井下光谱多参数分析系统开发

本系统基于气体浓度光学分析方法理论朗伯-比尔(Lambert-Beer)定律、光谱气体检测技术开发,实现了对煤矿火灾与瓦斯灾害超前预警、灾害产生的有毒有害气体实时监测和煤矿环境气体爆炸危险性辨识,对于煤矿灾害防治、救灾过程中杜绝次生灾害,保障煤矿工人及救护队员的生命安全,促进煤矿安全生产具有重要意义。     

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     

表面活性剂吸收法治理含苯废气的中试实验

采用添加表面活性剂的填料塔来吸收治理含苯废气，分析了水一吸收剂的吸收机理。考察了喷淋量、废气入口浓度和表面活性剂添加量这三个因素对苯去除率的影响。结果表明，对苯来说入口浓度对去除率的影响最大，喷淋液体流量次之，表面活性剂的影响最小。条件满足时，含苯废气可以达标排放。     

用煤矸石制取水玻璃的研究

本文研究了用煤矸石制取水玻璃的可行性，利用正交试验，研究了焙烧温度、焙烧时间、反应温度、ＮａＯＨ浓度、渣样粒度等因素对制取过程的影响，确定了最佳操作条件。     

燃煤锅炉排烟脱硫技术

本文介绍了治理燃煤排烟除脱ＳＯ２的主要技术和工艺流程，并对其进行了比较。     

分级喷水增湿对半干法烟气脱硫效率的影响

研究了增湿水量、增湿水级数以及增湿水分配方式等参数对半干法烟气脱硫效率的影响。得出了一定试验条件下这些参数的优化值，它们分别为：增湿水量30％、三级增湿、递减分配方式。在此优化工况下，可以使塔内和系统脱硫效率分别达到68％和90％以上，比无增湿时分别提高6％和5％左右。     

红外和热分析联用在化工产品研究中的应用

运用实例论述了红外光谱分析与热分析联用在化工产品的产品开发和检测方面的应用。     

城市燃气管网的地震紧急处置系统研究

燃气管网的地震破坏有时会导致火灾、爆炸等严重的次生灾害。城市中的燃气管网系统若能具备地震紧急处置功能,在地震来临时及时采取自动关闭燃气供应阀门等紧急处置措施,可以避免或减少此类次生灾害的发生。介绍了普遍用于燃气管网日常调度管理的SCADA系统的组成与工作原理,探讨了在SCADA系统中加入地震紧急处置功能的可行性,并基于ArcGIS地理软件,通过VBA二次开发编制了燃气管网的地震紧急处置模拟程序,为燃气管网地震紧急处置系统的实现提供了一定依据。     

钯离子液相催化氧化低浓度磷化氢

采用Pd^2＋液相催化氧化低浓度PH3,考察了Pd^2＋浓度、O2体积分数、PH3质量浓度、混合气流量、反应温度等因素对Pd^2＋吸收液去除低浓度PH3效果的影响。实验结果表明,采用10mL Pd^2＋浓度为0．112mol／L的水溶液作为吸收液净化含低浓度PH3的混合气,在反应温度22℃、O2体积分数5％、PH3质量浓度850mg／m^3、混合气流量190mL／min的条件下,印min之内PH3去除率保持在90％以上。Pd^2＋浓度越高、O2体积分数越大、反应温度越高,PH3去除率越高;混合气流量越大,PH3去除率越低;反应温度越低、O2体积分数越大,PH3去除率的下降速率越小。