Pb/Zn冶炼废渣中重金属的生物浸出-盐浸处理

利用中温嗜热菌对某铅锌冶炼废渣进行生物浸出盐浸处理研究,并根据国家固体废物浸出毒性方法(HJ/T299-2007)对盐浸后余渣进行毒性分析。研究结果表明,在pH 1.5、温度65℃、矿浆浓度5%的优化条件下生物浸出3 d后,废渣中Cu、In、Ga和Zn的浸出率分别达到了91.5%、91.8%、84.9%和93.4%;盐浸生物浸出渣,其浸出液中Ag、Pb浓度分别为7.6和247.5 mg/L,可从废渣中有效回收Cu、In、Ga、Zn、Ag和Pb。生物浸出盐浸处理后余渣约为原渣量的70%;毒性分析浸出液中重金属元素Ag、As、Cd、Cu、Pb和Zn浓度分别为2～3.5、2～3、0.3～0.5、30～50、2～4、20～60 mg/L,低于国家危险废物鉴别标准(GB5085.3-2007)。根据试验结果,提出了针对冶炼废渣资源化、减量化、无害化的生物浸出盐浸联用工艺。     

湖州市埭溪镇污水处理厂的工程设计

湖州市埭溪镇污水处理厂的设计规模,近期为2万m^2／d,远期为3万m^2／d,其污水处理工艺采用改良式A^2／O工艺,污泥处理工艺采用带式浓缩脱水一体机。文中着重介绍了工程设计参数、处理工艺流程及其设计特点。     

人为泥石流起动及产沙放水冲刷实验——以神府-东胜矿区为例

神府东胜矿区位于黄土高原北部干旱半旱过度地带。由于煤田的大量开采,诱发了大量的环境问题,尤以人为泥石流最为严重,本文以神府－东胜矿区人为泥石流为研究对象,采用人工放水冲刷模拟的方法,分析了坡面型和沟谷型泥石流源地松散体起动、产沙、泥石流过程的特性,所得结论为：（１）放水历时长,强度大,有利于泥石流的形成;（２）弃土石渣起动,是该区泥石流固体物质的主体;（３）沟道型泥石流放水冲刷模拟实验,便于观测石     

Comparison of China’s Environmental Impact Assessment (EIA) Law with the European Union (EU) EIA Directive

In this paper, we first review the development of China’s Environmental Impact Assessment (EIA) system in the past 30 years. Then we compare the framework and operational procedures of China’s new EIA law with those of the EU EIA Directive. We also compare public participation, as well as sanctions and control in the two EIA systems. In addition, we identify where the processes in both EIA systems are similar or different from one another. By comparison, we noted that there are at least three obvious weaknesses in China’s EIA system: (1) the application of new models for EIA legislation; (2) the improvement of EIA guidance and education; and (3) the enhancement of public participation in EIA process. Our study indicates that these three major shortcomings should be overcome and improved in China’s EIA system, when compared with the EU EIA system.     

固硫生物型煤

研究出生物型煤的生产工艺流程,对型煤和生物型煤的固硫技术进行了研究,成功试验生产出固硫性能优良的生物型煤,为中国煤能源可持续发展利用开辟了新途径。     

Uncertainty in integrated coastal zone management

Uncertainty plays a major role in Integrated Coastal Zone Management (ICZM). A large part of this uncertainty is connected to our lack of knowledge of the integrated functioning of the coastal system and to the increasing need to act in a pro-active way. Increasingly, coastal managers are forced to take decisions based on information which is surrounded by uncertainties. Different types of uncertainty can be identified and the role of uncertainty in decision making, scientific uncertainty and model uncertainty in ICZM is discussed. The issue of spatial variability, which is believed to be extremely important in ICZM and represents a primary source of complexity and uncertainty, is also briefly introduced. Some principles for complex model building are described as an approach to handle, in a balanced way, the available data, information, knowledge and experience. The practical method of sensitivity analysis is then introduced as a method for a posterior evaluation of uncertainty in simulation models. We conclude by emphasising the need for the definition of an analysis plan in order to handle model uncertainty in a balanced way during the decision making process.     

