 Subjects -> METEOROLOGY (Total: 106 journals)
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- Atmosphere, Vol. 14, Pages 1380: South American Monsoon Lifecycle
Projected by Statistical Downscaling with CMIP6-GCMs
Authors: Michelle Simões Reboita, Glauber Willian de Souza Ferreira, João Gabriel Martins Ribeiro, Rosmeri Porfírio da da Rocha, Vadlamudi Brahmananda Rao
First page: 1380
Abstract: This study analyzed the main features (onset, demise, and length) of the South American Monsoon System (SAMS) projected in different time slices (2020–2039, 2040–2059, 2060–2079, and 2080–2099) and climate scenarios (SSP2–4.5 and SSP5–8.5). Eight global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) that perform well in representing South America’s historical climate (1995–2014) were initially selected. Thus, the bias correction–statistical downscaling (BCSD) technique, using quantile delta mapping (QDM), was applied in each model to obtain higher-resolution projections than their original grid. The horizontal resolution adopted was 0.5° of latitude × longitude, the same as the Climate Prediction Center precipitation analysis used as a reference dataset in BCSD. The QDM technique improved the monsoon onset west of 60° W and the simulated demise and length in southwestern Amazonia. Raw and BCSD ensembles project an onset delay of approximately three pentads compared to the historical period over almost all regions and a demise delay of two pentads northward 20° S. Additionally, the BCSD ensemble projects a reduced length with statistical significance in most South Atlantic Convergence Zone regions and a delay of three pentads in the demise over the Brazilian Amazon from the second half of the 21st century.
Citation: Atmosphere
PubDate: 2023-08-31
DOI: 10.3390/atmos14091380
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1382: Evaluation of an Automatic Meteorological
Drone Based on a 6-Month Measurement Campaign
Authors: Maxime Hervo, Gonzague Romanens, Giovanni Martucci, Tanja Weusthoff, Alexander Haefele
First page: 1382
Abstract: From December 2021 to May 2022, MeteoSwiss and Meteomatics conducted a proof of concept to demonstrate the capability of automatic drones to provide data of sufficient quality and reliability on a routine operational basis. Over 6 months, Meteodrones MM-670 were operated automatically eight times per night at Payerne, Switzerland. In total, 864 meteorological profiles were measured and compared to co-located standard measurements, including radiosoundings and remote sensing instruments. To our knowledge, this is the first time that Meteodrone’s atmospheric profiles have been evaluated in such an extensive campaign. The paper highlights two case studies that showcase the performance and challenges of measuring temperature, humidity, and wind with a Meteodrone. It also focuses on the overall quality of the drone measurements. Throughout the campaign, the availability of Meteodrone measurements was 75.7%, with 82.2% of the flights reaching the nominal altitude of 2000 m above sea level. The quality of the measurements was assessed against the WMO’s (World Meteorological Organization) requirements. The temperature measurements gathered by the Meteodrone met the “breakthrough” target, while the humidity and wind profiles met the “threshold” target for high-resolution numerical weather prediction. The temperature measurement quality was comparable to that of a microwave radiometer, and the humidity quality was similar to that obtained from a Raman LiDAR. However, the wind measurements gathered by a Doppler LiDAR were more accurate than the estimation provided by the Meteodrone. This campaign marks a significant step towards the operational use of automatic drones for meteorological applications.
Citation: Atmosphere
PubDate: 2023-08-31
DOI: 10.3390/atmos14091382
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1383: The Influence of Meteorology
Initialization on Ozone Forecasting in the Great Lakes Region during MOOSE
Study
Authors: Rabab Mashayekhi, Craig A. Stroud, Junhua Zhang, Oumarou Nikiema, Sandrine Trotechaud
First page: 1383
Abstract: This study investigates the influence of meteorology initialization on surface ozone prediction in the Great Lakes region using Canada’s operational air quality model (GEM-MACH) at a 2.5 km horizontal resolution. Two different initialization techniques are compared, and it is found that the four-dimensional incremental analysis updating (IAU) method yields improved model performance for surface ozone prediction. The IAU run shows better ozone regression line statistics (y = 0.7x + 14.9, R2 = 0.2) compared to the non-IAU run (y = 0.6x + 23.1, R2 = 0.1), with improved MB and NMB values (3.9 ppb and 8.9%, respectively) compared to the non-IAU run (4.1 ppb and 9.3%). Furthermore, analyzing ozone prediction sensitivity to model initialization time reveals that the 18z initialization leads to enhanced performance, particularly during high ozone exceedance days, with an improved regression slope of 0.9 compared to 0.7 for the 00z and 12z runs. The MB also improves to −0.2 ppb in the 18z run compared to −2.8 ppb and −3.9 ppb for the 00z and 12z runs, respectively. The analysis of meteorological fields reveals that the improved ozone predictions at 18z are linked to a more accurate representation of afternoon wind speed. This improvement enhances the transport of ozone, contributing to the overall improvement in ozone predictions.
Citation: Atmosphere
PubDate: 2023-09-01
DOI: 10.3390/atmos14091383
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1384: The Robustness of the Derived Design Life
Levels of Heavy Precipitation Events in the Pre-Alpine Oberland Region of
Southern Germany
Authors: Patrick Laux, Elena Weber, David Feldmann, Harald Kunstmann
First page: 1384
Abstract: Extreme value analysis (EVA) is well-established to derive hydrometeorological design values for infrastructures that have to withstand extreme events. Since there is concern about increased extremes with higher hazard potential under climate change, alterations of EVA are introduced for which statistical properties are no longer assumed to be constant but vary over time. In this study, both stationary and non-stationary EVA models are used to derive design life levels (DLLs) of daily precipitation in the pre-alpine Oberland region of Southern Germany, an orographically complex region characterized by heavy precipitation events and climate change. As EVA is fraught with uncertainties, it is crucial to quantify its methodological impacts: two theoretical distributions (i.e., Generalized Extreme Value (GEV) and Generalized Pareto (GP) distribution), four different parameter estimation techniques (i.e., Maximum Likelihood Estimation (MLE), L-moments, Generalized Maximum Likelihood Estimation (GMLE), and Bayesian estimation method) are evaluated and compared. The study reveals large methodological uncertainties. Discrepancies due to the parameter estimation methods may reach up to 45% of the mean absolute value, while differences between stationary and non-stationary models are of the same magnitude (differences in DLLs up to 40%). For the end of this century in the Oberland region, there is no robust tendency towards increased extremes found.
Citation: Atmosphere
PubDate: 2023-09-01
DOI: 10.3390/atmos14091384
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1385: Modelling of Deep Street Canyon Air
Pollution Chemistry and Transport: A Wintertime Naples Case Study
Authors: Yuqing Dai, Andrea Mazzeo, Jian Zhong, Xiaoming Cai, Benedetto Mele, Domenico Toscano, Fabio Murena, A. Rob MacKenzie
First page: 1385
Abstract: The impact of urban morphology on air quality, particularly within deep canyons with longer residence times for complex chemical processes, remains insufficiently addressed. A flexible multi-box framework was used to simulate air quality at different canyon heights (3 m and 12 m). This approach incorporated essential parameters, including ventilation rates, background concentrations, photochemical schemes, and reaction coefficients. A field campaign within a deep canyon with an aspect ratio of 3.7, in Naples, Italy was conducted and used for the model evaluation. The model performance demonstrated good agreement, especially at the street level, when employing a realistic light intensity profile and incorporating volatile organic compound (VOC) chemistry. Our findings indicate that peroxyl radical production affects NO2 and O3 levels by up to 9.5% in deep canyons and underscore the significance of vertical distribution (approximately 5% variance) in health assessments and urban air quality strategy development. The model response was sensitive to changes in emissions as expected, but also, somewhat more surprisingly, to background conditions, emphasizing that policies to remove pollution hotspots must include local and broader citywide action. This work advances the understanding of air quality dynamics in deep urban canyons and presents a valuable tool for effective air quality management in intricate urban environments.
Citation: Atmosphere
PubDate: 2023-09-01
DOI: 10.3390/atmos14091385
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1386: Ionospheric Variations Induced by
Thunderstorms in the Central Region of Argentina during the
RELAMPAGO–CACTI Campaign
Authors: Constanza Inés Villagrán Asiares, María Gabriela Nicora, Amalia Meza, María Paula Natali, Eldo Edgardo Ávila, Marcos Rubinstein, Farhad Rachidi
First page: 1386
Abstract: The ionosphere can be perturbed by solar and geomagnetic activity, earthquakes, thunderstorms, etc. In particular, electromagnetic pulses produced by thunderstorms can generate wave structures in the ionospheric plasma, which are known as atmospheric gravity waves (AGWs), which can be detected by measuring the total electron content (TEC). We studied ionospheric variations resulting from thunderstorms on 10 November 2018, between 00:00 and 08:00 UTC, in the central region of Argentina, site of the RELAMPAGO–CACTI Project (Remote sensing of Electrification, Lightning, and Mesoscale/Microscale Processes with Adaptive Ground Observations; Clouds, Aerosols, and Complex Terrain Interactions). Atmospheric electrical activity data were provided by the Earth Networks Total Lightning Network (ENTLN) and the TEC was computed from Global Navigation Satellite System (GNSS) measurements provided by the Argentinian Continuous Satellite Monitoring Network (RAMSAC by its Spanish acronym). We found AGWs with periods less than or equal to 100 min and peak-to-peak Differential Vertical Total Electron Content (DVTEC) amplitude values up to 1.35 TECU (1 total electron content unit =1016 electrons/m2). We observed that AGWs show the highest peak-to-peak amplitudes during intense thunderstorm periods. On a day without thunderstorms, the peak-to-peak amplitudes were approximately 2.91 times lower.
