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Atmosphere
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  This is an Open Access Journal Open Access journal
ISSN (Online) 2073-4433
Published by MDPI Homepage  [246 journals]
  • Atmosphere, Vol. 13, Pages 1940: The Vertical Distribution of VOCs and
           Their Impact on the Environment: A Review

    • Authors: Da Chen, Yanhong Xu, Jingcheng Xu, Meiling Lian, Wei Zhang, Wenhao Wu, Mengying Wu, Jingbo Zhao
      First page: 1940
      Abstract: Volatile organic compounds (VOCs) play an important role in atmospheric chemistry. Primary VOCs take part in chemical and photochemical reactions, contributing to ozone (O3) and secondary organic aerosol (SOA) formation, which may cause air pollution problems. High VOC concentrations might lead to dizziness, nausea, headaches, genotoxicity, reproductive weakness, and other diseases harmful to human health. Several studies have been performed to analyze the components, variations, or sources of VOCs at the ground level. In contrast, studies of the vertical distribution characteristics of VOCs are scarce, and the VOC potential for O3 formation in the boundary layer is not yet well understood. To better understand the VOC vertical variation regularities and related reasons in temporal and spatial dimensions, thus to deepen the understanding of their effects on O3 and SOA formation in the vertical direction and to identify the existing gaps in VOC vertical distributions, this study reviewed VOC sampling techniques, VOC vertical distribution characteristics, VOC diffusion models, and effects caused by VOCs. This work can be a valuable reference for decision making regarding environmental and health problems.
      Citation: Atmosphere
      PubDate: 2022-11-22
      DOI: 10.3390/atmos13121940
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1941: Monitoring and Analysis of Indoor Air
           Quality in Graduate Dormitories in Northern China

    • Authors: Liu, Li, Zhao
      First page: 1941
      Abstract: In recent years, the indoor air quality (IAQ) of educational buildings has attracted people’s attention. As a resting place, the dormitory occupies more than half of the students’ time in school. During sleep, the IAQ in dormitories is easily affected by breathing, which in turn affects the sleep quality and mental state of students. In order to study the relevant IAQ during sleep, this paper selected the dormitories of graduate students of different grades in a university in northern China, and monitored the temperature, humidity, CO2, PM2.5, HCHO and TVOC for two weeks during the changing seasons of autumn and winter. In addition, by issuing questionnaires, students made a subjective evaluation of the IAQ. According to the results of objective monitoring data and subjective evaluation, the IAQ changes in student dormitories of different grades, genders, and locations are statistically analyzed, and the correlation between environmental parameters is discussed. The research results show that temperature and humidity basically meet the national standards; indoor PM2.5 is positively correlated with outdoor PM2.5; and HCHO and TVOC are positively correlated with indoor temperature and humidity. Most dormitories lack natural ventilation, and the concentration of CO2 during sleep is too high, which affects the quality of sleep and mental state.
      Citation: Atmosphere
      PubDate: 2022-11-22
      DOI: 10.3390/atmos13121941
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1942: Assessing the Impact of Natural
           Conditions/Socioeconomic Indicators on the Urban Thermal Environment Based
           on Geographic Big Data

    • Authors: Xiaolong Lu, Haihui Wang, Huanliang Chen, Shuai Gao
      First page: 1942
      Abstract: Understanding correctly the factors influencing the urban thermal environment is a prerequisite and basis for formulating heat-island-effect mitigation policies and studying urban ecological issues. The rapid urbanization process has led to the gradual replacement of natural landscapes by products of socioeconomic activities, and although previous studies have shown that natural conditions and socioeconomic intensity can significantly influence land surface temperature (LST), few studies have explored the combined effects of both on LST, especially at a fine scale. Therefore, this study investigated the relationship between natural conditions/socioeconomic and summer daytime LST based on big data and a random forest (RF) algorithm using the city of Jinan as the study area. The results showed that the spatial pattern of LST, natural condition characteristics of the city, and socioeconomic characteristics are consistent in spatial pattern and have significant correlation. In the RF model, the fitted R2 of the regression model considering two influencing factors reaches 0.86, which is significantly higher than that of the regression model considering only one influencing factor. In the optimal regression model, topographic factors in natural conditions and socioeconomic factors in buildings and roads are very important factors influencing the urban thermal environment. Based on the results, strategies and measures for developing and managing measures related to the thermal environment are discussed in depth. The results can be used as a reference for mitigating urban heat islands in the study area or other cities with similar characteristics.
      Citation: Atmosphere
      PubDate: 2022-11-22
      DOI: 10.3390/atmos13121942
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1943: Forecasting and Optimization of Wind
           Speed over the Gobi Grassland Wind Farm in Western Inner Mongolia

    • Authors: Jinyuan Xin, Daen Bao, Yining Ma, Yongjing Ma, Chongshui Gong, Shuai Qiao, Yunyan Jiang, Xinbing Ren, Tao Pang, Pengcheng Yan
      First page: 1943
      Abstract: Wind power, as one of the primary clean energies, is an important way to achieve the goals of carbon peak and carbon neutrality. Therefore, high-resolution measurement and accurate forecasting of wind speed are very important in the organization and dispatching of the wind farm. In this study, several methodologies, including the mesoscale WRF (Weather Research and Forecasting(WRF) model, mathematical statistics algorithms, and machine learning algorithms, were adopted to systematically explore the predictability and optimization of wind speed of a Gobi grassland wind farm located in western Inner Mongolia. Results show that the rear-row turbines were significantly affected by upwind turbine wakes. The output power of upwind-group turbines was 591 KW with an average wind speed of 7.66 m/s, followed by 532 KW and 7.02 m/s in the middle group and 519 KW and 6.92 m/s in the downwind group. The higher the wind speed was, the more significantly the wake effect was presented. Intercomparison between observations and WRF simulations showed an average deviation of 3.73 m/s. Two postprocessing methods of bilinear interpolation and nearest replacement could effectively reduce the errors by 34.85% and 36.19%, respectively, with average deviations of 2.43 m/s and 2.38 m/s. A cycle correction algorithm named Average Variance–Trend (AVT) can further optimize the errors to 2.14 m/s and 2.13 m/s. In another aspect, the categorical boosting (CatBoost) artificial intelligence algorithm also showed a great performance in improving the accuracy of WRF outputs, and the four-day average deviation of 26–29 September decreased from 3.21 m/s to around 2.50 m/s. However, because of the influence of large-scale circulations, there still exist large errors in the results of various correction algorithms. It is therefore suggested through the investigation that data assimilation of the northwest and Mongolian plateau, boundary layer parameterization scheme optimization, and embedding of high-resolution topographic data could have great potential for obtaining more accurate forecasting products.
      Citation: Atmosphere
      PubDate: 2022-11-22
      DOI: 10.3390/atmos13121943
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1944: Using a Pollution-to-Risk Method to
           Evaluate the Impact of a Cold Front: A Case Study in a Downstream Region
           in Southeastern China

    • Authors: Changqing Lin, Wengwan Zhang
      First page: 1944
      Abstract: Cold fronts frequently intrude China in winter, causing air pollution episodes in downwind regions. Fine particulate matter (PM2.5) has been used as a major proxy of air pollution to examine the impacts of cold fronts. Compared to particles, gaseous pollutants can cause comparable or even higher levels of short-term health risks. In this study, a pollution-to-risk model was used to systematically evaluate the impacts of cold fronts on the combined health risks of air pollution mixtures, including PM2.5, nitrogen dioxide (NO2), ozone (O3), and sulfur dioxide (SO2). Dominant pollutants that caused significant mortality risks during a cold frontal passage in December 2019 over Fuzhou, a downwind city in southeastern China, were then examined. Under northerly frontal airflows, a pollution belt propagated southwards. In Fuzhou, two pollution peaks existed during the cold frontal passage. At the first peak, convergence and stagnant air in the frontal zone rapidly accumulated local air pollutants. The dominant pollutants that caused the mortality risk were identified as NO2 and PM2.5, both of which contributed 45% to the total risk. At the second peak, advection transported a significant amount of secondary pollutants from the upwind regions. Although PM2.5 was the dominant pollutant at this peak, gaseous pollutants still accounted for 34% of the total risk. Our risk analyses underscore the significant health impacts of gaseous pollutants during cold frontal passages in winter. The results generated from this study will help guide environmental policy makers in forming and improving air pollution control strategies during pollution episodes.
      Citation: Atmosphere
      PubDate: 2022-11-22
      DOI: 10.3390/atmos13121944
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1945: The Extremely Active 2020 Hurricane
           Season in the North Atlantic and Its Relation to Climate Variability and
           Change

    • Authors: José Javier Hernández Ayala, Rafael Méndez-Tejeda
      First page: 1945
      Abstract: The 2020 hurricane season in the North Atlantic basin was the most active on record, with 30 named tropical cyclones. In this study, climate trends in oceanic and atmospheric parameters (including the sea surface temperatures, ocean heat content, cloud cover, mid-level humidity, vertical wind shear, and sea level pressure) were used to model the tropical cyclone, hurricane, and major hurricane frequency in the post-satellite era (1966–2020). The relationships between storm frequency and climate variability factors (including the El Niño Southern Oscillation, the North Atlantic Oscillation, the Atlantic Multidecadal Oscillation, and the Atlantic Meridional Mode) were also examined. This was performed to determine the factors that exerted the greatest influence on the most active hurricane seasons on record. Mann–Kendall trend tests, Pearson’s correlations tests, stepwise Poisson linear regression models and spatial analysis techniques were used to identify the climate change and variability factors that best explained the tropical cyclone frequency in the North Atlantic. Our results show that hyperactive hurricane seasons, such as that of 2020, tend to be associated with higher cloud cover development, lower sea level pressure patterns, higher sea surface temperatures, positive phases of the Atlantic Multidecadal Oscillation and the Atlantic Meridional Mode, and weaker wind shear environments. Seasons with more major hurricanes had higher ocean heat contents and weaker wind shear environments. The 2020 and 2005 seasons had similar cloud cover and sea level pressure patterns, yet the wind shear was lower in 2020 than in 2005, which was associated with La Niña dominant conditions that could explain why 2020 surpassed 2005 in the total number of storms.
      Citation: Atmosphere
      PubDate: 2022-11-23
      DOI: 10.3390/atmos13121945
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1946: CALIPSO Observations of Sand and Dust
           Storms and Comparisons of Source Types near Kuwait City

    • Authors: Ali H. Omar, Jason Tackett, Ali Al-Dousari
      First page: 1946
      Abstract: The Lidar on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission, makes robust measurements of dust and has generated a record that is significant both seasonally and interannually. We exploit this record to determine the properties of dust emanating from different source types during sand and dust storms (SDS). We use the relevant browsed images to describe the characteristics of the SDS layers qualitatively and the average properties quantitatively. In particular, we examine dust optical depths, dust layer frequencies, and layer heights during three sandstorms. The data are screened by using standard CALIPSO quality-assurance flags, cloud aerosol discrimination (CAD) scores, overlying features, and layer properties. To evaluate the effects of the SDS origin, phenomena such as morphology, vertical extent, and size of the dust layers, we compare probability distribution functions of the layer integrated volume depolarization ratios, geometric depths, and integrated attenuated color ratios as a function of source type. This study includes 17 individual dust storm cases observed near the city of Kuwait from three categories of sources: single source, combined sources, and unspecified sources. The strongest dust storms occurred in the summer months. The dust layers reached the highest altitudes for the combined cases. The layer top altitudes were approximately 3 km for the SDS from unspecified and single sources whereas the layer top altitudes averaged 4.1 km for the SDS from combined sources. Particles from single and combined sources recorded depolarization ratios of 0.22 and 0.23, respectively, whereas the depolarization ratios of SDS particles from unspecified sources were noticeably lower at 0.17. SDS from single sources resulted in the highest average AOD (0.66) whereas the SDS from combined sources and unspecified sources resulted in AODs of 0.41 and 0.28, respectively. Winter dust layers were disorganized, especially at night when the boundary layer was weak. The most well-organized layers close to the ground were observed in the daytime during the summer months.
      Citation: Atmosphere
      PubDate: 2022-11-23
      DOI: 10.3390/atmos13121946
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1947: Evaluation and Correction of Climate
           Simulations for the Tibetan Plateau Using the CMIP6 Models

    • Authors: Jiajia Gao, Jun Du, Cheng Yang, Zhuoga Deqing, Pengfei Ma, Ga Zhuo
      First page: 1947
      Abstract: This study evaluates the abilities of fifteen High-resolution Coupled Model Intercomparison Project phase 6 (CMIP6) models to simulate temperature and precipitation over the Tibetan Plateau (TP) for the years 1980–2014. The impacts of terrain correction and Empirical Orthogonal Function (EOF) correction on simulations of temperature and precipitation are examined. The results show that equal-weighted ensemble averaging of the CMIP6 high-resolution model provides a good representation of the spatial distribution of temperature over the TP, although simulations underestimate observations by 1.87 °C. The simulated spatial range of temperature cooling significantly exceeds the observed range, particularly in the central and southwestern TP. The performances of the simulations for precipitation are far poorer than those for temperature, and although the CMIP6 model represents the distribution of annual mean precipitation, simulations of precipitation show significant deviations from observations. Furthermore, model simulations of precipitation are 1.57 mm lower than observed, and 30% lower than observed in the southeastern TP. However, the CMIP6 model overestimated the intensity of precipitation in most regions, especially in the southeastern part of the TP. Meanwhile, the EOF analysis indicates that the effects of the correction of temperature exceed that of precipitation. Therefore, a range of methods should be considered for correcting temperature and precipitation over a complex terrain.
      Citation: Atmosphere
      PubDate: 2022-11-23
      DOI: 10.3390/atmos13121947
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1948: Short-Term Regional Temperature
           Prediction Based on Deep Spatial and Temporal Networks

    • Authors: Shun Wu, Fengchen Fu, Lei Wang, Minhang Yang, Shi Dong, Yongqing He, Qingqing Zhang, Rong Guo
      First page: 1948
      Abstract: Accurate prediction of air temperature is of great significance to outdoor activities and daily life. However, it is important and more challenging to predict air temperature in complex terrain areas because of prevailing mountain and valley winds and variable wind directions. The main innovation of this paper is to propose a regional temperature prediction method based on deep spatiotemporal networks, designing a spatiotemporal information processing module to align temperature data with regional grid points and further transforming temperature time series data into image sequences. Long Short-Term Memory network is constructed on the images to extract the depth features of the data to train the model. The experiments demonstrate that the deep learning prediction model containing the spatiotemporal information processing module and the deep learning prediction module is fully feasible in short-term regional temperature prediction. The comparison experiments show that the model proposed in this paper has better prediction results for classical models, such as convolutional neural networks and LSTM networks. The experimental conclusion shows that the method proposed in this paper can predict the distribution and change trend of temperature in the next 3 h and the next 6 h on a regional scale. The experimental result RMSE reached 0.63, showing high stability and accuracy. The model provides a new method for local regional temperature prediction, which can support the planning of production and life in advance and tend to save energy and reduce consumption.
      Citation: Atmosphere
      PubDate: 2022-11-23
      DOI: 10.3390/atmos13121948
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1949: Multitemporal Analysis of the Influence
           of PM10 on Human Mortality According to Urban Land Cover

    • Authors: Laura Marcela Ochoa-Alvarado, Carlos Alfonso Zafra-Mejía, Hugo Alexander Rondón-Quintana
      First page: 1949
      Abstract: High urbanization and a consequent change in land cover can lead to a deterioration in air quality and generate impacts on public health. The objective of this paper is to provide a multitemporal analysis of the influence of particulate matter ≤ 10 μm (PM10) on human mortality from the land cover variation in a Latin American megacity. Six monitoring stations (monitoring daily PM10 concentration, increases in daily mortality (IDM), and land cover) were established throughout the megacity. The results suggest that for every 10% increase in vegetation cover, the daily PM10 concentration and IDM decreases by 7.5 μg/m3 and 0.34%, respectively. Moreover, it is evident that the monitoring station with the lowest vegetation cover (8.96 times) shows an increase of 1.56 times and 4.8 times in the daily PM10 concentration and IDM, respectively, compared with the monitoring station with the highest vegetation cover (46.7%). It is also suggested that for each increase of 100 inhabitants/hectare in population density, the daily PM10 concentration and IDM increases by 9.99 µg/m3 and 0.45%, respectively. Finally, the population densification of the megacity possibly implies a loss of vegetation cover and contributes to the increase in PM10 and IDM.
      Citation: Atmosphere
      PubDate: 2022-11-23
      DOI: 10.3390/atmos13121949
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1950: Sea Port SO2 Atmospheric Emissions
           Influence on Air Quality and Exposure at Veracruz, Mexico

    • Authors: Fuentes García, Echeverría, Reynoso, Baldasano Recio, Rueda, Retama Hernández, Kahl
      First page: 1950
      Abstract: In this work, we identify the current atmospheric sulfur dioxide emissions of the Veracruz port, an important Mexican seaport experiencing rapid growth, and its influence on the surrounding areas. Sulfur dioxide emissions based on port activity, as well as meteorology and air quality simulations, are used to assess the impact. It was found that using marine fuel with low sulfur content reduces emissions by 88%. Atmospheric emission estimates based on the bottom-up methodology range from 3 to 7 Mg/year and can negatively impact air quality up to 3 km downwind. After evaluating different characteristics of vessels in CALPUFF, it was found that maximum sulfur dioxide concentrations ranging between 50 and 88 µg/m3 for a 24-h average occurred 500 m from the port. During 2019, five days had unsatisfactory air quality. The combination of a shallow planetary boundary layer, low wind speed, and large atmospheric emissions significantly degraded local air quality.
      Citation: Atmosphere
      PubDate: 2022-11-23
      DOI: 10.3390/atmos13121950
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1951: A Deep Learning Model and Its Application
           to Predict the Monthly MCI Drought Index in the Yunnan Province of China

    • Authors: Mei, Liu, Liu, Liu
      First page: 1951
      Abstract: The Yunnan province of China is a typical humid region but with several severe region-wide droughts. Drought indices are generally used to identify and characterize drought events, and then play a key role in drought prediction. Therefore, a novel prediction model was proposed to predict a comprehensive drought indicator (meteorological composite index, MCI) in Yunnan province. This model combined the recurrent neural networks (RNN) based on a gated recurrent neural unit (GRU) and convolutional neural networks (CNN) with optimization using the modified particle swarm optimization (PSO) algorithm. In this model, pre-processed predictor data were input into the GRU module to extract the time features of the sequences. Furthermore, the feature matrices were input into the CNN module to extract the deep local features and the inter-relationship of the predictors. The model was trained and used to predict the monthly MCI drought index of the representative five stations of Yunnan province from 1960 to 2020. The combined model was evaluated by comparison with traditional machine learning models such as the least absolute shrinkage and selection operator (LASSO) and random forest (RF), and the traditional GRU model. The results show significantly improved skills in root mean square error, mean absolute error and Nash–Sutcliffe efficiency coefficient. This novel method was valuable for the monthly drought prediction in Yunnan province and related climate-risk management.
      Citation: Atmosphere
      PubDate: 2022-11-23
      DOI: 10.3390/atmos13121951
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1952: Prioritization of VOCs Emitted from
           

    • Authors: Yong Yang, Guoao Li, Yaling Wang, Zhiping Wang, Bao Jiang, Huahua Bai, Lei Nie, Xue Chen, Xianglong Jing, Guohao Li, Chengyi Sun
      First page: 1952
      Abstract: The violate organic compounds (VOCs) emission from co-processing cement kiln has not been comprehensively investigated and evaluated. In this study, we sampled and determined the VOCs emitted from a typical co-processing cement kiln in Beijing, China. VOCs characteristics, ozone formation potential (OFP), and main odor components for the emitted gas were analyzed. Additionally, a Fuzzy Analytic Hierarchy Process (F-AHP) was innovatively applied to estimate the priority VOCs. The study shows that aromatic (36.6%) and oxygen contained VOCs (O-VOCs) (30.3%) were the most abundant VOCs, with a high average concentration of benzene (1622.0 μg/m3) and acrolein (1105.5 μg/m3). Acrolein, propene, benzene, 1-butane, and 1,3-butadiene were the dominate OFP compounds, with the corresponding average OFP concentration of 8325.6, 3768.2, 1167.9, 1065.9, and 1027.2 μg/m3, respectively. Acrolein was also found to be the dominate main odor component. Eleven VOCs, including one O-VOC, one halohydrocarbon, and nine alkenes, were screened out by F-AHP. Alkene was the priority VOCs category and acrolein was the most important VOC in the stack gas. The results of this study are helpful to systematically understand the VOCs’ characteristics, OFP, main odor components, and priority compounds of VOCs in the stack gas of co-processing cement kiln, and provide a new method for the screening of priority VOCs compounds.
      Citation: Atmosphere
      PubDate: 2022-11-23
      DOI: 10.3390/atmos13121952
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1953: Evaluation of Fengyun-4A Detection
           Accuracy: A Case Study of the Land Surface Temperature Product for Hunan
           Province, Central China

