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Exploring the sustainability of urban ecosystem is becoming a key area in global sustainable development. Urban metabolism is an effective analysis tool for the study of urban ecosystem. In this regard, how to evaluate the level of urban sustainable development and identify the key factors that affect urban metabolism is critical. Many studies on urban metabolism have been explored during the past half century, but few concerns about the key factors that affect urban metabolism. Therefore, this paper fills such a gap by combining emergy and Logarithmic Mean Divisia Index (LMDI) methods in order to analyze the sustainable development level and identify the driving forces of emergy utilization, respectively. A typical industrial city, Shenyang in northeast China, was chosen as a case study city in this paper. Results show that renewable resource utilization in Shenyang was very limited from 2000 to 2010, while nonrenewable resources and the imported resources increased rapidly. During this period, total emergy utilization of Shenyang increased from 8.52 × 10 22 sej to 21.53 × 10 22 sej, and emergy density increased with annual increasing rate of 10.34%, demonstrating a fast development of the economy and high level of resident's consumption. LMDI method was employed to analyze the driving forces of emergy consumption from the aspects of scale, structure and intensity. Results show that the rapid increase of emergy utilization in Shenyang was mainly caused by the expansion of economic scale, while emergy intensity greatly contributed to offset total consumption, and industry structure played a marginal role, with a minor value for its growth. Based upon these results, several policy recommendations were raised, including the use of more renewable and clean energy sources, a regenerative and preventative eco-industrial development approach, and capacity-building efforts, so that the overall environment pressure on urban development can be reduced. [ABSTRACT FROM AUTHOR]

In light of various environmental problems and challenges concerning resource allocation, the utilisation of renewable resources is increasingly important for the efficient use of raw materials. Therefore, cascading utilisation (i.e., the multiple material utilisations of renewable resources prior to their conversion into energy) and approaches that aim to further increase resource efficiency (e.g., the utilisation of by-products) can be considered guiding principles. This paper therefore introduces the Special Volume "Improved Resource Efficiency and Cascading Utilisation of Renewable Materials". Because both research aspects, resource efficiency and cascading utilisation, belong to several disciplines, the Special Volume adopts an interdisciplinary perspective and presents 16 articles, which can be divided into four subjects: Innovative Materials based on Renewable Resources and their Impact on Sustainability and Resource Efficiency, Quantitative Models for the Integrated Optimisation of Production and Distribution in Networks for Renewable Resources, Information Technology-based Collaboration in Value Generating Networks for Renewable Resources, and Consumer Behaviour towards Eco-friendly Products. The interdisciplinary perspective allows a comprehensive overview of current research on resource efficiency, which is supplemented with 15 book reviews showing the extent to which textbooks of selected disciplines already refer to resource efficiency. This introductory article highlights the relevance of the four subjects, presents summaries of all papers, and discusses future research directions. The overall contribution of the Special Volume is that it bridges the resource efficiency research of selected disciplines and that it presents several approaches for more environmentally sound production and consumption. [ABSTRACT FROM AUTHOR]

Increased competition and reduced profit margins are pushing manufacturing plants to find ways to improve operational efficiency and reduce costs. At the same time, government incentives and community initiatives are encouraging the industrial sector to pursue sustainability in operation and energy consumption. This has introduced a paradigm shift where the focus of plant operation is moving from solely cost reduction to one that considers asset management, emission control, and utilization of alternative energy resources. Mathematically speaking, the problem is changing from a single objective optimization to one with multiple objective functions that may at times be contradictory. The focus of this paper is to propose a methodology for management of an industrial plant considering the above factors. It is assumed that the plant is equipped with distributed generation (DG), and can also participate in demand response (DR). Further, the effect of ambient temperature on the lifetime and available capacity of assets such as the plant transformer has been taken into account and incorporated into their daily schedule. The objective is then to find an optimal solution for operating various workstations in such a way that it minimizes the operational costs, the emissions produced, and the loss of life of assets exposed to excess temperatures. A multi-objective optimization problem is therefore formulated through extended lexicographic goal programming, which is further modified to ensure Pareto optimality. A case study has also been presented for a manufacturing plant for luxury vehicle cockpit assembly line. [ABSTRACT FROM AUTHOR]