Simulating the air quality impacts of traffic calming schemes in a dense urban neighborhood

In this study, the effects of isolated traffic calming measures and area-wide calming schemes on air quality in a dense neighborhood were estimated using a combination of microscopic traffic simulation, emission, and dispersion modeling. Results indicated that traffic calming measures did not have as large an effect on nitrogen dioxide (NO₂) concentrations as the effect observed on nitrogen oxide (NO_x) emissions. Changes in emissions resulted in highly disproportional changes in pollutant levels due to daily meteorological conditions, road geometry and orientation with respect to the wind. Average NO₂ levels increased between 0.1% and 10% with respect to the base-case while changes in NO_x emissions varied between 5% and 160%. Moreover, higher wind speeds decreased NO₂ concentrations on both sides of the roadway. Among the traffic calming measures, speed bumps produced the highest increases in NO₂ levels.     

基于运行工况的旅游城镇小客车排放测算

获取车辆的实际运行工况,是准确进行污染物排放测算的关键工作.以韶山为例,通过调查本地驾驶员和外地驾驶员在不同道路类型上驾驶小客车行驶的逐秒GPS数据,统计分析相应的运行工况分布并导入MOVES模型,采用先按类分解再聚类合计的方法测算污染物排放因子,据此评估交通管理与控制策略对污染物排放的影响.研究发现,采用MOVES默认的运行工况分布,得出的排放结果将会产生较大误差;相对于外地驾驶员,韶山本地驾驶员平均车速更高,车辆比功率分布更离散,运行工况的差别使得本地驾驶员的污染物排放因子在所有道路类型上全部高于外地驾驶员,景区道路上高出更多;韶山实施游客换乘方案后, 2016年8月各污染物总减排比例为73%~78%.     

A simulation of transit bus emissions along an urban corridor: Evaluating changes under various service improvement strategies

This study investigates the impacts of transit improvement strategies on bus emissions along a busy corridor in Montreal, Canada. The local transit provider, Société de Transport de Montréal, has implemented a number of strategies which include the use of smart cards, limited-stop (express bus) service, and reserved bus lanes along this corridor. Using data collected on-board for instantaneous speeds and stop-level ridership, we estimated bus emissions of greenhouse gases and other pollutants at three levels: road segment, bus-stop, and per passenger. A regression of segment-level emissions against a number of explanatory variables reveals that reserved bus lanes and express bus service reduce emissions significantly. On the other hand, smart card use reduces idling emissions compared to other fare payment methods. Our findings are of most relevance for transit planners who are seeking to implement different strategies to reduce emissions and improve transit performance.     

Emission evaluation of inter-vehicle safety warning information systems

Driver inattentiveness is one of critical factors contributing to vehicle crashes. The inter-vehicle safety warning information system (ISWS) is a technology to enhance driver attentiveness by providing warning messages about upcoming hazards using connected vehicle environments. A novel feature of the proposed ISWS is its ability to detect hazardous driving events, such as abrupt accelerations and lane changes, which are defined as moving hazards with a higher potential of causing crashes. This study evaluated the effectiveness of the ISWS in reducing vehicle emissions and its potential for traffic congestion mitigation. This study included a field experiment that documented actual vehicle maneuvering patterns for abrupt accelerations and lane changes, which were used for more realistic simulation evaluations, in addition to normal accelerations and lane changes. Probe vehicles equipped with customized on-board units consisting of a global positioning system (GPS) device, accelerometer, and gyro sensor were used to obtain the vehicle maneuvering data. A microscopic simulator, VISSIM, was used to simulate a driver’s responsive behavior when warning messages were delivered. A motor vehicle emission simulator (MOVES) was then used to estimate vehicle emissions. The results show that reduction in vehicle emissions increased when the ISWS’s market penetration rate (MPR) and the congestion level of the traffic conditions increased. The maximum CO and CO₂ emission reductions achieved were approximately 6% and 7%, respectively, under LOS D traffic conditions. The outcomes of this study can be valuable for deriving smarter operational strategies for ISWS to account for environmental impacts.     

Sensitive analysis of emission rates in MOVES for developing site-specific emission database

With the rapid social and economic development, vehicle emissions have been identified as a major source of urban air pollutions in China. Therefore, the study on vehicle emission estimations is necessary. In light of the limitation of emission data for establishing a local comprehensive emission database, this paper analyzes the characteristics of emission rates in MOVES released by U.S. Environmental Protection Agency (EPA) to investigate the feasibility and to design a method for developing site-specific emission database. Sensitive analysis for model year, age group and speed interval is performed, and the regularity is concluded. The result shows that emission rates are almost constant with model year, but increase with age groups because of emission deterioration. With respect to speed intervals, the emission rates in 25–50 mph are higher than both those <25 mph and >50 mph in the same VSP (vehicle specific power) bins. In addition, an analysis of local emission data in Beijing is conducted to build the relationship between vehicle activities and emission rates. After that, a comparison of emission rates by VSP bins in MOVES and in local database is conducted in this study. The result shows that the absolute values are different because of regulatory emission standards, fuel quality, and other factors. However, the relative changes described by normalizing emission rates have a good consistency. Hence, the regularities of emission rates by VSP bins in MOVES can be used to develop local emission database in Beijing.     

