复合磁性光催化剂Co_(0.5)Zn_(0.5)Fe_2O_4/Bi_2WO_6的制备及其光催化性能

以Co_(0.5)Zn_(0.5)Fe_2O_4为磁基体,制备了Co_(0.5)Zn_(0.5)Fe_2O_4/Bi_2WO_6复合磁性光催化剂。分别采用XRD、SEM、EDS和PL光谱技术对光催化剂进行了表征。利用氙灯为光源,以环丙沙星为目标污染物,考察了光催化剂对环丙沙星的降解性能。表征结果显示:复合磁性光催化剂中Bi_2WO_6晶相含量高,且结晶度大;Co_(0.5)Zn_(0.5)Fe_2O_4与Bi_2WO_6的质量比为1∶8时,Co_(0.5)Zn_(0.5)Fe_2O_4磁基体与Bi_2WO_6基本复合(该复合磁性光催化剂以Co_(0.5)Zn_(0.5)Fe_2O_4/Bi_2WO_6(Ⅱ)表示);Co_(0.5)Zn_(0.5)Fe_2O_4/Bi_2WO_6复合光催化剂光生空穴和电子复合几率低,具有较好的光催化性能。实验结果表明,Co_(0.5)Zn_(0.5)Fe_2O_4/Bi_2WO_6(Ⅱ)具有较高的光催化活性,光催化反应140 min后对环丙沙星的降解率达82.39%,且具有良好的磁性能,易实现固液分离,便于回收再利用。     

Characteristics of atmospheric single particles during haze periods in a typical urban area of Beijing: A case study in October, 2014

To investigate the composition and possible sources of particles, especially during heavy haze pollution, a single particle aerosol mass spectrometer (SPAMS) was deployed to measure the changes of single particle species and sizes during October of 2014, in Beijing. A total of 2,871,431 particles with both positive and negative spectra were collected and characterized in combination with the adaptive resonance theory neural network algorithm (ART-2a). Eight types of particles were classified: dust particles (dust, 8.1%), elemental carbon (EC, 29.0%), organic carbon (OC, 18.0%), EC and OC combined particles (ECOC, 9.5%), Na-K containing particles (NaK, 7.9%), K-containing particles (K, 21.8%), organic nitrogen and potassium containing particles (KCN, 2.3%), and metal-containing particles (metal, 3.6%). Three haze pollution events (P1, P2, P3) and one clean period (clean) were analyzed, based on the mass and number concentration of PM_2.5 and the back trajectory results from the hybrid single particle Lagrangian integrated trajectory model (Hysplit-4 model). Results showed that EC, OC and K were the major components of single particles during the three haze pollution periods, which showed clearly increased ratios compared with those in the clean period. Results from the mixing state of secondary species of different types of particles showed that sulfate and nitrate were more readily mixed with carbon-containing particles during haze pollution episodes than in clean periods.     

基于Vague集的隧道施工安全管理脆弱性评价

为了客观地查找并量化隧道施工安全管理系统的脆弱点及管控要点,本文以系统脆弱性的3个特征要素,即暴露性、敏感性和适应性为二级指标,以隧道施工安全管理系统脆弱性的8项直接影响因素为三级指标,构建系统脆弱性评价体系。提出基于区间数互反判断矩阵与Vague集理论的隧道施工安全管理系统脆弱性评价模型,该模型使用区间数描述指标之间的相对重要程度,以模糊信息对系统脆弱性进行量化评价。通过山西吕梁某隧道施工项目,验证该模型的有效性,结果表明,该模型能够实现对系统脆弱性、特征要素以及各关键指标的量化评价。     

事故树-风险矩阵评估高校实验室火灾风险

为了使高校实验室安全管理科学化、精准化,应用事故树-风险矩阵法进行风险评估。首先采用事故树法对实验室火灾事故进行分析,得出导致事故发生的基本事件,然后依照事故致因理论,得出事故隐患三级原因,采用层次分析法对事故发生的频率和后果严重度及安全措施补偿系数的等级赋值,得到四级风险矩阵模型,对基本事件调查并由专家评估得出其风险值。评估结果表明导致实验室火灾事故的主要原因为:燃烧反应失控、加热、人员消防素质、操作不当、实验室管理水平、火灾报警系统缺陷、电气火花、灭火材料不足、消防系统缺陷、木制品、反应放热、存放不当。根据基本事件风险值高低针对性采取相应预防措施可以一定程度上提升实验室安全管理水平。     