    • Authors: Jiazhi Fan, Qinzhe Han, Songqi Wang, Hailei Liu, Leishi Chen, Shiqi Tan, Haiqing Song, Wei Li
      First page: 1953
      Abstract: Land surface temperature (LST) is an important parameter in determining surface energy balance and a fundamental variable detected by the advanced geostationary radiation imager (AGRI), the main payload of FY-4A. FY-4A is the first of a new generation of Chinese geostationary satellites, and the detection product of the satellite has not been extensively validated. Therefore, it is important to conduct a comprehensive assessment of this product. In this study, the performance of the FY-4A LST product in the Hunan Province was authenticity tested with in situ measurements, triple collocation analyzed with reanalysis products, and impact analyzed with environmental factors. The results confirm that FY-4A captures LST well (R = 0.893, Rho = 0.915), but there is a general underestimation (Bias = −0.6295 °C) and relatively high random error (RMSE = 8.588 °C, ubRMSE = 5.842 °C). In terms of accuracy, FY-4A LST is more accurate for central-eastern, northern, and south-central Hunan Province and less accurate for western and southern mountainous areas and Dongting Lake. FY-4A LST is not as accurate as Himawari-8 LST; its accuracy also varies seasonally and between day and night. The accuracy of FY-4A LST decreases as elevation, in situ measured LST, surface heterogeneity, topographic relief, slope, or NDVI increase and as soil moisture decreases. FY-4A LST is also more accurate when the land cover is cultivated land or artificial surfaces or when the landform is a platform for other land covers and landforms. The conclusions drawn from the comprehensive analysis of the large quantity of data are generalizable and provide a quantitative baseline for assessing the detection capability of the FY-4A satellite, a reference for determining improvement in the retrieval algorithm, and a foundation for the development and application of future domestic satellite products.
      Citation: Atmosphere
      PubDate: 2022-11-23
      DOI: 10.3390/atmos13121953
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1954: Tomographic Inversion of the Ionosphere
           by Rejecting Abnormal Corrections and Rays

    • Authors: Jianmin Zhang, Jieqing Yu, Chenyi Jia, Yuchen Dai, Yanyu Zhu, Yingqi Huang, Lixin Wu
      First page: 1954
      Abstract: The errors contained in slant total electron content (STEC) have a strong impact on the image generated by ionosphere tomography. This paper presents a method that rejects abnormal corrections and rays (RACR) in the multiplicative algebraic reconstruction technique (MART) algorithm by applying a correction threshold and a rejecting ratio threshold. The RACR algorithm was validated using ionosonde observations, Swarm satellite measurements, independent STEC observations and a vertical total electron content (TEC) map. Its performance was compared with the MART algorithm on both geomagnetically quiet days and disturbed days. The results show that the RACA algorithm is able to capture the main phase and the recovery phase of a storm and outperforms the MART algorithm under both geomagnetic conditions. The average improvements over the MART algorithm are 36.01%, 36.56%, 6.18%, 22.10% and 6.03% in the validation tests of the peak density of F2 layer, peak height of F2 layer, the electron density of the topside ionosphere, STEC and VTEC, respectively. The quality of the image produced by the RACR algorithm was controlled by the correction threshold and the rejection threshold. Smaller threshold values tend to make the image smoother. The RACR algorithm provides not only a way to produce a better tomographic image but also a means to detect abnormal rays.
      Citation: Atmosphere
      PubDate: 2022-11-23
      DOI: 10.3390/atmos13121954
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1955: A Study of Land Ecological Environment
           Evaluation Based on an Ideal Point Model

    • Authors: Chen, Shi
      First page: 1955
      Abstract: The paper took Guang’an City in Sichuan Province of China as a research region, and it built an evaluation index system based on 14 evaluation indices according to four criteria, namely, ecological background, ecological structure, ecological benefits, and ecological stress. The Delphi algorithm and entropy weight (a combination of subjective and objective methods) were used to calculate the weight value of each evaluation index, and an ideal point model was used to calculate the ideal point value. The ideal point ecological grade was classified, and the principal component analysis method was used to obtain the main control factors of each year, which revealed the relationship between the ecological distribution of ideal points and the environmental impact factor, with the changing characteristics of the ecology in the research region according to the hotspot model of the spatial differentiation of land ecological quality as the main control factor. Lastly, the paper also analyzed the land ecological quality of Guang’an City in 2000, 2005, 2010, and 2015. The study results show that the overall land ecological quality in Guang’an City generally increased from 2005 to 2015. The proportion of forest land area and the temperature were the most important main control factors. The air temperature and the land ecological quality were positively correlated.
      Citation: Atmosphere
      PubDate: 2022-11-23
      DOI: 10.3390/atmos13121955
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1956: Spatiotemporal Patterns of Air Pollution
           in an Industrialised City—A Case Study of Ust-Kamenogorsk,
           Kazakhstan

    • Authors: Daulet Assanov, Ivan Radelyuk, Olessya Perederiy, Stanislav Galkin, Gulira Maratova, Valeriy Zapasnyi, Jiří Jaromír Klemeš
      First page: 1956
      Abstract: Air quality issues still affect the quality of life for people in industrialised cities around the world. The investigations should include the identification of the sources of the pollution and its distribution in space and time. This work is the first attempt to perform identification of the sources of pollution in Ust-Kamenogorsk city in Kazakhstan. Analysis of retrospective data (including ten variables (TSP, SO2, CO, NO2, phenol, HF, HCl, H2SO4, formaldehyde, H2S) from five monitoring stations for the period 2017–2021) using multivariate statistical methods and hierarchical cluster analysis has been performed to assess spatiotemporal patterns of air quality of the city. The results indicate that the contamination patterns can be grouped into two categories: cold and warm seasons. The study revealed the dangerous concentrations of NO2 and SO2 exceeded the limits by 2–3 and 1.5–2 times, independently of the seasonality. Averaged concentrations of TSP slightly exceeded the established limits for the most industrialised part of the city. Concentrations of HF and formaldehyde significantly rose during the cold seasons compared to the warm seasons. Other chemical parameters significantly depend on the seasonality and locations of the sampling points. The major reason for air pollution is twofold—the use of a burnt-coal throughout the year for electricity and heat generation (especially during the cold seasons) and the high density of the heavy metallurgy industry in the city. The principal component analysis confirms a high loading of industrial sources of air pollution on both spatial and seasonal dimensions.
      Citation: Atmosphere
      PubDate: 2022-11-23
      DOI: 10.3390/atmos13121956
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1957: Contributions of Multiple Water Vapor
           Sources to the Precipitation in Middle and Lower Reaches of Yangtze River
           Based on Precipitation Recycle Ratio

    • Authors: Zeng-Ping Zhang, Xi-Yu Wang, Min Liu, Bi-Cheng Huang, Yong-Ping Wu, Guo-Lin Feng, Gui-Quan Sun
      First page: 1957
      Abstract: Global warming weakened the summer monsoon and increased the evaporation, leading to more contribution of local evaporation moisture to the local precipitation for the monsoon areas. However, the descriptions of the contribution of the local moisture to the total precipitation and its characteristics have not been known very well. In this paper, taking the middle and lower Reaches of the Yangtze River (MLRYR) as a case and using the precipitation recycling process model, we analyzed the characteristics of the contribution of the local moisture to the total precipitation and the possible reasons. The results show that: the seasonal difference in precipitation recycling rates is obvious, the precipitation recycling rates in spring and summer are small (18.30% and 19.30%), the maximum in autumn is 30.50%, and the precipitation recycling rates in all seasons except summer show a significant upward trend (about 1.70%/10a). Additionally, the water vapor input into MLRYR from four boundaries significantly reduced except for the eastern boundary, and the water vapor contribution from the South and East borders is in summer, and the water vapor contribution from the North and West borders is in autumn, winter and spring. We suggest that the model of the precipitation recycling rate is important to evaluate the contribution of different water vapor sources, and help to further improve the ability of river water prediction in flood season.
      Citation: Atmosphere
      PubDate: 2022-11-23
      DOI: 10.3390/atmos13121957
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1958: Review of Carbon Capture and Methane
           Production from Carbon Dioxide

    • Authors: Stephen Okiemute Akpasi, Yusuf Makarfi Isa
      First page: 1958
      Abstract: In the last few decades, excessive greenhouse gas emissions into the atmosphere have led to significant climate change. Many approaches to reducing carbon dioxide (CO2) emissions into the atmosphere have been developed, with carbon capture and sequestration (CCS) techniques being identified as promising. Flue gas emissions that produce CO2 are currently being captured, sequestered, and used on a global scale. These techniques offer a viable way to encourage sustainability for the benefit of future generations. Finding ways to utilize flue gas emissions has received less attention from researchers in the past than CO2 capture and storage. Several problems also need to be resolved in the field of carbon capture and sequestration (CCS) technology, including those relating to cost, storage capacity, and reservoir durability. Also covered in this research is the current carbon capture and sequestration technology. This study proposes a sustainable approach combining CCS and methane production with CO2 as a feedstock, making CCS technology more practicable. By generating renewable energy, this approach provides several benefits, including the reduction of CO2 emissions and increased energy security. The conversion of CO2 into methane is a recommended practice because of the many benefits of methane, which make it potentially useful for reducing pollution and promoting sustainability.
      Citation: Atmosphere
      PubDate: 2022-11-24
      DOI: 10.3390/atmos13121958
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1959: Sol–Gel Synthesis of LiTiO2 and
           LiBO2 and Their CO2 Capture Properties

    • Authors: Liang Li, Haidi Yu, Yuqi Chen
      First page: 1959
      Abstract: LiTiO2 was prepared from tetraethoxy titanium and lithium ethoxide by a sol–gel process and then treated at 773 K and 973 K under oxygen atmosphere, respectively. Compared with LiTiO2 prepared at 973 K, LiTiO2 prepared at 773 K has better CO2 capture properties. XRD patterns of synthetic LiTiO2 before and after CO2 capture confirm that the intermediate product, LixTizO2, is produced during CO2 capture. CO2 absorption degree of LiTiO2 was determined to be 37% (293 K), 40.8% (333 K), 45.5% (373 K), and 50.1% (393 K) for 11.75 h, respectively. Repetitive CO2 capture experiment indicates that LiTiO2 has excellent cyclic regeneration behavior. The CO2 absorption degree of LiTiO2 increased with increasing CO2 concentration. At a concentration of 0.05%, the absorption degree of LiTiO2 had a stable value of 1% even after an absorption time of 1.4 h. LiBO2 was fabricated by the similar sol–gel method and treated at 713 K. Mass percentage and specific surface area of synthesized LiBO2 increased with the increasing absorption temperature. Evidently, the diffusion of the CO2 molecule through the reaction product, which had a low activation energy of 15 kJ·mol−1 and apparent specific surface value of 55.63 m2/g, determined the efficiency of the absorption reaction. Compared with the other sol–gel synthesized lithium-based oxides, LiTiO2 possessed higher absorption capabilities and lower desorption temperature.
      Citation: Atmosphere
      PubDate: 2022-11-24
      DOI: 10.3390/atmos13121959
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1960: Selection of Plant Species for
           Particulate Matter Removal in Urban Environments by Considering Multiple
           Ecosystem (Dis)Services and Environmental Suitability

    • Authors: Samira Muhammad, Karen Wuyts, Roeland Samson
      First page: 1960
      Abstract: To select plant species for particulate matter (PM) removal from urban environments, it is important to consider the plant species’ ecosystem (dis)services and environmental suitability in addition to their effectiveness in PM removal. In this study, 61 plant species were ranked for PM removal using three separate models: (i) leaf traits, (ii) leaf saturation isothermal remanent magnetization (SIRM), and (iii) ecosystem services and disservices. The plant species’ effectiveness in PM accumulation and the effective leaf traits were identified using leaf SIRM. In each model, plant species were assigned scores and weights for each criterion. The weighted average or the product (Π)-value was calculated for each plant species. The weighted average of each plant species was multiplied by the scores of leaf longevity and leaf area index (LAI) to scale up to a yearly basis and per unit of ground surface area. The preference ranking organization method for enrichment of evaluations (PROMETHEE) method was employed for the services and disservices model because of the lack of precise weights for the included criteria in the model. A scenario analysis was performed to determine a change in the ranking of plant species when the weights of the criteria were modified in the services and disservices model. The plant species with increased ecosystem services and reduced ecosystem disservices were Tilia cordata (Mill.), Tilia platyphyllos (Scop.), Alnus incana (L.), Acer campestre (L.), and Picea abies (L.). The findings of this study can be relevant to urban planners for recommending suitable choices of plant species for the development of urban green spaces.
      Citation: Atmosphere
      PubDate: 2022-11-24
      DOI: 10.3390/atmos13121960
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1961: Trend Analysis of Hydro-Climatological
           Factors Using a Bayesian Ensemble Algorithm with Reasoning from Dynamic
           and Static Variables

    • Authors: Keerthana A, Archana Nair
      First page: 1961
      Abstract: This study examines the variations in groundwater levels from the perspectives of the dynamic layers soil moisture (SM), normalized difference vegetation index (VI), temperature (TE), and rainfall (RA), along with static layers lithology and geomorphology. Using a Bayesian Ensemble Algorithm, the trend changes are examined at 385 sites in Kerala for the years 1996 to 2016 and for the months January, April, August, and November. An inference in terms of area under the probability curve for positive, zero, and negative trend was used to deduce the changes. Positive or negative changes were noticed at 19, 32, 26, and 18 locations, in that order. These well sites will be the subject of additional dynamic and static layer investigation. According to the study, additional similar trends were seen in SM during January and April, in TE during August, and in TE and VI during November. According to the monthly order, the matching percentages were 63.2%, 59.4%, 76.9%, and 66.7%. An innovative index named SMVITERA that uses dynamic layers has been created using the aforementioned variables. The average proportion of groundwater levels that follow index trends is greater. The findings of the study can assist agronomists, hydrologists, environmentalists, and industrialists in decision making for groundwater resources.
      Citation: Atmosphere
      PubDate: 2022-11-24
      DOI: 10.3390/atmos13121961
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1962: Variations of Secondary PM2.5 in an Urban
           Area over Central China during 2015–2020 of Air Pollutant Mitigation
           

    • Authors: Dingyuan Liang, Tianliang Zhao, Yan Zhu, Yongqing Bai, Weikang Fu, Yuqing Zhang, Zijun Liu, Yafei Wang
      First page: 1962
      Abstract: The lack of long-term observational data on secondary PM2.5 (SPM) has limited our comprehensive understanding of atmospheric environment change. This study develops an SPM estimation method, named Single-Tracer Approximate Envelope Algorithm (STAEA), to assess the long-term changes of SPM under different PM2.5 levels and in all seasons in Wuhan, Central China, over the period of anthropogenic pollutant mitigation in 2015–2020. The results show that: (1) the average proportions of SPM in ambient PM2.5 is 59.61% in a clean air environment, rising significantly to 71.60%, 73.73%, and 75.55%, respectively, in light, moderate, and heavy PM2.5 pollution, indicating the dominant role of SPM in air quality deterioration; (2) there are increasing trends of interannual changes of SPM at the light and moderate pollution levels of 1.95 and 3.11 μg·m−3·a−1 with extending SPM proportions in PM2.5 pollution, raising a challenge for further improvement in ambient air quality with mitigating light and moderate PM2.5 pollution; (3) the high SPM contributions ranging from 55.63% to 68.65% on a seasonal average and the large amplitude of seasonal SPM changes could dominate the seasonality of air quality; (4) the wintertime SPM contribution present a consistent increasing trend compared with the declining trends in spring, summer, and autumn, suggesting underlying mechanisms of SPM change for further deciphering the evolution of the atmospheric environment. Our results highlight the effects of air pollutant mitigation on long-term variations in SPM and its contributions with implications for atmospheric environment change.
      Citation: Atmosphere
      PubDate: 2022-11-24
      DOI: 10.3390/atmos13121962
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1963: Short-Term Rainfall Prediction Based on
           Radar Echo Using an Improved Self-Attention PredRNN Deep Learning Model

    • Authors: Dali Wu, Li Wu, Tao Zhang, Wenxuan Zhang, Jianqiang Huang, Xiaoying Wang
      First page: 1963
      Abstract: Accurate short-term precipitation forecast is extremely important for urban flood warning and natural disaster prevention. In this paper, we present an innovative deep learning model named ISA-PredRNN (improved self-attention PredRNN) for precipitation nowcasting based on radar echoes on the basis of the advanced PredRNN-V2. We introduce the self-attention mechanism and the long-term memory state into the model and design a new set of gating mechanisms. To better capture different intensities of precipitation, the loss function with weights was designed. We further train the model using a combination of reverse scheduled sampling and scheduled sampling to learn the long-term dynamics from the radar echo sequences. Experimental results show that the new model (ISA-PredRNN) can effectively extract the spatiotemporal features of radar echo maps and obtain radar echo prediction results with a small gap from the ground truths. From the comparison with the other six models, the new ISA-PredRNN model has the most accurate prediction results with a critical success index (CSI) of 0.7001, 0.5812 and 0.3052 under the radar echo thresholds of 10 dBZ, 20 dBZ and 30 dBZ, respectively.
      Citation: Atmosphere
      PubDate: 2022-11-24
      DOI: 10.3390/atmos13121963
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1964: The Dynamic Impacts of COVID-19 Pandemic
           Lockdown on the Multifractal Cross-Correlations between PM2.5 and O3
           Concentrations in and around Shanghai, China

    • Authors: Xing Li, Fang Su
      First page: 1964
      Abstract: Although the outbreak of the COVID-19 pandemic caused serious restrictions on human activities in and around Shanghai, China, the period can be viewed as a helpful experiment to investigate the correlation between PM2.5 and O3 concentrations. In this study, the hourly PM2.5 and O3 series in four cities (i.e., Shanghai, Jiaxing, Nantong and Suzhou) from 27 November 2019 to 23 March 2020 are used. The “seesaw effect” is observed in the study data. The dynamic impacts of the COVID-19 pandemic on the multifractal cross-correlations and the coordinated control degree of PM2.5-O3 are examined in these cities. First of all, the multifractal cross-correlations, multifractality components and dynamic influences of the COVID-19 pandemic on cross-correlations between PM2.5 and O3 in four cities are illustrated. Furthermore, a new quantification index, ζ, evaluating the coordinated control degree of PM2.5-O3 is developed, validated and compared. The multifractal cross-correlation analysis results reveal that the cross-correlations between PM2.5 and O3 in and around Shanghai both before and during the COVID-19 partial lockdown have multifractal characteristics. Moreover, there are weaker multifractal cross-correlation degrees of PM2.5-O3 in four cities during the COVID-19 partial lockdown. The multifractal cause analysis based on stochastic simulation illustrates that the impacts of multifractality due to the nonlinear correlation part are greater than the linear correlation part and the fat-tailed probability distribution part in and around Shanghai. The intrinsic multifractal cross-correlations decreased in all cities during the COVID-19 lockdown. However, the effects of the COVID-19 lockdown on the multifractal cross-correlations are limited from the perspective of intrinsic multifractality. The mean values of ζ in and around Shanghai all increase during the COVID-19 partial lockdown, which indicates that the PM2.5-O3 coordinated control degrees in all four cities become weaker.
      Citation: Atmosphere
      PubDate: 2022-11-24
      DOI: 10.3390/atmos13121964
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1965: A Possible Reconciliation between Eddy
           Covariance Fluxes and Surface Energy Balance Closure

    • Authors: Pierre Durand
      First page: 1965
      Abstract: At the surface of the earth, the available radiative energy Rn is distributed between the ground heat flux and the sensible and latent heat fluxes according to the surface energy balance (SEB) equation. In the past decades, most attempts to measure the individual terms of this equation have revealed a non-closure problem, regardless of the site of observation or period of the year. Today, no definitive answer has been provided to this question. In general, it is suspected that the sensible and latent heat fluxes (H and LvE, respectively) that are calculated with the eddy-covariance technique are underestimated. This paper suggests two additional terms that should be considered in the SEB equation, which are based on thermodynamic considerations. They are directly related to H and LvE and appear to be interesting candidates for explaining (at least in part) the non-closure of the SEB. The distribution of the correction between H and LvE varies as a function of the Bowen ratio B. The correction relative to H is dominant for values of B that are greater than 0.2 and represents more than 80% of the total correction for values greater than unity. The impact of these corrections on the SEB closure was tested on a large set of observations from 24 FLUXNET sites around the world with different vegetation types. The closure defect, which is about 17% in the original dataset, is reduced to about 3% with the proposed corrections.
      Citation: Atmosphere
      PubDate: 2022-11-24
      DOI: 10.3390/atmos13121965
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1966: High Spatial and Temporal Resolution
           Methane Emissions Inventory from Terrestrial Ecosystems in China,
           2010–2020

