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Atmosphere
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New Insights into Human Health by Air Quality Modeling, Simulation,...
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New Insights into Human Health by Air Quality Modeling, Simulation, and Observation

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

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 11206

Special Issue Editors

Dr. Hui Liu

E-Mail Website
Guest Editor
School of Remote Sensing & Geomatics Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
Interests: spatiotemporal modeling; atmospheric dispersion; numerical simulation; remote sensing observation; risk assessment and prediction
Dr. Mei Li

E-Mail Website
Guest Editor
Institute of Remote Sensing and Geographic Information System, School of Earth and Space Sciences，Peking University, Beijing 100871, China
Interests: atmospheric dispersion and simulation; public safety; emergency response
Special Issues, Collections and Topics in MDPI journals
Dr. Mingyue Lu

E-Mail Website
Guest Editor
School of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China
Interests: 3D meteorological/GIS modeling; remote sensing observation; risk assessment
Dr. Hua Shao

E-Mail Website
Guest Editor
College of Geomatics Science and Technology, Nanjing Tech University, Nanjing 211816, China
Interests: spatiotemporal modeling; GIScience; data mining; risk assessment and prediction

Special Issue Information

Dear Colleagues,

Air quality is of great importance to environmental safety and human health. In each year, both indoor and outdoor air pollution are thought to contribute to millions of premature deaths around the world. Statistics show that at the end of 2021, there were a total of 915 thousand people diagnosed with occupational pneumoconiosis in China, and only about 450 thousand patients survived among them. Despite the increased attention being paid to the risks associated with air pollution, there still remain significant challenges and gaps in our understanding of scientific issues such as air quality control, carbon emissions and monitoring, and the assessment of the global carbon cycle via both remote sensing observations and modeling. In addition, with the implementation of carbon-neutral policies and increases in energy and operating costs, it is vital to accurately monitor and control the main greenhouse gases and air pollutants, such as carbon dioxide (CO2), methane (CH4), and carbon monoxide (CO), etc. Here, to improve our scientific knowledge of air quality control, air pollution simulation and the assessment of the carbon cycle via both observations and modeling, we present this Special Issue entitled “New Insights into Air Quality and Health” in the journal Atmosphere. Any papers related to air quality simulation, air quality control, air pollution simulation, atmospheric dispersion, carbon flux and transport (especially for CO2, CH4, and CO), and the assessment of the carbon cycle via both remote sensing observations and modeling are warmly welcomed for submission to this Special Issue. Papers can focus on observations, computational modeling, spatiotemporal simulations, and computational fluid dynamics (CFD) from natural or anthropogenic sources, and can be in the field of safety production, be at the city, regional, or even global scale, and use field or remote sensing observations, model simulations, meta-analyses, or a combination of the above methods. Regions of interest include, but are not limited to, industrial parks, forests, grassland, water, and urban areas.

Dr. Hui Liu
Dr. Mei Li
Dr. Mingyue Lu
Dr. Hua Shao
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • carbon emission and monitoring
  • greenhouse gases monitoring
  • atmospheric pollutants
  • hazardous and toxic substances
  • air quality management
  • atmospheric dispersion and transport
  • indoor air quality
  • air pollution climatology
  • exposure assessment of air pollution

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Published Papers (5 papers)

