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.     

利用卫星遥感数据估算PM2.5浓度的应用研究进展

近年来,PM_(2.5)已成为中国大气污染的首要污染物,危害人体健康。为弥补地基监测站点在空间分布上的局限性,借助卫星遥感技术估算PM_(2.5)浓度已成为研究热点。文章总结了利用卫星估算PM_(2.5)浓度的各种研究方法,探讨了不同方法的优势和不足,指出不同方法对不同应用目的的选择性差异较大。提出,应针对不同应用目的选择相应的方法,从而取得满足各方面需求的研究成果,为未来PM_(2.5)浓度估算应用工作提供参考。     

基于支持向量回归机的南黄海浒苔分布面积预测模型

绿潮作为一种新型的海洋灾害,已经引起了各个国家的重视.依据2012年南黄海海域浒苔遥感监测分布面积数据,选取了温度、天气状况、风向、风力、浪高5种影响浒苔扩散的气候因子,建立了基于SVR的浒苔分布面积预测模型,并与经典的最近邻点插值模型、线性插值模型、3次样条函数插值模型和分段3次Hermite插值模型进行了回归效果的对比.分析结果表明,基于SVR的浒苔分布面积预测模型能够为浒苔遥感数据的插补提供一种方法,且回归效果优于传统的回归方法,为浒苔的防治提供辅助决策信息.     

16S rDNA克隆文库解析AO-MBR系统中细菌种群多样性

采用分子生物学手段16S rDNA克隆文库方法对缺氧/好氧膜生物反应器(AO-MBR)的好氧池与缺氧池中细菌进行了多样性研究.实验结果表明,好氧池污泥样品的克隆文库包括9个类群,其中变形菌(Proteobacteria)和拟杆菌(Bacteroidetes)在文库中所占比例最大,分别为37.04％和14.81％;其次是酸杆菌(Acidobacteria)、未培养菌(uncultured bacterium)、绿菌(Chlorobi)和未培养的绿弯菌(uncultured Chloroflexi bacterium)、浮霉状菌(Planctomycetes),分别为11.11％、11.11％、7.41％、7.41％和5.56％;硝化螺旋菌(Nitrospirae)和裸藻门(Euglenozoa)所占比例相对较小,均为1.85％.缺氧池样品克隆文库包括10个类群,其中变形菌(Proteobacteria)、拟杆菌(Bacteroidetes)和未培养菌(uncultured bacterium)在文库中所占比例最大,分别为27.91％、13.95％和12.79％;其次是浮霉状菌(Planctomycetes)、酸杆菌(Acidobacteria)和绿弯菌(Chloroflexi),在文库中所占比例分别为9.3％、9.3％和9.3％;硝化螺旋菌(Nitrospirae)、裸藻门(Euglenozoa)、芽单胞菌(Gemmatimonadetes)和放线菌(Actinobacteria)所占比例相对较少,分别为6.98％、8.14％、1.16％和1.16％.两池细菌的主要类群相似,但菌属及比例有所差异,变形菌是系统中的主要脱氮菌属.     

固相萃取-气质联用法测定固体废物浸出液中的二硝基苯

建立了一种利用固相萃取法对固体废物浸出液(TCLP)中二硝基苯进行萃取,DB-5石英毛细管柱(30 m×0.25 mm×0.25μm)进行分离,质谱检测器检测二硝基苯的方法。方法在0.002 0~0.020 0 mg/L之间线性关系良好,二硝基苯三种同分异构体的检出限均为0.5μg/L,模拟样品加标回收率为93%~96%,RSD≤2%;实际固体废物样品测定的加标回收率为95%~98%。     

利用3S技术动态监测天山草地农业产量及其成因分析

在新疆阜康县大量“天地”资料观测基础上，利用3S(RS、GIS和GPS)技术和生态系统分析方法，对新疆天山草地农业资源进行了系统的动态监测和大面积估产研究。结果表明，该县草地和森林面积1998年比1988年分别下降了17．5％和51．o％，而农业用地面积和沙漠危害面积却分别增加了57．8％和21．2％，实现了利用3s技术系统准确监测新疆阜康县草地农业资源动态变化，其大面积草地遥感估产精度达到75．8％以上。最后，建立了新型PPR估产模型，其估产精度达到81．76％以上，并给出了理论生态成因解释与定量分析结果等。     

湖北省2008年初低温雨雪冰冻过程气候特征分析

2008年初，湖北省出现了严重的低温雨雪冰冻灾害，直接经济损失高达110亿元以上，有必要对灾害期间的气候特征进行系统、科学的分析和总结。对湖北省76个气象站2008年1月12日～2月3日气温、降水（雪）、日照以及低温持续日数等要素进行时空间差异分析及历史与同期比较，并选取10个代表站历史上所有低温雨雪天气过程，对其过程持续低温日数、最长连续雨雪日数、过程极端低温进行比较分析。结果表明：（1）此次过程的平均气温异常偏低，该省大部为-1～-2℃，比常年同期偏低4～6℃，为各站历史同期最低，其中主要是最高气温异常偏低所致，但极端低温并不低；（2）降雪过程频繁，雨雪量异常偏多；（3）低温冰冻持续时间长，该省大部在16～22 d，位于历史第一；（4）日照异常偏少。持续而稳定的大气环流异常形势是湖北省大范围低温雨雪天气的直接原因。     

城市给水管网优化设计研究

研究了几种典型的城市给水管网优化设计数学模型,并给出了求解方法,指出在给水管网系统的优化设计中进一步完善广义简约(GRG)算法的必要性.     

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