安宁市环境噪声污染及防治控制措施

分析了安宁市环境噪声质量状况、主要来源和污染原因,提出了防治及控制措施。     

Air quality nearby road traffic tunnel portals： BTEX monitoring

A monitoring campaign of BTEX （benzene, toluene, ethylbenzene, o- m- and p-xylene） was carried out nearby two tunnel portals in the urban area of Naples with the aim to verify air quality in this kind of urban sites. Sampling was carried out using the active adsorption technique. Sampling time was 1 h. Ambient temperature and traffic flow measurements were carried out during each sampling operation. The results indicate that average benzene concentrations at both sites exceed the limit value of 10 μg/Nm^3 established by the European Community （EC） （Dir. 2000/69）. Concentration levels of other BTEX are relatively high as well. A correlation between BTEX concentration and two wheeler vehicle flow was observed.     

某军用机场内部飞机噪声监测及防治分析

针对军用机场内部受飞机噪声影响的突出问题,对某军用机场进行了监测,得到了机场内部典型单位室内、外以及飞机起飞加力过程和滑跑时的飞机噪声值,在分析飞机噪声对机场内部影响的基础上,总结提出了针对该机场飞机噪声影响的防治对策。     

噪声对学生学习能力的影响调查

用剂量作业试验和短时记忆法2个指标对处在不同声环境条件下的两所中学的学生之学习能力进行调查，结果表明高噪声会导致中学生学习能力的下降，但并不存在显著差异。     

废旧汽车轮胎复合吸声屏障的振动与吸声特性

利用废旧汽车轮胎与水泥穿孔板两种主体材料研发出一种新型的复合吸声屏障,并从实验和理论上证实了该种声屏障在中、低频段吸声性能良好;同时制作成本低廉,便于维护,适合于高速公路交通噪声降噪需要。     

空分站大型空压机组的噪声治理

介绍了洛阳分公司空压车间空分站大型空压机组的噪声治理,采用局部敞开式隔声罩隔音降噪,选用合适的吸声材料,效果明显.     

雾霾时车辆尾气排放对驾驶员能见度的影响

针对北京道路车辆尾气排放对雾霾时驾驶员道路能见度的影响问题,建立了雾霾时车辆尾气排放与驾驶员道路能见度关系模型。该模型以车辆为单元建立车辆尾气排放元胞,考虑了车辆尾气排放后的污染物物理和化学变化,并以车道中的尾气排放位置截面及截面单元、交叉口处的尾气排放位置区间为模型单元。为验证该模型,于2016年10月-2017年2月和2017年10月-2018年2月,在北京地区部分路网检测了驾驶员道路能见度等数据,并统计了各时段驾驶员道路能见度的分布情况。对建立的关系模型进行仿真,结果表明,该关系模型的仿真结果与实际检测数据的误差占比平均值小于4. 98%,验证了该关系模型用于描述北京市道路车辆尾气排放对雾霾时驾驶员道路能见度影响的有效性。     

弯道路段集重型大型货物运输车辆通过宽度研究*

为研究集重型大型货物运输车辆在弯道路段不同圆曲线半径条件下的通过宽度,基于Ackerman转向原理建立集重型大型货物运输车辆转弯模型,研究道路圆曲线路段车辆通过所需道路宽度与牵引车前轴中心运行半径和液压轴线挂车长度间的关系;得到车辆外廓弯道最外侧点的判别方法,以及牵引车前轴中心运行半径、液压轴线挂车长度对车辆通过所需道路宽度的影响强度、相对优势影响区域及三者间的分段函数关系;得到典型车辆通过不同半径弯道所需道路宽度与牵引车前轴中心运行半径间的关系。结果表明:计算方法及结果可为大型货物运输道路规划设计和集重型大型货物的运输路径优选提供理论依据。     

基于最优尺度Logit模型的交通事故形态致因分析

为剖析典型交通事故形态致因,在利用最优尺度分析法诊断交通事故形态致因共线性的基础上,筛选关键影响因素,构建无序多分类Logit交通事故致因模型并对模型进行参数标定,并选择100个交通事故样本对模型进行精度验证,该模型相对误差仅为4.0%,能够较为准确地分析典型交通事故形态致因。研究结果表明:路侧及中央隔离设施、照明是事故的保护性因子,可有效降低事故率;路侧行道树设置不合理或未及时修剪,使车辆不能有效识别道路信息,是正面碰撞的重要影响因素;机非混合道是事故的危险因子,增大了侧面碰撞事故发生概率。研究结果可为交通隐患精准识别、交通事故主动预防以及交通设施科学设计提供理论依据和技术支撑。     

Impact of medical fitness to drive policies in preventing property damage,injury, and death from motor vehicle collisions in Ontario,Canada

Introduction: Drivers with medical conditions and functional impairments are at increased collision risk. A challenge lies in identifying the point at which such risk becomes unacceptable to society and requires mitigating measures. This study models the road safety impact of medical fitness-to-drive policy in Ontario. Method: Using data from 2005 to 2014, we estimated the losses to road safety incurred during the time medically-at-risk drivers were under review, as well as the savings to road safety accrued as a result of licensing decisions made after the review process. Results: While under review, drivers with medical conditions had an age- and sex-standardized collision rate no different from the general driver population, suggesting no road safety losses occurred (RR = 1.02; 95% CI: 0.93–1.12). Licensing decisions were estimated to have subsequently prevented 1,211 (95% CI: 780–1,730) collisions, indicating net road safety savings resulting from medical fitness to drive policies. However, more collisions occurred than were prevented for drivers with musculoskeletal disorders, sleep apnea, and diabetes. We theorize on these findings and discuss its multiple implications. Conclusions: Minimizing the impact of medical conditions on collision occurrence requires robust policies that balance fairness and safety. It is dependent on efforts by academic researchers (who study fitness to drive); policymakers (who set driver medical standards); licensing authorities (who make licensing decisions under such standards); and clinicians (who counsel patients on their driving risk and liaise with licensing authorities). Practical Applications: Further efforts are needed to improve understanding of the effects of medical conditions on collision risk, especially for the identified conditions and combinations of conditions. Results reinforce the value of optimizing the processes by which information is solicited from physicians in order to better assess the functional impact of drivers’ medical conditions on driving and to take suitable licensing action.