重型柴油车对空气质量的影响及其排放的控制

通过对柴油车污染物排放的特征和机动车排放清单的分析,探讨了重型柴油车对我国城市空气质量的影响及其排放的控制.重型柴油车排放大量的氮氧化物和颗粒物,其中氮氧化物为大气中产生二次细粒子以及臭氧的重要前体物之一,导致区域性灰霾的形成,而柴油颗粒物是影响健康的一个主要有毒空气污染物,尤其是其中粒径为30～100 nm的超细粒子...     

中山市机动车尾气污染防治对策探讨

随着城市建设的加快和私人购车意愿的增加,中山市机动车保有量增长迅速,机动车排气污染量越来越大,排气污染问题日益突出.通过对中山市机动车发展及尾气污染现状的总结与回顾,指出了机动车尾气可能造成的危害,提出了相关对策建议,如实施更严排放标准、加快淘汰黄标车、提升车用燃油品质,强化机动车环境监管,调控城市机动车保有总量,加快信息化建设,建立部门信息交换机制等,为中山市机动车尾气污染综合防治工作的开展提供了一定的参考.     

乌鲁木齐市城区机动车大气污染物排放特征

对乌鲁木齐市城区车辆信息(包括车流量和车辆构成、车辆控制技术水平、车辆行驶工况、车辆启动分布等)进行调研和测试,并根据IVE模型计算得到机动车污染物排放清单,获得分车型、燃料类型及启动/运行方式的机动车污染物排放分担率.结果表明:2011年乌鲁木齐市机动车CO、NO_x、HC和PM的排放量分别为20.22×104、2.60×104、1.84×104和0.44×10~4t·a~(-1),机动车污染物排放分担率差别显著,乘用车、公交车和重型货车是CO和HC主要排放源;重型货车和乘用车是NO_x的主要排放源;重型货车是PM的主要排放源.汽油车是CO和HC排放的主要来源,柴油车是NO_x和PM排放的主要来源,天然气车各类污染物排放量均较低.控制柴油重型货车是消减机动车污染物排放的重要方式.     

Age- and Sex-Specific Thorax Finite Element Model Development and Simulation

Objective: The shape, size, bone density, and cortical thickness of the thoracic skeleton vary significantly with age and sex, which can affect the injury tolerance, especially in at-risk populations such as the elderly. Computational modeling has emerged as a powerful and versatile tool to assess injury risk. However, current computational models only represent certain ages and sexes in the population. The purpose of this study was to morph an existing finite element (FE) model of the thorax to depict thorax morphology for males and females of ages 30 and 70 years old (YO) and to investigate the effect on injury risk.

Methods: Age- and sex-specific FE models were developed using thin-plate spline interpolation. In order to execute the thin-plate spline interpolation, homologous landmarks on the reference, target, and FE model are required. An image segmentation and registration algorithm was used to collect homologous rib and sternum landmark data from males and females aged 0–100 years. The Generalized Procrustes Analysis was applied to the homologous landmark data to quantify age- and sex-specific isolated shape changes in the thorax. The Global Human Body Models Consortium (GHBMC) 50th percentile male occupant model was morphed to create age- and sex-specific thoracic shape change models (scaled to a 50th percentile male size). To evaluate the thoracic response, 2 loading cases (frontal hub impact and lateral impact) were simulated to assess the importance of geometric and material property changes with age and sex.

Results: Due to the geometric and material property changes with age and sex, there were observed differences in the response of the thorax in both the frontal and lateral impacts. Material property changes alone had little to no effect on the maximum thoracic force or the maximum percent compression. With age, the thorax becomes stiffer due to superior rotation of the ribs, which can result in increased bone strain that can increase the risk of fracture. For the 70-YO models, the simulations predicted a higher number of rib fractures in comparison to the 30-YO models. The male models experienced more superior rotation of the ribs in comparison to the female models, which resulted in a higher number of rib fractures for the males.

Conclusion: In this study, age- and sex-specific thoracic models were developed and the biomechanical response was studied using frontal and lateral impact simulations. The development of these age- and sex-specific FE models of the thorax will lead to an improved understanding of the complex relationship between thoracic geometry, age, sex, and injury risk.     

