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.     

The organic composition of diesel particulate matter, diesel fuel and engine oil of a non-road diesel generator

Diesel-powered equipment is known to emit significant quantities of fine particulate matter to the atmosphere. Numerous organic compounds can be adsorbed onto the surfaces of these inhalable particles, among which polycyclic aromatic hydrocarbons (PAHs) are considered potential occupational carcinogens. Guidelines have been established by various agencies regarding diesel emissions and various control technologies are under development. The purpose of this study is to identify, quantify and compare the organic compounds in diesel particulate matter (DPM) with the diesel fuel and engine oil used in a non-road diesel generator. Approximately 90 organic compounds were quantified (with molecular weight ranging from 120 to 350), which include alkanes, PAHs, alkylated PAHs, alkylbenzenes and alkanoic acids. The low sulfur diesel fuel contains 61% alkanes and 7.1% of PAHs. The identifiable portion of the engine oil contains mainly the alkanoic and benzoic acids. The composition of DPM suggests that they may be originated from unburned diesel fuel, engine oil evaporation and combustion generated products. Compared with diesel fuel, DPM contains fewer fractions of alkanes and more PAH compounds, with the shift toward higher molecular weight ones. The enrichment of compounds with higher molecular weight in DPM may be combustion related (pyrogenic).     

石河子市空气污染成因及防治对策

对石河子市空气环境质量状况进行了评价，对影响石河子市环境质量的主要因素进行了分析，得出石河子市空气污染属煤烟沙尘型，提出了相应的治理措施和建议。     

上海汽车制造业涂装废气VOCs排放特征

于2015年10月对上海市嘉定区4家(A、B、C、D)汽车制造企业涂装废气ρ(VOCs)和组成特征进行了调查分析。结果表明,A、B、C、D厂涂装废气排放口ρ(VOCs)总为0. 743～6. 11 mg/m~3,主要检出物和最高检出值分别为:A厂二甲苯2. 06 mg/m~3、B厂二甲苯0. 578 mg/m~3、C厂甲苯2. 59 mg/m~3、D厂庚烷0. 274 mg/m~3;芳香烃类是A、B、C厂排放比例最高的VOCs组分,烷烃类是D厂排放比例最高的VOCs组分。指出,原、辅料种类影响排放物的主要成分,废气处理工艺类型影响排放物主要成分和浓度。     

环境样品中痕量锰的催化动力学测定法

对环境样品中痕量锰的催化动力学测定方法进行简要评述，引述文献１６篇。     

Occurrence of dissolved PAHs in the Jinsha River (Panzhihua)--upper reaches of the Yangtze River,Southwest China

16 priority polycyclic aromatic hydrocarbons (PAHs) were determined in water samples from the Jinsha River (Panzhihua part), Southwest China. Total dissolved PAH concentrations varied from 21.89 microg l(-1) to 382.8 microg l(-1). It was found that the concentration of PAHs decreased along the flow direction due to the higher density distribution of coal chemical industry in the upstream of our study rivers. The pollution levels in our study area are significantly higher than previously reported values in other waters both in China and other countries. The predominance of benzo[k]fluoranthene and indeno[1,2,3-cd]pyrene was clearly observed in all water samples. On average these two compounds accounted for 98.3% of the total dissolved PAH concentration in water. The results showed the positive correlations among total dissolved PAHs, benzo[k]fluoranthene and indeno[1,2,3-cd]pyrene, which suggested that these two predominant PAHs have similar source and environmental behaviors in our study area. When compared with the survey results of organic micropollutants two decades ago, it was found that hydrocarbon pollution both predominated and even increased with the development of coal chemical industry in this area during the past 20 years. The results therefore provide important information on the current contamination status of a key industrial city in China, and points to the need for urgent action to investigate the relationship between the PAH composition and concentration in water from the Jinsha River and the wastewater discharge from coal chemical industry, and to identify the source, transport pathway and fate of PAHs in the area. It should then be necessary to adopt appropriate and instant measures to control the pollution around this area.     

A study of the elemental leachability and retention capability of compost

In this work a comparison is made between the different approaches that can be taken to evaluate the mobility of elements in compost. The practical consequences of the results obtained are also discussed in terms of methods for cleaning up compost and using compost in environmental remediation. The mobility of potentially toxic elements in compost is evaluated by leaching with four selected eluents, i.e. diluted sulfuric acid, oxalate, citrate and EDTA. In contrast to the chelating agents, diluted sulfuric acid was found to generally have a low leaching capability for removal of heavy metals from compost. This implies that the risk of heavy metal leaching caused by natural rainfall is likely to be low. The results obtained in the leaching experiment were compared with previous results obtained from sequential fractionation. This comparison confirmed that both methods gave similar results for predicting the lability of elements in compost. A non-linear regression analysis of the leaching curves was also conducted. The leaching curves for elements with high lability could be fitted with a two components model. The labile components identified by the kinetic model are approximately in accordance with the fractions obtained from the first step of the sequential extraction method. The kinetic speciation method is shown to be a relatively rapid and simple procedure for compost which gives more information about element lability than simple leaching experiments. The leaching reagents used in this work were not effective enough to be used for cleaning up compost with a high metal content. Compost was however shown to have a high affinity for heavy metals, with the order of affinity of metal for the compost being very similar to that seen for humic acid. Compost may therefore prove to be a good remediation material for metal contaminated waste.     

国内外饮用水水质标准的综合评价

在参考国内外饮用水水质标准的基础上,建立了饮用水水质综合评价体系,通过专家咨询法获得判断矩阵,利用层次分析法计算各水质指标的权重,结合国内外饮用水水质标准的指标进行层次总排序,根据总排序结果对国内外饮用水水质标准的特点进行了综合评价。     

大气微生物与气象条件及大气污染物的灰色关联分析

根据大气微生物浓度、气象因子和大气污染理化因子的监测结果，应用灰色关联分析原理，分析研究大气微生物浓度与气象条件和大气污染物的关联程度，说明气象因子对各类微生物浓度的影响大于大气污染因子，特别是对耐高渗透压霉菌。     

沙湾荒漠区生态环境的植物监测

利用植物生态学常规方法进行了荒漠植被种群生物量和数量特证调查,以植物为监测对象,并就群落地上部分生物量,Shannon-Wiener多样性指数,群落均匀度,生态优势度等指标探讨了在荒漠生态环境监测和评价中的具体应用。