TiO2复合催化剂弱光催化降解模拟海水中苯酚及其催化活性的影响

为了获得适用于海水中有机污染物光降解催化剂,分别选用纳米SiO_2粒子和氧化石墨烯GO为载体,利用吸附相反应技术并结合热处理过程制备了基于TiO_2的复合催化剂,研究了弱光(光强小于1mW·cm~(-3))激发下复合催化剂光催化降解模拟海水中苯酚.结果表明,吸附相反应技术结合焙烧得到的La~(3+)掺杂TiO_2-SiO_2,表面亲水性较强和对苯酚吸附能力较弱,难以克服盐离子的干扰并有效降解模拟海水中高浓度苯酚.而吸附相反应技术结合醇溶剂热还原处理后,La~(3+)掺杂TiO_2-SiO_2催化剂表面亲水性显著减弱,但该催化剂在模拟海水中不能形成稳定的悬浮体系.吸附相反应技术得到的TiO_2-GO和La~(3+)掺杂TiO_2-GO中,TiO_2粒子粒径小于10nm且均匀负载于GO的表面.醇溶剂热还原处理可使TiO_2形成晶型结构,从而提高其催化活性,同时还能将GO表面的含氧基团还原,降低催化剂表面亲水性.从而提升催化剂对苯酚的吸附能力和对盐离子的抗干扰能力.另外,还原GO与小粒径TiO_2粒子紧密结合,使光生电子能很快转移至还原GO表面,增大光生电荷分离率,进一步提升催化剂的光降解性能.     

咪唑氯盐离子液体对蚯蚓急性毒性及体重影响研究

采用OECD标准滤纸接触法和人工土壤法,研究了3种离子液体1-丁基-3-甲基咪唑氯盐([Bmim]Cl)、1-己基-3-甲基咪唑氯盐([Hmim]Cl)、1-辛基-3-甲基咪唑氯盐([Omim]Cl)对赤子爱胜蚓(Eisenia fetida)的急性致死作用,并测定亚慢性暴露试验下蚯蚓的体重变化.滤纸接触法测得[Bmim]Cl、[Hmim]Cl、[Omim]Cl对蚯蚓24 h的半致死浓度(LC50)分别为109.60、50.38、7.94μg.cm-2;48 h的LC50分别为98.52、39.14、3.61μg.cm-2.人工土壤法得到[Bmim]Cl、[Hmim]Cl、[Omim]Cl对蚯蚓7 d的LC50分别为447.78、245.56、180.51 mg.kg-1,14 d的LC50分别288.42、179.75、150.35 mg.kg-1.蚯蚓在3种离子液体作用下表现出不同的中毒症状.3种离子液体对蚯蚓的生长表现出不同程度的抑制作用,体重随着浓度增加而下降.离子液体对蚯蚓毒性随着碳链长度的增加而增大.     

应用ANFIS预测蠕虫反应器的污泥减量速率并优化其运行条件

利用水生蠕虫的捕食作用可以有效地实现污泥减量.为了研究环境条件波动对蠕虫捕食污泥减量效率的影响,应用自适应神经模糊推理系统(ANFIS)和人工神经网络(ANN)模型分别预测蠕虫反应器的污泥减量速率.结果表明,溶解氧浓度(D0)、温度(T)、蠕虫密度和污泥负荷是蠕虫捕食过程的主要影响因素,通过性能比较得出ANFIS模型预测值与实验测定值间具有更好的一致性,其相关系数(r)为0.82,绝对平均误差百分比(MAPE)为71.5％,均方根误差(RMSE)为16.7.根据ANFIS模型的预测结果,得出蠕虫反应器的最适运行条件为:DO 1.8 ～3.1mg·L-1,温度18.4～21.7℃,蠕虫密度低于1.7 g·cm-2(以湿重计),污泥负荷563～734 mg·g-1(以TSS计),在此操作条件下获得的污泥减量速率均高于100 mg· g-1·d-1.     

机动车闯红灯判别模型及评价研究

为了提高机动车闯红灯警示系统判别准确率,提出适用于该系统的机动车闯红灯判别模型并进行评价。首先综述闯红灯警示系统的产生与发展现状,根据系统服务需求与工作流程,提出使用Logistic回归与神经网络方法建立判别模型预测机动车停止-通过行为,通过城市交通实测数据对模型进行评价。数据采集自上海城市道路交叉口进口道,通过Autoscope视频检测系统提取机动车运行数据。评价结果表明,Logistic回归与神经网络模型正确判别率均达到90%以上,神经网络具有更好的判别准确率。相对于速度,当前检测地点与上游地点30 m处车速差或速度比更宜作为模型中的判别参数。     

