Giving green to get green? Incentives and consumer adoption of hybrid vehicle technology

Federal, state, and local governments use a variety of incentives to induce consumer adoption of hybrid-electric vehicles. We study the relative efficacy of state sales tax waivers, income tax credits, and non-tax incentives and find that the type of tax incentive offered is as important as the generosity of the incentive. Conditional on value, sales tax waivers are associated with more than a ten-fold increase in hybrid sales relative to income tax credits. In addition, we examine how adoption varies with fuel prices. Rising gasoline prices are associated with greater hybrid vehicle sales, but this effect operates almost entirely through high fuel-economy vehicles. By comparing consumer response to sales tax waivers and estimated future fuel savings, we estimate an implicit discount rate of 14.6% on future fuel savings.     

Optimization of the recovery of plastics for recycling by density media separation cyclones

Material recovery processes are presented as the optimum option for recycling plastic wastes as a means of recovering hydrocarbon resources. There exist a large variety of automated material recovery processes for recycling of such wastes but each with significant limitations. Of these, the separation based on differences in densities is advocated as the optimum process either for producing recycled products or preparing wastes for subsequent recovery processing.Density separation processes based on cyclone type density media separation (DMS) is presented as an important, potential method for increasing plastics recycling process capacities. It is demonstrated to have the capacity to separate a significantly larger range of particle sizes than those presently processed industrially. The mathematical relationship for the prediction of quality of typical LARCODEMS type density media separations by particle size and density as expressed by the Ecart Probable is presented.A proposed device configuration is presented for density media separation to optimize the recovery and purity of both density fractions produced. It is also suggested that to be economically viable, a large scale of operation is required for industrial plastics recycling operations recovering and producing a number of different plastics with a purity to be used as a substitute for virgin material.     

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.     

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.     

Dangerous student car drop-off behaviors and child pedestrian–motor vehicle collisions: An observational study

Objectives: The objective of this study was to examine the association between dangerous student car drop-off behaviors and historical child pedestrian–motor vehicle collisions (PMVCs) near elementary schools in Toronto, Canada.

Methods: Police-reported child PMVCs during school travel times from 2000 to 2011 were mapped within 200 m of 118 elementary schools. Observers measured dangerous student morning car drop-off behaviors and number of children walking to school during one day in 2011. A composite score of school social disadvantage was obtained from the Toronto District School Board. Built environment and traffic features were mapped and included as covariates. A multivariate Poisson regression was used to model the rates of PMVC/number of children walking and dangerous student car drop-off behaviors, adjusting for the built environment and social disadvantage.

Results: There were 45 child PMVCs, with 29 (64%) sustaining minor injuries resulting in emergency department visits. The mean collision rate was 2.9/10,000 children walking/year (SD = 6.7). Dangerous drop-off behaviors were observed in 104 schools (88%). In the multivariate analysis, each additional dangerous drop-off behavior was associated with a 45% increase in collision rates (incident rate ratio [IRR] = 1.45, 95% confidence interval [CI], 1.02, 2.07). Higher speed roads (IRR = 1.27, 95% CI, 1.13, 1.44) and social disadvantage (IRR = 2.99, 95% CI, 1.03, 8.68) were associated with higher collision rates.

Conclusions: Dangerous student car drop-off behaviors were associated with historical nonfatal child PMVC rates during school travel times near schools. Some caution must be taken in interpreting these results due small number of events and limitations in the data collection, because collision data were collected historically over a 12-year period, whereas driving behavior was only observed on a single day in 2011. Targeted multifaceted intervention approaches related to the built environment, enforcement, and education could address dangerous drop-off behaviors near schools to reduce child PMVCs and promote safe walking to school.     

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.     

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.