    • Authors: Yongliang Yang, Yusheng Shi
      First page: 1966
      Abstract: Methane (CH4) is not only an important greenhouse gas next to carbon dioxide (CO2), but also an important chemically active gas. Under the background of climate warming, the measurement of CH4 emissions from terrestrial ecosystems in China is not only very important for exploring the impact of climate change on the ecological environment, but also of great significance for the in-depth study of ecosystem carbon cycling. In this study, we used the Emission-Factor Approach to estimate CH4 emissions from terrestrial ecosystems in China from 2010–2020 and explored the spatial distribution characteristics of CH4 emissions. The estimated CH4 emission inventory of terrestrial ecosystems with 0.05 spatial resolution on monthly time scale is in good agreement with the results of the latest emission inventory. It is estimated that CH4 emissions from terrestrial ecosystems in China are 19.955 Tg yr−1, including 18.61% (3.713 Tg yr−1) from vegetation, 21.47% (4.285 Tg yr−1) from wetlands and 59.92% (11.957 Tg yr−1) from paddy fields, with the largest contribution from paddy fields. The regions with high CH4 emissions from terrestrial ecosystems in China are mainly located in the central, eastern and southeastern regions of China, and show a decreasing trend from southeast to northwest. The CH4 emission from terrestrial ecosystems in China has obvious seasonal variation characteristics, with the lowest emission in January (0.248 Tg month−1) and the highest emission in August (3.602 Tg month−1). The emissions are high in summer and autumn and low in spring and winter. CH4 emissions from terrestrial ecosystems in China showed an overall upward trend from 2010–2020.
      Citation: Atmosphere
      PubDate: 2022-11-25
      DOI: 10.3390/atmos13121966
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1967: Simulation of Piston Effects on Platform
           Screen Doors Considering Air Leakage

    • Authors: Jian Zhang, Jianyao Wang, Qingshan Yang, Qiusheng Li
      First page: 1967
      Abstract: The complex wind effects around platform screen doors (PSDs) caused by train-induced piston wind effect and positive micropressure waves in subway station platforms are investigated. Numerical modeling of the wind field around full-scale PSDs with real gaps under different inflow conditions is developed to analyze the pressure distributions on and around the PSDs and the corresponding recirculation regions in the frontal and rear PSD areas with computational fluid dynamics (CFD) method. An equivalent porous media model is developed to obtain the relationship between the pressure difference and wind velocity based on Darcy–Forchheimer’s Law. It includes a viscosity loss term and an inertial loss term in the simulation of the air leakage flow generated from the PSD gap. The coefficients of these two terms are estimated from the CFD results from the full-scale models. The complicated flow field originated from the gaps is the main cause of the large wind pressure on the PSD, and the flow velocity on the platform may significantly affect the comfort of pedestrians and of the safety design of the PSD system.
      Citation: Atmosphere
      PubDate: 2022-11-25
      DOI: 10.3390/atmos13121967
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1968: Seasonal Variation of Aerosol Composition
           and Sources of Water-Soluble Organic Carbon in an Eastern City of China

    • Authors: Jiameng Li, Linghong Chen, Zhier Bao, Xin Zhang, Huifeng Xu, Xiang Gao, Kefa Cen
      First page: 1968
      Abstract: The mitigation of aerosol pollution is a great challenge in many cities in China, due to the complex sources and formation mechanism of particulate matter (PM) in different seasons. To understand the particular features of pollution in China and formulate different targeted policies, aerosol samples of PM2.5 were collected from January to October of 2018 in Longyou. The temporal profile of the meteorological parameters and the concentrations of water-soluble inorganic ions (WSIs) and organic matter (OM) were characterized. An Aerodyne High-Resolution Time-of-Flight Aerosol Mass Spectrometer (HR-TOF-AMS) was also applied to further analyze the composition of water-soluble organic carbon (WSOC). The sources of WSOC were resolved by positive matrix factorization (PMF) analysis. The origin of air parcels and potential sources of WSOC were analyzed using a backward trajectory and potential source contribution function (PSCF). Winds from the northeast dominated each sampling period, and the relative humidity did not show a significant difference. The results showed that the proportion of OM in PM2.5 was the highest in summer and decreased in spring, autumn, and winter in turn. Four organic aerosol (OA) factors, including a hydrocarbon-like factor, a coal combustion factor, and two oxygenated OA factors, were identified in the WSOC by means of PMF analysis. The hydrocarbon-like OA (HOA) contributed the majority of the WSOC in summer, while the contribution of the coal-combustion OA (CCOA) increased significantly in winter, suggesting the presence of different sources of WSOC in different seasons. The air parcels from the north of China and Zhejiang province contributed to the CCOA in winter, while those from the marine regions in the south and southeast of China mainly contributed to the HOA during spring and summer. The weighted PSCF (WPSCF) analysis showed that the regions of east Zhejiang province were the main contributors, which means that local and regional emissions were the most probable source areas of WSOC. It implied that not only were the emissions control of both local and regional emissions important but also that the transport of pollutants needed to be sufficiently well accounted for to ensure the successful implementation of air pollution mitigation in Longyou.
      Citation: Atmosphere
      PubDate: 2022-11-25
      DOI: 10.3390/atmos13121968
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1969: Probabilistic Forecast of Visibility at
           Gimpo, Incheon, and Jeju International Airports Using Weighted Model
           Averaging

    • Authors: Hee-Wook Choi, Keunhee Han, Chansoo Kim
      First page: 1969
      Abstract: In this study, weighted model averaging (WMA) was applied to calibrating ensemble forecasts generated using Limited-area ENsemble prediction System (LENS). WMA is an easy-to-implement post-processing technique that assigns a greater weight to the ensemble member forecast that exhibits better performance; it is used to provide probabilistic visibility forecasting in the form of a predictive probability density function for ensembles. The predictive probability density function is a mixture of discrete point mass and two-sided truncated normal distribution components. Observations were obtained at Gimpo, Incheon, and Jeju International Airports, and 13 ensemble member forecasts were obtained using LENS, for the period of December 2018 to June 2019. Prior to applying WMA, a reliability analysis was conducted using rank histograms and reliability diagrams to identify the statistical consistency between the ensembles and the corresponding observations. The WMA method was then applied to each raw ensemble model, and a weighted predictive probability density function was proposed. Performances were evaluated using the mean absolute error, the continuous ranked probability score, the Brier score, and the probability integral transform. The results showed that the proposed method provided improved performance compared with the raw ensembles, indicating that the raw ensembles were well calibrated using the predicted probability density function.
      Citation: Atmosphere
      PubDate: 2022-11-25
      DOI: 10.3390/atmos13121969
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1970: Remote-Sensing Drought Monitoring in
           Sichuan Province from 2001 to 2020 Based on MODIS Data

    • Authors: Yuxin Chen, Jiajia Yang, Yuanyuan Xu, Weilai Zhang, Yongxiang Wang, Jiaxuan Wei, Wuxue Cheng
      First page: 1970
      Abstract: In this study, four drought monitoring indices were selected to simulate drought monitoring in the study area and a correlation analysis was conducted using the self-calibrated Palmer Drought Index (sc-PDSI) to screen for the most suitable drought monitoring index for the study area. Then, the spatio-temporal variation characteristics of drought in the study area were discussed and analyzed. The results showed that the Crop Water Stress Index (CWSI) was most suitable for drought monitoring in the Sichuan Province. CWSI had the best monitoring in grasslands (r = 0.48), the worst monitoring in woodlands (r = 0.43) and the highest fitting degree of overall correlation (r = 0.47). The variation of drought time in the Sichuan Province showed an overall trend of wetting and the drought situation was greatly alleviated. In the past 20 years, the dry years in the Sichuan Province were from 2001 to 2007, in which the driest years were 2006 and 2007; 2012–2013 was the transition interval between drought and wet; any year from 2013 to 2020 was a wet year, showing a transition trend of “drought first and then wet”. The spatial distribution of drought was greater in the south than in the north and greater in the west than in the east. Panzhihua City and the southern part of the Liangshan Prefecture were the most arid areas, while the non-arid areas were the border zone between the western Sichuan Plateau and the Sichuan Basin. Looking at the spatial distribution of drought, “mild drought” accounted for the largest percentage of the total area (60%), mainly concentrated in the western Sichuan plateau. The second largest was “drought free” (33%), mostly concentrated in the transition area between the western Sichuan Plateau and the Sichuan Basin (western Aba Prefecture, Ya’an City, Leshan City and northern Liangshan Prefecture). The area of “moderate drought” accounted for a relatively small proportion (6%), mainly concentrated in Panzhihua City, the surrounding areas of Chengdu City and the southern area of the Liangshan Prefecture. The area of severe drought accounted for the least (1%), mostly distributed in Panzhihua City and a small part in the southern Liangshan Prefecture. The drought center ranged from 101.8° E to 103.6° E and 28.8° N to 29.8° N, with the movement trend of the drought center moving from the northeast to the southwest to the northeast.
      Citation: Atmosphere
      PubDate: 2022-11-25
      DOI: 10.3390/atmos13121970
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1971: Air Monitoring of Polychlorinated
           Biphenyls and Organochlorine Pesticides in Eastern Siberia: Levels,
           Temporal Trends, and Risk Assessment

    • Authors: Elena A. Mamontova, Alexander A. Mamontov
      First page: 1971
      Abstract: In this study, we evaluate the long-term and seasonal variations of polychlorinated biphenyls (PCBs), hexachlorobenzene (HCB), α-, γ-hexachlorocyclohexanes (HCH), and p,p’-dichlorodiphenyltrichloroethane (p,p’-DDT) and its metabolites through a passive air sampling method at two (urban and suburban) stations in Eastern Siberia, Russia, in 2011–2017. The median levels of HCB, ∑HCHs, ∑DDTs, ∑PCB39, and ∑PCB6 in the air were 116, 84, 55, 128, and 41 pg/m3 and 83, 21, 11, 52, and 16 pg/m3 at the urban and suburban stations, respectively. PCB and HCH levels in the air of Irkutsk decreased considerably in the 2000s, in comparison to the late 1980s and early 1990s, while an increasing trend was observed for HCB during the 2010s. The seasonality of air concentrations (with summer concentrations higher than winter concentrations) was well exhibited by PCB, HCH, and DDT, but not HCB. Significant correlations were observed between approximately all studied persistent organic pollutants and the average air temperature, quantity of precipitation, and frequency of the prevailing wind direction during the sampling period. The daily doses of PCBs, DDTs, HCHs, and HCB under human exposure by inhalation amounted to 38, 21, 27, and 35 and 17, 6, 7, and 27 pg/kg body weight per day in urban and suburban areas, respectively.
      Citation: Atmosphere
      PubDate: 2022-11-25
      DOI: 10.3390/atmos13121971
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1972: Spatial Clustering of Vegetation Fire
           Intensity Using MODIS Satellite Data

    • Authors: Upenyu Naume Mupfiga, Onisimo Mutanga, Timothy Dube, Pedzisai Kowe
      First page: 1972
      Abstract: This work analyses the spatial clustering of fire intensity in Zimbabwe, using remotely sensed Moderate Resolution Imaging Spectroradiometer (MODIS) active fire occurrence data. In order to investigate the spatial pattern of fire intensity, MODIS-derived fire radiative power (FRP) was utilized. A local indicator of spatial autocorrelation method, the Getis-Ord (Gi*) spatial statistic, was applied to show the spatial distribution of high and low fire intensity clusters. Analysis of the relationship between topographic variables, vegetation type, agroecological zones and fire intensity was done. According to the study's findings, the majority (44%) of active fires detected in the study area in 2019 were of low-intensity (cold spots), and the majority (49.3%) of them occurred in shrubland. High-intensity fires (22%) primarily occurred in the study area’s eastern and western regions. The study findings demonstrate the utility of spatial statistics methods in conjunction with satellite fire data in detecting clusters of high and low-intensity fires (hot spots and cold spots).
      Citation: Atmosphere
      PubDate: 2022-11-25
      DOI: 10.3390/atmos13121972
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1973: FastICA Algorithm Applied on Black Sea
           Water-Level Ultrasound Measurements

    • Authors: Cristian Ghita, Leontin Tuta, Iren-Adelina Moldovan, Constantin Ionescu, Mircea Nicolaescu
      First page: 1973
      Abstract: The parameters influencing the sea level measured with ultrasonic devices that are analyzed in this paper are the air temperature, atmospheric pressure and wind speed. As these variations are independent to each other and to the sea level, they can be removed from the measured sea level by applying a filtering algorithm based on independent component analysis (FastICA), adapted and improved for this application. The sound speed increases with temperature, so an internal temperature sensor is required to compensate for the sound-speed variation. Though this may improve the measurement accuracy, it is not enough to achieve the best results because there is a discrepancy between the internal sensor and the actual environment temperature. For high accuracy measurements, an external temperature sensor is required. In our case, we imported temperature datasets from a weather station, along with other datasets regarding atmospheric pressure and wind speed. The use of these external datasets, along with an algorithm based on principal component analysis (PCA) for error removal and the filtering algorithm based on FastICA for environmental phenomena extraction, allows us to achieve more accurate values for the Black Sea level in Constanta (2017–2020), independent of external influences.
      Citation: Atmosphere
      PubDate: 2022-11-25
      DOI: 10.3390/atmos13121973
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1974: Physical and Chemical Characteristics of
           Dew and Rain in North-West Africa with Focus on Morocco: Mapping Past and
           Future Evolution (2005–2100)

    • Authors: Marc Muselli, Imad Lekouch, Daniel Beysens
      First page: 1974
      Abstract: In the context of global warming and a reduction in fresh water availability, this study presents the evolution of dew, rain and evapotranspiration in the North-West (NW) of Africa. This study is followed by a chemical analysis of dew and rain data in a representative site. The time periods are concerned with the years 2005–2020 using existing data, and years 2020–2100 using the low and high emissions representative concentration pathway scenarios RCP 2.6/8.5 from the coordinated regional climate downscaling experiment database. A continuous decrease in rain precipitation is observed, on the order of −14 mm·decade−1 for the more credible scenario RCP 8.5. The amplitude is maximum on the coast and on the foothills of Atlas. A clear decrease in dew yields (up to 7%) is also observed along a NW/SE axis. It is strongly correlated with a corresponding decrease in relative humidity. Chemical dew and rain data in the representative site of Mirleft correspond to the major cations of Na+ > Ca2+ > Mg2+ > K+, similar to local spring water. The concentrations in rain are about two times less than in dew water. Ionic concentrations are compatible with the World Health Organization standards. The seasonal variations of the ionic concentrations in dew and rain follow a volume dilution dependence. In the future, the expected diminution in dew and rain volumes according to the RCPs 2.6 and 8.5 should increase the dew and rain ionic concentrations.
      Citation: Atmosphere
      PubDate: 2022-11-25
      DOI: 10.3390/atmos13121974
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1975: Aerosol Evolution and Influencing Factor
           Analysis during Haze Periods in the Guanzhong Area of China Based on
           Multi-Source Data

    • Authors: Yanling Zhong, Jinling Kong, Yizhu Jiang, Qiutong Zhang, Hongxia Ma, Xixuan Wang
      First page: 1975
      Abstract: Aerosols suspended in the atmosphere negatively affect air quality and public health and promote global climate change. The Guanzhong area in China was selected as the study area. Air quality data from July 2018 to June 2021 were recorded daily, and 19 haze periods were selected for this study. The Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model was used to simulate the air mass transport trajectory during this haze period to classify the formation process. The spatial distribution of the aerosol optical depth (AOD) was obtained by processing Moderate-resolution Imaging Spectroradiometer (MODIS) data using the dark target (DT) method. Three factors were used to analyze the AOD spatial distribution characteristics based on the perceptual hashing algorithm (PHA): GDP, population density, and topography. Correlations between aerosols and the wind direction, wind speed, and precipitation were analyzed using weather station data. The research results showed that the haze period in Guanzhong was mainly due to locally generated haze (94.7%). The spatial distribution factors are GDP, population density, and topography. The statistical results showed that wind direction mainly affected aerosol diffusion in Guanzhong, while wind speed (r = −0.63) and precipitation (r = −0.66) had a significant influence on aerosol accumulation and diffusion.
      Citation: Atmosphere
      PubDate: 2022-11-25
      DOI: 10.3390/atmos13121975
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1976: Comparison of Planetary Boundary Layer
           Height Derived from Lidar in AD-Net and ECMWFs Reanalysis Data over East
           Asia

    • Authors: Zhijuan Zhang, Ling Mu, Chen Li
      First page: 1976
      Abstract: The planetary boundary layer height is a very important parameter in the atmosphere because it determines the range where the most effective dispersion processes take place, and it serves as a medium for the vertical transport of heat, moisture, and pollutants. The accurate estimation of boundary layer height (BLH) is vital for air pollution prediction. In this paper, the BLH estimated by AD-Net was compared with that from the ECMWFs over East Asia from September 2015 to August 2018. A continuous 24 h BLH estimation from AD-Net generally matched with the aerosol vertical structures. Diurnal and seasonal variation and spatial variation of BLH can also be shown, suggesting the good performance of AD-Net BLH. The comparison of seasonal mean BLH between AD-Net and ECMWFs was conducted at 20 lidar sites. On average, there was an underestimation of the ECMWFs, mostly in summer and winter. A significant disagreement between AD-Net and the ECMWFs was noted, especially over coastal areas and mountain areas. In order to investigate the difference between them, two BLHs were compared under different land cover types and climate conditions. In general, the BLH of the ECMWFs was less than that of AD-Net over most of the land cover types in summer and winter. The smallest differences (0.26 km) existed over water surfaces in winter compared with AD-Net, and the largest underestimation (1.42 km) occurred over grassland surfaces in summer. Similarly, all the BLHs of the ECMWFs were lesser than those of AD-Net under different climatological conditions in summer and winter. The mean difference between AD-Net BLH and ECMWFs BLH was 1.05, 0.71, and 0.48 km for arid regions, semi-arid and semi-wet regions, and wet regions, respectively. The largest underestimation occurred over arid regions in winter, with a value of 1.42 km. The smallest underestimation occurred over wet regions, with a value of 0.27 km. The present research provides better insight into the BLH performance in the ECMWFs reanalysis data. The new continuous PBL dataset can be used to improve the model parameterization of PBL and our understanding of the atmospheric transport of pollutants which affect air quality and human health.
      Citation: Atmosphere
      PubDate: 2022-11-26
      DOI: 10.3390/atmos13121976
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1977: Performance of a Thermodynamic Model for
           Predicting Inorganic Aerosols in the Southeastern U.S.

