利用轨迹模式研究上海大气污染的输送来源

利用HYSPLIT4模式和全球资料同化系统(GDAS)气象数据,计算了2010年12月─2011年11月期间抵达上海的气流后向轨迹. 结合聚类方法和上海ρ(SO₂)、ρ(NO₂)、ρ(PM₁₀)数据,分析了各季节不同类型气流轨迹对污染物浓度的影响,利用引入权重因子后的潜在源贡献算法分析了不同季节PM₁₀和NO₂潜在WPSCF(源区分布概率)特征. 结果表明:上海气流输送季节变化特征明显. 冬、春和秋季,上海较易受到来自西北、西南等区域的大陆性气流影响,受沙尘或人为污染排放的影响相对较大,ρ(PM₁₀)、ρ(SO₂)和ρ(NO₂)平均值相对较高,分别为162、74和53μg/m3. 夏季上海主要受较清洁的海洋性气流影响,ρ(PM₁₀)、ρ(SO₂)和ρ(NO₂)相对较低,分别为47、19和36μg/m3. 上海PM₁₀和NO₂的WPSCF分布特征类似,在冬、春和秋季,WPSCF高值(0.2~0.4)主要集中在江苏南部,河南、安徽等地的带状区域也有一定贡献,说明这些区域是上海这2种污染物的潜在源区. 夏季WPSCF的分布较为集中,上海以外区域值基本小于0.1,说明外来污染输送的贡献较小.      

Preparing for major terrorist attacks against chemical clusters: Intelligently planning protection measures w.r.t. domino effects

Chemical industrial areas or so-called chemical clusters consist of hundreds, and sometimes thousands, of chemical installations situated next to each other. Such areas can thus be seen as the summation of a large number of structures exhibiting danger to a certain degree for initiating or continuing accident domino effects or knock-on effects. In this article, an approach to investigate in a systemic way the vulnerability of each installation within the larger chemical cluster context, is developed. Our suggested method results in a prioritization of chemical installations with respect to their vulnerability for domino effects. The method can be used for intelligently designed protection of chemical industrial areas against terrorist attacks.     

Temporary disaster debris management site identification using binomial cluster analysis and GIS

An essential component of disaster planning and preparation is the identification and selection of temporary disaster debris management sites (DMS). However, since DMS identification is a complex process involving numerous variable constraints, many regional, county and municipal jurisdictions initiate this process during the post‐disaster response and recovery phases, typically a period of severely stressed resources. Hence, a pre‐disaster approach in identifying the most likely sites based on the number of locational constraints would significantly contribute to disaster debris management planning. As disasters vary in their nature, location and extent, an effective approach must facilitate scalability, flexibility and adaptability to variable local requirements, while also being generalisable to other regions and geographical extents. This study demonstrates the use of binomial cluster analysis in potential DMS identification in a case study conducted in Hamilton County, Indiana.     

Accumulation trends of metals and a metalloid in the freshwater crayfish Astacus leptodactylus from Lake Yeniçağa (Turkey)

This study aims to determine the extent of metal pollution in Lake Yeniça?a (Bolu, Turkey) by investigating the accumulation trends of five metals (Al, Cu, Fe, Ni and Zn) and a metalloid (As) in gills, exoskeleton, hepatopancreas and abdominal muscles of the freshwater crayfish Astacus leptodactylus. Principal component analysis (PCA), cluster analysis (CA), correlation analysis and analysis of variance (ANOVA) were utilised to determine the accumulation profiles of each element over four seasons. The greatest element accumulation was found to occur in the gills. All elements in exoskeletal tissue displayed positive correlations with each other, a similar trend was also observed in the hepatopancreas samples. Strong (r=0.868) and very strong (r=0.960) positive correlations were found between the accumulations of Al and Fe in gills and the exoskeleton, respectively. Correlations in tissue accumulation rates are discussed in the context of metabolic roles and impacts associated with the elements tested. Elemental compositions of Yeniça?a water and sediment samples were also investigated to determine whether the composition of the surrounding environment matches the metal accumulation trends of tissue samples. We demonstrate that, by the criteria set by the United States Environmental Protection Agency, Lake Yeniça?a is heavily polluted in terms of As and Ni.     

