Journal Description
Atmosphere
Atmosphere
is an international, peer-reviewed, open access journal of scientific studies related to the atmosphere published monthly online by MDPI. The Italian Aerosol Society (IAS) and Working Group of Air Quality in European Citizen Science Association (ECSA) are affiliated with Atmosphere and their members receive a discount on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), Ei Compendex, GEOBASE, GeoRef, Inspec, CAPlus / SciFinder, Astrophysics Data System, and other databases.
- Journal Rank: CiteScore - Q2 (Environmental Science (miscellaneous))
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 17.7 days after submission; acceptance to publication is undertaken in 2.8 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
- Testimonials: See what our editors and authors say about the Atmosphere.
- Companion journal: Meteorology.
Impact Factor:
2.9 (2022);
5-Year Impact Factor:
3.0 (2022)
Latest Articles
Impacts of Climate Change on Runoff in the Heihe River Basin, China
Atmosphere 2024, 15(5), 516; https://doi.org/10.3390/atmos15050516 - 23 Apr 2024
Abstract
Located in the central part of the arid regions of Northwest China, the Heihe River Basin (HRB) plays an important role in wind prevention, sand fixation, and soil and water conservation as the second largest inland river basin. In the context of the
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Located in the central part of the arid regions of Northwest China, the Heihe River Basin (HRB) plays an important role in wind prevention, sand fixation, and soil and water conservation as the second largest inland river basin. In the context of the warming and wetting climate observed in Northwest China, the situation of the ecological environment in the HRB is of significant concern. Using the data from meteorological observation stations, grid fusion and hydrological monitoring, this study analyzes the multi-scale climate changes in the HRB and their impacts on runoff. In addition, predictive models for runoff in the upper and middle reaches were developed using machine learning methods. The results indicate that the climate in the HRB has experienced an overall warming and wetting trend over the past 60 years. At the same time, there are clear regional variabilities in the climate changes. Precipitation shows decreasing trends in the northwestern part of the HRB, while it shows increases at rates higher than the regional average in the southeastern part. Moreover, the temperature increases are generally smaller in the upper reaches than those in the middle and lower reaches. Over the past 60 years, there has been a remarkable increase in runoff at the Yingluo Gorge (YL) hydrological station, which exhibits a distinct “single-peak” pattern in the variation of monthly runoff. The annual runoff volume at the YL (ZY) hydrological station is significantly correlated with the precipitation in the upper (middle) reaches, indicating the precipitation is the primary influencing factor determining the annual runoff. Temperature has a significant impact only on the runoff in the upper reaches, while its impact is not significant in the middle reaches. The models trained by the support vector machines and random forest models perform best in predicting the annual runoff and monthly runoff, respectively. This study can provide a scientific basis for environmental protection and sustainable development in the HRB.
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(This article belongs to the Section Climatology)
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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
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
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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.
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(This article belongs to the Special Issue Advances in Integrated Air Quality Management: Emissions, Monitoring, Modelling (3rd Edition))
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Open AccessArticle
The Observed Changes in Climate Characteristics in the Trebinje Vineyard Area (Bosnia and Herzegovina)
by
Tijana Banjanin, Zorica Ranković-Vasić, Milica Glišić and Zoran Pržić
Atmosphere 2024, 15(4), 514; https://doi.org/10.3390/atmos15040514 - 22 Apr 2024
Abstract
The productivity and quality of grapes and wine are significantly influenced by changing climate conditions in vineyard regions worldwide. This study assesses changes in temperature, precipitation, and viticultural indices between the periods of 1971–1990 and 2000–2019 in Trebinje, a vineyard area located in
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The productivity and quality of grapes and wine are significantly influenced by changing climate conditions in vineyard regions worldwide. This study assesses changes in temperature, precipitation, and viticultural indices between the periods of 1971–1990 and 2000–2019 in Trebinje, a vineyard area located in the Herzegovina region of Bosnia and Herzegovina. Between the two periods, mean annual temperature increased by 2 °C and mean vegetational temperature by 2.4 °C, while mean precipitation remained within the range of climatological variability, with annual values increasing by 6% and vegetational values decreasing by 4.6%. Warming resulted in a longer duration of the vegetation season by 23.7 days, a reduced risk of late spring frosts, and an increased risk of very high temperatures during summer. These changes led to the reclassification of Trebinje vineyards’ climate from Region III to Region V, based on the Winkler index values, from a “temperate warm” to a “warm” category, based on the Huglin heliothermic index, and from “cool nights” to “temperate nights” based on the cool nights index. The category of the dryness index remained unchanged between the two periods. The findings emphasize the necessity for a renewal of the viticultural zoning and the development of climate change-adaptation plans for this region.
