潜流人工湿地处理地下水TCE污染实验研究

分别构建无植物、宽叶香蒲和芦苇3组潜流人工湿地系统,研究潜流人工湿地对受到TCE(三氯乙烯)污染地下水的处理效果。实验结果表明:无植物湿地系统和芦苇湿地系统的出水TCE去除率波动较大,香蒲湿地系统出水TCE去除率相对稳定,其出水TCE平均去除率为77.7%,最大值为87.5%,最小值为70.7%。对于无植物湿地系统,湿地床中层和下层的TCE去除率相差较大,而该差异在香蒲和芦苇湿地系统中并不明显。在湿地系统中TCE沿水平方向的降解反应基本符合一级反应动力学模型。     

博斯腾湖西岸表流人工湿地水体脱盐效果研究

针对博斯腾湖日益严重的盐污染问题,以博斯腾湖西岸表面流人工湿地为研究对象,引当地排渠水进入人工湿地,对人工湿地的进水和出水进行连续7个月的水质监测,对比分析进水和出水中8种离子(Ca~(2+)、Na~+、K~+、Mg~(2+)、Cl~-、SO_4~(2-)、CO_3~(2-)、HCO_3~-)和矿化度的变化,结果表明:人工湿地进水含盐量较高,8种离子的浓度和矿化度波动较大,4月和10月进水为微咸水,5—9月进水为咸水,而出水含盐量相对较低,8种离子的浓度和矿化度波动较小,各月出水均为微咸水。经计算分析可知,人工湿地对水体总盐的平均去除率为51%,水体盐分的去除率与温度呈正相关,且随季节性温度变化而发生变化。     

青藏高原土壤柴油降解菌的筛选及降解实验研究

青藏高原北麓河地区土壤为典型的低温土壤环境,夏季高温季节表层土壤(5 cm处)温度仅为9℃,中层(20 cm处)为7.5℃,而40 cm处仅为4℃左右。土壤高温季节为7月中旬至9月上旬,而10月至来年6月土壤日平均温度下降为0℃以下。针对青藏高原低温土壤环境,在北麓河试验现场进行人工模拟柴油污染,16个月后采集污染土样,进行土著低温菌的复合筛选,柴油菌的筛选驯化温度为10℃。经过4次转接复合培养驯化后,菌液中微生物数量可达2.7×1012CFU/mL。筛选后的柴油降解菌90%以上为杆状菌,长度为2~3μm,少见球菌,其直径约为0.5μm。通过柴油摇瓶模拟降解实验,17 d后柴油去除率可达到62%。研究为青藏高原低温条件下的土壤柴油污染土著微生物修复提供了研究基础。     

人工湿地植物水体净化效能研究进展

通过检索近20年来人工湿地植物在净化水质方面代表性文献,筛选出50种常见人工湿地植物,包括水生植物(挺水植物、浮水植物及浮叶植物、沉水植物)、湿生植物、旱生植物,对该50种常见植物的净化效能进行分析比较;指出湿地植物在净化水体时可能受物种、环境因子、种类配置模式三方面的影响;提出未来人工湿地植物选择应用方面发展方向为:应进一步扩大其种类的选择范围,加强探究维持其生长代谢的机理,加强与微生物的耦合作用完成水体污染物净化的效能研究,根据不同人工湿地和水体污染物类型进行配置等4个方面。     

人工快渗一体化设备在农村污水处理中的应用

针对农村污水的特点,结合湖北十堰地区农村污水处理工程案例,分析了以人工快渗技术为核心的一体化设备在实际应用中的运行效果和工艺优势。经过实际运行监测,工程处理出水主要水质指标可达到GB 18918—2002《城镇污水处理厂污染物排放标准》一级A排放标准,并且该工艺设备具有运行成本低、抗冲击负荷能力强、运行管理方便等优点,可有效地解决目前农村地区由于资金、技术、人才等因素限制造成的污水处理能力低和管理水平低的问题,是一种适合我国农村地区污水处理的工艺设备。     

一种多介质层波形潜流人工湿地处理重污染河水试验

我国河流污染严重,城市黑臭水体的比率日益增加。人工湿地作为一种高效低耗能的绿色处理技术,已被广泛应用于污染河水的治理。通过对比分析分层装填复合填料的多介质层波形潜流人工湿地和单一砾石填料的普通人工湿地处理重污染河水的效果,研究了特种基质填料强化脱氮除磷作用以及不同水力负荷条件的影响。试验结果表明:在水力负荷为0.2 m~3/(m~2·d)时,普通湿地对COD、NH3-N、TN和TP的去除率分别达到55.95%、77.85%、39.80%和54.94%;多介质层湿地对COD、NH3-N、TN和TP的去除率分别达到58.52%、75.99%、67.08%和57.31%。在水力负荷为0.5 m~3/(m~2·d)时,普通湿地对COD、NH3-N、TN和TP的去除率分别达到68.46%、90.73%、42.13%和53.70%;多介质层湿地对COD、NH3-N、TN和TP的去除率分别达到69.61%、89.94%、77.58%和68.63%,其脱氮效果明显好于普通湿地。以复合填料包分层装填的波形潜流人工湿地系统具有良好的脱氮除磷效果,有很好的推广应用价值。     

