城市老工业区土壤重金属污染状况与健康风险评价

本文对西部某老工业区土壤中As、Pb、Cr、Cd、Hg、Zn的含量、空间分布状况展开了研究,并依据《污染场地风险评估技术导则》对该老工业区的健康风险进行了评价。研究结果表明,该老工业区土壤重金属污染严重,6种元素与陕西土壤背景值相比超标100%,表明其不适宜作为居住用地开发。健康风险评价结果显示,As、Pb、Cr、Cd元素的非致癌风险值分别为3.83、1.7、1.94、1.09,均超过非致癌风险可接受值1,表明该老工业区对人们存在非致癌健康风险;对于致癌风险,As、Cr、Cd元素的致癌风险值远大于致癌风险边界值,分别超过致癌风险值的2个数量级(2.64×10-4)、4个数量级(1.94×10-2)、1个数量级(6.12×10-5),表示As和Cr已经达到了显著致癌风险的水平。     

石英砂加工企业职业病危害防护措施与管理对策研究

通过对安徽省石英砂加工企业生产工艺流程和现场进行调查分析,得出矽尘和噪声是两种最主要的职业病危害因素,发现石英砂生产企业矽尘和噪声危害十分严重,生产作业现场未配备任何防护装备和个人防护用品,作业人员接触职业病危害的比率非常高。分析了石英砂加工企业在职业病危害防护与管理方面的欠缺与不足,提出了针对矽尘和噪声危害因素的具体工程防护措施与管理对策,从源头控制和消除职业病危害,保护劳动者的生命安全与健康。     

饮用水中氧化性物质的危害及处理技术研究进展

氧化性物质作为饮用水中一种特殊污染物已对人体健康产生了危害,如何有效地去除这些物质迫在眉睫。对水中氧化性物质的产生、危害及其处理技术进行总结,详述了物化处理和氢自养生物还原处理技术的原理、特点及国内外的研究进展。     

基于粗糙集理论的危险品运输风险分析

为解决危险品风险分析问题,利用粗糙集理论在处理不确定、不精确问题上的优势,提出基于粗糙集理论的危险品运输风险分析方法。首先,建立决策表,经化简后获得各属性的重要度,识别出影响危险品运输的主要因素与次要因素,以及主次因素所占比例;然后,利用区分函数对决策表进行约简,得出决策表的属性约简;最后,利用决策表的决策规则对原始数据进行推导,得出危险品运输事故的一般规律。结果表明,影响危险品运输事故类型的最重要因素是危险品的类型,所占比重为42.86%,其次是危险品运输的道路状况与危险品运输车辆状况,各占28.57%。在道路状况欠佳且车辆状况良好的前提下,腐蚀品发生危险品事故的严重程度要依次高于毒害品与压缩气体和液化气体。     

高速公路交通流实时安全性评价

根据多条高速公路近3年的事故数据及实时交通流数据,分析了高速公路运营安全性的相关影响因素,在此基础上提出了车速变异系数指标及其分级标准,建立了考虑交通流量、平均车速、车速变异系数、天气条件等多因素的高速公路交通流运行风险预测多元模型,并提出了高速公路交通流实时行车风险指数TRI指标,制定了交通流状态实时安全性评价标准,最后给出了高速公路交通流混合交通状态下的实时安全风险评价流程。通过西攀高速公路的交通流实时数据,验证了模型的有效性。     

火灾探测报警系统失效风险评估

火灾探测报警系统的可靠程度,直接影响消防系统控制火灾蔓延和保护人民生命财产安全的能力,对系统进行失效风险评估是检验火灾探测报警系统可靠性的有效方法。先采用故障树分析法对火灾探测报警系统的失效风险进行分析,得出影响火灾探测报警系统失效的底事件;再利用模糊综合评价法和重要度算法得到各底事件的失效概率和权重,并给出火灾探测报警系统失效风险计算步骤;以沈阳航空航天大学图书馆火灾探测报警系统为例,评价该系统不失效的概率为0.795 0,不易失效的概率为0.144 1,较易失效的概率为0.0608,易失效的概率为0,然后根据模糊评价的最大隶属度原则,确定评估结果为该系统不失效。     

石油化工企业环境风险分级评价指标体系研究

在现有研究基础上,从石化行业环境风险特点与现状着手,针对现有环境风险分级评价体系无法适应我国当前石化行业环境风险现状这一问题,对石化企业环境风险要素进行了梳理和分析.以此为基础从突发性环境风险、非突发性环境风险和选址敏感性三方面入手选取了石化企业环境风险分级评价指标,对各指标的含义及量化方法进行了分析,构建了石化企业环境风险分级评价指标体系.利用层次分析法确定体系指标权重,利用专家评分法对评价指标进行赋分,能够准确反映石化企业环境风险的实际情况.以天津滨海新区某石油化工企业为案例,验证了评价指标体系的有效性.     

河南省武陟县大田土壤重金属形态分布及潜在生态风险评价

为了解河南省武陟县大田土壤重金属Cr、Cd、Pb、As、Cu、Se、Ni和Co的形态分布和生态风险情况,在该区域采集了12个表层土壤(0～20cm)样品,采用修正的BCR连续提取法进行形态分析,探讨其生物有效性,并采用Hakanson指数法评价了重金属的潜在生态风险.结果表明,土壤中不同重金属的形态分布差异很大,其中,Cr、As、Ni和Co均主要以残渣态存在,分别占其总量的66.6％、61.4％、50.7％和41.8％;Cu和Se主要以可氧化态存在,分别占其总量的43.8％和67.8％;Pb主要以可还原态存在,占总量的61.1％;Cd主要以酸提取态存在,占总量的53.3％.生物有效性分析表明,Cd的可利用态K1为0.933,生物有效性是最大的,对土壤生态系统的潜在危害性较大,其次是Pb和Co;Cu和Se在土壤环境发生变化时,很容易再次释放到外界环境中;Cr、As和Ni不易被外界生物利用.潜在生态风险评价结果显示,以国家土壤环境质量标准二级标准为参比值时,Cr、Cd、Pb、As、Cu和Ni的单项潜在生态风险程度均为轻微,综合潜在生态风险处于轻微等级.     

