电厂燃煤锅炉颗粒物分段去除效率及成因分析

选取某大型发电企业进行实测,根据测试数据计算颗粒物去除装置对颗粒物的分段去除效率。结果表明:静电除尘器除尘效率为99.91%、湿法脱硫装置除尘效率为60.51%、湿法脱硫装置出口相对静电除尘器进口的颗粒物去除效率为99.61%、湿法脱硫装置出口颗粒物浓度是静电除尘器出口颗粒物浓度的4.18倍。此外,也依据计算结果并结合实际情况分析了影响各除尘段颗粒物去除效率的主要成因,这些成因主要包括各除尘段功能、脱硫剂与脱硫副产品的颗粒物、脱硫装置运行平稳性等,期望本研究成果能对电厂燃煤锅炉大气污染控制设施关系调整、重新设计及大气环境污染治理思路调整提供重要科学依据与指导。     

柴油车尾气颗粒物排放现状评价

对2013年哈尔滨市不同供油方式的柴油车排气细颗粒物或黑碳测量参数—光吸收系数进行了统计分析,结果表明:涡轮增压和自然吸气供油方式光吸收系数均值分别为1.39 m-1和1.27 m-1,超标率分别为5.8%和2.4%,采用颗粒物控制措施及排气装置强制维护降低了颗粒物排放,符合排放标准。     

Particulate organic matter in the Northern and Central Adriatic

The particulate organic matter distribution and its elemental composition in the northern and central Adriatic Sea during different seasonal periods are shown, highlighting the principal processes and factors influencing their distribution and characteristics. In the low salinity waters the concentrations of particulate carbon, nitrogen and phosphorus were higher and more variable than in the dense waters, mainly due to dilution effects which induce an abundant phytoplankton growth. Generally in summer the particulate organic matter distribution followed the trophic gradient while in winter resuspension events often became more important. Differences between summer and winter were more evident in the diluted waters and were mainly due to the seasonal heat exchanges and to the fresh water inputs. Marked differences in C/P ratios were observed in the POM: high ratios in the northern diluted waters and low in the more saline waters and in the central Adriatic.     

环境空气颗粒物来源解析受体采样频率优选方法初探

环境空气颗粒物来源解析受体样品化学组成的时空差异,除受采样点位分布制约外,主要还受采样时间的制约。如何选取时间段及采样周期显得尤为重要。通过青岛市空气自动监测系统近几年获取的颗粒物连续时均值数据,采用统计优化组合选择法,筛选出日均值、年均值的最佳采样时段,可供类似研究参考。     

Heavy metals and their source identification in particulate matter (PM2.5) in Isfahan City, Iran

The presence of heavy metals(HMs) in particulate matters(PMs) particularly fine particles such as PM_(2.5) poses potential risk to the health of human being. The purpose of this study was to analyze the contents of HMs in PM_(2.5) in the atmospheric monitoring stations in Isfahan city,Iran, in different seasons between March 2014 and March 2015 and their source identification using principle component analysis(PCA). The samples of PM_(2.5) were taken using a high volume sampler in 7 monitoring stations located throughout the city and industrial zones since March 2014 to March 2015. The HMs content of the samples was measured using ICP-MS.The results showed that the concentrations of As, Cd and Ni were in a range of 23–36, 1–12,and 5–76 ng/m~3 at all the stations which exceeded the US-EPA standards. Furthermore,the concentrations of Cr and Cu reached to 153 and 167 ng/m~3 in some stations which were also higher than the standard levels. Depending on the potential sources of HMs, their concentration in PM_(2.5) through the various seasons was different. PCA illustrated that the different potential sources of HMs in the atmosphere, showing that the most important sources of HMs originated from fossil fuel combustion, abrasion of vehicle tires, industrial activities(e.g., iron and steel industries) and dust storms. Management and control of air pollution of industrial plants and vehicles are suggested for decreasing the risk of the HMs in the region.     

Modelling and Prediction of Diesel Engine Performance using Relevance Vector Machine

Diesel engines are being increasingly adopted by many car manufacturers today, yet no exact mathematical diesel engine model exists due to its highly nonlinear nature. In the current literature, black-box identification has been widely used for diesel engine modelling and many artificial neural network (ANN) based models have been developed. However, ANN has many drawbacks such as multiple local minima, user burden on selection of optimal network structure, large training data size, and over-fitting risk. To overcome these drawbacks, this article proposes to apply an emerging machine learning technique, relevance vector machine (RVM), to model and predict the diesel engine performance. The property of global optimal solution of RVM allows the model to be trained using only a few experimental data sets. In this study, the inputs of the model are engine speed, load, and cooling water temperature, while the output parameters are the brake-specific fuel consumption and the amount of exhaust emissions like nitrogen oxides and carbon dioxide. Experimental results show that the model accuracy is satisfactory even the training data is scarce. Moreover, the model accuracy is compared with that using typical ANN. Evaluation results also show that RVM is superior to typical ANN approach.     

Promoting effect of vanadium on catalytic activity of Pt/Ce–Zr–O diesel oxidation catalysts

A series of Pt–V/Ce–Zr–O diesel oxidation catalysts was prepared using the impregnation method. The catalytic activity and sulfur resistance of Pt–V/Ce–Zr–O were investigated in the presence of simulated diesel exhaust. The effect of vanadium on the structure and redox properties of the catalysts was also investigated using the Brunauer–Emmett–Teller method,X-ray diffraction, H2temperature-programmed reduction, CO temperature-programmed desorption, X-ray photoelectron spectroscopy, and Energy Dispersive Spectroscopy. Results showed that the Pt particles were well dispersed on the Ce–Zr–O carrier through the vanadium isolation effect, which significantly improved the oxidation activity toward CO and hydrocarbons. An electron-withdrawing phenomenon occurred from V to Pt, resulting in an increase in the metallic nature of platinum, which was beneficial to hydrocarbon molecular activation.     

平纹滤布除尘性能的研究

从织物的结构来分析过滤的机理,推导出颗粒通过滤布的理论计算式,并用实际滤布作试验来验证该计算式的可靠性。     

La-Na-Co-Mn-O系钙钛矿型催化剂同时去除柴油机碳颗粒和NO_x性能的研究

采用低温燃烧法制备了Na+部分取代La3+的La1-xNaxCo0.5Mn0.5O3系钙钛矿型复合氧化物催化剂。利用程序升温反应(TPR)技术,对催化剂应用于柴油机常规排放物中的碳微粒(soot)和氮氧化合物(NOx)的同时催化脱除性能进行了研究。     

氨荒酸膦酸树脂滤器的制备及其在AAS分析中的应用

本文介绍了氨荒酸膦酸树脂过滤器的制备方法，以及应用该过滤器分离与富集地面水、海水中Ｃｕ、Ｐｂ、Ｚｎ、Ｃｄ多元素的适用条件。实际样品中的Ｃｕ、Ｐｂ、Ｚｎ、Ｃｄ等重金属离子经过过滤器过滤，被吸附在树脂滤层中，用少量酸洗脱，以ＡＡＳ测试，结果稳定、准确度高。此过滤器在痕量分析中具有很高的应用价值。