浅析我国汽车排放新标准

针对我国汽车排放标准体系中对汽车制造厂新车"型式核准"认证、"生产一致性检查"以及客户所使用的新生产汽车和在用汽车等不同层面的排放要求,通过引证大量的原始材料,分析并介绍现阶段我国汽车污染物排放限制的最新标准,对实际工作者有一定的指导作用.     

中小物流企业低碳之道

针对国内中小物流企业发展现状,从企业发展模式、业务拓展、发展策略、市场营销等方面,提出符合其实际状况、较为可行的低碳物流建设途径.     

异形管道的危险区域的判定与分析

为保证特殊压力管道的安全运行,针对使用20年以上的异形压力管道提出了一种检验方法,通过壁厚测定和硬度测量确定了材质的基本情况;基于有限元法进行了危险区域的分析和判断;利用声发射检测来对危险区域进行实时检测和分析。结果表明：通过此方法不仅可判断危险区域的可靠性和安全性,解决了复杂管道的安全使用问题,也为复杂管道检验提供了参考。     

Siting public electric vehicle charging stations in Beijing using big-data informed travel patterns of the taxi fleet

Charging infrastructure is critical to the development of electric vehicle (EV) system. While many countries have implemented great policy efforts to promote EVs, how to build charging infrastructure to maximize overall travel electrification given how people travel has not been well studied. Mismatch of demand and infrastructure can lead to under-utilized charging stations, wasting public resources. Estimating charging demand has been challenging due to lack of realistic vehicle travel data. Public charging is different from refueling from two aspects: required time and home-charging possibility. As a result, traditional approaches for refueling demand estimation (e.g. traffic flow and vehicle ownership density) do not necessarily represent public charging demand. This research uses large-scale trajectory data of 11,880 taxis in Beijing as a case study to evaluate how travel patterns mined from big-data can inform public charging infrastructure development. Although this study assumes charging stations to be dedicated to a fleet of PHEV taxis which may not fully represent the real-world situation, the methodological framework can be used to analyze private vehicle trajectory data as well to improve our understanding of charging demand for electrified private fleet. Our results show that (1) collective vehicle parking “hotspots” are good indicators for charging demand; (2) charging stations sited using travel patterns can improve electrification rate and reduce gasoline consumption; (3) with current grid mix, emissions of CO₂, PM, SO₂, and NO_x will increase with taxi electrification; and (4) power demand for public taxi charging has peak load around noon, overlapping with Beijing’s summer peak power.     

基于比功率分布的排放因子速度修正误差控制研究

高分辨率的排放因子是进行交通能耗排放测算的重要参数，然而，由于数据采集与质量控 制问题，排放因子速度修正曲线常存在异常波动。为提高排放因子速度修正结果的准确性，本文 分别从比功率分布和排放率两个角度分析排放因子敏感性和区间容许误差，建立机动车工况数 据和PEMS排放数据需求量计算模型。敏感性分析结果表明，个别比功率区间分布误差是造成 排放因子速度修正曲线产生异常波动的重要原因；排放率误差会导致排放因子速度修正结果出 现整体性误差。数值模拟计算结果表明，在95%的置信水平下，平均速度在20~120 km·h-1内，控 制快速路CO2排放因子速度修正误差不超过1%：需采集40 min的排放数据，细化至1 kW·t-1 粒度 下各比功率区间数据需求量差异显著；各平均速度下需采集710 min工况数据，相同误差下，80~ 120 km·h-1 内工况数据需求量更低；为进一步消除曲线的异常波动，需大量增加平均速度为64~ 80 km·h-1 范围内的工况数据量。本文的研究结果对工况和排放数据的采集工作有实际指导意 义，可有效克服曲线异常波动问题，提高排放因子结果可靠性，为节能减排工作提供支持。     

Exploring the link between the neighborhood typologies,bicycle infrastructure and commuting cycling over time and the potential impact on commuter GHG emissions

