Real-Time Black Carbon Emissions from Light-Duty Passenger Vehicles Using a Portable Emissions Measurement System

Black carbon(BC)is considered the second largest anthropogenic climate forcer,but the radiative effects of BC are highly correlated with its combustion sources.On-road vehicles are an important source of anthropogenic BC.However,there are major uncertainties in the estimates of the BC emissions from on-road light-duty passenger vehicles(LDPVs),and results obtained with the portable emissions measurement system(PEMS)method are particularly lacking.We developed a PEMS platform and evaluated the on-road BC emissions from ten in-use LDPVs.We demonstrated that the BC emission factors(EFs)of gasoline direction injection(GDI)engine vehicles range from 1.10 to 1.56 mg.km^(-1),which are higher than the EFs of port fuel injection(PFI)engine vehicles(0.10–0.17 mg.km^(-1))by a factor of 11.The BC emissions during the cold-start phase contributed 2%–33%to the total emissions.A strong correlation(R^(2)=0.70)was observed between the relative BC EFs and average vehicle speed,indicating that traffic congestion alleviation could effectively mitigate BC emissions.Moreover,BC and particle number(PN)emissions were linearly correlated(R^(2)=0.90),and compared to PFI engine vehicles,the instantaneous PN-to-BC emission rates of GDI engine vehicles were less sensitive to vehicle specific power-to-velocity(VSPV)increase in all speed ranges.

The Future Trend of E-Mobility in Terms of Battery Electric Vehicles and Their Impact on Climate Change: A Case Study Applied in Hungary

The transportation sector is responsible for 25% of the total Carbon dioxide (CO2) emissions, whereas 60.6% of this sector represents small and medium passenger cars. However, as noted by the European Union Long-term strategy, there are two ways to reduce the amount of CO2 emissions in the transportation sector. The first way is characterized by creating more efficient vehicles. In contrast, the second way is characterized by changing the fuel used. The current study addressed the second way, changing the fuel type. The study examined the potential of battery electric vehicles (BEVs) as an alternative fuel type to reduce CO2 emissions in Hungarys transportation sector. The study used secondary data retrieved from Statista and stata.com to analyze the future trends of BEVs in Hungary. The results showed that the percentage of BEVs in Hungary in 2022 was 0.4% compared to the total number of registered passenger cars, which is 3.8 million. The simple exponential smoothing (SES) time series forecast revealed that the number of BEVs is expected to reach 84,192 in 2030, indicating a percentage increase of 2.21% in the next eight years. The study suggests that increasing the number of BEVs is necessary to address the negative impact of CO2 emissions on society. The Hungarian Ministry of Innovation and Technologys strategy to reduce the cost of BEVs may increase the percentage of BEVs by 10%, resulting in a potential average reduction of 76,957,600 g/km of CO2 compared to gasoline, diesel, hybrid electric vehicles (HEVs), and plug-in hybrid vehicles (PHEVs).

Modeling the Effect of Variable Timing of the Exhaust Valves on SI Engine Emissions for Greener Vehicles

The problem with fixed valve timing that the valve train is set by the automaker for peak efficiency running at a specific point in the engine’s operating range. When the vehicle is moving slower or faster than this ideal operating point the engine’s combustion cycle fails to properly burn the air/fuel mixture leading to considerably compromised engine performance and wastes fuel. Variable Valve Timing (VVT) is a solution developed to overcome this engine deficiency, dynamically altering the valve's opening and closing for optimal performance at any speed. The intension in this work is to contribute towards pursuing the development of variable valve timing (VVT) for improving the engine performance. This investigation covers the effect of exhaust valve opening (EVO), and closing (EVC) angle on engine performance and emissions. The aim is to optimize engine power and brake specific fuel consumption (BSFC) where the effect of engine speed has also been considered. Power, BMEP, BSFC, NO, and CO were calculated and presented to show the effect of varying valve timing on them for all the valve timing cases. The calculations of engine performance were carried out using the simulation and analysis engineering software: LOTUS”, and engine emissions were calculated using “ZINOX” program. Sensitivity analysis shows that the reduction of 10% of (EVO) angle gave a reduction of around 2.5% in power and volumetric efficiency, also a slight increase in nitrogen oxide (NO) and carbon monoxide (CO), while a 10% decrease in (EVC) causes around 1% improvement in Power. The effects of different (VVT) from the simulations are analyzed and compared with those in the reviewed literature.

