Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
4.6
2.5
Journals
Atmosphere
Editor’s Choice
share announcement

Editor’s Choice Articles

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

Order results
Result details
Results per page
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
15 pages, 5169 KiB  
Article
Overheating in the Tree Shade of Urban Parks: A Field Study of Thermal Adaption in China
by Zhongjun Zhang, Yaqian Wang and Dangwei Zhu
Atmosphere 2024, 15(5), 575; https://doi.org/10.3390/atmos15050575 - 8 May 2024
Cited by 1 | Viewed by 809
Abstract
With increased atmospheric temperature, temperatures in the shade of trees in parks also increase, and people are faced with high temperature challenges. In this study, thermal comfort in the shade of the trees of an urban park during summer in China was assessed. [...] Read more.
With increased atmospheric temperature, temperatures in the shade of trees in parks also increase, and people are faced with high temperature challenges. In this study, thermal comfort in the shade of the trees of an urban park during summer in China was assessed. The subjective responses of the respondents were recorded via questionnaires, and environment parameters were measured. The results show that the air temperature in the shade was 31.1 ± 3.0 °C during the day, and that it peaked at 36.9 °C; the globe temperature was 31.3 ± 3.1 °C, and it peaked at 40.1 ℃. Respondents’ clothing insulation was 0.31 ± 0.08 clo, and the effect of clothing adjustment on thermal adaptation was limited. Thermal sensation is linearly related to standard effective temperature (SET), and the upper limit of 80% acceptable SET was 32.1 °C. At different temperature values, the proportion of expected airflow enhancement exceeded 50%. The respondents preferred a neutral-warm sensation. Moreover, there was an obvious thermal adaptation, with thermal history and psychological adaptation being the main factors affecting thermal comfort. This study confirmed the value of shade and provided us with guidance for park planning and design. Full article
(This article belongs to the Section Biometeorology and Bioclimatology)
►▼ Show Figures

Figure 1

19 pages, 9531 KiB  
Article
Irrigation Schedule Optimization for Wheat and Sunflower Intercropping under Water Supply Restrictions in Inner Mongolia, China
by Hexiang Zheng, Hongfei Hou, Jiabin Wu, Delong Tian and Ping Miao
Atmosphere 2024, 15(5), 566; https://doi.org/10.3390/atmos15050566 - 3 May 2024
Cited by 1 | Viewed by 1079
Abstract
Precise water management is essential for the efficient development of irrigated agricultural crops in the Hetao Irrigation Area of Inner Mongolia. Given the severe water scarcity in the region and the significant use of intercropping as a cropping method, the development of rational [...] Read more.
Precise water management is essential for the efficient development of irrigated agricultural crops in the Hetao Irrigation Area of Inner Mongolia. Given the severe water scarcity in the region and the significant use of intercropping as a cropping method, the development of rational irrigation scheduling is crucial. The objective of this work was to combine the ISAREG model with wheat–sunflower intercropping crops in order to enhance the effectiveness of irrigation scheduling in intercropping systems. This was achieved by changing and verifying crucial parameters for simulating irrigation patterns in intercropping. We conducted an assessment of nine irrigation schedules for a wheat–sunflower intercropping system in order to provide a range of irrigation scenarios that effectively fulfill the water requirements of the system. In light of this, we suggested implementing restrictions on the dates and volumes of irrigation based on the demand for agricultural irrigation. This approach aimed to establish irrigation schedules that are highly efficient and tailored to the specific crops in the area. As a result, we achieved a water use efficiency rate of 100%, saved 28.78% of water resources, optimized crop irrigation schedules, and enhanced crop economics by 6.7%. This study presents a novel and efficient method to optimize agricultural irrigation schedules, boost agricultural water use efficiency, and maximize crop yields in order to promote sustainable agricultural development. Full article
(This article belongs to the Special Issue Agrometeorology, Agricultural Water Management and Impacts of Extreme Events (2nd Edition))
►▼ Show Figures

Figure 1

11 pages, 1190 KiB  
Brief Report
Why Does the Ensemble Mean of CMIP6 Models Simulate Arctic Temperature More Accurately Than Global Temperature?
by Petr Chylek, Chris K. Folland, James D. Klett, Muyin Wang, Glen Lesins and Manvendra K. Dubey
Atmosphere 2024, 15(5), 567; https://doi.org/10.3390/atmos15050567 - 3 May 2024
Cited by 2 | Viewed by 1202
Abstract
An accurate simulation and projection of future warming are needed for a proper policy response to expected climate change. We examine the simulations of the mean global and Arctic surface air temperatures by the CMIP6 (Climate Models Intercomparison Project phase 6) climate models. [...] Read more.
An accurate simulation and projection of future warming are needed for a proper policy response to expected climate change. We examine the simulations of the mean global and Arctic surface air temperatures by the CMIP6 (Climate Models Intercomparison Project phase 6) climate models. Most models overestimate the observed mean global warming. Only seven out of 19 models considered simulate global warming that is within ±15% of the observed warming between the average of the 2014–2023 and 1961–1990 reference period. Ten models overestimate global warming by more than 15% and only one of the models underestimates it by more than 15%. Arctic warming is simulated by the CMIP6 climate models much better than the mean global warming. The reason is an equal spread of over and underestimates of Arctic warming by the models, while most of the models overestimate the mean global warming. Eight models are within ±15% of the observed Arctic warming. Only three models are accurate within ±15% for both mean global and Arctic temperature simulations. Full article
(This article belongs to the Special Issue Arctic Climate Change: Observations, Modeling, and Arctic Amplification)
►▼ Show Figures

Figure 1

15 pages, 2970 KiB  
Article
Analysis of Ozone Pollution Characteristics, Meteorological Effects, and Transport Sources in Zhuzhou, China
by Bei Yan, Jia Luo, Min Zhang, Yi Zhang, Tongjue Xiao, Lu Wang, Bo Liu, Yunjuan Han, Gongxiu He, Lili Yang and Zhihong Huang
Atmosphere 2024, 15(5), 559; https://doi.org/10.3390/atmos15050559 - 30 Apr 2024
Viewed by 979
Abstract
Based on the hourly surface ozone (O3) observations and meteorological data from Zhuzhou in 2021, the pollution characteristics and influencing factors of O3 in Zhuzhou were investigated in the study. In addition, the Potential Source Contribution Function (PSCF) and Concentration [...] Read more.
Based on the hourly surface ozone (O3) observations and meteorological data from Zhuzhou in 2021, the pollution characteristics and influencing factors of O3 in Zhuzhou were investigated in the study. In addition, the Potential Source Contribution Function (PSCF) and Concentration Weighted Trajectory (CWT) analysis methods were employed to analyze the transmission paths and potential pollution sources of O3 pollution in Zhuzhou. The results showed that the total number of days with O3 exceeding the standard at all monitoring stations in Zhuzhou was 142 days in 2021. The overall air quality was less affected by SO2, NO2, and CO, and the trend of O3 pollution was still increasing. The concentrations of O3, CO, and NO2 varied significantly in different months, and the variation of O3 exhibited a “double-peak” pattern, with the peak value occurring in September. The O3 concentration in urban areas was significantly higher than that in suburban areas. Meteorological conditions had a significant impact on the degree of O3 pollution in Zhuzhou. The average wind speed in Zhuzhou throughout the year was 1.7 m/s, and the prevailing wind direction in summer was southeast, with a frequency of 16%. O3 pollution was mainly transported by short-distance airflow during the over-standard periods in 2021, accounting for 37.64%. The main source of O3 pollutant was from Jiangxi Province in the east, with the shortest distance of regional transport and the highest O3 concentration. In addition, transportation from central Guangdong Province, western Jiangxi Province, and central Hubei Province also had a significant impact. Full article
(This article belongs to the Special Issue Air Pollution in Urban and Regional Level: Sources, Sinks and Transportation (2nd Edition))
►▼ Show Figures

Figure 1

18 pages, 3125 KiB  
Article
Impact of COVID-19 Lockdown on Inhaled Toxic Elements in PM2.5 in Beijing: Composition Characterization and Source-Specific Health Risks Assessment
by Mingsheng Zhao, Lihong Ren, Xiaoyang Yang, Yuanguan Gao, Gang Li and Yani Liu
Atmosphere 2024, 15(5), 563; https://doi.org/10.3390/atmos15050563 - 30 Apr 2024
Viewed by 822
Abstract
In early 2020, China experienced a mass outbreak of a novel coronavirus disease (COVID-19). With an aim to evaluate the impact of emission variations on toxic element species in PM2.5 and the health risks associated with inhalation exposure during COVID-19, we collected [...] Read more.
In early 2020, China experienced a mass outbreak of a novel coronavirus disease (COVID-19). With an aim to evaluate the impact of emission variations on toxic element species in PM2.5 and the health risks associated with inhalation exposure during COVID-19, we collected PM2.5 filter samples in Beijing from January 1 to February 28, 2020. Positive matrix factorization (PMF) and a health risk (HR) assessment model were used to assess the health risks of the toxic elements and critical risk sources. The total concentration of eight toxic elements (Se, Cd, Pb, Zn, As, Cu, Ni, and Cr) in Beijing showed a trend of first increasing and then decreasing: full lockdown (322.9 ng m−3) > pre-lockdown (264.2 ng m−3) > partial lockdown (245.3 ng m−3). During the lockdown period, stringent control measures resulted in significant reductions (6−20%) in Zn, Pb, Cd, and Ni levels, while concentrations of Se, As, Cu, and Cr were unexpectedly elevated (14−348%). A total of five sources was identified: traffic emission, coal combustion, dust emission, industrial emission and mixed source of biomass burning and firework combustion. Total carcinogenic risk (TCR) of the selected toxic elements exceeded the US EPA limits for children and adults. As and Cr (IV) were the main contributors to non-carcinogenic and carcinogenic risks, respectively. For source-resolved risks, coal combustion was the main contributor to HI (43%), while industrial emissions were the main cause of TCR (45%). Additionally, increased contributions from coal combustion, biomass burning, and firework combustion during the full lockdown elevated the HI and TCR values. Full article
(This article belongs to the Section Air Quality and Health)
►▼ Show Figures

Figure 1

21 pages, 6516 KiB  
Article
Evaluating Phoenix Metropolitan Area Ozone Behavior Using Ground-Based Sampling, Modeling, and Satellite Retrievals
by Jason A. Miech, Pierre Herckes, Matthew P. Fraser, Avelino F. Arellano, Mohammad Amin Mirrezaei and Yafang Guo
Atmosphere 2024, 15(5), 555; https://doi.org/10.3390/atmos15050555 - 30 Apr 2024
Cited by 1 | Viewed by 1209
Abstract
An oxidizing and harmful pollutant gas, tropospheric ozone is a product of a complex set of photochemical reactions that can make it difficult to enact effective control measures. A better understanding of its precursors including volatile organic compounds (VOCs) and nitrogen oxides (NO [...] Read more.
An oxidizing and harmful pollutant gas, tropospheric ozone is a product of a complex set of photochemical reactions that can make it difficult to enact effective control measures. A better understanding of its precursors including volatile organic compounds (VOCs) and nitrogen oxides (NOx) and their spatial distribution can enable policymakers to focus their control efforts. In this study we used low-cost sensors (LCSs) to increase the spatial resolution of an existing NO2 monitoring network in addition to VOC sampling to better understand summer ozone formation in Maricopa County, Arizona, and observed that afternoon O3 values at the downwind sites were significantly correlated, ~0.27, to the morning NO2 × rate values at the urban sites. Additionally, we looked at the impact of wildfire smoke on ozone exceedances and compared non-smoke days to smoke days. The average O3 on smoke days was approximately 20% higher than on non-smoke days, however, the average NO2 concentration multiplied by estimated photolysis rate (NO2 × rate) values were only 2% higher on smoke days. Finally, we evaluated the ozone sensitivity of the region by calculating HCHO/NO2 ratios using three different datasets: ground, satellite, and model. Although the satellite dataset produced higher HCHO/NO2 ratios than the other datasets, when the proper regime thresholds are applied the three datasets consistently show transition and VOC-limited O3 production regimes over the Phoenix metro area. This suggests a need to implement more VOC emission controls in order to reach O3 attainment in the county. Full article
(This article belongs to the Section Air Quality)
►▼ Show Figures

