Journal Description
Atmosphere
Atmosphere
is an international, peer-reviewed, open access journal of scientific studies related to the atmosphere published monthly online by MDPI. The Italian Aerosol Society (IAS) and Working Group of Air Quality in European Citizen Science Association (ECSA) are affiliated with Atmosphere and their members receive a discount on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), Ei Compendex, GEOBASE, GeoRef, Inspec, CAPlus / SciFinder, Astrophysics Data System, and other databases.
- Journal Rank: CiteScore - Q2 (Environmental Science (miscellaneous))
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 17.7 days after submission; acceptance to publication is undertaken in 2.8 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
- Testimonials: See what our editors and authors say about the Atmosphere.
- Companion journal: Meteorology.
Impact Factor:
2.9 (2022);
5-Year Impact Factor:
3.0 (2022)
Latest Articles
Assessing the Accuracy of 50 Temperature-Based Models for Estimating Potential Evapotranspiration (PET) in a Mediterranean Mountainous Forest Environment
Atmosphere 2024, 15(6), 662; https://doi.org/10.3390/atmos15060662 (registering DOI) - 30 May 2024
Abstract
Potential evapotranspiration (PET) is a crucial parameter for forest development, having an important role in ecological, biometeorological, and hydrological assessments. Accurate estimations of PET using the FAO–56 Penman–Monteith (FAO–56 PM) benchmark method require a wide range of data parameters, which are not typically
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Potential evapotranspiration (PET) is a crucial parameter for forest development, having an important role in ecological, biometeorological, and hydrological assessments. Accurate estimations of PET using the FAO–56 Penman–Monteith (FAO–56 PM) benchmark method require a wide range of data parameters, which are not typically available at meteorological stations installed in forest environments. The aim of this study is to investigate the accuracy of various methods with low data requirements for assessing PET in a Mediterranean forest environment and propose appropriate alternatives for accurate PET estimation. Specifically, 50 temperature-based methods were evaluated against the FAO–56 PM method in a sub-humid forest in northern Greece, using high-quality daily meteorological data. The outcomes indicate that temperature-based methods offer a viable alternative for PET estimation when data availability is limited, with a considerable number of methods (22) presenting low deviations (up to 10%) compared to the benchmark method. Temperature-based models outperformed those incorporating water-related parameters (as relative humidity or precipitation) in Mediterranean forest environments. The top performing methods in the study site, based on several statistical indices, were the equations of Ravazzani et al., proposed in 2012, followed by Hargreaves–Samani in 1985 and Heydari and Heydari in 2014.
Full article
(This article belongs to the Section Biosphere/Hydrosphere/Land–Atmosphere Interactions)
Open AccessArticle
Five Large 13th Century C.E. Volcanic Eruptions Recorded in Antarctica Ice Cores
by
Jihong Cole-Dai, Derek L. Brandis and Dave G. Ferris
Atmosphere 2024, 15(6), 661; https://doi.org/10.3390/atmos15060661 (registering DOI) - 30 May 2024
Abstract
Major explosive volcanic eruptions impact the climate by altering the radiative balance of the atmosphere and through feedback mechanisms in the climate system. The extent of the impact depends on the magnitude (aerosol mass loading) and the number or frequency of such eruptions.
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Major explosive volcanic eruptions impact the climate by altering the radiative balance of the atmosphere and through feedback mechanisms in the climate system. The extent of the impact depends on the magnitude (aerosol mass loading) and the number or frequency of such eruptions. Multiple Antarctica ice core records of past volcanic eruptions reveal that the number (5) of major eruptions (volcanic sulfate deposition flux greater than 10 kg km−2) was the highest in the 13th century over the last two millennia. Signals of four of the five eruptions are dated to the second half of the century, indicating consecutive major eruptions capable of causing sustained climate impact via known feedback processes. The fact that signals of four corresponding eruptions have been found in a Greenland ice core indicates that four of the five 13th century eruptions were probably by volcanoes in the low latitudes (between 20° N and 20° S) with substantial aerosol mass loading. These eruptions in the low latitudes likely exerted the strongest volcanic impact on climate in the last two millennia.
Full article
(This article belongs to the Special Issue Impact of Volcanic Eruptions on the Atmosphere)
Open AccessArticle
Seasonal Cycle of Southern Hemisphere Explosive Growth and Decay of Storms
by
Stacey L. Osbrough and Jorgen S. Frederiksen
Atmosphere 2024, 15(6), 660; https://doi.org/10.3390/atmos15060660 (registering DOI) - 30 May 2024
Abstract
The seasonal variability of Southern Hemisphere (SH) synoptic-scale weather systems is analysed for the 20-year timespan 1997 to 2016. The relationships between the SH jet streams and storm tracks based on lower tropospheric circulation anomalies filtered into the high-pass (periods < 4 days)
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The seasonal variability of Southern Hemisphere (SH) synoptic-scale weather systems is analysed for the 20-year timespan 1997 to 2016. The relationships between the SH jet streams and storm tracks based on lower tropospheric circulation anomalies filtered into the high-pass (periods < 4 days) and band-pass (periods between 4 and 8 days) types are examined based on 6-hourly reanalysis data. Leading Empirical Orthogonal Functions (EOFs) and storm tracks based on all (growing and decaying) disturbances are determined. As well, the structure and standard deviations of streamfunction fluctuations are determined separately in three growth rate and three decay rate bins focusing on explosive growth and decay. In all cases, and in each season, the band-pass storm tracks are more zonally symmetric than the high-pass standard deviations and this is also reflected by the EOFs. Leading EOFs in both bands are monopole wavetrains of highs and lows located in the storm tracks with some band-pass disturbances having dipole structures consistent with blocking and northwest cloud bands. EOFs based on the bin with slow-growing fluctuations are structurally similar to the standard EOFs based on all disturbances. EOFs for moderately and explosively growing disturbances are increasingly displaced equatorward with a larger growth rate.
