Planning hierarchical urban transit systems for reductions in greenhouse gas emissions

Public transit systems with high occupancy can reduce greenhouse gas (GHG) emissions relative to low-occupancy transportation modes, but current transit systems have not been designed to reduce environmental impacts. This motivates the study of the benefits of design and operational approaches for reducing the environmental impacts of transit systems. For example, transit agencies may replace level-of-service (LOS) by vehicle miles traveled (VMT) as a criterion in evaluating design and operational changes. In previous work, we explored the unintended consequences of lowering transit LOS on emissions in a single-technology transit system. Herein, we extend the analysis to account for a more realistic case: a transit system with a hierarchical structure (trunk and feeder lines) providing service to a city where demand is elastic. By considering the interactions between the trunk and the feeder systems, we provide a quantitative basis for designing and operating integrated urban transit systems that can reduce GHG emissions and societal costs. We find that highly elastic transit demand may cancel emission reduction potentials resulting from lowering LOS, due to demand shifts to lower occupancy vehicles. However, for mass transit modes, these potentials are still significant. Transit networks with buses, bus rapid transit or light rail as trunk modes should be designed and operated near the cost-optimal point when the demand is highly elastic, while this is not required for metro. We find that the potential for unintended consequences increases with the size of the city. Our results are robust to uncertainties in the costs and emissions parameters.     

Optimal bus fleet management strategy for emissions reduction

Transportation is a major cause for environmental degradation via exhaust emissions. For many transit-oriented metropolitan areas, bus trips often constitute a sizeable mode share. Managing the bus fleet, in particular updating buses to comply with the newer emissions standards, therefore, can have a substantial impact on transportation-induced air quality. This paper presents the approach of remaining life additional benefit–cost (RLABC) analysis for maximising the total net benefit by either early-retiring or retrofitting the current bus fleet within their lifespans. By referring to the net benefits for different bus types estimated by RLABC analysis, the most beneficial management scheme for the current bus fleet can be identified. Optimal bus fleet management (BFM) models based on the RLABC analysis for the operator and the government are developed. Then a government subsidy plan is produced to achieve win–win solutions, which will offer efficient and flexible management schemes. To illustrate the approach, the largest bus company in Hong Kong, which carries more than 23% of the total trips in Hong Kong, is taken as a case study example. Instead of adopting a fixed retirement plan, such as replacing buses at the age of 17 as is currently practised, the proposed method develops an optimal BFM scheme that progressively phases out buses or retrofits them. This study produces promising results to demonstrate the large benefit of this approach for optimal bus fleet management.     

基于多源数据的公交车能耗碳排放测算模型

公交车能耗碳排放强度与车辆、线路和驾驶员有显著相关关系，为精准刻画其能耗碳排放强度特征，整合OBD监测数据、加油(气)数据、运营排班数据等多源数据资源. OBD监测数据和加油(气)数据呈显著的线性关系，证明修正后的OBD监测数据可满足分析要求. 搭建“速度-能耗碳排放强度曲线”测算模型，幂函数关系的拟合优度R2 =0.972 6 为最高. 实证研究发现，平均速度在10~60 km/h 变化时，液化天然气(LNG)车比柴油车能耗碳排放强度高 3.3%~33.7%，双层车比铰接车高2.4%~13.3%；LNG铰接车在不同线路、相同速度下的强度相差9.6%；不同驾驶员在相同线路的能耗碳排放强度可相差24.2%. 模型为各城市基于多源数据开展公交能耗碳排放目标设定提供数据支撑.     

Did Chinese cities that implemented driving restrictions see reductions in PM10?

Imposing driving restrictions is becoming increasingly popular as a policy intended to control urban air pollution. Existing studies on this topic offer highly mixed observations, and each study tends to focus on only one city. In this paper, we used 11 Chinese cities with driving restrictions as the treatment group, and compared them to other cities that did not implement the policy. Based on a propensity score matching and difference-in-difference analysis, we found no evidence of a decrease in PM10 concentrations in cities after they implemented driving restrictions. This finding may be attributed to an increase in the number of cars in these cities after implementing driving restrictions, but we also found no evidence of an improvement in air quality for a given number of cars after implementation of the policies.     

