Development and evaluation of RAMP I – a practitioner’s tool for screening of musculoskeletal disorder risk factors in manual handling

RAMP I is a screening tool developed to support practitioners in screening for work-related musculoskeletal disorder risk factors related to manual handling. RAMP I, which is part of the RAMP tool, is based on research-based studies combined with expert group judgments. More than 80 practitioners participated in the development of RAMP I. The tool consists of dichotomous assessment items grouped into seven categories. Acceptable reliability was found for a majority of the assessment items for 15 practitioners who were given 1?h of training. The usability evaluation points to RAMP I being usable for screening for musculoskeletal disorder risk factors, i.e., usable for assessing risks, being usable as a decision base, having clear results and that the time needed for an assessment is acceptable. It is concluded that RAMP I is a usable tool for practitioners.     

A hybrid model for human factor analysis in process accidents: FBN-HFACS

Human factors are the largest contributing factors to unsafe operation of the chemical process systems. Conventional methods of human factor assessment are often static, unable to deal with data and model uncertainty, and to consider independencies among failure modes. To overcome the above limitations, this paper presents a hybrid dynamic human factor model considering Human Factor Analysis and Classification System (HFACS), intuitionistic fuzzy set theory, and Bayesian network. The model is tested on accident scenarios which have occurred in a hot tapping operation of a natural gas pipeline. The results demonstrate that poor occupational safety training, failure to implement risk management principles, and ignoring reporting unsafe conditions were the factors that contributed most failures causing accident. The potential risk-based safety measures for preventing similar accidents are discussed. The application of the model confirms its robustness in estimating impact rate (degree) of human factor induced failures, consideration of the conditional dependency, and a dynamic and flexible modelling structure.     

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     

基于蒙特卡罗法的煤巷锚杆支护结构可靠性分析

应用工程结构可靠性理论,建立煤巷锚杆支护结构可靠性模型,针对其结构稳定性的极限状态功能函数高度非线性的特征,采用蒙特卡罗法在Matlab环境下直接产生服从各相应概率分布函数的随机变量数组计算其结构可靠度,编程过程简化,计算速度快,精度高,且不受极限状态方程非线性、随机变量非正态的限制,开辟了煤巷锚杆支护结构可靠度计算的新途径。建立了支护参数与可靠度的关系,指出了提高煤巷锚杆支护结构可靠度的方法和措施,为煤巷锚杆支护参数设计和优化提供了科学依据。     

基于遥感尾气监测的柴油车气态污染物排放因子计算方法研究

采用遥感尾气测试系统实测了柴油车在实际道路工况下的CO、HC和NO排放特征,修正了排放因子的计算方法,并与车载排放测试系统（PEMS）实测结果进行了验证,获得了实测车辆的CO、HC和NO排放因子.测试结果显示,在各种遥感监测的工况下柴油车尾气中均含有较高浓度的氧气,未考虑氧气影响的燃烧方程反演获得的各污染物体积浓度计算值与PEMS实测值的偏差较大,且氧气浓度越大,偏差越大.经过氧气修正的燃烧方程反演计算的尾气浓度与PEMS实测值吻合度大幅提升,适用于实际工况下遥感检测车辆尾气的反演计算.修正算法得到CO、HC和NO的排放因子离散性较小,精确度较高,可以为量化柴油车尾气排放贡献提供科学依据.     

Development of a static test apparatus for evaluating the performance of three PM2.5 separators commonly used in China

PM_(2.5) separator directly affects the accuracy of PM_(2.5) sampling.The specification testing and evaluation for PM_(2.5) separator is particularly important,especially under China's wide variation of terrain and climate.In this study,first a static test apparatus based on polydisperse aerosol was established and calibrated to evaluate the performance of the PM_(2.5) separators.A uniform mixing chamber was developed to make particles mix completely.The aerosol concentration relative standard deviations of three test points at the same horizontal chamber position were less than 0.57%,and the particle size distribution obeyed logarithmic normal distribution with an R~2 of 0.996.The flow rate deviation between the measurement and the set point flow rate agreed to within ± 1.0% in the range of -40 to 50℃.Secondly,the separation,flow and loading characteristics of three cyclone separators(VSCC-A,SCC-A and SCC112) were evaluated using this system.The results showed that the 50% cutoff sizes(D_(50)) of the three cyclones were 2.48,2.47 and 2.44 μm when worked at the manufacturer's recommended flow rates,respectively.The geometric standard deviation(GSD) of the capture efficiency of VSCCA was 1.23,showed a slightly sharper than SCC-A(GSD = 1.27),while the SCC112 did not meet the relevant indicator(GSD = 1.2 ± 0.1) with a GSD = 1.44.The flow rate and loading test had a great effect on D_(50),while the GSD remained almost the same as before.In addition,the maintenance frequency under different air pollution conditions of the cyclones was summarized according to the loading test.     

基于野外原位抽注试验和同位素技术的含水层反硝化速率研究

反硝化作用是地下水硝酸盐污染去除最重要的过程.由于水文地质条件和水文地球化学环境的复杂性和不确定性,精准测定含水层反硝化速率是反硝化过程的研究难点.选取潮白河冲洪积扇中部中国环境科学研究院地下水创新野外基地作为研究区,基于野外原位试验和15N同位素示踪法提出一种含水层反硝化速率的测定方法.该方法综合体现了研究区实际水文地质条件和水文地球化学环境对反硝化作用的影响,并充分考虑了硝酸盐在含水层中稀释弥散作用对计算结果的影响.结果表明:①潮白河冲洪积扇中部某地地下26~28 m处于还原环境,含水介质以粉细砂为主,ρ（NO₃-N）平均值为2.77 mg/L.②地下26~28 m反硝化速率在349.52~562.99 μg/（kg·d）（以N计,下同）之间,平均值为450.31 μg/（kg·d）.通过与研究区含水介质、采样深度和硝酸盐背景值相似的国内外案例对比研究,初步评估结果处于合理区间.③测试结果具有一定不确定性,主要来自忽略中间产物NO₂-和NO的计算方法、扰动采样方法、N₂O的操作规范程度及采样频率等方面.研究方法为测定含水层硝酸盐速率研究提供了新的思路,研究结果可为地下水中硝酸盐转化过程机理研究、地下水硝酸盐污染修复及风险管控提供关键的理论支撑数据.      

基于模糊PI控制的瞬态高温控制策略研究

目的通过地面环境试验研究气动热引起的瞬态高温环境对飞行器结构的影响。方法设计基于石英灯和离心机的瞬态高温-加速度复合试验系统,研究温度和加速度同步控制系统的结构和原理,分析无制冷装置环境下瞬态高温控制的难点,提出基于模糊PI控制器的温度控制策略。结果通过MATLAB仿真验证,设计的模糊PI控制器相比传统的PI控制器能够有效提高温度控制的动态性能与精确性。结论将基于模糊PI控制的瞬态加热控制策略应用于瞬态高温控制是可行、有效的,能为地面气动热模拟环境试验提供技术保障。