Figure 1

13 pages, 4097 KiB  
Article
A Year-Long Measurement and Source Contributions of Volatile Organic Compounds in Nanning, South China
by Ying Wu, Zhaoyu Mo, Qinqin Wu, Yongji Fan, Xuemei Chen, Hongjiao Li, Hua Lin, Xishou Huang, Hualei Tang, Donglan Liao, Huilin Liu and Ziwei Mo
Atmosphere 2024, 15(5), 560; https://doi.org/10.3390/atmos15050560 - 30 Apr 2024
Viewed by 950
Abstract
Severe ozone (O3) pollution has been recorded in China in recent years. The key precursor, volatile organic compounds (VOCs), is still not well understood in Nanning, which is a less developed city compared to other megacities in China. In this study, [...] Read more.
Severe ozone (O3) pollution has been recorded in China in recent years. The key precursor, volatile organic compounds (VOCs), is still not well understood in Nanning, which is a less developed city compared to other megacities in China. In this study, a year-long measurement of VOCs was conducted from 1 October 2020 to 30 September 2021, to characterize the ambient variations and apportion the source contributions of VOCs. The daily-averaged concentration of VOCs was measured to be 26.4 ppb, ranging from 3.2 ppb to 136.2 ppb across the whole year. Alkanes and oxygenated VOCs (OVOCs) were major species, contributing 46.9% and 25.2% of total VOC concentrations, respectively. Propane, ethane, and ethanol were the most abundant in Nanning, which differed from the other significant species, such as toluene (3.7 ppb) in Guangzhou, ethylene (3.8 ppb) in Nanjing, and isopentane (5.5 ppb), in Chengdu. The positive matrix factorization (PMF) model resolved six source factors, including vehicular emission (contributing 33% of total VOCs), NG and LPG combustion (19%), fuel burning (17%), solvent use (16%), industry emission (10%), and biogenic emission (5%). This indicated that Nanning was less affected by industrial emission compared with other megacities of China, with industry contributing 12–50%. Ethylene, m/p-xylene, butane, propylene, and isoprene were key species determined by ozone formation potential (OFP) analysis, which should be priority-controlled. The variations in estimated OFP and observed O3 concentrations were significantly different, suggesting that VOC reactivity-based strategies as well as meteorological and NOx effects should be considered collectively in controlling O3 pollution. This study presents a year-long dataset of VOC measurements in Nanning, which gives valuable implications for VOC control in terms of key sources and reactive species and is also beneficial to the formulation of effective ozone control strategies in other less developed regions of China. Full article
(This article belongs to the Special Issue Urban VOC Emission, Transport, and Chemistry (VOC/ETC))
►▼ Show Figures

Figure 1

17 pages, 1283 KiB  
Article
Towards a Model of Snow Accretion for Autonomous Vehicles
by Mateus Carvalho, Sadegh Moradi, Farimah Hosseinnouri, Kiran Keshavan, Eric Villeneuve, Ismail Gultepe, John Komar, Martin Agelin-Chaab and Horia Hangan
Atmosphere 2024, 15(5), 548; https://doi.org/10.3390/atmos15050548 - 29 Apr 2024
Viewed by 1510
Abstract
Snow accumulation on surfaces exposed to adverse weather conditions has been studied over the years due to a variety of problems observed in different industry sectors, such as aeronautics and wind and civil engineering. With the growing interest in autonomous vehicles (AVs), this [...] Read more.
Snow accumulation on surfaces exposed to adverse weather conditions has been studied over the years due to a variety of problems observed in different industry sectors, such as aeronautics and wind and civil engineering. With the growing interest in autonomous vehicles (AVs), this concern extends to advanced driver-assistance systems (ADAS). Weather stressors, such as snow and icing, negatively influence the sensor functionality of AVs, and their autonomy is not guaranteed by manufacturers during episodes of intense weather precipitation. As a basis for mitigating the negative effects caused by heavy snowfall, models need to be developed to predict snow accumulation over critical surfaces of AVs. The present work proposes a framework for the study of snow accumulation on road vehicles. Existing icing and snow accretion models are reviewed, and adaptations for automotive applications are discussed. Based on the new capabilities developed by the Weather on Wheels (WoW) program at Ontario Tech University, a model architecture is proposed in order to progress toward adequate snow accretion predictions for autonomous vehicle operating conditions, and preliminary results are presented. Full article
(This article belongs to the Special Issue Sensitivity of Local Numerical Weather Prediction Models)
►▼ Show Figures

Figure 1

16 pages, 4372 KiB  
Article
Wind Shear and Aircraft Aborted Landings: A Deep Learning Perspective for Prediction and Analysis
by Afaq Khattak, Jianping Zhang, Pak-Wai Chan, Feng Chen, Arshad Hussain and Hamad Almujibah
Atmosphere 2024, 15(5), 545; https://doi.org/10.3390/atmos15050545 - 29 Apr 2024
Cited by 1 | Viewed by 1216
Abstract
In civil aviation, severe weather conditions such as strong wind shear, crosswinds, and thunderstorms near airport runways often compel pilots to abort landings to ensure flight safety. While aborted landings due to wind shear are not common, they occur under specific environmental and [...] Read more.
In civil aviation, severe weather conditions such as strong wind shear, crosswinds, and thunderstorms near airport runways often compel pilots to abort landings to ensure flight safety. While aborted landings due to wind shear are not common, they occur under specific environmental and situational circumstances. This research aims to accurately predict aircraft aborted landings using three advanced deep learning techniques: the conventional deep neural network (DNN), the deep and cross network (DCN), and the wide and deep network (WDN). These models are supplemented by various data augmentation methods, including the Synthetic Minority Over-Sampling Technique (SMOTE), KMeans-SMOTE, and Borderline-SMOTE, to correct the imbalance in pilot report data. Bayesian optimization was utilized to fine-tune the models for optimal predictive accuracy. The effectiveness of these models was assessed through metrics including sensitivity, precision, F1-score, and the Matthew Correlation Coefficient. The Shapley Additive Explanations (SHAP) algorithm was then applied to the most effective models to interpret their results and identify key factors, revealing that the intensity of wind shear, specific runways like 07R, and the vertical distance of wind shear from the runway (within 700 feet above runway level) were significant factors. The results of this research provide valuable insights to civil aviation experts, potentially revolutionizing safety protocols for managing aborted landings under adverse weather conditions, thereby improving overall airport efficiency and safety. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
►▼ Show Figures

Figure 1

19 pages, 14004 KiB  
Article
Spatiotemporal Dynamics of CO2 Emissions in China Based on Multivariate Spatial Statistics
by Mengyao Wang, Xiaoyan Dai and Hao Zhang
Atmosphere 2024, 15(5), 538; https://doi.org/10.3390/atmos15050538 - 28 Apr 2024
Viewed by 854
Abstract
With China’s rapid industrialization and urbanization in the process of socio-economic development, the extensive use of energy has resulted in a large amount of CO2 emissions, which puts great pressure on China’s carbon emission reduction task. Through multivariate socio-economic data, this paper [...] Read more.
With China’s rapid industrialization and urbanization in the process of socio-economic development, the extensive use of energy has resulted in a large amount of CO2 emissions, which puts great pressure on China’s carbon emission reduction task. Through multivariate socio-economic data, this paper proposes an extraction and screening method of multivariate variables based on land-use types, and the downscaled spatial decomposition of carbon emissions at different scales was carried out by using the spatial lag model (SLM). This paper makes up for the shortcomings of previous studies, such as an insufficient modeling scale, simple modeling variables, limited spatio-temporal span of spatial decomposition, and no consideration of geographical correlation. Based on the results of the spatial decomposition of carbon emissions, this paper explores the spatial and temporal dynamics of carbon emissions at different scales. The results showed that SLM is capable of downscaling the spatialization of carbon emissions with high precision, and the continuity of the decomposition results at the provincial scale is stronger, while the differences of the decomposition results at the municipal scale are more obvious within the municipal units. In terms of the spatial and temporal dynamics of CO2 emissions, carbon emissions at both scales showed a significant positive correlation. The dominant spatial correlation types are “Low–Low” at the provincial level, and “Low–Low” and “High–High” at the municipal level. The smaller spatial scope is more helpful to show the geographic dependence and geographic differences of China’s carbon emissions. The findings of this paper will help deepen the understanding of the spatial and temporal changes of carbon emissions in China. They will provide a scientific basis for the formulation of feasible carbon emission reduction policies. Full article
(This article belongs to the Special Issue Carbon Emission and Carbon Neutrality in China)
►▼ Show Figures

Figure 1

11 pages, 9112 KiB  
Communication
Global Precipitation for the Year 2023 and How It Relates to Longer Term Variations and Trends
by Robert F. Adler and Guojun Gu
Atmosphere 2024, 15(5), 535; https://doi.org/10.3390/atmos15050535 - 27 Apr 2024
Viewed by 1522
Abstract
In this paper, the global distribution of precipitation for 2023, in terms of global totals and regional anomaly patterns, is analyzed using information from the new Global Precipitation Climatology Project (GPCP) V3.2 Monthly product, including how the precipitation amounts and patterns from 2023 [...] Read more.
In this paper, the global distribution of precipitation for 2023, in terms of global totals and regional anomaly patterns, is analyzed using information from the new Global Precipitation Climatology Project (GPCP) V3.2 Monthly product, including how the precipitation amounts and patterns from 2023 fit into the longer record from 1983–2023. The tropical pattern of anomalies for 2023 is dominated by the effect of the El Nino which began during the Northern Hemisphere spring, after three plus years of La Nina conditions. The transition from La Nina conditions through 2022 shows the rapid change in many regional features from positive to negative anomalies or the reverse. Comparison of the observed regional trend maps with climate model results indicates similarity between the observations and the model results forced by observed SSTs, while the “free-running” model ensemble shows only a broad general agreement over large regions. Global total precipitation shows about a 3% range over the span of data, with El Nino and La Nina years prominent as positive and negative features, with 2023 showing a small positive global anomaly. The ITCZ (Inter-Tropical Convergence Zone) latitude band, 0–10° N, sets a record high mean rain rate in 2023 after a steady upward trend over the decades, probably a response related to global warming. Full article
(This article belongs to the Special Issue The Water Cycle and Climate Change (2nd Edition))
►▼ Show Figures

Figure 1

16 pages, 7351 KiB  
Article
Study of the Spatiotemporal Distribution Characteristics of Rainfall Using Hybrid Dimensionality Reduction-Clustering Model: A Case Study of Kunming City, China
by Weijie Lin, Yuanyuan Liu, Na Li, Jing Wang, Nianqiang Zhang, Yanyan Wang, Mingyang Wang, Hancheng Ren and Min Li
Atmosphere 2024, 15(5), 534; https://doi.org/10.3390/atmos15050534 - 26 Apr 2024
Viewed by 844
Abstract
In recent years, the frequency and intensity of global extreme weather events have gradually increased, leading to significant changes in urban rainfall patterns. The uneven distribution of rainfall has caused varying degrees of water security issues in different regions. Accurately grasping the spatiotemporal [...] Read more.
In recent years, the frequency and intensity of global extreme weather events have gradually increased, leading to significant changes in urban rainfall patterns. The uneven distribution of rainfall has caused varying degrees of water security issues in different regions. Accurately grasping the spatiotemporal distribution patterns of rainfall is crucial for understanding the hydrological cycle and predicting the availability of water resources. This study collected rainfall data every five minutes from 62 rain gauge stations in the main urban area of Kunming City from 2019 to 2021, constructing an unsupervised hybrid dimensionality reduction-clustering (HDRC) model. The model employs the Locally Linear Embedding (LLE) algorithm from manifold learning for dimensionality reduction of the data samples and uses the dynamic clustering K-Means algorithm for cluster analysis. The results show that the model categorizes the rainfall in the Kunming area into three types: The first type has its rainfall center distributed on the north shore of Dian Lake and the southern part of Kunming’s main urban area, with spatial dynamics showing the rainfall distribution gradually developing from the Dian Lake water body towards the land. The second type’s rainfall center is located in the northern mountainous area of Kunming, with a smaller spatial dynamic change trend. The water vapor has a relatively fixed and concentrated rainfall center due to the orographic uplift effect of the mountains. The third type’s rainfall center is located in the main urban area of Kunming, with this type of rainfall showing smaller variations in all indicators, mainly occurring in May and September when the temperature is lower, related to the urban heat island effect. This research provides a general workflow for spatial rainfall classification, capable of mining the spatiotemporal distribution patterns of regional rainfall based on extensive data and generating typical samples of rainfall types. Full article
(This article belongs to the Special Issue Characteristics of Extreme Climate Events over China)
►▼ Show Figures

