Bi-PbO2电极电化学氧化去除模拟废水中氨氮的研究

本实验采用钛网作为基体,利用电沉积方法制备了纯PbO2电极和Bi-PbO2电极,通过SEM、XRD、XPS对电极的表面形态进行了表征,利用循环伏安法对Bi-PbO2电极电化学特性进行了研究.同时,以氨氮模拟废水作为研究对象,考察了Bi-PbO2电极的电催化活性,探讨了氨氮电化学氧化降解机理.结果表明,Bi-PbO2电极的形态表征、电催化活性明显高于纯PbO2电极,氨氮的去除效率随电流密度的增加而提高,碱性条件下氨氮的去除效果明显好于酸性条件,适量浓度的Cl-的引入在碱性条件下提高了氨氮的去除效果.当氨氮初始浓度为50 mg·L-1、电流密度为40 mA·cm-2、pH=12、Cl-浓度为600 mg·L-1时,电解120 min后,氨氮100%去除.氨氮的降解机理为:体系中无添加氯离子,酸性条件下氨氮主要是通过间接氧化去除,碱性条件下通过直接电氧化和间接氧化共同完成;体系中添加氯离子,氨氮的去除主要是通过溶液中生成的有效氯间接氧化去除.     

电化学法处理工业废水的现状与发展研究

随着工业的快速发展,如何对工业废水进行高效处理是我们需要解决的问题。电化学方法反应装置简单,反应效率高,不会产生二次污染。对中国工业废水目前常用的电化学处理技术的进展和应用进行了综述,包括电化学氧化、电化学还原、电絮凝、电渗析等内容,对国内外的研究成果的总结可知,电化学法对工业废水的处理效率较高,有一定的应用前景。同时对电化学法将来的重点研究方向提出了展望。     

生态环境变化遥感评价指数的应用研究——以敖江流域为例

利用1994年5月12日与2009年6月6日的Landsat TM和2001年5月23日的Landsat ETM＋卫星影像,选用遥感生态指数（RSEI）,结合流域的植被覆盖度状况,定量评价了15年间敖江流域的生态环境变化与植被覆盖度变化情况,并对二者的关系进行了简要分析.结果表明：15年间,敖江流域生态等级为优所占的面积比例从13.48％上升到24.90％,增加了304.29 km2;植被覆盖度等级为极高的面积增加比例为29.31％.总体看来,敖江流域生态环境状况和植被覆盖状况均有明显的提高,两者具有较好的对应关系.     

电化学还原-氧化工艺降解4-氯酚的毒性研究

采用紫外光还原法制备了Pd-Fe/石墨烯催化阴极,并以Ti/IrO_2/RuO_2为阳极,构成三电极体系(双阴极)和两电极体系(单阴极)的电化学还原-氧化降解工艺,分别对4-氯酚进行降解.采用离子色谱、高效液相色谱、TOC仪对4-氯酚降解过程中中间产物及其浓度进行测定.根据公式计算降解过程中理论计算毒性值,应用发光细菌法测定降解过程中的实际毒性值,对理论计算毒性值与实际毒性值进行比较,分析不同体系下降解过程中毒性的变化规律.结果表明,两种工艺体系在最佳降解条件下,阴极室毒性均呈下降的趋势,由于降解过程中在阳极室生成高毒性的苯醌,阳极室毒性均先升高后降低.通过相关性分析得到,两种体系理论计算毒性与实际毒性在P=0.01水平下,相关性系数均为1,显著相关,表明降解过程中实际毒性的测定结果真实可靠.降解至120 min时,三电极体系毒性小于两电极体系,表明三电极体系优于两电极体系.据此提出实际毒性测定方法在电化学还原-氧化工艺降解氯酚类有机废水毒性测试的工业应用中有着广泛的前景.     

基于EMD-HHT可定位长输天然气管道第三方破坏事件监测技术

为适应目前管道安全监测需要,满足对扰动信号分类监测的实际需求,提出1种基于希尔伯变换和经验模态分解(EMD-HHT)的信号特征提取技术,利用基于φ-OTDR分布式光纤传感系统采集振动信号,通过EMD+HHT区分算法对管道沿线振动事件进行分解并提取6个典型特征向量,各特征事件数据经过EMD后选取IMF3为最终提取特征向量的原始数据,BP神经元网络可有效识别机械破坏、敲击破坏、车辆经过、人工挖掘、动力干扰5种事件。研究结果表明：在长输管道信号识别中,BP神经网络对5类事件平均识别率高达98.6%,该技术分类识别5类事件扰动信号,能够达到较高准确性,并且误报率平均在1.3%,能较好满足现场安全实时监测需求。研究结果对长输油气管道附近第三方破坏扰动信号分类监测具有一定参考意义。     

