3 resultados para Performance Indicators

em Digital Commons - Michigan Tech


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A range of societal issues have been caused by fossil fuel consumption in the transportation sector in the United States (U.S.), including health related air pollution, climate change, the dependence on imported oil, and other oil related national security concerns. Biofuels production from various lignocellulosic biomass types such as wood, forest residues, and agriculture residues have the potential to replace a substantial portion of the total fossil fuel consumption. This research focuses on locating biofuel facilities and designing the biofuel supply chain to minimize the overall cost. For this purpose an integrated methodology was proposed by combining the GIS technology with simulation and optimization modeling methods. The GIS based methodology was used as a precursor for selecting biofuel facility locations by employing a series of decision factors. The resulted candidate sites for biofuel production served as inputs for simulation and optimization modeling. As a precursor to simulation or optimization modeling, the GIS-based methodology was used to preselect potential biofuel facility locations for biofuel production from forest biomass. Candidate locations were selected based on a set of evaluation criteria, including: county boundaries, a railroad transportation network, a state/federal road transportation network, water body (rivers, lakes, etc.) dispersion, city and village dispersion, a population census, biomass production, and no co-location with co-fired power plants. The simulation and optimization models were built around key supply activities including biomass harvesting/forwarding, transportation and storage. The built onsite storage served for spring breakup period where road restrictions were in place and truck transportation on certain roads was limited. Both models were evaluated using multiple performance indicators, including cost (consisting of the delivered feedstock cost, and inventory holding cost), energy consumption, and GHG emissions. The impact of energy consumption and GHG emissions were expressed in monetary terms to keep consistent with cost. Compared with the optimization model, the simulation model represents a more dynamic look at a 20-year operation by considering the impacts associated with building inventory at the biorefinery to address the limited availability of biomass feedstock during the spring breakup period. The number of trucks required per day was estimated and the inventory level all year around was tracked. Through the exchange of information across different procedures (harvesting, transportation, and biomass feedstock processing procedures), a smooth flow of biomass from harvesting areas to a biofuel facility was implemented. The optimization model was developed to address issues related to locating multiple biofuel facilities simultaneously. The size of the potential biofuel facility is set up with an upper bound of 50 MGY and a lower bound of 30 MGY. The optimization model is a static, Mathematical Programming Language (MPL)-based application which allows for sensitivity analysis by changing inputs to evaluate different scenarios. It was found that annual biofuel demand and biomass availability impacts the optimal results of biofuel facility locations and sizes.

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Advances in information technology and global data availability have opened the door for assessments of sustainable development at a truly macro scale. It is now fairly easy to conduct a study of sustainability using the entire planet as the unit of analysis; this is precisely what this work set out to accomplish. The study began by examining some of the best known composite indicator frameworks developed to measure sustainability at the country level today. Most of these were found to value human development factors and a clean local environment, but to gravely overlook consumption of (remote) resources in relation to nature’s capacity to renew them, a basic requirement for a sustainable state. Thus, a new measuring standard is proposed, based on the Global Sustainability Quadrant approach. In a two‐dimensional plot of nations’ Human Development Index (HDI) vs. their Ecological Footprint (EF) per capita, the Sustainability Quadrant is defined by the area where both dimensions satisfy the minimum conditions of sustainable development: an HDI score above 0.8 (considered ‘high’ human development), and an EF below the fair Earth‐share of 2.063 global hectares per person. After developing methods to identify those countries that are closest to the Quadrant in the present‐day and, most importantly, those that are moving towards it over time, the study tackled the question: what indicators of performance set these countries apart? To answer this, an analysis of raw data, covering a wide array of environmental, social, economic, and governance performance metrics, was undertaken. The analysis used country rank lists for each individual metric and compared them, using the Pearson Product Moment Correlation function, to the rank lists generated by the proximity/movement relative to the Quadrant measuring methods. The analysis yielded a list of metrics which are, with a high degree of statistical significance, associated with proximity to – and movement towards – the Quadrant; most notably: Favorable for sustainable development: use of contraception, high life expectancy, high literacy rate, and urbanization. Unfavorable for sustainable development: high GDP per capita, high language diversity, high energy consumption, and high meat consumption. A momentary gain, but a burden in the long‐run: high carbon footprint and debt. These results could serve as a solid stepping stone for the development of more reliable composite index frameworks for assessing countries’ sustainability.

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Multiple indices of biotic integrity and biological condition gradient models have been developed and validated to assess ecological integrity in the Laurentian Great Lakes Region. With multiple groups such as Tribal, Federal, and State agencies as well as scientists and local watershed management or river-focused volunteer groups collecting data for bioassessment it is important that we determine the comparability of data and the effectiveness of indices applied to these data for assessment of natural systems. We evaluated the applicability of macroinvertebrate and fish community indices for assessing site integrity. Site quality (i.e., habitat condition) could be classified differently depending on which index was applied. This highlights the need to better understand the metrics driving index variation as well as reference conditions for effective communication and use of indices of biotic integrity in the Upper Midwest. We found the macroinvertebrate benthic community index for the Northern Lakes and Forests Ecoregion and a coldwater fish index of biotic integrity for the Upper Midwest were most appropriate for use in the Big Manistee River watershed based on replicate sampling, ability to track trends over time and overall performance. We evaluated three sites where improper road stream crossings (culverts) were improved by replacing them with modern full-span structures using the most appropriate fish and macroinvertebrate IBIs. We used a before-after-control-impact paired series analytical design and found mixed results, with evidence of improvement in biotic integrity based on macroinvertebrate indices at some of the sites while most sites indicated no response in index score. Culvert replacements are often developed based on the potential, or the perception, that they will restore ecological integrity. As restoration practitioners, researchers and managers, we need to be transparent in our goals and objectives and monitor for those results specifically. The results of this research serve as an important model for the broader field of ecosystem restoration and support the argument that while biotic communities can respond to actions undertaken with the goal of overall restoration, practitioners should be realistic in their expectations and claims of predicted benefit, and then effectively evaluate the true impacts of the restoration activities.