Figure 1

20 pages, 15059 KiB  
Article
Multi-Source Dataset Assessment and Variation Characteristics of Snow Depth in Eurasia from 1980 to 2018
by Kaili Cheng, Zhigang Wei, Xianru Li and Li Ma
Atmosphere 2024, 15(5), 530; https://doi.org/10.3390/atmos15050530 - 26 Apr 2024
Viewed by 854
Abstract
Snow is an indicator of climate change. Its variation can affect surface energy, water balance, and atmospheric circulation, providing important feedback on climate change. There is a lack of assessment of the spatial characteristics of multi-source snow data in Eurasia, and these data [...] Read more.
Snow is an indicator of climate change. Its variation can affect surface energy, water balance, and atmospheric circulation, providing important feedback on climate change. There is a lack of assessment of the spatial characteristics of multi-source snow data in Eurasia, and these data exhibit high spatial variability and other differences. Therefore, using data obtained from the Global Historical Climatology Network Daily (GHCND) from 1980 to 2018, snow depth information from ERA5, MERRA2, and GlobSnow is assessed in this study. The spatiotemporal variation characteristics and the primary spatial modes of seasonal variations in snow depth are analyzed. The results show that the snow depth, according to GlobSnow data, is closer to that of the measured site data, while the ERA5_Land and MERRA2 data are overestimated. The annual variations in snow depth are consistent with seasonal variations in winter and spring, with an increasing trend in the mountains of Central Asia and Siberia and a decreasing trend in most of the rest of Eurasia. The dominant patterns of snow depth in late autumn, winter, and spring are all north–south dipole patterns, and there is overall consistency in summer. Full article
(This article belongs to the Section Meteorology)
►▼ Show Figures

Figure 1

29 pages, 17908 KiB  
Article
Dust Transport from North Africa to the Middle East: Synoptic Patterns and Numerical Forecast
by Sara Karami, Dimitris G. Kaskaoutis, Ioannis Pytharoulis, Rafaella-Eleni P. Sotiropoulou and Efthimios Tagaris
Atmosphere 2024, 15(5), 531; https://doi.org/10.3390/atmos15050531 - 26 Apr 2024
Cited by 1 | Viewed by 1141
Abstract
Every year, large quantities of dust are transported from North Africa to the Americas, Europe, and West Asia. The purpose of this study is to analyze four intense and pervasive dust storms that entered the Middle East from Northern Africa. Satellite products, ground-based [...] Read more.
Every year, large quantities of dust are transported from North Africa to the Americas, Europe, and West Asia. The purpose of this study is to analyze four intense and pervasive dust storms that entered the Middle East from Northern Africa. Satellite products, ground-based remote sensing measurements, reanalysis data, and the outputs of the Aire Limitée Adaptation dynamique Développement InterNational-Dust (ALADIN-Dust) and the ICOsahedral Nonhydrostatic weather and climate model with Aerosols and Reactive Trace gases (ICON-ART) forecasting models were synergized. The dust storms originated from different source regions located in the north, northeastern, and central parts of the Sahara Desert. The transport height of the main dust plumes was about 3–5 km, triggered by the westerly zonal winds. The presence of a closed low over the Eastern Mediterranean and the penetration of a deep trough into North Africa at 500 hPa were the main synoptic circulation patterns favoring long-range dust transport during the four dust events. A comparison of aerosol optical depth (AOD) outputs from the two models with satellite data revealed that although both models forecasted dust transport from Africa to the Middle East, they considerably underestimated the AOD values, especially near the dust sources. The ICON-ART model performed slightly better than ALADIN in forecasting these dust storms, and for longer forecasting leading time, although the performance of both models decreased, the superiority of the ICON-ART model became more apparent. Full article
(This article belongs to the Special Issue Numerical Weather Prediction Models and Ensemble Prediction Systems)
►▼ Show Figures

Figure 1

28 pages, 13221 KiB  
Article
Machine Learning Forecast of Dust Storm Frequency in Saudi Arabia Using Multiple Features
by Reem K. Alshammari, Omer Alrwais and Mehmet Sabih Aksoy
Atmosphere 2024, 15(5), 520; https://doi.org/10.3390/atmos15050520 - 24 Apr 2024
Cited by 1 | Viewed by 1415
Abstract
Dust storms are significant atmospheric events that impact air quality, public health, and visibility, especially in arid Saudi Arabia. This study aimed to develop dust storm frequency predictions for Riyadh, Jeddah, and Dammam by integrating meteorological and environmental variables. Our models include multiple [...] Read more.
Dust storms are significant atmospheric events that impact air quality, public health, and visibility, especially in arid Saudi Arabia. This study aimed to develop dust storm frequency predictions for Riyadh, Jeddah, and Dammam by integrating meteorological and environmental variables. Our models include multiple linear regression, support vector machine, gradient boosting regression tree, long short-term memory (LSTM), and temporal convolutional network (TCN). This study highlights the effectiveness of LSTM and TCN models in capturing the complex temporal dynamics of dust storms and demonstrates that they outperform traditional methods, as evidenced by their lower mean absolute error (MAE) and root mean square error (RMSE) values and higher R2 score. In Riyadh, the TCN model demonstrates its remarkable performance, with an R2 score of 0.51, an MAE of 2.80, and an RMSE of 3.48, highlighting its precision, adaptability, and responsiveness to changes in dust storm frequency. Conversely, in Dammam, the LSTM model proved to be the most accurate, achieving an MAE of 3.02, RMSE of 3.64, and R2 score of 0.64. In Jeddah, the LSTM model also exhibited an MAE of 2.48 and an RMSE of 2.96. This research shows the potential of using deep learning models to improve the accuracy and reliability of dust storm frequency forecasts. Full article
(This article belongs to the Special Issue New Insights in Air Quality Assessment: Forecasting and Monitoring)
►▼ Show Figures

Figure 1

12 pages, 5189 KiB  
Article
Quantifying Urban Daily Nitrogen Oxide Emissions from Satellite Observations
by 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
Cited by 1 | Viewed by 1815
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Reactive Nitrogen and Halogen in the Atmosphere)
►▼ Show Figures

Figure 1

33 pages, 9246 KiB  
Review
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
Cited by 1 | Viewed by 1793
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. [...] Read more.
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. Full article
(This article belongs to the Special Issue Observations and Analysis of Upper Atmosphere)
►▼ Show Figures

Figure 1

17 pages, 5425 KiB  
Article
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
Viewed by 1185
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Advancements in Thunderstorm Nowcasting and Atmospheric Electricity Monitoring by Remote Sensing)
►▼ Show Figures

Figure 1

18 pages, 16362 KiB  
Article
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
Viewed by 959
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Multi-Year ENSO Events: Dynamics, Predictability, Teleconnections, and Impacts)
►▼ Show Figures

Figure 1

13 pages, 3986 KiB  
Article
Characteristics of Atmospheric Pollutants in Paddy and Dry Field Regions: Analyzing the Oxidative Potential of Biomass Burning
by Myoungki Song, Minwook Kim, Sea-Ho Oh, Geun-Hye Yu, Seoyeong Choe, Hajeong Jeon, Dong-Hoon Ko, Chaehyeong Park and Min-Suk Bae
Atmosphere 2024, 15(4), 493; https://doi.org/10.3390/atmos15040493 - 17 Apr 2024
Cited by 4 | Viewed by 1018
Abstract
This study aimed to identify the characteristics of atmospheric pollutants emitted by agricultural activities and to evaluate factors that may cause harm to human health. For the research, atmospheric pollutants were measured over the course of a year in representative rice farming and [...] Read more.
This study aimed to identify the characteristics of atmospheric pollutants emitted by agricultural activities and to evaluate factors that may cause harm to human health. For the research, atmospheric pollutants were measured over the course of a year in representative rice farming and field crop farming areas in South Korea. The results confirmed that the characteristics of atmospheric pollutants in agricultural areas are influenced by the nature of agricultural activities. Specifically, when comparing rice paddies and field crop areas, during summer, the correlation between oxidative potential and levoglucosan—a marker for biomass burning—weakens due to less burning activity in the rice-growing season, leading to lower oxidative potential despite different PM2.5 across areas. The study also finds that methyl sulfonic acid, indicating marine influence, plays a big role in keeping oxidative potential low in summer. This suggests that the main causes of PM2.5-related health risks in the area are from biomass burning and external sources, with burning being a significant factor in increasing oxidative potential. Based on these results, it is hoped that measures can be taken in the future to reduce atmospheric pollutants in agricultural areas. Full article
(This article belongs to the Special Issue Novel Insights into Air Pollution over East Asia)
►▼ Show Figures

Graphical abstract

28 pages, 81499 KiB  
Article
Mid- and High-Latitude Electron Temperature Dependence on Solar Activity in the Topside Ionosphere through the Swarm B Satellite Observations and the International Reference Ionosphere Model
by Alessio Pignalberi, Vladimir Truhlik, Fabio Giannattasio, Igino Coco and Michael Pezzopane
Atmosphere 2024, 15(4), 490; https://doi.org/10.3390/atmos15040490 - 16 Apr 2024
Cited by 3 | Viewed by 1047
Abstract
This study focuses on the open question of the electron temperature (Te) variation with solar activity in the topside ionosphere at mid- and high latitudes. It takes advantage of in situ observations taken over a decade (2014–2023) from Langmuir probes [...] Read more.
This study focuses on the open question of the electron temperature (Te) variation with solar activity in the topside ionosphere at mid- and high latitudes. It takes advantage of in situ observations taken over a decade (2014–2023) from Langmuir probes on board the low-Earth-orbit Swarm B satellite and spanning an altitude range of 500–530 km. The study also includes a comparison with Te values modeled using the International Reference Ionosphere (IRI) model and with Millstone Hill (42.6° N. 71.5° W) incoherent scatter radar observations. The largest Te variation with solar activity was found at high latitudes in the winter season, where Te shows a marked decreasing trend with solar activity in the polar cusp and auroral regions and, more importantly, at sub-auroral latitudes in the nightside sector. Differently, in the summer season, Te increases with solar activity in the polar cusp and auroral regions, while for equinoxes, variations are smaller and less clear. Mid-latitudes generally show negligible Te variations with solar activity, which are mostly within the natural dispersion of Te observations. The comparison between measured and modeled values highlighted that future implementations of the IRI model would benefit from an improved description of the Te dependence on solar activity, especially at high latitudes. Full article
(This article belongs to the Special Issue Effect of Solar Activities to the Earth's Atmosphere)
►▼ Show Figures

