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- Atmosphere, Vol. 15, Pages 1019: Warm and Dry Compound Events in Poland
Authors: Joanna Wibig, Joanna Jędruszkiewicz
First page: 1019
Abstract: The aim of this paper was to characterize the warm and dry compound events (WD days) in Poland during the period of 1966–2023, focusing on assessing the frequency and intensity of such events and their spatial and temporal variability, as well as on the driving factors of warm and dry compound events. WD days are those days that have a maximum temperature equal to or higher than the 90th percentile and the precipitation on that day and the 14 preceding days are equal to or less than the 25 percentile. During 1966–2023, the frequency of WD days increased significantly, mainly in April, the summer months, and December. Higher temperatures favored the occurrence of WD days from March to November, but, in winter months, the heat did not favor the occurrence of WD days. The exception was December, when high temperatures in the first part of the analyzed period did not favor the occurrence of a dry day, whereas, in the second part, it did. The strongest influence on the frequency of WD days had the East Atlantic pattern, where air flowed over Poland from the southwest. Warm and humid air flowing from the Atlantic Ocean must overcome the mountain barrier; therefore, it flows to Poland as warm and dry air. From spring to autumn, the WD days were related to an increase in the geopotential height in central Eastern Europe, and, in the winter, they were related with blocking over the Balkans.
Citation: Atmosphere
PubDate: 2024-08-23
DOI: 10.3390/atmos15091019
Issue No: Vol. 15, No. 9 (2024)
- Atmosphere, Vol. 15, Pages 1020: A Deep Forest Algorithm Based on TropOMI
Satellite Data to Estimate Near-Ground Ozone Concentration
Authors: Mao Zong, Tianhong Song, Yan Zhang, Yu Feng, Shurui Fan
First page: 1020
Abstract: The accurate estimation of near-ground ozone (O3) concentration is of great significance to human health and the ecological environment. In order to improve the accuracy of estimating ground-level O3 concentration, this study adopted a deep forest algorithm to construct a model for estimating near-ground O3 concentration. It is pointed out whether input data on particulate matter (PM2.5) and nitrogen dioxide (NO2) concentrations also affect the estimation accuracy. The model first uses the multi-granularity scanning technique to learn the features of the training set, and then it adopts the cascade forest structure to train the processed data, and at the same time, it adaptively adjusts the number of layers in order to achieve a better performance. Daily near-ground O3 concentrations in Shijiazhuang were estimated using satellite O3 column concentrations, ground-based PM2.5 and NO2 concentration data, meteorological element data, and elevation data. The deep forest model was compared with six models, namely, random forest, CatBoost, XGBoost, LightGBM, Decision Tree, and GBDT. The R-squared (R2), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE) of the proposed deep forest model were 0.9560, 13.2542, and 9.0250, respectively, which had significant advantages over other tree-based regression models. Meanwhile, the model performance was improved by adding NO2 and PM2.5 features to the model estimations, indicating the necessity of synergistic observations of NO2, PM2.5, and O3. Finally, the seasonal distribution of O3 concentrations in the Shijiazhuang area was plotted, with the highest O3 concentrations in the summer, the lowest in the winter, and the O3 concentration is in the middle of spring and autumn.
Citation: Atmosphere
PubDate: 2024-08-23
DOI: 10.3390/atmos15091020
Issue No: Vol. 15, No. 9 (2024)
- Atmosphere, Vol. 15, Pages 1021: Influence of Field Sampling Methods on
Measuring Volatile Organic Compounds in a Swine Facility Using SUMMA
Canisters
Authors: Xin Li, Qinqin Sun, Lei Yu, Xiaoshuai Wang, Li Feng, Kaiying Wang
First page: 1021
Abstract: Volatile organic compounds (VOCs) play a crucial role in emission control, being one of the most important sources of odor while also serving as significant precursors to secondary organic aerosols and ozone formation. Appropriate sampling methods are essential for accurately assessing the concentration and composition of VOCs within swine barns. In this study, the effects of both passive air sampling and active air sampling on VOCs were evaluated, and the influence of storage time on the VOC stability in sampling canisters for both methods was investigated. SUMMA canisters, which are electropolished and passivated with silanization, offer excellent corrosion protection and resistance to high pressure and temperature and were used in this study. The predominant component categories prevailing within the pig house were found to be oxygenated VOCs (OVOCs) and volatile sulfur compounds (VSCs), with ethanol emerging as the most abundant component of VOCs detected. Notably, the statistical analysis results revealed no significant differences between passive and active sampling regarding the impact of storage time on substance concentration. Changes in canister pressure also did not significantly affect substance stability. The results showed that the C2–C3 compounds remained relatively stable, especially within 3 days, with recoveries above 80% within 20 days. Methyl sulfide, dimethyl disulfide, and ethanol were more stable within the first week, but their recoveries significantly dropped by day 20, with methyl sulfide and dimethyl disulfide at 62.3% and 65.3%, respectively. This study contributes to the development of a foundation for selecting appropriate VOC sampling methods in swine facilities for conducting a rational analysis of VOC samples.
Citation: Atmosphere
PubDate: 2024-08-23
DOI: 10.3390/atmos15091021
Issue No: Vol. 15, No. 9 (2024)
- Atmosphere, Vol. 15, Pages 1022: Dynamic Changes and Influencing Factors
Analysis of Groundwater Icings in the Permafrost Region in Central Sakha
(Yakutia) Republic under Modern Climatic Conditions
Authors: Miao Yu, Nadezhda Pavlova, Jing Zhao, Changlei Dai
First page: 1022
Abstract: In central Sakha (Yakutia) Republic, groundwater icings, primarily formed by intrapermafrost water, are less prone to contamination and serve as a stable freshwater resource. The periodic growth of icings threatens infrastructure such as roads, railways, and bridges in permafrost areas. Therefore, research in this field has become urgently necessary. This study aims to analyze the impacts of various factors on the scale of icing formation using Landsat satellite data, Gravity Recovery and Climate Experiment (GRACE)/GRACE Follow-On (GRACE-FO) data, Global Land Data Assimilation System (GLDAS) data, and field observation results. The results showed that the surface area of icings in the study area showed an overall increasing trend from 2002 to 2022, with an average growth rate of 0.06 km2/year. Suprapermafrost water and intrapermafrost water are the main sources of icings in the study area. The total Groundwater Storage Anomaly (GWSA) values from October to April showed a strong correlation with the maximum icing areas. Icings fed by suprapermafrost water were influenced by precipitation in early autumn, while those fed by intrapermafrost water were more affected by talik size and distribution. Climate warming contributed to the degradation of the continuous permafrost covering an area of 166 km2 to discontinuous permafrost, releasing additional groundwater. This may also be one of the reasons for the observed increasing trend in icing areas. This study can provide valuable insights into water resource management and infrastructure construction in permafrost regions.
Citation: Atmosphere
PubDate: 2024-08-23
DOI: 10.3390/atmos15091022
Issue No: Vol. 15, No. 9 (2024)
- Atmosphere, Vol. 15, Pages 1023: Qualitative and Quantitative Analyses of
Automotive Exhaust Plumes for Remote Emission Sensing Application Using
Gas Schlieren Imaging Sensor System
Authors: Hafiz Hashim Imtiaz, Paul Schaffer, Yingjie Liu, Paul Hesse, Alexander Bergmann, Martin Kupper
First page: 1023
Abstract: Remote emission sensing (RES) is a state-of-the-art technique for monitoring thousands of vehicles on the road every day to detect high emitters. Modern commercial RES systems use absorption spectroscopy to measure the ratio of pollutants to CO2 from vehicle exhaust gases. In this work, we present an approach to enable direct concentration measurements by spectroscopic techniques in RES through measurement of the absorption path length. Our gas schlieren imaging sensor (GSIS) system operates on the principle of background-oriented schlieren (BOS) imaging in combination with advanced image processing and deep learning techniques to calculate detected exhaust plume sizes. We performed a qualitative as well as a quantitative analysis of vehicle exhaust and plume dimensions with the GSIS system. We present the system details and results from the GSIS system in the lab in comparison to a BOS model based on flow simulations, the results from characterization measurements in the lab with defined gas mixtures and temperatures, and the results from measurements on the road from different vehicles.
Citation: Atmosphere
PubDate: 2024-08-23
DOI: 10.3390/atmos15091023
Issue No: Vol. 15, No. 9 (2024)
- Atmosphere, Vol. 15, Pages 1024: Evaluation of Seasonal Prediction of
Extreme Wind Resource Potential over China Based on a Dynamic Prediction
System SIDRI-ESS V1.0
Authors: Yan, Li, Zhou, Lin, Zang, Li
First page: 1024
Abstract: Wind resources play a pivotal role in building sustainable energy systems, crucial for mitigating and adapting to climate change. With the increasing frequency of extreme events under global warming, effective prediction of extreme wind resource potential can improve the safety of wind farms and other infrastructure, while optimizing resource allocation and emergency response plans. In this study, we evaluate the seasonal prediction skill for summer extreme wind events over China using a 20-year hindcast dataset generated by a dynamical seamless prediction system designed by Shanghai Investigation, Design and Research Institute Co., Ltd. (Shanghai, China) (SIDRI−ESS V1.0). Firstly, the hindcast effectively simulates the spatial distribution of summer extreme wind speed thresholds, even though it tends to overestimate the thresholds in most regions. Secondly, high prediction skills, measured by temporal correlation coefficient (TCC) and normalized root mean square error (nRMSE), are observed in northeast China, central east China, southeast China, and the Tibetan Plateau (TCC is about 0.5 and the nRMSE is below 0.9 in these regions). The highest skills emerge in southeast China with a maximum TCC greater than 0.7, and effective prediction skill can extend up to a 5-month lead time. Ensemble prediction significantly enhances predictive skill and reduces uncertainty, with 24 ensemble members being sufficient to saturate TCC and 12–16 members for nRMSE in most key regions and lead times. Furthermore, we show that the prediction skill for extreme wind counts is strongly related to the prediction skill for summer mean wind speeds, particularly in southeast China. Overall, SIDRI−ESS V1.0 shows promising performance in predicting extreme winds and has great potential to provide services to the wind industry. It can effectively help to optimize wind farm operating strategies and improve power generation efficiency. However, further improvements are needed, particularly in areas where prediction skills for extreme winds are influenced by smaller-scale weather phenomena and areas with complex underlying surfaces and climate characteristics.
Citation: Atmosphere
PubDate: 2024-08-23
DOI: 10.3390/atmos15091024
Issue No: Vol. 15, No. 9 (2024)
- Atmosphere, Vol. 15, Pages 1025: River Flashiness in Great Britain: A
Spatio-Temporal Analysis
Authors: Benjamin Olin, Lindsay Beevers
First page: 1025
Abstract: Flashiness refers to the rapidity and frequency of fluctuations in river flow. It can provide insights into flooding, by capturing dramatic increases in river flow, as well as contaminant transport, relating to concentrations of diffuse pollution. Despite a very well gauged river system, there is limited research in Great Britain targeting this component of river flow. This study addresses that gap in knowledge, with a detailed spatio-temporal analysis of river flashiness in Great Britain. Using 513 gauging stations, with historical records of at least 30 years, the average Richards–Baker flashiness index (RBI¯) was calculated for 1990–2020, showing an overall west- (0.6–0.8) to east-coast (0.1–0.2) gradient, being higher in the west (with the exception of some gauges in the south-east). Employing random forest models, the main predictor for flashiness was found to be soil composition, with some additional region-specific predictors. These include flood attenuation by reservoirs and catchment areas, affecting flashiness in the north and west of Great Britain. Additionally, using a subset of 208 gauging stations with data recorded from 1970 to 2020, a temporal analysis examined significant breakpoints and/or trends in yearly flashiness, using the Pettitt test and Mann–Kendall trend test, respectively. Increases in flashiness were found mainly in the north-east and south-west of Great Britain, with implications in flooding and river health. On a seasonal scale, and using a monthly RBI¯, the timing of flashy events was found to oscillate between autumn and spring over the 50 years, gravitating around winter.
Citation: Atmosphere
PubDate: 2024-08-24
DOI: 10.3390/atmos15091025
Issue No: Vol. 15, No. 9 (2024)
- Atmosphere, Vol. 15, Pages 1026: Long-Term Validation of Aeolus Level-2B
Winds in the Brazilian Amazon
Authors: Alexandre Calzavara Yoshida, Patricia Cristina Venturini, Fábio Juliano da Silva Lopes, Eduardo Landulfo
First page: 1026
Abstract: The Atmospheric Dynamics Mission ADM-Aeolus was successfully launched in August 2018 by the European Space Agency (ESA). The Aeolus mission carried a single instrument, the first-ever Doppler wind lidar (DWL) in space, called Atmospheric LAser Doppler INstrument (ALADIN). Aeolus circled the Earth, providing vertical profiles of horizontal line-of-sight (HLOS) winds on a global scale. The Aeolus satellite’s measurements filled critical gaps in existing wind observations, particularly in remote regions such as the Brazilian Amazon. This area, characterized by dense rainforests and rich biodiversity, is essential for global climate dynamics. The weather patterns of the Amazon are influenced by atmospheric circulation driven by Hadley cells and the Intertropical Convergence Zone (ITCZ), which are crucial for the distribution of moisture and heat from the equator to the subtropics. The data provided by Aeolus can significantly enhance our understanding of these complex atmospheric processes. In this long-term validation study, we used radiosonde data collected from three stations in the Brazilian Amazon (Cruzeiro do Sul, Porto Velho, and Rio Branco) as a reference to assess the accuracy of the Level 2B (L2B) Rayleigh-clear and Mie-cloudy wind products. Statistical validation was conducted by comparing Aeolus L2B wind products and radiosonde data covering the period from October 2018 to March 2023 for Cruzeiro do Sul and Porto Velho, and from October 2018 to December 2022 for Rio Branco. Considering all available collocated winds, including all stations, a Pearson’s coefficient (r) of 0.73 was observed in Rayleigh-clear and 0.85 in Mie-cloudy wind products, revealing a strong correlation between Aeolus and radiosonde winds, suggesting that Aeolus wind products are reliable for capturing wind profiles in the studied region. The observed biases were −0.14 m/s for Rayleigh-clear and −0.40 m/s for Mie-cloudy, fulfilling the mission requirement of having absolute biases below 0.7 m/s. However, when analyzed annually, in 2022, the bias for Rayleigh-clear was −0.95 m/s, which did not meet the mission requirements.
Citation: Atmosphere
PubDate: 2024-08-24
DOI: 10.3390/atmos15091026
Issue No: Vol. 15, No. 9 (2024)
- Atmosphere, Vol. 15, Pages 1027: Comparative Study οf the
Frequencies οf Atmospheric Circulation Types at Different
Geopotential Levels and Their Relationship with Precipitation in Southern
Romania
Authors: Konstantia Tolika, Christina Anagnostopoulou, Myriam Traboulsi, Liliana Zaharia, Dana Maria (Oprea) Constantin, Ioannis Tegoulias, Panagiotis Maheras
First page: 1027
Abstract: The primary aim of this study is to examine the characteristics of atmospheric circulation patterns at various geopotential levels and their relationship with precipitation in southern Romania during the period from 1961 to 2020. Daily geopotential heights (1000 hPa, 850 hPa, 700 hPa and 500 hPa) were utilized in an automatic updated atmospheric circulation scheme for the creation of daily calendars of 12 circulation types (5 anticyclonic and 7 cyclonic) as well as daily time series derived from five stations over the domain of interest. To assess the influence of the atmospheric circulation on precipitation, correlations and time trends were explored between the rainfall totals and the different circulation types. The findings reveal a rising trend in anticyclonic circulation types across the region, while cyclonic types exhibit a consisted decrease. Precipitation and number of rain days percentages associated with specific cyclonic types depend on the geopotential levels, while annual and seasonal precipitation linked to cyclonic types decreases progressively from higher to lower levels. The strongest correlations in circulation type frequencies are observed between adjacent circulation types. Taylor diagram analysis indicates that the relationships between circulation types and precipitation vary both seasonally and across different atmospheric levels. Notably, the two rainiest circulation types are more accurately simulated at higher atmospheric levels (700 hPa and 500 hPa).
Citation: Atmosphere
PubDate: 2024-08-24
DOI: 10.3390/atmos15091027
Issue No: Vol. 15, No. 9 (2024)
- Atmosphere, Vol. 15, Pages 1028: Quantification of Polycyclic Aromatic
Hydrocarbons (PAHs) in Various Fruit Types: A Comparative Analysis
Authors: Cristina Di Fiore, Monica Maio, Ivan Notardonato, Pasquale Avino
First page: 1028
Abstract: The exposure of humans to polycyclic aromatic hydrocarbons (PAHs) through fruits is a scarcely investigated topic. The atmospheric deposition of PAHs could contribute to such an issue. The present paper would like to propose an easy, fast, and routinary analytical method to extract and quantify PAHs in apples, pears, and grapes. Dispersive liquid–liquid microextraction allowed us to recover PAHs ranging between 68.0 ± 1.2 and 96.2 ± 0.8% from fruit. Gas chromatography equipped with flame ionization detector analysis showed satisfactory analytical parameters, with details like R2 > 0.9912 in a concentration range of 0.5–500 µg mL−1, with a variability ranging within 0.7–2.3%. Rural fruit samples were found to be more contaminated by PAHs compared to urban samples, likely due to the use of non-green fuels in rural areas considered in this study. Further in-depth research on this topic is strongly recommended due to the relevance of fruits in the Mediterranean diet.
Citation: Atmosphere
PubDate: 2024-08-25
DOI: 10.3390/atmos15091028
Issue No: Vol. 15, No. 9 (2024)
- Atmosphere, Vol. 15, Pages 1029: Potential Impacts of Future Climate
Change on Super-Typhoons in the Western North Pacific: Cloud-Resolving
Case Studies Using Pseudo-Global Warming Experiments
Authors: Chung-Chieh Wang, Min-Ru Hsieh, Yi Ting Thean, Zhe-Wen Zheng, Shin-Yi Huang, Kazuhisa Tsuboki
First page: 1029
Abstract: Potential impacts of projected long-term climate change toward the end of the 21st century on rainfall and peak intensity of six super-typhoons in the western North Pacific (WNP) are assessed using a cloud-resolving model (CRM) and the pseudo-global warming (PGW) method, under two representative concentration pathway (RCP) emission scenarios of RCP4.5 and RCP8.5. Linear long-term trends in June–October are calculated from 38 Coupled Model Intercomparison Project phase 5 (CMIP5) models from 1981–2000 to 2081–2100, with warmings of about 3 °C in sea surface temperature, 4 °C in air temperature in the lower troposphere, and increases of 20% in moisture in RCP8.5. The changes in RCP4.5 are about half the amounts. For each typhoon, three experiments are carried out: a control run (CTL) using analysis data as initial and boundary conditions (IC/BCs), and two future runs with the trend added to the IC/BCs, one for RCP4.5 and the other for RCP8.5, respectively. Their results are compared for potential impacts of climate change. In future scenarios, all six typhoons produce more rain rather consistently, by around 10% in RCP4.5 and 20% in RCP8.5 inside 200–250 km from the center, with increased variability toward larger radii. Such increases are tested to be highly significant and can be largely explained by the increased moisture and water vapor convergence in future scenarios. However, using this method, the results on peak intensity are mixed and inconsistent, with the majority of cases becoming somewhat weaker in future runs. It is believed that in the procedure to determine the best initial time for CTL, which yielded the strongest TC, often within a few hPa in minimum central sea-level pressure to the best track data, an advantage was introduced to the CTL unintentionally. Once the long-term trends were added in future runs, the environment of the storm was altered and became not as favorable for subsequent intensification. Thus, the PGW approach may have some bias in assessing the peak intensity of such super-typhoon cases, and caution should be practiced.
Citation: Atmosphere
PubDate: 2024-08-25
DOI: 10.3390/atmos15091029
Issue No: Vol. 15, No. 9 (2024)
- Atmosphere, Vol. 15, Pages 1030: GNSS Real-Time ZTD/PWV Retrieval Based on
PPP with Broadcast Ephemerides
Authors: Zongqiu Xu, Shuhao Liu, Yantian Xu, Longjiang Tang, Nannan Yang, Gen Zhang
First page: 1030
Abstract: GNSS precise point positioning (PPP) plays an important role in retrieving atmospheric water vapor values and performing numerical weather prediction. However, traditional PPP relies on real-time orbits and clocks, which require continuous internet or satellite communication. Improved broadcast ephemerides of GNSSs offer new opportunities for PPP with broadcast ephemerides (BE-PPP) instead of using precise ephemeride products. Therefore, we investigated the feasibility of utilizing BE-PPP for retrieving zenith tropospheric delay (ZTD) and precipitable water vapor (PWV) data. We processed the GPS/Galileo observations from 80 IGS stations during a 30-day experiment to retrieve ZTD values using both real-time PPP (RT-PPP) and BE-PPP solutions. Then, we processed observations from 20 EUREF Permanent GNSS Network (EPN) stations to retrieve PWV data. The IGS final tropospheric products were used to validate the ZTD, and radiosonde (RDS) and ERA5 data were used to validate the PWV. The results show that the real-time ZTD from BE-PPP agrees well with that from RT-PPP: the standard deviation (STD) of the ZTD is 1.07 cm when using BE-PPP and 0.6 cm when using RT-PPP. Furthermore, the STD of the PWV is 1.69 mm when using BE-PPP, and 0.96 mm when using RT-PPP, compared to the ERA5-PWV. Compared to the RDS-PWV, the STD is 3.09 mm when using BE-PPP and 1.39 mm when using RT-PPP. In conclusion, the real-time ZTD/PWV products obtained using the BE-PPP solution are consistent with those of RT-PPP and meet the requirements of NWP, so this method can be used as an effective complement to RT-PPP to expand its application potential.
