Traffic Related Emission

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Air Quality".

Deadline for manuscript submissions: closed (20 April 2023) | Viewed by 24040

Special Issue Editor

School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China
Interests: exhaust and brake emission measurement and control; particularly particles; non regulated pollutants; combustion and emission characteristics of alternative fuels
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Globally, traffic-related emissions play a critical role in contributing to local air pollution issues. The increasing applications of cleaner fuels (including alternative fuels and traditional fuels meeting stricter standards) and emission control devices have largely alleviated the problem of traffic-related emissions. However, new challenges emerge, such as new toxic pollutants (ammonia, benzene, smaller exhaust particles, etc.), concerns over secondary contamination via atmospheric reactions, and life-cycle emission reduction capabilities. All these issues establish the necessity to continue engine emissions research, legislation, and policy assessment in this ‘electrified’ era.

The non-road sector is another source of air pollution but has been relatively underestimated before now. Along with the reduction in on-road engine emissions, the impacts of non-road mobile machineries (NRMMs) are attracting increasing focus. Especially with the outbreaks of several international incidents in the past few years, recent changes in marine emissions may significantly impact both global and coastal inventories.

In addition to engine emissions, non-exhaust emissions, primarily brake and tire particles from motor vehicles and rails, have been considered for future legislation. The priority of their control may potentially grow with the increase in gross vehicle weight and urban traffic congestion.

The scope of this Special Issue covers a wide range of traffic-related emission research on motor vehicles, non-road equipment and engines, and non-exhaust particles. Original research reporting the cutting-edge technologies in emission control and fuel, life-cycle assessment of carbon footprint, and forthcoming emission regulations with experimental data support are highly appreciated. Model-based simulation with insufficient verification and validation will not be considered for publication in this Special Issue.

Dr. Xin Wang
Guest Editor

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Keywords

  • traffic-related emission
  • alternative fuel
  • internal combustion engine
  • motor vehicle
  • non-road mobile machinery (nrmm)
  • non-exhaust particles
  • life-cycle assessment

Published Papers (14 papers)

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15 pages, 1595 KiB  
Article
Estimation of Road Transportation Emissions in Colombia from 2010 to 2021
by Laura Mantilla-Romo, Yiniva Camargo-Caicedo, Sindy Bolaño-Diaz, Fredy Tovar-Bernal and Angélica Garrido-Galindo
Atmosphere 2023, 14(7), 1167; https://doi.org/10.3390/atmos14071167 - 19 Jul 2023
Viewed by 1188
Abstract
This work aimed to estimate the emissions associated with the transport sector in Colombia during the 2010–2021 period for the following four groups of pollutants: greenhouse gases or GHG (CO2, CH4, N2O), ozone precursors (CO, NMVOC, NO [...] Read more.
This work aimed to estimate the emissions associated with the transport sector in Colombia during the 2010–2021 period for the following four groups of pollutants: greenhouse gases or GHG (CO2, CH4, N2O), ozone precursors (CO, NMVOC, NOx), acidifying gases (NH3, SO2), and aerosols (PM, BC), based on the data provided by the Ministry of Mines and Energy. The estimate of emissions from road transportation was calculated using a standardized method with a top-down approach consistent with the 2006 IPCC Guidelines for National GHG Inventories and the EEA/EMEP Emission Inventory Guidebook 2019. Total annual emissions and the emissions for regions were estimated, and a comparison was made between estimated emissions and the emissions calculated by the Emissions Database for Global Atmospheric Research (EDGAR). Total annual emissions by road transport showed a progressive increase except for the annual emissions in 2020, which registered a reduction due to the COVID-19 lockdown. The highest yearly emissions were reported in 2021, with the most significant contributions by GHG (33,109.29 Gg CO2, 201.55 Gg CO2 Eq. CH4, and 512.43 Gg CO2 Eq. N2O). The Andean region was the one with the highest contributions of total emissions within the four groups of pollutants (57–66%), followed by the Caribbean (12–20%) and the Pacific region (14–18%). The most-used fuel was gasoline, with an increase of 103% for personal cars and motorcycles throughout the study period. These results contribute to decision-making at local, regional, and national levels regarding energy transition opportunities and strategies to adopt in the transport sector. Full article
(This article belongs to the Special Issue Traffic Related Emission)
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12 pages, 3709 KiB  
Article
Emission Characteristics of Tyre Wear Particles from Light-Duty Vehicles
by Jiachen Li, Mengzhu Zhang, Yunshan Ge, Yi Wen, Jiaxin Luo, Dailin Yin, Chongyao Wang and Changyu Wang
Atmosphere 2023, 14(4), 724; https://doi.org/10.3390/atmos14040724 - 17 Apr 2023
Cited by 4 | Viewed by 1794
Abstract
Tyre wear particle emissions have gained significant attention due to their harmful effects on the environment and human health. However, studies on tyre wear particles generated under chassis dynamometer conditions are still scarce. This study measures the instantaneous number concentrations and elemental species [...] Read more.
