|
|
- Atmosphere, Vol. 14, Pages 1425: Experimental Investigation on the
Influence of Swirl Ratio on Tornado-like Flow Fields by Varying Updraft
Radius and Inflow Angle
Authors: Pengfei Lv, Yumeng Zhang, Yanlei Wang, Bo Wang
First page: 1425
Abstract: The swirl ratio is the most critical parameter for determining the intensity and structure of tornado-like vortex, defined as the ratio of angular momentum to radial momentum. The angle of entry flow and the updraft radius are two key parameters affecting the swirl ratio. Many laboratory simulators have studied the effect of swirl ratio by changing the angle of entry flow, but there is a lack of research on the updraft radius. Therefore, for a deep sight of the impact of the updraft radius on the swirl ratio and tornado-like vortex, a laboratory tornado simulator capable of adjusting the updraft radius was designed, built, and tested. And, the effects of various swirl ratios caused by the updraft radius and the angle of entry flow on the tornado-like vortices were investigated, in terms of the dual-celled vortex transformation and vortex wandering. It was found that the effects of the updraft radius and the angle of turning vanes on the tornado-like vortices are quite different, and the formation of the dual-celled vortex is more sensitive to the updraft radius, because a larger angular momentum and axial pressure gradient can be provided. In addition, increasing the updraft radius has a greater inhibitory effect on the vortex wandering phenomenon compared to the angle of the turning vanes due to the flow fluctuations induced by turbulence.
Citation: Atmosphere
PubDate: 2023-09-11
DOI: 10.3390/atmos14091425
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1426: Effect of the Method Detection Limit on
the Health Risk Assessment of Ambient Hazardous Air Pollutants in an Urban
Industrial Complex Area
Authors: Jiun-Horng Tsai, Tzu-Lin Hung, Vivien How, Hung-Lung Chiang
First page: 1426
Abstract: Hazardous air pollutants (HAPs) significantly impacted environmental air quality and were widely studied to determine human health risks. Kaohsiung is Taiwan’s second-largest city, known for its heavily industrialized and densely populated development. The Linhai industrial park, located in this region, contains roughly 500 industrial facilities that contributed to the emission of HAPs. The purpose of this study was to identify the volatile organic compound (VOCs) and particulate matter (PM)-bounded heavy metals and to examine the effects of the method detection limit (MDL) for analyzed species and the sampling program on health risk assessments. This study identified formaldehyde, 1,2-dichloroethane, acetaldehyde, benzene, and vinyl chloride. As, ethylbenzene, Ni, Cr(VI), Cd, Pb, and 1,3-butadiene were defined as high-risk species and VOCs accounted for more than 95% of respiratory-related health risks, this study proposes that the MDL for analysis methods and the sampling frequency for different species (and the species of interest) would eventually affect the results of health risk assessments. In other words, the current control strategies for reducing health risks may be ineffective. This research output can be used to comprehend the effects of MDL on the health risk assessments of HAPs better while also providing a reliable method to determine the major sources of air pollutants in urban industrial areas.
Citation: Atmosphere
PubDate: 2023-09-11
DOI: 10.3390/atmos14091426
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1427: Exploration of Vegetation Change Trend in
the Greater Khingan Mountains Area of China Based on EEMD Method
Authors: Wenrui Fan, Hongmin Zhou, Changjing Wang, Guodong Zhang, Wu Ma, Qian Wang
First page: 1427
Abstract: Vegetation, especially forest ecosystems, plays an important role in the global energy flow and material cycle. The vegetation index (VI) is an important index reflecting the dynamic change in vegetation and directly reflects the response of ecosystem to global climate change. The Greater Khingan Mountains Forest region is located in the northeast of China. It is the largest primeval forest region in China, which is well preserved and less affected by human activities. It is of great significance to study the driving mechanism of forest vegetation change for future ecological prediction and management. In this study, GIMMS NDVI data were used to explore the characteristics of nonlinear temporal and spatial variation of NDVI in the Greater Khingan Mountains and its relationship with climatic factors. Firstly, the EEMD method was used to analyze the characteristics of vegetation change in the study area from 1982 to 2015. Secondly, the relationship between vegetation change and climate was discussed by using precipitation and temperature data. The results showed that the following: (1) from 1982 to 2015, the interannual change in vegetation in the Greater Khingan Mountains presented a trend of slow fluctuation and gradual decrease (SLOPE = −0.1645/10,000, p < 0.01). (2) The spatial distribution of vegetation change had obvious geographical differences, and in the central region, the overall distribution characteristics had an obvious browning trend, and in the northwest and southeast, the distribution characteristics had a green trend. (3) The correlation analysis results of vegetation change and climate factors showed that NDVI change was significantly positively correlated with temperature and precipitation; additionally, NDVI change was more correlated with temperature with a range of 0.8–1 than precipitation. (4) The results of vegetation attribution analysis in four typical areas of the study area showed that the following: the coniferous forest area has good cold tolerance and drought tolerance, the correlation between vegetation change and climate factors (temperature, precipitation) was not the strongest, which was 0.537 and 0.828, respectively. The ecological transition area and the broad-leaved forest area, which was located at the edge of the study area, have relatively fragile ecosystems, showed a strong correlation with precipitation, and the correlation coefficients reached 0.670 and 0.632, respectively. The surface water resources provide favorable conditions for the growth of vegetation, it showed a weak correlation with precipitation, and the correlation coefficient was 0.5349.
Citation: Atmosphere
PubDate: 2023-09-12
DOI: 10.3390/atmos14091427
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1428: Experimental Campaign of Massive CO2
Atmospheric Releases in an Urban Area
Authors: Lauris Joubert, Guillaume Leroy, Théo Claude, Omar Riahi
First page: 1428
Abstract: Over recent decades, several campaigns have been carried out to collect data regarding the release and atmospheric dispersion of dense chemical products in an open field. All these experimental data are valuable information to challenge the predictions of numerical tools (Gaussian, integral-type, and CFD) and, if needed, to improve the code itself and the way we are using it. On the other hand, little attention has been paid to atmospheric dispersion releases with massive flow rates in a complex urban environment. To fill this gap, Ineris carried out an experimental campaign intended to study the atmospheric dispersion of massive CO2 releases on the CENZUB site (an action training center in an urban area located in Sissonne, France). Three CO2 releases were performed with mass flow rates of about 7 kg/s in three different configurations: one axial street release and two impacting releases (against a small and high-rise building). Several technologies of CO2 sensors were used to ensure better measurement accuracy. The main experimental campaign features and preliminary data analysis are presented. The results demonstrated the influence of the built environment on dispersion patterns.
Citation: Atmosphere
PubDate: 2023-09-12
DOI: 10.3390/atmos14091428
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1429: Evaluation and Projection of Climate
Change in the Second Songhua River Basin Using CMIP6 Model Simulations
Authors: Heng Xiao, Yue Zhuo, Hong Sun, Kaiwen Pang, Zhijia An
First page: 1429
Abstract: The aim of this study is to evaluate the performance of the Global Climate Model (GCM) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) in historical simulations of temperature and precipitation. The goal is to select the best performing GCMs for future projection of temperature and precipitation in the Second Songhua River Basin under multiple shared socioeconomic pathways (SSPs). Interannual variability skill (IVS) and Taylor diagrams are used to evaluate the spatiotemporal performance of GCMs against temperature and precipitation data published by the China Meteorological Science Commons during 1956–2016. In addition, five relatively independent models are selected to simulate the temperature and precipitation for 2021–2050 using Hierarchical Clustering. The selected models are CMCC-ESM2, EC-Earth3-Veg-LR, IPSL-CM6A-LR, MIROC-ES2L, and MPI-ESM1-2-HR. The projected results find that SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios show an increasing trend of future annual mean temperature and precipitation. However, for annual precipitation, there is a mixed state of increase and decrease among different models on the seasonal scale. In general, future temperature and precipitation changes still show a trend of growth and uneven distribution in the Second Songhua River Basin, which may be further accelerated by human activities.
Citation: Atmosphere
PubDate: 2023-09-12
DOI: 10.3390/atmos14091429
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1430: Trace Elements Concentrations in Urban
Air in Helsinki, Finland during a 44-Year Period
Authors: Eleftheria Ioannidou, Stefanos Papagiannis, Manousos Ioannis Manousakas, Chrysoula Betsou, Konstantinos Eleftheriadis, Jussi Paatero, Lambrini Papadopoulou, Alexandra Ioannidou
First page: 1430
Abstract: The atmospheric concentrations of seventeen elements were measured in air filters at the Finnish Meteorological Institute station in Helsinki, Finland, during a period of 44 years (1962–2005). The mean annual concentrations were calculated and are presented from the lowest values to the highest ones Cr < Ni < Ti < Br < V < Mn < Cu < Zn < Cl < Al < Fe < K < Ca < Na < Pb < Si < S. Most of the elements (Fe, Si, Ti, K, Ca, Zn, Br, Pb, V, Ni, S, Cr, Na, Al, and Cl) present higher values during spring and winter season, while in summer the elements (Ti, Ca, S, and Na) are found in higher concentrationsdue to the weather conditions across seasons and the sources and emissions of air pollutants. There is a strong correlation between the elements (V-Ni, Si-Pb, Fe-Ca, V-Cr, Si-K, K-Ca, Fe-Ti, K-Na, Si-Ca, and V-S), indicating their common source. The identification of the sources of trace elements was performed based on positive matrix factorization analysis, using SoFi software. Four Suspended Particulate Matter (PM) sources were identified: road dust (due to usage of leaded fuel), heavy oil combustion/secondary sulfates, traffic emissions, and natural dust (soil). For the total of 44 years studied, significant decreases in concentrations were observed for all elements, most of which were over 50%: Na (−74%), Al (−86%), Si (−88%), S (−82%), K (−82%), Ca (−89%), Ti (−80%), V (−89%), Cr (−82%), Mn (−77%), Fe (−77%), Ni (−61%), Zn (−72%), and Pb (−95%). In general, a significant decline has been observed in the majority of the elemental concentrations since the end of the 1970s, underlying the effectiveness of different environmental policies that have been applied during the last few decades.
Citation: Atmosphere
PubDate: 2023-09-13
DOI: 10.3390/atmos14091430
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1431: Distribution Characteristics of Meteor
Angle of Arrival in Mohe and Wuhan, China
Authors: Xiaoyong Du, Wenjie Yin, Zhitao Du, Yufeng Zhou, Jian Feng, Bin Xu, Tong Xu, Zhongxin Deng, Zhengyu Zhao, Yuqiang Zhang, Chen Zhou, Jiawei Zhu, Yi Liu
First page: 1431
Abstract: Meteor radar is one of the key tools for studying the atmospheric dynamics in the mesosphere and lower thermosphere. The physical parameters obtained by meteor radar inversion can provide important statistical information for research. The daily and annual variations in meteor azimuth distribution detected by meteor radars contain information about meteor source regions and patterns related to the rotation and revolution of the Earth. Using the meteor parameters from two meteor radars located in Mohe (53.5° N, 122.3° E) and Wuhan (30.6° N, 114.4° E), this study calculates the variation patterns in the meteor azimuth distribution over the two sites over 1 year. Additionally, this study introduces the variable, Max_Azi, to describe the position of the peak of azimuth distribution. The peak value of azimuth distribution is calculated by Gaussian fitting to quantify the variation patterns in azimuth distribution. This study provides complementary information on the azimuth distribution in high and middle latitudes. The results indicated that the azimuth distribution variation for the Mohe meteor radar is consistent with the Earth’s revolution model.
Citation: Atmosphere
PubDate: 2023-09-13
DOI: 10.3390/atmos14091431
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1432: Modeling of Nonlinear SOEC Parameter
System Based on Data-Driven Method
Authors: Dehao Hou, Wenjun Ma, Lingyan Hu, Yushui Huang, Yunjun Yu, Xiaofeng Wan, Xiaolong Wu, Xi Li
First page: 1432
Abstract: Based on the basic nonlinear parameter system of the solid oxide electrolysis cell, the data-driven method was used for system identification. The basic model of the solid oxide electrolysis cell was accomplished in Simulink and experiments were performed under a diversified input/output operating environment. The experimental results of the solid oxide electrolysis cell basic parameter system generated 15 datasets. The system identification process involved the utilization of these datasets with the application of nonlinear autoregressive-exogenous models. Initially, data identification came from the Matlab mechanism model. Then, the nonlinear autoregressive-exogenous structures were estimated and selected exploratively through an individual operating condition. In terms of fitness, we conclude that the solid oxide electrolysis cell parameter system cannot be satisfied by a solitary autoregressive-exogenous model for all datasets. Nevertheless, the nonlinear autoregressive-exogenous model utilized S-type nonlinearities to fit a total of 2 validation datasets and 15 estimated datasets. The obtained results were compared with the basic parameter system of a solid oxide electrolysis cell, and the nonlinear autoregressive-exogenous projected output demonstrated an accuracy of over 93% across diverse operational circumstances—regardless of whether there was noise interference. This result has positive significance for the future use of the solid oxide electrolysis cell to achieve the dual carbon goal in China.
Citation: Atmosphere
PubDate: 2023-09-13
DOI: 10.3390/atmos14091432
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1433: Spatial Configuration of Urban Greenspace
Affects Summer Air Temperature: Diurnal Variations and Scale Effects
Authors: Qin Tian, Qingdong Qiu, Zhiyu Wang, Zhengwu Cai, Li Hu, Huanyao Liu, Ye Feng, Xiaoma Li
First page: 1433
Abstract: Optimizing the spatial pattern (spatial compositive and spatial configuration) of urban greenspace can effectively alleviate the urban heat island effect. While the relationship between air temperature (AT) and spatial composition of urban greenspace has been widely studied, this study aimed to investigate the relationship between AT and spatial configuration of urban greenspace and its diurnal variations and scale effects. Based on hourly AT data from 36 meteorological stations in Changsha, China, and land cover data interpreted from the Gaofen 2 remote sensing images, this study first quantified spatial composition (i.e., percent of greenspace) and spatial configuration (i.e., average patch area, patch density, edge density, landscape shape index, and mean shape index) of urban greenspace at different scales (30 m to 2000 m buffer surrounding the air station), then Pearson correlations (between AT and each landscape metric) and partial Pearson correlations (between AT and spatial configuration metrics with percent of greenspace controlled) were analyzed. Multiple linear regression was applied to model the variation of AT using the landscape metrics as independent variables. Finally, the variance partitioning analysis was performed to investigate the relative importance of spatial composition and spatial configuration of urban greenspace to explain the variation of AT. The results showed that (1) the temperature range reached 1.73 °C during the day and 2.94 °C at night. Urban greenspace was fragmented especially at small scales. (2) The Pearson correlation between AT and percent of greenspace fluctuated with the increase of scale and was generally higher during the day than during the night. (3) The spatial pattern of urban greenspace explained as high as 55% of the AT variation, showing diurnal variations and scale effects (i.e., a maximum of 0.54 during the day at 50 m buffer and a maximum of 0.55 during the night at 400 m buffer). (4) A higher percent of greenspace, more aggregated greenspace patches, and simpler greenspace shapes can generate a stronger cooling effect. (5) The relative importance of spatial composition and spatial configuration of greenspace varied among spatial scales and showed diurnal variations. These results emphasize the scale effect as well as diurnal variation of the relationship between urban greenspace spatial pattern and AT. These findings provide theoretical guidance for urban greenspace planning and management to improve the urban thermal environment in rapidly developing subtropical cities such as Changsha, China.
Citation: Atmosphere
PubDate: 2023-09-14
DOI: 10.3390/atmos14091433
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1434: Study on Dynamic Characteristics of
Magnetic Coagulation of Fe-Based Fine Particles in Iron and Steel Industry
Authors: Dengke Xu, Zuxiang Hu, Li’an Zhang, Wenqing Zhang
First page: 1434
Abstract: Fine dust, represented by Fe-based fine particles and emitted from the production process of the iron and steel industry, is the primary factor causing many diseases represented by industrial pneumoconiosis, and ultra-low dust emission has always been a thorny problem to be solved urgently. To explore the magnetic coagulation effect of Fe-based fine particles in the magnetic field when removing them from industrial flue gas by the magnetic field effect in the iron and steel industry, using FLUENT software, magnetic dipole force was added between particles through user defined function (UDF) based on the computational fluid dynamics-discrete phase model (CFD-DPM) method so that the collision process of particles was then equivalent to their mutual trapping process. Next, the effects of particle size, particle volume fraction, external magnetic field strength, and particle magnetic susceptibility on the magnetic coagulation process were comprehensively studied. Meanwhile, the proton balance equation (PBE) was solved using the partition method on the basis of the computational fluid dynamics-population balance model (CFD-PBM) to compare the coagulation removal effect under random and aligned orientations of magnetic dipoles, respectively. The results showed that the magnetic coagulation strength under the random orientation of magnetic dipoles was greater than that under the aligned orientation. When the particle size of Fe-based fine particles increased from 0.5 μm to 1.5 μm, the magnetic coagulation coefficient decreased from 0.5414 to 0.2882, and the difference in the removal efficiency under the two different orientations of magnetic dipoles became smaller. When the particle volume fraction increased from 0.01 to 0.03, the magnetic coagulation coefficient increased from 0.2353 to 0.5061, and the difference in the removal efficiency under two orientations was enlarged. When the applied external magnetic field strength increased from 0.5 T to 1.0 T, the magnetic coagulation coefficient increased from 0.3940 to 0.5288, and the magnetic susceptibility increased from 0.0250 to 0.0500, the coagulation coefficient increased from 0.3940 to 0.5288, and the difference under two orientations basically stayed unchanged.
Citation: Atmosphere
PubDate: 2023-09-14
DOI: 10.3390/atmos14091434
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1435: Regional Climate Simulation Ensembles
within CORDEX-EA Framework over the Loess Plateau: Evaluation and Future
Projections
Authors: Siliang Liu
First page: 1435
Abstract: As a semi-arid to semi-humid transitional zone, the Loess Plateau is sensitive to climate change due to its fragile ecological environment and geographic features. This study assesses the performance of six historical experiments from the Coordinated Regional Climate Downscaling Experiment (CORDEX) in this region during 1980–2005. In addition, projected future changes in surface air temperature and precipitation are investigated under the representative concentration pathways (RCP) 2.6 and 8.5 during three periods in the 21st century: the early future (2011–2040), middle future (2041–2070), and late future (2071–2099). Results show that experiments reasonably reproduce the spatial pattern of 2m temperature and precipitation for all seasons, yet with a slight warm bias and prominent wet bias. In the future, the area-averaged magnitude of change will be 1.1 °C, 1.4 °C, and 1.4 °C under RCP2.6 and 1.3 °C, 2.7 °C, and 4.5 °C under RCP8.5 for the early, middle, and late periods, respectively. The warming effect is greater in elevated areas. Precipitation change in future periods is more complex, with both increasing and decreasing trends, depending on the season, location, and scenario. The results are expected to provide regional climate information for decision makers and benefit applications such as agriculture, ecological environment protection, and water resource management.
Citation: Atmosphere
PubDate: 2023-09-14
DOI: 10.3390/atmos14091435
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1436: Frequency Dependence of the Correlation
between Ozone and Temperature Oscillations in the Middle Atmosphere
Authors: Klemens Hocke, Eric Sauvageat
First page: 1436
Abstract: This study investigates the frequency dependence of the correlation or anticorrelation of ozone and temperature in the middle atmosphere. The anticorrelation of ozone and temperature plays a role for a possible super recovery of upper stratospheric ozone in the presence of man-made cooling of the middle atmosphere due to increasing carbon dioxide emissions. The correlation between lower stratospheric ozone and temperature indicates the dependence of lower stratospheric temperature trends on the ozone evolution in addition to greenhouse gas emissions. Ozone and temperature measurements of the microwave limb sounder (MLS) on the satellite Aura from 2004 to 2021 are utilized for Bern (46.95° N, 7.44° E) at middle latitudes and for the equator region. The time series are bandpass filtered for periods from 2 days to 5 years. The correlation coefficient depends on the period of the oscillation in temperature and ozone. The strongest correlation and anticorrelation are found for the annual oscillation. The anticorrelation between ozone and temperature in the upper stratosphere is about −0.7 at a period of two days and −0.99 at a period of one year. Thus, the temperature dependence of the ozone reaction rates also leads to an anticorrelation of ozone and temperature at short periods so that ozone can be considered as a tracer of planetary waves. At the equator, a dominant semiannual oscillation and an 11 year solar cycle are found for nighttime ozone in the upper mesosphere. The semiannual oscillation (SAO) in ozone and temperature shows a strong correlation indicating a dynamical control of the ozone SAO in the upper mesosphere. The SAO in the equatorial nighttime values of ozone and temperature is possibly due to a semiannual modulation of vertical advection by the diurnal tide.
