Analysis of pollutant levels in central Hong Kong applying neural network method with particle swarm optimization

Air pollution has emerged as an imminent issue in modernsociety. Prediction of pollutant levels is an importantresearch topic in atmospheric environment today. For fulfillingsuch prediction, the use of neural network (NN), and inparticular the multi-layer perceptrons, has presented to be acost-effective technique superior to traditional statisticalmethods. But their training, usually with back-propagation (BP)algorithm or other gradient algorithms, is often with certaindrawbacks, such as: 1) very slow convergence, and 2) easilygetting stuck in a local minimum. In this paper, a newlydeveloped method, particle swarm optimization (PSO) model, isadopted to train perceptrons, to predict pollutant levels, andas a result, a PSO-based neural network approach is presented. The approach is demonstrated to be feasible and effective bypredicting some real air-quality problems.     

青铜峡铝厂氟污染对广武乡玉米影响的调查分析

监测了青铜峡铝厂东南方向４．５ｋｍ的广武乡玉米叶，得知含氟量为４３．９４－１６６．１ｍｇ／ｋｇ，对照样品树新林场玉米叶的含氟均值为１３．１５ｍｇ／ｋｇ，广武乡的玉米受到了严重的氟污染，农作物减产严重。     

Determination of PAHs by On-Line Polarization Synchronous Fluorescence with HPLC

A novel analytical method has been established for on-line simultaneous determination of fluorene and acenaphthene,chrysene and benzo[a]anthracene (B[a]A) by polarization synchronous fluoromet.y (PSF) coupled to high performance liquid chromatography (HPLC). The detection limits were: 0.039, 0.046, 0.016 and 0.042 mgL-1 for fluorene, acenaphthene, chrysene and B[a]A, respectively. The proposed method has been successfisily applied to simultaneous determination of these PAHs in environmental air and marine sediment samples.     

Reduction of SO2 emissions by ammonia gas during unstaged combustion

The reduction of SO₂ by the addition of ammonia gas has been studied in a 2 m high fluidized bed combustor having a 30 cm static bed height and a freeboard height of 170 cm. Ammonia gas was injected at 52 cm above the distributor where the temperature is ca. 700° C by an uncooled stainless steel tube injector. Experiments were carried out to investigate the effects of amminia gas injection on sulphur dioxide emissions at unstaged conditions of: (i) excess air level, (ii) NH₃:SO₂ molar ratio, (iii) fluidizing velocity and (iv) bed height.A maximum reduction of 75% in SO₂ emissions was found at 40% excess air, at an NH₃:SO₂ molar ratio of 5.4. The onset of SO₂ reduction occurred at an NH₃:SO₂ ratio of 1.5 However, the most effective ratio was found to be between 3 and 5. Fluidizing velocity and bed height were also found to have significant influence on SO₂ reduction.It is difficult to determine how the SO₂ reduction varied with operating conditions. When ammonia is added in the main combustor zone, the temperature is much higher than that required for the occurrence of sulphur dioxide-ammonia and sulphur trioxide-ammonia reactions. However, this paper points out the significance of ammonia addition in the reduction of sulphur dioxide.     

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 Trace Organochlorinated Pesticides and Polychlorinated Biphenyls in Water

A modified steam distillation liquid-liquid extraction (SDE) device is developed for the enrichment of trace organochlorinated pesticides (OCPs) and polychlorinated biphenyls (PCBs) in up to one litre of water samples. One ml of n-hexane is sufficient to extract the analytes. The extract can be analysed directly by a capillary gas chromatography-electron capture detector. The recoveries range from 84.6 to 102.3% for OCPs and 80.5 to 106.2% for PCBs, respectively. Matrice materials such as lipids and humic substances were removed by the SDE method from the extract and no further cleanup and concentration steps were needed.     

Preliminary studies of a fast screening method for polycyclic aromatic hydrocarbons in soil by using solvent microextraction-gas chromatography

Solvent microextraction (SME) was applied to the extraction of polycyclic aromatic hydrocarbons (PAHs) from spiked and real environmental soil samples with different matrices. Soil sample was mixed with 7 mL of acetone and 14 mL of water to allow partitioning of the PAHs from the soil to the liquid phase. A 2 microL octane drop suspended from a microsyringe needle tip was then immersed into the stirred solution-soil mixture for extraction. After an 11 min extraction, the octane drop was withdrawn into the syringe and injected directly into the GC for identification and quantification. The whole analysis procedure took 27 min, with an extraction time of 11 min, and a GC separation time of 16 min. A second extraction could be undertaken whilst the GC is running, hence the GC run time currently limits the sample throughput. In this method, a small amount of organic solvent was used for the extraction process, which produced little waste. The limits of detection for lower molecular weight (< 230) PAHs range from 0.13 to 0.36 mg kg-1, and for higher molecular weight (> 250) PAHs are estimated to be between 0.5 and 1.0 mg kg-1, with RSD values generally under 20%. Due to the small volumes of organic solvent used, the consumable cost per extraction is only US$ 0.12. This is the first report of the application of SME to solid samples, and the first report of the use of SME for the analysis of PAHs.     

某铀矿工人头发中总α,总β,铀,钍放射性水平的调查

本文对某铀矿职业工人和非职业工人头发中的总β、总α放射性水平和铀、钍含量进行了分析测定.结果表明,该矿工人体内铀和钍的蓄积量均在正常放射性本底水平范围内,从头发中检验未观察到工人体内铀、钍放射性水平有明显的升高.     

分光光度法测定染色废水的色度

为消除测定染色废水色度的主观误差，采用分光光度法测定染色废水的色度，与稀释倍数法相比，具有精确，重现性好，适用范围广等特点，ＰＨ值对色度的测定有明显影响，控制ＰＨ值为７．６０，测定色度具有可比性。     

唐山市空气中SO2与TSP污染状况分析

分析了唐山市从1988年至1992年大气中SO2和TSP的污染状况和变化规律，取得对该市环境管理的科学依据。