Tyre wear particle emissions have gained significant attention due to their harmful effects on the environment and human health. However, studies on tyre wear particles generated under chassis dynamometer conditions are still scarce. This study measures the instantaneous number concentrations and elemental species of tyre wear particles in different light-duty vehicle test cycles. The results show that the particle number (PN) concentrations of the US06 test cycle are much higher than those of the WLTC test cycle due to the larger and more frequent accelerations and decelerations in the former. High PN concentrations are observed during high driving speeds with rapid accelerations, while PN concentrations are much lower during low driving speed with rapid acceleration. Furthermore, tyre tread temperature is found to be related to the formation of tyre wear particles. The PN concentration in the second and third US06 test cycles are similar, indicating that once the tyre temperature exceeds the critical value, the tyres become heated to a steady state, and the PN concentrations will not be affected by the average temperature of the tyre. A low initial tyre temperature can produce high PN concentrations during the cold start phase of test cycles and prolong the time required for tyres to warm up. In addition, the particles contained a high mass fraction of Zn, which can serve as a tracer of tyre wear particles in non-exhaust particle tests of vehicles. Full article
(This article belongs to the Special Issue Traffic Related Emission)
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17 pages, 6659 KiB  
Article
Physicochemical Analysis of Particle Matter from a Gasoline Direct Injection Engine Based on the China Light-Duty Vehicle Test Cycle
by Hao Wang, Chao He, Haisheng Yu, Jiaqiang Li and Xueyuan Liu
Atmosphere 2023, 14(4), 710; https://doi.org/10.3390/atmos14040710 - 13 Apr 2023
Cited by 1 | Viewed by 1439
Abstract
This paper investigated the physical and chemical properties of gasoline direct injection (GDI) engine particulate matter (PM). The physical properties mainly included the particulate aggregate morphology, primary particle size, and internal nanostructure. High-resolution transmission electron microscopy (HRTEM) and scanning electron microscopy (SEM) were [...] Read more.
