工业废水毒性评估与致毒物质鉴别技术进展

综述了工业废水毒性的化学评估方法、生物毒性评估方法、毒性鉴定评估(TIE)程序以及效应引导的毒物鉴别分析(EDA)中污染物提取、分离、毒性测试、致毒物质识别等技术。指出,工业废水毒害风险评估方法正逐渐向化学分析与生物毒性测试相结合的关键致毒物质鉴别方法转变,便捷、高通量是致毒物质鉴别技术的发展方向,质谱技术及替代定性监测技术的发展将提供更为准确、便捷的致毒物质鉴别方法,为工业废水潜在风险防控提供依据。     

Collecting representative dust samples: A comparison of various sampling methods in underground coal mines

Former methods used in the U.S. to assess hazardous and explosible coal dust date back to the 1950s. As mining technologies advanced, so too have the hazards. Given the results of the recent coal dust particle size survey and full-scale experimental mine explosion tests, the National Institute for Occupational Safety and Health (NIOSH) recommended a new minimum standard, in the absence of background methane, of 80% total incombustible content (TIC) be required in the intake airways of bituminous coal mines, replacing the previous 65% TIC requirement. Most important to monitoring and maintaining the 80% TIC is the ability to effectively collect and analyze representative dust samples that would likely disperse and participate in dust explosion propagation. Research has shown that dust suspended on elevated surfaces is usually finer, more reactive, and more readily dispersible while floor deposits of dust are generally coarser and more difficult to disperse given the same blast of air. The roof, rib, and floor portions of the dust samples were collected and analyzed for incombustible content separately and the results were compared to a band sample of the roof, rib, and floor components. Results indicate that the roof and rib dust samples should be kept separate from floor dust samples and considered individually for analyses. The various experimental collection methods are detailed along with preferred sampling approaches that improve the detectability of potentially hazardous accumulations of explosible dust.     

Risk assessment and risk reduction of an acrylonitrile production plant

Reducing accident occurrence in petrochemical plants is crucial, thus appropriately allocating management resources to safety investment is a vital issue for corporate management as international competition intensifies. Understanding the priority of safety investment in a rational way helps achieve this objective.In this study, we targeted an acrylonitrile plant. First, Dow Chemical's Fire and Explosion Index (F&EI) identified the reaction process as having the greatest physical risk. We evaluated the severity of accidents in the reaction process using the Process Safety Metrics advocated by the Center for Chemical Process Safety (CCPS); however, this index does not express damages a company actually experience. To solve this problem, we proposed a new metric that adds indirect cost to CCPS metrics. We adopted fault tree analysis (FTA) as a risk assessment method. In identifying top events and basic events, we attempted to improve the completeness of risk identification by considering accidents from the past, actual plant operation and equipment characteristics, natural disasters, and cyber-attacks and terrorist attacks. Consequently, we identified the top events with high priority in handling because of serious accidents as fire/explosion outside the reactor, fire/explosion inside the reactor, and reactor destruction. The new CCPS evaluation index proposed in this study found that fire and explosion outside the reactor has the highest severity. We considered the creation of the fault tree (FT) diagram of the top event, estimating the occurrence probability, and identifying the risk reduction part and capital investment aimed at risk reduction. As an economically feasible selection method for risk reduction investment, using the difference in loss amounts before and after safety investments indicated investment priority.     

井下光谱多参数分析系统开发

本系统基于气体浓度光学分析方法理论朗伯-比尔(Lambert-Beer)定律、光谱气体检测技术开发,实现了对煤矿火灾与瓦斯灾害超前预警、灾害产生的有毒有害气体实时监测和煤矿环境气体爆炸危险性辨识,对于煤矿灾害防治、救灾过程中杜绝次生灾害,保障煤矿工人及救护队员的生命安全,促进煤矿安全生产具有重要意义。     

一株耐盐柴油降解菌的分离鉴定及其降解性能

从某油田附近受石油污染土壤中分离出一株以柴油为惟一碳源的耐盐菌株LS1。通过对菌株的生理生化特性、菌体的形态观察及16S r DNA基因序列分析鉴定菌株LS1为假单胞菌属(pseudomonas)。该菌株可耐受的最高盐度(Na Cl)和柴油浓度分别为6%~8%和12 000 mg/L。菌株生长的适宜p H和温度条件分别为6.0~8.0和28~36℃。在盐度为6%、p H为7.0、温度为32℃、菌种投加量为10%的条件下,初始浓度为3 000 mg/L的柴油经6 d降解后,去除率可达78.3%,加入适量外加碳源葡萄糖和蔗糖,可使降解率分别提高至92%和90%左右。菌株LS1的耐盐机理可能是通过在细胞内积累甜菜碱以调节菌株细胞内外渗透压平衡。投加甜菜碱可提高耐盐菌LS1在高盐环境下对柴油的降解效率。     

