纳米铁氧化物吸附处理重金属废水的研究进展

概述了用于吸附重金属的主要纳米铁氧化物的种类及其吸附效果,介绍了常见的纳米铁氧化物制备方法及改性方法,讨论了影响纳米铁氧化物吸附重金属的主要因素,并对纳米铁氧化物在水环境保护领域中的研究方向提出了展望:如发展绿色、高效的纳米铁氧化物制备工艺,探讨纳米铁氧化物结构调控和表面功能化对其吸附性能的影响等。     

Ti3C2纳米层状材料对废水中Cr（Ⅵ）的光催化去除性能

以Ti₃AlC₂为原料,采用HF刻蚀工艺制备出12种Ti₃C₂纳米层状材料,对其形貌进行了表征,并考察了以其作为光催化剂对废水中Cr（Ⅵ）的处理效果。实验结果表明：HF体积分数为80%、刻蚀时间为48 h时得到的MX-80-48的形貌较好;MX-80-48具有类似石墨烯的二维层状结构,纳米层厚度约20~50 nm,孔径2~10 nm,比表面积14.8 m²/g,在400~700 nm可见光范围内表现出强烈的吸光性;当Cr（Ⅵ）的初始质量浓度为40.00 mg/L、MX-80-48投加量为200 mg/L、pH=2、反应时间4 h（暗反应1 h+光照3 h）时,Cr（Ⅵ）去除率可达100%。     

水处理中微生物絮凝剂产生菌的选育及应用

综述了微生物絮凝剂产生菌筛选和培育方面的研究进展,介绍了微生物絮凝剂在给水和饮用水、乳化液的油水分离、污水处理等领域的应用,以及廉价培养基的探索实践。提出针对影响微生物絮凝剂产生菌生长代谢的环境条件开展深入研究,同时寻找或设计廉价培养基,降低生产成本,推动其工业化应用。     

加速溶剂同时萃取和净化-气相色谱-三重四极杆串联质谱测定土壤和沉积物中8种多溴联苯醚

建立了土壤和沉积物中8种多溴联苯醚(PBDEs,BDE-28、BDE-47、BDE-99、BDE-100、BDE-153、BDE-154、BDE-183和BDE-209)加速溶剂同时萃取和净化-气相色谱-三重四极杆串联质谱(ASE-GC-MS-MS)的分析方法。通过优化加速溶剂萃取与弗罗里硅土在线净化和串联质谱多反应监测模式的条件,较好地去除基质干扰,并提高了三重四极杆串联质谱定性的准确性及定量的灵敏性。该方法采用改进的色谱柱能同时分析包括高溴代联苯醚BDE-209在内的8种PBDEs,其浓度范围为1～100 ng/mL(BDE-209为10～1 000 ng/mL),线性良好,线性回归系数均大于0.997。方法检出限为0.004～0.1 ng/g,方法回收率为75%～110%,方法精密度为2.4%～15.6%。适于批量处理土壤和沉积物中含有多组分痕量PBDEs的样品。     

SMBBR-AF-SMBBR组合工艺处理高氨氮农药废水

采用特异性移动床生物膜反应器(SMBBR)和厌氧生物滤池(AF)组合工艺处理高氨氮农药废水。考察了HRT、pH和DO等工艺条件对SMBBR-AF-SMBBR组合工艺运行稳定期COD和氨氮去除率的影响。试验结果表明,在进水COD为2 408~7 440 mg/L、ρ(NH_4~+-N)为160.21~433.84 mg/L、TN为208.27~537.65 mg/L、HRT为8d、pH为8.0、DO为4 mg/L的条件下,处理后出水平均COD为342 mg/L,COD去除率达92.3%;ρ(NH_4~+-N)小于4.0mg/L,氨氮平均去除率为89.2%;TN小于50 mg/L,平均TN去除达83.0%。出水各指标均优于原A2O工艺出水。     

