Bacterial colonization of the phyllosphere of nineteen plant species and antimicrobial activity of their leaf secondary metabolites against leaf associated bacteria

Summary. The scope of this work was to examine whether leaf constitutive secondary metabolites play a role in determining bacterial colonization of the phyllosphere. To this aim, we surveyed nineteen native or cultivated plant species that share a common bacterial pool in a North Mediterranean area, and estimated the size of total and ice nucleation active (INA) bacterial populations on their leaves. Large differences in the colonization of their phyllosphere were found; the population size of epiphytic bacteria ranged from 7.5 × 10² to 1 × 10⁶ CFU/g fresh weight, in eucalypt and celery, respectively. Species native in Mediterranean-type climate areas, particularly those belonging to the group of aromatic plants, are characterized by scarce presence of INA bacteria. The antibacterial activity of essential oils, surface phenolics and leaf tissue extracts was also estimated against the INA strains P. syringae and E. herbicola, isolated from two of these plant species. E. herbicola proved more sensitive than P. syringae. Of the species examined, oregano [Origanum vulgare L. subsp. hirtum (Link.) Ietswaart], an aromatic plant, had the highest antimicrobial activity, whereas six species showed no activity at all. Further experiments were performed with oregano and bean (Phaseolus vulgaris L.) that represent two extremes in their secondary metabolite content. Both plants were inoculated with P. syringae. By the end of incubation, the bacterial population on bean plants was about 100 times higher than that on oregano leaves. Scanning electron micrographs showed that bacterial growth on oregano leaves was confined to sites away from glandular hairs. Results from the bacterial colonization survey together with those from the toxicity tests showed that all species rich in antibacterial secondary metabolites harbored low leaf bacterial populations. These results provide substantial evidence that leaf secondary metabolites function as constitutive defense chemicals against microbial invasions. However, the fact that species with non- or moderately active leaf secondary metabolites are not always highly colonized suggests mediation of other unknown factors, the contribution of which requires further investigation.     

便携式GC/MS对空气中苯系物的定量分析方法研究

文章采用简单快速的采气袋配气方式,以苯系物为例,研究了便携式GC/MS对大气中痕量有机污染物的快速定量测定方法。分别在Full scan和建立的SIM扫描方式下对苯系物标准样品进行了测定。对比实验结果表明,Full scan和SIM两种扫描方式下苯系物测定结果的相对标准偏差分别在5.1%~28.4%和13%~19%之间,回收率范围分别为46%~186%和60%~110%,方法检出限范围分别为2.504~10.63μg/m3和0.494~2.399μg/m3。总体而言,SIM方式在测定结果的精密度与准确度上均优于Full scan方式。室内外空气样品的测试结果映证了SIM方式在对痕量有机污染物测定的优势。     

燃煤电厂排放细颗粒物的水溶性无机离子特征综述

当前我国面临严重的大气细颗粒物(PM2.5)污染,燃煤电厂是大气中PM2.5的重要来源之一.为了实现国家"十一五"和"十二五"规划对二氧化硫(SO2)和氮氧化物(NOx)的总量减排目标,燃煤电厂大规模安装烟气脱硫和脱硝设施,这虽然减少了气态污染物转化生成的二次PM2.5,但另一方面也会对烟气中PM2.5的物理化学特征产生影响,有可能增加一次PM2.5的排放.本文综述了燃煤电厂排放PM2.5及其水溶性离子的粒径分布特征,重点介绍了脱硫和脱硝这两种烟气处理设施对燃煤电厂排放PM2.5的影响原理及相关研究结果,特别是对细颗粒物中水溶性离子(如SO2-4、Ca2+和NH+4)的影响.在目前我国PM2.5污染十分严重和燃煤电厂大量安装脱硫和脱硝装置的背景下,定量研究脱硫和脱硝对PM2.5排放特征的影响具有十分重要的意义.     