This paper investigated the physical and chemical properties of gasoline direct injection (GDI) engine particulate matter (PM). The physical properties mainly included the particulate aggregate morphology, primary particle size, and internal nanostructure. High-resolution transmission electron microscopy (HRTEM) and scanning electron microscopy (SEM) were used to obtain particle morphology information and to conduct image processing and analysis. The chemical characterization tests included X-ray photoelectron spectroscopy (XPS), energy dispersive scanning (EDS), Raman spectroscopy, Fourier-transform infrared spectroscopy (FTIR), and thermal gravimetric analysis (TGA). XPS can be used to observe the content of carbon and oxygen components and the surface carbon chemistry status, EDS can be used to obtain the elemental composition of particles, and TGA is used to analyze the oxidative kinetics of particles. Samples were collected from the exhaust emissions of a passenger vehicle compliant with China’s VI emission standards under China Light-Duty Vehicle Test Cycle (CLTC) test conditions. The study found that the particle morphology mainly comprised primary particles stacked on top of each other to form agglomerate structures, and the primary particles exhibited a core–shell structure. Analysis showed that carbon and oxygen were the predominant components of the particles, with other metallic elements also present. The XPS observations agreed with the FTIR results, indicating a small amount of oxygen was present on the particle surface and that the carbon components consisted mainly of sp2 hybridized graphite and sp3 hybridized organic carbon. The TGA results indicated high characteristic temperatures and low oxidation activity. Full article
(This article belongs to the Special Issue Traffic Related Emission)
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13 pages, 3265 KiB  
Article
Evaluating the Measurement Uncertainty of On-Road NOx Using a Portable Emission Measurement System (PEMS) Based on Real Testing Data in China
by Sheng Su, Pan Hou, Xin Wang, Liqun Lyu, Yang Ge, Tao Lyu, Yitu Lai, Wanyou Luo and Yachao Wang
Atmosphere 2023, 14(4), 702; https://doi.org/10.3390/atmos14040702 - 11 Apr 2023
Cited by 4 | Viewed by 1533
Abstract
An evaluation of the measurement uncertainty of on-road NOx emissions using portable emission measurement system (PEMS) based on real local testing data collected in China was carried out as per the type B method defined in the EN 17507 standard. The aim of [...] Read more.
An evaluation of the measurement uncertainty of on-road NOx emissions using portable emission measurement system (PEMS) based on real local testing data collected in China was carried out as per the type B method defined in the EN 17507 standard. The aim of this work was to quantify the “absolute” measurement uncertainty of PEMSs, which excluded “PEMS relative to laboratory constant volume sampler (CVS)” uncertainty from the calculation of on-road NOx measurement uncertainty using PEMSs. PEMS instruments from three mainstream manufacturers were employed. The zero drift of the NOx analyzers was evaluated periodically during the real driving emissions (RDE) test, and it was noticed that there was neither a linear nor step model of zero drift, with no correlation with the boundary conditions or measurement principle. Additionally, from the 256 valid RDE tests, the zero drift always ranged from 3.8 ppm to −3.8 ppm, and more than 95% of the span drifts were within a range of 1.5%. Based on the laboratory testing of ten vehicles using the worldwide harmonized light-duty vehicle test cycle (WLTC), the type B uncertainty of PEMS NOx measurements corresponding to China-6a and China-6b limits was assessed. An uncertainty of 26.5% for China-6a was found (NOx limit = 60 mg/km over the WLTC), which is very close to the 22.5% from the EU evaluation results (NOx limit = 80 mg/km over the WLTC); the uncertainty with respect to China-6b was found to be 42.8% because the type-I limit was tuned down to 35 mg/km. This result indicates that, with the ever-tightening regulatory limits of vehicle NOx emissions, big challenges will be posed in terms of the reliability of PEMS measurements, which requires PEMS manufacturers to improve the performance of the instruments and policymakers to refine the test procedures and/or result calculation method to minimize the impacts. Full article
(This article belongs to the Special Issue Traffic Related Emission)
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16 pages, 2287 KiB  
Article
Machine Learning-Aided Remote Monitoring of NOx Emissions from Heavy-Duty Diesel Vehicles Based on OBD Data Streams
by Yang Ge, Pan Hou, Tao Lyu, Yitu Lai, Sheng Su, Wanyou Luo, Miao He and Lin Xiao
Atmosphere 2023, 14(4), 651; https://doi.org/10.3390/atmos14040651 - 30 Mar 2023
Viewed by 1435
Abstract
Most of the current, popular approaches to monitoring real driving NOx emissions are based on direct measurement. However, due to the uncertainty of sensor-based measurements, such methods cannot always be used to accurately screen out the malfunctions of an emission control system. In [...] Read more.
