沈阳市浑南新区发展循环经济可行性探讨

浑南新区拟用循环经济和生态工业的理论建设生态工业园区,为切实做好新区创建环保样板城循环经济试点工作,将发展循环经济的观念注入全区经济结构调整和产业转型之中,从根本上解决浑南新区在发展过程中遇到的经济增长与资源环境之间的尖锐矛盾,协调社会经济与资源环境的发展。以园区内主导优势产业的物质、能量的资源化利用为基础,以生态产业链为主线建立园区的生态工业,在经济结构战略性调整中大力推进循环经济。     

生态工业园工业共生网络的构建

工业共生网络是生态工业园建设过程中的核心内容。本文以铜陵循环经济工业试验园为例,开展了工业共生网络构建的实证研究。研究内容主要包括：（1）试验园建设背景和产业现状分析;（2）生态产业链（硫化工产业链、冶金产业链、纺织服装产业链、铜延伸加工产业链）的构建;（3）各产业链间在物质、能量和水层面上的耦合共生。最后,从参与共生企业的所有权关系和网络构成方式两方面,对试验园工业共生网络模式的优缺点进行了讨论,并提出进一步完善的建议。     

聚苯乙烯热降解动力学参数与降解反应机理关系

基于Arrhenius理论及相关公式,推导出表观活化能与幂指数相对变化关系。这种相对变化关系与聚苯乙烯热降解、热氧化降解、及其在各种添加剂情形下热降解动力学参数变化特征完全吻合。     

Modeling flood induced interdependencies among hydroelectricity generating infrastructures

This paper presents a new kind of integrated modeling method for simulating the vulnerability of a critical infrastructure for a hazard and the subsequent interdependencies among the interconnected infrastructures. The developed method has been applied to a case study of a network of hydroelectricity generating infrastructures, e.g., water storage concrete gravity dam, penstock, power plant and transformer substation. The modeling approach is based on the fragility curves development with Monte Carlo simulation based structural–hydraulic modeling, flood frequency analysis, stochastic Petri net (SPN) modeling, and Markov Chain analysis. A certain flood level probability can be predicted from flood frequency analysis, and the most probable damage condition for this hazard can be simulated from the developed fragility curves of the dam. Consequently, the resulting interactions among the adjacent infrastructures can be quantified with SPN analysis; corresponding Markov Chain analysis simulates the long term probability matrix of infrastructure failures. The obtained results are quite convincing to prove the novel contribution of this research to the field of infrastructure interdependency analysis which might serve as a decision making tool for flood related emergency response and management.     

Regional Scale Stressor‐Response Models in Aquatic Ecosystems1

Abstract: A systematic method for identification and estimation of regional scale stressor‐response models in aquatic ecosystems will be useful in monitoring and assessment of aquatic resources, determination of regional nutrient criteria and for increased understanding of the differences between regions. The model response variable is chlorophyll a, a measure of algal density, while the stressors include nutrient concentrations from the USEPA Nutrient Criteria Database (NCD) for lakes/ponds and reservoirs of the continental United States. The NCD has observations for both stressors and biological responses determined using methods that are not consistently available at the continental scale. To link multiple environmental stressors to biological responses and quantify uncertainty in model predictions, we take a multilevel modeling approach to the estimation of a linear model for prediction of log Chlorophyll a using predictors log TP and log TN. The multilevel modeling approach allows us to adjust the impact of covariates at all levels (observation, higher level groups) for the simultaneous operation of contextual and individual variability in the outcome. Here, we wish to allow separate regression coefficients for inference regarding similarities and differences between each of 14 ecoregions, and between the two water‐body types, lakes/ponds and reservoirs. We are also interested in the nuisance effects of the categorical variables indicating the type of nitrogen measurements (three levels) and the type of chlorophyll a measurements (four levels) used. Model‐based determination of nutrient criteria points to an apparent incompatibility of criteria developed for nutrient stressors and eutrophication responses using current Environmental Protection Agency’s guidance.     

论循环经济在工业园区规划中的作用

新兴的工业园区在规划建设中应遵循一定的发展规律,而循环经济体现在区域层面即是中循环,这也正是现代工业集成的发展趋势。将循环经济理念融入工业园区的规划建设中已成必然。     

Characterizing natural degradation of tetrachloroethene (PCE) using a multidisciplinary approach

A site in mid-western Sweden contaminated with chlorinated solvents originating from a previous dry cleaning facility, was investigated using conventional groundwater analysis combined with compound-specific isotope data of carbon, microbial DNA analysis, and geoelectrical tomography techniques. We show the value of this multidisciplinary approach, as the different results supported each interpretation, and show where natural degradation occurs at the site. The zone where natural degradation occurred was identified in the transition between two geological units, where the change in hydraulic conductivity may have facilitated biofilm formation and microbial activity. This observation was confirmed by all methods and the examination of the impact of geological conditions on the biotransformation process was facilitated by the unique combination of the applied methods. There is thus significant benefit from deploying an extended array of methods for these investigations, with the potential to reduce costs involved in remediation of contaminated sediment and groundwater.Electronic supplementary materialThe online version of this article (10.1007/s13280-020-01418-5) contains supplementary material, which is available to authorized users.     

Road to full bioconversion of biowaste to biochemicals centering on chain elongation: A mini review

Production of biochemicals from waste streams has been attracting increasing worldwide interest to achieve climate protection goals. Chain elongation(CE) for production of mediumchain carboxylic acids(MCCAs, especially caproate, enanthate and caprylate) from diverse biowaste has emerged as a potential economic and environmental technology for a sustainable society. The present mini review summarizes the research utilizing various synthetic or real waste-derived substrates available for MCCA production. Additionally, the microbial characteristics of the CE process are surveyed and discussed. Considering that a large proportion of recalcitrantly biodegradable biowaste and residues cannot be further utilized by CE systems and remain to be treated and disposed, we propose here a loop concept of bioconversion of biowaste to MCCAs making full use of the biowaste with zero emission. This could make possible an alternative technology for synthesis of value-added products from a wide range of biowaste, or even non-biodegradable waste(such as, plastics and rubbers). Meanwhile, the remaining scientific questions, unsolved problems, application potential and possible developments for this technology are discussed.     

K_4锅炉改善燃煤条件消烟除尘效果显著

采用机械燃烧方式和炉膛内部改造相结合方法以及装设省煤器和除尘器等技措施，对阜阳市青峰机械厂Ｋ４锅炉进行技术改造，不仅使排放烟尘达到国家标准，而且提高了锅炉热效率．经过几年运行实践，解决了Ｋ４锅炉烟尘污染问题，该方法对于保护环境，节约能源有较大的实用价值．     

Availability estimation of a multi-state wind farm in fuzzy environment

Wind is one of the fastest growing renewable energy resources in the electric power system. Availability of wind energy is volatile in nature due to the stochastic behavior of wind speed and non-linear variation of the wind power curve of wind turbine generator. Because of this impression and uncertainty, the availability estimation of wind power has become a challenging issue. In this paper, Markov Fuzzy Reward technique has been proposed for finding out the reliability of wind farm by assessing the availability of wind power. According to this technique, availability of the wind power has been estimated considering wind farm and demand both as a multi-state system. In addition to the availability, different reliability indices such as the number of absolute failures, mean time to deficiency, and probability of failures of a wind farm have been assessed in a time horizon, which can provide useful information for the power system planner at wind farm installing stage. A comparison of this study reveals the efficacy of the proposed Markov Fuzzy Reward approach over the conventional Markov Reward approach.