Comparing urban air quality in Europe in real time a review of existing air quality indices and the proposal of a common alternative

The EU directives on air quality force member states to inform the public on the status of the ambient air quality. The Internet is commonly used for this purpose and often air quality is being presented as an index ranging from good to bad. A review of existing websites and air quality indices shows that the way air quality is interpreted differs considerably. The paper presents a new air quality index. The index is part of a project to develop a website dedicated to comparing air quality in European cities. The common air quality index (CAQI) is not aimed at replacing existing local indices. The CAQI is a set of two indices: one for roadside monitoring sites and one for average city background conditions. Differentiating between roadside and general city conditions is a first step in assuring consistence in the parameters that are being compared.     

Identifying crash propensity using specific traffic speed conditions

INTRODUCTION: In spite of recent advances in traffic surveillance technology and ever-growing concern over traffic safety, there have been very few research efforts establishing links between real-time traffic flow parameters and crash occurrence. This study aims at identifying patterns in the freeway loop detector data that potentially precede traffic crashes. METHOD: The proposed solution essentially involves classification of traffic speed patterns emerging from the loop detector data. Historical crash and loop detector data from the Interstate-4 corridor in the Orlando metropolitan area were used for this study. Traffic speed data from sensors embedded in the pavement (i.e., loop detector stations) to measure characteristics of the traffic flow were collected for both crash and non-crash conditions. Bayesian classifier based methodology, probabilistic neural network (PNN), was then used to classify these data as belonging to either crashes or non-crashes. PNN is a neural network implementation of well-known Bayesian-Parzen classifier. With its superb mathematical credentials, the PNN trains much faster than multilayer feed forward networks. The inputs to final classification model, selected from various candidate models, were logarithms of the coefficient of variation in speed obtained from three stations, namely, station of the crash (i.e., station nearest to the crash location) and two stations immediately preceding it in the upstream direction (measured in 5 minute time slices of 10-15 minutes prior to the crash time). RESULTS: The results showed that at least 70% of the crashes on the evaluation dataset could be identified using the classifiers developed in this paper.     

兰州市道路交通噪声污染与人体健康的分析

随着环保事业的发展,人们已认识到环境系统的健康与人体的健康状况有着密切的关系。笔者采用流行病学研究方法和SPSS 11.0forWindows的统计软件,对居住在交通干线两旁的居民,按照不同个体特征和不同居住环境所受交通噪声影响的程度进行了对比分析,其结果表明,中年人比老年人和青年人受噪声影响明显;不同性别受噪声影响程度没有明显差异;各功能区特征不同,混合区受噪声影响最严重;在道路交通噪声较高的区域,该地区居民的受影响程度也相对较高。最后,提出了在新城建设和旧城改造过程之中考虑城市道路规划设计,居民自身也应加强个人防护的防治对策     

开封市交通噪声环境质量二级模糊综合评价

在开封市2005年交通噪声实地监测数据的基础上,运用二级模糊综合评价法,对市区交通噪声环境质量进行现状评价,评价结果为开封市交通噪声环境质量总体上昼间属于轻污染,夜间属于重度污染,夜间交通噪声环境质量明显劣于昼间。其结论符合开封市的实际情况,不仅能较好地描述开封市交通噪声环境污染的连续、渐变、模糊的特点,而且还弥补了一级模糊综合评价难以反映出小范围路段对整体环境质量贡献的不足。     

Comparison of epidemiology and injury profile between vulnerable road users and motor vehicle occupants in road traffic fatalities

Objective: Road traffic injuries (RTIs) are a major global health issue causing a global burden of mortality and morbidity. Half of all fatalities on the world’s roads are vulnerable road users (VRUs). The targeted intervention strategies based on fatality analysis focusing on VRUs can effectively contribute to reducing RTIs. This study aimed to compare VRUs and motor vehicle occupants (MVOs) in terms of epidemiology and injury profile.

