知识生产视角下应急管理学科建设的使命与路径

为厘清应急管理学科建设机制、推进应急管理学科良性发展,通过回顾学科建设历史,来分析应急管理学科建设面临的困境与肩负的使命,并提出相应的建设路径.研究表明:在知识生产模式转型视角下,应急管理学科建设面临知识生产者离散、知识创新度不足、知识转化率有限的三重困境,需要完成"朝向人才培养的应急管理知识直接再生产""朝向科学研究...     

Detection of dicofol and related pesticides in human breast milk from China, Korea and Japan

Previously, we demonstrated that the concentrations of DDTs were greater in breast milk collected from Chinese mothers than from Japanese and Korean mothers. To investigate dicofol as a possible source of the DDTs in human breast milk, we collected breast milk samples from 2007 to 2009 in China (Beijing), Korea (Seoul, Busan) and Japan (Sendai, Takarazuka and Takayama). Using these breast milk samples, we quantified the concentrations of dichlorobenzophenone, a pyrolysis product of dicofol (simply referred to as dicofol hereafter), dichlorodiphenyltrichloroethane and its metabolites (DDTs) using GC-MS. Overall, 12 of 14 pooled breast milk samples from 210 mothers contained detectable levels of dicofol (>0.1 ng g⁻¹ lipid). The geometric mean concentration of dicofol in the Japanese breast milk samples was 0.3 ng g⁻¹ lipid and significantly lower than that in Chinese (9.6 ng g⁻¹ lipid) or Korean breast milk samples (1.9 ng g⁻¹ lipid) (p < 0.05 for each). Furthermore, the ΣDDT levels in breast milk from China were 10-fold higher than those from Korea and Japan. The present results strongly suggest the presence of extensive emission sources of both dicofol and DDTs in China. However, exposure to dicofol cannot explain the large exposure of Chinese mothers to DDTs because of the trace levels of dicofol in the ΣDDTs. In the present study, dicofol was confirmed to be detectable in human breast milk. This is the first report to identify dicofol in human samples.     

微波-过氧乙酸联合作用处理剩余污泥的研究

采用微波-过氧乙酸(PAA)联合作用处理剩余污泥,考察了微波辐照时间、微波功率、PAA投加量对剩余污泥分解效果的影响.同时以单独微波作用为对比,考察了微波-PAA联合作用下剩余污泥性质的变化.结果表明,当微波功率为600 W,PAA投加量为0.24 g/g(以干质量SS计)时,微波辐照60 s后剩余污泥分解率可达35%...     

Modeling transit bus fuel consumption on the basis of cycle properties

A method exists to predict heavy-duty vehicle fuel economy and emissions over an "unseen" cycle or during unseen on-road activity on the basis of fuel consumption and emissions data from measured chassis dynamometer test cycles and properties (statistical parameters) of those cycles. No regression is required for the method, which relies solely on the linear association of vehicle performance with cycle properties. This method has been advanced and examined using previously published heavy-duty truck data gathered using the West Virginia University heavy-duty chassis dynamometer with the trucks exercised over limited test cycles. In this study, data were available from a Washington Metropolitan Area Transit Authority emission testing program conducted in 2006. Chassis dynamometer data from two conventional diesel buses, two compressed natural gas buses, and one hybrid diesel bus were evaluated using an expanded driving cycle set of 16 or 17 different driving cycles. Cycle properties and vehicle fuel consumption measurements from three baseline cycles were selected to generate a linear model and then to predict unseen fuel consumption over the remaining 13 or 14 cycles. Average velocity, average positive acceleration, and number of stops per distance were found to be the desired cycle properties for use in the model. The methodology allowed for the prediction of fuel consumption with an average error of 8.5% from vehicles operating on a diverse set of chassis dynamometer cycles on the basis of relatively few experimental measurements. It was found that the data used for prediction should be acquired from a set that must include an idle cycle along with a relatively slow transient cycle and a relatively high speed cycle. The method was also applied to oxides of nitrogen prediction and was found to have less predictive capability than for fuel consumption with an average error of 20.4%.     

