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1
Mądziel, Maksymilian. "Future Cities Carbon Emission Models: Hybrid Vehicle Emission Modelling for Low-Emission Zones." Energies 16, no. 19 (2023): 6928. http://dx.doi.org/10.3390/en16196928.
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Current emission models primarily focus on traditional combustion vehicles and may not accurately represent emissions from the increasingly diverse vehicle fleet. The growing presence of hybrid and electric vehicles requires the development of accurate emission models to measure the emissions and energy consumption of these vehicles. This issue is particularly relevant for low-emission zones within cities, where effective mobility planning relies on simulation models using continuously updated databases. This research presents a two-dimensional emission model for hybrid vehicles, employing artificial neural networks for low-emission zones. The key outcome is the methodology developed to create a CO2 emission model tailored for hybrid vehicles, which can be used to simulate various road solutions. The CO2 emission model achieved an R2 coefficient of 0.73 and an MSE of 0.91, offering valuable information for further advancements in emission modelling.
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Zhang, Ye, Yating Song, Tianshi Feng, and Yanyan Chen. "Comparative Analysis of Emission Characteristics of In-Use China II–V Gasoline, Hybrid, Diesel-Fueled Vehicles." Atmosphere 14, no. 2 (2023): 272. http://dx.doi.org/10.3390/atmos14020272.
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Increasingly stringent regulations regarding vehicle emissions have contributed to the diversification of vehicle technologies, resulting in the increasing complexity of typical vehicles that make up a fleet. In order to investigate the real gas emissions of different typical vehicles, tests were conducted using a portable emission measurement system (PEMS) in Beijing and emission studies were conducted on eight light-duty passenger vehicles (LDPVs, including light-duty gasoline passenger vehicles and hybrid electric vehicles), eight heavy-duty passenger vehicles (HDPVs), and four light-duty trucks (LDTs). The results show that the emissions of relevant pollutants from LDPV meet the emission standard limits. The emission factors of CO2, CO, NOX, and HC of China IV and China V hybrid electric vehicles (HEVs) are much smaller than the emission standard limits and the emission factors of other vehicles, which have better emission reduction effects. Among LDPV, heavy-duty passenger vehicles (HDPVs), and LDT, the emissions of HDPV and LDT are extremely high. Emission characteristics vary on different types of roads, with the highest emission factors generally occurring on secondary roads. The micro-trip method was used to explore the influence of speed on emission factors. HEV are less sensitive to speed changes and can still maintain a low emission level at low speeds. The average speed and emission factors of HDPV in micro-trip has a strong correlation.
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Liu, Shiwen, Hongxiong Li, Wen Kun, Zhen Zhang, and Haotian Wu. "How Do Transportation Influencing Factors Affect Air Pollutants from Vehicles in China? Evidence from Threshold Effect." Sustainability 14, no. 15 (2022): 9402. http://dx.doi.org/10.3390/su14159402.
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In recent years, China has promoted a series of legal norms to reduce the environmental impact of air pollutants from vehicles. The three main vehicle emission species (carbon monoxide, hydrocarbons, nitrogen oxides) contribute significantly to air pollution. In this study, the emission factor method was used to estimate air pollutants from vehicles in 31 provinces from 2006 to 2016. The results show a trend of total vehicle carbon monoxide (CO) and hydrocarbons (HC) emissions decreasing with time; the vehicle nitrogen oxides (NOx) emission trend is divided into two stages: an upward trend between 2006 and 2012 and a downward trend after 2012. Based on a panel threshold, a regression method was used to divide the vehicle NOx and CO emissions in China into four emission zones: low emissions, medium emissions, high emissions, and extra-high emissions. Vehicle HC emissions were divided into three emission zones, which corresponded to low emissions, medium emissions, and high emissions. Overall, vehicle pollution emission efficiency and per capita GDP have a significant inhibitory effect on the three main air pollutants from vehicles (NOx, HC, CO). Both passenger and freight turnover have significant roles in promoting the three air pollutants from vehicles (NOx, HC, CO). Road density and road carrying capacity have a significant role in promoting vehicle HC and CO emissions. Increasing truck proportion inhibits vehicle CO emissions and promotes vehicle NOx emissions. The urbanization rate has a positive effect on vehicle HC and CO emissions. Moreover, there is obvious heterogeneity in different emission zones of the three air pollutants from vehicles (NOx, HC, CO).
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Hao, Lijun, Hang Yin, Junfang Wang, et al. "Research on Analysis Method of Remote Sensing Results of NO Emission from Diesel Vehicles." Atmosphere 13, no. 7 (2022): 1100. http://dx.doi.org/10.3390/atmos13071100.
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Remote sensing technology has been used for gasoline vehicle gaseous emissions monitoring for nearly 30 years. However, the application effect of the remote sensing detection of diesel vehicle tailpipe emission concentrations is unsatisfactory. Therefore, several approaches were proposed to analyze the remote sensing results for gaseous exhaust emissions from diesel vehicles, including the concentration ratios of gaseous emission components to carbon dioxide (CO2) and fuel-based emission factors. Based on our experimental results, these two metrics have some high values in low-speed or low-load conditions of vehicles, which introduces uncertainty when evaluating vehicle emission levels. Therefore, an inversion calculation method originally developed for remote sensing light duty diesel vehicle gaseous emissions was used for the remote sensing of nitrogen monoxide (NO) tailpipe concentrations in heavy duty diesel vehicles, and validated by PEMS tested emission results. For the first time, the above three options for evaluating the NOx emission level of diesel vehicles, including the concentration ratio of NO to CO2, the fuel-based NO emission factor and the estimated tailpipe NO emission concentration were investigated, and some influencing factors were also discussed. The remote sensing tailpipe NO emission concentration can be directly used to evaluate diesel vehicle NO emission levels compared with the two other metrics.
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Ball, Douglas, David Moser, Yonghong Yang, and David Lewis. "N2O Emissions of Low Emission Vehicles." SAE International Journal of Fuels and Lubricants 6, no. 2 (2013): 450–56. http://dx.doi.org/10.4271/2013-01-1300.
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Reddy, Kovvuri Akhil. "Low Emission Engines for Hybrid Electric Vehicles." International Journal of Research Publication and Reviews 4, no. 12 (2023): 2063–66. http://dx.doi.org/10.55248/gengpi.4.1223.123431.
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Árpád, István, Judit T. Kiss, Gábor Bellér, and Dénes Kocsis. "Sustainability Investigation of Vehicles’ CO2 Emission in Hungary." Sustainability 13, no. 15 (2021): 8237. http://dx.doi.org/10.3390/su13158237.
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The regulation of vehicular CO2 emissions determines the permissible emissions of vehicles in units of g CO2/km. However, these values only partially provide adequate information because they characterize only the vehicle but not the emission of the associated energy supply technology system. The energy needed for the motion of vehicles is generated in several ways by the energy industry, depending on how the vehicles are driven. These methods of energy generation consist of different series of energy source conversions, where the last technological step is the vehicle itself, and the result is the motion. In addition, sustainability characterization of vehicles cannot be determined by the vehicle’s CO2 emissions alone because it is a more complex notion. The new approach investigates the entire energy technology system associated with the generation of motion, which of course includes the vehicle. The total CO2 emissions and the resulting energy efficiency have been determined. For this, it was necessary to systematize (collect) the energy supply technology lines of the vehicles. The emission results are not given in g CO2/km but in g CO2/J, which is defined in the paper. This new method is complementary to the European Union regulative one, but it allows more complex evaluations of sustainability. The calculations were performed based on Hungarian data. Finally, using the resulting energy efficiency values, the emission results were evaluated by constructing a sustainability matrix similar to the risk matrix. If only the vehicle is investigated, low CO2 emissions can be achieved with vehicles using internal combustion engines. However, taking into consideration present technologies, in terms of sustainability, the spread of electric-only vehicles using renewable energies can result in improvement in the future. This proposal was supported by the combined analysis of the energy-specific CO2 emissions and the energy efficiency of vehicles with different power-driven systems.
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Liu, Weiwei, Jianbei Liu, Qiang Yu, Donghui Shan, Chao Wang, and Zhiwei Wu. "Optimal Speed Ranges for Different Vehicle Types for Exhaust Emission Control." Sustainability 16, no. 23 (2024): 10344. http://dx.doi.org/10.3390/su162310344.
