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

Deadline for manuscript submissions: closed (22 September 2023) | Viewed by 27555

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Special Issue Editor

Dr. Mingliang Fu

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Guest Editor

Vehicle Emission Control Center of Ministry of Ecology and Environment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
Interests: vehicle emission test; emission factors measurement; emission inventory; after-treatment device performance evaluation; emission model development
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Special Issue Information

Dear Colleagues,

With the rapid growth of the economy, the number of mobile sources is also rapidly increasing. It is well-known that mobile sources emit a large amount of VOC, NOx and PM, which are major precursors to ozone and secondary organic aerosols (SOA). Therefore, mobile source emissions, especially vehicle emissions, are an important contributor to urban atmospheric pollution. Therefore, how to effectively monitor and control mobile source emission remains a serious challenge.

In recent decades, various emission measurement technologies have been applied to mobile sources, helping us to better understand these emissions in real-world scenarios. In the meantime, more detailed information about mobile source activity can be obtained by various monitoring approaches. Developing a mobile source emission inventory with a high spatial-temporal resolution has become a popular research topic.

The aim of this Special Issue is to provide recent advances in the factors and inventory of on-road and off-road mobile source emissions. The scope covers emission factors from different measurement technologies, the activity approach of mobile sources, emission inventory development method and policy and recommendations.

Topics of interest for this Special Issue include but are not limited to:

(1) Regulated and unregulated pollutants tests;

(2) Measurement and control technologies;

(3) Exhaust emission and non-exhaust emission;

(4) Emission model;

(5) Emission inventory development;

(6) Environmental effect;

(7) Management policy and recommendation.

Dr. Mingliang Fu
Guest Editor

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Keywords

mobile source
emission factor
emission characteristics
emission inventory
measurement technology
policy and recommendation

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Published Papers (9 papers)

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Research

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19 pages, 10542 KiB

Open AccessArticle

Numerical Model of Filtration Efficiency Based on Fractal Characteristics of Particulate Matter and Particle Filter

by Yiqing Liu, Hao Wang and Haisheng Yu

Atmosphere 2023, 14(11), 1689; https://doi.org/10.3390/atmos14111689 - 15 Nov 2023

Cited by 2 | Viewed by 1555

Abstract

Fractal theory was used to characterize particles and particle trapping parameters to accurately predict the particle filtration process inside a gasoline engine particle filter (GPF). The particles were fractal aggregates, and the fractal dimension (D_f) was introduced to redefine the particle size. The porous medium inside the particle filter was a solid phase fractal. The pore tortuosity fractal dimension (D_t) and the pore area fractal dimension (D_a) were introduced to define the fiber length of the trap. The Brownian diffusion coefficient and permeability were modified. A new fractal numerical model of GPF filtration efficiency was proposed based on the classical filtration theory. The results show that the fractal expansion model of filtration efficiency has good applicability. The influence of GPF structural parameters on filtration efficiency and pressure drop was analyzed. In this study, two performance metrics, trapping efficiency and pressure drop, were considered by fractal expansion filtration modeling. It is possible to increase or decrease filtration efficiency by adjusting the porosity and pore diameter. Full article

(This article belongs to the Special Issue Recent Advances in Mobile Source Emissions)

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15 pages, 2437 KiB

Open AccessArticle

Analysis of the Actual Usage and Emission Reduction Potential of Electric Heavy-Duty Trucks: A Case Study of a Steel Plant

by Guangyu Dou, Jia Ke, Jindong Liang, Junfang Wang, Jinhu Li, Qing Liu and Chunxiao Hao

Atmosphere 2023, 14(10), 1562; https://doi.org/10.3390/atmos14101562 - 13 Oct 2023