Full article
(This article belongs to the Section Climatology)
Open AccessArticle
Assessing the Air Pollution Tolerance Index of Urban Plantation: A Case Study Conducted along High-Traffic Roadways
by
Zunaira Asif and Wen Ma
Atmosphere 2024, 15(6), 659; https://doi.org/10.3390/atmos15060659 (registering DOI) - 30 May 2024
Abstract
Road transport and traffic congestion significantly contribute to dust pollution, which negatively impacts the growth of roadside plants in urban areas. This study aims to quantify the air pollution tolerance index (APTI) and analyze the impacts of dust deposition on different plant species
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Road transport and traffic congestion significantly contribute to dust pollution, which negatively impacts the growth of roadside plants in urban areas. This study aims to quantify the air pollution tolerance index (APTI) and analyze the impacts of dust deposition on different plant species and trees planted along a busy urban roadside in Lahore, Pakistan by considering seasonal variations. The APTI of each species is determined based on inputs of various biochemical parameters (leaf extract pH, ascorbic acid content, relative water content, and total chlorophyll levels), including dust deposition. In this study, laboratory analysis techniques are employed to assess these factors in selected plant species such as Mangifera indica, Saraca asoca, Cassia fistula, and Syzygium cumini. A statistical analysis is conducted to understand the pairwise correlation between various parameters and the APTI at significant and non-significant levels. Additionally, uncertainties in the inputs and APTI are addressed through a probabilistic analysis using the Monte Carlo simulation method. This study unveils seasonal variations in key parameters among selected plant species. Almost all biochemical parameters exhibit higher averages during the rainy season, followed by the summer and winter. Conversely, dust deposition on plants follows an inverse trend, with values ranging from 0.19 to 4.8 g/cm2, peaking during winter, notably in Mangifera indica. APTI values, ranging from 9.39 to 14.75, indicate varying sensitivity levels across species, from sensitive (Syzygium cumini) to intermediate tolerance (Mangifera indica). Interestingly, plants display increased tolerance during regular traffic hours, reflecting a 0.9 to 5% difference between the APTI at peak and regular traffic hours. Moreover, a significant negative correlation (−0.86 at p < 0.05 level) between APTI values and dust deposition suggests a heightened sensitivity to pollutants during the winter. These insights into the relationship between dust pollution and plant susceptibility will help decision makers in the selection of resilient plants for urban areas and improve air quality.
Full article
(This article belongs to the Special Issue Air Pollution in Asia)
Open AccessArticle
Simulation and Diagnosis of Physical Precipitation Process of Local Severe Convective Rainstorm in Ningbo
by
Tingting Lu, Yeyi Ding, Zan Liu, Fan Wu, Guoqiang Xue, Chengming Zhang and Yuan Fu
Atmosphere 2024, 15(6), 658; https://doi.org/10.3390/atmos15060658 (registering DOI) - 30 May 2024
Abstract
On 31 July 2021, Ningbo, an eastern coast city in China, experienced a severe convective rainstorm, characterized by intense short-duration precipitation extremes with a maximum rainfall rate of 130 mm h−1. In this research, we first analyzed this rainstorm using Doppler
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On 31 July 2021, Ningbo, an eastern coast city in China, experienced a severe convective rainstorm, characterized by intense short-duration precipitation extremes with a maximum rainfall rate of 130 mm h−1. In this research, we first analyzed this rainstorm using Doppler radar and precipitation observation and then conducted high-resolution simulation for it. A three-dimensional precipitation diagnostic equation is introduced to quantitatively analyze the microphysical processes during the rainstorm. It is shown that this rainstorm was triggered and developed locally in central Ningbo under favorable large-scale quasi-geostrophic conditions and local conditions. In the early stage, the precipitation increase is mainly driven by the strong convergence of water vapor, and a noticeable increase in both the intensity and spatial extent of uplift promotes the upward transportation of water vapor. As the water vapor flux and associated convergence weaken in the later stage, the precipitation reduces accordingly. Cloud microphysical processes are also important in the entire precipitation process. The early stage updraft supports the escalations in raindrops, with the notable fluctuations in raindrop concentrations directly linked to variations in ground precipitation intensity. The behavior of graupel particles is intricately connected to their melting as they fall below the zero-degree layer. Although cloud water and snow exhibit changes during this period, the magnitudes of these adjustments are considerably less pronounced than those in raindrops and graupels, highlighting the differentiated response of various condensates to the convective dynamics. These results can help deepen the understanding of local severe rainstorms and provide valuable scientific references for practical forecasting.
