城市土地置换过程中土壤有机污染物健康影响度评价

城市化过程中日益严峻的土壤污染已成为制约城市土地可持续开发利用的主要因素,而有机物已成为土壤中重要的污染物. 在我国目前缺乏相关环境质量标准的背景下,选择某区域土地置换开发为案例,尝试采用人体健康影响度评价法,对城市土地置换中土壤有机污染物可能给未来入住人群健康带来的潜在危害进行了分析与定量评价,识别出该区域土壤有机污染物以2,4-二硝基酚、五氯酚以及PAHs为主. 需要指出的是,参与评价的有机污染物仅为被检出有机污染物总量的一部分,因此评价结果中的健康影响度可能较实际数值偏低. 随着环境管理工作的深入进行,在城市土地置换过程中应逐步加强环境健康风险评价的研究.       

基于Logistic的不同车型碰撞行人事故严重程度致因分析

为定量分析不同车型碰撞行人事故严重程度影响因素,以美国北卡罗来纳州2007-2016年人车碰撞事故数据为样本,将其分为小轿车、SUV、货车碰撞行人事故3类,以事故严重程度为因变量,交通参与者属性、道路、环境条件和事故特征为候选自变量,分别建立累计logistic模型进行对比分析,探究人、车、路和环境因素对人车碰撞事故严...     

Analysis of risk factors affecting driver injury and crash injury with drivers under the influence of alcohol (DUI) and non-DUI

Objective: The objective of this research was to study risk factors that significantly influence the severity of crashes for drivers both under and not under the influence of alcohol.

Methods: Ordinal logistic regression was applied to analyze a crash data set involving drivers under and not under the influence of alcohol in China from January 2011 to December 2014.

Results: Four risk factors were found to be significantly associated with the severity of driver injury, including crash partner and intersection type. Age group was found to be significantly associated with the severity of crashes involving drivers under the influence of alcohol. Crash partner, intersection type, lighting conditions, gender, and time of day were found to be significantly associated with severe driver injuries, the last of which was also significantly associated with severe crashes involving drivers not under the influence of alcohol.

Conclusions: This study found that pedestrian involvement decreases the odds of severe driver injury when a driver is under the influence of alcohol, with a relative risk of 0.05 compared to the vehicle-to-vehicle group. The odds of severe driver injury at T-intersections were higher than those for traveling along straight roads. Age was shown to be an important factor, with drivers 50–60 years of age having higher odds of being involved in severe crashes compared to 20- to 30-year-olds when the driver was under the influence of alcohol.

When the driver was not under the influence of alcohol, drivers suffered more severe injuries between midnight and early morning compared to early nighttime. The vehicle-to-motorcycle and vehicle-to-pedestrian groups experienced less severe driver injuries, and vehicle collisions with fixed objects exhibited higher odds of severe driver injury than did vehicle-to-vehicle impacts. The odds of severe driver injury at cross intersections were 0.29 compared to travel along straight roads. The odds of severe driver injury when street lighting was not available at night were 3.20 compared to daylight. The study indicated that female drivers are more likely to experience severe injury than male drivers when not under the influence of alcohol. Crashes between midnight and early morning exhibited higher odds of severe injury compared to those occurring at other times of day.

The identification of risk factors and a discussion on the odds ratio between levels of the impact of the driver injury and crash severity may benefit road safety stakeholders when developing initiatives to reduce the severity of crashes.     

Risk factors affecting the severity of traffic accidents at Shanghai river-crossing tunnel

Objective: With increasing traffic volume and urban development, increasing numbers of underground tunnels have been constructed to relieve conflict between strained land and heavy traffic. However, as more long tunnels are constructed, tunnel traffic safety is becoming increasingly serious. Thus, it is necessary to acquire their implications and impacts. This study examined 4,539 traffic accidents that have occurred in 14 Shanghai river-crossing tunnels for the period 2011–2012 and analyze the correlation between potential factors and accident injury severity.

Methods: An ordered logit model was developed to examine the correlation between potential factors and accident injury severity.

Results: Results show that increased injury severity is associated with male drivers, drivers aged 65 years or older, accident time from midnight to dawn, weekends, wet road surface, goods vehicles, 3 or more vehicles, 4 or more lanes, middle speed limits (50–79 km/h), zone 3, extra-long tunnels (over 3,000 m), and maximum longitudinal gradient.

Conclusions: This article aims to provide useful information for engineers to develop interventions and countermeasures to improve tunnel safety in China.     

Does time of day matter at highway work zone crashes?