Cited by 3 | Viewed by 2166

Abstract

In order to understand the driving characteristics of electric heavy-duty trucks in practical application scenarios and promote their usage to replace diesel trucks, this study analyzed the actual usage of electric and diesel heavy-duty trucks in a steel factory based on vehicle-monitoring data and remote online monitoring data and estimated the emission reduction potential of the application of electric trucks by using a mileage-based method and the greenhouse gas emission model. The results showed that the electric heavy-duty trucks in the steel factory mostly operated for over 14 h, with a vehicle kilometers traveled (VKT) of 50–300 km each day, which could meet most of the demands of the transportation of the steel industry. The average daily energy consumption for most trucks falls within the range of 210–230 kWh/100 km, with higher consumption in winter than in summer, which can save approximately 18–26% in operating costs compared with diesel trucks. It is estimated that the usage of these electric heavy-duty trucks can achieve an annual reduction of 115.8 tons of NO_x emissions, 0.7 tons of PM emissions, and 18,000 tons of CO₂ emissions. To further promote the application of electric heavy-duty trucks in China, several policy suggestions, such as introducing priority road-right policies, promoting vehicle and battery leasing markets, and exempting zero-emission vehicles during heavy pollution days, were proposed. Full article

(This article belongs to the Special Issue Recent Advances in Mobile Source Emissions)

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15 pages, 3292 KiB

Open AccessArticle

A Comparison of the Evaporative Emissions Performance of Light-Duty Vehicles under US Tier 3 and China 6 Test Conditions

by Di Peng, Miao Tian, Fei Yi, Xinping Yang, Liang Ji, Junfang Wang, Hang Yin, Yan Ding and Haiguang Zhao

Atmosphere 2023, 14(7), 1128; https://doi.org/10.3390/atmos14071128 - 7 Jul 2023

Cited by 3 | Viewed by 2675

Abstract

To further improve air quality in China, especially ozone and fine particulate matter (PM_2.5), additional reductions of volatile organic compounds (VOCs) are needed. Evaporative emissions from internal combustion engines (ICE) and hybrid vehicles are known to be an important source of VOCs in urban cities, which can be efficiently reduced through the introduction of more stringent regulatory standards. The most stringent global standards for evaporative emissions are the U.S. Tier 3 light-duty vehicle standards. This study compares the evaporative emissions of light-duty ICE vehicles designed to China 6 and U.S. Tier 3 regulations for both China and U.S. test conditions. Data are analyzed from manufacturer testing of full vehicle evaporative emissions conducted in the laboratory following U.S. Tier 3 and China 6 certification test methods utilizing Sealed Housing for Evaporative Determination (SHED) chambers equipped with Flame Ionization Detection (FID) analyzers. Vehicles designed to U.S. Tier 3 standards are observed to have 64% lower diurnal and hot soak evaporative emissions and 98% lower canister bleed emissions relative to vehicles designed to China 6 standards. U.S. Tier 3, U.S. Tier 2, and China 6 light-duty evaporative emission certification values submitted by manufacturers are also compared. The average of all current U.S. Tier 3 certifications is, on average, 52.4% lower than the average of all China 6 certifications. The results from the testing and data analysis of five vehicles, with comparison to the certification data, suggest that the introduction of standards equivalent in stringency to U.S. Tier 3 in China can significantly reduce evaporative emissions relative to China 6. Full article

(This article belongs to the Special Issue Recent Advances in Mobile Source Emissions)

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15 pages, 14886 KiB

Open AccessArticle

Research on Promotion Pathways for Zero-Emission Medium- and Heavy-Duty Trucks: A Case Study of Hainan Island

by Chunxiao Hao, Yunshan Ge, Jindong Liang, Zhuoshi He, Zhihui Huang and Guangyu Dou

Atmosphere 2023, 14(5), 882; https://doi.org/10.3390/atmos14050882 - 18 May 2023

Cited by 1 | Viewed by 1887

Abstract

Promoting the use of zero-emission vehicles is an important measure for reducing pollutant and carbon dioxide emissions from medium- and heavy-duty trucks (MHDTs). This study took Hainan Island as an example. Based on big data such as industrial layout and traffic flow, it clarified that the main channels of freight transportation on Hainan Island are concentrated in the northern region, including the surrounding areas of Haikou; the important ports of Haikou, Yangpu, and Basuo; and Chengmai and Tunchang counties. Furthermore, pathways for the promotion of zero-emission MHDTs are proposed, which can reduce exhaust emissions by 1549 tons of NOx, 62 tons of particulate matter (PM), and 3.60 million tons of CO₂ by 2030. Compared with the vehicle type categorization plan, the spatial layout plan can achieve higher emission reduction benefits in the medium term (2025). In addition, in conjunction with existing policies and planning requirements, this study also puts forward policy suggestions for the promotion of zero-emission MHDTs. Full article

