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Atmosphere
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ISSN (Online) 2073-4433
Published by MDPI Homepage  [84 journals]
  • Atmosphere, Vol. 13, Pages 996: Impacts of the Interannual Variability of
           the Kuroshio Extension on the East Asian Trough in Winter

    • Authors: Jianxiang Sun, Suping Zhang, Yuxi Jiang, Yanshuo Wang, Baoqin Wu, Haijiao Wang
      First page: 996
      Abstract: The responses of the East Asian Trough (EAT) to the Kuroshio Extension (KE) interannual fluctuation and the underlying mechanisms in the boreal winter are investigated through the lag regression approach in this study. When the KE is in the stable state, the sea surface temperature (SST) front is strengthened, with cold (warm) SST anomaly in the western (eastern) region of the KE, releasing less (more) heat into the atmosphere. The opposite patterns hold for the KE unstable periods. The analysis of the observations shows that the stable KE corresponds to a deeper EAT, accompanied with a stronger winter monsoon over Mongolia and northeastern China. The atmospheric Rossby waves, transient eddies, and thermal winds are found to be responsible for this relationship between the KE and EAT. The SST warming in the lower reaches of the KE excites the Rossby wave activity that propagates toward East Asia, leading to 25% of the EAT amplification. Meanwhile, influenced by the KE-induced Rossby waves, the background baroclinicity is intensified over Japan, which enhances the transient eddy activity, contributing to another 42% magnitude of the EAT deepening. In addition, as depicted by the thermal wind theory, the strong SST cooling in the upper branch of the KE forces an anomalous cyclonic circulation through modifying the meridional temperature gradient, facilitating the EAT development. The finding points to the better understandings of the EAT and associated East Asian winter climate variability, which are crucial for their major economic and social impacts on the large populations in the region.
      Citation: Atmosphere
      PubDate: 2022-06-21
      DOI: 10.3390/atmos13070996
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 997: Pearl Millet (Pennisetum glaucum)
           Seedlings Transplanting as Climate Adaptation Option for Smallholder
           Farmers in Niger

    • Authors: Bouba Traore, Abdourazak Alio Moussa, Amadou Traore, Yahaya Seydou Abdel Nassirou, Malick N. Ba, Ramadjita Tabo
      First page: 997
      Abstract: Pearl millet is the most widely grown cereal crop in the arid and semi-arid regions of Africa, and in Niger in particular. To determine an optimized management strategy for smallholder farmers in southern Niger to cope with crop production failure and improve cropping performance in the context of climate change and variability, multi-site trials were conducted to evaluate the impacts of transplanting on pearl millet growth and productivity. Eight treatments viz. T1-0NPK (100% transplanting without NPK), T1-NPK (100% transplanting + NPK), T2-0NPK (100% transplanting of empty hills without NPK), T2-NPK (100% transplanting of empty hills + NPK), T3-0NPK (50% transplanting of empty hills without NPK), T3-NPK (50% transplanting of empty hills + NPK), T4-0NPK (farmer practice without NPK), and T4-NPK (farmer practice + NPK) were included in the experiment. Compared to farmer practice, transplanting significantly reduced time to tillering, flowering, and maturity stages by 15%, 27%, and 11%, respectively. The results also revealed that T1-NPK significantly increased panicle weight, total biomass, grain yield, and plant height by 40%, 38%, 27%, and 23%, respectively. Farmers’ evaluations of the experiments supported these findings, indicating three substantial advantages of transplanting, including higher yield (37.50% of responses), larger, more vigorous and more panicles (34.17% of responses), and good tillering (28.33% of responses). An economic profitability analysis of the system revealed that biomass gain (XOF 359,387/ha) and grain gain (XOF 324,388/ha) increased by 34% and 22%, respectively, with T1-NPK. Therefore, it can be inferred that transplanting is a promising strategy for adapting millet cultivation to climate change and variability in southern Niger.
      Citation: Atmosphere
      PubDate: 2022-06-21
      DOI: 10.3390/atmos13070997
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 998: Comparison of East Asian Summer Monsoon
           Simulation between an Atmospheric Model and a Coupled Model: An Example
           from CAS-ESM

    • Authors: Wen Zhang, Feng Xue, Jiangbo Jin, Xiao Dong, He Zhang, Renping Lin
      First page: 998
      Abstract: In this study, the Chinese Academy of Sciences’ Earth System Model Version 2 (CAS-ESM2) and its atmospheric component were evaluated for the ability to simulate the East Asian summer monsoon (EASM), in terms of climatology and composites in El Niño decaying years (EN) and La Niña years (LN). The results show that the model can realistically simulate the El Niño Southern Oscillation (ENSO) annual cycle, the interannual variation, the evolution process, and the prerequisites of ENSO, but the trend of developing and decaying is faster than that of the observations. With regard to the climatological mean state in the EASM, the coupled model run can largely improve the precipitation and 850 hPa wind simulated in the atmospheric model. Moreover, the coupled run can also reduce the mid-latitude bias in the atmospheric model simulation. Composite methods were then adopted to examine performance in different phases of the ENSO, from a mature winter to a decaying summer. The atmospheric model can well reproduce the Western North Pacific Anomalous Anticyclone (WNPAC)/Western North Pacific Anomalous Cyclone (WNPC) during EN/LN well, but the westerly/easterly anomalies and the associated precipitation anomalies over the equatorial Central Eastern Pacific are somewhat overestimated. Compared with the atmospheric model, these anomalies are all underestimated in the coupled model, which may be related to the ENSO-related SST bias appearing in the Eastern Indian Ocean. Due to the ENSO and ITCZ bias in the historical simulations, the simulated ENSO-related SST and the precipitation anomaly are too equator-trapped in comparison with the observations, and the cold tongue overly extends westward. This limits the ability of the model to simulate ENSO-related EASM variability. For the subseasonal simulations, though atmospheric model simulations can reproduce the westward extension of the Western Pacific subtropic high (WPSH) in EN decaying summers, the eastward retreat of the WPSH in LN is weak. The historical simulations show limited improvement, indicating that the subseasonal variation in the EASM is still a considerable challenge for current generation models.
      Citation: Atmosphere
      PubDate: 2022-06-21
      DOI: 10.3390/atmos13070998
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 999: Performance of CMIP6 HighResMIP on the
           Representation of Onset and Cessation of Seasonal Rainfall in Southern
           West Africa

    • Authors: Francis Nkrumah, Kwesi Akumenyi Quagraine, Kwesi Twentwewa Quagraine, Caroline Wainwright, Gandomè Mayeul Leger Davy Quenum, Abraham Amankwah, Nana Ama Browne Klutse
      First page: 999
      Abstract: Changes in rainfall onset and cessation dates are critical for improving decision making and adaptation strategies in numerous socio-economic sectors. An objective method of determining onset and cessation date is employed over Southern West Africa (SWA) in this study. The method is applied over 34 years of the quasi-global rainfall dataset from the Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) and five High Resolution Model Intercomparison Project (HighResMIP) model datasets under the Coupled Model Intercomparison Project Phase 6 (CMIP6) experiment. Generally, a strong agreement exists between CHIRPS and the HighResMIP models in capturing the behaviour of seasonal rainfall over SWA, with models able to capture the bimodal rainfall season. The ability of models in capturing onset and cessation dates as observed in CHIRPS shows the strength of these models in representing the short break between the two wet seasons that is otherwise known as the ‘Little Dry Season’. Patterns observed in the onset and cessation dates over the SWA region are consistent with the northward and southward displacement of the Intertropical Convergence Zone (ITCZ). The seasonal timing of the models shows good agreement with observations such that most mean onset/cessation dates agree within 26 days. While IPSL-CM6A-ATM-HR, a model among the five HighResMIPs used in the study, best agrees with CHIRPS in representing onset and cessation dates during the unimodal rainfall season, no one model best agrees with CHIRPS during the bimodal season, with models outperforming each other in representing onset/cessation dates with little variation.
      Citation: Atmosphere
      PubDate: 2022-06-21
      DOI: 10.3390/atmos13070999
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1000: Impact of Preventive Measures on
           Subjective Symptoms and Antigen Sensitization against Japanese Cedar,
           Cypress Pollen and House Dust Mites in Patients with Allergic Rhinitis: A
           Retrospective Analysis in the COVID-19 Era

    • Authors: Takashi Oda, Fumiaki Maeda, Sachio Takeno, Yuri Tsuru, Chie Ishikawa, Takashi Ishino, Kota Takemoto, Takao Hamamoto, Tsutomu Ueda, Tomohiro Kawasumi, Hiroshi Iwamoto, Kazunori Kubota, Yoshio Nakao, Masaru Kunimoto
      First page: 1000
      Abstract: For >2 years, Japan’s government has been urging the populace to take countermeasures to prevent COVID-19, including mask wearing. We examined whether these preventive behaviors have affected the rate and degree of sensitization against pollen and house dust antigens in patients with allergic rhinitis. We retrospectively surveyed 2565 patients who had undergone allergy blood testing during the period 2015–2021. We subdivided this period into eras based on the COVID-19 pandemic: the pre-COVID (2015–2019, n = 1879) and COVID (2020–2021, n = 686) eras. The positive rates for Japanese cedar and cypress in the 40–59-year-olds and those for house dust in the 20–39-year-olds were significantly reduced in the COVID era versus those in the pre-COVID era. Each group’s mean antigen-specific CAP scores decreased significantly from the 1st to 2nd era: from 1.98 to 1.57 for cedar (p < 0.01), 1.42 to 0.95 for cypress (p < 0.05), and 2.86 to 2.07 for house dust (p < 0.01). Our survey of the patients’ clinical records indicates that 47.5% of the pollinosis patients reported improvement in nasal symptoms after the three seasons of pollen dispersion in the COVID era. Japan’s quarantine policies designed to combat the spread of COVID-19 thus coincide with pivotal measures to alleviate allergic reactions.
      Citation: Atmosphere
      PubDate: 2022-06-21
      DOI: 10.3390/atmos13071000
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1001: The Influence of Teleconnections on the
           Precipitation in Baluchistan

    • Authors: Erum Aamir, Aamir Khan, Muhammad Abubakar Tariq
      First page: 1001
      Abstract: Precipitation plays a vital role in the economies of agricultural countries, such as Pakistan. Baluchistan is the largest province in Pakistan (in terms of land) and it is facing reoccurring droughts due to changing precipitation patterns. The landscape of the province consists of rugged terrain, mountains, hills, and valleys. The torrential rains lead to devastating flash floods due to the topography of the province, which has proven to be more catastrophic in nature. It is quite intriguing to observe the changing precipitation patterns in Baluchistan. Precipitation has become less frequent but intense, resulting in flash floods and landslides, as well as damage to agriculture, infrastructure, trade, environment, and the ecosystem. Baluchistan is under a drought warning and is already facing a water crisis. This study was performed on monthly precipitation time series data obtained from the Pakistan Meteorological Department (PMD) for determining trends in precipitation from 41 years of data (1977 to 2017) over 13 selected stations in Baluchistan. Due to the non-linear nature of the precipitation data, a non-parametric Mann–Kendall (MK) test was used to determine the increasing or decreasing trends in precipitation on a monthly basis. Large-scale atmospheric circulation and climate indices that affected precipitation were considered to determine their influence on precipitation. Statistical techniques of the partial Mann–Kendall (PMK) and Pearson correlation were applied to each station to ascertain the influence on precipitation due to climatic indices.
      Citation: Atmosphere
      PubDate: 2022-06-22
      DOI: 10.3390/atmos13071001
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1002: Snow Representation over Siberia in
           Operational Seasonal Forecasting Systems

    • Authors: Danny Risto, Kristina Fröhlich, Bodo Ahrens
      First page: 1002
      Abstract: Seasonal forecasting systems still have difficulties predicting temperature over continental regions, while their performance is better over some maritime regions. On the other hand, the land surface is a substantial source of (sub-)seasonal predictability. A crucial land surface component in focus here is the snow cover, which stores water and modulates the surface radiation balance. This paper’s goal is to attribute snow cover seasonal forecasting biases and lack of skill to either initialization or parameterization errors. For this purpose, we compare the snow representation in five seasonal forecasting systems (from DWD, ECMWF, Météo-France, CMCC, and ECCC) and their performances in predicting snow and 2-m temperature over a Siberian region against ERA5 reanalysis and station data. Although all systems use similar atmospheric and land initialization approaches and data, their snow and temperature biases differ in sign and amplitude. Too-large initial snow biases persist over the forecast period, delaying and prolonging the melting phase. The simplest snow scheme (used in DWD’s system) shows too-early and fast melting in spring. However, systems including multi-layer snow schemes (Météo-France and CMCC) do not necessarily perform better. Both initialization and parameterization are causes of snow biases, but, depending on the system, one can be more dominant.
      Citation: Atmosphere
      PubDate: 2022-06-22
      DOI: 10.3390/atmos13071002
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1003: Observation of Gravity Wave Vertical
           Propagation through a Mesospheric Inversion Layer

    • Authors: Thurian Le Du, Philippe Keckhut, Alain Hauchecorne, Pierre Simoneau
      First page: 1003
      Abstract: The impact of a mesospheric temperature inversion on the vertical propagation of gravity waves has been investigated using OH airglow images and ground-based Rayleigh lidar measurements carried out in December 2017 at the Haute-Provence Observatory (OHP, France, 44N). These measurements provide complementary information that allows the vertical propagation of gravity waves to be followed. An intense mesospheric inversion layer (MIL) observed near 60 km of altitude with the lidar disappeared in the middle of the night, offering a unique opportunity to evaluate its impact on gravity wave (GW) propagation observed above the inversion with airglow cameras. With these two instruments, a wave with a 150 min period was observed and was also identified in meteorological analyses. The gravity waves’ potential energy vertical profile clearly shows the GW energy lost below the inversion altitude and a large increase of gravity wave energy above the inversion in OH airglow images with waves exhibiting higher frequency. MILs are known to cause instabilities at its top part, and this is probably the reason for the enhanced gravity waves observed above.
      Citation: Atmosphere
      PubDate: 2022-06-22
      DOI: 10.3390/atmos13071003
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1004: Impacts of the Thermal Gradient on Inland
           Advecting Sea Breezes in the Southeastern United States

    • Authors: Joseph Wermter, Stephen Noble, Brian Viner
      First page: 1004
      Abstract: Sea breezes are frequently observed in the South Carolina/Georgia region of the Southeastern United States (SEUS) and can reach upwards of 150km inland. This region is unique among the places frequently affected by sea breeze due to it being a continental location with relatively flat topography. The thermal gradient between land and water environments is a factor in introducing the sea breeze, but its role in the inland extent of sea breeze propagation isn’t as well known. We investigate the role of the thermal gradient in previously catalogued sea breeze events observed at the Savannah River Site (SRS) by taking differences of temperature measurements at inland and coastal weather stations for the days that the events occurred. We saw that the temperature differences for those days were much higher than in the non-sea breeze days during the mornings and afternoon. Numerical models were also used to conduct a sensitivity study on a sea breeze case, using simple modifications of the temperature gradient. We found that while the modifications did not stop the generation of a sea breeze circulation, the extent of the inland propagation was dependent on the magnitude of the thermal gradient.
      Citation: Atmosphere
      PubDate: 2022-06-22
      DOI: 10.3390/atmos13071004
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1005: The Effects of Indoor Air Filter on
           Reductions in PM2.5 Associated Health Risks of Respiratory Function in
           Mouse

    • Authors: Zheng Yang, Qingyang Liu, Yanju Liu, Qingyun Guo, Yunfang Shan, Zhibin Cheng, Zhenyu Zhong
      First page: 1005
      Abstract: This study aimed to assess whether protective measures could reduce the health risks of air pollution in mice living in the chambers situated at a suburban site in Beijing. The living chambers of mice were divided into four groups: male mice with and without the high-efficiency particulate air (HEPA) filter (male group A and group B), as well as female mice with and without the HEPA filter (female group A and group B). The experiment was carried out from 1 December 2017 to 31 May 2018. Parameters of respiratory function during periods of clean air and air pollution were determined for all groups to evaluate the role of the indoor air filter (i.e., HEPA) in protection against respiratory health risks in mice. Significant differences in minute volumes were observed in male and female groups with versus without the HEPA. Additionally, respiratory health parameters including respiratory rate, duration of breaking, expiratory time, and relaxation time exhibited differences in female groups with HEPA versus without HEPA. Levels of inflammatory factors in the lungs were measured for all groups after 6months of exposure. Greater mean levels of IL-6 and TNF-α were found in the male groups without HEPA than in those with HEPA. Higher average concentrations of IL-6, T-AOC, SOD, GSH-Px, LDH, TNF-α, and TGF-β1 were found in the female group without HEPA than those without HEPA. Our study has proved the effective protection provided by indoor air filters (i.e., HEPA filters) in reducing respiratory health risks associated with PM2.5.
      Citation: Atmosphere
      PubDate: 2022-06-22
      DOI: 10.3390/atmos13071005
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1006: Explore the Benefits of Natural Air: New
           Insights from Field and Chamber Tests on Cognitive Performance

    • Authors: Wenmao Zeng, Huan Liu, Shanshan Hou, Xiangwei Qiu, Xinchang Chen, Meng Liu, Dehai Wu, Lumeng Liu
      First page: 1006
      Abstract: Exposure to natural environments has a range of health benefits, including enhancing psychological restoration and cognitive development. While there are various explanations on the causes for the benefits of the natural exposure, such as less air pollution and noise, more physical activity, stronger social interactions, or even more diverse microbial community, etc., this study has zeroed in on the air quality of the natural environment. In addition to low-level pollution, what makes the natural air superior remains unclear. To this end, we conducted a series of psychological evaluation and cognitive tests on a couple of subjects in a national forest park in southwest China. Based on the results, we built an artificial chamber where selected air parameters can be independently manipulated and carried out similar tests in the chamber. We came to the following conclusion. (1) Exposure to real natural environment demonstrated tangible benefits for cognitive performances and mental states and the benefits can be obtained to some extent in the artificial environment by creating air qualities similar to the air in the natural environment. (2) Scents in natural environments may be one of the key beneficial factors. (3) Adopting proper cognitive test is critical for distinguishing the differences made by the natural exposure. Working memory showed marked responses to the natural exposure.
      Citation: Atmosphere
      PubDate: 2022-06-22
      DOI: 10.3390/atmos13071006
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1007: State of the Simulation of Mesoscale
           Winds in the Mediterranean and Opportunities for Improvements

    • Authors: Anika Obermann-Hellhund
      First page: 1007
      Abstract: The Mediterranean region is a densely populated and economically relevant area with complex orography including mountain ranges, islands, and straits. In combination with pressure gradients, this creates many mesoscale wind systems that cause, e.g., wind gusts and wildfire risk in the Mediterranean. This article reviews the recent state of the science of several mesoscale winds in the Mediterranean and associated processes. Previous work, including case studies on several time ranges and resolutions, as well as studies on these winds under future climate conditions, is discussed. Simulations with grid spacings of 25 to 50 km can reproduce winds driven by large-scale pressure patterns such as Mistral, Tramontane, and Etesians. However, these simulations struggle with the correct representation of winds channeled in straits and mountain gaps and around islands. Grid spacings of 1–3 km are certainly necessary to resolve these small-scale features. The smaller grid spacings are widely used in case studies, but not yet in simulations over large areas and long periods, which also could help to understand the interaction between small-scale phenomena in separate locations. Furthermore, by far not all Mediterranean straits, islands, and mountain gaps were studied in-depth and many interesting Mediterranean small-scale winds still need to be studied.
      Citation: Atmosphere
      PubDate: 2022-06-22
      DOI: 10.3390/atmos13071007
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1008: Opportunity for Tropical Cyclone
           Lifecycle Predictions from Pre-Formation to Ending Stage: Eastern North
           Pacific 2021 Season

    • Authors: Russell L. Elsberry, Hsiao-Chung Tsai, Corie Capalbo, Wei-Chia Chin, Timothy P. Marchok
      First page: 1008
      Abstract: Building on previous studies of western North Pacific formation and intensity predictions along the ECMWF ensemble medium-range track forecasts, the first objective of this transition to the eastern North Pacific was to provide earlier forecasts of the Time-to-Formation (T2F) and Time-to-Hurricane (T2H) than are available from the National Hurricane Center Advisories. For the first six hurricanes of the 2021 season, the first detections in the ECMWF ensemble were 8 days to 12 days in advance of the T2F times and 9 days to 13 days in advance of the T2H times. The major advance in this study has been to document that the ECMWF ensemble is also capable of predicting Ending-T2H and Ending-T2F timings and positions along those 15-day ECMWF ensemble track forecasts. This study for the first time documents the opportunity for high wind warnings during the entire lifecycle of the 2021 season hurricanes even days in advance of formation. Validations of the pre-hurricane and Ending-hurricane tracks and timings are provided for the lifecycles of seven hurricanes and the “Almost-Hurricane Guillermo”. Because the technique has been accepted for operational testing at the Joint Typhoon Warning Center, a companion article has been submitted that will describe the flowchart methodology for evaluating the twice-daily ECMWF ensemble forecasts to select the most likely pre-hurricane circulation as early as possible while non-selecting the likely false alarm circulations.
      Citation: Atmosphere
      PubDate: 2022-06-22
      DOI: 10.3390/atmos13071008
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1009: MP-PIC Simulation of Biomass Steam
           Gasification Using Ilmenite as an Oxygen Carrier