Beyond demographic identities and motivation to learn: The effect of organizational identification on diversity training outcomes

There is a pressing need for better explanations of diversity training effectiveness so that organizations can administer training programs that facilitate positive intergroup interactions. In this paper, we consider the unique predictive effect of organizational identification on diversity training outcomes beyond the effects of the traditional predictors of demographic-based identities and motivation to learn across two samples of employees involved in diversity-related training at their employing organizations. Organizational identification predicted unique variance in voluntary participation in diversity training, diversity training-related knowledge application, motivation to transfer diversity training, and diversity training-related organizational citizenship behavior intentions. Research and practitioner implications are discussed based on our findings.     

State of research on the automation of HAZOP studies

For more than 30 years, multiple research groups have worked on the automation of hazard and operability (HAZOP) studies, or more specifically on the hazard identification process. So far, very few of these approaches have been used in the chemical process industry. Automatic hazard identification is a knowledge-intensive process that demands high standards with regard to the way in which knowledge is stored and made available. There are various suitable approaches to the qualitative modeling of processes and plants, which are the foundation for reasoning systems that are used for the identification of hazards. Additionally, there are quantitative methods that are based on process simulations and can be used to identify potential hazards. The investigation of the state of research demonstrates that there are sophisticated technologies for automated systems that include powerful reasoning techniques. The benefits and shortcomings of existing technologies are discussed with regard to their industrial applicability. Often, the quality of the necessary specific and generic knowledge is not sufficient to detect potential hazardous events and operational malfunctions. Computer-aided HAZOP systems should be integrated with computer-aided design- or process simulation software using common data models based on the digital representation of the process plant. In order to be used by HAZOP practitioners automated systems need to be comprehensive, serve as specialized decision support systems, and be tested and evaluated using round robin tests.     

On the need for system-theoretic hazard analysis in the process industries

Most process hazard analysis (PHA) studies today are conducted using traditional methods such as the hazard and operability study (HAZOP). Traditional methods are based on a chain-of-events model of accident causality. Current models of accident causality are based on systems theory and provide a more complete representation of the causal factors involved in accidents. Consequently, it is logical to expect that PHA methods should reflect these models, that is, system-theoretic hazard analysis (STHA) should be used. Indeed, system-theoretic process analysis (STPA) has been developed as such a method. STPA has been used in a variety of industries but, at this time, it has not gained acceptance by the process industries. This article explores the reasons for this situation. Expectations for PHA in the process industries are examined and issues for the application of STPA in the process industries are discussed. It is concluded that a variety of matters must be addressed before STPA can be considered as a viable PHA method for the process industries and the case for the use of STHA in the process industries is not yet proven.     

高效复合菌在木薯酒精废液处理中的应用研究

对酒精废液生物处理反应器内颗粒污泥中的微生物进行分离纯化.分离出的8株高效优势菌,初步鉴定结果:1号为皮杆菌属;2号为棒杆菌属;3号、4号为微小杆菌属;5号为乳杆菌属;6号为纤维单胞菌属;7号为丙酸杆菌属;8号为红长命菌属.对8种纯化后的菌株进行混合培养,确定了复合菌群生长最佳培养温度为37℃,最适pH值为6.8.在处理过程中投加适量葡萄糖、硝酸铵和微量元素能够提高复合菌群的处理效果.最佳添加量为:葡萄糖0.5g/L,硝酸铵1g/L,Fe2 5mg/L和Ca2 25mg/L.在日处理量100 m3的UASB生物反应器中投加该复合菌群后,木薯酒精废液的COD去除率明显提高,达到90%以上.处理系统运行稳定.     

基于模糊聚类关联分析法的煤与瓦斯突出程度分析

运用模糊聚类分析方法对煤与瓦斯突出的样本集合进行分类,建立了不同突出程度的模糊模式.用关联分析确定待分析样本与模式的关联程度,以此预测预报样本的煤与瓦斯突出危险程度.实例分析表明,与模糊聚类分类后、将模式与待预报样本组成新样本集合进行聚类分析并以此分类结果进行预报的方法相比,这种预报方法不仅可靠程度高,而且能定量描述待报样本与模式的亲和程度.