油气储运设施事故风险指数模糊逻辑评估方法

油气储运设施风险是其事故发生概率和事故后果的综合度量,而事故概率和后果的定量评估结果往往是具有不确定性的数据,以确定性风险评估准则为基础的传统风险矩阵法和风险值法显然难以评估油气储运设施风险。为此提出开展油气储运设施事故风险的模糊逻辑推理法,首先,对风险矩阵的概率语言等级和损失语言等级的边界进行定量划分;然后,建立油气储运设施风险矩阵模糊集和模糊逻辑推理规则;最后,通过风险模糊推理运算和模糊风险解模糊化以确定油气储运设施的风险水平。实例应用与分析表明,利用推荐方法可得到较为详尽的风险数据信息,不但风险指数更加清晰,而且其所属风险等级类别也更加明确,评估结果能更好地指导油气储运设施的风险管理。     

Endogenous nitric oxide mediates alleviation of cadmium toxicity induced by calcium in rice seedlings

The effect of calcium chloride (CaCl₂) on rice seedling growth under cadmium chloride (CdCl₂) stress, as well as the possible role of endogenous nitric oxide (NO) in this process, was studied. The growth of rice seedlings was seriously inhibited by CdCl₂, and the inhibition was significantly mitigated by CaCl₂. However, hemoglobin (Hb) and 2-(4-carboxyphenyl)-4, 4,5,5-tetramethylimidazolinel- oxyl-3-oxide (cPTIO) weakened the promotion effect of CaCl₂. The results of NO fluorescence localization suggest that growth accelerated by CaCl₂ might be associated with elevated NO levels. The content of Cd, protein thiols (PBT), and nonprotein thiols (NPT) in cell walls, cell organelles, and soluble fractions, respectively, of rice seedlings decreased considerably in the presence of CaCl₂, whereas the content of pectin, hemicellulose 1 (HC1), and hemicellulose 2 (HC2) increased significantly. Elimination of endogenous NO in Cd+Ca treatment could promote the transportation of Cd²⁺ to cell organelles and soluble fractions and increase the content of NPT and PBT in leaves. In addition, transportation of Cd²⁺ to cell organelles and soluble fractions was retarded in roots, the content of NPT increased, and the content of PBT decreased. With elimination of endogenous NO in Cd+Ca treatment, the content of pectin, HC1, and HC2 decreased significantly. Thus, Ca may alleviate Cd toxicity via endogenous NO with variation in the levels of NPT, PBT, and matrix polysaccharides.     

Comparison of PM10 concentrations and metal content in three different sites of the Venice Lagoon: An analysis of possible aerosol sources

The Venice Lagoon is exposed to atmospheric pollutants from industrial activities, thermoelectric power plants, petrochemical plants, incinerator, domestic heating, ship traffic, glass factories and vehicular emissions on the mainland. In 2005, construction began on the mobile dams (MOSE), one dam for each channel connecting the lagoon to the Adriatic Sea as a barrier against high tide. These construction works could represent an additional source of pollutants. PM₁₀ samples were taken on random days between 2007 and 2010 at three different sites: Punta Sabbioni, Chioggia and Malamocco, located near the respective dam construction worksites. Chemical analyses of V, Cr, Fe, Co, Ni, Cu, Zn, As, Mo, Cd, Sb, Tl and Pb in PM₁₀ samples were performed by Inductively coupled plasma-quadrupole mass spectrometry (ICP-QMS) and results were used to identify the main aerosol sources. The correlation of measured data with meteorology, and source apportionment, failed to highlight a contribution specifically associated to the emissions of the MOSE construction works. The comparison of the measurements at the three sites showed a substantial homogeneity of metal concentrations in the area. Source apportionment with principal component analysis (PCA) and positive matrix factorization (PMF) showed that a four principal factors model could describe the sources of metals in PM₁₀. Three of them were assigned to specific sources in the area and one was characterised as a source of mixed origin (anthropogenic and crustal). A specific anthropogenic source of PM₁₀ rich in Ni and Cr, active at the Chioggia site, was also identified.     