藻华聚集的环境效应:对漂浮植物水葫芦光合作用的影响

利用适应性强、生物量大的水生植物来净化污染水体,已成为目前水体生态修复的一种快捷有效的方法.然而,在夏季蓝藻水华严重聚集的水体,藻华聚集后对水生植物的生理生态影响及其环境效应,尚缺乏系统研究.本研究以水葫芦为代表,模拟在高温阶段(水温WT25℃)、水华严重聚集时,对水葫芦的光合作用的影响进行研究,以揭示蓝藻水华聚集后造成的浅水生态系统中水生植物消亡的深层机制,并为减轻藻华聚集对水生植物的不良影响、充分发挥水生植物的水体净化功能提供理论依据.结果表明,藻华聚集会很快消耗掉水生植物根区内的溶氧,呈现缺氧状态(DO0.2 mg·L-1);植物根区内ORP出现明显下降现象,实验进行1 d后低于-100 m V,实验结束时达-200 m V,水体呈现强还原环境.与对照相比,根区内p H值低0.7个单位.藻华细胞在死亡、分解后释放大量的无机营养盐于水体中,植物根区内的NH+4-N含量比对照实验中高102倍;较高的NH+4-N含量(平均为45.6 mg·L-1)加之缺氧的协迫作用,导致植物机体受到破坏,植物的光合作用能力严重下降.叶片的平均净光合速率仅为对照的0.6倍,实验结束时其光合速率Pn为3.96μmol·(m2·s)-1,而同期对照实验的叶片净光合速率Pn为22.0μmol·(m2·s)-1;叶片蒸腾速率仅为对照的0.55倍,至实验结束时其蒸腾速率为1.38 mmol·(m2·s)-1,同期对照实验的叶片蒸腾速率为7.61 mmol·(m2·s)-1,表明藻华长期的聚集对植物产生了不可逆的伤害作用.在实际生产中,要避免蓝藻的严重堆积和快速消亡,以减轻藻华暴发对植物的伤害,充分发挥植物的水体净化功能.     

京津冀天然源挥发性有机物排放研究

为探明2017年京津冀地区天然源挥发性有机物(BVOCs)的空间分布,将研究区划分成3 km分辨率的格网,并通过WRF模型提供气象驱动数据,MODIS影像提供植被功能类型和叶面积指数,最终利用MEGAN模型进行模拟研究.结果表明,该模型将BVOCs分成147个细类,其中主要有异戊二烯、单萜烯41类、半萜烯32类、其他VOC73类.2017年京津冀地区BVOCs排放总量为426.26×10~3 t,四大类别的排放比例依次为29.38%、12.32%、6.24%、52.05%.单萜烯中排放较高的类别是α-蒎烯、β-蒎烯、t-β-罗勒烯,而半萜烯中排放较高的是α-法呢烯和β-石竹烯.整个研究区域内BVOCs排放较高的区域位于北部森林与灌丛分布密集的燕山山脉和西南的太行山山脉,其中主要的城市有承德、北京、张家口、保定、石家庄等.排放量较低的地区为廊坊、衡水、天津等地.本研究通过模型模拟得到了京津冀地区2017年高时空分辨率BVOCs排放清单,同时可为以后的大气环境研究提供基础数据.     

基于数据分解的AQI的CEEMD-Elman神经网络预测研究

针对Elman神经网络在预测空气质量指数（AQI）时易受到数据非平稳性的影响导致预测趋势良好但准确度较低的问题,提出以互补集合经验模态分解（Complementary Ensemble Empirical Mode Decomposition,CEEMD）为基础的CEEMD-Elman模型.应用CEEMD对AQI序列分解成不同时间尺度上的本征模态函数分量和剩余分量,进而首次将对非平稳的AQI序列的预测研究转化为对多个平稳的本征模态函数分量的研究.分别与Elman单一模型、EMD-Elman模型、BP单一模型及CEEMD-BP模型进行实验对比.结果表明：应用该方法建立的模型的均方误差、平均绝对误差和平均绝对百分比误差分别为4.80、0.71、1.84%,均小于其他模型结果;对应空气质量等级预报正确天数的频率为94.12%.该模型能有效的降低非平稳性对实验预测结果的影响,实现对空气质量等级的准确预报;该研究为进一步预测AQI的走向提供了有效依据,也为政府决策和管理部门制定空气污染控制提供了更充分的参考.     