Citation: Atmosphere
PubDate: 2023-09-01
DOI: 10.3390/atmos14091386
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1387: Comparative Analysis of Ozone Pollution
Characteristics between Urban Area and Southern Mountainous Area of
Urumqi, China
Authors: Cuiyun Zhu, Qing He, Zhujun Zhao, Xinchun Liu, Zongchao Pu
First page: 1387
Abstract: The difference in ozone (O3) concentration between stations in the urban and southern mountainous areas of Urumqi was explored based on mathematical statistics and comparative analysis of pollutant concentrations. Besides, potential source contribution function (PSCF) analysis and concentration weighted trajectory (CWT) analysis were performed to identify the potential sources of PM2.5 and O3. The results showed that the daily and monthly mean O3 concentrations in the urban area of Urumqi showed a bimodal variation from October 2017 to August 2018, and the O3 concentration had obvious seasonal characteristics, with the highest in July (120.57 μg/m3) and the lowest in January (22.38 μg/m3). The overall variation of O3 concentration in the mountainous area in the southern suburb of Urumqi was not significant (56.69–84.06 μg/m3), and the O3 concentration was slightly higher in summer than in other seasons. The daily O3 concentration in the urban area showed a unimodal variation in all seasons, and the daily variation was the smallest in winter and the largest in summer. However, the daily variation in the mountainous area was not significant. The O3 concentration in the urban area showed a significant negative weekend effect in winter and a positive weekend effect in spring and summer. However, the O3 concentration only showed a significant positive weekend effect in the mountainous area in summer. The PSCF and CWT analysis results of urban O3 concentration showed that Urumqi, Shihezi, and Wusu were the main O3 source areas. In addition, some areas bordering Kazakhstan in Xinjiang, China were also important source areas.
Citation: Atmosphere
PubDate: 2023-09-01
DOI: 10.3390/atmos14091387
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1388: Evaluation of Extreme Hydroclimatic
Trends in River Basins Located in the Northeast and South Regions of
Brazil
Authors: Priscila Esposte Esposte Coutinho, Marcio Cataldi
First page: 1388
Abstract: Brazil has a large availability of natural resources, and its economy was historically built around their exploitation. Changes in climate trends are already causing several environmental impacts, which affect the economic and social organization of the country. Impacts linked to the hydrological cycle are particularly concerning since water resources are used for electricity production, representing approximately 65% of the Brazilian electricity matrix. This study, therefore, aims to evaluate the extreme hydroclimatic trends of river basins located in the Northeast and South regions of the country. For this purpose, we carried out a flow analysis from 2020 to 2100, considering the precipitation data from the BCC CSM1-1, CCSM4, MIROC5, and NorESM1-M models presented in the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC). We used the SMAP rainfall-runoff model to obtain future flow projections for the RCP4.5 and RCP8.5 scenarios. As a result, we observed a trend toward water loss and the intensification of extreme events, with an increase in variability in both scenarios. We also noted that these climate models have difficulty reproducing the natural variability of southern basins, as parameterization of small-scale atmospheric processes prevents them from correctly projecting the precipitation.
Citation: Atmosphere
PubDate: 2023-09-02
DOI: 10.3390/atmos14091388
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1389: Examining the Effects of Tree Canopy
Coverage on Human Thermal Comfort and Heat Dynamics in Courtyards: A Case
Study in Hot-Humid Regions
Authors: Chang Lin, Jiahao Yang, Jun Huang, Ruize Zhong
First page: 1389
Abstract: Providing thermal comfort in the courtyards of academic buildings is important and increasing tree canopy coverage (TCC) presents a convenient and feasible method to achieve this; however, few studies have comprehensively evaluated the cooling effects of TCC, considering both outdoor thermal comfort and heat dynamics. In this study, we selected two typical academic buildings at Guangzhou University, each with courtyards having different height-to-width ratios (H/W ratios). We employed both field measurements and ENVI-met-based numerical models to simulate scenarios with varying TCCs. The results demonstrated that the cooling effects caused by arranging trees increase with the TCC values. During the hottest hours of the day, trees arranged in courtyards with high H/W ratios exhibited a superior cooling effect compared to those in courtyards with low H/W ratios, with a difference of up to 0.6 °C in the PET (physiological equivalent temperature); however, over the entire daytime, the total sensible heat reduction achieved by trees in courtyards with low H/W ratios surpassed that of courtyards with high H/W ratios, with a difference of up to 0.25 × 104 J/m2. Our findings underscore the crucial role of TCC in enhancing cooling in the courtyard of academic buildings, with important implications for university planning and design.
Citation: Atmosphere
PubDate: 2023-09-02
DOI: 10.3390/atmos14091389
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1390: Demographic Evaluation and Parametric
Assessment of Air Pollutants over Delhi NCR
Authors: Abul Amir Khan, Kalpana Garsa, Prakhar Jindal, Panuganti C. S. Devara, Shubhansh Tiwari, P. B. Sharma
First page: 1390
Abstract: The impact of air pollution on people and the environment is a severe issue that has recently been the subject of extensive research. This study has looked at the factors that contribute to the seasonal and spatial variability of pollutant concentration over Delhi NCR from 2019 to 2021. Additionally, the causes of changes in air quality during the COVID-19’s lockdown period in 2020 have been discussed, along with comparisons to the pre-lockdown year (2019) and the post-lockdown year (2021). Seven pollutant parameters, viz., (PM2.5, PM10, NOx, CO, SO2, NH3, and O3) were retrieved from the air quality monitoring stations spread over Delhi NCR. The results show a significant temporal (seasonal) and spatial variability in the air pollutants' concentration. The highest pollutant level was observed in winter and the lowest in summer seasons. The results suggest that the concentration of atmospheric pollutants was already lower (20–30%) before the implementation of the lockdown. Meteorology played an important role in emission reduction during the lockdown, in particular, and seasonal, in general. The results also suggest that Bhiwadi is not the most polluted city, as claimed in the World Air Quality Report 2022. The most polluted sites in terms of pollutant concentration were observed over Delhi in all the years considered.
Citation: Atmosphere
PubDate: 2023-09-02
DOI: 10.3390/atmos14091390
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1391: Experimental and Numerical Investigation
on the Damage Mechanism of a Loess–Mudstone Tunnel in Cold Regions
Authors: Dongrui Wang, Xueyi Zhao, Chenghu Qiu, Xin Guo, Yaohui Du, Xianhan Li, Yue Gao, Junjie Xuan
First page: 1391
Abstract: To address loess–mudstone tunnel damage resulting from mudstone swelling induced by water absorption in cold regions, model experiments and numerical simulations were employed to study the tunnel surrounding rock pressure distribution and the stress characteristics of support structures during mudstone swelling at the tunnel base. The findings reveal that the base uplift of the tunnel leads to a rapid stress increase on the arch, and the self-supporting of the interface is insufficient, causing uneven stress distribution on the tunnel. The stress peak value at the bottom of the outer arch is 30.8% of that at the inner side. The internal force of the tunnel lining at the arch crown is the largest. The compressive stress appears at the arch feet, while the tensile stress appears at the outer side of the lining. The bending moments of the inverted arch are larger than those of the arch shoulders and arch crown. The left arch shoulder and arch bottom are primarily subjected to negative bending moments, and the maximum values are about −500 kN·m and −400 kN·m, respectively. The left side of the inverted arch is first to crack, and two main cracks then appeared at the left and right arch shoulders, respectively. The formation and development of the longitudinal cracks in the arch induced by water absorption cause the inverted arch bulge failure. This study helps understand the damage mechanism of the loess–mudstone tunnel in cold regions.