Full article
(This article belongs to the Special Issue Characteristics of Extreme Climate Events over China)
Open AccessArticle
Agroclimatic Indicators for Grapevines in the Zielona Góra Wine Region (Poland) in the Era of Advancing Global Warming
by
Dominika Jaster, Arkadiusz Marek Tomczyk, Iwona Hildebrandt-Radke and Paweł Matulewski
Atmosphere 2024, 15(6), 657; https://doi.org/10.3390/atmos15060657 (registering DOI) - 30 May 2024
Abstract
Grapevine is a highly climate-sensitive plant. In the last few decades, an increase in the number and area of vineyards has been observed in the country, with the Zielona Góra region pioneering this revival. A comprehensive analysis of climatic and agroclimatic indicators for
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Grapevine is a highly climate-sensitive plant. In the last few decades, an increase in the number and area of vineyards has been observed in the country, with the Zielona Góra region pioneering this revival. A comprehensive analysis of climatic and agroclimatic indicators for grapevines was conducted to assess the possibilities and limitations in this region. Based on data obtained from the Institute of Meteorology and Water Management—National Research Institute (IMGW-PIB) for stations in Zielona Góra, nine key indicators were identified. The analysis of agroclimatic conditions for the Zielona Góra winegrowing region from 1951 to 2022 revealed significant changes in air temperature, length of the vegetative period, and number of frosts. The average annual air temperature increased, while the number of days with temperatures below 8 °C decreased. The extension of the vegetative period (starting earlier and ending later) favours grapevine cultivation. The increase in temperature during the vegetative period and the lengthening of the frost-free period have a beneficial effect on grape production in the Zielona Góra region.
Full article
(This article belongs to the Section Biometeorology)
Open AccessArticle
Wind Tunnel Evaluation of Plant Protection Products Drift Using an Integrated Chemical–Physical Approach
by
Lorenzo Becce, Giovanna Mazzi, Ayesha Ali, Mara Bortolini, Elena Gregoris, Matteo Feltracco, Elena Barbaro, Daniele Contini, Fabrizio Mazzetto and Andrea Gambaro
Atmosphere 2024, 15(6), 656; https://doi.org/10.3390/atmos15060656 (registering DOI) - 30 May 2024
Abstract
The use of plant protection products (PPPs) has become fundamental to guarantee excellent field productivity. Nevertheless, their usage presents critical issues, such as the quantity of substances used, the relative toxicity, and the contamination of nearby fields caused by atmospheric drift. This study
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The use of plant protection products (PPPs) has become fundamental to guarantee excellent field productivity. Nevertheless, their usage presents critical issues, such as the quantity of substances used, the relative toxicity, and the contamination of nearby fields caused by atmospheric drift. This study focuses on the characterization of aerosol droplets of PPPs produced by spraying a chemical marker, fluorescein, with an orchard airblast sprayer equipped with conventional hollow cone (HC) and anti-drift air inclusion (AI) nozzles, using a wind tunnel as a controlled environment. A particle/droplet image analysis was employed to study the droplet production of the nozzles, while a liquid chromatography tandem mass spectrometry (HPLC-MS/MS) analysis allowed us to evaluate samples collected using a cascade impactor located at 5 m, 10 m, and 20 m from the emission point. Overall, HC nozzles are very accurate at producing specific drop size distributions (DSDs), while AI nozzles produce a much wider DSD, concentrating the largest part of the distributed volume into droplets of a larger size. The marker concentration was much lower for the AI nozzles compared to the HC nozzles; moreover, the two nozzles show a similar trend in the coarse droplet range, while significantly differing in the fine droplet spectrum.
Full article
(This article belongs to the Special Issue Characteristics and Control of Particulate Matter)
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Open AccessArticle
Potential Strengthening of the Madden–Julian Oscillation Modulation of Tropical Cyclogenesis
by
Patrick Haertel and Yu Liang
Atmosphere 2024, 15(6), 655; https://doi.org/10.3390/atmos15060655 (registering DOI) - 30 May 2024
Abstract
A typical Madden–Julian Oscillation (MJO) generates a large region of enhanced rainfall over the equatorial Indian Ocean that moves slowly eastward into the western Pacific. Tropical cyclones often form on the poleward edges of the MJO moist-convective envelope, frequently impacting both southeast Asia
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A typical Madden–Julian Oscillation (MJO) generates a large region of enhanced rainfall over the equatorial Indian Ocean that moves slowly eastward into the western Pacific. Tropical cyclones often form on the poleward edges of the MJO moist-convective envelope, frequently impacting both southeast Asia and northern Australia, and on occasion Eastern Africa. This paper addresses the question of whether these MJO-induced tropical cyclones will become more numerous in the future as the oceans warm. The Lagrangian Atmosphere Model (LAM), which has been carefully tuned to simulate realistic MJO circulations, is used to study the sensitivity of MJO modulation of tropical cyclogenesis (TCG) to global warming. A control simulation for the current climate is compared with a simulation with enhanced radiative forcing consistent with that for the latter part of the 21st century under Shared Socioeconomic Pathway (SSP) 585. The LAM control run reproduces the observed MJO modulation of TCG, with about 70 percent more storms forming than monthly climatology predicts within the MJO’s convective envelope. The LAM SSP585 run suggests that TCG enhancement within the convective envelope could reach 170 percent of the background value under a high greenhouse gas emissions scenario, owing to a strengthening of Kelvin and Rossby wave components of the MJO’s circulation.