Soil contamination of heavy metals in the Katedan Industrial Development Area, Hyderabad, India

Studies on quantitative soil contamination due to heavy metals were carried out in Katedan Industrial Development Area (KIDA), south of Hyderabad, Andhra Pradesh, India under the Indo-Norwegian Institutional Cooperation Programme. The study area falls under a semi-arid type of climate and consists of granites and pegmatite of igneous origin belonging to the Archaean age. There are about 300 industries dealing with dyeing, edible oil production, battery manufacturing, metal plating, chemicals, etc. Most of the industries discharge their untreated effluents either on open land or into ditches. Solid waste from industries is randomly dumped along roads and open grounds. Soil samples were collected throughout the industrial area and from downstream residential areas and were analysed by X-ray Fluorescence Spectrometer for fourteen trace metals and ten major oxides. The analytical data shows very high concentrations of lead, chromium, nickel, zinc, arsenic and cadmium through out the industrial area. The random dumping of hazardous waste in the industrial area could be the main cause of the soil contamination spreading by rainwater and wind. In the residential areas the local dumping is expected to be the main source as it is difficult to foresee that rain and wind can transport the contaminants from the industrial area. If emission to air by the smokestacks is significant, this may contribute to considerable spreading of contaminants like As, Cd and Pb throughout the area. A comparison of the results with the Canadian Soil Quality Guidelines (SQGL) show that most of the industrial area is heavily contaminated by As, Pb and Zn and local areas by Cr, Cu and Ni. The residential area is also contaminated by As and some small areas by Cr, Cu, Pb and Zn. The Cd contamination is detected over large area but it is not exceeding the SQGL value. Natural background values of As and Cr exceed the SQGL values and contribute significantly to the contamination in the residential area. However, the availability is considerably less than anthropogenic contaminants and must therefore be assessed differently. The pre- and post-monsoon sampling over two hydrological cycles in 2002 and 2003 indicate that the As, Cd and Pb contaminants are more mobile and may expect to reach the groundwater. The other contaminants seem to be much more stable. The contamination is especially serious in the industrial area as it is housing a large permanent residing population. The study not only aims at determining the natural background levels of trace elements as a guide for future pollution monitoring but also focuses on the pollution vulnerability of the watershed. A plan of action for remediation is recommended.     

全氟/多氟烷基化合物在水环境中污染现状

文章基于产业结构和经济发展水平,将中国水环境分为6个区域,简述了全氟/多氟烷基化合物(PFASs)物理化学性质,分析了各区域水环境PFASs污染水平、组成特点、来源解析与时空分布特征,将污染程度从高至低排序:东三省>京津冀>长三角>珠三角>华中>华西。基于研究现状,探讨了PFASs水环境中亟待解决的热点问题,对未来的研究聚焦方向提出了如下建议与展望:根据链长度和同分异构体,建立对PFASs污染水平和毒性效应的系统认识;着重关注饮用水PFASs污染水平,以明确评估其人体健康危害;针对PFASs治理手段,进一步研究其实际应用情况。     

水体中塑料助剂迁移值的检测方法

正增塑剂、抗氧化剂、阻燃剂等小分子助剂可以提升塑料的物理化学性能,在制造领域被广泛应用.然而,小分子助剂易迁移至外部环境且化学性质稳定,与生物体接触后,由于其亲脂的特性,易累积产生毒害效应.目前已有采用液液萃取法(LLE)或固相萃取法(SPE),建立了针对邻苯二甲酸酯类和多溴联苯醚类塑料助剂在环境中迁移值的检测方法,但并无一种方法能系统地反应样品中多种小分子助剂的迁移值.本实验选取高分子工业常见且易迁移的1种抗氧化剂、1种阻燃剂、3种传统的增塑剂和1种环保型的增塑剂为测试对象,在LLE法基础上,改良了萃取溶剂和色谱条件.优化后的实验条件操作简便,并成功应用于环境实际样品的分析.     

外源ABA对不同品种辣椒种子萌发的影响

以4种辣椒种子为试验材料,研究了不同浓度ABA(0~100 mg/L)对种子萌发的影响.结果表明:低浓度ABA对种子的发芽势和发芽率没有显著影响,高浓度ABA极显著抑制种子的发芽势和发芽率,辣椒品种(系)不同,种子萌发对ABA浓度的敏感性也不同.不同浓度ABA溶液极显著降低了种子的发芽指数,随着ABA浓度的增加,对发芽指数的抑制程度逐渐加强,种子的发芽起始时间也被推迟,浓度越高,萌发延迟天数越多.ABA溶液极显著抑制种子胚根和胚轴的分化和生长,ABA浓度越高,抑制程度越强.图6,表1,参17.     

碳酸盐鲕粒的成因与鉴别

<正> 一、对碳酸盐鲕粒及其成因的一般认识 在许多化学岩和生物化学岩中,经常见到引人注意的鲕状结构和鲕状构造。前者系对每一鲕粒而言,后者是指由鲕粒组成的岩石构造。 所谓鲕粒,是指具有核心和同心层包壳的凝聚——加积颗粒,多呈球形到椭球形,大小和形态似鱼卵。碳酸盐鲕粒系由碳酸盐矿物组成。其核心可以是