模糊综合评价法在钢铁企业安全投资合理性评价中的应用

为了对钢铁企业安全投资进行模糊综合评价,建立了钢铁企业安全投资的评价体系,确定各因素的权重。得出模糊综合评价矩阵,可对各因素进行评价分析;得出某钢铁企业安全投资现状分数为83.9分,等级为较好,需着重加强安全培训、劳保品、工业卫生等人因素方面的投资;在环境方面的投资较合理。     

Performance assessment system of health,safety and environment based on experts' weights and fuzzy comprehensive evaluation

Performance evaluation of Health, Safety and Environment (HSE) is the measurement of a company's achievement in HSE management. In order to receive a comprehensive and objective evaluation result, it is necessary to consider all evaluation factors and experts at different levels when HSE performance assessment is conducted. To improve conventional HSE performance evaluation, where weighted average method was used, a Fuzzy Comprehensive Evaluation (FCE) method is used in this study by taking experts' weights into account. Further, an HSE operating performance assessment system is designed to simplify manual and complex assessment process and generate charts and analysis reports automatically. Finally, a case of petrochemical enterprise is used to illustrate the effectiveness of the method and system.     

加速溶剂同时萃取和净化-气相色谱-三重四极杆串联质谱测定土壤和沉积物中8种多溴联苯醚

建立了土壤和沉积物中8种多溴联苯醚(PBDEs,BDE-28、BDE-47、BDE-99、BDE-100、BDE-153、BDE-154、BDE-183和BDE-209)加速溶剂同时萃取和净化-气相色谱-三重四极杆串联质谱(ASE-GC-MS-MS)的分析方法。通过优化加速溶剂萃取与弗罗里硅土在线净化和串联质谱多反应监测模式的条件,较好地去除基质干扰,并提高了三重四极杆串联质谱定性的准确性及定量的灵敏性。该方法采用改进的色谱柱能同时分析包括高溴代联苯醚BDE-209在内的8种PBDEs,其浓度范围为1～100 ng/mL(BDE-209为10～1 000 ng/mL),线性良好,线性回归系数均大于0.997。方法检出限为0.004～0.1 ng/g,方法回收率为75%～110%,方法精密度为2.4%～15.6%。适于批量处理土壤和沉积物中含有多组分痕量PBDEs的样品。     

企业安全管理体系标准模式的比较研究

采用对比分析法和实证分析法,对当前国内外流行的企业安全管理体系标准模式及其评价方法进行比较研究,旨在把握诸多标准模式的原则、路径、结构、方法和共性特征及其可以发挥的具体优点,将研究的标准模式的评价方法归纳为两大类即体系认证审核法和综合考评打分法,并对两类评价方法的优缺点进行剖析。体系认证审核法的优点是过程方法、符合性及抽样,考评打分法则提供了安全绩效准则。对吸收融合两类评价方法的优点形成综合性评价方法的途径和方式进行了探讨,为企业建立有效、适用的安全管理体系提供了依据。     

Analysis of the Trend and Seasonal Cycle of Carbon Monoxide Concentrations in an Urban Area (4 pp)