Most of the current, popular approaches to monitoring real driving NOx emissions are based on direct measurement. However, due to the uncertainty of sensor-based measurements, such methods cannot always be used to accurately screen out the malfunctions of an emission control system. In this paper, a random forest (RF) model which extracts information from on-board diagnostics (OBD) data streams transmitted by a remote emission management vehicle terminal (REMVT) is proposed to provide a specific emission method for the online screening of high NOx emissions. First, two particular forms of modeling, random forest and logistic regression (LR), are laid out as representatives of nonparametric models and specified linear models. These two models were trained, validated and compared using OBD data collected from three China-VI heavy-duty diesel vehicles (HDDVs). The results show that as a data-driven, highly adaptive and robust learning method, the RF model can more accurately identify an abnormal emission state. Finally, a further validation was conducted, in which another China-VI HDDV was tested in two typical states, including a fault state and a normal state. The results indicated that the RF model could clearly distinguish the out-of-control emission condition from the normal operation state. The outcome of this research verifies the feasibility of using a machine learning model to process remote OBD data on HD vehicles and to identify high emissions in the case of an in-use fleet. On this basis, more sophisticated combined models and multi-stage models could be developed. Full article
(This article belongs to the Special Issue Traffic Related Emission)
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19 pages, 3610 KiB  
Article
Investigation of Heavy-Duty Vehicle Chassis Dynamometer Fuel Consumption and CO2 Emissions Based on a Binning-Reconstruction Model Using Real-Road Data
by Shuojin Ren, Tengteng Li, Gang Li, Xiaofei Liu, Haoye Liu, Xiaowei Wang, Dongzhi Gao and Zhiwei Liu
Atmosphere 2023, 14(3), 528; https://doi.org/10.3390/atmos14030528 - 09 Mar 2023
Cited by 1 | Viewed by 1333
Abstract
Global warming is directly related to heavy-duty vehicle fuel consumption and greenhouse gas (CO2 mainly) emissions, which, in China, are certified on the vehicle chassis dynamometer. Currently, vast amounts of vehicle real-road data from the portable emission measurement system (PEMS) and remote [...] Read more.
Global warming is directly related to heavy-duty vehicle fuel consumption and greenhouse gas (CO2 mainly) emissions, which, in China, are certified on the vehicle chassis dynamometer. Currently, vast amounts of vehicle real-road data from the portable emission measurement system (PEMS) and remote monitoring are being collected worldwide. In this study, a binning-reconstruction calculation model is proposed, to predict the chassis dynamometer fuel consumption and CO2 emissions with real-road data, regardless of operating conditions. The model is validated against chassis dynamometer and PEMS test results, and remote monitoring data. Furthermore, based on the proposed model, the fuel consumption levels of 1408 heavy-duty vehicles in China are analyzed, to evaluate the challenge to meet the upcoming China fourth stage fuel consumption limits. For accumulated fuel consumption based on the on-board diagnostic (OBD) data stream, a predictive relative error less than 5% is expected for the present model. For bag sampling results, the proposed model’s accuracy is expected to be within 10%. The average relative errors between the average fuel consumption and the China fourth stage limits are about 3%, 8%, and 0.7%, for current trucks, tractors, and dump trucks, respectively. The urban operating condition, with lower vehicle speeds, is the main challenge for fuel consumption optimization. Full article
(This article belongs to the Special Issue Traffic Related Emission)
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21 pages, 2645 KiB  
Article
Contribution of Cold Starts to Real-World Trip Emissions for Light-Duty Gasoline Vehicles
by Jiangchuan Hu, H. Christopher Frey and Behdad Yazdani Boroujeni
Atmosphere 2023, 14(1), 35; https://doi.org/10.3390/atmos14010035 - 24 Dec 2022
Cited by 4 | Viewed by 2750
Abstract
For catalytic converter-equipped light-duty gasoline vehicles (LDGV), the hot-stabilized tailpipe emissions for pollutants such as carbon monoxide (CO), hydrocarbons (HC), and nitrogen oxides (NOx) are well controlled. However, there are few reported real-world measurements of cold starts. Idling cold start and [...] Read more.