Estimated Injury Risk for Specific Injuries and Body Regions in Frontal Motor Vehicle Crashes

Objective: Injury risk curves estimate motor vehicle crash (MVC) occupant injury risk from vehicle, crash, and/or occupant factors. Many vehicles are equipped with event data recorders (EDRs) that collect data including the crash speed and restraint status during a MVC. This study's goal was to use regulation-required data elements for EDRs to compute occupant injury risk for (1) specific injuries and (2) specific body regions in frontal MVCs from weighted NASS-CDS data.

Methods: Logistic regression analysis of NASS-CDS single-impact frontal MVCs involving front seat occupants with frontal airbag deployment was used to produce 23 risk curves for specific injuries and 17 risk curves for Abbreviated Injury Scale (AIS) 2+ to 5+ body region injuries. Risk curves were produced for the following body regions: head and thorax (AIS 2+, 3+, 4+, 5+), face (AIS 2+), abdomen, spine, upper extremity, and lower extremity (AIS 2+, 3+). Injury risk with 95% confidence intervals was estimated for 15–105 km/h longitudinal delta-Vs and belt status was adjusted for as a covariate.

Results: Overall, belted occupants had lower estimated risks compared to unbelted occupants and the risk of injury increased as longitudinal delta-V increased. Belt status was a significant predictor for 13 specific injuries and all body region injuries with the exception of AIS 2+ and 3+ spine injuries. Specific injuries and body region injuries that occurred more frequently in NASS-CDS also tended to carry higher risks when evaluated at a 56 km/h longitudinal delta-V. In the belted population, injury risks that ranked in the top 33% included 4 upper extremity fractures (ulna, radius, clavicle, carpus/metacarpus), 2 lower extremity fractures (fibula, metatarsal/tarsal), and a knee sprain (2.4–4.6% risk). Unbelted injury risks ranked in the top 33% included 4 lower extremity fractures (femur, fibula, metatarsal/tarsal, patella), 2 head injuries with less than one hour or unspecified prior unconsciousness, and a lung contusion (4.6–9.9% risk). The 6 body region curves with the highest risks were for AIS 2+ lower extremity, upper extremity, thorax, and head injury and AIS 3+ lower extremity and thorax injury (15.9–43.8% risk).

Conclusions: These injury risk curves can be implemented into advanced automatic crash notification (AACN) algorithms that utilize vehicle EDR measurements to predict occupant injury immediately following a MVC. Through integration with AACN, these injury risk curves can provide emergency medical services (EMS) and other patient care providers with information on suspected occupant injuries to improve injury detection and patient triage.     

Lower Leg Injury Reference Values and Risk Curves from Survival Analysis for Male and Female Dummies: Meta-analysis of Postmortem Human Subject Tests

Objective: Derive lower leg injury risk functions using survival analysis and determine injury reference values (IRV) applicable to human mid-size male and small-size female anthropometries by conducting a meta-analysis of experimental data from different studies under axial impact loading to the foot–ankle–leg complex.

Methods: Specimen-specific dynamic peak force, age, total body mass, and injury data were obtained from tests conducted by applying the external load to the dorsal surface of the foot of postmortem human subject (PMHS) foot–ankle–leg preparations. Calcaneus and/or tibia injuries, alone or in combination and with/without involvement of adjacent articular complexes, were included in the injury group. Injury and noninjury tests were included. Maximum axial loads recorded by a load cell attached to the proximal end of the preparation were used. Data were analyzed by treating force as the primary variable. Age was considered as the covariate. Data were censored based on the number of tests conducted on each specimen and whether it remained intact or sustained injury; that is, right, left, and interval censoring. The best fits from different distributions were based on the Akaike information criterion; mean and plus and minus 95% confidence intervals were obtained; and normalized confidence interval sizes (quality indices) were determined at 5, 10, 25, and 50% risk levels. The normalization was based on the mean curve. Using human-equivalent age as 45 years, data were normalized and risk curves were developed for the 50th and 5th percentile human size of the dummies.

Results: Out of the available 114 tests (76 fracture and 38 no injury) from 5 groups of experiments, survival analysis was carried out using 3 groups consisting of 62 tests (35 fracture and 27 no injury). Peak forces associated with 4 specific risk levels at 25, 45, and 65 years of age are given along with probability curves (mean and plus and minus 95% confidence intervals) for PMHS and normalized data applicable to male and female dummies. Quality indices increased (less tightness-of-fit) with decreasing age and risk level for all age groups and these data are given for all chosen risk levels.

Conclusions: These PMHS-based probability distributions at different ages using information from different groups of researchers constituting the largest body of data can be used as human tolerances to lower leg injury from axial loading. Decreasing quality indices (increasing index value) at lower probabilities suggest the need for additional tests. The anthropometry-specific mid-size male and small-size female mean human risk curves along with plus and minus 95% confidence intervals from survival analysis and associated IRV data can be used as a first step in studies aimed at advancing occupant safety in automotive and other environments.