    • Authors: Bin Cheng, Lingjuan Wang-Li, John Classen, Peter Bloomfield
      First page: 1977
      Abstract: Fine particulate matter (i.e., PM2.5) has gained intensive attention due to its adverse health and visibility degradation effects. As a significant fraction of atmospheric PM2.5, secondary inorganic PM2.5 may be formed through the gas-phase ammonia (NH3) and particle-phase ammonium (NH4+) partitioning. While partitioning of NH3-NH4+ may be simulated using a thermodynamic equilibrium model, disagreement between model predictions and measurements have been realized. In addition, the applicability of the model under different conditions has not been well studied. This research aims to investigate the applicability of a thermodynamic equilibrium model, ISORROPIA II, under different atmospheric conditions and geographic locations. Based upon the field measurements at the Southeastern Aerosol Research and Characterization (SEARCH) network, the performance of ISORROPIA II was assessed under different temperature (T), relative humidity (RH), and model setups in urban and rural locations. The impact of organic aerosol (OA) on the partitioning of NH3-NH4+ was also evaluated. Results of this research indicate that the inclusion of non-volatile cations (NVCs) in the model input is necessary to improve the model performance. Under high T (>10 °C) and low RH (<60%) conditions, ISORROPIA II tends to overpredict nitric acid (HNO3) concentration and underpredict nitrate (NO3−) concentration. The predominance of one phase of semi-volatile compound leads to low accuracy in the model prediction of the other phase. The model with stable and metastable setups may also perform differently under different T-RH conditions. Metastable model setup might perform better under high T (>10 °C) and low RH (<60%) conditions, while stable model setup might perform better under low T (<5 °C) conditions. Both model setups have consistent performance when RH is greater than 83%. Future studies using ISORROPIA II for the prediction of NH3-NH4+ partitioning should consider the inclusion of NVCs, the under/over prediction of NO3−/HNO3, the selection of stable/metastable model setups under different T-RH conditions, and spatiotemporal variations of inorganic PM2.5 chemical compositions.
      Citation: Atmosphere
      PubDate: 2022-11-26
      DOI: 10.3390/atmos13121977
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1978: Comprehensive Evaluation of Environmental
           Air Quality Based on the Entropy Weights and Concentration Variation
           Trends of Pollutants

    • Authors: Hao Zheng, Zhen Yang, Jianhua Yang, Yanan Tao, Linlin Zhang
      First page: 1978
      Abstract: The comprehensive index method has difficulties in evaluating the influence of air pollutant concentration changes on ambient air quality. Thus, a comprehensive evaluation method based on pollutant entropy weights and trend-regulating factors is proposed. According to the information entropy rates of 6 pollutants, the single entropy weight index is proposed by integrating it with the single-quality index, which reflects pollutant variations in evaluation periods. The Spearman’s rank correlation coefficient between the pollutant and Air Quality Index (AQI) is defined as the trend-regulating factor, which indicates the correlations between pollutants and improvements or retrogressions in ambient air quality. The covariance is used to determine the variation trend of ambient air quality, which decides the positive or negative of trend-regulating factor. This method is used to study the ambient air quality rates in 10 cities of Shaanxi Province from 2017 to 2022. The trends of air quality improvements vary among the central, northern, and southern cities. The central cities have more spaces for air quality improvements in terms of PM2.5 and O3. Although prevention efforts have reduced the impacts of pollutants, PM2.5 is still the key factor affecting improvements in ambient air quality in most cities in winter. Additionally, the O3 pollution in summer was not controlled effectively. The contribution to air pollution of O3 increased, on the contrary with the improvement in air quality. The coordinated control of PM2.5 and O3 is still an important method of ambient air quality improvement.
      Citation: Atmosphere
      PubDate: 2022-11-26
      DOI: 10.3390/atmos13121978
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1979: Spatio–Temporal Variation of
           Extreme Climates and Its Relationship with Teleconnection Patterns in
           Beijing–Tianjin–Hebei from 1980 to 2019

    • Authors: Jinjie Wang, Anzhou Zhao
      First page: 1979
      Abstract: Extreme climate events have a significant impact both on the ecological environment and human society, and it is crucial to analyze the spatial–temporal evolutionary trends of extreme climate. Based on the RClimDex model, this study used trend analysis, probability density function, and wavelet coherence analysis to analyze the spatiotemporal variation characteristics of extreme climate indices and their response mechanisms to teleconnection patterns. The results of the study show that: (1) All the extreme precipitation indices, except max 1-day precipitation amount, max 5-day precipitation amount, and extremely wet days increased, with no significant abrupt changes. The extreme warm indices increased and extreme cold indices decreased. The years with abrupt changes were mainly distributed between 1988 and 1997. (2) Spatially, the extreme precipitation indices of most meteorological stations decreased, except for the simple daily intensity index and the number of very heavy precipitation days. The extreme warm indices of most meteorological stations increased, and the extreme cold indices decreased. (3) Except for consecutive dry days, the frequency of extreme precipitation indices increased significantly, the severity and frequency of high-temperature events increased, while the frequency of low-temperature events increased, but the severity decreased. The results of rescaled range (R/S) analysis indicated that the climate in the Beijing–Tianjin–Hebei region will further tend to be warm and humid in the future. (4) The Polar/Eurasia Pattern, the East Atlantic Pattern, the Arctic Oscillation, and the East Atlantic/West Russian Pattern were most closely associated with extreme climate events in the Beijing–Tianjin–Hebei region. The multi-factor combination greatly enhanced the explanatory power of the teleconnection pattern for extreme climates.
      Citation: Atmosphere
      PubDate: 2022-11-27
      DOI: 10.3390/atmos13121979
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1980: Net Ecosystem CO2 Exchange in Mountain
           Grasslands Is Seriously Endangered by the Temperature Increase in the
           Eastern Pyrenees

    • Authors: Mercedes Ibañez, Maria Teresa Sebastià
      First page: 1980
      Abstract: Mediterranean mountain grasslands, including the Pyrenees, are highly vulnerable to climate change, due to the increasing temperatures and heat weaves frequency, among other factors. However, the effects of the increased temperatures on CO2 fluxes in those ecosystems have been barley explored. To address this gap of knowledge, we established the FLUXPYR-ECOFUN micrometeorological flux network, which included three eddy covariance flux stations in grasslands along a management and a climatic gradient (montane to subalpine) at the Pyrenees; we aimed at assessing interactions among environmental and phenological drivers on CO2 fluxes, with special attention at the role of temperature as CO2 flux driver under the different climatic and management conditions across the studied gradient. Our results showed that temperature drove CO2 dynamics along the studied gradient in different ways. At the subalpine grassland net CO2 uptake was linearly enhanced by temperature and CO2 fluxes had not reached a temperature shifting point yet (according to the segmented linear models) at which the net uptake would become CO2 emissions. This suggests that in the short term, and under the incoming enhanced temperatures, sub‑alpine grasslands in the Pyrenees might increase their net CO2 uptake, although the mid long‑term uptake may be compromised. On the contrary, the montane grasslands already presented CO2 emissions at the highest temperatures, most likely driven by a decrease in the greenness and photosynthesis, which suggests that montane grasslands are expected to reduce their CO2 sink capacity under the increasing temperatures. Overall, mountain grasslands in the mid- to long-term in the Pyrenees may experience a reduction in their net CO2 uptake capacity under the current climate change scenario.
      Citation: Atmosphere
      PubDate: 2022-11-27
      DOI: 10.3390/atmos13121980
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1981: Agricultural Production, Renewable Energy
           Consumption, Foreign Direct Investment, and Carbon Emissions: New Evidence
           from Africa

    • Authors: Nneka Maris Chidiebere-Mark, Robert Ugochukwu Onyeneke, Ifeyinwa Josephine Uhuegbulem, Daniel Adu Ankrah, Louis Uchenna Onyeneke, Basil Ngozichukwu Anukam, Maureen Obiageli Chijioke-Okere
      First page: 1981
      Abstract: This paper explores the nexus between agricultural production, renewable energy, foreign direct investment (FDI), and carbon emissions in Africa, where there is limited evidence on the topic. Relying on panel data covering thirty-one African countries obtained from the World Bank World Development Indicators and FAOSTAT databases, we answered the question of whether agricultural production (proxied by livestock production, fertilizer consumption, and land under cereal cultivation), the use of renewable energy, and FDI increase or reduce carbon emissions. Using the panel autoregressive distributed lag model for analysis, our results show that net FDI, fertilizer consumption, livestock production significantly increased carbon emissions, both in the short run and long run. Meanwhile, renewable energy use consumption significantly decreased carbon emissions, both in the short run and long run. Specifically, a 1% increase in net FDI increased total carbon emissions by 0.003% in the short run and by 0.01% in the long run. Renewable energy consumption significantly decreased carbon emissions, both in the short run and long run. A 1% increase in renewable energy consumption decreased total carbon emissions by 0.16% in the short run and by 0.22% in the long run. Additionally, fertilizer consumption and livestock production significantly increased carbon emissions in the short run and long run. A 1% increase in fertilizer consumption increased total carbon emissions by 0.01% in the short run and by 0.04% in the long run, while a 1% increase in livestock production increased total carbon emissions by 0.20% in the short run and by 0.56% in the long run. The findings call for investment in renewable energy technologies and consumption while advocating for large-scale uptake of climate-smart agriculture, and environmentally friendly targeted foreign direct investments on the continent.
      Citation: Atmosphere
      PubDate: 2022-11-27
      DOI: 10.3390/atmos13121981
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1982: Crown Fire Modeling and Its Effect on
           Atmospheric Characteristics

    • Authors: Egor Loboda, Denis Kasymov, Mikhail Agafontsev, Vladimir Reyno, Anastasiya Lutsenko, Asya Staroseltseva, Vladislav Perminov, Pavel Martynov, Yuliya Loboda, Konstantin Orlov
      First page: 1982
      Abstract: The article is concerned with the experimental study of the crown fire effect on atmospheric transport processes: the formation of induced turbulence in the vicinity of the fire source and the transport of aerosol combustion products in the atmosphere surface layer at low altitudes. The studies were carried out in seminatural conditions on the reconstructed forest canopy. It was established that the structural characteristics of fluctuations of some atmosphere physical parameters in the case of a crown fire practically coincide with the obtained earlier values for a steppe fire. The highest concentration of aerosol combustion products was recorded at a height of 10–20 m from the ground surface. It was found that the largest number of aerosol particles formed during a crown fire had a particle diameter of 0.3 to 0.5 µm. As a result of experimental data extrapolation, it is concluded that an excess of aerosol concentration over the background value will be recorded at a distance of up to 2000 m for a given volume of burnt vegetation. It is of interest to further study these factors of the impact of wildfires on atmosphere under the conditions of a real large natural wildfire and determine the limiting distance of aerosol concentration excesses over background values.
      Citation: Atmosphere
      PubDate: 2022-11-27
      DOI: 10.3390/atmos13121982
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1983: Spatial-Temporal Variation of AOD Based
           on MAIAC AOD in East Asia from 2011 to 2020

    • Authors: Ping Wang, Qingxin Tang, Yuxin Zhu, Yaqian He, Quanzhou Yu, Tianquan Liang, Ke Zheng
      First page: 1983
      Abstract: In recent years, atmospheric aerosol pollution has seriously affected the ecological environment and human health. Understanding the spatial and temporal variation of AOD is essential to revealing the impact of aerosols on the environment. Based on the MAIAC AOD 1 km product from 2011 to 2020, we analyzed AOD’s distribution patterns and trends in different time series across East Asia. The results showed that: (1) The annual average AOD in East Asia varied between 0.203 and 0.246, with a decrease of 14.029%. The areas with high AOD values were mainly located in the North China Plain area, the Sichuan Basin area, and the Ganges Delta area, with 0.497, 0.514, and 0.527, respectively. Low AOD values were mainly found in the Tibetan Plateau and in mountainous areas north of 40° N, with 0.061 in the Tibetan Plateau area. (2) The distribution of AOD showed a logarithmic decreasing trend with increasing altitude. Meanwhile, the lower the altitude, the faster the rate of AOD changes with altitude. (3) The AOD of East Asia showed different variations in characteristics in different seasons. The maximum, minimum, and mean values of AOD in spring and summer were much higher than those in autumn and winter. The monthly average AOD reached a maximum of 0.326 in March and a minimum of 0.190 in November. The AOD showed a continuous downward trend from March to September. The highest quarterly AOD values in the North China Plain occurred in summer, while the highest quarterly AOD values in the Sichuan Basin, the Ganges Delta, and the Tibetan Plateau all occurred in spring, similar to the overall seasonal variation in East Asia.
      Citation: Atmosphere
      PubDate: 2022-11-27
      DOI: 10.3390/atmos13121983
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1984: The Characteristics of Light-Duty
           Passenger Vehicle Mileage and Impact Analysis in China from a Big Data
           Perspective

    • Authors: Dong Ma, Xiaomeng Wu, Xin Sun, Shaojun Zhang, Hang Yin, Yan Ding, Ye Wu
      First page: 1984
      Abstract: Vehicle mileage is one of the key parameters for accurately evaluating vehicle emissions and energy consumption. With the support of the national annual vehicle emission inspection networked platform in China, this study used big data methods to analyze the activity level characteristics of the light-duty passenger vehicle fleet with the highest ownership proportion. We found that the annual mileage of vehicles does not decay significantly with the increase in vehicle age, and the mileage of vehicles is relatively low in the first few years due to the run-in period, among other reasons. This study indicated that the average mileage of the private passenger car fleet is 10,300 km/yr and that of the taxi fleet was 80,000 km/yr in China in 2019, and the annual mileage dropped by 22% in 2020 due to the pandemic. Based on the vehicle mileage characteristics, the emission inventory of major pollutants from light-duty passenger vehicles in China for 2010–2020 was able to be updated, which will provide important data support for more accurate environmental and climate benefit assessments in the future.
      Citation: Atmosphere
      PubDate: 2022-11-27
      DOI: 10.3390/atmos13121984
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1985: Characteristics of VOCs Emissions from
           Circulating Water of Typical Petrochemical Enterprises and Their Impact on
           Surroundings

    • Authors: Li Fang, Run Hao, Xiaoqi Xie, Guoao Li, Hailin Wang
      First page: 1985
      Abstract: The petrochemical industry is regarded as the main source of anthropogenic VOCs emissions in China. As one of the main sources of unorganized emissions, circulating water is scarcely studied and reported. In this research, six circulating water systems (LC2X, HGLY, YJ, XJ, LC4X and LC5X) of a typical petrochemical enterprise were selected as targets to characterize VOCs emitted from such unorganized emissions. The results showed that there was a great difference in the VOCs disorganized emissions from the six circulating water systems, among which the main VOCs of HG2X, HGLY and YJ were oxygen-containing VOCs (OVOCs), accounting for about 48.0–81.2%. The main compounds of XJ, LC4X and LC5X were alkynes (89.1%), aromatic hydrocarbons (69.7%) and alkane (50.1%), respectively. TVOCs ranged from 276.0 to 23,009.6 µg·m−3. Based on POC test results, VOCs emissions of the circulating water system were 1237.5 tons, indicating further control was needed. As for their ambient impact, XJ had higher OFP contribution, and the OFP values of the six systems ranged from 823.3 to 145,739.0 µg·m−3, among which the major contributors were aromatic hydrocarbons (0.2–85.1%), OVOCs (0.1–77.2%) and alkynes (1.7–97.6%). In addition, aromatic hydrocarbons showed the largest contribution of the potential of SOA generation, which was more than 88.0%. As far as control was concerned, the replacement of an open cooling tower to closed cooling tower combined with regular POC detection will be an efficient way to control VOCs from such sources.
      Citation: Atmosphere
      PubDate: 2022-11-28
      DOI: 10.3390/atmos13121985
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1986: Analysis of Spatio-Temporal Evolution
           Characteristics of Drought and Its Driving Factors in Yangtze River Basin
           Based on SPEI

    • Authors: Jieru Wei, Zhixiao Wang, Lin Han, Jiandong Shang, Bei Zhao
      First page: 1986
      Abstract: Using a dataset of 114 meteorological stations in the Yangtze River Basin from 1980–2019, the standardized precipitation evapotranspiration index (SPEI) was calculated based on the Penman-Monteith evapotranspiration model for multiple time scales, and the spatial and temporal evolution characteristics and driving factors of drought in the Yangtze River Basin were analyzed by combining spatial and temporal analysis methods as well as geodetector. The main results obtained are as follows: (1) The climate of the Yangtze River Basin is an overall wet trend, and the trend of summer drought is more similar to the annual scale trend. (2) Most areas in the Yangtze River Basin showed mild drought or no drought, and there is little difference in drought condition among the Yangtze River Basin regions. The areas with drought conditions are mainly distributed in the southwest and east of the Yangtze River Basin. (3) There are significant seasonal differences in drought conditions in all regions, and the drought condition is more different in autumn compared to spring, summer and winter. (4) The average annual precipitation and elevation factors are the dominant driving factors of drought in the Yangtze River Basin, and the double-factor interaction has a greater influence on the drought variation in the Yangtze River Basin than the single-factor effect, indicating that the difference of drought condition in the Yangtze River Basin is the result of the combination of multiple factors.
      Citation: Atmosphere
      PubDate: 2022-11-28
      DOI: 10.3390/atmos13121986
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1987: Rainfall Simulations of High-Impact
           

    • Authors: Mary-Jane M. Bopape, Francois A. Engelbrecht, Robert Maisha, Hector Chikoore, Thando Ndarana, Lesetja Lekoloane, Marcus Thatcher, Patience T. Mulovhedzi, Gift T. Rambuwani, Michael A. Barnes, Musa Mkhwanazi, Jonas Mphepya
      First page: 1987
      Abstract: Warnings of severe weather with a lead time longer that two hours require the use of skillful numerical weather prediction (NWP) models. In this study, we test the performance of the Commonwealth Scientific and Industrial Research Organisation (CSIRO) Conformal Cubic Atmospheric Model (CCAM) in simulating six high-impact weather events, with a focus on rainfall predictions in South Africa. The selected events are tropical cyclone Dineo (16 February 2017), the Cape storm (7 June 2017), the 2017 Kwa-Zulu Natal (KZN) floods (10 October 2017), the 2019 KZN floods (22 April 2019), the 2019 KZN tornadoes (12 November 2019) and the 2020 Johannesburg floods (5 October 2020). Three configurations of CCAM were compared: a 9 km grid length (MN9km) over southern Africa nudged within the Global Forecast System (GFS) simulations, and a 3 km grid length over South Africa (MN3km) nudged within the 9 km CCAM simulations. The last configuration is CCAM running with a grid length of 3 km over South Africa, which is nudged within the GFS (SN3km). The GFS is available with a grid length of 0.25°, and therefore, the configurations allow us to test if there is benefit in the intermediate nudging at 9 km as well as the effects of resolution on rainfall simulations. The South African Weather Service (SAWS) station rainfall dataset is used for verification purposes. All three configurations of CCAM are generally able to capture the spatial pattern of rainfall associated with each of the events. However, the maximum rainfall associated with two of the heaviest rainfall events is underestimated by CCAM with more than 100 mm. CCAM simulations also have some shortcomings with capturing the location of heavy rainfall inland and along the northeast coast of the country. Similar shortcomings were found with other NWP models used in southern Africa for operational forecasting purposes by previous studies. CCAM generally simulates a larger rainfall area than observed, resulting in more stations reporting rainfall. Regarding the different configurations, they are more similar to one another than observations, however, with some suggestion that MN3km outperforms other configurations, in particular with capturing the most extreme events. The performance of CCAM in the convective scales is encouraging, and further studies will be conducted to identify areas of possible improvement.
      Citation: Atmosphere
      PubDate: 2022-11-28
      DOI: 10.3390/atmos13121987
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1988: The Effect of Assimilating AMSU-A
           Radiance Data from Satellites and Large-Scale Flows from GFS on Improving
           Tropical Cyclone Track Forecast

    • Authors: Zhijuan Lai, Shiqiu Peng
      First page: 1988
      Abstract: This study aimed to investigate the effect of assimilating either AMSU-A radiance data from satellites, large-scale flows from the Global Forecast System (GFS), or both together, on improving the track forecast of tropical cyclone (TC). The scale-selective data assimilation (SSDA) approach was employed for the assimilation of large-scale GFS flows, while the conventional 3D variational data assimilation (3DVAR) method was used for that of AMSU-A radiance data. The results show that assimilating either AMSU-A radiance data or large-scale GFS flows has a significant improvement on TC track forecast, but the improvement occurs within the first 72 h and after 72 h, respectively. When assimilating both AMSU-A radiance data and large-scale GFS flows, the forecast can take advantage of both data and thus lead to the smallest 5-day mean errors of the track forecast. These results are instructive to future operational TC track forecasting.
      Citation: Atmosphere
      PubDate: 2022-11-28
      DOI: 10.3390/atmos13121988
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1989: Energy Industry Methane Emissions
           Trajectory Analysis in China until 2050

    • Authors: Alun Gu, Sheng Zhou, Shuangqing Xu, Qing Tong
      First page: 1989
      Abstract: Methane (CH4) is an important greenhouse gas. There is increasing attention to CH4 abatement strategies because of its contribution to short-term warming and strong benefits of decreasing CH4 emissions. China greenhouse gas inventory methods are used to predict CH4 emissions from the energy industry and to assess the potentials of CH4 abatement policies and techniques by 2050. The NDC scenario results show using oil and gas as transitional clean energy sources instead of coal will increase CH4 emissions from oil and gas industries at least 70%, but CH4 emissions from the coal industry will decrease 45%, meaning total CH4 emissions from the energy industry will continually decrease at least 30% in 2030 compared with 2020. Energy-related CH4 emissions might peak around 2025, ahead of CO2 emission peaking. CH4 emissions will then decrease slightly and decrease markedly after 2030. Emissions in 2050 are expected to be 32% lower than emissions in 2020. In an extreme scenario, emissions may be 90% lower in 2050 than in 2020. It is suggested that the verification system for the energy industry’s CH4 emission accounting at the national level be improved and CH4 control targets in line with national emission targets and the “14th Five-Year Plan” development stage be formulated.
      Citation: Atmosphere
      PubDate: 2022-11-28
      DOI: 10.3390/atmos13121989
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1990: Investigation of Two Severe Shamal Dust
           Storms and the Highest Dust Frequencies in the South and Southwest of Iran
           