Methods: We utilized a nationwide, prospective database of RTI-related mortality cases for patients who visited 23 emergency departments between January 2011 and December 2015. All fatalities due to RTIs in the prehospital phase or in-hospital were eligible, excluding patients with unknown mode of transport and those admitted to general wards. The primary and secondary outcomes were fracture injuries and visceral injuries diagnosed using the International Classification of Diseases, Tenth Revision (ICD-10). We compared fracture injuries between VRUs and MVOs using Abbreviated Injury Scale (AIS) 2? and 2+ classification.

Results: Among a total 3,694 road traffic fatalities (RTFs), 43.3% were pedestrians, followed by MVOs (27.0%), motorcyclists (18.9), bicyclists (6.6%), and agricultural vehicle users (4.2%). The elderly (>60 years old) accounted for 54.9% of VRU fatalities. RTFs occurred most frequently in the autumn and the VRU group and the MVO group showed significant differences in weekly and diurnal variation in RTFs. The injury severities (AIS 2+) of the head, neck, and thorax were significantly different between the 2 groups (P?Conclusions: Elderly pedestrians should be targeted for decreases in RTFs, and road traffic safety interventions for VRUs should be made based on the analysis of temporal epidemiology and injury profiles of RTFs.     

Deciphering urban traffic impacts on air quality by deep learning and emission inventory

Air pollution is a major obstacle to future sustainability, and traffic pollution has become a large drag on the sustainable developments of future metropolises. Here, combined with the large volume of real-time monitoring data, we propose a deep learning model, iDeepAir, to predict surface-level PM_2.5 concentration in Shanghai megacity and link with MEIC emission inventory creatively to decipher urban traffic impacts on air quality. Our model exhibits high-fidelity in reproducing pollutant concentrations and reduces the MAE from 25.355 µg/m³ to 12.283 µg/m³ compared with other models. And identifies the ranking of major factors, local meteorological conditions have become a nonnegligible factor. Layer-wise relevance propagation (LRP) is used here to enhance the interpretability of the model and we visualize and analyze the reasons for the different correlation between traffic density and PM_2.5 concentration in various regions of Shanghai. Meanwhile, As the strict and effective industrial emission reduction measurements implementing in China, the contribution of urban traffic to PM_2.5 formation calculated by combining MEIC emission inventory and LRP is gradually increasing from 18.03% in 2011 to 24.37% in 2017 in Shanghai, and the impact of traffic emissions would be ever-prominent in 2030 according to our prediction. We also infer that the promotion of vehicular electrification would achieve further alleviation of PM_2.5 about 8.45% by 2030 gradually. These insights are of great significance to provide the decision-making basis for accurate and high-efficient traffic management and urban pollution control, and eventually benefit people's lives and high-quality sustainable developments of cities.     

The effectiveness of reducing illegal blood alcohol concentration (BAC) limits for driving: evidence for lowering the limit to .05 BAC

PURPOSE: This scientific review provides a summary of the evidence regarding the benefits of reducing the illegal blood alcohol concentration (BAC) limit for driving and providing a case for enacting a .05 BAC limit. RESULTS: Fourteen independent studies in the United States indicate that lowering the illegal BAC limit from .10 to .08 has resulted in 5-16% reductions in alcohol-related crashes, fatalities, or injuries. However, the illegal limit is .05 BAC in numerous countries around the world. Several studies indicate that lowering the illegal per se limit from .08 to .05 BAC also reduces alcohol-related fatalities. Laboratory studies indicate that impairment in critical driving functions begins at low BACs and that most subjects are significantly impaired at .05 BAC. The relative risk of being involved in a fatal crash as a driver is 4 to 10 times greater for drivers with BACs between .05 and .07 compared to drivers with .00 BACs. SUMMARY: There is strong evidence in the literature that lowering the BAC limit from .10 to .08 is effective, that lowering the BAC limit from .08 to .05 is effective, and that lowering the BAC limit for youth to .02 or lower is effective. These law changes serve as a general deterrent to drinking and driving and ultimately save lives. IMPACT ON INDUSTRY: This critical review supports the adoption of lower illegal BAC limits for driving.