Design standards for product end-of-life processing

In 2006, the British Standards Institute (BSI) published BS 8887-1 ‘Design for Manufacture, Assembly, Disassembly and End-of-life processing’ (MADE) subtitled ‘General Concepts, Processes and Requirements’. This was the first British Standard to address design for efficient post-consumer product reprocessing. By designing and planning for remanufacture, much of the embodied energy and production investment can be retrieved after the consumer no longer requires the original item. Therefore, end-of-life products become an asset rather than a liability. Design for disassembly facilitates efficient deconstruction and thus enables materials to be recycled with minimal loss of purity, thus maximising their value. The analysis presented here is based on the Standard Industrial Classification codes of companies and organisations that have purchased BS 8887-1. These data are considered in relation to the influence of environmental legislation. Company age, size and location, as well as ISO 9001 and ISO 14001 certifications, are discussed. This paper concludes by suggesting suitable directions for the continued distribution and development of this environmentally, economically and socially beneficial standard.     

基于能值理论的工业生态系统分析——以龙盛科技工业园为例

基于能值理论．以龙盛科技工业园为例,对其能量流动和物质循环进行分析,通过能值分析的方法,将能量漉、物质流等转化为统一的能值单位,对工业生态系统的效率和稳定性进行了评价。结果表明,龙盛科技工业固由于注重物质循环利用和能量梯级利用,已经形成比较完善的产业链,生态效率和系统稳定性都相对较高。     

氨碱行业工业固废循环经济活动开展情况分析与探讨

以青岛碱业股份有限公司为例,分析了氨碱行业工业固废的产生源、废物性质、危害特征与资源化特征．分析公司针对行业固废开展的循环经济活动、废物流向,对固废资源化技术的经济、技术可行性及环境风险性进行了探讨。     

Applications of resilience engineering principles in different fields with a focus on industrial systems: A literature review

This paper reviews literature that addresses applications of resilience engineering principles to various fields. Recently the concept has attracted great attention from a technical and industrial perspective. The primary focus of this paper is to review the resilience engineering applications to industrial systems with the purpose of applying them to the chemical industry. A systematic review is performed to classify peer-reviewed journal papers that are associated with resilience engineering applications into three categories: industrial systems, ecological systems, and interlinked systems. The literature in the category of industrial systems is further divided based on the type of approaches such as field studies, case studies, methodologies, and mathematical modeling. After thoroughly analyzing the literature, four key research areas are identified: Considering socio-technical factors for resilience assessment efficiently; Inculcating the possibility of multiple disasters in resilience assessment; Design optimization for resilience enhancement; Efficient restoration strategies. All these research areas have not been explored exclusively for chemical facilities to a great extent. It is concluded that if these research areas are addressed appropriately, it would help in triggering the research pertaining to the application of resilience engineering principles in chemical facilities.     

Assessing determinants of industrial waste reuse: The case of coal ash in the United States

Devising effective strategies to facilitate waste reuse depends on the solid understanding of reuse behaviors. However, previous studies of reuse behavior have been limited in scope, focusing mostly on household recycling behaviors or very limited types of industrial wastes. To gain a better understanding of the business reuse behaviors, this study examined the impact of various factors in technical, economic, regulatory, and behavioral categories in the case of coal ash generated in the United States. The results of fixed effect models for fly ash and bottom ash particularly showed the significance role of the behavioral factor. In both models, a proxy variable, which represents knowledge sharing among the power plants or the utility's decision-making, turned out to be statistically significant and had the largest coefficient estimates among a group of variables. This finding may imply that the characteristics of waste reuse behavior are determined more by business decision-making behaviors than by market or institutional factors. However, the role of the behavioral variable was stronger in the bottom ash models than in the fly ash models. While the reuse of bottom ash was determined primarily by the behavioral variable, fly ash reuse was determined by more diverse factors including economic and regulatory variables. This could be explained by material characteristics in relation to competing resources and the nature of reuse applications.     

Multi-objective optimization of waste and resource management in industrial networks – Part I: Model description

This article presents a general multi-objective mixed-integer linear programming (MILP) optimization model aimed at providing decision support for waste and resources management in industrial networks. The MILP model combines material flow analysis, process models of waste treatments and other industrial processes, life cycle assessment, and mathematical optimization techniques within a unified framework. The optimization is based on a simplified representation of industrial networks that makes use of linear process models to describe the flows of mass and energy. Waste-specific characteristics, e.g. heating value or heavy metal contamination, are considered explicitly along with potential technologies or process configurations. The systems perspective, including both provision of waste treatment and industrial production, enables constraints imposed upon the systems, e.g. available treatment capacities, to be explicitly considered in the model. The model output is a set of alternative system configurations in terms of distribution of waste and resources that optimize environmental and economic performance. The MILP also enables quantification of the improvement potential compared to a given reference state. Trade-offs between conflicting objectives are identified through the generation of a set of Pareto-efficient solutions. This information supports the decision making process by revealing the quantified performance of the efficient trade-offs without relying on weighting being expressed prior to the analysis. Key features of the modeling approach are illustrated in a hypothetical case. The optimization model described in this article is applied in a subsequent paper (Part II) to assess and optimize the thermal treatment of sewage sludge in a region in Switzerland.