    • Authors: Timo Dymala, Shen Wang, Kolja Jarolin, Tao Song, Laihong Shen, Maksym Dosta, Stefan Heinrich
      First page: 1009
      Abstract: Biomass chemical looping gasification (BCLG) is a complex process for the conversion of biomass using an oxygen carrier, which is influenced by various operating parameters. For a better understanding of this process, biomass steam gasification using ilmenite as an oxygen carrier is numerically investigated in this work using the multiphase particle-in-cell (MP-PIC) method, which is a modified Euler–Lagrange approach. As a first step, a reduced reaction network for biomass gasification is investigated in a spouted bed. As a second step, the reaction network is coupled with oxygen carrier kinetics of ilmenite for the simulation of BCLG in a lab-scale fluidized bed. For both steps, the influence of the main operating parameters, such as reactor temperature, steam-to-biomass ratio, and oxidation degree of the oxygen carrier, are investigated and compared with experimental data from the literature. In general, the simulations show satisfying results and the predicted syngas compositions with varied operating parameters are in good agreement with the experimental data. Furthermore, the main trends for the syngas composition are predicted correctly and the oxidation degree of the oxygen carrier has a significant influence on the resulting syngas composition confirming the experimental results.
      Citation: Atmosphere
      PubDate: 2022-06-22
      DOI: 10.3390/atmos13071009
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1010: Effect of Dust Types on the
           Eco-Physiological Response of Three Tree Species Seedlings: Eucalyptus
           camaldulensis, Conocarpus erectus and Bombax ceiba

    • Authors: Muhammad Farrakh Nawaz, Muhammad Haroon U. Rashid, Muhammad Saeed-Ur-Rehman, Sadaf Gul, Taimoor Hassan Farooq, Muhammad Azeem Sabir, Junaid Iftikhar, Nader R. Abdelsalam, Eldessoky S. Dessoky, Saqer S. Alotaibi
      First page: 1010
      Abstract: Dust is the collection of fine particles of solid matter, and it is a major issue of atmospheric pollution. Dust particles are becoming the major pollutants of the urban environment due to hyperbolic manufacturing and automobile pollution. These atmospheric pollutants are not only hazardous for human beings, but they also affect tree growth, particularly in urban environments. This study was designed to examine the changes in morphological and physiological traits of three tree species seedlings (Eucalyptus camaldulensis, Conocarpus erectus, and Bombax ceiba) in response to different dust types. In a pot experiment under controlled conditions, three-month-old seedlings of selected trees species were subjected to four treatments of dust: T1 = controlled; T2 = wood dust; T3 = soil dust; and T4 = carbon dust. During the whole experiment, 10 g/plant/dose was applied in 8 doses with a one-week interval. The results depicted that the growth was the maximum in T1 (control) and the minimum in T4 (carbon dust). In our findings, B. ceiba performed better under the same levels of dust pollution as compared with the other two tree species. The B. ceiba tree species proved to be the most tolerant to dust pollution by efficiently demolishing oxidative bursts by triggering SOD, POD, and CAT under different dust types compared to controlled conditions. Stomatal conductance, photosynthetic rate, and transpiration rate were negatively influenced in all three tree species in response to different dust applications. Based on the findings, among these three tree species, B. ceiba is recommended for dust polluted areas followed by E. camaldulensis and Conocarpus erectus due to their better performance and efficient dust-foraging potential.
      Citation: Atmosphere
      PubDate: 2022-06-23
      DOI: 10.3390/atmos13071010
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1011: An Ensemble-Based Analysis of a Liminal
           Extreme Rainfall Event near Taiwan

    • Authors: Alexandra S. Cole, Michael M. Bell, Jennifer C. DeHart
      First page: 1011
      Abstract: This study analyzes an ensemble of numerical simulations of a heavy rainfall event east of Taiwan on 9 June 2020. Heavy rainfall was produced by quasi-stationary back-building mesoscale convective systems (MCS) associated with a mei-yu front. Global model forecast skill was poor in location and intensity of rainfall. The mesoscale ensemble showed liminal conditions between heavy rainfall or little to no rainfall. The two most accurate and two least accurate ensemble members are selected for analysis via validation against radar-estimated rainfall observations. All members feature moist soundings with low levels of free convection (LFC) and sufficient instability for deep convection. We find that stronger gradients in 100-m θe and θv in the most accurate members associated with a near-surface frontal boundary focus the lifting mechanism for deep, moist convection and enhanced rainfall. As the simulations progress, stronger southerly winds in the least accurate members advect drier mid-level air into the region of interest and shift the near-surface boundary further north and west. Analysis of the verification ensemble mean analysis reveals a strong near-surface frontal boundary similarly positioned as in the most accurate members and dry air aloft more similar to that in the least accurate members, suggesting that the positioning of the frontal boundary is more critical to accurately reproducing rainfall patterns and intensity in this case. The analyses suggest that subtle details in the simulation of frontal boundaries and mesoscale flow structures can lead to bifurcations in producing extreme or almost no rainfall. Implications for improved probabilistic forecasts of heavy rainfall events will be discussed.
      Citation: Atmosphere
      PubDate: 2022-06-23
      DOI: 10.3390/atmos13071011
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1012: Seasonal Aerosol Acidity, Liquid Water
           Content and Their Impact on Fine Urban Aerosol in SE Canada

    • Authors: Andrea M. Arangio, Pourya Shahpoury, Ewa Dabek-Zlotorzynska, Athanasios Nenes
      First page: 1012
      Abstract: This study explores the drivers of aerosol pH and their impact on the inorganic fraction and mass of aerosol in the S.E. Canadian urban environments of Hamilton and Toronto, Ontario. We find that inter-seasonal pH variability is mostly driven by temperature changes, which cause variations of up to one pH unit. Wintertime acidity is reduced, compared to summertime values. Because of this, the response of aerosol to precursors fundamentally changes between seasons, with a strong sensitivity of aerosol mass to levels of HNO3 in the wintertime. Liquid water content (LWC) fundamentally influences the aerosol sensitivity to NH3 and HNO3 levels. In the summertime, organic aerosol is mostly responsible for the LWC at Toronto, and ammonium sulfate for Hamilton; in the winter, LWC was mostly associated with ammonium nitrate at both sites. The combination of pH and LWC in the two sites also affects N dry deposition flux; NO3− fluxes were comparable between the two sites, but NH3 deposition flux at Toronto is almost twice what was seen in Hamilton; from November to March N deposition flux slows down leading to an accumulation of N as NO3− in the particle phase and an increase in PM2.5 levels. Given the higher aerosol pH in Toronto, aerosol masses at this site are more sensitive to the emission of HNO3 precursors compared to Hamilton. For both sites, NOx emissions should be better regulated to improve air quality during winter; this is specifically important for the Toronto site as it is thermodynamically more sensitive to the emissions of HNO3 precursors.
      Citation: Atmosphere
      PubDate: 2022-06-23
      DOI: 10.3390/atmos13071012
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1013: Performance Evaluation of the RANS Models
           in Predicting the Pollutant Concentration Field within a Compact Urban
           Setting: Effects of the Source Location and Turbulent Schmidt Number

    • Authors: Mohammad Reza Kavian Nezhad, Carlos F. Lange, Fleck
      First page: 1013
      Abstract: Computational Fluid Dynamics (CFD) is used to accurately model and predict the dispersion of a passive scalar in the atmospheric wind flow field within an urban setting. The Mock Urban Setting Tests (MUST) experiment was recreated in this work to test and evaluate various modeling settings and to form a framework for reliable representation of dispersion flow in compact urban geometries. Four case studies with distinct source locations and configurations are modeled using Reynolds-Averaged Navier–Stokes (RANS) equations with ANSYS CFX. The performance of three widely suggested closure models of standard k−ε, RNG k−ε, and SST k−ω is assessed by calculating and interpreting the statistical performance metrics with a specific emphasis on the effects of the source locations. This work demonstrates that the overprediction of the turbulent kinetic energy by the standard k−ε counteracts the general underpredictions by RANS in geometries with building complexes. As a result, the superiority of the standard k−ε in predicting the scalar concentration field over the two other closures in all four cases is observed, with SST k−ω showing the most discrepancies with the field measurements. Additionally, a sensitivity study is also conducted to find the optimum turbulent Schmidt number (Sct) using two approaches of the constant and locally variable values.
      Citation: Atmosphere
      PubDate: 2022-06-23
      DOI: 10.3390/atmos13071013
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1014: The Performance of Three-Frequency GPS
           PPP-RTK with Partial Ambiguity Resolution

    • Authors: Zhongbao Yan, Xiaohong Zhang
      First page: 1014
      Abstract: The correct ambiguity resolution of real-time kinematic precise point positioning (PPP-RTK) plays an essential role in achieving fast, reliable, and high-precision positioning. However, the ambiguity of incorrect fixing will cause poor PPP-RTK positioning performance. Hence, it is essential to optimize the selected strategy of the ambiguity subset to obtain a more reliable ambiguity resolution performance for PPP-RTK. For this reason, a partial ambiguity resolution (PAR) method combining quality control and Schmidt orthogonalization (Gram–Schmidt) is proposed in this study. To investigate the performance of global positioning system (GPS) dual- and three-frequency PPP-RTK comprehensively, the PAR method based on the Gram–Schmidt method was analyzed and compared with the highest elevation angle method, which considered the satellite with the highest elevation angle as the reference satellite. The performance of ambiguity fixing, atmospheric corrections, and positioning were evaluated using five stations in Belgium and its surrounding area. The results showed average epoch fixing rates of 81.01%, 95.92%, 82.05%, and 97.93% in the dual-frequency highest elevation angle (F2-MAX), dual-frequency Gram–Schmidt (F2-ALT), three-frequency highest elevation angle (F3-MAX), and three–frequency Gram–Schmidt (F3-ALT), respectively. In terms of the time to first fix (TTFF), 89.02%, 94.25%, 90.24%, and 95.69% of the single-differenced (SD) narrow lane (NL) ambiguity fell within 3 min in F2-MAX, F2-ALT, F3-MAX, and F3-ALT, respectively. As far as the ionospheric corrections are concerned, the proportion of SD ionospheric residuals within ±0.25 total electron content units (TECU) were 95.08%, 95.93%, 95.68%, and 96.98% for the F2-MAX, F2-ALT, F3-MAX, and F3-ALT, respectively. The centimeter-level accuracy of both the horizontal and vertical positioning errors can be achieved almost instantaneously in F3-ALT. This is attributed to the accurate and reliable SD NL ambiguity fixing based on the Gram–Schmidt approach.
      Citation: Atmosphere
      PubDate: 2022-06-23
      DOI: 10.3390/atmos13071014
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1015: Mapping Thunderstorm Electrical Structure
           in the Troposphere in Warm Season with VLF/LF Total Lightning Monitoring
           Data over the Pearl River Delta Region, China

    • Authors: Jianguo Wang, Si Cheng, Li Cai, Yadong Fan, Mi Zhou, Quanxin Li, Yijun Huang
      First page: 1015
      Abstract: Mapping the thunderstorm electrical structure could provide an effective way for lightning-sensitive facilities protection, such as aircraft and maritime assets. However, the weather radar that is normally used to forecast storms and rainfall mainly detects precipitation in the atmosphere and indicates the existence of liquid raindrops and ice particles by reflectivity. Here, we use intra-cloud events of eight thunderstorm days in the warm season, which are detected by VLF/LF Total Lightning monitoring system, to reveal the thunderstorm electrical structures in the 300 × 300 km area of the Pearl River Delta (PRD) region. The differences in height range in four types of time intervals and three types of intro-cloud events proportions are compared on 16 May. With the proportion between 20% and 80% in the time interval of 15 min, the height distribution and the electrical structure of eight thunderstorm days are clearly exhibited. The positive IC events lie in the average height between 7.5 and 12.4 km, while the negative IC events are located between 5.3 and 11.7 km. The electrical structures show the variations during the evolution process, with a dipole structure in most circumstances, while temporary reversions are identified in the initial and the dissipating stage of thunderstorms, presenting the inverted dipole and the tripole structures.
      Citation: Atmosphere
      PubDate: 2022-06-24
      DOI: 10.3390/atmos13071015
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1016: Investigation and Evaluation of Flue Gas
           Pollutants Emission in Waste-to-Energy Plant with Flue Gas Recirculation

    • Authors: Weishu Wang, Shujian Tian, Jisheng Long, Jun Liu, Qinhui Ma, Kai Xu, Zhen Zhang
      First page: 1016
      Abstract: The emissions of pollutants by waste-to-energy power plants, which contain more toxic substances owing to the complicated composition of municipal solid waste (MSW), such as NOx, SO2, HCl, HF, particulate matter, and heavy metals, has attracted increasing attention worldwide. To effectively control the pollutants, a flue gas cleaning system is indispensable in the operation of MSW incineration power plants. In this study, the flue gas cleaning system in a waste-to-energy power plant with flue gas recirculation (FGR) was evaluated. The concentrations of various pollutants were measured and compared with the standards at home and abroad. The results indicated that NOx emission can be effectively reduced by FGR, and that the emission concentration of NOx may meet the national emission standards only by adopting FGR. However, the emission levels of HCl and PM exceeded the limits in legislative standards; therefore, operation optimization or retrofit of a deacidification system and bag filter were proposed to comply with the international standards and near-zero-emissions goal.
      Citation: Atmosphere
      PubDate: 2022-06-24
      DOI: 10.3390/atmos13071016
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1017: Seasonal Aspects of Radiative and
           Advective Air Temperature Populations: A Canadian Perspective

    • Authors: Ana Žaknić-Ćatović, William A. Gough
      First page: 1017
      Abstract: Canadian high-frequency temperature time series exhibit physical heterogeneity in the coexistence of radiative and advective populations in the total air temperature sample. This work examines forty-five Canadian hourly air temperature records to study seasonal characteristics and variability of radiative and advective population counts and their corresponding temperature biases and trends. The Linear Pattern Discrimination algorithm, conceptualized in a previous study, was adjusted to seasonal analysis on the equinox-to-equinox time scale. Count analysis of radiative and advective days supports the existence of two distinct thermal regimes, Spring–Summer and Fall–Winter. Further, seasonal advective counts for the majority of examined stations typically decrease in numbers. The consistently warmer winter radiative temperature extrema points to the critical role of the advective population in control of the overall temperature magnitude. Canadian northwest warming trends are found to be the highest, indicating the amplifying effect of decreasing advective counts with rapidly increasing temperatures that weaken the advective population’s moderating ability to control the magnitude of the total temperature population.
      Citation: Atmosphere
      PubDate: 2022-06-24
      DOI: 10.3390/atmos13071017
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1018: PM2.5 Pollution Levels and Chemical
           Components at Teahouses along the Poon Hill Trek in Nepal

    • Authors: James D. Johnston, John D. Beard, M. Lelinneth B. Novilla, Frank X. Weber, Ryan T. Chartier
      First page: 1018
      Abstract: Unhealthy levels of fine particulate matter (PM2.5) from the local burning of solid fuels, and from regional transport of pollutants, remain a major public health problem in the Himalayan foothill villages in Nepal. Teahouses (i.e., mountain lodges) along popular hiking trails in the lower Himalayas commonly use wood as the primary energy source for heating; however, little is known about teahouse air quality. The purpose of this study was to characterize the levels and chemical constituents of indoor and ambient PM2.5 at three villages along the Poon Hill circuit trek in the Annapurna Conservation Area in Nepal. A convenience sample of five PM2.5 measurements was collected with portable MicroPEM V.3.2A exposure monitors. Filters were analyzed for black and brown carbon using integrating sphere optical transmittance and 33 elemental constituents using energy-dispersive X-ray fluorescence. Median indoor PM2.5 over the sampling period was 41.3 µg/m3, whereas median ambient PM2.5 over the sampling period was 34.7 µg/m3. Chemical species associated with wood smoke, such as potassium (GM = 0.88 µg/m3), predominated. High indoor and ambient PM2.5 levels may pose a significant occupational health risk to teahouse workers, who may experience chronic exposures during trekking seasons. Our findings warrant additional research to characterize teahouse air pollution exposures more fully and to evaluate intervention measures.
      Citation: Atmosphere
      PubDate: 2022-06-24
      DOI: 10.3390/atmos13071018
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1019: Study on Improving the Air Quality with
           Emission Enhanced Control Measures in Beijing during a National Parade
           Event

    • Authors: Bingbo Huang, Minjun Deng, Qingxian Gao, Zhanyun Ma, Mindong Chen
      First page: 1019
      Abstract: Research on the enhanced control and emission-reduction measures to improve air quality during major events could provide data theory and scientific support for air-quality improvement during non-activities. Based on the air-quality data published by the China Environmental Monitoring Station and the meteorological elements and weather conditions released by the China Meteorological Administration, this paper explored the characteristics of air-quality evolution in Beijing from 5 August to 18 September 2015 and the weather situation during the Military Parade. The results showed that: (1) Emission-reduction measures implemented for air quality by Beijing and its surrounding area were induced, and we explored the contribution of these measures to pollutants or AQI in the locality. (2) During the 2015 Military Parade, Beijing was in the front or lower part of the high-pressure system. Due to the strong effect of North or Northeast winds, the weather situation was conducive to the diffusion of pollutants. When before or after the implementation, once the atmospheric diffusion was poor, the pollutants would accumulate gradually. Thus, it can be seen that the weather situation had a great impact on air quality. (3) During the implementation, PM2.5, PM10, NO2 and other pollutants decreased significantly, of which the concentration of PM10 decreased the most, from 109 μg·m−3 down to 34 μg·m−3, and the concentration of PM2.5 decreased by 72.73%. According to the changes between before and during the implementation or during and after the implementation, the concentration of PM10 and PM2.5 increased when the implementation of the emission-reduction measures had been finished, indicating that the enhanced control measures made a great contribution to the emission reduction in particles. (4) In addition, the annual average of AQI in the three years is 87.49, and the average value of a normal year was the average value of 2013 and 2014. The average value of the normal year during the military parade is 64.63, which was 70.40% lower than the average value of AQI during the military parade. The goal of reaching the secondary standard of GB-3095-2012 was achieved, and there was still a long way to go from the primary standard. In a few words, in order to achieve the goal of better air quality throughout the year, all parties still needed to coordinate control and make joint efforts.
      Citation: Atmosphere
      PubDate: 2022-06-24
      DOI: 10.3390/atmos13071019
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1020: Editorial for the Special Issue
           “Atmospheric Radon Measurements, Control, Mitigation and
           Management”

    • Authors: Alexandra
      First page: 1020
      Abstract:  The Special Issue of the open-access journal Atmosphere addresses the issue of “Atmospheric Radon Measurements, Control, Mitigation and Management”, based on the global need for better management of radon and indoor air pollutants inside buildings, based on reliable research experience. [...]
      Citation: Atmosphere
      PubDate: 2022-06-24
      DOI: 10.3390/atmos13071020
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1021: Chemical Compositions of Rainfall Water
           in Nyingchi City, Tibet

    • Authors: Wei Wang, Lixue Guan, Jiamin Zhao, Zhipeng Sha, Jiangping Fang
      First page: 1021
      Abstract: Understanding precipitation chemistry is highlighted as important worldwide due to its close relationship with air quality and impacts on ecosystems. However, the chemical composition of precipitation is limited in Tibet, where alpine ecosystems are sensitive to global change. Here, rainwater samples were collected in Nyingchi city from January 2021 to December 2021, and a total of 44 samples were obtained. Major ions (NO3−, NH4+, Cl−, SO42−, Na+, K+, Ca2+ and Mg2+) were analyzed. Results showed that the predominant ions in the precipitation were Ca2+, Na+, SO42−, and Cl−. Precipitation was mainly concentrated in summer, accounting for 65.2% of all samples collected during the monitoring period. As a result, ion deposition fluxes were mainly concentrated in summer, accounting for 55%, 53%, 84%, 82%, 61%, 63%, 75.8%, and 37.8% of the annual Ca2+, K+, Mg2+, Na+, NH4+, Cl−, SO42−, and NO3−, respectively. Backward trajectory analysis revealed that airmasses were mainly from the southern direction, but the sources varied widely. In addition, Na+ and Cl− ions were dominated by the sea source fraction; the ions of Ca2+ and K+ were dominated by crustal fraction sources. The NH4+ and NO3− ions were mainly influenced by local pollution. However, SO42− was mainly from long distance transports. Our results suggest that ions abundance was varied largely in different direction airmasses in southeast Tibet. Considering that ion deposition fluxes were mainly concentrated in the summer and the airmasses were mainly from the southern direction in this season, the pollutants from the southern direction the environmental effects of those ions should be given more attention in the future.
      Citation: Atmosphere
      PubDate: 2022-06-24
      DOI: 10.3390/atmos13071021
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1022: Shelter Efficiency of Various Shelterbelt
           Configurations: A Wind Tunnel Study