    • Authors: Abbas Ranjbar Saadat Abadi, Nasim Hossein Hamzeh, Maggie Chel Gee Ooi, Steven Soon-Kai Kong, Christian Opp
      First page: 1990
      Abstract: Dust storms create some of the most critical air quality problems in the world; the Middle East, located in the dust belt, suffers substantially from dust storms. Iran, as a country in the Middle East, is affected by dust storms from multiple internal and external sources that mostly originate from deserts in Iraq and Syria (especially the Mesopotamia region). To determine the highest dust loadings in the south and west of Iran, dust frequencies were investigated in the eight most polluted stations in the west, southwest, and southern Iran for a period of 21 years from 2000 to 2021. During the study’s duration, the dust frequency was much higher from 2008 to 2012, which coincided with severe droughts reported in Iraq and Syria; from which, we investigated two severe dust storms (as well as the dust sources and weather condition effects) that took place on 15–17 September 2008 and 1–3 June 2012; we used secondary data from ground measurement stations, and satellite and modeling products. In both cases, horizontal visibility was reduced to less than 1 km at most weather stations in Iran. The measured PM10 in the first case reached 834 μg m−3 at Ilam station in west Iran and the Iran–Iraq borders while the measured PM10 in the second case reached 4947 μg m−3 at Bushehr station in the northern shore of the Persian Gulf. The MODIS true color images and MODIS AOD detected the dust mass over Iraq, southern Iran, and Saudi Arabia in both cases; the AOD value reached 4 in the first case and 1.8 in the second case over the Persian Gulf. During these two severe dust storms, low-level jets were observed at 930 hPa atmospheric levels in north Iraq (2008 case) and south Iraq (2012 case). The output of the NAPPS model and CALIPSO satellite images show that the dust rose to higher than 5 km in these dust storm cases, confirming the influence of Shamal wind on the dust storm occurrences.
      Citation: Atmosphere
      PubDate: 2022-11-28
      DOI: 10.3390/atmos13121990
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1991: Effects of Mixed Cropping of Garden
           Plants with Brassica parachinensis on Remediation of Cr-Polluted Soil in
           Community Garden

    • Authors: Shiyu Cui, Wenbin Liu, Hexian Jin, Qiao Yi, Ying Wang, Dan Liu
      First page: 1991
      Abstract: Industrialization and urbanization have produced large amounts of atmospheric and soil pollutants. Among them, heavy metals are one of the main byproducts that are widely distributed in the atmosphere, water, soil and organisms, which have a great impact on climate. It is of great significance to reduce their enrichment in soil by ecological restoration methods for the sustainable development of urban atmosphere and climate. This study investigated the effects of different garden plants (Festuca arundinacea, Ageratum conyzoides, Trifolium repens) mixed with Brassica parachinensis on plant growth, physiological indexes and Cr (chromium) content in aboveground and underground parts in Cr (the main heavy metal pollution produced by industrialization) contaminated soil. The yield of B. parachinensis was the highest under the mixed cropping mode with T. repens, with the Cr content in edible parts being lower than the standard, suggesting an effective combination of B. parachinensis in community gardens. The mixed cropping of F. arundinacea with Bra decreased B. parachinensis yield. Under the mixed cropping of A. conyzoides, the edible parts of B. parachinensis were aggravated by Cr pollution, which was not recommended for planting. Our results suggest that converting the monoculture mode of vegetables to mixed cropping with garden plants reduced heavy metal pollution of community garden plants and improved soil productivity and environmental quality.
      Citation: Atmosphere
      PubDate: 2022-11-28
      DOI: 10.3390/atmos13121991
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1992: Spatial Variation and Relation of Aerosol
           Optical Depth with LULC and Spectral Indices

    • Authors: Vipasha Sharma, Swagata Ghosh, Sultan Singh, Dinesh Kumar Vishwakarma, Nadhir Al-Ansari, Ravindra Kumar Tiwari, Alban Kuriqi
      First page: 1992
      Abstract: In the current study area (Faridabad, Gurugram, Ghaziabad, and Gautam Buddha Nagar), the aerosol concentration is very high, adversely affecting the environmental conditions and air quality. Investigating the impact of Land Use Land Cover (LULC) on Aerosol Optical Depth (AOD) helps us to develop effective solutions for improving air quality. Hence, the spectral indices derived from LULC ((Normalized difference vegetation index (NDVI), Soil adjusted vegetation index (SAVI), Enhanced vegetation index (EVI), and Normalized difference build-up index (NDBI)) with Moderate Resolution Imaging Spectroradiometer (MODIS) Multiangle Implementation of Atmospheric Correction (MAIAC) high spatial resolution (1 km) AOD from the years 2010–2019 (less to high urbanized period) has been correlated. The current study used remote sensing and Geographical Information System (GIS) techniques to examine changes in LULC in the current study region over the ten years (2010–2019) and the relationship between LULC and AOD. A significant increase in built-up areas (12.18%) and grasslands (51.29%) was observed during 2010–2019, while cropland decreased by 4.42%. A positive correlation between NDBI and SAVI (0.35, 0.27) indicates that built-up soils play an important role in accumulating AOD in a semi-arid region. At the same time, a negative correlation between NDVI and EVI (−0.24, −0.15) indicates the removal of aerosols due to an increase in vegetation. The results indicate that SAVI can play an important role in PM2.5 modeling in semi-arid regions. Based on these findings, urban planners can improve land use management, air quality, and urban planning.
      Citation: Atmosphere
      PubDate: 2022-11-28
      DOI: 10.3390/atmos13121992
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1993: Multi-Scale Spatiotemporal Variations and
           Drivers of PM2.5 in Beijing-Tianjin-Hebei from 2015 to 2020

    • Authors: Nanjian Liu, Song Li, Fengtai Zhang
      First page: 1993
      Abstract: Understanding the spatiotemporal heterogeneity and complex drivers of PM2.5 concentration variations has important scientific value for sustainable urban development. Taking Beijing-Tianjin-Hebei (BTH) as the research area, and using spatial analysis techniques and wavelet methods to explore the spatiotemporal heterogeneity of variations in PM2.5 concentrations, the research shows that in the past six years (2015–2020), the PM2.5 concentrations in the BTH area have a downward trend, and the mean is 59.41 μg/m3; however, the distribution pattern of PM2.5 pollution has changed very little, and the concentration in the south and southwest is still generally high. The continuous wavelet transform revealed that the PM2.5 concentrations in the study area have a short period of about a week to a half a month and a long period dominated by annual cycle. The effect of a single meteorological factor on PM2.5 concentrations is weak, but this effect has obvious spatial differentiation characteristics from coastal to inland and has a double-sided effect due to different geographical locations. The wavelet transform coherence revealed that dewpoint temperature at 2 m (TED), meridional wind at 10 m (WV) and air temperature at 2 m (TEM) are important single meteorological factors that affect the variation of PM2.5 concentrations. The multiple wavelet coherence reveals that in scenarios where two meteorological factors are combined, the combination of TED-mean wind speed (WS) is the best combination to explain the variation in PM2.5 concentrations (AWC = 0.77, PASC = 41%). In the combination of three meteorological factors, TEM-WV-WS explained the variations of PM2.5 concentrations in the BTH region to the greatest degree (AWC = 0.89, PASC = 45%). Finally, the research shows that the variations of PM2.5 concentrations in the BTH region can be better explained by a combination of 2–3 meteorological factors, among which temperature and wind are the key meteorological factors. This research will provide a new window for the multi-scale variation characteristics and multi-factor control relationship of PM2.5 concentrations in the BTH region and provide a new insight for the prevention and control of air pollution.
      Citation: Atmosphere
      PubDate: 2022-11-28
      DOI: 10.3390/atmos13121993
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1994: Air Quality Assessment along
           China-Pakistan Economic Corridor at the Confluence of
           Himalaya-Karakoram-Hindukush

    • Authors: Maqbool Ahmad, Khadim Hussain, Jawad Nasir, Zhongwei Huang, Khan Alam, Samreen Liaquat, Peng Wang, Waqar Hussain, Lyudmila Mihaylova, Ajaz Ali, Suhaib Bin Farhan
      First page: 1994
      Abstract: Recently, analyses of the air quality in Pakistan have received significant interest, especially regarding the impact of air pollutant concentrations on human health. The Atlas of Baseline Environmental Profiling along the China-Pakistan Economic Corridor (CPEC) at five locations in Gilgit-Baltistan (GB) is a major landmark in this regard due to the presence of massive glaciers in the region, which are considered as water reserves for the country. Using various statistical measurements, the air quality was analyzed at the studied geographic locations. Further, air quality was evaluated based on air pollutant data acquired from ambient air monitoring laboratories. For example, 24 h concentrations of particulate matter (PM2.5) were found to range from 25.4 to 60.1 µg/m3, with peaks in the winter season at Gilgit. It was found that PM2.5 values were 1.7 and 1.3 times greater than National Environmental Quality Standards (NEQS) standards only at Gilgit and Chilas, respectively, and 1.5 to 4 times greater than the World Health Organization (WHO) standards at all locations. Similarly, PM2.5 concentrations were found to range from 31.4 to 63.9 µg/m3, peaking at Chilas in summer 2020. The observed values were 1.1 to 1.8 times and 2 to 4.2 times greater than the NEQS and WHO standards, respectively, at all locations. In addition, the average peaks of black carbon (BC) were measured at Gilgit, both in winter (16.21 µg/m3) and summer (7.83 µg/m3). These elevated levels could be attributed to the use of heavy diesel vehicles, various road activities and different meteorological conditions. Pollutants such as carbon monoxide (CO), sulfur dioxide (SO2), nitrogen oxides (NOX) and ozone (O3) were found to be within NEQS and WHO limits. Based on air quality metrics, the effect of PM2.5 on air quality was found to be moderate in Sost, Hunza and Jaglot, while it was at unhealthy levels at Gilgit and Chilas in the winter of 2019; moderate levels were observed at Sost while unhealthy levels were detected at the remaining locations in the summer of 2020. There are no specific guidelines for BC. However, it is associated with PM2.5, which was found to be a major pollutant at all locations. The concentrations of CO, SO2 and O3 were found to be at safe levels at all locations. The major fraction of air masses is received either locally or from transboundary emissions. This study demonstrates that PM2.5 and BC are the major and prevailing air pollutants within the study region, while other air pollutants were found to be within the permissible limits of the WHO and NEQS.
      Citation: Atmosphere
      PubDate: 2022-11-28
      DOI: 10.3390/atmos13121994
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1995: Climate Change Trends in a European
           Coastal Metropolitan Area: Rainfall, Temperature, and Extreme Events
           (1864–2021)

    • Authors: Luis Angel Espinosa, Maria Manuela Portela, José Pedro Matos, Salem Gharbia
      First page: 1995
      Abstract: This paper summarises an updated climate change trends analysis—developed for the period from 1 October 1864 to 30 September 2021 within the scope of a Horizon 2020-funded project to increase climate resilience in European coastal cities—for a representative site of the Lisbon Metropolitan Area (Portugal). By using long ground-based daily records of rainfall and surface temperature at the Lisboa-Geofísico climatological station, the analysis aimed to identify (i) long-term and recent climate trends in rainfall and temperature, (ii) changes in extreme rainfalls, heatwaves, and droughts, and (iii) possible effects of the coupled changes of minimum and maximum daily temperatures (Tmin and Tmax, respectively) on drought development based on the diurnal temperature range (DTR) indicator. To detect these trends and quantify their magnitude, the Mann−Kendall and Sen’s slope estimator tests were implemented. The analysis of the mean annual temperatures indicated that the study area has warmed ∼1.91 °C through the 157 analysed years. Results evidenced statistically significant upward trends in both Tmin and Tmax, and in the number of Tmax heatwave days. In what concerns the extreme hydrological events, the analysis of annual maximum rainfall series and peaks-over-threshold (POT) techniques showed more frequent and intense events in recent years, reaching up to ∼120.0 mm in a single day. With regard to drought, the study proved that the characterisation based on the commonly used standardised precipitation index (SPI) might differ from that based on the standardised precipitation evapotranspiration index (SPEI), as the latter can take into account not only rainfall but also temperature, an important trigger for the development of drought. According to the SPEI index, severe and extreme drought conditions have been more frequent in the last 60 years than in any other recorded period. Finally, a decreasing DTR trend towards the present was found to influence evapotranspiration rates and thus drought characteristics.
      Citation: Atmosphere
      PubDate: 2022-11-28
      DOI: 10.3390/atmos13121995
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1996: Simulations of Organic Aerosol with CAMx
           over the Po Valley during the Summer Season

    • Authors: Barbara Basla, Valentina Agresti, Alessandra Balzarini, Paolo Giani, Guido Pirovano, Stefania Gilardoni, Marco Paglione, Cristina Colombi, Claudio A. Belis, Vanes Poluzzi, Fabiana Scotto, Giovanni Lonati
      First page: 1996
      Abstract: A new sensitivity analysis with the Comprehensive Air Quality Model with Extensions (CAMx) using a traditional two-product scheme (SOAP) and the newer Volatility Basis Set (VBS) algorithm for organic aerosol (OA) calculations is presented. The sensitivity simulations include the default versions of the SOAP and VBS schemes, as well as new parametrizations for the VBS scheme to calculate emissions and volatility distributions of semi- and intermediate-volatile organic compounds. The focus of the simulations is the summer season (May to July 2013), in order to quantify the sensitivity of the model in a period with relatively large photochemical activity. In addition to the model sensitivity, we validate the results with ad hoc OA measurements obtained from aerosol mass spectrometers at two monitoring sites. Unlike winter cases previously published, the comparison with experimental data showed limited sensitivity to total OA amount, with an estimated increase in OA concentrations limited to a few tenths of µg m−3, for both the primary and secondary components. We show that the lack of pronounced sensitivity is related to the effect of the new parametrizations on different emissions sectors. Furthermore, the minor sensitivity to the new parametrizations could be related to the greater partitioning of OA towards the gaseous phase in the summer period, thus reducing the organic fraction in the aerosol phase.
      Citation: Atmosphere
      PubDate: 2022-11-28
      DOI: 10.3390/atmos13121996
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1997: Atmospheric Aerosol Outbreak over
           Nicosia, Cyprus, in April 2019: Case Study

    • Authors: Yuliia Yukhymchuk, Gennadi Milinevsky, Ivan Syniavskyi, Ioana Popovici, Florin Unga, Jean Sciare, Franco Marenco, Michael Pikridas, Philippe Goloub
      First page: 1997
      Abstract: This paper aims to analyze the significant changes in atmospheric aerosol characteristics during the extreme aerosol outbreak event in April 2019 in the atmosphere over Cyprus in the Eastern Mediterranean. We study the aerosol optical depth (AOD), Ångström exponent (AE), single-scattering albedo, refractive index, size, and vertical distribution of aerosol particles during the event of intense aerosol advection in detail. For this purpose, we used the ground-based observations of the sun-photometer AERONET Nicosia station, lidar measurements, and back trajectories of air movements calculated using the Hybrid Single-Particle Lagrangian Integrated Trajectory Model (HYSPLIT). To compare with background aerosol load conditions during the year, the available data of AOD and AE were used from the observations at the Nicosia AERONET site in the 2015–2022 period. On 23–25 April 2019, strong aerosol advection over Nicosia was detected according to lidar and sun-photometer observations. On 25 April 2019, the day with the largest aerosol contamination, the AOD value exceeded 0.9 at λ = 500 nm. Analysis of the optical and microphysical characteristics during the extreme event supported that the aerosol advection consists of mainly Saharan dust particles. This assumption was confirmed by the AOD versus AE variations, single-scattering albedo, refractive index, and size distribution retrievals, as well as lidar data and HYSPLIT backward trajectories, where air masses containing dust particles came mostly from North Africa. The analysis shows that the April 2019 event was one of the strongest aerosol surges that regularly take place in springtime in the atmosphere over Cyprus. The noticeable reduction in the effective radiative forcing caused by increasing aerosol amount during the aerosol dust outbreak was revealed.
      Citation: Atmosphere
      PubDate: 2022-11-29
      DOI: 10.3390/atmos13121997
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1998: Impact of the Destination Weather
           Conditions on Decision and Complaint Behavior of Guests Who Booked
           Vacation Rentals

    • Authors: Harald Zeiss, Kathrin Graw, Andreas Matzarakis
      First page: 1998
      Abstract: Climate and weather conditions at a destination influence the decision regarding what season and which location tourists might travel to. Assuming that the holiday experiences and satisfaction during their stay are influenced by weather and climate as well, this study investigates the question: does bad weather lead to a higher complaint rate among guests who booked vacation rentals' To answer this question, the complaint behavior and the weather parameters temperature, precipitation, wind speed and humidity are examined. The correlations between weather and complaining behavior are proven using the four-field coefficient. The chi-square four-field test is used to subsequently test independence. As a result, a correlation between the weather parameters and complaints cannot be proven based on the applied methods and used data. The four-field coefficient cannot confirm a correlation, as it is close to zero for all four weather parameters. For further investigations, more complaint data are required to obtain more significant results.
      Citation: Atmosphere
      PubDate: 2022-11-29
      DOI: 10.3390/atmos13121998
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1999: Application of BP Neural Networks in Tide
           Forecasting

    • Authors: Haotong Xu, Hongyuan Shi, Shiquan Ni
      First page: 1999
      Abstract: Tidal phenomenon is a significant dynamical phenomenon in the ocean, and the accurate prediction of tide is an important task for various maritime activities. This paper proposes analysis method considering tidal periodicity and apply it to the actual tide prediction. The results prove that this method can solve the delay problem in tide prediction, improve the accuracy of prediction. Compared with the tidal harmonic analysis method, the prediction result of this method is more accurate and requires less data for short-term tidal forecast. Although this study can only provide an accurate forecast for 3 days, it is enough to deal with risks. How to improve the accuracy of long-term prediction is one of the future research directions.
      Citation: Atmosphere
      PubDate: 2022-11-29
      DOI: 10.3390/atmos13121999
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 2000: Characteristics and Meteorological
           Effects of Ozone Pollution in Spring Season at Coastal City, Southeast
           China

    • Authors: Saisai Ren, Xiaoting Ji, Xiangliang Zhang, Meimei Huang, Hong Li, Hong Wang
      First page: 2000
      Abstract: Surface ozone (O3) pollution has become one of the top environmental issues in recent years around the world and can be influenced by meteorological processes on multiple scales. Understanding the meteorological mechanism and contributions of O3 pollution is of great importance for O3 mitigation. In this study, we explored the impacts of meteorological conditions on O3 concentrations in a coastal city in Southeast China, with a particular focus on O3 pollution episodes inspringtime. A significant increase in the O3 pollution ratefrom 2015 to 2020 was observed (41.7% year−1) and the seasonal characteristics of O3 concentrations showed a two-peak pattern. We selected 12 pollution episodes during the springtime of 2015 to 2020 and identified four dominant synoptic weather patterns (SWPs) that could cause O3 pollution. The local meteorological conditions and vertical dynamic structures under different SWPs were analyzed. The results showed that high O3 levels tend to be associated with high temperature, weak wind, low relative humidity, and deep vertical sinking motion. We also established a quantitative linkage between the O3 values and meteorological factors. Based on meteorological conditions, 60.8~80.8% of the variation in O3 can be explained.
      Citation: Atmosphere
      PubDate: 2022-11-29
      DOI: 10.3390/atmos13122000
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 2001: Integrated SWAT-MODFLOW Modeling-Based
           Groundwater Adaptation Policy Guidelines for Lahore, Pakistan under
           Projected Climate Change, and Human Development Scenarios

    • Authors: Rana Ammar Aslam, Sangam Shrestha, Muhammad Nabeel Usman, Shahbaz Nasir Khan, Sikandar Ali, Muhammad Shoaib Sharif, Muhammad Waqas Sarwar, Naeem Saddique, Abid Sarwar, Mohib Ullah Ali, Arfan Arshad
      First page: 2001
      Abstract: Urban aquifers are experiencing increasing pressures from climate change, land-use change, and abstraction, consequently, altering groundwater levels and threatening sustainable water availability, consumption, and utilization. Sustainability in such areas requires the adaptation of groundwater resources to these stressors. Consequently, this research made projections about future climate, land use, and abstraction, examines how these drives will affect groundwater levels, and then proposes adaptation strategies to reduce the impact on Lahore’s groundwater resources. The objectives are achieved using an integrated modeling framework involving applications of Soil Water Assessment Tool (SWAT) and MODFLOW models. The results indicated a projected rise in Tmin by ~2.03 °C and Tmax by ~1.13 °C by 2100 under medium (RCP 4.5) and high-end (RCP 8.5) scenarios, respectively. Future precipitation changes for mid, near and far periods are projected to be −1.0%, 25%, and 24.5% under RCP4.5, and −17.5%, 27.5%, and 29.0% under RCP8.5, respectively. The built-up area in the Lahore division will dominate agricultural land in the future with an expansion from 965 m2 to 3716 km2 by the year 2100 under R1S1 (R2S2) land-use change scenarios (significant at p = 5%). The future population of the Lahore division will increase from 6.4 M to 24.6 M (28.7 M) by the year 2100 under SSP1 (SSP3) scenarios (significant at p = 5%). Groundwater level in bult-up areas will be projected to decline from 185 m to 125 m by 2100 due to increasing groundwater abstraction and expansion in the impermeable surface under all scenarios. In contrast, agricultural areas show a fluctuating trend with a slight increase in groundwater level due to decreasing abstraction and multiple recharge sources under combined scenarios. The results of this study can be a way forward for groundwater experts and related institutions to understand the potential situation of groundwater resources in the Lahore division and implement adaptation strategies to counteract diminishing groundwater resources.
      Citation: Atmosphere
      PubDate: 2022-11-29
      DOI: 10.3390/atmos13122001
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 2002: Health Impacts of Surface Ozone in
           

