产业生态系统资源代谢分析方法

产业生态系统是由企业群、资源及环境组成的社会-经济-环境复合生态系统。资源代谢是其功能运行的重要保障。资源代谢在时间和空间尺度上的耗竭及阻滞是造成严重生态环境问题的主要原因。根据生态学原理,运用物质流分析手段解析了产业生态系统的物质流、能流及资金流结构,构建了产业生态系统资源代谢分析模型,提出了资源输入-使用-输出-循环共生四方面的资源代谢分析指标体系和基于模糊综合分析的资源代谢问题树分析方法。在此基础上提出了基于循环共生网络结构模型的生态管理模式。以期为产业资源的生态管理提供方法支撑。

An approach for analyzing resources metabolism of industrial ecosystems

Industrial ecosystems are complex social-economic-environmental systems that are comprised of industrial communities (a group of industrial enterprises), resources and environment. Resources metabolism is an important support for industrial ecosystem function. Resource depletion and metabolism blocking on both temporal and spatial scale is the major causes of eco-environmental stress. Based on the ecological principles and MFA methodology, this paper analyzed the structure of industrial ecosystems' material flow, energy flow and money flow, and suggested the framework model of resources metabolism for industrial ecosystems. This model consists of six sub-modules including a resources exploitation module, a raw material production module, a product exchange center module, a consumption module, a waste collection and control module. To complement this model, an analysis indicator system based on input-use-output-circular symbiosis for resources metabolism was also proposed. The indicator system includes four categories of indicators: resource input, resource use, environmental stress and circular-symbiosis. Resource input indicators include raw material input, water resource input and energy input; resource use indicators include raw material use, water resource use, energy use and product use; environmental stress indicators include waste discharge and specific material discharge; circular symbiosis indicators include cleaner production, waste control and sustainable use of resources and symbiosis potential. Based on the indicator system, an assessment method by using Fuzzy Analysis and Problems Tree tool for resources metabolism analysis was explored. In addition, an ecological management model was established based on a circular-symbiosis network consisting four modules: a main community module including associated factories; an upstream community module including the factories associated with the main community; a downstream community module including the factories and consumers associated with the main community; a reuse community module including collection, category, process and control factories. The four modules are connected by material flow so that the entire system forms a singular network. By implementing metabolism analysis, the major issues occurring at individual modules or connections can be identified. In turn, the network structure may be optimized through industrial symbiosis management. The following conclusions were drawn: (1) Circular function is weak in traditional industrial ecosystem in comparison to natural ecosystems. Environmental stress comes from resource overuse and excessive waste emissions. (2) Based on the material flow process, the indicator system can effectively reflect the characteristics of resources metabolism. Thus this system can be used as a guide for improving the efficiency of resources use and reducing environmental stress. (3) The method analyzing metabolism effectiveness based on the indicator system and Problems Tree tool is efficient and practical. It can allow decision makers to immediately understand the major problems within different processes and thus make suitable decisions to solve them. (4) The ecological management model based on the ecological networks provides a feasible method to identify and address issues associated with resources metabolism. Applying this model can allow identified stresses on the eco-environment to be released. (5) The approach for resources metabolism analysis proposed in this paper focuses more on processes in comparison to the MFA methods that are implemented at the national and urban scale. This approach may complement MFA methodlogy. This method has been applied in the resource flow analysis of the pulp and paper industry in Wuhan, China. Ongoing work will focus on the research of corresponding policies and databases.