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  Subjects -> METEOROLOGY (Total: 106 journals)
Showing 1 - 36 of 36 Journals sorted alphabetically
Acta Meteorologica Sinica     Hybrid Journal   (Followers: 4)
Advances in Atmospheric Sciences     Hybrid Journal   (Followers: 45)
Advances in Climate Change Research     Open Access   (Followers: 50)
Advances in Meteorology     Open Access   (Followers: 27)
Advances in Statistical Climatology, Meteorology and Oceanography     Open Access   (Followers: 11)
Aeolian Research     Hybrid Journal   (Followers: 7)
Agricultural and Forest Meteorology     Hybrid Journal   (Followers: 20)
American Journal of Climate Change     Open Access   (Followers: 37)
Atmósfera     Open Access   (Followers: 2)
Atmosphere     Open Access   (Followers: 33)
Atmosphere-Ocean     Full-text available via subscription   (Followers: 16)
Atmospheric and Oceanic Science Letters     Open Access   (Followers: 13)
Atmospheric Chemistry and Physics (ACP)     Open Access   (Followers: 43)
Atmospheric Chemistry and Physics Discussions (ACPD)     Open Access   (Followers: 15)
Atmospheric Environment     Hybrid Journal   (Followers: 72)
Atmospheric Environment : X     Open Access   (Followers: 3)
Atmospheric Research     Hybrid Journal   (Followers: 73)
Atmospheric Science Letters     Open Access   (Followers: 40)
Boundary-Layer Meteorology     Hybrid Journal   (Followers: 32)
Bulletin of Atmospheric Science and Technology     Hybrid Journal   (Followers: 5)
Bulletin of the American Meteorological Society     Open Access   (Followers: 63)
Carbon Balance and Management     Open Access   (Followers: 6)
Ciencia, Ambiente y Clima     Open Access   (Followers: 1)
Climate     Open Access   (Followers: 8)
Climate and Energy     Full-text available via subscription   (Followers: 6)
Climate Change Economics     Hybrid Journal   (Followers: 44)
Climate Change Responses     Open Access   (Followers: 23)
Climate Dynamics     Hybrid Journal   (Followers: 45)
Climate Law     Hybrid Journal   (Followers: 6)
Climate of the Past (CP)     Open Access   (Followers: 6)
Climate of the Past Discussions (CPD)     Open Access   (Followers: 1)
Climate Policy     Hybrid Journal   (Followers: 51)
Climate Research     Hybrid Journal   (Followers: 9)
Climate Resilience and Sustainability     Open Access   (Followers: 21)
Climate Risk Management     Open Access   (Followers: 10)
Climate Services     Open Access   (Followers: 4)
Climatic Change     Open Access   (Followers: 69)
Current Climate Change Reports     Hybrid Journal   (Followers: 17)
Dynamics and Statistics of the Climate System     Open Access   (Followers: 6)
Dynamics of Atmospheres and Oceans     Hybrid Journal   (Followers: 19)
Earth Perspectives - Transdisciplinarity Enabled     Open Access   (Followers: 1)
Economics of Disasters and Climate Change     Hybrid Journal   (Followers: 13)
Energy & Environment     Hybrid Journal   (Followers: 24)
Environmental and Climate Technologies     Open Access   (Followers: 3)
Environmental Dynamics and Global Climate Change     Open Access   (Followers: 21)
Frontiers in Climate     Open Access   (Followers: 4)
GeoHazards     Open Access   (Followers: 2)
Global Meteorology     Open Access   (Followers: 20)
International Journal of Atmospheric Sciences     Open Access   (Followers: 25)
International Journal of Biometeorology     Hybrid Journal   (Followers: 3)
International Journal of Climate Change Strategies and Management     Hybrid Journal   (Followers: 29)
International Journal of Climatology     Hybrid Journal   (Followers: 28)
International Journal of Environment and Climate Change     Open Access   (Followers: 20)
International Journal of Image and Data Fusion     Hybrid Journal   (Followers: 3)
Journal of Agricultural Meteorology     Open Access  
Journal of Applied Meteorology and Climatology     Hybrid Journal   (Followers: 42)
Journal of Atmospheric and Oceanic Technology     Hybrid Journal   (Followers: 33)
Journal of Atmospheric and Solar-Terrestrial Physics     Hybrid Journal   (Followers: 133)
Journal of Atmospheric Chemistry     Hybrid Journal   (Followers: 23)
Journal of Climate     Hybrid Journal   (Followers: 56)
Journal of Climate Change and Health     Open Access   (Followers: 4)
Journal of Climatology     Open Access   (Followers: 4)
Journal of Hydrology and Meteorology     Open Access   (Followers: 39)
Journal of Hydrometeorology     Hybrid Journal   (Followers: 10)
Journal of Integrative Environmental Sciences     Hybrid Journal   (Followers: 4)
Journal of Meteorological Research     Full-text available via subscription   (Followers: 2)
Journal of Meteorology and Climate Science     Full-text available via subscription   (Followers: 21)
Journal of Space Weather and Space Climate     Open Access   (Followers: 30)
Journal of the Atmospheric Sciences     Hybrid Journal   (Followers: 83)
Journal of the Meteorological Society of Japan     Partially Free   (Followers: 7)
Journal of Weather Modification     Full-text available via subscription   (Followers: 4)
Mediterranean Marine Science     Open Access   (Followers: 2)
Meteorologica     Open Access   (Followers: 2)
Meteorological Applications     Open Access   (Followers: 4)
Meteorological Monographs     Hybrid Journal   (Followers: 1)
Meteorologische Zeitschrift     Full-text available via subscription   (Followers: 4)
Meteorology and Atmospheric Physics     Hybrid Journal   (Followers: 29)
Mètode Science Studies Journal : Annual Review     Open Access  
Michigan Journal of Sustainability     Open Access   (Followers: 1)
Modeling Earth Systems and Environment     Hybrid Journal   (Followers: 1)
Monthly Notices of the Royal Astronomical Society     Hybrid Journal   (Followers: 13)
Monthly Weather Review     Hybrid Journal   (Followers: 30)
Nature Climate Change     Full-text available via subscription   (Followers: 145)
Nature Reports Climate Change     Full-text available via subscription   (Followers: 40)
Nīvār     Open Access   (Followers: 1)
npj Climate and Atmospheric Science     Open Access   (Followers: 6)
Open Atmospheric Science Journal     Open Access   (Followers: 6)
Open Journal of Modern Hydrology     Open Access   (Followers: 5)
Revista Iberoamericana de Bioeconomía y Cambio Climático     Open Access   (Followers: 1)
Russian Meteorology and Hydrology     Hybrid Journal   (Followers: 4)
Space Weather     Full-text available via subscription   (Followers: 27)
Studia Geophysica et Geodaetica     Hybrid Journal   (Followers: 1)
Tellus A     Open Access   (Followers: 21)
Tellus B     Open Access   (Followers: 20)
The Cryosphere (TC)     Open Access   (Followers: 8)
The Quarterly Journal of the Royal Meteorological Society     Hybrid Journal   (Followers: 32)
Theoretical and Applied Climatology     Hybrid Journal   (Followers: 14)
Tropical Cyclone Research and Review     Open Access   (Followers: 1)
Urban Climate     Hybrid Journal   (Followers: 5)
Weather     Hybrid Journal   (Followers: 20)
Weather and Climate Dynamics     Open Access   (Followers: 1)
Weather and Climate Extremes     Open Access   (Followers: 18)
Weather and Forecasting     Hybrid Journal   (Followers: 43)
Weatherwise     Hybrid Journal   (Followers: 18)
气候与环境研究     Full-text available via subscription   (Followers: 2)

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Journal Cover
Atmosphere
Number of Followers: 33  

  This is an Open Access Journal Open Access journal
ISSN (Online) 2073-4433
Published by MDPI Homepage  [84 journals]
  • Atmosphere, Vol. 13, Pages 735: Interannual Variations of Rainfall in Late
           Spring over Southwest China and Associated Sea Surface Temperature and
           Atmospheric Circulation Anomalies

    • Authors: Shuangli Mei, Shangfeng Chen, Yong Li, Hasi Aru
      First page: 735
      Abstract: Based on rainfall data for the period of 1960–2018 from 382 stations in southwest China and multiple reanalysis datasets, interannual variation of rainfall in late spring over Southwest China and associated sea surface temperature and atmospheric circulation anomalies are examined. The first leading mode of late-spring rainfall anomalies displays a uniform-distribution pattern. The second leading mode shows a zonal dipole pattern. The leading mode is related to an atmospheric wave train over mid-high latitudes of Eurasia, with a center of action of atmospheric anomaly over Southwest China. The atmospheric anomalies over Southwest China modulate late-spring rainfall there via modulating vertical motion and water vapor transport. In addition, the leading mode of late-spring rainfall anomalies has a close relation with sea surface temperature anomalies (SSTA) in the central and eastern equatorial Pacific. SSTA in the central and eastern equatorial Pacific impacts late-spring rainfall anomalies over Southwest China via modulation of the tropical Walker and Hadley circulation. The second leading mode of late-spring rainfall variation over Southwest China is closely associated with SSTA in the tropical western Pacific and a mid-high latitude wave train. SSTA in the tropical western Pacific and the mid-high latitudes wave train together leads to out-of-phase variation of meridional wind anomalies between western and eastern parts of Southwest China, which further results in a zonal dipole rainfall anomaly over Southwest China.
      Citation: Atmosphere
      PubDate: 2022-05-04
      DOI: 10.3390/atmos13050735
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 736: Interdecadal Variation of the Antarctic
           Circumpolar Wave Based on the 20CRV3 Dataset

    • Authors: Zhichao Lu, Tianbao Zhao, Weican Zhou, Haikun Zhao
      First page: 736
      Abstract: As a large-scale ocean–atmosphere coupling system in the Southern Hemisphere, the Antarctic Circumpolar Wave (ACW) greatly impacts the global climate. However, the interdecadal variation of the ACW has rarely been studied due to the lack of long-term data. In this research, the latest 20th Century Reanalysis Version 3 dataset is used to analyze the interdecadal variations of sea level pressure (SLP) and sea surface temperature (SST) signals in the ACW during 1836–2015. The results indicate that the ACW has not always been present in the recent 180 years, and it has remarkable interdecadal variations. Specifically, the ACW was hard to distinguish before the 1870s. The SLP anomalies propagated eastwards over the South Pacific and South Atlantic during part of the 1880s–1940s. The SST anomalies also have an eastward propagation in the 1880s–1960s. The most active period of the SLP signal is in the 1950s–1990s, while that of the SST signal is in the 1980s–1990s. The ACW has not been significant since the 21st century. The interdecadal variation of the SLP may be related to the variations of the long-term Southern Annular Mode and Pacific-South American pattern, while the interdecadal variation of the SST is more associated with the ENSO.
      Citation: Atmosphere
      PubDate: 2022-05-04
      DOI: 10.3390/atmos13050736
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 737: Long-Term (2017–2020) Aerosol
           Optical Depth Observations in Hohhot City in Mongolian Plateau and the
           Impacts from Different Types of Aerosol

    • Authors: Yongjing Ma, Yongli Tian, Yuanzhe Ren, Zifa Wang, Lin Wu, Xiaole Pan, Yining Ma, Jinyuan Xin
      First page: 737
      Abstract: Aerosol optical depth (AOD) measurements for 2017–2020 in urban Hohhot of the Mongolian plateau, a transition zone between the depopulated zone and East Asian urban agglomeration, were analyzed for the first time. Results show that annual AOD500 and Ångström exponent α440-675 were 0.36 ± 0.09 and 1.11 ± 0.16 (2017), 0.41 ± 0.12 and 0.90 ± 0.28 (2018), 0.38 ± 0.09 and 1.13 ± 0.24 (2019), 0.38 ± 0.12 and 1.17 ± 0.22 (2020), respectively, representing a slightly polluted level with a mixed type of coarse dust aerosol and a fine urban/industrial aerosol. Throughout the year, depopulated-zone continental air flows predominated in Hohhot (i.e., NW-quadrant wind), accounting for 82.12% (spring), 74.54% (summer), 63.61% (autumn), and 100% (winter). The clean and strong NW-quadrant air flows induced by the south movement of a Siberian anticyclone resulted in a low 500-nm AOD of 0.30 ± 0.29, 0.20 ± 0.15, 0.24 ± 0.29, and 0.13 ± 0.08 from spring to winter. Meanwhile, the local emissions from Hohhot city, as well as anthropogenic urban/industrial aerosols transported by southern and western air masses, originating from southern urban agglomeration and western industrial cities (Baotou, Wuhai, etc.), contributed to the highest aerosol loading, with significant transformation rates of the secondary aerosols Sulfate-Nitrate-Ammonium (SNA) of 47.45%, 57.39%, 49.88%, and 45.16–47.36% in PM2.5 for each season. The extinction fraction of fine aerosols under these anthropogenic trajectories can be as high as 80%, and the largest fine aerosol size was around 0.2–0.25 μm. Dust aerosols were suspending in urban Hohhot all year, although at different levels for different seasons, and the extinction fraction of dust aerosol during sandstorms was generally higher than 70%.
      Citation: Atmosphere
      PubDate: 2022-05-05
      DOI: 10.3390/atmos13050737
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 738: Warm–Wet Climate Trend Enhances Net
           

    • Authors: Yuhe Ji, Guangsheng Zhou, Shudong Wang, Jun Zhao
      First page: 738
      Abstract: A significant greening trend has been reported globally in recent decades. The greening indicates the improvement in net primary production (NPP) in vegetation. Adopting statistics-based regression models, we investigated the dynamics of NPP and its climatic drivers in main ecosystems (forest land, grass land, and unused land) over China during the period 2000–2021. The results confirmed an increasing NPP covering approximately 86% area in the main ecosystems. NPP exhibited an increase rate of 6.11 g C m−2 yr−1 in forest land, 4.77 g C m−2 yr−1 in grass land, and 1.25 g C m−2 yr−1 in unused land, respectively. Over the same period, warm–wet climate trend was observed covering approximately 90% of the main ecosystems. The warm–wet climate has had a positive effect rather than negative effect on NPP in the main ecosystems, judging by their significant positive correlation. Our results suggested that the increase in annual precipitation exerted much more important effect on the increasing NPP. The warm–wet climate trend contributes to the upward trend in NPP, even if variability in NPP might involve the influence of solar radiation, atmospheric aerosols, CO2 fertilization, nitrogen deposition, human intervention, etc.
      Citation: Atmosphere
      PubDate: 2022-05-05
      DOI: 10.3390/atmos13050738
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 739: Accessing the Heat Exposure Risk in
           Beijing–Tianjin–Hebei Region Based on Heat Island Footprint
           Analysis

    • Authors: Xuecheng Fu, Lei Yao, Shuo Sun
      First page: 739
      Abstract: The urbanization process leads to the enhancement of the urban heat island (UHI) effect, and the high temperature brought by it exacerbates the risk of heat exposure and seriously endangers human health. Analyzing the spatiotemporal characteristics and levels of heat exposure risk is important for formulating heat risk prevention and control measures. Therefore, this study analyzes the spatiotemporal characteristics of heat exposure risk based on the UHI footprint (FP) and explores the relationship between it and urbanization factors in the Beijing–Tianjin–Hebei (BTH) region from 2000 to 2020, and obtains the following conclusions: (1) The BTH region suffers from severe UHI problems, with FP ranging from 6.05 km (Chengde) to 32.51 km (Beijing), and the majority of cities show significant trends of FP increase. (2) With the increase in FP, massive populations are exposed within the heat risk areas, with the average annual population at risk across cities ranging from 269,826 (Chengde) to 166,020,390 (Beijing), with a predominance of people exposed to high risk (more than 65% of the total) and generally showing increasing trends. (3) The population at risk of heat exposure is significantly correlated with urbanization factors, indicating that urbanization is an important reason for the increase in the risk population and the enhancement of the risk level. These results suggest that with the continuous urbanization process, the heat exposure risk problem faced by cities in the BTH region will persist and gradually worsen, which must be paid attention to and effective mitigation measures must be taken.
      Citation: Atmosphere
      PubDate: 2022-05-05
      DOI: 10.3390/atmos13050739
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 740: Correlating Traffic Data, Spectral Noise
           and Air Pollution Measurements: Retrospective Analysis of Simultaneous
           Measurements near a Highway in The Netherlands

    • Authors: Luc Dekoninck, Marcel Severijnen
      First page: 740
      Abstract: Road traffic simultaneously emits noise and air pollution. This relation is primarily assessed by comparing A-weighted noise levels (LAeq) and various air pollutants. However, despite the common local traffic source, LAeq and the various sets of air pollution show a lower correlation than expected. Prior work, using simultaneous mobile noise and air pollution measurements, shows that the spectral content of the noise explains the complex and highly nonlinear relation between noise and air pollution significantly better. The spectral content distinguishes between traffic volume and traffic dynamics, two relevant modifiers explaining both the variability in noise and air pollution emissions of the local traffic flow. In May 2011, the environmental agency in the Netherlands performed noise and air pollutant measurements near a major highway and included spectral noise. In the resulting report, the analysis of the traffic, the noise and a wide set of air pollutants only showed a strong correlation between noise and NO. In this work, this dataset is re-evaluated using the noise-related covariates, engine noise and cruising noise, defined in prior work. The modeling approach proves valid for most of the measured air pollutants except for the large PM fractions. Conclusion: the prior established methodology explains the complex interaction between traffic dynamics, noise emission and air pollution emissions for a wide variety of air pollutants. The applicability of the ‘noise-as-a-traffic-proxy’ approach is extended.
      Citation: Atmosphere
      PubDate: 2022-05-05
      DOI: 10.3390/atmos13050740
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 741: Projection of Extreme Temperature Events
           over the Mediterranean and Sahara Using Bias-Corrected CMIP6 Models

    • Authors: Hassen Babaousmail, Brian Ayugi, Adharsh Rajasekar, Huanhuan Zhu, Collins Oduro, Richard Mumo, Victor Ongoma
      First page: 741
      Abstract: Climate change continues to increase the intensity, frequency and impacts of weather and climate extremes. This work uses bias-adjusted Coupled Model Intercomparison Project Phase six (CMIP6) model datasets to investigate the future changes in temperature extremes over Mediterranean (MED) and Sahara (SAH) regions. The mid- (2041–2070) and far-future (2071–2100) are studied under two Shared Socioeconomic Pathways: SSP2-4.5 and SSP5-8.5 scenarios. Quantile mapping function greatly improved the performance of CMIP6 by reducing the notable biases to match the distribution of observation data, the Climate Prediction Center (CPC). Results show persistent significant warming throughout the 21st century, increasing with the increase in radiative forcing. The MED will record a higher increase in temperature extremes as compared to SAH. The warming is supported by the projected reduction in cold days (TX10p) and cold nights (TN10p), with the reduction in the number of cold nights exceeding cold days. Notably, warm spell duration index (WSDI) and summer days (SU) have a positive trend in both timelines over the entire study area. There is a need to simulate how climate sensitive sectors, such as water and agriculture, are likely to be affected by projected changes under different scenarios for informed decision making in the choice and implementation of adaptation and mitigation effective measures.
      Citation: Atmosphere
      PubDate: 2022-05-06
      DOI: 10.3390/atmos13050741
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 742: The Impact of Modifications in Forest
           Litter Inputs on Soil N2O Fluxes: A Meta-Analysis

    • Authors: Yuting Zhou, Delong Meng, Bruce Osborne, Yue Fan, Junliang Zou
      First page: 742
      Abstract: Although litter can regulate the global climate by influencing soil N2O fluxes, there is no consensus on the major drivers or their relative importance and how these impact at the global scale. In this paper, we conducted a meta-analysis of 21 global studies to quantify the impact of litter removal and litter doubling on soil N2O fluxes from forests. Overall, our results showed that litter removal significantly reduced soil N2O fluxes (−19.0%), while a doubling of the amount of litter significantly increased soil N2O fluxes (30.3%), based on the results of a small number of studies. Litter removal decreased the N2O fluxes from tropical forest and temperate forest. The warmer the climate, the greater the soil acidity, and the larger the soil C:N ratio, the greater the impact on N2O emissions, which was particularly evident in tropical forest ecosystems. The decreases in soil N2O fluxes associated with litter removal were greater in acid soils (pH < 6.5) or soils with a C:N > 15. Litter removal decreased soil N2O fluxes from coniferous forests (−21.8%) and broad-leaved forests (−17.2%) but had no significant effect in mixed forests. Soil N2O fluxes were significantly reduced in experiments where the duration of litter removal was <1 year. These results showed that modifications in ecosystem N2O fluxes due to changes in the ground litter vary with forest type and need to be considered when evaluating current and future greenhouse gas budgets.
      Citation: Atmosphere
      PubDate: 2022-05-06
      DOI: 10.3390/atmos13050742
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 743: Assessment of Fine Particulate Matter for
           Port City of Eastern Peninsular India Using Gradient Boosting Machine
           Learning Model

