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Advances in Integrated Air Quality Management: Emissions, Monitoring, Modelling (3rd...
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Advances in Integrated Air Quality Management: Emissions, Monitoring, Modelling (3rd Edition)

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

Deadline for manuscript submissions: 29 January 2025 | Viewed by 10958

Special Issue Editors

Dr. Adrianos Retalis

E-Mail Website
Guest Editor
Institute for Environmental Research & Sustainable Development (IERSD), National Observatory of Athens (NOA), GR 15236 Athens, Greece
Interests: environmental applications of remote sensing; atmospheric correction; air quality assessment/monitoring; aerosols; natural hazards; land cover/use change; GIS; spatial data analysis; climate change; natural disasters and extremes; desertification; precision farming; soil erosion
Special Issues, Collections and Topics in MDPI journals
Dr. Vasiliki Assimakopoulos

E-Mail Website
Guest Editor
Institute for Environmental Research & Sustainable Development, National Observatory of Athens, GR-15236 Athens, Greece
Interests: emission inventory development; chemical transport modeling; urban air quality; air pollution mitigation strategies
Special Issues, Collections and Topics in MDPI journals
Dr. Kyriaki-Maria Fameli

E-Mail Website
Guest Editor
Institute for Environmental Research & Sustainable Development, National Observatory of Athens, GR-15236 Athens, Greece
Interests: emission inventory development (classical pollutants and GHGs); air and particulate pollution over urban areas; GIS; air quality modeling; low-cost sensor monitoring; raising climate change awareness
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue is a follow-up of the Special Issue entitled “Advances in Integrated Air Quality Management: Emissions, Monitoring, Modelling (2nd Volume)” (https://www.mdpi.com/journal/atmosphere/special_issues/588FW03HQ9) published in Atmosphere, and it will cover all aspects of air quality management issues.

Air pollution has become an increasingly important environmental issue on a global scale since the sources that cause poor air quality and are responsible for climate change are common. Both natural and anthropogenic components of air pollution have been long recognized and are continuously being investigated to identify their links with local and regional air quality, the impact on the climate, health and ecosystems, and new sources and pollutants, as well as links between emissions and air pollution management. In this respect, climate change effects feed the increase in critical air pollutants such as Ozone, and air pollution enhances climate change (e.g., black carbon from fossil fuels burning).

Air quality is monitored at the surface through ground-based monitors, official networks, low-cost sensors and, recently, cheap and easy-to-use sensors by citizens. Additional data come from satellite and remote observations to contribute to the temporal and spatial study of air pollution. Monitoring aims to identify and quantify the pollution sources, air quality, compliance with ambient air quality standards, exposure and impact from other parameters (meteorology, topography, accidental release, etc.).  In order for air quality to be managed, the continuous application and updating of modeling tools, emissions inventories, and advanced statistical methodologies to produce solutions and assess policies is a prerequisite.

This proposal aims to gather research papers focused on air pollution and climate change inter-relations, assessing the implementation of policies and measures, novel methodologies for emission inventories, remote and in situ experimental observations, meteorological parameters, the application of chemical transport and/or development of statistical models for forecasting air pollution levels, and assisting the monitoring and mapping of air pollution close to major sources or in greater areas. 

Dr. Adrianos Retalis
Dr. Vasiliki Assimakopoulos
Dr. Kyriaki-Maria Fameli
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

  • emission inventory
  • air pollution monitoring
  • air pollution assessment
  • exposure
  • climate change and air pollution
  • PM2.5, PM10
  • ozone
  • aerosols
  • statistical forecasting models
  • chemical transport models
  • urban air pollution
  • remote sensing

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Published Papers (8 papers)