    • Authors: Huiliang Li, Yongdong Wang, Shengyu Li, Aikedai Askar, Haifeng Wang
      First page: 1022
      Abstract: The construction of protective forests in Nursultan is key to reducing near-surface wind speeds and snowstorm effects in urban areas. This study analyzed the effects of the number of plant rows and spacing of the shelterbelts on the flow field around protective forests to evaluate the wind protection benefits of the existing configuration of the shelterbelt in Nursultan and guide the construction of protective forests. We measured the airflow fields of four shelterbelts with different numbers of rows, seven double pure shelterbelts, and double mixed shelterbelts of arbors and shrubs with different spacings. The results showed that the airflow field around the shelterbelts can be divided into five characteristic regions based on shelter efficiency: a deceleration region before the shelterbelt, acceleration region above the canopy, strong deceleration region in the canopy layer, deceleration region behind the shelterbelt, and recovery region behind the shelterbelt. In terms of windproof ability, the wind protection benefits of a shelterbelt with six rows are the best in a single shelterbelt. Behind the shelterbelt, the wind protection benefits of double pure shelterbelts are greater than that of double mixed shelterbelts of arbor and shrub. On the contrary, the windbreak benefits of the latter are stronger than those of the former between the two shelterbelts.
      Citation: Atmosphere
      PubDate: 2022-06-25
      DOI: 10.3390/atmos13071022
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1023: Spatialized Analysis of Air Pollution
           Complaints in Beijing Using the BERT+CRF Model

    • Authors: Xiaoshuang Wang, Yunqiang Zhu, Hongyun Zeng, Quanying Cheng, Xiaohong Zhao, Haihong Xu, Tianmo Zhou
      First page: 1023
      Abstract: (1) Background: To better carry out air pollution control and to assist in accurate investigations of air pollution, in this study, we fully explore the spatial distribution characteristics of air pollution complaint results and provide guidance for air pollution control by combining regional air monitoring data. (2) Methods: By selecting the air pollution complaint information in Beijing from 2019 to 2020, in this study, we extract the names and addresses of complaint points, as well as the complaint times and types by adopting the BERT (bidirectional encoder representations from transformers) + CRF (conditional random field) model deep learning method. Moreover, through further filtering and processing of the complaint points’ address information, we achieve address matching and spatial positioning of the complaint points, and realize the regional spatial representation of air pollution complaints in Beijing in the form of a heat map. (3) Results: The experimental results are compared and analyzed with the ranking data of total suspended particulate (TSP) concentration of townships (streets) in Beijing during the same period, indicating that the key areas of air pollution complaints have a high correlation with the key polluted township (street) areas. The distribution of complaints and the types of complaints in each township (street) differ according to the population density in each township (street), the level of education, and economic activity. (4) Conclusions: The results of this study show that the public, as the intuitive perceiver of air pollution, is sensitive to the air pollution situation at a smaller spatial scale; furthermore, complaints can provide guidance and reference for the direction of air pollution control and law enforcement investigations when coupled with geographical features and economic status.
      Citation: Atmosphere
      PubDate: 2022-06-27
      DOI: 10.3390/atmos13071023
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1024: Spatiotemporal Variations of Chinese
           Terrestrial Ecosystems in Response to Land Use and Future Climate Change

    • Authors: Shuaishuai Li, Jiahua Zhang, Malak Henchiri, Dan Cao, Sha Zhang, Yun Bai, Shanshan Yang
      First page: 1024
      Abstract: Terrestrial ecosystems in China are threatened by land use and future climate change. Understanding the effects of these changes on vegetation and the climate-vegetation interactions is critical for vegetation preservation and mitigation. However, land-use impacts on vegetation are neglected in terrestrial ecosystems exploration, and a deep understanding of land-use impacts on vegetation dynamics is lacking. Additionally, few studies have examined the contribution of vegetation succession to changes in vegetation dynamics. To fill the above gaps in the field, the spatiotemporal distribution of terrestrial ecosystems under the current land use and climate baseline (1970–2000) was examined in this study using the Comprehensive Sequential Classification System (CSCS) model. Moreover, the spatiotemporal variations of ecosystems and their succession under future climate scenarios (the 2030s–2080s) were quantitatively projected and compared. The results demonstrated that under the current situation, vegetation without human disturbance was mainly distributed in high elevation regions and less than 10% of the national area. For future vegetation dynamics, more than 58% of tundra and alpine steppe would shrink. Semidesert would respond to climate change with an expansion of 39.49 × 104 km2, including the succession of the steppe to semidesert. Although some advancement of the temperate forest at the expense of substantial dieback of tundra and alpine steppe is expected to occur, this century would witness a considerable shrinkage of them, especially in RCP8.5, at approximately 55.06 × 104 km2. Overall, a warmer and wetter climate would be conducive to the occurrence and development of the CSCS ecosystems. These results offer new insights on the potential ecosystem response to land use and climate change over the Chinese domain, and on creating targeted policies for effective adaptation to these changes and implementation of ecosystem protection measures.
      Citation: Atmosphere
      PubDate: 2022-06-27
      DOI: 10.3390/atmos13071024
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1025: Centennial Precipitation Characteristics
           Change in Haihe River Basin, China

    • Authors: Xin Chen, Yanli Liu, Zhouliang Sun, Jianyun Zhang, Tiesheng Guan, Junliang Jin, Cuishan Liu, Guoqing Wang, Zhenxin Bao
      First page: 1025
      Abstract: Research on precipitation regularity in the past 120 years is an important link in analyzing the precipitation characteristics of watersheds. This paper systematically analyzes the characteristic changes of centennial precipitation data in the Haihe River basin with the help of CRU data, PCI, SPI, and the Pearson type III curve. The results show that the spatial and temporal distribution of precipitation in the Haihe River basin has a more obvious inconsistency. The temporal distribution shows the characteristics of relatively stable in the early period and increasing fluctuation in the later period, the concentration of precipitation gradually decreases, and the overall drought level decreases. The spatial distribution shows a general pattern of gradually decreasing from southwest to northeast, the overall trend of summer precipitation changes from stable to north–south extremes, and the distribution probability of extreme precipitation events in the basin decreases from southeast to northwest, while the drought-prone area transitions from the northeast to the west and southwest of the basin. Under the influence of both climate change and human activities, the seasonal distribution of precipitation tends to be average, the area affected by extreme precipitation rises, and the arid area shifts to the inland area.
      Citation: Atmosphere
      PubDate: 2022-06-28
      DOI: 10.3390/atmos13071025
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1026: The Influence of Urbanization on the
           Development of a Convective Storm—A Study for the Belém
           Metropolitan Region, Brazil

    • Authors: Juarez Ventura de Oliveira, Julia Cohen, Michael Barlage, Maria Assunção Silva Dias
      First page: 1026
      Abstract: One of the main problems faced by the Belém Metropolitan Region (BMR) inhabitants is flash floods caused by precarious infrastructure and extreme rainfall events. The objective of this article is to investigate whether and how the local urban characteristics may influence the development of thunderstorms. The Weather Research and Forecasting (WRF) model was used with three distinct configurations of land use/cover to represent urbanization scenarios in 2017 and 1986 and the forest-only scenario. The WRF model simulated reasonably well the event. The results showed that the urban characteristics of the BMR may have an impact on storm systems in the urban areas close to the Northern Coast of South America. In particular, for the urban characteristics in the BMR in 2017, the intensification of the storm may be linked to a higher value of energy available for convection (over 1000 J kg−1) and favorable wind convergence and vertical shear in the urban area (where the wind speed at the surface was more than 3 m s−1 slower than in the forest-only scenario). Meanwhile, the other land cover scenarios could not produce a similar storm due to lack of moisture, wind convergence/shear, or convective energy.
      Citation: Atmosphere
      PubDate: 2022-06-28
      DOI: 10.3390/atmos13071026
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1027: Lowering the Temperature to Increase Heat
           Equity: A Multi-Scale Evaluation of Nature-Based Solutions in Toronto,
           Ontario, Canada

    • Authors: Vidya Anderson, William A. Gough, Matej Zgela, Dragan Milosevic, Jelena Dunjic
      First page: 1027
      Abstract: Nature-based solutions (NbS) present an opportunity to reduce rising temperatures and the urban heat island effect. A multi-scale study in Toronto, Ontario, Canada, evaluates the effect of NbS on air and land surface temperature through two field campaigns at the micro and meso scales, using in situ measurements and LANDSAT imagery. This research demonstrates that the application of NbS in the form of green infrastructure has a beneficial impact on urban climate regimes with measurable reductions in air and land surface temperatures. Broad implementation of green infrastructure is a sustainable solution to improve the urban climate, enhance heat and greenspace equity, and increase resilience.
      Citation: Atmosphere
      PubDate: 2022-06-28
      DOI: 10.3390/atmos13071027
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1028: Large-Eddy Simulation of Airflow and
           Pollutant Dispersion in a Model Street Canyon Intersection of Dhaka City

    • Authors: Sheikh Hassan, Umma Habiba Akter, Preetom Nag, Md. Mamun Molla, Amirul Khan, Md Farhad Hasan
      First page: 1028
      Abstract: The atmospheric flow and dispersion of traffic exhaust were numerically studied in this work while considering a model street canyon intersection of a city. The finite volume method (FVM)-based large-eddy simulation (LES) technique in line with ANSYS Fluent have been used for flow and pollutant dispersion modelling through the consideration of the atmospheric boundary layer (ABL). Hexahedral elements are considered for computational domain discretization in order to numerically solve problems using FVM-LES. The turbulence parameters were superimposed through a spectral synthesizer in the existing LES model through ANSYS Fluent as part of ’damage control’ due to the unsteady k−ϵ simulation. Initially, the code is validated with an experimental study of an urban street canyon where the width and height ratio is in unity. After validation, a model urban street canyon intersection was investigated in this work. The model shows a high pollutant concentration in the intersecting corner areas of the buildings. Additionally, the study of this model intersection shows a high level of pollutant concentration at the leeward wall of downwind building in the case of increased height of an upwind building. Most importantly, it was realized from the street intersection design that three-dimensional interconnection between the dominating canyon vortices and roof level flow plays a pivotal role in pollutant concentration level on the windward walls. The three-dimensional extent of corner eddies and their interconnections with dominating vortices were found to be extremely important as they facilitate enhanced ventilation. Corner eddies only form for the streets towards the freeway and not for the streets towards the intersection. The results and key findings of this work offer qualitative and quantitative data for the estimation, planning, and implementation of exposure mitigation in an urban environment.
      Citation: Atmosphere
      PubDate: 2022-06-28
      DOI: 10.3390/atmos13071028
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1029: The Impact of Long-Range Transport of
           Biomass Burning Emissions in Southeast Asia on Southern China

    • Authors: Lijuan Zhang, Sijia Ding, Wenmin Qian, Aimei Zhao, Shimin Zhao, Yi Yang, Guoqing Weng, Minghui Tao, Hui Chen, Shaohua Zhao, Zhongting Wang
      First page: 1029
      Abstract: The long-range transport of biomass burning pollutants from Southeast Asia has a significant impact on air quality in China. In this study, the Moderate Resolution Imaging Spectroradiometer (MODIS) fire data and aerosol optical depth (AOD) products and the Tropospheric Monitoring Instrument (TROPOMI) carbon monoxide (CO) data were used to analyze the impact of air pollution caused by biomass burning in Southeast Asia on southern China. Results showed that Yunnan, Guangdong and Guangxi were deeply affected by biomass burning emissions from March to April during 2016–2020. Comparing the data for fires on the Indochinese Peninsula and southern provinces of China, it is obvious that the contribution of pollutants emitted by local biomass burning in China to air pollution is only a small possibility. The distribution of CO showed that the overall emissions increased greatly from March to April, and there was an obvious transmission process. In addition, the MODIS AOD in areas close to the national boundary of China is at a high level (>0.6), and the AOD in the southwest of Guangxi province and the southeast of Yunnan Province is above 0.8. Combined with a typical air pollution event in southern China, the UVAI combined with wind direction and other meteorological data showed that the pollutants were transferred from the Indochinese Peninsula to southern China under the southwest monsoon. The PM2.5 data from ground-based measurements and backward tracking were used to verify the pollutant source of the pollution event, and it was concluded that the degree of pollution in Yunnan, Guangxi and Guangdong provinces was related to the distance from the Indochinese Peninsula. Results indicate that it is necessary to carry out in-depth research on the impact of cross-border air pollution transport on domestic air quality as soon as possible and to actively cooperate with foreign countries to carry out pollution source research and control.
      Citation: Atmosphere
      PubDate: 2022-06-28
      DOI: 10.3390/atmos13071029
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1030: Summertime Assessment of an Urban-Scale
           Numerical Weather Prediction System for Toronto

    • Authors: Sylvie Leroyer, Stéphane Bélair, Vanh Souvanlasy, Marcel Vallée, Simon Pellerin, David Sills
      First page: 1030
      Abstract: Urban-scale Numerical Weather Prediction (NWP) systems will be important tools for decision-making in and around large cities in a changing climate exposed to more extreme weather events. Such a state-of-the-art real-time system down to 250-m grid spacing was implemented in the context of the Toronto 2015 Panamerican games, Canada (PanAm). Combined with the Global Environmental Multiscale (GEM) model, attention was brought to the representation of the detailed urban landscape, and to the inclusion of sub-daily variation of the Great Lakes surface temperature. Results show a refined representation of the urban coastal environment micro-meteorology with a strong anisotropy of the urban heat island reaching about 2 °C on average for the summer season, coastal upwelling, and mesoscale features such as cumulus clouds and lake-breeze flow. Objective evaluation at the surface with a dense observational network reveals an overall good performance of the system and a clear improvement in comparison to reference forecasts at 2.5-km grid spacing in particular for standard deviation errors in urban areas up to 0.3 °C for temperature and dew point temperature, and up to 0.5 m s−1 for the wind speed, as well as for precipitation with an increased Equitable Threat Score (ETS) by up to 0.3 for the evening accumulation. The study provides confidence in the capacity of the new system to improve weather forecasts to be delivered to urban dwellers although further investigation of the initialization methods in urban areas is needed.
      Citation: Atmosphere
      PubDate: 2022-06-28
      DOI: 10.3390/atmos13071030
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1031: Three-Dimensional Dynamic Variations of
           Ground/Air Surface Temperatures and Their Correlation with Large-Scale
           Circulation Indexes in Southwest China (1980–2019)

    • Authors: Hanyu Jin, Qingping Cheng, Ping Wang
      First page: 1031
      Abstract: Air/soil temperatures play important roles in land–atmosphere interactions. The three-dimensional (temporal, spatial, and vertical) variations of maximum, mean, and minimum ground soil temperature at 0 cm (GSTx, GSTm, and GSTn, respectively), surface air temperature at 2 m (SATx, SATm, and SATn, respectively), and soil–air temperature difference (SATDx, SATDm, and SATDn, respectively) and their potential linkages with large-scale indexes in Southwest China during 1980–2019 were analyzed. Variations of GST and SAT at the majority of stations (pixels) exhibited significant (p ≤ 0.05) warming, albeit at different rates; consequently, SATD exhibited different variation. Moreover, the period of GST, SAT, and SATD was similar in intra-annual and interannual oscillation but was different in interdecadal oscillation. The variation rate of GST, SAT, and SATD exhibited significant (p ≤ 0.05) correlation with elevation, but with different variation gradient. Notably, asymmetric variation of SATDx (downward trend) and of SATDn (upward trend) with elevation was found at elevations >3 km. Wavelet coherence showed that the Atlantic Multidecadal Oscillation is the dominant factor affecting GST and SAT, whereas the Pacific Decadal Oscillation and the North Atlantic Oscillation make the greatest contributions to SATD. It was found that GST, SAT, and SATD exhibit different variations under the effects of global warming, the driving mechanism of which requires further study.
      Citation: Atmosphere
      PubDate: 2022-06-28
      DOI: 10.3390/atmos13071031
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1032: Road Traffic and Its Influence on Urban
           Ammonia Concentrations (France)

    • Authors: Mélodie Chatain, Eve Chretien, Sabine Crunaire, Emmanuel Jantzem
      First page: 1032
      Abstract: Ammonia (NH3) is an unregulated atmospheric gaseous pollutant in ambient air, involved in the formation of fine particles. Ammonia is therefore a major precursor of particulate matter (PM), the health effects of which have been widely demonstrated. NH3 emissions are clearly dominated by the agricultural sector (livestock and fertilizers), but other sources may also be important and less studied, such as road traffic with the increased use of catalytic converters in vehicles. This study is based on a long-term real-time measurements campaign (December 2019–September 2021) on two urban sites: a background site and a roadside site in the same agglomeration in France. The study of historical measurements at the background site clearly demonstrated the dominance of agriculture on the ammonia concentrations. This influence was also observed at both sites during the measurement campaign. The annual and monthly averages obtained in the study were similar to previous ones, with concentrations between 1–10 µg/m3 at both sites, indicating lower levels than previous studies for the roadside site. The ammonia levels measured during the campaign at the traffic site were significantly higher than those measured at the background site, highlighting the road traffic influence on ammonia in urban area. The biomass burning influence also seemed to be observed during this long measurement campaign at the agglomeration scale. The influences of road traffic and biomass burning on ammonia concentration remain small compared to agriculture.
      Citation: Atmosphere
      PubDate: 2022-06-29
      DOI: 10.3390/atmos13071032
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1033: Effects of Manure Removal Frequencies and
           Deodorants on Ammonia and GHG Concentrations in Livestock House

    • Authors: Xia Zhang, Jian Li, Le Shao, Hailin Huan, Feng Qin, Pin Zhai, Jie Yang, Xiaoqing Pan
      First page: 1033
      Abstract: In order to mitigate the concentration of NH3 and greenhouse gases (GHGs: CO2, N2O, CH4) in livestock houses, two experiments, one determining the ideal manure removal frequency by cleaning the feces from a livestock house once, twice, three, and four times a day, and one in which microbial deodorant and VenaZn deodorant were sprayed, were conducted in a rabbit breeding house. The NH3, CO2, N2O, and CH4 concentrations were monitored continuously with an Innova 1512 photoacoustic gas monitor during the experiments. The results were as follows: the manure removal frequency had a significant impact on the average concentrations of NH3, CO2, and CH4 in the rabbit house. Cleaning the feces in the rabbit breeding house two to three times a day significantly reduced the NH3 concentration, and, on the contrary, cleaning the feces four times a day increased the NH3 concentration in rabbit house; increasing the manure removal frequency significantly reduced the concentrations of CO2 and CH4 in the rabbit house. Considering the average concentrations of NH3, CO2, N2O, and CH4 in the rabbit house and economic cost, it was better to remove feces twice a day. The average NH3 and CO2 concentration declined significantly within 3 days in the summer and winter; the N2O concentration declined within 3 days in the summer but did not decline in the winter; and there was no effect on the CH4 concentration in the summer and in the winter after spraying the rabbit house with microbial deodorant. Therefore, it was better to spray microbial deodorant twice a week on Monday and Thursday to reduce the NH3, CO2, and N2O concentrations in rabbit houses. The NH3, CO2, N2O, and CH4 concentrations first showed a decreasing trend and then an increasing trend over 5 days in the summer and 7 days in the winter after VenaZn deodorant was sprayed in the rabbit house, and the NH3, CO2, N2O, and CH4 concentrations on day 3 and day 4 were significantly lower than they were on the other days.
      Citation: Atmosphere
      PubDate: 2022-06-29
      DOI: 10.3390/atmos13071033
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1034: Analyzing Thermal Comfort Sensations in
           Semi-Outdoor Space on a University Campus: On-Site Measurements in
           Tehran’s Hot and Cold Seasons

    • Authors: Sevil Zafarmandi, Mohammadjavad Mahdavinejad, Leslie Norford, Andreas Matzarakis
      First page: 1034
      Abstract: Outdoor and semi-outdoor thermal comfort on the university campus is essential for encouraging students’ outdoor activities and interactions and reducing energy consumption in occupied buildings. For this reason, the current study presents on-site measurements and questionnaire surveys on a university campus in Tehran, Iran. It aims to investigate the most applicable thermal indices in Tehran’s cold and hot seasons. Measurements were conducted over winter and summer days; in addition, the survey collected 384 responses. The results confirm that the Predicted Mean Vote (PMV) and Physiological Equivalent Temperature (PET) indices are better predictors of semi-outdoor thermal comfort in summer and winter than Universal Thermal Climate Index (UTCI) and New Standard Effective Temperature (SET*), respectively, highlighting the importance of considering accurate thermal indices in different seasons. Finally, all analyses were gathered in a predictive empirical model, knowledge of which may be helpful in the planning and design of outdoor and semi-outdoor environments in Tehran and similar climates.
      Citation: Atmosphere
      PubDate: 2022-06-29
      DOI: 10.3390/atmos13071034
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1035: Increased Exposure of China’s
           Cropland to Droughts under 1.5 °C and 2 °C Global Warming