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(This article belongs to the Special Issue Climate Change Impacts and Adaptation Strategies in Agriculture)
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Open AccessArticle
Monitoring Snow Cover in Typical Forested Areas Using a Multi-Spectral Feature Fusion Approach
by
Yunlong Wang and Jianshun Wang
Atmosphere 2024, 15(4), 513; https://doi.org/10.3390/atmos15040513 - 22 Apr 2024
Abstract
Accurate snow cover monitoring is greatly significant for the research of the hydrology model and regional climate variation, especially in Northeast China where forests cover almost forty percent of the total area. However, effectively monitoring snow cover under the forest canopy is still
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Accurate snow cover monitoring is greatly significant for the research of the hydrology model and regional climate variation, especially in Northeast China where forests cover almost forty percent of the total area. However, effectively monitoring snow cover under the forest canopy is still challenging with either in situ or remote sensing observations. The global SNOWMAP algorithm pertinent to the fixed normalized difference snow index (NDSI) threshold is, therefore, no longer applicable in a typical forested region of Northeast China. In order to achieve the goal of improving the accuracy of monitoring snow cover in areas with forest, utilizing MOD09GA and MOD13A1 products, a new approach of snow mapping was developed in this study, and it exploits the fusion and coupling of spectral features by integrating and analyzing the normalized difference forest snow index (NDFSI), the normalized difference vegetation index (NDVI), and the NDSI index. Then, the Landsat 8 OLI images of high resolution were used to evaluate the snow-mapping precision. The experimental results indicated that the NDFSI index combined with the NDVI index showed great potential for extracting the snow cover distribution in forested regions. Compared with the snow distribution obtained from the Landsat 8 images, the average bias and FAR (false alarm ratio) values of snow cover mapping obtained by this algorithm are 1.23 and 13.54%, which are reduced by 1.98 and 29.36%, respectively. The overall accuracy of 81.31% is reached, which is improved by 20.19%. Thus, the snow classification scheme combining multiple spectral features from MODIS data works effectively in improving the precision of automatic snow cover mapping in typical areas with forest of Northeast China, which provides essential support and significant perspective for the next step of establishing a runoff model and rationally regulating forest water resources.
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(This article belongs to the Special Issue Precipitation Monitoring and Databases)
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Open AccessArticle
Investigation on the Sensitivity of Precipitation Simulation to Model Parameterization and Analysis Nudging over Hebei Province, China
by
Yuanhua Li, Zhiguang Tian, Xia Chen, Xiashu Su and Entao Yu
Atmosphere 2024, 15(4), 512; https://doi.org/10.3390/atmos15040512 - 22 Apr 2024
Abstract
The physical parameterizations have important influence on model performance in precipitation simulation and prediction; however, previous investigations are seldom conducted at very high resolution over Hebei Province, which is often influenced by extreme events such as droughts and floods. In this paper, the
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The physical parameterizations have important influence on model performance in precipitation simulation and prediction; however, previous investigations are seldom conducted at very high resolution over Hebei Province, which is often influenced by extreme events such as droughts and floods. In this paper, the influence of parameterization schemes and analysis nudging on precipitation simulation is investigated using the WRF (weather research and forecasting) model with many sensitivity experiments at the cumulus “gray-zone” resolution (5 km). The model performance of different sensitivity simulations is determined by a comparison with the local high-quality observational data. The results indicate that the WRF model generally reproduces the distribution of precipitation well, and the model tends to underestimate precipitation compared with the station observations. The sensitivity simulation with the Tiedtke cumulus parameterization scheme combined with the Thompson microphysics scheme shows the best model performance, with the highest temporal correlation coefficient (0.45) and lowest root mean square error (0.34 mm/day). At the same time, analysis nudging, which incorporates observational information into simulation, can improve the model performance in precipitation simulation. Further analysis indicates that the negative bias in precipitation may be associated with the negative bias in relative humidity, which in turn is associated with the positive bias in temperature and wind speed. This study highlights the role of parameterization schemes and analysis nudging in precipitation simulation and provides a valuable reference for further investigations on precipitation forecasting applications.