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Research

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24 pages, 4262 KiB  
Article
The Seasonality of PM and NO2 Concentrations in Slovakia and a Comparison with Chemical-Transport Model
by Tereza Šedivá and Dušan Štefánik
Atmosphere 2024, 15(10), 1203; https://doi.org/10.3390/atmos15101203 - 8 Oct 2024
Viewed by 581
Abstract
The air quality (AQ) of a given location depends mostly on two factors: emissions and meteorological conditions. For most places on Earth, the meteorology of an area changes seasonally. For central Europe, winters are associated with poor dispersion conditions, which, in combination with [...] Read more.
The air quality (AQ) of a given location depends mostly on two factors: emissions and meteorological conditions. For most places on Earth, the meteorology of an area changes seasonally. For central Europe, winters are associated with poor dispersion conditions, which, in combination with high emissions from local heating systems, lead to significantly higher concentrations than during summer. In this study, the seasonality of AQ is analysed using hourly measurements from 44 monitoring stations in Slovakia for the years 2007–2023 for NO2, PM10 and PM2.5. Two factors are used to evaluate the seasonality—the difference and ratio of the winter and summer mean concentrations. It was found that the seasonal difference has been gradually decreasing for all pollutants since 2017. In the case of PM2.5, the seasonal ratio drops from a value of around 2.5 in 2018 to approximately 1.7 in 2023. While in the past, the seasonal ratio was the highest for PM2.5, in the last three years it is the highest for NO2 with values larger than 2. Our results imply that summer sources of PM emissions start to play a more important role for the AQ than in the past. The observed seasonality was compared with two full-year chemical-transport model simulations. Full article
(This article belongs to the Special Issue Advances in Integrated Air Quality Management: Emissions, Monitoring, Modelling (3rd Edition))
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14 pages, 7934 KiB  
Article
Assimilating Satellite-Derived Snow Cover and Albedo Data to Improve 3-D Weather and Photochemical Models
by Colleen Jones, Huy Tran, Trang Tran and Seth Lyman
Atmosphere 2024, 15(8), 954; https://doi.org/10.3390/atmos15080954 - 10 Aug 2024
Viewed by 640
Abstract
During wintertime temperature inversion episodes, ozone in the Uinta Basin sometimes exceeds the standard of 70 ppb set by the US Environmental Protection Agency. Since ozone formation depends on sunlight, and less sunlight is available during winter, wintertime ozone can only form if [...] Read more.
During wintertime temperature inversion episodes, ozone in the Uinta Basin sometimes exceeds the standard of 70 ppb set by the US Environmental Protection Agency. Since ozone formation depends on sunlight, and less sunlight is available during winter, wintertime ozone can only form if snow cover and albedo are high. Researchers have encountered difficulties replicating high albedo values in 3-D weather and photochemical transport model simulations for winter episodes. In this study, a process to assimilate MODIS satellite data into WRF and CAMx models was developed, streamlined, and tested to demonstrate the impacts of data assimilation on the models’ performance. Improvements to the WRF simulation of surface albedo and snow cover were substantial. However, the impact of MODIS data assimilation on WRF performance for other meteorological quantities was minimal, and it had little impact on ozone concentrations in the CAMx photochemical transport model. The contrast between the data assimilation and reference cases was greater for a period with no new snow since albedo appears to decrease too rapidly in default WRF and CAMx configurations. Overall, the improvement from MODIS data assimilation had an observed enhancement in the spatial distribution and temporal evolution of surface characteristics on meteorological quantities and ozone production. Full article
(This article belongs to the Special Issue Advances in Integrated Air Quality Management: Emissions, Monitoring, Modelling (3rd Edition))
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14 pages, 2237 KiB  
Article
Impact of the No-Driving Day Program on Air Quality in a High-Altitude Tropical City: The Case of the Toluca Valley Metropolitan Area