Analysis of diffusion behavior of harmful emissions from trackless rubber-wheel diesel vehicles in underground coal mines

To define the diffusion behavior of harmful exhaust substances from diesel vehicles and support safety risk assessments of underground coal mines,we performed a multi-species coupling calculation of the emission and diffusion of harmful substances from a trackless rubber-wheel diesel vehicle.A computational fluid dynamics(CFD)model of the diffusion of harmful emissions was hence established and verified.From the perspective of risk analysis,the diffusion behavior and distribution of hazardous substances emitted by the diesel vehicle were studied under 4 different conditions;moreover,we identified areas characterized by hazardous levels of emissions.When the vehicle idled upwind in the roadway,high-risk areas formed behind and to the right of the vehicle:particularly high concentrations of pollutants were measured near the rear floor of the vehicle and within 5 m behind the vehicle.When the vehicle idled downwind,high-risk areas formed in front of it:particularly high concentrations of pollutants were measured near the floor and within 5 m from the front of the vehicle.In the above cases,the driver would not breathe highly polluted air and would be relatively safe.When the vehicle idled into the chamber,however,high-risk areas formed on both sides of the vehicle and near the upper roof.Forward entry of the vehicle caused a greater increase in the concentration of pollutants in the chamber and in the driver’s breathing zone compared with reverse entry.

Benefits of Reducing Air Emissions: Replacing Conventional with Electric Passenger Vehicles

The study estimated the cost of local and global air emissions, and to compare the differences between electric passenger vehicles (EV) and conventional, internal combustion engine (ICE) vehicles. The air emissions were estimated for the year 2020, for Denmark, France and Israel, because of their significantly different fuel mixes to produce electricity—a high percentage of renewable energy, mainly nuclear energy and high fossil fuels, respectively. Air emissions from electricity production and conventional traffic were calculated for each country and then multiplied by the specific country’s cost of emissions. Subtracting the total cost of electricity production from the total cost of conventional transportation yields the total benefit for each of the economies studied. The environmental benefit, depending on EV penetration rates, was found to be in the range of 7.8 to 133 MEUR/year for Denmark, 94 to1948 MEUR/year for France and only 4 to 82 MEUR/year for Israel, whose energy mix is the most polluting. Our analysis also shows higher potential benefits when replacing passenger car fleets comprising a high percentage of diesel cars with EVs, as well as in highly populated areas. In addition, we quantified the differences between EVs with fixed batteries and the new switch able battery concept (EASYBAT), as part of the EU 7th Framework Program me. The additional electricity demands for the EASYBAT concept are negligible, and therefore, do not change the overall conclusion that the cleaner the electricity energy mix and the higher the penetration of EVs, the higher the environmental benefits achieved.

Comparison of the Mutagenicity of Exhaust Emissions From Motor Vehicles Using Leaded and Unleaded Gasoline as Fuel

While Unleaded gasoline has the advantage of eliminating lead from automobile exhaust, its potential to reduce the exhaust gas and particles, merits further examination. In the present studies,the concentrations of hydrocarbons (HC) and earbon monoxides (CO) in emissions were analyzed on Santana engine Dynamometer under a standard test cycle, and total exhaust particles were collected from engines using leaded and unleaded gasoline. It was found that unleaded gasoline reduced the emissions of CO and HC, and decreased the quantity of vehicle exhaust particulate matters by 60%.With the unlead gasoline, only 23 kinds of organic substances, adsorbed in the particles, were identified by gas chromatography/mass spectrometer (GC/MS) while 32 components were detected using the leaded gasoline. The results of in vitro Salmonella/ microsomal test and micronucleus induction assay in CHL cells indicated that both types of gasoline increased the number of histidine-independent colonies and the frequencies of micronucleus induction; no significant differellce was found in their mutagenicity.