Citation: Atmosphere
PubDate: 2024-08-25
DOI: 10.3390/atmos15091030
Issue No: Vol. 15, No. 9 (2024)
- Atmosphere, Vol. 15, Pages 1031: Sea Fog Recognition near Coastline Using
Millimeter-Wave Radar Based on Machine Learning
Authors: Tao Li, Jianhua Qiu, Jianjun Xue
First page: 1031
Abstract: Sea fog is a hazardous natural phenomenon that reduces visibility, posing a threat to ports and nearshore navigation, making the identification of nearshore sea fog crucial. Millimeter-wave radar has significant advantages over satellites in capturing sudden and localized sea fog weather. The use of millimeter-wave radar for sea fog identification is still in the exploratory stage in operational fields. Therefore, this paper proposes a nearshore sea fog identification algorithm that combines millimeter-wave radar with multiple machine learning methods. Firstly, Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is used to partition radar echoes, followed by the K-means clustering algorithm (KMEANS) to divide the partitions into recognition units. Then, Sea-Fog-Recognition-Convolutional Neural Network (SFRCNN) is used to classify whether the recognition units are sea fog areas, and finally, the partition coverage algorithm is employed to improve identification accuracy. The experiments conducted using millimeter-wave radar observation data from the Pingtan Meteorological Observation Base in Fujian, China, achieved an identification accuracy of 96.94%. The results indicate that the proposed algorithm performs well and expands the application prospects of such equipment in meteorological operations.
Citation: Atmosphere
PubDate: 2024-08-25
DOI: 10.3390/atmos15091031
Issue No: Vol. 15, No. 9 (2024)
- Atmosphere, Vol. 15, Pages 1032: Spatial and Temporal Variability of
Rainfall Erosivity in the Niyang River Basin
Authors: Qingqin Bai, Lei Wang, Yangzong Cidan
First page: 1032
Abstract: Rainfall erosivity is a crucial factor in the evaluation of soil erosion, significantly influencing the complex relationships among water, soil, and the environment. Understanding its attributes and variations in space and time is essential for effective water resource management, erosion mitigation, and land-use planning. This paper utilizes daily precipitation data from 123 grid points in the Niyang River Basin, spanning from 2008 to 2016, to calculate rainfall erosivity using a straightforward algorithmic model. Ordinary Kriging was used to examine the spatial and temporal variations in rainfall erosivity, while Spearman’s correlation analysis was employed to examine the relationships between annual rainfall erosivity and various factors, including multi-year average precipitation, erosive rainfall, dry-season rainfall, wet-season rainfall, temperature, and elevation. The results indicate a year-by-year increase in rainfall erosivity in the basin, with a trend towards stabilization. The average annual rainfall erosivity over the years is 711 MJ·mm·hm−2·h−1, peaking at 1098 MJ·mm·hm−2·h−1 in 2014. A significant 93.9% of rainfall erosivity is concentrated in the wet season, with a maximum of 191 MJ·mm·hm−2·h−1 in July. The left bank of the mainstream, especially the central and lower sections of the main river and its tributaries, experiences the highest rainfall erosivity. Rainfall factors predominantly influence erosivity, with erosive rainfall showing the strongest correlation (rho = 0.93), while temperature and elevation have relatively minor effects. This study enhances the understanding of rainfall erosive forces in the plateau region and provides a scientific basis for predicting soil loss, developing effective erosion control measures, and ensuring sustainable land use.
Citation: Atmosphere
PubDate: 2024-08-26
DOI: 10.3390/atmos15091032
Issue No: Vol. 15, No. 9 (2024)
- Atmosphere, Vol. 15, Pages 1033: Unusual Forbush Decreases and Geomagnetic
Storms on 24 March, 2024 and 11 May, 2024
Authors: Helen Mavromichalaki, Maria-Christina Papailiou, Maria Livada, Maria Gerontidou, Pavlos Paschalis, Argyris Stassinakis, Maria Abunina, Nataly Shlyk, Artem Abunin, Anatoly Belov, Victor Yanke, Norma Crosby, Mark Dierckxsens, Line Drube
First page: 1033
Abstract: As the current solar cycle 25 progresses and moves towards solar maxima, solar activity is increasing and extreme space weather events are taking place. Two severe geomagnetic storms accompanied by two large Forbush decreases in galactic cosmic ray intensity were recorded in March and May, 2024. More precisely, on 24 March 2024, a G4 (according to the NOAA Space Weather Scale for Geomagnetic Storms) geomagnetic storm was registered, with the corresponding geomagnetic indices Kp and Dst equal to 8 and −130 nT, respectively. On the same day, the majority of ground-based neutron monitor stations recorded an unusual Forbush decrease. This event stands out from a typical Forbush decrease because of its high amplitude decrease phase and rapid recovery phase, i.e., 15% decrease and an extremely rapid recovery of 10% within 1.5 h, as recorded at the Oulu neutron monitor station. Furthermore, on 10–13 May 2024, an unusual G5 geomagnetic storm (geomagnetic indices Kp = 9 and Dst = −412 nT) was registered (the last G5 storm had been observed in 2003). In addition, the polar neutron monitor stations recorded a Ground Level Enhancement (GLE74) during the recovery phase of a large Forbush decrease of 15%, which started on 10 May 2024. In this study, a detailed analysis of these two severe events in regard to the accompanying solar activity, interplanetary conditions and solar energetic particle events is provided. Moreover, the results of the NKUA “GLE Alert++ system”, the NKUA/IZMIRAN “FD Precursory Signals” method and the NKUA “ap Prediction tool” concerning these events are presented.
Citation: Atmosphere
PubDate: 2024-08-26
DOI: 10.3390/atmos15091033
Issue No: Vol. 15, No. 9 (2024)
- Atmosphere, Vol. 15, Pages 1034: Identification of Urban Ventilation
Corridor System Using Meteorology and GIS Technology: A Case Study in
Zhengzhou, China
Authors: Pan Pan, Fengxiu Li, Yeyu Zhu, Pengpeng Xu, Yulong Shang, Rongwei Liao
First page: 1034
Abstract: Urban ventilation corridors are designed to enhance air quality, alleviate urban thermal conditions, reduce pollution and energy consumption, as well as improve human comfort within cities. They play a pivotal role in mitigating environmental impacts, particularly in densely populated urban areas. Based on satellite remote sensing data, meteorological observations, basic geographic information of Zhengzhou City and its surroundings, and urban planning data, we analyzed the urban wind environment, urban heat island, ecological cold sources, and ventilation potential. The findings reveal several key insights: (1) Dominant winds in Zhengzhou City predominantly originate from the northwest, northeast, and south, influenced by topography and the monsoon climate, with seasonal variations. These wind patterns are crucial considerations for designing primary ventilation corridors. (2) The urban heat island exhibits a polycentric spatial distribution, with intensity decreasing from the city center towards the periphery. Ecological cold sources, primarily situated in the city outskirts, act as reservoirs of fresh air that mitigate the urban heat island effect through designated corridors. (3) A preliminary corridor system, termed “eight primary and thirteen secondary corridors”, is proposed for Zhengzhou City based on an integrated assessment of ventilation potential, urban surface roughness, and sky view factor. This research contributes to advancing the understanding of urban ventilation systems and provides practical insights for policymakers, urban planners, and researchers seeking sustainable solutions to mitigate climate impacts in rapidly urbanizing environments in the region.
Citation: Atmosphere
PubDate: 2024-08-27
DOI: 10.3390/atmos15091034
Issue No: Vol. 15, No. 9 (2024)
- Atmosphere, Vol. 15, Pages 935: PT-ESM: A Parameter-Testing and
Integration Framework for Earth System Models Oriented towards
High-Performance Computing
Authors: Jiaxu Guo, Liang Hu, Gaochao Xu, Juncheng Hu, Xilong Che
First page: 935
Abstract: High-performance computing (HPC) plays a crucial role in scientific computing, and the efficient utilization of HPC to accomplish computational tasks remains a focal point of research. This study addresses the issue of parameter tuning for Earth system models by proposing a comprehensive solution based on the concept of scientific workflows. This solution encompasses detailed methods from sensitivity analysis to parameter tuning and incorporates various approaches to enhance result accuracy. We validated the reliability of our methods using five cases in the Single Column Atmosphere Model (SCAM). Specifically, we investigated the influence of fluctuations of 11 typical parameters on 10 output variables. The experimental results show that the magnitude of the impact on the results varies significantly when different parameters are perturbed. These findings will help researchers develop more reasonable parameterization schemes for different regions and seasons.
Citation: Atmosphere
PubDate: 2024-08-05
DOI: 10.3390/atmos15080935
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 936: Observed Impacts of Ground-Mounted
Photovoltaic Systems on the Microclimate and Soil in an Arid Area of
Gansu, China
Authors: Jia Zhang, Zaixin Li, Junyu Tao, Yadong Ge, Yuzhen Zhong, Yibo Wang, Beibei Yan
First page: 936
Abstract: Ground-mounted photovoltaic (GMPV) systems are a crucial component of photovoltaic (PV) applications, and their environmental impacts during large-scale development require thorough attention. This study conducted continuous observations at a GMPV plant in an arid region, employing a three-site comparative monitoring system to assess the environmental impact of both shaded and non-shaded areas within GMPV systems. The parameters measured included atmospheric temperature (AT), relative humidity (RH), soil temperature (ST), soil water content (SWC), and wind speed. The results revealed significant diurnal and seasonal variations in AT, with daytime warming and nighttime cooling ranging from 0.1 to 0.7 °C, with particularly large variations observed during high-temperature seasons. Shaded areas under the PV panels exhibited increased RH at night and decreased RH during the day, along with a cooling effect on ST, with a maximum reduction of 7 °C. SWC was higher in shaded areas during dry seasons but exhibited complex redistribution patterns during rainy seasons. Wind speed and direction were notably altered, demonstrating a corridor effect. These findings contrast with previous studies that only focused on the environmental assessment of non-shaded areas within PV systems and external areas using two-site monitoring. This study highlights the critical role of shaded areas in understanding the local environmental impacts of PV systems. This comprehensive approach offers deeper insights into how PV systems influence local meteorological and environmental conditions, suggesting that optimized design and placement of PV systems can enhance their ecological benefits and mitigate adverse environmental impacts in arid regions.
Citation: Atmosphere
PubDate: 2024-08-05
DOI: 10.3390/atmos15080936
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 937: An Improved CH4 Profile Retrieving Method
for Ground-Based Differential Absorption Lidar
Authors: Lu Fan, Yong Wan, Yongshou Dai
First page: 937
Abstract: Range-resolved CH4 concentration measurement is important prior data for atmospheric physical and chemical models. Ground-based differential absorption lidar (DIAL) can measure the vertical distribution of CH4 concentration in the atmosphere. The traditional method uses lidar observational data and the lidar equation to calculate profiles, but the inversion accuracy is greatly affected by noise. Although some denoising methods can improve accuracy at low altitudes, the low signal-to-noise ratio caused by the effect of aerosol Mie scattering and lower aerosol concentrations at high altitudes cannot be solved. Here, an improved cubic smoothing spline fitting CH4 concentration profile inversion method is proposed to address this challenge. By adding a penalty term of the second derivative of the conventional cubic spline function to the objective function, this penalty term acts to smooth the fitting, allowing the fitting function to avoid necessarily passing through those noisy sampling points. This avoids the large fluctuations caused by noisy sampling points, effectively suppresses noise, captures signals with lower noise levels, and thereby enhances the inversion accuracy of the profiles. Simulations and case studies demonstrated the superiority of the proposed method. Compared with the traditional method, cubic smoothing spline fitting can reduce the mean error of the whole CH4 profile by 85.54%. The standard deviation of CH4 concentration retrieved is 3.59 ppb–90.29 ppb and 0.01 ppb–6.75 ppb smaller than the traditional method and Chebyshev fitting, respectively. Three real cases also indicate that the CH4 concentration retrieved by cubic smoothing spline fitting is more consistent with in-situ measurements. In addition, long-term DIAL observations have also revealed notable diurnal and seasonal trends in CH4 concentration at observation sites.
Citation: Atmosphere
PubDate: 2024-08-05
DOI: 10.3390/atmos15080937
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 938: Source Profile Analysis, Source
Apportionment, and Potential Health Risk of Ambient Particle-Bound
Polycyclic Aromatic Hydrocarbons in Areas of Specific Interest
Authors: Dikaia Saraga, Michail Pachoulis, Maria Dasopoulou, Panagiotis Panagopoulos, Dimitra Balla, Kyriaki Bairachtari, Thomas Maggos
First page: 938
Abstract: Ambient particulate matter (PM10) and its chemical composition in polycyclic aromatic hydrocarbons (PAHs) were studied in areas of specific interest, between September 2015 and July 2016. The principal aim of this study was to assess the different PAH source profiles in each area, as well as their potential health risk. In particular, the studied areas were (a) the semiurban industrialized zone of the Municipality of Peloponnese (Meligalas, Messini) of Messinia prefecture, due to the intensive olive-productive activity in the extensive area, (b) the industrialized zone of Oinofyta in Voiotia prefecture, and (c) the urban/traffic center of Athens (Aristotelous). Intense spatial and seasonal variations in PAH levels were observed among the study areas collectively, but also for each one individually. During the winter period, the total PAHs average concentration was 11.45 and 9.84 ng/m3 at Meligalas–Skala (S1, S2 stations), 8.84 ng/m3 at Messini (S3 station), and 6.30 ng/m3 at the center of Athens (Aristotelous). During the summer campaign, the corresponding levels were 0.99, 1.20, and 0.70 ng/m3 (S1, S2, and S3 stations), and 5.84 ng/m3 (Aristotelous), respectively. The highest potential cancer risk of the PAHs mixture was estimated based on winter season measurements taken at the Municipality of Peloponnese. In order to determine PAH sources, two different source apportionment techniques were applied, i.e., diagnostic ratios (DRs) and the positive matrix factorization (PMF) model.
Citation: Atmosphere
PubDate: 2024-08-05
DOI: 10.3390/atmos15080938
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 939: The Impact of Climate Change on Solar
Radiation and Photovoltaic Energy Yields in China
Authors: Yaping Hua, Mingbang Wei, Jun Yuan, Wei He, Long Chen, Yang Gao
First page: 939
Abstract: Solar photovoltaics is a direct use of solar resources to generate electricity, which is one of the most important renewable energy application approaches. Regional PV output could be affected by the regional patterns of temperature and irradiance, which are impacted by climate change. This study examines the impact of climate change on the energy yields from solar PV across China in the future under the medium-emission scenario (SSP245) and high-emission scenario (SSP585) by calculating PV potential using the data of solar radiation on a tilted surface and temperature. Generally, under the SSP245 scenario, solar radiation increased by 0.8% and 2.15%, and PV energy yields increased by 0.28% and 1.21% in 2020–2060 and 2061–2099, respectively; under the SSP585 scenario, solar radiation increased by 0.73% and 1.35%, and PV energy yields increased by 0.04% and −1.21% in 2020–2060 and 2061–2099, respectively. Under both scenarios, PV energy potential showed an obvious increase in southeast and central China and a significant decrease in northwest China, Tibet, and Inner Mongolia. Therefore, it is suggested that under the medium-emission scenario, climate change could increase the PV energy potential, while under the high-emission scenario, it could inhibit the PV energy potential in China.
Citation: Atmosphere
PubDate: 2024-08-05
DOI: 10.3390/atmos15080939
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 940: Assessment of Radon Concentration and
Health Hazards in Natural Spring Water of a Sub-Himalayan District
Authors: Ayesha Sajid, Mavia Anjum, Hannan Younis, Moustafa Salouci, Khurram Mehboob, Abd Haj Ismail
First page: 940
Abstract: The objective of this study was to evaluate the extent of radon contamination in twenty-six drinking water samples from natural springs were collected from Dhirkot Azad Kashmir, along with four bottled mineral water samples. Radon gas escapes from the earth’s crust due to uranium ores and diffuses into the atmosphere. This study assessed the levels of radon concentration, the yearly effective radiation dose, and carcinogenic risk from radon exposure in drinking water samples. The radon concentration varied from 0.28 to 30.25 Bq/L. The mean radon concentration of all samples was found to be 7.86 ± 2.3 Bq/L. The radon concentrations in bottled drinking water were found to be lower than those in natural springs. The statistical and GIS analyses included the use of interpolation and Pearson’s correlation matrix. Seven samples had radon concentration that surpassed the standard limit established by the US-EPA, which is 11 Bq/L. The average annual effective dose from inhalation and ingestion was found to be lower than the value (0.1 mSv/y) provided by the WHO, but for some natural spring water samples, it exceeded the risk limit. The cancer risk revealed that 40% of the samples had an elevated lifetime cancer risk from radon exposure. Overall, the majority of the results obtained aligned with the worldwide guidelines established by the US-EPA. However, there were a few instances where the limits were exceeded, and constant monitoring is recommended. This study establishes a baseline for radon concentration in the area and provides a basis for future studies.
Citation: Atmosphere
PubDate: 2024-08-06
DOI: 10.3390/atmos15080940
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 941: Challenges of Using Historical Aurora
Observations for the Reconstruction of Solar Activity before the 19th
Century, Especially during and near the Maunder Minimum
Authors: Martin Stangl, Ulrich Foelsche
First page: 941
Abstract: In order to complement gaps in the surveillance of solar activity in historical times, various proxies are used to reconstruct past solar cycles and long-term maxima and minima of solar activity, the most famous being the Maunder Minimum (MM), which is usually defined to span the period between the years 1645 and 1715. We explain the problems within existing data bases and call upon trying to find the original sources of Schröder, since his aurorae catalog spans the whole MM and contradicts what has been deduced from more used compilations. We take a critical look at the proposed source-critical scheme introduced by Neuhäuser and Neuhäuser and show it to be counterproductive because it largely ignores the source situation, i.e., the scientific understanding of the reporters of times long past and their intentions. While historical sunspot and aurora reports can be useful to fine-tune our knowledge of solar activity in times before the onset of systematical surveillances, they should not be used as an index of solar activity, since they cannot be quantitatively expressed due to the non-scientific manner of the reports and ambiguous wording. Reconstructions based on cosmogenic isotopes are significantly preferable for establishing the level of solar activity in the past. The conclusions reached by this review should be regarded as a caution against expecting important conclusions to emerge from low quality data.
Citation: Atmosphere
PubDate: 2024-08-06
DOI: 10.3390/atmos15080941
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 942: An Ozone Episode in the Urban
Agglomerations along the Yangtze River in Jiangsu Province: Pollution
Characteristics and Source Apportionment
Authors: Zhe Cai, Derong Zhou, Jianqiao Yu, Sheng Zhong, Longfei Zheng, Zijun Luo, Zhiwei Tang, Fei Jiang
First page: 942
Abstract: A severe ozone episode occurred in cities along the Yangtze River of Jiangsu Province (UAYRJS) from 6 to 8 September 2022, with daily maximum 8-h average ozone concentrations in the range of 65.8–119 ppb, peaking in Nanjing on 7 September. We used the air quality model WRF-CMAQ-ISAM and the Lagrange trajectory model HYSPLIT to quantify the ozone contribution of each region and analyze the causes and regional transmission pathways of ozone pollution in the UAYRJS. Based on simulated emissions, we also estimated the contribution of biogenic volatile organic compounds. We found that weather has a negative impact on pollution, and ozone pollution tracks the movement of the Western Pacific Subtropical High. UAYRJS was affected by oceanic pollution, and there was a mutual influence among the area’s cities. On 6 September, the ozone in UAYRJS was mostly locally generated (50–98%); on 7 September, it was dominated by extra-regional transport (50–80%). Isoprene concentrations in UAYRJS increased by 0.03–0.1 ppb on 6 and 7 September compared with 5 September. Sensitivity testing showed that the hourly ozone concentration increased by 0.1–27.8 ppb (7.6–19.1%) under the influence of biogenic emissions. The results provide a scientific basis for future ozone control measures.