by Agustin Garcia, Victor Almanza, Dzoara Tejeda and Mauro Alvarado-Castillo
Atmosphere 2024, 15(4), 437; https://doi.org/10.3390/atmos15040437 - 31 Mar 2024
Viewed by 1190
Abstract
This study addresses the pressing issue of urban air pollution impact, emphasizing the need for emissions control to ensure environmental equity. Focused on the Toluca Valley Metropolitan Area (TVMA), this research employs air quality modeling to examine ozone, sulfur dioxide, nitrogen dioxide, and [...] Read more.
This study addresses the pressing issue of urban air pollution impact, emphasizing the need for emissions control to ensure environmental equity. Focused on the Toluca Valley Metropolitan Area (TVMA), this research employs air quality modeling to examine ozone, sulfur dioxide, nitrogen dioxide, and carbon monoxide concentrations during three different periods in 2019. It quantitatively assesses the performance of a state-of-the-art air quality model while evaluating the efficacy of a No-Driving day mitigation measure program, similar to the one which is currently implemented in Mexico City. Using an updated national emissions inventory for 2016, this study highlights the model capability of representing ozone formation and shows that reducing mobile emissions of key pollutants contributes to lowering downwind surface ozone levels, albeit with a minimal local impact. The insights and tools from this work hold potential value for decision-making in the broader Megalopolis context, aligning with global efforts to comprehend and mitigate urban air pollution impacts. Full article
(This article belongs to the Special Issue Advances in Integrated Air Quality Management: Emissions, Monitoring, Modelling (3rd Edition))
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20 pages, 6050 KiB  
Article
Improving the Estimation of PM2.5 Concentration in the North China Area by Introducing an Attention Mechanism into Random Forest
by Luo Zhang, Zhengqiang Li, Jie Guang, Yisong Xie, Zheng Shi, Haoran Gu and Yang Zheng
Atmosphere 2024, 15(3), 384; https://doi.org/10.3390/atmos15030384 - 20 Mar 2024
Viewed by 1308
Abstract
Fine particulate matter with an aerodynamic diameter less than 2.5 µm (PM2.5) profoundly affects environmental systems, human health and economic structures. Multi-source data and advanced machine or deep-learning methods have provided a new chance for estimating the [...] Read more.
Fine particulate matter with an aerodynamic diameter less than 2.5 µm (PM2.5) profoundly affects environmental systems, human health and economic structures. Multi-source data and advanced machine or deep-learning methods have provided a new chance for estimating the PM2.5 concentrations at a high spatiotemporal resolution. In this paper, the Random Forest (RF) algorithm was applied to estimate hourly PM2.5 of the North China area (Beijing–Tianjin–Hebei, BTH) based on the next-generation geostationary meteorological satellite Himawari-8/AHI (Advanced Himawari Imager) aerosol optical depth (AOD) products. To improve the estimation of PM2.5 concentration across large areas, we construct a method for co-weighting the environmental similarity and the geographical distances by using an attention mechanism so that it can efficiently characterize the influence of spatial–temporal information hidden in adjacent ground monitoring sites. In experiment results, the hourly PM2.5 estimates are well correlated with ground measurements in BTH, with a coefficient of determination (R2) of 0.887, a root-mean-square error (RMSE) of 18.31 μg/m3, and a mean absolute error (MAE) of 11.17 µg/m3, indicating good model performance. In addition, this paper makes a comprehensive analysis of the effectiveness of multi-source data in the estimation process, in this way, to simplify the model structure and improve the estimation efficiency of the model while ensuring its accuracy. Full article
(This article belongs to the Special Issue Advances in Integrated Air Quality Management: Emissions, Monitoring, Modelling (3rd Edition))
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16 pages, 5349 KiB  
Article
Trends of the Global Burden of Disease Linked to Ground-Level Ozone Pollution: A 30-Year Analysis for the Greater Athens Area, Greece
by Kleopatra Ntourou, Kyriaki-Maria Fameli, Konstantinos Moustris, Nikolaos Manousakis and Christos Tsitsis
Atmosphere 2024, 15(3), 380; https://doi.org/10.3390/atmos15030380 - 20 Mar 2024