    • Authors: Suneela Jadoon, Shamyla Nawazish, Zahid Majeed, Ayesha Baig, Syed Majid Bukhari, Abu ul Hassan Faiz, Abdulnoor A. J. Ghanim, Muhammad Irfan, Saifur Rahman, Farid Ullah
      First page: 2002
      Abstract: This research was carried out to analyze variations in indoor and outdoor ozone concentrations and their health impact on local communities of megacities in Pakistan. For indoor ozone measurements, industrial units of an economic zone, Hattar Industrial Estate, Haripur, KPK, Pakistan, were selected. For outdoor ozone measurements, maximum and minimum peaks from different selected stations of three megacities (Islamabad, Abbottabad, and Haripur Hattar) in Pakistan were analyzed for paired comparisons. The tropospheric ozone levels were measured with the help of a portable SKY 2000-WH-O3 meter from December 2018 to November 2019. According to the findings of this investigation, the indoor ozone concentrations at Hattar Industrial Estate exceeded the permissible limit devised by the WHO. The highest concentration (0.37 ppm) was recorded in the month of May in the food industry, while the lowest concentration (0.00 ppm) was recorded in the cooling area of the steel industry in the month of December. For outdoor ozone concentrations, the maximum concentration (0.23 ppm) was detected in Islamabad in the month of March 2019, whereas the rest of year showed comparatively lower concentrations. In Haripur, the maximum concentration (0.22 ppm) was detected in the month of February 2019 and a minimum concentration (0.11 ppm) was found in the month of November 2019. In Abbottabad, the maximum concentration (0.21 ppm) was detected in the month of March 2019 and the minimum concentration was 0.082 ppm. Increasing tropospheric ozone levels might be harmful for local communities and industrial laborers in the winter season because of the foggy weather. In the Abbottabad and Hattar regions, since COVID infection is indirectly related to low temperature and high emission of gases may compromise the respiratory systems of humans. The results of the present study were shared with industrialists to set precautions for ambient air quality and support the adoption of low emission techniques in industries for the safety of labour and nearby residents.
      Citation: Atmosphere
      PubDate: 2022-11-29
      DOI: 10.3390/atmos13122002
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 2003: Air Pollution and Tear Lactoferrin among
           Dry Eye Disease Modifications by Stress and Allergy: A Case–Control
           Study of Taxi Drivers

    • Authors: Wei Hao, Fanxue Kong, Wei Song, Lei Zhang, Xueying Xu, Zhongjuan Ren, Jing Li, Fei Yu
      First page: 2003
      Abstract: Few studies have explored the possible associations between air pollution and tear lactoferrin (Lf) levels, a non-invasive biological marker of ocular surface diseases, among taxi drivers, while none have explored the modifications by stress and allergic tendencies in the relationship. We recruited 1905 taxi drivers with dry eye disease (DED) and 3803 non-DED controls in Liaoning, China, in 2012–2014. After physical examination and questionnaires were recorded, ocular surface was measured and tear Lf was determined by electrophoresis. Air pollutants and humidity were estimated by measured concentrations from monitoring stations. Conditional logistic regression models were employed to examine the associations of air pollutants and humidity with tear Lf levels. Among taxi drivers with stress or allergic tendencies, an IQR (26 μg/m3, 10 μg/m3) increase in PM10 and NO2 levels elevated the adjusted odds ratio by 1.89 (95% CI, 1.19 to 3.08) or 1.77 (95% CI, 1.06 to 2.90); and 2.87 (95% CI, 1.60 to 3.58) or 2.93 (95% CI, 1.64 to 3.83), respectively. In contrast, humidity was inversely associated for taxi drivers with stress [0.51 (95% CI, 0.38 to 0.64)] or allergic tendencies [0.49 (95% CI, 0.11 to 0.84)]; and for taxi drivers without stress [0.33 (95% CI: 0.17, 0.39)] or without allergic tendencies [0.39 (95% CI, 0.19 to 0.59)]. Tear Lf was negatively associated with each quartile of PM10 or NO2 exposure, and low humidity. PM10, NO2, and low humidity were inversely associated with Lf levels, especially for DED taxi drivers with stress and allergic tendencies.
      Citation: Atmosphere
      PubDate: 2022-11-29
      DOI: 10.3390/atmos13122003
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 2004: Correction: Korras-Carraca et al. Global
           Clear-Sky Aerosol Speciated Direct Radiative Effects over 40 Years
           (1980–2019). Atmosphere 2021, 12, 1254

    • Authors: Marios-Bruno Korras-Carraca, Antonis Gkikas, Christos Matsoukas, Nikolaos Hatzianastassiou
      First page: 2004
      Abstract: There was an error in the original publication [...]
      Citation: Atmosphere
      PubDate: 2022-11-29
      DOI: 10.3390/atmos13122004
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 2005: Overview of Radon Flux Characteristics,
           Measurements, Models and Its Potential Use for the Estimation of Radon
           Priority Areas

    • Authors: Igor Čeliković, Gordana Pantelić, Ivana Vukanac, Jelena Krneta Nikolić, Miloš Živanović, Giorgia Cinelli, Valeria Gruber, Sebastian Baumann, Giancarlo Ciotoli, Luis Santiago Quindos Poncela, Daniel Rábago
      First page: 2005
      Abstract: Radon flux measurements provide information about how much radon rises from the ground toward the atmosphere, thus, they could serve as good predictors of indoor radon concentrations. Although there are many different mapping methods with many different input data, radon flux data are generally missing and are not included for the delineation of radon priority areas (RPA). The aim of this literature review is to investigate to what extent radon flux was used, or could be used, for the delineation of RPAs. Numerous factors influencing radon flux were identified, but quantifying their contribution to radon flux measurement still remains a challenge. Different methods and measuring devices were used for the determination of radon flux, thus it is necessary to identify possible inconsistencies in order to harmonise different radon flux measurements. Due to the complexity of radon flux measurements, only two countries were identified to have performed national surveys on outdoor radon, which were of much smaller scale compared to those on indoor radon. A positive correlation between radon flux and radon quantities, such as radon in soil gas and indoor radon, indicates that radon flux could be used as an input parameter for the estimation of RPA. By reviewing radon flux models, it was concluded that up-to-date modelled radon flux maps have reached excellent spatial resolution and will be further improved, hence, they could serve as an input for the estimation and delineation of RPA.
      Citation: Atmosphere
      PubDate: 2022-11-29
      DOI: 10.3390/atmos13122005
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 2006: A Review: Comparison of Approaches to the
           Approval Process and Methodology for Estimation of Ammonia Emissions from
           Livestock Farms under IPPC

    • Authors: Radim Kunes, Zbynek Havelka, Pavel Olsan, Lubos Smutny, Martin Filip, Tomas Zoubek, Roman Bumbalek, Bojana Petrovic, Radim Stehlik, Petr Bartos
      First page: 2006
      Abstract: Ammonia (NH3) emissions have a negative impact on the welfare of breeding animals, human health, and the environment. These influences of modern intensive agriculture have led to numerous protocols, national regulations, and European Directives. Following previous regulatory measures, the Commission Implementing Decision European Union (EU) 2017/302 on 15 February 2017 has established best available technique (BAT) conclusions, under Directive 2010/75/EU of the European Parliament and the Council, for the intensive rearing of poultry and pigs. This applies to intensive poultry and pig producers with a capacity of over 40,000 poultry, 750 sows, or 2000 fattening pigs. Due to the application of this directive, air emissions have been reduced by between 40% and 75% over the last 15 years. The integrated permit monitors the entire environmental burden of the farm on its surroundings (air pollution, water, soil pollution, waste production, energy use). This review aims to provide a critical overview of how member states (including the United Kingdom) are approaching the implementation of IPPC (Integrated Pollution Prevention and Control) and the conclusions of BAT in their legislation and related documents, and how they monitor NH3 emissions from intensive livestock farming. The data for this review were obtained from 2019 to 2020.
      Citation: Atmosphere
      PubDate: 2022-11-29
      DOI: 10.3390/atmos13122006
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 2007: Birch Pollen Deposition and Transport
           along an Altitudinal Gradient in the Bavarian Alps—A Case Study
           Using Gravimetric Pollen Traps in the Pollen Season 2020

    • Authors: Verena Wörl, Johanna Jetschni, Susanne Jochner-Oette
      First page: 2007
      Abstract: There is only little and partially contradicting knowledge on the variation of pollen abundance at different altitudes in mountainous regions. The aim of this work is to gain new insights on the influence of wind and surrounding trees on the deposition and transport of birch (Betula spec.) pollen in the Bavarian Alps, Germany. Data on birch pollen deposition were collected at five sites using gravimetric traps along an altitudinal gradient from Garmisch-Partenkirchen (720 m a.s.l.) to the Environmental Research Station Schneefernerhaus (2650 m a.s.l) in the pollen season 2020. We compared these data with birch pollen concentration derived from a volumetric trap at Schneefernerhaus and with phenological data, i.e., flowering onset times observed at 21 birch trees at different altitudes. Wind data were gathered directly at or near each pollen trap and surrounding birch trees were mapped in the field. Whereas the pollen load was lowest at the highest location, substantially higher values were measured at medium altitudes (1300–1600 m a.s.l.). This can be explained by the pronounced mountain-valley wind system, which ensured the transport of pollen to the corresponding altitudes. We conclude that pollen levels are influenced by topography, local wind systems and the availability of pollen. Pollen levels in complex mountainous environments are therefore not substantially affected by the occurrence of birch trees in the immediate vicinity.
      Citation: Atmosphere
      PubDate: 2022-11-29
      DOI: 10.3390/atmos13122007
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 2008: Establishment of Crop Water Stress Index
           for Sustainable Wheat Production under Climate Change in a Semi-Arid
           Region of Pakistan

    • Authors: Muhammad Imran Khan, Qaisar Saddique, Xingye Zhu, Sikandar Ali, Ali Ajaz, Muhammad Zaman, Naeem Saddique, Noman Ali Buttar, Rao Husnain Arshad, Abid Sarwar
      First page: 2008
      Abstract: The Crop Water Stress Index (CWSI) is a useful tool for evaluating irrigation scheduling and achieving water conservation and crop yield goals. This study examined the CWSI under different water stress conditions for the scheduling of wheat crop irrigation and developed indices using the leaf canopy temperature in Faisalabad, Pakistan. The experiments were conducted using a randomized, complete block design and four irrigation treatments with deficit levels of D0%, D20%, and D40% from the field capacity (FC) and D100% (100% deficit level). The CWSI was determined at pre-heading and post-heading stages through the lower baseline (fully watered crop) and upper limit (maximum stress). These baselines were computed using the air temperature and canopy temperature of plant leaves and the vapor pressure deficit (VPD). The CWSI for each irrigation treatment was calculated and the average seasonal CWSI value for the whole season was used to develop the empirical relationships for scheduling irrigation. The relationships between the air canopy temperatures and the VPD resulted in slope (x) = −0.735 and interception (c) = −0.8731 as well as x = −0.5143 and c = −1.273 at the pre- and post-heading stages, respectively. The values of the CWSI for the treatment at deficit levels of Do%, D20%, D40%, and D100% were found to be 0.08, 0.61, 0.20, and 0.64, respectively. The CWSI values developed in this study can be effectively used to promote better the monitoring of irrigated wheat crops in the region.
      Citation: Atmosphere
      PubDate: 2022-11-29
      DOI: 10.3390/atmos13122008
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 2009: Emulation of a Chemical Transport Model
           to Assess Air Quality under Future Emission Scenarios for the Southwest of
           Western Australia

    • Authors: Stephen Vander Hoorn, Jill S. Johnson, Kevin Murray, Robin Smit, Jane Heyworth, Sean Lam, Martin Cope
      First page: 2009
      Abstract: Simulation outputs from chemical transport models (CTMs) are essential to plan effective air quality policies. A key strength of these models is their ability to separate out source-specific components which facilitate the simulation of the potential impact of policy on future air quality. However, configuring and running these models is complex and computationally intensive, making the evaluation of multiple scenarios less accessible to many researchers and policy experts. The aim of this work is to present how Gaussian process emulation can provide a top-down approach to interrogating and interpreting the outputs from CTMs at minimal computational cost. A case study is presented (based on fine particle sources in the southwest of Western Australia) to illustrate how an emulator can be constructed to simultaneously evaluate changes in emissions from on-road transport and electricity sectors. This study demonstrates how emulation provides a flexible way of exploring local impacts of electric vehicles and wider regional effects of emissions from electricity generation. The potential for emulators to be applied to other settings involving air quality research is discussed.
      Citation: Atmosphere
      PubDate: 2022-11-29
      DOI: 10.3390/atmos13122009
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 2010: Analysis of Changes in Vegetation Index
           during the Rapid Urban Spatial Development Period (1990–2020) in
           Tehran Metropolis, Iran

    • Authors: Shahin Alizadeh Zenouzi, Komali Yenneti, Raziyeh Teimouri, Fatemeh Abbasiyan, Massimo Palme
      First page: 2010
      Abstract: Rapid urbanisation, economic growth, and urban spatial development in developing countries, such as Iran, have resulted in tremendous loss of green cover and associated ecological problems. Any effort to achieve sustainable urban development should be supported by recognising and evaluating the ecological health of vegetation cover. This study investigates vegetation cover reduction and changes in the Tehran Metropolis, Iran and identifies the most important factors influencing the observed changes. The aim of this study is two-fold: first, to assess the spatio-temporal changes in vegetation cover in Tehran between 1990 and 2020, and second, to identify the factors contributing to the changes. The Normalised Difference Vegetation Index (NDVI) is used as an indicator of green cover. The spatial and statistical data used in this study were extracted from Landsat satellite imagery and the last approved Master Plan of Tehran (2006). Geographically Weighted Regression (GWR) and geographical modelling methods were employed to analyse vegetation cover in all municipal districts of the Tehran metropolis. The results show that the vegetation density in the Tehran metropolis decreased significantly (from 38,936.80 hectares to 4663.23 hectares) between 1990 and 2020. The expansion of construction lands and the increase of population density were the most significant factors affecting the reduction in vegetation cover in Tehran. In contrast, the growth of industrial units in the urban areas of Tehran had no significant relationship with vegetation cover. The results of this study can help urban planners understand the significant drivers of vegetation loss and identify appropriate interventions to prevent it.
      Citation: Atmosphere
      PubDate: 2022-11-30
      DOI: 10.3390/atmos13122010
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 2011: Predicting the Environmental Change of
           Carbon Emission Patterns in South Asia: A Deep Learning Approach Using
           BiLSTM

    • Authors: Muhammad Aamir, Mughair Aslam Bhatti, Sibghat Ullah Bazai, Shah Marjan, Aamir Mehmood Mirza, Abdul Wahid, Ahmad Hasnain, Uzair Aslam Bhatti
      First page: 2011
      Abstract: China’s economy has made significant strides in the past three decades. As a direct result of China’s “one belt, one road” (OBOR) initiative, the country’s rate of industrialization and urbanization is currently the fastest in the entire world. This rapid development is largely dependent on the enormous amounts of energy currently being consumed and forms the foundation of the world’s high levels of carbon emissions. It is generally agreed that the production of greenhouse gases, particularly carbon dioxide, is the primary contributor to the current state of climate change. In this paper, a CO2 emission prediction model based on Bi-LSTM is constructed. In order to conduct empirical tests on the model, this study uses data from South Asian countries and China from 2001 to 2020. China’s CO2 emissions from 2022 to 2030 were predicted along with those of other countries in order to study the combined effects of the scientific and technological progress, industrial structures, and energy structure factors affecting CO2 emissions. When compared with the LSTM and GRU methods, the Bi-LSTM model’s results produced lower MAE, MSE, and MAPE values, indicating that it performs better. According to the findings, carbon emissions represent a significant problem that will become much worse in the future due to China and India’s high emissions, particularly in the next 10 years, if the government does not implement policies that help reduce those emissions.
      Citation: Atmosphere
      PubDate: 2022-11-30
      DOI: 10.3390/atmos13122011
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 2012: A Dynamic Large-Scale Driving-Force to
           Control the Targeted Wind Speed in Large Eddy Simulations above Ocean
           Waves

    • Authors: Liad Paskin, Boris Conan, Yves Perignon, Sandrine Aubrun
      First page: 2012
      Abstract: We performed large eddy simulations to study micro-scale wind–wave interactions under undisturbed freestream conditions. We identified that standard approaches lead to wave-related disturbances at the top boundary. Therefore, we developed a numerical strategy to maintain an undisturbed wind speed at the top, while considering arbitrary waves at the bottom. In a broader context, the method is capable of controlling the wind speed at any height in the domain, and may also be used to enhance atmospheric simulations over land. The method comprises an evolution equation that controls the dynamic evolution of the large-scale driving force, representing the geostrophic forcing from the meso- to the micro-scales. In flat-bottom applications, this guided the reference freestream velocities towards a certain target; convergence to a steady state regime was favored and self-similarity was ensured. In wavy bottom applications considering the prescription of a monochromatic wave, we were able to maintain a quasi-steady wind speed close to the target on the freestream. The wave-induced disturbances were then investigated as functions of varying wave age conditions. We performed a systematic wave age variation study by varying the reference wind speed, and evaluated wave-induced disturbances in the velocity, normal, and shear stress profiles.
      Citation: Atmosphere
      PubDate: 2022-11-30
      DOI: 10.3390/atmos13122012
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 2013: Dry and Wet Changes and Vegetation
           Time-Delay Responses in Western China

    • Authors: Jie Chen, Bo Zhang, Rongpeng Yao, Xiaofang Zhang, Yaowen Zhang, Jing Zhou
      First page: 2013
      Abstract: Due to global warming and other climate changes, it is increasingly important to study the response of regional environmental changes and dynamic changes in vegetation to climate change. Based on meteorological data from the last 60 years, this paper calculates the humidity index of western China under a wide range of long time series in different regions and explores the cross-correlation effect between series by offering a comparison with NDVI data, to analyze the cross-correlation between wet and dry changes and changes in vegetation in western China on a spatial scale. The results show that the spatial distribution of the interdecadal humidity index is different between different regions in western China. For example, the semi-arid and the semi-humid zones of the Weihe River region exhibit significant changes, while the Xinjiang and Qinghai–Tibet regions show a trend of constant wetness, on the whole, and the Sichuan and Yunnan–Guizhou regions are relatively humid and the distribution of wetness and dryness is relatively stable. The distribution of high and low values of the humidity index is very obvious and consistent with that of the distribution of desert bare land and precipitation in western China. In common with the distribution in the humidity index, the maximum correlation number between the NDVI and the humidity index in the whole western region is also significantly different in spatial distribution. There is a positive correlation between the NDVI and the humidity index in 99% of the study area. However, the delay in response time of the NDVI to changes in the humidity index in each region is inconsistent. For example, changes in the NDVI lag changes in the humidity index in the Menggan region by generally either 2 months or 5 months, while in the Sichuan region the delay in response time is generally 3 months. The variation and trend in dry and wet areas are closely related to the geographical location, climate zone, and topographic terrain, which may be the reason for the differences in the distribution of vegetation types and the response time to dry and wet changes. There is significant interaction between the humidity index and the vegetation type or precipitation distribution in western China. The positive correlation between the NDVI and the humidity index means that the positive effect is more sensitive, and the response of grassland is the most sensitive in the ecosystem.
      Citation: Atmosphere
      PubDate: 2022-11-30
      DOI: 10.3390/atmos13122013
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 2014: Measuring and Regression Modeling of
           Gas–Particle Partitioning of Atmospheric Oxidized Mercury at a
           Coastal Site in Shanghai

