A new leak location method based on leakage acoustic waves for oil and gas pipelines

In order to study a new leak detection and location method for oil and natural gas pipelines based on acoustic waves, the propagation model is established and modified. Firstly, the propagation law in theory is obtained by analyzing the damping impact factors which cause the attenuation. Then, the dominant-energy frequency bands of leakage acoustic waves are obtained through experiments by wavelet transform analysis. Thirdly, the actual propagation model is modified by the correction factor based on the dominant-energy frequency bands. Then a new leak detection and location method is proposed based on the propagation law which is validated by the experiments for oil pipelines. Finally, the conclusions and the method are applied to the gas pipelines in experiments. The results indicate: the modified propagation model can be established by the experimental method; the new leak location method is effective and can be applied to both oil and gas pipelines and it has advantages over the traditional location method based on the velocity and the time difference. Conclusions can be drawn that the new leak detection and location method can effectively and accurately detect and locate the leakages in oil and natural gas pipelines.     

Analysis of the Trend and Seasonal Cycle of Carbon Monoxide Concentrations in an Urban Area (4 pp)

Background, Aim and Scope Air quality is an field of major concern in large cities. This problem has led administrations to introduce plans and regulations to reduce pollutant emissions. The analysis of variations in the concentration of pollutants is useful when evaluating the effectiveness of these plans. However, such an analysis cannot be undertaken using standard statistical techniques, due to the fact that concentrations of atmospheric pollutants often exhibit a lack of normality and are autocorrelated. On the other hand, if long-term trends of any pollutant’s emissions are to be detected, meteorological effects must be removed from the time series analysed, due to their strong masking effects. Materials and Methods The application of statistical methods to analyse temporal variations is illustrated using monthly carbon monoxide (CO) concentrations observed at an urban site. The sampling site is located at a street intersection in central Valencia (Spain) with a high traffic density. Valencia is the third largest city in Spain. It is a typical Mediterranean city in terms of its urban structure and climatology. The sampling site started operation in January 1994 and monitored CO ground level concentrations until February 2002. Its geographic coordinates are W0°22′52″ N39°28′05″ and its altitude is 11 m. Two nonparametric trend tests are applied. One of these is robust against serial correlation with regards to the false rejection rate, when observations have a strong persistence or when the sample size per month is small. A nonparametric analysis of the homogeneity of trends between seasons is also discussed. A multiple linear regression model is used with the transformed data, including the effect of meteorological variables. The method of generalized least squares is applied to estimate the model parameters to take into account the serial dependence of the residuals of this model. This study also assesses temporal changes using the Kolmogorov-Zurbenko (KZ) filter. The KZ filter has been shown to be an effective way to remove the influence of meteorological conditions on O₃ and PM to examine underlying trends. Results The nonparametric tests indicate a decreasing, significant trend in the sampled site. The application of the linear model yields a significant decrease every twelve months of 15.8% for the average monthly CO concentration. The 95% confidence interval for the trend ranges from 13.9% to 17.7%. The seasonal cycle also provides significant results. There are no differences in trends throughout the months. The percentage of CO variance explained by the linear model is 90.3%. The KZ filter separates out long, short-term and seasonal variations in the CO series. The estimated, significant, long-term trend every year results in 10.3% with this method. The 95% confidence interval ranges from 8.8% to 11.9%. This approach explains 89.9% of the CO temporal variations. Discussion The differences between the linear model and KZ filter trend estimations are due to the fact that the KZ filter performs the analysis on the smoothed data rather than the original data. In the KZ filter trend estimation, the effect of meteorological conditions has been removed. The CO short-term componentis attributable to weather and short-term fluctuations in emissions. There is a significant seasonal cycle. This component is a result of changes in the traffic, the yearly meteorological cycle and the interactions between these two factors. There are peaks during the autumn and winter months, which have more traffic density in the sampled site. There is a minimum during the month of August, reflecting the very low level of vehicle emissions which is a direct consequence of the holiday period. Conclusions The significant, decreasing trend implies to a certain extent that the urban environment in the area is improving. This trend results from changes in overall emissions, pollutant transport, climate, policy and economics. It is also due to the effect of introducing reformulated gasoline. The additives enable vehicles to burn fuel with a higher air/fuel ratio, thereby lowering the emission of CO. The KZ filter has been the most effective method to separate the CO series components and to obtain an estimate of the long-term trend due to changes in emissions, removing the effect of meteorological conditions. Recommendations and Perspectives Air quality managers and policy-makers must understand the link between climate and pollutants to select optimal pollutant reduction strategies and avoid exceeding emission directives. This paper analyses eight years of ambient CO data at a site with a high traffic density, and provides results that are useful for decision-making. The assessment of long-term changes in air pollutants to evaluate reduction strategies has to be done while taking into account meteorological variability     

碘化阶层孔氧化硅纳米球对水中典型有机氯污染物的吸附性能研究

采用共缩聚法,成功地原位合成了碘改性的阶层多孔氧化硅纳米球（SiO₂-I）,研究了其基于卤键作用对典型有机氯污染物六六六的吸附性能,并考察了改性剂I-硅烷含量和pH值对吸附效果的影响.实验结果表明,该纳米材料对六六六表现出优异的吸附富集性能,吸附速率快,60 min内对六六六的去除率为71.6%,240 min内达到吸附平衡,去除率可达98.3%,最大吸附量为178.6 mg·g^-1;吸附动力学符合拟二级动力学模型;碘物种的加入提高了阶层多孔氧化硅的吸附速率和吸附效率.另外,为了便于纳米吸附材料的分离,本研究对SiO₂-I纳米球进行了磁性化.研究发现,磁性化修饰后,SiO₂-I纳米材料仍然保留对六六六优异的吸附富集性能,240 min时的吸附去除率达90.3%.     