Geographical analysis of commercial motor vehicle hazardous materials crashes on the Oregon state highway system

Crashes on highways frequently cause hazardous material exposure to the public and the environment. We evaluated differences in hazardous materials-related crashes vs. non-hazardous-material-related commercial motor vehicle crashes occurring from 2000 to 2006 on the Oregon state highway network. The two groups were compared for crash characteristics by χ² analysis, and spatial clustering was tested using Ripley's K-function and kernel density estimator analyses. There were 8,622 total commercial motor vehicle crashes, 232 being hazardous-materials related. Hazardous materials-related crashes were not significantly associated with different road surface conditions, weather conditions or cause of crash. Hazardous materials-related crashes were associated more frequently with late evening/early morning hours and under artificial lights or at dusk. The commercial motor vehicle drivers in hazardous materials-related crashes were less frequently at fault than ones in the non-hazardous materials-related crashes. The planar Ripley's K-function indicated non-hazardous materials-related crashes were more clustered than hazardous materials-related ones. Both cohorts clustered at the 12–14 mile range. The kernel density estimator analysis indicated hazardous materials-related clusters are small and discrete along the main highway corridors, non-Hazardous materials-related ones seemed to form elongated confluent clusters along all highways. Since there seem to be few differences between the two cohorts in characteristics of the crashes and the frequency of hazardous materials-related crashes is low compared to the total commercial vehicle crashes, future geographical studies may focus on characteristics of all commercial motor vehicle crashes.     

佛山市冬季PM2.5中重金属元素的污染特征

为了解珠江三角洲典型工业城市佛山冬季大气细颗粒物中重金属元素的污染特征,在佛山的城区(禅城)和城市清洁点(三水)同步采集24h PM2.5样品,分析了16种元素Fe、Ti、Zn、V、Mn、Cu、As、Rb、Sr、Cd、Cs、Ba、Hg、Tl、Pb和Bi的浓度.禅城的重金属处于较高的污染水平,三水重金属元素浓度普遍低于禅城,但Fe、Ti、Sr、Cd的浓度高于禅城.与国家大气颗粒物中重金属浓度标准相比,禅城的As、Cd超标严重,Pb略超标,三水的As、Cd超标严重.Zn、Cu、As、Pb的富集因子均高于10,表明其主要与人类活动导致的污染有关.重金属元素的浓度在灰霾期都有增高的趋势,但各重金属浓度日变化趋势和幅度在禅城较为一致,在三水则不太一致.气团后向轨迹分析表明,研究期间重金属元素的浓度分布受靠近或者始于福建的广东东北方向气团、广福沿岸气团、海洋方向气团和来自江西的气团影响,其中第1类气团主要使得重金属元素浓度提高,后面3类气团均使得重金属浓度下降.     

机场热点区域三选法研究

要预防机场活动区内航空器滑错滑行道或跑道,就必须有效、准确地识别机场活动区内可能发生混淆的热点区域。为此,在对比研究德尔菲法和头脑风暴法的基础上,提出矩阵法和模糊聚类分析2种定量研究模型。算例结果表明,矩阵法和模糊聚类分析的结果相互印证。结合德尔菲法、矩阵法和模糊聚类分析的三选法在识别机场热点区域过程中能够减少人为主观偏见,提高准确性和可靠性,识别精度总体优于单一的筛选方法。     

企业火灾疏散人员行为及心理特征研究

为研究生产经营企业火灾情况下人员疏散行为及心理特征,从环境因素、管理因素、人的因素3方面,现场调研182名员工。通过系统聚类分析,获得4个典型因素。根据卡方检验,建立疏散影响因素列联表。从不同企业、性别、年龄、文化程度4方面,分析火灾中个体疏散行为及心理特征。结果表明:火灾中人员的逃生意愿跟学历背景有明显关系,学历越高自我逃生的意愿越强。定期应急演练及日常安全学习,能够促进人员安全疏散。在帮助他人、逃离现场、采取控制措施等方面,女性与男性有明显区别。企业应在日常应急管理中,关注不同学历、性别人员的教育培训,以及应急器材使用和事故控制措施的演练,以提高员工应对火灾事故的能力和信心。     

基于聚类分析的城乡结合部群体性突发事件归类研究

城乡结合部群体性突发事件是影响经济发展、社会稳定的重要根源。为实现对城乡结合部群体性突发事件的归类研究,基于聚类分析理论,探究了我国城乡结合部管理现状以及各类群体性突发事件的原因和具体表现形式,构建了分布聚类模型,利用MATLAB软件生成聚类分析的谱系图,动态模拟了群体性突发事件、原因、表现形式之间的相互关系。研究表明:城乡结合部群体性突发事件基于各类原因呈现不同的表现形式,根据造成群体性突发事件各原因之间的相似度,将城乡结合部群体性突发事件归类为以征地拆迁为主线的经济利益冲突、以执法不当为导向的政治矛盾、以打架斗殴为主要形式的个体冲突、以信访维权等为基础的社会纠纷、以群体竞争为代表的组织斗争。在对城乡结合部群体性突发事件的管理中,根据事件所属的类别,可以制定明确的预警计划,从根本上降低城乡结合部群体性突发事件的发生率,为政府等相关部门的预警管理工作提供借鉴和参考。