互花米草入侵对长江口湿地土壤碳动态的影响

为了评价互花米草入侵对长江河口湿地土壤碳动态的影响,利用配对的试验设计在长江口崇明东滩湿地的高潮滩和低潮滩各设置1条入侵种互花米草与土著种的配对样线.结果表明,与土著植物相比,互花米草入侵显著增加了长江口湿地的植物碳库、土壤微生物碳、土壤总碳库和有机碳库,而对占土壤总碳库60%以上的无机碳库无显著影响,意味着互花米草入侵导致的土壤总碳库改变主要是通过增加土壤有机碳库来实现的.高潮滩互花米草和芦苇群落的年均土壤呼吸强度分别为（210.02±4.90）,（157.79±6.39）mg/（m²·h）;低潮滩互花米草和海三棱藨草群落年均土壤CO₂排放速率分别为（157.41±5.27）,（110.90±5.16）mg/（m²·h）,表明互花米草入侵显著增加长江口湿地的土壤呼吸.上述结果意味着互花米草入侵同时增加土壤碳输入和碳输出,但入侵也显著增加了土壤碳库表明入侵增加的土壤碳输入显著高于增加的土壤碳输出.本研究表明互花米草入侵可能会增强了长江河口湿地的土壤碳汇强度和固碳能力.但仍然需要长期系统的监测研究,以便全面定量评估互花米草入侵我国滨海湿地的综合生态影响.     

Effect of TiO2 nanoparticle aggregation on marine microalgae Isochrysis galbana

TiO_2 nanoparticles(NPs) could adversely impact aquatic ecosystems. However, the aggregation of these NPs could attenuate this effect. In this work, the biological effects of TiO_2 NPs on a marine microalgae Isochrysis galbana were investigated. The aggregation kinetics of TiO_2 NPs under different conditions was also investigated to determine and understand these effects. Results showed that, though TiO_2 NPs had no obvious impact on the size and reproducibility of algal cells under testing conditions, they caused a negative effect on algal chlorophyll, which led to a reduction in photosynthesis. Furthermore, fast aggregation of TiO_2 NPs occurred under all conditions, especially at the pH close to the p Hzpc. Increasing ionic strength and NP concentration also enhanced the aggregation rate.The aggregation and the following sedimentation of TiO_2 NPs reduced their adverse effects on I. galbana.     

提升汇流环湿热环境适应性方法研究

目的提高汇流环在湿热环境下的适应能力。方法实物解剖,观察汇流环绝缘材料损坏情况、碳粉堆积情况,在不同温度、湿度下测试绝缘材料绝缘度、抗电强度,碳粉堆积和导电情况,比对不同绝缘材料性能,并找出最适合的绝缘材料,比对滚动汇流环、碳刷组件、刷丝组件,找到解决碳粉堆积的方法。结果汇流环受湿热影响会从接缝处和电缆连接处进入湿气,温度、湿度的上升会使得原绝缘材料性能下降,长时间使用汇流环,碳粉会在汇流环内堆积并受到湿热的影响而导电,局部密封汇流环可以减少湿气进入。PPO材料性能优异,可以替换原绝缘材料从而减少湿热的影响,使用刷丝组件替代碳刷可以避免碳粉的产生。结论综合运用局部密封、绝缘材料改进、碳刷组件改进三种措施,可以有效提高汇流环在湿热环境下的适应能力。     

碳量子点掺杂氮化碳提高的光电化学阴极保护性能研究

目的研究g-C_3N_4/C-Dots-M复合材料的光电化学阴极保护性能。方法采用X射线衍射(XRD)、扫描电子显微镜(SEM)和紫外可见漫反射光谱技术对样品的晶体结构、微观形貌和光吸收性能进行表征。通过电化学测试可见光照射下g-C_3N_4/C-Dots-M复合材料光电极偶联316L不锈钢后的光电化学阴极保护电流密度和电位变化曲线,研究材料的光电化学阴极保护性能。结果可见光照射下,该偶联体系的光致混合电位下降至-0.43 V(vs. Ag/AgCl),光电化学阴极保护电流密度达到4.3μA/cm。结论得益于碳量子点优异的电子传导特性,g-C_3N_4/C-Dots-550复合材料的光电化学阴极保护性能比纯g-C_3N_4的明显增强。该复合材料在光电化学阴极保护方面展现了较大的应用潜力。     

包装箱用碳纤维增强复合材料贮存寿命研究

目的研究碳纤维增强复合材料贮存条件下的性能变化趋势和寿命评估。方法对碳纤维增强复合材料开展四个不同温度条件下的热氧老化试验,按试验周期定期取样开展冲击性能测试,对试验数据采用寿命预估方法进行处理,对材料性能进行预估。结果通过数据计算分别得到我国热带海洋、干热沙漠等典型气候条件下的碳纤维增强复合材料贮存寿命分别为17.21~35.89年。结论碳纤维增强复合材料具有较好的贮存性能,在较为严酷的热带海洋气候和给定的失效判据条件下,寿命预计为17.21年。试验和数据处理方法可以较好地预计材料的性能变化趋势和开展寿命评估。     

气体中毒窒息事故的环境应急监测

以株洲市攸县某矿业公司"5·7"重大中毒窒息事故的环境应急监测为例，详细阐述了该事故开展应急监测的全过程。针对锁定污染因子、查找污染源、判断污染团的扩散趋势以及监控敏感点的安全等监测目的设计监测方案。通过监测数据分析确定事故特征因子为CO，其周边环境空气中浓度随着与抽风口距离的增加而快速下降，监测到附近居民区环境空气质量未受事故影响。     

超临界二氧化碳萃取－GC／MS测定土壤中的多环芳烃

本文开发了一种采用超临界二氧化碳萃取土壤中多环芳烃、不须经过纯化步骤，直接可用于ＧＣ／ＭＳ分析的简便、高效的方法。本实验中超临界革取的流体是二氧化碳，改善剂是５％的二氯甲烷／甲醇，萃取温度为１２０℃、压力为３４ＭＰａ。ＧＣ／ＭＳ分析时除了采用外标外，还加入了６种同位素ＰＡＨｓ内标以校正各段ＰＡＨｓ的响应因子。采用本方法成功地测定了我国未开垦森林土壤中的ＰＡＨｓ。     

WK－1A型二氧化硫自动测定仪测定烟气中SO_2的方法研究

本文研究了仪器电导法测定烟气中ＳＯ２的监测方法，并与碘量法进行了比较，提出了吸收液测定的影响及吸收液的配制方法。本方法简单快速，能够满足烟气中ＳＯ２监测工作的要求。     

Photocatalytic degradation of phenol

In this study photocatalytic degradation of phenol in thepresence of UV irradiated TiO₂ catalyst andH₂O₂was investigated. Effects of TiO₂ andH₂O₂concentrations and pH on photocatalytic degradation were examined. The rate constants for photocatalytic degradation wereevaluated as a function of TiO₂ and H₂O₂ concentrations and pH of the solution. It was found thatphotodegradation is an effective method for the removal of phenoland disappearance of phenol obeyed first order kinetics. The amount of CO₂h produced during photocatalytic degradation wascorresponding to the complete mineralization. Photodegradationcan be an alternative method for the treatment of phenol containing wastewaters.     

Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NO_x and NO₂ are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x and NO₂ concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods.