小型水利工程项目对环境的影响分析与研究

水利工程是农业项目发展的重要组成部分之一,小型水利工程项目的建设对环境的影响不容忽视。因此,以环境影响因素为基础对水利工程项目进行详细的设计是保障工程有序进行的重要前提。环境影响评价工作直接影响水利工程建设方案的价值,是判断工程设计方案可行性的重要依据。通过对小型水利工程项目对环境的影响进行调查和分析以及对水利工程对周围环境带来的影响进行评析,分析和介绍了环境影响评价的原则和思想,进而分析了水利工程建设与环境之间的关系,希望为建设水利项目提供借鉴作用。     

西安市文教区表层土壤中PAHs来源及风险分析

文教区土壤环境质量直接影响学生以及职工的身体健康。本研究应用高效液相色谱仪对采集的西安市文教区表层土壤样品中的16种优控多环芳烃(PAHs)进行含量检测,分析其组分特征、来源及健康风险。结果表明,西安市文教区表层土壤中∑PAHs含量为0.290~4.147μg/g,平均值为1.515μg/g,7种致癌多环芳烃的含量为0.079~2.093μg/g,均值为0.593μg/g,土壤PAHs污染较为严重。其中4环的高环PAHs为土壤PAHs污染的主要物质,平均占∑PAHs含量的40.72%。源解析结果表明西安市文教区表层土壤中PAHs主要来源于石油燃烧、煤及生物质等的不完全燃烧。终生癌症风险评价表明西安市文教区表层土壤中PAHs污染对其生活在周围的人群产生的终生致癌风险性较小,但71.4%的样点达到严重污染水平,产生的间接影响应引起足够重视。     

8-氨基喹啉-5-偶氮-对苯酚荧光光度法测定微量铬(Ⅵ)

在盐酸介质中,铬(Ⅵ)与AQAPOH形成可被氯仿萃取的荧光化合物,其λex/λem=295nm/400nm.线性范围为0-1.0μg Cr(Ⅵ)/25ml(水相),检测限为0.7μg/L.除Mn(Ⅶ)外,常见金属离子无干扰,可在数千倍Cr(Ⅲ)存在下测定废水中微量铬(Ⅵ).初步探讨了荧光反应的机理.     

湖南未耕种土壤中~(234、238)U、~(226)Ra、~(210)Po和~(210)Pb的分布和移动规律的研究

本文采集了湖南省十三个地区未耕种的０８０ｃｍ不同类型土壤样品，分别测定了０１０ｃｍ、２０３０ｃｍ、４０５０ｃｍ、７０８０ｃｍ样品中的２３４、２３８Ｕ、２２６Ｒａ、２１０Ｐｂ、２１０Ｐｏ含量，研究了土壤中铀系放射性核素分布影响和移动规律     

浅谈烟道气现场监测的工作管理

烟道气现场监测，易出差错。监测人员必须有良好的专业理论水平、丰富的工作经验、高度的敬业精神。本文就现场监测工作易出现问题进行了分析，列举了解决问题的方法     

原煤二氯甲烷浸取液中多环芳烃分布特征

本文用色谱／质谱／红外联用系统研究了原煤二氯甲烷浸取液中多环芳烃的种类、数量、含量及其分布特征。为进一步研究煤燃烧排放飞灰、烟气、炉渣中多环芳烃分布打下良好基础。     

空气颗粒物中铅、镉超声浸取-原子吸收测定方法研究

用超声波震荡方法对大气滤膜样品进行前处理,提取待测元素。研究了浸取液种类、酸度、浸取时间和干扰因素等,确定了颗粒物样品溶液制备的最佳条件,与流动注射在线富集——原子吸收技术结合,建立了大气颗粒物样品测定Pb、Cd方法。结果表明,方法快速、准确,标准样品测定回收率在97％以上,6次测定方目对标准偏差小于2.6％。     

大气环境质量模糊评价的可视化实现

以模糊聚类法为算法基础,运用计算机可视化技术,进行大气环境质量评价初步探索。计算机技术在环境评价中的应用,可以方便数据处理和资源共享。选用武汉市大气环境监测资料,应用该方法评价和分析武汉市大气环境质量,取得了令人满意的结果。     

Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NO_x and NO₂ are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x and NO₂ concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods.     

Determination of organophosphorus pesticides and related compounds in water samples by membrane extraction and gas chromatography

A membrane extraction-gas chromatography method was developed fordetermination of organophosphorus pesticides and related compounds including methamidophos, DDVP, dimethoate, methyl parathion, parathion, thiophosphoric acid trimethyl ester, and thiophosphoramidic acid dimethyl ester in water samples. In thismethod, surface-modified acetic cellulose membranes were used to extract the target analytes in water samples, the extracted analytes were back-extracted into a small amount of methanol, andgas chromatography with pulsed flame photometric detector (GC-PFPD) was used to determine the concentrations of targetanalytes in the extracts. The recoveries obtained for thetarget analytes spiked into the water samples ranged from 66to 94%. The method detection limit for each target analyte was 0.05 g L^-1. The method developed in this study had shown the advantages of being cheap, simple, fast, and reliable. It had been used successfully to determine the concentrations of target analytes in river water samples.