A/O-MBR处理餐饮废水过程中DOM特性解析

借助凝胶过滤色谱(GFC)分子量测定技术和三维荧光(EEM)光谱技术,对厌氧微网与好氧平板膜-生物反应器(A/O-MBR)联合处理餐饮废水过程中各阶段的溶解性有机物(DOM)及污泥胞外聚合物(EPS)的性质进行研究。分子量研究表明:好氧段污泥滤液的GFC谱图中在10 min以前有大分子物质析出,分析是微生物代谢产物;且随着处理过程的进行水样DOM中的分子量分布范围不断变宽。EEM光谱研究表明:进水、好氧段出水、好氧段污泥滤液的DOM中的2种主要荧光物质为高激发波长类色氨酸和可见区类富里酸,而厌氧段出水中仅有高激发波长类色氨酸,且峰强较强。同时,厌氧段出水中在形成可见区类富里酸的区域内有成峰趋势,分析是由较强的类色氨酸峰的掩蔽作用造成的。好氧段污泥EPS中存在3个明显的荧光峰,指示了色氨酸和腐殖酸的存在。     

Ability of Matrix Models to Explain the Past and Predict the Future of Plant Populations

Uncertainty associated with ecological forecasts has long been recognized, but forecast accuracy is rarely quantified. We evaluated how well data on 82 populations of 20 species of plants spanning 3 continents explained and predicted plant population dynamics. We parameterized stage‐based matrix models with demographic data from individually marked plants and determined how well these models forecast population sizes observed at least 5 years into the future. Simple demographic models forecasted population dynamics poorly; only 40% of observed population sizes fell within our forecasts’ 95% confidence limits. However, these models explained population dynamics during the years in which data were collected; observed changes in population size during the data‐collection period were strongly positively correlated with population growth rate. Thus, these models are at least a sound way to quantify population status. Poor forecasts were not associated with the number of individual plants or years of data. We tested whether vital rates were density dependent and found both positive and negative density dependence. However, density dependence was not associated with forecast error. Forecast error was significantly associated with environmental differences between the data collection and forecast periods. To forecast population fates, more detailed models, such as those that project how environments are likely to change and how these changes will affect population dynamics, may be needed. Such detailed models are not always feasible. Thus, it may be wiser to make risk‐averse decisions than to expect precise forecasts from models. Habilidad de los Modelos Matriciales para Explicar el Pasado y Predecir el Futuro de las Poblaciones de Plantas     

Actual and Potential Use of Population Viability Analyses in Recovery of Plant Species Listed under the U.S. Endangered Species Act

Use of population viability analyses (PVAs) in endangered species recovery planning has been met with both support and criticism. Previous reviews promote use of PVA for setting scientifically based, measurable, and objective recovery criteria and recommend improvements to increase the framework's utility. However, others have questioned the value of PVA models for setting recovery criteria and assert that PVAs are more appropriate for understanding relative trade‐offs between alternative management actions. We reviewed 258 final recovery plans for 642 plants listed under the U.S. Endangered Species Act to determine the number of plans that used or recommended PVA in recovery planning. We also reviewed 223 publications that describe plant PVAs to assess how these models were designed and whether those designs reflected previous recommendations for improvement of PVAs. Twenty‐four percent of listed species had recovery plans that used or recommended PVA. In publications, the typical model was a matrix population model parameterized with ≤5 years of demographic data that did not consider stochasticity, genetics, density dependence, seed banks, vegetative reproduction, dormancy, threats, or management strategies. Population growth rates for different populations of the same species or for the same population at different points in time were often statistically different or varied by >10%. Therefore, PVAs parameterized with underlying vital rates that vary to this degree may not accurately predict recovery objectives across a species’ entire distribution or over longer time scales. We assert that PVA, although an important tool as part of an adaptive‐management program, can help to determine quantitative recovery criteria only if more long‐term data sets that capture spatiotemporal variability in vital rates become available. Lacking this, there is a strong need for viable and comprehensive methods for determining quantitative, science‐based recovery criteria for endangered species with minimal data availability. Uso Actual y Potencial del Análisis de Viabilidad Poblacional para la Recuperación de Especies de Plantas Enlistadas en el Acta de Especies En Peligro de E.U.A