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Controlling vehicle speed is crucial for reducing exhaust emissions and ensuring the sustainable development of road transportation. Currently, speed limits on expressways are primarily set from a safety perspective, with limited research addressing speed limits from an environmental protection standpoint. In this study, based on real-world vehicle experiments and a vehicle flow exhaust emission model, we investigated the exhaust emission characteristics of light passenger vehicles (categorized as M1) and freight vehicles (categorized as N, including N1-minivans, N2-light heavy-duty vehicles, N3-medium heavy-duty vehicles, and N4-large heavy-duty vehicles) both individually and in traffic flows at varying speeds. We take carbon monoxide (CO), nitrogen oxides (NOx), particular matter (PM), and hydrocarbons (HCs) as representative emission components. The emission rate ranking of typical exhaust factors differs between M1-light passenger vehicles and N-freight vehicles. For M1-light passenger vehicles, the order is CO > HC > NOx > PM2.5, while for N-freight vehicles, it is NOx > CO > PM2.5 > HC. Conversely, for freight vehicles, higher speeds correlate with increased exhaust emissions in general, although carbon emissions specifically decrease as the speed increases. The results indicate the following speed limits conducive to sustainable road transportation development and low exhaust and carbon emissions: 90–110 km/h for light passenger vehicles and 80–100 km/h for freight vehicles.
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Fan, Jieyu, Arsalan Najafi, Jokhio Sarang, and Tian Li. "Analyzing and Optimizing the Emission Impact of Intersection Signal Control in Mixed Traffic." Sustainability 15, no. 22 (2023): 16118. http://dx.doi.org/10.3390/su152216118.
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Signalized intersections are one of the typical bottlenecks in urban transport systems that have reduced speeds and which have substantial vehicle emissions. This study aims to analyze and optimize the impacts of signal control on the emissions of mixed traffic flow (CO, HC, and NOx) containing both heavy- and light-duty vehicles at urban intersections, leveraging high-resolution field emission data. An OBEAS-3000 (Manufacturer: Xiamen Tongchuang Inspection Technology Co., Ltd., Xiamen, China.) vehicle emission testing device was used to collect microscopic operating characteristics and instantaneous emission data of different vehicle types (light- and heavy-duty vehicles) under different operating conditions. Based on the collected data, the VSP (Vehicle Specific Power) model combined with the VISSIM traffic simulation platform was used to quantitatively analyze the impact of signal control on traffic emissions. Heavy-duty vehicles contribute to most of the emissions regardless of the low proportion in the traffic flows. Afterward, a model is proposed for determining the optimal signal control at an intersection for a specific percentage of heavy-duty vehicles based on the conversion of emission factors of different types of vehicles. Signal control is also optimized based on conventional signal timing, and vehicle emissions are calculated. In the empirical analysis, the changes in CO, HC, and NOx emissions of light- and heavy-duty vehicles before and after conventional signal control optimization are quantified and compared. After the signal control optimization, the CO, HC, and NOx emissions of heavy-duty vehicles were reduced. The CO and HC emissions of light-duty vehicles were reduced, but the NOx emissions of light-duty vehicles remained unchanged. The emissions of vehicles after optimized signal control based on vehicle conversion factors are reduced more significantly than those after conventional optimized signal control. This study provides a scientific basis for developing traffic management measures for energy saving and emission reduction in transport systems with mixed traffic.
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Dimokas, Nikos, Dimitris Margaritis, Manuel Gaetani, Kerem Koprubasi, and Evangelos Bekiaris. "A Big Data Application for Low Emission Heavy Duty Vehicles." Transport and Telecommunication Journal 21, no. 4 (2020): 265–74. http://dx.doi.org/10.2478/ttj-2020-0021.
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AbstractRecent advances in green and smart mobility aim to reduce congestion and foster greener, cheaper and with less delay transportation. The reduction of fuel consumption and CO2 emissions have worked on light-duty vehicles. However, the reduction of emissions and consumables without sacrificing on emission standards is an important challenge for heavy-duty vehicles. The paper introduces a big data system architecture that provides an on-demand route optimization service reducing NOx emissions of heavy-duty vehicles. The system utilizes the information provided by the navigation systems, big data analytics such as predictive traffic and weather conditions, road topography and road network and information about vehicle payload, vehicle configuration and transport mission to develop a strategy for the best route and the best velocity profile. The system was proven efficient during the performance evaluation phase, since the cumulative engine-out NOx has been decreased more than 10%.
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Qiu, Tao, Yakun Zhao, Yan Lei, et al. "Experimental Research on Regulated and Unregulated Emissions from E20-Fuelled Vehicles and Hybrid Electric Vehicles." Atmosphere 15, no. 6 (2024): 669. http://dx.doi.org/10.3390/atmos15060669.
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Ethanol as a renewable fuel has been applied in fuel vehicles (FVs), and it is promising in hybrid electric vehicles (HEVs). This work aims to investigate the emission characteristics of ethanol applied in both FVs and plug-in hybrid electric vehicles (PHEVs). The paper conducted a real-road test of an internal combustion FV and PHEV, respectively, based on the world light vehicle test cycle (WLTC) by using gasoline and regular gasoline under different temperature conditions. The use of E10 and E20 in FVs has been effective in reducing the conventional emissions of the vehicles. At 23 °C, E10 and E20 reduced the conventional emissions including carbon monoxide (CO), total hydrocarbon compound (THC), non-methane hydrocarbon compound (NMHC), particulate matter (PM), and particulate number (PN) by 15.40–31.11% and 11.00–44.13% respectively. At 6 °C, E10 and E20 reduced conventional emissions including THC, CO, and PM by 2.15–8.61% and 11.02–13.34%, respectively. However, nitrogen oxide (NOX) emissions increased to varying degrees. The reduction trend of non-conventional emissions including methane (CH4), nitrous oxide (N2O), and carbon dioxide (CO2) from FVs fueled with E10 and E20 is not significant for vehicles. Overall, the emission reduction effect of E20 is better than that of E10, and the emission reduction effect of ethanol gasoline on vehicle emissions is reduced at low temperatures. Lower ambient temperatures increase vehicle emissions in the low-speed segment but decrease vehicle emissions in the ultra-high-speed segment. HEV emissions of THC, CO, PN, and PM are reduced by 25.28%, 12.72%, 77.34%, and 64.59%, respectively, for E20 compared to gasoline, and the use of E20 in HEVs contributes to the reduction of overall vehicle emissions.
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Fu, Huazhao, Yi Zhao, Qichao Chen, et al. "Low-Carbon Incentive Guidance Strategy for Electric Vehicle Agents Based on Carbon Emission Flow." World Electric Vehicle Journal 14, no. 12 (2023): 327. http://dx.doi.org/10.3390/wevj14120327.
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The cleanliness of charging power determines whether electric vehicles can fully utilize their low-carbon properties. This paper, taking into account the impact of temperature on the energy consumption of electric vehicle air conditioning, uses the Monte Carlo algorithm to calculate the typical daily charging load of electric vehicle clusters in different seasons. Secondly, based on the Shapley value carbon responsibility allocation method, a reasonable range of carbon emission responsibilities for different electric vehicle agents is calculated, and a tiered carbon pricing method is proposed accordingly. Then, using carbon emission flow theory, we calculate the carbon emissions generated by the different agents’ charging amounts and corresponding carbon emission costs. Finally, a low-carbon incentive guidance model is constructed with the signal of tiered carbon prices and the goal of minimizing operating costs to re-optimize the charging load distribution of electric vehicles. Case studies showcase that the proposed method is effective in reducing power system carbon emissions and electric vehicle charging costs.
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Zheng, Yi Ling, Yuan Qi Wei, Ya Xing Xiao, and Yu Feng. "Guiding Model and Empirical Analysis of Vehicle Behavior at Signalized Intersections Based on Carbon Emissions." Applied Mechanics and Materials 253-255 (December 2012): 1282–88. http://dx.doi.org/10.4028/www.scientific.net/amm.253-255.1282.
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A model based on carbon emissions is established to guide vehicle behavior at signalized intersections. This model takes working conditions and emission characteristics of vehicles into account, uses VT-Micro model exploited by Oak Ridge National Laboratory to calculate emissions, and provides vehicles with the lowest-emission working plan to drive through intersections. This model is able to reducing carbon emissions at the source and it agrees with the development of low-carbon transportation.
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Ko, Sangchul, Junhong Park, Hyungjun Kim, et al. "NOx Emissions from Euro 5 and Euro 6 Heavy-Duty Diesel Vehicles under Real Driving Conditions." Energies 13, no. 1 (2020): 218. http://dx.doi.org/10.3390/en13010218.
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Despite the strengthening of vehicle emissions standards and test methods, nitrogen oxide (NOx) emissions from on-road mobile sources are not being notably reduced. The introduction of real driving emission (RDE) regulations is expected to reduce the discrepancy between emission regulations and actual air pollution. To analyze the effects of RDE regulations on heavy-duty diesel vehicles, pollutants emitted while driving were measured using a portable emission measurement system (PEMS) for Euro 5 and Euro 6 vehicles, which were produced before and after RDE regulations, respectively. NOx emissions were compared as a function of emissions allowance standards, gross vehicle weight (GVW), average vehicle speed, and ambient temperature. NOx emissions from Euro 6 vehicles were found to be low, regardless of GVW; emissions from both vehicular categories increased with a decline in the average speed. To reflect real road driving characteristics more broadly in the RDE test method for heavy-duty vehicles, it is necessary to consider engine power, which is a criterion for classifying effective sections, in the moving average window (MAW) analysis method, as well as including cold start conditions.