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(This article belongs to the Section Meteorology)
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Open AccessArticle
Complexity and Nonlinear Dependence of Ionospheric Electron Content and Doppler Frequency Shifts in Propagating HF Radio Signals within Equatorial Regions
by
Aderonke Akerele, Babatunde Rabiu, Samuel Ogunjo, Daniel Okoh, Anton Kascheyev, Bruno Nava, Olawale Bolaji, Ibiyinka Fuwape, Elijah Oyeyemi, Busola Olugbon, Jacob Akinpelu and Olumide Ajani
Atmosphere 2024, 15(6), 654; https://doi.org/10.3390/atmos15060654 (registering DOI) - 30 May 2024
Abstract
The abundance of ions within the ionosphere makes it an important region for both long range and satellite communication systems. However, characterizing the complexity in the ionosphere within the equatorial region of Abuja, with geographic coordinates of 8.99° N and 7.39° E and
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The abundance of ions within the ionosphere makes it an important region for both long range and satellite communication systems. However, characterizing the complexity in the ionosphere within the equatorial region of Abuja, with geographic coordinates of 8.99° N and 7.39° E and a geomagnetic latitude of −1.60, and Lagos, with geographic coordinates of 3.27° E and 6.48° N and a dip latitude of −1.72°, is a challenging and daunting task due to the intrinsic and external forces involved. In this study, chaos theory was applied on data from both an HF Doppler sounding system and the Global Navigation Satellite System (GNSS) for the characterization of the ionosphere over these two tropical locations during 2020–2021 with respect to the quality of high-frequency radio signals between the two locations. Our results suggest that the ionosphere at the two locations is chaotic, with its largest Lyapunov exponent values being greater than 0 ( ) and its correlation dimension being in the range of . Furthermore, it was revealed that there exists a negative correlation between the state of the ionosphere and signal quality at the two locations. Using transfer entropy, it was confirmed that the ionosphere interfered more with signals during 2020, a year of lower solar activity (sunspot number, 8.8) compared to 2021 (sunspot number, 29.6). On a monthly scale, the influence of the ionosphere on signal quality was found to be complicated. The results obtained in this study will be useful in communication systems design, modelling, and prediction.
Full article
(This article belongs to the Special Issue Variability and Predictability of Space Weather and the Ionosphere: Recent Advances)
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Open AccessPerspective
Accelerating the Low-Carbon Energy Transition in Sub-Saharan Africa through Floating Photovoltaic Solar Farms
by
Tarelayefa Igedibor Ingo, Louis Gyoh, Yong Sheng, Mustafa Kemal Kaymak, Ahmet Duran Şahin and Hamid M. Pouran
Atmosphere 2024, 15(6), 653; https://doi.org/10.3390/atmos15060653 (registering DOI) - 30 May 2024
Abstract
Climate change has become a global issue and is predicted to impact less-developed regions, such as sub-Saharan Africa, severely. Innovative, sustainable renewable energy systems are essential to mitigate climate change’s effects and unlock the region’s potential, especially with the increasing energy demands and
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Climate change has become a global issue and is predicted to impact less-developed regions, such as sub-Saharan Africa, severely. Innovative, sustainable renewable energy systems are essential to mitigate climate change’s effects and unlock the region’s potential, especially with the increasing energy demands and population growth. The region relies heavily on fossil fuels, which calls for urgent action towards energy security and expansion. Hybrid floating solar photovoltaic-hydropower (FPV-HEP) technology has emerged as a cost-effective and transformative solution to accelerate the low-carbon energy transition in sub-Saharan Africa. The technology combines solar panels with existing hydropower infrastructure, ensuring energy security while reducing carbon emissions. This technology offers several benefits over conventional ground-mounted solar systems, including efficient land utilization, energy generation, and water conservation. However, its adoption remains challenging due to technical complexities and evolving regulatory frameworks. Despite these challenges, Nigerian energy professionals have preferred renewable alternatives, mainly distributed solar PV and FPV-HEP plants. This collective embrace of FPV and renewables reflects a growing understanding of their critical role in mitigating climate change through sustainable energy practices. This research aims to contribute to the existing body of knowledge and assist policymakers in making informed decisions on adopting this technology. It also stimulates further research on this topic, offering a new potential solution to the ever-increasing demand for green energy in the region to meet their sustainable development needs.
