重庆主城区秋冬季逆温对空气质量影响的观测分析

2013年9—11月利用RPG-HATPRO地基多通道微波辐射计对重庆主城区大气进行连续探测,统计了大气逆温情况,并对典型重污染天气下大气逆温与空气质量状况进行综合分析。结果表明,逆温出现的频率为63.3%,基本为接地逆温类型,逆温层厚度为953 m,逆温强度为0.3℃/hm;逆温的存在为气溶胶的积聚和凝聚创造了有利条件。     

磷酸活化-微波热解改性污泥对镉的吸附性能

以城市污水处理厂剩余污泥为原料,利用磷酸活化-微波热解制取改性污泥。以此污泥作为吸附剂,对含Cd2+废水进行了吸附实验研究。考察了溶液反应时间、Cd2+浓度、pH值和吸附剂用量对镉吸附去除效果的影响;利用等温吸附实验作出吸附等温线,并考察了改性污泥吸附剂吸附Cd2+的动力学方程。实验结果表明,改性污泥对Cd2+有良好的吸附性能,吸附最佳pH值为6.0,吸附较好地符合一级动力学吸附模型和Langmuir-Freundlich等温吸附方程,吸附为物理吸附,吸附反应发生12 h后达到吸附平衡。     

酸改性泥炭对含亚甲基蓝废水的吸附净化作用

采用稀硝酸对泥炭进行改性处理获得酸改性泥炭,并将其用于处理亚甲基蓝废水。考察初始溶液pH、接触时间、酸改性泥炭投加量和亚甲基蓝溶液初始浓度等因素对酸改性泥炭吸附效果影响。结果表明,初始溶液pH、接触时间、酸改性泥炭投加量和亚甲基蓝溶液初始浓度对酸改性泥炭吸附性能都有一定的影响。在最佳的反应条件下(接触时间为60 min,反应温度为35℃,初始溶液pH为7.12,酸改性泥炭投加量为2 g),亚甲基蓝去除率可达90.88%,其吸附较好地符合Freundlich和Langmuir等温方程,拟合相关系数均大于0.9。通过热力学计算发现,ΔG<0、ΔS>0,表明该吸附反应是自发的、吸热反应。且该吸附过程符合准二级动力学方程(R2=0.98)。     

内源电子受体产生及其在抑制富磷剩余污泥释磷行为中的应用

根据生物脱氮除磷系统产生的富磷剩余污泥含有硝化细菌和生产废水含有高浓度氨氮的特点,将生产废水中的氨氮转化为硝酸盐(内源电子受体),并将获得的内源电子受体利用在富磷剩余污泥浓缩过程,同步实现内源电子受体反硝化及其抑制富磷剩余污泥释磷行为。结果表明,将富磷剩余污泥(excess activated sludge,EAS。EAS1是在好氧方式下添加,EAS2是在缺氧方式下添加)与生产废水(reject water)按4种比例(Ⅰ、生产废水∶EAS1∶EAS2=15%∶85%∶0%;Ⅱ、生产废水∶EAS1∶EAS2=15%∶80%∶5%;Ⅲ、生产废水∶EAS1∶EAS2=15%∶75%∶10%;Ⅳ、生产废水∶EAS1∶EAS2=15%∶65%∶20%)混合曝气用于产生内源电子受体时,最佳硝化时间均为12 h,可将液相中的氨氮分别由初始的(113.16±0.85)mg/L、(117.18±4.39)mg/L、(129.48±4.85)mg/L及(142.53±0)mg/L降至(0.74±0.41)mg/L、(0.45±0.15)mg/L、(0.41±0.15)mg/L及(0.38±0.08)mg/L;同时,硝酸盐氮分别由初始的(7.48±7.91)mg/L、(12.87±5.81)mg/L、(12.87±5.81)mg/L及(13.55±6.18)mg/L升为(128.37±11.03)mg/L、(141.43±12.71)mg/L、(148.01±14.84)mg/L及(146.22±7.53)mg/L。内源电子受体可将重力浓缩过程中释磷量分别削减85%、63%、64%及83%,同时使得由生产废水回流引起的氨氮积累量分别减少89.25%、69.93%、74.31%及85.40%。在整个内源电子受体产生及其应用于抑制污泥释磷阶段,TN去除率分别为39.59%、44.54%、51.86%及57.33%。上述内源电子受体胁迫条件下的浓缩过程中,不仅可以有效降低由重力浓缩释磷引起的磷积累量,且可同步实现减少由生产废水回流引起的氨氮积累量。     

MFC-MBR耦合系统运行效果及产电性能

为了解决膜生物反应器(MBR)运行成本高、膜污染的问题,本研究建立了一个微生物燃料电池(MFC)-MBR耦合系统,通过MFC回收污水中的能量,同时控制膜污染。研究结果表明,耦合系统对COD和NH3-N的去除率分别为(94.6±3.0)%和(90.9±6.9)%,出水水质稳定。由于MFC的耦合作用,使MBR的运行周期由18 d延长至36 d,膜污染得到了明显的减缓。耦合系统中MFC产电性能稳定,电流密度稳定在5.7 A/m3,最大功率密度达到了928.0 mW/m3,循环伏安法(CV)表明,阴极附着的微生物具有良好的电化学催化作用。MFC-MBR耦合系统将污水中的化学能转化为电能从而实现了膜污染的减缓及能量的回收,显示出巨大的发展前景。     