Citation: Atmosphere
PubDate: 2023-09-14
DOI: 10.3390/atmos14091436
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1437: Comparison of Portable and Large Mobile
Air Cleaners for Use in Classrooms and the Effect of Increasing Filter
Loading on Particle Number Concentration Reduction Efficiency
Authors: Finn Felix Duill, Florian Schulz, Aman Jain, Berend van Wachem, Frank Beyrau
First page: 1437
Abstract: This study focuses on the effect of portable and large filter-based air cleaners (HEPA filters), which became popular indoors during the COVID-19 pandemic, and their suitability for classrooms (here 186 m3). The decay rates of the particle number concentration (PNC) were measured simultaneously at up to four positions in the room. It was found that the different air outlet configurations of the units have an effect on the actual PNC removal in the room when operated at the same volume flow rates. This effect of the airflow efficiency of the air cleaners (AP) in a classroom is quantified with an introduced Air Cleaning Efficiency Factor in this study to identify beneficial airflows. In this context, the effect of filter loading in long-term operation on the cleaning effect is also investigated. The emitted sound pressure levels of the APs are given special attention as this is a critical factor for use in schools, as well as power consumption. A total of six different devices were tested—two portable APs and four large APs. In order to achieve the necessary volume flow rates, three or four of the portable units were used simultaneously in one room, while only one of the large units was used per room. When used at the same air circulation rates in the room, the portable APs exhibit higher sound pressure levels compared to the large APs. At air circulation rates of 4–5 h−1, the portable APs exceeded a value of 45 dB(A). Two of the four large units reach sound pressure levels below 40 dB(A) at air circulation rates of 4–5 h−1, whereby both large units, which are positioned on the rear wall, realize a homogeneous dilution of the room air. This is achieved by an air outlet directed horizontally at a height above 2 m or diagonally towards the ceiling, which points into the room and partly to the sides. On the other hand, an air outlet directed exclusively to the sides or horizontally into the room at floor level to all sides achieves lower particle decay rates. To investigate the influence of the filter loading, three large APs were operated in a school for a period of one year (190 days with 8 h each). For the three APs, long-term operation leads to different changes in PNC reduction efficiency, ranging from −3% to −34%. It is found that not only the size of the prefilter and main filter has a significant influence, but also whether there is a prefilter bypass that negatively affects the loading level of the main filter. At the same time, it was shown that one type of AP, measuring the pressure drop across the filters and readjusting the fan, kept the circulation rate almost constant (up to −3%) over a year.
Citation: Atmosphere
PubDate: 2023-09-14
DOI: 10.3390/atmos14091437
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1438: Studying the Regional Transmission of Air
Pollution Based on Spatiotemporal Multivariable Data
Authors: Xi Lu, Yong Xue, Botao He, Xingxing Jiang, Shuhui Wu, Xiangkai Wang
First page: 1438
Abstract: Imported air pollution has a significant impact on urban air quality. Relevant studies have shown that many urban air pollution events are not resourced by local emissions but are imported by air pollution from surrounding areas transported across regions. The prevention and control of air pollution is very necessary. However, the existing supervision of urban air quality mostly relies on ground monitoring stations, which are extremely limited in time and space, and cannot satisfy continuous time-space air pollution research. Therefore, aiming at the problem of urban air pollution control, this paper used MERRA-2 reanalysis data and ground monitoring data to establish a “Time-Longitude-Latitude” three-dimensional pollution curve, and then a genetic algorithm was used to optimize its fitting. This study finally reconstructed the imported air pollution transmission route. This paper takes an air pollution event that occurred in Xuzhou City, China, on 12 January 2020, as an example. Through the analysis of aerosol optical depth (AOD), particulate matter (PM), wind speed, and other factors, we found the source, transmission route, and impact time of this pollution. We have verified the correctness and accuracy of the reconstructed contamination transport paths. It is proved that the method is universal and it can quickly and accurately restore the air pollution transmission route and identify the urban imported air pollution transmission entrance. This method will also provide strong data support for the division of responsibilities of environmental protection departments in various regions for severe air pollution transmission events and provide effective governance ideas for the prevention and control of imported air pollution in recipient cities.
Citation: Atmosphere
PubDate: 2023-09-14
DOI: 10.3390/atmos14091438
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1439: A Study on Avalanche-Triggering Factors
and Activity Characteristics in Aerxiangou, West Tianshan Mountains, China
Authors: Jie Liu, Tianyi Zhang, Changtao Hu, Bin Wang, Zhiwei Yang, Xiliang Sun, Senmu Yao
First page: 1439
Abstract: Through analyzing the triggering factors and activity characteristics of avalanches in Aerxiangou in the Western Tianshan Mountains, the formation and disaster-causing process of avalanches were studied to provide theoretical support and a scientific basis for avalanche disaster prevention. In this paper, based on remote sensing interpretation and field investigation, a spatial distribution map of avalanches was established, and the induced and triggering factors in disaster-prone environments were analyzed using the certainty factor model. The degree of influence (E) of the disaster-causing factors on avalanche triggering was quantified, and the main control conditions conducive to avalanche occurrence in different periods were obtained. The RAMMS-avalanche model was used to analyze the activity characteristics at points where multiple avalanches occurred. Research results: (1) The E values of the average temperature, average snowfall, and surface roughness in February were significantly higher than those of other hazard-causing factors, reaching 1.83 and 1.71, respectively, indicating strong control. The E values of the surface cutting degree, average temperature, and average snow depth in March were all higher than 1.8, indicating that these control factors were more prominent than the other factors. In contrast, there were four hazard-causing factors with E values higher than 1.5 in April: the mean temperature, slope, surface roughness, and mean wind speed, with clear control. (2) Under the influence of the different hazard-causing factors, the types of avalanches from February–April mainly included new full-layer avalanches, surface avalanches, and full-layer wet avalanches. (3) In the RAMMS-avalanche simulation test, considering the deposition effect, compared to the previous avalanche movement path, the secondary avalanche flow accumulation area impact range changes were slight, while the movement area within the avalanche path changes was large, as were the different categories of avalanches and their different movement characteristic values. Overall, wet snow avalanches are more hazardous, and the impact force is larger. The new snow avalanches start in a short period, the sliding rate is fast, and the avalanche sliding surface (full-snow surface and face-snow) of the difference is mainly manifested in the differences in the value of the flow height.
Citation: Atmosphere
PubDate: 2023-09-15
DOI: 10.3390/atmos14091439
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1440: Elevated Risk of Compound Extreme
Precipitation Preceded by Extreme Heat Events in the Upper Midwestern
United States
Authors: Manas Khan, Rabin Bhattarai, Liang Chen
First page: 1440
Abstract: Compound extreme events can potentially cause deadlier socio-economic consequences. Although several studies focused on individual extreme climate events, the occurrence of compound extreme events is still not well studied in the upper Midwestern United States. In this study, compound extreme precipitation preceded by extreme hot day events was investigated. Results showed a strong linkage between extreme precipitation events and extreme hot days. A significant increasing trend was noticed mainly in Iowa (10.1%), northern parts of Illinois (5.04%), and Michigan (5.04%). Results also showed a higher intensity of extreme precipitation events preceded by an extremely hot day compared to the intensity of extreme precipitation events not preceded by an extremely hot day, mostly in the central and lower parts of Minnesota, western and upper parts of Iowa, lower and upper parts of Illinois, parts of Ohio, Michigan, and Wisconsin for 1950–2010. In other words, extreme heat contributed to more extreme precipitation events. Our findings would provide important insights related to flood management under future climate change scenarios in the region.
Citation: Atmosphere
PubDate: 2023-09-15
DOI: 10.3390/atmos14091440
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1441: Methods for Urban Air Pollution
Measurement and Forecasting: Challenges, Opportunities, and Solutions
Authors: Elena Mitreska Jovanovska, Victoria Batz, Petre Lameski, Eftim Zdravevski, Michael A. Herzog, Vladimir Trajkovik
First page: 1441
Abstract: In today’s urban environments, accurately measuring and forecasting air pollution is crucial for combating the effects of pollution. Machine learning (ML) is now a go-to method for making detailed predictions about air pollution levels in cities. In this study, we dive into how air pollution in urban settings is measured and predicted. Using the PRISMA methodology, we chose relevant studies from well-known databases such as PubMed, Springer, IEEE, MDPI, and Elsevier. We then looked closely at these papers to see how they use ML algorithms, models, and statistical approaches to measure and predict common urban air pollutants. After a detailed review, we narrowed our selection to 30 papers that fit our research goals best. We share our findings through a thorough comparison of these papers, shedding light on the most frequently predicted air pollutants, the ML models chosen for these predictions, and which ones work best for determining city air quality. We also take a look at Skopje, North Macedonia’s capital, as an example of a city still working on its air pollution measuring and prediction systems. In conclusion, there are solid methods out there for air pollution measurement and prediction. Technological hurdles are no longer a major obstacle, meaning decision-makers have ready-to-use solutions to help tackle the issue of air pollution.
Citation: Atmosphere
PubDate: 2023-09-15
DOI: 10.3390/atmos14091441
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1442: Validation and Selection of a
Representative Subset from the Ensemble of EURO-CORDEX EUR11 Regional
Climate Model Outputs for the Czech Republic
Authors: Jan Meitner, Petr Štěpánek, Petr Skalák, Martin Dubrovský, Ondřej Lhotka, Radka Penčevová, Pavel Zahradníček, Aleš Farda, Miroslav Trnka
First page: 1442
Abstract: To better understand the impact of climate change at a given location, it is crucial to consider a wide range of climate models that are representative of the area. In this study, we emphasize the importance of the careful validation and selection of climate models most suitable for a particular region. This step is critical to enhance the relevance of climate change impact studies and consequently design appropriate and robust adaptation measures, particularly in agriculture, forestry and water resources management. We propose validation and selection methods for regional climate models that can help identify a smaller group of well-performing models using the Central European area and Czech Republic as examples. In the validation process, 7 out of 19 regional climate models performed poorly. Of the 12 well-performing models, a subset of 7 models was selected to represent the uncertainty in the entire ensemble, which could be used in subsequent studies. The methodology is sufficiently general and may be applied to other climate model ensembles.
Citation: Atmosphere
PubDate: 2023-09-15
DOI: 10.3390/atmos14091442
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1443: Dynamic and Thermodynamic Drivers of
Severe Sub-Hourly Precipitation Events in Mainland Portugal
Authors: José Cruz, Margarida Belo-Pereira, André Fonseca, João A. Santos
First page: 1443
Abstract: Sub-hourly heavy precipitation events (SHHPs) associated with regional low-pressure (RegL) systems in Portugal are a natural hazard that may have significant socioeconomic implications, namely in agriculture. Therefore, in this paper, their dynamic and thermodynamic drivers are analysed. Three weather stations were used to isolate SHHPs from 2000 to 2022. Higher precipitation variability is found in southern Portugal, with a higher ratio of extreme events on fewer rainy days. This study shows that these SHHP events are associated with low-pressure systems located just to the west of the Iberian Peninsula. These systems exhibit a cold core, particularly strong at mid-levels, and a positive vorticity anomaly, which is stronger in the upper troposphere, extending downward to low levels. These conditions drive differential positive vorticity advection and, therefore, rising motion to the east of the low-pressure systems. Moreover, at low levels, these systems promote moisture advection over western Iberia, also generating instability conditions, which are assessed by instability indices (Convective available potential energy, the Total-Totals index, and the K-index). The combination of these conditions drives heavy precipitation events. Lastly, the total column cloud ice water revealed higher values for the heavier precipitation events, suggesting that it may be a useful predictor of such events.
Citation: Atmosphere
PubDate: 2023-09-16
DOI: 10.3390/atmos14091443
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1444: Air Quality Mapping in Bandung City
Authors: Resa Septiani Pontoh, Leivina Saliaputri, Audrey Nayla Nashwa, Nadhira Khairina, Bertho Tantular, Toni Toharudin, Farhat Gumelar
First page: 1444
Abstract: One of the most commonly encountered issues in large cities is air pollution. As a major city, Bandung also experiences the same problem. This issue arises due to the increasing levels of human activity. This contributes to elevated levels of pollutants in the atmosphere, which can impact human life and ecosystems. This research is intended to map the regions in Bandung based on their air quality. This study used ambient air quality measurement results from Bandung, which included PM10, PM2.5, dust, SO2, CO, and NO2. This ambient air quality measurement was conducted by the Department of Environment and Hygiene in Bandung. The research methodology utilized in this study was multidimensional scaling analysis. The outcomes of the examination carried out utilizing the multidimensional scaling technique reveal a clustering of regions in Bandung, West Java, based on their air quality. According to the research findings, the locations were grouped into four quadrants, each with different air quality characteristics. Some locations showed high similarity, while others did not exhibit similarity with other groups. These findings can be used for policy-making and improving air quality in Bandung. Conclusions were drawn from the formed groups, where each group had high similarity among its members, but differed from the members of other groups. Among all observed locations in Bandung City, there were areas that were most similar when viewed based on the distance between objects, namely Punclut St. and KPAD Sarijadi; Soekarno Hatta St. (in front of Astra Bizz) and Elang St.; and Buah Batu St. (in front of STSI/ISBI) and Bunderan Cibiru.
Citation: Atmosphere
PubDate: 2023-09-16
DOI: 10.3390/atmos14091444
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1445: Coastal Flooding Associated with
Hurricane Irma in Central Cuba (Ciego de Ávila Province)
Authors: Felipe Matos-Pupo, Matthew C. Peros, Roberto González-De Zayas, Alexey Valero-Jorge, Osvaldo E. Pérez-López, Flor Álvarez-Taboada, Rogert Sorí
First page: 1445
Abstract: Irma was a major hurricane that developed during the 2017 season. It was a category 5 on the Saffir–Simpson Hurricane wind scale. This hurricane caused severe damage in the Caribbean area and the Florida Keys. The social, economic, and environmental impacts, mainly related to coastal flooding, were also significant in Cuba. The maximum limits of coastal flooding caused by this hurricane were determined in this research. Field trips and the use of the GPS supported our work, which focused on both the northern and southern coasts of the Ciego de Ávila province. This work has been critical for improving coastal flooding scenarios related to a strong hurricane, as it has been the first experience according to hurricane data since 1851. Results showed that the Punta Alegre and Júcaro towns were the most affected coastal towns. The locals had never seen similar flooding in these places before. The differences between flood areas associated with Hurricane Irma and previous modeled hazard scenarios were evident (the flooded areas associated with Hurricane Irma were smaller than those modeled for categories 1, 3, and 5 hurricanes). The effects of this hurricane on the most vulnerable coastal settlements, including the impacts on the archeological site “Los Buchillones”, were also assessed.
Citation: Atmosphere
PubDate: 2023-09-16
DOI: 10.3390/atmos14091445
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1446: Long-Term Tropospheric Ozone Data
Analysis 1997–2019 at Giordan Lighthouse, Gozo, Malta
Authors: Brunislav Matasović, Martin Saliba, Rebecca Muscat, Marvic Grima, Raymond Ellul
First page: 1446
Abstract: Long-term data analysis of the hourly ozone volume fractions in the middle of the Mediterranean Seawas carried out covering a period of 22 years. It was noticed that the amount of ozone during this period very rarely exceeded the recommended upper limit value of 80 ppb and that the amount of tropospheric ozone in the area is rather low. Fourier data analysis shows the presence of only a seasonal cycle in ozone concentrations. Statistical analysis of the data is showing a slightly negative trend in ozone concentrations of −0.46 ± 0.08 ppb/year for average values and a slightly higher negative trend of −0.54 ± 0.11 ppb/year for the 95th percentile values. These results obtained through simple linear regression were confirmed using the more appropriate Mann–Kendall test. The possible quadratic trend was not observed for the whole series of data. Air mass trajectories were calculated for those days in the year with the highest pollution, indicating that during those days horizontal air transfer, in most cases, brings the air mass from the North and from Sicily in Southern Italy.
Citation: Atmosphere
PubDate: 2023-09-17
DOI: 10.3390/atmos14091446
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1447: Hydrological Drought Prediction Based on
Hybrid Extreme Learning Machine: Wadi Mina Basin Case Study, Algeria
Authors: Mohammed Achite, Okan Mert Katipoğlu, Muhammad Jehanzaib, Nehal Elshaboury, Veysi Kartal, Shoaib Ali
First page: 1447
Abstract: Drought is one of the most severe climatic calamities, affecting many aspects of the environment and human existence. Effective planning and decision making in disaster-prone areas require accurate and reliable drought predictions globally. The selection of an effective forecasting model is still challenging due to the lack of information on model performance, even though data-driven models have been widely employed to anticipate droughts. Therefore, this study investigated the application of simple extreme learning machine (ELM) and wavelet-based ELM (W-ELM) algorithms in drought forecasting. Standardized runoff index was used to model hydrological drought at different timescales (1-, 3-, 6-, 9-, and 12-month) at five Wadi Mina Basin (Algeria) hydrological stations. A partial autocorrelation function was adopted to select lagged input combinations for drought prediction. The results suggested that both algorithms predict hydrological drought well. Still, the performance of W-ELM remained superior at most of the hydrological stations with an average coefficient of determination = 0.74, root mean square error = 0.36, and mean absolute error = 0.43. It was also observed that the performance of the models in predicting drought at the 12-month timescale was higher than at the 1-month timescale. The proposed hybrid approach combined ELM’s fast-learning ability and discrete wavelet transform’s ability to decompose into different frequency bands, producing promising outputs in hydrological droughts. The findings indicated that the W-ELM model can be used for reliable drought predictions in Algeria.
Citation: Atmosphere
PubDate: 2023-09-17
DOI: 10.3390/atmos14091447
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1448: A Case Study of Drought during Summer
2022: A Large-Scale Analyzed Comparison of Dry and Moist Summers in the
Midwest USA
Authors: Sarah M. Weaver, Patrick E. Guinan, Inna G. Semenova, Noel Aloysius, Anthony R. Lupo, Sherry Hunt
First page: 1448
Abstract: The summer of 2022 was very dry across Missouri and the surrounding regions including much of the Great Lakes, Midwest, and southern plains of the USA. A comparison of this summer to the dry summer of 2012 and the relatively wet summers of 2018 and 2021 was carried out using the National Centers for Environmental Prediction/National Centers for Atmospheric Research reanalysis, the Climate Prediction Center teleconnection indexes, and the blocking archive at the University of Missouri. The summer of 2022 was like that of 2012 which was characterized by a strong 500 hPa height anomaly centered over the western US and plains as well as very little blocking in the East Pacific. The summers of 2018 and 2021 were characterized by more zonal flow over the USA and more blocking in the East Pacific, similarly to the results of an earlier study. The teleconnection indexes for the prior spring and summer were largely similar for the two drier years and opposite for the wetter years. The surface conditions for the drier years were more similar while these were opposite for the wetter years. The integrated enstrophy (IE) used in earlier studies identified a change in the large-scale flow regime in early June 2022, which coincided with a decrease in the precipitation over the study region. However, one key difference was that the spring of 2022 was characterized by blocking more consistent with a wetter summer. This would have made the predictability of the drought of summer 2022 less certain.