    • Authors: Manoj Sharma, Naresh Kumar, Shallu Sharma, Vikas Jangra, Seema Mehandia, Sumit Kumar, Pawan Kumar
      First page: 743
      Abstract: An assessment and prediction of PM2.5 for a port city of eastern peninsular India is presented. Fifteen machine learning (ML) regression models were trained, tested and implemented to predict the PM2.5 concentration. The predicting ability of regression models was validated using air pollutants and meteorological parameters as input variables collected from sites located at Visakhapatnam, a port city on the eastern side of peninsular India, for the assessment period 2018–2019. Highly correlated air pollutants and meteorological parameters with PM2.5 concentration were evaluated and presented during the period under study. It was found that the CatBoost regression model outperformed all other employed regression models in predicting PM2.5 concentration with an R2 score (coefficient of determination) of 0.81, median absolute error (MedAE) of 6.95 µg/m3, mean absolute percentage error (MAPE) of 0.29, root mean square error (RMSE) of 11.42 µg/m3 and mean absolute error (MAE) of 9.07 µg/m3. High PM2.5 concentration prediction results in contrast to Indian standards were also presented. In depth seasonal assessments of PM2.5 concentration were presented, to show variance in PM2.5 concentration during dominant seasons.
      Citation: Atmosphere
      PubDate: 2022-05-06
      DOI: 10.3390/atmos13050743
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 744: Spatiotemporal Variations and
           

    • Authors: Shuangtao Wang, Zhe Cao, Pingping Luo, Wei Zhu
      First page: 744
      Abstract: Precipitation, as an important part of the hydrological cycle, is often related to flood and drought. In this study, we collected daily rainfall data from 21 rainfall stations in Shaanxi Province from 1961 to 2017, and calculated eight extreme climate indices. Annual and seasonal concentration indices (CI) were also calculated. The trends in the changes in precipitation were calculated using the M–K test and Sen’s slope. The results show that the precipitation correlation index and CI (concentration index) in Shaanxi Province are higher in the south and lower in the north. For the annual scale, the CI value ranges from 0.6369 to 0.6820, indicating that Shaanxi Province has a high precipitation concentration and an uneven distribution of annual precipitation. The eight extreme precipitation indices of most rainfall stations showed a downward trend during the study period, and more than half of the stations passed the 0.05 confidence interval test. Among them, the Z value of PRCPTOT (annual total precipitation in wet days) at Huashan station reached −6.5270. The lowest slope of PRCPTOT reached −14.3395. This shows that annual rainfall in Shaanxi Province has been decreasing in recent decades. These findings could be used to make decisions about water resources and drought risk management in Shaanxi Province, China.
      Citation: Atmosphere
      PubDate: 2022-05-06
      DOI: 10.3390/atmos13050744
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 745: Evidence for Intensification in
           Meteorological Drought Since the 1950s and Recent Dryness–Wetness
           Forecasting in China

    • Authors: Ruting Yang, Bing Xing
      First page: 745
      Abstract: Drought is one of the major environmental stressors; drought is increasingly threatening the living environment of mankind. The standardized precipitation evapotranspiration index (SPEI) with a 12-month timescale was adopted to monitor dry–wet status over China from 1951 to 2021. The modified Mann–Kendall (MMK) and Pettitt tests were used to assess the temporal trend and nonlinear behavior of annual drought variability. The analysis focuses on the spatio-temporal structure of the dry–wet transition and its general connections with climate change processes. In addition, the seasonal autoregressive integrated moving average (SARIMA) model was applied to forecast the dry–wet behavior in the next year (2022) at 160 stations, and the hotspot areas for extreme dryness–wetness in China were identified in the near term. The results indicate that the dry–wet climate in China overall exhibits interannual variability characterized by intensified drought. The climate in the Northeast China (NEC), North China (NC), Northwest China (NWC), and Southwest China (SWC) has experienced a significant (p < 0.05) drying trend; however, the dry–wet changes in the East China (EC) and South Central China (SCC) are highly spatially heterogeneous. The significant uptrend in precipitation is mainly concentrated to the west of 100° E; the rising magnitude of precipitation is higher in Eastern China near 30° N, with a changing rate of 20–40 mm/decade. Each of the sub-regions has experienced significant (p < 0.01) warming over the past 71 years. Geographically, the increase in temperature north of 30° N is noticeably higher than that south of 30° N, with trend magnitudes of 0.30–0.50 °C/decade and 0.15–0.30 °C/decade, respectively. The response of the northern part of Eastern China to the warming trend had already emerged as early as the 1980s; these responses were earlier and more intense than those south of 40° N latitude (1990s). The drying trends are statistically significant in the northern and southern regions, bounded by 30° N, with trend magnitudes of −0.30–−0.20/decade and −0.20–−0.10/decade, respectively. The northern and southwestern parts of China have experienced a significant (p < 0.05) increase in the drought level since the 1950s, which is closely related to significant warming in recent decades. This study reveals the consistency of the spatial distribution of variations in precipitation and the SPEI along 30° N latitude. A weak uptrend in the SPEI, i.e., an increase in wetness, is shown in Eastern China surrounding 30° N, with a changing rate of 0.003–0.10/decade; this is closely associated with increasing precipitation in the area. Drought forecasting indicates that recent drying areas are located in NWC, the western part of NC, the western part of SWC, and the southern part of SCC. The climate is expected to show wetting characteristics in NEC, the southeastern part of NC, and the eastern part of EC. The dry–wet conditions spanning the area between 30–40° N and 100–110° E exhibit a greater spatial variability. The region between 20–50° N and 80–105° E will continue to face intense challenges from drought in the near future. This study provides compelling evidence for the temporal variability of meteorological drought in different sub-regions of China. The findings may contribute to understanding the spatio-temporal effect of historical climate change on dry–wet variation in the region since the 1950s, particularly in the context of global warming.
      Citation: Atmosphere
      PubDate: 2022-05-06
      DOI: 10.3390/atmos13050745
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 746: Kolmogorov Complexity Analysis and
           Prediction Horizon of the Daily Erythemal Dose Time Series

    • Authors: Slavica Malinović-Milićević, Anja Mihailović, Dragutin T. Mihailović
      First page: 746
      Abstract: Influenced by stratospheric total ozone column (TOC), cloud cover, aerosols, albedo, and other factors, levels of daily erythemal dose (Her) in a specific geographic region show significant variability in time and space. To investigate the degree of randomness and predictability of Her time series from ground-based observations in Novi Sad, Serbia, during the 2003–2012 time period, we used a set of information measures: Kolmogorov complexity, Kolmogorov complexity spectrum, running Kolmogorov complexity, the largest Lyapunov exponent, Lyapunov time, and Kolmogorov time. The result reveals that fluctuations in daily Her are moderately random and exhibit low levels of chaotic behavior. We found a larger number of occurrences of deviation from the mean in the time series during the years with lower values of Her (2007–2009, 2011–2012), which explains the higher complexity. Our analysis indicated that the time series of daily values of Her show a tendency to increase the randomness when the randomness of cloud cover and TOC increases, which affects the short-term predictability. The prediction horizon of daily Her values in Novi Sad given by the Lyapunov time corrected for randomness by Kolmogorov is between 1.5 and 3.5 days.
      Citation: Atmosphere
      PubDate: 2022-05-06
      DOI: 10.3390/atmos13050746
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 747: Differentiating Semi-Volatile and Solid
           Particle Events Using Low-Cost Lung-Deposited Surface Area and Black
           Carbon Sensors

    • Authors: Molly J. Haugen, Ajit Singh, Dimitrios Bousiotis, Francis D. Pope, Adam M. Boies
      First page: 747
      Abstract: Low-cost particle sensors have proven useful in applications such as source apportionment, health, and reactivity studies. The benefits of these instruments increase when used in parallel, as exemplified with a 3-month long deployment in an urban background site. Using two lung-deposited surface area (LDSA) instruments, a low-cost method was developed to assess the solid component of an aerosol by applying a catalytic stripper to the inlet stream of one LDSA instrument, resulting in only the solid fraction of the sample being measured (LDSAc). To determine the semi-volatile fraction of the sample, the LDSAC was compared to the LDSA without a catalytic stripper, thus measuring all particles (LDSAN). The ratio of LDSA (LDSAC/LDSAN) was used to assess the fraction of solid and semi-volatile particles within a sample. Here, a low ratio represents a high fraction of semi-volatile particles, with a high ratio indicating a high fraction of solid particles. During the 3-month urban background study in Birmingham, UK, it is shown that the LDSA ratios ranged from 0.2–0.95 indicating a wide variation in sources and subsequent semi-volatile fraction of particles. A black carbon (BC) instrument was used to provide a low-cost measure of LDSA to BC ratio. Comparatively, the LDSA to BC ratios obtained using low-cost sensors showed similar results to high-cost analyses for urban environments. During a high LDSAC/LDSAN ratio sampling period, representing high solid particle concentrations, an LDSA to BC probability distribution was shown to be multimodal, reflecting urban LDSA to BC ratio distributions measured with laboratory-grade instrumentation. Here, a low-cost approach for data analyses presents insight on particle characteristics and insight into PM composition and size, useful in source apportionment, health, and atmospheric studies.
      Citation: Atmosphere
      PubDate: 2022-05-06
      DOI: 10.3390/atmos13050747
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 748: Dendroclimatology in Latin America: A
           Review of the State of the Art

    • Authors: Oscar David Sánchez-Calderón, Teodoro Carlón-Allende, Manuel E. Mendoza, José Villanueva-Díaz
      First page: 748
      Abstract: The application of dendrochronology for understanding climatic variations has been of great interest to climatologists, ecologists, geographers, archeologists, among other sciences, particularly in recent decades when more dendrochronological studies have been developed. We analyzed and identified the current state and recent advances in dendroclimatology in Latin America for the period 1990 to 2020. We carried out reviews in ScienceDirect, Web of Science, and Scopus databases with the keywords “dendrochronology”, “dendroclimatology”, “dendrochronology and climatic variability”, “dendroclimatology and climatic variability”, “dendrochronology and trend”, and “dendroclimatology and trend” for each Latin American country. Results show that dendroclimatological research in the last 11 years has increased and has been mainly developed in temperate climate zones (83%) and tropical or subtropical areas (17%), where conifer species have been the most used with over 59% of the studies. However, broadleaf species for dendrochronological studies have also increased in the last decade. Dendroclimatological research in Latin America has provided important advances in the study of climatic variability by defining the response functions of tree-rings to climate and developing climatic reconstructions. Our research identified areas where it is necessary to increase dendroclimatic studies (e.g., dry and tropical forests), in addition to applying new techniques such as isotope analysis, blue intensity, dendrochemistry, among other tree-ring applications.
      Citation: Atmosphere
      PubDate: 2022-05-06
      DOI: 10.3390/atmos13050748
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 749: Climatic Trends of Variable Temperate
           Environment: A Complete Time Series Analysis during 1980–2020

    • Authors: Bilal Ahmad Lone, Sameera Qayoom, Aijaz Nazir, Shafat Ahmad Ahanger, Umer Basu, Tauseef Ahmad Bhat, Zahoor Ahmad Dar, Muntazir Mushtaq, Ayman El Sabagh, Walid Soufan, Muhammad Habib ur Rahman, Rasha Fathallah El-Agamy
      First page: 749
      Abstract: The western Himalayan region is susceptible to minor climate changes because of its fragile ecology, which might threaten the valley’s prestigious ecosystems and socio-economic components. The Himalayas’s local climate and weather are vulnerable to and interlinked with world-scale climatic changes since the region’s hydrology is predominantly dominated by snow and glaciers. The Himalayas, notably the Jammu and Kashmir region in the western Himalayas, has clearly shown distinct and robust evidence of climate change. This study used observed data to examine the climatic variability and trends of change in precipitation and temperature for the Kashmir valley between 1980 and 2020. Gulmarg, Pahalgam, Kokernag, Qazigund, Kupwara, and Srinagar (Shalimar) meteorological stations in the Kashmir valley were studied in detail for long- and short-term as well as localized fluctuations in temperature and precipitation. The annual temperature and precipitation fluctuations were calculated using Sen’s slope approach, and the sloping trend was determined using linear regression. The research showed statistically insignificant growing trends in maximum and minimum temperatures throughout the Kashmir valley. The average annual temperature in the Kashmir valley increased by 1.55 °C during the last 41 years (from 1980 to 2020), with a higher rise in maximum and minimum temperature by 2.00 and 1.10 °C, respectively. However, precipitation showed a non-significant decreasing trend concerning time series analysis over 1980 to 2020 in Kashmir valley. Results of annual average maximum temperature at all the stations revealed that Pahalgam (2.2 °C), Kokernag (1.8 °C), and Kupwara (1.8 °C) displayed a steep upsurge and statistically significant trends; however, annual average minimum temperature followed an increasing trend from 1980 to 2020 at all the stations except Shalimar. However, non-significant declining trends in precipitation were recorded at all the locations in Kashmir valley. This changing pattern of temperature and precipitation could have significant environmental consequences, affecting the western Himalayan region’s food security and ecological sustainability.
      Citation: Atmosphere
      PubDate: 2022-05-06
      DOI: 10.3390/atmos13050749
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 750: Convection Initiation Associated with the
           Merger of an Immature Sea-Breeze Front and a Gust Front in Bohai Bay
           Region, North China: A Case Study

    • Authors: Jingjing Zheng, Abuduwaili Abulikemu, Yan Wang, Meini Kong, Yiwei Liu
      First page: 750
      Abstract: The mechanism for convection initiation (CI) associated with the merger of an immature sea-breeze front (SBF) and gust front (GF) that occurred in North China on 31 July 2010 was investigated based on both observations and Weather Research and Forecasting (WRF) model simulation. The results show that many CIs occurred continuously in the merging area, and eventually resulted in an intense mesoscale convective system (MCS). The WRF simulation captured the general features of the SBF, GF, their merger processes and associated CIs, as well as the resulting MCS. Quantitative Lagrangian vertical momentum budgets, in which the vertical acceleration was decomposed into dynamic and buoyant components, were conducted along the backward trajectories of air parcels within a convective cell initiated in the merger processes. It was found that both of the dynamic and buoyant accelerations played important roles for the CI. The buoyant acceleration was dominated by the warming due to the latent heat release within the convective cell. Further decomposition of the dynamic acceleration showed the vertical twisting and extension contributed significantly to the dynamic acceleration, while the horizontal curvature was rather small. The vertical twisting was generated due to the vertical shear of horizontal wind, while the extension indicated convergences owing to a mid-level blocking convergence effect and squeezing, and (or) merging of the convergent leading edges of both fronts during their merger processes. The weak convergent leading edge of the immature SBF played an important role for the formation of the convergences.
      Citation: Atmosphere
      PubDate: 2022-05-06
      DOI: 10.3390/atmos13050750
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 751: Two Large Earthquakes Registered by the
           CSES Satellite during Its Earthquake Prediction Practice in China

    • Authors: Mei Li, Haitao Wang, Jie Liu, Xuhui Shen
      First page: 751
      Abstract: Two large earthquakes, the Maduo MS 7.4 earthquake and the Menyuan MS 6.9 earthquake, have been successfully recorded on the Chinese mainland, since the data of the CSES satellite were put into service for earthquake prediction work on the Chinese mainland at the end of April 2020. Obvious variations in O+ density and electron density were found during our weekly data processing work during 5–11 May 2021 and 28 December 2021–2 January 2022, respectively. Two warnings of impending events around the anomalous areas within two weeks had been reported immediately after the anomaly appearance. The Maduo MS 7.4 earthquake occurred on 22 May 2021 and the Menyuan MS 6.9 earthquake on 8 January 2022, during these two warning periods. More details were revealed after these two large shocks occurred. Ionospheric enhancement took place on 8 May 2021, with a magnitude of 41.6% for O+ density and 22.2% for electron density, a distance of 680 km from the Maduo epicenter, 14 days prior to the event. Before the Menyuan earthquake, ionospheric enhancement took place on 28 December 2021, as well as during its revisiting orbit on 2 January 2022, with a magnitude of 47.3% for O+ density and 38.4% for electron density, an epicentral distance of 120 km, 11 and 6 days prior to this event. The Kp index was also examined to avoid the influence from solar activities. Despite this, accurate earthquake prediction is not possible due to much uncertainty, such as the correct location and magnitude of an impending event. Thus, long-term practice and comprehensive investigation of the seismo-ionospheric influence are necessary in the future.
      Citation: Atmosphere
      PubDate: 2022-05-06
      DOI: 10.3390/atmos13050751
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 752: An Investigation of Near Real-Time Water
           Vapor Tomography Modeling Using Multi-Source Data

    • Authors: Laga Tong, Kefei Zhang, Haobo Li, Xiaoming Wang, Nan Ding, Jiaqi Shi, Dantong Zhu, Suqin Wu
      First page: 752
      Abstract: Global Navigation Satellite Systems (GNSS) tomography is a well-recognized modeling technique for reconstruction, which can be used to investigate the spatial structure of water vapor with a high spatiotemporal resolution. In this study, a refined near real-time tomographic model is developed based on multi-source data including GNSS observations, Global Forecast System (GFS) products and surface meteorological data. The refined tomographic model is studied using data from Hong Kong from 2 to 11 October 2021. The result is compared with the traditional model with physical constraints and is validated by the radiosonde data. It is shown that the root mean square error (RMSE) values of the proposed model and traditional model are 0.950 and 1.763 g/m3, respectively. The refined model can decrease the RMSE by about 46%, indicating a better performance than the traditional one. In addition, the accuracy of the refined tomographic model is assessed under both rainy and non-rainy conditions. The assessment shows that the RMSE in the rainy period is 0.817 g/m3, which outperforms the non-rainy period with the RMSE of 1.007 g/m3.
      Citation: Atmosphere
      PubDate: 2022-05-06
      DOI: 10.3390/atmos13050752
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 753: One Saddle Point and Two Types of
           Sensitivities within the Lorenz 1963 and 1969 Models

    • Authors: Bo-Wen Shen, Roger A. Pielke, Xubin Zeng
      First page: 753
      Abstract: The fact that both the Lorenz 1963 and 1969 models suggest finite predictability is well known. However, less well known is the fact that the mechanisms (i.e., sensitivities) within both models, which lead to finite predictability, are different. Additionally, the mathematical and physical relationship between these two models has not been fully documented. New analyses, along with a literature review, are performed here to provide insights regarding similarities and differences for these two models. The models represent different physical systems, one for convection and the other for barotropic vorticity. From the perspective of mathematical complexities, the Lorenz 1963 model is limited-scale and nonlinear; and the Lorenz 1969 model is closure-based, physically multiscale, mathematically linear, and numerically ill-conditioned. The former possesses a sensitive dependence of solutions on initial conditions, known as the butterfly effect, and the latter contains numerical sensitivities due to an ill-conditioned matrix with a large condition number (i.e., a large variance of growth rates). Here, we illustrate that the existence of a saddle point at the origin is a common feature that produces instability in both systems. Within the chaotic regime of the L63 nonlinear model, unstable growth is constrained by nonlinearity, as well as dissipation, yielding time varying growth rates along an orbit, and, thus, a dependence of (finite) predictability on initial conditions. Within the L69 linear model, multiple unstable modes at various growth rates appear, and the growth of a specific unstable mode (i.e., the most unstable mode during a finite time interval) is constrained by imposing a saturation assumption, thereby yielding a time varying system growth rate. Both models were interchangeably applied for qualitatively revealing the nature of finite predictability in weather and climate. However, only single type solutions were examined (i.e., chaotic and linearly unstable solutions for the L63 and L69 models, respectively), and the L69 system is ill-conditioned and easily captures numerical instability. Thus, an estimate of the predictability limit using either of the above models, with or without additional assumptions (e.g., saturation), should be interpreted with caution and should not be generalized as an upper limit for atmospheric predictability.
      Citation: Atmosphere
      PubDate: 2022-05-07
      DOI: 10.3390/atmos13050753
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 754: Crop Yield, Nitrogen Recovery, and Soil
           Mineral Nitrogen Accumulation in Extremely Arid Oasis Cropland under
           Long-Term Fertilization Management