Figure 1

14 pages, 11063 KiB  
Article
Impact of Climate Change on Extreme Rainfall Events and Pluvial Flooding Risk in the Vojvodina Region (North Serbia)
by Jovana Bezdan, Atila Bezdan, Boško Blagojević, Sanja Antić, Amela Greksa, Dragan Milić and Aleksa Lipovac
Atmosphere 2024, 15(4), 488; https://doi.org/10.3390/atmos15040488 - 15 Apr 2024
Viewed by 1732
Abstract
Extreme precipitation events, which are common natural hazards, are expected to increase in frequency due to global warming, leading to various types of floods, including pluvial floods. In this study, we investigated the probabilities of maximum 3-day precipitation amount (Rx3day) occurrences during spring [...] Read more.
Extreme precipitation events, which are common natural hazards, are expected to increase in frequency due to global warming, leading to various types of floods, including pluvial floods. In this study, we investigated the probabilities of maximum 3-day precipitation amount (Rx3day) occurrences during spring in the Vojvodina region, covering both past (1971–2019) and future (2020–2100) periods. We utilized an ensemble of eight downscaled, bias-corrected regional climate models from the EURO-CORDEX project database, selecting the RCP8.5 scenario to examine future Rx3day amounts. The probabilities of occurrences of Rx3day were modeled using the GEV distribution, while the number of events where Rx3day in spring exceeds specific thresholds was modeled using the Poisson distribution. The results indicate that Rx3day with a ten-year return period during the spring months is expected to increase by 19% to 33%. Additionally, the probabilities of having more than one event where Rx3day exceeds thresholds are projected to rise by 105.6% to 200.0% in the future compared to the historical period. The analysis comparing the design values of Rx3day with future projections for the period 2020–2100 revealed that 51 drainage systems are likely to function without difficulties under future climate conditions. However, for the remaining 235 drainage systems, an increased risk of pluvial flooding was identified, as their design precipitation amounts are lower than the future projections. This study reveals that analyzing extreme rainfall events in the context of climate change yields crucial information that facilitates effective planning and policy making in water management, particularly flood protection. Full article
(This article belongs to the Special Issue Climate Change Impacts and Adaptation Strategies in Agriculture)
►▼ Show Figures

Figure 1

20 pages, 2433 KiB  
Article
The Spatiotemporal Evolution of the Growing Degree Days Agroclimatic Index for Viticulture over the Northern Mediterranean Basin
by Ioannis Charalampopoulos, Iliana Polychroni, Fotoula Droulia and Panagiotis T. Nastos
Atmosphere 2024, 15(4), 485; https://doi.org/10.3390/atmos15040485 - 14 Apr 2024
Cited by 1 | Viewed by 1674
Abstract
The agricultural sector faces significant challenges worldwide due to climate change. The pressure exerted by altered thermal conditions drives the zonal shift for various cultivations. This study aims to analyze and present the spatiotemporal evolution of the growing degree days (GDD) index in [...] Read more.
The agricultural sector faces significant challenges worldwide due to climate change. The pressure exerted by altered thermal conditions drives the zonal shift for various cultivations. This study aims to analyze and present the spatiotemporal evolution of the growing degree days (GDD) index in the northern Mediterranean Basin (NMB). More specifically, this research presents the multiyear analysis of the GDD index, which is focused on a high-value vine cultivation derived from the E-OBS dataset. The investigated time period spans from 1969 to 2018, and the performed analysis indicates a broad shift/expansion in areas with GDDs exceeding 2000 heat units. This is present in traditional winemaker countries such as France and Italy. Still, it is also evident that there is a high positive change in countries such as Serbia, Bulgaria, and other Balkans countries. The findings may be helpful in the strategic planning of the agricultural sector in these countries or on a vinery scale. Full article
(This article belongs to the Section Biometeorology and Bioclimatology)
►▼ Show Figures

Figure 1

21 pages, 9517 KiB  
Article
A Satellite Analysis: Comparing Two Medicanes
by Giuseppe Ciardullo, Leonardo Primavera, Fabrizio Ferrucci, Fabio Lepreti and Vincenzo Carbone
Atmosphere 2024, 15(4), 481; https://doi.org/10.3390/atmos15040481 - 12 Apr 2024
Viewed by 932
Abstract
Morphological features of the Mediterranean Sea basin have recently been precursors to a significant increase in the formation of extreme events, in relation to climate change effects. It happens very frequently that rotating air masses and the formation of mesoscale vortices can evolve [...] Read more.
Morphological features of the Mediterranean Sea basin have recently been precursors to a significant increase in the formation of extreme events, in relation to climate change effects. It happens very frequently that rotating air masses and the formation of mesoscale vortices can evolve into events with characteristics similar to large-scale tropical cyclones. Generally, they are less intense, with smaller size and duration; thus, they are called Medicanes, a short name for Mediterranean hurricanes, or tropical-like cyclones (TLCs). In this paper, we propose a new perspective for the study and analysis of cyclonic events, starting with data and images acquired from satellites and focusing on the diagnostics of the evolution of atmospheric parameters for these events. More precisely, satellite remote sensing techniques are employed to elaborate on different high spatial-resolution satellite images of the events at a given sensing time. Two case studies are examined, taking into account their development into Medicane stages: Ianos, which intensified in the Ionian Sea and reached the coast of Greece between 14 and 21 September 2020, and Apollo, which impacted Mediterranean latitudes with a long tracking from 24 October to 2 November 2021. For these events, 20 images were acquired from two different satellite sensors, onboard two low-Earth orbit (LEO) platforms, by deeply exploiting their thermal infrared (TIR) spectral channels. A useful extraction of significant physical information was carried out from every image, highlighting several atmospheric quantities, including temperature and altitude layers from the top of the cloud, vertical temperature gradient, atmospheric pressure field, and deep convection cloud. The diagnostics of the two events were investigated through the spatial scale capabilities of the instruments and the spatiotemporal evolution of the cyclones, including the comparison between satellite data and recording data from the BOLAM forecasting model. In addition, 384 images were extracted from the geostationary (GEO) satellite platform for the investigation of the events’ one-day structure intensification, by implementing time as the third dimension. Full article
(This article belongs to the Section Meteorology)
►▼ Show Figures

Graphical abstract

42 pages, 25177 KiB  
Review
Climatology of the Nonmigrating Tides Based on Long-Term SABER/TIMED Measurements and Their Impact on the Longitudinal Structures Observed in the Ionosphere
by Dora Pancheva, Plamen Mukhtarov and Rumiana Bojilova
Atmosphere 2024, 15(4), 478; https://doi.org/10.3390/atmos15040478 - 12 Apr 2024
Viewed by 875
Abstract
This paper presents climatological features of the longitudinal structures WN4, WN3, and WN2 and their drivers observed in the lower thermospheric temperatures and in the ionospheric TEC. For this purpose, two long-term data sets are utilized: the satellite SABER/TIMED temperature measurements, and the [...] Read more.
This paper presents climatological features of the longitudinal structures WN4, WN3, and WN2 and their drivers observed in the lower thermospheric temperatures and in the ionospheric TEC. For this purpose, two long-term data sets are utilized: the satellite SABER/TIMED temperature measurements, and the global TEC maps generated with the NASA JPL for the interval of 2002–2022. As the main drivers of the longitudinal structures are mainly nonmigrating tides, this study first investigates the climatology of those nonmigrating tides, which are the main contributors of the considered longitudinal structures; these are nonmigrating diurnal DE3, DE2, and DW2, and semidiurnal SW4 and SE2 tides. The climatology of WN4, WN3, and WN2 structures in the lower thermosphere reveals that WN4 is the strongest one with a magnitude of ~20 K observed at 10° S in August, followed by WN2 with ~13.9 K at 10° S in February, and the weakest is WN3 with ~12.4 K observed over the equator in July. In the ionosphere, WN3 is the strongest structure with a magnitude of 5.9 TECU located at −30° modip latitude in October, followed by WN2 with 5.4 TECU at 30 modip in March, and the last is WN4 with 3.7 TECU at −30 modip in August. Both the climatology of the WSA and the features of its drivers are investigated as well. Full article
(This article belongs to the Special Issue Variability and Predictability of Space Weather and the Ionosphere: Recent Advances)
►▼ Show Figures

Figure 1

12 pages, 7943 KiB  
Article
Subgrid-Scale Topographic Effects on Radiation for Global Weather Forecast Models
by Sunghye Baek and Junghan Kim
Atmosphere 2024, 15(4), 479; https://doi.org/10.3390/atmos15040479 - 12 Apr 2024
Viewed by 930
Abstract
The incoming solar radiation arriving the Earth’s surface is strongly influenced by surface terrain. Conventional global weather forecast models, with grid scales of about 10 km, lack the resolution to accurately capture terrain-induced variations. We devised a new parameterization method to incorporate high-resolution [...] Read more.
The incoming solar radiation arriving the Earth’s surface is strongly influenced by surface terrain. Conventional global weather forecast models, with grid scales of about 10 km, lack the resolution to accurately capture terrain-induced variations. We devised a new parameterization method to incorporate high-resolution subgrid-scale terrain data into grid-scale radiative flux calculations without averaging or smoothing topographic features. Utilizing a 15″ digital elevation model from the Shuttle Radar Topography Mission, we computed subgrid-scale data and transformed them onto the Korean Integrated Model’s cubed sphere grid using a Voronoi diagram to maintain geographical accuracy. The new scheme was initially evaluated through offline ideal tests and case studies. The results demonstrated that the scheme accurately captured the variations in downward shortwave flux, keeping the mean flux on a global scale nearly constant. The global mean flux difference in all skies was less than 0.01%. Statistical analyses demonstrated improved temperature and geopotential height predictions compared to reanalysis data. The anomaly correlation coefficient for East Asia at 850 hPa increased by 0.036 at 240 forecast hours. Overall, the anomaly correlation coefficient and root mean square error of geopotential height and temperature showed enhancements, particularly in the Northern Hemisphere and tropics. Importantly, the scheme introduces negligible additional memory and CPU requirements, making it suitable for both regional and global models. Only a 0.58% increase in CPU time was observed for the 10-day forecast. Full article
(This article belongs to the Section Meteorology)
►▼ Show Figures

Figure 1

28 pages, 13624 KiB  
Review
State-of-the-Art Low-Cost Air Quality Sensors, Assemblies, Calibration and Evaluation for Respiration-Associated Diseases: A Systematic Review
by Hasan Tariq, Farid Touati, Damiano Crescini and Adel Ben Mnaouer
Atmosphere 2024, 15(4), 471; https://doi.org/10.3390/atmos15040471 - 11 Apr 2024
Cited by 1 | Viewed by 3949
Abstract
Indoor air quality and respiratory health have always been an area of prime interest across the globe. The significance of low-cost air quality sensing and indoor public health practices spiked during the pandemic when indoor air pollution became a threat to living beings, [...] Read more.
Indoor air quality and respiratory health have always been an area of prime interest across the globe. The significance of low-cost air quality sensing and indoor public health practices spiked during the pandemic when indoor air pollution became a threat to living beings, especially human beings. Problem Definition: Indoor respiration-associated diseases are hard to diagnose if they are due to indoor environmental conditions. A major challenge was observed in establishing a baseline between indoor air quality sensors and associated respiratory diseases. Methods: In this work, 10,000+ articles from top literature databases were reviewed using six bibliometric analysis methods (Lorenz Curve of Citations, Hirch’s H-Index, Kosmulski’s H2-Index, Harzing’s Hl-Norm-Index, Sidoropolous’s HC-Index, and Schrieber’s HM-index) to formulate indoor air quality sensor and disease correlation publication rubrics to critically review 482 articles. Results: A set of 152 articles was found based on systematic review parameters in six bibliometric indices for publications that used WHO, NIH, US EPA, CDC, and FDA-defined principles. Five major respiratory diseases were found to be causing major death toll (up to 32%) due to five key pollutants, measured by 30+ low-cost sensors and further optimized by seven calibration systems for seven practical parameters tailored to respiratory disease baselines evaluated through 10 cost parameters. Impact: This review was conducted to assist end-users, public health facilities, state agencies, researchers, scientists, and air quality protection agencies. Full article
(This article belongs to the Special Issue Air Pollution Exposure and Health Impact Assessment (2nd Edition))
►▼ Show Figures