氨废水资源化利用的折流式超重力床集成技术

利用折流式超重力床将氨废水处理的精馏和吸收过程集成在一台设备中,开发出一种设备小型化、流程紧凑的氨废水资源化利用集成技术。与传统技术相比,该技术在大幅节省占地面积和空间的同时,还可大幅节约设备建设所用钢材。工业规模试验结果表明,不同浓度的氨废水经该技术处理后可转化为氨质量分数大于22%的氨水资源,处理出水中氨氮质量浓度低于8.2 mg/L,尾气中未检测到氨,处理结果优于GB 31573—2015《无机化学工业污染物排放标准》。     

煤制乙二醇废水预处理装置的工业化调试

针对煤制乙二醇废水含高浓度硝酸盐氮的特点,设计了缺氧膨胀床(AEB)反应器预处理装置,并进行了工业化启动和调试运行,考察了其在反硝化连续流运行条件下的处理效果及工艺参数变化。结果表明,AEB反应器启动后,填料层生物膜挂膜快速且生长稳定。反应器在工业化调试阶段运行稳定,COD和TN的去除率和去除负荷较为稳定。在受到来水冲击后,AEB反应器处理效果稳定,出水可在短期内恢复正常。该技术的系统操控参数范围较广,易于工业化操控运行,在煤制乙二醇废水和其他含高浓度硝酸盐氮废水的处理中具有较大的推广价值。     

室内空气和灰尘中全(多)氟烷基化合物的研究进展

全(多)氟烷基化合物(per(poly)fluoroalkyl substances,PFASs)在环境各个介质及人体样品中广泛被检出,近年,在室内空气和灰尘中也普遍发现PFASs.研究表明,室内空气中PFASs的含量普遍高于室外空气,室内空气和灰尘中的PFASs可能是室外空气的污染来源及人体暴露源,因此室内环境中PFASs成为环境领域的又一个研究热点.但目前为止,我国还没有开展室内空气中PFASs的相关研究,室内灰尘中PFASs的研究也相对较少.本文就室内空气和灰尘中PFASs的采样与分析方法、污染现状、来源分析及人体暴露等4个方面进行了综合阐述,以期为我国室内环境中PFASs的研究提供参考.     

Review: recent advances in biogas purifying technologies

Biomethane production through biogas upgrading is a promising renewable energy for some industries which could be part of the equilibrium needed with fossil fuels consumption to achieve a sustainable society. This paper presents a comprehensive list of biogas upgrading technologies focused on carbon dioxide removal as well as recent advances reported by researcher with wide expertise in this topic. Additionally, an extensive costs–performance comparison among the technologies studied is discussed. Among the different alternatives, chemical scrubbing stood out to achieve high biomethane purities while cryogenic technologies proved to be effective against methane losses. Regarding the different costs, water scrubbing and membrane separation seem to be the most affordable techniques.     

Modeling of a sequencing batch reactor treating municipal wastewater using multi-layer perceptron and radial basis function artificial neural networks

A sequencing batch reactor was modeled using multi-layer perceptron and radial basis function artificial neural networks (MLPANN and RBFANN). Then, the effects of influent concentration (IC), filling time (FT), reaction time (RT), aeration intensity (AI), SRT and MLVSS concentration were examined on the effluent concentrations of TSS, TP, COD and NH₄⁺-N. The results showed that the optimal removal efficiencies would be obtained at FT of 1 h, RT of 6 h, aeration intensity of 0.88 m³/min and SRT of 30 days. In addition, COD and TSS removal efficiencies decreased and TP and NH₄⁺-N removal efficiencies did not change significantly with increases of influent concentration. The TSS, TP, COD and NH₄⁺-N removal efficiencies were 86%, 79%, 94% and 93%, respectively. The training procedures of all contaminants were highly collaborated for both RBFANN and MLPANN models. The results of training and testing data sets showed an almost perfect match between the experimental and the simulated effluent of TSS, TP, COD and NH₄⁺-N. The results indicated that with low experimental values of input data to train ANNs the MLPANN models compared to RBFANN models are more precise due to their higher coefficient of determination (R²) and lower root mean squared errors (RMSE) values.