This paper investigates the evolution of urban cycling in Montreal, Canada and its link to both built environment indicators and bicycle infrastructure accessibility. The effect of new cycling infrastructure on transport-related greenhouse gas (GHG) emissions is then explored. More specifically, we aim at investigating how commuting cycling modal share has evolved across neighborhood built-environment typologies and over time in Montreal, Canada. For this purpose, automobile and bicycle trip information from origin–destination surveys for the years 1998, 2003 and 2008 are used. Neighborhood typologies are generated from different built environment indicators (population and employment density, land use diversity, etc.). Furthermore, to represent the commuter mode choice (bicycle vs automobile), a standard binary logit and simultaneous equation modeling approach are adopted to represent the mode choice and the household location. Among other things, we observe an important increase in the likelihood to cycle across built environment types and over time in the study region. In particular, urban and urban-suburb neighborhoods have experienced an important growth over the 10 years, going from a modal split of 2.8–5.3% and 1.4–3.0%, respectively. After controlling for other factors, the model regression analysis also confirms the important increase across years as well as the significant differences of bicycle ridership across neighborhoods. A statistically significant association is also found between the index of bicycle infrastructure accessibility and bike mode choice – an increase of 10% in the accessibility index results in a 3.7% increase in the ridership. Based on the estimated models and in combination with a GHG inventory at the trip level, the potential impact of planned cycling infrastructure is explored using a basic scenario. A reduction of close to 2% in GHG emissions is observed for an increase of 7% in the length of the bicycle network. Results show the important benefits of bicycle infrastructure to reduce commuting automobile usage and GHG emissions.     

Vehicular emissions prediction with CART-BMARS hybrid models

Vehicular emission models play a key role in the development of reliable air quality modeling systems. To minimize uncertainties associated with these models, it is essential to match the high-resolution requirements of emission models with up-to-date information. However, these models are usually based on average trip speed, not on environmental parameters like ambient temperature, and vehicle’s motion characteristics, such as speed, acceleration, load and power. This contributes to the degradation of its predictive performance. In this paper, we propose to use the non-parametric Classification and Regression Trees (CART), the Boosting Multivariate Adaptive Regression Splines (BMARS) algorithm and a combination of them in hybrid models to improve the accuracy of vehicular emission prediction using on-board measurements and the chassis dynamometer testing. The experimental comparison between the proposed CART-BMARS hybrid model with the BMARS and artificial neural networks (ANNs) algorithms demonstrates its effectiveness and efficiency in estimating vehicular emissions.     

Integrating multi-source maritime information to estimate ship exhaust emissions under wind,wave and current conditions

How to accurately calculate ship exhaust emissions has become urgent needs. In this paper, multi-source maritime information is integrated to estimate ship exhaust emissions under ocean environment. Influences of wind, wave and current on ship speed are firstly analyzed and mathematically modeled. Based on the influences, ocean environment information and ship trajectories are integrated to identify ship activities exactly. After that, ship activity based calculation method is present to obtain exhaust emissions from ship in various activities. Contribution ratios of different ship type and ship activities have been further discussed. In a case study of Ningbo-Zhoushan port in China, greenhouse gas (CO₂, CO, SO_x, NO_x and PM) emissions from ships in 2014 calculated by the proposed method are 8.72 × 10⁵ ton, 2.07 × 10³ ton, 1.47 × 10⁴ ton, 2.60 × 10⁴ ton and 1.40 × 10³ ton respectively. The maximum error is under 10%. Experimental results illustrate that the proposed method can produce more accurate ship exhaust emissions than traditional method under ocean environment conditions.     

电力推进技术在渡船中的应用

近年来,国家陆续出台了关于长江生态保护的相关文件。随着电力推进技术在节能减排方面的优势显现,常规动力渡船存在的问题显而易见,如较长传动轴增加了能量损耗,降低了能源效率;柴油机的响应较慢,影响船舶的机动性;柴油机的燃烧不充分导致燃油的过多消耗,以及柴油机直驱渡船的动力推进装置占据了机舱的大部分空间。本文结合电力推进渡船的应用情况,针对上述常规推进渡船的缺点,对船舶动力系统进行了改进,采用全回转电力推进取代原先柴油机直驱,电站采用高压共轨电喷式柴油机带动发电机发电,经整流实现直流组网后,统一为全船提供动力和日常用电。     

控制船舶尾气排放水污染对策分析

文中从介绍船舶尾气水污染的现状入手,梳理了国际公约、国内法规对船舶尾气排放水污染控制要求,分析了目前船舶尾气排放水污染控制方面的短板,提出了解决对策。