Citation: Atmosphere
PubDate: 2024-08-06
DOI: 10.3390/atmos15080942
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 943: Stability Detection of Canopy RGB Images
for Different Underlying Surfaces Based on SVM
Authors: Wei Tao, Yanli Chen, Lu Huang, Kun Jing, Zhenhua Cheng
First page: 943
Abstract: This study aims to investigate the impact of different environmental conditions on the stability of RGB images in ecological sites and the anti-interference properties of vegetation images on different underlying surfaces. Three vegetation types including sugarcane, forest, and karst (mainly shrub and grass) are used to segment green vegetation using machine learning, and the RGB vegetation indices are calculated using color channel data. Then, The effect of weather, season, and time period on different types of vegetation indices are studied, which provide technical references for quantitative application of RGB image data. The results indicate the following: ① For the vegetation with high canopy density, the SVM machine learning segmentation algorithm used in this study is more applicable, as the RGB image segmentation accuracy of sugarcane and forest is significantly higher than karst. For different weather conditions, the segmentation accuracy of sugarcane and forest RGB images on sunny or cloudy days is higher than that on rainy or foggy days, but the effect on sparse vegetation in karst is not obvious. Additionally, the segmentation accuracy of different vegetation types has a small increase with NLM filter processing. ② Change in weather, season, and time can affect the stability of the image index. For different weather conditions, the vegetation indices of sugarcane and forest images on sunny or cloudy days are the more stable (ExGR, outlier proportion between 3.25% and 5.63%), while on rainy and foggy days they are less stable (ExR, outlier proportion between 17.60% and 21.59%). For different seasons, the stability of the sugarcane and karst image index obtained in spring is better (ExG, outlier proportion between 3.32% and 6.88%), while the stability of the forest image index obtained in summer is better (ExR, outlier proportion = 10.32%). For different times within a day, the sugarcane image index obtained in the morning is more stable (ExGR, outlier proportion = 4.62%), while the stability of the forest image index obtained in the afternoon is better (ExGR, outlier proportion = 9.24%). ③ The stability of the sugarcane image index is more affected by weather and season. For forest, the influence of the weather is more obvious than the season. But, for karst, the effect of season on the vegetation index is greater than that of weather.
Citation: Atmosphere
PubDate: 2024-08-06
DOI: 10.3390/atmos15080943
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 944: Mesospheric Ozone Depletion during
2004–2024 as a Function of Solar Proton Events Intensity
Authors: Grigoriy Doronin, Irina Mironova, Nikita Bobrov, Eugene Rozanov
First page: 944
Abstract: Solar proton events (SPEs) affect the Earth’s atmosphere, causing additional ionization in the high-latitude mesosphere and stratosphere. Ionization rates from such solar proton events maximize in the stratosphere, but the formation of ozone-depleting nitrogen and hydrogen oxides begins at mesospheric altitudes. The destruction of mesospheric ozone is associated with protons with energies of about 10 MeV and higher and will strongly depend on the intensity of the flux of these particles. Most studies investigating the impact of SPEs on the characteristics of the middle atmosphere have been based on either simulations or reanalysis datasets, and some studies have used satellite observations to validate model results. We study the impact of SPEs on cold-season ozone loss in both the northern and southern hemispheres using Aura MLS mesospheric ozone measurements over the 2004 to 2024 period. Here, we show how strongly SPEs can deplete polar mesospheric ozone in different hemispheres and attempt to evaluate this dependence on the intensity of solar proton events. We found that moderate SPEs consisting of protons with an energy of more than 10 MeV and a flux intensity of more than 100 pfu destroy mesospheric ozone in the northern hemisphere up to 47% and in the southern hemisphere up to 33%. For both hemispheres, the peak of winter ozone loss was observed at about 76 km. In the northern hemisphere, maximum winter ozone loss was observed on the second day after a solar proton event, but in the southern hemisphere, winter ozone depletion was already detected on the first day. In the southern hemisphere, mesospheric ozone concentrations return to pre-event levels on the ninth day after a solar proton event, but in the northern hemisphere, even on the tenth day after a solar proton event, the mesospheric ozone layer may not be fully recovered. The strong SPEs with a proton flux intensity of more than 1000 pfu lead to a maximum winter ozone loss of up to 85% in the northern hemisphere, and in the southern hemisphere winter, ozone loss reaches 73%.
Citation: Atmosphere
PubDate: 2024-08-06
DOI: 10.3390/atmos15080944
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 945: Carbon and Water Balances in a Watermelon
Crop Mulched with Biodegradable Films in Mediterranean Conditions at
Extended Growth Season Scale
Authors: Rossana M. Ferrara, Alessandro Azzolini, Alessandro Ciurlia, Gabriele De Carolis, Marcello Mastrangelo, Valerio Minorenti, Alessandro Montaghi, Mariagrazia Piarulli, Sergio Ruggieri, Carolina Vitti, Nicola Martinelli, Gianfranco Rana
First page: 945
Abstract: The carbon source/sink nature and the water balance of a drip-irrigated and mulched watermelon cultivated under a semi-arid climate were investigated. Biodegradable films, plants and some fruits were left on the soil as green manure. The study spanned from watermelon planting to the subsequent crop (June–November 2023). The eddy covariance technique was employed to monitor water vapor (H2O) and carbon dioxide (CO2) fluxes, which were partitioned into transpiration, evaporation, photosynthesis and respiration, respectively, using the flux variance similarity method.This method utilizesthe Monin–Obukhov similarity theory to separate stomatal (photosynthesis and transpiration) from non-stomatal (respiration and evaporation) processes. The results indicate that mulching films contribute to carbon sequestration in the soil (+19.3 g C m−2). However, the mulched watermelon crop presented in this study functions as a net carbon source, with a net biome exchange, representing the net rate of C accumulation in or loss from ecosystems, equal to +230 g C m−2. This is primarily due to the substantial amount of carbon exported through marketable fruits. Fixed water scheduling led to water waste through deep percolation (approximately 1/6 of the water supplied), which also contributed to the loss of organic carbon via leaching (−4.3 g C m−2). These findings recommend further research to enhance the sustainability of this crop in terms of both water and carbon balances.
Citation: Atmosphere
PubDate: 2024-08-07
DOI: 10.3390/atmos15080945
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 946: Integrated Analysis of Methane Cycles and
Authors: Francesco D’Amico, Ivano Ammoscato, Daniel Gullì, Elenio Avolio, Teresa Lo Feudo, Mariafrancesca De Pino, Paolo Cristofanelli, Luana Malacaria, Domenico Parise, Salvatore Sinopoli, Giorgia De Benedetto, Claudia Roberta Calidonna
First page: 946
Abstract: Due to its high short-term global warming potential (GWP) compared to carbon dioxide, methane (CH4) is a considerable agent of climate change. This research is aimed at analyzing data on methane gathered at the GAW (Global Atmosphere Watch) station of Lamezia Terme (Calabria, Southern Italy) spanning seven years of continuous measurements (2016–2022) and integrating the results with key meteorological data. Compared to previous studies on detected methane mole fractions at the same station, daily-to-yearly patterns have become more prominent thanks to the analysis of a much larger dataset. Overall, the yearly increase of methane at the Lamezia Terme station is in general agreement with global measurements by NOAA, though local peaks are present, and an increase linked to COVID-19 is identified. Seasonal changes and trends have proved to be fully cyclic, with the daily cycles being largely driven by local wind circulation patterns and synoptic features. Outbreak events have been statistically evaluated depending on their weekday of occurrence to test possible correlations with anthropogenic activities. A cross analysis between methane peaks and specific wind directions has also proved that local sources may be deemed responsible for the highest mole fractions.
Citation: Atmosphere
PubDate: 2024-08-07
DOI: 10.3390/atmos15080946
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 947: Seasonal Contributions and Influencing
Factors of Urban Carbon Emission Intensity: A Case Study of Tianjin, China
Authors: Tianchun Xiang, Jiang Bian, Yumeng Li, Yiming Gu, Yang Wang, Yahui Zhang, Junfeng Wang
First page: 947
Abstract: The escalating concern over global warming has garnered significant international attention, with carbon emission intensity emerging as a crucial barrier to sustainable economic development across various regions. While previous studies have largely focused on annual scales, this study introduces a novel examination of Tianjin’s quarterly carbon emission intensity and its influencing factors from 2012 to 2022 using quarterly data and the Logarithmic Mean Divisia Index (LMDI) model. The analysis considers the carbon emission effects of thermal power generation, the power supply structure, power intensity effects, and economic activity intensity. The results indicate a general decline in Tianjin’s carbon emission intensity from 2012 to 2020, followed by an increase in 2021 and 2022. This trend, exhibiting significant seasonal fluctuations, revealed the highest carbon emission intensity in the first quarter (an average of 1.4093) and the lowest in the second quarter (an average of 1.0019). Economic activity intensity emerged as the predominant factor influencing carbon emission intensity changes, particularly notable in the second quarter (an average of −0.0374). Thermal power generation and electricity intensity effects were significant in specific seasons, while the power supply structure’s impact remained relatively minor yet stable. These findings provide essential insights for formulating targeted carbon reduction strategies, underscoring the need to optimize energy structures, enhance energy efficiency, and account for the seasonal impacts of economic activity patterns on carbon emissions.
Citation: Atmosphere
PubDate: 2024-08-08
DOI: 10.3390/atmos15080947
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 948: On the Relation between Wind Speed and
Maximum or Mean Water Wave Height
Authors: Sarah Balkissoon, Y. Charles Li, Anthony R. Lupo, Samuel Walsh, Lukas McGuire
First page: 948
Abstract: Dimensional analysis shows that the relation between wind speed and maximum or mean water wave height takes the form H=cU02g, where H is the maximum or mean water wave height caused by wind of speed U0, g is the gravitational acceleration, and c is a dimensionless constant. This relation is important in predicting the maximum or mean water wave height caused by a tropical cyclone. Firstly, the mathematical and theoretical justification for determining c is presented. Verification is conducted using four tropical cyclones as case studies for determining c using significant wave heights rather than the overall maximum and mean. The observed values of c are analyzed statistically. On the days when the fixed buoy captured the highest wind speeds, the frequency distributions of the data for c are close to a bell shape with very small standard deviations in comparison with the mean values; thus, the mean values provide good predictions for c. In view of the fact that tropical cyclone waves are turbulent and the background waves caused by many other factors such as lunar tidal effect cannot be ignored, the obtained results for c are quite satisfactory. This method provides a direct approach in the prediction of the wave height or the wind speeds given the c value and can serve an interpolation methodology to increase the temporal resolution of the data.
Citation: Atmosphere
PubDate: 2024-08-08
DOI: 10.3390/atmos15080948
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 949: Study on CO2 Emission Forecast of
“Four Provinces of Mountains and Rivers” Based on
Time-SeriesMachine Learning
Authors: Xiaoting Zhou, Zhiqiang Liu, Lang Wu, Yangqing Wang
First page: 949
Abstract: CO2 emissions prediction plays a key role in atmospheric environment management and regional sustainable development. Taking the Four Provinces of Mountains and Rivers (Henan, Hebei, Shandong, and Shanxi) in China as an example, the Autoregressive Integrated Moving Average Model (ARIMA) and random forest importance analysis were used to calculate the future trend of the CO2 emission–influencing factors and obtain the main influencing factors. Based on the above, BP neural network (BPNN), support vector machine (SVR), and random forest (RF) models were used to predict the future apparent CO2 emissions of the four provinces. The results show that, in general, population, coal consumption, and per capita GDP are the main factors influencing CO2 emissions. The RF model has the best prediction performance; for instance, RMSE (81.86), R2 (0.905), and MAE (64.69). The prediction results show that the total apparent CO2 emissions of the Four Provinces of Mountains and Rivers will peak in 2028 (with a peak of about 4500 Mt). The apparent CO2 emissions of Henan, Hebei, and Shandong Province peaked in 2011 (with a peak of about 654 Mt), 2013 (with a peak of about 657 Mt), and 2020 (with a peak of about 1273 Mt), respectively. Shanxi is forecast to reach its peak (with a peak of about 2486 Mt) in 2029. The apparent CO2 emissions of all provinces showed an obvious downward trend after reaching their peak. Henan, Hebei Shandong, and Shanxi showed a significant downward trend in 2018, 2023, and 2032, respectively.
Citation: Atmosphere
PubDate: 2024-08-08
DOI: 10.3390/atmos15080949
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 950: The Impact of Annual Cycles on Anomalous
Wind Meridional Structures of the ENSO
Authors: Yuhan Gong, Jiahao Lu, Tian Li
First page: 950
Abstract: The anomalous zonal wind moves southward during the ENSO mature phase in boreal winter. Previous studies suggest that it may be caused by the nonlinear interaction of annual cycles or the influence of background mean state changes. In this research, the ECHAM4.6 atmospheric model is used to confirm the mechanism of the anomalous zonal wind southward shifting. The annual cycle of solar radiation and SST are removed in the sensitivity experiments to avoid the interaction between the ENSO and annual cycle. The results show that the north–south asymmetry mode of the ENSO anomalous wind field is not the result of a nonlinear interaction between ENSO and the annual cycle. The mean v-winds in winter motivate the southward shifting of the ENSO anomalous wind field through advection.
Citation: Atmosphere
PubDate: 2024-08-08
DOI: 10.3390/atmos15080950
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 951: Raindrop Size Distribution Characteristics
for Typhoons over the Coast in Eastern China
Authors: Dongdong Wang, Sheng Chen, Yang Kong, Xiaoli Gu, Xiaoyu Li, Xuejing Nan, Sujia Yue, Huayu Shen
First page: 951
Abstract: This study investigates the characteristics of the raindrop size distribution (DSD) for five typhoons that made landfall or passed by Zhejiang on the eastern coast of China, from 2019 to 2022. Additionally, it examines the raindrop shape–slope (µ-Λ) relationship, as well as the local Z-R relationship for these typhoons. The DSD datasets were collected by the DSG1 disdrometer located in Ningbo, Zhejiang Province. Based on rainfall rate (R), the DSD can be categorized into convective and stratiform rainfall types. Some rainfall parameters can also be derived from the DSDs to further analyze the specific characteristics of rainfall. The histograms of the generalized intercept parameter (log10Nw) exhibit negative skewness in both convective and stratiform rainfall, whereas the histograms of the mass-weighted mean diameter (Dm) of raindrops display positive skewness. During typhoon periods on the eastern coast of China, the DSD characteristic was composed of a lower number concentration of small and midsize raindrops (3.42 for log10Nw, 1.43 mm for Dm in the whole dataset) as compared to Jiangsu in eastern China, Tokyo, in Japan, Miryang, in South Korea, and Thiruvananthapuram in south India, respectively. At the same time, the scatter plots of Dm and log10Nw indicate that the convective rain during typhoon periods exhibits characteristics that are intermediate between “maritime-like” and “continental-like” clusters. Additionally, the raindrop spectra of convective rainfall and midsize raindrops in stratiform rainfall are well-represented by a three-parameter gamma distribution. The µ-Λ relation in this region is similar to Taiwan and Fujian, located along the southeastern coast of China. The Z-R relationship for eastern coastal China during typhoons based on filtered disdrometer data is Z = 175.04R1.53. These results could offer deeper insights into the microphysical characteristics of different rainfall types along the eastern coast of China and potentially improve the accuracy of precipitation estimates from weather radar observations.
Citation: Atmosphere
PubDate: 2024-08-09
DOI: 10.3390/atmos15080951
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 952: Combined Exposure to High-Cholesterol Diet
and PM2.5: Brain Injury and Regulatory Mechanism of HIF-1α in
ApoE−/− Female Mice
Authors: Wenqi Chen, Shanshan Chen, Lirong Bai, Ruijin Li
First page: 952
Abstract: High-cholesterol diet (HCD) and fine particulate matter (PM2.5) are related to stroke. However, little is known about the combined effects of stroke, especially for females. This study investigated the brain injuries in Apolipoprotein E−/− (ApoE−/−) female mice exposed to HCD plus PM2.5 for 6 months. The protein levels of the genes related to stroke and the blood–brain barrier (BBB) in different groups of mice were measured. The molecular regulation mechanisms were explored. The results showed that HCD and PM2.5 co-exposure altered brain–body weight ratio, behavior, brain pathology, and inflammatory markers in mice relative to exposure to HCD or PM2.5 alone. Co-exposure significantly changed the expressions of HIF-1α and the key genes in its signaling pathway in the brains of mice compared to the single exposure. It suggests that the HIF-1α pathway exerts an important regulatory role in brain injury and behavioral abnormality in female mice after 6-month exposure to HCD plus PM2.5, which are potential mechanisms for HCD and PM2.5-triggering stroke in female individuals.
Citation: Atmosphere
PubDate: 2024-08-09
DOI: 10.3390/atmos15080952
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 953: Progress on Numerical Simulation of
Gas-Liquid Two-Phase Flow in Self-Priming Pump
Authors: Heng Qian, Hongbo Zhao, Chun Xiang, Zhenhua Duan, Sanxia Zhang, Peijian Zhou
First page: 953
Abstract: The fundamentals of the design and operation of self-priming pumps, as indispensable equipment in industry, have been the focus of research in the field of fluid mechanics. This paper begins with a comprehensive background on self-priming pumps and gas-liquid two-phase flow, and it outlines recent advances in the field. Self-priming pumps within the gas-liquid two-phase flow state and the spatial and temporal evolution of the transient characteristics of self-priming pumps determine the self-priming pump self-absorption performance. Through mastery of the self-absorption mechanism, high-performance self-absorption pump products can be formed to provide theoretical support for the development of products. In current research, numerical simulation has become an important tool for analyzing and predicting the behavior of gas-liquid two-phase flow in self-priming pumps. This paper reviews existing numerical models of gas-liquid two-phase flow and categorizes them. Reviewing these models not only provides us with a comprehensive understanding of the existing research but also offers possible directions for future research. The complexity of gas–liquid interactions and their impact on pump performance is analyzed. Through these detailed discussions, we are able to identify the challenges in the simulation process and summarize what has been achieved. In order to further improve the accuracy and reliability of simulations, this paper introduces the latest simulation techniques and research methodologies, which provide new perspectives for a deeper understanding of gas-liquid two-phase flow. In addition, this paper investigates a variety of factors which affect the operating efficiency of self-priming pumps, including the design parameters, fluid properties, and operating conditions. Comprehensive consideration of these factors is crucial for optimizing pump performance. Finally, this paper summarizes the current research results and identifies the main findings and deficiencies. Based on this, the need to improve the accuracy of numerical simulations and to study the design parameters in depth to improve pump performance is emphasized.
Citation: Atmosphere
PubDate: 2024-08-10
DOI: 10.3390/atmos15080953
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 954: Assimilating Satellite-Derived Snow Cover
and Albedo Data to Improve 3-D Weather and Photochemical Models
Authors: Colleen Jones, Huy Tran, Trang Tran, Seth Lyman
First page: 954
Abstract: During wintertime temperature inversion episodes, ozone in the Uinta Basin sometimes exceeds the standard of 70 ppb set by the US Environmental Protection Agency. Since ozone formation depends on sunlight, and less sunlight is available during winter, wintertime ozone can only form if snow cover and albedo are high. Researchers have encountered difficulties replicating high albedo values in 3-D weather and photochemical transport model simulations for winter episodes. In this study, a process to assimilate MODIS satellite data into WRF and CAMx models was developed, streamlined, and tested to demonstrate the impacts of data assimilation on the models’ performance. Improvements to the WRF simulation of surface albedo and snow cover were substantial. However, the impact of MODIS data assimilation on WRF performance for other meteorological quantities was minimal, and it had little impact on ozone concentrations in the CAMx photochemical transport model. The contrast between the data assimilation and reference cases was greater for a period with no new snow since albedo appears to decrease too rapidly in default WRF and CAMx configurations. Overall, the improvement from MODIS data assimilation had an observed enhancement in the spatial distribution and temporal evolution of surface characteristics on meteorological quantities and ozone production.
Citation: Atmosphere
PubDate: 2024-08-10
DOI: 10.3390/atmos15080954
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 955: A Novel Apportionment Method Utilizing
Particle Mass Size Distribution across Multiple Particle Size Ranges
Authors: Peizhi Wang, Qingsong Wang, Yuhuan Jia, Jingjin Ma, Chunying Wang, Liping Qiao, Qingyan Fu, Abdelwahid Mellouki, Hui Chen, Li Li
First page: 955
Abstract: Many cities in China are facing the dual challenge of PM2.5 and PM10 pollution. There is an urgent need to develop a cost-effective method that can apportion both with high-time resolution. A novel and practical apportionment method is presented in this study. It combines the measurement of particle mass size distribution (PMSD) with an optical particle counter (OPC) and the algorithm of normalized non-negative matrix factorization (N-NMF). Applied in the city center of Baoding, Hebei, this method separates four distinct pollution factors. Their sizes (ordered from the smallest to largest) range from 0.16 μm to 0.6 μm, 0.16 μm to 1.0 μm, 0.5 μm to 17.0 μm, and 2.0 μm to 20.0 μm, respectively. They correspondingly contribute to PM2.5 (PM10) with portions of 26% (17%), 37% (26%), 33% (41%), and 4% (16%), respectively, on average. The smaller three factors are identified as combustion, secondary, and industrial aerosols because of their high correlation with carbonaceous aerosols, nitrate aerosols, and trace elements of Fe/Mn/Ca in PM2.5, respectively. The largest-sized factor is linked to dust aerosols. The primary origin regions, oxidation degrees, and formation mechanisms of each source are further discussed. This provides a scientific basis for the comprehensive management of PM2.5 and PM10 pollution.
