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Applied Sciences
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Atmospheric Pollutants: Dispersion and Environmental Behavior
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Atmospheric Pollutants: Dispersion and Environmental Behavior

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Environmental Sciences".

Deadline for manuscript submissions: 31 May 2025 | Viewed by 8664

Special Issue Editor

Dr. Jiangjun Wei

E-Mail Website
Guest Editor
School of Automotive and Transportation Engineering, Hefei University of Technology, Hefei 230009, China
Interests: vehicle emissions; particulates; air pollution; environmental health

Special Issue Information

Dear Colleagues,

At present, with the gradual deepening of urbanization and the rapid upgrading of roads and other infrastructures, particulate pollution related to traffic has become an important factor affecting the quality of the atmospheric environment. In terms of vehicle particulate matter pollutants, exhaust and non-exhaust emissions contribute almost equally to the generation of traffic-related atmospheric aerosols. Among non-exhaust emission sources, brake system, tire and road wear are the main sources of many heavy metals and organic particles. Some of these particles can be directly discharged into the atmosphere or adsorbed on the surface of friction materials, and the others can settle on the road and suspended into the atmosphere again by wind or motor vehicle driving. Particulates enter the human body through various ways such as respiratory tract, posing an ongoing challenge for public health. Particulate matter will also evolve in the process of atmospheric transmission, and its own properties will change, so the harm to the environment and human health is changeable, which is the current hot research direction of the atmosphere.

Dr. Jiangjun Wei
Guest Editor

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Keywords

  • vehicle emissions (exhaust and non-exhaust)
  • particulates
  • environmental health

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Published Papers (5 papers)

