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.     

A new leak location method based on leakage acoustic waves for oil and gas pipelines

In order to study a new leak detection and location method for oil and natural gas pipelines based on acoustic waves, the propagation model is established and modified. Firstly, the propagation law in theory is obtained by analyzing the damping impact factors which cause the attenuation. Then, the dominant-energy frequency bands of leakage acoustic waves are obtained through experiments by wavelet transform analysis. Thirdly, the actual propagation model is modified by the correction factor based on the dominant-energy frequency bands. Then a new leak detection and location method is proposed based on the propagation law which is validated by the experiments for oil pipelines. Finally, the conclusions and the method are applied to the gas pipelines in experiments. The results indicate: the modified propagation model can be established by the experimental method; the new leak location method is effective and can be applied to both oil and gas pipelines and it has advantages over the traditional location method based on the velocity and the time difference. Conclusions can be drawn that the new leak detection and location method can effectively and accurately detect and locate the leakages in oil and natural gas pipelines.     

洪涝灾害条件下疏散交通生成预测方法

为有助于有关部门更准确预测洪涝灾害受灾民众的疏散量,结合非集计数据和集计数据的优点,提出分区集计数据的概念,设计了受灾区域分区方法,并通过意向偏好(SP)调查法对我国居民在洪涝条件下疏散交通需求数据进行调查。在此基础上,引入BP神经网络建立基于分区集计数据的疏散交通生成预测模型。利用调查数据进行实证分析发现,所设计方法取得了较好的预测效果,鲁棒性较好,平均相对预测误差仅为1.8%,其预测效果明显优于现有的非集计和整集计模型。     

矿热炉炉壳安装作业危险性分析

为减少事故损失,必须对矿热炉安装施工危险源进行分析。基于此,对矿热炉安装工序中最重要工序炉壳安装应用作业危险性分析进行分析。将炉壳安装作业分成3大部分,用鱼刺图分析方法进行分析,总结出矿热炉炉壳安装中事故发生的主要原因并提出对策措施,以预防和减少事故的发生。     

情感诉求对交通安全广告效果的影响

为检验交通公益广告中情感诉求变化对广告效果的影响,采用试验法操作广告情感诉求类型,使用眼动技术和Go/no-go联想测验(GNAT),通过比较不同效价和唤醒度的情感诉求广告对受众的注意力和内隐态度的影响,评估交通安全广告情感诉求类型的说服效果。研究发现:被试对低唤醒广告文字区的眼动注视时间和注视点个数显著长于/多于对高唤醒广告文字区的注视时间和注视点个数;被试观看高唤醒消极的广告后,正确驾驶行为的积极态度显著下降,而低唤醒消极/高唤醒积极/低唤醒积极的公益广告对于被试的内隐态度的改变没有显著差异。结果表明,高唤醒度积极广告能够提升受众的注意力,而高唤醒度消极广告则会损害受众对正确驾驶行为的内隐态度。     

室内空气和灰尘中全(多)氟烷基化合物的研究进展

全(多)氟烷基化合物(per(poly)fluoroalkyl substances,PFASs)在环境各个介质及人体样品中广泛被检出,近年,在室内空气和灰尘中也普遍发现PFASs.研究表明,室内空气中PFASs的含量普遍高于室外空气,室内空气和灰尘中的PFASs可能是室外空气的污染来源及人体暴露源,因此室内环境中PFASs成为环境领域的又一个研究热点.但目前为止,我国还没有开展室内空气中PFASs的相关研究,室内灰尘中PFASs的研究也相对较少.本文就室内空气和灰尘中PFASs的采样与分析方法、污染现状、来源分析及人体暴露等4个方面进行了综合阐述,以期为我国室内环境中PFASs的研究提供参考.     

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     

Exploring Chemical Variables in Ligustrum lucidum Ait. F. Tricolor (Rehd.) Rehd. in Relation to Air Pollutants and Environmental Conditions

Ligustrum lucidum Ait. f. tricolor (Rehd.) Rehd. in relation to atmospheric pollutants in Córdoba city, Argentina. The study area receives regional pollutants and was categorized taking into account traffic level, industrial density, type of industry, location of the sample point in relation to the street corner, treeless condition, and topographic level. Dried weight/fresh weight ratio (DW/FW) and specific leaf area (SLA) were calculated, and concentrations of chlorophylls, carotenoids, total sulfur, soluble proteins, malondialdehyde (MDA), and hydroperoxy conjugated dienes (HPCD) were determined in leaf samples. Sulfur content correlates positively with traffic density and SLA correlates negatively with some combinations of the categorical variables; MDA correlates positively with topographic level and total protein concentration correlates negatively with treeless condition. On the basis of our results, traffic, location of trees, type of industry, situation of a tree with respect to others, and topographic level are the environmental variables to bear in mind when selecting analogous sampling points in a passive monitoring program. An approximation to predict tree injury may be obtained by measuring DW/FW ratio, proteins, pigments, HPCD, and MDA as they are responsible for the major variability of data.     

Physicochemical aspects of using natural scavengers in removing methylene blue (basic dye) from solution

Effluent from dyeing and finishing processes is an important source of water pollution. The effectiveness of bentonite, kaolinite and sediment from a local deposit in removing methylene blue as a cationic dye from aqueous solutions has been investigated. The adsorption equilibrium (isotherm) has been determined according to Freundlich and Langmuir equations. The optimum amount is 0.5 g for all adsorbents, and the optimum pH ranges are 2-8 for bentonite and 2-6 for kaolinite and sediment. With respect to kinetic modelling, the adsorption of methylene blue on various adsorbents was fitted to a second-order equation. Also, the thermodynamic parameters were determined. The negative free energy values indicate the feasibility of the process and spontaneous nature of adsorption. The positive ΔH° values indicate the endothermic nature of the process. Thus, Egyptian clay minerals and sediments have a great tendency to remove the dye from solutions.