Citation: Atmosphere
PubDate: 2023-09-17
DOI: 10.3390/atmos14091448
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1449: Trends and Variability in Temperature and
Related Extreme Indices in Rwanda during the Past Four Decades
Authors: Bonfils Safari, Joseph Ndakize Sebaziga
First page: 1449
Abstract: Analysis of the trends and variability of climate variables and extreme climate events is important for climate change detection in space and time. In this study, the trends and variabilities of minimum, maximum, and mean temperatures, as well as five extreme temperature indices, are analyzed over Rwanda for the period of 1983 to 2022. The Modified Mann–Kendall test and the Theil–Sen estimator are used for the analysis of, respectively, the trend and the slope. The standard deviation is used for the analysis of the temporal variability. It is found, on average, over the country, a statistically significant (α = 0.05) positive trend of 0.17 °C/decade and 0.20 °C/decade in minimum temperature, respectively, for the long dry season and short rain season. Statistically significant (α = 0.05) positive trends are observed for spatially averaged cold days (0.84 days/decade), warm nights (0.62 days/decade), and warm days (1.28 days/decade). In general, maximum temperature represents higher variability compared to the minimum temperature. In all seasons except the long dry season, statistically significant (α = 0.05) high standard deviations (1.4–1.6 °C) are observed over the eastern and north-western highlands for the maximum temperature. Cold nights show more variability, with a standard deviation ranging between 5 and 7 days, than the cold days, warm nights, and warm days, having, respectively, standard deviations ranging between 2 and 3, 4 and 5 days, and 3 and 4, and, especially in the area covering the central, south-western, south-central, and northwestern parts of Rwanda. Temperature increase and its variability have an impact on agriculture, health, water resources, infrastructure, and energy. The results obtained from this study are important since they can serve as the baseline for future projections. These can help policy decision making take objective measures for mitigation and adaptation to climate change impacts.
Citation: Atmosphere
PubDate: 2023-09-17
DOI: 10.3390/atmos14091449
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1450: A New SLF/ELF Algorithm of Fields Excited
by a Radiator in a Soil Foundation in the Earth–Ionosphere Cavity
Authors: Yuanxin Wang, Jutao Yang, Shuji Hao, Jing Chen, Yonggan Liang, Yanshuai Zheng
First page: 1450
Abstract: Abnormal electromagnetic radiation associated with seismic activity has been reported across a wide range of frequencies, but its primary energy is concentrated in the super-low-frequency (SLF) and extremely low-frequency (ELF) bands. To estimate the effect of the seismic radiation source, a radiator in a soil foundation was modeled as a horizontal electric dipole (HED), and the propagation characteristics of the electromagnetic fields were studied in the Earth–ionosphere cavity. The expressions of the electromagnetic fields could be obtained according to the reciprocity theorem. Therefore, a new algorithm named the numerical integral algorithm was proposed, which is suitable for both the SLF and ELF bands. The new algorithm was compared with the asymptotic approximation algorithm when the receiving point was not close to the field source and the antipode. The two algorithms were found to be in excellent agreement, confirming the validity of the new algorithm for SLF and ELF bands.
Citation: Atmosphere
PubDate: 2023-09-18
DOI: 10.3390/atmos14091450
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1451: Vectorial EM Propagation Governed by the
3D Stochastic Maxwell Vector Wave Equation in Stratified Layers
Authors: Bryce M. Barclay, Eric J. Kostelich, Alex Mahalov
First page: 1451
Abstract: The modeling and processing of vectorial electromagnetic (EM) waves in inhomogeneous media are important problems in physics and engineering, and new methods need to be developed to incorporate novel vector sensor technology. Vectorial phenomena of EM waves in stratified atmospheric layers can be incorporated into governing equations by retaining the gradient of the refractive index when deriving the Maxwell Vector Wave Equation (MVWE) from Maxwell’s equations. The MVWE, as opposed to the scalar wave, Helmholtz, and paraxial equations, couples the EM field components in inhomogeneous media and thus captures important physics phenomena such as depolarization. Here, recent developments are reviewed on using sensor time series data to reconstruct electromagnetic waves that propagate through stratified media. In modern applications, often many sensors can be deployed simultaneously to observe electromagnetic waves. These networks of sensors can be used to improve the quality of the reconstructed EM wave fields and cross-validate the observed sensor time series. Lastly, the effects of noisy current densities on sensor time series are considered. Generally, as the sensor observes for longer periods of time, the variance of estimates of the wave field obtained from sensor time series data increases. As a result, longer sensor observation times do not always result in better estimates of the EM wave fields, and an optimal observation time can be obtained.
Citation: Atmosphere
PubDate: 2023-09-18
DOI: 10.3390/atmos14091451
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1452: Composition Characteristics of VOCs in
the Atmosphere of the Beibei Urban District of Chongqing: Insights from
Long-Term Monitoring
Authors: Shixu Luo, Qingju Hao, Zhongjun Xu, Guosheng Zhang, Zhenghao Liang, Yongxiang Gou, Xunli Wang, Fanghui Chen, Yangjian He, Changsheng Jiang
First page: 1452
Abstract: Reducing anthropogenic volatile organic compounds (VOCs) is the most effective way to mitigate O3 pollution, which has increased over the past decades in China. From 2012 to 2017, special stainless-steel cylinders were used to collect ambient air samples from the urban area of Beibei district, Chongqing. Three-step pre-concentration gas chromatography–mass spectrometry was used to detect the collected air samples. The composition, concentration, photochemical reactivity, and sources of VOCs in Beibei were analyzed. During the observation period, the annual average VOC concentration was 31.3 ppbv, which was at an intermediate range compared to other cities in China. Alkanes (36.8%) and aromatics (35.6%) were the most abundant VOC groups, followed by halo-hydrocarbons (14.4%) and alkenes (12.6%). The overall trend of seasonal distribution of VOC concentration was high in summer and autumn, and low in winter and spring, with a statistically significant difference between summer and winter concentrations. The ozone formation potential (OFP) showed that alkenes were the most active species, followed by aromatics and alkanes, and summer was the season with the highest OFP (131.6 ppbv). Three major emission sources were identified through principal component analysis (PCA), i.e., vehicle exhaust emissions (66.2%), fuel oil evaporation (24.8%), and industrial sources (9.0%). To ameliorate the air quality within the study area, concerted efforts should be directed towards curtailing traffic emissions and mitigating the release of alkenes, particularly emphasizing more stringent interventions during the summer season.
Citation: Atmosphere
PubDate: 2023-09-18
DOI: 10.3390/atmos14091452
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1453: Spatial and Temporal Evolution
Characteristics of Water Conservation in the Three-Rivers Headwater Region
and the Driving Factors over the Past 30 Years
Authors: Pan, Yin
First page: 1453
Abstract: The Three-Rivers Headwater Region (TRHR), located in the hinterland of the Tibetan Plateau, serves as the “Water Tower of China”, providing vital water conservation (WC) services. Understanding the variations in WC is crucial for locally tailored efforts to adapt to climate change. This study improves the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) water yield model by integrating long-term time series of vegetation data, emphasizing the role of interannual vegetation variation. This study also analyzes the influences of various factors on WC variations. The results show a significant increase in WC from 1991 to 2020 (1.4 mm/yr, p < 0.05), with 78.17% of the TRHR showing improvement. Precipitation is the primary factor driving the interannual variations in WC. Moreover, distinct interactions play dominant roles in WC across different eco-geographical regions. In the north-central and western areas, the interaction between annual precipitation and potential evapotranspiration has the highest influence. Conversely, the interaction between annual precipitation and vegetation has the greatest impact in the eastern and central-southern areas. This study provides valuable insights into the complex interactions between the land and atmosphere of the TRHR, which are crucial for enhancing the stability of the ecosystem.
Citation: Atmosphere
PubDate: 2023-09-18
DOI: 10.3390/atmos14091453
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1454: New Observations of the Meteorological
Conditions Associated with Particulate Matter Air Pollution Episodes in
Santiago, Chile
Authors: Ricardo C. Muñoz, René Garreaud, José A. Rutllant, Rodrigo Seguel, Marcelo Corral
First page: 1454
Abstract: The meteorological factors of the severe wintertime particulate matter (PM) air pollution problem of the city of Santiago, Chile, are investigated with newly available observations, including a 30 m tower measuring near-surface stability, winds and turbulence, as well as lower-tropospheric vertical profiles of temperature and winds measured by commercial airplanes operating from the Santiago airport (AMDAR database). Focusing on the cold season of the years 2017–2019, high-PM days are defined using an index of evening concentrations measured in the western part of the city. The diurnal cycles of the different meteorological variables computed over 25 PM episodes are compared against the overall diurnal cycles. PM episodes are associated with enhanced surface stability and weaker surface winds and turbulence during the evening and night. AMDAR vertical profiles of temperature and winds during episodes reveal a substantial lower-tropospheric warming attributed to enhanced regional subsidence, which is consistent with the shallower daytime boundary layer depth and the increased surface thermal amplitude observed during these days. An explanation for the weak surface winds during PM episodes was not evident, considering that these are clear days that would strengthen the local valley wind system. Two possible mechanisms are put forward to resolve this issue, which can be tested in the future using high-resolution numerical modeling validated with the new data described here.
Citation: Atmosphere
PubDate: 2023-09-19
DOI: 10.3390/atmos14091454
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1455: Simulation Analysis of Methane Exhaust
Reforming Mechanism Based on Marine LNG Engine
Authors: Jie Shi, Haoyu Yan, Yuanqing Zhu, Yongming Feng, Zhifan Mao, Xiaodong Ran, Chong Xia
First page: 1455
Abstract: LNG is a potential alternative fuel for ships. Generating H2 through exhaust reforming is an effective method to improve the performance of the LNG engine and reduce its pollutant emissions. It is necessary to study the mechanism of methane exhaust reforming to guide the design of the reformer. Based on the detailed mechanism, the characteristics of methane reforming reaction were studied for a marine LNG engine. Firstly, the reforming characteristics of exhaust were studied. The results show that methane reforming requires a lean oxygen environment, and the hydrogen production reaction will not occur when the O2 concentration is too high. Then, the effects of the O2/CH4 ratio (0.2–1) and H2O/CH4 ratio (0–2) on the reforming reaction were studied. The results show that under O2/CH4 = 0.4, the molar fraction of hydrogen at the outlet of the reactor decreases with the increase in the H2O/CH4 ratios. Finally, a mechanism analysis was conducted. The results show that an oxidation reaction occurs first and then the steam reforming reaction occurs on palladium-based catalysts.
Citation: Atmosphere
PubDate: 2023-09-19
DOI: 10.3390/atmos14091455
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1456: Mesosphere and Lower Thermosphere
Authors: Chen Zhou, Zhibin Yu
First page: 1456
Abstract: The mesosphere and low thermosphere (MLT) region is defined as the region of the atmosphere between approximately 60 and 110 km in height [...]
Citation: Atmosphere
PubDate: 2023-09-19
DOI: 10.3390/atmos14091456
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1457: Diagnosing Hurricane Barry Track Errors
and Evaluating Physics Scalability in the UFS Short-Range Weather
Application
Authors: Nicholas D. Lybarger, Kathryn M. Newman, Evan A. Kalina
First page: 1457
Abstract: To assess the performance and scalability of the Unified Forecast System (UFS) Short-Range Weather (SRW) application, case studies are chosen to cover a wide variety of forecast applications. Here, model forecasts of Hurricane Barry (July 2019) are examined and analyzed. Several versions of the Global Forecast System (GFS) and Rapid Refresh Forecast System (RRFS) physics suites are run in the UFS-SRW at grid spacings of 25 km, 13 km, and 3 km. All model configurations produce significant track errors of up to 350 km at landfall. The track errors are investigated, and several commonalities are seen between model configurations. A westerly bias in the environmental steering flow surrounding the tropical cyclone (TC) is seen across forecasts, and this bias is coincident with a warm sea surface temperature (SST) bias and overactive convection on the eastern side of the forecasted TC. Positive feedback between the surface winds, latent heating, moisture, convection, and TC intensification is initiated by this SST bias. The asymmetric divergent flow induced by the excess convection results in all model TC tracks being diverted to the east as compared to the track derived from reanalysis. The large differences between runs using the same physics packages at different grid spacing suggest a deficiency in the scalability of these packages with respect to hurricane forecasting in vertical wind shear.
Citation: Atmosphere
PubDate: 2023-09-19
DOI: 10.3390/atmos14091457
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1458: Reliability Analysis Based on Air Quality
Characteristics in East Asia Using Primary Data from the Test Operation of
Geostationary Environment Monitoring Spectrometer (GEMS)
Authors: Won Jun Choi, Kyung-Jung Moon, Goo Kim, Dongwon Lee
First page: 1458
Abstract: Air pollutants adversely affect human health, and thus a global improvement in air quality is urgent. A Geostationary Environment Monitoring Spectrometer (GEMS) was mounted on the geostationary Chollian 2B satellite in 2020 to observe the spatial distribution of air pollution, and sequential observations have been released since July 2022. The reliability of GEMS must be analyzed because it is the first payload on the geostationary Earth orbit satellite to observe trace gases. This study analyzed the initial results of GEMS observations such as the aerosol optical depth and vertical column densities (VCD) of ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), and formaldehyde (HCHO), and compared them with previous studies. The correlation coefficient of O3 ranged from 0.90 (Ozone Monitoring Instrument, OMI) to 0.97 (TROPOspheric Monitoring Instrument, TROPOMI), whereas that of NO2 ranged from 0.47 (winter, OMI and OMPS) to 0.83 (summer, TROPOMI). GEMS yielded a higher VCD of NO2 than that of OMI and TROPOMI. Based on the sources of O3 and NO2, GEMS observed the maximum VCD at a different time (3–4 h) to that of the ground observations. Overall, GEMS can make observations several times a day and is a potential tool for atmospheric environmental analysis.
Citation: Atmosphere
PubDate: 2023-09-20
DOI: 10.3390/atmos14091458
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1459: Evaluation of the Performance of CMIP6
Climate Models in Simulating Rainfall over the Philippines
Authors: Shelly Jo Igpuara Ignacio-Reardon, Jing-jia Luo
First page: 1459
Abstract: The Philippines is highly vulnerable to multiple climate-related hazards due to its geographical location and weak adaptation measures. Floods are the most catastrophic hazards that impact lives, livelihoods, and, consequently, the economy at large. Understanding the ability of the general circulation models to simulate the observed rainfall using the latest state-of-the-art model is essential for reliable forecasting. Based on this background, this paper objectively aims at assessing and ranking the capabilities of the recent Coupled Model Intercomparison Project Phase 6 (CMIP6) models in simulating the observed rainfall over the Philippines. The Global Precipitation Climatology Project (GPCP) v2.3 was used as a proxy to gauge the performance of 11 CMIP6 models in simulating the annual and rainy-season rainfall during 1980–2014. Several statistical metrics (mean, standard deviation, normalized root means square error, percentage bias, Pearson correlation coefficient, Mann–Kendall test, Theil–Sen slope estimator, and skill score) and geospatial measures were assessed. The results show that that CMIP6 historical simulations exhibit satisfactory effectiveness in simulating the annual cycle, though some models display wet/dry biases. The CMIP6 models generally underestimate rainfall on the land but overestimate it over the ocean. The trend analysis shows that rainfall over the country is insignificantly increasing both annually and during the rainy seasons. Notably, most of the models could correctly simulate the trend sign but over/underestimate the magnitude. The CMIP6 historical rainfall simulating models significantly agree on simulating the mean annual cycle but diverge in temporal ability simulation. The performance of the models remarkably differs from one metric to another and among different time scales. Nevertheless, the models may be ranked from the best to the least best at simulating the Philippines’ rainfall in the order GFDL, NOR, ACCESS, ENS, MRI, CMCC, NESM, FIO, MIROC, CESM, TAI, and CAN. The findings of this study form a good basis for the selection of models to be used in robust future climate projection and impact studies regarding the Philippines. The climate model developers may use the documented shortcoming of these models and improve their physical parametrization for better performance in the future.
Citation: Atmosphere
PubDate: 2023-09-20
DOI: 10.3390/atmos14091459
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1460: Chemical Characterization and Optical
Properties of the Aerosol in São Paulo, Brazil
Authors: Erick Vinicius Ramos Vieira, Nilton Evora do Rosario, Marcia Akemi Yamasoe, Fernando Gonçalves Morais, Pedro José Perez Martinez, Eduardo Landulfo, Regina Maura de Miranda
First page: 1460
Abstract: Air pollution in the Metropolitan Area of São Paulo (MASP), Brazil, is a serious problem and is strongly affected by local sources. However, atmosphere column composition in MASP is also affected by biomass burning aerosol (BB). Understanding the impacts of aerosol particles, from both vehicles and BB, on the air quality and climate depends on in-depth research with knowledge of some parameters such as the optical properties of particles and their chemical composition. This study characterized fine particulate matter (PM2.5) from July 2019 to August 2020 in the eastern part of the MASP, relating the chemical composition data obtained at the surface and columnar optical parameters, such as aerosol optical depth (AOD), Ångström Exponent (AE), and single-scattering albedo (SSA). According to the analyzed data, the mean PM2.5 concentration was 18.0 ± 12.5 µg/m3; however, daily events exceeded 75 times the air quality standard of the World Health Organization (15 µg/m3). The mean black carbon concentration was 1.8 ± 1.5 µg/m3 in the sampling period. Positive matrix factorization (PMF) identified four main sources of aerosol: heavy vehicles (42%), followed by soil dust plus local sources (38.7%), light vehicles (9.9%), and local sources (8.6%). AOD and AE presented the highest values in the dry period, during which biomass burning events are more frequent, suggesting smaller particles in the atmosphere. SSA values at 440 nm were between 0.86 and 0.94, with lower values in the winter months, indicating the presence of more absorbing aerosol.
Citation: Atmosphere
PubDate: 2023-09-20
DOI: 10.3390/atmos14091460
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1461: Simulation of Storm Surge Heights Based
on Reconstructed Historical Typhoon Best Tracks Using Expanded Wind Field
Information
Authors: Seung-Won Suh
First page: 1461
Abstract: A numerical model integrating tides, waves, and surges can accurately evaluate the surge height (SH) risks of tropical cyclones. Furthermore, incorporating the external forces exerted by the storm’s wind field can help to accurately reproduce the SH. However, the lack of long-term typhoon best track (BT) data degrades the SH evaluations of past events. Moreover, archived BT data (BTD) for older typhoons contain less information than recent typhoon BTD. Thus, herein, the wind field structure, specifically its relationship with the central air pressure, maximum wind speed, and wind radius, are augmented. Wind formulae are formulated with empirically adjusted radii and the maximum gradient wind speed is correlated with the central pressure. Furthermore, the process is expanded to four quadrants through regression analyses using historical asymmetric typhoon advisory data. The final old typhoon BTs are converted to a pseudo automated tropical cyclone forecasting format for consistency. Validation tests of the SH employing recent BT and reconstructed BT (rBT) indicate the importance of the nonlinear interactions of tides, waves, and surges for the macrotidal west and microtidal south coasts of Korea. The expanded wind fields—rBT—based on the historical old BT successfully assess the return periods of the SH. The proposed process effectively increases typhoon population data by incorporating actual storm tracks.
Citation: Atmosphere
PubDate: 2023-09-20
DOI: 10.3390/atmos14091461
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1462: A Convolutional Neural Network for
Steady-State Flow Approximation Trained on a Small Sample Size
Authors: Guodong Zhong, Xuesong Xu, Jintao Feng, Lei Yuan
First page: 1462
Abstract: The wind microclimate plays an important role in architectural design, and computational fluid dynamics is a method commonly used for analyzing the issue. However, due to its high technical difficulty and time-consuming nature, it limits the interaction and exploration between designers and environment performance analyses. To address the issue, scholars have proposed a series of approximation models based on machine learning that have partially improved computational efficiency. However, these methods face challenges in terms of balancing applicability, prediction accuracy, and sample size. In this paper, we propose a method based on the classic Vggnet deep convolutional neural network as the backbone to construct an approximate model for predicting steady-state flow fields in urban areas. The method is trained on a small amount of sample data and can be extended to calculate the wind environment performance. Furthermore, we investigated the differences between geometric representation methods, such as the Boolean network representation and signed distance function, as well as different structure models, such as Vgg-CFD-11, Vgg-CFD-13, Vgg-CFD-16, and Vgg-CFD-19. The results indicate that the model can be trained using a small amount of sample data, and all models generally possess the ability to predict the wind environment. The best performance on the validation set and test set was achieved with an RMSE (Root Mean Square Error) of 0.7966 m/s and 2.2345 m/s, respectively, and an R-Squared score of 0.9776 and 0.8455. Finally, we embedded the best-performing model into an architect-friendly urban comprehensive analysis platform, URBAN NEURAL-CFD.
