报废汽车内饰件塑料浮选技术研究

报废汽车内饰件塑料品种复杂、难以分选,为此,以分离汽车内饰件中4种主体塑料——PP(聚丙烯)、ABS(丙烯腈-丁二烯-苯乙烯)、PC(聚碳酸酯)、PVC(聚氯乙烯)为目标,利用实验室自制浮选设备,考察了浮选液流量、溶气罐压力、润湿液浓度等因素对浮选效果的影响. 结果表明:当溶气罐压力为0.22 MPa、浮选液流量为10 L/min、润湿液中ρ(单宁酸)为15 mg/L时,一级浮选PP、ABS、PC、PVC效果达到最佳,其中PP和ABS为上浮料,二者上浮率分别为100%和98.63%;PC和PVC为下沉料,二者下沉率分别为98.95%和100%. 当溶气罐压力为0 MPa、浮选液流量为6 L/min、润湿液中ρ(单宁酸)为10 mg/L时,二级浮选完全分离PP/ABS;当溶气罐压力为0.24 MPa、浮选液流量为10 L/min、润湿液采用10 mg/L单宁酸和10 mmol/L癸二酸二丁酯时,二级浮选分离PC/PVC效果达到最佳,PC上浮率为92.87%,PVC下沉率为91.41%. 通过二级浮选分离,PP、ABS、PC、PVC的最终分离率分别达到100%、98.63%、92.87%和91.41%,显示出该二级浮选工艺在报废汽车内饰件塑料分选方面具有较为广阔的应用前景.      

IVE机动车排放模型应用研究

对IVE模型进行了系统分析和介绍,以北京市为研究对象给出了模型的主要输入参数的确定方法和思路,运用IVE模型对北京市不同车型车队的排放进行计算。结果显示：公交车和卡车的排放因子明显较高,特别是颗粒物排放因子,分别为普通轻型车的14和44倍。北京市机动车的CO、VOC、NOx和PM的平均日排放总量分别为2767.4、182.5、353.8和7.1t。对于CO和VOC,普通轻型车的分担率分别为42.0%和34.7%;对于NOx和PM而言,卡车的贡献率最高,分别达到66.3%和83.0%。此外,比较了IVE模型与MOBILE6模型的方法和计算结果,讨论了IVE模型在我国的主要应用优势。     

重型柴油车车载排放实测与加载影响研究

采用车载排放测试仪,对2辆重型柴油卡车在空载和加载条件下进行实际道路车载排放测试.通过分析获得了油耗与排放速率的速度-加速度及其工况点的分布,发现高油耗与高排放工况点主要集中在高速加速区域,加载时油耗与排放高值随工况点分布更广;车辆在(30±2.5)km·h^-1等速及加速行驶时受加载影响最大,此时加载油耗与排放约是空载的1.6～3.2倍左右;由实测结果发现,卡车Ⅰ和卡车Ⅱ加载时油耗及CO、HC、NO_x排放因子分别是空载的1.6倍、3.5倍、1.1倍、1.5倍以及1.2倍、1.0倍、0.9倍和1.5倍,加载对油耗与NO_x排放影响最为明显,对HC影响最小,CO影响取决于车辆保养水平;卡车Ⅱ较卡车Ⅰ车型更大,发动机功率更高,相同荷载时受加载影响较小,说明重型车在发动机负荷可承受的范围内合理装载,有助于避免油耗与排放恶化,提高燃油经济性和排放水平.     

应急救援物资车辆运输线路的选择

为了给紧急救援物资支持保障中心的物资调度人员提供科学的车辆路线调度决策方法,提高应急救援工作的响应能力,基于应急条件下物资运输调度的时效性、安全性和经济性特征,运用旅行商理论,对上述3个决策属性分量进行了数学描述,构造了它们的目标函数,并进行了无量纲和权重聚合处理,继而按照多属性决策理论建立了用来评价备选线路决策效用函数的数学模型.利用期望效用属性合并所搜集的信息,将多属性决策问题转化成单属性决策问题,确立了选择具有最高期望效用方案的方法,最后进行了实例分析.结果表明,应急救援条件下的运输调度与正常环境下的企业运输调度决策目标之间存在明显的差异,前者虽然本质上属于图论中最短路线问题的范畴,但由于多个决策目标的存在,不能直接运用最短路线模型和Dijkstra算法求解.运用多属性决策理论建立的评价备选线路决策效用函数,是有关人员进行车辆路线安排的有效方法,但其相对优越性尚需做进一步的研究和探讨.     

应用IVE模型计算上海市机动车污染物排放

为了解上海市机动车污染现状,建立上海市机动车源排放清单,分别选择上海市中心城区、商业区和收入相对较低区域中的主干道、快速道和次干道3种共9条典型道路,开展机动车技术水平参数、比功率(VSP)分布状况、启动状况等测试,并在此基础上将International Vehicle E-mission(IVE)模型本地化.调查结果表明,上海市区实际道路上轻型客车、出租车、公交巴士、卡车和摩托车(包含助动车)分别占道路总车流量的41.0%、30.8%、15.6%、6.9%和5.7%;从技术组成看,约85%的轻型客车和97%的出租车均安装有三元催化装置,约30%的公交巴士和90%的卡车没有达到欧Ⅰ标准;机动车的VSP分布主要集中在-2.9～1.2 kw·t-1.模式计算结果表明,2004年上海市机动车CO、VOC、NOx和PM排放量分别为57.06×104t、7.75×104t、9.20×104t和0.26×104t;20%的高排放车对总排放量的贡献占到25%～45%;启动过程中排放的CO、VOC和PM占总排放量的15%～25%,NOx仅占总排放量的4.5%.     