Infrastructure development through PPPs in India: criteria for sustainability assessment

Public private partnerships (PPPs) allow the Indian Government to leverage private capital for meeting the widening demand-supply gap in the provision of infrastructure services. The private sector, however, prefers to limit the participation to financially attractive projects only, thereby resulting in patterns of infrastructure creation impeding the progress towards sustainable development. In order to promote sustainable development, the PPP procurement process should focus on incentivising the private sector for sustainable infrastructure development rather than concentrating on ensuring financial sustainability only. This paper discusses the principles-based PPP-specific framework that has been developed to facilitate assessment of PPP projects' progress towards sustainable development. The framework development was based on a holistic approach to sustainability assessment and subsequently validated through questionnaire survey with key stakeholders in the Indian PPP programme. This framework will provide the decision makers with appropriate decision aid for integration of sustainable development principles in the PPP procurement process.     

Application of environmental risk assessment for strategic decision-making in coastal areas: case studies in China

Environmental risk assessment (ERA) is a powerful technical tool for analyzing potential and extreme adverse environmental impacts, and has found wide application in supporting decision-making processes over the last two decades. However, to date there has been no interrelated application of ERA to support the processes of strategic decision-making (SDM), especially in coastal areas.

In this paper, we attempt to verify the feasibility of the proposed integrated ERA–SDM approach and its methodology by applying it to two case studies (in Xiamen Bay and Luoyuan Bay) of the principal coastal functional zoning (PCFZ, a kind of SDM and similar to the coastal and marine spatial planning in western). The results show that the integrated ERA–SDM approach could integrate ERA into the entire SDM process, directly support the PCFZ, and avoid or mitigate dire environmental risk that can be introduced by SDM processes.     

钙钛矿型La_(0.8)Ce_(0.2)Fe_(1-x)Co_xO_3催化剂的制备及其三效催化活性

采用自燃烧法制备了一组钙钛矿型复合氧化物La_(0.8)Ce_(0.2)Fe_(1-x)Co_xO_3(x=0.9,0.7,0.5,0.3,0.1),并考察了其对CO、C_3H_6和NO的三效催化活性。XRD和SEM表征结果显示,La_(0.8)Ce_(0.2)Fe_(1-x)Co_xO_3具有良好的钙钛矿型晶体结构,晶粒大小为纳米级并自组装成片状结构。催化剂的比表面积为14.73~22.43 m~2/g,含有微孔和介孔结构。催化活性评价结果表明:La_(0.8)Ce_(0.2)Fe_(0.1)Co_(0.9)O_3具有很好的三效催化活性,在理论空燃比的条件下,CO、C_3H_6和NO的起燃温度分别为195℃、264℃和290℃,完全转化温度分别为239℃、418℃和415℃,低温三效催化活性良好;Fe和Co的掺杂量同时影响着La_(0.8)Ce_(0.2)Fe_(1-x)Co_xO_3的催化效果。     

Optimizing mixture properties of biodiesel production using genetic algorithm-based evolutionary support vector machine

Nowadays, biodiesel is used as one of the alternative renewable energy due to the increasing energy demand. However, optimum production of biodiesel still requires a huge number of expensive and time-consuming laboratory tests. To address the problem, this research develops a novel Genetic Algorithm-based Evolutionary Support Vector Machine (GA-ESIM). The GA-ESIM is an Artificial Intelligence (AI)-based tool that combines K-means Chaotic Genetic Algorithm (KCGA) and Evolutionary Support Vector Machine Inference Model (ESIM). The ESIM is utilized as a supervised learning technique to establish a highly accurate prediction model between the input--output of biodiesel mixture properties; and the KCGA is used to perform the simulation to obtain the optimum mixture properties based on the prediction model. A real biodiesel experimental data is provided to validate the GA-ESIM performance. Our simulation results demonstrate that the GA-ESIM establishes a prediction model with better accuracy than other AI-based tool and thus obtains the mixture properties with the biodiesel yield of 99.9%, higher than the best experimental data record, 97.4%.