沸石负载介孔TiO_2的制备及其可见光催化性能研究

以人工沸石为载体,采用溶胶-凝胶法,制备出了沸石负载介孔改性TiO2光催化剂。以亚甲基蓝为目标污染物,研究了不同掺杂金属及介孔薄膜制备方法对纳米TiO2可见光催化性能的影响。用扫描电镜(SEM)、紫外-可见吸收光谱(UV-vis)等手段研究了掺杂改性前后TiO2的变化。研究发现,N-Fe掺杂可使催化剂的光吸收谱带红移。当掺杂Fe的比为0.2%,焙烧温度为500℃时制备的TiO2效果最好,在可见光照射2 h后,亚甲基蓝的去除率可达90%。研究表明经十六烷基三甲基溴化铵(CTAB)作为模板剂修饰后的TiO2催化效果有明显提高,通过将经过萃取去除模板剂的共掺TiO2和直接高温焙烧的TiO2对比后发现,前者比后者降解亚甲基蓝的效果要好,原因在于,高温直接焙烧去除模板剂很容易使模板剂形成的骨架塌陷,减小了比表面积,从而影响了其光催化性能。     

塔里木河下游区域植被时空变化

为了对比生态输水工程实施前后塔里木河下游植被变化,分析植被对生态输水的时空响应,基于1986-2017年研究区上方无云的22期Landsat NDVI数据,辅以波动分析、趋势分析,探索研究区植被的时空变化特征,并对其驱动因素进行分析。结果表明：（1）空间上,植被的分布与水资源的分布密切相关,主要沿河道和积水区域分布。（2）1986-2000年,NDVI呈现缓慢下降趋势,2000-2017年NDVI总体呈现波动增加趋势;植被对生态输水有一定的滞后性,且与输水量密切相关。（3）研究区NDVI时间序列的方差介于0.0077~0.1957间,存在明显的空间差异,其波动的大小与植被种类密切相关。（4）1986-2000年,植被的NDVI空间趋势以减小为主,并主要发生在英苏和老英苏附近;2000-2017年,植被的NDVI空间趋势以增加为主,且主要发生在沿河道区域和喀尔达依东侧。     

温度对镁合金牺牲阳极材料电化学行为的影响研究

目的研究温度对常用镁合金阳极材料MIC、AZ31、AZ63电化学行为的影响。方法根据GB/T 17848—1999,采用四天加速试验法,在25～70℃的人造海水介质中进行阳极电化学性能评价,并观察腐蚀后阳极的宏观腐蚀形貌。采用极化曲线测试技术,研究温度对加速试验前后阳极的极化行为影响。结果随着温度的升高,三种镁阳极的局部腐蚀明显加剧,溶解状态逐渐变得不均匀。随着温度的上升,三种镁阳极的实际电容量和电流效率呈小幅增加趋势,温度的影响不显著。极化曲线显示,镁阳极表现出活化溶解特征,温度升高明显促进了镁阳极的阴极过程,自腐蚀速率逐渐增加。结论在腐蚀初期,温度升高明显促进了镁合金阳极的腐蚀过程,但对镁阳极的电化学性能影响不显著,这可能与后期腐蚀产物生成以及表面状态的变化有关。     

气候变化和人类活动对东部沿海地区NDVI变化的影响分析

植被是陆地生态系统的重要组成部分,特别是在人类活动密集地区,良好的植被覆盖对于维持区域生态环境稳定、增进居民生活福祉和促进社会经济可持续发展意义重大.基于归一化植被指数(NDVI)、气温、降水和太阳辐射数据,采用趋势分析、偏相关分析和残差分析等方法,探究了1982～2019年中国东部沿海地区NDVI时空变化特征及其与气候因子的关系,评估了气候因素和人类活动等非气候因素对NDVI变化的影响.结果表明：(1)1982～2019年研究区NDVI变化趋势具有明显区域性、阶段性和季节性差异,就区域平均而言,2000年以前(第一阶段)的生长季NDVI比2001年以后(第二阶段)增加更快,而两阶段春季NDVI增加速率均为各季节最快;(2)同一阶段NDVI与各气候因子的关系在不同季节存在差异,而同一季节NDVI的主要气候控制因子在不同阶段也不一致,并且NDVI与气候因子的关系具有很大空间差异.总体上,1982～2019年研究区生长季NDVI的增加与气温的持续上升关系紧密,第二阶段降水和太阳辐射的增加也产生了积极作用;(3)相比于人类活动等非气候因素的影响,气候变化对近38年来研究区生长季NDVI变化的...     