    • Authors: Shimin Li, Xihe Wang, Changlin Kou, Jinling Lv, Jianhua Gao
      First page: 754
      Abstract: Crop yield stability and soil mineral nitrogen (Nmin) have rarely been evaluated from a long-term perspective in the extremely arid cropland regions of China. Therefore, a nationwide experiment aimed to optimize fertilizer application and increase productivity and nitrogen use efficiency in gray desert soils was initiated in 1990. Eight combinations of chemical fertilizers (CK, N, NK, NP, and NPK), straw return (NPKS), and manure amendments (NPKM and NPKM+) were tested for 24 years on spring wheat, winter wheat, and maize. The results displayed that the yield of three crops from balanced fertilizer treatments (NPK, NPKS, NPKM, and NPKM+) did not differ significantly after 24 years; however, reliable yield stability due to lower coefficient of variation (CV) and higher nitrogen harvest index (NHI) were recorded for manure amendment treatments. Compared to NPKM, NHI was lower for the NPKM+ treatment, but crop yield and stability did not improve, suggesting that the appropriate choice for manure amendment is important for guaranteeing food security in extremely arid regions. Balanced fertilizer treatments resulted in lower Nmin residual in the 300 cm soil profile, compared to unbalanced fertilizer treatments. The NPKS treatment gave the lowest value. In the 0–100 cm soil profile, Nmin was higher in NPKM than in the NPK treatment, suggesting that straw or manure amendment can effectively maintain Nmin in the topsoil undercurrent cropland management in arid areas. The NPKM treatment had the highest crop nitrogen recovery rate and the lowest nitrogen losses, further illustrating that manure amendment has higher N retention potential. Overall, although Nmin residues are relatively high in these regions, balanced fertilizer treatments, especially NPKM and NPKS, are the optimum strategies in extremely arid regions.
      Citation: Atmosphere
      PubDate: 2022-05-07
      DOI: 10.3390/atmos13050754
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 755: Comparison of Wildfire Meteorology and
           Climate at the Adriatic Coast and Southeast Australia

    • Authors: Ivana Čavlina Tomašević, Kevin K. W. Cheung, Višnjica Vučetić, Paul Fox-Hughes
      First page: 755
      Abstract: Wildfire is one of the most complex natural hazards. Its origin is a combination of anthropogenic factors, urban development and weather plus climate factors. In particular, weather and climate factors possess many spatiotemporal scales and various degrees of predictability. Due to the complex synergy of the human and natural factors behind the events, every wildfire is unique. However, there are indeed common meteorological and climate factors leading to the high fire risk before certain ignition mechanismfigures occur. From a scientific point of view, a better understanding of the meteorological and climate drivers of wildfire in every region would enable more effective seasonal to annual outlook of fire risk, and in the long term, better applications of climate projections to estimate future scenarios of wildfire. This review has performed a comparison study of two fire-prone regions: southeast Australia including Tasmania, and the Adriatic coast in Europe, especially events in Croatia. The former is well known as part of the ‘fire continent’, and major resources have been put into wildfire research and forecasting. The Adriatic coast is a region where some of the highest surface wind speeds, under strong topographic effect, have been recorded and, over the years, have coincided with wildfire ignitions. Similar synoptic background and dynamic origins of the meso-micro-scale meteorological conditions of these high wind events as well as the accompanied dryness have been identified between some of the events in the two regions. We have also reviewed how the researchers from these two regions have applied different weather indices and numerical models. The status of estimating fire potential under climate change for both regions has been evaluated. This review aims to promote a global network of information exchange to study the changing anthropogenic and natural factors we have to confront in order to mitigate and adapt the impacts and consequences from wildfire.
      Citation: Atmosphere
      PubDate: 2022-05-07
      DOI: 10.3390/atmos13050755
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 756: Retrieval of High-Resolution Aerosol
           Optical Depth for Urban Air Pollution Monitoring

    • Authors: Rui Bai, Yong Xue, Xingxing Jiang, Chunlin Jin, Yuxin Sun
      First page: 756
      Abstract: Aerosol Optical Depth (AOD) is one of the most important parameters of aerosol and a key physical quantity to characterize atmospheric turbidity and air pollution. Accurate retrieval of AOD is of great significance for air quality assessment. However, the spatial resolution of the currently widely used Moderate Resolution Imaging Spectroradiometer (MODIS) AOD products is too low to meet the application research of atmospheric environment at the regional scale. In 2013, China launched the Gaofen-1 (GF-1) satellite, which provides a new idea for AOD retrieval. In this paper, we apply the synergetic use of TERRA and AQUA satellite MODIS data to calculate the high-resolution AOD over Beijing based on the Synergetic Retrieval of Aerosol Properties algorithm (SRAP) and discussed scale conversion problems between AODs with different resolutions. To obtain the 100 m MODIS data, we use GF-1 wide-field-of-view data to downscale 1 km MODIS data based on mutual information method. The retrieved AOD has a spatial resolution of 100 m and can cover many land surface types. Preliminary validation was carried out with the Aerosol Robotic Network (AERONET) ground observation data. The correlation coefficient is about 0.88, and the root-mean-square error is about 0.15. Due to the high resolution of retrieved results, more detailed features can be provided in the spatial distribution. The experimental results show that the method has high precision, and further verification work is continuing.
      Citation: Atmosphere
      PubDate: 2022-05-07
      DOI: 10.3390/atmos13050756
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 757: Knowledge-Enhanced Deep Learning for
           Simulation of Extratropical Cyclone Wind Risk

    • Authors: Reda Snaiki, Teng Wu
      First page: 757
      Abstract: Boundary-layer wind associated with extratropical cyclones (ETCs) is an essential element for posing serious threats to the urban centers of eastern North America. Using a similar methodology for tropical cyclone (TC) wind risk (i.e., hurricane tracking approach), the ETC wind risk can be accordingly simulated. However, accurate and efficient assessment of the wind field inside the ETC is currently not available. To this end, a knowledge-enhanced deep learning (KEDL) is developed in this study to estimate the ETC boundary-layer winds over eastern North America. Both physics-based equations and semi-empirical formulas are integrated as part of the system loss function to regularize the neural network. More specifically, the scale-analysis-based reduced-order Navier–Stokes equations that govern the ETC wind field and the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA) ERA-interim data-based two-dimensional (2D) parametric formula (with respect to radial and azimuthal coordinates) that prescribes an asymmetric ETC pressure field are respectively employed as rationalism-based and empiricism-based knowledge to enhance the deep neural network. The developed KEDL, using the standard storm parameters (i.e., spatial coordinates, central pressure difference, translational speed, approach angle, latitude of ETC center, and surface roughness) as the network inputs, can provide the three-dimensional (3D) boundary-layer wind field of an arbitrary ETC with high computational efficiency and accuracy. Finally, the KEDL-based wind model is coupled with a large ETC synthetic track database (SynthETC), where 6-hourly ETC center location and pressure deficit are included to effectively assess the wind risk along the US northeast coast in terms of annual exceedance probability.
      Citation: Atmosphere
      PubDate: 2022-05-08
      DOI: 10.3390/atmos13050757
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 758: A Novel Framework Based on the Stacking
           Ensemble Machine Learning (SEML) Method: Application in Wind Speed
           Modeling

    • Authors: Amirreza Morshed-Bozorgdel, Mojtaba Kadkhodazadeh, Mahdi Valikhan Valikhan Anaraki, Saeed Farzin
      First page: 758
      Abstract: Wind speed (WS) is an important factor in wind power generation. Because of this, drastic changes in the WS make it challenging to analyze accurately. Therefore, this study proposed a novel framework based on the stacking ensemble machine learning (SEML) method. The application of a novel framework for WS modeling was developed at sixteen stations in Iran. The SEML method consists of two levels. In particular, eleven machine learning (ML) algorithms in six categories neuron based (artificial neural network (ANN), general regression neural network (GRNN), and radial basis function neural network (RBFNN)), kernel based (least squares support vector machine-grid search (LSSVM-GS)), tree based (M5 model tree (M5), gradient boosted regression (GBR), and least squares boost (LSBoost)), curve based (multivariate adaptive regression splines (MARS)), regression based (multiple linear regression (MLR) and multiple nonlinear regression (MNLR)), and hybrid algorithm based (LSSVM-Harris hawks optimization (LSSVM-HHO)) were selected as the base algorithms in level 1 of the SEML method. In addition, LSBoost was used as a meta-algorithm in level 2 of the SEML method. For this purpose, the output of the base algorithms was used as the input for the LSBoost. A comparison of the results showed that using the SEML method in WS modeling greatly affected the performance of the base algorithms. The highest correlation coefficient (R) in the WS modeling at the sixteen stations using the SEML method was 0.89. The SEML method increased the WS modeling accuracy by >43%.
      Citation: Atmosphere
      PubDate: 2022-05-08
      DOI: 10.3390/atmos13050758
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 759: The Effect of Metro Construction on the
           Air Quality in the Railway Transport System of Sydney, Australia

    • Authors: Puchanee Larpruenrudee, Nic C. Surawski, Mohammad S. Islam
      First page: 759
      Abstract: Sydney Metro is the biggest project of Australia’s public transport, which was designed to provide passengers with more trains and faster services. This project was first implemented in 2017 and is planned to be completed in 2024. As presented, the project is currently in the construction stage located on the ground stations of the Sydney Trains Bankstown line (T3). Based on this stage, several construction activities will generate air pollutants, which will affect the air quality around construction areas. Moreover, it might cause health problems to people around there and also the passengers who usually take the train on the T3 line. However, there is no specific data for air quality inside the train that may be affected by the construction from each area. Therefore, the aim of this study is to investigate the air quality inside the train carriage of all related stations from the T3 line. A sampling campaign was conducted over 3 months to analyze particulate matter (PM) concentration, the main indoor pollutants including formaldehyde (HCHO) and total volatile organic compounds (TVOC). The results of the T3 line were analyzed and compared to Airport & South line (T8) that were not affected by the project’s construction. The results of this study indicate that Sydney Metro construction activities insignificantly affected the air quality inside the train. Average PM2.5 and PM10 inside the train of T3 line in the daytime were slightly higher than in the nighttime. The differences in PM2.5 and PM10 concentrations from these periods were around 6.8 μg/m3 and 12.1 μg/m3, respectively. The PM concentrations inside the train from the T3 line were slightly higher than the T8 line. However, these concentrations were still lower than those recommended by the national air quality standards. For HCHO and TVOC, the average HCHO and TVOC concentrations were less than the recommendation criteria.
      Citation: Atmosphere
      PubDate: 2022-05-08
      DOI: 10.3390/atmos13050759
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 760: Sr1-xKxFeO3 Perovskite Catalysts with
           Enhanced RWGS Reactivity for CO2 Hydrogenation to Light Olefins

    • Authors: Yuanhao Hou, Xinyu Wang, Ming Chen, Xiangyu Gao, Yongzhuo Liu, Qingjie Guo
      First page: 760
      Abstract: The catalytic hydrogenation of CO2 to light olefins (C2–C4) is among the most practical approaches to CO2 utilization as an essential industrial feedstock. To achieve a highly dispersed active site and enhance the reactivity of the reverse water–gas shift (RWGS) reaction, ABO3-type perovskite catalysts Sr1-xKxFeO3 with favorable thermal stability and redox activity are reported in this work. The role of K-substitution in the structure–performance relationship of the catalysts was investigated. It indicated that K-substitution expedited the oxygen-releasing process of the SrFeO3 and facilitated the synchronous formation of active-phase Fe3O4 for the reverse water–gas shift (RWGS) reaction and Fe5C2 for the Fischer–Tropsch synthesis (FTS). At the optimal substitution amount, the conversion of CO2 and the selectivity of light olefins achieved 30.82% and 29.61%, respectively. Moreover, the selectivity of CO was up to 45.57% even when H2/CO2=4 due to CO2-splitting reactions over the reduced Sr2Fe2O5. In addition, the reversibility of perovskite catalysts ensured the high dispersion of the active-phase Fe3O4 and Fe5C2 in the SrCO3 phase. As the rate-determining step of the CO2 hydrogenation reaction to light olefins over Sr1-xKxFeO3 perovskite catalysts, FTS should be further tailored by partial substitution of the B site. In sum, the perovskite-derived catalyst investigated in this work provided a new idea for the rational design of a catalyst for CO2 hydrogenation to produce light olefins.
      Citation: Atmosphere
      PubDate: 2022-05-08
      DOI: 10.3390/atmos13050760
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 761: Atmospheric Carbonyl Compounds in the
           Central Taklimakan Desert in Summertime: Ambient Levels, Composition and
           Sources

    • Authors: Chunmei Geng, Shijie Li, Baohui Yin, Chao Gu, Yingying Liu, Liming Li, Kangwei Li, Yujie Zhang, Merched Azzi, Hong Li, Xinhua Wang, Wen Yang, Zhipeng Bai
      First page: 761
      Abstract: Although carbonyl compounds are a key species with atmospheric oxidation capacity, their concentrations and sources have not been sufficiently characterized in various atmospheres, especially in desert areas. In this study, atmospheric carbonyl compounds were measured from 16 May to 15 June 2018 in Tazhong in the central Taklimakan Desert, Xinjiang Uygur Autonomous Region, China. Concentrations, chemical compositions, and sources of carbonyl compounds were investigated and compared with those of different environments worldwide. The average concentration of total carbonyls during the sampling period was 11.79 ± 4.03 ppbv. Formaldehyde, acetaldehyde, and acetone were the most abundant carbonyls, with average concentrations of 6.08 ± 2.37, 1.68 ± 0.78, and 2.52 ± 0.68 ppbv, respectively. Strong correlations between formaldehyde and other carbonyls were found, indicating same or similar sources and sinks. A hybrid single-particle Lagrangian integrated trajectory was used to analyze 72 h back trajectories. The values of C1/C2 (formaldehyde to acetaldehyde, 3.22–4.59) and C2/C3 (acetaldehyde to propionaldehyde, 15.00–17.03) from different directions and distances of the trajectories were consistent with the characteristics of a remote area. Relative to various environments, the carbonyl concentration in the Tazhong desert site was lower than that in urban areas and higher than that in suburban and remote areas, implying contributions from local primary and secondary sources. The obtained data can be used to improve the source and sink estimation of carbonyls at the regional scale.
      Citation: Atmosphere
      PubDate: 2022-05-08
      DOI: 10.3390/atmos13050761
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 762: Correction: Elnumin et al. Evaluating the
           Performance of IRI-2016 Using GPS-TEC Measurements over the Equatorial
           Region. Atmosphere 2021, 12, 1243

    • Authors: Nouf Abd Elmunim, Mardina Abdullah, Siti Aminah Bahari
      First page: 762
      Abstract: In the original publication [...]
      Citation: Atmosphere
      PubDate: 2022-05-09
      DOI: 10.3390/atmos13050762
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 763: Using Objective Analysis for the
           Assimilation of Satellite-Derived Aerosol Products to Improve PM2.5
           Predictions over Europe

    • Authors: Mounir Chrit, Marwa Majdi
      First page: 763
      Abstract: We used the objective analysis method in conjunction with the successive correction method to assimilate MODerate resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth (AOD) data into the Chimère model in order to improve the modeling of fine particulate matter (PM2.5) concentrations and AOD field over Europe. A data assimilation module was developed to adjust the daily initial total column aerosol concentrations based on a forecast-analysis cycling scheme. The model is then evaluated during one-month winter period to examine how such a data assimilation technique pushes the model results closer to surface observations. This comparison showed that the mean biases of both surface PM2.5 concentrations and the AOD field could be reduced from −34 to −15% and from −45 to −27%. The assimilation, however, leads to false alarms because of the difficulty in distributing AOD550 over different particle sizes. The impact of the influence radius is found to be small and depends on the density of satellite data. This work, although preliminary, is important in terms of near-real time air quality forecasting using the Chimère model and can be further developed to improve modeled PM2.5 and ozone concentrations.
      Citation: Atmosphere
      PubDate: 2022-05-09
      DOI: 10.3390/atmos13050763
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 764: Innovative Trend Analysis of High-Altitude
           Climatology of Kashmir Valley, North-West Himalayas

    • Authors: Ishfaq Gujree, Ijaz Ahmad, Fan Zhang, Arfan Arshad
      First page: 764
      Abstract: This paper investigates the annual and seasonal variations in the minimum and maximum air temperature (Tmin and Tmax) and precipitation over Kashmir valley, Northwestern Himalayas from 1980–2019 by using the innovative trend analysis (ITA), Mann-Kendall (MK), and Sen’s slope estimator methods. The results indicated that the annual and seasonal Tmin and Tmax are increasing for all the six climatic stations, whereas four of them exhibit significant increasing trends at (α = 0.05). Moreover, this increase in Tmin and Tmax was found more pronounced at higher altitude stations, i.e., Pahalgam (2650 m asl) and Gulmarg (2740 m asl). The annual and seasonal precipitation patterns for all climatic stations showed downward trends. For instance, Gulmarg station exhibited a significant downward trend for the annual, spring, and winter seasons (α = 0.05). Whereas, Qazigund showed a significant downward trend for the annual and spring seasons (α = 0.05). The overall analysis revealed that the increased Tmin and Tmax trends during the winter season are one of the reasons behind the early onset of melting of snow and the corresponding spring season. Furthermore, the observed decreased precipitation trends could result in making the region vulnerable towards drier climatic extremes. Such changes in the region’s hydro-meteorological processes shall have severe implications on the delicate ecological balance of the fragile environment of the Kashmir valley.
      Citation: Atmosphere
      PubDate: 2022-05-09
      DOI: 10.3390/atmos13050764
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 765: The December 2021 Marshall Fire:
           Predictability and Gust Forecasts from Operational Models

    • Authors: Robert G. Fovell, Matthew J. Brewer, Richard J. Garmong
      First page: 765
      Abstract: We analyzed meteorological conditions that occurred during the December 2021 Boulder, Colorado, downslope windstorm. This event is of particular interest due to the ignition and spread of the Marshall Fire, which quickly became the most destructive wildfire in Colorado history. Observations indicated a rapid onset of fast winds with gusts as high as 51 m/s that generally remained confined to the east-facing slopes and foothills of the Rockies, similar to previous Boulder windstorms. After about 12 h, the windstorm shifted into a second, less intense phase. Midtropospheric winds above northwestern Colorado weakened prior to the onset of strong surface winds and the event strength started waning as stronger winds moved back into the area. Forecasts from NOAA high-resolution operational models initialized more than a few hours prior to windstorm onset did not simulate the start time, development rate and/or maximum strength of the windstorm correctly, and day-ahead runs even failed to develop strong downslope windstorms at all. Idealized modeling confirmed that predictability was limited by errors on the synoptic scale affecting the midtropospheric wind conditions representing the Boulder windstorm’s inflow environment. Gust forecasts for this event were critically evaluated.
      Citation: Atmosphere
      PubDate: 2022-05-09
      DOI: 10.3390/atmos13050765
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 766: Characterizing Real-World Particle-Bound
           Polycyclic Aromatic Hydrocarbon Emissions from Diesel-Fueled Construction
           Machines

    • Authors: Narayan Babu Dhital, Lin-Chi Wang, Hsi-Hsien Yang, Nicholas Kiprotich Cheruiyot, Che-Hsuan Lee
      First page: 766
      Abstract: This study employed an onboard emission measurement system to measure the real-world emission factors of particulate matter (PM), particle-bound polycyclic aromatic hydrocarbons (PAHs), and gaseous air pollutants for different types of diesel-fueled non-road construction machines operated inside confined spaces within a brick manufacturing factory located in Taiwan. To the best knowledge of the authors, this is the first study that reports real-world PM, PAH, and gaseous pollutant emission factors for non-road engines in Taiwan. The mean real-world fuel-specific emission factors of PM, carbon monoxide, total hydrocarbons, and nitric oxide were 0.712–1.17, 8.27–17.9, 3.04–5.77, and 38.1–96.8 g/kg-fuel, respectively, for the test machines. Likewise, mean ΣPAHs emission factors ranged from 157 to 230 μg/kg-fuel for three types of test machines. Further, the average emission of particle-bound PAH per unit PM emission ranged from 213 to 384 μg-PAH/g-PM. Among the analyzed PAHs, the medium-molecular weight (3- and 4-ring) compounds contributed to the largest share of particle-bound PAH emissions. However, in terms of Benzo[a]pyrene equivalent (BaPeq) toxicity, the high-molecular weight (5- and 6-ring) PAHs were more important, as they had the highest BaPeq toxic emission factors. This study provides detailed composition and emission factors of particle-bound PAHs in non-road diesel construction machine emissions, which may be useful as a chemical fingerprint for source apportionment studies.
      Citation: Atmosphere
      PubDate: 2022-05-09
      DOI: 10.3390/atmos13050766
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 767: Impact of Environmental Regulation on
           Efficiency of Green Innovation in China

    • Authors: Tongtong Shen, Dongju Li, Yuanyuan Jin, Jie Li
      First page: 767
      Abstract: The implementation of a reasonable and effective environmental regulation policy can compensate for the dual externalities of green technology innovation and improve green innovation efficiency. Therefore, environmental regulation policy has gradually become an effective means of solving ecological environment problems and achieving green industrial transformation. This paper measures the green innovation efficiency of 30 provinces in China from 2009 to 2019 using the SBM (slacks-based measure) of super-efficiency based on the undesirable output. The dynamic panel regression model is established to explore the impact of different environmental regulations on green innovation efficiency and regional differences. The results reveal that the green innovation efficiency of the 30 provinces shows a fluctuating upward trend, but that differences among provinces are relatively significant. There is a nonlinear relationship between environmental regulation and green innovation efficiency. The impact of command-control and market incentive environmental regulations on green innovation efficiency shows inverted N-shaped and U-shaped patterns, respectively. In different regions, the impact of environmental regulation on green innovation efficiency is also different. In order to ensure that environmental regulation promotes green innovation efficiency, some recommendations are proposed for the government, enterprises, and three regions, respectively.
      Citation: Atmosphere
      PubDate: 2022-05-09
      DOI: 10.3390/atmos13050767
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 768: Application of Affinity Propagation
           Clustering Method in Medium and Extended Range Forecasting of Heavy
           Rainfall Processes in China

