Risk assessment tools incorporating human error probabilities in the Japanese small-sized establishment

Although it has been estimated that as many as 80% of all occupational accidents have human errors as a cause, no risk assessment tools incorporating human-related elements have been developed for small companies. Human error probability (HEP) and human error analysis (HEA) have been used for large-scale, safety-critical industries for last three decades, but these tools are not suitable for smaller, more general industries that comprise the majority of accident settings.Here, we describe and verify a risk assessment tool that includes human-related elements for small companies. The tool expands on traditional risk assessment methods, such as matrix, risk graph and numerical scoring method, by adding human-related elements. The tool is easy-to-use in occupational environments, and includes assessments of human behavior and potentially outdated machinery at work place.     

Pilot sample risk analysis for underground coal mine fires and explosions using MSHA citation data

After three decades of sustained continuous improvement of mine safety performances in the US, mine disasters in 2006 and 2007 compromised an excellent record and presented new challenges and vulnerabilities for the underground coal mining industry. In the aftermath of the incidents, formal investigations and new scrutiny of mine safety by the US Congress and expert study groups followed. The US Congress passed the Mine Improvement and New Emergency Response Act of 2006 (MINER Act), which mandated new laws to address the issues, including those related to mine fires and explosions from which miners must be protected. The National Mining Association-sponsored Mine Safety Technology and Training Commission report highlighted the role of risk analysis and management in identifying and controlling major hazards, such as fires and explosions. In this paper an approach is given for analyzing the risks for fires and explosions based on the Mine Safety and Health Administration citation database. Using 2006 citation data and focusing on subsystem failures, the methodology is applied to a database for a pilot sample of underground coal mines stratified by mine size and state.     

Process design optimization and risk analysis

Hazard identification and risk assessment are key aspects in process plant design. They are often applied in the final stages of the process at whatever the cost, unless financial constraints are imposed. However, a much better solution would be to introduce risk analysis earlier by including it in earlier stages of the design process, such as when the cost of a plant and the cost of any accidents that may occur are estimated. In this paper, an optimization methodology is proposed, in which both cost and risk (with a deterministic approach) are taken into account, to improve on the current situation. If a decision variable is chosen, an objective function will be established that makes it possible to analyze variations in overall costs, including the cost of the investment and the cost of accidents. This leads to an optimum situation in which costs are kept to a minimum. Of course, this optimization is subject to constraints, the greatest of which is the fact that risk must not exceed tolerated threshold levels. The procedure is explained and two examples, one involving a toxic release and the other a BLEVE/fireball, are used to illustrate it.     

基于信息熵评价决策模型的突发公共事件应急处置指挥方案优选

提出基于信息熵评价决策模型对突发公共事件应急处置指挥决策中的作战方案进行优选的方法。首先介绍应急处置指挥决策的概念和过程;其次,分析了信息熵以及基于信息熵评价模型的多属性决策方法;最后,给出基于信息熵的评价决策模型在突发公共事件应急处置指挥方案优选中的应用。实地演练表明,该决策模型在应急指挥决策方案排序与优选是客观合理、切实可行的,能够为应急处置指挥决策提供一定的参考。     

信息可视化在化工企业水环境安全影响评价中的研究及应用

运用data system.exe技术,对水环境评价系统功能模块进行设计;提出水环境影响评价信息可视化软件的设计方法;建立水环境污染因子数据信息可视化软件,并应用该软件对石油化工企业的水环境进行了初步的风险评价。结果表明:该软件能在识别污染因子数据信息的同时生成与之相匹配的直观的模拟环境图像,有助于管理者进行及时分析与决策;通过输入水环境污染因子监测值后,系统可以自动判定环境的污染的程度,并把对应环境质量的级别、环境的安全程度以及污染对人体与生物的影响程度在图中显示出来,能够有效地提高环境影响评价的可靠度;评价示意图中的评价因子可以根据需要进行增加或更换,有助于该系统的推广应用,建立的环境污染因子数据信息可视化模型具有很强的适用性。     

我国危险化学品安全监管网络整合研究

分析我国危险化学品安全监管网络的特征,指出安全监管网络中存在的法律法规、监管部门信息共享、合作协调机制等方面存在的突出问题,提出了我国危险化学品安全监管网络整合的主要对策,包括建立监管部门之间的常态合作协调机制、无缝隙化城市安全监管平台以及跨区域合作监管机制。危险化学品安全监管网络整合,对提高我国危险化学品监管水平具有重要意义。     

Monitoring urban growth and detecting land-cover changes on the Istanbul metropolitan area

