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Atmosphere, Volume 15, Issue 6 (June 2024) – 111 articles

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21 pages, 1918 KiB  
Article
Fiber Lidar for Control of the Ecological State of the Atmosphere
by Sergei N. Volkov, Nikolai G. Zaitsev, Sun-Ho Park, Duk-Hyeon Kim and Young-Min Noh
Atmosphere 2024, 15(6), 729; https://doi.org/10.3390/atmos15060729 (registering DOI) - 18 Jun 2024
Viewed by 54
Abstract
Methods and means of remote control of the ecological state of the atmosphere are constantly improving. Lidar sensing allows obtaining up-to-date information about natural and technogenic sources of atmospheric pollution. There is a wide range of problems in ecological control, where the deployment [...] Read more.
Methods and means of remote control of the ecological state of the atmosphere are constantly improving. Lidar sensing allows obtaining up-to-date information about natural and technogenic sources of atmospheric pollution. There is a wide range of problems in ecological control, where the deployment of an inexpensive mobile lidar network is required. For this purpose, it is suggested to use Q-switch and MOPA fiber lasers in lidars. Q-switch fiber lasers have a simpler design and are more practical to use. However, pulses from Q-switch lasers have long full-pulse durations. In the present work, a lidar signal inversion method (LSIM) is proposed for solving this problem. Verification and outdoor experimentation of the LSIM was carried out with the reference signal method (RSM). The advantage of the proposed RSM is the minimum number of controllable parameters necessary for LSIM verification and approbation. As a result, the accuracy of the obtained results increased. Thus, the possibility of application of the Q-switch fiber lasers for lidar sensing is shown both theoretically and experimentally. Full article
18 pages, 11359 KiB  
Article
Study of Quality Control Methods Utilizing IRMCD for HY-2B Data Assimilation Application
by Jiazheng Hu, Yu Zhang, Jianjun Xu, Jiajing Li, Duanzhou Shao, Qichang Tan and Junjie Feng
Atmosphere 2024, 15(6), 728; https://doi.org/10.3390/atmos15060728 - 18 Jun 2024
Viewed by 101
Abstract
Quality control (QC) of HaiYang-2B (HY-2B) satellite data is mainly based on the observation process, which remains uncertain for data assimilation (DA). The data in operation have not been widely used in numerical weather prediction. To ensure HY-2B data meet the theoretical assumptions [...] Read more.
Quality control (QC) of HaiYang-2B (HY-2B) satellite data is mainly based on the observation process, which remains uncertain for data assimilation (DA). The data in operation have not been widely used in numerical weather prediction. To ensure HY-2B data meet the theoretical assumptions for DA applications, the iterated reweighted minimum covariance determinant (IRMCD) QC method was studied in HY-2B data based on the typhoon “Chanba”. The statistical results showed that most of the outliers were eliminated, and the observation increment distribution of the HY-2B data after QC (QCed) was closer to a Gaussian distribution than the raw data. The kurtosis and skewness of the QCed data were much closer to zero. The QCed track demonstrated the lowest accumulated error and the best intensity in typhoon assimilation, and the QCed intensity was closest to the observation during the nearshore enhancement, exhibiting the strongest intensity among the experiment. Further analysis revealed that the improvement was accompanied by a significant reduction in vertical wind shear during the nearshore enhancement of the typhoon. The QCed moisture flux divergence and vertical velocity in the upper layer increased significantly, which promoted the upward transport of momentum in the lower layers and contributed to the maintenance of the typhoon’s barotropic structure. Compared with the assimilation of raw data, the effective removal of outliers using the IRMCD algorithm significantly improved the simulation results for typhoons. Full article
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14 pages, 3730 KiB  
Article
Spatiotemporal Modeling of Carbon Fluxes over Complex Underlying Surfaces along the North Shore of Hangzhou Bay
by Kaidi Zhang, Min Zhao, Zhenyu Zhao, Xuchen Sheng, Yanyu Lu and Jun Gao
Atmosphere 2024, 15(6), 727; https://doi.org/10.3390/atmos15060727 (registering DOI) - 17 Jun 2024
Viewed by 167
Abstract
Urban areas contribute to over 80% of carbon dioxide emissions, and considerable efforts are being undertaken to characterize spatiotemporal variations of CO2 (carbon dioxide) at a city, regional, and national level, aiming at providing pipelines for carbon mission reduction. The complex underlying [...] Read more.
Urban areas contribute to over 80% of carbon dioxide emissions, and considerable efforts are being undertaken to characterize spatiotemporal variations of CO2 (carbon dioxide) at a city, regional, and national level, aiming at providing pipelines for carbon mission reduction. The complex underlying surface composition of urban areas makes process-based and physiology-based models inadequate for simulating carbon flux in this context. In this study, long short-term memory (LSTM), support vector machine (SVM), random forest (RF), and artificial neural network (ANN) were employed to develop and investigate their viability in estimating carbon flux at the ecosystem level. All the data used in our study were derived from the long-term chronosequence observations collected from the flux towers within urban complex underlying surface, along with meteorological reanalysis datasets. To assess the generalization ability of these models, the following statistical metrics were utilized: coefficient of determination (R2), root mean square error (RMSE), and mean absolute error (MAE). Our analysis revealed that the RF model performed the best in simulating carbon flux over long time series, with the highest R2 values reaching up to 0.852, and exhibiting the smallest RMSE and MAE values at 0.293 μmol·m−2·s−1 and 0.157 μmol·m−2·s−1. As a result, the RF model was chosen for simulating carbon flux at spatial scale and assessing the impact of urban impervious surfaces in the simulation. The results showed that the RF model performs well in simulating carbon flux at the spatial scale. The input of impervious surface area index can improve the performance of the RF model in simulating carbon flux, with R2 values of 84.46% (with the impervious surface area index in) and 83.74% (without the impervious surface area index in). Furthermore, the carbon flux in Fengxian District, Shanghai, exhibited significant spatial heterogeneity: the CO2 flux in the western part of Fengxian District was less than in the eastern part, and the CO2 flux gradually increased from the west to the east. In addition, we creatively introduced the diurnal impervious surface area index based on the Kljun model, and clarified the influence of impervious surface on the spatiotemporal simulation of CO2 flux over the complex urban underlying surface. Based on these findings, we conclude that the RF models can be effectively applied for estimating carbon flux on the complex underlying urban surface. The results of our study reduce the uncertainty in modeling carbon cycling in terrestrial ecosystems, and make the variety of models for the carbon cycling of terrestrial ecosystems more diverse. Full article
16 pages, 1499 KiB  
Article
Rainfall Estimation Model in Seasonal Zone and Non-Seasonal Zone Regions Using Weather Radar Imagery Based on a Gradient Boosting Algorithm
by Maulana Putra, Mohammad Syamsu Rosid and Djati Handoko
Atmosphere 2024, 15(6), 726; https://doi.org/10.3390/atmos15060726 - 17 Jun 2024
Viewed by 144
Abstract
Indonesia, a country located in the equatorial region with hilly and valley lands surrounded by vast oceans, has complex rainfall patterns that can generally be classified into three types: equatorial, monsoon, and local. Rainfall estimates have only been derived based on local data [...] Read more.