(This article belongs to the Special Issue Recent Advances in Mobile Source Emissions)

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25 pages, 28263 KiB

Open AccessArticle

URANS Simulations of Vehicle Exhaust Plumes with Insight on Remote Emission Sensing

by Justin Plogmann, Christian Stauffer, Panayotis Dimopoulos Eggenschwiler and Patrick Jenny

Atmosphere 2023, 14(3), 558; https://doi.org/10.3390/atmos14030558 - 15 Mar 2023

Cited by 2 | Viewed by 3073

Abstract

Remote Emission Sensing (RES) is a measurement method based on absorption spectroscopy for the determination of pollutant concentrations. The absorption of the exhaust plume of a vehicle is measured from the roadside without intervention by means of a light/laser barrier during a short [...] Read more.

_{x}

to CO

_{2}

) are estimated. Unsteady Reynolds-Averaged Navier-Stokes (URANS) simulations of exhaust plumes in vehicle wakes are performed using the k-

ω

SST turbulence model with focus on pollutant dispersion. The simulation setup has been validated by a comparison with experimentally obtained drag coefficients. The resulting concentration fields represent the pollutants available for measurements by a RES device. The influence of the characteristics of the RES device on the measurement is assessed. In addition, investigations involve several environmental and vehicle related parameters. The results demonstrate that due to strong turbulence, mixing is enhanced and the exhaust plumes rapidly disperse in the near vehicle wakes. Results show that emission characteristics of a vehicle are contained downstream for approximately half the vehicle length, regardless of different vehicle configurations, driving and ambient parameters. Further downstream dispersion of pollutants results in concentrations that are less than

1 / 100

of the pollutant concentration in the vehicle’s exhaust tailpipe implying that RES devices have to measure at a high sampling frequency. Therefore, reliable determination of the concentration ratios of pollutant at high vehicle velocities requires the RES device to operate in the order of 1000 Hz sampling frequency. Ultimately, the numerical simulations not only help to understand exhaust plume dispersion, but provide a very useful tool to minimize RES uncertainties. Full article

(This article belongs to the Special Issue Recent Advances in Mobile Source Emissions)

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11 pages, 2027 KiB

Open AccessArticle

The Characteristics of Light-Duty Passenger Vehicle Mileage and Impact Analysis in China from a Big Data Perspective

by Dong Ma, Xiaomeng Wu, Xin Sun, Shaojun Zhang, Hang Yin, Yan Ding and Ye Wu

Atmosphere 2022, 13(12), 1984; https://doi.org/10.3390/atmos13121984 - 27 Nov 2022

Cited by 9 | Viewed by 3221

Abstract

Vehicle mileage is one of the key parameters for accurately evaluating vehicle emissions and energy consumption. With the support of the national annual vehicle emission inspection networked platform in China, this study used big data methods to analyze the activity level characteristics of the light-duty passenger vehicle fleet with the highest ownership proportion. We found that the annual mileage of vehicles does not decay significantly with the increase in vehicle age, and the mileage of vehicles is relatively low in the first few years due to the run-in period, among other reasons. This study indicated that the average mileage of the private passenger car fleet is 10,300 km/yr and that of the taxi fleet was 80,000 km/yr in China in 2019, and the annual mileage dropped by 22% in 2020 due to the pandemic. Based on the vehicle mileage characteristics, the emission inventory of major pollutants from light-duty passenger vehicles in China for 2010–2020 was able to be updated, which will provide important data support for more accurate environmental and climate benefit assessments in the future. Full article

(This article belongs to the Special Issue Recent Advances in Mobile Source Emissions)

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15 pages, 2157 KiB

Open AccessArticle

Application of Remote Sensing Methodology for Vehicle Emission Inspection

by Xianfeng Ren, Nan Jiang, Yunxia Li, Wenhui Lu, Zhouhui Zhao and Lijun Hao

Atmosphere 2022, 13(11), 1862; https://doi.org/10.3390/atmos13111862 - 9 Nov 2022