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Wu, Rui, Hao Zhang, Daoyuan Yang, et al. "Vehicle greenhouse gas emission factors based on multi-dimensional Bin interval mode." E3S Web of Conferences 536 (2024): 01009. http://dx.doi.org/10.1051/e3sconf/202453601009.
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The emission factors of greenhouse gases from motor vehicles are of significant importance for low-carbon and environmentally friendly initiatives. This paper focuses on greenhouse gas emission factors of heavy-duty vehicles. The multi-dimensional Bin interval mode are proposed, which considers multiple parameters such as vehicle speed, acceleration, torque, and rotational speed. Based on this, the emission characteristics of greenhouse gases from heavy-duty vehicles. are investigated under different parameter conditions. The results indicate that as the VSPA value or the engine torque increases, the CO2 emission factor also increases accordingly. The CO2 emission factor is lower at medium to high rotational speeds, while it tends to increase at low rotational speeds. The research findings provide support for monitoring and evaluating greenhouse gas emissions and offer scientific guidance for formulating specific carbon reduction policies, emission targets, and plans.
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Ma, Chao, Lin Wu, Hong-jun Mao, et al. "Transient Characterization of Automotive Exhaust Emission from Different Vehicle Types Based on On-Road Measurements." Atmosphere 11, no. 1 (2020): 64. http://dx.doi.org/10.3390/atmos11010064.
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Previous works on real-world vehicle emission characteristics have mainly focused on the influences of fuel, speed, vehicle type, elevation, and other factors on vehicle emission quantity and components. However, few studies have investigated the transient trend of automotive exhaust emissions through on-road measurements. The key objective of the present paper was to examine the transient characteristics of exhaust emissions from different vehicle types on the roads of Tianjin. To achieve the goal, a portable emission measurement system (PEMS) was employed to monitor emissions from selected test vehicles—private cars, passenger vehicles, and cargo vehicles. It was found that the high-emission points of test vehicles were mainly distributed in two regions: the high-speed region (speed > 70–90 km/h, vehicle-specific power (VSP) > 0 kW/t) and the medium-speed–acceleration region (20–30 km/h < speed < 60–90 km/h, 0 kW/t <VSP < 12 kW/t). The CO, hydrocarbon (HC), NOx, and particulate number (PN) average emission rates in the high-emission points could be 3.15–14.93 times, 1.93–24.89 times, 3.23–6.03 times, and 3.22–30.27 times of those of average emission rates. The HC, NOx, and PN average emission rates of China IV vehicles in the high-emission points were 2.46–4.92 times, 3.56–6.03 times, and 3.22–13.21 times of those of average emission rates, not less than those of China III (1.93–2.52 times, 2.75–3.90 times, and 9.98–22.34 times). Test vehicles mainly emitted nucleation-mode and Aitken-mode particles, and the increase of the PN concentration emission rate in low-speed and high-speed regions was higher than that in the medium-speed region. The exhaust gas recirculation (EGR) + diesel particulate filter (DPF) could effectively inhibit the Aitken output caused by turbocharged intercooler (CIC). The selective catalytic reduction (SCR) might cause more nucleation-mode particles.
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Lyu, Meng, Meili Lyu, Boyang Li, Yanming Yang, Hao Wen, and Yongwei Wang. "The Impact of Fuel Type on Emissions in High-altitude Cities: A PEMS Study of LPG/Gasoline and Gasoline Vehicles." Advances in Computer and Materials Scienc Research 3, no. 1 (2025): 269. https://doi.org/10.70114/acmsr.2025.3.1.p269.
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To determine whether liquefied petroleum gas (LPG)/gasoline dual-fuel vehicles reduce atmospheric pollution in high-altitude cities compared to gasoline vehicles, experiments were conducted on two LPG/gasoline and two gasoline vehicles in a high-altitude city using a portable emissions measurement system (PEMS), and real-world emissions from two gasoline vehicles in a low-altitude city were also analyzed. The emission factors were obtained and the effects of driving mode, speed, and acceleration on emission characteristics were examined. Results show that the mean emission factors of CO₂, CO, and NOx for LPG/gasoline-fueled vehicles in high-altitude cities are 159.22±11.81, 18.38±9.72 and 1.53±0.46 g/km, and those for gasoline-fueled vehicles are 226.64±27.80, 1.46±0.83 and 0.22±0.17 g/km. For gasoline vehicles in low-altitude cities, the emission factors are 188.01±4.82, 2.21±0.67 and 0.07±0.003 g/km. Unlike CO₂, CO and NOx emissions from LPG/gasoline vehicles are higher than those from gasoline vehicles. Further analysis indicates that idle and accelerating modes significantly affect CO and NOx emissions. In high-altitude tests, these two modes account for about 24.5% and 31.2% of total testing time, respectively, with higher emissions than low-altitude vehicles (22.5% and 27.7%). Generally, gasoline-fueled vehicles exhibit better gaseous pollutant emissions behavior than LPG/gasoline-fueled ones. These findings can serve as a reference for developing emission inventories and emission-control strategies in high-altitude cities
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Zhang, Ying, Xinping Yang, and Mingliang Fu. "Emission Characteristics of Particle Number from Conventional Gasoline and Hybrid Vehicles." Sustainability 16, no. 1 (2023): 12. http://dx.doi.org/10.3390/su16010012.
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Vehicular particle number (PN) emissions have garnered increasing attention. In this study, nine light-duty vehicles, involving conventional internal combustion engine gasoline vehicles (ICEVs) and hybrid electric vehicles (HEVs), underwent testing on a chassis dynamometer to elucidate key factors influencing PN emissions. We found that with more stringent emission standards Gasoline Direct Injection (GDI) vehicles exhibited a reduction in PN emission factors. Higher PN emissions for GDI vehicles than vehicles with Multi-Port Fuel Injection (PFI) engines were observed; meanwhile, HEV showed lower PN emissions than ICEVs. PN emissions for cold start consistently exceeded warm start across vehicles with different standards and technologies. Notably, China VI HEV exhibited a substantial 19.2-fold increase in PN emissions for cold start compared to warm start. Analysis on a second-by-second basis revealed that cold-start emissions concentrated in low speed, while warm-start emissions were prominent in extra-high speed. Concerning vehicle specific power (VSP), the lowest mean PN emission rate occurred during idle conditions. PN emissions for China IV-VI ICEVs with GDI engines would increase with the increasing VSP, whereas China VI ICEVs with PFI engines and HEV with GDI engines showed varied patterns of PN emissions, especially under cold start. Our study would further facilitate formulating effective strategies for vehicular PN emissions.
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Mourad, Mohamed. "A proposed fuel cell vehicle for reducing CO2 emissions and its contribution to reducing greenhouse gas emissions." International Journal of Engineering & Technology 3, no. 2 (2014): 252. http://dx.doi.org/10.14419/ijet.v3i2.2349.
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Because of their high efficiency and low emissions, fuel cell vehicles are undergoing extensive research and development. When considering the introduction of advanced vehicles, a complete evaluation must be performed to determine the potential impact of a technology on carbon dioxide (CO2) and greenhouse gases emissions. However, the reduction of CO2 emission from the vehicle became the most important objective for all researches institutes of vehicle technologies worldwide. There interest recently to find unconventional methods to reduce greenhouse gas emission from vehicle to keep the environment clean. This paper offers an overview and simulation study to fuel cell vehicles, with the aim of introducing their main advantages and evaluates their influence on emissions of carbon dioxide from fuel cell vehicle and compares advanced propulsion technologies on a well-to-wheel energy basis by using current technology for conventional and fuel cell. The results indicate that the use of fuel cells, and especially fuel cells that consume hydrogen, provide a good attempt for enhancing environment quality and reducing greenhouse gas (GHG) emissions. Moreover, the emission reduction percentage of fuel cell vehicle reaches to 64% comparing to the conventional vehicle. Keywords: Fuel Cell Electric Vehicle, Performance, Simulation, Driving Cycle, CO2 Emissions, Greenhouse Gas Emissions, Fuel Consumption.
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Mieles, Maria, Josué Pita, and Katherine Rengel. "Zoned Traffic Limitation Plan (LEZ) to mitigate the increase in traffic congestion on the main roads in the center of Guayaquil." INTRA: Interdisciplinary Research and Analysis Journal 1, no. 1 (2025): 1–13. https://doi.org/10.63948/intraj.v1i1.308.