Citation: Atmosphere
PubDate: 2024-08-10
DOI: 10.3390/atmos15080955
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 956: Real-World Emission Characteristics of
Diesel Pallet Trucks under Varying Loads: Using the Example of China
Authors: Ye Zhang, Yating Song, Tianshi Feng
First page: 956
Abstract: Diesel pallet trucks, a type of heavy-duty diesel trucks (HDDTs), have historically been a vital component in logistics and transport due to their high payload capacity. However, they also present significant challenges, particularly in terms of emissions which contribute substantially to urban air pollution. Traditional HDDTs emission measurement methods, such as engine bench tests and those used in laboratory settings, often fail to capture real-world emission behaviors accurately. This study specifically examines the real-world emission characteristics of diesel pallet trucks exceeding 30 t under varying loads (unloaded, half loaded, and fully loaded) and different road conditions (urban, suburban, and high-speed). Considering that data quality is the key to the accuracy of the scheme, this research utilized a portable emission measurement system (PEMS) to capture real-time emissions data of carbon dioxide (CO2), carbon monoxide (CO), nitrogen oxides (NOX), and total hydrocarbons (THC). Key findings demonstrate a direct correlation between vehicle load and emission factors, with the emission factors for CO2, CO, and NOX increasing by 39.5%, 105.4%, and 22.7%, respectively, from unloaded to fully loaded states under comprehensive operating conditions. Regression analyses further provide an emission factor prediction model for HDDPTs, underscoring the continuous relationship between speed, load, and emission rates. These findings provide a scientific basis for pollution control strategies for diesel trucks.
Citation: Atmosphere
PubDate: 2024-08-11
DOI: 10.3390/atmos15080956
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 957: Relative Homogenization of Climatic Time
Series
Authors: Peter Domonkos
First page: 957
Abstract: Homogenization of the time series of observed climatic data aims to remove non-climatic biases caused by technical changes during the history of the climate observations. The spatial redundancy of climate information helps to recognize station-specific inhomogeneities with statistical methods, but the correct detection and removal of inhomogeneity biases is generally not easy for the combined effects of individual inhomogeneities. In a homogenization procedure, several time series of a given climatic variable observed in one climatic region are usually homogenized together via a large number of spatial comparisons between them. Such procedures are called relative homogenization. A relative homogenization procedure may include one or more homogenization cycles where a cycle includes the steps of time series comparison, inhomogeneity detection and corrections for inhomogeneities, and they may include other steps like the filtering of outlier values or spatial interpolations for infilling data gaps. Relative homogenization methods differ according to the number and content of the individual homogenization cycles, the procedure for the time series comparisons, the statistical inhomogeneity detection method, the way of the inhomogeneity bias removal, among other specifics. Efficient homogenization needs the use of tested statistical methods to be included in partly or fully automated homogenization procedures. Due to the large number and high variety of homogenization experiments fulfilled in the Spanish MULTITEST project (2015–2017), its method comparison test results are still the most informative about the efficiencies of homogenization methods in use. This study presents a brief review of the advances in relative homogenization, recalls some key results of the MULTITEST project, and analyzes some theoretical aspects of successful homogenization.
Citation: Atmosphere
PubDate: 2024-08-11
DOI: 10.3390/atmos15080957
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 958: Evaluation of GNSS-TEC Data-Driven
IRI-2016 Model for Electron Density
Authors: Jing Peng, Yunbin Yuan, Yanwen Liu, Hongxing Zhang, Ting Zhang, Yifan Wang, Zelin Dai
First page: 958
Abstract: The ionosphere is one of the important error sources that affect the communication of radio signals. The international reference ionosphere (IRI) model is a commonly used model to describe ionospheric parameters. The driving parameter IG12 of the IRI-2016 model was optimally updated based on GNSS-TEC data from 2015 and 2019. The electron density profiles and NmF2 calculated by the IRI-2016 model (upda-IRI-2016) driven by the updated IG12 value (IG-up) were evaluated for their accuracy using ionosonde observations and COSMIC inversion data. The experiments show that both the electron density profiles and NmF2 calculated by upda-IRI-2016 driven by IG-up show significant optimization effects, compared to the IRI-2016 model driven by IG12. For electron density, the precision improvement (PI) for both MAE and RMSE at the Beijing station exceed 31.2% in January 2015 and 16.0% in January 2019. While the PI of MAE and RMSE at the Wuhan station, which is located at a lower latitude, both exceed 32.5% in January 2015, both exceed 42.1% in January 2019, which is significantly higher than that of the Beijing station. In 2015, the PI of MAE and RMSE compared with COSMIC are both higher than 20%. For NmF2, the PI is greater for low solar activity years and low latitude stations, with the Wuhan station showing a PI of more than 11.7% in January 2019 compared to January 2015. The PI compared to COSMIC was higher than 17.2% in 2015.
Citation: Atmosphere
PubDate: 2024-08-12
DOI: 10.3390/atmos15080958
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 959: The Application of an Intermediate
Complexity Atmospheric Research Model in the Forecasting of the Henan 21.7
Rainstorm
Authors: Xingbao Wang, Qun Xu, Xiajun Deng, Hongjie Zhang, Qianhong Tang, Tingting Zhou, Fengcai Qi, Wenwu Peng
First page: 959
Abstract: To improve the forecast accuracy of heavy precipitation, re-forecasts are conducted for the Henan 21.7 rainstorm. The Intermediate Complexity Atmospheric Research Model (ICAR) and the Weather Research and Forecasting Model (WRF) with a 1 km horizontal grid spacing are used for the re-forecasts. The results indicate that heavy precipitation forecasted by ICAR primarily accumulates on the windward slopes of the mountains. In contrast, some severe precipitation forecasted by WRF is beyond the mountains. The main difference between ICAR and WRF is that ICAR excludes the “impacts of physical processes on winds and the nonlinear interactions between the small resolvable-scale disturbances” (briefed as the “physical–dynamical interactions”). Thus, heavy precipitation beyond the mountains is attributed to the “physical–dynamical interactions”. Furthermore, severe precipitation on the windward slopes of the mountains typically aligns with the observations, whereas heavy rainfall beyond the mountains seldom matches the observations. Therefore, severe precipitation on the windward slopes of (beyond) the mountains is more (less) predictable. Based on these findings and theoretical thinking about the predictability of severe precipitation, a scheme of using the ICAR’s prediction to adjust the WRF’s prediction is proposed, thereby improving the forecast accuracy of heavy rainfall.
Citation: Atmosphere
PubDate: 2024-08-12
DOI: 10.3390/atmos15080959
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 960: Long-Term Variability of Surface Ozone and
Its Associations with NOx and Air Temperature Changes from Air Quality
Monitoring at Belsk, Poland, 1995–2023
Authors: Izabela Pawlak, Janusz Krzyścin, Janusz Jarosławski
First page: 960
Abstract: Surface ozone (O3) and nitrogen oxides (NOx = NO + NO2) measured at the rural station in Belsk (51.83° N, 20.79° E), Poland, over the period of 1995−2023, were examined for long-term variability of O3 and its relationship to changes in the air temperature and NOx. Negative and positive trends were found for the 95th and 5th percentile, respectively, in the O3 data. A weak positive correlation (statistically significant) of 0.33 was calculated between O3 and the temperature averaged from sunrise to sunset during the photoactive part of the year (April–September). Recently, O3 maxima have become less sensitive to temperature changes, reducing the incidence of photochemical smog. The ozone–climate penalty factor decreased from 4.4 µg/m3/°C in the 1995–2004 period to 3.9 µg/m3/°C in the 2015−2023 period. The relationship between Ox (O3 + NO2) and NOx concentrations averaged from sunrise to sunset determined the local and regional contribution to Ox variability. The seasonal local and regional contributions remained unchanged in the period of 1995−2023, stabilizing the average O3 level at Belsk. “NOx-limited” and “VOC-limited” photochemical regimes prevailed in the summer and autumn, respectively. For many winter and spring seasons between 1995 and 2023, the type of photochemical regime could not be accurately determined, making it difficult to build an effective O3 mitigation policy.
Citation: Atmosphere
PubDate: 2024-08-12
DOI: 10.3390/atmos15080960
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 961: Environmental Policies and Countermeasures
for the Phase-Out of Ozone-Depleting Substances (ODSs) over the Last 30
Years: A Case Study in Taiwan
Authors: Wen-Tien Tsai
First page: 961
Abstract: It is well established that the reaction cycles involving some halogenated alkanes (so-called ozone-depleting substances—ODSs) contribute to the depletion of ozone in the stratosphere, prompting the Montreal Protocol (initially signed in 1987), and later amendments. The Protocol called for the scheduled phase-out of ODSs, including chlorofluorocarbons (CFCs), hydrochlorofluorocarbons (HCFCs), carbon tetrachloride (CCl4), halon, methyl chloroform (CH3CCl3), methyl chloride (CH3Cl), and even hydrofluorocarbons (HFCs). In view of the urgent importance of ozone layer protection to the global ecological environment, the Taiwanese government has taken regulatory actions to reduce ODS consumption since 1993, through the joint venture of the central competent authorities. Under the government’s regulatory requirements, and the industry’s efforts to adopt both alternatives to ODSs and abatement technologies, the phase-out of some ODSs (i.e., CFCs, CCl4, halon, and CH3CCl3) was achieved prior to 2010. The consumption of HCFCs and methyl chloride has significantly declined over the past three decades (1993–2022). However, HFC emissions indicated a V-type variation during this period. Due to local production and extensive use of HFCs in Taiwan, the country’s emissions increased from 663 kilotons of carbon dioxide equivalents (CO2eq) in 1993 to 2330 kilotons of CO2eq in 2001, and then decreased to 373 kilotons of CO2eq in 2011. Since then, the emissions of HFCs largely used as the alternatives to ODSs showed an upward trend, increasing to 1555 kilotons of CO2eq in 2022. To be in compliance with the Kigali Amendment (KA-2015) to the Montreal Protocol for mitigating global warming, the Taiwanese government has taken regulatory actions to reduce the consumption of some HFC substances with high global warming potential (GWP) under the authorization of the Climate Change Response Act in 2023, aiming at an 80% reduction by 2045 of the baseline consumption in 2024.
Citation: Atmosphere
PubDate: 2024-08-12
DOI: 10.3390/atmos15080961
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 962: Precipitation Characteristics and
Mechanisms over Sri Lanka against the Background of the Western Indian
Ocean: 1981–2020
Authors: Dan Ye, Xin Wang, Yong Han, Yurong Zhang, Li Dong, Hao Luo, Xinxin Xie, Danya Xu
First page: 962
Abstract: In the current environment of climate change, the precipitation situation of marine islands is particularly valued. So, this study explores precipitation characteristics and mechanisms over Sri Lanka in the background of the western Indian Ocean using satellite and reanalysis datasets based on 40 years (from 1981 to 2020). The results show that the highest precipitation occurs between October and December, accounting for 46.3% of the entire year. The Indian Ocean sea surface temperature warming after 2002 significantly influences precipitation patterns. Particularly during the Second Inter-Monsoon, the western Indian Ocean warming induces an east–west zonal sea surface temperature gradient, leading to low-level circulation and westerly wind anomalies. This, in turn, results in increased precipitation in Sri Lanka between October and December. This study used the Trend-Free Pre-Whitening Mann–Kendall test and Sen’s slope estimator to study nine extreme precipitation indices, identifying a significant upward trend in extreme precipitation events in the Jaffna, arid northern Sri Lanka, peaking on 9 November 2021. This extreme event is due to the influence of weather systems like the Siberian High and intense convective activities, transporting substantial moisture to Jaffna from the Indian Ocean, the Arabian Sea, and the Bay of Bengal during winter. The findings highlight the impact of sea surface temperature warming anomalies in the western Indian Ocean and extreme precipitation events, anticipated to be more accentuated during Sri Lanka’s monsoon season. This research provides valuable insights into the variability of tropical precipitation, offering a scientific basis for the sustainable development of marine islands.
Citation: Atmosphere
PubDate: 2024-08-12
DOI: 10.3390/atmos15080962
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 963: Comments on the Quantification of Thermal
Comfort and Heat Stress with Thermal Indices
Authors: Andreas Matzarakis
First page: 963
Abstract: Today, and when reflecting upon the growing effects of heat (and its respective quantification), it has never been clearer that these concerns will remain, if not augment, for decades to come [...]
Citation: Atmosphere
PubDate: 2024-08-13
DOI: 10.3390/atmos15080963
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 964: Humidity-Controlling Ceramic Bricks:
Enhancing Evaporative Cooling Efficiency to Mitigate Urban Heat Island
Effect
Authors: Xueli Jin, Junsong Wang, Kanghao Tan, Zhenjie Zou
First page: 964
Abstract: Passive evaporative cooling technology using the building envelope is a crucial measure to mitigate the urban heat island effect. This study aims to enhance the cooling efficiency of the surface of enclosure structures by utilizing volcanic ash, potassium–sodium stone powder, and silica-based mesoporous oxide (SMO) as primary materials. These components are incorporated into the ceramic brick production process to create innovative humidity-controlling ceramic bricks (HCCTs). This study extensively investigates the impact of SMO and the amount of applied glaze on the physical and mechanical characteristics of these HCCTs. Additionally, it examines the water absorption and evaporative cooling properties of the studied materials under optimal substitution conditions. Numerical calculations are used to determine the heat and moisture transfer properties of HCCTs. The results indicate that incorporating 2% SMO and applying 70 g/m2 of glaze results in a moisture absorption capacity of 385 g/m2 and a moisture discharge capacity of 370 g/m2. These conditions also yield a notable flexural strength of 15.2 MPa. Importantly, the HCCTs exhibit significantly enhanced capillary water absorption and water retention capabilities. Increased water absorption reduces surface temperature by 2–3 °C, maintaining the evaporative cooling effect for 20 to 30 h. It is also found that the temperature of HCCTs decreases linearly with increasing water content and porosity, while the temperature difference gradually decreases with thickness. Water migration in HCCTs with greater thickness is notably influenced by gravity, with water moving from top to bottom. Therefore, it is recommended that brick thickness does not exceed 15 mm.
Citation: Atmosphere
PubDate: 2024-08-13
DOI: 10.3390/atmos15080964
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 965: Estimation of Particulate Matter Levels in
City Center Pedestrian Routes with the Aid of Low-Cost Sensors
Authors: Dimos Dimitrios Plakotaris, Theodosios Kassandros, Evangelos Bagkis, Kostas Karatzas
First page: 965
Abstract: Particulate matter is one of the most dangerous air pollutants, especially in urban areas, due to its significant adverse health effects. Traditionally, air quality monitoring relies on fixed reference stations, which often have a low temporal and spatial resolution. To address this limitation, a low-cost, portable air quality monitoring device with a rapid measurement response was used to assess particulate matter concentration levels in the afternoon hours in central Thessaloniki, Greece. This approach enabled the identification of local hotspots directly related to human activities. Statistical analysis and spatial mapping were employed, and data collected were categorized using k-means clustering. The findings of the study suggest that data acquired via portable low-cost sensors can describe the local variability of PM2.5 concentrations. The results indicate that local activities, such as increased human accumulation, traffic congestion at traffic lights, market working hours, together with meteorological parameters, can significantly impact air quality in specific urban locations. They also highlight the differences between data recorded in colder and warmer periods, with the concentrations of PM2.5 in the first period being 3.7 μg/m3 greater on average than in the second. These differences are also identified via the k-means clustering method, which suggest that higher concentrations appear mostly during the colder period of the study.
Citation: Atmosphere
PubDate: 2024-08-13
DOI: 10.3390/atmos15080965
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 966: High-Resolution WRF Modeling of Wind and
Thermal Regimes with LCZ in Almaty, Kazakhstan
Authors: Tatyana Dedova, Larissa Balakay, Edige Zakarin, Kairat Bostanbekov, Galymzhan Abdimanap
First page: 966
Abstract: This study evaluates the effectiveness of the Weather Research and Forecasting (WRF) model in simulating high-resolution atmospheric conditions for Almaty, Kazakhstan, a city prone to stagnant winter air. While the previously used Bougeault and Lacarrere scheme for parameterizing the planetary boundary layer was applied in high-resolution modeling, the number of vertical levels was increased, and a detailed local climate zones (LCZs) map was included. Ground-based observations from meteorological stations and monitoring stations, remote sensing data, and radiosonde measurements are used to verify the model. Comparison results with ground-based observations show that the WRF model with the LCZ map provides a better representation of the wind and thermal regimes of Almaty compared to the three-class land use map, including in high resolution. A good correspondence of wind direction is demonstrated by comparing the modeling results with pollutant transport plumes recorded by remote sensing data. In addition, a good correlation was found between land surface temperature from satellite data and air temperature simulated by WRF with a resolution of 333 m. A comparison of simulated data and aerological measurements confirmed that downscaling did not have a significant impact on boundary layer calculations. Analysis of turbulent processes showed that the adopted model effectively describes the attenuation and dissipation of turbulent kinetic energy and reflects the typical diurnal variations of meteorological processes in the atmosphere of Almaty in the anticyclonic winter period. The results of high-resolution WRF modeling can form the basis for the development of a hybrid system capable of modeling atmospheric processes at the building level.
Citation: Atmosphere
PubDate: 2024-08-13
DOI: 10.3390/atmos15080966
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 967: Diurnal Variation in Summer Precipitation
and the Characteristics of Precipitation Events in the Western Tarim
Basin, China
Authors: Man Li, Zaiyong Zhang, Chenxiang Ju, Junqiang Yao
First page: 967
Abstract: The Tarim Basin in the western part of Northwest China (NWC) is the largest inland basin in the world and one of the most arid regions in the middle latitudes. In recent years, heavy precipitation events have occurred frequently in this region, especially in the western Tarim Basin (WTB), due to the climate change. Based on the hourly precipitation data from 2010 to 2022, the diurnal variation in summer precipitation and the characteristics of precipitation events with different durations in WTB have been analyzed. The results mainly show that (1) the diurnal variations in the precipitation amount (PA), precipitation frequency (PF) and precipitation intensity (PI) mainly present a unimodal pattern, but the times of maximum value do not coincide. The peak value of PA and PF appears between 01:00 and 03:00 BJT (Beijing Time), while the valley value appears around 18:00 BJT, yet the peak value of PI appears between 20:00 and 23:00 BJT with no obvious valley value. (2) There are some differences in the diurnal variation characteristics of precipitation among different summer months and different regions. (3) During the past decade, the precipitation structure in WTB has been continuously adjusted, and short-duration- and long-duration-precipitation-dominant periods appear alternately. On the whole, short-duration precipitation has been more frequent in summer, accounting for 70% of the total precipitation events and 40% of the total accumulated precipitation amount. These results can help us to better understand the refined physical characteristics of precipitation events and enhance our understanding of the local climate in the WTB under the background of climate change.
Citation: Atmosphere
PubDate: 2024-08-13
DOI: 10.3390/atmos15080967
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 968: Personal Recollections on Jack Herring and
Developments in Theory of Turbulence, Atmospheric Sciences, and
Computational Fluid Dynamics
Authors: Boris Galperin, Semion Sukoriansky
First page: 968
Abstract: The majority of articles in this Special Issue illuminate various aspects of Jack Herring’s contributions to the theory of turbulence, atmospheric sciences, and computational fluid dynamics (CFD), be it through his publications, presentations, collaborations, work with colleagues and students, or personal contacts [...]