Subjective-utility travel time budget modeling in the stochastic traffic network assignment

ABSTRACT

In this article, we propose a new model called subjective-utility travel time budget (SU-TTB) model to capture travelers' risk-averse route choices. In the travel time budget (TTB) and mean-excess travel time (METT) model, a predefined confidence level is needed to capture the risk-aversion in route choice. Due to the day-to-day route travel time variations, the exact confidence level is hard to be predicted. With the SU-TTB model, we assume travelers' confidence level belongs to an interval that they may comply with in the route choice. The two main components of SU-TTB are the utility function and the TTB model. We can show that the SU-TTB can be reduced to the TTB and METT model with proper utility function for the confidence levels. We can also prove its equivalence with our recently proposed nonlinear-expectation route travel time (NERTT) model in some cases and give some new interpretation on the NERTT with this equivalence. Finally, we formulate the SU-TTB model as a variational inequality (VI) problem to model the risk-averse user equilibrium (RAUE), termed as generalized RAUE (GRAUE). The GRAUE is solved via a heuristic gradient projection algorithm, and the model and solution algorithm are demonstrated with the Braess's traffic network and the Nguyen and Dupuis's traffic network.     

4缸柴油机停缸仿真及试验研究

采用停缸技术对小型4缸柴油机的燃油消耗率和排放进行了仿真和试验研究。利用GT-Power建立模型并模拟了停缸位置对燃油消耗率的影响,结合传热损失等因素确定了试验停缸位置。在断油式停缸和断油断气式停缸模式下进行试验和燃烧分析。试验结果表明:停缸后缸内等容度降低;断油式停缸后燃油消耗率和NOx增大但炭烟减少;断油断气式停缸后部分试验点燃油消耗率降低,但NOx和炭烟排放增加。     

乙醇汽油对车辆颗粒物排放的影响

在符合国Ⅰ、国Ⅲ、国Ⅴ标准的3辆试验车上,分别燃用国Ⅴ汽油、低芳烃E10、低烯烃E10 3种燃料,进行了NEDC和WLTC工况下的常温冷起动排放试验,重点对颗粒物(PM)排放量和粒子数量(PN)进行分析。结果表明:在两种工况下,燃用乙醇汽油相比普通汽油能大幅降低车辆的PM排放,低芳烃E10对国Ⅰ和国Ⅲ车辆PM降低效果最明显,分别下降19%和35%,低烯烃E10对国Ⅴ车辆PM降低效果最好,下降46%;在WLTC工况下燃用乙醇汽油能大幅降低车辆PN排放,其中低芳烃E10平均降低43%,低烯烃E10平均降低32%。     

面向控制的SCR催化转化器温度模型

为了建立面向控制的SCR催化器温度模型,根据能量守恒和质量守恒方程并考虑热平衡中所涉及的换热过程不同,建立了4种SCR催化器温度的数学模型,并利用Matlab/Simulink构建图形化的计算模型。采用柴油机欧洲稳态循环(ESC)和欧洲瞬态循环(ETC)条件下的台架实测数据对模型进行检验,基于最大离散程度、拟合度和计算时间3个指标对模型进行评价和比较。结果表明,考虑催化器与废气和周围环境对流换热的温度模型具有良好的预测精度和实时性,更适合用于SCR控制策略。     

轻型汽油车N_2O排放特性研究

选择1辆满足国Ⅴ排放标准的轻型汽油车作为试验样车,应用全流稀释排放测试系统在FTP75和US06测试循环下,对车辆在不同测试工况下的N_2O排放水平、车辆N_2O排放的影响因素以及N_2O排放随着车辆里程增加的劣化情况进行了研究。研究结果表明:FTP75循环下的N_2O排放结果高于US06循环,前者是后者的4倍左右;在冷起动阶段,由于催化剂没有达到正常的工作温度,车辆会产生较多的N_2O排放,且随着燃油硫含量的增加,车辆的N_2O排放呈现上升的趋势;随着车辆里程的不断增加,车辆的N_2O排放存在一定程度的劣化。     

低温独立液舱曲面外板加工减薄量评估

基于耐低温合金材料的非线性特性,以某液化气船的低温独立液舱曲面外板加工成形过程为研究对象,研究其塑形变形过程及机理。利用ABAQUS作为计算分析工具,建立了板材原料及上、下加工模具的分析模型,给定冲压成形的时间和初始速度,并设定时间步长,考察每个时间步长的计算结果,分析了其加工过程中的弹塑性变形过程,评估了低温合金材料在加工过程中的板厚变化情况,并与实际加工测量值进行对比,验证了模型和计算分析过程的准确性。为各类低温独立液舱的设计和材料尺寸选用提供了技术支持和指导。