粘土矿物与重金属界面反应的研究进展

介绍了3种粘土吸附剂：蒙脱石、高岭石和伊利石对重金属的吸附、脱附等界面反应机理，以及粘土矿物对重金属的选择性及对吸附的影响因素。另外，还探讨了为提高其吸附性能而进行的改性方法。     

青霉菌HHE-P7利用酱油废水产生微生物絮凝剂的研究

研究了微生物絮凝剂产生菌HHE-P7在酱油废水中产生微生物絮凝剂的絮凝特性。实验表明，酱油废水由于碳源丰富，是一种良好的培养基。HHE-P7菌最佳培养条件为：COD20000mg／L，K2HP041．0g／L，培养3d。最佳絮凝条件为在1L高岭土水中投加10～15mL微生物絮凝剂（MBF7），pH调至9，则絮凝率为90％以上；微生物絮凝荆在水系中主要起吸附架桥的作用。     

人工湿地处理系统中多环芳烃的行为

采用Oasis HLB柱固相萃取的前处理技术,以气相色谱质谱联用仪（GC/MS）的分析方法,对我国北方永定河上游黑土洼人工湿地中多环芳烃污染的特征以及分布规律进行了研究.结果表明,该湿地系统以低环数多环芳烃污染为主,其中浓度最高的是菲和蒽,未检出高环数（5环、6环）多环芳烃.通过比较进水和出水的浓度,湿地系统总体上不能有效去除进水中的多环芳烃.但是比较不同工艺单元进出水浓度,复氧、植物根系及微生物等均影响到多环芳烃的去除效果,去除率在28%～65%之间.     

微絮凝-超滤工艺处理微污染水源水的中试研究

进行了微絮凝．超滤工艺处理微污染水源水的中试研究。试验结果表明：在微絮凝-超滤工艺中，相同混凝剂投加量（相同金属摩尔浓度）下铁盐比铝盐的混凝效果好；微絮凝-超滤工艺的最佳絮凝时间为120s左右；最佳混凝剂投加量为2．2mg／L（以Fe计）。微絮凝-超滤工艺在改善出水水质和缓解膜污染方面均优于直接超滤工艺。微絮凝-超滤工艺的出水水质均符合建设部《城市供水水质标准》（CJ／T206-2005）要求。     

高效喷淋泡沫脱硫技术及装置的应用

SO2是产生酸雨的主要气体，其主要来源于工业燃煤锅炉。以沈阳一家电厂为例，该厂选用新型高效的喷淋泡沫脱硫除尘器对锅炉排放的SO2进行治理。进入喷淋泡沫塔前的SO2平均浓度为2780mg／m^3，经脱硫后出塔平均浓度为289．3mg／m^3，去除率为89．6％。结果表明，这种有别于传统湿法的新型高效的喷淋泡沫脱硫技术及装置具有脱硫效率高、装置占地少、运行稳定、沉淀物易于回收利用等特点，对锅炉排放的SO2进行治理是非常有效的。     

Ce掺杂纳米TiO2光催化剂的制备及降解甲醛的研究

介绍了溶胶-凝胶法制备Ce离子掺杂纳米TiO2的工艺流程.采用X射线衍射(XRD)、紫外可见分光光度法(UV-Vis)等方法表征了Ce掺杂TiO2的相组成、紫外可见漫反射率与掺杂量的关系.结果表明,掺杂的TiO2在520℃、650℃焙烧2 h呈锐钛矿结构,在520℃焙烧2 h的TiO2的晶粒尺寸大约为20 nm,而掺杂Ce后其晶粒尺寸均减小,大约为12nm.UV-Vis吸光度分析表明,掺Ce后吸收带边明显发生红移,但随着Ce掺杂浓度的增大,其对可见光的吸收影响不大.光催化降解反应表明,未掺杂Ce的TiO2反应2 h后对甲醛的没有降解作用,而Ce掺杂TiO2反应2 h后甲醛降解率达15%.     

中国山东电网燃煤锅炉NOx排放状况和治理技术试验研究

通过对山东电网所属发电厂锅炉NOx排放状况进行调查、测试,得出锅炉NOx排放量与煤种、炉型、燃烧器型式、运行中空气过剩系数、负荷等的关系.结果表明,山东省火力发电厂50 MW及以上容量机组2003年的NOx排放总量超过40万t(按NO2计算).控制和治理NOx排放已成为刻不容缓的重要工作.     

水源水中摇蚊幼虫的孳生与生态控制

摇蚊幼虫(红虫)在城市供水系统中的出现,成为困扰水厂正常生产运行的又一水处理难题.首先对其生理特性与环境因子之间的关系进行了论述,然后从生态学角度出发,利用生态群落中的食物链关系,分析了富营养化水体中摇蚊幼虫大量孳生的原因.在此基础上提出了利用合理的生物操纵技术,通过鱼类与水生生物间的"下行效应",以达到恢复生态平衡并控制摇蚊幼虫孳生为目的的生态治理方案.     

一种高速反硝化颗粒污泥的培养

以葡萄糖为碳源,在USB反应器内接种好氧活性污泥在40 d内培养出良好的反硝化颗粒污泥.颗粒污泥形成经历了2个阶段:起始阶段,接种的好氧活性污泥中非反硝化菌逐渐衰亡演变为"惰性固体",与原有的固体一起,成为反硝化菌附着生长的载体,与此同时,反硝化菌在载体表面渐渐繁殖,形成细颗粒污泥;随后,反硝化菌在细颗粒污泥表面不断增殖,颗粒长大,发育成为成熟的颗粒污泥.成熟的颗粒污泥密实,表面均为杆状菌,且排列紧密,当污泥床容积负荷为19.1 g N/L·d时,去除率高达98.4%(N).     

Variations in exposure to in-vehicle particle mass and number concentrations in different road environments

Road environments significantly affect in cabin concentration of particulate matter (PM). This study conducted measurements of in-vehicle and on-road concentrations of PM10, PM2.5, PM1, and particle number (PN) in size of 0.02–1 µm, under six ventilation settings in different urban road environments (tunnels, surface roads and elevated roads). Linear regression was then used to analyze the contributions of multiple predictor variables (including on-road concentrations, temperature, relative humidity, time of day, and ventilation settings) to measured variations. On-road measurements of PM2.5, PM1, and PN concentrations from the open surface roads were 5.5%, 3.7%, and 16% lower, respectively, than those measured in tunnels, but 7.6%, 7.1% and 24% higher, respectively, than those on elevated roads. The highest on-road PM10 concentration was observed on surface roads. The time series pattern of in-vehicle particle concentrations closely tracked the on-road concentrations outside of the car and exhibited a smoother profile. Irrespective of road environment, the average I/O ratio of particles was found to be the lowest when air conditioning was on with internal recirculation, the highest purification efficiency via ventilation was obtained by switching on external air recirculation and air conditioning. Statistical models showed that on-road concentration, temperature, and ventilation setting are common factors of significance that explained 58%-80%, 64%-97%, and 87%-98% of the variations in in-vehicle PM concentrations on surface roads, on elevated roads, and in tunnels, respectively.

Implications: Inside vehicles, both driver and passengers will be exposed to elevated particle concentrations. However, for in-vehicle particles, there has been no comprehensive comparative study of the three-dimensional traffic environment including tunnels surface roads and elevated roads. This study focuses on the analysis of the trends and main influencing factors of particle concentrations in different road environments. The results can provide suggestions for the driver's behavior, and provide data support for the environmental protection department to develop pollutant concentration limits within the vehicle.