Indonesia, a country located in the equatorial region with hilly and valley lands surrounded by vast oceans, has complex rainfall patterns that can generally be classified into three types: equatorial, monsoon, and local. Rainfall estimates have only been derived based on local data and characteristics so far, and have not yet been developed based on universal data for all of Indonesia. This study aimed to develop a rainfall estimation model based on weather radar data throughout Indonesia using ensemble machine learning with the gradient boosting algorithm. The proposed rainfall estimation model is universal, can be applied to different rainfall pattern areas, and has a temporal resolution of 10 min. It is based on determining the root mean square error (RMSE) and R-squared (R2) values. Research was conducted in six areas with different rainfall patterns: Bandar Lampung and Banjarmasin with monsoon rain patterns, Pontianak and Deli Serdang with equatorial rain patterns, and the Gorontalo and Biak areas with local rain patterns. The analysis of the proposed model reveals that the best hyperparameters for the learning rate, maximum depth, and number of trees are 0.7, 3, and 50, respectively. The results demonstrate that the estimated rainfall in the six areas was very accurate, with RMSE < 2 mm/h and R2 > 0.7. Full article
(This article belongs to the Section Meteorology)
16 pages, 1877 KiB  
Article
Study on the Health Effect of Temperature on Cardiovascular and Cerebrovascular Diseases in Haikou City
by Mingjie Zhang, Shaowu Lin, Yajie Zhang and Jinghong Zhang
Atmosphere 2024, 15(6), 725; https://doi.org/10.3390/atmos15060725 - 17 Jun 2024
Viewed by 125
Abstract
Research on the impact of temperature in tropical regions on the risk of cardiovascular and cerebrovascular diseases was limited. The aim of the study was to investigate this topic using Haikou, a tropical city, as the research area. Outpatient data on cardiovascular and [...] Read more.
Research on the impact of temperature in tropical regions on the risk of cardiovascular and cerebrovascular diseases was limited. The aim of the study was to investigate this topic using Haikou, a tropical city, as the research area. Outpatient data on cardiovascular and cerebrovascular diseases (CVD and CeVD) from Hainan Provincial People’s Hospital during 2016–2018 (total of 77,820) and meteorological and air-quality data were used to establish a distributed-lag nonlinear model (DLNM) based on the nested generalized addition model (GAM) of meteorological elements. The results revealed the impact on the risk of CVD and CeVD was mainly due to the cold effect, which significantly lagged behind. The thermal effect had a strong impact on the onset of CVD and CeVD on the day of high temperature. Males were easily affected by low temperatures, while females were the opposite. The lag period of the working-age group affected by low temperatures was longer and greater than that of the elderly group. The high-temperature effect only had an impact on the working-age group. The lag effect of low temperatures on the risk of hypertension was the greatest. These results can provide technical support for carrying out meteorological forecasting, warning, and services for individuals with CVD and CeVD, suggesting attaching importance to health protection for special populations. Full article
(This article belongs to the Section Biometeorology)
26 pages, 7611 KiB  
Article
Numerical Analysis of the Effects of Different Window-Opening Strategies on the Indoor Pollutant Dispersion in Street-Facing Buildings
by Yongjia Wu, Yilian Ouyang, Tianhao Shi, Zhiyong Li and Tingzhen Ming
Atmosphere 2024, 15(6), 724; https://doi.org/10.3390/atmos15060724 - 17 Jun 2024
Viewed by 217
Abstract
The idling of automobiles at street intersections can lead to pollutant accumulation which impacts the health of residents in street-facing buildings. Previous research focused on pollutant dispersion within street canyons and did not consider the coupling of indoor and outdoor pollutants. This paper [...] Read more.
The idling of automobiles at street intersections can lead to pollutant accumulation which impacts the health of residents in street-facing buildings. Previous research focused on pollutant dispersion within street canyons and did not consider the coupling of indoor and outdoor pollutants. This paper employs the computational fluid dynamics (CFD) method to simulate the dispersion characteristics of vehicle emission pollutants in street canyons, primarily investigating the indoor and outdoor pollutant dispersion patterns under various window opening configurations (single-sided ventilation, corner ventilation, and different positions of the glass under corner ventilation). Additionally, the study considers the impacts of the aspect ratio and ambient wind speed. Studies have shown that corner ventilation is effective in reducing indoor pollutant levels. When the two window glass positions are far away from the center of the intersection, the average CO mass fraction in the single-sided ventilation room is reduced by 87.1%. The average indoor CO mass fraction on the leeward side decreases with the increasing wind speed and aspect ratio. At a wind speed of 8 m/s, the average indoor CO mass fraction on the leeward side decreases to 2.45 × 10−8. At an aspect ratio of 2, the indoor CO mass fraction on the leeward side decreases with increasing floors before stabilizing at approximately 4.77 × 10−9. This study suggests optimal window opening strategies to reduce indoor pollutant levels in street-facing buildings at street intersections, offering guidance to indoor residents on window ventilation practices. Full article
(This article belongs to the Special Issue Urban Air Quality Modelling)
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22 pages, 8987 KiB  
Article
Assessment of Wind over Complex Terrain Considering the Effects of Topography, Atmospheric Stability and Turbine Wakes
by Atsushi Yamaguchi, Alireza Tavana and Takeshi Ishihara
Atmosphere 2024, 15(6), 723; https://doi.org/10.3390/atmos15060723 - 17 Jun 2024
Viewed by 185
Abstract
This study proposes a microscale flow model to estimate mean wind speed, fluctuating wind speed and wind direction over complex terrain considering the effects of topography, atmospheric stability, and turbine wakes. Firstly, the effect of topography is considered using Computational Fluid Dynamics (CFD). [...] Read more.
This study proposes a microscale flow model to estimate mean wind speed, fluctuating wind speed and wind direction over complex terrain considering the effects of topography, atmospheric stability, and turbine wakes. Firstly, the effect of topography is considered using Computational Fluid Dynamics (CFD). Next, a mesoscale model is presented to account for the effect of atmospheric stability. The effect of turbine wakes on the mean and fluctuating wind speeds are then represented by an advanced wake model. The model is validated using the measurement data of a wind farm located in the North of Japan. The measured wind data by Lidar at a reference height are horizontally extrapolated to a nearby met mast hub height and validated by a cup anemometer. Moreover, a novel averaging method is proposed to calculate a directional equivalent Monin–Obukhov length scale to account for the effect of atmospheric stability. Finally, the measured wind data at the reference height are vertically extrapolated and validated at the lidar location. The predicted mean and fluctuating wind speeds show good agreement with the measurements. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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18 pages, 3339 KiB  
Article
Enhancing Tomato Production by Using Non-Conventional Water Resources within Integrated Sprinkler Irrigation Systems in Arid Regions
by Ramadan Eid Abdelraouf, Mamdouh A. A. Abdou, Ahmed Bakr, Ahmed E. Hamza, Younes M. Rashad, Ahmed M. Abd-ElGawad, Mohamed Hafez and R. Ragab
Atmosphere 2024, 15(6), 722; https://doi.org/10.3390/atmos15060722 - 16 Jun 2024
Viewed by 217
Abstract
This research evaluated the importance of establishing an integrated sprinkler irrigation design connected to fish farm ponds in order to achieve environmental and financial benefits. To achieve the aim of the study, two field experiments were conducted at a private farm in the [...] Read more.