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(This article belongs to the Special Issue Observations and Modeling of Precipitation Extremes and Tropical Cyclones)
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Open AccessArticle
Inactivation Mechanisms of Escherichia coli in Simulants of Respiratory and Environmental Aerosol Droplets
by
Mara Otero-Fernandez, Richard J. Thomas, Henry Oswin, Robert Alexander, Allen Haddrell and Jonathan P. Reid
Atmosphere 2024, 15(4), 511; https://doi.org/10.3390/atmos15040511 - 22 Apr 2024
Abstract
The airborne transmission of disease relies on the ability of microbes to survive aerosol transport and, subsequently, cause infection when interacting with a host. The length of time airborne microorganisms remain infectious in aerosol droplets is a function of numerous variables. We present
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The airborne transmission of disease relies on the ability of microbes to survive aerosol transport and, subsequently, cause infection when interacting with a host. The length of time airborne microorganisms remain infectious in aerosol droplets is a function of numerous variables. We present measurements of mass and heat transfer from liquid aerosol droplets combined with airborne survival data for Escherichia coli MRE162, an ACDP category 1 microorganism used as a model system, under a wide range of environmental conditions, droplet compositions and microbiological conditions. In tandem, these companion measurements demonstrate the importance of understanding the complex relationship between aerosol microphysics and microbe survival. Specifically, our data consist of the correlation of a wide range of physicochemical properties (e.g., evaporation rates, equilibrium water content, droplet morphology, compositional changes in droplet solute and gas phase, etc.), with airborne viability decay to infer the impact of aerosol microphysics on airborne bacterial survival. Thus, a mechanistic approach to support prediction of the survival of microorganisms in the aerosol phase as a function of biological, microphysical, environmental, and experimental (aerosol-generation and sampling) processes is presented. Specific findings include the following: surfactants do not increase bacteria stability in aerosol, while both the bacteria growth phase and bacteria concentration may affect the rate at which bacteria decay in aerosol.
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(This article belongs to the Special Issue Atmospheric Bioaerosols: Detection, Characterization and Modelling)
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Open AccessArticle
The Synergistic Effect of the Filtration Area Controlled by the Electromagnetic Valve and Injection Pressure on Pulse-Jet Dust Cleaning Performance
by
Yu Fu, Juan Lǖ, Shenglong Huang, Longyuan Lin and Haiyan Chen
Atmosphere 2024, 15(4), 510; https://doi.org/10.3390/atmos15040510 - 22 Apr 2024
Abstract
In engineering pulse-jet dust collector applications, the filtration area and injection pressure are chosen mostly based on experience. The peak pressure is tested under different injection pressures and filtration areas controlled by an electromagnetic valve, and then comprehensively analyzes the effects of dust
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In engineering pulse-jet dust collector applications, the filtration area and injection pressure are chosen mostly based on experience. The peak pressure is tested under different injection pressures and filtration areas controlled by an electromagnetic valve, and then comprehensively analyzes the effects of dust intensity, uniformity, and air consumption on dust cleaning to obtain a better filtration area controlled by an electromagnetic valve and injection pressure. The results show that considering the uniformity and intensity of dust cleaning, the filtration area of 33 m2 under the injection pressure of 0.4 MPa should be preferentially selected, with a standard deviation of 0.246 and a variance of 0.061. The filtration area of 27 m2 under the injection pressure of 0.3 MPa should be preferentially selected considering the unit air consumption, uniformity, and intensity of dust cleaning, the standard deviation of 0.252, and the variance of 0.064. The paper presents a theoretical foundation for selecting the optimal injection pressure and filter area regulated by an electromagnetic valve in pulse-jet dust collector systems.
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(This article belongs to the Section Air Quality)
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Wavelet Analysis of Atmospheric Ozone and Ultraviolet Radiation on Solar Cycle-24 over Lumbini, Nepal
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Prakash M. Shrestha, Suresh P. Gupta, Usha Joshi, Morgan Schmutzler, Rudra Aryal, Babu Ram Tiwari, Binod Adhikari, Narayan P. Chapagain, Indra B. Karki and Khem N. Poudyal
Atmosphere 2024, 15(4), 509; https://doi.org/10.3390/atmos15040509 - 21 Apr 2024
Abstract
This research aims to comprehensively examine the clearness index (KT), total ozone column (TOC), and ultraviolet A (UVA) and ultraviolet B radiation (UVB) over Lumbini, Nepal (27°28’ N, 83°16’ E, and 150 m above sea level) throughout the 11 years of
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This research aims to comprehensively examine the clearness index (KT), total ozone column (TOC), and ultraviolet A (UVA) and ultraviolet B radiation (UVB) over Lumbini, Nepal (27°28’ N, 83°16’ E, and 150 m above sea level) throughout the 11 years of solar cycle 24 (2008 to 2018). The Lumbini, a highly polluted region, is important in advancing the identification and analysis of TOC variations across regions with similar geographical and climatic attributes. Data from the Ozone Monitoring Instrument (OMI) of the EOS-AURA satellite of NASA were used to analyze the daily, monthly, seasonal, and annual trends in the clearness index (KT), ultraviolet A (UVA), ultraviolet B (UVB), and TOC from the Comprehensive Environmental Data Archive (CEDA). The study found that the yearly averages for KT, TOC, UVA, and UVB were 0.55 ± 0.13, 272 ± 14 DU, 12.61 ± 3.50 W/m2, and 0.32 ± 0.11 W/m2, respectively. These values provide insights into the long-term variations in atmospheric parameters at Lumbini. The study also applied the continuous wavelet transform (CWT) to analyze KT, TOC, UVA, and UVB temporal variations. The power density peak of 35,000 DU2 in the TOC was observed from the end of 2010 to the end of 2011, within 8.5 years, underscoring the significance of analyzing TOC dynamics over extended durations to understand atmospheric behavior comprehensively.
