鞍山市城郊污灌区农地污染状况分析与评价

土壤是人类赖以生存的自然资源,它能把大量有机物最终分解为二氧化碳和水,以及各种土壤基肥的其他组成部分,但当施入的废弃物超过土壤的自净力时,就会破坏土壤的正常机能,使之失去自然生态平衡,从而严重影响农作物的产量和品质。文章主要就鞍山市城郊污灌区的农地重金属与农药污染状况作出分析与评价,并利用趋势面分析的方法得出污染的源地,以期为鞍山市污灌区的环境整治工作提供借鉴。     

纺织品中有毒有害物质检测技术的研究现状

纺织品中有毒有害物质超标是纺织品顺利进出口的主要限制因素,而目前中国的检测技术在具体实施中仍存在许多问题。本文阐述了国内纺织品中主要的三类物质检测技术的发展现状,并针对常用检测方法提出一些建议。     

一种高分辨率遥感影像建筑物边缘提取方法

提出一种利用高分辨率遥感影像半自动提取建筑物边缘的方法。先对遥感影像进行预处理,对所有边缘进行边缘检测。然后进行边缘跟踪,提取建筑物的主方向线,利用模型进行线段关系判断,再进行线段关系处理、区域分割和区域生长,最后进行区域合并提取出建筑物的轮廓。用上述方法对Quick Bird卫星的高分辨率影像进行了实验,实验结果证明该方法有较高的识别率、较好的准确性,具有一定的实用价值。     

石墨炉原子吸收法测定电子废弃物处理场地附近植物中的钼

利用预烘干一湿法酸化消解方法处理植物并获得消解液,然后采用涂层石墨管,在探索不同原子化温度与灰化温度的多种优化试验条件基础上,对电子废弃物处理场地附近植物体内的钼进行了测定,样品进行平行试验,相对标准偏差（n=11）〈2．3％。     

ICP发射光谱仪锌元素检出限不确定度分析

依据JJG1059-1999对ICP发射光谱仪锌元素检出限的不确定度进行了评估,分析了影响测量不确定度的各个因素,计算得出ICP发射光谱仪锌元素检出限的扩展不确定度为:U=0.00066(μg.mL-1),k=2。     

填埋场直流电阻电路模型及分析

为研究垃圾填埋场的导电特性,建立了一种填埋场直流电阻电路模型,并对回路中的各部分电阻进行了分析.结果表明:随着供电电极直径和入土深度的增加,回路电阻减小,而随着供电电极与漏洞之间距离的增大,回路电阻缓慢增加;漏洞电阻由接触电阻和内阻组成,前者远大于后者,对一个半径为1cm的圆形漏洞来说,接触电阻可达1500Ω,而内阻只占到接触电阻的1/10;在供电电极周围浇水可明显降低回路电阻,在场内电极直径为20mm,入土深度为0.4m,电极与漏洞之间距离为20m时,浇水后的回路电阻可减小26.6%.     

莱州湾滨海平原咸水入侵分析与趋势预测——以山东省广饶县为例

文章以鲁北平原山东省广饶县为例,阐述了咸、淡水形成的地质背景、咸淡水变化带形成与演化;分析了大规模开发利用地下水引起的咸水入侵的历史与现状;采用非确定性模型方法对咸水入侵趋势进行了预测,提出了缓解咸水入侵的对策与建议。取得的主要认识和结论为:(1)鲁北平原自山前冲洪积扇向莱州湾滨海平原,地下水水质具有水平和垂直分带特征;(2)20世纪70年代中期大量开采南部地下淡水后,地下淡水水位持续下降,破坏了咸淡水之间的水动力平衡,北部咸水向南入侵,引起淡水咸水、机井报废等一系列环境地质问题;(3)预测结果表明,在不采取调控措施情况下,咸淡水界面以每年平均240m速度向南部推进;(4)人工回灌、营造淡水帷幕并减少淡水区开采量是防止咸水入侵的有效途径。     

Real-time leak detection in oil pipelines using an Inverse Transient Analysis model

Based on Inverse Transient Analysis (ITA) method, a real-time leak detection method is proposed to capture leak location and the associated leak rate in oil pipe conveyance systems. In the proposed approach, location and flow rate of leak (if any), the fluid properties, as well as physical parameters of the system, are calculated in consecutive periods through minimizing the discrepancy between the calculated and measured flow parameters of the system. The method of characteristics is employed to numerically calculate the transient responses of the system and the genetic algorithm is utilized as the optimization engine. The proposed approach was applied to several real pipeline systems in which the required transient flow data are either directly collected from the field or fabricated with a third-party numerical software. Extensive numerical explorations were conducted to investigate the performance of the proposed method in real-time leak detection and to determine the extent to which field data errors, stemming from Supervisory Control and Data Acquisition (SCADA) systems and measurement equipment, affect the leak flow rate and location detectability of the proposed approach. The results show that the proposed approach provides promising results under a variety of transient and steady-state flow conditions even in the case with small leak flow rate of around 2% of the line rate. The results also reveal that the noises in the measurement data and the errors originated from SCADA systems do not significantly compromise the leak detectability of the proposed approach, confirming that the proposed approach can be utilized in practice.     

Correction model for CO detection in the coal combustion loss process in mines based on GWO-SVM

Accurate detection of CO gas is crucial to the prevention of coal combustion. Tuneable diode laser absorption spectroscopy (TDLAS) is a reliable method for CO detection during coal combustion. The influences of temperature and pressure cause changes in the line strength and linewidth of the index gases’ absorption spectra, leading to sizable measurement errors. To correct the distortion of the CO absorption spectrum caused by temperature and pressure fluctuation, a compensation model based on the grey wolf optimizer–support vector machine (GWO–SVM) was proposed. The results were compared with those of the single SVM, the back propagation neural network (BPNN), and multiple regression analysis (MRA). MRA was revealed to result in the lowest accuracy, which indicated that MRA is not ideal for compensation in TDLAS. The hyperparameter selection of the SVM had the disadvantages of randomness and blindness, which led to instability and large errors. The BPNN achieved better correction in the training stage, but severe overfitting occurred in the testing stage. The modified results revealed that the GWO–SVM model had higher accuracy and stability than the other models. It effectively inhibited the effects of temperature and pressure on the measured concentration and greatly improved the measurement accuracy. The equipment is thus suitable for CO gas detection with the aim to preventing coal combustion loss, and it can be further applied to loss prevention in other process fields.     

Evaluation of ambient air quality in Guangzhou, China

On the basis of the reported air quality index （API） and air pollutant monitoring data provided by the Guangzhou Environment Monitoring Stations over the last twenty-five years, the characteristics of air quality, prominent pollutants, and variation of the average annual concentrations of SOE, NOE, total suspended particulate （TSP）, fine particulates （PM10）, CO and dustfall in Guangzhou City were analyzed. Results showed that TSP was the prominent pollutant in the ambient air environment of Guangzhou City. Of the prominent pollutants, TSP accounted for nearly 62%, SOE 12.3%, and NOx 6.4%, respectively. The average API of Guangzhou over 6 years was higher than that of Beijing, Tianjin, Nanjing, Hangzhou, Suzhou and Shanghai, and lower than that of Shenzhen, Zhuhai and Shantou. Concentrations of air pollutants have shown a downward trend in recent years, but they are generally worse than ambient air quality standards for USA, Hong Kong and EU. SOE and NOx pollution were still serious, impling that waste gas pollution from all kinds of vehicles had become a significant problem for environmental protection in Guangzhou. The possible causes of worsening air quality were also discussed in this paper.