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Research

17 pages, 14278 KiB  
Article
Laser Attenuation and Ranging Correction in the Coal Dust Environment Based on Mie Theory and Phase Ranging Principle
by Ben Li, Shanjun Mao and Hong Zhang
Atmosphere 2023, 14(5), 845; https://doi.org/10.3390/atmos14050845 - 9 May 2023
Cited by 1 | Viewed by 1626
Abstract
The inadequate ventilation and complex environments in underground coal mines lead to a high concentration of dust particles. As a result, the health of the miners and the accuracy of laser rangefinder measurements are endangered. It is crucial to enhance the laser rangefinder’s [...] Read more.
The inadequate ventilation and complex environments in underground coal mines lead to a high concentration of dust particles. As a result, the health of the miners and the accuracy of laser rangefinder measurements are endangered. It is crucial to enhance the laser rangefinder’s efficiency to mitigate health risks and reduce labor intensity. In this study, we propose a laser power attenuation model and a ranging correction model to address the issues of laser power attenuation and inaccurate ranging in coal dust environments. The proposed models are based on theoretical analysis and practical experiments, and both are dependent on the dust particle size (<250 μm) and mass concentration. Firstly, we assessed the factors that caused laser power attenuation and demonstrated that our proposed model could accurately predict them (maximum residual of 0.06). Secondly, we obtained the connection between the attenuation coefficient and dust concentration by applying the Lambert–Beer law. Lastly, we established the ranging correction model by collecting laser wavelength information. The outcomes show that the root mean square error of the corrected values ranges between 0.27 and 0.47 mm. To summarize, our suggested model and correction technique can efficiently enhance the precision of laser rangefinder measurements, thus improving underground work in coal mines. Full article
(This article belongs to the Special Issue New Insights into Human Health by Air Quality Modeling, Simulation, and Observation)
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26 pages, 14642 KiB  
Article
A System Coupled GIS and CFD for Atmospheric Pollution Dispersion Simulation in Urban Blocks
by Qunyong Wu, Yuhang Wang, Haoyu Sun, Han Lin and Zhiyuan Zhao
Atmosphere 2023, 14(5), 832; https://doi.org/10.3390/atmos14050832 - 5 May 2023
Cited by 2 | Viewed by 2567
Abstract
Atmospheric pollution is a critical issue in public health systems. The simulation of atmospheric pollution dispersion in urban blocks, using CFD, faces several challenges, including the complexity and inefficiency of existing CFD software, time-consuming construction of CFD urban block geometry, and limited visualization [...] Read more.
Atmospheric pollution is a critical issue in public health systems. The simulation of atmospheric pollution dispersion in urban blocks, using CFD, faces several challenges, including the complexity and inefficiency of existing CFD software, time-consuming construction of CFD urban block geometry, and limited visualization and analysis capabilities of simulation outputs. To address these challenges, we have developed a prototype system that couples 3DGIS and CFD for simulating, visualizing, and analyzing atmospheric pollution dispersion. Specifically, a parallel algorithm for coordinate transformation was designed, and the relevant commands were encapsulated to automate the construction of geometry and meshing required for CFD simulations of urban blocks. Additionally, the Fluent-based command flow was parameterized and encapsulated, enabling the automatic generation of model calculation command flow files to simulate atmospheric pollution dispersion. Moreover, multi-angle spatial partitioning and spatiotemporal multidimensional visualization analysis were introduced to achieve an intuitive expression and analysis of CFD simulation results. The result shows that the constructed geometry is correct, and the mesh quality meets requirements with all values above 0.45. CPU and GPU parallel algorithms are 13.3× and 25× faster than serial. Furthermore, our case study demonstrates the developed system’s effectiveness in simulating, visualizing, and analyzing atmospheric pollution dispersion in urban blocks. Full article
(This article belongs to the Special Issue New Insights into Human Health by Air Quality Modeling, Simulation, and Observation)
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10 pages, 574 KiB  
Article
Evaluation of Respiratory, Genotoxic and Cytotoxic Effects from Occupational Exposure to Typography Activities
by Diana Linhares, Joana Rocha, Armindo Rodrigues, Ricardo Camarinho and Patrícia Garcia
Atmosphere 2023, 14(3), 562; https://doi.org/10.3390/atmos14030562 - 15 Mar 2023
Viewed by 1399
Abstract
This cross-sectional study was structured to allow the evaluation of the respiratory, genotoxic, and cytotoxic effects of occupational exposure to products resulting from the activity of printers in typographies and, to determine the risk of genotoxicity associated with such exposure. This study comprised [...] Read more.