Istanbul is the most populated city of Turkey with a population of around 10.58 M (2000) living on around 5,750 km². In 1980, the population was only 4.7 M and then it has been more than doubled in only two decades. The population has been increasing as a result of mass immigration. An urbanization process continues and it causes serious increases in urban areas while decreasing the amount of green areas. This rapid, uncontrolled, and illegal urbanization accompanied by insufficient infrastructure has caused degradation of forest and barren lands in the metropolitan area, especially through the last two decades. The watershed basins inside the metropolitan area and the transportation network have accelerated the land-cover changes, which have negative impacts on water quality of the basins. Monitoring urban growth and land cover change will enable better management of this complex urban area by the Greater Istanbul Metropolitan Municipality (GIMM). A temporal assessment of land-cover changes of Istanbul has been documented in this study. The study mainly focuses on the acquisition and analysis of Landsat TM and Landsat GeoCover LC satellite images reflecting the significant land-cover changes between the years of 1990 and 2005. Raster data were converted to vector data and used in Geographic Information Systems (GIS). A database was created for Istanbul metropolitan area to plan, manage, and utilize statistical attribute data covering population, water, forest, industry, and topographic position. Consequently an overlay analysis was carried out and land use/cover changes through years have been detected for the case study area. The capability of Landsat images in determining the alterations in the macro form of the city are also discussed.     

Using Multi-Scale Sampling and Spatial Cross-Correlation to Investigate Patterns of Plant Species Richness

Land managers need better techniques to assess exoticplant invasions. We used the cross-correlationstatistic, I _YZ, to test for the presence ofspatial cross-correlation between pair-wisecombinations of soil characteristics, topographicvariables, plant species richness, and cover ofvascular plants in a 754 ha study site in RockyMountain National Park, Colorado, U.S.A. Using 25 largeplots (1000 m²) in five vegetation types, 8 of 12variables showed significant spatial cross-correlationwith at least one other variable, while 6 of 12variables showed significant spatial auto-correlation. Elevation and slope showed significant spatialcross-correlation with all variables except percentcover of native and exotic species. Percent cover ofnative species had significant spatialcross-correlations with soil variables, but not withexotic species. This was probably because of thepatchy distributions of vegetation types in the studyarea. At a finer resolution, using data from ten1 m² subplots within each of the 1000 m² plots, allvariables showed significant spatial auto- andcross-correlation. Large-plot sampling was moreaffected by topographic factors than speciesdistribution patterns, while with finer resolutionsampling, the opposite was true. However, thestatistically and biologically significant spatialcorrelation of native and exotic species could only bedetected with finer resolution sampling. We foundexotic plant species invading areas with high nativeplant richness and cover, and in fertile soils high innitrogen, silt, and clay. Spatial auto- andcross-correlation statistics, along with theintegration of remotely sensed data and geographicinformation systems, are powerful new tools forevaluating the patterns and distribution of native andexotic plant species in relation to landscape structure.     

Finding threatened forest areas in the central volcanic mountain range conservation area in Costa Rica

The degree at which tropical forests are exposed to human pressure is spatially dependent. Population density, proximity to roads, terrain slope, logging activities and land distribution projects are well known factors inducing deforestation and forest degradation in Latin America. Using expert knowledge to weight these threat factors and a Geographical Information System for spatial modeling, a multi-criteria analysis procedure is presented, that allows stratifying a study region in categories of deforestation threat. The procedure was implemented in the Central Volcanic Mountain Range Conservation Area (CVMRCA) in Costa Rica with the purpose of finding areas with a combination of physical and socioeconomic characteristics that is particularly predisposing to a high probability of deforestation. To validate the map, the CVMRCA was stratified in categories of deforestation risk, and the result was superposed to historical deforestation data of the period 1986–1996. The good correlation between risk category and historical deforestation (r = 0.91, p < 0.001) indicates that the map can be used as a decision support tool for defining priority areas for conservation action.     

A Sensitivity Analysis of an Integrated Modelling Approach to Assess the Risk of Wind-borne Spread of Foot-and-mouth Disease Virus from Infected Premises

The sensitivity of an integrated model to assess the potential for wind-borne spread of foot-and-mouth disease (FMD) to variations in key parameters controlling different physical and biological processes was evaluated. The estimated number of farms at risk is sensitive to the virus strain used and the accompanying effective contact rate. The C Noville strain increased the estimated number of exposed farms ranked as high and medium risk of being infected by a factor of 5, compared to the baseline, based on the O UKG 2001 strain. The inclusion of a model for biological ageing of the virus can also have a significant effect on the concentration patterns arising from transport and dispersion of the virus. Its inclusion has the practical advantage of markedly reducing the time required for the calculations. The estimated number of farms affected by exposure to high and medium virus concentrations is not grossly sensitive to attenuation caused by temperature or relative humidity effects. Changes in susceptibility to infection, as determined by the parameter θ in the exposure-risk model, does not change the configuration of the virus plumes, but it does change the distribution of farms at risk by risk category. These findings suggest that a good understanding of characteristics (excretion rates from infected animals, susceptibility of different species to infection, virus survival, etc.) of the virus strain involved in an FMD outbreak is necessary to provide a reliable assessment of the risk of wind-borne spread. In the event of an incursion of FMD, provision for laboratory studies on the virus will be an essential component of the disease response and should be factored into contingency plans.