    • Authors: Lijuan Miao, Jing Zhang, Giri Raj Kattel, Ran Liu
      First page: 1035
      Abstract: Global warming and human activities have intensified the duration, frequency, and extent of climatic extremes. The projected rise in global mean annual temperature of 1.5 °C/2 °C is thought to have severe impacts on the population exposed to droughts. Although these impacts on humans have been widely explored, the impacts associated with the cropland exposed to droughts have not been widely investigated. Here, we have examined the spatiotemporal pattern of China’s drought conditions and cropland exposure to droughts under global warming of 1.5 °C and 2 °C, along with the avoided impacts (as evaluated by the cropland exposure to droughts) when limiting the global warming to 1.5 °C instead of 2 °C. Results suggest that compared to the reference period (1995–2014), drought conditions will be alleviated when the projected rise in mean global temperature is limited to 1.5 °C rather than 2.0 °C. Although severe droughts tend to be mainly distributed in northwestern China, drought severities are increasing in southern China, especially in the southeastern region. In addition, the total cropland exposure to droughts across China exhibits an increasing trend in response to the 0.5 °C of additional global warming, especially in northwestern China and Huang−Huai−Hai region. If global warming could be limited to 1.5 °C, the avoided impact will exceed 30%, especially in northwestern China, southwestern China, and the Huang−Huai−Hai Plain. Furthermore, the rising cropland exposure to droughts under the 2 °C global warming is likely to be triggered by the rising frequencies of moderate and extreme droughts. Therefore, climate mitigation strategies are urgently needed to keep the global temperature rise below 1.5 °C, for the future sustainability of China’s cropland.
      Citation: Atmosphere
      PubDate: 2022-06-29
      DOI: 10.3390/atmos13071035
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1036: Non-Invasive-Monitoring Methodology for
           the Evaluation of Environmental Impacts on Istrian Stone Surfaces in
           Venice

    • Authors: Margherita Gnemmi, Laura Falchi, Elisabetta Zendri
      First page: 1036
      Abstract: This work proposes a non-invasive, affordable, and easily reproducible methodology for monitoring limestone surfaces vulnerability. The proposed methodology integrates the study of environmental factors impacting limestone surfaces with physical–chemical and morphological observations of historical Istria stone surfaces in Venice. Pollutant trends of particulate matters (PPM), NO2, SO2, O3, and the meteorological forcing were considered over a 20-year period. To collect information on the conservation state of stone surfaces, visual, optical microscopy observation, chemical analysis via FT-IR-ATR spectroscopy, and the evaluation of morphological and profilometric parameters by digitalizing the surface of silicone molds were carried out. The surfaces of Ca’ Foscari, Ca’ Dolfin, and Garzoni Palace were monitored in 2015 and five years after. Indicators, such as site, sheltered or exposed position, and location of the stone surfaces, were taken into consideration for data interpretation. A relationship between surface conservation state and the proposed environmental indicators has been evaluated. Deposits and crusts were found only in the courtyard façade and in sheltered points, reflecting SO2 reduction; large, eroded areas were found on exposed surfaces related to rain runoff and possibly related to the locally high NOx levels.
      Citation: Atmosphere
      PubDate: 2022-06-29
      DOI: 10.3390/atmos13071036
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1037: Mapping Heat Wave Hazard in Urban Areas:
           A Novel Multi-Criteria Decision Making Approach

    • Authors: Javad Shafiei Shiva, David G. Chandler, Kenneth E. Kunkel
      First page: 1037
      Abstract: Global population is experiencing more frequent, longer, and more severe heat waves due to global warming and urbanization. Episodic heat waves increase mortality and morbidity rates and demands for water and energy. Urban managers typically assess heat wave risk based on heat wave hazard, population exposure, and vulnerability, with a general assumption of spatial uniformity of heat wave hazard. We present a novel analysis that demonstrates an approach to determine the spatial distribution of a set of heat wave properties and hazard. The analysis is based on the Livneh dataset at a 1/16-degree resolution from 1950 to 2009 in Maricopa County, Arizona, USA. We then focused on neighborhoods with the most frequent, severe, earlier, and extended periods of heat wave occurrences. On average, the first heat wave occurs 40 days earlier in the eastern part of the county; the northeast part of this region experiences 12 days further extreme hot days and 30 days longer heat wave season than other regions of the area. Then, we applied a multi-criteria decision-making (MCDM) tool (TOPSIS) to evaluate the total hazard posed by heat wave components. We found that the northern and central parts of the metropolitan area are subject to the greatest heat wave hazard and that individual heat wave hazard components did not necessarily indicate heat hazard. This approach is intended to support local government planning for heat wave adaptation and mitigation strategies, where cooling centers, heat emergency water distribution networks, and electrical energy delivery can be targeted based on current and projected local heat wave characteristics.
      Citation: Atmosphere
      PubDate: 2022-06-29
      DOI: 10.3390/atmos13071037
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1038: Self-Organized Criticality of
           Precipitation in the Rainy Season in East China

    • Authors: Zhonghua Qian, Yuxin Xiao, Luyao Wang, Qianjin Zhou
      First page: 1038
      Abstract: Based on daily precipitation data from 1960 to 2017 in the rainy season in east China, to a given percentile threshold of one observation station, the time that precipitation spends below threshold is defined as quiet time τ. The probability density functions τ in different thresholds follow power-law distributions with exponent β of approximately 1.2 in the day, pentad and ten-day period time scales, respectively. The probability density functions τ in different regions follow the same rules, too. Compared with sandpile model, Γ function describing the collapse behavior can effectively scale the quiet time distribution of precipitation events. These results confirm the assumption that for observation station data and low-resolution precipitation data, even in China, affected by complex weather and climate systems, precipitation is still a real world example of self-organized criticality in synoptic. Moreover, exponent βof the probability density function τ, mean quiet time τ¯q and hazard function Hq of quiet times can give sensitive regions of precipitation events in China. Usual intensity precipitation events (UPEs) easily occur and cluster mainly in the middle Yangtze River basin, east of the Sichuan Province and north of the Gansu Province. Extreme intensity precipitation events (EPEs) more easily occur in northern China in the rainy season. UPEs in the Hubei Province and the Hunan Province are more likely to occur in the future. EPEs in the eastern Sichuan Province, the Guizhou Province, the Guangxi Province and Northeast China are more likely to occur.
      Citation: Atmosphere
      PubDate: 2022-06-29
      DOI: 10.3390/atmos13071038
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1039: Ionospheric TEC Prediction Base on
           Attentional BiGRU

    • Authors: Dongxing Lei, Haijun Liu, Huijun Le, Jianping Huang, Jing Yuan, Liangchao Li, Yali Wang
      First page: 1039
      Abstract: Many studies indicated that ionospheric total electron content (TEC) prediction is vital for terrestrial and space-based radio-communication systems. In previous TEC prediction schemes based on RNN, they learn TEC representations from previous time steps, and each time-step made an equal contribution to a prediction. To overcome these drawbacks, we propose two improvements in our study: (1) To predict TEC with both past and future time-step, Bidirectional Gate Recurrent Unit (BiGRU) was presented to improve the capabilities. (2) To highlight critical time-step information, attention mechanism was used to provide weights to each time-step. The proposed attentional BiGRU TEC predicting method was evaluated on the publicly available data set from the Centre for Orbit Determination in Europe. We chose three geographical locations in low latitude, middle latitude, and high latitude to verify the performance of our proposed model. Comparative experiments were conducted using Deep Neural Network (DNN), Artificial Neural Network (ANN), Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), Bidirectional Long Short-Term Term memory (BiLSTM), and Gated Recurrent Unit (GRU). Experimental results show that the proposed Attentional BiGRU model is superior to the other models in the selected nine regions. In addition, the paper discussed the effects of latitudes and solar activities on the performance of Attentional BiGRU model. Experimental results show that the higher the latitude, the higher the prediction accuracy of our proposed model. Experimental results also show that in the middle latitude, the prediction accuracy of the model is less affected by solar activity, and in other areas, the model is greatly affected by solar activity.
      Citation: Atmosphere
      PubDate: 2022-06-29
      DOI: 10.3390/atmos13071039
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1040: Field Measurement and Evaluation of
           Effective Ventilation and Particulate Matter Discharge Efficiency of Air
           Shafts in Subway Tunnels

    • Authors: Haibo Qu, Jianbin Zang, Yan Wu
      First page: 1040
      Abstract: The ventilation performance of air shafts is important to the air quality of subway tunnels, but there is no unified evaluation index of ventilation performance. In this paper, the air shafts at different locations in subway tunnels were taken as research objects, and the wind speed as well as the particulate matter concentration of each air shaft was tested. The effective ventilation volume and PM2.5 discharge efficiency of the air shafts were defined to evaluate the ventilation performance. It was found that on average, during the subway train service, the station air shaft on the train-arriving side can discharge 2050 m3 of dirty air in the tunnels and inhale 218 m3 of fresh air from the outside environment, while the station air shaft on the train-leaving side can absorb 2430 m3 of fresh air but can hardly effectively discharge dirty air; meanwhile, the middle air shaft can not only effectively exhaust 1519 m3 of dirty air but can also absorb 7572 m3 of fresh air. In addition, the middle air shaft has better ventilation performance if its inner opening is set on the top rather than on the side of the tunnel. The PM2.5 discharge efficiency of the station air shaft on the train-arriving side is 52.0~62.8%, higher than that of the middle air shaft of which the value is 26.8~40.7%. This research can provide guidance for ventilation performance evaluation of subway air shafts and provide a reference for subway tunnel air shaft location design.
      Citation: Atmosphere
      PubDate: 2022-06-29
      DOI: 10.3390/atmos13071040
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1041: Influence of Air Pollution Factors on
           Corrosion of Metal Equipment in Transmission and Transformation Power
           Stations

    • Authors: Xiufang Chen, Zhenyu Zhang, Hanping Zhang, Hanbing Yan, Fengchun Liu, Shan Tu
      First page: 1041
      Abstract: In this paper, the atmospheric environmental corrosion grade of substations in 11 prefecture level cities in Shanxi Province is evaluated through a metal hanging sheet experiment. Combined with the main environmental factors, such as temperature, relative humidity, and the concentration of main pollution factors, such as SO2, Cl−, dust, etc., the influence of various factors on the corrosion of transmission and transformation equipment is analyzed, and the corresponding anti-corrosion measures are put forward.
      Citation: Atmosphere
      PubDate: 2022-06-29
      DOI: 10.3390/atmos13071041
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1042: An Application of Artificial Neural
           Network to Evaluate the Influence of Weather Conditions on the Variation
           of PM2.5-Bound Carbonaceous Compositions and Water-Soluble Ionic Species

    • Authors: Siwatt Pongpiachan, Qiyuan Wang, Ronbanchob Apiratikul, Danai Tipmanee, Yu Li, Li Xing, Guohui Li, Yongming Han, Junji Cao, Ronald C. Macatangay, Saran Poshyachinda, Aekkapol Aekakkararungroj, Muhammad Zaffar Hashmi
      First page: 1042
      Abstract: Previous studies have determined biomass burning as a major source of air pollutants in the ambient air in Thailand. To analyse the impacts of meteorological parameters on the variation of carbonaceous aerosols and water-soluble ionic species (WSIS), numerous statistical models, including a source apportionment analysis with the assistance of principal component analysis (PCA), hierarchical cluster analysis (HCA), and artificial neural networks (ANNs), were employed in this study. A total of 191 sets of PM2.5 samples were collected from the three monitoring stations in Chiang-Mai, Bangkok, and Phuket from July 2020 to June 2021. Hotspot numbers and other meteorological parameters were obtained using NOAA-20 weather satellites coupled with the Global Land Data Assimilation System. Although PCA revealed that crop residue burning and wildfires are the two main sources of PM2.5, ANNs highlighted the importance of wet deposition as the main depletion mechanism of particulate WSIS and carbonaceous aerosols. Additionally, Mg2+ and Ca2+ were deeply connected with albedo, plausibly owing to their strong hygroscopicity as the CCNs responsible for cloud formation.
      Citation: Atmosphere
      PubDate: 2022-06-30
      DOI: 10.3390/atmos13071042
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1043: Improving the Performance of Pipeline
           Leak Detection Algorithms for the Mobile Monitoring of Methane Leaks

    • Authors: Tian Xia, Julia Raneses, Stuart Batterman
      First page: 1043
      Abstract: Methane (CH4) is the major component of natural gas, a potent greenhouse gas, and a precursor for the formation of tropospheric ozone. Sizable CH4 releases can occur during gas extraction, distribution, and use, thus, the detection and the control of leaks can help to reduce emissions. This study develops, refines, and tests algorithms for detecting CH4 peaks and estimating the background levels of CH4 using mobile monitoring, an approach that has been used to determine the location and the magnitude of pipeline leaks in a number of cities. The algorithm uses four passes of the data to provide initial and refined estimates of baseline levels, peak excursions above baseline, peak locations, peak start and stop times, and indicators of potential issues, such as a baseline shift. Peaks that are adjacent in time or in space are merged using explicit criteria. The algorithm is refined and tested using 1-s near-ground CH4 measurements collected on 20 days while driving about 1100 km on surface streets in Detroit, Michigan by the Michigan Pollution Assessment Laboratory (MPAL). Sensitivity and other analyses are used to evaluate the effects of each parameter and to recommend a parameter set for general applications. The new algorithm improves the baseline estimates, increases sensitivity, and more consistently merges nearby peaks. Comparisons of two data subsets show that results are repeatable and reliable. In the field study application, we detected 534 distinct CH4 peaks, equivalent to ~0.5 peaks per km traveled; larger peaks detected at nine locations on multiple occasions suggested sizable pipeline leaks or possibly other CH4 sources.
      Citation: Atmosphere
      PubDate: 2022-06-29
      DOI: 10.3390/atmos13071043
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1044: A Novel Missing Data Imputation Approach
           for Time Series Air Quality Data Based on Logistic Regression

    • Authors: Mei Chen, Hongyu Zhu, Yongxu Chen, Youshuai Wang
      First page: 1044
      Abstract: Missing values in air quality datasets bring trouble to exploration and decision making about the environment. Few imputation methods aim at time series air quality data so that they fail to handle the timeliness of the data. Moreover, most imputation methods prefer low-missing-rate datasets to relatively high-missing-rate datasets. This paper proposes a novel missing data imputation method, called FTLRI, for time series air quality data based on the traditional logistic regression and a presented “first Five & last Three” model, which can explain relationships between disparate attributes and extract data that are extremely relevant, both in terms of time and attributes, to the missing data, respectively. To investigate the performance of FTLRI, it is benchmarked with five classical baselines and a new dynamic imputation method using a neural network with average hourly concentration data of pollutants from three disparate stations in Lanzhou in 2019 under different missing rates. The results show that FTLRI has a significant advantage over the compared imputation approaches, both in the particular short-term and long-term time series air quality data. Furthermore, FTLRI has good performance on datasets with a relatively high missing rate, since it only selects the data extremely related to the missing values instead of relying on all the other data like other methods.
      Citation: Atmosphere
      PubDate: 2022-06-29
      DOI: 10.3390/atmos13071044
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1045: A Rainfall Forecast Model Based on GNSS
           Tropospheric Parameters and BP-NN Algorithm

    • Authors: Huanian Fu, Wenfeng Zhang, Chunjin Li, Zaihuang Hu
      First page: 1045
      Abstract: The occurrence of rainfall is the result of a combination of various meteorological factors. Traditional rainfall early warning models solely use Global Navigation Satellite System (GNSS)-derived Zenith Total Delay (ZTD) or Precipitable Water Vapor (PWV) to forecast rainfall, resulting in a low true detected rate. While non-linear rainfall early warning models based on the Back-Propagation Neural Network (BP-NN) algorithm consider the influences of various meteorological factors, the forecasts often exhibit a high false rate. To further improve the prediction of rainfall, a short-term rainfall early warning model based on the GNSS and BP-NN algorithms is proposed in this study. The method uses the traditional rainfall forecasting model and utilizes the BP-NN algorithm to combine various meteorological factors for rainfall early warning. The results of GNSS and BP-NN together improve the precision of rainfall early warning. Observation data from eight GNSS stations, the fifth-generation reanalysis of European Centre for Medium-Range Weather Forecast (ECMWF ERA5), and temperature, pressure, and rainfall data from corresponding meteorological stations in Ningbo, China were utilized to verify the rainfall early warning model proposed in this study. The results show that the proposed model can complement the advantages of the traditional linear and non-linear rainfall early warning methods. The model can maintain a high True Detected Rate (TDR) of rainfall early warning while simultaneously reducing the False Forecasted Rate (FFR). The average TDR of the eight GNSS stations is 100% and the FFR is 20.75%, which are both better than those of existing traditional linear and non-linear rainfall early warning models.
      Citation: Atmosphere
      PubDate: 2022-06-29
      DOI: 10.3390/atmos13071045
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1046: Exploring Non-Linear Dependencies in
           Atmospheric Data with Mutual Information

    • Authors: Petri Laarne, Emil Amnell, Martha Arbayani Zaidan, Santtu Mikkonen, Tuomo Nieminen
      First page: 1046
      Abstract: Relations between atmospheric variables are often non-linear, which complicates research efforts to explore and understand multivariable datasets. We describe a mutual information approach to screen for the most significant associations in this setting. This method robustly detects linear and non-linear dependencies after minor data quality checking. Confounding factors and seasonal cycles can be taken into account without predefined models. We present two case studies of this method. The first one illustrates deseasonalization of a simple time series, with results identical to the classical method. The second one explores associations in a larger dataset of many variables, some of them lognormal (trace gas concentrations) or circular (wind direction). The examples use our Python package ‘ennemi’.
      Citation: Atmosphere
      PubDate: 2022-06-29
      DOI: 10.3390/atmos13071046
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1047: Diagnostic Analysis of Multimodel
           Rainstorm Forecast for Cases Based on MODE Method

    • Authors: Hongfang Zhang, Liujie Pan
      First page: 1047
      Abstract: It is very important to analyze the performance of the model rainstorm forecast for understanding the intensity and position deviation of the model precipitation and improving the forecast ability. This paper uses classical scoring and the MODE (Method for Object-Based Diagnostic Evaluation) method to evaluate the forecast performance of different products. The forecast and observation data used in the article mainly include CMA (China Meteorological Administration) multi-source merged precipitation analysis, the precipitation forecast of ECMWF (European Centre for Medium-Range Weather Forecasts), CMA-Meso (Mesoscale model forecast of CMA) and SCMOC (National Meteorological Center grid precipitation forecast guidance product) data. At the same time, the possible correction method of heavy rainfall area is explored by using the high and low-level circulation configuration of the ECMWF model. The main conclusions are as follows: ① MODE spatial verification shows that the number, intensity, area and location of ECMWF rainstorm precipitation objects match the observed precipitation best, which is obviously better than SCMOC and CMA-Meso precipitation forecasts. There are significantly fewer SCMOC rainstorm precipitation objects, and the area of each single precipitation object is significantly larger, which often fails to report the small area objects of convective precipitation. ② The reason for the high TS score of SCMOC is that it reduces the number of small area rainstorm objects and avoids the “double punishment” phenomenon caused by position forecast error, which leads to the failure of SCMOC in local rainstorm forecasts. ③ Analyzing the relationship between the circulation situation of the ECMWF model and the location of rainstorm forecasts by the model, it is found that the location of the rainstorm area is consistent with the upper circulation system, especially with the strong rising area of the vertical velocity of 700 hPa and the high value area of the specific humidity of 850 hPa. When the rainstorm area coincides with the upper air system but is not consistent with the ground convergence area and the high value area of velocity potential, the rainstorm location often has a large deviation. The location of the surface convergence area can be used as a reference to improve the performance of the rainstorm forecast.
      Citation: Atmosphere
      PubDate: 2022-06-30
      DOI: 10.3390/atmos13071047
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1048: Optimization Study of Sampling Device for
           Semi-Volatile Oil Mist in the Industrial Workshop