    • Authors: Wei Huang, Yong Li
      First page: 768
      Abstract: Based on the precipitation data of an ensemble forecast from the European Centre for Medium-Range Weather Forecasts, we establish a clustering model named EOF_AP by using the empirical orthogonal function decomposition and the affinity propagation clustering method. Then, using EOF_AP, we conducted research on the identification and classification of the characteristics of medium and extended range forecasts on 11 heavy rainfall events in the middle–lower reaches of the Yangtze River, North China, and the Huanghuai region, from June to September in 2021. We then selected two representative cases to analyze the common characteristics in detail to evaluate the effect of the model. The results show that the EOF_AP clustering model can better identify and classify the main rainfall pattern characteristics, and their corresponding occurrence probability of heavy rainfall processes, on the basis of comprehensively retaining the main forecast information of ensemble members with a few representative types. The rainfall pattern characteristics of some types with low occurrence probability can be identified, such as the extreme type. The distributions of rainfall patterns of the same type are basically consistent, whereas those among different types are distinct. Moreover, through the comparison of the forecast results with different starting times, we analyze the forecast performance of ensemble members and the variation trend of forecast results. We hope this study can provide a reference for the probability forecast of medium and extended range heavy rainfall process.
      Citation: Atmosphere
      PubDate: 2022-05-09
      DOI: 10.3390/atmos13050768
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 769: Sources and Variability of Plutonium in
           Chinese Soils: A Statistical Perspective with Moving Average

    • Authors: Sixuan Li, Youyi Ni, Qiuju Guo
      First page: 769
      Abstract: We investigated the different sources and their corresponding impact areas of Pu in Chinese surface soils to illustrate the state-of-the-art of the sources, levels and distributions of 240Pu/239Pu atom ratios as well as 239+240Pu activity concentrations in China. For the first time a moving average strategy in combination with statistical analysis was employed to partition geographic areas in China based on the reported 240Pu/239Pu atom ratio and 239+240Pu concentration data from public literature. During the partitioning, the median (MED) of the dataset was basically employed as a criteria in place of the commonly used arithmetic average (AM). Concisely, three areas were partitioned according to the different influences of Pu from the Lop Nor (LNTS) and Semipalatinsk (STS) test sites and the global fallout. The partitioned Ternary area (80° E–105° E, 35° N–50° N) was supposed to have multiple sources of Pu including the STS and LNTS besides the global fallout, which was characterized with slightly lower 240Pu/239Pu atom ratios (MED = 0.174) as well as elevated 239+240Pu concentrations (MED = 0.416 mBq/g). Meanwhile, the Binary area (35° N–45° N, 100° E–115° E) was considered to have received the extra contribution from the high-yield nuclear tests at the LNTS besides the global fallout, resulting in the highest 240Pu/239Pu atom ratios (MED = 0.200) across China. The remaining area was marked as the Unitary area, where it only received the exclusive contribution of global fallout. Furthermore, through the statistical analysis of the 240Pu/239Pu data in the Unitary area, we recommended a value of 0.186 ± 0.021 (AM ± SD) as a representative or area-specific 240Pu/239Pu atom ratio baseline to characterize the global fallout derived Pu in Chinese soils.
      Citation: Atmosphere
      PubDate: 2022-05-10
      DOI: 10.3390/atmos13050769
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 770: Influence of Relative Humidity on the
           Characteristics of Filter Cake Using Particle Flow Code Simulation

    • Authors: Dinglian Shi, Jianlong Li, Yongnan Du, Quanquan Wu, Shan Huang, Hong Huang, Daishe Wu
      First page: 770
      Abstract: To study the effect of air humidity on particle filtration performance, the Particle Flow Code (PFC) calculation program was used to numerically simulate the formation process of filter cake. The effects of relative air humidity on the deposition morphology, porosity and filtration resistance characteristics of the filter cake were revealed. The results show that relative humidity (RH) is mainly reflected in the density and surface viscosity of the particles. It was found that the higher the relative humidity, the higher the particle moisture content, the greater the density, and the greater the surface viscosity. With an increase in the particle density or with a decrease in the viscosity, the bridging phenomenon of particle deposition became more obvious; the dendritic deposition phenomenon became weaker; and, therefore, the filter cake structure became denser; the porosity decreased; and the total filtration resistance increased. As the humidity changed, the actual density and viscosity of the particles changed simultaneously with different degrees, which caused different variation trends of the filter cake characteristics. Three different types of particles, DM828 (Starch), PVA1788 (Polyvinyl Alcohol) and Polyacrylamide (Polyacrylic acid), were selected for comparison. For the studied PVA1788 and Polyacrylamide particles, with an increase in relative humidity, the porosity of the filter cake increased monotonously, while the total filtration resistance decreased monotonously. For DM828 particles, the cake porosity first decreased and then increased, and the total filtration resistance first increased and then decreased, with an inflection point at 30% RH. By combining these results with existing reports, three kinds of variations of the filtration performance with humidity could be determined: (1) as the humidity increased, the filtration resistance first increased and then decreased; (2) the filtration resistance decreased; and (3) the filtration resistance increased.
      Citation: Atmosphere
      PubDate: 2022-05-10
      DOI: 10.3390/atmos13050770
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 771: Sensitivity to Different Reanalysis Data
           on WRF Dynamic Downscaling for South China Sea Wind Resource Estimations

    • Authors: Anandh Thankaswamy, Tao Xian, Yong-Feng Ma, Lian-Ping Wang
      First page: 771
      Abstract: As the world is moving toward greener forms of energy, to mitigate the effects of global warming due to greenhouse gas emissions, wind energy has risen as the most invested-in renewable energy. China, as the largest consumer of world energy, has started investing heavily in wind energy resources. Most of the wind farms in China are located in Northern China, and they possess the disadvantage of being far away from the energy load. To mitigate this, recently, offshore wind farms are being proposed and invested in. As an initial step in the wind farm setting, a thorough knowledge of the wind energy potential of the candidate region is required. Here, we conduct numerical experiments with Weather Research and Forecasting (WRF) model forced by analysis (NCEP-FNL) and reanalysis (ERA-Interim and NCEP-CFSv2) to find the best choice in terms of initial and boundary data for downscale in the South China Sea. The simulations are validated by observation and several analyses. Specific locations along China’s coast are analyzed and validated for their wind speed, surface temperature, and energy production. The analysis shows that the model forced with ERA-Interim data provides the best simulation of surface wind speed characteristics in the South China Sea, yet the other models are not too far behind. Moreover, the analysis indicates that the Taiwan Strait along the coastal regions of China is an excellent region to set up wind farms due to possessing the highest wind speeds along the coast.
      Citation: Atmosphere
      PubDate: 2022-05-10
      DOI: 10.3390/atmos13050771
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 772: European Grid Dataset of Actual
           Evapotranspiration, Water Availability and Effective Precipitation

    • Authors: Mărgărit-Mircea Nistor, Alfrendo Satyanaga, Ştefan Dezsi, Ionel Haidu
      First page: 772
      Abstract: The sustainability of a territory is closely related to its resources. Due to climate change, the most precious natural resource, water, has been negatively affected by climatic conditions in terms of quantity and quality. CLIMAT datasets of 1 km2 spatial resolution were used and processed in the ArcGIS environment to generate maps of actual evapotranspiration, water availability, and effective precipitation for the periods of 1961–1990 (1990s), 2011–2040 (2020s), and 2041–2070 (2050s). The product is of paramount importance for the analysis of the actual situation in Europe indicating high water availability in the Alps Range, the Carpathians Mountains, Northern European countries, and the British Islands. On the other hand, low water availability has been evidenced in the Southern and Eastern European areas. For the future period (2050s), the monthly potential evapotranspiration is expected to increase by 30%. The climate models also show an increase in the actual evapotranspiration between past and future periods by 40%. The changes in water availability and effective precipitation between the past (1990s) and future (2050s) indicate decreases of 10%. The most affected areas by climate change are located within the Mediterranean areas, the Iberian Peninsula, and Eastern Europe.
      Citation: Atmosphere
      PubDate: 2022-05-10
      DOI: 10.3390/atmos13050772
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 773: Intercomparison of Vaisala RS92 and RS41
           Radiosonde Temperature Sensors under Controlled Laboratory Conditions

    • Authors: Marco Rosoldi, Graziano Coppa, Andrea Merlone, Chiara Musacchio, Fabio Madonna
      First page: 773
      Abstract: Radiosoundings are essential for weather and climate applications, as well as for calibration and validation of remote sensing observations. Vaisala RS92 radiosondes have been widely used on a global scale until 2016; although in the fall of 2013, Vaisala introduced the RS41 model to progressively replace the RS92. To ensure the highest quality and homogeneity of measurements following the transition from RS92 to RS41, intercomparisons of the two radiosonde models are needed. A methodology was introduced to simultaneously test and compare the two radiosonde models inside climatic chambers, in terms of noise, calibration accuracy, and bias in temperature measurements. A pair of RS41 and RS92 radiosondes has been tested at ambient pressure under very different temperature and humidity conditions, reproducing the atmospheric conditions that a radiosonde can meet at the ground before launch. The radiosondes have also been tested before and after fast (within ≈ 10 s) temperature changes of about ±20 °C, simulating a scenario similar to steep thermal changes that radiosondes can meet when passing from indoor to outdoor environment during the pre-launch phase. The results show that the temperature sensor of RS41 is less affected by noise and more accurate than that of RS92, with noise values less than 0.06 °C for RS41 and less than 0.1 °C for RS92. The deviation from the reference value, referred to as calibration error, is within ±0.1 °C for RS41 and the related uncertainty (hereafter with coverage factor k = 1) is less than 0.06 °C, while RS92 is affected by a cold bias in the calibration, which ranges from 0.1 °C up to a few tenths of a degree, with a calibration uncertainty less than 0.1 °C. The temperature bias between RS41 and RS92 is within ±0.1 °C, while its uncertainty is less than 0.1 °C. The fast and steep thermal changes that radiosondes can meet during the pre-launch phase might lead to a noise increase in temperature sensors during radiosoundings, up to 0.1 °C for RS41 and up to 0.3 °C for RS92, with a similar increase in their calibration uncertainty, as well as an increase in the uncertainty of their bias up to 0.3 °C.
      Citation: Atmosphere
      PubDate: 2022-05-10
      DOI: 10.3390/atmos13050773
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 774: Influence of the Grid Resolutions on the
           Computer-Simulated Surface Air Pollution Concentrations in Bulgaria

    • Authors: Georgi Gadzhev, Kostadin Ganev, Plamen Mukhtarov
      First page: 774
      Abstract: The present study aims to demonstrate the effects of horizontal grid resolution on the simulated pollution concentration fields over Bulgaria. The computer simulations are performed with a set of models used worldwide—the Weather Research and Forecasting Model (WRF)—the meteorological preprocessor, the Community Multiscale Air Quality Modeling System (CMAQ)—chemical transport model, Sparse Matrix Operator Kernel Emissions (SMOKE)—emission model. The large-scale (background) meteorological data used in the study were taken from the ‘NCEP Global Analysis Data’ with a horizontal resolution of 1° × 1°. Using the ‘nesting’ capabilities of the WRF and CMAQ models, a resolution of 9 km was achieved for the territory of Bulgaria by sequentially solving the task in several consecutive nested areas. Three cases are considered in this paper: Case 1: The computer simulations result from the domain with a horizontal resolution (both of the emission source description and the grid) of 27 km.; Case 2: The computer simulations result from the domain with a horizontal resolution (both of the emission source description and the grid) of 9 km.; Case 3: A hybrid case with the computer simulations performed with a grid resolution of 9 km, but with emissions such as in the 27 km × 27 km domain. The simulations were performed, for all the three cases, for the period 2007–2014 year, thus creating an ensemble large and comprehensive enough to reflect the most typical atmospheric conditions with their typical recurrence. The numerical experiments showed the significant impact of the grid resolution not only in the pollution concentration pattern but also in the demonstrated generalized characteristics. Averaged over a large territory (Bulgaria); however, the performances for cases one and two are quite similar. Bulgaria is a country with a complex topography and with several considerably large point sources. Thus, some of the conclusions made, though based on Bulgarian-specific experiments, may be of general interest.
      Citation: Atmosphere
      PubDate: 2022-05-10
      DOI: 10.3390/atmos13050774
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 775: In Situ Observations of Wind Turbines
           Wakes with Unmanned Aerial Vehicle BOREAL within the MOMEMTA Project

    • Authors: Sara Alaoui-Sosse, Pierre Durand, Patrice Médina
      First page: 775
      Abstract: The MOMENTA project combines in situ and remote sensing observations, wind tunnel experiments, and numerical modeling to improve the knowledge of wake structure in wind farms in order to model its impact on the wind turbines and to optimize wind farm layout. In this context, we present the results of a first campaign conducted with a BOREAL unmanned aerial vehicle (UAV) designed to measure the three wind components with a horizontal resolution as fine as 3 m. The observations were performed at a wind farm where six turbines were installed. Despite the strong restrictions imposed by air traffic control authorities, we were able to document the wake area of two turbines during two flights in April 2021. The flight patterns consisted of horizontal racetracks with various orientations performed at different distances from the wind turbines; thus, horizontal wind speed fields were built in which the wind reduction area in the wake is clearly displayed. On a specific day, we observed an overspeed area between the individual wakes of two wind turbines, likely resulting from the cumulative effect of the wakes generated behind two successive rows of turbines. This study demonstrates the potential of BOREAL to document turbine wakes.
      Citation: Atmosphere
      PubDate: 2022-05-10
      DOI: 10.3390/atmos13050775
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 776: Prediction of Emission Reduction Potential
           from Road Diesel Vehicles in the Beijing–Tianjin–Hebei (BTH)
           Region, China

    • Authors: Xiurui Guo, Yao Liu, Dongsheng Chen, Xiaoqian Gong
      First page: 776
      Abstract: China has started to focus on the reduction in pollutants from diesel vehicles with high emission intensities in recent years. Therefore, it is essential and valuable to conduct a deep and detailed exploration of the reduction potential from diesel vehicles and compare the abatement effect from different control measures in upcoming decades. This study attempted to estimate the present emissions of four conventional pollutants from diesel vehicles by applying the Computer Program to Calculate Emissions from Road Transport (COPERT) model, and to predict the future emission trends under different scenarios during 2019–2030, taking the Beijing–Tianjin–Hebei (BTH) region as the case study area. In addition, we analyzed the emission reduction potential of diesel vehicles and compared the reduction effects from different control measures. The results showed that the CO and NOx emissions from diesel vehicles in this region could increase by 104.8% and 83.9%, respectively, given no any additional control measures adopted over the next decade. The largest emission reduction effect could be achieved under the comprehensive scenario, which means that vehicular diesel emissions in 2030 could decrease by 74.8–94.0% compared to values in 2018. The effect of emission reduction under the emission standards’ upgrade scenario could cause a gradual increase and achieve a 19.8–82.6% reduction for the four pollutants in 2030. Furthermore, the new energy vehicle promotion scenario could achieve a considerable reduction effect. It could also offer better emission reduction effects under the highway to railway scenario for Tianjin and Hebei provinces. The old vehicle elimination scenario could have a considerable reduction effect, but only in the short term. Furthermore, emission reductions could be mainly influenced by heavy diesel trucks. These results can provide scientific support to formulate effective reduction measures to diesel vehicles for policy makers.
      Citation: Atmosphere
      PubDate: 2022-05-10
      DOI: 10.3390/atmos13050776
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 777: Soil Enzyme Activity Regulates the
           Response of Soil C Fluxes to N Fertilization in a Temperate Cultivated
           Grassland

    • Authors: Yan Yang, Huajun Fang, Shulan Cheng, Lijun Xu, Mingzhu Lu, Yifan Guo, Yuna Li, Yi Zhou
      First page: 777
      Abstract: Exogenous nitrogen (N) inputs greatly change the emission and uptake of carbon dioxide (CO2) and methane (CH4) from temperate grassland soils, thereby affecting the carbon (C) budget of regional terrestrial ecosystems. Relevant research focused on natural grassland, but the effects of N fertilization on C exchange fluxes from different forage soils and the driving mechanisms were poorly understood. Here, a three-year N addition experiment was conducted on cultivated grassland planted with alfalfa (Medicago sativa) and bromegrass (Bromus inermis) in Inner Mongolia. The fluxes of soil-atmospheric CO2 and CH4; the content of the total dissolved N (TDN); the dissolved organic N (DON); the dissolved organic C (DOC); NH4+–N and NO3−–N in soil; enzyme activity; and auxiliary variables (soil temperature and moisture) were simultaneously measured. The results showed that N fertilization (>75 kg N ha−1 year−1) caused more serious soil acidification for alfalfa planting than for brome planting. N fertilization stimulated P-acquiring hydrolase (AP) in soil for growing Bromus inermis but did not affect C- and N-acquiring hydrolases (AG, BG, CBH, BX, LAP, and NAG). The oxidase activities (PHO and PER) of soil for planting Bromus inermis were higher than soil for planting Medicago sativa, regardless of N, whether fertilization was applied or not. Forage species and N fertilization did not affect soil CO2 flux, whereas a high rate of N fertilization (150 kg N ha−1 year−1) significantly inhibited CH4 uptake in soil for planting Medicago sativa. A synergistic effect between CO2 emission and CH4 uptake in soil was found over the short term. Our findings highlight that forage species affect soil enzyme activity in response to N fertilization. Soil enzyme activity may be an important regulatory factor for C exchange from temperate artificial grassland soil in response to N fertilization.
      Citation: Atmosphere
      PubDate: 2022-05-11
      DOI: 10.3390/atmos13050777
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 778: Rapid Sampling Protocol of Isoprene
           Emission Rate of Palm (Arecaceae) Species Using Excised Leaves

    • Authors: Ting-Wei Chang, Hiroshi Okamoto, Akira Tani
      First page: 778
      Abstract: The high isoprene emission capacity of palm species can decrease regional air quality and enhance the greenhouse effect when land is converted to palm plantations. Propagation of low-emitting individuals can be a strategy for reducing isoprene emission from palms. However, the identification of low-emitting individuals requires large-scale sampling. Thus, we aimed to develop a rapid method in which the isoprene emission rate of leaf segments is observed. We examined the temperature response and effect of incubation length on the isoprene emission rate of palm leaf and found that leaf temperatures at 25 to 30 °C and an incubation length of 40 min are suitable parameters. To further examine the validity of the method, we applied both the enclosure method and this method to the same sections of leaves. High coefficient of determinations (0.993 and 0.982) between the results of the two methods were detected regardless of seasonal temperature. This result proves that the method is capable of measuring the isoprene emission rate under any growth conditions if the incubation temperature is controlled. By using a water bath tank and a tested light source, we can simply implement a unified environmental control of multiple samples at once, which achieves a higher time efficiency than conventional enclosure measurements.
      Citation: Atmosphere
      PubDate: 2022-05-11
      DOI: 10.3390/atmos13050778
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 779: An Observing System Simulation Experiment
           (OSSE) to Study the Impact of Ocean Surface Observation from the Micro
           Unmanned Robot Observation Network (MURON) on Tropical Cyclone Forecast

    • Authors: Junkyung Kay, Xuguang Wang, Masaya Yamamoto
      First page: 779
      Abstract: The Micro Unmanned Robot Observation Network (MURON) is a planned in-situ observation network over the surface of West Pacific Ocean, and it is designed to sample high spatial and temporal resolution observations of wind and mass fields over the ocean surface. The impacts of MURON observations for Tropical Cyclone (TC) intensity forecast are investigated using Observation System Simulation Experiments. The regional Ensemble Kalman Filter (EnKF) system of Gridpoint Statistical Interpolation is used with the Advanced Research version of the Weather Research and Forecasting model to conduct OSSEs for typhoon Haiyan (2013) while Haiyan goes through rapid intensification. Assimilating MURON observations improves the TC structure and intensity analysis and forecast. The intensity forecast is improved largely due to the correction of initial vorticity and vertical transport of mass flux. The improvement of intensity forecast is attributed largely to the assimilated MURON wind observations when Haiyan is at the tropical disturbance stage, and then by the MURON mass observations when Haiyan enters the tropical storm stage. In addition, our results show that the quality of moisture analysis is sensitive to the choice of the moisture control variable (CV) in the EnKF system. Using the default pseudo relative humidity (PRH) as the moisture CV degrades the accuracy of the moisture analysis. This is likely due to the neglect of updated temperature field during the nonlinear conversion from the PRH CV to the mixing ratio variable and due to the larger deviation of the PRH from Gaussian distribution. The use of mixing ratio moisture CV mitigates these problems.
      Citation: Atmosphere
      PubDate: 2022-05-11
      DOI: 10.3390/atmos13050779
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 780: Parameter Optimization of Catering Oil
           Droplet Electrostatic Coalescence under Coupling Field with COMSOL
           Software