Characterization and prediction of tailpipe ammonia emissions from in-use China 5/6 light-duty gasoline vehicles

On-road tailpipe ammonia (NH3) emissions contribute to urban secondary organic aerosol formation and have direct or indirect adverse impacts on the environment and human health. To understand the tailpipe NH3 emission characteristics, we performed comprehensive chassis dynamometer measurements of NH3 emission from two China 5 and two China 6 light-duty gasoline vehicles (LDGVs) equipped with three-way catalytic converters (TWCs). The results showed that the distance-based emission factors (EFs) were 12.72 ± 2.68 and 3.18 ± 1.37 mg/km for China 5 and China 6 LDGVs, respectively. Upgrades in emission standards were associated with a reduction in tailpipe NH3 emission. In addition, high NH3 EFs were observed during the engine warm-up period in cold-start cases owing to the intensive emissions of incomplete combustion products and suitable catalytic temperature in the TWCs. Notably, based on the instantaneous NH3 emission rate, distinct NH3–emitting events were detected under high/extra high velocity or rapid acceleration. Furthermore, NH3 emission rates correlated well with engine speed, vehicle specific power, and modified combustion efficiency, which were more easily accessible. These strong correlations were applied to reproduce NH3 emissions from China 5/6 LDGVs. The predicted NH3 EFs under different dynamometer and real-world cycles agreed well with existing measurement and prediction results, revealing that the NH3 EFs of LDGVs in urban routes were within 8.55–11.62 mg/km. The results presented here substantially contribute to improving the NH3 emission inventory for LDGVs and predicting on-road NH3 emissions in China.

A remote sensing system of vehicle emissions based on tunable diode laser technology

As being an effective real-time method of monitoring vehicle emissions on-road, a remote sensing system based on the tunable diode laser （TDL） technology was presented, and the key technologies were discussed. A field test in Guangzhou（Guangdong, China） was performed and was found that the factors, such as slope, instantaneous speed and acceleration, had significant influence on the detectable rate of the system. Based on the results, the proposal choice of testing site was presented.

Reducing congestion and emissions via roadside unit deployment under mixed traffic flow

It is expected that for a long time the future road trafc will be composed of both regular vehicles(RVs)and connected autonomous vehicles(CAVs).As a vehicle-to-infrastructure technology dedicated to facilitating CAV under the mixed trafc fow,roadside units(RSUs)can also improve the quality of information received by CAVs,thereby infuencing the routing behavior of CAV users.This paper explores the possibility of leveraging the RSU deployment to afect the route choices of both CAVs and RVs and the adoption rate of CAVs so as to reduce the network congestion and emissions.To this end,we frst establish a logit-based stochastic user equilibrium model to capture drivers’route choice and vehicle type choice behaviors provided the RSU deployment plan is given.Particularly,CAV users’perception error can be reduced by higher CAV penetration and denser RSUs deployed on the road due to the improved information quality.With the established equilibrium model,the RSU deployment problem is then formulated as a mathematical program with equilibrium constraints.An active-set algorithm is presented to solve the deployment problem efciently.Numerical results suggest that an optimal RSU deployment plan can efectively drive the system towards one with lower network delay and emissions.

Particles Emission from Gasoline Vehicles

Number concentration and size distribution from gasoline ears are investigated at transient modes on the chassis dynamometers, which are measured using electrical low pressure impactor （ELPI） for the ECE15 and EUDC cycles. Results indicate that, during cold start, particle number emission is higher than that under hot start. It is found that the number of particles increases with the vehicle speeds. Furthermore, particles with diameter smaller than 200 nm constitute the predominant part of total emission in the entire cycle. In addition, the tentative information about composition of emitted particles is also discussed.

Characterization of on-road CO, HC and NO emissions for petrol vehicle fleet in China city