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The center of Guayaquil faces a growing problem of traffic congestion on its central roads; to mitigate this problem it is intended to design low emission zones (LEZ) within the center of the city of Guayaquil since these can help control traffic congestion and improve air quality in urban areas. in general terms, Low Emission Zones consist of traffic management, so they are designed to reduce the number of highly polluting vehicles circulating in specific areas of a city. They work by extracting the entry of vehicles that do not meet certain emission standards or do not have environmental labels, vehicles with high emissions are not allowed to enter or have limited access to specific areas. This reduces the number of polluting vehicles in those areas, decreasing congestion. Implementing low-emission zones in downtown Guayaquil could help control traffic congestion by discouraging high-polluting vehicle traffic and promoting more sustainable forms of transportation. In Ecuador, this measure has already been implemented with very positive results, however, its effectiveness will depend on adequate planning and integration with other urban mobility measures.
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Valdes-Montenegro, Ana, Franchesca Gonzalez-Olivardia, Sarawut Thepanondh, and Cesar Pinzon-Acosta. "Estimation of on-road mobile emissions based on the vehicle technology in a high-traffic avenue in Panama City, Panama." E3S Web of Conferences 530 (2024): 01003. http://dx.doi.org/10.1051/e3sconf/202453001003.
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This study addresses the emissions from mobile sources in a busy avenue. Latest mobile emission inventories estimated pollutants based on fuel sales activities in the country. While this is an approved methodology, it does not consider the characteristics of vehicles and their emissions control systems. Applying the International Vehicle Emissions (IVE) model involves low costs, the vehicle fleet’s technology features, and the study region’s environmental parameters. The IVE model allows a better understanding of how vehicle technology impacts air quality. This study aims to generate information about vehicle emissions in Panama using a model that considers factors like vehicle technology, driving patterns, and local conditions, all of which influence air pollution in the region. The focuses are on passenger vehicles, the most common in the country, particularly in one of the densest districts. Carbon monoxide (CO), sulfates (SOx), nitrogen oxide (NO, and particulate matter (PMx) emissions were estimated with the IVE model, the first one stood out, represented 98% (6479.82 g/km) of the air pollutants emitted into the atmosphere by these four gases. Finally, it is established that the combination of emission control technologies and vehicle features is what will determine its emission reduction efficiency. Only in diesel vehicles, an increase in PMx emissions was identified.
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Liu, Kai, Dong Liu, Cheng Li, and Toshiyuki Yamamoto. "Eco-Speed Guidance for the Mixed Traffic of Electric Vehicles and Internal Combustion Engine Vehicles at an Isolated Signalized Intersection." Sustainability 11, no. 20 (2019): 5636. http://dx.doi.org/10.3390/su11205636.
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Although electric vehicles (EVs) have been regarded as promising to reduce tailpipe emissions and energy consumption, a mixed traffic flow of EVs and internal combustion engine vehicles (ICEVs) makes the energy/emissions reduction objective more difficult because EVs and ICEVs have various general characteristics. This paper proposes a low-emission-oriented speed guidance model to address the energy/emission reduction issue under a mixed traffic flow at an isolated signalized intersection to achieve the objective of reducing emissions and total energy consumption while reducing vehicle delay and travel time. The total energy/emissions under different market penetration rates of EVs with various traffic volumes are analyzed and compared. Numerical examples demonstrate that the proposed speed guidance model has better performance than those without considering the impact of queues. For a certain traffic volume, the energy/emission reduction effects under speed guidance will increase with an increasing share of EVs. This paper also explores the impact of the time interval for guidance renewal on vehicle emissions in practice.
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Qi, Zhaoyu, Ming Gu, Chuanzhou You, Yue Zhan, Zhongwu Ma, and Wei Huang. "Research on the driving characteristics of motor vehicles in high-altitude areas for the analysis of exhaust emission characteristics." E3S Web of Conferences 478 (2024): 01007. http://dx.doi.org/10.1051/e3sconf/202447801007.
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Research on the driving characteristics of motor vehicles at different altitudes in plateau regions and road emission intensity can provide technical support for energy conservation and emission reduction policies in plateau areas. This paper selects gasoline and diesel vehicles for on-board testing on typical road sections in plateau regions to study the overall driving characteristics of motor vehicles and the driving characteristics at different altitude intervals in plateau areas. The results show that with the increase in altitude, the driving conditions gradually concentrate towards ’high speed, low acceleration.’ The relevant conclusions can further study and analyze the distribution patterns of pollutants in motor vehicle exhaust emissions and road emission intensity.
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Twigg, M. V. "Aftertreatment for Low Emission Vehicles." Platinum Metals Review 43, no. 3 (1999): 119–21. http://dx.doi.org/10.1595/003214099x433119121.
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Dong, Yaping, and Jinliang Xu. "Estimation of Vehicle Carbon Emissions in China Accounting for Vertical Curve Effects." Mathematical Problems in Engineering 2020 (August 29, 2020): 1–20. http://dx.doi.org/10.1155/2020/1595974.
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Predicting vehicle carbon emissions on vertical curve sections can provide guidance for low-carbon vertical profile designs. Given that the influence of vertical curve design indicators on the fuel consumption and CO2 emissions of vehicles are underexplored, this study filled this research gap by establishing a theoretical carbon emission model of vehicles on vertical curve sections. The carbon emission model was established based on Xu’s vehicle energy conversion model, the conversion model of energy, fuel consumption, and CO2 emissions. The accuracy of the theoretical carbon emission model and the CO2 emission rules on vertical curve sections were verified by field test results. Field tests were carried out on flat sections, longitudinal slope sections, and various types of vertical curve sections, with five common types of vehicles maintaining cruising speed. The carbon emission rate effects on the vertical curve are closely related to the gradient and irrelevant of the radius. On the vertical profile composed with downhill/asymmetric/symmetrical vertical curve with a gradient greater than the balance gradient, the carbon emission rate is determined by the gradient and radius. The influence of the gradient on carbon emissions of vehicle on these vertical profiles was more significant than the radius. The radius is irrelevant to the carbon emission rate on the other forms of vertical profile. These results may benefit highway designers and engineers by providing guidelines regarding the environmental effects of highway vertical curve indexes.
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Todor, Koritarov. "VEHICLE CLASSIFICATION AS A TOOL FOR PROMOTING SUSTAINABLE URBAN MOBILITY AND DEVELOPMENT." Deutsche internationale Zeitschrift für zeitgenössische Wissenschaft 92 (November 18, 2024): 124–26. https://doi.org/10.5281/zenodo.14181664.
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The classification of vehicles is of vital importance in the advancement of sustainable urban mobility and development. This research examines the impact of vehicle classification on urban sustainability, considering the environmental, economic, social, and public health implications. By directing targeted policies and enhancing the efficiency of infrastructure, vehicle classification contributes to reductions in emissions and the promotion of social equity, resulting in more efficient and sustainable transportation systems. The integration of vehicle classification into transport policies enables the formulation of regulations that endorse the adoption of cleaner technologies and prioritize the utilization of low-emission vehicles. Additionally, it facilitates the development of infrastructure by accommodating a variety of transportation modes. Moreover, the categorization of vehicles according to their emissions profiles serves to enhance environmental sustainability, encourage the adoption of low-emission alternatives, and address the needs of disadvantaged groups. As urban areas continue to expand, it will be imperative to implement effective vehicle classification within urban planning in order to establish fair and sustainable environments for future generations.
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Figenbaum, Erik, and Christian Weber. "Estimating Real-World Emissions of PHEVs in Norway by Combining Laboratory Measurement with User Surveys." World Electric Vehicle Journal 9, no. 2 (2018): 31. http://dx.doi.org/10.3390/wevj9020031.
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The paper presents the results of experimental testing of the exhaust emission and energy consumption of two gasoline plug-in hybrid vehicles in an emission testing laboratory with different drive cycles and drive modes and at summer and winter temperatures. One was a compact vehicle with a type approval electric mode range of 50 km, the other a mid-sized vehicle with an electric mode range of 31 km. Additionally, an online survey of 2065 private plug-in hybrid vehicles (PHEV) owners investigated the usage pattern of the vehicles. Combining the laboratory tests with the user survey results provided an estimate for the reduction of CO2-emission of PHEVs in use in Norway. The main conclusion is that the PHEV is a vehicle type that needs to match well with the use pattern to produce low CO2- and local emissions. The achievable CO2-emission reduction was proportional to the range in electric drive-mode (E-mode), i.e., 50 km range resulted in about 50% reduction.
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Rashmi B. Kale. "Analysis and Exploration of Carbon Emission Dataset using Machine Learning Techniques." Panamerican Mathematical Journal 34, no. 4 (2024): 614–24. http://dx.doi.org/10.52783/pmj.v34.i4.2029.