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Research

20 pages, 4773 KiB  
Article
Comparison of PM10 Levels in Three of the Most Polluted Cities in Romania over the Periods Related to Lower Traffic—Implications for Human Health
by George-Bogdan Burghelea, Luminita Mărmureanu, Gabriela Iorga and Bogdan Antonescu
Appl. Sci. 2024, 14(18), 8169; https://doi.org/10.3390/app14188169 - 11 Sep 2024
Cited by 1 | Viewed by 1231
Abstract
The COVID-19 pandemic has provided an opportunity to examine the impact of reduced human activity on air quality. This study assesses the levels of particulate matter (PM10) in three cities—Bucharest, Brașov, and Iași—during the pandemic restrictions in 2020, comparing them with [...] Read more.
The COVID-19 pandemic has provided an opportunity to examine the impact of reduced human activity on air quality. This study assesses the levels of particulate matter (PM10) in three cities—Bucharest, Brașov, and Iași—during the pandemic restrictions in 2020, comparing them with data from the pre-pandemic period (2017–2019) and post-lockdown period (2021–2022). The results show a significant decrease in PM10 levels during the lockdown, which is closely associated with reduced traffic and mobility. Notably, while PM10 concentrations initially spiked at the beginning of 2020, they markedly declined following the enforcement of lockdown measures, during which mobility to workplaces in these cities decreased by about 60% in Bucharest, 50% in Brașov, and 45% in Iași. Health risks related to PM10 exposure were evaluated using the hazard quotient method, following EU and WHO guidelines. Despite the reduction in pollution levels in 2020, the findings suggest long-term human health risks for residents of these cities. This research highlights the critical need for sustainable strategies to address air quality issues in urban areas and protect public health. Full article
(This article belongs to the Special Issue Atmospheric Pollutants: Dispersion and Environmental Behavior)
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26 pages, 687 KiB  
Article
Study of the Interrelations of the Concentrations of Six Tree Pollen Types and Six Atmospheric Pollutants with Rhinitis and Allergic Conjunctivitis in the Community of Madrid
by Javier Chico-Fernández and Esperanza Ayuga-Téllez
Appl. Sci. 2024, 14(7), 2965; https://doi.org/10.3390/app14072965 - 31 Mar 2024
Cited by 2 | Viewed by 1392
Abstract
Allergic pathologies of aerobiological origin, specifically those caused by exposure to pollen allergens, have shown a growing trend in recent decades worldwide. This trend is most evident in urban areas experiencing an incessant expansion of their territory. Several studies have shown an interaction [...] Read more.
Allergic pathologies of aerobiological origin, specifically those caused by exposure to pollen allergens, have shown a growing trend in recent decades worldwide. This trend is most evident in urban areas experiencing an incessant expansion of their territory. Several studies have shown an interaction between atmospheric pollutants and pollen grains, which implies a potentiation of the allergenicity of the latter. This study aims to analyze the possible influence, in the Community of Madrid (CAM), of the concentrations of six atmospheric pollutants (O3, particles PM10 and PM2.5, NO2, CO, and SO2), and of the pollen concentrations of six types of tree pollen (Cupressaceae, Olea, Platanus, Pinus, Ulmus, and Populus) on the episodes of attention of two pathologies, rhinitis and allergic conjunctivitis. The data collected came from the Air Quality Networks of the CAM and the Madrid City Council, the Palynological Network of the CAM, and the General Subdirectorate of Epidemiology of the Health Department of the CAM. Descriptive multiple linear regression models were used to analyze the interrelationships of the three variables. In most of the calculations performed, the adjusted R2 value is higher than 30%, and, in all cases, the p-values of the models obtained are less than 0.0001. All the models performed in the study period for allergic rhinitis indicate a reasonable correlation, and this is also true for almost all of the models calculated for allergic conjunctivitis. Moreover, it is allergic rhinitis for which the highest values of adjusted R2 were obtained. Pinus is the pollen type most frequently interrelated with conjunctivitis and allergic rhinitis (followed in both cases by Olea and Populus) throughout the study years. In this same period, O3 is the air pollutant most frequently present in the models calculated for allergic conjunctivitis (followed by NO2 and PM10), while particle PM10 is the most frequently included in the calculations made for allergic rhinitis, followed by O3 and SO2. Full article
(This article belongs to the Special Issue Atmospheric Pollutants: Dispersion and Environmental Behavior)
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19 pages, 9748 KiB  
Article
Odor Impact Assessment via Dispersion Model: Comparison of Different Input Meteorological Datasets
by Francesca Tagliaferri, Laura Facagni, Marzio Invernizzi, Adrian Luis Ferrer Hernández, Anel Hernández-Garces and Selena Sironi
Appl. Sci. 2024, 14(6), 2457; https://doi.org/10.3390/app14062457 - 14 Mar 2024
Cited by 9 | Viewed by 1886
Abstract
Dispersion modeling is a useful tool for reproducing the spatial–temporal distribution of pollutants emitted by industrial sites, particularly in the environmental odor field. One widely used tool, accepted by regulatory agencies for environmental impact assessments, is the CALPUFF model, which requires a large [...] Read more.