Morphology and composition of particles emitted from a port fuel injection gasoline vehicle under real-world driving test cycles

Traffic vehicles, many of which are powered by port fuel injection (PFI) engines, are major sources of particulate matter in the urban atmosphere. We studied particles from the emission of a commercial PFI-engine vehicle when it was running under the states of cold start, hot start, hot stabilized running, idle and acceleration, using a transmission electron microscope and an energy-dispersive X-ray detector. Results showed that the particles were mainly composed of organic, soot, and Ca-rich particles, with a small amount of S-rich and metal-containing particles, and displayed a unimodal size distribution with the peak at 600?nm. The emissions were highest under the cold start running state, followed by the hot start, hot stabilized, acceleration, and idle running states. Organic particles under the hot start and hot stabilized running states were higher than those of other running states. Soot particles were highest under the cold start running state. Under the idle running state, the relative number fraction of Ca-rich particles was high although their absolute number was low. These results indicate that PFI-engine vehicles emit substantial primary particles, which favor the formation of secondary aerosols via providing reaction sites and reaction catalysts, as well as supplying soot, organic, mineral and metal particles in the size range of the accumulation mode. In addition, the contents of Ca, P, and Zn in organic particles may serve as fingerprints for source apportionment of particles from PFI-engine vehicles.     

基于动态时间弯曲算法的核电厂瞬态识别方法研究

目的对核电厂运行瞬态识别进行有效识别。方法基于动态时间弯曲算法,计算运行瞬态中温度、压力和流速数据与设计瞬态中对应数据之间的相似程度,通过定义等效相似度反应温度、压力和流速的不同权重。在完成当前运行瞬态与各条设计瞬态之间的相似程度后,通过比较相似度值,将运行瞬态归类为设计瞬态。结果通过对"华龙一号"核电厂的设计瞬态和基于设计瞬态摄动获得的虚拟运行瞬态进行验证,文中提出的方法能够快速有效地对运行瞬态进行分类,结果显示,有95%以上的运行瞬态能够被正确识别。结论基于动态时间弯曲算法和等效相似度建立的瞬态识别方法具有高效、准确等优点,能够有效应用于核电厂的疲劳监测系统。     

热障涂层对DD6单晶高温合金高周疲劳性能的影响

目的研究电子束物理气相沉积热障涂层对单晶高温合金高周疲劳性能的影响,为热障涂层在涡轮叶片上的应用提供技术支持。方法采用真空电弧镀和电子束物理气相沉积工艺制备YSZ热障涂层,进行900℃条件下高周疲劳性能测试,采用扫描电镜对测试后的试样表面、断口形貌进行观察与分析。结果在900℃、380 MPa条件下,带涂层的DD6单晶试棒循环次数(Nf)超过了107,420 MPa条件下超过了106。通过对DD6单晶试棒断口分析,失效后的带涂层试棒仍以DD6单晶常见滑移解离形式发生破坏。结论高周疲劳性能测试条件下,带YSZ热障涂层的试棒中粘结层率先产生垂直微裂纹,但是裂纹扩展延伸中发生氧化钝化,之后DD6基体沿正常的滑移方向从表面向内部疲劳扩展,带涂层的试棒疲劳裂纹并非由涂层微裂纹直接扩展形成,热障涂层对DD6单晶高温合金高周疲劳性能影响较小。     

典型平原地区生活垃圾焚烧厂周边土壤重金属赋存形态分布特征及生物有效性评价

为考察并掌握典型平原地区生活垃圾焚烧厂周边土壤中重金属Cd、Cr、Cu、Pb、Ni和Zn的污染现状,以上海市某生活垃圾焚烧厂为例,研究其周边土壤中重金属赋存形态分布特征及生物有效性,采用Tessier连续提取法结合电感耦合等离子体发射光谱检测分析表层土壤中目标重金属总量及形态分布,并利用风险评估编码法（RAC）评价其生态风险水平.结果表明:研究区域土壤中Pb和Zn主要以Fe-Mn氧化物结合态和残渣态为主（>80%）;Cr、Cu和Ni则以残渣态为主（>60%）;Cd虽以残渣态为主（>50%）,但与其他重金属相比,其碳酸盐结合态占比相对较高.生物有效性分析结果显示,Cr、Cu和Ni以惰性态为主,生物有效性低,而潜在可利用态Cd、Pb和Zn占比较高,存在较高的释放风险.土壤中各重金属潜在生态风险水平由高到低依次为Cd > Zn > Pb > Cu > Ni > Cr,其中,Cu、Pb和Zn处于低风险水平,Cr和Ni处于无风险水平,而Cd处于中等风险水平.研究显示,该垃圾焚烧厂周边土壤中重金属已存在不同程度的污染累积,其中,潜在可利用态Cd的占比较高,已达中等风险水平,应引起重视.