    • Authors: Danyun Xu, Ling Zhu, Ziyu Yang, Jiale Gao, Man Jin
      First page: 780
      Abstract: At present, the common cooking fume purification devices are mostly based on electrostatic technology. There are few researches on the microscopic process of coalescence and electric field parameters’ optimization. In this paper, COMSOL MultiphysicsTM was used to simulate the electrostatic coalescence of oil droplets in the coupling field of an electric field and flow field. The degree of deformation of oil droplets (D) and the starting coalescence time (tsc) were used to evaluate the coalescence process. The feasibility of the model was verified through experimental results. The effects of voltage, flow speed and oil droplet radius on tsc were investigated, and the parameters were optimized by the response surface method and Matrix correlation analysis. It can be concluded that increasing the voltage, flow speed and oil droplet radius appropriately would be conducive to the coalescence of oil droplets. When the oil droplet radius was in the range of 0–1.5 mm, it promoted the coalescence of oil droplets. The influence of various factors on oil droplet coalescence was flow speed > voltage > oil droplet radius. The optimal result obtained by simulation was that when the radius of the oil droplet was 1.56 mm, the voltage 12 kV and the flow speed 180 mm/ms, the shortest coalescence time of oil droplets was 16.8253 ms.
      Citation: Atmosphere
      PubDate: 2022-05-12
      DOI: 10.3390/atmos13050780
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 781: Temporal Distribution and Source
           

    • Authors: Kejun Li, Dilinuer Talifu, Bo Gao, Xiaoxiao Zhang, Wei Wang, Abulikemu Abulizi, Xinming Wang, Xiang Ding, Huibin Liu, Yuanyu Zhang
      First page: 781
      Abstract: In order to identify the pollution characteristics and sources of PM2.5 in Urumqi, fine particulate matter samples were collected from September 2017 to August 2018, and the water-soluble ions (WSIs), organic carbon (OC), elemental carbon (EC), polycyclic aromatic hydrocarbons (PAHs), and metal elements were analyzed. The results indicate that the annual mass concentration of PM2.5 in Urumqi was 158.85 ± 15.11 μg/m3, with the highest seasonal average in autumn (180.49 ± 87.22 μg/m3) and the lowest in summer (148.41 ± 52.60 μg/m3). SO42− (13.58 ± 16.4 μg/m3), NO3− (13.46 ± 17.5 μg/m3), and NH4+ (10.88 ± 12.2 μg/m3) were the most abundant WSIs, and the secondary inorganic ions (SNA = SO42− + NO3− + NH4+) accounted for 87.23% of the WSIs. The NO3−/SO42− ratio indicates that the contribution of stationary sources was dominant. The annual concentrations of OC and EC were 12.00 ± 4.4 µg/m3 and 5.00 ± 3.5 µg/m3, respectively, the OC/EC ratios in winter (2.55 ± 0.7), spring (3.43 ± 1.3), and summer (3.22 ± 1.1) were greater than 2, and there was the formation of secondary organic carbon (SOC). The correlation between OC and EC in spring in Urumqi (R2 = 0.53) was low. In the PM2.5, Al and Fe were the most abundant elements. The highest mass concentration season occurred in autumn, with mass concentrations of 15.11 ± 10.1 µg/m3 and 8.33 ± 6.9 µg/m3, respectively. The enrichment factor (EF) shows that most of the metal elements come from natural sources, and the Cd element mainly comes from anthropogenic sources. PAHs with a middle molecular weight were the main ones, and the annual average annual mass concentration of the PAHs was 451.35 ng/m3. The positive matrix factor model (PMF) source analysis shows that there are five main sources of PM2.5 in Urumqi, including crustal minerals, biomass combustion, coal combustion, vehicular transport, and secondary aerosols. The distribution percentages of these different sources were 19.2%, 10.2%, 12.1%, 8.2%, and 50.3%, respectively.
      Citation: Atmosphere
      PubDate: 2022-05-12
      DOI: 10.3390/atmos13050781
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 782: Predicting Daily PM2.5 Exposure with
           Spatially Invariant Accuracy Using Co-Existing Pollutant Concentrations as
           Predictors

    • Authors: Shin Araki, Hikari Shimadera, Hideki Hasunuma, Yoshiko Yoda, Masayuki Shima
      First page: 782
      Abstract: The spatiotemporal variation of PM2.5 should be accurately estimated for epidemiological studies. However, the accuracy of prediction models may change over geographical space, which is not conducive for proper exposure assessment. In this study, we developed a prediction model to estimate daily PM2.5 concentrations from 2010 to 2017 in the Kansai region of Japan with co-existing pollutant concentrations as predictors. The overall objective was to obtain daily estimates over the study domain with spatially homogeneous accuracy. We used random forest algorithm to model the relationship between the daily PM2.5 concentrations and various predictors. The model performance was evaluated via spatial and temporal cross-validation and the daily PM2.5 surface was estimated from 2010 to 2017 at a 1 km × 1 km resolution. We achieved R2 values of 0.91 and 0.92 for spatial and temporal cross-validation, respectively. The prediction accuracy for each monitoring site was found to be consistently high, regardless of the distance to the nearest monitoring location, up to 10 km. Even for distances greater than 10 km, the mean R2 value was 0.88. Our approach yielded spatially homogeneous prediction accuracy, which is beneficial for epidemiological studies. The daily PM2.5 estimates will be used in a related birth cohort study to evaluate the potential impact on human health.
      Citation: Atmosphere
      PubDate: 2022-05-12
      DOI: 10.3390/atmos13050782
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 783: Tropical Cyclone Intensity Prediction
           Using Deep Convolutional Neural Network

    • Authors: Xiao-Yan Xu, Min Shao, Pu-Long Chen, Qin-Geng Wang
      First page: 783
      Abstract: In this study, deep convolutional neural network (CNN) models of stimulated tropical cyclone intensity (TCI), minimum central pressure (MCP), and maximum 2 min mean wind speed at near center (MWS) were constructed based on ocean and atmospheric reanalysis, as well Best Track of tropical hurricane data over 2014–2018. In order to explore the interpretability of the model structure, sensitivity experiments were designed with various combinations of predictors. The model test results show that simplified VGG-16 (VGG-16 s) outperforms the other two general models (LeNet-5 and AlexNet). The results of the sensitivity experiments display good consistency with the hypothesis and perceptions, which verifies the validity and reliability of the model. Furthermore, the results also suggest that the importance of predictors varies in different targets. The top three factors that are highly related to TCI are sea surface temperature (SST), temperature at 500 hPa (TEM_500), and the differences in wind speed between 850 hPa and 500 hPa (vertical wind shear speed, VWSS). VWSS, relative humidity (RH), and SST are more significant than MCP. For MWS and SST, TEM_500, and temperature at 850 hPa (TEM_850) outweigh the other variables. This conclusion also implies that deep learning could be an alternative way to conduct intensive and quantitative research.
      Citation: Atmosphere
      PubDate: 2022-05-12
      DOI: 10.3390/atmos13050783
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 784: Particle Sedimentation in Numerical
           Modelling: A Case Study from the Puyehue-Cordón Caulle 2011
           Eruption with the PLUME-MoM/HYSPLIT Models

    • Authors: Alessandro Tadini, Mathieu Gouhier, Franck Donnadieu, Mattia de’ Michieli Vitturi, Federica Pardini
      First page: 784
      Abstract: Numerical modelling of tephra fallout is a fast-developing research area in volcanology. Several models are currently available both to forecast the dispersion of volcanic particles in the atmosphere and to calculate the particles deposited at different locations on the ground. Data from these simulations can then be used both to manage volcanic crises (e.g., protect air traffic) or perform long-term hazard assessment studies (e.g., through hazard maps). Given the importance of these tasks, it is important that each model is thoroughly tested in order to assess advantages and limitations, and to provide useful information for quantifying the model uncertainty. In this study we tested the coupled PLUME-MoM/HYSPLIT models by applying them to the Puyehue–Cordon Caulle 2011 sub-Plinian eruption. More specifically, we tested new features recently introduced in these well-established models (ash aggregation, external water addition, and settling velocity models), we implemented a new inversion procedure, and we performed a parametric analysis. Our main results reaffirm the pivotal role played by mass eruption rate on the final deposit and show that some choices for the input parameters of the model can lead to the large overestimation in total deposited mass (which can be reduced with our inversion procedure). The parametric analysis suggests a most likely value of the mass eruption rate in the range 2.0–6.3 × 106 kg/s. More studies with a similar approach would be advisable in order to provide final users with useful indications about the parameters that should be carefully evaluated before being used as input for this kind of model.
      Citation: Atmosphere
      PubDate: 2022-05-12
      DOI: 10.3390/atmos13050784
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 785: Effects of Urbanization on Extreme Climate
           Indices in the Valley of Mexico Basin

    • Authors: Martín José Montero-Martínez, Mercedes Andrade-Velázquez
      First page: 785
      Abstract: This study analyzes 50 annual climate change indices related to temperature and precipitation in the Valley of Mexico basin for the period 1951–2010. First, a quality and homogenization analysis of 90 weather stations (categorized as urban, suburban, and rural) in the basin was performed using the Climatol algorithm. The non-parametric Mann–Kendall test and the Sen’s slope method were applied to determine the existence of a trend and to estimate the magnitude of the change in extreme climate indices, respectively. To eliminate the serial correlation problem, the lag-1 method and the Patakamuri tests were used. Statistically significant positive trends were found for SU, TMm, TNm, TNn, TX90p, and WSDI, as well as negative ones for FD, TX10p, TN10p, CSDI, and HDDheat18. The results seem to support an influence of anthropogenic global warming on the study region, rather than local effects of urbanization. However, it is likely that some significant differences in the urban change rate of some indices could be due to local effects, such as the difference in land cover that occurs between urban and rural stations. Not enough statistically significant results were found for the climate change indices related to precipitation in most of the stations. Compared to other studies in the Mexico City area, the main contribution of this study is the analysis of 50 climate indices in a 60-year period working with a quality-controlled and homogenized database.
      Citation: Atmosphere
      PubDate: 2022-05-12
      DOI: 10.3390/atmos13050785
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 786: Transformation and Migrant Mechanism of
           Sulfur and Nitrogen during Chemical Looping Combustion with CuFe2O4

    • Authors: Haichuan Li, Ziheng Han, Chenye Hu, Jingjing Ma, Qingjie Guo
      First page: 786
      Abstract: Chemical looping combustion (CLC) is a key technology for capturing CO2. Different types of oxygen carrier (OC) particles are used in coal CLC. The migration and transformation behaviors of sulfur and nitrogen are basically the same when CaFe2O4 and Fe2O3/Al2O3 are used as OC. CLC can be divided into two reaction stages: coal pyrolysis and char gasification; SO2 and NO show bimodal release characteristics, both of which show a basic trend of rising first and then falling down. The contents of H2S and NO2 increased rapidly at the beginning of the reaction and then decreased slowly at the stage of char gasification. H2S is released rapidly during coal pyrolysis and discharged from the reactor with flue gas, and then part of H2S is converted to SO2 during the char gasification stage by OC particles. NO can be oxidized by OC particles and form NO2. The increase in the reaction temperature and oxygen-to-carbon ratio (O/C) contributes to the release of sulfur and nitrogen and higher reaction temperature and O/C can inhibit the formation of metal sulfide. O2 released by CuFe2O4 significantly increases the contents of SO2, H2S, NO and NO2 in flue gas. This work is helpful for improving control strategies for pollutants.
      Citation: Atmosphere
      PubDate: 2022-05-12
      DOI: 10.3390/atmos13050786
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 787: Correction: Han et al. Interpolation-Based
           Fusion of Sentinel-5P, SRTM, and Regulatory-Grade Ground Stations Data for
           Producing Spatially Continuous Maps of PM2.5 Concentrations Nationwide
           over Thailand. Atmosphere 2022, 13, 161

    • Authors: Shinhye Han, Worasom Kundhikanjana, Peeranan Towashiraporn, Dimitris Stratoulias
      First page: 787
      Abstract: In the original publication [...]
      Citation: Atmosphere
      PubDate: 2022-05-12
      DOI: 10.3390/atmos13050787
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 788: Time Series Forecasting of Air Quality: A
           Case Study of Sofia City

    • Authors: Evgeniy Marinov, Dessislava Petrova-Antonova, Simeon Malinov
      First page: 788
      Abstract: Air pollution has a significant impact on human health and the environment, causing cardiovascular disease, respiratory infections, lung cancer and other diseases. Understanding the behavior of air pollutants is essential for adequate decisions that can lead to a better quality of life for citizens. Air quality forecasting is a reliable method for taking preventive and regulatory actions. Time series analysis produces forecasting models, which study the characteristics of the data points over time to extrapolate them in the future. This study explores the trends of air pollution at five air quality stations in Sofia, Bulgaria. The data collected between 2015 and 2019 is analyzed applying time series forecasting. Since the time series analysis works on complete data, imputation techniques are used to deal with missing values of pollutants. The data is aggregated by granularity periods of 3 h, 6 h, 12 h, 24 h (1 day). The AutoRegressive Integrated Moving Average (ARIMA) method is employed to create statistical analysis models for the prediction of pollutants’ levels at each air quality station and for each granularity, including carbon oxide (CO), nitrogen dioxide (NO2), ozone (O3) and fine particles (PM2.5). In addition, the method allows us to find out whether the pollutants’ levels exceed the limits prescribed by the World Health Organization (WHO), as well as to investigate the correlation between levels of a given pollutant measured in different air quality stations.
      Citation: Atmosphere
      PubDate: 2022-05-12
      DOI: 10.3390/atmos13050788
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 789: Self-Rated Health, Life Balance and
           Feeling of Empowerment When Facing Impacts of Permafrost Thaw—A Case
           Study from Northern Canada

    • Authors: Ulla Timlin, Justine Ramage, Susanna Gartler, Tanja Nordström, Arja Rautio
      First page: 789
      Abstract: Climate warming in Arctic Canada, e.g., permafrost thaw, comprehensively impacts biota and the environment, which then affects the lives of people. This study aimed to investigate which perceived environmental and adaptation factors relate to self-rated well-being, quality of life, satisfaction with life (sum variable = life balance), self-rated health, and feeling of empowerment to face the changes related to permafrost thaw. The study sample was collected from one community using a questionnaire (n = 53) and analyzed by cross-tabulation. Results indicated that most participants had at least good well-being, quality of life, satisfaction with life, and a medium level of health, and over 40% assessed being empowered to face the changes related to permafrost thaw. Problems and challenges associated with permafrost thaw, e.g., health, traditional lifeways, and infrastructure, were recognized; these had impacts on life balance, feeling of empowerment, and self-rated health. Traditional knowledge regarding adaptation to face changes was seen as important. More adaptation actions from the individual to global level seemed to be needed. This study provides an overview of the situation in one area, but more research, with a larger study sample, should be conducted to achieve a deeper understanding of climate-related impacts on life and holistic well-being.
      Citation: Atmosphere
      PubDate: 2022-05-12
      DOI: 10.3390/atmos13050789
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 790: Comparison of COSMIC and COSMIC-2 Radio
           Occultation Refractivity and Bending Angle Uncertainties in August 2006
           and 2021

    • Authors: Richard Anthes, Jeremiah Sjoberg, Xuelei Feng, Stig Syndergaard
      First page: 790
      Abstract: We compare the random error statistics (uncertainties) of COSMIC (Constellation Observing System for Meteorology, Ionosphere and Climate, C1) and COSMIC-2 (C2) radio occultation (RO) bending angles and refractivities for the months of August 2006 and 2021 over the tropics and subtropics using the three-cornered hat method. The uncertainty profiles are similar for the two RO missions in the troposphere. However, a higher percentage of C2 profiles reach close to the surface in the moisture-rich tropics, an advantage of the higher signal-to-noise ratio (SNR) in C2. C2 uses signals from both GPS (Global Positioning System) and GLONASS Global Navigation System Satellites (GNSS). The GPS occultations show smaller uncertainties in the stratosphere and lower mesosphere (30–60 km) than the GLONASS occultations, a result of more accurate GPS clocks. Therefore, C2 (GPS) uncertainties are smaller than C1 uncertainties between 30–60 km while the C2 (GLONASS) uncertainties are larger than those of C1. The uncertainty profiles vary with latitude at all levels. We find that horizontal gradients in temperature and water vapor, and therefore refractivity, are the major cause of uncertainties in the tropopause region and troposphere through the violation of the assumption of spherical symmetry in the retrieval of bending angles and refractivity.
      Citation: Atmosphere
      PubDate: 2022-05-12
      DOI: 10.3390/atmos13050790
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 791: Analysing the Main Standards for
           Climate-Induced Mechanical Risk in Heritage Wooden Structures: The Case of
           the Ringebu and Heddal Stave Churches (Norway)

    • Authors: America Califano, Marco Baiesi, Chiara Bertolin
      First page: 791
      Abstract: Studying, controlling and extrapolating the indoor microclimate of historical buildings have always been at the forefront among numerous preventive conservation strategies, especially in case of buildings made of organic hygroscopic materials, e.g., wood. The variations and fluctuations of the microclimatic variables, namely temperature (T) and relative humidity (RH), could have a detrimental effect on the mechanical properties of wooden objects, works of art and structures. For this reason, through the years, several guidelines have been provided by standards and protocols about the optimal microclimatic conditions that should be ensured to avoid the decay and the eventual catastrophic failure of heritage objects and buildings. In this work, two historical buildings entirely made of Scots pine wood have been analysed: the Ringebu and Heddal stave churches (Norway). These churches store several wooden medieval statues and paintings that are also susceptible to the effects of the microclimate. For this reason, the timeseries of the indoor relative humidity of the two churches have been analysed, in the framework of the indications provided by the standards. The criticalities of the existing protocols have been pointed out, emphasizing the need for systematically and periodically updated specifications, tailorable to a given case study of concern, without forgetting the ever-present needs of energy- and money-saving approaches.
      Citation: Atmosphere
      PubDate: 2022-05-13
      DOI: 10.3390/atmos13050791
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 792: Inventory of Commercial Cooking Activities
           and Emissions in a Typical Urban Area in Greece

    • Authors: Kyriaki-Maria Fameli, Aggelos Kladakis, Vasiliki D. Assimakopoulos
      First page: 792
      Abstract: The pollutants emitted during meal preparation in restaurants deteriorate the air quality. Thus, it is an environmental issue that needs to be addressed, especially in areas where these activities are densely located. The purpose of this study is to examine the impact on air quality from commercial cooking activities by performing a qualitative and quantitative analysis of the related parameters. The area of interest is located in the southeastern Mediterranean (Greater Athens area in Greece). Due to the lack of the necessary activity information, a survey was conducted. Emissions from the fuel burnt during the cooking procedures were calculated and it was found that, overall, 940.1 tonnes are attributed to commercial cooking activities annually (generated by classical pollutants, heavy metals, particulates and polycyclic aromatic hydrocarbon emissions). Comparing the contribution of different sources to the pollutants emitted, it was found that commercial cooking is responsible for about 0.6%, 0.8% and 1.0% of the total CO, NOx and PM10 values. Cooking organic aerosol (COA) and volatile organic compound (VOC) emissions from grilled meat were also calculated, accounting for 724.9 tonnes and 37.1 tonnes, respectively. Monthly, daily and hourly profiles of the cooking activities were developed and emissions were spatially disaggregated, indicating the city center as the area with higher values. Numerical simulations were performed with the WRF/CAMx modeling system and the results revealed a contribution of about 6% to the total PM10 concentrations in the urban center, where the majority of restaurants are located.
      Citation: Atmosphere
      PubDate: 2022-05-13
      DOI: 10.3390/atmos13050792
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 793: Progress in Metal-Organic Framework
           Catalysts for Selective Catalytic Reduction of NOx: A Mini-Review

    • Authors: Yuan Gao, Si-Yan Gong, Baixiao Chen, Wen-Hao Xing, Yan-Fei Fei, Zhong-Ting Hu, Zhiyan Pan
      First page: 793
      Abstract: Nitrogen oxides released from the combustion of fossil fuels are one of the main air pollutants. Selective catalytic reduction technology is the most widely used nitrogen oxide removal technology in the industry. With the development of nanomaterials science, more and more novel nanomaterials are being used as catalysts for the selective reduction of nitrogen oxides. In recent years, metal-organic frameworks (MOFs), with large specific surface areas and abundant acid and metal sites, have been extensively studied in the selective catalytic reduction of nitrogen oxides. This review summarizes recent progress in monometallic MOFs, bimetallic MOFs, and MOF-derived catalysts for the selective catalytic reduction of nitrogen oxides and compares the reaction mechanisms of different catalysts. This article also suggests the advantages and disadvantages of MOF-based catalysts compared with traditional catalysts and points out promising research directions in this field.
      Citation: Atmosphere
      PubDate: 2022-05-13
      DOI: 10.3390/atmos13050793
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 794: Comparison of the on Board Measured and
           Simulated Exhaust Gas Emissions on the Ro-Pax Vessels