Figure 1

18 pages, 5137 KiB  
Article
Predicting Summer Precipitation Anomalies in the Yunnan–Guizhou Plateau Using Spring Sea-Surface Temperature Anomalies
by Ya Tuo, Panjie Qiao, Wenqi Liu and Qingquan Li
Atmosphere 2024, 15(4), 453; https://doi.org/10.3390/atmos15040453 - 5 Apr 2024
Viewed by 756
Abstract
By constructing a correlation network between global sea surface temperature anomalies (SSTAs) and summer precipitation anomalies in the Yunnan–Guizhou Plateau, key SST regions influencing summer precipitation anomalies in the Yunnan–Guizhou Plateau were selected. It was found that spring SSTAs in the Bay of [...] Read more.
By constructing a correlation network between global sea surface temperature anomalies (SSTAs) and summer precipitation anomalies in the Yunnan–Guizhou Plateau, key SST regions influencing summer precipitation anomalies in the Yunnan–Guizhou Plateau were selected. It was found that spring SSTAs in the Bay of Bengal, southwestern Atlantic, and eastern Pacific are crucial for influencing summer precipitation anomalies in the Yunnan–Guizhou Plateau. Setting SSTAs from these three regions as predictor variables 3 months in advance, we constructed multiple linear regression (MLR), ridge regression (RR), and lasso regression (LR) models to predict summer precipitation anomalies over the Yunnan–Guizhou region. The training phase involved data spanning from 1961 to 2005, which aimed to predict precipitation anomalies in the Yunnan–Guizhou Plateau for the period extending from 2006 to 2022. Based on MLR, RR, and LR models, the correlations between predicted values and observed summer precipitation anomalies in Yunnan–Guizhou were 0.48, 0.46, and 0.46, respectively. These values were all higher than the correlation coefficients of the NCC_CSM model’s predicted and observed values. Additionally, its performance in predicting summer precipitation anomalies over the Yunnan–Guizhou region, based on key SST regions, was assessed using performance metrics such as anomaly correlation coefficient (ACC), anomaly sign consistency rate (PC), and trend anomaly comprehensive score (PS score). The average ACC of MLR, RR, and LR models was higher than that of the NCC_CSM model’s predictions. For MLR, RR, LR, and NCC_CSM models, the PCs exceeding 50% of the year were 14, 14, 11, and 10, respectively. Furthermore, the average PS score for predicting summer precipitation anomalies over the Yunnan–Guizhou region using MLR, RR, and LR was approximately 73 points; 8 higher than the average PS score of the NCC_CSM model. Therefore, predicting summer precipitation anomalies over the Yunnan–Guizhou region based on key SST regions is of great significance for improving the prediction skills of precipitation anomalies in this region. Full article
(This article belongs to the Special Issue Climate Extremes in China (2nd Edition))
►▼ Show Figures

Figure 1

21 pages, 1013 KiB  
Article
Socioeconomic Impacts of Climate Mitigation Actions in Greece: Quantitative Assessment and Public Perception
by Yannis Sarafidis, Nicolas Demertzis, Elena Georgopoulou, Lydia Avrami, Sevastianos Mirasgedis and Othon Kaminiaris
Atmosphere 2024, 15(4), 454; https://doi.org/10.3390/atmos15040454 - 5 Apr 2024
Cited by 1 | Viewed by 1984
Abstract
Appropriately designed and implemented climate mitigation actions have multiple co-benefits (yet some trade-offs cannot be excluded) that result in substantial social and economic value beyond their direct impact on reducing energy consumption and GHG emissions. Despite their wider acknowledgement by the research community, [...] Read more.
Appropriately designed and implemented climate mitigation actions have multiple co-benefits (yet some trade-offs cannot be excluded) that result in substantial social and economic value beyond their direct impact on reducing energy consumption and GHG emissions. Despite their wider acknowledgement by the research community, decision makers and the public have incomplete information on these multiple effects. This paper has a twofold objective: First, through analytical bottom-up approaches, it assesses, in quantitative terms, the macroeconomic effects and the public health benefits attributed to a variety of mitigation actions under consideration in the context of the Greek Energy and Climate Plan. Second, it investigates, through a social survey, how citizens perceive climate change and value these multiple impacts of mitigation actions, and to what extent they are willing to pay for them and support the adoption of policy measures aiming at the green transition of the Greek economy. We show that mitigation actions bring about significant health benefits, particularly in cities, and generate significant positive macroeconomic effects, particularly if mitigation actions focus on the decarbonization of the building sector and on the exploitation of local renewable sources. We also argue that most people do not realize that climate mitigation actions can have wider benefits for society, such as tackling energy poverty, improving public health, and creating new jobs. Unwillingness to pay tends to be the prominent attitude. People who are more reluctant to cover a part of the cost of environmental protection are less likely to perceive that climate change is one of the main challenges at global and national level and support the adoption of climate mitigation policies. In this context, the national strategy for climate change should focus on effectively informing and engaging the public in climate mitigation strategies, strengthening the public trust in government institutions, promoting mutually acceptable solutions with the local communities, and providing incentives for changing citizens’ behavior towards climate-related actions. Full article
(This article belongs to the Special Issue The Drivers and Impacts of Climate Change Over the Eastern Mediterranean)
►▼ Show Figures

Figure 1

19 pages, 3564 KiB  
Article
Biometeorological Conditions in Poznań, Poland: Insights from In Situ Summer Data
by Marek Półrolniczak, Arkadiusz Marek Tomczyk and Ewa Bednorz
Atmosphere 2024, 15(4), 448; https://doi.org/10.3390/atmos15040448 - 3 Apr 2024
Viewed by 885
Abstract
Recent climatic changes, most evident in air temperature, also significantly impact sensible conditions, particularly affecting the human body during the summer season in urban areas. This study utilized hourly values of air temperature (t, °C) and relative humidity (RH, %) for 2008–2022 obtained [...] Read more.
Recent climatic changes, most evident in air temperature, also significantly impact sensible conditions, particularly affecting the human body during the summer season in urban areas. This study utilized hourly values of air temperature (t, °C) and relative humidity (RH, %) for 2008–2022 obtained from nine measurement points located in the city of Poznań. The measurement network was set up and supported by the Department of Meteorology and Climatology of Adam Mickiewicz University in Poznań. Based on these data, thermal conditions were characterized using the Humidex (HD), as well as “hot days” (Tmax > 30 °C) and heat waves determined based on them. The conducted research revealed variability in thermal conditions across the city. The highest average Tmax (27.4 °C) and HD values (31.3 °C), as well as the greatest average number of hot days (15 days), were recorded in the compact, dense city center. In contrast, the lowest values (respectively: 25.9 °C, 27.5 °C, 8 days) were observed in areas with a significantly greater proportion of green spaces located further from the center. Furthermore, significant trends of change were observed: an annual average Tmax increase of 1.2–1.6 °C/decade and HD values showing an increase of 1.5–3.0 °C/decade. This study also highlighted the noteworthy impact of urbanization and the presence of urban greenery on the frequency and total duration of heat waves. Between 2008 and 2022, the area of compact development experienced 26 heat waves lasting a total of 115 days, whereas the area with a high proportion of greenery recorded 14 cases and 55 days, respectively. The longest recorded heat wave, spanning 9 days, occurred in July 2010. Individual heat waves identified based on Tmax (>30 °C) may exhibit significant variations in terms of perceived conditions, as indicated by HD. Full article
(This article belongs to the Section Biometeorology and Bioclimatology)
►▼ Show Figures

Figure 1

40 pages, 23230 KiB  
Article
Synoptic Analysis and Subseasonal Predictability of an Early Heatwave in the Eastern Mediterranean
by Dimitris Mitropoulos, Ioannis Pytharoulis, Prodromos Zanis and Christina Anagnostopoulou
Atmosphere 2024, 15(4), 442; https://doi.org/10.3390/atmos15040442 - 2 Apr 2024
Viewed by 1226
Abstract
Greece and the surrounding areas experienced an early warm spell with characteristics of a typical summer Mediterranean heatwave in mid-May 2020. The maximum 2 m temperature at Kalamata (southern Greece) reached 40 °C on 16 May and at Aydin (Turkey), it was 42.6 [...] Read more.
Greece and the surrounding areas experienced an early warm spell with characteristics of a typical summer Mediterranean heatwave in mid-May 2020. The maximum 2 m temperature at Kalamata (southern Greece) reached 40 °C on 16 May and at Aydin (Turkey), it was 42.6 °C on 17 May. There was a 10-standard deviation positive temperature anomaly (relative to the 1975–2005 climatology) at 850 hPa, with a southwesterly flow and warm advection over Greece and western Turkey from 11 to 20 May. At 500 hPa, a ridge was located over the Eastern Mediterranean, resulting in subsidence. The aims of this study were (a) to investigate the prevailing synoptic conditions during this event in order to document its occurrence and (b) to assess whether this out-of-season heatwave was predictable on subseasonal timescales. The subseasonal predictability is not a well-researched scientific topic in the Eastern Mediterranean Sea. The ensemble global forecasts from six international meteorological centres (European Centre for Medium-Range Weather Forecasts—ECMWF, United Kingdom Met Office—UKMO, China Meteorological Administration—CMA, Korea Meteorological Administration—KMA, National Centers for Environmental Prediction—NCEP and Hydrometeorological Centre of Russia—HMCR) and limited area forecasts using the Weather Research and Forecasting model with the Advanced Research dynamic solver (WRF) forced by Climate Forecast System version 2 (CFSv.2; NCEP) forecasts were evaluated for lead times ranging from two to six weeks using statistical scores. WRF was integrated using two telescoping nests covering Europe, the Mediterranean basin and large part of the Atlantic Ocean, with a grid spacing of 25 km, and Greece–western Turkey at 5 km. The results showed that there were some accurate forecasts initiated two weeks before the event’s onset. There was no systematic benefit from the increase of the WRF model’s resolution from 25 km to 5 km for forecasting the 850 hPa temperature, but regarding the prediction of maximum air temperature near the surface, the high resolution (5 km) nest of WRF produced a marginally better performance than the coarser resolution domain (25 km). Full article
(This article belongs to the Special Issue Numerical Weather Prediction Models and Ensemble Prediction Systems)
►▼ Show Figures

Figure 1

51 pages, 150653 KiB  
Article
Exploring the Hidden World of Lighting Flicker with a High-Speed Camera
by Christopher D. Elvidge, Mikhail Zhizhin, Ashley Pipkin, Sharolyn Anderson, William S. Kowalik and Morgan Bazilian
Atmosphere 2024, 15(4), 438; https://doi.org/10.3390/atmos15040438 - 2 Apr 2024
Viewed by 2449
Abstract
Alternating current can result in flickering—or pulsing—in the brightness of light emitted by luminaires. Lighting flicker typically occurs in the range of 100 to 140 cycles per second (Hz), which is too fast for visual perception by most organisms. However, evidence indicates that [...] Read more.
Alternating current can result in flickering—or pulsing—in the brightness of light emitted by luminaires. Lighting flicker typically occurs in the range of 100 to 140 cycles per second (Hz), which is too fast for visual perception by most organisms. However, evidence indicates that many organisms perceive flicker with non-visual photoreceptors present on the retinas. Exposure to flickering lights at night disrupts the circadian rhythm of organisms, leading to symptoms similar to blue light exposure at night. The traditional method for detecting flickering is with a flickermeter held near a single light. In this paper, we explore the use of high-speed camera data in the collection of temporal profiles for groups of luminaires simultaneously at distances ranging from several meters to several kilometers. Temporal profiles are extracted for individual lighting features and the full scene. The identification of luminaire types is based on their spectral signatures. With the camera data, it is possible to identify flickering and non-flickering lights, to determine the flicker frequency, to calculate percent flicker and the flicker index, and to identify groups of lights whose flickers are synchronized. Both flickering and non-flickering luminaires can be found for LED, metal halide, fluorescent, and compact fluorescent lights. To date, flickering has been detected in all of the incandescent, high-pressure sodium, and low-pressure sodium luminaires that we measured. We found that flicker synchronization is often present for lights installed within a single facility and also for strings of streetlights. We also found that flicker exposure can come from the light reflected off of the earth’s surface. Luminaires designed to illuminate large areas often saturate high-speed camera data collection. This saturation can be reduced or eliminated using neutral density filters on the camera. Published experimental data on the impacts of flicker on organisms remains sparse. Many studies have drawn inferences on the impacts of spectral and lighting brightness on organisms without controlling for flicker. Our conclusion is that lighting flicker is a type of light pollution. The use of high-speed camera data makes it easier to include flicker as a variable in studies regarding the impacts of lighting on organisms. Full article
(This article belongs to the Special Issue Emerging Topics in Light Pollution)
►▼ Show Figures

