The present work proposes a computer-aided methodology for designing sustainable supply chains in terms of sustainability metrics by utilizing the P-graph framework. The methodology is an outcome of the collaboration between the Office of Research and Development (ORD) of the U.S. EPA and the research group led by the creators of the P-graph framework at the University of Pannonia. The integration of supply chain design and sustainability is the main focus of this collaboration. The P-graph framework provides a mathematically rigorous procedure for synthesizing optimal and alternative suboptimal networks subject to multiple objectives and constraints, which include profitability and sustainability in the proposed methodology. Specifically, to evaluate the sustainability of a given process under construction including its supply chain, sustainability metrics are incorporated into the design procedure. The proposed methodology is demonstrated with the optimal design of a supply chain for providing heat and electric power to an agricultural region with relatively limited land area where agricultural wastes can potentially be recovered as renewable resources. The objective functions for optimization comprise the profit and the ecological footprint. The results of the study indicate that, compared to using electricity from the grid and/or natural gas, using renewable energy resources can yield substantial cost reductions of up to 5%, as well as significant ecological footprint reductions of up to 77%. It may, therefore, be possible to design more sustainable supply chains that are both cost-effective and less environmentally damaging.
One of the critical challenges in achieving sustainability is finding a way to meet the energy consumption needs of a growing population in the face of increasing economic prosperity and finite resources. According to ecological footprint computations, the global resource consumption began exceeding planetary supply in 1977 and by 2030, global energy demand, population, and gross domestic product are projected to greatly increase over 1977 levels. With the aim of finding sustainable energy solutions, we present a simple yet rigorous procedure for assessing and counterbalancing the relationship between energy demand, environmental impact, population, GDP, and energy efficiency. Our analyses indicated that infeasible increases in energy efficiency (over 100 %) would be required by 2030 to return to 1977 environmental impact levels and annual reductions (2 and 3 %) in energy demand resulted in physical, yet impractical requirements; hence, a combination of policy and technology approaches is needed to tackle this critical challenge. This work emphasizes the difficulty in moving toward energy sustainability and helps to frame possible solutions useful for policy and management.
The 20th century was characterized by substantial change on a global scale. There were multiple wars and unrest, social and political transitions, technological innovation and widespread development that impacted every corner of the earth. In order to assess the sustainability implications of these changes, we conducted a study of three advanced nations particularly affected during this time: France, Germany and the United States (USA). All three nation states withstood these changes and yet continued to thrive, which speaks to their resilience. However, we were interested in determining whether any of these countries underwent a regime shift during this period and if they did, whether there was advanced warning that transition was imminent. This study seeks to evaluate systemic trends in each country by exploring key variables that describe its condition over time. We use Fisher Information to assess changing conditions in the nation states based on trends in social, economic and environmental variables and employ Bayes Theorem as an objective means of determining whether declines in Fisher information provide early warning signals of critical transitions. Results indicate that while the United States was relatively stable and France experienced a great deal of change during this period, only Germany appeared to undergo a regime shift. Further, each country exhibited decreasing Fisher information when approaching significant events (e.g., World Wars, Great Depression), and reflected unique mechanisms linked to dynamic changes in each nation state. This study highlights the potential of using trends in Fisher information as a sentinel for evaluating dynamic change and assessing resilience in coupled human and natural systems.
The Campus Demotechnic Index (CDI) was modified from the Demotechnic Index (D-Index) to serve as an index of energy use for US colleges and universities. CDI values were calculated by assessing the total campus energy used for the built and mobile environments against energy required to meet the basal metabolic demand of the total campus population. Like the D-Index, the CDI measured the scalar quantity of energy used relative to the quantity of energy required for simple survival on a per capita basis, thus providing a rational metric for comparison among institutions. For the interval 2000-2005, CDI was calculated for 64 US higher education institutions and compared using maximum, minimum, mean and median CDI values, total gigajoules used, campus population, and consumption-adjusted population. Wilcoxon signed rank test results compared pair-by-pair differences of ranked CDI values from 2000 to 2005 to determine whether CDI values were significantly increasing or decreasing over time. In general, CDI values increased over time, but increases over the 6-year interval were only significantly higher in 8 of 30 two-year comparisons; in 2005, CDI values ranged from 1.1 to 56.3 (mean = 11.9, median = 8.2, n = 64), whereas in 2000, CDI values ranged from 2.0 to 53.0 (mean = 12.6, median = 9.1, n = 22). Results suggest that the CDI may serve as a useful metric for tracking campus energy efficiency over time as well as a means of comparison of energy use among institutions.Readers should send their comments on this paper to BhaskarNath@aol.com within 3 months of publication of this issue.
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