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(This article belongs to the Topic Accessing and Analyzing Air Quality and Atmospheric Environment)
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Quantifying Urban Daily Nitrogen Oxide Emissions from Satellite Observations
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Tao Tang, Lili Zhang, Hao Zhu, Xiaotong Ye, Donghao Fan, Xingyu Li, Haoran Tong and Shenshen Li
Atmosphere 2024, 15(4), 508; https://doi.org/10.3390/atmos15040508 - 21 Apr 2024
Abstract
Urban areas, characterized by dense anthropogenic activities, are among the primary sources of nitrogen oxides (NOx), impacting global atmospheric conditions and human health. Satellite observations, renowned for their continuity and global coverage, have emerged as an effective means to quantify pollutant
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Urban areas, characterized by dense anthropogenic activities, are among the primary sources of nitrogen oxides (NOx), impacting global atmospheric conditions and human health. Satellite observations, renowned for their continuity and global coverage, have emerged as an effective means to quantify pollutant emissions. Previous bottom-up emission inventories exhibit considerable discrepancies and lack a comprehensive and reliable database. To develop a high-precision emission inventory for individual cities, this study utilizes high-resolution single-pass observations from the TROPOspheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor satellite to quantify the emission rates of NOx. The Exponentially Modified Gaussian (EMG) model is validated for estimating NOx emission strength using real plumes observed in satellite single-pass observations, demonstrating good consistency with existing inventories. Further analysis based on the results reveals the existence of a weekend effect and seasonal variations in NOx emissions for the majority of the studied cities.
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(This article belongs to the Special Issue Reactive Nitrogen and Halogen in the Atmosphere)
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Forecasting the Mitigation Potential of Greenhouse Gas Emissions in Shenzhen through Municipal Solid Waste Treatment: A Combined Weight Forecasting Model
by
Xia Zhang, Bingchun Liu and Ningbo Zhang
Atmosphere 2024, 15(4), 507; https://doi.org/10.3390/atmos15040507 - 20 Apr 2024
Abstract
As a significant source of anthropogenic greenhouse gas emissions, the municipal solid waste sector’s greenhouse gas emission mode remains unknown, hampering effective decision-making on possible greenhouse gas emission reductions. Rapid urbanization and economic growth have resulted in massive volumes of municipal solid trash.
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As a significant source of anthropogenic greenhouse gas emissions, the municipal solid waste sector’s greenhouse gas emission mode remains unknown, hampering effective decision-making on possible greenhouse gas emission reductions. Rapid urbanization and economic growth have resulted in massive volumes of municipal solid trash. As a result, identifying emission reduction routes for municipal solid waste treatment is critical. In this research, we investigate the potential of municipal solid waste treatment methods in lowering greenhouse gas (GHG) emissions in Shenzhen, a typical Chinese major city. The results showed that the combined treatment of 58% incineration, 2% landfill, and 40% anaerobic digestion (AD) had the lowest greenhouse gas emissions of about 5.91 million tons under all scenarios. The implementation of waste sorting and anaerobic digestion treatment of organic municipal solid waste after separate collection can reduce greenhouse gas emissions by simply increasing the incineration ratio.
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(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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Open AccessCommunication
Optimal Variables for Retrieval Products
by
Simone Ceccherini
Atmosphere 2024, 15(4), 506; https://doi.org/10.3390/atmos15040506 - 20 Apr 2024
Abstract
The increase in satellite instruments sounding the atmosphere will increase the frequency of several instruments simultaneously measuring either the same vertical profile or vertical profiles related to nearby geo-locations, and users will consult fused products rather than individual measurements. Therefore, the retrieval products
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The increase in satellite instruments sounding the atmosphere will increase the frequency of several instruments simultaneously measuring either the same vertical profile or vertical profiles related to nearby geo-locations, and users will consult fused products rather than individual measurements. Therefore, the retrieval products should be optimized for use in data fusion operations, rather than for the representation of the profile. This change in paradigm raises the question of whether a more functional representation of the retrieval products exists. New variables for the retrieval products are proposed that have several advantages with respect to the standard retrieval products. These variables, in the linear approximation of the forward model, are independent of the a priori information used in the retrieval, allow us to represent the profile with any a priori information and can be used directly to perform the data fusion of a set of measurements. Furthermore, the use of these variables allows us to reduce the stored data to about one third of its volume with respect to the use of standard retrieval products.
