蛋白组学技术的发展及在水生态毒理学中的应用

作为后基因组时代重要的研究工具,蛋白组学技术的发展对水生态毒理学研究产生了巨大的促进作用。对近年来应用于水生态毒理学研究中的蛋白组学技术的发展历程和应用现状进行了全面的阐述。从蛋白提取、蛋白分离和鉴定、蛋白定量等方面对蛋白组学研究技术的发展进行了系统的介绍,重点介绍和比较了蛋白分离和鉴定技术中的基于胶的技术和非胶技术。在简介蛋白组学技术发展的基础上,以蛋白的识别和定量,特定功能蛋白的研究,蛋白相互作用研究这3个蛋白组学的研究方向为切入点,详细阐述了各类技术在水生态毒理学研究中的应用,如蛋白组学在阐明各种污染物对水生生物的毒性作用机制方面的应用,以及在水体污染状况的监测和评价方面的应用等。最后,指出了目前蛋白组学研究的不足,并有针对性地提出了水生态毒理学研究中蛋白组学的发展方向。     

SBR工艺处理晚期垃圾渗滤液的脱氮特性研究

采用有效容积为1 200 m3的SBR反应器处理晚期垃圾渗滤液,进行生物脱氮特性研究.结果表明,通过投加粪水调节进水C/N,能显著提高SBR反应器对晚期垃圾渗滤液中氮素污染物的去除效果,其中第112~136 d的TN平均去除率高达82.62%,出水TN≤190 mg.L-1,COD≤400 mg.L-1;能在反应器内达到各种生物脱氮反应的平衡状态,BOD5与TN去除量的比值稳定在1.43左右.在稳定平衡阶段,通过对反应器内氮素污染物和SO24-的含量变化进行周期跟踪监测,发现在搅拌回流阶段存在NH4+-N和SO24-的同时等比例去除现象,去除率分别为27.06%和76.17%,反应器内存在同步硝化反硝化和同步脱氮除硫(SO24-)过程;量化分析了反应器内各种生物脱氮反应,得到异养反硝化、同步硝化反硝化、同化作用、同步脱氮除硫(SO24-)和内源呼吸反硝化对TN去除量的贡献率分别为62.6%、33.8%、7.0%、26.1%和2.7%.     

数量化理论Ⅲ及其在煤与瓦斯突出危险性评估中的应用

研究了数量化理论Ⅲ建立煤与瓦斯突出危险性的原理和方法,以瓦斯地质学理论为基础,建立了包括煤层瓦斯含量、煤层瓦斯压力、煤层分岔合并现象、地质构造复杂程度、煤的破坏类型等11个地质因素的煤层突出危险性评估指标体系。以数量化理论Ⅲ为工具,实例分析得出马依西一井3煤层突出危险性的敏感地质因素及因素轴F1,以该轴上得分大于0.1的地质因素作为强突出的敏感地质因素;得分小于-0.1的地质因素作为弱突出的敏感地质因素,得分在0.1--0.1之间的地质因素作为中等突出的敏感地质因素,将矿井划分为强突出、中等突出和弱突出三个区域。该方法实现了地勘阶段煤与瓦斯突出的定量分析,进一步细化了突出区域的划分。     

电化学原位产生H2O2的影响因素分析及数学建模

以Pt为阳极,石墨碳棒为阴极,Na2SO4为支持电解质,实验探讨了电化学原位产生H2O2的规律.通过正交试验,确定阴极溶液初始pH值、电流密度CD、通氧流量Q和支持电解质浓度CNa2SO4等主要参数对H2O2产生量的影响,并提出最佳参数组合:pH=2.00,CD=1.02mA·cm-2,Q=0.4L·min-1,CNa2SO4=0.1 mol·L-1,极间距D=6cm.采用二次多项式逐步回归和BP神经元网络2种方法,建立了这些参数对于H2O2产生量的预测模型,并对模型进行检验.结果表明,2种方法在一定参数条件下都可预测阴极区溶液中H2O2浓度,BP神经元网络法预测的准确度好于二次多项式逐步回归方法,且更适合于在线控制.     