    • Authors: Deming Han, Shuxiao Wang, Qingru Wu, Yi Tang, Minneng Wen
      First page: 2014
      Abstract: Gas–particle partitioning between reactive gaseous mercury (RGM) and particle bound mercury (PBM) controls the fates of atmospheric oxidized mercury (namely reactive mercury, RM). We conducted a long-term observations of gaseous elemental mercury (GEM), RGM, PBM, and auxiliary parameters in Chongming Island, Shanghai, China, to understand the characteristics of speciated mercury and their gas–particle partitioning behaviors. The entire average abundances of GEM, RGM and PBM were 2.12 ± 0.94 ng/m3, 14.75 ± 9.94 pg/m3 and 21.81 ± 30.46 pg/m3, respectively. An observation data dependent empirical gas–particle partitioning relationship of partitioning coefficient and temperature log(1/KP) = −2692.20/T + 10.57 was obtained, and it varied in different season being by the temperature. To further evaluate the influences of temperature, particulate matter (PM), relative humidity on RGM and PBM partitioning process, the particulate fraction (φ = PBM/(PBM + RGM)) was used in this study. High φ values (φ > 0.8) mainly occurred at low temperature domain (<281 K), and high PM concentration enhanced this influence. In addition, high relative humidity shifts RGM from atmosphere partitioning to PBM in response to the diurnal valley φ values at 13:00–16:00 in the summer. Photochemical reactions were proposed to play important roles on partitioning processes between RGM and PBM. This study will benefit for the understanding of oxidized mercury fate and influencing factors in the complex atmospheric pollutants.
      Citation: Atmosphere
      PubDate: 2022-11-30
      DOI: 10.3390/atmos13122014
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 2015: Spatiotemporal Characteristics and
           Influencing Factors of Sunshine Duration in China from 1970 to 2019

    • Authors: Tang, Zhu, Wei, Zhao, Wu, Tian
      First page: 2015
      Abstract: In order to alleviate global warming and the energy crisis, it is of great significance to develop and utilize solar energy resources. Sunshine duration (SD) is considered to be the best substitute for solar radiation and a key factor in evaluating solar energy resources. Therefore, the spatial and temporal characteristics of SD and the reasons for its changes have received extensive attention and discussion. Based on the data of 415 meteorological stations from 1970 to 2019, this paper uses linear trend analysis, Mann–Kendall mutation analysis, the Hurst index, empirical orthogonal decomposition, correlation analysis and partial correlation analysis to analyze the spatiotemporal characteristics of SD and its relationship with influencing factors. The results show that the annual SD in China shows a downward trend, with a climate trend rate of −37.93 h/10a, and a significant decline from 1982 to 2019. The seasonal SD shows a downward trend, and the downward trend is most obvious in summer. The annual and seasonal SD will still show a downward trend in the future. The spatial distribution of SD not only has an overall consistent distribution but also takes the Yellow River from Ningxia to Shandong as the boundary, showing a north–south opposite distribution. Annual SD has a significant positive correlation, a significant negative correlation, a positive correlation and a negative correlation with wind speed, precipitation, temperature and relative humidity, respectively, and it is most closely related to wind speed and precipitation. In addition, the change in SD may also be related to human activities.
      Citation: Atmosphere
      PubDate: 2022-11-30
      DOI: 10.3390/atmos13122015
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 2016: Research on Outdoor Thermal Comfort of
           Children’s Activity Space in High-Density Urban Residential Areas of
           Chongqing in Summer

    • Authors: Han Gu, Qiqi Hu, Dongsheng Zhu, Jie Diao, Ying Liu, Mengmeng Fang
      First page: 2016
      Abstract: Children’s activity spaces in communities designed for children’s recreation are related to children’s safety and physical health. Outdoor thermal comfort of children’s activity spaces in high-density urban residential areas is the key to children’s use in summer. To this end, meteorological measurements and questionnaires were conducted to better understand children’s outdoor thermal comfort in summer, and children’s outdoor thermal comfort was evaluated using the universal thermal climate index (UTCI) for children’s activity spaces in high-density residential areas of Chongqing, China. We draw four conclusions: (1) Different landscape types of children’s activity spaces have different effects on outdoor thermal comfort, and gender differences also affect outdoor thermal comfort in the same type of children’s activity space. (2) Global radiation (G) and air temperature (Ta) were the primary meteorological factors influencing children’s thermal sensations. (3) Outdoor thermal comfort of children’s activity spaces in high-density urban residential areas was inferior overall. (4) Neutral UTCI (NUTCI) for male and female children in Chongqing were 22.2 °C and 21.8 °C, NUTCI ranges (NUTCIR) were 18.4–26.1 °C (male) and 16.2–27.3 °C (female), and acceptable UTCI ranged from 23.2 to 39.1 °C (male) and 22.8 to 40.3 °C (female). The results provide guidance for landscape architects and urban planners in the Chongqing area to create comfortable outdoor spaces for children, improve their physical activity levels, and promote their physical and mental health.
      Citation: Atmosphere
      PubDate: 2022-11-30
      DOI: 10.3390/atmos13122016
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 2017: Outdoor Microplastic Analysis Using Inlet
           Filters from an NOx Regulatory Air Quality Monitoring Device

    • Authors: Lauren C. Jenner, Rameez Raja Kureshi, David White, Emma Chapman, Laura R. Sadofsky, Jeanette M. Rotchell
      First page: 2017
      Abstract: Atmospheric microplastics (MPs) are a ubiquitous environmental contaminant of emerging concern. Sampling methods provide information relating to surface area concentration and MP characteristics, without direct comparison with routinely measured standard air quality parameters. This study analysed 6 active air samples generated by a local authority as part of their routine air quality monitoring activities. Continuous sampling totalled 10 months, within the city centre of Kingston-upon-Hull. By using μFTIR analysis, levels of total particles detected using the NOx inlet filters ranged from 5139 ± 2843 particles m−2 day−1, comprising 1029 ± 594 MPs m−2 day−1. The controls displayed a mean level of 2.00 ± 3.49 MPs. The polymers nylon (32%) and polypropylene, PP (22%) were the most abundant. Small fragments of 47.42 ± 48.57 μm (length) and 21.75 ± 13.62 μm (width) were most common. An increase in MP levels during April 2020 coincided with an increase in PM10 levels. This study used robust procedures to measure MPs in the air by exploiting existing air quality monitoring equipment. Knowing the levels, types, and characteristics of MPs can inform toxicity studies to provide more environmentally relevant exposures, which is urgent now that MPs have been reported in human lung tissue.
      Citation: Atmosphere
      PubDate: 2022-11-30
      DOI: 10.3390/atmos13122017
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 2018: Climate Change and Its Impact on the
           Agricultural Calendar of Riverine Farmers in Médio Juruá,
           Amazonas State, Brazil

    • Authors: Vasconcelos, Veiga, Silva, Guimarães, Brito, Santos, Lopes, Lima, Oliveira
      First page: 2018
      Abstract: The labor relationship developed by the Amazonian riverside dwellers is weakened due to changes in temperature, the flood pulse, the ebb tide of the rivers, and precipitation. In this context, this research aimed to evaluate the impacts of climate change on the socio-biodiversity chains in the region of Médio Juruá-Amazonas. Collections were carried out in two communities located in the Sustainable Development Reserve (RDS) Uacari, in July 2022, through participatory workshops. The communities affirm that the extreme flood events of the Juruá River are more intense in recent years, both concerning the extreme levels of the river and in periodicity and speed of flooding. The large floods have impacted the productive calendar, generating losses for farmers. In addition, rubber trees and cassava plantations have been dying with the large floods, and oil seeds are being carried by the water before harvest. The physical data of the Juruá River shows a trend of increasing extreme floods over the last 40 years for the period November to April, highlighting the years 2013 to 2015 and 2021 with the largest positive anomalies. Farmers have adapted their calendars, modified some planting areas to locations with higher altitudes and farther from the river banks, and have sought new rubber matrices. The results point to the need for mitigation and adaptation measures promoted by local governments.
      Citation: Atmosphere
      PubDate: 2022-11-30
      DOI: 10.3390/atmos13122018
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 2019: Fractional Importance of Various Moisture
           Sources Influencing Precipitation in Iran Using a Comparative Analysis of
           Analytical Hierarchy Processes and Machine Learning Techniques

    • Authors: Mojtaba Heydarizad, Nathsuda Pumijumnong, Rogert Sorí, Pouya Salari, Luis Gimeno
      First page: 2019
      Abstract: Studying the moisture sources responsible for precipitation in Iran is highly important. In recent years, moisture sources that influence precipitation across Iran have been studied using various methods. In this study, moisture uptake rate from individual sources that influences precipitation across Iran has been determined using the (E − P) values obtained by the FLEXPART model for the 1981–2015 period. Then, moisture uptake rate from individual sources has been used as independent parameters to investigate the fractional importance of moisture sources that influence precipitation in Iran using analytical hierarchy process (AHP) as well as machine learning (ML) methods including artificial neural networks, Decision Tree, Random Forest, Gboost, and XGboost. Furthermore, the average annual precipitation in Iran was simulated using ML methods. The results showed that the Arabian Sea has a dominant fractional influence on precipitation in both wet (November to April) and dry (May to October) periods. Simulation of precipitation amounts using the ML methods presented accurate models during the wet period, whereas the developed models for the dry period were not adequate. Finally, validation of the accuracy of the ML models using RMSE and R2 values showed that the models developed using XGboost had the highest accuracy.
      Citation: Atmosphere
      PubDate: 2022-12-01
      DOI: 10.3390/atmos13122019
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 2020: Effect of Window Openable Area and
           Shading on Indoor Thermal Comfort and Energy Efficiency in Residential
           Buildings with Various Operating Modes

    • Authors: Jiandong Ran, Ke Xiong, Mei Dou, Huizhi Zhong, Ya Feng, Mingfang Tang, Zhenjing Yang
      First page: 2020
      Abstract: Solar heat gain and natural ventilation cooling of the indoor environment in buildings are highly influenced by the shading and openable area of windows. In addition to the ambient condition, the Heating, ventilation and air conditioning (HVAC) system’s mode of use can affect the windows’ performance, especially when multiple modes are used in combination (mixed-mode). Although many studies have investigated the mixed-mode application, their conditions for starting/shutting down HVAC equipment and controlling window ventilation are inconsistent with the relevant codes. Here, we propose a mixed-mode operation that resolves the gap between the air conditioning operation temperature and the adaptive comfort upper temperature. It investigates residential buildings’ indoor thermal environment and energy efficiency by combining the effective ventilation opening area ratio (REV) and shading design. Simulation results show that our mixed-mode can reduce the indoor overheating hours by about 50% and the building’s energy consumption by about 50%. We thereby conclude that the openable area of exterior windows in residential buildings in Chongqing should not be less than 10% of the room’s floor axis area where the exterior windows are located. In general, our study expands the existing knowledge of passive energy-saving measures and provides a method for further research on building energy design in hot summer and cold winter regions.
      Citation: Atmosphere
      PubDate: 2022-12-01
      DOI: 10.3390/atmos13122020
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 2021: SPI-3 Analysis of Medjerda River Basin
           and Gamma Model Limits in Semi-Arid and Arid Contexts

    • Authors: Zoubeida Kebaili Bargaoui, Sabrine Jemai
      First page: 2021
      Abstract: The Standardized Precipitation Index SPI-3, associated with three months of rainfall accumulation, is a drought index for detecting immediate drought impacts. The two-parameter gamma distribution, recommended by the World Meteorological Organization as the underlying distribution for estimating SPI, has shown limits in semi-arid and arid conditions with respect to the normality test for the resulting SPI series. Our purpose was to evaluate its relevance for the Medjerda River Basin (Tunisia), a transboundary basin where the climate classes are temperate, dry, and hot summer, as well as arid hot desert and arid hot steppe. When analyzing the time series of 144 stations from 1950 to 2018, we found that the normality Shapiro–Wilk test was rejected in 17% of the cases, which agreed with the literature review results. The transition season (August, September, and October) had the highest rejection percentage. Three factors were identified to explain the deviation from normality. We first identified the rate of occurrence of completely dry (zero rain) three-month periods. The higher the rate of occurrence was, the higher that the probability was of its rejecting the normality test. High sample skewness was the second influencing factor. Finally, a series where the Grubbs’ test of identifying outliers was rejected was more likely to show the SPI-3 series deviating from normality.
      Citation: Atmosphere
      PubDate: 2022-12-01
      DOI: 10.3390/atmos13122021
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 2022: Effect of Prenatal Exposure to Household
           Air Pollution from Multiple Sources on Risk of Preterm Birth

    • Authors: Xin-Chen Liu, Esben Strodl, Li-Hua Huang, Bing-Jie Hu, Wei-Qing Chen
      First page: 2022
      Abstract: Prenatal exposure to air pollution has been suggested as a major risk factor for preterm birth (PTB). This study aimed to explore the independent and joint effects of prenatal exposure to multiple household air pollution (HAP) sources on PTB. This study involved 63,038 mother–child pairs from the Longhua Child Cohort Study in 2017. A series of logistic regression analyses on associations of environmental tobacco smoke (ETS), cooking oil fumes (COFs), burning mosquito coils (BMCs), indoor burning incense (IBI) and household renovation (HR) with PTB were conducted to evaluate their independent and joint effects on PTB. Compared to mothers without exposure, prenatal exposure to each individual HAP source increased the PTB risk. Moreover, the PTB risk increased incrementally with the number of prenatal HAP exposure sources. Finally, we found a synergistic interaction effect from COFs and HR on risk of PTB. Our results suggest that prenatal exposure to five sources of HAP might increase the risk of PTB, with the risk increasing with the number of exposure sources and synergistic interaction effects between some pollution sources.
      Citation: Atmosphere
      PubDate: 2022-12-01
      DOI: 10.3390/atmos13122022
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 2023: Twelve-Year Cycle in the Cloud Top Winds
           Derived from VMC/Venus Express and UVI/Akatsuki Imaging

    • Authors: Igor V. Khatuntsev, Marina V. Patsaeva, Dmitrij V. Titov, Ludmila V. Zasova, Nikolay I. Ignatiev, Dmitry A. Gorinov
      First page: 2023
      Abstract: We present joint analysis of the UV (365 nm) images captured by the cameras on board ESA’s Venus Express and JAXA’s Akatsuki spacecraft. These observations enabled almost continuous characterization of the cloud top circulation over the longest period of time so far (2006–2021). More than 46,000 wind vectors were derived from tracking the UV cloud features and revealed changes in the atmospheric circulation with the period of 12.5 ± 0.5 years. The zonal wind component is characterized by an annual mean of −98.6 ± 1.3 m/s and an amplitude of 10.0 ± 1.6 m/s. The mean meridional wind velocity is −2.3 ± 0.2 m/s and has an amplitude of 3.4 ± 0.3 m/s. Plausible physical explanations of the periodicity include both internal processes and external forcing. Both missions observed periodical changes in the UV albedo correlated with the circulation variability. This could result in acceleration or deceleration of the winds due to modulation of the deposition of the radiative energy in the clouds. The circulation can be also affected by the solar cycle that has a period of approximately 11 years with a large degree of deviation from the mean. The solar cycle correlated with the wind observations can probably influence both the radiative balance and chemistry of the mesosphere. The discovered periodicity in the cloud top circulation of Venus, and especially its similarity with the solar cycle, is strongly relevant to the study of exoplanets in systems with variable “suns”.
      Citation: Atmosphere
      PubDate: 2022-12-01
      DOI: 10.3390/atmos13122023
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 2024: Sensitivity of Ozone Formation in Summer
           in Jinan Using Observation-Based Model

    • Authors: Chenxi Xu, Xuejuan He, Shida Sun, Yu Bo, Zeqi Cui, Zhanchao Zhang, Hui Dong
      First page: 2024
      Abstract: According to online monitoring data on atmospheric ozone and the pollution characteristics of its precursors obtained in Jinan in June 2021, we analyzed different sites: urban sites (city monitoring station, Quancheng Square), an industrial park site (oil refinery), and a suburban site (Paomaling). The relative incremental reactivity of different precursors was calculated using a photochemical observation-based model to explore the sensitivity of O3 generation at each site and to draw a curve using the empirical kinetics modeling approach. The PMF model was used to analyze the origin of volatile organic compounds (VOCs) pollution in Jinan. The results showed that the concentration of O3 at the industrial park was higher than that in the urban area in Jinan, which may be related to the fact that ozone precursor concentrations in the industrial park were significantly higher than those in the urban area (the AVOCs concentration at the industrial park site was 56.9 ppbv, approximately twice that of the urban site), and there are emission peaks at night; alkanes, oxygenated compounds, and halogenated hydrocarbons were the main components of the AVOCs, and olefins, alkanes, and aromatic hydrocarbons were the main active components in Jinan. The O3 generation in urban areas generally occurred in the VOCs-sensitive zones, while the O3 generation in the other areas occurred in the VOCs-NOx transition zone; there was a clear diurnal variation in the sensitivity of the industrial park, with the site being in the obvious VOCs-sensitive zone from nighttime to morning hours and shifting to the VOCs-NOx transition zone in the afternoon hours; the relative incremental reactivity (RIR) value of AVOCs for O3 generation in Jinan was the largest, and olefins were the most sensitive component of O3. The AVOCs in Jinan mainly originated from motor vehicle exhaust, oil and gas volatilization, industrial emissions, and solvent use, and ozone prevention and control in summer should strengthen the control of these sources.
      Citation: Atmosphere
      PubDate: 2022-12-01
      DOI: 10.3390/atmos13122024
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 2025: Increase in the Intensity of
           Air–Sea Coupling in the Key ENSO Region during 1955–2020

    • Authors: Zhiqing Liu, Jianjun Xu
      First page: 2025
      Abstract: The El Niño and Southern Oscillation (ENSO), a phenomenon of air–sea coupling in the tropical Pacific, has strong response to global climate change. In this study, the primary region where ENSO occurred during the period 1955–2020 was selected as the key ENSO region, and the changes in air–sea coupling in this region were explored. The New Southern Oscillation Index (NSOI), modified from the previous Southern Oscillation Index, represents atmospheric changes, and the Niño-3.4 index represents oceanic changes. The absolute value of the running correlation coefficient between the Niño-3.4 index and NSOI in the 121-month time window was defined as the Intensity of Air–Sea Coupling (IASC) in the key ENSO region. The results showed that the IASC has significantly increased, with a confidence level of 95%, during the period 1955–2020, and the range where the correlation coefficient between the Niño-3.4 index and the sea level pressure anomaly over the key ENSO region was greater than 0.6 has evidently expanded in the context of global warming, which corresponded to the increase in IASC. Moreover, the coupling positions of sea surface temperature and wind anomalies changed, tending to the east of the equatorial Pacific during 1977–1998, and to the west during 1999–2020.
      Citation: Atmosphere
      PubDate: 2022-12-01
      DOI: 10.3390/atmos13122025
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 2026: Burden of Natural-Cause and
           Cause-Specific Mortality Associated with Long-Term Exposure to PM2.5: A
           Case Study in Attica Region, Greece

    • Authors: Paraskevi Begou, Pavlos Kassomenos
      First page: 2026
      Abstract: In this study, the AirQ+ software proposed by the World Health Organization (WHO) was applied in order to assess the health endpoints associated with the long-term exposure to PM2.5 in Attica Region, Greece. For this purpose, we analyzed the daily average concentrations of PM2.5 registered by the air quality monitoring stations in the region, from 1 January 2007 to 31 December 2018. Although there was a decreasing trend in PM2.5 concentrations levels, the levels of PM2.5 exceeded the AQG (Air Quality Guidelines) limit value (annual value: 5 μg/m3) established by the WHO. The findings revealed that the burden of mortality (from all-natural causes) at people above 30 years old associated with PM2.5 exposure was 4752 [3179–6152] deaths in 2007 and 2424 [1598–3179] deaths in 2018. In general, the attributable mortality from specific causes of deaths (e.g., lung cancer, IHD (ischemic heart diseases) and stroke) in people above 25 years old decreased between the years, but the mortality from COPD (chronic obstructive pulmonary diseases) was stable at 146 [79–220] deaths in 2007 and 147 [63–244] deaths in 2018. We also found differences in mortality cases from IHD and stroke among the age groups and between the years 2007 and 2018.
      Citation: Atmosphere
      PubDate: 2022-12-02
      DOI: 10.3390/atmos13122026
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 2027: Evidence for the Magnetoionic Nature of
           Oblique VHF Reflections from Midlatitude Sporadic-E Layers

    • Authors: Chris Deacon, Cathryn Mitchell, Robert Watson, Ben A. Witvliet
      First page: 2027
      Abstract: Mid-latitude sporadic-E (Es) is an intermittent phenomenon of the lower E region of the ionosphere. Es clouds are thin, transient, and patchy layers of intense ionization, with ionization densities which can be much higher than in the background ionosphere. Oblique reflection of radio signals in the very high frequency (VHF) range is regularly supported, but the mechanism for it has never been clearly established—specular reflection, scattering, and magnetoionic double refraction have all been suggested. This article proposes using the polarization behaviour of signals reflected from intense midlatitude sporadic-E clouds as an indicator of the true reflection mechanism. Results are presented from a measurement campaign in the summer of 2018, which gathered a large amount of data at a receiving station in the UK using 50 MHz amateur radio beacons as signal sources. In all cases the signals received were elliptically polarized, despite being transmitted with linear polarization; there were also indications that polarization behaviour varied systematically with the orientation of the path to the geomagnetic field. This represents, for all the examples recorded, clear evidence that signals were reflected from midlatitude Es by magnetoionic double refraction.
      Citation: Atmosphere
      PubDate: 2022-12-02
      DOI: 10.3390/atmos13122027
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 2028: The Geometry and Charge of the Streamer
           Bursts Generated by Lightning Rods under the Influence of High Electric
           Fields