Characteristics of operating mode distributions of light duty vehicles by road type,average speed,and driver type for estimating on-road emissions: Case study of Beijing

Abstract

Researchers have collected extensive vehicle activity data in Beijing using GPS and attempted to develop a comprehensive database of facility- and speed-specific operating mode (OpMode) distributions of various vehicle types for estimating on-road vehicle emissions. This study developed the specific OpMode distributions of light duty vehicles (LDVs) for both restricted access and unrestricted access road types at various average speeds for characteristic analysis. (1) Strong patterns are found in the variations in OpMode distributions with the increase in the average speed: the time fraction of Decelerating/Braking remains less than 7%. The fraction of Idling decreases dramatically from 95% to 0%, while the fraction of Cruising/Accelerating increases from 2% to 94%. The fraction of Coasting increases to 28% and then decreases. (2) The time fractions for restricted access and unrestricted access are significantly different at the same average speeds, especially in Operating Modes #0, #1, #11, #12, #13, #14, #21, and #22, possibly causing an error of 20% in the emissions estimations. (3) Taxis show different OpMode distributions than those for private cars in the operating modes of Decelerating/Braking, Idling, and high-VSP modes, especially at low average speeds. The differences are derived from the more skillful driving behaviors of taxi drivers and may cause an estimation error of over 10%. Thus, the activities of taxis and private cars should be modeled separately for on-road emissions estimations.     

Development of simulated driving cycles for light,medium, and heavy duty trucks: Case of the Toronto Waterfront Area

Driving cycles are an important input for state-of-the-art vehicle emission models. Development of a driving cycle requires second-by-second vehicle speed for a representative set of vehicles. Current standard driving cycles cannot reflect or forecast changes in traffic conditions. This paper introduces a method to develop representative driving cycles using simulated data from a calibrated microscopic traffic simulation model of the Toronto Waterfront Area. The simulation model is calibrated to reflect road counts, link speeds, and accelerations using a multi-objective genetic algorithm. The simulation is validated by comparing simulated vs. observed passenger freeway cycles. The simulation method is applied to develop AM peak hour driving cycles for light, medium and heavy duty trucks. The demonstration reveals differences in speed, acceleration, and driver aggressiveness between driving cycles for different vehicle types. These driving cycles are compared against a range of available driving cycles, showing different traffic conditions and driving behaviors, and suggesting a need for city-specific driving cycles. Emissions from the simulated driving cycles are also compared with EPA’s Heavy Duty Urban Dynamometer Driving Schedule showing higher emission factors for the Toronto Waterfront cycles.     

Impact of license plate restriction policy on emission reduction in Hangzhou using a bottom-up approach

Many emission models have been developed for estimating the impact of transport policies on vehicle emissions. Macroscopic models, such as MOBILE and COPERT, are used for area analysis, while microscopic models, such as CMEM, are applied for corridor analysis. It is well known that driving dynamics are critical for estimating vehicle emissions. MOVES can be used for both macroscopic and microscopic emission analysis, and its advantage lies in the consideration of driving dynamics. Using a bottom-up approach, we study the impact of license plate restriction policy on vehicle emission reduction by localizing the emission rates in MOVES according to the vehicle emission standards in China. We implement the approach to evaluate the impact on the total vehicle emissions in Hangzhou, China before and after the implementation of license plate restriction policy. In the restricted region, the reductions of total Vehicle Kilometer Traveled (VKT) and total emissions are 9.6% and 6.9%, respectively. The result shows that the license plate restriction policy is effective in achieving the targeted emission reduction.     

Evaluating policies to reduce greenhouse gas emissions from private transportation

This paper proposes a model system to forecast household greenhouse gas emissions (GHGEs) from private transportation. The proposed model combines an integrated discrete-continuous car ownership model with MOVES 2014. Four modeling components are calibrated and applied to the calculation of GHGEs: vehicle quantity, vehicle type and vintage, miles traveled, and rates of GHGEs. The model is applied to the Washington D.C. Metropolitan Area. Three tax schemes are evaluated: vehicle ownership tax, purchase tax and fuel tax. We calculate that the average GHGEs per vehicle is 5.15 tons of carbon dioxide-equivalent (CO₂E) gases. Our results show that: (a) a fuel tax is the most effective way to reduce vehicle GHGEs, especially for households with fewer vehicles; (b) a purchase tax reduces vehicle GHGEs mainly by decreasing vehicle quantity for households with more vehicles; and (c) an ownership tax reduces vehicle GHGEs by decreasing both vehicle quantity and miles traveled.     

An integrated modeling approach for facilitating emission estimations of alternative fueled vehicles

This paper develops an integrated model for reliable estimation of daily vehicle fuel savings and emissions using an integrated traffic emission modeling approach created by incorporating the US Environmental Protection Agency’s vehicle emission model, MOVES, and the PARAMICS microscopic traffic simulation package. A case study is conducted to validate the model using a well-calibrated road network in Greenville, South Carolina. For each transportation fuel considered, both emission and fuel consumption impacts are evaluated based on market shares.