Citation: Atmosphere
PubDate: 2023-09-03
DOI: 10.3390/atmos14091391
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1392: Application of CNN-LSTM Algorithm for
PM2.5 Concentration Forecasting in the Beijing-Tianjin-Hebei Metropolitan
Area
Authors: Yuxuan Su, Junyu Li, Lilong Liu, Xi Guo, Liangke Huang, Mingyun Hu
First page: 1392
Abstract: Prolonged exposure to high concentrations of suspended particulate matter (SPM), especially aerodynamic fine particulate matter that is ≤2.5 μm in diameter (PM2.5), can cause serious harm to human health and life via the induction of respiratory diseases and lung cancer. Therefore, accurate prediction of PM2.5 concentrations is important for human health management and governmental environmental management decisions. However, the time-series processing of PM2.5 concentration based only on a single region and a special time period is less explanatory, and thus, the spatial-temporal applicability of the model is more restricted. To address this problem, this paper constructs a PM2.5 concentration prediction optimization model based on Convolutional Neural Networks-Long Short-Term Memory (CNN-LSTM). Hourly data of atmospheric pollutants, meteorological parameters, and Precipitable Water Vapor (PWV) of 10 cities in the Beijing-Tianjin-Hebei metropolitan area during the period of 1–30 September 2021/2022 were used as the training set, and the PM2.5 data of 1–7 October 2021/2022 were used for validation. The experimental results show that the CNN-LSTM model optimizes the average root mean square error (RMSE) by 25.52% and 14.30%, the average mean absolute error (MAE) by 26.23% and 15.01%, and the average mean absolute percentage error (MAPE) by 35.64% and 16.98%, as compared to the widely used Back Propagation Neural Network (BPNN) and Long Short-Term Memory (LSTM) models. In summary, the CNN-LSTM model is superior in terms of applicability and has the highest prediction accuracy in the Beijing-Tianjin-Hebei metropolitan area. The results of this study can provide a reference for the relevant departments in the Beijing-Tianjin-Hebei metropolitan area to predict PM2.5 concentration and its trend in specific time periods.
Citation: Atmosphere
PubDate: 2023-09-03
DOI: 10.3390/atmos14091392
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1393: Examining Work Stress and Air Pollutants
Exposure of Home Healthcare Workers
Authors: Thomas Gerding, Jun Wang, Nicholas Newman
First page: 1393
Abstract: Occupational exposures in on-campus healthcare settings have increasingly been investigated, while the sector of home healthcare typically receives less focus. This study explored work stress exposure and air pollution’s effects on home healthcare workers through the collection of multiple salivary cortisol samples per day, the completion of stress diaries, and the use of low-cost personal air monitors. This study was designed to identify the physiological responses to various types of stress, as well as the impact of air pollution on the home healthcare workforce. Due to the sample size and duration, the data showed that neither the stress levels recorded in the diaries (p = 0.754), nor the air pollution data (with only VOC and PM1 having Pearson correlation coefficients of >0.25), exhibited a significant association with the cortisol levels. The air sensor data were inconsistent with previously published indoor air pollutant literature. Forty percent of events reported by participants were identified as high stressor (level 6–10) events. One participant in this study accounted for 18% of these high-stress events. The most common emotional responses to these stressor events included feelings of frustration, irritation, anger, and fury, which together comprised 22.4% of the reactions. Future work should include studies with a larger sample size, a more robust air quality monitor, and a longer study duration to improve the power to detect potential associations. Although previous studies have indicated that home healthcare workers experience workplace stress and exposure to multiple air pollutants, this study did not detect a consistent relationship between these exposures and the physiological stress response.
Citation: Atmosphere
PubDate: 2023-09-03
DOI: 10.3390/atmos14091393
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1394: Patterns and Influencing Factors of Air
Pollution at a Southeast Chinese City
Authors: Xiangjing Gao, Le Jian, Yun Zhao, Meibian Zhang, Qing Chen, Hua Zou, Mingluan Xing
First page: 1394
Abstract: Ambient air pollution is a pressing global environmental problem. To identify the source of air pollution and manage air quality in urban areas, the patterns of air pollutants under different traffic conditions and the impact of weather on air quality were explored in Hangzhou, China, a city experiencing rapid growth in vehicles. Data for particulate matters (PM10, PM2.5, PM1.0, and UFP), gaseous pollutants (CO, SO2, O3, and NO), and weather parameters (temperature, relative humidity, wind speed, and air pressure) were collected at two venues with different traffic conditions. An exploratory factor analysis was employed to identify the main factors contributing to air quality. The results showed that PMs, particularly PM1.0 and UFP, significantly contributed to air quality in monitoring venues, especially at Venue 2. As the leading factor, PMs contributed 40.85%, while gaseous pollutants and traffic (particularly fuel type) contributed 30.46% to air quality. The traffic was an independent contributor at Venue 2. Temperature and wind speed had negative influences on air pollutants. The outcomes of the study suggest that exhaust emissions from vehicles, particularly PM1.0 and UFP from heavy-duty vehicles, contributed significantly to ambient air quality. The contribution of meteorological factors to air quality varied at different venues and should not be ignored.
Citation: Atmosphere
PubDate: 2023-09-03
DOI: 10.3390/atmos14091394
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1395: Spatial Inhomogeneity of New Particle
Formation in the Urban and Mountainous Atmospheres of the North China
Plain during the 2022 Winter Olympics
Authors: Dongjie Shang, Min Hu, Xiaoyan Wang, Lizi Tang, Petri S. Clusius, Yanting Qiu, Xuena Yu, Zheng Chen, Zirui Zhang, Jiaqi Sun, Xu Dao, Limin Zeng, Song Guo, Zhijun Wu, Michael Boy
First page: 1395
Abstract: The new particle formation (NPF) process is a significant source of atmospheric secondary particles, which has remarkable impacts on the regional air quality and global radiative forcing. Most NPF studies conduct their measurements at a single site, which can hardly provide information about the regionality of NPF events at large scales (>100 km). During the 2022 Winter Olympic and Paralympic Games, simultaneous measurements of particle number size distributions and NPF-associated precursors were conducted at a mountainous site close to the Winter Olympic Village in Chongli (CL), Zhangjiakou, and an urban site in Beijing (BJ) located 150 km southeast of the CL site. High NPF frequencies were observed at the CL (50%) and BJ (52%) sites; however, the fraction of concurrent NPF events was smaller than the results in other regions. In addition, the wind distributions exhibited distinct air mass origins at the two sites during the concurrent NPF events. Compared with the BJ site, the NPF growth rates were higher at the CL site due to higher levels of volatile organic compounds (VOCs) and radiation. Surprisingly, the formation rates at the CL site were lower than at the BJ site, even with a higher sulfuric acid concentration and lower CS, which may be attributed to lower dimethylamine concentrations in the mountainous area. This study reveals that, although NPF events are commonly thought to occur on regional scales, their intensity and mechanisms may have significant spatial inhomogeneity. Further studies are required to reduce the uncertainty when expanding the mechanisms based on the urban conditions to regional or global scales in the models.
Citation: Atmosphere
PubDate: 2023-09-04
DOI: 10.3390/atmos14091395
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1396: Modeling of Precipitation Prediction
Based on Causal Analysis and Machine Learning
Authors: Hongchen Li, Ming Li
First page: 1396
Abstract: The factors influencing precipitation in western China are quite complex, which increases the difficulty in determining accurate predictors. Hence, this paper models the monthly measured precipitation data from 240 meteorological stations in mainland China and the precipitation data from the European Centre for Medium-Range Weather Forecasts and the National Climate Centre and employs 88 atmospheric circulation indices to develop a precipitation prediction scheme. Specifically, a high-quality grid-point field is created by fusing and revising the precipitation data from multiple sources. This field is combined with the Empirical Orthogonal Function decomposition and the causal information flow. Next, the best predictors are screened through Empirical Orthogonal Function decomposition and causal information flow, and a data-driven precipitation prediction model is established using a Back Propagation Neural Network and a Random Forest algorithm to conduct the 1-month, 3-month, and 6-month precipitation predictions. The results show that: The machine learning-based precipitation prediction model has high accuracy and is generally able to predict the precipitation trend in the western region better. The Random Forest algorithm significantly outperforms the Back Propagation Neural Network algorithm in the prediction of the three starting times, and the prediction ability of both models gradually decreases as the starting time increases. Compared with the 2022 flood season prediction scores of the Institute of Atmospheric Sciences of the Chinese Academy of Sciences, the model improves the prediction of 1-month and 3-month precipitation in the western region and provides a new idea for the short-term climate prediction of precipitation in western China.
Citation: Atmosphere
PubDate: 2023-09-04
DOI: 10.3390/atmos14091396
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1397: Combined Effects of Heat and Drought
Stress on the Growth Process and Yield of Maize (Zea mays L.) in Liaoning
Province, China
Authors: Wenying Yu, Ruipeng Ji, Jinwen Wu, Rui Feng, Na Mi, Nina Chen
First page: 1397
Abstract: A method was put forward to identify the combined heat and drought (CHD) events that occurred in summer and affected spring maize in Liaoning province. The spatial and temporal characteristics of CHD and its effects on maize were evaluated based on daily meteorological data at 52 meteorological stations in Liaoning from 1961 to 2020, as well as agricultural data including details of the maize development periods. The effects of CHD on the photosynthetic capacity of maize were evaluated using SIF remote sensing data from 2001 to 2020. The differences in maize photosynthetic capacity in the summers of 2009 and 2018 were compared in detail. The results show that from 1961 to 2020, the occurrence range, frequency, and severity of summer CHD events increased in Liaoning. CHD events were more frequent in June/July, and higher-intensity CHD events were more frequent in July/August. From 1961 to 2020, CHD events occurred in 69% of the years of reduced meteorological yield, and reduced meteorological yield occurred in 41% of the years with CHD events. Maize solar-induced chlorophyll fluorescence (SIF), an index of photosynthesis, was sensitive to temperature (negatively correlated) and precipitation (positively correlated). The CHD events slowed the increasing SIF from the three-leaf stage to the jointing stage, and they stopped the increasing SIF or decreased it at the tasseling–flowering to silking stages. Therefore, maize photosynthesis may be most sensitive to CHD during the flowering to silking stages, and CHD during the silking to milk stages may have the greatest impact on maize yield. Understanding the effects of CHD on maize growth/yield provides a scientific basis for reducing its negative impacts on maize production.