Effects of sludge retention time, carbon and initial biomass concentrations on selection process: From activated sludge to polyhydroxyalkanoate accumulating cultures

Four sequence batch reactors (SBRs) fed by fermented sugar cane wastewater were continuously operated under the aerobic dynamic feeding (ADF) mode with different configurations of sludge retention time (SRT), carbon and initial biomass concentrations to enrich polyhydroxyalkanoate (PHA) accumulating mixed microbial cultures (MMCs) from municipal activated sludge. The stability of SBRs was investigated besides the enrichment performance. The microbial community structures of the enriched MMCs were analyzed using terminal restriction fragment length polymorphism (T-RFLP). The optimum operating conditions for the enrichment process were: SRT of 5 days, carbon concentration of 2.52 g COD/L and initial biomass concentration of 3.65 g/L. The best enrichment performance in terms of both operating stability and PHA storage ability of enriched cultures (with the maximum PHA content and PHA storage yield (Y_PHA/S) of 61.26% and 0.68 mg COD/mg COD, respectively) was achieved under this condition. Effects of the SRT, carbon concentration and initial biomass concentration on the PHA accumulating MMCs selection process were discussed respectively. A new model including the segmentation of the enrichment process and the effects of SRT on each phase was proposed.     

复合生物阴极型微生物燃料电池处理废水及同步产电性能

为研究生物阴极在MFC（微生物燃料电池）中的应用,分别以粒径为2~4 mm的颗粒活性炭和粒径为2~4、4~8、8~12 mm的颗粒石墨为阴极基质材料,构建升流复合生物阴极型单室MFC,研究阴极基质材料的种类和粒径对MFC的产电性能和净水效能的影响.结果表明:当阳极基质材料为2~4 mm粒径的颗粒活性炭时,燃料电池中利用玻璃纤维取代离子交换膜,阴极基质材料为选用4~8 mm粒径颗粒石墨的反应柱产电量最大,为534 mV（外电阻为1 000 Ω）,最大功率密度达到631.6 mW/m3,库伦效率为3.82%;阴极的pH越低越有利于阴极的产电反应;不同阴极基质材料的MFC对COD_Cr去除率均在80%左右,TN、NH₄+-N及TP的去除率最高可分别达到79%、93%和34%.研究显示,阴极基质材料的种类和粒径对MFC的产电性影响较大,但对其净水效能的影响不大.      

CHO cell cytotoxicity and genotoxicity analyses of disinfection by-products: An updated review

The disinfection of drinking water is an important public health service that generates high quality, safe and palatable tap water. The disinfection of drinking water to reduce waterborne disease was an outstanding public health achievement of the 20th century. An unintended consequence is the reaction of disinfectants with natural organic matter, anthropogenic contaminants and bromide/iodide to form disinfection by-products (DBPs). A large number of DBPs are cytotoxic, neurotoxic, mutagenic, genotoxic, carcinogenic and teratogenic. Epidemiological studies demonstrated low but significant associations between disinfected drinking water and adverse health effects. The distribution of DBPs in disinfected waters has been well defined by advances in high precision analytical chemistry. Progress in the analytical biology and toxicology of DBPs has been forthcoming. The objective of this review was to provide a detailed presentation of the methodology for the quantitative, comparative analyses on the induction of cytotoxicity and genotoxicity of 103 DBPs using an identical analytical biological platform and endpoints. A single Chinese hamster ovary cell line was employed in the assays. The data presented are derived from papers published in the literature as well as additional new data and represent the largest direct quantitative comparison on the toxic potency of both regulated and emerging DBPs. These data may form the foundation of novel research to define the major forcing agents of DBP-mediated toxicity in disinfected water and may play an important role in achieving the goal of making safe drinking water better.     

Predicting vehicle fuel consumption patterns using floating vehicle data

The status of energy consumption and air pollution in China is serious. It is important to analyze and predict the different fuel consumption of various types of vehicles under different influence factors. In order to fully describe the relationship between fuel consumption and the impact factors, massive amounts of floating vehicle data were used. The fuel consumption pattern and congestion pattern based on large samples of historical floating vehicle data were explored, drivers'' information and vehicles'' parameters from different group classification were probed, and the average velocity and average fuel consumption in the temporal dimension and spatial dimension were analyzed respectively. The fuel consumption forecasting model was established by using a Back Propagation Neural Network. Part of the sample set was used to train the forecasting model and the remaining part of the sample set was used as input to the forecasting model.