Citation: Atmosphere
PubDate: 2023-09-20
DOI: 10.3390/atmos14091462
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1463: Exploring the Centennial-Scale Climate
History of Southern Brazil with Ocotea porosa (Nees & Mart.) Barroso
Tree-Rings
Authors: Daniela Oliveira Silva Muraja, Virginia Klausner, Alan Prestes, Tuomas Aakala, Humberto Gimenes Macedo, Iuri Rojahn da Silva
First page: 1463
Abstract: This article explores the dendrochronological potential of Ocotea porosa (Nees & Mart) Barroso (Imbuia) for reconstructing past climate conditions in the General Carneiro region, Southern Brazil, utilizing well-established dendroclimatic techniques. A total of 41 samples of Imbuia were subjected to dendroclimatic analysis to reconstruct precipitation and temperature patterns over the period from 1446 to 2011. Notably, we achieved the longest reconstructions of spring precipitation and temperature for the Brazilian southern region, spanning an impressive 566-year timeframe, by employing a mean chronology approach. To achieve our objectives, we conducted a Pearson’s correlation analysis between the mean chronology and the climatic time series, with a monthly temporal resolution employed for model calibration. Impressively, our findings reveal significant correlations with coefficients as high as rx,P = 0.32 for precipitation and rx,T = 0.45 for temperature during the spring season. Importantly, our climate reconstructions may elucidate a direct influence of the El Niño—South Oscillation phenomenon on precipitation and temperature patterns, which, in turn, are intricately linked to the natural growth patterns of the Imbuia trees. These results shed valuable light on the historical climate variability in the Southern Brazil region and provide insights into the climatic drivers affecting the growth dynamics of Ocotea porosa (Nees & Mart) Barroso.
Citation: Atmosphere
PubDate: 2023-09-20
DOI: 10.3390/atmos14091463
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1464: Standardized Precipitation and
Evapotranspiration Index Approach for Drought Assessment in
Slovakia—Statistical Evaluation of Different Calculations
Authors: Jaroslava Slavková, Martin Gera, Nina Nikolova, Cyril Siman
First page: 1464
Abstract: In the conditions of rising air temperature and changing precipitation regimes in Central Europe and Slovakia over the last two decades, it is necessary to analyse drought, develop high-quality tools for drought detection, and understand its reactions to the emerging drought situation. One of the frequently used meteorological drought indices is the Standardized Precipitation and Evapotranspiration Index (SPEI). Several parameters can be modified in different steps of the calculation process of SPEI. In the article, we analyse the influence of selected adjustable parameters on the index results. Our research has shown that the choice of a statistical distribution (Log-logistic, Pearson III, or Generalized Extreme Value) for fitting water balance can affect the feasibility of calculating distribution parameters (and thus the index) from the provided input data, as well as lead to either underestimation or overestimation of the index. The normality test of SPEI can be used as a tool for the detection and elimination of highly skewed indices and cases when the indices were not well determined by the distribution function. This study demonstrated improved results when using the GEV distribution, despite the common use of the Log-logistic distribution. With the Pearson III distribution, unusually high or low SPEI values ( SPEI > 6) were detected.
Citation: Atmosphere
PubDate: 2023-09-21
DOI: 10.3390/atmos14091464
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1465: Concentration Gradients of Ammonia,
Methane, and Carbon Dioxide at the Outlet of a Naturally Ventilated Dairy
Building
Authors: Harsh Sahu, Sabrina Hempel, Thomas Amon, Jürgen Zentek, Anke Römer, David Janke
First page: 1465
Abstract: In natural ventilation system-enabled dairy buildings (NVDB), achieving accurate gas emission values is highly complicated. The external weather affects measurements of the gas concentration of pollutants (cP) and volume flow rate (Q) due to the open-sided design. Previous research shows that increasing the number of sensors at the side opening is not cost-effective. However, accurate measurements can be achieved with fewer sensors if an optimal sampling position is identified. Therefore, this study attempted to calibrate the outlet of an NVDB for the direct emission measurement method. Our objective was to investigate the cP gradients, in particular, for ammonia (cNH3), carbon dioxide (cCO2), and methane (cCH4) considering the wind speed (v) and their mixing ratios ([cCH4/cNH3¯]) at the outlet, and assess the effect of sampling height (H). The deviations in each cP at six vertical sampling points were recorded using a Fourier-transform infrared (FTIR) spectrometer. Additionally, wind direction and speed were recorded at the gable height (10 m) by an ultrasonic anemometer. The results indicated that, at varied heights, the average cNH3 (p < 0.001), cCO2 (p < 0.001), and (p < 0.001) were significantly different and mostly concentrated at the top (H = 2.7). Wind flow speed information revealed drastic deviations in cP, for example up to +105.1% higher cNH3 at the top (H = 2.7) compared to the baseline (H = 0.6), especially during low wind speed (v < 3 m s−1) events. Furthermore, [cCH4/cNH3¯] exhibited significant variation with height, demonstrating instability below 1.5 m, which aligns with the average height of a cow. In conclusion, the average cCO2, cCH4, and cNH3 measured at the barn’s outlet are spatially dispersed vertically which indicates a possibility of systematic error due to the sensor positioning effect. The outcomes of this study will be advantageous to locate a representative gas sampling position when measurements are limited to one constant height, for example using open-path lasers or low-cost devices.
Citation: Atmosphere
PubDate: 2023-09-21
DOI: 10.3390/atmos14091465
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1466: Modeling Turbulent Fluctuations in
High-Latitude Ionospheric Plasma Using Electric Field CSES-01 Observations
Authors: Simone Benella, Virgilio Quattrociocchi, Emanuele Papini, Mirko Stumpo, Tommaso Alberti, Maria Federica Marcucci, Paola De Michelis, Mirko Piersanti, Giuseppe Consolini
First page: 1466
Abstract: High-latitude ionospheric plasma constitutes a very complex environment, which is characterized by turbulent dynamics in the presence of different ion species. The turbulent plasma motion produces statistical features of both electromagnetic and velocity fields, which have been broadly studied over the years. In this work, we use electric field high-resolution observations provided by the China-Seismo Electromagnetic Satellite-01 in order to investigate the properties of plasma turbulence within the Earth’s polar cap. We adopt a model of turbulence in which the fluctuations of the electric field are assimilated to a stochastic process evolving throughout the scales, and we show that such a process (i) satisfies the Markov condition (ii) can be modeled as a continuous diffusion process. These observations enable us to use a Fokker–Planck equation to model the changes in the statistics of turbulent fluctuations throughout the scales. In this context, we discuss the advantages and limitations of the proposed approach in modeling plasma electric field fluctuations.
Citation: Atmosphere
PubDate: 2023-09-21
DOI: 10.3390/atmos14091466
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1467: Research on the CO2 Emission
Characteristics of a Light-Vehicle Real Driving Emission Experiment Based
on Vehicle-Specific Power Distribution
Authors: Hualong Xu, Yi Lei, Ming Liu, Yunshan Ge, Lijun Hao, Xin Wang, Jianwei Tan
First page: 1467
Abstract: China implemented the China VI emission standard in 2020. The China VI emission standard has added requirements for the RDE (real-world driving emission) test. To evaluate vehicle CO2 emission for different vehicles, 10 conventional gasoline vehicles were tested under the RDE procedure using the PEMS (portable emission testing system) method. All vehicles tested meet the sixth emission regulation with a displacement of 1.4 L~2.0 L. Among the vehicles tested, the highest CO2 emission factor was 281 g/km and the lowest was 189 g/km, while the acceleration of RDE gets a wider distribution, varying from −2.5 m/s2 to 2.5 m/s2. The instantaneous mass emission rate could reach around 16 g/s. The amounts of total CO2 emission in the positive region and the negative region make up 82~89% and 11~18% of the overall CO2 emission during the entire RDE driving period, respectively. The same vehicle has a wide range of CO2 emission factors at different VSP (vehicle specific power) intervals. Different RDE test conditions can lead to large differences in CO2 emissions.
Citation: Atmosphere
PubDate: 2023-09-21
DOI: 10.3390/atmos14091467
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1468: Investigating the Characteristics of
Tropical Cyclone Size in the Western North Pacific from 1981 to 2009
Authors: Qing Cao, Xiaoqin Lu, Guomin Chen
First page: 1468
Abstract: Tropical cyclone (TC) size is an important parameter for estimating TC risks, such as precipitation distribution, gale-force wind damage, and storm surge. This paper uses the TC size dataset compiled by the Shanghai Typhoon Institute of China Meteorological Administration (STI/CMA) to investigate the interannual, monthly variation in TC size, and the relationships between TC size and intensity in the WNP basin from 1981 to 2009. The results show that the annual mean TC size oscillated within the range of 175–210 km from 1981 to 2002, then decreased following 2003. For the monthly average TC size, there are two peaks in September and October. The TC size, overall, becomes larger with increasing intensity; the samples with an unusually large size are mainly concentrated near a 40 m s−1 intensity. After the TC intensity exceeds 40 m s−1, the number of unusually large size samples gradually decreases. About 60% of the TCs reach their maximum size after reaching the peak intensity, and the average lag time is 8.3 h.
Citation: Atmosphere
PubDate: 2023-09-21
DOI: 10.3390/atmos14091468
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1469: Mitigating Ammonia Deposition Derived
from Open-Lot Livestock Facilities into Colorado’s Rocky Mountain
National Park: State of the Science
Authors: Carolina B. Brandani, Myeongseong Lee, Brent W. Auvermann, David B. Parker, Kenneth D. Casey, Erik T. Crosman, Vinícius N. Gouvêa, Matthew R. Beck, K. Jack Bush, Jacek A. Koziel, Bryan Shaw, David Brauer
First page: 1469
Abstract: Northeast Colorado’s livestock operations have been identified as a major contributor to reactive nitrogen deposition in the Rocky Mountains National Park (RMNP). We present a review on the state of knowledge concerning the emission, transport, deposition, and mitigation of gaseous ammonia (NH3) from open-lot cattle feeding facilities located east of the Northern Front Range of the Rocky Mountains. Gaseous NH3 mitigation strategies discussed are related to diet manipulation and management practices. Crude protein content of 11% and condensed tannins of 8% reduced the NH3 emission by 43% and 57%, respectively. Ambiguous results for NH3 mitigation by using water sprinklers have been reported—an increase in NH3 emission by 27% and decrease of 27 to 56%. Manure harvesting should be evaluated in terms of maintaining proper moisture content, and not necessarily as a mitigation option. The use of chemical and physical manure amendments has shown a wide range in NH3 mitigation effectiveness, ranging from 19 to 98% for chemical and 0 to 43% for physical amendments, respectively. The review outlined the scientific basis, practicality, and expected efficacy of each management practice. The most plausible management practices to reduce NH3 emissions from corral surfaces in cattle feedyards are presented.
Citation: Atmosphere
PubDate: 2023-09-22
DOI: 10.3390/atmos14101469
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1470: Characterization of the Cultivable
Microbiota Components of Marine Bioaerosols in the North Tropical Atlantic
Authors: Gabriela Cristina Chagas Moura, Yasmin Marques Ayres, Anna Luisa de Carvalho Brito, Edmilson Ferreira de Souza Júnior, Rafael dos Santos Rocha, Paulo Miguel Vieira De Sousa, Antônio Geraldo Ferreira, Oscarina Viana de Sousa, Doris Veleda
First page: 1470
Abstract: Microorganisms are key to balancing marine ecosystems and have complex interactions at the ocean–atmosphere interface, affecting global climate and human health. This research investigated the diversity of cultivable bacteria and fungi in marine bioaerosols in the North Tropical Atlantic Ocean. Using the technique of spontaneous sedimentation in selective culture media, samples were collected during oceanographic expeditions. After isolation and purification, microbial strains were identified by phenotypic and genetic analyses. Fungi isolated included Acrophialophora, Aspergillus, Chrysosporium, Cladosporium, Fonsecaea, Mucor, Rhodotorula, Schizophyllum, Stemphylium, Candida, Curvularia, Cystobasidium, Exophiala, Neotestudina, Penicillium, Pestalotiopsis, and Preussia. The bacterial isolates belonged to the Bacillota, Pseudomonadota, Enterobacteriaceae family, Bacillus genus, and Serratia liquefaciens groups. About 40% of bacteria and 42% of fungi were identified as potential human pathogens, suggesting a relationship between human actions and the microbiota present in bioaerosols on the high seas. Sea surface temperature (SST) and wind speed influenced microorganisms. More studies and analyses in different scenarios should be conducted considering environmental and climate variables in order to deepen knowledge and generate information on the subject, so that standards can be established, and quality parameters determined.
Citation: Atmosphere
PubDate: 2023-09-22
DOI: 10.3390/atmos14101470
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1471: Investigating Willingness to Invest in
Renewable Energy to Achieve Energy Targets and Lower Carbon Emissions
Authors: Evangelia Karasmanaki, Spyridon Galatsidas, Konstantinos Ioannou, Georgios Tsantopoulos
First page: 1471
Abstract: There is a keen interest in renewable energy sources (RES) as a key aspect of reducing the emissions of greenhouse gases (GHG). Supporting policies have facilitated citizen investments in renewable energy, as such investments can make a substantial contribution to emissions reduction. The problem, however, is that the factors affecting citizen willingness- to invest in renewable energy are still uncertain and tend to constantly change, highlighting the need to perform studies on the subject more frequently. As citizen investments in RES can contribute to emissions reduction, the aim of this study is to understand the factors that affect the willingness of citizens to invest in renewable energy. Using simple random sampling, a representative sample of 1536 citizens in an EU country was administered structured questionnaires, and the results were analyzed using logistic regression. It was shown that willingness to invest is affected by both financial and non-financial factors, such as citizens’ agreement with the construction of renewable facilities near their residence, information sources for obtaining information about environmental and energy topics, satisfaction with the media’s coverage of renewable investments, and their occupation. Results from this study raise substantial policy implications and may be used to improve the design of strategies for attracting citizen investments.
Citation: Atmosphere
PubDate: 2023-09-23
DOI: 10.3390/atmos14101471
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1472: Investigating Vertical Distributions and
Driving Factors of Black Carbon in the Atmospheric Boundary Layer Using
Unmanned Aerial Vehicle Measurements in Shanghai, China
Authors: Hanyu Wang, Changhai Huang
First page: 1472
Abstract: Black carbon (BC) is a significant component of fine particulate matter (PM2.5, with aerodynamic diameters ≤ 2.5 μm), and its spatial distribution greatly affects the global radiation budget. However, the vertical distributions and key driving factors of BC in the atmospheric boundary layer, where BC is mostly concentrated, remain unclear. In this study, gradient measurements of BC were made using an unmanned aerial vehicle (UAV) platform from ground level to 500 m above ground level (AGL) during and after the 2016 G20 control period in Shanghai. Generally, vertical profiles of BC from local time (LT) 9 to 17 on all experimental days demonstrated an upward trend with increasing height. The BC emitted from chimneys was initially released at higher altitudes, resulting in the positive gradients of vertical BC profiles. Furthermore, with the progressive development of the boundary layer height from LT 9 to 15, the average concentration of BC per vertical profile decreased. However, meteorological conditions unfavorable for dispersions caused by particularly high temperatures, low wind speed, unfavorable boundary layer conditions, or especially high relative humidity, and hygroscopic growth owing to the extremely high relative humidity, led to an overall increase in vertical BC and ground-based PM2.5 and BC. Despite the impact of adverse meteorological conditions, emission control measures during the control period not only effectively decreased the BC concentration but also reduced the proportion of BC in PM2.5 in the atmospheric boundary layer. The results of this study can provide valuable observations for evaluating numerical model results and important implications for making control strategies of BC in the future.
Citation: Atmosphere
PubDate: 2023-09-23
DOI: 10.3390/atmos14101472
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1473: A Review of Infrasound and Seismic
Observations of Sample Return Capsules Since the End of the Apollo Era in
Anticipation of the OSIRIS-REx Arrival
Authors: Elizabeth A. Silber, Daniel C. Bowman, Sarah Albert
First page: 1473
Abstract: Advancements in space exploration and sample return technology present a unique opportunity to leverage sample return capsules (SRCs) towards studying atmospheric entry of meteoroids and asteroids. Specifically engineered for the secure transport of valuable extraterrestrial samples from interplanetary space to Earth, SRCs offer unexpected benefits that reach beyond their intended purpose. As SRCs enter the Earth’s atmosphere at hypervelocity, they are analogous to naturally occurring meteoroids and thus, for all intents and purposes, can be considered artificial meteors. Furthermore, SRCs are capable of generating shockwaves upon reaching the lower transitional flow regime, and thus can be detected by strategically positioned geophysical instrumentation. NASA’s OSIRIS-REx (Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer) SRC is one of only a handful of artificial objects to re-enter the Earth’s atmosphere from interplanetary space since the end of the Apollo era and it will provide an unprecedented observational opportunity. This review summarizes past infrasound and seismic observational studies of SRC re-entries since the end of the Apollo era and presents their utility towards the better characterization of meteoroid flight through the atmosphere.
Citation: Atmosphere
PubDate: 2023-09-23
DOI: 10.3390/atmos14101473
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1474: Investigation of Land–Atmosphere
Coupling during the Extreme Rainstorm of 20 July 2021 over Central East
China
Authors: Yakai Guo, Changliang Shao, Aifang Su
First page: 1474
Abstract: In this study, a rainstorm of the type experienced on 20 July 2021 over central East China was simulated using the first-generation Chinese Reanalysis datasets and Global Land Data Assimilation System datasets, and the Noah land surface model coupled with the advanced weather research and forecasting model. Based on this, the gridded planetary boundary layer (PBL) profiles and ensemble states within soil perturbations were collected to investigate the typical land–atmosphere coupling chain during this modeled rainstorm by using various local coupling metrics and introduced ensemble statistical metrics. The results show that (1) except for the stratospheric thermodynamics and the surface temperature over mountain areas, the main characteristics of the mid-low atmospheric layers and the surface have been well captured in this modeled rainstorm; (2) the typical coupling intensity is characterized by the dominant morning moistening, an early afternoon weak PBL warming factor of around 2, a noontime buoyant mixing temperature deficit around 274 K, daytime PBL and surface latent flux contributions of around 100 and 280 W/m2, respectively, and significant afternoon soil-surface latent flux coupling; and (3) an overall negative soil–rainfall relationship can be identified from the ensemble metrics in which the moist static energy is more significant than PBL height, and this is consistent with the significance of daytime surface moistening indicated by local coupling metrics. Taking the multi-process chain in chronological order, the wet soil contributes greatly to daytime moisture evaporation, which then increases the early noon PBL warming and enhances the noon period buoyant mixing within weak moist heating; however, this is suppressed by large-scale forcing such as the upper southwestern inflows of rainstorms, which further significantly shapes the spatial distribution of the statistical metrics. These quantitatively described local daytime couplings highlight the potential local application of promoting public weather forecasting efforts, while the high spatial differences in the coupling indicate the more applicable threshold diagnoses within finer-scale spatial investigations.
Citation: Atmosphere
PubDate: 2023-09-23
DOI: 10.3390/atmos14101474
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1475: A Novel Combined Model for Air Quality
Index Forecasting in Changchun
Authors: Feng Chen, Lei Wang, Hongyu Deng
First page: 1475
Abstract: With the rapid development of the economy and continuous improvement in people’s living standards, the predictions of the air quality index have attracted wide attention. In this paper, a new feature selection method (Pearson-MI) and a combined model construction method (modified inverse variance method) were proposed to study the air quality index (AQI) and its influencing factors in Changchun. The Pearson-MI method selects the factors that affect the AQI of Changchun City from many influencing factors. This method reduces the RMSE of the LSTM model and XGBoost model by 27% and 5% and the MAE by 41% and 5%, respectively. A model that combines XGBoost, SVR, RF, and LSTM was constructed using the inverse variance method to predict the air quality index of Changchun City. The modified combined model resulted in a 2% reduction in RMSE and a 0.6% reduction in MAE compared with the unmodified combined model. The numerical results of our study show that the prediction accuracy of the modified combined model is obviously higher than that of the basic model, and the prediction accuracy is further improved under the Pearson-MI feature selection.