车辆排出物是在城市的区域的空气污染的主要来源。如果车辆排出物的趋势很好被理解，城市的空气质量上的影响能被减少。在现在的学习，车辆的真实世界的排出物在 Hangzhou 在五个地点用一个遥感系统被测量，从 2004 年 2 月的中国到 2005 年 8 月。超过 48000 有效汽油一氧化碳(公司) 的动力的车辆排出物，烃(HC ) ；氮氧化物(没有) 被测量。结果证明在 Hangzhou 的那支汽油车辆舰队有更加高的公司排出物，与 2.71%± 0 .02% 的平均排放集中，当时 HC；没有排出物相对更低，与平均排放集中(153.72 ± 1 .16 )× 1 0 [6 ] ；(233.53 ± 1 .80 )× 1 0 [6 ] 分别地。两平均排放集中的 Quintile 分析；到模型年的全部的数量排出物建议井之间的在里面使用排放差别维持了；糟糕维持的车辆比排出物的年龄依赖者恶化大。另外，相对新的高弄脏车辆是到有例如， 46.55% 一氧化碳舰队排出物被高从模型 2000 年～ 2 射出车辆的最高的五人一组瓦正在生产的舰队排出物的最大的贡献者 004。因此，舰队排出物能是如果新高度弄脏的车辆服从于测试的有效排出物，减少的 significantl 由适当补救行动列在后面。

Multi-objective comprehensive optimization of fuel consumption and emission for hybrid electric vehicles

Aiming to reduce fuel consumption and emissions of a dual-clutch hybrid electric vehicle during cold start, multiobjective optimization for fuel consumption and HC/CO emission from a TWC(three-way catalytic converter) outlet is presented in this paper. DP(dynamic programming) considering dual-state variables is proposed based on the Bellman optimality principle. Both the battery SOC(state of charge) and the temperature of TWC monolith are considered in the algorithm simultaneously. In this way the global optimal control strategy and the Pareto optimal solution of multi-objective function are derived. Simulation results show that the proposed method is able to promote the TWC light-off significantly by decreasing the engine's load and improving exhaust temperature from the outlet of the engine, in comparison with original DP considering the single battery SOC. Compared to the results achieved by rule-based control strategy, fuel economy and emission of TWC outlet for cold start are optimized comprehensively. Each indicator of Pareto solution set shows the significant improvement.

Localization and Evaluation of Motor Vehicle Emission Simulator (MOVES) Model for Predicting the Emissions of Private Cars:a Case Study of Shenzhen City,China

Motor Vehicle emission simulator(MOVES)model was localized by changing the base emission rates in MySQL database of the model,and using the actual measured data for private cars in Shenzhen City,China.The performances of localized MOVES model and non-localized MOVES model were evaluated by comparing the predicted emission factors to the measured ones.The results showed that by localization of the base emission rates,the prediction accuracy of the localized MOVES model for hydrocarbon(HC)and nitrogen oxides(NO x)was significantly improved.The accuracy of the localized MOVES model simulations in the Opmode increased by 86%,88%and 71%for HC,76%,42%and 72%for NO x on arterial roads,expressways and highways.For carbon monoxide(CO),however,the simulation performance based on the average velocity mode on expressways and highways became poor after localization,with the decrease of 28%and 8%respectively.Overall,by the localization of the base emission rates,the relative errors of the simulated emission factors of HC,CO and NO x of private cars were less than 37%.

An Interval Programming-based Traffic Planning Model for Urban Vehicle Emissions Management

An interval linear traffic planning model is developed for supporting vehicle emissions limited under uncertainty. The interval linear traffic planning model can address uncertainties of traffic system and vehicle emissions related to system costs and limitation of emission. The interval linear traffic planning model is applicable to complex traffic system. One virtual city as our study object was taken by using the interval linear traffic planning model. In this study, one virtual case and a scenario are provided for three planning periods. The results indicate that the interval linear traffic planning model can effectively reduce the vehicles emission and provide strategies for authorities to deal with problems of transportation system.

基于Vehicle Spy的排放相关网络故障码测试方法实现

针对排放相关的网络故障码确认需要两个或更多个驾驶循环的问题,提出一种基于Vehicle Spy的半自动化测试方法,在省去复杂硬件测试系统设计,节约成本的同时,保证测试结果的准确性,为今后排放相关网络故障码的设计评价、问题分析和逻辑测试奠定基础。

A Promising Distance-Based Gasoline Tax Charging System Based on Spatio-Temporal Grid Reservation in the Era of Zero-Emission Vehicles