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One of the primary environmental climate issues in metropolitan cities is that most people are faced with low air quality. Climate variance is impacting the world, triggering drought, storms, and extreme weather events. The primary contributor to climate change is affected greenhouse carbon gas emissions, of which carbon dioxide (CO2) and carbon monoxide (CO) make up the majority. The carbon emissions are expected to rise steadily worldwide. Many factors, including the burning of fossil fuels in transportation and manufacturing sectors, cause climate variance. Fast urbanization has used a high rate of motor vehicles as compared to a rural area. In metropolitan cities across the world, automobiles are the primary cause of air pollution. The use rate of vehicles keeps increasing, and that results in traffic congestion. This work is focusing on collecting two real-time vehicle emission datasets from two different devices to predict and compare the emissions of different light-duty vehicles by using the machine learning techniques. This research also analyzes the Canadian government emission dataset It shows the results of emission by fuel type and vehicle model. It shows the comparison graph of, mean square error, root mean square error and accuracy comparison of different machine learning algorithms. The work suggests some policies for reducing the carbon emissions. Even the government can adapt certain policies for mitigating the carbon emissions of individual vehicles. In this research work issues for reducing the emission of individual vehicles have been addressed. This work helps the automobile sector to reduce the emission and play a part to save the environment.
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Shao, Heng, Hua Hu, Yitao Luo, et al. "Impact of Mid-to-Low-Ash, Low-Viscosity Lubricants on Aftertreatment Systems after 210,000-Kilometer Real-World Road Endurance Trials." Lubricants 12, no. 7 (2024): 240. http://dx.doi.org/10.3390/lubricants12070240.
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Engine lubricants globally face the challenge of meeting the demands of new engine technologies while enhancing energy efficiency and reducing emissions. Lubricants must enhance their performance and sustainability, improve reliability in complex and harsh environments, and minimize environmental impact and health risks. This study explores the influence of two different formulations of low viscosity lubricants, tested through actual road endurance trials, on a hybrid vehicle’s aftertreatment system performance and overall emission levels. The study includes 120,000 km of endurance testing in four different challenging environments in China, as well as 90,000 km of endurance testing in a typical urban and highway driving cycle in a large city. Results indicate that emissions from the test vehicles during the 120,000 km and 210,000 km durable Worldwide harmonized Light vehicle Test Cycles (WLTCs) meet China’s Stage 6 light-duty vehicle emission standards, with the 210,000 km Real Driving Emission test (RDE) results also conforming to these standards. Relative to fresh TWC, the light-off temperature increased by a mere 60 °C, and the oxygen storage capacity declined by around 19% following endurance testing. Additionally, the GPF exhibited satisfactory performance after 210,000 km of endurance testing, showing lower backpressure values compared to the fresh-coated samples, with no notable ash buildup observed in the substrate. Drawing on the outcomes of actual road endurance testing, this study illustrates that employing low-to-mid-ash-content, low-viscosity lubricants is both compatible and reliable for aftertreatment systems in present or advanced hybrid technologies. Premium lubricants facilitate vehicles in sustaining compliant and stable emission performance, even amid harsh environments and complex operating conditions. Furthermore, the tested lubricants effectively inhibit excessive aging of the aftertreatment system over prolonged mileage. Moreover, this study discusses the feasibility of rapid aging evaluation methods for aftertreatment systems based on engine test benches, juxtaposed with actual road endurance testing. These findings and conclusions offer crucial references and guidance for enhancing lubricant performance and sustainability. Subsequent studies can delve deeper into the correlation between lubricant performance and environmental impact, alongside optimization strategies for lubricants across various vehicle models and usage scenarios.
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Xue, Yifeng, Xizi Cao, Yi Ai, Kangli Xu, and Yichen Zhang. "Primary Air Pollutants Emissions Variation Characteristics and Future Control Strategies for Transportation Sector in Beijing, China." Sustainability 12, no. 10 (2020): 4111. http://dx.doi.org/10.3390/su12104111.
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Air pollutant emissions from vehicles, railways, and aircraft for freight and passenger transportation are major sources of air pollution, and strongly impact the air quality of Beijing, China. To better understand the variation characteristics of these emissions, we used the emission factor method to quantitatively determine the air pollutant emissions from the transportation sector. The emission intensity of different modes of transportation was estimated, and measures are proposed to prevent and control air pollutants emitted from the transportation sector. The results showed that air pollutant emissions from the transportation sector have been decreasing year by year as a result of the reduction in emissions from motor vehicles, benefiting from the structural adjustment of motor vehicles. A comparison of the emission intensity of primary air pollutants from different modes of transportation showed that the emission level of railway transportation was much lower than that of road transportation. However, Beijing relies heavily on road transportation, with road freight transportation accounting for 96% of freight transportation, whereas the proportion of railway transportation was low. Primary air pollutants from the transportation sector contributed significantly to the total emissions in Beijing. The proportion of NOX emissions increased from 54% in 2013 to 58% in 2018. To reduce air pollutant emissions from the transportation sector, further adjustments and optimization of the structure of transportation in Beijing are needed. As for the control of motor vehicle pollutant emissions, vehicle composition must be adjusted and the development of clean energy must be promoted, as well as the replacement of diesel vehicles with electric vehicles for passenger and freight transportation.
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Kawamoto, Ryuji, Hideo Mochizuki, Yoshihisa Moriguchi, et al. "Estimation of CO2 Emissions of Internal Combustion Engine Vehicle and Battery Electric Vehicle Using LCA." Sustainability 11, no. 9 (2019): 2690. http://dx.doi.org/10.3390/su11092690.
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In order to reduce vehicle emitted greenhouse gases (GHGs) on a global scale, the scope of consideration should be expanded to include the manufacturing, fuel extraction, refinement, power generation, and end-of-life phases of a vehicle, in addition to the actual operational phase. In this paper, the CO2 emissions of conventional gasoline and diesel internal combustion engine vehicles (ICV) were compared with mainstream alternative powertrain technologies, namely battery electric vehicles (BEV), using life-cycle assessment (LCA). In most of the current studies, CO2 emissions were calculated assuming that the region where the vehicles were used, the lifetime driving distance in that region and the CO2 emission from the battery production were fixed. However, in this paper, the life cycle CO2 emissions in each region were calculated taking into consideration the vehicle’s lifetime driving distance in each region and the deviations in CO2 emissions for battery production. For this paper, the US, European Union (EU), Japan, China, and Australia were selected as the reference regions for vehicle operation. The calculated results showed that CO2 emission from the assembly of BEV was larger than that of ICV due to the added CO2 emissions from battery production. However, in regions where renewable energy sources and low CO2 emitting forms of electric power generation are widely used, as vehicle lifetime driving distance increase, the total operating CO2 emissions of BEV become less than that of ICV. But for BEV, the CO2 emissions for replacing the battery with a new one should be added when the lifetime driving distance is over 160,000 km. Moreover, it was shown that the life cycle CO2 emission of ICV was apt to be smaller than that of BEV when the CO2 emissions for battery production were very large.
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Mei, Hui, Lulu Wang, Menglei Wang, et al. "Characterization of Exhaust CO, HC and NOx Emissions from Light-Duty Vehicles under Real Driving Conditions." Atmosphere 12, no. 9 (2021): 1125. http://dx.doi.org/10.3390/atmos12091125.
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On-road exhaust emissions from light-duty vehicles are greatly influenced by driving conditions. In this study, two light-duty passenger cars (LDPCs) and three light-duty diesel trucks (LDDTs) were tested to investigate the on-road emission factors (EFs) with a portable emission measurement system. Emission characteristics of carbon monoxide (CO), hydrocarbons (HC) and nitrogen oxides (NOx) emitted from vehicles at different speeds, accelerations and vehicle specific power (VSP) were analyzed. The results demonstrated that road conditions have significant impacts on regulated gaseous emissions. CO, NOx, and HC emissions from light-duty vehicles on urban roads increased by 1.1–1.5, 1.2–1.4, and 1.9–2.6 times compared with those on suburban and highway roads, respectively. There was a rough positive relationship between transient CO, NOx, and HC emission rates and vehicle speeds, while the EFs decreased significantly with the speed decrease when speed ≤ 20 km/h. The emissions rates of NOx and HC tended to increase and then decrease as the acceleration increased and the peak occurred at 0 m/s2 without considering idling conditions. For HC and CO, the emission rates were low and changed gently with VSP when VSP < 0, while emission rates increased gradually with the VSP increase when VSP > 0. For NOx NOx emission rates were lower and had no obvious change when VSP < 0. However, NOx emissions were positively correlated with VSP, when VSP > 0.