Cited by 1 | Viewed by 3339

Abstract

Remote sensing detection of vehicle emissions is an effective supplement to the statutory periodic inspection of in-use vehicle emissions and it is a convenient technical method for real-time screening of high-emission vehicles. The principle of remote sensing detection is to inversely calculate the absolute concentrations of gaseous pollutants in vehicle exhaust according to the relative volume concentration ratio of each exhaust component to carbon dioxide (CO₂) in the vehicle exhaust plume. Because the combustion mechanisms of gasoline engines and diesel engines are different, different inversion calculation methods of remote sensing data must be applied. The absolute concentrations of gasoline vehicle gaseous emissions measured by remote sensing can be calculated by the inversion calculation method based on the theoretical air–fuel ratio combustion mechanism. However, the absolute concentrations of diesel vehicle nitrogen oxide (NOx) measured by remote sensing must be calculated by the inversion calculation method based on the correction of the excess air coefficient. For the integrated remote sensing test system of gasoline and diesel vehicles, it is necessary to determine the vehicle category according to the vehicle type and license plate and adopt different inversion calculation methods to obtain the correct remote sensing results of vehicle emissions. The big data statistical analysis method for vehicle emission remote sensing results can quickly screen high-emission vehicles and dynamically determine the remote sensing emission screening threshold of high-emission vehicles as the composition of in-use vehicles changes and the overall emission of vehicles declines, so as to achieve dynamic and accurate screening of high-emission vehicles. Full article

(This article belongs to the Special Issue Recent Advances in Mobile Source Emissions)

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12 pages, 3666 KiB

Open AccessArticle

Prediction of Real Driving Emission of Light Vehicles in China VI Based on GA-BP Algorithm

by Hao Yu, Hong Chang, Zengjia Wen, Yunshan Ge, Lijun Hao, Xin Wang and Jianwei Tan

Atmosphere 2022, 13(11), 1800; https://doi.org/10.3390/atmos13111800 - 30 Oct 2022

Cited by 10 | Viewed by 1842

Abstract

In the China VI regulations for light-duty vehicles, the (RDE) test is introduced as a supplementary test procedure. In the actual test process, the RDE results are more significantly influenced by driving behavior and vehicle type. To reduce the test cost, the NOx and PN prediction models are established based on the GA-BP method. The results showed that the coefficients of determination of the GA-BP model for NOx and PN predictions are all greater than 0.9 and are linearly highly correlated at the instantaneous emission level. At the overall emission level, the overall error of the GA-BP model is less than 7% for NOx prediction and less than 6% for PN prediction. The model has high accuracy for both instantaneous and overall emissions of light-duty vehicles. This provides practical engineering value for guiding the RDE test. Full article

(This article belongs to the Special Issue Recent Advances in Mobile Source Emissions)

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Review

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17 pages, 2232 KiB

Open AccessReview

Diesel Engine Emission Aftertreatment Device Aging Mechanism and Durability Assessment Methods: A Review

by Tian Yu, Kai Li, Qian Wu, Peng Yao, Jia Ke, Bowen Wang and Yanjun Wang

Atmosphere 2023, 14(2), 314; https://doi.org/10.3390/atmos14020314 - 4 Feb 2023

Cited by 15 | Viewed by 4359

Abstract

To meet more and more stringent emission standards, the combined technologies must be used to purify the emission pollutants of vehicle exhaust. Among them, the aftertreatment devices, including DOC, SCR, DPF, and so on, are the most efficient methods. However, after long-term running, the performance of the aftertreatment devices will inevitably degrade. There are several mechanisms that can be used to explain the aging phenomena. For the catalytic devices, such as DOC and SCR, thermal aging and poisoning aging are the most important reasons for their performance deterioration. As for DPF, ash clogging is a key problem for its stable working. To develop and test aftertreatment devices better and faster, the accelerated aging methods must be researched and applied. The small-sample aging method enables accelerated aging of catalyst samples at a very low cost, but its aging accuracy may not be good enough. Although the results of the whole-vehicle aging method and bench engine aging method are more in accord with the real using course, they take too much time and are too expensive to be used widely. Burner aging is a promising way to simulate the long-term running of the catalysts. Full article

(This article belongs to the Special Issue Recent Advances in Mobile Source Emissions)

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