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(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
Open AccessReview
Meteor Radar for Investigation of the MLT Region: A Review
by
Iain M. Reid
Atmosphere 2024, 15(4), 505; https://doi.org/10.3390/atmos15040505 - 20 Apr 2024
Abstract
This is an introductory review of modern meteor radar and its application to the measurement of the dynamical parameters of the Mesosphere Lower Thermosphere (MLT) Region within the altitude range of around 70 to 110 km, which is where most meteors are detected.
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This is an introductory review of modern meteor radar and its application to the measurement of the dynamical parameters of the Mesosphere Lower Thermosphere (MLT) Region within the altitude range of around 70 to 110 km, which is where most meteors are detected. We take a historical approach, following the development of meteor radar for studies of the MLT from the time of their development after the Second World War until the present. The application of the meteor radar technique is closely aligned with their ability to make contributions to Meteor Astronomy in that they can determine meteor radiants, and measure meteoroid velocities and orbits, and so these aspects are noted when required. Meteor radar capabilities now extend to measurements of temperature and density in the MLT region and show potential to be extended to ionospheric studies. New meteor radar networks are commencing operation, and this heralds a new area of investigation as the horizontal spatial variation of the upper-atmosphere wind over an extended area is becoming available for the first time.
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(This article belongs to the Special Issue Observations and Analysis of Upper Atmosphere)
Open AccessProject Report
A Mixed Method Study to Explore How Maintenance Personnel Can Enhance Wildfire Smoke Resilience at Long-Term Care Facilities in the US Mountain West
by
Adhieu Arok, James Caringi, Sarah Toevs, Meredith Spivak and Luke Montrose
Atmosphere 2024, 15(4), 504; https://doi.org/10.3390/atmos15040504 - 20 Apr 2024
Abstract
Wildfire activity is increasing around the world, concurrent with climate change, and mitigation strategies for protecting vulnerable populations are desperately needed. Because inhaled particles are deleterious to respiratory health, particularly among older adults with co-morbidities, we engaged maintenance personnel working in long term
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Wildfire activity is increasing around the world, concurrent with climate change, and mitigation strategies for protecting vulnerable populations are desperately needed. Because inhaled particles are deleterious to respiratory health, particularly among older adults with co-morbidities, we engaged maintenance personnel working in long term care facilities located in the Western US. Our objective was to identify opportunities to build resilience during wildfire smoke events. We implemented a virtual workshop that addressed wildfire smoke health impacts as well as strategies to assess and maintain indoor air quality. A total of 24 maintenance personnel attended the virtual workshop and 14 participated in a quantitative survey. Workshop attendees found value in the material and there was enthusiasm for educational resources and enhancing indoor air quality. Four months later, four maintenance staff participated in a follow-up interview. Our qualitative assessment revealed the following themes: awareness and prioritization, application of knowledge, barriers, and educational resources. Access to real-time actionable air quality data was a consistent feature across these themes. Maintenance personnel could play a key role in a facility’s ability to prepare for and respond to wildfire smoke events, and this study highlights potential challenges and opportunities to involving them in resilience building strategies.