An inverse model for the analysis of the Venice lagoon food web

A steady-state model of the Venice lagoon food web was constructed, based on a comprehensive set of data, which were collected in the years 2001-2005. Energy flows were estimated by means of an inverse methodology of constrained optimization based on the Minimum Norm criterion, i.e. on the minimization of both the sum of squares of the residuals and of the sum of squares of energy flows. The solution was constrained by a set inequalities, which were derived from general eco-physiological knowledge and site specific data on energy flows. The trophic network was represented by thirty-two nodes, including single-species compartments for the species of high economical or ecological relevance. Mass balance equations were weighted, in order to obtain meaningful results in presence of large differences, up to 5 orders of magnitude, among biomasses. A perturbation technique was applied, with the purpose of reducing the risk of finding solutions heavily affected by the set of constraints and of obtaining a more robust representation of the energy flows. The main patterns of energy flow are consistent with those obtained in previous attempts at modelling the Venice lagoon food web. Micro- and macro-phytobenthos account for the largest fraction of the primary production. Energy is then transferred towards higher trophic levels by means of two main pathways: the recycling of dead biomass through the detritus compartment and the direct consumption by grazers. The first pathway is the most important and accounts for approximately two/thirds of the energy transferred to the second trophic level.     

基于人工蜂群算法的边坡最危险滑动面搜索

将用于连续数值优化问题的人工蜂群算法引入边坡稳定分析临界滑动面搜索领域.该方法模拟了蜂群的群体协作采蜜过程,具有自适应收敛的特点,克服了传统方法容易陷入局部最优的缺点,是一种全局优化算法.为进一步改善其在复杂边坡搜索中的效果,将Hooke-Jeeves模式搜索操作引入人工蜂群算法,提出一种用于边坡临界滑动面搜索的模式搜...     

Stabilised Coal Ash Studies in Italy

The ENEL Ash Research Centre - (Brindisi, Italy) - has started a research programme on the use of coal ash derived from its thermoelectric power plants as a component of blocks for artificial habitats. After preliminary laboratory tests, systematic physical, chemical, and biological tests were carried out in an experimental installation constructed in the area of the Torrevaldaliga power plant (80 km NW of Rome).

Two reef models - each made by assembling pyramids of 225 20 × 20 × 20 cm blocks - were submerged in two tanks (10 × 2 × 1.5 m) with running sea water (water flow: 3-5 cm s-1). the ash blocks were composed of fly ash (52.1%), bottom ash (26.1%), hydrated lime (5.2%) and water 16.6%, while concrete blocks were made of pozzolanic cement, sand and gravel. After two years, ash based blocks showed no weathering, volume variation or swelling; marked compressive strength and sonic velocity increases have, on the contrary, been recorded. No significant leaching of chemical elements of environmental concern was found. the biotic settlement on the ash blocks proved greater in quantity and better in quality than that on the concrete blocks; on ash blocks 62 species were found, compared to 54 on concrete. Ash-based materials seem to be more suitable for the settlement of the macrobenthos.     

基于综合主成分及径向基网络的环境质量评价

运用综合主成分分析对监测数据进行处理,集成径向基函数人工神经网络(RBF-ANN),参考国家环境质量评价标准设定RBF的学习样本,从而构建区域环境质量综合评价模型,对安徽省合肥市新站综合开发试验区进行环境质量综合评价。实例分析结果表明,运用综合主成分法可以精准的统计出一个区域的环境综合数据,而且在matlab环境下运用RBF-ANN模型既可以准确,客观的评定环境质量的等级,又可以表现其环境污染的具体程度,能在同一评价等级内对不同环境质量的评价对象进行更加细微的污染程度的比较。结果表明,合肥市新站综合开发试验区环境综合质量介于轻度污染和中度污染的标准极限值之间,属于中度污染。     

Adaptive neuro fuzzy inference system for classification of water quality status

An adaptive neuro fuzzy inference system was used for classifying water quality status of river. It applied several physical and inorganic chemical indicators including dissolved oxygen, chemical oxygen demand, and ammonia-nitrogen. A data set (nine weeks, total 845 observations) was collected from 100 monitoring stations in all major river basins in China and used for training and validating the model. Up to 89.59% of the data could be correctly classified using this model. Such performance was more competitive when compared with artificial neural networks. It is applicable in evaluation and classification of water quality status.     

污水处理中人工神经网络应用研究的探讨

针对污水处理系统的时变性、非线性、复杂性和不确定性的特点,提出应用人工神经网络技术对其控制,实现污水处理系统自动控制。简述了目前广泛应用于废水处理的神经网络以及建模原理。结合国内外研究动态,分析了人工神经网络在污水处理领域取得的成果,结果表明:在污水处理中引入神经网络智能控制是一种提高处理效率、降低运行成本的有效方法,国内在污水处理的神经网络智能控制的研究与国外有较大的差距,国内的研究及应用还处在发展阶段,应当加强。并对神经网络待解决的问题和发展趋势作了讨论。