This research evaluated the importance of establishing an integrated sprinkler irrigation design connected to fish farm ponds in order to achieve environmental and financial benefits. To achieve the aim of the study, two field experiments were conducted at a private farm in the Nubaria area of Beheira Governorate during the 2022 and 2023 seasons to quantify all the benefits from using fish water effluent (FWE) in irrigation. The obtained results indicated that the effluent could represent a good source of irrigation and bio-fertilization. The yield of tomato was higher when using FWE for irrigation compared with using groundwater for irrigation (IW). This was due to the additional amounts of dissolved bio-nitrogen along with other nutrients present in the FWE. The proportion of dissolved nitrogen added by using FWE was 22.3 kg nitrogen per hectare in 2022 and 24.6 kg nitrogen per hectare in 2023, in addition to some other major elements such as phosphorus and potassium, which are also among the main nutrients needed by crops. It has also been noticed that the fertility of the sandy soil increased with the use of FWE for irrigation. One of the most important results was the possibility of reducing the addition of nitrogen mineral fertilizers by 25%, thus saving on N fertilizers when growing tomato. In addition to the vitality of the FWE and its macro- and microelements, algae, microorganisms, and other organic materials, the use of this type of water as an alternative source for irrigation, along with the reduction in the amount of added mineral fertilizers, will reduce the degree of groundwater contamination with mineral fertilizers and increase the income of farmers. It was also observed that the air temperature decreased during the growing season when compared with the temperature of uncultivated surrounding areas. Full article
(This article belongs to the Special Issue Agriculture-Climate Interactions in Tropical Regions)
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21 pages, 6978 KiB  
Article
Associations between Indoor and Outdoor Size-Resolved Particulate Matter in Urban Beijing: Chemical Compositions, Sources, and Health Risks
by Shili Tian, Liming Wang, Qingyang Liu, Liang Luo, Chunyan Qian, Baocheng Wang and Yanju Liu
Atmosphere 2024, 15(6), 721; https://doi.org/10.3390/atmos15060721 - 16 Jun 2024
Viewed by 249
Abstract
Ventilation may lead to a deterioration in indoor air quality in urban environments located close to roads. Understanding the differences in the chemical compositions of size-resolved particulate matter (PM) in indoor air and outdoor air could aid in assessing the health impacts of [...] Read more.
Ventilation may lead to a deterioration in indoor air quality in urban environments located close to roads. Understanding the differences in the chemical compositions of size-resolved particulate matter (PM) in indoor air and outdoor air could aid in assessing the health impacts of air in these settings and establishing relevant regulation policies. In this study, indoor and outdoor size-resolved PM was collected from an office in Beijing in summer (between 5 and 25 July 2020) and winter (between 5 and 31 January 2021). Its chemical components, including sulfate, nitrate, ammonium, chlorine, organic matter (OM), elemental carbon (EC), crustal materials (CM), and heavy metals (HM), were analyzed. The mean levels of indoor and outdoor PM2.1 and PM9 were found to be much higher than those in the guidelines for PM2.5 and PM10 outlined by the National Ambient Air Quality Standard. Moreover, the levels of PM2.1 and PM2.1–9 mass were higher outdoors than they were indoors. The size distributions of mass concentrations were shown to be bimodal, peaking at 0.43–0.65 μm and 4.7–5.8 μm, respectively. The most abundant chemicals were OM, nitrate, and sulfate for PM2.1 and OM, CM, and nitrate for PM2.1–9. We found higher percentages of sulfate, nitrate, ammonium, EC, and HM in smaller-size fractions of PM. Additionally, positive matrix factorization showed that biomass burning, secondary inorganic aerosol, coal combustion, dust, traffic, and industrial pollution were the main sources of PM during the study period. The greatest non-carcinogenic and carcinogenic hazards were found at 0.43–0.65 μm in summer and 2.1–3.3 μm in winter. Our results indicate that size-resolved PM of ambient origin may infiltrate buildings near roads to varying degrees, resulting in negative health effects. Full article
(This article belongs to the Special Issue New Insights into Exposure and Health Impacts of Air Pollution)
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21 pages, 3129 KiB  
Article
Study on Spatial-Temporal Evolution, Decoupling Effect and Influencing Factors of Tourism Transportation Carbon Emissions: Taking North China as an Example
by Dongni Feng, Cheng Li and Yangzhou Li
Atmosphere 2024, 15(6), 720; https://doi.org/10.3390/atmos15060720 - 15 Jun 2024
Viewed by 154
Abstract
As global warming intensifies, reducing carbon emissions has become a global common mission. Tourism transportation is one of the important sources of carbon emissions, and reducing its carbon emissions is a key part of achieving China’s carbon reduction goals. Based on the panel [...] Read more.
As global warming intensifies, reducing carbon emissions has become a global common mission. Tourism transportation is one of the important sources of carbon emissions, and reducing its carbon emissions is a key part of achieving China’s carbon reduction goals. Based on the panel data of various provinces and cities in North China from 2000 to 2022, this paper calculates the carbon emissions of tourism transportation by using the carbon emission coefficients of different transportation modes in different segments. Moreover, the temporal and spatial evolution of the tourism economy is systematically analyzed. The Tapio decoupling model and LMDI addition decomposition model are used to analyze the relationship between carbon emissions and tourism economic growth and the effects of 11 influencing factors on carbon emissions. The results show that: ① The carbon emission of tourism transportation in North China has experienced four stages: a steady growth period, a transitional adaptation period, a stable equilibrium period, and a drastic decline period. The overall carbon emission level of tourism transportation is as follows: Hebei Province > Shanxi Province > Inner Mongolia Autonomous Region > Beijing City > Tianjin City. ② The decoupling coefficient between tourism traffic carbon emissions and economic development fluctuates but mainly shows a weak decoupling state. ③ In terms of influencing factors, passenger size and passenger density have the greatest impact on the carbon emissions of tourism transportation. Full article
(This article belongs to the Special Issue Urban Carbon Emissions)
13 pages, 1027 KiB  
Article
Seasonal Patterns and Allergenicity of Casuarina Pollen in Sydney, Australia: Insights from 10 Years of Monitoring and Skin Testing
by Edwin R. Lampugnani, Jeremy D. Silver, Pamela Burton, Usha Nattala and Constance H. Katelaris
Atmosphere 2024, 15(6), 719; https://doi.org/10.3390/atmos15060719 - 15 Jun 2024
Viewed by 161
Abstract
Casuarina (Australian pine, She-oak) is native to Australia and South East Asia and is known for its abundant wind-borne pollen. Despite not being considered a major aeroallergen, some patients report respiratory symptoms upon exposure, with positive skin prick tests (SPT) to Casuarina pollen [...] Read more.
Casuarina (Australian pine, She-oak) is native to Australia and South East Asia and is known for its abundant wind-borne pollen. Despite not being considered a major aeroallergen, some patients report respiratory symptoms upon exposure, with positive skin prick tests (SPT) to Casuarina pollen extract. This study investigates Casuarina pollen dispersal patterns in Sydney, Australia, over a 10-year period, from 2008 to 2018, revealing a bimodal distribution of pollen from September to October (southern hemisphere spring) and February to March (mid-late summer). Analysis of historical SPT data shows 20% of individuals with respiratory allergies reacting positively to Casuarina pollen extract, with almost 90% of these also reacting to grass pollen, suggesting potential cross-reactivity. Notably, there are no exclusive reactions to Casuarina pollen. Understanding the prolonged pollen season underscores the importance of year-round monitoring for accurate characterization. Currently lacking are commercially available skin test extracts or specific IgE assays for Casuarina sensitization, necessitating challenge studies to confirm clinical symptoms directly attributable to Casuarina pollen. By elucidating the seasonal dynamics and meteorological drivers of Casuarina pollen dispersion, alongside the potential allergenicity suggested by skin prick tests, this study paves the way for improved management of Casuarina-related allergies and highlights the critical need for further research on native Australian plant allergens. Full article
(This article belongs to the Special Issue Real-Time Detection, Discrimination, and Forecasting of Bioaerosols)
17 pages, 3121 KiB  
Article
Near-Surface Thermodynamic Influences on Evaporation Duct Shape
by Sarah E. Wessinger, Daniel P. Greenway, Tracy Haack and Erin E. Hackett
Atmosphere 2024, 15(6), 718; https://doi.org/10.3390/atmos15060718 - 15 Jun 2024
Viewed by 184
Abstract
This study utilizes in situ measurements and numerical weather prediction forecasts curated during the Coupled Air–Sea Processes Electromagnetic Ducting Research (CASPER) east field campaign to assess how thermodynamic properties in the marine atmospheric surface layer influence evaporation duct shape independent of duct height. [...] Read more.