Citation: Atmosphere
PubDate: 2024-08-13
DOI: 10.3390/atmos15080968
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 969: Emission Rate Estimation of Industrial Air
Pollutant Emissions Based on Mobile Observation
Authors: Xinlei Cui, Qi Yu, Weichun Ma, Yan Zhang
First page: 969
Abstract: Mobile observation has been widely used in the monitoring of air pollution. However, studies on pollution sources and emission characteristics based on mobile navigational observation are rarely reported in the literature. A method for quantitative source analysis for industrial air pollutant emissions based on mobile observations is introduced in this paper. NOx pollution identified in mobile observations is used as an example of the development of the method. A dispersion modeling scheme that fine-tuned the meteorological parameters according to the actual meteorological conditions was adopted to minimize the impact of uncertainties in meteorological conditions on the accuracy of small-scale dispersion modeling. The matching degree between simulated and observed concentrations was effectively improved through this optimization search. In response to the efficiency requirements of source resolution for multiple sources, a random search algorithm was first used to generate candidate solution samples, and then the solution samples were evaluated and optimized. Meanwhile, the new index Smatch was established to evaluate the quality of candidate samples, considering both numerical error and spatial distribution error of concentration, in order to address the non-uniqueness of the solution in the multi-source problem. Then, the necessity of considering the spatial distribution error of concentration is analyzed with the case study. The average values of NOx emission rates for the two study cases were calculated as 69.8 g/s and 70.8 g/s. The Smatch scores were 0.92–0.97 and 0.92–0.99. The results were close to the online monitoring data, and this kind of pollutant emission monitoring based on the mobile observation experiment was initially considered feasible. Additional analysis and clarifications were provided in the discussion section on the impact of uncertainties in meteorological conditions, the establishment of a priori emission inventories, and the interpretation of inverse calculation results.
Citation: Atmosphere
PubDate: 2024-08-13
DOI: 10.3390/atmos15080969
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 970: Emissions of Oxygenated Volatile Organic
Compounds and Their Roles in Ozone Formation in Beijing
Authors: Xiao Yan, Xionghui Qiu, Zhen Yao, Jiye Liu, Lin Wang
First page: 970
Abstract: Oxygenated volatile organic compound (OVOC) emissions play a critical role in tropospheric ozone (O3) formation. This paper aims to establish an emission inventory and source profile database for OVOCs in Beijing, utilizing revised and reconstructed data from field measurements and existing literature. The study also assesses their potential impact on the O3 base on the ozone formation potential (OFP). Results indicate that OVOC emissions in Beijing predominantly originate from natural and residential sources, encompassing commercial solvent usage, cooking, residential combustion, construction adhesives, and construction coatings. OVOCs contributed 5.6% to OFP, which is significantly less than their emission contribution of 20.1%. Major OFP contributors include plant sources (26.2%), commercial solvent use (21.0%), cooking (20.5%), and construction adhesives (8.4%). The primary OVOC species contributing to OFP for OVOCs are acetaldehyde, methanol, hexanal, ethanol, and acetone, collectively contributing 59.0% of the total OFP. Natural sources exhibit significant seasonal variability, particularly in summer when plant emissions peak, constituting 78.9% of annual emissions and significantly impacting summer ozone pollution (OFP of 13,954 t). Conversely, emissions from other OVOC sources remain relatively stable year-round. Thus, strategies to mitigate summer ozone pollution in Beijing should prioritize plant sources while comprehensively addressing residential sources in other seasons. District-specific annual OVOC emissions are from Fangshan (3967 t), Changping (3958 t), Daxing (3853 t), and Chaoyang (3616 t), which reflect year-round forested areas in these regions and high populations.
Citation: Atmosphere
PubDate: 2024-08-14
DOI: 10.3390/atmos15080970
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 971: Accumulation of Heavy Metals in Blueberry
(Vaccinium myrtillus L.) and Dominant Mosses (Pleurozium schreberi (Willd.
ex Brid.) Mitt.) as Bioindicators of the Expressway Influence on Forest
Ecosystems
Authors: Arkadiusz Warczyk, Piotr Gruba, Agnieszka Józefowska, Tomasz Wanic, Agata Warczyk, Bartłomiej Świątek, Julita Bujak, Marcin Pietrzykowski
First page: 971
Abstract: The intensive use, development, and expansion of the road network is expanding the zones of direct impact of road transport on forest ecosystems. Issues related to the mobility of trace elements in forest ecosystems along motorways are very important due to the numerous environmental risks associated with the excessive accumulation of metals, the ability to migrate and accumulate in plants and animals, and the risk of transferring these elements to higher trophic levels. The aim of this article was therefore to determine the impact of road traffic on the basis of contents of trace metals Cd, Cr, Cu, Ni, Pb, and Zn and to describe the relationship of these contents in moss gametophytes and blueberry leaves taken in the vicinity of an existing and variously expanded expressway (S7, Poland, Europe). Analyses of transport impacts included the effects of distance and time of pollutant deposition and road transport on habitat and stand conditions. The highest contents of Cd, Cr, Cu, Ni, Pb, and Zn in moss tissues were found in fir stands and the contents were, respectively, 0.36 mg·kg−1, 5.91 mg·kg−1, 12.5 mg·kg−1, 3.26 mg·kg−1, 8.82 mg·kg−1, and 55.28 mg·kg−1. Mosses showed the best bioindication capacity of all of the studied ecosystem elements. The Pb, Zn, Cr, Cu, and Ni contents were particularly markedly elevated in moss tissues relative to non-anthropopressured areas and dependent on distance from the emitter (road). Blueberry proved to be a less useful bioindicator, as the contents of Cd, Cr, Cu, Ni, Pb, and Zn found were similar to the data from non-anthropopressured areas and were, respectively, 0.09 mg·kg−1, 0.98 mg·kg−1, 7.12 mg·kg−1, 2.49 mg·kg−1, 1.18 mg·kg−1, and 15.91 mg·kg−1 in fir stands and 0.04 mg·kg−1, 0.47 mg·kg−1, 6.63 mg·kg−1, 1.65 mg·kg−1, 0.72 mg·kg−1, and 17.44 mg·kg−1 in pine stands.
Citation: Atmosphere
PubDate: 2024-08-14
DOI: 10.3390/atmos15080971
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 972: Variations in Cloud Concentration Nuclei
Related to Continental Air Pollution Control and Maritime Fuel Regulation
over the Northwest Pacific Ocean
Authors: Lei Sun, Wenxin Cui, Nan Ma, Juan Hong, Yujiao Zhu, Yang Gao, Huiwang Gao, Xiaohong Yao
First page: 972
Abstract: Here, we compared the concentrations of cloud condensation nuclei (CCN) and particle number size distributions (PNSDs) measured during the transient period from the winter to the summer East Asian monsoon in 2021 with those in 2014 to explore possible responses to how CCN responds to upwind continental air pollutant mitigation and marine traffic fuel sulfur content (FSC) regulation over the northwest Pacific Ocean (NWPO). We also employed the Positive Matrix Factorization (PMF) analysis to apportion concentrations of CCN (Nccn) to different sources in order to quantify its source-specified responses to mitigation of air pollution during the transient period. Our results showed that (1) upwind continental mitigation likely reduced Nccn by approximately 200 cm−3 and 400 cm−3 at 0.2% and 0.4% supersaturation (SS), respectively, in the marine background atmosphere over the NWPO; (2) FSC regulation resulted in a decrease in Nccn at 0.4% SS by about 50 cm−3 and was nearly negligible at 0.2% SS over the NWPO. Additionally, a PMF-resolved factor, characterized by a dominant nucleation mode, was present only in 2014 and disappeared in 2021, likely due to the reduction. This estimation, however, suffered from uncertainties since seasonal changes were hard to be deducted accurately. PMF-resolved factors accurately represented Nccn in 80–90% of cases, but this accuracy was not observed in the remaining cases. Finally, an integrated analysis of satellite-derived cloud parameters and ship-based measurements indicated that the reduced Nccn over the NWPO might be co-limited with meteorological factors in forming cloud droplets during the transient period.
Citation: Atmosphere
PubDate: 2024-08-14
DOI: 10.3390/atmos15080972
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 973: Atmospheric Conditions Related to Extreme
Heat and Human Comfort in the City of Rio de Janeiro (Brazil) during the
First Quarter of the Year 2024
Authors: Ayobami Badiru Moreira, Lucas Suassuna de Albuquerque Wanderley, Cristiana Coutinho Duarte, Andreas Matzarakis
First page: 973
Abstract: This study aims to investigate the atmospheric conditions and human thermal comfort related to extreme heat in Rio de Janeiro during the first quarter of 2024. The dataset includes meteorological data from the A636-Jacarepaguá station of INMET and seven stations from the Alerta Rio system. Weather types were classified using principal components analysis (PCA) and cluster analysis (CA). Additionally, three thermal comfort indices were calculated: the heat index (HI), physiologically equivalent temperature (PET), and modified PET (mPET). Five groups of surface weather types were identified, with two being more frequent and associated with extreme heat events. These two groups accounted for over 70% of the days in all months. Critical thermal sensation values were found, particularly at the Guaratiba station, where the daytime HI exceeded 60 °C, and at the Riocentro station, where the nighttime HI surpassed 40 °C. The HI showed a greater range and variability compared with the PET and mPET, highlighting the importance of investigating microclimatic factors which intensify urban heat in central and coastal areas and cause daytime overheating in more distant regions like Guaratiba. This study emphasizes the need for detailed investigation into microclimatic factors and their public health implications, especially in areas with high tourist activity and vulnerable populations.
Citation: Atmosphere
PubDate: 2024-08-14
DOI: 10.3390/atmos15080973
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 974: Weather Research and Forecasting Model
(WRF) Sensitivity to Choice of Parameterization Options over Ethiopia
Authors: Andualem Shiferaw, Tsegaye Tadesse, Clinton Rowe, Robert Oglesby
First page: 974
Abstract: Downscaling seasonal climate forecasts using regional climate models (RCMs) became an emerging area during the last decade owing to RCMs’ more comprehensive representation of the important physical processes at a finer resolution. However, it is crucial to test RCMs for the most appropriate model setup for a particular purpose over a given region through numerical experiments. Thus, this sensitivity study was aimed at identifying an optimum configuration in the Weather, Research, and Forecasting (WRF) model over Ethiopia. A total of 35 WRF simulations with different combinations of parameterization schemes for cumulus (CU), planetary boundary layer (PBL), cloud microphysics (MP), longwave (LW), and shortwave (SW) radiation were tested during the summer (June to August, JJA) season of 2002. The WRF simulations used a two-domain configuration with a 12 km nested domain covering Ethiopia. The initial and boundary forcing data for WRF were from the Climate Forecast System Reanalysis (CFSR). The simulations were compared with station and gridded observations to evaluate their ability to reproduce different aspects of JJA rainfall. An objective ranking method using an aggregate score of several statistics was used to select the best-performing model configuration. The JJA rainfall was found to be most sensitive to the choice of cumulus parameterization and least sensitive to cloud microphysics. All the simulations captured the spatial distribution of JJA rainfall with the pattern correlation coefficient (PCC) ranging from 0.89 to 0.94. However, all the simulations overestimated the JJA rainfall amount and the number of rainy days. Out of the 35 simulations, one that used the Grell CU, ACM2 PBL, LIN MP, RRTM LW, and Dudhia SW schemes performed the best in reproducing the amount and spatio-temporal distribution of JJA rainfall and was selected for downscaling the CFSv2 operational forecast.
Citation: Atmosphere
PubDate: 2024-08-14
DOI: 10.3390/atmos15080974
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 975: Examining the Impact of Climate Change
Risks on Pregnancy through a Climate Justice Lens: A Review
Authors: Olivia J. Keenan, Stefania Papatheodorou, Arnab K. Ghosh
First page: 975
Abstract: Climate change impacts such as climate-amplified weather events are increasing in intensity, frequency, and severity. Despite climate change affecting areas all around the world, the adverse impacts of climate change are unequally distributed, causing specific populations to be more susceptible to the impacts of climate change. Addressing climate inequalities in health research requires a climate justice approach, which prioritizes recognitional, distributional, and procedural justice in research and intervention design. Pregnant individuals are particularly vulnerable to climate change impacts since pregnancy represents a time of both psychological and physiological change that can be extremely sensitive to the environment. Nevertheless, there are few studies examining the association between pregnancy health and climate justice. This review evaluates the status of climate change impacts and pregnancy health outcomes through recognitional, distributive, and procedural justice definitions. We identify four themes already present in the literature: 1. Vulnerable Populations Within an Already Vulnerable Population, 2. Need for More Ecological-level Studies, 3. Addressing the Structural Factors that Drive Climate Injustice, and 4. Community-Centered Solutions Moving Forward. Our findings emphasize the importance of transdisciplinary, participatory, and multisectoral collaboration to improve climate-related pregnancy health interventions.
Citation: Atmosphere
PubDate: 2024-08-14
DOI: 10.3390/atmos15080975
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 976: Influence of Time–Activity Patterns
on Indoor Air Quality in Italian Restaurant Kitchens
Authors: Marta Keller, Davide Campagnolo, Francesca Borghi, Alessio Carminati, Giacomo Fanti, Sabrina Rovelli, Carolina Zellino, Rocco Loris Del Vecchio, Giovanni De Vito, Andrea Spinazzé, Viktor Gábor Mihucz, Carlo Dossi, Mariella Carrieri, Andrea Cattaneo, Domenico Maria Cavallo
First page: 976
Abstract: This study aims to delve deeper into the relationship between the professional activities carried out in restaurant kitchens and some key air pollutants. The ultrafine particles (UFPs), nitrogen dioxide (NO2), ozone (O3), Total Volatile Organic Compounds (TVOCs) and formaldehyde (HCHO) indoor air concentrations were determined using real-time monitors. Simultaneously, the kitchen environment was characterized using video recordings with the aim to retrieve information pertaining to cooking, cookware washing and surface cleaning activities. Statistical analysis was carried out separately for the winter and summer campaigns. The obtained results confirmed that the professional activities carried out in restaurant kitchens had a significant impact on the concentrations of all the selected pollutants. Specifically, this study revealed the following key results: (i) indoor UFPs and NO2 concentrations were significantly higher during cooking than during washing activities (e.g., about +60% frying vs. handwashing and dishwasher running), mainly in the winter; (ii) washing activity had a statistically significant impact on the TVOC (+39% on average) and HCHO (+67% on average) concentrations compared to other activities; (iii) some specific sources of short-term pollutant emissions have been identified, such as the different types of cooking and opening the dishwasher; and (iv) in some restaurants, a clear time-dependent relationship between O3 and UFP, TVOC and HCHO has been observed, underlining the occurrence of ozonolysis reactions.
Citation: Atmosphere
PubDate: 2024-08-15
DOI: 10.3390/atmos15080976
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 977: Evaluation of Near-Taiwan Strait Sea
Surface Wind Forecast Based on PanGu Weather Prediction Model
Authors: Jun Yi, Xiang Li, Yunfei Zhang, Jiawei Yao, Hongyu Qu, Kan Yi
First page: 977
Abstract: Utilizing observed wind speed and direction data from observation stations near the Taiwan Strait and ocean buoys, along with forecast data from the EC model, GRAPES_GFS model, and PanGu weather prediction model within the same period, RMSE, MAE, CC, and other parameters were calculated. To comparatively evaluate the forecasting performance of the PanGu weather prediction model on the sea surface wind field near the Taiwan Strait from 00:00 on 1 June 2023, to 23:00 on 31 May 2024. The PanGu weather prediction model is further divided into the ERA5 (PanGu) model driven by ERA5 initial fields and the GRAPES_GFS (PanGu) model driven by GRAPES_GFS initial fields. The main conclusions are as follows: (1) over a one-year evaluation period, for wind speed forecasts with lead times of 0 h to 120 h in the Taiwan Strait region, the overall forecasting skill of the PanGu weather prediction model is superior to that of the model forecasts; (2) different initial fields input into the PanGu weather prediction model lead to different final forecast results, with better initial field data corresponding to forecast results closer to observations, thus indicating the operational transferability of the PanGu model in smaller regions; (3) regarding forecasts of wind speed categories, the credibility of the results is high when the wind speed level is ≤7, and the PanGu weather prediction model performs better among similar forecasts; (4) although the EC model’s wind direction forecasts are closer to the observation field results, the PanGu weather forecasting model also provides relatively accurate and rapid forecasts of the main wind directions within a shorter time frame.
Citation: Atmosphere
PubDate: 2024-08-15
DOI: 10.3390/atmos15080977
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 978: Evaluation of Fine Particulate Matter
(PM2.5) Concentrations Measured by Collocated Federal Reference Method and
Federal Equivalent Method Monitors in the U.S.
Authors: Tanvir R. Khan, Zachery I. Emerson, Karen H. Mentz
First page: 978
Abstract: The comparison between Federal Equivalent Method (FEM) and Federal Reference Method (FRM) monitors in measuring fine particulate matter (PM2.5) concentrations frequently raises concerns about the accuracy and reliability of data. The comparability, or lack thereof, of data between FRM and FEM monitors may have significant implications for maintaining compliance with the National Ambient Air Quality Standards (NAAQSs). This study investigates the performance of continuous FEM monitors collocated with FRM monitors across 10 EPA regions in the U.S., focusing on PM2.5 measurements collected from 276 monitoring stations. Through an analysis of annually averaged paired concentration data, the study examines concentration ratios (FEM/FRM) and associated biases (in %, defined as [(FEM/FRM)−1] × 100) in FEM monitors across different manufacturers, measurement methods, EPA regions, and sampling location types. The study findings reveal a varied distribution of FEM/FRM ratios, with more than 50% of the FEM monitors having FEM/FRM > 1.1 and approximately 30% having FEM/FRM > 1.2. Substantial variations in estimated biases are identified among monitor types, measurement methods, EPA regions, and sampling site locations. Light scatter-based FEM monitors, notably Teledyne models 640 and 640x, dominate all locations (urban, suburban, and rural), with rural areas exhibiting higher mean bias values for both light scatter and beta attenuation FEM monitors (41% and 23%, respectively). On average, light scatter-based FEM monitors demonstrate higher biases compared to beta attenuation monitors across all EPA regions (28% vs. 12%). Irrespective of the measurement method employed, FEM monitors demonstrate a significant positive bias (mean bias 22%) relative to FRM monitors, which could result in an overestimation of PM2.5 design values (DVs) by 13–21% at monitoring sites designating FEMs as primary monitors for NAAQSs compliance designations. These findings emphasize the critical need to address method comparability issues, especially considering the recent tightening of NAAQSs for PM2.5 (annual) from 12 µg/m3 to 9 µg/m3 in the U.S.
Citation: Atmosphere
PubDate: 2024-08-15
DOI: 10.3390/atmos15080978
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 979: Multilevel Drought-Induced Resistance and
Resilience Analysis for Vegetation in the Yellow River Basin
Authors: Jingjing Fan, Wenwei Zhang, Fanfan Xu, Xiong Zhou, Wei Dong, Chenyu Wu, Shibo Wei, Yue Zhao, Dongnan Wang
First page: 979
Abstract: In this study, a multilevel drought-induced resistance and resilience analysis (MDRRA) approach was developed to investigate the stability of vegetation in the Yellow River Basin (YRB). MDRRA was quantified by utilizing the Normalized Difference Vegetation Index (NDVI). It was applied to YRB to assess vegetation resistance and resilience to various levels of drought by utilizing precipitation and NDVI data from 2000 to 2019. The results reveal that vegetation resistance and resilience in YRB are affected by drought severity. Monthly and annual changes in SPI over the warm–temperate humid zone of the YRB show a decreasing trend, with rates of 0.001 per decade and 0.034 per decade, respectively; however, the other climatic subregions exhibit an increasing trend, with rates ranging from 0.002 per decade to 0.82 per decade. Over 77.56% of the downstream areas show increases in the annual SPI averages. Drought severity differs across subregions in the YRB. More severe drought events occur in its upper and middle reaches, while less severe ones happen in its lower reaches. As the drought severity increases, the arid and semiarid regions of the mesothermal zone exhibit a decrease in the resistance and resilience indices. MDRRA can help improve the stability and resilience of the ecosystem in the YRB.
Citation: Atmosphere
PubDate: 2024-08-15
DOI: 10.3390/atmos15080979
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 980: Indoor Concentration Distributions of
Ammonia and Sulfur-Based Odorous Substances According to Types of Laying
Hen Houses in South Korea
Authors: Ki-Youn Kim, Jung-Kon Kim
First page: 980
Abstract: In South Korea, environmental complaints related to livestock odors continue to increase, and various efforts are underway to overcome them. An objective of this study is to monitor indoor concentrations of ammonia and sulfur-based odorous substances emitted from laying hen houses in South Korea through on-site visits for one year to understand their temporal emission patterns. The highest concentration was found in ammonia (NH3), at 6.92 ppmv, followed by hydrogen sulfide (H2S), at 8.98 ppbv. The concentrations of methyl mercaptan (CH3SH), dimethyl sulfide (DMS), and dimethyldisulfide (DMDS) ranged from sub ppbv to 10 ppbv. In general, there was no consistent concentration distribution of ammonia and sulfur-based odorous substances in laying hen houses between those with forced ventilation and natural ventilation. Regarding the seasonal distribution of odorous compounds, their concentrations in winter season (December to February) when the ventilation rate in laying hen houses decreased were generally higher than those in the summer season (June to August) when the ventilation rate in poultry buildings was relatively high, which is applied to properly maintain the thermal environment in laying hen houses. The limitation of this study is that unexpected conditions such as clearance of laying hen houses, chicken shipments, and disorders of exhaust fans were not controlled for intentionally due to on-site investigations.