Citation: Atmosphere
PubDate: 2023-09-04
DOI: 10.3390/atmos14091397
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1398: Variability of Air Pollutant
Concentrations and Their Relationships with Meteorological Parameters
during COVID-19 Lockdown in Western Macedonia
Authors: Paraskevi Begou, Vasilios Evagelopoulos, Nikolaos D. Charisiou
First page: 1398
Abstract: The lockdown implemented to tackle the spread of the COVID-19 pandemic had a positive impact on air quality. Globally, studies have shown that air pollutant levels decreased temporally during the restriction measures. In this study, we evaluated the impact of COVID-19 restrictions on the air quality of Western Macedonia, Greece, using the concentrations of PM2.5 and PM10 along with meteorological data from the Air Quality Monitoring Stations (AQMS) operated by the Lignite Center of Western Macedonia. In Western Macedonia, previous studies have identified a general reduction in air pollutant levels during the last decade due to the coal phase-out plan for power generation. During the lockdown, the levels of PM2.5 and PM10 decreased further. The reduced emissions from the local mining activities and lignite-fired power plant electricity generation, as well as the weather conditions, seem to contribute to improving air quality.
Citation: Atmosphere
PubDate: 2023-09-04
DOI: 10.3390/atmos14091398
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1399: A Reconstruction Method for Ionospheric
foF2 Spatial Mapping over Australia
Authors: Yiran Liu, Qiao Yu, Yafei Shi, Cheng Yang, Jian Wang
First page: 1399
Abstract: To improve the accuracy of predicting the ionospheric critical frequency of the F2 layer (foF2), a reconstruction method for the spatial map of the ionospheric foF2 based on modified geomagnetic dip coordinates is proposed. Based on the strong correlation between the ionospheric foF2 and geomagnetic coordinates, the variation function of ionospheric distance is built. In the end, the spatial map of the ionospheric foF2 is predicted by solving the Kriging equation. The results show that the regional characteristics of the ionospheric foF2 analyzed by the proposed method are consistent with the observations. Compared with the reconstructed value of foF2 using traditional geographic coordinates, the root-mean-square error (RMSE) in high solar activity years decreased by 0.43 MHz, and the relative RMSE decreased by 5.48%; The RMSE decreased by 0.35 MHz during low solar activity which is 5.99% lower to relative RMSE. The research results provide support for high-frequency communication frequency selection.
Citation: Atmosphere
PubDate: 2023-09-05
DOI: 10.3390/atmos14091399
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1400: Aerosol Optical Depth Retrieval for
Sentinel-2 Based on Convolutional Neural Network Method
Authors: Jie Jiang, Jiaxin Liu, Donglai Jiao
First page: 1400
Abstract: Atmospheric aerosol significantly affects the climate environment and public health, and Aerosol Optical Depth (AOD) is a fundamental optical characteristic parameter of aerosols, so it is important to develop methods for obtaining AOD. In this work, a novel AOD retrieval algorithm based on a Convolutional Neural Network (CNN) method that could provide continuous and detailed aerosol distribution is proposed. The algorithm utilizes data from Sentinel-2 and Aerosol Robotic Network (AERONET) spanning from 2016 to 2022. The CNN AOD data are consistent with the AERONET measurements, with an R2 of 0.95 and RMSE of 0.049 on the test dataset. CNN demonstrates superior performance in retrieving AOD compared with other algorithms. CNN retrieves AOD well on high reflectance surfaces, such as urban and bare soil, with RMSEs of 0.051 and 0.042, respectively. CNN efficiently retrieves AOD in different seasons, but it performs better in summer and winter than in spring and autumn. In addition, to study the relationship between image size and model retrieval performance, image datasets of 32 × 32, 64 × 64 and 128 × 128 pixels were created to train and test the CNN model. The results show that the 128-size CNN performs better because large images contain rich aerosol information.
Citation: Atmosphere
PubDate: 2023-09-05
DOI: 10.3390/atmos14091400
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1401: Analysis and Research on the Differences
in Observed Data of Sand–Dust Weather between China and Mongolia
Authors: Yuan You, Linchang An, Siteng Li, Bihui Zhang, Jianzhong Zhang
First page: 1401
Abstract: The difference in meteorological factors (such as weather phenomena, wind speed, and visibility) of sand–dust weather between China and Mongolia from 2011 to 2021 was analyzed using meteorological observational data and international exchange of meteorological observation data. Additionally, consistency analysis was performed by integrating satellite retrieval products with meteorological observation data. The results showed that the average annual frequency of sand–dust weather in Mongolia was significantly higher than that in China. In China, the sand–dust weather was mainly characterized by floating dust or blowing dust, while in Mongolia, it was primarily characterized by blowing dust or a sand and dust storm. The average annual wind speed and visibility during sand–dust weather in Mongolia were relatively higher than those in China. Based on the dust grade standard of China, when the floating dust occurred in Mongolia, there were cases with wind speed > level 3 and visibility > 10 km; when the blowing dust or sand and dust storm occurred in Mongolia, there were cases with wind speed ≤ level 3 and visibility > 10 km. In China, the sand–dust weather mainly occurred in the spring, while the sand-dust weather occurred frequently throughout the year in Mongolia. The number of days with dust lasting for 2 days or more in Mongolia exceeded that of China, and Mongolia had a significant impact on the sand–dust weather in China. According to the ground observation data and satellite retrieve products during the dust events, all dust events that significantly affected China and Mongolia during the same period from 2021 to 2022 were classified into three categories; among them, the proportion of types of large-scale sand–dust weather phenomena observed by both satellite and ground observation stations was significantly higher (6 times). By integrating ground observation data and satellite retrieval products and following the dust grade standard of China, the consistent correction of sand–dust weather phenomena was carried out. This laid the foundation for the future development of international dust grade standards and provided technological support for improved dust forecasting services in the Asian region.
Citation: Atmosphere
PubDate: 2023-09-05
DOI: 10.3390/atmos14091401
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1402: Persistent Meteorological Drought in the
Yangtze River Basin during Summer–Autumn 2022: Relay Effects of
Different Atmospheric Internal Variabilities
Authors: Ruili Wang, Xiao Li, Hedi Ma, Xing Li, Junchao Wang, Anwei Lai
First page: 1402
Abstract: During the summer–autumn (July–October, Jul–Oct) period of 2022, the Yangtze River Basin (YRB) of China experienced an extreme meteorological drought, with Jul–Oct containing the lowest precipitation in the YRB since 1979. The possible causes of this drought were analyzed in the present study. Surprisingly, unlike many previous drought events, we found that this event was not characterized by a consistent atmospheric circulation anomaly regime throughout the entire drought period. Instead, two distinct circulation patterns were responsible for the precipitation deficit in two different stages, i.e., July–August (Jul–Aug) and September–October (Sep–Oct). In Jul–Aug, the YRB precipitation deficit primarily resulted from an intensified and northward-shifted East Asian subtropical jet, which allowed for an extremely northwestward shift of western Pacific subtropical highs, leading to an anomalous descending motion. Such circulation patterns in Jul–Aug originated from the dispersion of Rossby waves upstream from central Asia and Europe. Meanwhile, in Sep–Oct, the YRB drought was primarily attributed to a low-level cyclonic anomaly over the western North Pacific, which was closely associated with frequent tropical cyclones traveling across this region. Observational analysis and a model ensemble hindcast suggest that atmospheric internal variabilities dominated the drought process, while the SSTA, particularly the La Niña event, played a limited role. Therefore, this long-lasting extreme YRB meteorological drought was largely driven by the relay effects of different atmospheric internal variabilities in Jul–Aug and Sep–Oct, respectively, which shows limited model predictability and poses a great challenge for operational climate predictions.