Figure 1

17 pages, 1035 KiB  
Article
Modification and Validation of the Soil–Snow Module in the INM RAS Climate Model
by Alexey Chernenkov, Evgeny Volodin, Sergey Kostrykin, Maria Tarasevich and Vasilisa Vorobyeva
Atmosphere 2024, 15(4), 422; https://doi.org/10.3390/atmos15040422 - 29 Mar 2024
Cited by 1 | Viewed by 1134
Abstract
This paper describes the modification of a simple land snow cover module of the INM RAS climate model. The possible liquid water and refreezing of meltwater in the snow layer are taken into account by the proposed parameterization. This is particularly important for [...] Read more.
This paper describes the modification of a simple land snow cover module of the INM RAS climate model. The possible liquid water and refreezing of meltwater in the snow layer are taken into account by the proposed parameterization. This is particularly important for modelling the transition season, as this phenomenon is mainly observed during the formation and melting of the snow cover when the surface temperature fluctuates around 0 °C. The snow density evolution simulation is also added. This parameterization is implemented in the INM-CM snow module and verified on observation data using the ESM-SnowMIP-like protocol. As a result, the INM-CM mean climate snow melt periods are refined, particularly in middle and high latitudes. The snow-covered area according to the model is also improved. In the future, a modified version of the land snow module can be used, coupled with a snow albedo model that takes into account snow metamorphism. This module can also be applied to sea ice snow. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
►▼ Show Figures

Figure 1

13 pages, 11891 KiB  
Article
Tracking Carbon Dioxide with Lagrangian Transport Simulations: Case Study of Canadian Forest Fires in May 2021
by Ye Liao, Xuying Deng, Mingming Huang, Mingzhao Liu, Jia Yi and Lars Hoffmann
Atmosphere 2024, 15(4), 429; https://doi.org/10.3390/atmos15040429 - 29 Mar 2024
Viewed by 1006
Abstract
The large amounts of greenhouse gases, such as carbon dioxide, produced by severe forest fires not only seriously affect the ecosystems in the area where the fires occur but also cause a greenhouse effect that has a profound impact on the natural environment [...] Read more.
The large amounts of greenhouse gases, such as carbon dioxide, produced by severe forest fires not only seriously affect the ecosystems in the area where the fires occur but also cause a greenhouse effect that has a profound impact on the natural environment in other parts of the world. Numerical simulations of greenhouse gas transport processes are often affected by uncertainties in the location and timing of the emission sources and local meteorological conditions, and it is difficult to obtain accurate and credible predictions by combining remote sensing satellite data with given meteorological forecasts or reanalyses. To study the regional transport processes and impacts of greenhouse gases produced by sudden large-scale forest fires, this study applies the Lagrangian particle dispersion model Massive-Parallel Trajectory Calculations (MPTRAC) to conduct forward simulations of the CO2 transport process of greenhouse gases emitted from forest fires in the central region of Saskatchewan, Canada, during the period of 17 May to 25 May 2021. The simulation results are validated with the Orbiting Carbon Observatory-2 Goddard Earth Observing System (OCO-2 GEOS) Level 3 daily gridded CO2 product over the study area. In order to leverage the high computational costs of the numerical simulations of the model, we implement the forward simulations on the Tianhe-2 supercomputer platform and the JUWELS HPC system, which greatly improves the computational efficiency through parallel computation and makes near-real-time predictions of atmospheric transport processes feasible. Full article
(This article belongs to the Special Issue High-Performance Computing for Atmospheric Modeling)
►▼ Show Figures

Figure 1

18 pages, 5756 KiB  
Article
Measurement and Analysis of Brake and Tyre Particle Emissions from Automotive Series Components for High-Load Driving Tests on a Wheel and Suspension Test Bed
by Martin Kupper, Ludwig Schubert, Manfred Nachtnebel, Hartmuth Schröttner, Michael Peter Huber, Peter Fischer and Alexander Bergmann
Atmosphere 2024, 15(4), 430; https://doi.org/10.3390/atmos15040430 - 29 Mar 2024
Viewed by 1123
Abstract
A current challenge in realising clean road transport is non-exhaust emissions. Important advances regarding measurement systems, including well-defined characterisation techniques, as well as regulation, will be made in the next few years. In this work, we present the detailed results of particle emission [...] Read more.
A current challenge in realising clean road transport is non-exhaust emissions. Important advances regarding measurement systems, including well-defined characterisation techniques, as well as regulation, will be made in the next few years. In this work, we present the detailed results of particle emission analyses, consisting of aerosol (size distribution, particle number (PN), and mass (PM)) and electron microscopy (EM) measurements, under different load conditions on a test bed for a wheel suspension and brakes. Standard tyres and brakes from serial production were tested with a high-load driving cycle, while particle measurements were conducted by gravimetric measurements and with a TSI SMPS, a TSI APS, and a GRIMM OPS. Furthermore, samples were analysed by electron microscopy. A bimodal particle size distribution (PSD) was obtained with an SMPS, with peaks at 20 nm and around 400 nm. The results of an EM analysis of >1400 single particles from the electrostatic sampler match the PSD results. The EM analysis also showed ultrafine particles, mainly containing O, Fe, Si, Ba, Mg, and S, and also fractal particles with high-C fractions. Our results suggest, in agreement with the previously published literature, that particulate emissions are related to the brake disc temperature and occur in significant amounts above a threshold temperature. Full article
(This article belongs to the Special Issue Transport Emissions and Their Environmental Impacts)
►▼ Show Figures

Figure 1

17 pages, 2456 KiB  
Article
Impact of Urban Forest and Park on Air Quality and the Microclimate in Jinan, Northern China
by Kun Liu, Juan Li, Lei Sun, Xueqiao Yang, Chongqing Xu and Guihuan Yan
Atmosphere 2024, 15(4), 426; https://doi.org/10.3390/atmos15040426 - 29 Mar 2024
Cited by 1 | Viewed by 1165
Abstract
Though the impact of urban vegetation on air quality and the microclimate has attracted increasing attention, there have been few studies quantitatively assessing this impact in North China, where air pollution is severe. In this study, we investigated the impact of urban forests [...] Read more.
Though the impact of urban vegetation on air quality and the microclimate has attracted increasing attention, there have been few studies quantitatively assessing this impact in North China, where air pollution is severe. In this study, we investigated the impact of urban forests and urban parks on air quality and the microclimate in Jinan, northern China. Six sites were chosen to represent urban forest, urban park, and downtown areas, respectively. The results indicate that urban forest can effectively reduce PM2.5 and ozone (O3) concentrations in the warm season, when temperatures are higher and plants are lush. The PM2.5 and O3 concentrations in the urban forest areas were 6.3–6.5 μg m−3 and 21–23 μg m−3 lower than those in downtown areas during the period of 10:00–15:00. In contrast, urban park areas can reduce PM2.5 concentrations but have little impact on gaseous pollutants such as nitrogen dioxide and O3. Furthermore, both urban forest and urban park areas reduced temperatures, by approximately 4.1–6.8 °C and 1.36 °C, respectively, and increased relative humidity, by about 13.4–12.9% and 0.9%, promoting a more comfortable thermal environment for residents. Therefore, this study highlights the crucial role of urban vegetation in improving air quality and creating a comfortable environment for residents. Full article
(This article belongs to the Special Issue The Role of Vegetation in Urban Air Quality)
►▼ Show Figures

Figure 1

20 pages, 3151 KiB  
Article
The Effects of Lockdown, Urban Meteorology, Pollutants, and Anomalous Diffusion on the SARS-CoV-2 Pandemic in Santiago de Chile
by Patricio Pacheco, Eduardo Mera and Gustavo Navarro
Atmosphere 2024, 15(4), 414; https://doi.org/10.3390/atmos15040414 - 26 Mar 2024
Viewed by 874
Abstract
A study was carried out in Santiago de Chile, located in a geographic basin, on the sustainability and diffusion of the recent SARS-CoV-2 pandemic. Hourly measurements were used (carried out for 3.25 years in seven communes of the city) to quantify the accumulated [...] Read more.
A study was carried out in Santiago de Chile, located in a geographic basin, on the sustainability and diffusion of the recent SARS-CoV-2 pandemic. Hourly measurements were used (carried out for 3.25 years in seven communes of the city) to quantify the accumulated sick (AS) population, urban meteorology variables (MVs) (temperature (T), relative humidity (RH), and magnitude of wind speed (WS)), and air pollution (P) (PM10, PM2.5, 03). Time series (TS) were constructed for each commune, which related AS to MVs, called AS/VM, and to P, noted AS/P. Chaos theory was applied to each TS, requiring the following variables: the Lyapunov exponent (λ > 0), the correlation dimension (DC < 5), Kolmogorov entropy (SK > 0), the Hurst exponent (H, such that 0 < H < 1), Lempel–Ziv complexity (LZ > 0), and information loss (<ΔI> < 0). Every TS complied with chaos theory. For each commune, CK was calculated as a quotient between the sum of AS/T, AS/WS, and AS/RH entropies and the sum of AS/PM10, AS/PM2.5, and AS/O3 entropies. The results show that the entropy for the AS/P ratio is lower than that of the AS/VM ratio in three of the seven communes, since between 2020 and early 2022, the population was confined, reducing pollution. The TS of the AS/P ratio is more persistent and complex. The predictability times of the ratios are comparable in four of the seven communes. The TS of the AS/MV ratios shows greater information loss and chaos. According to the calculated CK values, it is possible to relate it to anomalous diffusion (sub/super-diffusion) and the context that favored the expansion of the pandemic: urban densification, pollution, urban meteorology, population density, etc. Using Fréchet heavy-tailed probability, the compatibility of the results with CK is verified. Full article
(This article belongs to the Section Biometeorology and Bioclimatology)
►▼ Show Figures

Figure 1

0 pages, 2081 KiB  
Article
Considering the Size Distribution of Elements in Particle Matter and Oxidation Potential: Association before and after Respiratory Exposure
by Xing Li, Tingting Xu and Ying Guo
Atmosphere 2024, 15(4), 411; https://doi.org/10.3390/atmos15040411 - 26 Mar 2024
Viewed by 989
Abstract
Oxidation potential (OP), reflecting the redox activities of particle matter (PM), is considered an optimal measure to explain the biological effects of PM exposure. However, the size resolution of the relationship between OP and chemical composition in PM, especially how the relationship changes [...] Read more.
Oxidation potential (OP), reflecting the redox activities of particle matter (PM), is considered an optimal measure to explain the biological effects of PM exposure. However, the size resolution of the relationship between OP and chemical composition in PM, especially how the relationship changes after respiratory exposure, has not been well investigated. In this study, size-resolved indoor PM10 samples were collected from a waste recycling plant from November to December 2021 using an Anderson eight-stage cascade impactor. OP, measured by a dithiothreitol (DTT) assay (defined as OPDTT), and elements, determined by inductively coupled plasma–mass spectrometry (ICP-MS) in size-resolved PM, were determined to check their relationships and the related human exposure risk. The results indicated that compared with PM0.4 and PM0.4–2.1, PM2.1–10 contributed the most to total OPDTT and its bound elements contributed the most to potential health risks, both before and after respiratory exposure. The association between OPDTT and the elements varied with PM size. Pearson correlation analysis showed that the PM0.4- and PM0.4–2.1-bound elements were moderate-to-strongly positively correlated with OPvDTT (r: 0.60–0.90). No significant correlation or dose–response relationship was found in PM2.1–10. After respiratory exposure, several PM0.4- and PM0.4–2.1-bound elements had a moderate-to-strongly positive correlation with deposition fluxes of OP (defined as OPFlux) (0.69–0.90). A generalized linear model analysis showed that the interquartile range (IQR) increase in the PM-bound elements (ng h−1) was associated with a 41.7–58.1% increase in OPFlux. Our study is a special case that enriches the knowledge of the association between OPDTT and the chemical composition of PM of different sizes, especially after respiratory exposure, but the generalizability of the findings to other settings or types of PM may be limited. The associations among OPDTT, other chemical compositions of PM, and human exposure risk merit further research. Full article
(This article belongs to the Special Issue Composition Analysis and Health Effects of Atmospheric Particulate Matter)
►▼ Show Figures