This cross-sectional study was structured to allow the evaluation of the respiratory, genotoxic, and cytotoxic effects of occupational exposure to products resulting from the activity of printers in typographies and, to determine the risk of genotoxicity associated with such exposure. This study comprised 69 subjects, 25 individuals occupationally exposed to the products of typographies (study group), and 44 individuals non-exposed to the environment studied (reference group). The frequency of micronucleated cells and other nuclear anomalies (binucleated, karyolitic, pyknotic, and karyorrhectic cells) in the oral epithelia of each subject were analyzed. The frequency of micronucleated cells was significantly higher in the study group when compared to the reference one (12.96 MN/2000 cells vs. 4 MN/2000 cells, respectively). Occupational exposure to products of typography is a risk factor for the occurrence of micronucleated cells in the study group (RR = 3.2; 95% CI, 2.7–3.9; p < 0.001). The results of the spirometry test did not reveal significant respiratory effects between the reference and study groups. Full article
(This article belongs to the Special Issue New Insights into Human Health by Air Quality Modeling, Simulation, and Observation)
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10 pages, 1085 KiB  
Article
Application of New Modified Genetic Algorithm in Inverse Calculation of Strong Source Location
by Jiming Yao, Yajing Liu, Zhengwen Feng, Tong Liu, Shuai Zhou and Hongjian Liu
Atmosphere 2023, 14(1), 89; https://doi.org/10.3390/atmos14010089 - 31 Dec 2022
Cited by 1 | Viewed by 1923
Abstract
With the rapid development of intelligent systems, the application of genetic algorithms to quickly and accurately determine the location of hazardous gas leaks is of great practical significance. To further improve the convergence efficiency and stability of the inverse calculation, a new improved [...] Read more.
With the rapid development of intelligent systems, the application of genetic algorithms to quickly and accurately determine the location of hazardous gas leaks is of great practical significance. To further improve the convergence efficiency and stability of the inverse calculation, a new improved genetic algorithm (NMGA) is designed on the basis of the improved genetic algorithm (MGA). The adaptive crossover rate and mutation rate change with the evolution algebra to guide the development trend of good gene genetics and change the genetic crossover ratio of parents and children in the culler’s gene pool to avoid damaging the good group genes by introducing bad genes. This study modified the adaptive crossover rate and mutation rate that change with the evolutionary generations to guide the development of good gene inheritance. Meanwhile, this study changed the genetic crossover ratio of parent and offspring in the elimination gene pool to avoid the introduction of unfavorable genes and the destruction of excellent group genes. Through the calculation simulation of the new improved genetic algorithm (NMGA) in Matlab and the quantitative and qualitative comparative analysis with the MGA statistical results, it is shown that NMGA can improve the slow convergence speed of MGA by reducing the number of iterations on the premise of ensuring the stability of MGA and the accuracy of the inverse calculation. The results indicated that the convergence rate and stability of NMGA greatly improved its convergence efficiency, inverse calculation accuracy, and stability, thereby providing powerful decision-making data for rapid emergency rescue work for sudden light gas leakage accidents. Full article
(This article belongs to the Special Issue New Insights into Human Health by Air Quality Modeling, Simulation, and Observation)
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13 pages, 2924 KiB  
Article
A Parallel Computing Algorithm for the Emergency-Oriented Atmospheric Dispersion Model CALPUFF
by Dongou Yang, Mei Li and Hui Liu
Atmosphere 2022, 13(12), 2129; https://doi.org/10.3390/atmos13122129 - 19 Dec 2022
Cited by 2 | Viewed by 1867
Abstract
The calculation of the three-dimensional atmospheric dispersion model is often time-consuming, which makes the model difficult to apply to the emergency field. With the aim of addressing this problem, we propose a parallel computing algorithm for the CALPUFF atmospheric dispersion model. Existing methods [...] Read more.
The calculation of the three-dimensional atmospheric dispersion model is often time-consuming, which makes the model difficult to apply to the emergency field. With the aim of addressing this problem, we propose a parallel computing algorithm for the CALPUFF atmospheric dispersion model. Existing methods for parallelizing the atmospheric dispersion model can be divided into two categories, with one using the parallel computing interface to rewrite the source code and the other directly dividing the repetitive elements in the computation task. This paper proposes an improved method based on the latter approach. Specifically, the method of spatial division with buffers is adopted to parallelize the wind field module of the CALPUFF model system, and the method for receptor layering is adopted to parallelize the dispersion module. In addition, the message queue software RabbitMQ is used as the communication middleware. A performance test is conducted on nine computing nodes on the Alibaba Cloud Computing Platform for a single-source continuous emergency leak case. The results show that the division method with a buffer of ten cells is most suitable for the case above in order to maintain the balance between computation speed and accuracy. This reduces the computation time of the model to about one-sixth, which is of great significance for extending the atmospheric dispersion model to the emergency field. Full article
(This article belongs to the Special Issue New Insights into Human Health by Air Quality Modeling, Simulation, and Observation)
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