水泥窑共处置过程中水泥生料对砷的吸附/冷凝特性

针对水泥生料开展了氮吸附与SEM测试分析,研究了水泥生料的比表面积,孔径结构和微观表面积。同时,利用管式回转炉和控温立式炉联用装置研究了砷元素在水泥生料上的吸附冷凝特性。结果表明,水泥生料的比表面积很小,微观表面结构致密无孔,砷元素主要是冷凝在生料表面上。进入吸附冷凝炉的重金属可以分为3部分,第1部分冷凝在管壁上,占80%左右;第2部分吸附/冷凝在生料上,占10%左右;第3部分随烟气释放到空气中,不到10%。水泥生料对砷的吸附冷凝量随时间的增加而增加,随温度的升高而降低。水泥生料对砷的吸附冷凝特性可用双常数速率方程拟合,拟合效果较好,计算得表观活化能在6~7 kJ/mol之间。此外,砷的初始浓度对水泥生料的吸附冷凝特性影响很小。     

络合萃取技术分离制药废水中的金刚烷胺

以P204为络合剂萃取水溶液中的金刚烷胺,研究了正辛醇和煤油2种稀释剂对萃取效果的影响,分析了萃取过程的络合机理和热力学过程,并考察了该萃取体系对实际制药废水中金刚烷胺的萃取效果。结果表明,采用P204/正辛醇=3∶2的复配萃取剂,在初始pH为8.0,在油/水相比为1∶1的条件下,金刚烷胺的萃取效率可以达到99.8%以上;以2.0mol/L的HCl溶液为反萃取剂,可以将51.1%的负载金刚烷胺反萃回收;红外光谱分析表明,P204对金刚烷胺的萃取遵循离子交换和离子缔合成盐机制;萃取过程为放热过程,低温条件下有利于萃取反应的进行;P204/正辛醇复配萃取剂对实际制药废水中的金刚烷胺也具有很高的萃取效率。     

The effects of residual tetracycline on soil enzymatic activities and plant growth

A pot trial was carried out to investigate the adverse effects of tetracycline (TC) on soil microbial communities, microbial activities, and the growth of ryegrass (Lolium perenne L). The results showed that the presence of TC significantly disturbed the structure of microbial communities and inhibited soil microbial activities in terms of urease, acid phosphatase and dehydrogenase (p < 0.05). Plant biomass was adversely influenced by TC, especially the roots with a reduction of 40% when compared with the control. Furthermore, TC decreased the assimilation of phosphorus by the plant although the concentration of phosphorus was increased by 20% due to decreased plant biomass. TC seemed to increase the concentration of dissolved organic carbon (by 20%) in soil. The findings implied that the agricultural use of animal manure or fishpond sediment containing considerable amounts of antibiotics may give rise to ecological risks.     

Enantioselectivity of racemic metolachlor and S-metolachlor in maize seedlings

Chiral herbicides may have enantioselective effects on plants. In this study, we assessed and compared the enantioselectivity of the chiral herbicides rac-metolachlor and S-metolachlor to maize seedlings. The superoxide dismutase activity (SOD) activity of roots and stem leaves treated by rac-metolachlor was 1.38 and 1.99 times that of roots and stem leaves treated by S-metolachlor. The peroxidase activity (POD) activity of roots and stem leaves was 1.48 and 2.79 times that of roots and stem leaves treated by S-metolachlor, respectively, while the catalase activity (CAT) activity was 4.77 and 8.37 times greater, respectively. The Hill reaction activity of leaves treated by rac-metolachlor were 1.45, 1.33, and 1.14 times those treated by S-metolachlor with treatments of 18.6, 37.2, and 74.4 μM. The differences observed between treatments of rac- and S-metolachlor were significant. Significant differences in maize seedling morphology were also observed between rac- and S-metolachlor treatments. The degradation rate of S-metolachlor in roots was greater than that of rac-metolachlor. The half-lives of rac- and S-metolachlor were 80.6 and 60.3 h at 18.6 μM; 119.5 and 90 h at 37.2 μM; and 169 and 164.8 h at 74.4 μM, respectively. Using the liquid chromatography-mass spectrometry method, hydroxymetolachlor, deschlorometolachlor and deschlorometolachlor propanol were considered to be possible metabolites. We determined the enantioselective toxicity of rac- and S-metolachlor to maize and speculated on the proposed metabolic pathway of metolachlor in maize roots. These results will help to develop an understanding of the proper application of rac- and S-metolachlor in crops, and give some information for environmental safety evaluation of rac- and S-metolachlor.     

An Intelligent Emissions Controller for Fuel Lean Gas Reburn in Coal-Fired Power Plants

ABSTRACT

The application of artificial intelligence techniques for performance optimization of the fuel lean gas reburn (FLGR) system is investigated. A multilayer, feedforward artificial neural network is applied to model static nonlinear relationships between the distribution of injected natural gas into the upper region of the furnace of a coal-fired boiler and the corresponding oxides of nitrogen (NO_x) emissions exiting the furnace. Based on this model, optimal distributions of injected gas are determined such that the largest NO_x reduction is achieved for each value of total injected gas. This optimization is accomplished through the development of a new optimization method based on neural networks. This new optimal control algorithm, which can be used as an alternative generic tool for solving multidimensional nonlinear constrained optimization problems, is described and its results are successfully validated against an off-the-shelf tool for solving mathematical programming problems. Encouraging results obtained using plant data from one of Commonwealth Edison's coal-fired electric power plants demonstrate the feasibility of the overall approach.

Preliminary results show that the use of this intelligent controller will also enable the determination of the most cost-effective operating conditions of the FLGR system by considering, along with the optimal distribution of the injected gas, the cost differential between natural gas and coal and the open-market price of NO_x emission credits. Further study, however, is necessary, including the construction of a more comprehensive database, needed to develop high-fidelity process models and to add carbon monoxide (CO) emissions to the model of the gas reburn system.