Browsing by Author "Clemen, Robert T"

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    Decision Models for Corporate Sustainability
    (2013) Mendoza, Alvaro

    This dissertation explores decision problems faced by organizations willing to address or support the incorporation of sustainability aspects on their "business as usual" activities. We study to specific problems. First, we analyze the decision problem of a forest manager who, in addition to selling timber, has the option of selling carbon offsets for the carbon sequestered by the forest. We study both the single-rotation and the multiple-rotations harvesting problems, and develop stochastic dynamic programming models to find the optimal harvesting and offset-selling policy, the expected optimal harvesting time, and the expected optimal reward under different offset-trading schemes. Then, we study the case in which an organization (sustainability buyer) outsources sustainability efforts to another organization (sustainability seller). While buyers cannot directly exert sustainability efforts, they can provide economic or technical support to their sellers in order to incentivize these efforts. We investigate how the effort and support decisions change according to characteristics of stakeholders, buyers, and sellers. Considering that buyers can compete on the sustainability effort exerted by their sellers, we extend our analysis to the case of competing buyers, and we determine conditions under which sharing sellers is preferred by the buyers to having separate sellers for each buyer.

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    Duke Carbon Offsets Initiative: Organic Waste Diversion Options & Waste to Energy Opportunities
    (2011-04-29) Wangerman, Emilie; Kaufmann, Matthew; Tang, Chen Wei
    The primary purpose of this paper is to highlight the opportunity for organic waste diversion from landfills for greenhouse gas emission reduction purposes. Duke University’s Duke Carbon Offsets Initiative (DCOI) is looking for opportunities to facilitate and catalyze offset projects, which will help Duke University become carbon neutral by 2024. The following analysis reviews different project opportunities related to organic waste composting and organic waste digestion and highlights the advantages of using anaerobic digestion to convert waste to energy and to use the composting co-product for other applications, including mulch for Duke University landscaping.
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    Environmental Impact Study: CSP vs. CdTe thin film photovoltaics
    (2009-12-02T01:08:28Z) Montgomery, Zoe
    Due to the recent market fascination with alternative energy, there has been a proliferation in solar energy technologies. Among all the new technologies, it is hard to see which will be successes and which will become obsolete as the industry matures. Even more difficult is analyzing the environmental impact of each of these technologies. The industry and recent entrants often tout the lack of resources needed to operate a solar plant, but ignore the resources required to get a product into operation. This study compares the two cheapest and most recently developed technologies in the solar energy industry: concentrated solar power parabolic trough technology and cadmium telluride photovoltaic solar panel technology. The two technologies are analyzed at a utility scale. The input materials and embodied energy are analyzed using two life cycle analysis tools: the EIOLCA tool from Carnegie Mellon and GaBi. Embodied energy is compared to the energy output of the respective technologies using two metrics: energy return on energy invested, and energy payback time. In addition to energy input and output, the two technologies are compared on land use, water use, and toxicology. The results of this study show that both technologies have advantages and disadvantages with respect to the impacts studied. Cadmium telluride photovoltaic technology is more efficient in terms of water and energy payback time, while concentrated solar trough technology is more efficient in terms of land use, toxicity, and energy returned on energy invested.
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    On the Choice of Baselines in Multiattribute Portfolio Analysis: A Cautionary Note.
    (Decision Analysis, 2009) Clemen, Robert T; Smith, James E
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    Which Nutrient Criteria Should States and Tribes Choose to Determine Waterbody Impairment?: Using Science and Judgments to Inform Decision-making
    (2007-12-12) Kenney, Melissa A
    Nutrients are the number one water pollution problem for U.S. lakes, reservoirs, and ponds. Excessive nutrients, such as nitrogen and phosphorus, lead to eutrophication, a condition that can include low oxygen levels, noxious algal blooms, and fish kills. Since eutrophication is a condition that manifests itself differently in different systems, there is not a criterion variable with a clear threshold that can be used to set the criterion level. This dissertation presents an approach to address the question: How should States and Tribes choose nutrient criteria to determine eutrophication-related impairments of the designated use? To address this question I used a combination of water quality modeling and decision analysis to determine the optimal nutrient criterion variables and levels. To choose criterion variables that are predictive of the designated use, I utilized statistical models (structural equation models, multiple regression, and binomial regression model) to link the measured water quality variables to expert elicited categories of eutrophication and the designated uses. These models were applied successfully to single waterbodies, the Kissimmee Chain-of-Lakes region, and the State of North Carolina to assess which candidate criterion variables were the most predictive. Additionally, the models indicated that the variables that were most predictive of eutrophication were also the most predictive of the designated use. Using the predictive nutrient criteria variables, I applied a decision-analytic approach to nutrient criteria setting in North Carolina. I developed a nutrient criteria value model that included two submodels, a water quality model and a multiattribute value model. The submodels were parameterized using a combination of water quality data, expert elicitation data, and utility assessments. The outcome of the nutrient criteria value model is the overall expected value for a criterion level choice; the optimal criterion level would be the choice that maximized the expected value. Using the preferences of North Carolina environmental decision-makers and a total phosphorus criterion variable, the optimal criterion level was between 0.03 mg/L and 0.07 mg/L. Ultimately, I hope this research will establish methodology used to set appropriate water quality criteria.