超临界二氧化碳萃取－GC／MS测定土壤中的多环芳烃

本文开发了一种采用超临界二氧化碳萃取土壤中多环芳烃、不须经过纯化步骤，直接可用于ＧＣ／ＭＳ分析的简便、高效的方法。本实验中超临界革取的流体是二氧化碳，改善剂是５％的二氯甲烷／甲醇，萃取温度为１２０℃、压力为３４ＭＰａ。ＧＣ／ＭＳ分析时除了采用外标外，还加入了６种同位素ＰＡＨｓ内标以校正各段ＰＡＨｓ的响应因子。采用本方法成功地测定了我国未开垦森林土壤中的ＰＡＨｓ。     

WK－1A型二氧化硫自动测定仪测定烟气中SO_2的方法研究

本文研究了仪器电导法测定烟气中ＳＯ２的监测方法，并与碘量法进行了比较，提出了吸收液测定的影响及吸收液的配制方法。本方法简单快速，能够满足烟气中ＳＯ２监测工作的要求。     

膜、柱串联固相萃取-高效液相色谱法测定水中多环芳烃(PAHs)的研究

建立了用膜-柱串联固相萃取(SPE)技术,甲醇和水作为流动相进行梯度洗脱,紫外和荧光检测器串联的高效液相色谱法(HPLC)分析水中EPA优先监控的16种PAHs的方法.     

毛细柱气相色谱法测定废水中的三氯乙醛

讨论了用毛细柱气相色谱法测定废水中三氯乙醛的方法。该方法用(2+1)石油醚-乙醚萃取废水中的三氯乙醛,方法的相对标准偏差4.9％,回收率91.2％～101.1％,最低检出限4×10~(-2)ng。     

Photocatalytic degradation of phenol

In this study photocatalytic degradation of phenol in thepresence of UV irradiated TiO₂ catalyst andH₂O₂was investigated. Effects of TiO₂ andH₂O₂concentrations and pH on photocatalytic degradation were examined. The rate constants for photocatalytic degradation wereevaluated as a function of TiO₂ and H₂O₂ concentrations and pH of the solution. It was found thatphotodegradation is an effective method for the removal of phenoland disappearance of phenol obeyed first order kinetics. The amount of CO₂h produced during photocatalytic degradation wascorresponding to the complete mineralization. Photodegradationcan be an alternative method for the treatment of phenol containing wastewaters.     

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.     

微波萃取-气相色谱/质谱法测定土壤中的有机氯农药

通过微波萃取提取土壤中的有机氯农药,萃取溶液经浓硫酸脱色、佛罗里硅土柱净化,最后用气相色谱/质谱法分析.以石英砂为基体进行加标回收测定,有机氯农药的回收率在75.5%～103%之间,检出限为0.01μg/kg.     

Factors influencing Aerosol Characteristics over Urban Environment

Atmospheric aerosols are an important contributing factor to turbidity in urban areas besides having impact on health. Aerosol characteristics show a high degree of variability in space and time as anthropogenic share of total aerosol loading is quite substantial and is essential to monitor the aerosol features over long time scales. In the present study extensive observations of columnar aerosol optical depth (AOD), total columnar ozone (TCO) and precipitable water content (PWC) have been carried over a tropical urban city of Hyderabad, India. Significant variations of AOD have been observed during course of the day with low values of AOD during morning and evening hours and high values during afternoon hours. Spectral variation of AOD exhibits high AOD at smaller wavelengths and vice versa except a slight enhancement in AOD at 500 nm. Anomalies in AOD, particulate matter and black carbon concentrations have been observed during May, 2003. Back trajectory analysis of air mass during these episodes suggested variation in air mass trajectories. Analysis of the results suggests that air trajectories from land region north of study area cause high loading of atmospheric aerosols. The results are discussed in the paper.     

Higher Plants As Bioindicators Of Sulphur Dioxide Emissions In Urban Environments

The evaluation of certain vascular plants that grow in the city of Madrid as biomonitors of SO₂ air pollution in urban environments has been carried out. Total concentration of sulphur in leaves of the chosen higher plants as well as other parameters in close relation to this contaminant (visible injury symptoms, chlorophyll a- and b-content and peroxidase activity) have been determined in order to study the spatial distribution and temporal changes in SO₂ deposition. Results obtained show that coniferous species such as Pinus pinea, were more sensitive to SO₂ atmospheric concentration than leafy species as Quercux ilex subspecies ballota and, in the same way, bush species, such asPyracantha coccinea and Nerium oleander, were more sensitive than wooded species, such as Cedrus deodaraandPinus pinea, respectively. There is a higher accumulation of sulphur in vegetable species located near highways and dense traffic incidence roads and near areas with high density of population. The minimum values for accumulation of SO₂ were registered in winter and spring seasons (from January to April) due to the vegetative stop; while maximum values are obtained during the summer season (from June to September), due to the stoma opening. The highest increments in sulphur concentration, calculated as the difference between two consecutive months, are obtained in May and June for all considered species except forCedrus deodara and Pyracantha coccinea, both species have few seasonal changes during the whole year. Some species are more sensitive to natural washing than others, showing a decrease in sulphur concentration after rainfall periods.