天然高寒草地转变为混播人工草地对土壤微生物群落特征的影响

为了研究天然高寒草地转变为混播人工草地对土壤微生物群落的影响,采用高通量测序技术分析了青海省共和县的天然以及由天然转变为混播人工草地样地土壤中的微生物群落.结果表明,天然草地转变为混播人工草地后植被物种多样性和土壤有机质含量显著下降(P<0.05).在两块样地共检测到29个细菌门和11个真菌门的微生物.天然草地转变为人工草地后,土壤细菌的多样性显著升高,细菌的香农指数从9.51增加到9.89;土壤真菌的多样性降低但差异不显著.与天然草地相比,人工草地的土壤细菌与真菌群落结构、组成均发生了明显的变化,细菌群落结构与总有机质的含量、总氮含量和土壤含水量显著相关,真菌群落结构与总有机质含量和土壤含水量显著相关.线性判别分析(LEfSe)结果表明,暗黑菌门细菌(Atribacteria)和子囊菌门真菌(Ascomycota)可作为天然草地的指示微生物类群,出芽菌属细菌(Gemmata)和发菌科真菌(Trichocomaceae)可作为人工草地的指示微生物类群.利用Tax4Fun2对细菌群落功能的预测发现,天然草地向人工草地的转变影响了细菌群落对不同碳源的利用潜力.     

Seven Years of Change Following Liming of Sphagnum Communities in Sector Vii of the Loch Fleet Catchment

In 1986, application of lime within the upper wetland area of sector VII of the Loch Fleet catchment initiated numerous unscheduled small-scale experiments on the vegetation of this heterogeneous terrain. Vegetation changes and erosion were monitored in permanent or relocated plots established in 1987 and 1989 and re-surveyed in 1993, seven years after liming.

The most striking early effect, possibly occurring within a few weeks of lime application, was the death of Sphagnum papillosum carpet in soakways within the 2.5 ha area. Some patches of dead material were washed away, but bare surfaces were generally colonised by vascular plants, notably Juncus bulbosus. Effects in moorland and bog communities with dwarf shurbs were more subtle, involving reduction in Sphagnum cover and expansion of Erica teralix, Molinia caerulea, sedges and Narthecium ossifragum, but little change in the frequency of occurrence of Calluna vulgaris.     

Pipeline leakage detection and isolation: An integrated approach of statistical and wavelet feature extraction with multi-layer perceptron neural network (MLPNN)

Leakage diagnosis of hydrocarbon pipelines can prevent environmental and financial losses. This work proposes a novel method that not only detects the occurrence of a leakage fault, but also suggests its location and severity. The OLGA software is employed to provide the pipeline inlet pressure and outlet flow rates as the training data for the Fault Detection and Isolation (FDI) system. The FDI system is comprised of a Multi-Layer Perceptron Neural Network (MLPNN) classifier with various feature extraction methods including the statistical techniques, wavelet transform, and a fusion of both methods. Once different leakage scenarios are considered and the preprocessing methods are done, the proposed FDI system is applied to a 20-km pipeline in southern Iran (Goldkari-Binak pipeline) and a promising severity and location detectability (a correct classification rate of 92%) and a low False Alarm Rate (FAR) were achieved.     

盐池封育草场土壤种子库特征及其与植被的关系

封育是退化草场恢复的重要措施之一,封育的效果在一定程度上取决于土壤中种子库的状况。以毛乌素沙地西南缘宁夏盐池县的退化草场为研究对象,采用相似性分析和排序方法对封育和未封育草场土壤种子库的特征及其与地上植被间关系进行了研究,结果表明无论封育区还是未封育区,土壤种子库中的种子主要分布于0～5cm的土层,6～15cm土层的种子数很少;封育区土壤种子库的物种丰富度大于未封育区,物种多样性则表现为H值较大,而D值较小,总体上看封育措施可以提高地上植被和土壤中种子的种类和数量,一些一年生植物、中生植物和盐生植物开始出现在地面或土壤种子库中。地上植被和土壤种子库间的相似性分析结果则表明相同措施同一土层间种子库中等相似,而不同土层间还是存在着一些差异。由于封育措施导致了植被样方的相似性较低,然而土壤种子库间的相似性仍然较高,两者间是否存在着一定程度的滞后效应有待于进一步研究。     

The potential implementation of green infrastructure assessment using high-resolution National Agriculture Imagery Program data for sustainable hazard mitigation

As green infrastructure gets its attention in hazard mitigation, it is necessary to improve general understanding on what makes green infrastructure important for hazard and resiliency research. To better understand how green infrastructure fits with more traditional notions of structural and nonstructural mitigation, this study examines the relationship between green infrastructure and ‘structural and nonstructural’ mitigation approaches for hazard mitigation. Also, this study discusses a new measurement of locational aspects and spatial patterns of green infrastructure by utilizing high-resolution data in urban areas, and its potential implementation in hazard mitigation. Compared to previous research using land-use land-cover datasets, the normalized difference vegetation index (NDVI) utilizing National Agriculture Imagery Program dataset provides an ability to capture green infrastructure in greater detail. A visual comparison suggests that the NDVI data are able to capture and identify more types of ‘green’ land uses in Harris County. The total green infrastructure percentages for Harris County, Texas, based on 1-m high resolution were found to be 61.5% of the area, compared to the 51.5% based on the National Land Cover Database. This study provides support for utilizing high-resolution data to establish guidelines for green infrastructure’s spatial characteristics and sustainable hazard mitigation. The outcomes of this study will be helpful in the strategic planning and implementation of green infrastructure in urban areas with hazard issues.