Full article
(This article belongs to the Special Issue New Insights into Exposure and Health Impacts of Air Pollution)
Open AccessArticle
Characterization of Microbials in the Lung Induced by Allergenic Platanus Pollen Protein (Pla a3) and Ambient Fine Particulate Matter
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Jin Liu, Senlin Lu, Guoqing Hou, Wenwen Hu, Jiumei Zhao, Wei Zhang, Xinchun Liu, Enyoh Christian Ebere, Weiqian Wang and Qingyue Wang
Atmosphere 2024, 15(4), 503; https://doi.org/10.3390/atmos15040503 - 19 Apr 2024
Abstract
Ambient pollen proteins play key roles in the incidence of allergenic respiratory health, and numerous reports have focused on respiratory diseases caused by air pollutants. However, there is still a lack of understanding of the specific mechanisms underlying the involvement of microbiota in
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Ambient pollen proteins play key roles in the incidence of allergenic respiratory health, and numerous reports have focused on respiratory diseases caused by air pollutants. However, there is still a lack of understanding of the specific mechanisms underlying the involvement of microbiota in the respiratory tracts and effects induced by air pollutants. Therefore, an allergenic animal model was established to investigate the characterization of microbials in the lung induced by allergenic Platanus pollen protein (Pla a3) and ambient fine particulate matter. Our data showed that the mice exhibited strong immune and inflammatory responses after being exposed to PMs and Pla a3 protein. This included increased levels of immunoglobulins IgG and IgE, as well as elevated levels of cytokines TNF-α, IFN-γ, IL-4, and IL-13. Furthermore, the amounts of pathogenic bacteria, such as Desulfobacterota, Enterococcus, Ferruginibacter, and Pseudoxanthomonas, in the lung microbiota of the Pla a3 exposure group increased significantly. Correlation analysis revealed a strong association between specific lung bacteria and alterations in cytokines from the lung samples. Probiotic bacteria, Deferribacterota and Bifidobacterium, was associated with changes in the level of IgG and IgE. However, pathogenic bacteria, like Prevotella and Fusobacterium, were linked with the cytokines IL-4 and TNF-α.
Full article
(This article belongs to the Special Issue Composition Analysis and Health Effects of Atmospheric Particulate Matter)
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Open AccessArticle
Influence of Vertical Load, Inflation Pressure, and Driving Speed on the Emission of Tire–Road Particulate Matter and Its Size Distribution
by
Stefan Schläfle, Meng Zhang, Hans-Joachim Unrau and Frank Gauterin
Atmosphere 2024, 15(4), 502; https://doi.org/10.3390/atmos15040502 - 19 Apr 2024
Abstract
As fleet electrification progresses, vehicles are continuously becoming heavier, while the used electric motors, with their high torques, enable longitudinal dynamics to be maintained or even increased. This raises the question of what effect electric vehicles have on the emission of tire–road particulate
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As fleet electrification progresses, vehicles are continuously becoming heavier, while the used electric motors, with their high torques, enable longitudinal dynamics to be maintained or even increased. This raises the question of what effect electric vehicles have on the emission of tire–road particulate matter (PM). To answer this question, investigations were carried out in this study on a tire internal drum test bench with real road surfaces. In addition to the vertical load, the tire inflation pressure and the driving speed were varied. PM emissions were recorded in real time, resulting in emission factors (emission per kilometer driven) for different load conditions. This allows statements to be made about both the effect on the total emission and on the particle size distribution. It was shown that the PM emission increases linearly with the vertical load at constant longitudinal dynamics. If the tire inflation pressure is increased, the emission also increases linearly, and the increases in emission are equally large for both influences. A clear influence of the driving speed on the emission factor could not be determined. With regard to the particle size distribution, the following correlations were found: higher vertical load and higher tire inflation pressure result in a larger mean particle diameter, while a higher driving speed reduces it. Thus, this study contributes to a better understanding of the expected changes in tire-road PM emissions as a result of electrification.
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(This article belongs to the Special Issue Traffic Related Emission (2nd Edition))
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Open AccessArticle
Impact of a New Radiation Scheme on Simulated Climate in the Global–Regional Integrated SysTem Model under Varying Physical Parameterization Schemes
by
Chang Yuan, Hua Zhang, Xianwen Jing, Shuyun Zhao and Xiaohan Li
Atmosphere 2024, 15(4), 501; https://doi.org/10.3390/atmos15040501 - 19 Apr 2024
Abstract
In this study, the radiation scheme BCC-RAD (Beijing Climate Center RADiative transfer model) developed for global climate models is implemented into the Global–Regional Integrated SysTem (GRIST) model as an alternative to the default RRTMG (general circulation model (GCM) version of the Rapid Radiative
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In this study, the radiation scheme BCC-RAD (Beijing Climate Center RADiative transfer model) developed for global climate models is implemented into the Global–Regional Integrated SysTem (GRIST) model as an alternative to the default RRTMG (general circulation model (GCM) version of the Rapid Radiative Transfer Model) scheme. Its impact on the simulated climate is comprehensively evaluated under different physics parametrization packages, in comparison with both the CERES (partly from ERA5 reanalysis) observations and multi-model results from CMIP6. The results indicate that under the default physics parameterization package of GRIST (PhysC), BCC-RAD improved the simulated global mean cloud cover by ~3% and the clear-sky outgoing longwave radiation by ~5.6 W/m2. Upon the inclusion of the PhysCN parameterization package, BCC-RAD exhibited further improvement in simulated cloud cover and radiative forcing (particularly longwave radiative forcing, the bias of which decreases from −9.2 W/m2 to −1.8 W/m2), leading it to be closer to observations than RRTMG. Additionally, BCC-RAD improved the simulation of atmospheric temperature and hence notably diminished the apparent overestimation of atmospheric humidity seen in RRTMG. This study demonstrates the advantages of BCC-RAD over RRTMG in certain aspects of the GRIST-simulated climate, verifying its capability for the climate-oriented configuration of GRIST.