Mortality Risk in Pediatric Motor Vehicle Crash Occupants: Accounting for Developmental Stage and Challenging Abbreviated Injury Scale Metrics

Objective: Survival risk ratios (SRRs) and their probabilistic counterpart, mortality risk ratios (MRRs), have been shown to be at odds with Abbreviated Injury Scale (AIS) severity scores for particular injuries in adults. SRRs have been validated for pediatrics but have not been studied within the context of pediatric age stratifications. We hypothesized that children with similar motor vehicle crash (MVC) injuries may have different mortality risks (MR) based upon developmental stage and that these MRs may not correlate with AIS severity.

Methods: The NASS-CDS 2000–2011 was used to define the top 95% most common AIS 2+ injuries among MVC occupants in 4 age groups: 0–4, 5–9, 10–14, and 15–18 years. Next, the National Trauma Databank 2002–2011 was used to calculate the MR (proportion of those dying with an injury to those sustaining the injury) and the co-injury-adjusted MR (MR_MAIS) for each injury within 6 age groups: 0–4, 5–9, 10–14, 15–18, 0–18, and 19+ years. MR differences were evaluated between age groups aggregately, between age groups based upon anatomic injury patterns and between age groups on an individual injury level using nonparametric Wilcoxon tests and chi-square or Fisher's exact tests as appropriate. Correlation between AIS and MR within each age group was also evaluated.

Results: MR and MR_MAIS distributions of the most common AIS 2+ injuries were right skewed. Aggregate MR of these most common injuries varied between the age groups, with 5- to 9-year-old and 10- to 14-year-old children having the lowest MRs and 0- to 4-year-old and 15- to 18-year-old children and adults having the highest MRs (all P <.05). Head and thoracic injuries imparted the greatest mortality risk in all age groups with median MR_MAIS ranging from 0 to 6% and 0 to 4.5%, respectively. Injuries to particular body regions also varied with respect to MR based upon age. For example, thoracic injuries in adults had significantly higher MR_MAIS than such injuries among 5- to 9-year-olds and 10- to 14-year-olds (P =.04; P <.01). Furthermore, though AIS was positively correlated with MR within each age group, less correlation was seen for children than for adults. Large MR variations were seen within each AIS grade, with some lower AIS severity injuries demonstrating greater MRs than higher AIS severity injuries. As an example, MR_MAIS in 0- to 18-year-olds was 0.4% for an AIS 3 radius fracture versus 1.4% for an AIS 2 vault fracture.

Conclusions: Trauma severity metrics are important for outcome prediction models and can be used in pediatric triage algorithms and other injury research. Trauma severity may vary for similar injuries based upon developmental stage, and this difference should be reflected in severity metrics. The MR-based data-driven determination of injury severity in pediatric occupants of different age cohorts provides a supplement or an alternative to AIS severity classification for pediatric occupants in MVCs.     

Evaluation of Vehicle-Based Crash Severity Metrics

Objective: Vehicle change in velocity (delta-v) is a widely used crash severity metric used to estimate occupant injury risk. Despite its widespread use, delta-v has several limitations. Of most concern, delta-v is a vehicle-based metric which does not consider the crash pulse or the performance of occupant restraints, e.g. seatbelts and airbags. Such criticisms have prompted the search for alternative impact severity metrics based upon vehicle kinematics. The purpose of this study was to assess the ability of the occupant impact velocity (OIV), acceleration severity index (ASI), vehicle pulse index (VPI), and maximum delta-v (delta-v) to predict serious injury in real world crashes.

Methods: The study was based on the analysis of event data recorders (EDRs) downloaded from the National Automotive Sampling System / Crashworthiness Data System (NASS-CDS) 2000–2013 cases. All vehicles in the sample were GM passenger cars and light trucks involved in a frontal collision. Rollover crashes were excluded. Vehicles were restricted to single-event crashes that caused an airbag deployment. All EDR data were checked for a successful, completed recording of the event and that the crash pulse was complete. The maximum abbreviated injury scale (MAIS) was used to describe occupant injury outcome. Drivers were categorized into either non-seriously injured group (MAIS2?) or seriously injured group (MAIS3+), based on the severity of any injuries to the thorax, abdomen, and spine. ASI and OIV were calculated according to the Manual for Assessing Safety Hardware. VPI was calculated according to ISO/TR 12353-3, with vehicle-specific parameters determined from U.S. New Car Assessment Program crash tests. Using binary logistic regression, the cumulative probability of injury risk was determined for each metric and assessed for statistical significance, goodness-of-fit, and prediction accuracy.