Analysis of pollutant levels in central Hong Kong applying neural network method with particle swarm optimization

Air pollution has emerged as an imminent issue in modernsociety. Prediction of pollutant levels is an importantresearch topic in atmospheric environment today. For fulfillingsuch prediction, the use of neural network (NN), and inparticular the multi-layer perceptrons, has presented to be acost-effective technique superior to traditional statisticalmethods. But their training, usually with back-propagation (BP)algorithm or other gradient algorithms, is often with certaindrawbacks, such as: 1) very slow convergence, and 2) easilygetting stuck in a local minimum. In this paper, a newlydeveloped method, particle swarm optimization (PSO) model, isadopted to train perceptrons, to predict pollutant levels, andas a result, a PSO-based neural network approach is presented. The approach is demonstrated to be feasible and effective bypredicting some real air-quality problems.     

A modular approach to Integrated Assessment modeling

In this paper, we present a new approach to model coupling that probably forms the methodological basis of a new generation of Integrated Assessment models. This approach respects the knowledge and expertise that is embodied in existing models and encourages their gradual evolution. Modularity is the guiding principle. Our approach is distinguished by the way modules are coupled which is based on an interplay of a job control module, a numerical coupling module, and a couple of stand-alone functional modules. The numerical coupling module - the core component - serves to treat the feedbacks between the functional modules. A first implemented example that couples an economic and a climate module by means of a two-phase meta-optimization is presented here. The algorithm and mathematical structure behind are discussed as well as important features such as convergence behavior and reliability.     

固定化微生物处理有机污染物的研究进展

综述了近年来固定化微生物技术用于有机污染物治理中的最新进展，这些有机污染物包括难降解有机污染物（酚类、芳香烃类等）及其它化合物（DMP、甲硫醇恶臭气体、制药废水等）。此外，对藻类固定化技术作了简介，并对固定化技术的应用前景及存在问题进行了评述。     

我国热带地区胶—茶—鸡农林复合系统物质循环研究

以海南省文昌市典型的胶—茶—鸡农林复合模式为研究对象 ,以单作胶园、胶茶间作园为对照 ,采用定量研究与定性分析相结合的方法 ,研究其物质循环规律。结果表明 ,胶—茶—鸡农林复合系统的氮、磷输入、输出量最大 ,系统外物质投入率比另两系统明显减少 ,系统内养分循环量增加 ,因此 ,该系统具有较合理的物质循环结构。     

高级氧化技术机理及在水处理中的应用进展

综述了近年来发展迅速的高级氧化技术，主要包括Fenton法、臭氧氧化法、湿式氧化技术、超临界水氧化法、纳米光催化氧化法电化学催化降解法及超声降解法等。介绍了各种高级氧化技术的基本原理及在废水处理中的应用进展，并对其特点进行了评述。     

The Dynamic Safety Evaluation ModelOf the Safety Control Theory and Its Application

The Safety Sate Equation of theSafety System　　 Any system is moving,and the system mo-tion is the results of contradiction existing in thesystem.So is the safety system.In the safetysystem,the contradiction is the affection of thetwo concentrated variables,the hazard(H) andthe hazard control(C) .The ratio of injury anddeath of the system (Y) is one of the indexes de-scribing the safety state of system.Therefore,Yis the reflection of the result between hazard Hand hazard control C.Ac…     

综合福利视角下中国生态文明建设绩效评价及国际比较

基于强可持续研究范式,以生态经济学和可持续发展理论为基础,运用两阶段网络Super-EBM模型进行绩效测算和评价,打开生态福利转化过程的“黑箱”,基于综合福利视角将生态文明建设绩效进一步分解为生态经济效率和经济福利效率,实证研究部分选取2006-2015年的时间序列数据对中国“十一五”和“十二五”期间的生态文明建设绩效水平进行纵向分析,与此同时,选取42个国家2014年的截面数据进行横向的国际对比研究。研究表明：（1）“十一五”到“十二五”期间,中国生态文明建设绩效（0.986）整体水平一般,均未实现DEA有效,但“十二五”期间已呈现出逐年改善的利好趋势。国际比较层面,瑞士（1.647）、印度尼西亚（1.365）、爱尔兰（1.039）依次排名前三位,中国（0.297）排名相对靠后,位列倒数第二。各国之间差异较大,总体上呈现出“OECD国家（0.677）最高、G20国家（0.611）次之、金砖国家（0.417）最低”的态势。（2）从分阶段效率来看,无论是纵向分析还是横向对比,均发现第一阶段的生态经济效率明显低于第二阶段的经济福利效率,生态经济效率偏低是导致生态文明建设绩效总体水平偏低的主要原因。（3）与传统的单阶段、径向或非径向DEA模型相比,两阶段网络Super-EBM模型综合考虑了径向和松弛变量问题,测算出来的效率值更为精确,能够更为客观地反映现实。同时,对于其他领域涉及两阶段或多阶段生产系统的效率或绩效评估具有较好的借鉴价值。最后,根据上述结论提出相应的政策建议。