This study utilizes in situ measurements and numerical weather prediction forecasts curated during the Coupled Air–Sea Processes Electromagnetic Ducting Research (CASPER) east field campaign to assess how thermodynamic properties in the marine atmospheric surface layer influence evaporation duct shape independent of duct height. More specifically, we investigate evaporation duct shape through a duct shape parameter, a parameter known to affect the propagation of X-band radar signals and is directly related to the curvature of the duct. Relationships between this duct shape parameter and air sea temperature difference (ASTD) reveal that during unstable periods (ASTD < 0), the duct shape parameter is generally larger than in near-neutral or stable atmospheric conditions, indicating tighter curvature of the M-profile. Furthermore, for any specific duct height, a strong linear relationship between the near-surface-specific humidity gradient and the duct shape parameter is found, suggesting that it is primarily driven by near-surface humidity gradients. The results demonstrate that an a priori estimate of duct shape, for a given duct height, is possible if the near-surface humidity gradient is known. Full article
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18 pages, 3802 KiB  
Article
Influence of Natural Tropical Oscillations on Ozone Content and Meridional Circulation in the Boreal Winter Stratosphere
by Tatiana Ermakova, Andrey Koval, Kseniia Didenko, Olga Aniskina and Arina Okulicheva
Atmosphere 2024, 15(6), 717; https://doi.org/10.3390/atmos15060717 - 15 Jun 2024
Viewed by 188
Abstract
The dependence of ozone content in the polar stratosphere upon different phases of the quasi-biennial oscillation (QBO) of the zonal wind and the El Niño–Southern Oscillation (ENSO) during winter was studied. The monthly (from November to January) mean residual meridional circulation (RMC) was [...] Read more.
The dependence of ozone content in the polar stratosphere upon different phases of the quasi-biennial oscillation (QBO) of the zonal wind and the El Niño–Southern Oscillation (ENSO) during winter was studied. The monthly (from November to January) mean residual meridional circulation (RMC) was calculated for four different combinations of the main phases of ENSO and QBO using MERRA2 reanalysis data. It has been demonstrated that the QBO phase manifests itself in different vertical distributions of ozone in the equatorial stratosphere, as well as in strengthening/weakening of the secondary meridional circulation in the tropics. The enhancement of the RMC from the tropical to the polar stratosphere is stronger at altitudes where ozone is higher in the tropics under El Niño conditions. The RMC modification and intensification are observed from ozone-depleted areas under La Niña conditions. A “cumulative” effect is observed by February under La Niña conditions and the easterly QBO, which is expressed in the lowest ozone content in the polar stratosphere. The numerical experiments carried out using the Middle and Upper Atmosphere Model (MUAM) confirmed tendencies in changes in the meridional transport detected from the reanalysis data for different combinations of QBO and ENSO. Full article
(This article belongs to the Special Issue Ozone Evolution in the Past and Future (2nd Edition))
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18 pages, 2150 KiB  
Article
Characterization of Spatial and Temporal Variations in Air Pollutants and Identification of Health Risks in Xi’an, a Heavily Polluted City in China
by Li Han and Yongjie Qi
Atmosphere 2024, 15(6), 716; https://doi.org/10.3390/atmos15060716 - 14 Jun 2024
Viewed by 127
Abstract
The study of the temporal and spatial characteristics of air pollutants in heavily polluted cities is extremely important for analyzing the causes of pollution and achieving a viable means of control. Such characteristics in the case of Xi’an, a typical heavily polluted city [...] Read more.
The study of the temporal and spatial characteristics of air pollutants in heavily polluted cities is extremely important for analyzing the causes of pollution and achieving a viable means of control. Such characteristics in the case of Xi’an, a typical heavily polluted city in Fenwei Plain, China, have remained unclear due to limitations in data accuracy and research methods. The monthly, daily, and hourly patterns of O3 and particulate matter (PM2.5 and PM10) are analyzed in this study using on-site data provided by an urban air quality monitoring network. The analysis of variance (ANOVA) method was used to compare differences in pollutant concentrations during different seasons and time periods. The spatial distributions of O3, PM2.5, and PM10 at different time points following interpolation of the air quality monitoring sites have been analyzed. The results show that the O3 concentration from 12 p.m. to 3 p.m. was significantly higher than that in the morning and evening, and the concentrations of PM2.5 and PM10 from 7 p.m. to 10 p.m. were significantly higher than those in the morning and afternoon. The number of qualified days for PM2.5 was less than 30 and unqualified days for O3 was more than 100 in 2019. There is a potential risk of exposure to pollution with associated health risks. Even on the same day, the spatial pollutant distributions at different time points can differ significantly. This study provides a scientific basis for reducing O3 and particulate matter exposure. Outdoor activities in the morning in summer are more beneficial to reduce O3 exposure, and outdoor activities should be curtailed in the evening in winter to reduce particulate exposure. This study provides a scientific basis for the government to formulate public health policies to reduce pollution exposure from outdoor activities. Full article
(This article belongs to the Section Air Quality and Human Health)
13 pages, 2997 KiB  
Article
Evaluating Real Driving Emissions of Compressed Natural Gas Taxis in Chongqing, China—A Typical Mountain Cities
by Wei Hu, Linfeng Duan, Min Tang, Rui Yuan, Gaiyan Lv, Pingjiang Lv, Zhenliang Li, Ling Li, Hualong Xu, Jiajia Ding and Dan Zhang
Atmosphere 2024, 15(6), 715; https://doi.org/10.3390/atmos15060715 - 14 Jun 2024
Viewed by 172
Abstract
Compressed natural gas (CNG) taxis represent the most ubiquitous and dynamically active passenger vehicles in urban settings. The pollutant emission characteristics of in-use CNG taxis driving on a typical mountain city before and after three-way catalyst (TWC) replacement was examined using a modular [...] Read more.
