Regulated emission characteristics of in-use LNG and diesel semi-trailer towing vehicles under real driving conditions using PEMS

On-road driving emissions of six liquefied natural gas(LNG) and diesel semi-trailer towing vehicles(STTVs) which met China Emission Standard IV and V were tested using Portable Emission Measurement System(PEMS) in northern China.Emission characteristics of these vehicles under real driving conditions were analyzed and proved that on-road emissions of heavy-duty vehicles(HDVs) were underestimated in the past.There were large differences among LNG and diesel vehicles, which also existed between China V vehicles and China IV vehicles.Emission factors showed the highest level under real driving conditions, which probably be caused by frequent acceleration, deceleration, and start-stop.NOx emission factors ranged from 2.855 to 20.939 g/km based on distance-traveled and 6.719–90.557 g/kg based on fuel consumption during whole tests, which were much higher than previous researches on chassis dynamometer.It was inferred from tests that the fuel consumption rate of the test vehicles had a strong correlation with NOx emission, and the exhaust temperature also affected the efficiency of Selected Catalytic Reduction(SCR) aftertreatment system, thus changing the NOx emission greatly.THC emission factors of LNG vehicles were 2.012–10.636 g/km, which were much higher than that of diesel vehicles(0.029–0.185 g/km).Unburned CH_4 may be an important reason for this phenomenon.Further on-road emission tests, especially CH_4 emission test should be carried out in subsequent research.In addition, the Particulate Number(PN) emission factors of diesel vehicles were at a very high level during whole tests, and Diesel Particulate Filter(DPF)should be installed to reduce PN emission.     

北京市清洁汽车可持续发展战略与对策研究

在分析北京市清洁车行动实施现状的基础上，提出了北京市清洁汽车行动的基本原则与可持续发展战略及对策。     

中国国道和省道机动车尾气排放特征

近年来,随着我国机动车保有量的持续增长,机动车排放已成为我国重要的大气污染物来源之一.现有的机动车排放研究多关注城市内的机动车大气污染物排放,针对城市间的大气污染物排放研究较少.我国城市间交通道路主要包括国道和省道,截止至2015年我国国道里程18.53万km、省道里程32.97万km,约占全国等级公路总里程的13%,因此开展我国国道和省道机动车大气污染物排放研究十分重要.本研究基于全国国道和省道交通监测站的年均监测数据,采用环境保护部发布的《道路机动车大气污染物排放清单编制技术指南(试行)》中的指导方法,计算了2015年我国国道和省道机动车的大气污染物排放清单,分析了污染物排放的时空分布特征.结果表明,我国国道和省道公路机动车排放的一氧化碳(CO)、氮氧化物(NO_x)、颗粒物(PM)和碳氢化合物(HC)排放量分别占全国机动车污染物总排放量的4.5%、27.9%、14.4%和7.7%;不同车型对国道和省道机动车大气污染物排放的分担率不同,其中大货车是NO_x、PM_(10)、PM_(2.5)的主要来源,摩托车是CO和HC的主要来源;不同道路类型中各车型的大气污染物排放分担率也不同,如高速路上大货车是NO_x、PM_(10)和PM_(2.5)的主要来源,普通道路上大客车和大货车是NO_x、PM_(10)和PM_(2.5)的主要来源.     

Impacts of converting from leaded to unleaded gasoline on ambient lead concentrations in Jakarta metropolitan area

Total suspended particulate mater （TSP） concentrations were monitored for one year from July 2000 and for one year from April 2003 in Jakarta City. Thirteen elemental TSP components, aluminum （Al）, sodium （Na）, iron （Fe）, lead （Pb）, potassium （K）, zinc （Zn）, titanium （Ti）, manganese （Mn）, bromine （Br）, copper （Cu）, chromium （Cr）, nickel （Ni）, and vanadium （V） were analyzed by a sequential X-ray fluorescence spectrometer. Al, Na, Fe, K, and Pb were major components at most of the sampling locations in 2000. However, only Pb in 2003 dramatically decreased to one tenth. The phase-out of leaded gasoline began on July 1, 2001 in Jakarta City and lead content in gasoline decreased to one tenth, too. The decrease in Pb concentration was a result of the phase-out of leaded gasoline, as lead emissions mainly are exhaust gas from vehicles.     

柴油车尾气颗粒物排放现状评价

对2013年哈尔滨市不同供油方式的柴油车排气细颗粒物或黑碳测量参数—光吸收系数进行了统计分析,结果表明:涡轮增压和自然吸气供油方式光吸收系数均值分别为1.39 m-1和1.27 m-1,超标率分别为5.8%和2.4%,采用颗粒物控制措施及排气装置强制维护降低了颗粒物排放,符合排放标准。     

CFD Prediction of Air Quality in the Area between Two City Vehicular Tunnels Considering Moving Cars

Concentration fields of different pollutants that spread outside two roadtunnels predicted with a CFD code will be presented. The solution domain represents the city area located between two tunnel outlets – tunnel Strahov and tunnel Mrazovka in Prague. The vicinity of both tunnels is a heavily built up area with tall buildings forming typical street canyons. The CFD modelling predicts the situation after the tunnel Mrazovka will be finished and traffic will increase considerably between both tunnels. Namely, an interest was given to the prediction of dispersion of emissions leaving both tunnel and the area touched by the traffic. For the CFD predictions, a method previously developed for moving vehicles was used. The method uses combination of Eulerian and Lagrangian approaches to moving objects and is capable of modeling different speeds and traffic rates of cars as well as traffic-induced turbulence. Influence of several meteorological parameters was studied, namely wind speed and direction and traffic parameters, like traffic rates and speed of cars. The method separates contributions from different sources to the total concentration field, namely from background, tunnel outlet and roadway. Results are presented in the form of horizontal and vertical concentration fields of NO_x.     