Citation: Atmosphere
PubDate: 2023-09-24
DOI: 10.3390/atmos14101475
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1476: Modelling the Impact of Adverse Weather
on Airport Peak Service Rate with Machine Learning
Authors: Ramon Dalmau, Jonathan Attia, Gilles Gawinowski
First page: 1476
Abstract: Accurate prediction of traffic demand and airport capacity plays a crucial role in minimising ground delays and airborne holdings. This paper focuses on the latter aspect. Adverse weather conditions present significant challenges to airport operations and can substantially reduce capacity. Consequently, any predictive model, regardless of its complexity, should account for weather conditions when estimating the airport capacity. At present, the sole shared platform for airport capacity information in Europe is the EUROCONTROL Public Airport Corner, where airports have the option to voluntarily report their capacities. These capacities are presented in tabular form, indicating the maximum number of hourly arrivals and departures for each possible runway configuration. Additionally, major airports often provide a supplementary table showing the impact of adverse weather in a somewhat approximate manner (e.g., if the visibility is lower than 100 m, then arrival capacity decreases by 30%). However, these tables only cover a subset of airports, and their generation is not harmonised, as different airports may use different methodologies. Moreover, these tables may not account for all weather conditions, such as snow, strong winds, or thunderstorms. This paper presents a machine learning approach to learn mapping from weather conditions and runway configurations to the 99th percentile of the delivered throughput from historical data. This percentile serves as a capacity proxy for airports operating at or near capacity. Unlike previous attempts, this paper takes a novel approach, where a single model is trained for several airports, leveraging the generalisation capabilities of cutting-edge machine learning algorithms. The results of an experiment conducted using 2 years of historical traffic and weather data for the top 45 busiest airports in Europe demonstrate better alignment in terms of mean pinball error with the observed departure and arrival throughput when compared to the operational capacities reported in the EUROCONTROL Public Airport Corner. While there is still room for improvement, this system has the potential to assist airports in defining more reasonable capacity values, as well as aiding airlines in assessing the impact of adverse weather on their flights.
Citation: Atmosphere
PubDate: 2023-09-24
DOI: 10.3390/atmos14101476
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1477: Special Issue Editorial: Long-Term
Research on the Quality of Air and the Trends of Its Variability
Authors: Liudmila P. Golobokova
First page: 1477
Abstract: Long-term observations are integral to encouraging research of atmospheric composition, the climate, and human health, and thus, filling some gaps in scientific knowledge [...]
Citation: Atmosphere
PubDate: 2023-09-24
DOI: 10.3390/atmos14101477
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1478: Air Quality Index Prediction in Six Major
Chinese Urban Agglomerations: A Comparative Study of Single Machine
Learning Model, Ensemble Model, and Hybrid Model
Authors: Binzhe Zhang, Min Duan, Yufan Sun, Yatong Lyu, Yali Hou, Tao Tan
First page: 1478
Abstract: Air pollution is a hotspot of wide concern in Chinese cities. With the worsening of air pollution, urban agglomerations face an increasingly complex environment for air quality monitoring, hindering sustainable and high-quality development in China. More effective methods for predicting air quality are urgently needed. In this study, we employed seven single models and ensemble learning algorithms and constructed a hybrid learning algorithm, the LSTM-SVR model, totaling eight machine learning algorithms, to predict the Air Quality Index in six major urban agglomerations in China. We comprehensively compared the predictive performance of the eight algorithmic models in different urban agglomerations. The results reveal that, in areas with higher levels of air pollution, the situation for model prediction is more complicated, leading to a decline in predictive accuracy. The constructed hybrid model LSTM-SVR demonstrated the best predictive performance, followed by the ensemble model RF, both of which effectively enhanced the predictive accuracy in heavily polluted areas. Overall, the predictive performance of the hybrid and ensemble models is superior to that of the single-model prediction methods. This study provides AI technological support for air quality prediction in various regions and offers a more comprehensive discussion of the performance differences between different types of algorithms, contributing to the practical application of air pollution control.
Citation: Atmosphere
PubDate: 2023-09-24
DOI: 10.3390/atmos14101478
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1479: How Well Does Weather Research and
Forecasting (WRF) Model Simulate Storm Rashmi (2008) Itself and Its
Associated Extreme Precipitation over the Tibetan Plateau at the Same
Time'
Authors: Pengchao An, Ying Li, Wei Ye, Xiaoting Fan
First page: 1479
Abstract: Northward tropical cyclones over the Bay of Bengal (BoB TCs) often interact with atmospheric circulation, transporting large amounts of water vapor to the Tibetan Plateau (TP), causing extreme precipitation. The BoB surrounded by land on three sides and the complex topography of the TP bring challenges to implementing numerical simulation in these regions. However, the scarcity of data in the two areas makes it necessary to find a technological process to perform practicable numerical simulations on the BoB TC and its induced extreme precipitation to carry out further research. In this study, the WRF 3.9.1 is used to perform many simulation experiments on a northward BoB TC Rashmi (2008) from 24 to 27 October 2008 associated with a record-breaking extreme precipitation on the TP, indicating that the selection of the simulation region, the source of initial-boundary conditions, and the cumulus convection schemes are three important factors influencing the results. We examined and compared the simulation of Rashmi with 10 experiments that were generated by combining The Final Operational Global Analysis (FNL) reanalysis data and the European Centre for Medium-Range Weather Forecasting 5(th) generation reanalysis (ERA5) data as initial-boundary conditions with five cumulus convection schemes. Most of the experiments can predict Rashmi and precipitation in the TP to a certain degree, but present different characteristics. Compared with FNL, the ERA5 performs well regarding Rashmi’s intensity and thermal structure but overestimates Rashmi’s moving speed. For the extreme precipitation in the TP, experiments suffice to reproduce the heavy rainfall (>25 mm/day) in the TP, with TS and ETS scores above 0.3 and most HSS scores greater than 0.4. The optimal experiments of three stations with extreme precipitation deviated from the actual precipitation by less than 15%. The ERA5 TDK scheme is recommended as the optimal solution for balancing the simulation of Rashmi and its extreme precipitation in the TP.
Citation: Atmosphere
PubDate: 2023-09-24
DOI: 10.3390/atmos14101479
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1480: Fire Weather Conditions in Plantation
Areas in Northern Sumatra, Indonesia
Authors: Hiroshi Hayasaka
First page: 1480
Abstract: Peatland fires in Indonesia tend to be more active during El Niño-related droughts, with the exception of fires in North Sumatra. As North Sumatra is located north of the equator and is affected by the winter and summer monsoons, fires tend to be more active not only during the dry main season from January to March, but also in June and August due to short-term droughts. Due to these complex fire trends, no appropriate fire-related indices have been found in North Sumatra. In this paper, 20 years of fire (hotspot (HS) data from 2003 to 2022, weather data (hourly and daily), and various satellite data were used to analyze fire weather conditions in Dumai plantation areas. Analysis results of 20 fire incidents (largest fires (HSs) of each year) showed the following fire weather conditions: high wind speeds (>19 km h−1), high temperatures (>33 °C), and low relative humidity (<50%). Based on the results of fire and weather analyses, several fire-related indices selected from various satellite-measured data were examined. Precipitable water vapor has the highest negative correlation with fires. It is hoped that this new fire index will be used for fire prevention not only Sumatra but also in other areas in Indonesia.
Citation: Atmosphere
PubDate: 2023-09-24
DOI: 10.3390/atmos14101480
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1481: Reclassifying the Spring Maize Drought
Index on the Loess Plateau under a Changing Climate
Authors: Shujie Yuan, Nan Jiang, Jinsong Wang, Liang Xue, Lin Han
First page: 1481
Abstract: Drought is the main meteorological disaster that affects the yield and quality of spring maize on the Loess Plateau. This study used data of the spring maize growth period, relative soil humidity, and yield at 18 agricultural meteorological observation stations on the Loess Plateau from 1997 to 2013 to determine the drought category based on the yield reduction rate. Through the drought index according to the conformity rate of category standard and individual case verification, a refined suitability drought index of spring maize on the Loess Plateau was constructed, and the spatial distribution characteristics of drought in different growth stages of spring maize were analyzed. The results showed the following: (1) The number of days in the whole growth period of spring maize in all regions of the Loess Plateau has been extended. The average sowing date of spring maize in the northwest region of the Loess Plateau was 9 April, and that in the east and central regions was 26 April. In terms of spatial distribution, each growth period was gradually delayed from west to east. (2) The correlation between relative soil humidity and yield of spring maize at the jointing stage and heading stage was the best, followed by the milky stage and mature stage, and the relative soil humidity at the sowing stage and emergence stage had little effect on the yield. (3) According to the national drought category standard “Drought Category of Spring Maize in the North”, based on the data of yield reduction rate, the drought index of spring maize on the Loess Plateau was refined by region and growth stage. The drought category index values of spring maize in different growth stages and regions changed according to the revised drought category standard, with 71.4% of the sites in the sowing seedling stage and 85.7% of the sites in the seedling jointing stage, and the revised drought category was more severe than the national drought category standard, while at 57.1% of the sites in the jointing and tasseling stages and 71.4% in the tasseling and milking stages, the revised drought category was less severe than the national drought category standard. (4) Based on the revised refined drought index for spring maize on the Loess Plateau, the spatial distribution of drought occurrence frequency across different growth stages of spring maize on the Loess Plateau was analyzed. The frequency of drought occurrence during the seeding and emergence stages was 25–75%. With the change in growth stages, the high-value area of drought occurrence frequency gradually moved northward, and the overall frequency of drought occurrence decreased. For the milky mature stage, the frequency of drought occurrence in a few regions was around 42%, and the drought frequency in most regions was between 8% and 33%.
Citation: Atmosphere
PubDate: 2023-09-25
DOI: 10.3390/atmos14101481
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1482: An Ensemble Model for PM2.5 Concentration
Prediction Based on Feature Selection and Two-Layer Clustering Algorithm
Authors: Xiaoxuan Wu, Qiang Wen, Jun Zhu
First page: 1482
Abstract: Determining accurate PM2.5 pollution concentrations and understanding their dynamic patterns are crucial for scientifically informed air pollution control strategies. Traditional reliance on linear correlation coefficients for ascertaining PM2.5-related factors only uncovers superficial relationships. Moreover, the invariance of conventional prediction models restricts their accuracy. To enhance the precision of PM2.5 concentration prediction, this study introduces a novel integrated model that leverages feature selection and a clustering algorithm. Comprising three components—feature selection, clustering, and integrated prediction—the model first employs the non-dominated sorting genetic algorithm (NSGA-III) to identify the most impactful features affecting PM2.5 concentration within air pollutants and meteorological factors. This step offers more valuable feature data for subsequent modules. The model then adopts a two-layer clustering method (SOM+K-means) to analyze the multifaceted irregularity within the dataset. Finally, the model establishes the Extreme Learning Machine (ELM) weak learner for each classification, integrating multiple weak learners using the AdaBoost algorithm to obtain a comprehensive prediction model. Through feature correlation enhancement, data irregularity exploration, and model adaptability improvement, the proposed model significantly enhances the overall prediction performance. Data sourced from 12 Beijing-based monitoring sites in 2016 were utilized for an empirical study, and the model’s results were compared with five other predictive models. The outcomes demonstrate that the proposed model significantly heightens prediction accuracy, offering useful insights and potential for broadened application to multifactor correlation concentration prediction methodologies for other pollutants.
Citation: Atmosphere
PubDate: 2023-09-25
DOI: 10.3390/atmos14101482
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1483: Investigation of the Pre- and Co-Seismic
Ionospheric Effects from the 6 February 2023 M7.8 Turkey Earthquake by a
Doppler Ionosonde
Authors: Nazyf Salikhov, Alexander Shepetov, Galina Pak, Serik Nurakynov, Azamat Kaldybayev, Vladimir Ryabov, Valery Zhukov
First page: 1483
Abstract: During the catastrophic M7.8 earthquake in Turkey on 6 February 2023, anomalous effects were revealed in the ionosphere associated with various propagation mechanisms of seismogenic disturbance from the lithosphere up to the height of the ionosphere. Seventeen minutes after the main shock, a co-seismic disturbance was detected by a Doppler ionosonde on an inclined, 3010 km long, two-hop radio path “Kuwait—Institute of Ionosphere (Almaty)”. An appearance of acoustic waves at the height of 232 km in the ionosphere was fixed 568 s after arrival of the surface Rayleigh wave to the sub-ionospheric point, and such a delay agrees with the calculated propagation time of a vertically moving acoustic wave. The disturbance lasted 160 s, and its double amplitude was above 2 Hz, which noticeably exceeds the background fluctuation of Doppler frequency. The best coincidence between the waveforms of the Doppler signal and of the surface seismic wave was observed over the duration of the two leading periods, with correlation coefficients of 0.86 and 0.79, correspondingly. Pre-seismic effects in the ionosphere were revealed 8 days before the main shock both in the variations of the Doppler frequency and of the critical frequency f0F2. The probable origination mechanism of the pre-seismic ionospheric disturbances above the region of the earthquake preparation determined by the Dobrovolsky radius may be considered in accordance with the concept of lithospheric–atmospheric–ionospheric coupling.
Citation: Atmosphere
PubDate: 2023-09-25
DOI: 10.3390/atmos14101483
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1484: Predictive Study on Extreme Precipitation
Trends in Henan and Their Impact on Population Exposure
Authors: Zongming Wang, Yuyan Wu, Shiping Xi, Xuerong Sun
First page: 1484
Abstract: This study employs precipitation data sets from historical trials on 20 CMIP6 global climate models and four shared socioeconomic pathway scenario trials (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) to predict trends in extreme precipitation changes in Henan Province quantitatively, while ascertaining the risk of population exposure to extreme precipitation in this area. The capacity of the CMIP6 models to simulate extreme precipitation indices from 1985 to 2014 is assessed using CN05.1 daily precipitation observational data. The correlation coefficients of the multi-model ensemble median’s simulation of the extreme precipitation indices are approximately 0.8, with a standard deviation ratio closer to 1 compared with the single models, demonstrating superior modeling ability. Analyses using the multi-model ensemble median demonstrate an overall increase in the total amount, frequency, and intensity of extreme precipitation in Henan throughout this century, particularly in its southern regions; in the mid-century high-emission scenario (SSP5-8.5), the maximum increase in annual total precipitation exceeds 150 mm, and it can be over 250 mm in the late-century period. For the entire province, the maximum five-day precipitation increase relative to the historical period is nearly 25 mm in the late-century SSP5-8.5 scenario. The spatiotemporal concentration of precipitation will significantly increase, heightening the risk of flood disasters. Comparative analysis reveals that, under the same population prediction, the total population exposure will be higher in high radiative forcing scenarios than in low radiative forcing scenarios, especially in Kaifeng City, where the total population exposure in SSP1 and SSP5-8.5 exceeds that in SSP1-2.6 by 2 million person-days. However, in the same radiative forcing scenario, the total population exposure in the development pathway dominated by traditional fossil fuels (SSP5) will not be significantly higher than that in the sustainable development pathway (SSP1), indicating that population activity in this century will not be the main contributor to changes in total exposure. Overall, for Henan, in the same population forecast scenario, population exposure to extreme precipitation will gradually rise with global warming.
Citation: Atmosphere
PubDate: 2023-09-25
DOI: 10.3390/atmos14101484
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1485: Near-Road Traffic Emission Dispersion
Model: Traffic-Induced Turbulence Kinetic Energy (TKE) Measurement
Authors: Zhice Hu, Kenneth E. Noll
First page: 1485
Abstract: This article delineates the characterization of traffic-induced turbulent kinetic energy (TKE) in areas proximate to roadways using real-world traffic conditions. Traffic-induced TKE serves as a pivotal tool to refine the parameters of eddy diffusivity within air dispersion modeling, thereby facilitating a more accurate representation of near-road model-estimated traffic emission with TKE-related traffic conditions. Six hundred observations facilitated the detailed TKE characterization, which incorporated a comprehensive assessment of wind speed and traffic conditions, including parameters such as vehicle flow rate, speed, and classifications into categories such as heavy-duty vehicles (HDVs) and light-duty vehicles (LDVs). Five-minute measurement intervals were utilized to pinpoint the substantial variations in TKE generated through traffic flow, particularly highlighting the more chaotic yet swiftly dissipating energy contributions from HDVs. Monitoring was conducted on two urban freeways characterized by markedly different traffic compositions (quantified with HDV%) and distinct road configurations. The TKE derived from traffic over five-minute intervals is correlated with concurrently measured variables such as vehicle flow, speed, and traffic types. The ensemble mean method was utilized to delineate the characteristics of traffic-induced TKE during both steady- and unsteady-state traffic flows, with a focus on traffic density as a key parameter. The results reveal different trends in the behavior of traffic induced TKE. The substantial impact of HDV-induced TKE was quantified using a comparative analysis of normalized traffic-induced TKEs between HDVs and LDVs. This analysis demonstrates that the influence exerted by a single HDV is approximately eleven times that of a single LDV in close proximity to road locations. Within the traffic fleet, HDVs constitute only a minor fraction, typically amounting to 1 to 10% of the total vehicle flow rate. However, their considerable impact and positive correlation with traffic induced TKE was evaluated using a detailed analysis of LDV flow subdivisions.
Citation: Atmosphere
PubDate: 2023-09-25
DOI: 10.3390/atmos14101485
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1486: Recent Advances of Single-Atom Metal
Supported at Two-Dimensional MoS2 for Electrochemical CO2 Reduction and
Water Splitting
Authors: Jiahao Wang, Xiaorong Gan, Tianhao Zhu, Yanhui Ao, Peifang Wang
First page: 1486
Abstract: Due to increasing concerns about global warming and energy crisis, intensive efforts have been made to explore renewable and clean energy sources. Single-atom metals and two-dimensional (2D) nanomaterials have attracted extensive attention in the fields of energy and environment because of their unique electronic structures and excellent properties. In this review, we summarize the state-of-art progress on the single-atom metal supported at 2D MoS2 (single-atom metal/2D MoS2) for electrochemical CO2 reduction and water splitting. First, we introduce the advantages of single-atom metal/2D MoS2 catalysts in the fields of electrocatalytic CO2 reduction and water splitting, followed by the strategies for improving electrocatalytic performances of single-atom metal/2D MoS2 hybrid nanomaterials and the typical preparation methods. Furthermore, we discuss the important applications of the nanocomposites in electrocatalytic CO2 reduction and water splitting via some typical examples, particularly focusing on their synthesis routes, modification approaches, and physiochemical mechanisms for improving their electrocatalytic performances. Finally, our perspectives on the key challenges and future directions of exploring high-performance metal single-atom catalysts are presented based on recent achievements in the development of single-atom metal/2D MoS2 hybrid nanomaterials.
Citation: Atmosphere
PubDate: 2023-09-26
DOI: 10.3390/atmos14101486
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1487: Impact of Economic and Environmental
Factors on O3 Concentrations in the Yangtze River Delta Region of China
Authors: Lei Hong, Xuewei Hou, Dong Liu, Changxin Zou
First page: 1487
Abstract: The concentration of atmospheric ozone (O3) pollution is showing a rapid growing tendency, and O3 pollution has become one of the bottleneck issues that restrict the continuous improvement of air quality in China. In this study, we first identified the primary factors based on the source apportionment of O3, then used factor analysis to divide these selected factors into economic and environmental categories. The geographical detector model was used to analyze the impact of factors and their interactions on O3 concentration in 41 cities in the Yangtze River Delta (YRD) region in 2020. The results showed that forest coverage ranked first among all the detected factors, suggesting a strong relationship between the regional O3 concentration and forest coverage. The driving factors of economic activity were ranked as follows: actual utilization of foreign capital (0.400) > gross domestic product (GDP) per capita (0.387) > proportion of tertiary industry (0.360) > urbanization rate (0.327) > per capita consumption expenditure (0.194) > research and development (R&D) of full-time equivalents of industrial enterprises above designated size (0.182) > number of industrial enterprises (0.126). The interaction between any two factors enhanced their influence on O3 concentration more than any single factor, indicating that the variability of regional O3 concentration was an outcome of a combination of multiple factors. This study could provide recommendations for the prevention and control of O3 pollution and the development of ecological integration in the YRD region.