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(This article belongs to the Special Issue Climate Change and the Potential Impacts on Wind/Solar Power Systems)
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Open AccessArticle
Long-Term Changes in the Permafrost Temperature and Surface Frost Number in Northeast China
by
Wei Shan, Lisha Qiu, Ying Guo, Chengcheng Zhang and Shuai Liu
Atmosphere 2024, 15(6), 652; https://doi.org/10.3390/atmos15060652 (registering DOI) - 29 May 2024
Abstract
The permafrost in Northeast China is experiencing rapid degradation due to the influence of climate change and human activities, profoundly impacting the local ecological environment and engineering construction. Understanding the spatiotemporal dynamics of long-term permafrost in this region is crucial; however, systematic research
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The permafrost in Northeast China is experiencing rapid degradation due to the influence of climate change and human activities, profoundly impacting the local ecological environment and engineering construction. Understanding the spatiotemporal dynamics of long-term permafrost in this region is crucial; however, systematic research on this topic remains scarce. This study combines meteorological station data, MODIS land surface temperature (LST) datasets, and borehole locations to apply the surface frost number (SFn) model. This approach enables the simulation and estimation of the spatial distribution and changes in the area of the surface frost number without vegetation effects (SFnv) and permafrost temperature (PT) in Northeast China from 1971 to 2020. The area of the SFnv > 0.49 within the permafrost region decreased substantially from approximately 44.353 × 104 km2 to 19.909 × 104 km2 between 1971 and 2020, with a notable change in 1988. The area of permafrost calculated using PT < 0 was slightly smaller, declining from 39.388 × 104 km2 to 29.852 × 104 km2. There was also a significant increase in the area with PT ranging from −1 °C to 0 °C, indicating a decline in permafrost stability. Approximately 10.926 × 104 km2 of stable permafrost has been transformed into semi-stable and unstable permafrost. Moreover, from 1982 to 2020, the NDVI was negatively correlated with the area of stable permafrost and positively correlated with the area of transitional or unstable permafrost. Vegetation cover decreased as transitional or unstable permafrost degraded. These findings provide valuable information for permafrost research and engineering development in cold regions, as well as for future planning and adaptation strategies.
Full article
(This article belongs to the Section Biosphere/Hydrosphere/Land–Atmosphere Interactions)
Open AccessArticle
Emission Pattern of Biogenic Volatile Organic Compounds from Wetland Vegetation
by
Wenbin Chen, Luxi Wang, Ju Wu, Xiaoxiu Lun, Xiaoyue Wang and Xiaoyi Li
Atmosphere 2024, 15(6), 651; https://doi.org/10.3390/atmos15060651 (registering DOI) - 29 May 2024
Abstract
Biogenic volatile organic compounds (BVOCs) significantly contribute to atmospheric chemistry at both regional and global scales. The composition and intensity of BVOC emissions vary significantly among different plant species. Previous studies have focused on BVOC emissions from tree species, but the results of
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Biogenic volatile organic compounds (BVOCs) significantly contribute to atmospheric chemistry at both regional and global scales. The composition and intensity of BVOC emissions vary significantly among different plant species. Previous studies have focused on BVOC emissions from tree species, but the results of research on BVOC emissions from wetland plants are still limited. Therefore, in this study, BVOCs emitted by three aquatic plants (Phragmites australis, Typha angustifolia, and Iris pseudacorus) were sampled and analyzed using a dynamic headspace technique combined with GC-MS at daily scales. The diurnal observation data showed that the total BVOC emission rates of the three plants peaked with the increase in environmental factors (temperature, PAR, and water temperature). P. australis was the only of the three plants that emitted isoprene with a high rate of 48.34 μg·g−1Dw·h−1. Moreover, the peak emission rates of total BVOC (78.45 μg·g−1Dw·h−1) in P. australis were higher than most tree species. The emissions rates of volatile organic compounds, including monoterpenes, oxygenated volatile organic compounds, alkanes, and other volatile organic compounds, were statistically correlated across all species. The emission rates of isoprene from P. australis had significant associations with intercellular CO2 concentration (Ci) (0.58, p < 0.05) and transpiration rate (Tr) (−0.63, p < 0.01). The emission rates of monoterpenes from P. australis were found to have a significantly positive correlation with the net photosynthetic rate (Pn) (0.58, p < 0.05) while T. angustifolia (−0.59, p < 0.05) and I. pseudacorus (−0.47, p < 0.05) showed the opposite trend. Such findings hold significance for the refinement of localized emission inventories and the development of comprehensive emission process models in future research, as BVOC emissions from wetland plants were reported here for the first time.