地表水环境遥感监测关键技术与系统

本文主要是围绕地表水环境遥感检测展开讨论,全面介绍了水环境检测的关键技术和系统,建立改进双峰法的水体分布遥感提取方法,并以具体地区为例进行分析,采用不同方法建立解析方法,从根本上提升反演方法的区域和积极适用性,希望能够对相关人员起到参考性价值。     

二氧化碳资源化技术研究进展

过量的二氧化碳(CO2)排放可导致温室效应的不断加剧,因此CO2减排受到越来越多的关注,其中将CO2转化为附加值较高的化工产品,即CO2资源化利用技术不仅可实现CO2减排,同时具有一定的经济效益。CO2资源化利用技术主要包括光化学还原法、电化学还原法和催化转移氢化法等。重点介绍并总结了以上3种方法的特点、优势和不足,指出未来需研究解决的关键问题和研究方向,为实现高效的CO2资源化利用提供借鉴和参考。     

玛纳斯河流域荒漠草地沙化遥感监测研究

以1989—2016年玛纳斯河流域TM/OLI遥感影像为数据源,利用混合像元分解技术,计算玛纳斯河流域草地总覆盖度和裸沙面积。在此基础上通过监测年与基期年的比较,计算草地覆盖度相对基期年的减少率和裸沙面积相对基期年的增加率两个监测指标,依据《天然草地退化、沙化、盐渍化的分级指标》(GB 19377—2003),对计算出的两个指标分别进行沙化等级评定和赋值,将两种评定结果相综合来监测草地沙化。结果表明,玛纳斯河流域近30年来荒漠草地沙漠化总体呈现先增加后降低的趋势。分析表明,玛纳斯河流域草地沙化是人为和自然因素双重作用的结果。     

Mapping the Spatial Variability of Plant Diversity in a Tropical Forest: Comparison of Spatial Interpolation Methods

Knowledge of the spatial distribution of plant species is essential to conservation and forest managers in order to identify high priority areas such as vulnerable species and habitats, and designate areas for reserves, refuges and other protected areas. A reliable map of the diversity of plant species over the landscape is an invaluable tool for such purposes. In this study, the number of species, the exponent Shannon and the reciprocal Simpson indices, calculated from 141 quadrat sites sampled in a tropical forest were used to compare the performance of several spatial interpolation techniques used to prepare a map of plant diversity, starting from sample (point) data over the landscape. Means of mapped classes, inverse distance functions, kriging and co-kriging, both, applied over the entire studied landscape and also applied within vegetation classes, were the procedures compared. Significant differences in plant diversity indices between classes demonstrated the usefulness of boundaries between vegetation types, mapped through satellite image classification, in stratifying the variability of plant diversity over the landscape. These mapped classes, improved the accuracy of the interpolation methods when they were used as prior information for stratification of the area. Spatial interpolation by co-kriging performed among the poorest interpolators due to the poor correlation between the plant diversity variables and vegetation indices computed by remote sensing and used as covariables. This indicated that the latter are not suitable covariates of plant diversity indices. Finally, a within-class kriging interpolator yielded the most accurate estimates of plant diversity values. This interpolator not only provided the most accurate estimates by accounting for the indices' intra-class variability, but also provided additional useful interpretations of the structure of spatial variability of diversity values through the interpretation of their semi-variograms. This additional role was found very useful in aiding decisions in conservation planning.     

Hyperspectral Characteristics of Canopy Components and Structure for Phenological Assessment of an Invasive Weed

Spectral reflectance values of four canopy components (stems, buds, opening flowers, and postflowers of yellow starthistle (Centaurea solstitialis)) were measured to describe their spectral characteristics. We then physically combined these canopy components to simulate the flowering stage indicated by accumulated flower ratios (AFR) 10%, 40%, 70%, and 90%, respectively. Spectral dissimilarity and spectral angles were calculated to quantitatively identify spectral differences among canopy components and characteristic patterns of these flowering stages. This study demonstrated the ability of hyperspectral data to characterize canopy components, and identify different flowering stages. Stems had a typical spectral profile of green vegetation, which produced a spectral dissimilarity with three reproduction organs (buds, opening flowers, and postflowers). Quantitative differences between simulated flower stages depended on spectral regions and phenological stages examined. Using full-range canopy spectra, the initial flowering stage could be separated from the early peak, peak, and late flowering stages by three spectral regions, i.e. the blue absorption (around 480 nm) and red absorption (around 650 nm) regions and NIR plateau from 730 nm to 950 nm. For airborne CASI data, only the red absorption region and NIR plateau could be used to identify the flowering stages in the field. This study also revealed that the peak flowering stage was more easily recognized than any of the other three stages.