Background, Aim and Scope Air quality is an field of major concern in large cities. This problem has led administrations to introduce plans and regulations to reduce pollutant emissions. The analysis of variations in the concentration of pollutants is useful when evaluating the effectiveness of these plans. However, such an analysis cannot be undertaken using standard statistical techniques, due to the fact that concentrations of atmospheric pollutants often exhibit a lack of normality and are autocorrelated. On the other hand, if long-term trends of any pollutant’s emissions are to be detected, meteorological effects must be removed from the time series analysed, due to their strong masking effects. Materials and Methods The application of statistical methods to analyse temporal variations is illustrated using monthly carbon monoxide (CO) concentrations observed at an urban site. The sampling site is located at a street intersection in central Valencia (Spain) with a high traffic density. Valencia is the third largest city in Spain. It is a typical Mediterranean city in terms of its urban structure and climatology. The sampling site started operation in January 1994 and monitored CO ground level concentrations until February 2002. Its geographic coordinates are W0°22′52″ N39°28′05″ and its altitude is 11 m. Two nonparametric trend tests are applied. One of these is robust against serial correlation with regards to the false rejection rate, when observations have a strong persistence or when the sample size per month is small. A nonparametric analysis of the homogeneity of trends between seasons is also discussed. A multiple linear regression model is used with the transformed data, including the effect of meteorological variables. The method of generalized least squares is applied to estimate the model parameters to take into account the serial dependence of the residuals of this model. This study also assesses temporal changes using the Kolmogorov-Zurbenko (KZ) filter. The KZ filter has been shown to be an effective way to remove the influence of meteorological conditions on O₃ and PM to examine underlying trends. Results The nonparametric tests indicate a decreasing, significant trend in the sampled site. The application of the linear model yields a significant decrease every twelve months of 15.8% for the average monthly CO concentration. The 95% confidence interval for the trend ranges from 13.9% to 17.7%. The seasonal cycle also provides significant results. There are no differences in trends throughout the months. The percentage of CO variance explained by the linear model is 90.3%. The KZ filter separates out long, short-term and seasonal variations in the CO series. The estimated, significant, long-term trend every year results in 10.3% with this method. The 95% confidence interval ranges from 8.8% to 11.9%. This approach explains 89.9% of the CO temporal variations. Discussion The differences between the linear model and KZ filter trend estimations are due to the fact that the KZ filter performs the analysis on the smoothed data rather than the original data. In the KZ filter trend estimation, the effect of meteorological conditions has been removed. The CO short-term componentis attributable to weather and short-term fluctuations in emissions. There is a significant seasonal cycle. This component is a result of changes in the traffic, the yearly meteorological cycle and the interactions between these two factors. There are peaks during the autumn and winter months, which have more traffic density in the sampled site. There is a minimum during the month of August, reflecting the very low level of vehicle emissions which is a direct consequence of the holiday period. Conclusions The significant, decreasing trend implies to a certain extent that the urban environment in the area is improving. This trend results from changes in overall emissions, pollutant transport, climate, policy and economics. It is also due to the effect of introducing reformulated gasoline. The additives enable vehicles to burn fuel with a higher air/fuel ratio, thereby lowering the emission of CO. The KZ filter has been the most effective method to separate the CO series components and to obtain an estimate of the long-term trend due to changes in emissions, removing the effect of meteorological conditions. Recommendations and Perspectives Air quality managers and policy-makers must understand the link between climate and pollutants to select optimal pollutant reduction strategies and avoid exceeding emission directives. This paper analyses eight years of ambient CO data at a site with a high traffic density, and provides results that are useful for decision-making. The assessment of long-term changes in air pollutants to evaluate reduction strategies has to be done while taking into account meteorological variability     

中国可持续社会养老保险的综合评价体系和实证分析

我国可持续社会养老保险的综合评价指标体系包括四个层次和三级子系统，内容涉及养老保险人数、机构设置、基金管理和代际平衡四个子目标。应用因子分析模糊综合评价方法对我国1990-2001年养老保险建设状况进行评价，本文认为基金管理，行政管理和代际失衡是影响我国可持续养老保险发展的主要因素。     

生态型港口综合评价指标体系初探

基于上海市建设生态型城市的长期目标，将港口作为城市生态系统中重要的子系统，对如何建设生态型港口提出了综合评价指标体系。通过筛选得到45项单因素指标，针对不同类型的港区有所分异，整个评价体系分为5个准则层（生态环境、经济效率、污染控制、环境管理、社会评价）和10个因素层（大气/声环境、生物资源、基底质量、经济发展、生产效率、循环经济、污染排放、清洁生产、环保投入、社会参与），并采用AHP（层次分析）法确定了各层次的权重分配。进而根据2005年上海港年均生产状况和2006年上半年的港区环境－资源调查，尝试对上海港7种主要类型（集装箱、件杂货/成品、多用途、干散、粮食港区、液散、客运）的15个港区进行了现状评估。然而，生态港评价系统的指标选取、权重制定、评估级别等实践与完善仍需要多学科和政府职能部门的参与。最后，项目还提出了水生态健康、航道淤积、生态风险、水陆景观等非定量生态港评价因子。     

城市燃气管道事故应急抢修方案的决策分析

通过对近年来的城市燃气管道事故抢险统计数据的分析与研究,管道事故抢险方案的选择存在着很大的主观性和片面性.为了克服应急抢修方案的种种局限,笔者应用模糊综合评判方法建立了城市燃气管道事故应急抢修方案评价选择模型;考虑可靠性、抢修时间、事故损失、抢险费用、社会影响及政治影响等6类影响因素来评判抢修方案的优劣,可以科学合理地选择最佳的管道事故应急抢修方案,达到经济合理、快速可靠的目的;实例验证,评判模型对城市燃气管道事故抢险具有重要的现实意义和参考价值.