    • Authors: Yukun Wang, Zhengwei Long, Hongsheng Zhang, Xiong Shen, Tao Yu
      First page: 1048
      Abstract: A large number of metalworking fluids in industrial manufacturing processes generate high-concentrations of oil mist pollution, which is a typical semi-volatile aerosol and is generally composed of liquid particles and volatile gas components. Long-term exposure to oil mist pollution brings a series of occupational diseases to workers. For the semi-volatile aerosol, the traditional filter sampling method will lead to particle volatilization, which underestimates the concentration of particles and overestimates the concentration of gas. Therefore, this study combined the advantages of the electrostatic method and the Tenax tube adsorption method, to develop a more accurate measurement technology. First, a dichotomous sampler that could efficiently separate the gas and liquid phases of aerosols was optimized through a numerical model, which was validated by literature results. Next, a test table for oil mist sampling was built with a sampler which was fabricated by 3D printing, and the performance of the sampler was evaluated. The results show that the sampling technique can separate the gas and particulate phases of the oil mist efficiently and accurately. Compared with the traditional single sampling methods, the new sampler can better determine the true concentration of oil mist.
      Citation: Atmosphere
      PubDate: 2022-06-30
      DOI: 10.3390/atmos13071048
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1049: Reconstruction of Daily Courses of
           SO42−, NO3−, NH4+ Concentrations in Precipitation from
           Cumulative Samples

    • Authors: Iva Hůnová, Marek Brabec, Marek Malý, Hana Škáchová
      First page: 1049
      Abstract: It is important to study precipitation chemistry to comprehend both atmospheric and environmental processes. The aim of this study was the reconstruction of daily concentration patterns of major ions in precipitation from samples exposed for longer and differing time periods. We explored sulphates (SO42−), nitrates (NO3−) and ammonium (NH4+) ions measured in precipitation within a nation-wide atmospheric deposition monitoring network in the Czech Republic during 1980–2020. We visualised the long-term trends at selected individual years for four stations, Praha 4-Libuš (LIB), Svratouch (SVR), Rudolice v Horách (RUD) and Souš (SOU), differing in geographical location and reflecting different environments. We found anticipated time trends reflecting the emission patterns of the precursors, i.e., sharp decreases in SO42−, milder decreases in NO3- and steady states in NH4+ concentrations in precipitation. Statistically significant decreasing time trends in SO42− and NO3− concentrations in precipitation between 1990 and 2015 were revealed for the LIB and SVR sites. Spring maxima in April were found for all major ions at the LIB site and for NO3- for the SVR site, for both past and current samples, whereas no distinct seasonal behaviour was recorded for NH4+ at the RUD and SO42− at the SVR sites. By applying Bayesian modelling and the Integrated Nested Laplace Approximation approach, we were able to reconstruct the daily patterns of SO42−, NO3− and NH4+ concentrations in precipitation, which might be further utilised for a wide range of tasks, including comparison of magnitudes and shapes between stations, grouping the decomposed daily data into the ecologically motivated time periods, as well as for logical checks of sampling and measurement reliability.
      Citation: Atmosphere
      PubDate: 2022-06-30
      DOI: 10.3390/atmos13071049
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1050: The Impact of High-Resolution SRTM
           Topography and Corine Land Cover on Lightning Calculations in WRF

    • Authors: Alexander de Meij, Narendra Ojha, Narendra Singh, Jaydeep Singh, Dieter Roel Poelman, Andrea Pozzer
      First page: 1050
      Abstract: The goal of this study is to investigate the impact of high-resolution SRTM and Corine Land Cover on the number of cloud–ground lightning flashes and their spatial distribution simulated by a numerical weather-prediction model. Two lightning episodes were selected: (1) over a non-complex terrain and (2) over a complex terrain, the Alps. Significant discrepancies were found in the geographical distribution of the land-cover classes and also in the topography between Corine Land Cover and 30-arc seconds USGS. In general, the timing and the spatial distribution of Cloud-to-Ground (CG) lightning by the model were well-represented when compared to the observations. In general, more CG flashes were calculated by the simulation with USGS Land Cover and topography than the simulation with Corine Land Cover and SRTM topography. It appears that the differences in sensible and latent heat fluxes between the simulations were caused by the differences in land-cover classes. Moreover, differences in the vertical wind speeds, specific humidity, temperature and the convective available potential energy were found when compared to observations, resulting in the differences in cloud–ground lightning flashes between the simulation with the SRTM topography and Corine Land Cover and the simulation with the USGS Land Cover and topography. Using the high-resolution land cover and topography data may help to reduce uncertainties in CG lightning calculations by the model.
      Citation: Atmosphere
      PubDate: 2022-06-30
      DOI: 10.3390/atmos13071050
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1051: The 1-31-Day Predictions of the South
           China Sea Summer Monsoon in the CAMS-CSM Climate Forecast System

    • Authors: Xin Wang, Yi Fan, Lijuan Wang, Yan Zhu
      First page: 1051
      Abstract: The South China Sea summer monsoon (SCSSM) is crucial for the East Asian monsoon system, which has been detected from plenty of aspects, while its prediction has been relatively less investigated on the subseasonal timescale. The 1-31-day predictions of SCSSM, including fundamental dynamic and thermodynamic characteristics, indices, onset date and associated circulations, are examined and diagnosed for different climate systems, i.e., T106 and T106 × T255 (with a nudging process added) in the Chinese Academy of Meteorological Sciences climate system model (CAMS-CSM). The results indicate the general decreasing prediction skills of the model with the growing lead times. For lead times of 1–10 days, zonal winds at the lower (850 hPa) and higher (200 hPa) levels can be reasonably predicted, as well as the pseudo-equivalent potential temperatures at 850 hPa. Meanwhile, the prediction skill for the higher level generally shows a better performance than that for the lower level. The prediction capability is relatively weak during the circulation adjustment period before the monsoon onset, while a significant enhancement occurs after that. During the analyzed period of 2011–2020, the prediction of SCSSM onset date is mainly skillful in most years, while the year of 2015 shows a prediction result with at least six pentads earlier than the observation, which is subsequently taken as a failure case for further investigation. At the lower level, the model could not effectively predict the weakening and eastward withdrawal of the Western Pacific subtropical high and the shift in wind field during the SCSSM onset. As for the upper level, the rapid northward movement of the South Asia high and its establishment in the Indochina Peninsula are neither well captured. In addition, the models of T106 and T106 × T255 do not show significant differences in most cases, but the latter tends to be more skillful on the continent.
      Citation: Atmosphere
      PubDate: 2022-06-30
      DOI: 10.3390/atmos13071051
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1052: Winter Potato Water Footprint Response to
           Climate Change in Egypt

    • Authors: Amal Mohamed Abdel-Hameed, Mohamed EL-Sayed Abuarab, Nadhir Al-Ansari, Hazem Sayed Mehawed, Mohamed Abdelwahab Kassem, Hongming He, Yeboah Gyasi-Agyei, Ali Mokhtar
      First page: 1052
      Abstract: The limited amount of freshwater is the most important challenge facing Egypt due to increasing population and climate change. The objective of this study was to investigate how climatic change affects the winter potato water footprint at the Nile Delta covering 10 governorates from 1990 to 2016. Winter potato evapotranspiration (ETC) was calculated based on daily climate variables of minimum temperature, maximum temperature, wind speed and relative humidity during the growing season (October–February). The Mann–Kendall test was applied to determine the trend of climatic variables, crop evapotranspiration and water footprint. The results showed that the highest precipitation values were registered in the northwest governorates (Alexandria followed by Kafr El-Sheikh). The potato water footprint decreased from 170 m3 ton−1 in 1990 to 120 m3 ton−1 in 2016. The blue-water footprint contributed more than 75% of the total; the remainder came from the green-water footprint. The findings from this research can help government and policy makers better understand the impact of climate change on potato crop yield and to enhance sustainable water management in Egypt’s major crop-producing regions to alleviate water scarcity.
      Citation: Atmosphere
      PubDate: 2022-06-30
      DOI: 10.3390/atmos13071052
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1053: Evaluation and Application of MSWEP in
           Drought Monitoring in Central Asia

    • Authors: Min Li, Xiaoyu Lv, Li Zhu, Friday Uchenna Ochege, Hao Guo
      First page: 1053
      Abstract: Thanks to the large scope, high spatial resolution, and increasing data records, satellite-based precipitation products are playing an increasingly important role in drought monitoring. First, based on the data from ground sites, the long-term Multi-Source Weighted-Ensemble Precipitation (MSWEP) precipitation product was evaluated in respect to drought monitoring. Then, based on the MSWEP product, the drought trends and the spatiotemporal characteristics of the drought events in four major basins (Amu Darya Basin, Syr Darya Basin, Chu-Talas River Basin, and Ili River Basin) in Central Asia, which have relatively dense gauge sites, were studied. The Standardized Precipitation Index (SPI) and the run theory were used to identify drought events and describe their characteristics. The results showed that MSWEP can effectively capture drought events and their basic characteristics. In the past 40 years, the study area experienced 27 drought events, among which the severest one (DS = 15.66) occurred from June 2007 to September 2008. The drought event that occurred from June 1984 to October 1984 had a drought peak value of 3.39, with the largest drought area (99.2%). Since 1881, there appeared a drying trend and a wetting trend in the Amu Darya River basin and the Ili River basin, respectively. No obvious wetting or drying trend was found in both the Chu-Talas River basin and the Syr Darya basin. Since 2016, the drought area has been on the increase.
      Citation: Atmosphere
      PubDate: 2022-07-01
      DOI: 10.3390/atmos13071053
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1054: Solar Ultraviolet Radiation Temporal
           Variability Analysis from 2-Year of Continuous Observation in an Amazonian
           City of Brazil

    • Authors: Gabriela Reis, Samuel Souza, Helvécio Neto, Rardiles Branches, Rodrigo Silva, Lucas Peres, Damaris Pinheiro, Kevin Lamy, Hassan Bencherif, Thierry Portafaix
      First page: 1054
      Abstract: Solar ultraviolet radiation (UVR) is a highly energetic component of the solar spectrum that needs to be monitored because of the effects on human health and on the ecosystems. In Brazil, few cities monitor UVR, especially in the Amazon region which is particularly poor in observation. This work is the first to address the short-term (2-year) time variability of UVR in Santarém (2°25′ S, 54°44′ W, 51 m) using ground-based measurements. The irradiance in the wavelength range of 250–400 nm was investigated on different time scales. Furthermore, to understand how the UVR varies without the influence of clouds, the hours corresponding to the clear sky condition were analyzed as well as the hours in all sky conditions. Regarding the averages, there is a slight variation over the year. In all sky and clear sky conditions, the dry season had a higher average than the rainy season, despite the slight difference. Also, both in all-sky and clear-sky conditions the maximums occurred around local solar noon, and reached a maximum of 87 in the dry season under the clear sky condition. Further understanding of the radiative effects of the clouds in UVR time variability is considered essential for future research. This study can serve as a reference for UVR levels in this region where no other ground-based UVR measurements are made.
      Citation: Atmosphere
      PubDate: 2022-07-02
      DOI: 10.3390/atmos13071054
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1055: An Intelligent Time Series Model Based on
           Hybrid Methodology for Forecasting Concentrations of Significant Air
           Pollutants

    • Authors: Ching-Hsue Cheng, Ming-Chi Tsai
      First page: 1055
      Abstract: Rapid industrialization and urban development are the main causes of air pollution, leading to daily air quality and health problems. To find significant pollutants and forecast their concentrations, in this study, we used a hybrid methodology, including integrated variable selection, autoregressive distributed lag, and deleted multiple collinear variables to reduce variables, and then applied six intelligent time series models to forecast the concentrations of the top three pollution sources. We collected two air quality datasets from traffic and industrial monitoring stations and weather data to analyze and compare their results. The results show that a random forest based on selected key variables has better classification metrics (accuracy, AUC, recall, precision, and F1). After deleting the collinearity of the independent variables and adding the lag periods using the autoregressive distributed lag model, the intelligent time-series support vector regression was found to have better forecasting performance (RMSE and MAE). Finally, the research results could be used as a reference by all relevant stakeholders and help respond to poor air quality.
      Citation: Atmosphere
      PubDate: 2022-07-02
      DOI: 10.3390/atmos13071055
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1056: Evaluation of Sea Ice Simulation of
           CAS-ESM 2.0 in Historical Experiment

    • Authors: Xin Gao, Peng Fan, Jiangbo Jin, Juanxiong He, Mirong Song, He Zhang, Kece Fei, Minghua Zhang, Qingcun Zeng
      First page: 1056
      Abstract: A sea ice model is an important component of an Earth system model, which is an essential tool for the study of sea ice, including its internal processes, interactions with other components, and projected future changes. This paper evaluates a simulation of sea ice by the Chinese Academy of Sciences Earth System Model version 2 (CAS-ESM 2.0), focusing on a historical simulation in the Coupled Model Intercomparison Project Phase 6 (CMIP6). Compared with the observations, CAS-ESM 2.0 reproduces reasonable seasonal cycle features and the climatological spatial distribution of Arctic and Antarctic sea ice, including sea ice extent (SIE), sea ice concentration, and sea ice thickness and motion. However, the SIE in CAS-ESM 2.0 is too large in winter and too low in summer in both hemispheres, indicating higher seasonal variations of the model relative to observations. Further sea ice mass budget diagnostics show that basal growth contributes most to ice increase in both hemispheres, basal melt and top melt make a comparable contribution to Arctic ice decrease, and basal melt plays a dominant role in Antarctic ice loss. This, combined with surface air temperature (SAT) and sea surface temperature (SST) biases, suggests that the excess of sea ice simulated in wintertime in both hemispheres and the lower SIE simulated in the Antarctic summer are mainly attributable to the bias in SST, whereas the lower SIE simulated in the Arctic summer is probably due to the combined effects of both the SST and SAT biases.
      Citation: Atmosphere
      PubDate: 2022-07-02
      DOI: 10.3390/atmos13071056
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1057: Comparison between Multi-Physics and
           Stochastic Approaches for the 20th July 2021 Henan Heavy Rainfall Case

    • Authors: Duanzhou Shao, Yu Zhang, Jianjun Xu, Hanbin Zhang, Siqi Chen, Shifei Tu
      First page: 1057
      Abstract: In this study, three model perturbation schemes, the stochastically perturbed parameter scheme (SPP), stochastically perturbed physics tendency (SPPT), and multi-physics process parameterization (MP), were used to represent the model errors in the regional ensemble prediction systems (REPS). To study the effects of different model perturbation schemes on heavy rainfall forecasting, three sensitive experiments using three different combinations (EXP1: MP, EXP2: SPPT + SPP, and EXP3: MP + SPPT + SPP) of the model perturbation schemes were set up based on the Weather Research and Forecasting (WRF)-V4.2 model for a heavy rainfall case that occurred in Henan, China during 20–22 July 2021. The results show that the model perturbation schemes can provide forecast uncertainties for this heavy rainfall case. The stochastic physical perturbation method could improve the heavy rainfall forecast skill by approximately 5%, and EXP3 had better performance than EXP1 or EXP2. The spread-to-root mean square error ratios (spread/RMSE) of EXP3 were closer to 1 compared with those of the EXP1 and EXP2; particularly for the meridional wind above 10 m, the spread/RMSE was 0.94 for EXP3 and approximately 0.85 for EXP1 and EXP2. EXP3 exhibited better performance in Brier score verification. EXP3 had a 5% lower Brier score than EXP1 and EXP2, when the rainfall threshold was 25 mm. The growth of the initial ensemble variances of different model perturbation schemes were explored, and the results show that the perturbation energy of EXP3 developed faster, with a magnitude of 27.22 J/kg, whereas those of EXP1 and EXP2 were only 19.18 J/kg and 20.81 J/kg, respectively. The weak initial perturbation associated with the wind shear north of the heavy rainfall location can be easily developed by EXP3.
      Citation: Atmosphere
      PubDate: 2022-07-03
      DOI: 10.3390/atmos13071057
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1058: Baroclinic Instability of a
           Time-Dependent Zonal Shear Flow

    • Authors: Chengzhen Guo, Jian Song
      First page: 1058
      Abstract: In the real atmosphere, the development of large-scale motion is often related to the baroclinic properties of the atmosphere. So, it is necessary to discuss the stability condition of baroclinic flow. It is advantageous to use a layered model to discuss baroclinic instability, not only to apply the potential vortex equation directly, but also to deal with shear of basic flow. The stability and oscillatory shear ability of Rossby waves are studied based on the two-layer Phillips model in the β plane; then, we summarize the baroclinic instability of time-dependent zonal shear flows. The multiscale method is used to eliminate some terms of natural frequency oscillations of nonlinear operators in the third-order expansion, thus generating an equation about the amplitude of the lowest-order Rossby wave in the long-time variable. The large amplitude perturbation begins to decrease, which produces the desired behavior. After the amplitude decreases for some time, the amplitude of Rossby waves can still be found to oscillate periodically with the time variable.
      Citation: Atmosphere
      PubDate: 2022-07-03
      DOI: 10.3390/atmos13071058
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 1059: Tropical Air Chemistry in Lagos, Nigeria

    • Authors: Adebola Odu-Onikosi, Pierre Herckes, Matthew Fraser, Philip Hopke, John Ondov, Paul A. Solomon, Olalekan Popoola, George M. Hidy
      First page: 1059
      Abstract: The Nigerian city of Lagos experiences severe air pollution as a result of emissions and subsequent atmospheric photochemistry and aerosol chemistry. A year-long study, between August 2020 and July 2021, included measurements of gas-phase and aerosol processes, with surface meteorology at six urban sites. The sites were selected to represent near seacoast conditions, urban sites, and inland locations near agricultural and grassland ecosystems. The observations included continuous concentrations for CO, SO2, NOx, O3, PM2.5, and PM10. Samples were collected and analyzed for speciated volatile organic compounds (VOCs) and particulate chemical composition including inorganic and organic chemical species. The average diel variations in concentrations indicated well-known local photochemistry resulting from the presence of combustion sources, including motor vehicles, petroleum production and use, and open burning. The annual diel characteristics were emission-dependent and were modulated by meteorological variability, including the sea breeze and the seasonal changes associated with monsoons and Harmattan winds. Gases and particulate matter varied daily, consistent with the onset of source activities during the day. Fine particles less than 2.5 μm in diameter (PM2.5) included both primary particles from emission sources and secondary particles produced in the atmosphere by photochemical reactions. Importantly, particle sources included a large component of dust and carbonaceous material. For the latter, there was evidence that particle concentrations were dominated by primary sources, with little secondary material formed in the atmosphere. From complementary measurements, there were occasions when regional chemical processes affected the local conditions, including transportation, industry, commercial activity, and open waste burning.
      Citation: Atmosphere
      PubDate: 2022-07-03
      DOI: 10.3390/atmos13071059
      Issue No: Vol. 13, No. 7 (2022)
       
  • Atmosphere, Vol. 13, Pages 960: Prediction of Air Pollutant Concentrations
           via RANDOM Forest Regressor Coupled with Uncertainty Analysis—A Case
           Study in Ningxia

    • Authors: Weifu Ding, Xueping Qie
      First page: 960
      Abstract: Air pollution has not received much attention until recent years when people started to understand its dreadful impacts on human health. According to air pollution and the meteorological monitoring data from 1 January 2016 to 31 December 2017 in Ningxia, we analyzed the impact of ground surface temperature, air temperature, relative humidity and the power of wind on air pollutant concentrations. Meanwhile, we analyze the relationships between air pollutant concentrations and meteorological variables by using the mathematical model of decision tree regressor (DTR), feedforward artificial neural network with back-propagation algorithm (FFANN-BP) and random forest regressor (RFR) according to air-monitoring station data. For all pollutants, the RFR increases R2 of FFANN-BP and DTR by up to 0.53 and 0.42 respectively, reduces root mean square error (RMSE) by up to 68.7 and 41.2, and MAE by up to 25.2 and 17. The empirical results show that the proposed RFR displays the best forecasting performance and could provide local authorities with reliable and precise predictions of air pollutant concentrations. The RFR effectively establishes the relationships between the influential factors and air pollutant concentrations, and well suppresses the overfitting problem and improves the accuracy of prediction. Besides, the limitation of machine learning for single site prediction is also overcame.
      Citation: Atmosphere
      PubDate: 2022-06-14
      DOI: 10.3390/atmos13060960
      Issue No: Vol. 13, No. 6 (2022)
       
  • Atmosphere, Vol. 13, Pages 961: Restricted Anthropogenic Activities and
           Improved Urban Air Quality in China: Evidence from Real-Time and Remotely
           Sensed Datasets Using Air Quality Zonal Modeling

