Mathematical model for the microbial metabolism of glucose induced enhanced biological phosphorus removal in an anaerobic/aerobic sequential batch reactor

Glucose plays a significant role in enhanced biological phosphorus removal (EBPR). Previous experimental studies have shown that in addition to acetate, glucose can induce and maintain a successful EBPR performance under certain operating procedures. Mathematical modeling of the EBPR metabolism is an important consideration that is necessary to produce a deeper insight into this process. In this study, four anaerobic reactions plus four aerobic reactions with fourteen kinetic constants are structured to describe the dynamic behavior of the key metabolic components in the glucose induced EBPR system. The development of the stoichiometric coefficients for the reactions is based on fundamental biochemical principles. The model describes the dynamics of the important storage compounds, which are considered separately from the active biomass. Sequential batch experiments were performed to find the optimum model parameters using sludges exhibiting stable EBPR from glucose fed system. The maximum specific substrate conversion rate in the glucose model is composed of two factors: the maximum specific rates of glucose direct conversion to PHV (q _gv ^max ) and glucose conversion to glycogen q _gl ^max , which are 14.1 and 699.7 C-mmol/C-mmol·h, respectively. The maximum specific rate of polyphosphate synthesis k _pp ^max is 0.2 P-mmol/C-mmol·h. The model with the best-fit parameters satisfactorily simulates the dynamic behavior of the key components during both anaerobic and aerobic conditions.     

湘西、湘中新元古界—古生界微量元素地球化学特征

湘西湘中新元古界—古生界是金锑砷等金属矿床的重要产出层位。岩石地层微量元素地球化学研究对于认识矿源层以及矿床成因具有重要的意义。本文根据单一地球化学过程产生的地质体中元素含量趋向于正态分布的认识 ,对于湘西湘中的新元古界—古生界中的微量元素进行了系统研究 ,结果表明 :新元古界的板溪群和震旦系是Au、Sb、As的重要含矿建造 ;Pb在奥陶系、志留系中显著富集 ;Hg在寒武系和奥陶系中明显富集。古生代各地层中Sb、As、Hg、Au等成矿元素均不同程度地受到后期成矿作用的影响 ,泥盆系和石炭系中Sb、As的高平均含量是由成矿叠加作用所引起的。     

聚硅氯化铝铁(PSAFC)絮凝剂的形态分析

通过对聚硅氯化铝铁水解共聚物的合成制备及水解共聚过程 pH变化的研究 ,对铝铁共聚物的化学形态、二氧化硅的加入和碱化度B对铝铁共聚物的影响进行了研究和讨论 ;并应用Ferron配合逐时比色法对聚合物中铁的形态进行了表征。为深入研究聚硅氯化铝铁奠定了理论基础。     

柯树背岩体铀金成矿远景分析

本文在研究柯树背岩体矿物岩石学特征基础上 ,通过对该岩体的铀金成矿元素丰度、铀金矿化类型、铀金矿石物质成分及成矿阶段的划分、矿脉的铀金含量及其相关关系、围岩蚀变及原生晕特点、铀金矿化控制因素的详细研究 ,从岩体的放射性地质地球化学特点、岩体蚀变及剥蚀强度、岩石化学及稀土元素地球化学、矿脉向深部的变化趋势等几个方面分析了该岩体的铀金成矿远景及今后找矿工作的意见 ,指出该岩体西体南部断续出现的柯树背—隘高断裂上盘 1km范围与下寮—大坑里断裂夹持区为铀金成矿远景区。     

重庆大气可吸入颗粒物中多环芳烃的分析测定

本文报告了重庆大气可吸入颗粒物(IP)中多环芳烃(PAH)的分析测定方法和结果.用GC-MS定性和定量分析了重庆IP中的PAH;研究了IP中PAH的种类和分布情况;确认重庆IP中存在甲基多环芳烃(MePAH)、约占33%;颗粒大小分布表明,约有98%PAH存在于小于3μm的颗粒中.     

物理化学法治理印染废水的研究

本文提出了两个治理印染废水的综合物化流程:(1)SE—J型絮凝剂絮凝→气浮→次氯酸钙氧化→炉渣吸附;(2)SE—型絮凝剂絮凝→气浮→活性炭吸附,并对每个处理过程进行了条件实验。实验结果表明:废水经流程(1)处理后,COD去除率达82—87%,色度去除率达88—92%,废水经流程(2)处理后,COD去除率达89—92%,色度去除率达97—98%。经两个流程处理后的出水水质分别接近或达到国家排放标准。     

水厂排泥水的处理技术：分离水回用 泥饼综合利用及铝盐回收

介绍了水厂排泥水处理后,分离水的水质和回用、泥饼制砖和污泥用作水泥掺合料的方法和试验结果,以及铝盐回收的工艺。     

鄱阳湖水质状况分析与评价

鄱阳湖是我国最大的淡水湖,对其水质的监测和分析有着重要意义。本文通过1980～1988年水质监测资料的搜集整理,分析了鄱阳湖水质的时空分布规律,并作出了比较全面的评价。评价结果表明,鄱阳湖已受到轻度污染,但其水质总体状况尚属良好,是全国淡水湖泊中最好的湖泊之一。     

The responses of the hepatosomatic index (HSI), 7-ethoxyresorufin-O-deethylase (EROD) activity and glutathione-S-transferase (GST) activity in sea bass (Dicentrarchus labrax, Linnaeus 1758) caged at a polluted site: implications for their use in environmental risk assessment

The present study investigates the response of three hepatic biomarkers in adult sea bass (Dicentrarchus labrax, Linnaeus 1758) caged at a wastewater outlet of an oil refinery with fish caged at a pristine site used as controls. The biomarkers that were investigated were the hepatosomatic index (HSI), 7-ethoxyresorufin-O-deethylase (EROD) activity and glutathione-S-transferase (GST) activity. In addition, we have measured the levels of polycyclic aromatic hydrocarbons (PAHs) and selected heavy metals (lead, cadmium, mercury, copper and zinc) in sediment samples at the polluted site. Although the polluted site had high environmental levels of PAHs and heavy metals, there was no difference in hepatic EROD activity and HSI between fish caged at the polluted site and controls. On the other hand, GST activity was significantly lower in fish caged at the polluted site compared to controls. Our results point out that the studied biomarkers have limited use in environmental risk assessment studies, at least when caged adult sea bass is used as the sentinel species and complex toxicant mixtures are involved.     

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.