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(This article belongs to the Special Issue The Role of Vegetation in Urban Air Quality)
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Impacts of Land–Atmosphere Interactions on Boundary Layer Variables: A Classification Perspective from Modeling Approaches
by
Xin-Min Zeng, Congmin Li, Ning Wang and Irfan Ullah
Atmosphere 2024, 15(6), 650; https://doi.org/10.3390/atmos15060650 (registering DOI) - 29 May 2024
Abstract
Previously, the types of impacts of land–atmosphere interactions have scarcely been clarified systematically. In this article, we present a classification of these impacts based on modeling boundary layer variables/parameters, which is grouped into local, regional, and remote impacts. In the narrow sense, land
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Previously, the types of impacts of land–atmosphere interactions have scarcely been clarified systematically. In this article, we present a classification of these impacts based on modeling boundary layer variables/parameters, which is grouped into local, regional, and remote impacts. In the narrow sense, land surface processes (LSPs) influence the atmospheric state via vertical land–atmosphere coupling at local scales, which is referred to as local LSP impacts. However, local LSP impacts can lead to the advection effect due to the horizontal heterogeneity in the parameters over a region, which can be defined as regional LSP impacts. Furthermore, remote LSP impacts on the regional atmospheric state are induced by some land/sea surface variables/parameters over remote key areas of the Earth’s surface, which are conventionally taken as strong signals of climate variation. Of the three impacts, local impacts are the most important essential, as the other two types of impacts are derived from these impacts. We describe the quantification of local impacts based on our previous studies from the perspective of modeling approaches, and we discuss some issues related to these impacts. Previous investigations showed that local LSP impacts are mostly stronger than regional LSP impacts, e.g., the diabatic process is dominant in the physical processes responsible for daily maximum temperatures, and two first-order physical processes including vertical diffusion largely induce changes in surface wind speed in China. Finally, some aspects for future research are noted. This study provides insights into the research on land–atmosphre interactions at different scales.
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(This article belongs to the Special Issue Land-Atmosphere Interactions)
Open AccessArticle
Placing 21st Century Warming in Southern California, USA in a Multi-Century Historical Context
by
Paul A. Knapp, Avery A. Catherwood and Peter T. Soulé
Atmosphere 2024, 15(6), 649; https://doi.org/10.3390/atmos15060649 - 29 May 2024
Abstract
Warming in southern California during the 21st century is unprecedented in the instrumental record. To place this warming in a multi-century historical context, we analyzed tree ring data sampled from Jeffrey pine (Pinus jeffreyi) and sugar pine (Pinus lambertiana)
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Warming in southern California during the 21st century is unprecedented in the instrumental record. To place this warming in a multi-century historical context, we analyzed tree ring data sampled from Jeffrey pine (Pinus jeffreyi) and sugar pine (Pinus lambertiana) collected from minimally disturbed, old-growth high-elevation forests within Mt. San Jacinto State Park California, USA. Based on a calibration/verification period of 1960–2020 between earlywood radial growth and California Climate Division 6 climate data, we reconstructed annual (November–October) minimum temperature (Tmin) from 1658 to 2020. During the 61-year calibration/verification period, instrumental Tmin increased (r = 0.69, p < 0.01) and was positively associated with annual radial growth (r = 0.71, p < 0.01). Using regime shift analysis, we found that the 363-year reconstruction revealed Tmin stability until 1958 and then decreased until 1980, followed by the two warmest regimes (1981–2007, 2008–2020) on record. The last 13-year period was 0.77 °C warmer than the multi-century average with nine of the ten warmest years in the reconstruction recorded. These results suggest that 21st century warming in southern California is unique in the context of the past four centuries, indicating the rarity of exceptional warmth captured in the tree ring record.
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(This article belongs to the Section Climatology)
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Earthquake Risk Assessment in Seismically Active Areas of Qinghai Province Based on Geographic Big Data
by
Zhouping Zhang, Junmei Kang, Jun Wang, Dengmao Fang and Yang Liu
Atmosphere 2024, 15(6), 648; https://doi.org/10.3390/atmos15060648 - 28 May 2024
Abstract
Earthquakes can cause serious damage to buildings, roads and other infrastructure. The large amount of dust and particulate matter generated when these structures collapse and are damaged can quickly enter the air, leading to a decline in air quality. At the same time,
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Earthquakes can cause serious damage to buildings, roads and other infrastructure. The large amount of dust and particulate matter generated when these structures collapse and are damaged can quickly enter the air, leading to a decline in air quality. At the same time, earthquakes may cause secondary disasters such as fires and landslides, which will also produce large amounts of soot and particulate matter, which will have a negative impact on air quality. Therefore, earthquake disaster risk assessment studies are carried out to identify potentially hazardous areas and facilities in advance in order to reduce the air pollution problems that may be caused by earthquakes. Existing research on earthquake disaster risk assessment mainly evaluates earthquake risk from the perspective of geology or seismology, but there are few studies based on multidisciplinary assessment that integrates geology, seismology, engineering and social sciences into socioeconomic factors. To this end, based on remote sensing and GIS technology, this paper takes Qinghai Province, a seismically active area, as the research area, and integrates land use data, natural environment data, social environment data and seismic parameter zoning data to construct a comprehensive assessment model for earthquake disaster vulnerability and risk. The results showed that there were 5 very high-risk areas, 7 high-risk areas, 10 medium-risk areas, 11 low-risk areas and 12 very low-risk areas in Qinghai Province. The high-risk areas are mainly distributed in the central and western parts of Qinghai Province, where the earthquake breeding environment is sufficient, the scale of active faults is huge and the adaptability of the carrier is low. The results of an earthquake disaster risk assessment can provide a reference for the government to formulate environmental protection policies. According to the assessment results, the government can formulate targeted measures to strengthen air pollution control and improve air quality.