    • Authors: Saidur Rahaman, Selim Jahangir, Ruishan Chen, Pankaj Kumar
      First page: 961
      Abstract: The study aims to examine the major atmospheric air pollutants such as NO2, CO, O3, PM2.5, PM10, and SO2 to assess the overall air quality using air quality zonal modeling of 15 major cities of China before and after the COVID-19 pandemic period. The spatio-temporal changes in NO2 and other atmospheric pollutants exhibited enormous reduction due to the imposition of a nationwide lockdown. The present study used a 10-day as well as 60-day tropospheric column time-average map of NO2 with spatial resolution 0.25 × 0.25° obtained from the Global Modeling and Assimilation Office, NASA. The air quality zonal model was employed to assess the total NO2 load and its change during the pandemic period for each specific region. Ground surface monitoring data for CO, NO2, O3, PM10, PM2.5, and SO2 including Air Quality Index (AQI) were collected from the Ministry of Environmental Protection of China (MEPC). The results from both datasets demonstrated that NO2 has drastically dropped in all the major cities across China. The concentration of CO, PM10, PM2.5, and SO2 demonstrated a decreasing trend whereas the concentration of O3 increased substantially in all cities after the lockdown effect as observed from real-time monitoring data. Because of the complete shutdown of all industrial activities and vehicular movements, the atmosphere experienced a lower concentration of major pollutants that improves the overall air quality. The regulation of anthropogenic activities due to the COVID-19 pandemic has not only contained the spread of the virus but also facilitated the improvement of the overall air quality. Guangzhou (43%), Harbin (42%), Jinan (33%), and Chengdu (32%) have experienced maximum air quality improving rates, whereas Anshan (7%), Lanzhou (17%), and Xian (25%) exhibited less improved AQI among 15 cities of China during the study period. The government needs to establish an environmental policy framework involving central, provincial, and local governments with stringent laws for environmental protection.
      Citation: Atmosphere
      PubDate: 2022-06-14
      DOI: 10.3390/atmos13060961
      Issue No: Vol. 13, No. 6 (2022)
       
  • Atmosphere, Vol. 13, Pages 962: Spatial-Temporal Variation Characteristics
           and Influencing Factors of Soil Moisture in the Yellow River Basin Using
           ESA CCI SM Products

    • Authors: Lei Guo, Bowen Zhu, Hua Jin, Yulu Zhang, Yaxin Min, Yuchen He, Haoyu Shi
      First page: 962
      Abstract: Soil moisture (SM) plays an important role in regulating terrestrial–atmospheric water circulation and energy balance. Most of the existing studies have explored the dynamic patterns of SM based on experimental methods. However, the analysis of large-scale regions and long-term SM sequences was limited. Alternatively, satellite remote sensing data is a potential source for SM analysis for large-scale basins. Therefore, the SM data from the European Space Agency (ESA) Climate Change Initiative (CCI) from 2000 to 2015 is used in this paper to analyze the SM spatial-temporal changes in the Yellow River Basin (YRB). Further, the Normalized Difference Vegetation Index (NDVI) and meteorological data are used to explore the relationships between SM and NDVI, precipitation, air temperature, and wind speed, respectively. The results showed that the overall trend of SM in the YRB was decreasing from southeast to northwest during the past 16 years. The upper reaches of the YRB had shown a humid trend, with a value of 0.00047 m3·m−3·year−1, mainly due to the increase in precipitation; there was an obvious drought trend in the middle reaches of the YRB, especially in Shanxi Province and Henan Province, with a value of −0.00030 m3·m−3·year−1, which may be owed to vegetation greening increasing the soil evaporation. Overall, it is determined that the main factors influencing SM changes were NDVI and precipitation, followed by air temperature and wind speed. This study can provide a scientific basis for the spatial-temporal distribution characteristics and attributions of SM in the YRB over a long time series.
      Citation: Atmosphere
      PubDate: 2022-06-14
      DOI: 10.3390/atmos13060962
      Issue No: Vol. 13, No. 6 (2022)
       
  • Atmosphere, Vol. 13, Pages 963: The Impacts of Urban Form on PM2.5
           Concentrations: A Regional Analysis of Cities in China from 2000 to 2015

    • Authors: Zefa Wang, Jing Chen, Chunshan Zhou, Shaojian Wang, Ming Li
      First page: 963
      Abstract: The urban form (e.g., city size, shape, scale, density, etc.) can impact the air quality and public health. However, few studies have been conducted to assess the relationship between the urban form and PM2.5 concentrations on a regional scale and long-term basis in China. In this study, we explored the impact of the urban form on the PM2.5 concentrations in four different regions (i.e., northeast, central, east, western) across China for the years 2000, 2005, 2010, and 2015. Five landscape metrics were classified into three characteristics of the urban form (compactness, shape complexity, and urban expansion) using high-resolution remote-sensing data. With considerations given to regional differences, panel-data models and city-level panel data were used to calculate the impact of the urban form on the PM2.5 concentrations. The results of the study indicate that urban expansion is positively correlated with the PM2.5 concentrations across China, with the only exception being the country’s western region, which suggests that urban extension is conducive to increasing the PM2.5 levels in relatively developed regions. Meanwhile, the positive relationship between the irregularity of cities and the PM2.5 concentrations indicates that reducing the urban shape complexity will help to mitigate PM2.5 pollution. Moreover, urban compactness, which mainly refers to the landscape-division-index values, proved to have a negative effect on the PM2.5 concentrations, suggesting that the optimization of urban spatial compactness could reduce PM2.5 levels. The findings of this study are beneficial for a better understanding of the intensity and direction of the effect of the urban form on PM2.5 concentrations.
      Citation: Atmosphere
      PubDate: 2022-06-14
      DOI: 10.3390/atmos13060963
      Issue No: Vol. 13, No. 6 (2022)
       
  • Atmosphere, Vol. 13, Pages 964: Transmission Risk Prediction and
           Evaluation of Mountain-Type Zoonotic Visceral Leishmaniasis in China Based
           on Climatic and Environmental Variables

    • Authors: Yuwan Hao, Zhuowei Luo, Jian Zhao, Yanfeng Gong, Yuanyuan Li, Zelin Zhu, Tian Tian, Qiang Wang, Yi Zhang, Zhengbin Zhou, Zengyun Hu, Shizhu Li
      First page: 964
      Abstract: With global warming and socioeconomic developments, there is a tendency toward the emergence and spread of mountain-type zoonotic visceral leishmaniasis (MT-ZVL) in China. Timely identification of the transmission risk and spread of MT-ZVL is, therefore, of great significance for effectively interrupting the spread of MT-ZVL and eliminating the disease. In this study, 26 environmental variables—namely, climatic, geographical, and 2 socioeconomic indicators were collected from regions where MT-ZVL patients were detected during the period from 2019 to 2021, to create 10 ecological niche models. The performance of these ecological niche models was evaluated using the area under the receiver-operating characteristic curve (AUC) and true skill statistic (TSS), and ensemble models were created to predict the transmission risk of MT-ZVL in China. All ten ecological niche models were effective at predicting the transmission risk of MT-ZVL in China, and there were significant differences in the mean AUC (H = 33.311, p < 0.05) and TSS values among these ten models (H = 26.344, p < 0.05). The random forest, maximum entropy, generalized boosted, and multivariate adaptive regression splines showed high performance at predicting the transmission risk of MT-ZVL (AUC > 0.95, TSS > 0.85). Ensemble models predicted a transmission risk of MT-ZVL in the provinces of Shanxi, Shaanxi, Henan, Gansu, Sichuan, and Hebei, which was centered in Shanxi Province and presented high spatial clustering characteristics. Multiple ensemble ecological niche models created based on climatic and environmental variables are effective at predicting the transmission risk of MT-ZVL in China. This risk is centered in Shanxi Province and tends towards gradual radiation dispersion to surrounding regions. Our results provide insights into MT-ZVL surveillance in regions at high risk of MT-ZVL.
      Citation: Atmosphere
      PubDate: 2022-06-14
      DOI: 10.3390/atmos13060964
      Issue No: Vol. 13, No. 6 (2022)
       
  • Atmosphere, Vol. 13, Pages 965: Tropopause Characteristics Based on
           Long-Term ARM Radiosonde Data: A Fine-Scale Comparison at the
           Extratropical SGP Site and Arctic NSA Site

    • Authors: Zhang
      First page: 965
      Abstract: The variations in the characteristics of the tropopause are sensitive indicators for the climate system and climate change. By using Atmospheric Radiation Measurement (ARM) radiosonde data that were recorded at the extratropical Southern Great Plains (SGP) and Arctic North Slope of Alaska (NSA) sites over an 18-year period (January 2003 to December 2020), this study performs a fine-scale comparison of the climatological tropopause features between these two sites that are characterized by different climates. The static stability increases rapidly above the tropopause at both sites, indicating the widespread existence of a tropopause inversion layer. The structures of both the tropopause inversion layer and the stability transition layer are more obvious at NSA than at SGP, and the seasonal variation trends of the tropopause inversion layer and stability transition layer are distinctly different between the two sites. A fitting method was used to derive the fitted tropopause height and tropopause sharpness (λ). Although this fitting method may determine a secondary tropopause rather than the primary tropopause when multiple tropopause heights are identified on one radiosonde profile, the fitted tropopause heights generally agree well with the observed tropopause heights. Broad tropopause sharpness values (λ > 2 km) occur more frequently at SGP than at NSA, resulting in a greater average tropopause sharpness at SGP (1.0 km) than at NSA (0.6 km). Significant positive trends are exhibited by the tropopause heights over the two sites, with rates of increase of 23.7 ± 6.5 m yr−1 at SGP and 28.0 ± 4.0 m yr−1 at NSA during the study period.
      Citation: Atmosphere
      PubDate: 2022-06-14
      DOI: 10.3390/atmos13060965
      Issue No: Vol. 13, No. 6 (2022)
       
  • Atmosphere, Vol. 13, Pages 966: Impact of Collaborative Agglomeration of
           Manufacturing and Producer Services on Air Quality: Evidence from the
           Emission Reduction of PM2.5, NOx and SO2 in China

    • Authors: Penghao Ye, Jin Li, Wenjing Ma, Huarong Zhang
      First page: 966
      Abstract: Industrial agglomeration is a major source of regional economic development and the main pattern enterprises employ after having developed to a certain stage. Industrial agglomeration also affects the emissions of air pollutants in production. Based on provincial panel data for China from 2006 to 2019, this paper introduces the full generalized least squares (FGLS) panel econometrics model. By considering spatial correlation, the potential endogenous problem has been controlled using the instrumental variable and the effects of the co-agglomeration of manufacturing and producer services on three major air pollutants, i.e., SO2, PM2.5, and NOx, have been empirically estimated. The empirical results show that: (1) The agglomeration of manufacturing increases the emission of PM2.5 in the air, while the agglomeration of producer services and the co-agglomeration of manufacturing and producer services reduce it. Moran correlation index test showed that SO2 and NOx had no significant spatial correlation. (2) The agglomeration of manufacturing, the agglomeration of producer services, and co-agglomeration exert the most significant effects on PM2.5 in the air in central and western China. This is probably because of the availability of basic natural resources in these areas. (3) The energy consumption structure mediates the effect of the agglomeration of manufacturing on PM2.5, and human capital mediates the effect of the agglomeration of producer services on PM2.5 emissions. Based on the results, policy suggestions to improve the atmospheric environment during the process of industrial agglomeration are proposed.
      Citation: Atmosphere
      PubDate: 2022-06-14
      DOI: 10.3390/atmos13060966
      Issue No: Vol. 13, No. 6 (2022)
       
  • Atmosphere, Vol. 13, Pages 967: An Evaluation of Risk Ratios on Physical
           and Mental Health Correlations due to Increases in Ambient Nitrogen Oxide
           (NOx) Concentrations

    • Authors: Stephanie Shaw, Bill Van Heyst
      First page: 967
      Abstract: Nitrogen oxides (NOx) are gaseous pollutants contributing to pollution in their primary form and are also involved in reactions forming ground-level ozone and fine particulate matter. Thus, NOx is of great interest for targeted pollution reduction because of this cascade effect. Primary emissions originate from fossil fuel combustion making NOx a common outdoor and indoor air pollutant. Numerous studies documenting the observed physical health impacts of NOx were reviewed and, where available, were summarized using risk ratios. More recently, the literature has shifted to focus on the mental health implications of NOx exposure, and a review of the current literature found five main categories of mental health-related conditions with respect to NOx exposure: common mental health disorders, sleep, anxiety, depression, and suicide. All the physical and mental health effects with available risk ratios were organized in order of increasing risk. Mental health concerns emerged as those most influenced by NOx exposure, with physical health impacts, such as asthma, only beginning to surface as the fourth highest risk. Mental health conditions occupied seven of the top ten highest risk health ailments. The results summarized in this narrative review show that there are clear positive correlations between NOx and negative physical and mental health manifestations, thus strengthening the argument in support of the reduction in ambient NOx levels.
      Citation: Atmosphere
      PubDate: 2022-06-14
      DOI: 10.3390/atmos13060967
      Issue No: Vol. 13, No. 6 (2022)
       
  • Atmosphere, Vol. 13, Pages 968: Hygroscopic Ground-Based Generator Cloud
           Seeding Design; A Case Study from the 2020 Weather Modification in Larona
           Basin Indonesia

    • Authors: Findy Renggono, Mahally Kudsy, Krisna Adhitya, Purwadi Purwadi, Halda Aditya Belgaman, Saraswati Dewi, Rahmawati Syahdiza, Erwin Mulyana, Edvin Aldrian, Jon Arifian
      First page: 968
      Abstract: Cloud seeding activities have been carried out in the form of experiments and operation activities as part of water resource management in some parts of the world. Recently, a new method of cloud seeding using a ground-based generator (GBG) was introduced in Indonesia. This method is used to seed orographic clouds with the aid of a 50 m GBG tower located in a mountainous area. By taking advantage of the topography and local circulation, the GBG tower will introduce hygroscopic seeding materials into orographic clouds to accelerate the collision and coalescence process within the clouds, increasing the cloud’s rainfall amount. The hygroscopic ground-based cloud seeding was conducted over the Larona Basin in Sulawesi, Indonesia, from December 2019 to April 2020. There were five towers installed around Larona Basin, located over 500 m above sea level. The results show that there was an increase in monthly rainfall amount from the GBG operation period in January, February, and March compared to its long-term average of as much as 79%, 17%, and 46%, respectively. Meanwhile, despite an increase of 0.4% in Lake Towuti water level, it is still not concluded that the GBG cloud seeding operation was involved in the lake water level raise. Therefore, more studies need to be performed in the future to answer whether the cloud seeding affected the lake water level.
      Citation: Atmosphere
      PubDate: 2022-06-15
      DOI: 10.3390/atmos13060968
      Issue No: Vol. 13, No. 6 (2022)
       
  • Atmosphere, Vol. 13, Pages 969: Study on the Source Profile
           Characteristics of Carbon Plant

    • Authors: Sen Li, Danni Liang, Jianhui Wu
      First page: 969
      Abstract: In the background of carbon neutrality, carbon emissions are basked in the attention. As a significant source of carbon emissions, the emission characteristics of carbon plant should be known. Particulate matter in flue gas was collected in a carbon plant in Tongliao. The chemical components in PM10 and PM2.5 were analyzed, and source profile of carbon plant was established. The results showed that the mass fractions of EC, Ca, Ca2+, S, Al, Si and Fe were higher in particles than other components. The chemical marker of carbon plant was EC, and the trace carbonaceous components of carbon plant were EC1 and EC2, which were very different from other carbon emission sources. In the absence of other chemical composition information, eight carbonaceous components can be used to identify the sources of particle.
      Citation: Atmosphere
      PubDate: 2022-06-15
      DOI: 10.3390/atmos13060969
      Issue No: Vol. 13, No. 6 (2022)
       
  • Atmosphere, Vol. 13, Pages 970: Characterization of Imidazole Compounds in
           Aqueous Secondary Organic Aerosol Generated from Evaporation of Droplets
           Containing Pyruvaldehyde and Inorganic Ammonium

    • Authors: Xin Lin, Mingqiang Huang, Tingting Lu, Weixiong Zhao, Changjin Hu, Xuejun Gu, Weijun Zhang
      First page: 970
      Abstract: Imidazole compounds are important constituents of atmospheric brown carbon. The imidazole components of aqueous secondary organic aerosol (aqSOA) that are generated from the evaporation of droplets containing pyruvaldehyde and inorganic ammonium are on-line characterized by an aerosol laser time-of-flight mass spectrometer (ALTOFMS) and off-line detected by optical spectrometry in this study. The results demonstrated that the laser desorption/ionization mass spectra of aqSOA particles that were detected by ALTOFMS contained the characteristic mass peaks of imidazoles at m/z = 28 (CH2N+), m/z = 41 (C2H3N+) and m/z = 67 (C3H4N2+). Meanwhile, the extraction solution of the aqSOA particles that were measured by off-line techniques showed that the characteristic absorption peaks at 217 nm and 282 nm appeared in the UV-Vis spectrum, and the stretching vibration peaks of C-N bond and C=N bond emerged in the infrared spectrum. Based on these spectral information, 4-methyl-imidazole and 4-methyl-imidazole-2-carboxaldehyde are identified as the main products of the reaction between pyruvaldehyde and ammonium ions. The water evaporation accelerates the formation of imidazoles inside the droplets, possibly owing to the highly concentrated environment. Anions, such as F−-, CO32−, NO3−, SO42− and Cl− in the aqueous phase promote the reaction of pyruvaldehyde and ammonium ions to produce imidazole products, resulting in the averaged mass absorption coefficient (<MAC>) in the range of 200–600 nm of aqSOA increases, and the order of promotion is: F− > CO32− > SO42− ≈ NO3− ≈ Cl−. These results will help to analyze the constituents and optics of imidazoles and provide a useful basis for evaluating the formation process and radiative forcing of aqSOA particles.
      Citation: Atmosphere
      PubDate: 2022-06-15
      DOI: 10.3390/atmos13060970
      Issue No: Vol. 13, No. 6 (2022)
       
  • Atmosphere, Vol. 13, Pages 971: Genetic Algorithm-Optimized Extreme
           Learning Machine Model for Estimating Daily Reference Evapotranspiration
           in Southwest China

    • Authors: Quanshan Liu, Zongjun Wu, Ningbo Cui, Wenjiang Zhang, Yaosheng Wang, Xiaotao Hu, Daozhi Gong, Shunsheng Zheng
      First page: 971
      Abstract: Reference evapotranspiration (ET0) is an essential component in hydrological and ecological processes. The Penman–Monteith (PM) model of Food and Agriculture Organization of the United Nations (FAO) model requires a number of meteorological parameters; it is urgent to develop high-precision and computationally efficient ET0 models with fewer parameter inputs. This study proposed the genetic algorithm (GA) to optimize extreme learning machine (ELM), and evaluated the performances of ELM, GA-ELM, and empirical models for estimating daily ET0 in Southwest China. Daily meteorological data including maximum temperature (Tmax), minimum temperature (Tmin), wind speed (u2), relative humidity (RH), net radiation (Rn), and global solar radiation (Rs) during 1992–2016 from meteorological stations were used for model training and testing. The results from the FAO-56 Penman–Monteith formula were used as a control group. The results showed that GA-ELM models (with R2 ranging 0.71–0.99, RMSE ranging 0.036–0.77 mm·d−1) outperformed the standalone ELM models (with R2 ranging 0.716–0.99, RMSE ranging 0.08–0.77 mm·d−1) during training and testing, both of which were superior to empirical models (with R2 ranging 0.36–0.91, RMSE ranging 0.69–2.64 mm·d−1). ET0 prediction accuracy varies with different input combination models. The machine learning models using Tmax, Tmin, u2, RH, and Rn/Rs (GA-ELM5/GA-ELM4 and ELM5/ELM4) obtained the best ET0 estimates, with R2 ranging 0.98–0.99, RMSE ranging 0.03–0.21 mm·d−1, followed by models with Tmax, Tmin, and Rn/Rs (GA-ELM3/GA-ELM2 and ELM3/ELM2) as inputs. The machine learning models involved with Rn outperformed those with Rs when the quantity of input parameters was the same. Overall, GA-ELM5 (Tmax, Tmin, u2, RH and Rn as inputs) outperformed the other models during training and testing, and was thus recommended for daily ET0 estimation. With the estimation accuracy, computational costs, and availability of input parameters accounted, GA-ELM2 (Tmax, Tmin, and Rs as inputs) was determined to be the most effective model for estimating daily ET0 with limited meteorological data in Southwest China.
      Citation: Atmosphere
      PubDate: 2022-06-15
      DOI: 10.3390/atmos13060971
      Issue No: Vol. 13, No. 6 (2022)
       
  • Atmosphere, Vol. 13, Pages 972: Dynamics of Precipitation Anomalies in
           Tropical South America

