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).     

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。     

用好防灾科技学院教育平台创建和弘扬防震减灾文化-恭贺母校升本暨校庆30周年

本文对防震减灾文化的组成、创建动力及其方法进行了探讨.初次提出了防震减灾文化的概念,并对创建防震减灾文化的目的和如何创建、弘扬防震减灾文化提出了看法和观点.     

用好防灾科技学院教育平台 创建和弘扬防震减灾文化——恭贺母校升本暨校庆30周年

本文对防震减灾文化的组成、创建动力及其方法进行了探讨。初次提出了防震减灾文化的概念，并对创建防震减灾文化的目的和如何创建、弘扬防震减灾文化提出了看法和观点。     

区域环评中废水排放量的预测方法研究

阐述了区域环评污染物排放源强的预测原则,对区域开发活动中废水量和COD排放量的预测方法作了详细论述,并以温州滨海新区环评为例作了实证研究.     

金属铁还原降解2,4-二硝基甲苯的实验研究

研究了金属铁对2,4-二硝基甲苯(2,4-DNT)的还原降解情况.实验结果表明,2,4-DNT的还原降解与溶液初始pH值、初始浓度和溶解氧等因素有关.氯离子能消除金属铁的钝化现象.金属铁表面附载的铜对2,4-DNT的还原降解具有催化作用.     

石油化工企业灭火中的环境保护

针对近几年来连续发生的石化企业重大火灾后污染水源的恶性事故,在此从消防部队的角度对消防污水的产生与特点进行了探讨,阐述了灭火战斗中注意的问题以及消防污水紧急处置的措施,对石化企业的防火设计及消防监管提出了一些建议,希望消防工作者在致力于消防事业时,同时树立强烈的环保意识,将保护环境作为消防工作的又一目标,力求避免因火灾引发的突发环境事件造成政治、经济和社会方面的重大影响.     

以监测预报工作为导向推进数字化监测教学

地震预测的发展方向,是从协同的观点,多层面地统筹考虑地震监测体系的建设,实现基础研究与实际地震预测工作的结合.本文从如何利用原有监测资料、连续前兆监测数据处理系统的建立、前兆监测体系数据报送体系等地震监测工作环节,分析地震监测教学如何与监测工作方向相一致,并对教学改革如何结合台站技术人员更新提出了几点看法.