Citation: Atmosphere
PubDate: 2023-09-05
DOI: 10.3390/atmos14091402
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1403: Assessment of Different Boundary Layer
Parameterization Schemes in Numerical Simulations of Typhoon Nida (2016)
Based on Aircraft Observations
Authors: Chaoyong Tu, Zhongkuo Zhao, Mingsen Zhou, Weibiao Li, Min Xie, Changjiang Ni, Shumin Chen
First page: 1403
Abstract: This study aimed to find a boundary layer parameter scheme suitable for typhoons in the South China Sea based on a comparison with the aircraft detection data from Typhoon Nida (2016). We simulated the typhoon boundary layer wind field in different boundary layer schemes, such as YSU, MYNN, BouLac, and Shin-Hong, and with a no-boundary-layer parametrization scheme. The results were as follows: (1) In the eye and eyewall area, the YSU and MYNN schemes could better simulate the east–west wind characteristics and the YSU scheme could also simulate the jet current of the southerly wind component in the boundary layer in the eyewall. (2) Compared with the eye area, the easterly wind in the eyewall area was strong, and the overall vertical movement was weak. (3) The YSU and MYNN schemes had similar turbulent kinetic energies that were also similar to those from aircraft observations; the turbulent kinetic energy in the simulations of several schemes in the boundary layer was evidently lower than that in the aircraft observations. Thus, the MYNN and the YSU schemes yielded better simulations for the eye and eyewall areas, and the YSU scheme was more similar to the boundary layer observations.
Citation: Atmosphere
PubDate: 2023-09-06
DOI: 10.3390/atmos14091403
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1404: Influence of Key Climate Factors on
Desertification in Inner Mongolia
Authors: Zhihui Liu, Long Ma, Tingxi Liu, Zixu Qiao, Yang Chen
First page: 1404
Abstract: Desertification is a major environmental problem facing the world today, and climate change is an important factor influencing desertification. This study investigates the impact of changes in key climate factors on desertification based on normalized difference vegetation index data, precipitation data and evaporation data from Inner Mongolia between 1982 and 2020 using correlation analysis, regression modelling, and residual analysis. The results show that precipitation and evaporation are significantly correlated with mild desertification and severe desertification, respectively, with correlation coefficients reaching 0.98 and −0.96, respectively. In severely desertified areas in central-eastern Inner Mongolia, there is a high correlation between desertification and temperature, the characteristics of the correlation of average maximum and minimum temperatures with desertification are similar to those of the correlation of average temperature with desertification, and the average maximum and minimum temperatures are well correlated with mild desertification, with correlation coefficients as high as 0.98 and 0.978, respectively. Climate contribution accounts for 97% of desertification in severely desertified areas, indicating that climate change has increased desertification in these areas. In regions with improved desertification, approximately 75% are primarily influenced by climate change (with a relative contribution greater than 50%), with climate factors exhibiting a relative contribution greater than 75% to desertification in 30% of these regions.
Citation: Atmosphere
PubDate: 2023-09-06
DOI: 10.3390/atmos14091404
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1405: CloudY-Net: A Deep Convolutional Neural
Network Architecture for Joint Segmentation and Classification of
Ground-Based Cloud Images
Authors: Feiyang Hu, Beiping Hou, Wen Zhu, Yuzhen Zhu, Qinlong Zhang
First page: 1405
Abstract: Ground-based cloud images contain a wealth of cloud information and are an important part of meteorological research. However, in practice, ground cloud images must be segmented and classified to obtain the cloud volume, cloud type and cloud coverage. Existing methods ignore the relationship between cloud segmentation and classification, and usually only one of these is studied. Accordingly, our paper proposes a novel method for the joint classification and segmentation of cloud images, called CloudY-Net. Compared to the basic Y-Net framework, which extracts feature maps from the central layer, we extract feature maps from four different layers to obtain more useful information to improve the classification accuracy. These feature maps are combined to produce a feature vector to train the classifier. Additionally, the multi-head self-attention mechanism is implemented during the fusion process to enhance the information interaction among features further. A new module called Cloud Mixture-of-Experts (C-MoE) is proposed to enable the weights of each feature layer to be automatically learned by the model, thus improving the quality of the fused feature representation. Correspondingly, experiments are conducted on the open multi-modal ground-based cloud dataset (MGCD). The results demonstrate that the proposed model significantly improves the classification accuracy compared to classical networks and state-of-the-art algorithms, with classification accuracy of 88.58%. In addition, we annotate 4000 images in the MGCD for cloud segmentation and produce a cloud segmentation dataset called MGCD-Seg. Then, we obtain a 96.55 mIoU on MGCD-Seg, validating the efficacy of our method in ground-based cloud imagery segmentation and classification.
Citation: Atmosphere
PubDate: 2023-09-06
DOI: 10.3390/atmos14091405
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1406: Source-Specific Health Risk of
PM2.5-Bound Metals in a Typical Industrial City, Central China,
2021–2022
Authors: Ziguo Liu, Changlin Zhan, Hongxia Liu, Shan Liu, Jihong Quan, Xianli Liu, Jiaquan Zhang, Chengkai Qu
First page: 1406
Abstract: In order to study the pollution characteristics, sources, and health risks of heavy metals in urban atmospheric PM2.5, samples were collected in Huangshi City from June 2021 to May 2022. The contents of 16 kinds of metal elements were analyzed by XRF, and the pollution degree and sources of elements were analyzed by the enrichment factor method, correlation analysis, and cluster analysis. The health risk of heavy metal elements was evaluated by the USEPA health risk assessment model. The results of enrichment factor analysis show that the metal elements carried by PM2.5 were affected by human emissions except for Ti. Heavy metals mainly come from industrial sources, motor vehicle sources, mixed combustion sources, and dust sources, according to correlation analysis and cluster analysis. Mn had a non-carcinogenic risk to children, and the non-carcinogenic risk of other elements to the human body was generally acceptable. The carcinogenic risks of Cr, As, Cd, and Co exceeded the acceptable carcinogenic risk threshold (10−6 ~10−4), and there were potential carcinogenic risks.
Citation: Atmosphere
PubDate: 2023-09-06
DOI: 10.3390/atmos14091406
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1407: Investigating the Relationship of Outdoor
Heat Stress upon Indoor Thermal Comfort and Qualitative Sleep Evaluation:
The Case of Ankara
Authors: Merve Münevver Ahan, Andre Santos Nouri, Andreas Matzarakis
First page: 1407
Abstract: The necessity of exploring the relationship between sleep quality and the thermal environment has amplified regarding increasing heat stress risk on the human body due to climate change, particularly in vulnerable uninsulated buildings in Ankara. Within this scope, this study investigated occupants’ sleep quality and human thermal comfort in insulated and uninsulated buildings under three local extreme heat event thresholds: (1) typical summer days (TSD25), (2) very hot days (VHD33), and lastly, (3) heat wave events (HWE31). Within a two-tiered approach to thermal comfort evaluations, the human thermal comfort of occupants was identified through the calculation of physiologically equivalent temperature (PET) from the climatic data of local meteorological stations. The psychological thermal comfort and sleep quality of participants were evaluated by questionnaires during each heat event. The results of this study demonstrated that the physiological thermal load of the participants was highest during VHD33s, given that both outdoor and indoor PET values presented their highest values within VHD33 events. Furthermore, the outdoor PET values reached extreme heat stress based on physiological stress grades with 43.5 °C, which indicated the exacerbated vulnerability of Ankara during extreme heat events. The PET values were consistently higher in uninsulated buildings than in insulated buildings. Also, most of the mean psychological thermal comfort votes and sleep quality votes were better in uninsulated buildings than in insulated ones during TSD25s and HWE31s, while it was the opposite within extreme conditions of VHD33s. The outputs of this study contribute to interdisciplinary efforts to attenuate the existing and impending risks of climate change on human life by defining the influence of increasing outdoor heat stress on indoor spaces, thermal comfort, and the sleep quality of occupants.
Citation: Atmosphere
PubDate: 2023-09-06
DOI: 10.3390/atmos14091407
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1408: Investigating Whether the Ensemble
Average of Multi-Global-Climate-Models Can Necessarily Better Project
Seasonal Drought Conditions in China
Authors: Jinping Liu, Yanqun Ren, Patrick Willems, Tie Liu, Bin Yong, Masoud Jafari Shalamzari, Huiran Gao
First page: 1408
Abstract: Global drought patterns are substantially impacted by climate change, with far-reaching implications for socioeconomic and ecological systems. Existing global climate models (GCMs) are unable to accurately project precipitation and drought characteristics, particularly in countries or regions with complex topography and significant seasonal variability, such as China. Consequently, the purpose of this study is to assess the efficacy of GCMs, and their multi-model ensemble mean, as well as to investigate the seasonal drought characteristics in China using precipitation data from CMIP6 under various “possible future” scenarios. This study selected five GCMs with historical (1961–2014) and future (2015–2100) periods, namely CNRM-CM6-1, GFDL-ESM4, MPI-ESM1-2-HR, MPI-ESM1-2-LR, and NorESM2-MM, as well as their ensemble mean ENS-CGMMN. Based on the China Daily Precipitation Analysis Product (CPAP) as the reference precipitation, the performance of these models is evaluated using the DISO index and the quantile mapping (QM) method for calibration, as well as seasonal-scale drought using the standardized precipitation index (SPI) and spatiotemporal variability analysis methods. In comparison to other climate models and the ensemble mean, the calibrated MPI-ESM1-2-HR model can more precisely describe the actual precipitation conditions at the seasonal scale. Under four scenarios, China’s climate will shift from arid to moist in the future period (2015–2100) (SSP126, SSP245, SSP370, and SSP585). Autumn and summer will see a considerable increase in China’s moisture levels. During the autumn, winter, and spring, the moisture will generally increase in the northern subregions of China, including the Qinghai-Tibet Plateau (QTP), Xinjiang (XJ), Northwest (NW), Northeast (NE), and North China (NC). Dryness will decrease in southern subregions, such as the Southwest (SW) and South China (SC). In contrast to these three seasons, summer in XJ exhibits a distinct trend of aridity, especially in the SSP245 scenario, whereas the NE, NC, and SC exhibit a distinct trend of moisture. To be more specific, the aridity changes in subregions during various seasons under different future climate scenarios vary significantly. This study’s findings can provide significant support for future research on climate change and drought, which can help improve the accuracy of future climate projections and serve as a reference for drought risk management and policy formulation.
