAL SKETCH

He was born August 13, 1968 in Tampa, Florida. He graduated from Hillsborough

High School in 1986 and later graduated from Hillsborough Community College in 1990

with an Associate of Arts degree in liberal arts. He then came to the University of

Florida in 1990 and received a Bachelor of Arts degree in criminal justice (with a minor

in sociology) in 1994. Later, he began pursuing a Master of Arts degree in English in the

fall semester of 1997 and graduated August 2000. He then began a teaching career as an

Adjunct English Professor and later returned to the University of Florida for a Master of

Science degree in environmental science