Investigation of chlorinated phenols sorption mechanisms on different layers of the Danube alluvial sediment

The characteristics of the Danube river alluvial sediment are of great importance in assessing the risk for transport of pollutants to drinking water sources. Characterization of the sediment column layers has shown that the alluvial sediment, sampled near the city of Novi Sad, is a mesoporous sandy material with certain differences in the properties of individual layers. In order to investigate the sorption mechanisms of four chlorinated phenols (CPs) on the alluvial deposit, static sorption experiments were performed at pH 4, 7 and 10. The results of sorption experiments, confirmed by principal components analysis sugest different mechanisms govern the sorption process at different pH conditions. This can be attributed to the molecular characteristics of CPs, geosorbent properties and to variations in the surface charge of the sorbent at different pH conditions.     

Relationship between physicochemical properties and dewaterability of hydrothermal sludge derived from different source

Sewage sludge (SS) and deinking sludge (DS) were used to comparatively study the hydrothermal dewatering of sludge with different components. For a better overview, an insight into the relationship between physicochemical properties and dewaterability of hydrothermal sludge was provided. Results found that not all kinds of sludge were suitably conditioned by hydrothermal treatment (HT) in term of the elevation of dewaterability. Higher hydrothermal temperature tended to enhance the dewaterability of SS rather than DS, which was supported by the variation of their physicochemical properties (including water distribution, bonding energy, extracellular polymeric substance (EPS), particles size, acid functional groups and zeta potential in this study). In addition, the changes in surface morphology suggested that the reverse effect of HT on sludge dewaterability was mainly due to their dewatering behavior. For SS, the destruction of EPS structure leaded to the release of bound water, thereby strengthening sludge dewatering. Conversely, “Bridging effect” generated by lignocellulose in DS was beneficial for sludge dewatering; however, the increasing hydrothermal temperature degraded part of lignocellulose and weakened “bridging effect”, finally resulting in worse dewaterability of DS.     

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.     

ASM1中废水和污泥组分浓度的测定方法研究

对呼吸计量法应用于校准ASM1作了简明的阐述。在呼吸速率与模型组分关系的基础上,介绍了ASM1中废水与污泥各组分浓度的测定方法,并指出模型组分细化的意义。     

主成份分析法在大气环境质量综合评价中的应用

介绍了主成份分析法评价大气环境质量的基本原理，并对某市的大气环境质量进行了综合评价。最后，与其它方法的评价结果进行了对比分析，进一步证实了主成份分析法的科学性、合理性。     

水环境监测点位优化数学模型探讨

根据雨山湖的环境特征和水质状况,在加密监测获取更多的信息的基础上应用多元统计定量分析,选用主成份分析统计模式,用编制计算机程序处理数据,获得优化点数和确定点位.经可靠性检验证明优化方案完全能满足环境监测和环境管理的要求.     

机械强化污泥回流式一体化活性污泥法的运行机理研究

活性污泥通过机械搅拌强化污泥内循环回流,提高了污泥的活性,并且使污泥浓度可达到4.5kg/m3,用该机械强化污泥回流式一体化活性污泥法处理小区生活污水,当水力停留时间为3h,溶解氧为2.2mg/L,机械搅拌速度为250r/min时,CODcr、氨氮去除率均可达到83% 以上,出水达到国家污水排放一级标准.该一体化活性污泥法简单易行,运行成本低,投资小,操作维护方便,是生活小区生活污水适宜的处理工艺技术.     

用主成分分析法研究评价地下水质量——以邯郸市为例

运用主成分分析法(PCA)对邯郸市地下水主要污染指标年均值进行了探索性评价研究。分析结果表明,前5个主成分综合携带了全部信息的91.374%。通过对这5个新的综合指标进行分析,确定了地下水的主要污染物,同时根据其综合得分对地下水进行分级,分析了其变化趋势,为地下水资源的有效利用和保护提供了科学依据。     

小边距冲孔模的凹模设计

在五金、家电、办公用品等行业中,常存在一些零件需要先弯曲成形,再进行冲孔。由于结构设计要求,有些孔到弯曲边的距离尺寸较小,尺寸精度要求较高,因此在这类模具设计中,凹模的强度问题较为突出。从结构设计和工艺设计两方面给出了设计这种模具的一些心得体会。     

色基生产废水的三级处理工艺试验

在染料中间体红色基Ｂ，紫酱色基ＧＰ的生产过程中，全产生降解处理的废水，采用中和隔油－生物接触氧化－电解脱色工艺处理可达标准排放。试验结果表明，硝化废酸液和水解母液的混合废水经过中和隔油处理后，ＣＯＤｃｒ的去除率可达到５６％以上，而ＢＯＤ５／ＣＤＯｃｒ的比值可在从０．２２提高到０．５以上；再经生物接触氧化处理后，ＣＯＤｃｒ的去除率在８８％以上，ＢＯＤ５的去除率在９２％以上；最后，电解处理能使ＣＯＤｃ