Citation: Atmosphere
PubDate: 2023-09-26
DOI: 10.3390/atmos14101487
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1488: Research on a Clustering Forecasting
Method for Short-Term Precipitation in Guangdong Based on the CMA-TRAMS
Ensemble Model
Authors: Jiawen Zheng, Pengfei Ren, Binghong Chen, Xubin Zhang, Hongke Cai, Haowen Li
First page: 1488
Abstract: In light of the 2020–2021 flood season in Guangdong, we conducted a comprehensive assessment of short-term precipitation forecasts generated by the ensemble prediction system (EPS) based on the China Meteorological Administration Tropical Regional Atmosphere Model for the South China Sea (CMA-TRAMS). Furthermore, we applied four distinct strategies to cluster the ensemble forecast data produced by the model for precipitation, aiming to enhance our understanding of their applicability in short-term precipitation forecasting for Guangdong. Our key findings were as follows.: Precipitation during the 2020–2021 flood season in Guangdong exhibited distinct characteristics. The impacting areas of frontal and subtropical high-edge rainfall were relatively scattered, predominantly occurring in the evening and nighttime. In contrast, monsoon precipitation and return-flow precipitation were concentrated, with their impacts lasting from early morning to evening. Notably, the errors using the ensemble maximum and minimum values were large, while the errors for the ensemble mean values and medians were small. This indicated that the model’s short-term precipitation forecasts possessed a high degree of stability. The vertical shear of different types of precipitation exerted a noticeable influence on the model’s performance. The model consistently displayed a tendency to underestimate short-term precipitation in Guangdong; however, this bias decreased with longer lead times. Simultaneously, the model’s dispersion increased with longer lead times. In terms of mean absolute error (MAE) test results, there was little difference in the performance of ensemble primary forecasts under various strategies, while the “ward” strategy performed well in sub-primary cluster forecasts. This was particularly true for areas and types of precipitation where the model’s performance was poor. While the clustering approach lagged behind ensemble mean forecasts in predicting rainy conditions, it exhibited improvement in forecasting short-term heavy rainfall events. The “complete” and “single” strategies consistently delivered the most accurate forecasts for such events. Our study sheds light on the effectiveness of clustering methods in improving short-term precipitation forecasts for Guangdong, particularly in regions and conditions where the model initially struggled. These findings contribute to our understanding of precipitation forecasting during flood seasons and can inform strategies for enhancing forecast accuracy in similar contexts.
Citation: Atmosphere
PubDate: 2023-09-26
DOI: 10.3390/atmos14101488
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1489: Spatial Downscaling of GPM Satellite
Precipitation Data Using Extreme Random Trees
Authors: Shaonan Zhu, Xiangyuan Wang, Donglai Jiao, Yiding Zhang, Jiaxin Liu
First page: 1489
Abstract: Obtaining precise and detailed precipitation data is crucial for analyzing watershed hydrology, ensuring sustainable water resource management, and monitoring events such as floods and droughts. Due to the complex relationship between precipitation and geographic factors, this study divides the entire country of China into eight vegetation zones based on different vegetation types. Within each vegetation zone, we employ a seasonally adjusted Extreme Random Trees approach to spatially downscale GPM (Global Precipitation Measurement) satellite monthly precipitation data. To validate the effectiveness of this method, we compare it with kriging interpolation and traditional global downscaling methods. By increasing the spatial resolution of the GPM monthly precipitation dataset from 0.1° to 0.01°, we evaluate the downscaled results and validate them against ground-level rain gauge data and GPM satellite precipitation data. The results indicate that the partitioned area prediction method outperforms other approaches, resulting in a precipitation dataset that not only achieves high accuracy but also offers finer spatial resolution compared to the original GPM precipitation dataset. Overall, this approach enhances the model’s capability to capture complex spatial features and demonstrates excellent generalization. The resulting higher-resolution precipitation dataset enables the creation of more accurate precipitation distribution maps, providing data support for regions lacking hydrological information. These data can be used to analyze seasonal precipitation patterns and reveal differences in precipitation across different seasons and geographic regions.
Citation: Atmosphere
PubDate: 2023-09-26
DOI: 10.3390/atmos14101489
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1490: Responses of Extreme Climates in South
Asia under a G6sulfur Scenario of Climate Engineering
Authors: Jingrong Wang, Zhihua Zhang, M. James C. Crabbe, Lipon Chandra Das
First page: 1490
Abstract: Under global warming scenarios, extreme climate events in South Asia will occur more frequently which will seriously threaten the safety of local residents. South Asia faces dual pressures of the obligation of carbon emissions reduction globally and the demand for a better life for huge populations. Stratospheric Aerosol Injection (SAI) climate engineering provides a potential solution to this dilemma. We compared the evolution of 12 climate extreme indices under historical scenarios, two future scenarios (SSP245, SSP585) and an implementation scenario of SAI climate engineering (G6sulfur). We showed that the intensity and frequency of extreme climates under a G6sulfur scenario would be significantly higher than those under historical scenarios, and that the difference in extreme climates under three scenarios (SSP245, SSP585, and G6sulfur) would be widely varying, with some indices being considerably mitigated while others would reflect a worse set of circumstances than would be the case without SAI climate engineering. Therefore, SAI climate engineering is not an effective tool to mitigate future climate extremes in South Asia under global warming scenarios.
Citation: Atmosphere
PubDate: 2023-09-26
DOI: 10.3390/atmos14101490
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1491: Potential Health Impacts from a Wildfire
Smoke Plume over Region Jämtland Härjedalen, Sweden
Authors: Andreas Tornevi, Camilla Andersson, Ana Carvalho, Joakim Langner, Bertil Forsberg
First page: 1491
Abstract: In the summer of 2018, Sweden experienced widespread wildfires, particularly in the region of Jämtland Härjedalen during the final weeks of July. We previously conducted an epidemiological study and investigated acute respiratory health effects in eight municipalities relation to the wildfire air pollution. In this study, we aimed to estimate the potential health impacts under less favorable conditions with different locations of the major fires. Our scenarios focused on the most intense plume from the 2018 wildfire episode affecting the largest municipality, which is the region’s only city. Combining modeled PM2.5 concentrations, gridded population data, and exposure–response functions, we assessed the relative increase in acute health effects. The cumulative population-weighted 24 h PM2.5 exposure during the nine highest-level days reached 207 μg/m3 days for 63,227 inhabitants. We observed a small number of excess cases, particularly in emergency unit visits for asthma, with 13 additional cases compared to the normal 12. Overall, our scenario-based health impact assessment indicates minor effects on the studied endpoints due to factors such as the relatively small population, limited exposure period, and moderate increase in exposure compared to similar assessments. Nonetheless, considering the expected rise in fire potential due to global warming and the long-range transport of wildfire smoke, raising awareness of the potential health risks in this region is important.
Citation: Atmosphere
PubDate: 2023-09-26
DOI: 10.3390/atmos14101491
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1492: Assessing the Cooling Potential of
Tailing Piles for Urban Heat Mitigation in Germany’s Ruhr
Metropolitan Area—A Case Study of the Rungenberg in Gelsenkrichen
Authors: Patricia Glocke, Tobias Scholz, A. Martina Grudzielanek
First page: 1492
Abstract: Elevated air temperatures in cities with potential negative effects on, e.g., residents are a major challenge for urban planning. Open green spaces on hills where at night air can cool and drain into residential areas are of great importance to ameliorate the heat load in urban areas. In the Ruhr Metropolitan Region in Germany, tailing piles from the former coal mining industry offer a previously neglected potential for cooling neighbourhoods. The genesis and drainage of cold air on tailing piles have not been extensively investigated so far. Tailing piles are often located in or nearby residential areas and are exposed as open spaces, where cold air can build up and drain into the surrounding neighbourhoods due to their slopes. In the present study, the genesis of cold air and the cold air drainage are empirically investigated using thermal infrared imagery and air temperature measurements during one night in 2019 at the Rungenberg tailing pile in Gelsenkirchen. Furthermore, the cooling effect on the adjacent residential area, Schüngelberg, was studied. The results indicate that cold air builds up at Rungenberg and drains into Schüngelberg. However, the cold air flow into the residential area was blocked by a brick wall located at the foot of the Rungenberg tailing pile. More awareness should be given to the cooling potential of tailing piles, and urban planners should improve this cooling potential by keeping tailing piles open and removing barriers located in the drainage pathways in order to alleviate urban heat.
Citation: Atmosphere
PubDate: 2023-09-27
DOI: 10.3390/atmos14101492
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1493: The Characteristics of the Abnormal
Day-to-Day TEC Variation above East Asian Region
Authors: Fanfan Su, Jian Yang, Liangchen Hu, Fuying Zhu
First page: 1493
Abstract: We investigate the abnormal day-to-day variability of total electron content (TEC) over 60 Global Navigation Satellite System (GNSS) stations above the East Asian region from 2012 to 2018 and find that the positive anomalies occur more frequently at the middle latitude at about LT 14–20 and occur frequently around 28° N at about LT 22–00. The negative anomalies occur more frequently at the middle latitude at LT 10–02, and they obviously occur less frequently at about 15° N~30° N and LT 08–12, and occur less frequently near about 22° N~30° N and LT 14–18. The quantities of positive anomalies and negative anomalies are comparable. The direction of moving anomalies is from east to west in a zonal direction in all conditions. The moving speeds of anomalies are around 15~19 degrees per hour in the zonal direction and seem to grow as the latitude increases. TEC anomalies occur in 22.1% of temporal bins before large earthquakes within seven days and occur in 24% of temporal bins in the interval, which is within one day before and three days later than the main phase of geomagnetic storms. Further work is necessary to determine the sources of these anomalies.
Citation: Atmosphere
PubDate: 2023-09-27
DOI: 10.3390/atmos14101493
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1494: Analysis of Hotspots and Trends in Soil
Moisture Research since the 21st Century
Authors: Yuanxiang Cai, Yaping Yang, Xiafang Yue, Yang Xu
First page: 1494
Abstract: Soil moisture is a key factor in ecosystems that profoundly affects carbon, nitrogen, and water cycles on land surfaces, vegetation growth, and climate change. Consequently, numerous scholars have researched and authored scientific literature on soil moisture and related topics. Using the Web of Science database, we conducted a bibliometric analysis of 60,581 papers published in the field of soil moisture between 2000 and 2022. The findings revealed the following trends. (1) The number of publications on soil moisture has consistently increased in the 21st century at an increasing rate. For instance, although the annual increase was only 94 publications in 2005, it surged to 321 publications in 2020. (2) The United States (US), China, and developed European countries emerged as primary research institutions and authors. The US occupies a leading position in soil moisture research, boasting the highest number of publications and total citations in the field, whereas China ranks second in both publications and total citations. (3) Regarding international collaboration, the US has established close partnerships with numerous international research institutions. However, China’s international cooperation in this field requires improvement. (4) The Journal of Hydrology holds the top position in terms of both the total number of published articles and citations. Research on water resources ranked first in terms of its H-index. (5) Keyword analysis highlighted several current research hotspots, including the coupled covariance effect of soil moisture and land surface environmental factors in the context of climate change, soil moisture utilization rate, crop yield, influence mechanism of soil moisture on soil ecosystem structure, and development of high-precision soil moisture data products. In conclusion, this study provides a systematic review of the research hotspots and trends in soil moisture studies in the 21st century. The objective is to offer a comprehensive reference to aid in understanding the evolutionary patterns of soil moisture research in multiple dimensions.
Citation: Atmosphere
PubDate: 2023-09-27
DOI: 10.3390/atmos14101494
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1495: Atmospheric Transport of Adulticides Used
to Control Mosquito Populations across an Urban Metropolitan Area
Authors: Sarah L. Guberman VerPloeg, Subin Yoon, Sergio L. Alvarez, James H. Flynn, Don Collins, Robert J. Griffin, Rebecca J. Sheesley, Sascha Usenko
First page: 1495
Abstract: Pesticides registered with the U.S. EPA for mosquito control are called adulticides and are released directly into the atmosphere as aerosols to target flying mosquitos. This adulticide application approach is different from traditional (agricultural) pesticide applications, yet the fate and transport of adulticides in large metropolitan areas is largely unknown. The Houston Metropolitan Area encompasses eight counties, many of which require county-level mosquito control programs that utilize adulticides. Malathion and permethrin are the primary adulticides used by Harris County (HC) in Houston, TX, USA. Houston, like many other metropolitan areas, has an urban atmosphere supporting the oxidation of both gas and particle phase pollutants. During the summer mosquito season of 2016, we collected atmospheric total suspended particulate matter (PM) samples at Jones Forest (JF), located in Montgomery County (directly north of HC) to investigate the atmospheric transport and oxidation of adulticides in an urban atmosphere. Despite HC alternating the adulticide treatment schedule, we measured permethrin, malathion, and malaoxon (oxidation product of malathion), throughout the sampling campaign. These consistent measurements, in conjunction with 12 h backward trajectories, support the conclusion that JF is influenced by other county-level mosquito-control programs and agricultural pesticide use. This cross-county transport may impact adulticide effectiveness by supporting pesticide resistance in mosquito populations due to repeated exposures to pesticides. This study highlights the need for mosquito control collaborations between counties, especially in areas of urban expansion overlapping with agricultural activities.
Citation: Atmosphere
PubDate: 2023-09-27
DOI: 10.3390/atmos14101495
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1496: Twenty-Year Review of Outdoor Air Quality
in Utah, USA
Authors: Callum E. Flowerday, Ryan Thalman, Jaron C. Hansen
First page: 1496
Abstract: Air quality is a prevalent concern due to its imposing health risks. The state of Utah, USA, at times over the last 20 years has suffered from some of the worst air quality in the nation. The propensity for the state of Utah to experience elevated concentrations of particulate matter and ozone can in part be attributed to its unique geography that features dry, mountainous topography. Valleys in Utah create ideal environments for extended cold-pool events. In this review, we summarize the research executed in Utah over the past 20 years (2002–2022) by dividing the state into six regions: Utah Valley, Summit County, Southern Utah (regions south of Utah Valley), Cache Valley, Uinta Basin, and Salt Lake Valley. We review the published literature chronologically and provide a summary of each region identifying areas where additional research is warranted. We found that the research effort is weighted towards Uinta Basin and Salt Lake Valley, with the other regions in Utah only adding up to 20% of the research effort. We identified a need for more source apportionment studies, speciated volatile organic compound (VOC) studies, and ozone isopleths. Where ozone isopleths are not able to be created, measurement of glyoxal and formaldehyde concentrations could serve as surrogates for more expensive studies to inform ozone mitigation policies.
Citation: Atmosphere
PubDate: 2023-09-27
DOI: 10.3390/atmos14101496
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1497: Assessment of NEX-GDDP-CMIP6 Downscale
Data in Simulating Extreme Precipitation over the Huai River Basin
Authors: Jiang, Wen, Gao, Zhu
First page: 1497
Abstract: This study aimed to assess the performance of 35 global climate models included in NEX-GDDP-CMIP6, derived from downscaling CMIP6 data to high spatial (25 km) and temporal (daily) resolutions, in reproducing extreme precipitation events over the Huai River Basin. Eight widely used extreme precipitation indices were employed to quantitatively describe the models’ capability of simulation. Results indicate that the majority of models can reasonably capture trends, with UKESM1-0-LL performing the best among all considered models. All models demonstrate high accuracy in simulating climatological means, especially for the total precipitation (PRCPTOT), displaying a spatial correlation coefficient exceeding 0.8 when compared to the observed data. NorESM2-MM and MRI-ESM2-0 can accurately simulate the frequency and intensity of extreme precipitation, respectively. In general, UKESM1-0-LL, CESM2, MIROC6, MRI-ESM2-0, CMCC-CM2-SR5, and MPI-ESM-2-LR exhibit superior simulation capabilities in terms of capturing both the trends and climatology of extreme precipitation. The aforementioned findings provide guidance for future studies on the regional impacts of climate change using NEX model data, and therefore hold great importance in comprehending the regional impacts of, and the adaptability to, climate change, as well as the development of adaptation strategies.
Citation: Atmosphere
PubDate: 2023-09-27
DOI: 10.3390/atmos14101497
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1498: Mortality during Heatwaves and Tropical
Nights in Vienna between 1998 and 2022
Authors: Manuel Hagen, Philipp Weihs
First page: 1498
Abstract: Rising summer temperatures lead to heat waves and tropical nights, which can result in health problems among the population. This work examined if mortality among Viennese people has increased under such weather conditions or whether the population was able to adapt to those periods of extreme heat. Therefore, the daily climatic data of the Austrian Weather Service and the number of daily deaths in Vienna from 1998 to 2022 have been put into relation. After calculating the mean values from those data sets, we analyzed the total number of daily deaths but also the death rate per 100,000 inhabitants for the total Viennese population, for men and women. The impact of age structure on possible trends was analyzed and ruled out. The analysis showed that the mortality on days with heat events was still higher, but the mean values of daily deaths decreased over time, despite a doubling of heatwaves and tropical nights, which speaks for an adaptation to heat events by the Viennese population.
Citation: Atmosphere
PubDate: 2023-09-28
DOI: 10.3390/atmos14101498
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1499: Impact of Anthropogenic Heat on Urban
Environment: A Case Study of Singapore with High-Resolution Gridded Data
Authors: Ao Wang, Xian-Xiang Li, Rui Xin, Lup Wai Chew
First page: 1499
Abstract: Anthropogenic heat (AH) emissions have great impacts on urban climate. AH is usually spatially heterogeneous and depends on the urban land use type. Studies using high-resolution gridded data that can resolve spatially heterogeneous AH are still scarce. The present study uses AH data of a high spatial resolution of 200 m by 200 m and a temporal resolution of 1 h to investigate the impact of AH in Singapore in April 2016, particularly regarding the relative contribution of individual AH components. The WRF model coupled with a single-layer urban canopy model is employed. The WRF model can predict the 2-m air temperature and 2-m relative humidity with good agreement with the observation data, while the simulated 10-m wind speed has relatively large deviation from the observation data. The largest spatially averaged temperature increases caused by total AH (QF), AH from buildings (QB) and AH from traffic (QV) are 1.44 °C, 1.44 °C and 1.35 °C, respectively. The effects of AH on sensible heat flux and boundary layer height are largely consistent, with both QF and QB exhibiting significant effects at night, while the effects of QV are small. The effect of AH on the local circulations (sea and land breezes) in Singapore is small, while its effect on the urban heat island (UHI) circulations is more pronounced. Due to the UHI circulations, the sum of the effects on local temperatures caused by QB and QV may exceed that by QF in some areas. This finding can guide comprehensive mitigation measures of AH by not only focusing on land use type but also on the contribution of individual AH components, in order to ameliorate the impacts of urban overheating.
Citation: Atmosphere
PubDate: 2023-09-28
DOI: 10.3390/atmos14101499
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1500: The Impact of Surface Waves and Spray
Injection Velocities on Air–Sea Momentum and Heat Fluxes
Authors: Ting Zhang
First page: 1500
Abstract: Surface waves and sea spray play a significant role in air–sea fluxes in high winds. The present study used a marine atmosphere surface layer (MASL), which couples the traditional Monin–Obukhov similarity theory, sea spray generation function, the balance of turbulent kinetic budget, and momentum/enthalpy conservation equations. Based on this model, the effects of wave states and spray injection velocities on air–sea momentum/enthalpy fluxes and near-surface wind/temperature profiles were theoretically investigated. Based on the assumption that the velocity of injected spray is the same as that of the ambient airflow, it was found that spray could increase the near-surface air turbulence intensity and inhibit air–sea fluxes at 10 m above the sea surface. Correspondingly, near-surface wind speeds and temperature increase in high winds. This phenomenon becomes prominent in cases of large wave ages or surface waves supporting a minority of air–sea fluxes. Based on the assumption that the velocity of the edges of breaking water bags is used to estimate that of spray injection, the opposite results were found: spray could weaken the near-surface air turbulence and increase total air–sea fluxes at 10 m above the sea surface. In this case, the near-surface wind speeds and temperature decreased. This reduction becomes remarkable when surface waves are full-developed or the majority of air–sea momentum fluxes are supported by waves.