Compressed natural gas (CNG) taxis represent the most ubiquitous and dynamically active passenger vehicles in urban settings. The pollutant emission characteristics of in-use CNG taxis driving on a typical mountain city before and after three-way catalyst (TWC) replacement was examined using a modular on-board portable emissions measurement system (PEMS), the OBS-ONE developed by Horiba. The results showed that the exhaust NO of CNG taxis equipped with deactivation TWC exceeded the emission limits, even higher than gasoline vehicles. The high emission rate of CNG taxis is mainly concentrated on road slopes between a 2% and 6% gradient and a deceleration rate in the interval of [0.5, 4], respectively, which results in higher emissions from CNG taxis traveling in the mountain city of Chongqing than other cities and vehicles. Moreover, the pollutant emission rates of the in-use CNG taxis were highly correlated with the velocity and the vehicle specific power (VSP). After a new TWC replacement, the emission factors of carbon monoxide (CO), total hydrocarbons (THC), nitrogen oxides (NOx), and particle number (PN) decreased by 85.21–89.11%, 68.71–85.49%, 60.91–81.11%, and 62.26–68.39%, respectively. Our results will provide guidance for urban environments to carry out the comprehensive management of in-use vehicles and emphasize the importance of TWC replacement for CNG taxis. Full article
(This article belongs to the Special Issue Traffic Related Emission (2nd Edition))
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15 pages, 1580 KiB  
Article
Three-Dimensional Computerized Ionospheric Tomography over Maritime Areas Based on Simulated Slant Total Electron Content Along Small-Satellite Constellation–Automatic Identification System Signal Rays
by Haiying Li, Bin Xu, Cheng Wang, Haisheng Zhao, Ruimin Jin, Hongbo Zhang and Feifei Wang
Atmosphere 2024, 15(6), 714; https://doi.org/10.3390/atmos15060714 - 14 Jun 2024
Viewed by 221
Abstract
Ionospheres over sea areas have an inevitable impact on maritime–satellite communications; however, due to geographic constraints, ionospheric observation and analysis over sea areas are far from adequate. In our paper, slant total electron content (STEC) along small-satellite constellation–automatic identification system (AIS) signal rays [...] Read more.
Ionospheres over sea areas have an inevitable impact on maritime–satellite communications; however, due to geographic constraints, ionospheric observation and analysis over sea areas are far from adequate. In our paper, slant total electron content (STEC) along small-satellite constellation–automatic identification system (AIS) signal rays is used for computerized ionospheric tomography (CIT) over sea areas, and small-satellite constellations can provide more effective signal rays than a single satellite. An adjustment factor δ is introduced to optimize the initial electron density for the multiplicative algebraic reconstruction technique (MART). The CIT results reconstructed by a traditional MART and our new method at 00:00 and 06:00, 15 March 2022, are compared, and our new method produces about a 15% and over 40% improvement in average deviation (AD) and root-mean-square error (RMSE). The results show that the bigger the difference between δ and 1, the better improvement will be in the 3D CIT process. The initial electron density is well selected during CIT when δ is approximate to 1, which is the case at 12:00, and the reconstructed 3D electron density, applying the initial ne and the adjusted initial ne, are both close to the true electron density. The small-satellite constellation–AIS signals are valuable resources for electron density reconstruction in sea areas. Full article
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13 pages, 3037 KiB  
Article
Rainy Season Migration across the Northeast Coast of Brazil Related to Sea Surface Temperature Patterns
by Marcos Paulo Santos Pereira, Fabiana Couto, Vanúcia Schumacher, Fabrício Daniel dos Santos Silva, Helber Barros Gomes, Djane Fonseca da Silva, Heliofábio Barros Gomes, Rafaela Lisboa Costa, Flávio B. Justino and Dirceu Luís Herdies
Atmosphere 2024, 15(6), 713; https://doi.org/10.3390/atmos15060713 - 14 Jun 2024
Viewed by 253
Abstract
Accurate regional seasonal forecasts of the rainy season are essential for the implementation of effective socioeconomic activities and policy. However, current characteristics of the period of occurrence of the rainy season in the Eastern Northeast Brazil (ENEB) region demonstrated that maximum precipitation varies [...] Read more.
Accurate regional seasonal forecasts of the rainy season are essential for the implementation of effective socioeconomic activities and policy. However, current characteristics of the period of occurrence of the rainy season in the Eastern Northeast Brazil (ENEB) region demonstrated that maximum precipitation varies substantially depending on the period analyzed. From 1972 to 2002, the rainy season occurred during the June–July–August (JJA) quarter, while from 1981 to 2011, it occurred in the April–May–June (AMJ) quarter. To access how these differences may be due to different patterns of sea surface temperature (SST), using observed precipitation and SST data from NOAA for the period from 1982 to 2018, this study identified the spatial patterns of inter-annual changes in Pacific and Atlantic SST related to the occurrence of the ENEB rainy seasons. We focus on the statistical method of symmetric mean absolute percentage error (sMAPE) for forecasting these periods based on SST information. Our results revealed five different quarterly periods (FMA, MAM, AMJ, MJJ, JJA) to the rainy season, in which MJJ is more prevalent. The sMAPE values of the SST patterns are inversely proportional to precipitation in the ENEB. Hence, it may be concluded that our climate analysis demonstrates that seasonal SST patterns can be used for forecasting the period of the rainy season. Full article
(This article belongs to the Section Biosphere/Hydrosphere/Land–Atmosphere Interactions)
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25 pages, 8774 KiB  
Article
Analysis of Atmospheric Aerosol Changes in the Qinghai-Tibetan Plateau Region during 2009–2019 Using a New Fusion Algorithm
by Zhijian Zhao and Hideyuki Tonooka
Atmosphere 2024, 15(6), 712; https://doi.org/10.3390/atmos15060712 - 14 Jun 2024
Viewed by 230
Abstract
The Qinghai-Tibetan Plateau (QTP) is the largest permafrost-covered area in the world, and it is critical to understand accurately and dynamically the cyclical changes in atmospheric aerosols in the region. However, due to the scarcity of researchers in this field and the complexity [...] Read more.
The Qinghai-Tibetan Plateau (QTP) is the largest permafrost-covered area in the world, and it is critical to understand accurately and dynamically the cyclical changes in atmospheric aerosols in the region. However, due to the scarcity of researchers in this field and the complexity of analyzing the spatial and temporal dynamics of aerosols, there is a gap in research in this area, which we hope to fill. In this study, we constructed a new fusion algorithm based on the V5.2 algorithm and the second-generation deep blue algorithm through the introduced weight factor of light and dark image elements. We used the algorithm to analyze the spatial and temporal changes in aerosols from 2009–2019. Seasonal changes and the spatial distribution of aerosol optical depth (AOD) were analyzed in comparison with the trend of weight factor, which proved the stability of the fusion algorithm. Spatially, the AOD values in the northeastern bare lands and southeastern woodland decreased most significantly, and combined with the seasonal pattern of change, the AOD values in this region were higher in the spring and fall. In these 11 years, the AOD values in the spring and fall decreased the most, and the aerosol in which the AOD decreases occurred should be the cooling-type sulfate aerosol. In order to verify the accuracy of the algorithm, we compared the AOD values obtained by the algorithm at different time intervals with the measured AOD values of several AERONET stations, in which the MAE, RMSE, and R between the AOD values obtained by the algorithm and the measured averages of the 12 nearest AERONET stations in the QTP area were 0.309, 0.094, and 0.910, respectively. In addition, this study also compares the AOD results obtained from the fusion algorithm when dynamically weighted and mean-weighted, and the results show that the error value is smaller in the dynamic weighting approach in this study. Full article
(This article belongs to the Special Issue Climate Dynamics and Variability Over the Tibetan Plateau)
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27 pages, 2091 KiB  
Article
Zonons Are Solitons Produced by Rossby Wave Ringing
by Nimrod Cohen, Boris Galperin and Semion Sukoriansky
Atmosphere 2024, 15(6), 711; https://doi.org/10.3390/atmos15060711 - 14 Jun 2024
Viewed by 235
Abstract
Along with the familiar Rossby–Haurwitz waves, two-dimensional flows on the surface of a rotating sphere in the regime of zonostrophic turbulence harbor another class of waves known as zonons. Zonons are wave packets produced by energetic large-scale Rossby–Haurwitz wave modes ‘enslaving’ other wave [...] Read more.
