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.     

Distribution of airborne particles from multi-emission source

The purpose of this work was to study the distribution of airborne particles in the surroundings of an iron and steel factory in southern Finland. Several sources of particulate emissions are lying side by side, causing heavy dust loading to the environment. This complicated multi-pollutant situation was studied mainly by SEM/EDX methodology.Particles accumulated on Scots pine bark were identified andquantitatively measured according to their element content,size and shape. As a result, distribution maps of particulateelements were drawn and the amount of different particle typesalong the study lines was plotted. Particulate emissions fromthe industrial or energy production processes were not themain dust source. Most emissions were produced from theclinker crusher. Numerous stockpiles of the industrial wastesand raw materials also gave rise to particulate emissions as aresult of wind erosion. It was concluded that SEM/EDXmethodology is a useful tool for studying the distribution ofparticulate pollutants.     

Trace Metal Concentration in Roadside Surface Soil and Tree Back: A Measurement of Local Atmospheric Pollution in Abuja, Nigeria

Cadmium, copper, lead, nickel and zinc concentrations were analysed by atomic absorption spectrophotometry in surface soil and tree bark from different districts of Abuja, Nigeria, in order to determine the atmospheric trace metal input in the area.Elevated concentrations of some of the studied metals were observed in the soil and tree bark samples from the commercial/high traffic areas of the city compared to backgroundvalues. In soil samples, the average concentration of the metals were 0.6±0.4, 18.0±4.0, 281±39, 16±4 and66±23 g g^-1 dry weight for Cd, Cu, Pb, Ni and Zn, respectively, whilst the average concentrations in tree bark were 0.3±0.2, 12±4, 133±32, 13±3 and 61±10 g g^-1 dry weight for Cd, Cu, Pb, Ni and Zn, respectively. The trend in trace metal levels suggested that automobile emissions are a major source of these metals as the highest concentrations of Pb and Zn were recorded in the commercial areas of the city known for their high traffic densities. The levels of metal in the study area were relativelylow compared to levels found in some larger and older cities in various countries worldwide.     

Sharing the geo-Referenced Results of Climate Change Impact Research

The Prairie Adaptation Research Collaborative (PARC) has implemented an Internet Map Server (IMS) at the PARC web site (www.parc.ca) to 1) disseminate the geo-referenced results of PARC sponsored research on climate change impacts and adaptation, and 2) address data, information and knowledge management within the PARC network of researchers and partners. PARC facilitates interdisciplinary research on adaptation to the impacts of climate change in the Canadian Prairie Provinces. The web site is intended as a platform for sharing information and encouraging discussion of climate change impacts and adaptation. The IMS enables scientists and stakeholders to apply simple climate change scenarios to geo-referenced biophysical and social data, and dynamically create maps that display the geographic distribution of potential impacts of climate change. With a limited capacity for spatial analysis, most geo-processing and the climate impact modeling is done offline within a GIS environment. The IMS will serve the output from climate impact models, such that the model results can be customized by the web site user and be most readily applied to the planning and analysis of adaptation strategies.     

Formulation and Validation of an Empirical Moisture Damage Index

An empirical moisture damage index was developed in order to reduce the subjectivity of the estimation of moisture damage in domestic residences, in relation to occupant health. The database was generated using information gathered from a sample of 164 houses that were examined by civil engineers, and questionnaire data collected from the occupants. The index was formulated to associate with the occupant reported respiratory symptoms by calculating weighted estimates of selected moisture damage attributes using 80% of the sample. The remaining 20% of the sample was used to verify the final index. The index associated strongly with the health symptoms of interest. This index is a tool that may be used as an indicator of moisture damage induced exposure in domestic residences.     

长江流域等重污染行业经济和污染贡献率剖析

应用"污染贡献率"这一指标,分析了长江、黄河、珠江和松花江流域COD和氨氮排放的重污染行业以及地区分布,指出了各流域COD和氨氮排放的控制重点.同时分析了各流域重污染行业的经济贡献率,最后结合行业的污染贡献率和经济贡献率以及行业在地区所占的比例,提出了几点重要的结论.     

城市大气中颗粒物的研究现状及健康效应

综述了大气尘(TSP、PM10、PM2.5)的研究现状,重点围绕TSP、PM10、PM2.5的物理特征、化学组成(有机组成、重金属元素的总含量及其各化学形态分布)及其源解析进行描述,也提及了大气颗粒物与健康的关系.     

对室内装饰装修材料检测中甲醛分析方法的研究

目前室内装饰装修材料中甲醛含量的检测有六个类别,分析方法不统一,且没有一定的质量控制措施.文章对分析方法进行了改进,并且研究用水中的甲醛标样来对检测过程进行质量控制,结果较好.     

南京某县空气、土壤中多环芳烃的分布及来源

采用建立的采样及分析监测程序对南京某县空气、土壤中的多环芳烃进行了调查监测,探讨了多环芳烃在空气、土壤中的分布特征、相关性及可能的污染来源.     

辽河流域浑河沈阳段地表水重点控制有机污染物的筛选

采用美国环保局工业环境实验室提出的化学物质的“潜在危害指数法”,对辽河流域浑河沈阳段地表水和底质中检出的有机污染物的潜在危害进行了排序,参考国内外有毒化学品优先控制名单的筛选原则和方法,结合本流域的实际情况,制定出重点控制有机污染物的评分标准,提出辽河流域浑河沈阳段重点控制有机污染物名单。考虑到个别有机污染物在水中的浓度很低,但在底质中相对含量较高,所以将底质的检测结果也纳入评分标准。