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Yan, Feng, and Haiguang Zhao. "Research on the impacts of GPF on RDE emission behaviors." E3S Web of Conferences 522 (2024): 01005. http://dx.doi.org/10.1051/e3sconf/202452201005.
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In this research, RDE tests were carried out on a pre-China 6 TGDI vehicle in the two cases of installing or not installing GPF to explore the impacts of GPF on RDE emission behaviors. The results indicated that the GPF can effectively filter PN emissions, especially at low speed, high load engine operating conditions, where the PN emissions can be reduced to about 1/200 of the original emissions. For TGDI vehicles, the installation of GPF can reduce the RDE PN emissions by more than 30 times, which indicates that the GPF is the key post-processing device for TGDI vehicles to meet the China 6 regulation. And in the upgrade process of China 5 vehicles to China 6 vehicles, especially for TGDI vehicles, the engine, the post processor and the turbocharger all needs re-calibrating or re-matching to concur a series of problems the back pressure raise caused by the installation of GPF, which may bring deterioration of engine combustion process, decrease of catalyst temperature and similar conditions that will worsen the vehicle emissions.
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Heimrich, M. J., S. Albu, and M. Ahuja. "Electrically Heated Catalysts for Cold-Start Emission Control on Gasoline- and Methanol-Fueled Vehicles." Journal of Engineering for Gas Turbines and Power 114, no. 3 (1992): 496–501. http://dx.doi.org/10.1115/1.2906616.
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Cold-start emissions from current technology vehicles equipped with catalytic converters can account for over 80 percent of the emissions produced during the Federal Test Procedure (FTP). Excessive pollutants can be emitted for a period of one to two minutes following cold engine starting, partially because the catalyst has not reached an efficient operating temperature. Electrically heated catalysts, which are heated prior to engine starting, have been identified as a potential strategy for controlling cold-start emissions. This paper summarizes the emission results of three gasoline-fueled and three methanol-fueled vehicles equipped with electrically heated catalyst systems. Results from these vehicles demonstrate that heated catalyst technology can provide FTP emission levels of nonmethane organic gases (NMOG), carbon monoxide (CO), and oxides of nitrogen (NOx) that show promise of meeting the Ultra-Low Emission Vehicle (ULEV) standards established by the California Air Resources Board.
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Li, Bingbing, Jiaren Li, Jiang Lu, and Zhenyi Xu. "Spatiotemporal Distribution Characteristics and Inventory Analysis of Near-Road Traffic Pollution in Urban Areas." Atmosphere 15, no. 4 (2024): 417. http://dx.doi.org/10.3390/atmos15040417.
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Vehicle emissions belong to the category of near-surface sources, occur close to human activity areas, and pose a greater threat to human health than other anthropogenic pollution sources. Furthermore, the study of the spatiotemporal characteristics of near-road traffic pollution is of great significance to urban and regional ambient air quality management, and is also an important basis for vehicle emission inventories, as well as the assessment of ambient air impact. Most previous studies have analyzed the spatiotemporal characteristics of hydrocarbons (HCs), carbon monoxide (CO), nitrogen oxides (NOx), and carbon dioxide (CO2) in urban vehicle emissions over a certain time, without considering the synergistic effect of mobile source particulate matter, NOx, and volatile organic compounds (VOCs). In this study, we analyze the composition of vehicles with different emission standards from road mobile sources in Anqing City, China. National category III and IV vehicles are the main contribution sources of various pollutants, accounting for more than 60% of emissions. Although national category I and II vehicles accounted for less than 1% of the total number of vehicles, their contribution to emissions cannot be ignored, especially for CO and HCs, the contribution of which from such vehicles can reach about 7%. This is mainly due to the low level of pollution control arising from the larger emission factor and greater age of these vehicles. Furthermore, eliminating old cars and increasing the proportion of national category VI vehicles can effectively reduce vehicle pollutant emissions. In terms of the spatiotemporal distribution characteristics, highways around urban areas are also the main sources of heavy vehicles, and the emission intensity of these pollutants is also higher on national roads and highways surrounding urban areas. In addition, the presence of m/p-xylene and toluene solvent-using species is detected, which indicates that petrol vehicle emissions, LPG and petrol volatilization, and solvent-using sources contribute significantly to ozone formation in the ozone pollution process. Comparing weekdays and non-weekdays, the PM2.5 peaks on non-weekdays are significantly higher than those on weekdays, and there is no “weekend effect”, which indicates that traffic emissions have little influence on PM2.5 emissions, and may be related to energy use and industrial pollution. Overall, this study strengthens the understanding of the relationship between emissions, traffic volumes, and vehicle types on spatial and temporal scales, and emphasizes the need for further investigation and comprehensive measures to mitigate pollution from these emissions.
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Gan, Yu, Zifeng Lu, Xin He, Michael Wang, and Amer Ahmad Amer. "Cradle-to-Grave Lifecycle Analysis of Greenhouse Gas Emissions of Light-Duty Passenger Vehicles in China: Towards a Carbon-Neutral Future." Sustainability 15, no. 3 (2023): 2627. http://dx.doi.org/10.3390/su15032627.
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Vehicle electrification is considered a pathway for on-road transportation decarbonization in China. Different from the conventional gasoline vehicles whose emissions are mainly released from vehicle tailpipes, emissions of battery electric vehicles (BEVs) are from the upstream processes of electricity generation and vehicle manufacturing, thus a comprehensive lifecycle analysis and comparison of BEVs with gasoline vehicles is required to quantify the emission mitigation benefit of vehicle electrification and determine the path to a carbon-neutral future. In the study, we compare the cradle-to-grave (C2G) lifecycle greenhouse gas emissions of gasoline and electric vehicles in China and analyze the greenhouse gas emission reduction of vehicle electrification in different provinces. Results show that under the current technologies, the national average C2G GHG emissions for battery electric vehicles (BEVs) of 100 miles (i.e., 160 km) and 300 miles (i.e., 480 km) all-electric range (AER) are 231 and 279 g CO2eq/km, respectively, 22% and 5% lower than those for gasoline internal combustion engine vehicles (ICEVs). Improving vehicle fuel efficiency by hybridizing gasoline ICEVs can effectively reduce C2G emissions to 212 g CO2eq/km. At the provincial level, C2G GHG emissions of BEVs vary according to the provincial electricity mix. In eight provinces, C2G GHG emissions of BEVs with 300 miles AER (BEV300s) are higher than those of gasoline ICEVs due to the GHG-intensive coal-based electricity mix. In the future scenario, with low carbon fuels (such as high-level bioethanol blending gasoline) and electricity decarbonization, the national average C2G emissions of hybrid electric vehicles (HEVs) and BEV300s can be reduced to 55 and 73 g CO2eq/km, respectively. Further decrease of C2G GHG emissions relies on reducing vehicle-cycle emissions from material processing and vehicle component manufacturing.
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Pratiwi, Ningsih Ika, Suherman Suherman, Bambang Yulianto, and Muhammad Amin. "Impact of Electric Vehicle Transition Scenarios on Road Transport Emission in Semarang City." Jurnal Presipitasi : Media Komunikasi dan Pengembangan Teknik Lingkungan 22, no. 1 (2024): 301–13. https://doi.org/10.14710/presipitasi.v22i1.301-313.
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The transition from fossil-fueled vehicles into electric vehicles is considered to be a strategy that can significantly reduce emissions and improve urban air quality. This study aims to examine the impact of the battery electric vehicles growth in Semarang City on carbon emissions within the road transport sector. Projections were made to assess the long-term impact and contribution of this trend towards meeting government targets in 2030 and 2060. Low Emission Analysis Platform (LEAP) software was used to estimate carbon emissions based on amount of vehicle and vehicle kilometer traveled (VKT) data. Three scenarios were set: the BEV scenario, which focuses on the widespread use of electric vehicles, demonstrates a significant reduction, especially in PM10 emissions, highlighting the advantages of transitioning away from internal combustion engine vehicles. The EMX scenario, which emphasizes an energy mix plan to support electricity, does not demonstrate a significant reduction in emissions. The COM scenario, which combine the BEV and EMX scenarios achieves the lowest emissions overall, indicating that a comprehensive strategy is most effective for achieving long-term emission reductions. All scenarios indicate the need for more aggressive policies, technological innovations, and carbon capture strategies to achieve reduction targets, particularly in the road transport sector.
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Salazar, Joseph R., Benton T. Cartledge, John P. Haynes, et al. "Water-soluble iron emitted from vehicle exhaust is linked to primary speciated organic compounds." Atmospheric Chemistry and Physics 20, no. 3 (2020): 1849–60. http://dx.doi.org/10.5194/acp-20-1849-2020.