Figure 1

9 pages, 2444 KiB  
Opinion
Is Recent Warming Exceeding the Range of the Past 125,000 Years?
by Jan Esper, Philipp Schulz and Ulf Büntgen
Atmosphere 2024, 15(4), 405; https://doi.org/10.3390/atmos15040405 - 25 Mar 2024
Cited by 1 | Viewed by 1812
Abstract
The Intergovernmental Panel on Climate Change (IPCC) concluded that the latest decade was warmer than any multi-century period over the past 125,000 years. This statement rests on a comparison of modern instrumental measurements against the course of past temperatures reconstructed from natural proxy [...] Read more.
The Intergovernmental Panel on Climate Change (IPCC) concluded that the latest decade was warmer than any multi-century period over the past 125,000 years. This statement rests on a comparison of modern instrumental measurements against the course of past temperatures reconstructed from natural proxy archives, such as lake and marine sediments, and peat bogs. Here, we evaluate this comparison with a focus on the hundreds of proxy records developed by paleoclimatologists across the globe to reconstruct climate variability over the Holocene (12,000 years) and preceded by the Last Glacial Period (125,000 years). Although the existing proxy data provide a unique opportunity to reconstruct low-frequency climate variability on centennial timescales, they lack temporal resolution and dating precision for contextualizing the most recent temperature extremes. While the IPCC’s conclusion on the uniqueness of latest-decade warming is thus not supported by comparison with these smoothed paleotemperatures, it is still likely correct as ice core-derived forcing timeseries show that greenhouse gases were not elevated during any pre-instrumental period of the Holocene. Full article
(This article belongs to the Section Climatology)
►▼ Show Figures

Figure 1

20 pages, 6050 KiB  
Article
Improving the Estimation of PM2.5 Concentration in the North China Area by Introducing an Attention Mechanism into Random Forest
by Luo Zhang, Zhengqiang Li, Jie Guang, Yisong Xie, Zheng Shi, Haoran Gu and Yang Zheng
Atmosphere 2024, 15(3), 384; https://doi.org/10.3390/atmos15030384 - 20 Mar 2024
Viewed by 1171
Abstract
Fine particulate matter with an aerodynamic diameter less than 2.5 µm (PM2.5) profoundly affects environmental systems, human health and economic structures. Multi-source data and advanced machine or deep-learning methods have provided a new chance for estimating the [...] Read more.
Fine particulate matter with an aerodynamic diameter less than 2.5 µm (PM2.5) profoundly affects environmental systems, human health and economic structures. Multi-source data and advanced machine or deep-learning methods have provided a new chance for estimating the PM2.5 concentrations at a high spatiotemporal resolution. In this paper, the Random Forest (RF) algorithm was applied to estimate hourly PM2.5 of the North China area (Beijing–Tianjin–Hebei, BTH) based on the next-generation geostationary meteorological satellite Himawari-8/AHI (Advanced Himawari Imager) aerosol optical depth (AOD) products. To improve the estimation of PM2.5 concentration across large areas, we construct a method for co-weighting the environmental similarity and the geographical distances by using an attention mechanism so that it can efficiently characterize the influence of spatial–temporal information hidden in adjacent ground monitoring sites. In experiment results, the hourly PM2.5 estimates are well correlated with ground measurements in BTH, with a coefficient of determination (R2) of 0.887, a root-mean-square error (RMSE) of 18.31 μg/m3, and a mean absolute error (MAE) of 11.17 µg/m3, indicating good model performance. In addition, this paper makes a comprehensive analysis of the effectiveness of multi-source data in the estimation process, in this way, to simplify the model structure and improve the estimation efficiency of the model while ensuring its accuracy. Full article
(This article belongs to the Special Issue Advances in Integrated Air Quality Management: Emissions, Monitoring, Modelling (3rd Edition))
►▼ Show Figures

Figure 1

22 pages, 1756 KiB  
Article
Regionalization of the Onset and Offset of the Rainy Season in Senegal Using Kohonen Self-Organizing Maps
by Dioumacor Faye, François Kaly, Abdou Lahat Dieng, Dahirou Wane, Cheikh Modou Noreyni Fall, Juliette Mignot and Amadou Thierno Gaye
Atmosphere 2024, 15(3), 378; https://doi.org/10.3390/atmos15030378 - 20 Mar 2024
Viewed by 1242
Abstract
This study explores the spatiotemporal variability of the onset, end, and duration of the rainy season in Senegal. These phenological parameters, crucial for agricultural planning in West Africa, exhibit high interannual and spatial variability linked to precipitation. The objective is to detect and [...] Read more.
This study explores the spatiotemporal variability of the onset, end, and duration of the rainy season in Senegal. These phenological parameters, crucial for agricultural planning in West Africa, exhibit high interannual and spatial variability linked to precipitation. The objective is to detect and spatially classify these indices across Senegal using different approaches. Daily precipitation data and ERA5 reanalyses from 1981 to 2018 were utilized. The employed method enables the detection of key dates. Subsequently, the Kohonen algorithm spatially classifies these indices on topological maps. The results indicate a meridional gradient of the onset, progressively later from the southeast to the northwest, whereas the end follows a north–south gradient. The duration varies from 45 days in the north to 150 days in the south. The use of self-organizing maps allows for classifying the onset, end, and duration of the season into four zones for the onset and end, and three zones for the duration of the season. They highlight the interannual irregularity of transitions, with both early and late years. The dynamic analysis underscores the complex influence of atmospheric circulation fields, notably emphasizing the importance of low-level monsoon flux. These findings have tangible implications for improving seasonal forecasts and agricultural activity planning in Senegal. They provide information on the onset, end, and duration classes for each specific zone, which can be valuable for planning crops adapted to each region. Full article
(This article belongs to the Special Issue Statistical Approaches in Climatic Parameters Prediction)
►▼ Show Figures

Figure 1

15 pages, 2726 KiB  
Article
Time Series Analysis of the Impact of Meteorological Conditions and Air Quality on the Number of Medical Visits for Hypertension in Haikou City, China
by Mingjie Zhang, Yajie Zhang, Jinghong Zhang and Shaowu Lin
Atmosphere 2024, 15(3), 370; https://doi.org/10.3390/atmos15030370 - 18 Mar 2024
Viewed by 1051
Abstract
Meteorological conditions and air quality are important environmental factors in the occurrence and development of cardiovascular diseases (CVDs) such as hypertension. The aim of this study was to take Haikou City, located on the tropical edge, as the research area and to analyze [...] Read more.
Meteorological conditions and air quality are important environmental factors in the occurrence and development of cardiovascular diseases (CVDs) such as hypertension. The aim of this study was to take Haikou City, located on the tropical edge, as the research area and to analyze the exposure–response relationship and lag effect between its meteorological conditions, air quality, and the number of hypertensive patients. Using the data from the hypertension outpatient department of Hainan Provincial People’s Hospital from 2016 to 2018, together with meteorological data and air quality data, a distributed lag nonlinear model based on the nested generalized addition model of meteorological element base variables was established. The results showed that the impact of temperature on the risk of hypertension was mainly due to the cold effect, which was associated with high risk, with a lag of 1–10 days. When the temperature dropped to 10 °C, the cumulative effect on the risk of hypertension of relative risk (RR) reached its highest value on the day the low temperature occurred (RR was 2.30 and the 95% confidence interval was 1.723~3.061), passing the test with a significance level of 0.05. This result indicated that efforts should be made to strengthen the prevention of hypertension under low-temperature conditions and the prediction and early warning of disease risks. The impact of the air-quality effect (the environmental Air Quality Index was selected as an indicator) on the risk of hypertension was mainly characterized by a low air-quality effect, with a lag effect of 0–8 days. When the risk reached approximately 124, the RR was highest (RR was 1.63 and the 95% confidence interval was 1.104~2.408), passing the test with a significance level of 0.05. The research results can provide technical support for conducting medical meteorological forecasting, early warning, and services for hypertension. A joint work and research mechanism among multiple departments such as meteorology and medical health should be established to improve the level of medical and health care, optimize the allocation of social resources, and develop targeted prevention and control strategies to reduce the health and economic burden of hypertension. Full article
(This article belongs to the Section Biometeorology and Bioclimatology)
►▼ Show Figures

Figure 1

21 pages, 5495 KiB  
Article
Assessment of Water Resources under Climate Change in Western Hindukush Region: A Case Study of the Upper Kabul River Basin
by Tooryalay Ayoubi, Christian Reinhardt-Imjela and Achim Schulte
Atmosphere 2024, 15(3), 361; https://doi.org/10.3390/atmos15030361 - 16 Mar 2024
Cited by 1 | Viewed by 1525
Abstract
This study aims to estimate the surface runoff and examine the impact of climate change on water resources in the Upper Kabul River Basin (UKRB). A hydrological model was developed using the Soil and Water Assessment Tool (SWAT) from 2009 to 2019. The [...] Read more.
This study aims to estimate the surface runoff and examine the impact of climate change on water resources in the Upper Kabul River Basin (UKRB). A hydrological model was developed using the Soil and Water Assessment Tool (SWAT) from 2009 to 2019. The monthly calibration was conducted on streamflow in six stations for the period from 2010 to 2016, and the results were validated from 2017 to 2018 based on available observed data. The hydrological sensitivity parameters were further prioritized using SWAT-CUP. The uncertainty of the model was analyzed by the 95% Prediction Uncertainty (95PPU). Future projections were analyzed for the 2040s (2030–2049) and 2090s (2080–2099) compared to the baseline period (1986–2005) under two representation concentration pathways (RCP4.5, RCP8.5). Four Regional Climate Models (RCMs) were bias-corrected using the linear scaling bias correction method. The modeling results exhibited a very reasonable fit between the estimated and observed runoff in different stations, with NS values ranging from 0.54 to 0.91 in the calibration period. The future mean annual surface runoff exhibited an increase in the 2040s and 2090s compared to the baseline under both RCPs of 4.5 and 8.5 due to an increase in annual precipitation. The annual precipitation is projected to increase by 5% in the 2040s, 1% in the 2090s under RCP4.5, and by 9% in the 2040s and 2% in the 2090s under RCP8.5. The future temperature is also projected to increase and consequently lead to earlier snowmelt, resulting in a shift in the seasonal runoff peak to earlier months in the UKRB. However, the shifts in the timing of runoff could lead to significant impacts on water availability and exacerbate the water stress in this region, decreasing in summer runoff and increasing in the winter and spring runoffs. The future annual evapotranspiration is projected to increase under both scenarios; however, decreases in annual snowfall, snowmelt, sublimation, and groundwater recharge are predicted in the UKRB. Full article
(This article belongs to the Special Issue The Impact of Climate Change on Water Resources)
►▼ Show Figures

Figure 1

11 pages, 857 KiB  
Review
A Comprehensive Review of Assessing Storm Surge Disasters: From Traditional Statistical Methods to Artificial Intelligence-Based Techniques
by Yuxuan Zhang and Tianyu Zhang
Atmosphere 2024, 15(3), 359; https://doi.org/10.3390/atmos15030359 - 15 Mar 2024
Viewed by 1861
Abstract
In the context of global climate change and rising sea levels, the adverse impacts of storm surges on the environment, economy, and society of affected areas are becoming increasingly significant. However, due to differences in geography, climate, and other conditions among the affected [...] Read more.
In the context of global climate change and rising sea levels, the adverse impacts of storm surges on the environment, economy, and society of affected areas are becoming increasingly significant. However, due to differences in geography, climate, and other conditions among the affected areas, a single method for assessing the risk of storm surge disasters cannot be fully applicable to all regions. To address this issue, an increasing number of new methods and models are being applied in the field of storm surge disaster risk assessment. This paper introduces representative traditional statistical methods, numerical simulation methods, and artificial intelligence-based techniques in this field. It compares these assessment methods in terms of accuracy, interpretability, and implementation difficulty. The paper emphasizes the importance of selecting appropriate assessment methods based on specific conditions and scientifically combining various methods in practice to improve the accuracy and reliability of storm surge disaster risk assessments. Full article
(This article belongs to the Special Issue Coastal Hazards and Climate Change)
►▼ Show Figures