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(This article belongs to the Section Biosphere/Hydrosphere/Land–Atmosphere Interactions)
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Construction and Validation of Surface Soil Moisture Inversion Model Based on Remote Sensing and Neural Network
by
Rencai Lin, Zheng Wei, Rongxiang Hu, He Chen, Yinong Li, Baozhong Zhang, Fengjing Wang and Dongxia Hu
Atmosphere 2024, 15(6), 647; https://doi.org/10.3390/atmos15060647 - 28 May 2024
Abstract
Surface soil moisture (SSM) reflects the dry and wet states of soil. Microwave remote sensing technology can accurately obtain regional SSM in real time and effectively improve the level of agricultural drought monitoring, and it is of great significance for agricultural precision irrigation
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Surface soil moisture (SSM) reflects the dry and wet states of soil. Microwave remote sensing technology can accurately obtain regional SSM in real time and effectively improve the level of agricultural drought monitoring, and it is of great significance for agricultural precision irrigation and smart agriculture construction. Based on Sentinel-1, Sentinel-2, and Landsat-8 images, the effect of vegetation was removed by the water cloud model (WCM), and SSM was retrieved and validated by a radial basis function (RBF) neural network model in bare soil and vegetated areas, respectively. The normalized difference vegetation index (NDVI) calculated by Landsat-8 (NDVI_Landsat-8) had a better effect on removing the influence the of vegetation layer than that of NDVI_Sentinel-2. The RBF network model, established in a bare area (R = 0.796; RMSE = 0.029 cm3/cm3), and the RBF neural network model, established in vegetated areas (R = 0.855; RMSE = 0.024 cm3/cm3), have better simulation effects on SSM than a linear SSM inversion model with single polarization. The introduction of surface parameters to the RBF neural network model can improve the accuracy of the model and realize the high-accuracy inversion of SSM in the study area.
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(This article belongs to the Section Biosphere/Hydrosphere/Land–Atmosphere Interactions)
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Open AccessArticle
The Design of a Parameterization Scheme for 137Cs Based on the WRF-Chem Model and Its Application in Simulating the Fukushima Nuclear Accident
by
Qun Long, Zengliang Zang, Xiaoyan Ma, Sheng Fang, Yiwen Hu, Yijie Wang, Shuhan Zhuang and Liang Wang
Atmosphere 2024, 15(6), 646; https://doi.org/10.3390/atmos15060646 - 28 May 2024
Abstract
Based on the Weather Research and Forecasting Model Coupled with Chemistry (WRF-Chem) atmospheric chemistry model, a parameterization scheme for the radioactive isotope caesium (137Cs), considering processes such as advection, turbulent diffusion, dry deposition, and wet deposition, was constructed, enabling the spatial
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Based on the Weather Research and Forecasting Model Coupled with Chemistry (WRF-Chem) atmospheric chemistry model, a parameterization scheme for the radioactive isotope caesium (137Cs), considering processes such as advection, turbulent diffusion, dry deposition, and wet deposition, was constructed, enabling the spatial distribution simulation of the concentration and deposition of 137Cs. The experimental simulation studies were carried out during the high emission period of the Fukushima nuclear accident (from 11 to 17 March 2011). Two sets of comparison experiments, with or without deposition, were designed, the effects of wind field and precipitation on the spatial transport and ground deposition of 137Cs were analyzed, and the influence of wind field and precipitation on 137Cs vertical transport was analyzed in detail. The results indicate that the model can accurately simulate the meteorological and 137Cs variables. On 15 March, 137Cs dispersed towards the Kanto Plain in Japan under the influence of northeastern winds. In comparison to the experiment without deposition, the concentration of 137Cs in the Fukushima area decreased by approximately 286 Bq·m−3 in the deposition experiment. Under the influence of updrafts in the non-deposition experiment, a 137Cs cloud spread upward to a maximum height of 6 km, whereas in the deposition experiment, the highest dispersion of the 137Cs cloud only reach a height of 4 km. Affected by the wind field, dry deposition is mainly distributed in Fukushima, the Kanto Plain, and their eastern ocean areas, with a maximum dry deposition of 5004.5 kBq·m−2. Wet deposition is mainly influenced by the wind field and precipitation, distributed in the surrounding areas of Fukushima, with a maximum wet deposition of 725.3 kBq·m−2. The single-station test results from the deposition experiment were better than those for the non-deposition experiment: the percentage deviations of the Tokyo, Chiba, Maebashi, and Naraha stations decreased by 61%, 69%, 46%, and 51%, respectively, and the percentage root mean square error decreased by 46%, 25%, 38%, and 48%, respectively.