Citation: Atmosphere
PubDate: 2023-09-06
DOI: 10.3390/atmos14091408
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1409: Comparison of the Performance of the
GRASP and MERRA2 Models in Reproducing Tropospheric Aerosol Layers
Authors: Alnilam Fernandes, Artur Szkop, Aleksander Pietruczuk
First page: 1409
Abstract: Two approaches, based on Generalized Retrieval of Aerosol and Surface Properties (GRASP) and Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) models, are investigated for reproducing aerosol layers in the troposphere. The GRASP algorithm is supplied with synergistic LIDAR and sunphotometer measurements to obtain aerosol extinction profiles. MERRA-2 is an atmospheric reanalysis coupling model that includes an external mixture of sea salt, dust, organic carbon, black carbon, and sulfate aerosols. A data set from Racibórz observatory, obtained with LIDAR and a sunphotometer in the 2017–2020 period, is analysed with GRASP along with the closest grid point data given by MERRA-2. The models demonstrate satisfactory agreement, yet some discrepancies were observed, indicating the presence of biases. For vertically integrated profiles, the correlation coefficient (R) between aerosol optical thickness was calculated to be 0.84, indicating a strong linear relationship. The Pearson correlation coefficient calculated between profiles for the selected altitude sectors varies between 0.428 and 0.824, indicating moderate to good agreement at all altitudes. GRASP shows denser aerosol layers in the mid-troposphere, while MERRA-2 gives higher aerosol extinctions throughout the high troposphere to low stratosphere region. Moreover, GRASP does not provide vertical variability in the extinction profile near the ground, due to a lack of data in the LIDAR’s incomplete overlap range. Lastly, the aerosol layer identification and type recognition are validated with statistical analysis of air mass backward trajectories with endpoints spatially and temporally collocated with individual identified layers. These reveal potential source regions that are located within areas known to be significant sources for the different identified aerosol types.
Citation: Atmosphere
PubDate: 2023-09-07
DOI: 10.3390/atmos14091409
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1410: All-Day Cloud Classification via a Random
Forest Algorithm Based on Satellite Data from CloudSat and Himawari-8
Authors: Yuanmou Wang, Chunmei Hu, Zhi Ding, Zhiyi Wang, Xuguang Tang
First page: 1410
Abstract: It remains challenging to accurately classify complicated clouds owing to the various types of clouds and their distribution on multiple layers. In this paper, multi-band radiation information from the geostationary satellite Himawari-8 and the cloud classification product of the polar orbit satellite CloudSat from June to September 2018 are investigated. Based on sample sets matched by two types of satellite data, a random forest (RF) algorithm was applied to train a model, and a retrieval method was developed for cloud classification. With the use of this method, the sample sets were inverted and classified as clear sky, low clouds, middle clouds, thin cirrus, thick cirrus, multi-layer clouds and deep convection (cumulonimbus) clouds. The results indicate that the average accuracy for all cloud types during the day is 88.4%, and misclassifications mainly occur between low and middle clouds, thick cirrus clouds and cumulonimbus clouds. The average accuracy is 79.1% at night, with more misclassifications occurring between middle clouds, multi-layer clouds and cumulonimbus clouds. Moreover, Typhoon Muifa from 2022 was selected as a sample case, and the cloud type (CLT) product of an FY-4A satellite was used to examine the classification method. In the cloud system of Typhoon Muifa, a cumulonimbus area classified using the method corresponded well with a mesoscale convective system (MCS). Compared to the FY-4A CLT product, the classifications of ice-type (thick cirrus) and multi-layer clouds are effective, and the location, shape and size of these two varieties of cloud are similar.
Citation: Atmosphere
PubDate: 2023-09-07
DOI: 10.3390/atmos14091410
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1411: Particle Counter Design Upgrade for Euro
7
Authors: Norbert Biró, Dániel Szöllösi, Péter Kiss
First page: 1411
Abstract: This research article presents an optimized approach to enhance the performance of the APC exhaust gas particle analyzer, a significant instrument used for exhaust emission evaluation in diesel-powered vehicles considering EU regulations on pollutant emissions. The study aimed to address the challenge of particle counter contamination that often occurs during frequent exhaust gas measurements and leads to measurement interruptions until maintenance is conducted. To achieve this, a preparatory unit that extends the operational duration of the measurement system between maintenance intervals while preserving measurement accuracy was developed based on actual exhaust gas experiments. The preparatory unit comprises a condensate drainage system, cooling fan, HEPA filter, membrane pump, and interconnecting pipelines to prevent moisture and larger particle deposition, ensuring uninterrupted and accurate exhaust gas measurements. The research findings underscore the significance of reliable and precise exhaust gas emission measurements, contributing to advancements in particle counting technology and facilitating compliance with emissions regulations in various scientific and industrial applications. This study provides an objective representation of the proposed preparatory unit’s effectiveness in mitigating particle contamination with only 1.9% measurement variance, offering promising implications for the improvement of exhaust gas analysis methods.
Citation: Atmosphere
PubDate: 2023-09-07
DOI: 10.3390/atmos14091411
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1412: Surface Mesonet and Upper Air Analysis of
the 21 August 2017 Total Solar Eclipse
Authors: Robert Pasken, Jeffrey Halverson, Peter Braunschweig
First page: 1412
Abstract: The total solar eclipse of 21 August 2017 was unique in that the path of totality swept across the high spatial and temporal resolution QuantumWeather® mesonet and was very near the city of St. Louis Missouri. Thus, the meteorological response to the eclipse was complicated by the St. Louis urban heat island. Temperature changes of up 4 °C were observed across the network. Composite meteograms for rural, suburban, and urban stations displayed significant differences in the observed temperature and pressure response to the eclipse with a peak amplitude at the time of the eclipse. The differing response suggests that the urban heat island and changes in land surface characteristics alter the temperature and pressure response by the passage of the eclipse shadow. Oscillations in the composite meteograms appear to be the consequence of the passage of an outflow boundary across the network. As the outflow boundary moves north to south, the outflow boundary manifests its presence in the pressure field as a damped oscillation. Sounding data were collected along the center line of eclipse and along the southern edge of the eclipse before and during the eclipse. The soundings show that the eclipse altered the boundary layer height, the lowest layer of the atmosphere, in an unexpected way.
Citation: Atmosphere
PubDate: 2023-09-07
DOI: 10.3390/atmos14091412
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1413: A Novel AI Framework for PM Pollution
Prediction Applied to a Greek Port City
Authors: Fotios K. Anagnostopoulos, Spyros Rigas, Michalis Papachristou, Ioannis Chaniotis, Ioannis Anastasiou, Christos Tryfonopoulos, Paraskevi Raftopoulou
First page: 1413
Abstract: Particulate matter (PM) pollution is a major global concern due to its negative impact on human health. To effectively address this issue, it is crucial to have a reliable and efficient forecasting system. In this study, we propose a framework for predicting particulate matter concentrations by utilizing publicly available data from low-cost sensors and deep learning. We model the temporal variability through a novel Long Short-Term Memory Neural Network that offers a level of interpretability. The spatial dependence of particulate matter pollution in urban areas is modeled by incorporating characteristics of the urban agglomeration, namely, mean population density and mean floor area ratio. Our approach is general and scalable, as it can be applied to any type of sensor. Moreover, our framework allows for portable sensors, either mounted on vehicles or used by people. We demonstrate its effectiveness through a case study in Greece, where dense urban environments combined with low cost sensor networks is a peculiarity. Specifically, we consider Patras, a Greek port city, where the net PM pollution comes from a variety of sources, including traffic, port activity and domestic heating. Our model achieves a forecasting accuracy comparable to the resolution of the sensors and provides meaningful insights into the results.