Energy consumption estimation model for dual-motor electric vehicles based on multiple linear regression

ABSTRACT

The drive range of electric vehicle (EV) is one of the major limitations that impedes its universalism. A great deal of research has been devoted to drive range improvement of EV, an accurate and efficiency energy consumption estimation plays a crucial role in these researches. However, the majority of EV’s energy consumption estimation models are based on single motor EV, these models are not suitable for dual-motor EVs, which are composed of more complex transmission mechanisms and multiple operating modes. Thus, an energy consumption estimation model for dual-motor EV is proposed to estimate battery power. This article focuses on studying the operating modes and system efficiency in each operating mode. The limitation of working area of each mode ensures the vehicle dynamic performance, then PSO algorithm is adopted to optimize the torque (speed) distribution between two motors to improve the system efficiency in the coupled driving mode. Finally, the energy consumption estimation model is established by multiple linear regression (MLR). The result shows that the proposed model has a high precision in energy consumption estimation of dual-motor EV.     

Risk-based optimal operation of hybrid power system using multiobjective optimization

ABSTRACT

This paper solves an optimal generation scheduling problem of hybrid power system considering the risk factor due to uncertain/intermittent nature of renewable energy resources (RERs) and electric vehicles (EVs). The hybrid power system considered in this work includes thermal generating units, RERs such as wind and solar photovoltaic (PV) units, battery energy storage systems (BESSs) and electric vehicles (EVs). Here, the two objective functions are formulated, i.e., minimization of operating cost and system risk, to develop an optimum scheduling strategy of hybrid power system. The objective of proposed approach is to minimize operating cost and system risk levels simultaneously. The operating cost minimization objective consists of costs due to thermal generators, wind farms, solar PV units, EVs, BESSs, and adjustment cost due to uncertainties in RERs and EVs. In this work, Conditional Value at Risk (CVaR) is considered as the risk index, and it is used to quantify the risk due to intermittent nature of RERs and EVs. The main contribution of this paper lies in its ability to determine the optimal generation schedules by optimizing operating cost and risk. These two objectives are solved by using a multiobjective-based nondominated sorting genetic algorithm-II (NSGA-II) algorithm, and it is used to develop a Pareto optimal front. A best-compromised solution is obtained by using fuzzy min-max approach. The proposed approach has been implemented on modified IEEE 30 bus and practical Indian 75 bus test systems. The obtained results show the best-compromised solution between operating cost and system risk level, and the suitability of CVaR for the management of risk associated with the uncertainties due to RERs and EVs.     

Effectiveness of primary enforcement safety belt laws and enhanced enforcement of safety belt laws: a summary of the Guide to Community Preventive Services systematic reviews

BACKGROUND: The use of safety belts is the single most effective means of reducing fatal and nonfatal injuries in motor-vehicle crashes. This paper summarizes the systematic reviews of two interventions to increase safety belt use: primary enforcement safety belt laws and enhanced enforcement of safety belt laws. The reviews were previously published in the American Journal of Preventive Medicine. METHODS: We conducted the systematic reviews using the methodology developed for the Guide to Community Preventive Services. RESULTS: These reviews provide strong evidence that primary laws are more effective than secondary laws in increasing safety belt use and decreasing fatalities and that enhanced enforcement is effective in increasing safety belt use. Increases in belt use are generally highest in states with low baseline rates of belt use. DISCUSSION: Primary safety belt laws and enhanced enforcement programs tend to result in greater increases in usage rates for target groups with lower baseline rates. Concerns regarding public opposition to these interventions may impede their implementation in some jurisdictions. However, surveys indicate that a substantial majority of the public supports implementation of both primary laws and enhanced enforcement programs. CONCLUSION: Based on the strong evidence for effectiveness of primary safety belt laws and enhanced enforcement programs, the Task Force on Community Preventive Services recommended that all states enact primary safety belt laws and that communities implement enhanced enforcement programs.     

The connecticut indirect source review: A methodology and model for evaluating CO concentrations

The body of information presented in this paper is directed to air pollution engineers who are concerned with the effect of indirect sources on ambient concentrations of carbon monoxide (CO). Data taken under controlled conditions are used to empirically derive and calibrate a model for predicting CO concentrations in the vicinity of roadway intersections and other points of possible vehicular congestion. Since the predicted free flow CO contribution of vehicles traveling at normal road speeds is relatively low, it is concluded that idling vehicles at points of congestion are the major cause of CO violations, and that state and federal programs should place more emphasis on relieving congestion and reducing idling emission rates in new vehicles.