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(This article belongs to the Section Climatology)
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Open AccessArticle
Enhancing CO2 Injection Efficiency: Rock-Breaking Characteristics of Particle Jet Impact in Bottom Hole
by
Yi Wang and Jian Zhao
Atmosphere 2024, 15(6), 645; https://doi.org/10.3390/atmos15060645 - 28 May 2024
Abstract
Storing CO2 in oil and gas reservoirs offers a dual benefit: it reduces atmospheric CO2 concentration while simultaneously enhancing oil displacement efficiency and increasing crude oil production. This is achieved by injecting CO2 into producing oil and gas wells. Employing
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Storing CO2 in oil and gas reservoirs offers a dual benefit: it reduces atmospheric CO2 concentration while simultaneously enhancing oil displacement efficiency and increasing crude oil production. This is achieved by injecting CO2 into producing oil and gas wells. Employing particle jet technology at the bottom of CO2 injection wells significantly expands the bottom hole diameter, thereby improving CO2 injection efficiency and storage safety. To further investigate the rock-breaking characteristics and efficiency, a finite element model for particle jet rock breaking is established by utilizing the smoothed particle hydrodynamics (SPH) method. Specifically, this new model considers the high temperature and confining pressure conditions present at the bottom hole. The dynamic response and fracturing effects of rock subjected to a particle jet are also revealed. The results indicate that particle jet impact rebound significantly influences the size of the impact crater, with the maximum first principal stress primarily concentrated on the crater’s surface. The impact creates a “v”-shaped crater on the rock surface, with both depth and volume increasing proportionally to jet inlet velocity and particle diameter. However, beyond a key particle concentration of 3%, the increase in depth and volume becomes less pronounced. Confining pressure is found to hinder particle impact rock-breaking efficiency, while high temperatures contribute to larger impact depths and breaking volumes. This research can provide theoretical support and parameter guidance for the practical application of particle impact technology in enhancing CO2 injection efficiency at the bottom hole.
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(This article belongs to the Special Issue CO2 Geological Storage and Utilization (2nd Edition))
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Open AccessArticle
Applicability Study of Euler–Lagrange Integration Scheme in Constructing Small-Scale Atmospheric Dynamics Models
by
Xiangqian Wei, Yi Liu, Jun Guo, Xinyu Chang and Haochuan Li
Atmosphere 2024, 15(6), 644; https://doi.org/10.3390/atmos15060644 - 27 May 2024
Abstract
The atmospheric flow field and weather processes exhibit complex and variable characteristics at small scales, involving interactions between terrain features and atmospheric physics. To investigate the mechanisms of these process further, this study employs a Lagrangian particle motion model combined with a Euler
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The atmospheric flow field and weather processes exhibit complex and variable characteristics at small scales, involving interactions between terrain features and atmospheric physics. To investigate the mechanisms of these process further, this study employs a Lagrangian particle motion model combined with a Euler background field approach to construct a small-scale atmospheric flow field model. The model streamlines the modeling process by combining the benefits of the Lagrangian dynamics model and the Eulerian integration scheme. To verify the effectiveness of the Euler–Lagrange hybrid model, experiments using the Fluent wind field model were conducted for comparison. The results show that both models have their advantages in handling terrain-induced wind fields. The Fluent model excels in simulating the general characteristics of wind fields under specific terrain, while the Euler–Lagrange hybrid model is better at capturing the upstream and downstream disturbances of the terrain on the atmospheric flow field. These findings provide powerful tools for in-depth diagnostic analysis of atmospheric flow simulation and convective precipitation processes. Notably, the Euler–Lagrange hybrid model demonstrates excellent computational efficiency, with an average computation time of approximately 2 s per time step in a Python environment, enabling rapid simulation of 40 time steps within approximately 90 s.
Full article
(This article belongs to the Special Issue CFD Modeling in Multiphase Flow Transport/Separation Equipment)
Open AccessArticle
Cloud Top Height Retrieval from FY-4A Data: A Residual Module and Genetic Algorithm Approach
by
Tao Li, Niantai Chen, Fa Tao, Shuzhen Hu, Jianjun Xue, Rui Han and Di Wu
Atmosphere 2024, 15(6), 643; https://doi.org/10.3390/atmos15060643 - 27 May 2024
Abstract
This paper proposes a ResGA-Net algorithm for cloud top height (CTH) retrieval using FY-4A satellite data. The algorithm utilizes genetic algorithms for data selection and employs a residual module-based neural network for modeling. It takes the spectral channel data from the FY-4A satellite
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This paper proposes a ResGA-Net algorithm for cloud top height (CTH) retrieval using FY-4A satellite data. The algorithm utilizes genetic algorithms for data selection and employs a residual module-based neural network for modeling. It takes the spectral channel data from the FY-4A satellite as input features and uses CTH extracted from ground-based millimeter-wave cloud radar reflectivity as the target. By combining the large observation scale of the FY-4A satellite and the high accuracy of ground-based cloud radar observations, the model can generate satellite CTH products with higher precision. To validate the effectiveness of the algorithm, experiments were conducted using data from the Beijing area spanning from January 2020 to January 2022. The experimental results show that the metrics of the proposed ResGA-Net outperform those of various contrastive algorithms, and compared to the original FY-4A CTH product, the RMSE and MAE have decreased by 37.89% and 34.77%, while the PCC and SRCC have increased by 11.17% and 9.47%, respectively, demonstrating the superiority of the proposed method presented in this paper.
Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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