Fuel taxes are still a primary funding source for the development and maintenance of transportation infrastructure. Such a tax is collected as a flat fee from the importer or producer of the taxable fuel product. Fuel-efficiency improvements and the adoption of zero-emission vehicles result in a continuous decrease in gasoline tax revenues. This paper proposes a novel distance-based alternative method to replace current gasoline tax collection systems in Japan by providing a software architecture platform. In this platform, we utilize driving information gathered via communication mechanisms installed in connected automated vehicles to develop a system that collects gasoline tax based on reserving spatio-temporal grids. Spatio-temporal sections are created by dividing space and time into equal grids and a designated tax charge is assigned. Connected automated vehicles reserve a planned travel route in advance and travel based on reservation information. The performance evaluation results indicate that the proposed system adequately reserves the requested grids and accurately collects gasoline taxes based on a spatio-temporal grid with minimum communication time and no data package loss. The proposed method is based on micro travel distance charges, which generates gasoline tax revenue by 5.7 percent for model year 2022 and 21.8 percent for model year 2030 as compared to the current flat-fee system.

Remote Sensing CO,CO_2 in Vehicle Emissions Based on TDLAS

Knowing the quantity of pollutants that the vehicle fleet is emitting to the air has become a vital problem in almost every major city in China. Finding and fixing gross polluters is therefore very important to control the urban air quality and protect the human health and the environment. Remote sensing is an important advance in the technology of on-road vehicle emissions testing because it is fast, mobile, and unobtrusive. This on-road vehicle emissions remote system is designed to measure the carbon monoxide, carbon dioxide and opacity from the vehicles's tailpipe based on the Tunable Diode Laser Absorption Spectroscopy (TDLAS). There are several advantages of this system such as compact design and easy of use. The measurement principle and optical layout of the instrument has been described in this paper. Field testing at Beijing and Hefei were conducted over one year, more than 6 000 vehicles were tested. This vehicle emissions remote system has been shown to be able to measure CO,CO2 and opacity from individual at highway speeds. In parallel, the plate license, speed, acceleration and length of vehicle are recognised by computer so that the owners of vehicles exceeding the permissible level of emissions can be identified.

Dynamic emission characteristics and control strategies of air pollutants from motor vehicles in downtown Beijing,China

This study combined the real-time monitoring and investigation of traffic flows to comprehensively analyze the road traffic flow and vehicle structure in downtown Beijing.A dynamic emission inventory of motor vehicle air pollutants in downtown Beijing in 2021 was established,and the impact of these emissions on air quality was simulated and quantified,and different emission reduction control scenarios were proposed to evaluate their environmental improvement effects and explore measures to mitigate the impact of pollution emissions.The results show that the high traffic flow and the structure of the motor vehicle emissions in downtown Beijing are the main causes of severe motor vehicle pollution.Monitoring data shows that traffic flow in central Beijing is dominated by small passenger vehicles,while the vehicle mix is better than in other regions,with 72.0%of vehicles meeting"National V"or higher emission standards.However,to achieve higher air quality goals,further reducing vehicle emissions is necessary.Based on dynamic traffic flow,the average daily emissions of nitrogen oxides(NOX),particulate matters(PM_(2.5))and volatile organic compounds(VOC)from motor vehicles in central Beijing are 17.7 tons,0.6 tons and 14.0 tons,respectively,accounting for 23.0%of the city’s average daily motor vehicle emissions.If a zero-emission zone for motor vehicles were implemented in central Beijing,the annual average emission level of pollutants will be reduced by 10.4%to 21.0%.The designation of ultra-low emission zones for motor vehicles could be effective in improving the air quality in the center of Beijing.

Artificial neural network model for identifying taxi gross emitter from remote sensing data of vehicle emission

Vehicle emission has been the major source of air pollution in urban areas in the past two decades. This article proposes an artificial neural network model for identifying the taxi gross emitters based on the remote sensing data. After carrying out the field test in Guangzhou and analyzing various factors from the emission data, the artificial neural network modeling was proved to be an advisable method of identifying the gross emitters. On the basis of the principal component analysis and the selection of algorithm and architecture, the Back-Propagation neural network model with 8-17-1 architecture was established as the optimal approach for this purpose. It gave a percentage of hits of 93%. Our previous research result and the result from aggression analysis were compared, and they provided respectively the percentage of hits of 81.63% and 75%. This comparison demonstrates the potentiality and validity of the proposed method in the identification of taxi gross emitters.