Citation: Atmosphere
PubDate: 2024-08-15
DOI: 10.3390/atmos15080980
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 981: Monthly Precipitation Outlooks for Mexico
Using El Niño Southern Oscillation Indices Approach
Authors: Miguel Angel González-González, Arturo Corrales-Suastegui
First page: 981
Abstract: The socioeconomic sector increasingly relies on accessible and cost-effective tools for predicting climatic conditions. This study employs a straightforward decision tree classifier model to identify similar monthly ENSO (El Niño Southern Oscillation) conditions from December 2000 to November 2023, using historically monthly ENSO Indices data from December 1950 to November 2000 as a reference. The latter is to construct monthly precipitation hindcasts for Mexico spanning from December 2000 to November 2023 through historically high-resolution monthly precipitation rasters. The model’s performance is evaluated at a global and local scale across seasonal periods (winter, spring, summer, and fall). Assessment using global Hansen–Kuiper Skill Score and Heidkee Skill Score metrics indicates skillful performance across all seasons (>0.3) nationwide. However, local metrics reveal a higher spatial percent of corrects (>0.40) in winter and spring, corresponding to dry seasons, while a lower percent of corrects (<0.40) are observed in more extensive areas during summer and fall, indicative of rainy seasons, due to increased variability in precipitation. The choice of averaging method influences the degree of underestimations and overestimations, impacting the model’s variability. Spearman correlations highlight regions with significant model performance, revealing potential misinterpretations of high hit rates during winter and spring. Notably, during the fall, the model demonstrates spatial skill across most of Mexico, while in the spring, it performs well in the southern and northeastern regions and, in the summer, in the northwestern areas. Integration of accurate forecasts of ENSO Indices to predict precipitation months ahead is crucial for the operational efficacy of this model, given its heavy reliance on anticipating ENSO behavior. Overall, the empirical method exhibits great promise and potential for application in other developing countries directly impacted by the El Niño phenomenon, owing to its low resource costs.
Citation: Atmosphere
PubDate: 2024-08-16
DOI: 10.3390/atmos15080981
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 982: A Laboratory Model of the Large-Scale
Atmospheric Circulation of Tidally Locked Exoplanets
Authors: Bálint Vass, Ádám Kadlecsik, Miklós Vincze
First page: 982
Abstract: We report on a novel fluid dynamics experiment configuration based on a modified version of the differentially heated rotating annulus, a widely used laboratory model of the large-scale mid-latitude atmospheric circulation. Through applying an azimuthally (zonally) inhomogeneous, dipole-like thermal boundary condition—imitating a permanent “day side” and “night side” in the rotating setting—we explore the character of the flow patterns emerging at different values of the zonal temperature contrast and rotation rate. This configuration may prove to be a useful minimal model of the large-scale atmospheric circulation of tidally locked exoplanets.
Citation: Atmosphere
PubDate: 2024-08-16
DOI: 10.3390/atmos15080982
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 983: Projection of Extreme Summer Precipitation
over Hubei Province in the 21st Century
Authors: Abrar Mubark, Qian Chen, Mohamed Abdallah, Awad Hussien, Monzer Hamadalnel
First page: 983
Abstract: The link between the escalation of global warming and the increase in extreme precipitation events necessitates a deeper understanding of future trends. This study focused on the dynamics of extreme rainfall in Hubei Province throughout the 21st century, a region already sensitive to climatic shifts and extreme weather occurrences. Using the high-resolution global climate model RegCM4 driven by another high-resolution model, HadGEM2-ES, and based on the representative concentration pathway (RCP8.5) emissions scenario, this research predicted the changes in rainfall patterns in Hubei Province during the summer of the 21st century. The accuracy of the adjusted model was confirmed through the use of five extreme rainfall indices (EPIs), namely maximum 5-day amount of precipitation (RX5day), number of heavy rain days (R10), the simple daily intensity index (SDII), consecutive dry days (CDD), and consecutive wet days (CWD), that measured the intensity and frequency of such events. In particular, excluding the index for continuous dry days (CDD), there was an anticipated increase in extreme rainfall during the summer in the mid-21st century. The number of heavy rain days (R10mm) increased significantly (p < 0.05) in the southeastern parts, especially for Wuhan, Xiantao, Qianjiang, Jinzhou, and Ezhou. The EPI values were higher in southeastern Hubei. Consequently, areas such as Wuhan, Xiantao, and Qianjiang in Hubei Province are projected to face more frequent and severe extreme rainfall episodes as the century progresses.
Citation: Atmosphere
PubDate: 2024-08-16
DOI: 10.3390/atmos15080983
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 984: Spatial Dynamic Interaction Effects and
Formation Mechanisms of Air Pollution in the Central Plains Urban
Agglomeration in China
Authors: Jie Huang, Hongyang Lu, Yajun Huang
First page: 984
Abstract: Accurately identifying the dynamic interaction effects and network structure characteristics of air pollution is essential for effective collaborative governance. This study investigates the spatial dynamic interactions of air pollution among 30 cities in the Central Plains Urban Agglomeration using convergent cross mapping. Social network analysis is applied to assess the overall and node characteristics of the spatial interaction network, while key driving factors are analyzed using an exponential random graph model. The findings reveal that air pollution levels in the Central Plains Urban Agglomeration initially increase before they decrease, with heavily polluted cities transitioning from centralized to sporadic distribution. Among the interactions, Heze’s air pollution impact on Kaifeng was the strongest, while Xinxiang’s impact on Changzhi was the weakest. The emission and receiving effects peaked during 2010–2012. The air pollution interactions among cities exhibit significant network characteristics, with block model results indicating that emitting and receiving relationships are primarily concentrated in the bidirectional spillover plate. Natural factors such as temperature and precipitation significantly influence the spatial interaction network. Economic and social factors like economic level and industrial sector proportion also have a significant impact. However, population density does not influence the spatial interaction network. This study contributes to understanding the spatial network of air pollution, thereby enhancing strategies for optimizing regional collaborative governance efforts to address air pollution.
Citation: Atmosphere
PubDate: 2024-08-16
DOI: 10.3390/atmos15080984
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 985: Generating Daily High-Resolution Regional
XCO2 by Deep Neural Network and Multi-Source Data
Authors: Wenjie Tian, Lili Zhang, Tao Yu, Dong Yao, Wenhao Zhang, Chunmei Wang
First page: 985
Abstract: CO2 is one of the primary greenhouse gases impacting global climate change, making it crucial to understand the spatiotemporal variations of CO2. Currently, commonly used satellites serve as the primary means of CO2 observation, but they often suffer from striping issues and fail to achieve complete coverage. This paper proposes a method for constructing a comprehensive high-spatiotemporal-resolution XCO2 dataset based on multiple auxiliary data sources and satellite observations, utilizing multiple simple deep neural network (DNN) models. Global validation results against ground-based TCCON data demonstrate the excellent accuracy of the constructed XCO2 dataset (R is 0.94, RMSE is 0.98 ppm). Using this method, we analyze the spatiotemporal variations of CO2 in China and its surroundings (region: 0°–60° N, 70°–140° E) from 2019 to 2020. The gapless and fine-scale CO2 generation method enhances people’s understanding of CO2 spatiotemporal variations, supporting carbon-related research.
Citation: Atmosphere
PubDate: 2024-08-16
DOI: 10.3390/atmos15080985
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 986: Investigating Different Interpolation
Methods for High-Accuracy VTEC Analysis in Ionospheric Research
Authors: Serkan Doğanalp, İrem Köz
First page: 986
Abstract: The dynamic structure of the ionosphere and its changes play an important role in comprehending the natural cycle by linking earth sciences and space sciences. Ionosphere research includes a variety of fields like meteorology, radio wave reflection from the atmosphere, atmospheric anomaly detection, the impact on GNSS (Global Navigation Satellite Systems) signals, the exploration of earthquake precursors, and the formation of the northern lights. To gain further insight into this layer and to monitor variations in the total electron content (TEC), ionospheric maps are created using a variety of data sources, including satellite sensors, GNSS data, and ionosonde data. In these maps, data deficiencies are addressed by using interpolation methods. The objective of this study was to obtain high-accuracy VTEC (Vertical Total Electron Content) information to analyze TEC anomalies as precursors to earthquakes. We propose an innovative approach: employing alternative mathematical surfaces for VTEC calculations, leading to enhanced change analytical interpretation for anomaly detections. Within the scope of the application, the second-degree polynomial method, kriging (point and block model), the radial basis multiquadric, and the thin plate spline (TPS) methods were implemented as interpolation methods. During a 49-day period, the TEC values were computed at three different IGS stations, generating 1176 hourly grids for each interpolation model. As reference data, the ionospheric maps produced by the CODE (Center for Orbit Determination in Europe) Analysis Center were used. This study’s findings showed that, based on statistical values, the TPS model offered more accurate results than other methods. Additionally, it has been observed that the peak values in TEC calculations based on polynomial surfaces are eliminated in TPSs.
Citation: Atmosphere
PubDate: 2024-08-17
DOI: 10.3390/atmos15080986
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 987: A Generalised Additive Model and Deep
Authors: Md Wahiduzzaman, Alea Yeasmin
First page: 987
Abstract: This study introduces an innovative analytical methodology for examining the interconnections among the atmosphere, ocean, and society. The primary area of interest pertains to the North Atlantic Oscillation (NAO), a notable phenomenon characterised by daily to decadal fluctuations in atmospheric conditions over the Northern Hemisphere. The NAO has a prominent impact on winter weather patterns in North America, Europe, and to some extent, Asia. This impact has significant ramifications for civilization, as well as for marine, freshwater, and terrestrial ecosystems, and food chains. Accurate predictions of the surface NAO hold significant importance for society in terms of energy consumption planning and adaptation to severe winter conditions, such as winter wind and snowstorms, which can result in property damage and disruptions to transportation networks. Moreover, it is crucial to improve climate forecasts in order to bolster the resilience of food systems. This would enable producers to quickly respond to expected changes and make the required modifications, such as adjusting their food output or expanding their product range, in order to reduce potential hazards. The forecast centres prioritise and actively research the predictability and variability of the NAO. Nevertheless, it is increasingly evident that conventional analytical methods and prediction models that rely solely on scientific methodologies are inadequate in comprehensively addressing the transdisciplinary dimension of NAO variability. This includes a comprehensive view of research, forecasting, and social ramifications. This study introduces a new framework that combines sophisticated Big Data analytic techniques and forecasting tools using a generalised additive model to investigate the fluctuations of the NAO and the interplay between the ocean and atmosphere. Additionally, it explores innovative approaches to analyze the socio-economic response associated with these phenomena using text mining tools, specifically modern deep learning techniques. The analysis is conducted on an extensive corpora of free text information sourced from media outlets, public companies, government reports, and newspapers. Overall, the result shows that the NAO index has been reproduced well by the Deep-NAO model with a correlation coefficient of 0.74.
Citation: Atmosphere
PubDate: 2024-08-17
DOI: 10.3390/atmos15080987
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 988: An Interseasonal Comparison of Soil
Respiration in Xeric and Mesic Pine Forest Ecosystems in Central Siberia
Authors: Makhnykina Anastasia, Eugene Vaganov, Alexey Panov, Daria Polosukhina, Anatoly Prokushkin
First page: 988
Abstract: An understanding of how boreal forest composition responds to global environmental changes is an important challenge to predicting the future global carbon balance. Boreal forests are the most significant sink for atmospheric carbon dioxide; however, their sequestration capacity is highly sensitive to ongoing climate changes. The combination of the hydrothermal conditions of a territory strongly regulates its biogeochemical processes. The carbon fluxes in boreal forests are strongly mediated by the ground vegetation cover, composed of mosses (mesic) and lichens (xeric). Despite the concurrence of xeric and mesic vegetation types, their responses to climate variations varies significantly. Soil emission is an informative indicator of ecosystem functioning. In this study, we focused on the soil CO2 dynamics during frost-free seasons with different precipitation regimes in the xeric and mesic boreal ecosystems of Central Siberia. Seasonal measurements of soil CO2 emissions were conducted during frost-free seasons using the dynamic chamber method. Our findings reveal that the precipitation regimes of each year may control the seasonal soil emission dynamics. The soil moisture is the most important driver of emissions growth in the water-limited lichen pine forest (R2adj. = 18%). The soil temperature plays the largest role in the feather moss pine forest during the dry (R2adj. = 31%) seasons, and in the lichen pine forest during the wet (R2adj. = 41%) seasons. The cumulative efflux for the xeric and mesic sites is mostly related to the hydrothermal conditions, and not to the differences in ground vegetation cover. During the dry seasons, on average, the soil CO2 emissions are 45% lower than during the wet seasons for both sites. These findings emphasize the need for estimating and including the hydrothermal characteristics of the growing season for detailed emission assessments.
Citation: Atmosphere
PubDate: 2024-08-17
DOI: 10.3390/atmos15080988
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 989: Evolution of Dew and Rain Water Resources
in Gujarat (India) between 2005 and 2021
Authors: Rupal Budhbhatti, Anil K. Roy, Marc Muselli, Daniel Beysens
First page: 989
Abstract: The present study, carried out in Gujarat (India) between 2005 and 2021, aims to prepare dew and rain maps of Gujarat over a long period (17 years, from 2005 to 2021) in order to evaluate the evolution of the potential for dew and rain in the state. The ratio of dew to precipitation is also determined, which is an important metric that quantifies the contribution of dew to the overall water resources. Global warming leads, in general, to a reduction in precipitation and non-rainfall water contributions such as dew. The study shows, however, a rare increase in the rainfall and dew condensation, with the latter related to an increase in relative humidity and a decrease in wind amplitudes. Rain primarily occurs during the monsoon months, while dew forms during the dry season. Although dew alone cannot resolve water scarcity, it nonetheless may provide an exigent and unignorable contribution to the water balance in time to come. According to the site, the dew–rain ratios, which are also, in general, well correlated with dew yields, can represent between 4.6% (Ahmedabad) and 37.2% (Jamnagar). The positive trend, observed since 2015–2017, is expected to continue into the future.
Citation: Atmosphere
PubDate: 2024-08-17
DOI: 10.3390/atmos15080989
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 990: Forecasting In-Flight Icing over Greece:
Insights from a Low-Pressure System Case Study
Authors: Petroula Louka, Ioannis Samos, Flora Gofa
First page: 990
Abstract: Forecasting in-flight icing conditions is crucial for aviation safety, particularly in regions with variable and complex meteorological configurations, such as Greece. Icing accretion onto the aircraft’s surfaces is influenced by the presence of supercooled water in subfreezing environments. This paper outlines a methodology of forecasting icing conditions, with the development of the Icing Potential Algorithm that takes into consideration the meteorological scenarios related to icing accretion, using state-of-the-art Numerical Weather Prediction model results, and forming a fuzzy logic tree based on different membership functions, applied for the first time over Greece. The synoptic situation of an organized low-pressure system passage, with occlusion, cold and warm fronts, over Greece that creates dynamically significant conditions for icing formation was investigated. The sensitivity of the algorithm was revealed upon the precipitation, cloud type and vertical velocity effects. It was shown that the greatest icing intensity is associated with single-layer ice and multi-layer clouds that are comprised of both ice and supercooled water, while convectivity and storm presence lead to also enhancing the icing formation. A qualitative evaluation of the results with satellite, radar and METAR observations was performed, indicating the general agreement of the method mainly with the ground-based observations.
Citation: Atmosphere
PubDate: 2024-08-17
DOI: 10.3390/atmos15080990
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 991: Spatial Mapping of Air Pollution Hotspots
around Commercial Meat-Cooking Restaurants Using Bicycle-Based Mobile
Monitoring
Authors: Gwang-Soon Yong, Gun-Woo Mun, Kyung-Hwan Kwak
First page: 991
Abstract: Mobile measurement techniques are increasingly utilized to monitor urban emissions, regional air quality, and air pollutant exposure assessments. This study employed a bicycle measurement method to obtain the detailed distribution of air pollutant concentrations in roadside, commercial, residential, and recreational areas. The study area is located in Chuncheon, South Korea, with approximately 280,000 residents. Black carbon (BC), PM2.5, and NO2 were monitored using portable devices equipped on an electric bicycle. Results showed that in the evening (6–8 p.m.), the concentrations were higher in both commercial and residential areas compared to the background location, while concentrations were notably elevated only in roadside areas in the morning (8–10 a.m.). Spatial mapping of measured concentrations revealed that the highest concentrations corresponded to areas with densely operated charbroiling meat-cooking restaurants. Additionally, it was confirmed that BC and PM2.5 emitted from the commercial areas influenced nearby recreational areas (e.g., streamside roads). In conclusion, this study demonstrated that air pollutant hotspots resulting from human activities, such as dining at commercial restaurants, significantly worsen the local air quality on a small scale. Efforts to reduce the uncontrolled emissions of air pollutants from charbroiling meat-cooking restaurants are necessary.
Citation: Atmosphere
PubDate: 2024-08-17
DOI: 10.3390/atmos15080991
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 992: The Evaluation of Rainfall Forecasting in
a Global Navigation Satellite System-Assisted Numerical Weather Prediction
Model
Authors: Hongwu Guo, Yongjie Ma, Zufeng Li, Qingzhi Zhao, Yuan Zhai
First page: 992
Abstract: Accurate water vapor information is crucial for improving the quality of numerical weather forecasting. Previous studies have incorporated tropospheric water vapor data obtained from a global navigation satellite system (GNSS) into numerical weather models to enhance the accuracy and reliability of rainfall forecasts. However, research on evaluating forecast accuracy for different rainfall levels and the development of corresponding forecasting platforms is lacking. This study develops and establishes a rainfall forecasting platform supported by the GNSS-assisted weather research and forecasting (WRF) model, quantitatively assessing the effect of GNSS precipitable water vapor (PWV) on the accuracy of WRF model forecasts for light rain (LR), moderate rain (MR), heavy rain (HR), and torrential rain (TR). Three schemes are designed and tested using data from seven ground meteorological stations in Xi’an City, China, in 2021. The results show that assimilating GNSS PWV significantly improves the forecast accuracy of the WRF model for different rainfall levels, with the root mean square error (RMSE) improvement rates of 8%, 15%, 19%, and 25% for LR, MR, HR, and TR, respectively. Additionally, the RMSE of rainfall forecasts demonstrates a decreasing trend with increasing magnitudes of assimilated PWV, particularly effective in the range of [50, 55) mm where the lowest RMSE is 3.58 mm. Moreover, GNSS-assisted numerical weather model shows improvements in statistical forecasting indexes such as probability of detection (POD), false alarm rate (FAR), threat score (TS), and equitable threat score (ETS) across all rainfall intensities, with notable improvements in the forecasts of HR and TR. These results confirm the high precision, visualization capabilities, and robustness of the developed rainfall forecasting platform.
Citation: Atmosphere
PubDate: 2024-08-17
DOI: 10.3390/atmos15080992
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 993: Long-Term Wind and Air Temperature
Patterns in the Southeastern Region of Iran through Model Simulation and
Ground Observations
Authors: Nasim Hossein Hamzeh, Abbas Ranjbar Saadat Abadi, Khan Alam, Karim Abdukhakimovich Shukurov, Christian Opp
First page: 993
Abstract: Dust storms are one of the important natural hazards that affect the lives of inhabitants all around the world, especially in North Africa and the Middle East. In this study, wind speed, wind direction, and air temperature patterns are investigated in one of the dustiest cities in Sistan Basin, Zahedan City, located in southeast Iran, over a 17-year period (2004–2020) using a WRF model and ground observation data. The city is located near a dust source and is mostly affected by local dust storms. The World Meteorology Organization (WMO) dust-related codes show that the city was affected by local dust, with 52 percent of the total dust events occurring during the period (2004–2021). The city’s weather station reported that 17.5% and 43% were the minimum and maximum dusty days, respectively, during 2004–2021. The summer and July were considered the dustiest season and month in the city. Since air temperature, wind speed, and wind direction are important factors in dust rising and propagation, these meteorological factors were simulated using the Weather Research and Forecasting (WRF) model for the Zahedan weather station. The WRF model’s output was found to be highly correlated with the station data; however, the WRF simulation mostly overestimated when compared with station data during the study period (2004–2020). The model had a reasonable performance in wind class frequency distribution at the station, demonstrating that 42.6% of the wind was between 0.5 and 2, which is in good agreement with the station data (42% in the range of 0.5–2). So, the WRF model effectively simulated the wind class frequency distribution and the wind direction at Zahedan station, despite overestimating the wind speed as well as minimum, maximum, and average air temperatures during the 17-year period.