Cited by 1 | Viewed by 1387
Abstract
The Greater Athens Area (GAA), situated in the southern part of the European continent (in Greece), has a Mediterranean climate characterized by hot, dry summers and mild, wet winters. As a result of increased sunshine and high temperatures, exceedances in ozone concentrations are [...] Read more.
The Greater Athens Area (GAA), situated in the southern part of the European continent (in Greece), has a Mediterranean climate characterized by hot, dry summers and mild, wet winters. As a result of increased sunshine and high temperatures, exceedances in ozone concentrations are often recorded during the hot period. In the present study, the monthly as well as daily variations of O3 concentrations at thirteen stations in the GAA were investigated for the period 1987–2019. Moreover, the impact of O3 on the people’s health in Greece was examined by using data from the Global Burden of Disease (GBD) study with the socio-economic conditions of the country. Ozone concentrations were found to be particularly high during the summer months, especially in suburban stations. Values ranged from 65 μg/m3 to 90 μg/m3 during the night, in contrast to urban areas and remain high for several hours. Comparing estimates from GBD, it was found that exposure to ozone can impair respiratory function, leading to death or susceptibility to respiratory diseases that reduce quality of life, especially for people over 55 years of age. Finally, since 2009, when the economic crisis began in Greece, an upward trend was observed for deaths and disability adjusted life years. Full article
(This article belongs to the Special Issue Advances in Integrated Air Quality Management: Emissions, Monitoring, Modelling (3rd Edition))
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13 pages, 1712 KiB  
Article
Effect of Heating Emissions on the Fractal Size Distribution of Atmospheric Particle Concentrations
by Namkha Norbu, Xiaolei Sheng, Qiang Liu, Haihui Han and Xin Zhang
Atmosphere 2024, 15(1), 95; https://doi.org/10.3390/atmos15010095 - 11 Jan 2024
Cited by 1 | Viewed by 972
Abstract
Excessive particle concentrations during heating periods, which greatly affect people’s physical and mental health and their normal lives, continue to be a concern. It is more practical to understand and analyze the relationship between the fractal dimension and particle size concentration distribution of [...] Read more.
Excessive particle concentrations during heating periods, which greatly affect people’s physical and mental health and their normal lives, continue to be a concern. It is more practical to understand and analyze the relationship between the fractal dimension and particle size concentration distribution of atmospheric particulate matter before and after adjusting heating energy consumption types. The data discussed and analyzed in this paper were collected by monitoring stations and measured from 2016 to 2018 in Xi’an. The data include fractal dimension and particle size concentration changes in the atmospheric particulate matter before and after adjusting the heating energy consumption types. The results indicate that adjusting the heating energy consumption types has a significant impact on particulate matter. The average concentration of PM2.5 decreased by 26.4 μg/m3. The average concentration of PM10 decreased by 31.8 μg/m3. At the same time, the different particle sizes showed a downward trend. The particles ranging from 0.265 to 0.475 μm demonstrated the maximum decrease, which was 8.80%. The heating period in Xi’an mainly involves particles ranging from 0 to 0.475 μm. The fractal dimensions of the atmospheric particulate matter before and after adjusting the heating energy consumption types were 4.809 and 3.397, respectively. After adjusting the heating energy consumption types, the fractal dimension decreased by 1.412. At that time, the proportions of particle sizes that were less than 1.0 μm, 2.0 μm, and 2.5 μm decreased by 1.467%, 0.604%, and 0.424%, respectively. This paper provides new methods and a reference value for the distribution and effective control of atmospheric particulate matter by adjusting heating energy consumption types. Full article
(This article belongs to the Special Issue Advances in Integrated Air Quality Management: Emissions, Monitoring, Modelling (3rd Edition))
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Review