For catalytic converter-equipped light-duty gasoline vehicles (LDGV), the hot-stabilized tailpipe emissions for pollutants such as carbon monoxide (CO), hydrocarbons (HC), and nitrogen oxides (NOx) are well controlled. However, there are few reported real-world measurements of cold starts. Idling cold start and hot-stabilized trip exhaust emissions were measured for 37 LDGVs using a portable emissions measurement system (PEMS). Five vehicles were also measured for transient driving cold starts. On average, it took approximately 400, 150, 330, and 120 s to accumulate 90 percent of the idle cold start increments for fuel use, CO, HC, and NOx, respectively. Driving cold start increments were substantially higher than idling cold start increments, whereas cold start duration was typically shorter. For example, driving cold start contributed approximately 64%, 68%, 58%, and 4.5% of the trip total CO, HC, NOx, and carbon dioxide (CO2), respectively. This study is unique in quantifying the cold start contribution on a trip basis with real-world data. Although the cold start increment is sensitive to driving compared to idling, in either case, cold starts contribute substantially to total exhaust mass emissions. Furthermore, driver decisions regarding driving versus idle can substantially affect the contribution of cold starts, especially for CO and NOx. Full article
(This article belongs to the Special Issue Traffic Related Emission)
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20 pages, 31303 KiB  
Article
Evolution of the Soot-Particle Size Distribution Function in the Cylinder and Exhaust System of Piston Engines: Simulation
by Sergey M. Frolov, Konstantin A. Avdeev, Vladislav S. Ivanov, Pavel A. Vlasov, Fedor S. Frolov, Ilya V. Semenov and Marina S. Belotserkovskaya
Atmosphere 2023, 14(1), 13; https://doi.org/10.3390/atmos14010013 - 22 Dec 2022
Cited by 2 | Viewed by 1569
Abstract
A computational tool for simulating the temporal evolution of the soot-particle size distribution function (SDF) in the internal combustion engine (ICE) and in the attached exhaust pipe is developed and tested against available experimental data on the soot-particle SDF at the outlet of [...] Read more.
A computational tool for simulating the temporal evolution of the soot-particle size distribution function (SDF) in the internal combustion engine (ICE) and in the attached exhaust pipe is developed and tested against available experimental data on the soot-particle SDF at the outlet of the exhaust system. Firstly, a database of soot particle properties (particle mean diameter, dispersion, total particle number density vs. time for different fuels, fuel-to-air equivalence ratios, temperatures, pressures, and exhaust gas recirculation) is developed based on the thoroughly validated detailed model of soot formation under ICE conditions. The database is organized in the form of look-up tables. Secondly, the soot-particle SDF in the database is approximated using the log-normal SDF, which is directly used in the multidimensional calculations of the ICE operation process. Thirdly, the coagulation model of soot particles is developed, which includes three coagulation mechanisms: Brownian, turbulent–kinetic, and turbulent–diffusion. This model is applied for simulating the evolution of the soot-particle SDF in the exhaust pipe after opening the exhaust valve. Calculations show that the coagulation process of soot particles in the exhaust pipe has a significant effect on the mean size of particles at the outlet of the exhaust system (the mean particle diameter can increase by almost an order of magnitude), and the dominant mechanism of particle coagulation in the exhaust system of a diesel engine is the Brownian mechanism. The objective, approach, and obtained results are the novel features of the study. Full article
(This article belongs to the Special Issue Traffic Related Emission)
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21 pages, 8181 KiB  
Article
Particle Number and Size Distributions (PNSD) from a Hybrid Electric Vehicle (HEV) over Laboratory and Real Driving Emission Tests
by Daisy Thomas, Hu Li, Xin Wang, Karl Ropkins, Alison S. Tomlin, Chris D. Bannister and Gary Hawley
Atmosphere 2022, 13(9), 1510; https://doi.org/10.3390/atmos13091510 - 16 Sep 2022
Cited by 1 | Viewed by 1480
Abstract
Particle number (PN) emissions from hybrid electric vehicles (HEV) during engine ignition and re-ignition events are an important but scarcely reported area. The objectives of the present work are to study the effects of drive cycle properties on the engine behaviour of a [...] Read more.