Citation: Atmosphere
PubDate: 2024-08-19
DOI: 10.3390/atmos15080993
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 994: Evaluation of Scikit-Learn Machine
Authors: Dan Wang, Yanbo Shen, Dong Ye, Yanchao Yang, Xuanfang Da, Jingyue Mo
First page: 994
Abstract: This article aims to evaluate the performance of solar radiation forecasts produced by CMA-WSP v2.0 (version 2 of the China Meteorological Administration Wind and Solar Energy Prediction System) and to explore the application of machine learning algorithms from the scikit-learn Python library to improve the solar radiation prediction made by the CMA-WSP v2.0. It is found that the performance of the solar radiation forecasting from the CMA-WSP v2.0 is closely related to the weather conditions, with notable diurnal fluctuations. The mean absolute percentage error (MAPE) produced by the CMA-WSP v2.0 is approximately 74% between 11:00 and 13:00. However, the MAPE ranges from 193% to 242% at 07:00–08:00 and 17:00–18:00, which is greater than that observed at other daytime periods. The MAPE is relatively low (high) for both sunny and cloudy (overcast and rainy) conditions, with a high probability of an absolute percentage error below 25% (above 100%). The forecasts tend to underestimate (overestimate) the observed solar radiation in sunny and cloudy (overcast and rainy) conditions. By applying machine learning models (such as linear regression, decision trees, K-nearest neighbors, random forests regression, adaptive boosting, and gradient boosting regression) to revise the solar radiation forecasts, the MAPE produced by the CMA-WSP v2.0 is significantly reduced. The reduction in the MAPE is closely connected to the weather conditions. The models of K-nearest neighbors, random forests regression, and decision trees can reduce the MAPE in all weather conditions. The K-nearest neighbor model exhibits the most optimal performance among these models, particularly in rainy conditions. The random forest regression model demonstrates the second-best performance compared to that of the K-nearest neighbor model. The gradient boosting regression model has been observed to reduce the MAPE of the CMA-WSP v2.0 in all weather conditions except rainy. In contrast, the adaptive boosting (linear regression) model exhibited a diminished capacity to improve the CMA-WSP v2.0 solar radiation prediction, with a slight reduction in MAPE observed only in sunny (sunny and cloudy) conditions. In addition, the input feature selection has a considerable influence on the performance of the machine learning model. The incorporation of the time series data associated with the diurnal variation of solar radiation as an input feature can further improve the model’s performance.
Citation: Atmosphere
PubDate: 2024-08-19
DOI: 10.3390/atmos15080994
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 995: Assessment of Perceived Indoor Air Quality
in the Classrooms of Slovenian Primary Schools and Its Association with
Authors: An Galičič, Jan Rožanec, Andreja Kukec, Sašo Medved, Ivan Eržen
First page: 995
Abstract: From a public health perspective, it is necessary to improve indoor air quality (IAQ) in schools. This study aims to assess the state of perceived IAQ in Slovenian school classrooms and its association with the selected IAQ factors to improve the understanding of perceived IAQ for designing public health interventions aimed to improve IAQ in schools. A national cross-sectional study was performed in all 454 Slovenian primary schools in the school year 2019/2020. The questionnaires were filled out by the 3rd-grade teachers with the support of the caretakers. Teachers rated the IAQ in the classroom as the worst in winter. We found that the teachers’ perceived IAQ in the classroom is statistically significantly associated with the micro location of the school and some of the IAQ factors. Poor IAQ is associated with reduced manual airing of classrooms due to the thermal comfort of the occupants. Interventions should be aimed at improving occupants’ adaptive behaviors to increase the frequency of natural ventilation in classrooms.
Citation: Atmosphere
PubDate: 2024-08-19
DOI: 10.3390/atmos15080995
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 996: Climatic Suitability for Outdoor Tourism
in Romania’s Big Cities
Authors: Adina-Eliza Croitoru, Ștefana Banc, Andreea-Sabina Scripcă, Adina-Viorica Rus
First page: 996
Abstract: This research aims to assess the climatic temporal suitability over the year and identify the appropriate season for open-air tourism in ten Romanian cities. It was evaluated using the Enhanced Tourism Climatic Index on a temporal scale of one day and then aggregated to 10 days over 61 years (1961–2021). Daily mean and maximum temperature, mean and minimum relative humidity, wind speed, precipitation, and sunshine hours were employed in the investigation. The Mann–Kendall test and Sen’s slope were used for trend detection in the frequency, season duration, and first/last suitable day during the year for outdoor tourism. Acceptable or better weather conditions usually begin in the last part of April and end in mid-October, with Good or better conditions lasting between 260 and 310 days/year. The trend shows a shift of Good conditions earlier in the year (0.3–9.0 days/decade), resulting in a longer season duration (0.8–13.0 days/decade) for open-air activities. The trend is statistically significant mainly for the extra-Carpathian regions. Big differences in open-air events number during the climatically suitable season have been identified among the cities considered (2–19 events/year). This study is useful for better planning open-air events and activities for tourism and recreation.
Citation: Atmosphere
PubDate: 2024-08-20
DOI: 10.3390/atmos15080996
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 997: Recent Advances in SCR Systems of
Heavy-Duty Diesel Vehicles—Low-Temperature NOx Reduction Technology
and Combination of SCR with Remote OBD
Authors: Zhengguo Chen, Qingyang Liu, Haoye Liu, Tianyou Wang
First page: 997
Abstract: Heavy-duty diesel vehicles are a significant source of nitrogen oxides (NOx) in the atmosphere. The Selective Catalytic Reduction (SCR) system is a primary aftertreatment device for reducing NOx emissions from heavy-duty diesel vehicles. With increasingly stringent NOx emission regulations for heavy-duty vehicles in major countries, there is a growing focus on reducing NOx emissions under low exhaust temperature conditions, as well as monitoring the conversion efficiency of the SCR system over its entire lifecycle. By reviewing relevant literature mainly from the past five years, this paper reviews the development trends and related research results of SCR technology, focusing on two main aspects: low-temperature NOx reduction technology and the combination of SCR systems with remote On-Board Diagnostics (OBD). Regarding low-temperature NOx reduction technology, the results of the review indicate that the combination of multiple catalytic shows potential for achieving high conversion efficiency across a wide temperature range; advanced SCR system arrangement can accelerate the increase in exhaust temperature within the SCR system; solid ammonium and gaseous reductants can effectively address the issue of urea not being able to be injected under low-temperature exhaust conditions. As for the combination of SCR systems with remote OBD, remote OBD can accurately assess NOx emissions from heavy-duty vehicles, but it needs algorithms to correct data and match the emission testing process required by regulations. Remote OBD systems are crucial for detecting SCR tampering, but algorithms must be developed to balance accuracy with computational efficiency. This review provides updated information on the current research status and development directions in SCR technologies, offering valuable insights for future research into advanced SCR systems.
Citation: Atmosphere
PubDate: 2024-08-20
DOI: 10.3390/atmos15080997
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 998: Impact of May–June Antarctic
Oscillation on July–August Heat-Drought Weather in Yangtze River
Basin
Authors: Zhengxuan Yuan, Jun Zhang, Liangmin Du, Ying Xiao, Sijing Huang
First page: 998
Abstract: Investigating the physical mechanism behind the formation of summer heat-drought weather (HDW) in the Yangtze River Basin (YRB) holds significant importance for predicting summer precipitation and temperature patterns in the region as well as disaster mitigation and prevention. This study focuses on spatiotemporal patterns of July–August (JA) HDW in the YRB from 1979 to 2022, which is linked partially to the preceding May–June (MJ) Antarctic Oscillation (AAO). Key findings are summarized as follows: (1) The MJ AAO displays a marked positive correlation with the JA HDW index (HDWI) in the southern part of upper YRB (UYRB), while showing a negative correlation in the area extending from the Han River to the western lower reaches of the YRB (LYRB); (2) The signal of MJ AAO persists into late JA through a specific pattern of Sea Surface Temperature anomalies in the Southern Ocean (SOSST). This, in turn, modulates the atmospheric circulation over East Asia; (3) The SST anomalies in the South Atlantic initiate Rossby waves that cross the equator, splitting into two branches. One branch propagates from the Somali-Tropical Indian Ocean, maintaining a negative-phased East Asia–Pacific (EAP) teleconnection pattern. This enhances the moisture flow from the Pacific towards the middle and lower reaches of the Yangtze River Basin (MYRB-LYRB). The other branch propagates northward, crossing the Somali region, and induces a positive geopotential height anomaly over Urals-West Asia. This reduces the southwesterlies towards the UYRB, thereby contributing to HDW variabilities in the region. (4) Partial Least Squares Regression (PLSR) demonstrated predictive capability for JA HDW in the YRB for 2022, based on Southern Ocean SST.
Citation: Atmosphere
PubDate: 2024-08-20
DOI: 10.3390/atmos15080998
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 999: The Black Sea Upwelling System: Analysis
on the Western Shallow Waters
Authors: Maria Emanuela Mihailov
First page: 999
Abstract: Upwelling is due to the combined effect of the coastal divergence process and Ekman pumping. The author aims to investigate two new upwelling indices for the Black Sea, derived from climate reanalysis models and the following in situ data: (a) the Coastal Upwelling Transport Index (CUTI) that estimates the rate of vertical volume transport and (b) the Biologically Effective Upwelling Transport Index (BEUTI) that estimates the nitrate flux into the surface mixed layer. Average monthly wind by the European Centre for Medium-Range Weather Forecasts (ECMWF) and Copernicus Marine Services for the Black Sea basin is used to calculate the CUTI and BEUTI Indexes for over 26 years (1993–2019) to analyse the sites along the North-Western Black Sea where changes in divergence phenomena occur. From 2000 to 2018, 31 divergence processes were observed based on daily in situ data from the coastal monitoring stations, with significant predominance in late spring and early summer. Nitrate supply by coastal upwelling has been estimated by combining sea surface temperature and salinity for the in situ data for the North-Western Black Sea shallow waters, and BEUTI indices were determined. Comparing 18 years of data results, the calculated indices and the observed upwelling events showed significant correlations.
Citation: Atmosphere
PubDate: 2024-08-20
DOI: 10.3390/atmos15080999
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 1000: Theory and Modelling of Isotropic
Turbulence: From Incompressible through Increasingly Compressible Flows
Authors: Claude Cambon
First page: 1000
Abstract: Homogeneous isotropic turbulence (HIT) has been a useful theoretical concept for more than fifty years of theory, modelling, and calculations. Some exact results are revisited in incompressible HIT, with special emphasis on the 4/5 Kolmogorov law. The finite Reynolds number effect (FRN), which yields corrections to that law, is investigated, using both Kármán–Howarth-type equations and a statistical spectral closure of the Eddy-Damped Quasi-Normal Markovian (EDQNM)-type. This discussion offers an opportunity to give an extended review of such spectral closures, from weak turbulence, as in wave turbulence theory, to a strong one. Extensions of the 4/5 or 4/3 Kolmogorov/Monin laws to anisotropic cases, such as stably stratified and MHD turbulence, are briefly touched on. Before addressing more recent work on compressible isotropic turbulence, the simplest case of quasi-incompressible turbulence subjected to externally imposed isotropic compression or dilatation is presented. Rapid distortion theory is found to be a poor model in this isotropic case, in contrast with its relevance in strongly anisotropic flow cases. Accordingly, a fully nonlinear approach based on a rescaling of all fluctuating variables is used, in order to show its interplay with the linear operator. This opens the discussion on the cases of homogeneous incompressible turbulence, where RDT and nonlinear models are relevant, provided that anisotropy is accounted for. Finally, isotropic compressible flows of increasing complexity are considered. Recent studies using weak turbulence theory, modelling, and DNS are discussed. A final unpublished study involves interactions between the solenoidal mode, inherited from incompressible turbulence, and the acoustic and entropic modes, which are specific to the compressible problem. An approach to acoustic wave turbulence, with resonant triads, is revisited on this occasion.
Citation: Atmosphere
PubDate: 2024-08-20
DOI: 10.3390/atmos15081000
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 1001: The Assessment of Precipitation and
Droughts in the Aegean Region Using Stochastic Time Series and
Standardized Precipitation Index
Authors: Ahmet Tanrıkulu, Ulker Guner, Ersin Bahar
First page: 1001
Abstract: This study analyzes drought conditions in the Aegean region using monthly precipitation data from nine stations between 1972 and 2020. The Standardized Precipitation Index (SPI) was calculated for 1-, 3-, 6-, 9-, and 12-month periods to evaluate drought conditions at different timescales and station-specific conditions. The results indicate that short-term droughts are more frequent but shorter in duration, while longer periods exhibit fewer but more prolonged droughts. The relative frequency of drought across all periods ranges between 9% and 27%. The İzmir and Denizli stations were highlighted due to their representation of coastal and inner regions, respectively. The findings show that coastal stations, like İzmir, experience more frequent wet years compared to inner stations like Denizli, which have more dry years. Time series linear autoregressive (AR) models, using SPI-12 data, were developed to represent long-term drought trends and forecasts. The best-fitting models were determined using AIC, AICC, FPE, and Var(e) criteria, with AR(2) generally being the most suitable, except for Denizli. This integrated analysis of SPI and AR models provides a robust basis for understanding regional precipitation regimes and predicting future droughts, aiding in the development of effective drought mitigation strategies and water resource management. Future research is anticipated to extend this analysis to encompass all of Turkey and explore various time series models’ applicability.
Citation: Atmosphere
PubDate: 2024-08-20
DOI: 10.3390/atmos15081001
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 1002: The Long-Term Monitoring of Atmospheric
Polychlorinated Dibenzo-p-Dioxin Dibenzofurans at a Background Station in
Taiwan during Biomass Burning Seasons in El Niño and La Niña
Events
Authors: Shih Yu Pan, Yen-Shun Hsu, Yuan Cheng Hsu, Tuan Hung Ngo, Charles C.-K. Chou, Neng-Huei Lin, Kai Hsien Chi
First page: 1002
Abstract: To measure the long-range transport of PCDD/Fs, a background sampling site at Mt. Lulin station (Taiwan) was selected based on meteorological information and its location relative to burning events in Southeast Asia. During regular sampling periods, a higher concentration of PCDD/Fs was recorded in 2008 at Mt. Lulin station during La Niña events, with levels reaching 390 fg I-TEQ/m3. In contrast, a higher concentration of 483 fg I-TEQ/m3 was observed in 2013 during biomass burning events. This indicates that La Niña affects the ambient PCDD/F concentrations. The ratio of ΣPCDD/ΣPCDF was 0.59, suggesting significant long-range transport contributions from 2007 to 2023. From 2007 to 2015, the predominant species was 2,3,4,7,8-PCDF, accounting for 25.3 to 39.6% of the total PCDD/Fs. From 2018 onward, 1,2,3,7,8-PCDD became more dominant, accounting for 15.0 to 27.1%. According to the results from the receptor model PMF (n = 150), the sources of PCDD/Fs were identified as dust storms and monsoon events (19.3%), anthropogenic activity (28.5%), and biomass burning events (52.2%). The PSCF values higher than 0.7 highlighted potential PCDD/F emission source regions for Mt. Lulin during biomass burning events, indicating high PSCF values in southern Thailand, Cambodia, and southern Vietnam.
Citation: Atmosphere
PubDate: 2024-08-20
DOI: 10.3390/atmos15081002
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 1003: Sun Declination and Distribution of
Natural Beam Irradiance on Earth
Authors: José A. Rueda, Sergio Ramírez, Miguel A. Sánchez, Juan de Dios Guerrero
First page: 1003
Abstract: The daily path of the Sun across longitude yields night and day, but the Sun also travels across latitude on a belt 47° wide. The solar meridian declination explains the latitudinal budget of natural beam irradiance (NBI), which is defined as the irradiance delivered to the Earth’s surface as a normal projection from the Sun. Data for the Sun meridian declination were obtained from the Spencer model, known as the geometric model. The distribution of NBI was weighed for the latitudinal belt between the Tropics of Cancer and Capricorn. The variation in the parameters of solar meridian declination were found to be analogous to that of pendular motion. The joint distributions of the solar meridian declination against its own velocity, or that of the velocity against the acceleration of solar meridian declination, displayed circular functions. The NBI budget that a particular latitude gathers, fluctuates in inverse proportion to the velocity of solar meridian declination, yielding 18 sun-paths per degree for latitudes above 20°, or 6 sun-paths per degree of latitude for latitudes under 20°. At an average Sun–Earth distance of 1 AU, all sites of the planet, whose latitude coincides, whether within or between hemispheres, accumulate an equivalent budget of NBI.
Citation: Atmosphere
PubDate: 2024-08-20
DOI: 10.3390/atmos15081003
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 1004: Elucidating Decade-Long Trends and
Diurnal Patterns in Aerosol Acidity in Shanghai
Authors: Zhixiao Lv, Xingnan Ye, Weijie Huang, Yinghui Yao, Yusen Duan
First page: 1004
Abstract: Aerosol acidity is a critical factor affecting atmospheric chemistry. Here, we present a study on annual, monthly, and daily variations in PM2.5 pH in Shanghai during 2010–2020. With the effective control of SO2 emissions, the NO2/SO2 ratio increased from 1.26 in 2010 to 5.07 in 2020 and the NO3−/SO42− ratio increased from 0.68 to 1.49. Aerosol pH decreased from 3.27 in 2010 to 2.93 in 2020, regardless of great achievement in reducing industrial SO2 and NOx emissions. These findings suggest that aerosol acidity might not be significantly reduced in response to the control of SO2 and NOx emissions. The monthly variation in pH values exhibited a V-shape trend, mainly attributable to aerosol compositions and temperature. Atmospheric NH3 plays the decisive role in buffering particle acidity, whereas Ca2+ and K+ are important acidity buffers, and the distinct pH decline during 2010–2016 was associated with the reduction of Ca2+ and K+ while both temperature and SO42− were important drivers in winter. Sensitivity tests show that pH increases with the increasing relative humidity in summer while it is not sensitive to relative humidity in winter due to proportional increases in Hair+ and aerosol liquid water content (ALWC). Our results suggest that reducing NOx emissions in Shanghai will not significantly affect PM2.5 acidity in winter.
Citation: Atmosphere
PubDate: 2024-08-20
DOI: 10.3390/atmos15081004
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 1005: Causes for the Occurrence of Severe
Drought at the Ogasawara (Bonin) Islands during the El Niño Event
in 2018–2019
Authors: Hiroshi Matsuyama
First page: 1005
Abstract: The Ogasawara (Bonin) Islands, consisting of more than 30 islands and located approximately 1000 km south of central Tokyo, occasionally experience severe droughts. Severe drought does not typically occur during El Niño (EN) events in the Ogasawara Islands because convective activity around the tropical western Pacific is inactive during EN events and correspondingly induces substantial precipitation around the Ogasawara Islands through the Pacific–Japan (P-J) pattern. However, a severe drought in 2018–2019 occurred during EN. In this study, we investigated the causes of drought occurrence. In 2018–2019, the El Niño Modoki (EN Modoki) event occurred simultaneously with EN, which decreased precipitation around the Ogasawara Islands from autumn to the following spring. This was induced by the positive sea level pressure anomaly and anticyclonic circulation around the Ogasawara Islands peculiar to the EN Modoki condition. In relation to the 2018–2019 drought, the investigation of past drought events at the Ogasawara Islands revealed that the drought in the spring and summer of 1991 also occurred during the simultaneous occurrence of the EN and EN Modoki events.
Citation: Atmosphere
PubDate: 2024-08-20
DOI: 10.3390/atmos15081005
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 1006: The Implementation of Cloud and Vertical
Velocity Relocation/Cycling System in the Vortex Initialization of the
HAFS
Authors: JungHoon Shin, Zhan Zhang, Bin Liu, Yonghui Weng, Qingfu Liu, Avichal Mehra, Vijay Tallapragada
First page: 1006
Abstract: The first version operational Hurricane Analysis and Forecast System (HAFS) implemented the Vortex Initialization (VI) technique to optimize tropical cyclone structure and intensity, which was adopted from the Hurricane Weather Research and Forecasting system (HWRF) and does not initialize cloud hydrometeors and vertical velocity. This limitation in the VI caused the inconsistency issue between hurricane vortex and its cloud in the model initial condition. A new VI, which can relocate or cycle cloud hydrometeors and vertical velocity, has been developed to solve this issue. For the cold start, the VI simply relocates the cloud and vertical velocity fields of Global Forecasting System (GFS) analysis; for the warm start, the cloud and vertical velocity associated with a hurricane in the GFS analysis are replaced by the fields extracted from the 6 h HAFS forecast of a previous cycle. This new VI has been tested for the 2023 HAFS-A real-time experiment configuration, and another sensitivity experiment without relocating or cycling both cloud and vertical velocity is conducted to examine the effect of the new VI. A comparison of the results reveals that the new VI improves the intensity forecast and generates a very realistic initial cloud field in correct position. Validating the model initial conditions with observed radar data reveals that the new VI captures the secondary eyewall of major hurricanes and asymmetric convective structure of weak tropical storms. This improvement of the cloud field in the model initial condition through the new VI expects to provide a better background for further data assimilation. Additional sensitivity experiment that only relocates or cycles cloud hydrometeors without correcting the vertical velocity field results in poorer intensity forecasts, which highlights the importance of vertical velocity in the model initial condition.