Citation: Atmosphere
PubDate: 2023-09-28
DOI: 10.3390/atmos14101500
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1501: Estimating Daily Temperatures over Andhra
Pradesh, India, Using Artificial Neural Networks
Authors: Gubbala Ch. Satyanarayana, Velivelli Sambasivarao, Peddi Yasaswini, Meer M. Ali
First page: 1501
Abstract: In the recent past, Andhra Pradesh (AP) has experienced increasing trends in surface air mean temperature (SAT at a height of 2 m) because of climate change. In this paper, we attempt to estimate the SAT using the GFDL-ESM2G (Geophysical Fluid Dynamics Laboratory Earth System Model version 2G), available from the Coupled Model Intercomparison Project Phase-5 (CMIP5). This model has a mismatch with the India Meteorological Department (IMD)’s observations during April and May, which are the most heat-prone months in the state. Hence, in addition to the SAT from the model, the present paper considers other parameters, such as mean sea level pressure, surface winds, surface relative humidity, and surface solar radiation downwards, that have influenced the SAT. Since all five meteorological parameters from the GFDL-ESM2G model influence the IMD’s SAT, an artificial neural network (ANN) technique has been used to predict the SAT using the above five meteorological parameters as predictors (input) and the IMD’s SAT as the predictand (output). The model was developed using 1981–2020 data with different time lags, and results were tested for 2021 and 2022 in addition to the random testing conducted for 1981–2020. The statistical parameters between the IMD observations and the ANN estimations using GFDL-ESM2G predictions as input confirm that the SAT can be estimated accurately as described in the analysis section. The analysis conducted for different regions of AP reveals that the diurnal variations of SAT in the IMD observations and the ANN predictions over three regions (North, Central, and South AP) and overall AP compare well, with root mean square error varying between 0.97 °C and 1.33 °C. Thus, the SAT predictions provided in the GFDL-ESM2G model simulations could be improved statistically by using the ANN technique over the AP region.
Citation: Atmosphere
PubDate: 2023-09-28
DOI: 10.3390/atmos14101501
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1502: The Difference in Cloud Water Resources
and Precipitation on the Eastern and Western Sides of the Liupan Mountains
Caused by Topographic Effects
Authors: Rui Xu, Yujun Qiu
First page: 1502
Abstract: In order to explore the possible impact of topography on precipitation between the eastern and western sides of the Liupan Mountains (LMs) in the northwest region of China, the differences in distribution characteristics of total column water vapor (TCWV), total column cloud water (TCCW), and total precipitation (TP) were studied by using the 40-year hourly data of the fifth generation reanalysis (ERA5) from the European Centre for Medium-Range Weather Forecasts (ECMWF). The results showed the following: (1) The TCCW and TP on the eastern and western sides of the LMs decrease gradually from south to north, following a southwestward bias along the latitude. The high values of the TCCW and TP are predominantly concentrated in the period from July to September. The greatest difference between the two sides occurs in September, with the eastern side exhibiting 15% and 18% higher values compared to the western side, respectively. (2) Both the TCCW and TP exhibit distinct diurnal distribution patterns. The high values on the eastern side persist for a longer duration throughout the day compared to the western side, and they occur in more consecutive months. There is a certain correlation between the steepness of the eastern slope and the gentle gradient of the western slope. Additionally, the occurrence of these high values in the afternoon is earlier on the eastern side compared to the western side. (3) The monthly mean TP is significantly linearly correlated with the TCWV and TCCW, with slightly higher coefficients for the western side compared to the eastern side. This relationship is closely related to the topography of the mountain range. The regression equation provides a quantitative tool for predicting the monthly mean TP in the LM region and serves as a reference basis for the development of cloud water resources in the area.
Citation: Atmosphere
PubDate: 2023-09-28
DOI: 10.3390/atmos14101502
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1503: Molecular Dynamics Simulation Study on
Adsorption Characteristics of Illite for Hg2+
Authors: Zhengchao Guo, Biao Wang, Xin Tang
First page: 1503
Abstract: The Three Gorges Reservoir area of the Yangtze River has formed vast riverine fallout zones as a result of its periodic water storage and flood discharge operations, and the main constituents of this area are quaternary loose clays. It is important to study the microscopic characteristics of clay minerals in these fallout zones and their adsorption properties of Hg2+ to guide the environmental safety of the fallout zones in the Three Gorges Reservoir area. In this context, the authors of this paper used X-ray diffraction (XRD) experiments to reveal the main clay mineral compositions in the fallout zones and then constructed the molecular model structures of the clay minerals based on molecular dynamics theory and studied the adsorption characteristics of these clay minerals with Hg2+ in depth. The results show that the main clay minerals in the Three Gorges Reservoir area fallout zone include illite, illite-mixed layer and green-mixed layer, in which the content of illite ranges from 21% to 54%. Taking illite as the study object, the heat of adsorption of Hg2+ in illite ranged from 14.83 kJ·mol−1 to 31.92 kJ·mol−1, which is a physical adsorption. The heat of adsorption was mainly affected by the water content and had little relationship with temperature. With the gradual increase in water content, the heat of adsorption gradually decreases. The adsorption amount of Hg2+, on the other hand, is jointly affected by water content and temperature and decreases with the increase in water content and temperature; under natural environmental conditions (P = 0.1 Mpa), the adsorption characteristics of Hg2+ in illite change with the change in water content. When the water content was between 0% and 6.95%, the increase in water content led to an increase in the interlayer spacing of illite, and the adsorption of Hg2+ in illite was in a monolayer state, with the adsorption peaks located from 4.5~5.5 Å. When the water content increased to 6.95% to 13.90%, the layer spacing of illite reached the maximum, and the adsorption of Hg2+ in illite transitioned from a monolayer to a bilayer, with the adsorption peaks located between 5 Å and 9~10 Å, respectively. When the water content was further increased to 13.90% to 20.85%, the increase in water content instead led to a slight decrease in the layer spacing of illite, showing a tendency of transitioning from a bilayer to a monolayer adsorption layer, which at the same time changed the number of adsorption layers of Hg2+; the study also revealed that the interaction between illite and Hg2+ was regulated by van der Waals and Coulomb forces, whereas the increase in temperature promoted the Hg2+ +diffusion, and an increase in water content inhibits the diffusion of Hg2+. In summary, these findings provide valuable theoretical support for solving the problem of Hg2+ pollution in the Three Gorges Reservoir Decline Zone.
Citation: Atmosphere
PubDate: 2023-09-28
DOI: 10.3390/atmos14101503
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1504: Calibration of DustTrak and Low-Cost
Sensors and Their Application for Assessment of Inhalation Exposures to
Traffic-Related PM2.5 and PM1 in Ho Chi Minh City
Authors: Nguyen Doan Thien Chi, Tran Anh Ngan, Tran Cong-Thanh, Duong Huu Huy, Shih-Chun Candice Lung, To Thi Hien
First page: 1504
Abstract: The in-traffic microenvironment can enhance personal exposure to fine particulate matter (PM). With this study, we aimed to calibrate a DustTrak instrument (DustTrak 8533 DRX Aerosol Monitor, TSI Incorporated, Shoreview, MN, USA) and low-cost sensors (AS-LUNG-P sensors) and then assess inhalation exposure to PM2.5 and PM1 for different commuters in central areas of Ho Chi Minh City (HCM). The DustTrak instrument and low-cost sensors were calibrated using a gravimetric method under side-by-side conditions. Relationships between the DustTrak signals and PM concentrations measured by the gravimetric method were identified using simple linear regression models for PM2.5 (R2 = 0.998, p-value < 0.05) and PM1 (R2 = 0.989, p-value < 0.05). Meanwhile, PM concentrations determined by the AS-LUNG-P sensors and the gravimetric method were correlated using two-segmented linear regressions. To obtain the corresponding two-segment regression equations, the response of the AS-LUNG-P sensors was compared with the corrected DustTrak data. The coefficient of variation (CV) evaluated for all sensors was smaller than 10%, indicating that the data were applicable for particle assessment. For inhalation exposure assessment, the results showed that commuters using open transport modes, such as bikes, motorbikes, and walking, were exposed to more PM than those using closed transport modes (e.g., cars). Specifically, the bicyclists had the highest inhaled doses of PM among the open transport groups. PM exposure levels in the morning were higher than in the afternoon. Additionally, exposure levels to PM concentrations rapidly increased when passing through intersections of major roads and moderately decreased when using surgical facemasks.
Citation: Atmosphere
PubDate: 2023-09-28
DOI: 10.3390/atmos14101504
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1505: Effects of Typhoon Chanthu on Marine
Chlorophyll a, Temperature and Salinity
Authors: Jushang Wang, Biyun Guo, Zhaokang Ji, Yingliang Che, Venkata Subrahmanyam Mantravadi
First page: 1505
Abstract: A typhoon is a severe weather process in tropical oceans. Typhoon transit is often accompanied by strong convective weather, such as gales and rainstorms, which threatens fishery, property, and human safety. In this study, the effects of typhoon Chanthu on chlorophyll a (Chl a), temperature, and ocean surface salinity are analyzed using remote sensing data. The results illustrate that before the transit of Chanthu (6–12 September), the mean concentration of Chl a and sea surface salinity (SSS) are low (0.74 mg/m3, 30.59 psu, respectively), while the mean sea surface temperature (SST) is high (29.01 °C). After the typhoon transits (13–30 September), the mean Chl a concentration and salinity increase (1.29 mg/m3, 30.87 psu respectively), while the mean SST decrease (27.43 °C). The Ekman pumping transports nutrients from the deep ocean to the surface layer, promotes the photosynthesis of surface phytoplankton, and increases the concentration of sea surface Chl a. Typhoon Chanthu causes the mixing and entrainment of the upper ocean, which causes the deep cold water of the ocean to rise into the mixed layer and cause the SST to decrease. Severe vertical mixing transports deep high-salt water to the surface, causing SSS to rise. The results of this study have important scientific significance and application value for developing coastal economy, aquaculture, and fishery.
Citation: Atmosphere
PubDate: 2023-09-28
DOI: 10.3390/atmos14101505
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1506: GraphAT Net: A Deep Learning Approach
Combining TrajGRU and Graph Attention for Accurate Cumulonimbus
Distribution Prediction
Authors: Ting Zhang, Soung-Yue Liew, Hui-Fuang Ng, Donghong Qin, How Chinh Lee, Huasheng Zhao, Deyi Wang
First page: 1506
Abstract: In subtropical regions, heavy rains from cumulonimbus clouds can cause disasters such as flash floods and mudslides. The accurate prediction of cumulonimbus cloud distribution is crucial for mitigating such losses. Traditional machine learning approaches have been used on radar echo data generated by constant altitude plan position indicator (CAPPI) radar systems for predicting cumulonimbus cloud distribution. However, the results are often too foggy and fuzzy. This paper proposes a novel approach that integrates graph convolutional networks (GCN) and trajectory gated recurrent units (TrajGRU) with an attention mechanism to predict cumulonimbus cloud distribution from radar echo data. Experiments were conducted using the moving modified National Institute of Standards and Technology (moving MNIST) dataset and real-world radar echo data, and the proposed model showed a 59.12% improvement in mean square error (MSE) and a 16.26% improvement in structure similarity index measure (SSIM) on average in the moving MNIST dataset, a 65.40% improvement in MSE, and an 10.29% improvement in SSIM on average in the radar echo dataset. These results demonstrate the effectiveness of the proposed approach for improving the prediction accuracy of cumulonimbus cloud distribution.
Citation: Atmosphere
PubDate: 2023-09-29
DOI: 10.3390/atmos14101506
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1507: Characteristics of the Blitzortung.org
Lightning Location Catalog in Japan
Authors: Masashi Kamogawa, Tomoyuki Suzuki, Hironobu Fujiwara, Tomomi Narita, Egon Wanke, Kotaro Murata, Toshiyasu Nagao, Tetsuya Kodama, Jun Izutsu, Atsushi Matsuki, Ning Tang, Yasuhiro Minamoto
First page: 1507
Abstract: We evaluated the detection efficiency and location accuracy of lightning discharges in Japan using Blitzortung.org, a volunteer-based network for locating lightning discharges from sferics measured by very low frequency (VLF) electromagnetic receivers that have been deployed worldwide in recent years. A comparison of the flash rate (the detected lightning rate per area and period) from Blitzortung.org with that from the satellite-based OTD/LIS and the ground-based World Wide Lightning Location Network (WWLLN) observations showed that Blitzortung.org clearly observed intense lightning activity in and around the Kanto area, including Tokyo, in summer, which is typical of Japanese lightning activity. However, it did not clearly observe lightning activity in and around the Nansei Islands, including Okinawa. Conversely, Blitzortung.org observed winter lightning activity in the Hokuriku area and off the Kanto. In addition, event studies have compared the detection efficiency and location accuracy of Blitzortung.org with those of the Japanese Lightning Location Network (JLDN) to infer their absolute values. The latest detection efficiency of Blitzortung.org in the Kanto area was estimated at roughly 90%. The mean location accuracy was estimated at up to 5.6 km.
Citation: Atmosphere
PubDate: 2023-09-29
DOI: 10.3390/atmos14101507
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1508: Forecast and Analysis of a Rainstorm Case
in East China Based on the Blown-Up Theory
Authors: Tao Song, Dongmei Xu, Feifei Shen, Aiqing Shu, Lixin Song
First page: 1508
Abstract: Practical application has shown that the blown-up theory has great predictive ability for predicting transitional weather systems, especially catastrophic weather systems. This study applies the blown-up theory to analyze and predict a rainstorm case in Jiangsu Province of East China to explore the applicability of the blown-up theory. At the same time, a numerical simulation experiment is conducted using the Weather Research and Forecasting Model (WRF) v4.2. The numerical results are compared with the European Center for Medium Weather Forecasting (ECMWF) Reanalysis v5 (ERA5) data and the China Meteorological Administration (CMA) Land Data Assimilation System (CLDAS) products. It is found that there is a deviation in the simulation for the precipitation center, and further analysis indicates that it is likely related to the position of the simulated low-level shear line. On the other hand, the blown-up analyses are consistent with the actual situation and provide additional information besides the numerical simulation results. These results indicate that the blown-up charts and V-3θ diagrams are able to predict the weather system transformation, the rainfall area, and the evolution of the rainstorm, which confirms the applicability of the blown-up theory to rainstorm forecasts. This provides an auxiliary analysis method in addition to numerical simulations for rainstorm forecasts.
Citation: Atmosphere
PubDate: 2023-09-29
DOI: 10.3390/atmos14101508
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1509: Optimization of Vibrating Mesh Nebulizer
Air Inlet Structure for Pulmonary Drug Delivery
Authors: Yu Liu, Xiaole Chen, Zhengqi Li, Huizhen Yang, Jianwei Wang
First page: 1509
Abstract: The vibrating mesh nebulizer (VMN) has gained popularity for its compactness and noiselessness. This study investigates the impact of different air inlet structures on the deposition fraction (DF) of droplets generated by VMNs in an idealized mouth–throat (MT) airway model. Three homemade VMNs with semi-circular inlet, symmetrical four-inlet, and multiple-orifice inlet structures were evaluated through simulations and experiments. The changes in droplet DF of 0.9% w/v concentration of nebulized sodium chloride (NaCl) droplets as a function of inertial parameters were acquired under different inhalation flow conditions. Additionally, flow field distributions in models with different inlet structures were analyzed at a steady inspiratory flow rate of 15 L/min. The results indicate that optimizing the VMN’s air inlet structure significantly enhances droplet delivery efficiency. The multiple–orifice inlet structure outperformed the other designs, directing the airflow from the inlet position to the center of the mouthpiece and then into the oral cavity, achieving a DF of up to 20% at an inhalation flow rate of 15 L/min. The region of high airflow velocity between the mouthpiece and oral cavity proved to be a favorable VMN inlet optimization, reducing direct droplet–wall collisions and improving delivery efficiency. These findings offer insights for VMN design and optimization to enhance pulmonary drug delivery effectiveness and therapeutic outcomes.
Citation: Atmosphere
PubDate: 2023-09-29
DOI: 10.3390/atmos14101509
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1510: Research Advances on Nitrogen-Doped
Carbon Materials in COx Hydrogenation
Authors: Chao Deng, Lujing Xu, Kehao Hu, Xixi Chen, Ruxing Gao, Leiyu Zhang, Lei Wang, Chundong Zhang
First page: 1510
Abstract: The excessive consumption of fossil fuels has resulted in massive carbon emissions and serious ecological and environmental crises. Therefore, achieving the efficient utilization of waste carbon sources is considered as an important pathway to addressing the aforementioned issues in the context of carbon neutrality. Developing and designing suitable catalyst materials has become the key to converting COx into valuable platform chemicals and value-added liquid fuels (e.g., CO, CH4, CH3OH, and C2+ hydrocarbons). A moderate interaction between nitrogen-doped carbon materials and active metals is more favorable for the progress of the COx hydrogenation reaction compared to traditional metal oxide carriers. In this work, we comprehensively summarize the synthesis methods of N-doped carbon materials and the relevant research progress in the field of COx hydrogenation. In addition, a general assessment of carbon-based catalysts for COx hydrogenation reactions, concerning the support and metal properties, the activity and product selectivity, and their interactions is systematically discussed. Finally, this review discusses the roles of N-doped carbon materials, the current challenges, and future development directions.
Citation: Atmosphere
PubDate: 2023-09-29
DOI: 10.3390/atmos14101510
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1511: On the Impact of ENSO Cycles and Climate
Change on Telescope Sites in Northern Chile
Authors: Julia Victoria Seidel, Angel Otarola, Valentina Théron
First page: 1511
Abstract: The Atacama desert stands as the most arid, non-polar, region on Earth and has accommodated a considerable portion of the world’s ground-based astronomical observatories for an extended period. The comprehension of factors important for observational conditions in this region, and the potential alterations induced by the escalating impact of climate change, are, therefore, of the utmost significance. In this study, we conduct an analysis of the surface-level air temperature, water vapour density, and astronomical seeing at the European Southern Observatory (commonly known by its acronym, ESO) telescope sites in northern Chile. Our findings reveal a discernible rise in temperature across all sites during the last decade. Moreover, we establish a correlation between the air temperature and water vapour density with the El Niño Southern Oscillation (ENSO) phases, wherein, the warm anomaly known as El Niño (EN) corresponds to drier observing conditions, coupled with higher maximum daily temperatures favouring more challenging near-infrared observations. The outcomes of this investigation have potential implications for the enhancement of the long-term scheduling of observations at telescope sites in northern Chile, thereby aiding in better planning and allocation of resources for the astronomy community.
Citation: Atmosphere
PubDate: 2023-09-29
DOI: 10.3390/atmos14101511
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1512: The Effect of Green Roofs and Green
Façades in the Pedestrian Thermal Comfort of a Mediterranean Urban
Residential Area
Authors: Areti Tseliou, Emmanouil Melas, Athina Mela, Ioannis Tsiros, Efthimios Zervas
First page: 1512
Abstract: The present study investigated the cooling effect of extensive green roofs and green façades, at the pedestrian level, of a Mediterranean densely populated neighborhood. The ENVI-met environmental model was employed to simulate the microclimatic environment on a typical summer day. Thermal conditions of the study area were evaluated based on air temperature and the Mediterranean thermal stress scale of UTCI (Universal Thermal Climate Index). Three mitigation strategies were developed to ameliorate the thermal conditions in the examined area focusing on the efficacy of green façades, green roofs, and the synergetic effect of the green façade and green roof. The mitigation strategies’ performance was evaluated in characteristic design layouts of the study area, namely the following: a typical Mediterranean square, a church with a churchyard, an avenue, NS and EW street orientations, and courtyards. Results showed that compared to the existing configuration, the synergetic effect of the green façade and green roof achieved the greatest amelioration of the thermal conditions during the hottest hours of the day (12:00–18:00) since it produced an average Tair reduction of up to 0.7 °C and a UTCI reduction of 1.6 °C (both in the courtyards design layout). Among the examined design layouts, the courtyards produced the greatest reductions in air temperature and UTCI, whereas the EW streets were the lowest.