    • Authors: Josip Orović, Marko Valčić, Vlatko Knežević, Zoran Pavin
      First page: 794
      Abstract: Increasingly stringent environmental requirements for marine engines imposed by the International Maritime Organisation and the European Union require that marine engines have the lowest possible emissions of greenhouse and harmful exhaust gases into the atmosphere. In this research, exhaust gas emissions were measured on three Ro-Pax vessels sailing in the Adriatic Sea. Testo 350 Maritime exhaust gas analyser was used for monitoring the dry exhaust gas concentrations of CO2 and O2 in percentage, concentrations of CO and NOx in ppm and exhaust gas temperature in °C after the turbocharger at different engine loads. In order to compare and validate measured values, exhaust gas measurement data were also obtained from a Wartsila-Transas simulator model of a similar Ro-Pax vessel during the joint operation of the engine room and navigational simulators. All analysed main engines on three vessels had complete combustion processes in the cylinders with small differences which should be further investigated. Comparison of on board measured parameters with simulated parameters showed that significant fuel oil reduction per voyage could be accomplished by voyage and/or engine operation optimization procedures. Results of this analysis could be used for creating additional emission database and data-driven models for further analysis and improved estimation of exhaust gasses under various marine engine conditions. Additionally, the results could be useful to all interested parties in reducing the fuel oil consumption and emissions of greenhouse and harmful exhaust gases from vessels into the atmosphere.
      Citation: Atmosphere
      PubDate: 2022-05-13
      DOI: 10.3390/atmos13050794
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 795: Effects of Environmental Relative
           Vorticity and Seasonal Variation on Tropical Cyclones over the Western
           North Pacific

    • Authors: Yusi Wu, Shumin Chen, Mingsen Zhou, Yilun Chen, Aoqi Zhang, Chaoyong Tu, Weibiao Li
      First page: 795
      Abstract: An improved understanding of the environmental factors influencing tropical cyclones (TCs) is vital to enhance the accuracy of forecasting TC intensity. More than half of TCs that were substantially affected by environmental factors were predominantly affected by low-level environmental relative vorticity (hereafter, VOR TCs). In this study, the seasonal variation and related physical features of VOR TCs from 2003–2017 during TC seasons in summer and autumn over the western North Pacific were analyzed. Autumn VOR TCs exhibited the strongest intensity among all TCs over the western North Pacific. The enhanced environmental relative vorticity during the TC intensification period was larger and more favorably distributed for VOR TC development in autumn. The vorticity diagnostic analysis showed that the convergence was the positive source of environmental relative vorticity of VOR TCs, while the contribution of convergence was larger in autumn than in summer. The increased convergence was related to seasonal variation in larger-scale systems, especially the higher environmental pressure gradient, which reflected the larger subtropical high and the compressed East Asian summer monsoon trough in autumn. In addition, the East Asian summer monsoon trough was also somewhat stronger during the intensification period of VOR TCs, especially in autumn.
      Citation: Atmosphere
      PubDate: 2022-05-13
      DOI: 10.3390/atmos13050795
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 796: A Quality Control Method and
           Implementation Process of Wind Profiler Radar Data

    • Authors: Yang Qi, Yong Guo
      First page: 796
      Abstract: Wind profiler radar (WPR) is used for all-weather atmospheric wind-field monitoring. However, the reliability of these observations reduces significantly when there is electromagnetic interference echo, generally caused by ground objects, birds, or rain. Therefore, to optimize the data reliability of WPR, we proposed a synthetic data quality control process. The process included the application of a minimum connection method, judgment rule, and median test optimization algorithm for optimizing clutter suppression, spectral peak symmetry detection, and radial speed, respectively. We collected the base data from a radiosonde and multiple radars and conducted an experiment using these data and algorithms. The results indicated that the quality control method: (1) had good adaptability to multiple WPRs both in clear sky and precipitation; (2) was useful for suppressing ground clutter and (3) was superior to those of the manufacturer as a whole. Thus, the data quality control method proposed in this study can improve the accuracy and reliability of WPR products and multiple types of WPR, even when they function under vastly different weather conditions.
      Citation: Atmosphere
      PubDate: 2022-05-13
      DOI: 10.3390/atmos13050796
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 797: Dual-Polarization Radar Observations of
           the Evolution of a Supercell Tornado and Analysis of the Echo Mechanisms

    • Authors: Bin Wu, Ming Wei, Yanfang Li
      First page: 797
      Abstract: To gain a deeper understanding of the structural and evolutionary characteristics of supercell tornadoes that occurred in eastern China on 14 May 2021, observations from the S-band dual-polarization radars, soundings and other instruments are used to investigate the evolutionary process of the tornado formation by the mergering and strengthening of supercell storms. The results are described as follows. The updraft by upper divergence and vertical thermal instability induced by the cold source at the tropopause provided the environmental conditions suitable for tornado formation. The tornado event involved three storm merger processes, each of which was associated with an increase in the echo intensity, vertical rising speed, and vertical vorticity of the supercell. Furthermore, during the last merger, the merging of the two vortices resulted in the reduction of the rotation radius of the new vortex, which also provided a favorable condition for tornadogenesis. A schematic was proposed to describe storm mergers. The characteristics of the velocity spectrum width were indicative of the occurrence and evolution of the tornado in this case. During the tornado stage, distinct polarimetric variable signatures (e.g., a tornado debris signature and a differential reflectivity arc) and radial velocity signatures (i.e., a tornadic vortex signature) were observed.
      Citation: Atmosphere
      PubDate: 2022-05-13
      DOI: 10.3390/atmos13050797
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 798: Odors Emitted from Biological Waste and
           Wastewater Treatment Plants: A Mini-Review

    • Authors: Daniel González, David Gabriel, Antoni Sánchez
      First page: 798
      Abstract: In recent decades, a new generation of waste treatment plants based on biological treatments (mainly anaerobic digestion and/or composting) has arisen all over the world. These plants have been progressively substituted for incineration facilities and landfills. Although these plants have evident benefits in terms of their environmental impact and higher recovery of material and energy, the release into atmosphere of malodorous compounds and its mitigation is one of the main challenges that these plants face. In this review, the methodology to determine odors, the main causes of having undesirable gaseous emissions, and the characterization of odors are reviewed. Finally, another important topic of odor abatement technologies is treated, especially those related to biological low-impact processes. In conclusion, odor control is the main challenge for a sustainable implementation of modern waste treatment plants.
      Citation: Atmosphere
      PubDate: 2022-05-13
      DOI: 10.3390/atmos13050798
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 799: Impact of Climate Change on Water
           Resources in the Western Route Areas of the South-to-North Water Diversion
           Project

    • Authors: Zhongrui Ning, Jianyun Zhang, Shanshui Yuan, Guoqing Wang
      First page: 799
      Abstract: The South-to-North Water Diversion Project (SNWDP) is a national strategic project for water shortages in northern China. Climate change will affect the availability of water resources in both source and receiving areas. A grid-based RCCC-WBM model based on climate projections from nine Global Climate Models under SSP2-4.5 was used for analyzing the changes in temperature, precipitation, and streamflow in the near future (2025–2045, NF) and far future (2040–2060, FF) relative to the baseline (1956–2000). The results showed that: (1) the temperature of the western route will increase significantly in the NF and FF with an extent of 1.6 °C and 2.0 °C, respectively, (2) precipitation will very likely increase even though Global Climate Model (GCM) projections are quite dispersed and uncertain, and (3) over half of the GCMs projected that streamflow of receiving area will slightly increase with a rate of 1.68% [−8.67%, 12.3%] and 2.78% [−3.30%, 11.0%] in the NF and FF, respectively. Climate change will support the planning of the western route to a certain extent. However, water supply risk induced by the extreme situation of climate change should be paid adequate consideration when the project operates in practice due to the large dispersion and uncertainty of GCM projections.
      Citation: Atmosphere
      PubDate: 2022-05-13
      DOI: 10.3390/atmos13050799
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 800: A Review of Selected Types of Indoor Air
           Purifiers in Terms of Microbial Air Contamination Reduction

    • Authors: Maciej Szczotko, Izabela Orych, Łukasz Mąka, Jolanta Solecka
      First page: 800
      Abstract: Aims: With the ongoing pandemic and increased interest in measures to improve indoor air quality, various indoor air purifiers have become very popular and are widely used. This review presents the advantages and disadvantages of various types of technologies used in air purifiers in terms of reducing microbial contamination. Methods: A literature search was performed using Web of Science, Scopus, and PubMed, as well as technical organizations dealing with indoor air-quality to identify research articles and documents within our defined scope of interest. Relevant sections: The available literature data focus mainly on the efficiency of devices based on tests conducted in laboratory conditions with test chambers, which does not reflect the real dimensions and conditions observed in residential areas. According to a wide range of articles on the topic, the actual effectiveness of air purifiers is significantly lower in real conditions than the values declared by the manufacturers in their marketing materials as well as technical specifications. Conclusions: According to current findings, using indoor air purifiers should not be the only measure to improve indoor air-quality; however, these can play a supporting role if their application is preceded by an appropriate technical and environmental analysis considering the real conditions of its use.
      Citation: Atmosphere
      PubDate: 2022-05-13
      DOI: 10.3390/atmos13050800
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 801: Impact of Vehicle Soot Agglomerates on
           Snow Albedo

    • Authors: Sofía González-Correa, Diego Gómez-Doménech, Rosario Ballesteros, Magín Lapuerta, Diego Pacheco-Ferrada, Raúl P. Flores, Lina Castro, Ximena Fadic-Ruiz, Francisco Cereceda-Balic
      First page: 801
      Abstract: Snow covers are very sensitive to contamination from soot agglomerates derived from vehicles. A spectroradiometric system covering a wavelength from 300 to 2500 nm with variable resolution (from 2.2 to 7.0 nm) was used to characterize the effect of soot derived from a diesel vehicle whose exhaust stream was oriented towards a limited snowed area. The vehicle was previously tested in a rolling test bench where particle number emissions and size distributions were measured, and fractal analysis of particle microscopic images was made after collecting individual agglomerates by means of an electrostatizing sampler. Finally, the experimental results were compared to modelled results of contaminated snow spectral albedo obtained with a snow radiative transfer model developed by our research group (OptiPar) and with other models. Both experimental and modelled results show that increasingly accumulated soot mass reduces the snow albedo with a constant rate of around 0.03 units per mg/kg, with a predominant effect on the UV-VIS range. Based on the small size of the primary particles (around 25 nm), the Rayleigh-Debye-Gans approximation, further corrected to account for the effect of multiple scattering within the agglomerates, was revealed as an appropriate technique in the model.
      Citation: Atmosphere
      PubDate: 2022-05-13
      DOI: 10.3390/atmos13050801
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 802: Enhanced Methane Oxidation Potential of
           Landfill Cover Soil Modified with Aged Refuse

    • Authors: Haijie He, Tao Wu, Zhanhong Qiu, Chenxi Zhao, Shifang Wang, Jun Yao, Jie Hong
      First page: 802
      Abstract: Aged refuse with a landfill age of 1.5 years was collected from a municipal solid waste landfill with high kitchen waste content and mixed with soil as biocover material for landfill. A series of laboratory batch tests was performed to determine the methane oxidation potential and optimal mixing ratio of landfill cover soil modified with aged refuse, and the effects of water content, temperature, CO2/CH4, and O2/CH4 ratios on its methane oxidation capacity were analyzed. The microbial community analysis of aged refuse showed that the proportions of type I and type II methane-oxidizing bacteria were 56.27% and 43.73%, respectively. Aged refuse could significantly enhance the methane oxidation potential of cover soil, and the optimal mixing ratio was approximately 1:1. The optimal temperature and water content were about 25 °C and 30%, respectively. Under the conditions of an initial methane concentration of 15% and an O2/CH4 ratio of 0.8–1.2, the measured methane oxidation rate was negatively correlated with the O2/CH4 ratio. The maximum methane oxidation capacity measured in the test reached 308.5 (μg CH4/g)/h, indicating that the low-age refuse in the landfill with high kitchen waste content is a biocover material with great application potential.
      Citation: Atmosphere
      PubDate: 2022-05-13
      DOI: 10.3390/atmos13050802
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 803: Co-Production System Based on Lean Methane
           and Biogas for Power Generation in Coal Mines

    • Authors: Feifei Yin, Baisheng Nie, Yueying Wei, Shuangshuang Lin
      First page: 803
      Abstract: The problem of low efficiency of coal mine methane utilization is caused by the concentration of methane of less than 10%, or a concentration that varies dramatically directly emitted into the atmosphere. This work deals with the concept of a co-production system that blends lean methane and biogas to produce electric energy. It is recommended to add the biogas generated by straws around the mines in a controlled manner to the lean methane flow to obtain the desired gas concentration in order to generate electricity. Potential electricity generation and reduced greenhouse gas emissions were also evaluated. The result shows that the co-production system can significantly improve the utilization efficiency of lean methane in coal mines; the average use of pure methane in three coal mines is 0.18, 1.12, and 5.32 million m3 every year, respectively, and the emission reduction effect of carbon dioxide (CO2) equivalent is, respectively, 3081, 18,796, and 89,050 tons. The electricity generated and the economic environmental benefits of the co-production system are remarkable, and it has economic feasibility and broad perspectives for popularization. It not only has the advantage of improving the utilization rate of methane and biomass and providing power supply and heat source for mines, but also has practical significance in terms of saving energy, reducing environmental pollution, adjusting the energy structure, and achieving the target of carbon emission peak and carbon neutrality.
      Citation: Atmosphere
      PubDate: 2022-05-14
      DOI: 10.3390/atmos13050803
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 804: A Study of a Miniature TDLAS System
           Onboard Two Unmanned Aircraft to Independently Quantify Methane Emissions
           from Oil and Gas Production Assets and Other Industrial Emitters

    • Authors: Abigail Corbett, Brendan Smith
      First page: 804
      Abstract: In recent years, industries such as oil and gas production, waste management, and renewable natural gas/biogas have made a concerted effort to limit and offset anthropogenic sources of methane emissions. However, the state of emissions, what is emitting and at what rate, is highly variable and depends strongly on the micro-scale emissions that have large impacts on the macro-scale aggregates. Bottom-up emissions estimates are better verified using additional independent facility-level measurements, which has led to industry-wide efforts such as the Oil and Gas Methane Partnership (OGMP) push for more accurate measurements. Robust measurement techniques are needed to accurately quantify and mitigate these greenhouse gas emissions. Deployed on both fixed-wing and multi-rotor unmanned aerial vehicles (UAVs), a miniature tunable diode laser absorption spectroscopy (TDLAS) sensor has accurately quantified methane emissions from oil and gas assets all over the world since 2017. To compare bottom-up and top-down measurements, it is essential that both values are accompanied with a defensible estimate of measurement uncertainty. In this study, uncertainty has been determined through controlled release experiments as well as statistically using real field data. Two independent deployment methods for quantifying methane emissions utilizing the in situ TDLAS sensor are introduced: fixed-wing and multi-rotor. The fixed-wing, long-endurance UAV method accurately measured emissions with an absolute percentage difference between emitted and mass flux measurement of less than 16% and an average error of 6%, confirming its suitability for offshore applications. For the quadcopter rotary drone surveys, two flight patterns were performed: perimeter polygons and downwind flux planes. Flying perimeter polygons resulted in an absolute error less than 36% difference and average error of 16.2%, and downwind flux planes less than 32% absolute difference and average difference of 24.8% when flying downwind flux planes. This work demonstrates the applicability of ultra-sensitive miniature spectrometers for industrial methane emission quantification at facility level with many potential applications.
      Citation: Atmosphere
      PubDate: 2022-05-14
      DOI: 10.3390/atmos13050804
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 805: Simulation of Summer Rainfall in Thailand
           by IAP-AGCM4.1

    • Authors: Kritanai Torsri, Zhaohui Lin, Victor Nnamdi Dike, He Zhang, Chenglai Wu, Yue Yu
      First page: 805
      Abstract: Thailand is located in the Southeast Asian region, where the summer rainfall exhibits strong interannual variability, and the successful simulation of rainfall variation in Thailand by current climate models remains a challenge. Therefore, this paper evaluates the capability of the state-of-the-art Atmospheric GCM of the Institute of Atmospheric Physics (IAP-AGCM) in simulating summer rainfall over Thailand by comparing the model’s results with ground-truth observation during 1981–2012. Generally, the model shows a certain skill in reproducing the observed spatial distribution of the summer rainfall climatology and its interannual variability over Thailand, although the model underestimated both rainfall amount and its variability. Using Empirical Orthogonal Function (EOF) analysis, it is found that the IAP climate model reproduced creditably the spatial patterns of the first three dominant modes of summer rainfall in Thailand, whereas it underestimated the explained variance of the observed EOF-1 and overestimated the explained variance of the observed EOF-2 significantly. It was further found that the correlation between the observed rainfall anomalies in Thailand and the Niño3.4 index can be reproduced by the IAP model. However, the observed negative correlation is largely underestimated by the IAP climate model, and this could be the reason for the underestimation of explained variance of the EOF-1 by the IAP model. The evaluation results would be of great importance for further model improvement and thus potential application in seasonal prediction in the region.
      Citation: Atmosphere
      PubDate: 2022-05-14
      DOI: 10.3390/atmos13050805
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 806: Investigating Spatial Heterogeneity of the
           Environmental Kuznets Curve for Haze Pollution in China

    • Authors: Abdul Samad Abdul-Rahim, Yoomi Kim, Long Yue
      First page: 806
      Abstract: This study investigates the environmental Kuznets curve (EKC) for haze in 31 cities and provinces across China using the spatial data for a period of 15 years, from 2000 to 2014. We utilized the geographically weighted regression (GWR) model to consider the spatial non-stationary characteristics of the air quality in a vast territory. This approach allowed us to verify the region-specific characteristics, while the global model estimated the average relationship across the entire nation. Although the EKC for haze was statistically significant in the global models, the results only confirmed the existence of an EKC between the overall air quality and economic performance. Thus, it was difficult to determine the regional differences in an EKC. The results of the GWR model found the spatial variability of each variable and showed significant spatial heterogeneity in the EKC across regions. Although six regions—Beijing, Gansu, Heilongjiang, Jiangxi, Jilin, Liaoning, Shanghai, Tianjin, Xinjiang, and Zhejiang—showed inverted U-shaped EKCs, these were only statistically significant in three big cities—Beijing, Tianjin, and Shanghai. The results demonstrated no EKCs in the other 25 provinces and cities. These results provide strong empirical evidence that there is significant spatial heterogeneity in the EKC of China. Thus, a more regionally specialized air pollution control policy is required to create an effective policy for balanced economic growth in China.
      Citation: Atmosphere
      PubDate: 2022-05-14
      DOI: 10.3390/atmos13050806
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 807: Automatic Detection of Electric Field VLF
           Electromagnetic Wave Abnormal Disturbance on Zhangheng-1 Satellite

    • Authors: Ying Han, Jing Yuan, Jianping Huang, Zhong Li, Xuhui Shen
      First page: 807
      Abstract: Ionosphere disturbances are mainly caused by solar activities and earth surface activities. Different electromagnetic wave disturbances show different shapes on the spectrogram, such as artificial very low frequency transmitting stations, power systems, and satellite platform disturbances which all show a horizontal shape. Due to the electric field coupling or superposition by other electromagnetic disturbances, the horizontal electromagnetic wave clarity on the spectrogram is reduced, interrupted, or disappears. Aiming at this phenomenon, based on computer vision technology, this paper proposes an automatic detection and recognition algorithm for the space electric field abnormal interference. Firstly, the horizontal electromagnetic wave on the spectrogram is detected, and then the detected window density on the horizontal line is counted. We then record and save the density anomaly windows on multiple horizontal lines at the same time, so as to realize the electric field anomaly disturbance automatic detection. The accuracy of the algorithm for detecting continuous electromagnetic wave disturbance with a wide frequency and time interval is up to 98.2%. Through the space electromagnetic disturbances automatic identification from massive data, combined with space events and multi-dimensional information, such as time, space and orbit, it is helpful to further find out the global space-time transformation laws of space events.
      Citation: Atmosphere
      PubDate: 2022-05-15
      DOI: 10.3390/atmos13050807
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 808: Can the Correlation between Radar and
           Cloud-to-Ground Daily Fields Help to Identify the Different Rainfall
           Regimes' The Case of Catalonia

    • Authors: Sergio Castillo, Tomeu Rigo, Carme Farnell
      First page: 808
      Abstract: The rainfall regime is changing in the Catalan territory, likely in most areas in the Mediterranean Basin. This variability, spatial and temporal, means that there may be periods of severe drought combined with periods of heavy rainfall and floods. In this way, the management of water resources is complicated and can produce a high impact on different social aspects. The high convective activity leads to investigating the relationship between the electric discharges and radar parameters (reflectivity, echo top, vertically integrated liquid, and accumulated rainfall). The correlation allows identifying some elements that may be significant in terms of changes in rainfall regimes. Besides, using several radar parameters apart from precipitation accumulation reveals interesting explicit patterns of the previously known. These patterns can help better understand the precipitation behavior and the changes associated with it.
      Citation: Atmosphere
      PubDate: 2022-05-16
      DOI: 10.3390/atmos13050808
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 809: Study on the Influence of Globe
           Thermometer Method on the Accuracy of Calculating Outdoor Mean Radiant
           Temperature and Thermal Comfort

