China, an oil and NG scarcity country, is coal dependent, and this situation will remain for a long time. DME, as an ideal replacer of liquid fuel, is considered to develop. The efficient way of producing DME from coal is under research. Considering the components of coal and natural gas (NG), we choose co-feed (coal and NG) and co-production (electricity and DME) system (Co–Co system) to be studied on. Three systems which are the standalone system, co-generation system and Co–Co system are simulated by Aspen-Plus. The simulation results concerning material flows, exergy flows, CO2 emission and the evaluation indexes are obtained. It is found that Co–Co system has higher exergy efficiency, higher economic benefit, and it is environmental friendly because of releasing the least CO2.The analysis llustrates that Co–Co system has obviously advantage over the other two kinds of systems.

生态工业作为一种新型的工业发展模式，兼顾了经济、资源和环境等多方面的需求，是实现可持续发展的一种重要途径。本文应用Matlab-simulink工具箱建立了一个生态工业系统模型，进行了仿真分析，在此基础上提出生态工业系统柔性分析的影响因子法，对限制系统柔性的关键因素进行分析，提出了改进系统柔性的方案。对某工业园区的实例分析表明，该模型能够给出稳态和动态的仿真结果并较好地改善系统柔性。

针对现代中国磷资源利用存在的问题，以代谢网络模型为基础，从代谢结构和代谢强度2个方面对不同历史时期中国磷元素代谢模式的演化过程进行分析。代谢强度指标包括；磷输入量、磷循环量及磷循环率、产品载磷量及产品载磷率、水体排磷量及水体排磷率、固废输磷量及固废输磷率。分析表明：中国现代社会磷元素代谢不可持续的瓶颈包括土壤累积量增加、水体排磷量增加、磷循环率降低和“农田土壤”产品载磷率降低4个方面。并从微观层面揭示中国磷资源利用过程中不合理的环节，提出了相应的解决策略。

磷是国民经济发展必须的重要矿产资源，由于其难以再生的特点，它的消耗将造成严重的资源流失，各种含磷产品的消费对水体等自然环境也会产生巨大影响。本文以科学发展观为指导，贯彻循环经济理念，从磷矿资源产业全生命周期出发，运用灰色系统方法建立其动态模型，在此基础上对现状发展趋势及各项循环经济策略实施效果进行定量描述和情景分析，考察磷资源的利用和环境影响状况，比较优劣，得到结论以指导实践，具有重要意义。

A systematic methodology is presented for refinery modelling and optimisation on the basis of much more detail molecular information than conventional lumped methods. The novelty of this work is to incorporate models based on microscopic understanding into optimisation to achieve macroscopic im- provement. A molecular matrix based on homologous series of hydrocarbon compounds (B. Peng, Ph.D. Thesis, UMIST, 1999, pp. 22-41) is used to characterise refining streams. A transformation method is developed for obtaining molecular compositions from stream bulk properties. Molecular models are then built for several processes. Molecular modelling and optimisation are finally integrated into an overall refinery optimisation framework. Results show that molecular information can provide much better un-derstanding and new insights into refining operation. Consequently optimisation based on molecular modelling can greatly improve total profit while making quality products satisfying environmental regu-lations.