Dispersion modeling is a useful tool for reproducing the spatial–temporal distribution of pollutants emitted by industrial sites, particularly in the environmental odor field. One widely used tool, accepted by regulatory agencies for environmental impact assessments, is the CALPUFF model, which requires a large number of input variables, including meteorological and orographical variables. The reliability of model results depends on the accuracy of these input variables. The present research aims to discuss a comparative study of odor dispersion modeling by initializing the CALMET meteorological processor with different input data: surface and upper air observational meteorological data, 3D prognostic data, and a blend of prognostic and measured data. Two distinct sources (a point and an area source) and two different simulation domains in Cuba and Italy are considered. The analysis of results is based on odor impact criteria enforced in some Italian regions by computing the 98th percentile of odor peak concentrations on an annual basis. For the area source, simulation results reveal that the ‘OBS’ and ‘HYBRID’ modes are largely comparable, whereas prognostic data tend to underestimate the odor concentrations, likely due to a reduced percentage of wind calms. For point sources, different input meteorological settings provide comparable results, with no significant differences. Full article
(This article belongs to the Special Issue Atmospheric Pollutants: Dispersion and Environmental Behavior)
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16 pages, 4637 KiB  
Article
Solid Particle Number (SPN) Portable Emission Measurement Systems (PEMS) for Heavy-Duty Applications
by Barouch Giechaskiel, Anastasios Melas, Stijn Broekaert, Roberto Gioria and Ricardo Suarez-Bertoa
Appl. Sci. 2024, 14(2), 654; https://doi.org/10.3390/app14020654 - 12 Jan 2024
Cited by 1 | Viewed by 1647
Abstract
A heavy-duty engine is homologated in a test cell. However, starting with Euro VI regulation, the in-service conformity is controlled with the engine installed in the vehicle using portable emission measurement systems (PEMS). In Europe, the application of solid particle number (SPN) PEMS [...] Read more.
A heavy-duty engine is homologated in a test cell. However, starting with Euro VI regulation, the in-service conformity is controlled with the engine installed in the vehicle using portable emission measurement systems (PEMS). In Europe, the application of solid particle number (SPN) PEMS started in 2021 for compression ignition (diesel) vehicles and in 2023 for positive ignition vehicles, thus including those operating with compressed natural gas (CNG). Even though today only particles with sizes > 23 nm are regulated, the Euro 7 proposal includes particles > 10 nm. There are not many studies on the accuracy of the SPN PEMS, especially for heavy-duty applications. In this study, PEMS measuring > 23 and >10 nm from two instrument manufacturers were compared with laboratory-grade instruments. The particle detector of one PEMS was a condensation particle counter (CPC), and of the other a the diffusion charger (DC). The results showed the robustness and good accuracy (40% or 1 × 1011 #/kWh) of the PEMS for ambient temperatures from −7 °C to 35 °C, active regeneration events, different fuels (Diesel B7, HVO, and CNG), different test cycles, cold start or hot engine operations, and high exhaust gas humidity content. Nevertheless, for the DC-based PEMS, sensitivity to pre-charged urea particles was identified, and for the CPC-based PEMS, sensitivity to pressure changes with one vehicle was nnoticed. Nevertheless, the results of this study confirm that the PEMS are accurate enough to measure even the stricter Euro 7 limits. Full article
(This article belongs to the Special Issue Atmospheric Pollutants: Dispersion and Environmental Behavior)
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24 pages, 12741 KiB  
Article
A Novel Longitudinal Control Method Integrating Driving Style and Slope Prediction for High-Efficiency HD Vehicles
by Yifang Zhou, Mingzhang Pan, Wei Guan, Xinxin Cao, Huasheng Chen and Leyi Yuan
Appl. Sci. 2023, 13(21), 11968; https://doi.org/10.3390/app132111968 - 2 Nov 2023
Cited by 5 | Viewed by 1619
Abstract
Developing high-precision vehicle longitudinal control technology guided by ecological driving represents a highly promising yet challenging endeavor. It necessitates the fulfillment of the driver’s operational intentions, precise speed control, and reduced fuel consumption. In light of this challenge, this study presents a novel [...] Read more.
Developing high-precision vehicle longitudinal control technology guided by ecological driving represents a highly promising yet challenging endeavor. It necessitates the fulfillment of the driver’s operational intentions, precise speed control, and reduced fuel consumption. In light of this challenge, this study presents a novel vehicle longitudinal control model that integrates real-time driving style analysis and road slope prediction. First, it utilizes spectral clustering based on Bi-LSTM automatic encoders to identify driver driving styles. Next, it examines the driving environment and predicts the current slope of the vehicle. Additionally, a fuzzy controller is designed to optimize control performance, adapt to various driving styles and slopes, and achieve better fuel efficiency. The research results indicate that the DS-MPC control model developed in this paper can effectively distinguish various driving modes and has high speed control accuracy while saving 3.27% of fuel. Full article
(This article belongs to the Special Issue Atmospheric Pollutants: Dispersion and Environmental Behavior)
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