    • Authors: Mario Córdova, Rolando Célleri, Aarnout van Delden
      First page: 972
      Abstract: In this study, precipitation in Tropical South America in the 1931–2016 period is investigated by means of Principal Component Analysis and composite analysis of circulation fields. The associated dynamics are analyzed using the 20th century ERA-20C reanalysis. It is found that the main climatic processes related to precipitation anomalies in Tropical South America are: (1) the intensity and position of the South Atlantic Convergence Zone (SACZ); (2) El Niño Southern Oscillation (ENSO); (3) the meridional position of the Intertropical Convergence Zone (ITCZ), which is found to be related to Atlantic Sea Surface Temperature (SST) anomalies; and (4) anomalies in the strength of the South American Monsoon System, especially the South American Low-Level Jet (SALLJ). Interestingly, all of the analyzed anomalies are related to processes that operate from the Atlantic Ocean, except for ENSO. Results from the present study are in agreement with the state of the art literature about precipitation anomalies in the region. However, the added strength of the longer dataset and the larger study area improves the knowledge and gives new insights into how climate variability and the resulting dynamics are related to precipitation in Tropical South America.
      Citation: Atmosphere
      PubDate: 2022-06-15
      DOI: 10.3390/atmos13060972
      Issue No: Vol. 13, No. 6 (2022)
       
  • Atmosphere, Vol. 13, Pages 973: Topographical and Thermal Forcing in
           Favorable Circulation Pattern to Early Spring Precipitation over the
           Southeastern Tibetan Plateau

    • Authors: Yaoxian Yang, Zeyong Hu, Maoshan Li, Haipeng Yu, Weiqiang Ma, Weiwei Fan
      First page: 973
      Abstract: During the boreal spring (March–May), the precipitation that occurs from March over the southeastern Tibetan Plateau (TP) can account for 20–40% of the total annual amount. The origin of this phenomenon has not been clearly understood from a climatological perspective. In this study, the role of topographical and thermal forcing on the precipitation over the southeastern TP in early spring (March) was investigated through sensitivity numerical simulations based on general circulation model. The simulated results show the favorable circulation and static stability to early spring precipitation over the southeastern TP when the model is simultaneously forced by realistic topography, zonal symmetric radiative equilibrium temperature, and diabatic heating over the TP and its surrounding areas. The quasi-stationary wave pattern over the Eurasian continent forced by realistic and TP topographical forcing leads to prolonged low pressure and intensified zonal winds over the southeastern TP due to quasi-steady wave activities. Thermal forcing experiments reveals that sensible heating over the southeastern TP not only strengthens the cyclonic circulation, ascending motion and statically unstable over the southeastern TP through thermal adaptation and the Sverdrup balance, but also triggers an anticyclone at upper tropospheric level extending from north of the Bay of Bengal to the eastern TP, which further favors precipitation over the southeastern TP. This work will provide useful background information for spring climate prediction over the TP.
      Citation: Atmosphere
      PubDate: 2022-06-15
      DOI: 10.3390/atmos13060973
      Issue No: Vol. 13, No. 6 (2022)
       
  • Atmosphere, Vol. 13, Pages 974: Black Sea Freezing and Relation to the
           Winter Conditions in 2006–2021

    • Authors: Mirna Matov, Elisaveta Peneva, Vasko Galabov
      First page: 974
      Abstract: Black Sea freezing in winter is observed regularly in its northern parts and near the Kerch Strait. The reason for this is the relatively shallow northwestern shelf part and the river inflow of the three major European rivers Danube, Dnieper, and Dniester, as well as Don through the Azov Sea, carrying a large amount of fresh water to this part of the Black Sea. The global warming that has been observed in recent decades has made these episodes less intense; nevertheless, they exist and impact people who live n the area. The aim of this study is to analyze the extent of sea-ice variability in the last 15 years, observed by satellite observations, and to describe the weather conditions favorable for freezing to occur. It is found that, in 2006, 2012 and 2017, sea ice extended unusually southward, which is related to the unusually cold winter and weather conditions in these years. The weather patterns associated with the periods of maximal sea ice in the Black Sea are discussed. In addition, we analyze how the winter conditions change in the period 1926–2021 by combining different data sources. The winter is classified as cold, moderate or mild through the Winter Severity Index following a previously published methodology. The findings in our paper could help to monitor and predict these events and to inform the interested end-users.
      Citation: Atmosphere
      PubDate: 2022-06-16
      DOI: 10.3390/atmos13060974
      Issue No: Vol. 13, No. 6 (2022)
       
  • Atmosphere, Vol. 13, Pages 975: Development of an Engine Power Binning
           Method for Characterizing PM2.5 and NOx Emissions for Off-Road
           Construction Equipment with DPF and SCR

    • Authors: Qi Yao, Seungju Yoon, Yi Tan, Liang Liu, Jorn Herner, George Scora, Robert Russell, Hanwei Zhu, Tom Durbin
      First page: 975
      Abstract: Aftertreatment technologies in Tier 4 off-road engines have resulted in significant emission reductions compared to older tier engines without aftertreatments. The appropriate characterization of Tier 4 engine emissions in consideration of aftertreatment operation is important for projecting emissions and developing mitigation strategies. The current method of aggregating emissions over an entire duty cycle and averaging them by engine load has a limitation in developing emission profiles over various duty cycles of Tier 4 engines, especially at low-load operations, where aftertreatment control for NOx may not be effective. In this study, an engine power binning method was developed to characterize emissions for Tier 4 construction equipment with aftertreatment systems, especially at low-power operating conditions. This binning method was applied to real-time emissions and activity data for four different types of Tier 4 construction equipment. Results show that low-power operations (<20% engine power) are responsible for 38–60% NOx and 11–51% of PM2.5 emissions depending on the equipment types. These results underscore the need for controlling NOx emissions during low-power operations. PM2.5 EFs for non-DPF backhoes were one to two orders of magnitude greater than all the other equipment due to the lack of a DPF, despite being certified to the same PM2.5 standard. This shows the benefits of DPFs on construction equipment and that they are substantial in reducing PM2.5 emissions. Estimated emission differences between using the binning and the averaging methods were 49–86% and 16–82% for NOx and PM2.5, respectively. These differences may change once the binning method is applied to larger emission datasets obtained from real-world vocational activities.
      Citation: Atmosphere
      PubDate: 2022-06-16
      DOI: 10.3390/atmos13060975
      Issue No: Vol. 13, No. 6 (2022)
       
  • Atmosphere, Vol. 13, Pages 976: Effects of Chemical Reactions on the
           Oxidative Potential of Humic Acid, a Model Compound of Atmospheric
           Humic-like Substances

    • Authors: Yohei Koike, Takayuki Kameda
      First page: 976
      Abstract: Atmospheric particulate matter (PM) contains various chemicals, some of which generate in vivo reactive oxygen species (ROS). Owing to their high reactivity and oxidation ability, ROS can cause various diseases. To understand how atmospheric PM affects human health, we must clarify the PM components having oxidative potential (OP) leading to ROS production. According to previous studies, OP is exhibited by humic-like substances (HULIS) in atmospheric PM. However, the OP-dependence of the chemical structures of HULIS has not been clarified. Therefore, in this study, humic acid (HA, a model HULIS material) was exposed to ozone and ultraviolet (UV) irradiation, and its OP and structures were evaluated before and after the reactions using dithiothreitol (DTT) assay and Fourier transform infrared (FT-IR), respectively. The OP of HA was more significantly increased by UV irradiation than by ozone exposure. FT-IR analysis showed an increased intensity of the C=O peak in the HA structure after UV irradiation, suggesting that the OP of HA was increased by a chemical change to a more quinone-like structure after irradiation.
      Citation: Atmosphere
      PubDate: 2022-06-16
      DOI: 10.3390/atmos13060976
      Issue No: Vol. 13, No. 6 (2022)
       
  • Atmosphere, Vol. 13, Pages 977: Evapotranspiration of an Abandoned
           Grassland in the Italian Alps: Influence of Local Topography, Intra- and
           Inter-Annual Variability and Environmental Drivers

    • Authors: Davide Gisolo, Ivan Bevilacqua, Justus Van Ramshorst, Alexander Knohl, Lukas Siebicke, Maurizio Previati, Davide Canone, Stefano Ferraris
      First page: 977
      Abstract: Evapotranspiration is a key variable of the hydrological cycle but poorly studied in Alpine ecosystems. The current study aimed to characterise the impact of topography and temporal variability on actual evapotranspiration (ETa) and its environmental drivers at an Alpine abandoned grassland encroached by shrubs on a steep slope. Eddy covariance, meteorological, hydrological and soil data were analysed over four growing seasons, of which two had wet and two dry conditions. The topography caused a systematic morning inflexion of ETa in all growing seasons, reflecting the valley wind system. Inter-annual differences of ETa exceeded 100 mm, and ETa means and cumulative values were significantly different between wet and dry growing seasons in the four years. Besides, ETa had a larger temporal variability in wet growing seasons. A bimodality of ETa was found in all years, caused by the onset of plant activity in the morning hours. Energy- and water-limited ETa periods were identified by comparing ETa to potential evapotranspiration (ETo). Periods of fifteen days revealed the main intra- and inter-annual differences of the environmental variables (air temperature, vapour pressure deficit—VPD, precipitation and ETa). The fixed effects of a linear mixed model based on ETa drivers explained 56% of ETa variance. The most important ETa drivers were net radiation and VPD, followed by wind speed. In growing seasons characterised by dry conditions, air temperature and the ground heat flux at the surface (either both or one of them) influenced ETa as well. The current study contributed to the understanding of topographical and temporal effects on evapotranspiration and other micrometeorological variables in an Alpine ecosystem still rarely studied.
      Citation: Atmosphere
      PubDate: 2022-06-16
      DOI: 10.3390/atmos13060977
      Issue No: Vol. 13, No. 6 (2022)
       
  • Atmosphere, Vol. 13, Pages 978: Phenological Response of Flood Plain
           Forest Ecosystem Species to Climate Change during 1961–2021

    • Authors: Lenka Bartošová, Petra Dížkova, Jana Bauerová, Lenka Hájková, Milan Fischer, Jan Balek, Monika Bláhová, Martin Možný, Pavel Zahradníček, Petr Štěpánek, Zdeněk Žalud, Miroslav Trnka
      First page: 978
      Abstract: The present study analyses 61 years of phenological observations (1961–2021) of five herb, five shrub, four tree, and one bird species representing the prevalent spring species of floodplain forest ecosystems in the Czech Republic, central Europe. The in situ observations were conducted at the Vranovice site (48°48′ N, 16°46′ E, 170 m above mean sea level) representing the Plaček’ forest National Reserve. The observed plants and bird species showed statistically significant (p < 0.05) shifts in phenological terms to an earlier date of the year, but the rate of the shift among the observed species differed. The most progressive shifts were detected for the herbs (14 days), followed by the shrubs (13 days), trees (9 days), and finally by the bird species (8 days). All the phenophases were significantly correlated with the daily maximum temperature (r = 0.72–0.91). The results also showed a decline in the correlation for species among the phenophases of the herbs and trees. The phenophases that were highly correlated in the past were less correlated and had higher variability in the last decades. We conclude that the phenological response of the ecosystem to warming in the spring resulted in higher variability and a lower correlation among the observed phenophases mainly caused by the most expressive phenological shifts of the early herbs.
      Citation: Atmosphere
      PubDate: 2022-06-17
      DOI: 10.3390/atmos13060978
      Issue No: Vol. 13, No. 6 (2022)
       
  • Atmosphere, Vol. 13, Pages 979: A Study of the Vertical Distribution and
           Sub-Peaks of Ozone below 12 km over Wuyishan Region Based on Ozone
           Sounding in Winter

    • Authors: Yulan Zheng, Huiying Deng, Huabiao You, Yiming Qiu, Tianfu Zhu, Xugeng Cheng, Hong Wang
      First page: 979
      Abstract: An understanding of the vertical distribution of ozone is critical to assessing the ozone variabilities both in the stratosphere and the troposphere. We collected the profiles of atmospheric ozone partial pressure and ozone volume mixing ratio (VMR) by a sounding system at the Wuyi Mountain National Meteorological Observation Station (Shaowu sounding station 58725) from November 2021 to February 2022. In this study, the vertical distribution and sub-peak phenomenon of tropospheric ozone below 12 km are investigated using mathematical statistics and synthetic analysis. The results show that the ozone partial pressure decreased from the ground to the tropopause, which is consistent with the temperature profile. However, 66.7% of cases first showed an increasing trend from the ground to about 3 km, while there were one or more temperature inversions in the corresponding temperature profiles and the atmosphere was stable and the relative humidity was high; then, in the stratosphere, the ozone partial pressure began to increase significantly, The ozone partial pressure reaches its maximum at an average height of 24.9 km, and the maximum value was 14 mPa. The ozone VMR in troposphere is the fluctuating increase from the ground to the tropopause, and 83.3% of the cases begin to rise rapidly at about 2–5 km away from the tropopause, and the ozone surge height is 2.9 km lower than the tropopause on average. Some of these tropopause ozone VMR have shown the characteristics of stratospheric ozone. The sub-peaks of tropospheric ozone below 12 km has four cases. All the sub-peaks occur between 6.7 km and 11.5 km vertically, and peak ozone VMR is 1.6–1.9 times larger than that of the average state at the same height. The maximum stratospheric ozone VMR is 8649 ppb on average, occurring at an average height of 31.3 km, and this average height of the maximum stratospheric ozone VMR is 6.4 km higher than that for the ozone partial pressure. The total ozone in the boundary layer (0–1.5 km) is 4.3 DU on average, accounting for 1.5% in total ozone column. The total ozone in the troposphere is 39.5 DU, accounting for 13.1% in total ozone column, and the total ozone in the stratosphere is 262.4 DU, accounting for 86.9% in total ozone column.
      Citation: Atmosphere
      PubDate: 2022-06-17
      DOI: 10.3390/atmos13060979
      Issue No: Vol. 13, No. 6 (2022)
       
  • Atmosphere, Vol. 13, Pages 980: Characteristics of Fine Particulate Matter
           (PM2.5)-Bound n-Alkanes and Polycyclic Aromatic Hydrocarbons (PAHs) in a
           Hong Kong Suburban Area

    • Authors: Yuan Gao, Zhenhao Ling, Zhuozhi Zhang, Shuncheng Lee
      First page: 980
      Abstract: PM2.5 samples were collected at Tung Chung (TC), Hong Kong, during four nonconsecutive months in 2011/2012 to determine the concentrations, seasonal variations, and potential sources of polycyclic aromatic hydrocarbons (PAHs) and n-alkanes (n-C15-n-C35). Samples were analyzed using the thermal desorption gas chromatography/mass spectrometry (TD-GC/MS) method. The concentrations of particulate PAHs ranged from 1.26–13.93 ng/m3 with a mean value of 2.57 ng/m3, dominated by 4-ring species. Phenanthrene (Phe) and fluoranthene (Flu) were the two most abundant species, accounting for 13% and 18%, respectively. The dominant sources of PAHs were coal and biomass burning. The inhalation cancer risk value in our study exceeded 1 × 10−6 but was below 1 × 10−4, implying that the inhalation cancer risk of PAHs at the TC site is acceptable. The average concertation of n-alkanes was 103.21 ng/m3 (ranging from 38.58 to 191.44 ng/m3), and C25 was the most abundant species. Both PAHs and n-alkanes showed higher concentrations in autumn and winter whilst these values were lowest in summer. The carbon preference index (CPI) and percent contribution of wax n-alkanes showed that biogenic sources were the major sources. The annual average contributions of higher plant wax to n-alkanes at TC were over 40%.
      Citation: Atmosphere
      PubDate: 2022-06-17
      DOI: 10.3390/atmos13060980
      Issue No: Vol. 13, No. 6 (2022)
       
  • Atmosphere, Vol. 13, Pages 981: Large-Scale Saharan Dust Episode in April
           2019: Study of Desert Aerosol Loads over Sofia, Bulgaria, Using Remote
           Sensing, In Situ, and Modeling Resources

    • Authors: Zahari Peshev, Atanaska Deleva, Liliya Vulkova, Tanja Dreischuh
      First page: 981
      Abstract: Emissions of immense amounts of desert dust into the atmosphere, spreading over vast geographical areas, are in direct feedback relation with ongoing global climate changes. An extreme large-scale Saharan dust episode occurred over Mediterranean and Europe in April 2019, driven by a dynamic blocking synoptic pattern (omega block) creating conditions for a powerful northeastward circulation of air masses rich in dust and moisture. Here, we study and characterize the effects of related dust intrusion over Sofia, Bulgaria, using lidar remote sensing combined with in situ measurements, satellite imagery, and modeling data. Optical and microphysical parameters of the desert aerosols were obtained and vertically profiled, namely, backscatter coefficients and backscatter-related Ångström exponents, as well as statistical distributions of the latter as qualitative analogs of the actual particle size distributions. Dynamical and topological features of the dust-dominated aerosol layers were determined. Height profiles of the aerosol/dust mass concentration were obtained by synergistic combining and calibrating lidar and in situ data. The comparison of the retrieved mass concentration profiles with the dust modeling ones shows a satisfactory compliance. The local meteorological conditions and the aerosol composition and structure of the troposphere above Sofia during the dust event were seriously affected by the desert air masses.
      Citation: Atmosphere
      PubDate: 2022-06-17
      DOI: 10.3390/atmos13060981
      Issue No: Vol. 13, No. 6 (2022)
       
  • Atmosphere, Vol. 13, Pages 982: Vertical Eddy Diffusivity in the Tropical
           Cyclone Boundary Layer during Landfall

    • Authors: Chen Chen
      First page: 982
      Abstract: This study investigated surface layer turbulence characteristics and parameters using 20 Hz eddy covariance data collected from five heights with winds up to 42.27 m s–1 when Super Typhoon Maria (2018) made landfall. The dependence of these parameters including eddy diffusivities for momentum (Km) and heat (Kt), vertical mixing length (Lm), and strain rate (S) on wind speed (un), height, and radii was examined. The results show that momentum fluxes (τ), turbulent kinetic energy (TKE), and Km had a parabolic dependence on un at all five heights outside three times the RMW, the maximum of Km and S increased from the surface to a maximum value at a height of 50 m, and then decreased with greater heights. However, Km and S were nearly constant with wind and height within two to three times the RMW from the TC center before landfall. Our results also found the τ , TKE, and Km were larger than over oceanic areas at any given wind, and Km was about one to two orders of magnitude bigger than Kt. The turbulence characteristic and parameters’ change with height and radii from the TC center should be accounted for in sub-grid scale physical processes of momentum fluxes in numerical TC models.
      Citation: Atmosphere
      PubDate: 2022-06-17
      DOI: 10.3390/atmos13060982
      Issue No: Vol. 13, No. 6 (2022)
       
  • Atmosphere, Vol. 13, Pages 983: Landfill Emissions of Methane Inferred
           from Unmanned Aerial Vehicle and Mobile Ground Measurements

    • Authors: Eduardo P. Olaguer, Shelley Jeltema, Thomas Gauthier, Dustin Jermalowicz, Arthur Ostaszewski, Stuart Batterman, Tian Xia, Julia Raneses, Michael Kovalchick, Scott Miller, Jorge Acevedo, Jonathan Lamb, Jeff Benya, April Wendling, Joyce Zhu
      First page: 983
      Abstract: Municipal solid waste landfills are significant sources of atmospheric methane, the second most important greenhouse gas after carbon dioxide. Large emissions of methane from landfills contribute not only to global climate change, but also to local ozone formation due to the enhancement of radical chain lengths in atmospheric reactions of volatile organic compounds and nitrogen oxides. Several advanced techniques were deployed to measure methane emissions from two landfills in the Southeast Michigan ozone nonattainment area during the Michigan–Ontario Ozone Source Experiment (MOOSE). These techniques included mobile infrared cavity ringdown spectrometry, drone-mounted meteorological sensors and tunable diode laser spectrometry, estimation of total landfill emissions of methane based on flux plane measurements, and Gaussian plume inverse modeling of distributed methane emissions in the presence of complex landfill terrain. The total methane emissions measured at the two landfills were of the order of 500 kg/h, with an uncertainty of around 50%. The results indicate that both landfill active faces and leaking gas collection systems are important sources of methane emissions.
      Citation: Atmosphere
      PubDate: 2022-06-18
      DOI: 10.3390/atmos13060983
      Issue No: Vol. 13, No. 6 (2022)
       
  • Atmosphere, Vol. 13, Pages 984: Ambient Size-Segregated Particulate Matter
           Characterization from a Port in Upstate New York