    • Authors: Kuixing Liu, Weijie You, Xiyue Chen, Wenyu Liu
      First page: 809
      Abstract: With global warming and the rapid development of urbanization, the outdoor thermal environment is deteriorating. More and more research focuses on the outdoor thermal environment and thermal comfort. The globe thermometer method is widely used in more than half of the outdoor thermal environment research studies, but there is a large error compared with the six-direction method. In order to explore the accuracy of the results of the globe thermometer method and its impact on the subsequent thermal comfort indicators, this study carried out a year-round comparative experiment under multiple working conditions outdoors in cold areas to explore the impact of meteorological parameters such as shortwave radiation, wind speed, and wind direction on the results of the globe thermometer method. The results show that the continuous increase of shortwave radiation reduces the accuracy of the black bulb thermometer to less than 60%, and the instantaneous change of wind speed will make the deviation of the mean radiation temperature obtained by the globe thermometer method exceed 5 °C. The influence of the mean radiation temperature obtained by the globe thermometer method on the thermal comfort index is mainly reflected in the working condition of a high temperature and strong radiation in summer. Taking the six-direction method as the standard, this study gives the scope of application of the globe thermometer method; and taking the human body calculation model of PET as an example, a universal optimization method for detailed division of radiation heat transfer calculation is proposed, so that it can get more accurate and rigorous conclusions in the evaluation of outdoor complex radiation environment.
      Citation: Atmosphere
      PubDate: 2022-05-16
      DOI: 10.3390/atmos13050809
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 810: Nicotine Affects Multiple Biological
           Processes in EpiDermTM Organotypic Tissues and Keratinocyte Monolayers

    • Authors: Giovanna L. Pozuelos, Matine Rubin, Samantha Vargas, Erik Ramirez, Dhiresh Bandaru, Jihui Sha, James Wohlschlegel, Prue Talbot
      First page: 810
      Abstract: Dermal exposure to nicotine is common due to the widespread use of tobacco products. Here, we assessed the effects of nicotine at concentrations found in thirdhand smoke (THS) contaminated environments and electronic cigarette (EC) spills or leaks on a 3D human skin model (EpiDermTM) and on submerged keratinocyte cultures. Air liquid interface treatment of EpiDermTM with 10 or 400 μg/mL of nicotine for 24 h followed by proteomics analysis showed altered pathways related to inflammation, protein synthesis, cell–cell adhesion, apoptosis, and mitochondrial function. Submerged cultured keratinocytes were used to validate the proteomics data and further characterize the response of skin cells to nicotine. Mitochondrial phenotype changed from networked to punctate in keratinocytes treated with 10 or 400 μg/mL of nicotine for 48 h and 24 h, respectively. After 72 h, all concentrations of nicotine caused a significant decrease in the networked phenotype. In Western blots, keratinocytes exposed to 400 μg/mL of nicotine had a significant decrease in mitofusin 2, while mitofusin 1 decreased after 72 h. The shift from networked to punctate mitochondria correlated with a decrease in mitofusin 1/2, a protein needed to establish and maintain the networked phenotype. Mitochondrial changes were reversible after a 24 h recovery period. Peroxisomes exposed to 400 μg/mL of nicotine for 24 h became enlarged and were fewer in number. Nicotine concentrations in THS and EC spills altered the proteome profile in EpiDermTM and damaged organelles including mitochondria and peroxisomes, which are involved in ROS homeostasis. These changes may exacerbate skin infections, inhibit wound healing, and cause oxidative damage to cells in the skin.
      Citation: Atmosphere
      PubDate: 2022-05-16
      DOI: 10.3390/atmos13050810
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 811: Air Pollution Dispersion over Durban,
           South Africa

    • Authors: Mark R. Jury, Mandisa S. Buthelezi
      First page: 811
      Abstract: Air pollution dispersion over Durban is studied using satellite, reanalysis and in situ measurements. This coastal city of 4 million people located on the east coast of South Africa contributes 29 million T/yr of trace gases, mostly from transport and industry. Terrestrial and agricultural particulates derive from the Kalahari Desert, Zambezi Valley and Mozambique. Surface air pollutants accumulate during winter (May–August) and provide a focus for statistical analysis of monthly, daily and hourly time series since 2001. The mean diurnal cycle has wind speed minima during the land−sea breeze transitions that follow morning and evening traffic emissions. Daily air pollution concentrations (CO, NO2, O3, PM2.5 and SO2) vary inversely with dewpoint temperature and tend to peak during winter prefrontal weather conditions. Descending airflow from the interior highlands induces warming, drying and poor air quality, bringing dust and smoke plumes from distant sources. Spatial regression patterns indicate that winters with less dispersion are preceded by warm sea surface temperatures in the tropical West Indian Ocean that promote a standing trough near Durban. Statistical outcomes enable the short- and long-range prediction of atmospheric dispersion and risk of exposure to unhealthy trace gases and particulates. The rapid inland decrease of mean wind speed from 8 to 2 m/s suggests that emissions near the coast will disperse readily compared with in interior valleys.
      Citation: Atmosphere
      PubDate: 2022-05-16
      DOI: 10.3390/atmos13050811
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 812: Ongoing Decline in the Atmospheric COS
           Seasonal Cycle Amplitude over Western Europe: Implications for Surface
           Fluxes

    • Authors: Sauveur Belviso, Marine Remaud, Camille Abadie, Fabienne Maignan, Michel Ramonet, Philippe Peylin
      First page: 812
      Abstract: Atmospheric carbonyl sulfide (COS) was monitored at the GIF site (France) from August 2014 to November 2021. A significant decreasing trend in the seasonal cycle amplitude (SCA) of the COS was observed for the first time in the Northern Hemisphere (−27 ppt over 6 years). The lowest SCA was recorded in 2021 (80 ppt vs. 107 ppt in 2015). The trend in the SCA results revealed a steeper decline in the spring maximum than in that of the autumn minimum (−49 ppt vs. −10 ppt over 6 years, respectively). These negative trends were qualitatively consistent with those in the tropospheric COS put forward by the NDACC network of ground-based FTIR instruments, which were attributed to a slowing in the rate of COS anthropogenic emissions. Simulations using the ORCHIDEE land-surface model showed that a decrease in COS lowers the uptake of this gas by plants. Our observations suggest the existence of a causal relationship between the decline in the SCA and that in the tropospheric COS, implying that the temporal variations in the COS SCA over Western Europe are essentially driven by plant uptake. However, the transport by the LMDz 3-D model of surface fluxes for each component of the COS budget failed to reproduce this feature at GIF, pointing to a likely misrepresentation of the marine and anthropogenic fluxes in the footprint of this station.
      Citation: Atmosphere
      PubDate: 2022-05-16
      DOI: 10.3390/atmos13050812
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 813: Short-Term Canyon Wind Speed Prediction
           Based on CNN—GRU Transfer Learning

    • Authors: Lipeng Ji, Chenqi Fu, Zheng Ju, Yicheng Shi, Shun Wu, Li Tao
      First page: 813
      Abstract: Due to the particularity of the site selection of hydropower stations, the canyon wind with large fluctuations often occurs during the construction of the hydropower station, which will seriously affect the safety of construction personnel. Especially in the early stage of the construction of the hydropower station, the historical data and information on the canyon wind are scarce. Short-term forecasting of canyon wind speed has become extremely important. The main innovation of this paper is to propose a time series prediction method based on transfer learning. This method can achieve short-term prediction when there are few wind speed sample data, and the model is relatively simple while ensuring the accuracy of prediction. Considering the temporal and nonlinear characteristics of canyon wind speed data, a hybrid transfer learning model based on a convolutional neural network (CNN) and gated recurrent neural network (GRU) is proposed to predict short-term canyon wind speed with fewer observation data. In this method, the time sliding window is used to extract time series from historical wind speed data and temperature data of adjacent cities as the input of the neural network. Next, CNN is used to extract the feature vector from the input, and the feature vector can form time series. Then, the GRU network is used for short-term wind speed prediction by the time series. Experimental results show that the proposed method improves MAE and RMSE by nearly 20%, which will provide new ideas for the application of wind speed forecasting in canyons under complex terrain. The research contents of this paper contribute to the actual construction of hydropower stations.
      Citation: Atmosphere
      PubDate: 2022-05-16
      DOI: 10.3390/atmos13050813
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 814: Updated Climatology of Mesospheric
           Temperature Inversions Detected by Rayleigh Lidar above Observatoire de
           Haute Provence, France, Using a K-Mean Clustering Technique

    • Authors: Maryam Ardalan, Philippe Keckhut, Alain Hauchecorne, Robin Wing, Mustapha Meftah, Ghazal Farhani
      First page: 814
      Abstract: A climatology of Mesospheric Inversion Layers (MIL) has been created using the Rayleigh lidar located in the south of France at L’Observatoire de Haute Provence (OHP). Using criteria based on lidar measurement uncertainties and climatological mean gravity wave amplitudes, we have selected significant large temperature anomalies that can be associated with MILs. We have tested a novel approach for classifying MILs based on a k-mean clustering technique. We supplied different parameters such as the MIL amplitudes, altitudes, vertical extension, and lapse rate and allowed the computer to classify each individual MIL into one of three clusters or classes. For this first proof of concept study, we selected k = 3 and arrived at three distinct MIL clusters, each of which can be associated with different processes generating MILs in different regimes. All clusters of MIL exhibit a strong seasonal cycle with the largest occurrence in winter. The four decades of measurements do not reveal any long-term changes that can be associated with climate changes and only show an inter-annual variability with a quasi-decadal oscillation.
      Citation: Atmosphere
      PubDate: 2022-05-16
      DOI: 10.3390/atmos13050814
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 815: Weather Radar Echo Extrapolation Method
           Based on Deep Learning

    • Authors: Fugui Zhang, Can Lai, Wanjun Chen
      First page: 815
      Abstract: In order to forecast some high intensity and rapidly changing phenomena, such as thunderstorms, heavy rain, and hail within 2 h, and reduce the influence brought by destructive weathers, this paper proposes a weather radar echo extrapolation method based on deep learning. The proposed method includes the design and combination of the data preprocessing, convolutional long short-term memory (Conv-LSTM) neuron and encoder–decoder model. We collect eleven thousand weather radar echo data in high spatiotemporal resolution, these data are then preprocessed before they enter the neural network for training to improve the data’s quality and make the training better. Next, the neuron integrates the structure and the advantages of convolutional neural network (CNN) and long short-term memory (LSTM), called Conv-LSTM, is applied to solve the problem that the full-connection LSTM (FC-LSTM) cannot extract the spatial information of input data. This operation replaced the full-connection structure in the input-to-state and state-to-state parts so that the Conv-LSTM can extract the information from other dimensions. Meanwhile, the encoder–decoder model is adopted due to the size difference of the input and output data to combine with the Conv-LSTM neuron. In the neural network training, mean square error (MSE) loss function weighted according to the rate of rainfall is added. Finally, the matrix “point-to-point” test method, including the probability of detection (POD), critical success index (CSI), false alarm ratio (FAR) and spatial test method contiguous rain areas (CRA), is used to examine the radar echo extrapolation’s results. Under the threshold of 30 dBZ, at the time of 1 h, we achieved 0.60 (POD), 0.42 (CSI) and 0.51 (FAR), compared with 0.42, 0.28 and 0.58 for the CTREC algorithm, and 0.30, 0.24 and 0.71 for the TITAN algorithm. Meanwhile, at the time of 1 h, we achieved 1.35 (total MSE ) compared with 3.26 for the CTREC algorithm and 3.05 for the TITAN algorithm. The results demonstrate that the radar echo extrapolation method based on deep learning is obviously more accurate and stable than traditional radar echo extrapolation methods in near weather forecasting.
      Citation: Atmosphere
      PubDate: 2022-05-16
      DOI: 10.3390/atmos13050815
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 816: Unusual Enhancement of Midlatitude
           Sporadic-E Layers in Response to a Minor Geomagnetic Storm

    • Authors: Qiong Tang, Haiyang Sun, Zhitao Du, Jiaqi Zhao, Yi Liu, Zhengyu Zhao, Xueshang Feng
      First page: 816
      Abstract: This study investigates the variations of middle and low latitude sporadic-E (Es) layers in response to a geomagnetic storm. Es layers are observed by five ionosondes located in the Eastern Asian sector. The critical frequencies of Es layers (foEs) at six stations increased in sequence from high latitude stations to low latitude stations after IMF/Bz turning southward. Lomb–Scargle analysis shows the amplification of semidiurnal oscillation amplitude in the vertical height of Es layers during geomagnetic disturbance. Modeling results of the NCAR Thermosphere-Ionosphere-Electrodynamics General Circulation Model (TIEGCM) show the enhancement of the wind field in the mesosphere and the lower thermosphere (MLT) region. Our study provides evidence that the enhanced wind field in the MLT region during the storm period could result in the enhancement of Es layers at middle and low latitude.
      Citation: Atmosphere
      PubDate: 2022-05-16
      DOI: 10.3390/atmos13050816
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 817: Experimental Study on the Dust-Cleaning
           Performance of New Structure Microporous Membrane Filter Plate

    • Authors: Lumin Chen, Zhe Liu, Yi Sun, Fuping Qian, Yunlong Han, Jinli Lu
      First page: 817
      Abstract: On the basis of the existing dust collector structure, this study designed a fan-shaped new structure microporous membrane filter plate (NSMMFP). The pressure distribution law of the NSMMFP can be obtained by measuring the wall surface peak pressure under different injection pressures. The powder attachment experiment was carried out to explore the influence of the dust moisture content on the dust stripping rate (DSR), and a high-speed camera was used to observe the peeling process of the dust. The results show that the peak pressure of each measuring point and the average wall surface peak pressure gradually increase with the injection pressure. The dust stripping quality (DSQ) and rate show an increasing trend as a whole as the injection distance. The DSR of the filter plate shows a downward trend when the dust quality G increases, while DSQ shows the opposite trend. Furthermore, as the dust moisture content increases, the DSQ and DSR gradually decrease. As the dust moisture content increases, the dust attached to the surface of the filter plate is more fragmented and peels from the surface of the filter plate during the dust cleaning process.
      Citation: Atmosphere
      PubDate: 2022-05-16
      DOI: 10.3390/atmos13050817
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 818: Optimization of the Efficient Extraction
           of Organic Components in Atmospheric Particulate Matter by Accelerated
           Solvent Extraction Technique and Its Application

    • Authors: Hao Zhang, Yanqin Ren, Jie Wei, Yuanyuan Ji, Xurong Bai, Yanqiu Shao, Hong Li, Rui Gao, Zhenhai Wu, Zhijian Peng, Feng Xue
      First page: 818
      Abstract: Organic components in atmospheric fine particulate matter have attracted much attention and several scientific studies have been performed, although most of the sample extraction methods are time consuming and laborious. Accelerated solvent extraction (ASE) is a new sample extraction method offering number of advantages, such as low extraction cost, reduced solvent and time consumption, and simplified extraction protocols. In order to optimize ASE methods to determine the concentrations of organic compounds in atmospheric fine particulate matter, different parameters were set out for the experiment, and the optimal method was selected according to the recoveries of the standard (i.e., n−alkanes and polycyclic aromatic hydrocarbons (PAHs)). This study also involves a comparison of the optimal method with the traditional method of ultrasonic extraction (USE). In addition, the optimized method was applied to measure the mass concentrations of organic compounds (n−alkanes and PAHs) in fine particulate matter samples collected in Beijing. The findings showed that the average recovery of target compounds using ASE was 96%, with the majority of compounds falling within the confidence levels, and the ASE recoveries and precision were consistent with the USE method tested. Furthermore, ASE combines the advantages of high extraction efficiency, automation, and reduced solvent use. In conclusion, the optimal ASE methods can be used to extract organic components in atmospheric particulate matter and serve as a point of reference for the development of analytical methodologies for assessing organic compounds in atmospheric particulate matter in China.
      Citation: Atmosphere
      PubDate: 2022-05-17
      DOI: 10.3390/atmos13050818
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 819: Interannual Variability of Summer Hotness
           in China: Synergistic Effect of Frequency and Intensity of High
           Temperature

    • Authors: Wenyan Zhang, Er Lu, Juqing Tu, Qingchen Chao, Hui Wang
      First page: 819
      Abstract: In the context of global warming, the impact of summer high temperature events is increasing. The accumulated summer high temperature is often used to reflect the overall hotness of summer. The internal variation of the accumulated temperature can be affected by both the frequency and intensity. In this study, by using the daily data during summers of 1960–2018, we examine the relative importance of the two factors with a multiple linear regression method. It is demonstrated that that the dominant result of summer accumulated temperature is sensitive to the change of threshold. As the threshold increases, the importance of frequency gradually increases, while the importance of the intensity decreases. In addition, it is found that when the threshold changes, the sensitivity of the dominant results is different over regions. This can provide a basis for the selection of regional thresholds and further improve the representation of accumulated temperature for high summer temperatures.
      Citation: Atmosphere
      PubDate: 2022-05-17
      DOI: 10.3390/atmos13050819
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 820: Book Review: Pfister, C.; Wanner, H.
           Climate and Society in Europe: The Last Thousand Years; Haupt: Berne,
           Switzerland, 2021; ISBN: 978-3-258-08234-9

    • Authors: Antonio Contino
      First page: 820
      Abstract: The book Climate and Society in Europe: The Last Thousand Years, through an appropriate interdisciplinary approach, identifies and analyses the nexus between past and present climatic variability (opening also a window on the future) but also its impact on environmental contexts, on historical events and on the becoming of European societies in the last millennium. This relevant publication is a must not only for scholars but also for any reader who is interested in the study of climate and its history and is curious to find out how much climate change has had an impact on the history of human societies in Europe. Climate and Society in Europe: The Last Thousand Years, written by two of the leading climate scientists in Europe, achieves an advanced goal through an innovative methodological approach, harmoniously managing to connect the historical climate sciences with the natural climate sciences, thus obtaining new and significant insights into both branches of knowledge. The authors paint an exhaustive picture of the relationships between climatic variability (long and short term) and historical and social aspects in Europe, producing a clear and intriguing text even for non-insiders, with an excellent iconographic apparatus and numerous in-depth inserts.
      Citation: Atmosphere
      PubDate: 2022-05-17
      DOI: 10.3390/atmos13050820
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 821: Particulate Matter and Ammonia Pollution
           in the Animal Agricultural-Producing Regions of North Carolina: Integrated
           Ground-Based Measurements and Satellite Analysis

    • Authors: Rebecca Wiegand, William H. Battye, Casey Bray Myers, Viney P. Aneja
      First page: 821
      Abstract: Intensive animal agriculture is an important part of the US and North Carolina’s (NC’s) economy. Large emissions of ammonia (NH3) gas emanate from the handling of animal wastes at these operations contributing to the formation of fine particulate matter (PM2.5) around the state causing a variety of human health and environmental effects. The objective of this research is to provide the relationship between ammonia, aerosol optical depth and meteorology and its effect on PM2.5 concentrations using satellite observations (column ammonia and aerosol optical depth (AOD)) and ground-based meteorological observations. An observational-based multiple linear regression model was derived to predict ground-level PM2.5 during the summer months (JJA) from 2008–2017 in New Hanover County, Catawba County and Sampson County. A combination of the Cumberland and Johnston County models for the summer was chosen and validated for Duplin County, NC, then used to predict Sampson County, NC, PM2.5 concentrations. The model predicted a total of six 24 h exceedances over the nine-year period. This indicates that there are rural areas of the state that may have air quality issues that are not captured for a lack of measurements. Moreover, PM2.5 chemical composition analysis suggests that ammonium is a major component of the PM2.5 aerosol.
      Citation: Atmosphere
      PubDate: 2022-05-17
      DOI: 10.3390/atmos13050821
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 822: PM2.5 Air Pollution Prediction through
           Deep Learning Using Multisource Meteorological, Wildfire, and Heat Data

