建筑火灾风险评价体系的建立与应用探讨

探讨基于安全系统工程思想的建筑火灾风险评价指标体系的建立方法,并在该基础上,通过专家打分和层次分析法,计算得出各指标因子的权重值。根据有关标准和规范,对各评价指标因子进行等级划分,并设计出建筑火灾风险综合分值评分表,为厘定火灾保险费率提供依据。笔者的研究成果为完善建筑火灾风险评价方法、制定财产保险火灾风险评价标准等提供了科学依据。     

公共场所火灾伤员转运护理应急资源评估

为保障伤员生命与健康,提升火灾伤员救治率,该文研究公共场所火灾伤员转运护理应急资源评估方法.以火灾伤员转运护理应急资源需求分析为基础,从应急人员、应急设备、应急环境信息与应急管理四个方面出发,共选取15个评估指标,构建公共场所火灾伤员转运护理应急资源评估指标体系,根据各指标采集相关数据并对数据实施量纲标准化处理.构建基...     

喻家湖水质时空分布特征和影响因子分析

通过设计合理的水质监测网,采用多元统计分析,并结合地理信息技术对武汉市喻家湖在2011年-2012年期间12个监测点、13个水质参数监测值进行水质时空分布特征研究.结果表明,喻家湖13个水质指标概括为4个主成分:第一主成分代表喻家湖的重金属污染,第二主成分代表其富营养化水平,第三主成分代表有机污染程度,第四主成分间接指示富营养化程度;在时间和空间变化上都可分为二组,显著性指标的时空差异较明显,水质污染程度从南至北逐渐减弱,湖溪河是喻家湖的最主要污染源.并对水质参数,监测点位和频次进行了优化.     

基于熵权综合健康指数法的瀛湖水生态系统健康评估

瀛湖是南水北调丹江口水库重要的水源涵养区,承担着丹江口水库60%的供水量,又是沿线乡镇和安康市城区饮用水水源地。在充分调查的基础上,采用综合健康指数法对1986—2012年之间瀛湖的水生态系统健康状况进行了评估,结果表明,1986—2005年,瀛湖水生态系统健康指数呈逐渐下降趋势,健康状态由健康降至一般病态;2005—2012年之间,瀛湖水生态系统健康指数总体呈上升趋势,健康状态除2010年为一般病态外,其余均为亚健康状态。     

基于熵权TOPSIS模型的土地利用多功能性诊断

从经济、社会和生态3个方面出发构建土地利用多功能性评价指标体系,应用熵权TOPSIS模型对江苏省近年来土地利用多功能性进行诊断分析可以优化区域土地的合理开发,提高土地利用效率,为促进区域的可持续发展提供有效依据。研究结果表明：2006~2016年江苏省土地利用综合功能经历了一般—良好的发展阶段,综合功能在不断优化;经济功能经历了较差—一般—良好—优秀—良好的发展阶段,虽然有所波动,但其依旧呈增长态势;社会功能经历了较差—一般—良好—优秀的发展阶段,呈现出持续稳步提高趋势;生态功能经历了一般—良好—一般的发展趋势,整体呈下降趋势。另外土地利用的经济功能和社会功能子目标的障碍度在逐年下降,对目前江苏省土地利用有效性起制约作用的主要是生态功能,应减少废水排放和工业固体废弃物等污染造成的生态破坏,加强水资源的保护,同时缩小城乡差距,推进城乡融合,促进土地利用过程中经济、社会和生态功能的协调发展。     

Validation of the Polish version of the World Health Organization Disability Assessment Schedule (WHODAS 2.0) in an elderly population (60–70 years old)

Purpose. To assess the reliability and validity of the Polish version of the 36-point World Health Organization Disability Assessment Schedule (WHODAS 2.0) in an elderly population. Method. One thousand randomly selected individuals, aged 60–70 years, living in south-eastern Poland were assessed using the Polish version of the WHODAS 2.0. Results. The analysis confirmed the high reliability and validity of the tool. Cronbach’s α index was 0.89. The tool had high stability, and the correlation between test and retest results was high. The relevance of the domain selection was high or very high. A factor analysis confirmed the relevance of assigning questions to domains. High theoretical relevance was also demonstrated. Statistically significant differences between those who were and were not suffering from health problems were observed. An analysis of the internal structure of the WHODAS 2.0 revealed strong correlations between the components of each domain and the final result. Conclusion. The Polish version of the WHODAS 2.0 showed high reliability and validity; thus, it can be used to assess health, functioning and disability in the elderly population of Poland.     