北京市天然气公交车的发展现状及前景

随着石油资源短缺、城市空气污染问题的日益严重,天然气汽车作为一种实用的低排放汽车逐渐得到了重视和应用。本文首先通过汽车与能源、汽车与环境两个方面,分析说明了北京市发展天然气汽车的重要性;然后简要介绍了北京市天然气公交车的发展现状、未来几年的发展规划,最后指出了实现发展规划的条件和政策。     

跨座式单轨交通人身安全雷电防护分析

针对跨座式单轨交通列车遭受雷击时列车内的人员安全性,本文通过对列车内人员不接触与列车金属外壳直接连接的金属构件和接触与列车金属外壳直接连接的金属构件两种情况进行计算分析,得出第一种情况下,人员是完全安全的;第二种情况下,人员可能会有像蜜蜂刺痛或烟头灼痛的感觉,但不威胁生命安全。     

Characteristics of animal-related motor vehicle crashes in select National Park Service units—United States, 1990–2013

Objectives: Nationally, animal–motor vehicle crashes (AVCs) account for 4.4% of all types of motor vehicle crashes (MVCs). AVCs are a safety risk for drivers and animals and many National Park Service (NPS) units (e.g., national park, national monument, or national parkway) have known AVC risk factors, including rural locations and substantial animal densities. We sought to describe conditions and circumstances involving AVCs to guide traffic and wildlife management for prevention of AVCs in select NPS units.

Methods: We conducted an analysis using NPS law enforcement MVC data. An MVC is a collision involving an in-transit motor vehicle that occurred or began on a public roadway. An AVC is characterized as a collision between a motor vehicle and an animal. A non-AVC is a crash between a motor vehicle and any object other than an animal or noncollision event (e.g., rollover crash). The final data for analysis included 54,068 records from 51 NPS units during 1990–2013. Counts and proportions were calculated for categorical variables and medians and ranges were calculated for continuous variables. We used Pearson’s chi-square to compare circumstances of AVCs and non-AVCs. Data were compiled at the park regional level; NPS parks are assigned to 1 of 7 regions based on the park’s location.

Results: AVCs accounted for 10.4% (5,643 of 54,068) of all MVCs from 51 NPS units. The Northeast (2,021 of 5,643; 35.8%) and Intermountain (1,180 of 5,643; 20.9%) regions had the largest percentage of the total AVC burden. November was the peak month for AVCs across all regions (881 of 5,643; 15.6%); however, seasonality varied by park geographic regions. The highest counts of AVCs were reported during fall for the National Capital, Northeast/Southeast, and Northeast regions; winter for the Southeast region; and summer for Intermountain and Pacific West regions.

Conclusions: AVCs represent a public health and wildlife safety concern for NPS units. AVCs in select NPS units were approximately 2-fold higher than the national percentage for AVCs. The peak season for AVCs varied by NPS region. Knowledge of region-specific seasonality patterns for AVCs can help NPS staff develop mitigation strategies for use primarily during peak AVC months. Improving AVC data collection might provide NPS with a more complete understanding of risk factors and seasonal trends for specific NPS units. By collecting information concerning the animal species hit, park managers can better understand the impacts of AVC to wildlife population health.     

The need to improve information on road user type in National Vital Statistics System mortality data

Objectives: Both the National Vital Statistics System (NVSS) and the Fatality Analysis Reporting System (FARS) can be used to examine motor vehicle crash (MVC) deaths. These 2 data systems operate independently, using different methods to collect and code information about the type of vehicle (e.g., car, truck, bus) and road user (e.g., occupant, motorcyclist, pedestrian) involved in an MVC. A substantial proportion of MVC deaths in NVSS are coded as “unspecified” road user, which reduces the utility of the NVSS data for describing burden and identifying prevention measures. This study aimed to describe characteristics of unspecified road user deaths in NVSS to further our understanding of how these groups may be similar to occupant road user deaths.

Methods: Using data from 1999 to 2015, we compared NVSS and FARS MVC death counts by road user type, overall and by age group, gender, and year. In addition, we examined factors associated with the categorization of an MVC death as unspecified road user such as state of residence of decedent, type of medical death investigation system, and place of death.

Results: The number of MVC occupant deaths in NVSS was smaller than that in FARS in each year and the number of unspecified road user deaths in NVSS was greater than that in FARS. The sum of the number of occupant and unspecified road user deaths in NVSS, however, was approximately equal to the number of FARS occupant deaths. Age group and gender distributions were roughly equivalent for NVSS and FARS occupants and NVSS unspecified road users. Within NVSS, the number of MVC deaths listed as unspecified road user varied across states and over time. Other categories of road users (motorcyclists, pedal cyclists, and pedestrians) were consistent when comparing NVSS and FARS.

Conclusions: Our findings suggest that the unspecified road user MVC deaths in NVSS look similar to those of MVC occupants according to selected characteristics. Additional study is needed to identify documentation and reporting challenges in individual states and over time and to identify opportunities for improvement in the coding of road user type in NVSS.