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Abstract. Iron is the most abundant transition element in airborne particulate matter (PM), primarily existing as Fe(II) or Fe(III). Generally, the fraction of water-soluble iron is greater in urban areas compared to areas dominated by crustal emissions. To better understand the origin of water-soluble iron in urban areas, tailpipe emission samples were collected from 32 vehicles with emission certifications of Tier 0 low emission vehicles (LEV I), Tier 2 low emission vehicles (LEV II), ultralow emission vehicles (ULEVs), super-ultralow emission vehicles (SULEVs), and partial-zero emission vehicles (PZEVs). The components quantified included gases, inorganic ions, elemental carbon (EC), organic carbon (OC), total metals, and water-soluble metals. Naphthalene and intermediate-volatility organic compounds (IVOCs) were quantified for a subset of vehicles. The IVOCs quantified contained 12 to 18 carbons and were divided into three subgroups: aliphatic, single-ring aromatic (SRA), and polar (material not classified as either aliphatic or SRA). Iron solubility in the tested vehicles ranged from 0 % to 82 % (average 30 %). X-ray absorption near-edge structure (XANES) spectroscopy showed that Fe(III) was the primary oxidation state in 14 of the 16 tested vehicles, confirming that the presence of Fe(II) was not the main driver of water-soluble Fe. The correlation of water-soluble iron with sulfate was insignificant, as was correlation with every chemical component except naphthalene and some C12–C18 IVOCs with R2 values as high as 0.56. A controlled benchtop study confirmed that naphthalene alone increases iron solubility from soils by a factor of 5.5 and that oxidized naphthalene species are created in the extract solution. These results suggest that the large driver in water-soluble iron from primary vehicle tailpipe emissions is related to the organic composition of the PM. We hypothesize that, during the extraction process, specific components of the organic fraction of the PM are oxidized and chelate the iron into water.
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Garcia, Julieth Stefany, Laura Milena Cárdenas, Jose Daniel Morcillo, and Carlos Jaime Franco. "Policy Assessment for Energy Transition to Zero- and Low-Emission Technologies in Pickup Trucks: Evidence from Mexico." Energies 17, no. 10 (2024): 2386. http://dx.doi.org/10.3390/en17102386.
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The transport sector is under scrutiny because of its significant greenhouse gas emissions. Essential strategies, particularly the adoption of zero- and low-emission vehicles powered by electricity, are crucial for mitigating emissions in road transport. Pickups, which are integral to Mexico’s fleet, contribute to such emissions. Thus, implementing effective policies targeting pickups is vital for reducing air pollution and aligning with Mexico’s decarbonization objectives. This paper presents a simulation model based on system dynamics to represent the adoption process of zero- and low-emission vehicles, with a focus on pickups and utilizing data from the Mexican case. Three policy evaluation scenarios are proposed based on the simulation model: business as usual; disincentives for zero- and low-emission vehicles; and incentives for unconventional vehicles. One of the most significant findings from this study is that even in a scenario with a greater number of vehicles in circulation, if the technology is fully electric, the environmental impact in terms of emissions is lower. Additionally, a comprehensive sensitivity analysis spanning a wide spectrum is undertaken through an extensive computational process, yielding multiple policy scenarios. The analysis indicates that to achieve a maximal reduction in the country’s emissions, promoting solely hybrid electric vehicles and plug-in hybrid electric vehicles is advisable, whereas internal combustion engines, vehicular natural gas, and battery electric vehicles should be discouraged.
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Stanojevic, Nada, Milos Vasic, and Vladimir Popovic. "The contribution of CNG powered vehicles in the transition to zero emission mobility - example of the light commercial vehicles fleet." Thermal Science, no. 00 (2020): 241. http://dx.doi.org/10.2298/tsci200721241s.
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The aim of paper was to discuss contribution of bi-fuel CNG powered light commercial vehicles to the Well-To-Wheel CO2 equivalent emissions, both today and in the coming decades in which the development of new fuels and new vehicles is expected. Field research was done in Belgrade, during one year, using Euro 5 diesel/LPG/CNG light commercial vehicles driving under low vehicle speed, low engine load, low exhaust gas temperature and high number of stops. WTW as neutral methodology was applied for understanding of each fuel pathway in terms of reducing greenhouse gas emissions and increasing energy efficiency. Calculation showed that total energy consumption per km is the lowest for diesel vehicles since petrol/LPG and petrol/CNG vehicles use 21% and 7 % more energy. Tank-To-Wheel emission of CO2e is most favorable for petrol/CNG with 28.8 % and 6.7 % less CO2e with petrol/LPG and diesel vehicles. The same conclusion brings Well-To-Wheel analysis showing that diesel/CNG CO2e emission is 13.5 % less than petrol/LPG, apropos 1.5 % less than diesel operated vehicles considered within this field research. Figures are not as high as previous, due to the results of Well-To-Tank emission, that were most favorable for petrol/LPG powered vehicles, with almost 51% and 32% better results regarding to petrol/CNG and diesel, respectively. Within same time, lowest fuel cost per km was achieved by petrol/CNG vehicles, with 32% and 35% less cost than petrol/LPG and diesel vehicles. The available CNG technology should not be neglected, waiting for new solutions to be proven.
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Jo, Hanghun, and Heungsoon Kim. "Developing a Traffic Model to Estimate Vehicle Emissions: An Application in Seoul, Korea." Sustainability 13, no. 17 (2021): 9761. http://dx.doi.org/10.3390/su13179761.
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In this study, a traffic demand model was created based on a simulation network, and another model was built to calculate exhaust-gas emissions generated by vehicles based on the emission function. Subsequently, emissions for three scenarios were analyzed based on the traffic restriction policy according to the vehicle grading system implemented in Seoul. According to the results of the analysis, emission reduction under the vehicle restriction policy was the highest among passenger cars in the low-speed range, while the emissions of cargo trucks in the high-speed range were found to be high. The emissions showed a high ratio of carbon monoxide and nitrogen oxides, and high emissions were generated from liquefied petroleum gas and diesel vehicles. Furthermore, the effects of vehicle restriction policy were confirmed to reduce emissions from diesel and other vehicle types. Using the established model, we were able to confirm that the vehicle restriction policy contributed to the improvement of air quality. Furthermore, the diesel vehicle restriction policy also had an impact on reducing the emissions of vehicle types other than those using diesel.
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Peng, Tu, Xu Yang, Zi Xu, and Yu Liang. "Constructing an Environmental Friendly Low-Carbon-Emission Intelligent Transportation System Based on Big Data and Machine Learning Methods." Sustainability 12, no. 19 (2020): 8118. http://dx.doi.org/10.3390/su12198118.
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The sustainable development of mankind is a matter of concern to the whole world. Environmental pollution and haze diffusion have greatly affected the sustainable development of mankind. According to previous research, vehicle exhaust emissions are an important source of environmental pollution and haze diffusion. The sharp increase in the number of cars has also made the supply of energy increasingly tight. In this paper, we have explored the use of intelligent navigation technology based on data analysis to reduce the overall carbon emissions of vehicles on road networks. We have implemented a traffic flow prediction method using a genetic algorithm and particle-swarm-optimization-enhanced support vector regression, constructed a model for predicting vehicle exhaust emissions based on predicted road conditions and vehicle fuel consumption, and built our low-carbon-emission-oriented navigation algorithm based on a spatially optimized dynamic path planning algorithm. The results show that our method could help to significantly reduce the overall carbon emissions of vehicles on the road network, which means that our method could contribute to the construction of low-carbon-emission intelligent transportation systems and smart cities.
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Bajerlein, Maciej, and Michał Kerntopf. "Assessment of actual vehicle emissions in the context of Low Emission Zones." Journal of Civil Engineering and Transport 6, no. 4 (2024): 39–54. https://doi.org/10.24136/tren.2024.016.
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In 2024, Clean Transport Zones were established in the first Polish cities, restricting the right to enter the centers of the largest agglomerations for vehicles that do not meet the latest exhaust emission standards. This solution aims to both counteract air pollution in the vicinity of the largest population centers, but also to limit car traffic in the centers of the largest cities. The imperfection of the vehicle selection key is limited to meeting the appropriate EURO standard, which may not clearly define the actual emission. The aim of the work is to determine the methodology for effective comparison of the results of total vehicle exhaust emissions.
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Deng, Yueming. "Future Vehicle Trend: A Comparative Study of the Fuel Vehicle, Electrical Vehicle, and Hybrid Vehicles." Highlights in Science, Engineering and Technology 29 (January 31, 2023): 143–48. http://dx.doi.org/10.54097/hset.v29i.4531.