Particle number (PN) emissions from hybrid electric vehicles (HEV) during engine ignition and re-ignition events are an important but scarcely reported area. The objectives of the present work are to study the effects of drive cycle properties on the engine behaviour of a hybrid electric vehicle (HEV) and to investigate how this impacts the tailpipe PN emissions and their size distributions (PNSD). Worldwide harmonised light vehicles test cycle (WLTC) testing was conducted, as well as chassis dynamometer emission measurements over a realistic real driving emissions (RDE) speed pattern, using a Euro 5 Toyota Prius HEV with a Cambustion DMS500 sampling PN concentrations at the tailpipe. It is shown that the number of vehicle stops during a test cycle has a direct impact on the re-ignition activity for the HEV. 64 ± 3% of the total PN from WLTC testing was produced during engine re-ignition events while only 6 ± 1% was from stabilised engine operation. Similar proportions were observed for the RDE-style test cycle. The majority of engine reignition and destabilised activity, and hence PN emission, was during the low-speed sections of the drive cycles used. The average PNSD across cycle phases was different between cycles, due to the influence of dynamic properties on engine behaviour and hence the PN emission profile. The PNSD at the engine re-ignition and destabilised events had a merged wide peak with a maximum at 60 nm diameter and a shoulder at 12 nm diameter. The HEV had increased emissions of particles smaller than 23 nm under cold start, but similar overall PN emission values, compared to a warm start. The results of this work highlight the importance of controlling HEV PN emissions to limit human exposure to PN in urban environments where the majority of PN emissions occur. The sensitivity of HEV PN emission factors and PNSD to engine behaviour and, in turn, test cycle dynamic properties, is important to note when considering legislative test cycles, particularly with reference to the freedoms afforded by the RDE test cycle. The results also indicate that substantial improvements to air quality could be made by reducing the particle measurement protocol PN cut-off size to 10 nm. Full article
(This article belongs to the Special Issue Traffic Related Emission)
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17 pages, 3141 KiB  
Article
Comparative Analysis, Use Recommendations, and Application Cases of Methods for Develop Ship Emission Inventories
by Yue Li, Yonglin Zhang, Jinxiang Cheng, Chaohui Zheng, Mingjun Li, Honglei Xu, Renjie Wang, Dongsheng Chen, Xiaotong Wang, Xinyi Fu, Yuehua Zhao, Rui Wu, Xiaowen Yang and Lan Shi
Atmosphere 2022, 13(8), 1224; https://doi.org/10.3390/atmos13081224 - 03 Aug 2022
Cited by 3 | Viewed by 1563
Abstract
Ship exhaust emissions have been considered as a significant source of air pollution that has an adverse impact on the global climate and human health. It is of vital importance to create an accurate ship emission inventory for the purpose of formulating effective [...] Read more.