    • Authors: Omosehin D. Moyebi, Brian P. Frank, Shida Tang, Gil LaDuke, David O. Carpenter, Haider A. Khwaja
      First page: 984
      Abstract: Air pollution impacts human health and the environment, especially in urban cities with substantial industrial activities and vehicular traffic emissions. Despite increasingly strict regulations put in place by regulatory agencies, air pollution is still a significant environmental problem in cities across the world. The objective of this study was to evaluate the environmental pollution from stationary and mobile sources using real-time monitoring and sampling techniques to characterize size-segregated particulate matter (PM), black carbon (BC), and ozone (O3) at the Port of Albany, NY. Air pollution monitoring was carried out for 3 consecutive weeks under a 24-hour cycle in 2018 at the New York State Department of Environmental Conservation (NYSDEC) site within the Port. Sampling was done with an AEROCET 531, optical particle sizer (OPS), ozone monitor, and MicroAeth AE51. Higher mass and number concentrations of size-segregated particles were observed during the daytime. PM2.5 and PM10 concentrations ranged from 1 to 271 micrograms per cubic meter (µg/m3) and 1 to 344 µg/m3, respectively. While these values do not exceed the level of the USEPA 24-hour standards, frequent sharp peaks were observed at higher concentrations. Size-segregated PM at sizes 0.3 µm and 0.374 µm recorded maximum concentrations of 10,1631 particle number per cubic centimeter (#/cm3) and 43,432 #/cm3, respectively. Wide variations were observed in the particle number concentrations for 0.3 µm, 0.374 µm, and 0.465 µm sizes, which ranged from 1,521 to 10,1631 #/cm3; 656 to 43,432 #/cm3; and 311 to 29,271 #/cm3, respectively. BC concentration increased during morning and evening rush hours with the maximum concentration of 11,971 ng/m3 recorded at 8:00 AM. This suggests that mobile sources are the primary contributor to anthropogenic sources of BC within the Port. Episodic elevations in the concentrations of size-segregated PM and BC confirmed the contribution of industrial and vehicular activities around the Port of Albany. This study underscores the importance of measuring particles on a size-segregated basis in order to more fully understand the contributions of the multiple sources present within and surrounding a port environment.
      Citation: Atmosphere
      PubDate: 2022-06-18
      DOI: 10.3390/atmos13060984
      Issue No: Vol. 13, No. 6 (2022)
       
  • Atmosphere, Vol. 13, Pages 985: Evaluation of the Performance of the WRF
           Model in a Hyper-Arid Environment: A Sensitivity Study

    • Authors: Rachid Abida, Yacine Addad, Diana Francis, Marouane Temimi, Narendra Nelli, Ricardo Fonseca, Oleksandr Nesterov, Emmanuel Bosc
      First page: 985
      Abstract: Accurate simulation of boundary layer surface meteorological parameters is essential to achieve good forecasting of weather and atmospheric dispersion. This paper is devoted to a model sensitivity study over a coastal hyper-arid region in the western desert of the United Arab Emirates. This region hosts the Barakah Nuclear Power Plant (BNPP), making it vital to correctly simulate local weather conditions for emergency response in case of an accidental release. We conducted a series of high-resolution WRF model simulations using different combinations of physical schemes for the months January 2019 and June 2019. The simulated results were verified against in-situ meteorological surface measurements available offshore, nearshore, and inland at 12 stations. Several statistical metrics were calculated to rank the performance of the different simulations and a near-to-optimal set of physics options that enhance the performance of a WRF model over different locations in this region has been selected. Additionally, we found that the WRF model performed better in inland locations compared to offshore or nearshore locations, suggesting the important role of dynamical SSTs in mesoscale models. Moreover, morning periods were better simulated than evening ones. The impact of nudging towards station observations resulted in an overall reduction in model errors by 5–15%, which was more marked at offshore and nearshore locations. The sensitivity to grid cell resolution indicated that a spatial resolution of 1 km led to better performance compared to coarser spatial resolutions, highlighting the advantage of high-resolution simulations in which the mesoscale coastal circulation is better resolved.
      Citation: Atmosphere
      PubDate: 2022-06-18
      DOI: 10.3390/atmos13060985
      Issue No: Vol. 13, No. 6 (2022)
       
  • Atmosphere, Vol. 13, Pages 986: Spatiotemporal Variations in the Air
           Pollutant NO2 in Some Regions of Pakistan, India, China, and Korea, before
           and after COVID-19, Based on Ozone Monitoring Instrument Data

    • Authors: Wardah Naeem, Jaemin Kim, Yun Gon Lee
      First page: 986
      Abstract: In 2020, COVID-19 was proclaimed a pandemic by the World Health Organization, prompting several nations throughout the world to block their borders and impose a countrywide lockdown, halting all major manmade activities and thus leaving a beneficial impact on the natural environment. We investigated the influence of a sudden cessation of human activity on tropospheric NO2 concentrations to understand the resulting changes in emissions, particularly from the power-generating sector, before (2010–2019) and during the pandemic (2020). NO2 was chosen because of its short lifespan in the Earth’s atmosphere. Using daily tropospheric NO2 column concentrations from the Ozone Monitoring Instrument, the geographic and temporal characteristics of tropospheric NO2 column were investigated across 12 regions in India, Pakistan, China, and South Korea (2010–2020). We analyzed weekly, monthly, and annual trends and found that the NO2 concentrations were decreased in 2020 (COVID-19 period) in the locations investigated. Reduced anthropogenic activities, including changes in energy production and a reduction in fossil fuel consumption before and during the COVID-19 pandemic, as well as reduced traffic and industrial activity in 2020, can explain the lower tropospheric NO2 concentrations. The findings of this study provide a better understanding of the process of tropospheric NO2 emissions over four nations before and after the coronavirus pandemic for improving air quality modeling and management approaches.
      Citation: Atmosphere
      PubDate: 2022-06-18
      DOI: 10.3390/atmos13060986
      Issue No: Vol. 13, No. 6 (2022)
       
  • Atmosphere, Vol. 13, Pages 987: Data Assimilation of Doppler Wind Lidar
           for the Extreme Rainfall Event Prediction over Northern Taiwan: A Case
           Study

    • Authors: Chih-Ying Chen, Nan-Ching Yeh, Chuan-Yao Lin
      First page: 987
      Abstract: On 4 June 2021, short-duration extreme precipitation occurred in Taipei. Within 2 h, over 200 mm of rainfall accumulated in the Xinyi district. In this study, advanced data assimilation technology (e.g., hybrid data and 3D variations) was incorporated to develop a high-resolution, small-scale (e.g., northern Taiwan) data assimilation forecast system, namely the weather research and forecast-grid statistical interpolation (WRF-GSI) model. The 3D wind field data recorded by the Doppler wind lidar system of Taipei Songshan Airport were assimilated for effective simulation of the extreme precipitation. The results revealed that the extreme rainfall was caused by the interaction between the northeast wind incurred by a front to the north of Taiwan, a humid southerly wind generated by Typhoon Choi-wan, and the regional sea–land breeze circulation. For the Xinyi district, the WRF-GSI_lidar model reported accumulated rainfall 30 mm higher than that in the non-assimilated experiment (WRF-GSI_noDA), indicating that the WRF-GSI model with lidar observation was improved 15% more than the nonassimilated run.
      Citation: Atmosphere
      PubDate: 2022-06-18
      DOI: 10.3390/atmos13060987
      Issue No: Vol. 13, No. 6 (2022)
       
  • Atmosphere, Vol. 13, Pages 988: Precipitable Water Content Climatology
           over Poland

    • Authors: Hanna Ojrzyńska, Marek Błaś, Maciej Kryza
      First page: 988
      Abstract: In this work, the high-resolution spatial and temporal variability of precipitable water (PW) over Poland is presented. PW is one of the key parameters of the atmosphere taken into account in thermodynamic and radiation models. The daily PW values from years 2001–2010, calculated with the use of the WRF model, were compared with PW from soundings. The WRF modeled PW is in close agreement with measurements for the whole column of the troposphere and for individual levels: below 1.5 km, 1.5–3 km, 3–6 km and 6–10 km. The best agreement is observed in the lower part of the troposphere, especially for winter months. At the levels of 1.5 km to 10 km, the WRF model overestimates the PW values throughout the year, whereas up to 1.5 km PW is underestimated. The study shows an increasing trend of PW annual values between 1983 and 2010, but the trend is statistically insignificant. A significant positive trend with a high Sen’s slope is observed for the summer season up to 3 km in the troposphere, along with a significant negative tendency for spring. The trends in PW over Poland and Central Europe identified in this study contribute to the ongoing discussion on the observed climate changes.
      Citation: Atmosphere
      PubDate: 2022-06-19
      DOI: 10.3390/atmos13060988
      Issue No: Vol. 13, No. 6 (2022)
       
  • Atmosphere, Vol. 13, Pages 989: Multitask Learning Based on Improved
           Uncertainty Weighted Loss for Multi-Parameter Meteorological Data
           Prediction

    • Authors: Junkai Wang, Lianlei Lin, Zaiming Teng, Yu Zhang
      First page: 989
      Abstract: With the exponential growth in the amount of available data, traditional meteorological data processing algorithms have become overwhelmed. The application of artificial intelligence in simultaneous prediction of multi-parameter meteorological data has attracted much attention. However, existing single-task network models are generally limited by the data correlation dependence problem. In this paper, we use a priori knowledge for network design and propose a multitask model based on an asymmetric sharing mechanism, which effectively solves the correlation dependence problem in multi-parameter meteorological data prediction and achieves simultaneous prediction of multiple meteorological parameters with complex correlations for the first time. The performance of the multitask model depends largely on the relative weights among the task losses, and manually adjusting these weights is a difficult and expensive process, which makes it difficult for multitask learning to achieve the expected results in practice. In this paper, we propose an improved multitask loss processing method based on the assumptions of homoscedasticity uncertainty and the Laplace loss distribution and validate it using the German Jena dataset. The results show that the method can automatically balance the losses of each subtask and has better performance and robustness.
      Citation: Atmosphere
      PubDate: 2022-06-20
      DOI: 10.3390/atmos13060989
      Issue No: Vol. 13, No. 6 (2022)
       
  • Atmosphere, Vol. 13, Pages 990: Spatiotemporal Variation in Air Pollution
           Characteristics and Influencing Factors in Ulaanbaatar from 2016 to 2019

    • Authors: Suriya, Narantsogt Natsagdorj, Aorigele, Haijun Zhou, Sachurila
      First page: 990
      Abstract: Ambient air pollution is a global environmental issue that affects human health. Ulaanbaatar (UB), the capital of Mongolia, is one of the most polluted cities in the world, and it is of great importance to study the temporal and spatial changes in air pollution in this city, along with their influencing factors. To understand the characteristics of atmospheric pollutants in UB, the contents of PM10, PM2.5, SO2, NO2, CO, and O3, as well as their influencing factors, were analyzed from data obtained from automatic air quality monitoring stations. These analyses yielded six major findings: (1) From 2016 to 2019, there was a total of 883 pollution days, and PM2.5 and PM10 were the primary pollutants on 553 and 351 of these days, respectively. The air pollution was dominated by PM10 in spring and summer, affected by both PM2.5 and PM10 in autumn, and dominated by PM2.5 in winter. (2) Compared with 2016, the number of days with good air quality in UB in 2019 increased by 45%, and the number of days with unhealthy or worse levels of pollution decreased by 56%, indicating that the air quality improved year by year. (3) From 2016 to 2019, the annual average PM2.5/PM10 ratio dropped from 0.55 to 0.45, and the proportion of PM2.5 in particulate matter decreased year by year. The PM concentration and PM2.5/PM10 ratio were highest in winter and lowest in summer. When comparing the four-season averages, the average PM2.5 concentration decreased by 89% from its highest level, and the PM10 concentration decreased by 67%, indicating stronger seasonal differences in PM2.5 than in PM10. (4) The hourly changes in PM concentration showed a bimodal pattern, exhibiting a decrease during the day and a slight increase in the afternoon due to temperature inversion, so the PM2.5/PM10 ratio increased at night in all four seasons. The PM concentration during the heating season was significantly higher than that in the non-heating season, indicating that coal-fired heating was the main cause of air pollution in UB. (5) Sand dust and soot were the two main types of pollution in UB. (6) Correlation analysis and linear fitting analysis showed that PM2.5 and PM10 caused by coal-firing had an important impact on air quality in UB. Coal combustion and vehicle emissions with SO2, NO2, and CO as factors made large contributions to PM2.5.
      Citation: Atmosphere
      PubDate: 2022-06-20
      DOI: 10.3390/atmos13060990
      Issue No: Vol. 13, No. 6 (2022)
       
  • Atmosphere, Vol. 13, Pages 991: Characterizing Atmospheric Brown Carbon
           and Its Emission Sources during Wintertime in Shanghai, China

    • Authors: Linyuan Zhang, Jung Hyun Son, Zhe Bai, Wei Zhang, Ling Li, Lina Wang, Jianmin Chen
      First page: 991
      Abstract: Atmospheric brown carbon (BrC) is a kind of organic aerosol that efficiently absorbs ultraviolet-visible light and has an impact on climate forcing. We conducted an in-depth field study on ambient aerosols at a monitoring point in Shanghai, China, aiming to investigate the potential emission sources, molecular structures, and the contributions to light absorptions of ambient BrC chromophores. The results indicated that nine molecules were identified as nitroaromatic compounds, five of which (4-nitrophenol, 4-nitrocatechol, 2-nitro-1-naphthol, 3-methyl-4-nitrocatechol, and 2-methyl-4-nitrophenol) usually came from biomass burning or were produced from the photo-oxidation of anthropogenic volatile organic compounds (e.g., toluene, benzene) under high-NOx conditions. 4-nitrophenol was the strongest BrC chromophore and accounted for 13% of the total aerosol light absorption at λ = 365 nm. The estimated light absorption of black carbon was approximately three times the value of methanol-soluble BrC at λ = 365 nm. The ratios of K+/OC and K+/EC, and the correlations with WSOC, OC, HULIS-C and K+, and MAE values of methanol extracts also indicated that the primary emissions from biomass burning contributed more aerosol light absorption compared to the secondary formation during the wintertime in Shanghai. Therefore, biomass burning control is still the most urgent strategy for reducing BrC in Shanghai.
      Citation: Atmosphere
      PubDate: 2022-06-20
      DOI: 10.3390/atmos13060991
      Issue No: Vol. 13, No. 6 (2022)
       
  • Atmosphere, Vol. 13, Pages 992: Variations in Aerosol Optical Properties
           over East Asian Dust Storm Source Regions and Their Climatic Factors
           during 2000–2021

    • Authors: Saichun Tan, Bin Chen, Hong Wang, Huizheng Che, Huaying Yu, Guangyu Shi
      First page: 992
      Abstract: The East Asian dust storms occur in western and northern China, and southern Mongolia every year, particularly in spring. In this study, we use satellite aerosol products to demonstrate the spatial and temporal variation in aerosol optical depth (AOD) from MODIS, and the absorbing aerosol index (AAI) from TOMS and OMI, over the main dust storm source regions (MDSR), and to investigate their relationship to vegetation coverage (NDVI), soil properties (surface soil moisture content and soil temperature 0–10 cm underground), and climatic factors (surface wind speed, air temperature at 2 m above the ground, and precipitation) in spring for the period of 2000–2021. Compared with dust storm occurrence frequency (DSF) observed at surface stations, MODIS AOD, TOMS AAI, and OMI AAI showed consistent spatial distributions and seasonal variations with DSF in the MDSR, with correlation coefficients of 0.88, 0.55, and 0.88, respectively. The results showed that AOD and AAI over the MDSR decreased during 2000–2005, 2006–2017, and 2000–2021, but increased during 2017–2021.The improvements in vegetation coverage and soil moisture together with favorable climatic factors (the increase in temperature and precipitation and the decrease in surface wind speed) resulted in the decreasing trend of AOD and AAI during 2000–2005, 2006–2017, and the entire period of 2000–2021. Conversely, the increase in surface wind speed, the decrease in temperature and the low soil moisture in 2018 and 2020 were the reasons for the increases in AOD and AAI over the MDSR during 2017–2021. The combination effects of surface wind, temperature, soil moisture, and vegetation coverage would determine DSF, AOD, and AAI, in the end, under global climate change.
      Citation: Atmosphere
      PubDate: 2022-06-20
      DOI: 10.3390/atmos13060992
      Issue No: Vol. 13, No. 6 (2022)
       
  • Atmosphere, Vol. 13, Pages 993: Analytical Four-Dimensional Ensemble
           Variational Data Assimilation for Joint State and Parameter Estimation

    • Authors: Kangzhuang Liang, Wei Li, Guijun Han, Yantian Gong, Siyuan Liu
      First page: 993
      Abstract: The joint state and parameter estimation problem is an important issue in data assimilation. An adjoint free data assimilation method, namely analytical four-dimensional ensemble variational (A-4DEnVar) data assimilation method, was developed to provide a solution for the joint estimation problem. In the algorithm, to estimate the adjoint model reasonably, the ensemble initial conditions and parameters are generated by Gaussian noise whose covariance is constructed by multiplying a very small factor by their background error covariance. The ensemble perturbations are calculated with respect to background states rather than the ensemble mean. Next, the usage of temporal cross covariances makes it possible to avoid the adjoint model and estimate the gradient in 4DVar. Furthermore, we update the solution iteratively with a linear search process to improve the stability and ensure the convergence of the algorithm. The method is tested using the three-variable Lorenz model (Lorenz-1963) to illustrate its efficiency. It is shown that A-4DEnVar results in similar performance with 4DVar. Sensitivity experiments show that A-4DEnVar is able to assimilate observations successfully with different settings. The proposed method is able to work as well as 4DVar and avoid adjoint models for the joint state and parameter estimation.
      Citation: Atmosphere
      PubDate: 2022-06-20
      DOI: 10.3390/atmos13060993
      Issue No: Vol. 13, No. 6 (2022)
       
  • Atmosphere, Vol. 13, Pages 994: Long-Term Variations of Meteorological and
           Precursor Influences on Ground Ozone Concentrations in Jinan, North China
           Plain, from 2010 to 2020

    • Authors: Jing Sun, Shixin Duan, Baolin Wang, Lei Sun, Chuanyong Zhu, Guolan Fan, Xiaoyan Sun, Zhiyong Xia, Bo Lv, Jiaying Yang, Chen Wang
      First page: 994
      Abstract: Ground-level ozone (O3) pollution in the North China Plain has become a serious environmental problem over the last few decades. The influence of anthropogenic emissions and meteorological conditions on ozone trends have become the focus of widespread research. We studied the long-term ozone trends at urban and suburban sites in a typical city in North China and quantified the contributions of anthropogenic and meteorological factors. The results show that urban O3 increased and suburban O3 decreased from 2010 to 2020. The annual 90th percentile of the maximum daily 8-h average of ozone in urban areas increased by 3.01 μgm−3year−1 and, in suburban areas, it decreased by 3.74 μgm−3year−1. In contrast to the meteorological contributions, anthropogenic impacts are the decisive reason for the different ozone trends in urban and suburban areas. The rapid decline in nitrogen oxides (NOX) in urban and suburban areas has had various effects. In urban areas, this leads to a weaker titration of NOX and enhanced O3 formation, while in suburban areas, this weakens the photochemical production of O3. Sensitivity analysis shows that the O3 formation regime is in a transition state in both the urban and suburban areas. However, this tends to be limited to volatile organic compounds (VOCs) in urban areas and to NOX in suburban areas. One reasonable approach to controlling ozone pollution should be to reduce nitrogen oxide emissions while strengthening the control of VOCs.
      Citation: Atmosphere
      PubDate: 2022-06-20
      DOI: 10.3390/atmos13060994
      Issue No: Vol. 13, No. 6 (2022)
       
  • Atmosphere, Vol. 13, Pages 995: Impacts of Different Land Use Scenarios on
           Future Global and Regional Climate Extremes

    • Authors: Tao Hong, Junjie Wu, Xianbiao Kang, Min Yuan, Lian Duan
      First page: 995
      Abstract: Land use and land cover change (LULCC) alters the character of the land surface and directly impacts the climate. The impacts of LULCC on historical and future climate have been largely investigated, mostly using simulations with or without land use change. However, it is still not clear to what extent the projections of future climate change depend on the choice of land use scenario, which can provide important guidance on using land use and land management as a tool for regional climate mitigation. Here, using ten Earth system models participating in future land use policy sensitivity experiments in Land Use Model Intercomparison Project (LUMIP), we assessed the impact of two different land use scenarios (SSP1-2.6 and SSP3-7.0) on extreme climate. The results demonstrate that the use of different land use change scenarios has a substantial effect on the projections of regional climate extreme changes. Our study also reveals that, compared with other anthropogenic forcings, land use change has a considerable contribution to regional temperature extreme changes, with the contribution ranging from −14.0% to 10.3%, and the contribution to regional precipitation extreme change is larger, with a range of −118.4~138.8%. The global climate effects of land use change are smaller in magnitude than regional effects, with a small (5%) contribution to temperature extreme change. We also found a large spread in the model’s responses to LULCC, especially for precipitation extremes, suggesting that observation-based studies on reducing models’ uncertainties are needed to obtain more robust future projections of regional climate change. Our study highlights the essential role of land use and land management strategies in future regional climate mitigation.
      Citation: Atmosphere
      PubDate: 2022-06-20
      DOI: 10.3390/atmos13060995
      Issue No: Vol. 13, No. 6 (2022)
       
 
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