Along with the familiar Rossby–Haurwitz waves, two-dimensional flows on the surface of a rotating sphere in the regime of zonostrophic turbulence harbor another class of waves known as zonons. Zonons are wave packets produced by energetic large-scale Rossby–Haurwitz wave modes ‘enslaving’ other wave modes. They propagate westward with the phase speed of the enslaving modes. Zonons can be visualized as enslaving modes’ ‘ringing’ in the enslaved ones with the frequencies of the former, the property that renders zonons non-dispersive. Zonons reside in high-shear regions confined between the opposing zonal jets yet they are mainly attached to westward jets and sustained by the ensuing barotropic instability. They exchange energy with the mean flow while preserving their identity in a fully turbulent environment, a feature characteristic of solitary waves. The goal of this study is to deepen our understanding of zonons’ physics using direct numerical simulations, a weakly non-linear theory, and asymptotic analysis, and ascertain that zonons are indeed isomorphic to solitary waves in the Korteweg–de Vries framework. Having this isomorphism established, the analysis is extended to eddies detected in the atmospheres of Jupiter and Saturn based upon the observed mean zonal velocity profiles and earlier findings that circulations on both planets obey the regime of zonostrophic macroturbulence. Not only the analysis confirms that many eddies and eddy trains on both giant planets indeed possess properties of zonons, but the theory also correctly predicts latitudinal bands that confine zonal trajectories of the eddies. Full article
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18 pages, 2502 KiB  
Article
Impact of Integrating Flameless Combustion Technology and Sludge–Fly Ash Recirculation on PCDE Emissions in Hazardous Waste Thermal Treatment Systems
by Sheng-Lun Lin, Lu-Lu Duan, Jhong-Lin Wu, Chien-Er Huang and Meng-Jie Song
Atmosphere 2024, 15(6), 710; https://doi.org/10.3390/atmos15060710 - 14 Jun 2024
Viewed by 267
Abstract
Polychlorinated diphenyl ethers (PCDEs), persistent environmental pollutants, are found in flue gas from incinerators. While air pollution control systems (APCSs) capture pollutants, the resulting sludge/fly ash (SFA) requires further treatment due to residual PCDEs and other harmful substances. This study investigated a hazardous [...] Read more.
Polychlorinated diphenyl ethers (PCDEs), persistent environmental pollutants, are found in flue gas from incinerators. While air pollution control systems (APCSs) capture pollutants, the resulting sludge/fly ash (SFA) requires further treatment due to residual PCDEs and other harmful substances. This study investigated a hazardous waste thermal treatment system (HAWTTS) utilizing flameless combustion technology alongside a multistage APCS (scrubbers, cyclone demisters, bag houses). SFA from the APCS was recirculated for secondary combustion. PCDE levels were measured before and after each unit within the HAWTTS. The HAWTTS achieved a remarkable overall PCDE removal efficiency of 99%. However, the incinerator alone was less effective for low-chlorine PCDEs. Scrubbers and bag houses exhibited lower removal efficiencies (17.8% and 30.9%, respectively) due to the memory effect. Conversely, the cyclone demister achieved a high removal rate (98.2%). Following complete APCS treatment, PCDE emissions were significantly reduced to 1.02 ng/Nm3. While SFA still contained some PCDEs, the flameless combustion’s uniform temperature distribution enhanced combustion efficiency, minimizing overall PCDE emissions. This system demonstrates significant potential for mitigating PCDE pollution from incinerators. Further research could focus on optimizing treatment processes to address residual PCDEs in SFA. Full article
(This article belongs to the Special Issue Toxicity of Persistent Organic Pollutants and Microplastics in Air)
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30 pages, 32244 KiB  
Article
Microclimate Zoning Based on Double Clustering Method for Humid Climates with Altitudinal Gradient Variations: A Case Study of Colombia
by Cristian Mejía-Parada, Viviana Mora-Ruiz, Jonathan Soto-Paz, Brayan A. Parra-Orobio and Shady Attia
Atmosphere 2024, 15(6), 709; https://doi.org/10.3390/atmos15060709 (registering DOI) - 14 Jun 2024
Viewed by 342
Abstract
Climatic classification is essential for evaluating climate parameters that allow sustainable urban planning and resource management in countries with difficult access to meteorological information. Clustering methods are on trend to identify climate zoning; however, for microclimate, it is necessary to apply a double [...] Read more.
Climatic classification is essential for evaluating climate parameters that allow sustainable urban planning and resource management in countries with difficult access to meteorological information. Clustering methods are on trend to identify climate zoning; however, for microclimate, it is necessary to apply a double clustering technique to reduce the variability from former clusters. This research raised a climate classification of an emerging country, Colombia, using climatological models based on freely available satellite image data. A double clustering approach was applied, including climatological, geographic, and topographic patterns. The research was divided into four stages, covering the collection and selection of climatic and geographic data, and multivariate statistical analysis including principal components analysis (PCA) and agglomerative hierarchical clustering (HAC). The meteorological data were from reliable sources from the Center for Hydrometeorology and Remote Sensing (CHRS) and the National Renewable Energy Laboratory (NREL). The results showed that a total of 17 microclimates distributed across the country were identified, each characterized by a different threshold of the climatic and geographic factors evaluated. This subdivision provided a detailed understanding of local climatic conditions, especially in the mountain chains of the Andes. Full article
(This article belongs to the Section Climatology)
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23 pages, 7533 KiB  
Article
Study on Wind Profile Characteristics Using Cluster Analysis
by Yanru Wang, Shengbao Tian, Bin Fu, Maoyu Zhang, Xu Wang, Shuqin Zheng, Chuanxiong Zhang and Lei Zhou
Atmosphere 2024, 15(6), 708; https://doi.org/10.3390/atmos15060708 - 13 Jun 2024
Viewed by 181
Abstract
The accurate characterization of typhoon wind profile properties is of great importance in the field of wind engineering and wind design of high-rise structures. In this paper, the average typhoon wind profile characteristics are investigated using the 930 m height measurement data of [...] Read more.
The accurate characterization of typhoon wind profile properties is of great importance in the field of wind engineering and wind design of high-rise structures. In this paper, the average typhoon wind profile characteristics are investigated using the 930 m height measurement data of Typhoon Lekima 2019 obtained from the observations of the mobile acoustic profiling radar deployed in the coastal area. Specifically, this paper adopts a cohesive hierarchical cluster analysis method to classify the mean wind profiles of Super Typhoon Lekima 2019, and the optimal number of clusters is obtained as two classes by the profile coefficient with the sum of squares of clustering errors, the Calinski–Harabasz index, and the Davies–Bouldin index, and the two classes of typical wind profiles are named as cluster 1 type and cluster 2 type. The model fitting analysis of the two types of typical wind profiles was carried out in the height range of 0~300 m after classification, and the effects of fitting the cluster 1-type mean wind profiles with the Vickery model and the Snaiki and Wu model and the cluster 2-type mean wind profiles with the Power-law model, the Log-law model, and the Deaves–Harris and Gryning models were discussed. The results show that the cohesive hierarchical cluster analysis method used in this paper can effectively categorize the mean typhoon profiles. In addition, this paper has some reference significance for future research on the characteristics of measured typhoon wind profiles and engineering applications such as the wind-resistant design of high-rise structures. Full article
(This article belongs to the Special Issue Advances in Wind and Wind Power Forecasting and Diagnostics)
24 pages, 4579 KiB  
Article
Investigating the Role of Wave Process in the Evaporation Duct Simulation by Using an Ocean–Atmosphere–Wave Coupled Model
by Zhigang Shan, Niaojun Sun, Wei Wang, Jing Zou, Xiaolei Liu, Hong Zhang, Zhijin Qiu, Bo Wang, Jinyue Wang and Shuai Yang
Atmosphere 2024, 15(6), 707; https://doi.org/10.3390/atmos15060707 - 13 Jun 2024
Viewed by 206
Abstract
In this study, a diagnostic model for evaporation ducts was established based on the Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) and the Naval Postgraduate School (NPS) models. Utilizing this model, four sensitivity tests were conducted over the South China Sea from 21 September to 5 [...] Read more.