Results: The dataset included 102,744 vehicles. A Wald chi-square test showed each vehicle-based crash severity metric estimate to be a significant predictor in the model (p < 0.05). For the belted drivers, both OIV and VPI were significantly better predictors of serious injury than delta-v (p < 0.05). For the unbelted drivers, there was no statistically significant difference between delta-v, OIV, VPI, and ASI.

Conclusions: The broad findings of this study suggest it is feasible to improve injury prediction if we consider adding restraint performance to classic measures, e.g. delta-v. Applications, such as advanced automatic crash notification, should consider the use of different metrics for belted versus unbelted occupants.     

Vehicle-Induced Lead and Cadmium Contamination of Roadside Soil and Plants in Italy

Lead and cadmium concentrations in spontaneous vegetation and in soil sampled at various distances (0–208 m) from several motorways throughout Italy were measured. Lead and cadmium concentrations appear to be correlated to distance from the motorway and to traffic levels. A comparison with data from a remote and unpolluted site shows that foliar lead concentrations can be up to 40 times higher, and foliar cadmium concentrations up to 3 times higher. Plants behave differently in their accumulation of lead and cadmium; conifers present the highest levels. Also the various receptors and compartments of the roadside ecosystem differ in their accumulation of lead and cadmium; soil and bark have consistently higher concentrations, while the leaves and twigs of trees have consistently lower levels. the data recorded by ad hoc introduced bio-accumulating plants (Lolium multiflorum L.) are consistent with those of the spontaneous vegetation. the concentrations of both lead and cadmium in Lolium vary from June to November, following in part the fluctuation in traffic density.     

A simple empirical model to predict forest insecticide ground-level deposition from a compendium of field data

Deposit data from 205 aerial forest insecticide applications conducted in field trials by the Canadian Forest Service, Great Lakes Forestry Centre over a 15-year period are summarized. Deposit measurements were taken under “worst case” scenarios in the sense that direct applications were made over water bodies, and ground samplers were intentionally placed in open or cleared areas of forest. The median % deposit on shoreline collectors (32 separate applications) was 5.7%, on mid-stream collectors (44 separate applications) was 6.2%, and on forest floor collectors (129 separate applications) was 4.9%. Forest floor deposit was most closely associated with application rate and droplet size (r = 0.624, p < 0.001 and r = 0.662, p = 0.011, respectively) but these variables combined only explained 44% of the variation in deposit. Data from all three collector types were grouped by 10% deposit increments and combined to provide a data set from all deposition scenarios. A negative exponential model was fitted to the proportion of these combined sites regressed on % deposit in 10% increments and plotted as a deposit probability distribution curve (p < 0.001, r² = 0.992). The probability distribution curve indicated that 5–10% deposit would be expected about 57–91% of the time, whereas 50% deposit or greater would be expected about 2% of the time or less. In a probabilistic risk assessment for aerially applied insecticides in a conifer-dominated forest environment, the probability distribution curve based on empirical data presented here can be used to refine the characterization of exposure scenarios from which effects estimates can be derived.     

基于模糊网络和时间依赖的应急车辆调度优化研究

突发灾害的应急物资调度是减轻人民财产损失、防止次生灾害发生、保障社会稳定的必要支撑。借助模糊数学中的三角模糊数学方法对不确定的需求信息特征进行描述,用模糊函数积分确定车辆在路段的模糊行驶时间。以应急车辆调度的总时间最短为调度的主要目标,同时配送数量应最大限度地满足需求点的需求量为次要目标建立应急车辆调度模型。然后设计粒子群算法对模型进行求解。最后通过算例,验证建立的模型拟合现实中的情况,结果不是确定数值,而是模糊数值范围的优化。