基于蒙特卡洛模拟的多米诺事故风险量化管理*

为降低危化品相关的化工事故造成的人员伤亡和财产损失,以化工多米诺事故为研究对象,探讨由初始事故引发1个或多个次生事故的连锁反应机理与风险评估方法。提出应用蒙特卡洛模拟对多米诺事故风险进行动态量化的方法,梳理化工多米诺事故风险的识别、分析、评定、处理全周期管理流程,并以1个天然气压气站为案例,验证基于蒙卡模拟的化工多米诺事故风险量化方法的有效性。结果表明:该方法可以更准确地对化工多米诺事故风险进行定量评估。多米诺事故风险全周期管理流程的梳理能够有效指导化工企业开展安全管理、事故预防等工作。     

Trends of air pollution in the Fichtelgebirge Mountains, Bavaria

We analyzed 13 years of hourly measurements of SO₂, NO_x, and O₃, at forest ecosystem research sites in SE Germany. A quasi-continuous data record was obtained by combining data sets from two locations. Before interpreting trends in the combined data set, we analyzed if the change of location introduced a systematic bias. We employed autocorrelation functions, Hurst statistics, complexity analysis, and recurrence quantification and found that the partial data sets exhibited no indication of the presence of any bias. For SO₂, we also compared the data from the forest sites with data obtained in nearby cities and also found no indications for any systematic effects. Applying nonparametric trend statistics we found a significant decrease of the SO₂. Most of the observed decrease is due to the reductions of SO₂ emissions in eastern Germany, but reductions in western Germany and the Czech Republic also played important roles. For O₃, we observed a significant increase, the causes of which are unclear from our data alone. No trend was identified for NO_x.     

Matrix effect on the performance of headspace solid phase microextraction method for the analysis of target volatile organic compounds (VOCs) in environmental samples

Solid phase microextraction (SPME) is a fast, cheap and solvent free methodology widely used for environmental analysis. A SPME methodology has been optimized for the analysis of VOCs in a range of matrices covering different soils of varying textures, organic matrices from manures and composts from different origins, and biochars. The performance of the technique was compared for the different matrices spiked with a multicomponent VOC mixture, selected to cover different VOC groups of environmental relevance (ketone, terpene, alcohol, aliphatic hydrocarbons and alkylbenzenes). VOC recovery was dependent on the nature itself of the VOC and the matrix characteristics. The SPME analysis of non-polar compounds, such as alkylbenzenes, terpenes and aliphatic hydrocarbons, was markedly affected by the type of matrix as a consequence of the competition for the adsorption sites in the SPME fiber. These non-polar compounds were strongly retained in the biochar surfaces limiting the use of SPME for this type of matrices. However, this adsorption capacity was not evident when biochar had undergone a weathering/aging process through composting. Polar compounds (alcohol and ketone) showed a similar behavior in all matrices, as a consequence of the hydrophilic characteristics, affected by water content in the matrix. SPME showed a good performance for soils and organic matrices especially for non-polar compounds, achieving a limit of detection (LD) and limit of quantification (LQ) of 0.02 and 0.03 ng g⁻¹ for non-polar compounds and poor extraction for more hydrophilic and polar compounds (LD and LQ higher 310 and 490 ng g⁻¹). The characteristics of the matrix, especially pH and organic matter, had a marked impact on SPME, due to the competition of the analytes for active sites in the fiber, but VOC biodegradation should not be discarded in matrices with active microbial biomass.     

基于可拓物元模型的安全经济开采评价指标体系的构建及应用

首先根据安全经济开采的内涵,建立以人员安全、设施设备安全、开采环境安全、安全投资和安全管理为主要制约因素的安全经济开采评价模型,并运用改进的层次分析法确定人员可靠度对安全经济开采水平影响最大,开采环境可靠度影响最小。其次,采用函数拟合法、专家打分法、标准化打分法量化安全经济开采水平指标,并将安全经济开采水平划分为3个等级。最后,运用可拓物元模型方法,得出某铁矿安全经济开采水平为二级,无重大经济损失,与实际吻合。     

航空维修人为差错影响因素分析中的模糊层次分析法

航空维修中的人为差错影响因素分析对于预防事故发生至关重要,如何定量分析及辨识出主要影响因素是亟待解决的问题。为此,结合航空维修实际,提出运用群组模糊层次分析法对人为差错影响因素进行量化排序和分类,归纳细化了影响因素层次体系,并给出了分析计算流程。以一起由维修人为差错所引发的航空事故为例进行了实证分析,结果表明:该方法能够辨识出航空维修中人为差错产生的主要影响因素,进而对制订最优事故预防方案,控制和减少该类事故的发生有积极意义。同时该方法对其他行业中的人为差错主要影响因素辨识有着一定的参考价值。