In this study, a diagnostic model for evaporation ducts was established based on the Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) and the Naval Postgraduate School (NPS) models. Utilizing this model, four sensitivity tests were conducted over the South China Sea from 21 September to 5 October 2008, when four tropical cyclones affected the study domain. These tests were designed with different roughness schemes to investigate the impact mechanisms of wave processes on evaporation duct simulation under extreme weather conditions. The results indicated that wave processes primarily influenced the evaporation duct heights by altering sea surface roughness and dynamical factors. The indirect impacts of waves without dynamical factors were rather weak. Generally, a decrease in local roughness led to increased wind speed, decreased humidity, and a reduced air–sea temperature difference, resulting in the formation of evaporation ducts at higher altitudes. However, this affecting mechanism between roughness and evaporation ducts was also greatly influenced by changes in regional circulation. In the eastern open sea areas of the South China Sea, changes in evaporative ducts were more closely aligned with local impact mechanisms, whereas the changes in the central and western areas demonstrated greater complexity and fewer local impacts due to variations in regional circulation. Full article
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16 pages, 4079 KiB  
Article
Machine Learning Approach for the Estimation of Henry’s Law Constant Based on Molecular Descriptors
by Atta Ullah, Muhammad Shaheryar and Ho-Jin Lim
Atmosphere 2024, 15(6), 706; https://doi.org/10.3390/atmos15060706 - 13 Jun 2024
Viewed by 239
Abstract
In atmospheric chemistry, the Henry’s law constant (HLC) is crucial for understanding the distribution of organic compounds across gas, particle, and aqueous phases. Quantitative structure–property relationship (QSPR) models described in scientific research are generally tailored to specific groups or categories of substances and [...] Read more.
In atmospheric chemistry, the Henry’s law constant (HLC) is crucial for understanding the distribution of organic compounds across gas, particle, and aqueous phases. Quantitative structure–property relationship (QSPR) models described in scientific research are generally tailored to specific groups or categories of substances and are often developed using a limited set of experimental data. This study developed a machine learning model using an extensive dataset of experimental HLCs for approximately 1100 organic compounds. Molecular descriptors calculated using alvaDesc software (v 2.0) were used to train the models. A hybrid approach was adopted for feature selection, ensuring alignment with the domain knowledge. Based on the root mean squared error (RMSE) of the training and test data after cross-validation, Gradient Boosting (GB) was selected as a model for predicting HLC. The hyperparameters of the selected model were optimized using the automated hyperparameter optimization framework Optuna. The impact of features on the target variable was assessed using the SHapley Additive exPlanations (SHAP). The optimized model demonstrated strong performance across the training, evaluation, and test datasets, achieving coefficients of determination (R2) of 0.96, 0.78, and 0.74, respectively. The developed model was used to estimate the HLC of compounds associated with carbon capture and storage (CCS) emissions and secondary organic aerosols. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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12 pages, 6897 KiB  
Article
Comprehensive Detection of Particle Radiation Effects on the Orbital Platform of the Upper Stage of the Chinese CZ-4C Carrier Rocket
by Guohong Shen, Zheng Chang, Huanxin Zhang, Chunqin Wang, Ying Sun, Zida Quan, Xianguo Zhang and Yueqiang Sun
Atmosphere 2024, 15(6), 705; https://doi.org/10.3390/atmos15060705 - 12 Jun 2024
Viewed by 334
Abstract
Based on the characteristics of space particle radiation in the Sun-synchronous orbit (SSO), a space particle radiation effect comprehensive measuring instrument (SPRECMI) was installed on the orbital platform of the upper stage of the Chinese CZ-4C carrier rocket, which can acquire the high-energy [...] Read more.
Based on the characteristics of space particle radiation in the Sun-synchronous orbit (SSO), a space particle radiation effect comprehensive measuring instrument (SPRECMI) was installed on the orbital platform of the upper stage of the Chinese CZ-4C carrier rocket, which can acquire the high-energy proton energy spectra, linear energy transfer (LET) spectra of particles, and radiation dose rate. The particle radiation detection data were obtained at 1000 km altitude for the first time, which can be used mainly for scientific research of the space environment, in-orbit fault analysis, and the operational control management of spacecraft, and can also serve as reference data for component validation tests. After SPRECMI’s development, accelerator calibration and simulations were conducted, and the results demonstrated that all the measured indicators, including the high-energy proton spectra (energy range: 21.8–275.0 MeV, precision: <3.3%), total radiation dose (dose range: 0–1.04 × 106 rad, sensitivity: 6.2 µrad/h), and the LET spectra (range: 0.001–37.20 MeV/(mg/cm2), >37.2 MeV/(mg/cm2)), met the relevant requirements. Furthermore, the in-orbit flight test revealed that the detection results of the load components were consistent with the physical characteristics of the particle radiation environment of the spacecraft’s orbit. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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17 pages, 1021 KiB  
Article
Analysis of Particle Number Emissions in a Retrofitted Heavy-Duty Spark Ignition Engine Powered by LPG
by Vicente Bermúdez, Pedro Piqueras, Enrique José Sanchis and Brayan Conde
Atmosphere 2024, 15(6), 704; https://doi.org/10.3390/atmos15060704 - 12 Jun 2024
Viewed by 165
Abstract
This study aims to examine the particle number (PN) emissions of a retrofitted heavy-duty spark ignition (HD-SI) engine powered by liquefied petroleum gas (LPG) under both steady-state and transient conditions. The engine was tested under seven steady-state operating points to investigate the PN [...] Read more.