Citation: Atmosphere
PubDate: 2024-08-20
DOI: 10.3390/atmos15081006
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 1007: Meteorological Modulation of Atmospheric
Boundary Layer Height over a Caribbean Island
Authors: Alejandro Álvarez-Valencia, Juan L. Colón-Perez, Mark R. Jury, Héctor J. Jiménez
First page: 1007
Abstract: This study analyzes fluctuations in the atmospheric boundary layer height (aBLH) over a Caribbean island using hourly measured and model-interpolated data from the 2019–2023 period. Our focus is the mean structure, diurnal cycle, and aBLH correlation with meteorological parameters on the leeward coast at Mayaguez (18.2 N, 67.1 W). The mean diurnal cycle of the aBLH increases from 300 m near sunrise (07:00) to 1200 m by 13:00 because of turbulent heating. Summer-time thermal circulations lead to a 3 °C increase in near-surface dewpoint temperature (Td) that propagates upward to 3000 m by 16:00. A case study demonstrates how mid-day trade winds turn onshore and generate significant rainfall and river discharge across the island. The context for this study is provided by a 24 yr cluster analysis that identifies rainfall over the island’s northwest interior driven by upstream heating. Analysis of linear trends from 1979 to 2023 shows that Td declined by −0.02 °C/yr above 1500 m because of large-scale subsidence. However, cool interior forests transpire humidity and instill contrasting trends that may amplify climate extremes. A better understanding of entrainment at the top of the atmospheric boundary layer could be critical for managing future water resources in Caribbean islands.
Citation: Atmosphere
PubDate: 2024-08-20
DOI: 10.3390/atmos15081007
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 1008: Effects of the 2024 Total Solar Eclipse
on the Structure of the Planetary Boundary Layer: A Preliminary Analysis
Authors: Robert Pasken, Richard Woodford, Jimmy Bergmann, Carter Hickel, Margaret Ideker, Riley Jackson, Jack Rotter, Benjamin Schaefer
First page: 1008
Abstract: A total solar eclipse provides an unparalleled opportunity to study the changes in the atmosphere’s planetary boundary layer (PBL) due to changes in radiative heating. Although previous eclipse studies have demonstrated that significant changes occur, few studies have explored the evolution of these changes. To better understand the changes in the lowest layers of the PBL during an eclipse, a multi-sensor sampling approach was taken. Radiosonde launches were used to explore the depth of the column, while Unmanned Aerial Vehicles (UAVs) were used to document with high-resolution the brief changes in the vertical structure of the PBL caused by the eclipse. These changes highlighted differences from previous studies that relied solely on radiosonde and/or mesonet data alone. Higher-resolution sampling of the lower PBL showed a delay in the local vertical mixing as well as changes in the PBL height from pre- to post-eclipse. Slow responses were noted at the top of the PBL while very rapid changes to the PBL profile were captured in the near-surface layer. These changes highlighted differences from previous studies that relied solely on radiosonde and/or mesonet data alone. A preliminary analysis of the collected data highlighted a slow response to the eclipse near the top of the planetary boundary layer (radiosonde data) with very rapid changes noted in the near surface layer (UAV data). Preliminary results show that PBL heights remained nearly constant until well after third contact when a 35 hPa lowering of the PBL heights was observed and were limited to the lowest 25 hPa. The UAV soundings demonstrated the development of a strong inversion where the air below 990 hPa rapidly cooled with a nearly 1 °C drop in temperature observed. These observed changes raise interesting questions about how the lower and upper parts of the planetary boundary layer interact.
Citation: Atmosphere
PubDate: 2024-08-21
DOI: 10.3390/atmos15081008
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 1009: VOCs Concentration, SOA Formation
Contribution and Festival Effects during Heavy Haze Event: A Case Study in
Zhengzhou, Central China
Authors: Shijie Yu, Chaofang Xue, Fuwen Deng, Qixiang Xu, Bingnan Zhao
First page: 1009
Abstract: In this study, online ambient volatile organic compounds (VOCs) were collected at an urban site of Zhengzhou in Central China during February 2018. The VOCs characteristics, source contributions and the Chinese New Year (CNY) effects have been investigated. During the sampling period, three haze periods have been identified, with the corresponding VOCs concentrations of (92 ± 45) ppbv, (62 ± 18) ppbv and (83 ± 34) ppbv; in contrast, the concentration during non-haze days was found to be (57 ± 27) ppbv. In addition, the festival effects of the CNY were investigated, and the concentration of particulate matter precursor decreased significantly. Meanwhile, firework-displaying events were identified, as the emission intensity had been greatly changed. Both potential source contribution function (PSCF) and the concentration weighted trajectory (CWT) models results indicated that short-distance transportation was the main influencing factor of the local VOCs pollution, especially by transport from the northeast. Source contribution results by the positive matrix factorization (PMF) model showed that vehicle exhaust (24%), liquid petroleum gas and natural gas (LPG/NG, 23%), coal combustion (21%), industrial processes (16%) and solvent usages (16%) were the major sources of ambient VOCs. Although industry and solvents have low contribution to the total VOCs, their secondary organic aerosol (SOA) contribution were found to be relatively high, especially in haze-1 and haze-3 periods. The haze-2 period had the lowest secondary organic aerosol potential (SOAp) during the sampling period; this is mainly caused by the reduction of industrial and solvent emissions due to CNY.
Citation: Atmosphere
PubDate: 2024-08-21
DOI: 10.3390/atmos15081009
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 1010: Comparative Analysis of Two Tornado
Processes in Southern Jiangsu
Authors: Yang Li, Shuya Cao, Xiaohua Wang, Lei Wang
First page: 1010
Abstract: Jiangsu is a province in China and has the highest frequency of tornado occurrences. Studying the meteorological background and mechanisms of tornado formation is crucial for predicting tornado events and preventing the resulting disasters. This paper analyzed the meteorological background, instability mechanisms, and lifting conditions of the two Enhanced Fujita Scale level 2 (EF2) and above tornadoes that occurred in southern Jiangsu on 14 May 2021 (“5.14”) and 6 July 2020 (“7.06”) using ERA5 reanalysis data. Detailed analyses of the internal structure of tornado storms were conducted using Changzhou and Qingpu radar data. The results showed that (1) both tornadoes occurred in warm and moist areas ahead of upper-level troughs with significant dry air transport following the cold troughs. The continuous strengthening of low-level warm and moist advection was crucial in maintaining potential instability and triggering tornado vortices. The 14 May tornado formed within a low-level shear line and a warm area of a surface trough, while the 6 July tornado occurred at the end of a low-level jet stream, north of the eastern section of a quasi-stationary front. (2) The convective available potential energy (CAPE) and K indices for both tornado processes were very close (391 for “5.14” and 378 for “7.06”), with the lifting condensation level (LCL) near the ground. The “5.14” showed greater instability and more favorable thermodynamic conditions, with deep southwesterly jets at the mid-level shear line producing rotation under strong convergent action (convergence center value exceeding −1 × 10−4s−1). In contrast, the “7.06” was driven by super-low-level jet stream pulsations and wind direction convergence under the influence of the Meiyu Front (convergence center value exceeding −1.5 × 10−4 s−1), resulting in intense lifting and vertical vorticity triggered by a surface convergence line. (3) The “5.14” tornado process involved a supercell storm over a surface dry line experiencing tilting due to strong vertical wind shear, which led to the formation of smaller cyclonic vortices near a hook echo that developed into a tornado. The “7.06” developed on a bow echo structure within a mesoscale convective system formed over the Meiyu Front, where dry air subsidence, entrainment, and convergence of the southeast jet stream triggered a “miniature” supercell. The relevant research results provide a reference for the prediction and early warning of tornadoes.
Citation: Atmosphere
PubDate: 2024-08-21
DOI: 10.3390/atmos15081010
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 1011: Oxidation of Aminoacetaldehyde Initiated
by the OH Radical: A Theoretical Mechanistic and Kinetic Study
Authors: Ashraful Alam, Gabriel da Silva
First page: 1011
Abstract: Aminoacetaldehyde (glycinal, NH2CH2CHO) is a first-generation oxidation product of monoethanolamine (MEA, NH2CH2CH2OH), a solvent widely used for CO2 gas separation, which is proposed as the basis for a range of carbon capture technologies. A complete oxidation mechanism for MEA is required to understand the atmospheric transformation of carbon capture plant emissions, as well as the degradation of this solvent during its use and the oxidative destruction of waste solvent. In this study, we have investigated the •OH radical-initiated oxidation chemistry of aminoacetaldehyde using quantum chemical calculations and RRKM theory/master equation kinetic modeling. This work predicts that aminoacetaldehyde has a tropospheric lifetime of around 6 h and that the reaction predominantly produces the NH2CH2C•O radical intermediate at room temperature, along with minor contributions from NH2•CHCHO and •NHCH2CHO. The dominant radical intermediate NH2CH2C•O is predicted to promptly dissociate to NH2•CH2 and CO, where NH2•CH2 is known to react with O2 under tropospheric conditions to form the imine NH = CH2 + HO2. The NH2•CHCHO radical experiences captodative stabilization and is found to form a weakly bound peroxyl radical upon reaction with O2. Instead, the major oxidation product of NH2•CHCHO and the aminyl radical •NHCH2CHO is the imine NH = CHCHO (+HO2). In the atmosphere, the dominant fate of imine compounds is thought to be hydrolysis, where NH = CH2 will form ammonia and formaldehyde, and NH = CHCHO will produce ammonia and glyoxal. Efficient conversion of the dominant first-generation oxidation products of MEA to ammonia is consistent with field observations and supports the important role of imine intermediates in MEA oxidation.
Citation: Atmosphere
PubDate: 2024-08-21
DOI: 10.3390/atmos15081011
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 1012: Physical and Statistical Links between
Errors at the Surface, in the Boundary Layer, and in the Free Atmosphere
in Medium-Range Numerical Weather Predictions
Authors: Stéphane Bélair, Nasim Alavi, Sylvie Leroyer, Marco L. Carrera, Maria Abrahamowicz, Bernard Bilodeau, Dragan Simjanovski, Dorothée Charpentier, Bakr Badawy
First page: 1012
Abstract: The adequate representation of interactions between the land surface and the atmosphere is of crucial importance in modern numerical weather prediction (NWP) systems. In this context, this study examines how errors in the planetary boundary layer (PBL) depend on the quality of near-surface prediction over land for medium-range NWP. Two series of 10-day forecasts from Environment and Climate Change Canada (ECCC)’s global deterministic prediction system were evaluated: one similar to what is currently used in ECCC’s operational systems and the other with improved land surface modeling and land data assimilation. An objective evaluation was performed for the 2019 summer season in North America, with a special emphasis on three specific areas: northern Canada, the central US, and the southeastern US. The results indicate that the impact of the new land surface package is more difficult to interpret in the PBL than it is at the screen level. The error differences between the two experiments are quite distinct for the three regions examined. As expected, random errors (standard deviations) for air temperature and specific humidity in the PBL are directly linked with their own random errors at the screen level, with correlation coefficients decreasing from a value of one at the surface to values of about 0.2–0.3 a few kilometers above the surface. Less expected, however, is the fact that random errors in the lower atmosphere also strongly depend on changes in air temperature biases at the surface. Warmer near-surface conditions lead to increased random errors for air temperature in the lower atmosphere, in association with the development of the deeper PBL, with greater spatial variability. This finding is of particular interest when evaluating new configurations of NWP systems for implementation in national meteorological and environmental prediction centers.
Citation: Atmosphere
PubDate: 2024-08-21
DOI: 10.3390/atmos15081012
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 1013: Ensemble Predictions of Rainfall-Induced
Landslide Risk under Climate Change in China Integrating Antecedent
Soil-Wetness Factors
Authors: Han Zong, Qiang Dai, Jingxuan Zhu
First page: 1013
Abstract: Global warming has increased the occurrence of extreme weather events, causing significant economic losses and casualties from rainfall-induced landslides. China, being highly prone to landslides, requires comprehensive predictions of future rainfall-induced landslide risks. By developing a landslide-prediction model integrated with the CMIP6 GCMs ensemble, we predict the spatiotemporal distribution of future rainfall-induced landslides in China, incorporating antecedent soil-wetness factors. In this study, antecedent soil wetness is represented by the antecedent effective rainfall index (ARI), which accounts for cumulative rainfall, evaporation, and runoff losses. Firstly, we calculated landslide susceptibility using seven geographic factors, such as slope and geology. Then, we constructed landslide threshold models with two antecedent soil-wetness indicators. Compared to the traditional recent cumulative rainfall thresholds, the landslide threshold model based on ARI demonstrated higher hit rates and lower false alarm rates. Ensemble predictions indicate that in the early 21st century, the risk of landslides decreases in the Qinghai–Tibet Plateau, Southwest, and Southeast regions but increases in other regions. Mid-century projections show a 10% to 40% increase in landslide risk across most regions. By the end of the century, the risk is expected to rise by more than 15% nationwide, displaying a spatial distribution pattern that intensifies from east to west.
Citation: Atmosphere
PubDate: 2024-08-21
DOI: 10.3390/atmos15081013
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 1014: A Novel Hybrid Method for Multi-Step
Short-Term 70 m Wind Speed Prediction Based on Modal Reconstruction and
STL-VMD-BiLSTM
Authors: Xuanfang Da, Dong Ye, Yanbo Shen, Peng Cheng, Jinfeng Yao, Dan Wang
First page: 1014
Abstract: In the context of achieving the goals of carbon peaking and carbon neutrality, the development of clean resources has become an essential strategic support for the low-carbon energy transition. This paper presents a method for the modal decomposition and reconstruction of time series to enhance the prediction accuracy and performance regarding the 70 m wind speed. The experimental results indicate that the STL-VMD-BiLSTM hybrid algorithm proposed in this paper outperforms the STL-BiLSTM and VMD-BiLSTM models in forecasting accuracy, particularly in extracting nonlinearity characteristics and effectively capturing wind speed extremes. Compared with other machine learning algorithms, including the STL-VMD-LGBM, STL-VMD-SVR and STL-VMD-RF models, the STL-VMD-BiLSTM model demonstrates superior performance. The average evaluation criteria, including the RMSE, MAE and R2, for the proposed model, from t + 15 to t + 120 show improvements to 0.582–0.753 m/s, 0.437–0.573 m/s and 0.915–0.951, respectively.
Citation: Atmosphere
PubDate: 2024-08-21
DOI: 10.3390/atmos15081014
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 1015: Integrated Analysis of Multi-Parameter
Precursors to the Fukushima Offshore Earthquake (Mj = 7.3) on 13 February
2021 and Lithosphere–Atmosphere–Ionosphere Coupling Channels
Authors: Masashi Hayakawa, Yasuhide Hobara
First page: 1015
Abstract: The preparation phase of earthquakes (EQs) has been investigated by making full use of multi-parameter and multi-layer observations of EQ precursors, in order to better understand the lithosphere–atmosphere–ionosphere coupling (LAIC) process. For this purpose, we chose a specific target EQ, the huge EQ of Fukushima-ken-oki EQ on 13 February 2021 (magnitude Mj = 7.3). We initially reported on EQ precursors in different physical parameters not only of the lithosphere, but also of the atmosphere and ionosphere (Hayakawa et al. followed by Akhoondzadeh et al. and Draz et al., both based on satellite observations). Our first two papers dealt with seven electromagnetic precursors in the three layers (with emphasis on our own ground-based observations in the atmosphere and lower ionosphere), while the second paper dealt with Swarm satellite observations of magnetic field, electron density, and GPS TEC in the ionosphere, and the third paper dealt only with climatological parameters on and above the Earth’s surface (together with GPS TEC). We have extensively reviewed all of these results, and have coordinated the temporal evolutions of various physical parameters relevant to the LAIC system; we have sought to understand which hypothesis is more plausible in explaining the LAIC process. Then, we came to a conclusion that two possible LAIC channels seem to exist simultaneously for this EQ: a fast channel (nearly simultaneous responses on the ground and ionosphere), and a slow channel (or diffusion-type), with a time delay of a few to several days, in which the agent effects in the lithosphere and lowest atmosphere seem to propagate up to the ionosphere with a definite time delay. Finally, we have suggested some research directions for the future elucidation of LAIC channels, and also made some comments on an early EQ warning system.
Citation: Atmosphere
PubDate: 2024-08-21
DOI: 10.3390/atmos15081015
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 1016: Energy Dependence of Solar Energetic
Protons and Their Origin in Solar Cycles 23 and 24
Authors: Rositsa Miteva, Susan W. Samwel, Momchil Dechev
First page: 1016
Abstract: The study presents the compilation of a comprehensive catalog of solar energetic protons (SEPs) in solar cycles (SCs) 23 and 24 (1996–2019) in 10 energy channels from about 20 to 100 MeV based on data from the Energetic and Relativistic Nuclei and Electron (ERNE) instrument aboard Solar and Heliospheric Observatory (SOHO). For comparison, we added previously reported SEP fluxes by a number of different sources. We identified the SEP-solar origin in terms of solar flares and coronal mass ejections and calculated the statistical correlations (Pearson and partial) as a function of the SEP energy.
Citation: Atmosphere
PubDate: 2024-08-21
DOI: 10.3390/atmos15081016
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 1017: An Analysis of Extreme Rainfall Events in
Cambodia
Authors: Sytharith Pen, Saeed Rad, Liheang Ban, Sokhorng Brang, Panha Nuth, Lin Liao
First page: 1017
Abstract: Extreme rainfall, also known as heavy rainfall or intense precipitation, is a weather event characterized by a significant amount of rainfall within a short period. This study analyzes the trends in extreme precipitation indices at 17 stations in four main regions in Cambodia—the Tonle Sap, coastal, Mekong Delta, and Upper Mekong regions—between 1991 and 2021. Analyzing the data with RClimDex v1.9 reveals diverse spatial and temporal variations. The statistical analysis of the extreme rainfall indices in Cambodia from 1991 to 2021 reveals significant trends. In the Tonle Sap region, consecutive dry days (CDDs) increased at most stations, except Battabang, Kampong Thmar, and Pursat, while consecutive wet days (CWDs) increased at most stations. These trends align with rising temperatures and reduced forest cover. In the coastal region, particularly at the Krong Khemarak Phummin station, most rainfall indices increased, with a slope value of 89.94 mm/year. The extreme rainfall indices max. 1-day precipitation (RX1day) and max. 5-day precipitation (RX5day) also increased, suggesting higher precipitation on days exceeding the 95th (R95p) and 99th percentiles (R99p). The Kampot station showed a significant increase in CDDs, indicating a heightened drought risk. In the Mekong Delta, the Prey Veng station recorded a decrease in the CDDs slope value by −4.892 days/year, indicating potential drought risks. The Stung Treng station, which is the only station in Upper Mekong, showed a decreasing trend in CDDs with a slope value of −1.183 days/year, indicating a risk of extreme events. These findings underscore the complex interplay between climate change, land use, and rainfall patterns in Cambodia.
Citation: Atmosphere
PubDate: 2024-08-22
DOI: 10.3390/atmos15081017
Issue No: Vol. 15, No. 8 (2024)
- Atmosphere, Vol. 15, Pages 1018: Interpolation of Temperature in a
Mountainous Region Using Heterogeneous Observation Networks
Authors: Soorok Ryu, Joon Jin Song, GyuWon Lee
First page: 1018
Abstract: Accurately generating high-resolution surface grid datasets often involves merging multiple weather observation networks and addressing the challenge of network heterogeneity. This study aims to tackle the problem of accurately interpolating temperature data in regions with a complex topography. To achieve this, we introduce a deterministic interpolation method that incorporates elevation to enhance the accuracy of temperature datasets. This method is particularly valuable for areas with intricate terrains. Our robust methodology integrates a network harmonization method with radial basis function (RBF) interpolation for complex topographical regions. The method was tested on 10 min average temperature data from Jeju Island, South Korea, over 2 years that had a spatial resolution of 100 m. The results show a significant reduction of 5.5% in error rates, from an average of 0.73 °C to 0.69 °C, by incorporating all adjusted data. Integrating a parameterized nonlinear temperature profile further enhances accuracy, yielding an average reduction of 4.4% in error compared to the linear model. The spatial interpolation method, based on regression-based radial basis functions, demonstrates a 6.7% improvement over regression-based kriging for the same temperature profile. This research offers a valuable approach for precise temperature interpolation, especially in regions with a complex topography.
Citation: Atmosphere
PubDate: 2024-08-22
DOI: 10.3390/atmos15081018
Issue No: Vol. 15, No. 8 (2024)
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