River water quality and pollution sources in the Pearl River Delta, China

Some physicochemical parameters were determined for thirty field water samples collected from different water channels in the Pearl River Delta Economic Zone river system. The analytical results were compared with the environmental quality standards for surface water. Using the SPSS software, statistical analyses were performed to determine the main pollutants of the river water. The main purpose of the present research is to investigate the river water quality and to determine the main pollutants and pollution sources. Furthermore, the research provides some approaches for protecting and improving river water quality. The results indicate that the predominant pollutants are ammonium, phosphorus, and organic compounds. The wastewater discharged from households in urban and rural areas, industrial facilities, and non-point sources from agricultural areas are the main sources of pollution in river water in the Pearl River Delta Economic Zone.     

连续采样与五日法采样效果及费用的对比分析

通过对连续采样与五日法采样五种方法监测结果及所需费用的比较，得出连续采样方法监测结果更具有代表性，合理性，一次性投资大，但运行费用并不高的结论。     

Faculty position announcement

Faculty position announcement     

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.     

采样系统中金属氧化物对SO2测定值影响分析

通过实验与实际工程相结合，定量描述了大气采样系统中金属氧化物的存在对ＳＯ２测定值的影响，并阐述了其反应机理，提出了相应措施。     

中国水环境的NPSP问题及对策

介绍了我国水环境中的非点源污染（ＮｏｎｐｏｉｎｔＳｏｕｒｃｅｐｏｌｌｕｔｉｏｎ，缩写为ＮＰＳＰ）的情况，强调农业生产是最主要的非点源污染。同时，针对我国水污染防治的政策目标，提出一些建议。     

梅梁湖的富营养化状况及治理对策讨论

监测结果表明，梅梁湖水体ＴＰ，ＴＮ含量分别为０．１ｍｇ／Ｌ和３．４ｍｇ／Ｌ藻类生物量达９－１３亿个细胞／Ｌ，富营养化相当严重，污染的主要原因，工农业，渔业，畜牧业和生活污水的直接排放，使水全营养盐含量较高，藻类大量繁殖，可采用“控源截汛”，“清除淤泥”，“调水搞活”及生物治理等综合性措施，对梅梁湖的富营养化进行了治理。     

建立锡山市跨行政区水域边界监控点的必要性和可行性

分析了建立锡山市跨行政区水域边界监控点的必要和可行性，并阐述了建立锡山市排污总量控制体系的重要性，以便提高整个区域的水环境质量。     

用密切值法评价沙湾荒漠区生态环境质量

利用多目标决策中的密切值法进行沙湾荒漠区生态环境综合评价。该方法简便、适用、且分辨率较高，对各监测点群的定量描述符合实际状况。