Citation: Atmosphere
PubDate: 2023-09-29
DOI: 10.3390/atmos14101512
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1513: Enhancing Maritime Safety and Efficiency:
A Comprehensive Sea Fog Monitoring System for Ningbo Zhoushan Port
Authors: Lijun Hu, Rong Xu, Ming Yang, Hao Yang, Yun Lu, Chenru Li, Jinhong Xian, Risheng Yao, Weixuan Chen
First page: 1513
Abstract: Sea fog poses a considerable challenge to port operations, impacting maritime safety and efficiency. During the past five years, the average annual downtime of the navigation dispatch department in Ningbo Zhoushan Port due to weather was 800–1000 h, of which approximately 300 h can be attributed to sea fog. This study addresses the issue by developing a comprehensive sea fog monitoring system for Ningbo Zhoushan Port. The system utilizes automatic weather stations (AWS) and visibility laser imaging, detection, and ranging (LIDAR) to assess sea fog severity and improve monitoring accuracy. By increasing monitoring frequency and adopting corresponding warning measures, the system aims to enhance maritime safety and efficiency in Ningbo Zhoushan Port. The results showed that the implemented system successfully determines sea fog severity, enables real-time monitoring, and provides precise visibility assessments. Joint assessments revealed a substantial increase in the annual operating time and revenue of the port. These findings underscore the importance of advanced monitoring techniques in optimizing port operations, reducing collision risks, and mitigating economic losses caused by sea fog.
Citation: Atmosphere
PubDate: 2023-09-29
DOI: 10.3390/atmos14101513
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1514: Evaluating Drought Effects on Soil:
Innovative Soil Salinity Monitoring via SAR Data, Sentinel-2 Imagery, and
Machine Learning Algorithms in Kerkennah Archipelago
Authors: Sarra Hihi, Rim Katlane, Boubaker Kilani, Mohamed Waddah Zekri, Rafik Bensalah, Christian Siewert, Monem Kallel
First page: 1514
Abstract: The Kerkennah archipelago in Tunisia is one of the most vulnerable areas where the influence of climate change is undeniable. Soil salinization has emerged as a major consequence of climate variation on this island. In this study, remote sensing techniques were implemented to develop a model for predicting soil salinity from satellite images. Machine learning algorithms, Sentinel-1 and Sentinel-2 data, and ground truth measurements were used to estimate soil salinity. Several algorithms were considered to achieve accurate findings. These algorithms are categorized as polynomial regression, random forest regression, exponential regression, and linear regression. The results demonstrate that exponential regression is the pre-eminent algorithm for estimating soil salinity with high predictive accuracy of R2 = 0.75 and RMSE = 0.47 ds/m. However, spatiotemporal soil salinity maps reveal distinct and clear distribution patterns, highlighting salty areas (i.e., sebkhas) and agricultural parcels. Thus, through the model, we explore areas of moderately high salinity within agricultural lands that could be affected by irrigation practices. The present work demonstrates a reliable model for soil salinity monitoring in the Kerkennah archipelago and inspires more successful technologies such as remote sensing and machine learning to improve the estimation of soil salinity in climate-affected vulnerable areas.
Citation: Atmosphere
PubDate: 2023-09-29
DOI: 10.3390/atmos14101514
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1515: Industrial Emission Monitoring and
Assessment of Air Quality in Karachi Coastal City, Pakistan
Authors: Mohammad Idrees, Yasmin Nergis, Muhammad Irfan
First page: 1515
Abstract: Industrialization, anthropogenic activities, the exhaust of vehicles and exponential population growth have a significant impact on the outdoor air quality of megacities across the world. Karachi is one of the largest cities in Pakistan, South Asia. The dense population, rapid economic growth and unplanned industrial activities have improved the socioeconomic status but also deteriorated the air quality of Karachi. The severe increase in air pollution has become a threat to the local population in terms of their health issues, quality of life and environment. Therefore, it is essential to quantify and monitor the spatiotemporal variation in outdoor air quality parameters. The current study aims to monitor the air quality in four major industrial zones of Karachi for three years (2020–2022). The field data was collected during the periods of post-monsoon and pre-monsoon using the HAZ-SCANNER (HIM-6000) apparatus, which measured outdoor air pollutants such as carbon monoxide (CO), nitrogen oxides (NO2), sulfur dioxide (SO2) and particulate matter (PM10, PM2.5 and TSPM). The data from 24 stations was analyzed using statistical analysis tools to estimate the parameters and Arc GIS to map the spatial variation of each parameter. The result shows that the concentration of particulate matter (TSPM, PM2.5 and PM10), SO2, NO2 and CO values at sampling sites are moderate in the post-monsoon season as compared to the pre-monsoon season due to cyclical monsoon effects and exceed the environmental quality standards. It was also noted that the North Karachi industrial area is at lower risk due to the small-scale industry. The higher levels of air pollutants have numerous health implications and may cause chronic infections. The air pollutant has a severe impact on plant growth and soil. Therefore, it is important to implement local environmental standards regarding outdoor air pollutants to mitigate the adverse impact on human health and economic activities.
Citation: Atmosphere
PubDate: 2023-09-30
DOI: 10.3390/atmos14101515
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1516: A New ANN Technique for Short-Term Wind
Speed Prediction Based on SCADA System Data in Turkey
Authors: R. K. Reja, Ruhul Amin, Zinat Tasneem, Sarafat Hussain Abhi, Uzair Aslam Bhatti, Subrata Kumar Sarker, Qurat ul Ain, Yazeed Yasin Ghadi
First page: 1516
Abstract: The restored interest now receives renewable energy due to the global decline in greenhouse gas emanations and fossil fuel combustion. The fasted growing energy source, wind energy generation, is recognized as a clean energy source that has grown fast and is used extensively in wind power-producing facilities. This study’s short-term wind speed estimations are made using a multivariate model based on an artificial neural network (ANN) that combines several local measurements, including wind speed, wind direction, LV active power, and theoretical power curve. The dataset was received from Turkey’s SCADA system at 10-min intervals, and the actual data validated the expected performance. The research took wind speed into account as an input parameter and created a multivariate model. To perform prediction outcomes on time series data, an algorithm such as an artificial neural network (ANN) is utilized. The experiment verdicts reveal that the ANN algorithm produces reliable predicting results when metrics like 0.693 for MSE, 0.833 for RMSE and 0.96 for R- squared or Co-efficient of determination are considered.
Citation: Atmosphere
PubDate: 2023-09-30
DOI: 10.3390/atmos14101516
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1517: Prediction of PM2.5 Concentration Using
Spatiotemporal Data with Machine Learning Models
Authors: Xin Ma, Tengfei Chen, Rubing Ge, Fan Xv, Caocao Cui, Junpeng Li
First page: 1517
Abstract: Among the critical global crises curbing world development and sustainability, air quality degradation has been a long-lasting and increasingly urgent one and it has been sufficiently proven to pose severe threats to human health and social welfare. A higher level of model prediction accuracy can play a fundamental role in air quality assessment and enhancing human well-being. In this paper, four types of machine learning models—random forest model, ridge regression model, support vector machine model, extremely randomized trees model—were adopted to predict PM2.5 concentration in ten cities in the Jing-Jin-Ji region of north China based on multi-sources spatiotemporal data including air quality and meteorological data in time series. Data were fed into the model by using the rolling prediction method which is proven to improve prediction accuracy in our experiments. Lastly, the comparative experiments show that at the city level, RF and ExtraTrees models have better predictive results with lower mean absolute error (MAE), root mean square error (RMSE), and higher index of agreement (IA) compared to other selected models. For seasonality, level four models all have the best prediction performances in winter time and the worst in summer time, and RF models have the best prediction performance with the IA ranging from 0.93 to 0.98 with an MAE of 5.91 to 11.68 μg/m3. Consequently, the demonstration of how each model performs differently in each city and each season is expected to shed light on environmental policy implications.
Citation: Atmosphere
PubDate: 2023-09-30
DOI: 10.3390/atmos14101517
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1518: Carbon Emission Model and Emission
Reduction Technology in the Asphalt Mixture Mixing Process
Authors: Nieyangzi Liu, Yuanqing Wang, Haitao Yang
First page: 1518
Abstract: This paper attempts to develop a calculation model to estimate the carbon dioxide (CO2) emissions during the mixing process of asphalt mixtures and explore energy-saving and emission reduction technologies. Based on a comprehensive analysis of the mixer’s working mechanism, mixing quality requirement, and theoretical deductions, a CO2 emission model for the mixing process of asphalt mixtures is established. The model highlights the significant impact of mixing time on both mixing quality and carbon emissions. The model demonstrates that the mixing quality improves with an increase in mixing time, but the degree of improvement diminishes after an initial significant enhancement, eventually stabilizing. Importantly, excessive mixing time does not significantly improve the mixing quality; conversely, an extended mixing time has a notable impact on carbon emissions. Results show that when the deviation of the asphalt content is changed from 0.3% to 0.2% for a 5% asphalt content mixture, the mixing time and resulting CO2 emissions increase by 14%; similarly, when the deviation is 0.1%, the mixing time and resulting CO2 emissions increase by nearly 40%. Additionally, the agitator’s capacity also significantly influences the CO2 emissions. For a project of a given scale, increasing the agitator capacity leads to a reduction in total carbon emissions during the mixing process. Compared to a type 1500 agitator, employing agitators of types 3000, 4000, and 5000 can achieve reductions in total CO2 emissions by 26.3%, 32.9%, and 36.8%, respectively. Therefore, for large-scale engineering projects aiming to minimize CO2 emissions during the mixing process, it is essential to determine the optimal mixing time to avoid excessive mixing and select a larger capacity agitator, preferably type 4000 or higher. These findings could support the development of effective emission reduction measures in the field of road construction, thereby contributing to the achievement of emission reduction targets and promoting the advancement of sustainable road development.
Citation: Atmosphere
PubDate: 2023-09-30
DOI: 10.3390/atmos14101518
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1519: Characteristic Variation of Particulate
Matter-Bound Polycyclic Aromatic Hydrocarbons (PAHs) during Asian Dust
Events, Based on Observations at a Japanese Background Site, Wajima, from
2010 to 2021
Authors: Pengchu Bai, Yan Wang, Hao Zhang, Xuan Zhang, Lulu Zhang, Atsushi Matsuki, Seiya Nagao, Bin Chen, Ning Tang
First page: 1519
Abstract: Asian dust (AD) events and total suspended particles (TSPs) were observed at the Kanazawa University Wajima Air Monitoring Station (KUWAMS), a Japanese background site, during the East Asian winter monsoon periods (from November to May of the following year) from 2010 to 2021. Nine kinds of polycyclic aromatic hydrocarbons (PAHs) were determined in each TSP sample. In this study, a total of 54 AD events were observed. According to the different pathways of long-range transportation, AD events were divided into AD-high events (transported at higher altitudes, approximately 4000 m) and AD-low events (transported at lower altitudes, approximately 2500 m). The TSP concentrations increased sharply in the AD events and were higher in the AD-high events (39.8 ± 19.5 μg/m3) than in the AD-low events (23.5 ± 10.5 μg/m3). AD did not have a significant effect on the ΣPAHs characteristic variation, as ΣPAHs (ΣPAHs = fluoranthene, pyrene, benz[a]anthracene, chrysene, benzo[b]fluoranthene, benzo[k]fluoranthene, benzo[a]pyrene, benzo[ghi]perylene, and indeno [1,2,3-cd]pyrene) concentrations in non-AD periods, AD-high events, and AD-low events were 543 ± 374, 404 ± 221, and 436 ± 265 pg/m3, respectively. The PAH compositions were also consistent. As a result, the TSP concentration was affected by the input air mass transported at higher altitudes from the desert region while the PAH concentration was impacted by the air mass at lower altitudes, which carried the PAHs emitted from fossil fuels and biomass combustion in northeastern China. Moreover, the health risks of PAHs were calculated with the inhalation lifetime cancer risk, which ranged from 10−6 to 10−5 ng/m3, indicating a potential carcinogenic risk at the KUWAMS during the East Asian winter monsoon periods.
Citation: Atmosphere
PubDate: 2023-09-30
DOI: 10.3390/atmos14101519
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1520: Indoor Air Purifiers in the Fight against
Airborne Pathogens: The Advantage of Circumferential Outflow Diffusers
Authors: Yevgen Nazarenko, Chitra Narayanan, Parisa A. Ariya
First page: 1520
Abstract: Airborne particles containing pathogens such as bacteria (e.g., M. tuberculosis) or virions (e.g., influenza or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)) can cause infections. It has been speculated that the outflow from indoor air purifiers with a directional outlet could entrain and spread pathogen-containing aerosol particles. To date, only the case of indoor air purifiers with a directional outflow has been considered, and here we investigate an indoor air purifier with a circumferential outflow diffuser—an alternative design solution that is already commercially available. We measured the airflow velocity at two different angles to the surface of the circumferential outflow diffuser and two blower speeds. We visualized in scattered light the deflection of a vertical mist spray cone from a sneeze-simulating nebulizer parallel to the side of the air purifier. We found a significant difference in airflow velocities for different angles to the circumferential outflow diffuser: 0.01–0.02 m/s for 0° vs. 0.01–0.65 m/s for 45° at 1 m distance. We observed no significant deflection of the sneeze-simulating spray cone at the minimum blower speed and a 5 cm deflection at the maximum speed. The deflection of the sneeze-simulating spray mist particles by the tested indoor air purifier with the circumferential outflow, under the experimental conditions, is low relative to the recommended safer distances between people in indoor spaces. We conclude that indoor air purifiers with circumferential outflow diffusers have a lower potential to spread infectious aerosols in indoor spaces compared to devices with unidirectional outflow.
Citation: Atmosphere
PubDate: 2023-09-30
DOI: 10.3390/atmos14101520
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1521: Diurnal Cycle of Tropospheric Winds over
West Sumatra and Its Variability Associated with Various Climate and
Weather Modes
Authors: Wojciech Ryszard Szkolka, Dariusz Bartłomiej Baranowski, Maria K. Flatau, Marzuki Marzuki, Toyoshi Shimomai, Hiroyuki Hashiguchi
First page: 1521
Abstract: The typical diurnal variability of tropospheric winds over West Sumatra and their changes associated with El Niño Southern Oscillation, Quasi-Biennial Oscillation, Madden–Julian Oscillations and convectively coupled Kelvin waves during the extended boreal winter season are investigated based on nineteen years of observations from Equatorial Atmosphere Radar in Kototabang, Indonesia. Sub-diurnal wind variability is assessed based on the amplitude and phase of the diurnal (24 h) and semidiurnal (12 h) modes.The results show that composite diurnal variability is dominated by cloud-induced circulation and thermal tides. Although these sub-diurnal modes do not change the daily mean wind direction, they modulate velocities throughout the day. Typical diurnal evolution of the vertical wind component is consistent with changes in the latent heating profiles associated with the evolution of a cloud field from cumulus before noon to deep convection in the afternoon and stratiform clouds in the evening. El Niño Southern Oscillation and Quasi-Biennial Oscillation affect the mean tropospheric winds, throughout the troposphere and above 250 hPa, respectively, but do not affect sub-diurnal amplitudes. Eastward propagating Madden–Julian Oscillations and convectively coupled Kelvin waves impact both the mean and sub-diurnal tropospheric wind variability. Both horizontal and vertical winds show the largest variability in the lower and mid troposphere (below 400 hPa). The observed variability in the vertical wind component highlights that large-scale phenomena interact with both the local evolution and progression of a cloud field through dynamical feedback.
Citation: Atmosphere
PubDate: 2023-09-30
DOI: 10.3390/atmos14101521
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1522: Study on Spatial and Temporal
Distribution Characteristics of the Cooking Oil Fume Particulate and
Carbon Dioxide Based on CFD and Experimental Analyses
Authors: Minting Ding, Shunyu Zhang, Jiahua Wang, Feng Ye, Zhenlei Chen
First page: 1522
Abstract: The cooking oil fume particulate (COFP) produced by indoor cooking can harm human health seriously, and therefore requires urgent monitoring and optimization. In this paper, the kitchen cooking simulation process was established by using computational fluid dynamics (CFD) based on the fluid dynamics theory. Combined with the user defined function (UDF), the spatial and temporal distributions of COFP and carbon dioxide (CO2) during the cooking process were simulated and analyzed, respectively. Both simulation results were verified using experimental data. Moreover, this paper introduces a COFP concentration correlation function that utilizes the spatiotemporal correlation between COFP and CO2 concentrations during the cooking process. The function is based on the spatiotemporal distribution of CO2 concentration. By comparing it with traditional calculations, the proposed function is shown to achieve a remarkable 70% improvement in efficiency and maintain an accuracy rate exceeding 90%. This enables the rapid analysis and control of COFP concentration through monitoring and analyzing CO2 levels in the kitchen.
Citation: Atmosphere
PubDate: 2023-09-30
DOI: 10.3390/atmos14101522
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1523: Mean Flow from Phase Averages in the 2D
Boussinesq Equations
Authors: Beth A. Wingate, Juliane Rosemeier, Terry Haut
First page: 1523
Abstract: The atmosphere and ocean are described by highly oscillatory PDEs that challenge both our understanding of their dynamics and their numerical approximation. This paper presents a preliminary numerical study of one type of phase averaging applied to mean flows in the 2D Boussinesq equations that also has application to numerical methods. The phase averaging technique, well-known in dynamical systems theory, relies on a mapping using the exponential operator, and then an averaging over the phase. The exponential operator has connections to the Craya–Herring basis pioneered by Jack Herring to study the fluid dynamics of oscillatory, nonlinear fluid dynamics. In this paper, we perform numerical experiments to study the effect of this averaging technique on the time evolution of the solution. We explore its potential as a definition for mean flows. We also show that, as expected from theory, the phase-averaging method can reduce the magnitude of the time rate of change in the PDEs, making them potentially suitable for time stepping methods.
Citation: Atmosphere
PubDate: 2023-09-30
DOI: 10.3390/atmos14101523
Issue No: Vol. 14, No. 10 (2023)
- Atmosphere, Vol. 14, Pages 1524: Study on the Optical–Physical
Properties of Aerosol Layers in Africa Based on a Laser Satellite
Authors: Miao Zhang, Pengyu Mu, Xin Chen, Di Wu, Fengxian Lu, Pengcheng Qi, B. Larry Li, Wei Gong
First page: 1524
Abstract: Atmospheric aerosols have important effects on the environment and human health. In this study, we analyzed the atmospheric aerosol layers’ optical and physical properties over Africa utilizing CALIPSO level 2 products from 2007 to 2019. Interannual and seasonal variations in aerosol optical parameters were studied: the lowest aerosol layer (AODL), the base height of the lowest aerosol layer (BL), the top height of the lowest aerosol layer (HL), the top height of the highest aerosol layer (HH), the volumetric depolarization ratio of the lowest aerosol layer (DRL), the color ratio of the lowest aerosol layer (CRL), the total AOD of all aerosol layers (AODT), the number of aerosol feature layers (N), the thickness of the lowest aerosol layer (TL), and the AOD proportion of the lowest aerosol layer (PAODL). The annual mean AODT was slightly higher in southern Africa than in northern Africa. HL and HH had strongly positive correlations with landform elevations. However, HL and HH were greater in northern Africa than in southern Africa from March to August. The reason could be that northern Africa is dominated by deserts with high temperatures and intense atmospheric vertical convections leading to dust layers existing in the upper air. PAODL values were lower in northern Africa (daytime: 71%; nighttime: 61%) than in southern Africa (daytime: 78%; nighttime: 69%), revealing that aerosol stratifications were more frequent in northern Africa than in southern Africa. DRL values were higher in northern Africa (daytime: 0.16; nighttime: 0.11) than in southern Africa (daytime: 0.07; nighttime: 0.05) indicating the predominance of non-spherical dust particles in northern Africa. This work can provide an important understanding of regional aerosol layers’ optical and physical properties to scientists and local environmental protection agencies.
Citation: Atmosphere
PubDate: 2023-09-30
DOI: 10.3390/atmos14101524
Issue No: Vol. 14, No. 10 (2023)
|
Open Access journal