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23 pages, 4347 KiB  
Review
Drone-Assisted Particulate Matter Measurement in Air Monitoring: A Patent Review
by Eladio Altamira-Colado, Daniel Cuevas-González, Marco A. Reyna, Juan Pablo García-Vázquez, Roberto L. Avitia and Alvaro R. Osornio-Vargas
Atmosphere 2024, 15(5), 515; https://doi.org/10.3390/atmos15050515 - 23 Apr 2024
Cited by 2 | Viewed by 2060
Abstract
Air pollution is caused by the presence of polluting elements. Ozone (O3), carbon monoxide (CO), carbon dioxide (CO2), nitrogen dioxide (NO2), sulfur dioxide (SO2), and particulate matter (PM) are the most controlled gasses because they [...] Read more.
Air pollution is caused by the presence of polluting elements. Ozone (O3), carbon monoxide (CO), carbon dioxide (CO2), nitrogen dioxide (NO2), sulfur dioxide (SO2), and particulate matter (PM) are the most controlled gasses because they can be released into the atmosphere naturally or as a result of human activity, which affects air quality and causes disease and premature death in exposed people. Depending on the substance being measured, ambient air monitors have different types of air quality sensors. In recent years, there has been a growing interest in designing drones as mobile sensors for monitoring air pollution. Therefore, the objective of this paper is to provide a comprehensive patent review to gain insight into the proprietary technologies currently used in drones used to monitor outdoor air pollution. Patent searches were conducted using three different patent search engines: Google Patents, WIPO’s Patentscope, and the United States Patent and Trademark Office (USPTO). The analysis of each patent consists of extracting data that supply information regarding the type of drone, sensor, or equipment for measuring PM, the lack or presence of a cyclone separator, and the ability to process the turbulence generated by the drone’s propellers. A total of 1473 patent documents were retrieved using the search engine. However, only 13 met the inclusion criteria, including patent documents reporting drone designs for outdoor air pollution monitoring. Therefore, was found that most patents fall under class G01N (measurement; testing) according to the International Patents Classification, where the most common sensors and devices are infrared or visible light cameras, cleaning devices, and GPS tracking devices. The most common tasks performed by drones are air pollution monitoring, assessment, and control. These categories cover different aspects of the air pollution management cycle and are essential to effectively address this environmental problem. Full article
(This article belongs to the Special Issue Advances in Integrated Air Quality Management: Emissions, Monitoring, Modelling (3rd Edition))
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22 pages, 972 KiB  
Review
Smartphone-Based Color Evaluation of Passive Samplers for Gases: A Review
by Kanokwan Kiwfo, Kate Grudpan, Andreas Held and Wolfgang Frenzel
Atmosphere 2024, 15(4), 451; https://doi.org/10.3390/atmos15040451 - 4 Apr 2024
Viewed by 1961
Abstract
The application of smartphone-based color evaluation of passive sampling devices for gases has only been sparsely reported. The present review aims to compile available publications with respect to the configuration of the passive samplers, conditions of smartphone photographing, analytical procedures for color detection [...] Read more.
The application of smartphone-based color evaluation of passive sampling devices for gases has only been sparsely reported. The present review aims to compile available publications with respect to the configuration of the passive samplers, conditions of smartphone photographing, analytical procedures for color detection and quantification (including calibration processes), and their application to different target gases. The performance of the methods—whenever available—is presented regarding the analytical specifications selectivity, sensitivity, and limit of detection in comparison with other color evaluation methods of passive samplers. Practical aspects like requirements of instrumentation and ease of use will be outlined in view of the potential employment in education and citizen science projects. In one section of the review, the inconsistent terminology of passive and diffusive sampling is discussed in order to clarify the distinction of information obtained from the uptake of the passive samplers between gas-phase concentration and the accumulated deposition flux of gaseous analytes. Colorimetric gas sensors are included in the review when applied in passive sampling configurations and evaluation is performed with smartphone-based color evaluation. Differences in the analytical procedures employed after the passive sampling step and prior to the detection of the colored compounds are also presented. Full article
(This article belongs to the Special Issue Advances in Integrated Air Quality Management: Emissions, Monitoring, Modelling (3rd Edition))
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