Ship exhaust emissions have been considered as a significant source of air pollution that has an adverse impact on the global climate and human health. It is of vital importance to create an accurate ship emission inventory for the purpose of formulating effective control measures. A wide range of inventory compilation methods have been proposed around the globe, and there has long been a pressing need to analyze and compare these methods in depth. This study sorted out and categorized inventory compilation methods of ship emissions in recent decades. Five main methods were compared and analyzed by their applicability, complexity, time of calculation, accuracy of results, etc. In addition, a new method was proposed to develop an emission inventory based on a vessel energy consumption reporting system. This method is believed to have the potential advantages to produce results of higher accuracy and temporal and spatial resolutions. To perform the validation, three cases at different scales were selected in part of China and surrounding maritime waters (large-scale), the Yangtze River Delta region (medium-scale), and Tianjin Port (small-scale), respectively. The analysis results show that: each of methods have different technical characteristics. Computed results significantly between methods, with the maximum deviation of up to 87%. It is advisable that the optimal method should be chosen based on the actual needs in inventory compilation and the data available. In terms of accuracy of results, Methods 1 and 5 offer moderately high accuracy; Method 2 provides average accuracy; while Methods 3 and 4 produce low accuracy. In terms of resolution of results, Methods 1 and 5 provide high-resolution temporal and spatial distribution of ship emissions; Method 2 delivers low-resolution spatial distribution; while Methods 3 and 4 are incapable of spatial distribution. In terms of applicability, Method 1 applies to the calculation of inventories of varying scales; Method 2 is more applicable to small-scale calculations, such as a port; Methods 3, 4, and 5 are more desirable for large-scale calculations, such as a country. The author recommends Methods 5, 1, 3, and 2/4 in a descending order of preference for large-scale ship emissions inventory compilations; recommends Method 5 (if accuracy is the first priority) or Method 1 (if temporal and spatial resolutions are given first priority), followed by Methods 2, 3, and 4 in a descending order of preference for small/medium-scale ship emissions inventory compilations. These results may serve to help inventory compilers choose an applicable method and support improvements in inventory compilation methods. Full article
(This article belongs to the Special Issue Traffic Related Emission)
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13 pages, 2237 KiB  
Article
Sub-23 nm Particle Emissions from China-6 GDI Vehicle: Impacts of Drive Cycle and Ambient Temperature
by Dongdong Guo, Yunshan Ge, Xin Wang, Haixu Liu, Sheng Su, Chunbo Li and Tinghong Tao
Atmosphere 2022, 13(8), 1216; https://doi.org/10.3390/atmos13081216 - 01 Aug 2022
Cited by 5 | Viewed by 1374
Abstract
Both the EU and China are evaluating the feasibility of lowering the detection limit of particle number (PN) measurement to 10 nm in future legislations, making it necessary to better understand the sub-23 nm particle emission characteristics from state-of-the-art vehicles. In this study, [...] Read more.
Both the EU and China are evaluating the feasibility of lowering the detection limit of particle number (PN) measurement to 10 nm in future legislations, making it necessary to better understand the sub-23 nm particle emission characteristics from state-of-the-art vehicles. In this study, solid PN emissions with a diameter larger than 10 nm and 23 nm (known as SPN10 and SPN23) were compared over the WLTC, RTS95, and a so-called “worst-case” real driving emission (RDE) cycle (highly dynamic/0 °C) using two certification-level particle number counters (PNCs) employing evaporation tube (ET) and catalytic stripper (CS) as volatile particle remover (VPR). The results show that SPN10 emissions were 31.7%, 27.8%, and 15.2% higher than SPN23 over the WLTC, RTS95, and laboratory RDE cycles. Sub-23 nm particles were almost not identified within the engine cold-start phase and tended to be a hot-running pollutant favored by aggressive driving styles (frequent accelerations and high engine loads), fuel-cut during decelerations, and long idles. Lower testing temperature delayed the light-off of catalyst and, therefore, significantly reduced the formation of sub-23 nm particles within the engine warm-up stage. Lowering the detection limit to 10 nm is deemed to provide more public health protection since it will guide manufacturers to pay more attention to vehicle hot-running emissions. Full article
(This article belongs to the Special Issue Traffic Related Emission)
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16 pages, 2196 KiB  
Article
Research on Analysis Method of Remote Sensing Results of NO Emission from Diesel Vehicles
by Lijun Hao, Hang Yin, Junfang Wang, Miao Tian, Xiaohu Wang, Yunshan Ge, Yoann Bernard and Åke Sjödin
Atmosphere 2022, 13(7), 1100; https://doi.org/10.3390/atmos13071100 - 13 Jul 2022
Cited by 1 | Viewed by 1464
Abstract
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Traffic Related Emission)
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15 pages, 2991 KiB  
Article
Reproducibility of the 10-nm Solid Particle Number Methodology for Light-Duty Vehicles Exhaust Measurements
by Tero Lähde, Barouch Giechaskiel, Giorgio Martini, Joseph Woodburn, Piotr Bielaczyc, Daniel Schreiber, Mathias Huber, Panayotis Dimopoulos Eggenschwiler, Corrado Fittavolini, Salvatore Florio, Leonardo Pellegrini, Norbert Schuster, Ulf Kirchner, Hiroyuki Yamada, Jean-Claude Momique, Richard Monier, Yitu Lai, Timo Murtonen, Joonas Vanhanen, Athanasios Mamakos, Christos Dardiotis, Yoshinori Otsuki and Jürgen Spielvogeladd Show full author list remove Hide full author list
Atmosphere 2022, 13(6), 872; https://doi.org/10.3390/atmos13060872 - 26 May 2022
Cited by 4 | Viewed by 1985
Abstract
Many countries worldwide have introduced a limit for solid particles larger than 23 nm for the type approval of vehicles before their circulation in the market. However, for some vehicles, in particular for port fuel injection engines (gasoline and gas engines) a high [...] Read more.