This study aims to examine the particle number (PN) emissions of a retrofitted heavy-duty spark ignition (HD-SI) engine powered by liquefied petroleum gas (LPG) under both steady-state and transient conditions. The engine was tested under seven steady-state operating points to investigate the PN behavior and particle size distribution (PSD) upstream and downstream of the three-way catalyst (TWC). This analysis intends to assess the impact of including particles with diameters ranging from 10 nm to 23 nm on the total particle count, a consideration for future regulations. The study employed the World Harmonized Transient Cycle (WHTC) for transient conditions to encompass the same engine working region as is used in the steady-state analysis. A Dekati FPS-4000 diluted the exhaust sample to measure the PSD and PN for particle diameters between 5.6 nm and 560 nm using the TSI-Engine Exhaust Particle Sizer (EEPS) 3090. The findings indicate that PN levels tend to increase downstream of the TWC under steady-state conditions in operating points with low exhaust gas temperatures and flows (equal to or less than 500 °C and 120 kg/h). Furthermore, the inclusion of particles with diameters between 10 nm and 23 nm leads to an increase in PN emissions by 17.70% to 40.84% under steady conditions and by an average of 40.06% under transient conditions, compared to measurements that only consider particles larger than 23 nm. Notably, in transient conditions, most PN emissions occur during the final 600 s of the cycle, linked to the most intense phase of the WHTC. Full article
(This article belongs to the Special Issue Traffic Related Emission (2nd Edition))
16 pages, 5865 KiB  
Article
Application of Statistical Learning Algorithms in Thermal Stress Assessment in Comparison with the Expert Judgment Inherent to the Universal Thermal Climate Index (UTCI)
by Peter Bröde, Dusan Fiala and Bernhard Kampmann
Atmosphere 2024, 15(6), 703; https://doi.org/10.3390/atmos15060703 - 12 Jun 2024
Viewed by 155
Abstract
This study concerns the application of statistical learning (SL) in thermal stress assessment compared to the results accomplished by an international expert group when developing the Universal Thermal Climate Index (UTCI). The performance of diverse SL algorithms in predicting UTCI equivalent temperatures and [...] Read more.
This study concerns the application of statistical learning (SL) in thermal stress assessment compared to the results accomplished by an international expert group when developing the Universal Thermal Climate Index (UTCI). The performance of diverse SL algorithms in predicting UTCI equivalent temperatures and in thermal stress assessment was assessed by root mean squared errors (RMSE) and Cohen’s kappa. A total of 48 predictors formed by 12 variables at four consecutive 30 min intervals were obtained as the output of an advanced human thermoregulation model, calculated for 105,642 conditions from extreme cold to extreme heat. Random forests and k-nearest neighbors closely predicted UTCI equivalent temperatures with an RMSE about 3 °C. However, clustering applied after dimension reduction (principal component analysis and t-distributed stochastic neighbor embedding) was inadequate for thermal stress assessment, showing low to fair agreement with the UTCI stress categories (Cohen’s kappa <0.4). The findings of this study will inform the purposeful application of SL in thermal stress assessment, where they will support the biometeorological expert. Full article
(This article belongs to the Special Issue Indoor Thermal Comfort Research)
23 pages, 83064 KiB  
Article
Study of the Atmospheric Transport of Sea-Spray Aerosols in a Coastal Zone Using a High-Resolution Model
by Alix Limoges, Jacques Piazzola, Christophe Yohia, Quentin Rodier, William Bruch, Elisa Canepa and Pierre Sagaut
Atmosphere 2024, 15(6), 702; https://doi.org/10.3390/atmos15060702 - 12 Jun 2024
Viewed by 214
Abstract
Fine-scale models for the transport of marine aerosols are of great interest for the study of micro-climates and air quality in areas of complex topography, such as in urbanized coastal areas. To this end, the MIO laboratory implemented the Meso-NH model in its [...] Read more.
Fine-scale models for the transport of marine aerosols are of great interest for the study of micro-climates and air quality in areas of complex topography, such as in urbanized coastal areas. To this end, the MIO laboratory implemented the Meso-NH model in its LES version over the northwest Mediterranean coastal zone using a recent sea-spray source function. Simulated meteorological parameters and aerosol concentrations are compared to experimental data acquired in the Mediterranean coastal zone in spring 2008 on board the R/V Atalante. Key findings indicate that the large eddy simulation (LES) mode closely matches with the experimental data, enabling an in-depth analysis of the numerical model ability to predict variations in aerosol concentrations. These variations are influenced by different wind directions, which lead to various fetch distances typical of coastal zones. Full article
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12 pages, 1773 KiB  
Article
Seasonal Variations in Radon and Thoron Exhalation Rates from Solid Concrete Interior Walls Observed Using In Situ Measurements
by Akihiro Sakoda, Yuu Ishimori, Md. Mahamudul Hasan, Qianhao Jin and Takeshi Iimoto
Atmosphere 2024, 15(6), 701; https://doi.org/10.3390/atmos15060701 - 12 Jun 2024
Viewed by 207
Abstract
Building materials, such as brick and concrete, are known indoor radon (222Rn) and thoron (220Rn) sources. Most radon and thoron exhalation studies are based on the laboratory testing of pieces and blocks of such materials. To discuss if laboratory [...] Read more.
Building materials, such as brick and concrete, are known indoor radon (222Rn) and thoron (220Rn) sources. Most radon and thoron exhalation studies are based on the laboratory testing of pieces and blocks of such materials. To discuss if laboratory findings can be applied to a real-world environment, we conducted intensive in situ exhalation tests on two solid concrete interior walls of an apartment in Japan for over a year. Exhalation rates of radon (JRn) and thoron (JTn) were measured using an accumulation chamber and dedicated monitors, alongside monitoring indoor air temperature (T) and absolute humidity (AHin). There were weak correlations between JRn or JTn and T or AHin at one tested wall, and moderate correlations of JRn and strong correlations of JTn with T or AHin at the other wall, meaning more or less seasonal variations. The findings aligned with previous laboratory experiments on JRn but lacked corresponding data for JTn. Additionally, a moderate or strong correlation between JRn and JTn was observed for both tested walls. Comparison with theoretical calculations revealed a new issue regarding the impact of each process of emanation and migration within concrete pores on radon and thoron exhalation. Overall, this study provides insight into parameterizing radon and thoron source inputs in modeling the spatiotemporal dynamics of indoor radon and thoron. Full article
(This article belongs to the Special Issue Environmental Radon Measurement and Radiation Exposure Assessment)
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20 pages, 21819 KiB  
Article
Machine Learning for Global Bioclimatic Classification: Enhancing Land Cover Prediction through Random Forests
by Morgan Sparey, Mark S. Williamson and Peter M. Cox
Atmosphere 2024, 15(6), 700; https://doi.org/10.3390/atmos15060700 - 12 Jun 2024
Viewed by 328
Abstract
Traditional bioclimatic classification schemes have several inherent shortcomings; they do not represent anthropogenic impact, they contain a bias for global north representation, and they lack flexibility regarding novel climates that may arise due to climate change. Here we present an alternative approach, using [...] Read more.
Traditional bioclimatic classification schemes have several inherent shortcomings; they do not represent anthropogenic impact, they contain a bias for global north representation, and they lack flexibility regarding novel climates that may arise due to climate change. Here we present an alternative approach, using a machine learning approach. We combine European Space Agency Land Cover Classification data with traditional bioclimate classification climate variables, and additional variables; latitude, elevation, and topography. We utilise a random forest algorithm to create a classification system that overcomes the limitations and biases of the traditional schemes. The algorithm produced is able to predict land cover classification globally at 0.5-degree resolution with 93% accuracy. The resulting classifications account for human impact, particularly via agriculture, are informed by the topography of a region, and avoids the biases that traditional bioclimatic schemes contain. The algorithm can provide insights into the drivers of land cover change, the spatial distribution of land cover change, the potential impacts on ecosystem services and human well-being. Furthermore, the random forest model serves as a novel approach to the prediction of future land cover, and can be used to identify regions at risk of a land cover transition. Our data-based machine learning approach produces larger land-cover changes due to climate change than a traditional bioclimatic scheme, especially in sensitive regions such as Amazonia. Overall, our new approach projects approximately 17.4 million square kilometre of land-cover change per degree celsius of global warming. Full article
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