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As the second largest carbon emission industry in the world, the automobile industry faces serious energy consumption and environmental pollution problems. The development of a low-carbon economy requires cars to achieve low energy consumption, lower emissions require the development of more advanced and environmentally friendly technologies. Three dominant kinds of vehicles, fuel vehicles, electrical vehicles, and hybrid vehicles will be explored in this paper. Section one introduces the types of fuel vehicles, the factors that affect them, and their negative impact on the environment. Section two focuses on the advantages of hybrid vehicles over gasoline and pure electric vehicles in terms of their operation and driving costs. Section two discusses the advantages of hybrid vehicles compared to gasoline and electric vehicles in terms of their operation and driving costs. In section three, the characteristics of various types of electric vehicles are comprehensively evaluated, and the prospects of the exhibition of electric vehicles are discussed. Finally, the future development trend of electric vehicles is forecasted.
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Giechaskiel, Barouch, Victor Valverde, Anastasios Kontses, et al. "Effect of Extreme Temperatures and Driving Conditions on Gaseous Pollutants of a Euro 6d-Temp Gasoline Vehicle." Atmosphere 12, no. 8 (2021): 1011. http://dx.doi.org/10.3390/atmos12081011.
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Gaseous emissions of modern Euro 6d vehicles, when tested within real driving emissions (RDE) boundaries, are, in most cases, at low levels. There are concerns, though, about their emission performance when tested at or above the boundaries of ambient and driving conditions requirements of RDE regulations. In this study, a Euro 6d-Temp gasoline direct injection (GDI) vehicle with three-way catalyst and gasoline particulate filter was tested on the road and in a laboratory at temperatures ranging between −30 °C and 50 °C, with cycles simulating urban congested traffic, uphill driving while towing a trailer at 85% of the vehicle’s maximum payload, and dynamic driving. The vehicle respected the Euro 6 emission limits, even though they were not applicable to the specific cycles, which were outside of the RDE environmental and trip boundary conditions. Most of the emissions were produced during cold starts and at low ambient temperatures. Heavy traffic, dynamic driving, and high payload were found to increase emissions depending on the pollutant. Even though this car was one of the lowest emitting cars found in the literature, the proposed future Euro 7 limits will require a further decrease in cold start emissions in order to ensure low emission levels under most ambient and driving conditions, particularly in urban environments. Nevertheless, motorway emissions will also have to be controlled well.
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Marzoug, Rachid, Noureddine Lakouari, José Roberto Pérez Cruz, and Carlos Jesahel Vega Gómez. "Cellular Automata Model for Analysis and Optimization of Traffic Emission at Signalized Intersection." Sustainability 14, no. 21 (2022): 14048. http://dx.doi.org/10.3390/su142114048.
Full textAbstract:
Traffic emission is one of the most severe issues in our modern societies. A large part of emissions occurs in cities and especially at intersections due to the high interactions between vehicles. In this paper, we proposed a cellular automata model to investigate the different traffic emissions (CO2, PM, VOC, and NOx) and speeds at a two-lane signalized intersection. The model is designed to analyze the effects of signalization by isolating the parameters involved in vehicle-vehicle interactions (lane changing, speed, density, and traffic heterogeneity). It was found that the traffic emission increases (decreases) with the increasing of green lights duration (Tg) at low (high) values of vehicles injection rate (α). Moreover, by taking CO2 as the order parameter, the phase diagram shows that the system can be in four different phases (I, II, III, and IV) depending on α and Tg. The transition from phase II (I) to phase III (II) is second order, while the transition from phase II to phase IV is first order. To reduce the traffic emission and enhance the speed, two strategies were proposed. Simulation results show a maximum reduction of 13.6% in vehicles’ emissions and an increase of 9.5% in the mean speed when adopting self-organizing intersection (second strategy) at low and intermediate α. However, the first strategy enhances the mean speed up to 28.8% and reduces the traffic emissions by 3.6% at high α. Therefore, the combination of both strategies is recommended to promote the traffic efficiency in all traffic states. Finally, the model results illustrate that the system shows low traffic emission adopting symmetric lane-changing rules than asymmetric rules.
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Gao, Tao. "Research on Simulation Algorithm of Series Hybrid Electric Vehicle Energy and Intelligent Control." International Journal of Advanced Pervasive and Ubiquitous Computing 9, no. 4 (2017): 33–77. http://dx.doi.org/10.4018/ijapuc.2017100103.
Full textAbstract:
Hybrid electric vehicle (HEV) is a kind of new cars with low fuel consumption and low emissions, which combines the advantages of traditional vehicle's long endurance and no-pollution of pure electric vehicles. It represents the future direction of development of vehicle for a period of time. Therefore, the research of HEV technology has important practical significance to the development of China's automobile. This paper takes Shijiazhuang bus as the research object, makes parameter matching according to the parameters of the vehicle, builds the vehicle model using Cruise software, set the simulation task, and studies the control strategy to reduce automobile fuel and pollutant emission targets. The research of this paper has certain directive significance to the modeling and energy optimization of hybrid electric vehicle.
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Jiang, Xiaoyun, Xiangxin Liu, Fubin Pan, and Zinuo Han. "Optimizing Cold Chain Distribution Routes Considering Dynamic Demand: A Low-Emission Perspective." Sustainability 16, no. 5 (2024): 2013. http://dx.doi.org/10.3390/su16052013.
Full textAbstract:
Cold chain logistics, with its high carbon emissions and energy consumption, contradicts the current advocacy for a “low-carbon economy”. Additionally, in the real delivery process, customers often generate dynamic demand, which has the characteristic of being sudden. Therefore, to help cold chain distribution companies achieve energy-saving and emission-reduction goals while also being able to respond quickly to customer needs, this article starts from a low-carbon perspective and constructs a two-stage vehicle distribution route optimization model that minimizes transportation costs and refrigeration costs, alongside carbon emissions costs. This research serves to minimize the above-mentioned costs while also ensuring a quick response to customer demands and achieving the goals of energy conservation and emission reduction. During the static stage, in order to determine the vehicle distribution scheme, an enhanced genetic algorithm is adopted. During the dynamic optimization stage, a strategy of updating key time points is employed to address the dynamic demand from customers. By comparing the dynamic optimization strategy with the strategy of dispatching additional vehicles, it is demonstrated that the presented model is capable of achieving an overall cost reduction of approximately 17.13%. Notably, carbon emission costs can be reduced by around 17.11%. This demonstrates that the dynamic optimization strategy effectively reduces the usage of distribution vehicles and lowers distribution costs.
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Huang, Junfeng, Jianbing Gao, Yufeng Wang, Ce Yang, and Chaochen Ma. "Real-World Pipe-Out Emissions from Gasoline Direct Injection Passenger Cars." Processes 11, no. 1 (2022): 66. http://dx.doi.org/10.3390/pr11010066.
Full textAbstract:
The analysis of real-world emissions is necessary to reduce the emissions of vehicles during on-road driving. In this paper, the matrix of gasoline direct injection passenger cars is applied to analyze the real-world emissions. The results show that high acceleration and high speed conditions are major conditions for the particulate number emissions, and the particulate number emissions are positively correlated with torque and throttle opening. The catalyst temperature and saturation are important factors that affect nitrogen oxide emission. The nitrogen oxide emissions of low speed and low torque conditions cannot be ignored in real-world driving. The carbon dioxide emissions are positively correlated with acceleration, torque and throttle opening. Once the vehicles are in the acceleration condition, the carbon dioxide emissions increase rapidly. The vehicles with higher average emission factors are more susceptible to driving behaviors, and the differences in the emission factors are more obvious, leading to an increase in the difficulty of emission control.
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Li, Yixuan, Zhuoying Zhao, Xinxin Su, and Yunquan Song. "Machine Learning for New Energy Vehicle Sales Prediction and Carbon Emission Impact." Journal of Computing and Electronic Information Management 16, no. 3 (2025): 48–53. https://doi.org/10.54097/ygxwhp75.
Full textAbstract:
China's new energy vehicle market is in a booming stage, with the number of new energy vehicle buyers increasing year by year. The promotion of new energy vehicles is of great significance in reducing carbon emissions, environmental protection and promoting the construction of a clean and low-carbon society. In-depth analysis of market demand through the use of data mining and machine learning algorithms can help companies improve the market competitiveness and promotion of new energy vehicles. At the same time, in-depth study of the reduction effect of new energy vehicles on carbon emissions will help to comprehensively assess their environmental benefits and provide a scientific basis for the government to formulate carbon emission reduction policies and promote the development of the new energy vehicle industry. In this paper, we screened the multifaceted factors affecting the sales of new energy vehicles by using the random forest model, and then used the support vector regression machine to predict the sales of different brands of new energy vehicles in the next two months, and further verified the accuracy and reliability of the model after the effect evaluation on the test set. In addition, this paper establishes a panel regression model of the carbon emission reduction effect of new energy vehicles by introducing control variables and using panel data from 31 provinces, autonomous regions and municipalities in China from 2017 to 2022. The panel regression model verifies that the development of the new energy vehicle industry is conducive to promoting carbon emission reduction from the overall national level.