Introduction: It is widely agreed that highway work zones pose significant threats to road users because driving conditions in work zones are quite different from the normal ones, particularly when traffic volumes approach a highway capacity. Therefore, work zone safety is a critical aspect for state agencies and traffic engineers. Method: In the current study, a total of 10,218 crashes that occurred in highway work zones in the state of Washington for the period between 2007 and 2013 were used. Time of day is disaggregated into four subgroups: (1) Morning from 6:00 to 11:00 a.m. (2) Midday from 12:00 to 5:00 p.m. (3) Night from 6:00 to 11:00 p.m., and (4) Late night from 12:00 to 5:00 a.m. Then, four mixed logit models were estimated to account and correct for heterogeneity in the crash data by considering three injury severity levels: severe injury, minor injury, and no injury. Results: The estimation results reveal that most contributing factors are uniquely significant in a specific time of day period, whereas three factors affect injury severity regardless of time of day such as the indicators of not deployed airbag, one passenger vehicle involved in the crash, and rear-end collision. Further, some factors were found to affect injury severity into two or three time periods, such as female drivers that found to decrease the probability of no injury in morning and night time periods, while increasing severe injury outcome in midday time. Conclusions: The effect of time of day on injury severity of work-zone related crashes should be modeled separately rather than using a holistic model. Practical applications: As a starting point, findings of the current study can be used by transportation officials to reduce fatalities and injuries of work zone crashes by identifying factors that uniquely contribute to each time of day period.     

重大危险设备的确定及其失效后果严重度分析

采用火灾、爆炸危险指数(F&EI)方法对石化设备的危险性进行评价,根据计算设备的危险指数值来确定其是否为重大危险设备;应用模糊综合评价方法对石化装置失效后果严重程度进行综合评价研究,建立了石化装置失效后果严重程度的综合评价指标体系;采用定性与定量相结合的层次分析法计算评价因素的权重,运用模糊综合评判理论,提出失效后果严重度的二级模糊综合评价方法,实现对其失效后果严重度的综合评判。实例表明:模糊综合评价方法可操作性强、效果较好,可在石化装置失效后果严重度评价中广泛应用。     

云南省Palmer旱度模式的建立——2010年干旱灾害特征分析

2010年春季云南省发生了特大干旱灾害,造成了严重的经济损失。按照Palmer旱度模式的思路,利用云南省的气象和土壤数据,建立了云南省的Palmer旱度模式。通过将计算得到的Palmer指数值与云南省的实际旱涝灾情历史记录进行对比,发现所建立的Palmer旱度模式能够较好地反映云南省的旱涝情况。基于该模式对2010年云南特大干旱灾害进行了特征分析,结果表明,此次干旱灾害是云南省30年来干旱变化过程中的一次突变。而且结果显示,在2010年的云南干旱灾害中,严重干旱地区整体呈现东西走向的空间分布,极端干旱地区主要分布在云南省的东南部。     

风险严重度指数法在毒气泄漏评价中的应用

为评价某区域或某设备潜在的毒气泄漏事故场景的风险水平,以对不同的风险等级进行风险控制和安全规划,详细介绍了工业事故风险评估方法ARAMIS所采用的风险严重度指数法.首先基于事故频率和后果的风险矩阵选取毒气泄漏事故场景;然后运用毒气当量浓度计算任意暴露时间下不同风险严重度等级所对应的特征距离,并根据同一风险等级内风险严重度指数与距离的线性关系计算任意点的风险严重度指数;最后应用1个实例分析了考虑所研究区域的风向概率后对风险严重度指数的真实影响,便于工厂或企业识别不同的风险等级,进行不同场景下风险水平的对比性研究,为其安全设计及风险分析提供了一种新的评估方法.     

Environmental policy indicators: A systems model

This article describes and tests a systems theory-based policy indicators model. The framework is used to examine propositions about linkages between states' ecological-spatial characteristics and subsequent selected solid waste management (SWM) -related environmental policies. It was hypothesized that state characteristics of: (1) population density (used as a garbage-per-land area index), (2) population convergence within urban areas, and (3) percent population change in the interval 1980–1985, could jointly explain state variation in both the number and the vigor of SWM policy outputs. Greater levels of spatial pressure were proposed to be related directly to more numerous, more convincing policies. Proposals are grounded in the literature of organizational search theory, crisis stimulation, and technological pressure. Results revealed that the sociospatial model in fact could explain a reasonable proportion of policy variation across states. However, not all hypotheses are supported. Population change shows an indirect, rather than the anticipated direct, relationship with policy output levels. In addition, when used in the model as a pollution intensity index, population density failed to contribute significantly to an explanation of differences in state SWM policy levels. The analysis raises questions about changes occurring over time in the nature and direction of linkages between sociospatial measures and policy responses. This study suggests that strengthening policy indicator models may require questioning key assumptions and theoretical bases, conducting longitudinal studies, and factoring in political, economic, and other policy environment forces.