Figure 1

15 pages, 661 KiB  
Article
Comparison of Exposure to Pb and Mn Levels by Using Environmental Personal Monitors and Biomarkers in Relation to Cognitive and Motor Function
by Miguel Santibáñez, Laura Ruiz-Azcona, Andrea Expósito, Bohdana Markiv and Ignacio Fernández-Olmo
Atmosphere 2024, 15(3), 350; https://doi.org/10.3390/atmos15030350 - 13 Mar 2024
Viewed by 1083
Abstract
We conducted a cross-sectional study of 130 participants living near a ferromanganese alloy plant, analyzing Pb and Mn exposure by biomarkers (blood, hair, and fingernails) and particulate matter personal environmental monitors (PEMs). Cognitive and motor function were assessed by five and three tests, [...] Read more.
We conducted a cross-sectional study of 130 participants living near a ferromanganese alloy plant, analyzing Pb and Mn exposure by biomarkers (blood, hair, and fingernails) and particulate matter personal environmental monitors (PEMs). Cognitive and motor function were assessed by five and three tests, respectively. Mean differences (MDs) adjusted for age, sex, and study level were determined. In addition, MDs for Pb were adjusted for Mn levels and vice versa. Medians of 9.14 µg/L, 149.04 ng/g, and 96.04 ng/g were obtained for blood, scalp hair, and fingernails Pb levels, respectively. Regarding PEMs, median Pb levels were 6.56 ng/m3 for the fine fraction and, for the coarse fraction, they were below the limit of detection in 97% of participants. Exposure to Pb at low levels was not associated with worse cognitive function. In comparison, exposure to high levels of Mn was associated with worse cognitive function at least in the domains evaluated through Stroop, Digit Span, and Verbal Fluency tests. In terms of motor function, our results suggest that even the currently low Pb levels may have negative health effects on dynamometer-determined strength—adjusted MD on dominant hand = −2.68; 95%CI (−4.85 to −0.51), p = 0.016. Further studies should investigate this association. Full article
(This article belongs to the Special Issue Biomonitoring—an Effective Tool for Air Pollution Assessment (2nd Edition))
►▼ Show Figures

Figure 1

13 pages, 3381 KiB  
Article
Lidar Observations of the Fe Layer in the Mesopause and Lower Thermosphere over Beijing (40.5° N, 116.0° E) and Mohe (53.5° N, 122.4° E)
by Kexin Wang, Zelong Wang, Yuxuan Wu, Lifang Du, Haoran Zheng, Jing Jiao, Fang Wu, Yuchang Xun and Yuan Xia
Atmosphere 2024, 15(3), 344; https://doi.org/10.3390/atmos15030344 - 12 Mar 2024
Viewed by 1012
Abstract
Lidar observations of metal layers play a significant role in research on the chemistry and dynamics of the mesosphere and lower thermosphere. This work reports on Fe lidar observations conducted in Beijing and Mohe. Utilizing the same laser emission system, a 1064 nm [...] Read more.
Lidar observations of metal layers play a significant role in research on the chemistry and dynamics of the mesosphere and lower thermosphere. This work reports on Fe lidar observations conducted in Beijing and Mohe. Utilizing the same laser emission system, a 1064 nm seed laser was injected into an Nd: YAG laser to generate a single longitudinal-mode pulse 532 nm laser, which pumped a dye laser to produce a 572 nm laser. The 572 nm laser and the remaining 1064 nm fundamental frequency laser passed through a sum–frequency module to generate a 372 nm laser to detect the Fe layer. According to a total of 52.6 h of observations for 10 nights in Beijing, the Fe layer has an average column density of 1.24 × 1010 cm−2, an RMS width of 4.4 km and a centroid altitude of 89.4 km. In Mohe, observed for 16 nights and a total of 91.5 h, the Fe layer has an average column density of 1.08 × 1010 cm−2, an RMS width of 4.6 km and a centroid altitude of 89.5 km. The probability of the occurrence of sporadic Fe layers was 42.4% in Beijing and 29.4% in Mohe. Compared to simultaneously observed Na layers, the occurrence probabilities of sporadic Fe layers were higher than those of sporadic Na layers in both stations. Based on the two cases observed in Beijing, it is conjectured that the formation mechanism of sporadic metal layers above approximately 100 km has a more significant influence on sporadic Fe layers than on sporadic Na layers. The lower thermospheric Fe layers with densities significantly larger than those of the main layer were observed during two nights in Mohe. This work contributes to the refinement of the global distribution of Fe layers and provides abundant observational data for the modeling and study of the metal layers. Full article
(This article belongs to the Special Issue Advances in Lidar Remote Sensing Research in the Middle and Upper Atmosphere)
►▼ Show Figures

Figure 1

16 pages, 1432 KiB  
Article
An Assessment of the GLE Alert++ Warning System
by Helen Mavromichalaki, Pavlos Paschalis, Maria Gerontidou, Anastasia Tezari, Maria-Christina Papailiou, Dimitra Lingri, Maria Livada, Argyris Stassinakis, Norma Crosby and Mark Dierckxsens
Atmosphere 2024, 15(3), 345; https://doi.org/10.3390/atmos15030345 - 12 Mar 2024
Cited by 3 | Viewed by 937
Abstract
Over the last years the Athens Cosmic Ray Group of the National & Kapodistrian University of Athens has implemented a warning tool called GLE Alert, which is a highly credible application that issues alerts when a ground level enhancement (GLE) starts due to [...] Read more.
Over the last years the Athens Cosmic Ray Group of the National & Kapodistrian University of Athens has implemented a warning tool called GLE Alert, which is a highly credible application that issues alerts when a ground level enhancement (GLE) starts due to very high energy solar energetic particles reaching the Earth. This application warns of a high intensity solar energetic particle event up to several minutes before it reaches near the near-Earth space environment. In this work, an assessment of the latest updated version of GLE Alert, GLE Alert++, is presented. GLE Alert++ is a federated product of the ESA S2P SWE Space Radiation Expert Service Centre, which is part of the ESA Space WEather Service NETwork (SWESNET) project. The assessment of the GLE Alert++, which was finalized in October 2022, focused on: (a) the availability of the real-time data provided by the neutron monitor stations that contribute to the GLE Alert++, (b) the behaviour of each station regarding the different Alert levels status (Watch, Warning and Alert), and (c) the definition of the real-time assessment index. The results of this work are of essential importance since they ensure a reliable and trustworthy warning tool, and can be highly useful in protecting humans during extreme solar energetic events. Full article
(This article belongs to the Section Upper Atmosphere)
►▼ Show Figures

Figure 1

22 pages, 15666 KiB  
Article
Adaptability of Prunus cerasifera Ehrh. to Climate Changes in Multifunctional Landscape
by Djurdja Petrov, Mirjana Ocokoljić, Nevenka Galečić, Dejan Skočajić and Isidora Simović
Atmosphere 2024, 15(3), 335; https://doi.org/10.3390/atmos15030335 - 8 Mar 2024
Cited by 1 | Viewed by 1044
Abstract
Urban trees play a vital role in mitigating climate changes, maintaining the sustainability of ecosystems. This study focuses on the assessment of the resilience of cherry plums to climate changes, a fruit-bearing species that offers diverse ecosystem services within multifunctional urban and suburban [...] Read more.
Urban trees play a vital role in mitigating climate changes, maintaining the sustainability of ecosystems. This study focuses on the assessment of the resilience of cherry plums to climate changes, a fruit-bearing species that offers diverse ecosystem services within multifunctional urban and suburban landscapes. This study examines flowering and fruiting in the context of climate characteristics, expressed through the Day of the Year (DOY), Growing Degree Days (GDDs), and a yield over 17 consecutive years. The results indicate significant shifts in the DOY but not in the GDD, apart from the end of flowering. The onset of flowering was earlier and the end postponed, extending the phenophase by an average of 4 days. The cherry plum’s yield was unaffected by climate changes, including extreme events like a late-spring frost. The stability of the cherry plum was confirmed by the phenological patterns of the bullace (cherry plum and blackthorn hybrid) exhibiting repeated flowering in the warmest year of 2023. The cherry plum is an adaptive species, with a high adaptability to a changing climate and a high resistance to late-spring frosts; thus, it is a favorable choice in urban design and planning, demonstrating resilience to climate shifts and thriving in polluted urban environments. It is especially appreciated for multiple ecosystem services: biodiversity conservation in natural and semi-natural areas, yielding good provisions in challenging environments, and the preservation of ornamental values through an extended flowering phenophase. Full article
(This article belongs to the Special Issue Climate Change Impacts and Adaptation Strategies in Agriculture)
►▼ Show Figures

Figure 1

21 pages, 7267 KiB  
Article
Exposure to PM2.5 on Public Transport: Guidance for Field Measurements with Low-Cost Sensors
by Kyriaki-Maria Fameli, Konstantinos Moustris, Georgios Spyropoulos and Dimitrios-Michael Rodanas
Atmosphere 2024, 15(3), 330; https://doi.org/10.3390/atmos15030330 - 7 Mar 2024
Cited by 1 | Viewed by 1060
Abstract
Air pollution is one of the most important problems in big cities, resulting in adverse health effects. The aim of the present study was to characterize the personal exposure to indoor and outdoor pollution in the Greater Athens Area in Greece by taking [...] Read more.
Air pollution is one of the most important problems in big cities, resulting in adverse health effects. The aim of the present study was to characterize the personal exposure to indoor and outdoor pollution in the Greater Athens Area in Greece by taking measurements during a journey from suburban to mixed industrial–urban areas, encompassing walking, waiting, bus travel, and metro travel at various depths. For this reason, low-cost (LC) sensors were used, and the inhaled dose of particulate matter with an aerodynamic diameter of less than or equal to 2.5 μm (PM2.5) in different age groups of passengers was calculated. Specific bus routes and the Athens metro network were monitored throughout different hours of the day. Then, the average particulate matter (PM2.5) exposure for a metro passenger was calculated and evaluated. By considering the ventilation rate of a passenger, an estimation of the total PM2.5 inhaled dose for males and females as well as for different age groups was made. The results showed that the highest PM2.5 concentrations were observed inside the wagons with significant increases during rush hours or after rush hours. Furthermore, there should be a concern regarding older individuals using the subway network in Athens during rush hours and in general for sensitive groups (people with asthma, respiratory and cardiovascular problems, etc.). Full article
(This article belongs to the Special Issue Composition Analysis and Health Effects of Atmospheric Particulate Matter)
►▼ Show Figures

Figure 1

17 pages, 6456 KiB  
Article
Correlation of Rate of TEC Index and Spread F over European Ionosondes
by Krishnendu Sekhar Paul, Mehdi Hasan Rafi, Haris Haralambous and Mohammad Golam Mostafa
Atmosphere 2024, 15(3), 331; https://doi.org/10.3390/atmos15030331 - 7 Mar 2024
Viewed by 1814
Abstract
One of the most popular indices for monitoring the occurrence and intensity of ionospheric L-band irregularities is the Rate of TEC Index (ROTI). Due to low TEC in the mid-latitude ionosphere, ROTI has received significantly less attention than the equatorial and polar ionosphere. [...] Read more.
One of the most popular indices for monitoring the occurrence and intensity of ionospheric L-band irregularities is the Rate of TEC Index (ROTI). Due to low TEC in the mid-latitude ionosphere, ROTI has received significantly less attention than the equatorial and polar ionosphere. On the other hand, spread F is an established ionogram irregularity signature. The present study aims to correlate ROTI and spread F activity over European Digisonde stations for a low-to-moderate solar activity year (2011). With a focus on the latitude-dependent occurrence, the analysis demonstrates that range spread F (RSF) has been identified for all notable ROTI (>0.15 TECU/min) cases which also coincide with MSTID activity over the stations, suggesting induced gravity waves or polarization electric fields as the driving mechanism for enhanced ROTI activity. The diurnal and seasonal features are also presented. Maximum irregularity occurrence was observed around the 45° N from 18:00 to 05:00 UT with the seasonal maximum occurrence in January. Over lower mid-latitude Digisonde stations (latitude < 45° N), the diurnal and seasonal occurrence was observed from 19:00 to 04:30 UT in July. Full article
(This article belongs to the Special Issue Ionospheric Irregularity)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying article 51-100 on page 2 of 13.

Go to page    chevron_left 1 2 3 4 5 chevron_right last_page
Back to TopTop