Many countries worldwide have introduced a limit for solid particles larger than 23 nm for the type approval of vehicles before their circulation in the market. However, for some vehicles, in particular for port fuel injection engines (gasoline and gas engines) a high fraction of particles resides below 23 nm. For this reason, a methodology for counting solid particles larger than 10 nm was developed in the Particle Measurement Programme (PMP) group of the United Nations Economic Commission for Europe (UNECE). There are no studies assessing the reproducibility of the new methodology across different laboratories. In this study we compared the reproducibility of the new 10 nm methodology to the current 23 nm methodology. A light-duty gasoline direct injection vehicle and two reference solid particle number measurement systems were circulated in seven European and two Asian laboratories which were also measuring with their own systems fulfilling the current 23 nm methodology. The hot and cold start emission of the vehicle covered a range of 1 to 15 × 1012 #/km with the ratio of sub-23 nm particles to the >23 nm emissions being 10–50%. In most cases the differences between the three measurement systems were ±10%. In general, the reproducibility of the new methodology was at the same levels (around 14%) as with the current methodology (on average 17%). Full article
(This article belongs to the Special Issue Traffic Related Emission)
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Review

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13 pages, 1967 KiB  
Review
Characterization of Laboratory Particulate Matter (PM) Mass Setups for Brake Emission Measurements
by Theodoros Grigoratos, Athanasios Mamakos, RaviTeja Vedula, Michael Arndt, Dmytro Lugovyy, Christian Hafenmayer, Mikko Moisio, Carlos Agudelo and Barouch Giechaskiel
Atmosphere 2023, 14(3), 516; https://doi.org/10.3390/atmos14030516 - 07 Mar 2023
Cited by 2 | Viewed by 1507
Abstract
Vehicles’ exhaust particulate matter (PM) emissions have significantly decreased over the years. On the other hand, non-exhaust emissions, i.e., particle emissions from brakes and tires, have increased due to the increase in the vehicle fleet, traffic congestion, and the distance traveled. As a [...] Read more.
Vehicles’ exhaust particulate matter (PM) emissions have significantly decreased over the years. On the other hand, non-exhaust emissions, i.e., particle emissions from brakes and tires, have increased due to the increase in the vehicle fleet, traffic congestion, and the distance traveled. As a result, regulatory bodies are investigating the possibility of mitigating non-exhaust emissions. The Euro 7 proposal introduces specific emission limits for both brakes and tires for the first time in a regulation worldwide. The methodology for brake particle emissions sampling and measurement builds on the work of the Particle Measurement Programme (PMP) informal working group of the United Nations Economic Commission for Europe (UNECE). The recently adopted Global Technical Regulation (GTR) on brakes from light-duty vehicles up to 3.5 t prescribes the technical details. In this paper, we present the technical specifications for the measurements of PM. We also evaluate the penetrations for two cases with two setups for minimum and maximum particle losses. This study, using aerosol engineering calculations, estimates the maximum expected differences between the two setups, both of which are compliant with the GTR. This study also discusses the mass ratios of PM2.5 and PM10 as a function of the mass median diameters. Full article
(This article belongs to the Special Issue Traffic Related Emission)
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