Citation: Atmosphere
PubDate: 2023-09-07
DOI: 10.3390/atmos14091413
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1414: Large-Scale Climate Factors of Compound
Authors: Siwen Zhao, Ruipeng Ji, Saidi Wang, Xiaoou Li, Siyu Zhao
First page: 1414
Abstract: Co-occurring extreme heat, drought, and moisture events are increasing under global warming and pose serious threats to ecosystem and food security. However, how to effectively link compound agrometeorological disasters (CADs) with climate change has not been well assessed. In this study, we focus on the comprehensive influence of large-scale climate factors on CADs rather than extreme meteorological elements. The results indicate that there are two main CADs of spring maize in Shenyang, Northeast China (NEC), including concurrent drought and cold damage (DC) and drought in multiple growth periods (MD). The related circulation anomalies at mid–high latitudes are identified as four patterns, namely, the Northeast Asia Low (NEAL) and Ural High (UH) patterns affecting DC, the Baikal High and Okhotsk Low (BHOL), and the Northeast Asia High (NEAH) patterns leading to MD. The vertical profile and water vapor transport anomalies further demonstrate the influence mechanism of large-scale circulation on compound heat–moisture stresses. This study highlights the role of atmospheric circulation, which can provide effective predictors for these synergistic agrometeorological disasters.
Citation: Atmosphere
PubDate: 2023-09-08
DOI: 10.3390/atmos14091414
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1415: Effects of Extreme Precipitation on
Runoff and Sediment Yield in the Middle Reaches of the Yellow River
Authors: Zongping Ren, Xiaoni Ma, Kaibo Wang, Zhanbin Li
First page: 1415
Abstract: Understanding the link between extreme precipitation and changes in runoff and sediment yield is of great significance for regional flood disaster response and soil and water conservation decision-making. This study investigated the spatial and temporal distribution of extreme precipitation (characterized by 10 extreme precipitation indices recommended by the Expert Team on Climate Change Detection and Indices) in the Toudaoguai–Longmen section of the middle Yellow River from 1960 to 2021 and quantified the effects of extreme precipitation on runoff and sediment yield based on the method of partial least squares regression (PLSR). The extreme precipitation index showed an obvious upward trend in the last 20 years, with the increases in the central and northern regions (upstream) being stronger than the increase in the southern region (downstream). However, the runoff and sediment yield decreased significantly due to the implementation of large-scale soil and water conservation measures on the Loess Plateau, with average rates of 94.7 million m3/a and 13.3 million t/a during 1960–2021, respectively. The change points of runoff and sediment yield change occurred in 1979. Compared with those in the period from 1960 to 1979, the reductions in runoff and sediment yield in the years 1980–2021 were 52.7% and 70.6%, respectively. Moreover, extreme precipitation contributed 35.3% and 6.2% to the reduction in runoff in the 1980–1999 and 2000–2021 periods, respectively, and contributed 84.3% and 40.0% to the reduction in sediment yield, respectively. It indicated that other factors (such as large-scale soil and water conservation construction) played main roles in the decrease in runoff and sediment yield in the study area in recent 20 years.
Citation: Atmosphere
PubDate: 2023-09-08
DOI: 10.3390/atmos14091415
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1416: Comparative Analysis of Traditional and
Advanced Clustering Techniques in Bioaerosol Data: Evaluating the Efficacy
of K-Means, HCA, and GenieClust with and without Autoencoder Integration
Authors: Maxamillian A. N. Moss, Dagen D. Hughes, Ian Crawford, Martin W. Gallagher, Michael J. Flynn, David O. Topping
First page: 1416
Abstract: In a comparative study contrasting new and traditional clustering techniques, the capabilities of K-means, the hierarchal clustering algorithm (HCA), and GenieClust were examined. Both K-means and HCA demonstrated strong consistency in cluster profiles and sizes, emphasizing their effectiveness in differentiating particle types and confirming that the fundamental patterns within the data were captured reliably. An added dimension to the study was the integration of an autoencoder (AE). When coupled with K-means, the AE enhanced outlier detection, particularly in identifying compositional loadings of each cluster. Conversely, whilst the AE’s application to all methods revealed a potential for noise reduction by removing infrequent, larger particles, in the case of HCA, this information distortion during the encoding process may have affected the clustering outcomes by reducing the number of observably distinct clusters. The findings from this study indicate that GenieClust, when applied both with and without an AE, was effective in delineating a notable number of distinct clusters. Furthermore, each cluster’s compositional loadings exhibited greater internal variability, distinguishing up to 3× more particle types per cluster compared to traditional means, and thus underscoring the algorithms’ ability to differentiate subtle data patterns. The work here postulates that the application of GenieClust both with and without an AE may provide important information through initial outlier detection and enriched speciation with an AE applied, evidenced by a greater number of distinct clusters within the main body of the data.
Citation: Atmosphere
PubDate: 2023-09-08
DOI: 10.3390/atmos14091416
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1417: Assessment of Heavy-Duty Diesel Vehicle
NOx and CO2 Emissions Based on OBD Data
Authors: Lijun Hao, Yanxu Ren, Wenhui Lu, Nan Jiang, Yunshan Ge, Yachao Wang
First page: 1417
Abstract: Controlling NOx and CO2 emissions from heavy-duty diesel vehicles (HDDVs) is receiving increasing attention. Accurate measurement of HDDV NOx and CO2 emissions is the prerequisite for HDDV emission control. Vehicle emission regulations srecommend the measurement of NOx and CO2 emissions from vehicles using an emission analyzer, which is expensive and unsuitable to measure a large number of vehicles in a short time. The on-board diagnostics (OBD) data stream of HDDVs provides great convenience for calculating vehicle NOx and CO2 emissions by providing the engine fuel flow rate, NOx sensor output, and air mass flow. The calculated vehicle NOx and CO2 emissions based on the OBD data were validated by testing a heavy-duty truck’s emissions on the chassis dynamometer over the CHTC-HT driving cycle, showing that the calculated NOx and CO2 emissions based on the OBD data are consistent with the measured results by the emission analyzer. The calculated vehicle fuel consumptions based on the OBD data were close to the calculated results based on the carbon balance method and the measured results by the fuel flowmeter. The experimental results show that accessing vehicle NOx and CO2 emissions based on the OBD data is a convenient and applicable method.
Citation: Atmosphere
PubDate: 2023-09-08
DOI: 10.3390/atmos14091417
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1418: Assessment of the Influence of Instrument
Parameters on the Detection Accuracy of Greenhouse-Gases Absorption
Spectrometer-2 (GAS-2)
Authors: Shizhao Li, Long Cheng, Hongchun Yang, Zengwei Wang, Lei Ding
First page: 1418
Abstract: Satellite-based monitoring of atmospheric greenhouse gas (GHG) concentrations has emerged as a prominent and globally recognized field of research. With the imminent launch of the Greenhouse-Gases Absorption Spectrometer-2 (GAS-2) on the FengYun3-H (FY3-H) satellite in 2024, there is a promising prospect for substantial advancements in GHG detection capabilities. Crucially, the accurate acquisition of spectral information by GAS-2 is heavily reliant on its instrument parameters. However, the existing body of research predominantly emphasizes the examination of atmospheric parameters and their impact on GHG detection accuracy, thereby leaving a discernible gap in the comprehensive evaluation of instrument parameters specifically concerning the acquisition of atmospheric greenhouse gas concentration data by GAS-2. To address this knowledge gap, our study employs a radiation transfer model grounded in radiation transfer theory. This comprehensive investigation aims to quantitatively analyze the effects of various instrument parameters, encompassing crucial aspects such as spectral resolution, spectral sampling rate, signal-to-noise ratio, radiometric resolution, and spectral calibration accuracy (including instrument line shape function, central wavelength shift, and spectral resolution broadening). Based on our preliminary findings, it is evident that GAS-2 has the necessary spectral resolution, spectral sampling rate, and signal-to-noise ratio, slightly surpassing existing international instruments and enabling a significant detection accuracy level of 1 part per million (ppm). Moreover, it is essential to recognize the critical impact of instrument spectral calibration accuracy on overall detection precision. Among the five commonly used instrument line shape functions, the sinc function has the least impact on detection accuracy. Additionally, GAS-2’s radiance quantization depth is 14 bits, which is comparable to similar international payloads and maintains a root mean squared error below 0.1 ppm, thus ensuring a high level of precision. This study provides a comprehensive evaluation of the influence of GAS-2’s instrument parameters on detection accuracy, offering valuable insights for the future development of spectral calibration, the optimization of similar payload instrument parameters, and the overall improvement of instrument quantification capabilities.
Citation: Atmosphere
PubDate: 2023-09-08
DOI: 10.3390/atmos14091418
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1419: Human Activities Accelerated Increase in
Vegetation in Northwest China over the Three Decades
Authors: Liqin Yang, Hongyan Fu, Chen Zhong, Jiankai Zhou, Libang Ma
First page: 1419
Abstract: Natural ecosystems are changing more quickly because of human activities, the type and intensity of which are directly correlated with vegetation greenness. To effectively determine how human activities affect trends in vegetation under climate change, we must differentiate between various types of human activities. The GTWR model can study the spatiotemporal non-stationary relationship between the NDVI trend and climate change. The GTWR model was incorporated into multiple climate variables and improved residual analysis to quantify the contributions of climate change and human activities on vegetation change trends in the Hexi region during different periods. This study divides human activities into four groups based on land use change: urbanization, agricultural expansion, desertification, and ecological restoration to further investigate their contribution to vegetation greenness change. The results showed that in 56.9% of the significant vegetation greening trends between 1982 and 2015, climate factors contributed only 7.4%, while human factors contributed a significant 22.7%. Since the ecological restoration project implemented in 2000, the expansion intensity of ecological restoration and urbanization increased significantly, followed by agricultural expansion and desertification. For the considerable greening trends in the Hexi region, the ecological restoration project contributed 26.7%, while agricultural expansion and urbanization contributed 17.5% and 4.6%, respectively. This study aims to provide new insights for more accurate simulation and evaluation of the interaction effects of climate change and human socio-economic development on vegetation growth.