Full article
(This article belongs to the Special Issue Ozone Pollution and Effects in China)
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Open AccessArticle
Global El Niño–Southern Oscillation Teleconnections in CMIP6 Models
by
Ilya V. Serykh and Dmitry M. Sonechkin
Atmosphere 2024, 15(4), 500; https://doi.org/10.3390/atmos15040500 - 19 Apr 2024
Abstract
The results of a piControl experiment investigating general circulation models participating in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) were examined. The global interannual variability in the monthly surface temperature (ST) and sea level pressure (SLP) anomalies was considered. The
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The results of a piControl experiment investigating general circulation models participating in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) were examined. The global interannual variability in the monthly surface temperature (ST) and sea level pressure (SLP) anomalies was considered. The amplitudes of the fluctuations in the anomalies of these meteorological fields between opposite phases of the El Niño–Southern Oscillation (ENSO) were calculated. It was shown that most CMIP6 models reproduced fluctuations in the ST and SLP anomalies between El Niño and La Niña not only in the equatorial Pacific, but also throughout the tropics, as well as in the middle and high latitudes. Some of the CMIP6 models reproduced the global structures of the ST and SLP anomaly oscillations quite accurately between opposite phases of ENSO, as previously determined from observational data and reanalyses. It was found that the models AS-RCEC TaiESM1, CAMS CAMS-CSM1-0, CAS FGOALS-f3-L, CMCC CMCC-ESM2, KIOST KIOST-ESM, NASA GISS-E2-1-G, NCAR CESM2-WACCM-FV2, and NCC NorCPM1 reproduced strong ENSO teleconnections in regions beyond the tropical Pacific.
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(This article belongs to the Special Issue Multi-Year ENSO Events: Dynamics, Predictability, Teleconnections, and Impacts)
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Open AccessArticle
Data-Driven Prediction of Severe Convection at Deutscher Wetterdienst (DWD): A Brief Overview of Recent Developments
by
Richard Müller and Axel Barleben
Atmosphere 2024, 15(4), 499; https://doi.org/10.3390/atmos15040499 - 19 Apr 2024
Abstract
Thunderstorms endanger life and infrastructure. The accurate and precise prediction of thunderstorms is therefore helpful to enable protection measures and to reduce the risks. This manuscript presents the latest developments to improve thunderstorm forecasting in the first few hours. This includes the description
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Thunderstorms endanger life and infrastructure. The accurate and precise prediction of thunderstorms is therefore helpful to enable protection measures and to reduce the risks. This manuscript presents the latest developments to improve thunderstorm forecasting in the first few hours. This includes the description and discussion of a new Julia-based method (JuliaTSnow) for the temporal extrapolation of thunderstorms and the blending of this method with the numerical weather prediction model (NWP) ICON. The combination of ICON and JuliaTSnow attempts to overcome the limitations associated with the pure extrapolation of observations with atmospheric motion vectors (AMVs) and thus increase the prediction horizon. For the blending, the operational ICON-D2 is used, but also the experimental ICON-RUC, which is implemented with a faster data assimilation update cycle. The blended products are evaluated against lightning data. The critical success index (CSI) for the blended RUC product is higher for all forecast time steps. This is mainly due to the higher resolution of the AMVs (prediction hours 0–2) and the rapid update cycle of ICON-RUC (prediction hours 2–6). The results demonstrate the potential of the rapid update cycle to improve the short-term forecasts of thunderstorms. Moreover, the transition between AMV-driven nowcasting to NWP is much smoother in the blended RUC product, which points to the advantages of fast data assimilation for seamless predictions. The CSI is well above the critical value of 0.5 for the 0–2 h forecasts. Values below 0.5 mean that the number of hits (correct informations) is lower than the number of failures, which results from the missed cells plus false alarms. The product is then no longer useful in forecasting thunderstorms with a spatial accuracy of 0.3 degrees. Unfortunately, with RUC, the CSI also drops below 0.5 when the last forecast is more than 3 h away from the last data assimilation, indicating the lack of model physics to accurately predict thunderstorms. This lack is simply a result of chaos theory. Within this context, the role of NWP in comparison with artificial intelligence (AI) is discussed, and it is concluded that AI could replace physical short-term forecasts in the near future.