    • Authors: Pratyush Muthukumar, Kabir Nagrecha, Dawn Comer, Chisato Fukuda Calvert, Navid Amini, Jeanne Holm, Mohammad Pourhomayoun
      First page: 822
      Abstract: Air pollution is a lethal global threat. To mitigate the effects of air pollution, we must first understand it, find its patterns and correlations, and predict it in advance. Air pollution is highly dependent on spatial and temporal correlations of prior meteorological, wildfire, and pollution structures. We use the advanced deep predictive Convolutional LSTM (ConvLSTM) model paired with the cutting-edge Graph Convolutional Network (GCN) architecture to predict spatiotemporal hourly PM2.5 across the Los Angeles area over time. Our deep-learning model does not use atmospheric physics or chemical mechanism data, but rather multisource imagery and sensor data. We use high-resolution remote-sensing satellite imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument onboard the NASA Terra+Aqua satellites and remote-sensing data from the Tropospheric Monitoring Instrument (TROPOMI), a multispectral imaging spectrometer onboard the Sentinel-5P satellite. We use the highly correlated Fire Radiative Power data product from the MODIS instrument which provides valuable information about the radiant heat output and effects of wildfires on atmospheric air pollutants. The input data we use in our deep-learning model is representative of the major sources of ground-level PM2.5 and thus we can predict hourly PM2.5 at unparalleled accuracies. Our RMSE and NRMSE scores over various site locations and predictive time frames show significant improvement over existing research in predicting PM2.5 using spatiotemporal deep predictive algorithms.
      Citation: Atmosphere
      PubDate: 2022-05-18
      DOI: 10.3390/atmos13050822
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 823: The Umbrella Type Canopy Increases
           Tolerance to Abiotic Stress-Leaf Microenvironment Temperature and
           Tropospheric Ozone in ‘Chambourcin’

    • Authors: Xinfeng Li, Shangrui Li, Yifan Zhang, Wenwei Huang, Huaping Zhu, Heng Zhai, Zhen Gao, Yuanpeng Du
      First page: 823
      Abstract: This study reports on the effect of the vertical shoot type canopy (VST) and umbrella type canopy (UT) on the fruit region microenvironment, light interception, tropospheric ozone, and berry quality of vertical trellis ‘Chambourcin’. The real-time temperature and humidity fluctuation and the daily average temperature of the UT canopy were lower than that of the VST canopy. An extremely high temperature was recorded around the fruit region of the VST canopy. Notably, the UT canopy significantly increased light interception and leaf area index and reduced the damage of atmospheric ozone to the leaves. These phenomena increased the content of soluble solids, anthocyanins, total phenols, flavonoids, and flavanols in the mature fruits of the UT canopy more than in the VST canopy. In conclusion, the UT canopy saves shoot management labor and improves the fruit region’s microenvironment and the content of anthocyanins, total phenols, flavonoids, and flavanols.
      Citation: Atmosphere
      PubDate: 2022-05-18
      DOI: 10.3390/atmos13050823
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 824: The Light Absorption Heating Method for
           Measurement of Light Absorption by Particles Collected on Filters

    • Authors: Carl G. Schmitt, Martin Schnaiter, Claudia Linke, W. Patrick Arnott
      First page: 824
      Abstract: A new instrument for the quantification of light absorption by particles collected on filters has been developed to address long standing environmental questions about light-absorbing particles in air, water, and on snow and ice. The Light Absorption Heating Method (LAHM) uses temperature changes when filters are exposed to light to quantify absorption. Through the use of calibration standards, the observed temperature response of unknown materials can be related to the absorption cross section of the substance collected on the filter. Here, we present a detailed description of the instrument and calibration. The results of the calibration tests using a common surrogate for black carbon, Fullerene soot, show that the instrument provides stable results even when exposed to adverse laboratory conditions, and that there is little drift in the instrument over longer periods of time. Calibration studies using Fullerene soot suspended in water, airborne propane soot, as well as atmospheric particulates show consistent results for absorption cross section when using accepted values for the mass absorption cross section of the soot and when compared to results from a 3-wavelength photoacoustic instrument. While filter sampling cannot provide the time resolution of other instrumentation, the LAHM instrument fills a niche where time averaging is reasonable and high-cost instrumentation is not available. The optimal range of absorption cross sections for LAHM is from 0.1 to 5.0 cm2 (~1.0–50.0 µg soot) for 25 mm filters and 0.4 to 20 cm2 (4.0–200.0 µg soot) for 47 mm filters, with reduced sensitivity to higher values.
      Citation: Atmosphere
      PubDate: 2022-05-18
      DOI: 10.3390/atmos13050824
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 825: Prediction of Fine Particulate Matter
           Concentration near the Ground in North China from Multivariable Remote
           Sensing Data Based on MIV-BP Neural Network

    • Authors: Hailing Wu, Ying Zhang, Zhengqiang Li, Yuanyuan Wei, Zongren Peng, Jie Luo, Yang Ou
      First page: 825
      Abstract: Rapid urbanization and industrialization lead to severe air pollution in China, threatening public health. However, it is challenging to understand the pollutants’ spatial distributions by relying on a network of ground-based monitoring instruments, considering the incomplete dataset. To predict the spatial distribution of fine-mode particulate matter (PM2.5) pollution near the surface, we established models based on the back propagation (BP) neural network for PM2.5 mass concentration in North China using remote sensing products. According to our predictions, PM2.5 mass concentrations are affected by changes in surface reflectance and the dominant particle size for different seasons. The PM2.5 mass concentration predicted by the seasonal model shows a similar spatial pattern (high in the east but low in the west) influenced by the terrain, but shows high value in winter and low in summer. Compared to the ground-based data, our predictions agree with the spatial distribution of PM2.5 mass concentrations, with a mean bias of +17% in the North China Plain in 2017. Furthermore, the correlation coefficients (R) of the four seasons’ instantaneous measurements are always above 0.7, indicating that the seasonal models primarily improve the PM2.5 mass concentration prediction.
      Citation: Atmosphere
      PubDate: 2022-05-18
      DOI: 10.3390/atmos13050825
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 826: On the Detection of Snow Cover Changes
           over the Australian Snowy Mountains Using a Dynamic OBIA Approach

    • Authors: Aliakbar A. Rasouli, Kevin K. W. Cheung, Keyvan Mohammadzadeh Alajujeh, Fei Ji
      First page: 826
      Abstract: This study detected the spatial changes in Snow Cover Area (SCA) over the Snowy Mountains in New South Wales, Australia. We applied a combination of Object-Based Image Analysis (OBIA) algorithms by segmentation, classification, and thresholding rules to extract the snow, water, vegetation, and non-vegetation land covers. For validation, the Maximum Snow Depths (MSDs) were collected at three local snow observation sites (namely Three Mile Dam, Spencer Creek, and Deep Creek) from 1984 to 2020. Multiple Landsat 5, 7, and 8 imageries extracted daily MSDs. The process was followed by applying an Estimation Scale Parameter (ESP) tool to build the local variance (LV) of object heterogeneity for each satellite scene. By matching the required segmentation parameters, the optimal separation step of the image objects was weighted for each of the image bands and the Digital Elevation Model (DEM). In the classification stage, a few land cover classes were initially assigned, and three different indices—Normalized Differential Vegetation Index (NDVI), Surface Water Index (SWI), and a Normalized Differential Snow Index (NDSI)—were created. These indices were used to adjust a few classification thresholds and ruleset functions. The resulting MSDs in all snow observation sites proves noticeable reduction trends during the study period. The SCA classified maps, with an overall accuracy of nearly 0.96, reveal non-significant trends, although with considerable fluctuations over the past 37 years. The variations concentrate in the north and south-east directions, to some extent with a similar pattern each year. Although the long-term changes in SCA are not significant, since 2006, the pattern of maximum values has decreased, with fewer fluctuations in wet and dry episodes. A preliminary analysis of climate drivers’ influences on MSD and SCA variability has also been performed. A dynamic indexing OBIA indicated that continuous processing of satellite images is an effective method of obtaining accurate spatial–temporal SCA information, which is critical for managing water resources and other geo-environmental investigations.
      Citation: Atmosphere
      PubDate: 2022-05-18
      DOI: 10.3390/atmos13050826
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 827: Analysis of Particulate Matter
           Concentration Changes before, during, and Post COVID-19 Lockdown: A Case
           Study from Victoria, Mexico

    • Authors: Bárbara A. Macías-Hernández, Edgar Tello-Leal
      First page: 827
      Abstract: The lockdown measures implemented due to the SARS-CoV-2 pandemic to reduce the epidemic curve, in most cases, have had a positive impact on air quality indices. Our study describes the changes in the concentration levels of PM2.5 and PM10 during the lockdown and post-lockdown in Victoria, Mexico, considering the following periods: before the lockdown (BL) from 16 February to 14 March, during the lockdown (DL) from 15 March to 2 May, and in the partial lockdown (PL) from 3 May to 6 June. When comparing the DL period of 2019 and 2020, we document a reduction in the average concentration of PM2.5 and PM10 of −55.56% and −55.17%, respectively. Moreover, we note a decrease of −53.57% for PM2.5 and −51.61% for PM10 in the PL period. When contrasting the average concentration between the DL periods of 2020 and 2021, an increase of 91.67% for PM2.5 and 100.00% for PM10 was identified. Furthermore, in the PL periods of 2020 and 2021, an increase of 38.46% and 31.33% was observed for PM2.5 and PM10, respectively. On the other hand, when comparing the concentrations of PM2.5 in the three periods of 2020, we found a decrease between BL and DL of −50.00%, between BL and PL a decrease of −45.83%, and an increase of 8.33% between DL and PL. In the case of PM10, a decrease of −48.00% between BL and DL, −40.00% between BL and PL, and an increase of 15.38% between the DL and PL periods were observed. In addition, we performed a non-parametric statistical analysis, where a significant statistical difference was found between the DL-2020 and DL-2019 pairs (x2 = 1.204) and between the DL-2021 and DL-2019 pairs (x2 = 0.372), with a p<0.000 for PM2.5, and the contrast between pairs of PM10 (DL) showed a significant difference between all pairs with p<0.01.
      Citation: Atmosphere
      PubDate: 2022-05-18
      DOI: 10.3390/atmos13050827
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 828: Non-Stationary Hydrological Regimes Due to
           Climate Change: The Impact of Future Precipitation in the Spillway Design
           of a Reservoir, Case Study: Sube Y Baja Dam, in Ecuador

    • Authors: Jorge Enrique Herbozo, Luis Eduardo Muñoz, María José Guerra, Veronica Minaya, Patricia Haro, Veronica Carrillo, Carla Manciati, Lenin Campozano
      First page: 828
      Abstract: Changes in flood loads and reservoir levels, produced by climate change (CC), represent an increasing concern for dam safety managers and downstream populations, highlighting the need to define adaptation strategies based on the dam failure risk management framework. Currently, thousands of dams worldwide, varying in use, age, and maintenance, may represent a threat to downstream cities in the case of structural failure. Several studies relate the failure of dams to several issues in the spillway, which may be even more vulnerable in CC conditions. This study provides a review of dam safety threats due to CC and approaches for the design/redesign of the spillway to cope with CC. A general four-stage methodology is proposed: data gathering and hydro-climatic, hydrological, and hydraulic analyses. Afterward, this methodology is applied to the spillway design for the Sube y Baja dam in Ecuador. The Probable Maximum Precipitation (PMP) increases around 20% considering CC under the Representative Concentration Pathway 8.5. Such an increment derived a 25% increase in the spillway maximum flow. These results show that the non-stationary hydrological regimes related to CC require a revision of engineering design criteria for hydraulic structures in general, and call for a consensus on design variables under CC.
      Citation: Atmosphere
      PubDate: 2022-05-18
      DOI: 10.3390/atmos13050828
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 829: Numerical Evaluation of a Novel Vertical
           Drop Airflow System to Mitigate Droplet Transmission in Trains

    • Authors: Sungho Yun, Jae-Chul Kim
      First page: 829
      Abstract: Owing to the outbreak of COVID-19, researchers are exploring methods to prevent contact and non-contact infections that occur via multiple transmission routes. However, studies on preventing infections caused by droplet transmission in public transportation are insufficient. To prevent the spread of infectious diseases, a new ventilation system in railway vehicles must be developed. In this study, a novel vertical drop airflow (VDA) system is proposed to mitigate the effect of droplet transmission in a high-speed train cabin. The droplet transmission route and droplet fate are investigated using three-dimensional fluid dynamics simulations, performed employing the Eulerian–Lagrangian model. Additionally, a porous model is adopted to simulate the effect of close-fitting masks. The results indicate that 120 s after coughing, the decrease in the droplet number in the VDA system is 72.1% of that observed in the conventional system. Moreover, the VDA system effectively suppresses droplet transmission because the maximum droplet travel distances of the VDA systems are 49.9% to 67.0% of those of the conventional systems. Furthermore, the effect of reducing droplet transmission by wearing a close-fitting mask is confirmed in all systems. Thus, the decrease in both droplet number and droplet transmission area in train cabins validate that the proposed VDA system has an effective airflow design to prevent droplet infection.
      Citation: Atmosphere
      PubDate: 2022-05-18
      DOI: 10.3390/atmos13050829
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 830: Conifers May Ameliorate Urban Heat Waves
           Better Than Broadleaf Trees: Evidence from Vancouver, Canada

    • Authors: Harold N. Eyster, Brian Beckage
      First page: 830
      Abstract: Anthropogenic greenhouse gas emissions are increasing the frequency of deadly heat waves. Heat waves are particularly devastating in cities, where air pollution is high and air temperatures are already inflated by the heat island effect. Determining how cities can ameliorate extreme summer temperature is thus critical to climate adaptation. Tree planting has been proposed to ameliorate urban temperatures, but its effectiveness, particularly of coniferous trees in temperate climates, has not been established. Here, we use remote sensing data (Landsat 8), high-resolution land cover data, and Bayesian models to understand how different tree and land cover classes affect summer surface temperature in Metro Vancouver, Canada. Although areas dominated by coniferous trees exhibited the lowest albedo (95% CrI 0.08–0.08), they were significantly (12.2 °C) cooler than areas dominated by buildings. Indeed, we found that for conifers, lower albedo was associated with lower surface temperatures. Planting and maintaining coniferous trees in cities may not only sequester CO2 to mitigate global climate change, but may also ameliorate higher temperatures and deadly heat waves locally.
      Citation: Atmosphere
      PubDate: 2022-05-19
      DOI: 10.3390/atmos13050830
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 831: Intra-Seasonal Variations and Frequency of
           Major Sudden Stratospheric Warmings for Northern Winter in Multi-System
           Seasonal Hindcast Data

    • Authors: Masakazu Taguchi
      First page: 831
      Abstract: This study investigates intra-seasonal variations and frequency of major sudden stratospheric warmings (MSSWs) in Northern winter seasonal hindcasts of six systems from 1993/1994 to 2016/2017, in comparison to the Japanese 55-year Reanalysis data. Results show that, over all, all systems reproduce precursory signals to the MSSWs well, such as the increase in the planetary wave heat flux in the extratropical lower stratosphere and the anomalous planetary wave patterns in the troposphere. Some systems are suggested to underestimate or overestimate the mean MSSW frequency. Such differences in the frequency of the MSSWs among the systems are related to those in the mean strength of the stratospheric polar vortex, and also may be partly contributed by those in the frequency of notable heat flux events. The hindcast data exhibit a weaker mean vortex and an increased MSSW frequency for a warm phase than for a cold phase of El Niño/Southern Oscillation, and for an easterly phase than for a westerly phase of the Quasi-Biennial Oscillation. These are qualitatively consistent with reanalysis results, except for a lower MSSW frequency for the warm phase in the reanalysis data. The reanalysis teleconnection results are larger in magnitude than the hindcast results for most ensemble members, although they are included near the edge of the distributions of the ensemble members. The changes in the MSSW frequency with the two external factors are correlated to those in the mean vortex strength among the ensemble members and also the ensemble means for some systems.
      Citation: Atmosphere
      PubDate: 2022-05-19
      DOI: 10.3390/atmos13050831
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 832: Study on the Water and Heat Fluxes of a
           Very Humid Forest Ecosystem and Their Relationship with Environmental
           Factors in Jinyun Mountain, Chongqing

    • Authors: Kai Wang, Yunqi Wang, Yujie Wang, Jieshuai Wang, Songnian Wang, Yincheng Feng
      First page: 832
      Abstract: The high-humidity mountain forest ecosystem (HHMF) of Jinyun Mountain in Chongqing is a fragile ecosystem that is sensitive to climate change and human activities. Because it is shrouded in fog year-round, illumination in the area is seriously insufficient. However, the flux (energy, water) exchanges (FEs) in this ecosystem and their influencing factors are not clear. Using one-year data from flux towers with a double-layer (25 m and 35 m) eddy covariance (EC) observation system, we proved the applicability of the EC method on rough underlying surfaces, quantified the FEs of HHMFs, and found that part of the fog might also be observed by the EC method. The observation time was separated from day and night, and then the environmental control of the FEs was determined by stepwise regression analysis. Through the water balance, it was proven that the negative value of evapotranspiration (ETN), which represented the water vapor input from the atmosphere to the ecosystem, could not be ignored and provided a new idea for the possible causes of the evaporation paradox. The results showed that the annual average daily sensible heat flux (H) and latent heat flux (LE) ranged from −126.56 to 131.27 W m−2 and from −106.7 to 222.27 W m−2, respectively. The annual evapotranspiration (ET), positive evapotranspiration (ETP), and negative evapotranspiration (ETN) values were 389.31, 1387.76, and −998.45 mm, respectively. The energy closure rate of the EC method in the ecosystems was 84%. Fog was the ETN observed by the EC method and an important water source of the HHMF. Therefore, the study area was divided into subtropical mountain cloud forests (STMCFs). Stepwise regression analysis showed that the H and LE during the day were mainly determined by radiation (Rn) and temperature (Tair), indicating that the energy of the ecosystem was limited, and future climate warming may enhance the FEs of the ecosystem. Additionally, ETN was controlled by wind speed (WS) in the whole period, and WS was mainly affected by altitude and temperature differences within the city. Therefore, fog is more likely to occur in the mountains near heat island cities in tropical and subtropical regions. This study emphasizes that fog, as an important water source, is easily ignored in most EC methods and that there will be a large amount of fog in ecosystems affected by future climate warming, which can explain the evaporation paradox.
      Citation: Atmosphere
      PubDate: 2022-05-19
      DOI: 10.3390/atmos13050832
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 833: A Systematic Review of Drought Indices in
           Tropical Southeast Asia

    • Authors: Muhamad Khoiru Zaki, Keigo Noda
      First page: 833
      Abstract: This study systematically reviews the under-researched experience of performance indices to determine extreme hydroclimate in tropical Southeast Asia. The review was conducted by the Preferred Reporting Items for Systematic Review and Meta-Analysis methods with SCOPUS databases. The screening of the articles is based on the inclusion and exclusion criteria encompassing articles published between 2000 and 2021 with solely focused on three extreme hydroclimate indices (standardized precipitation index or SPI, standardized precipitation evapotranspiration index or SPEI, and palmer drought severity index or PDSI) applied in tropical Southeast Asia, and articles form in English. This study found solely 14 of the 532 articles met the criteria and those articles were analyzed thematically and synthesized narratively. The results showed the strengths of indices with the simple data input (SPI and SPEI); those indices are commonly used at the government level in Southeast Asia due to their data availability, which has Viet Nam as the highest (5 articles) number of publications, followed by Malaysia (4 articles), Thailand (3 articles), and Indonesia (2 articles). On the other hand, the sensitivity of SPI and SPEI has the limitation for specific purposes such as in the agricultural sector when applied to Southeast Asia. In the end, we highlighted the potential of future research applying quasi-biennial oscillation and South Western Indian Ocean as well as El Niño Southern Oscillation climate indices.
      Citation: Atmosphere
      PubDate: 2022-05-19
      DOI: 10.3390/atmos13050833
      Issue No: Vol. 13, No. 5 (2022)
       
  • Atmosphere, Vol. 13, Pages 834: Evaluation of the Wind Environment around
           Multiple Urban Canyons Using Numerical Modeling

    • Authors: Minu Son, Jeong-In Lee, Jae-Jin Kim, Soo-Jin Park, Daegi Kim, Do-Yong Kim
      First page: 834
      Abstract: This study aimed to evaluate the wind environment in step-up and step-down urban canyons through a computational numerical experiment using the computational fluid dynamics (CFD) model. Spatial structural conditions were considered according to the location of high-rise buildings, and the changing wind patterns inside canyons were compared and analyzed by varying the building heights. Under the step-up to step-down condition, wind velocity inside the canyon weakened, a vertical vortex formed, and vertical air flow separated; additionally, in shallow and deep canyons, wind velocity and detailed flow differed slightly according to each additional condition. For the step-down to step-up condition, the building located in the center appeared to be isolated, and a general wind environment phenomenon consistent with the step-up and step-down structures was observed. However, depending on the isolated area, an additional roof-top canyon was formed, and the wind field in the canyon was found to affect the wind velocity and detailed flow in other canyons. The wind velocity components of the inflow and outflow winds into the canyon differed based on the step-up to step-down or step-down to step-up conditions, and according to the conditions in the first and second canyons. Furthermore, the vertical wind velocity components were greatly affected by the step-up and step-down structures. Accordingly, the height and structural location of the building could affect various phenomena, such as the separation of vortices and air currents inside the canyon, and a variable wind environment was formed according to a series of conditions for the building.
      Citation: Atmosphere
      PubDate: 2022-05-19
      DOI: 10.3390/atmos13050834
      Issue No: Vol. 13, No. 5 (2022)
       
 
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