Citation: Atmosphere
PubDate: 2023-09-08
DOI: 10.3390/atmos14091419
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1420: Methane Emissions of a Western Dairy
Manure Storage Basin and Their Correlation with Hydrogen Sulfide Emissions
Authors: Richard H. Grant, Matthew T. Boehm
First page: 1420
Abstract: Anaerobic decomposition in manure storage contributes to hydrogen sulfide (H2S) and methane (CH4) emissions. Coincident emission measurements were made of these gases from a western free stall dairy manure storage basin over a two-month period (August and September) as manure filled the basin and dried to assess the similarity or differences in the emissions characteristics. Path-integrated CH4 concentrations were measured from sampled air using photoacoustic spectrometric technology. Half-hourly emissions were determined using a backward Lagrangian Stochastic method utilizing on-site turbulence measurements. The median daily CH4 emission for the basin was 3.5 mg CH4 m−2 s−1 (772 g d−1 hd−1). Aging of the manure over the 44 days of this study did not appear to influence the CH4 emissions. A high correlation between the CH4 and H2S emissions during the study period suggested that the production and transport of these two gases from the basin were influenced by the same factors. Emissions did not appear to be influenced by the above-ground environmental conditions (wind speed, turbulent mixing, air temperature, change in barometric pressure, or vapor pressure deficit) but were likely more a function of the bacterial population present and/or available substrate for bacterial decomposition. Similarity in the CH4 to H2S emission ratio during basin manure filling and drying down to that of a slurry storage in a midwestern US dairy suggested that the bacterial species involved in the decomposition of dairy manure slurry is similar regardless of climate.
Citation: Atmosphere
PubDate: 2023-09-10
DOI: 10.3390/atmos14091420
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1421: Climate Change in the Eastern Xinjiang of
China and Its Connection to Northwestern Warm Humidification
Authors: Lu Li, Shijie Wang, Youping Chen, Heli Zhang, Jiyun Zhang, Yang Xu, Jiachang Wei
First page: 1421
Abstract: Eastern Xinjiang, as a typical extremely arid area, exhibits a high sensitivity to climate change. Gaining a comprehensive understanding of the climatic changes in this region, along with their driving mechanisms, and comparing these with the broader trend of “warming and humidifying” in the Northwest can provide a scientific foundation for adapting to and addressing climate change. Based on a study of precipitation and temperature data from seven meteorological stations in Eastern Xinjiang from 1960 to 2022, the following findings were observed: (1) The climate of eastern Xinjiang is generally characterized by a warming and humidifying trend, with the rates of mean annual temperature and total annual precipitation being 0.39 °C/10 a and 3.32 mm/10 a. The eastern part of Xinjiang has less precipitation, with a lower growth rate than that of the neighboring regions, and higher temperatures, with a higher growth rate than that of the neighboring regions. (2) The first principal component of precipitation explains 47.85% of the variation in total precipitation, with a significant upward trend (p < 0.05) and an abrupt change in the late 1970s. It contains strong signals of regional precipitation, temperature, and dry and wet changes. (3) The increase in the first principal component of annual precipitation in eastern Xinjiang is mainly related to the warming of SSTs in the Indian Ocean and the central-eastern part of the tropical southern Pacific Ocean as well as the weakening of the Asian monsoon.
Citation: Atmosphere
PubDate: 2023-09-10
DOI: 10.3390/atmos14091421
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1422: Study on Characteristics and Model
Prediction of Methane Emissions in Coal Mines: A Case Study of Shanxi
Province, China
Authors: Xueli Zhang, Tao Zhu, Nengjing Yi, Bo Yuan, Chen Li, Zefu Ye, Zhujun Zhu, Xing Zhang
First page: 1422
Abstract: The venting of methane from coal mining is China’s main source of methane emissions. Accurate and up-to-date methane emission factors for coal mines are significant for reporting and controlling methane emissions in China. This study takes a typical coal mine in Shanxi Province as the research object and divides the coal mine into different zones based on the occurrence structure of methane in Shanxi Province. The methane emission characteristics of underground coal mine types and monitoring modes were studied. The emissions of methane from coal seams and ventilation methane of six typical coal mine groups in Shanxi Province were monitored. The measured methane concentration data were corrected by substituting them into the methane emission formula, and the future methane emissions were predicted by the coal production and methane emission factors. The results show that the number of methane mines and predicted reserves in Zone I of Shanxi Province are the highest. The average methane concentration emitted from coal and gas outburst mines is about 22.52%, and the average methane concentration emitted from high-gas mines is about 10.68%. The methane emissions from coal and gas outburst mines to the atmosphere account for about 64% of the total net methane emissions. The predicted methane emission factor for Shanxi coal mines is expected to increase from 8.859 m3/t in 2016 to 9.136 m3/t in 2025, and the methane emissions from Shanxi coal mines will reach 8.43 Tg in 2025.
Citation: Atmosphere
PubDate: 2023-09-11
DOI: 10.3390/atmos14091422
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1423: Relationships between Temperature at
Surface Level and in the Troposphere over the Northern Hemisphere
Authors: Zbigniew Ustrnul, Jadwiga Woyciechowska, Agnieszka Wypych
First page: 1423
Abstract: The thermal structure of the troposphere remains a hot topic, including modelling issues as well as temperature field simulations. This study evaluates the relationship between the air temperature at the Earth’s surface and the temperature of various layers of the troposphere over the Northern Hemisphere, as well as attempts to identify determinants of its variability. Vertical differentiation has been analyzed from the layer σ = 0.995 representing the surface (surface air temperature, SAT), up to an isobaric level of 300 hPa with a focus on the main pressure levels, i.e., 925 hPa, 850 hPa, 700 hPa, 500 hPa. The data were obtained from an NCEP/NCAR reanalysis with a resolution of 2.5 degrees latitude and longitude for the period 1961–2020. The relationship between the SAT and the temperature at each level was expressed using a simple but effective correlation coefficient by Pearson (PCC). These relationships obviously, according to Tobler’s law, weaken with an increasing altitude. However, the distribution of PCC (both horizontal and vertical) proves the impact of geographic factors associated with the relief and also with the surface itself (e.g., land cover). These factors are the main drivers of inversion layers and significantly disturb the straight vertical structure of the atmosphere. The research has shown a significant interannual differentiation of these interactions, as well as their spatial diversity in geographic space. The altitude–temperature relationship becomes weaker in all seasons, but much faster during summer and winter, relative to both spring and autumn.
Citation: Atmosphere
PubDate: 2023-09-11
DOI: 10.3390/atmos14091423
Issue No: Vol. 14, No. 9 (2023)
- Atmosphere, Vol. 14, Pages 1424: Determination of Grid-Wise Monsoon Onset
and Its Spatial Analysis for India (1901–2019)
Authors: Atul Saini, Netrananda Sahu, Sridhara Nayak
First page: 1424
Abstract: Monsoon onset in India has always been a topic of interest for the research fraternity and various stakeholders. This study aimed to determine the monsoon onset date at the grid point scale, to obtain the trend of monsoon onset, and to unravel the spatial distribution of monsoon onset during the period 1901–2019 (especially in different climate modes). Based on observed cumulative rainfall, the piecewise linear regression model (PLRM), which employs least-squares principles, finds changepoints that signify the beginning of the monsoon season with the onset of monsoon. In this study, monsoon onset is examined with respect to several climate modes to evaluate their impact on monsoon onset. Monsoon onset is delayed in El Niño and drought years due to strong negative anomalies that are revealed by a spatial examination of monsoon onset. However, because of local atmospheric circulation impacts, there are outliers. The study also reveals areas with notable monotonic tendencies in monsoon onset, suggesting future changes in onset dates. These areas need more sophisticated frameworks for developing mitigation strategies since they should be viewed as susceptible. The comparison of the PLRM outcomes with objective methods reveals a strong correlation, confirming the accuracy of the PLRM method. Overall, the PLRM has been shown to be a useful tool for predicting the start of the monsoon on fine spatial scales and may be used in conjunction with regional climate models to anticipate the start of the monsoon in various regions of India. The results of this study could have a significant impact on regional planning and policy initiatives for sustainable development.
Citation: Atmosphere
PubDate: 2023-09-11
DOI: 10.3390/atmos14091424
Issue No: Vol. 14, No. 9 (2023)
- 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)
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