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(This article belongs to the Special Issue Advancements in Thunderstorm Nowcasting and Atmospheric Electricity Monitoring by Remote Sensing)
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An Update of the NeQuick-Corr Topside Ionosphere Modeling Based on New Datasets
by
Michael Pezzopane, Alessio Pignalberi, Marco Pietrella, Haris Haralambous, Fabricio Prol, Bruno Nava, Artem Smirnov and Chao Xiong
Atmosphere 2024, 15(4), 498; https://doi.org/10.3390/atmos15040498 - 18 Apr 2024
Abstract
A new analytical formula for H0, one of the three parameters (H0, g, and r) on which the NeQuick model is based to describe the altitude profile of the electron density above the F2-layer peak height
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A new analytical formula for H0, one of the three parameters (H0, g, and r) on which the NeQuick model is based to describe the altitude profile of the electron density above the F2-layer peak height hmF2, has recently been proposed. This new analytical representation of H0, called H0,corr, relies on numerical grids based on two different types of datasets. On one side, electron density observations by the Swarm satellites over Europe from December 2013 to September 2018, and on the other side, IRI UP (International Reference Ionosphere UPdate) maps over Europe of the critical frequency of the ordinary mode of propagation associated with the F2 layer, foF2, and hmF2, at 15 min cadence for the same period. The new NeQuick topside representation based on H0,corr, hereafter referred to as NeQuick-corr, improved the original NeQuick topside representation. This work updates the numerical grids of H0,corr by extending the underlying Swarm and IRI UP datasets until December 2021, thus allowing coverage of low solar activity levels, as well. Moreover, concerning Swarm, besides the original dataset, the calibrated one is considered, and corresponding grids of H0,corr calculated. At the same time, the role of g is investigated, by considering values different from the reference one, equal to 0.125, currently adopted. To understand what are the best H0,corr grids to be considered for the NeQuick-corr topside representation, vertical total electron content data for low, middle, and high latitudes, recorded from five low-Earth-orbit satellite missions (COSMIC/FORMOSAT-3, GRACE, METOP, TerraSAR-X, and Swarm) have been analyzed. The updated H0,corr grids based on the original Swarm dataset with a value for g = 0.15, and the updated H0,corr grids based on the calibrated Swarm dataset with a value for g = 0.14, are those for which the best results are obtained. The results show that the performance of the different NeQuick-corr models is reliable also for low latitudes, even though these are outside the spatial domain for which the H0,corr grids were obtained, and are dependent on solar activity.
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(This article belongs to the Special Issue The Role of Solar Wind-Magnetosphere Coupling in the Ionospheric Dynamics)
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Open AccessArticle
Quantifying the Atmospheric Water Balance Closure over Mainland China Using Ground-Based, Satellite, and Reanalysis Datasets
by
Linghao Zhou, Yunchang Cao, Chuang Shi, Hong Liang and Lei Fan
Atmosphere 2024, 15(4), 497; https://doi.org/10.3390/atmos15040497 - 18 Apr 2024
Abstract
Quantifying the atmospheric water balance is critical for the study of hydrological processes in significant regions. This study quantified atmospheric water balance closure at 205 stations in mainland China on a monthly timescale from 2009 to 2018 using datasets from ground- and satellite-based
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Quantifying the atmospheric water balance is critical for the study of hydrological processes in significant regions. This study quantified atmospheric water balance closure at 205 stations in mainland China on a monthly timescale from 2009 to 2018 using datasets from ground- and satellite-based observations and reanalysis data. The closure performances were firstly quantified using the mean and root mean square (RMS) of the residuals, and the possible influencing factors were explored, as well as the influence of different water balance components (WBCs) using different datasets. In the closure experiment using ERA5, the mean and residuals were 6.26 and 12.39 mm/month, respectively, on average, which indicated a closure uncertainty of 12.8%. Using ERA5 analysis as a reference, the closure experiment using different combinations revealed average mean residuals of 8.73, 11.50, and 15.89 mm/month, indicating a precipitation closure uncertainty of 22.0, 23.7, and 24.4% for the ground- and satellite-based observations and reanalysis data, respectively. Two possible influencing factors, station latitude and the climatic zone in which the station is located, were shown to be related to closure performance. Finally, the analysis of the impact from different WBCs showed that precipitation tended to have the most significant impact, which may have been due to larger observation uncertainties. Generally, the atmospheric water balance in mainland China can be closed using datasets from different observational techniques.
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(This article belongs to the Special Issue Hydroclimate in a Changing World: Recent Trends, Current Progress and Future Directions (2nd Edition))
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