电气伤亡事故的主客体场景指标设计及统计规律

为合理预防控制电气伤亡事故的发生提供依据,通过检索查阅国内外相关文献和政府网站公布的电气伤亡事故和案例情况描述,选取105起典型电气伤亡事故案例进行统计与分析;针对电气伤亡事故涉及的主客体场景要素,对其进行筛选、分类、排序及指标设计,形成系统的电气伤亡事故指标体系;结合现实情况对统计结果进行原因分析,根据统计结果,得到电气伤亡事故发生的一般规律,据此提出安全管理中需要关注与重视之处,以此来预防电气伤亡事故的发生。     

基于统计方法的辽东湾沉积物中多环芳烃来源特征分析

为研究辽东湾表层沉积物中多环芳烃(PAHs)的来源特征,2014年5月采集了20个辽东湾海域表层沉积物样品,并利用气相色谱质谱联用仪对优先控制的16种PAHs进行测定,采用聚类分析、主成分分析-多元线性回归分析、异构体比值3种统计方法对辽东湾表层沉积物中PAHs来源特征进行了研究。结果表明,辽东湾表层沉积物中PAHs含量范围88.5~199.3 ng·g-1,平均值为(126.3±35.3)ng·g-1,其中,萘、菲和荧蒽是PAHs优势组分。通过统计分析结果表明,辽东湾北部表层沉积物中PAHs含量低于西南部,沉积物中PAHs的来源包括石油燃烧来源、煤炭、木材等生物质燃烧来源和石油来源,其中燃烧来源是主要来源,煤炭、木材等生物质燃烧来源占49.9%,石油燃烧来源和石油来源占50.1%。     

基于AHP的可听噪声影响因素权值分析

影响超高压输电线路可听噪声的因素众多,对影响可听噪声的因素进行合理分析确定其对可听噪声影响的权重是进行可听噪声预测和合理有效降低可听噪声的前提。对影响可听噪声的因素进行分析并运用层次分析法（AnalyticHierarchyProcess,AHP）对影响可听噪声的主要因素进行加权分析,以定量的形式确定影响因素的相对重要度。结果表明,应用层次分析法确定的可听噪声影响因素权重符合实际,准确性较高,为可听噪声选择主要影响因素用于预测及有效降低可听噪声提供参考依据。     

Using multivariate regression modeling for sampling and predicting chemical characteristics of mixed waste in old landfills

Municipal solid waste landfills pose a threat on environment and human health, especially old landfills which lack facilities for collection and treatment of landfill gas and leachate. Consequently, missing information about emission flows prevent site-specific environmental risk assessments. To overcome this gap, the combination of waste sampling and analysis with statistical modeling is one option for estimating present and future emission potentials. Optimizing the tradeoff between investigation costs and reliable results requires knowledge about both: the number of samples to be taken and variables to be analyzed.This article aims to identify the optimized number of waste samples and variables in order to predict a larger set of variables. Therefore, we introduce a multivariate linear regression model and tested the applicability by usage of two case studies. Landfill A was used to set up and calibrate the model based on 50 waste samples and twelve variables. The calibrated model was applied to Landfill B including 36 waste samples and twelve variables with four predictor variables.The case study results are twofold: first, the reliable and accurate prediction of the twelve variables can be achieved with the knowledge of four predictor variables (Loi, EC, pH and Cl). For the second Landfill B, only ten full measurements would be needed for a reliable prediction of most response variables. The four predictor variables would exhibit comparably low analytical costs in comparison to the full set of measurements. This cost reduction could be used to increase the number of samples yielding an improved understanding of the spatial waste heterogeneity in landfills.Concluding, the future application of the developed model potentially improves the reliability of predicted emission potentials. The model could become a standard screening tool for old landfills if its applicability and reliability would be tested in additional case studies.