    • Authors: Vernon Cooray, Hasupama Jayasinghe, Marcos Rubinstein, Farhad Rachidi
      First page: 2028
      Abstract: The streamer bursts generated during the initiation and propagation of leaders play an important role in the creation and maintenance of hot discharge channels in air. The most important parameters related to streamer bursts in this respect are the length of the streamer bursts, their lateral extent and the charge associated with them. The lateral extent of the streamer bursts may play a significant role in deciding the path and the tortuosity of the discharge channels of laboratory discharges and lightning. The charges associated with the streamer bursts are needed in understanding the physical processes associated with the streamer-to-leader transition. In this paper, the length, the lateral extension and the charge of the streamer regions generated by grounded conductors when exposed to external electric fields are estimated. This estimation is based on two assumptions: (i) once a streamer is incepted, the streamer head follows the direction of maximum background electric field at the location of the streamer head and (ii) the streamer continues to extend along this direction until the potential drop along the streamer channel matches the potential drop caused by the background electric field between the initial and end points of the streamer channel. The same technique could be used to estimate the streamer bursts generated in laboratory discharges and lightning stepped leaders. It is shown that in estimating the geometry of the streamer region, it is necessary to include the spread of streamers caused by branching. Moreover, the charge associated with the streamer region increases as the frequency of branching increases. The results obtained confirm that the charge in the streamer region can significantly change the potential ahead of the streamer region from the background potential and this has to be taken into account in any study that simulates the initiation and propagation of lightning leaders. Since the streamer bursts of leaders control the direction and speed of the leaders, the technique we have used here could be implemented in lightning leader progression models.
      Citation: Atmosphere
      PubDate: 2022-12-02
      DOI: 10.3390/atmos13122028
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 2029: Bioaerosol Release from Concentrated
           Microbial Suspensions in Bubbling Processes

    • Authors: Kruglyakova, Mirskaya, Agranovski
      First page: 2029
      Abstract: Bursting bubbles are one of the most common mechanisms in aerosols’ formation from natural and artificial waterbodies. The presence of microbial materials in the liquid could cause their aerosolization and generation of bioaerosols. The process depends on a number of parameters of the gas and liquid involved. This project investigated the influence of the air flow, bubble size, the temperature of the liquid and its surface tension on the efficiency of bioaerosol generation. It was found that the bioaerosol is more efficiently produced at higher air flow rates and smaller bubble size. The influence of the liquid temperature was also identified to be quite high, reaching an order of magnitude of the bioaerosol concentration over the temperature range from 4 °C to 38 °C. The addition of surfactants did suppress the foam formation, which was found to have a negative effect on the process; the rate of the bioaerosol generation increased with the increase in the antifoam concentration.
      Citation: Atmosphere
      PubDate: 2022-12-02
      DOI: 10.3390/atmos13122029
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 2030: Effect of Airborne Particulate Matter on
           Cardiovascular Diseases

    • Authors: Naof Faiz Saleem, Mahmoud Fathy ElSharkawy, Ayman M. Azoz
      First page: 2030
      Abstract: Context: Airborne particulate matter (PM) attracts heightened attention due to its implication in various diseases, especially cardiovascular diseases. Although numerous epidemiological studies have been published worldwide in developing countries on risks associated with exposure to PM, such studies are still scarce in developing countries such as Saudi Arabia. Objective: To examine the association between the concentration of airborne particulate matter (PM) and hospital admissions resulting from cardiovascular diseases (CVD) in the Eastern Region of Saudi Arabia, specifically in the cities of Dammam and Khobar. Methodology: The daily concentrations of PM10 and PM2.5 were obtained from 10 monitoring stations distributed around the two hospitals. There was an examination of the discharge data of patients diagnosed with cardiac arrhythmias, acute myocardial infarction, and heart failure as their primary diagnoses. The data were obtained from two big governmental hospitals in the Eastern Region. The primary cause of hospital admission of 259 patients was identified as acute cardiac condition. Results: For PM10 and PM2.5, the 24 h mean was calculated as 101.2 and 37.1 µg/m3, respectively; such means are considered higher than the Air Quality Guidelines (AQGs). We found evidence of an increased risk of cardiovascular events for long-term exposure to PM2.5–10 concentrations, and a correlation with the IHD hospital admission within 6 days of the peak PM10 or PM2.5 concentration. In addition, the increased PM2.5 concentration also had a correlation with hospital admissions; however, analysis shows an increase in mortality at lag1, lag2, and lag3 prior to hospital admission. Conclusions: Hospital admissions for several cardiovascular diseases acutely increase in response to higher ambient PM concentrations. It is recommended that residents need to use personal protection, especially those residents with cardiovascular disease, while the government needs to strengthen the governance of air pollution in areas with lighter air pollution.
      Citation: Atmosphere
      PubDate: 2022-12-02
      DOI: 10.3390/atmos13122030
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 2031: Impact of the COVID-19 Pandemic on the
           2020 Diurnal Temperature Range (DTR) in the Contiguous USA

    • Authors: Walid Ahmed, Lydia Marini Hoffmann, Talib Al-Hasani, Rafael M. Santos
      First page: 2031
      Abstract: Following the emergence of COVID-19, nations around the world implemented effective restrictions that limited people’s movements and economic activity, which reportedly led to environmental improvements. The lowering of air emissions is one environmental indicator that has been connected to the pandemic. The diurnal temperature range (DTR) is one environmental indicator that has been linked to air pollution. In this study, it was hypothesized that because of the pandemic restrictions and slowdowns, the DTR in 2020 for a country that implemented major restrictive measures in reaction to the pandemic would be higher than in previous years, despite or in addition to background climatic forcings. Based on information from weather stations in the contiguous United States of America (USA), the DTR for the year 2020 was compared to the five years before it as a test of this hypothesis. It was verified that the annual mean DTR of 2020 was higher than the three years prior (2017–2019), but lower than the DTR of 2015 and 2016. Compared to historical trends (since 1911), the DTR change in 2020 is within past mean DTR variations that occurred over approx. 12-year cycles, linked to sunspot activity (Schwabe solar cycle). Moreover, climatic effects such as El Niño, La Niña and the prolonged trend of global warming reduce the confidence in the perceived effect of the pandemic. To determine if or how anthropogenic and environmental factors can magnify the impact of the COVID-19 restrictions on the regional mean DTR, five other parameters (annual snowfall quantities, gross domestic product per capita, population density, latitude (northern/southern), and longitude (coastal/inner)) were also examined against changes in DTR from 2015 to 2020. This analysis pointed to the environmental and industrial factors being more strongly correlated with short-term climate changes than societal factors and geographical location.
      Citation: Atmosphere
      PubDate: 2022-12-03
      DOI: 10.3390/atmos13122031
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 2032: Reducing Particle Exposure and SARS-CoV-2
           Risk in Built Environments through Accurate Virtual Twins and
           Computational Fluid Dynamics

    • Authors: Fabian Quintero, Vijaisri Nagarajan, Stefan Schumacher, Ana Maria Todea, Jörg Lindermann, Christof Asbach, Charles M. A. Luzzato, Jonathan Jilesen
      First page: 2032
      Abstract: The World Health Organization has pointed out that airborne transmission via aerosol particles can be a strong vector for the spread of SARS-CoV-2. Protecting occupants from infectious diseases or harmful particulate matter (PM) in general can be challenging. While experimentally outlining the detailed flow of PM in rooms may require complex setups, computational fluid dynamics (CFD) simulations can provide insights into improving the safety of the built environment and the most effective positioning of air-purifying devices. While previous studies have typically leveraged Reynolds-averaged Navier–Stokes (RANS) approaches for predicting particle propagation, the turbulence length scales accurately captured in these simulations may not be sufficient to provide a realistic spread and the mixing of particles under the effects of forced convection. In this paper, we experimentally validate a Lattice Boltzmann very large eddy simulation (VLES) approach including particle modeling. We also demonstrate how this simulation approach can be used to improve the effectiveness of air filtration devices in realistic office environments.
      Citation: Atmosphere
      PubDate: 2022-12-03
      DOI: 10.3390/atmos13122032
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 2033: The Association between Household Air
           Pollution and Blood Pressure in Obuasi Municipality, Ghana

    • Authors: Theresa Tawiah, Matthew Shupler, Stephaney Gyaase, Rachel Anderson de Cuevas, Jason Saah, Emily Nix, Mieks Twumasi, Reginald Quansah, Elisa Puzzolo, Daniel Pope, Kwaku Poku Asante
      First page: 2033
      Abstract: Emerging evidence suggests a possible link between exposure to household air pollution (HAP) from a reliance on polluting solid fuels (SFs) (e.g., wood and charcoal) for cooking and high blood pressure. As part of the CLEAN-Air(Africa) project, we measured the blood pressure among 350 cooks in Obuasi Municipality, Ghana after 24 h exposure to particulate matter (PM2.5) from the combustion of either solid fuels (n = 35) or liquefied petroleum gas (LPG) (n = 35). Multinomial regression models were used to describe the relationship between different stages of blood pressure (mmHg) and the respondents’ main fuel type used, adjusting for key covariates. A linear regression model was used to describe the relationship between personal exposure to PM2.5 and the respondent’s systolic as well as diastolic blood pressure, adjusting for key covariates. Blood pressure was higher in cooks using SFs for cooking than in those using LPG. A significant exposure–response relationship was not observed between increasing exposure to PM2.5 and increasing blood pressure (systolic: β = −2.42, 95% CI: −8.65, 3.80, p-value = 0.438, and diastolic: β = −0.32, 95% CI: −5.09; 4.45, p-value = 0.893).
      Citation: Atmosphere
      PubDate: 2022-12-03
      DOI: 10.3390/atmos13122033
      Issue No: Vol. 13, No. 12 (2022)
       
  • Atmosphere, Vol. 13, Pages 1934: Imputation of Missing PM2.5 Observations
           in a Network of Air Quality Monitoring Stations by a New kNN Method

    • Authors: Idit Belachsen, David M. Broday
      First page: 1934
      Abstract: Statistical analyses often require unbiased and reliable data completion. In this work, we imputed missing fine particulate matter (PM2.5) observations from eight years (2012–2019) of records in 59 air quality monitoring (AQM) stations in Israel, using no auxiliary data but the available PM2.5 observations. This was achieved by a new k-Nearest Neighbors multivariate imputation method (wkNNr) that uses the correlations between the AQM stations’ data to weigh the distance between the observations. The model was evaluated against an iterative imputation with an Ensemble of Extremely randomized decision Trees (iiET) on artificially and randomly removed data intervals of various lengths: very short (0.5–3 h, corresponding to 1–6 missing values), short (6–24 h), medium-length (36–72 h), long (10–30 d), and very long (30 d–2 y). The new wkNNr model outperformed the iiET in imputing very short missing-data intervals when the adjacent lagging and leading observations were added as model inputs. For longer missing-data intervals, despite its simplicity and the smaller number of hyperparameters required for tuning, the new model showed an almost comparable performance to the iiET. A parallel Python implementation of the new kNN-based multivariate imputation method is available on github.
      Citation: Atmosphere
      PubDate: 2022-11-21
      DOI: 10.3390/atmos13111934
      Issue No: Vol. 13, No. 11 (2022)
       
  • Atmosphere, Vol. 13, Pages 1935: The Relationship between Elemental Carbon
           and Volatile Organic Compounds in the Air of an Underground Metal Mine

    • Authors: Andrzej Szczurek, Marcin Przybyła, Monika Maciejewska
      First page: 1935
      Abstract: Elemental carbon (EC) content in air is considered a proxy for the diesel exhaust impact at workplaces. This paper examines the possibility of estimating EC content in mine air on the basis of measurements of volatile organic compounds (VOC). The measurement study was carried out in an underground metal mine. Gas chromatography with mass spectrometry (GC/MS) was applied for VOC determination, and thermal-optical analysis (TOA) with an FID detector was utilized for EC measurements. A correlation was found between the measurements of EC and total VOC (TVOC) as well as the content of individual hydrocarbons C12–C14 in the air of an extraction zone in the mine. A regression model was developed which predicts EC based on C12, C13, and C14, considered individually, and the remaining VOCs detected with GC/MS taken in total. The model was statistically significant (p = 0.053), and it offered an EC prediction error of RMSE = 4.60 µg/sample. The obtained result confirms the possibility of using VOC measurements for the preliminary estimation of EC concentrations in mine air. This approach is feasible given the availability of portable GC/MS and offers easy and fast measurements providing qualitative and quantitative information.
      Citation: Atmosphere
      PubDate: 2022-11-21
      DOI: 10.3390/atmos13111935
      Issue No: Vol. 13, No. 11 (2022)
       
  • Atmosphere, Vol. 13, Pages 1936: Error Decomposition of CRA40-Land and
           ERA5-Land Reanalysis Precipitation Products over the Yongding River Basin
           in North China

    • Authors: Ye Zhang, Yintang Wang, Lingjie Li, Leizhi Wang, Qin Wang, Yong Huang, Liping Li
      First page: 1936
      Abstract: Long-term and high-resolution reanalysis precipitation datasets provide important support for research on climate change, hydrological forecasting, etc. The comprehensive evaluation of the error performances of the newly released ERA5-Land and CRA40-Land reanalysis precipitation datasets over the Yongding River Basin in North China was based on the two error decomposition schemes, namely, decomposition of the total mean square error into systematic and random errors and decomposition of the total precipitation bias into hit bias, missed precipitation, and false precipitation. Then, the error features of the two datasets and precipitation intensity and terrain effects against error features were analyzed in this study. The results indicated the following: (1) Based on the decomposition approach of systematic and random errors, the total error of ERA5-Land is generally greater than that of CRA40-Land. Additionally, the proportion of random errors was higher in summer and over mountainous areas, specifically, the ERA5-Land accounts for more than 75%, while the other was less than 70%; (2) Considering the decomposition method of hit, missed, and false bias, the total precipitation bias of ERA5-Land and CRA40-Land was consistent with the hit bias. The magnitude of missed precipitation and false precipitation was less than the hit bias. (3) When the precipitation intensity is less than 38 mm/d, the random errors of ERA5-Land and CRA40-Land are larger than the systematic error. The relationship between precipitation intensity and hit, missed, and false precipitation is complicated, for the hit bias of ERA5-L is always smaller than that of CRA40-L, and the missed precipitation and false precipitation are larger than those ofCRA40-L when the precipitation is small. The error of ERA5-Land and CRA40-Land was significantly correlated with elevation. A comprehensive understanding of the error features of the two reanalysis precipitation datasets is valuable for error correction and the construction of a multi-source fusion model with gauge-based and satellite-based precipitation datasets.
      Citation: Atmosphere
      PubDate: 2022-11-21
      DOI: 10.3390/atmos13111936
      Issue No: Vol. 13, No. 11 (2022)
       
  • Atmosphere, Vol. 13, Pages 1937: Seasonal Variations in Concentrations and
           Chemical Compositions of TSP near a Bulk Material Storage Site for a Steel
           Plant

    • Authors: Yen-Yi Lee, Sheng-Lun Lin, Bo-Wun Huang, Justus Kavita Mutuku, Guo-Ping Chang-Chien
      First page: 1937
      Abstract: The concentrations of total suspended particles (TSPs) on four buildings near a steel plant’s bulk material storage site for iron ore, coal, limestone, and sinter were evaluated for summer and winter, where the concentrations were 58 (17–55) μg m−3 and 125 (108–155) μg m−3, respectively. A multivariate regression analysis of meteorological parameters with TSP concentrations indicates that temperature, wind speed, and frequency of rainfall are potential predictors of TSP concentrations, where the respective p values for the model are p = 0.005, p = 0.049, and p = 0.046. The strong correlation between usual co-pollutants, CO, NO2, and NOX with TSP concentrations, as indicated by the Pearson correlation values of 0.87, 0.86, and 0.77, respectively, implies substantial pollution from mobile sources. The weak correlation of SO2 with TSP concentrations rules out a significant pollution contribution from power plants. The speciation of TSPs in winter showed the percentage proportions of water-soluble ions, metal elements, and carbon content in winter as 60%, 15%, and 25%, while in summer, they were 68%, 14%, and 18%, respectively. Water-soluble ions were the most significant composition for both seasons, where the predominant species in summer and winter are SO42− and NO3−, respectively. In the TSP metal elements profile, the proportion of natural origin ones exceeded those from anthropogenic sources. The health risk assessment indicates a significant cancer risk posed by chromium, while that posed by other metal elements including Co, Ni, As, and Pb are insignificant. Additionally, all metal elements’ chronic daily occupational exposure levels were below the reference doses except for Cu and Zn. Insights from this investigation can inform decisions on the design of the TSP-capturing mechanism. Specifically, water sprays to capture the water-soluble portion would substantially reduce the amplified concentrations of TSPs, especially in winter.
      Citation: Atmosphere
      PubDate: 2022-11-21
      DOI: 10.3390/atmos13111937
      Issue No: Vol. 13, No. 11 (2022)
       
  • Atmosphere, Vol. 13, Pages 1938: Usage of Needle and Branches in the
           Applications of Bioindicator, Source Apportionment and Risk Assessment of
           PAHs

    • Authors: Sevil Caliskan Eleren, Yücel Tasdemir
      First page: 1938
      Abstract: Biomonitoring studies have enormous benefits providing a fruitful and cost-efficient means of measuring environmental exposure to toxic chemicals. This study collected ambient air and pine tree components, including needles and 1-year-old and 2-year-old branches, for one year. Concentrations, potential sources and temporal variations of atmospheric polycyclic aromatic hydrocarbons (PAHs) were investigated. In general, lower concentration levels were observed in the warmer months. Ambient PAHs pose a serious public health threat and impose a need for calculating cancer risks. It was also intended to define the best tree component reflecting the ambient air PAHs. The consideration of the representative tree component minimizes the unnecessary laboratory processes and expenses in biomonitoring studies. The coefficient of divergence (COD), diagnostic ratio (DR) and principal component analysis (PCA) were employed to specify the PAH sources. As a result of the DR and PCA evaluations, the effect of the industrial area has emerged, besides the dominance of the pollutants originating from traffic and combustion. The results have shown that pine needles and branches were mainly affected by similar sources, which also influenced air concentrations. Inhalation cancer risk values were also calculated and they varied between 1.64 × 10−6 and 3.02 × 10−5. A potential risk increases in the colder season depending on the ambient air PAH concentrations.
      Citation: Atmosphere
      PubDate: 2022-11-21
      DOI: 10.3390/atmos13111938
      Issue No: Vol. 13, No. 11 (2022)
       
  • Atmosphere, Vol. 13, Pages 1939: Ionospheric TEC Prediction in China Based
           on the Multiple-Attention LSTM Model

    • Authors: Haijun Liu, Dongxing Lei, Jing Yuan, Guoming Yuan, Chunjie Cui, Yali Wang, Wei Xue
      First page: 1939
      Abstract: The prediction of the total electron content (TEC) in the ionosphere is of great significance for satellite communication, navigation and positioning. This paper presents a multiple-attention mechanism-based LSTM (multiple-attention Long Short-Term Memory, MA-LSTM) TEC prediction model. The main achievements of this paper are as follows: (1) adding an L1 constraint to the LSTM-based TEC prediction model—an L1 constraint prevents excessive attention to the input sequence during modelling and prevents overfitting; (2) adding multiple-attention mechanism modules to the TEC prediction model. By adding three parallel attention modules, respectively, we calculated the attention value of the output vector from the LSTM layer, and calculated its attention distribution through the softmax function. Then, the vector output by each LSTM layer was weighted and summed with the corresponding attention distribution so as to highlight and focus on important features. To verify our model’s performance, eight regions located in China were selected in the European Orbit Determination Center (CODE) TEC grid dataset. In these selected areas, comparative experiments were carried out with LSTM, GRU and Att-BiGRU. The results show that our proposed MA-LSTM model is obviously superior to the comparison models. This paper also discusses the prediction effect of the model in different months. The results show that the prediction effect of the model is best in July, August and September, with the R-square reaching above 0.99. In March, April and May, the R-square is slightly low, but even at the worst time, the fitting degree between the predicted value and the real value still reaches 0.965. We also discussed the influence of a magnetic quiet period and a magnetic storm period on the prediction performance. The results show that in the magnetic quiet period, our model fit very well. In the magnetic storm period, the R-square is lower than that of the magnetic quiet period, but it can also reach 0.989. The research in this paper provides a reliable method for the short-term prediction of ionospheric TEC.
      Citation: Atmosphere
      PubDate: 2022-11-21
      DOI: 10.3390/atmos13111939
      Issue No: Vol. 13, No. 11 (2022)
       
 
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